paperID stringlengths 36 36 | pwc_id stringlengths 8 47 | arxiv_id stringlengths 6 16 ⌀ | nips_id float64 | url_abs stringlengths 18 329 | url_pdf stringlengths 18 742 | title stringlengths 8 325 | abstract stringlengths 1 7.27k ⌀ | authors stringlengths 2 7.06k | published stringlengths 10 10 ⌀ | conference stringlengths 12 47 ⌀ | conference_url_abs stringlengths 16 198 ⌀ | conference_url_pdf stringlengths 27 199 ⌀ | proceeding stringlengths 6 47 ⌀ | taskID stringlengths 7 1.44k | areaID stringclasses 688 values | embedding stringlengths 9.26k 12.5k | umap_embedding stringlengths 29 44 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ea65497c-cfbb-43ea-9748-27784926127d | temporal-knowledge-graph-completion-with | null | null | https://aclanthology.org/2022.coling-1.416 | https://aclanthology.org/2022.coling-1.416.pdf | Temporal Knowledge Graph Completion with Approximated Gaussian Process Embedding | Knowledge Graphs (KGs) stores world knowledge that benefits various reasoning-based applications. Due to their incompleteness, a fundamental task for KGs, which is known as Knowledge Graph Completion (KGC), is to perform link prediction and infer new facts based on the known facts. Recently, link prediction on the temporal KGs becomes an active research topic. Numerous Temporal Knowledge Graph Completion (TKGC) methods have been proposed by mapping the entities and relations in TKG to the high-dimensional representations. However, most existing TKGC methods are mainly based on deterministic vector embeddings, which are not flexible and expressive enough. In this paper, we propose a novel TKGC method, TKGC-AGP, by mapping the entities and relations in TKG to the approximations of multivariate Gaussian processes (MGPs). Equipped with the flexibility and capacity of MGP, the global trends as well as the local fluctuations in the TKGs can be simultaneously modeled. Moreover, the temporal uncertainties can be also captured with the kernel function and the covariance matrix of MGP. Moreover, a first-order Markov assumption-based training algorithm is proposed to effective optimize the proposed method. Experimental results show the effectiveness of the proposed approach on two real-world benchmark datasets compared with some state-of-the-art TKGC methods. | ['Deyu Zhou', 'Linhai Zhang'] | null | null | null | null | coling-2022-10 | ['temporal-knowledge-graph-completion'] | ['knowledge-base'] | [-5.70549607e-01 9.95051935e-02 -5.34037128e-02 4.91613485e-02
-1.33640870e-01 -2.02071592e-01 6.94914520e-01 2.70157218e-01
8.72052014e-02 9.78569269e-01 5.71316741e-02 -7.28824511e-02
-7.50083625e-01 -1.12402320e+00 -6.43259406e-01 -8.15061510e-01
-1.47351101e-01 6.48525476e-01 3.59321326e-01 -6.06843494e-02
-1.72618985e-01 2.37770945e-01 -1.20596099e+00 -3.92014951e-01
1.22210860e+00 1.06140804e+00 2.03746974e-01 1.53529599e-01
-4.22510058e-01 7.10033715e-01 -1.52049586e-01 -6.36913717e-01
-9.22263861e-02 1.85956329e-01 -3.69387746e-01 -4.85462956e-02
-4.73922879e-01 9.25691873e-02 -8.72268736e-01 1.13597238e+00
1.38957560e-01 5.13657987e-01 6.62829697e-01 -1.33464825e+00
-8.07718039e-01 5.01624227e-01 -4.01676327e-01 1.31144583e-01
2.93524433e-02 -8.07343051e-02 7.40547359e-01 -7.58923829e-01
5.74971318e-01 1.39954162e+00 4.95084941e-01 2.03536591e-03
-9.28982139e-01 -4.67556596e-01 4.69539434e-01 8.11181188e-01
-1.67499566e+00 -5.79967350e-03 8.64422143e-01 -5.74894607e-01
5.77343047e-01 -9.00805220e-02 7.34200895e-01 7.43473053e-01
3.21411014e-01 7.35448420e-01 9.75731850e-01 -3.16140428e-02
3.87528211e-01 1.78196177e-01 8.36561546e-02 6.01348877e-01
5.50875783e-01 -1.25850156e-01 -5.34938276e-01 -6.80794194e-02
5.35001755e-01 2.36606404e-01 -4.78606611e-01 -4.61529374e-01
-1.14351141e+00 5.88078201e-01 2.02704787e-01 3.75986546e-02
-6.84630454e-01 3.41554843e-02 2.69290537e-01 -2.02530190e-01
6.20803773e-01 -2.02311993e-01 -4.81321603e-01 -1.21537089e-01
-5.47282338e-01 1.02739848e-01 8.11170459e-01 1.17741954e+00
8.29546094e-01 1.82937399e-01 -2.37022400e-01 3.92095000e-01
6.26149058e-01 7.05441117e-01 2.76110113e-01 -3.10011894e-01
8.28728676e-01 7.29576886e-01 5.07447422e-01 -1.51666033e+00
-3.61573935e-01 -6.38096571e-01 -9.40466166e-01 -4.85012978e-01
6.26817718e-03 -2.73550242e-01 -6.06156588e-01 1.40435863e+00
6.63224697e-01 9.77724493e-01 3.72649461e-01 5.14387488e-01
5.79223633e-01 1.12377489e+00 2.49277428e-02 -4.50344592e-01
1.09027112e+00 -5.10241151e-01 -1.11149979e+00 1.38914689e-01
3.07197243e-01 -4.45063353e-01 5.91255665e-01 2.51936644e-01
-4.94159400e-01 -3.74301553e-01 -9.61833775e-01 3.58886302e-01
-5.31262219e-01 2.06261322e-01 7.34657645e-01 3.73791099e-01
-5.20337701e-01 5.55490971e-01 -1.07295966e+00 -1.73719496e-01
2.28521809e-01 -2.92796455e-02 -1.78193301e-01 -3.60212773e-01
-1.57265854e+00 8.94267797e-01 1.14572680e+00 6.55490398e-01
-7.12280631e-01 -7.21947908e-01 -6.35549247e-01 2.12056056e-01
9.14902508e-01 -5.32651246e-01 6.20090008e-01 8.14065188e-02
-1.41601717e+00 -6.97080046e-02 2.94832736e-02 -3.51299524e-01
4.02122319e-01 -2.09692493e-01 -1.08180976e+00 7.20453933e-02
-8.85105357e-02 -3.89192462e-01 8.53275537e-01 -1.26921058e+00
-6.46996737e-01 -4.54755217e-01 -1.97156250e-01 2.63800383e-01
-2.89216250e-01 -6.22107208e-01 -7.73064673e-01 -5.03744543e-01
2.37847835e-01 -8.01255465e-01 1.48139091e-03 -5.67703068e-01
-5.89248121e-01 -2.81100005e-01 8.98984849e-01 -1.09595585e+00
1.37422228e+00 -1.99525559e+00 3.58693331e-01 4.37396079e-01
1.29921541e-01 3.95348877e-01 3.56910855e-01 8.21735382e-01
2.89607316e-01 -8.90739262e-02 -3.54296193e-02 -1.92291632e-01
2.21442312e-01 4.52504069e-01 -4.55745310e-01 3.71774077e-01
-1.41823098e-01 8.37356031e-01 -1.07380211e+00 -5.36809385e-01
3.55971873e-01 3.94080102e-01 6.72747791e-02 -3.54198739e-02
-5.53488195e-01 3.77356321e-01 -8.97704482e-01 6.83156133e-01
8.79433870e-01 -1.33100688e-01 2.88746297e-01 -5.08614957e-01
7.49924127e-03 -4.63749439e-01 -1.55032027e+00 1.52772081e+00
-3.96151245e-01 5.88383935e-02 -2.46569023e-01 -1.08385527e+00
1.05909514e+00 3.89968365e-01 3.17104131e-01 -2.08792582e-01
-7.55273178e-02 1.98295936e-01 -3.68109375e-01 -5.08803189e-01
4.90346074e-01 -9.36255679e-02 1.80952236e-01 -1.11838199e-01
2.24807844e-01 1.10098533e-02 1.82190120e-01 3.28291029e-01
7.41343141e-01 3.81336957e-01 1.13143548e-01 -1.33740291e-01
7.00586498e-01 -1.68221012e-01 1.02976716e+00 2.03692541e-01
8.05786476e-02 -1.41408324e-01 4.76136595e-01 -1.76763281e-01
-4.97324347e-01 -1.15818655e+00 1.81471765e-01 2.81423070e-02
3.78891230e-01 -4.97098178e-01 -2.29222894e-01 -5.33717275e-01
3.43918592e-01 9.73268807e-01 -5.36306262e-01 -2.66690135e-01
2.13296674e-02 -8.44481170e-01 1.88804373e-01 4.21925068e-01
6.54923677e-01 -4.96529162e-01 1.77082941e-01 4.67580557e-01
-1.00658558e-01 -1.30137670e+00 9.51817483e-02 -3.17134112e-01
-7.88576543e-01 -1.24017942e+00 -3.83145958e-01 -3.34230602e-01
5.19161224e-01 5.08683696e-02 4.28017080e-01 -3.37136269e-01
4.15317900e-02 5.53983152e-01 -4.04565096e-01 -3.36500913e-01
1.94802915e-03 -2.15867236e-01 3.70732963e-01 6.82694912e-01
-8.83571152e-03 -8.18895221e-01 -3.33991140e-01 1.58194259e-01
-9.27398443e-01 1.63808048e-01 6.66462719e-01 7.14746892e-01
9.16792870e-01 9.53221798e-01 7.60838509e-01 -8.14619660e-01
5.46073675e-01 -7.80237615e-01 -9.76870656e-01 7.63190269e-01
-8.52332354e-01 1.78660467e-01 6.17068589e-01 -3.61036122e-01
-1.68914270e+00 -3.40913981e-01 6.05303645e-01 -8.56344342e-01
2.59069353e-01 1.24102032e+00 -5.70029736e-01 2.67455071e-01
-1.71685126e-03 5.70939541e-01 -2.16762379e-01 -5.12854218e-01
8.12508941e-01 2.78865278e-01 5.76506913e-01 -7.96049595e-01
1.16976821e+00 4.29576278e-01 4.53761131e-01 -7.41211057e-01
-6.28955901e-01 -4.48327661e-01 -3.28974426e-01 -2.81054527e-01
6.87826395e-01 -1.01798522e+00 -8.28559339e-01 4.70898777e-01
-9.21227753e-01 1.07909836e-01 -1.08391486e-01 1.00275874e+00
-4.14315760e-01 5.14088809e-01 -4.39666569e-01 -1.11303127e+00
-3.36768441e-02 -6.46690965e-01 6.54110014e-01 4.03229475e-01
4.83184129e-01 -1.43799758e+00 6.04290050e-03 2.09460244e-01
1.75030276e-01 4.91811603e-01 1.12354851e+00 -5.90508223e-01
-9.66498733e-01 -4.01167512e-01 -2.34032825e-01 2.71579623e-01
3.38095218e-01 1.29320949e-01 -4.66104954e-01 7.09467381e-03
-1.44971125e-02 3.52066666e-01 5.58795810e-01 1.83113635e-01
7.88197815e-01 -2.82265335e-01 -6.49289250e-01 4.46503848e-01
1.60879529e+00 2.99584657e-01 5.91612518e-01 1.82155237e-01
1.05065441e+00 4.49368060e-01 9.92481828e-01 6.72442138e-01
6.13999188e-01 5.07819116e-01 3.76281381e-01 7.31983483e-01
2.54162014e-01 -7.14210153e-01 9.47356448e-02 1.22730708e+00
-4.08982873e-01 -2.85122424e-01 -9.85640943e-01 4.93913978e-01
-2.42569923e+00 -9.39362824e-01 -4.28206116e-01 2.13955545e+00
5.01602709e-01 6.34510741e-02 -6.22594774e-01 1.10535696e-02
9.94725645e-01 1.70950174e-01 -5.75951695e-01 3.67831022e-01
-9.85797867e-02 -2.29487464e-01 5.52579641e-01 4.18233037e-01
-8.99792314e-01 7.59581029e-01 4.16088057e+00 1.25845194e+00
-5.53311884e-01 6.53306171e-02 7.50915855e-02 2.81892180e-01
-4.86292303e-01 3.40850383e-01 -8.46761048e-01 7.17880726e-01
7.03736603e-01 -6.59653306e-01 5.13511300e-01 7.04725683e-01
3.70499939e-01 -1.18643895e-01 -6.03359818e-01 1.07596183e+00
-1.94797739e-01 -1.23079860e+00 1.07240885e-01 -7.01517239e-03
1.06073964e+00 -4.08886313e-01 -7.06587881e-02 5.45977890e-01
3.47748101e-01 -5.16114414e-01 4.65729684e-01 1.47001576e+00
4.03375685e-01 -9.58272099e-01 9.83299196e-01 3.54653656e-01
-1.53454053e+00 -7.90533125e-02 -4.46176827e-01 2.61796832e-01
4.75570142e-01 1.12258315e+00 -7.82431483e-01 1.77388704e+00
4.87722486e-01 1.04322219e+00 -4.65064108e-01 1.02512109e+00
-5.01494408e-01 6.41640246e-01 -2.93894589e-01 9.54822078e-02
1.32311592e-02 -7.58297443e-01 5.99878848e-01 5.26991606e-01
6.96738183e-01 1.49415120e-01 1.70750961e-01 7.56203890e-01
1.36599824e-01 2.54930198e-01 -3.75477195e-01 -3.94465834e-01
7.37985373e-01 1.17869270e+00 -6.48104429e-01 -4.33616906e-01
-3.90270293e-01 6.32164359e-01 1.62910685e-01 7.48224676e-01
-7.92333066e-01 -1.86242014e-01 4.84031826e-01 -2.21768886e-01
4.94674265e-01 -4.07335520e-01 1.34501904e-01 -1.38168871e+00
2.22012639e-01 -3.38533074e-01 4.93191808e-01 -8.41296613e-01
-1.39884150e+00 9.42072347e-02 3.05231959e-01 -1.31899047e+00
9.86399949e-02 -3.10928196e-01 -5.09507120e-01 9.69571888e-01
-1.46294796e+00 -1.34053075e+00 -2.94070691e-01 7.55917490e-01
-9.27804038e-02 -1.46308064e-01 5.61513662e-01 1.43411160e-01
-8.74921441e-01 -1.31795660e-01 7.37577140e-01 -2.55877614e-01
3.45161110e-01 -1.08890676e+00 -9.38139707e-02 9.10783052e-01
-3.84904593e-02 5.57167232e-01 6.56224966e-01 -1.14430499e+00
-1.72388387e+00 -1.46050799e+00 5.45114279e-01 -5.37619554e-02
1.23946536e+00 1.71159040e-02 -1.04699731e+00 9.34111714e-01
-3.43493134e-01 3.27725738e-01 3.02528590e-01 2.50638843e-01
1.64585151e-02 -4.86790508e-01 -8.14151168e-01 5.18611014e-01
7.49383688e-01 -5.10632098e-01 -6.15281105e-01 4.50910300e-01
8.74679923e-01 -4.32450682e-01 -1.23528004e+00 5.57625055e-01
1.08166791e-01 -3.62629026e-01 8.07260692e-01 -4.94832963e-01
-1.05826542e-01 -7.89646029e-01 -2.01392829e-01 -1.58626294e+00
-1.65324315e-01 -3.98244381e-01 -7.32186794e-01 1.66087949e+00
-7.71276206e-02 -1.05119956e+00 5.18406272e-01 7.19019353e-01
-1.38370380e-01 -6.30179882e-01 -9.90888715e-01 -1.17660296e+00
-5.01723289e-01 -4.54599172e-01 9.19436812e-01 9.34361041e-01
-2.48153489e-02 8.14223960e-02 -5.54091275e-01 9.33250189e-01
7.55587280e-01 1.88387364e-01 5.80764890e-01 -1.55985129e+00
-3.20039630e-01 4.01956886e-02 -7.98516273e-01 -5.30395389e-01
1.44649744e-01 -8.27265799e-01 -2.64499933e-01 -1.99257767e+00
-2.45568439e-01 -4.69874889e-01 -3.64966333e-01 9.51968282e-02
-3.28713715e-01 -8.33707869e-01 -5.99274179e-03 2.70887643e-01
-4.98455763e-01 1.31656289e+00 1.04140353e+00 -2.30549172e-01
-1.69014305e-01 2.26275250e-03 -1.64553568e-01 6.08705163e-01
6.67322576e-01 -2.07805738e-01 -1.02475631e+00 -6.81241602e-02
3.28319758e-01 3.63475174e-01 2.19379902e-01 -1.07668710e+00
4.05465990e-01 -4.02260542e-01 -4.47448008e-02 -8.97620082e-01
4.77037817e-01 -8.50620091e-01 8.39133918e-01 1.20091692e-01
3.92835557e-01 -1.67411283e-01 1.84808984e-01 1.52336669e+00
-4.18664813e-01 -2.21929494e-02 -7.89789632e-02 1.52632758e-01
-1.07693601e+00 7.48608530e-01 -2.08559427e-02 -8.95302072e-02
1.21787381e+00 2.69791067e-01 -5.17845988e-01 -2.71940321e-01
-9.77093518e-01 5.98313749e-01 4.63046581e-02 2.37250388e-01
7.01618016e-01 -1.53787887e+00 -3.97702962e-01 -4.69314992e-01
2.34842181e-01 2.36196578e-01 8.41580868e-01 1.01253664e+00
-1.75914451e-01 6.03504717e-01 3.23264748e-01 -2.02850714e-01
-5.83512604e-01 9.98201668e-01 -6.23570196e-03 -4.99893695e-01
-6.37169302e-01 3.19393635e-01 -9.07765701e-02 -2.33283475e-01
-1.14285521e-01 -3.52039725e-01 -3.52500081e-01 2.03787804e-01
1.37647346e-01 5.90100586e-01 1.41158588e-02 -5.43484867e-01
-3.47065657e-01 3.77865613e-01 2.60459810e-01 -4.25530151e-02
1.23824942e+00 -4.50573474e-01 -1.26813456e-01 7.54789174e-01
7.28923380e-01 5.45766652e-02 -1.05056262e+00 -6.12153232e-01
1.03516050e-01 -4.26502436e-01 1.00510843e-01 -5.30502856e-01
-1.15280545e+00 6.66373730e-01 2.92604923e-01 6.69471025e-02
7.45039284e-01 -2.95078844e-01 5.51615357e-01 3.54053527e-01
7.06383228e-01 -1.24608231e+00 -2.84098625e-01 2.38215610e-01
7.10190773e-01 -7.94040918e-01 1.52860731e-01 -7.99972475e-01
-6.16754472e-01 9.75903690e-01 4.27802563e-01 1.37398198e-01
1.09824455e+00 -4.70320940e-01 -4.37078983e-01 -2.98896641e-01
-5.62124133e-01 -3.64352584e-01 2.33080432e-01 6.64272666e-01
-4.71811324e-01 4.30949390e-01 -2.39742696e-01 9.69962180e-01
9.95281413e-02 2.27448270e-01 3.96360695e-01 6.29743099e-01
-1.93661377e-01 -8.24729264e-01 -4.40964043e-01 4.55913156e-01
6.08020648e-02 1.71660885e-01 4.95943576e-01 8.27047467e-01
2.05793351e-01 1.04712486e+00 -4.81462806e-01 -4.66944993e-01
3.22178572e-01 2.48275444e-01 1.57019094e-01 -5.29382646e-01
5.94394922e-01 -2.19627559e-01 1.97995424e-01 -3.34833115e-01
-2.40062982e-01 -7.07962990e-01 -1.36728609e+00 -2.39154115e-01
-4.74851876e-01 4.39534605e-01 6.01913691e-01 1.20253587e+00
4.08141971e-01 7.57219434e-01 4.38848615e-01 -2.97386795e-01
-4.29257780e-01 -8.72883201e-01 -1.31693101e+00 2.24240601e-01
-3.42401952e-01 -1.24763680e+00 -1.44074023e-01 -1.59870416e-01] | [8.60688304901123, 7.895254135131836] |
ae83bdbd-3ad3-4bd2-a437-951531e2d833 | covid-19-therapy-target-discovery-with | 2007.15681 | null | https://arxiv.org/abs/2007.15681v2 | https://arxiv.org/pdf/2007.15681v2.pdf | COVID-19 therapy target discovery with context-aware literature mining | The abundance of literature related to the widespread COVID-19 pandemic is beyond manual inspection of a single expert. Development of systems, capable of automatically processing tens of thousands of scientific publications with the aim to enrich existing empirical evidence with literature-based associations is challenging and relevant. We propose a system for contextualization of empirical expression data by approximating relations between entities, for which representations were learned from one of the largest COVID-19-related literature corpora. In order to exploit a larger scientific context by transfer learning, we propose a novel embedding generation technique that leverages SciBERT language model pretrained on a large multi-domain corpus of scientific publications and fine-tuned for domain adaptation on the CORD-19 dataset. The conducted manual evaluation by the medical expert and the quantitative evaluation based on therapy targets identified in the related work suggest that the proposed method can be successfully employed for COVID-19 therapy target discovery and that it outperforms the baseline FastText method by a large margin. | ['Martin Marzidovšek', 'Nada Lavrač', 'Blaž Škrlj', 'Matej Martinc', 'Sergej Pirkmajer', 'Bojan Cestnik', 'Senja Pollak'] | 2020-07-30 | null | null | null | null | ['literature-mining'] | ['natural-language-processing'] | [ 3.51228505e-01 2.44161174e-01 -4.88277972e-01 -3.70848626e-02
-1.03578889e+00 -7.04842091e-01 7.68128872e-01 8.72129321e-01
-6.12798691e-01 1.41934550e+00 4.52094823e-01 -4.23313528e-01
-5.41797936e-01 -5.48265755e-01 -7.53155351e-01 -5.19445360e-01
2.94659939e-03 9.00472760e-01 -2.98298523e-02 -6.11256585e-02
2.43080720e-01 6.07968807e-01 -9.14494157e-01 1.92179367e-01
9.94726837e-01 4.96300161e-01 2.51845777e-01 4.12110627e-01
-1.47252038e-01 2.72129804e-01 -6.67200983e-01 -6.04407370e-01
-2.66074151e-01 -2.16685653e-01 -7.34012008e-01 -7.77246058e-01
-1.78274978e-02 2.42891908e-01 -3.15538384e-02 8.05471718e-01
8.24726939e-01 -2.02919513e-01 1.21896470e+00 -9.58334088e-01
-6.97545111e-01 7.28694081e-01 -5.00836432e-01 3.96240145e-01
1.92912236e-01 6.66869283e-02 1.09333742e+00 -1.05717278e+00
1.35702193e+00 8.56557250e-01 6.44489467e-01 3.80901814e-01
-1.18328846e+00 -9.35275316e-01 -3.55286062e-01 3.52873743e-01
-1.54343653e+00 1.02407940e-01 5.81017673e-01 -6.80003643e-01
1.13580894e+00 9.85587090e-02 3.61074090e-01 1.70641971e+00
4.46163684e-01 5.18010482e-02 9.19202507e-01 -4.74305123e-01
3.88679594e-01 4.79338348e-01 2.03127220e-01 5.81633925e-01
6.52341545e-01 -1.26487404e-01 -6.08597040e-01 -7.05730498e-01
1.78804532e-01 -1.70822963e-01 -2.39340901e-01 4.43347134e-02
-1.20609212e+00 9.35559154e-01 8.49638283e-02 7.17925310e-01
-7.35013843e-01 -8.39367285e-02 9.68489170e-01 4.78261476e-03
5.90578377e-01 9.21681643e-01 -5.93615830e-01 6.77161813e-02
-8.88536751e-01 2.17073649e-01 7.30381966e-01 8.59465778e-01
3.80531609e-01 -3.77727270e-01 -4.78889227e-01 5.27838349e-01
1.44352078e-01 2.61518329e-01 5.57515800e-01 -4.04818386e-01
2.74929464e-01 7.74507582e-01 -2.06803493e-02 -9.71685231e-01
-3.77201319e-01 -5.35653234e-01 -9.61894691e-01 -2.48637915e-01
1.16920546e-02 -4.45053875e-01 -5.32016277e-01 1.77716982e+00
3.80811810e-01 6.15135193e-01 3.72288108e-01 4.72933948e-01
8.75847280e-01 5.02711833e-01 8.70243788e-01 -4.24440861e-01
1.72201300e+00 -4.92870867e-01 -9.66171980e-01 4.13492501e-01
7.93693841e-01 -6.59156322e-01 6.10837698e-01 3.49384159e-01
-5.73899329e-01 -2.48478949e-01 -1.16874254e+00 1.03371097e-02
-1.04400754e+00 2.97072023e-01 5.99542201e-01 3.46758634e-01
-7.11671114e-01 3.81232709e-01 -3.21951598e-01 -5.94995081e-01
6.62318170e-01 3.09975356e-01 -5.85941076e-01 1.34037703e-01
-1.64817595e+00 1.12601638e+00 7.74560869e-01 -2.58607000e-01
-8.11420202e-01 -1.27659535e+00 -3.81577969e-01 1.20724097e-01
1.85483351e-01 -1.08636439e+00 3.94306958e-01 -2.23550647e-01
-1.14958954e+00 1.01565707e+00 5.37288375e-02 -6.55255437e-01
2.00632408e-01 -1.22550711e-01 -5.82728863e-01 3.87872040e-01
2.05724269e-01 2.37347901e-01 4.66157407e-01 -7.49178052e-01
-3.96968931e-01 -5.16582310e-01 -3.41596872e-01 -8.92692655e-02
-8.13457549e-01 1.23176202e-01 -2.50352174e-01 -7.89023399e-01
-1.04442811e+00 -7.93682039e-01 -4.10184473e-01 -3.18115324e-01
-4.40113783e-01 -7.59147823e-01 7.18039870e-01 -5.04132748e-01
1.39316916e+00 -1.69940090e+00 2.20142007e-01 3.23766112e-01
3.07673901e-01 3.74319106e-01 -8.47260356e-02 7.17132270e-01
-3.66984338e-01 4.03390765e-01 -1.06340438e-01 2.27211654e-01
-2.53813148e-01 -6.53256383e-03 -4.22870636e-01 5.03765583e-01
4.05622989e-01 9.08661366e-01 -1.21770692e+00 -7.71343470e-01
-2.40247980e-01 5.42381525e-01 -3.30611527e-01 3.73296976e-01
-4.79630172e-01 4.27493662e-01 -1.01835620e+00 5.10460556e-01
4.84557569e-01 -4.13540751e-01 4.88196611e-01 -4.94913906e-01
1.16978943e-01 -2.53906727e-01 -5.40870845e-01 1.96104062e+00
-3.31727773e-01 3.34005952e-01 -3.82387757e-01 -1.17636168e+00
8.57353926e-01 7.25137532e-01 7.92555809e-01 -7.27119371e-02
2.59379357e-01 2.00154185e-01 -9.73375663e-02 -7.75092304e-01
1.23817228e-01 -1.93968371e-01 -4.06813920e-02 3.02982241e-01
3.96509409e-01 1.05969720e-01 1.18963279e-01 2.83446521e-01
1.52592719e+00 1.53528014e-02 4.72489566e-01 -3.77971768e-01
8.74237120e-01 1.68317363e-01 2.83872753e-01 4.60895449e-01
1.22704133e-01 3.57639752e-02 3.08334559e-01 -2.59116530e-01
-9.52990174e-01 -8.15598965e-01 -6.81028187e-01 8.16592693e-01
-3.72623563e-01 -5.90653121e-01 -5.75108528e-01 -8.23358119e-01
1.38665468e-01 7.53499508e-01 -1.00631869e+00 -1.10090606e-01
-1.35759711e-01 -9.80819702e-01 9.92745936e-01 3.40018719e-01
-7.98510909e-02 -9.02367115e-01 -3.14608276e-01 3.52629721e-01
1.82179749e-01 -1.17435646e+00 -1.51631236e-01 2.56269366e-01
-6.13090277e-01 -1.20719624e+00 -8.75185728e-01 -6.37559891e-01
4.80869263e-01 -6.81030512e-01 8.60338569e-01 -2.12951079e-01
-6.46771431e-01 2.60667324e-01 -2.71509767e-01 -8.71461749e-01
-4.43589509e-01 3.20263267e-01 2.38185450e-01 -2.39989579e-01
8.18040967e-01 -5.27617276e-01 -5.08507371e-01 -3.05793375e-01
-9.20431972e-01 -2.26721510e-01 9.72132802e-01 1.01750219e+00
7.04251349e-01 -2.44605079e-01 1.22205794e+00 -1.31736457e+00
1.08934689e+00 -1.18800235e+00 -3.62303436e-01 3.56229037e-01
-1.06767118e+00 2.49446273e-01 4.86962885e-01 -4.34886217e-01
-1.08792317e+00 -2.18345627e-01 -2.21068621e-01 -3.59750092e-01
-1.67575061e-01 9.02899683e-01 1.38686866e-01 2.81712979e-01
9.99868333e-01 -1.35272946e-02 -3.36081803e-01 -4.54233825e-01
7.15297282e-01 8.79042625e-01 5.44839263e-01 -7.23606944e-01
5.99696159e-01 5.17726727e-02 4.36568290e-01 -7.39079535e-01
-5.91383100e-01 -6.46579266e-01 -4.21883941e-01 3.07856083e-01
1.21100700e+00 -9.10066247e-01 -7.39184320e-01 -3.06746632e-01
-1.56166041e+00 2.87565529e-01 -1.95475027e-01 6.57369912e-01
-1.97773859e-01 2.37844676e-01 -3.92433167e-01 -3.71018559e-01
-9.96547282e-01 -9.44762111e-01 1.10034680e+00 6.57203421e-02
-5.66274583e-01 -1.05377674e+00 8.77362370e-01 3.52960266e-02
2.33708903e-01 4.45218414e-01 1.46905565e+00 -1.31886601e+00
-2.39456189e-03 -2.54105091e-01 -2.91088521e-01 -8.71963874e-02
3.15561384e-01 6.52055666e-02 -9.92702425e-01 1.39354710e-02
-4.30630207e-01 -4.83173609e-01 6.32270575e-01 1.28099456e-01
1.34007680e+00 -3.29046667e-01 -8.58160675e-01 2.94435859e-01
1.48501134e+00 1.13856614e-01 3.87930125e-01 3.68440986e-01
4.46243167e-01 3.96612078e-01 5.26298344e-01 4.47410196e-01
-1.93155870e-01 4.85773206e-01 -2.99256146e-02 -1.65924251e-01
3.58670652e-02 -1.78911597e-01 -1.67722642e-01 6.44202828e-01
-5.03139675e-01 -2.70516217e-01 -9.90966976e-01 7.15410829e-01
-1.54803622e+00 -8.05823982e-01 1.48291960e-01 1.77988422e+00
1.52387965e+00 1.39065934e-02 -1.71484649e-01 -4.98845935e-01
4.96014744e-01 -5.34906983e-01 -5.52093983e-01 -5.69513142e-01
-1.56684861e-01 8.66509795e-01 3.92580837e-01 1.82824969e-01
-7.67186761e-01 8.32629561e-01 6.28044605e+00 1.20932651e+00
-8.78760755e-01 2.70507157e-01 5.80979347e-01 3.28984469e-01
-4.48956668e-01 -2.54311740e-01 -7.66463697e-01 3.74988168e-01
1.44018972e+00 -6.83244526e-01 -3.69509101e-01 7.85912752e-01
1.47022694e-01 5.66493809e-01 -1.27878034e+00 7.72654474e-01
-1.42534912e-01 -2.06124282e+00 2.35443577e-01 5.83447665e-02
6.61424458e-01 6.84737116e-02 1.78391878e-02 3.84234995e-01
2.77214348e-01 -1.19950771e+00 -2.28477716e-01 7.22131610e-01
1.03949130e+00 -4.95513320e-01 9.53838885e-01 5.76896556e-02
-6.94077373e-01 2.60409772e-01 -3.52116942e-01 6.57452047e-01
-2.01640278e-01 6.71941340e-01 -1.57356262e+00 1.01069760e+00
4.26280886e-01 7.76541054e-01 -5.03304660e-01 6.87120259e-01
-1.48590490e-01 8.01376164e-01 -6.69246241e-02 -2.97455162e-01
1.30772203e-01 -2.54437141e-03 5.58564425e-01 1.85862815e+00
3.92692477e-01 1.21684209e-01 -1.84506923e-01 1.06591368e+00
-6.21181905e-01 7.92926311e-01 -1.02595842e+00 -6.32434189e-01
5.11073053e-01 1.52757514e+00 -1.40318945e-01 -5.75013638e-01
-2.70111978e-01 7.50214100e-01 2.99218237e-01 4.01377767e-01
-7.38796949e-01 -3.85057479e-01 2.82437861e-01 -3.45889777e-02
7.92307258e-02 2.53496140e-01 -1.91281110e-01 -6.85465813e-01
-5.14994144e-01 -8.65499854e-01 6.89485133e-01 -6.74505591e-01
-1.75844765e+00 9.08442378e-01 9.54250321e-02 -1.04539585e+00
-2.35945761e-01 -7.57810533e-01 -4.61898953e-01 1.03944182e+00
-1.28773582e+00 -1.41704547e+00 2.04550311e-01 3.17756832e-01
2.83000320e-01 -5.94339192e-01 1.43612862e+00 3.03397149e-01
-5.37763119e-01 5.70161760e-01 2.77383238e-01 -2.22331300e-01
1.10395062e+00 -1.13062394e+00 -3.58695507e-01 1.49028197e-01
-2.19436899e-01 1.04333794e+00 8.37527037e-01 -8.22618425e-01
-1.34034288e+00 -1.23086047e+00 9.66063857e-01 -6.91817284e-01
1.02967274e+00 -1.52524486e-01 -1.04815733e+00 4.61227268e-01
7.44165480e-01 -2.53482848e-01 1.28996289e+00 1.55348539e-01
-3.46003234e-01 9.32882428e-02 -1.27241266e+00 4.47495937e-01
7.42444515e-01 -3.96499366e-01 -1.03753400e+00 7.06896484e-01
7.79996395e-01 1.02907857e-02 -1.48327672e+00 4.35981601e-01
3.29269201e-01 2.47977972e-01 1.09255302e+00 -1.31559050e+00
7.23277032e-01 -1.39721155e-01 8.30635652e-02 -1.17864060e+00
-2.13837922e-01 -5.53362608e-01 -5.07396087e-02 1.28591919e+00
7.33645856e-01 -2.77364135e-01 5.40258229e-01 3.91592324e-01
1.50859877e-01 -9.90187407e-01 -1.08952487e+00 -3.76031160e-01
3.77351254e-01 -3.48996520e-02 3.35603297e-01 1.28440464e+00
3.81630331e-01 8.60844135e-01 -6.48506880e-02 1.37599036e-01
4.10212457e-01 -6.38242811e-02 6.20817900e-01 -1.38872623e+00
-1.99080586e-01 -2.39710629e-01 -4.03920859e-01 -9.01493728e-02
4.80253339e-01 -1.32391703e+00 -3.52461606e-01 -1.38946748e+00
5.55044115e-01 -3.95530701e-01 -7.68917382e-01 3.91061753e-01
-2.84326792e-01 -5.80808446e-02 -6.48719609e-01 -1.22146294e-01
-3.01980823e-01 5.56379676e-01 8.59687090e-01 -4.61670846e-01
1.98078658e-02 -6.32832408e-01 -8.64221394e-01 5.74456751e-01
4.39329803e-01 -7.61455238e-01 -4.56456035e-01 2.94487417e-01
3.94736230e-01 -2.29499459e-01 -2.66128778e-03 -4.37630326e-01
3.54254752e-01 -1.88435048e-01 4.03296947e-01 -5.38675904e-01
-7.16810152e-02 -9.07055974e-01 3.34502518e-01 3.26957792e-01
-5.55195928e-01 5.88003173e-02 6.99016154e-01 8.99056971e-01
-1.01101249e-02 -4.69408274e-01 3.67965460e-01 7.23033026e-02
-5.63077807e-01 2.61124641e-01 -4.58351046e-01 2.01787949e-01
1.12462318e+00 4.72571015e-01 -3.70110720e-01 2.85885066e-01
-5.58969080e-01 5.12028337e-02 -1.22766525e-01 3.19772542e-01
5.06110728e-01 -1.15841472e+00 -1.00360966e+00 -4.16827351e-01
4.60675150e-01 -4.75820899e-01 4.90411073e-02 7.86204755e-01
-2.68023461e-01 6.29771411e-01 -1.11791708e-01 -3.45391035e-01
-1.18859327e+00 9.59369719e-01 -5.64637445e-02 -8.58283043e-01
-4.66918647e-01 7.53353536e-01 2.03064516e-01 -1.15234144e-01
1.26218870e-01 -1.66475147e-01 -6.17523432e-01 1.00220561e-01
4.75360990e-01 1.00113191e-01 1.98586002e-01 -3.26263458e-01
-5.91638267e-01 4.95281219e-01 -2.73194790e-01 7.13720620e-02
1.68039405e+00 4.55085844e-01 -1.16335928e-01 2.01932222e-01
1.16333175e+00 2.79158890e-01 -1.38663441e-01 -2.95403808e-01
1.78706408e-01 -2.93796752e-02 1.70425326e-02 -1.15677488e+00
-5.13279557e-01 7.47027397e-01 7.84646928e-01 -5.09414494e-01
8.70886683e-01 4.61281948e-02 3.35780740e-01 6.55259609e-01
3.28894183e-02 -1.00592482e+00 -3.11912391e-02 -3.75641859e-03
1.10934162e+00 -1.01332700e+00 1.90718457e-01 -2.03130573e-01
-5.16014814e-01 1.18053603e+00 3.36340457e-01 2.46682242e-01
7.89999187e-01 3.17819476e-01 -2.12274984e-01 -7.40183175e-01
-7.87979126e-01 1.57312155e-01 3.42831790e-01 5.65445125e-01
6.68454051e-01 -1.03812672e-01 -1.05572462e+00 1.07996011e+00
3.60371947e-01 6.09602332e-01 1.69907317e-01 5.32904029e-01
7.78464451e-02 -1.46458113e+00 -5.37439547e-02 4.90509927e-01
-8.31052065e-01 -3.96866083e-01 -5.32280684e-01 7.29227781e-01
4.46402878e-01 4.53219056e-01 -4.41944122e-01 -1.92774385e-01
3.83306384e-01 3.07802171e-01 2.90073186e-01 -6.33948386e-01
-5.56085885e-01 -5.56841344e-02 3.15113813e-01 -2.79522836e-02
-6.07010186e-01 -3.88129324e-01 -1.34134102e+00 1.84285104e-01
-2.34783530e-01 5.61926067e-01 5.11726856e-01 8.99476647e-01
8.39469910e-01 7.62038648e-01 1.92598671e-01 -1.41434118e-01
-3.16979408e-01 -1.13591599e+00 -3.66231799e-01 4.90276456e-01
-8.08603838e-02 -7.62621999e-01 8.91221911e-02 3.62483740e-01] | [8.475812911987305, 8.670805931091309] |
8b772d8b-8ac4-4331-88ca-5f6ecc220f4b | transformer-based-hand-gesture-recognition | 2212.00743 | null | https://arxiv.org/abs/2212.00743v2 | https://arxiv.org/pdf/2212.00743v2.pdf | Transformer-based Hand Gesture Recognition via High-Density EMG Signals: From Instantaneous Recognition to Fusion of Motor Unit Spike Trains | Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In this context, the paper proposes a compact deep learning framework referred to as the CT-HGR, which employs a vision transformer network to conduct hand gesture recognition using highdensity sEMG (HD-sEMG) signals. The attention mechanism in the proposed model identifies similarities among different data segments with a greater capacity for parallel computations and addresses the memory limitation problems while dealing with inputs of large sequence lengths. CT-HGR can be trained from scratch without any need for transfer learning and can simultaneously extract both temporal and spatial features of HD-sEMG data. Additionally, the CT-HGR framework can perform instantaneous recognition using sEMG image spatially composed from HD-sEMG signals. A variant of the CT-HGR is also designed to incorporate microscopic neural drive information in the form of Motor Unit Spike Trains (MUSTs) extracted from HD-sEMG signals using Blind Source Separation (BSS). This variant is combined with its baseline version via a hybrid architecture to evaluate potentials of fusing macroscopic and microscopic neural drive information. The utilized HD-sEMG dataset involves 128 electrodes that collect the signals related to 65 isometric hand gestures of 20 subjects. The proposed CT-HGR framework is applied to 31.25, 62.5, 125, 250 ms window sizes of the above-mentioned dataset utilizing 32, 64, 128 electrode channels. The average accuracy over all the participants using 32 electrodes and a window size of 31.25 ms is 86.23%, which gradually increases till reaching 91.98% for 128 electrodes and a window size of 250 ms. The CT-HGR achieves accuracy of 89.13% for instantaneous recognition based on a single frame of HD-sEMG image. | ['Arash Mohammadi', 'Svetlana Yanushkevich', 'S. Farokh Atashzar', 'Farnoosh Naderkhani', 'Elahe Rahimian', 'Mansooreh Montazerin'] | 2022-11-29 | null | null | null | null | ['hand-gesture-recognition', 'hand-gesture-recognition-1', 'gesture-recognition'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [ 2.54271388e-01 -3.67603928e-01 2.40502715e-01 2.55200177e-01
-7.90276706e-01 -2.72332221e-01 3.71702611e-01 -5.64682961e-01
-6.57380879e-01 9.20021176e-01 8.92067403e-02 -1.11793146e-01
-2.08671466e-01 -3.96613777e-01 -6.89728141e-01 -1.10129976e+00
2.18876675e-02 8.80536884e-02 1.88637137e-01 2.56650507e-01
4.93788064e-01 4.96280938e-01 -1.58076060e+00 3.21380645e-01
6.29539132e-01 1.26478183e+00 8.20812404e-01 7.38379717e-01
2.34840557e-01 2.36125067e-01 -6.73744917e-01 8.85350779e-02
3.72747689e-01 -4.91561264e-01 -3.12420458e-01 -3.64648223e-01
-3.68047878e-02 -5.60675442e-01 -6.02314651e-01 8.09847295e-01
1.14370298e+00 1.06736468e-02 8.42715383e-01 -8.70341063e-01
-7.36713648e-01 4.35005873e-01 -6.67960167e-01 4.18411165e-01
1.34143546e-01 4.79589134e-01 4.43641633e-01 -8.99430513e-01
5.51090837e-01 7.15419233e-01 5.30018210e-01 6.99960828e-01
-9.54085290e-01 -6.95298672e-01 -1.94128469e-01 4.08010334e-01
-1.45796394e+00 -2.51292765e-01 6.61343336e-01 -5.70218265e-01
1.51717305e+00 2.26101488e-01 6.90766454e-01 1.45192039e+00
6.63500726e-01 5.20023346e-01 1.37147498e+00 -3.67878258e-01
4.48144615e-01 -3.87065172e-01 2.99775332e-01 2.80139089e-01
3.91202599e-01 1.38829768e-04 -7.67550588e-01 4.52683829e-02
1.31857502e+00 1.86176106e-01 -4.85818774e-01 4.97180074e-01
-1.26798594e+00 2.58257180e-01 1.96042553e-01 6.63399160e-01
-1.03112829e+00 1.99668109e-01 1.84198275e-01 1.23639196e-01
-2.59982675e-01 1.12404101e-01 -6.02746382e-02 -5.21119237e-01
-8.76516879e-01 -7.82367066e-02 4.75145310e-01 8.31331730e-01
1.25072300e-01 2.37256423e-01 -4.03450668e-01 6.23548985e-01
4.12627339e-01 8.70738626e-01 8.79148543e-01 -7.67821610e-01
5.53563774e-01 2.91059256e-01 -7.92004466e-02 -6.06032014e-01
-3.14951360e-01 -2.06463307e-01 -8.92593443e-01 5.63807845e-01
4.90727901e-01 -1.94823012e-01 -1.25977015e+00 1.52823710e+00
-2.53359169e-01 6.72220960e-02 -1.36998799e-02 1.33109748e+00
7.14182019e-01 5.71713150e-01 -9.23756510e-02 -3.09489608e-01
1.28498149e+00 -3.56736273e-01 -7.03331411e-01 -6.35635331e-02
-1.77339807e-01 -4.31410879e-01 1.12528336e+00 5.17214596e-01
-1.05861592e+00 -3.70033026e-01 -9.74295974e-01 2.47948915e-01
-7.30552152e-02 4.35093015e-01 3.96107882e-01 4.24064368e-01
-9.08167183e-01 5.12967646e-01 -1.19972479e+00 -4.10610020e-01
3.64500999e-01 8.39460433e-01 -3.44703585e-01 2.89656222e-01
-8.64982188e-01 6.98635519e-01 1.93467773e-02 4.70890969e-01
-7.74601161e-01 -2.27765381e-01 -4.91419956e-02 4.26756740e-02
-3.41212660e-01 -4.22988266e-01 6.26858234e-01 -6.01191938e-01
-1.75371718e+00 6.54418170e-01 -2.86976695e-01 -1.65151462e-01
2.26559505e-01 4.08835709e-02 -8.64124075e-02 3.54284912e-01
-2.17862368e-01 2.05317542e-01 9.82247472e-01 -7.52367318e-01
-1.12050556e-01 -1.07479596e+00 -4.24192578e-01 1.23887919e-01
-3.41014504e-01 1.68553531e-01 2.03172257e-03 -8.30108583e-01
3.33835959e-01 -8.88300180e-01 3.42231691e-01 -4.14431691e-01
-2.44077921e-01 -7.02408701e-02 5.99891007e-01 -1.03744996e+00
9.95255232e-01 -1.89583278e+00 3.00782621e-01 3.22479844e-01
2.50887752e-01 4.32704091e-01 -1.02108821e-01 3.93743038e-01
4.70814705e-02 -3.95386994e-01 -2.59017020e-01 1.31905347e-01
-2.35078797e-01 -2.13606939e-01 -1.90738395e-01 3.48475724e-01
-1.25788644e-01 1.08554041e+00 -3.61650765e-01 -1.69315696e-01
2.45242089e-01 7.05549598e-01 -1.72954097e-01 3.10354650e-01
3.47897202e-01 5.59785545e-01 -3.87262195e-01 8.80947709e-01
5.22517383e-01 -2.17670575e-01 6.90005422e-02 -4.45258707e-01
-2.16878578e-01 1.31769672e-01 -9.06204760e-01 1.84785366e+00
-1.84293672e-01 7.35029399e-01 1.85095351e-02 -9.83161271e-01
9.87931848e-01 5.42752028e-01 5.29722512e-01 -8.46533418e-01
5.52271187e-01 5.94082296e-01 3.90645951e-01 -6.96137965e-01
-2.22179562e-01 -2.03452706e-01 3.57162803e-01 6.44862473e-01
2.67553896e-01 5.65001428e-01 -2.98385799e-01 -2.50463367e-01
1.46250033e+00 2.57611647e-02 4.69136573e-02 5.79606881e-03
3.29323918e-01 -4.73184109e-01 8.10944736e-02 7.44896889e-01
-2.33107194e-01 6.62657738e-01 -8.93685892e-02 -2.41290666e-02
-7.45132267e-01 -1.36930597e+00 7.51741370e-03 5.88202178e-01
1.95142284e-01 9.39569399e-02 -6.61404669e-01 -1.56355739e-01
-1.16483551e-02 6.87881783e-02 -5.03112018e-01 -4.46738414e-02
-7.08955586e-01 -5.94862700e-01 6.36869490e-01 8.60943794e-01
7.09439814e-01 -1.59041023e+00 -1.13414061e+00 2.86658168e-01
-2.33486369e-01 -8.89337003e-01 -1.53116941e-01 2.92491794e-01
-9.84035969e-01 -7.68436968e-01 -1.37457585e+00 -9.06960964e-01
3.79742771e-01 -1.44987375e-01 1.74629062e-01 -4.95380878e-01
-6.76256776e-01 4.82530504e-01 -3.52504551e-01 -3.19911063e-01
3.33528191e-01 -1.11721694e-01 1.40187576e-01 5.25402762e-02
7.28643417e-01 -1.13849664e+00 -6.24614656e-01 4.64581959e-02
-3.12745184e-01 -1.59216031e-01 9.80631232e-01 8.70274603e-01
6.32673442e-01 -5.05734146e-01 7.80196846e-01 1.73073992e-01
7.62845397e-01 -2.22604126e-01 -1.50079355e-01 2.94834286e-01
-3.94355625e-01 5.70681058e-02 5.68551958e-01 -8.17013919e-01
-1.02367377e+00 -2.56578714e-01 -2.46481150e-02 -5.94405353e-01
-2.08970696e-01 2.07138360e-01 -2.85724103e-02 -1.44479901e-01
5.14499366e-01 6.79223597e-01 2.98474729e-02 -5.21712124e-01
-1.18084356e-01 1.40785551e+00 7.32951224e-01 -4.94637877e-01
2.31864408e-01 3.29739898e-01 -1.94134325e-01 -9.24573958e-01
3.91716987e-01 -1.48546368e-01 -3.95474672e-01 -3.26518625e-01
7.28137791e-01 -6.41140282e-01 -1.10983324e+00 1.26303852e+00
-1.20240939e+00 -4.34734553e-01 9.65738446e-02 1.18273735e+00
-6.66317463e-01 2.00397611e-01 -1.02536106e+00 -1.20243311e+00
-9.29626822e-01 -9.58554983e-01 1.07977629e+00 2.63227403e-01
-1.99892193e-01 -4.42792982e-01 -1.79967731e-01 1.91953868e-01
4.96339142e-01 7.59105608e-02 6.49104655e-01 -4.21413332e-01
-5.45900881e-01 -1.82210982e-01 -2.46876523e-01 1.89710990e-01
4.66473311e-01 -5.24859965e-01 -1.11896980e+00 -3.55892122e-01
3.85487229e-01 -2.48031661e-01 5.82970023e-01 8.30241203e-01
8.92304122e-01 -2.00481489e-01 -3.36960196e-01 3.81938457e-01
1.47460949e+00 8.56218815e-01 1.05161047e+00 1.19473219e-01
7.07345665e-01 2.36607239e-01 1.34913653e-01 5.04761755e-01
-4.97809164e-02 6.17427051e-01 7.37523735e-02 2.50190824e-01
-3.75091791e-01 3.60743329e-02 3.86988670e-01 9.69760835e-01
-9.02305424e-01 -2.59516225e-03 -7.78330624e-01 4.04121101e-01
-1.48862290e+00 -9.29584384e-01 4.24481034e-02 2.24585915e+00
7.61088252e-01 -2.52260149e-01 8.80349055e-02 4.14650142e-01
8.85853887e-01 -2.78205603e-01 -9.84084308e-01 -1.34548441e-01
-7.75931478e-02 9.77145255e-01 4.66911286e-01 2.29572430e-01
-4.20276850e-01 5.47019601e-01 5.28863001e+00 6.01076066e-01
-1.50549400e+00 9.80026722e-02 -1.71207935e-01 -4.08017188e-01
1.79255635e-01 -4.58726376e-01 -5.94927728e-01 8.51111829e-01
1.01917410e+00 3.80196758e-02 9.18182850e-01 3.26026708e-01
3.07050586e-01 -1.57105848e-01 -8.97422194e-01 1.66482520e+00
6.84422329e-02 -1.05909514e+00 -7.21849203e-02 3.43369305e-01
2.40413621e-01 1.37161061e-01 4.61384729e-02 -2.16731697e-01
-5.65246284e-01 -1.20850670e+00 6.42519772e-01 6.55930042e-01
1.19533706e+00 -2.66819388e-01 7.07797945e-01 3.00253600e-01
-1.29485548e+00 -2.78463662e-01 -1.85458809e-01 -2.84483105e-01
1.02557525e-01 7.67878667e-02 -3.51887882e-01 3.26387405e-01
8.87615561e-01 5.56734025e-01 -1.37178555e-01 7.74903595e-01
2.39028916e-01 5.47367096e-01 -5.98958135e-01 -2.92603880e-01
-3.07850279e-02 -4.64172140e-02 6.16950750e-01 9.29602087e-01
7.93817580e-01 4.28634018e-01 -6.97305977e-01 1.13229859e+00
2.15741917e-01 -2.39897877e-01 -6.08892500e-01 -2.99334377e-01
7.68646300e-01 8.12133849e-01 -7.78749406e-01 -1.31471291e-01
-2.38103837e-01 1.24372768e+00 -4.91708554e-02 7.20075488e-01
-7.01181769e-01 -9.88675892e-01 2.43492022e-01 -7.69736245e-02
3.10543209e-01 -3.66937906e-01 -7.08526015e-01 -1.06695461e+00
6.54196978e-01 -7.08616316e-01 -6.94965497e-02 -8.43827069e-01
-1.15018797e+00 6.64272189e-01 -3.53283137e-01 -1.10309243e+00
-3.02073061e-01 -9.75802779e-01 -5.38289309e-01 1.18217552e+00
-9.43161607e-01 -9.00192380e-01 -6.18104577e-01 1.15878785e+00
3.76397103e-01 -3.79274338e-01 8.68738174e-01 2.81753093e-01
-4.29905355e-01 7.15112150e-01 6.19057529e-02 1.29816204e-01
4.06016588e-01 -8.77090394e-01 1.92712560e-01 6.65977359e-01
-1.23605579e-01 1.01596403e+00 1.68164656e-01 -7.79460192e-01
-1.77442193e+00 -5.52462995e-01 5.48202634e-01 -1.05680950e-01
1.72689438e-01 -3.33063006e-01 -8.10884714e-01 5.54419041e-01
-7.86906630e-02 -1.30478948e-01 3.66203874e-01 -5.58012545e-01
-2.33852714e-01 -1.13495633e-01 -1.31368411e+00 3.88110220e-01
1.30636621e+00 -7.97505200e-01 -9.16128695e-01 -1.84870586e-01
-9.65716094e-02 -2.11217672e-01 -1.03285336e+00 2.30583876e-01
1.24460542e+00 -7.58087099e-01 7.52934158e-01 -1.45897001e-01
-6.11865297e-02 -1.73717692e-01 -4.14441109e-01 -7.94032931e-01
-1.93913907e-01 -4.87350672e-01 -2.84933150e-01 9.87344265e-01
4.57884856e-02 -1.02787256e+00 7.10793495e-01 7.00973153e-01
-1.06453627e-01 -6.96245372e-01 -1.23180270e+00 -1.04596663e+00
-7.45316446e-02 -2.51380593e-01 1.92321986e-01 2.39216998e-01
4.08238053e-01 1.15947127e-01 -1.48397073e-01 -9.05796885e-02
8.98232520e-01 1.44783873e-02 8.15734789e-02 -1.13884044e+00
-2.61453420e-01 -2.97139674e-01 -6.67000413e-01 -9.11398590e-01
-1.52471229e-01 -8.47296178e-01 2.25053415e-01 -1.78601289e+00
3.10190380e-01 -4.62732911e-02 -4.07831043e-01 4.68567133e-01
2.51276374e-01 3.88930738e-01 1.00992329e-01 5.29719055e-01
1.39001131e-01 4.27183241e-01 1.08456075e+00 -3.80890705e-02
-3.25799525e-01 -2.94753939e-01 -9.64689329e-02 2.68160731e-01
7.94478834e-01 -6.32052422e-02 -2.99248546e-01 -2.60245413e-01
-5.65347135e-01 1.57904103e-01 6.26672387e-01 -1.26060069e+00
3.68574500e-01 1.74791425e-01 6.57854617e-01 -4.64479864e-01
4.39375430e-01 -6.85897708e-01 4.01524723e-01 4.61001694e-01
-1.36526078e-01 -1.57183558e-01 2.81138103e-02 4.77468878e-01
1.90989710e-02 1.47416353e-01 5.81581116e-01 -1.33883759e-01
-6.00505054e-01 2.60306261e-02 -7.04416156e-01 -3.40678066e-01
1.07478344e+00 -8.38220775e-01 -2.52617151e-01 9.74956304e-02
-8.60074401e-01 -5.07521570e-01 4.80027683e-02 2.91574866e-01
1.10117614e+00 -1.43443799e+00 -3.29706937e-01 6.03623629e-01
-1.77270249e-01 -5.27836442e-01 5.38609087e-01 1.07731903e+00
-1.74685240e-01 7.25629866e-01 -8.55674863e-01 -6.07549429e-01
-1.27128303e+00 2.19149262e-01 3.07560354e-01 1.62521407e-01
-1.05528331e+00 8.27476919e-01 -6.85273632e-02 3.63603473e-01
3.52951229e-01 -4.12142277e-01 -8.18646848e-02 -1.57560363e-01
5.81047297e-01 5.49880207e-01 2.21251965e-01 -5.10322034e-01
-6.50922239e-01 1.05158591e+00 3.02311450e-01 -5.70110738e-01
1.22469020e+00 -1.15378179e-01 6.15992434e-02 5.66403270e-01
1.18671739e+00 -4.31773752e-01 -1.33115697e+00 1.62181944e-01
-3.13357562e-01 -2.96569914e-01 -1.62802469e-02 -1.13359618e+00
-1.08917272e+00 1.21618223e+00 1.11491823e+00 -4.98531789e-01
1.34474659e+00 -6.05047643e-02 1.03382444e+00 2.75809228e-01
9.28967953e-01 -8.98347437e-01 1.73626348e-01 2.03765884e-01
1.11017716e+00 -6.47922873e-01 -6.67570174e-01 1.72272205e-01
-4.22557294e-01 1.22510719e+00 5.52699625e-01 -4.23600793e-01
4.85674918e-01 4.49245274e-01 -1.83261752e-01 -2.76208103e-01
-2.87475437e-01 -1.47943124e-01 1.76777959e-01 7.95162916e-01
2.49525487e-01 1.01916641e-01 -6.06783092e-01 1.13434625e+00
4.25611064e-02 7.35609829e-01 2.08695084e-01 1.00839257e+00
-1.90708727e-01 -5.28563142e-01 -3.65661174e-01 7.77787209e-01
-3.72970372e-01 -1.45795092e-01 -6.59297407e-02 4.83668983e-01
-1.14813074e-01 8.21424127e-01 3.07965861e-03 -8.49894941e-01
2.09960416e-01 3.27899247e-01 1.05558336e+00 -2.53545970e-01
-5.00281632e-01 3.25674802e-01 -4.44368869e-01 -5.99507630e-01
-3.89654756e-01 -5.38848042e-01 -1.71455669e+00 -9.68261659e-02
-1.31998107e-01 -1.38534412e-01 7.60270536e-01 1.03136373e+00
5.11435688e-01 5.30992866e-01 1.05677448e-01 -1.11563981e+00
-5.76357543e-01 -1.45900595e+00 -1.10288823e+00 2.54253168e-02
3.60531002e-01 -7.75739849e-01 -4.12647545e-01 1.14138275e-01] | [6.825743198394775, 0.12341788411140442] |
e37252ff-9093-4427-99b8-3a3dac3dc670 | a-survey-on-computational-propaganda | 2007.08024 | null | https://arxiv.org/abs/2007.08024v1 | https://arxiv.org/pdf/2007.08024v1.pdf | A Survey on Computational Propaganda Detection | Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda. They exploit the anonymity of the Internet, the micro-profiling ability of social networks, and the ease of automatically creating and managing coordinated networks of accounts, to reach millions of social network users with persuasive messages, specifically targeted to topics each individual user is sensitive to, and ultimately influencing the outcome on a targeted issue. In this survey, we review the state of the art on computational propaganda detection from the perspective of Natural Language Processing and Network Analysis, arguing about the need for combined efforts between these communities. We further discuss current challenges and future research directions. | ['Roberto Di Pietro', 'Alberto Barron-Cedeno', 'Giovanni Da San Martino', 'Stefano Cresci', 'Preslav Nakov', 'Seunghak Yu'] | 2020-07-15 | null | null | null | null | ['propaganda-detection'] | ['natural-language-processing'] | [ 2.84905285e-01 6.22013509e-01 -6.89786077e-01 2.85315271e-02
-3.19385916e-01 -7.17869401e-01 1.06216097e+00 8.18623543e-01
-4.23869014e-01 6.17960572e-01 9.85345602e-01 -6.80934608e-01
2.54788715e-02 -1.00005817e+00 1.85702652e-01 -1.55405745e-01
-5.99546880e-02 2.91796386e-01 -5.59819229e-02 -3.16701382e-01
6.06093466e-01 2.10020855e-01 -7.49979436e-01 2.47260362e-01
5.92657268e-01 1.56302571e-01 -6.92221820e-01 4.47929949e-01
-4.27271664e-01 1.08784211e+00 -8.44351649e-01 -5.93014598e-01
-3.78259048e-02 -3.51678193e-01 -7.99028993e-01 -4.41218093e-02
4.75065500e-01 -2.31806993e-01 -2.79708475e-01 1.26815879e+00
2.88335860e-01 -1.91305131e-01 3.94610345e-01 -7.24488676e-01
-6.33366525e-01 1.17255199e+00 -5.14095068e-01 6.18923545e-01
5.66854000e-01 -1.44705355e-01 1.12168741e+00 -2.41964236e-01
8.90979171e-01 1.45444942e+00 5.43366969e-01 4.40474719e-01
-1.20887971e+00 -5.81146240e-01 2.63744503e-01 -3.71455848e-01
-9.58864570e-01 -6.05848730e-01 9.43823814e-01 -8.87786388e-01
3.42395306e-01 4.98108089e-01 8.45532417e-01 1.29786909e+00
3.00606154e-02 3.31053764e-01 1.13918912e+00 -2.57288843e-01
1.59749761e-01 2.30756059e-01 5.58713615e-01 5.04390836e-01
4.35715914e-01 -4.72326458e-01 -6.20771587e-01 -1.22048092e+00
2.16403708e-01 -3.12408060e-01 1.90949459e-02 1.99375719e-01
-1.08099592e+00 1.49597180e+00 3.77959847e-01 5.92823803e-01
-3.28731716e-01 -1.70517460e-01 7.03384280e-01 1.21393852e-01
9.44850326e-01 7.03384757e-01 4.79628220e-02 -1.54280469e-01
-5.90633094e-01 1.38478056e-01 1.17540562e+00 -1.09334635e-02
4.19769287e-01 -3.53072971e-01 -1.60317630e-01 4.58099812e-01
4.95132506e-01 3.75606626e-01 1.31799236e-01 -6.40941858e-01
4.16417003e-01 8.14149797e-01 -7.83504769e-02 -1.69671285e+00
-3.74081463e-01 -3.92891169e-01 -6.45332515e-01 -1.43747568e-01
5.10968983e-01 -6.89992905e-01 -5.09591680e-03 1.55141068e+00
6.25084460e-01 -4.39240545e-01 -4.11265552e-01 3.71970326e-01
5.61780334e-01 4.02143687e-01 4.11012679e-01 -4.00306106e-01
1.61470103e+00 -2.28064626e-01 -7.68689096e-01 -2.74940729e-01
5.79173386e-01 -9.54889953e-01 4.89695221e-01 -1.64531022e-01
-6.44010186e-01 2.96389371e-01 -5.34338236e-01 7.07882270e-02
-3.88676733e-01 -5.46868145e-01 8.25124860e-01 1.08410072e+00
-5.59351325e-01 3.62216979e-01 -3.47066343e-01 -4.85035360e-01
9.07739580e-01 -1.82136402e-01 6.86024949e-02 4.66230869e-01
-1.47529030e+00 7.35802531e-01 -1.37262344e-01 -1.19590037e-01
-1.70572177e-01 -4.81060117e-01 -5.65111518e-01 -2.94417232e-01
4.39170748e-01 -3.35069329e-01 8.37033212e-01 -8.58216763e-01
-1.14092815e+00 9.45718765e-01 -1.89359263e-02 -4.57017481e-01
6.41928017e-01 -2.69111395e-01 -6.03990197e-01 2.20211893e-01
5.66782892e-01 1.23957328e-01 8.70726228e-01 -5.32535076e-01
-3.44478428e-01 -3.45298707e-01 4.89400700e-02 -6.78948686e-02
-6.73090696e-01 8.43204141e-01 5.24711132e-01 -3.63751322e-01
-2.56433457e-01 -5.82870841e-01 -3.81018847e-01 -3.98067743e-01
-8.56334627e-01 -2.85411507e-01 9.91866052e-01 -7.39926279e-01
1.34691024e+00 -1.90427363e+00 -7.79870003e-02 6.54905260e-01
9.43003297e-01 4.73613530e-01 3.43205214e-01 7.98665643e-01
3.73357385e-01 8.28562140e-01 4.81606036e-01 3.67264040e-02
-2.44736955e-01 -2.74066716e-01 -3.31759632e-01 8.60807121e-01
-3.46511155e-01 7.70204246e-01 -1.08663726e+00 -3.67809951e-01
8.72406736e-03 3.56143475e-01 -3.10500056e-01 -5.06912827e-01
-3.48421514e-01 5.02049923e-01 -1.13854420e+00 2.63234794e-01
1.36897802e-01 -5.41768372e-01 7.77504921e-01 2.72237569e-01
-5.73877633e-01 1.01657021e+00 -6.00451052e-01 5.11322618e-01
7.15556554e-03 1.09267855e+00 5.98773479e-01 -3.22446436e-01
7.44788289e-01 2.86762029e-01 1.68765903e-01 3.80555131e-02
6.39428556e-01 -1.86752662e-01 2.04509765e-01 -2.38584533e-01
3.65627676e-01 1.35235533e-01 -3.02127242e-01 1.28224337e+00
-7.57322490e-01 4.53146636e-01 1.18840657e-01 8.61279488e-01
9.91074085e-01 -8.19324315e-01 6.88604593e-01 -4.96697515e-01
4.72606599e-01 1.50306970e-01 6.32997677e-02 8.57935488e-01
-5.51688910e-01 -3.86349380e-01 8.10200751e-01 -5.06722033e-01
-8.80351484e-01 -6.16346300e-01 1.07728370e-01 1.33460963e+00
-2.26738095e-01 -5.55846393e-01 -5.97805262e-01 -8.23670328e-01
1.13166645e-01 6.12296820e-01 -7.52408147e-01 2.87923127e-01
-6.52620018e-01 -7.21843958e-01 5.83694577e-01 -4.63723928e-01
5.52781284e-01 -6.79784119e-01 -3.06607276e-01 2.99247384e-01
-4.64360625e-01 -8.89263868e-01 -3.86369735e-01 -8.08532715e-01
-5.12034535e-01 -1.33894217e+00 -6.65454417e-02 -4.38604832e-01
6.18340552e-01 3.55451733e-01 7.93986738e-01 3.00898373e-01
-3.04055177e-02 2.53892303e-01 -1.52605116e-01 -4.46301848e-01
-1.03908718e+00 5.15810311e-01 7.32095167e-02 3.35466176e-01
5.22518516e-01 -7.11474359e-01 -2.69675344e-01 1.57606043e-02
-5.26155829e-01 8.00233148e-03 2.47567836e-02 7.12677762e-02
-5.39583862e-01 -1.59268543e-01 7.48273492e-01 -1.45030820e+00
1.27734995e+00 -8.94567549e-01 -2.52916664e-01 -8.99091363e-02
-3.46684426e-01 -5.25590301e-01 1.94100112e-01 -4.59038764e-01
-7.82858849e-01 -6.65012598e-01 8.76887739e-02 6.62016213e-01
1.14017077e-01 5.37507355e-01 3.50908935e-01 -1.09882370e-01
1.09938955e+00 -2.74836719e-01 4.89423364e-01 -4.56180960e-01
6.66900873e-01 9.15211201e-01 -1.18654050e-01 -1.34539202e-01
8.22099745e-01 7.40664124e-01 -3.46020669e-01 -1.06231833e+00
-1.13568437e+00 -5.72809875e-01 -2.70593613e-01 -6.10641837e-01
6.99173331e-01 -6.82716310e-01 -8.72215748e-01 3.95069659e-01
-1.23218834e+00 2.26465553e-01 7.88628608e-02 1.59515381e-01
3.47472042e-01 5.62148452e-01 -9.16342735e-01 -8.46254468e-01
-7.77309418e-01 -2.18953207e-01 8.60310718e-02 -1.15872230e-02
-1.12742031e+00 -1.36599910e+00 3.36815506e-01 7.76761889e-01
6.88355207e-01 4.64036703e-01 7.41641223e-01 -1.01172173e+00
-1.05510838e-01 -5.25481284e-01 -2.98426867e-01 -1.04192719e-01
5.36217153e-01 1.26095474e-01 -6.32426322e-01 7.25546703e-02
1.08215980e-01 -6.61823004e-02 3.35920423e-01 1.57020628e-01
2.50366330e-01 -1.11176836e+00 -4.77080524e-01 -5.39838314e-01
8.30486536e-01 -5.66418767e-01 5.38248301e-01 3.63743782e-01
5.38505137e-01 7.68230140e-01 -3.81180011e-02 6.76290870e-01
3.22377801e-01 2.05445245e-01 2.75801569e-01 1.83314621e-01
1.87659845e-01 -4.90046561e-01 4.31996912e-01 5.67455232e-01
-5.21462299e-02 -6.90869289e-03 -9.11907673e-01 5.92540085e-01
-1.63936484e+00 -1.27171028e+00 -4.48239535e-01 1.53446758e+00
8.05276871e-01 3.25223923e-01 4.47172999e-01 -7.35316202e-02
1.35670805e+00 7.08928227e-01 1.44979581e-01 -6.32947743e-01
-6.26636147e-02 -2.46437132e-01 5.65500915e-01 1.01358557e+00
-9.78377521e-01 8.47922444e-01 6.86704874e+00 6.03053451e-01
-8.27101052e-01 2.22523704e-01 7.10922480e-01 -1.82115421e-01
-3.22662801e-01 3.91258039e-02 -6.97009504e-01 2.87875891e-01
8.17242146e-01 -4.57163870e-01 4.43458498e-01 5.71526647e-01
6.03976548e-01 -4.90983129e-02 -4.82236356e-01 1.23907104e-01
-3.77387665e-02 -1.92678380e+00 -9.16338861e-02 5.43177485e-01
6.91744924e-01 2.25220397e-01 -7.80066401e-02 -3.88534099e-01
6.49423957e-01 -7.06442118e-01 5.14905572e-01 5.63246384e-02
1.65304884e-01 -2.50864863e-01 2.53207147e-01 4.65959430e-01
-5.47851086e-01 2.32390817e-02 5.05667068e-02 -9.48512852e-01
6.38647437e-01 1.08116508e+00 -8.95027101e-01 1.38756083e-02
8.80508684e-03 7.31072426e-01 -3.11765671e-01 3.42774868e-01
-5.92923284e-01 1.11776340e+00 -3.07530224e-01 -7.18636990e-01
4.30363446e-01 -1.79873511e-01 1.04963791e+00 1.10498118e+00
-4.98864144e-01 2.55763441e-01 2.82030404e-01 8.03920567e-01
-1.44151941e-01 1.87060669e-01 -6.31321251e-01 -7.28634000e-01
6.41553164e-01 1.49501705e+00 -7.30472028e-01 -3.61024439e-01
-1.17989980e-01 8.75892863e-02 4.98618960e-01 1.24670770e-02
-2.11559296e-01 8.89308453e-02 7.36602783e-01 7.32807696e-01
-3.65169317e-01 -4.45604265e-01 -4.15818185e-01 -8.45107079e-01
-5.07427573e-01 -1.04015386e+00 4.84938204e-01 7.91516155e-03
-1.40620124e+00 1.64384305e-01 -3.75615627e-01 -2.29509428e-01
-8.35793540e-02 -1.06181756e-01 -1.01738262e+00 6.08541369e-01
-7.11442828e-01 -8.95831287e-01 2.65261650e-01 2.16133952e-01
3.00550610e-02 5.27662374e-02 6.56791389e-01 7.87012652e-02
-4.66076434e-01 4.67739552e-02 -3.94269437e-01 4.78520751e-01
3.73013496e-01 -4.52497095e-01 5.35165966e-01 5.73510349e-01
-5.65476567e-02 8.67962837e-01 8.29656243e-01 -1.00625408e+00
-1.12041259e+00 -7.58254170e-01 1.54035604e+00 -6.42371595e-01
1.42200017e+00 -6.49740815e-01 -5.84978044e-01 6.14425898e-01
3.28064889e-01 -8.74355912e-01 1.15554547e+00 7.03294337e-01
-6.33467853e-01 6.89723194e-01 -1.33063960e+00 9.26357687e-01
1.04495025e+00 -7.35049784e-01 -5.24582148e-01 8.01482379e-01
3.63834769e-01 1.31805852e-01 -4.97876376e-01 -4.27409738e-01
3.92232507e-01 -6.26240313e-01 5.66723704e-01 -8.97762895e-01
4.31910694e-01 1.79919764e-01 3.52317572e-01 -8.26392293e-01
-5.75016797e-01 -1.24882340e+00 8.79942626e-02 1.30247474e+00
4.11091805e-01 -1.08815706e+00 7.40040302e-01 8.21212828e-01
7.78330982e-01 -8.41256157e-02 -7.54692733e-01 1.84363753e-01
-1.47474274e-01 -2.74519950e-01 1.57612175e-01 1.52884448e+00
7.41531491e-01 9.12187934e-01 -5.57305396e-01 5.29673584e-02
7.01872826e-01 -4.87766787e-02 8.08492243e-01 -1.36252356e+00
-2.83645634e-02 -4.64165181e-01 -1.11364983e-01 -6.41594112e-01
2.46462375e-02 -7.17374802e-01 -6.98192179e-01 -1.29346776e+00
2.34046534e-01 -2.78319865e-01 4.98457074e-01 1.80317506e-01
1.36459738e-01 2.19509929e-01 -2.82495469e-02 2.98899472e-01
-5.93066037e-01 -7.88724869e-02 1.09790242e+00 -4.52328660e-02
-5.82977533e-01 1.71787113e-01 -1.47440445e+00 1.02425885e+00
1.08701634e+00 -5.07007182e-01 3.82016152e-02 -1.78009924e-02
9.70350206e-01 -4.55423564e-01 3.11528623e-01 -1.86862096e-01
2.40082383e-01 -3.93084645e-01 -1.44430473e-01 -1.97046995e-01
-5.46736531e-02 -1.50150478e-01 -1.58282131e-01 7.73089945e-01
-6.59184992e-01 -3.41390938e-01 -1.99240938e-01 7.32704818e-01
1.91863328e-01 -2.64791436e-02 5.86911857e-01 -2.42450118e-01
2.87403334e-02 -7.11941496e-02 -1.15036309e+00 3.02370846e-01
7.30036020e-01 1.85371295e-01 -9.51480687e-01 -8.46612155e-01
-6.87241852e-01 4.09576949e-03 1.87925413e-01 4.33973610e-01
3.94053124e-02 -8.36288929e-01 -1.10859275e+00 -1.94439277e-01
-2.77917922e-01 -7.24901378e-01 -1.17516100e-01 7.01516926e-01
-2.14295834e-01 9.75578353e-02 5.24860844e-02 1.11887762e-02
-1.44817400e+00 2.07258791e-01 1.35439098e-01 -2.42523372e-01
-5.91504872e-01 4.04910833e-01 -2.60197431e-01 -7.46886879e-02
-2.54617095e-01 4.71225709e-01 -6.80062950e-01 4.37146872e-01
1.01522148e+00 8.12750876e-01 -5.11498034e-01 -7.36544967e-01
-3.47374022e-01 -2.47177348e-01 -2.87464231e-01 -4.73167002e-02
1.02932811e+00 -2.12890029e-01 -9.86872852e-01 8.87067467e-02
9.00925517e-01 9.53046978e-01 -2.75458425e-01 -3.37447375e-01
7.50946552e-02 -6.56677306e-01 -1.49686979e-02 -5.11554182e-01
-6.28427625e-01 1.48599952e-01 -3.50191146e-01 1.14177823e+00
1.01132048e-02 2.84111321e-01 6.21497929e-01 7.56684989e-02
6.52636737e-02 -1.07433248e+00 -1.38344476e-02 5.91970980e-01
7.15911865e-01 -6.90665066e-01 3.76817137e-01 -1.13977027e+00
-2.51315475e-01 8.51567209e-01 -1.35811819e-02 -7.52243102e-02
1.02268147e+00 -1.55997083e-01 1.48552224e-01 -5.86906493e-01
-4.57075030e-01 1.87340468e-01 7.47934058e-02 3.55399370e-01
4.25906271e-01 3.95621270e-01 -9.50217962e-01 7.63383359e-02
-1.41447648e-01 -4.39191133e-01 7.78531909e-01 7.34330475e-01
-8.95770848e-01 -1.02462614e+00 -4.73809481e-01 5.94525695e-01
-9.54672396e-01 -2.25061208e-01 -1.36498058e+00 3.81030947e-01
-2.44124159e-01 1.43371856e+00 -1.63279384e-01 -1.73705444e-01
-2.33971074e-01 -8.05829242e-02 -1.83130622e-01 -7.79509842e-01
-1.10213292e+00 -1.53035536e-01 1.16421139e+00 -1.23344108e-01
-5.77883899e-01 -8.65307808e-01 -6.49108410e-01 -1.18223822e+00
-2.73119181e-01 4.21583831e-01 5.21349311e-01 1.04969025e+00
5.88563442e-01 -1.71572432e-01 6.15789235e-01 -2.96474844e-01
-4.23353016e-01 -8.32160950e-01 -3.30037445e-01 2.04901814e-01
1.26893237e-01 -5.13677523e-02 -6.60128593e-01 -4.41940844e-01] | [8.545976638793945, 10.24406909942627] |
b6096d42-729c-4d62-a0ba-d2a832ed8761 | tensoir-tensorial-inverse-rendering | 2304.12461 | null | https://arxiv.org/abs/2304.12461v1 | https://arxiv.org/pdf/2304.12461v1.pdf | TensoIR: Tensorial Inverse Rendering | We propose TensoIR, a novel inverse rendering approach based on tensor factorization and neural fields. Unlike previous works that use purely MLP-based neural fields, thus suffering from low capacity and high computation costs, we extend TensoRF, a state-of-the-art approach for radiance field modeling, to estimate scene geometry, surface reflectance, and environment illumination from multi-view images captured under unknown lighting conditions. Our approach jointly achieves radiance field reconstruction and physically-based model estimation, leading to photo-realistic novel view synthesis and relighting results. Benefiting from the efficiency and extensibility of the TensoRF-based representation, our method can accurately model secondary shading effects (like shadows and indirect lighting) and generally support input images captured under single or multiple unknown lighting conditions. The low-rank tensor representation allows us to not only achieve fast and compact reconstruction but also better exploit shared information under an arbitrary number of capturing lighting conditions. We demonstrate the superiority of our method to baseline methods qualitatively and quantitatively on various challenging synthetic and real-world scenes. | ['Hao Su', 'Zexiang Xu', 'Xiaowei Zhou', 'Sai Bi', 'Songfang Han', 'Xiaoshuai Zhang', 'Peijia Xu', 'Isabella Liu', 'Haian Jin'] | 2023-04-24 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Jin_TensoIR_Tensorial_Inverse_Rendering_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Jin_TensoIR_Tensorial_Inverse_Rendering_CVPR_2023_paper.pdf | cvpr-2023-1 | ['novel-view-synthesis', 'inverse-rendering'] | ['computer-vision', 'computer-vision'] | [ 2.99837649e-01 -6.75125182e-01 4.29701030e-01 -3.72968286e-01
-4.80031073e-01 -7.57039964e-01 5.36750615e-01 -4.23950583e-01
1.91600561e-01 6.00196421e-01 3.98313075e-01 -2.30364054e-01
-6.46287948e-02 -9.31966007e-01 -8.20687592e-01 -6.60925090e-01
2.19578505e-01 5.37438020e-02 -3.18170965e-01 -1.39293239e-01
1.24904975e-01 9.19735193e-01 -1.86611867e+00 3.66561890e-01
7.69551039e-01 1.15454626e+00 3.25243920e-01 9.30974841e-01
3.94340120e-02 1.02375603e+00 -2.20947534e-01 -1.91416189e-01
3.68622333e-01 2.78394580e-01 -6.14780545e-01 2.42135048e-01
1.00072646e+00 -8.73927891e-01 -5.85613251e-01 6.73506618e-01
3.87068123e-01 3.62624735e-01 3.68850052e-01 -8.29333782e-01
-7.65976012e-01 -1.98915437e-01 -5.53743720e-01 -3.60869348e-01
4.96396333e-01 1.25568047e-01 9.41724181e-01 -1.06533837e+00
3.60945106e-01 1.25527763e+00 6.95655048e-01 3.96356098e-02
-1.42074370e+00 -3.98802161e-01 2.61669308e-01 9.20579657e-02
-1.28644466e+00 -4.93320942e-01 9.32598293e-01 -3.65448415e-01
9.69156682e-01 6.65140927e-01 7.09720075e-01 9.58825350e-01
-5.80370463e-02 5.15455484e-01 1.35086620e+00 -2.26374105e-01
6.08908795e-02 -1.92921847e-01 -3.02893281e-01 8.52442086e-01
-2.90366977e-01 2.31688917e-01 -6.24206305e-01 -4.31963116e-01
1.12795079e+00 2.18337908e-01 -8.27314615e-01 -1.84531629e-01
-1.52788997e+00 5.30884862e-01 6.77647710e-01 -2.81270802e-01
-3.84684026e-01 5.23020267e-01 8.29365179e-02 -1.40785038e-01
6.65402889e-01 1.38024122e-01 -5.52885890e-01 1.48449734e-01
-6.22757971e-01 9.18785781e-02 5.87621570e-01 7.10334301e-01
1.12354481e+00 3.10254008e-01 -2.42291726e-02 9.87185180e-01
3.65724444e-01 1.01220334e+00 -1.61765054e-01 -1.44795251e+00
2.31748998e-01 3.19453418e-01 4.66628969e-01 -1.27673829e+00
-2.88901359e-01 -5.08008003e-01 -1.04836178e+00 2.51423001e-01
2.99861245e-02 8.70704576e-02 -7.95572281e-01 1.59662986e+00
4.21826243e-01 4.11664873e-01 -1.39055997e-01 1.07778585e+00
9.36131716e-01 7.89661705e-01 -4.78456378e-01 -1.93341393e-02
1.24418545e+00 -1.00661874e+00 -4.98795837e-01 -7.28092790e-02
2.32929572e-01 -1.06880784e+00 1.13417637e+00 6.33242309e-01
-9.21981931e-01 -4.93187129e-01 -8.30176473e-01 -5.26804328e-01
-3.46675212e-03 4.36493933e-01 1.24014640e+00 3.38605344e-01
-1.17530775e+00 5.67487836e-01 -8.02509725e-01 -1.47321103e-02
2.64850825e-01 7.16728419e-02 -2.99636245e-01 -5.39801776e-01
-6.24656141e-01 4.24817115e-01 -4.31595922e-01 4.92059380e-01
-9.27104414e-01 -9.22559142e-01 -7.94847786e-01 1.13970324e-01
1.86137810e-01 -1.10800111e+00 9.28430617e-01 -7.23535836e-01
-1.71011293e+00 2.31088623e-01 -4.09191281e-01 2.91018784e-01
2.25212127e-01 -3.44705641e-01 -1.13352671e-01 1.88989699e-01
-1.36418805e-01 3.34304392e-01 7.21022606e-01 -1.70046020e+00
-3.16541903e-02 -3.52506578e-01 4.42859143e-01 4.98249680e-01
-2.19359636e-01 -3.18508238e-01 -4.50661242e-01 -4.38625932e-01
3.81338596e-01 -7.18694270e-01 -3.18077058e-01 5.97025454e-01
-4.94910002e-01 4.96970803e-01 7.43909240e-01 -7.44351625e-01
5.60269594e-01 -1.90663850e+00 7.88899660e-02 1.14400210e-02
3.79382998e-01 -6.13859557e-02 -2.17875928e-01 4.95066464e-01
4.75671794e-03 -2.10484266e-01 -8.55539739e-02 -6.00393891e-01
-1.79102868e-01 3.97435337e-01 -6.73152745e-01 4.93527919e-01
-1.82535365e-01 6.47572577e-01 -9.26234841e-01 -2.10001543e-02
7.68608689e-01 1.22036874e+00 -6.94174826e-01 3.72842640e-01
-2.93476582e-01 8.03875268e-01 -4.30019170e-01 6.58656061e-01
1.03431571e+00 -4.42285061e-01 -3.92462732e-03 -8.25346589e-01
-1.08367793e-01 1.77728966e-01 -1.27356386e+00 1.91303468e+00
-1.22678936e+00 6.86715901e-01 2.46021822e-01 -3.93112183e-01
7.87887216e-01 2.00683847e-01 5.02745450e-01 -6.08671606e-01
-1.86199509e-02 3.02223451e-02 -7.56926656e-01 -3.20301026e-01
7.49457300e-01 -5.49591780e-02 5.27864218e-01 5.28884292e-01
-2.49679998e-01 -2.95840681e-01 -3.56257021e-01 1.50470346e-01
8.61098051e-01 8.28378737e-01 -9.11717117e-02 -1.43626213e-01
4.94762361e-01 -5.20862758e-01 4.28582966e-01 3.83434445e-01
5.05106866e-01 9.11237955e-01 -8.98799300e-02 -7.58546293e-01
-7.86410749e-01 -1.11854649e+00 -9.61325392e-02 1.02837062e+00
9.32228565e-02 -2.75087178e-01 -3.90953183e-01 -7.93308541e-02
-3.66908088e-02 6.32177889e-01 -5.04347742e-01 4.40719604e-01
-5.35039842e-01 -8.05655479e-01 1.21914938e-01 3.33601058e-01
5.63684225e-01 -4.93786544e-01 -5.19417584e-01 -4.42400277e-02
-6.75962925e-01 -1.44853294e+00 -1.95145980e-01 -1.43045619e-01
-7.10972905e-01 -8.92391562e-01 -5.79715133e-01 -1.15984544e-01
7.57000446e-01 8.62013042e-01 1.54579329e+00 2.16757327e-01
-3.77020895e-01 6.02127194e-01 5.91382496e-02 2.66775656e-02
-2.86509600e-02 -6.40441597e-01 -1.84227675e-01 4.18516219e-01
-4.23392475e-01 -1.01088929e+00 -1.00136626e+00 4.68569905e-01
-1.01159573e+00 6.41530812e-01 7.02080056e-02 7.32791781e-01
6.69510126e-01 -1.44020170e-01 -2.49987468e-01 -7.10309505e-01
-4.07074988e-02 -1.37565494e-01 -9.08442557e-01 3.17000061e-01
-2.28962362e-01 -1.15359291e-01 8.84054482e-01 -2.03585267e-01
-1.54042208e+00 -3.15384194e-02 -1.00125812e-01 -6.74935997e-01
-1.66526943e-01 1.33869573e-01 -1.32868245e-01 -6.01879239e-01
6.10568047e-01 2.40549564e-01 -5.56883097e-01 -6.72874570e-01
5.57828367e-01 3.46326798e-01 5.90647757e-01 -7.80138910e-01
8.16372633e-01 1.20778596e+00 3.24292511e-01 -9.67769921e-01
-9.81005013e-01 -2.61966288e-01 -4.93141502e-01 -4.16325599e-01
5.20921290e-01 -1.24472070e+00 -1.12438142e+00 6.10915661e-01
-1.39756095e+00 -3.53707254e-01 -1.19775258e-01 3.97352308e-01
-5.17850280e-01 4.93037730e-01 -5.94055235e-01 -9.28544998e-01
-2.01343104e-01 -1.15167153e+00 1.57706940e+00 -4.69770133e-02
4.49203551e-01 -1.03160608e+00 1.01763075e-02 6.31484509e-01
4.30494905e-01 5.03814995e-01 8.39914978e-01 9.16175663e-01
-1.25493193e+00 3.33794773e-01 -7.00108051e-01 3.92089695e-01
2.23706469e-01 1.16022952e-01 -1.56523919e+00 -3.32389683e-01
3.63764726e-02 -3.21208030e-01 7.33243406e-01 3.23847920e-01
1.46141744e+00 -2.53262520e-01 -2.24550851e-02 1.40127659e+00
2.00666571e+00 -3.69161665e-01 7.25754559e-01 -8.88863876e-02
1.35895979e+00 6.45787835e-01 2.09166214e-01 6.57619834e-01
7.50744700e-01 6.56403959e-01 8.48560870e-01 -6.38886511e-01
-3.74324322e-01 -1.44118145e-01 7.98219666e-02 9.38776195e-01
-2.84668833e-01 -5.24012506e-01 -5.83325326e-01 4.36883241e-01
-1.57570124e+00 -6.02747262e-01 -3.88527870e-01 2.25786495e+00
3.85357469e-01 -5.80307066e-01 -4.78841573e-01 -9.77677032e-02
1.66148886e-01 5.23059070e-01 -4.69309807e-01 -2.52458811e-01
-3.25960696e-01 1.14648633e-01 5.93657136e-01 6.77217305e-01
-6.19411767e-01 6.29224896e-01 6.29803419e+00 3.98977548e-01
-1.36358333e+00 1.17475865e-02 6.27507865e-01 -1.80468693e-01
-1.06927299e+00 4.18220647e-02 -3.00898105e-01 -4.73791137e-02
5.66216409e-01 6.78323925e-01 1.18457687e+00 4.63562667e-01
2.77966887e-01 -1.97022811e-01 -8.85829270e-01 1.15062559e+00
1.18743248e-01 -1.42572188e+00 1.14231415e-01 8.96413103e-02
8.85977745e-01 4.43454713e-01 8.28119181e-03 -2.75099814e-01
4.63048518e-01 -9.49982285e-01 6.91652417e-01 9.04104233e-01
1.11159170e+00 -4.97160941e-01 2.15023965e-01 1.60388067e-01
-1.13297248e+00 1.10948503e-01 -4.88681525e-01 -1.90782696e-01
3.78392458e-01 9.99688506e-01 -3.41835916e-01 9.09126937e-01
7.86956668e-01 7.95815647e-01 -2.57755548e-01 5.71056902e-01
-2.27905095e-01 4.89168704e-01 -5.98314106e-01 3.87769312e-01
-1.28434412e-02 -4.88539428e-01 4.53410685e-01 8.41950178e-01
3.58433098e-01 9.21710357e-02 2.64776289e-01 8.95262659e-01
3.52356508e-02 3.75558436e-02 -5.87503910e-01 3.42039734e-01
6.92522004e-02 1.55006540e+00 -4.26002890e-01 -1.26494974e-01
-5.20789623e-01 1.07802367e+00 3.49595398e-01 9.82985675e-01
-6.86350942e-01 5.80401234e-02 8.03949177e-01 8.28866363e-02
3.68386388e-01 -5.09149134e-01 -3.56342942e-01 -1.57761180e+00
1.78062096e-01 -5.84441245e-01 -4.17961091e-01 -1.41745579e+00
-1.17946887e+00 6.75136924e-01 -8.10502842e-02 -1.19393981e+00
5.74989170e-02 -8.61548781e-01 -3.87037128e-01 1.10204029e+00
-2.06156635e+00 -1.74413347e+00 -8.44499528e-01 6.59499466e-01
1.17509723e-01 3.40425581e-01 1.08140182e+00 3.60622793e-01
-3.25501949e-01 -7.97880888e-02 4.88787681e-01 -2.08733216e-01
5.29896557e-01 -1.17785490e+00 4.72768724e-01 7.87920117e-01
2.20848083e-01 5.91279984e-01 5.25620997e-01 -2.11779565e-01
-1.80475795e+00 -1.14615822e+00 3.30012470e-01 -3.96767855e-01
3.89947921e-01 -6.03437960e-01 -6.83972478e-01 5.91436028e-01
6.91250339e-02 4.84788835e-01 7.65280843e-01 1.12344168e-01
-7.53266752e-01 -3.37285489e-01 -1.06954336e+00 6.64583862e-01
1.13267171e+00 -7.44641364e-01 2.12934241e-01 6.74276590e-01
5.65880716e-01 -6.26597881e-01 -9.26241100e-01 3.80687505e-01
7.73973942e-01 -1.54416168e+00 1.31556237e+00 -2.42132116e-02
5.82426250e-01 -5.28848588e-01 -7.80209303e-01 -1.26974714e+00
-4.09396619e-01 -7.16880381e-01 -1.33632541e-01 1.02834868e+00
-8.70266557e-02 -7.83310533e-01 4.76698101e-01 4.02659446e-01
-1.48595765e-01 -6.95297956e-01 -5.49363196e-01 -2.69089788e-01
-3.08260411e-01 -6.88223422e-01 9.82243240e-01 7.38825321e-01
-9.78769481e-01 2.75380343e-01 -6.34591162e-01 5.89060307e-01
9.00542378e-01 6.35321259e-01 8.79039288e-01 -1.07897437e+00
-7.20072627e-01 1.36640325e-01 1.23953164e-01 -1.38618982e+00
9.99038219e-02 -5.46220303e-01 1.19221009e-01 -1.62161779e+00
7.37861246e-02 -6.17017865e-01 -8.50899369e-02 3.40924621e-01
8.08105618e-03 8.36969554e-01 3.24005969e-02 2.39122003e-01
-2.13713914e-01 7.83902586e-01 1.55294240e+00 7.04601333e-02
1.42362878e-01 -3.20384353e-01 -5.73523819e-01 8.91365886e-01
2.58391917e-01 -5.31105064e-02 -6.17585242e-01 -1.22680938e+00
6.83243036e-01 3.17632616e-01 7.32392192e-01 -6.74090445e-01
-2.18922973e-01 -3.90403152e-01 6.11933768e-01 -6.56501889e-01
9.34645534e-01 -8.33208799e-01 5.14599323e-01 -1.75298572e-01
7.39176199e-02 -9.77592990e-02 1.82760254e-01 6.26923084e-01
9.12672207e-02 1.91856280e-01 5.50727427e-01 -2.47812614e-01
-4.44913119e-01 5.11028230e-01 7.95582682e-02 -3.98535609e-01
3.85838956e-01 -1.36094302e-01 -4.40831006e-01 -5.89595556e-01
-2.03167751e-01 -9.65063944e-02 8.17411304e-01 5.92654832e-02
6.34243369e-01 -1.31446397e+00 -7.23200321e-01 4.50768113e-01
1.52807385e-01 2.36752078e-01 6.42295897e-01 5.23864090e-01
-8.52642536e-01 1.05800927e-02 4.51024584e-02 -7.86474228e-01
-1.05710876e+00 2.67272562e-01 3.70000839e-01 -1.80441275e-01
-7.84819186e-01 8.45907748e-01 8.26560557e-01 -8.45134914e-01
-1.86913431e-01 -3.77094120e-01 9.48793441e-02 -5.05107701e-01
5.39157391e-01 4.30096775e-01 2.76517123e-01 -8.69926751e-01
-9.17535648e-02 9.55080032e-01 5.16809881e-01 -8.18297192e-02
1.46992540e+00 -3.53297681e-01 -3.45886648e-01 3.14756572e-01
1.28272045e+00 2.61787921e-01 -1.52303720e+00 -3.71195167e-01
-1.00718164e+00 -1.10243285e+00 7.92036891e-01 -9.69255626e-01
-1.29588616e+00 1.14298999e+00 4.74164039e-01 -2.05518380e-01
1.38453925e+00 -5.54645538e-01 9.48186815e-01 3.81161183e-01
6.29732490e-01 -5.06975234e-01 -5.40908799e-02 3.78389299e-01
1.11774445e+00 -1.05231154e+00 4.10115153e-01 -8.18744659e-01
-2.14865640e-01 1.13459146e+00 1.57106325e-01 -4.02708501e-02
5.33871353e-01 3.77277285e-01 2.34531164e-01 -1.26241282e-01
-7.34793723e-01 1.46078929e-01 4.73009855e-01 7.18456864e-01
3.84456724e-01 1.26076728e-01 7.14119971e-01 -3.38351458e-01
-1.67211294e-01 -7.68556893e-02 5.33453524e-01 5.47784150e-01
1.72098771e-01 -8.21976483e-01 -5.76831520e-01 3.61060619e-01
-1.77131146e-01 -2.91341454e-01 7.32404292e-02 2.66280025e-01
1.13853313e-01 9.04438317e-01 3.01215500e-02 -2.70774603e-01
9.85537395e-02 -5.98712385e-01 6.95633769e-01 -3.54426503e-01
-4.55930769e-01 3.06294769e-01 9.93075147e-02 -9.79954183e-01
-6.67243183e-01 -4.45745468e-01 -8.14287364e-01 -3.91749144e-01
-4.94759202e-01 -4.21456397e-01 1.02650464e+00 7.02370703e-01
4.18076575e-01 5.65232754e-01 9.22333598e-01 -1.31900215e+00
-1.44594878e-01 -6.83953285e-01 -5.71184993e-01 2.01773986e-01
7.71135628e-01 -8.11487377e-01 -3.39144975e-01 3.49991303e-03] | [9.68392562866211, -3.088932991027832] |
8766a63d-0cd6-4b81-a260-a89f2e68f820 | iris-recognition-with-image-segmentation | 1901.01028 | null | http://arxiv.org/abs/1901.01028v1 | http://arxiv.org/pdf/1901.01028v1.pdf | Iris Recognition with Image Segmentation Employing Retrained Off-the-Shelf Deep Neural Networks | This paper offers three new, open-source, deep learning-based iris
segmentation methods, and the methodology how to use irregular segmentation
masks in a conventional Gabor-wavelet-based iris recognition. To train and
validate the methods, we used a wide spectrum of iris images acquired by
different teams and different sensors and offered publicly, including data
taken from CASIA-Iris-Interval-v4, BioSec, ND-Iris-0405, UBIRIS,
Warsaw-BioBase-Post-Mortem-Iris v2.0 (post-mortem iris images), and
ND-TWINS-2009-2010 (iris images acquired from identical twins). This varied
training data should increase the generalization capabilities of the proposed
segmentation techniques. In database-disjoint training and testing, we show
that deep learning-based segmentation outperforms the conventional (OSIRIS)
segmentation in terms of Intersection over Union calculated between the
obtained results and manually annotated ground-truth. Interestingly, the
Gabor-based iris matching is not always better when deep learning-based
segmentation is used, and is on par with the method employing Daugman's based
segmentation. | ['Kevin Bowyer', 'Mateusz Trokielewicz', 'Daniel Kerrigan', 'Adam Czajka'] | 2019-01-04 | null | null | null | null | ['iris-segmentation'] | ['medical'] | [-1.26071677e-01 -8.05828422e-02 -1.40092611e-01 -3.78523737e-01
-7.13536501e-01 -3.59817564e-01 3.18233609e-01 2.02836290e-01
-4.74873781e-01 4.99752820e-01 -1.43632501e-01 -1.01174712e-01
-8.12611639e-01 -8.16100836e-01 -1.98005617e-01 -9.93958056e-01
-2.95377463e-01 7.87858427e-01 -1.36542916e-01 -1.14825889e-02
2.36423776e-01 7.55111754e-01 -1.83436692e+00 4.18687984e-02
9.89759088e-01 9.78192568e-01 -5.55432379e-01 8.52690220e-01
1.51775107e-01 -8.54209997e-03 -5.92892349e-01 -6.37237310e-01
7.05889165e-01 -5.59369385e-01 -8.57990086e-01 1.81733802e-01
9.79833305e-01 -1.55360013e-01 6.52436912e-03 1.02412987e+00
8.30798686e-01 -1.64662804e-02 3.83051515e-01 -4.49376285e-01
-5.41761875e-01 1.84834138e-01 -8.99714708e-01 2.08989963e-01
2.54306763e-01 4.66755658e-01 4.62025940e-01 6.75124824e-02
6.83435678e-01 9.24267709e-01 1.26412940e+00 4.46592927e-01
-1.25602794e+00 -2.25880980e-01 -9.09897983e-01 -1.56787440e-01
-1.49591517e+00 -3.41283649e-01 2.36145817e-02 -6.43296242e-01
6.61327481e-01 7.08794355e-01 8.31118226e-01 5.99649847e-01
-1.24836981e-01 3.39914292e-01 1.85042953e+00 -6.26115918e-01
-1.61790788e-01 -1.42000899e-01 1.45321473e-01 8.24826658e-01
2.65689701e-01 9.45949137e-01 -2.46062368e-01 -1.97323084e-01
9.21378016e-01 -2.24576414e-01 -1.92703828e-02 2.75498539e-01
-9.30577278e-01 5.22896290e-01 2.51034826e-01 6.98556066e-01
-3.98587257e-01 -4.69899952e-01 4.09860164e-01 5.35102487e-01
7.78873563e-01 4.49598640e-01 -3.90935630e-01 -1.41746864e-01
-1.60358894e+00 1.00583114e-01 4.98635054e-01 2.78053284e-01
6.73729300e-01 -1.40239134e-01 -3.92179877e-01 7.87345409e-01
2.49681443e-01 3.98476601e-01 5.56434512e-01 -4.99402702e-01
-4.03316140e-01 6.98005974e-01 -3.86481248e-02 -9.34296787e-01
-9.02047098e-01 -7.95637369e-01 -8.55625212e-01 2.00776562e-01
9.17069554e-01 -3.37809831e-01 -1.49644423e+00 9.39423382e-01
5.12211204e-01 4.80529398e-01 -1.93513315e-02 1.20302105e+00
1.28345549e+00 -2.17596412e-01 -3.33930165e-01 -1.70707971e-01
1.23688817e+00 -4.72879529e-01 -4.58198458e-01 4.72943902e-01
5.30342102e-01 -1.11726415e+00 5.87581277e-01 6.93668902e-01
-8.27717423e-01 -7.28619456e-01 -6.75558865e-01 1.38701126e-01
-5.74898303e-01 5.88149846e-01 7.44693100e-01 1.14070058e+00
-1.02452064e+00 8.08253169e-01 -7.75515616e-01 -8.23934436e-01
4.37511057e-01 7.16053903e-01 -3.37144077e-01 3.41323465e-01
-7.92309463e-01 5.91528714e-01 2.57617533e-01 9.80216861e-02
-2.38518901e-02 -5.07045865e-01 -6.52017951e-01 -4.76626188e-01
-1.95076093e-01 -4.78665888e-01 6.58998966e-01 -9.46251631e-01
-1.51389146e+00 1.76323640e+00 4.88154218e-02 -8.70975614e-01
5.15544236e-01 3.71542782e-01 -5.52916765e-01 1.69801131e-01
-2.44983852e-01 4.91479486e-01 8.04174542e-01 -8.12540412e-01
-6.64608359e-01 -7.99846292e-01 -1.97137490e-01 -4.27777231e-01
2.65125513e-01 2.70673424e-01 -3.16678524e-01 -5.69576025e-01
1.53999329e-01 -7.61006296e-01 -7.69344643e-02 -4.25430030e-01
-5.82177997e-01 -3.33663762e-01 3.06087770e-02 -1.03783977e+00
9.94600892e-01 -1.96676755e+00 -1.39554337e-01 6.50618732e-01
2.16084242e-01 7.35190630e-01 -2.46236861e-01 1.27379671e-01
-3.43690366e-01 -5.07796332e-02 -1.73457816e-01 -4.07456040e-01
-2.05330193e-01 2.77297080e-01 2.46442094e-01 9.64090049e-01
-1.71781793e-01 5.79157889e-01 -4.55139965e-01 -5.48581004e-01
4.29532975e-01 3.42617005e-01 -6.58941194e-02 -5.79827391e-02
1.10541359e-01 6.63360178e-01 7.62624294e-02 1.10313106e+00
1.14703870e+00 5.86023703e-02 -3.78319383e-01 -6.62612244e-02
-4.67755556e-01 -3.90363038e-01 -1.19206178e+00 1.72809350e+00
-8.11450705e-02 6.91209733e-01 4.15315405e-02 -1.30022335e+00
1.13698804e+00 3.81570727e-01 6.09846532e-01 -7.01117992e-01
2.91865230e-01 3.03306311e-01 1.85432702e-01 -8.35479498e-01
9.43935588e-02 -4.38686460e-02 6.55528963e-01 2.93151259e-01
3.72695714e-01 -7.20636360e-03 4.09255981e-01 -7.56638646e-01
5.29926360e-01 8.09131786e-02 5.63828684e-02 -2.58881330e-01
5.78361452e-01 2.50149190e-01 6.54809833e-01 7.36333251e-01
-2.59766132e-01 7.84466207e-01 5.07734239e-01 -8.84028792e-01
-8.55761647e-01 -5.58455586e-01 -1.35152268e+00 4.63049322e-01
-3.38902265e-01 6.24470375e-02 -1.09929371e+00 -3.23665291e-01
2.62915760e-01 -1.89132825e-01 -9.39807296e-01 6.29144847e-01
-3.83441225e-02 -1.34271395e+00 1.02490640e+00 -2.97401518e-01
5.69951236e-01 -6.71187818e-01 -3.96544099e-01 -2.63859164e-02
2.98755139e-01 -6.80965662e-01 -3.78636606e-02 -4.21394765e-01
-8.07964504e-01 -1.61834180e+00 -9.50751245e-01 -4.98500705e-01
6.35558724e-01 -7.10333288e-01 9.84734237e-01 4.57120746e-01
-1.12815428e+00 2.63621986e-01 -1.40770555e-01 -3.97134662e-01
-2.18296200e-01 -1.34466410e-01 9.72472057e-02 4.76223081e-01
1.05677569e+00 -2.10579872e-01 -4.88158256e-01 2.36051649e-01
-6.29541099e-01 -3.87266934e-01 4.67547417e-01 1.13349509e+00
7.66173005e-01 4.12876643e-02 1.00785144e-01 -6.33866489e-01
3.36548597e-01 7.37669468e-02 -1.20662022e+00 3.07818472e-01
-7.79287338e-01 -3.63129646e-01 -1.18764341e-02 -1.44129157e-01
-5.02274930e-01 -8.29427913e-02 -4.61568475e-01 -2.44966492e-01
-8.00367653e-01 5.01014173e-01 7.25307345e-01 -8.40594292e-01
1.05719531e+00 5.82405850e-02 3.77795458e-01 -8.40707958e-01
-1.93727165e-02 1.02041471e+00 8.34964514e-01 -4.75551665e-01
3.80989492e-01 5.71057022e-01 3.44881475e-01 -9.98973966e-01
-4.90388364e-01 -6.91646457e-01 -7.73926318e-01 -1.85654387e-02
9.94304597e-01 -5.65089703e-01 -9.20855701e-01 1.09920645e+00
-9.18935359e-01 -8.51361826e-02 -5.76741934e-01 6.60425425e-01
-5.16903639e-01 3.70109528e-01 -7.27608621e-01 -7.95282722e-01
-5.59943020e-01 -1.37157309e+00 1.03332853e+00 7.86113620e-01
1.15503207e-01 -1.04100287e+00 5.48263073e-01 6.99573100e-01
3.97473812e-01 9.44392443e-01 4.60787773e-01 -8.27749014e-01
-1.37550220e-01 -4.77486223e-01 -4.53525960e-01 4.20245737e-01
2.18853086e-01 5.94724774e-01 -1.19472587e+00 -2.15186343e-01
-1.99905083e-01 -6.09599426e-02 8.20348978e-01 8.70205283e-01
1.14793348e+00 7.62783410e-03 -3.96756493e-02 1.23777688e+00
1.62138724e+00 2.52512664e-01 8.72417867e-01 4.62383777e-01
-8.38311017e-03 7.69574463e-01 2.74269462e-01 3.49205703e-01
-2.44113021e-02 6.49254560e-01 9.78513435e-02 -8.54078710e-01
-2.24134475e-01 4.87783551e-01 -6.89827383e-01 9.78114009e-02
-9.51954305e-01 3.22382152e-01 -1.14786601e+00 8.52585495e-01
-1.52886820e+00 -9.15523112e-01 -3.88871998e-01 2.56282067e+00
1.06880260e+00 -1.81607366e-01 5.14033079e-01 1.62980482e-01
5.25001943e-01 -3.01635832e-01 -3.20135921e-01 -5.30354917e-01
-4.34813857e-01 1.15686381e+00 7.09151268e-01 5.15592217e-01
-1.33800519e+00 6.93552136e-01 6.45966816e+00 9.53427017e-01
-1.35450566e+00 1.57009214e-01 6.70846641e-01 -1.15662396e-01
4.34097916e-01 -3.00518095e-01 -5.26085556e-01 3.34866405e-01
1.07648885e+00 2.10103244e-01 4.84775305e-01 1.71341106e-01
1.94574192e-01 -4.28798735e-01 -5.88447213e-01 1.01538563e+00
-2.00206012e-01 -1.61704803e+00 -7.12352157e-01 3.68818998e-01
7.85449147e-01 2.85923243e-01 2.61397749e-01 -3.15937757e-01
-1.83181897e-01 -1.33269382e+00 -3.67452741e-01 9.58704889e-01
1.17271280e+00 -7.13165700e-01 1.15772831e+00 -1.83268160e-01
-5.49501419e-01 2.16107532e-01 -2.89479434e-01 1.49717420e-01
-5.73541760e-01 9.53884482e-01 -4.81714875e-01 9.84930813e-01
7.85992980e-01 5.79599023e-01 -7.13546932e-01 1.54226553e+00
2.70147532e-01 6.12719774e-01 -4.26790833e-01 4.38475907e-01
2.79703051e-01 -7.07533956e-01 6.05101526e-01 1.18837047e+00
2.16518506e-01 1.15135014e-02 -2.54595101e-01 9.50982451e-01
3.27535510e-01 1.80258214e-01 -3.46459925e-01 -1.48824245e-01
-3.20568591e-01 1.26290429e+00 -6.02742255e-01 -2.74617255e-01
-4.76759315e-01 4.62466955e-01 -4.37906206e-01 3.23806465e-01
-3.30673546e-01 -5.45659006e-01 1.00012112e+00 3.71237010e-01
5.49579076e-02 1.43604368e-01 -3.46694440e-01 -8.68981540e-01
-4.33100820e-01 -1.11197674e+00 3.51054192e-01 -3.74791443e-01
-1.23737025e+00 5.88437438e-01 -1.71008453e-01 -1.19299269e+00
-2.28106529e-01 -8.02022040e-01 -5.62305033e-01 1.43416786e+00
-1.35358942e+00 -1.37699997e+00 -1.40463263e-01 4.96034682e-01
-2.00987443e-01 -6.84468329e-01 9.91184890e-01 5.16397953e-01
-7.69409955e-01 9.45207536e-01 2.57762998e-01 5.20777762e-01
7.50495434e-01 -1.29971302e+00 2.32267886e-01 1.00407112e+00
2.10100845e-01 6.59330308e-01 5.30322433e-01 -5.16618609e-01
-9.87918913e-01 -7.19365239e-01 6.77464604e-01 3.57069336e-02
4.14062768e-01 3.95300359e-01 -6.51198566e-01 3.57778251e-01
3.61594856e-01 2.14866266e-01 1.04915476e+00 3.84723753e-01
2.83216666e-02 -2.05297098e-01 -1.84224689e+00 6.29955381e-02
6.66721463e-01 -4.35728490e-01 -4.39738423e-01 8.76256645e-01
5.35025820e-02 -1.17359507e+00 -1.51107752e+00 5.31158507e-01
6.42479837e-01 -1.52625859e+00 8.95779967e-01 -8.27842951e-01
2.65485533e-02 -2.53965437e-01 2.99933702e-01 -9.93737042e-01
1.93882972e-01 -9.19427454e-01 4.23496783e-01 1.03376257e+00
1.11812547e-01 -1.05757833e+00 9.08337414e-01 3.15306336e-01
1.06071189e-01 -7.42811501e-01 -1.35644531e+00 -7.64659524e-01
7.94004872e-02 -9.13382992e-02 9.15984035e-01 1.13408148e+00
-4.48484778e-01 -7.99365640e-01 8.05906653e-02 3.79768431e-01
8.56951714e-01 4.02063578e-01 8.65328252e-01 -1.58451033e+00
-3.93317223e-01 -6.53681695e-01 -1.06790066e+00 -2.79414117e-01
-2.34102726e-01 -4.86857176e-01 -5.72048962e-01 -1.15175712e+00
-4.65163648e-01 -6.15496457e-01 -1.17491528e-01 7.73728430e-01
3.37682188e-01 6.42815471e-01 -3.41497302e-01 8.10645446e-02
3.43213379e-01 -5.13750374e-01 1.37002206e+00 -3.11031844e-02
-4.02714282e-01 3.91711801e-01 -2.43676051e-01 6.48090720e-01
4.62677598e-01 -1.91654086e-01 3.90274435e-01 -4.32729814e-03
-1.41381070e-01 1.87091112e-01 3.50056767e-01 -1.11542404e+00
3.15942138e-01 3.12186629e-02 3.19837242e-01 -5.59411407e-01
-4.93052192e-02 -4.30005610e-01 2.91143000e-01 5.11844993e-01
4.28715497e-02 -4.70888674e-01 5.50672829e-01 -1.78829312e-01
-4.16915596e-01 -2.94969290e-01 1.10053730e+00 -7.05304816e-02
-3.73959750e-01 4.94078070e-01 1.32746845e-01 -1.44136071e-01
7.92041063e-01 -5.40087283e-01 -5.11494875e-01 2.40417749e-01
-1.10552692e+00 -2.11406350e-02 6.00941837e-01 -4.21272554e-02
2.99534887e-01 -9.09666240e-01 -1.14453077e+00 9.76342380e-01
2.21818238e-01 -3.59292179e-02 3.91161501e-01 1.41371262e+00
-9.27394986e-01 4.54785854e-01 -4.09117401e-01 -9.77118015e-01
-1.52125442e+00 1.80879071e-01 9.57510471e-01 -1.67485356e-01
-4.41724837e-01 1.08160198e+00 -6.34753227e-01 -7.12459445e-01
1.94875285e-01 -4.90388602e-01 -2.65751272e-01 2.92480826e-01
5.15545189e-01 2.91290790e-01 5.69725335e-01 -6.48513436e-01
-6.50438666e-02 1.12054062e+00 1.63127154e-01 3.63896757e-01
1.11295784e+00 2.91793525e-01 -6.88795745e-01 -1.10303588e-01
7.29509175e-01 -5.88964559e-02 -4.24440444e-01 -2.62786537e-01
-6.94291480e-03 -6.98991835e-01 2.89291322e-01 -9.11922991e-01
-1.39241195e+00 6.34348691e-01 1.54143441e+00 4.71659869e-01
1.44258368e+00 -4.35975313e-01 5.63116908e-01 -1.41201332e-01
1.66179627e-01 -1.02610135e+00 -1.05133760e+00 -2.20485926e-02
5.55695534e-01 -1.32581568e+00 1.35978460e-01 -4.32890095e-02
3.77970524e-02 1.32495975e+00 1.37059838e-01 2.23031547e-02
6.38723195e-01 6.75741434e-02 4.55018014e-01 -4.33059692e-01
8.53606686e-02 -9.44198847e-01 9.43557799e-01 9.86479223e-01
5.73521972e-01 2.51776338e-01 -6.15342200e-01 3.06086019e-02
-3.13463271e-01 3.02683681e-01 2.82048345e-01 3.87702376e-01
6.31515235e-02 -1.36810672e+00 -6.47234738e-01 9.17980611e-01
-7.63748884e-01 -2.22252496e-02 -3.39506418e-01 9.64128256e-01
7.83518255e-01 8.45140278e-01 3.66563499e-01 -2.57424861e-01
1.44448891e-01 1.10982489e-02 6.66557729e-01 -3.34440887e-01
-9.92811322e-01 3.43859255e-01 2.20422987e-02 -5.75706780e-01
-1.06927407e+00 -7.03408659e-01 -7.64548182e-01 -6.50100708e-01
-3.30478162e-01 7.21850917e-02 7.54360855e-01 1.03365982e+00
2.93011159e-01 1.92870513e-01 4.18012410e-01 -5.48293293e-01
-2.43244901e-01 -1.06055021e+00 -1.14436448e+00 2.02938095e-01
7.42127419e-01 -5.04510462e-01 -5.44327259e-01 -1.56550284e-03] | [3.74352765083313, -3.631197214126587] |
8c9c6c7b-b788-48da-8f91-166992b99058 | relation-prediction-as-an-auxiliary-training | 2110.02834 | null | https://arxiv.org/abs/2110.02834v1 | https://arxiv.org/pdf/2110.02834v1.pdf | Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representations | Learning good representations on multi-relational graphs is essential to knowledge base completion (KBC). In this paper, we propose a new self-supervised training objective for multi-relational graph representation learning, via simply incorporating relation prediction into the commonly used 1vsAll objective. The new training objective contains not only terms for predicting the subject and object of a given triple, but also a term for predicting the relation type. We analyse how this new objective impacts multi-relational learning in KBC: experiments on a variety of datasets and models show that relation prediction can significantly improve entity ranking, the most widely used evaluation task for KBC, yielding a 6.1% increase in MRR and 9.9% increase in Hits@1 on FB15k-237 as well as a 3.1% increase in MRR and 3.4% in Hits@1 on Aristo-v4. Moreover, we observe that the proposed objective is especially effective on highly multi-relational datasets, i.e. datasets with a large number of predicates, and generates better representations when larger embedding sizes are used. | ['Pontus Stenetorp', 'Sebastian Riedel', 'Pasquale Minervini', 'Yihong Chen'] | 2021-10-06 | null | https://openreview.net/forum?id=Qa3uS3H7-Le | https://openreview.net/pdf?id=Qa3uS3H7-Le | akbc-2021-10 | ['knowledge-base-completion', 'link-property-prediction', 'knowledge-graph-embeddings', 'knowledge-base-completion', 'knowledge-graph-embeddings'] | ['graphs', 'graphs', 'graphs', 'knowledge-base', 'methodology'] | [-1.37951925e-01 4.71746802e-01 -7.14301884e-01 -1.02053843e-01
-8.67633343e-01 -2.57423550e-01 6.67611003e-01 9.31395411e-01
-4.52536821e-01 7.55310893e-01 4.28699642e-01 -1.33399814e-01
-5.01666367e-01 -1.33429074e+00 -1.02664161e+00 -2.24992007e-01
-2.72741467e-01 8.33548903e-01 5.04979789e-01 -5.64400017e-01
-1.59704193e-01 4.35701758e-01 -1.44464135e+00 4.51232821e-01
6.89576268e-01 1.13468909e+00 -1.08217284e-01 2.96060562e-01
-5.47580123e-02 1.19571424e+00 -4.96062994e-01 -8.98432612e-01
-1.25504836e-01 1.93835661e-01 -1.20177841e+00 -5.67978561e-01
1.45761013e-01 3.64022464e-01 -4.76542711e-01 7.21936405e-01
2.80383617e-01 1.76077053e-01 7.84301877e-01 -9.98590827e-01
-6.61680222e-01 1.03092408e+00 -5.32125592e-01 1.88236326e-01
3.70738566e-01 -5.62651813e-01 1.74285877e+00 -7.60561824e-01
8.20923507e-01 1.14112270e+00 4.59986597e-01 1.69069558e-01
-1.09613490e+00 -2.67492503e-01 -2.13915378e-01 6.44012570e-01
-1.55731070e+00 -2.30042338e-01 4.49190974e-01 -1.75236791e-01
1.30539143e+00 4.33559954e-01 2.86276788e-01 6.61739051e-01
-1.16728604e-01 6.01523757e-01 5.96120596e-01 -5.88019013e-01
-8.90645534e-02 3.02302480e-01 3.47916514e-01 6.93325043e-01
7.57136047e-01 -2.35015765e-01 -3.10248256e-01 -3.95184681e-02
2.90407985e-01 -1.79507092e-01 -2.04900354e-01 -2.39804804e-01
-1.02181959e+00 8.85972500e-01 7.61751592e-01 4.18065012e-01
-4.31959480e-01 4.25521642e-01 4.34968263e-01 2.02797160e-01
2.32089743e-01 6.16820633e-01 -4.60971981e-01 -3.64872143e-02
-1.83244348e-01 3.07362735e-01 7.68774748e-01 9.73096848e-01
8.04506660e-01 -2.55376071e-01 -2.06098452e-01 1.02377975e+00
1.15188725e-01 4.52241004e-01 4.17751193e-01 -5.29286861e-01
9.33123231e-01 1.14356446e+00 -1.57276779e-01 -1.33134866e+00
-6.06402874e-01 -6.06549978e-01 -7.76340365e-01 -5.44833601e-01
6.70261830e-02 2.94082791e-01 -5.46428263e-01 1.59914732e+00
3.00370157e-01 -8.88124704e-02 5.07682681e-01 4.05673891e-01
1.22411346e+00 6.77396655e-01 1.01922251e-01 -1.01463400e-01
1.48753762e+00 -7.81637013e-01 -6.18551016e-01 -2.44009584e-01
1.38326466e+00 -4.54241335e-01 7.77559042e-01 -6.16566017e-02
-8.49047899e-01 -4.09119129e-01 -9.95524228e-01 -2.15770602e-01
-7.73127556e-01 2.62776166e-01 9.58652556e-01 4.85806942e-01
-6.84813082e-01 5.59861779e-01 -3.04498702e-01 -1.16009332e-01
2.56345063e-01 3.66671771e-01 -6.23532414e-01 -4.31799680e-01
-1.52449143e+00 1.28769076e+00 9.91359174e-01 -3.36074889e-01
-3.19290847e-01 -6.98493183e-01 -9.75859582e-01 2.96882600e-01
8.50216568e-01 -3.46470773e-01 4.81992364e-01 2.01011412e-02
-8.12275827e-01 7.34768867e-01 5.18899877e-03 -7.79549778e-01
1.49936423e-05 -4.76197451e-01 -9.47910726e-01 1.81037128e-01
1.35085329e-01 4.10990208e-01 1.46685883e-01 -1.31243396e+00
-5.40914416e-01 -3.93992603e-01 4.08059418e-01 2.55169868e-01
-4.50353742e-01 -3.63572538e-01 -6.41288817e-01 -5.47152340e-01
-6.59890547e-02 -8.35987568e-01 -7.18691424e-02 -6.78986490e-01
-4.57030237e-01 -7.28783369e-01 5.45093119e-01 -6.15668535e-01
1.33021009e+00 -1.92003739e+00 3.50460351e-01 5.74119747e-01
3.44963282e-01 3.51855576e-01 -1.48187190e-01 4.75901723e-01
-2.68109888e-01 3.88327777e-01 3.16043407e-01 3.41850407e-02
-1.83470890e-01 3.08590651e-01 -1.11483775e-01 1.20033249e-01
2.89941251e-01 1.15917754e+00 -7.26976991e-01 -5.30770600e-01
-7.70314112e-02 3.40596765e-01 -5.42675972e-01 -1.71715707e-01
-1.79387495e-01 -3.51255476e-01 -3.51738483e-01 5.36399603e-01
2.86151528e-01 -7.09336340e-01 5.01261890e-01 -4.19514656e-01
3.63811105e-01 5.05080283e-01 -1.16339922e+00 1.30487370e+00
-5.94914317e-01 1.84290454e-01 -8.03947687e-01 -1.18407094e+00
1.09016025e+00 2.26450160e-01 4.91215587e-01 -7.91136682e-01
-2.02196673e-01 2.86658615e-01 -2.63628382e-02 -1.49618685e-01
8.90168190e-01 1.95838556e-01 -1.75448015e-01 1.14489995e-01
2.32664123e-01 1.97764173e-01 5.97209573e-01 5.96915185e-01
1.29325390e+00 -3.89994085e-01 5.54956794e-01 -1.70145661e-01
6.69978678e-01 -9.32886899e-02 5.91307938e-01 3.29175591e-01
6.10178530e-01 7.81515390e-02 9.00464237e-01 -4.07025933e-01
-6.07234538e-01 -6.36701584e-01 -7.34605361e-03 1.00499487e+00
1.64509147e-01 -1.14268816e+00 5.69247603e-02 -9.46910381e-01
4.44243640e-01 8.29114854e-01 -6.04286611e-01 -5.85621536e-01
-6.69602334e-01 -6.72048390e-01 5.65405369e-01 6.17411911e-01
1.96596205e-01 -7.66143918e-01 -8.89613032e-02 1.18011869e-01
-3.68709683e-01 -1.43791139e+00 1.31378204e-01 2.91214138e-01
-7.17456818e-01 -1.28036034e+00 -2.96594799e-01 -7.34366775e-01
3.86905313e-01 3.37079763e-02 1.27899289e+00 1.88262150e-01
-1.24136440e-01 1.54465914e-01 -7.34666109e-01 -1.66752294e-01
-3.57872665e-01 4.06971931e-01 -8.30106158e-03 -1.26395628e-01
1.23357549e-01 -3.13484102e-01 -1.65566549e-01 2.77707189e-01
-7.82993972e-01 8.76657106e-03 5.49792051e-01 7.16006994e-01
7.57664979e-01 3.02357048e-01 7.51536906e-01 -1.28151143e+00
3.77589732e-01 -4.94141310e-01 -5.39740086e-01 7.76830435e-01
-8.77538145e-01 4.29926515e-01 5.70725918e-01 -1.22927554e-01
-8.16466212e-01 -2.15469047e-01 -3.08683421e-02 -1.90215483e-01
3.85540664e-01 9.80972230e-01 -2.26595208e-01 4.34436053e-02
8.70578647e-01 -1.06970184e-01 -4.46374387e-01 -3.92552227e-01
5.93568802e-01 2.28421301e-01 2.91855991e-01 -7.37751901e-01
8.19121838e-01 1.85804278e-01 3.81155044e-01 -6.89394295e-01
-9.23189580e-01 -6.31109118e-01 -5.09128928e-01 1.11238234e-01
6.47921741e-01 -1.12466812e+00 -9.46469843e-01 -2.46504545e-01
-1.07314086e+00 -7.41366893e-02 -3.28105569e-01 4.77186263e-01
-2.14452595e-01 1.99022353e-01 -4.50028867e-01 -2.93552727e-01
-3.89708787e-01 -9.13039804e-01 8.58564556e-01 -4.07344438e-02
-2.26564392e-01 -1.05461264e+00 4.75742333e-02 6.32281959e-01
1.27442285e-01 2.85960227e-01 1.62513888e+00 -9.98127878e-01
-6.04618073e-01 -3.85374129e-01 -4.28734779e-01 2.25036576e-01
9.65743735e-02 -3.76131892e-01 -5.94146192e-01 -2.05121815e-01
-7.82291412e-01 -5.46458721e-01 1.03051496e+00 -1.78841084e-01
1.27007687e+00 -2.97082543e-01 -4.99331415e-01 3.55309725e-01
1.71809995e+00 5.03339507e-02 7.16378272e-01 2.99608707e-01
1.06453288e+00 5.30747890e-01 7.34734893e-01 2.99942166e-01
6.61268353e-01 1.04253626e+00 5.22139072e-01 2.75280625e-01
-2.48272642e-01 -3.41596752e-01 9.89695266e-02 8.97192359e-01
-5.61569095e-01 -3.51884037e-01 -1.19774210e+00 5.62734962e-01
-1.79236794e+00 -7.51218498e-01 -4.12230849e-01 2.18524384e+00
9.72760379e-01 1.68112859e-01 1.47883473e-02 3.16320419e-01
5.37006199e-01 2.12474555e-01 -1.05781406e-01 -2.37196181e-02
-3.21977079e-01 4.81338263e-01 6.94755912e-01 3.21050644e-01
-1.02041388e+00 1.15194404e+00 5.11053944e+00 1.00812674e+00
-7.47718275e-01 -3.03416681e-02 3.80923569e-01 -4.46981676e-02
-5.27608037e-01 5.19812107e-02 -1.05267143e+00 7.06750005e-02
1.10849202e+00 -4.27727342e-01 2.32094780e-01 7.67053723e-01
-5.20555854e-01 -8.04997236e-02 -1.23230255e+00 1.12887502e+00
8.29749405e-02 -1.79152000e+00 3.57170761e-01 3.21212590e-01
4.78895307e-01 -1.28896818e-01 -2.00452760e-01 7.13867128e-01
3.24271232e-01 -1.12913799e+00 3.75101268e-01 3.20561528e-01
8.30989063e-01 -9.83467758e-01 9.59429801e-01 -2.38686949e-02
-1.33371913e+00 1.48373276e-01 -4.75716293e-01 3.21221262e-01
-5.15171960e-02 8.18011343e-01 -8.71594191e-01 1.22249961e+00
5.01907647e-01 8.31928492e-01 -9.69259143e-01 6.71969831e-01
-3.74755591e-01 3.41728389e-01 -2.17275873e-01 -1.04645200e-01
-1.13434725e-01 2.44829461e-01 1.88335121e-01 1.05722821e+00
1.79333031e-01 2.08719578e-02 4.03600931e-02 3.21875125e-01
-6.89945579e-01 5.20356953e-01 -7.13210166e-01 -1.00873061e-01
5.13052881e-01 1.22726810e+00 -3.64977717e-01 -4.53275949e-01
-3.83903891e-01 6.17484629e-01 8.34043086e-01 1.68154120e-01
-9.16403294e-01 -5.49104095e-01 2.60806531e-01 -9.91684496e-02
4.51398611e-01 2.52537221e-01 -1.53109163e-01 -1.06053102e+00
2.51182020e-01 -7.00442553e-01 8.30183566e-01 -3.91390771e-01
-8.97245884e-01 5.30891538e-01 6.77088052e-02 -7.75515378e-01
-2.92630970e-01 -5.53367317e-01 -1.38206050e-01 5.85022628e-01
-1.58493602e+00 -1.23031080e+00 -9.10035744e-02 5.68960428e-01
-1.51312545e-01 -2.79705375e-01 1.05679953e+00 6.10421658e-01
-6.41932011e-01 7.82235026e-01 2.54324311e-03 2.11463079e-01
5.03694057e-01 -1.39968395e+00 1.88400269e-01 5.20882845e-01
6.00894928e-01 5.87119758e-01 3.57335627e-01 -6.24711514e-01
-1.46070135e+00 -1.39200449e+00 1.27586138e+00 -4.65187669e-01
6.55175865e-01 -1.41083673e-01 -9.97810662e-01 7.99557209e-01
-3.39529723e-01 3.20235521e-01 7.97972798e-01 8.45114410e-01
-7.14632750e-01 -4.33344334e-01 -8.65799963e-01 3.93734127e-01
1.04736042e+00 -5.40700138e-01 -5.68943620e-01 5.74733913e-01
1.00474429e+00 -4.02495652e-01 -1.64315212e+00 8.70735109e-01
2.19126254e-01 -4.29270387e-01 1.28697586e+00 -7.51061976e-01
5.84916890e-01 -4.00672518e-02 -4.97405171e-01 -1.26484060e+00
-4.71302420e-01 -5.03629223e-02 -7.72310793e-01 1.27264071e+00
9.13230836e-01 -5.89037716e-01 8.00336778e-01 2.55950391e-01
-1.42169965e-03 -1.04344714e+00 -8.41531634e-01 -9.73842561e-01
-7.84197599e-02 -3.25377464e-01 5.97098053e-01 9.60002184e-01
9.15760621e-02 7.72607327e-01 -3.31794739e-01 2.95312345e-01
3.77614379e-01 1.67764738e-01 8.14742029e-01 -1.43707430e+00
-2.18570411e-01 -1.51023060e-01 -6.68966591e-01 -6.02654994e-01
1.50424838e-01 -1.35233355e+00 -6.01315200e-01 -1.59857452e+00
1.13885358e-01 -7.53704607e-01 -4.24152195e-01 6.60374939e-01
-2.18312860e-01 -8.31212103e-02 1.85306311e-01 1.49390206e-01
-7.66369283e-01 6.35334551e-01 8.64648521e-01 -1.99404538e-01
-1.61058344e-02 -5.73743992e-02 -8.77517879e-01 3.89363438e-01
6.75086856e-01 -5.05516708e-01 -4.91052657e-01 -2.75632471e-01
6.91629410e-01 1.20105006e-01 2.83187956e-01 -8.75317931e-01
1.41065627e-01 -2.44776849e-02 1.04710139e-01 -6.06984913e-01
6.24908328e-01 -6.47306681e-01 1.21648677e-01 4.44200844e-01
-3.90883505e-01 3.94428410e-02 2.31276318e-01 8.19727302e-01
-4.31572109e-01 -2.20784023e-01 3.24007869e-01 6.89837039e-02
-9.48938966e-01 3.66044566e-02 4.86151636e-01 3.12195688e-01
1.11505890e+00 3.08581918e-01 -8.03137004e-01 -1.69126481e-01
-6.38765693e-01 3.11332524e-01 -8.73750448e-02 5.67494810e-01
6.87923551e-01 -1.66565752e+00 -6.56032026e-01 -1.98474646e-01
7.20425248e-01 6.68526739e-02 1.06114477e-01 5.95172822e-01
-3.37680161e-01 6.89591527e-01 1.39247164e-01 -1.70839697e-01
-1.38960898e+00 4.82167661e-01 -1.91067412e-01 -9.92083788e-01
-5.65798342e-01 8.27706635e-01 -1.37074336e-01 -3.77818972e-01
1.24186307e-01 -5.08375287e-01 -4.81341243e-01 2.64399707e-01
2.34365627e-01 5.60007215e-01 5.15608251e-01 -7.15689480e-01
-5.81394136e-01 2.29377329e-01 -4.93489265e-01 3.32101732e-01
1.55130529e+00 4.29738641e-01 -1.93235070e-01 4.46225405e-01
1.35553467e+00 7.80372247e-02 -1.96367338e-01 -5.36687970e-01
5.20947814e-01 -2.91661680e-01 3.04119233e-02 -7.78616846e-01
-1.05799341e+00 4.29952919e-01 1.38924077e-01 2.30805412e-01
7.11450279e-01 4.98568535e-01 6.63884997e-01 8.55289340e-01
5.90090930e-01 -9.31713283e-01 1.71854228e-01 6.51530325e-01
1.07596362e+00 -1.09528613e+00 4.15114641e-01 -7.59706140e-01
-8.89703751e-01 7.75564313e-01 5.18747807e-01 1.97412699e-01
4.95317072e-01 -3.37892890e-01 -6.05569184e-01 -6.98287904e-01
-8.39394212e-01 -3.86127591e-01 6.31266832e-01 4.29244906e-01
4.13159847e-01 3.69723409e-01 -2.31883377e-01 5.03798783e-01
-3.14184904e-01 -4.15809453e-01 3.62001568e-01 5.94055712e-01
-2.58940637e-01 -1.29246902e+00 9.49347168e-02 7.41786420e-01
-5.01453936e-01 -1.05062701e-01 -2.31376648e-01 1.02978730e+00
-7.08087534e-02 7.29980528e-01 -2.47743964e-01 -6.43675566e-01
6.18142247e-01 2.62515917e-02 3.22612375e-01 -8.13922703e-01
-2.96532750e-01 -5.23363233e-01 7.69274950e-01 -5.68188369e-01
-3.83259594e-01 -4.11230475e-01 -1.30536532e+00 -2.35634193e-01
-6.22411609e-01 2.88090080e-01 3.08559477e-01 7.79595613e-01
4.63392317e-01 7.84952164e-01 3.28192919e-01 1.94530040e-01
-3.13037843e-01 -8.54759991e-01 -6.45181417e-01 5.43558300e-01
-1.02131076e-01 -9.47826922e-01 -5.21584079e-02 -3.77017587e-01] | [8.798128128051758, 7.943556308746338] |
387a90a3-09bd-4a81-b33c-a49fd0059753 | msp-refine-boundary-segmentation-via | 2112.01746 | null | https://arxiv.org/abs/2112.01746v1 | https://arxiv.org/pdf/2112.01746v1.pdf | MSP : Refine Boundary Segmentation via Multiscale Superpixel | In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. Inspired by the generated sharp edges of superpixel blocks, we employ superpixel to guide the information passing within feature map. Simultaneously, the sharp boundaries of the blocks also restrict the message passing scope. Specifically, we average features that the superpixel block covers within feature map, and add the result back to each feature vector. Further, to obtain sharper edges and farther spatial dependence, we develop a multiscale superpixel module (MSP) by a cascade of different scales superpixel blocks. Our method can be served as a plug-and-play module and easily inserted into any segmentation network without introducing new parameters. Extensive experiments are conducted on three strong baselines, namely PSPNet, DeeplabV3, and DeepLabV3+, and four challenging scene parsing datasets including ADE20K, Cityscapes, PASCAL VOC, and PASCAL Context. The experimental results verify its effectiveness and generalizability. | ['Leye Wang', 'Yong liu', 'Banghuai Li', 'Huabin Huang', 'Jie Zhu'] | 2021-12-03 | null | null | null | null | ['scene-parsing'] | ['computer-vision'] | [ 1.42400200e-02 -1.11020207e-02 -4.83699851e-02 -8.00661385e-01
-6.15845025e-01 -6.07715011e-01 2.71902561e-01 5.93335256e-02
-5.82225800e-01 4.84426856e-01 -1.99228525e-02 -1.89432010e-01
3.65571856e-01 -9.71945167e-01 -9.58228052e-01 -5.75856745e-01
2.02749431e-01 -1.22122914e-01 1.14897704e+00 5.52501455e-02
8.26180279e-02 1.09373122e-01 -9.96993959e-01 5.38113415e-01
1.01796949e+00 1.05496609e+00 5.54301977e-01 5.85665107e-01
-4.27923232e-01 7.77567923e-01 -6.06182754e-01 -3.10948581e-01
2.24173144e-01 -2.02670977e-01 -1.10725510e+00 1.83994040e-01
3.94492298e-01 -6.63864732e-01 -3.72930586e-01 1.24221241e+00
1.10795408e-01 -3.18246111e-02 -1.75933409e-02 -1.04032302e+00
-5.44344544e-01 9.49026525e-01 -8.34075391e-01 2.36230403e-01
2.48404965e-02 2.80412316e-01 9.48328137e-01 -6.36322081e-01
6.82190895e-01 1.51444447e+00 5.43686450e-01 2.53029943e-01
-9.52122569e-01 -7.51362741e-01 6.22378707e-01 1.98494405e-01
-1.13232470e+00 -1.26821414e-01 6.34772360e-01 -8.38996843e-02
5.97002566e-01 2.47262076e-01 5.53848684e-01 6.84288323e-01
-1.22766539e-01 1.40274918e+00 9.14187491e-01 2.45771334e-01
2.04879105e-01 -1.58479273e-01 6.24677300e-01 7.29978800e-01
-3.38469595e-02 -2.79368937e-01 -1.21260099e-01 7.36787021e-02
9.33663309e-01 1.04978815e-01 -2.25160822e-01 -1.06199555e-01
-1.03999436e+00 8.19388449e-01 1.05077994e+00 1.80498347e-01
-7.13774934e-02 4.30901110e-01 5.06794930e-01 -4.56359750e-03
4.95368510e-01 -1.76678210e-01 -6.81179047e-01 1.03529327e-01
-7.79175818e-01 1.61336526e-01 6.19008124e-01 1.18793964e+00
1.15283334e+00 -4.05455470e-01 -3.81091177e-01 8.88990462e-01
5.07923961e-01 1.92522272e-01 2.09609494e-01 -1.22035801e+00
6.36888504e-01 7.44840860e-01 -1.26215786e-01 -1.03365409e+00
-3.02697301e-01 -3.32675427e-01 -7.24050105e-01 -1.69096172e-01
2.94271022e-01 -1.77207455e-01 -1.15852308e+00 1.48710012e+00
7.91701376e-01 5.06200671e-01 -1.27886564e-01 1.15455842e+00
1.02510273e+00 1.04748297e+00 1.36128604e-01 1.82312995e-01
1.39517915e+00 -1.51076388e+00 -2.66037941e-01 -3.59158456e-01
7.92516172e-01 -7.05822587e-01 9.39599693e-01 1.03219025e-01
-9.23005342e-01 -8.31818640e-01 -9.91750717e-01 -4.20470685e-01
-2.67098784e-01 -1.29471356e-02 7.85881341e-01 2.51783669e-01
-9.01753724e-01 6.14479661e-01 -1.16680133e+00 -6.24231286e-02
7.21037328e-01 1.86181515e-01 -1.17989518e-02 -1.37085125e-01
-9.67133462e-01 1.19362406e-01 5.96123457e-01 2.79772729e-01
-8.14343393e-01 -7.08455980e-01 -1.00545681e+00 3.96259949e-02
2.76948601e-01 -5.02127051e-01 1.18400979e+00 -9.46632147e-01
-1.37338078e+00 7.56582677e-01 -1.16765037e-01 -4.18440819e-01
7.99733520e-01 -2.83696175e-01 3.30801047e-02 2.79500455e-01
3.43672097e-01 1.20875943e+00 4.80993479e-01 -1.12953579e+00
-1.02806592e+00 -3.04840684e-01 4.29985374e-01 7.25208223e-03
-3.00585590e-02 1.26213491e-01 -1.07832921e+00 -4.87349451e-01
3.53671879e-01 -6.10751390e-01 -5.29470801e-01 -6.22821823e-02
-7.54534721e-01 -2.71259367e-01 8.86099279e-01 -6.65935218e-01
1.06566894e+00 -2.56831884e+00 -1.11900739e-01 7.11807311e-02
2.41333038e-01 1.70600191e-01 -2.92882979e-01 -1.32925421e-01
3.61111015e-01 1.94695801e-01 -5.88403165e-01 -2.87550151e-01
-9.30317342e-02 4.60939735e-01 -1.95153385e-01 2.55046636e-01
2.64239758e-01 1.06799781e+00 -9.67457533e-01 -8.77502084e-01
2.62610555e-01 3.34309369e-01 -6.90376699e-01 3.07879262e-02
-3.94893646e-01 2.96514213e-01 -9.19892073e-01 3.82818431e-01
1.28779364e+00 -4.35956895e-01 -1.95134386e-01 -1.77395821e-01
-3.00725996e-01 4.04080331e-01 -1.24043489e+00 1.95207238e+00
-1.98002592e-01 3.90453130e-01 4.20695841e-01 -7.88737357e-01
8.33769143e-01 -3.38936597e-01 8.19618627e-02 -6.07720315e-01
1.02925248e-01 2.24486683e-02 -2.76107311e-01 -3.26702863e-01
6.63101614e-01 4.82273757e-01 -5.61391488e-02 3.48744914e-02
-1.05546981e-01 -9.23749283e-02 3.36268365e-01 4.20469433e-01
1.06457233e+00 3.25431228e-01 -3.14373374e-01 -3.64021242e-01
5.73813856e-01 9.75370109e-02 1.00502205e+00 6.77438080e-01
-4.12686557e-01 8.20199311e-01 7.43303359e-01 -3.43018532e-01
-7.47127116e-01 -9.92770731e-01 -1.91817895e-01 1.28180575e+00
8.22842062e-01 -3.90235096e-01 -1.12852979e+00 -8.93511415e-01
-4.51737791e-02 3.76696140e-01 -5.04121006e-01 1.48218766e-01
-8.44846725e-01 -9.45733190e-01 4.67436105e-01 9.28866625e-01
1.27830064e+00 -1.02601886e+00 -3.77796769e-01 4.71387237e-01
-2.53792018e-01 -1.31658936e+00 -7.39008665e-01 -1.11322075e-01
-8.59688699e-01 -9.74427283e-01 -5.92484713e-01 -1.15961099e+00
6.02331817e-01 5.52766263e-01 7.78090715e-01 1.75721616e-01
-1.50970295e-01 -1.96337596e-01 -5.38507521e-01 5.64317890e-02
-2.58361846e-01 2.50968039e-01 -8.46867561e-01 -1.91046372e-02
1.15382418e-01 -3.64473343e-01 -1.00650394e+00 4.51296657e-01
-8.98224592e-01 4.40200865e-01 4.09521073e-01 6.14003599e-01
7.37289488e-01 -1.52272716e-01 1.97725922e-01 -9.31807220e-01
1.19772986e-01 -3.81821185e-01 -8.55329931e-01 1.11509748e-01
-1.64673775e-02 -1.49807975e-01 6.46224558e-01 -2.91883312e-02
-1.25137472e+00 2.18104750e-01 -3.82497102e-01 -5.15144691e-02
-2.75176823e-01 1.73051581e-01 -4.40993816e-01 6.65070266e-02
1.42864451e-01 2.16610983e-01 -4.35216099e-01 -6.56931341e-01
6.66246295e-01 7.50079513e-01 6.71582460e-01 -5.12942016e-01
5.08979440e-01 6.57550573e-01 -5.61128914e-01 -5.69062352e-01
-9.01564240e-01 -4.75243717e-01 -5.32052398e-01 1.98205173e-01
1.14588201e+00 -9.56121147e-01 -5.66680372e-01 8.61438215e-01
-1.44249427e+00 -6.38908803e-01 3.26956473e-02 8.78771618e-02
-1.09390728e-01 5.20612478e-01 -1.19555092e+00 -1.90511733e-01
-2.78737903e-01 -1.35376060e+00 1.21341598e+00 6.75646842e-01
2.21949324e-01 -7.62412369e-01 -2.26417944e-01 4.59064335e-01
1.76002949e-01 1.55199841e-01 5.31206548e-01 -4.17144775e-01
-9.49704409e-01 7.04778880e-02 -9.69173133e-01 5.27685463e-01
7.24439742e-03 2.58894980e-01 -1.03428864e+00 -1.07779078e-01
-2.38670453e-01 -2.05194473e-01 1.43701231e+00 3.76319945e-01
1.41699553e+00 -9.56109464e-02 -4.41995293e-01 9.79767263e-01
1.27678287e+00 -1.99204274e-02 4.58254457e-01 3.06242287e-01
9.89908218e-01 3.63947034e-01 5.76206744e-01 1.78383246e-01
8.59003425e-01 2.68459618e-01 4.84886676e-01 -3.64000201e-01
-2.40759626e-01 -3.34134161e-01 2.11192116e-01 9.11892593e-01
4.15794492e-01 -8.10279995e-02 -5.22962570e-01 6.02955282e-01
-1.91623759e+00 -4.86815155e-01 -3.43642026e-01 1.69899726e+00
8.32800210e-01 4.61817801e-01 -1.70632660e-01 -2.79430181e-01
8.71546745e-01 5.98001063e-01 -6.25434220e-01 -2.14820832e-01
-1.57368958e-01 -6.50977939e-02 6.25180185e-01 6.04398131e-01
-1.39658916e+00 1.49309075e+00 5.34603214e+00 1.12863100e+00
-1.05233085e+00 1.59419984e-01 1.01488805e+00 2.43312448e-01
-3.43959779e-01 1.11850172e-01 -9.28921998e-01 6.12252951e-01
2.58726388e-01 1.81853265e-01 1.78974956e-01 9.09674704e-01
2.09740981e-01 -1.60664260e-01 -9.23923075e-01 5.80838680e-01
-5.04246652e-01 -1.38740718e+00 -1.36389941e-01 -3.55504841e-01
7.70002902e-01 5.21544933e-01 -1.57940060e-01 3.44022542e-01
7.36820757e-01 -5.74232161e-01 7.12353170e-01 -1.41864866e-01
2.73826122e-01 -5.58542967e-01 6.00929618e-01 2.25250393e-01
-1.50818074e+00 1.58390969e-01 -7.00456202e-01 5.46683499e-04
2.08681569e-01 6.78363204e-01 -3.47142160e-01 5.15161991e-01
9.59592402e-01 8.74020994e-01 -5.61286330e-01 9.74452019e-01
-5.36798239e-01 8.12376320e-01 -5.60513377e-01 -3.58651727e-02
6.83986962e-01 -2.35417694e-01 2.29638979e-01 1.55332828e+00
-2.29645029e-01 2.15446159e-01 4.64229405e-01 1.15796685e+00
-3.14491719e-01 3.25728729e-02 -1.73766562e-03 4.01202321e-01
5.39764524e-01 1.60782635e+00 -1.15948105e+00 -6.72335982e-01
-6.35687470e-01 1.26803732e+00 3.63819420e-01 5.07321000e-01
-1.05920327e+00 -5.98633766e-01 6.86666727e-01 -3.77262473e-01
6.54942453e-01 -1.32083401e-01 -4.94200587e-01 -1.15826893e+00
9.33810920e-02 -4.75683063e-01 3.21266353e-01 -6.34877563e-01
-1.00954485e+00 5.32939076e-01 -1.98141128e-01 -7.16027856e-01
4.47302073e-01 -3.82042617e-01 -8.75785708e-01 6.02534652e-01
-1.69473076e+00 -1.12306023e+00 -4.68293339e-01 4.54665840e-01
7.15584099e-01 7.01176226e-01 1.54310077e-01 2.93262362e-01
-9.66593981e-01 4.26923007e-01 2.40543094e-02 6.00968778e-01
3.36311042e-01 -1.22698867e+00 8.69004130e-01 1.01970327e+00
-1.25619501e-01 3.27214092e-01 2.73639619e-01 -5.79182982e-01
-9.37487066e-01 -1.61311829e+00 4.81747687e-01 -7.86038712e-02
6.48317575e-01 -4.86504555e-01 -1.04737282e+00 7.50622511e-01
1.45134345e-01 1.69410959e-01 1.81697048e-02 -3.27177942e-01
-3.67281467e-01 -2.32334241e-01 -1.07084394e+00 5.59639275e-01
1.22340512e+00 -1.69974893e-01 -5.71034014e-01 2.72136927e-01
1.44432652e+00 -6.49818182e-01 -6.49735987e-01 4.91512299e-01
1.67927116e-01 -1.02972865e+00 9.62003112e-01 -3.38803947e-01
6.31844819e-01 -4.00145024e-01 -9.14630815e-02 -1.05949736e+00
-3.66521657e-01 -4.64094907e-01 4.88765270e-01 1.58547270e+00
5.51447988e-01 -5.74516654e-01 9.68022883e-01 5.72138190e-01
-4.63533461e-01 -6.35306418e-01 -8.68641257e-01 -5.87273180e-01
1.51241094e-01 -5.06513536e-01 8.91135454e-01 7.32135713e-01
-2.46074855e-01 7.01042488e-02 1.11737065e-01 4.00074959e-01
6.24257445e-01 4.50498581e-01 8.13279808e-01 -7.80185640e-01
-2.93375760e-01 -4.62484896e-01 -1.76798597e-01 -1.99697638e+00
3.25910039e-02 -8.42690170e-01 3.10845256e-01 -1.60328162e+00
3.79745364e-01 -6.48787260e-01 -4.65442449e-01 5.42000175e-01
-5.71494043e-01 1.81863531e-01 3.81791472e-01 4.32765745e-02
-1.05279362e+00 5.01133680e-01 1.63496542e+00 -2.94260830e-01
-3.24445426e-01 -2.62894958e-01 -5.99061489e-01 1.13018179e+00
7.18505502e-01 -4.83072490e-01 -2.27449074e-01 -1.03433406e+00
-1.14850357e-01 -1.40985146e-01 4.94040489e-01 -7.63473094e-01
2.70242900e-01 -1.93825275e-01 3.09917033e-01 -6.19358301e-01
4.30323854e-02 -4.71022815e-01 -3.83578658e-01 4.34419483e-01
-2.47221440e-01 -3.23896557e-01 2.09996715e-01 4.50711310e-01
-2.74612129e-01 -4.92539369e-02 7.79782057e-01 -8.74004737e-02
-1.06708598e+00 5.35960913e-01 -3.07288207e-02 3.45897079e-01
9.92783785e-01 -1.71393305e-01 -4.99697506e-01 1.62362680e-01
-5.10055482e-01 9.63931441e-01 4.16580319e-01 4.68566597e-01
6.07601702e-01 -1.05788565e+00 -7.26092875e-01 2.12683454e-01
-4.82853018e-02 7.33661950e-01 4.06259030e-01 6.62615418e-01
-9.56885695e-01 6.68235123e-02 9.58955139e-02 -8.31940293e-01
-1.10908103e+00 3.33806038e-01 2.53413260e-01 -5.59046604e-02
-8.46889198e-01 1.38339758e+00 8.19171309e-01 -5.66647589e-01
1.90126017e-01 -9.41794455e-01 -2.70821117e-02 -1.83582157e-01
5.43751717e-01 3.26120108e-01 -4.95577306e-01 -4.82212961e-01
-4.41303998e-01 6.02623522e-01 -3.20054054e-01 1.34880930e-01
1.15136695e+00 -4.10764426e-01 -3.37481529e-01 5.28310016e-02
1.36477077e+00 -2.50972718e-01 -1.68042111e+00 -2.17154682e-01
-1.10679314e-01 -2.60600269e-01 5.87727949e-02 -4.15758312e-01
-1.52253151e+00 8.92283499e-01 2.72359669e-01 2.94328868e-01
1.00751805e+00 1.95229366e-01 1.32025266e+00 5.11892401e-02
2.75328904e-01 -1.13457119e+00 -2.88839012e-01 4.24980223e-01
4.36200738e-01 -1.09708798e+00 -4.37258571e-01 -9.82120216e-01
-4.06143636e-01 8.42703164e-01 8.16306174e-01 -4.38620716e-01
6.72544479e-01 3.30038130e-01 2.02647790e-01 7.23860189e-02
-5.65192938e-01 -1.07621595e-01 -1.77074879e-01 2.81774044e-01
1.56540647e-01 1.31400853e-01 -4.15984809e-01 7.81679988e-01
-7.55173862e-02 1.25601426e-01 4.39571172e-01 7.50519991e-01
-6.79150224e-01 -8.01146150e-01 -1.20225266e-01 1.74842253e-01
-5.12631655e-01 -2.02866942e-01 -2.47306004e-01 6.36287928e-01
3.21724355e-01 1.02998328e+00 2.96597362e-01 -2.97469914e-01
3.19960803e-01 -4.18362260e-01 4.98026349e-02 -4.38713014e-01
-6.14963412e-01 2.03318909e-01 -1.40027069e-02 -9.24204290e-01
-1.97716206e-01 -5.19919097e-01 -1.91484082e+00 -2.57248372e-01
-3.41209352e-01 1.48191914e-01 4.03885543e-01 9.24024224e-01
4.74504918e-01 7.90031850e-01 6.62804365e-01 -4.73968297e-01
-2.45822355e-01 -9.58026648e-01 -3.56962651e-01 4.08296466e-01
2.10171089e-01 5.28706610e-03 -1.53833121e-01 6.61057383e-02] | [9.551346778869629, 0.2629944682121277] |
f7af5a31-cf36-4370-966d-bb1e89d5da3d | unsupervised-voice-activity-detection-by | 2206.13420 | null | https://arxiv.org/abs/2206.13420v1 | https://arxiv.org/pdf/2206.13420v1.pdf | Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering | Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which contain voicing information. In recent years, it has been shown that voice source and vocal tract system information can be extracted using zero-frequency filtering (ZFF) without making any explicit model assumptions about the speech signal. This paper investigates the potential of zero-frequency filtering for jointly modeling voice source and vocal tract system information, and proposes two approaches for VAD. The first approach demarcates voiced regions using a composite signal composed of different zero-frequency filtered signals. The second approach feeds the composite signal as input to the rVAD algorithm. These approaches are compared with other supervised and unsupervised VAD methods in the literature, and are evaluated on the Aurora-2 database, across a range of SNRs (20 to -5 dB). Our studies show that the proposed ZFF-based methods perform comparable to state-of-art VAD methods and are more invariant to added degradation and different channel characteristics. | ['Mathew Magimai. -Doss', 'RaviShankar Prasad', 'Eklavya Sarkar'] | 2022-06-27 | null | null | null | null | ['activity-detection'] | ['computer-vision'] | [ 1.10862598e-01 -2.70041883e-01 7.46837333e-02 3.01429927e-02
-1.04945469e+00 -7.84271657e-01 4.30280775e-01 2.59149000e-02
-4.97139432e-02 5.14134228e-01 5.65354645e-01 -5.10696590e-01
-8.14846158e-02 -1.68783411e-01 3.86866331e-02 -8.35367501e-01
-1.78605750e-01 -2.68093705e-01 3.22635978e-01 2.22654436e-02
7.61609599e-02 6.35985613e-01 -2.06273723e+00 1.46166474e-01
7.58116841e-01 1.01457536e+00 3.38843346e-01 1.12326193e+00
-6.96834028e-02 1.89918235e-01 -1.06041455e+00 2.33312547e-01
1.46650657e-01 -7.72159815e-01 -5.54628372e-01 3.20004076e-01
2.43358880e-01 -2.74327048e-03 -7.37297684e-02 1.05119860e+00
9.36980665e-01 2.88232386e-01 7.69262612e-01 -7.70865798e-01
1.08336419e-01 3.20926964e-01 3.93403172e-02 5.81933856e-01
4.34375286e-01 -5.15027829e-02 9.44136262e-01 -1.08209658e+00
3.43982220e-01 1.19986022e+00 4.62057263e-01 4.28807408e-01
-1.17856121e+00 -4.14770037e-01 -3.59634012e-01 1.22232549e-01
-1.18524420e+00 -8.10717165e-01 1.13334441e+00 -7.14996815e-01
1.08841443e+00 6.35855138e-01 4.05024141e-01 5.53661346e-01
8.24778304e-02 6.60736382e-01 1.07311952e+00 -8.16920102e-01
3.49915355e-01 1.00862533e-01 3.01269948e-01 2.08711758e-01
-2.42511421e-01 2.35382468e-01 -3.93685907e-01 -3.50046366e-01
4.07275051e-01 -7.86937892e-01 -8.01624238e-01 4.02941406e-02
-9.70490336e-01 5.87054431e-01 -1.40471146e-01 6.64452851e-01
-6.63618445e-01 -2.43522123e-01 4.42145348e-01 5.72077513e-01
7.49429286e-01 5.08665740e-01 -2.51004606e-01 -2.56854385e-01
-1.22946513e+00 1.31762072e-01 8.30885530e-01 4.87773865e-01
1.03005238e-01 7.71899164e-01 -2.45234013e-01 1.18728733e+00
5.62608480e-01 4.33697462e-01 4.59765732e-01 -9.09803271e-01
2.99552321e-01 -3.56397629e-01 1.18568681e-01 -3.60508293e-01
-1.93851054e-01 -6.35933280e-01 -2.38198921e-01 2.77167648e-01
5.34107387e-01 -2.52504170e-01 -1.00819361e+00 1.38804400e+00
4.02443260e-01 1.71309248e-01 2.81841457e-01 8.16381156e-01
7.62318075e-01 9.85292375e-01 -3.89470994e-01 -1.00907528e+00
1.17160749e+00 -7.94741869e-01 -1.34512877e+00 1.33303210e-01
-1.80941790e-01 -1.38110578e+00 1.04891968e+00 9.64193106e-01
-1.09385264e+00 -7.06044853e-01 -1.08033407e+00 3.00599515e-01
-3.88914645e-02 1.18486367e-01 -8.73755291e-02 1.23730850e+00
-9.37415361e-01 4.67316926e-01 -4.50887710e-01 -2.63909027e-02
-2.58928210e-01 1.02813296e-01 6.20572083e-02 4.85611677e-01
-1.14067686e+00 5.45427263e-01 -2.57893205e-01 7.93778822e-02
-1.19833302e+00 -5.43197691e-01 -6.89784467e-01 -5.34329005e-03
1.17692910e-01 -3.49138194e-04 1.88307571e+00 -7.82198012e-01
-2.04596686e+00 1.82849184e-01 -6.07105792e-01 -3.21809977e-01
2.35072821e-01 -3.32149029e-01 -1.04406381e+00 3.65805387e-01
-3.95598024e-01 -2.84717023e-01 1.50965679e+00 -1.25582170e+00
-4.38410372e-01 1.81542654e-02 -4.89354491e-01 2.33821109e-01
-1.07218055e-02 2.46656954e-01 -1.13293119e-01 -7.94604242e-01
3.09671581e-01 -4.73298132e-01 1.27697647e-01 -5.03305793e-01
-3.73119831e-01 -1.45562559e-01 8.55823874e-01 -1.12642431e+00
1.52600098e+00 -2.32577229e+00 -6.58378303e-02 3.42394233e-01
-2.11342216e-01 6.81087792e-01 4.14966978e-02 4.69205588e-01
-1.59147203e-01 -6.32558689e-02 -1.12920798e-01 -3.36233258e-01
-1.47432834e-01 -6.26126453e-02 -4.61150706e-01 5.76937318e-01
-1.02452539e-01 -3.07748113e-02 -7.60597110e-01 -3.09512228e-01
5.61412752e-01 7.04788446e-01 -3.65069777e-01 4.12472010e-01
2.05766305e-01 5.46471477e-01 1.63310692e-01 4.86117303e-01
5.98515093e-01 8.61047983e-01 -2.27060635e-02 -1.80735648e-01
-4.86233652e-01 9.10606861e-01 -1.39138401e+00 1.09003139e+00
-6.25521541e-01 9.39741313e-01 6.39722705e-01 -5.20291448e-01
9.67645645e-01 1.13925159e+00 3.19763809e-01 -2.40699306e-01
2.88123280e-01 4.80122298e-01 3.46982926e-01 -5.30153990e-01
2.68177897e-01 -3.47373337e-01 2.93611974e-01 5.19604050e-02
5.40060818e-01 -6.79963171e-01 -5.85372671e-02 -2.94519871e-01
6.15960062e-01 -3.74107182e-01 3.39613765e-01 -3.13128412e-01
8.98200393e-01 -5.31999886e-01 4.09362078e-01 2.84450710e-01
-5.34443378e-01 5.05574167e-01 2.22121835e-01 6.37585878e-01
-9.34801519e-01 -1.31951058e+00 -4.50791448e-01 7.16191590e-01
-2.27513820e-01 -3.75715524e-01 -1.14723969e+00 4.76058535e-02
-2.15075001e-01 1.05443430e+00 -2.86092386e-02 2.60124374e-02
-4.20827597e-01 -1.72495350e-01 7.09190130e-01 1.89531922e-01
1.90214571e-02 -9.04431880e-01 -1.19393714e-01 4.84748334e-01
-3.45753282e-01 -8.26129973e-01 -5.57507277e-01 2.55231202e-01
-8.60204756e-01 -4.70345348e-01 -8.60472500e-01 -8.10133815e-01
1.40263960e-01 3.93365264e-01 6.80771768e-01 -3.60977441e-01
-9.97178555e-02 5.52689850e-01 -3.72955352e-01 -5.66372931e-01
-9.86322403e-01 -3.21559578e-01 4.63439733e-01 3.88783813e-01
9.38667357e-02 -6.01278126e-01 -4.19401288e-01 4.64710951e-01
-5.53479373e-01 -6.83962047e-01 2.03798771e-01 6.65196657e-01
7.34300256e-01 4.41760957e-01 1.02776814e+00 -2.77101308e-01
1.16635144e+00 -4.93622690e-01 -5.21035552e-01 -3.29649746e-01
-4.53505903e-01 -3.31904143e-01 7.21661150e-01 -5.48725069e-01
-1.38797235e+00 9.69116613e-02 -6.79031074e-01 -5.35236299e-01
-4.11425680e-01 2.84934223e-01 -6.43909812e-01 2.41268650e-01
7.95817733e-01 2.29926273e-01 1.75967231e-01 -1.00846982e+00
3.44336480e-01 1.42265284e+00 8.89172375e-01 -6.87043145e-02
6.83469832e-01 4.35562842e-02 -4.46905434e-01 -1.67579329e+00
-2.22879499e-01 -1.11400926e+00 -5.65934122e-01 -5.23830771e-01
7.30666697e-01 -7.17039168e-01 -2.12035358e-01 7.52307832e-01
-1.03438389e+00 8.79035564e-04 -3.84822428e-01 1.03339946e+00
-6.70410693e-01 5.87308466e-01 -5.71585476e-01 -1.54647565e+00
-4.77684945e-01 -9.76656079e-01 5.78714490e-01 9.62632373e-02
-3.33916157e-01 -7.71923244e-01 1.34576425e-01 2.81235963e-01
2.73900419e-01 -5.67789469e-03 6.08799219e-01 -4.83036369e-01
1.89290628e-01 -7.69524500e-02 7.74078727e-01 1.00658512e+00
6.57666206e-01 5.43193556e-02 -1.67434740e+00 -2.36051738e-01
5.68684757e-01 2.83632517e-01 6.04456663e-01 7.05744088e-01
5.75982571e-01 -2.70462126e-01 1.50705367e-01 7.91841820e-02
9.85401332e-01 6.64094865e-01 6.41609311e-01 -2.69821942e-01
2.10193112e-01 7.59997964e-01 9.28155601e-01 1.66056499e-01
-4.21409070e-01 5.13977349e-01 3.17836642e-01 -1.34383053e-01
-7.03280389e-01 -1.05004959e-01 5.69853425e-01 1.36906946e+00
6.97450154e-03 -4.19015080e-01 -4.14614707e-01 1.06956494e+00
-1.06451523e+00 -1.05172169e+00 -5.01078427e-01 2.38120627e+00
8.04321408e-01 1.81571335e-01 4.31591094e-01 1.15887499e+00
9.55893219e-01 3.27478647e-01 -4.68282193e-01 -9.25624669e-01
1.17953233e-01 4.94559139e-01 1.54873610e-01 9.33821738e-01
-8.69548023e-01 4.95533228e-01 6.94789553e+00 9.06020701e-01
-1.22206283e+00 2.54527837e-01 -1.34029761e-01 -5.00414446e-02
-2.12775901e-01 -4.00001079e-01 -3.95784825e-01 1.69600457e-01
1.40976834e+00 -3.22722018e-01 5.70497215e-01 6.46163106e-01
7.90435791e-01 -1.11544453e-01 -6.25555694e-01 7.34782696e-01
1.22955758e-02 -5.07615983e-01 -4.30973172e-01 4.05959561e-02
4.08354998e-01 -2.15524137e-01 9.76435542e-02 -1.02949478e-01
-4.88822967e-01 -7.53436983e-01 9.67642069e-01 3.79812390e-01
8.46694589e-01 -8.27758789e-01 5.12591541e-01 2.96168178e-01
-1.44290638e+00 -2.44524181e-02 -1.53369218e-01 -1.23538096e-02
4.61477995e-01 7.75683165e-01 -1.39575279e+00 4.81462300e-01
4.65945184e-01 3.94036509e-02 7.56441429e-02 1.51631582e+00
-3.30125302e-01 1.51958179e+00 -2.20877364e-01 1.96799706e-03
-4.84405346e-02 1.77799836e-01 1.15933383e+00 1.33908772e+00
4.66625750e-01 -9.97186154e-02 -4.02441680e-01 5.00995338e-01
3.09878230e-01 4.07249838e-01 -3.91003549e-01 -2.43101969e-01
5.94900548e-01 1.00998890e+00 -3.96621883e-01 -1.99085161e-01
-3.62524778e-01 6.01844311e-01 -6.28195763e-01 4.34763759e-01
-3.93488944e-01 -8.54687691e-01 9.78923738e-01 1.41856030e-01
4.63587403e-01 -4.03843433e-01 3.82672101e-02 -7.03813314e-01
-1.37588322e-01 -8.38224769e-01 1.25077203e-01 -7.14784443e-01
-9.47373688e-01 7.76929140e-01 -1.15105296e-02 -1.71510017e+00
-6.82297230e-01 -5.14761448e-01 -7.11692214e-01 1.29516864e+00
-1.43467569e+00 -3.04009914e-01 1.47287443e-01 6.32109582e-01
1.11048913e+00 -1.24607474e-01 8.03700805e-01 4.26909477e-01
-9.45026129e-02 4.13399190e-01 5.03674984e-01 -2.73026109e-01
5.15537143e-01 -1.36283433e+00 4.98571545e-01 1.07201993e+00
2.53984451e-01 4.12370265e-01 1.20794785e+00 -4.73882109e-01
-1.12021220e+00 -9.13672030e-01 1.00579000e+00 -3.51978764e-02
3.76754642e-01 -4.41304147e-01 -1.11580563e+00 2.71249153e-02
3.40455264e-01 -1.56030506e-01 8.38007629e-01 -3.14106315e-01
3.68629175e-04 -1.50474906e-01 -1.22220850e+00 1.40038803e-01
5.67707419e-01 -8.26863229e-01 -1.15585446e+00 -1.92983702e-01
7.72661746e-01 -2.04004407e-01 -8.91337812e-01 1.57579973e-01
3.05718035e-01 -7.78162301e-01 7.22077668e-01 -1.34251446e-01
-4.77321088e-01 -7.87406564e-01 -1.79202676e-01 -1.79413497e+00
-8.42512622e-02 -1.15303397e+00 -1.21281207e-01 1.62036753e+00
4.76170391e-01 -6.03851318e-01 2.79540513e-02 -2.09201142e-01
-3.83513153e-01 -1.59387231e-01 -1.05814373e+00 -1.14852524e+00
-5.13539463e-03 -8.82671118e-01 3.25608671e-01 4.55728412e-01
2.41463661e-01 3.71513128e-01 -4.22796577e-01 4.28813994e-01
4.27521527e-01 -1.66454047e-01 4.08076167e-01 -1.20499432e+00
-3.38644117e-01 -2.87496388e-01 -2.19557077e-01 -9.31167364e-01
-2.38795623e-01 -4.11531150e-01 4.30980712e-01 -1.49552619e+00
-9.29526448e-01 1.66388378e-01 -4.02929604e-01 -6.55109137e-02
2.50283163e-02 2.37848219e-02 9.03504863e-02 1.11247465e-01
5.08435726e-01 4.09619868e-01 1.18370330e+00 2.42660008e-03
-6.74974263e-01 6.73014998e-01 -1.83650598e-01 8.33296061e-01
7.86111534e-01 -3.25458080e-01 -8.60211134e-01 2.79627025e-01
-6.77725792e-01 3.70305598e-01 -2.24044211e-02 -1.11150265e+00
-1.15674343e-02 2.01402262e-01 -1.60245687e-01 -9.45863664e-01
6.12558663e-01 -6.73608720e-01 5.76498508e-02 4.07982320e-01
-1.31287023e-01 -5.15838563e-01 3.34816009e-01 4.43542540e-01
-5.48063159e-01 -4.70591575e-01 9.20142412e-01 2.42728427e-01
-4.65146899e-01 -4.32470441e-01 -1.11984932e+00 -3.17471296e-01
5.97806990e-01 -2.49539375e-01 6.46297187e-02 -6.89965308e-01
-8.89354348e-01 -4.64625001e-01 -1.79087058e-01 4.17807817e-01
6.09057248e-01 -1.03179550e+00 -6.53967202e-01 2.98988402e-01
-2.96271026e-01 -3.93473029e-01 2.21194282e-01 8.41240883e-01
-3.33045095e-01 4.50754762e-01 2.77733430e-02 -6.04605913e-01
-1.68009448e+00 5.40742934e-01 6.41161084e-01 3.93177688e-01
-3.58407646e-01 7.24618614e-01 -5.50629385e-02 2.16588359e-02
4.88690138e-01 -6.12421393e-01 -6.43681765e-01 2.25915104e-01
7.08001196e-01 6.13855302e-01 4.85707372e-01 -1.02519310e+00
-2.70607352e-01 4.98026252e-01 3.54200780e-01 -7.98638642e-01
8.01934600e-01 -5.04222274e-01 2.56247222e-01 8.88322651e-01
1.12861657e+00 6.80551529e-01 -8.65751088e-01 -1.30764425e-01
-9.09932777e-02 -5.72261274e-01 5.06797433e-01 -8.20421636e-01
-7.16904461e-01 1.23602033e+00 8.79777312e-01 7.48637974e-01
1.55351198e+00 -1.48759857e-01 7.09200084e-01 -1.94391489e-01
1.85785323e-01 -1.16355598e+00 -7.84172118e-02 3.35693568e-01
1.03772461e+00 -3.98719251e-01 -3.89705956e-01 -7.50656962e-01
-3.64769936e-01 1.14815331e+00 8.99932981e-02 1.07221738e-01
8.27606082e-01 1.55533463e-01 5.64361930e-01 3.36974531e-01
-4.87902522e-01 -5.78177452e-01 6.65958226e-01 8.10477257e-01
5.42628646e-01 -9.81520023e-03 -6.40439928e-01 6.35992229e-01
-5.13804495e-01 -3.80978376e-01 5.69162846e-01 7.54683673e-01
-8.61727893e-01 -1.01187825e+00 -9.35620010e-01 2.64965773e-01
-8.23811591e-01 -6.04900941e-02 -5.11263728e-01 3.31247151e-01
-1.64130837e-01 1.70435214e+00 -6.90899715e-02 -4.71971869e-01
6.38787270e-01 5.15339792e-01 2.32926920e-01 -4.96477932e-01
-6.40216649e-01 9.41654146e-01 5.03677130e-01 -1.19675472e-01
-3.08107585e-01 -9.21112478e-01 -1.25454557e+00 3.17129403e-01
-8.35078359e-01 5.81179559e-01 9.44988906e-01 7.65109718e-01
5.16591296e-02 9.09640849e-01 1.15213180e+00 -8.25793564e-01
-5.19786775e-01 -1.21011794e+00 -9.43632185e-01 -4.98449104e-03
8.97152245e-01 -5.90460718e-01 -1.03777003e+00 2.00663239e-01] | [14.967116355895996, 5.839415550231934] |
359d5ec3-09c7-4255-b49d-73a67472f1a4 | derivation-of-the-backpropagation-algorithm | 2102.04320 | null | https://arxiv.org/abs/2102.04320v2 | https://arxiv.org/pdf/2102.04320v2.pdf | Derivation of the Backpropagation Algorithm Based on Derivative Amplification Coefficients | The backpropagation algorithm for neural networks is widely felt hard to understand, despite the existence of some well-written explanations and/or derivations. This paper provides a new derivation of this algorithm based on the concept of derivative amplification coefficients. First proposed by this author for fully connected cascade networks, this concept is found to well carry over to conventional feedforward neural networks and it paves the way for the use of mathematical induction in establishing a key result that enables backpropagation for derivative amplification coefficients. Then we establish the connection between derivative amplification coefficients and error coefficients (commonly referred to as errors in the literature), and show that the same backpropagation procedure can be used for error coefficients. The entire derivation is thus rigorous, simple, and elegant. | ['Yiping Cheng'] | 2021-02-08 | null | null | null | null | ['mathematical-induction'] | ['reasoning'] | [ 2.29694262e-01 3.24258685e-01 4.96121682e-02 -3.41049850e-01
4.70185101e-01 -3.89247924e-01 3.13698679e-01 -4.15990725e-02
-4.98862505e-01 7.48868883e-01 -3.90192509e-01 -7.14209199e-01
-5.62585354e-01 -6.94858491e-01 -5.35158813e-01 -5.71431398e-01
-3.15614820e-01 -2.28290454e-01 7.56763965e-02 -7.92806685e-01
4.64556307e-01 8.95855367e-01 -1.10437715e+00 -1.18233889e-01
3.95659745e-01 9.18036580e-01 -3.22630495e-01 9.11188722e-01
-2.97376633e-01 1.08661699e+00 -5.59221923e-01 -6.56084418e-01
5.37733920e-02 -5.27580082e-01 -9.94983792e-01 -3.11106384e-01
3.52904238e-02 -2.20437646e-01 -4.28050905e-01 9.65972185e-01
1.84530973e-01 7.37363249e-02 6.72092259e-01 -1.15081584e+00
-7.16957748e-01 6.69612586e-01 -8.96848589e-02 4.43097293e-01
-8.37294385e-02 -5.29049933e-01 8.32081378e-01 -1.05292833e+00
1.18387297e-01 9.51300144e-01 1.32396734e+00 6.36578560e-01
-1.00960553e+00 -3.29903066e-01 -3.83365713e-02 1.99827716e-01
-1.14269197e+00 -1.97726429e-01 6.94947302e-01 -2.70008534e-01
1.13010216e+00 3.40334862e-01 9.05889869e-01 5.44936180e-01
2.41416410e-01 5.82620621e-01 8.69787455e-01 -1.07004070e+00
-9.88503825e-03 5.15534699e-01 5.43552697e-01 9.58587050e-01
4.39384878e-01 3.49350452e-01 -2.94903666e-01 2.67458826e-01
1.29598880e+00 -4.79716286e-02 -4.63416189e-01 1.27362072e-01
-6.26615584e-01 8.83055389e-01 8.00863802e-01 7.71330774e-01
-1.83455855e-01 1.47457898e-01 1.09999940e-01 5.66345870e-01
2.26038367e-01 4.98415560e-01 -2.51163214e-01 2.29291245e-01
-8.66340816e-01 8.14755186e-02 1.05720866e+00 6.11944020e-01
5.14378190e-01 4.61500823e-01 4.47561204e-01 7.34179080e-01
4.52421129e-01 3.94226089e-02 4.30200338e-01 -9.59650397e-01
2.06026524e-01 3.71194869e-01 -4.86193337e-02 -1.29900396e+00
-5.90239048e-01 -9.58563507e-01 -9.83389258e-01 6.90731764e-01
5.31123936e-01 -3.28351200e-01 -5.00834465e-01 1.55499303e+00
-2.96467006e-01 -3.14868599e-01 1.12853825e-01 6.24416173e-01
5.03140450e-01 6.59316897e-01 -2.79069334e-01 -3.40470225e-01
5.46929240e-01 -1.03784347e+00 -8.72106075e-01 -1.26958182e-02
3.31404984e-01 -5.01963735e-01 6.63233459e-01 4.50596273e-01
-1.24379385e+00 -5.31248093e-01 -1.38222051e+00 1.45670578e-01
-7.69539714e-01 -2.67985202e-02 1.09438825e+00 7.45266974e-01
-1.17571366e+00 1.28988314e+00 -5.45436025e-01 -2.28333905e-01
1.11092828e-01 5.81234276e-01 6.19728900e-02 4.67760086e-01
-1.26996756e+00 1.37183344e+00 3.96568507e-01 9.04299736e-01
-3.72673385e-02 -3.45120460e-01 -5.07483304e-01 -1.66831687e-02
-2.10079283e-01 -7.81112552e-01 1.48590767e+00 -1.43084645e+00
-1.84785628e+00 5.72378695e-01 -2.12808788e-01 -6.33215189e-01
5.04772663e-01 -1.80962637e-01 -4.53258932e-01 2.82188028e-01
-5.20333350e-01 4.70943958e-01 8.48866105e-01 -8.51610541e-01
-4.81294721e-01 -2.18578801e-01 2.50737488e-01 -1.76518504e-02
-5.25160789e-01 -2.41862703e-02 1.65066347e-01 -7.08583236e-01
5.56830764e-01 -4.28624392e-01 -6.50340691e-02 3.11399817e-01
-9.28878039e-02 -2.15317413e-01 2.01013178e-01 -5.12436867e-01
1.37545586e+00 -1.97816503e+00 -1.61148429e-01 6.23535275e-01
2.48598203e-01 2.35422388e-01 3.15043837e-01 4.57063317e-01
-6.11995161e-01 6.95663691e-02 -4.34163123e-01 1.48496106e-01
-5.88707589e-02 3.17185521e-01 -4.80630934e-01 3.01949799e-01
3.82408619e-01 8.58163595e-01 -7.17289269e-01 -2.06596553e-02
5.27015366e-02 8.24155331e-01 -2.23461002e-01 -2.07558990e-01
6.41200304e-01 -3.39097917e-01 -9.66846943e-02 3.26268226e-01
3.59153837e-01 -1.29339680e-01 -2.19937459e-01 -7.12250769e-02
-3.32340747e-01 2.94144899e-01 -1.14757478e+00 8.10844839e-01
-2.22412631e-01 1.14792979e+00 1.36064906e-02 -1.27571595e+00
1.03184712e+00 4.98077482e-01 -6.71802014e-02 -1.84090436e-01
4.53406990e-01 5.92535198e-01 -2.10054498e-02 -3.95573139e-01
3.43777359e-01 -6.95582211e-01 5.59728086e-01 1.05610155e-01
1.97375193e-01 -1.73018873e-01 2.78291583e-01 1.36274472e-01
6.30575001e-01 -1.48709834e-01 2.45702744e-01 -1.68947890e-01
8.28632891e-01 5.59614487e-02 -1.33624589e-02 7.14389920e-01
-3.24551016e-02 2.36230254e-01 3.03007483e-01 -4.28702146e-01
-8.08873475e-01 -9.50001478e-01 -1.32013738e-01 8.30849528e-01
-2.06241995e-01 4.48616855e-02 -8.33186328e-01 1.53905511e-01
-1.15189128e-01 4.68798250e-01 -8.19278896e-01 -3.43505479e-02
-2.53831029e-01 -6.72267020e-01 9.06879425e-01 8.21321905e-01
6.54067576e-01 -8.38354051e-01 -3.89989257e-01 3.36348295e-01
3.21399540e-01 -6.31453216e-01 3.18170398e-01 6.51658475e-01
-1.55164540e+00 -1.01998246e+00 -1.01072466e+00 -9.52778578e-01
7.80700445e-01 -5.17265461e-02 7.70707071e-01 4.02627587e-01
1.95055753e-02 3.84286582e-01 9.81161371e-02 -5.18129766e-01
-6.01741672e-01 -1.17955752e-01 4.03388217e-02 -4.01918560e-01
2.27312341e-01 -7.21016109e-01 -2.62035072e-01 -1.16123110e-01
-7.55434096e-01 -4.60811406e-02 5.67097306e-01 7.74588585e-01
1.37908861e-01 2.50283718e-01 6.29548728e-01 -8.09012711e-01
9.70575273e-01 -2.22143494e-02 -4.68815982e-01 7.62815475e-02
-1.00761294e+00 1.00924231e-01 5.79772234e-01 -3.05452347e-01
-7.17813313e-01 -4.10082638e-01 -5.56586683e-01 9.87451300e-02
4.47696336e-02 5.41066766e-01 6.07003808e-01 -8.38131070e-01
6.68406904e-01 5.76655418e-02 1.52520230e-02 -4.06983346e-01
4.21180367e-01 4.11582440e-01 8.55561793e-01 4.78427857e-02
6.66084349e-01 1.52010575e-01 1.48997054e-01 -8.74546766e-01
-4.97032672e-01 -2.85519511e-01 -5.95196486e-01 -3.47518831e-01
3.83557558e-01 -3.52740943e-01 -6.65095031e-01 5.89942515e-01
-1.33620656e+00 -9.22473669e-02 -3.43179226e-01 6.47352815e-01
-5.97390532e-01 9.60836932e-02 -1.09208572e+00 -9.81313348e-01
-2.82750875e-01 -5.35337865e-01 -2.18149647e-01 2.98747301e-01
-2.44110569e-01 -1.66076684e+00 -7.49040693e-02 -3.92689586e-01
6.07999206e-01 3.00651379e-02 8.93138289e-01 -3.74001175e-01
-9.60221235e-03 -5.54360867e-01 -1.74095437e-01 9.58043456e-01
-1.85999542e-01 3.43959868e-01 -1.01843429e+00 2.33647212e-01
3.98143262e-01 2.30916232e-01 9.25967991e-01 2.86624402e-01
7.42819309e-01 -4.26628828e-01 -4.89107966e-02 4.78901058e-01
1.76789689e+00 7.25292042e-02 6.12911284e-01 3.97671551e-01
1.98955372e-01 5.26141286e-01 -3.94565940e-01 -2.35213451e-02
-1.42932206e-01 -1.48006767e-01 2.25931689e-01 -2.15940997e-01
1.99823603e-01 -1.27106860e-01 1.83953196e-01 1.32765031e+00
-5.46537757e-01 2.03530222e-01 -5.57952166e-01 3.49570245e-01
-1.39571893e+00 -1.27059519e+00 -4.41496253e-01 1.87425542e+00
9.25070047e-01 5.61244607e-01 8.96664411e-02 1.12058449e+00
7.46207178e-01 -3.44995886e-01 -1.81338519e-01 -1.18023849e+00
-3.13611060e-01 7.29687333e-01 6.84666216e-01 9.49185967e-01
-7.69923568e-01 4.52423811e-01 8.82951355e+00 4.09677774e-01
-1.10335720e+00 -1.78983659e-01 2.36054957e-01 3.77691925e-01
-2.57332642e-02 -1.19660497e-01 -6.36360347e-01 2.77776625e-02
9.08182323e-01 -1.78477302e-01 4.93053347e-01 7.18462586e-01
9.36635807e-02 2.00271308e-02 -1.03838611e+00 8.04781914e-01
-1.74867794e-01 -1.36606455e+00 1.40718043e-01 -4.80221927e-01
5.70926785e-01 -3.15169305e-01 3.33185792e-02 2.06660807e-01
-1.95858523e-01 -9.74801540e-01 5.45868814e-01 5.56982279e-01
1.66787207e-01 -6.01877809e-01 5.86731076e-01 2.94292301e-01
-7.51520395e-01 -3.34131867e-01 -5.13243496e-01 -8.69668007e-01
-1.55200377e-01 7.63808250e-01 -5.92607856e-01 3.21820557e-01
2.68433332e-01 4.70390469e-01 -3.34415376e-01 1.30261254e+00
-6.65781081e-01 6.50424957e-01 -4.76406872e-01 -6.02691770e-01
4.69883472e-01 -1.07461452e-01 2.73133963e-01 1.47292745e+00
6.40410036e-02 1.03560746e-01 -9.89059448e-01 1.05302072e+00
1.43508762e-01 6.07941933e-02 -4.81555015e-01 -2.39999164e-02
2.01926664e-01 1.10193861e+00 -6.34627283e-01 -2.85797983e-01
-3.18550408e-01 9.21018004e-01 -3.67868319e-02 6.51714921e-01
-5.21361947e-01 -1.16656065e+00 2.09069639e-01 2.16572378e-02
1.47446811e-01 -2.77505010e-01 -5.86975694e-01 -6.58611536e-01
-5.58748581e-02 -2.58133411e-01 -2.79890168e-02 -9.93501008e-01
-1.20487714e+00 6.22000694e-01 -1.54691488e-02 -7.65402853e-01
-4.42600459e-01 -1.31876624e+00 -8.32254946e-01 1.01292717e+00
-1.69267476e+00 -3.61872286e-01 -1.19298242e-01 5.90618670e-01
3.73489335e-02 8.41861144e-02 9.89543378e-01 3.28316092e-01
-5.18473148e-01 6.50820196e-01 1.80152297e-01 4.17446136e-01
2.31472719e-02 -1.21028197e+00 5.54419868e-02 6.90327585e-01
-2.18935087e-02 9.11144972e-01 7.83031881e-01 1.65883735e-01
-9.57905948e-01 -4.38057572e-01 1.25711715e+00 5.32859117e-02
8.22655678e-01 3.95999014e-01 -9.19662476e-01 6.75475657e-01
1.73927218e-01 -3.95078182e-01 5.14438212e-01 -7.36061856e-02
-1.45366877e-01 -1.48421854e-01 -9.18532729e-01 5.88726521e-01
6.83273852e-01 -4.67420846e-01 -1.09987223e+00 5.37190773e-02
4.13413703e-01 -1.65426925e-01 -6.93149388e-01 2.39694342e-01
7.88923025e-01 -1.20848811e+00 8.72052550e-01 -5.23952603e-01
3.69342864e-01 9.61117819e-03 7.72549659e-02 -1.09840834e+00
-3.57275486e-01 -7.94520020e-01 -1.45398408e-01 7.32282400e-01
7.42826521e-01 -1.20447147e+00 3.83356571e-01 4.51033056e-01
-4.98967357e-02 -1.07140124e+00 -6.95113599e-01 -8.18037629e-01
4.15230364e-01 -6.23720348e-01 4.74645309e-02 8.37652564e-01
5.01980662e-01 3.97402316e-01 3.34780425e-01 -1.25198573e-01
3.96563023e-01 -4.39521581e-01 -1.00909941e-01 -1.38041258e+00
-2.52078801e-01 -1.15170372e+00 -4.72677141e-01 -1.35118353e+00
-2.63182551e-01 -6.80015385e-01 -9.49767232e-02 -1.67556727e+00
-6.31695211e-01 -4.19969618e-01 -5.45814693e-01 3.59485239e-01
9.64263231e-02 4.23753262e-01 -2.03602184e-02 1.90986112e-01
1.86264321e-01 -1.74171440e-02 1.02268469e+00 1.05008848e-01
-2.17134371e-01 4.67014402e-01 -7.37708867e-01 1.28718317e+00
1.04983306e+00 -3.05225462e-01 -4.37993735e-01 -3.86354536e-01
8.01428556e-01 -2.15696111e-01 6.43746376e-01 -1.26941919e+00
3.65803629e-01 3.67096424e-01 6.34187043e-01 -4.43703413e-01
2.37969473e-01 -8.50724936e-01 -1.86003298e-01 6.24689698e-01
-7.08309829e-01 2.46094853e-01 2.18284920e-01 2.54257411e-01
-3.02400529e-01 -1.03114772e+00 7.00408220e-01 -2.06983373e-01
-7.48907208e-01 -1.92296162e-01 -4.01603490e-01 -2.19328359e-01
3.36780608e-01 -6.30045295e-01 3.02755018e-03 -4.48046505e-01
-1.13058209e+00 -2.44743302e-01 -1.40402645e-01 -1.57691330e-01
8.39314640e-01 -1.16589248e+00 -2.89415270e-01 3.62606138e-01
-6.05624914e-01 -4.38557386e-01 -3.31304520e-01 1.06597841e+00
-9.00231421e-01 4.68266517e-01 -2.02925250e-01 -1.70226455e-01
-8.39250922e-01 2.73111522e-01 9.53415215e-01 1.29173905e-01
-3.62545222e-01 1.31993151e+00 -4.54680681e-01 3.21533792e-02
5.14337361e-01 -5.71037591e-01 -2.44223267e-01 -1.60158172e-01
7.98435390e-01 5.51593602e-01 1.08118549e-01 -9.81812701e-02
-2.30770856e-01 8.50189805e-01 4.17196691e-01 -3.15313995e-01
1.29534614e+00 4.92376648e-02 -4.12722468e-01 9.26830173e-01
1.19233811e+00 -3.07183087e-01 -7.50607252e-01 -8.51426870e-02
-1.50077462e-01 2.17960492e-01 5.68229370e-02 -7.92178512e-01
-7.89415956e-01 1.39001274e+00 4.88407850e-01 7.53389955e-01
1.26143384e+00 -6.12052500e-01 4.55709457e-01 8.86612773e-01
3.14535499e-02 -1.06926084e+00 -2.47906610e-01 8.09429705e-01
8.63891184e-01 -6.16570234e-01 1.81098282e-02 -4.94554371e-01
-8.22516717e-03 1.91763186e+00 6.82843700e-02 -5.08719921e-01
9.45305705e-01 4.38441962e-01 1.20936342e-01 1.36355191e-01
-5.06502450e-01 5.93504794e-02 -1.65705418e-03 5.75914323e-01
6.74209774e-01 -2.13344991e-01 -5.49974561e-01 4.95854497e-01
-4.21148777e-01 4.50812310e-01 4.93818939e-01 8.66324782e-01
-8.99401307e-01 -7.58569539e-01 -4.57754076e-01 -2.23446870e-03
-5.42418897e-01 -3.78932655e-01 -3.70549530e-01 1.07987416e+00
1.08450152e-01 8.06565464e-01 4.32027020e-02 -3.76026005e-01
4.13339257e-01 3.03592533e-01 1.05770671e+00 -1.03319496e-01
-6.81109667e-01 -3.72874975e-01 -2.38610029e-01 6.31423742e-02
-7.13410378e-01 1.51710823e-01 -1.49982822e+00 -7.02930629e-01
-5.38323402e-01 3.95535588e-01 9.03260231e-01 1.02081680e+00
-2.73659408e-01 7.25194097e-01 4.71809536e-01 -7.84252346e-01
-7.87634432e-01 -9.64182377e-01 -6.60728276e-01 -1.90752879e-01
4.26190555e-01 -4.16131347e-01 -6.85474932e-01 8.95806476e-02] | [8.043670654296875, 3.391005277633667] |
dd9a1068-2a87-4ca6-a09a-c7ab1f8ae90a | cyber-attack-detection-thanks-to-machine | 2001.06309 | null | https://arxiv.org/abs/2001.06309v1 | https://arxiv.org/pdf/2001.06309v1.pdf | Cyber Attack Detection thanks to Machine Learning Algorithms | Cybersecurity attacks are growing both in frequency and sophistication over the years. This increasing sophistication and complexity call for more advancement and continuous innovation in defensive strategies. Traditional methods of intrusion detection and deep packet inspection, while still largely used and recommended, are no longer sufficient to meet the demands of growing security threats. As computing power increases and cost drops, Machine Learning is seen as an alternative method or an additional mechanism to defend against malwares, botnets, and other attacks. This paper explores Machine Learning as a viable solution by examining its capabilities to classify malicious traffic in a network. First, a strong data analysis is performed resulting in 22 extracted features from the initial Netflow datasets. All these features are then compared with one another through a feature selection process. Then, our approach analyzes five different machine learning algorithms against NetFlow dataset containing common botnets. The Random Forest Classifier succeeds in detecting more than 95% of the botnets in 8 out of 13 scenarios and more than 55% in the most difficult datasets. Finally, insight is given to improve and generalize the results, especially through a bootstrapping technique. | ['Antoine Delplace', 'Sheryl Hermoso', 'Kristofer Anandita'] | 2020-01-17 | null | null | null | null | ['cyber-attack-detection'] | ['miscellaneous'] | [ 7.09702298e-02 -2.72834003e-01 -3.31286490e-01 -1.68041036e-01
2.35589053e-02 -1.00344241e+00 6.27973914e-01 3.33288163e-01
-4.13621366e-01 6.96987867e-01 -5.69341302e-01 -8.62837851e-01
-2.16059044e-01 -8.17868769e-01 2.00547889e-01 -4.98487592e-01
-3.87404799e-01 4.88302559e-01 7.02569425e-01 -2.80416161e-01
6.55835986e-01 1.02815330e+00 -1.32777512e+00 1.51542395e-01
5.57650805e-01 9.31776047e-01 -2.52597392e-01 7.69507170e-01
-2.91634083e-01 7.34312415e-01 -9.03374076e-01 -5.54305255e-01
5.16769052e-01 -2.14403287e-01 -9.00954306e-01 9.06056818e-03
5.65608293e-02 -2.87846953e-01 -1.36830956e-01 9.19238627e-01
1.77207649e-01 -3.29346120e-01 1.30345449e-01 -1.55986679e+00
3.02691460e-01 4.65409338e-01 -6.33930922e-01 5.80309927e-01
1.45918444e-01 3.86787981e-01 8.11592400e-01 -2.28201136e-01
4.83213782e-01 1.21640503e+00 4.45002705e-01 3.70581865e-01
-1.18182290e+00 -7.88402557e-01 -2.36651655e-02 3.01335663e-01
-7.93527842e-01 -1.55183271e-01 7.57899761e-01 -4.12523031e-01
8.56514752e-01 3.81300837e-01 5.76834679e-01 9.96208429e-01
1.51352912e-01 9.64686945e-02 1.17871606e+00 -4.49680001e-01
2.89446652e-01 6.65535629e-01 3.89336944e-01 5.66230416e-01
8.71285796e-01 2.69055218e-01 1.77126437e-01 -5.28453529e-01
5.14381289e-01 2.17504948e-01 2.63431184e-02 -6.34333044e-02
-6.73317313e-01 1.07764816e+00 1.97031617e-01 6.14179552e-01
-3.10512185e-01 -5.19509733e-01 7.90304005e-01 5.78984439e-01
2.16089427e-01 8.82026911e-01 -7.32779920e-01 -3.86779040e-01
-9.23863530e-01 3.78469974e-02 1.12090492e+00 1.21621855e-01
6.94632947e-01 2.79260278e-01 5.25984585e-01 3.43702018e-01
1.63676322e-01 2.27383360e-01 2.23969385e-01 -6.55458152e-01
1.04214936e-01 8.90351295e-01 -2.82331139e-01 -1.24445462e+00
-4.41043437e-01 -5.70142806e-01 -5.52044809e-01 7.91216791e-01
6.34677708e-01 -1.75947577e-01 -6.24734879e-01 1.27645719e+00
3.06674659e-01 3.54615971e-02 -3.40687126e-01 2.89359123e-01
1.67169288e-01 3.57884079e-01 1.56018749e-01 -3.25489759e-01
1.31960905e+00 -4.04728085e-01 -2.84308732e-01 -2.21033562e-02
4.04805303e-01 -7.82893062e-01 4.68114227e-01 5.90134740e-01
-5.05959928e-01 -2.89587349e-01 -8.72280359e-01 8.62147570e-01
-6.83455586e-01 -5.04397690e-01 6.89098895e-01 1.39703608e+00
-6.81307077e-01 7.05656171e-01 -6.37988687e-01 -5.61979294e-01
5.96131742e-01 3.58509213e-01 -2.68229038e-01 1.53288126e-01
-8.14037621e-01 8.85521531e-01 4.60445046e-01 -3.16169977e-01
-6.58162475e-01 -5.78175485e-01 -3.22052419e-01 2.07270667e-01
4.24409240e-01 -1.65119469e-02 8.01353097e-01 -7.38317311e-01
-1.14812851e+00 7.73612440e-01 3.42776209e-01 -7.65935719e-01
5.07848024e-01 1.45352304e-01 -8.29153836e-01 3.52169722e-01
-3.52546684e-02 1.42362565e-01 1.03873050e+00 -1.24946618e+00
-8.78683329e-01 -3.25111300e-01 2.32448727e-01 -7.82624245e-01
-4.26237136e-01 5.37802696e-01 4.22105670e-01 -3.98056835e-01
-3.43760140e-02 -7.81865776e-01 -2.95628518e-01 -3.51689845e-01
-5.15295386e-01 -5.76706044e-02 1.50317228e+00 -4.17720020e-01
1.20684540e+00 -1.77357149e+00 -3.58068258e-01 7.22204983e-01
4.98916090e-01 9.74823654e-01 1.42317623e-01 5.05536199e-01
-2.73022443e-01 6.20276034e-01 2.40137819e-02 1.24330170e-01
-1.37626097e-01 1.44800007e-01 -5.60957730e-01 1.88892826e-01
4.24282193e-01 3.00430208e-01 -6.74618304e-01 -2.59168029e-01
4.95247185e-01 2.66253501e-01 -4.80209261e-01 9.38298032e-02
8.00946727e-02 5.62562466e-01 -4.31210041e-01 8.23300838e-01
6.30969763e-01 -1.22014008e-01 2.59891480e-01 1.46791652e-01
-2.13414997e-01 1.55425653e-01 -9.67032790e-01 5.39029419e-01
-2.00593427e-01 5.87259054e-01 8.03772509e-02 -1.22393239e+00
1.08424783e+00 1.83855727e-01 5.76398849e-01 -4.12277281e-01
4.11759019e-01 3.33001912e-01 5.37553489e-01 -3.96139741e-01
-5.40470108e-02 -5.77473119e-02 6.21440597e-02 6.31517351e-01
-5.20341136e-02 3.47767144e-01 4.87692833e-01 2.21073195e-01
1.56364954e+00 -5.35802841e-01 3.83668274e-01 -2.73556113e-01
9.10133958e-01 7.17428103e-02 6.00706100e-01 7.84881473e-01
-7.87182927e-01 -2.39951789e-01 9.37024474e-01 -9.37474966e-01
-7.73658454e-01 -1.02106261e+00 -9.89652425e-02 8.00940514e-01
-2.28735775e-01 -3.44526023e-01 -6.11027956e-01 -1.23142588e+00
-4.27273996e-02 4.75750536e-01 -3.36957067e-01 -2.27265656e-01
-6.07502282e-01 -7.47674406e-01 6.67378485e-01 1.84036512e-02
7.07940996e-01 -1.25905645e+00 -9.17316616e-01 1.36610270e-01
1.49026483e-01 -1.36581504e+00 5.04733741e-01 2.24274218e-01
-9.91592944e-01 -1.52561283e+00 1.32574484e-01 -2.77183473e-01
3.84593934e-01 3.12105447e-01 1.03461504e+00 5.09703696e-01
-8.75693500e-01 6.00877665e-02 -5.48477829e-01 -5.03058791e-01
-8.83611441e-01 1.90283418e-01 1.80895552e-01 -3.35951038e-02
4.99531716e-01 -8.78811181e-01 -2.23654345e-01 2.91455448e-01
-6.91360414e-01 -8.00206721e-01 7.02199101e-01 4.01423395e-01
-2.57380307e-01 6.71768665e-01 7.66232252e-01 -1.01518190e+00
5.07955551e-01 -6.32597744e-01 -7.14606524e-01 -1.23778313e-01
-7.39276111e-01 -2.27945253e-01 9.45884049e-01 -5.34914732e-01
-6.67595088e-01 -3.75640601e-01 -1.23840161e-01 -2.49767959e-01
-6.17729902e-01 4.90505695e-02 -1.24452263e-01 -3.73491615e-01
9.27550077e-01 -1.53999567e-01 2.22933218e-01 -4.91329968e-01
-1.57215253e-01 5.29738367e-01 -3.33974846e-02 -2.71871895e-01
1.34399986e+00 5.08118987e-01 2.21346036e-01 -1.12731767e+00
-4.52951461e-01 -2.50257224e-01 -6.39796555e-01 -4.10787553e-01
5.08415461e-01 5.97119667e-02 -9.88935113e-01 4.11310971e-01
-8.74793947e-01 1.67834833e-01 -6.42994046e-02 3.15241486e-01
8.03419501e-02 5.73192000e-01 -5.29953301e-01 -9.78731811e-01
-1.53798893e-01 -1.04284680e+00 2.65389889e-01 3.18596601e-01
-1.83598027e-01 -1.04780340e+00 9.43332911e-02 4.03448492e-01
7.83981264e-01 4.29385722e-01 1.09873056e+00 -1.29595554e+00
-4.33111370e-01 -7.64607012e-01 -3.86351705e-01 4.00772482e-01
3.90002340e-01 4.61233377e-01 -8.56617928e-01 -4.67462540e-01
1.74974829e-01 -6.39014170e-02 5.33610821e-01 -5.16559444e-02
9.31592584e-01 -3.01553339e-01 -3.61855954e-01 3.06802511e-01
1.44520295e+00 6.31968856e-01 6.35862410e-01 6.25143647e-01
3.62448215e-01 8.06904972e-01 3.43265504e-01 4.40113157e-01
-3.28847855e-01 3.81739169e-01 9.40145731e-01 7.91660249e-02
3.88546109e-01 1.10994160e-01 2.42574021e-01 1.42971158e-01
-1.28053710e-01 -3.18222381e-02 -1.11835313e+00 9.74844955e-03
-1.26459038e+00 -1.33607221e+00 -1.81070238e-01 2.13940501e+00
1.54465869e-01 7.27096498e-01 6.44567370e-01 7.09208965e-01
7.67506897e-01 7.03446269e-02 -4.06290680e-01 -6.72973096e-01
1.89591035e-01 5.06757796e-01 3.07054967e-01 2.21014440e-01
-1.09497046e+00 8.28544855e-01 6.44184446e+00 4.48536843e-01
-1.38792527e+00 -2.72128552e-01 6.05015218e-01 3.54314357e-01
3.89745563e-01 2.95759559e-01 -7.06662893e-01 5.38170636e-01
1.12812948e+00 1.01048894e-01 3.03073525e-01 8.42717767e-01
2.39269778e-01 -4.07972150e-02 -4.26816225e-01 6.92158997e-01
-2.80205280e-01 -1.27860737e+00 4.37903441e-02 3.73181432e-01
1.36272222e-01 -2.12053657e-01 -5.73280156e-02 4.14742947e-01
3.25278550e-01 -7.53456235e-01 7.40638599e-02 -7.42700044e-03
2.00704634e-01 -8.26249063e-01 9.06868219e-01 4.16392028e-01
-9.32903647e-01 -6.26888156e-01 -8.98259953e-02 -3.29141289e-01
1.01239197e-01 6.27458930e-01 -8.46238196e-01 4.78110760e-01
7.85721600e-01 3.12213838e-01 -7.45538354e-01 1.02744937e+00
1.21885594e-02 9.42664385e-01 -2.92898357e-01 9.47841108e-02
2.39001319e-01 1.19369820e-01 7.38727987e-01 1.22426033e+00
-2.86250979e-01 -2.18059212e-01 3.79731178e-01 6.02570593e-01
3.91782045e-01 -1.58579573e-02 -6.79700673e-01 -2.68943280e-01
5.05470514e-01 1.76472437e+00 -1.21051133e+00 -1.72173887e-01
-2.39192814e-01 5.38024187e-01 4.31561507e-02 1.24730214e-01
-9.53908563e-01 -6.27647281e-01 9.79465067e-01 4.25509602e-01
8.61937627e-02 -2.66598403e-01 -3.04675937e-01 -1.01309228e+00
-3.28984708e-01 -1.20496631e+00 5.53692520e-01 1.32209301e-01
-1.27090192e+00 8.74182701e-01 -1.45047270e-02 -1.04911363e+00
-2.76373029e-01 -8.78910303e-01 -1.02343285e+00 5.17230213e-01
-1.32082272e+00 -8.23959827e-01 -2.05069631e-01 4.23938364e-01
3.74020100e-01 -7.62903333e-01 8.83706868e-01 4.30347472e-01
-7.80086339e-01 3.06498677e-01 -3.34541261e-01 3.69498819e-01
3.52501214e-01 -8.32228601e-01 1.42094523e-01 9.56314206e-01
6.17506243e-02 6.52911901e-01 6.90803766e-01 -6.21295452e-01
-9.28857148e-01 -8.08584332e-01 5.98392308e-01 -2.77915120e-01
9.67678487e-01 -2.71302283e-01 -8.67612004e-01 4.53204811e-01
2.74900198e-02 -9.40205902e-02 7.43287921e-01 -1.07838288e-01
-6.41455412e-01 -1.77315027e-01 -1.63462400e+00 3.84791195e-01
4.49509442e-01 -2.01207265e-01 -1.98567539e-01 7.33222291e-02
2.97799438e-01 4.80039328e-01 -6.66809738e-01 4.39668983e-01
3.87994826e-01 -1.38760936e+00 7.53602445e-01 -1.04940426e+00
-7.65392482e-02 -1.27695099e-01 -7.55106434e-02 -6.57622218e-01
-2.73544222e-01 -8.83921266e-01 -7.57150576e-02 1.36382544e+00
2.55385667e-01 -1.09650433e+00 1.10832250e+00 6.06859997e-02
5.08569121e-01 -6.62434757e-01 -7.83464789e-01 -8.73596668e-01
-6.43048882e-02 -3.49200159e-01 2.62987882e-01 1.15948892e+00
3.21450680e-02 2.14260951e-01 -9.67513118e-03 -4.96390052e-02
9.29623902e-01 -8.96261409e-02 8.36067855e-01 -1.77521670e+00
-2.35493556e-01 -6.83302164e-01 -1.04955292e+00 -1.10951908e-01
9.15932730e-02 -5.34840047e-01 -7.68949032e-01 -8.54955077e-01
-8.80823061e-02 -4.37185705e-01 -1.62616983e-01 4.32647377e-01
2.37460092e-01 3.52129430e-01 2.49202475e-01 1.79765970e-01
-7.77426213e-02 -2.55859077e-01 5.42129636e-01 8.98899138e-02
-1.59553662e-01 4.54265952e-01 -6.42720222e-01 9.84196246e-01
1.37828481e+00 -4.45910513e-01 -3.39616299e-01 4.19235289e-01
-2.20263615e-01 -1.83857188e-01 4.53772724e-01 -1.20637369e+00
-2.24285126e-01 -1.60745203e-01 2.99030989e-01 -3.09140116e-01
5.50570711e-02 -1.16367948e+00 -1.79868877e-01 1.03242421e+00
9.56211314e-02 2.58905262e-01 2.44120359e-01 3.57481211e-01
-2.72980165e-02 -2.25083083e-01 1.27333486e+00 -1.54678702e-01
-5.58483839e-01 2.30204418e-01 -7.84499705e-01 -1.01644754e-01
1.45039892e+00 -4.60329533e-01 -3.54076058e-01 -2.06756353e-01
-8.25454116e-01 -1.00845814e-01 2.50879586e-01 5.95922828e-01
3.82711947e-01 -5.48716486e-01 -5.36963582e-01 4.74120259e-01
-2.72059351e-01 -8.75836968e-01 -5.12809828e-02 7.24344015e-01
-7.38262117e-01 4.37970310e-01 -6.60569787e-01 -5.01110375e-01
-1.59286225e+00 7.52887964e-01 3.15155119e-01 -6.69980884e-01
-4.59839404e-01 3.98755819e-01 -5.59427440e-01 -1.55869648e-01
2.51190215e-01 2.39943951e-01 -4.15620059e-01 -1.06924716e-02
6.78897977e-01 8.12493324e-01 -8.99179429e-02 -5.00901461e-01
-5.23422539e-01 1.54773757e-01 -4.87980008e-01 1.44604489e-01
1.18972385e+00 2.43665755e-01 -4.30946916e-01 4.58044447e-02
9.51600790e-01 4.44616098e-03 -5.77096701e-01 1.32172376e-01
5.99536836e-01 -7.12758243e-01 -3.28043371e-01 -8.38525236e-01
-1.10689235e+00 8.73986959e-01 5.95535755e-01 1.10845423e+00
1.16809249e+00 -3.10105294e-01 5.54207981e-01 3.51175457e-01
5.21310687e-01 -4.62731093e-01 1.29602507e-01 5.49411774e-01
1.19638667e-02 -1.20760894e+00 -1.34558842e-01 -5.77163160e-01
-3.04264665e-01 1.45705593e+00 6.63580537e-01 -2.81686753e-01
8.76387656e-01 4.35558617e-01 8.02798644e-02 -2.02658921e-01
-6.69877946e-01 2.62040049e-02 -5.24213493e-01 8.24572742e-01
1.65254489e-01 -7.92992488e-02 -2.81120420e-01 7.92903453e-02
-6.28521442e-02 -4.97752279e-01 5.92619002e-01 9.70542252e-01
-9.47482169e-01 -1.47431445e+00 -3.74361783e-01 6.21254504e-01
-8.00314903e-01 2.80401826e-01 -7.06270874e-01 1.00412047e+00
6.26479089e-02 1.29501057e+00 -2.03415155e-01 -7.14542150e-01
1.21400088e-01 1.03801496e-01 -6.04298059e-03 -4.13254201e-01
-9.52781975e-01 -3.94241065e-01 -5.17180637e-02 -5.61952353e-01
-4.48455736e-02 -5.14602005e-01 -1.01989830e+00 -7.72410929e-01
-3.91322017e-01 3.69706839e-01 8.56465399e-01 7.91488707e-01
1.89086065e-01 3.92581880e-01 1.08966267e+00 -6.15381002e-01
-7.76547313e-01 -6.83604658e-01 -4.50494349e-01 2.48060703e-01
1.33637875e-01 -6.60477638e-01 -7.75273681e-01 -3.29439223e-01] | [5.218775749206543, 7.224337577819824] |
f5e32c8d-9fa3-4d61-bfc6-539fb90ab1c5 | n-best-hypotheses-reranking-for-text-to-sql | 2210.10668 | null | https://arxiv.org/abs/2210.10668v1 | https://arxiv.org/pdf/2210.10668v1.pdf | N-Best Hypotheses Reranking for Text-To-SQL Systems | Text-to-SQL task maps natural language utterances to structured queries that can be issued to a database. State-of-the-art (SOTA) systems rely on finetuning large, pre-trained language models in conjunction with constrained decoding applying a SQL parser. On the well established Spider dataset, we begin with Oracle studies: specifically, choosing an Oracle hypothesis from a SOTA model's 10-best list, yields a $7.7\%$ absolute improvement in both exact match (EM) and execution (EX) accuracy, showing significant potential improvements with reranking. Identifying coherence and correctness as reranking approaches, we design a model generating a query plan and propose a heuristic schema linking algorithm. Combining both approaches, with T5-Large, we obtain a consistent $1\% $ improvement in EM accuracy, and a $~2.5\%$ improvement in EX, establishing a new SOTA for this task. Our comprehensive error studies on DEV data show the underlying difficulty in making progress on this task. | ['Dilek Hakkani-Tur', 'Sree Hari Krishnan Parthasarathi', 'Lu Zeng'] | 2022-10-19 | null | null | null | null | ['text-to-sql'] | ['computer-code'] | [ 3.22605819e-01 4.69741970e-01 -3.99877876e-01 -7.75641382e-01
-1.51544106e+00 -6.55239224e-01 4.59781766e-01 3.90898973e-01
-4.48963732e-01 2.92942554e-01 2.49979511e-01 -5.24900317e-01
-8.61871764e-02 -8.73990059e-01 -1.13478911e+00 3.48414689e-01
-1.72772542e-01 1.00462592e+00 5.20950317e-01 -2.42970139e-01
3.26776505e-01 2.26180200e-02 -1.51302338e+00 6.88130319e-01
6.75595939e-01 1.16050422e+00 -8.01877379e-02 6.43086314e-01
-6.45368814e-01 9.72996414e-01 -5.90929031e-01 -7.77936637e-01
1.69019580e-01 -1.09187797e-01 -1.05036092e+00 -4.51753646e-01
7.28320897e-01 -2.94607162e-01 5.72939180e-02 6.59010053e-01
3.09964895e-01 -3.56091589e-01 1.61642104e-01 -1.16404653e+00
-1.55329183e-01 1.09875202e+00 -2.79396713e-01 -1.53877437e-01
7.48889804e-01 -2.88858283e-02 1.51672733e+00 -7.75274158e-01
9.56644595e-01 1.04274344e+00 5.73258400e-01 2.07152322e-01
-1.52461779e+00 -5.55583835e-01 -5.55532873e-02 1.01682590e-02
-1.47790504e+00 -7.34314084e-01 3.38108659e-01 -2.14128301e-01
1.74783659e+00 5.14186203e-01 2.56422460e-01 6.15613043e-01
-2.19671763e-02 9.40019131e-01 1.02164495e+00 -4.60567415e-01
1.49228752e-01 2.82656163e-01 1.60643175e-01 8.01364899e-01
9.77269933e-02 -2.61568241e-02 -7.76580393e-01 -3.38476181e-01
1.79034278e-01 -4.06634092e-01 1.90390408e-01 -5.37504613e-01
-1.11838639e+00 5.79151928e-01 1.17316827e-01 -5.24567626e-02
-1.41694233e-01 2.55320132e-01 4.98921216e-01 5.80015779e-01
2.64712349e-02 9.42017019e-01 -7.25248933e-01 -6.26171649e-01
-1.04568195e+00 6.10374928e-01 1.23601115e+00 1.53963244e+00
8.78688693e-01 -3.60394746e-01 -9.11021009e-02 7.38884151e-01
3.86372879e-02 6.39419317e-01 1.05539672e-01 -1.17696357e+00
8.46224904e-01 9.45960760e-01 3.04606259e-02 -6.02038026e-01
-2.95039564e-01 -3.95047456e-01 4.64699119e-02 -2.79810220e-01
3.45838517e-01 2.43974224e-01 -6.40778244e-01 1.86991227e+00
9.69033875e-03 -4.46879685e-01 1.74825743e-01 2.97829002e-01
2.42617041e-01 3.29828143e-01 -7.26919249e-02 -3.18242222e-01
1.37252831e+00 -4.90417689e-01 -3.05104643e-01 -4.45452064e-01
9.59230185e-01 -7.71976292e-01 1.55016005e+00 5.53002238e-01
-1.34209025e+00 -2.97228396e-01 -9.95782793e-01 -9.17887241e-02
-1.91934064e-01 -2.41646871e-01 7.64913797e-01 4.45983112e-01
-9.06126618e-01 3.16968113e-01 -9.51109827e-01 -5.59731305e-01
1.02319300e-01 3.34225267e-01 -1.93362862e-01 -9.72751006e-02
-7.70761490e-01 8.02200377e-01 3.86895239e-01 -5.33462644e-01
-7.02993393e-01 -8.27521622e-01 -5.96248150e-01 1.85457263e-02
1.01354539e+00 -5.09703696e-01 1.67014134e+00 -1.08910404e-01
-1.12447345e+00 9.54693556e-01 -5.65590501e-01 -7.20040858e-01
3.31673741e-01 -4.53374296e-01 -3.98447633e-01 -1.13811791e-01
2.39830971e-01 6.44104600e-01 2.66828299e-01 -9.29736376e-01
-8.03405643e-01 -3.51575971e-01 1.77085236e-01 -6.65323883e-02
-2.05509067e-01 2.15729043e-01 -6.89213872e-01 -3.35520357e-01
3.30754519e-01 -7.52817869e-01 -6.67315023e-03 -3.37476313e-01
-5.46219468e-01 -4.03055251e-01 2.19901338e-01 -6.00115120e-01
1.91535163e+00 -1.82302237e+00 -5.93607835e-02 4.08305287e-01
2.80580670e-01 -2.28157833e-01 -9.10457373e-02 6.50390685e-01
2.19685510e-01 3.58579874e-01 -2.74145544e-01 1.11423638e-02
4.45704222e-01 9.26866159e-02 -6.46775126e-01 -2.62175441e-01
3.29271853e-01 1.09061289e+00 -5.08692801e-01 -6.57204092e-01
-3.53445590e-01 -4.67869014e-01 -1.07396889e+00 5.91179371e-01
-9.50971305e-01 -4.75845128e-01 -2.32071474e-01 6.99780405e-01
2.97209829e-01 -3.57675940e-01 4.93846565e-01 -1.17585532e-01
-3.78625765e-02 9.36281323e-01 -1.15844715e+00 1.82191801e+00
-4.65461254e-01 4.04356420e-01 -1.18422724e-01 -6.51347995e-01
8.98933351e-01 -1.59984246e-01 4.35209990e-01 -1.09884799e+00
-4.10440326e-01 4.93679672e-01 -1.62944913e-01 -7.24696040e-01
6.10936344e-01 2.71766275e-01 -4.20586020e-01 7.22834289e-01
-7.54048210e-03 -3.92487854e-01 2.86088288e-01 4.16344821e-01
1.55413079e+00 1.31231159e-01 1.88034028e-01 -2.45626882e-01
-5.62180765e-03 5.34330845e-01 3.96033347e-01 9.60223556e-01
2.56959438e-01 2.79318511e-01 8.36147606e-01 -2.86313325e-01
-1.23061264e+00 -9.37384248e-01 -1.19672425e-01 1.40096819e+00
-1.28843680e-01 -9.81015921e-01 -9.06932831e-01 -7.71660149e-01
1.94643855e-01 1.22689962e+00 -2.75157690e-01 3.49946506e-02
-9.83047068e-01 -2.83094049e-01 9.28746104e-01 7.03803420e-01
2.97305942e-01 -8.37196231e-01 -7.43372381e-01 3.38846266e-01
-2.10645288e-01 -1.17634618e+00 -4.20475304e-01 5.34197986e-01
-6.76660299e-01 -1.11856985e+00 1.12172022e-01 -4.11440581e-01
2.76044726e-01 -1.23257302e-01 1.71401763e+00 5.46793528e-02
-1.54595807e-01 2.28904918e-01 -9.80814472e-02 -3.79668057e-01
-5.77216506e-01 4.47582006e-01 -1.72828525e-01 -7.61220276e-01
7.07061768e-01 -2.39335701e-01 -2.47332290e-01 3.67705584e-01
-8.07736099e-01 7.53065944e-02 7.40795612e-01 8.13482881e-01
7.40601897e-01 -2.74736732e-01 3.57450664e-01 -1.37049425e+00
4.86760855e-01 -3.23022902e-01 -8.71476412e-01 6.69057012e-01
-1.47894084e+00 6.08017743e-01 4.24028724e-01 -7.76214749e-02
-7.78534353e-01 -1.37928426e-01 -2.91207016e-01 -3.94787267e-02
-1.72413379e-01 8.05370569e-01 -2.17218384e-01 2.85502762e-01
9.76941049e-01 2.16505349e-01 -2.02105790e-01 -3.97993207e-01
5.73453128e-01 4.50774074e-01 7.29434013e-01 -1.03006470e+00
6.03842318e-01 -6.54629618e-02 -3.95921648e-01 -2.65507013e-01
-6.78710580e-01 -2.54455686e-01 -3.13818514e-01 3.56235564e-01
4.49003339e-01 -7.85199821e-01 -8.62297535e-01 -4.04573716e-02
-9.39532757e-01 -4.62392896e-01 -2.65596122e-01 1.04698412e-01
-8.09571147e-01 1.98658764e-01 -3.44298035e-01 -6.11149967e-01
-4.16226983e-01 -1.03008008e+00 1.04116058e+00 -2.97077060e-01
-6.35296047e-01 -4.38423514e-01 8.82446840e-02 5.22025168e-01
5.89223981e-01 -1.98557183e-01 1.48616648e+00 -1.04197669e+00
-9.45294082e-01 -1.95848405e-01 -3.79518181e-01 5.21541480e-03
-4.99461681e-01 -6.37600645e-02 -6.94073021e-01 -2.09764451e-01
-1.58149377e-01 -6.47576272e-01 5.07491350e-01 -1.91497877e-01
1.08184767e+00 -4.53688294e-01 -2.77492017e-01 6.11932456e-01
1.45896530e+00 2.78091282e-01 5.01051366e-01 3.52022856e-01
2.59911120e-01 4.76891667e-01 7.69947469e-01 3.41639668e-01
7.20433712e-01 8.45074296e-01 3.54236811e-01 4.14659262e-01
1.91843006e-04 -8.13263237e-01 2.66789049e-01 6.88252628e-01
5.95126987e-01 -1.30891412e-01 -1.34308648e+00 6.03792489e-01
-1.66302252e+00 -6.91643536e-01 1.44941658e-01 2.37778473e+00
1.13208306e+00 7.62496531e-01 9.43851024e-02 -1.90870628e-01
1.96452618e-01 -4.13835719e-02 -7.14791477e-01 -3.71292323e-01
-5.29027022e-02 5.53760707e-01 6.06328130e-01 4.08535749e-01
-7.14844227e-01 1.11484385e+00 7.11514568e+00 8.31741452e-01
-1.09345937e+00 -1.30289599e-01 3.68162781e-01 -2.33289912e-01
-8.68765056e-01 3.76299441e-01 -9.90649164e-01 2.79652297e-01
1.40018284e+00 -3.65604997e-01 7.54601717e-01 1.00812137e+00
-3.05369645e-01 -2.65435845e-01 -1.60545480e+00 7.61343241e-01
-1.51648074e-02 -1.45920622e+00 -9.06540304e-02 -4.51896340e-02
2.95517117e-01 2.73360610e-01 -2.48016715e-01 7.15970874e-01
5.13633490e-01 -9.77568984e-01 9.10186470e-01 5.32142520e-01
1.09460175e+00 -5.60095131e-01 5.63823521e-01 4.73984689e-01
-9.57734704e-01 1.76323541e-02 -1.45122871e-01 2.96021193e-01
-2.53945030e-02 2.66235560e-01 -1.23479223e+00 4.02312994e-01
7.31883526e-01 1.17358498e-01 -8.27030897e-01 5.13346195e-01
-1.32090552e-02 7.56650031e-01 -5.97817123e-01 -2.17374787e-01
-2.37029403e-01 2.73974925e-01 2.94034749e-01 1.40263355e+00
2.45484456e-01 1.27012029e-01 1.57949224e-01 1.03277564e+00
-3.38000625e-01 1.29552558e-01 -5.15851140e-01 -4.65636313e-01
9.57371414e-01 7.21955001e-01 -2.04018265e-01 -6.08991027e-01
-4.22800988e-01 6.02713525e-01 5.53671896e-01 1.07357465e-01
-7.76931286e-01 -6.20838165e-01 4.06158239e-01 3.56068641e-01
3.32957745e-01 -1.47612318e-01 -4.38713372e-01 -1.14781308e+00
4.67809260e-01 -1.35280323e+00 4.94317204e-01 -6.76199019e-01
-8.51807654e-01 7.06799030e-01 2.61952043e-01 -7.15259373e-01
-8.01932454e-01 -2.93693841e-01 -1.08291745e-01 6.32784784e-01
-1.04529262e+00 -8.92919004e-01 -1.09117061e-01 2.29929522e-01
3.81530046e-01 -1.77242190e-01 8.94364357e-01 4.29232746e-01
-4.22591060e-01 1.12424958e+00 -2.40254223e-01 -2.01333947e-02
7.88634062e-01 -1.44145226e+00 7.54716754e-01 8.15778196e-01
3.27203512e-01 1.20105946e+00 7.11967349e-01 -5.87332010e-01
-1.96457183e+00 -8.67916226e-01 1.29166293e+00 -9.38669622e-01
7.58007228e-01 -5.60001671e-01 -9.80721772e-01 9.36999440e-01
1.42395914e-01 -3.53617996e-01 4.92644757e-01 4.82584685e-01
-8.25849652e-01 -3.80457819e-01 -9.62618947e-01 3.44129205e-01
1.31563330e+00 -9.84296441e-01 -5.62503517e-01 1.13334000e-01
1.08779776e+00 -6.75400853e-01 -1.34468937e+00 5.53556859e-01
7.77280092e-01 -9.70475197e-01 7.87311018e-01 -9.86400783e-01
4.74978745e-01 -7.28603750e-02 -7.26134658e-01 -6.08699620e-01
2.18364552e-01 -6.89780533e-01 -3.30400407e-01 1.16577101e+00
8.22732985e-01 -4.60476220e-01 1.00202322e+00 1.01609957e+00
-2.81083733e-01 -1.02966809e+00 -6.53446913e-01 -7.63178229e-01
-4.69384491e-02 -1.03355289e+00 8.68133783e-01 5.99974513e-01
2.51421839e-01 3.57643157e-01 3.52779515e-02 3.38880159e-02
5.52059829e-01 3.32522839e-01 1.18476474e+00 -8.63099933e-01
-5.73567092e-01 -3.78497958e-01 2.14400068e-02 -1.45968115e+00
-7.00455755e-02 -8.32211196e-01 9.62877423e-02 -1.13724196e+00
3.33528966e-01 -6.80060863e-01 -5.53476661e-02 6.57673597e-01
5.88997044e-02 -2.99052119e-01 5.93218841e-02 2.92045385e-01
-8.99958193e-01 3.90090942e-02 3.53083283e-01 -9.78804305e-02
-5.49099445e-02 -9.00358781e-02 -9.03068483e-01 2.69271731e-01
4.00300086e-01 -5.76720595e-01 -4.89544362e-01 -8.47820163e-01
8.43584657e-01 5.66548288e-01 1.20695733e-01 -9.15462017e-01
5.10503054e-01 -3.09375554e-01 -2.54308969e-01 -7.95922339e-01
6.89236596e-02 -5.42482674e-01 3.40420216e-01 2.76379198e-01
-9.88616586e-01 4.81994063e-01 1.85128480e-01 3.32499981e-01
-2.94295430e-01 -2.15707660e-01 4.20502126e-01 -1.04723074e-01
-6.95329249e-01 -4.80267918e-03 1.33680180e-01 6.24039173e-01
5.85523844e-01 5.17064109e-02 -5.95211208e-01 -2.09901944e-01
-4.20662612e-01 3.44211310e-01 6.25065923e-01 2.98223764e-01
3.84259582e-01 -9.02041554e-01 -4.99857664e-01 4.32369530e-01
6.51932597e-01 -7.74701536e-02 -3.41027051e-01 6.86316252e-01
-5.16744673e-01 7.86127567e-01 1.43757358e-01 -6.23574555e-01
-9.91932929e-01 4.91972446e-01 7.92199820e-02 -3.56932819e-01
-1.81059435e-01 1.00943375e+00 -3.24847072e-01 -5.70901692e-01
4.07595575e-01 -6.65077448e-01 5.16381979e-01 -2.77824074e-01
5.25231324e-02 3.00612569e-01 3.61663580e-01 1.40267164e-01
-4.58890676e-01 2.32632205e-01 -2.44095042e-01 -4.06218082e-01
1.19260263e+00 9.08207223e-02 -3.60133350e-01 3.01766008e-01
1.17375028e+00 3.36396515e-01 -7.86675394e-01 -5.98926365e-01
7.39846885e-01 -3.71144503e-01 -3.84077758e-01 -1.16653681e+00
-5.82342505e-01 6.91211879e-01 3.35363179e-01 3.61473769e-01
1.05301106e+00 2.88514644e-01 9.51343358e-01 9.19735909e-01
7.31074512e-01 -1.00168121e+00 -1.59783717e-02 5.16344249e-01
7.77800918e-01 -1.25520301e+00 -1.11352228e-01 -2.42413625e-01
-5.05227864e-01 9.77237344e-01 8.18362713e-01 2.59550273e-01
1.29710630e-01 5.77801645e-01 2.64748186e-02 -4.88257974e-01
-1.37672627e+00 -5.56039326e-02 4.10692878e-02 1.01692565e-01
5.73222935e-01 5.25973700e-02 -1.93364277e-01 7.42495239e-01
-5.56588352e-01 -3.93434092e-02 1.60984278e-01 1.12514079e+00
-5.89065969e-01 -1.31499672e+00 4.74914759e-02 8.07810605e-01
-3.22738439e-01 -2.59928286e-01 -3.15343082e-01 8.45878839e-01
-2.32261062e-01 8.10094774e-01 9.21636894e-02 -7.78514028e-01
7.85658300e-01 4.13265526e-01 3.71061385e-01 -7.05086410e-01
-6.51104450e-01 7.10432902e-02 6.41547382e-01 -1.06055343e+00
2.23833144e-01 -8.25492799e-01 -1.39378822e+00 -5.26327014e-01
-3.12671512e-01 3.00749093e-01 7.07583010e-01 6.44496441e-01
7.52419293e-01 1.02389321e-01 3.92872483e-01 2.40737915e-01
-1.00928080e+00 -7.81539559e-01 2.60852315e-02 4.60749298e-01
-6.72606677e-02 -2.04509139e-01 1.85672324e-02 -2.11260729e-02] | [9.839747428894043, 7.8671488761901855] |
f34d6b7e-71b3-471e-8ace-b33ee218092e | response-generation-in-longitudinal-dialogues | 2305.15908 | null | https://arxiv.org/abs/2305.15908v1 | https://arxiv.org/pdf/2305.15908v1.pdf | Response Generation in Longitudinal Dialogues: Which Knowledge Representation Helps? | Longitudinal Dialogues (LD) are the most challenging type of conversation for human-machine dialogue systems. LDs include the recollections of events, personal thoughts, and emotions specific to each individual in a sparse sequence of dialogue sessions. Dialogue systems designed for LDs should uniquely interact with the users over multiple sessions and long periods of time (e.g. weeks), and engage them in personal dialogues to elaborate on their feelings, thoughts, and real-life events. In this paper, we study the task of response generation in LDs. We evaluate whether general-purpose Pre-trained Language Models (PLM) are appropriate for this purpose. We fine-tune two PLMs, GePpeTto (GPT-2) and iT5, using a dataset of LDs. We experiment with different representations of the personal knowledge extracted from LDs for grounded response generation, including the graph representation of the mentioned events and participants. We evaluate the performance of the models via automatic metrics and the contribution of the knowledge via the Integrated Gradients technique. We categorize the natural language generation errors via human evaluations of contextualization, appropriateness and engagement of the user. | ['Giuseppe Riccardi', 'Simone Caldarella', 'Seyed Mahed Mousavi'] | 2023-05-25 | null | null | null | null | ['response-generation'] | ['natural-language-processing'] | [ 6.57556653e-02 7.70681083e-01 1.80543125e-01 -4.96938944e-01
-5.84151626e-01 -5.06836236e-01 1.02010357e+00 4.16393548e-01
-2.22717866e-01 8.84448290e-01 1.00818789e+00 -1.36203784e-03
4.43498582e-01 -6.98557496e-01 6.61460087e-02 -8.12052190e-02
-1.94885314e-01 6.77609026e-01 -3.19199830e-01 -7.05431283e-01
3.06402296e-01 7.35988915e-02 -8.73844087e-01 7.13756740e-01
8.40223789e-01 5.95968604e-01 -7.63498321e-02 1.01663446e+00
-3.11803043e-01 1.13232934e+00 -1.11131454e+00 -5.13894618e-01
-4.58839864e-01 -9.66028392e-01 -1.28969407e+00 1.72611207e-01
-1.01523727e-01 -2.72827178e-01 -1.24328770e-01 5.29770494e-01
8.01695585e-01 6.53616250e-01 6.69506907e-01 -1.00081718e+00
-3.89401138e-01 9.06532168e-01 2.06951378e-03 5.69502525e-02
1.19198918e+00 3.42013329e-01 8.17136526e-01 -8.98599446e-01
7.34747112e-01 1.62158179e+00 6.14740610e-01 1.04998267e+00
-1.25173819e+00 -2.00328946e-01 -1.97818721e-04 -1.17567256e-01
-9.02337611e-01 -7.47108579e-01 7.98937023e-01 -4.84078288e-01
1.18444955e+00 5.20524979e-01 4.46770877e-01 1.82556450e+00
-2.43546385e-02 6.61633074e-01 8.67497861e-01 -4.60291296e-01
2.76147604e-01 5.95346749e-01 3.15953463e-01 5.82646370e-01
-4.30085003e-01 -5.23740888e-01 -9.29155767e-01 -5.74600756e-01
4.42381114e-01 -6.16721809e-01 -5.53352594e-01 4.64351386e-01
-1.29812181e+00 1.15467131e+00 4.03824225e-02 4.65982676e-01
-6.87205315e-01 -4.16052192e-01 6.59860313e-01 1.82972893e-01
8.14240158e-01 9.20831084e-01 -9.80674475e-02 -4.60646212e-01
-5.02592385e-01 2.46332884e-01 1.65013778e+00 8.76941681e-01
5.99476695e-01 -2.26028606e-01 -8.99152696e-01 1.17736053e+00
1.45374656e-01 1.17344014e-01 6.39060080e-01 -6.65795803e-01
5.11549413e-01 8.13938856e-01 3.46466392e-01 -1.27706254e+00
-6.42509997e-01 6.39894903e-02 -1.12634277e+00 -6.66687787e-01
2.35295296e-01 -8.80223691e-01 -1.49489060e-01 1.77850771e+00
3.22613835e-01 -2.08543554e-01 3.57239813e-01 6.20794833e-01
1.25369871e+00 8.75068903e-01 2.29765683e-01 -5.09675026e-01
1.17237616e+00 -8.97361338e-01 -1.05248117e+00 -4.53533769e-01
7.54761398e-01 -6.64846539e-01 1.25307143e+00 2.93714721e-02
-1.16259587e+00 -5.63921690e-01 -5.78387439e-01 -3.14961709e-02
-1.33667693e-01 2.22112551e-01 3.23611379e-01 3.05001080e-01
-1.00753975e+00 6.09080255e-01 -1.28600433e-01 -7.20471323e-01
-3.64510953e-01 -7.13807121e-02 -4.45665196e-02 5.95022380e-01
-1.88103604e+00 1.12213886e+00 3.14724930e-02 3.01437050e-01
-5.46602130e-01 -3.60189974e-01 -8.41282368e-01 -2.27453858e-01
3.47233303e-02 -6.44991040e-01 1.45523226e+00 -6.96583509e-01
-1.86614966e+00 1.00941062e+00 -1.26765683e-01 -3.56306046e-01
5.32093704e-01 -9.57223102e-02 -4.60107028e-01 2.22067423e-02
-1.36643928e-02 4.86115485e-01 5.76721609e-01 -9.22140539e-01
-2.22110987e-01 -7.26250485e-02 2.17165768e-01 6.00561500e-01
-3.23679984e-01 1.90200116e-02 -4.21755500e-02 -2.62692153e-01
-4.11998272e-01 -8.40852797e-01 -3.26899648e-01 -9.17701840e-01
-7.44438887e-01 -7.72577882e-01 2.50494063e-01 -8.30270410e-01
1.50149071e+00 -1.88642931e+00 3.56175452e-01 3.84713821e-02
1.11675777e-01 2.00845584e-01 -1.48804843e-01 1.21518254e+00
3.54441822e-01 1.48868322e-01 1.00300215e-01 -6.25882030e-01
1.42149463e-01 -7.72693083e-02 -4.01078314e-01 -1.39766186e-01
1.01274751e-01 8.53618920e-01 -1.15384734e+00 -4.32131171e-01
-5.34748472e-02 3.87941152e-01 -2.06336081e-01 9.61634696e-01
-4.87930536e-01 8.19449127e-01 -4.23987150e-01 -1.75819948e-01
-1.30441144e-01 -4.10022408e-01 3.74347955e-01 -1.97612733e-01
6.54180944e-02 8.96770477e-01 -7.39924729e-01 1.61258686e+00
-8.34541321e-01 4.53764200e-01 -1.65092155e-01 -2.41892993e-01
1.09445322e+00 6.85988963e-01 6.33658394e-02 -5.53521395e-01
-1.07748456e-01 -2.79571623e-01 -3.26481760e-01 -7.46994019e-01
8.29734564e-01 3.22622969e-03 -4.71089453e-01 1.04975486e+00
1.60661668e-01 -5.48093244e-02 2.93142438e-01 7.38627076e-01
9.82519269e-01 -4.21389043e-01 6.52070403e-01 -5.62718511e-03
4.99704838e-01 -2.02472642e-01 7.90971983e-03 7.63170421e-01
1.25786383e-02 2.50926763e-01 7.52012610e-01 -2.79273599e-01
-5.43721557e-01 -4.86574411e-01 5.52904963e-01 1.42211521e+00
-1.40486792e-01 -6.79129779e-01 -8.14641416e-01 -7.53423333e-01
-5.48432350e-01 1.30333686e+00 -5.78347027e-01 -3.69099557e-01
-4.46443915e-01 -7.63070643e-01 7.08557129e-01 1.90464795e-01
5.60107410e-01 -1.64063561e+00 -5.75724244e-01 5.27230024e-01
-9.18325245e-01 -1.09758127e+00 -6.58039391e-01 -3.45362633e-01
-4.27311540e-01 -7.62226701e-01 -3.89408052e-01 -4.94126260e-01
4.73642349e-01 -2.02235416e-01 1.49498320e+00 -8.46136212e-02
-5.76630281e-03 6.41250193e-01 -6.14024282e-01 1.81598142e-02
-9.46271956e-01 1.00131676e-01 9.37773846e-03 2.82783121e-01
3.71049792e-01 -4.42174166e-01 -5.08034587e-01 1.97261646e-01
-5.16840458e-01 5.13686538e-01 1.29935905e-01 7.43663967e-01
-1.76111281e-01 -4.10661221e-01 7.33407855e-01 -1.17412961e+00
1.82539082e+00 -8.57535541e-01 3.18771034e-01 3.96678478e-01
-3.84641677e-01 -1.12307966e-01 5.16232431e-01 -4.51168984e-01
-1.33759832e+00 -4.72078741e-01 -1.06034830e-01 3.28183919e-01
-2.12921172e-01 5.55406690e-01 1.53540581e-01 4.63903844e-01
1.17225182e+00 1.03872865e-01 -2.24707618e-01 -2.27980599e-01
5.06906927e-01 9.72625613e-01 2.58007407e-01 -7.36716449e-01
1.02637000e-02 -2.88082957e-01 -7.49087036e-01 -1.07581377e+00
-9.36314344e-01 -4.63885367e-01 -2.63200432e-01 -6.65623903e-01
7.72037685e-01 -6.66152418e-01 -9.02602494e-01 2.55289376e-01
-1.71388674e+00 -7.01389074e-01 -1.82223260e-01 1.55072942e-01
-4.66795713e-01 3.39769840e-01 -8.87106061e-01 -1.21787167e+00
-7.90723860e-01 -5.92279196e-01 9.34687853e-01 2.77651578e-01
-1.33141959e+00 -1.36697626e+00 4.95600671e-01 3.51296186e-01
4.93397534e-01 4.21039134e-01 7.75273860e-01 -1.05383408e+00
2.49074444e-01 -5.98452091e-02 4.03580405e-02 1.66091755e-01
2.67840058e-01 -2.97344148e-01 -9.91501391e-01 -8.66766125e-02
2.17721164e-01 -8.59941244e-01 3.04915667e-01 -1.97097898e-01
6.66090071e-01 -1.12189960e+00 -4.98189516e-02 -2.55053550e-01
6.45296216e-01 5.66743277e-02 5.21923125e-01 -3.41593385e-01
5.86570203e-01 1.20780349e+00 3.83855104e-01 8.87722969e-01
7.38365412e-01 5.91049969e-01 -2.16971382e-01 8.38468969e-02
1.32615387e-01 -5.52149534e-01 7.24246144e-01 1.07670724e+00
-1.31961424e-02 -5.74436665e-01 -8.51431787e-01 4.78682101e-01
-1.98655748e+00 -9.03187633e-01 -2.03979835e-01 1.90241301e+00
1.35613775e+00 -2.14335650e-01 1.55645624e-01 -3.55583638e-01
7.99449444e-01 4.72323239e-01 -2.21165061e-01 -8.46203268e-01
1.11298427e-01 3.70063223e-02 -2.97463179e-01 9.39860106e-01
-4.93549258e-01 8.27162385e-01 6.08541536e+00 4.64739591e-01
-7.86708534e-01 -1.22997276e-02 8.35502326e-01 5.93544990e-02
-3.90204728e-01 -2.76503354e-01 -7.81858385e-01 3.69527072e-01
1.29807806e+00 -3.82072508e-01 5.58140278e-01 3.59292448e-01
4.65068042e-01 -7.49050751e-02 -1.48648822e+00 6.39943659e-01
2.44857565e-01 -9.97362673e-01 4.09451537e-02 -3.86660755e-01
5.92235506e-01 -4.60682750e-01 -2.94661462e-01 5.23488343e-01
5.40995359e-01 -1.02985740e+00 1.47782058e-01 8.14877272e-01
6.11781061e-01 -3.41461688e-01 5.64943612e-01 6.27709091e-01
-6.19604230e-01 4.04523581e-01 5.27896024e-02 -2.04171509e-01
2.94030845e-01 4.43326473e-01 -1.55277050e+00 3.15450817e-01
1.99241295e-01 4.04304951e-01 -4.13655430e-01 7.68571673e-03
-4.63247180e-01 6.89722478e-01 -1.34040654e-01 -5.82361281e-01
1.09064423e-01 -1.25859275e-01 5.75009465e-01 1.64140916e+00
7.90055022e-02 4.35322315e-01 2.40861759e-01 9.75953460e-01
-2.13407770e-01 4.43484157e-01 -7.27573812e-01 -5.21761060e-01
5.20427108e-01 1.53383470e+00 -1.01238675e-01 -5.14706552e-01
-3.00518125e-02 1.20253289e+00 5.61061621e-01 3.91229212e-01
-3.91646564e-01 -1.32049873e-01 3.02872151e-01 -1.85064096e-02
-5.20907044e-01 6.76050037e-02 -3.70862521e-02 -1.04827368e+00
-1.47466809e-01 -1.08686316e+00 4.57449287e-01 -7.77215064e-01
-1.60804260e+00 1.00574172e+00 -1.19971216e-01 -6.17626488e-01
-1.10917306e+00 9.39898007e-03 -9.81449127e-01 1.03405547e+00
-7.50960231e-01 -7.92525291e-01 -4.18982863e-01 6.16282701e-01
7.74721324e-01 -1.02257125e-01 1.44026828e+00 -2.05496475e-01
-5.36330163e-01 3.97596776e-01 -7.11991131e-01 1.37396246e-01
9.21170354e-01 -1.22785735e+00 5.62602341e-01 2.52683014e-01
-1.35952234e-01 7.98974872e-01 9.44395781e-01 -7.79527068e-01
-1.03948200e+00 -9.89399135e-01 1.52256584e+00 -4.46155190e-01
5.85398912e-01 -4.89665836e-01 -9.01809812e-01 6.15186274e-01
6.61041558e-01 -8.50804448e-01 1.01882815e+00 4.65669543e-01
2.33295411e-02 4.81484056e-01 -1.04503345e+00 8.49540532e-01
9.55162942e-01 -7.39529252e-01 -7.88288534e-01 8.01857889e-01
6.40998900e-01 -4.67717111e-01 -9.17622685e-01 -8.32046662e-03
1.20704100e-01 -9.23782468e-01 5.74252248e-01 -7.82846987e-01
5.74959099e-01 3.21711004e-01 1.85534626e-01 -1.76813233e+00
-1.11031279e-01 -1.38350332e+00 -5.92579283e-02 1.44745028e+00
4.80906934e-01 -4.99248236e-01 1.69073462e-01 1.08564258e+00
1.31402314e-01 -4.96089548e-01 -2.92214423e-01 5.94599359e-02
-3.99076700e-01 -1.08053111e-01 4.18822855e-01 1.10019040e+00
8.82369459e-01 1.22249389e+00 -7.49268234e-01 -2.06218496e-01
1.81488425e-01 6.61685839e-02 8.86726320e-01 -1.08003318e+00
-3.65161061e-01 -3.21847677e-01 3.29302758e-01 -8.83762598e-01
2.51525819e-01 -6.43637180e-01 1.64243758e-01 -1.63916302e+00
1.56891271e-02 -1.17930304e-02 3.74381334e-01 3.01208705e-01
-3.86104792e-01 -2.46809229e-01 -1.66662663e-01 -6.76441193e-03
-7.45240331e-01 6.10287666e-01 1.05100143e+00 -6.76773349e-03
-6.80106461e-01 3.56762893e-02 -7.18089283e-01 5.79446137e-01
9.27778602e-01 -1.20507246e-02 -5.47947884e-01 -1.46404393e-02
4.38638449e-01 5.86906850e-01 2.68093437e-01 -5.66332817e-01
4.24267262e-01 -8.88032913e-02 2.70736478e-02 -2.20009357e-01
4.20225888e-01 1.06391022e-02 7.63977021e-02 -5.37374578e-02
-1.05395865e+00 -1.74064711e-01 -1.11189727e-02 3.72338444e-01
-1.94680184e-01 -1.59175143e-01 3.66138965e-01 -4.33506548e-01
-4.15044874e-01 -5.41472845e-02 -6.70768619e-01 4.90735412e-01
6.05754554e-01 1.57307550e-01 -2.67580062e-01 -1.09461498e+00
-9.44139004e-01 3.37563276e-01 3.92329842e-02 5.03255546e-01
7.65382051e-01 -1.22858262e+00 -9.89136338e-01 4.34982777e-02
2.35167161e-01 -2.42163658e-01 3.45735937e-01 5.90043306e-01
8.63200147e-03 2.98538089e-01 -1.15335395e-03 -1.52500793e-01
-1.12232316e+00 -5.99790476e-02 3.10842484e-01 -5.81779242e-01
-4.12271738e-01 9.33661044e-01 1.56373665e-01 -4.60866481e-01
3.23748827e-01 1.17697157e-01 -6.91714764e-01 5.45342445e-01
6.63983464e-01 3.82888645e-01 -8.92614648e-02 -4.68966007e-01
2.86663491e-02 -1.39874056e-01 -3.95988747e-02 -4.09176171e-01
9.77968514e-01 -2.08764195e-01 -3.07888687e-01 8.99145067e-01
9.84916687e-01 -6.76595140e-03 -7.55967617e-01 -3.16166699e-01
6.66359290e-02 -4.68644165e-02 -4.25746500e-01 -1.02182889e+00
-3.56340915e-01 7.47128963e-01 -2.22009912e-01 7.08580554e-01
7.21684992e-01 -1.68251410e-01 7.98466206e-01 4.54090446e-01
3.17592680e-01 -1.12974298e+00 3.95363450e-01 7.68606603e-01
1.51196873e+00 -1.05578911e+00 -4.25178438e-01 -3.69668826e-02
-1.36963928e+00 1.12783933e+00 7.44104028e-01 2.77807266e-01
2.24976540e-01 -2.96531528e-01 2.61713713e-01 -2.95197368e-01
-1.28310955e+00 1.83737680e-01 4.36427355e-01 3.17651212e-01
9.17221665e-01 2.75499701e-01 -4.66204971e-01 7.59361029e-01
-4.38947141e-01 -3.39967936e-01 5.72830617e-01 4.28468257e-01
-1.55530185e-01 -8.65857124e-01 2.49763988e-02 2.65886426e-01
5.20414440e-03 -4.73503098e-02 -1.26775706e+00 1.29130200e-01
-4.08324361e-01 1.54281199e+00 -2.86840647e-01 -5.69463849e-01
5.43119371e-01 5.44763625e-01 1.61021963e-01 -9.77322996e-01
-1.17301011e+00 -4.11191940e-01 1.03726149e+00 -6.48719132e-01
-3.02650839e-01 -4.64575678e-01 -1.17873228e+00 -3.85671258e-01
-2.18177941e-02 4.63138312e-01 4.39555228e-01 8.46594274e-01
3.67816925e-01 3.83134723e-01 9.53410566e-01 -7.45605767e-01
-6.24980867e-01 -1.57174063e+00 -2.30292946e-01 7.61939466e-01
-3.30574811e-02 -1.06722601e-02 -4.82650548e-01 -9.37246233e-02] | [12.670618057250977, 8.131457328796387] |
3b0326c1-9ad8-4cfe-9b61-67cd4e2222e2 | strong-baselines-for-complex-word | 1904.05953 | null | http://arxiv.org/abs/1904.05953v1 | http://arxiv.org/pdf/1904.05953v1.pdf | Strong Baselines for Complex Word Identification across Multiple Languages | Complex Word Identification (CWI) is the task of identifying which words or
phrases in a sentence are difficult to understand by a target audience. The
latest CWI Shared Task released data for two settings: monolingual (i.e. train
and test in the same language) and cross-lingual (i.e. test in a language not
seen during training). The best monolingual models relied on language-dependent
features, which do not generalise in the cross-lingual setting, while the best
cross-lingual model used neural networks with multi-task learning. In this
paper, we present monolingual and cross-lingual CWI models that perform as well
as (or better than) most models submitted to the latest CWI Shared Task. We
show that carefully selected features and simple learning models can achieve
state-of-the-art performance, and result in strong baselines for future
development in this area. Finally, we discuss how inconsistencies in the
annotation of the data can explain some of the results obtained. | ['Fernando Alva-Manchego', 'Daniel King', 'Elisabeth Fritzsch', 'Pierre Finnimore', 'Alison Sneyd', 'Aneeq Ur Rehman', 'Andreas Vlachos'] | 2019-04-11 | strong-baselines-for-complex-word-1 | https://aclanthology.org/N19-1102 | https://aclanthology.org/N19-1102.pdf | naacl-2019-6 | ['complex-word-identification'] | ['natural-language-processing'] | [ 9.71284956e-02 -2.46386662e-01 -5.09506501e-02 -4.16172922e-01
-1.30351925e+00 -1.01271772e+00 8.82812619e-01 1.91332638e-01
-9.41810250e-01 7.81454206e-01 2.94610262e-01 -7.77019083e-01
-9.57118871e-04 -2.50510573e-01 -6.46970570e-01 -3.12213272e-01
-2.47817803e-02 7.51881421e-01 9.23640579e-02 -2.03247249e-01
1.18457548e-01 1.17056839e-01 -1.19713700e+00 5.12831807e-01
5.52575171e-01 3.50829124e-01 3.73770207e-01 7.68566668e-01
-1.97971359e-01 3.96534353e-01 -6.64922297e-01 -4.58733737e-01
-2.75742169e-02 -1.05167605e-01 -1.12762654e+00 -5.06466746e-01
7.55664885e-01 1.67811930e-01 2.30461687e-01 8.56369793e-01
6.79997444e-01 -2.24494681e-01 5.88916183e-01 -8.71730983e-01
-5.64169943e-01 8.89893174e-01 -2.44296685e-01 4.61005688e-01
4.50372130e-01 -1.06354989e-01 1.37956190e+00 -1.19108343e+00
5.91751158e-01 1.57820749e+00 7.78763831e-01 5.00259519e-01
-1.26066041e+00 -9.78373647e-01 4.50504333e-01 1.76151529e-01
-1.32476425e+00 -8.13664615e-01 2.33528316e-01 -4.86351728e-01
1.45620263e+00 2.23212183e-01 -3.51650384e-03 1.48547482e+00
2.55700707e-01 9.66040492e-01 1.46279180e+00 -7.05910265e-01
-3.59685928e-01 2.84073561e-01 4.66879785e-01 3.43257874e-01
2.89175242e-01 2.95074051e-03 -7.06801295e-01 -1.01713806e-01
-3.71129811e-02 -6.60538495e-01 -3.02904993e-01 9.69444364e-02
-1.49271119e+00 9.79626477e-01 -2.87232220e-01 7.91246235e-01
2.10144371e-01 -2.16758311e-01 6.82456732e-01 6.90871894e-01
7.61855185e-01 8.00083280e-01 -1.11399591e+00 -1.44547686e-01
-9.08080041e-01 2.34134763e-01 9.41383958e-01 8.07238758e-01
7.51851678e-01 -1.44703731e-01 -2.00516656e-01 1.14749670e+00
2.58662641e-01 6.44495368e-01 7.95693099e-01 -4.45316285e-01
6.95800900e-01 1.18303850e-01 -7.94340223e-02 -4.01184797e-01
-7.03926504e-01 -4.74736929e-01 -2.81883121e-01 9.19501707e-02
7.64869630e-01 -3.26324821e-01 -7.07452238e-01 1.95310485e+00
-2.92237848e-01 -1.94983169e-01 1.42201081e-01 3.25530142e-01
9.04145181e-01 5.24767101e-01 2.96912849e-01 -1.13699630e-01
1.48376715e+00 -9.39290226e-01 -4.81083065e-01 -8.11761558e-01
1.19595289e+00 -1.28655624e+00 1.28620577e+00 4.23790514e-01
-9.31729138e-01 -7.04238951e-01 -1.01744306e+00 5.30991703e-02
-7.30855286e-01 1.18463300e-01 3.61812204e-01 7.74824083e-01
-1.15469551e+00 2.88474262e-01 -4.50107187e-01 -5.04136503e-01
-1.15307599e-01 2.23173454e-01 -5.47721684e-01 -1.13736980e-01
-1.51948559e+00 1.36154616e+00 4.23084289e-01 -2.28223711e-01
-7.57221341e-01 -7.21856833e-01 -9.35751319e-01 -2.23761708e-01
3.65421623e-01 -6.51832670e-02 1.49368525e+00 -8.93724442e-01
-9.53617036e-01 1.46437585e+00 -2.82140017e-01 -3.40790957e-01
3.46847206e-01 -3.62022728e-01 -6.95454717e-01 -3.45861495e-01
6.33060157e-01 3.81832004e-01 4.88146603e-01 -1.10974169e+00
-9.14179564e-01 -2.90176332e-01 -1.05989866e-01 1.17441066e-01
-3.00635070e-01 5.63802600e-01 -4.52609390e-01 -4.56285328e-01
-3.13464642e-01 -9.79342699e-01 2.39016682e-01 -5.23731649e-01
-5.02012134e-01 -7.60377884e-01 7.40164340e-01 -7.86158979e-01
1.30140865e+00 -2.07336783e+00 -1.04648294e-02 -2.94915419e-02
2.82835364e-02 4.60182905e-01 -4.44508642e-01 6.37941062e-01
-3.69590312e-01 6.34819150e-01 1.41951621e-01 -8.04077864e-01
-1.61585361e-02 2.43124276e-01 -4.75137942e-02 3.97277802e-01
2.71329314e-01 9.20171440e-01 -8.80014181e-01 -4.27058965e-01
-1.29434809e-01 1.09620914e-01 -1.12675883e-01 1.77628566e-02
9.32724550e-02 4.11027700e-01 -7.21126348e-02 3.52094352e-01
3.21070462e-01 -9.30185989e-02 1.22022159e-01 -1.10259056e-01
-5.10764182e-01 7.73748338e-01 -1.01122653e+00 1.56119359e+00
-9.87770617e-01 7.73510754e-01 1.75961763e-01 -8.60311747e-01
5.36594272e-01 4.99882877e-01 -1.48282424e-01 -7.42751777e-01
-2.85662472e-01 6.33281291e-01 4.71128911e-01 -3.57944161e-01
1.18339702e-01 -4.76946011e-02 -3.04720521e-01 6.81026518e-01
3.35121334e-01 1.33833261e-02 5.36989748e-01 9.45190266e-02
7.35491931e-01 -1.03853494e-02 4.59962249e-01 -7.99356222e-01
7.30761647e-01 -1.78457528e-01 4.76066142e-01 1.07527661e+00
-1.31024837e-01 3.81789297e-01 1.82369336e-01 -3.26256096e-01
-9.67128813e-01 -8.92159760e-01 -4.03958827e-01 1.61210942e+00
-3.89255077e-01 -4.29423243e-01 -4.04863387e-01 -6.61203146e-01
-1.61871970e-01 9.54792976e-01 -5.74380398e-01 1.13979273e-01
-7.11173117e-01 -6.19793415e-01 7.20526993e-01 4.74304855e-01
7.77771100e-02 -1.12906504e+00 -8.13129768e-02 2.41986841e-01
-3.07463557e-01 -1.19583952e+00 -7.31103957e-01 5.83216727e-01
-1.29564419e-01 -8.72116804e-01 -6.47553504e-01 -1.17386639e+00
1.41045332e-01 2.16864288e-01 1.52665269e+00 4.97693159e-02
-1.46502391e-01 3.14867616e-01 -4.76669639e-01 -5.70138097e-01
-7.22997189e-01 5.71707308e-01 2.50164032e-01 -2.08797053e-01
6.39821291e-01 -3.09959520e-02 -1.46541551e-01 2.81799048e-01
-4.88246918e-01 -1.14401855e-01 5.11973798e-01 1.01534235e+00
7.69821331e-02 -3.55353296e-01 6.44550741e-01 -1.12640417e+00
8.07150126e-01 -3.95603657e-01 -2.65155911e-01 5.20630181e-01
-6.23053193e-01 2.19418555e-01 4.97261852e-01 -5.48445880e-01
-7.27382958e-01 -3.62462759e-01 -4.91974592e-01 2.74421543e-01
-2.68892825e-01 7.22756445e-01 -1.03588738e-01 -9.55294818e-02
5.39684534e-01 -7.47688999e-03 -2.99747199e-01 -6.46057010e-01
1.06330514e-01 7.23002791e-01 2.50667602e-01 -6.40995443e-01
7.29228139e-01 -1.61273226e-01 -6.45919681e-01 -8.06826174e-01
-1.18396604e+00 -7.10696101e-01 -7.77092397e-01 3.80907096e-02
9.25314784e-01 -1.13126290e+00 -4.00361776e-01 5.93567133e-01
-1.29234648e+00 -5.45845091e-01 1.39508441e-01 4.83327806e-01
-1.35038823e-01 2.99222857e-01 -3.89028102e-01 -7.43389726e-01
-4.14296180e-01 -1.26482451e+00 1.19045877e+00 -2.58367687e-01
-7.19316006e-01 -1.42436409e+00 2.53732532e-01 2.24718153e-01
4.77235854e-01 -2.66739845e-01 1.12902677e+00 -1.35983002e+00
1.26655325e-01 -4.92151156e-02 -1.71153575e-01 4.57188129e-01
3.84642743e-02 -1.15176417e-01 -1.09348381e+00 -6.64329231e-01
-1.15662381e-01 -9.79064405e-01 8.86327684e-01 1.36852205e-01
6.62423253e-01 2.73020547e-02 -3.56724441e-01 4.03855413e-01
1.23275471e+00 1.08460814e-01 9.89139304e-02 5.09269774e-01
5.89055300e-01 7.88238645e-01 2.90809602e-01 -5.01194559e-02
5.62059104e-01 6.53869927e-01 -1.14150055e-01 -1.39595032e-01
-1.69713527e-01 -1.05673298e-01 6.09726191e-01 1.06655824e+00
3.96818966e-01 -3.01436126e-01 -1.38655567e+00 8.78252566e-01
-1.47417343e+00 -7.83630490e-01 -3.02847266e-01 2.28804874e+00
1.10455775e+00 5.43267369e-01 5.63585386e-02 5.24168508e-03
5.02726734e-01 1.40043825e-01 -1.49698704e-01 -7.36115158e-01
-5.14838219e-01 5.21893620e-01 5.45785308e-01 1.06763077e+00
-1.32249987e+00 1.23566139e+00 6.75128698e+00 1.05371177e+00
-1.03510451e+00 5.15960157e-01 5.38439631e-01 2.25368574e-01
-2.20784575e-01 -1.18235245e-01 -1.33645225e+00 2.70937890e-01
1.39525771e+00 -3.54529321e-01 2.98792750e-01 5.31446099e-01
-1.54535532e-01 -1.11840880e-02 -1.36869073e+00 8.05234909e-01
2.07668334e-01 -8.10864091e-01 -3.13045025e-01 -1.40100181e-01
5.45125008e-01 7.22272456e-01 3.19360308e-02 6.83817923e-01
4.17175889e-01 -1.11871624e+00 8.27816963e-01 -3.12545593e-03
1.05888653e+00 -5.26195824e-01 8.17931235e-01 4.68650967e-01
-1.16803849e+00 2.07924917e-01 -7.52463564e-02 -8.66843984e-02
-2.07174923e-02 6.10514656e-02 -6.57570660e-01 4.05105382e-01
7.38890707e-01 6.33266032e-01 -9.82935011e-01 7.60268450e-01
-2.16798380e-01 1.00251973e+00 -3.66266727e-01 -2.08388433e-01
4.91737664e-01 1.40788585e-01 3.83661389e-01 1.74899638e+00
1.32997364e-01 -6.36406183e-01 4.71399605e-01 3.85451734e-01
5.94181567e-02 5.20935833e-01 -8.17216873e-01 3.15930955e-02
3.01754653e-01 1.15216553e+00 -3.02396685e-01 -2.36393884e-01
-1.10015643e+00 9.30936813e-01 5.46461463e-01 2.85300434e-01
-1.38174579e-01 -2.70268351e-01 6.50204182e-01 -1.65835455e-01
1.47016868e-01 -3.71235669e-01 -2.44795412e-01 -1.27317321e+00
-2.39838865e-02 -1.01450431e+00 4.30420250e-01 -3.87582690e-01
-1.66754735e+00 8.16020429e-01 1.64142027e-01 -9.78581607e-01
-5.84335029e-01 -1.17522573e+00 -7.13602424e-01 1.29711771e+00
-1.76076519e+00 -1.30644441e+00 3.05125862e-01 4.12123531e-01
7.76601076e-01 -3.73431623e-01 1.30344737e+00 3.08110833e-01
-3.50627929e-01 9.22020495e-01 2.31405497e-01 3.01447093e-01
1.21549618e+00 -1.35112202e+00 8.59431684e-01 6.66030943e-01
5.36057055e-01 7.67525494e-01 6.02464020e-01 -4.29176986e-01
-9.75109577e-01 -9.52278733e-01 1.73968792e+00 -6.83152974e-01
1.17117715e+00 -8.24383080e-01 -8.85876298e-01 8.42155516e-01
5.80745101e-01 -3.14949006e-01 9.93842423e-01 8.54619205e-01
-5.18006444e-01 1.39283746e-01 -5.79934597e-01 5.13379395e-01
8.61997485e-01 -9.36251819e-01 -6.82852328e-01 7.44165599e-01
6.19417369e-01 -1.14189163e-01 -7.01076388e-01 6.78727999e-02
5.51492095e-01 -6.31912887e-01 8.50465834e-01 -7.59865761e-01
4.02571596e-02 1.71337441e-01 -5.81970289e-02 -1.62137699e+00
-4.33961481e-01 -4.35604393e-01 5.86153507e-01 1.28442621e+00
1.20173895e+00 -8.66083264e-01 1.14424884e-01 2.35423326e-01
-2.75988668e-01 -6.57511830e-01 -1.04017901e+00 -1.11240792e+00
8.64264727e-01 -7.74119258e-01 9.75998119e-02 9.38745260e-01
-1.22934207e-02 7.26006627e-01 -2.83708125e-01 -2.55000796e-02
3.31032008e-01 -1.76519409e-01 4.98284876e-01 -1.31477082e+00
-2.54976720e-01 -4.70431805e-01 -4.18589264e-02 -8.88518333e-01
6.93655372e-01 -1.28853965e+00 -2.27973796e-03 -1.14204323e+00
2.73179710e-01 -2.47951865e-01 -2.27921590e-01 7.10269511e-01
-5.66131532e-01 3.75569403e-01 2.62480795e-01 2.12870881e-01
-4.73081023e-01 6.79710461e-03 7.99071074e-01 -2.08501801e-01
9.48970914e-02 2.14539897e-02 -9.12658989e-01 6.57260060e-01
8.31651747e-01 -4.56064194e-01 -2.09423676e-01 -9.00516987e-01
2.99319178e-01 -4.83062893e-01 -5.71870990e-02 -7.54900098e-01
1.76399797e-01 1.28519565e-01 1.58132464e-01 -4.68048632e-01
1.31042883e-01 -4.32960510e-01 -4.66572434e-01 3.17172498e-01
-3.71621728e-01 4.11489278e-01 5.36456823e-01 -2.59149056e-02
-2.38162488e-01 -6.54428542e-01 7.17937708e-01 -2.98156440e-01
-6.76114678e-01 4.26553898e-02 -6.45470083e-01 5.09928703e-01
6.68365121e-01 1.09891228e-01 -3.43892932e-01 -2.66260743e-01
-7.48184800e-01 3.85466039e-01 7.55878240e-02 7.46687949e-01
1.43477097e-01 -1.13921893e+00 -1.21725976e+00 2.83219725e-01
5.43658376e-01 -4.98593003e-01 -2.10264772e-01 6.47667587e-01
-1.72235757e-01 8.27772856e-01 2.64666915e-01 -4.91429329e-01
-1.32317734e+00 2.58679271e-01 2.66847134e-01 -6.36493623e-01
-8.29644576e-02 9.62261260e-01 2.76865602e-01 -8.67118180e-01
2.16595411e-01 -1.05795361e-01 -2.71749318e-01 2.64139742e-01
7.22422600e-01 -1.17619738e-01 2.59769499e-01 -9.42396879e-01
-6.35179162e-01 6.15254581e-01 -5.76874018e-01 -3.40168595e-01
1.05757821e+00 -1.66994080e-01 -1.02880903e-01 1.13161743e+00
1.53825819e+00 1.92809880e-01 -3.66659403e-01 -6.67529225e-01
3.75675887e-01 -3.30559239e-02 3.61272506e-02 -1.07953167e+00
-4.27672476e-01 1.00178266e+00 4.33754474e-01 2.14681655e-01
5.76090336e-01 2.00457782e-01 5.32484531e-01 4.85108525e-01
3.72545004e-01 -1.26152086e+00 -2.63055652e-01 9.47304070e-01
9.59184945e-01 -1.61487496e+00 -1.85725480e-01 -1.50472343e-01
-6.72533035e-01 1.13370407e+00 5.20034075e-01 2.16857180e-01
7.77144372e-01 2.86354005e-01 4.06156063e-01 -1.03793710e-01
-9.12023365e-01 -4.01374012e-01 4.53035057e-01 4.32837576e-01
1.05483079e+00 -3.26270424e-02 -5.33333719e-01 5.25447011e-01
-3.38243783e-01 -6.55205846e-01 1.11876227e-01 7.25177169e-01
-2.41256386e-01 -1.39472747e+00 -1.84450388e-01 4.72980767e-01
-7.54591882e-01 -5.83346665e-01 -4.67083097e-01 1.04624999e+00
1.52720600e-01 1.35211158e+00 -8.24219361e-02 -1.99069098e-01
3.57467920e-01 7.30702877e-01 1.55781850e-01 -1.08807564e+00
-8.04022014e-01 1.05402686e-01 5.88070691e-01 -3.21252078e-01
-2.74119824e-01 -9.35581744e-01 -6.77250743e-01 9.65771079e-02
-3.71949047e-01 2.12426722e-01 7.59821773e-01 1.31722450e+00
-1.55830249e-01 1.87475950e-01 4.17633057e-01 -7.21133590e-01
-5.61720848e-01 -1.44991708e+00 -3.85416627e-01 5.38609266e-01
4.36894357e-01 -3.75248224e-01 -6.64966881e-01 -3.77981290e-02] | [10.60196590423584, 10.326299667358398] |
4faef81f-1ef1-46de-a455-d049bf32c7fc | where-is-my-parcel-fast-and-efficient | null | null | https://ieeexplore.ieee.org/document/8931717 | http://fabondzogang.wdfiles.com/local--files/publications/ASOS_User_Intent_Classification_conversationalAI.pdf | “Where is My Parcel?” Fast and Efficient Classifiers to Detect User Intent in Natural Language | We study the performance of customer intent classifiers designed to predict the most popular intent received through ASOS.com Customer Care Department, namely “Where is my order?”. These queries are characterised by the use of colloquialism, label noise and short message length. We conduct extensive experiments with two well established classification models: logistic regression via n-grams to account for sequences in the data and recurrent neural networks that perform the extraction of these sequential patterns automatically. Maintaining the embedding layer fixed to GloVe coordinates, a Mann-Whitney U test indicated that the F1 score on a held out set of messages was lower for recurrent neural network classifiers than for linear n-grams classifiers (M1=0.828, M2=0.815; U=1,196, P=1.46e-20), unless all layers were jointly trained with all other network parameters (M1=0.831, M2=0.828, U=4,280, P=8.24e-4). This plain neural network produced top performance on a denoised set of labels (0.887 F1) matching with Human annotators (0.889 F1) and superior to linear classifiers (0.865 F1). Calibrating these models to achieve precision levels above Human performance (0.93 Precision), our results indicate a small difference in Recall of 0.05 for the plain neural networks (training under 1hr), and 0.07 for the linear n-grams (training under 10min), revealing the latter as a judicious choice of model architecture in modern AI production systems. | ['Nikos Konstantinidis', 'David Wardrope', 'Amal Vaidya', 'Fabon Dzogang', 'Constantina Nicolaou'] | 2019-12-16 | null | null | null | snams-2019-12 | ['english-conversational-speech-recognition'] | ['speech'] | [ 8.43500346e-02 2.37387270e-01 -3.71311754e-01 -4.43257719e-01
-5.86632967e-01 -7.56361485e-01 6.87631011e-01 4.57666427e-01
-6.89330876e-01 3.50726843e-01 1.75056756e-01 -7.30129898e-01
-1.56899557e-01 -6.54386222e-01 -5.66315532e-01 -4.92064565e-01
-1.90656275e-01 3.83769751e-01 -1.88721642e-01 -2.95868456e-01
2.88896292e-01 3.15465659e-01 -1.30173934e+00 5.54413378e-01
2.70495653e-01 1.40328085e+00 -4.45909292e-01 1.06210041e+00
1.41920492e-01 1.14616799e+00 -6.70375824e-01 -7.23864853e-01
1.34931356e-01 -1.33547544e-01 -5.45138657e-01 -2.65344679e-01
2.80777931e-01 -3.49465072e-01 -4.27544445e-01 7.34380007e-01
3.51301223e-01 -1.87476780e-02 8.26149523e-01 -1.17555821e+00
-7.96370447e-01 9.06622469e-01 -2.87296146e-01 3.54404896e-01
3.34096670e-01 7.30587021e-02 1.57126844e+00 -7.28608847e-01
3.87499988e-01 1.00036097e+00 1.18864930e+00 1.85030371e-01
-1.44225585e+00 -9.07204330e-01 -1.37504548e-01 -1.84408978e-01
-1.35175240e+00 -4.40274894e-01 4.03046340e-01 -4.44923073e-01
1.26080573e+00 4.12561476e-01 2.58553863e-01 1.26523280e+00
6.77154660e-01 5.16394317e-01 8.90459836e-01 -5.80185592e-01
4.49868664e-02 5.62577665e-01 4.77964818e-01 5.46214044e-01
2.44102970e-01 1.58770323e-01 -4.09618914e-01 -5.15700459e-01
4.81305778e-01 1.12657636e-01 3.50390345e-01 4.59143430e-01
-8.14376950e-01 1.24347579e+00 4.68778640e-01 5.42937577e-01
-5.48812389e-01 5.14941886e-02 3.48739505e-01 6.55836821e-01
3.78489822e-01 6.74632907e-01 -6.49650931e-01 -1.21999070e-01
-8.05724561e-01 2.98283517e-01 1.13500631e+00 1.01143897e+00
4.68234837e-01 2.93680187e-02 -3.47660109e-02 1.08300543e+00
1.43636823e-01 2.35432059e-01 1.00417709e+00 -7.31094062e-01
2.27862686e-01 6.09496236e-01 1.98576637e-02 -1.33165979e+00
-8.18443775e-01 -6.92451477e-01 -7.61042535e-01 -6.04243398e-01
5.17484009e-01 -4.18360502e-01 -8.57319891e-01 1.53353417e+00
-4.11030859e-01 -4.60797399e-01 8.05764273e-02 3.03777546e-01
7.20938087e-01 7.52421677e-01 1.81767836e-01 -8.04081485e-02
1.55512190e+00 -8.41666818e-01 -5.94748080e-01 -5.39398491e-01
1.15204382e+00 -9.75996375e-01 9.32983577e-01 4.44244325e-01
-6.66405439e-01 -5.41248202e-01 -9.64229643e-01 5.35026118e-02
-4.27704632e-01 1.71608582e-01 6.84249043e-01 7.94123292e-01
-8.02860200e-01 5.41639864e-01 -3.66618693e-01 -3.38111311e-01
1.49798453e-01 4.87824976e-01 -2.83387661e-01 2.63105277e-02
-1.32485664e+00 1.03879941e+00 3.32961828e-01 -2.38710828e-02
-2.84454435e-01 -3.94600779e-01 -5.49941123e-01 2.80788094e-02
-8.07104111e-02 -1.46480039e-01 1.51141715e+00 -9.01571035e-01
-1.06450093e+00 9.32511985e-01 -5.01083657e-02 -7.71696925e-01
2.64713645e-01 -2.11137325e-01 -7.45429814e-01 -1.13227427e-01
9.60212573e-02 5.73986351e-01 4.95026261e-01 -1.10864079e+00
-9.58559632e-01 -3.40053409e-01 -1.86112389e-01 -1.15203105e-01
-5.13628721e-01 2.40294784e-01 7.06078783e-02 -7.29320228e-01
3.88806969e-01 -1.20244396e+00 -1.62862286e-01 -7.10060179e-01
-2.62601733e-01 -4.32553023e-01 3.30487430e-01 -9.58682775e-01
1.55472898e+00 -2.03731537e+00 -7.13279843e-01 5.39036989e-01
2.44610548e-01 -1.34262629e-02 1.28020972e-01 6.14256442e-01
-2.78662831e-01 3.35847706e-01 1.38110086e-01 -2.81389117e-01
2.43678510e-01 8.17600861e-02 -3.78360063e-01 4.21333313e-01
-4.40595709e-02 1.14781249e+00 -4.25684571e-01 -1.44375145e-01
-1.55952305e-01 3.10507655e-01 -5.66695511e-01 1.47545740e-01
7.47071207e-02 -3.14938664e-01 -1.06006814e-02 5.64888418e-01
1.83541939e-01 -4.60587531e-01 3.08911145e-01 -1.28167167e-01
1.46645397e-01 4.45239156e-01 -8.05183411e-01 9.96420205e-01
-5.98039627e-01 8.34065855e-01 -1.92630947e-01 -7.20015824e-01
1.31859648e+00 3.36403221e-01 4.86735702e-01 -7.06273675e-01
4.48496014e-01 3.33012402e-01 3.19846451e-01 -3.97276938e-01
5.95236123e-01 -3.69967133e-01 -5.01583219e-01 5.05411506e-01
9.84467193e-02 2.69813746e-01 -2.51369923e-02 1.16191648e-01
1.34986091e+00 -6.99678302e-01 2.41290018e-01 -8.73525590e-02
1.21327423e-01 -2.58577019e-02 3.69152308e-01 1.15410030e+00
-8.00519735e-02 5.53654671e-01 6.71078861e-01 -7.40820348e-01
-1.08754838e+00 -5.02462447e-01 -4.50363696e-01 1.47756922e+00
-3.10031384e-01 -4.20324624e-01 -4.68676537e-01 -6.03181958e-01
2.63195544e-01 1.29662812e+00 -5.58701396e-01 -3.19949210e-01
-5.23087084e-01 -8.69630694e-01 8.80758584e-01 5.50214171e-01
6.84760734e-02 -1.16812265e+00 -3.16781938e-01 4.34259564e-01
-1.12501144e-01 -1.05762458e+00 -2.45760098e-01 7.98392713e-01
-7.34103322e-01 -7.27633119e-01 -2.63412565e-01 -6.85854197e-01
3.36556882e-01 -2.81381428e-01 1.18210876e+00 3.00129890e-01
1.73810333e-01 4.81016487e-02 -3.40371311e-01 -2.35008165e-01
-6.07138336e-01 4.99029815e-01 2.60716975e-01 -5.64875454e-03
1.19458580e+00 -4.94352102e-01 -3.44836146e-01 4.01156664e-01
-9.35289085e-01 -3.89556795e-01 7.64871836e-01 1.06574810e+00
-1.14516743e-01 1.54610664e-01 5.14988959e-01 -1.11533201e+00
8.32404971e-01 -7.73071289e-01 -3.70403290e-01 6.65053213e-03
-1.17565894e+00 -1.38469860e-01 6.63684130e-01 -6.53014421e-01
-5.01812279e-01 -9.33770761e-02 -4.17416126e-01 -1.43002078e-01
-2.01918006e-01 5.95287561e-01 4.28437501e-01 3.57197225e-01
1.02804840e+00 5.01933433e-02 -1.10572223e-02 -5.20536423e-01
1.55527547e-01 1.25836670e+00 4.46764588e-01 -1.77779734e-01
3.44805062e-01 -5.74000292e-02 -6.47977531e-01 -7.20880270e-01
-8.53907526e-01 -6.13829970e-01 -4.54750568e-01 2.15122446e-01
4.68090564e-01 -7.35269606e-01 -1.06037974e+00 2.23242208e-01
-9.48584318e-01 -2.14924719e-02 4.04466037e-03 6.16971970e-01
-4.07267570e-01 -2.20269281e-02 -1.09444797e+00 -8.83594096e-01
-6.11623824e-01 -8.81887257e-01 6.10699713e-01 -3.11228894e-02
-1.16265690e+00 -9.98843670e-01 -1.41022936e-01 6.19753540e-01
4.13424999e-01 -4.54358421e-02 1.01174891e+00 -1.69899976e+00
7.67026097e-02 -8.37040246e-01 -2.04547957e-01 3.99597108e-01
1.96289808e-01 -1.82357475e-01 -1.05536997e+00 -2.52079874e-01
2.21062496e-01 -2.86324054e-01 7.23203897e-01 3.10071766e-01
6.55926824e-01 -8.35300148e-01 -3.40364039e-01 2.47024924e-01
1.17135799e+00 5.61403155e-01 4.90646988e-01 5.27058840e-01
4.74340558e-01 6.18111968e-01 1.62865981e-01 3.38893890e-01
2.80559570e-01 5.47501147e-01 4.58643883e-02 2.25489408e-01
5.83378792e-01 -6.01728082e-01 3.18851054e-01 6.77418828e-01
4.48071033e-01 -3.13924909e-01 -1.20526540e+00 4.73884046e-01
-1.65887165e+00 -7.30733812e-01 -1.61586106e-01 2.00222230e+00
8.11899185e-01 7.40919650e-01 1.42609522e-01 2.53301769e-01
5.38989425e-01 2.87176576e-02 -3.19668263e-01 -8.22668195e-01
-1.22953661e-01 5.65830134e-02 8.78843963e-01 4.70980376e-01
-9.73828316e-01 6.94936752e-01 6.31108618e+00 6.96371555e-01
-9.03103352e-01 -4.20407169e-02 9.64861870e-01 -6.12352639e-02
-2.29919791e-01 -3.04179471e-02 -1.12471533e+00 9.57357943e-01
1.74392235e+00 2.20953804e-02 2.91590303e-01 9.88423765e-01
-2.43648008e-01 -4.31706607e-02 -1.24691880e+00 9.59931493e-01
2.71916151e-01 -1.22224212e+00 -2.50394404e-01 1.19053267e-01
7.61586249e-01 1.05218709e-01 1.70117587e-01 6.27765954e-01
6.02973282e-01 -1.43481815e+00 6.22364283e-01 3.22481006e-01
3.43247175e-01 -7.75825977e-01 1.14718056e+00 6.41065836e-01
-5.00494897e-01 -5.45343935e-01 -9.41916108e-02 -2.00124487e-01
-7.62948859e-03 7.41413534e-01 -1.18373835e+00 2.41361931e-02
8.06832969e-01 3.67657572e-01 -4.24810112e-01 3.21666628e-01
9.62279290e-02 7.40672469e-01 -6.69578671e-01 -3.68618757e-01
5.32203615e-01 1.79722279e-01 1.30747885e-01 1.51516044e+00
1.45790046e-02 4.95458720e-03 -1.20507479e-01 4.37613100e-01
-2.76717842e-01 1.66656882e-01 -6.05981171e-01 -2.17703924e-01
4.45386559e-01 1.06373894e+00 -6.75327182e-01 -1.89375490e-01
-2.97716171e-01 6.43838465e-01 1.08463846e-01 2.35722482e-01
-6.40605807e-01 -5.23300588e-01 3.26619029e-01 3.78302097e-01
2.39903077e-01 -3.62452120e-02 -6.30850911e-01 -7.65714824e-01
-6.41642213e-02 -1.12294173e+00 6.47478223e-01 -5.09160101e-01
-1.54928017e+00 7.64603317e-01 -3.06050152e-01 -7.60009944e-01
-7.01236725e-01 -7.77728260e-01 -2.76325494e-01 8.87406290e-01
-9.42080855e-01 -8.84688616e-01 1.61897928e-01 -4.12218273e-02
2.71996945e-01 -4.62399930e-01 9.06764030e-01 2.96974331e-01
-3.89039338e-01 1.02628791e+00 1.44263789e-01 5.31970322e-01
6.74708366e-01 -8.89093935e-01 4.86723274e-01 3.16692442e-01
2.71067739e-01 1.13893032e+00 6.16721034e-01 -5.98509550e-01
-8.93513858e-01 -7.35587418e-01 1.69032228e+00 -7.89946973e-01
7.75261581e-01 -3.65813673e-01 -8.76570821e-01 1.14608765e+00
6.54226616e-02 -4.06306088e-01 9.05781269e-01 4.08762634e-01
-4.96923029e-01 -1.00351796e-01 -1.12633812e+00 4.08717602e-01
5.53361595e-01 -7.00430095e-01 -5.88510871e-01 5.01862943e-01
6.87693179e-01 -2.99530149e-01 -1.21332192e+00 3.59376848e-01
9.60436642e-01 -9.06539023e-01 7.08940029e-01 -7.41506577e-01
3.69762510e-01 2.36501664e-01 -4.30887014e-01 -7.54403770e-01
-4.56897497e-01 -5.75004280e-01 4.05300409e-02 1.09768152e+00
8.74718606e-01 -8.96466136e-01 9.02261376e-01 8.54323506e-01
1.59135282e-01 -9.07745898e-01 -8.58244300e-01 -4.29136485e-01
9.33240205e-02 -5.10649979e-01 3.39306563e-01 1.09042478e+00
1.80327184e-02 6.83129191e-01 -3.68433148e-01 -7.74625018e-02
1.39794737e-01 -1.45325720e-01 5.39089322e-01 -1.27369452e+00
-1.17223538e-01 -4.04310286e-01 -3.64643842e-01 -1.07562673e+00
2.25017108e-02 -8.47357094e-01 -3.34478945e-01 -1.07013047e+00
-1.10899679e-01 -6.71951473e-01 -4.05991822e-01 6.52932227e-01
2.22857848e-01 2.79136509e-01 -1.25821516e-01 4.75560099e-01
-9.94286835e-02 8.31074119e-02 1.83432132e-01 -1.54026583e-01
-2.68305272e-01 2.80397534e-01 -1.09172761e+00 6.66450083e-01
1.00838387e+00 -7.60878265e-01 -1.63457602e-01 -7.98021778e-02
4.21859831e-01 -1.26734480e-01 9.38141197e-02 -6.47634149e-01
4.24236894e-01 1.19795404e-01 6.92698658e-01 -5.77142775e-01
4.09720480e-01 -9.84917164e-01 3.33784789e-01 6.24335766e-01
-7.97993720e-01 4.84908611e-01 1.38093442e-01 2.51182735e-01
-4.83132750e-02 -5.24484634e-01 4.92869914e-01 -3.28359082e-02
-3.51590514e-01 -2.95040280e-01 -5.17938137e-01 3.71731371e-02
6.49349809e-01 -3.24465007e-01 -1.00805342e-01 -6.76567912e-01
-6.36363685e-01 -2.88558844e-02 1.45769626e-01 6.92085087e-01
2.59747714e-01 -1.26126158e+00 -6.03996217e-01 4.57129717e-01
1.69676855e-01 -4.85500574e-01 -2.34572217e-01 4.93466198e-01
-4.65332657e-01 7.19281256e-01 7.64138624e-02 -6.32283211e-01
-1.02971780e+00 3.01832646e-01 2.39342585e-01 -3.66597444e-01
-3.20025623e-01 8.32986116e-01 -3.03061664e-01 -6.64935946e-01
2.61730969e-01 -4.02018160e-01 -1.14129215e-01 5.18457711e-01
2.68398196e-01 4.11944300e-01 4.44560140e-01 -6.94018483e-01
-3.32866609e-01 1.42709300e-01 -6.27576232e-01 -3.74471806e-02
1.42571831e+00 1.23240486e-01 -4.22225520e-02 7.10354865e-01
1.63919926e+00 -9.77807343e-02 -5.38137674e-01 -3.40867966e-01
3.09573442e-01 -1.13109738e-01 5.57854597e-04 -7.62342393e-01
-5.91413856e-01 3.27535570e-01 4.88926977e-01 7.58211553e-01
5.85791886e-01 -1.12403847e-01 7.13748634e-01 5.99539816e-01
-9.03806239e-02 -1.25590062e+00 -1.35145813e-01 6.58481717e-01
6.99407518e-01 -1.08150709e+00 1.36231348e-01 9.14032087e-02
-7.27860093e-01 9.70336914e-01 3.58229905e-01 -6.15666099e-02
7.40636289e-01 1.93253323e-01 3.58852714e-01 -2.33508453e-01
-1.00674117e+00 4.48951989e-01 1.87715232e-01 -1.72491789e-01
6.47389948e-01 3.06876097e-02 -1.91089630e-01 8.18426847e-01
-8.29698563e-01 -1.58925876e-01 2.17505381e-01 8.94807994e-01
-3.20286423e-01 -7.72230983e-01 -1.68494552e-01 1.04912877e+00
-6.74004257e-01 -2.14475840e-01 -2.59467363e-01 7.67515898e-01
-1.80198506e-01 1.19104004e+00 4.71497536e-01 -9.21157300e-01
4.51687574e-01 6.41886175e-01 -3.30489784e-01 -4.08885449e-01
-1.11730540e+00 -5.52996397e-02 2.92867064e-01 -2.87895113e-01
-2.96408427e-03 -5.68539262e-01 -9.73805130e-01 -6.41803324e-01
-6.02033079e-01 2.39924178e-01 6.86867058e-01 6.87224329e-01
3.22484583e-01 1.39676347e-01 8.28115284e-01 -2.41226375e-01
-9.67899799e-01 -1.29482603e+00 -5.96928835e-01 5.05414665e-01
3.06020409e-01 -2.87095696e-01 -8.37926805e-01 2.69211996e-02] | [11.025479316711426, 7.386396884918213] |
f5f2a2a6-bd91-4523-847f-ba65e0d6a4e1 | 3-dimensional-sonic-phase-invariant-echo | 2306.08281 | null | https://arxiv.org/abs/2306.08281v2 | https://arxiv.org/pdf/2306.08281v2.pdf | 3-Dimensional Sonic Phase-invariant Echo Localization | Parallax and Time-of-Flight (ToF) are often regarded as complementary in robotic vision where various light and weather conditions remain challenges for advanced camera-based 3-Dimensional (3-D) reconstruction. To this end, this paper establishes Parallax among Corresponding Echoes (PaCE) to triangulate acoustic ToF pulses from arbitrary sensor positions in 3-D space for the first time. This is achieved through a novel round-trip reflection model that pinpoints targets at the intersection of ellipsoids, which are spanned by sensor locations and detected arrival times. Inter-channel echo association becomes a crucial prerequisite for target detection and is learned from feature similarity obtained by a stack of Siamese Multi-Layer Perceptrons (MLPs). The PaCE algorithm enables phase-invariant 3-D object localization from only 1 isotropic emitter and at least 3 ToF receivers with relaxed sensor position constraints. Experiments are conducted with airborne ultrasound sensor hardware and back this hypothesis with quantitative results. | ['Christopher Hahne'] | 2023-06-14 | null | null | null | null | ['object-localization'] | ['computer-vision'] | [ 5.21326840e-01 -5.86491562e-02 4.04317290e-01 -1.59142360e-01
-8.79906833e-01 -7.66542077e-01 6.06244624e-01 1.16996273e-01
-7.97033548e-01 1.20557182e-01 -4.62280363e-01 5.98951764e-02
-6.15083992e-01 -1.89061970e-01 -9.26013172e-01 -9.58859026e-01
-5.06985724e-01 7.04068065e-01 2.93379456e-01 3.58570188e-01
4.61632043e-01 1.16017139e+00 -1.40522373e+00 -1.07057758e-01
1.74293816e-01 1.19804728e+00 5.10362625e-01 1.17027056e+00
4.02606755e-01 3.33512187e-01 -3.86792064e-01 1.92896679e-01
3.33187521e-01 4.22644287e-01 2.69148886e-01 -2.25512251e-01
5.47132611e-01 -3.95858735e-01 -5.34962058e-01 9.11446691e-01
6.52102292e-01 -5.87447956e-02 8.70041847e-01 -1.04809308e+00
-1.55113295e-01 3.21278542e-01 -4.73539859e-01 1.46128431e-01
4.82355058e-01 -2.63439387e-01 4.13702250e-01 -1.18820274e+00
1.52996585e-01 9.66215312e-01 1.13910878e+00 1.27750129e-01
-5.82215846e-01 -7.14244545e-02 -4.84816343e-01 1.38759404e-01
-1.22437656e+00 -3.73475730e-01 7.84526646e-01 -6.50967240e-01
9.69889462e-01 1.47918403e-01 3.77533942e-01 9.31935012e-01
6.18373573e-01 2.45248526e-01 8.35584223e-01 -5.06003737e-01
1.35723487e-01 -1.00254819e-01 3.01414710e-02 7.81079113e-01
2.30847895e-01 6.22703731e-01 -7.10031211e-01 -7.12623307e-03
1.00019503e+00 -1.38834909e-01 -4.79281932e-01 -7.44669497e-01
-1.77263188e+00 4.29483503e-01 4.12523240e-01 7.99549073e-02
-6.80763662e-01 2.28638947e-01 -6.35982528e-02 -4.86110598e-02
4.07045856e-02 4.97731209e-01 -1.86834484e-01 -1.17244072e-01
-4.31758463e-01 -3.23308021e-01 8.65487754e-01 1.04688895e+00
4.80757803e-01 2.89605200e-01 2.73295164e-01 2.55555362e-01
6.26103342e-01 1.58442426e+00 5.19240610e-02 -9.38216925e-01
2.64473438e-01 -1.92394048e-01 4.75487500e-01 -1.05702782e+00
-7.13408768e-01 -6.76638186e-01 -6.72150612e-01 3.06720525e-01
4.43640560e-01 -2.65779704e-01 -8.50896537e-01 1.14930582e+00
5.09369314e-01 7.43732214e-01 4.52275664e-01 1.16687441e+00
5.62291682e-01 6.09815001e-01 -6.69011831e-01 -3.34415346e-01
9.33618009e-01 -2.87256241e-01 -2.60254174e-01 -3.28533977e-01
2.62774467e-01 -6.91194534e-01 2.21546859e-01 5.75658500e-01
-9.04084504e-01 -4.87851381e-01 -1.13709700e+00 6.76987469e-01
-1.89752400e-01 9.83816907e-02 2.46421233e-01 5.70926666e-01
-7.36624837e-01 2.54869938e-01 -1.06805551e+00 1.56716853e-01
-2.16071025e-01 3.60167414e-01 -2.28366435e-01 -6.02039918e-02
-8.37780595e-01 1.11493909e+00 1.24049768e-01 6.33474886e-01
-8.02425921e-01 -7.41167724e-01 -7.90577412e-01 -4.25665230e-01
1.71384633e-01 -2.63773203e-01 1.08201480e+00 -2.60584384e-01
-1.53807425e+00 6.70978189e-01 -1.14725545e-01 -5.46775937e-01
1.65320858e-01 -5.72696328e-01 -3.63371670e-01 7.47550845e-01
4.37034108e-02 2.78391004e-01 1.32721603e+00 -1.56075215e+00
-6.45567298e-01 -5.29902816e-01 -3.37453902e-01 3.32442760e-01
2.03680187e-01 -1.90373659e-01 -1.47301525e-01 2.14870498e-01
8.21888447e-01 -8.97357881e-01 -9.59814787e-02 -4.84702103e-02
-2.93858856e-01 -2.83791665e-02 5.93745053e-01 -2.24354088e-01
4.05254424e-01 -1.93261755e+00 1.91780254e-01 3.57755035e-01
1.57363877e-01 -1.42796353e-01 -6.66570440e-02 3.66190314e-01
9.66258496e-02 -6.98783040e-01 -9.16572586e-02 -1.86499134e-01
-8.47317800e-02 -3.15335654e-02 -3.81225258e-01 1.10450625e+00
-8.93948749e-02 5.09237826e-01 -1.04380965e+00 -2.31651112e-01
6.47648096e-01 5.31831443e-01 8.79261717e-02 1.69132188e-01
5.42901158e-02 6.96503460e-01 -6.01048648e-01 7.77519166e-01
8.66423249e-01 2.47774780e-01 -5.78127205e-01 -5.36509752e-01
-7.29877174e-01 -3.51000518e-01 -1.11836326e+00 1.56114316e+00
-4.76639271e-01 7.27616072e-01 5.25783420e-01 -9.96866107e-01
9.93477821e-01 4.66757715e-01 8.17766011e-01 -7.92152762e-01
1.80844620e-01 4.62335289e-01 -2.10751072e-01 -9.77792144e-01
3.39372993e-01 3.20060551e-02 -1.87653527e-01 2.17502102e-01
-1.50383011e-01 -4.51109976e-01 -4.71368521e-01 -2.13205695e-01
1.20093989e+00 -5.60987704e-02 -1.66785806e-01 1.49061993e-01
3.53943825e-01 1.08175583e-01 2.20907286e-01 1.16757405e+00
-1.39171720e-01 7.01395929e-01 -3.58015090e-01 -2.14099646e-01
-9.18068051e-01 -1.60830700e+00 -2.14648589e-01 3.43398958e-01
5.84303498e-01 5.43541491e-01 -1.95544675e-01 -2.74326414e-01
1.29008457e-01 5.32456934e-01 -2.98287809e-01 7.58051351e-02
-8.78948033e-01 -8.04231837e-02 5.67096233e-01 2.04500675e-01
1.45666108e-01 -5.96121430e-01 -1.47779477e+00 2.62244463e-01
6.48558587e-02 -1.52293169e+00 -4.19583358e-02 4.19352710e-01
-5.60206473e-01 -1.30416882e+00 -9.18484092e-01 -5.81357539e-01
6.96002364e-01 7.23187804e-01 5.44807136e-01 -9.00990188e-01
-2.87592292e-01 1.34129870e+00 -4.47576523e-01 -8.01879585e-01
-2.84128398e-01 -6.74331605e-01 7.20871985e-01 1.83601361e-02
2.37025514e-01 -4.57172722e-01 -3.74317080e-01 3.94578904e-01
-3.90005052e-01 -3.01260412e-01 7.97141492e-01 4.17482972e-01
5.73314726e-01 -7.43881240e-02 2.79773921e-01 9.20938700e-02
1.81121632e-01 -3.92800778e-01 -1.14285910e+00 1.73549384e-01
1.11991718e-01 -8.68019685e-02 3.59724790e-01 -6.66733980e-01
-6.79094732e-01 4.06611055e-01 1.76874131e-01 -8.81113112e-01
-3.12815845e-01 5.08936226e-01 4.19714928e-01 -6.02631032e-01
8.53256226e-01 5.94027996e-01 6.43693283e-02 5.79803425e-04
2.46687606e-01 8.52894843e-01 8.48822951e-01 -3.12419444e-01
1.02059603e+00 6.99042678e-01 5.47498167e-01 -1.55199587e+00
-6.88828945e-01 -6.94850981e-01 -9.48934853e-01 -8.16994786e-01
6.49043083e-01 -8.71841669e-01 -9.69726562e-01 6.04419410e-01
-1.43774974e+00 8.78525991e-03 -7.85541832e-02 1.38243139e+00
-5.33722103e-01 6.24980211e-01 -8.51502270e-02 -1.33117580e+00
-5.17528504e-03 -7.70188093e-01 1.25805736e+00 2.94827878e-01
2.84719765e-01 -8.11144233e-01 3.98160309e-01 7.94233382e-02
1.00189686e-01 2.68398196e-01 5.47176152e-02 -1.77805498e-01
-7.97148705e-01 -6.38693333e-01 1.66057255e-02 9.40004140e-02
-8.64821672e-02 -2.46181414e-01 -1.14806545e+00 -3.16522270e-01
4.09713656e-01 -1.18409552e-01 6.52813077e-01 1.12848115e+00
4.22579736e-01 1.57355219e-01 -6.16338968e-01 7.17005789e-01
1.28560770e+00 5.38160682e-01 -5.38729411e-03 1.50120512e-01
7.22352505e-01 5.15956521e-01 8.72360945e-01 5.95144749e-01
1.05432391e-01 4.20274109e-01 9.09898818e-01 2.37443462e-01
2.84766793e-01 1.52768210e-01 4.55012470e-01 6.67183280e-01
2.99018472e-02 -2.73160160e-01 -6.97675645e-01 3.80270451e-01
-1.41439211e+00 -6.53870821e-01 -3.19050759e-01 2.52834654e+00
4.87823226e-02 1.06308378e-01 -5.04853785e-01 5.04080020e-02
6.64368451e-01 -1.05929539e-01 -5.99631906e-01 -3.22382264e-02
-9.76596922e-02 -5.74961677e-02 9.90709364e-01 8.02193344e-01
-1.05539346e+00 3.59055340e-01 5.48876333e+00 2.72620827e-01
-1.47881067e+00 -1.50970474e-01 -5.13554275e-01 1.03655517e-01
-5.63351624e-02 -2.95269847e-01 -7.46382833e-01 7.06642866e-02
6.73420310e-01 3.86343241e-01 2.43592635e-01 3.66207570e-01
1.31753772e-01 -2.05610260e-01 -1.18548381e+00 1.28299320e+00
3.61615688e-01 -1.04727209e+00 -6.13033652e-01 -1.65822014e-01
1.40877008e-01 6.97295964e-01 2.11834282e-01 -3.72646689e-01
-1.86188132e-01 -6.62303150e-01 9.09637928e-01 8.02559614e-01
8.45520794e-01 -2.32137829e-01 3.87954444e-01 6.02999270e-01
-1.02885461e+00 -1.44058958e-01 -5.13520837e-01 2.37220973e-01
6.12229347e-01 7.65791059e-01 -1.47608376e+00 5.93036115e-01
6.87500775e-01 6.09960914e-01 4.09767419e-01 1.31501949e+00
-3.38872708e-02 2.02068821e-01 -1.09334934e+00 -4.68749404e-01
3.94809186e-01 -3.88062708e-02 1.33150589e+00 1.05864847e+00
1.00339127e+00 2.21149743e-01 -3.04747075e-02 4.70498979e-01
5.26283085e-01 -7.17994273e-01 -1.00903487e+00 2.03615710e-01
8.59195173e-01 1.23188818e+00 -6.25559747e-01 4.01870966e-01
-2.75344998e-01 5.13160288e-01 -3.70886981e-01 5.19465327e-01
-7.52730608e-01 -5.30005574e-01 1.34739429e-01 -4.47892100e-02
4.67154443e-01 -9.84057546e-01 1.59054562e-01 -6.70314848e-01
5.72312437e-02 7.09953383e-02 -1.94109321e-01 -1.08174348e+00
-1.13882053e+00 3.08613360e-01 8.04157853e-02 -1.57164323e+00
-8.51172730e-02 -8.93990099e-01 -3.86428177e-01 5.96696258e-01
-1.69526529e+00 -1.08197689e+00 -2.80194283e-01 4.76795912e-01
1.58994138e-01 -9.03326645e-02 7.63775766e-01 4.31671133e-03
2.60606147e-02 1.51132904e-02 2.72678226e-01 -8.58737230e-02
5.15436053e-01 -1.03693771e+00 -2.29831482e-03 8.35685670e-01
3.34091574e-01 1.41080528e-01 9.12019372e-01 -6.74895287e-01
-2.19952917e+00 -6.34616196e-01 4.57492620e-01 -5.91579139e-01
6.98207438e-01 -2.17012689e-01 -4.21860069e-01 4.57509190e-01
-1.36055186e-01 1.02843113e-01 2.52780430e-02 -3.86032015e-01
-1.62065223e-01 -2.34843522e-01 -9.58885014e-01 9.20735896e-02
6.22364163e-01 -4.42939490e-01 -6.33514345e-01 4.64981228e-01
4.89819169e-01 -9.12286997e-01 -7.70682454e-01 5.50062835e-01
8.03943098e-01 -8.15938473e-01 1.30689168e+00 1.71243832e-01
-2.16806501e-01 -3.08892697e-01 -4.33951497e-01 -1.27226424e+00
-5.18427230e-02 -8.77489924e-01 -1.84085473e-01 3.77428174e-01
1.51167274e-01 -9.28374946e-01 8.32078815e-01 -2.81471997e-01
-8.17401230e-01 -2.75756747e-01 -1.48533714e+00 -8.49991262e-01
-3.63063782e-01 -8.71183395e-01 -3.05546075e-01 6.07077360e-01
-1.85070649e-01 1.45683527e-01 -1.79228246e-01 1.46009588e+00
1.43314385e+00 8.27012658e-02 4.70468640e-01 -1.36423373e+00
-1.40442848e-01 -1.04425304e-01 -2.85175174e-01 -1.59240019e+00
-5.72434217e-02 -5.79001725e-01 6.31960273e-01 -1.32024086e+00
-5.31931579e-01 -7.94053793e-01 -9.11463052e-02 -2.34996423e-01
7.00992584e-01 -6.37185052e-02 -1.92963347e-01 2.09865808e-01
-4.52845335e-01 4.00015116e-01 9.31058526e-01 -4.76513021e-02
-1.15152098e-01 5.52577496e-01 2.23927975e-01 7.60572553e-01
4.78888184e-01 -5.52321732e-01 -2.93058753e-01 -8.56118917e-01
4.19423968e-01 7.23640025e-01 6.32892668e-01 -1.33739197e+00
9.49557364e-01 6.94729015e-02 3.75826359e-01 -1.15800309e+00
9.80071843e-01 -1.19296575e+00 2.69837938e-02 5.89255154e-01
-1.09867245e-01 -1.18671693e-01 -3.64720933e-02 8.24737728e-01
4.36161421e-02 -4.00476009e-01 5.92763126e-01 -7.03979507e-02
-6.76915109e-01 2.55863816e-01 -4.95788991e-01 -2.67003477e-01
1.07308483e+00 -6.53117299e-01 -2.27824599e-01 -3.53545994e-01
-5.24941802e-01 1.31190732e-01 -1.38889641e-01 5.80138564e-02
1.19918311e+00 -7.87337244e-01 -7.21759498e-01 4.45573062e-01
4.16718125e-02 6.80664703e-02 2.82297581e-01 1.16015565e+00
-6.73627675e-01 8.04476857e-01 7.03716278e-02 -1.43222594e+00
-1.23487210e+00 3.04673970e-01 6.48774147e-01 5.23869693e-01
-5.77203631e-01 1.30326903e+00 -1.49393067e-01 -6.04931891e-01
5.11258245e-01 -4.86735821e-01 -1.58470616e-01 -2.15515524e-01
2.21835956e-01 3.23227018e-01 -1.12935588e-01 -8.03554833e-01
-4.39030021e-01 1.43746364e+00 3.22173387e-01 -4.79779601e-01
1.22506177e+00 -1.72933862e-01 2.20015272e-01 5.41199386e-01
9.81241107e-01 1.50793001e-01 -1.78251123e+00 -3.09372962e-01
-9.63709131e-02 -2.43895233e-01 1.97685748e-01 -4.96095538e-01
-5.70376992e-01 1.10768592e+00 7.65684485e-01 4.85362291e-01
7.75579989e-01 1.61808804e-01 4.40794766e-01 9.45521533e-01
5.45329213e-01 -6.30798161e-01 2.25737259e-01 8.48523438e-01
6.58135533e-01 -9.36371684e-01 -3.12082559e-01 -2.89683968e-01
-1.24651209e-01 1.36829519e+00 2.57882383e-02 -1.86452776e-01
7.54770815e-01 5.79072535e-01 1.71612203e-01 -2.34995693e-01
-1.40760899e-01 1.16887808e-01 8.82938579e-02 1.05771935e+00
-3.31972480e-01 -1.21399947e-01 5.38135707e-01 -4.43964154e-02
1.71237186e-01 -4.31710422e-01 4.75852311e-01 1.10478044e+00
-9.68233287e-01 -3.40463102e-01 -8.17423403e-01 3.30151059e-02
-1.11600257e-01 1.95653901e-01 1.92273140e-01 5.59370041e-01
-1.29160255e-01 9.19287086e-01 1.68398917e-01 -4.53603745e-01
4.39904869e-01 -4.01846379e-01 1.01818788e+00 -2.66589284e-01
-7.25407526e-03 2.98604608e-01 -5.96723408e-02 -4.45351124e-01
-4.93921012e-01 -7.37132847e-01 -1.47367942e+00 5.81571281e-01
-3.58864337e-01 2.59294987e-01 1.42369914e+00 8.87139916e-01
3.08862120e-01 2.18955308e-01 9.36454058e-01 -1.42099011e+00
-9.33927238e-01 -7.89439201e-01 -5.55744410e-01 -7.16903925e-01
9.32538927e-01 -7.03791797e-01 -8.37041080e-01 -6.47442341e-02] | [7.513197898864746, -2.0268428325653076] |
8d1cdc1e-9589-48b6-81cd-020c4d736c56 | learning-low-dimensional-dynamics-from-whole | 2305.14369 | null | https://arxiv.org/abs/2305.14369v1 | https://arxiv.org/pdf/2305.14369v1.pdf | Learning low-dimensional dynamics from whole-brain data improves task capture | The neural dynamics underlying brain activity are critical to understanding cognitive processes and mental disorders. However, current voxel-based whole-brain dimensionality reduction techniques fall short of capturing these dynamics, producing latent timeseries that inadequately relate to behavioral tasks. To address this issue, we introduce a novel approach to learning low-dimensional approximations of neural dynamics by using a sequential variational autoencoder (SVAE) that represents the latent dynamical system via a neural ordinary differential equation (NODE). Importantly, our method finds smooth dynamics that can predict cognitive processes with accuracy higher than classical methods. Our method also shows improved spatial localization to task-relevant brain regions and identifies well-known structures such as the motor homunculus from fMRI motor task recordings. We also find that non-linear projections to the latent space enhance performance for specific tasks, offering a promising direction for future research. We evaluate our approach on various task-fMRI datasets, including motor, working memory, and relational processing tasks, and demonstrate that it outperforms widely used dimensionality reduction techniques in how well the latent timeseries relates to behavioral sub-tasks, such as left-hand or right-hand tapping. Additionally, we replace the NODE with a recurrent neural network (RNN) and compare the two approaches to understand the importance of explicitly learning a dynamical system. Lastly, we analyze the robustness of the learned dynamical systems themselves and find that their fixed points are robust across seeds, highlighting our method's potential for the analysis of cognitive processes as dynamical systems. | ['Vince Calhoun', 'Sergey Plis', 'Amrit Kashyap', 'Marlena Duda', 'Riyasat Ohib', 'Donghyun Kim', 'Eloy Geenjaar'] | 2023-05-18 | null | null | null | null | ['dimensionality-reduction'] | ['methodology'] | [ 1.23006172e-01 -7.38241374e-02 2.40921170e-01 -8.79576653e-02
-1.80885866e-01 -6.56414688e-01 9.41863298e-01 -2.78839916e-01
-5.16208947e-01 2.45817408e-01 6.07357979e-01 2.95292033e-04
-6.93675399e-01 -3.83341968e-01 -4.82686758e-01 -7.92233527e-01
-3.43333870e-01 4.61862236e-01 -1.39357314e-01 -7.80846030e-02
5.35680614e-02 4.98898506e-01 -1.25201392e+00 1.58526555e-01
6.08216524e-01 4.06459361e-01 1.69317394e-01 4.57774639e-01
4.15295303e-01 6.32542133e-01 -2.24742979e-01 5.23723625e-02
1.73635811e-01 -4.82004404e-01 -7.64227867e-01 -2.03807890e-01
3.00399065e-01 -3.29964161e-01 -6.38755083e-01 9.32218432e-01
3.33127886e-01 5.67280591e-01 9.95432734e-01 -8.32540095e-01
-7.19848573e-01 2.45250538e-01 -2.63132811e-01 7.97695935e-01
-9.92591679e-02 4.43870634e-01 9.13188040e-01 -8.05979192e-01
8.91180754e-01 1.31535697e+00 8.41459811e-01 6.63345158e-01
-1.92667580e+00 -4.37591553e-01 1.12609081e-01 1.98030785e-01
-1.23089552e+00 -5.75251162e-01 6.87887967e-01 -9.15744066e-01
1.25412118e+00 -1.27278492e-01 7.91977108e-01 1.43903208e+00
6.78315938e-01 4.78864014e-01 1.41326010e+00 6.32726029e-02
3.63613009e-01 -4.51954603e-01 4.84095305e-01 6.43642485e-01
2.50328928e-02 3.81562859e-01 -5.09877801e-01 -4.33420062e-01
1.03963959e+00 -6.94834581e-03 -4.54658866e-02 -5.34857213e-01
-1.49098873e+00 8.24875772e-01 2.53884494e-01 5.66767633e-01
-9.06181693e-01 3.43728930e-01 4.94322509e-01 8.74998644e-02
4.39127952e-01 6.38172686e-01 -2.43499398e-01 -1.36575252e-01
-1.08754814e+00 4.11814839e-01 4.57092643e-01 2.90228091e-02
3.24968696e-01 2.80158669e-01 -1.89886749e-01 7.05484092e-01
6.84302300e-02 1.34041801e-01 7.88052082e-01 -1.34482110e+00
6.99880645e-02 2.39206046e-01 -1.95084304e-01 -1.03559291e+00
-8.66806984e-01 -3.40844870e-01 -9.85320151e-01 8.02467912e-02
4.45015192e-01 -4.03530560e-02 -5.63652515e-01 2.07850337e+00
3.29752043e-02 5.09371161e-02 -1.42266810e-01 8.68406177e-01
8.58900845e-02 4.99146253e-01 3.07768464e-01 -3.96596581e-01
1.35621154e+00 -5.17561913e-01 -8.07711184e-01 -3.87875766e-01
5.53735137e-01 8.63589421e-02 1.01734829e+00 3.01260769e-01
-1.28395140e+00 -4.87253666e-01 -6.23467505e-01 -2.04970285e-01
-2.06391335e-01 -7.63455108e-02 8.77009630e-01 2.03417823e-01
-1.24201012e+00 1.00955248e+00 -1.59448183e+00 -2.49178588e-01
4.54951316e-01 4.29024726e-01 -4.52291548e-01 2.83187866e-01
-1.08754230e+00 1.00339758e+00 1.88574210e-01 2.33799219e-02
-1.13104701e+00 -9.49360490e-01 -6.86916411e-01 2.42872581e-01
-1.44579753e-01 -8.26325357e-01 9.26467717e-01 -6.85416102e-01
-1.28329098e+00 7.94043183e-01 -3.59754562e-01 -5.28327584e-01
1.88554063e-01 2.63384320e-02 -3.12928408e-01 3.39321166e-01
8.01311508e-02 6.97698295e-01 1.05144525e+00 -5.22517383e-01
2.90890396e-01 -5.38258851e-01 -2.81726986e-01 2.12854773e-01
-5.36344409e-01 -1.83168918e-01 1.53222218e-01 -8.15515995e-01
3.98351133e-01 -1.15511978e+00 -1.53918728e-01 8.34351480e-02
1.24830846e-02 -2.76522249e-01 4.19567466e-01 -9.89766717e-01
1.10664797e+00 -2.09853244e+00 7.11618543e-01 1.42377049e-01
7.75708973e-01 -1.70522228e-01 -2.31231570e-01 1.52445212e-01
-5.87260306e-01 2.66766790e-02 -4.82153565e-01 -1.09981045e-01
1.51654497e-01 1.29465222e-01 -1.52317256e-01 7.42641330e-01
1.59844294e-01 1.39814639e+00 -7.73399174e-01 6.63056076e-02
-2.43079662e-02 6.37304306e-01 -7.94526279e-01 -2.25566745e-01
-8.00108388e-02 4.83057648e-01 -9.08703730e-02 9.60043892e-02
9.51523781e-02 -2.75465518e-01 3.06688666e-01 -2.54377127e-01
-1.09292597e-01 3.12305868e-01 -7.75756001e-01 1.65978396e+00
-2.24657163e-01 1.04669511e+00 4.94342670e-02 -1.34765244e+00
4.07030553e-01 2.82571375e-01 7.70548224e-01 -9.04495060e-01
-3.18675973e-02 -1.51152015e-01 5.81918120e-01 -4.95973289e-01
-1.58585720e-02 -3.28790545e-01 9.89496112e-02 8.88882756e-01
3.38184863e-01 2.18086720e-01 7.53467605e-02 1.02543652e-01
1.44462609e+00 2.48563156e-01 1.34071872e-01 -6.34260654e-01
7.92078972e-02 -1.55224979e-01 3.61424804e-01 6.23440862e-01
-4.46615428e-01 1.79680318e-01 8.75733733e-01 -4.19855893e-01
-1.19578612e+00 -1.15044343e+00 -2.17097819e-01 1.02194691e+00
-6.94566667e-01 -2.09373087e-01 -8.91828597e-01 -5.18465713e-02
2.48756260e-03 6.39320076e-01 -1.03740096e+00 -5.93674242e-01
-6.55264676e-01 -9.73288476e-01 6.50309861e-01 6.21015728e-01
4.96467724e-02 -1.10551810e+00 -9.13977206e-01 3.38789970e-01
-1.13847889e-01 -1.05439639e+00 -2.29177639e-01 1.62293464e-01
-1.24256599e+00 -9.21545148e-01 -7.56733894e-01 -4.36510086e-01
5.47885299e-01 5.69651136e-03 8.59419942e-01 -3.87150437e-01
-5.69374979e-01 6.09997213e-01 3.44001859e-01 1.51937231e-01
-2.83251226e-01 4.11960937e-04 6.53414845e-01 -1.58549324e-01
3.30347359e-01 -9.86211479e-01 -7.18152523e-01 1.43193696e-02
-8.45118344e-01 -8.41953531e-02 4.04045403e-01 7.90856719e-01
5.72483301e-01 6.77822307e-02 3.80408466e-01 -4.62748826e-01
1.17099369e+00 -7.50759482e-01 -3.65434200e-01 -1.78695679e-01
-5.55132627e-01 5.63857555e-01 4.58381474e-01 -7.20491827e-01
-1.01028931e+00 -8.65380690e-02 2.46354356e-01 -6.07224584e-01
-1.22479014e-01 4.77488399e-01 4.25231725e-01 1.25773653e-01
9.43896592e-01 3.46008062e-01 4.35500443e-01 -3.39219183e-01
3.08861911e-01 -5.46650514e-02 5.22878349e-01 -5.15866041e-01
5.95873892e-01 7.77989626e-01 1.52517959e-01 -9.76480544e-01
-4.53169227e-01 -5.12777679e-02 -9.05512750e-01 -2.15470847e-02
9.78246212e-01 -7.94249415e-01 -1.18023765e+00 1.31612822e-01
-9.49144423e-01 -6.16111457e-01 -3.50953460e-01 7.86555409e-01
-9.03731167e-01 1.51066199e-01 -1.06009376e+00 -6.37522280e-01
-1.37925282e-01 -9.93738949e-01 8.87613356e-01 -2.77037829e-01
-7.35133886e-01 -1.28762662e+00 3.95481288e-01 -7.44109526e-02
4.78236169e-01 3.60338330e-01 1.31255162e+00 -3.83111745e-01
-2.66945302e-01 8.56159106e-02 8.00129697e-02 1.46856278e-01
-1.10562846e-01 -2.42812201e-01 -8.23256969e-01 -1.56915173e-01
5.23322701e-01 -1.39993340e-01 1.03913343e+00 8.25135589e-01
1.09225726e+00 -1.07471354e-01 -2.34089583e-01 6.04006469e-01
1.01766145e+00 -1.86986662e-02 4.85406846e-01 -5.31743616e-02
5.67638040e-01 1.08215857e+00 -2.81554967e-01 7.23453313e-02
3.43871564e-01 3.65399510e-01 -5.87713271e-02 2.86611438e-01
3.21413912e-02 -3.37281637e-02 6.91958368e-01 1.02048469e+00
-2.30140179e-01 5.05932152e-01 -1.23635614e+00 5.48657537e-01
-1.71172071e+00 -1.36413574e+00 -1.03431113e-01 1.76390374e+00
6.60228312e-01 7.44024813e-02 2.01193586e-01 -6.01876639e-02
2.11308897e-01 2.29882315e-01 -1.00557530e+00 -2.78380781e-01
-5.58870137e-02 3.24110419e-01 2.32979488e-02 4.05167520e-01
-7.64100254e-01 8.50360155e-01 7.40134287e+00 2.06659779e-01
-8.76862288e-01 4.70532358e-01 3.29783529e-01 -5.07254839e-01
-1.79473564e-01 -1.93997830e-01 -3.44787568e-01 1.68084547e-01
1.42376685e+00 -2.95819849e-01 1.08818257e+00 3.62747610e-01
5.96634746e-01 3.92868705e-02 -1.24026191e+00 8.23925316e-01
-9.93385538e-02 -1.31789160e+00 -3.07485104e-01 4.00729150e-01
5.75453937e-01 7.48016462e-02 3.08995098e-01 2.76389271e-01
2.13682920e-01 -1.27248192e+00 4.55445349e-01 1.15026891e+00
5.69384813e-01 -4.40167427e-01 1.46677326e-02 6.10445142e-01
-8.39280128e-01 -1.40870750e-01 -4.20785755e-01 -3.22013080e-01
2.17272099e-02 4.89170492e-01 -2.83224523e-01 -3.38860601e-01
5.30040622e-01 8.40715408e-01 -4.79429632e-01 3.52324009e-01
8.95115659e-02 6.98602200e-01 -3.09392869e-01 2.17954397e-01
1.02105245e-01 -2.14217231e-01 6.29255474e-01 8.52491617e-01
5.79645149e-02 2.94512868e-01 -3.84002835e-01 1.64286280e+00
3.02724242e-01 -2.31513605e-01 -7.17089176e-01 -5.25761783e-01
4.39979620e-02 1.19919038e+00 -8.34879279e-01 -5.71451969e-02
-9.15021226e-02 1.11118901e+00 5.48175693e-01 7.00316131e-01
-4.98019367e-01 2.94206515e-02 8.95261645e-01 6.89836740e-02
-2.12568529e-02 -8.94576192e-01 -1.40024945e-01 -1.36106658e+00
7.41173998e-02 -7.67838776e-01 1.02248192e-01 -8.71199787e-01
-1.22937679e+00 3.32984298e-01 3.25450480e-01 -5.87551713e-01
-6.23044789e-01 -7.79318035e-01 -3.87571186e-01 1.07744861e+00
-8.96899104e-01 -5.98891437e-01 -6.05757385e-02 7.18745768e-01
3.79267186e-01 -6.84919134e-02 1.00200558e+00 1.35397732e-01
-7.29146540e-01 2.97856815e-02 1.76034197e-01 -3.55274533e-03
4.10569042e-01 -1.00184691e+00 6.26639903e-01 7.31828511e-01
2.23232076e-01 1.16063631e+00 4.46689516e-01 -8.26913238e-01
-1.35509145e+00 -7.25576699e-01 4.89108562e-01 -7.95221031e-01
9.85491753e-01 -7.86444187e-01 -1.24085784e+00 8.88568938e-01
-7.13633969e-02 7.05343336e-02 6.13645732e-01 1.98609203e-01
-1.45451441e-01 3.54327172e-01 -7.68762529e-01 7.57100880e-01
1.42110026e+00 -1.06587088e+00 -8.17878604e-01 5.73305845e-01
4.87876147e-01 -4.97510284e-02 -9.58326101e-01 -2.24565305e-02
6.47688985e-01 -7.46666670e-01 1.13226652e+00 -9.51370418e-01
6.01855159e-01 2.38221824e-01 1.35221243e-01 -1.55960882e+00
-9.98190701e-01 -5.20956337e-01 -6.56654775e-01 7.05670536e-01
-1.02697536e-01 -6.16076767e-01 6.76753759e-01 9.01040554e-01
1.99768156e-01 -5.05964160e-01 -7.64325857e-01 -7.30480433e-01
4.62178648e-01 -4.23244566e-01 5.19755967e-02 1.21539116e+00
-2.00188644e-02 3.59946877e-01 -4.83937040e-02 -1.43846840e-01
7.21229613e-01 -2.68628955e-01 -1.35268550e-03 -1.48859036e+00
-3.08200836e-01 -5.94597816e-01 -2.36651033e-01 -5.29796302e-01
7.57045686e-01 -1.22282684e+00 -4.01140660e-01 -1.32463980e+00
2.17544258e-01 9.71028581e-02 -1.74335912e-01 5.10451794e-01
1.13026939e-01 -1.81377232e-02 4.79313023e-02 4.75551099e-01
-5.26878051e-02 6.08503163e-01 1.01153541e+00 8.37464407e-02
-3.55380267e-01 -4.69491035e-01 -6.08251393e-01 8.94620001e-01
7.59230733e-01 -6.02634668e-01 -4.85746264e-01 -3.49659026e-01
3.00251216e-01 1.55221999e-01 7.89040864e-01 -9.40767109e-01
2.65940428e-01 -1.62136590e-03 7.45831847e-01 -7.32695609e-02
2.95944929e-01 -4.14419264e-01 1.15465321e-01 6.92729592e-01
-5.14951825e-01 3.56764704e-01 3.35235685e-01 5.53507686e-01
1.21456072e-01 5.96402474e-02 6.80361450e-01 -2.91006863e-01
-5.47875643e-01 2.83385068e-01 -8.60870957e-01 2.24253744e-01
6.82198822e-01 -2.53083169e-01 -8.22267011e-02 -2.79937595e-01
-1.23700392e+00 -3.59563865e-02 -4.41648588e-02 3.89295220e-01
4.33078825e-01 -1.35767937e+00 -5.31355143e-01 3.19235206e-01
-3.72986883e-01 -6.75907850e-01 5.60667157e-01 1.20889378e+00
-1.89463705e-01 6.50227904e-01 -6.19384110e-01 -5.59253693e-01
-6.55662417e-01 4.75070924e-01 6.49169624e-01 -2.93381929e-01
-8.71363163e-01 5.47746301e-01 5.22451699e-01 -3.80173683e-01
-1.22917362e-01 -4.09965277e-01 -1.58460960e-01 4.90993798e-01
3.57911021e-01 5.96816599e-01 -1.02693662e-01 -6.74204588e-01
-3.45014274e-01 2.27455750e-01 1.49048805e-01 -4.49376374e-01
1.62448061e+00 -5.75505756e-02 -3.02254498e-01 7.41217852e-01
1.33056521e+00 -4.33741152e-01 -1.54999650e+00 -3.20165992e-01
6.39454648e-02 2.13590011e-01 3.57385218e-01 -5.31611502e-01
-8.30989838e-01 1.16513610e+00 8.48854721e-01 7.05860108e-02
8.97132874e-01 -2.17318147e-01 3.62978131e-01 5.63315868e-01
-2.92945839e-02 -1.29544616e+00 3.56002212e-01 5.78373551e-01
9.62099612e-01 -7.72340178e-01 4.40537371e-02 2.81734169e-01
-5.83141088e-01 1.02872086e+00 4.09717828e-01 -6.20640457e-01
8.05674016e-01 9.60540548e-02 -5.09455025e-01 -6.36865616e-01
-9.42939758e-01 2.01217365e-02 4.95648831e-01 4.84032720e-01
3.37641209e-01 2.24664919e-02 -1.84165344e-01 7.08729744e-01
-3.61709386e-01 -1.68370053e-01 3.74481112e-01 7.10538626e-01
-1.39307365e-01 -6.34564996e-01 -2.72837460e-01 7.43957520e-01
-3.80131543e-01 -1.88357696e-01 -2.52602190e-01 8.69791865e-01
-2.55105346e-01 1.41536877e-01 4.11192983e-01 1.01354076e-02
2.28530884e-01 7.97669649e-01 6.55633926e-01 -6.09174192e-01
-5.00280857e-01 1.50833830e-01 -4.31897312e-01 -1.02103364e+00
-3.35998088e-01 -1.23581874e+00 -1.28129447e+00 -2.00271845e-01
2.35209152e-01 -3.19359511e-01 5.40442646e-01 9.81372178e-01
5.28878272e-01 8.07830036e-01 -2.79038996e-02 -1.02729881e+00
-6.30246222e-01 -8.80141675e-01 -5.88958025e-01 4.90113467e-01
5.17852962e-01 -9.10208821e-01 -2.09108204e-01 2.21486911e-01] | [12.53559398651123, 3.4110279083251953] |
e2206218-ccd7-46c6-afd7-8bfcf0ef26b3 | learning-libraries-of-subroutines-for | null | null | http://papers.nips.cc/paper/8006-learning-libraries-of-subroutines-for-neurallyguided-bayesian-program-induction | http://papers.nips.cc/paper/8006-learning-libraries-of-subroutines-for-neurallyguided-bayesian-program-induction.pdf | Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction | Successful approaches to program induction require a hand-engineered
domain-specific language (DSL), constraining the space of allowed
programs and imparting prior knowledge of the domain. We contribute
a program induction algorithm that learns a DSL while
jointly training a neural network to efficiently search for programs
in the learned DSL. We use our model to synthesize functions on lists,
edit text, and solve symbolic regression problems, showing how the
model learns a domain-specific library of program components for
expressing solutions to problems in the domain. | ['Armando Solar-Lezama', 'Mathias Sablé-Meyer', 'Lucas Morales', 'Kevin Ellis', 'Josh Tenenbaum'] | 2018-12-01 | null | null | null | neurips-2018-12 | ['program-induction'] | ['computer-code'] | [ 3.50994855e-01 4.87179965e-01 -9.33880270e-01 -7.18475223e-01
-4.92705017e-01 -8.63096178e-01 3.40460956e-01 1.84338614e-01
1.07104115e-01 6.37728393e-01 -7.47983903e-02 -1.03004038e+00
1.28853828e-01 -1.46763110e+00 -1.50499094e+00 1.79690018e-01
-4.78447825e-01 3.63827497e-01 2.01912388e-01 -1.95816532e-01
3.78202349e-01 5.24519384e-01 -1.62928128e+00 4.93739307e-01
1.08734775e+00 3.22225183e-01 2.10705817e-01 1.08373880e+00
-5.08079290e-01 1.47752321e+00 -7.36804903e-01 -1.18268803e-01
-9.08487439e-02 -2.19962358e-01 -1.08210862e+00 -3.28320503e-01
2.18047485e-01 -2.73304462e-01 -3.44903648e-01 1.01565576e+00
-3.37495565e-01 -4.03389633e-02 3.51264775e-01 -1.56290066e+00
-7.92915285e-01 1.10882831e+00 2.33229741e-01 -3.31025600e-01
6.15825891e-01 3.57474625e-01 1.15839839e+00 -2.28869602e-01
9.13191438e-01 1.10301840e+00 5.46705008e-01 7.87224591e-01
-1.87475586e+00 -3.40997994e-01 -5.75344488e-02 -3.26553702e-01
-9.73927736e-01 -1.85378239e-01 6.22880816e-01 -7.93301105e-01
1.61529875e+00 2.18534961e-01 5.07120728e-01 6.40248239e-01
9.94527116e-02 6.18334591e-01 5.91471136e-01 -8.47731531e-01
3.20776463e-01 4.60915476e-01 6.44951105e-01 1.20604575e+00
9.43222344e-02 4.72280711e-01 -2.93132991e-01 -6.75734162e-01
8.00272703e-01 -2.56826878e-01 -9.16351452e-02 -8.54505897e-01
-8.77918661e-01 1.01025271e+00 1.85021520e-01 3.14650834e-02
2.95495927e-01 6.14120603e-01 8.67323816e-01 7.55107224e-01
-8.62642005e-02 1.05082250e+00 -9.45075393e-01 4.02320661e-02
-6.39654517e-01 4.80195701e-01 1.39206648e+00 1.30114949e+00
1.00992596e+00 2.51245975e-01 -1.34812873e-02 4.00968671e-01
3.13911028e-02 4.90602821e-01 1.65569335e-01 -1.02477765e+00
3.76260340e-01 1.00160265e+00 -8.94062221e-02 -6.08342111e-01
1.47322714e-01 -2.10373607e-02 1.66263163e-01 4.50649470e-01
1.80664491e-02 -3.41090471e-01 -4.74016428e-01 2.04638267e+00
-1.21366866e-01 -1.62683189e-01 2.02770039e-01 1.57006860e-01
5.31388402e-01 8.23599279e-01 -3.71795148e-02 -3.89980525e-02
4.73923504e-01 -8.24327111e-01 -2.28029722e-03 -4.32806104e-01
1.46128201e+00 1.84717655e-01 1.19852602e+00 2.59194404e-01
-1.27012277e+00 -4.54367608e-01 -1.21710443e+00 4.71542925e-02
-3.21227103e-01 2.07888305e-01 1.22183299e+00 5.37015140e-01
-1.45198691e+00 6.43030047e-01 -5.73008955e-01 -9.27460939e-03
2.23591298e-01 7.85462141e-01 -2.05184266e-01 -1.57775392e-03
-7.79725969e-01 8.00597429e-01 9.11864877e-01 -5.05286932e-01
-1.32540989e+00 -8.44230413e-01 -1.46523976e+00 3.96096222e-02
3.19126368e-01 -5.95806956e-01 1.65782368e+00 -1.32760036e+00
-1.38663316e+00 1.18523538e+00 -1.94600672e-01 -6.96863353e-01
-1.11466818e-01 1.83945373e-01 -3.02164227e-01 -2.88344324e-01
-8.87101367e-02 4.76714671e-01 5.98999023e-01 -1.05772614e+00
-5.05561829e-01 -1.26593187e-01 9.36083615e-01 -5.24900019e-01
1.83334537e-02 3.93245846e-01 -3.82939205e-02 -2.64809310e-01
-5.35185158e-01 -8.56585920e-01 -2.10132122e-01 -6.36451840e-02
-4.35146838e-01 -2.07401738e-01 6.32776916e-01 -4.40710634e-01
1.32732356e+00 -2.19894934e+00 4.77326512e-01 4.55746740e-01
1.13005236e-01 -4.93429899e-02 -2.75527149e-01 2.84843206e-01
-3.83421630e-01 2.74564266e-01 -4.19970244e-01 5.63356459e-01
4.73138899e-01 6.07379258e-01 -6.56226754e-01 1.47135437e-01
5.26499093e-01 9.22440886e-01 -8.32323015e-01 -3.91382098e-01
-9.53722075e-02 -2.73675710e-01 -1.41165805e+00 6.50298357e-01
-1.60845780e+00 4.13529091e-02 -5.27804315e-01 4.56496984e-01
4.01361495e-01 -1.39426470e-01 4.79144871e-01 3.60599637e-01
-2.21669674e-01 6.49200678e-01 -9.80129898e-01 1.82794559e+00
-9.84673917e-01 8.04363191e-01 1.00647368e-01 -1.10184646e+00
1.05380929e+00 -1.80515125e-02 -5.59413619e-02 -1.86401293e-01
-1.38573661e-01 3.23328137e-01 -2.58192755e-02 -7.71086097e-01
1.03862450e-01 1.47797927e-01 -5.93700826e-01 7.47464538e-01
2.23478898e-01 -5.05819380e-01 3.28146785e-01 3.66717041e-01
1.33950353e+00 4.25648242e-01 1.46754578e-01 -3.19117635e-01
5.96466541e-01 5.31815886e-01 4.46190745e-01 1.04849255e+00
5.65129936e-01 -3.11284870e-01 1.14659977e+00 -6.77574575e-01
-1.17487419e+00 -6.86146975e-01 1.21696241e-01 1.50427961e+00
-5.23355365e-01 -6.82566583e-01 -8.07320833e-01 -9.58868563e-01
4.95125279e-02 1.26386595e+00 -4.69437867e-01 -3.56579572e-01
-1.02320957e+00 -3.10733430e-02 9.84815657e-01 7.18409717e-01
2.02293484e-03 -1.16370130e+00 -7.00592875e-01 -7.37857521e-02
4.24748063e-01 -5.42604446e-01 -4.29796785e-01 6.84741199e-01
-9.36872959e-01 -1.39169645e+00 9.33214203e-02 -1.46751392e+00
1.16177607e+00 -6.96937621e-01 1.69008887e+00 4.58005488e-01
-3.52642179e-01 3.33642840e-01 2.59933978e-01 -1.06318846e-01
-1.15870512e+00 1.67300835e-01 -4.94437814e-01 -8.39773297e-01
3.51727873e-01 -7.25026190e-01 4.83471453e-01 -2.69476146e-01
-9.12990093e-01 1.42282233e-01 3.47356647e-02 9.01241362e-01
1.34303555e-01 1.92974165e-01 5.96325286e-02 -1.41864932e+00
6.22128785e-01 -4.07830000e-01 -1.41365409e+00 4.62516844e-01
-2.58487761e-01 9.28975821e-01 8.35262954e-01 -3.22030425e-01
-8.15940499e-01 4.57275391e-01 1.44717783e-01 -1.21400515e-02
-3.65060121e-01 9.26430404e-01 -4.39623535e-01 -2.17504874e-01
1.22738850e+00 3.18242192e-01 2.55637486e-02 1.13131329e-02
6.01360857e-01 1.53000087e-01 7.38632917e-01 -1.64404559e+00
8.12518835e-01 -3.11100841e-01 -4.62251279e-04 -1.56316325e-01
-3.47239166e-01 4.06945765e-01 -6.35537982e-01 4.54121411e-01
3.56162667e-01 -6.37140274e-01 -6.89480484e-01 4.55677696e-02
-1.50655353e+00 -1.16916454e+00 -4.43451285e-01 -2.53400117e-01
-8.73751223e-01 -1.82520092e-01 -2.69122958e-01 -5.27039289e-01
-4.77120765e-02 -1.39575458e+00 6.44486487e-01 -3.22186559e-01
-7.34404683e-01 -1.07053673e+00 3.96167010e-01 -5.88441253e-01
2.73529321e-01 1.93257704e-01 2.02440476e+00 -9.15404320e-01
-9.63393688e-01 -6.74641430e-02 -1.03169113e-01 4.63321447e-01
-7.10082799e-02 3.43554378e-01 -5.09562135e-01 1.53960422e-01
-2.75629699e-01 -5.33253908e-01 1.00122303e-01 1.68277755e-01
1.70151150e+00 -7.96959221e-01 -5.30207753e-01 8.67425144e-01
1.42688930e+00 2.50287235e-01 4.38404918e-01 3.56187612e-01
1.41545996e-01 4.05257761e-01 6.34598881e-02 1.89222679e-01
2.27728654e-02 3.25511426e-01 1.71129376e-01 3.64074141e-01
1.99437737e-01 -4.97566789e-01 5.23940444e-01 1.69696957e-02
4.76455569e-01 4.57487375e-01 -1.22272956e+00 7.19914079e-01
-1.64195609e+00 -7.06067383e-01 1.84421211e-01 2.09218597e+00
1.49312758e+00 2.14528784e-01 2.73041695e-01 -1.53227493e-01
4.83594239e-01 -1.06537849e-01 -7.02872992e-01 -9.28165615e-01
2.66957402e-01 8.28255713e-01 4.99926567e-01 8.92640293e-01
-8.53426635e-01 8.93508315e-01 7.78833580e+00 1.67086571e-01
-1.17111266e+00 -3.51919740e-01 -5.10348678e-02 2.09466517e-01
-9.07278299e-01 3.79967391e-01 -6.65613472e-01 5.13159670e-02
1.23926592e+00 -7.54823744e-01 9.71183300e-01 1.57219362e+00
-3.27503592e-01 1.51889130e-01 -1.90957665e+00 1.96070880e-01
-1.47034496e-01 -1.68688953e+00 -6.85091838e-02 -4.34082747e-01
6.63421690e-01 -8.63705426e-02 -2.07277358e-01 9.28302646e-01
1.15915573e+00 -1.24408901e+00 6.21637940e-01 3.07613432e-01
8.99098456e-01 -9.08368528e-01 3.86024825e-02 5.30436277e-01
-6.65479660e-01 -2.70468146e-01 -2.91251135e-03 -2.78278172e-01
-5.77428222e-01 2.58968860e-01 -1.02235925e+00 -1.11535557e-01
1.19310558e-01 7.54136145e-01 -4.81747359e-01 6.85678065e-01
-6.74953520e-01 4.65538889e-01 -7.75441155e-02 -2.48113453e-01
-4.11240906e-02 9.93711650e-02 4.24300581e-01 1.55991066e+00
1.68661177e-01 5.11554815e-02 4.14391071e-01 1.66774189e+00
-1.28615722e-01 -4.06106830e-01 -1.12383795e+00 -4.76471275e-01
4.28781658e-01 5.07328451e-01 -9.48281866e-03 -5.08553267e-01
-4.37747270e-01 5.36468387e-01 4.66892064e-01 4.21395451e-01
-8.41436148e-01 -8.48812222e-01 4.97708410e-01 -2.57126195e-03
1.66244969e-01 -3.50032210e-01 -7.06835210e-01 -1.16001105e+00
6.57615215e-02 -1.38841200e+00 3.30792725e-01 -8.28166187e-01
-5.96102476e-01 3.23425651e-01 3.15231562e-01 -3.79532635e-01
-7.24624336e-01 -8.38278949e-01 -7.81265020e-01 1.13431060e+00
-1.08176756e+00 -6.96392179e-01 1.73855394e-01 4.48668361e-01
2.98413426e-01 -4.76332098e-01 1.26621735e+00 -5.09398580e-02
-3.80432069e-01 6.07845783e-01 -4.19326216e-01 2.13590130e-01
1.12287946e-01 -1.38578713e+00 6.08186126e-01 7.41929948e-01
-4.25893992e-01 1.40553617e+00 8.17748904e-01 -5.06337762e-01
-2.04768515e+00 -1.20612860e+00 7.89519548e-01 -5.37600338e-01
1.00138450e+00 -3.50164890e-01 -8.24633062e-01 1.42521429e+00
2.64756978e-02 -9.02669132e-02 3.80997181e-01 2.87495792e-01
-9.38602567e-01 8.95060003e-02 -1.04921091e+00 5.85903943e-01
1.03123891e+00 -1.17686665e+00 -7.37776697e-01 3.25592518e-01
1.18745565e+00 -8.17699254e-01 -7.21261561e-01 1.27796829e-01
3.18352312e-01 -3.68365735e-01 8.73545766e-01 -1.27858436e+00
1.11305845e+00 -4.11348224e-01 -3.52880806e-01 -1.34694839e+00
1.80820793e-01 -5.52906215e-01 -5.12731731e-01 9.35152590e-01
8.01639795e-01 -4.83361542e-01 9.02537823e-01 1.11808503e+00
-2.40420923e-01 -4.63944703e-01 -6.70270771e-02 -6.86083913e-01
3.24567229e-01 -6.46929383e-01 8.72569084e-01 8.43002915e-01
5.61019778e-01 2.28869841e-01 1.51440591e-01 2.63477534e-01
2.45467082e-01 5.48442900e-01 9.31919515e-01 -1.11004257e+00
-1.04606354e+00 -4.88192052e-01 1.32571340e-01 -9.39029574e-01
1.11881804e+00 -1.55044329e+00 1.83435380e-01 -1.18232226e+00
1.77681506e-01 -6.94687486e-01 2.55866885e-01 8.98183227e-01
5.77811539e-01 -9.75272119e-01 -3.76895577e-01 -1.27300516e-01
-3.20596218e-01 6.40460290e-04 6.37476325e-01 -6.08458281e-01
-2.44908214e-01 -1.13489181e-02 -8.03869963e-01 6.86961234e-01
5.83110750e-01 -7.56712735e-01 -6.51992798e-01 -6.50833011e-01
7.63021231e-01 4.38334465e-01 4.05503929e-01 -7.72022784e-01
3.43129545e-01 -7.41187096e-01 -3.32028836e-01 -6.09916188e-02
-4.09738421e-01 -6.40274823e-01 1.43445477e-01 6.54943109e-01
-1.29534638e+00 -8.96249041e-02 6.24161482e-01 8.77152979e-02
-3.07942390e-01 -8.83111238e-01 5.73138952e-01 -3.55687499e-01
-9.81908381e-01 -1.76163588e-03 -3.29988003e-01 1.15157552e-01
9.14091289e-01 2.21450061e-01 -1.75090224e-01 -1.04218073e-01
-6.93623185e-01 1.58561856e-01 8.84417534e-01 9.64633226e-02
2.65793353e-01 -8.59605253e-01 -1.79979309e-01 5.82926512e-01
3.35630894e-01 -5.21313306e-03 -5.75237572e-01 -2.96631712e-03
-9.00119960e-01 4.54859525e-01 -2.00731263e-01 -2.17720091e-01
-1.11131930e+00 8.31718087e-01 5.87031126e-01 -2.25042552e-01
-2.15395778e-01 8.42876315e-01 8.96329507e-02 -1.37197077e+00
4.32078421e-01 -8.12877595e-01 4.67398018e-01 -9.91750062e-01
4.72162396e-01 -2.42588580e-01 -1.83142647e-01 3.42528552e-01
-3.32884043e-01 4.33431417e-02 7.29441866e-02 8.44914690e-02
1.51208103e+00 8.57120991e-01 -1.04131961e+00 1.21799238e-01
1.21609271e+00 7.30455574e-03 -7.74761260e-01 -3.05098027e-01
3.83683473e-01 -4.62457985e-02 -1.49320140e-01 -8.47329974e-01
-5.33971012e-01 7.07966805e-01 -1.93865433e-01 2.75364742e-02
1.01702762e+00 6.79967999e-02 2.17109308e-01 1.24063492e+00
6.06550455e-01 -6.84426665e-01 1.05201632e-01 1.12316310e+00
7.86810338e-01 -7.55880356e-01 -2.57222384e-01 -4.86361235e-01
-9.88109335e-02 1.48200655e+00 7.10285068e-01 -4.59601700e-01
3.07347327e-01 1.11940813e+00 -7.43670404e-01 -1.91788390e-01
-8.92080724e-01 3.89017254e-01 -4.08606650e-03 9.77672696e-01
5.51049292e-01 -1.07433140e-01 8.84405822e-02 7.41192520e-01
-2.31696874e-01 6.20995283e-01 4.06703889e-01 1.43900096e+00
-4.23086584e-01 -1.65955484e+00 -2.37856746e-01 4.27535325e-01
-1.54864147e-01 -3.24913710e-01 -3.68922979e-01 8.49435210e-01
2.48636588e-01 2.48167381e-01 -1.53290823e-01 -1.82884783e-01
2.58864522e-01 3.02313119e-01 8.64002109e-01 -1.24876535e+00
-5.22474587e-01 -8.32713306e-01 6.78392649e-01 -4.70565945e-01
7.73290768e-02 -4.01455611e-01 -1.45398843e+00 -1.97722748e-01
1.27984853e-02 2.47527286e-01 4.99137938e-01 6.18363023e-01
3.62364799e-01 4.30354744e-01 4.07455325e-01 -2.42836624e-01
-5.36566198e-01 -1.87236726e-01 -1.89715803e-01 1.17330244e-02
6.07687116e-01 1.21092476e-01 -7.43357614e-02 4.48733330e-01] | [8.455288887023926, 7.244536876678467] |
098b85e8-f0cf-45ac-8883-2be980dcbd30 | partcom-part-composition-learning-for-3d-open | 2211.10880 | null | https://arxiv.org/abs/2211.10880v1 | https://arxiv.org/pdf/2211.10880v1.pdf | PartCom: Part Composition Learning for 3D Open-Set Recognition | 3D recognition is the foundation of 3D deep learning in many emerging fields, such as autonomous driving and robotics.Existing 3D methods mainly focus on the recognition of a fixed set of known classes and neglect possible unknown classes during testing. These unknown classes may cause serious accidents in safety-critical applications, i.e. autonomous driving. In this work, we make a first attempt to address 3D open-set recognition (OSR) so that a classifier can recognize known classes as well as be aware of unknown classes. We analyze open-set risks in the 3D domain and point out the overconfidence and under-representation problems that make existing methods perform poorly on the 3D OSR task. To resolve above problems, we propose a novel part prototype-based OSR method named PartCom. We use part prototypes to represent a 3D shape as a part composition, since a part composition can represent the overall structure of a shape and can help distinguish different known classes and unknown ones. Then we formulate two constraints on part prototypes to ensure their effectiveness. To reduce open-set risks further, we devise a PUFS module to synthesize unknown features as representatives of unknown samples by mixing up part composite features of different classes. We conduct experiments on three kinds of 3D OSR tasks based on both CAD shape dataset and scan shape dataset. Extensive experiments show that our method is powerful in classifying known classes and unknown ones and can attain much better results than SOTA baselines on all 3D OSR tasks. The project will be released. | ['Jiang Haiyong', 'Xiao Jun', 'Weng Tingyu'] | 2022-11-20 | null | null | null | null | ['open-set-learning'] | ['miscellaneous'] | [-8.15856904e-02 2.19072580e-01 -3.66695881e-01 -7.09377706e-01
-7.70007670e-01 -5.71340978e-01 7.09232986e-01 -2.95642227e-01
5.35695255e-02 1.83474392e-01 -1.38700724e-01 -5.18063784e-01
2.76992805e-02 -8.72336924e-01 -1.17974365e+00 -3.82487237e-01
9.08973888e-02 8.51170063e-01 5.68158209e-01 -3.95834655e-01
2.80967832e-01 1.09623015e+00 -2.24924207e+00 2.50824332e-01
6.58810079e-01 1.34204769e+00 -1.75782129e-01 -7.22360834e-02
-3.79967421e-01 7.89668038e-02 -7.24171162e-01 -3.21708560e-01
7.02911198e-01 3.97525206e-02 -4.51037586e-01 3.18333089e-01
6.66438341e-01 -2.67211765e-01 -1.94980785e-01 9.56398666e-01
5.13569176e-01 5.29662445e-02 1.11685359e+00 -1.57518268e+00
-4.20557171e-01 3.73975396e-01 -5.46498418e-01 1.53846666e-02
2.27070540e-01 1.93557233e-01 6.89821899e-01 -1.07026100e+00
3.97360384e-01 1.51698220e+00 7.64718592e-01 6.48440599e-01
-7.50182271e-01 -1.09560859e+00 3.26479912e-01 2.91491985e-01
-1.36393845e+00 -3.87235492e-01 9.83590364e-01 -4.37982231e-01
9.04392540e-01 2.39080876e-01 4.69733715e-01 1.20614982e+00
3.82015407e-01 1.20937085e+00 8.99343073e-01 -5.19689918e-02
2.65736073e-01 5.71627617e-02 4.94814754e-01 5.55122495e-01
5.05329728e-01 5.76057553e-01 -2.81568974e-01 5.80414869e-02
3.65261793e-01 3.62190567e-02 1.63950741e-01 -8.16647530e-01
-8.35030079e-01 7.18072236e-01 5.10456383e-01 3.83579498e-03
6.86178207e-02 -2.75028676e-01 6.45310432e-02 1.97456732e-01
3.70587975e-01 2.05393448e-01 -6.31693840e-01 1.64870605e-01
-2.97139198e-01 3.13146293e-01 6.28655195e-01 1.29394889e+00
9.53968704e-01 -5.43490611e-02 -1.01236030e-01 1.06425846e+00
2.71852434e-01 7.02114224e-01 4.27688062e-01 -5.32955766e-01
3.44272941e-01 9.28700149e-01 -2.27240101e-01 -6.96641266e-01
-4.24093992e-01 -4.07183319e-01 -6.22596264e-01 5.43390036e-01
1.09864160e-01 4.29132789e-01 -1.48172736e+00 1.29515970e+00
4.94902432e-01 3.46397199e-02 -6.88530579e-02 7.36073315e-01
1.10103476e+00 2.74827242e-01 -5.54066300e-01 3.16005439e-01
1.10407078e+00 -6.21641219e-01 -3.46130222e-01 -4.60124224e-01
7.14735448e-01 -4.08504665e-01 9.01989460e-01 3.86662424e-01
-4.72184688e-01 -8.07850778e-01 -1.39415586e+00 4.54357788e-02
-6.10878766e-01 4.23598737e-02 4.67209876e-01 9.11296070e-01
-3.28930229e-01 4.75198418e-01 -8.51068914e-01 1.80210218e-01
9.05668139e-01 2.99963027e-01 -5.92334330e-01 -4.07987505e-01
-8.79709005e-01 1.03673589e+00 2.34571159e-01 -1.84555892e-02
-1.25387931e+00 -6.73283696e-01 -1.24926233e+00 -3.89995903e-01
4.88983244e-01 -3.20096821e-01 1.17685950e+00 -3.88765424e-01
-1.06264126e+00 9.63773668e-01 4.79143076e-02 -2.38773927e-01
5.11285901e-01 -2.06074864e-01 -5.10497451e-01 -3.52736801e-01
1.69719711e-01 5.02628446e-01 9.35523391e-01 -1.47288132e+00
-5.48677802e-01 -6.68615162e-01 1.18465070e-02 8.54041718e-04
1.66327506e-01 -3.50800484e-01 -2.43572548e-01 -4.06433254e-01
6.42893255e-01 -9.18198228e-01 -1.05477504e-01 1.43854260e-01
-5.46832323e-01 -4.05798733e-01 8.08024406e-01 -9.64959860e-02
5.39225340e-01 -2.27136469e+00 -3.63930881e-01 2.27924198e-01
2.23424494e-01 3.77001643e-01 -2.95591474e-01 -1.26168728e-01
-1.34979367e-01 1.74142122e-01 -4.21068341e-01 -1.10011220e-01
1.71831235e-01 4.86619353e-01 -4.75999683e-01 4.66340423e-01
7.10616469e-01 8.29166114e-01 -5.69756031e-01 -1.34906471e-01
3.15724432e-01 2.13831753e-01 -3.66349816e-01 1.76823393e-01
-1.87948942e-01 5.67298196e-02 -6.64986730e-01 1.16878939e+00
1.04126287e+00 3.53691250e-01 -4.33068752e-01 -1.80326566e-01
2.27098539e-01 3.68717045e-01 -1.30618322e+00 1.23229849e+00
-2.95616210e-01 2.21929625e-01 -3.50688785e-01 -1.27649200e+00
1.53822029e+00 -2.28531674e-01 1.93449631e-01 -6.55667365e-01
3.62178802e-01 3.45981002e-01 1.88902691e-01 -3.50825429e-01
3.77327710e-01 -2.47876540e-01 -1.92213640e-01 2.07781136e-01
2.00091619e-02 -6.48249626e-01 -3.30899507e-01 -3.11376005e-01
1.08613861e+00 1.91047639e-01 1.99771255e-01 -9.52291638e-02
3.30118388e-01 4.36026827e-02 6.56392634e-01 8.59224439e-01
-3.97968739e-01 8.26573074e-01 3.80897462e-01 -6.15050018e-01
-6.67114377e-01 -1.09666014e+00 -5.17819703e-01 3.76176298e-01
6.13359988e-01 2.42683701e-02 -1.86626941e-01 -1.29110384e+00
5.68298995e-01 8.41444552e-01 -6.89787209e-01 -6.44901276e-01
-3.99586111e-01 -4.84501272e-01 4.83984321e-01 8.13604951e-01
3.30572337e-01 -7.32921362e-01 -4.25795764e-01 -2.17399791e-01
2.22744942e-01 -9.57386434e-01 -2.22559899e-01 3.86899263e-01
-7.38207281e-01 -1.37733996e+00 -4.51194137e-01 -7.87426531e-01
7.39817798e-01 6.29039407e-01 1.05418611e+00 -5.02488986e-02
-4.30488527e-01 2.11247608e-01 -6.06883585e-01 -9.24597919e-01
-6.32490814e-01 -2.26184011e-01 3.75534505e-01 6.17129020e-02
6.88051164e-01 -3.46736461e-01 -1.15849897e-01 9.63668048e-01
-6.24847293e-01 -3.93716067e-01 8.56249094e-01 7.42700458e-01
9.03235137e-01 3.05676937e-01 5.01863658e-01 -6.90289319e-01
1.63295984e-01 -4.69281703e-01 -6.44376040e-01 1.07143193e-01
-4.94390637e-01 2.92284697e-01 2.73030758e-01 -7.98216403e-01
-6.54159129e-01 3.00694764e-01 -3.42215836e-01 -9.51315463e-01
-4.68668997e-01 1.29542008e-01 -8.44883144e-01 -1.27513573e-01
7.36818314e-01 2.19372824e-01 1.56966284e-01 -7.91857123e-01
2.01103285e-01 7.88802505e-01 2.54297197e-01 -6.96634710e-01
1.18091524e+00 4.42586064e-01 4.11760733e-02 -7.38794148e-01
-8.07813406e-01 -5.56126058e-01 -6.26971960e-01 -1.94360048e-01
3.47178608e-01 -9.40979421e-01 -3.06828469e-01 5.83475113e-01
-8.95244598e-01 -3.14507969e-02 -3.37165385e-01 3.01354140e-01
-4.15150464e-01 2.98936248e-01 1.59211323e-01 -7.92094767e-01
1.65925235e-01 -1.41238153e+00 1.49546456e+00 -4.43457216e-02
1.58420950e-01 -2.70736486e-01 -3.06781441e-01 3.58089626e-01
-7.19071925e-02 1.31879970e-01 8.61585081e-01 -1.12266541e+00
-5.54060698e-01 -6.21526778e-01 4.45030779e-02 6.14849925e-01
8.93094689e-02 -2.45101586e-01 -1.11912346e+00 -5.70609383e-02
7.48093426e-02 -4.73778784e-01 1.09932280e+00 8.76888037e-02
1.27356851e+00 1.62700430e-01 -6.34240985e-01 5.18006980e-01
7.62502670e-01 3.33827913e-01 6.43903017e-01 7.49820098e-02
6.08570516e-01 7.60131359e-01 9.39288437e-01 1.67764351e-01
3.13465595e-01 5.68561137e-01 6.72636449e-01 1.44386694e-01
-3.04677039e-01 -4.52127010e-01 4.27896559e-01 3.18017274e-01
3.91808867e-01 -1.56585664e-01 -1.05099356e+00 4.92090434e-01
-1.42318487e+00 -6.53299689e-01 -1.28736541e-01 2.22349524e+00
4.87801969e-01 7.09369600e-01 2.55830083e-02 4.78840202e-01
7.31420457e-01 -7.62007907e-02 -9.37252700e-01 -4.71328944e-02
-1.71947256e-01 2.11150736e-01 5.00957847e-01 1.18437253e-01
-1.22160149e+00 7.01645970e-01 5.84831524e+00 1.00116670e+00
-9.26051617e-01 -2.38204122e-01 5.70209086e-01 2.68248558e-01
-4.26660478e-01 -1.65915981e-01 -1.34449375e+00 1.70337304e-01
3.29867721e-01 4.26440164e-02 -3.22708972e-02 1.21911681e+00
-4.25139457e-01 6.16087168e-02 -1.46121466e+00 1.11635900e+00
2.64414161e-01 -1.12023568e+00 2.94377387e-01 2.11241499e-01
4.82141405e-01 1.50241479e-01 -4.70570177e-02 7.11400926e-01
1.72918022e-01 -9.39030468e-01 1.02450335e+00 2.51562536e-01
8.40563536e-01 -7.53825545e-01 7.04674721e-01 7.62581289e-01
-1.14954972e+00 -1.13916814e-01 -5.80801070e-01 -1.67541113e-02
-1.80300400e-01 7.51168430e-01 -8.21288288e-01 6.33928418e-01
7.29308903e-01 8.75821233e-01 -5.55990160e-01 1.17295444e+00
-2.61955053e-01 3.46551508e-01 -5.57653010e-01 -2.49938108e-02
-5.34461588e-02 9.37609151e-02 6.88129246e-01 4.59516138e-01
3.45547259e-01 9.26484168e-02 2.94189394e-01 1.08220422e+00
-4.15418632e-02 -3.75154465e-01 -1.07728982e+00 6.30715042e-02
4.41605777e-01 8.30957294e-01 -6.79636776e-01 -4.83217128e-02
-3.41530889e-01 3.79489690e-01 9.26928520e-02 -1.48031741e-01
-7.46522546e-01 -4.47168738e-01 9.78807688e-01 1.75562471e-01
5.10558188e-01 -2.64084190e-01 -3.60431790e-01 -1.16030657e+00
3.32270145e-01 -8.20343137e-01 2.77762830e-01 -5.44602454e-01
-1.57701957e+00 5.84091425e-01 1.92772225e-01 -1.75052035e+00
3.67681049e-02 -1.08528864e+00 -4.40871507e-01 4.82855767e-01
-1.67618966e+00 -1.07162738e+00 -1.68407217e-01 2.02840731e-01
7.07565963e-01 -3.25177252e-01 4.84059662e-01 1.55773744e-01
-4.48005348e-01 7.99108386e-01 -1.72755286e-01 1.38489991e-01
4.59915072e-01 -8.86007667e-01 9.11091149e-01 6.29304051e-01
2.79588699e-01 2.16626123e-01 3.51815969e-01 -9.11946416e-01
-1.56814194e+00 -1.24441051e+00 4.25758064e-01 -9.60330665e-01
2.97331154e-01 -6.75374329e-01 -9.52204883e-01 4.86465007e-01
-9.48272586e-01 4.79500294e-01 4.05319959e-01 1.37753010e-01
-7.71914780e-01 -1.13679186e-01 -1.16798985e+00 1.82506442e-01
1.49368215e+00 -3.20891827e-01 -1.05652010e+00 2.40466282e-01
7.56180227e-01 -6.76826954e-01 -5.96511424e-01 1.08738029e+00
6.02391958e-01 -9.57993925e-01 1.13562500e+00 -6.14304543e-01
1.74186587e-01 -4.02109534e-01 -4.16000277e-01 -1.18171048e+00
2.42335834e-02 -1.47030294e-01 -1.47126958e-01 1.06593192e+00
3.67833823e-01 -7.78048217e-01 8.38042319e-01 5.22667348e-01
-8.25316608e-01 -7.11289883e-01 -1.13995743e+00 -1.45547581e+00
2.26789325e-01 -1.04829705e+00 1.01036286e+00 7.36289144e-01
-5.53780794e-01 1.96606398e-01 6.39606714e-02 4.55567718e-01
5.19149661e-01 2.56148815e-01 1.08232331e+00 -1.59333169e+00
5.04245758e-02 -4.99557585e-01 -9.58109558e-01 -1.07997763e+00
4.89373684e-01 -1.13421035e+00 2.88069725e-01 -1.19067407e+00
-3.14759947e-02 -8.69541466e-01 -1.85222521e-01 7.15379655e-01
9.81275737e-02 1.64950639e-01 -1.59734175e-01 6.91699535e-02
-2.23661661e-01 8.19844127e-01 1.33759475e+00 -6.32328629e-01
-9.21833813e-02 4.98704135e-01 -7.31098890e-01 6.72494650e-01
5.53294539e-01 -4.61659372e-01 -3.71933430e-01 -3.67730409e-01
-1.67523041e-01 -2.65358448e-01 3.69688034e-01 -1.06772637e+00
-2.95045197e-01 -1.90555170e-01 4.39749599e-01 -1.20587027e+00
4.33482826e-01 -8.80978227e-01 -5.92893697e-02 3.73424053e-01
-1.99098382e-02 -4.65665072e-01 4.65908289e-01 7.21272707e-01
-6.68267310e-02 -1.10809788e-01 7.05676317e-01 4.20202464e-02
-8.56297016e-01 6.00342751e-01 -1.94257293e-02 9.05853510e-02
1.06473053e+00 -6.47942126e-01 -2.75009900e-01 6.38411567e-02
-3.88918430e-01 3.50811750e-01 4.58433688e-01 1.04969549e+00
9.57404792e-01 -1.50106454e+00 -5.94478428e-01 8.90958369e-01
7.62840748e-01 4.73080128e-01 6.28933907e-02 2.97348917e-01
-5.02811708e-02 6.72833771e-02 -1.86954886e-01 -8.54512751e-01
-1.02869713e+00 6.52076602e-01 5.58652222e-01 4.01032507e-01
-8.18141818e-01 9.57769513e-01 4.69992012e-01 -9.90709364e-01
4.44952160e-01 -6.17747843e-01 -2.84545928e-01 -1.57725498e-01
4.81500536e-01 1.10699765e-01 4.56861824e-01 -8.48921657e-01
-6.22955799e-01 7.65108645e-01 -5.37666231e-02 5.18852174e-01
1.21333802e+00 2.48816997e-01 3.78225923e-01 6.00844741e-01
1.27436686e+00 -2.32660264e-01 -1.22805536e+00 -1.82936355e-01
-6.42130012e-03 -5.23961246e-01 5.00599481e-02 -7.73826659e-01
-9.20624375e-01 1.04961360e+00 8.27152133e-01 -2.14941893e-02
6.38163269e-01 3.50754231e-01 7.84393191e-01 6.29821718e-01
6.69610381e-01 -8.07181895e-01 -5.76367788e-02 6.85517848e-01
1.05211890e+00 -1.53408170e+00 -3.22148129e-02 -5.20775914e-01
-4.63280499e-01 1.04279661e+00 8.06284845e-01 -5.81982210e-02
9.70547378e-01 2.12199673e-01 1.32861640e-02 -3.32371980e-01
-5.25044680e-01 -5.32741606e-01 8.34114075e-01 9.72884536e-01
-2.42839277e-01 1.80031970e-01 2.60362297e-01 1.07459271e+00
-2.16463089e-01 -3.35795671e-01 3.87415349e-01 9.76365805e-01
-6.10212386e-01 -1.10343432e+00 -5.44638097e-01 7.95395136e-01
1.75113410e-01 4.67344731e-01 -6.66140258e-01 9.57666814e-01
3.26440960e-01 7.59531677e-01 1.40295535e-01 -1.02171457e+00
7.27919877e-01 1.08468950e-01 5.40047884e-01 -8.24854314e-01
-1.35050891e-02 -3.38168353e-01 2.10279077e-01 -6.36337280e-01
-1.29012205e-02 -6.91811562e-01 -1.22270596e+00 2.40242884e-01
-7.82002985e-01 -2.00421795e-01 7.93404281e-01 1.01767087e+00
3.31083357e-01 4.16311473e-01 9.18442547e-01 -1.06422746e+00
-1.05485964e+00 -6.34458601e-01 -6.14328206e-01 3.48279953e-01
4.61502522e-01 -1.48714542e+00 -5.64247668e-01 -4.58841532e-01] | [8.063688278198242, -2.8324174880981445] |
3677741b-5807-4cef-82e7-870cfa473a0e | hardware-accelerator-and-neural-network-co | 2209.03807 | null | https://arxiv.org/abs/2209.03807v2 | https://arxiv.org/pdf/2209.03807v2.pdf | Hardware Accelerator and Neural Network Co-Optimization for Ultra-Low-Power Audio Processing Devices | The increasing spread of artificial neural networks does not stop at ultralow-power edge devices. However, these very often have high computational demand and require specialized hardware accelerators to ensure the design meets power and performance constraints. The manual optimization of neural networks along with the corresponding hardware accelerators can be very challenging. This paper presents HANNAH (Hardware Accelerator and Neural Network seArcH), a framework for automated and combined hardware/software co-design of deep neural networks and hardware accelerators for resource and power-constrained edge devices. The optimization approach uses an evolution-based search algorithm, a neural network template technique, and analytical KPI models for the configurable UltraTrail hardware accelerator template to find an optimized neural network and accelerator configuration. We demonstrate that HANNAH can find suitable neural networks with minimized power consumption and high accuracy for different audio classification tasks such as single-class wake word detection, multi-class keyword detection, and voice activity detection, which are superior to the related work. | ['Oliver Bringmann', 'Konstantin Lübeck', 'Paul Palomero Bernardo', 'Tobias Hald', 'Adrian Frischknecht', 'Christoph Gerum'] | 2022-09-08 | null | null | null | null | ['activity-detection'] | ['computer-vision'] | [-1.46983504e-01 -5.16002238e-01 -2.17346862e-01 -1.75978951e-02
1.26772359e-01 -4.36410695e-01 -3.44556905e-02 6.31544692e-03
-4.30876344e-01 6.44491166e-02 -2.10938767e-01 -6.48168087e-01
-3.21100980e-01 -4.45804715e-01 -1.29611388e-01 -7.79134810e-01
-3.18780430e-02 2.51243234e-01 2.30322331e-01 -5.37031293e-02
-2.81424471e-03 7.35686779e-01 -2.15685940e+00 -1.01921812e-01
4.63472217e-01 1.45893192e+00 2.31061563e-01 9.89062667e-01
3.07517111e-01 4.40831333e-01 -7.78289199e-01 -1.36606172e-01
2.42749393e-01 -3.24929446e-01 1.08098134e-01 -7.73591101e-01
1.71635449e-01 4.48148809e-02 -3.01530808e-01 1.07433200e+00
1.26197171e+00 1.39347196e-01 4.23990875e-01 -1.53504992e+00
-6.24391250e-02 6.58610284e-01 -3.47528569e-02 7.06589580e-01
-1.89792633e-01 1.27791330e-01 6.91635132e-01 -6.35205925e-01
4.58337553e-02 6.78818464e-01 1.06027699e+00 6.66220307e-01
-5.54361582e-01 -9.69928145e-01 -4.15270805e-01 6.54806793e-01
-1.62830079e+00 -7.31708586e-01 8.04792225e-01 -9.61930379e-02
1.74141872e+00 5.07537305e-01 1.11311364e+00 7.72500992e-01
5.36190152e-01 2.73847312e-01 2.75440067e-01 -6.50222003e-01
7.47218072e-01 1.39096260e-01 2.50715435e-01 8.34255278e-01
3.91562194e-01 3.14557552e-01 -8.68103623e-01 -1.86202496e-01
1.72611549e-01 -2.41454467e-01 -9.44655612e-02 3.63653660e-01
-5.26319563e-01 6.48285866e-01 2.66270518e-01 4.55917746e-01
-5.34991920e-01 2.53955364e-01 8.10354292e-01 4.60136496e-02
2.80094631e-02 6.67324007e-01 -6.96660697e-01 -4.65555519e-01
-1.02542555e+00 -2.69422848e-02 7.18633175e-01 7.62843370e-01
-1.23964772e-01 8.79356325e-01 -1.24096319e-01 7.00178504e-01
2.15803817e-01 2.45642543e-01 1.02283573e+00 -7.13175356e-01
-7.41710663e-02 3.27042520e-01 -4.73136276e-01 -7.38946915e-01
-9.94595468e-01 -8.34147930e-01 -9.68174636e-01 2.63188571e-01
-1.57983705e-01 -3.91184300e-01 -6.65029049e-01 1.46772456e+00
4.89003122e-01 1.03211232e-01 2.54412174e-01 7.40040660e-01
9.59939718e-01 7.75767803e-01 -1.22689404e-01 -3.01456451e-01
1.73030603e+00 -1.15941679e+00 -7.05826938e-01 -4.87699807e-01
7.19481707e-01 -5.30880451e-01 1.00175703e+00 4.03579026e-01
-1.11498916e+00 -5.55018783e-01 -1.61397386e+00 1.19293094e-01
-3.20982873e-01 4.69277054e-01 6.93766177e-01 1.29059637e+00
-1.06704009e+00 6.28644884e-01 -9.14317131e-01 3.33999246e-02
2.90175915e-01 8.49336386e-01 4.46289986e-01 5.04726052e-01
-1.02366185e+00 6.15929425e-01 6.23598337e-01 4.48289141e-02
-1.85687512e-01 -9.11671937e-01 -5.29581726e-01 5.23464620e-01
-9.59569737e-02 -7.56871283e-01 1.32609916e+00 -7.97099590e-01
-1.82670534e+00 2.19167262e-01 3.47478181e-01 -7.32643127e-01
-3.11889291e-01 1.78767502e-01 -8.17846894e-01 -1.89878002e-01
-5.65168381e-01 5.38351297e-01 9.89150524e-01 3.78427729e-02
-9.30651248e-01 -2.54107207e-01 -6.32145762e-01 1.65883690e-01
-1.07128704e+00 2.31958255e-01 -1.99646860e-01 -5.37118375e-01
-8.52621123e-02 -1.00142765e+00 -1.15695655e-01 -1.43362954e-01
-1.16576873e-01 -2.67028749e-01 9.86849844e-01 -3.33457857e-01
1.61607552e+00 -2.25174022e+00 -1.16944008e-01 1.08673528e-01
2.76153404e-02 5.23364007e-01 1.94140479e-01 -3.45248520e-01
-5.97223528e-02 -3.77769053e-01 4.90273297e-01 -1.03785872e-01
-1.63751561e-02 8.44970271e-02 7.43200481e-02 2.61768252e-01
-4.28817749e-01 5.29093087e-01 -3.17999452e-01 -2.92712599e-01
1.39600053e-01 7.22821474e-01 -6.87205136e-01 9.39738899e-02
4.25185636e-02 -2.25866973e-01 8.71582702e-03 8.11523438e-01
1.93088710e-01 -6.13633841e-02 -7.86020160e-02 -6.88291907e-01
-2.96223104e-01 9.31955129e-02 -1.11191797e+00 1.14678526e+00
-7.11492240e-01 1.05815220e+00 2.31082037e-01 -7.33294845e-01
9.08503532e-01 4.73914534e-01 3.50736380e-01 -8.47026169e-01
8.55232716e-01 3.21296602e-01 4.00959969e-01 -4.69797879e-01
5.80991209e-01 2.50670701e-01 -2.33131368e-02 2.18822226e-01
1.67003557e-01 2.63295710e-01 1.20065380e-02 -5.21585643e-01
1.12988877e+00 -5.66981494e-01 5.46982400e-02 -4.02495295e-01
3.62519771e-01 -1.67847216e-01 6.38109148e-01 6.32596552e-01
-7.21321702e-02 -1.11410923e-01 1.71877872e-02 -5.98253131e-01
-1.13507402e+00 -3.16268772e-01 -2.33054206e-01 1.26535094e+00
-2.64067769e-01 -5.55582762e-01 -9.56089973e-01 1.57818168e-01
-4.46798146e-01 7.19008684e-01 1.01273976e-01 -6.51497126e-01
-5.54916203e-01 -1.01669192e+00 8.03922534e-01 5.28498471e-01
3.41580898e-01 -8.74502778e-01 -1.57708704e+00 2.30317563e-01
7.07879126e-01 -1.27621377e+00 -4.76929009e-01 8.96056533e-01
-7.68242896e-01 -3.73182118e-01 -1.67196915e-01 -9.57521558e-01
4.04332370e-01 -2.33980894e-01 7.71585643e-01 1.31968930e-01
-8.12651634e-01 -7.57375509e-02 -7.93006048e-02 -7.65998542e-01
-3.76308709e-01 2.63178349e-01 6.69649541e-01 -3.25901270e-01
2.07326934e-01 -7.21174479e-01 -5.82060814e-01 9.63649973e-02
-3.17108631e-01 3.08386590e-02 4.86476779e-01 7.97261000e-01
4.63329881e-01 7.45809674e-01 3.82871538e-01 -6.93791583e-02
1.03854251e+00 -2.62811422e-01 -1.14082634e+00 1.89015344e-01
-1.18603241e+00 2.18399778e-01 9.84480679e-01 -9.36922014e-01
-3.71252745e-01 5.01136184e-01 -5.96912265e-01 -7.70707965e-01
2.99288154e-01 2.14495167e-01 -1.49807110e-01 -5.29423594e-01
9.28473592e-01 -5.25632966e-03 -2.94478893e-01 -3.35243523e-01
-2.17055470e-01 9.33182001e-01 7.64310598e-01 -5.80661818e-02
2.02099025e-01 -1.67798266e-01 2.25488022e-01 -9.79429543e-01
-2.88966656e-01 -2.55306326e-02 -1.02871715e-03 -3.78312230e-01
7.23038495e-01 -6.94743812e-01 -1.18030262e+00 3.87623876e-01
-1.10131168e+00 -1.78276762e-01 -1.58747122e-01 6.35542572e-01
-1.20947964e-01 -1.93754137e-01 -4.47619915e-01 -1.13459790e+00
-1.31700170e+00 -1.31718981e+00 7.00765431e-01 8.30963314e-01
-3.73493850e-01 -6.10616982e-01 -3.11360836e-01 -1.99766830e-01
7.27379084e-01 -2.50569791e-01 9.01808023e-01 -5.97533882e-01
-2.62998283e-01 -5.13121963e-01 2.27234498e-01 9.66612697e-02
-3.06238264e-01 5.23726493e-02 -9.94749129e-01 -3.28554332e-01
2.70782501e-01 2.47588307e-01 1.25399485e-01 7.60089278e-01
1.35258210e+00 -6.26240730e-01 -3.13829869e-01 1.08996320e+00
1.21515775e+00 8.40323865e-01 8.45587179e-02 1.04455709e-01
4.58449781e-01 -8.78644809e-02 2.76830584e-01 6.56988502e-01
-2.40231097e-01 1.00384617e+00 4.02388364e-01 3.94025855e-02
1.65887505e-01 1.72554404e-01 2.13650554e-01 1.16985714e+00
2.75265843e-01 -4.11017418e-01 -8.79518390e-01 2.39393488e-01
-1.49689209e+00 -6.34769142e-01 6.67334944e-02 1.97797251e+00
4.23714221e-01 4.35823768e-01 3.18371087e-01 7.72524416e-01
5.84145188e-01 -3.60522717e-01 -8.39257836e-01 -1.01082158e+00
1.49026334e-01 4.33274120e-01 8.14898968e-01 3.32408249e-02
-6.85645461e-01 4.54870194e-01 6.56949091e+00 1.09188068e+00
-1.36179852e+00 5.11073530e-01 4.19820428e-01 -5.45325458e-01
3.70703638e-01 -4.13558334e-01 -1.35073280e+00 7.10301042e-01
1.76588392e+00 -2.07737714e-01 4.93960440e-01 1.40354705e+00
-1.08215369e-01 1.78249970e-01 -9.81092453e-01 1.65729249e+00
-5.03450297e-02 -1.63671887e+00 -6.70138896e-01 -7.54151493e-02
2.37388074e-01 9.86841097e-02 1.39262483e-01 2.85032660e-01
-3.06356519e-01 -7.28780270e-01 8.81762564e-01 6.05797162e-03
8.04833472e-01 -1.24336779e+00 6.93361044e-01 4.41613257e-01
-1.31269097e+00 -7.15227246e-01 -2.36431181e-01 -4.12337594e-02
8.89898166e-02 4.73807663e-01 -7.69769847e-01 -3.18829924e-01
1.06173396e+00 -3.02822236e-02 -2.40446806e-01 1.10938036e+00
3.16195756e-01 4.12160635e-01 -6.51188254e-01 -9.52164769e-01
-5.36368899e-02 2.28064820e-01 5.12392700e-01 1.12789595e+00
8.24654758e-01 1.13825694e-01 -2.16652721e-01 4.69945192e-01
1.14035979e-01 5.49908057e-02 -2.30372250e-01 1.52002731e-02
9.11233902e-01 1.52010882e+00 -9.72076893e-01 -1.32504106e-01
1.19865108e-02 6.81745589e-01 -3.04704696e-01 -2.41298467e-01
-1.06014812e+00 -7.67317891e-01 8.67530465e-01 -2.49727890e-01
1.31793007e-01 -2.40224391e-01 -5.83446920e-01 -4.44770336e-01
-1.45315245e-01 -8.08916569e-01 3.03552538e-01 -8.58951151e-01
-5.16182780e-01 1.14160430e+00 -2.35087156e-01 -1.15819824e+00
-5.84005594e-01 -7.42662549e-01 -6.79128170e-01 5.90674341e-01
-8.09723437e-01 -5.14612317e-01 -3.02068889e-01 3.07759762e-01
6.73475325e-01 -7.99205303e-01 9.10219431e-01 7.41141140e-01
-1.00226402e+00 1.16993546e+00 -1.03516951e-02 -4.45313513e-01
-1.86901078e-01 -4.69450235e-01 4.53628391e-01 9.01121199e-01
8.64596888e-02 5.44633381e-02 9.91003454e-01 -4.14145112e-01
-1.92650628e+00 -8.50734293e-01 5.57810545e-01 3.41411471e-01
5.28194726e-01 -5.59843957e-01 -6.23609781e-01 -1.79633558e-01
6.88832477e-02 1.06851600e-01 7.04867363e-01 -1.41133726e-01
2.54694730e-01 -3.33571315e-01 -1.05443132e+00 8.56894612e-01
9.96422350e-01 -2.87215412e-01 3.28327149e-01 6.79908216e-01
8.43906701e-01 -8.31104398e-01 -6.99980855e-01 4.81278867e-01
7.38578558e-01 -6.41081631e-01 1.05969775e+00 -2.51592159e-01
-2.74242520e-01 -2.93139983e-02 -7.13227913e-02 -1.01037610e+00
-2.06498563e-01 -8.56942177e-01 -6.50070190e-01 8.65524232e-01
5.23992777e-01 -3.45036834e-01 1.03967464e+00 5.47254980e-01
-5.02899170e-01 -9.33007598e-01 -1.42059183e+00 -1.10590184e+00
-7.63776243e-01 -5.70297539e-01 6.93011940e-01 6.39577448e-01
9.29925218e-02 6.31891131e-01 -2.45578349e-01 3.36974293e-01
3.34843427e-01 -3.95013958e-01 1.06920442e-02 -1.20618558e+00
-5.85528791e-01 -8.81620467e-01 -7.62236774e-01 -3.79918635e-01
9.00750235e-02 -7.64484763e-01 -4.69136573e-02 -7.80017138e-01
-6.03587449e-01 -5.28050363e-01 -3.05230841e-02 4.90104169e-01
4.54098165e-01 8.09562355e-02 -1.07894413e-01 -1.47697702e-01
-1.56117991e-01 2.39079833e-01 2.30248764e-01 6.76517561e-02
-5.46158135e-01 2.91328937e-01 -3.97631168e-01 7.02775836e-01
9.61463213e-01 -7.41176963e-01 -6.62584543e-01 -2.87650645e-01
4.64166194e-01 1.26428515e-01 4.34181169e-02 -1.75751221e+00
9.24467623e-01 3.06666762e-01 2.78929234e-01 -3.89938265e-01
5.22277892e-01 -1.08566010e+00 4.46093678e-01 1.01468945e+00
-1.14065528e-01 7.31764674e-01 6.43664420e-01 1.11055799e-01
2.95900166e-01 -6.91975474e-01 8.33835304e-01 5.13045549e-01
-6.24372065e-01 1.39931113e-01 -6.97324336e-01 -4.45205957e-01
7.92383134e-01 -2.67283112e-01 -2.31976718e-01 -7.31245875e-02
-5.58989227e-01 -6.46674410e-02 -2.59162486e-01 5.08371353e-01
6.18742228e-01 -1.34452963e+00 -1.34800419e-01 6.00197375e-01
-3.52389336e-01 -3.99104655e-01 3.53970230e-01 4.90969568e-01
-5.44540763e-01 5.19372642e-01 -4.79048759e-01 -5.99177897e-01
-1.82934928e+00 5.45408130e-01 7.35243499e-01 1.37053624e-01
-5.71470380e-01 1.06438291e+00 -7.31147468e-01 8.75602290e-02
7.35743821e-01 -3.03680599e-01 -1.82944313e-01 -1.05571195e-01
6.62708461e-01 4.91075993e-01 6.67031705e-01 -1.85122907e-01
-6.01577818e-01 4.43825245e-01 3.29352438e-01 6.64633289e-02
1.10930860e+00 4.08752263e-01 1.48062289e-01 6.12634979e-03
1.15125656e+00 -4.52657551e-01 -4.97240484e-01 1.28304288e-01
-8.98532867e-02 5.29403798e-02 9.27226007e-01 -4.67919022e-01
-1.35772800e+00 6.79103136e-01 1.52090681e+00 1.22202113e-01
1.67083573e+00 -3.79864037e-01 1.00925756e+00 5.34161091e-01
9.26286355e-02 -1.44317889e+00 -1.98118955e-01 5.34081757e-01
4.38206285e-01 -5.18879354e-01 5.55037968e-02 8.13550651e-02
-1.00241061e-02 1.25558352e+00 8.38269114e-01 2.26271883e-01
9.91809130e-01 1.26830089e+00 -4.43626553e-01 -9.39991698e-02
-1.10938561e+00 2.04679117e-01 2.94640690e-01 5.08698285e-01
5.50904386e-02 -1.71783492e-01 -2.16043979e-01 9.66819704e-01
-6.79403007e-01 -7.82073885e-02 8.86716098e-02 9.61197972e-01
-4.72502649e-01 -7.93614388e-01 -3.29900056e-01 6.28482640e-01
-4.79071021e-01 -2.16344684e-01 1.77000254e-01 9.01981294e-02
3.07885110e-01 5.77669621e-01 5.94118357e-01 -1.21377492e+00
3.69893432e-01 3.97619195e-02 2.87178397e-01 -9.44371074e-02
-1.17260635e+00 -1.75090767e-02 1.06905982e-01 -2.34782562e-01
3.37898940e-01 -3.86550814e-01 -1.31349850e+00 -3.79769653e-01
-6.97131395e-01 8.59175175e-02 1.67396057e+00 7.16918349e-01
7.95701981e-01 1.04318094e+00 4.57774699e-01 -1.05188787e+00
-3.35494608e-01 -4.66107309e-01 -2.57902235e-01 -8.46292794e-01
1.53428450e-01 -5.80129862e-01 -4.41534340e-01 -4.89722818e-01] | [8.43000316619873, 2.803692102432251] |
ed61319e-dc2f-48f8-b905-c2abebf4ddc9 | power-normalizations-in-fine-grained-image | 2012.13975 | null | https://arxiv.org/abs/2012.13975v2 | https://arxiv.org/pdf/2012.13975v2.pdf | Power Normalizations in Fine-grained Image, Few-shot Image and Graph Classification | Power Normalizations (PN) are useful non-linear operators which tackle feature imbalances in classification problems. We study PNs in the deep learning setup via a novel PN layer pooling feature maps. Our layer combines the feature vectors and their respective spatial locations in the feature maps produced by the last convolutional layer of CNN into a positive definite matrix with second-order statistics to which PN operators are applied, forming so-called Second-order Pooling (SOP). As the main goal of this paper is to study Power Normalizations, we investigate the role and meaning of MaxExp and Gamma, two popular PN functions. To this end, we provide probabilistic interpretations of such element-wise operators and discover surrogates with well-behaved derivatives for end-to-end training. Furthermore, we look at the spectral applicability of MaxExp and Gamma by studying Spectral Power Normalizations (SPN). We show that SPN on the autocorrelation/covariance matrix and the Heat Diffusion Process (HDP) on a graph Laplacian matrix are closely related, thus sharing their properties. Such a finding leads us to the culmination of our work, a fast spectral MaxExp which is a variant of HDP for covariances/autocorrelation matrices. We evaluate our ideas on fine-grained recognition, scene recognition, and material classification, as well as in few-shot learning and graph classification. | ['Hongguang Zhang', 'Piotr Koniusz'] | 2020-12-27 | null | null | null | null | ['material-classification', 'scene-recognition'] | ['computer-vision', 'computer-vision'] | [ 2.75272280e-01 6.58476772e-03 7.81391189e-02 -1.74312681e-01
-1.95710376e-01 -5.72373927e-01 9.09262717e-01 3.97357285e-01
-5.43955207e-01 4.03252393e-01 1.99982986e-01 -4.03602123e-02
-7.41031766e-01 -1.01195955e+00 -7.10006952e-01 -1.13003016e+00
-4.77813840e-01 -3.09032369e-02 3.01841855e-01 -2.86566287e-01
2.23491251e-01 9.15221095e-01 -1.45093656e+00 5.19907027e-02
6.41814888e-01 1.17036450e+00 -1.97518468e-01 7.31194973e-01
2.41378564e-02 7.21667707e-01 -4.63697255e-01 -3.93152088e-01
2.61669308e-01 -2.66855568e-01 -8.12959611e-01 -1.73730090e-01
4.66890007e-01 4.01973486e-01 -4.73715901e-01 1.25650370e+00
4.52619702e-01 5.92816412e-01 1.14354765e+00 -1.46783793e+00
-8.86084795e-01 5.83735704e-01 -5.72183728e-01 6.80463016e-01
6.70026317e-02 1.02103855e-02 1.17313278e+00 -7.47743011e-01
4.96847361e-01 9.76214707e-01 9.13760960e-01 1.61489740e-01
-1.50499451e+00 -3.18029284e-01 -3.52992535e-01 5.19966125e-01
-1.56750989e+00 -2.68136054e-01 8.87371302e-01 -6.01273119e-01
9.05795038e-01 2.94833630e-01 4.55100387e-01 1.05964959e+00
4.30265069e-01 4.32726264e-01 1.05117881e+00 -5.36783993e-01
2.30180308e-01 1.54336207e-02 5.14068425e-01 9.20289338e-01
2.15571418e-01 -1.31051689e-01 -8.30993056e-01 -5.77655621e-02
6.33326888e-01 -1.43581659e-01 -3.19444597e-01 -4.22828346e-01
-1.00492179e+00 7.92152345e-01 7.03229964e-01 6.25013053e-01
-4.12564278e-01 1.32635295e-01 1.52295887e-01 1.71989098e-01
5.06362498e-01 4.31718767e-01 -1.65143535e-01 -8.93291377e-04
-5.83429873e-01 3.84921487e-03 8.76773298e-01 4.95852530e-01
1.00447464e+00 -3.72379988e-01 -7.03210235e-01 7.78265178e-01
7.43114650e-02 3.35844398e-01 2.97335386e-01 -6.53397202e-01
1.66623369e-01 4.50953066e-01 -4.22741771e-01 -1.09032798e+00
-9.71377254e-01 -7.44714320e-01 -1.28339553e+00 1.39253214e-01
5.65441549e-01 5.21831736e-02 -6.20231390e-01 1.81124651e+00
-4.46641445e-02 1.71151578e-01 -1.95959926e-01 6.90984845e-01
4.68005955e-01 4.62433577e-01 1.46091715e-01 -4.58476469e-02
1.38819396e+00 -6.13656878e-01 -4.77626383e-01 3.22788239e-01
4.48051393e-01 -4.19329375e-01 1.25412452e+00 1.80207804e-01
-7.92136967e-01 -4.63216662e-01 -1.05818629e+00 -1.44708201e-01
-6.92353487e-01 1.10529356e-01 5.90680122e-01 6.34809077e-01
-1.20830798e+00 1.45728970e+00 -8.32709312e-01 -4.57438707e-01
6.64646268e-01 1.73854426e-01 -3.67780834e-01 2.27482140e-01
-1.16594040e+00 7.64159083e-01 7.92060196e-02 2.57025629e-01
-2.01573193e-01 -9.44913566e-01 -7.85781503e-01 3.44179899e-01
-3.45357396e-02 -5.70501924e-01 6.58191383e-01 -6.78872645e-01
-1.47853780e+00 8.26625586e-01 1.82299949e-02 -4.94872451e-01
3.48704666e-01 -1.86476763e-02 -2.69205034e-01 -4.29925285e-02
-2.78118234e-02 1.61859229e-01 9.59566832e-01 -6.20922506e-01
-1.12391256e-01 -4.10265356e-01 -5.38694412e-02 -1.59539863e-01
-6.68964088e-01 -1.65871978e-01 2.11324748e-02 -5.81627071e-01
8.79440606e-02 -6.63644373e-01 3.57971601e-02 -1.79743782e-01
-7.46623337e-01 -4.54981893e-01 4.36964869e-01 -4.91316527e-01
1.18383336e+00 -2.26484394e+00 2.66778320e-01 7.05276847e-01
2.71443665e-01 -5.55402301e-02 -3.45740050e-01 5.50503910e-01
-4.10634518e-01 2.65004307e-01 -3.67372453e-01 -1.84184983e-01
3.65331590e-01 8.96017347e-03 -2.56195456e-01 9.26326513e-01
7.26260483e-01 1.09078491e+00 -7.76791275e-01 -9.51111615e-02
2.38901585e-01 7.15809882e-01 -3.12568128e-01 -1.11399107e-01
1.14442259e-01 1.95179015e-01 2.85689030e-02 2.14225709e-01
8.01078737e-01 -2.52805591e-01 -2.25896835e-01 -6.09872043e-01
-2.30837479e-01 1.46743283e-01 -1.03829110e+00 1.45500755e+00
-3.72977346e-01 7.62315035e-01 -3.43714982e-01 -1.15969276e+00
6.76271260e-01 -2.65857875e-01 4.81734782e-01 -7.68008471e-01
2.02820495e-01 5.57533652e-02 6.28797188e-02 -3.65574837e-01
2.75455564e-01 -2.57836938e-01 1.24617256e-01 3.23936850e-01
5.63588619e-01 3.08727950e-01 5.48193872e-01 7.26052374e-02
1.47236943e+00 -1.92447186e-01 3.51932019e-01 -8.49906504e-01
6.12620533e-01 -6.34419322e-01 -1.47275785e-02 8.91196370e-01
-5.12136817e-02 6.82496130e-01 1.28445148e+00 -1.88344389e-01
-8.57948124e-01 -1.24007320e+00 -4.09365952e-01 1.29343534e+00
-1.86645642e-01 -3.40770364e-01 -7.13423908e-01 -4.81320620e-01
-9.94082689e-02 4.69718277e-01 -9.43586171e-01 -5.80274940e-01
-3.39933842e-01 -1.16537738e+00 6.18406475e-01 5.24495304e-01
4.62720692e-01 -9.01972711e-01 -4.64607835e-01 -1.10373721e-01
4.27337915e-01 -1.02854550e+00 -3.97962958e-01 8.02466989e-01
-4.12744522e-01 -1.17116606e+00 -7.80684412e-01 -3.62185031e-01
4.23741251e-01 -1.83405846e-01 8.91036630e-01 -3.51501077e-01
-3.95154595e-01 4.58922833e-01 -2.58710682e-01 -2.44395584e-01
-9.59046260e-02 3.57849151e-01 9.23318043e-02 4.92603213e-01
1.70932472e-01 -1.05766833e+00 -4.98210102e-01 4.56967838e-02
-1.15124667e+00 -1.98677644e-01 7.83483863e-01 7.10649729e-01
3.76635611e-01 1.25518605e-01 -5.49786761e-02 -7.21620440e-01
9.57196891e-01 -3.33683610e-01 -5.90979815e-01 2.79247403e-01
-2.60354996e-01 6.44940436e-01 7.39864647e-01 -3.77943307e-01
-6.10736847e-01 -1.13617569e-01 -1.83004051e-01 -3.74603748e-01
4.00443561e-02 4.90063518e-01 -7.63103738e-02 -3.66814494e-01
1.09930396e+00 8.54275525e-02 -2.31220871e-01 -3.80700201e-01
4.98539209e-01 4.94746417e-02 5.30235231e-01 -3.25794220e-01
1.05399239e+00 4.06549633e-01 6.77960634e-01 -1.21200907e+00
-9.42868114e-01 -5.04054487e-01 -7.99018323e-01 -5.42231873e-02
9.84877884e-01 -3.07291925e-01 -9.51038837e-01 5.97008705e-01
-1.21972311e+00 -3.64430100e-01 -7.71828830e-01 2.47139588e-01
-3.84280294e-01 2.14726344e-01 -5.77782035e-01 -9.17084813e-01
-1.53668240e-01 -5.66682160e-01 1.04656994e+00 3.85157079e-01
8.17135945e-02 -1.17828798e+00 1.91303834e-01 -2.74454415e-01
5.42281806e-01 2.53289729e-01 1.21742547e+00 -7.48924673e-01
-3.03788334e-01 -1.31243005e-01 -6.19043171e-01 5.47922909e-01
-2.64376789e-01 6.15015365e-02 -1.28411603e+00 -6.25167936e-02
-3.08498759e-02 1.86764389e-01 1.35107148e+00 5.38887560e-01
1.22855794e+00 -2.36238167e-01 6.40215203e-02 7.55801678e-01
1.39456856e+00 -3.64029527e-01 5.21453857e-01 -2.39019841e-02
8.21485698e-01 5.99796534e-01 -1.84071019e-01 4.79719967e-01
-1.68399557e-01 6.97828889e-01 2.39464581e-01 -1.01021687e-02
-2.18122721e-01 -1.30534336e-01 2.33716846e-01 8.80989850e-01
-4.50719327e-01 -4.58161682e-02 -8.83094192e-01 1.22824870e-01
-1.58916211e+00 -8.54358912e-01 -4.28419620e-01 2.18711591e+00
4.60475028e-01 1.42482117e-01 -9.69417915e-02 2.67180622e-01
5.77871621e-01 4.92709875e-01 -3.37407291e-01 -1.68110579e-01
-4.96926188e-01 9.37850416e-01 7.35472918e-01 5.53866446e-01
-1.46924305e+00 4.88627166e-01 5.00180626e+00 1.13393128e+00
-1.14438236e+00 3.49792629e-01 3.86797398e-01 2.02539116e-01
-2.75081217e-01 -3.12269419e-01 -3.97781849e-01 1.94417641e-01
8.70122671e-01 -7.35389581e-03 6.71492457e-01 5.35334945e-01
-9.33320895e-02 -3.52461748e-02 -1.11298883e+00 1.04850519e+00
3.44185308e-02 -1.41527104e+00 -1.23416148e-01 1.25379175e-01
5.94332337e-01 2.28132337e-01 1.05379336e-01 1.86769173e-01
-5.36893420e-02 -1.04592240e+00 6.83130085e-01 8.74011159e-01
5.29383361e-01 -6.96367800e-01 7.21634805e-01 -9.08053368e-02
-1.22041941e+00 -1.32095769e-01 -5.30098319e-01 -5.01097888e-02
-2.68243402e-02 1.11208272e+00 -3.58695984e-01 6.16335094e-01
4.27426606e-01 7.42023170e-01 -8.10322344e-01 1.02028763e+00
-3.17167640e-01 4.00332451e-01 -4.60734576e-01 -2.05463335e-01
4.06479612e-02 -4.02397513e-01 5.40104091e-01 1.34150684e+00
2.19947696e-01 -1.22679897e-01 -3.56141776e-01 1.16283178e+00
-3.74429464e-01 1.41397595e-01 -3.87584388e-01 -2.54667222e-01
-1.73512995e-01 1.63695109e+00 -1.11212027e+00 2.05139872e-02
-7.10069016e-02 1.09036601e+00 5.18175960e-01 5.54677010e-01
-6.84662223e-01 -7.31156170e-01 7.80015767e-01 1.65052444e-01
2.06309587e-01 -1.81913853e-01 -3.12827885e-01 -1.10145056e+00
3.61793339e-01 -1.37001455e-01 1.84240058e-01 -4.07543927e-01
-1.75575686e+00 5.17077208e-01 -1.04223199e-01 -8.90677035e-01
2.10931495e-01 -1.04716611e+00 -7.72512317e-01 9.87537205e-01
-1.61186457e+00 -8.64354074e-01 -3.52653295e-01 6.10556245e-01
-1.26982287e-01 1.54993758e-01 7.71497548e-01 3.59498113e-01
-7.41868377e-01 4.04617697e-01 1.17791913e-01 1.85631752e-01
1.87902436e-01 -1.45462584e+00 4.31692600e-01 9.39251363e-01
4.15932745e-01 5.53894818e-01 6.21140420e-01 -2.90386289e-01
-1.23969817e+00 -9.37928915e-01 7.69093990e-01 -2.67382026e-01
1.15932643e+00 -7.16305852e-01 -1.01193154e+00 1.32427379e-01
-2.55981497e-02 3.59128177e-01 4.29936856e-01 2.15864763e-01
-4.67001170e-01 -2.26056740e-01 -7.62116551e-01 3.21597546e-01
1.29818833e+00 -8.90721917e-01 -1.65133908e-01 5.59633791e-01
5.18029928e-01 4.40144055e-02 -7.18743861e-01 3.14586729e-01
3.74244988e-01 -1.16169095e+00 8.38326514e-01 -6.94579244e-01
4.09841359e-01 -5.35067469e-02 2.71842014e-02 -1.33546376e+00
-6.67879224e-01 -5.95951557e-01 9.36982706e-02 1.06656146e+00
4.21537668e-01 -8.35381567e-01 5.75499415e-01 3.48055214e-01
-9.29688364e-02 -7.86619246e-01 -1.08453393e+00 -8.61239970e-01
-2.75174603e-02 -6.74246073e-01 4.80705835e-02 9.08099055e-01
-4.06832919e-02 4.78469849e-01 4.61480245e-02 1.40433818e-01
4.72710192e-01 -2.51324981e-01 1.98347151e-01 -1.47629905e+00
-3.35857600e-01 -9.13356483e-01 -7.98086166e-01 -5.21943510e-01
1.87081859e-01 -1.19250405e+00 -7.17995465e-02 -1.25552285e+00
1.47309586e-01 -6.30546957e-02 -5.03624499e-01 4.57452774e-01
1.33906052e-01 3.54958087e-01 2.20282331e-01 -1.66621655e-02
-4.53090936e-01 5.87290645e-01 8.47543955e-01 -1.07243665e-01
-2.94721633e-01 1.06655389e-01 -3.73088658e-01 6.73938632e-01
6.70383751e-01 -2.48202145e-01 -9.24030542e-02 9.99470204e-02
5.78758061e-01 -5.08373797e-01 6.74611151e-01 -1.30900455e+00
3.43158364e-01 2.88205028e-01 3.78936887e-01 -1.89668983e-02
1.00985043e-01 -5.36222696e-01 -1.09228291e-01 3.38843375e-01
-3.54798734e-01 -2.20470682e-01 6.51932284e-02 4.12214637e-01
-4.28177752e-02 -3.16143513e-01 7.51585782e-01 2.58279830e-01
-4.48268652e-01 3.55399251e-01 -3.07497650e-01 5.18763289e-02
7.15292871e-01 1.96087822e-01 -4.89756316e-01 -1.92074433e-01
-7.94954419e-01 -2.17447147e-01 4.29969914e-02 2.25148723e-01
2.95767546e-01 -1.34852958e+00 -4.63914931e-01 4.31787550e-01
2.76514404e-02 -3.83364260e-01 4.56471711e-01 1.40457058e+00
-3.62335622e-01 3.33560973e-01 -3.88752162e-01 -4.62608725e-01
-9.01093423e-01 4.55632925e-01 4.34940100e-01 -4.35964108e-01
-3.26312512e-01 9.62479413e-01 1.77826598e-01 -1.68265671e-01
9.63138193e-02 -6.61996067e-01 -2.81713575e-01 4.63890284e-01
4.85232025e-01 5.56412101e-01 4.22765583e-01 -5.30776620e-01
-4.08550560e-01 5.87632239e-01 4.86856252e-01 -7.18911663e-02
1.53567398e+00 2.64563680e-01 -5.59087217e-01 6.67799175e-01
1.63074064e+00 -4.00204258e-03 -1.17860734e+00 -2.28965238e-01
3.11340123e-01 8.39333087e-02 -5.94170652e-02 -3.61978263e-01
-1.05224395e+00 1.07357800e+00 7.02495039e-01 8.46650541e-01
1.13888443e+00 3.49062532e-01 2.50759602e-01 3.24438095e-01
-9.84673277e-02 -9.11116660e-01 -4.38371971e-02 6.76726878e-01
9.95700657e-01 -7.64374673e-01 -1.68259088e-02 -5.20352542e-01
-1.23069420e-01 1.37251782e+00 1.26261823e-02 -3.08140218e-01
9.54065442e-01 1.43803492e-01 -4.08561260e-01 -3.41884136e-01
-2.24440292e-01 -6.39848650e-01 7.39866257e-01 5.91116786e-01
2.97344774e-01 3.46715786e-02 -3.69928360e-01 6.55129492e-01
-4.36521798e-01 -3.53746325e-01 3.58264565e-01 5.37405550e-01
-1.61291361e-01 -8.50006223e-01 -5.57292532e-03 5.48522413e-01
-2.27449045e-01 -2.37073496e-01 -3.93611819e-01 4.88647848e-01
1.87526956e-01 4.92803603e-01 1.51261315e-01 -5.37693620e-01
6.30784690e-01 2.76759297e-01 5.36396921e-01 -3.65807056e-01
-4.49538857e-01 -4.63927448e-01 -1.98665783e-01 -6.61794305e-01
-3.90056789e-01 -5.51187217e-01 -9.44190383e-01 -8.38406309e-02
-1.18597209e-01 -2.02686727e-01 7.50420868e-01 9.23278809e-01
1.44359216e-01 8.42986047e-01 5.16590595e-01 -1.09644902e+00
-4.98783261e-01 -1.13031888e+00 -9.82859552e-01 6.38589859e-01
3.08660388e-01 -6.39227033e-01 -4.84317482e-01 -2.55952954e-01] | [8.809890747070312, 2.6992204189300537] |
379f08d2-5a48-46a5-ac2e-43bbabaa46d6 | fast-trajectory-end-point-prediction-with | 2302.13796 | null | https://arxiv.org/abs/2302.13796v1 | https://arxiv.org/pdf/2302.13796v1.pdf | Fast Trajectory End-Point Prediction with Event Cameras for Reactive Robot Control | Prediction skills can be crucial for the success of tasks where robots have limited time to act or joints actuation power. In such a scenario, a vision system with a fixed, possibly too low, sampling rate could lead to the loss of informative points, slowing down prediction convergence and reducing the accuracy. In this paper, we propose to exploit the low latency, motion-driven sampling, and data compression properties of event cameras to overcome these issues. As a use-case, we use a Panda robotic arm to intercept a ball bouncing on a table. To predict the interception point, we adopt a Stateful LSTM network, a specific LSTM variant without fixed input length, which perfectly suits the event-driven paradigm and the problem at hand, where the length of the trajectory is not defined. We train the network in simulation to speed up the dataset acquisition and then fine-tune the models on real trajectories. Experimental results demonstrate how using a dense spatial sampling (i.e. event cameras) significantly increases the number of intercepted trajectories as compared to a fixed temporal sampling (i.e. frame-based cameras). | ['Chiara Bartolozzi', 'Arren Glover', 'Massimiliano Iacono', 'Luna Gava', 'Marco Monforte'] | 2023-02-27 | null | null | null | null | ['data-compression'] | ['time-series'] | [ 2.86552429e-01 -2.33824849e-02 -6.96419403e-02 -6.09369017e-02
-2.13724181e-01 -3.87631893e-01 5.69470525e-01 -1.13438681e-01
-8.78392637e-01 5.33344150e-01 -3.40828449e-01 -3.83517593e-01
-2.01652825e-01 -7.39479899e-01 -1.10449314e+00 -6.72068298e-01
-1.38488054e-01 4.43612128e-01 4.66881990e-01 5.18808588e-02
3.04286927e-01 7.95038879e-01 -1.59980619e+00 7.84759223e-02
3.21392685e-01 8.83557260e-01 7.02958584e-01 8.08052540e-01
2.42326483e-01 8.83866131e-01 -4.79998738e-01 1.17562830e-01
4.12519604e-01 -1.80776685e-01 -5.13198733e-01 1.22472197e-01
1.66067600e-01 -7.96467006e-01 -5.36856651e-01 6.97130620e-01
9.52146426e-02 3.60713363e-01 2.94343114e-01 -1.16861439e+00
2.93995421e-02 4.45292324e-01 -4.17030871e-01 2.99404226e-02
3.58776972e-02 5.07934928e-01 5.60921848e-01 -5.41265011e-01
6.47549570e-01 1.01398015e+00 7.11230516e-01 6.02283895e-01
-1.05024028e+00 -3.38420033e-01 2.24233910e-01 3.34878176e-01
-1.06229067e+00 -4.42266345e-01 6.61275864e-01 -3.53977621e-01
9.69330370e-01 -2.47864604e-01 9.15234864e-01 1.41093564e+00
4.15763646e-01 6.94711685e-01 5.04867971e-01 -2.21118510e-01
6.52607441e-01 -2.73531795e-01 -1.14310041e-01 5.33979177e-01
2.79072046e-01 2.27148533e-01 -3.62287968e-01 1.15149066e-01
1.02970552e+00 4.96729463e-01 -2.80864477e-01 -6.65142417e-01
-1.46992171e+00 7.14831769e-01 5.17037511e-01 1.00030906e-01
-6.22257113e-01 6.09555185e-01 4.59254652e-01 4.38198119e-01
-1.90777183e-01 4.32708830e-01 -3.85228842e-01 -4.02097523e-01
-8.47040117e-01 2.16742501e-01 7.50181496e-01 1.06526113e+00
4.27508950e-01 1.22509748e-01 4.39102761e-03 2.93411195e-01
-5.50875701e-02 4.72081065e-01 4.41592515e-01 -1.24136162e+00
4.93548781e-01 3.72738510e-01 5.52128434e-01 -7.34821737e-01
-6.86938226e-01 4.62264344e-02 -6.63153887e-01 5.67871571e-01
8.02277923e-01 -4.06377763e-01 -9.48009014e-01 1.64760029e+00
2.25031540e-01 1.21449515e-01 1.09640732e-01 1.24284279e+00
-2.58482814e-01 8.33680630e-01 -3.47434282e-01 -2.10089847e-01
1.07108366e+00 -8.82543147e-01 -4.48249698e-01 -3.15879345e-01
5.89545548e-01 -4.23839003e-01 1.26171124e+00 7.28599608e-01
-9.05082524e-01 -5.04876196e-01 -1.07685006e+00 1.15018614e-01
-7.87155852e-02 3.87695849e-01 3.36734593e-01 4.06354852e-02
-6.72751725e-01 8.39960575e-01 -1.60141206e+00 -5.81683338e-01
1.99555740e-01 5.32795787e-01 -3.36234063e-01 -6.86426684e-02
-7.41480768e-01 9.92210507e-01 5.52118063e-01 1.28484562e-01
-1.05605412e+00 -3.75998735e-01 -6.46701872e-01 1.07945122e-01
5.60788035e-01 -5.52054405e-01 1.47745180e+00 -9.29238617e-01
-1.79093027e+00 1.55901641e-01 1.70509398e-01 -9.46747243e-01
7.95825183e-01 -5.16697168e-01 3.53567362e-01 1.71809256e-01
-2.86091775e-01 7.07601726e-01 9.40940797e-01 -9.81528401e-01
-6.87349081e-01 -2.75057346e-01 3.85255367e-01 2.12735921e-01
-2.23014206e-01 -3.63770247e-01 -8.38575959e-02 -1.22307323e-01
-1.16915710e-01 -1.31861603e+00 -4.45276052e-01 2.89611608e-01
-7.61227682e-02 1.20861024e-01 1.15009749e+00 -2.17839435e-01
5.41495860e-01 -2.05359721e+00 5.67718446e-02 -1.86633077e-02
-1.95494741e-01 2.81100631e-01 9.56092030e-02 6.18683279e-01
2.81810522e-01 -5.20861804e-01 -1.00424416e-01 -4.32728916e-01
-2.84270763e-01 5.21618903e-01 -5.26756644e-01 5.97148716e-01
1.08529031e-01 4.28544343e-01 -9.78711426e-01 -1.79152563e-01
5.71863651e-01 4.13584411e-01 -4.76657927e-01 1.78964883e-01
-3.65487993e-01 5.57605267e-01 -5.87233305e-01 1.45710096e-01
1.71534419e-01 -7.92786777e-02 1.51190996e-01 9.09850746e-03
-3.77277553e-01 9.39313620e-02 -1.10571623e+00 1.80257988e+00
-9.06179547e-01 8.82845402e-01 -3.25512467e-03 -8.73492718e-01
9.60265934e-01 4.99727540e-02 4.77080435e-01 -4.21234787e-01
1.09065294e-01 1.68198064e-01 1.01796109e-02 -5.74155748e-01
6.29429162e-01 6.43520951e-02 5.89997508e-02 2.23129660e-01
-2.16197714e-01 -3.14719491e-02 9.41192918e-03 -2.48890355e-01
1.40189314e+00 5.27195752e-01 3.47925574e-01 8.54743496e-02
1.24784306e-01 4.95915681e-01 3.48823845e-01 7.62724698e-01
-2.82274131e-02 6.28667235e-01 3.17873061e-01 -6.67106032e-01
-1.45722330e+00 -6.86623693e-01 2.79149652e-01 6.83321893e-01
4.42335784e-01 -1.47265986e-01 -7.72014737e-01 -3.45849335e-01
-2.41147101e-01 9.06491756e-01 -2.93660849e-01 -3.69519383e-01
-1.03846312e+00 -3.12354118e-01 3.23170245e-01 5.87576866e-01
3.83370847e-01 -1.07344687e+00 -2.02551746e+00 4.74457711e-01
6.93147480e-02 -1.14362681e+00 -1.56824797e-01 4.58061814e-01
-9.71328616e-01 -1.07598448e+00 -5.40496469e-01 -4.43386972e-01
6.66056097e-01 3.52913797e-01 7.02515185e-01 -3.92712146e-01
-1.32812457e-02 4.42028552e-01 -3.43442202e-01 -4.42342550e-01
-2.31546924e-01 5.34151495e-02 1.74297929e-01 -2.05624506e-01
9.69857350e-02 -5.31694770e-01 -6.32482708e-01 1.60914093e-01
-8.91547203e-01 3.20846438e-01 7.04264104e-01 1.00949275e+00
4.99384731e-01 -1.01124058e-02 2.80070841e-01 -2.54176557e-01
4.50768173e-01 -2.97810823e-01 -1.05689502e+00 -6.15824480e-03
-3.69673699e-01 1.42724946e-01 1.21946168e+00 -1.06046128e+00
-7.09543765e-01 6.42078042e-01 2.45089099e-01 -1.03365743e+00
-1.21488295e-01 3.69986415e-01 3.05746019e-01 3.92913148e-02
4.71160293e-01 2.87337005e-01 2.47881457e-01 -2.49337569e-01
1.58760175e-01 5.43975413e-01 3.80975693e-01 -2.72896141e-01
2.92012066e-01 5.79952359e-01 2.84018368e-01 -7.82825530e-01
-3.70296448e-01 -2.47349814e-01 -6.12947881e-01 -4.11729455e-01
5.74083805e-01 -7.13369608e-01 -1.09741926e+00 3.24845463e-01
-1.44833148e+00 -6.60082698e-01 -6.13776207e-01 8.69765460e-01
-1.08393145e+00 -2.96486672e-02 -4.71336246e-01 -1.13960731e+00
-1.17004417e-01 -1.19898093e+00 1.16380858e+00 1.55091688e-01
-1.10551417e-01 -4.79774505e-01 -4.86423485e-02 -3.42951447e-01
1.89451456e-01 3.98458987e-01 4.21376944e-01 -5.04164040e-01
-7.28294015e-01 -3.91989529e-01 9.73235145e-02 2.65851151e-02
-1.14872552e-01 -4.79582734e-02 -5.97488165e-01 -4.24385190e-01
3.73266667e-01 -2.61225402e-01 6.06663048e-01 3.79622161e-01
1.10785460e+00 -4.39760357e-01 -4.84011203e-01 2.89156795e-01
1.25966239e+00 4.26752627e-01 3.58491212e-01 4.28564608e-01
5.91955841e-01 5.77879906e-01 9.88591552e-01 7.54022121e-01
2.98489332e-01 9.66488779e-01 7.86056936e-01 4.30481225e-01
2.18164742e-01 -3.15634400e-01 6.71124637e-01 5.38685203e-01
-5.74513301e-02 -3.34106565e-01 -9.94037330e-01 7.36916065e-01
-2.13262939e+00 -8.61371636e-01 4.17512245e-02 2.52036023e+00
5.09010911e-01 2.65083313e-01 1.17124014e-01 1.21607341e-01
6.63085699e-01 -5.86367846e-02 -8.85677814e-01 -3.34523529e-01
5.51382780e-01 -3.49740058e-01 9.97718871e-01 3.38745713e-01
-8.60551655e-01 7.11900234e-01 5.26131105e+00 4.21954989e-01
-1.51492989e+00 -8.90028328e-02 1.75862953e-01 -5.57514310e-01
4.74146903e-01 -3.05851717e-02 -7.15209723e-01 6.78016543e-01
1.35422468e+00 1.08571328e-01 4.95575309e-01 1.07004464e+00
6.48782194e-01 -1.46307439e-01 -1.47444701e+00 9.82726336e-01
-2.62508780e-01 -1.13236034e+00 -2.26872966e-01 1.39152333e-01
9.37779918e-02 2.36235306e-01 -1.97693184e-01 1.47956729e-01
2.66729534e-01 -7.51397789e-01 1.02690744e+00 6.38111174e-01
5.90117097e-01 -5.96278906e-01 5.71399033e-01 9.22698200e-01
-7.84926593e-01 -3.60197335e-01 -5.54733694e-01 -2.82379746e-01
4.52540278e-01 3.46956193e-01 -9.96246994e-01 2.08197936e-01
7.14490056e-01 4.75725055e-01 1.99010130e-02 1.08560562e+00
1.14477508e-01 4.95702028e-01 -9.95606720e-01 -2.83658564e-01
5.13904274e-01 -1.48419127e-01 7.59809732e-01 9.19980049e-01
6.84375525e-01 4.39939722e-02 1.07097991e-01 7.60114849e-01
2.68746376e-01 -5.78423262e-01 -1.01110756e+00 2.66679376e-01
4.47651267e-01 9.09039795e-01 -6.80441499e-01 -1.48158595e-01
-3.69100422e-01 9.72142756e-01 1.96257517e-01 2.31951073e-01
-9.41073596e-01 -2.30919659e-01 3.82850051e-01 1.71209201e-01
4.79127645e-01 -7.84119427e-01 -5.88377416e-02 -9.65840340e-01
1.84690922e-01 -4.96139437e-01 -1.73209589e-02 -7.81120718e-01
-7.28161991e-01 3.76848906e-01 1.50048330e-01 -1.63980877e+00
-7.44211495e-01 -5.89270949e-01 -5.14520645e-01 2.88020790e-01
-1.21136129e+00 -9.03157771e-01 -4.11208451e-01 3.98930371e-01
8.91264677e-01 1.87100723e-01 4.48052526e-01 4.19475324e-02
-3.09477687e-01 4.47209291e-02 1.05814509e-01 -2.49465019e-01
2.88680613e-01 -1.06017566e+00 3.81804883e-01 7.36271739e-01
9.55254734e-02 4.54923093e-01 9.25772488e-01 -5.02884448e-01
-1.84235346e+00 -1.14541364e+00 2.79656738e-01 -2.88678467e-01
6.41106427e-01 -3.93207431e-01 -7.36556351e-01 8.42922866e-01
-1.79261699e-01 1.33584797e-01 -9.76826921e-02 -5.34730136e-01
3.67042542e-01 -2.05484331e-01 -1.14543295e+00 8.61721814e-01
9.15110171e-01 -8.12110081e-02 -5.50738275e-01 2.97215641e-01
7.97035933e-01 -5.42591810e-01 -6.52158797e-01 2.14096099e-01
7.54298091e-01 -8.23770821e-01 8.18285584e-01 -3.02653015e-01
2.93388367e-01 -2.79444456e-01 5.85163459e-02 -1.12426424e+00
9.27756801e-02 -6.16867125e-01 -4.24494326e-01 6.53874278e-01
7.53737465e-02 -3.69967371e-01 9.75729585e-01 5.62711239e-01
-1.05030894e-01 -8.80764246e-01 -1.16097200e+00 -1.01612246e+00
-1.75369725e-01 -3.81281585e-01 3.59630466e-01 2.78973132e-01
-1.02395797e-02 1.51096612e-01 -4.98469442e-01 2.47688487e-01
3.96344781e-01 1.13752484e-01 9.01692212e-01 -8.83990526e-01
-2.38652796e-01 -1.03997536e-01 -3.14667344e-01 -1.47806847e+00
-9.95367318e-02 -1.11973785e-01 4.32730913e-01 -1.20673037e+00
-3.65594834e-01 -4.95603889e-01 7.20342025e-02 3.90204996e-01
4.05101478e-01 -2.74296641e-01 3.80935371e-01 4.47629452e-01
-4.62967306e-01 6.31469727e-01 9.48477149e-01 2.71516778e-02
-4.89884108e-01 2.27139741e-01 2.51143932e-01 9.41304803e-01
7.82164156e-01 -5.23759961e-01 -6.42426610e-01 -5.77053785e-01
5.81984371e-02 5.19028723e-01 5.71053505e-01 -1.44670308e+00
6.54140592e-01 -3.58660370e-01 2.43517369e-01 -6.28501296e-01
8.10058653e-01 -1.47203314e+00 2.77216285e-01 8.43045712e-01
-4.86413628e-01 3.21306109e-01 7.56663084e-02 7.88547575e-01
-3.25090787e-03 -5.89712143e-01 6.80887759e-01 -2.21254498e-01
-5.69611549e-01 7.48349205e-02 -5.81245661e-01 -5.97169280e-01
1.38322830e+00 -4.82119232e-01 -6.09077625e-02 -3.43218863e-01
-3.83333266e-01 2.07891569e-01 7.05477118e-01 3.18964750e-01
6.64946854e-01 -9.32416916e-01 -1.33070856e-01 9.16670784e-02
-7.41969571e-02 4.84945863e-01 -1.42924994e-01 9.00566101e-01
-7.05299199e-01 3.48486006e-01 -3.07305008e-01 -7.76346743e-01
-8.68211448e-01 6.52213097e-01 3.65804940e-01 -9.77970436e-02
-1.17312574e+00 2.71924049e-01 -2.54040081e-02 -1.25865817e-01
3.55779767e-01 -7.59402752e-01 -5.88212870e-02 -2.69023567e-01
2.64950514e-01 4.52510446e-01 -2.29909234e-02 -1.07002161e-01
-1.95848197e-01 4.86089617e-01 -2.52658175e-03 -2.10140958e-01
1.38779306e+00 -1.66034296e-01 4.63829100e-01 9.05313373e-01
6.73282444e-01 -3.79285932e-01 -2.02200556e+00 1.02643117e-01
3.19646411e-02 -3.40910017e-01 4.51766737e-02 -4.68845427e-01
-8.87878299e-01 9.62631464e-01 5.19704819e-01 2.09262550e-01
9.25734520e-01 -4.59907532e-01 1.02201438e+00 1.01147711e+00
8.55078876e-01 -9.57837760e-01 -7.11955829e-03 5.63591063e-01
7.35804081e-01 -1.02074540e+00 -1.41708195e-01 1.20944016e-01
-6.18803859e-01 1.41478705e+00 6.51455760e-01 -4.58164722e-01
1.18547104e-01 4.25453156e-01 -2.91167080e-01 3.63153778e-02
-9.28609312e-01 1.36303693e-01 -3.69003952e-01 5.01272380e-01
-2.98001140e-01 -1.85640752e-01 -2.05677822e-02 2.94466972e-01
-1.27686188e-01 4.67061847e-01 9.39429462e-01 1.03507435e+00
-5.01697004e-01 -6.03895485e-01 -3.74630541e-01 3.47838938e-01
-2.58324653e-01 2.64538139e-01 -2.86148582e-02 8.73700500e-01
-2.79174019e-02 6.84598267e-01 4.42278922e-01 -3.15748841e-01
4.64808702e-01 -2.39708975e-01 5.38924813e-01 -3.25769156e-01
-4.19802785e-01 -3.27914894e-01 -7.86165223e-02 -8.28093708e-01
-2.58652776e-01 -8.01334679e-01 -1.43176830e+00 -2.68882841e-01
-3.18327338e-01 -2.98778772e-01 8.42326701e-01 8.09398234e-01
5.37566304e-01 4.08550799e-01 3.71162742e-01 -1.36599922e+00
-9.31617796e-01 -9.70114648e-01 -1.80579081e-01 3.27460952e-02
7.29462922e-01 -7.93770611e-01 -2.18271270e-01 2.74546772e-01] | [4.8200578689575195, 1.1690418720245361] |
57dcfd37-6db8-4d57-8b46-865337ad4223 | discriminative-clustering-for-robust | 1905.13331 | null | https://arxiv.org/abs/1905.13331v1 | https://arxiv.org/pdf/1905.13331v1.pdf | Discriminative Clustering for Robust Unsupervised Domain Adaptation | Unsupervised domain adaptation seeks to learn an invariant and discriminative representation for an unlabeled target domain by leveraging the information of a labeled source dataset. We propose to improve the discriminative ability of the target domain representation by simultaneously learning tightly clustered target representations while encouraging that each cluster is assigned to a unique and different class from the source. This strategy alleviates the effects of negative transfer when combined with adversarial domain matching between source and target representations. Our approach is robust to differences in the source and target label distributions and thus applicable to both balanced and imbalanced domain adaptation tasks, and with a simple extension, it can also be used for partial domain adaptation. Experiments on several benchmark datasets for domain adaptation demonstrate that our approach can achieve state-of-the-art performance in all three scenarios, namely, balanced, imbalanced and partial domain adaptation. | ['Ricardo Henao', 'Rui Wang', 'Guoyin Wang'] | 2019-05-30 | null | null | null | null | ['partial-domain-adaptation'] | ['methodology'] | [ 4.1486090e-01 -5.4195956e-03 -7.5436425e-01 -6.3471079e-01
-9.5544857e-01 -1.0254761e+00 5.8531827e-01 1.6884111e-01
-2.3656829e-01 1.0120931e+00 3.1418900e-03 2.5666794e-01
1.7623356e-01 -6.4064288e-01 -5.7965428e-01 -8.4007335e-01
3.6659479e-01 9.0499020e-01 2.6780042e-01 -1.6672742e-01
-5.9331637e-02 5.5328166e-01 -1.0376949e+00 1.6198194e-01
8.5053259e-01 8.6319178e-01 -1.3743012e-01 8.7733485e-02
-1.5495403e-01 6.3307714e-01 -7.9838824e-01 -2.4527732e-01
4.9109274e-01 -5.6159824e-01 -7.0603603e-01 1.0408267e-01
3.1984609e-01 -1.5578082e-02 -2.8070477e-01 1.0593194e+00
5.2913487e-01 1.7973346e-01 1.2104471e+00 -1.3676615e+00
-7.9300016e-01 1.6347630e-01 -8.1399554e-01 2.4301663e-01
1.6329932e-01 -3.2889053e-02 6.6899872e-01 -7.9913318e-01
6.8873292e-01 1.0104837e+00 5.3304386e-01 8.8484806e-01
-1.6503193e+00 -1.1776172e+00 3.6487561e-01 -3.7969150e-02
-1.2465197e+00 -4.5264664e-01 1.0075806e+00 -4.7116622e-01
5.2570510e-01 -3.5209242e-01 8.9786490e-03 1.5075090e+00
-2.4344525e-01 7.3375416e-01 1.0696559e+00 -4.0089774e-01
4.9267143e-01 4.7148466e-01 9.5353812e-02 1.3875324e-01
2.3696539e-01 2.8348878e-01 -2.6357424e-01 -3.6827561e-01
5.6847775e-01 -2.9969364e-02 -1.1040499e-02 -1.2566251e+00
-1.0463336e+00 1.0882183e+00 5.6809264e-01 2.8978455e-01
-2.4548426e-01 -3.3528501e-01 6.3011634e-01 5.3645945e-01
6.6283250e-01 3.4425652e-01 -7.3711866e-01 2.4657243e-01
-6.3223708e-01 2.6426524e-01 6.6894686e-01 1.1558810e+00
1.0155143e+00 2.5758317e-01 -1.0109306e-01 1.0332189e+00
-6.9797717e-02 8.0001295e-01 8.0819654e-01 -6.6192639e-01
6.4818317e-01 6.2873930e-01 1.1933481e-01 -5.8988905e-01
-2.0418301e-01 -4.5293134e-01 -7.5166929e-01 4.0457070e-01
5.7030576e-01 -1.9833876e-01 -1.2433125e+00 2.1876032e+00
4.4324160e-01 1.7172828e-01 3.1261420e-01 6.7455333e-01
6.7890263e-01 4.8158309e-01 5.3538114e-01 -8.3603077e-02
7.1171266e-01 -8.0042511e-01 -3.7833917e-01 -7.3987919e-01
4.2525524e-01 -5.3943586e-01 9.8530549e-01 1.3601201e-02
-6.1298144e-01 -5.8950812e-01 -1.0191617e+00 1.4945669e-01
-3.9855522e-01 -1.7891634e-01 3.1291002e-01 6.7615288e-01
-4.8824242e-01 1.8683338e-01 -5.6153595e-01 -4.1363531e-01
7.5576675e-01 4.8835951e-01 -6.7812008e-01 -4.7704256e-01
-1.1033921e+00 9.2517585e-01 6.2185931e-01 -9.3689311e-01
-1.0077199e+00 -8.9392382e-01 -9.1976058e-01 4.0458664e-03
-1.9688668e-02 -5.4141819e-01 1.1052796e+00 -1.6130412e+00
-1.3426410e+00 1.1615596e+00 -1.4096531e-01 -4.0370691e-01
2.4180873e-01 3.6601365e-02 -5.6103939e-01 7.3429734e-02
3.0950862e-01 7.1290469e-01 1.0351639e+00 -1.2783364e+00
-5.0013250e-01 -6.5608555e-01 -4.0020084e-01 3.8937727e-01
-6.1464322e-01 -1.8128365e-01 -1.3238269e-01 -8.3780766e-01
-7.9949521e-02 -1.0107757e+00 -1.5501896e-01 4.5361407e-02
-6.7681678e-02 -7.7190667e-02 1.0848773e+00 -4.8672932e-01
7.2454381e-01 -2.3667891e+00 2.2817080e-01 3.9111757e-01
-1.1657640e-01 4.2344612e-01 -4.1377723e-01 2.0589837e-01
-4.6794221e-01 -2.5630495e-01 -4.6577790e-01 -1.1929070e-01
-1.8542844e-01 3.7647447e-01 -4.5559308e-01 5.8754200e-01
4.3435559e-01 7.6071495e-01 -9.8483193e-01 -3.3918777e-01
2.5871800e-02 3.2131460e-01 -4.7224692e-01 4.6316209e-01
-5.1323015e-02 8.2543290e-01 -5.2016813e-01 6.2296766e-01
8.2193321e-01 -1.6826938e-01 3.9226893e-01 2.3225082e-01
7.7152497e-01 1.9792376e-01 -1.1660862e+00 1.6798253e+00
-3.3650798e-01 4.1284049e-01 8.0270946e-02 -1.4529601e+00
1.3400049e+00 2.6312780e-01 4.3916422e-01 -8.2463926e-01
-2.7476144e-01 2.6658255e-01 -1.5682153e-01 8.2147561e-02
6.6061758e-02 -7.5841892e-01 -4.9836278e-01 5.5722857e-01
5.0220490e-01 4.7425840e-02 -2.7947614e-01 1.7520407e-02
8.2145846e-01 1.7169456e-01 7.2683835e-01 -1.4000304e-01
4.5221853e-01 7.9405971e-02 8.1393772e-01 5.0333375e-01
-4.6035063e-01 6.0654789e-01 3.3303076e-01 -2.4116772e-01
-1.2095519e+00 -1.5208749e+00 -2.6973804e-02 1.4580905e+00
2.1335268e-01 3.7099037e-01 -4.8103553e-01 -1.3437462e+00
3.1294009e-01 6.8585664e-01 -7.7448791e-01 -6.6223931e-01
-5.5610979e-01 -5.8468342e-01 5.7209933e-01 8.3938396e-01
1.9970284e-01 -9.9739212e-01 1.0229830e-02 2.0558050e-01
-1.7564762e-01 -9.3253678e-01 -3.9487669e-01 5.8419985e-01
-1.1519780e+00 -1.0353806e+00 -9.3324637e-01 -1.2122331e+00
8.5316420e-01 1.9213383e-01 1.2999419e+00 -5.8388841e-01
2.0914261e-01 3.4536281e-01 -2.4976802e-01 -4.6117315e-01
-5.9832674e-01 3.9444748e-01 1.7404199e-01 -4.3691013e-02
8.1046885e-01 -6.5517348e-01 -2.5690934e-01 5.8644307e-01
-9.8558110e-01 -6.5906602e-01 3.3819857e-01 1.0383792e+00
5.9263086e-01 -1.1278791e-01 1.1359153e+00 -1.1670643e+00
5.0428188e-01 -8.7245387e-01 -2.5277704e-01 1.4202102e-01
-5.3518933e-01 1.4640467e-02 9.1719651e-01 -9.4184923e-01
-1.1949133e+00 3.5585144e-01 2.5944191e-01 -5.5094784e-01
-6.1860585e-01 5.5368330e-02 -5.4968673e-01 -2.5439847e-02
1.1627133e+00 1.3111767e-01 1.6021422e-01 -5.1918703e-01
4.2917845e-01 7.0707327e-01 5.6095976e-01 -6.7898595e-01
1.2859198e+00 5.0662249e-01 -3.9236769e-01 -3.7553829e-01
-8.9429247e-01 -6.3522106e-01 -8.9643103e-01 3.6864799e-01
3.7555718e-01 -1.3041277e+00 2.7198219e-01 4.0785143e-01
-6.2249351e-01 -4.1514331e-01 -6.8762177e-01 2.4933264e-01
-5.8155227e-01 2.6115289e-01 -1.6430056e-01 -2.2278990e-01
-1.6033092e-01 -8.0074471e-01 8.5480148e-01 2.4855389e-01
-4.1300800e-01 -1.3489270e+00 3.3026865e-01 7.2622240e-02
2.9515296e-01 2.9470870e-01 1.0439391e+00 -1.3767178e+00
9.1836952e-02 -3.5844186e-01 -1.0227818e-01 7.0518017e-01
4.8018646e-01 -5.9612459e-01 -9.7708374e-01 -6.8073869e-01
-8.6944595e-02 -7.9731375e-01 7.4312049e-01 6.8323933e-02
7.4933338e-01 -1.8561122e-01 -4.2621332e-01 5.6178951e-01
1.4413344e+00 1.9632253e-01 5.4646075e-01 4.3782312e-01
5.9902078e-01 6.5008777e-01 9.0482497e-01 2.5326797e-01
6.9112189e-02 7.3326761e-01 2.2376753e-01 -3.1701303e-01
-1.8712462e-01 -3.5391948e-01 4.5461905e-01 1.5738979e-01
6.7891741e-01 -4.8552610e-02 -9.2116451e-01 9.3719858e-01
-1.5721238e+00 -8.7923682e-01 4.9486944e-01 2.3664584e+00
1.0679264e+00 3.6484323e-02 4.3783656e-01 -3.8399524e-04
9.8655236e-01 2.6554886e-02 -1.0623026e+00 -3.7582853e-01
-1.9771560e-01 4.9595734e-01 4.6283373e-01 1.3488431e-01
-1.3680376e+00 1.0652257e+00 7.0260725e+00 8.2887769e-01
-1.1636643e+00 1.3756831e-01 5.5719751e-01 2.6944809e-02
-2.3525955e-01 -3.3020678e-01 -5.5601764e-01 5.2646983e-01
7.6710320e-01 -4.1357043e-01 2.0818067e-01 1.2298443e+00
-4.6923897e-01 3.4670252e-01 -1.1989549e+00 6.2987179e-01
7.8972146e-02 -8.6957747e-01 2.5256405e-02 -4.7202572e-02
1.1263440e+00 1.9666295e-01 2.8145605e-01 6.6602439e-01
6.2000269e-01 -9.7507757e-01 2.8572035e-01 -2.0448765e-01
1.2087904e+00 -9.4145739e-01 6.3639987e-01 3.7365782e-01
-8.1171942e-01 -2.0209809e-01 -3.9781702e-01 1.3514155e-01
-3.6350244e-01 3.2822526e-01 -1.0685290e+00 3.6955178e-01
4.6759212e-01 8.3642048e-01 -5.1716697e-01 8.0126768e-01
-2.5363693e-01 6.0146284e-01 -2.0214616e-01 4.4229922e-01
2.6257658e-02 8.6953789e-02 4.0364864e-01 1.1065067e+00
9.8252550e-02 -1.1073623e-01 4.3560287e-01 5.8923405e-01
-2.9929283e-01 1.7487167e-01 -1.0219779e+00 1.3249516e-01
7.7582574e-01 8.0124146e-01 -3.5905549e-01 -4.4228232e-01
-2.7624682e-01 9.8912770e-01 5.4307306e-01 6.0375440e-01
-6.9926697e-01 -2.6760381e-01 9.5883209e-01 2.4559416e-02
5.7935977e-01 1.2357399e-01 -5.6353986e-01 -1.1799868e+00
-9.9725276e-02 -1.0418129e+00 8.7562627e-01 -3.8748196e-01
-1.8864298e+00 3.8690615e-01 -2.3099370e-02 -1.6599779e+00
-4.5213598e-01 -4.8077530e-01 -5.0867200e-01 1.1549737e+00
-1.8124142e+00 -1.1270609e+00 -1.8029872e-01 1.1623968e+00
2.7860057e-01 -5.8118761e-01 1.2291574e+00 2.5025272e-01
-2.1592484e-01 9.8190200e-01 6.8138778e-01 3.5322171e-01
1.3794988e+00 -1.1902238e+00 2.2751537e-01 6.3594788e-01
1.8067969e-02 3.8525689e-01 5.0714922e-01 -4.7144276e-01
-6.6497129e-01 -1.4702557e+00 5.7690692e-01 -4.6124831e-01
3.6319324e-01 -2.4495761e-01 -1.1214020e+00 9.0344220e-01
-5.3484123e-02 2.6516673e-01 1.1294873e+00 2.4869935e-01
-9.5168173e-01 -2.5760683e-01 -1.7560505e+00 1.2012554e-01
7.2146869e-01 -5.5010253e-01 -8.6190283e-01 3.8978240e-01
4.8466867e-01 -3.3607295e-01 -9.1597891e-01 3.5245490e-01
2.0738120e-01 -6.6829598e-01 1.2238595e+00 -9.9522847e-01
4.0084454e-01 -1.8659711e-01 -1.1959509e-01 -1.6388437e+00
-5.6250083e-01 1.1916046e-02 -1.3109127e-01 1.3490186e+00
2.6563507e-01 -6.7085117e-01 1.0466074e+00 3.3664685e-01
2.6852599e-01 -1.9501989e-01 -1.0330322e+00 -1.1448722e+00
7.1052331e-01 7.3885903e-02 5.9914583e-01 1.2903957e+00
-1.4683014e-01 5.0241190e-01 -3.0441001e-01 2.1305646e-01
6.6591787e-01 4.1045475e-01 9.0906966e-01 -1.4192415e+00
-1.7203817e-01 -1.2363413e-01 -4.3539172e-01 -9.2876869e-01
6.2667263e-01 -1.0941409e+00 -4.8052453e-02 -1.0188887e+00
2.1489926e-01 -6.4979506e-01 -7.1303171e-01 6.2794900e-01
-2.0136200e-01 5.2158231e-01 1.6200680e-01 3.7357688e-01
-4.3687019e-01 5.6899327e-01 9.0266985e-01 -3.0972970e-01
-2.0473972e-01 1.0866573e-01 -1.1907524e+00 5.4441315e-01
8.8732582e-01 -8.5534841e-01 -5.3125137e-01 -3.3672193e-01
-5.6106907e-01 -2.5080761e-01 1.8781751e-01 -8.9859819e-01
-2.0569290e-01 -3.3766884e-01 8.2775652e-01 -1.5934180e-01
1.5954739e-01 -1.0851395e+00 -1.1342838e-01 2.2237936e-01
-5.0381094e-01 -4.4732538e-01 4.3647876e-01 8.3163351e-01
-4.5409599e-01 -1.4772375e-01 1.4632691e+00 -4.9522677e-03
-9.3327457e-01 2.8280100e-01 6.6242948e-02 5.2071738e-01
1.2898220e+00 -3.3900753e-01 -2.7837953e-01 -3.7230596e-01
-6.8655074e-01 2.1780075e-01 8.9494580e-01 5.0781131e-01
3.3897680e-01 -1.6809332e+00 -7.1472514e-01 4.7072881e-01
5.7846427e-01 -6.8733297e-02 -1.6017517e-03 1.1382834e-01
9.5199898e-02 1.4957252e-01 -6.7581248e-01 -6.5974784e-01
-1.0437136e+00 9.2555034e-01 2.8849524e-01 -5.5643123e-01
-3.5726953e-01 7.3822278e-01 6.3511336e-01 -9.4041014e-01
1.9814986e-01 3.2798195e-01 -2.4437049e-01 4.2290550e-02
4.6044254e-01 7.1811147e-02 -2.4558773e-02 -8.0685478e-01
-5.5392355e-01 5.2938342e-01 -2.6214060e-01 2.4150904e-01
1.2123778e+00 -1.3695200e-01 3.6341989e-01 2.8409979e-01
1.4252614e+00 -1.2426876e-01 -1.5206831e+00 -6.7702931e-01
6.5958351e-02 -4.1903496e-01 -4.4756326e-01 -1.1913637e+00
-1.1764719e+00 7.8298765e-01 7.9132801e-01 -2.1845858e-01
1.3721815e+00 7.7949196e-02 5.4185987e-01 1.8315606e-01
2.8099015e-01 -1.0009598e+00 3.3357710e-01 5.0806516e-01
6.1528748e-01 -1.4118103e+00 -1.2142214e-01 -3.2256487e-01
-1.0106457e+00 8.4250939e-01 8.2506657e-01 -3.3294353e-01
4.2300013e-01 5.8480404e-02 2.3239085e-01 2.4327439e-01
-3.8082859e-01 -2.6846291e-02 2.6615748e-01 1.4059317e+00
3.5439977e-01 6.3051999e-02 1.9261658e-01 4.7123495e-01
2.7089459e-01 -1.1311185e-01 1.2698436e-01 8.8334161e-01
-2.9599199e-01 -1.4940070e+00 -4.9487093e-01 1.9920845e-01
-3.7770233e-01 7.9706006e-02 -6.0724610e-01 9.3186140e-01
-7.0760436e-03 6.4532524e-01 1.6073461e-01 -1.4021659e-01
4.7887933e-01 4.2016044e-01 2.8613082e-01 -9.5394778e-01
-5.0491619e-01 -7.3503166e-02 -2.6679528e-01 -3.3402196e-01
-3.6123872e-01 -5.9498566e-01 -1.0927025e+00 4.5267407e-02
-6.6470116e-02 6.2224451e-02 2.1562453e-01 6.9989562e-01
4.3552408e-01 1.7842163e-01 8.4868747e-01 -7.2254682e-01
-9.3567610e-01 -8.6880404e-01 -7.5065547e-01 1.0033826e+00
3.8005823e-01 -9.3513185e-01 -2.5501657e-01 1.5164235e-01] | [10.331658363342285, 3.0665111541748047] |
d1bd2b1f-61e2-4309-9ffc-d568cf590681 | building-machines-that-learn-and-think-like | 1604.00289 | null | http://arxiv.org/abs/1604.00289v3 | http://arxiv.org/pdf/1604.00289v3.pdf | Building Machines That Learn and Think Like People | Recent progress in artificial intelligence (AI) has renewed interest in
building systems that learn and think like people. Many advances have come from
using deep neural networks trained end-to-end in tasks such as object
recognition, video games, and board games, achieving performance that equals or
even beats humans in some respects. Despite their biological inspiration and
performance achievements, these systems differ from human intelligence in
crucial ways. We review progress in cognitive science suggesting that truly
human-like learning and thinking machines will have to reach beyond current
engineering trends in both what they learn, and how they learn it.
Specifically, we argue that these machines should (a) build causal models of
the world that support explanation and understanding, rather than merely
solving pattern recognition problems; (b) ground learning in intuitive theories
of physics and psychology, to support and enrich the knowledge that is learned;
and (c) harness compositionality and learning-to-learn to rapidly acquire and
generalize knowledge to new tasks and situations. We suggest concrete
challenges and promising routes towards these goals that can combine the
strengths of recent neural network advances with more structured cognitive
models. | ['Tomer D. Ullman', 'Samuel J. Gershman', 'Joshua B. Tenenbaum', 'Brenden M. Lake'] | 2016-04-01 | null | null | null | null | ['board-games'] | ['playing-games'] | [ 2.30577916e-01 3.48708630e-01 8.25851485e-02 -4.41630572e-01
3.61666888e-01 -4.58336085e-01 8.45499873e-01 1.79993287e-01
-2.15306118e-01 5.34377038e-01 2.24034518e-01 -4.94590491e-01
-4.86207992e-01 -1.14861190e+00 -6.85020626e-01 -3.87335390e-01
-4.34607081e-02 6.03962123e-01 3.63245726e-01 -6.72968566e-01
3.80975425e-01 3.85085285e-01 -1.71438432e+00 2.90537566e-01
9.06941414e-01 7.92558014e-01 2.41714880e-01 7.95428813e-01
-7.27365464e-02 1.40738499e+00 -6.77516982e-02 -2.37728566e-01
1.16862059e-01 -6.83133006e-01 -1.05976856e+00 -2.37550020e-01
1.13300927e-01 -1.06962971e-01 -4.97067064e-01 7.45735645e-01
-5.18819578e-02 2.75029689e-01 4.97364432e-01 -9.42730367e-01
-1.30923975e+00 4.27176327e-01 -2.10115314e-01 2.33663514e-01
9.97355431e-02 5.29177248e-01 9.36371446e-01 -5.48895061e-01
3.47785711e-01 1.11165524e+00 5.60226858e-01 1.10389054e+00
-9.79566514e-01 -4.40282673e-01 7.94991329e-02 5.53348660e-01
-7.57056892e-01 -2.45579213e-01 5.64358771e-01 -6.49046719e-01
1.19580591e+00 -9.85844657e-02 1.19704604e+00 8.58541369e-01
2.74999887e-01 6.41150296e-01 9.78140295e-01 -6.10063553e-01
3.87976706e-01 -1.02120996e-01 1.96292117e-01 8.86713207e-01
3.18155557e-01 5.14283240e-01 -8.14207375e-01 4.70985472e-01
9.83988285e-01 -1.16097435e-01 1.31644890e-01 -1.76128432e-01
-1.33988440e+00 7.30461240e-01 7.31295049e-01 3.52866918e-01
-5.12288749e-01 5.18828332e-01 1.39256686e-01 8.09834674e-02
-2.20870227e-01 1.12742341e+00 -5.87753296e-01 -1.74491316e-01
-5.91241181e-01 3.66616160e-01 8.94658089e-01 5.79535663e-01
7.44438589e-01 4.71347332e-01 4.34730470e-01 3.49722058e-01
1.39879659e-01 2.95400947e-01 5.75443387e-01 -1.16630173e+00
-2.53631830e-01 6.96961522e-01 -1.68127328e-01 -9.53260779e-01
-5.51796794e-01 -6.44113541e-01 -6.80448830e-01 6.29376471e-01
4.38613415e-01 -7.99389407e-02 -9.93104577e-01 1.73501456e+00
6.58307821e-02 1.34948984e-01 1.44179925e-01 8.70096505e-01
7.34269500e-01 6.42386436e-01 2.02897891e-01 3.83807391e-01
1.33899176e+00 -7.94222772e-01 -2.80958563e-02 -8.41938138e-01
4.37769085e-01 -1.83833092e-01 1.13132381e+00 7.34332383e-01
-1.22497559e+00 -8.04254353e-01 -1.32483780e+00 -2.54030347e-01
-4.86604840e-01 -5.33006966e-01 1.29121768e+00 8.14670146e-01
-1.14532340e+00 7.09014595e-01 -7.57205665e-01 -4.52262789e-01
6.74897730e-01 4.91411150e-01 -1.44582465e-01 1.12402834e-01
-1.20123124e+00 1.19606996e+00 8.36545408e-01 -1.93080261e-01
-9.61081326e-01 -9.50762808e-01 -5.48150182e-01 2.77520478e-01
4.91932929e-01 -1.13644946e+00 1.25719750e+00 -1.23342049e+00
-1.56897986e+00 9.20607924e-01 3.45759802e-02 -7.70486295e-01
-2.21958965e-01 -4.08854485e-01 -1.62257269e-01 2.37430143e-03
-3.96916658e-01 9.30960119e-01 2.72744030e-01 -1.25371087e+00
-6.31208003e-01 -3.27919304e-01 3.46973747e-01 -3.30991894e-02
-3.07541102e-01 -8.95273685e-02 2.45335609e-01 -3.54912132e-01
2.40706712e-01 -7.55890667e-01 -3.60742092e-01 9.62954164e-02
1.17576838e-01 -4.26362038e-01 5.22070706e-01 -2.91654795e-01
5.06513178e-01 -1.73937476e+00 1.62157699e-01 1.22065857e-01
7.70639420e-01 4.28046405e-01 -3.17217000e-02 3.08493644e-01
-9.69311669e-02 1.56290568e-02 1.99418098e-01 5.39568007e-01
-2.41074394e-02 3.75241011e-01 -4.77470934e-01 -1.33985549e-01
3.02513748e-01 1.42868805e+00 -1.16124022e+00 2.44666040e-02
3.04687351e-01 2.40932003e-01 -9.62872386e-01 -1.37332482e-02
-7.54126549e-01 6.22425497e-01 -3.89572680e-01 1.60505787e-01
-2.23828573e-02 -5.61658084e-01 2.01266050e-01 2.71660715e-01
-1.61160097e-01 5.74697793e-01 -6.84847951e-01 1.55817437e+00
-4.73054886e-01 8.77041399e-01 -2.57996172e-01 -1.63951719e+00
9.77880597e-01 2.22109273e-01 2.42654800e-01 -9.73489940e-01
2.47518778e-01 5.02700396e-02 6.61455691e-01 -7.17224240e-01
1.44414976e-01 -6.55626297e-01 2.78918177e-01 6.39246643e-01
2.87903398e-01 -5.83748400e-01 9.25716981e-02 5.91749772e-02
9.87752080e-01 2.47663289e-01 2.68150717e-01 -4.41571027e-01
4.25567150e-01 1.89445764e-01 4.08961833e-01 9.89817202e-01
-7.27641433e-02 1.53252363e-01 2.22851485e-01 -1.06613243e+00
-1.13282442e+00 -1.31384492e+00 3.47593099e-01 1.49104691e+00
2.65145916e-02 -2.01884955e-01 -7.18057811e-01 -1.59002896e-02
-3.23657602e-01 9.49476421e-01 -6.94068491e-01 -4.95372564e-01
-5.28637946e-01 -5.90233803e-01 4.05409187e-01 7.64582098e-01
6.50925040e-01 -1.41565609e+00 -9.67655480e-01 2.43158832e-01
2.98067778e-01 -9.42084014e-01 4.86118793e-01 3.15393716e-01
-9.32496011e-01 -9.02462661e-01 -1.99803516e-01 -7.95838535e-01
3.56856197e-01 2.82665789e-01 1.35785651e+00 5.01877010e-01
-4.86254305e-01 4.90450770e-01 -2.23582238e-01 -8.97543490e-01
-5.18851876e-01 -7.73574933e-02 3.30277592e-01 -5.49700439e-01
5.30096233e-01 -1.14367127e+00 -5.26852787e-01 1.54366732e-01
-9.33746397e-01 4.17627782e-01 6.89546704e-01 7.09713936e-01
-1.25983879e-01 9.33640227e-02 9.32822347e-01 -5.20048141e-01
6.08032107e-01 -5.15323102e-01 -2.63946027e-01 3.27383935e-01
-7.05472410e-01 1.83611870e-01 7.21047401e-01 -2.73597032e-01
-1.07392228e+00 -3.71396452e-01 -9.09685269e-02 3.14287126e-01
-4.53794956e-01 5.80160260e-01 9.66917351e-02 -2.51106750e-02
1.04487264e+00 4.60314065e-01 -1.09721780e-01 4.07611672e-03
6.49630129e-01 2.03250870e-01 8.02346647e-01 -1.11265922e+00
7.68495023e-01 2.81819254e-01 1.17324494e-01 -1.01969051e+00
-9.51909661e-01 2.02062979e-01 -6.89635396e-01 -3.29066277e-01
1.10751057e+00 -5.77966094e-01 -1.22840858e+00 3.58365953e-01
-1.05911922e+00 -5.38055539e-01 -6.28209233e-01 4.10465002e-01
-7.00697243e-01 -1.83778271e-01 -4.77974087e-01 -6.48903906e-01
3.44237201e-02 -7.17050970e-01 3.69813591e-01 8.59196007e-01
-5.84911704e-01 -1.13219869e+00 9.96050164e-02 4.13300067e-01
8.18389595e-01 1.73341797e-03 1.41729712e+00 -6.66517138e-01
-7.19461143e-01 3.56740057e-02 -2.13554651e-01 3.03638935e-01
-7.57695287e-02 -1.78208187e-01 -8.87826800e-01 2.54905552e-01
2.29095481e-02 -8.99709046e-01 7.12065637e-01 1.09350577e-01
1.21524978e+00 -7.17023090e-02 -1.90019146e-01 3.26622784e-01
1.11907983e+00 5.24219573e-01 7.23887920e-01 3.33321482e-01
3.97630215e-01 8.01496923e-01 -3.84201199e-01 3.92501764e-02
4.96224076e-01 1.87646240e-01 3.31842363e-01 1.53620586e-01
-1.58069134e-01 -3.99083763e-01 2.74229217e-02 9.41819787e-01
-6.30324066e-01 3.12571451e-02 -1.44710922e+00 4.51689243e-01
-1.73435521e+00 -1.22080648e+00 1.44019291e-01 1.77701175e+00
8.36730361e-01 5.75769842e-01 1.56989601e-02 8.12411234e-02
2.07991406e-01 -2.03081474e-01 -8.64434600e-01 -5.57848454e-01
-5.53192608e-02 7.75871694e-01 -2.34575644e-01 2.72527546e-01
-5.37927032e-01 1.19395280e+00 7.38054371e+00 4.62936819e-01
-1.17797399e+00 -1.19255379e-01 5.70060611e-01 1.25483200e-01
-3.46667439e-01 9.34842154e-02 -3.56661111e-01 -1.58340022e-01
1.04354250e+00 -2.35057309e-01 8.73535275e-01 7.57474899e-01
-3.66296768e-02 -1.08257256e-01 -1.26169670e+00 6.06297433e-01
-1.40763953e-01 -1.74806011e+00 2.21219063e-01 -6.77510276e-02
7.05403388e-01 3.44704301e-03 3.34537067e-02 5.34237444e-01
8.37415397e-01 -1.54592586e+00 7.05553472e-01 6.16577566e-01
6.67484477e-02 -3.93443733e-01 1.87912673e-01 6.25263214e-01
-7.57670522e-01 -2.48842120e-01 -4.99311447e-01 -9.71746743e-01
-3.12073648e-01 4.63009268e-01 -6.58435643e-01 1.37999088e-01
6.15991056e-01 6.44128799e-01 -5.02212644e-01 9.30496514e-01
-5.35803318e-01 7.23985612e-01 -1.16704695e-01 -6.68028235e-01
3.12275857e-01 6.16279878e-02 2.58338213e-01 8.21455002e-01
-4.48409431e-02 6.71032965e-01 -3.85746323e-02 1.31134140e+00
2.33379707e-01 -4.64065999e-01 -5.29799163e-01 -4.67586368e-01
2.75130838e-01 9.31929171e-01 -1.05918980e+00 -3.38684231e-01
-4.74374533e-01 4.68380213e-01 2.29391605e-01 1.89749733e-01
-6.89830184e-01 -1.93559960e-01 7.41197705e-01 -1.65277615e-03
1.53160095e-01 -6.68879986e-01 -7.25000799e-01 -9.62602496e-01
-3.94887924e-01 -9.61513996e-01 -1.66492313e-01 -1.10056210e+00
-1.18719566e+00 4.75832015e-01 -1.27683759e-01 -4.15800363e-01
-2.59540349e-01 -1.21343839e+00 -8.53968501e-01 4.78716582e-01
-8.85891795e-01 -1.08116949e+00 -3.26481849e-01 4.14729089e-01
4.82212096e-01 -3.48531961e-01 9.22898710e-01 -2.87133425e-01
-1.44016549e-01 1.02582350e-01 -1.19152151e-01 1.95032433e-01
-3.76050770e-02 -1.11040723e+00 6.12314761e-01 5.36032259e-01
3.33988994e-01 8.97293925e-01 8.23908627e-01 -2.62231380e-01
-1.48450089e+00 -3.36642057e-01 3.15105110e-01 -6.94513857e-01
7.11710513e-01 -5.57658792e-01 -8.66883814e-01 7.21386790e-01
2.74541140e-01 -3.35793197e-01 7.44173706e-01 6.41938269e-01
-6.98051274e-01 3.44064347e-02 -8.36291909e-01 8.39851499e-01
1.14035046e+00 -4.75400448e-01 -1.15299487e+00 1.48723155e-01
7.46144831e-01 3.14152651e-02 -4.31341141e-01 2.04540029e-01
1.03242385e+00 -1.17825449e+00 1.17087209e+00 -1.37481904e+00
1.00720322e+00 -1.19784936e-01 2.48810314e-02 -1.23709011e+00
-6.63541675e-01 -5.04246771e-01 5.46799526e-02 6.20682061e-01
3.56235772e-01 -6.50937140e-01 1.01283669e+00 9.27955985e-01
-1.88313767e-01 -7.73195565e-01 -5.35061657e-01 -7.05324054e-01
7.53678918e-01 -7.65234411e-01 5.29807687e-01 8.65103722e-01
4.68177587e-01 6.23931408e-01 6.37805015e-02 -1.74112827e-01
4.20009881e-01 -1.47888502e-02 6.38270199e-01 -1.62099433e+00
-5.57366729e-01 -7.46461034e-01 -6.06598735e-01 -1.00214553e+00
1.04958415e-01 -9.10318315e-01 7.30958506e-02 -1.55340195e+00
2.77076274e-01 -1.98199779e-01 -2.02994809e-01 5.77024400e-01
3.72001939e-02 5.97052239e-02 2.29895622e-01 -1.86566152e-02
-5.58695257e-01 3.98646861e-01 1.21449447e+00 6.24109767e-02
1.32661844e-02 -4.68559474e-01 -1.29012024e+00 1.15113068e+00
9.32271123e-01 -1.03386834e-01 -4.93897647e-01 -6.10084236e-01
1.01375866e+00 -2.24219099e-01 6.88719571e-01 -1.55437469e+00
5.36521971e-01 -5.69626629e-01 7.58616149e-01 8.73153359e-02
1.53480053e-01 -5.54049551e-01 -3.00345629e-01 8.30892861e-01
-5.69885850e-01 -1.67695761e-01 4.24503714e-01 3.46714705e-01
2.10826710e-01 -2.09444419e-01 8.06241870e-01 -6.26403928e-01
-1.09800637e+00 -2.03595050e-02 -8.67704928e-01 2.22376138e-01
9.68924403e-01 -3.36629927e-01 -6.78435981e-01 -5.39425135e-01
-8.57177854e-01 2.16170073e-01 2.38630876e-01 6.06563568e-01
6.30200565e-01 -9.21072006e-01 -6.64537966e-01 9.78082046e-02
-9.67036709e-02 -1.77548602e-01 1.70488909e-01 3.44715863e-01
-6.92857444e-01 6.15414798e-01 -7.13704944e-01 -3.58433008e-01
-5.38540006e-01 6.34933054e-01 4.67322558e-01 6.65119141e-02
-5.37191987e-01 1.08170140e+00 6.39434934e-01 -4.98737544e-01
-3.72144170e-02 -1.46519467e-01 -1.02130175e-01 -6.10888600e-01
9.04272377e-01 2.06559628e-01 -2.56381452e-01 1.59030795e-01
-2.85394102e-01 4.07267481e-01 -8.67829695e-02 -1.70699850e-01
1.76314235e+00 3.80686790e-01 -2.26337269e-01 3.59316766e-01
3.38379860e-01 -3.06534052e-01 -1.10688806e+00 -1.50071874e-01
1.71314210e-01 5.62632941e-02 -6.46135733e-02 -1.09711480e+00
-7.63902545e-01 1.31472194e+00 1.73045501e-01 3.57749611e-01
1.00224960e+00 1.56447768e-01 7.55578995e-01 8.42308700e-01
5.33219874e-01 -9.15097833e-01 6.23824954e-01 9.49721336e-01
7.99165845e-01 -1.02030718e+00 -1.66386515e-02 -1.84876062e-02
-2.79099524e-01 1.53737092e+00 8.48944783e-01 -5.01120389e-01
8.03895473e-01 2.29966119e-01 -3.04844379e-01 -4.96202379e-01
-1.02344930e+00 -2.82671750e-01 2.46880278e-01 9.65258479e-01
7.80680060e-01 -1.12561107e-01 9.72268730e-02 7.63533592e-01
-6.56391144e-01 4.05133545e-01 4.92732853e-01 7.32993782e-01
-1.14925003e+00 -8.40562046e-01 -2.62004197e-01 2.90908962e-01
3.92895862e-02 -2.21444473e-01 -6.09495044e-01 7.49778628e-01
5.07215619e-01 9.58548963e-01 -6.00339239e-03 -5.90051591e-01
2.89491232e-04 2.30356947e-01 1.02221680e+00 -6.94822192e-01
-4.71472561e-01 -8.18556130e-01 -2.19528407e-01 -3.25678647e-01
-2.44440153e-01 -3.74064714e-01 -1.50593674e+00 -6.15391195e-01
8.54089409e-02 8.53103399e-02 5.36944807e-01 1.40599716e+00
2.57634014e-01 7.95917451e-01 -4.11914401e-02 -9.97760832e-01
-1.98729545e-01 -6.22693181e-01 -1.72238186e-01 -7.68070221e-02
1.00965895e-01 -5.70192277e-01 -7.51851127e-02 2.41490915e-01] | [9.117765426635742, 6.516641139984131] |
cd7c7e2b-e4a0-4d1e-9555-ead70c553a08 | segmentation-based-vs-regression-based | null | null | https://www.mdpi.com/2313-433X/8/2/23 | https://doi.org/10.3390/jimaging8020023 | Segmentation-Based vs. Regression-Based Biomarker Estimation: A Case Study of Fetus Head Circumference Assessment from Ultrasound Images | The fetus head circumference (HC) is a key biometric to monitor fetus growth during pregnancy, which is estimated from ultrasound (US) images. The standard approach to automatically measure the HC is to use a segmentation network to segment the skull, and then estimate the head contour length from the segmentation map via ellipse fitting, usually after post-processing. In this application, segmentation is just an intermediate step to the estimation of a parameter of interest. Another possibility is to estimate directly the HC with a regression network. Even if this type of segmentation-free approaches have been boosted with deep learning, it is not yet clear how well direct approach can compare to segmentation approaches, which are expected to be still more accurate. This observation motivates the present study, where we propose a fair, quantitative comparison of segmentation-based and segmentation-free (i.e., regression) approaches to estimate how far regression-based approaches stand from segmentation approaches. We experiment various convolutional neural networks (CNN) architectures and backbones for both segmentation and regression models and provide estimation results on the HC18 dataset, as well agreement analysis, to support our findings. We also investigate memory usage and computational efficiency to compare both types of approaches. The experimental results demonstrate that even if segmentation-based approaches deliver the most accurate results, regression CNN approaches are actually learning to find prominent features, leading to promising yet improvable HC estimation results. | ['Jing; Caroline Petitjean; and Samia Ainouz', 'Zhang'] | 2022-01-25 | null | null | null | journal-of-imaging-2022-1 | ['2d-semantic-segmentation'] | ['computer-vision'] | [ 2.56942902e-02 6.70226514e-01 8.31242949e-02 -5.95333576e-01
-3.39604169e-01 -4.41134989e-01 3.28382403e-01 4.67810243e-01
-5.14652014e-01 4.67912436e-01 -3.54800195e-01 -4.67085481e-01
-9.58013833e-02 -1.02253735e+00 -7.56376207e-01 -7.13847935e-01
-2.47933954e-01 8.66877496e-01 1.43591911e-01 -2.63661202e-02
8.14226642e-02 8.96489918e-01 -1.35976756e+00 -2.32109264e-01
8.48887265e-01 1.09973526e+00 -3.36936295e-01 7.40292907e-01
-2.56185502e-01 1.86671391e-01 -3.58357847e-01 -5.77359796e-01
8.48749429e-02 -3.73154283e-01 -7.31194437e-01 -2.19878837e-01
3.60887140e-01 -3.15032154e-01 3.61821145e-01 8.33125889e-01
5.61212480e-01 -2.83501506e-01 7.50178814e-01 -7.28272140e-01
2.57596839e-02 7.82881320e-01 -6.53985679e-01 3.63426507e-02
1.93326801e-01 -3.30535650e-01 4.63754117e-01 -6.85033202e-01
5.48683584e-01 8.50334406e-01 1.02156281e+00 3.86789620e-01
-9.25338924e-01 -5.34486294e-01 -5.10531723e-01 -2.11128935e-01
-1.46856332e+00 -4.03098613e-01 6.16653919e-01 -5.34733295e-01
3.26231658e-01 3.61770511e-01 9.63710785e-01 5.04982352e-01
-2.31251493e-02 6.26449466e-01 1.10615361e+00 -5.88512838e-01
1.53700739e-01 2.14928493e-01 1.20989680e-01 9.54431713e-01
5.12010157e-01 2.34229751e-02 8.89648050e-02 8.88747647e-02
8.81154478e-01 -3.64674032e-01 -2.31461331e-01 -3.53112459e-01
-6.31507456e-01 9.01509345e-01 1.93111762e-01 7.68408537e-01
-4.07824576e-01 -4.48410196e-04 3.71415764e-01 -7.05955410e-03
4.56894904e-01 4.88432109e-01 -4.57488954e-01 -1.38973773e-01
-1.65643287e+00 3.10781449e-01 1.06503069e+00 8.25494051e-01
7.98403621e-01 -8.28650519e-02 -1.25763491e-01 6.65305793e-01
2.76556492e-01 4.08294469e-01 2.90615141e-01 -8.74746919e-01
1.18740082e-01 5.22601247e-01 -1.34910256e-01 -1.04549873e+00
-1.16418517e+00 -4.28196251e-01 -9.26408768e-01 2.18886793e-01
1.01623785e+00 -4.23084676e-01 -8.51419210e-01 1.37361026e+00
3.11700016e-01 7.33048022e-02 -3.15643102e-01 7.48237848e-01
1.11180341e+00 1.34783164e-01 -1.99496746e-01 -5.18210173e-01
1.29281497e+00 -6.23626947e-01 -6.35643005e-01 3.12437326e-01
6.02462828e-01 -6.16319895e-01 4.42966759e-01 6.46536708e-01
-1.34211123e+00 -3.12560350e-01 -1.01882017e+00 1.58966035e-01
-4.05997425e-01 3.01116884e-01 6.31184518e-01 1.24497163e+00
-1.09444547e+00 9.89111185e-01 -1.29387951e+00 -3.71785760e-01
4.52870965e-01 4.24382180e-01 -3.20201844e-01 4.00497884e-01
-9.53560591e-01 1.01951051e+00 3.86648715e-01 2.97716796e-01
-2.78098345e-01 -6.29836142e-01 -8.18185151e-01 2.15401590e-01
1.36628404e-01 -1.97622061e-01 1.17929709e+00 -8.54542136e-01
-1.55208635e+00 1.00011289e+00 -5.36312312e-02 -7.11815000e-01
7.52062678e-01 9.64933485e-02 3.21430005e-02 4.01468992e-01
-4.28977668e-01 6.15189195e-01 7.15931833e-01 -1.10399914e+00
-4.17469025e-01 -3.35355073e-01 -1.29507288e-01 -3.97332698e-01
-1.50451988e-01 2.58048326e-01 -5.28640151e-01 -1.34167328e-01
5.23583770e-01 -8.15096259e-01 -2.53456414e-01 6.65054843e-02
-2.28772819e-01 -1.52555361e-01 3.54918033e-01 -9.59652483e-01
1.17408657e+00 -1.50233710e+00 -2.32691020e-01 5.54106593e-01
5.53005457e-01 4.94930774e-01 3.12825710e-01 5.39214090e-02
-1.38425872e-01 1.72275558e-01 -4.03869629e-01 -4.64225084e-01
-1.82072163e-01 1.41448909e-02 3.85664910e-01 7.71209478e-01
1.56191424e-01 1.01497102e+00 -5.73618531e-01 -7.85452783e-01
2.95321107e-01 5.80029011e-01 -4.44383115e-01 8.77933577e-02
8.56258795e-02 5.55467546e-01 -3.87517214e-01 6.27535284e-01
1.04509020e+00 9.17046219e-02 2.48535618e-01 -2.66019702e-01
-3.66125464e-01 -1.94884554e-01 -9.91661727e-01 1.46345603e+00
-3.41310233e-01 7.69532979e-01 8.84468779e-02 -1.59585345e+00
1.14015019e+00 5.20646214e-01 7.35593319e-01 -5.46999812e-01
5.31687319e-01 5.27310014e-01 2.39666656e-01 -6.06953621e-01
1.76568553e-01 -1.43451527e-01 3.13433379e-01 2.25186706e-01
1.38419539e-01 -1.83772862e-01 4.12436545e-01 -3.54293734e-01
7.21453905e-01 3.76335770e-01 6.43679798e-01 -5.68871021e-01
6.64620697e-01 -3.28436404e-01 2.77012408e-01 5.50945938e-01
3.14606540e-03 1.03825748e+00 9.21051145e-01 -6.86536372e-01
-8.68795455e-01 -5.32288790e-01 -6.79513693e-01 5.23392618e-01
-8.89215469e-02 -5.53588197e-02 -1.34114027e+00 -6.35609269e-01
-8.44830573e-02 2.65603185e-01 -8.90220642e-01 4.56705779e-01
-8.32945287e-01 -9.11018670e-01 9.13205862e-01 4.67609435e-01
2.57482111e-01 -9.06908989e-01 -1.01554167e+00 2.41778120e-01
1.62915260e-01 -9.72396135e-01 2.97427237e-01 1.38533548e-01
-9.07256544e-01 -1.17427278e+00 -1.10702002e+00 -3.52996916e-01
6.74325347e-01 -5.43347299e-01 1.07062054e+00 6.58766210e-01
-2.58575588e-01 3.20276283e-02 -4.14633453e-01 -6.61908567e-01
-6.73687160e-01 2.73983002e-01 -1.84574530e-01 -1.09867506e-01
1.96439102e-01 -7.40171909e-01 -8.54531467e-01 4.68584336e-02
-6.74476147e-01 -1.55299321e-01 5.54978371e-01 3.38519454e-01
3.15360248e-01 -4.92380917e-01 3.69710356e-01 -1.10813642e+00
1.50057107e-01 -3.85186315e-01 -9.76168931e-01 3.00518036e-01
-9.31147993e-01 -6.45121038e-02 6.25687480e-01 -1.40037864e-01
-6.32332444e-01 5.89433052e-02 -7.52195954e-01 -3.46049845e-01
-5.69714427e-01 6.16738677e-01 2.35215023e-01 -2.91788787e-01
5.50703585e-01 7.84309283e-02 2.40710795e-01 -4.70915437e-01
2.36456636e-02 5.36552429e-01 3.71944517e-01 -5.46455860e-01
5.60748875e-01 4.47775692e-01 3.52882713e-01 -9.79503036e-01
-4.32535410e-01 -3.41056973e-01 -9.02295649e-01 -3.47703606e-01
1.03518558e+00 -2.56159037e-01 -8.27056348e-01 2.10430562e-01
-1.42345953e+00 -1.97204143e-01 -7.85152912e-02 4.54708993e-01
-5.49760282e-01 4.61250931e-01 -5.58268487e-01 -9.38812137e-01
-4.54715997e-01 -1.32907093e+00 9.02702451e-01 3.92142236e-01
-5.57741299e-02 -1.17765903e+00 -5.50258718e-02 1.01255305e-01
5.75078368e-01 7.75460482e-01 6.30620241e-01 -9.15266454e-01
-2.41826549e-01 -5.16094804e-01 -3.89181286e-01 1.66091979e-01
-1.94960192e-01 4.81755525e-01 -1.15394413e+00 -2.44006470e-01
-6.56467527e-02 1.93880007e-01 5.44229031e-01 7.83734560e-01
1.27145803e+00 3.76930907e-02 -3.53768438e-01 8.94253671e-01
1.44612741e+00 1.82920411e-01 7.22314775e-01 1.02405131e-01
4.17734504e-01 7.81455994e-01 5.80845356e-01 4.20675099e-01
4.11308289e-01 5.67228615e-01 3.75184953e-01 -4.82154220e-01
-1.09471314e-01 1.99372366e-01 -4.02444363e-01 8.27170908e-01
-8.03655326e-01 -5.87097518e-02 -1.30040169e+00 2.68959671e-01
-1.42909706e+00 -5.86826622e-01 -4.81908709e-01 2.22467780e+00
6.78848565e-01 1.70187443e-01 3.04691076e-01 2.78693587e-01
4.81205404e-01 -2.49707803e-01 2.63486505e-02 -7.29851782e-01
2.37003118e-01 5.63651204e-01 5.01809120e-01 2.02971518e-01
-1.02385318e+00 5.22367477e-01 6.43515873e+00 7.04951286e-01
-1.55600381e+00 1.33419573e-01 8.97716165e-01 4.01978314e-01
3.04958038e-02 -9.70429629e-02 -6.29905105e-01 4.79334652e-01
1.01732540e+00 2.43082389e-01 5.90917841e-02 6.43599331e-01
1.76624343e-01 -3.53971332e-01 -1.14958930e+00 6.24421716e-01
-7.02739656e-02 -1.45750928e+00 -5.30031443e-01 2.36322768e-02
5.20812750e-01 -1.59465805e-01 -4.24852282e-01 6.93526790e-02
-4.15881604e-01 -1.23885512e+00 5.90555549e-01 8.02072883e-01
9.76645231e-01 -6.70170784e-01 1.16439509e+00 4.49142337e-01
-1.13462329e+00 3.12147021e-01 -3.40862483e-01 9.88639444e-02
-2.22283024e-02 6.68753505e-01 -9.82077599e-01 5.57188809e-01
7.24347949e-01 1.47010192e-01 -5.29676795e-01 1.27923751e+00
-4.84738350e-02 8.51636529e-01 -5.03615439e-01 -5.95223382e-02
1.76651441e-02 -4.57579970e-01 3.52277100e-01 1.62130892e+00
5.15021682e-01 7.74468780e-02 -3.91747624e-01 1.14254355e+00
1.76453784e-01 6.10462964e-01 -3.39824677e-01 1.79519877e-01
1.94243118e-01 1.51635587e+00 -1.37932682e+00 -1.86691120e-01
-5.29995799e-01 3.03500533e-01 2.63487071e-01 1.83059797e-02
-7.86392331e-01 -3.72942984e-01 -4.51094471e-02 4.03392494e-01
1.63403258e-01 -2.68316716e-02 -4.46031094e-01 -6.34889245e-01
-6.13196567e-02 -3.80161732e-01 8.91936645e-02 -3.15957665e-01
-4.72159654e-01 4.71846163e-01 1.99850306e-01 -1.12574279e+00
-4.40633863e-01 -6.25678658e-01 -7.25862741e-01 6.31852150e-01
-1.66623068e+00 -1.06762171e+00 -3.67716283e-01 -1.61763847e-01
2.84828812e-01 1.01281285e-01 8.13522756e-01 5.07732928e-01
-4.49494213e-01 8.55708420e-01 -1.62869081e-01 3.32654506e-01
2.05453724e-01 -1.51892769e+00 4.05303985e-02 7.40378618e-01
-6.27285019e-02 6.85436726e-01 8.37328374e-01 -3.71521533e-01
-1.02218449e+00 -6.01207495e-01 7.11178660e-01 -1.63378790e-01
2.39911139e-01 -1.18133955e-01 -1.01624334e+00 4.07914937e-01
6.57460466e-02 3.76816243e-01 4.68753904e-01 -4.23320606e-02
2.44001582e-01 -2.75037941e-02 -1.16241777e+00 1.30162686e-01
5.88596761e-01 3.31563264e-01 -2.91135401e-01 -1.05454877e-01
3.58096540e-01 -8.94963861e-01 -1.33416700e+00 8.04814041e-01
9.92821217e-01 -1.51193607e+00 7.08958089e-01 -1.39580831e-01
6.43798709e-01 1.35184377e-01 4.56438661e-01 -8.97574604e-01
2.94182926e-01 -5.38438022e-01 -1.38972148e-01 1.18874133e+00
6.81237757e-01 -6.40697956e-01 1.10619247e+00 6.79063499e-01
-9.92238596e-02 -1.14588857e+00 -9.14715230e-01 -4.53412980e-01
4.98896927e-01 -6.08737528e-01 8.67050648e-01 9.78561699e-01
-1.88021958e-01 -3.08405519e-01 1.12758458e-01 8.60138312e-02
4.38788086e-01 2.64868200e-01 6.71376824e-01 -1.42402208e+00
4.43718582e-02 -8.86278510e-01 -5.32902360e-01 -6.00224555e-01
-3.06468289e-02 -6.62166476e-01 3.67249250e-02 -1.31778085e+00
-6.31551817e-02 -7.15637088e-01 -5.74039705e-02 2.65567839e-01
1.12173468e-01 4.52367842e-01 -6.50552809e-02 -2.45221823e-01
-1.71704173e-01 -2.06302136e-01 1.26795018e+00 3.93110186e-01
-1.56697780e-01 5.79336882e-01 -2.61714607e-01 1.11747813e+00
7.38699496e-01 -3.41452748e-01 -5.08464947e-02 -7.28776455e-02
2.19805524e-01 6.53157115e-01 -3.59012485e-02 -9.75135684e-01
2.60593414e-01 1.02229595e-01 5.15831590e-01 -6.68362677e-01
3.94442603e-02 -7.76713312e-01 -1.70742109e-01 4.65073764e-01
-1.79532692e-01 -3.38320047e-01 1.21428058e-01 -2.03291431e-01
-1.58757865e-01 -7.62908161e-01 9.79800701e-01 -2.31360272e-02
-4.95608896e-02 3.98378193e-01 -2.82819480e-01 -1.74720064e-01
6.61675155e-01 -5.68718553e-01 2.61915237e-01 -3.54392827e-01
-1.01415610e+00 -2.37742811e-02 1.68603346e-01 -1.34095982e-01
5.63924968e-01 -7.41408050e-01 -9.29600596e-01 2.67946929e-01
-2.00988010e-01 2.48490736e-01 -1.01715662e-01 1.49509859e+00
-1.25740743e+00 4.47175324e-01 -1.11613739e-02 -8.70255053e-01
-1.36038065e+00 3.92375559e-01 6.21294200e-01 -2.23460928e-01
-5.07868469e-01 8.09536457e-01 -2.26246104e-01 -5.85417807e-01
2.79685289e-01 -6.33457065e-01 -7.36206055e-01 2.52094209e-01
2.60885477e-01 6.41711354e-01 4.69916999e-01 -5.56153655e-01
-1.77172780e-01 9.13872659e-01 3.98323834e-01 2.18145013e-01
1.26137412e+00 -7.74876103e-02 -4.39932883e-01 9.97588262e-02
1.21031427e+00 -3.45170707e-03 -7.61288166e-01 9.07719061e-02
3.36870134e-01 -1.09926663e-01 -7.53130615e-02 -4.54945356e-01
-1.52856207e+00 1.25894904e+00 6.60504460e-01 7.39075720e-01
1.09789610e+00 -7.02153891e-02 5.56402922e-01 1.44033194e-01
1.57241896e-01 -9.22038138e-01 -5.52260995e-01 2.40802974e-03
8.58821094e-01 -1.33005404e+00 2.63373911e-01 -6.45086229e-01
-4.63512130e-02 1.74955630e+00 5.18973470e-01 -1.46640852e-01
8.79285038e-01 6.37054145e-01 6.93156198e-02 -2.65316606e-01
-4.91132885e-02 -3.28959495e-01 5.43429136e-01 3.79038692e-01
8.59738767e-01 1.51027456e-01 -8.13384235e-01 6.86206043e-01
-4.86143619e-01 8.93235207e-03 4.48574513e-01 6.02934480e-01
-4.40788299e-01 -1.00362754e+00 -4.47633654e-01 5.65580726e-01
-9.22264457e-01 8.78892019e-02 3.64989005e-02 1.13975441e+00
4.83028114e-01 5.86525500e-01 7.48731494e-02 3.20529453e-02
2.14136958e-01 -3.58017012e-02 6.71634853e-01 -3.69945288e-01
-5.51769078e-01 3.00599575e-01 6.56899661e-02 -5.71386039e-01
-4.46778297e-01 -8.15900564e-01 -1.43805647e+00 -1.10628493e-02
-6.36493802e-01 1.22404389e-01 1.07760394e+00 1.12656891e+00
-4.65942711e-01 3.99268001e-01 6.02583528e-01 -9.66395020e-01
-1.56703904e-01 -8.89502287e-01 -6.25572324e-01 8.70092362e-02
3.31373811e-01 -5.40887952e-01 -2.25513041e-01 -1.07615091e-01] | [14.243382453918457, -2.4404587745666504] |
570e0285-c956-4887-902f-6ddd4c1391db | improving-signer-independent-sign-language | null | null | https://aclanthology.org/2022.sltat-1.7 | https://aclanthology.org/2022.sltat-1.7.pdf | Improving Signer Independent Sign Language Recognition for Low Resource Languages | The reliance of deep learning algorithms on large scale datasets represents a significant challenge when learning from low resource sign language datasets. This challenge is compounded when we consider that, for a model to be effective in the real world, it must not only learn the variations of a given sign, but also learn to be invariant to the person signing. In this paper, we first illustrate the performance gap between signer-independent and signer-dependent models on Irish Sign Language manual hand shape data. We then evaluate the effect of transfer learning, with different levels of fine-tuning, on the generalisation of signer independent models, and show the effects of different input representations, namely variations in image data and pose estimation. We go on to investigate the sensitivity of current pose estimation models in order to establish their limitations and areas in need of improvement. The results show that accurate pose estimation outperforms raw RGB image data, even when relying on pre-trained image models. Following on from this, we investigate image texture as a potential contributing factor to the gap in performance between signer-dependent and signer-independent models using counterfactual testing images and discuss potential ramifications for low-resource sign languages. Keywords: Sign language recognition, Transfer learning, Irish Sign Language, Low-resource languages | ['Anthony Ventresque', 'Frank Fowley', 'Ellen Rushe', 'Ruth Holmes'] | null | null | null | null | sltat-lrec-2022-6 | ['sign-language-recognition'] | ['computer-vision'] | [ 2.96830416e-01 -2.40811810e-01 8.42435062e-02 -5.22837937e-01
-8.45212102e-01 -7.24636674e-01 6.41883910e-01 -1.00152791e+00
-8.40802848e-01 6.62706852e-01 5.68671882e-01 -2.15968922e-01
-2.22563282e-01 -3.06189775e-01 -8.33112836e-01 -6.62411928e-01
2.14112755e-02 6.12896323e-01 1.30223945e-01 -2.47307301e-01
2.03846946e-01 7.28057921e-01 -1.76102257e+00 3.46698225e-01
3.17052633e-01 6.05875552e-01 -7.61044174e-02 8.76658261e-01
2.16572762e-01 5.76444268e-01 -7.08635926e-01 -1.59801304e-01
5.50775349e-01 -4.89449918e-01 -6.09357774e-01 3.58968861e-02
1.02918124e+00 -6.87821507e-01 -3.17004800e-01 4.86486048e-01
1.17017829e+00 -1.70188755e-01 9.08555150e-01 -1.20615983e+00
-4.53520000e-01 1.44027203e-01 -1.61276802e-01 -1.30414039e-01
2.49434561e-01 8.81610036e-01 7.41962254e-01 -5.29695868e-01
1.18625343e+00 1.32571828e+00 9.08301294e-01 7.01786041e-01
-9.79606509e-01 -9.23672020e-01 1.48191914e-01 2.86281377e-01
-1.11031973e+00 -4.72907811e-01 6.08491242e-01 -5.89070022e-01
9.58898902e-01 2.19945051e-02 8.40581238e-01 1.29421175e+00
-1.12152547e-01 7.95602202e-01 1.68568385e+00 -6.02146387e-01
-1.05776764e-01 -1.25221059e-01 -3.21312100e-01 4.68402892e-01
3.70150536e-01 6.22966349e-01 -6.96320713e-01 5.99093772e-02
9.33982790e-01 -6.64166987e-01 -3.42044204e-01 -6.60676718e-01
-9.67298508e-01 5.10217845e-01 4.11870271e-01 3.27997833e-01
-2.69405991e-01 2.65481710e-01 3.05574745e-01 3.57248396e-01
-6.62001446e-02 3.18606198e-01 -8.17143857e-01 -3.86885196e-01
-8.02037597e-01 3.59578192e-01 6.84397399e-01 6.65369332e-01
2.63829529e-01 6.88416064e-02 -8.48926604e-02 5.73748112e-01
5.13835311e-01 8.27876627e-01 5.75284362e-01 -5.73308229e-01
4.86768186e-01 4.18386459e-01 3.50039825e-02 -4.41153556e-01
-5.95967233e-01 -1.72390446e-01 -1.67861760e-01 9.69705641e-01
1.11926627e+00 -2.75391787e-01 -1.55390334e+00 1.71095383e+00
-7.59482384e-02 -1.39079481e-01 -4.74574566e-02 1.23835325e+00
6.02581859e-01 -5.14189526e-02 2.81248719e-01 3.46025109e-01
1.04479825e+00 -3.33251119e-01 -8.76972750e-02 -2.74177611e-01
6.55580997e-01 -8.46706092e-01 1.34590220e+00 5.25130749e-01
-7.06583440e-01 -2.61054635e-01 -8.28773916e-01 2.09697876e-02
-3.75502288e-01 3.20614368e-01 6.49821341e-01 1.03376687e+00
-8.35419714e-01 4.20607686e-01 -8.48248303e-01 -7.94573307e-01
5.25808752e-01 5.60599506e-01 -5.92278719e-01 -1.37735233e-01
-7.46454835e-01 1.29063320e+00 2.38774642e-01 3.14313650e-01
-5.24864852e-01 -5.95554173e-01 -6.66990995e-01 -5.61747849e-01
-1.13344900e-01 -5.09181917e-01 1.05456185e+00 -1.32919860e+00
-1.60200012e+00 1.23892927e+00 1.01399422e-03 -1.43613487e-01
1.19411874e+00 -1.16217382e-01 -2.47798756e-01 -1.45919338e-01
-2.87352800e-01 5.94937086e-01 8.34153354e-01 -1.46734285e+00
-6.13532126e-01 -5.24363041e-01 -2.02884063e-01 1.24241672e-01
3.15872192e-01 2.45817542e-01 -2.20587701e-01 -4.61173832e-01
1.39254304e-02 -1.29963410e+00 1.20491661e-01 2.01914683e-01
1.34524003e-01 -1.69293641e-03 9.13681209e-01 -1.00094664e+00
4.69026417e-01 -1.92259610e+00 -3.49752679e-02 5.09441674e-01
-3.90302122e-01 5.75398624e-01 -4.14517581e-01 1.64812490e-01
1.31554361e-02 -2.06419095e-01 -2.22652137e-01 1.92704022e-01
3.23798805e-02 4.08273697e-01 -1.79816365e-01 7.63256073e-01
3.10182244e-01 1.16135240e+00 -6.51315987e-01 -2.82141745e-01
3.61566365e-01 8.06463420e-01 -4.52484369e-01 -2.16036454e-01
-1.65096074e-02 9.16671991e-01 1.71945395e-03 7.81863451e-01
4.85106140e-01 2.33166918e-01 1.27965540e-01 -2.55094528e-01
-8.36088881e-02 6.27734289e-02 -1.20016801e+00 1.31157577e+00
-6.59804761e-01 1.00052834e+00 1.61188945e-01 -6.56415820e-01
6.79814041e-01 2.26586267e-01 3.09861779e-01 -7.94527769e-01
3.33384037e-01 8.38283718e-01 6.53066695e-01 -5.73048890e-01
-4.44019660e-02 -5.22487402e-01 1.95433468e-01 5.15811801e-01
7.81142637e-02 -3.43596816e-01 -3.15631256e-02 -4.79028404e-01
7.62543559e-01 7.31643438e-01 -1.42553849e-02 1.50681930e-02
2.48300835e-01 2.30559111e-02 1.65290207e-01 5.32543600e-01
-4.55984712e-01 7.95565009e-01 2.35747024e-01 -3.78859758e-01
-9.78825212e-01 -9.53451574e-01 -2.56942153e-01 9.67652917e-01
-3.38683665e-01 3.63845557e-01 -3.36613923e-01 -6.91473663e-01
3.49282771e-01 5.88315010e-01 -6.56390965e-01 1.68390889e-02
-9.16023731e-01 -6.96638882e-01 9.89098728e-01 8.76970768e-01
4.22445029e-01 -1.24616289e+00 -1.23529994e+00 -8.37024674e-02
1.65807739e-01 -8.19241405e-01 -5.58372997e-02 -1.53028388e-02
-6.80010498e-01 -1.29515827e+00 -1.28073883e+00 -6.85312629e-01
7.32808650e-01 -3.78951997e-01 7.07666159e-01 -1.60439406e-02
-4.52129096e-01 9.86451268e-01 -4.24450666e-01 -6.66282058e-01
-5.25620282e-01 -2.37713188e-01 3.54852192e-02 -1.62891090e-01
5.11027753e-01 -3.69698793e-01 -5.62238872e-01 5.19282401e-01
-7.76428819e-01 -2.86265671e-01 1.00943685e+00 1.02546418e+00
2.12243453e-01 -6.61975920e-01 6.22356758e-02 -3.62993807e-01
4.91118968e-01 3.03994089e-01 -5.18377960e-01 4.14922118e-01
-4.73498404e-01 3.50046188e-01 1.24221005e-01 -6.39856160e-01
-1.13370228e+00 3.90171021e-01 -1.86788086e-02 -9.08066183e-02
-2.88577646e-01 1.70792520e-01 -2.10062668e-01 -5.41615307e-01
9.28042471e-01 2.20171556e-01 2.98860013e-01 -4.05643433e-01
5.04601777e-01 7.91256368e-01 5.17684817e-01 -6.27004445e-01
8.52671325e-01 8.18229377e-01 8.70166272e-02 -9.16144967e-01
-1.99399203e-01 -3.41254592e-01 -1.16246474e+00 -4.92490977e-01
6.21323943e-01 -6.79757893e-01 -5.64728022e-01 9.20744061e-01
-9.08568919e-01 -8.50309610e-01 -4.52213585e-01 8.12747538e-01
-7.98359692e-01 2.01164797e-01 6.35551661e-03 -6.58287287e-01
1.45382956e-01 -1.07187736e+00 1.09094739e+00 -9.08784196e-02
-3.55444908e-01 -7.16381550e-01 2.66691267e-01 4.19420958e-01
5.10235429e-01 4.24260527e-01 6.65473759e-01 -4.29989815e-01
-5.28204024e-01 -5.36000550e-01 -3.24329466e-01 5.87719142e-01
2.04627246e-01 -1.21742174e-01 -1.13325751e+00 -4.36855644e-01
-5.95278144e-01 -7.59050310e-01 8.72948945e-01 4.58532244e-01
3.75620127e-01 -6.06175028e-02 3.83490436e-02 6.08920932e-01
1.26417673e+00 -1.24773413e-01 6.34866178e-01 5.63994467e-01
6.85348392e-01 7.57374585e-01 3.03353697e-01 8.09928551e-02
2.64695108e-01 7.39684761e-01 -3.31585482e-02 -1.20677844e-01
-7.51676202e-01 -4.36031938e-01 3.71607184e-01 3.49950582e-01
-8.66221130e-01 1.85382128e-01 -1.14070547e+00 4.79824632e-01
-1.50231946e+00 -8.64749432e-01 6.53067557e-03 2.36917996e+00
4.40694988e-01 -2.21000880e-01 4.73091245e-01 2.70815581e-01
1.98691025e-01 -1.40292302e-01 -6.73978508e-01 -3.33696246e-01
-4.75027800e-01 4.12959635e-01 1.06535137e+00 4.96379524e-01
-9.10003185e-01 1.04258466e+00 6.67218733e+00 1.37448415e-01
-1.63035822e+00 -4.92463447e-02 6.48492947e-02 -2.03232363e-01
1.86110567e-02 3.77422571e-03 -4.84680474e-01 1.09129995e-01
6.12759113e-01 1.20748334e-01 2.79051125e-01 5.98826468e-01
2.87865043e-01 -9.68452394e-02 -1.16265261e+00 8.95250380e-01
4.28721160e-01 -6.93943322e-01 3.54421586e-02 2.54712522e-01
7.09092259e-01 3.34419966e-01 4.61696871e-02 3.25547993e-01
3.46084923e-01 -1.13243937e+00 8.88373792e-01 3.88180405e-01
1.08309484e+00 -1.77008659e-01 8.36933076e-01 3.03535368e-02
-9.38939393e-01 -5.45017272e-02 1.24491639e-01 -2.99564630e-01
2.92641371e-01 -5.39834499e-01 -8.75892937e-01 3.17988843e-02
4.66256261e-01 2.66424090e-01 -6.47294104e-01 1.09592807e+00
-5.06169260e-01 6.10812306e-01 -6.50091231e-01 -1.28715679e-01
1.54180795e-01 1.34838060e-01 3.55513871e-01 1.34255826e+00
1.76227286e-01 -8.58250335e-02 -2.74732590e-01 3.98624808e-01
4.22928572e-01 1.85690731e-01 -5.65759242e-01 1.34276137e-01
-5.05885184e-02 4.53970134e-01 -6.49424374e-01 -3.02775297e-02
-3.49740297e-01 1.17538834e+00 -1.64185464e-02 6.31426871e-01
-4.34084207e-01 -7.63114393e-02 5.55240631e-01 3.44931185e-01
4.60585296e-01 -4.48699832e-01 -3.88351262e-01 -1.01571012e+00
3.73177081e-01 -1.07121217e+00 3.32423300e-01 -7.06069112e-01
-1.14487076e+00 1.30538726e-02 7.30941966e-02 -1.33133030e+00
-6.34581923e-01 -1.32456291e+00 -4.04567391e-01 1.02315712e+00
-1.57367182e+00 -1.85056365e+00 -2.87015587e-01 6.64128602e-01
1.05311029e-01 -9.39982608e-02 7.75357842e-01 1.26746163e-01
2.23276228e-01 8.23779941e-01 4.96730357e-02 4.31792617e-01
8.37016046e-01 -9.00569379e-01 3.32570881e-01 6.31218493e-01
4.14538503e-01 5.15126646e-01 5.61391771e-01 -6.36053205e-01
-1.39200032e+00 -5.08153677e-01 7.31583595e-01 -8.92381728e-01
3.92529100e-01 -1.43611684e-01 -3.67029071e-01 6.81843340e-01
-4.61594343e-01 6.50885031e-02 4.87716705e-01 7.27087185e-02
-6.86363161e-01 1.89421460e-01 -1.28003550e+00 5.83534300e-01
1.43469501e+00 -5.95519304e-01 -7.51649857e-01 2.36259818e-01
-3.27864826e-01 -5.67264557e-01 -5.17598629e-01 4.36647803e-01
1.46602643e+00 -9.88795340e-01 9.56701577e-01 -8.97182703e-01
1.37532473e-01 -2.02137947e-01 -1.82254016e-01 -1.07080221e+00
-2.59722676e-03 -1.72795594e-01 4.10837471e-01 8.52329075e-01
4.14025784e-01 -8.00765574e-01 1.01020491e+00 9.10003364e-01
4.19582844e-01 -3.22045624e-01 -1.38331497e+00 -1.29685771e+00
4.40221488e-01 -8.19793642e-01 3.04760963e-01 5.57512283e-01
-3.37678015e-01 -2.51688004e-01 -3.96681786e-01 1.65906791e-02
5.07692218e-01 -1.06904007e-01 1.24763548e+00 -1.16590822e+00
-3.89109910e-01 -7.02971041e-01 -9.53455985e-01 -6.62379265e-01
1.71653926e-01 -7.60810137e-01 1.56495690e-01 -1.62961066e+00
-2.68427640e-01 -3.05853069e-01 -1.15754254e-01 6.35263979e-01
1.82749927e-01 4.19662476e-01 6.46328688e-01 3.21276397e-01
1.57355815e-02 7.63836205e-02 1.19383037e+00 -4.30606268e-02
-3.55407000e-01 1.54607221e-01 -2.33271167e-01 8.64278734e-01
6.05367124e-01 -8.23773965e-02 -4.86808307e-02 -4.21801776e-01
-6.16969801e-02 -7.31219113e-01 8.49878252e-01 -9.54288363e-01
-2.56433412e-02 -1.11969130e-03 5.45125782e-01 -2.04213366e-01
2.55337030e-01 -9.97908115e-01 -1.29833102e-01 8.45108330e-01
-1.35203421e-01 -3.65407318e-01 4.73988771e-01 1.57269090e-01
1.14060596e-01 9.01044384e-02 7.92436421e-01 -2.15351894e-01
-1.09273887e+00 -6.62839115e-02 -2.59828508e-01 1.92367017e-01
7.09985018e-01 -6.97439253e-01 1.10615656e-01 -5.09929538e-01
-5.55102408e-01 -1.37803942e-01 6.03779614e-01 7.17436910e-01
3.61168891e-01 -1.16899395e+00 -8.96954656e-01 4.46394444e-01
4.19731021e-01 -4.19291764e-01 8.88642892e-02 6.50376022e-01
-7.81882107e-01 6.19214833e-01 -5.33021271e-01 -5.20929754e-01
-1.55814493e+00 -1.22652136e-01 4.51869696e-01 9.64012668e-02
-6.54788017e-01 8.71450007e-01 -3.17800194e-01 -7.21196473e-01
3.99628431e-01 -5.93900621e-01 3.34488451e-01 -1.21719673e-01
2.55061179e-01 3.01469266e-01 -9.68825296e-02 -1.19528270e+00
-5.36661565e-01 1.13585317e+00 3.80029261e-01 -6.27622902e-01
1.15721488e+00 4.28624630e-01 4.73597616e-01 3.60557795e-01
9.79586065e-01 -2.30347272e-02 -1.52324414e+00 -1.62464008e-02
8.97480361e-03 -6.17933333e-01 -1.58553421e-01 -1.36555135e+00
-7.98215032e-01 8.53663981e-01 1.14873910e+00 -9.27040637e-01
9.65203702e-01 1.36208221e-01 3.76518309e-01 3.74700397e-01
6.17551684e-01 -1.33605838e+00 -3.09279591e-01 3.14084470e-01
1.30288100e+00 -1.39125073e+00 1.25303611e-01 1.41544938e-01
-6.34691954e-01 1.05882668e+00 2.88428247e-01 -2.26419613e-01
5.40568888e-01 2.07235441e-01 8.71122539e-01 -1.54908523e-01
8.85445774e-02 -5.71585476e-01 5.61707854e-01 1.10357261e+00
5.36526024e-01 1.96907967e-01 -4.80053037e-01 1.34082884e-01
-5.78850865e-01 5.76799631e-01 7.14805424e-02 1.11568642e+00
7.38406181e-02 -1.34137738e+00 -6.90937042e-01 3.80046159e-01
6.28936365e-02 2.60083646e-01 -8.48229170e-01 1.44931567e+00
5.21550119e-01 3.27205837e-01 -5.10715581e-02 -2.88281530e-01
7.76681364e-01 4.26390201e-01 1.15668321e+00 -2.58529723e-01
-4.68917787e-01 -2.19588012e-01 1.35403141e-01 -4.10630107e-01
-5.65394342e-01 -1.04840469e+00 -9.87078071e-01 2.39131451e-01
-2.04777628e-01 -8.29932749e-01 9.70399141e-01 1.10855377e+00
5.13402447e-02 3.25079858e-02 -2.07961723e-01 -1.23900235e+00
-8.26900303e-01 -1.06132507e+00 -4.29890901e-01 7.20234752e-01
2.58806944e-01 -7.17777789e-01 -4.28717196e-01 8.33087191e-02] | [9.180654525756836, -6.498172760009766] |
47bbba2a-a83e-4fb0-ae54-9d2d8fb2ff25 | improving-safety-in-physical-human-robot | 2302.11933 | null | https://arxiv.org/abs/2302.11933v2 | https://arxiv.org/pdf/2302.11933v2.pdf | Improving safety in physical human-robot collaboration via deep metric learning | Direct physical interaction with robots is becoming increasingly important in flexible production scenarios, but robots without protective fences also pose a greater risk to the operator. In order to keep the risk potential low, relatively simple measures are prescribed for operation, such as stopping the robot if there is physical contact or if a safety distance is violated. Although human injuries can be largely avoided in this way, all such solutions have in common that real cooperation between humans and robots is hardly possible and therefore the advantages of working with such systems cannot develop its full potential. In human-robot collaboration scenarios, more sophisticated solutions are required that make it possible to adapt the robot's behavior to the operator and/or the current situation. Most importantly, during free robot movement, physical contact must be allowed for meaningful interaction and not recognized as a collision. However, here lies a key challenge for future systems: detecting human contact by using robot proprioception and machine learning algorithms. This work uses the Deep Metric Learning (DML) approach to distinguish between non-contact robot movement, intentional contact aimed at physical human-robot interaction, and collision situations. The achieved results are promising and show show that DML achieves 98.6\% accuracy, which is 4\% higher than the existing standards (i.e. a deep learning network trained without DML). It also indicates a promising generalization capability for easy portability to other robots (target robots) by detecting contact (distinguishing between contactless and intentional or accidental contact) without having to retrain the model with target robot data. | ['Hans Wernher van de Venn', 'Davide Scaramuzza', 'Ying Zaoshi', 'Grammatiki Zanni', 'Maryam Rezayati'] | 2023-02-23 | null | null | null | null | ['metric-learning', 'metric-learning'] | ['computer-vision', 'methodology'] | [ 1.32376328e-01 4.85386282e-01 -1.00052953e-01 -3.29561997e-03
9.62965041e-02 -2.67802179e-01 3.71235520e-01 -6.95496574e-02
-7.51775026e-01 7.15635061e-01 -4.23679978e-01 -1.09859928e-01
-6.80397630e-01 -7.87511528e-01 -6.29417181e-01 -7.59101748e-01
-3.27031732e-01 7.24673271e-01 3.65164846e-01 -5.63081741e-01
1.15446895e-01 9.78003860e-01 -1.56378138e+00 -9.30905715e-02
8.39257836e-01 9.77970243e-01 7.21044183e-01 2.42748946e-01
3.07155758e-01 5.04331172e-01 -6.59354687e-01 1.79364860e-01
5.48885643e-01 -1.99827567e-01 -1.00962198e+00 -9.52862501e-02
-1.44900680e-01 -4.85558629e-01 -1.88690022e-01 7.70546615e-01
3.21729034e-01 2.64362365e-01 8.23871732e-01 -1.51660526e+00
-4.40668017e-02 3.07650745e-01 -3.41377735e-01 -3.40850919e-01
5.93808889e-01 3.19821596e-01 3.12545687e-01 -4.34608072e-01
5.47626674e-01 1.11240041e+00 6.48216724e-01 4.87277776e-01
-9.70405877e-01 -5.01481056e-01 -2.76914120e-01 1.73703805e-01
-1.10440886e+00 7.29450211e-02 6.38024628e-01 -4.83936846e-01
1.02432072e+00 9.46098939e-02 4.78664875e-01 1.32599890e+00
9.05311882e-01 3.30848277e-01 6.03519559e-01 -3.74095172e-01
6.15652353e-02 1.17401823e-01 -3.03623497e-01 3.52026314e-01
4.82305765e-01 1.54511154e-01 -2.47686114e-02 1.68016210e-01
8.89948726e-01 7.56958798e-02 -4.69248593e-01 -7.89912760e-01
-1.39125097e+00 3.36666852e-01 7.44852006e-01 5.98861873e-01
-8.04498553e-01 -8.06586221e-02 5.85428655e-01 4.72487330e-01
-4.79196340e-01 8.88731837e-01 -4.64798957e-01 -2.02474907e-01
-2.11259276e-01 3.34085524e-01 9.39034760e-01 1.02669978e+00
3.57597649e-01 -1.53776392e-01 3.04861307e-01 7.34709620e-01
5.52820750e-02 3.39105308e-01 2.55890429e-01 -1.09974015e+00
4.96499002e-01 7.16733515e-01 5.46443343e-01 -1.18515038e+00
-9.47290659e-01 7.20000118e-02 -9.57030654e-01 1.13953578e+00
5.28077841e-01 -1.75788552e-01 -5.29432416e-01 1.33370137e+00
1.88484609e-01 -7.86113918e-01 2.79502928e-01 1.08683527e+00
2.29435652e-01 4.34725732e-01 -1.19139135e-01 5.74083440e-02
1.24191093e+00 -5.46582103e-01 -8.53766203e-01 -3.53522182e-01
7.15585768e-01 -5.49600601e-01 9.92256284e-01 1.03280354e+00
-7.09593177e-01 -7.41811633e-01 -1.42148864e+00 1.87028840e-01
-2.67177463e-01 1.15791246e-01 6.29257083e-01 2.47067615e-01
-4.65079665e-01 1.04842639e+00 -8.87326539e-01 -6.70514405e-01
-3.11286777e-01 9.67658997e-01 -8.90714407e-01 5.16495444e-02
-1.30882359e+00 1.69170833e+00 4.39983964e-01 5.45844257e-01
-5.72947502e-01 1.05012152e-02 -8.86927664e-01 -3.07964265e-01
3.88577223e-01 -2.47621849e-01 1.01160264e+00 -5.95369101e-01
-1.63543248e+00 5.46709180e-01 5.84960938e-01 -5.60761809e-01
8.00625324e-01 -6.99333072e-01 -2.80678153e-01 1.41925365e-01
-1.79652721e-01 5.65014541e-01 4.93449956e-01 -1.41260564e+00
-5.57640731e-01 -4.65615839e-02 3.82664323e-01 3.13555151e-01
-2.64036804e-01 -2.73554683e-01 1.16108701e-01 -1.87343538e-01
9.07256901e-02 -1.38064826e+00 -1.47134185e-01 4.32763606e-01
-4.05624151e-01 -4.41079855e-01 9.01099205e-01 -4.38855201e-01
4.33255404e-01 -2.16186213e+00 2.30259866e-01 2.31528118e-01
-2.03092545e-01 4.20723259e-01 9.05790702e-02 6.92346334e-01
3.69902328e-02 -4.05756414e-01 -2.85938025e-01 2.31163174e-01
-8.61543417e-02 3.79594475e-01 7.69887790e-02 5.69856405e-01
1.71814322e-01 2.92516619e-01 -8.39491844e-01 -2.35180542e-01
5.60437679e-01 2.98964173e-01 -1.80652723e-01 3.85584533e-01
2.61069894e-01 5.06378531e-01 -2.99664885e-01 3.78519684e-01
6.34521604e-01 4.94199216e-01 3.69120270e-01 -3.05703402e-01
-1.39996603e-01 5.90207390e-02 -1.32023156e+00 1.29458368e+00
-7.42804825e-01 4.31514889e-01 6.19147062e-01 -1.12594736e+00
1.28337753e+00 5.44992149e-01 7.71714330e-01 -6.96311951e-01
4.18532640e-01 4.27369624e-01 3.24281484e-01 -9.21695709e-01
3.41474414e-01 -3.51816346e-03 -2.61581033e-01 1.20028347e-01
-7.24717528e-02 -3.71356130e-01 -2.22877264e-01 -3.97672266e-01
1.20428276e+00 4.69964385e-01 1.59192950e-01 -3.94529134e-01
4.28723663e-01 2.02392682e-01 4.35032725e-01 4.88644928e-01
-2.81880856e-01 3.44213933e-01 1.65828213e-01 -3.46907109e-01
-6.62188888e-01 -1.17777646e+00 -8.35300088e-02 5.94087362e-01
7.63538778e-01 4.44212019e-01 -6.25536919e-01 -4.75462884e-01
1.00178905e-01 6.27764702e-01 -2.80935138e-01 -7.11791217e-01
-9.59386110e-01 -1.94029078e-01 3.35086852e-01 6.36316359e-01
5.25644124e-01 -1.55331421e+00 -1.22550178e+00 3.42098445e-01
-2.12572888e-01 -1.05239570e+00 2.67442226e-01 7.57036746e-01
-7.07829118e-01 -1.23297751e+00 -5.75503707e-01 -1.05161393e+00
6.23346865e-01 2.07158044e-01 4.14865792e-01 9.47942734e-02
-3.47108215e-01 2.13403121e-01 -4.84492481e-01 -2.48207480e-01
-6.74576402e-01 -6.05481826e-02 6.24620140e-01 -6.54933810e-01
4.46159877e-02 -4.22618866e-01 -5.71203768e-01 8.22700381e-01
-5.75850725e-01 -2.59805441e-01 9.93785977e-01 6.72881961e-01
7.51843601e-02 4.16695237e-01 6.25502229e-01 -1.55484661e-01
5.80270469e-01 -3.80296946e-01 -2.21734613e-01 -9.53284875e-02
-3.58011574e-01 -1.76846534e-01 8.23161781e-01 -6.64084613e-01
-1.12740660e+00 2.52767414e-01 -2.16007650e-01 -1.68232307e-01
-4.89781946e-01 1.29367411e-01 -3.45418125e-01 -7.94906095e-02
8.39447618e-01 -2.70007104e-01 4.33771610e-01 -3.86690229e-01
-9.61822122e-02 9.64960635e-01 7.17863023e-01 -3.32767189e-01
6.71434522e-01 3.65565330e-01 2.26810843e-01 -7.22563326e-01
-2.85368552e-03 -2.68240929e-01 -1.05374360e+00 -3.83789271e-01
8.78211021e-01 -4.11323100e-01 -1.18999946e+00 6.29658461e-01
-1.17852271e+00 -4.76289302e-01 -4.88180332e-02 8.35620582e-01
-8.06596875e-01 4.56251144e-01 -6.52838111e-01 -9.13643181e-01
-1.49867460e-01 -1.19651878e+00 7.99406171e-01 1.10775912e-02
-7.56110668e-01 -5.66989899e-01 -4.34062719e-01 2.05789715e-01
3.39152426e-01 6.15583122e-01 6.48642838e-01 -5.07442415e-01
-8.63042846e-02 -5.91738701e-01 2.00952455e-01 5.13604164e-01
6.49430573e-01 -3.11133623e-01 -4.47209030e-01 -3.97546679e-01
3.59070122e-01 -5.08143604e-01 2.32575536e-01 -2.27946453e-02
5.67875564e-01 -1.21752150e-01 -6.21286213e-01 -1.32900998e-01
9.38093245e-01 5.95548749e-01 8.72850478e-01 6.59704447e-01
4.91643131e-01 1.21598256e+00 1.42711329e+00 1.47393525e-01
-1.65609002e-01 8.73175979e-01 8.22922409e-01 -1.15782760e-01
2.08336726e-01 1.96593702e-01 5.39450586e-01 3.82845700e-01
-3.02876532e-01 -2.35072896e-01 -8.16183567e-01 2.60884762e-01
-1.69175684e+00 -8.69623601e-01 -4.12189960e-01 2.44915819e+00
5.69331527e-01 6.11829519e-01 -1.05149634e-01 6.21709406e-01
5.96790969e-01 -4.87276763e-01 -4.25469756e-01 -8.72803330e-01
3.79047245e-01 -8.41385052e-02 6.12783372e-01 1.95836559e-01
-1.11124611e+00 4.46397930e-01 5.50115633e+00 5.10394275e-01
-1.16486669e+00 -3.31247956e-01 -1.67664751e-01 1.64109543e-01
6.04599893e-01 -3.72307777e-01 -3.48231643e-01 2.36620143e-01
5.50780833e-01 4.14255202e-01 1.80222437e-01 1.08258426e+00
1.32004216e-01 -6.13733172e-01 -1.35910034e+00 6.26234770e-01
-1.84942350e-01 -4.01499242e-01 -3.70254964e-01 9.48754996e-02
-5.35282306e-02 -2.23711118e-01 -3.21716130e-01 3.99597377e-01
-1.27413303e-01 -8.95209849e-01 6.89545274e-01 5.16449809e-01
5.62475920e-01 -7.71712422e-01 1.15497196e+00 7.51291692e-01
-1.04428589e+00 -3.08374852e-01 -3.51392537e-01 -3.22387844e-01
3.41874599e-01 2.56357968e-01 -9.08680856e-01 7.48619676e-01
8.32307875e-01 4.66468036e-02 9.66934860e-02 8.42513859e-01
-1.28364280e-01 -1.97614387e-01 -4.70571458e-01 -2.40903556e-01
-2.23978199e-02 -1.05011582e-01 6.19153142e-01 8.84048045e-01
4.01283622e-01 -2.35650986e-01 2.19936669e-01 6.61921978e-01
5.54346561e-01 -2.63950288e-01 -1.02283990e+00 4.75388259e-01
2.88718283e-01 1.18094814e+00 -7.02553749e-01 2.96164632e-01
-1.03629380e-01 1.46505678e+00 4.79352139e-02 2.87398249e-02
-8.92828047e-01 -9.94819820e-01 7.59060860e-01 1.81254610e-01
-9.73149464e-02 -6.09374821e-01 -1.25460476e-02 -2.65365332e-01
3.77655536e-01 -5.78610063e-01 -1.21185668e-01 -6.82942688e-01
-1.08617103e+00 4.89699632e-01 2.01412037e-01 -1.82873785e+00
-5.25957525e-01 -1.18017471e+00 -4.53830510e-01 5.88413537e-01
-7.54844368e-01 -8.20091724e-01 -3.61171216e-01 3.60019058e-01
3.62363189e-01 2.95889914e-01 9.12212968e-01 9.31694955e-02
-4.70155701e-02 4.15684819e-01 -2.26131901e-01 5.14869206e-02
8.05108130e-01 -9.64708567e-01 -1.68019887e-02 1.56028062e-01
-5.68554997e-01 6.42315805e-01 9.41720128e-01 -7.05515921e-01
-1.71521389e+00 -5.89594841e-01 6.73374891e-01 -3.53834838e-01
3.68587524e-01 -5.77940941e-01 -1.01808333e+00 2.95827121e-01
9.29557979e-02 -2.53451318e-01 8.20698366e-02 -1.26454666e-01
3.58919084e-01 -1.10425286e-01 -1.44993806e+00 7.20796347e-01
1.12036443e+00 -1.59654155e-01 -9.33760643e-01 3.64735007e-01
5.32331884e-01 -2.89153814e-01 -9.33342755e-01 9.22729373e-01
7.63823628e-01 -9.50372636e-01 7.93083608e-01 1.90815460e-02
4.56527732e-02 -3.35098654e-01 2.29991570e-01 -1.22326434e+00
-2.75252998e-01 -4.38767850e-01 3.51299614e-01 9.41230357e-01
2.19061732e-01 -7.12424815e-01 5.24693191e-01 6.92960322e-01
-4.50760663e-01 -7.43378758e-01 -1.16993201e+00 -1.36839998e+00
9.22564534e-04 -2.34510154e-01 1.09516464e-01 8.87051702e-01
6.95094168e-01 -5.24892733e-02 -4.56894815e-01 2.61591375e-01
9.42864865e-02 -2.21643686e-01 9.16717231e-01 -1.47346306e+00
-4.81662303e-02 -2.81984121e-01 -7.03250468e-01 -7.27437854e-01
8.86150822e-02 -4.35385674e-01 6.48233831e-01 -1.88595736e+00
-4.13072497e-01 -5.05091190e-01 -1.79530025e-01 5.84492087e-01
4.52920765e-01 -1.49633676e-01 1.49527295e-02 1.37657925e-01
-8.58146921e-02 5.04888594e-01 1.41229975e+00 2.52917670e-02
-2.80080140e-01 2.95393705e-01 6.48234040e-02 8.11730206e-01
9.80838895e-01 -2.72476256e-01 -2.09081039e-01 -1.02181070e-01
-4.71195988e-02 1.57179117e-01 3.41339171e-01 -1.67091644e+00
2.38675386e-01 -2.25136489e-01 2.88089067e-01 -2.37012252e-01
4.86575067e-01 -1.43555534e+00 2.61614323e-01 1.07586110e+00
-2.84248535e-02 -2.01310441e-01 1.94432497e-01 3.90657246e-01
-1.04105771e-02 -3.20317596e-01 6.93559468e-01 8.85005519e-02
-5.96911192e-01 -3.89631599e-01 -1.00250494e+00 -7.02650428e-01
1.43358803e+00 -5.82140088e-01 1.69306844e-02 -1.64322525e-01
-6.79308057e-01 2.95680106e-01 4.61570829e-01 8.48176718e-01
4.91211176e-01 -1.02696407e+00 -9.11582336e-02 1.45138623e-02
8.45680758e-02 3.31685245e-02 1.74378231e-01 9.71522987e-01
-6.61858916e-01 3.03262174e-01 -7.01870739e-01 -4.63436425e-01
-9.33567345e-01 6.73075378e-01 3.33004206e-01 1.03679851e-01
-9.07371223e-01 4.15996552e-01 -5.68205640e-02 -8.21195066e-01
4.20140386e-01 -6.14327550e-01 -3.90711069e-01 -3.62739891e-01
6.73931371e-03 4.67275321e-01 1.95525482e-01 -5.91928899e-01
-4.93771911e-01 4.50802088e-01 2.67439872e-01 2.10887522e-01
1.00749481e+00 1.13455795e-01 1.06979728e-01 4.56141889e-01
8.48060489e-01 -1.30143523e-01 -1.37558019e+00 3.84334326e-01
2.34008297e-01 -1.40634492e-01 -4.95765477e-01 -7.58143306e-01
-6.59138501e-01 7.58012593e-01 7.61059642e-01 2.59269655e-01
9.13162410e-01 -4.31250446e-02 8.07220280e-01 9.41520870e-01
1.09760857e+00 -1.37782967e+00 2.03068420e-01 5.16065300e-01
1.44844627e+00 -1.18926513e+00 -9.58048645e-03 -5.87630093e-01
-6.15228593e-01 1.21780932e+00 9.96098220e-01 -4.82760847e-01
4.98330534e-01 4.88080740e-01 1.38357833e-01 -1.23987727e-01
-1.55652449e-01 1.12049565e-01 1.03665978e-01 8.91353607e-01
2.37066388e-01 4.08235602e-02 -4.08839196e-01 5.50528765e-01
-1.60690755e-01 -1.27989888e-01 3.96772385e-01 1.36222577e+00
-7.43074298e-01 -1.04397953e+00 -5.12917936e-01 3.52279305e-01
-1.34693459e-01 8.09316874e-01 -3.53307247e-01 1.34636784e+00
3.75081182e-01 1.17808437e+00 7.54133761e-02 -6.63757443e-01
9.05899823e-01 -1.62587047e-01 4.10562456e-01 -5.23356915e-01
-6.05303526e-01 -3.44829857e-01 2.22366676e-01 -8.72288227e-01
-2.21057996e-01 -4.54592228e-01 -1.91014373e+00 1.11360317e-02
-4.92765754e-01 7.55973335e-04 7.36490369e-01 9.13339853e-01
9.56765711e-02 4.78179097e-01 3.65505815e-01 -1.49732840e+00
-7.13995099e-01 -1.18956888e+00 -6.41899765e-01 3.85045558e-01
2.05699816e-01 -1.25739431e+00 -4.27908093e-01 -2.73633182e-01] | [4.897934913635254, 1.0509798526763916] |
43fe59a3-25bc-4507-98f6-4178326af0cd | reconnaissance-automatique-de-la-parole | null | null | https://aclanthology.org/F12-1083 | https://aclanthology.org/F12-1083.pdf | Reconnaissance automatique de la parole distante dans un habitat intelligent : m\'ethodes multi-sources en conditions r\'ealistes (Distant Speech Recognition in a Smart Home : Comparison of Several Multisource ASRs in Realistic Conditions) [in French] | null | ['Fran{\\c{c}}ois Portet', 'Michel Vacher', 'Benjamin Lecouteux'] | 2012-06-01 | reconnaissance-automatique-de-la-parole-1 | https://aclanthology.org/F12-1083 | https://aclanthology.org/F12-1083.pdf | jeptalnrecital-2012-6 | ['distant-speech-recognition'] | ['speech'] | [-8.63703638e-02 1.71006292e-01 -6.22772932e-01 -4.08054382e-01
-8.41685571e-03 -9.08429027e-01 6.55310392e-01 -6.53472245e-01
-2.85945535e-01 1.06888819e+00 -4.63127941e-02 -1.01159286e+00
-3.91567826e-01 -9.63214397e-01 -4.95059669e-01 -6.31337762e-01
-9.79754329e-01 7.25764990e-01 3.30370307e-01 -6.93831444e-01
7.03166842e-01 7.88774848e-01 -1.68942046e+00 7.18545914e-01
7.04417467e-01 8.52217197e-01 2.49141872e-01 1.14950800e+00
-1.95044339e-01 1.55633950e+00 -7.48382092e-01 -5.46825826e-01
3.13719302e-01 -1.23176083e-01 -7.22945035e-01 -1.01074085e-01
9.28529128e-02 -8.59008506e-02 -2.09758401e-01 9.22211111e-01
5.37373662e-01 4.49454933e-02 1.08379531e+00 -1.42548037e+00
-5.91619551e-01 6.10313773e-01 -4.01565880e-02 1.21627934e-01
1.03678203e+00 -5.39447069e-01 1.19919395e+00 -1.13026452e+00
7.20913768e-01 1.26888943e+00 8.66221786e-01 5.44149756e-01
-1.22286928e+00 -1.94712028e-01 -3.26822817e-01 -9.51717794e-02
-1.46558487e+00 -3.25250506e-01 4.25783843e-02 -2.08119690e-01
1.66093647e+00 1.26596653e+00 1.20609856e+00 1.01401424e+00
1.26658809e+00 8.34431887e-01 1.04267764e+00 -5.13792276e-01
3.35295945e-01 3.66983831e-01 1.54683650e-01 6.33519173e-01
8.40953708e-01 5.26628852e-01 -7.06372619e-01 -9.13127720e-01
9.33553874e-01 -2.94925272e-01 1.71355158e-01 -5.05680561e-01
-9.05919552e-01 6.91228509e-01 1.78732842e-01 3.83959889e-01
-1.39880210e-01 9.89067405e-02 1.26390755e-01 5.30987144e-01
-2.58292928e-02 6.47037446e-01 -9.11868811e-01 -1.33165747e-01
-8.71728659e-01 5.10332465e-01 1.25398111e+00 1.52653182e+00
1.24482810e-01 2.94908643e-01 -9.34252143e-02 3.17179203e-01
8.92314315e-01 1.01808000e+00 4.28362608e-01 -1.36146402e+00
-6.87414408e-02 1.72361732e-01 5.01781464e-01 -8.52631688e-01
-6.33224547e-01 -9.64177120e-03 -8.93263519e-01 4.49267089e-01
3.49161088e-01 4.57367361e-01 -8.02827001e-01 5.07305264e-01
4.33481112e-02 -2.34125629e-01 4.53833073e-01 5.55570945e-02
4.99930978e-01 3.76208365e-01 -1.34477139e-01 -5.73289394e-01
1.06082785e+00 -1.36716676e+00 -1.35299087e+00 2.33215362e-01
9.05734658e-01 -1.07320261e+00 4.35900748e-01 5.33875942e-01
-1.55548143e+00 -1.37560293e-01 -1.08699942e+00 1.78573877e-01
-7.27255583e-01 -3.14239264e-01 8.57801437e-01 1.43120694e+00
-1.60129595e+00 9.73287821e-01 -4.91727620e-01 6.59165755e-02
1.20568443e-02 8.24621081e-01 -2.64718989e-03 4.62812334e-01
-1.33193445e+00 1.08501506e+00 2.22979754e-01 -1.21242590e-01
-1.65216476e-01 -2.13068098e-01 -8.23704481e-01 -5.63443303e-01
-4.78693932e-01 -5.29636025e-01 1.44139910e+00 -2.59346128e-01
-1.65295815e+00 9.71794367e-01 -1.42069459e-01 -1.97814897e-01
6.14786744e-01 -1.28011424e-02 -8.31891418e-01 2.42498964e-01
-1.89849049e-01 5.76383233e-01 9.28263724e-01 -1.35132408e+00
-7.59897232e-01 -1.67359829e-01 -1.23336017e-01 2.66287565e-01
-1.25510961e-01 1.89734384e-01 2.11616129e-01 -1.12999000e-01
3.27147305e-01 -7.20919967e-01 -2.53068686e-01 -5.32041907e-01
-1.46512717e-01 -7.10518599e-01 7.70373225e-01 -4.51523662e-01
1.83705616e+00 -1.67618537e+00 -2.06720144e-01 3.98590982e-01
3.57815564e-01 -1.24705513e-03 2.40583986e-01 1.08380008e+00
-2.76906848e-01 7.32199550e-01 4.11965609e-01 -1.10722095e-01
2.24991128e-01 4.85861301e-01 -4.16602850e-01 3.05609167e-01
-1.29282743e-01 1.15307164e+00 -1.16605783e+00 -5.23096442e-01
4.11106765e-01 9.42391157e-02 -4.58732933e-01 4.79237735e-01
2.99364805e-01 1.47170946e-01 -3.56553018e-01 1.39399457e+00
1.15709066e+00 -1.31984919e-01 1.45911396e-01 5.30878425e-01
-3.79135728e-01 3.55090618e-01 -6.96863770e-01 1.05554795e+00
7.08333924e-02 5.00173986e-01 1.02364108e-01 -7.94621468e-01
3.33247900e-01 8.61540735e-01 4.37155962e-01 -9.67555881e-01
-2.26398129e-02 6.92409754e-01 1.12803578e-01 -6.07703328e-01
7.58228302e-01 3.94563079e-02 -3.64872098e-01 6.40070081e-01
-2.37588286e-01 -6.59476995e-01 9.64643434e-02 3.08100313e-01
6.22585893e-01 -5.18246442e-02 5.62923312e-01 -1.05613089e+00
7.86340594e-01 -1.82965681e-01 -1.81299388e-01 1.03415680e+00
-3.09923887e-01 3.19085121e-01 2.99841821e-01 -6.65102363e-01
-6.45341039e-01 -1.12307119e+00 -4.89381433e-01 1.30636716e+00
3.24267983e-01 -4.39044595e-01 -9.54439282e-01 -2.49762803e-01
1.77620783e-01 6.89606130e-01 -5.90509653e-01 3.84124845e-01
-5.03739953e-01 -8.32535863e-01 7.39044368e-01 3.45434904e-01
-5.07752821e-02 -1.33414865e+00 -6.58416986e-01 1.25490099e-01
-2.20292807e-01 -6.63697243e-01 -6.23428151e-02 4.48765576e-01
-1.35989368e+00 -5.18594682e-01 -6.66252747e-02 -8.20914626e-01
5.87345481e-01 2.46782884e-01 1.27047324e+00 5.39230824e-01
-2.31483161e-01 4.26904231e-01 -1.21292919e-01 -4.95818377e-01
-4.59671497e-01 -8.00336525e-02 5.28869390e-01 -5.87835789e-01
5.19427478e-01 -2.50617653e-01 -7.29350567e-01 5.37953973e-01
-6.88540697e-01 1.62748516e-01 1.79803044e-01 1.04410267e+00
1.35816500e-01 -9.34035778e-02 1.22507080e-01 -6.38007045e-01
8.72274399e-01 -1.69219792e-01 -3.78732830e-01 5.77745810e-02
-6.77108407e-01 -3.74140263e-01 3.21430594e-01 -3.25342178e-01
-1.01981449e+00 -4.87835288e-01 -9.82677937e-02 2.45538145e-01
1.11353043e-02 -1.46784872e-01 6.47139177e-02 -5.24923325e-01
8.02199244e-01 9.25758183e-02 1.99174434e-02 -6.80815242e-03
3.01039815e-01 7.09525108e-01 -6.82967342e-03 -6.68678164e-01
8.44880998e-01 4.91470337e-01 7.98524171e-02 -9.57177758e-01
-1.52186140e-01 -2.60129690e-01 -9.51962709e-01 -6.54426932e-01
6.56643391e-01 -6.78531289e-01 -9.10833478e-01 3.91110867e-01
-9.38691139e-01 -3.38627815e-01 -3.91645581e-01 4.25431967e-01
-1.01278400e+00 2.75717527e-02 -3.90154392e-01 -1.27895141e+00
-5.10977268e-01 -1.02017939e+00 9.43384409e-01 5.30070923e-02
-5.10597289e-01 -1.26927447e+00 5.87685481e-02 2.71537274e-01
1.81734428e-01 -1.73075795e-01 6.90226793e-01 -2.38256708e-01
-4.24233019e-01 -1.53791070e-01 2.34436691e-02 -1.39755070e-01
1.70832314e-02 4.95917559e-01 -9.81751978e-01 -5.31145096e-01
6.65065646e-02 -1.92070693e-01 -1.08835101e-01 6.52520418e-01
5.91872573e-01 -2.29931593e-01 -8.56000841e-01 5.40386558e-01
1.38545322e+00 3.85070026e-01 5.32770038e-01 7.28214979e-01
1.41836226e-01 5.53460240e-01 9.17806149e-01 4.63203549e-01
1.30579369e-02 3.28798652e-01 2.40537539e-01 1.49327129e-01
1.11720070e-01 -1.54819340e-01 3.77893507e-01 1.16112018e+00
-8.18235934e-01 -2.69281328e-01 -5.07867396e-01 4.42987174e-01
-1.72482407e+00 -1.40330648e+00 -4.32368398e-01 6.90478683e-01
6.25676990e-01 1.56016424e-01 -1.48347050e-01 3.35214496e-01
4.99015123e-01 -2.03574806e-01 -1.19133167e-01 -1.06291151e+00
-1.43546045e-01 3.15233678e-01 7.37729073e-01 1.00061214e+00
-7.20721722e-01 1.03317809e+00 1.29781246e+01 1.02230716e+00
2.21112028e-01 1.03134915e-01 5.16071796e-01 3.48020852e-01
-4.36954498e-01 -4.56139445e-02 -1.04416132e+00 2.72933897e-02
1.38140702e+00 -4.30666685e-01 6.85999811e-01 5.44219851e-01
3.44648361e-01 -4.23268199e-01 -1.26188684e+00 5.26221812e-01
9.73738134e-02 -1.40886843e+00 -2.83300440e-04 6.85225725e-01
7.73699820e-01 -5.08050561e-01 6.22419357e-01 3.24184299e-01
6.09259963e-01 -1.14389277e+00 8.60300779e-01 2.53660440e-01
1.03040910e+00 -6.05088234e-01 5.67372203e-01 1.68872893e-01
-1.14389896e+00 -2.20873043e-01 -8.77727985e-01 -1.00755692e+00
3.93533185e-02 -1.81779593e-01 -4.29956943e-01 3.48861217e-01
9.58353162e-01 2.99398601e-01 -3.93658698e-01 9.95779395e-01
-4.78694476e-02 1.04875881e-02 -2.71853864e-01 -4.48467314e-01
4.83122796e-01 -3.54241252e-01 4.66730654e-01 1.00164843e+00
2.48499006e-01 3.51035744e-01 -9.84472036e-02 4.01770771e-01
5.45058846e-01 3.29446048e-02 -1.19659424e+00 -1.78908288e-01
2.83276141e-01 9.16795909e-01 -4.83487815e-01 -4.22520459e-01
-2.00212970e-01 8.62069130e-01 -3.55488248e-02 5.01107454e-01
-6.11489356e-01 -4.35615242e-01 9.72222984e-01 -1.27327025e-01
-1.14700586e-01 -3.48497719e-01 -6.23769283e-01 -7.30352640e-01
-5.89872956e-01 -4.54965204e-01 5.93606755e-02 -5.53365827e-01
-1.39813089e+00 5.79277515e-01 -2.27688253e-02 -1.40553558e+00
-6.99901402e-01 -1.27676582e+00 -4.76714373e-01 4.92853165e-01
-1.11898029e+00 -1.10984349e+00 2.50124663e-01 4.52870727e-01
1.64141744e-01 -5.34416080e-01 1.39563632e+00 3.57715860e-02
1.00637585e-01 9.24474537e-01 6.69434488e-01 -7.37814724e-01
5.56605101e-01 -1.27867436e+00 5.68737745e-01 -1.37897313e-01
-4.31265175e-01 9.05828118e-01 6.28349900e-01 -5.39804697e-01
-1.41196322e+00 -3.66917729e-01 1.08350635e+00 -9.83769417e-01
6.55218959e-01 -3.86345625e-01 4.23767231e-02 7.88592756e-01
7.15902448e-01 -6.18741751e-01 8.21781039e-01 -1.83753878e-01
1.80774391e-01 5.75296998e-01 -1.39248300e+00 6.12354755e-01
1.66275799e+00 -4.63594139e-01 -6.25784039e-01 7.60327101e-01
8.13696027e-01 -6.94087505e-01 -1.30082703e+00 3.34633321e-01
8.65424156e-01 -8.75409484e-01 1.61978090e+00 -1.32660246e+00
-4.43697497e-02 2.81152606e-01 -2.61993498e-01 -9.32519078e-01
-5.96193194e-01 -1.23518765e+00 -5.33532679e-01 -5.83747849e-02
5.96577883e-01 -1.13057327e+00 3.42365682e-01 8.74560475e-01
-2.82833427e-01 -6.42737269e-01 -1.06996536e+00 -1.32016802e+00
-3.35779637e-02 -1.45572275e-01 4.90409225e-01 7.63798356e-01
6.83744550e-01 1.09839931e-01 -6.36873543e-02 -1.00294888e-01
5.33176839e-01 9.55312885e-03 4.41501856e-01 -1.34294486e+00
3.86843324e-01 -5.75816095e-01 -3.07655483e-01 -9.45992947e-01
-8.85957032e-02 -8.12076271e-01 -6.53862000e-01 -1.28511906e+00
-8.32044985e-03 -1.91056758e-01 -1.11109078e-01 -1.65725678e-01
3.67937148e-01 2.13746816e-01 1.20859891e-02 1.03788137e-01
-3.71160030e-01 6.18435517e-02 1.29639816e+00 6.91750320e-05
-1.62315920e-01 4.85058486e-01 -4.81304944e-01 7.84440815e-01
8.58408585e-02 -2.99253196e-01 -6.78878546e-01 6.11881316e-02
6.69384480e-01 4.61409837e-02 3.24159935e-02 -7.42885649e-01
5.37211418e-01 -3.75702560e-01 4.78586555e-01 -1.32223868e+00
1.30741090e-01 -9.61415648e-01 6.95283338e-02 9.40189242e-01
2.74610907e-01 1.20424610e-02 8.66204947e-02 5.39500564e-02
-1.44871444e-01 -5.70943117e-01 9.21121240e-01 -4.07591403e-01
-4.92852688e-01 -5.20386267e-03 -1.03226590e+00 8.97834301e-02
9.92593169e-01 -7.84614205e-01 -3.59281451e-01 -4.20183957e-01
-8.29068601e-01 -1.95836127e-02 6.50830388e-01 3.03609259e-02
7.30431557e-01 -1.51530886e+00 -2.30721906e-01 7.18729138e-01
-3.22939813e-01 -3.74400020e-01 -1.70157343e-01 6.58265352e-01
-1.32361674e+00 1.02442718e+00 -5.41665435e-01 -4.55340147e-01
-1.14228773e+00 4.78126436e-01 4.28307921e-01 -2.41845414e-01
-2.15481281e-01 1.11954463e+00 2.71224789e-02 -8.23025763e-01
1.85185194e-01 -9.21545625e-02 -7.54407048e-01 3.55081353e-03
6.88606799e-01 1.05194807e+00 -2.91290224e-01 -6.04341030e-01
-4.56784427e-01 6.65885091e-01 2.32151806e-01 -2.87484169e-01
9.17833567e-01 -2.19243199e-01 -9.89108324e-01 4.28274393e-01
8.38715494e-01 -1.36269778e-01 -3.69319022e-02 4.16855574e-01
1.25943512e-01 -8.02164078e-01 -4.32406247e-01 -3.55811834e-01
-1.85641110e-01 5.54822803e-01 5.34874737e-01 8.99602413e-01
8.57008278e-01 -3.02566767e-01 8.18335712e-01 9.66778398e-01
5.72402716e-01 -1.68019545e+00 -2.13140488e-01 6.89524531e-01
9.12339568e-01 -9.28350806e-01 5.44190466e-01 -7.27165341e-01
-4.14997995e-01 1.32979155e+00 4.68304873e-01 -1.55325383e-01
1.27306652e+00 5.74917436e-01 1.14069022e-02 -3.70670199e-01
-9.44949508e-01 1.12705544e-01 3.75366658e-01 1.11147714e+00
5.06513238e-01 5.07374525e-01 -9.66500878e-01 3.21953118e-01
-7.28706717e-01 -2.34555230e-01 4.90474731e-01 1.41972518e+00
-6.43810987e-01 -1.20391917e+00 -7.23931909e-01 4.61561680e-01
-5.49773455e-01 -1.16372630e-01 -5.28106689e-01 8.46754074e-01
-5.76629937e-02 1.49448860e+00 -1.97535474e-03 -5.03491640e-01
4.11356747e-01 1.41089618e-01 7.21762300e-01 -1.23501487e-01
-9.04846430e-01 4.15413082e-01 3.84890139e-01 -1.23056793e+00
-8.58632207e-01 -1.05834293e+00 -1.40667629e+00 -1.19437599e+00
-5.12782812e-01 1.89310342e-01 3.83317530e-01 3.90289724e-01
-2.06836104e-01 2.85260603e-02 9.80917513e-01 -1.07949340e+00
-3.90341938e-01 -9.39418614e-01 -1.00026262e+00 -7.84516707e-02
2.89751232e-01 -8.00943017e-01 -7.83523321e-01 2.83909619e-01] | [-7.492165565490723, 3.5879523754119873] |
a75af41a-f0ee-4758-a000-ed98adee7d74 | towards-the-evolution-of-vertical-axis-wind | 1204.4107 | null | http://arxiv.org/abs/1204.4107v4 | http://arxiv.org/pdf/1204.4107v4.pdf | Towards the Evolution of Vertical-Axis Wind Turbines using Supershapes | We have recently presented an initial study of evolutionary algorithms used
to design vertical-axis wind turbines (VAWTs) wherein candidate prototypes are
evaluated under approximated wind tunnel conditions after being physically
instantiated by a 3D printer. That is, unlike other approaches such as
computational fluid dynamics simulations, no mathematical formulations are used
and no model assumptions are made. However, the representation used
significantly restricted the range of morphologies explored. In this paper, we
present initial explorations into the use of a simple generative encoding,
known as Gielis superformula, that produces a highly flexible 3D shape
representation to design VAWT. First, the target-based evolution of 3D
artefacts is investigated and subsequently initial design experiments are
performed wherein each VAWT candidate is physically instantiated and evaluated
under approximated wind tunnel conditions. It is shown possible to produce very
closely matching designs of a number of 3D objects through the evolution of
supershapes produced by Gielis superformula. Moreover, it is shown possible to
use artificial physical evolution to identify novel and increasingly efficient
supershape VAWT designs. | ['Larry Bull', 'Richard J. Preen'] | 2012-04-18 | null | null | null | null | ['3d-shape-representation'] | ['computer-vision'] | [-1.15941294e-01 -8.58450383e-02 6.50609136e-01 3.49574447e-01
3.11209649e-01 -8.99826527e-01 7.42647827e-01 -2.54504472e-01
-7.54384622e-02 8.95476580e-01 -3.18750590e-01 -3.85516644e-01
-6.78204477e-01 -1.00366557e+00 -3.80784571e-01 -6.04679465e-01
-4.60484892e-01 6.22747958e-01 1.54662892e-01 -5.39347231e-01
2.06562728e-01 8.21301579e-01 -2.19445801e+00 -3.74095410e-01
9.97623205e-01 5.64999223e-01 4.02831048e-01 8.32859933e-01
-1.78658769e-01 -3.68035108e-01 -9.25402761e-01 -2.19471619e-01
5.34828961e-01 -7.34210134e-01 -5.76378882e-01 1.94443792e-01
-9.84092876e-02 1.98784783e-01 6.71375453e-01 7.49997795e-01
6.75472736e-01 3.67440134e-01 9.70997453e-01 -9.66592014e-01
-6.17765129e-01 2.51868278e-01 -2.37874418e-01 -1.27999438e-02
3.90250921e-01 2.65494943e-01 4.76765633e-01 -8.98646414e-01
9.74541724e-01 1.26688135e+00 8.59259069e-01 5.58164954e-01
-1.41594112e+00 -2.67710179e-01 -3.69007587e-01 -5.15295565e-01
-1.54682255e+00 -1.07176732e-02 8.98733735e-01 -5.95208228e-01
1.01304758e+00 6.50864780e-01 1.49532938e+00 6.33683324e-01
5.26205957e-01 5.35953522e-01 1.12376773e+00 -7.02743053e-01
8.50946963e-01 1.55182064e-01 -6.33457243e-01 6.44342363e-01
7.58201540e-01 6.98380351e-01 -1.27719149e-01 -3.33521992e-01
9.26702976e-01 -8.14030766e-01 -2.74106801e-01 -8.87394667e-01
-6.53245091e-01 7.38217592e-01 9.38369185e-02 6.41506195e-01
-3.45014751e-01 1.21942140e-01 7.99262598e-02 7.93567970e-02
3.05694252e-01 1.41214120e+00 -4.77105409e-01 -2.76559055e-01
-8.65839303e-01 6.29728019e-01 7.65125513e-01 7.62379348e-01
2.61105299e-01 7.48521864e-01 3.36392343e-01 6.57884479e-01
2.77861595e-01 5.25381088e-01 5.50887406e-01 -7.55976140e-01
-9.73789170e-02 4.14836645e-01 3.34910065e-01 -6.23681605e-01
-3.49956572e-01 -5.99421680e-01 -3.27355266e-01 1.01383829e+00
-1.01620451e-01 -6.52604461e-01 -9.15060878e-01 1.06581426e+00
6.45665467e-01 -1.14695668e-01 1.41257167e-01 8.00849319e-01
4.03244823e-01 4.89342600e-01 -1.97492748e-01 -2.97953010e-01
1.06322360e+00 -3.95619601e-01 -6.04729652e-01 4.76169914e-01
5.98461688e-01 -7.68571913e-01 8.37592542e-01 4.65749234e-01
-1.40121150e+00 -8.20042729e-01 -1.33739090e+00 7.86090016e-01
-6.33430660e-01 -2.36730084e-01 5.15053749e-01 1.21308506e+00
-1.22350335e+00 1.00529361e+00 -7.56476462e-01 -3.10965478e-01
1.92479342e-01 1.82807401e-01 1.05227411e-01 6.50324166e-01
-9.69386041e-01 1.28456473e+00 4.51993018e-01 1.40910879e-01
-4.37054902e-01 -7.69681334e-01 -5.97248495e-01 -1.43836334e-01
-1.58581495e-01 -1.21584427e+00 1.12768722e+00 -5.27593017e-01
-2.09559464e+00 3.46510768e-01 2.74304509e-01 -3.13041151e-01
6.87328041e-01 6.28404245e-02 -5.05805016e-01 -1.03982970e-01
-2.74460435e-01 5.00245512e-01 8.71843159e-01 -1.81452024e+00
-4.99558061e-01 3.00254226e-01 -1.44436330e-01 1.12721585e-01
-2.04453975e-01 -2.07501411e-01 5.86040437e-01 -9.74494278e-01
-4.32027690e-02 -9.21556890e-01 -4.36348140e-01 6.18864708e-02
-4.58896644e-02 9.86979753e-02 1.01509774e+00 -2.38930330e-01
1.28472769e+00 -1.73684311e+00 6.99939728e-01 5.17264903e-01
-2.08443731e-01 6.10712051e-01 1.80107653e-01 8.99300933e-01
1.63413724e-03 7.77928054e-01 -3.99357557e-01 -1.22276116e-02
1.42716289e-01 4.22923356e-01 -1.79505691e-01 -5.58212735e-02
2.19579250e-01 7.49569952e-01 -8.80683303e-01 -1.34081155e-01
3.93320084e-01 3.83524776e-01 -5.54031312e-01 -1.68401152e-01
-2.80260354e-01 3.09776276e-01 -7.19258070e-01 5.30902028e-01
6.46693528e-01 6.05107427e-01 -7.12167993e-02 1.86768815e-01
-8.43553364e-01 -4.53084171e-01 -1.07725859e+00 1.50295925e+00
-7.55057693e-01 4.03995186e-01 1.65050805e-01 -6.41162515e-01
1.43163061e+00 4.54517543e-01 3.41900945e-01 -3.88162822e-01
3.93873662e-01 5.94106257e-01 1.08577400e-01 -4.30443883e-01
6.98060036e-01 -4.72600400e-01 2.70574726e-02 3.26216012e-01
-9.01664570e-02 -1.39129984e+00 3.14209789e-01 -4.96306956e-01
7.78396249e-01 6.71805143e-01 2.30205268e-01 -8.12969744e-01
3.49319428e-01 4.00692582e-01 2.06624389e-01 4.02985662e-01
3.64594072e-01 6.79688573e-01 -3.10368259e-02 -7.26974189e-01
-1.39471662e+00 -1.21983647e+00 -6.06319249e-01 2.71034464e-02
2.07192898e-01 -3.55219096e-01 -6.56504691e-01 -2.20008045e-01
1.96316659e-01 1.06665790e+00 -7.37533033e-01 -1.66674823e-01
-6.00028038e-01 -6.70919836e-01 3.08324277e-01 2.59717882e-01
3.77006710e-01 -9.19585526e-01 -1.59578395e+00 4.10261810e-01
8.28319490e-01 -1.31786868e-01 2.11845636e-01 1.41328424e-01
-1.28901851e+00 -6.73813283e-01 -7.31266081e-01 -5.21662831e-01
6.37856483e-01 -1.24612309e-01 9.99463320e-01 4.27249551e-01
-8.08251560e-01 2.58030623e-01 -7.23428249e-01 -6.76055551e-01
-6.57368422e-01 -3.20763886e-01 1.98341429e-01 -5.63364625e-01
-5.53342581e-01 -9.27907467e-01 -3.53439152e-01 3.93891454e-01
-7.99538195e-01 -5.34382984e-02 4.96840566e-01 8.64933074e-01
5.50179303e-01 9.61017489e-01 4.37128186e-01 -3.58836889e-01
9.74473774e-01 -1.11224934e-01 -7.16687202e-01 1.88331380e-01
-5.21660864e-01 3.13408941e-01 7.61933744e-01 -5.33959568e-01
-1.18085551e+00 -9.34083462e-02 -8.20430368e-02 -5.18204927e-01
-2.54284352e-01 3.73935312e-01 1.57110825e-01 -3.43048245e-01
7.01734960e-01 1.46883028e-02 -2.09549647e-02 -6.75682127e-01
3.37034762e-01 3.08607787e-01 1.09714910e-01 -8.02049041e-01
1.41342759e+00 9.10350531e-02 2.41615355e-01 -1.03027761e+00
4.09718007e-01 3.99034113e-01 -8.46222281e-01 -4.56637561e-01
6.49512589e-01 -8.59865248e-02 -2.59631604e-01 1.76333770e-01
-7.46092796e-01 -2.79865116e-01 -1.10225487e+00 3.99287641e-01
-6.66791618e-01 -5.04258685e-02 2.24577710e-01 -1.32061124e+00
-2.61396796e-01 -1.10882831e+00 9.88062263e-01 2.08434328e-01
-8.12081873e-01 -1.11159897e+00 2.81170696e-01 -3.09454501e-01
6.10062957e-01 8.60782504e-01 1.20309949e+00 1.31134465e-01
-1.76862046e-01 -1.35034621e-01 7.76873469e-01 -1.12214908e-01
3.66532415e-01 8.38824153e-01 -5.07934034e-01 -3.55189115e-01
-1.51733398e-01 3.02373379e-01 1.60465941e-01 3.05206567e-01
5.86330175e-01 -9.28098895e-03 -5.84102392e-01 5.56473196e-01
1.37085104e+00 1.01826787e+00 4.74159926e-01 5.07417738e-01
-6.78220466e-02 5.60143232e-01 6.16177917e-01 4.69211191e-01
-5.56192338e-01 7.70252466e-01 3.21120173e-01 -3.83249260e-02
-3.42417568e-01 -2.00378448e-01 -1.92172229e-02 5.50978363e-01
-5.88837147e-01 -5.25550008e-01 -6.17990017e-01 5.06279230e-01
-1.23920572e+00 -8.72405946e-01 -9.40225869e-02 2.02022767e+00
3.20785254e-01 1.30503446e-01 7.23804608e-02 4.22983557e-01
7.66611576e-01 -2.62211889e-01 -1.64764881e-01 -1.08000576e+00
-1.11703821e-01 9.08489287e-01 1.18790567e-01 3.59087437e-01
-6.90641165e-01 3.90210778e-01 6.77945423e+00 6.27876222e-01
-8.74274015e-01 -4.06221986e-01 -5.20197023e-03 -2.08265260e-01
-6.80342555e-01 1.02089040e-01 -2.68394142e-01 4.87855732e-01
5.70488930e-01 -6.87578201e-01 3.75437915e-01 5.83704174e-01
3.34263355e-01 -2.50511914e-01 -3.39227766e-01 3.70156914e-01
-4.52029794e-01 -1.38361657e+00 1.05967551e-01 1.66206390e-01
1.16138840e+00 -9.31846738e-01 1.53152600e-01 -9.14944708e-02
4.25593674e-01 -8.55447233e-01 1.32082009e+00 5.72025478e-01
8.18628430e-01 -9.17403698e-01 5.96184134e-01 1.20538056e-01
-1.47053850e+00 -2.50107110e-01 -1.95293531e-01 -2.04931777e-02
7.20576048e-01 2.33548313e-01 -9.97843146e-01 1.05761790e+00
7.98968315e-01 1.10477693e-01 -3.31099272e-01 1.48667204e+00
-4.77856658e-02 3.14245909e-01 -5.89131474e-01 -5.98816991e-01
2.46768564e-01 -4.99762028e-01 1.10569215e+00 7.32671261e-01
1.23715425e+00 9.63628441e-02 -2.25841999e-01 1.04410529e+00
5.68791687e-01 1.53443187e-01 -8.99060965e-01 -1.11786865e-01
4.86096799e-01 8.29954684e-01 -1.01709068e+00 1.16241304e-02
3.87163103e-01 4.79016870e-01 -3.66015673e-01 2.96771049e-01
-8.59016359e-01 -4.82599825e-01 7.16941237e-01 3.62350315e-01
6.93082392e-01 -4.40605193e-01 -4.40239966e-01 -5.16835093e-01
-3.37829798e-01 -3.42308015e-01 -6.31562527e-03 -1.25497448e+00
-1.02358127e+00 8.58213246e-01 5.17826021e-01 -1.36325729e+00
-4.17423487e-01 -5.13997793e-01 -1.06169283e+00 1.01701593e+00
-6.02405488e-01 -7.60982931e-01 5.22981919e-02 -3.04830879e-01
6.65635645e-01 -4.60624486e-01 9.69808221e-01 -3.24342698e-01
-3.18835199e-01 8.11399594e-02 4.32996780e-01 -8.05964410e-01
-3.23145896e-01 -1.20595324e+00 6.39567912e-01 6.78522825e-01
-1.09036632e-01 5.87280810e-01 1.31392133e+00 -1.11647797e+00
-1.42010880e+00 -7.27497458e-01 2.89395154e-01 -1.95035368e-01
4.58760202e-01 -1.41029358e-01 -7.16780424e-01 -2.12923944e-01
4.55547035e-01 -4.10292536e-01 2.88182080e-01 -3.13826263e-01
7.03974962e-01 4.67337668e-01 -1.40006995e+00 8.31119299e-01
1.61611378e+00 2.55758286e-01 -7.30999112e-01 -1.20087542e-01
5.31124175e-01 -3.48972261e-01 -1.00032449e+00 7.53853321e-01
7.06675768e-01 -7.28420198e-01 1.00934231e+00 -5.69419324e-01
9.17003229e-02 -6.54313862e-01 3.47738475e-01 -1.86627960e+00
-3.82032484e-01 -1.00545752e+00 -4.28741500e-02 1.14481115e+00
4.53190178e-01 -7.23729074e-01 5.31348526e-01 2.76840985e-01
-6.47751331e-01 -9.85753179e-01 -1.02323592e+00 -1.27619803e+00
2.56707877e-01 1.09333441e-01 1.05711269e+00 6.81715250e-01
-1.89406186e-01 -2.99491286e-01 1.76218048e-01 -5.09434752e-02
2.56293297e-01 4.84242827e-01 4.50104237e-01 -1.39953613e+00
-3.69486481e-01 -7.67542303e-01 -3.72801095e-01 -3.44606370e-01
-2.92261302e-01 -7.15422034e-01 -4.30093110e-02 -1.52875507e+00
-9.81763422e-01 -8.93012464e-01 4.22627151e-01 -1.93086281e-01
2.90157437e-01 7.78294681e-03 1.27136812e-01 -1.05892837e-01
6.18297696e-01 8.35010707e-01 1.62259245e+00 2.60625273e-01
-6.69043958e-01 5.73173240e-02 -2.41305783e-01 4.69925821e-01
8.30653250e-01 -3.67813259e-01 -8.04481387e-01 -2.73251116e-01
2.92542517e-01 1.62072654e-03 1.75335839e-01 -1.16230273e+00
-3.72335196e-01 -1.21984527e-01 5.48237920e-01 -5.61625421e-01
3.01605970e-01 -7.61046410e-01 1.27985823e+00 7.72947669e-01
2.32756004e-01 4.51561332e-01 7.06941605e-01 4.23817754e-01
9.70304832e-02 -6.74855411e-01 5.74581623e-01 -1.55828506e-01
-5.29428482e-01 -4.96919870e-01 -8.38716388e-01 -4.57450330e-01
1.37050426e+00 -9.00078475e-01 -1.21946922e-02 2.55801141e-01
-7.56155908e-01 -1.04415692e-01 9.11038041e-01 2.79283494e-01
5.77427387e-01 -1.22091830e+00 -4.88008529e-01 4.43246126e-01
-5.26628494e-01 2.70425193e-02 2.07515627e-01 1.65077090e-01
-1.18584883e+00 1.20510206e-01 -5.98824680e-01 -4.24999505e-01
-1.00312114e+00 6.14687264e-01 5.76726139e-01 2.80309856e-01
-7.37371743e-01 9.93221641e-01 -1.82651892e-01 -2.52718359e-01
-7.35793591e-01 -3.14260274e-01 -1.05603397e-01 -8.78062658e-03
-5.91682643e-02 4.45803016e-01 1.06871858e-01 -4.52443630e-01
-1.42431065e-01 1.03267574e+00 9.44491029e-01 -3.27591181e-01
1.44867945e+00 1.55340627e-01 1.96624130e-01 4.70233634e-02
5.56477308e-01 1.86397642e-01 -1.10228395e+00 7.16812849e-01
-3.36878389e-01 -7.87645221e-01 -5.11210114e-02 -7.89616823e-01
-1.00138211e+00 5.04581392e-01 5.50328553e-01 5.03685832e-01
1.15661395e+00 -4.49443728e-01 5.36992133e-01 9.42287818e-02
8.07876945e-01 -9.40369964e-01 -1.38447315e-01 8.60444009e-02
1.32686448e+00 -9.98160243e-02 2.10433468e-01 -3.37213308e-01
-3.67314935e-01 1.35696650e+00 2.93255955e-01 -7.57196769e-02
6.04670405e-01 6.97916090e-01 -1.71001807e-01 -3.29450905e-01
-6.47886634e-01 -1.66383758e-01 2.27239117e-01 7.86979198e-01
7.49462917e-02 -1.28996633e-02 -7.19794869e-01 1.39183640e-01
-8.92180860e-01 -2.55258024e-01 4.80884701e-01 1.47439468e+00
-4.31133091e-01 -1.35127103e+00 -5.87127686e-01 1.26062766e-01
1.86832935e-01 2.78443694e-01 -5.00778496e-01 1.28978908e+00
6.51259601e-01 6.47779047e-01 3.76518443e-02 -5.37636280e-01
5.65336585e-01 1.09997086e-01 7.28673816e-01 -4.84564841e-01
-8.89292598e-01 -1.14714734e-01 3.43715727e-01 1.35427445e-01
-2.27739140e-01 -9.36622977e-01 -1.10264182e+00 -1.33293539e-01
-6.37644231e-01 8.13421965e-01 8.86273265e-01 4.78507608e-01
3.94859850e-01 7.15376198e-01 5.93179524e-01 -1.19753599e+00
-1.48214713e-01 -4.84671175e-01 -6.60996675e-01 -1.29349098e-01
-2.36287326e-01 -1.40089369e+00 -2.67443389e-01 9.10094827e-02] | [5.738297462463379, 3.740584373474121] |
af00f8dc-4d18-4879-a01a-05df10ee0989 | classification-of-passes-in-football-matches | 1407.5093 | null | http://arxiv.org/abs/1407.5093v1 | http://arxiv.org/pdf/1407.5093v1.pdf | Classification of Passes in Football Matches using Spatiotemporal Data | A knowledgeable observer of a game of football (soccer) can make a subjective
evaluation of the quality of passes made between players during the game. We
investigate the problem of producing an automated system to make the same
evaluation of passes. We present a model that constructs numerical predictor
variables from spatiotemporal match data using feature functions based on
methods from computational geometry, and then learns a classification function
from labelled examples of the predictor variables. Furthermore, the learned
classifiers are analysed to determine if there is a relationship between the
complexity of the algorithm that computed the predictor variable and the
importance of the variable to the classifier. Experimental results show that we
are able to produce a classifier with 85.8% accuracy on classifying passes as
Good, OK or Bad, and that the predictor variables computed using complex
methods from computational geometry are of moderate importance to the learned
classifiers. Finally, we show that the inter-rater agreement on pass
classification between the machine classifier and a human observer is of
similar magnitude to the agreement between two observers. | ['Joël Estephan', 'Michael Horton', 'Sanjay Chawla', 'Joachim Gudmundsson'] | 2014-07-18 | null | null | null | null | ['game-of-football', 'pass-classification'] | ['playing-games', 'playing-games'] | [-3.77566367e-01 6.28456175e-02 -1.32827416e-01 -4.72444206e-01
-8.84878218e-01 -7.30590820e-01 1.53649762e-01 4.46083248e-01
-6.17152810e-01 7.64522433e-01 1.89427175e-02 -1.30200356e-01
-4.68939424e-01 -9.66819406e-01 -5.48398614e-01 -3.75022620e-01
-1.48258284e-01 7.06832409e-01 5.41323066e-01 -3.74386668e-01
6.34320319e-01 3.68099868e-01 -1.82118046e+00 4.78866816e-01
3.63621980e-01 1.26797104e+00 -2.51286477e-01 1.03125107e+00
4.08004522e-01 1.02096212e+00 -7.15976954e-01 -6.88950717e-01
5.82981408e-01 -6.33959830e-01 -1.13458431e+00 5.22472970e-02
1.86756834e-01 2.36048877e-01 1.73024256e-02 6.77172303e-01
6.65602684e-02 5.45997083e-01 8.67297828e-01 -1.30232847e+00
-2.30878294e-01 3.40160966e-01 3.70664429e-03 3.84368509e-01
8.22577775e-01 9.15117413e-02 1.05784392e+00 -6.12025321e-01
5.73263109e-01 6.05992079e-01 1.00238669e+00 8.75291228e-03
-1.00875902e+00 -3.87124240e-01 -2.45149553e-01 6.24229550e-01
-1.66698527e+00 -9.12254229e-02 2.51422256e-01 -8.84272516e-01
7.20491409e-01 5.19151270e-01 1.11326456e+00 1.32301807e-01
1.41722783e-01 2.11691573e-01 1.14770508e+00 -4.46970940e-01
5.19017696e-01 3.50151092e-01 -4.87214178e-02 7.50103414e-01
-1.17395677e-01 4.83522534e-01 -8.80333006e-01 6.78801611e-02
7.76064396e-01 -5.30033231e-01 4.47219796e-02 -1.78755865e-01
-6.92552745e-01 7.47327447e-01 3.99725765e-01 2.48853266e-01
-3.73106211e-01 -3.51787582e-02 2.84030080e-01 5.99043548e-01
3.33076894e-01 9.82450724e-01 -4.67975557e-01 -7.45333672e-01
-9.24439073e-01 6.25920892e-01 1.15097201e+00 6.58421874e-01
7.95213521e-01 -2.73193896e-01 1.91938788e-01 3.92015278e-01
-2.16111138e-01 1.77697882e-01 2.25932762e-01 -1.00698614e+00
1.64064944e-01 9.20596242e-01 2.25557864e-01 -1.40496647e+00
-4.11522478e-01 -3.05511832e-01 1.74410239e-01 8.25027704e-01
8.22927415e-01 7.32117072e-02 -3.10591757e-01 1.10854912e+00
2.88460404e-01 -2.09223524e-01 -1.43689871e-01 1.24856186e+00
6.90494537e-01 1.40983284e-01 -4.26615067e-02 3.21790278e-01
1.10025966e+00 -6.06197476e-01 -1.78001970e-01 -6.37535527e-02
8.19648802e-01 -7.46026099e-01 9.74149406e-01 7.60212183e-01
-1.19742465e+00 -1.04023087e+00 -1.09087443e+00 3.59309465e-02
-2.80286193e-01 3.00833017e-01 6.46895528e-01 5.56623816e-01
-6.99960113e-01 9.10214007e-01 -8.80440474e-01 -1.32412940e-01
-1.78227127e-01 5.61980724e-01 -6.27323091e-01 4.54600155e-01
-9.44673121e-01 1.53130472e+00 5.29003322e-01 -1.94906909e-02
-6.45789862e-01 -5.13517022e-01 -8.95095170e-01 -5.84366806e-02
2.10488677e-01 -1.09289445e-01 1.23397803e+00 -1.39857817e+00
-1.29896307e+00 1.15593624e+00 7.67410398e-02 -2.13001698e-01
6.66959703e-01 -1.16059855e-01 -2.81511754e-01 1.13522753e-01
3.88754219e-01 -6.22619782e-03 3.70636374e-01 -9.47355986e-01
-1.16969311e+00 -1.92394108e-01 4.55860525e-01 3.84396642e-01
3.29322994e-01 2.58813277e-02 -1.83343992e-01 -1.26100630e-01
3.55471820e-01 -8.97682548e-01 -5.57846949e-02 2.01866418e-01
1.74180388e-01 -3.63547653e-01 3.73563208e-02 -8.15592647e-01
1.23741984e+00 -2.10041285e+00 1.68868437e-01 7.27251649e-01
2.01732188e-01 -1.22587010e-02 3.68055671e-01 3.10030669e-01
-1.78688958e-01 -1.58102140e-01 1.41532451e-01 4.16902810e-01
-1.96466997e-01 1.98013976e-01 2.02170819e-01 6.76798582e-01
-7.09204823e-02 4.17636901e-01 -8.46165180e-01 -5.35219371e-01
1.59943536e-01 -3.90583314e-02 -5.46302736e-01 4.53832328e-01
3.11749578e-01 2.27392495e-01 -4.44923639e-01 3.48478049e-01
-2.09406787e-03 2.88641334e-01 1.01597741e-01 2.18162686e-03
-1.28052384e-01 2.48435199e-01 -1.63255227e+00 1.20472705e+00
-2.72082686e-01 6.96778119e-01 -1.70728818e-01 -1.09425259e+00
1.37736559e+00 2.66166925e-01 7.62563124e-02 -5.82336605e-01
2.78525740e-01 2.83990800e-01 1.94117472e-01 -8.57680440e-01
6.45699322e-01 -5.20475864e-01 -3.66349161e-01 3.66336167e-01
1.59583330e-01 -5.37800550e-01 3.20348382e-01 -1.54674664e-01
1.04107618e+00 2.52164274e-01 4.56108838e-01 -2.68368036e-01
4.35213655e-01 5.06282985e-01 4.67425257e-01 8.27425063e-01
-1.68421596e-01 4.96534675e-01 6.91501081e-01 -1.01753438e+00
-1.03655028e+00 -9.69638824e-01 3.31356972e-01 1.21690047e+00
3.30984712e-01 -4.91305530e-01 -7.08400309e-01 -2.36675903e-01
-2.31599174e-02 4.75343555e-01 -7.94553876e-01 -3.57629776e-01
-4.40438956e-01 -4.16508764e-02 5.01936376e-01 8.99155200e-01
1.77300885e-01 -8.89418721e-01 -8.77953351e-01 1.90290481e-01
-2.46826023e-01 -8.68209302e-01 -2.97235157e-02 1.44863665e-01
-5.46551108e-01 -1.46120882e+00 1.38398245e-01 -7.83917308e-01
5.26089728e-01 -2.45659515e-01 1.24669361e+00 6.94468975e-01
-2.80008703e-01 3.13030362e-01 -6.67587817e-01 -2.82868385e-01
-4.14132208e-01 8.15982521e-02 2.48344049e-01 -2.02378169e-01
5.66038668e-01 -2.64536917e-01 -2.67131209e-01 8.22217643e-01
-3.66759658e-01 -5.79160079e-02 1.88252866e-01 5.54097295e-01
4.82414097e-01 3.93879116e-01 -5.79661923e-03 -4.41407591e-01
6.33071065e-01 -2.19723701e-01 -3.51952434e-01 2.23620892e-01
-2.20408380e-01 -6.27781125e-03 5.31979322e-01 -4.76332724e-01
-7.54349411e-01 2.85993278e-01 9.49261859e-02 3.67635153e-02
-2.87746191e-01 7.55210102e-01 2.63802618e-01 -3.50807637e-01
1.24700654e+00 -1.65749848e-01 -1.52994636e-02 -2.67255634e-01
9.00426060e-02 5.41518390e-01 7.45077431e-01 -9.56523716e-01
8.94919932e-01 2.48268679e-01 1.59771666e-01 -4.13109541e-01
-8.30064297e-01 -6.58600152e-01 -1.01891744e+00 -8.13490868e-01
7.89181113e-01 -6.49287105e-01 -1.09179211e+00 1.99190825e-01
-6.12580717e-01 -3.48499238e-01 -4.88264531e-01 9.77647424e-01
-1.00861299e+00 -1.09628171e-01 -4.28069502e-01 -8.38243127e-01
2.55491972e-01 -8.56541157e-01 5.43484747e-01 3.41592878e-01
-8.24854970e-01 -8.78102541e-01 1.71474308e-01 6.89390123e-01
7.17778653e-02 2.22645044e-01 6.88365936e-01 -8.47741187e-01
-1.30495414e-01 -9.59417105e-01 1.88721567e-01 2.32031256e-01
-1.48005664e-01 1.93817739e-03 -6.45954669e-01 9.42591429e-02
-3.82889733e-02 -3.95438850e-01 1.40962794e-01 1.69588864e-01
8.50787818e-01 3.39034721e-02 6.02458678e-02 4.35138881e-01
1.23356366e+00 5.84010966e-02 6.03442669e-01 5.84778070e-01
2.52963930e-01 7.44910777e-01 1.11250830e+00 4.15880270e-02
2.21751735e-01 8.33852530e-01 -7.44408667e-02 -1.79511979e-01
2.38687679e-01 -4.39557612e-01 8.72259669e-04 5.18759310e-01
-8.92342865e-01 4.00977194e-01 -9.77718711e-01 4.93795425e-01
-1.86969626e+00 -1.04344440e+00 -3.63954276e-01 2.17356777e+00
5.93881428e-01 5.16243637e-01 5.25631845e-01 8.30715001e-01
6.41943097e-01 -5.24027050e-01 3.29174474e-02 -9.38541412e-01
4.81289834e-01 5.32200933e-01 6.29750371e-01 6.57153964e-01
-9.66739655e-01 8.05139124e-01 7.09232473e+00 9.16852295e-01
-6.25961065e-01 -2.41528034e-01 3.51223081e-01 -1.10499039e-01
5.69044769e-01 3.05683345e-01 -3.89928252e-01 8.21120143e-02
7.94562817e-01 -5.37429690e-01 4.86711651e-01 1.08322299e+00
1.01334944e-01 -5.70841372e-01 -1.28600848e+00 5.56568682e-01
1.67267486e-01 -1.03845656e+00 -4.59146291e-01 -1.49150074e-01
4.20914292e-01 -6.85931206e-01 -3.05599123e-01 3.71420830e-01
3.39320779e-01 -1.30987370e+00 1.12904119e+00 8.97107065e-01
4.86051291e-01 -8.55625570e-01 9.94177818e-01 6.62577033e-01
-1.39815950e+00 -5.54288626e-02 -2.11795941e-01 -1.18326807e+00
-1.35567278e-01 -1.15705825e-01 -9.99543607e-01 2.59168625e-01
7.40761757e-01 3.30045432e-01 -6.52744472e-01 1.27802241e+00
-5.28041899e-01 6.77730262e-01 -3.77499431e-01 -2.86178082e-01
4.47466858e-02 6.25155270e-02 2.84485579e-01 9.40685630e-01
5.44192903e-02 5.57127714e-01 4.41574544e-01 6.37374043e-01
7.04169989e-01 2.41928980e-01 -2.66658008e-01 4.35590625e-01
2.63402194e-01 9.76283312e-01 -9.66891050e-01 -3.00043821e-01
-1.04395136e-01 4.83357549e-01 4.71676379e-01 -8.95792544e-02
-5.37309647e-01 -3.82206410e-01 5.63054681e-01 5.76003373e-01
1.81937829e-01 -1.22622900e-01 -6.38035357e-01 -6.09905958e-01
3.09948832e-01 -8.04340839e-01 4.69854206e-01 -9.90523458e-01
-1.14680719e+00 5.86971164e-01 3.40891071e-02 -1.49513793e+00
-3.27502131e-01 -6.90097153e-01 -6.81910098e-01 1.07982838e+00
-5.36850214e-01 -7.57185161e-01 -3.50421250e-01 3.48182559e-01
3.11108269e-02 -2.06146538e-01 8.14819157e-01 -1.02779239e-01
1.41442180e-01 5.12356937e-01 -5.35214901e-01 6.03297472e-01
2.66755402e-01 -1.29068935e+00 1.65552814e-02 5.80672860e-01
5.98795936e-02 2.53443986e-01 1.00566602e+00 -6.24086142e-01
-8.49622130e-01 -3.43358845e-01 9.12211359e-01 -7.69955993e-01
6.44872189e-01 5.91680780e-02 -7.83097565e-01 5.11525631e-01
-6.66689277e-01 -3.59888338e-02 8.81978095e-01 5.36324918e-01
-1.94764540e-01 -3.69020179e-02 -1.11857188e+00 7.20686316e-02
8.54932070e-01 -7.71165073e-01 -9.25588250e-01 -2.72902213e-02
-2.50009596e-01 -7.87071645e-01 -1.13056803e+00 1.99267883e-02
8.05208385e-01 -1.08687758e+00 8.19876969e-01 -1.03162742e+00
5.91022909e-01 -4.29441720e-01 -5.56045398e-02 -1.28447521e+00
-4.18032110e-01 1.22709721e-02 6.09283507e-01 5.83005309e-01
5.58197916e-01 -1.26491070e-01 1.08207178e+00 1.12780726e+00
1.36104554e-01 -6.84250116e-01 -1.08658099e+00 -7.21830487e-01
6.21258691e-02 -6.82958007e-01 2.91291952e-01 7.81610787e-01
5.99114537e-01 -1.35654276e-02 -3.28313023e-01 2.23211423e-01
2.29952693e-01 1.13399863e-01 1.10328925e+00 -1.29546905e+00
-5.95286906e-01 -2.46566072e-01 -1.59154928e+00 -6.00017071e-01
-1.62101179e-01 -7.89989173e-01 2.81327635e-01 -1.28423190e+00
-4.55625094e-02 -3.45797539e-01 1.11010252e-02 3.53610367e-01
-2.39490673e-01 3.15605164e-01 1.42424792e-01 3.52083072e-02
-5.93883812e-01 -2.43705168e-01 9.52693522e-01 3.80883425e-01
-2.80906498e-01 3.52192700e-01 -6.15709126e-01 1.02759862e+00
5.55542171e-01 -7.64052451e-01 5.17545789e-02 -1.80409893e-01
6.67766571e-01 4.23086524e-01 6.14528716e-01 -1.36143756e+00
3.76744151e-01 -3.49047422e-01 5.83669901e-01 1.09607399e-01
3.04458648e-01 -7.24256694e-01 3.20371509e-01 4.71144348e-01
-5.87164283e-01 6.50739148e-02 -1.57150757e-02 2.04227731e-01
-3.29567343e-01 -5.16365409e-01 4.49424267e-01 -3.05158705e-01
-7.68400967e-01 -2.69202143e-01 -4.82857853e-01 1.24417856e-01
9.44093823e-01 -6.16268277e-01 3.14273149e-01 -6.29125357e-01
-1.22226083e+00 3.47715728e-02 4.02754456e-01 7.43976757e-02
3.46754104e-01 -1.08469009e+00 -8.70991647e-01 1.00418352e-01
1.63281277e-01 -5.54372728e-01 -1.37058616e-01 6.65414453e-01
-1.00296545e+00 -3.08918804e-02 -4.40360576e-01 -3.02312553e-01
-1.49803269e+00 2.37559691e-01 6.36819780e-01 -1.57997563e-01
-3.90700907e-01 8.80864322e-01 -5.25723994e-01 -4.31080699e-01
2.04256047e-02 -2.58509278e-01 -2.10793361e-01 -5.27537242e-02
5.21931529e-01 5.90015292e-01 2.67593116e-01 -8.92076492e-01
-1.86065912e-01 8.52721035e-01 3.72328371e-01 -3.12777370e-01
1.25435686e+00 2.54079819e-01 3.51376265e-01 6.21343732e-01
8.31729591e-01 -1.83611438e-01 -1.11204910e+00 -1.23483919e-01
-1.05437085e-01 -8.75268877e-01 -1.01721719e-01 -8.10603559e-01
-8.93930972e-01 6.60655379e-01 4.42385584e-01 4.06818122e-01
9.10581708e-01 2.24727876e-02 2.57024199e-01 4.40501094e-01
8.16717863e-01 -1.57080495e+00 -1.84069216e-01 3.07122439e-01
7.26156592e-01 -1.12598073e+00 3.71065348e-01 -4.30018604e-01
-1.01673222e+00 1.21231174e+00 6.73695624e-01 -6.59084678e-01
6.68445230e-01 1.84478879e-01 1.95555687e-01 -4.87866640e-01
-5.15839577e-01 -2.85585463e-01 7.25606859e-01 6.33326054e-01
2.91087359e-01 4.37615156e-01 -7.04027951e-01 7.89823472e-01
-1.08903229e+00 3.12469691e-01 5.45336187e-01 8.67205977e-01
-5.82903326e-01 -6.48954809e-01 -4.59952861e-01 4.46126699e-01
-2.24353015e-01 3.86449307e-01 -3.88833672e-01 8.90238106e-01
5.73783994e-01 1.03814161e+00 2.68341810e-01 -7.87149668e-01
6.73781693e-01 -4.66462970e-02 4.85992819e-01 -7.27779984e-01
-1.10632038e+00 -5.38716733e-01 4.35447514e-01 -5.98054886e-01
-4.05860722e-01 -5.92524290e-01 -1.18721712e+00 -4.93722886e-01
-4.57700670e-01 7.46129274e-01 6.06832147e-01 1.31419694e+00
-5.20762622e-01 2.76713613e-02 5.58999777e-01 -7.71406531e-01
-2.16432542e-01 -6.45607054e-01 -8.09645236e-01 6.84004068e-01
-1.56863421e-01 -1.03093481e+00 -6.19279742e-01 2.47606441e-01] | [6.6689252853393555, 0.4043344259262085] |
7938246e-fb40-4d25-a836-81be6e159814 | hospital-transfer-risk-prediction-for-covid | 2301.01596 | null | https://arxiv.org/abs/2301.01596v1 | https://arxiv.org/pdf/2301.01596v1.pdf | Hospital transfer risk prediction for COVID-19 patients from a medicalized hotel based on Diffusion GraphSAGE | The global COVID-19 pandemic has caused more than six million deaths worldwide. Medicalized hotels were established in Taiwan as quarantine facilities for COVID-19 patients with no or mild symptoms. Due to limited medical care available at these hotels, it is of paramount importance to identify patients at risk of clinical deterioration. This study aimed to develop and evaluate a graph-based deep learning approach for progressive hospital transfer risk prediction in a medicalized hotel setting. Vital sign measurements were obtained for 632 patients and daily patient similarity graphs were constructed. Inductive graph convolutional network models were trained on top of the temporally integrated graphs to predict hospital transfer risk. The proposed models achieved AUC scores above 0.83 for hospital transfer risk prediction based on the measurements of past 1, 2, and 3 days, outperforming baseline machine learning methods. A post-hoc analysis on the constructed diffusion-based graph using Local Clustering Coefficient discovered a high-risk cluster with significantly older mean age, higher body temperature, lower SpO2, and shorter length of stay. Further time-to-hospital-transfer survival analysis also revealed a significant decrease in survival probability in the discovered high-risk cluster. The obtained results demonstrated promising predictability and interpretability of the proposed graph-based approach. This technique may help preemptively detect high-risk patients at community-based medical facilities similar to a medicalized hotel. | ['Fang-Ming Hung', 'Ling Chen', 'Kuan-Chia Ling', 'Chih-Ho Hsu', 'Jun-En Ding'] | 2022-12-31 | null | null | null | null | ['survival-analysis'] | ['miscellaneous'] | [-2.09016994e-01 -2.33161021e-02 2.84314305e-02 1.28378302e-01
-3.66126269e-01 -2.07572535e-01 -1.15451261e-01 1.18720138e+00
-4.18224037e-01 4.89548653e-01 1.88896269e-01 -7.25243092e-01
-8.37284863e-01 -9.41835701e-01 -2.95192972e-02 -7.66470373e-01
-1.16636801e+00 6.57035589e-01 -2.10141271e-01 -1.40749186e-01
-1.40299082e-01 7.80577183e-01 -5.00181913e-01 2.09699348e-01
9.69907820e-01 8.17631662e-01 9.43641812e-02 8.73003364e-01
6.02317572e-01 8.21007788e-01 -5.71741641e-01 -3.81844467e-03
1.59303233e-01 -7.37429976e-01 -4.16196287e-01 -5.33593774e-01
-3.77116650e-01 -3.31402302e-01 -3.85505170e-01 1.67187169e-01
5.69266140e-01 1.53451607e-01 8.96079719e-01 -1.17810690e+00
-2.07382306e-01 2.34718099e-01 1.76238734e-02 6.19021714e-01
-2.50791758e-02 4.78943065e-02 5.72540700e-01 -3.25907320e-01
1.02057844e-01 4.20751125e-01 1.02739549e+00 2.83865929e-01
-8.53898644e-01 -5.07664204e-01 -3.18797767e-01 6.94519505e-02
-1.48057234e+00 2.89688885e-01 5.36800563e-01 -6.18673027e-01
1.03566706e+00 1.36368573e-01 1.17729330e+00 8.55015159e-01
9.21867549e-01 -2.48031676e-01 4.94584054e-01 1.66343823e-01
-8.57172608e-02 -2.81284720e-01 -1.53707728e-01 1.11877525e+00
7.09380448e-01 -3.03015746e-02 5.97121567e-03 -5.18211544e-01
8.03165436e-01 8.99834812e-01 -3.94969374e-01 -1.89540282e-01
-1.50285566e+00 9.49246645e-01 8.34071517e-01 4.46947932e-01
-8.58793557e-01 -1.51989400e-01 7.38326788e-01 1.90806493e-01
4.65703458e-01 5.42444825e-01 -4.90116626e-01 4.66852915e-03
-5.75848341e-01 -4.64342117e-01 5.78033388e-01 4.45617169e-01
4.12511602e-02 8.63165110e-02 -2.10526809e-01 4.17312473e-01
1.47020385e-01 5.35709143e-01 4.19587344e-01 -5.43920159e-01
3.59326065e-01 7.73692071e-01 -6.71812007e-03 -1.37653911e+00
-1.27656746e+00 -6.42108381e-01 -1.43545878e+00 -4.93625134e-01
4.62285839e-02 -6.21743381e-01 -5.85562646e-01 1.30576444e+00
-4.47736681e-02 2.32420400e-01 1.57782495e-01 6.43758893e-01
5.12801111e-01 4.75564212e-01 1.51351839e-01 -5.23579955e-01
1.08111548e+00 -7.01022387e-01 -5.47750890e-01 3.87700170e-01
1.19828761e+00 1.23542637e-01 5.72173834e-01 2.48455927e-02
-6.23377085e-01 -1.91787869e-01 -7.69568026e-01 8.19986224e-01
-2.72950977e-01 -2.53539920e-01 2.25146636e-01 5.08621335e-01
-1.25683367e+00 9.55509126e-01 -9.70142603e-01 -8.39401662e-01
4.39454108e-01 4.15155321e-01 -2.98091084e-01 3.01907975e-02
-1.30294156e+00 8.26676250e-01 1.35266349e-01 2.81785756e-01
-1.05160725e+00 -5.94542861e-01 -9.54847157e-01 1.35459736e-01
-2.32218921e-01 -1.19655955e+00 4.67690229e-01 -9.45775434e-02
-6.49073303e-01 7.06944108e-01 3.25201638e-02 -5.04517615e-01
4.81580764e-01 -7.83615559e-02 -5.08156061e-01 4.66084749e-01
-5.59343435e-02 -1.88561618e-01 3.87894452e-01 -1.00539327e+00
-2.63504088e-01 -4.36614811e-01 -3.43764037e-01 3.45356792e-01
-4.27856356e-01 -1.90996900e-01 3.56963515e-01 -3.59872669e-01
-1.92979261e-01 -9.07421112e-01 -4.66165662e-01 -5.02945960e-01
-1.28933206e-01 -1.68516133e-02 5.69402874e-01 -7.86912978e-01
1.37760127e+00 -1.83290946e+00 -2.28714511e-01 4.08040076e-01
7.77118921e-01 1.66846827e-01 9.41657498e-02 7.12303579e-01
-7.17026442e-02 3.59865248e-01 -2.15218231e-01 1.41933188e-01
-6.75363839e-01 -1.04689673e-01 3.21983367e-01 9.40612793e-01
-3.62754725e-02 9.08297300e-01 -1.35432184e+00 -5.73916674e-01
5.28627217e-01 6.19040430e-01 -3.87680531e-01 6.39243066e-01
6.04780138e-01 8.53853047e-01 -3.43988925e-01 5.43501616e-01
1.63136289e-01 -7.03936696e-01 4.00851965e-01 2.14800969e-01
2.77332276e-01 -7.07439333e-02 1.23735229e-02 1.27667546e+00
-3.05241495e-01 7.02360392e-01 -1.89193144e-01 -9.96611774e-01
1.08013165e+00 6.62380219e-01 1.34996104e+00 -4.22146797e-01
4.91626322e-01 -9.47502777e-02 1.56867713e-01 -8.63138080e-01
-3.30677256e-02 -2.96915740e-01 -6.06588125e-02 3.47957492e-01
-6.76566601e-01 1.06219567e-01 -3.83823097e-01 2.14578375e-01
1.32142162e+00 -4.92630720e-01 4.02442664e-01 -4.96718705e-01
3.93455297e-01 2.02141032e-01 3.88966113e-01 5.19006550e-01
-6.58313990e-01 3.82493824e-01 4.11912709e-01 -6.81066632e-01
-6.79053128e-01 -1.15696239e+00 2.92018298e-02 5.97439051e-01
2.42654204e-01 -2.58345336e-01 -4.91049618e-01 -6.02967322e-01
-1.84170231e-01 6.49672031e-01 -7.36910820e-01 -6.93086922e-01
-7.47631848e-01 -8.82436335e-01 6.33768141e-01 5.96289873e-01
2.07382306e-01 -8.89201403e-01 -9.39928472e-01 4.23714191e-01
-4.66436982e-01 -5.41680932e-01 -3.18577170e-01 1.58304453e-01
-1.22378385e+00 -1.39903891e+00 -8.81706595e-01 -1.06999791e+00
7.32877254e-01 3.16700727e-01 8.62775326e-01 4.60616618e-01
-5.20305991e-01 5.45649409e-01 -1.47469521e-01 -4.71913069e-01
-5.70190072e-01 5.22410683e-03 3.25193793e-01 -1.80785149e-01
3.77305895e-01 -4.16378200e-01 -1.44074535e+00 4.04796630e-01
-5.38209319e-01 -2.61146694e-01 2.56710529e-01 6.77166164e-01
3.69904429e-01 7.36158714e-02 9.00756598e-01 -3.22487742e-01
1.03464425e+00 -1.13164711e+00 1.00714583e-02 7.23812357e-02
-1.11867630e+00 -4.28639263e-01 7.54670084e-01 3.84852737e-02
-2.62609094e-01 -5.03564358e-01 4.06507671e-01 -5.02720237e-01
-4.43557724e-02 6.60087228e-01 7.77593195e-01 5.85001886e-01
5.85765898e-01 3.92315052e-02 2.21601412e-01 1.82783723e-01
-5.23666263e-01 6.18413985e-01 1.74628198e-01 -4.27081138e-02
4.22268420e-01 3.56780410e-01 5.18477321e-01 -7.45366573e-01
-2.54639655e-01 -8.79997730e-01 -8.29637647e-01 -5.65495670e-01
1.54058492e+00 -9.18092668e-01 -1.13695741e+00 3.38677764e-01
-8.96443844e-01 -6.86770976e-01 8.88711289e-02 8.88692379e-01
-2.74298280e-01 1.47817358e-01 -5.74470103e-01 -6.57548130e-01
-7.27636993e-01 -7.10499406e-01 5.93039274e-01 -1.69375941e-01
-4.10234243e-01 -1.76326895e+00 4.60649014e-01 2.82277107e-01
5.84555268e-01 1.03707862e+00 1.24988043e+00 -9.16850686e-01
-1.25492692e-01 -5.36400199e-01 -1.28651455e-01 1.98343322e-01
8.44975770e-01 -2.05108538e-01 -4.48423296e-01 -7.87433445e-01
-1.84026703e-01 3.31508487e-01 4.31785882e-01 6.66429937e-01
1.00226319e+00 -2.46730864e-01 -7.04625130e-01 6.43826187e-01
1.25095594e+00 8.14013720e-01 1.43502399e-01 1.10315368e-01
8.52413714e-01 4.45848584e-01 1.70340598e-01 7.67845094e-01
5.52359819e-01 -4.68763672e-02 7.87106812e-01 -2.49952137e-01
4.19573545e-01 -1.85582265e-02 1.55805528e-01 1.26860952e+00
-6.49973571e-01 -5.54161310e-01 -1.61137211e+00 7.87906885e-01
-1.38194299e+00 -8.93231094e-01 -4.80467767e-01 2.37264204e+00
3.50321755e-02 -3.02273303e-01 2.11001962e-01 -1.20696336e-01
8.18256378e-01 -8.57965127e-02 -4.94981289e-01 -5.18380582e-01
2.91786790e-01 -1.58968613e-01 5.36092103e-01 1.44480094e-01
-8.00716043e-01 1.64576530e-01 6.38814878e+00 -3.62158895e-01
-1.11951435e+00 -7.35740662e-02 8.33014190e-01 -8.33917633e-02
1.19168080e-01 -3.76877815e-01 3.56656015e-02 1.96446076e-01
1.36617696e+00 -3.00061822e-01 3.01921278e-01 5.33126175e-01
6.38180137e-01 3.62989455e-01 -1.08028734e+00 8.08327556e-01
1.65967330e-01 -1.16084957e+00 -1.15283035e-01 2.17351869e-01
5.78453898e-01 2.85874903e-01 -1.38486624e-01 5.69307320e-02
1.46511227e-01 -1.21608758e+00 -2.56316364e-01 6.46057010e-01
1.20817089e+00 -8.09654295e-01 1.03189850e+00 1.63490102e-01
-1.41734624e+00 -2.73286730e-01 1.24786586e-01 1.24802433e-01
1.96934372e-01 1.83516383e-01 -1.56551814e+00 5.16519368e-01
7.15451002e-01 7.25654721e-01 -2.92050540e-01 8.99908841e-01
1.10220104e-01 6.05757594e-01 -1.13701187e-01 -1.59893781e-01
1.50285199e-01 -2.01682687e-01 4.38343078e-01 1.13202894e+00
6.16826713e-01 2.08811536e-01 -4.09154408e-03 4.63496596e-01
7.09474832e-02 9.52727348e-02 -1.34873009e+00 -5.91733307e-03
1.10624880e-01 9.02534127e-01 -9.22435284e-01 -3.14733207e-01
-2.38335267e-01 9.32849467e-01 1.88651960e-02 4.35828000e-01
-1.08655727e+00 -5.95441997e-01 4.30023700e-01 5.92017114e-01
-2.92761922e-01 -3.96224201e-01 -3.32696110e-01 -9.41950500e-01
-6.07142687e-01 -2.15730056e-01 7.68057287e-01 -5.10134995e-01
-9.95150864e-01 8.16907465e-01 -3.38469595e-02 -1.36956978e+00
-3.48586977e-01 -2.23580271e-01 -9.74467099e-01 7.34137893e-01
-1.46893632e+00 -5.43067992e-01 -8.89568329e-01 1.00302351e+00
1.64194256e-01 -6.37547076e-02 1.27246261e+00 6.96042851e-02
-6.21761858e-01 3.79034460e-01 1.88405335e-01 4.46706265e-01
4.01514411e-01 -9.01404858e-01 -7.70082995e-02 4.45500821e-01
-9.24709201e-01 9.18967664e-01 -2.54994463e-02 -1.04602289e+00
-1.03006613e+00 -1.56027174e+00 9.18455601e-01 -3.58117014e-01
6.79229975e-01 2.38420125e-02 -8.03184509e-01 5.95173776e-01
2.22219214e-01 -1.89079583e-01 1.13406265e+00 -3.45635295e-01
2.13667378e-01 7.04895705e-02 -1.21342158e+00 4.52111781e-01
9.83691752e-01 -4.26333308e-01 -4.98163849e-01 6.27457857e-01
7.91388869e-01 1.28038615e-01 -1.36367536e+00 6.75414324e-01
2.68403411e-01 -7.32618034e-01 7.70545602e-01 -7.35691488e-01
1.30502164e-01 2.28085145e-01 1.89904541e-01 -1.44602323e+00
-6.62636161e-01 -6.61274672e-01 2.80735910e-01 1.29852787e-01
3.64074737e-01 -1.06632352e+00 4.50340778e-01 4.30194229e-01
-3.83704662e-01 -9.53440845e-01 -7.11489916e-01 -8.12671125e-01
1.32396147e-01 1.45653989e-02 4.49898332e-01 1.09772480e+00
2.37322301e-01 1.93720683e-01 -8.12524259e-02 3.00550997e-01
5.28582215e-01 -1.21865068e-02 1.91734463e-01 -1.45678067e+00
1.96421236e-01 -4.30061162e-01 -4.05740082e-01 -9.47917178e-02
-2.31896549e-01 -1.27205944e+00 -1.79573998e-01 -2.46473932e+00
1.16393492e-01 -5.78638732e-01 -1.14093077e+00 4.68150854e-01
-1.54259577e-01 -1.42304704e-01 -2.16894299e-01 2.94954747e-01
-2.00091019e-01 3.74806494e-01 1.34208035e+00 -6.60737827e-02
-7.32170165e-01 6.03492036e-02 -1.85776889e-01 4.19745237e-01
1.35974765e+00 -5.94612598e-01 -6.68751121e-01 -2.28130609e-01
1.95298105e-01 6.66992426e-01 3.23971838e-01 -1.10834026e+00
-4.17909101e-02 -4.17405218e-01 3.45984489e-01 -3.98625821e-01
3.88826542e-02 -1.01293993e+00 1.82219103e-01 1.30559123e+00
-9.93441865e-02 7.20898449e-01 3.36825192e-01 6.34908557e-01
5.86989224e-02 6.21607363e-01 6.51141584e-01 6.93329871e-02
-7.44003430e-02 7.21879065e-01 -9.57175076e-01 1.07970774e-01
1.60867858e+00 -2.99220413e-01 -3.72223407e-01 -3.80187243e-01
-6.50526762e-01 7.18493238e-02 2.59906739e-01 3.60876173e-01
1.03359413e+00 -1.12140417e+00 -9.21616375e-01 2.22336248e-01
2.13064983e-01 1.48608670e-01 5.28204918e-01 1.47810066e+00
-1.21553290e+00 4.19035465e-01 -1.02855012e-01 -6.28747344e-01
-1.13948750e+00 8.20856750e-01 4.97400254e-01 -3.47442806e-01
-9.05715823e-01 5.34429789e-01 2.79116422e-01 -6.63716123e-02
1.31856456e-01 -4.27738845e-01 -2.37213790e-01 8.82209390e-02
1.56824455e-01 6.75954700e-01 -2.45092250e-02 -5.57149351e-01
-6.98109388e-01 4.53243732e-01 4.63560253e-01 5.71374595e-01
1.32836080e+00 -1.48753420e-01 -2.27261111e-01 4.36562866e-01
1.49215186e+00 -3.81670237e-01 -7.31508791e-01 3.41292679e-01
-3.34370941e-01 4.89855297e-02 -1.77440912e-01 -4.91493434e-01
-1.05659962e+00 8.60790968e-01 8.56380403e-01 4.63714808e-01
1.11606693e+00 -3.68976370e-02 9.53008294e-01 4.07153606e-01
2.48921573e-01 -4.49708164e-01 2.05211550e-01 3.70069563e-01
5.74192762e-01 -1.15086293e+00 -2.65521854e-01 1.67599156e-01
-5.45034170e-01 1.07303190e+00 2.66736597e-01 -1.58417866e-01
9.69740391e-01 -1.87505797e-01 2.46310368e-01 -7.28846788e-01
-5.03726542e-01 4.54970509e-01 3.81299928e-02 9.05542910e-01
3.44467014e-01 5.99120200e-01 1.69241317e-02 3.24413717e-01
5.36109954e-02 -1.75563842e-01 4.97698545e-01 8.60551238e-01
-3.21388423e-01 -1.34904221e-01 -1.52125463e-01 8.82882178e-01
-3.86340022e-01 -3.28296304e-01 -1.47379458e-01 6.90216959e-01
-1.47533447e-01 1.30567586e+00 1.75676659e-01 -7.55032957e-01
2.84444571e-01 2.05412805e-01 -4.37758751e-02 -3.94956917e-01
-7.36791790e-01 -3.02764446e-01 -9.43559706e-02 -4.58315879e-01
-2.93296218e-01 -2.59256721e-01 -1.73327291e+00 -3.37944776e-01
6.98224604e-02 4.25053507e-01 6.22914732e-01 3.18353057e-01
7.14203119e-01 9.82245147e-01 8.64321291e-01 -4.09877568e-01
2.22338457e-02 -8.63154411e-01 -7.55338609e-01 2.40710258e-01
8.53484035e-01 -2.65037090e-01 -6.47164285e-01 -9.12475884e-02] | [7.9308271408081055, 6.19534969329834] |
72c68025-24b1-4f7a-90fa-c428e074db94 | a-survey-of-algorithms-for-black-box-safety | 2005.02979 | null | https://arxiv.org/abs/2005.02979v3 | https://arxiv.org/pdf/2005.02979v3.pdf | A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems | Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-critical applications, but require rigorous testing before deployment. The complexity of these systems often precludes the use of formal verification and real-world testing can be too dangerous during development. Therefore, simulation-based techniques have been developed that treat the system under test as a black box operating in a simulated environment. Safety validation tasks include finding disturbances in the environment that cause the system to fail (falsification), finding the most-likely failure, and estimating the probability that the system fails. Motivated by the prevalence of safety-critical artificial intelligence, this work provides a survey of state-of-the-art safety validation techniques for CPS with a focus on applied algorithms and their modifications for the safety validation problem. We present and discuss algorithms in the domains of optimization, path planning, reinforcement learning, and importance sampling. Problem decomposition techniques are presented to help scale algorithms to large state spaces, which are common for CPS. A brief overview of safety-critical applications is given, including autonomous vehicles and aircraft collision avoidance systems. Finally, we present a survey of existing academic and commercially available safety validation tools. | ['Robert J. Moss', 'Ritchie Lee', 'Mykel J. Kochenderfer', 'Mark Koren', 'Anthony Corso'] | 2020-05-06 | null | null | null | null | ['problem-decomposition'] | ['miscellaneous'] | [ 3.50181133e-01 3.99396718e-01 -3.55388463e-01 5.50081604e-04
-4.99957412e-01 -4.71579820e-01 4.05034244e-01 2.58169860e-01
8.72440711e-02 1.16596639e+00 -6.00559711e-01 -1.03780067e+00
-4.75256145e-01 -7.71846294e-01 -6.53320611e-01 -4.80283082e-01
-5.53718328e-01 3.54723305e-01 6.88918829e-01 -3.46673638e-01
5.29796534e-06 6.59127951e-01 -1.71864772e+00 -3.73078167e-01
7.03080058e-01 8.97013187e-01 -2.95586050e-01 6.48225844e-01
5.51892877e-01 5.93770981e-01 -7.55254388e-01 4.34667677e-01
2.49450266e-01 -3.47536922e-01 -8.07018220e-01 8.22131187e-02
-3.42306674e-01 -2.88466603e-01 -2.49334872e-01 1.05054629e+00
-2.27694154e-01 2.79796451e-01 2.45186314e-01 -2.54404664e+00
5.27269602e-01 2.44734406e-01 1.61046773e-01 -3.04456800e-01
4.57288891e-01 6.98982537e-01 4.27647084e-01 2.37649828e-02
2.49557674e-01 1.12508881e+00 3.57778490e-01 6.54178500e-01
-1.17411113e+00 -5.99969327e-01 5.14270604e-01 1.47753358e-01
-1.30083084e+00 -1.70483008e-01 5.89932978e-01 -5.84361196e-01
1.54338682e+00 3.39520693e-01 8.62519920e-01 8.97245884e-01
1.02702773e+00 2.88279980e-01 1.00630569e+00 -3.62500250e-01
7.74893820e-01 -1.48933083e-01 6.10739477e-02 5.84456921e-01
6.58543646e-01 1.13802075e+00 2.46806845e-01 -4.48965788e-01
1.17799141e-01 -1.42517313e-01 1.51878551e-01 -6.93162739e-01
-1.03401184e+00 7.19416082e-01 -2.29554713e-01 -1.45631403e-01
-6.74501732e-02 3.23905826e-01 6.42436385e-01 5.03689647e-01
-2.03864083e-01 6.76610708e-01 -7.45390177e-01 -1.24503925e-01
-5.01291633e-01 7.41015732e-01 1.07372642e+00 1.03195930e+00
3.16110402e-01 6.38236105e-01 9.79686975e-02 -2.66421288e-01
5.68286896e-01 4.11845684e-01 -2.73983181e-01 -1.16629457e+00
-4.38654982e-03 4.21538442e-01 4.37726945e-01 -2.92700320e-01
-3.90595704e-01 5.12559041e-02 -2.53036082e-01 1.24014914e+00
-5.70014715e-02 -4.22661245e-01 -7.59988725e-01 1.50014734e+00
5.97531855e-01 4.41871613e-01 2.23664463e-01 5.75842142e-01
-2.37638697e-01 7.32128263e-01 4.17561717e-02 -6.60309374e-01
8.17435682e-01 -6.48860216e-01 -6.95002496e-01 -4.62675601e-01
5.70396125e-01 -2.50835150e-01 2.93275386e-01 7.07048595e-01
-9.24645722e-01 -3.05608928e-01 -1.68335140e+00 1.16869676e+00
-3.23764384e-01 -7.81836212e-01 4.55755353e-01 6.59627378e-01
-8.14501822e-01 6.56582117e-01 -1.09784162e+00 -4.09298949e-02
2.50642048e-03 6.12626612e-01 -1.44613326e-01 -7.12434873e-02
-1.37260377e+00 1.40756607e+00 4.97723222e-01 -1.05582707e-01
-1.68669677e+00 -6.28537416e-01 -1.24883711e+00 -2.72164196e-01
8.52827072e-01 -3.72313738e-01 1.59806132e+00 -4.25025076e-01
-1.47830582e+00 -1.26678750e-01 3.99632365e-01 -6.56584561e-01
3.17673057e-01 1.64336473e-01 -1.13971090e+00 -1.98961407e-01
-2.39745732e-02 2.22984359e-01 7.67607629e-01 -1.10436237e+00
-9.40453827e-01 6.87775016e-02 3.52777451e-01 -5.39620280e-01
5.75182736e-01 8.46475139e-02 4.91453111e-01 -5.50702401e-03
-2.96287686e-01 -1.27877843e+00 -8.60380471e-01 -3.87560844e-01
-2.88546681e-01 2.07727887e-02 1.02931917e+00 -3.72226894e-01
1.31923020e+00 -2.04010630e+00 -6.93908855e-02 7.08858013e-01
-3.08114409e-01 1.59289643e-01 -1.15324706e-02 8.82083178e-01
-4.10676271e-01 -1.37318000e-01 -3.00089717e-01 4.79168504e-01
1.20887868e-01 4.47645247e-01 -4.78150249e-01 6.39780760e-01
5.99098623e-01 3.34676504e-01 -9.01999593e-01 -3.71330112e-01
6.96711779e-01 -1.97314635e-01 -4.16266143e-01 1.95092022e-01
-6.02045834e-01 5.61907172e-01 -6.01314068e-01 5.95342815e-01
3.67496878e-01 4.56720650e-01 1.19906239e-01 5.51451802e-01
-4.66620386e-01 3.07300717e-01 -1.29521418e+00 7.76664853e-01
-4.57367152e-01 2.31032118e-01 1.44302204e-01 -9.22754824e-01
5.92215419e-01 6.96844995e-01 5.34747005e-01 -5.16005754e-01
3.38300288e-01 5.53602651e-02 2.86832571e-01 -3.21589619e-01
1.90641493e-01 -4.19405133e-01 -6.16326928e-01 2.47543812e-01
-3.38538110e-01 -8.31891656e-01 4.32318419e-01 -2.35253528e-01
1.59219027e+00 3.89241241e-02 6.01424038e-01 -1.66542187e-01
8.42344940e-01 5.61508358e-01 8.94347191e-01 4.27589327e-01
-5.80968738e-01 -3.09505761e-01 8.04363251e-01 -3.35366815e-01
-9.01233017e-01 -8.55096042e-01 -3.68082896e-02 2.79364705e-01
3.01039845e-01 -3.72778118e-01 -6.33724511e-01 -8.25783193e-01
2.54341453e-01 1.31756639e+00 -3.31820607e-01 -9.06186640e-01
-4.35043782e-01 4.14332785e-02 3.47204417e-01 3.25972080e-01
-2.19514802e-01 -9.67284262e-01 -1.01171935e+00 4.33499396e-01
4.65085924e-01 -9.90354896e-01 2.25238293e-01 3.54150116e-01
-8.39709342e-01 -1.43887055e+00 5.07344127e-01 -4.95365053e-01
7.49447584e-01 -1.51308879e-01 6.77844286e-01 1.67443007e-01
-3.96679342e-01 4.87790495e-01 -1.41941175e-01 -6.04945719e-01
-1.14200151e+00 -6.95878565e-01 4.42251235e-01 -6.34839892e-01
-2.17973933e-01 -6.07001707e-02 6.24496937e-02 7.08564937e-01
-8.41023624e-01 -3.90302151e-01 1.86193362e-01 8.32181215e-01
5.77031553e-01 9.19789553e-01 6.61383986e-01 -3.00816834e-01
7.77055979e-01 -2.94370353e-01 -1.41803217e+00 3.29524517e-01
-9.31441784e-01 6.56747669e-02 7.43037105e-01 -3.85336667e-01
-5.99210441e-01 3.08829278e-01 1.59104224e-02 -3.33691299e-01
-4.87527281e-01 4.90189761e-01 -2.51618892e-01 -2.73386210e-01
4.50172633e-01 -1.28725648e-01 4.45607990e-01 3.67567360e-01
-2.64593303e-01 7.66667128e-02 -1.77936926e-02 -6.06309414e-01
9.29740369e-01 -4.54471186e-02 5.50827086e-01 -4.34931099e-01
-2.72960782e-01 -1.72951072e-02 -4.21701893e-02 -5.03444374e-01
3.73299837e-01 -4.56524193e-01 -1.19558990e+00 9.74762142e-02
-7.81878769e-01 -6.59028709e-01 -5.84900022e-01 3.38085353e-01
-8.81189048e-01 1.55837297e-01 -8.24021548e-02 -1.33923900e+00
2.88637131e-01 -1.58926725e+00 8.88812959e-01 -1.67221844e-01
-6.14822507e-01 -5.12059391e-01 5.28970957e-01 -1.27355918e-01
-4.56171017e-03 7.16942608e-01 9.75432456e-01 -4.17734623e-01
-5.45046866e-01 -7.71549463e-01 6.70444727e-01 4.51263934e-01
-7.39246607e-02 4.02746558e-01 -5.55982351e-01 -6.31675959e-01
2.00450551e-02 -4.23646122e-02 -2.54569054e-01 3.30021441e-01
9.53641295e-01 -3.67351204e-01 -6.04594052e-01 -2.44078472e-01
1.18524063e+00 7.81460643e-01 4.52815354e-01 4.02706593e-01
-1.39296219e-01 8.10159862e-01 1.55933869e+00 5.85618496e-01
-1.57513395e-01 5.47133982e-01 1.03739941e+00 3.78847629e-01
5.72808862e-01 7.60505274e-02 6.50342762e-01 -7.84481689e-02
4.01233464e-01 -1.99202187e-02 -1.06410348e+00 4.67819154e-01
-1.92173088e+00 -9.04190779e-01 8.71495008e-02 2.45745564e+00
5.18112123e-01 7.60829270e-01 2.82284558e-01 7.37695456e-01
5.38670421e-01 -4.20114517e-01 -5.88247597e-01 -6.98576868e-01
5.58995783e-01 1.45719558e-01 5.79076350e-01 7.83158302e-01
-1.04958677e+00 5.60869992e-01 6.91328621e+00 3.94082278e-01
-7.98951685e-01 -2.54865408e-01 6.66160807e-02 9.18836221e-02
7.91011602e-02 4.53231007e-01 -6.02642715e-01 1.78290516e-01
1.53817022e+00 -4.58823174e-01 3.65161866e-01 1.13302886e+00
4.62780386e-01 -5.17248333e-01 -1.27940774e+00 1.59470722e-01
-6.01836503e-01 -7.36326635e-01 -6.34718597e-01 -4.74542864e-02
6.79911435e-01 -2.73885816e-01 -1.47228718e-01 5.28437734e-01
5.14497042e-01 -9.04880583e-01 9.89026666e-01 1.20828137e-01
4.87447262e-01 -1.25673962e+00 6.79546833e-01 4.71144915e-01
-1.01504147e+00 -4.45274055e-01 3.44491422e-01 -4.26527172e-01
6.18847668e-01 3.70843172e-01 -9.85509217e-01 4.84719664e-01
4.76479203e-01 2.75655091e-01 -1.44429594e-01 1.18151283e+00
-4.42024797e-01 3.00664216e-01 -2.37408623e-01 -2.35970750e-01
2.22544596e-01 7.65705332e-02 7.84620583e-01 5.89654028e-01
2.43833229e-01 -1.06865149e-02 6.37643397e-01 5.57844579e-01
1.18176186e+00 -8.64720106e-01 -9.55616117e-01 -2.29228348e-01
2.31566533e-01 9.17790294e-01 -6.14039004e-01 -1.57334611e-01
-2.55863011e-01 -6.14794856e-03 -4.69107509e-01 3.09798628e-01
-1.39194584e+00 -4.68359888e-01 1.26596451e+00 2.97405303e-01
-9.82952490e-02 -6.05592787e-01 -2.53123969e-01 -3.01979542e-01
-1.14722893e-01 -1.15105975e+00 2.53061771e-01 -4.87246096e-01
-7.04391897e-01 4.89536077e-01 5.06018460e-01 -1.64434171e+00
-7.06301272e-01 -6.87905967e-01 -5.63910067e-01 5.34848213e-01
-1.09729135e+00 -4.90798116e-01 8.68584663e-02 4.42355901e-01
3.78490031e-01 -7.52117187e-02 7.77718246e-01 -5.82062975e-02
-7.75424123e-01 -4.71070446e-02 -5.12511373e-01 -6.20688617e-01
2.72448987e-01 -6.09610558e-01 4.88732457e-01 1.08475411e+00
-8.64490747e-01 4.97065753e-01 1.39204371e+00 -1.14034438e+00
-1.89996755e+00 -1.22538638e+00 4.21677291e-01 -3.55588019e-01
1.05537641e+00 -3.03751528e-02 -5.02183318e-01 6.45710766e-01
4.05698083e-02 -9.50116888e-02 1.30357072e-01 -1.46374807e-01
6.50232807e-02 -1.44476980e-01 -1.39461946e+00 9.24329817e-01
6.76451206e-01 -1.71004444e-01 -4.90686327e-01 3.01356226e-01
9.07042563e-01 -2.83320427e-01 -5.92151880e-01 7.94583857e-01
1.42415211e-01 -4.00324494e-01 7.38597810e-01 -9.17155445e-01
-2.61694908e-01 -8.71548414e-01 1.76871732e-01 -1.30750859e+00
-3.12082797e-01 -9.21784461e-01 -4.39683139e-01 4.85198647e-01
4.77728456e-01 -9.07127202e-01 2.76762933e-01 9.08254743e-01
-6.47253036e-01 -6.04166746e-01 -1.24060035e+00 -1.36863756e+00
-2.99840331e-01 -7.63948917e-01 6.10413373e-01 5.63719511e-01
7.25555420e-01 -2.51052734e-02 2.04244815e-02 6.31986141e-01
5.77878237e-01 -4.87183370e-02 3.96543205e-01 -1.08024430e+00
-1.90844119e-01 -3.33801568e-01 -5.51656127e-01 8.13818723e-02
6.60574138e-01 -1.78765193e-01 7.47087061e-01 -1.28264320e+00
-7.22577631e-01 -3.34144354e-01 -2.00960308e-01 6.28256977e-01
4.56315875e-01 -6.38677061e-01 -2.54610837e-01 -6.20525062e-01
-6.26995325e-01 5.17605484e-01 9.91395473e-01 -4.07778412e-01
-1.02824919e-01 5.37791729e-01 -1.10557795e-01 5.41269362e-01
1.01853275e+00 -4.55939949e-01 -6.91950977e-01 3.94983172e-01
3.19640607e-01 7.54315078e-01 4.62909251e-01 -1.47427475e+00
1.13803081e-01 -1.07306325e+00 -3.06538433e-01 -5.04835427e-01
3.39781910e-01 -1.53894651e+00 7.32691169e-01 1.23059046e+00
-1.12306945e-01 4.16213989e-01 7.29213774e-01 6.68220818e-01
-4.94043559e-01 -3.83056372e-01 8.18161309e-01 3.81720454e-01
-9.60007846e-01 2.70904541e-01 -1.06345379e+00 -3.20372164e-01
2.00368309e+00 -1.32839248e-01 -1.60858154e-01 -1.35035366e-01
-6.53240442e-01 7.34031498e-01 3.23338747e-01 5.74067473e-01
7.72030234e-01 -9.75243390e-01 -1.78293616e-01 3.18181485e-01
2.67516285e-01 -3.97534937e-01 1.91540197e-01 7.52590358e-01
-2.55304307e-01 6.10904396e-01 -4.98428553e-01 -3.10107201e-01
-1.23618925e+00 1.05001533e+00 2.45539725e-01 -2.06226222e-02
-2.65062362e-01 2.49084055e-01 -4.10155170e-02 -3.13582152e-01
1.67199865e-01 -5.46032608e-01 1.57790214e-01 -6.72718048e-01
3.65591437e-01 5.11068106e-01 3.06186497e-01 -8.17783847e-02
-7.75520146e-01 -3.54488418e-02 4.60623622e-01 -4.71406341e-01
9.12798643e-01 3.27001750e-01 -3.92267331e-02 2.90257543e-01
3.38847101e-01 -6.71993315e-01 -1.31004560e+00 6.16366267e-01
-3.10387574e-02 -2.56295294e-01 6.63745552e-02 -7.37463892e-01
-4.76046264e-01 5.18599808e-01 2.66047269e-01 5.94206989e-01
1.06062520e+00 -4.40125555e-01 4.56600815e-01 4.07096237e-01
1.09569168e+00 -1.32987654e+00 -1.92841038e-01 7.71289825e-01
8.79179060e-01 -8.69114518e-01 3.57071124e-02 -5.49478889e-01
-5.17203093e-01 7.78143883e-01 1.02082527e+00 -3.38915229e-01
8.28434527e-01 8.42520595e-01 -5.82218766e-01 1.84596762e-01
-1.09778512e+00 1.37082785e-01 -7.32616261e-02 7.85543799e-01
-3.36251169e-01 9.80575904e-02 -6.48902431e-02 4.11251158e-01
2.03546405e-01 -2.04940997e-02 6.48925304e-01 1.65216029e+00
-5.18471777e-01 -1.25765419e+00 -6.33822203e-01 1.06039941e-01
1.32970363e-01 5.52723587e-01 -3.24278295e-01 1.03690040e+00
-4.04882357e-02 1.28579307e+00 -3.59461129e-01 -4.87216443e-01
7.83967555e-01 1.21572457e-01 5.97637773e-01 -5.85393250e-01
-5.13493478e-01 -2.89346874e-01 6.87860489e-01 -9.22683239e-01
6.26557618e-02 -7.76723921e-01 -1.47163606e+00 -2.34708324e-01
-3.17272961e-01 3.31269801e-01 7.70861626e-01 9.94826019e-01
1.59486115e-01 1.11686683e+00 6.70446932e-01 -6.27333462e-01
-8.18807244e-01 -2.25238785e-01 -3.77075076e-01 -4.10775363e-01
5.91308355e-01 -1.12444973e+00 -3.34261984e-01 -2.74021178e-01] | [4.945737361907959, 2.2474992275238037] |
352b8b53-d0d4-4a15-83c2-a66f235add24 | exploiting-dynamic-and-fine-grained-semantic | 2205.11973 | null | https://arxiv.org/abs/2205.11973v1 | https://arxiv.org/pdf/2205.11973v1.pdf | Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification | Extreme multi-label text classification (XMTC) refers to the problem of tagging a given text with the most relevant subset of labels from a large label set. A majority of labels only have a few training instances due to large label dimensionality in XMTC. To solve this data sparsity issue, most existing XMTC methods take advantage of fixed label clusters obtained in early stage to balance performance on tail labels and head labels. However, such label clusters provide static and coarse-grained semantic scope for every text, which ignores distinct characteristics of different texts and has difficulties modelling accurate semantics scope for texts with tail labels. In this paper, we propose a novel framework TReaderXML for XMTC, which adopts dynamic and fine-grained semantic scope from teacher knowledge for individual text to optimize text conditional prior category semantic ranges. TReaderXML dynamically obtains teacher knowledge for each text by similar texts and hierarchical label information in training sets to release the ability of distinctly fine-grained label-oriented semantic scope. Then, TReaderXML benefits from a novel dual cooperative network that firstly learns features of a text and its corresponding label-oriented semantic scope by parallel Encoding Module and Reading Module, secondly embeds two parts by Interaction Module to regularize the text's representation by dynamic and fine-grained label-oriented semantic scope, and finally find target labels by Prediction Module. Experimental results on three XMTC benchmark datasets show that our method achieves new state-of-the-art results and especially performs well for severely imbalanced and sparse datasets. | ['Tingting Zhao', 'Yarui Chen', 'Jucheng Yang', 'Tao Xu', 'Peng Huo', 'Huiling Song', 'YuAn Wang'] | 2022-05-24 | null | null | null | null | ['multi-label-text-classification', 'multi-label-text-classification'] | ['methodology', 'natural-language-processing'] | [ 3.67007792e-01 4.04687636e-02 -7.39340365e-01 -7.55694211e-01
-7.02171504e-01 -3.85307103e-01 4.17589724e-01 1.01652555e-01
-2.96447128e-01 6.05119824e-01 2.43260711e-01 -1.41945593e-02
-2.83509970e-01 -5.80850303e-01 -2.86212593e-01 -9.39717293e-01
4.24252808e-01 1.12760735e+00 2.60704905e-01 3.22333723e-02
1.38642386e-01 -2.42398173e-01 -1.97120237e+00 8.08490694e-01
9.23891544e-01 1.20105946e+00 4.29187089e-01 1.69268668e-01
-7.55423367e-01 1.18247545e+00 -5.95436752e-01 7.07137361e-02
2.67162975e-02 -3.16443443e-01 -1.06057990e+00 2.66000479e-01
5.55652261e-01 1.69886380e-01 1.08760156e-01 1.02813816e+00
4.40652430e-01 -7.17090862e-03 8.69270921e-01 -1.45702922e+00
-4.64524537e-01 1.15056729e+00 -1.13461947e+00 -1.48303807e-01
-7.26509467e-03 -3.01020473e-01 1.31508875e+00 -5.12940705e-01
3.40951562e-01 1.33925879e+00 7.57408679e-01 6.44289076e-01
-9.88340914e-01 -1.05754054e+00 5.80150545e-01 1.18703052e-01
-1.29638267e+00 -1.63088292e-01 7.19925940e-01 -2.97836423e-01
6.21816874e-01 3.95715952e-01 1.22903116e-01 6.83337450e-01
-4.45163622e-02 1.01398861e+00 1.36777794e+00 -5.24203897e-01
1.93892330e-01 1.59225345e-01 6.93317056e-01 6.88680351e-01
-1.87761992e-01 -3.76129895e-01 -5.88808775e-01 -2.34954417e-01
-2.13512592e-02 1.67030573e-01 -8.21683854e-02 -2.08977655e-01
-1.16287589e+00 9.03972089e-01 3.74261439e-02 4.56046343e-01
1.20547108e-01 4.80135046e-02 6.59227967e-01 4.28153425e-01
7.19639003e-01 -7.66089782e-02 -1.07114065e+00 1.74418747e-01
-1.09775817e+00 -1.74564302e-01 5.58186233e-01 1.27096403e+00
1.07511234e+00 -4.01368886e-01 -3.94248545e-01 1.11987948e+00
5.55285811e-01 5.40426612e-01 9.92303908e-01 -6.92724824e-01
6.80250525e-01 1.11027086e+00 -5.21561682e-01 -6.10327244e-01
-7.35745132e-01 -6.23498678e-01 -8.40883911e-01 -2.47693792e-01
2.05966130e-01 -9.52622911e-04 -1.10830510e+00 1.85926092e+00
6.95965707e-01 2.63601363e-01 4.69668843e-02 6.02078915e-01
1.06405997e+00 7.05280244e-01 4.40106273e-01 -5.00824273e-01
1.69120061e+00 -1.17503119e+00 -6.88097715e-01 -2.04980448e-01
1.28656459e+00 -5.32972217e-01 1.17727280e+00 2.10982248e-01
-6.02475107e-01 -5.04512489e-01 -6.04600251e-01 -8.02450329e-02
-4.59007233e-01 3.36873680e-01 6.25409245e-01 6.11531615e-01
-8.05646122e-01 9.10029188e-02 -3.67865592e-01 -8.41526762e-02
5.98527849e-01 6.07632577e-01 -4.37543988e-02 -1.56189620e-01
-1.36651111e+00 4.16518122e-01 8.14068258e-01 -3.47628623e-01
-6.75602019e-01 -8.53137851e-01 -7.95853794e-01 1.36662766e-01
7.03464270e-01 -4.32065606e-01 1.21722364e+00 -1.14369571e+00
-1.23780358e+00 1.07297289e+00 -1.79797590e-01 8.94040093e-02
2.15867832e-01 3.99138212e-01 -3.77130747e-01 8.44309926e-02
6.76723838e-01 8.45136523e-01 1.07541025e+00 -1.32602704e+00
-1.31925249e+00 -5.49047291e-01 -2.20383599e-01 6.27490640e-01
-7.16116130e-01 4.57752384e-02 -3.47127795e-01 -5.55072665e-01
3.25646222e-01 -7.88769245e-01 -2.15493888e-02 -5.85466564e-01
-3.16736758e-01 -9.23789859e-01 1.16411710e+00 -8.53714421e-02
1.53810835e+00 -1.81650198e+00 1.02661690e-02 1.76888071e-02
4.14156556e-01 -1.20059736e-01 1.21300556e-01 1.00055240e-01
-1.05853066e-01 -4.92834672e-02 6.67456165e-02 -5.44432700e-01
3.19296777e-01 4.55757082e-01 -3.34990710e-01 3.55303496e-01
-4.30989712e-01 8.05035233e-01 -9.20303702e-01 -1.10040808e+00
3.65765579e-02 -5.24912663e-02 -3.52368027e-01 1.09957188e-01
-6.46976411e-01 3.54206681e-01 -7.26428628e-01 7.99310923e-01
6.30688608e-01 -9.20228243e-01 3.93419534e-01 -1.63043499e-01
7.73758590e-02 -6.52338043e-02 -1.18526721e+00 1.59259808e+00
-5.21516562e-01 -1.94602311e-02 -1.68272778e-01 -1.17549253e+00
7.12253630e-01 4.11774069e-01 7.12187290e-01 -5.33609807e-01
3.39982957e-01 2.78900206e-01 -4.96340841e-01 -4.48639125e-01
2.77708083e-01 -3.88112158e-01 -4.65559989e-01 9.93011951e-01
4.03845869e-03 2.02262491e-01 1.75564632e-01 2.13268518e-01
7.84250975e-01 1.66118573e-02 1.69808581e-01 -4.41329062e-01
6.68179929e-01 1.39172047e-01 7.18229294e-01 5.87183297e-01
-7.68385082e-02 3.41058791e-01 2.55918294e-01 -5.17284811e-01
-6.74814641e-01 -4.14733678e-01 -4.36330169e-01 2.13492918e+00
3.34351599e-01 -3.38506490e-01 -6.58020198e-01 -1.32997632e+00
5.14175817e-02 5.06385624e-01 -8.83758664e-01 -9.45160091e-02
-5.20204961e-01 -1.16945577e+00 4.19825524e-01 3.53936315e-01
5.67680180e-01 -1.14122295e+00 -2.81672031e-01 8.46816376e-02
-3.58711869e-01 -8.69066238e-01 -7.10621655e-01 8.67570281e-01
-6.69618547e-01 -1.01979208e+00 -3.32126766e-01 -1.21064878e+00
8.32025170e-01 2.59004980e-01 1.17008746e+00 1.13245822e-01
8.44732746e-02 -3.40282023e-02 -5.81977010e-01 -7.94687793e-02
-4.29094464e-01 4.34423625e-01 -7.71261081e-02 1.31087944e-01
6.40325904e-01 -3.58706534e-01 -1.78021565e-01 5.82892120e-01
-9.77638960e-01 3.51082176e-01 3.08810115e-01 9.61850107e-01
6.57644987e-01 6.89070106e-01 7.75899291e-01 -1.41579401e+00
2.27522925e-01 -7.56989598e-01 -4.23944443e-01 4.99324441e-01
-1.16206586e+00 9.26412940e-02 9.87574756e-01 -6.32893860e-01
-1.10856104e+00 9.69364345e-02 5.77444844e-02 -2.42578998e-01
-2.44867548e-01 3.73612732e-01 -4.00368124e-01 1.35236174e-01
4.21130896e-01 3.55742544e-01 -3.39333206e-01 -5.22157967e-01
3.40031922e-01 1.09120655e+00 1.35729939e-01 -9.40776050e-01
4.25247937e-01 3.91467184e-01 -3.54082100e-02 -1.21613499e-02
-1.74151516e+00 -7.99783766e-01 -7.18053937e-01 -1.84313461e-01
6.99259579e-01 -1.18374431e+00 -7.87629068e-01 6.12330377e-01
-5.37452281e-01 -4.43947345e-01 -3.87696892e-01 4.53343941e-03
-4.34926748e-01 3.01421881e-01 -6.68246090e-01 -2.53843576e-01
-4.10350055e-01 -1.24239194e+00 1.63191426e+00 2.04849556e-01
2.13341281e-01 -1.33674514e+00 -1.39128447e-01 6.28956020e-01
2.77060457e-02 -2.08395272e-01 1.14513803e+00 -8.37340832e-01
-1.80512130e-01 1.94312558e-01 -3.58314008e-01 -3.64378560e-03
4.61233146e-02 -6.03524566e-01 -1.07103992e+00 -5.88538170e-01
6.63553253e-02 -8.80966723e-01 1.02057135e+00 3.77813429e-01
1.37285125e+00 -2.48548791e-01 -8.28423083e-01 6.29903793e-01
1.52472937e+00 3.21375877e-02 -2.69889347e-02 3.90479386e-01
1.19849908e+00 6.74582481e-01 8.95722687e-01 4.36777204e-01
8.44938815e-01 7.01614618e-01 3.39714825e-01 5.88100776e-02
-1.48718879e-01 -1.36504009e-01 3.78683284e-02 1.12203228e+00
6.05444252e-01 -4.10697818e-01 -7.80582845e-01 4.00418609e-01
-1.94187605e+00 -6.45278871e-01 -2.39082113e-01 1.60340428e+00
1.42959666e+00 -4.94983532e-02 -1.18411127e-02 2.29989037e-01
1.17378151e+00 1.08119510e-01 -6.24713063e-01 6.91119358e-02
-2.63207972e-01 -1.53184131e-01 5.63538253e-01 1.98129117e-01
-1.22701383e+00 1.17038739e+00 5.31011295e+00 1.80062056e+00
-9.70700502e-01 5.70992827e-01 8.20373237e-01 3.73748653e-02
-3.07669133e-01 6.91135228e-02 -1.55852628e+00 7.57907867e-01
8.53714049e-01 2.29701489e-01 4.26935703e-02 6.82746649e-01
-1.96628883e-01 -3.08452994e-02 -8.96211088e-01 8.60221446e-01
8.49650279e-02 -1.12880611e+00 2.43878048e-02 8.36257935e-02
1.13711441e+00 -7.78551474e-02 1.18362918e-01 6.73854589e-01
6.31186128e-01 -7.86163330e-01 7.59202302e-01 1.73973180e-02
1.26785302e+00 -6.76216424e-01 6.06966734e-01 7.38475919e-01
-1.41830921e+00 -3.77015203e-01 -5.68910539e-01 9.69553366e-02
-3.07171822e-01 7.68711925e-01 -5.70464969e-01 4.00151879e-01
5.61094105e-01 8.70375037e-01 -6.05281115e-01 2.76829273e-01
-5.74806184e-02 8.29518378e-01 -2.98003167e-01 1.78102180e-02
4.87021983e-01 2.15114906e-01 -6.61471486e-02 1.14155579e+00
9.06960070e-02 5.89964651e-02 8.59867811e-01 3.05725336e-01
-2.40940407e-01 4.61922020e-01 2.91476212e-02 4.43353087e-01
7.68241644e-01 1.44921052e+00 -1.05893481e+00 -5.81866920e-01
-4.74390149e-01 5.87925613e-01 5.32708764e-01 2.75536776e-02
-8.48896563e-01 -2.44725123e-02 -1.49300033e-02 -1.97874904e-01
3.42852294e-01 6.38478160e-01 -5.74670017e-01 -1.19481957e+00
-2.55883723e-01 -8.27884495e-01 9.64994669e-01 -5.64918876e-01
-1.29450524e+00 4.91531819e-01 -3.00452001e-02 -1.31184268e+00
3.18757854e-02 -3.78186464e-01 -9.52250734e-02 6.05595946e-01
-1.63155043e+00 -1.70906627e+00 -2.21932858e-01 7.52469778e-01
7.55483031e-01 -3.43061209e-01 7.85183012e-01 2.72546321e-01
-5.79895854e-01 9.62349474e-01 5.73947012e-01 -1.37034014e-01
9.29906785e-01 -1.49856579e+00 -2.23317921e-01 9.22360122e-02
-9.89385694e-02 7.55682960e-02 2.26313397e-01 -8.05309236e-01
-8.00104201e-01 -1.60453856e+00 1.11829305e+00 -5.13189971e-01
4.73707050e-01 -2.65053272e-01 -7.91622519e-01 8.64841938e-01
-2.78853625e-02 1.23745345e-01 8.77512157e-01 2.83574790e-01
-4.58021253e-01 -1.54590130e-01 -1.14411736e+00 1.87453493e-01
9.46206450e-01 -2.51862884e-01 -5.66492617e-01 6.87614143e-01
1.01680923e+00 -4.27692771e-01 -1.03705347e+00 3.94927353e-01
2.18874037e-01 -6.41064763e-01 6.51412845e-01 -2.89677024e-01
3.42458904e-01 -5.21291971e-01 -1.29170448e-01 -1.18428457e+00
-4.80261415e-01 -1.04788400e-01 -3.46137583e-02 1.42580235e+00
2.66846031e-01 -4.47864115e-01 1.07845116e+00 1.26064822e-01
-3.41801584e-01 -9.24781263e-01 -8.03944290e-01 -4.37824100e-01
2.68133581e-01 -4.26785439e-01 9.94245052e-01 1.57257831e+00
1.54228061e-01 6.76944077e-01 -4.72380519e-01 1.40975360e-02
7.70766795e-01 7.75524974e-01 2.97641367e-01 -1.63949490e+00
-6.37685061e-02 -3.45809311e-01 -4.42081392e-02 -1.12408590e+00
7.76758075e-01 -1.52393365e+00 2.57458575e-02 -1.11729693e+00
8.63907695e-01 -1.22538650e+00 -3.74359041e-01 1.08645427e+00
-4.80694920e-01 4.39790726e-01 -1.52161449e-01 6.23391211e-01
-1.36098409e+00 4.15927172e-01 1.40329266e+00 -3.21877092e-01
1.42647550e-02 -5.87592721e-02 -8.74409974e-01 5.69527507e-01
6.40859544e-01 -9.22864497e-01 -7.24134564e-01 -4.18171078e-01
4.00862604e-01 -3.47848125e-02 -2.22524092e-01 -7.28252709e-01
4.91134793e-01 -3.95161778e-01 3.10859114e-01 -7.94142842e-01
-1.89854980e-01 -1.02690935e+00 6.48015961e-02 1.00152597e-01
-7.70101249e-01 -6.22552931e-01 -1.47012502e-01 4.64714527e-01
-5.77545650e-02 -5.18137932e-01 9.05976057e-01 -2.11518809e-01
-8.38407576e-01 4.65692341e-01 -1.41000926e-01 5.17190397e-01
1.04347897e+00 -1.92011520e-01 -4.21655476e-01 1.88523695e-01
-7.23131359e-01 7.51306176e-01 4.43341464e-01 2.35977322e-01
1.61841124e-01 -1.52600420e+00 -5.77384830e-01 3.34714442e-01
3.56744111e-01 4.43775982e-01 4.06395942e-01 6.13977075e-01
1.15554027e-01 3.58074307e-01 1.70056537e-01 -9.83515501e-01
-1.27409136e+00 7.29746461e-01 1.89675659e-01 -7.22940803e-01
-5.02411544e-01 1.02830184e+00 6.52513325e-01 -9.37061369e-01
3.05958420e-01 -1.05223753e-01 -6.31593585e-01 3.06959510e-01
4.81953800e-01 1.23920344e-01 4.63229662e-04 -1.02482641e+00
-1.10830300e-01 1.00008106e+00 -3.76522064e-01 4.41310287e-01
9.99704063e-01 -6.30300939e-01 -3.61122012e-01 5.75461924e-01
1.40905511e+00 -2.87823409e-01 -1.11985219e+00 -6.81888580e-01
1.60036385e-01 -2.24176243e-01 3.16545576e-01 -1.03906620e+00
-1.25735736e+00 5.98204136e-01 4.32376683e-01 1.44512489e-01
1.37139702e+00 2.49995336e-01 8.92575741e-01 8.23061839e-02
4.28896308e-01 -1.34114552e+00 1.55501455e-01 7.06612170e-01
5.45738116e-02 -1.33733976e+00 -7.35108554e-02 -5.06550610e-01
-6.02742851e-01 8.75204623e-01 8.39992344e-01 5.93858838e-01
8.28336000e-01 3.72334361e-01 3.17951262e-01 -3.77956659e-01
-1.03089845e+00 -1.76560253e-01 1.80759564e-01 3.30747753e-01
3.42676461e-01 2.58611798e-01 -1.89461604e-01 7.18394876e-01
-3.97407934e-02 -3.18974674e-01 2.92767193e-02 8.55079770e-01
-9.88237560e-01 -1.21844387e+00 -4.82373595e-01 8.32650602e-01
-6.03248060e-01 -2.54890263e-01 1.71449989e-01 3.59471351e-01
7.87160516e-01 1.00721812e+00 -5.35301007e-02 -3.82172465e-01
-1.62338555e-01 2.55236030e-01 2.24150047e-01 -9.55915630e-01
-7.80900478e-01 2.93799162e-01 -2.05013156e-01 -8.27364251e-02
-5.71641922e-01 -7.49778986e-01 -1.71265352e+00 -2.23306000e-01
-6.62647188e-01 4.97789890e-01 3.48400891e-01 1.21690679e+00
7.60336295e-02 5.77712893e-01 8.67884278e-01 -2.96272188e-01
-5.94752669e-01 -1.13448441e+00 -1.00524485e+00 4.56143886e-01
1.01002797e-01 -7.13583708e-01 -4.45329577e-01 2.19702676e-01] | [9.607993125915527, 4.3376898765563965] |
bcb50c40-f431-492c-8a91-b617144cc1e4 | response-ranking-with-multi-types-of-deep | null | null | https://dl.acm.org/doi/abs/10.1145/3462207 | https://dl.acm.org/doi/pdf/10.1145/3462207 | Response Ranking with Multi-types of Deep Interactive Representations in Retrieval-based Dialogues | Building an intelligent dialogue system with the ability to select a proper response according to a multi-turn context is challenging in three aspects: (1) the meaning of a context–response pair is built upon language units from multiple granularities (e.g., words, phrases, and sub-sentences, etc.); (2) local (e.g., a small window around a word) and long-range (e.g., words across the context and the response) dependencies may exist in dialogue data; and (3) the relationship between the context and the response candidate lies in multiple relevant semantic clues or relatively implicit semantic clues in some real cases. However, existing approaches usually encode the dialogue with mono-type representation and the interaction processes between the context and the response candidate are executed in a rather shallow manner, which may lead to an inadequate understanding of dialogue content and hinder the recognition of the semantic relevance between the context and response. To tackle these challenges, we propose a representation[K]-interaction[L]-matching framework that explores multiple types of deep interactive representations to build context-response matching models for response selection. Particularly, we construct different types of representations for utterance–response pairs and deepen them via alternate encoding and interaction. By this means, the model can handle the relation of neighboring elements, phrasal pattern, and long-range dependencies during the representation and make a more accurate prediction through multiple layers of interactions between the context–response pair. Experiment results on three public benchmarks indicate that the proposed model significantly outperforms previous conventional context-response matching models and achieve slightly better results than the BERT model for multi-turn response selection in retrieval-based dialogue systems. | ['Dongyan Zhao', 'Rui Yan', 'Wei Wu', 'Jiazhan Feng', 'Chongyang Tao', 'Ruijian Xu'] | 2021-08-17 | null | null | null | acm-transactions-on-information-systems-2021 | ['conversational-response-selection'] | ['natural-language-processing'] | [ 3.12658519e-01 7.01332837e-02 -1.79444805e-01 -6.95998192e-01
-7.08187222e-01 -5.46629488e-01 8.09978724e-01 6.23960912e-01
-3.74433726e-01 5.98265707e-01 8.13489854e-01 -2.65391022e-01
-1.68769255e-01 -8.68863642e-01 -6.40472351e-03 -3.18596005e-01
3.39848220e-01 6.63875163e-01 3.86200666e-01 -1.06042111e+00
6.37157321e-01 -2.65833195e-02 -1.36120594e+00 8.97279441e-01
8.53427112e-01 1.03106451e+00 5.08300841e-01 5.77264547e-01
-7.76215136e-01 7.21188486e-01 -7.34684169e-01 -7.05180392e-02
-1.47702679e-01 -8.93799961e-01 -1.39439845e+00 -1.26062840e-01
-1.81796819e-01 -2.10099563e-01 -1.44153014e-01 7.23551810e-01
5.37171125e-01 5.64862907e-01 5.99752367e-01 -5.76298118e-01
-4.89145190e-01 7.47851372e-01 -1.64054424e-01 1.42398924e-01
1.15271854e+00 -1.97764132e-02 1.20998526e+00 -8.81726742e-01
4.62711096e-01 1.68424284e+00 3.58260036e-01 7.02213287e-01
-1.06999910e+00 -2.01794028e-01 5.21062434e-01 3.53393257e-01
-9.68162656e-01 -3.91063035e-01 6.14717662e-01 -1.36578694e-01
1.19616747e+00 5.55870116e-01 3.28546524e-01 9.95455742e-01
-2.93127857e-02 8.45332265e-01 8.60032618e-01 -6.73246861e-01
-2.88516767e-02 1.60823181e-01 6.36598468e-01 3.41094702e-01
-7.39534318e-01 -4.00702953e-01 -4.82390463e-01 -5.38430572e-01
4.48946685e-01 -1.20672695e-01 -3.40628207e-01 3.53804976e-01
-9.74021614e-01 1.01037920e+00 3.36120695e-01 5.73123097e-01
-2.04071045e-01 -4.62881714e-01 8.11155081e-01 6.16967559e-01
1.16111353e-01 5.24505615e-01 -4.54453498e-01 -1.68202609e-01
-1.73822254e-01 3.67279917e-01 1.14409888e+00 7.49860287e-01
8.76655459e-01 -3.79770964e-01 -6.29508734e-01 1.43191266e+00
3.16146135e-01 -1.07816420e-02 7.89366603e-01 -4.02958661e-01
7.77608752e-01 9.17275250e-01 2.46660307e-01 -1.17845070e+00
-5.03014565e-01 2.79532582e-01 -7.67279565e-01 -5.19138157e-01
5.31545341e-01 -1.51223943e-01 -3.77737880e-01 1.83364081e+00
5.11630952e-01 -2.17267394e-01 4.02304262e-01 1.05374455e+00
1.42362821e+00 8.40971470e-01 2.66886890e-01 -3.07010174e-01
1.71655738e+00 -8.64052057e-01 -9.40676510e-01 -5.63157737e-01
7.95451045e-01 -8.91335011e-01 1.34224284e+00 -1.99877784e-01
-9.35809195e-01 -5.69068253e-01 -7.01595187e-01 -2.37886086e-01
-2.84082443e-01 1.98334642e-02 4.07649130e-01 8.24290067e-02
-6.75107121e-01 2.64982313e-01 1.49932802e-01 -4.68397349e-01
-6.13220990e-01 2.67352939e-01 -2.34552979e-01 -1.16127044e-01
-2.01555943e+00 1.03657830e+00 4.10146892e-01 2.70495772e-01
-1.78834632e-01 -1.42006904e-01 -9.22613561e-01 6.51248544e-02
5.30933022e-01 -5.52430689e-01 1.22413898e+00 -1.07237828e+00
-1.72477996e+00 6.68208361e-01 -3.23898554e-01 -9.99736488e-02
1.09196648e-01 -1.44148186e-01 -3.72795492e-01 7.28330836e-02
-7.51232654e-02 2.50028372e-01 4.87690836e-01 -8.91919792e-01
-7.23644614e-01 -4.51307237e-01 5.62977910e-01 8.60909820e-01
-2.40570456e-02 4.81484920e-01 -3.22713614e-01 -4.06466484e-01
2.31159315e-01 -6.58872843e-01 -1.68910086e-01 -7.11840630e-01
-3.10776114e-01 -8.85598004e-01 6.21588707e-01 -5.63935816e-01
1.54572189e+00 -2.07208490e+00 1.91532120e-01 -8.56510624e-02
-2.20515095e-02 3.60097587e-01 -2.17707142e-01 1.01727700e+00
6.27539307e-02 1.02457121e-01 -3.32999527e-02 2.34517306e-02
-5.24923652e-02 2.11416274e-01 -4.17025208e-01 -6.59087449e-02
7.52953514e-02 6.21738374e-01 -9.83832657e-01 -3.41736466e-01
1.07822508e-01 8.87720883e-02 -3.70221198e-01 8.14278781e-01
-3.20558995e-01 5.34724653e-01 -8.20771396e-01 2.70111650e-01
1.19000643e-01 1.36233075e-02 4.98020589e-01 -1.50605410e-01
6.18788563e-02 1.03071177e+00 -1.08209229e+00 1.50156856e+00
-6.84488058e-01 2.54931808e-01 2.54132718e-01 -9.10156310e-01
1.16326952e+00 5.40913999e-01 -1.79929100e-02 -8.83524477e-01
-7.49766380e-02 1.56432047e-01 1.82631403e-01 -6.63765669e-01
7.84244835e-01 -1.14833266e-01 -5.82740486e-01 8.11308920e-01
-1.62387550e-01 -3.61268111e-02 4.49236147e-02 2.18469277e-01
1.02627444e+00 -1.84667915e-01 6.52983844e-01 -6.78481460e-02
1.01914012e+00 -1.93139911e-01 5.94434619e-01 7.74235249e-01
-1.13894723e-01 3.14359456e-01 6.09811902e-01 -5.01961946e-01
-4.74004239e-01 -3.30288768e-01 4.96859737e-02 1.77809632e+00
4.67642844e-01 -6.51827455e-01 -6.04277492e-01 -7.03240633e-01
-2.91513622e-01 7.10610151e-01 -5.28278530e-01 -2.58813024e-01
-8.82635355e-01 -4.38826442e-01 5.43872833e-01 3.92467648e-01
4.79962617e-01 -1.37377775e+00 -2.85065264e-01 5.73763371e-01
-7.18090773e-01 -1.00497031e+00 -6.31874144e-01 1.57737628e-01
-5.34712613e-01 -9.91203606e-01 1.33803543e-02 -8.21503937e-01
4.20792252e-01 3.16065580e-01 1.21333432e+00 4.45087403e-01
2.52683669e-01 2.70588487e-01 -7.92507946e-01 8.53257701e-02
-5.57756484e-01 -7.88794905e-02 -1.54526263e-01 8.68564397e-02
5.52545309e-01 -8.61844942e-02 -6.15588605e-01 6.97572291e-01
-8.49511504e-01 4.85202149e-02 1.56310558e-01 1.27380455e+00
2.03661025e-01 -3.54005367e-01 8.89542758e-01 -1.00963700e+00
1.39670384e+00 -7.43058383e-01 8.14328417e-02 6.52088642e-01
-3.31896186e-01 6.01418465e-02 7.64965594e-01 -5.12614310e-01
-1.36043441e+00 -2.91492939e-01 -3.40307772e-01 4.46623325e-01
-3.48689258e-01 7.30513930e-01 -3.37039202e-01 3.33122253e-01
5.73138297e-01 2.90000021e-01 -8.91908780e-02 -4.26502436e-01
3.53072673e-01 1.00574934e+00 1.24182470e-01 -1.06772327e+00
-3.65864821e-02 -2.19369963e-01 -5.99365830e-01 -6.42531097e-01
-6.38055027e-01 -6.69277012e-01 -5.52688539e-01 -1.75661102e-01
6.19068742e-01 -4.95625019e-01 -5.19434988e-01 1.82129189e-01
-1.48042989e+00 -1.90530613e-01 7.89186135e-02 2.80715466e-01
-4.17747498e-01 6.13291919e-01 -9.18970585e-01 -8.56678009e-01
-4.74244237e-01 -1.27927208e+00 8.23531151e-01 4.56965476e-01
-7.33765960e-01 -1.00062466e+00 -2.12035283e-01 4.66707200e-01
3.96318883e-01 -3.16579372e-01 1.44761646e+00 -1.30468273e+00
-3.14116664e-02 -1.46747574e-01 -2.33636066e-01 3.36191207e-02
2.99296111e-01 -2.54087269e-01 -6.57861769e-01 3.94772664e-02
2.90036172e-01 -7.61765778e-01 5.14345586e-01 -1.38092607e-01
7.66137898e-01 -6.24656081e-01 -6.14081584e-02 -1.10051855e-01
8.69584560e-01 4.72637683e-01 6.24143064e-01 4.15159985e-02
2.96834826e-01 1.20818233e+00 1.11407244e+00 5.63046038e-01
6.85411096e-01 9.10096109e-01 1.56351969e-01 1.08062275e-01
2.87478626e-01 -2.41283923e-01 3.07221144e-01 9.49719369e-01
2.55074203e-01 -2.70599365e-01 -7.24489927e-01 3.14621001e-01
-2.20666504e+00 -8.25089097e-01 -1.36466309e-01 2.23583508e+00
1.32883036e+00 -1.58683673e-01 -3.53029557e-02 -1.38681471e-01
8.37418675e-01 3.35906804e-01 -3.64931643e-01 -9.51348186e-01
-2.82148737e-03 -1.48114383e-01 -4.45092976e-01 8.02757382e-01
-6.31966710e-01 1.12089932e+00 5.55541754e+00 9.55137908e-01
-9.19055045e-01 -9.28338841e-02 6.30670190e-01 3.84350777e-01
-4.98918802e-01 1.18795119e-01 -1.01904511e+00 3.52794707e-01
6.63178802e-01 -1.31242514e-01 3.76185089e-01 4.43686157e-01
1.04216881e-01 -2.33648375e-01 -1.33427882e+00 7.61068046e-01
1.25709921e-02 -1.08904946e+00 1.60040498e-01 -4.08421308e-01
3.99637930e-02 -5.45532763e-01 -4.32599515e-01 6.83439434e-01
1.24172077e-01 -9.86305654e-01 3.40021938e-01 3.86404932e-01
5.35564721e-01 -5.66996336e-01 8.13813925e-01 6.99818730e-01
-1.36361015e+00 -9.55272913e-02 -4.17292058e-01 -1.25756025e-01
-7.92454481e-02 -3.68879437e-02 -1.04459095e+00 6.47678494e-01
3.03051412e-01 1.84115738e-01 -2.40661800e-01 4.43614095e-01
-3.60525608e-01 3.45629692e-01 -1.98037446e-01 -3.38340074e-01
4.07039881e-01 -2.92084038e-01 5.60141921e-01 1.38921750e+00
-4.18366566e-02 6.21014059e-01 5.26068330e-01 6.14661515e-01
1.88007206e-01 6.04740918e-01 -4.84736443e-01 1.57139406e-01
8.51282656e-01 1.10262215e+00 -4.40906644e-01 -2.80556113e-01
-4.24858302e-01 7.11241424e-01 5.15676498e-01 3.86310726e-01
-3.49456131e-01 -3.58463705e-01 6.32228315e-01 -7.07149059e-02
-2.51237839e-01 1.45080715e-01 -1.00919515e-01 -8.78634691e-01
4.43476252e-03 -1.15302396e+00 7.32187867e-01 -4.23475206e-01
-1.36377859e+00 8.15204024e-01 -6.30228966e-02 -9.38959479e-01
-7.30344176e-01 -1.98622167e-01 -9.05996919e-01 1.21929967e+00
-1.12527716e+00 -8.82297516e-01 8.56646299e-02 6.34391010e-01
1.03738797e+00 -1.18300475e-01 1.32846928e+00 -9.35016572e-02
-4.31893140e-01 4.96798247e-01 -4.17716801e-01 2.27822825e-01
7.84668386e-01 -1.09802437e+00 3.51314545e-02 4.05051708e-01
-2.40350515e-01 9.29307520e-01 4.84063357e-01 -4.81708109e-01
-1.28991199e+00 -5.12137771e-01 1.35435283e+00 -2.13667601e-01
4.99050826e-01 -2.52250969e-01 -1.37331963e+00 2.64905930e-01
4.89275217e-01 -4.58757311e-01 1.12559319e+00 5.55111110e-01
-3.05934131e-01 1.39140695e-01 -1.01493418e+00 6.66995227e-01
6.19552851e-01 -8.73215497e-01 -1.15170789e+00 2.46071085e-01
8.45055819e-01 -5.55989683e-01 -6.60117686e-01 3.34966660e-01
4.58956808e-01 -9.86536741e-01 8.10556591e-01 -8.77781808e-01
3.15586656e-01 -6.54905364e-02 -3.04351896e-01 -1.27735651e+00
-1.32567942e-01 -6.54136419e-01 -2.32602493e-03 1.42674088e+00
3.78347427e-01 -4.42599833e-01 3.45249586e-02 1.02662420e+00
-2.06589192e-01 -1.00129449e+00 -8.87786686e-01 1.77396871e-02
-1.41098782e-01 -2.80605346e-01 8.39476109e-01 1.05201495e+00
6.08105123e-01 9.67348576e-01 -3.02432597e-01 -2.42177904e-01
-2.71258414e-01 4.53574330e-01 5.93945801e-01 -9.69031096e-01
-2.40711212e-01 -5.65126717e-01 1.01449266e-01 -1.65437973e+00
3.38535875e-01 -5.72364032e-01 2.73125619e-01 -1.60247374e+00
-7.96651542e-02 -6.91924036e-01 -1.76298290e-01 4.28527832e-01
-5.87527096e-01 -5.30144811e-01 2.72023752e-02 2.97484249e-01
-6.10210776e-01 6.00334883e-01 1.16881168e+00 -6.34299293e-02
-4.33764100e-01 2.65953541e-01 -7.35482574e-01 6.38318002e-01
6.39373541e-01 -1.96295664e-01 -4.62023199e-01 -3.28300178e-01
3.41494322e-01 9.39526379e-01 -1.19125634e-01 -1.73546195e-01
5.55758476e-01 -5.79650283e-01 -4.75390479e-02 -3.92240077e-01
3.76729161e-01 -4.97582942e-01 -4.35734451e-01 3.26111279e-02
-1.00896251e+00 7.81855136e-02 -1.24007411e-01 6.14152670e-01
-4.69879955e-01 -6.38658285e-01 5.39987206e-01 -4.08333302e-01
-7.75269866e-01 -1.27206624e-01 -6.66260779e-01 2.64512926e-01
4.60113347e-01 -1.94861010e-01 -3.46060246e-01 -6.24090433e-01
-6.36427224e-01 5.43662190e-01 8.59106779e-02 7.63365626e-01
8.35288346e-01 -1.23655653e+00 -6.22968018e-01 1.75182536e-01
3.27701330e-01 9.09148678e-02 2.97371566e-01 5.60619712e-01
1.77602097e-01 4.07187581e-01 5.21420948e-02 -3.50643367e-01
-1.54042864e+00 2.46572886e-02 3.81329983e-01 -5.49928904e-01
-4.80346322e-01 9.17708457e-01 3.78715307e-01 -7.91784286e-01
3.47365409e-01 -1.47141412e-01 -1.01057553e+00 3.47576082e-01
8.03949356e-01 -3.96817960e-02 -4.20810506e-02 -9.05846477e-01
-2.78730214e-01 1.89255342e-01 -3.03227782e-01 2.51535904e-02
7.89759874e-01 -5.48474491e-01 -4.54431415e-01 6.13120914e-01
9.39524233e-01 -9.79061350e-02 -6.81232572e-01 -9.06519473e-01
1.90111235e-01 -4.74700570e-01 -3.92369598e-01 -7.82650888e-01
-4.06616300e-01 7.44771838e-01 4.94289957e-02 6.95093811e-01
9.11567628e-01 4.23635310e-03 8.87100816e-01 6.58291459e-01
2.67274499e-01 -1.47725248e+00 1.92256168e-01 1.09657168e+00
1.19720745e+00 -1.18219447e+00 -2.98608273e-01 -3.55929732e-01
-9.60206151e-01 1.41820550e+00 1.03387046e+00 2.98311323e-01
3.06736022e-01 -1.25682279e-01 2.42962301e-01 -1.89764142e-01
-1.20395899e+00 -2.01331899e-01 3.73275101e-01 2.88050413e-01
9.55970287e-01 4.23098430e-02 -7.95221150e-01 8.39778244e-01
3.18976194e-02 -6.84458673e-01 2.24089935e-01 7.88226545e-01
-5.70029795e-01 -1.51242864e+00 -2.36882523e-01 2.67281383e-01
-2.59030342e-01 -1.83601201e-01 -9.47380900e-01 3.66511166e-01
-2.29131371e-01 1.53919637e+00 -1.56993926e-01 -5.58760822e-01
5.04423738e-01 3.37105632e-01 1.56904720e-02 -1.11665285e+00
-1.30310905e+00 1.33829758e-01 6.38543546e-01 -5.36256313e-01
-3.07809800e-01 -3.79706621e-01 -1.59053838e+00 -1.19988292e-01
-5.08030295e-01 5.53229690e-01 3.21379870e-01 1.42651308e+00
2.58454084e-01 3.41168195e-01 9.11810100e-01 -4.76413786e-01
-9.27847326e-01 -1.21562815e+00 -2.64160037e-01 6.16295457e-01
6.22955896e-02 -4.14695859e-01 -1.62549853e-01 -5.71790278e-01] | [12.575089454650879, 7.84657096862793] |
09d43aba-05be-43c1-849b-9363a56e14bc | source-free-domain-adaptation-for-multi-site | 2203.04299 | null | https://arxiv.org/abs/2203.04299v3 | https://arxiv.org/pdf/2203.04299v3.pdf | Plug-and-play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping | Skull stripping is a crucial prerequisite step in the analysis of brain magnetic resonance images (MRI). Although many excellent works or tools have been proposed, they suffer from low generalization capability. For instance, the model trained on a dataset with specific imaging parameters cannot be well applied to other datasets with different imaging parameters. Especially, for the lifespan datasets, the model trained on an adult dataset is not applicable to an infant dataset due to the large domain difference. To address this issue, numerous methods have been proposed, where domain adaptation based on feature alignment is the most common. Unfortunately, this method has some inherent shortcomings, which need to be retrained for each new domain and requires concurrent access to the input images of both domains. In this paper, we design a plug-and-play shape refinement (PSR) framework for multi-site and lifespan skull stripping. To deal with the domain shift between multi-site lifespan datasets, we take advantage of the brain shape prior, which is invariant to imaging parameters and ages. Experiments demonstrate that our framework can outperform the state-of-the-art methods on multi-site lifespan datasets. | ['Li Wang', 'Yaqi Wang', 'You Zhang', 'Huiyu Zhou', 'Gangyong Jia', 'Chenghao Tan', 'Xiangde Luo', 'Yifan Cao', 'Shuai Wang', 'Ruilong Dan', 'Yunxiang Li'] | 2022-03-08 | null | null | null | null | ['source-free-domain-adaptation', 'skull-stripping'] | ['computer-vision', 'medical'] | [ 1.56401396e-01 -2.21424565e-01 4.90460843e-02 -5.89891434e-01
-2.75335729e-01 -7.42952973e-02 1.85103759e-01 -9.58654433e-02
-6.64876878e-01 7.31383622e-01 -8.42127353e-02 1.30179614e-01
-1.97766960e-01 -4.98710096e-01 -3.92111629e-01 -7.71990776e-01
4.15529460e-02 7.55785167e-01 7.69393682e-01 -1.89089939e-01
1.62007004e-01 4.74458545e-01 -1.42581928e+00 -1.73545137e-01
1.11387384e+00 7.71891654e-01 5.67525566e-01 -1.28924638e-01
-7.39064515e-02 -3.39515917e-02 -3.13482940e-01 -3.07290077e-01
2.86207497e-01 -2.80968457e-01 -5.91260493e-01 1.15821972e-01
1.83705598e-01 -4.37620282e-01 -2.17425898e-01 1.15152454e+00
8.00554693e-01 8.98505151e-02 7.11482167e-01 -1.15817106e+00
-5.91585636e-01 4.78772670e-01 -9.60001051e-01 5.44862747e-01
-1.60120521e-02 -1.24733724e-01 1.50040045e-01 -8.00982893e-01
6.02105737e-01 9.45804358e-01 5.87424815e-01 8.12665939e-01
-1.06680727e+00 -9.99278486e-01 2.99366593e-01 2.57829428e-01
-1.15960133e+00 -3.88021678e-01 8.32672000e-01 -6.13238990e-01
3.79251897e-01 -2.99653053e-01 7.02397525e-01 1.11708951e+00
1.45930111e-01 4.02399987e-01 1.28786135e+00 -7.37134442e-02
1.87266469e-01 -2.09593028e-01 8.56135786e-02 4.32739139e-01
3.49628568e-01 -1.52515501e-01 -4.28375721e-01 -8.12293664e-02
1.00014114e+00 5.64249381e-02 -2.42377087e-01 -5.87932885e-01
-1.17595530e+00 5.37009299e-01 1.85161188e-01 4.91864800e-01
-3.15923065e-01 -5.37204623e-01 4.89462227e-01 1.82903305e-01
3.92316699e-01 1.49198100e-01 -4.64480996e-01 4.21892293e-02
-1.09452081e+00 2.82157987e-01 3.05175871e-01 8.08867216e-01
3.82433981e-01 -1.05663493e-01 2.15899736e-01 1.12253010e+00
1.11981727e-01 2.42943436e-01 9.78001952e-01 -5.21935523e-01
3.07888329e-01 5.13507366e-01 -3.73806089e-01 -7.46680439e-01
-9.12106574e-01 -4.95734543e-01 -1.06030762e+00 -2.53904257e-02
4.99378413e-01 -6.38086572e-02 -1.06068969e+00 1.84167302e+00
6.41962230e-01 1.62604347e-01 -2.44767427e-01 9.11120296e-01
8.99948537e-01 -1.10218367e-02 1.63712233e-01 -3.57550442e-01
1.40572345e+00 -7.74817526e-01 -5.16308248e-01 -4.38628227e-01
2.54949301e-01 -5.61438918e-01 9.44253027e-01 4.30076480e-01
-9.64600921e-01 -4.53542054e-01 -1.05987644e+00 1.25395164e-01
-2.48168513e-01 -1.02472395e-01 4.08110708e-01 5.66595614e-01
-8.19963098e-01 3.95246148e-01 -9.78040814e-01 -4.98535097e-01
5.05135834e-01 4.94661301e-01 -6.01241708e-01 -4.38466929e-02
-1.13159704e+00 1.03991973e+00 4.88678455e-01 -3.15087661e-02
-7.37554491e-01 -9.28930283e-01 -5.57073176e-01 -2.77850628e-01
4.16923195e-01 -6.38507366e-01 9.99873579e-01 -7.17615247e-01
-1.36790121e+00 1.05669594e+00 1.53925300e-01 -3.51569027e-01
6.28053486e-01 -4.37687375e-02 -5.45967698e-01 2.37519816e-01
2.48441294e-01 4.74281251e-01 8.97901654e-01 -1.01433182e+00
-2.48895317e-01 -9.27730501e-01 -1.90542340e-01 7.71845654e-02
-4.25578475e-01 3.98330301e-01 -4.71231163e-01 -8.52529466e-01
3.69435340e-01 -8.50394189e-01 -1.52812421e-01 5.44628799e-02
1.31563842e-01 5.64699471e-02 7.16909766e-01 -1.07457232e+00
1.22371984e+00 -2.12639928e+00 2.42119089e-01 4.82018553e-02
2.13107347e-01 2.68410176e-01 7.00659975e-02 4.49855216e-02
-1.40617505e-01 -2.43148431e-01 -5.66169560e-01 -2.83928692e-01
-3.82351160e-01 1.26014024e-01 1.87870994e-01 5.88474035e-01
-1.42679036e-01 3.19132030e-01 -8.06627452e-01 -8.62526357e-01
-2.34943241e-01 3.44389498e-01 -5.34708142e-01 1.85298607e-01
2.26622835e-01 1.13180518e+00 -5.93828499e-01 5.05686879e-01
9.76750791e-01 -1.13150142e-01 1.35837361e-01 -1.60338983e-01
-4.80181947e-02 -2.91769922e-01 -1.00046098e+00 2.12557769e+00
-1.37504175e-01 -2.04888716e-01 2.19929218e-01 -1.20968151e+00
1.11895835e+00 4.15871114e-01 8.26238394e-01 -7.13477492e-01
1.00628294e-01 5.88237464e-01 2.74689227e-01 -6.87991858e-01
-1.09855674e-01 -4.86270934e-01 2.84202605e-01 4.19811010e-01
1.49153367e-01 -6.77066296e-02 2.75568336e-01 -1.09338947e-01
9.05463576e-01 1.67938828e-01 2.42487326e-01 -3.74517530e-01
7.56190121e-01 -4.32533950e-01 1.04593647e+00 2.71306694e-01
-3.68703187e-01 8.90752673e-01 2.28297338e-01 -4.80045944e-01
-1.06102216e+00 -1.02309692e+00 -5.15302956e-01 9.02197063e-01
4.79184017e-02 -8.22538212e-02 -9.72813189e-01 -7.48738766e-01
-1.82899624e-01 2.19110087e-01 -6.24821186e-01 -2.09755883e-01
-7.82503963e-01 -1.05269325e+00 4.50873286e-01 6.71166420e-01
8.10332835e-01 -1.02133393e+00 -8.62157881e-01 3.43186766e-01
-1.35763466e-01 -1.18059766e+00 -5.68246901e-01 -1.30376473e-01
-1.20550847e+00 -1.02251506e+00 -1.13888478e+00 -8.82330775e-01
7.88947225e-01 2.04899386e-02 7.24677920e-01 2.17188969e-01
-1.94972038e-01 2.08052695e-01 -3.84043723e-01 -2.62521058e-01
-2.58478761e-01 4.07302529e-01 3.76794726e-01 1.98107526e-01
5.78834079e-02 -1.09064293e+00 -8.38929415e-01 5.37327051e-01
-1.10347569e+00 1.86284289e-01 6.43938243e-01 9.30962443e-01
5.60936809e-01 5.93270920e-03 9.88144457e-01 -9.00906682e-01
4.88907874e-01 -5.76058686e-01 -2.93602288e-01 4.11912024e-01
-7.20981061e-01 -6.26436472e-02 6.03866100e-01 -7.30537057e-01
-1.24368274e+00 1.14416711e-01 -1.66863337e-01 -2.30465129e-01
-1.75057650e-01 5.44753790e-01 -3.21283191e-01 -1.62250429e-01
4.75369036e-01 2.30935708e-01 3.39409649e-01 -9.24547613e-01
-2.38671020e-01 5.59166431e-01 7.54476607e-01 -9.12040591e-01
6.37612462e-01 4.42902952e-01 1.12751491e-01 -6.14201546e-01
-5.83863258e-01 -2.79480308e-01 -1.25818932e+00 -1.77864477e-01
8.23595047e-01 -5.69634318e-01 5.58625348e-02 8.60877097e-01
-8.96100283e-01 -1.12015061e-01 1.53846279e-01 5.76971889e-01
-4.54301447e-01 6.55572593e-01 -3.03169429e-01 -3.52040201e-01
-4.88620937e-01 -1.43067873e+00 7.26722002e-01 3.77613366e-01
6.03173673e-02 -8.63843799e-01 -3.25862356e-02 3.47947031e-01
5.05199373e-01 2.92201012e-01 1.17596853e+00 -7.58853555e-01
1.95512593e-01 9.22170747e-03 -9.28713381e-02 3.07048023e-01
1.64574236e-01 -2.95857251e-01 -5.87616026e-01 -5.30863404e-01
4.54368085e-01 -2.31531903e-01 5.56114256e-01 3.64181250e-01
1.38129914e+00 1.69490784e-01 -2.77321368e-01 6.80906653e-01
1.05292630e+00 3.60249668e-01 5.12934148e-01 5.91888309e-01
4.57010359e-01 7.61684716e-01 6.18842244e-01 4.08636034e-01
4.95540410e-01 6.81321084e-01 2.12425470e-01 4.96266596e-02
-9.99125987e-02 5.87689839e-02 6.23827800e-02 9.91112113e-01
-3.89393628e-01 4.68527853e-01 -1.18663716e+00 4.71674085e-01
-1.75201869e+00 -6.14490807e-01 9.71755311e-02 2.32412076e+00
9.56946552e-01 9.63554978e-02 4.06278253e-01 -2.99827121e-02
8.18924069e-01 -1.49550572e-01 -8.21775854e-01 2.10650146e-01
-3.02390661e-02 2.34906405e-01 2.20195666e-01 -1.50587693e-01
-8.49190116e-01 5.21170795e-01 6.28194427e+00 5.88839710e-01
-1.22027457e+00 4.85114157e-01 3.30451339e-01 9.62673053e-02
5.73346727e-02 -4.76484410e-02 -5.16316891e-01 6.35063112e-01
4.76176471e-01 -2.66589373e-01 4.37574774e-01 7.48832226e-01
-2.03646868e-02 -6.67658001e-02 -1.06774378e+00 1.04493129e+00
1.83062032e-01 -5.75982213e-01 -1.86060950e-01 -8.26953910e-03
4.02160466e-01 -1.48009464e-01 4.34040278e-03 2.45487928e-01
-4.57847357e-01 -8.40614140e-01 5.85004389e-01 5.33271432e-01
8.85718524e-01 -5.29673219e-01 5.91266990e-01 4.95125860e-01
-1.02254069e+00 -8.52353778e-03 -4.59440261e-01 2.42654055e-01
1.21245205e-01 6.13936722e-01 -5.46302319e-01 6.77669942e-01
9.12502110e-01 4.70174253e-01 -7.81834543e-01 1.20788205e+00
8.50172788e-02 2.59385169e-01 -2.12028638e-01 5.85176408e-01
-3.36521119e-01 -3.84443253e-01 4.56504613e-01 7.97402143e-01
5.12895525e-01 1.80373013e-01 1.59874007e-01 7.21257567e-01
1.12116121e-01 3.51112902e-01 -4.19676393e-01 3.06112975e-01
4.94528890e-01 1.18132341e+00 -8.54758203e-01 -1.55580446e-01
-6.47952795e-01 7.56523967e-01 3.19762081e-01 1.50605410e-01
-8.37618113e-01 -6.39058324e-03 2.78140068e-01 5.24834752e-01
1.55642748e-01 -2.99643457e-01 -2.11147621e-01 -1.37693763e+00
1.38052240e-01 -1.03654039e+00 5.66504180e-01 -5.87320447e-01
-1.56323457e+00 5.31951666e-01 5.13741612e-01 -1.08957672e+00
5.04063852e-02 -3.06542635e-01 -4.92641121e-01 6.86455190e-01
-1.36707020e+00 -1.20284235e+00 -3.27954441e-01 7.70783186e-01
5.29573858e-01 -2.48261362e-01 6.02742970e-01 7.05299556e-01
-6.64886296e-01 5.51271439e-01 -6.86684400e-02 6.02466147e-03
9.32692289e-01 -8.54300022e-01 6.98207393e-02 7.60421216e-01
-5.06345034e-01 8.13605428e-01 4.98501837e-01 -8.76098096e-01
-1.10211301e+00 -7.21674204e-01 4.09151644e-01 6.85373917e-02
5.94344020e-01 -1.27883002e-01 -1.35077310e+00 6.17255807e-01
-7.50554577e-02 1.54239997e-01 6.46224260e-01 6.35802150e-02
-1.86446816e-01 -2.46915460e-01 -1.34541714e+00 4.76345867e-01
1.38910937e+00 -3.78753021e-02 -8.63150239e-01 -4.94088270e-02
3.02268058e-01 -5.14122188e-01 -1.27602315e+00 8.24881196e-01
6.94254637e-01 -9.42780733e-01 9.55831289e-01 -4.01176959e-01
2.32402891e-01 -2.16441348e-01 1.62496939e-01 -1.29441118e+00
-3.48178327e-01 -2.35623389e-01 8.69359635e-03 1.42906392e+00
5.34314662e-02 -9.11800027e-01 4.40198660e-01 7.74545491e-01
-1.30731940e-01 -7.76353717e-01 -1.18542004e+00 -8.94561291e-01
4.13070023e-01 2.00335234e-02 1.06993377e+00 8.75696421e-01
-2.23866165e-01 2.25440741e-01 -2.93941319e-01 5.34935296e-02
6.99053049e-01 8.58028829e-02 5.61180532e-01 -1.70611250e+00
-1.39957651e-01 -3.78168225e-01 -3.46474797e-01 -7.03908384e-01
1.14767566e-01 -8.01532090e-01 -1.41440749e-01 -1.35292816e+00
5.06666303e-01 -5.66730320e-01 -3.86872590e-01 3.93977433e-01
-1.55120909e-01 3.57709937e-02 4.15394530e-02 4.27352518e-01
-1.78094625e-01 5.77023983e-01 1.57989395e+00 3.25964950e-02
-3.43182087e-02 -6.46280944e-02 -5.49868405e-01 8.88252914e-01
9.27146077e-01 -6.50764048e-01 -5.56699038e-01 -5.06482601e-01
-3.37754115e-02 -1.64524019e-02 1.56229883e-01 -1.22816038e+00
3.18190277e-01 -1.79350659e-01 3.68574232e-01 -5.61510801e-01
1.47122905e-01 -7.68029809e-01 3.31318885e-01 3.40225428e-01
1.94741771e-01 2.89141387e-01 1.82940240e-03 3.74570101e-01
-8.93032458e-03 -4.87283528e-01 1.05463183e+00 -2.57567823e-01
-4.77521151e-01 7.40527749e-01 -6.08845241e-02 3.53824109e-01
9.64653969e-01 -2.99597651e-01 -5.47345169e-02 1.82272688e-01
-7.20837712e-01 2.38173470e-01 7.41749346e-01 3.66687417e-01
6.13637388e-01 -1.24284077e+00 -6.97318971e-01 3.35151643e-01
1.02600090e-01 2.60728508e-01 5.19127250e-01 1.35961127e+00
-2.41486296e-01 8.28638580e-03 -7.95900047e-01 -4.52222496e-01
-1.08754110e+00 6.33985162e-01 2.97465473e-01 -3.24030638e-01
-8.36791754e-01 4.39959615e-01 4.60790455e-01 -5.24364173e-01
8.93401578e-02 -1.46758750e-01 -4.45113063e-01 6.43497407e-02
3.95778805e-01 3.66501361e-01 1.78661332e-01 -8.00494790e-01
-4.21300173e-01 8.94091487e-01 -1.45799488e-01 -1.12491727e-01
1.69048619e+00 -2.00921699e-01 -1.50451198e-01 2.92524934e-01
8.60601425e-01 -2.75110364e-01 -1.16115630e+00 -3.53079796e-01
-2.27175392e-02 -4.03237164e-01 -9.50544029e-02 -5.95430493e-01
-1.46410882e+00 8.87971163e-01 6.92357481e-01 -1.90826446e-01
1.36796033e+00 -1.72405899e-01 9.96710837e-01 -1.35339692e-01
7.68900216e-01 -1.32751989e+00 -7.74998888e-02 3.11421424e-01
1.04081750e+00 -1.15197492e+00 1.67283803e-01 -3.23423117e-01
-6.43719673e-01 1.21634543e+00 8.62246156e-01 7.65955597e-02
8.97682607e-01 1.46542907e-01 -1.22704044e-01 -2.91095585e-01
-1.82487458e-01 8.92419294e-02 1.68455943e-01 8.81492913e-01
3.04757774e-01 -1.81328759e-01 -9.58478749e-01 1.05849671e+00
-1.13919772e-01 2.50337571e-01 2.21891001e-01 8.49897087e-01
-2.14366108e-01 -1.43812704e+00 -4.86798555e-01 5.74571609e-01
-5.44022083e-01 1.87775359e-01 -8.08579847e-03 8.29495788e-01
3.73759061e-01 4.81853694e-01 -3.16161275e-01 -2.12803796e-01
3.75280052e-01 2.24406824e-01 8.04202020e-01 -6.80542707e-01
-3.88335645e-01 3.35464440e-02 -2.67730474e-01 -2.08479658e-01
-5.49618781e-01 -9.96118188e-01 -1.43401468e+00 8.09175335e-03
-2.04167932e-01 -1.27328768e-01 5.23503602e-01 9.02864993e-01
2.49676079e-01 3.25000376e-01 3.47211272e-01 -7.18947887e-01
-5.83611369e-01 -1.06299651e+00 -9.31339860e-01 5.53986967e-01
-8.28857943e-02 -1.27287698e+00 -6.41475990e-02 1.26363829e-01] | [14.324653625488281, -1.9573429822921753] |
478aa47e-91a8-4a7e-b311-44f6ce7a63b4 | skin-lesion-analyser-an-efficient-seven-way | 1907.03220 | null | https://arxiv.org/abs/1907.03220v3 | https://arxiv.org/pdf/1907.03220v3.pdf | Skin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet | Skin cancer, a major form of cancer, is a critical public health problem with 123,000 newly diagnosed melanoma cases and between 2 and 3 million non-melanoma cases worldwide each year. The leading cause of skin cancer is high exposure of skin cells to UV radiation, which can damage the DNA inside skin cells leading to uncontrolled growth of skin cells. Skin cancer is primarily diagnosed visually employing clinical screening, a biopsy, dermoscopic analysis, and histopathological examination. It has been demonstrated that the dermoscopic analysis in the hands of inexperienced dermatologists may cause a reduction in diagnostic accuracy. Early detection and screening of skin cancer have the potential to reduce mortality and morbidity. Previous studies have shown Deep Learning ability to perform better than human experts in several visual recognition tasks. In this paper, we propose an efficient seven-way automated multi-class skin cancer classification system having performance comparable with expert dermatologists. We used a pretrained MobileNet model to train over HAM10000 dataset using transfer learning. The model classifies skin lesion image with a categorical accuracy of 83.1 percent, top2 accuracy of 91.36 percent and top3 accuracy of 95.34 percent. The weighted average of precision, recall, and f1-score were found to be 0.89, 0.83, and 0.83 respectively. The model has been deployed as a web application for public use at (https://saketchaturvedi.github.io). This fast, expansible method holds the potential for substantial clinical impact, including broadening the scope of primary care practice and augmenting clinical decision-making for dermatology specialists. | ['Kajol Gupta', 'Saket S. Chaturvedi', 'Prakash. S. Prasad'] | 2019-07-07 | null | null | null | null | ['skin-cancer-classification'] | ['medical'] | [ 3.99055332e-01 1.11931473e-01 -3.61951500e-01 1.65665567e-01
-8.90789151e-01 -6.37201428e-01 1.61772385e-01 3.51880401e-01
-5.87888896e-01 8.22143018e-01 -1.38644159e-01 -6.38241112e-01
1.05529696e-01 -8.84993196e-01 -1.73113048e-01 -8.02884161e-01
2.92801231e-01 -2.96874996e-02 1.71466753e-01 7.01927319e-02
1.49269570e-02 3.89300406e-01 -9.41232443e-01 4.16725636e-01
1.20021355e+00 9.71112609e-01 -6.55415794e-03 1.12822580e+00
2.58596241e-01 5.57072043e-01 -4.50030714e-01 -5.57629645e-01
4.83003370e-02 -1.39943600e-01 -7.10706174e-01 8.73472840e-02
5.98192155e-01 -3.76177102e-01 -1.26666710e-01 9.81152236e-01
6.46316826e-01 -4.96827543e-01 7.43208289e-01 -6.36446834e-01
-7.27317691e-01 -2.98630357e-01 -9.99213815e-01 1.36749279e-02
3.58838528e-01 1.86576426e-01 2.99587280e-01 -3.68743211e-01
6.42453074e-01 5.58438718e-01 9.19708729e-01 9.94615436e-01
-7.22070277e-01 -3.28313529e-01 -5.22576630e-01 1.23394959e-01
-1.20313597e+00 -2.44615246e-02 2.49660984e-02 -3.75174493e-01
7.24673271e-01 6.50278687e-01 7.73408413e-01 9.77990270e-01
6.07399344e-01 3.76582026e-01 1.42430210e+00 -6.53228104e-01
1.35541543e-01 4.49607372e-01 -6.55864179e-02 1.00465000e+00
3.32891971e-01 -1.24355339e-01 -1.21729493e-01 -1.94880679e-01
7.09662616e-01 1.51705131e-01 -1.13003008e-01 3.30265105e-01
-4.45918024e-01 5.62760651e-01 5.99613130e-01 8.46671348e-04
-3.21067661e-01 6.64875656e-02 3.58644038e-01 1.83302328e-01
3.04822922e-01 -9.44262370e-02 -4.56539281e-02 1.88584928e-03
-4.16309148e-01 -4.02693659e-01 5.00194132e-01 9.74376202e-02
8.70885625e-02 -3.88743967e-01 -1.88224822e-01 1.00177264e+00
1.40117973e-01 6.74705803e-01 5.09899616e-01 -3.54803592e-01
-6.52283728e-02 8.67502153e-01 -6.17326610e-02 -6.14271462e-01
-3.47661406e-01 -2.19887808e-01 -1.10391867e+00 3.55369866e-01
5.57390988e-01 -3.82838368e-01 -1.53101206e+00 1.06815600e+00
4.36735243e-01 -1.44763246e-01 -1.52638508e-02 9.79108214e-01
7.23709464e-01 1.97000489e-01 5.67823112e-01 1.54965162e-01
1.44930494e+00 -7.59804547e-01 -3.36664796e-01 9.66260284e-02
5.25209367e-01 -8.27051699e-01 8.41156721e-01 6.05232120e-01
-8.39279652e-01 -1.54061377e-01 -7.52988100e-01 1.00812256e-01
-4.22724128e-01 6.39269650e-01 7.57096231e-01 1.18113291e+00
-1.14193439e+00 3.17142814e-01 -9.98136163e-01 -1.18625593e+00
8.60257030e-01 3.49150240e-01 -5.83807349e-01 -3.18606973e-01
-7.07450271e-01 8.67025614e-01 -2.07169831e-01 -2.44631525e-02
-6.67415798e-01 -7.55629003e-01 -4.62245941e-01 -4.39816862e-01
2.15808377e-02 -7.58707762e-01 1.08125198e+00 -9.03836310e-01
-1.31323135e+00 1.10061181e+00 -1.81344628e-01 -2.23230898e-01
6.82776511e-01 -1.07882373e-01 -6.51996970e-01 4.59437579e-01
-1.36691257e-01 4.36068147e-01 3.45370501e-01 -6.90441966e-01
-8.93179357e-01 -6.21056139e-01 -1.77681312e-01 2.79794872e-01
-7.17158139e-01 -1.78963885e-01 -5.29945970e-01 -1.15696445e-01
-4.39724147e-01 -9.61947381e-01 -3.61787707e-01 6.08641386e-01
-6.57057285e-01 -3.31027363e-03 6.69850230e-01 -1.05610108e+00
9.76689696e-01 -1.89546788e+00 -3.92579675e-01 3.55767220e-01
2.13512048e-01 8.47350061e-01 -1.20918890e-02 4.54971999e-01
1.28048360e-01 4.64760929e-01 -2.35415138e-02 2.39226446e-01
-6.20757401e-01 -3.83055925e-01 4.84413803e-01 5.64551234e-01
2.90435851e-01 7.86576629e-01 -8.40200603e-01 -2.80915558e-01
5.66719830e-01 9.46542978e-01 2.67699659e-01 -1.78262800e-01
1.52692601e-01 -5.45385852e-02 -2.64111131e-01 1.19162667e+00
7.03950047e-01 -6.18802130e-01 4.34371173e-01 -9.22454968e-02
1.57719538e-01 -2.18358442e-01 -8.30479324e-01 1.29366004e+00
-4.00052756e-01 5.83257675e-01 1.75111052e-02 -2.08862528e-01
3.39609891e-01 3.54928702e-01 2.02116370e-01 -6.06954515e-01
8.91630128e-02 4.87126037e-02 7.50437193e-03 -8.22388411e-01
-1.92948088e-01 -1.60487816e-01 3.74263197e-01 3.18048038e-02
-3.08317691e-01 4.45432663e-01 1.30773112e-01 2.00798899e-01
1.27454031e+00 -3.25998753e-01 6.65850997e-01 1.91449821e-01
3.82501453e-01 3.60584170e-01 1.72215309e-02 3.54638904e-01
-3.80492538e-01 3.61145735e-01 2.75052845e-01 -4.23435390e-01
-6.87287390e-01 -1.26542938e+00 -3.77709657e-01 5.56724608e-01
2.89826356e-02 1.17869362e-01 -8.54553044e-01 -6.77560568e-01
1.39912009e-01 1.61070302e-01 -8.21004272e-01 -6.53508008e-02
2.47170657e-01 -1.00342977e+00 7.28445053e-01 5.35655737e-01
7.97026396e-01 -6.21785283e-01 -4.84988719e-01 -2.48171270e-01
2.42938712e-01 -6.37630045e-01 -2.15942174e-01 -2.28872225e-01
-5.56470037e-01 -1.55548990e+00 -1.20239878e+00 -8.87661994e-01
1.00516248e+00 2.73026407e-01 4.32609528e-01 2.29831934e-01
-1.38151479e+00 3.16395700e-01 -1.73137337e-01 -6.15487993e-01
-2.88341135e-01 -4.11360823e-02 -1.53209999e-01 -4.77727875e-02
6.41686678e-01 1.03688210e-01 -1.05023646e+00 -1.12007730e-01
-7.64410317e-01 -9.35762897e-02 1.06154788e+00 8.08407187e-01
6.03291988e-01 -1.02876216e-01 5.01023650e-01 -1.19779277e+00
7.29074121e-01 -5.15958130e-01 -1.64237857e-01 4.99736696e-01
-5.77566326e-01 -7.14308500e-01 4.77095425e-01 -2.47955546e-01
-1.03883529e+00 2.53171027e-01 -5.08543551e-02 1.55656755e-01
-4.72665370e-01 5.05945206e-01 4.90943432e-01 -4.91734385e-01
1.02201200e+00 3.50482985e-02 2.34861687e-01 -1.04950063e-01
-2.27809355e-01 1.06158173e+00 2.74106085e-01 3.20581704e-01
4.23741132e-01 5.95055163e-01 2.48340636e-01 -1.29753637e+00
-6.16713822e-01 -8.11189115e-01 -1.61768526e-01 -4.63663131e-01
8.74428630e-01 -9.94239211e-01 -7.70720959e-01 9.36438143e-01
-6.15679383e-01 -3.79124701e-01 3.53692681e-01 1.19238965e-01
3.33111823e-01 6.19002223e-01 -7.22908258e-01 -9.96775627e-01
-7.68424869e-01 -4.76653963e-01 8.41693938e-01 8.21376860e-01
-3.12655807e-01 -1.35319495e+00 1.27222389e-01 5.39603174e-01
3.65949601e-01 6.65539026e-01 7.35961258e-01 -1.20261781e-01
-1.14555374e-01 -6.98660374e-01 -5.20574749e-01 3.15184146e-01
7.02341437e-01 4.18786258e-01 -1.13954425e+00 -3.81866843e-01
-8.97794366e-01 -4.47439879e-01 9.84102428e-01 7.07104504e-01
1.22709417e+00 5.37581667e-02 -7.75132120e-01 4.62944090e-01
1.92569232e+00 3.43697041e-01 7.48714626e-01 2.93032117e-02
5.30349672e-01 3.01311940e-01 3.06376159e-01 1.76803619e-01
2.06584692e-01 -9.77756754e-02 4.06574130e-01 -6.52785242e-01
-4.20248628e-01 -1.81045964e-01 -1.08512014e-01 6.47036433e-02
-4.22502428e-01 -3.58898968e-01 -1.18545699e+00 7.84353137e-01
-1.16238463e+00 -7.87384510e-01 -2.66343892e-01 2.40596151e+00
7.45865762e-01 -9.29475054e-02 3.41507018e-01 9.81546100e-03
9.15364981e-01 -6.53434753e-01 -6.75365150e-01 -4.58495945e-01
1.50506452e-01 5.71190655e-01 8.18630636e-01 3.90601814e-01
-1.08646643e+00 6.50218010e-01 5.78116751e+00 6.30019605e-01
-1.56218612e+00 -1.99973971e-01 9.80617762e-01 -3.96948978e-02
1.03043534e-01 -5.21577179e-01 -5.23599803e-01 4.08138305e-01
7.30371177e-01 4.36230004e-02 1.17873803e-01 4.76920754e-01
8.24285969e-02 -6.76231027e-01 -5.92935622e-01 8.17852795e-01
-8.55734851e-03 -1.45611811e+00 -7.89547991e-03 2.56884485e-01
6.95234418e-01 -1.94243208e-01 4.69390512e-01 -9.35993716e-02
1.60884187e-01 -1.51437366e+00 -4.64085788e-01 7.06769884e-01
1.61603022e+00 -7.16238558e-01 9.53015327e-01 1.23454943e-01
-7.87287772e-01 -6.90548420e-02 -4.68267016e-02 1.28182158e-01
-2.68595010e-01 5.55789590e-01 -1.39906275e+00 2.13517368e-01
6.64796293e-01 3.77445191e-01 -7.03491509e-01 1.32632506e+00
-8.88707638e-02 7.43541300e-01 -2.35908970e-01 -5.53935468e-01
1.66915476e-01 1.29351601e-01 5.08827679e-02 1.13588262e+00
2.65563726e-01 4.41415608e-02 -3.01087528e-01 1.49380490e-01
9.99664441e-02 1.87428594e-01 -4.84638184e-01 -4.20144647e-02
2.77457654e-01 1.58980691e+00 -5.72127342e-01 9.29891244e-02
-3.06959271e-01 1.17017436e+00 4.67490330e-02 2.76500434e-01
-6.11847758e-01 -6.74852014e-01 2.94706434e-01 3.75664800e-01
-2.21630067e-01 5.38784862e-01 -3.79966080e-01 -5.94254315e-01
-1.09223593e-02 -7.63124883e-01 6.29042983e-01 -4.63784844e-01
-1.29754853e+00 4.10781711e-01 -7.39191592e-01 -8.53206098e-01
1.83915362e-01 -1.11112285e+00 -9.02737021e-01 1.07769358e+00
-1.56910169e+00 -1.39140689e+00 -8.59197378e-01 4.09834594e-01
2.10745096e-01 -2.10175693e-01 1.19254422e+00 -6.45442083e-02
-8.07628870e-01 9.28765953e-01 1.41335398e-01 1.85932413e-01
9.55357134e-01 -1.55447721e+00 -3.90293822e-02 4.42579865e-01
-6.31246448e-01 4.18804437e-01 7.29905814e-02 -7.29531884e-01
-1.25916052e+00 -1.27310514e+00 5.98633587e-01 -2.31061637e-01
4.97191191e-01 9.74792019e-02 -4.14076656e-01 1.03527438e-02
2.09614500e-01 -1.42449662e-01 1.32536542e+00 1.73320808e-02
-2.65532404e-01 -1.74730584e-01 -1.66709805e+00 7.28069246e-01
2.92152077e-01 -5.26554465e-01 3.69868189e-01 7.62360156e-01
-9.56854522e-02 -4.10943300e-01 -9.12110448e-01 1.04455143e-01
9.55113351e-01 -7.59327888e-01 7.21116722e-01 -5.44984758e-01
7.43717909e-01 1.58648893e-01 1.28187507e-01 -1.19880867e+00
-1.69104367e-01 -3.46455902e-01 9.73047316e-02 7.76669800e-01
6.17048204e-01 -6.07204258e-01 1.14799905e+00 6.75675750e-01
4.14720863e-01 -1.24594367e+00 -6.73950493e-01 -3.69407117e-01
1.66358829e-01 2.07244143e-01 -3.25119019e-01 7.11702287e-01
1.49207443e-01 6.02823906e-02 6.84383437e-02 2.68078744e-01
7.12072790e-01 -5.28730392e-01 3.43718082e-01 -1.00897741e+00
-4.88054864e-02 -1.87451512e-01 -4.76063073e-01 -1.65452883e-01
-7.18274713e-01 -7.05279589e-01 -6.48167551e-01 -1.98777330e+00
5.79243064e-01 -1.34222180e-01 -4.62126762e-01 7.89781451e-01
-2.26229265e-01 6.32053316e-01 -2.12355286e-01 -3.08692843e-01
-2.28042290e-01 -5.21687984e-01 1.39242506e+00 -3.13692540e-01
-7.66146407e-02 9.15230662e-02 -9.43325579e-01 5.30851126e-01
1.23922265e+00 3.20373401e-02 -2.76544988e-01 -2.73102522e-01
9.65780243e-02 -4.99687111e-03 6.04276896e-01 -1.13587141e+00
3.81904483e-01 -3.17565471e-01 9.25120890e-01 -1.19954214e-01
3.49400043e-01 -4.73327041e-01 -4.27688770e-02 1.06999516e+00
-1.13270976e-01 -5.63708901e-01 4.19872314e-01 6.78346395e-01
7.56024495e-02 -7.98666384e-03 1.00899088e+00 -2.36129716e-01
-8.07985961e-01 2.08292767e-01 -5.23307502e-01 -4.97177184e-01
1.65841389e+00 -4.30364639e-01 -7.46302903e-01 -2.13934183e-01
-7.29546547e-01 3.80080082e-02 3.70505184e-01 2.66464055e-02
6.58755541e-01 -9.68467414e-01 -6.98203921e-01 -1.14503488e-01
2.81817794e-01 -3.41974497e-01 7.71335721e-01 8.35048378e-01
-1.02452505e+00 3.36621135e-01 -3.61070991e-01 -4.44202393e-01
-1.78713119e+00 -1.48526326e-01 5.75725138e-01 -2.69877557e-02
-1.64366305e-01 1.18380952e+00 -5.12525320e-01 -1.47647291e-01
2.03565091e-01 -1.63662750e-02 1.12950755e-02 -3.27569485e-01
7.31860042e-01 6.21472776e-01 1.74505770e-01 1.86791085e-02
-3.83862704e-01 6.46707237e-01 -6.60410225e-01 1.91249430e-01
9.66544449e-01 3.09341162e-01 -2.95029976e-03 4.58056927e-02
8.95350039e-01 -6.27540350e-02 -7.70675063e-01 3.65400910e-01
-4.77034390e-01 -4.15993840e-01 1.96440399e-01 -1.85399330e+00
-7.47566223e-01 9.49309111e-01 1.27685201e+00 2.85199672e-01
1.37970603e+00 -2.89901525e-01 7.43259788e-01 2.78648376e-01
1.11211009e-01 -1.21979487e+00 -5.87500492e-03 -2.28039324e-01
3.71600896e-01 -1.55324852e+00 4.03328724e-02 -7.44979739e-01
-7.10471988e-01 1.09078360e+00 8.09383214e-01 -1.50606245e-01
4.92958903e-01 2.80359387e-01 6.18666172e-01 -3.03548984e-02
-7.18276083e-01 -1.06034532e-01 2.60441810e-01 9.65369463e-01
7.51266181e-01 4.91780072e-01 -3.56475323e-01 2.16437340e-01
3.76521498e-01 3.00458133e-01 4.99097079e-01 8.53701472e-01
-3.01438361e-01 -9.21448112e-01 -1.10943682e-01 9.33866739e-01
-7.88553655e-01 4.00292762e-02 -9.31410491e-01 8.84302557e-01
9.03524235e-02 1.01463485e+00 -1.21687531e-01 -2.77522832e-01
1.77508295e-02 -2.45365605e-01 5.01591504e-01 -5.77332437e-01
-4.57543403e-01 -1.37186766e-01 2.12840289e-01 -2.11332232e-01
-1.92283764e-01 -3.25443596e-01 -9.28520203e-01 -2.52499670e-01
-1.44820347e-01 -3.32814038e-01 8.80243361e-01 4.92348284e-01
2.89377213e-01 5.02308667e-01 4.14242595e-01 2.22424001e-01
-4.64832187e-01 -8.77058804e-01 -6.51304305e-01 5.95822558e-02
3.20606560e-01 -1.41950220e-01 -6.15552999e-02 1.63966686e-01] | [15.677083015441895, -2.999216318130493] |
ef27c1a6-d35b-4861-a0be-d6069a2ca039 | slisemap-explainable-dimensionality-reduction | 2201.04455 | null | https://arxiv.org/abs/2201.04455v2 | https://arxiv.org/pdf/2201.04455v2.pdf | SLISEMAP: Supervised dimensionality reduction through local explanations | Existing methods for explaining black box learning models often focus on building local explanations of model behaviour for a particular data item. It is possible to create global explanations for all data items, but these explanations generally have low fidelity for complex black box models. We propose a new supervised manifold visualisation method, SLISEMAP, that simultaneously finds local explanations for all data items and builds a (typically) two-dimensional global visualisation of the black box model such that data items with similar local explanations are projected nearby. We provide a mathematical derivation of our problem and an open source implementation implemented using the GPU-optimised PyTorch library. We compare SLISEMAP to multiple popular dimensionality reduction methods and find that SLISEMAP is able to utilise labelled data to create embeddings with consistent local white box models. We also compare SLISEMAP to other model-agnostic local explanation methods and show that SLISEMAP provides comparable explanations and that the visualisations can give a broader understanding of black box regression and classification models. | ['Kai Puolamäki', 'Jarmo Mäkelä', 'Anton Björklund'] | 2022-01-12 | null | null | null | null | ['explainable-models', 'supervised-dimensionality-reduction'] | ['computer-vision', 'computer-vision'] | [ 3.94086875e-02 7.57433593e-01 -1.92029357e-01 -5.21169782e-01
-2.39674240e-01 -1.60854205e-01 1.28540576e+00 4.23633486e-01
3.55664909e-01 1.32031068e-01 6.87497139e-01 -7.10523784e-01
-8.17947149e-01 -4.71033424e-01 -1.63574859e-01 -8.28882337e-01
-2.64159977e-01 7.81367183e-01 -1.75646409e-01 -6.75991774e-02
7.75015593e-01 3.66353214e-01 -1.86156321e+00 4.62752193e-01
6.77939475e-01 1.43792525e-01 2.29475379e-01 1.27924597e+00
-5.85087955e-01 4.19349492e-01 -4.41046596e-01 -1.36716049e-02
2.24280134e-01 -7.69824862e-01 -8.21542919e-01 -4.03615385e-02
8.40506792e-01 1.46780208e-01 1.59909412e-01 4.98317003e-01
1.29340649e-01 2.46537238e-01 1.03924775e+00 -1.62840903e+00
-1.03387833e+00 7.83724636e-02 -4.42947716e-01 1.90185398e-01
2.58626521e-01 -1.46839514e-01 9.76344168e-01 -1.13766086e+00
6.52586699e-01 1.66867959e+00 6.27400815e-01 8.43889475e-01
-1.78106654e+00 -2.53153533e-01 2.67855406e-01 2.36836642e-01
-6.10586107e-01 1.19403088e-02 4.70650017e-01 -5.49365342e-01
1.02380323e+00 8.80415797e-01 4.75775331e-01 5.46828091e-01
2.75792181e-01 3.86608213e-01 1.28795898e+00 -5.31477034e-01
4.05159026e-01 2.03062847e-01 5.95662951e-01 6.71166480e-01
2.90745795e-02 4.05841917e-01 -7.98348784e-01 -3.85173410e-01
9.46322083e-01 3.27190936e-01 6.26614913e-02 -1.32271898e+00
-1.52154541e+00 1.21105278e+00 8.11345816e-01 6.25854433e-02
-5.31706437e-02 2.83823520e-01 7.71770701e-02 4.24647480e-01
6.01689935e-01 7.83571899e-01 -5.40338635e-01 -7.82023072e-02
-6.83101654e-01 3.65105510e-01 7.45886981e-01 4.59524900e-01
1.06976545e+00 -6.51521161e-02 3.20422947e-01 5.34954906e-01
6.78841054e-01 -9.34376493e-02 5.64125419e-01 -9.26974177e-01
1.37457088e-01 7.72316456e-01 -2.59702474e-01 -1.23542821e+00
-7.49100566e-01 -1.76807135e-01 -5.71315050e-01 9.90777314e-01
3.43740404e-01 1.94441527e-01 -8.91314447e-01 1.12851441e+00
5.60357213e-01 1.19284362e-01 2.02478707e-01 1.06646264e+00
1.10294592e+00 6.23852432e-01 1.08402349e-01 3.67578179e-01
1.03989315e+00 -1.22023952e+00 -5.50984204e-01 -4.23320591e-01
1.28803861e+00 -4.03044522e-01 1.09453690e+00 2.33002380e-01
-5.57518899e-01 -7.14733362e-01 -1.07692492e+00 -3.94606113e-01
-7.40146637e-01 -7.76043981e-02 8.95983696e-01 5.68037271e-01
-1.07901943e+00 1.04021502e+00 -8.48344207e-01 -8.30289900e-01
3.37868750e-01 4.52718586e-01 -6.40855193e-01 1.73129022e-01
-4.04472083e-01 1.22323930e+00 2.75940239e-01 -2.88518220e-01
-6.96621120e-01 -9.89144862e-01 -1.00208473e+00 -9.02163163e-02
-1.48075193e-01 -8.60162616e-01 8.95479143e-01 -7.75776565e-01
-9.28830802e-01 6.21164262e-01 -3.68555844e-01 -2.04372957e-01
1.85566485e-01 -2.53328711e-01 -3.18530172e-01 -1.68944776e-01
-9.74431038e-02 1.12918901e+00 8.67196202e-01 -1.50915933e+00
-3.11530650e-01 -4.23425138e-01 -2.69264728e-01 3.96571368e-01
-2.49061540e-01 1.58017613e-02 2.22586110e-01 -6.19459867e-01
4.89876956e-01 -7.00087130e-01 -5.45839608e-01 4.32815254e-01
-4.03737247e-01 -1.76232934e-01 1.31566405e+00 -5.99737763e-01
1.05674672e+00 -1.83217061e+00 3.80986124e-01 2.83905208e-01
7.75747061e-01 2.34710239e-02 -1.77353486e-01 5.50016642e-01
-8.03397775e-01 3.32220584e-01 -3.88938397e-01 -4.82804477e-01
2.77928948e-01 5.77786326e-01 -3.08516949e-01 4.26251918e-01
2.72950619e-01 9.74860132e-01 -9.71909106e-01 -1.21361554e-01
7.71068811e-01 7.34120548e-01 -6.02090716e-01 -5.48088085e-03
-5.67483203e-03 4.79930758e-01 1.38741806e-01 -6.10096194e-02
5.27275741e-01 -1.26412541e-01 5.61690554e-02 5.38007915e-01
-2.23523214e-01 5.47739744e-01 -1.43335164e+00 1.66205847e+00
-1.34944484e-01 1.24924529e+00 -3.08273196e-01 -7.42265701e-01
1.39208472e+00 7.53689650e-03 -9.14586931e-02 -2.11937249e-01
-2.69507915e-01 1.23623125e-01 -1.19713061e-01 -3.11547309e-01
3.59741777e-01 -3.38320792e-01 4.18337137e-01 9.49024260e-01
-2.26031765e-01 -3.21494862e-02 -4.66704398e-01 4.10385877e-01
9.30959344e-01 4.62499499e-01 5.29392600e-01 -6.44080400e-01
1.64790571e-01 4.39807653e-01 -2.81614929e-01 6.19987309e-01
2.64267623e-01 9.20449913e-01 4.96373236e-01 -1.02264023e+00
-1.04764211e+00 -9.46856618e-01 -2.90803134e-01 1.16621709e+00
1.82216555e-01 -1.04743433e+00 -4.92943913e-01 -9.18892920e-01
2.66674966e-01 1.11742187e+00 -1.15312898e+00 -7.28042275e-02
-2.25450769e-01 -4.96037543e-01 -2.33460724e-01 5.81843615e-01
-9.29424390e-02 -9.38738406e-01 -9.17212248e-01 -3.46723348e-01
6.91699982e-01 2.44640291e-01 1.54582306e-03 5.78227282e-01
-1.50089943e+00 -1.13481951e+00 -4.92899686e-01 -5.24930418e-01
1.13309872e+00 5.62609136e-01 1.06085861e+00 5.36225200e-01
-4.45874959e-01 2.38289490e-01 -5.02581522e-02 -4.45484132e-01
-5.18879056e-01 -2.19364643e-01 -1.67593360e-02 -6.08536959e-01
8.24303269e-01 -2.99259812e-01 -5.12411237e-01 5.98577142e-01
-6.45185471e-01 5.22987366e-01 1.75389841e-01 7.18413830e-01
3.00657481e-01 -3.57064694e-01 2.12672755e-01 -1.05498207e+00
7.25747466e-01 -6.86050773e-01 -5.23457304e-02 -8.76341481e-03
-9.63600338e-01 7.34480679e-01 2.08108664e-01 -3.35274994e-01
-7.40090132e-01 2.80326419e-02 3.34788203e-01 -3.15841556e-01
-6.36707366e-01 2.08449706e-01 1.42838582e-01 7.92176053e-02
1.15635216e+00 -2.96525627e-01 5.20082474e-01 -9.91301417e-01
9.97951508e-01 3.09672177e-01 4.37281221e-01 -6.77294731e-02
9.74641502e-01 5.69276214e-01 2.22050413e-01 -7.00268865e-01
-3.01454961e-01 -4.76307362e-01 -1.25709367e+00 -1.23347610e-01
7.18053818e-01 -2.39036635e-01 -2.93613195e-01 -5.46729505e-01
-9.39406514e-01 -2.53021091e-01 -5.65881371e-01 3.95063043e-01
-7.72276223e-01 1.85387880e-01 4.22804028e-01 -6.87554657e-01
2.65311480e-01 -7.16770828e-01 1.12452376e+00 -1.06936013e-02
-1.16890132e+00 -1.81427217e+00 5.68140566e-01 -9.02653039e-02
3.60246807e-01 4.20414984e-01 1.25795269e+00 -1.06099021e+00
-3.15553367e-01 -1.45954918e-02 -2.72953898e-01 -2.95995355e-01
1.11363016e-01 -3.17188129e-02 -1.17960525e+00 1.27260126e-02
-8.40494260e-02 1.53731912e-01 9.70725298e-01 2.11456627e-01
9.89526331e-01 -5.29223859e-01 -7.20810592e-01 5.65571189e-01
1.06525743e+00 -3.45705181e-01 4.68082666e-01 7.05315232e-01
9.25432980e-01 1.33233917e+00 6.44640267e-01 -2.40958761e-02
2.99099863e-01 5.34796834e-01 8.39690030e-01 -6.49409711e-01
-9.88718942e-02 -3.83577645e-01 1.30837053e-01 4.37048346e-01
2.46653080e-01 4.58465695e-01 -9.82743502e-01 4.70680773e-01
-2.27718973e+00 -8.88881087e-01 -1.07108831e+00 2.28810096e+00
2.37286221e-02 -3.84739131e-01 2.24828988e-01 1.76206782e-01
4.33821887e-01 1.16242729e-01 -5.10580540e-01 -1.22197199e+00
1.17709555e-01 -3.14581245e-02 2.19042420e-01 8.48638892e-01
-9.74876165e-01 3.90758842e-01 7.47645426e+00 1.97381720e-01
-4.69365507e-01 1.01705730e-01 2.94178575e-01 -4.48127568e-01
-7.24382341e-01 5.64893305e-01 -4.22989964e-01 -1.02052338e-01
1.14500129e+00 -5.44832796e-02 1.31716207e-01 9.11203504e-01
3.49993110e-01 -3.10523380e-02 -1.60984755e+00 9.40017760e-01
1.31516695e-01 -1.56891501e+00 9.22355875e-02 5.32646120e-01
7.53761411e-01 -3.45864087e-01 1.78478524e-01 -1.92419682e-02
4.98021334e-01 -1.56607175e+00 2.94374049e-01 5.57545543e-01
3.51736993e-01 -7.23973691e-01 2.99058944e-01 5.19257247e-01
-9.00199234e-01 -2.65533000e-01 -6.81020558e-01 -5.45792162e-01
-1.73790187e-01 -2.23193690e-02 -1.03517580e+00 4.26004022e-01
6.16799474e-01 1.14030039e+00 -1.18324506e+00 1.07274210e+00
-5.24151385e-01 1.23366795e-01 -1.98410496e-01 -2.97763161e-02
2.71316290e-01 -1.75589934e-01 6.01621151e-01 1.15767777e+00
3.69625628e-01 -1.82468966e-01 -2.57975876e-01 1.08992815e+00
8.32918465e-01 8.68694410e-02 -9.38762605e-01 3.14174354e-01
-3.47318687e-03 1.31319892e+00 -5.36789834e-01 -3.81041944e-01
-1.36318952e-01 7.54053652e-01 3.25742692e-01 1.34481892e-01
-3.05236936e-01 -1.78917229e-01 1.18821871e+00 2.64843345e-01
-4.07744907e-02 -2.79070914e-01 -9.12190139e-01 -8.78228486e-01
-5.47567010e-01 -7.47292519e-01 6.91988230e-01 -1.25607300e+00
-1.00260603e+00 1.54206097e-01 2.68437147e-01 -1.13240039e+00
-4.68742251e-01 -9.33455408e-01 -1.17747426e+00 1.11175489e+00
-1.08092713e+00 -8.32474411e-01 -3.18850607e-01 2.60419101e-01
5.05248427e-01 -5.70211001e-02 1.22099268e+00 -5.76229751e-01
-1.58929870e-01 2.73323078e-02 3.74882549e-01 -7.07351625e-01
5.26009560e-01 -1.99719405e+00 9.71475780e-01 4.26073641e-01
7.26466715e-01 1.21424282e+00 1.13849783e+00 -7.56954074e-01
-1.00224316e+00 -7.39986598e-01 1.02638841e+00 -1.24912238e+00
5.50639868e-01 -4.21871364e-01 -1.34352231e+00 7.23463953e-01
3.01319480e-01 -3.71987194e-01 8.67911696e-01 6.53411865e-01
-3.18443269e-01 5.99569798e-01 -9.13734853e-01 8.01585197e-01
8.97668183e-01 -3.53594840e-01 -1.01570678e+00 4.51151609e-01
3.33764374e-01 1.28706340e-02 -5.95585406e-01 -1.12803139e-01
5.04773855e-01 -1.29106057e+00 1.03909957e+00 -1.07315254e+00
4.28954542e-01 -5.51546991e-01 2.13184372e-01 -1.72885895e+00
-4.10833567e-01 -6.15626991e-01 -3.53197843e-01 8.68597686e-01
4.64038610e-01 -7.53613174e-01 8.05803299e-01 9.88868892e-01
1.68845564e-01 -5.84123850e-01 -7.84808874e-01 -5.31939626e-01
2.41684496e-01 -5.58469355e-01 7.44028866e-01 9.19746518e-01
5.37431538e-01 2.06361517e-01 -1.40903145e-01 1.40865684e-01
6.86248600e-01 -7.73785785e-02 1.36256385e+00 -1.60892665e+00
-3.01423166e-02 -4.47733641e-01 -7.64192641e-01 -9.88802910e-01
-1.02579460e-01 -1.22681785e+00 -3.26580673e-01 -2.14764500e+00
2.45102808e-01 -2.44132236e-01 6.91649541e-02 6.17858112e-01
-2.01272324e-01 1.33717135e-01 1.31155893e-01 5.84425032e-01
-2.33449683e-01 3.57505530e-01 1.03843105e+00 3.83970320e-01
-3.73984009e-01 -5.02977431e-01 -1.02270818e+00 7.56289124e-01
6.65472686e-01 -7.06844628e-01 -4.86966044e-01 -4.08455759e-01
1.90078318e-01 -6.72482610e-01 1.03769124e+00 -6.49593532e-01
8.34343880e-02 2.49322094e-02 7.06868947e-01 -5.74257135e-01
1.89503849e-01 -7.84107566e-01 3.02577883e-01 3.70667189e-01
-8.28065634e-01 2.29427636e-01 2.77051657e-01 7.99438298e-01
2.54119456e-01 -2.72346586e-01 4.48904455e-01 9.59732085e-02
-7.28979707e-01 -3.15611392e-01 -8.86505470e-02 -6.29088283e-01
1.01423299e+00 -8.35788250e-01 -7.25143075e-01 -4.63902682e-01
-9.08964753e-01 3.33620340e-01 7.58105755e-01 8.13952744e-01
7.09276736e-01 -1.60780263e+00 -4.60224450e-01 6.83789909e-01
3.20437491e-01 -1.82810396e-01 -9.38897133e-02 7.18237400e-01
-5.13359427e-01 5.47345757e-01 -1.08746581e-01 -9.55482543e-01
-1.71757817e+00 8.52670550e-01 2.56396592e-01 3.73610467e-01
-1.30076230e+00 8.29252660e-01 6.89972997e-01 -1.22441471e+00
-5.45564145e-02 -2.03539610e-01 -4.90099549e-01 -8.65009353e-02
8.60365987e-01 7.43265152e-01 -2.10152149e-01 -6.91358328e-01
-3.13841194e-01 8.03022087e-01 2.28096634e-01 -9.40777957e-02
1.52669001e+00 -1.33923084e-01 -2.14651283e-02 8.64763856e-01
1.21991909e+00 -5.46231866e-01 -1.59681833e+00 1.12696355e-02
3.69100928e-01 -9.16420877e-01 4.06364761e-02 -7.57135272e-01
-3.78550738e-01 1.59266627e+00 7.20227599e-01 5.51124632e-01
6.16379857e-01 4.48965192e-01 -2.70494401e-01 1.01642169e-01
-3.59435499e-01 -5.70410907e-01 6.36247471e-02 8.97454619e-02
1.17995012e+00 -1.18202865e+00 3.37483466e-01 -1.53476119e-01
-8.33602428e-01 1.55629563e+00 4.25061882e-01 -1.96938202e-01
4.59023267e-01 -1.93655550e-01 5.48060238e-01 -1.00289023e+00
-9.87149537e-01 5.67398742e-02 7.91434348e-01 1.10017049e+00
3.03332210e-01 1.97306089e-02 2.41529375e-01 6.76767230e-02
-5.85845530e-01 -7.63173282e-01 2.46605933e-01 6.28196239e-01
-6.59949780e-01 -1.07972574e+00 -9.69028056e-01 5.41106880e-01
3.26215744e-01 -2.64423192e-02 -9.93281722e-01 1.18224216e+00
-1.86390474e-01 9.29265618e-01 3.84434402e-01 -2.35107765e-01
-5.48293665e-02 4.59690899e-01 5.83900139e-04 -9.49292362e-01
-5.76252937e-01 -1.24768643e-02 -1.32730290e-01 -7.29145467e-01
-2.77637511e-01 -8.04929793e-01 -1.50775874e+00 -5.03025949e-01
-2.78258741e-01 1.16666958e-01 1.17183673e+00 1.00803792e+00
5.34270763e-01 4.64220911e-01 2.42496163e-01 -1.35129333e+00
-1.43851623e-01 -8.09449971e-01 -3.78142357e-01 4.50350851e-01
6.30036473e-01 -7.30875790e-01 -6.77088022e-01 -1.07228808e-01] | [8.65354061126709, 5.19645881652832] |
72eefc55-57b5-479f-b0ac-c97ca845e611 | no-rumours-please-a-multi-indic-lingual | 2010.06906 | null | https://arxiv.org/abs/2010.06906v1 | https://arxiv.org/pdf/2010.06906v1.pdf | No Rumours Please! A Multi-Indic-Lingual Approach for COVID Fake-Tweet Detection | The sudden widespread menace created by the present global pandemic COVID-19 has had an unprecedented effect on our lives. Man-kind is going through humongous fear and dependence on social media like never before. Fear inevitably leads to panic, speculations, and the spread of misinformation. Many governments have taken measures to curb the spread of such misinformation for public well being. Besides global measures, to have effective outreach, systems for demographically local languages have an important role to play in this effort. Towards this, we propose an approach to detect fake news about COVID-19 early on from social media, such as tweets, for multiple Indic-Languages besides English. In addition, we also create an annotated dataset of Hindi and Bengali tweet for fake news detection. We propose a BERT based model augmented with additional relevant features extracted from Twitter to identify fake tweets. To expand our approach to multiple Indic languages, we resort to mBERT based model which is fine-tuned over created dataset in Hindi and Bengali. We also propose a zero-shot learning approach to alleviate the data scarcity issue for such low resource languages. Through rigorous experiments, we show that our approach reaches around 89% F-Score in fake tweet detection which supercedes the state-of-the-art (SOTA) results. Moreover, we establish the first benchmark for two Indic-Languages, Hindi and Bengali. Using our annotated data, our model achieves about 79% F-Score in Hindi and 81% F-Score for Bengali Tweets. Our zero-shot model achieves about 81% F-Score in Hindi and 78% F-Score for Bengali Tweets without any annotated data, which clearly indicates the efficacy of our approach. | ['Amar Prakash Azad', 'Suranjana Samanta', 'Mohit Bhardwaj', 'Debanjana Kar'] | 2020-10-14 | null | null | null | null | ['rumour-detection'] | ['natural-language-processing'] | [-2.88152248e-01 2.39219218e-01 -2.79050678e-01 -6.84791282e-02
-7.82972455e-01 -2.81678349e-01 1.06798244e+00 2.97483504e-01
-6.11248434e-01 7.83214092e-01 3.05554956e-01 -2.72704959e-01
4.95697945e-01 -1.20550227e+00 -4.30974483e-01 -2.59085417e-01
1.16191179e-01 4.80158240e-01 4.69845593e-01 -1.06650686e+00
3.29813600e-01 1.15279473e-01 -1.01530719e+00 2.09063351e-01
8.97052646e-01 3.23230773e-01 -3.68140042e-01 4.81621265e-01
4.25033532e-02 9.93052900e-01 -7.59168625e-01 -9.14255440e-01
4.19362746e-02 -3.90210003e-01 -7.95729518e-01 -1.40991539e-01
4.40526903e-02 -4.36464012e-01 -5.07164299e-01 1.11146927e+00
4.73303199e-01 -2.61540502e-01 5.23028612e-01 -1.19163871e+00
-4.98340458e-01 6.90605879e-01 -6.59014702e-01 3.18351179e-01
2.76098371e-01 1.45286411e-01 7.81817913e-01 -9.70921576e-01
7.97922492e-01 1.31356454e+00 7.89725184e-01 4.51073766e-01
-7.49410927e-01 -8.40920091e-01 -3.77251059e-01 6.81079030e-02
-1.30687845e+00 -3.42115104e-01 6.42314911e-01 -5.44204831e-01
6.63499296e-01 3.33634108e-01 5.69337666e-01 1.22729576e+00
1.11952201e-01 7.85918951e-01 1.09885418e+00 -2.53794670e-01
7.29783177e-02 3.96873623e-01 3.65422107e-03 7.88909972e-01
4.24566984e-01 -1.99302435e-01 -4.29806054e-01 -4.11644012e-01
1.29508242e-01 1.99493449e-02 -5.62903509e-02 5.83030820e-01
-1.08731711e+00 1.48154950e+00 3.61308604e-01 6.87632442e-01
-1.80897981e-01 -9.50964093e-02 6.18730128e-01 3.59729052e-01
1.03018439e+00 5.04425585e-01 -1.63088053e-01 -2.48442963e-01
-9.81648028e-01 2.78854251e-01 8.05727482e-01 5.34175992e-01
6.09809577e-01 -1.95794143e-02 -3.34842727e-02 9.74727571e-01
2.31842063e-02 8.87709916e-01 5.79725802e-01 -2.05256879e-01
5.87072074e-01 5.53075314e-01 3.43586922e-01 -1.78319800e+00
-4.37931061e-01 -1.54679477e-01 -8.96282136e-01 -5.52694857e-01
3.38385075e-01 -1.82570606e-01 -7.22035527e-01 1.36163914e+00
4.29976523e-01 2.74667382e-01 -4.23645005e-02 9.17428374e-01
8.72723281e-01 8.30388546e-01 -3.43597084e-01 -3.21270853e-01
1.35519922e+00 -7.23775566e-01 -7.65088439e-01 -2.48244181e-01
8.45082641e-01 -8.10699701e-01 9.08004522e-01 2.43751869e-01
-5.11268616e-01 4.93169986e-02 -8.38252842e-01 1.48789495e-01
-7.68503964e-01 -4.22797918e-01 4.27787095e-01 1.01824963e+00
-4.40923631e-01 5.14643848e-01 -5.70313454e-01 -4.67320740e-01
5.84672987e-01 -1.48740485e-02 -3.71691674e-01 -8.65848064e-02
-1.79283214e+00 9.74909127e-01 2.17291117e-01 -1.95317954e-01
-6.57374620e-01 -3.37042868e-01 -7.49678254e-01 -4.26546544e-01
3.80856752e-01 1.54286966e-01 7.25891292e-01 -6.80841088e-01
-1.08185387e+00 1.08123302e+00 3.13104168e-02 -6.32227242e-01
8.33098769e-01 -7.19185323e-02 -7.63692319e-01 1.74077183e-01
5.52009463e-01 2.06136197e-01 1.03074801e+00 -1.02410197e+00
-5.84748268e-01 -2.28107989e-01 -2.77332980e-02 -3.63516688e-01
-6.30500495e-01 4.88997519e-01 -2.11840853e-01 -7.03415692e-01
-1.00563623e-01 -1.00341547e+00 -1.23153381e-01 -6.24350786e-01
-6.37123406e-01 -7.20342156e-03 1.14627790e+00 -8.33798707e-01
1.47597647e+00 -2.00126815e+00 -4.28434879e-01 1.29800469e-01
5.11303067e-01 6.36473596e-01 4.56966907e-02 6.74566150e-01
4.40294772e-01 3.86896193e-01 -2.98691303e-01 -7.22058192e-02
-5.43711595e-02 1.56369433e-01 -4.97244507e-01 8.39493692e-01
4.17716205e-01 8.20616305e-01 -1.34997678e+00 -3.84073853e-01
-1.24001149e-02 3.85687590e-01 -5.76781690e-01 -1.49316177e-01
6.73568323e-02 3.33141744e-01 -4.93849218e-01 7.18554914e-01
8.48008573e-01 -2.65792668e-01 1.72634721e-01 1.77517027e-01
-2.32198134e-01 2.07368568e-01 -5.80476105e-01 7.73019075e-01
-2.90881664e-01 5.99790871e-01 -7.94177204e-02 -9.63599026e-01
9.45182920e-01 1.83897018e-01 3.24076265e-01 -7.51518965e-01
5.48848867e-01 5.42984545e-01 -1.46901160e-01 -5.08016586e-01
6.79763556e-01 -3.34058255e-01 -5.70297599e-01 5.19680798e-01
-2.73584545e-01 -2.98795879e-01 6.97888583e-02 5.84567308e-01
1.01834571e+00 -5.33589482e-01 4.01199967e-01 -2.47525796e-01
6.01474822e-01 1.39233842e-01 1.81571499e-01 8.30104351e-01
-5.22407532e-01 3.52217287e-01 5.07337093e-01 -6.83460772e-01
-9.66467023e-01 -5.67323267e-01 -1.03180669e-01 1.10902750e+00
1.87935323e-01 -4.64365661e-01 -6.47479594e-01 -8.29106569e-01
-8.65814462e-03 7.51042843e-01 -7.22363353e-01 -1.14053182e-01
-6.23424172e-01 -1.31615043e+00 1.02656078e+00 -4.06304985e-01
7.75266707e-01 -8.37495506e-01 -4.37917680e-01 3.37957740e-01
-7.01493502e-01 -1.26646829e+00 -1.75017551e-01 -2.90533036e-01
-2.38405988e-01 -9.64616835e-01 -6.84434533e-01 -5.18942416e-01
2.86226392e-01 4.59164172e-01 7.64892399e-01 1.92995653e-01
-2.19577655e-01 -2.33108178e-01 -4.73512441e-01 -5.13986588e-01
-7.77586818e-01 -2.57774424e-02 2.18330115e-01 1.51145339e-01
3.60706270e-01 -1.70746446e-01 -3.44269305e-01 4.37477380e-01
-8.51659536e-01 -2.40264647e-02 3.17399763e-02 8.34981740e-01
-1.12882026e-01 -5.84517345e-02 8.74227822e-01 -1.24219120e+00
4.66070026e-01 -9.65023816e-01 -3.17032039e-01 -2.81763941e-01
-2.74507731e-01 -3.80859762e-01 5.90819895e-01 -3.97299349e-01
-6.60154998e-01 -3.85158300e-01 -2.93474227e-01 6.75147921e-02
2.64585584e-01 5.87362647e-01 4.30020392e-01 -2.09493985e-04
8.33377481e-01 9.64938551e-02 -9.03359149e-03 -1.51444346e-01
3.61132681e-01 1.30247986e+00 2.38354832e-01 4.22251299e-02
1.07130110e+00 9.41939175e-01 -3.21706116e-01 -1.40850949e+00
-1.15136313e+00 -6.67171836e-01 -3.76067847e-01 -1.31091148e-01
6.84250414e-01 -1.02523899e+00 -4.42239940e-01 8.04285765e-01
-1.26505029e+00 4.34934609e-02 3.66532415e-01 1.25645667e-01
-7.03511387e-02 4.83612239e-01 -8.50624561e-01 -9.28394616e-01
-2.97415078e-01 -8.08665156e-01 9.07335639e-01 -3.74944091e-01
-2.78322548e-01 -1.03479767e+00 2.86226571e-01 6.75292313e-01
6.10680401e-01 5.57500124e-01 4.48622942e-01 -1.12634802e+00
-3.39689404e-02 -4.51648325e-01 -6.89670622e-01 8.67714584e-02
3.62317711e-01 -2.61745751e-01 -9.78274584e-01 -3.15295637e-01
-2.39803437e-02 -5.83227634e-01 9.48974252e-01 -2.31061682e-01
3.87517542e-01 -9.07198727e-01 -3.19144815e-01 -8.89675543e-02
1.31302166e+00 -3.42552453e-01 6.44028723e-01 4.41872329e-01
7.43070841e-01 6.00302935e-01 7.94550955e-01 8.86946142e-01
5.49686313e-01 5.66973090e-01 4.38420147e-01 -3.06609441e-02
2.29158223e-01 -1.77664161e-01 4.78099793e-01 1.01075375e+00
4.54114843e-03 -2.29514062e-01 -1.18447828e+00 8.83976579e-01
-1.68426001e+00 -1.30524302e+00 -4.93096530e-01 2.12384534e+00
9.26211178e-01 2.25253060e-01 4.39755589e-01 2.11575076e-01
7.64799476e-01 4.11900669e-01 1.32047176e-01 -4.56275403e-01
-1.68109581e-01 9.52365771e-02 6.48016632e-01 7.79343605e-01
-1.41705966e+00 1.49239600e+00 5.32571840e+00 1.15590560e+00
-1.50962770e+00 5.99820375e-01 6.42452538e-01 2.14680657e-01
-2.23036960e-01 -2.45839134e-01 -7.50343382e-01 6.98298097e-01
1.05189157e+00 -1.56187400e-01 3.12148660e-01 5.93489468e-01
6.17801964e-01 -3.21970321e-02 -6.12732805e-02 7.87994742e-01
3.50779623e-01 -1.53407431e+00 -2.40218908e-01 2.17606544e-01
8.61419261e-01 5.87169468e-01 -1.39746964e-01 4.12043869e-01
2.88475782e-01 -9.63213027e-01 5.63751101e-01 -9.94161218e-02
7.64268517e-01 -9.15379941e-01 9.20448959e-01 7.71870434e-01
-6.14437640e-01 5.93967400e-02 -5.27921855e-01 -3.22137415e-01
2.22981542e-01 8.28365445e-01 -1.27522826e+00 2.87589073e-01
3.47241104e-01 7.23280489e-01 -4.89658415e-01 4.85416323e-01
-1.10228524e-01 8.89521122e-01 -3.70659441e-01 -3.87646526e-01
6.24180198e-01 1.06999509e-01 7.18142211e-01 1.55240619e+00
1.75655961e-01 2.56717931e-02 2.04211250e-01 4.68044728e-01
-1.24248534e-01 4.12619114e-01 -1.05263197e+00 -3.74425590e-01
2.45002136e-01 1.08834457e+00 -6.37298763e-01 -5.39146185e-01
-3.44964117e-01 1.11694145e+00 1.51614204e-01 -1.18181117e-01
-1.15550292e+00 -4.03985232e-01 3.19595814e-01 4.17486310e-01
6.63987175e-02 -5.45594916e-02 1.09920427e-01 -1.41261697e+00
-4.92132455e-01 -1.02765226e+00 2.42136732e-01 -1.09991990e-01
-1.34152961e+00 6.42206728e-01 -3.16263378e-01 -1.09202683e+00
-1.09749198e-01 -3.01938921e-01 -4.90711838e-01 3.16356868e-01
-1.45842648e+00 -1.27026212e+00 -1.57124680e-02 4.62420821e-01
4.35062855e-01 -1.40793547e-01 6.26647294e-01 4.45766240e-01
-4.38380033e-01 4.72939521e-01 1.98577210e-01 4.96803761e-01
8.13239276e-01 -6.40877187e-01 5.89602888e-01 7.06413269e-01
1.52581427e-02 3.85163486e-01 8.70959699e-01 -1.03851104e+00
-1.12606037e+00 -1.38379586e+00 1.55522752e+00 -6.14835799e-01
1.37683964e+00 -5.39564908e-01 -7.30570376e-01 4.57472056e-01
-1.55435339e-01 -1.82114869e-01 4.16850448e-01 -1.43319935e-01
-5.91012895e-01 3.81913871e-01 -1.44336879e+00 5.57253838e-01
6.18446350e-01 -4.91292179e-01 -4.11667287e-01 9.21555936e-01
7.39798486e-01 -5.16090430e-02 -4.02633697e-01 1.26597628e-01
4.72560048e-01 -1.07519209e+00 7.24454820e-01 -8.45406175e-01
7.08734214e-01 8.16139355e-02 -1.72010943e-01 -1.15751910e+00
-1.12455688e-01 -7.91709661e-01 3.40457827e-01 9.77917433e-01
4.69684124e-01 -8.88736486e-01 7.05618620e-01 -3.65703441e-02
2.69743323e-01 -3.81543070e-01 -1.03728104e+00 -8.02895665e-01
2.09858105e-01 -5.84433317e-01 1.52055591e-01 1.58450174e+00
2.42077008e-01 4.31732088e-01 -1.05042565e+00 1.19313098e-01
5.00530124e-01 -1.24718413e-01 9.55640435e-01 -1.04701972e+00
-4.02722359e-02 -1.85097516e-01 -4.50092822e-01 -3.68008226e-01
-3.21871042e-02 -7.15234160e-01 -1.08635180e-01 -1.03660047e+00
3.37053984e-01 -3.71421486e-01 2.36732677e-01 4.21909571e-01
-5.63020557e-02 1.07031703e+00 1.54017806e-01 3.91115010e-01
-5.56818664e-01 2.51700878e-01 1.14288855e+00 -3.51936579e-01
-1.70133471e-01 -1.76863909e-01 -5.44662297e-01 9.24037635e-01
7.61547327e-01 -7.76614308e-01 1.19474187e-01 1.01251565e-01
5.79767764e-01 -7.46463984e-02 3.38524401e-01 -6.32684469e-01
-2.34141335e-01 -2.97635496e-01 -2.57780492e-01 -3.07334423e-01
3.53695273e-01 -3.21491003e-01 -3.59686553e-01 1.02432871e+00
1.13988563e-01 -3.31100374e-01 -1.55766249e-01 5.15120029e-01
-2.31788397e-01 5.24454825e-02 1.08728290e+00 -1.80830002e-01
-3.04402232e-01 1.88353464e-01 -7.76196957e-01 4.28223282e-01
7.72298694e-01 1.24222152e-01 -7.51201451e-01 -7.32229292e-01
-4.36413318e-01 3.57917920e-02 4.17624265e-01 4.81373370e-01
5.27061999e-01 -1.09310377e+00 -1.19842374e+00 9.22831818e-02
3.81226987e-01 -7.40247369e-01 -1.60164349e-02 1.20115721e+00
-7.51971066e-01 3.17032337e-01 2.82769036e-02 -2.00114280e-01
-1.11628163e+00 4.23938870e-01 -1.76096067e-01 -3.71612877e-01
-3.33853781e-01 7.62590468e-01 -1.39864132e-01 -7.35947788e-01
-4.74218905e-01 1.27570838e-01 -2.16535896e-01 4.21995044e-01
7.35631108e-01 5.72400808e-01 -5.58137335e-02 -1.28163207e+00
-6.44373357e-01 -8.20575934e-03 -1.40744492e-01 -5.35976589e-02
1.32547307e+00 -1.32009014e-01 -4.22628015e-01 4.24939424e-01
1.23064613e+00 7.96766937e-01 -1.98590681e-01 4.02127095e-02
9.78971273e-02 -6.65077090e-01 -9.99047682e-02 -7.48761773e-01
-6.26926363e-01 6.62059367e-01 2.50966605e-02 6.04703963e-01
4.13549483e-01 6.12247139e-02 1.16159105e+00 2.11672589e-01
5.81413865e-01 -9.64380324e-01 2.99169928e-01 7.78849423e-01
6.80277884e-01 -1.63977730e+00 -6.11699075e-02 -6.56505346e-01
-7.20658302e-01 6.91641748e-01 1.71264812e-01 -2.63539821e-01
6.58757865e-01 -1.25324622e-01 1.71593711e-01 -2.98754245e-01
-3.56214315e-01 -1.06212161e-01 -3.54839629e-03 3.69977236e-01
3.40671152e-01 2.94871241e-01 -7.21375048e-01 4.85939085e-01
-3.13417137e-01 -2.40084216e-01 1.02097368e+00 6.93397760e-01
-8.32614899e-01 -7.83782005e-01 -3.90767962e-01 3.59615088e-01
-7.78146327e-01 -2.89905638e-01 -6.86849892e-01 8.70840967e-01
7.36877695e-02 1.18112397e+00 -1.97928637e-01 -5.31240463e-01
-2.53188550e-01 -2.39051878e-01 3.40966135e-02 -5.18232465e-01
-6.43252373e-01 -3.83058935e-02 4.83877152e-01 -4.13811684e-01
-2.23143280e-01 -2.60724306e-01 -1.05518293e+00 -8.21504295e-01
-5.17191052e-01 1.51710644e-01 5.34974813e-01 1.12136281e+00
8.94059613e-02 -3.28101426e-01 9.34775233e-01 -4.87691939e-01
-5.04590988e-01 -1.02992749e+00 -4.09836859e-01 4.87611592e-01
4.27929878e-01 -4.46238041e-01 -5.72069228e-01 -4.16346461e-01] | [8.203045845031738, 10.29011058807373] |
7df633dd-9452-40e8-b266-7a9c5fed3f94 | eautodet-efficient-architecture-search-for | 2203.10747 | null | https://arxiv.org/abs/2203.10747v1 | https://arxiv.org/pdf/2203.10747v1.pdf | EAutoDet: Efficient Architecture Search for Object Detection | Training CNN for detection is time-consuming due to the large dataset and complex network modules, making it hard to search architectures on detection datasets directly, which usually requires vast search costs (usually tens and even hundreds of GPU-days). In contrast, this paper introduces an efficient framework, named EAutoDet, that can discover practical backbone and FPN architectures for object detection in 1.4 GPU-days. Specifically, we construct a supernet for both backbone and FPN modules and adopt the differentiable method. To reduce the GPU memory requirement and computational cost, we propose a kernel reusing technique by sharing the weights of candidate operations on one edge and consolidating them into one convolution. A dynamic channel refinement strategy is also introduced to search channel numbers. Extensive experiments show significant efficacy and efficiency of our method. In particular, the discovered architectures surpass state-of-the-art object detection NAS methods and achieve 40.1 mAP with 120 FPS and 49.2 mAP with 41.3 FPS on COCO test-dev set. We also transfer the discovered architectures to rotation detection task, which achieve 77.05 mAP$_{\text{50}}$ on DOTA-v1.0 test set with 21.1M parameters. | ['Xiaokang Yang', 'Juanping Zhao', 'Junchi Yan', 'Jiale Lin', 'Xiaoxing Wang'] | 2022-03-21 | null | null | null | null | ['object-detection-in-aerial-images'] | ['computer-vision'] | [-9.14625749e-02 -5.00712812e-01 2.01557904e-01 -4.48716283e-02
-3.02625895e-01 -4.98470426e-01 1.39120474e-01 -2.08507240e-01
-9.06711340e-01 1.14348926e-01 -6.34949803e-01 -4.27715629e-01
3.38503510e-01 -8.10227633e-01 -8.78488719e-01 -5.93037188e-01
-2.13702414e-02 7.08087906e-02 9.95940626e-01 8.32745135e-02
2.82633573e-01 5.20558059e-01 -1.57166970e+00 1.46955743e-01
6.27608657e-01 1.25482893e+00 6.14450991e-01 7.15726972e-01
-2.83072777e-02 5.56082606e-01 -6.30941629e-01 -6.00492775e-01
5.37296534e-01 4.95143570e-02 -3.50319803e-01 -1.13759108e-01
5.94090760e-01 -6.60895348e-01 -5.89399517e-01 1.25533342e+00
5.81665695e-01 -1.86490029e-01 3.15613925e-01 -9.78492141e-01
-3.36462468e-01 4.37150896e-01 -1.14913380e+00 6.34655058e-01
-2.42725939e-01 2.62013525e-01 6.07126534e-01 -1.20888031e+00
2.93227136e-01 1.15021574e+00 6.51110411e-01 4.05120403e-01
-7.49608874e-01 -1.02630401e+00 2.08314031e-01 3.16439360e-01
-1.48503363e+00 -2.31442526e-01 1.19372763e-01 -3.44712049e-01
1.16796601e+00 9.95634794e-02 6.92924738e-01 7.03942716e-01
3.26908194e-03 8.81034076e-01 7.00557292e-01 -2.37130225e-01
-1.37950256e-01 -1.56484529e-01 2.02788860e-01 1.07120883e+00
7.94223309e-01 1.20637573e-01 -4.31956381e-01 1.82022721e-01
1.20855427e+00 8.05232301e-02 -1.87292233e-01 -8.39275680e-03
-1.13467574e+00 5.55402040e-01 6.89222276e-01 -2.37137869e-01
-1.11853592e-01 4.15741324e-01 6.95978940e-01 1.00353919e-01
-9.31750089e-02 1.60175353e-01 -4.37939912e-01 -1.20055914e-01
-6.62617862e-01 1.20639950e-02 5.18328905e-01 1.24897230e+00
7.02232540e-01 1.21368535e-01 -1.79557651e-01 6.70113266e-01
1.95479617e-01 5.61366260e-01 1.75884649e-01 -5.40155053e-01
4.63522434e-01 7.04014361e-01 1.26606999e-02 -1.03457558e+00
-5.65862000e-01 -9.38563943e-01 -9.04779732e-01 -1.60462279e-02
4.64233577e-01 -3.00756097e-01 -8.69073927e-01 1.21789384e+00
5.74742556e-01 5.24056494e-01 -2.30221093e-01 1.22068274e+00
8.73066366e-01 6.27964854e-01 -3.37591991e-02 1.13383140e-02
1.89180624e+00 -1.46173406e+00 -4.80157435e-02 -2.96006739e-01
7.68671691e-01 -9.55351472e-01 9.58297670e-01 5.06404102e-01
-9.34103549e-01 -8.39126706e-01 -1.08307230e+00 -1.07055724e-01
3.03536318e-02 8.76809597e-01 8.62143338e-01 6.02538705e-01
-7.23212898e-01 2.97432005e-01 -1.03508151e+00 -1.43020838e-01
7.54228950e-01 3.64959717e-01 1.47618413e-01 -1.67778917e-02
-6.03418529e-01 3.34137768e-01 5.84664345e-01 2.40447223e-01
-9.42191303e-01 -7.27438867e-01 -4.60768849e-01 2.26012826e-01
5.69122434e-01 -4.75846231e-01 1.25275517e+00 -4.69554216e-01
-1.32625663e+00 5.78150988e-01 1.70212358e-01 -5.44963539e-01
6.15844071e-01 -4.40537483e-01 -2.96680719e-01 5.93532696e-02
3.44018787e-02 7.75253654e-01 8.32937717e-01 -4.83831018e-01
-1.15938103e+00 -2.66119987e-01 5.17316684e-02 9.48596448e-02
-6.39907360e-01 3.90148461e-01 -1.33144271e+00 -5.54391503e-01
2.08990052e-01 -8.81212771e-01 -2.56895721e-01 3.06399912e-01
-4.10658360e-01 -2.42156208e-01 7.96035945e-01 -2.41629496e-01
1.32771027e+00 -2.25527811e+00 -3.17073166e-01 6.76343217e-02
4.36161339e-01 6.47055566e-01 -1.83732342e-02 -3.02961081e-01
2.94356167e-01 -3.42208475e-01 1.58924073e-01 -2.63975918e-01
-1.09021105e-01 -6.36827946e-02 -1.85278550e-01 5.82594514e-01
7.13555068e-02 7.79406905e-01 -6.61760569e-01 -5.36306441e-01
1.18004218e-01 4.11362648e-01 -5.98811805e-01 -1.06906526e-01
-3.86957708e-03 -1.63452160e-02 -5.78062236e-01 8.41850698e-01
1.04957068e+00 -6.11956298e-01 -1.25903621e-01 -4.50931251e-01
-4.35241938e-01 4.68100794e-02 -1.39941001e+00 1.62670803e+00
-2.10957184e-01 7.38199532e-01 -3.83092673e-04 -7.58368671e-01
9.31164026e-01 -3.69268477e-01 -1.58788469e-02 -6.68651819e-01
5.25120676e-01 3.35905850e-01 2.58419901e-01 -2.05097169e-01
4.05446231e-01 6.64813459e-01 9.83097106e-02 2.17444718e-01
-7.59057105e-02 4.51339066e-01 3.39651883e-01 9.18279961e-02
1.28748536e+00 -1.60248458e-01 -7.32487962e-02 -3.71073663e-01
4.94169354e-01 1.89219043e-02 6.75891280e-01 9.20482755e-01
-1.84157193e-01 3.74713451e-01 5.04655719e-01 -7.20998943e-01
-8.75296235e-01 -7.75031805e-01 -3.50770235e-01 1.26084578e+00
4.71533537e-01 -5.77629030e-01 -7.83840835e-01 -3.77233237e-01
-1.77685648e-01 2.07454618e-02 -3.65771979e-01 8.35578889e-02
-8.05261374e-01 -1.09432971e+00 8.05278838e-01 9.36198056e-01
1.01237988e+00 -8.65780652e-01 -1.26472819e+00 2.82003969e-01
2.01560497e-01 -1.31383359e+00 -4.67304617e-01 4.35113534e-02
-7.31478333e-01 -1.12443924e+00 -6.30895793e-01 -1.00579405e+00
6.85101569e-01 7.18285859e-01 9.51237977e-01 2.31934682e-01
-8.54587436e-01 -2.04422370e-01 -2.48525500e-01 -4.81814235e-01
3.40099961e-01 1.85858980e-01 1.93140823e-02 -1.33732080e-01
4.06450748e-01 -1.33860826e-01 -1.13888454e+00 6.54588342e-01
-5.36010027e-01 2.19020635e-01 8.98110926e-01 6.94116533e-01
8.19283009e-01 -1.25033021e-01 1.72370553e-01 -5.12675226e-01
1.14262678e-01 -3.95099297e-02 -1.33609331e+00 1.99072078e-01
-4.43607241e-01 -2.33580261e-01 4.50706393e-01 -6.58423841e-01
-8.36756706e-01 4.31281388e-01 1.16120704e-01 -7.80791759e-01
2.04742312e-01 -1.96997803e-02 1.85430661e-01 -4.63728011e-01
7.82156765e-01 3.28695834e-01 -3.31827223e-01 -5.61162651e-01
9.22364444e-02 3.85657668e-01 8.49350929e-01 -3.54593337e-01
7.50418365e-01 5.23337185e-01 -4.12660874e-02 -7.24850237e-01
-5.98035932e-01 -5.79363942e-01 -2.76237428e-01 -1.15026072e-01
7.84179330e-01 -1.31234145e+00 -1.09625936e+00 7.75625527e-01
-1.28457761e+00 -1.98750779e-01 2.59199858e-01 4.97908801e-01
1.15402251e-01 3.76960218e-01 -8.36110473e-01 -5.06949484e-01
-7.19278395e-01 -1.36745644e+00 1.00599945e+00 5.06759882e-01
4.74993736e-01 -1.02347232e-01 -4.46058989e-01 -5.60045466e-02
4.16759431e-01 -9.09112468e-02 2.12703943e-01 -1.31819859e-01
-1.06700289e+00 -3.32828015e-01 -1.16792512e+00 1.25650808e-01
-4.52645868e-01 1.69104431e-02 -6.95140362e-01 -4.99983251e-01
-2.28093535e-01 -2.06208289e-01 1.24492741e+00 2.19951630e-01
1.56523430e+00 8.70219246e-02 -6.03029490e-01 9.87418771e-01
1.48147082e+00 9.71342102e-02 5.65155745e-01 4.32686687e-01
9.09088969e-01 -4.49162014e-02 7.26025581e-01 7.42246389e-01
1.32572040e-01 6.76064849e-01 5.96915483e-01 -3.47502120e-02
-1.45710558e-01 -7.87852518e-03 2.20895454e-01 6.23583078e-01
-2.36828431e-01 -1.06622830e-01 -9.37523186e-01 3.07957590e-01
-1.74414492e+00 -5.22625923e-01 -5.39371669e-01 1.98373175e+00
5.49627244e-01 4.57309127e-01 2.07165033e-01 -2.36836255e-01
8.68688285e-01 -1.77666545e-01 -6.89117432e-01 8.26370195e-02
-1.11698277e-01 3.27507406e-01 9.01529253e-01 2.39405013e-03
-1.30617034e+00 1.11048782e+00 5.06719875e+00 1.09631956e+00
-1.12456870e+00 1.43217489e-01 5.47414660e-01 -2.38827199e-01
5.68868935e-01 -5.59890233e-02 -1.40524757e+00 4.83336180e-01
4.30753827e-01 1.57833397e-01 1.46839052e-01 1.21948254e+00
-2.24839985e-01 3.15226018e-02 -8.11948180e-01 1.47854257e+00
-1.44074291e-01 -1.51070559e+00 -1.66595250e-01 -7.10291117e-02
5.90993822e-01 3.86431962e-01 -3.46880481e-02 3.11238825e-01
-1.91807561e-02 -7.66378284e-01 8.25108826e-01 -3.32635604e-02
9.72140908e-01 -7.32706249e-01 5.97314596e-01 3.36465478e-01
-1.61470389e+00 -2.24583939e-01 -9.49314535e-01 -9.86539423e-02
-1.02344319e-01 4.17415708e-01 -6.19476080e-01 7.18636885e-02
1.22360277e+00 5.08658707e-01 -7.94338942e-01 1.48558557e+00
-1.89664125e-01 4.35285032e-01 -7.52365887e-01 -3.92329931e-01
3.09645355e-01 5.09337708e-02 3.66366178e-01 1.50947964e+00
4.94503647e-01 1.96338430e-01 2.28157207e-01 5.87407172e-01
-2.28505298e-01 4.93466966e-02 -2.66613737e-02 4.09442604e-01
6.88840628e-01 1.57572031e+00 -1.09008682e+00 -3.63629818e-01
-5.77926278e-01 1.11352396e+00 3.71458888e-01 -2.07051565e-03
-1.41919768e+00 -6.53884888e-01 5.05549729e-01 -7.26269186e-02
7.95580626e-01 -2.11997524e-01 -1.05154812e-01 -1.12130475e+00
2.91747034e-01 -5.63250184e-01 2.92184711e-01 -3.43045026e-01
-8.78796279e-01 6.34293556e-01 -3.88476908e-01 -1.36421418e+00
4.27759230e-01 -9.95110691e-01 -6.75683916e-01 4.93820250e-01
-1.40064669e+00 -8.83754313e-01 -8.14183891e-01 4.95680362e-01
5.41139722e-01 -3.04012150e-01 3.12446982e-01 6.82943165e-01
-1.05639911e+00 1.16869020e+00 -2.11829823e-02 4.82077837e-01
4.54596639e-01 -8.21696937e-01 8.81325543e-01 1.03294778e+00
1.03463121e-01 4.69779760e-01 2.93438464e-01 -3.87868345e-01
-1.81596482e+00 -1.29978383e+00 2.23455146e-01 -9.36103016e-02
6.73607647e-01 -5.75228274e-01 -8.99489999e-01 3.79912496e-01
-7.98150972e-02 5.54027915e-01 1.85766801e-01 -1.36693314e-01
-4.89862025e-01 -1.73272356e-01 -7.03951478e-01 6.23183966e-01
1.49004602e+00 -1.09307596e-03 1.41512051e-01 4.14166301e-01
8.17229331e-01 -8.55556428e-01 -3.85482401e-01 4.13872957e-01
5.67931056e-01 -8.96212816e-01 1.01010418e+00 -3.07970434e-01
1.12148620e-01 -6.94733262e-01 -3.48177925e-02 -4.36971635e-01
-4.31682795e-01 -6.53640151e-01 -3.51128459e-01 7.83807158e-01
4.96220976e-01 -6.62381053e-01 9.77882504e-01 1.24701768e-01
-2.99621522e-01 -9.76277232e-01 -9.27032590e-01 -8.69842291e-01
-3.28865856e-01 -4.67662007e-01 4.09928918e-01 5.17333031e-01
-6.10565543e-01 3.71073723e-01 -2.00446099e-01 4.63213354e-01
7.26136446e-01 2.31000379e-01 1.01481998e+00 -9.63839889e-01
-6.92523539e-01 -6.49079800e-01 -6.14281714e-01 -1.66757584e+00
-4.00780916e-01 -5.34964025e-01 -1.27530560e-01 -8.86056602e-01
2.64768511e-01 -5.99035025e-01 -2.88726270e-01 5.65719485e-01
-1.52577043e-01 5.07870317e-01 2.76124030e-01 3.68301421e-01
-9.44280803e-01 3.12767476e-01 1.20009601e+00 1.32823825e-01
-1.02648161e-01 -1.43640295e-01 -5.15709341e-01 9.19377446e-01
6.88753724e-01 -3.74606669e-01 -1.95409462e-01 -9.45985079e-01
2.44276062e-01 -1.36920810e-01 5.60041845e-01 -1.43690956e+00
6.20039523e-01 2.14999124e-01 5.78059137e-01 -8.78227830e-01
2.49166980e-01 -4.06731069e-01 -8.50628465e-02 8.52123857e-01
2.32985705e-01 2.50072777e-01 6.01326168e-01 6.66488886e-01
5.90491220e-02 -1.37826174e-01 8.99763942e-01 1.82576790e-01
-1.13160145e+00 4.54213083e-01 7.69778416e-02 -1.04927704e-01
1.16684091e+00 -2.22481385e-01 -5.50890088e-01 4.64328349e-01
-3.41529012e-01 4.06310976e-01 2.10333943e-01 3.17668796e-01
6.57161176e-01 -1.15465224e+00 -8.13001037e-01 2.20969066e-01
3.97664569e-02 3.43653351e-01 3.76281023e-01 7.87976146e-01
-1.06125498e+00 3.60366344e-01 -9.69378203e-02 -9.00198400e-01
-1.31452739e+00 4.11102355e-01 2.85569370e-01 1.43765491e-02
-8.55876625e-01 1.49744093e+00 6.01654589e-01 1.93256170e-01
3.88197005e-01 -2.89256215e-01 1.52584732e-01 -1.55335814e-01
8.33030999e-01 6.04948163e-01 7.61694536e-02 -2.45451167e-01
-5.17610669e-01 6.02804482e-01 -5.24975300e-01 4.19224620e-01
9.88845885e-01 2.43859470e-01 -5.58068044e-02 -5.25575757e-01
1.08891833e+00 -3.76763910e-01 -1.64461052e+00 -2.69562066e-01
-2.70764351e-01 -6.15714729e-01 1.20561205e-01 -4.37828004e-01
-1.44045901e+00 8.29330206e-01 9.51589763e-01 -2.45641395e-01
1.30039465e+00 4.25480604e-02 8.52829635e-01 7.48991013e-01
4.17500973e-01 -9.41925049e-01 2.18732521e-01 6.91763818e-01
5.46075165e-01 -1.10178864e+00 7.69173354e-02 -7.48599887e-01
-1.09108269e-01 1.14306343e+00 1.22939599e+00 -4.40540701e-01
4.14917469e-01 4.98875320e-01 -2.83634454e-01 -2.60393560e-01
-5.44773757e-01 -9.99062508e-02 7.53684640e-02 2.02949956e-01
9.30798873e-02 1.42171934e-01 -2.30712101e-01 5.56970596e-01
2.05324497e-02 -2.45349139e-01 3.65074307e-01 9.05105233e-01
-6.33671761e-01 -6.65262699e-01 -3.20636690e-01 5.94510436e-01
-3.78947943e-01 -2.65322328e-01 6.64301589e-02 7.74858236e-01
2.56263316e-01 4.97819483e-01 3.16530257e-01 -4.47636694e-01
4.07197207e-01 -5.46097696e-01 4.04706836e-01 -4.73423928e-01
-4.37169909e-01 3.00443590e-01 -2.03621238e-01 -6.58823550e-01
5.09073362e-02 -5.22529304e-01 -1.27635562e+00 -3.78190488e-01
-7.58538425e-01 -3.90224755e-01 5.58036685e-01 4.10007119e-01
6.29999459e-01 5.54629922e-01 2.64021754e-01 -8.04498017e-01
-6.12633049e-01 -8.46217096e-01 -2.51591742e-01 -2.03718320e-01
-7.00331703e-02 -7.88052082e-01 1.19434157e-02 -2.10875347e-01] | [8.722162246704102, -0.3459068238735199] |
bf95d00d-1ca6-43f4-85fa-cde5a4b083cb | efficient-quantization-aware-training-with | 2306.07215 | null | https://arxiv.org/abs/2306.07215v1 | https://arxiv.org/pdf/2306.07215v1.pdf | Efficient Quantization-aware Training with Adaptive Coreset Selection | The expanding model size and computation of deep neural networks (DNNs) have increased the demand for efficient model deployment methods. Quantization-aware training (QAT) is a representative model compression method to leverage redundancy in weights and activations. However, most existing QAT methods require end-to-end training on the entire dataset, which suffers from long training time and high energy costs. Coreset selection, aiming to improve data efficiency utilizing the redundancy of training data, has also been widely used for efficient training. In this work, we propose a new angle through the coreset selection to improve the training efficiency of quantization-aware training. Based on the characteristics of QAT, we propose two metrics: error vector score and disagreement score, to quantify the importance of each sample during training. Guided by these two metrics of importance, we proposed a quantization-aware adaptive coreset selection (ACS) method to select the data for the current training epoch. We evaluate our method on various networks (ResNet-18, MobileNetV2), datasets(CIFAR-100, ImageNet-1K), and under different quantization settings. Compared with previous coreset selection methods, our method significantly improves QAT performance with different dataset fractions. Our method can achieve an accuracy of 68.39% of 4-bit quantized ResNet-18 on the ImageNet-1K dataset with only a 10% subset, which has an absolute gain of 4.24% compared to the baseline. | ['Kwang-Ting Cheng', 'Shih-Yang Liu', 'Zechun Liu', 'Xijie Huang'] | 2023-06-12 | null | null | null | null | ['quantization', 'model-compression'] | ['methodology', 'methodology'] | [ 2.04100817e-01 -4.13844705e-01 -4.57575113e-01 -6.14423037e-01
-4.08332229e-01 -9.09725949e-02 1.79621145e-01 -1.76357385e-02
-1.02106321e+00 7.13504136e-01 -1.48998752e-01 -2.43522003e-01
-2.79933512e-01 -7.80077636e-01 -6.22147202e-01 -6.80298209e-01
9.24861506e-02 3.11601162e-01 3.78768027e-01 3.52925211e-02
1.02508277e-01 3.65836829e-01 -1.44357693e+00 1.48011446e-01
8.44529986e-01 1.50130856e+00 7.29089975e-01 4.05322671e-01
-1.09461613e-01 7.65817881e-01 -6.74741626e-01 -4.68083411e-01
2.61256635e-01 -5.60193136e-02 -6.26981080e-01 -3.81771356e-01
5.37718892e-01 -6.12371683e-01 -8.25414479e-01 1.24728894e+00
7.60555208e-01 1.00089237e-02 2.22047150e-01 -1.31328833e+00
-1.31994426e-01 9.75302994e-01 -2.59411275e-01 4.55491126e-01
-8.96812201e-01 2.34612767e-02 7.72404611e-01 -8.58356416e-01
2.77942389e-01 1.03195870e+00 5.49406946e-01 8.24190140e-01
-9.57803905e-01 -1.30213320e+00 4.76694517e-02 6.90179825e-01
-1.49725747e+00 -6.39710605e-01 6.54600143e-01 6.49404377e-02
1.17147791e+00 4.16309908e-02 8.89314771e-01 7.68322587e-01
-5.77156432e-02 7.68560529e-01 7.18993187e-01 -2.21788496e-01
6.22157991e-01 -1.58184290e-01 2.42805690e-01 5.37854970e-01
3.74207675e-01 -3.21664959e-02 -7.56320953e-01 9.03667957e-02
7.10464239e-01 2.64624596e-01 -1.90581858e-01 6.13959953e-02
-8.44364703e-01 7.30175316e-01 7.82088280e-01 7.12461174e-02
-3.91949505e-01 6.62857771e-01 6.98288739e-01 5.00882044e-02
2.67644316e-01 8.65510702e-02 -6.48563325e-01 -5.17731488e-01
-1.24647427e+00 2.23205164e-01 3.36536944e-01 9.93479252e-01
6.78711534e-01 3.79359663e-01 -2.78539658e-01 1.15774012e+00
3.37838739e-01 4.67917502e-01 9.04816210e-01 -9.52085376e-01
8.25725675e-01 7.44759560e-01 -5.51589727e-01 -5.70625961e-01
-2.01413140e-01 -7.66206741e-01 -1.32824683e+00 -2.06856504e-01
-2.30457470e-01 -1.28720537e-01 -1.18702507e+00 1.92526424e+00
6.16316535e-02 3.64008605e-01 4.80457172e-02 7.81625688e-01
7.72858381e-01 5.65796793e-01 2.60097235e-01 -1.98023736e-01
1.20268250e+00 -1.06758595e+00 -6.37345135e-01 -3.13070446e-01
8.38604212e-01 -3.66429150e-01 8.95023823e-01 2.63565719e-01
-1.00914526e+00 -5.26298285e-01 -1.32140124e+00 -1.27315940e-02
-1.84375092e-01 2.65993297e-01 5.11524439e-01 6.93375409e-01
-1.13876235e+00 8.29311609e-01 -9.56812024e-01 8.20351765e-02
1.07410967e+00 6.21893287e-01 9.41492915e-02 -2.73677349e-01
-1.17518806e+00 5.66174150e-01 7.16925740e-01 -2.80892819e-01
-9.43332732e-01 -8.91488671e-01 -3.87279898e-01 4.84183162e-01
6.74983263e-02 -5.04632711e-01 1.35556567e+00 -7.41627574e-01
-1.30843830e+00 2.98633546e-01 -1.69552803e-01 -1.08837128e+00
1.84237227e-01 -1.39993563e-01 -2.94676036e-01 2.74536818e-01
-2.82735705e-01 1.11909056e+00 6.00800514e-01 -7.16268361e-01
-6.42827153e-01 -4.42707777e-01 -1.19388454e-01 1.35836706e-01
-1.07634127e+00 -2.30228916e-01 -6.61104679e-01 -8.29016209e-01
1.88176483e-01 -8.16735029e-01 -2.20414385e-01 1.28081277e-01
-2.20342755e-01 -3.07792097e-01 9.73598301e-01 -3.54499429e-01
1.62438583e+00 -2.10596108e+00 -1.80764675e-01 4.16538157e-02
5.17016351e-01 7.95734048e-01 -1.10969253e-01 -1.52312323e-01
1.43460989e-01 3.62966746e-01 -1.57019347e-01 -6.83037579e-01
7.71330371e-02 4.74957764e-01 -1.44238785e-01 -5.82104968e-03
7.78856203e-02 8.53814244e-01 -7.21008599e-01 -6.57179356e-01
2.09264114e-01 5.62362909e-01 -7.48263121e-01 -1.33749023e-02
-6.35573268e-02 -2.93628514e-01 -3.02862227e-01 5.03418088e-01
8.79089773e-01 -3.82131159e-01 1.78786963e-01 -5.27781069e-01
1.86417818e-01 4.55490261e-01 -8.19419205e-01 1.65106344e+00
-3.22681606e-01 6.62457883e-01 -2.34087020e-01 -1.02833056e+00
8.06582570e-01 2.43525699e-01 3.84511560e-01 -1.06536925e+00
3.57942015e-01 3.56779993e-01 1.24647707e-01 -4.45610024e-02
5.36819220e-01 2.06442356e-01 3.55082572e-01 1.65879756e-01
3.19374353e-01 4.12714779e-01 3.86133373e-01 2.30433136e-01
1.11211669e+00 -5.03535509e-01 -1.33057177e-01 -1.67560726e-01
-8.88902321e-02 -1.88745141e-01 8.09583962e-01 5.37003040e-01
-4.94708717e-01 2.79732645e-01 1.38074458e-01 -4.56822127e-01
-1.18225253e+00 -6.26792371e-01 -3.72154474e-01 9.94026840e-01
5.59439883e-02 -7.94545531e-01 -9.46723044e-01 -4.95945752e-01
-1.87504798e-01 5.97130418e-01 -2.65736848e-01 -6.79678798e-01
-6.72356904e-01 -8.94186497e-01 7.23490119e-01 6.16750956e-01
1.27919006e+00 -7.22239077e-01 -9.74471867e-01 2.22383350e-01
-8.53420869e-02 -1.29820895e+00 -4.55203831e-01 5.25021970e-01
-1.49266827e+00 -7.18567193e-01 -6.79627180e-01 -7.13104904e-01
6.04475498e-01 3.38106751e-01 1.08056617e+00 1.88134283e-01
-1.19997840e-02 -2.41871431e-01 -3.55545104e-01 -3.86934459e-01
-8.79803002e-02 4.19164866e-01 2.25359529e-01 -2.83868223e-01
3.42805952e-01 -6.98261857e-01 -8.92797232e-01 1.81965247e-01
-9.26565707e-01 4.22963887e-01 7.87079453e-01 8.48797619e-01
8.59418392e-01 1.73895329e-01 6.55787647e-01 -7.36190856e-01
3.21622729e-01 -3.87292475e-01 -4.47443217e-01 2.02622026e-01
-1.07476032e+00 1.72512054e-01 8.27818573e-01 -5.80092490e-01
-5.03295898e-01 -1.78943619e-01 -1.62441164e-01 -9.95005310e-01
3.26775193e-01 4.73948598e-01 -1.17084719e-01 -2.33891025e-01
5.33350229e-01 4.45729494e-01 -3.74938548e-01 -5.56174099e-01
-5.80650382e-02 6.53184593e-01 3.73922110e-01 -2.55779147e-01
3.34773183e-01 2.14713775e-02 4.01616504e-04 -5.25592506e-01
-4.48898971e-01 -1.29009560e-01 -1.53190330e-01 2.47455500e-02
4.16025370e-01 -1.10641086e+00 -5.81768155e-01 6.45659506e-01
-9.57198143e-01 -5.64643621e-01 -2.40802780e-01 5.91208041e-01
-4.85615730e-02 1.20649919e-01 -6.64468586e-01 -6.77996993e-01
-1.01876581e+00 -1.44698560e+00 8.07590723e-01 2.95715630e-01
3.61888409e-01 -6.62704229e-01 -4.59422648e-01 1.00400001e-01
8.22556496e-01 -1.94982901e-01 9.91151452e-01 -4.81053531e-01
-6.10843122e-01 -6.98837340e-02 -5.55926502e-01 5.41452169e-01
-2.07506239e-01 -3.25830817e-01 -1.03583109e+00 -5.46855986e-01
-1.52204230e-01 -6.28774703e-01 1.13395762e+00 4.74949956e-01
1.89270759e+00 -4.58668381e-01 -3.24916422e-01 1.01292741e+00
1.58137226e+00 3.25347751e-01 5.09189487e-01 2.28351459e-01
7.60630310e-01 -2.91496783e-01 4.19852614e-01 7.08666325e-01
3.41583043e-01 7.24276543e-01 7.87310839e-01 2.26454228e-01
-3.69131833e-01 -2.16540262e-01 1.72731608e-01 1.23702705e+00
1.46174520e-01 -2.16818392e-01 -7.90804982e-01 4.32815194e-01
-1.60829401e+00 -5.92163861e-01 3.56230199e-01 2.09294868e+00
1.09224451e+00 4.44127828e-01 -2.51850486e-01 5.00528216e-01
5.53233266e-01 5.91965728e-02 -1.05794191e+00 -4.89383750e-02
-4.94534560e-02 4.23369676e-01 1.04540896e+00 -1.64149329e-01
-9.39773083e-01 8.09374750e-01 5.78963280e+00 1.46570563e+00
-1.36864102e+00 3.83908421e-01 9.16764379e-01 -4.98993784e-01
-1.70951281e-02 -2.79275328e-01 -1.25176001e+00 8.25725734e-01
1.35621262e+00 -1.76317751e-01 5.26327491e-01 1.01585972e+00
1.64778024e-01 2.54147559e-01 -8.46156836e-01 1.42117071e+00
-2.87616134e-01 -1.61682045e+00 2.82785416e-01 5.28372638e-02
7.89568007e-01 6.05464458e-01 1.61233783e-01 5.12312710e-01
9.02737901e-02 -9.75671589e-01 8.34190428e-01 5.88526577e-02
1.19458067e+00 -9.25707340e-01 7.70913839e-01 3.90534729e-01
-1.33927202e+00 -2.86394089e-01 -7.56911337e-01 2.18013600e-01
-1.20409526e-01 8.18283021e-01 -7.48244047e-01 1.73169926e-01
1.03292751e+00 8.20349216e-01 -5.50229490e-01 1.21095014e+00
1.53798342e-01 1.04436469e+00 -5.01017511e-01 -1.95277497e-01
1.90229207e-01 1.57079056e-01 1.28635287e-01 9.99270856e-01
3.59351993e-01 4.03853948e-04 -1.66484550e-01 6.79052353e-01
-7.88736939e-01 -1.07874140e-01 -4.33994681e-02 3.28945816e-02
1.29717958e+00 1.07629168e+00 -4.42977846e-01 -6.86661005e-01
-3.65215279e-02 6.78145587e-01 5.49273312e-01 1.31291628e-01
-9.54562068e-01 -5.37058949e-01 7.65047491e-01 -2.16064066e-01
3.68523687e-01 -1.32847145e-01 -3.80203605e-01 -9.16884303e-01
1.55689076e-01 -6.78789377e-01 5.16996756e-02 -5.62349141e-01
-6.96716964e-01 7.97710180e-01 6.88972473e-02 -1.19516206e+00
1.70271620e-01 -5.07460713e-01 -3.54983330e-01 6.05603576e-01
-1.77669466e+00 -6.61644578e-01 -5.92835724e-01 4.30268705e-01
6.92301750e-01 -3.50618482e-01 6.17479742e-01 8.98716331e-01
-9.35023904e-01 1.23689985e+00 3.09409916e-01 1.63865253e-01
3.63197148e-01 -8.47501695e-01 6.22288644e-01 6.73773766e-01
-6.85845986e-02 5.29718697e-01 2.10039109e-01 -2.50060737e-01
-1.40100050e+00 -1.62129748e+00 6.99053407e-01 3.26915085e-01
1.31495863e-01 -2.37103775e-01 -7.94516087e-01 3.47436547e-01
-1.61654666e-01 1.51018873e-01 4.51479495e-01 -4.82741177e-01
-2.97608703e-01 -6.80961668e-01 -1.12589693e+00 5.63151002e-01
1.33188128e+00 -2.07454249e-01 4.27614227e-02 2.60187000e-01
1.16419005e+00 -4.19432461e-01 -1.08014691e+00 5.98692536e-01
4.29086983e-01 -7.67395675e-01 9.27684844e-01 -2.05374941e-01
2.74472624e-01 -1.09365014e-02 -4.36882615e-01 -1.16611207e+00
-2.85219580e-01 -1.51912987e-01 -4.87982363e-01 1.00490034e+00
2.33629078e-01 -5.59072733e-01 1.12390494e+00 4.97916549e-01
-3.95772249e-01 -1.23051286e+00 -1.26606727e+00 -7.21164882e-01
-1.24570206e-01 -6.21402740e-01 9.36765969e-01 6.32024884e-01
-4.39100087e-01 2.19739109e-01 -2.26851657e-01 -2.77002543e-01
7.09591627e-01 -4.17535216e-01 3.18082839e-01 -1.15667236e+00
-1.53348505e-01 -6.84134185e-01 -4.86024529e-01 -1.34282875e+00
-7.38267526e-02 -9.37377393e-01 -2.58769095e-01 -1.30962670e+00
2.05796823e-01 -9.08378243e-01 -5.51402450e-01 7.99438894e-01
2.11927723e-02 2.83303648e-01 3.65052402e-01 4.46176291e-01
-7.19594002e-01 8.51777911e-01 1.04079390e+00 -2.39383295e-01
2.99062636e-02 -2.63189912e-01 -4.18475717e-01 3.55966568e-01
1.02968204e+00 -5.51152050e-01 -7.21377969e-01 -9.54509497e-01
3.64041626e-02 -3.30587417e-01 3.04251164e-01 -1.58580315e+00
5.23680627e-01 8.88022333e-02 3.81855130e-01 -7.10123658e-01
4.28319216e-01 -8.85759354e-01 1.30196229e-01 8.00289094e-01
-3.49932998e-01 2.30552852e-01 3.37494671e-01 4.46575344e-01
-2.07846627e-01 -3.21543306e-01 9.45295751e-01 1.51499540e-01
-9.28503633e-01 8.15373421e-01 7.60266706e-02 2.38178689e-02
6.86786771e-01 -2.46570960e-01 -5.66419899e-01 1.40674099e-01
-1.67898625e-01 2.89948076e-01 9.76525992e-02 1.32003427e-01
9.96569455e-01 -1.56129622e+00 -5.06737471e-01 2.77464807e-01
1.07212858e-02 3.32815707e-01 3.80394578e-01 7.03193605e-01
-6.32930636e-01 5.65596998e-01 -1.73044607e-01 -6.60461724e-01
-1.28754616e+00 7.01137856e-02 4.99624699e-01 -3.48009288e-01
-3.13380986e-01 1.04339814e+00 -1.68448955e-01 -5.65079264e-02
5.44153929e-01 -6.39377356e-01 -1.08802974e-01 -3.51991415e-01
5.39203584e-01 5.24963200e-01 4.59003359e-01 -4.03480083e-01
-2.98489898e-01 2.93196827e-01 -2.45956987e-01 2.05609918e-01
1.27391481e+00 1.93518370e-01 1.63072601e-01 3.20011601e-02
1.49120831e+00 -9.27876472e-01 -1.34260869e+00 -4.48104292e-01
-2.53790259e-01 -3.49481314e-01 7.00199008e-01 -6.00138068e-01
-1.76978076e+00 1.03476954e+00 1.10393858e+00 -1.75915316e-01
1.50683475e+00 -4.79873806e-01 1.27741301e+00 4.63139355e-01
5.18500805e-01 -1.08235383e+00 5.77645265e-02 6.39261127e-01
3.78141612e-01 -1.12817550e+00 -1.69856101e-02 7.94943143e-03
-2.91165829e-01 9.83697593e-01 8.82938445e-01 1.63672432e-01
8.59303236e-01 1.89412266e-01 -3.24678361e-01 -3.99680622e-02
-1.08817780e+00 2.11593792e-01 -5.38448431e-03 1.85969993e-01
1.00307569e-01 1.57746509e-01 -8.54655504e-02 7.01455474e-01
-3.58970135e-01 2.92093724e-01 -5.04815988e-02 9.88451779e-01
-6.65952802e-01 -8.40932250e-01 1.93612412e-01 1.02408373e+00
-3.86499882e-01 -4.56924170e-01 2.44582087e-01 2.65324354e-01
2.43869022e-01 7.65849531e-01 2.16338754e-01 -9.83157754e-01
2.67139584e-01 -9.50110927e-02 2.07187846e-01 -2.50264913e-01
-4.90012497e-01 -1.08726233e-01 -2.60255694e-01 -4.52704281e-01
-3.58148456e-01 -4.63370308e-02 -1.32807910e+00 -6.52984440e-01
-5.39733827e-01 -1.69935878e-02 1.01560128e+00 7.35049665e-01
7.63224185e-01 8.18935812e-01 5.41960418e-01 -8.23869586e-01
-8.43482614e-01 -1.07512629e+00 -5.19039929e-01 1.44911289e-01
8.73465836e-02 -6.18007779e-01 -1.62294194e-01 -1.76572040e-01] | [8.594949722290039, 3.0359551906585693] |
39a77c76-e477-429b-8bc4-0bfcfc374c65 | deep-learning-for-material-recognition-most | 2012.07495 | null | https://arxiv.org/abs/2012.07495v1 | https://arxiv.org/pdf/2012.07495v1.pdf | Deep Learning for Material recognition: most recent advances and open challenges | Recognizing material from color images is still a challenging problem today. While deep neural networks provide very good results on object recognition and has been the topic of a huge amount of papers in the last decade, their adaptation to material images still requires some works to reach equivalent accuracies. Nevertheless, recent studies achieve very good results in material recognition with deep learning and we propose, in this paper, to review most of them by focusing on three aspects: material image datasets, influence of the context and ad hoc descriptors for material appearance. Every aspect is introduced by a systematic manner and results from representative works are cited. We also present our own studies in this area and point out some open challenges for future works. | ['Damien Muselet', 'Sixiang Xu', 'Alain Tremeau'] | 2020-12-14 | null | null | null | null | ['material-recognition'] | ['computer-vision'] | [ 3.05204242e-01 -5.39184570e-01 -6.86147287e-02 -3.30190688e-01
-4.21932995e-01 -2.51622379e-01 5.51868856e-01 3.14062946e-02
-3.11388880e-01 5.49141943e-01 -2.60895401e-01 9.28629860e-02
-3.85669470e-01 -1.09409165e+00 -8.33367765e-01 -8.45840454e-01
-4.79781907e-03 4.17626351e-01 4.26322728e-01 -1.30547062e-01
3.83338302e-01 9.80140865e-01 -1.65695298e+00 4.21888381e-01
3.54554147e-01 1.22872031e+00 7.12282434e-02 5.81350446e-01
-3.47935617e-01 5.87174535e-01 -8.63672256e-01 -4.81317699e-01
4.42655295e-01 -1.72217727e-01 -8.65874410e-01 3.53805095e-01
9.02474999e-01 -2.94398129e-01 -4.82036769e-01 8.45710397e-01
7.88342237e-01 -4.12241602e-03 9.63699996e-01 -9.94380832e-01
-1.24534357e+00 4.87899452e-01 -3.85007769e-01 4.96026836e-02
2.79645592e-01 -1.95282146e-01 7.00617969e-01 -7.00868249e-01
6.85559511e-01 9.38720047e-01 7.07502544e-01 5.94204783e-01
-8.80372763e-01 -4.10676479e-01 1.83644608e-01 7.34314203e-01
-1.24719334e+00 -8.96291733e-02 1.38199902e+00 -3.93461466e-01
8.19816172e-01 3.64161372e-01 8.14492762e-01 9.80857790e-01
8.36863220e-02 1.09243369e+00 1.21857369e+00 -6.02392077e-01
1.00930341e-01 3.61253321e-01 2.47986168e-01 6.13186955e-01
2.46078223e-01 -2.14952633e-01 -3.28670323e-01 2.67448872e-01
8.83147120e-01 -1.03562670e-02 -1.79662958e-01 -5.89684248e-01
-8.99684668e-01 5.61546445e-01 6.21751189e-01 8.43377650e-01
-4.88028884e-01 1.16706714e-01 4.75124836e-01 2.96347708e-01
2.96057969e-01 3.90431732e-01 -3.11505228e-01 -1.37210116e-01
-8.86446416e-01 2.29526639e-01 7.25009620e-01 7.63633132e-01
4.38497901e-01 3.25784028e-01 -5.23339212e-02 1.26169109e+00
-2.53974885e-01 5.47923148e-01 1.05867863e-01 -5.06745279e-01
9.83045995e-02 4.46878791e-01 -1.24182351e-01 -1.27564979e+00
-5.52085698e-01 -4.55646157e-01 -9.16242182e-01 4.31274593e-01
6.54438913e-01 1.57405883e-01 -7.47230351e-01 1.00506020e+00
-8.16291943e-02 -5.91447055e-01 -1.77475929e-01 1.00612020e+00
1.23137939e+00 5.95681190e-01 -2.18070224e-01 2.45944723e-01
1.06140268e+00 -1.11129189e+00 -6.90159559e-01 2.40822881e-01
-2.39827439e-01 -9.77823377e-01 8.40907693e-01 9.12611306e-01
-1.34910846e+00 -6.06306553e-01 -9.67915356e-01 -2.64147446e-02
-7.64520109e-01 2.30778590e-01 8.67454171e-01 6.39941990e-01
-9.33447182e-01 6.52081370e-01 -6.31678343e-01 -7.04605758e-01
6.13777399e-01 4.95433003e-01 -2.10378468e-01 -9.92471948e-02
-9.74565446e-01 7.64519989e-01 1.91591412e-01 4.45740998e-01
-5.84066391e-01 -2.66769648e-01 -2.82556474e-01 -2.16362685e-01
2.84744889e-01 -5.65009356e-01 8.10643494e-01 -1.05279660e+00
-1.63894081e+00 1.13829744e+00 2.02895686e-01 -3.32622349e-01
8.01709712e-01 -2.44852349e-01 -4.75390315e-01 2.83339232e-01
-6.50832593e-01 5.93950748e-01 7.26301014e-01 -1.45407307e+00
-3.26869637e-01 -1.95085287e-01 4.38864052e-01 -1.95645556e-01
-6.77641809e-01 1.03419349e-01 -5.98122656e-01 -8.40414584e-01
-8.45410153e-02 -8.97291362e-01 1.24211796e-02 2.47992009e-01
-3.05112123e-01 -5.72456419e-01 7.39805937e-01 -6.03010237e-01
7.52129316e-01 -1.87645257e+00 1.33569866e-01 -1.38651982e-01
-1.07567161e-01 5.03680468e-01 -9.67163667e-02 6.07109964e-01
1.22020856e-01 -1.89411521e-01 -2.12613970e-01 -1.20504774e-01
4.94856983e-02 -5.78664616e-02 6.64941547e-03 6.61112905e-01
2.21591532e-01 9.06847358e-01 -3.97973925e-01 -4.85420763e-01
8.79306376e-01 8.96483719e-01 -1.32528976e-01 -1.17613815e-01
-1.27325952e-01 -1.78417582e-02 -2.30409175e-01 9.76337910e-01
9.43934381e-01 -1.48373663e-01 -1.91213027e-01 -6.33440256e-01
-5.52491657e-02 -2.64023364e-01 -1.17570794e+00 1.48041391e+00
-4.74175423e-01 1.04360545e+00 4.61724177e-02 -1.27207804e+00
1.04597604e+00 3.54279466e-02 7.70706832e-01 -8.22389126e-01
3.64666671e-01 1.75114781e-01 1.73505008e-01 -6.92579985e-01
7.42155433e-01 -1.31669700e-01 2.93029577e-01 1.78219974e-01
-2.01580793e-01 -1.88315243e-01 4.70825315e-01 -2.21224800e-01
7.34383643e-01 3.08545917e-01 7.57757351e-02 3.07266489e-02
7.42872357e-01 6.76047010e-03 -8.93587098e-02 7.40896642e-01
-2.55578905e-01 8.39016914e-01 -4.49050926e-02 -8.44448388e-01
-1.02932465e+00 -1.13729596e+00 -5.50110757e-01 8.38280976e-01
2.83546001e-01 -6.28338614e-03 -6.15442097e-01 -5.57729304e-01
-1.80110661e-03 1.22121520e-01 -9.52221751e-01 1.03056528e-01
-7.65500844e-01 -8.35984170e-01 -2.15827208e-02 9.25935388e-01
7.54863620e-01 -1.61203289e+00 -4.07653928e-01 3.92947420e-02
2.54317313e-01 -1.12903786e+00 4.88135248e-01 1.58879653e-01
-8.46534729e-01 -9.90154028e-01 -1.35528147e+00 -1.03532553e+00
7.35256076e-01 4.08600777e-01 1.27375162e+00 2.59370059e-01
-6.69417083e-01 5.01730323e-01 -5.42978942e-01 -5.14553428e-01
-3.05217564e-01 1.83178991e-01 -3.74066263e-01 -1.51908219e-01
5.90229869e-01 -3.42089862e-01 -6.02536201e-01 2.76662767e-01
-1.03379714e+00 7.95231983e-02 1.05309713e+00 6.18252277e-01
5.09791553e-01 8.56934115e-02 3.27283919e-01 -6.82466030e-01
4.78111476e-01 8.65733344e-03 -3.16106409e-01 2.76245117e-01
-2.30888098e-01 -2.14319795e-01 8.36041033e-01 -3.13957453e-01
-7.66187370e-01 -1.18593149e-01 -4.23446864e-01 -1.11303896e-01
-6.86498165e-01 1.05021976e-01 4.72501013e-03 -4.71540213e-01
5.27317822e-01 3.49382877e-01 -1.97691932e-01 -7.32413888e-01
1.41962171e-01 7.88408220e-01 2.03508928e-01 -7.55087018e-01
8.31232548e-01 7.02449441e-01 6.29553869e-02 -1.20651054e+00
-7.43577778e-01 -2.50290185e-01 -6.93356872e-01 -7.25317299e-01
6.64059103e-01 -2.91686565e-01 -7.64342546e-01 7.81021118e-01
-1.08647215e+00 -1.90397605e-01 -3.09653312e-01 2.08123714e-01
-4.38613057e-01 3.96655172e-01 -9.53911185e-01 -6.78754151e-01
-4.98444915e-01 -1.32310736e+00 8.55509281e-01 2.24276334e-01
-8.12708139e-02 -1.22649157e+00 -2.00322971e-01 3.92704338e-01
7.24269569e-01 2.52563030e-01 7.51466572e-01 -1.23404197e-01
-7.23453760e-01 -6.25511229e-01 -5.72564900e-01 6.32286012e-01
3.22843701e-01 1.14197314e-01 -1.09134221e+00 -1.12752497e-01
-3.83037746e-01 -3.33952993e-01 1.10540032e+00 5.60967445e-01
1.63371372e+00 4.11558181e-01 -1.21207260e-01 3.15310419e-01
1.72771251e+00 2.94046193e-01 7.12806106e-01 7.76830316e-01
7.21091092e-01 6.95910752e-01 2.39927828e-01 9.47358012e-02
4.63606194e-02 7.41394162e-01 5.57583153e-01 -3.19798231e-01
-6.92089379e-01 3.27130705e-01 2.20189206e-02 9.54624295e-01
-6.81467175e-01 -2.80924737e-01 -6.68952465e-01 4.35592920e-01
-1.32691813e+00 -8.29876423e-01 -2.31127024e-01 1.87712169e+00
3.40095907e-01 3.10335517e-01 3.95294905e-01 5.87441623e-01
6.69501662e-01 2.40099236e-01 -4.80227143e-01 -3.35714728e-01
-4.73405808e-01 2.92495847e-01 3.44789177e-01 3.71475879e-04
-1.11922622e+00 7.49616683e-01 7.14344501e+00 9.14151847e-01
-1.55168617e+00 -2.20074326e-01 4.47816312e-01 -1.44668967e-02
1.80472452e-02 -5.36228359e-01 -4.90199894e-01 3.48504752e-01
1.60149828e-01 1.99749157e-01 3.66845667e-01 1.00463939e+00
-1.30876109e-01 -8.75931904e-02 -8.13400328e-01 1.14236343e+00
6.19769871e-01 -1.31104434e+00 2.42228612e-01 -1.26674816e-01
8.61013889e-01 -8.63242373e-02 2.76922971e-01 -9.41627845e-03
-2.15479106e-01 -8.47087562e-01 7.65932918e-01 6.15648448e-01
3.92417133e-01 -6.39891028e-01 8.88140857e-01 -2.26165131e-01
-1.08112752e+00 9.01321471e-02 -5.52627206e-01 -1.25532657e-01
1.05184227e-01 8.43949914e-01 -2.10278377e-01 9.11591232e-01
9.24849033e-01 8.92780066e-01 -9.70577896e-01 1.47420120e+00
-1.83377173e-02 4.79837656e-01 -1.90679520e-01 -7.60565996e-01
2.14637145e-01 -2.20834821e-01 2.78377682e-01 1.33791935e+00
5.20360132e-04 -7.11046338e-01 3.21318395e-02 8.72773468e-01
-1.22091733e-02 4.44430083e-01 -4.40260947e-01 -2.16661587e-01
-2.44754270e-01 1.38830745e+00 -1.18846297e+00 -3.64126027e-01
-5.89273036e-01 8.27509463e-01 1.78832546e-01 3.14188242e-01
-6.82353497e-01 -4.90810364e-01 2.16869712e-01 1.17002279e-01
2.02315673e-01 -2.75547057e-01 -3.65371585e-01 -7.86379278e-01
2.80962169e-01 -5.58392644e-01 1.17850445e-01 -7.83712685e-01
-1.52635837e+00 6.67527020e-01 -7.84827992e-02 -1.40849555e+00
2.72610456e-01 -1.36329925e+00 -3.44077975e-01 4.20500994e-01
-1.38837194e+00 -1.07430387e+00 -5.06327748e-01 1.97128773e-01
7.21961021e-01 -1.59406155e-01 7.05352783e-01 5.02812803e-01
-4.96676981e-01 3.37072700e-01 2.94166446e-01 3.40455979e-01
6.79343820e-01 -1.15836644e+00 1.13117836e-01 3.62668157e-01
3.39386851e-01 4.90719020e-01 8.83364618e-01 -1.86547816e-01
-1.67216706e+00 -5.37365913e-01 3.87267590e-01 -2.34400600e-01
4.29245532e-01 -3.66026938e-01 -8.57418120e-01 1.78808764e-01
6.06256306e-01 -1.06319360e-01 6.05784655e-01 2.31958464e-01
-2.06962407e-01 -3.06811810e-01 -1.01579773e+00 5.53794682e-01
9.45623398e-01 -2.01459602e-01 -2.93565273e-01 4.05493408e-01
1.96132988e-01 -2.91219264e-01 -8.14510167e-01 4.34958607e-01
8.56136620e-01 -1.30136585e+00 1.02758527e+00 -1.81328833e-01
5.31095088e-01 -1.09997272e-01 -1.30998731e-01 -9.41304028e-01
-3.71915847e-01 1.23558261e-01 -1.01294275e-02 1.13968778e+00
1.75103210e-02 -2.67876834e-01 1.25042653e+00 2.43759647e-01
-1.14368342e-01 -9.78375137e-01 -4.58432347e-01 -9.62626040e-01
4.00502056e-01 -6.90510571e-01 3.42413068e-01 6.19302750e-01
-5.03960013e-01 5.59169613e-02 -5.03735781e-01 -5.06719470e-01
5.22647023e-01 5.32732010e-01 7.74103045e-01 -1.17864466e+00
-3.34197171e-02 -9.67300177e-01 -6.57571912e-01 -7.75853813e-01
9.33778733e-02 -8.21648359e-01 -1.28862754e-01 -2.16429114e+00
4.71799225e-01 -3.38163555e-01 -5.32848001e-01 2.05358729e-01
1.66453719e-01 7.68463075e-01 3.12177271e-01 -2.16610864e-01
-7.93651640e-01 3.90744090e-01 1.31691802e+00 -7.26051152e-01
2.01239988e-01 -4.28330041e-02 -4.43758786e-01 6.88874841e-01
8.86068761e-01 1.66513994e-02 8.67471695e-02 -5.86641192e-01
2.13402480e-01 -6.22041523e-01 3.23046744e-01 -1.49499667e+00
-8.60333294e-02 3.57813872e-02 8.56290102e-01 -9.97198105e-01
5.71540773e-01 -1.22287858e+00 -3.81419882e-02 4.25574243e-01
-2.53809780e-01 -1.91437125e-01 3.51944834e-01 1.96602330e-01
-2.55471706e-01 -4.89055127e-01 9.27912295e-01 -2.19857961e-01
-9.55271780e-01 3.27880353e-01 -5.27688801e-01 -4.35425967e-01
9.04010296e-01 -5.31734467e-01 -9.95589327e-03 -1.97129115e-01
-6.39684319e-01 -3.92865509e-01 6.45550609e-01 6.37414455e-01
5.54106116e-01 -1.44752860e+00 -3.74265820e-01 -1.37413114e-01
9.84355956e-02 -2.33343050e-01 6.14822745e-01 5.68277121e-01
-8.39880645e-01 6.87758565e-01 -6.58954322e-01 -6.53776288e-01
-1.22114241e+00 7.68929541e-01 2.11562723e-01 8.52377061e-03
-6.62105381e-01 6.41487181e-01 -1.33843616e-01 -1.06505871e-01
5.25486529e-01 -1.22980528e-01 -3.03201586e-01 -6.83865026e-02
4.72699165e-01 5.85304439e-01 3.66050333e-01 -4.99152958e-01
-3.26239765e-01 1.22076738e+00 -1.08619191e-01 4.20639157e-01
1.57432330e+00 1.28945440e-01 -1.35994896e-01 7.19335020e-01
1.29673266e+00 2.06262525e-02 -9.56984699e-01 -1.11176796e-01
-1.70988038e-01 -4.83777374e-01 4.09166403e-02 -9.28074658e-01
-1.53675461e+00 1.19034731e+00 8.44968259e-01 5.15517712e-01
1.30463123e+00 1.18911318e-01 7.55147934e-01 5.87080061e-01
4.76521879e-01 -1.26940501e+00 3.08893979e-01 1.86328903e-01
1.16324162e+00 -1.32512200e+00 2.02709690e-01 -5.37847161e-01
-7.75250047e-02 1.64258230e+00 6.89247966e-01 -4.80899572e-01
7.00712442e-01 3.96940291e-01 1.04929700e-01 -1.83858752e-01
-4.67364304e-02 -3.11163455e-01 3.79286498e-01 7.64667988e-01
8.19919825e-01 -2.51204912e-02 -4.06466931e-01 2.62830313e-02
-1.16500430e-01 8.78656134e-02 2.14107230e-01 1.03236449e+00
-2.96149343e-01 -1.34668100e+00 -5.70987344e-01 5.50613463e-01
-5.23480773e-01 3.60388070e-01 -6.83297336e-01 9.66217935e-01
5.99807166e-02 5.97723067e-01 1.09793782e-01 -4.47231799e-01
4.96342927e-01 -3.13337862e-01 1.14512444e+00 -1.58298656e-01
-5.79376578e-01 -1.71528563e-01 4.08185832e-02 -1.97221503e-01
-9.45755422e-01 -6.25585020e-01 -7.58562446e-01 -3.55441839e-01
-2.57005602e-01 -1.01361610e-01 9.53675628e-01 7.98332393e-01
-1.74874693e-01 8.36578608e-01 3.02181125e-01 -1.17986834e+00
9.95283872e-02 -1.08599401e+00 -7.39101589e-01 5.55847585e-01
-4.15524915e-02 -7.35149503e-01 -1.78578004e-01 7.23360479e-02] | [10.16850471496582, -0.17606307566165924] |
710b5cb8-5943-465d-91ed-ac3d41841efa | discovering-objects-that-can-move | 2203.10159 | null | https://arxiv.org/abs/2203.10159v1 | https://arxiv.org/pdf/2203.10159v1.pdf | Discovering Objects that Can Move | This paper studies the problem of object discovery -- separating objects from the background without manual labels. Existing approaches utilize appearance cues, such as color, texture, and location, to group pixels into object-like regions. However, by relying on appearance alone, these methods fail to separate objects from the background in cluttered scenes. This is a fundamental limitation since the definition of an object is inherently ambiguous and context-dependent. To resolve this ambiguity, we choose to focus on dynamic objects -- entities that can move independently in the world. We then scale the recent auto-encoder based frameworks for unsupervised object discovery from toy synthetic images to complex real-world scenes. To this end, we simplify their architecture, and augment the resulting model with a weak learning signal from general motion segmentation algorithms. Our experiments demonstrate that, despite only capturing a small subset of the objects that move, this signal is enough to generalize to segment both moving and static instances of dynamic objects. We show that our model scales to a newly collected, photo-realistic synthetic dataset with street driving scenarios. Additionally, we leverage ground truth segmentation and flow annotations in this dataset for thorough ablation and evaluation. Finally, our experiments on the real-world KITTI benchmark demonstrate that the proposed approach outperforms both heuristic- and learning-based methods by capitalizing on motion cues. | ['Martial Hebert', 'Adrien Gaidon', 'Yu-Xiong Wang', 'Allan Jabri', 'Pavel Tokmakov', 'Zhipeng Bao'] | 2022-03-18 | null | http://openaccess.thecvf.com//content/CVPR2022/html/Bao_Discovering_Objects_That_Can_Move_CVPR_2022_paper.html | http://openaccess.thecvf.com//content/CVPR2022/papers/Bao_Discovering_Objects_That_Can_Move_CVPR_2022_paper.pdf | cvpr-2022-1 | ['motion-segmentation'] | ['computer-vision'] | [ 3.49319160e-01 -2.12472647e-01 -3.65248531e-01 -3.04084033e-01
-5.41378021e-01 -8.60841513e-01 5.92076123e-01 -1.15669996e-01
-3.68807405e-01 6.38296425e-01 -2.10267946e-01 -1.74814984e-01
1.43404767e-01 -6.07754886e-01 -7.99841285e-01 -7.18198776e-01
-2.16941178e-01 5.18653929e-01 8.07854354e-01 -5.47281578e-02
2.50108186e-02 3.75466049e-01 -1.56596184e+00 2.35069960e-01
8.73384655e-01 8.15212369e-01 2.83536106e-01 7.13333845e-01
-1.52446488e-02 8.20323288e-01 -3.58580470e-01 -1.09824874e-01
5.66998482e-01 -4.30735379e-01 -8.72958720e-01 5.72926462e-01
1.07301390e+00 -4.83245850e-01 -4.33454365e-01 1.01906633e+00
4.01860476e-03 2.97445774e-01 5.01612902e-01 -1.22325993e+00
-4.21693355e-01 4.09864277e-01 -7.04027772e-01 3.96193177e-01
-2.69248225e-02 5.51271379e-01 9.87604797e-01 -6.80387139e-01
8.68660867e-01 1.06628227e+00 5.60069621e-01 5.79103172e-01
-1.35671103e+00 -4.11285400e-01 7.35540569e-01 2.02083409e-01
-1.15216911e+00 -6.62188530e-01 9.16630208e-01 -7.11637020e-01
4.99091476e-01 2.64789581e-01 6.16183579e-01 1.28464723e+00
-2.28406906e-01 1.17547858e+00 1.00418341e+00 -1.15885079e-01
3.23151618e-01 4.12286222e-02 2.79572159e-01 7.47654021e-01
5.40282309e-01 8.62470344e-02 -2.90933877e-01 2.33013585e-01
8.12807024e-01 -1.78817809e-01 -3.37245047e-01 -9.08597946e-01
-1.38532162e+00 4.97894585e-01 4.59590822e-01 7.51669854e-02
-1.54267818e-01 5.58628738e-01 9.50932801e-02 -2.22448543e-01
2.95736670e-01 2.14001298e-01 -4.25289333e-01 -1.35284513e-01
-1.09280241e+00 1.30053923e-01 7.06369877e-01 1.06439734e+00
9.30261374e-01 1.03651389e-01 -1.26231149e-01 4.51692522e-01
1.99146748e-01 5.98010302e-01 2.37042934e-01 -1.34626794e+00
5.21140873e-01 3.15319598e-01 4.80415106e-01 -9.96904671e-01
-3.13279122e-01 -5.59738278e-01 -4.55480576e-01 3.83651257e-01
8.29012871e-01 -1.71558648e-01 -1.40888274e+00 1.86936009e+00
4.84171808e-01 4.88731891e-01 -2.97401138e-02 1.19369745e+00
5.63653708e-01 4.07749236e-01 1.36770412e-01 9.41022560e-02
1.14407182e+00 -1.29354739e+00 -5.08848488e-01 -6.43638790e-01
4.17926192e-01 -3.14792722e-01 9.82263803e-01 3.34588826e-01
-9.89294291e-01 -5.73109090e-01 -1.00391483e+00 1.63358301e-01
-3.11368614e-01 3.14978138e-02 9.12219167e-01 7.72671938e-01
-8.30156803e-01 4.42828268e-01 -1.13607192e+00 -3.69760215e-01
7.12600112e-01 1.59420699e-01 -3.15339595e-01 -9.15239379e-02
-8.39181483e-01 5.47334850e-01 4.30546522e-01 1.24605335e-01
-1.07727134e+00 -5.73061347e-01 -8.78178298e-01 -1.58999875e-01
6.58093631e-01 -9.20566559e-01 1.08641267e+00 -1.40435636e+00
-1.22722888e+00 6.59330487e-01 -2.92596310e-01 -5.58712602e-01
8.41980457e-01 -1.54706389e-01 -2.18138471e-01 4.22434449e-01
2.74768174e-01 9.10019934e-01 8.44065964e-01 -1.80824518e+00
-9.91492569e-01 -1.27463520e-01 3.97049725e-01 1.12364769e-01
-3.46786082e-02 -4.40650821e-01 -9.84276772e-01 -5.68566322e-01
5.40975854e-02 -1.21831286e+00 -4.49563920e-01 1.13600455e-01
-5.40631533e-01 3.33864838e-01 9.28687215e-01 -4.02388781e-01
9.22737420e-01 -2.15452170e+00 1.97181497e-02 1.21777818e-01
2.64652431e-01 1.29090592e-01 -1.47166029e-01 -1.35257870e-01
2.29933247e-01 1.18202470e-01 -5.86039066e-01 -4.91192818e-01
-1.13754518e-01 4.81054753e-01 -2.26292640e-01 5.94113886e-01
4.10277069e-01 1.09186459e+00 -1.19055736e+00 -6.04350269e-01
4.35182273e-01 2.68480629e-01 -5.75206995e-01 -2.66057372e-01
-3.93660009e-01 7.24451661e-01 -5.78597903e-01 7.49805748e-01
6.39023840e-01 -4.00818855e-01 -2.45290659e-02 -8.44277292e-02
9.62992683e-02 2.81833522e-02 -1.48217499e+00 1.87227392e+00
-2.73165137e-01 8.72189522e-01 1.20132558e-01 -9.42645431e-01
2.74835706e-01 -1.90693319e-01 7.11578131e-01 -4.66489613e-01
-8.20027441e-02 -2.08300576e-02 1.96704403e-01 -7.29848862e-01
5.05535126e-01 2.16134816e-01 1.18167847e-01 2.41071001e-01
-1.21577933e-01 1.39818331e-02 5.30502319e-01 2.92784840e-01
1.16048586e+00 4.31555390e-01 -2.30642378e-01 -1.03273764e-01
2.30228439e-01 2.55486876e-01 8.63488674e-01 1.06353855e+00
-5.27220070e-01 9.19257700e-01 1.55656740e-01 -3.21095169e-01
-8.65344107e-01 -1.26894915e+00 -2.17637479e-01 9.02879655e-01
9.18493271e-01 -4.10566218e-02 -6.20321691e-01 -9.39626038e-01
9.32496935e-02 6.04982078e-01 -8.29753280e-01 1.34310842e-01
-7.49369562e-01 -8.55201066e-01 3.07547718e-01 6.04386151e-01
3.98703486e-01 -8.51148963e-01 -1.08506536e+00 2.42791593e-01
-3.94900948e-01 -1.54325140e+00 -5.17492056e-01 1.02135450e-01
-6.44392788e-01 -1.14646626e+00 -4.86896843e-01 -4.80907530e-01
6.34200871e-01 4.98132467e-01 1.20283592e+00 -1.13130659e-01
-5.80900490e-01 6.88674986e-01 -2.45837271e-01 -1.38593167e-01
-2.32298464e-01 -1.44430231e-02 -1.78886831e-01 4.82808739e-01
3.33227701e-02 -4.03371811e-01 -9.48298037e-01 3.50460142e-01
-8.83842647e-01 2.44811416e-01 6.58657551e-01 5.40408790e-01
4.77286726e-01 1.92000414e-03 2.62454569e-01 -9.04242516e-01
-1.39726058e-01 -4.57660407e-01 -5.45627594e-01 2.35533431e-01
-1.54672116e-01 5.55094518e-02 2.83555776e-01 -6.82830036e-01
-1.03672218e+00 5.10820389e-01 4.91391182e-01 -5.45871317e-01
-4.40986872e-01 1.30672947e-01 -2.36326307e-01 -8.23704004e-02
5.25713921e-01 2.31083959e-01 -3.80524814e-01 -2.50332534e-01
7.13084042e-01 1.90364778e-01 9.00969863e-01 -6.44901335e-01
8.71005476e-01 1.16824663e+00 -6.72001839e-02 -7.86737859e-01
-7.12590992e-01 -7.37853110e-01 -8.04172516e-01 -3.03751111e-01
1.04850280e+00 -9.31993663e-01 -3.93550277e-01 2.00041980e-01
-1.01369929e+00 -6.81523621e-01 -4.29582596e-01 4.26025093e-01
-6.94234431e-01 4.79494870e-01 -3.74827951e-01 -9.38053191e-01
2.39898652e-01 -1.26869392e+00 1.17146730e+00 2.07696557e-01
3.74734253e-02 -1.07422721e+00 -1.79557085e-01 3.67093712e-01
2.58251160e-01 5.23078680e-01 4.26148772e-01 -3.07465315e-01
-1.16711140e+00 -2.34144530e-03 -2.67565906e-01 1.15900256e-01
2.33607233e-01 1.61530569e-01 -1.08661282e+00 -1.08916223e-01
-2.94212520e-01 -1.27550676e-01 1.40454555e+00 4.68122542e-01
1.16245127e+00 -1.44609604e-02 -6.19645178e-01 8.45766962e-01
1.40738082e+00 1.91668347e-01 3.29700410e-01 2.84579843e-01
1.09250379e+00 6.31069779e-01 5.93981981e-01 2.30830431e-01
4.25253212e-01 7.51340389e-01 6.09794259e-01 -3.47754478e-01
-5.22799611e-01 -6.57610968e-02 3.47234398e-01 8.10698643e-02
-1.52118370e-01 -4.03920859e-01 -1.02236319e+00 8.55688691e-01
-2.06397390e+00 -1.02285433e+00 -2.23025024e-01 2.05549788e+00
6.55559659e-01 3.49897116e-01 2.17418283e-01 -2.08972842e-01
5.82833886e-01 1.36716306e-01 -7.86599040e-01 3.53465319e-01
-3.38541657e-01 -9.85193700e-02 8.51292670e-01 6.27691627e-01
-1.59725213e+00 1.18501425e+00 5.92331219e+00 4.59225476e-01
-1.27348542e+00 1.02198264e-02 6.45394027e-01 -6.64001703e-02
-2.11107373e-01 1.51580691e-01 -7.71782994e-01 4.55903947e-01
5.10083556e-01 1.39578864e-01 2.91458994e-01 6.41802311e-01
3.17129493e-01 -2.63025224e-01 -1.30630565e+00 8.26838970e-01
4.87618633e-02 -1.25178981e+00 -3.21297087e-02 -8.78546610e-02
9.27515090e-01 1.64792448e-01 2.30347246e-01 5.42275012e-02
5.05289733e-01 -9.31700051e-01 1.04143238e+00 4.12916183e-01
4.61265296e-01 -2.22611815e-01 3.12675893e-01 2.09116116e-01
-1.21024144e+00 -1.55387506e-01 -1.63144208e-02 1.49748981e-01
3.59611005e-01 4.10370529e-01 -6.57326043e-01 5.75628996e-01
5.60147405e-01 8.87252629e-01 -8.43292356e-01 1.24806118e+00
-8.85205120e-02 7.15482116e-01 -4.87277776e-01 4.10844743e-01
4.76809978e-01 -1.75195307e-01 6.61404610e-01 1.37101996e+00
-8.12143013e-02 3.30387689e-02 5.88894367e-01 1.07602620e+00
2.31941909e-01 -3.52661729e-01 -4.71158415e-01 1.31346285e-01
1.65349692e-01 1.19208670e+00 -1.19148827e+00 -5.20771205e-01
-4.63837415e-01 1.09676433e+00 1.61170617e-01 9.30800498e-01
-1.11229730e+00 -1.75117925e-01 8.16151857e-01 1.89984918e-01
7.25552917e-01 -6.38821244e-01 -2.51958907e-01 -1.39679611e+00
1.61850929e-01 -6.15711033e-01 9.46698561e-02 -4.96084571e-01
-1.03836823e+00 3.58328819e-01 1.31965607e-01 -1.24844408e+00
-7.59698078e-02 -6.19568348e-01 -3.63458037e-01 4.93737578e-01
-1.67228854e+00 -1.19412327e+00 -5.30449450e-01 3.63077581e-01
8.20398688e-01 3.76305014e-01 1.60172433e-01 3.45241874e-01
-7.49610960e-01 2.74764150e-01 -3.56253870e-02 4.24778521e-01
6.08341396e-01 -1.34175813e+00 3.91497582e-01 1.19599342e+00
6.10481620e-01 4.96918410e-01 6.77901864e-01 -5.77183604e-01
-1.32712960e+00 -1.35661662e+00 1.30586699e-01 -9.51736569e-01
5.68657994e-01 -6.09933197e-01 -8.51414025e-01 6.90708458e-01
-1.07165165e-01 6.07221901e-01 1.98727146e-01 -1.75557896e-01
-2.46960238e-01 6.16286658e-02 -7.19614267e-01 6.30140007e-01
1.39417791e+00 -1.81016445e-01 -3.25546205e-01 2.19191849e-01
6.37447715e-01 -4.70030695e-01 -3.77626628e-01 5.27371049e-01
4.75515246e-01 -9.42387879e-01 1.26493645e+00 -7.67587662e-01
3.35918903e-01 -7.51457632e-01 -4.08798866e-02 -8.81538868e-01
-1.92591771e-01 -5.61775327e-01 -2.70495236e-01 9.89598095e-01
3.93942624e-01 -3.06375921e-01 1.04396331e+00 7.23325968e-01
-6.73500299e-02 -3.81993353e-01 -7.41183043e-01 -9.20465231e-01
-3.64857204e-02 -6.35464370e-01 1.18844278e-01 1.08537316e+00
-4.80414003e-01 2.11672962e-01 -2.87497252e-01 4.11159903e-01
7.31201530e-01 3.53559345e-01 1.03312922e+00 -1.03370261e+00
-5.62503219e-01 -5.49341559e-01 -5.66749871e-01 -1.45737219e+00
1.72381476e-01 -7.32693136e-01 4.10071582e-01 -1.54328060e+00
1.61196247e-01 -8.45477879e-01 -3.00001204e-01 4.04777616e-01
-4.34046239e-01 4.33789015e-01 3.14051062e-01 1.77728415e-01
-9.77636695e-01 4.29023087e-01 1.35305774e+00 -5.45036912e-01
-3.80791038e-01 -7.81909376e-02 -4.09112006e-01 8.30298722e-01
5.82614541e-01 -3.68762016e-01 -6.16497278e-01 -6.08828425e-01
-2.56466329e-01 -1.10014334e-01 6.86174750e-01 -1.08011937e+00
1.63273290e-01 -5.28384566e-01 3.99845809e-01 -3.68952274e-01
3.98909092e-01 -8.99683654e-01 -3.23706158e-02 4.05822486e-01
-3.12240988e-01 -3.30865085e-01 2.34245986e-01 9.80593085e-01
5.95801976e-03 -5.23481937e-03 6.94796920e-01 -6.29756227e-02
-1.23984349e+00 4.83966678e-01 -2.33640462e-01 3.76182735e-01
1.17938161e+00 -4.62408423e-01 -2.40130231e-01 -3.45792055e-01
-8.85048211e-01 3.34481895e-01 6.79576039e-01 5.17688990e-01
2.82623410e-01 -9.30360675e-01 -6.06625915e-01 6.71591535e-02
2.33021528e-01 3.25800896e-01 1.13797963e-01 9.57329035e-01
-5.49179256e-01 2.68385589e-01 9.43188928e-03 -1.09401643e+00
-8.69817734e-01 6.56745315e-01 4.55458730e-01 1.64026126e-01
-8.27735245e-01 6.70860589e-01 7.87100971e-01 1.36744320e-01
1.92382231e-01 -7.52840042e-01 7.21372068e-02 -1.83398187e-01
2.10629866e-01 8.89155567e-02 -2.53650248e-01 -7.07832158e-01
-3.71540189e-01 6.98594570e-01 1.34277567e-01 -2.94708997e-01
9.34606135e-01 -3.89068514e-01 4.38910127e-01 6.90915406e-01
9.50173736e-01 2.03554466e-01 -1.74984622e+00 -1.83448017e-01
1.71648264e-01 -7.06373096e-01 -9.52689052e-02 -6.47695661e-01
-1.18713057e+00 8.67109120e-01 5.09653926e-01 2.33210195e-02
8.28076303e-01 4.53013517e-02 5.57936013e-01 3.47699285e-01
3.87772858e-01 -9.33293521e-01 1.92703992e-01 2.84938902e-01
2.94188261e-01 -1.60842776e+00 -2.27452174e-01 -6.53871000e-01
-6.07686937e-01 9.58164215e-01 7.82129109e-01 4.23109950e-03
3.34880173e-01 2.20012814e-01 1.71343327e-01 7.35259354e-02
-6.11879289e-01 -6.86683357e-01 3.48798871e-01 7.38480985e-01
4.26095575e-02 -1.16736583e-01 1.69358864e-01 3.06129664e-01
7.96435252e-02 -1.28204256e-01 6.19392395e-01 9.75787401e-01
-3.28599632e-01 -8.77984941e-01 -2.56429493e-01 1.12060212e-01
-2.84590691e-01 5.01817912e-02 -3.21885705e-01 1.12152660e+00
3.77078861e-01 8.12201500e-01 3.24031323e-01 -2.83178724e-02
5.46799786e-02 -2.32233956e-01 5.98527789e-01 -5.78596115e-01
1.07577229e-02 8.12834278e-02 3.66814137e-02 -6.66557252e-01
-7.27689326e-01 -8.01312625e-01 -1.29065764e+00 2.76089847e-01
-2.48259783e-01 -2.20701754e-01 5.41967571e-01 8.27950776e-01
2.47077137e-01 7.27198839e-01 3.13118607e-01 -1.02647686e+00
-1.53123558e-01 -4.32755649e-01 -3.00094634e-01 7.70756781e-01
7.88962603e-01 -7.53589272e-01 -3.92138392e-01 5.69959462e-01] | [9.092209815979004, -0.14029598236083984] |
e0fbee18-8f3a-468e-8a82-1ed692bda54a | multi-graph-convolution-network-for-pose | 2304.04956 | null | https://arxiv.org/abs/2304.04956v1 | https://arxiv.org/pdf/2304.04956v1.pdf | Multi-Graph Convolution Network for Pose Forecasting | Recently, there has been a growing interest in predicting human motion, which involves forecasting future body poses based on observed pose sequences. This task is complex due to modeling spatial and temporal relationships. The most commonly used models for this task are autoregressive models, such as recurrent neural networks (RNNs) or variants, and Transformer Networks. However, RNNs have several drawbacks, such as vanishing or exploding gradients. Other researchers have attempted to solve the communication problem in the spatial dimension by integrating Graph Convolutional Networks (GCN) and Long Short-Term Memory (LSTM) models. These works deal with temporal and spatial information separately, which limits the effectiveness. To fix this problem, we propose a novel approach called the multi-graph convolution network (MGCN) for 3D human pose forecasting. This model simultaneously captures spatial and temporal information by introducing an augmented graph for pose sequences. Multiple frames give multiple parts, joined together in a single graph instance. Furthermore, we also explore the influence of natural structure and sequence-aware attention to our model. In our experimental evaluation of the large-scale benchmark datasets, Human3.6M, AMSS and 3DPW, MGCN outperforms the state-of-the-art in pose prediction. | ['Kewei Liang', 'Yuhong Shi', 'Hongwei Ren'] | 2023-04-11 | null | null | null | null | ['pose-prediction', 'human-pose-forecasting'] | ['computer-vision', 'computer-vision'] | [-5.35308979e-02 -9.99638662e-02 -5.84100522e-02 -1.94786057e-01
-7.55210519e-02 1.32888585e-01 2.62189776e-01 -4.43857610e-01
-3.24534267e-01 4.73961800e-01 5.74666142e-01 4.83440645e-02
2.71647703e-02 -7.56137431e-01 -8.66268516e-01 -5.32961547e-01
-3.61849666e-01 3.37400705e-01 3.76983881e-01 -3.40573817e-01
-1.75564557e-01 3.08493942e-01 -1.20217514e+00 5.07785976e-02
5.44330299e-01 9.70900714e-01 3.29684794e-01 6.09864235e-01
-4.73502576e-02 1.23134708e+00 -3.97626638e-01 -4.15698439e-01
-3.21237370e-02 -3.88743252e-01 -6.85676217e-01 9.12725925e-02
9.56835225e-02 -4.24106002e-01 -8.04832578e-01 7.39291608e-01
7.34221816e-01 4.52196896e-01 3.06916982e-01 -1.25154877e+00
-5.31740248e-01 5.16323149e-01 -6.49172544e-01 1.39634877e-01
4.06790018e-01 1.36774465e-01 6.01737320e-01 -6.08234584e-01
6.21349752e-01 1.62704182e+00 8.09774339e-01 6.30619466e-01
-7.78642654e-01 -5.77109396e-01 6.33405566e-01 5.91218114e-01
-1.26110554e+00 -4.81582060e-03 9.87600148e-01 -3.73009235e-01
1.14490128e+00 -7.31791109e-02 1.07818770e+00 1.52641726e+00
5.74282885e-01 1.05761933e+00 4.85844046e-01 -1.96215697e-02
-3.15021098e-01 -6.47632003e-01 -6.23529516e-02 8.10119033e-01
-1.41783923e-01 9.78864059e-02 -5.58123112e-01 1.61662370e-01
1.08099949e+00 4.46327776e-01 -3.52964848e-01 -3.13746035e-01
-1.30389965e+00 6.57271862e-01 9.13640678e-01 2.20060408e-01
-5.69798410e-01 4.55063552e-01 5.99255860e-01 -1.95461661e-02
7.65672982e-01 -3.05320248e-02 -3.42394471e-01 -1.52803779e-01
-5.56804419e-01 3.78631055e-01 5.84872901e-01 9.00447309e-01
2.64818460e-01 2.10942253e-01 -6.85364231e-02 7.67725706e-01
5.93885839e-01 3.50361258e-01 6.84447229e-01 -5.81095278e-01
7.40678370e-01 5.74704170e-01 -2.95378745e-01 -1.55531704e+00
-8.64976168e-01 -6.20884955e-01 -1.31700480e+00 -3.56685013e-01
1.48505732e-01 -2.40421668e-01 -1.13923609e+00 1.88379800e+00
3.32185149e-01 5.11948168e-01 -1.83096513e-01 1.28762484e+00
1.14788640e+00 8.41356456e-01 1.76585108e-01 -4.67392877e-02
1.07423604e+00 -1.28282368e+00 -8.88649046e-01 -3.36775810e-01
5.99471509e-01 -4.59422857e-01 7.80402184e-01 1.65431559e-01
-9.39655900e-01 -8.77104282e-01 -8.80279660e-01 -2.19085738e-01
-1.78980261e-01 3.86603288e-02 6.09373748e-01 7.36849383e-02
-1.02443302e+00 8.64630401e-01 -1.22224045e+00 -3.59782547e-01
-6.96630627e-02 3.57702494e-01 -2.76386291e-01 9.75845940e-03
-1.55449772e+00 8.57169569e-01 2.72953600e-01 8.14849734e-01
-6.16528153e-01 -1.44779012e-01 -1.24723935e+00 -1.42089754e-01
5.39609790e-01 -1.03164971e+00 9.11165416e-01 -7.20291078e-01
-1.59955120e+00 3.68715346e-01 -1.16230212e-01 -6.09616756e-01
5.44586241e-01 -6.60869479e-01 -5.01469195e-01 -1.70053974e-01
-1.24309100e-01 6.44909978e-01 6.38241112e-01 -7.87338018e-01
-1.84689850e-01 -6.86554193e-01 4.06882651e-02 4.64677304e-01
-1.80751204e-01 -1.43374562e-01 -7.15586066e-01 -8.97597253e-01
3.57892513e-01 -1.25147104e+00 -5.48899472e-01 -3.32778424e-01
-5.71233273e-01 -2.64494002e-01 7.16806948e-01 -9.80865180e-01
1.49267554e+00 -1.87040603e+00 7.30632782e-01 2.01856382e-02
1.72635600e-01 2.56547540e-01 -1.05753310e-01 3.40716064e-01
-1.31128985e-03 -1.52760878e-01 1.29470423e-01 -5.29043436e-01
-1.67456254e-01 4.31210041e-01 -9.74815637e-02 4.63237256e-01
-6.00159988e-02 1.19427812e+00 -7.74618328e-01 -6.07016504e-01
4.21634167e-01 8.37169945e-01 -4.62147564e-01 2.88702726e-01
-3.16816509e-01 7.22842038e-01 -4.80521232e-01 3.42185110e-01
3.17969769e-01 -5.32375813e-01 1.14254922e-01 -3.93803269e-01
1.09084994e-01 1.39241666e-01 -1.08313191e+00 2.09083295e+00
-3.16086769e-01 3.35571021e-01 -4.45875198e-01 -9.02348876e-01
8.70798409e-01 3.84601414e-01 5.68589151e-01 -6.00580275e-01
2.71420538e-01 -5.68014644e-02 -6.93493336e-02 -6.92979336e-01
4.86509562e-01 3.40349413e-02 4.25417069e-03 -4.65990640e-02
1.43233985e-01 5.63887656e-01 -9.68613625e-02 -9.58762132e-03
9.51175153e-01 6.07973576e-01 2.47204527e-02 1.66656822e-01
4.78123844e-01 -3.33270609e-01 8.05373013e-01 2.13102654e-01
-1.29054353e-01 7.07758129e-01 2.95858264e-01 -8.01916420e-01
-6.47774875e-01 -6.46070361e-01 6.56592846e-01 1.03935969e+00
3.12538773e-01 -5.88779986e-01 -4.99213755e-01 -3.86947185e-01
-2.06183270e-01 1.64505050e-01 -6.68727458e-01 -3.31489086e-01
-1.07704496e+00 -5.02740562e-01 3.91141862e-01 8.84504080e-01
7.49574721e-01 -1.28715920e+00 -6.16834819e-01 5.19073486e-01
-5.69387794e-01 -1.27067041e+00 -6.93558276e-01 -3.66540968e-01
-9.61594403e-01 -8.55843902e-01 -1.16277468e+00 -7.45531440e-01
3.36754471e-01 8.89618844e-02 1.08222938e+00 -4.45009507e-02
-1.48486882e-01 2.21436724e-01 -4.45252031e-01 -1.21747337e-01
2.28997245e-01 2.72642821e-01 5.42221665e-02 1.31649360e-01
2.68136207e-02 -7.48674989e-01 -7.05078423e-01 3.90783638e-01
-5.60254097e-01 3.92664999e-01 6.04343891e-01 8.31416249e-01
6.27168238e-01 -3.26717794e-01 2.07866222e-01 -7.26915956e-01
5.01067519e-01 -4.07183826e-01 -2.24418238e-01 2.02386975e-01
-1.04120336e-01 1.04499340e-01 5.71228981e-01 -6.35204971e-01
-1.05070031e+00 2.32114822e-01 -3.66889119e-01 -1.05046117e+00
4.88755247e-03 9.03209329e-01 -1.73922420e-01 3.25099230e-02
2.51568407e-01 2.90605396e-01 8.53229016e-02 -5.57503045e-01
1.89947918e-01 8.26421678e-02 5.29729009e-01 -1.86564565e-01
4.73429650e-01 1.58998773e-01 2.61364400e-01 -7.42500901e-01
-7.75201857e-01 -3.21343422e-01 -7.59737670e-01 -5.10614157e-01
1.17894101e+00 -9.93285418e-01 -8.91898811e-01 8.11309993e-01
-1.33010781e+00 -4.10418838e-01 1.80595651e-01 8.32493484e-01
-6.02629781e-01 4.22407597e-01 -1.06390703e+00 -8.12911034e-01
-3.17253143e-01 -1.05352628e+00 1.17028272e+00 1.06728658e-01
-1.87921375e-01 -1.05145335e+00 -2.53521707e-02 1.85370490e-01
2.33388439e-01 6.80774808e-01 5.40248275e-01 -2.41728306e-01
-5.12119770e-01 -1.34867057e-01 3.06927729e-02 -1.88261382e-02
-4.46890630e-02 -3.24199170e-01 -4.19766128e-01 -2.27632329e-01
-5.66057563e-02 -2.13344038e-01 9.51838255e-01 7.80629218e-01
1.22746694e+00 -2.75785297e-01 -3.76529723e-01 7.66787350e-01
8.93454969e-01 5.10412641e-02 7.41280258e-01 1.51161075e-01
1.39029443e+00 6.68938458e-01 6.31890714e-01 3.54559988e-01
7.45071471e-01 7.70452976e-01 4.21889514e-01 -2.07790390e-01
-3.63693759e-03 -6.05253339e-01 3.38934749e-01 1.17317033e+00
-7.17242002e-01 -3.22762907e-01 -8.54757726e-01 2.69789100e-01
-2.29891229e+00 -9.01906073e-01 -1.34637684e-01 1.88356316e+00
2.70429194e-01 2.43966848e-01 2.60426015e-01 -1.76936146e-02
7.48604953e-01 6.33030236e-01 -5.66457331e-01 1.65435243e-02
8.60230252e-02 -2.10137516e-01 4.50191647e-01 2.66904533e-01
-1.27632856e+00 9.75330710e-01 5.33236551e+00 6.75177276e-01
-1.20183218e+00 -1.17331669e-01 5.47874749e-01 -1.32273182e-01
7.01488182e-02 -4.18735951e-01 -7.39506245e-01 4.39447105e-01
7.85565853e-01 8.25159177e-02 2.94272184e-01 6.89991236e-01
2.41174176e-01 3.30126166e-01 -8.21813822e-01 1.23083258e+00
3.30383241e-01 -9.64453697e-01 1.94523379e-01 8.59943926e-02
3.38088095e-01 4.21573892e-02 -2.61903424e-02 4.43246841e-01
1.28123373e-01 -1.04628944e+00 6.08417511e-01 8.49435687e-01
3.72430950e-01 -7.62526512e-01 8.20633590e-01 5.19004881e-01
-1.74933100e+00 1.20040551e-02 -2.34628633e-01 -3.07491928e-01
5.95913589e-01 3.36960316e-01 -3.17216665e-01 7.16184139e-01
7.38590479e-01 1.28134859e+00 -4.35610831e-01 9.35908616e-01
-2.40755111e-01 2.49162957e-01 -2.40909815e-01 -1.59567356e-01
3.25744689e-01 -1.49683222e-01 5.12172818e-01 8.31477702e-01
3.60465318e-01 3.16978902e-01 5.82929730e-01 6.63090706e-01
5.36582656e-02 -7.22155049e-02 -6.05397522e-01 5.52773010e-03
-1.04981340e-01 9.42154408e-01 -5.57571471e-01 -2.67496169e-01
-4.02535379e-01 1.14223254e+00 3.22380960e-01 4.59465861e-01
-1.03173482e+00 3.00081708e-02 4.24494028e-01 6.32976592e-02
8.76806006e-02 -6.27081811e-01 1.64251879e-01 -1.17151034e+00
2.44478956e-01 -6.48954093e-01 6.16755486e-01 -8.05254519e-01
-1.19848168e+00 7.63089538e-01 -2.00491361e-02 -1.39556837e+00
-5.66066980e-01 -4.19274986e-01 -3.60217512e-01 7.04712212e-01
-1.11151242e+00 -1.43824828e+00 -4.53791112e-01 8.47955167e-01
7.42862046e-01 1.95008054e-01 5.81097305e-01 4.53621984e-01
-5.97059846e-01 3.47877234e-01 -5.51124394e-01 4.40589041e-01
4.46203709e-01 -1.01168883e+00 8.68866861e-01 6.02330863e-01
1.28690392e-01 4.84762609e-01 5.67716181e-01 -9.60108101e-01
-1.50499249e+00 -1.36444938e+00 9.98807728e-01 -4.02812324e-02
4.27061647e-01 -2.58958250e-01 -9.00302172e-01 1.03398442e+00
-1.72562376e-01 2.06097290e-01 2.40417495e-01 2.16420695e-01
1.31366076e-02 1.67469278e-01 -5.44192255e-01 6.59861028e-01
1.64727890e+00 -3.26320142e-01 -3.65761697e-01 2.90740758e-01
9.86197114e-01 -8.64569545e-01 -8.81986320e-01 7.91506052e-01
6.51666224e-01 -8.58398438e-01 1.04942191e+00 -5.87045789e-01
6.36012197e-01 -1.28088236e-01 8.50055292e-02 -1.36325943e+00
-4.93348509e-01 -4.22111332e-01 -3.89025211e-01 7.21730769e-01
2.08095238e-01 -4.79675651e-01 9.61863875e-01 5.80244899e-01
-3.20029080e-01 -1.02579796e+00 -7.58555949e-01 -7.45077968e-01
-3.28216702e-01 -3.66046637e-01 5.34700215e-01 6.92632198e-01
-2.01184362e-01 5.28424859e-01 -1.27255666e+00 1.05030984e-02
3.31952840e-01 1.19643070e-01 8.85885656e-01 -1.11144924e+00
-3.64706427e-01 -1.94673553e-01 -7.94900060e-01 -1.58152115e+00
1.40032977e-01 -4.08083916e-01 6.78945184e-02 -1.72433114e+00
-5.09471446e-03 2.16238618e-01 -2.67850310e-01 3.24826837e-01
-2.12781444e-01 -7.58541450e-02 3.22033823e-01 1.21886447e-01
-8.45378876e-01 9.05434430e-01 1.52722919e+00 -1.04316153e-01
-3.54972184e-01 1.85088292e-01 4.15000804e-02 9.52941060e-01
5.11757553e-01 -3.36290188e-02 -4.67571914e-01 -6.22997701e-01
1.32996097e-01 6.05889320e-01 5.48719943e-01 -1.24229360e+00
5.33384264e-01 7.79455006e-02 6.33993208e-01 -1.05469429e+00
6.98125422e-01 -6.35666668e-01 4.70518857e-01 7.20458508e-01
-2.55384833e-01 4.92748797e-01 -1.71053689e-02 8.78063202e-01
-4.26004559e-01 6.17056310e-01 2.09382012e-01 -4.41929787e-01
-1.09571826e+00 9.61305618e-01 -1.40441865e-01 -2.37421885e-01
7.10073769e-01 -2.19254375e-01 7.67931417e-02 -6.50108933e-01
-1.16782916e+00 4.95548040e-01 -5.82825094e-02 8.22859108e-01
8.29606295e-01 -1.64582443e+00 -5.15421331e-01 1.13386147e-01
-3.81589085e-02 8.33641738e-02 7.18230486e-01 9.39626157e-01
-3.78526300e-01 4.57064092e-01 -2.18041033e-01 -7.25228131e-01
-1.32187319e+00 6.20363772e-01 4.80221063e-01 -5.95255136e-01
-8.97291422e-01 9.68380213e-01 3.57414007e-01 -4.04975504e-01
4.94983077e-01 -4.21970755e-01 -5.23947477e-01 -1.74034491e-01
1.97256014e-01 3.59386265e-01 -2.59751648e-01 -9.96465504e-01
-3.91840100e-01 7.05805302e-01 2.10218206e-01 1.48895472e-01
1.24915326e+00 -2.61034220e-01 4.48031873e-02 7.93673217e-01
1.17749476e+00 -7.37381339e-01 -1.15018344e+00 -3.75909716e-01
-1.74759969e-01 -2.76961982e-01 -2.12418467e-01 -3.68670583e-01
-1.43106258e+00 1.02855992e+00 4.69636828e-01 -3.34174670e-02
1.03415048e+00 -2.26153359e-01 1.22193980e+00 2.29321152e-01
6.35279775e-01 -9.99956727e-01 2.50366807e-01 7.91531146e-01
1.06918001e+00 -1.05004859e+00 -1.13303609e-01 -5.14714837e-01
-6.59189999e-01 1.04780316e+00 9.35681224e-01 -3.25046033e-01
7.65647113e-01 -1.84198514e-01 -1.49958089e-01 -2.47811481e-01
-6.47351563e-01 -2.11185932e-01 6.26699567e-01 3.69448841e-01
6.52159810e-01 1.44147828e-01 -2.74425060e-01 7.59632230e-01
-2.32596546e-01 1.97942495e-01 -7.87368882e-03 8.32071781e-01
-1.17372364e-01 -8.46582055e-01 -1.71882659e-01 4.09944683e-01
-4.02351767e-01 9.77553651e-02 -2.74770379e-01 7.61469960e-01
4.23973799e-02 7.08694339e-01 -1.00659803e-01 -9.42593277e-01
5.28749824e-01 -2.39262193e-01 4.36741471e-01 -3.56527895e-01
-4.60298806e-01 3.32158357e-01 8.55401605e-02 -9.76112008e-01
-6.52362406e-01 -3.75632226e-01 -1.14216447e+00 -3.77454966e-01
-2.54935831e-01 -5.65246418e-02 3.19775671e-01 1.00846326e+00
3.20827812e-01 9.94688630e-01 2.01349720e-01 -1.25613606e+00
-2.23375052e-01 -1.11659527e+00 -6.27870083e-01 5.76065719e-01
2.50569850e-01 -8.96300793e-01 6.88057169e-02 -1.01870365e-01] | [7.257897853851318, -0.3724294602870941] |
577c21aa-2109-4b6e-8abd-6a820b6692da | do-as-i-can-not-as-i-get-topology-aware-multi | 2306.10345 | null | https://arxiv.org/abs/2306.10345v1 | https://arxiv.org/pdf/2306.10345v1.pdf | Do as I can, not as I get: Topology-aware multi-hop reasoning on multi-modal knowledge graphs | Multi-modal knowledge graph (MKG) includes triplets that consist of entities and relations and multi-modal auxiliary data. In recent years, multi-hop multi-modal knowledge graph reasoning (MMKGR) based on reinforcement learning (RL) has received extensive attention because it addresses the intrinsic incompleteness of MKG in an interpretable manner. However, its performance is limited by empirically designed rewards and sparse relations. In addition, this method has been designed for the transductive setting where test entities have been seen during training, and it works poorly in the inductive setting where test entities do not appear in the training set. To overcome these issues, we propose TMR (Topology-aware Multi-hop Reasoning), which can conduct MKG reasoning under inductive and transductive settings. Specifically, TMR mainly consists of two components. (1) The topology-aware inductive representation captures information from the directed relations of unseen entities, and aggregates query-related topology features in an attentive manner to generate the fine-grained entity-independent features. (2) After completing multi-modal feature fusion, the relation-augment adaptive RL conducts multi-hop reasoning by eliminating manual rewards and dynamically adding actions. Finally, we construct new MKG datasets with different scales for inductive reasoning evaluation. Experimental results demonstrate that TMP outperforms state-of-the-art MKGR methods under both inductive and transductive settings. | ['Lei Zhao', 'Wei Chen', 'Quoc Viet Hung Nguyen', 'Tong Chen', 'Hongzhi Yin', 'Shangfei Zheng'] | 2023-06-17 | null | null | null | null | ['knowledge-graphs', 'multi-modal-knowledge-graph'] | ['knowledge-base', 'knowledge-base'] | [-6.60832003e-02 5.91180027e-01 -4.75896239e-01 -2.53987730e-01
-9.20400143e-01 -5.81603944e-01 3.82196218e-01 3.09552610e-01
-4.31682095e-02 9.98362720e-01 1.68665797e-01 -1.97685167e-01
-6.70852780e-01 -1.37458277e+00 -8.63059223e-01 -5.48059583e-01
-3.14177424e-01 9.67612088e-01 3.28829825e-01 -5.47464192e-01
-2.24459291e-01 3.55711311e-01 -1.44766927e+00 2.30352968e-01
1.22505558e+00 9.81147826e-01 -1.97173223e-01 4.22275662e-01
-8.32832232e-02 1.26213789e+00 -3.80156100e-01 -5.71158469e-01
4.12712954e-02 -1.64161935e-01 -1.13631320e+00 -1.66748449e-01
5.69635481e-02 -2.18353972e-01 -4.86204833e-01 7.15669334e-01
4.67568994e-01 3.12962353e-01 3.45460415e-01 -1.47374570e+00
-1.03123617e+00 1.09786975e+00 -4.01500136e-01 3.97246704e-02
6.47233546e-01 -4.77481559e-02 1.47744644e+00 -9.65849638e-01
6.84515297e-01 1.54495919e+00 4.02288765e-01 2.53287792e-01
-1.18125308e+00 -4.25671130e-01 5.46517789e-01 3.75183225e-01
-1.55068505e+00 -6.84711486e-02 9.56992388e-01 -3.30459489e-03
8.60927105e-01 2.08141640e-01 6.44675851e-01 8.77246082e-01
-1.63550526e-01 1.02545059e+00 9.07123804e-01 -3.38020742e-01
2.95354605e-01 -6.96503669e-02 -6.05440214e-02 1.02692485e+00
1.79244727e-01 -1.46686786e-03 -6.13202393e-01 -3.10949832e-01
7.12007463e-01 -1.23821288e-01 -1.29880324e-01 -5.41902900e-01
-1.36718798e+00 9.96011615e-01 8.13156009e-01 2.30734393e-01
-4.80504811e-01 1.94867626e-01 1.97930276e-01 4.57227468e-01
2.76948720e-01 5.49194455e-01 -5.59335113e-01 2.16669098e-01
-2.15018660e-01 5.06483987e-02 8.51725638e-01 1.11082935e+00
1.24029303e+00 -1.78981125e-01 -3.27707827e-01 8.65727007e-01
3.63022745e-01 5.46134710e-01 3.28582376e-01 -8.95066977e-01
8.07144523e-01 1.22746313e+00 -2.00895593e-01 -1.14550221e+00
-4.86055076e-01 -1.49511516e-01 -8.06845784e-01 -3.62993628e-01
8.47523287e-02 -2.48933330e-01 -8.97578835e-01 1.85353243e+00
6.15949929e-01 2.25399122e-01 4.81955886e-01 8.59370768e-01
1.28249300e+00 3.12083066e-01 1.54417619e-01 -7.15472251e-02
1.26944864e+00 -9.74659860e-01 -4.72445399e-01 -2.08206236e-01
9.57253933e-01 -1.71338990e-01 8.14930737e-01 -4.46166545e-02
-8.94116461e-01 -2.52520084e-01 -8.30757380e-01 1.09377345e-02
-7.96422720e-01 -1.51877180e-01 9.58096147e-01 2.10038647e-01
-1.11524248e+00 2.25955293e-01 -4.16285276e-01 -1.95876271e-01
2.07905725e-01 4.53078836e-01 -4.78537381e-01 -4.29003358e-01
-1.83645070e+00 7.51362860e-01 8.14279497e-01 1.86980382e-01
-6.46468639e-01 -5.37981987e-01 -1.14044476e+00 1.73311960e-02
1.23396742e+00 -9.94369507e-01 8.02952826e-01 -3.32292140e-01
-1.29545176e+00 4.48534459e-01 6.75100088e-02 -1.42156690e-01
2.76598364e-01 -3.34993973e-02 -7.42427289e-01 4.71999437e-01
1.86410636e-01 5.35330296e-01 5.85416794e-01 -1.49246037e+00
-5.51404178e-01 -4.36011732e-01 7.23571658e-01 6.12111449e-01
-1.24102749e-01 -7.73779273e-01 -7.04153657e-01 -4.78359848e-01
3.19625497e-01 -8.57775092e-01 -1.51315778e-01 -5.31145453e-01
-7.27868259e-01 -5.56716084e-01 8.26545596e-01 -9.81589779e-02
1.06300986e+00 -1.81260026e+00 3.59110534e-01 6.14691138e-01
5.29960275e-01 4.74465787e-02 -2.74371982e-01 5.63259840e-01
1.46129102e-01 1.31990924e-01 1.36513323e-01 1.20702408e-01
-6.34560781e-03 5.08421838e-01 -3.61818820e-01 -7.68088475e-02
3.60448569e-01 1.51978421e+00 -1.38343096e+00 -9.78930056e-01
1.95725217e-01 9.61842015e-02 -4.15976673e-01 8.66132230e-02
-3.71829063e-01 2.03302890e-01 -1.07175684e+00 1.25656188e+00
3.61680090e-01 -8.18693936e-01 5.60256302e-01 -5.00020921e-01
5.26276886e-01 -9.28033739e-02 -1.14898932e+00 1.59820580e+00
-4.40086275e-01 -1.50204208e-02 -3.74491513e-01 -1.11448014e+00
8.18382204e-01 1.46212280e-01 6.30053043e-01 -7.02779174e-01
-1.26942381e-01 6.91328868e-02 -3.49694490e-01 -4.99379456e-01
6.29427254e-01 -7.77262822e-03 -3.36991698e-01 3.48657131e-01
2.25357592e-01 2.12153550e-02 3.13324839e-01 7.04246461e-01
1.43812466e+00 9.65422913e-02 2.83494681e-01 3.05570215e-01
5.63319504e-01 5.81651628e-02 7.44892776e-01 8.22863519e-01
6.53367713e-02 2.31210943e-02 4.11835134e-01 -2.77528077e-01
-2.22353086e-01 -1.31936717e+00 2.71631271e-01 1.28289688e+00
7.47416139e-01 -5.52291572e-01 -1.06149554e-01 -1.07663608e+00
3.50533396e-01 5.13651848e-01 -7.80171514e-01 -4.82126206e-01
-4.21763450e-01 -5.73311031e-01 6.26919925e-01 6.95208251e-01
5.95258355e-01 -1.24232507e+00 2.81473603e-02 2.87694603e-01
-5.55797517e-01 -1.30959427e+00 -1.25806764e-01 1.14453174e-01
-6.28441632e-01 -1.47515857e+00 -1.53498262e-01 -6.36427522e-01
8.64559889e-01 3.00497741e-01 1.33392155e+00 1.20751828e-01
-8.37573335e-02 8.02304685e-01 -6.68572187e-01 9.50037837e-02
-1.59996092e-01 1.15266211e-01 -5.10251559e-02 -3.76258492e-02
2.53486782e-01 -5.30622661e-01 -5.11009991e-01 6.18461847e-01
-9.19101715e-01 -1.71023700e-02 1.08114779e+00 8.84183288e-01
8.02476943e-01 2.81794280e-01 1.06096017e+00 -1.16955400e+00
7.04187393e-01 -6.27683938e-01 -2.45130926e-01 9.07108128e-01
-6.22697175e-01 2.83249140e-01 7.08176315e-01 -5.23105562e-01
-1.08982694e+00 -2.67839164e-01 3.80952626e-01 -5.63456237e-01
1.60368964e-01 9.72476661e-01 -2.02983052e-01 -2.70260036e-01
5.58857381e-01 7.76427388e-02 -3.61497790e-01 -3.65458592e-03
7.78302789e-01 2.20306486e-01 4.09031481e-01 -1.13728905e+00
1.12619019e+00 3.43435317e-01 5.70464171e-02 -3.62037241e-01
-9.57938015e-01 -4.08204705e-01 -3.52588594e-01 -2.99649656e-01
5.25326610e-01 -9.92061794e-01 -1.06459069e+00 8.30276832e-02
-6.04429901e-01 -3.32665503e-01 -5.19871175e-01 5.25890946e-01
-5.74920118e-01 1.80662528e-01 -5.56159735e-01 -7.08153248e-01
-2.31554210e-01 -9.19866264e-01 1.10012710e+00 2.03137502e-01
1.92459300e-01 -1.12496710e+00 -1.66753978e-01 6.53038740e-01
2.77987849e-02 4.38086241e-01 1.11546552e+00 -6.84096038e-01
-9.91437376e-01 -3.76644880e-02 -3.39421481e-01 -1.04171783e-01
2.96823978e-01 -3.39201570e-01 -6.75813675e-01 -2.32311442e-01
-8.96089435e-01 -1.03599560e+00 7.72734821e-01 -4.24556062e-02
9.90307152e-01 -2.62207925e-01 -5.38093805e-01 2.03084946e-01
1.27857101e+00 -7.60403723e-02 2.82076925e-01 1.16147436e-01
1.00969589e+00 4.89873499e-01 1.02164865e+00 2.71104544e-01
1.12558472e+00 3.77702624e-01 5.08785307e-01 -2.30042726e-01
6.08000979e-02 -5.71816742e-01 -3.44785340e-02 7.30788529e-01
-2.44322419e-01 -3.16072702e-01 -7.85076141e-01 5.33642411e-01
-2.43730950e+00 -8.70693922e-01 2.86065549e-01 1.80973959e+00
8.48996341e-01 5.37582394e-03 5.53172976e-02 4.49886993e-02
6.14417851e-01 1.04814909e-01 -9.91592288e-01 3.58346663e-02
-3.49938929e-01 -2.20239282e-01 2.22329736e-01 3.52744937e-01
-8.54840219e-01 1.21947789e+00 5.47650337e+00 7.71222353e-01
-5.63435614e-01 -2.95506448e-01 3.39207798e-01 2.82514244e-01
-7.24729598e-01 1.80188105e-01 -6.20866597e-01 5.82423583e-02
4.21684325e-01 -1.91309765e-01 7.05235541e-01 7.17949927e-01
-4.13800865e-01 -1.44752517e-01 -1.11472237e+00 8.22656989e-01
-1.24462903e-01 -1.29614007e+00 2.66583860e-01 5.83052859e-02
6.77012861e-01 -6.89037144e-02 -1.14585891e-01 9.34351563e-01
9.38395679e-01 -7.76715934e-01 2.51383871e-01 7.20650434e-01
8.17530036e-01 -6.81309104e-01 7.01665819e-01 2.08951086e-01
-1.68115687e+00 -2.75289744e-01 -8.68875831e-02 4.28553104e-01
2.88303345e-02 6.80274904e-01 -1.00142455e+00 1.35268891e+00
5.93012989e-01 5.96774042e-01 -6.88375294e-01 4.51220363e-01
-3.74153823e-01 3.14278185e-01 -3.84885252e-01 6.26686215e-03
1.65873736e-01 -6.69189021e-02 4.47347552e-01 6.63839996e-01
-5.17344736e-02 3.61208320e-01 5.60802400e-01 7.71332026e-01
-4.32158321e-01 5.93088148e-03 -6.17230415e-01 -1.36055380e-01
8.05069327e-01 1.39500451e+00 -5.96108735e-01 -3.89533103e-01
-3.98883700e-01 5.67012310e-01 9.06746686e-01 6.42770469e-01
-7.75591969e-01 -2.63785630e-01 1.40481755e-01 -2.22932264e-01
3.26498538e-01 3.08404833e-01 2.18796358e-01 -1.32903707e+00
1.99794188e-01 -5.54315627e-01 1.01059413e+00 -8.78694654e-01
-1.58255482e+00 5.11729479e-01 1.36072621e-01 -9.75311279e-01
-5.09389162e-01 -1.42218515e-01 -1.97858989e-01 4.28126901e-01
-1.72479022e+00 -1.54359686e+00 -4.42580849e-01 9.31563377e-01
-1.81135014e-02 -7.19734132e-02 9.78280425e-01 1.44217372e-01
-5.10690272e-01 6.21854544e-01 -4.05857950e-01 2.69157112e-01
5.85875213e-01 -1.53530014e+00 -6.52567148e-02 3.94114137e-01
6.68509677e-02 5.87051034e-01 2.07955226e-01 -7.61409104e-01
-1.77713335e+00 -1.43191910e+00 5.23156643e-01 -3.37241918e-01
8.22393835e-01 -7.63461739e-02 -9.20621872e-01 7.95854926e-01
-4.33364928e-01 5.21062672e-01 7.44518816e-01 5.50910830e-01
-4.36667323e-01 -2.96896487e-01 -1.22887993e+00 6.14524007e-01
1.29973388e+00 -5.01745820e-01 -7.23393202e-01 4.23841327e-01
1.00150335e+00 -5.17069221e-01 -1.48106503e+00 8.63820493e-01
1.71757728e-01 -7.04070628e-01 1.12718129e+00 -5.75109303e-01
2.21948832e-01 -5.08479357e-01 -1.66608259e-01 -1.34188402e+00
-4.04119790e-01 -4.80584055e-01 -7.68253207e-01 1.24917018e+00
6.17643535e-01 -9.23439920e-01 6.30193174e-01 4.79766995e-01
1.01244196e-01 -1.18245530e+00 -6.97780728e-01 -7.17054963e-01
-4.36165690e-01 -1.41084954e-01 9.32660401e-01 1.13850355e+00
1.92827672e-01 6.43100739e-01 -2.10040674e-01 4.20359582e-01
5.49528301e-01 7.26060450e-01 6.75786793e-01 -1.31176889e+00
-3.30596000e-01 5.80067523e-02 -3.88654053e-01 -8.42381656e-01
3.67392749e-01 -8.35319579e-01 -1.36708096e-01 -1.79673624e+00
1.15644790e-01 -8.76991868e-01 -4.50894326e-01 1.01540422e+00
-4.52160388e-01 7.59967715e-02 -2.26532370e-02 1.55165374e-01
-1.32959521e+00 7.04656124e-01 1.56973922e+00 -2.77511209e-01
-3.33280772e-01 -2.39999205e-01 -9.47376192e-01 4.99914110e-01
5.57952046e-01 -9.87500884e-03 -8.74047577e-01 -2.06978768e-02
5.87872148e-01 3.69742900e-01 5.22687793e-01 -5.99780083e-01
3.67272556e-01 -3.48911911e-01 3.89108151e-01 -7.23039091e-01
5.13826132e-01 -7.94530511e-01 -1.73895503e-03 9.52202128e-04
-3.48239332e-01 -1.43807516e-01 -9.75156426e-02 1.04464781e+00
-3.01809907e-01 4.05641556e-01 1.53059959e-01 -7.45676633e-04
-9.48737860e-01 4.87054348e-01 2.14452937e-01 5.30183673e-01
1.14273798e+00 -1.76920399e-01 -7.91038752e-01 -3.01448554e-01
-8.07456076e-01 9.42088723e-01 1.99761555e-01 5.10178447e-01
8.25965881e-01 -1.55601323e+00 -4.76981580e-01 -1.35821849e-01
5.69178283e-01 5.66762388e-01 4.11741018e-01 8.04590583e-01
8.19562525e-02 2.62477309e-01 2.28455603e-01 -3.99389565e-01
-8.22940409e-01 8.06184351e-01 9.09850299e-02 -7.27054417e-01
-5.97920656e-01 5.83329499e-01 9.68952328e-02 -7.06616461e-01
2.63493508e-02 -1.31943285e-01 -2.27660149e-01 -1.40813580e-02
2.06790324e-02 3.68889719e-01 7.85615761e-03 -5.40523887e-01
-4.96589720e-01 3.94096345e-01 -3.04955930e-01 2.59485483e-01
1.22812486e+00 -1.22654252e-01 1.14798084e-01 4.96929258e-01
8.40332866e-01 -1.83640476e-02 -7.93670893e-01 -6.83209836e-01
-2.17328817e-01 -1.09922171e-01 -1.14139713e-01 -1.11540401e+00
-1.14549136e+00 7.78300911e-02 -1.20529972e-01 5.39567530e-01
1.19417465e+00 5.13583899e-01 7.17873931e-01 8.45221341e-01
6.42767072e-01 -1.23147964e+00 3.49883765e-01 3.18796337e-01
7.22514391e-01 -1.36175430e+00 6.75679743e-02 -8.48814726e-01
-8.03812861e-01 8.04991305e-01 1.02796054e+00 1.62573010e-01
5.26172340e-01 -7.90252164e-02 -2.04637572e-01 -6.85056686e-01
-8.47464859e-01 -6.12367332e-01 4.50364769e-01 6.30057395e-01
-9.38049033e-02 2.61171371e-01 1.05074674e-01 3.98600966e-01
-3.74584980e-02 -5.11895791e-02 2.84361932e-02 1.09833896e+00
-2.04812303e-01 -9.00624752e-01 -2.26764441e-01 6.83427155e-01
1.33325472e-01 1.77034382e-02 -7.08879232e-01 9.43564594e-01
-1.57722626e-02 1.18879426e+00 -4.42360044e-01 -6.62868381e-01
3.55798721e-01 -2.05681562e-01 4.30487663e-01 -4.38503057e-01
-2.62500465e-01 -3.65689248e-01 3.45810413e-01 -6.68643117e-01
-4.65082884e-01 -1.56630799e-01 -1.68029881e+00 -2.01501355e-01
-6.26356244e-01 4.02715683e-01 6.38406798e-02 1.21993995e+00
6.64078236e-01 8.63686442e-01 6.82364821e-01 -3.98621827e-01
-3.11831921e-01 -7.01064944e-01 -6.22555494e-01 5.00307620e-01
2.03908667e-01 -1.10408640e+00 -2.12761268e-01 -4.02284265e-01] | [8.88409423828125, 7.891096591949463] |
03e428c6-5856-4217-ad90-c6979f2fb427 | pix2vox-multi-scale-context-aware-3d-object | 2006.12250 | null | https://arxiv.org/abs/2006.12250v2 | https://arxiv.org/pdf/2006.12250v2.pdf | Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images | Recovering the 3D shape of an object from single or multiple images with deep neural networks has been attracting increasing attention in the past few years. Mainstream works (e.g. 3D-R2N2) use recurrent neural networks (RNNs) to sequentially fuse feature maps of input images. However, RNN-based approaches are unable to produce consistent reconstruction results when given the same input images with different orders. Moreover, RNNs may forget important features from early input images due to long-term memory loss. To address these issues, we propose a novel framework for single-view and multi-view 3D object reconstruction, named Pix2Vox++. By using a well-designed encoder-decoder, it generates a coarse 3D volume from each input image. A multi-scale context-aware fusion module is then introduced to adaptively select high-quality reconstructions for different parts from all coarse 3D volumes to obtain a fused 3D volume. To further correct the wrongly recovered parts in the fused 3D volume, a refiner is adopted to generate the final output. Experimental results on the ShapeNet, Pix3D, and Things3D benchmarks show that Pix2Vox++ performs favorably against state-of-the-art methods in terms of both accuracy and efficiency. | ['Shangchen Zhou', 'Wenxiu Sun', 'Hongxun Yao', 'Haozhe Xie', 'Shengping Zhang'] | 2020-06-22 | null | null | null | null | ['3d-object-reconstruction'] | ['computer-vision'] | [-4.98233065e-02 -3.37744802e-01 2.01331124e-01 -4.43926662e-01
-7.93258429e-01 -7.54748508e-02 3.13450068e-01 -4.32034671e-01
-4.90312912e-02 3.91594887e-01 3.48251522e-01 2.65149772e-01
2.51129624e-02 -9.46895063e-01 -9.71136153e-01 -5.57150424e-01
5.38850188e-01 6.28182411e-01 2.99883813e-01 -1.10004000e-01
3.19680609e-02 7.14225650e-01 -1.64699960e+00 3.98274481e-01
5.22348166e-01 1.22714412e+00 6.31473064e-01 2.02907726e-01
-3.92596722e-01 5.89318693e-01 -2.66962767e-01 -2.94058055e-01
4.73809332e-01 -3.26571167e-01 -5.85478902e-01 2.89470971e-01
5.09015858e-01 -6.78514600e-01 -5.25637150e-01 1.04972088e+00
6.66538119e-01 4.68308665e-02 3.89938951e-01 -6.04313791e-01
-9.71494496e-01 5.09627521e-01 -7.66578496e-01 -3.47879604e-02
1.07946478e-01 1.57338828e-01 7.19243705e-01 -1.64483678e+00
6.46491885e-01 1.46144581e+00 5.09430051e-01 5.15497744e-01
-1.19264472e+00 -5.73687732e-01 2.14716524e-01 1.26307279e-01
-1.49821067e+00 -4.27361250e-01 1.09835804e+00 -4.42431942e-02
1.10732424e+00 2.48614256e-03 6.93282604e-01 8.56106162e-01
2.81767666e-01 9.79000449e-01 1.04805899e+00 1.01728387e-01
-1.85000509e-01 -1.53175145e-01 -2.87259489e-01 8.10852289e-01
-2.13179216e-02 1.07823640e-01 -5.41107237e-01 1.78414255e-01
1.24951577e+00 5.16008019e-01 -4.10257936e-01 -4.63937581e-01
-1.28001428e+00 5.11079133e-01 8.29547465e-01 2.79275239e-01
-1.02780700e+00 1.57473296e-01 3.40965927e-01 1.44205511e-01
7.63712168e-01 -1.10869426e-02 -5.69791973e-01 1.98387444e-01
-8.84452224e-01 2.29283318e-01 2.96998501e-01 8.94353569e-01
7.70435810e-01 3.07299852e-01 -6.02613613e-02 1.01458001e+00
4.40688342e-01 6.29705667e-01 3.09276551e-01 -8.51778686e-01
7.05254853e-01 8.34436178e-01 -1.26658548e-02 -9.46211815e-01
-2.72807986e-01 -5.63534379e-01 -1.24146080e+00 3.69540006e-01
-4.15159352e-02 4.52305794e-01 -1.27434909e+00 1.26217866e+00
4.33419049e-01 1.86778709e-01 1.13464236e-01 1.28894794e+00
1.38935971e+00 8.84422243e-01 -3.10793936e-01 -8.52518231e-02
9.53368068e-01 -9.92647111e-01 -4.68914628e-01 -1.77271545e-01
-8.07794631e-02 -7.72975266e-01 8.10769260e-01 2.60985643e-01
-1.67779374e+00 -8.78944516e-01 -9.77223873e-01 -3.53769094e-01
-9.98613313e-02 1.45864934e-01 1.07184425e-01 -3.17833945e-02
-1.01947069e+00 6.69833183e-01 -9.29596424e-01 1.31629497e-01
7.60038137e-01 1.94602102e-01 -4.83417541e-01 -3.36407989e-01
-7.28711426e-01 9.28219557e-01 2.82619804e-01 4.04522657e-01
-1.01046491e+00 -8.83756697e-01 -9.63366807e-01 -4.56843749e-02
4.14104134e-01 -9.19930637e-01 1.09279025e+00 -6.81960821e-01
-1.45541596e+00 8.40800285e-01 -8.81871060e-02 -1.58365190e-01
4.36279714e-01 -2.60442644e-01 -1.76356509e-01 2.48994511e-02
1.54291600e-01 8.18780303e-01 8.99421632e-01 -1.64728749e+00
-5.27807057e-01 -6.18666291e-01 -3.06596011e-01 3.74063194e-01
3.30840379e-01 -2.25183725e-01 -7.58533180e-01 -8.03043365e-01
7.11740375e-01 -5.62848330e-01 -2.14575365e-01 7.28737488e-02
-4.54070926e-01 -1.49191663e-01 8.89700055e-01 -8.72995615e-01
6.36139214e-01 -1.91987336e+00 6.06644332e-01 1.23576233e-02
3.24131817e-01 3.66904676e-01 -3.37375313e-01 -2.12719217e-01
-9.01150107e-02 -1.63923711e-01 -3.45002383e-01 -6.82231545e-01
-2.89012015e-01 3.24258775e-01 -4.25075352e-01 4.78880465e-01
2.57540613e-01 1.21634316e+00 -6.66666448e-01 -2.20001370e-01
5.69706321e-01 8.83905172e-01 -4.69475806e-01 3.84455144e-01
-2.78320253e-01 4.89193618e-01 -3.49005461e-01 8.23801100e-01
9.36141014e-01 -5.81062615e-01 -2.26687700e-01 -5.89043140e-01
-8.83651897e-02 1.66024983e-01 -1.17151320e+00 2.09123182e+00
-6.69374406e-01 1.39539033e-01 1.07560828e-01 -8.30063701e-01
1.04369104e+00 2.66801685e-01 5.88334203e-01 -8.86983871e-01
2.93639213e-01 3.30559164e-01 -3.98627847e-01 -2.92937547e-01
5.20378470e-01 -2.35306442e-01 1.55715793e-01 5.08633971e-01
2.10256383e-01 -2.39045203e-01 -3.82883698e-01 -1.11704305e-01
6.90569520e-01 3.87466848e-01 1.87798992e-01 2.91227162e-01
6.67595863e-01 -3.36696178e-01 7.00918436e-01 3.95047933e-01
-1.62775107e-02 1.26461816e+00 -1.38946831e-01 -8.16143692e-01
-1.25774312e+00 -1.14998162e+00 1.41573563e-01 5.54788589e-01
4.45608854e-01 -5.64463530e-03 -1.91960320e-01 -7.80916393e-01
2.82790512e-02 5.19323409e-01 -5.09756207e-01 -3.44464518e-02
-8.50949347e-01 -2.83899724e-01 5.51472455e-02 7.18306899e-01
7.79723883e-01 -1.46087599e+00 -6.28809273e-01 4.62369382e-01
-2.93896288e-01 -1.05602610e+00 -5.37503123e-01 -9.96341463e-03
-1.08898413e+00 -8.41835797e-01 -1.09284711e+00 -7.79569924e-01
7.60325074e-01 6.65327609e-01 1.24884129e+00 1.73874915e-01
-7.26379512e-04 2.72158295e-01 -2.83994466e-01 -6.21745698e-02
-4.29929078e-01 -1.88896224e-01 -1.29939169e-02 1.19728237e-01
-6.88267052e-02 -8.60094726e-01 -6.38705134e-01 3.74322623e-01
-1.00216949e+00 2.99043864e-01 8.39094222e-01 8.76850188e-01
1.24776745e+00 -1.01524644e-01 4.42843467e-01 -5.79411089e-01
1.60607681e-01 -2.65946865e-01 -5.82485318e-01 3.51962507e-01
-4.86545891e-01 1.44446999e-01 6.98656499e-01 -3.45686615e-01
-1.07545877e+00 1.23614073e-01 -3.90655577e-01 -1.26474631e+00
4.19094376e-02 3.74222606e-01 -3.55620742e-01 9.68256369e-02
1.92899555e-01 7.25198507e-01 9.67151150e-02 -7.87099183e-01
3.47835600e-01 2.15428993e-01 6.60491824e-01 -1.08010009e-01
7.43107200e-01 4.55070347e-01 -2.37200826e-01 -2.63259679e-01
-9.18808162e-01 -1.56830296e-01 -6.10180199e-01 -3.32458794e-01
7.91003406e-01 -1.18902063e+00 -5.28923750e-01 6.16549253e-01
-1.40853500e+00 4.43067355e-03 -4.09559846e-01 4.78234231e-01
-5.77245891e-01 1.34649679e-01 -5.54761469e-01 -3.66129398e-01
-8.71795654e-01 -1.52378881e+00 1.31443393e+00 3.59860301e-01
2.61359036e-01 -5.19031823e-01 -2.14386895e-01 4.33770776e-01
4.07965511e-01 4.84355316e-02 7.40296662e-01 -1.20940730e-01
-1.03565085e+00 7.11505488e-02 -4.81340975e-01 5.54065526e-01
2.24914923e-01 -4.63816851e-01 -8.01850975e-01 -1.87673494e-01
1.76898569e-01 -3.72510135e-01 1.00062668e+00 6.22924209e-01
1.34600723e+00 -2.61786878e-01 -1.11595832e-01 8.10308397e-01
1.51966929e+00 -2.16533598e-02 6.68853104e-01 -3.67513485e-02
1.05739808e+00 1.46542355e-01 3.79578054e-01 4.23872977e-01
5.21016240e-01 6.07710898e-01 7.35873401e-01 6.67848811e-02
-5.19260764e-01 -3.75098497e-01 2.95774043e-01 1.20657313e+00
-1.30312905e-01 -7.00331032e-02 -6.32151902e-01 5.64838469e-01
-1.58704650e+00 -8.33505630e-01 1.72940239e-01 2.02999043e+00
6.72339261e-01 1.07681170e-01 -2.30589226e-01 -1.22095302e-01
6.60707533e-01 4.88220215e-01 -8.60473633e-01 9.35592279e-02
-2.41289869e-01 1.40436575e-01 2.24313319e-01 3.39895815e-01
-8.26883554e-01 8.30180705e-01 5.19872522e+00 8.75235021e-01
-1.24854279e+00 1.65584832e-01 7.30108380e-01 -2.60265350e-01
-5.73439300e-01 -2.89795578e-01 -6.92214012e-01 2.97660410e-01
3.60245883e-01 1.91096365e-01 4.90061760e-01 7.28912592e-01
5.52173406e-02 1.31477639e-01 -9.01606500e-01 1.39238989e+00
4.26584601e-01 -1.72114372e+00 3.68999094e-01 -1.06600016e-01
8.61870527e-01 4.77090955e-01 -1.95689965e-02 2.68803567e-01
1.48290098e-01 -9.73806679e-01 8.89783084e-01 9.68908012e-01
9.05665815e-01 -8.48542154e-01 6.81415737e-01 3.75805765e-01
-1.31957459e+00 2.48027667e-01 -5.32010913e-01 5.10992467e-01
4.53861237e-01 7.14800119e-01 -6.22299731e-01 8.92797053e-01
9.32370961e-01 1.06843424e+00 -4.36552048e-01 8.73494565e-01
-1.43402265e-02 1.04947314e-01 -2.91462779e-01 3.48759532e-01
1.67346478e-01 -1.94270954e-01 7.39294112e-01 5.05029082e-01
5.83704948e-01 2.90251583e-01 4.55840193e-02 1.26233351e+00
-4.45629835e-01 -2.31201172e-01 -6.75539076e-01 4.11455095e-01
2.74265677e-01 1.27187502e+00 -7.23017335e-01 -4.35680866e-01
-4.91857320e-01 1.11760342e+00 3.89851391e-01 1.00300238e-01
-6.12243176e-01 1.32449627e-01 4.25164998e-01 7.05611333e-02
7.62401164e-01 -7.81058669e-02 -4.25199062e-01 -1.22024083e+00
3.15877765e-01 -7.68457711e-01 1.20764650e-01 -1.20854640e+00
-1.40140545e+00 8.76625657e-01 -3.47063452e-01 -1.63721085e+00
-8.00733343e-02 -1.32263765e-01 -2.97271162e-01 9.06324148e-01
-1.52144945e+00 -1.20106244e+00 -3.87950510e-01 5.37913620e-01
8.75000596e-01 -2.69723326e-01 5.43496490e-01 3.27102989e-01
-2.67000586e-01 2.67937928e-01 -2.11686298e-01 1.63146928e-02
3.61208171e-01 -8.36598635e-01 6.91306829e-01 5.93823135e-01
1.34827107e-01 1.44415930e-01 3.42868567e-01 -9.04238045e-01
-1.66420281e+00 -1.46217036e+00 6.91541195e-01 -3.15824002e-01
-1.10955842e-01 -2.49766335e-02 -1.25542617e+00 5.52243412e-01
9.35470387e-02 6.27968371e-01 -5.35486601e-02 -5.50650954e-01
-3.07074100e-01 -2.41991550e-01 -1.18939924e+00 4.14879054e-01
1.19657183e+00 -5.23814082e-01 -5.50686836e-01 -6.99988306e-02
8.77919793e-01 -8.91256332e-01 -9.71291363e-01 7.29165792e-01
4.01866972e-01 -1.21047962e+00 1.29841053e+00 -1.28659353e-01
6.97778225e-01 -4.98839021e-01 -3.85288566e-01 -1.33517170e+00
-2.75904000e-01 -1.18132800e-01 -2.24107966e-01 1.08520484e+00
1.76498845e-01 -3.60503793e-01 6.95249259e-01 3.95925850e-01
-3.92982870e-01 -1.17541802e+00 -1.00433421e+00 -4.49433595e-01
-1.75796047e-01 -4.00827140e-01 9.18839455e-01 5.33367217e-01
-9.45273697e-01 3.53467792e-01 -5.48550963e-01 2.22751141e-01
7.12460876e-01 7.58214712e-01 7.63665974e-01 -1.00698423e+00
-2.24305782e-02 -3.99493515e-01 -3.33504230e-01 -1.40017962e+00
1.42775804e-01 -1.16846728e+00 1.05228968e-01 -1.71485150e+00
2.81752437e-01 -4.36954826e-01 -1.94017842e-01 4.38323021e-01
-1.03346698e-01 5.26986837e-01 2.93643653e-01 2.94570565e-01
-6.12494946e-01 1.14872062e+00 1.75248492e+00 -2.83140302e-01
-3.17094743e-01 5.15953079e-03 -6.28028393e-01 6.80381596e-01
4.48831916e-01 -4.76874858e-01 -1.59977630e-01 -7.43627787e-01
7.16649145e-02 4.53504890e-01 7.04425752e-01 -8.50813508e-01
1.38105944e-01 1.56754963e-02 9.40717459e-01 -1.50589764e+00
5.73412299e-01 -1.01669145e+00 3.31847429e-01 1.83660924e-01
-1.05470590e-01 2.89953142e-01 1.11390322e-01 5.95723629e-01
-2.94659108e-01 1.51420519e-01 8.68194342e-01 -4.93340373e-01
-6.71177149e-01 8.81599486e-01 2.84916073e-01 -1.57213986e-01
7.97985315e-01 -2.30249375e-01 1.18199654e-01 -3.17460239e-01
-5.60344994e-01 1.18140832e-01 4.49557096e-01 6.87046349e-01
1.38722360e+00 -1.63823676e+00 -8.99655104e-01 4.60219890e-01
-1.38782591e-01 6.65715456e-01 7.16357172e-01 5.92945814e-01
-2.94671863e-01 2.07519501e-01 -2.63776153e-01 -8.31265628e-01
-1.03031647e+00 4.68633443e-01 5.34832656e-01 -2.48769686e-01
-1.09749794e+00 9.03180957e-01 2.95536131e-01 -6.99262440e-01
1.78664312e-01 -5.01333714e-01 -6.62552714e-02 -2.06595331e-01
5.86000502e-01 1.40878260e-01 2.72131234e-01 -9.16241586e-01
-3.15281868e-01 8.14556003e-01 -2.32711643e-01 4.25960198e-02
1.85302389e+00 -2.17101291e-01 -1.03104532e-01 3.60596776e-01
1.43214965e+00 -3.56830031e-01 -1.50744772e+00 -7.59635568e-01
-5.67352772e-01 -5.51270008e-01 2.72372574e-01 -7.01223075e-01
-1.86779785e+00 7.03133643e-01 5.73222518e-01 -2.74898589e-01
1.28107321e+00 1.55686691e-01 1.20055962e+00 1.29984066e-01
4.52632934e-01 -7.55949080e-01 1.70778930e-01 5.46572685e-01
1.41875160e+00 -1.23108149e+00 2.38275573e-01 1.61807872e-02
-7.04438925e-01 1.01410592e+00 8.73473823e-01 -3.91216695e-01
7.91982293e-01 -3.67052830e-03 -4.75865640e-02 -4.40490603e-01
-7.37252653e-01 -1.25368731e-02 4.92080063e-01 2.77243733e-01
4.47604712e-03 -8.40869695e-02 2.88815916e-01 6.33566618e-01
-1.54428501e-02 -2.41002776e-02 3.10882956e-01 7.16529906e-01
-1.61564261e-01 -8.19736004e-01 -4.83585924e-01 6.07223332e-01
-2.09702179e-01 8.91869068e-02 -8.31886232e-02 5.08909225e-01
9.79937166e-02 3.85261148e-01 1.26715124e-01 -5.94314098e-01
6.06334031e-01 -2.04305053e-01 5.94962418e-01 -4.58982557e-01
-6.66340590e-01 3.06094944e-01 -4.21507031e-01 -8.08222115e-01
-6.51535213e-01 -6.12181246e-01 -1.39948022e+00 -2.66040206e-01
-2.40880385e-01 -3.73215348e-01 4.37672496e-01 9.21607077e-01
5.82756400e-01 6.63845181e-01 8.23541820e-01 -1.37649345e+00
-4.64645892e-01 -8.48016143e-01 -4.31840837e-01 2.32337460e-01
5.23205161e-01 -7.28719354e-01 -1.94403809e-02 -8.16878527e-02] | [8.371454238891602, -3.452169895172119] |
4a99d120-f13c-470d-9fcf-d52cd62a647b | thermal-image-super-resolution-using-second | 2108.00094 | null | https://arxiv.org/abs/2108.00094v1 | https://arxiv.org/pdf/2108.00094v1.pdf | Thermal Image Super-Resolution Using Second-Order Channel Attention with Varying Receptive Fields | Thermal images model the long-infrared range of the electromagnetic spectrum and provide meaningful information even when there is no visible illumination. Yet, unlike imagery that represents radiation from the visible continuum, infrared images are inherently low-resolution due to hardware constraints. The restoration of thermal images is critical for applications that involve safety, search and rescue, and military operations. In this paper, we introduce a system to efficiently reconstruct thermal images. Specifically, we explore how to effectively attend to contrasting receptive fields (RFs) where increasing the RFs of a network can be computationally expensive. For this purpose, we introduce a deep attention to varying receptive fields network (AVRFN). We supply a gated convolutional layer with higher-order information extracted from disparate RFs, whereby an RF is parameterized by a dilation rate. In this way, the dilation rate can be tuned to use fewer parameters thus increasing the efficacy of AVRFN. Our experimental results show an improvement over the state of the art when compared against competing thermal image super-resolution methods. | ['William J. Beksi', 'Nolan B. Gutierrez'] | 2021-07-30 | null | null | null | null | ['deep-attention', 'deep-attention'] | ['computer-vision', 'natural-language-processing'] | [ 8.90610576e-01 -3.00128907e-01 2.89354295e-01 -3.04611862e-01
-4.00058091e-01 -5.31514406e-01 4.54677194e-01 -5.45879722e-01
-5.03199399e-01 5.52169800e-01 1.66816562e-01 -2.13168308e-01
-6.07247688e-02 -9.09640551e-01 -6.44869387e-01 -1.06677580e+00
1.94518715e-01 -3.31528306e-01 1.46527961e-01 -3.88381898e-01
3.69901687e-01 6.66527331e-01 -1.61666739e+00 5.96012771e-01
9.49711025e-01 1.05363047e+00 5.17410696e-01 5.40965080e-01
1.80641249e-01 5.96736133e-01 -4.87415761e-01 4.44739819e-01
5.95155716e-01 -2.44781032e-01 -7.62842417e-01 -3.30591530e-01
6.67470276e-01 -6.57538593e-01 -2.73529112e-01 9.01683152e-01
4.52409178e-01 5.21751583e-01 3.99268836e-01 -5.92760980e-01
-9.11222696e-01 6.79562911e-02 -7.08300889e-01 4.92981285e-01
1.18715025e-01 5.05267009e-02 5.60419321e-01 -4.78011668e-01
3.94417942e-01 1.16644180e+00 3.61713290e-01 5.44289291e-01
-1.35843766e+00 -4.68919992e-01 1.99967131e-01 4.35379706e-02
-1.17702138e+00 -3.35227937e-01 6.09605551e-01 -1.49420783e-01
8.55841160e-01 3.63266051e-01 3.76339018e-01 1.15316498e+00
3.13838899e-01 2.94772442e-03 1.32951748e+00 -3.39798778e-01
3.25678319e-01 -1.38035372e-01 -3.03714722e-01 3.03576887e-01
5.71282655e-02 3.40096146e-01 -5.82910419e-01 -1.46898143e-02
1.34483171e+00 -1.06220871e-01 -5.84573269e-01 1.16662785e-01
-9.23369765e-01 4.34747636e-01 8.74460101e-01 3.22694421e-01
-4.04567629e-01 4.07534510e-01 -1.36153802e-01 1.52794674e-01
6.52627110e-01 6.04808271e-01 -2.44114295e-01 4.14552033e-01
-8.00032914e-01 -1.41615272e-01 -7.74061354e-03 3.11897755e-01
8.54119062e-01 1.63546905e-01 -3.28140408e-02 1.01504672e+00
-2.70144083e-02 3.82487357e-01 1.82680815e-01 -1.17290497e+00
1.58913568e-01 3.30188036e-01 2.43736431e-01 -5.88076949e-01
-4.11151290e-01 -4.07639652e-01 -1.10070074e+00 7.00787842e-01
1.11003496e-01 -9.11912248e-02 -1.10992563e+00 1.62226903e+00
2.53339529e-01 2.08582059e-01 7.60329664e-02 1.39597189e+00
6.59707308e-01 7.91328609e-01 6.49237959e-03 -1.33960247e-01
1.40024853e+00 -4.88171786e-01 -4.98358250e-01 -7.02168763e-01
1.35292336e-01 -7.05104649e-01 9.57922995e-01 2.66529948e-01
-8.25188458e-01 -7.53042758e-01 -9.35213089e-01 -1.88657284e-01
-1.53986976e-01 3.84177044e-02 5.68033040e-01 4.26406801e-01
-1.40815270e+00 6.64162159e-01 -8.13033104e-01 -3.51654559e-01
3.95745605e-01 3.31558257e-01 -2.48738050e-01 -1.46994486e-01
-1.23588622e+00 8.08017910e-01 3.67338240e-01 5.17865479e-01
-4.72569793e-01 -7.76801705e-01 -6.73302591e-01 -1.38239628e-02
1.37959942e-01 -8.73564422e-01 7.06336260e-01 -1.07348514e+00
-1.42762232e+00 5.11310399e-01 -5.83341122e-02 -2.15228155e-01
2.03668937e-01 -2.40155444e-01 -2.60462701e-01 4.98560876e-01
-2.49877706e-01 5.40470898e-01 1.06610930e+00 -1.42007899e+00
-3.74724537e-01 -3.59681785e-01 4.66801584e-01 4.35200632e-01
-2.88678050e-01 1.61688894e-01 -7.04145730e-02 -4.20481265e-01
2.11362407e-01 -9.61658835e-01 -3.01669806e-01 1.18960634e-01
-9.54564959e-02 2.93134391e-01 7.51133800e-01 -5.56401432e-01
8.24435174e-01 -2.10386348e+00 1.05656318e-01 5.29858097e-03
8.03123116e-02 1.76567003e-01 -2.66220778e-01 1.26263082e-01
-1.76759988e-01 3.24143976e-01 -3.80562603e-01 7.48719946e-02
-5.37006855e-01 -1.67934853e-03 -2.63480484e-01 5.48857987e-01
3.03787619e-01 6.19471312e-01 -5.45451462e-01 -1.34095192e-01
4.56016123e-01 9.51436341e-01 -3.15751582e-01 1.40856905e-02
-1.13454886e-01 7.90483117e-01 -5.75593054e-01 3.17392111e-01
9.89205062e-01 -1.43495977e-01 2.87010781e-02 -6.33576334e-01
-5.48612714e-01 8.25920478e-02 -7.75212407e-01 1.55874467e+00
-7.73313522e-01 7.11696327e-01 2.62533367e-01 -7.82411039e-01
9.26339865e-01 2.90724798e-03 4.42914724e-01 -1.11802173e+00
2.71404646e-02 -8.22567046e-02 -3.15720528e-01 -3.21520627e-01
6.85819745e-01 -2.79571682e-01 2.64368802e-01 4.51458544e-01
-5.09005606e-01 8.18455517e-02 -3.80465746e-01 -5.77747151e-02
7.96458840e-01 3.68642896e-01 -2.35828087e-01 -2.55727947e-01
3.15807581e-01 -2.56853819e-01 3.26495677e-01 8.34443331e-01
1.42184258e-01 8.15103412e-01 2.66789701e-02 -6.71228945e-01
-1.02945185e+00 -9.01274741e-01 -2.20318630e-01 1.27016580e+00
3.65449727e-01 1.85230821e-01 -6.48218632e-01 -3.60079743e-02
-4.32197273e-01 4.25962776e-01 -6.57688022e-01 -1.53202832e-01
-7.96868801e-01 -8.92637491e-01 1.60240844e-01 5.60250163e-01
9.57799852e-01 -1.02484751e+00 -1.12629271e+00 -1.16011396e-01
-4.40489680e-01 -1.37576473e+00 -2.47499913e-01 9.50738266e-02
-8.60468328e-01 -7.56862164e-01 -5.41224837e-01 -4.77826297e-01
6.92978799e-01 7.41789162e-01 8.98494840e-01 3.71318124e-02
-7.06201255e-01 5.55877760e-02 -2.94528157e-01 -4.60678488e-02
-8.22742656e-02 4.56577307e-03 -9.85950977e-02 1.99325196e-02
-5.43156266e-02 -5.83661735e-01 -1.10223162e+00 1.66030213e-01
-1.21354795e+00 2.29425445e-01 6.91889644e-01 5.68336844e-01
4.97729450e-01 2.82997102e-01 1.07916847e-01 -6.29835486e-01
2.85888016e-01 -3.83748598e-02 -7.33190477e-01 2.46219799e-01
-9.89900380e-02 3.00731182e-01 6.88936889e-01 -2.24470809e-01
-1.58918250e+00 7.66125023e-02 1.81702062e-01 -2.47657672e-01
-2.37900004e-01 2.00119436e-01 1.97826371e-01 -4.80247676e-01
8.95467997e-01 1.89352959e-01 -3.49849463e-01 -4.06958938e-01
2.93323934e-01 5.90779781e-01 7.08795786e-01 -4.50936884e-01
8.97018373e-01 9.28105175e-01 1.49620652e-01 -1.07879627e+00
-8.89111221e-01 -3.08977991e-01 -6.33934915e-01 -4.40918148e-01
9.83716071e-01 -8.08994174e-01 -7.06198514e-01 1.45921841e-01
-8.90127599e-01 -4.28209722e-01 1.69888884e-01 4.92902070e-01
-3.30771834e-01 2.59080708e-01 -4.40782338e-01 -9.80758607e-01
-4.38067317e-01 -8.19525361e-01 1.20136535e+00 5.01781583e-01
1.99745148e-01 -7.51685202e-01 -8.95459428e-02 4.67014402e-01
8.35941911e-01 5.96444011e-01 7.27174163e-01 4.99769777e-01
-8.56596112e-01 3.40676427e-01 -5.57587922e-01 2.81668574e-01
1.38210893e-01 -3.83165292e-02 -1.37441647e+00 -3.91929984e-01
1.14391416e-01 -2.43385762e-01 1.30813217e+00 6.96873903e-01
1.37741482e+00 -2.26874530e-01 -5.57990484e-02 1.10475290e+00
1.80527472e+00 3.10678650e-02 9.65016603e-01 5.51223218e-01
7.03344226e-01 8.00636351e-01 4.62425917e-01 3.10267717e-01
-1.15033910e-01 5.66848695e-01 6.92607343e-01 -5.80160081e-01
1.50123220e-02 3.28603655e-01 2.23034292e-01 -1.17751598e-01
-6.87999785e-01 -1.11357741e-01 -6.66082382e-01 2.09135935e-01
-1.55927753e+00 -1.10796976e+00 3.31148095e-02 2.35497952e+00
5.85044444e-01 -1.39929995e-01 -3.59172076e-01 -1.66917682e-01
7.03361154e-01 4.94749278e-01 -6.11624837e-01 -4.40832078e-01
-1.09998934e-01 4.48926777e-01 7.70273089e-01 5.34701347e-01
-1.01263988e+00 7.94030905e-01 6.41721153e+00 3.97514969e-01
-1.26969755e+00 -1.88225940e-01 6.14149868e-01 -2.73495406e-01
-4.11908686e-01 -6.45513460e-02 -2.54339635e-01 7.90654793e-02
8.29488277e-01 3.19716662e-01 8.90791714e-01 2.12807879e-01
4.53920811e-01 -3.59552860e-01 -7.02488124e-01 8.90398622e-01
-2.46008560e-01 -9.85766411e-01 -1.58648506e-01 1.24337293e-01
6.17745578e-01 1.24725223e-01 4.43933666e-01 -3.02344501e-01
1.06229097e-01 -1.27534962e+00 3.55395913e-01 5.91222167e-01
1.09096241e+00 -9.31075096e-01 4.81175423e-01 2.23113999e-01
-1.28794897e+00 -1.95905194e-01 -7.43951082e-01 1.65765405e-01
-7.82469288e-02 5.64162254e-01 -2.32019231e-01 7.50304282e-01
1.03034246e+00 3.58134389e-01 -3.16886723e-01 5.52070498e-01
3.40152020e-03 2.84543693e-01 -2.71713763e-01 4.56947058e-01
1.72486112e-01 -4.30685848e-01 6.19431771e-02 9.66770828e-01
2.63860941e-01 4.83554572e-01 -5.63484430e-02 1.15329301e+00
3.34599018e-02 -4.45560038e-01 -4.64052886e-01 1.92036718e-01
3.40952516e-01 1.45488667e+00 -6.71128988e-01 1.49873719e-01
-3.12954068e-01 1.17734325e+00 1.51580796e-01 7.45908380e-01
-7.64414251e-01 -1.45646259e-01 7.15036154e-01 7.85058439e-02
8.61031413e-02 -2.77477622e-01 -1.79381445e-01 -9.26332057e-01
6.28647283e-02 -4.52874303e-01 -4.49850922e-03 -1.12099361e+00
-1.00430858e+00 8.29856396e-01 -4.15271707e-02 -1.10444510e+00
1.20116964e-01 -5.12626350e-01 -3.26755136e-01 1.37693131e+00
-1.92680466e+00 -1.05500245e+00 -8.53685319e-01 5.00456989e-01
3.07395607e-01 5.69226861e-01 7.01910615e-01 -2.35270932e-02
-4.45204794e-01 8.00905898e-02 1.96458861e-01 -9.56959352e-02
7.75359809e-01 -9.00438845e-01 5.17395258e-01 8.60975385e-01
-3.90187263e-01 7.55102932e-01 6.58430636e-01 -4.42469835e-01
-1.32783294e+00 -1.11956561e+00 1.40422821e-01 -1.37579679e-01
2.60261327e-01 -3.10848653e-01 -1.02527916e+00 3.20222348e-01
1.01367094e-01 3.44442606e-01 5.07108331e-01 -1.59531102e-01
-5.48417449e-01 -3.28044832e-01 -1.20066726e+00 4.26000267e-01
9.35418487e-01 -7.76063919e-01 -1.37004241e-01 1.16839625e-01
6.05302572e-01 -2.45881468e-01 -6.96647167e-01 3.77609432e-01
7.57910550e-01 -1.31074202e+00 1.30708921e+00 -1.22882701e-01
4.36882854e-01 -5.29251397e-01 -5.25352471e-02 -1.25837314e+00
-6.68528318e-01 -3.31602663e-01 2.34457761e-01 7.58015513e-01
3.01363897e-02 -6.53346121e-01 5.03731847e-01 6.56422198e-01
-3.17909606e-02 -3.81355554e-01 -8.06431293e-01 -5.82157731e-01
-1.26816720e-01 -5.09812450e-03 2.94521064e-01 7.83599973e-01
-4.90415335e-01 9.21913534e-02 -3.89363021e-01 5.68541825e-01
8.20544720e-01 1.85619146e-01 5.04082404e-02 -1.21271193e+00
-2.26888672e-01 -2.11705685e-01 1.83075462e-02 -7.97326446e-01
-1.15021929e-01 -3.84829760e-01 2.40553334e-01 -1.68119848e+00
3.25733840e-01 -3.41164321e-01 -3.93221200e-01 4.75899637e-01
-2.99538732e-01 5.95661700e-01 2.66547371e-02 3.21806759e-01
-1.03905059e-01 3.49636436e-01 1.34126759e+00 2.46389117e-02
-2.18670070e-01 -3.73619914e-01 -8.21552515e-01 4.84281301e-01
1.13110149e+00 -9.42650959e-02 -5.40926874e-01 -8.73963058e-01
2.66138554e-01 -5.15262485e-02 6.05018318e-01 -8.22777212e-01
1.72382772e-01 -4.04182434e-01 7.61735141e-01 -3.16197246e-01
4.33635473e-01 -6.81041896e-01 2.24967003e-01 1.82127878e-01
-4.29323882e-01 -2.93100208e-01 2.95607150e-01 5.18754542e-01
1.59397289e-01 1.50945365e-01 1.11708891e+00 -4.09354329e-01
-6.42844737e-01 1.18080124e-01 -3.85840088e-01 -3.38464797e-01
7.04124510e-01 -2.77885467e-01 -7.77653635e-01 -1.62288412e-01
-1.79249376e-01 -4.74141072e-03 7.00549960e-01 3.86905760e-01
7.25274205e-01 -9.48372781e-01 -6.46423042e-01 1.32272229e-01
-3.16074975e-02 1.46781117e-01 7.25140750e-01 5.19932091e-01
-6.72998846e-01 1.88009620e-01 -4.58157778e-01 -4.63327527e-01
-1.21603215e+00 4.16387886e-01 6.46083176e-01 1.03550769e-01
-7.47729599e-01 7.89097905e-01 6.24804199e-01 -1.65666044e-01
-1.44194722e-01 -3.55283499e-01 -3.88589978e-01 -3.61907661e-01
8.30478549e-01 2.34661624e-01 9.36752483e-02 -5.29584110e-01
-4.23178643e-01 8.78167629e-01 1.18722720e-02 -1.35980800e-01
1.40080488e+00 -3.67016256e-01 -3.49117339e-01 6.85569495e-02
9.49837387e-01 -4.40471262e-01 -1.59738111e+00 -1.13981433e-01
-4.90454346e-01 -6.41571045e-01 6.52292907e-01 -7.53217816e-01
-1.11857784e+00 7.65370965e-01 9.02428508e-01 1.34064749e-01
1.71598101e+00 -1.64581850e-01 4.14588451e-01 2.17250511e-01
4.14323807e-01 -1.15790999e+00 3.20257321e-02 2.52835065e-01
7.34327674e-01 -1.08112240e+00 1.07426390e-01 -4.31111664e-01
-5.59094429e-01 1.26123798e+00 6.13374174e-01 -2.88179354e-03
1.80857345e-01 4.11518186e-01 1.57603279e-01 2.02163793e-02
-6.68599367e-01 -3.06544870e-01 2.24292755e-01 6.72783017e-01
5.58839798e-01 -2.47014359e-01 3.42953205e-02 -1.89680859e-01
2.67339568e-03 -8.82362425e-02 5.51463604e-01 9.09672260e-01
-7.33589113e-01 -6.41252816e-01 -6.55674458e-01 2.51195669e-01
-4.77389425e-01 -2.84114599e-01 -2.62286961e-01 2.17599303e-01
6.44995645e-02 1.17959917e+00 1.06770217e-01 -3.26975167e-01
3.00821592e-03 -3.86434764e-01 6.39021814e-01 -3.72177690e-01
-4.64534372e-01 1.40713409e-01 -1.09929107e-01 -8.50471616e-01
-7.99809873e-01 -1.68158785e-01 -1.11913860e+00 -2.56950527e-01
-2.60491490e-01 -2.88123965e-01 9.40335870e-01 7.53796697e-01
1.73533529e-01 8.48461330e-01 8.88341784e-01 -1.13761342e+00
-1.84584185e-01 -8.06789517e-01 -4.99626726e-01 -1.95441563e-02
6.57306910e-01 -3.40672195e-01 -3.67849857e-01 5.23565002e-02] | [10.554356575012207, -2.263338088989258] |
f1440878-8d75-411f-b271-68c6e318cc1f | category-level-6d-object-pose-estimation-in | 2206.15436 | null | https://arxiv.org/abs/2206.15436v1 | https://arxiv.org/pdf/2206.15436v1.pdf | Category-Level 6D Object Pose Estimation in the Wild: A Semi-Supervised Learning Approach and A New Dataset | 6D object pose estimation is one of the fundamental problems in computer vision and robotics research. While a lot of recent efforts have been made on generalizing pose estimation to novel object instances within the same category, namely category-level 6D pose estimation, it is still restricted in constrained environments given the limited number of annotated data. In this paper, we collect Wild6D, a new unlabeled RGBD object video dataset with diverse instances and backgrounds. We utilize this data to generalize category-level 6D object pose estimation in the wild with semi-supervised learning. We propose a new model, called Rendering for Pose estimation network RePoNet, that is jointly trained using the free ground-truths with the synthetic data, and a silhouette matching objective function on the real-world data. Without using any 3D annotations on real data, our method outperforms state-of-the-art methods on the previous dataset and our Wild6D test set (with manual annotations for evaluation) by a large margin. Project page with Wild6D data: https://oasisyang.github.io/semi-pose . | ['Xiaolong Wang', 'Yang Fu'] | 2022-06-30 | null | null | null | null | ['6d-pose-estimation-1', '6d-pose-estimation'] | ['computer-vision', 'computer-vision'] | [-3.41889784e-02 1.71593219e-01 -1.79182976e-01 -5.53017020e-01
-8.38386774e-01 -6.25562251e-01 4.33709204e-01 -3.39395881e-01
-4.71134067e-01 3.34475756e-01 5.80806434e-02 8.38233009e-02
2.59737611e-01 -3.89007747e-01 -1.08123088e+00 -5.26434481e-01
2.51933262e-02 9.49942887e-01 6.20774329e-01 -3.87878865e-02
1.14521384e-01 6.07792795e-01 -1.46223223e+00 -1.55122548e-01
5.50360501e-01 1.29996216e+00 2.97854990e-01 4.55568373e-01
9.80420858e-02 3.42539549e-01 -4.18052047e-01 -2.88298696e-01
8.73226523e-01 -1.96148604e-02 -6.29420042e-01 5.36018252e-01
9.88007426e-01 -6.78053379e-01 -4.59770143e-01 1.01159501e+00
6.54596508e-01 -8.01919103e-02 5.47242284e-01 -1.62011671e+00
-3.31537157e-01 5.40612936e-02 -7.15294242e-01 -2.14924321e-01
5.54473162e-01 3.61186892e-01 6.70848906e-01 -1.15371406e+00
8.40132236e-01 1.36500371e+00 6.69076264e-01 7.17948377e-01
-1.05342448e+00 -6.98789656e-01 3.09498191e-01 4.38118875e-02
-1.40127194e+00 -1.23057932e-01 9.07528937e-01 -5.85396051e-01
7.82152593e-01 -3.09195463e-03 8.16186547e-01 1.26021445e+00
-1.87450364e-01 9.15574491e-01 1.02709448e+00 -2.38497019e-01
2.06447095e-01 -1.61259443e-01 -1.37007684e-01 6.51550174e-01
3.89161199e-01 8.15717652e-02 -4.99862880e-01 6.12603016e-02
9.18936968e-01 1.29948169e-01 -3.37502539e-01 -1.45473421e+00
-1.54297328e+00 4.29019660e-01 6.16154432e-01 -3.95944238e-01
-2.27491394e-01 1.55826390e-01 2.25484967e-01 1.46504426e-02
5.89160919e-01 3.06554556e-01 -7.50654519e-01 -3.95702198e-03
-3.62365246e-01 5.11364996e-01 7.61313438e-01 1.48777318e+00
7.23589361e-01 -1.79325968e-01 1.84231605e-02 4.61229861e-01
6.11255109e-01 8.53059769e-01 1.32032499e-01 -1.12707043e+00
7.48112082e-01 7.47498333e-01 4.73012000e-01 -6.79726422e-01
-4.88013387e-01 -4.10631925e-01 -4.09838647e-01 4.63847637e-01
7.47877359e-01 7.77416229e-02 -1.13650024e+00 1.47069418e+00
8.05529594e-01 2.19283000e-01 -2.07674012e-01 1.34941792e+00
1.06215072e+00 3.69890362e-01 -4.14893895e-01 6.39914051e-02
9.39091146e-01 -1.13434327e+00 -3.27370912e-01 -3.86671066e-01
4.36656862e-01 -6.97394550e-01 1.08334386e+00 3.20635259e-01
-6.98958516e-01 -4.59862292e-01 -1.08070600e+00 -1.37311533e-01
-2.29965344e-01 1.37288973e-01 6.20738626e-01 3.57787699e-01
-6.97533369e-01 2.89810538e-01 -9.12589192e-01 -5.74290574e-01
5.85495472e-01 3.29003781e-01 -6.97811425e-01 -3.30931604e-01
-6.04037225e-01 1.10723305e+00 4.58315372e-01 1.45201147e-01
-1.17712927e+00 -6.55216336e-01 -9.47459698e-01 -6.95443928e-01
9.25977945e-01 -6.38673127e-01 1.39771116e+00 -2.75788039e-01
-1.35948205e+00 1.34464943e+00 4.91686672e-01 -5.72190024e-02
1.05958378e+00 -5.73741019e-01 2.57911116e-01 -7.46829286e-02
1.23393700e-01 8.41394603e-01 7.10512280e-01 -1.51715124e+00
-4.09298629e-01 -9.20444250e-01 2.77544558e-01 4.07772809e-01
1.37488663e-01 -3.63878787e-01 -9.96435285e-01 -4.79394704e-01
6.07541025e-01 -1.37631965e+00 -2.14127004e-01 6.53744459e-01
-4.60033506e-01 -2.81122953e-01 1.00495088e+00 -3.84490967e-01
2.27318004e-01 -2.02176261e+00 3.82792741e-01 -1.66935876e-01
1.72789603e-01 1.37763381e-01 -1.98187962e-01 2.88012228e-03
1.77618086e-01 -2.74179161e-01 -9.10329968e-02 -6.41471148e-01
1.78608090e-01 2.40264833e-01 -1.06513858e-01 8.28152716e-01
2.45434001e-01 9.77895081e-01 -1.05375040e+00 -5.65898180e-01
3.51058841e-01 4.02981371e-01 -5.93627691e-01 5.17341912e-01
-5.23195207e-01 6.81851804e-01 -5.10626078e-01 1.01876545e+00
9.32866812e-01 -1.50695145e-01 -2.74903804e-01 -5.68891644e-01
1.43212795e-01 3.59124132e-02 -1.47902918e+00 2.47194552e+00
4.14388860e-03 2.72025973e-01 -9.71152559e-02 -6.23979688e-01
8.75614583e-01 -5.50046004e-02 6.15861416e-01 -2.23309964e-01
2.20808014e-01 2.89893150e-01 -1.84034571e-01 -5.00130713e-01
2.52867192e-01 1.23726621e-01 -1.77214041e-01 1.24359675e-01
3.53597909e-01 -7.86437213e-01 -3.39504369e-02 -3.39881331e-03
9.80684757e-01 1.00224447e+00 1.65477455e-01 5.58533072e-02
-3.13306004e-02 1.78767532e-01 5.97923756e-01 5.30958593e-01
-5.02336979e-01 1.15896404e+00 1.29385591e-01 -4.53758448e-01
-1.21914101e+00 -1.16746438e+00 -2.48899281e-01 7.31334746e-01
6.59413934e-01 -2.62935638e-01 -5.53329051e-01 -9.25875783e-01
3.88016343e-01 2.71207601e-01 -6.09721184e-01 1.47137180e-01
-5.52509129e-01 -5.41822731e-01 2.25268513e-01 7.32707620e-01
6.51649714e-01 -7.62092113e-01 -7.24512517e-01 -4.60447669e-02
8.03313870e-03 -1.47680473e+00 -3.55440557e-01 2.69484997e-01
-9.03228343e-01 -1.21752810e+00 -8.61482441e-01 -5.49191654e-01
5.79184771e-01 3.15048188e-01 1.09447491e+00 -3.51268113e-01
-3.34032059e-01 4.63164061e-01 -4.21770811e-01 -6.57638788e-01
2.80865282e-02 -2.46364586e-02 2.64115661e-01 -2.37982884e-01
3.21401954e-01 -3.92760605e-01 -6.37122929e-01 6.39102638e-01
-4.32843745e-01 2.31631637e-01 7.05510914e-01 5.43374836e-01
9.28296685e-01 -6.06048703e-01 9.77939293e-02 -5.61420500e-01
-1.99753657e-01 -7.05462843e-02 -7.09815085e-01 8.36980622e-03
-2.35483840e-01 -9.20610055e-02 -1.43391222e-01 -6.46236777e-01
-8.14263642e-01 4.77793872e-01 1.62228309e-02 -1.02533209e+00
-3.38358730e-01 -4.56540994e-02 -7.06869066e-01 -2.73301393e-01
7.15454757e-01 -2.21978828e-01 7.36597627e-02 -8.28969955e-01
2.76630372e-01 4.69493717e-01 6.00597739e-01 -5.33899784e-01
1.17345822e+00 4.82091248e-01 1.02592260e-01 -3.73771340e-01
-1.25202155e+00 -5.86580038e-01 -1.03141034e+00 -3.67929965e-01
9.07827675e-01 -1.11568701e+00 -6.20902300e-01 7.12798476e-01
-1.14803088e+00 -4.54356104e-01 -4.24125850e-01 7.87010849e-01
-8.71637404e-01 7.95427710e-02 -2.51962066e-01 -6.12274766e-01
7.17544332e-02 -1.22228193e+00 1.69260371e+00 -1.21942066e-01
2.60626599e-02 -2.89673060e-01 -5.69571629e-02 5.99219263e-01
-1.82419986e-01 8.01055074e-01 1.60104588e-01 -5.30315638e-01
-9.71417427e-01 -4.36743945e-01 -2.62253910e-01 4.50821459e-01
8.82453844e-03 -2.58721113e-01 -8.79929006e-01 -2.19068617e-01
1.96074843e-02 -8.03694963e-01 6.43106461e-01 9.46728811e-02
1.16813123e+00 1.42865628e-01 -2.25770622e-01 8.85097384e-01
1.31901813e+00 -1.96247533e-01 2.15174749e-01 3.24643493e-01
1.15346301e+00 4.28709418e-01 1.10694015e+00 3.54545504e-01
4.24340218e-01 9.93996680e-01 1.13220453e+00 1.41751260e-01
-2.67902136e-01 -4.60723519e-01 1.17566474e-01 5.64312577e-01
-3.63677025e-01 -2.02292040e-01 -1.19511950e+00 2.51062572e-01
-1.91340566e+00 -3.94742161e-01 -9.70729589e-02 2.11584473e+00
6.42522395e-01 3.77228260e-01 1.51358604e-01 -7.25208921e-03
6.69251919e-01 1.30273521e-01 -1.02689826e+00 6.83243811e-01
-1.73637737e-02 -3.87821883e-01 6.99626267e-01 2.14794323e-01
-1.23073387e+00 9.31115627e-01 4.95654106e+00 5.24766803e-01
-9.65895355e-01 1.65341392e-01 1.80049583e-01 -1.33615464e-01
8.28394741e-02 -4.97765578e-02 -9.24455106e-01 1.13843977e-01
6.64726719e-02 2.69389361e-01 7.95330182e-02 1.20642436e+00
-1.44866213e-01 -1.14380419e-01 -1.41948080e+00 1.29087269e+00
4.43353355e-01 -9.94541049e-01 -1.19706653e-01 3.67995314e-02
7.70407557e-01 3.08918566e-01 -9.16926637e-02 2.19886482e-01
9.11017060e-02 -6.78975046e-01 1.08871329e+00 3.74580801e-01
9.13555801e-01 -3.73629540e-01 7.39735007e-01 6.31235838e-01
-9.94371712e-01 1.40139356e-01 -3.43905121e-01 -9.63881016e-02
1.71688423e-01 3.48147899e-01 -9.07421172e-01 4.23153937e-01
1.01450908e+00 9.98917580e-01 -7.69602001e-01 1.26011992e+00
-3.57005179e-01 1.39624387e-01 -5.60406387e-01 3.60543877e-02
-4.20604311e-02 -7.07777366e-02 7.87572205e-01 7.29567885e-01
1.81862906e-01 3.73450108e-02 4.60338354e-01 6.77616537e-01
-1.00000024e-01 -2.53564984e-01 -5.70541203e-01 3.28224361e-01
3.13542247e-01 1.15281177e+00 -7.30624795e-01 -3.93063463e-02
-2.13014796e-01 9.34511244e-01 2.15495557e-01 2.03874052e-01
-8.00611556e-01 1.23644266e-02 5.86713612e-01 2.93170542e-01
1.95787698e-01 -5.03773928e-01 -7.31452107e-02 -1.43383229e+00
3.17318112e-01 -5.73334157e-01 1.06804520e-01 -1.13880992e+00
-1.41042733e+00 3.42924476e-01 4.40642357e-01 -1.71839464e+00
-7.84049928e-02 -1.00535107e+00 2.53646821e-03 5.45987964e-01
-1.30531394e+00 -1.44347882e+00 -7.91959405e-01 4.29879516e-01
6.95877671e-01 9.52211954e-03 5.61302006e-01 7.04851225e-02
-1.92535207e-01 3.58902901e-01 -3.09494406e-01 3.94666046e-01
9.27608848e-01 -1.24673724e+00 3.75353694e-01 4.77450937e-01
8.17709789e-02 2.19299912e-01 7.27693021e-01 -6.00336492e-01
-1.88955486e+00 -1.30811656e+00 3.08347970e-01 -1.03619909e+00
4.53518003e-01 -9.26251113e-01 -6.35133862e-01 8.08498263e-01
-3.32755476e-01 6.38559461e-01 1.86857283e-01 -1.54766023e-01
-3.65800470e-01 -1.17404282e-01 -1.18681717e+00 4.55454409e-01
1.90283966e+00 -2.09768251e-01 -6.66781485e-01 5.17096341e-01
1.12050295e+00 -1.21831322e+00 -9.67965722e-01 8.88003349e-01
5.50509393e-01 -6.97401464e-01 1.14631009e+00 -4.38347429e-01
2.30585113e-01 -7.73519456e-01 -6.39263868e-01 -1.08524668e+00
1.35223269e-01 -2.86272049e-01 -3.96473169e-01 1.01366508e+00
1.06728069e-01 -2.43557900e-01 1.06735313e+00 5.29827535e-01
-2.97672331e-01 -8.02084506e-01 -9.55116928e-01 -1.11531687e+00
-2.31106356e-01 -6.99684680e-01 4.98468965e-01 5.96659601e-01
-6.85824573e-01 3.67403775e-01 -3.48986268e-01 2.72428751e-01
1.02305174e+00 3.58622044e-01 1.54402637e+00 -1.29266357e+00
-2.43199900e-01 2.72987448e-02 -1.05166042e+00 -1.47279370e+00
1.64276034e-01 -7.50969589e-01 3.38098764e-01 -1.57269681e+00
2.27494255e-01 -5.28070629e-01 1.18499987e-01 5.70717931e-01
1.29798707e-02 6.88092172e-01 3.97582054e-01 2.84898549e-01
-8.84364665e-01 8.58054340e-01 1.67675781e+00 -8.04901123e-02
8.60860862e-04 9.75652486e-02 -2.37642720e-01 9.55335200e-01
3.98957044e-01 -4.69861627e-01 -3.48624170e-01 -4.64468688e-01
4.91545461e-02 -3.43915634e-02 8.31455648e-01 -1.12833548e+00
2.92176232e-02 -3.11101198e-01 5.30957282e-01 -1.11599135e+00
7.49784648e-01 -1.12070537e+00 1.39979050e-01 3.35924685e-01
-1.52641237e-01 -7.47003928e-02 -6.63967337e-03 6.95999622e-01
1.00923888e-01 1.23060355e-02 5.56793213e-01 -2.25353852e-01
-1.03453100e+00 8.76538277e-01 5.68121433e-01 4.05422002e-01
1.29404914e+00 -3.69400293e-01 -1.49192631e-01 -9.95902494e-02
-6.97779000e-01 2.92355061e-01 9.16977525e-01 8.25315297e-01
6.14844859e-01 -1.41047919e+00 -7.73035645e-01 8.45674649e-02
6.93584859e-01 9.77927625e-01 -6.16583899e-02 5.59275150e-01
-6.14709437e-01 -3.57508734e-02 -1.88813880e-01 -1.33196282e+00
-1.02704155e+00 5.78378558e-01 3.13939840e-01 2.23127112e-01
-6.25678360e-01 9.26919401e-01 2.20107511e-01 -9.62990880e-01
6.35898352e-01 -5.08302748e-01 2.36902624e-01 -7.77003169e-02
1.73271343e-01 2.02768281e-01 1.33216664e-01 -7.58358181e-01
-5.41858375e-01 9.47538555e-01 2.49684423e-01 7.14970678e-02
1.53788805e+00 -3.12341340e-02 2.63397753e-01 7.61134446e-01
1.25892663e+00 -2.63301194e-01 -1.96793115e+00 -3.91730309e-01
-1.99483484e-01 -9.52878237e-01 -2.53855556e-01 -6.96306527e-01
-9.87824678e-01 7.55787909e-01 7.92284071e-01 -4.15440172e-01
6.85372472e-01 4.54795539e-01 3.42873126e-01 6.17784083e-01
1.03806841e+00 -8.95251632e-01 5.59355080e-01 5.97024739e-01
1.26502526e+00 -1.80686021e+00 1.22279525e-01 -6.43047094e-01
-5.58488429e-01 7.85164714e-01 1.19147611e+00 -3.87112737e-01
6.27774060e-01 2.57516712e-01 1.40301004e-01 9.42692626e-04
-2.89034337e-01 -2.56216347e-01 3.46451133e-01 9.47014749e-01
-8.73502791e-02 -7.49083832e-02 1.87270612e-01 3.17216843e-01
-1.66201308e-01 -7.71585405e-02 1.83573052e-01 1.13217854e+00
-3.25606972e-01 -8.98119271e-01 -4.98168826e-01 2.60214478e-01
-2.50613466e-02 5.38221240e-01 -3.98050755e-01 1.01008439e+00
4.31335777e-01 4.97020215e-01 -5.55577874e-02 -3.69834304e-01
6.86970890e-01 -1.17628828e-01 9.57507372e-01 -8.73736978e-01
-3.73751223e-02 6.80934591e-03 3.26468050e-02 -7.78743207e-01
-7.16215730e-01 -8.11986208e-01 -1.15153360e+00 -5.32868411e-03
-5.08618295e-01 -3.88869524e-01 8.45522702e-01 8.11544418e-01
1.66200310e-01 3.14151436e-01 3.19281220e-01 -1.73433554e+00
-7.01078475e-01 -1.05764937e+00 -5.17481804e-01 5.71284711e-01
3.34951788e-01 -1.10329461e+00 -2.04028711e-01 3.62570621e-02] | [7.482084274291992, -2.5353262424468994] |
f65ef21f-9d6c-4981-98ed-a6327e216199 | exploring-adaptive-mcts-with-td-learning-in | 2210.05014 | null | https://arxiv.org/abs/2210.05014v3 | https://arxiv.org/pdf/2210.05014v3.pdf | Exploring Adaptive MCTS with TD Learning in miniXCOM | In recent years, Monte Carlo tree search (MCTS) has achieved widespread adoption within the game community. Its use in conjunction with deep reinforcement learning has produced success stories in many applications. While these approaches have been implemented in various games, from simple board games to more complicated video games such as StarCraft, the use of deep neural networks requires a substantial training period. In this work, we explore on-line adaptivity in MCTS without requiring pre-training. We present MCTS-TD, an adaptive MCTS algorithm improved with temporal difference learning. We demonstrate our new approach on the game miniXCOM, a simplified version of XCOM, a popular commercial franchise consisting of several turn-based tactical games, and show how adaptivity in MCTS-TD allows for improved performances against opponents. | ['Richard Zhao', 'Kimiya Saadat'] | 2022-10-10 | null | null | null | null | ['board-games', 'starcraft'] | ['playing-games', 'playing-games'] | [-2.35680908e-01 -2.73339182e-01 -5.32091223e-02 5.58883436e-02
-4.58219826e-01 -6.81546092e-01 5.68650842e-01 -2.30242848e-01
-8.80444169e-01 9.70261991e-01 -1.11484528e-01 -6.97842240e-01
-1.42755747e-01 -8.39303434e-01 -2.23932058e-01 -3.54643941e-01
-3.64623755e-01 6.74744487e-01 8.39207172e-01 -1.02757013e+00
4.19728428e-01 3.51178557e-01 -1.46673763e+00 4.22948182e-01
6.12464130e-01 9.09114420e-01 2.99884528e-02 1.06646955e+00
8.03267956e-02 1.24373937e+00 -8.74150395e-01 -5.87644815e-01
5.53421795e-01 -5.82013071e-01 -8.38874638e-01 -3.53518277e-01
-2.12241903e-01 -5.29720068e-01 -1.97454229e-01 4.97159481e-01
8.60505641e-01 4.79635298e-01 1.30055755e-01 -1.19410527e+00
3.70555729e-01 6.98387623e-01 -6.18842781e-01 5.73203444e-01
3.85752112e-01 5.31661928e-01 8.65474641e-01 -1.48547068e-01
5.33703327e-01 9.67423022e-01 1.00330389e+00 5.48671603e-01
-1.01584566e+00 -7.83920288e-01 -1.84879050e-01 6.42205179e-01
-9.42979276e-01 -2.26374213e-02 5.92884779e-01 -4.37539518e-02
1.24840426e+00 -2.39692666e-02 1.36787283e+00 1.03329086e+00
3.71866971e-01 1.09898078e+00 1.44663966e+00 -4.08895612e-01
8.16381037e-01 -4.15432572e-01 -6.68399930e-01 4.62463140e-01
-1.61289170e-01 8.32686663e-01 -5.51041365e-01 -3.82727720e-02
8.86778235e-01 -3.64821702e-01 3.63793284e-01 -6.84366643e-01
-5.61401069e-01 1.34623015e+00 3.06617856e-01 3.05889696e-01
-4.62844431e-01 4.58697677e-01 7.71786332e-01 5.49955487e-01
2.05982432e-01 8.19366634e-01 -4.61014241e-01 -1.18314517e+00
-1.27426815e+00 8.65671933e-01 8.54951322e-01 2.69859970e-01
3.42527628e-01 4.32252228e-01 1.43865004e-01 5.96798420e-01
-8.46455768e-02 -2.22785115e-01 7.10192919e-01 -1.34460008e+00
2.27470025e-01 3.46165299e-01 1.55734867e-01 -5.66513181e-01
-6.73791409e-01 -5.43333232e-01 -3.83399904e-01 1.07552803e+00
4.57039744e-01 -6.77996993e-01 -6.52529776e-01 1.50283432e+00
5.11558175e-01 3.44073981e-01 -6.48374259e-02 7.70697773e-01
1.64722919e-01 3.52136135e-01 -2.58969106e-02 9.61214304e-02
8.51031542e-01 -9.82830763e-01 -2.63405085e-01 -2.72607744e-01
8.08058679e-01 -5.13056993e-01 8.65772545e-01 8.21558118e-01
-1.27980900e+00 -4.17284071e-01 -1.09865081e+00 4.42513704e-01
-3.16854626e-01 -6.14054859e-01 1.07030952e+00 1.19801795e+00
-1.07999480e+00 1.01483619e+00 -1.04931605e+00 -3.01967353e-01
4.18333858e-01 7.53994584e-01 -3.21418270e-02 3.23582023e-01
-1.39831030e+00 1.14288068e+00 5.88721633e-01 -1.71855032e-01
-1.08060241e+00 -3.73273790e-01 -5.42245269e-01 -1.81040559e-02
1.03671527e+00 -5.69066584e-01 1.94062579e+00 -9.07324195e-01
-2.42463636e+00 5.28568327e-01 6.69216633e-01 -9.95884538e-01
9.04913962e-01 -1.72116354e-01 -1.63944721e-01 -2.04902023e-01
-2.69235708e-02 5.13224840e-01 6.56571746e-01 -5.41594267e-01
-1.14829648e+00 -6.92211557e-03 8.53613317e-01 6.12459600e-01
1.57576099e-01 1.70335695e-01 8.20032880e-02 -4.87123877e-01
-4.15805757e-01 -9.75739539e-01 -7.43907213e-01 -4.66246277e-01
2.06647158e-01 -1.68671578e-01 5.56890368e-01 -2.44359747e-01
1.31497097e+00 -1.60633504e+00 8.21657032e-02 6.78155646e-02
6.00217059e-02 5.91691792e-01 -1.04647852e-01 7.45957434e-01
8.42557475e-03 -2.18553796e-01 7.40573257e-02 1.25255883e-01
1.00326605e-01 3.87758702e-01 1.24378435e-01 1.47765130e-01
-2.53613085e-01 1.03642344e+00 -1.03293657e+00 -3.00590068e-01
3.65256160e-01 -2.70990700e-01 -1.14777911e+00 -2.40479670e-02
-3.53956342e-01 3.34415853e-01 -3.77173603e-01 2.65190542e-01
3.26817662e-01 2.07245007e-01 2.78793156e-01 6.50179327e-01
-3.89496595e-01 4.65523511e-01 -1.25286388e+00 1.93907201e+00
-4.33074623e-01 5.58834493e-01 3.42891850e-02 -1.06335425e+00
4.53941852e-01 2.15490684e-02 5.66682458e-01 -9.71365213e-01
3.65268439e-01 1.65843591e-01 5.46142042e-01 -1.56068906e-01
9.58026648e-01 -5.63585222e-01 -3.13892961e-01 5.88392556e-01
-5.30133657e-02 -6.74676001e-01 6.45234168e-01 6.26145899e-02
1.34834385e+00 6.73338830e-01 6.48370743e-01 1.16759956e-01
1.85052916e-01 4.73998457e-01 4.32110339e-01 1.10726488e+00
-3.70506972e-01 2.03176960e-01 5.25493741e-01 -6.72691584e-01
-1.02446401e+00 -8.55594158e-01 3.97117674e-01 1.46790731e+00
-3.80115211e-02 -7.25910485e-01 -6.61126316e-01 -6.54488504e-01
-2.62339145e-01 6.39229298e-01 -6.52948201e-01 -2.66350448e-01
-7.10690618e-01 -7.13887990e-01 6.89223409e-01 5.63475192e-01
9.39253628e-01 -1.37694311e+00 -1.34591985e+00 7.50775695e-01
1.39709935e-01 -6.68249726e-01 -1.20991006e-01 4.95929658e-01
-7.19057500e-01 -1.06431997e+00 -4.16206628e-01 -2.98360795e-01
-4.72127110e-01 1.29528278e-02 1.24333894e+00 -6.20746538e-02
-3.10842067e-01 2.59259552e-01 -6.42158389e-01 -3.63631099e-01
-5.11828125e-01 4.28086281e-01 3.15704718e-02 -5.91655016e-01
2.08119243e-01 -8.32241774e-01 -5.86723924e-01 2.74241537e-01
-7.86276400e-01 2.25211769e-01 4.55517411e-01 1.07109690e+00
-7.75358453e-02 2.20024154e-01 1.14954352e-01 -7.42706656e-01
9.68709946e-01 -2.51396567e-01 -8.40840876e-01 -3.15843433e-01
-3.72407049e-01 -9.70098097e-03 5.22167683e-01 -4.53665853e-01
-8.97052884e-01 -2.69245356e-01 -5.40265620e-01 -4.77373041e-02
1.30462825e-01 7.61230230e-01 4.83559310e-01 -3.84034842e-01
9.73139405e-01 1.91868901e-01 -3.05146314e-02 -5.40240631e-02
2.78757036e-01 4.24574614e-01 3.22262585e-01 -6.48222566e-01
7.69946039e-01 9.13075954e-02 -5.75790964e-02 -4.25147086e-01
-3.76118541e-01 -1.11983277e-01 -3.93700659e-01 -4.00727183e-01
5.67417383e-01 -6.57860279e-01 -1.19864357e+00 6.68830216e-01
-6.36379302e-01 -1.02336490e+00 -6.46077633e-01 4.21888828e-01
-1.01115966e+00 1.23200178e-01 -7.42861807e-01 -7.48274207e-01
7.10745901e-02 -9.37130690e-01 4.52140987e-01 5.54005921e-01
-3.52975488e-01 -9.66575503e-01 6.87595963e-01 3.49423110e-01
6.53066576e-01 3.48092109e-01 2.94512749e-01 -5.67801952e-01
-2.68070221e-01 -2.05536619e-01 4.04736996e-01 1.23994343e-01
-5.51426224e-02 -1.52437180e-01 -3.57794285e-01 -4.01109934e-01
-2.43792206e-01 -7.71566391e-01 4.36771542e-01 4.43302244e-01
7.13743627e-01 9.50262025e-02 1.46965580e-02 6.06652498e-01
1.20539248e+00 7.03651309e-01 8.01211238e-01 1.14388824e+00
1.26777366e-01 1.90707073e-01 8.80625248e-01 8.74893486e-01
2.72659838e-01 8.90148580e-01 7.42778003e-01 -2.43500271e-03
1.49119869e-01 -2.52383143e-01 4.25129622e-01 4.47010219e-01
-6.66243792e-01 -2.46296730e-02 -8.06857109e-01 3.32937032e-01
-1.90157270e+00 -1.33231580e+00 2.81048834e-01 1.91166449e+00
8.58147204e-01 5.10361731e-01 7.73392439e-01 2.53473252e-01
4.03223783e-01 2.54711598e-01 -7.22372591e-01 -1.05333698e+00
7.84169734e-02 1.04162157e+00 3.16260338e-01 4.35897648e-01
-9.75396574e-01 1.42713904e+00 7.14132357e+00 1.29619241e+00
-1.04994631e+00 9.98450741e-02 3.36223096e-01 -6.14491224e-01
1.66134402e-01 3.16635370e-01 -2.80776113e-01 3.42568815e-01
8.98962200e-01 -3.76239210e-01 6.37732148e-01 1.02432215e+00
2.21304119e-01 -6.05140507e-01 -6.04376018e-01 6.87290490e-01
-4.37860131e-01 -1.57503355e+00 -4.25213188e-01 1.98433056e-01
8.19124341e-01 7.10430518e-02 1.45563558e-01 1.07584214e+00
1.36347461e+00 -1.10191286e+00 7.18190551e-01 -3.57026368e-01
5.81289887e-01 -1.16079175e+00 7.93102682e-01 3.69547755e-01
-1.12793720e+00 -3.71232867e-01 -2.14403659e-01 -8.95741642e-01
1.36829764e-01 -1.87771291e-01 -8.66605937e-01 5.55079818e-01
7.54106224e-01 3.53721023e-01 -3.29224795e-01 1.23504293e+00
-3.46875280e-01 7.43704438e-01 -3.75217289e-01 -4.53576982e-01
9.55221713e-01 -1.68203160e-01 4.25436169e-01 7.21134663e-01
4.91013192e-02 1.79252669e-01 2.73619831e-01 2.76792169e-01
4.56140876e-01 -1.08351693e-01 -3.49662006e-01 1.98966693e-02
1.27341300e-01 1.06653821e+00 -7.71952450e-01 -1.14064507e-01
-8.58781561e-02 1.02835083e+00 4.32031661e-01 -4.89269104e-03
-1.12707651e+00 -3.82306427e-01 7.59524345e-01 1.64088681e-01
6.52443767e-01 -2.72413284e-01 2.30017696e-02 -8.13517809e-01
-4.65542346e-01 -1.38398206e+00 4.56136137e-01 -6.82226956e-01
-7.17045903e-01 5.70814133e-01 3.45005244e-02 -1.29155636e+00
-1.04121709e+00 -4.81267124e-01 -7.23148465e-01 4.96207833e-01
-1.07840919e+00 -7.77370334e-01 -3.05075180e-02 7.41237044e-01
5.62264383e-01 -4.46654171e-01 6.68854892e-01 2.03475673e-02
-3.30734849e-01 5.29683471e-01 1.98814780e-01 -1.10375144e-01
2.81556219e-01 -1.29974532e+00 7.62220204e-01 6.07904971e-01
7.77933374e-02 5.70151731e-02 1.01189077e+00 -3.15607518e-01
-8.69894266e-01 -3.69122714e-01 -3.53026390e-02 2.62052324e-02
9.44584191e-01 -2.07332745e-01 -2.30085537e-01 4.77532685e-01
4.38509196e-01 -1.90706640e-01 4.98553306e-01 2.64944226e-01
1.09170616e-01 -6.97971135e-02 -1.00159311e+00 1.11805284e+00
1.05611682e+00 -2.32931599e-01 -5.38666427e-01 -6.40165806e-02
1.32321432e-01 -9.14189816e-01 -4.59576994e-01 2.08917096e-01
7.15186715e-01 -1.80406690e+00 7.45411038e-01 -8.23314905e-01
4.78867173e-01 -1.77050367e-01 1.82937339e-01 -1.80430877e+00
-4.39173877e-01 -1.06534839e+00 5.21250591e-02 4.50108320e-01
-6.42201751e-02 -5.06058037e-01 1.54612827e+00 1.68853492e-01
-1.34373069e-01 -8.12283039e-01 -1.33695257e+00 -9.53843474e-01
4.24877852e-01 -6.58877969e-01 5.00188410e-01 6.41076386e-01
2.53966689e-01 1.44383013e-01 -5.69805562e-01 -4.19335693e-01
2.72985816e-01 -3.62646319e-02 1.04270589e+00 -1.07108128e+00
-9.94118929e-01 -6.30192697e-01 -6.19498551e-01 -1.07177508e+00
-2.55343199e-01 -3.89323145e-01 -1.32926345e-01 -1.24337888e+00
-9.17700529e-02 -4.14522558e-01 -1.17337191e-02 4.98875022e-01
2.18329784e-02 3.64466012e-01 3.79935741e-01 -2.19292372e-01
-8.17317545e-01 5.77261984e-01 1.19727337e+00 4.05532354e-03
-3.71866167e-01 2.84248173e-01 -4.45575863e-01 8.14121842e-01
1.05787194e+00 -5.04034579e-01 -4.18006837e-01 -6.24272749e-02
5.82498372e-01 2.65580952e-01 -9.93706211e-02 -1.58271563e+00
1.97366282e-01 -3.48639876e-01 8.46808702e-02 -2.57001847e-01
4.47829247e-01 -4.23066378e-01 1.50287241e-01 1.01441014e+00
-3.13361362e-02 2.26601958e-01 6.69194520e-01 2.65592426e-01
-3.36324543e-01 -3.48065287e-01 7.19358206e-01 -4.42149341e-01
-1.03192246e+00 1.61573544e-01 -1.06640637e+00 2.55696505e-01
1.35240614e+00 -9.08863962e-01 1.37372002e-01 -7.58582830e-01
-7.05537617e-01 1.45697370e-01 3.38519186e-01 1.60436347e-01
3.12770903e-01 -1.07156396e+00 -6.57438517e-01 -1.34992316e-01
-2.69935280e-01 -2.53370345e-01 4.22891468e-01 5.82553983e-01
-1.07244134e+00 8.70095268e-02 -7.37473547e-01 -2.43394643e-01
-1.34758782e+00 2.41186023e-01 6.58225894e-01 -1.13684583e+00
-4.53041434e-01 8.73641074e-01 -1.65872574e-01 -4.45842981e-01
-8.28874260e-02 -4.69701402e-02 -1.98000252e-01 -1.86820030e-01
2.34006539e-01 3.89562160e-01 1.25367241e-02 8.33901316e-02
-3.77824545e-01 1.45666286e-01 -2.48959899e-01 -7.24720240e-01
1.43354380e+00 2.09972098e-01 4.50597286e-01 3.00544739e-01
2.90999502e-01 -1.15639098e-01 -1.61203003e+00 1.30762309e-01
1.29453763e-01 -3.77446264e-01 3.66481468e-02 -9.73776460e-01
-1.01135921e+00 6.73209250e-01 5.36150634e-01 2.13621527e-01
1.26615560e+00 -5.75600863e-01 7.37825394e-01 3.69791508e-01
1.07113743e+00 -1.29215431e+00 4.55445111e-01 9.72003818e-01
3.45452279e-01 -9.18850064e-01 5.12686931e-02 3.41600180e-01
-9.27169979e-01 1.03797030e+00 6.62447572e-01 -4.40806389e-01
1.72668263e-01 4.41130936e-01 -2.71499436e-03 -1.59668401e-02
-1.00854921e+00 -4.88324970e-01 -5.18184006e-01 8.68991613e-01
8.68785083e-02 -4.79096919e-02 -4.16192114e-01 3.50526243e-01
-7.13412285e-01 3.42335641e-01 7.87880421e-01 1.29555821e+00
-4.87477899e-01 -1.42737556e+00 -3.07939976e-01 2.30468199e-01
-4.81816292e-01 -2.18578205e-01 -3.27936411e-01 1.21810138e+00
2.98361450e-01 9.00801599e-01 2.13645445e-03 -6.48353875e-01
2.50817090e-01 -3.44796598e-01 9.00753736e-01 -3.97921354e-01
-1.38069248e+00 -2.21941754e-01 3.95931065e-01 -8.34603071e-01
-2.93472856e-01 -7.69843936e-01 -9.19874370e-01 -1.03127754e+00
-2.91770697e-01 4.36451197e-01 4.31264728e-01 9.26479101e-01
4.91249487e-02 6.49106145e-01 4.95601714e-01 -1.03780305e+00
-4.76482391e-01 -8.46711516e-01 -8.60766470e-01 -1.59698606e-01
-8.89688954e-02 -8.52227271e-01 3.34286969e-03 -6.89692497e-01] | [3.53910231590271, 1.4928343296051025] |
4fdd31e4-df7b-432f-b917-07b95445e95a | segment-anything | 2304.02643 | null | https://arxiv.org/abs/2304.02643v1 | https://arxiv.org/pdf/2304.02643v1.pdf | Segment Anything | We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentation. Using our efficient model in a data collection loop, we built the largest segmentation dataset to date (by far), with over 1 billion masks on 11M licensed and privacy respecting images. The model is designed and trained to be promptable, so it can transfer zero-shot to new image distributions and tasks. We evaluate its capabilities on numerous tasks and find that its zero-shot performance is impressive -- often competitive with or even superior to prior fully supervised results. We are releasing the Segment Anything Model (SAM) and corresponding dataset (SA-1B) of 1B masks and 11M images at https://segment-anything.com to foster research into foundation models for computer vision. | ['Ross Girshick', 'Piotr Dollár', 'Wan-Yen Lo', 'Alexander C. Berg', 'Spencer Whitehead', 'Tete Xiao', 'Laura Gustafson', 'Chloe Rolland', 'Hanzi Mao', 'Nikhila Ravi', 'Eric Mintun', 'Alexander Kirillov'] | 2023-04-05 | null | null | null | null | ['visual-prompting'] | ['computer-vision'] | [ 6.26770020e-01 5.73739707e-01 -4.82085705e-01 -7.10513890e-01
-1.17430770e+00 -7.95428216e-01 6.18991554e-01 -3.93400103e-01
-3.69350284e-01 3.51856232e-01 6.94010034e-02 -5.39168417e-01
1.75762445e-01 -1.18787311e-01 -9.32820737e-01 -2.01069877e-01
1.76941216e-01 7.27254689e-01 5.36892295e-01 2.03784779e-01
1.88084662e-01 1.15221843e-01 -1.37821352e+00 2.77531892e-01
5.22014380e-01 9.49087262e-01 2.08925739e-01 8.64561617e-01
2.49271929e-01 6.55864894e-01 -3.24638546e-01 -8.00449610e-01
8.70103419e-01 -2.03767598e-01 -1.34127712e+00 4.35712695e-01
9.01746690e-01 -6.17188394e-01 -2.96451390e-01 1.09055758e+00
4.66669500e-01 9.97042581e-02 5.79431593e-01 -1.53873074e+00
-9.41276670e-01 7.73396790e-01 -6.63900197e-01 1.04334190e-01
-4.49948907e-02 6.64733171e-01 9.00459886e-01 -8.46376538e-01
1.12496948e+00 8.49144042e-01 9.33800697e-01 1.04618692e+00
-1.33135641e+00 -4.70022261e-01 -6.78007975e-02 -1.79028720e-01
-1.10217619e+00 -8.48237276e-01 -1.01960571e-02 -5.23495018e-01
7.83499420e-01 4.03524786e-01 4.83104050e-01 1.34081399e+00
-3.46330583e-01 1.19931626e+00 1.18206847e+00 -1.20109998e-01
1.70506060e-01 3.74143213e-01 4.05354530e-01 7.21873999e-01
2.04229727e-02 2.01817192e-02 -3.37622017e-01 1.96692109e-01
6.02806926e-01 -3.13976079e-01 -1.63575396e-01 -4.62356299e-01
-1.18931437e+00 5.23173392e-01 4.45472211e-01 -1.24116704e-01
1.11247510e-01 4.38488036e-01 2.02519089e-01 9.35166553e-02
4.97206539e-01 5.53441763e-01 -5.39795280e-01 -2.43719116e-01
-1.28393579e+00 1.62248075e-01 7.47993588e-01 1.56620848e+00
9.70114768e-01 -3.36059719e-01 -4.98720288e-01 7.72107780e-01
3.39087620e-02 3.79589558e-01 1.32142633e-01 -1.69229734e+00
2.03454986e-01 9.99729931e-02 6.02323934e-02 -3.47146958e-01
-5.05776644e-01 -1.53460249e-01 -4.23307210e-01 7.85548463e-02
3.26079756e-01 -3.60704005e-01 -1.74480164e+00 1.46701312e+00
1.84733555e-01 3.68331730e-01 -2.94171721e-01 7.66709268e-01
1.04462540e+00 4.35987353e-01 7.77664185e-02 2.70288199e-01
1.34222949e+00 -1.18693435e+00 -4.55929458e-01 -6.57294691e-01
3.74858677e-01 -7.93219388e-01 1.34807074e+00 3.95661980e-01
-1.29650176e+00 -5.57310641e-01 -7.93771148e-01 -5.08322477e-01
-3.91378462e-01 -3.45387220e-01 7.02250540e-01 8.86091948e-01
-1.39820218e+00 3.73253644e-01 -5.88132799e-01 -6.75403833e-01
1.18819642e+00 1.12463884e-01 -3.75827730e-01 -2.59534955e-01
-5.03680289e-01 5.83743393e-01 2.31195346e-01 -3.54509056e-01
-1.49528754e+00 -8.33938479e-01 -6.91573381e-01 -4.22502011e-01
6.70881510e-01 -6.88939929e-01 1.69909000e+00 -5.96770883e-01
-9.35664415e-01 1.44732451e+00 -1.17811011e-02 -8.33975315e-01
6.22124255e-01 -1.40296519e-01 2.70130616e-02 2.75840074e-01
4.02960718e-01 1.59198165e+00 1.11707461e+00 -1.56641603e+00
-7.04559743e-01 -5.27525172e-02 -1.10817617e-02 -5.12533262e-02
-2.67518938e-01 6.46406487e-02 -9.61011112e-01 -5.05767643e-01
-1.97969511e-01 -9.19602275e-01 -6.01585925e-01 1.97991580e-01
-8.06873560e-01 1.32303759e-01 8.77816856e-01 -8.23162079e-01
6.46673203e-01 -2.32281494e+00 -3.12776178e-01 -1.84004262e-01
3.40402961e-01 5.10868132e-01 -5.28722763e-01 -3.61370330e-04
2.00531930e-01 4.61585492e-01 -6.19104266e-01 -9.36635733e-01
1.51562020e-01 3.67791981e-01 -3.54701370e-01 3.48527908e-01
2.24818215e-01 1.48913372e+00 -8.10394108e-01 -5.19978583e-01
3.44375372e-01 1.42296674e-02 -6.06017709e-01 1.66383713e-01
-6.06542587e-01 4.83752906e-01 -5.71906194e-02 1.02288413e+00
9.30550337e-01 -4.22478586e-01 -3.59983593e-01 1.10083148e-01
-1.07395174e-02 -3.76093835e-01 -6.49188697e-01 2.07206035e+00
-2.76901703e-02 7.91798353e-01 2.95002550e-01 -5.45946240e-01
7.42303252e-01 1.84063420e-01 4.54142541e-01 -4.40258145e-01
1.86623439e-01 3.67029160e-02 -3.77980143e-01 -7.02695906e-01
7.18270361e-01 3.54997307e-01 -1.89753681e-01 3.36794615e-01
4.94275212e-01 -5.49077868e-01 8.28830823e-02 5.08063972e-01
1.30458796e+00 4.39839736e-02 -6.11732714e-02 -3.53656411e-01
-3.40427786e-01 3.76863897e-01 5.46038270e-01 1.31852019e+00
-8.45329344e-01 1.16313815e+00 3.81114542e-01 -3.21224272e-01
-1.16679120e+00 -1.29514349e+00 -3.59130144e-01 1.26225257e+00
3.15348715e-01 -1.18051589e-01 -1.25433922e+00 -7.08400667e-01
8.84092320e-03 6.45509362e-01 -7.01680243e-01 2.41513014e-01
-2.38065724e-03 -2.70400763e-01 8.39073062e-01 4.90446478e-01
8.65852654e-01 -1.11207724e+00 -4.88237143e-01 -1.12015650e-01
-5.73343337e-02 -1.23981977e+00 -7.79172122e-01 2.39676416e-01
-4.43000942e-01 -1.10001004e+00 -8.25955749e-01 -1.06984401e+00
4.38755095e-01 4.22114015e-01 1.07452965e+00 -1.81899220e-01
-8.21512878e-01 7.25806236e-01 -3.72463167e-01 -6.82707727e-01
-1.08495884e-01 3.21787655e-01 -5.50831199e-01 -4.44819331e-02
3.51451218e-01 -1.11847617e-01 -6.33229852e-01 3.93346488e-01
-1.01153219e+00 1.45590052e-01 5.23870945e-01 4.44356471e-01
6.68569386e-01 -5.41070879e-01 3.99611324e-01 -1.42332566e+00
4.79945093e-01 -7.03952134e-01 -6.28777921e-01 2.58540124e-01
-6.31629407e-01 -6.19385123e-01 -1.52377516e-01 -3.57208252e-02
-1.12250602e+00 3.55409145e-01 -1.60763666e-01 -5.53594351e-01
-4.75546539e-01 -2.09851772e-01 -1.21636540e-02 -1.98158517e-01
8.24914157e-01 -3.37485108e-04 -2.68191807e-02 -4.83784616e-01
1.07704294e+00 9.28209126e-01 1.24760830e+00 -3.93976897e-01
7.49879479e-01 7.31086016e-01 -3.27701181e-01 -7.51798332e-01
-1.15532100e+00 -8.49633038e-01 -6.61296844e-01 -1.23379380e-01
1.50052619e+00 -9.94684398e-01 -3.30321431e-01 8.11175168e-01
-1.00367093e+00 -8.79981220e-01 -7.07537055e-01 -1.87566996e-01
-7.94314861e-01 1.56946108e-01 -6.48577213e-01 -5.41287243e-01
-2.44363308e-01 -1.30652368e+00 1.33931804e+00 4.23561692e-01
-7.64384046e-02 -9.02613401e-01 -1.70995325e-01 7.60379374e-01
4.94495511e-01 2.99079448e-01 3.35364968e-01 -5.68215311e-01
-1.00444591e+00 6.97198659e-02 -7.23506331e-01 4.81528908e-01
-2.57911205e-01 -3.62715907e-02 -1.36197305e+00 -1.94766536e-01
-1.01117924e-01 -7.46029019e-01 1.27459216e+00 5.89756906e-01
1.58408093e+00 -1.36285141e-01 -3.98969054e-01 1.09301984e+00
1.23338878e+00 -8.06000009e-02 7.67883301e-01 1.61175281e-01
6.26331866e-01 4.32575852e-01 7.49876618e-01 3.98513705e-01
4.63862479e-01 1.39111489e-01 5.62111616e-01 -3.29487771e-01
-5.72497129e-01 -3.53666812e-01 3.87516804e-02 2.87670106e-01
6.58638775e-02 -2.73829848e-01 -1.02888012e+00 9.21488345e-01
-1.95649564e+00 -8.00412655e-01 -2.50858575e-01 1.79118657e+00
8.36025715e-01 1.77766368e-01 1.68926060e-01 -6.58033311e-01
6.43751323e-01 3.48760933e-01 -1.03332460e+00 -5.24081051e-01
-1.04523189e-01 3.31265390e-01 9.51824009e-01 4.58224952e-01
-1.45118678e+00 1.35303712e+00 7.74751139e+00 8.10501277e-01
-4.34224486e-01 3.85310858e-01 1.09600902e+00 -4.55913134e-02
-3.79391909e-01 2.24563003e-01 -8.69785726e-01 2.68145859e-01
8.86101544e-01 -2.51700670e-01 6.70540631e-01 9.27821279e-01
-2.82385379e-01 -5.56673110e-02 -1.00096011e+00 8.57760906e-01
2.03188807e-01 -1.48787546e+00 -1.59477368e-01 3.19252610e-01
1.12115216e+00 7.74127543e-01 5.36088347e-01 3.20266962e-01
6.73328459e-01 -1.19022906e+00 8.03276837e-01 6.27061427e-01
1.19923949e+00 -3.52130413e-01 4.72514063e-01 3.80687535e-01
-7.59073079e-01 2.60603358e-03 -4.71089721e-01 1.28813118e-01
2.01175719e-01 4.03015047e-01 -1.05240309e+00 7.37368390e-02
1.00800633e+00 9.85387802e-01 -1.05339372e+00 1.30446839e+00
-1.14456654e-01 7.80561626e-01 -1.12638287e-01 3.73059183e-01
3.76448154e-01 8.45461182e-05 5.11534095e-01 1.21026945e+00
-6.80411384e-02 -1.15489569e-02 2.36952022e-01 8.55752349e-01
-6.71367228e-01 -3.36695790e-01 -8.26566637e-01 6.11965545e-02
6.25624299e-01 1.39667130e+00 -7.68570900e-01 -5.00430107e-01
-5.63459992e-01 1.08477974e+00 1.57959074e-01 3.78683060e-01
-8.02423656e-01 -1.86917156e-01 7.54159153e-01 3.08567621e-02
4.38307852e-01 5.63040487e-02 -5.49022973e-01 -8.51821423e-01
-3.28755438e-01 -8.90191197e-01 3.34557354e-01 -8.95790696e-01
-1.72237289e+00 3.77525419e-01 6.41180426e-02 -7.65626311e-01
1.16844051e-01 -5.65423012e-01 -3.32852215e-01 4.84209269e-01
-1.32597852e+00 -1.46183527e+00 -3.83847594e-01 8.23555231e-01
6.52644575e-01 -2.14228123e-01 7.44143128e-01 1.25365049e-01
-5.94463527e-01 7.62332976e-01 -5.62501848e-02 2.79870749e-01
8.77696991e-01 -1.39552021e+00 1.22872329e+00 9.31426525e-01
4.62241769e-01 3.29855114e-01 5.02521813e-01 -5.76101780e-01
-1.07959449e+00 -1.36280835e+00 2.76033759e-01 -1.11267436e+00
5.92674792e-01 -6.79136634e-01 -5.88453233e-01 1.29541934e+00
6.33946478e-01 2.80284315e-01 6.18778467e-01 -4.43499982e-02
-4.05759364e-01 2.20807210e-01 -1.43643749e+00 4.06026751e-01
1.46124411e+00 -4.69602883e-01 -4.94119078e-01 4.99236882e-01
1.28130698e+00 -5.96888483e-01 -8.27171564e-01 3.07339847e-01
3.47192556e-01 -1.20409322e+00 8.53396893e-01 -5.34043670e-01
3.65057558e-01 -8.39082301e-02 -2.66892999e-01 -8.69538546e-01
-3.40839148e-01 -1.05413508e+00 -7.74617493e-02 1.44691443e+00
7.21381664e-01 -6.58006728e-01 9.39094841e-01 9.36455727e-01
-3.99950206e-01 -7.42727458e-01 -9.54127729e-01 -8.23382497e-01
1.84202865e-02 -6.59556150e-01 7.33186960e-01 8.66140008e-01
-5.49545884e-01 5.49043380e-02 -4.26727027e-01 -8.47651344e-03
9.04580057e-01 9.13517829e-03 1.16480064e+00 -8.06930900e-01
-4.33623910e-01 -3.66138309e-01 -4.41289067e-01 -1.27281463e+00
-2.81736165e-01 -1.08524942e+00 3.45827460e-01 -1.62557340e+00
5.17783105e-01 -4.58993435e-01 -2.60666072e-01 9.84775603e-01
-8.39504749e-02 7.71832526e-01 3.86549979e-01 3.02662939e-01
-9.18729544e-01 -2.89499853e-02 1.36608255e+00 -2.48087376e-01
1.09161146e-01 1.76274940e-01 -1.08402610e+00 8.58602643e-01
8.77865851e-01 -4.35971916e-01 -5.05874574e-01 -8.24722171e-01
-3.60401362e-01 -4.93546605e-01 5.34482718e-01 -1.08863139e+00
1.78872779e-01 -3.39845195e-02 1.69040397e-01 -8.08651388e-01
4.51887846e-01 -5.41313887e-01 -8.11531395e-02 1.27340212e-01
-3.41485053e-01 -4.96979266e-01 2.49662966e-01 5.24113476e-01
1.37285843e-01 -3.94793242e-01 7.19418049e-01 -4.69590843e-01
-1.44897223e+00 7.94119477e-01 1.50230825e-01 5.14735460e-01
1.36390090e+00 -2.21811742e-01 -8.38545740e-01 -2.39400208e-01
-8.70997190e-01 4.94763553e-01 7.96385586e-01 5.63842475e-01
5.44893742e-01 -9.11412299e-01 -6.25637531e-01 1.92706615e-01
3.36725056e-01 2.52981275e-01 1.00146562e-01 5.27800918e-01
-6.09338403e-01 4.30695638e-02 -3.71563807e-02 -8.97879481e-01
-9.76164043e-01 6.29646838e-01 1.27385005e-01 1.21493623e-01
-6.92489386e-01 1.48110723e+00 8.70879963e-02 -6.35297954e-01
5.04906595e-01 -2.09321588e-01 5.24355233e-01 -1.05616197e-01
5.32937765e-01 3.74429047e-01 -3.41425478e-01 -2.22317457e-01
-1.24659501e-01 4.29918587e-01 -1.76112577e-01 -3.67503256e-01
1.33083951e+00 -1.72072813e-01 -4.11269031e-02 3.87976319e-01
1.11976850e+00 -2.81223536e-01 -1.87333989e+00 -5.82654998e-02
-1.88578833e-02 -7.47326195e-01 -1.80973127e-01 -1.00162590e+00
-1.03826249e+00 8.68086755e-01 5.02240658e-01 2.08498314e-01
9.97122407e-01 5.58622599e-01 1.26229882e+00 2.00255603e-01
5.98410130e-01 -1.22939014e+00 8.41551125e-02 3.71522397e-01
5.21462083e-01 -1.59851849e+00 -2.32593045e-01 -2.88040370e-01
-8.42006326e-01 3.45389485e-01 6.34848237e-01 1.39386326e-01
8.50271523e-01 3.38256121e-01 4.34995890e-01 -3.27162147e-01
-5.18942237e-01 -5.32153904e-01 1.19648099e-01 1.32763648e+00
-2.01575905e-01 1.93334594e-01 3.68009627e-01 4.57950234e-01
-2.81643391e-01 6.36667162e-02 4.37915504e-01 8.43899906e-01
-5.99982142e-01 -1.05871546e+00 -1.61541149e-01 7.14012682e-01
-7.44882450e-02 3.00450181e-03 -6.63388252e-01 7.49031544e-01
5.14717877e-01 1.08450699e+00 8.31061527e-02 -3.49522501e-01
1.78263351e-01 -1.73409685e-01 3.92440200e-01 -9.48177755e-01
-4.23031121e-01 -2.66473532e-01 2.48137768e-02 -8.35684657e-01
-2.71197677e-01 -7.79660523e-01 -1.00408566e+00 -2.88008779e-01
-1.26508072e-01 -5.10839760e-01 7.89742112e-01 5.31695664e-01
6.20347917e-01 2.47788399e-01 4.65263635e-01 -8.96658123e-01
-3.26614738e-01 -7.94297814e-01 -5.87327003e-01 4.31888044e-01
2.82628804e-01 -1.18730068e-01 -6.65899739e-02 3.39677393e-01] | [9.582902908325195, 0.49978604912757874] |
c9f548f9-77d9-4992-afc3-121eb788fccc | program-synthesis-performance-constrained-by | 1911.07721 | null | https://arxiv.org/abs/1911.07721v2 | https://arxiv.org/pdf/1911.07721v2.pdf | Program synthesis performance constrained by non-linear spatial relations in Synthetic Visual Reasoning Test | Despite remarkable advances in automated visual recognition by machines, some visual tasks remain challenging for machines. Fleuret et al. (2011) introduced the Synthetic Visual Reasoning Test (SVRT) to highlight this point, which required classification of images consisting of randomly generated shapes based on hidden abstract rules using only a few examples. Ellis et al. (2015) demonstrated that a program synthesis approach could solve some of the SVRT problems with unsupervised, few-shot learning, whereas they remained challenging for several convolutional neural networks trained with thousands of examples. Here we re-considered the human and machine experiments, because they followed different protocols and yielded different statistics. We thus proposed a quantitative reintepretation of the data between the protocols, so that we could make fair comparison between human and machine performance. We improved the program synthesis classifier by correcting the image parsings, and compared the results to the performance of other machine agents and human subjects. We grouped the SVRT problems into different types by the two aspects of the core characteristics for classification: shape specification and location relation. We found that the program synthesis classifier could not solve problems involving shape distances, because it relied on symbolic computation which scales poorly with input dimension and adding distances into such computation would increase the dimension combinatorially with the number of shapes in an image. Therefore, although the program synthesis classifier is capable of abstract reasoning, its performance is highly constrained by the accessible information in image parsings. | ['Mark C. W. van Rossum', 'Scott C. Lowe', 'Penelope A. Lewis', 'Lu Yihe'] | 2019-11-18 | null | null | null | null | ['unsupervised-few-shot-learning'] | ['computer-vision'] | [ 2.78786302e-01 2.10941836e-01 1.24758653e-01 -3.54856312e-01
-2.47937575e-01 -8.92747879e-01 9.29579496e-01 2.54776835e-01
-4.60282743e-01 3.36629391e-01 -5.32880783e-01 -5.21478355e-01
-8.75934362e-02 -9.75767374e-01 -8.48304451e-01 -4.83158857e-01
4.87596504e-02 6.67355061e-01 4.62024361e-01 -1.41062096e-01
4.36770231e-01 5.95274210e-01 -1.97578871e+00 6.46442950e-01
6.39042258e-01 8.26583087e-01 8.61815438e-02 9.81187403e-01
-3.40330660e-01 8.98999214e-01 -6.59331560e-01 -6.29695654e-01
2.08920509e-01 -2.94111967e-01 -7.67149270e-01 1.73418522e-02
5.31834722e-01 -8.47514570e-02 -5.87876029e-02 1.11279356e+00
8.97693112e-02 -1.46348737e-02 7.94535995e-01 -1.69840062e+00
-1.12204814e+00 4.95837331e-01 -1.28538191e-01 -1.38467997e-01
5.03794134e-01 4.83650625e-01 9.84974027e-01 -1.00282073e+00
8.17929864e-01 1.22300506e+00 7.51063585e-01 6.15332723e-01
-1.52028108e+00 -2.72523135e-01 -1.16457194e-01 2.96445847e-01
-1.10158563e+00 -1.84109718e-01 4.23054695e-01 -8.19547176e-01
1.28320742e+00 3.92993569e-01 7.55878031e-01 1.09006548e+00
-1.92998752e-01 4.75145280e-01 1.24738014e+00 -5.36199510e-01
6.26877666e-01 2.03327179e-01 2.56327152e-01 1.07412255e+00
3.44858438e-01 2.70119309e-01 -1.05653934e-01 -1.28097028e-01
8.07925642e-01 -1.75571650e-01 1.66884605e-02 -8.01668704e-01
-1.28896534e+00 9.66612816e-01 4.46792245e-01 4.63003159e-01
1.63736656e-01 -3.43831852e-02 4.90159780e-01 4.45734441e-01
-1.06230035e-01 6.50003314e-01 -3.13111842e-01 -9.50604212e-03
-7.25854456e-01 1.94822863e-01 9.76354182e-01 9.60984111e-01
7.35879600e-01 1.24877028e-01 -7.93075711e-02 5.11262655e-01
-7.89870843e-02 3.21341246e-01 4.51350361e-01 -1.12406206e+00
2.91272789e-01 9.19783711e-01 -8.38567689e-02 -1.14451337e+00
-5.23825645e-01 -1.27574950e-02 -7.86946535e-01 9.44379687e-01
1.08240843e+00 1.54000759e-01 -1.04606867e+00 1.53275025e+00
-2.04406455e-01 -7.34156311e-01 7.74918795e-02 8.38719368e-01
9.18245077e-01 5.31491935e-01 1.30084008e-01 1.94788560e-01
1.35274267e+00 -9.26783264e-01 -4.09003437e-01 -1.06154710e-01
9.18986022e-01 -4.11755651e-01 1.60705614e+00 3.41303110e-01
-1.01601923e+00 -7.56773710e-01 -1.27329278e+00 -3.41325291e-02
-9.99726832e-01 1.64125726e-01 9.02623713e-01 8.22132826e-01
-1.04640722e+00 7.67679870e-01 -5.38619757e-01 -6.30546153e-01
5.66163778e-01 2.91144907e-01 -4.13374543e-01 1.73368350e-01
-7.89733231e-01 9.86860394e-01 3.26318681e-01 -1.46919608e-01
-7.23202348e-01 -3.47327977e-01 -9.98215675e-01 2.25750133e-01
2.59527177e-01 -5.10719597e-01 1.17577171e+00 -1.19610965e+00
-1.35983026e+00 1.35271931e+00 1.23714790e-01 -5.00263095e-01
6.53647661e-01 5.63020170e-01 -1.76417410e-01 1.22783154e-01
-1.14313260e-01 7.68453121e-01 7.97177970e-01 -1.16847670e+00
-1.74434826e-01 -2.83101112e-01 3.00589353e-01 -3.00963521e-01
2.55384028e-01 1.24464184e-03 -2.10978417e-03 -5.52950561e-01
-3.28067727e-02 -9.49731410e-01 -8.20175260e-02 3.90775323e-01
-1.21434771e-01 -2.32040614e-01 6.15609407e-01 -3.26673418e-01
5.36001742e-01 -2.31092167e+00 2.34855384e-01 1.23192400e-01
2.75449485e-01 3.03427964e-01 -3.49438071e-01 3.71518135e-01
-2.10943162e-01 4.72310901e-01 -5.00167191e-01 1.05427019e-02
3.23924690e-01 3.93007010e-01 -4.23309058e-01 4.09863740e-01
1.93608657e-01 1.13341081e+00 -7.38175392e-01 -3.91245157e-01
1.16208822e-01 1.38069198e-01 -4.39892560e-01 9.69288051e-02
-4.89030719e-01 6.27495944e-02 3.14935930e-02 6.60496950e-01
5.18960118e-01 -3.05591494e-01 1.31071031e-01 -2.97695268e-02
-1.42292738e-01 -3.70213121e-01 -9.25032079e-01 1.49636376e+00
-2.07061261e-01 9.05476987e-01 -2.16603249e-01 -1.15291381e+00
9.91474807e-01 1.08994573e-01 -4.89114970e-02 -8.06825399e-01
5.82742020e-02 2.07242131e-01 1.84157267e-01 -7.01100528e-01
1.41149387e-01 1.67562068e-01 -1.60085902e-01 4.33320940e-01
7.79864639e-02 -4.47171479e-01 3.68770152e-01 -9.30636004e-03
1.13872004e+00 3.15950781e-01 4.66708720e-01 -1.14805184e-01
3.07139546e-01 4.76847380e-01 1.94161296e-01 1.03954792e+00
-2.92453706e-01 6.83763266e-01 1.03122878e+00 -9.94058728e-01
-1.38286746e+00 -1.07778788e+00 1.16447382e-01 1.19344842e+00
-6.55642226e-02 -3.47013116e-01 -9.73362923e-01 -6.57013297e-01
-1.62139475e-01 8.11601281e-01 -8.48702431e-01 3.86482701e-02
-4.87602234e-01 -5.18539369e-01 6.77132368e-01 5.02255380e-01
3.43131542e-01 -1.34108162e+00 -1.22101200e+00 -2.75544196e-01
4.03805733e-01 -1.16453195e+00 1.00142218e-01 2.94902384e-01
-6.39881849e-01 -1.42806709e+00 -6.75545514e-01 -1.04541457e+00
1.00238943e+00 -4.42908220e-02 1.03116620e+00 4.33149546e-01
-4.95206356e-01 4.58253384e-01 -4.67959404e-01 -3.29168677e-01
-6.07441962e-01 -2.42285043e-01 -2.71085054e-01 -3.31759930e-01
2.19896615e-01 -5.64785957e-01 -1.16487637e-01 2.29975283e-01
-9.63052452e-01 2.29357883e-01 6.47100031e-01 9.60773468e-01
2.33816624e-01 -5.63136004e-02 1.33059606e-01 -8.34805369e-01
5.17781258e-01 2.75095534e-02 -8.24625552e-01 4.65028286e-01
-4.14125234e-01 4.19052333e-01 7.35605240e-01 -6.87233865e-01
-7.16345549e-01 3.76578271e-01 1.36957362e-01 -2.17819989e-01
-3.76209617e-01 1.78538933e-01 -6.45773113e-02 -3.99466813e-01
8.96547556e-01 2.11993515e-01 3.33246589e-03 -1.10532813e-01
5.25941133e-01 3.02138120e-01 3.75297487e-01 -5.95201731e-01
7.96100318e-01 2.29039088e-01 1.32739604e-01 -7.56206036e-01
-3.99011165e-01 1.95893422e-01 -8.79680872e-01 -5.47974743e-02
1.03286624e+00 -3.31603080e-01 -9.85123754e-01 3.47096562e-01
-1.56767607e+00 -4.94749665e-01 -4.57897335e-01 1.80084959e-01
-9.04626846e-01 3.71977270e-01 -4.96789306e-01 -7.41259038e-01
6.56165332e-02 -1.37570119e+00 8.09626698e-01 -8.21942464e-02
-5.44524193e-01 -6.99241161e-01 -4.11798805e-02 -1.96817089e-02
3.72765720e-01 4.36526954e-01 1.64521432e+00 -8.75231326e-01
-5.32053471e-01 -1.27466962e-01 -5.13892591e-01 5.15010953e-02
-4.21915889e-01 2.19888657e-01 -9.83893692e-01 7.86051229e-02
-4.06362936e-02 -5.58285475e-01 6.64568424e-01 -4.19113748e-02
1.31312716e+00 -4.10346150e-01 3.26958634e-02 4.77434367e-01
1.37300253e+00 4.13510740e-01 8.27405035e-01 4.99548018e-01
5.63763499e-01 8.87612104e-01 1.14163846e-01 -8.53080302e-03
3.88272945e-03 6.77690506e-01 3.66682827e-01 3.59691866e-02
-1.09696321e-01 -1.93752632e-01 2.22020447e-01 3.11585695e-01
-2.75132030e-01 5.43069281e-02 -1.13932991e+00 3.00401956e-01
-1.95010889e+00 -1.07847703e+00 -1.25859395e-01 2.03962231e+00
5.42867422e-01 3.05674285e-01 2.24455222e-01 3.50321144e-01
6.11136198e-01 1.30408844e-02 -2.91591287e-01 -9.70366061e-01
-2.61696815e-01 2.46411458e-01 3.71132344e-01 3.20157140e-01
-7.73524523e-01 7.25895584e-01 7.11263609e+00 6.41754389e-01
-8.87737155e-01 -6.44000918e-02 4.83137757e-01 2.82424569e-01
-1.03653021e-01 1.64772928e-01 -3.32163662e-01 3.27653557e-01
8.15259933e-01 -2.70604696e-02 6.82721734e-01 1.06714296e+00
-4.44654346e-01 -2.03413934e-01 -1.53303635e+00 1.09560692e+00
2.10551411e-01 -1.31881011e+00 2.30521917e-01 -2.12632194e-01
3.65697324e-01 -2.69772202e-01 5.50942216e-03 5.85004628e-01
2.42563784e-01 -1.45201778e+00 8.75614762e-01 5.35298347e-01
5.56490600e-01 -3.00385743e-01 3.33313495e-01 4.53766972e-01
-9.32309687e-01 -2.43677139e-01 -3.04092765e-01 -3.95546675e-01
-4.38930511e-01 1.70949861e-01 -6.86344981e-01 1.54719818e-02
5.82281351e-01 1.56956300e-01 -1.14938438e+00 8.85924935e-01
-2.23847315e-01 -4.02914733e-02 5.38075529e-02 -3.73321950e-01
3.00019849e-02 -1.03524446e-01 3.94731045e-01 1.07382250e+00
2.92552620e-01 -5.20678349e-02 -1.59098227e-02 1.34683561e+00
3.30299199e-01 -2.64856685e-02 -9.74323153e-01 -2.44994745e-01
1.80291042e-01 1.13597035e+00 -1.16110480e+00 -3.66043091e-01
-5.25963485e-01 8.19583535e-01 4.94142473e-01 4.05011922e-01
-8.11461568e-01 -5.54634929e-01 1.17587209e-01 -2.60732844e-02
4.44895893e-01 -3.96913081e-01 -6.43832386e-01 -9.85289037e-01
9.56657082e-02 -8.97746623e-01 1.86144248e-01 -1.14292824e+00
-1.06740725e+00 7.75014639e-01 1.36265099e-01 -1.19172287e+00
-2.56577760e-01 -1.22596908e+00 -5.45304596e-01 5.07760882e-01
-8.58203113e-01 -1.17978644e+00 -3.48981768e-01 2.59473205e-01
4.40829962e-01 -3.72215271e-01 1.21758151e+00 -1.59266785e-01
-4.10912395e-01 5.36741912e-01 -3.44975173e-01 3.79511684e-01
2.14429542e-01 -1.27289569e+00 5.73043525e-01 5.28427839e-01
3.36863190e-01 5.08975863e-01 7.98063874e-01 -3.39377761e-01
-1.39319623e+00 -7.16916203e-01 7.18074679e-01 -5.68970025e-01
6.41910970e-01 -4.98793811e-01 -8.87949407e-01 6.15041912e-01
2.92996973e-01 2.64280617e-01 2.90857852e-01 -3.26598227e-01
-8.25478077e-01 3.54079753e-01 -1.22769368e+00 7.31980622e-01
1.13340569e+00 -6.24415517e-01 -8.00391555e-01 2.27523565e-01
6.89224482e-01 -1.99276701e-01 -5.41927338e-01 3.46243203e-01
6.14433110e-01 -1.30955267e+00 9.14408028e-01 -6.59488797e-01
5.20317912e-01 -2.59433568e-01 -2.25540563e-01 -1.12351990e+00
-1.72609568e-01 -1.77065253e-01 -9.92780551e-03 9.25062597e-01
5.62750399e-01 -6.64773047e-01 6.08587384e-01 7.84607053e-01
1.55380338e-01 -5.75067937e-01 -6.64967656e-01 -9.96756017e-01
6.51906431e-02 -3.09657216e-01 4.44992393e-01 7.91130304e-01
1.44401670e-01 2.22756788e-01 6.52847216e-02 -2.62234002e-01
5.39889634e-01 3.26137334e-01 7.51935661e-01 -1.41264391e+00
-4.29188371e-01 -8.22282791e-01 -7.20235407e-01 -2.83632219e-01
3.20485204e-01 -1.06789672e+00 -1.00186311e-01 -1.28373802e+00
1.83558360e-01 -1.27493083e-01 3.40276033e-01 7.71922231e-01
4.16761905e-01 2.03924194e-01 4.16029304e-01 2.20038444e-01
-3.98743004e-01 1.99246220e-02 1.11949515e+00 -5.06572127e-01
-4.48771864e-02 -2.23462850e-01 -3.81517142e-01 9.67533946e-01
7.48960257e-01 -4.69926834e-01 -2.94710159e-01 -3.95135999e-01
6.40064478e-01 -4.67419773e-02 9.50217664e-01 -1.18646264e+00
3.83701175e-01 -1.58442065e-01 6.18938506e-01 -3.83714616e-01
2.31248274e-01 -9.74864304e-01 1.80695638e-01 6.43739045e-01
-5.29275179e-01 1.61854163e-01 1.62766322e-01 2.61511117e-01
3.03159133e-02 -5.94045639e-01 7.98530996e-01 -5.33719957e-01
-9.63872075e-01 -1.87232226e-01 -4.06965733e-01 -1.17627278e-01
1.24066162e+00 -5.03948927e-01 -7.55129218e-01 -1.26676187e-01
-9.72018361e-01 -3.53551805e-01 7.42170870e-01 2.73973763e-01
6.37226224e-01 -1.26657021e+00 -2.81077713e-01 4.31722999e-01
2.71867216e-01 -1.94096625e-01 1.15644541e-02 7.91563153e-01
-8.56115103e-01 3.38090688e-01 -6.76661372e-01 -6.00260019e-01
-1.21014869e+00 1.01436520e+00 2.87935466e-01 9.15489867e-02
-6.88796937e-01 3.21480364e-01 8.34007040e-02 -5.89723587e-01
5.17819285e-01 -6.13145292e-01 -1.63909376e-01 8.41500610e-02
6.06858015e-01 2.49345273e-01 6.02463027e-04 -4.67511445e-01
-1.91410616e-01 8.06870997e-01 2.74681121e-01 -1.15160599e-01
1.23471701e+00 4.34804380e-01 -1.88579455e-01 5.59277952e-01
1.18540466e+00 -2.92920053e-01 -1.00794363e+00 1.08177036e-01
2.65154183e-01 -2.55877376e-01 -4.82904851e-01 -7.90999532e-01
-6.50588870e-01 9.49437797e-01 5.50425649e-01 7.34092593e-01
8.38950992e-01 -7.31052645e-03 2.66414106e-01 8.60320032e-01
4.33721215e-01 -8.80700231e-01 1.79929465e-01 7.63833702e-01
1.02864289e+00 -1.28617311e+00 -1.01725362e-01 -4.58611816e-01
-6.83662057e-01 1.45931959e+00 5.73504746e-01 -1.25250369e-01
2.06694871e-01 3.82869601e-01 -2.37813577e-01 -3.67724508e-01
-5.81797302e-01 -3.11606258e-01 3.24643880e-01 9.81248200e-01
9.22139362e-02 1.47709353e-02 -6.91191852e-02 6.97439730e-01
-3.67317885e-01 2.29482185e-02 5.82427800e-01 9.99525487e-01
-4.45843279e-01 -8.52544785e-01 -3.77629787e-01 2.05543935e-01
5.15921898e-02 1.51663125e-01 -6.33395672e-01 1.04844582e+00
1.54519379e-01 6.51399314e-01 9.65034664e-02 -5.24420440e-01
3.91057909e-01 2.69019306e-01 7.69215703e-01 -5.94223022e-01
-4.06802028e-01 -6.93616629e-01 1.47542097e-02 -5.37473798e-01
-4.22160774e-01 -3.97450179e-01 -1.30562639e+00 -1.68123320e-01
3.40502381e-01 -1.56314090e-01 6.36440516e-01 8.76194954e-01
4.85442877e-02 2.94140548e-01 2.01456040e-01 -1.06540251e+00
-6.29437208e-01 -6.28770053e-01 -3.39464515e-01 5.67749918e-01
2.05069274e-01 -5.13470888e-01 -6.98995352e-01 2.06149638e-01] | [10.298919677734375, 2.2637054920196533] |
a8b97f8d-2ece-450d-bda8-0209b4abc555 | identity-preserving-face-completion-for-large | 1807.08772 | null | http://arxiv.org/abs/1807.08772v1 | http://arxiv.org/pdf/1807.08772v1.pdf | Identity Preserving Face Completion for Large Ocular Region Occlusion | We present a novel deep learning approach to synthesize complete face images
in the presence of large ocular region occlusions. This is motivated by recent
surge of VR/AR displays that hinder face-to-face communications. Different from
the state-of-the-art face inpainting methods that have no control over the
synthesized content and can only handle frontal face pose, our approach can
faithfully recover the missing content under various head poses while
preserving the identity. At the core of our method is a novel generative
network with dedicated constraints to regularize the synthesis process. To
preserve the identity, our network takes an arbitrary occlusion-free image of
the target identity to infer the missing content, and its high-level CNN
features as an identity prior to regularize the searching space of generator.
Since the input reference image may have a different pose, a pose map and a
novel pose discriminator are further adopted to supervise the learning of
implicit pose transformations. Our method is capable of generating coherent
facial inpainting with consistent identity over videos with large variations of
head motions. Experiments on both synthesized and real data demonstrate that
our method greatly outperforms the state-of-the-art methods in terms of both
synthesis quality and robustness. | ['WangMeng Zuo', 'Jun Xing', 'Ruigang Yang', 'Zach Bessinger', 'Weikai Chen', 'Fuchang Liu', 'Yajie Zhao', 'Xiaoming Li'] | 2018-07-23 | null | null | null | null | ['facial-inpainting'] | ['computer-vision'] | [ 3.08595121e-01 3.08771700e-01 2.31092557e-01 -4.63694245e-01
-7.16483474e-01 -4.76299822e-01 5.32918513e-01 -7.79094279e-01
-2.39441041e-02 7.25610137e-01 2.13598847e-01 3.83274019e-01
2.15402409e-01 -5.32389760e-01 -1.00653827e+00 -8.53614926e-01
5.08266807e-01 3.74047667e-01 -1.45844281e-01 -3.94437402e-01
1.48840204e-01 8.38074565e-01 -1.89157414e+00 1.50918543e-01
7.65395045e-01 1.05567777e+00 1.46658020e-02 4.16376173e-01
1.83167592e-01 5.75198293e-01 -8.26258302e-01 -5.95774889e-01
5.74877977e-01 -6.55436873e-01 -3.70204329e-01 4.44311649e-01
1.08686793e+00 -6.35338128e-01 -5.68013549e-01 9.30969596e-01
9.13283646e-01 1.23442948e-01 5.34984589e-01 -1.12235534e+00
-5.22465587e-01 -1.49220839e-01 -6.37561500e-01 -2.89196908e-01
7.86385596e-01 1.56395167e-01 3.67173523e-01 -1.06292677e+00
1.01352155e+00 1.37943244e+00 4.03225362e-01 1.02251887e+00
-1.31132710e+00 -8.36560369e-01 7.99002796e-02 3.42589593e-03
-1.64345121e+00 -1.09030318e+00 9.76177216e-01 -2.61557251e-01
2.70094186e-01 2.77213544e-01 5.91082036e-01 1.21929073e+00
9.80491564e-02 3.23126972e-01 8.52915764e-01 -4.33529109e-01
1.12443104e-01 -1.96003472e-03 -7.96155930e-01 8.25907767e-01
-5.58208525e-02 1.40547082e-01 -8.07270408e-01 -7.65501037e-02
1.10265982e+00 -2.38807172e-01 -6.35543525e-01 -5.85960150e-01
-7.54628837e-01 7.30677724e-01 1.69057965e-01 -1.11208647e-01
-2.59125859e-01 -1.09027803e-01 2.55797412e-02 2.01336205e-01
4.70799237e-01 2.95664787e-01 -6.73211589e-02 3.57514679e-01
-1.18012917e+00 5.79262495e-01 7.79994607e-01 1.00494146e+00
7.22370028e-01 3.43592793e-01 -3.51263940e-01 7.97176838e-01
1.66218594e-01 4.74142849e-01 2.55245715e-01 -1.18270087e+00
2.18276262e-01 2.54088134e-01 1.20869085e-01 -8.93865526e-01
-4.16888259e-02 -4.30993497e-01 -6.10262513e-01 3.76496196e-01
2.69764185e-01 -1.25405133e-01 -1.04142642e+00 1.84555614e+00
7.05371976e-01 2.56949782e-01 -2.06639260e-01 9.80110466e-01
8.06530118e-01 3.34603101e-01 -4.46711928e-01 -4.78365690e-01
1.21377110e+00 -7.01058447e-01 -1.05054367e+00 -2.01090962e-01
-5.91563247e-02 -1.01725960e+00 7.42962420e-01 2.80380309e-01
-1.35927737e+00 -6.21107459e-01 -9.56938326e-01 -2.40615547e-01
2.16502532e-01 2.07845479e-01 2.33116239e-01 6.15194678e-01
-1.23754370e+00 4.83465910e-01 -5.59237778e-01 -9.84867364e-02
4.51027006e-01 5.59196711e-01 -7.16545761e-01 -1.92498550e-01
-8.85295868e-01 9.28195953e-01 -3.32570300e-02 3.61478776e-01
-9.28201377e-01 -7.57351875e-01 -1.00632322e+00 -1.59769490e-01
3.69417787e-01 -8.53113949e-01 1.01392281e+00 -1.25493169e+00
-2.00249362e+00 1.04056704e+00 -4.22454149e-01 1.21871009e-01
8.73865962e-01 -2.91075349e-01 -2.78152585e-01 3.12818259e-01
1.44312620e-01 8.82985771e-01 1.48620832e+00 -1.34599018e+00
-1.60943851e-01 -3.36365908e-01 -2.17085972e-01 3.63259763e-01
-1.36187533e-02 6.36420846e-02 -7.95429111e-01 -6.96640968e-01
6.24998324e-02 -1.01847267e+00 1.51725054e-01 4.78121728e-01
-1.78404167e-01 2.21145406e-01 9.01190162e-01 -6.95521414e-01
7.27727532e-01 -2.09442902e+00 4.33750421e-01 -3.49543840e-02
1.56488717e-01 1.65949017e-01 -1.51290491e-01 2.55007178e-01
-1.64008111e-01 -4.63846833e-01 -1.14691652e-01 -8.02460492e-01
-2.44565129e-01 1.58258721e-01 -3.93239051e-01 8.95544410e-01
3.57442081e-01 6.16004050e-01 -5.55740058e-01 -4.86694783e-01
2.53609419e-01 1.08170092e+00 -8.61100852e-01 6.31931245e-01
-1.85943469e-01 1.06935275e+00 -1.72756329e-01 6.63736999e-01
1.01505804e+00 2.02635586e-01 1.07162178e-01 -4.32701021e-01
2.85012890e-02 -8.30725655e-02 -1.18426561e+00 1.88608539e+00
-3.36631924e-01 5.27590036e-01 4.67720628e-01 -6.37247026e-01
9.30602014e-01 4.14640546e-01 3.78023952e-01 -4.93407786e-01
3.94168675e-01 2.43048340e-01 -5.25854863e-02 -4.72323656e-01
2.29026571e-01 -1.59556493e-01 4.05970246e-01 1.05515048e-02
3.17994505e-01 -3.24379146e-01 -1.16378136e-01 -1.52943805e-01
5.68485558e-01 5.37559569e-01 -2.08708555e-01 -1.20789103e-01
6.84191704e-01 -7.31935084e-01 6.57050431e-01 1.50915369e-01
1.40180439e-01 1.28756893e+00 4.06914622e-01 -3.48214477e-01
-1.02270281e+00 -1.02035177e+00 -2.24759400e-01 8.22335005e-01
3.01305745e-02 -1.02457799e-01 -1.10202467e+00 -3.11503887e-01
-2.79933989e-01 4.66112107e-01 -7.37879097e-01 -7.94643462e-02
-7.97538817e-01 -3.35507363e-01 3.82163405e-01 1.64229035e-01
4.32301372e-01 -1.04840529e+00 -3.59457582e-01 9.49213840e-03
-3.61636668e-01 -1.29984117e+00 -8.84717584e-01 -4.80109662e-01
-4.66609299e-01 -1.03666270e+00 -8.44070375e-01 -8.72823119e-01
1.05838609e+00 -1.20306663e-01 7.78258741e-01 -5.65756708e-02
-4.66503590e-01 1.54454798e-01 3.79999503e-02 -2.18378186e-01
-3.98410380e-01 -3.28499049e-01 1.07019030e-01 5.94556153e-01
-2.48785809e-01 -7.46556699e-01 -8.52436960e-01 3.19841236e-01
-8.86738777e-01 3.70588191e-02 2.26286501e-01 7.65212774e-01
4.72873539e-01 -1.82059899e-01 2.69663900e-01 -6.25774622e-01
3.51084173e-01 -1.19394206e-01 -7.12244391e-01 1.85598619e-02
-2.08028212e-01 1.08652964e-01 5.92388809e-01 -6.62386239e-01
-1.14565051e+00 3.87109339e-01 -1.92999959e-01 -9.86358404e-01
-1.78610906e-02 -3.74546140e-01 -6.64441645e-01 -4.24733937e-01
5.74184120e-01 3.00497979e-01 3.87334675e-01 -3.71713132e-01
3.72227490e-01 3.50345582e-01 9.35647130e-01 -5.76048911e-01
1.03056812e+00 7.30787337e-01 2.74938017e-01 -8.24681520e-01
-5.10480464e-01 1.08644076e-01 -8.19201291e-01 -2.89241612e-01
8.31010938e-01 -1.11802852e+00 -9.21325564e-01 6.45455897e-01
-1.33627141e+00 5.22345351e-03 -4.05398756e-03 2.72046983e-01
-7.29245067e-01 1.37887284e-01 -4.60894346e-01 -5.97086489e-01
-3.07941556e-01 -1.47885799e+00 1.48080683e+00 2.79068738e-01
-1.38394818e-01 -5.86497188e-01 -1.20577678e-01 3.82846743e-01
3.43211353e-01 5.51549435e-01 5.52353740e-01 3.58667225e-02
-7.00278640e-01 -1.38185635e-01 1.32425487e-01 2.69967526e-01
2.13326290e-01 7.00439289e-02 -1.21952987e+00 -5.53757012e-01
2.47294113e-01 -1.39754593e-01 4.20537025e-01 2.75861710e-01
8.74729335e-01 -5.47768116e-01 -1.42656073e-01 1.14314806e+00
1.13420188e+00 1.46695986e-01 9.30386782e-01 -6.54187724e-02
8.53390932e-01 9.14216697e-01 3.68464172e-01 4.44962531e-01
7.26678222e-02 1.01082373e+00 5.57819724e-01 -6.40542135e-02
-3.45202655e-01 -4.79811043e-01 3.16316992e-01 3.31565261e-01
-1.75169379e-01 -7.90773481e-02 -1.90810502e-01 2.32978866e-01
-1.47125292e+00 -9.19772923e-01 5.20125926e-01 2.29585958e+00
9.32891607e-01 -3.56174737e-01 -8.22022930e-03 -3.07458993e-02
8.31798017e-01 1.92235649e-01 -7.07132459e-01 -1.24965325e-01
-1.01099843e-02 5.08502722e-01 1.76872194e-01 6.24174535e-01
-8.52250218e-01 1.01511919e+00 5.89350748e+00 6.52002990e-01
-1.51078534e+00 -6.19708560e-02 4.68029916e-01 -4.59911615e-01
-1.92809612e-01 -2.58433759e-01 -8.64631414e-01 3.96155417e-01
5.90838432e-01 1.20184705e-01 6.07089818e-01 6.77037358e-01
1.58667058e-01 1.87642813e-01 -1.10245430e+00 1.15090597e+00
6.58223510e-01 -1.32285225e+00 1.14117652e-01 1.20906562e-01
6.94584072e-01 -5.17847121e-01 2.01099351e-01 -1.21680871e-01
-2.46535599e-01 -1.17710960e+00 1.04675519e+00 7.16892302e-01
1.38141358e+00 -9.24640238e-01 2.79409468e-01 1.20939381e-01
-8.54717374e-01 1.25851288e-01 -2.79995680e-01 2.04100341e-01
1.40601829e-01 1.50047317e-01 -5.74603260e-01 4.66238409e-01
4.91199464e-01 3.99554193e-01 -3.84663671e-01 5.82002759e-01
-4.31557298e-01 -5.78701235e-02 -1.94330275e-01 7.21439540e-01
-3.12307000e-01 -2.62341350e-01 6.50678992e-01 6.18153870e-01
3.96553606e-01 2.19194859e-01 -4.03729454e-03 9.56091404e-01
-3.00421774e-01 2.29042526e-02 -5.95727980e-01 3.82066846e-01
4.06945974e-01 1.16584921e+00 -3.14502954e-01 7.21852183e-02
-1.49237335e-01 1.31531632e+00 1.72263458e-01 3.86335075e-01
-8.54304969e-01 -1.32055327e-01 9.35221910e-01 6.36119246e-01
4.46366429e-01 -4.33642082e-02 4.99436520e-02 -1.25496006e+00
2.46529058e-01 -1.05184269e+00 -1.84763938e-01 -8.02152693e-01
-8.60594809e-01 1.00482619e+00 -5.90785071e-02 -1.22545898e+00
-6.32039487e-01 -3.17254126e-01 -6.12375319e-01 1.04561722e+00
-1.44648206e+00 -1.46312082e+00 -3.77653211e-01 9.14276600e-01
5.18464267e-01 -2.88253218e-01 7.63716817e-01 3.84024799e-01
-4.48814660e-01 9.39528406e-01 -2.82236099e-01 6.32120967e-02
1.12468922e+00 -5.40626407e-01 1.66280687e-01 8.16300511e-01
-1.20145932e-01 7.04709649e-01 9.90414083e-01 -6.06745958e-01
-1.60104930e+00 -1.06126189e+00 5.84279478e-01 -4.50367063e-01
4.11264934e-02 -6.48224413e-01 -8.19679499e-01 6.55243039e-01
1.34097174e-01 4.72176135e-01 2.79965311e-01 -5.37908733e-01
-4.07428354e-01 -2.66167343e-01 -1.33773136e+00 6.78213060e-01
1.18109310e+00 -5.14150202e-01 -3.05659950e-01 2.50315905e-01
5.79569340e-01 -9.04822886e-01 -6.03655398e-01 4.65060055e-01
7.98020005e-01 -1.08432245e+00 8.92754853e-01 -2.19037801e-01
3.83697957e-01 -3.88485879e-01 -2.05624457e-02 -1.11697972e+00
-9.83781219e-02 -1.15609610e+00 5.16867824e-03 1.28381538e+00
-1.01739302e-01 -5.23692489e-01 8.71389508e-01 5.69302559e-01
-1.06337607e-01 -6.87527537e-01 -1.00507784e+00 -4.77341264e-01
-1.23166546e-01 1.46985054e-01 7.06805587e-01 6.98951066e-01
-6.36494756e-01 1.81739122e-01 -7.19063044e-01 2.80264527e-01
7.80195355e-01 3.05505954e-02 1.05009437e+00 -1.11281395e+00
-2.25151315e-01 -9.57042798e-02 -4.74833518e-01 -7.49329090e-01
5.91920018e-01 -4.97827768e-01 2.09325347e-02 -9.29949880e-01
-2.27229625e-01 4.31341603e-02 5.18936932e-01 3.50528240e-01
-3.62350745e-03 5.45126796e-01 1.61478102e-01 2.08978578e-01
1.17631659e-01 8.05658698e-01 1.52453494e+00 2.37097144e-01
-3.00055265e-01 -2.55687293e-02 -6.33813381e-01 6.50606871e-01
3.98960024e-01 -2.94838965e-01 -6.09560251e-01 -3.88379365e-01
-1.42526105e-01 3.03152204e-01 3.43729436e-01 -9.22040522e-01
1.68533280e-01 -7.48992711e-02 7.46800065e-01 -3.16383213e-01
7.90009558e-01 -7.33127594e-01 5.62342703e-01 1.65433824e-01
-1.84385553e-01 -6.56750128e-02 1.85706258e-01 3.01101565e-01
-1.47550642e-01 1.37896925e-01 1.21151781e+00 9.57798678e-03
-6.87174127e-02 6.29319787e-01 2.68989235e-01 1.79659389e-02
9.03869390e-01 -3.75942737e-01 -1.48960903e-01 -6.15135014e-01
-6.52222335e-01 -1.47141188e-01 7.63391674e-01 5.20239830e-01
7.12117374e-01 -1.31302512e+00 -9.10778105e-01 9.03789639e-01
-1.25543639e-01 1.92452222e-01 3.01875651e-01 5.87679625e-01
-6.25839472e-01 7.06906095e-02 -4.76397276e-01 -5.41273654e-01
-1.32825410e+00 4.37820375e-01 5.78797936e-01 2.73559391e-01
-5.65788150e-01 7.84230649e-01 6.04810357e-01 -1.59373537e-01
2.96076149e-01 3.74427676e-01 -9.55925137e-02 1.17064789e-01
6.85854077e-01 1.11293592e-01 2.09983915e-01 -1.10514152e+00
-2.00901762e-01 8.79006267e-01 -2.00992048e-01 -2.48537168e-01
1.30689991e+00 -1.27224296e-01 -1.81487605e-01 -8.75813589e-02
1.32920647e+00 3.17293286e-01 -1.75480831e+00 3.74481045e-02
-7.71460176e-01 -8.70587289e-01 -1.62446439e-01 -4.27175343e-01
-1.51284111e+00 7.20790088e-01 5.66026211e-01 -6.74816906e-01
1.25966728e+00 -2.10783780e-01 6.51274145e-01 -2.29537964e-01
3.78089249e-01 -8.83294284e-01 9.03430060e-02 1.37382194e-01
1.38280702e+00 -9.93204474e-01 4.26849425e-02 -7.37765789e-01
-5.29699028e-01 1.11141622e+00 7.26772606e-01 -2.07294077e-01
4.13423508e-01 2.93620765e-01 4.76773717e-02 -7.81359449e-02
-4.85933870e-01 1.18814163e-01 4.32023346e-01 7.22140014e-01
3.02475125e-01 -3.67661089e-01 -6.30424097e-02 1.06492914e-01
-5.49253404e-01 -5.93375340e-02 3.86101514e-01 6.30148113e-01
-3.81530449e-02 -1.07809114e+00 -6.56688631e-01 -6.86545074e-02
-5.07572770e-01 1.25376284e-01 -1.48727506e-01 6.91003144e-01
2.62019515e-01 7.41415322e-01 8.80371109e-02 -1.04723826e-01
4.25784618e-01 8.76798108e-02 9.31049824e-01 -5.76297522e-01
-4.44348574e-01 4.52287823e-01 -2.50898749e-01 -8.07081342e-01
-1.82082489e-01 -6.17460668e-01 -9.72183406e-01 -3.16901058e-01
-1.58730835e-01 -1.69926420e-01 5.34718692e-01 6.95496380e-01
4.72734988e-01 3.20389658e-01 7.99324512e-01 -1.31899810e+00
-3.59086275e-01 -7.77933538e-01 -5.62885106e-01 5.27327418e-01
6.45721853e-01 -8.83431315e-01 -4.53778028e-01 1.79679409e-01] | [12.83283805847168, -0.22356252372264862] |
79a2278b-7f63-4e6c-be9e-42f4ac34555b | semantic-information-marketing-in-the | 2302.11457 | null | https://arxiv.org/abs/2302.11457v2 | https://arxiv.org/pdf/2302.11457v2.pdf | Semantic Information Marketing in The Metaverse: A Learning-Based Contract Theory Framework | In this paper, we address the problem of designing incentive mechanisms by a virtual service provider (VSP) to hire sensing IoT devices to sell their sensing data to help creating and rendering the digital copy of the physical world in the Metaverse. Due to the limited bandwidth, we propose to use semantic extraction algorithms to reduce the delivered data by the sensing IoT devices. Nevertheless, mechanisms to hire sensing IoT devices to share their data with the VSP and then deliver the constructed digital twin to the Metaverse users are vulnerable to adverse selection problem. The adverse selection problem, which is caused by information asymmetry between the system entities, becomes harder to solve when the private information of the different entities are multi-dimensional. We propose a novel iterative contract design and use a new variant of multi-agent reinforcement learning (MARL) to solve the modelled multi-dimensional contract problem. To demonstrate the effectiveness of our algorithm, we conduct extensive simulations and measure several key performance metrics of the contract for the Metaverse. Our results show that our designed iterative contract is able to incentivize the participants to interact truthfully, which maximizes the profit of the VSP with minimal individual rationality (IR) and incentive compatibility (IC) violation rates. Furthermore, the proposed learning-based iterative contract framework has limited access to the private information of the participants, which is to the best of our knowledge, the first of its kind in addressing the problem of adverse selection in incentive mechanisms. | ['Xuemin Shen', 'Dong In Kim', 'Sumei Sun', 'Dusit Niyato', 'Ismail Lotfi'] | 2023-02-22 | null | null | null | null | ['marketing'] | ['miscellaneous'] | [ 7.97840804e-02 6.20102525e-01 -5.09948909e-01 1.68832988e-01
-3.05184960e-01 -7.39591062e-01 2.42270455e-01 -3.92018348e-01
-4.01658535e-01 7.71591008e-01 -6.03544340e-02 -2.28015706e-01
-4.68067467e-01 -9.86270607e-01 -6.40615880e-01 -6.49236679e-01
-9.32602435e-02 4.35545415e-01 2.19041519e-02 -2.86564771e-02
8.61161500e-02 1.35501310e-01 -1.40789795e+00 -2.01805219e-01
8.00038576e-01 1.54930496e+00 3.83059412e-01 3.07637274e-01
8.09739307e-02 5.43970466e-01 -4.97571975e-01 -4.94968444e-01
7.89912701e-01 -1.16617225e-01 -5.72713673e-01 -7.96183292e-03
-7.65547276e-01 -7.29239583e-01 2.64443249e-01 1.02109718e+00
4.87118363e-01 -2.57653773e-01 3.64313513e-01 -2.10927701e+00
-4.94799674e-01 9.30957377e-01 -6.97504401e-01 -2.97012299e-01
1.75947487e-01 -2.76519004e-02 1.00767851e+00 -1.45225823e-01
7.75132716e-01 9.93974209e-01 2.77351797e-01 7.96876371e-01
-7.55908370e-01 -9.26402867e-01 5.69371432e-02 -2.21575201e-02
-9.33708310e-01 -1.00758247e-01 9.27167118e-01 -1.00336440e-01
4.71244007e-01 4.93738741e-01 6.44035399e-01 8.28042507e-01
-9.45753157e-02 7.11510479e-01 1.23249328e+00 -2.25350723e-01
6.37026310e-01 3.01158667e-01 -3.92075837e-01 -3.72878760e-02
6.22139692e-01 3.24902147e-01 -2.37121731e-01 -5.01443624e-01
6.61167622e-01 1.37850404e-01 1.34763002e-01 -5.83992779e-01
-9.90520597e-01 5.63250124e-01 3.09736341e-01 2.22233742e-01
-9.53163743e-01 2.97700167e-01 3.61381099e-02 4.79554057e-01
-7.88881332e-02 5.05622327e-01 -5.18523991e-01 -1.11933388e-01
-2.07971156e-01 2.65049469e-02 9.22889054e-01 1.01802397e+00
2.95370787e-01 -3.90863776e-01 8.81790072e-02 5.96739985e-02
6.04261458e-01 6.20544314e-01 7.91829452e-02 -1.66565359e+00
7.71195292e-01 6.56648815e-01 9.22923207e-01 -8.73257101e-01
-2.37053365e-01 6.23603910e-02 -7.73564756e-01 7.37670437e-02
1.46482974e-01 -6.00830674e-01 -4.64850441e-02 1.82659268e+00
6.17642105e-01 1.53599188e-01 3.52518141e-01 9.05543923e-01
2.22981811e-01 5.87649405e-01 1.25490621e-01 -7.23426163e-01
1.32714224e+00 -2.76443422e-01 -8.87733042e-01 3.06215197e-01
2.72921145e-01 -5.12780070e-01 7.02861607e-01 5.92398793e-02
-1.24688196e+00 1.58541501e-01 -9.60680127e-01 7.04668760e-01
-1.51546329e-01 -2.98488319e-01 6.33486509e-01 9.22875226e-01
-5.86972237e-01 3.16878796e-01 -5.21492958e-01 -1.47853032e-01
6.84773505e-01 7.45204747e-01 2.21804231e-01 2.03654990e-01
-1.30279315e+00 3.40599507e-01 1.34959891e-01 -2.93366820e-01
-8.18935931e-01 -7.35737145e-01 -1.69186041e-01 4.29819785e-02
1.03660071e+00 -8.79562438e-01 1.25555170e+00 -9.68388259e-01
-1.57353783e+00 4.73564535e-01 5.28395116e-01 -3.81104022e-01
8.89335334e-01 2.13564947e-01 -2.15910092e-01 8.43334869e-02
2.46597320e-01 3.87633860e-01 6.36361003e-01 -1.48316383e+00
-8.84384394e-01 -4.10062522e-01 5.09789884e-01 3.36436599e-01
-4.93449748e-01 1.88719202e-02 1.90515146e-01 -3.16730201e-01
-1.14759438e-01 -1.14071786e+00 -2.82641947e-01 -1.50121957e-01
-2.25373298e-01 -4.23730701e-01 9.79864240e-01 -1.96911871e-01
8.11871648e-01 -2.12327528e+00 -1.62544459e-01 2.14123905e-01
1.82674974e-01 6.59814253e-02 3.84005019e-03 4.47521687e-01
5.96393764e-01 5.59039414e-01 1.00957736e-01 -3.34484905e-01
4.73872155e-01 4.39257205e-01 -1.39349058e-01 1.82289690e-01
-3.35130185e-01 8.00207138e-01 -8.55255842e-01 -2.61389971e-01
-1.68580860e-01 -2.38982327e-02 -4.63830799e-01 3.66671205e-01
-3.31566036e-01 3.67602557e-01 -1.16483092e+00 5.69674671e-01
9.09529448e-01 -2.48424858e-01 5.01461446e-01 1.05886415e-01
-1.25969589e-01 1.61301196e-02 -1.56247962e+00 1.29375029e+00
-4.16143566e-01 -4.15643960e-01 6.56955540e-01 -8.21746945e-01
5.28339326e-01 4.56676066e-01 1.12447155e+00 -9.31997061e-01
3.54423136e-01 4.47601229e-01 -2.86061585e-01 -5.90185165e-01
2.68155992e-01 -1.30332842e-01 -4.66088712e-01 1.25117576e+00
-6.60654724e-01 1.57343611e-01 -3.75304431e-01 2.63096839e-01
9.77513433e-01 -2.09550649e-01 2.12174669e-01 4.67790626e-02
1.24718845e-01 -2.77826846e-01 9.05534267e-01 7.84758091e-01
-4.65300679e-01 -3.76254201e-01 6.53524339e-01 -1.84942544e-01
-9.50835645e-01 -8.41555834e-01 4.21054095e-01 6.56733692e-01
8.68035555e-01 1.31730840e-01 -6.64738595e-01 -7.47934639e-01
2.87640810e-01 5.48657298e-01 -1.86828747e-01 8.13876763e-02
-2.36301303e-01 -4.33118075e-01 2.08865866e-01 2.54951656e-01
9.41734552e-01 -1.06826234e+00 -1.34740484e+00 1.51241034e-01
-3.87197375e-01 -1.18286097e+00 -4.48264360e-01 -2.83925384e-01
-5.13478339e-01 -1.06566203e+00 -3.24503511e-01 -2.88422018e-01
5.29509902e-01 3.02387565e-01 4.49707121e-01 -7.13846553e-03
1.36722475e-01 5.21331370e-01 -3.13446403e-01 -7.02927828e-01
-3.25423688e-01 -1.24819189e-01 2.12604687e-01 3.06477368e-01
-5.70766479e-02 -4.75693852e-01 -9.19485271e-01 7.14099824e-01
-9.78414357e-01 -8.11101198e-02 4.81359810e-01 3.95841122e-01
6.30916953e-01 6.47449613e-01 8.89826775e-01 -5.64793110e-01
6.62148416e-01 -6.57378972e-01 -9.88267899e-01 2.48081043e-01
-7.96883166e-01 -5.16338162e-02 3.30868036e-01 -5.87813854e-01
-1.14741397e+00 -7.47500593e-03 6.01894677e-01 -1.52983859e-01
2.02631146e-01 9.19629447e-03 -8.15619230e-01 3.18749361e-02
-1.74712792e-01 -4.70101774e-01 -3.57593931e-02 -4.06446218e-01
4.46587741e-01 1.04627335e+00 7.20192418e-02 -5.45785129e-01
7.43797243e-01 6.82612419e-01 3.09557825e-01 5.23662008e-03
-2.71284670e-01 -1.71439245e-01 1.71952128e-01 -3.60761225e-01
8.09946716e-01 -6.83919311e-01 -1.78524661e+00 3.87175381e-01
-1.10458934e+00 -1.03510514e-01 -5.03808439e-01 3.69257510e-01
-7.89319992e-01 1.63205251e-01 -2.63823450e-01 -1.32955205e+00
-2.38448158e-01 -1.10557532e+00 7.51559913e-01 2.96924740e-01
8.44744369e-02 -4.19603825e-01 -2.57852882e-01 7.46346354e-01
4.81981039e-01 2.88698703e-01 5.51823318e-01 -3.64366323e-01
-1.27679980e+00 -6.92725033e-02 -1.43224210e-01 -2.40699816e-02
2.03554958e-01 -4.77339715e-01 -7.46060848e-01 -3.15437198e-01
2.70045102e-01 -1.03803612e-01 4.20612730e-02 2.78270453e-01
9.71028507e-01 -8.41599524e-01 -5.14884233e-01 4.47300784e-02
1.51023102e+00 4.77724344e-01 4.84745473e-01 4.27933544e-01
2.85165310e-01 9.18172657e-01 1.10137904e+00 9.39945757e-01
8.35344374e-01 7.62732983e-01 9.77921307e-01 1.75592542e-01
3.70642781e-01 -4.25177932e-01 3.30944479e-01 2.28629202e-01
-1.49621382e-01 -2.82284409e-01 -3.33900422e-01 3.74310583e-01
-2.21647573e+00 -9.64502931e-01 2.33462125e-01 2.23420596e+00
3.09648156e-01 -3.95256132e-02 4.48178172e-01 2.40116686e-01
8.21307242e-01 -2.68275797e-01 -8.85404527e-01 -4.07753199e-01
-4.52763811e-02 -3.61841381e-01 1.00379884e+00 1.01826251e-01
-6.13655686e-01 4.06781733e-01 5.55993366e+00 4.62903023e-01
-5.67957520e-01 5.87574184e-01 5.49339116e-01 -1.27513900e-01
-6.93119109e-01 3.32951397e-01 -2.91307777e-01 6.99506581e-01
7.57477045e-01 -4.03276563e-01 8.68228614e-01 6.77619159e-01
6.11422896e-01 -1.36192679e-01 -7.87971497e-01 9.52848136e-01
-6.57947421e-01 -1.26254976e+00 -5.11540055e-01 5.67133963e-01
9.78536248e-01 -2.13228524e-01 7.88376033e-02 -2.41347298e-01
4.53563899e-01 -3.77590865e-01 7.66609132e-01 5.52494586e-01
4.21786755e-01 -9.04801011e-01 6.42255962e-01 5.64416051e-01
-1.18736351e+00 -9.93495822e-01 -2.63030324e-02 -2.16305479e-01
3.55410486e-01 5.65725207e-01 -4.47339326e-01 6.21993840e-01
6.28319561e-01 -1.27727883e-02 2.65701175e-01 6.94465935e-01
-1.52521003e-02 -5.60060963e-02 -4.15887982e-01 -2.92862236e-01
-1.14014946e-01 -2.17406109e-01 6.03788853e-01 -3.89433466e-02
5.07946908e-01 4.41417754e-01 2.03450024e-01 1.13087606e+00
-5.58135569e-01 8.84148479e-03 -6.38991296e-01 -2.78475285e-01
9.60824370e-01 1.11631155e+00 -5.60508847e-01 -1.92600012e-01
-2.82366037e-01 6.29431307e-01 -3.53433460e-01 2.86599696e-01
-7.62690961e-01 -9.67946500e-02 5.93045413e-01 1.82232454e-01
3.24107081e-01 2.88419276e-01 -6.21600866e-01 -7.80228436e-01
4.70309317e-01 -5.55201590e-01 5.72705150e-01 -7.32464373e-01
-1.14566004e+00 -7.10720103e-03 -1.24162175e-01 -1.09416282e+00
-1.73020214e-01 4.76893783e-02 -3.83701175e-01 4.49832857e-01
-1.69446981e+00 -1.04055333e+00 6.18004724e-02 7.05896080e-01
-2.03998685e-01 -2.36646548e-01 4.65874672e-01 3.26316863e-01
-2.43626878e-01 3.42739016e-01 -6.16835132e-02 -3.94794554e-01
8.78462642e-02 -9.32005167e-01 -1.74603641e-01 4.83545393e-01
-4.88694161e-01 2.39118293e-01 4.59352881e-01 -8.80813003e-01
-1.82782340e+00 -7.82827795e-01 8.13893080e-01 -1.90034658e-01
6.62459195e-01 -3.14475268e-01 -8.73125903e-03 3.10537577e-01
1.57625247e-02 -1.71270058e-01 4.35078502e-01 -5.04199326e-01
-3.47544462e-03 -5.79315364e-01 -1.92407811e+00 4.34825033e-01
1.30206633e+00 -2.85260469e-01 -1.45854875e-01 1.63834661e-01
1.06620252e+00 2.52533406e-01 -1.07215154e+00 4.67333287e-01
5.82665741e-01 -6.63064599e-01 7.21758068e-01 -2.51405835e-01
-1.03114456e-01 -3.23677033e-01 -3.39566737e-01 -7.96908617e-01
2.59602219e-01 -1.24393415e+00 -1.33873016e-01 1.52761817e+00
1.85088933e-01 -1.03813052e+00 8.85230243e-01 1.12898743e+00
4.25537199e-01 -2.09932640e-01 -1.24064970e+00 -8.58985484e-01
-1.11576617e-01 -2.54902393e-01 1.43047655e+00 7.80050039e-01
1.81089506e-01 -1.66750520e-01 -4.43626702e-01 3.66926223e-01
1.15870225e+00 4.26025897e-01 4.78498697e-01 -1.17472422e+00
-3.78777087e-01 -2.49210030e-01 1.88098431e-01 -4.88283008e-01
-3.00812516e-02 -4.27730620e-01 -2.17516094e-01 -1.37595677e+00
2.44226873e-01 -1.22542024e+00 -5.04616201e-01 3.64722043e-01
5.30132353e-01 -1.77608535e-01 6.48280561e-01 5.21302819e-01
-6.88850820e-01 4.13274199e-01 1.43953395e+00 -1.50536820e-01
-4.44302082e-01 4.65136439e-01 -9.88446414e-01 2.99444705e-01
1.03073609e+00 -7.09184289e-01 -6.83361471e-01 -1.54369310e-01
6.10033572e-01 5.58295846e-01 4.26003337e-01 -3.89575183e-01
1.77475542e-01 -6.65523052e-01 -4.69508410e-01 -4.12744105e-01
8.82017538e-02 -1.43835163e+00 8.11039507e-01 7.35298753e-01
-1.48458451e-01 -1.39595583e-01 -4.73674625e-01 6.45903945e-01
4.45842803e-01 -3.46416421e-02 3.92626464e-01 -1.98231146e-01
-1.64373249e-01 2.93047220e-01 -3.41573924e-01 -3.39360267e-01
1.45826530e+00 1.41895879e-02 -3.35053742e-01 -5.46141565e-01
-4.61173892e-01 6.01925194e-01 5.47077596e-01 4.69721258e-01
1.93191975e-01 -1.37456632e+00 -2.09256589e-01 -1.99453771e-01
-1.46246016e-01 -1.89099908e-01 1.17424138e-01 7.06068873e-01
3.39743704e-01 2.36912772e-01 -2.65771568e-01 -1.23324685e-01
-9.94158149e-01 8.33272338e-01 2.49820307e-01 -3.73766273e-01
-1.96705863e-01 2.05143541e-01 -1.09406738e-02 -2.03966707e-01
3.64651769e-01 -1.21545158e-01 1.01224095e-01 1.28281295e-01
1.36300072e-01 6.92173839e-01 -4.15083915e-01 -3.65910709e-01
-4.03201371e-01 4.16507572e-01 5.11844218e-01 -3.93447101e-01
1.28027272e+00 -7.16511786e-01 2.91130301e-02 -1.45604447e-01
7.25337446e-01 -1.36672318e-01 -1.22998416e+00 -4.09512892e-02
-6.37347251e-02 -4.27199900e-01 -4.79482003e-02 -9.43178535e-01
-1.31650233e+00 1.33636028e-01 6.00922227e-01 6.85907662e-01
1.30590630e+00 3.76357920e-02 1.08387053e+00 1.16957627e-01
1.04053831e+00 -1.63738465e+00 1.58941880e-01 -4.33551490e-01
4.25351441e-01 -9.94752645e-01 -2.87104279e-01 -5.86656570e-01
-8.25364053e-01 3.01565170e-01 3.41692150e-01 2.03048006e-01
7.86408484e-01 3.23393524e-01 -9.20843408e-02 -1.37861803e-01
-5.63763201e-01 -1.38889328e-01 -6.25846148e-01 8.99583399e-01
-6.03496253e-01 7.28026748e-01 -6.17074311e-01 9.74563658e-01
1.37759209e-01 3.41337502e-01 8.07848752e-01 1.09986830e+00
-1.68589249e-01 -1.58547127e+00 -3.65906686e-01 2.13560894e-01
-4.46542591e-01 6.20445013e-01 -4.01473343e-01 5.00057220e-01
5.27823627e-01 1.41261363e+00 -1.27220795e-01 -7.90303946e-02
5.29983699e-01 -4.35705543e-01 1.87112883e-01 7.04319924e-02
-4.18069631e-01 1.14417911e-01 1.26707796e-02 -6.51661038e-01
-8.22581768e-01 -7.67086267e-01 -1.49203372e+00 -3.93088520e-01
-2.15225264e-01 2.36189544e-01 1.02674198e+00 8.79994154e-01
6.54080808e-01 1.66703761e-01 1.38302767e+00 -2.63345510e-01
-7.88721681e-01 -2.93386608e-01 -8.40685844e-01 5.65986037e-01
1.24410570e-01 -7.49271512e-01 -3.83491904e-01 -5.11493981e-01] | [5.426929473876953, 2.6208176612854004] |
51a72896-38a6-40fd-ad17-ccd203945e71 | egocentric-hierarchical-visual-semantics | 2305.05422 | null | https://arxiv.org/abs/2305.05422v1 | https://arxiv.org/pdf/2305.05422v1.pdf | Egocentric Hierarchical Visual Semantics | We are interested in aligning how people think about objects and what machines perceive, meaning by this the fact that object recognition, as performed by a machine, should follow a process which resembles that followed by humans when thinking of an object associated with a certain concept. The ultimate goal is to build systems which can meaningfully interact with their users, describing what they perceive in the users' own terms. As from the field of Lexical Semantics, humans organize the meaning of words in hierarchies where the meaning of, e.g., a noun, is defined in terms of the meaning of a more general noun, its genus, and of one or more differentiating properties, its differentia. The main tenet of this paper is that object recognition should implement a hierarchical process which follows the hierarchical semantic structure used to define the meaning of words. We achieve this goal by implementing an algorithm which, for any object, recursively recognizes its visual genus and its visual differentia. In other words, the recognition of an object is decomposed in a sequence of steps where the locally relevant visual features are recognized. This paper presents the algorithm and a first evaluation. | ['Fausto Giunchiglia', 'Andrea Passerini', 'Andrea Bontempelli', 'Luca Erculiani'] | 2023-05-09 | null | null | null | null | ['object-recognition'] | ['computer-vision'] | [ 3.98363620e-01 -1.54948726e-01 -5.46926036e-02 -7.35277116e-01
4.31439579e-01 -8.34527075e-01 9.40188229e-01 5.02210796e-01
-3.98481905e-01 2.43635587e-02 4.05513495e-01 -3.70222270e-01
-1.03622824e-01 -9.58029091e-01 -5.80267347e-02 -6.13412023e-01
2.85474867e-01 4.55434710e-01 3.65720391e-01 -3.08565706e-01
5.49792647e-01 6.92007780e-01 -1.97517025e+00 4.71346080e-01
1.84008211e-01 1.00561678e+00 3.41338307e-01 5.96533060e-01
-7.29640901e-01 6.44134104e-01 -6.55152321e-01 -1.17553145e-01
-1.59639463e-01 -5.78570068e-01 -1.40144718e+00 7.29641855e-01
2.73173124e-01 3.04250807e-01 5.25767207e-01 1.31101942e+00
-3.82967710e-01 2.21210644e-01 1.03195167e+00 -1.10409403e+00
-8.22348893e-01 3.09219331e-01 -7.11472854e-02 -1.46236375e-01
5.95502138e-01 -2.86227435e-01 1.32139671e+00 -7.68117964e-01
5.57278931e-01 1.67248058e+00 1.40059635e-01 3.98180068e-01
-1.44379771e+00 1.58824623e-01 1.68037549e-01 7.06095472e-02
-1.30608463e+00 -1.09177288e-02 4.38850880e-01 -9.12510633e-01
8.12236071e-01 5.61795235e-01 8.53072345e-01 3.00070643e-01
1.42577752e-01 4.30081695e-01 8.14983904e-01 -9.19834614e-01
4.77652252e-01 3.93270135e-01 7.62408495e-01 4.31346893e-01
2.79466957e-01 -3.62962365e-01 -1.72999382e-01 6.64808229e-02
5.55940092e-01 6.84983283e-02 4.44533862e-02 -6.10183597e-01
-1.04885209e+00 7.04056680e-01 4.98131990e-01 1.11340940e+00
-3.57426822e-01 9.53542739e-02 3.52831960e-01 2.53260434e-01
3.72485034e-02 5.46878457e-01 -1.00023434e-01 1.19397514e-01
-4.98944461e-01 -1.41728118e-01 1.00851655e+00 7.89604664e-01
7.45780706e-01 -2.53951132e-01 3.70962858e-01 5.76635301e-01
7.78396845e-01 2.23692268e-01 6.14753723e-01 -7.49386728e-01
-4.56281304e-01 1.26208580e+00 4.84798662e-03 -1.00213337e+00
-3.24290484e-01 -1.71955734e-01 -4.14186776e-01 5.78120708e-01
3.60010922e-01 6.84336722e-01 -8.66306484e-01 1.66414273e+00
3.50989819e-01 -5.29422402e-01 3.33116174e-01 9.04433310e-01
9.59083140e-01 6.37589455e-01 4.35135871e-01 -2.12058887e-01
2.00724864e+00 -4.35413241e-01 -6.66161001e-01 -8.64217654e-02
7.06258357e-01 -8.16536546e-01 1.37160301e+00 4.11981285e-01
-7.89281249e-01 -7.76644051e-01 -1.06532347e+00 -3.15713227e-01
-9.06498492e-01 -2.59924773e-02 6.30974472e-01 6.63553178e-01
-1.13303018e+00 2.17485189e-01 -4.22299087e-01 -1.01348412e+00
-2.69140363e-01 1.75042391e-01 -2.42731065e-01 4.91353750e-01
-7.78193772e-01 1.10642636e+00 8.00074935e-01 1.75858277e-03
-4.28154916e-01 -1.67549904e-02 -9.10747468e-01 1.43421113e-01
2.57659525e-01 -6.39410615e-01 1.24939466e+00 -1.64111936e+00
-8.52502525e-01 1.60896325e+00 -3.02584946e-01 -1.78036809e-01
-1.86217755e-01 8.28032717e-02 -5.71586132e-01 8.35061520e-02
2.07816169e-01 6.07080698e-01 7.76955187e-01 -1.65231252e+00
-8.17840099e-01 -6.62353396e-01 4.68810290e-01 2.58894533e-01
-2.57047057e-01 3.43667150e-01 -3.89054060e-01 -4.90095228e-01
6.64801776e-01 -6.68625355e-01 -2.16474552e-02 4.86030988e-02
-1.68566197e-01 -6.55263543e-01 8.92434418e-01 -2.37933487e-01
1.28019452e+00 -2.51273274e+00 2.33527854e-01 7.13524818e-01
6.12445831e-01 -4.17505577e-02 1.11376964e-01 5.05592883e-01
-2.22947404e-01 2.38117620e-01 -1.68392837e-01 1.40778095e-01
2.27624595e-01 5.42344809e-01 -3.23385566e-01 1.93236187e-01
-2.43346281e-02 5.45015991e-01 -8.43781412e-01 -5.65470636e-01
2.30166242e-01 3.52084935e-01 -2.19777361e-01 -8.44863243e-03
-1.67391345e-01 -9.15822759e-02 -7.50398159e-01 2.74143130e-01
1.47268564e-01 -4.71332431e-01 6.01533234e-01 -2.29819924e-01
-3.82742494e-01 1.91625729e-01 -1.39170039e+00 9.34478283e-01
-2.67461896e-01 5.93506217e-01 4.46816757e-02 -9.71079528e-01
1.25070822e+00 1.86318815e-01 1.00115895e-01 -4.33743060e-01
1.99204415e-01 3.35180849e-01 1.53794810e-01 -6.57204628e-01
6.41278446e-01 -5.34312069e-01 -1.12539895e-01 5.26589096e-01
-2.41835967e-01 -2.31800511e-01 2.80127883e-01 2.01738492e-01
5.78780055e-01 -5.19485883e-02 1.03825307e+00 -6.72971070e-01
8.77873540e-01 1.96966499e-01 1.18255481e-01 4.99710411e-01
5.57772182e-02 1.46689788e-01 5.30255139e-01 -7.23589063e-01
-9.51378286e-01 -1.29095650e+00 -2.75805682e-01 1.38836062e+00
3.30687732e-01 -4.95482802e-01 -7.63617456e-01 -1.24743298e-01
-1.30035385e-01 8.15170050e-01 -6.44209206e-01 3.80834602e-02
-3.12311739e-01 -1.38997331e-01 -2.82218261e-03 3.38572025e-01
2.44200394e-01 -1.39628756e+00 -1.34002256e+00 7.09599331e-02
2.29865387e-01 -7.16017723e-01 -7.13517964e-02 1.03474468e-01
-7.32549727e-01 -8.63032699e-01 -1.57250449e-01 -1.19598579e+00
9.68118548e-01 4.24368441e-01 1.33538783e+00 5.78714132e-01
-1.88828185e-01 5.73758602e-01 -6.98263466e-01 -3.52769762e-01
-6.33958519e-01 -3.29355210e-01 -1.13529703e-02 2.54156560e-01
7.08089411e-01 -3.00651550e-01 -1.19587071e-01 1.45513833e-01
-1.46256614e+00 2.41639167e-01 4.08013791e-01 2.83514023e-01
5.39467275e-01 2.10529249e-02 -2.73042694e-02 -7.65747190e-01
4.87589180e-01 -1.00110605e-01 -2.43121564e-01 7.20500886e-01
-3.31730276e-01 3.22907001e-01 4.29606408e-01 -2.99866915e-01
-8.44784975e-01 6.06902093e-02 2.54042178e-01 2.99781531e-01
-5.10563612e-01 5.02319515e-01 -6.18899941e-01 2.38149479e-01
7.20194280e-01 2.41768882e-01 -5.06573319e-02 -3.32446039e-01
5.78842282e-01 9.32809412e-01 5.05032301e-01 -6.07089520e-01
4.31749731e-01 5.00366986e-01 2.43701234e-01 -1.33707225e+00
-7.20015168e-01 -9.16625738e-01 -1.00676286e+00 -5.00255823e-01
1.22150886e+00 -2.70738125e-01 -8.36921573e-01 1.17784142e-01
-1.16831064e+00 2.87880510e-01 -5.08220494e-01 3.36658806e-01
-5.49894452e-01 3.80839288e-01 7.39124045e-02 -8.67933393e-01
6.14826381e-02 -8.59275579e-01 9.69647348e-01 1.84333205e-01
-8.08876395e-01 -1.09196699e+00 -2.06056014e-01 1.14495903e-01
1.38369858e-01 -1.15558449e-02 1.26938808e+00 -9.82606947e-01
-1.40262783e-01 4.76019271e-02 -2.49834239e-01 4.09734666e-01
4.72540736e-01 5.68073951e-02 -6.18907869e-01 -4.97979634e-02
4.67865974e-01 4.91625816e-02 4.69534218e-01 -3.03145852e-02
7.53076494e-01 -2.52167910e-01 -2.31365696e-01 1.40198201e-01
1.69625986e+00 7.17551410e-01 4.09039408e-01 3.04429799e-01
6.15005672e-01 1.08185184e+00 5.17595351e-01 1.68551028e-01
8.29412788e-02 7.32505679e-01 1.67893723e-01 -1.18079320e-01
9.42446887e-02 1.03254296e-01 5.08344881e-02 6.18092716e-01
1.32076340e-02 5.33200940e-03 -1.14501095e+00 4.41629320e-01
-1.78292120e+00 -8.54348004e-01 -4.99208450e-01 2.14398766e+00
6.72819853e-01 2.07011670e-01 2.04116926e-01 2.40084529e-01
7.22788215e-01 3.68502270e-03 -1.00935303e-01 -8.82113993e-01
8.31282288e-02 -8.65003243e-02 -1.55294582e-01 7.81465888e-01
-7.77167320e-01 1.06757092e+00 6.16043568e+00 5.26842713e-01
-1.14626348e+00 -1.99708477e-01 2.85514772e-01 5.73280871e-01
-4.16876078e-01 1.94221824e-01 -5.77489913e-01 -2.28688475e-02
4.99777496e-01 -3.33212405e-01 2.07234070e-01 7.59735286e-01
2.75057346e-01 -4.59661573e-01 -1.35046470e+00 7.50123560e-01
3.74533355e-01 -1.04149151e+00 6.34375215e-01 -2.41488889e-02
2.93271039e-02 -8.78481805e-01 -1.74718902e-01 -2.29902148e-01
7.39410818e-02 -1.05309486e+00 1.07071102e+00 5.53349972e-01
4.04108077e-01 -3.47199142e-01 4.12482083e-01 1.81443393e-01
-1.43182373e+00 1.07046045e-01 -2.55099207e-01 -4.98177707e-01
-7.11290985e-02 7.55923390e-02 -7.62681663e-01 2.54725784e-01
4.73726749e-01 4.03782010e-01 -6.20131195e-01 8.67894232e-01
-3.60886931e-01 2.33898833e-01 -1.25589684e-01 -5.93890250e-01
3.71567160e-01 -4.76603150e-01 4.66431409e-01 1.48434031e+00
4.75699604e-02 4.04021591e-01 3.80523026e-01 9.00629163e-01
4.36586291e-01 5.33019483e-01 -6.40538275e-01 1.02917412e-02
3.16823065e-01 1.03147388e+00 -1.28641546e+00 -7.50492275e-01
-3.98421466e-01 7.34888017e-01 -3.26945603e-01 2.80719012e-01
-3.80656272e-01 -4.46752101e-01 5.47666430e-01 2.16048419e-01
-8.80800840e-03 -2.89998978e-01 -4.71121013e-01 -7.09145904e-01
1.52316943e-01 -7.27418840e-01 4.02309537e-01 -1.10912585e+00
-1.09302843e+00 7.29918718e-01 2.57537335e-01 -1.18000698e+00
-1.44723520e-01 -1.08649361e+00 -4.06446218e-01 9.52777803e-01
-5.54908335e-01 -1.21894109e+00 -2.18996331e-01 4.75522637e-01
4.61684465e-01 1.74882978e-01 9.56474543e-01 -4.13510710e-01
9.86025035e-02 -2.37316310e-01 -3.45583290e-01 1.33869067e-01
4.28807847e-02 -1.42920434e+00 7.61926398e-02 7.03424573e-01
5.47918439e-01 9.68256116e-01 1.14085925e+00 -5.08692086e-01
-7.84010768e-01 -3.47493678e-01 1.66984987e+00 -2.13459283e-01
8.82683754e-01 -3.52226555e-01 -1.02081776e+00 5.39938450e-01
1.08077772e-01 -5.02665877e-01 7.03412354e-01 2.23689109e-01
-4.80721295e-01 -8.31715018e-02 -9.61210549e-01 7.08752692e-01
8.03525984e-01 -6.66307092e-01 -1.39039969e+00 1.68389812e-01
5.26635587e-01 2.20934182e-01 -6.25193000e-01 -2.32686754e-03
6.39389455e-01 -9.19171393e-01 8.23988557e-01 -8.82493138e-01
-7.19099790e-02 -7.82454133e-01 -4.83234704e-01 -9.41212714e-01
-5.15662789e-01 -2.31343489e-02 5.83445787e-01 1.08751523e+00
3.99230331e-01 -5.89531183e-01 4.77656990e-01 5.21385133e-01
9.33526531e-02 -8.23914558e-02 -8.34421217e-01 -8.14199567e-01
-2.29347229e-01 -5.36417365e-01 4.99704331e-01 9.73613024e-01
4.71305043e-01 7.56866336e-01 2.62890220e-01 1.25728725e-02
3.52081686e-01 2.56730378e-01 2.81480819e-01 -1.62782800e+00
-5.49246259e-02 -5.79153419e-01 -9.73484635e-01 -9.72232878e-01
-4.66517918e-02 -8.82714331e-01 1.81153521e-01 -1.73635674e+00
1.76742926e-01 -1.26011902e-02 -1.54555768e-01 4.20285195e-01
1.91134095e-01 4.87528481e-02 5.38010836e-01 5.27054071e-01
-6.34791851e-01 -4.77950871e-02 9.91981924e-01 8.39450434e-02
-2.42958516e-01 -1.95451587e-01 -6.29370451e-01 1.10183454e+00
7.43303597e-01 -3.17441374e-01 -3.83422911e-01 -1.79596275e-01
6.46938384e-01 -3.07305038e-01 4.59734261e-01 -1.01200020e+00
2.03021541e-01 -3.76636028e-01 1.29909545e-01 -2.29042917e-01
1.67827040e-01 -1.31155729e+00 2.93656945e-01 7.25514233e-01
-4.76808012e-01 3.27347159e-01 -1.61185667e-01 -4.32031378e-02
-4.14227873e-01 -7.22957432e-01 7.33304024e-01 -2.29278237e-01
-1.41345179e+00 -5.75989246e-01 -7.99006283e-01 -2.29924977e-01
1.08380389e+00 -7.76362240e-01 -9.44551006e-02 -1.94404051e-01
-1.13312972e+00 -5.41278385e-02 7.14006901e-01 5.20690858e-01
6.96876764e-01 -1.32298517e+00 -2.56221831e-01 2.29157686e-01
5.08033812e-01 -5.61004162e-01 -3.42104405e-01 4.26592052e-01
-6.61511421e-01 3.15617949e-01 -3.81299734e-01 -6.44398093e-01
-1.80898976e+00 7.36819327e-01 3.25031787e-01 1.95683435e-01
-4.62409616e-01 5.34914613e-01 7.65801549e-01 -7.40342401e-03
1.43762395e-01 -6.31971657e-01 -7.91155457e-01 2.60639995e-01
7.16279805e-01 4.37521935e-02 -3.22601110e-01 -1.23817706e+00
-4.56284970e-01 9.58731294e-01 2.34291986e-01 -3.33318621e-01
9.19758976e-01 -8.95127729e-02 -8.82412553e-01 9.72209573e-01
1.06291401e+00 -1.86413899e-01 -4.17546928e-01 -2.02682927e-01
5.50457597e-01 -2.87851989e-01 -2.83589453e-01 -7.13306785e-01
-4.49084729e-01 6.69435382e-01 5.76142251e-01 1.02241194e+00
1.26870263e+00 6.12808883e-01 -2.93701235e-02 4.68831450e-01
3.20780337e-01 -8.19713235e-01 5.91653958e-02 6.40579820e-01
1.04974437e+00 -7.14324951e-01 -1.31864458e-01 -7.63313711e-01
-6.43174112e-01 1.52579105e+00 2.67954767e-01 9.08168480e-02
7.59455740e-01 -4.46146242e-02 2.22039074e-01 -6.67946637e-01
-5.13480902e-01 -5.73684156e-01 6.07823849e-01 4.12011266e-01
5.39429545e-01 4.09177750e-01 -7.59420872e-01 1.40758350e-01
-3.03581059e-01 -1.54409409e-01 3.54044259e-01 1.05446863e+00
-1.25271869e+00 -1.14305842e+00 -6.14715815e-01 1.40167564e-01
-2.62097150e-01 -4.89942543e-03 -1.03857672e+00 8.17832172e-01
5.83910763e-01 1.04132724e+00 4.70834613e-01 -3.07318777e-01
5.22115767e-01 1.40406325e-01 3.10260028e-01 -1.01944947e+00
-6.96344852e-01 -4.76075821e-02 7.15140104e-02 -2.37009645e-01
-8.28080714e-01 -6.41300559e-01 -1.75202274e+00 -1.66346967e-01
2.94553220e-01 3.89768511e-01 5.75705945e-01 1.14363611e+00
-4.01248604e-01 2.21436918e-01 2.77990431e-01 -3.81563842e-01
-2.51743972e-01 -6.46843731e-01 -7.09597468e-01 8.28168094e-01
1.61303371e-01 -4.24215674e-01 -2.81597108e-01 5.54282367e-01] | [10.157367706298828, 8.836380004882812] |
57d8a8cd-a0ee-4d5f-a574-4c3dc3058fc7 | reprogramming-pretrained-language-models-for | 2301.02120 | null | https://arxiv.org/abs/2301.02120v1 | https://arxiv.org/pdf/2301.02120v1.pdf | Reprogramming Pretrained Language Models for Protein Sequence Representation Learning | Machine Learning-guided solutions for protein learning tasks have made significant headway in recent years. However, success in scientific discovery tasks is limited by the accessibility of well-defined and labeled in-domain data. To tackle the low-data constraint, recent adaptions of deep learning models pretrained on millions of protein sequences have shown promise; however, the construction of such domain-specific large-scale model is computationally expensive. Here, we propose Representation Learning via Dictionary Learning (R2DL), an end-to-end representation learning framework in which we reprogram deep models for alternate-domain tasks that can perform well on protein property prediction with significantly fewer training samples. R2DL reprograms a pretrained English language model to learn the embeddings of protein sequences, by learning a sparse linear mapping between English and protein sequence vocabulary embeddings. Our model can attain better accuracy and significantly improve the data efficiency by up to $10^5$ times over the baselines set by pretrained and standard supervised methods. To this end, we reprogram an off-the-shelf pre-trained English language transformer and benchmark it on a set of protein physicochemical prediction tasks (secondary structure, stability, homology, stability) as well as on a biomedically relevant set of protein function prediction tasks (antimicrobial, toxicity, antibody affinity). | ['Payel Das', 'Pin-Yu Chen', 'Ria Vinod'] | 2023-01-05 | null | null | null | null | ['protein-function-prediction'] | ['medical'] | [ 4.97492671e-01 -4.89576831e-02 -2.32107699e-01 -5.04703164e-01
-9.26165998e-01 -5.49411774e-01 2.69805253e-01 6.23015761e-01
-6.99308395e-01 1.03865516e+00 1.95025995e-01 -6.18558109e-01
2.06713855e-01 -5.56298256e-01 -1.17203116e+00 -8.63325119e-01
-5.89114353e-02 6.51431441e-01 -8.63812715e-02 -2.99416840e-01
6.15568236e-02 4.90749389e-01 -1.27833402e+00 3.47246677e-01
8.30910802e-01 7.54679739e-01 5.48497021e-01 3.52140903e-01
-2.53742427e-01 6.15471721e-01 -1.19474351e-01 -2.72698998e-01
-3.58038992e-02 -2.71220952e-01 -9.29160297e-01 -2.98527300e-01
5.19326366e-02 -5.52888960e-02 -2.41919011e-01 7.86728621e-01
7.00003862e-01 1.58614963e-02 7.44846225e-01 -6.60478532e-01
-1.22762990e+00 1.66958421e-01 -4.19812530e-01 1.03998087e-01
3.93478811e-01 2.31508732e-01 1.18494666e+00 -1.28411412e+00
9.02133703e-01 9.72178280e-01 6.50944054e-01 6.70794129e-01
-1.72057867e+00 -5.00753999e-01 -5.55983698e-03 1.91209003e-01
-1.26955235e+00 -2.60334253e-01 3.98649305e-01 -4.76777971e-01
1.81975937e+00 -2.43130878e-01 2.72635728e-01 1.42768145e+00
4.00725096e-01 5.89095235e-01 7.59777784e-01 -2.02524096e-01
2.13153511e-01 -6.87672719e-02 1.57314286e-01 7.92819738e-01
1.34418041e-01 7.60363042e-02 -5.29222727e-01 -5.62582374e-01
4.70355123e-01 3.85948628e-01 -3.39301258e-01 -8.15827847e-01
-1.22478819e+00 1.10374641e+00 3.69528532e-01 9.30840075e-02
-4.33179528e-01 -9.41882581e-02 6.80621266e-01 5.37871957e-01
5.77144682e-01 6.97757304e-01 -1.27671981e+00 -8.00276250e-02
-4.17365015e-01 2.53643394e-01 7.96617925e-01 7.80572057e-01
8.06458771e-01 -2.17534944e-01 2.16416389e-01 1.02687478e+00
2.54396707e-01 4.02282417e-01 7.98157215e-01 -1.90472513e-01
1.37545049e-01 5.96463025e-01 1.18254676e-01 -6.07999265e-01
-4.74631280e-01 -1.52485967e-01 -8.22268307e-01 -1.22006439e-01
3.23249102e-01 1.55536428e-01 -9.16503668e-01 1.82219028e+00
3.12743336e-01 1.85134858e-01 4.60448831e-01 8.49911273e-01
7.74407148e-01 1.03867865e+00 4.45698857e-01 -2.14930534e-01
1.52507126e+00 -7.85818279e-01 -3.88242126e-01 -1.09477006e-02
1.04618990e+00 -6.64864182e-01 1.28589368e+00 4.31352824e-01
-6.43556356e-01 -5.48508942e-01 -1.13537443e+00 -4.39276457e-01
-6.25092626e-01 -8.53998289e-02 7.21755326e-01 2.11387202e-01
-5.58026791e-01 6.77531123e-01 -8.74226809e-01 -4.15993363e-01
5.07121861e-01 5.44995964e-01 -9.15784359e-01 -3.62481594e-01
-1.24386251e+00 1.06025791e+00 4.18279439e-01 -5.37030280e-01
-1.09783709e+00 -1.06583679e+00 -1.03034294e+00 1.70654152e-02
9.56071392e-02 -4.61844206e-01 8.00020695e-01 -7.45015740e-01
-1.46986723e+00 1.21922576e+00 -1.93969250e-01 -6.72611773e-01
-2.66301394e-01 -4.07310128e-01 -4.52883601e-01 1.28998561e-02
-7.44886771e-02 6.23350322e-01 5.51053286e-01 -6.87845469e-01
-3.61242115e-01 -2.26984009e-01 -1.68181315e-01 -6.15843013e-02
-3.58586550e-01 -2.46210191e-02 -6.45238981e-02 -7.14982927e-01
-4.16236252e-01 -6.96770728e-01 -5.83602428e-01 9.89544094e-02
1.59262642e-01 -5.38686633e-01 4.52589959e-01 -6.34787261e-01
8.12038004e-01 -2.18091774e+00 4.97867197e-01 -7.59275034e-02
2.88563937e-01 4.87630099e-01 -6.47906423e-01 5.87405086e-01
-4.47192967e-01 -2.13231906e-01 -4.39046502e-01 3.36069651e-02
-2.01936085e-02 3.17275435e-01 -3.83414984e-01 7.16451764e-01
5.34676015e-01 9.50756848e-01 -9.50225949e-01 -4.04607728e-02
9.04761031e-02 6.75602615e-01 -7.42056966e-01 6.55286610e-01
-5.42735159e-01 3.00505161e-01 -4.08097237e-01 6.40136600e-01
5.91715276e-01 -7.18413711e-01 4.62532133e-01 -2.68415540e-01
1.58971056e-01 4.83097345e-01 -4.97108817e-01 2.19344640e+00
-3.77609015e-01 2.57658809e-01 -1.54390633e-01 -1.47950757e+00
1.06232429e+00 2.28077084e-01 7.96253383e-01 -6.34907305e-01
-6.52660877e-02 3.39018732e-01 3.71825993e-02 -4.75401700e-01
1.58306081e-02 -3.09146285e-01 1.43754734e-02 3.88877988e-01
4.42686737e-01 3.04645747e-01 -1.48692518e-01 7.65349045e-02
1.31527829e+00 4.36953962e-01 6.14869297e-01 -3.48088652e-01
6.08881414e-01 1.85648978e-01 5.87145448e-01 1.41855493e-01
-5.87109290e-02 3.51814628e-01 2.71654904e-01 -8.59537482e-01
-1.30480182e+00 -8.44437420e-01 -3.74467134e-01 1.76860178e+00
-9.72536579e-02 -5.73097408e-01 -4.61326867e-01 -8.46628845e-01
3.35908204e-01 2.52586037e-01 -4.62584645e-01 -4.50861365e-01
-6.10435903e-01 -1.04334414e+00 3.90811741e-01 5.08294106e-01
-1.47673100e-01 -1.22836375e+00 -2.42626339e-01 6.08870208e-01
2.53814071e-01 -9.68086064e-01 -5.00780284e-01 9.32151020e-01
-7.03842223e-01 -1.14281106e+00 -8.22394252e-01 -1.32591510e+00
6.16530061e-01 8.87355208e-02 1.24621677e+00 -1.80322111e-01
-5.28595686e-01 -1.88556269e-01 -3.99044961e-01 -3.51045698e-01
-3.96283478e-01 9.53447148e-02 3.81556302e-01 -1.77226365e-01
1.14954877e+00 -5.81480622e-01 -6.06943667e-01 2.01264501e-01
-9.23876345e-01 -2.05526486e-01 7.71966338e-01 1.24972284e+00
1.16688430e+00 -5.54019988e-01 8.37987900e-01 -1.08911109e+00
5.58845103e-01 -6.95940375e-01 -5.72997332e-01 2.82380253e-01
-7.26051569e-01 6.64486229e-01 1.07688344e+00 -4.84502524e-01
-5.80749393e-01 3.64554912e-01 -5.33332050e-01 -2.64614701e-01
-8.56472030e-02 7.54409075e-01 -1.96843117e-01 -9.09072161e-02
8.47919106e-01 4.81043428e-01 1.51092127e-01 -8.18618834e-01
5.48814476e-01 7.10851908e-01 3.99513066e-01 -7.88413167e-01
5.16209841e-01 1.24545388e-01 -2.00054541e-01 -6.83909833e-01
-7.59013355e-01 -5.87767541e-01 -6.28475189e-01 8.57662976e-01
8.62050653e-01 -1.19376159e+00 -5.78455985e-01 3.71489711e-02
-1.00238097e+00 -2.78982043e-01 -1.23618707e-01 4.78565007e-01
-5.98148763e-01 6.14169240e-01 -5.34775853e-01 -4.45719995e-02
-6.11840069e-01 -1.23960114e+00 1.08742094e+00 -3.56689155e-01
-1.80215135e-01 -9.08563614e-01 4.34842736e-01 9.89304632e-02
3.36997718e-01 1.87842146e-01 1.33673286e+00 -1.15062582e+00
-1.96563274e-01 5.95130434e-04 -2.69790292e-01 4.43262488e-01
2.71049619e-01 -6.33471370e-01 -6.67658150e-01 -7.34845579e-01
-2.64356732e-01 -9.39121723e-01 1.02821004e+00 1.17434256e-01
1.31187713e+00 -1.11192390e-01 -4.68364000e-01 9.66685236e-01
1.49679291e+00 5.67299202e-02 4.52045053e-01 2.65031874e-01
6.30236149e-01 3.34290206e-01 6.34275615e-01 4.35922503e-01
6.50077239e-02 5.34205854e-01 1.56079084e-01 -3.77024591e-01
1.89568907e-01 -4.11503851e-01 3.70349079e-01 6.75632238e-01
1.24575019e-01 -1.43932059e-01 -8.00688148e-01 5.81824005e-01
-1.77078593e+00 -5.72615087e-01 3.65862787e-01 1.95644104e+00
1.38748026e+00 -1.76556241e-02 9.35582817e-03 -3.50056142e-01
2.74041474e-01 -4.22998443e-02 -1.08332741e+00 -5.23942888e-01
-2.08120912e-01 7.87616789e-01 5.57331324e-01 2.94404060e-01
-1.10930204e+00 1.09161556e+00 6.11525345e+00 8.88833582e-01
-1.16994810e+00 6.25671297e-02 4.93812740e-01 3.64767723e-02
-2.29363859e-01 -1.98957339e-01 -8.33105087e-01 3.43480706e-01
1.39060032e+00 -3.37044224e-02 3.41383040e-01 1.11908555e+00
-7.95062748e-04 5.72168529e-01 -1.47650814e+00 1.20308971e+00
-5.65705411e-02 -1.73573363e+00 2.26153955e-01 1.81133255e-01
4.79287624e-01 4.94435251e-01 -2.89847646e-02 4.33419615e-01
4.99642789e-01 -1.50655186e+00 -1.37977660e-01 2.21837923e-01
1.25184703e+00 -8.44360352e-01 7.82270491e-01 1.76617503e-01
-9.52039540e-01 2.05691427e-01 -8.75014544e-01 1.42539456e-01
-2.01296329e-01 5.10379076e-01 -8.12787533e-01 2.95506805e-01
4.78804350e-01 1.12478864e+00 -1.29622176e-01 3.80675822e-01
-2.67290539e-04 6.02707028e-01 -1.93022341e-01 -9.67062935e-02
2.42593572e-01 -1.79377243e-01 -5.19491397e-02 1.37029874e+00
-1.28702670e-01 3.54883343e-01 4.00811374e-01 7.13971019e-01
-4.95186716e-01 4.63678628e-01 -5.91526031e-01 -5.16398370e-01
2.38518685e-01 9.86121833e-01 -1.17871977e-01 -1.59208536e-01
-6.92084789e-01 1.20887363e+00 8.10236096e-01 2.95892566e-01
-9.14362013e-01 -6.00850880e-01 1.31608856e+00 -8.22064653e-02
5.15640378e-01 -2.24466980e-01 2.52357543e-01 -1.25706637e+00
-2.96759725e-01 -1.30357146e+00 2.65906900e-01 -2.45908067e-01
-1.81616259e+00 4.88405973e-01 -6.28294051e-01 -8.90848696e-01
1.31678477e-01 -1.24872017e+00 1.14101395e-01 1.06998634e+00
-1.71505260e+00 -1.02605104e+00 3.38997990e-01 5.10543406e-01
5.21860003e-01 -7.34158933e-01 1.45920157e+00 4.04068857e-01
-5.09072900e-01 7.44310439e-01 7.26606131e-01 -3.31610404e-02
1.10001576e+00 -1.19059253e+00 6.48282409e-01 1.32521376e-01
5.01339324e-02 1.05221212e+00 5.77116787e-01 -2.70760119e-01
-1.72712255e+00 -1.31721044e+00 9.95814025e-01 -6.09974623e-01
6.84846342e-01 -7.01052666e-01 -1.20715761e+00 4.50435579e-01
-8.18698630e-02 3.87550801e-01 1.40884519e+00 1.93034977e-01
-6.72044218e-01 1.03979953e-01 -1.07251263e+00 2.10939765e-01
1.11695313e+00 -8.81109416e-01 -6.96625531e-01 7.18710899e-01
1.05419636e+00 -1.71452999e-01 -1.28424191e+00 3.76598746e-01
5.41052461e-01 -2.48505935e-01 1.34528565e+00 -1.44739246e+00
5.88895440e-01 -1.61102012e-01 -3.60599250e-01 -1.14921975e+00
-5.86784780e-01 -5.18912613e-01 -1.93246305e-01 5.78621328e-01
6.11329138e-01 -5.91150105e-01 8.42118204e-01 2.41854325e-01
-1.32081717e-01 -1.18248093e+00 -8.09646964e-01 -6.89984977e-01
5.38958669e-01 1.80312265e-02 5.50509572e-01 1.01371658e+00
3.29927415e-01 6.82646334e-01 -4.34864461e-01 -8.69326890e-02
3.09009254e-01 3.13275933e-01 7.56975889e-01 -1.24109113e+00
-4.15975809e-01 -2.87206769e-02 -4.16533083e-01 -1.60701251e+00
4.98308212e-01 -1.22333980e+00 -1.95310250e-01 -1.26557982e+00
4.18177038e-01 -2.59530604e-01 -7.70369828e-01 6.36080146e-01
-3.01780224e-01 2.32333243e-02 -4.73438531e-01 1.91170543e-01
-6.68240309e-01 7.54619420e-01 9.44559753e-01 -3.65177721e-01
-6.31210357e-02 -5.54592907e-01 -8.99151325e-01 3.18569362e-01
5.26008546e-01 -5.19437850e-01 -3.16995680e-01 -3.67894053e-01
1.96938559e-01 -2.84319937e-01 -8.42562392e-02 -5.04664779e-01
-1.52536497e-01 -3.57780933e-01 3.58957857e-01 -3.00363272e-01
2.65183181e-01 -7.48015881e-01 -2.12821215e-01 5.62326849e-01
-5.56194007e-01 -8.15780610e-02 2.07594827e-01 9.77466762e-01
-1.13480978e-01 1.91280484e-01 9.65650201e-01 -2.20199674e-02
-7.83707976e-01 6.07610166e-01 -2.93594718e-01 8.08753818e-03
9.04756844e-01 -3.93773941e-03 -6.67890832e-02 3.01447570e-01
-7.43887365e-01 2.16990616e-02 6.08053446e-01 3.97243470e-01
8.42719674e-01 -1.06613457e+00 -7.85075426e-01 4.75867540e-01
5.89235961e-01 -2.14322060e-01 -1.90420762e-01 4.45516855e-01
-6.84800446e-01 7.41646469e-01 -2.27852836e-01 -4.36058730e-01
-1.17156160e+00 1.09303749e+00 1.90149322e-01 -4.10449415e-01
-6.98385417e-01 1.16846836e+00 5.01672864e-01 -6.31473601e-01
1.56428263e-01 -4.15356427e-01 -9.00674462e-02 -3.32537949e-01
5.19626379e-01 -2.47274041e-01 1.53999850e-01 -4.88865376e-01
-6.16742074e-01 5.39964020e-01 -5.49141586e-01 6.75455213e-01
1.83255076e+00 3.95632744e-01 -2.83283796e-02 -1.24677327e-02
1.72253668e+00 -2.78886586e-01 -1.18557250e+00 -5.93578279e-01
1.89613268e-01 -1.20665856e-01 -1.69854879e-01 -8.24347973e-01
-5.46001196e-01 8.40424120e-01 6.55771792e-01 -5.58878481e-01
7.67543793e-01 9.44954064e-03 1.27903986e+00 9.43753898e-01
5.03048539e-01 -9.39896047e-01 1.56878546e-01 6.79052114e-01
6.38574064e-01 -1.56461537e+00 1.84755214e-02 -1.76502466e-02
-5.66855431e-01 1.06188595e+00 3.81081283e-01 -2.91096568e-01
7.53071010e-01 1.79945916e-01 -1.32585242e-01 -3.99096489e-01
-1.01740468e+00 -4.49846946e-02 1.16573669e-01 8.73463154e-01
9.72175181e-01 -2.32144464e-02 -4.07137781e-01 9.40942705e-01
2.08033383e-01 7.00857714e-02 -6.29196092e-02 9.95480657e-01
-6.08065724e-01 -1.52532256e+00 5.31145409e-02 3.45463663e-01
-5.78797221e-01 -4.25145566e-01 -4.38283205e-01 2.68651932e-01
6.34329319e-02 6.44978702e-01 -2.69023985e-01 -2.38148630e-01
3.52589965e-01 2.09470093e-01 3.70222926e-01 -8.64267468e-01
-4.11631316e-01 -1.29431620e-01 2.40168069e-02 -5.35158455e-01
-3.59019905e-01 -2.40169927e-01 -1.52472615e+00 -1.74649313e-01
-1.91679984e-01 3.39290619e-01 3.71589333e-01 7.70195484e-01
8.61721635e-01 2.56324053e-01 4.22457993e-01 -5.82350969e-01
-8.87123048e-01 -8.54492307e-01 -5.19423068e-01 7.82289982e-01
3.19758594e-01 -6.68978691e-01 -2.77559590e-02 2.74538547e-01] | [4.746641159057617, 5.695224761962891] |
76686a89-c44f-4c17-95fe-f6f9a17f0343 | dynamic-graph-reasoning-for-multi-person-3d | 2207.11341 | null | https://arxiv.org/abs/2207.11341v2 | https://arxiv.org/pdf/2207.11341v2.pdf | Dynamic Graph Reasoning for Multi-person 3D Pose Estimation | Multi-person 3D pose estimation is a challenging task because of occlusion and depth ambiguity, especially in the cases of crowd scenes. To solve these problems, most existing methods explore modeling body context cues by enhancing feature representation with graph neural networks or adding structural constraints. However, these methods are not robust for their single-root formulation that decoding 3D poses from a root node with a pre-defined graph. In this paper, we propose GR-M3D, which models the \textbf{M}ulti-person \textbf{3D} pose estimation with dynamic \textbf{G}raph \textbf{R}easoning. The decoding graph in GR-M3D is predicted instead of pre-defined. In particular, It firstly generates several data maps and enhances them with a scale and depth aware refinement module (SDAR). Then multiple root keypoints and dense decoding paths for each person are estimated from these data maps. Based on them, dynamic decoding graphs are built by assigning path weights to the decoding paths, while the path weights are inferred from those enhanced data maps. And this process is named dynamic graph reasoning (DGR). Finally, the 3D poses are decoded according to dynamic decoding graphs for each detected person. GR-M3D can adjust the structure of the decoding graph implicitly by adopting soft path weights according to input data, which makes the decoding graphs be adaptive to different input persons to the best extent and more capable of handling occlusion and depth ambiguity than previous methods. We empirically show that the proposed bottom-up approach even outperforms top-down methods and achieves state-of-the-art results on three 3D pose datasets. | ['Dongmei Fu', 'Jian Wang', 'Qiansheng Yang', 'Zhongwei Qiu'] | 2022-07-22 | null | null | null | null | ['3d-pose-estimation'] | ['computer-vision'] | [ 1.26440510e-01 4.56114739e-01 7.94155449e-02 -3.97109151e-01
-3.19217920e-01 -3.12371343e-01 2.58689761e-01 3.17119099e-02
-2.57437646e-01 3.90472591e-01 4.55831319e-01 2.91770756e-01
-1.80850074e-01 -8.53657961e-01 -5.77051759e-01 -3.10323298e-01
-7.80116245e-02 1.11831892e+00 5.14094293e-01 -4.72955257e-01
-1.30093336e-01 4.66395259e-01 -1.48989415e+00 -2.87025608e-02
8.80978882e-01 7.53326952e-01 2.03267574e-01 6.07115924e-01
1.29603148e-01 6.92522451e-02 -5.00723064e-01 -7.36576915e-01
4.26706523e-01 -1.72428057e-01 -3.73550534e-01 4.34171796e-01
5.73918760e-01 -4.45492506e-01 -4.50758249e-01 8.33036363e-01
7.75101185e-01 2.34821245e-01 4.74105299e-01 -1.17861044e+00
-1.69758722e-01 3.46478462e-01 -8.30034554e-01 -5.75051941e-02
8.79047513e-01 -2.51411591e-02 6.60432220e-01 -9.11004364e-01
8.15471232e-01 1.70691991e+00 7.13204145e-01 6.58998072e-01
-9.30700362e-01 -5.69613755e-01 8.06514561e-01 7.13876337e-02
-1.55403602e+00 -1.05643824e-01 8.47541213e-01 -4.10749525e-01
8.04589450e-01 3.13723296e-01 1.22797430e+00 9.32953477e-01
2.62707144e-01 6.62008762e-01 6.83460772e-01 -2.54605055e-01
-8.87745097e-02 -4.22845244e-01 1.59149989e-02 1.04140055e+00
4.28553909e-01 -7.95254186e-02 -7.21822679e-01 -5.32518215e-02
9.12399054e-01 -1.38787944e-02 -2.28736728e-01 -4.87251759e-01
-1.16898656e+00 4.85749364e-01 6.48155034e-01 -2.67445534e-01
-3.54895890e-01 5.42215519e-02 2.06423789e-01 -2.81102270e-01
2.39742398e-01 -3.52797657e-02 -4.05788183e-01 2.59416014e-01
-6.78732276e-01 7.13918388e-01 5.91996372e-01 1.29303789e+00
6.78591192e-01 -2.74138600e-01 -3.07258040e-01 6.78252578e-01
5.38896143e-01 4.88053173e-01 -2.59287022e-02 -8.47437978e-01
8.58946502e-01 9.89026010e-01 8.00677612e-02 -1.37862194e+00
-9.86524582e-01 -6.19296134e-01 -8.23377252e-01 1.70146413e-02
4.60951656e-01 -1.87130913e-01 -1.20430565e+00 1.75190294e+00
9.29485083e-01 4.05020081e-02 -2.96710849e-01 1.23495650e+00
1.04882514e+00 2.51587838e-01 2.06253305e-02 3.47403549e-02
1.45992529e+00 -1.08224070e+00 -5.69387853e-01 -5.97111225e-01
4.00833517e-01 -3.99326742e-01 6.63583815e-01 4.74066645e-01
-9.40423489e-01 -7.38706291e-01 -1.02191365e+00 -2.75643647e-01
-2.94317510e-02 2.20635861e-01 5.37264109e-01 5.57563007e-01
-8.47829640e-01 2.87710488e-01 -7.62627184e-01 -4.45234746e-01
1.22498624e-01 4.90709662e-01 -5.55018544e-01 -2.83292890e-01
-1.04036808e+00 7.25807190e-01 5.10670722e-01 6.43026710e-01
-6.68553412e-01 -9.57931206e-02 -1.25841856e+00 -3.19924504e-01
7.80854404e-01 -1.15847588e+00 7.06030846e-01 -4.61166352e-01
-1.26416337e+00 8.77924681e-01 -1.72339916e-01 2.20516417e-02
8.87743115e-01 -4.59148794e-01 -3.24592441e-01 8.69617835e-02
1.92898914e-01 8.09490263e-01 8.74272406e-01 -1.31350255e+00
-5.65006077e-01 -9.30519998e-01 2.35323027e-01 7.28442013e-01
2.62390692e-02 -2.91855067e-01 -1.30654263e+00 -7.08523870e-01
7.40544498e-01 -1.00394428e+00 -4.65411693e-01 8.29011202e-02
-7.35935688e-01 -2.55956948e-01 4.39466596e-01 -9.46134627e-01
1.24492133e+00 -1.75373769e+00 7.68724024e-01 5.80559850e-01
6.55600607e-01 -8.21282715e-02 -3.74725438e-03 1.94361746e-01
3.12889040e-01 -2.94430047e-01 -1.03037246e-01 -6.22586787e-01
1.74269192e-02 4.24075067e-01 4.63756502e-01 6.06353164e-01
-1.48787349e-01 8.10092211e-01 -7.38648355e-01 -6.82863533e-01
3.28734547e-01 5.53959250e-01 -7.70699739e-01 9.76082459e-02
-2.48072967e-01 6.65365696e-01 -5.98369539e-01 7.80147016e-01
7.66455114e-01 -1.11815006e-01 3.88911486e-01 -3.58546436e-01
8.69554281e-02 -1.98238850e-01 -1.75032938e+00 2.07559633e+00
1.28301606e-01 -1.28563881e-01 1.35810189e-02 -5.08469403e-01
9.86018598e-01 -3.36773917e-02 4.61215436e-01 -4.05870348e-01
3.03859830e-01 -7.30914250e-02 -1.60803139e-01 -3.77211332e-01
5.02729774e-01 3.25889856e-01 -2.71990001e-01 -1.00868016e-01
-8.32504183e-02 2.11506054e-01 1.19357429e-01 1.92960829e-01
7.62979686e-01 6.98521674e-01 2.49653101e-01 3.51875573e-02
6.73952878e-01 -1.63621992e-01 9.00530159e-01 5.77983618e-01
-9.82920006e-02 7.36454010e-01 3.17706883e-01 -5.58408320e-01
-7.60675967e-01 -9.77502584e-01 9.85476971e-02 1.00151479e+00
7.13035583e-01 -9.19402719e-01 -8.96730840e-01 -7.10608304e-01
1.55386657e-01 1.26504451e-01 -7.64818370e-01 7.09238574e-02
-8.40815067e-01 -5.61876059e-01 4.02343631e-01 6.13999069e-01
5.41163445e-01 -6.93237901e-01 -5.28204620e-01 3.34543020e-01
-4.57770526e-01 -1.28258801e+00 -5.77835739e-01 -3.17124546e-01
-6.74593985e-01 -1.29803693e+00 -7.86065578e-01 -6.26010478e-01
1.02477050e+00 1.69758052e-02 9.05468106e-01 3.91627192e-01
-1.67539820e-01 2.87639499e-01 -3.95522773e-01 -2.23160431e-01
1.29887983e-01 8.23055655e-02 3.17979693e-01 2.50687283e-02
2.32655823e-01 -4.53510880e-01 -8.26757848e-01 5.58151662e-01
-4.06221002e-01 3.91040087e-01 3.52809697e-01 3.56107712e-01
9.81909454e-01 -1.07272178e-01 1.10229924e-01 -6.67483211e-01
2.28800848e-01 -5.84229678e-02 -4.09593046e-01 2.20906958e-01
-3.06591153e-01 -9.50756595e-02 1.28698766e-01 -4.47737932e-01
-8.95086169e-01 2.18455940e-01 -3.94565761e-01 -3.56884718e-01
-7.05292672e-02 2.27962837e-01 -6.57660723e-01 -7.52253532e-02
6.19982481e-01 -1.86603069e-01 -1.76847681e-01 -5.40903628e-01
2.61761278e-01 2.41555259e-01 6.15233123e-01 -6.91944540e-01
9.00751293e-01 4.03007090e-01 2.32373938e-01 -4.81168509e-01
-8.48230362e-01 -2.05605403e-01 -1.09643710e+00 -7.61309981e-01
1.20960367e+00 -9.46402073e-01 -8.05338621e-01 6.14319086e-01
-1.05391312e+00 -1.93727300e-01 1.04564741e-01 4.93835896e-01
-4.05574888e-01 5.63846171e-01 -4.95315015e-01 -7.40174472e-01
-2.14190513e-01 -1.26317978e+00 1.44125450e+00 1.84291899e-01
-2.94608831e-01 -6.09760284e-01 -2.64127791e-01 4.84857053e-01
-2.64972776e-01 7.46701360e-01 5.11950731e-01 -1.65495977e-01
-4.39846247e-01 -2.34730020e-01 -8.42610672e-02 -1.93774074e-01
-1.56140506e-01 -4.63826537e-01 -6.14630163e-01 -3.70448023e-01
-4.95822281e-01 1.62513494e-01 5.49634993e-01 4.19992834e-01
1.01377618e+00 -1.69789016e-01 -5.90195119e-01 9.20786500e-01
1.02585554e+00 -2.46943310e-01 4.92000043e-01 3.58966827e-01
1.21293139e+00 8.50022912e-01 7.67167687e-01 5.48868179e-01
1.02787936e+00 9.79343235e-01 6.01679027e-01 -7.16340169e-03
-1.84179828e-01 -6.13681018e-01 1.74856603e-01 4.50960666e-01
-6.96220994e-01 -3.49415094e-01 -8.51754248e-01 2.50065941e-02
-2.01661944e+00 -5.04811168e-01 -2.98386753e-01 2.14594340e+00
3.45024735e-01 3.29270691e-01 3.47778141e-01 3.35526578e-02
9.11684632e-01 8.79965946e-02 -7.02997923e-01 1.91901535e-01
-6.26490335e-04 -1.93547308e-01 3.43761444e-01 5.79381526e-01
-9.96936321e-01 1.00498033e+00 4.98335505e+00 4.06238437e-01
-4.48410600e-01 -2.30415352e-02 1.74298257e-01 -2.37623882e-02
-1.54897720e-01 -6.14727885e-02 -1.19420075e+00 1.75019711e-01
-2.22255345e-02 2.94815540e-01 2.29090914e-01 7.12835968e-01
7.01445192e-02 -1.17120169e-01 -9.91520584e-01 1.25915885e+00
3.25053483e-01 -8.32910657e-01 1.64246574e-01 2.32635722e-01
3.70557189e-01 -4.54697222e-01 -4.71176624e-01 3.29956532e-01
-4.30443557e-04 -8.08569908e-01 1.03469205e+00 7.43539333e-01
8.23630631e-01 -8.39739025e-01 6.52461827e-01 6.46538734e-01
-1.72867465e+00 -2.87391841e-02 -2.56992519e-01 -9.75307301e-02
4.85893935e-01 3.91063184e-01 -3.79880577e-01 8.45468223e-01
9.32580531e-01 5.85649848e-01 -7.10430861e-01 8.49292159e-01
-4.74410892e-01 -4.37916778e-02 -4.30589676e-01 1.79714441e-01
-2.31840402e-01 -1.29403934e-01 8.42082322e-01 9.86187041e-01
3.55581284e-01 3.14868391e-01 7.67064393e-01 4.37510997e-01
1.90759137e-01 1.42228901e-01 -2.01264977e-01 6.48686707e-01
3.88278604e-01 1.19106781e+00 -8.42478037e-01 -3.12514722e-01
-5.07669821e-02 1.12913132e+00 4.21107113e-01 2.94535547e-01
-9.05755937e-01 4.47610579e-02 5.66821873e-01 5.69580793e-01
2.04058606e-02 -4.66951966e-01 -3.35969664e-02 -1.23457575e+00
2.94890434e-01 -7.71187007e-01 6.95085585e-01 -7.93808639e-01
-1.00894701e+00 6.77984297e-01 3.89173865e-01 -1.12467241e+00
-7.59755149e-02 -4.26185906e-01 -3.79216217e-04 7.11619556e-01
-1.03356135e+00 -1.47452390e+00 -7.84352899e-01 8.40160131e-01
4.84993011e-01 1.35549322e-01 5.68258107e-01 1.59635976e-01
-5.32016098e-01 6.18011236e-01 -9.18173909e-01 1.70551285e-01
4.89247501e-01 -1.18248010e+00 5.09850144e-01 8.99671078e-01
-1.18284240e-01 4.77098733e-01 5.99863648e-01 -1.33405328e+00
-1.44645429e+00 -1.01741624e+00 7.59684205e-01 -4.93424445e-01
2.18823850e-02 -6.73884153e-01 -6.19659245e-01 8.38931441e-01
-5.05760550e-01 1.93702783e-02 3.96056026e-01 1.39908552e-01
-1.19507037e-01 1.88166834e-02 -1.20987606e+00 6.94453597e-01
1.96097350e+00 8.64731967e-02 -5.82837343e-01 3.07883739e-01
7.09883749e-01 -1.33202481e+00 -8.62631559e-01 5.47882855e-01
6.14333630e-01 -8.29091787e-01 1.23819196e+00 -2.28209138e-01
1.29329460e-02 -7.06887424e-01 -9.89085138e-02 -9.06047881e-01
-5.05790174e-01 -5.22536516e-01 -4.19517130e-01 9.62414622e-01
8.33091810e-02 -4.30753797e-01 9.30846095e-01 6.50247812e-01
-2.02712685e-01 -6.55750692e-01 -9.95345831e-01 -3.80529791e-01
-5.06428778e-01 -5.68158269e-01 8.29112053e-01 5.58074176e-01
-4.46812570e-01 1.39149904e-01 -5.81703663e-01 6.38524890e-01
8.94938827e-01 -6.96834624e-02 1.25283086e+00 -1.33668911e+00
-4.04098153e-01 -2.80524269e-02 -7.28558838e-01 -1.49938703e+00
-1.48954093e-01 -7.49292672e-01 4.57931124e-02 -1.92004073e+00
-8.47498234e-03 -4.87723649e-01 1.98144808e-01 5.81451833e-01
-4.21327680e-01 3.85291725e-01 4.30800408e-01 2.56525520e-02
-5.88776946e-01 4.78178054e-01 1.59980738e+00 -9.77287535e-04
-4.52472776e-01 8.37703571e-02 -5.32659411e-01 1.03186965e+00
3.96617472e-01 -2.62934417e-01 -4.01126146e-01 -5.15882373e-01
4.14402902e-01 2.92758375e-01 6.30604744e-01 -1.19945049e+00
2.27295190e-01 -1.81302559e-02 9.29820955e-01 -9.92383063e-01
6.49266064e-01 -6.86588943e-01 4.45789427e-01 3.29025120e-01
1.26399368e-01 3.30860674e-01 -3.11854556e-02 7.78510332e-01
2.33163774e-01 1.52977407e-01 3.43365282e-01 -3.50142062e-01
-8.63298535e-01 7.47057796e-01 7.66624659e-02 -6.24110773e-02
9.82506752e-01 -7.24579334e-01 1.20112464e-01 -2.56476104e-01
-1.22542822e+00 6.00482643e-01 4.13553745e-01 6.32853806e-01
8.99420261e-01 -1.31435859e+00 -7.43750811e-01 3.01795453e-01
1.80674136e-01 7.01036394e-01 5.51317334e-01 7.85545945e-01
-4.19121385e-01 -2.05175787e-01 4.37001213e-02 -9.01179254e-01
-1.43553472e+00 3.47058088e-01 4.50360298e-01 -2.25992814e-01
-1.08006954e+00 8.66734445e-01 3.12507659e-01 -6.04960740e-01
3.37569296e-01 -1.67217821e-01 -3.80407393e-01 8.26613605e-03
4.06861424e-01 4.50083464e-01 -1.93916187e-01 -1.13017428e+00
-4.80834126e-01 1.06528366e+00 1.83134302e-01 4.20342162e-02
1.12309790e+00 -3.76491010e-01 7.77914897e-02 -1.24640629e-01
5.72969079e-01 1.61226928e-01 -1.44858301e+00 -1.66202396e-01
-4.14464563e-01 -5.99074781e-01 -4.10458744e-01 -6.78763092e-01
-1.06160462e+00 4.76252168e-01 4.43589449e-01 -4.35982168e-01
1.07434475e+00 8.82046074e-02 7.65428543e-01 1.27848536e-01
8.32127512e-01 -1.21560156e+00 1.37174815e-01 3.55524063e-01
1.10262656e+00 -8.47380996e-01 2.36030579e-01 -9.13784623e-01
-5.74038982e-01 1.12573361e+00 1.00561893e+00 -1.00971445e-01
3.95455599e-01 6.69901744e-02 -1.75889537e-01 -3.78576338e-01
1.79901179e-02 -3.61333698e-01 6.36508942e-01 8.83363962e-01
-5.17798550e-02 2.11765304e-01 -3.08711231e-01 6.96035743e-01
-5.67783117e-01 -1.72616839e-01 -2.17021164e-02 7.44619668e-01
-4.11690533e-01 -1.08490920e+00 -7.99327433e-01 3.10835212e-01
-2.05211230e-02 3.51157308e-01 -3.02068323e-01 9.76695776e-01
7.20051944e-01 8.93477380e-01 -1.92522034e-01 -6.86419010e-01
7.38464475e-01 -2.90902048e-01 7.38754094e-01 -6.76968277e-01
-5.14612138e-01 3.71963948e-01 2.76497811e-01 -6.95227444e-01
-3.76215369e-01 -8.20195317e-01 -1.54311037e+00 -2.07053363e-01
-3.35071623e-01 -2.64339536e-01 3.07948917e-01 1.01472068e+00
2.10654080e-01 6.40694022e-01 2.44010724e-02 -1.27749145e+00
1.31150916e-01 -7.83084810e-01 -4.17795599e-01 4.73668844e-01
-5.41704055e-03 -1.11956775e+00 1.13949157e-01 -2.27064699e-01] | [7.026687145233154, -0.959053635597229] |
b289a874-ad1b-458f-87db-aeb73c81357d | gait-recognition-with-mask-based | 2203.04038 | null | https://arxiv.org/abs/2203.04038v1 | https://arxiv.org/pdf/2203.04038v1.pdf | Gait Recognition with Mask-based Regularization | Most gait recognition methods exploit spatial-temporal representations from static appearances and dynamic walking patterns. However, we observe that many part-based methods neglect representations at boundaries. In addition, the phenomenon of overfitting on training data is relatively common in gait recognition, which is perhaps due to insufficient data and low-informative gait silhouettes. Motivated by these observations, we propose a novel mask-based regularization method named ReverseMask. By injecting perturbation on the feature map, the proposed regularization method helps convolutional architecture learn the discriminative representations and enhances generalization. Also, we design an Inception-like ReverseMask Block, which has three branches composed of a global branch, a feature dropping branch, and a feature scaling branch. Precisely, the dropping branch can extract fine-grained representations when partial activations are zero-outed. Meanwhile, the scaling branch randomly scales the feature map, keeping structural information of activations and preventing overfitting. The plug-and-play Inception-like ReverseMask block is simple and effective to generalize networks, and it also improves the performance of many state-of-the-art methods. Extensive experiments demonstrate that the ReverseMask regularization help baseline achieves higher accuracy and better generalization. Moreover, the baseline with Inception-like Block significantly outperforms state-of-the-art methods on the two most popular datasets, CASIA-B and OUMVLP. The source code will be released. | ['Xin Yu', 'Shiqi Yu', 'George Q. Huang', 'Shunli Zhang', 'Beibei Lin', 'Chuanfu Shen'] | 2022-03-08 | null | null | null | null | ['multiview-gait-recognition'] | ['computer-vision'] | [-6.11453690e-02 -4.04690504e-01 -3.98762017e-01 -3.01917315e-01
-1.42279387e-01 7.03157410e-02 1.71205595e-01 -3.54913026e-01
-2.39910558e-01 7.69974351e-01 1.62147358e-01 1.91148013e-01
-4.78971340e-02 -8.65432322e-01 -8.14263105e-01 -1.02315664e+00
-2.57078528e-01 -1.47370538e-02 6.07573807e-01 -3.98463130e-01
-7.64514878e-02 2.78673410e-01 -1.40703511e+00 2.69411594e-01
1.03660774e+00 1.11152554e+00 1.08291820e-01 -9.47533622e-02
4.31758864e-03 5.54109275e-01 -4.15585011e-01 -1.15560882e-01
1.29232168e-01 -3.00157636e-01 -2.85925716e-01 2.09849700e-01
3.40870112e-01 -2.83976644e-01 -9.13784564e-01 8.40519786e-01
4.96675938e-01 2.90113568e-01 6.28206730e-01 -1.36419713e+00
-8.75199020e-01 1.74742177e-01 -9.45468426e-01 4.40168917e-01
5.71959987e-02 5.22702575e-01 7.60473132e-01 -8.45281124e-01
4.31305856e-01 1.16688704e+00 8.15278351e-01 5.61611474e-01
-1.22530556e+00 -7.62824118e-01 5.11265278e-01 3.66216868e-01
-1.44799232e+00 -2.55475879e-01 1.04246724e+00 -3.04670781e-01
8.36654723e-01 1.85132861e-01 7.29162216e-01 1.32431006e+00
3.20860416e-01 1.11298347e+00 7.69508183e-01 2.63952278e-02
1.34510055e-01 -5.58505774e-01 2.20831797e-01 9.49807823e-01
6.11299157e-01 4.07796167e-02 -4.65117246e-01 8.87327194e-02
1.05643213e+00 3.15055937e-01 -4.55879509e-01 -5.58915198e-01
-9.59152818e-01 4.88663405e-01 8.56438160e-01 2.97941536e-01
-3.47958267e-01 3.00361454e-01 5.34528017e-01 1.16013624e-01
2.55744785e-01 -1.84123382e-01 -1.75594866e-01 -1.71198010e-01
-9.36059713e-01 1.89721957e-01 2.57384837e-01 6.18919373e-01
8.24133694e-01 4.01447505e-01 -2.48468384e-01 1.21241891e+00
2.11147711e-01 4.29527164e-01 8.57590079e-01 -5.10707259e-01
7.35137820e-01 7.89267719e-01 -2.68859059e-01 -1.22028124e+00
-5.56872904e-01 -5.60509503e-01 -1.17211068e+00 -9.07050818e-02
3.26713443e-01 -3.75949368e-02 -1.31215751e+00 1.82112718e+00
-6.44482523e-02 5.05416691e-01 -3.54759991e-01 1.12429619e+00
8.56944740e-01 4.89647090e-01 1.25983432e-01 -2.30292194e-02
1.30868042e+00 -9.83950496e-01 -6.00280643e-01 -5.61053634e-01
6.00824952e-01 -1.61157250e-01 1.21871138e+00 1.29536629e-01
-5.85397840e-01 -8.13948512e-01 -1.40240443e+00 1.51874289e-01
-3.90546024e-01 3.91499341e-01 6.87989950e-01 3.79751086e-01
-7.27374911e-01 8.62077653e-01 -1.13309407e+00 -4.15296406e-01
6.13842309e-01 2.29122937e-01 -5.48748553e-01 -2.60706961e-01
-1.22352052e+00 4.78317738e-01 3.83988142e-01 3.59126598e-01
-4.40636814e-01 -3.31298351e-01 -1.07951307e+00 -1.79412644e-02
2.89407104e-01 -6.26334369e-01 5.25599718e-01 -6.99079573e-01
-1.25961602e+00 5.83914518e-01 -1.35822713e-01 -3.73865455e-01
6.19586408e-01 -3.46068501e-01 -6.68585122e-01 6.57718927e-02
2.75508344e-01 5.77003062e-01 1.12007856e+00 -9.83422995e-01
-2.96234965e-01 -3.26578856e-01 -3.29276979e-01 -1.48271680e-01
-5.76480150e-01 -7.22668290e-01 -6.61586881e-01 -1.04103005e+00
4.30263788e-01 -6.79599762e-01 -1.34781957e-01 -5.63503727e-02
-3.66919398e-01 -1.34392902e-01 1.18522298e+00 -6.52587235e-01
1.62251997e+00 -2.32672095e+00 -9.71371531e-02 9.92389321e-02
2.41138041e-02 3.89786869e-01 -3.20075095e-01 3.20727676e-01
-3.65352243e-01 7.58911073e-02 -3.11187536e-01 -8.18583891e-02
-1.09116115e-01 6.11526132e-01 -2.07554370e-01 3.62736613e-01
4.95228559e-01 1.06681323e+00 -8.49153101e-01 -4.34791654e-01
3.07982653e-01 2.83020377e-01 -6.40002370e-01 -9.75045636e-02
1.62175909e-01 2.29223743e-01 -6.81895673e-01 9.23898399e-01
8.83064806e-01 -2.40078822e-01 -5.33830784e-02 -3.65764052e-01
6.32635951e-02 9.42209065e-02 -1.11647749e+00 1.84393883e+00
-1.10310063e-01 3.45334411e-01 -3.12833369e-01 -1.47267413e+00
1.21165097e+00 -5.21232970e-02 5.49950242e-01 -8.73639166e-01
2.33865958e-02 3.53074282e-01 -2.43781190e-02 -6.58401430e-01
3.14240038e-01 4.84856851e-02 -6.55104369e-02 4.75832373e-02
1.22007996e-01 5.84232926e-01 4.14467156e-01 -4.20424603e-02
1.18179500e+00 4.77598727e-01 7.14836642e-02 -2.75577337e-01
6.04758680e-01 -4.60198253e-01 1.22425580e+00 5.59999764e-01
-5.88704705e-01 7.60098159e-01 4.65440303e-01 -8.03777456e-01
-5.66851139e-01 -1.05892408e+00 -7.28022680e-02 8.32026124e-01
3.59307528e-01 -6.02506578e-01 -6.55297935e-01 -8.57855737e-01
2.90939808e-01 1.87339023e-01 -9.15098011e-01 -7.46663272e-01
-1.02467954e+00 -1.00175142e+00 5.60076892e-01 1.12635100e+00
1.21816421e+00 -1.08453417e+00 -4.28039849e-01 3.93277705e-01
-3.58633459e-01 -8.66789222e-01 -6.51890695e-01 1.58927262e-01
-1.10375321e+00 -9.65998828e-01 -8.84910762e-01 -8.07032883e-01
6.05690062e-01 2.66945630e-01 9.60998952e-01 3.31222057e-01
-2.59392112e-01 -1.01952575e-01 -4.62457597e-01 2.68261790e-01
3.41683954e-01 1.57785520e-01 1.02300160e-01 2.76611656e-01
5.71807623e-01 -1.02915192e+00 -8.49609792e-01 5.92792690e-01
-7.66245961e-01 -1.30274370e-01 7.56721497e-01 1.21652651e+00
5.77507734e-01 -2.72583663e-02 6.40348375e-01 -3.07344317e-01
4.85153466e-01 -3.41238678e-01 1.11933783e-01 4.69380729e-02
-2.13098168e-01 1.82281703e-01 6.90035641e-01 -6.59079731e-01
-6.32470906e-01 2.96944622e-02 -2.06093371e-01 -7.52344310e-01
-1.09078087e-01 4.58991289e-01 -4.29265797e-01 -8.74905959e-02
5.66006601e-01 5.46947062e-01 6.98523149e-02 -5.89199185e-01
-5.58978207e-02 3.85764062e-01 5.67048013e-01 -8.76920819e-01
8.06473255e-01 5.26286542e-01 -3.31852809e-02 -9.31120574e-01
-4.83539134e-01 -2.11618453e-01 -6.13312483e-01 -3.30061316e-01
5.76624393e-01 -7.18737602e-01 -2.80721128e-01 8.23368728e-01
-6.40752912e-01 -3.54543537e-01 -2.70375609e-01 2.62727261e-01
-4.63074833e-01 4.97987002e-01 -7.43441761e-01 -4.31659400e-01
-1.55948728e-01 -1.02772486e+00 9.89083946e-01 5.65922558e-01
-7.96706975e-02 -6.43027723e-01 -1.88117146e-01 4.62785410e-03
3.65208745e-01 4.01931792e-01 8.56496155e-01 -3.67563218e-01
-3.49448502e-01 -2.84478784e-01 -2.34934732e-01 3.95603448e-01
5.11081636e-01 -1.23848118e-01 -7.50943720e-01 -3.63928825e-01
-3.72331232e-01 -2.77198344e-01 1.38400197e+00 5.71720004e-01
1.18751490e+00 -1.08370401e-01 -5.77349067e-01 6.97961211e-01
1.16032469e+00 1.48422897e-01 1.04426360e+00 5.22640288e-01
7.55554736e-01 1.93546250e-01 4.25991058e-01 1.99360266e-01
2.30475411e-01 6.83346927e-01 3.08128834e-01 -1.34950295e-01
-1.62533194e-01 -4.16865766e-01 3.78863245e-01 8.91402185e-01
-4.20027703e-01 1.95659146e-01 -6.32743716e-01 4.82899666e-01
-2.10352230e+00 -9.16494668e-01 1.66080803e-01 2.04457569e+00
5.30490696e-01 4.19940889e-01 3.28876048e-01 3.46634597e-01
7.19581127e-01 5.95274687e-01 -6.68172002e-01 -6.97394684e-02
-1.96808934e-01 8.60257745e-02 3.01255077e-01 -1.78844243e-01
-1.33884513e+00 8.63929451e-01 5.15404415e+00 1.04476857e+00
-1.20789850e+00 -1.23302698e-01 4.97092545e-01 1.48308977e-01
2.11403161e-01 -2.43536413e-01 -6.69719517e-01 8.00134540e-01
3.24938893e-01 2.67501771e-01 1.55630499e-01 8.57998967e-01
3.35148305e-01 1.20152503e-01 -8.62425208e-01 1.02804399e+00
-6.21255301e-02 -1.23860908e+00 3.27693909e-01 9.33181122e-02
3.23393822e-01 -2.49368772e-01 -9.63388532e-02 5.74613750e-01
-1.82645574e-01 -6.68966293e-01 4.95530903e-01 5.17834246e-01
7.05988705e-01 -6.18045866e-01 6.61934018e-01 1.78642094e-01
-1.86251652e+00 -1.56959057e-01 -4.91609037e-01 -1.61658466e-01
1.45720005e-01 5.98898113e-01 1.35939211e-01 8.26362550e-01
8.59103203e-01 1.30006289e+00 -7.05984294e-01 1.15546560e+00
-2.88251728e-01 7.71939933e-01 -2.10553020e-01 1.22142687e-01
4.39287275e-01 -3.40937227e-01 4.73913670e-01 1.32086062e+00
1.88309431e-01 -2.20313035e-02 4.12746221e-01 8.52146029e-01
-2.06502639e-02 -1.23283029e-01 -4.45919961e-01 -6.94193542e-02
2.43560314e-01 9.62519884e-01 -8.38390887e-01 -2.64905125e-01
-3.90603989e-01 1.03088069e+00 3.10817331e-01 6.80749416e-01
-8.04070830e-01 -5.43067455e-01 8.58224154e-01 3.58803123e-01
5.73981345e-01 -2.15744242e-01 -2.47486472e-01 -1.42505741e+00
4.50306535e-01 -7.51568079e-01 5.04432738e-01 -4.68052030e-01
-1.48478985e+00 4.08068448e-01 -1.41468957e-01 -1.53175294e+00
3.97579037e-02 -6.49635375e-01 -9.32257891e-01 5.55846095e-01
-1.26434445e+00 -1.08448732e+00 -5.91277361e-01 6.50266111e-01
5.26453197e-01 -9.24267471e-02 4.80583072e-01 5.91899455e-01
-1.13118362e+00 7.95527875e-01 -7.74297193e-02 6.43240035e-01
5.33868551e-01 -7.98488021e-01 4.62738037e-01 9.14620340e-01
-1.20944023e-01 7.64170527e-01 4.21379626e-01 -8.02384496e-01
-1.14705729e+00 -1.16423655e+00 1.38881356e-01 1.48070425e-01
5.80118179e-01 -2.28092149e-01 -1.37626123e+00 5.85505247e-01
-3.42813015e-01 4.74850565e-01 2.74115711e-01 1.11909332e-02
-5.19097209e-01 -4.21676248e-01 -8.73772383e-01 6.14218593e-01
1.35325885e+00 -1.55577987e-01 -8.16636145e-01 -1.87999625e-02
3.60734314e-01 -2.56066561e-01 -5.21184981e-01 7.08307981e-01
7.04410493e-01 -8.55538607e-01 1.02911091e+00 -6.07553661e-01
4.89669532e-01 -4.57275242e-01 -1.03573948e-01 -1.32913029e+00
-6.26866937e-01 -3.57891560e-01 -3.76167953e-01 1.21876085e+00
3.27710807e-02 -8.77664268e-01 1.07696033e+00 1.16038650e-01
-3.01584363e-01 -1.14878428e+00 -1.05305314e+00 -1.29719055e+00
1.77992240e-01 -1.27368927e-01 5.42066216e-01 8.79340649e-01
-6.46272153e-02 -4.31780629e-02 -5.26574433e-01 -5.24657257e-02
5.33972442e-01 1.84547901e-01 5.67901313e-01 -1.15168810e+00
-1.33439913e-01 -4.90397125e-01 -7.98201501e-01 -1.38642764e+00
-3.63647938e-02 -6.25580966e-01 3.57238390e-02 -1.47301137e+00
3.44255455e-02 -3.88381839e-01 -6.47151053e-01 8.27990532e-01
-4.31738436e-01 3.35896611e-01 6.83669373e-02 3.75889510e-01
-2.87079781e-01 8.19224536e-01 1.35680628e+00 -3.59633505e-01
-2.87166446e-01 -1.11572094e-01 -3.63544464e-01 8.01239491e-01
8.34325433e-01 -3.40882033e-01 -2.52398193e-01 -2.10678488e-01
-4.14312869e-01 -4.62307960e-01 4.52619195e-01 -1.44269454e+00
-1.01731554e-01 -7.59919658e-02 6.35595262e-01 -5.24652302e-01
4.15526807e-01 -3.55434358e-01 -4.58592996e-02 7.77211010e-01
2.08995000e-01 -3.07061728e-02 3.11512470e-01 6.23340905e-01
-2.83260018e-01 6.65154979e-02 7.58759439e-01 -6.73217475e-02
-1.15836668e+00 5.29833794e-01 -2.96018422e-01 1.76417217e-01
7.18220472e-01 -6.89525843e-01 -3.05286884e-01 -1.13785930e-01
-5.52739084e-01 3.26225013e-01 2.76523203e-01 6.81208670e-01
8.00648689e-01 -1.77125108e+00 -5.18585920e-01 5.46269834e-01
1.22353006e-02 -2.05329955e-01 5.08465290e-01 9.28589106e-01
-3.57719332e-01 1.68588281e-01 -5.45267284e-01 -7.72324622e-01
-7.66329706e-01 2.99899846e-01 5.03896177e-01 -2.31173962e-01
-1.02603436e+00 7.35766232e-01 3.39853495e-01 -1.51786536e-01
1.06614001e-01 -4.05489504e-01 -1.00710131e-01 -1.89961903e-02
5.31283021e-01 4.08846974e-01 6.03111321e-03 -5.62155128e-01
-7.69260585e-01 7.28283286e-01 -1.73333392e-01 4.24804091e-01
1.23356557e+00 1.82333335e-01 1.65910050e-01 3.61245424e-01
1.05577338e+00 -4.15134072e-01 -1.60826302e+00 -8.53964761e-02
-1.28651291e-01 -5.42956054e-01 -2.65606284e-01 -4.99663770e-01
-1.52524376e+00 9.86076653e-01 6.05807602e-01 1.65680274e-02
1.29757714e+00 -3.95479351e-01 1.06736147e+00 2.60984272e-01
4.79643732e-01 -1.13193464e+00 4.02479649e-01 4.73334968e-01
8.69349718e-01 -9.64795291e-01 -9.72253755e-02 -4.85146850e-01
-5.22830784e-01 1.01590443e+00 1.11828196e+00 -5.11652768e-01
5.34199476e-01 1.75874695e-01 -1.87559888e-01 -1.56988595e-02
-4.62267369e-01 -1.20027654e-01 3.85947198e-01 7.75698841e-01
1.48618549e-01 -4.25372571e-02 -5.41379631e-01 9.37041163e-01
1.46342278e-01 1.62565365e-01 1.19118944e-01 1.10328531e+00
-5.23446202e-01 -8.72980893e-01 -2.28826195e-01 5.93291342e-01
-1.02051541e-01 6.33334890e-02 -1.51229694e-01 1.02342153e+00
3.52008075e-01 6.14570618e-01 3.31321061e-02 -8.67128551e-01
6.86413229e-01 1.31830618e-01 2.07613260e-01 -2.35171080e-01
-1.46130383e-01 6.16300143e-02 -8.99030790e-02 -8.92214298e-01
-1.90965220e-01 -5.13609290e-01 -1.24614632e+00 -1.82438120e-01
-2.65797734e-01 9.16023478e-02 -9.27531049e-02 1.02093446e+00
4.84152049e-01 7.73635685e-01 3.04703027e-01 -1.01079059e+00
-3.77966195e-01 -1.06118906e+00 -8.35856140e-01 5.14956951e-01
2.47052535e-01 -1.34467626e+00 -2.51775593e-01 -1.16349105e-02] | [14.333512306213379, 1.3712937831878662] |
94bca121-fb5c-49e3-bade-7970b82230b1 | pgnet-real-time-arbitrarily-shaped-text | 2104.05458 | null | https://arxiv.org/abs/2104.05458v1 | https://arxiv.org/pdf/2104.05458v1.pdf | PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network | The reading of arbitrarily-shaped text has received increasing research attention. However, existing text spotters are mostly built on two-stage frameworks or character-based methods, which suffer from either Non-Maximum Suppression (NMS), Region-of-Interest (RoI) operations, or character-level annotations. In this paper, to address the above problems, we propose a novel fully convolutional Point Gathering Network (PGNet) for reading arbitrarily-shaped text in real-time. The PGNet is a single-shot text spotter, where the pixel-level character classification map is learned with proposed PG-CTC loss avoiding the usage of character-level annotations. With a PG-CTC decoder, we gather high-level character classification vectors from two-dimensional space and decode them into text symbols without NMS and RoI operations involved, which guarantees high efficiency. Additionally, reasoning the relations between each character and its neighbors, a graph refinement module (GRM) is proposed to optimize the coarse recognition and improve the end-to-end performance. Experiments prove that the proposed method achieves competitive accuracy, meanwhile significantly improving the running speed. In particular, in Total-Text, it runs at 46.7 FPS, surpassing the previous spotters with a large margin. | ['Guangming Shi', 'Errui Ding', 'Jingtuo Liu', 'Junyu Han', 'Pengyuan Lyu', 'Xiaoqiang Zhang', 'Shanshan Liu', 'Fei Qi', 'Chengquan Zhang', 'Pengfei Wang'] | 2021-04-12 | null | null | null | null | ['text-spotting', 'scene-text-detection'] | ['computer-vision', 'computer-vision'] | [ 6.92512274e-01 7.56802037e-05 -7.06226602e-02 -2.78175831e-01
-9.17491436e-01 -3.24375153e-01 3.40798736e-01 3.54485482e-01
-5.75888693e-01 3.91608000e-01 -1.58594009e-02 -3.81366670e-01
2.14305341e-01 -7.45682359e-01 -6.51182234e-01 -7.49759257e-01
5.67874849e-01 2.62598515e-01 6.64762437e-01 9.15732011e-02
4.26176429e-01 3.14026028e-01 -1.08764601e+00 1.39230326e-01
1.16531420e+00 1.08249879e+00 6.19086742e-01 1.03521776e+00
-3.74905646e-01 7.21825838e-01 -5.18580377e-01 -7.34771490e-01
-1.31099652e-02 -3.78293931e-01 -2.08977610e-01 1.33165792e-01
5.78559458e-01 -3.97421420e-01 -6.43604636e-01 1.26372480e+00
5.96555471e-01 1.07217431e-01 4.32270527e-01 -6.62086248e-01
-5.59098482e-01 7.53682494e-01 -8.27399254e-01 -1.71735972e-01
1.23708583e-01 1.79350466e-01 1.11431861e+00 -9.55592930e-01
3.34479988e-01 1.12377501e+00 6.53762579e-01 3.25795263e-01
-9.20326352e-01 -2.93748558e-01 3.64582807e-01 1.88608885e-01
-1.34676337e+00 -2.83234358e-01 6.38903141e-01 -1.09346032e-01
8.65619659e-01 4.45400894e-01 5.84759593e-01 8.62981081e-01
1.25428811e-01 1.09961677e+00 4.56121892e-01 -4.82452869e-01
1.58577263e-01 -2.25349620e-01 1.38180584e-01 9.00769174e-01
2.89345324e-01 -5.47042966e-01 -5.42826116e-01 3.25647861e-01
8.29219103e-01 4.02509421e-02 -4.58309174e-01 -2.18073547e-01
-1.36708653e+00 3.29563141e-01 4.24487650e-01 1.49860680e-01
-3.38876247e-02 1.50864631e-01 4.08297896e-01 2.12751841e-03
3.58212829e-01 -2.78264955e-02 -1.95038058e-02 -3.25037777e-01
-1.34596252e+00 -3.29396665e-01 5.75806379e-01 1.25889993e+00
5.74729145e-01 1.14862032e-01 -5.76695383e-01 8.80818248e-01
3.14949870e-01 7.52516687e-01 2.76036859e-01 -7.60490000e-02
9.69933867e-01 7.80639589e-01 -2.19382018e-01 -1.17167485e+00
-3.74716103e-01 -6.55792117e-01 -1.22878540e+00 -1.86968774e-01
3.27274054e-01 -1.34771928e-01 -1.02055943e+00 1.11017013e+00
1.19450271e-01 3.23664904e-01 -1.78118289e-01 1.11227274e+00
4.67819124e-01 9.31201339e-01 -2.29753122e-01 -6.07731156e-02
1.44421840e+00 -1.20245957e+00 -6.69481516e-01 -3.53458852e-01
7.35513210e-01 -6.38532579e-01 1.22683191e+00 5.18644571e-01
-9.14163947e-01 -5.32540023e-01 -1.22727966e+00 -4.71049070e-01
-1.14668608e-01 8.01311255e-01 7.99546018e-02 6.99640632e-01
-7.94276953e-01 4.62218523e-01 -9.87012506e-01 -1.84151754e-01
5.24570107e-01 2.94447452e-01 -3.80487256e-02 -6.24812096e-02
-7.48582006e-01 3.72054100e-01 4.57883060e-01 5.25218606e-01
-6.14058852e-01 -3.61777753e-01 -7.69055843e-01 3.61604214e-01
6.27619982e-01 -2.27635264e-01 8.66297364e-01 -7.26490498e-01
-1.70310974e+00 4.08144683e-01 -2.60027856e-01 -3.92994821e-01
8.52677345e-01 -2.33049199e-01 -4.85199869e-01 1.72872126e-01
-6.16103411e-03 4.04466182e-01 9.83542323e-01 -7.97036648e-01
-9.26892638e-01 -3.41365933e-01 -2.41085410e-01 4.14182544e-01
-6.05229616e-01 -2.61857122e-01 -1.31599486e+00 -8.85315418e-01
2.48910785e-01 -6.99758649e-01 -1.29482210e-01 2.22284049e-01
-9.89016473e-01 1.18054718e-01 8.88636231e-01 -6.36271060e-01
1.40562785e+00 -2.30147505e+00 1.60395995e-01 3.89472917e-02
3.14143240e-01 3.65885586e-01 -2.72792950e-02 1.32135063e-01
4.74767685e-01 -1.59815490e-01 -4.64568555e-01 -6.13665164e-01
1.57829411e-02 -1.62172943e-01 -1.83327481e-01 5.77908158e-01
2.17241853e-01 9.96187806e-01 -7.72835076e-01 -7.06978440e-01
5.12383342e-01 3.65392745e-01 -3.03398430e-01 -4.28408757e-02
-4.71638054e-01 2.29336143e-01 -4.82436776e-01 7.12129295e-01
8.75377774e-01 -4.22962844e-01 2.61163771e-01 -2.63512731e-01
-2.26835161e-01 2.07028631e-02 -1.15714908e+00 1.84993219e+00
-2.03909412e-01 8.94011855e-01 4.35156263e-02 -7.95329332e-01
1.06112671e+00 -1.29317522e-01 -5.15655577e-02 -7.61169314e-01
2.29334921e-01 2.79189289e-01 -2.81183481e-01 -1.88114792e-01
7.79291749e-01 5.34645557e-01 -1.38728261e-01 8.58215541e-02
-2.48219833e-01 1.98362470e-01 3.77696641e-02 2.74961770e-01
1.09667253e+00 1.36362851e-01 -6.25526309e-02 -1.49463505e-01
7.29040504e-01 2.33266577e-02 3.76276553e-01 7.56918669e-01
7.12871924e-02 9.10756111e-01 7.01631188e-01 2.99968608e-02
-1.12648678e+00 -6.44639730e-01 3.49273570e-02 9.61217165e-01
6.46618009e-01 -5.03725529e-01 -9.89490271e-01 -5.48941791e-01
-2.62230277e-01 6.31645679e-01 -3.39112341e-01 1.34763336e-02
-7.83494711e-01 -6.01869524e-01 7.98219800e-01 4.73536909e-01
7.48534441e-01 -7.33072698e-01 -5.87642908e-01 2.83247769e-01
-5.09604663e-02 -1.30034530e+00 -8.35971892e-01 1.79978520e-01
-7.24476874e-01 -7.84686923e-01 -1.26955724e+00 -9.74230051e-01
8.84677529e-01 3.88775915e-01 5.48250675e-01 -5.97425885e-02
-2.84805477e-01 -1.88032955e-01 -4.75406826e-01 1.56511977e-01
-9.43487585e-02 4.18217242e-01 -5.94296694e-01 3.78975749e-01
2.43981585e-01 1.23269949e-02 -7.46515334e-01 3.85048926e-01
-7.18057871e-01 5.18626511e-01 9.81612861e-01 8.61108661e-01
7.71633029e-01 -7.31764883e-02 1.25792056e-01 -7.78550327e-01
4.69797015e-01 -1.25791997e-01 -8.64817917e-01 4.35248375e-01
-4.29279983e-01 -1.64284408e-02 9.64531779e-01 -3.75941157e-01
-8.45056653e-01 2.66993940e-01 -1.66184634e-01 -3.97290111e-01
2.63101347e-02 4.03251588e-01 -4.77043331e-01 2.86325961e-02
3.43614429e-01 8.54359806e-01 -3.39017004e-01 -4.76749539e-01
3.97902191e-01 1.00376987e+00 7.47453451e-01 -1.70696527e-01
7.55756021e-01 3.94637257e-01 -5.21454029e-04 -1.12519288e+00
-6.64839625e-01 -5.09773970e-01 -7.12900877e-01 -2.25342810e-01
1.03259897e+00 -9.90667880e-01 -6.77272141e-01 7.57156253e-01
-1.01561594e+00 -3.52193296e-01 6.22819290e-02 4.28689092e-01
-3.45433593e-01 8.55844855e-01 -6.18362427e-01 -8.53621006e-01
-5.35649836e-01 -1.25012434e+00 1.48301470e+00 3.68118554e-01
3.29747677e-01 -6.08904600e-01 -4.12710309e-01 2.36665517e-01
2.23327622e-01 -1.08157858e-01 8.18369806e-01 -4.50428337e-01
-8.92807722e-01 -3.46806973e-01 -7.19246328e-01 -1.69508327e-02
-1.93801075e-01 -1.31956071e-01 -7.68769383e-01 -3.47542942e-01
-4.33494091e-01 -5.75683825e-02 9.71763849e-01 2.49815375e-01
1.24511302e+00 -4.40592133e-02 -3.65468323e-01 8.44848633e-01
1.48431408e+00 1.57247841e-01 7.48630345e-01 1.06003575e-01
1.23348689e+00 1.51838571e-01 7.69714952e-01 7.00821698e-01
2.78099149e-01 7.34934092e-01 4.96795088e-01 -7.45754093e-02
-3.08919013e-01 -4.56741601e-01 3.25399876e-01 8.84723723e-01
4.10047233e-01 -9.24594045e-01 -8.62379014e-01 2.87773281e-01
-2.05978894e+00 -5.68321407e-01 -5.83353937e-01 2.25702047e+00
5.18610418e-01 5.33241391e-01 -5.31088486e-02 1.70026854e-01
1.17963457e+00 4.11928713e-01 -9.27615821e-01 -3.34025845e-02
-3.51288795e-01 -1.80859268e-01 8.25747848e-01 4.88557100e-01
-1.05851150e+00 1.12276411e+00 4.64276075e+00 1.24220514e+00
-1.13537073e+00 -1.61454394e-01 6.87387943e-01 7.10439533e-02
-1.62750900e-01 -5.52015677e-02 -1.10210991e+00 5.92584193e-01
6.44662559e-01 1.79457858e-01 2.91996062e-01 6.87007070e-01
2.05378681e-01 -3.66541445e-02 -7.79301882e-01 1.17902255e+00
3.04180920e-01 -1.27005887e+00 1.20673828e-01 -1.20907918e-01
4.35029924e-01 -1.07144162e-01 -7.10230321e-02 1.51570976e-01
-1.59201026e-01 -8.35409641e-01 9.04729962e-01 5.64384520e-01
1.33440316e+00 -7.28497505e-01 5.03682852e-01 4.69048500e-01
-1.58316338e+00 4.72257361e-02 -5.28054833e-01 3.52212608e-01
2.64835984e-01 9.03622270e-01 -5.79759061e-01 6.54135048e-01
1.82451934e-01 7.30528474e-01 -5.56876779e-01 1.12188625e+00
-1.19574346e-01 6.15098894e-01 -4.04983521e-01 -6.97565913e-01
4.95137155e-01 -2.18187630e-01 5.99848688e-01 1.49523175e+00
4.05837715e-01 5.58732823e-03 6.75801337e-02 7.70743310e-01
-2.40651354e-01 2.00645775e-01 3.39900330e-03 -1.49857461e-01
4.21005815e-01 1.34492755e+00 -1.11261117e+00 -4.50847387e-01
-4.25342262e-01 1.61480439e+00 3.12833101e-01 1.67365566e-01
-1.11169481e+00 -1.02067697e+00 1.13992482e-01 -2.11917609e-02
5.99180460e-01 -2.29994059e-01 -5.36097407e-01 -1.38543522e+00
4.18321878e-01 -7.74067402e-01 1.37251709e-02 -6.28340960e-01
-7.96842575e-01 4.53943729e-01 -7.24208355e-01 -1.40859675e+00
4.42837954e-01 -6.22348309e-01 -5.08914709e-01 7.63601243e-01
-1.42521024e+00 -1.11313784e+00 -7.20747232e-01 3.89635503e-01
8.74472857e-01 -1.93125047e-02 2.76815593e-01 3.79470199e-01
-1.06313682e+00 1.07667184e+00 4.50362235e-01 4.66234028e-01
6.02519870e-01 -1.16923308e+00 9.14073229e-01 1.08424926e+00
1.82712257e-01 9.22503173e-02 2.38773048e-01 -9.08423901e-01
-1.79310715e+00 -1.33276320e+00 6.33864403e-01 7.53519014e-02
4.72179890e-01 -8.80081117e-01 -9.04905856e-01 2.95101553e-01
-1.61706880e-01 -6.02103919e-02 8.22877064e-02 -3.46877396e-01
-1.47184521e-01 -1.75509471e-02 -8.57950807e-01 9.53770041e-01
1.06915104e+00 -4.08643961e-01 -9.38791409e-02 3.20286155e-01
6.62003517e-01 -6.71387970e-01 -4.87133324e-01 6.28781244e-02
4.18289602e-01 -9.42189395e-01 6.09508753e-01 4.65713590e-02
4.01282787e-01 -4.81459945e-01 -7.46507943e-02 -7.90494800e-01
-3.50774407e-01 -7.10179448e-01 -2.34610766e-01 1.14439285e+00
6.06251597e-01 -3.23886633e-01 1.20446014e+00 2.14467883e-01
-3.73116255e-01 -7.93847084e-01 -9.50441360e-01 -5.65316737e-01
-2.91767538e-01 -5.35162926e-01 4.67446834e-01 5.35064399e-01
2.34141201e-02 6.10027313e-01 -6.45776927e-01 3.64255905e-01
6.40187085e-01 6.06535897e-02 7.31702209e-01 -9.51784968e-01
-4.33157712e-01 -5.76121092e-01 -5.42659581e-01 -2.17557430e+00
-2.67632753e-01 -7.12980151e-01 4.15274441e-01 -1.69858503e+00
1.16620906e-01 -3.76274049e-01 -5.99778555e-02 3.04540813e-01
-4.81329441e-01 8.53253901e-02 1.83747798e-01 2.00147837e-01
-9.40005362e-01 6.27801895e-01 1.24668217e+00 -3.19330603e-01
-2.69578453e-02 -1.66400239e-01 -2.75743932e-01 4.34067577e-01
7.03402877e-01 -3.09312582e-01 -3.22731376e-01 -7.32555509e-01
1.65308535e-01 2.05437094e-01 1.49914503e-01 -1.24443245e+00
7.13502884e-01 1.96346655e-01 4.12753016e-01 -1.14302337e+00
3.34534287e-01 -7.16047108e-01 -2.06924334e-01 4.13029820e-01
-4.49153304e-01 -2.88784176e-01 -1.47036137e-02 1.03083158e+00
1.36302467e-02 -3.98628712e-01 9.72047210e-01 2.92772830e-01
-6.71606839e-01 3.35911155e-01 -1.78330258e-01 -5.49736619e-03
1.08271492e+00 -4.79961902e-01 -3.06551993e-01 -1.00624651e-01
-3.34900439e-01 2.99295634e-01 4.94800448e-01 1.75474167e-01
6.98264420e-01 -9.75322604e-01 -7.33331680e-01 2.79293954e-01
1.50036931e-01 3.30111355e-01 4.15084094e-01 9.90933180e-01
-9.56841588e-01 6.20074034e-01 3.57792109e-01 -7.43837357e-01
-1.03864121e+00 3.26238096e-01 2.10094720e-01 -2.47589216e-01
-1.16276932e+00 9.31217968e-01 8.56878906e-02 -3.64506505e-02
5.87493896e-01 -4.05536056e-01 1.61864571e-02 -4.78937402e-02
5.49753428e-01 3.35472584e-01 1.29341045e-02 -4.82135773e-01
-1.86508954e-01 8.70615721e-01 -3.54751110e-01 -8.95269811e-02
8.17710459e-01 -2.10370123e-01 2.43354335e-01 3.54502469e-01
9.83446717e-01 1.99698016e-01 -1.56147742e+00 -1.80559993e-01
-3.68944183e-02 -4.55976188e-01 2.01658249e-01 -6.57535434e-01
-1.03285480e+00 1.07768500e+00 4.39181447e-01 -3.17108370e-02
1.03817105e+00 -4.75360334e-01 1.21645367e+00 4.26300973e-01
1.40510231e-01 -1.21095598e+00 2.09152363e-02 5.86934686e-01
3.64879370e-01 -1.06907225e+00 -7.18341023e-02 -5.28519630e-01
-6.86056972e-01 1.39626086e+00 5.77700138e-01 -2.23335177e-02
2.28185043e-01 4.43631947e-01 -1.76808953e-01 1.24201432e-01
-5.29736280e-01 -1.60043001e-01 1.64122924e-01 2.96846151e-01
1.17422491e-01 -3.73655111e-02 8.90859496e-03 4.45257187e-01
2.05001295e-01 -1.93168104e-01 3.56866002e-01 7.00809240e-01
-7.48914719e-01 -7.45275736e-01 -1.38378471e-01 7.26386189e-01
-2.53947824e-01 -4.64710414e-01 -3.86361599e-01 3.83575290e-01
-2.16402784e-01 8.93778086e-01 1.56486541e-01 -5.32365799e-01
4.07328546e-01 -3.35169971e-01 5.56198210e-02 -4.55898881e-01
-3.80387902e-01 3.99843425e-01 -2.58609168e-02 -2.60947794e-01
2.06573725e-01 -4.49140906e-01 -1.42961657e+00 -2.73682594e-01
-8.97760987e-01 -1.22341961e-01 5.74629843e-01 6.30496025e-01
4.67000306e-01 5.80610275e-01 6.07850671e-01 -6.50902271e-01
-4.77402568e-01 -9.13889170e-01 -5.22044539e-01 -1.29737318e-01
2.51063406e-01 -4.72366810e-05 -1.89295620e-01 -6.82903826e-02] | [11.984793663024902, 2.2251806259155273] |
a9055bcc-16ec-452d-a86b-0656abf6a9e4 | structured-dialogue-discourse-parsing-1 | 2306.15103 | null | https://arxiv.org/abs/2306.15103v1 | https://arxiv.org/pdf/2306.15103v1.pdf | Structured Dialogue Discourse Parsing | Dialogue discourse parsing aims to uncover the internal structure of a multi-participant conversation by finding all the discourse~\emph{links} and corresponding~\emph{relations}. Previous work either treats this task as a series of independent multiple-choice problems, in which the link existence and relations are decoded separately, or the encoding is restricted to only local interaction, ignoring the holistic structural information. In contrast, we propose a principled method that improves upon previous work from two perspectives: encoding and decoding. From the encoding side, we perform structured encoding on the adjacency matrix followed by the matrix-tree learning algorithm, where all discourse links and relations in the dialogue are jointly optimized based on latent tree-level distribution. From the decoding side, we perform structured inference using the modified Chiu-Liu-Edmonds algorithm, which explicitly generates the labeled multi-root non-projective spanning tree that best captures the discourse structure. In addition, unlike in previous work, we do not rely on hand-crafted features; this improves the model's robustness. Experiments show that our method achieves new state-of-the-art, surpassing the previous model by 2.3 on STAC and 1.5 on Molweni (F1 scores). \footnote{Code released at~\url{https://github.com/chijames/structured_dialogue_discourse_parsing}.} | ['Alexander I. Rudnicky', 'Ta-Chung Chi'] | 2023-06-26 | structured-dialogue-discourse-parsing | https://aclanthology.org/2022.sigdial-1.32 | https://aclanthology.org/2022.sigdial-1.32.pdf | sigdial-acl-2022-9 | ['discourse-parsing'] | ['natural-language-processing'] | [ 3.77894551e-01 7.50059247e-01 -9.88918021e-02 -3.13990384e-01
-1.08663738e+00 -7.64226794e-01 5.59908330e-01 2.80483156e-01
-5.78965656e-02 7.90459573e-01 8.00459385e-01 -5.34550667e-01
-2.43138835e-01 -7.48620629e-01 -5.01147628e-01 -6.42553389e-01
-1.83574289e-01 6.39900088e-01 7.74174882e-03 -5.08246481e-01
2.98810452e-01 -3.29586595e-01 -1.12673092e+00 6.31418705e-01
9.75811183e-01 4.81594950e-01 2.00630859e-01 9.01940405e-01
-3.65022212e-01 1.03376913e+00 -5.51417649e-01 -6.09939814e-01
-2.15349242e-01 -8.58546376e-01 -1.29395962e+00 1.05066739e-01
-9.37435627e-02 -2.33173490e-01 -2.86059916e-01 9.29533005e-01
2.35676005e-01 1.61426798e-01 5.06238818e-01 -7.74586499e-01
-2.64041781e-01 1.05044961e+00 -5.69359899e-01 9.71325114e-02
8.85084748e-01 -1.77714214e-01 1.71542275e+00 -7.70080566e-01
7.58808911e-01 1.37708509e+00 4.13943470e-01 4.30969119e-01
-1.30180967e+00 -3.21536839e-01 2.52221435e-01 3.34735245e-01
-1.03081965e+00 -5.44225574e-01 9.36162174e-01 -5.31484067e-01
9.28021729e-01 5.39250195e-01 3.60867858e-01 1.01483548e+00
-2.09033281e-01 9.34659958e-01 9.77124512e-01 -6.55040085e-01
-3.58775407e-02 -3.26186717e-01 4.50942308e-01 9.47673380e-01
-2.28871211e-01 -3.45310569e-01 -6.91990614e-01 -3.31734002e-01
3.37358922e-01 -7.33440995e-01 -3.33853334e-01 -3.44818011e-02
-1.15183496e+00 1.04795563e+00 -3.75560522e-02 3.58391106e-01
-1.80546179e-01 -2.59593070e-01 4.61558849e-01 4.37001765e-01
4.80310440e-01 2.19470710e-01 -2.33660147e-01 -4.81455475e-01
-5.30412972e-01 2.40982994e-01 1.18996906e+00 7.37654328e-01
7.33882129e-01 -5.32994688e-01 -2.04080507e-01 9.05093253e-01
5.46615481e-01 -7.23132640e-02 2.03825086e-02 -1.37431896e+00
9.30149257e-01 7.14043379e-01 -1.57733217e-01 -1.03790414e+00
-4.37060058e-01 -1.79614723e-01 -6.36952639e-01 -3.11671227e-01
8.79058301e-01 -4.99370813e-01 -7.03623891e-02 1.85464740e+00
4.95849967e-01 -1.58692703e-01 1.39814496e-01 7.21250057e-01
9.61988926e-01 7.16978490e-01 -2.61242956e-01 -5.47632158e-01
1.43322086e+00 -1.07138276e+00 -1.02348566e+00 -7.38312900e-02
9.84632671e-01 -8.08917284e-01 9.26590621e-01 2.69960076e-01
-1.28275490e+00 -1.96610972e-01 -9.13478553e-01 -2.64415562e-01
2.76719004e-01 -5.88591397e-02 5.30408978e-01 5.73658884e-01
-9.88754451e-01 4.35104042e-01 -5.42840064e-01 -1.55903725e-02
1.24318926e-02 3.57802302e-01 -2.05598116e-01 3.25312279e-02
-1.34591329e+00 8.12901974e-01 3.46720099e-01 1.97356686e-01
-3.18388999e-01 -1.36600971e-01 -9.28327501e-01 3.50185335e-02
8.12803268e-01 -5.45855165e-01 1.33444083e+00 -7.22056627e-01
-2.00203180e+00 7.19942033e-01 -6.29128456e-01 -1.65494516e-01
3.57999861e-01 -9.72068608e-02 3.53361107e-02 2.46985257e-01
6.50556237e-02 2.91579574e-01 2.30581746e-01 -1.29877818e+00
-4.57331598e-01 -1.48459002e-01 5.46313941e-01 5.61158657e-01
-1.88310191e-01 1.69914305e-01 -6.40115738e-01 -3.61876458e-01
3.37145329e-01 -9.17749763e-01 -4.86067273e-02 -4.87355232e-01
-9.01311934e-01 -4.53023493e-01 4.01421577e-01 -9.97729421e-01
1.68481529e+00 -1.96048784e+00 7.58333802e-01 2.49376640e-01
3.91177118e-01 -2.67365705e-02 -4.66889143e-02 9.27705526e-01
6.60017729e-02 1.90236285e-01 -4.80447263e-01 -5.58914483e-01
7.74641037e-02 2.22383693e-01 1.17972173e-01 3.91273022e-01
7.83377141e-03 8.34805191e-01 -8.80884767e-01 -6.72692180e-01
5.94863221e-02 1.67017594e-01 -6.55561328e-01 2.00182304e-01
-4.37679738e-01 8.98707330e-01 -4.46572423e-01 2.64424026e-01
2.70541549e-01 -4.96746212e-01 1.05297184e+00 1.08274795e-01
-1.56784341e-01 9.60330069e-01 -1.22537184e+00 1.85107696e+00
-2.61778116e-01 5.99400520e-01 3.74116838e-01 -9.94651437e-01
6.47496879e-01 5.22608936e-01 4.69412625e-01 -3.23352098e-01
2.17878833e-01 6.45369962e-02 4.69690055e-01 -5.86746395e-01
3.85847569e-01 1.85586572e-01 -3.65327418e-01 7.17157423e-01
-7.21961707e-02 3.57609481e-01 3.58755827e-01 5.06761611e-01
1.17660570e+00 1.19944438e-01 3.90209615e-01 -2.30358616e-01
7.80788898e-01 -3.91690694e-02 6.29677713e-01 4.00209665e-01
1.18999362e-01 3.60893369e-01 1.26167214e+00 1.77046478e-01
-7.62911379e-01 -8.22224915e-01 -5.48041873e-02 1.27409565e+00
-2.33675935e-03 -8.82187068e-01 -1.02771795e+00 -5.41681588e-01
-4.89002883e-01 8.38897049e-01 -5.89820027e-01 3.79706949e-01
-1.05103648e+00 -7.04460442e-01 4.53156888e-01 8.45989659e-02
4.18161243e-01 -8.37381184e-01 -1.86229140e-01 2.77305931e-01
-8.94519210e-01 -1.08785224e+00 -3.83905053e-01 -7.60354921e-02
-5.70432603e-01 -1.24371552e+00 -2.45682657e-01 -6.56210005e-01
4.67141420e-01 1.35596851e-02 9.24515665e-01 3.04582298e-01
2.06654251e-01 1.75632596e-01 -5.96303225e-01 2.00447038e-01
-6.24483824e-01 2.48680830e-01 -3.41787964e-01 -7.87194073e-03
1.27971880e-02 -5.53153992e-01 -3.86881143e-01 1.14554286e-01
-3.21068734e-01 4.22783434e-01 1.20386578e-01 1.07403219e+00
1.96518317e-01 -2.00365297e-02 4.58378792e-01 -1.25408471e+00
8.79215419e-01 -5.74990869e-01 -2.09259853e-01 3.36987942e-01
-2.40715310e-01 -1.79683454e-02 3.96572888e-01 -1.49736688e-01
-1.26457345e+00 -1.28289938e-01 -3.21584374e-01 2.84846663e-01
1.44598447e-02 7.26133764e-01 -5.05745888e-01 4.03067112e-01
2.99080878e-01 -5.38041927e-02 -7.92282168e-03 -4.44005698e-01
5.48076689e-01 5.68947613e-01 2.39726588e-01 -8.62723112e-01
5.35569966e-01 1.19551904e-01 -1.43195137e-01 -9.74439383e-01
-9.30497825e-01 -3.65418851e-01 -9.27146018e-01 -3.85213375e-01
1.06689155e+00 -6.18727148e-01 -1.12851965e+00 8.02572742e-02
-1.44873738e+00 -4.01517779e-01 -1.94266124e-03 4.32168901e-01
-5.34940541e-01 8.48813534e-01 -9.41682816e-01 -1.03566241e+00
-9.58324298e-02 -1.10542345e+00 8.24179113e-01 -5.16207963e-02
-7.39112437e-01 -1.21401501e+00 8.96868780e-02 9.36549842e-01
-1.34705782e-01 2.92359591e-01 1.23628914e+00 -7.79047847e-01
-6.37864292e-01 2.37265185e-01 -8.84453580e-02 6.42791837e-02
2.19952874e-02 -2.84210611e-02 -8.90442848e-01 -1.06506787e-01
3.79844680e-02 -1.80063024e-01 6.53942227e-01 1.49718210e-01
6.36901021e-01 -4.97331172e-01 -1.47374913e-01 1.54060766e-01
9.21430945e-01 1.48170441e-01 4.14871544e-01 1.50481775e-01
7.04064488e-01 1.12236774e+00 3.75641555e-01 5.06913960e-01
8.87749195e-01 7.95676470e-01 2.37780437e-01 2.69331008e-01
5.85705936e-02 -2.26329684e-01 5.60050547e-01 1.32450771e+00
-1.61434039e-01 -5.10155916e-01 -9.58906054e-01 3.80669862e-01
-2.19770288e+00 -9.98389363e-01 -6.35964453e-01 1.92521751e+00
1.04751122e+00 1.81669250e-01 1.79735318e-01 2.63242573e-01
7.23793328e-01 3.79948139e-01 -1.44223288e-01 -3.99888277e-01
-1.37983024e-01 1.76245093e-01 -5.91336414e-02 1.11738503e+00
-8.53557527e-01 8.55797708e-01 5.47304821e+00 7.19946861e-01
-4.01199788e-01 2.85666257e-01 4.38801199e-01 3.56733650e-02
-5.72142899e-01 2.74783075e-01 -7.34304428e-01 2.76597351e-01
9.41107392e-01 -6.62558451e-02 5.14160275e-01 2.02825725e-01
1.07177354e-01 -3.58851463e-01 -1.03277290e+00 4.26319778e-01
-6.38593510e-02 -1.39472699e+00 -4.34092313e-01 2.81490564e-01
4.29172516e-01 -4.85755950e-01 -2.29489565e-01 2.48810187e-01
5.18296778e-01 -8.78690183e-01 5.52478075e-01 4.39677179e-01
6.62745595e-01 -5.67557633e-01 5.38709700e-01 6.63141549e-01
-1.19035852e+00 3.78382318e-02 2.38146856e-01 -3.82809699e-01
3.88817281e-01 4.35188383e-01 -8.44670653e-01 7.85988390e-01
2.51451135e-01 3.94653797e-01 -7.48904496e-02 4.03077215e-01
-5.54359019e-01 9.47557092e-01 -1.81439191e-01 -1.14034370e-01
1.27357408e-01 -4.65599924e-01 7.76897132e-01 1.17373395e+00
3.30143124e-02 5.44979215e-01 4.31848735e-01 6.71472490e-01
-8.85231197e-02 2.65242249e-01 -4.25357044e-01 1.50088936e-01
6.60938919e-01 1.04780853e+00 -6.70974910e-01 -1.07304178e-01
-4.28233773e-01 9.07392681e-01 4.97720093e-01 1.80066034e-01
-5.75375140e-01 -9.05234814e-02 3.49175155e-01 -1.78533733e-01
2.47097105e-01 -4.63228256e-01 -3.40934008e-01 -1.10525417e+00
5.64606450e-02 -9.45031762e-01 3.84149700e-01 -1.24559067e-01
-1.14468205e+00 4.18321878e-01 1.44434899e-01 -7.84395695e-01
-6.90197229e-01 -3.63097489e-01 -8.02379310e-01 9.79975104e-01
-1.14795756e+00 -1.06614089e+00 2.32071310e-01 4.31860864e-01
6.84215963e-01 4.07015868e-02 1.15788746e+00 1.63825065e-01
-8.82681072e-01 5.38567245e-01 1.48370251e-01 4.28513080e-01
4.70397323e-01 -1.31877005e+00 2.40108684e-01 6.02068424e-01
1.52879104e-01 7.41919994e-01 6.55789852e-01 -6.15706384e-01
-1.41838479e+00 -4.21350002e-01 1.39635372e+00 -4.39531088e-01
9.38257396e-01 -5.63100219e-01 -9.93515611e-01 6.79164588e-01
6.48665071e-01 -6.90844178e-01 1.16438198e+00 6.83889925e-01
-1.48007900e-01 5.04752874e-01 -7.37677157e-01 5.62599123e-01
1.11770892e+00 -6.04005575e-01 -7.48668373e-01 4.06600922e-01
7.15982556e-01 -6.73635423e-01 -1.08191061e+00 2.16634557e-01
3.47169429e-01 -1.09224510e+00 7.58178115e-01 -4.19673234e-01
6.89042687e-01 -3.86238508e-02 -3.66377950e-01 -9.33018863e-01
-2.85378277e-01 -9.98316169e-01 -2.89436460e-01 1.43956113e+00
7.66023815e-01 -4.64554608e-01 6.55378044e-01 3.97936642e-01
-2.13725343e-01 -8.86767805e-01 -1.07182395e+00 -2.43054211e-01
1.50536701e-01 -3.82613659e-01 2.83320814e-01 1.02881169e+00
5.44945896e-01 9.08604562e-01 -4.68779266e-01 6.32383153e-02
6.27105296e-01 3.25759113e-01 6.70794189e-01 -1.12552500e+00
-7.53395021e-01 -4.57673997e-01 4.31908518e-01 -1.32560372e+00
4.60550010e-01 -9.91493464e-01 -4.96190898e-02 -1.68889511e+00
1.05357103e-01 -3.76609296e-01 2.26398662e-01 3.20618659e-01
-2.22687364e-01 -2.34452292e-01 3.83260816e-01 2.86918402e-01
-7.89977610e-01 6.00276351e-01 1.25212276e+00 4.36280109e-02
-2.43030459e-01 1.15606934e-01 -8.04786265e-01 8.58126640e-01
7.83510566e-01 -3.18506390e-01 -3.70743603e-01 -3.12879354e-01
2.15903893e-01 8.20310891e-01 7.56331012e-02 -3.74887258e-01
3.74188006e-01 -1.38384387e-01 -1.98927104e-01 -5.04459620e-01
6.58486724e-01 -1.86709419e-01 -2.92011797e-02 2.13046104e-01
-6.83891416e-01 -6.30068853e-02 -1.54642418e-01 5.39512515e-01
-1.54103741e-01 -5.47631502e-01 2.34053224e-01 -1.66291580e-01
-2.33509660e-01 -2.43192673e-01 -5.83554864e-01 2.48166591e-01
7.43833423e-01 5.11626489e-02 -4.02301133e-01 -5.73506594e-01
-8.34824026e-01 3.72834444e-01 9.94728357e-02 9.27126408e-02
3.45029026e-01 -1.00800824e+00 -9.20059562e-01 -1.84096694e-01
-2.59773761e-01 1.78669989e-01 3.18807662e-01 1.08373189e+00
-1.83513477e-01 3.66835505e-01 1.97729543e-01 -4.31032389e-01
-1.58345354e+00 1.65641531e-02 -2.92368140e-02 -7.09293902e-01
-6.07709885e-01 9.61848617e-01 5.01019917e-02 -5.59518456e-01
2.22563624e-01 1.30674914e-01 -4.57240999e-01 4.08111632e-01
2.39594847e-01 3.82811576e-01 -2.45490059e-01 -8.65858257e-01
-1.59799293e-01 3.78057182e-01 -5.07242270e-02 -3.78796130e-01
1.23620963e+00 -4.21947509e-01 -5.06509185e-01 7.45377123e-01
1.15499604e+00 4.05208468e-01 -9.19108808e-01 -5.03166080e-01
2.94998020e-01 -2.37757161e-01 -2.54356772e-01 -6.09566212e-01
-4.98875558e-01 8.56579661e-01 -2.40375429e-01 4.32998538e-01
7.70019650e-01 7.78911859e-02 7.63385236e-01 4.01735365e-01
1.25100330e-01 -9.48288620e-01 2.10849464e-01 9.31180239e-01
8.11100185e-01 -1.08587623e+00 1.61789767e-02 -9.24159527e-01
-8.79754841e-01 1.09792721e+00 3.09733123e-01 7.65866041e-02
4.79687870e-01 2.84197211e-01 -1.17998429e-01 -2.88344175e-01
-9.69966948e-01 -2.17925742e-01 2.97473818e-01 1.14930063e-01
8.47904503e-01 1.47958845e-01 -6.14928186e-01 6.04686856e-01
-4.88427013e-01 -5.25538862e-01 3.93742740e-01 7.34090030e-01
-3.66798580e-01 -1.73484945e+00 -2.85096020e-01 2.87988812e-01
-3.56244177e-01 -1.79246068e-01 -6.43622041e-01 6.72378778e-01
-1.00501046e-01 1.41991532e+00 -1.97769925e-01 -6.08198643e-01
2.03848109e-01 3.30376089e-01 4.68762904e-01 -7.64624000e-01
-8.20386171e-01 3.83612454e-01 9.99361753e-01 -2.11762607e-01
-5.28476655e-01 -9.94001567e-01 -1.50382471e+00 -5.14152229e-01
-4.72418129e-01 3.96708816e-01 3.16823274e-01 1.09659827e+00
1.22178622e-01 7.55988836e-01 7.13393211e-01 -5.80136418e-01
-4.88940150e-01 -9.93714213e-01 -1.86861783e-01 1.60011709e-01
1.29138514e-01 -5.20899177e-01 -2.25524083e-01 -1.20982639e-01] | [12.494017601013184, 7.965246677398682] |
33044c8d-f198-43ee-885c-bcf8df4e5fc3 | jointprop-joint-semi-supervised-learning-for | 2305.15872 | null | https://arxiv.org/abs/2305.15872v1 | https://arxiv.org/pdf/2305.15872v1.pdf | Jointprop: Joint Semi-supervised Learning for Entity and Relation Extraction with Heterogeneous Graph-based Propagation | Semi-supervised learning has been an important approach to address challenges in extracting entities and relations from limited data. However, current semi-supervised works handle the two tasks (i.e., Named Entity Recognition and Relation Extraction) separately and ignore the cross-correlation of entity and relation instances as well as the existence of similar instances across unlabeled data. To alleviate the issues, we propose Jointprop, a Heterogeneous Graph-based Propagation framework for joint semi-supervised entity and relation extraction, which captures the global structure information between individual tasks and exploits interactions within unlabeled data. Specifically, we construct a unified span-based heterogeneous graph from entity and relation candidates and propagate class labels based on confidence scores. We then employ a propagation learning scheme to leverage the affinities between labelled and unlabeled samples. Experiments on benchmark datasets show that our framework outperforms the state-of-the-art semi-supervised approaches on NER and RE tasks. We show that the joint semi-supervised learning of the two tasks benefits from their codependency and validates the importance of utilizing the shared information between unlabeled data. | ['Anh Tuan Luu', 'Anran Hao', 'Yandan Zheng'] | 2023-05-25 | null | null | null | null | ['relation-extraction'] | ['natural-language-processing'] | [-1.08224200e-02 6.32363200e-01 -7.18669355e-01 -5.81365824e-01
-7.47007370e-01 -7.61773050e-01 6.43276989e-01 5.79725266e-01
-3.30710232e-01 8.31678748e-01 1.63112223e-01 -1.60073921e-01
-1.20421037e-01 -7.42999732e-01 -5.17016292e-01 -3.51101071e-01
-1.20668516e-01 7.10297167e-01 4.14118618e-01 1.32540777e-01
-2.70610362e-01 2.82824457e-01 -1.03102696e+00 7.85642341e-02
9.49928582e-01 7.58215427e-01 -2.72941172e-01 1.67465985e-01
-3.74259263e-01 1.09597898e+00 -1.39021933e-01 -7.67237782e-01
-2.30283123e-02 -2.25931525e-01 -1.36309838e+00 1.20118529e-01
1.51514977e-01 1.66762158e-01 -3.36540282e-01 1.07538736e+00
2.40038887e-01 -7.43410224e-03 6.72287643e-01 -1.36731434e+00
-5.92061341e-01 1.07378793e+00 -8.48448873e-01 9.44111943e-02
2.17106715e-01 -5.48923373e-01 1.49893248e+00 -9.70436096e-01
9.23846722e-01 8.75524461e-01 8.27244222e-01 2.01598868e-01
-1.20056212e+00 -4.87294257e-01 3.45207721e-01 7.55332410e-02
-1.69412398e+00 -3.51059377e-01 6.94763303e-01 -3.64883363e-01
1.05312967e+00 -8.08732435e-02 1.20732546e-01 7.28920698e-01
-3.72966498e-01 9.03081238e-01 8.70505154e-01 -6.24898374e-01
8.90138075e-02 3.40952337e-01 7.00194061e-01 8.96234751e-01
5.37191868e-01 -2.21028864e-01 -5.92817247e-01 -2.63647586e-01
2.79977262e-01 -1.36819556e-01 -2.56050110e-01 -5.70827246e-01
-1.06159008e+00 4.82565135e-01 3.47642332e-01 3.84183317e-01
-3.85811001e-01 -3.83455843e-01 3.86409611e-01 6.48025237e-03
7.70017385e-01 3.69432807e-01 -8.67289245e-01 3.63638908e-01
-9.24479008e-01 -3.22387248e-01 1.28283167e+00 1.33294368e+00
1.03534555e+00 -4.79550391e-01 -1.27014697e-01 8.89109492e-01
4.77603883e-01 1.20425619e-01 1.54783994e-01 -3.92420948e-01
7.18100965e-01 1.05006742e+00 -5.97806945e-02 -8.86252999e-01
-4.62465912e-01 -4.15066600e-01 -6.70655012e-01 -4.74279553e-01
2.79684991e-01 -4.17016149e-01 -8.72141540e-01 1.77700102e+00
7.92181432e-01 2.93153703e-01 2.29656085e-01 5.40496409e-01
1.21311498e+00 1.45621315e-01 3.45787466e-01 -3.47049326e-01
1.29487944e+00 -1.36460924e+00 -8.66919398e-01 -3.05950761e-01
9.47172225e-01 -4.31078315e-01 3.47443134e-01 -2.97203571e-01
-6.92979813e-01 -3.01130325e-01 -9.56497669e-01 -5.57067394e-02
-6.96398795e-01 2.33702660e-01 7.65726089e-01 4.71182108e-01
-6.40921414e-01 6.27017081e-01 -1.04417086e+00 -4.48960185e-01
3.62181902e-01 4.71217126e-01 -7.33332753e-01 -7.51029998e-02
-1.35207427e+00 8.91333103e-01 8.37691545e-01 2.51343817e-01
-3.14608932e-01 -4.38739359e-01 -1.14649069e+00 1.53289542e-01
8.80486548e-01 -4.95511889e-01 9.11113858e-01 -5.30331671e-01
-9.98740315e-01 9.29369628e-01 -3.40318859e-01 -3.97339135e-01
1.14987180e-01 -2.22783446e-01 -6.51431262e-01 3.93853709e-02
2.10935384e-01 2.75788367e-01 2.39244327e-01 -1.28423548e+00
-7.46092498e-01 -4.54562247e-01 -3.72545384e-02 2.50986040e-01
-4.63744223e-01 8.73532668e-02 -8.11382353e-01 -2.46713638e-01
2.96032101e-01 -9.03119564e-01 -1.46824554e-01 -5.43545663e-01
-9.85417962e-01 -5.41156530e-01 7.58030355e-01 -4.71590459e-01
1.37521195e+00 -1.90802872e+00 1.30289957e-01 4.04185832e-01
6.53640985e-01 2.39109635e-01 3.50035056e-02 5.45930147e-01
-8.66872817e-02 3.35485578e-01 -1.96877375e-01 -5.68936944e-01
-7.18543604e-02 2.58906990e-01 6.90616071e-02 2.91948855e-01
4.67698127e-01 1.08970368e+00 -1.22119510e+00 -1.01028442e+00
-2.75558442e-01 4.28645015e-01 1.28477439e-01 2.47666672e-01
8.62273127e-02 3.40881407e-01 -7.18355417e-01 7.39684403e-01
5.39244592e-01 -8.24172914e-01 7.96837151e-01 -3.83503556e-01
1.55938685e-01 5.07856607e-01 -1.24060714e+00 1.50084758e+00
-1.73426762e-01 2.25402370e-01 -8.85398220e-03 -9.48640049e-01
7.28177965e-01 5.17245948e-01 5.06599486e-01 -4.32168096e-02
-1.22058496e-01 2.96274006e-01 -2.96980888e-01 -4.74115431e-01
3.59578252e-01 9.46706459e-02 -1.69536415e-02 6.18669093e-01
6.50670350e-01 2.83541441e-01 5.01765728e-01 6.28879666e-01
1.26338196e+00 4.03837621e-01 6.75272763e-01 -4.74838959e-03
4.96200413e-01 2.44897697e-02 8.43712926e-01 6.70841098e-01
-6.87023401e-02 3.78813982e-01 4.99135941e-01 -2.06361692e-02
-5.47478557e-01 -8.71271253e-01 4.90952879e-02 1.09229791e+00
2.75927216e-01 -7.97950029e-01 -4.53546941e-01 -1.55500233e+00
-1.49868708e-02 3.81318480e-01 -6.94742262e-01 -5.92915751e-02
-3.78508925e-01 -8.37421298e-01 5.22477388e-01 6.67165816e-01
3.35995555e-01 -6.84552312e-01 2.82240242e-01 1.78703398e-01
-2.89000362e-01 -1.67536020e+00 -2.71497965e-01 5.88371396e-01
-6.89115047e-01 -1.21454906e+00 -3.18191081e-01 -9.67660546e-01
9.06728804e-01 1.19929440e-01 1.36585665e+00 2.95249261e-02
1.53171957e-01 3.88948441e-01 -4.96981353e-01 -2.55706068e-02
-2.05397189e-01 5.99351823e-01 -6.96870536e-02 5.10402173e-02
6.62052155e-01 -6.19297445e-01 -1.86471581e-01 3.36348414e-01
-5.47822595e-01 2.85055563e-02 6.32253766e-01 9.13560152e-01
7.41109610e-01 1.88189372e-01 6.79232836e-01 -1.71859992e+00
3.75334233e-01 -7.42484748e-01 -3.28195632e-01 9.20264482e-01
-9.73664343e-01 3.61424804e-01 2.71459252e-01 -3.08564514e-01
-1.32326615e+00 2.95783132e-01 3.61982405e-01 -7.07688183e-02
-2.00937733e-01 9.26751375e-01 -3.62241894e-01 1.89275164e-02
4.21760976e-01 -1.78013682e-01 -5.81327379e-01 -4.21933949e-01
6.48453593e-01 7.47636318e-01 4.83562231e-01 -5.60422540e-01
9.33471560e-01 4.87487078e-01 -4.98856716e-02 -4.80756253e-01
-1.45762861e+00 -9.25247490e-01 -1.18350303e+00 1.43030882e-01
8.13194573e-01 -1.01449955e+00 -3.10496300e-01 2.15445653e-01
-1.16759932e+00 4.65015024e-02 -3.52830946e-01 6.11347139e-01
1.79210715e-02 5.00370741e-01 -9.51669931e-01 -7.79606223e-01
-3.81600827e-01 -6.72785580e-01 1.00480735e+00 3.41653764e-01
-2.12575734e-01 -1.31829095e+00 3.22271228e-01 4.07028407e-01
-7.92229772e-02 1.84124023e-01 7.00826585e-01 -1.43597937e+00
-4.08633202e-01 -5.64936817e-01 -4.99191493e-01 5.98869771e-02
4.58469659e-01 -1.62746295e-01 -9.26009417e-01 1.00745641e-01
-4.51290637e-01 -6.01261258e-01 9.61715996e-01 -1.96283937e-01
3.78281623e-01 -1.63997576e-01 -8.41708422e-01 2.74494976e-01
1.18763709e+00 -4.23574656e-01 1.09036677e-01 4.00744602e-02
1.24622393e+00 9.73309815e-01 5.74977517e-01 2.06011966e-01
8.97389174e-01 4.40420896e-01 -5.18498896e-03 -3.14333528e-01
-6.63501397e-02 -4.97379512e-01 -1.81511045e-02 1.01461232e+00
-1.36331469e-01 -2.73374289e-01 -1.05164385e+00 5.97680807e-01
-2.13784170e+00 -6.31550908e-01 -3.56572747e-01 2.00195575e+00
1.19036758e+00 1.24667659e-01 -6.64380714e-02 -3.81578207e-02
1.05687761e+00 1.16581239e-01 -3.53171110e-01 2.87608892e-01
-2.79033691e-01 1.99453890e-01 6.42718256e-01 3.20288122e-01
-1.38266075e+00 1.23371124e+00 5.72894239e+00 6.45197928e-01
-6.19807363e-01 2.45630935e-01 3.75951648e-01 4.68561739e-01
-1.68007061e-01 2.97684848e-01 -1.08140492e+00 -1.28818164e-02
9.52613533e-01 -8.09251294e-02 -2.31544557e-03 7.53153265e-01
-3.67395520e-01 6.78881556e-02 -1.30628681e+00 4.21458185e-01
-6.21600337e-02 -1.00359595e+00 -3.16034734e-01 -9.14266929e-02
9.27661657e-01 3.01331192e-01 -5.05813897e-01 4.06403333e-01
9.93299603e-01 -6.19920373e-01 3.83916438e-01 2.77295530e-01
5.18840015e-01 -4.52344179e-01 1.03339148e+00 3.77863079e-01
-1.68121588e+00 3.54662389e-01 2.92598177e-02 3.06306481e-01
3.14244956e-01 8.91945720e-01 -8.40060651e-01 1.17060411e+00
4.06136274e-01 9.75402772e-01 -5.32880127e-01 6.91114068e-01
-7.80531764e-01 7.33847737e-01 -4.16338742e-01 2.48560742e-01
-4.96339165e-02 -7.67651871e-02 2.42338255e-01 1.45111799e+00
-1.91065088e-01 3.26679647e-02 4.58751500e-01 8.12072814e-01
-4.39495623e-01 3.47138226e-01 -4.70684052e-01 -4.41668004e-01
6.46295607e-01 1.60706329e+00 -9.13829684e-01 -4.52196896e-01
-8.43511701e-01 9.34227467e-01 1.06360066e+00 5.16479254e-01
-5.74638367e-01 -5.30052900e-01 -2.73899687e-03 -2.46909305e-01
4.86429989e-01 -2.22040474e-01 -1.98341340e-01 -1.43193793e+00
4.32635061e-02 -2.99007684e-01 8.01970601e-01 -3.16018552e-01
-1.46682644e+00 7.31588364e-01 -7.64905587e-02 -9.68724012e-01
-2.08853051e-01 -2.32317567e-01 -4.67246771e-01 7.24610209e-01
-1.83915341e+00 -1.55387008e+00 -9.47915018e-02 3.85136098e-01
-2.05343403e-03 1.51059136e-01 8.87872040e-01 2.84285605e-01
-9.49880242e-01 6.55427456e-01 -2.02273622e-01 6.78866923e-01
8.29000711e-01 -1.47129965e+00 3.25120687e-01 9.68135774e-01
6.21218920e-01 8.81832659e-01 1.86662406e-01 -9.20429111e-01
-1.00254571e+00 -1.20248771e+00 1.55147719e+00 -4.82353657e-01
8.89245212e-01 -3.63672465e-01 -1.02159214e+00 1.02175796e+00
9.31938961e-02 5.79622507e-01 1.10039854e+00 7.06975162e-01
-8.50926578e-01 1.60012320e-01 -9.09033060e-01 2.62879461e-01
1.26152122e+00 -7.63308048e-01 -6.30180299e-01 3.94769520e-01
7.87866473e-01 -2.60490328e-01 -1.07309759e+00 6.38767958e-01
2.40878955e-01 -6.56126440e-01 7.44241059e-01 -8.39184344e-01
2.77962804e-01 -3.83934081e-01 9.35281217e-02 -1.10318446e+00
-1.29481539e-01 -5.52204669e-01 -7.15116918e-01 1.85249233e+00
1.13070047e+00 -5.69520652e-01 7.75600135e-01 8.96884203e-01
2.72535712e-01 -6.81197107e-01 -4.14268255e-01 -7.41491795e-01
-3.61845225e-01 -1.23735636e-01 3.56825054e-01 1.37376201e+00
5.11441171e-01 9.62408721e-01 -3.32827717e-01 6.16758764e-01
6.93638146e-01 3.95753860e-01 4.71675515e-01 -1.45782495e+00
-3.96275282e-01 1.03255764e-01 -2.88488090e-01 -8.81259084e-01
6.38723314e-01 -1.12470472e+00 9.79820341e-02 -1.69580734e+00
4.73417640e-01 -6.46619260e-01 -5.49731910e-01 8.18009555e-01
-6.25135899e-01 1.22421369e-01 -2.16729656e-01 5.91861248e-01
-1.30167866e+00 4.02812243e-01 7.82610059e-01 1.44340834e-02
-3.93554062e-01 -8.66250917e-02 -7.14544594e-01 8.19162846e-01
5.07506311e-01 -7.60109067e-01 -3.62593472e-01 -3.23810309e-01
2.61245221e-01 -1.20647341e-01 -1.22082479e-01 -5.66741586e-01
6.90093875e-01 2.63059810e-02 1.22450460e-02 -4.58317578e-01
-1.44573729e-02 -8.40239763e-01 -1.01465099e-01 -1.50984645e-01
-5.38560092e-01 -4.37419623e-01 -2.81599075e-01 9.64602172e-01
-4.20953482e-01 -8.05007294e-02 2.93738514e-01 4.71380167e-02
-5.99016130e-01 4.38348621e-01 2.77084380e-01 4.09569353e-01
8.99713635e-01 2.16242328e-01 -3.86053145e-01 -7.34211579e-02
-9.97100294e-01 6.06884360e-01 9.49727371e-02 2.13493332e-01
1.70403957e-01 -1.18903637e+00 -6.16887808e-01 -2.29008302e-01
4.52682257e-01 2.95973361e-01 -3.25802043e-02 9.89839911e-01
1.49268940e-01 2.70096481e-01 3.34362924e-01 -2.93561429e-01
-1.35216272e+00 5.95170617e-01 1.10862553e-01 -1.01187789e+00
-2.95365214e-01 8.67593110e-01 -3.31523009e-02 -7.04168379e-01
2.19685063e-01 7.30489045e-02 -6.04147434e-01 1.97308943e-01
1.98886663e-01 2.26642638e-01 1.07821994e-01 -7.12275088e-01
-6.07579410e-01 2.51635700e-01 -4.93563533e-01 -3.27752866e-02
1.28647900e+00 -3.44828248e-01 -3.81276011e-01 5.24975240e-01
1.02208042e+00 2.41877303e-01 -9.28635359e-01 -8.97038937e-01
7.38296449e-01 6.24510087e-02 -9.89909545e-02 -7.57755995e-01
-1.07955301e+00 5.13703108e-01 -2.70807981e-01 3.40946466e-01
7.43277371e-01 5.16674101e-01 6.22186959e-01 4.59342957e-01
3.52259219e-01 -9.97711599e-01 -3.28982025e-01 5.69819927e-01
1.72502443e-01 -1.50739086e+00 2.36949638e-01 -1.21196997e+00
-7.57727385e-01 8.11769009e-01 6.47205412e-01 3.12052697e-01
9.04797494e-01 4.96825546e-01 -2.43687984e-02 -3.58808458e-01
-7.06433356e-01 -6.65754080e-01 6.03887439e-01 6.28800809e-01
7.14682341e-01 1.41599523e-02 -3.77062917e-01 9.31311309e-01
3.55985910e-01 -9.12068337e-02 4.08996902e-02 1.26816130e+00
-1.57463329e-03 -1.44243228e+00 2.58538127e-01 3.31934333e-01
-6.63510382e-01 -3.97377074e-01 -8.61152887e-01 6.49207056e-01
7.14671239e-02 1.05752301e+00 -4.22707796e-01 -5.31458795e-01
9.40850899e-02 3.49899709e-01 2.20597282e-01 -1.01926053e+00
-6.16896689e-01 -5.64602315e-02 5.21408498e-01 -2.50823855e-01
-8.80921900e-01 -3.90985757e-01 -1.48302829e+00 1.41590700e-01
-9.95363712e-01 5.35564423e-01 3.96831959e-01 1.24672163e+00
6.29540920e-01 4.96130884e-01 5.36966205e-01 -3.71422201e-01
-4.13210064e-01 -9.68487442e-01 -8.50219250e-01 5.00132084e-01
-4.80004586e-02 -6.64583743e-01 -4.51983839e-01 8.79266933e-02] | [9.273602485656738, 8.61877727508545] |
4f00e496-347a-49dd-bf73-e1c3b1a10cb3 | shuowen-jiezi-linguistically-informed | 2106.00400 | null | https://arxiv.org/abs/2106.00400v3 | https://arxiv.org/pdf/2106.00400v3.pdf | Sub-Character Tokenization for Chinese Pretrained Language Models | Tokenization is fundamental to pretrained language models (PLMs). Existing tokenization methods for Chinese PLMs typically treat each character as an indivisible token. However, they ignore the unique feature of the Chinese writing system where additional linguistic information exists below the character level, i.e., at the sub-character level. To utilize such information, we propose sub-character (SubChar for short) tokenization. Specifically, we first encode the input text by converting each Chinese character into a short sequence based on its glyph or pronunciation, and then construct the vocabulary based on the encoded text with sub-word segmentation. Experimental results show that SubChar tokenizers have two main advantages over existing tokenizers: 1) They can tokenize inputs into much shorter sequences, thus improving the computational efficiency. 2) Pronunciation-based SubChar tokenizers can encode Chinese homophones into the same transliteration sequences and produce the same tokenization output, hence being robust to homophone typos. At the same time, models trained with SubChar tokenizers perform competitively on downstream tasks. We release our code and models at https://github.com/thunlp/SubCharTokenization to facilitate future work. | ['Qun Liu', 'Yasheng Wang', 'Maosong Sun', 'Zhiyuan Liu', 'Xiaozhi Wang', 'Fanchao Qi', 'Yingfa Chen', 'Zhengyan Zhang', 'Chenglei Si'] | 2021-06-01 | null | null | null | null | ['transliteration'] | ['natural-language-processing'] | [ 4.48628850e-02 -1.45729706e-01 -5.94035447e-01 -2.48980433e-01
-7.31636941e-01 -9.08446133e-01 9.44721699e-02 8.16285759e-02
-8.13154757e-01 7.03996122e-01 4.11942959e-01 -7.05561161e-01
7.21339762e-01 -8.41941237e-01 -7.17534721e-01 -4.15482789e-01
5.90973139e-01 1.90017194e-01 -2.54237186e-02 6.14113323e-02
1.40311390e-01 2.05010965e-01 -6.53379083e-01 4.80015129e-01
1.38912320e+00 3.63254696e-01 6.24238372e-01 6.33942544e-01
-5.53794265e-01 4.66147840e-01 -6.91978633e-01 -5.12538135e-01
9.93764326e-02 -4.98274744e-01 -9.44340527e-01 -3.99697125e-02
1.83210503e-02 -3.24521989e-01 -1.45097688e-01 1.13620412e+00
1.57107487e-01 1.31535996e-02 5.31045735e-01 -5.89594841e-01
-1.22539687e+00 1.53164661e+00 -2.76114523e-01 -1.52385831e-01
1.39249966e-01 -4.84213904e-02 1.23564804e+00 -1.18631196e+00
5.11585116e-01 1.14730561e+00 4.73093599e-01 7.37944722e-01
-1.15602362e+00 -7.44439840e-01 5.60627401e-01 -8.32488313e-02
-1.53195453e+00 -2.22248077e-01 3.28428596e-01 -1.76365480e-01
1.22844815e+00 1.98726699e-01 4.94255543e-01 6.69817567e-01
1.09927505e-02 1.20946550e+00 6.28887057e-01 -7.51964688e-01
-3.26176137e-02 1.48823068e-01 2.16617271e-01 4.02615637e-01
1.57104701e-01 -5.71814775e-01 -3.91676128e-01 3.59069556e-01
8.12491596e-01 7.83511251e-02 -2.30536923e-01 5.50250769e-01
-1.33237684e+00 6.83587313e-01 1.71773538e-01 5.76992512e-01
-1.13378204e-01 4.24902707e-01 4.94207233e-01 1.54676348e-01
3.16732466e-01 5.53678870e-01 -6.78491056e-01 -3.77386630e-01
-8.99599910e-01 -9.21899676e-02 6.85408950e-01 1.51196897e+00
9.80854571e-01 3.34044933e-01 -2.16994435e-01 1.04580903e+00
3.26757468e-02 5.62103868e-01 9.14680719e-01 -6.87395215e-01
7.48108149e-01 2.28914842e-01 -1.49800286e-01 -1.83405966e-01
1.42310262e-01 -1.74650475e-01 -5.69808543e-01 -5.74208796e-01
2.99624473e-01 -6.21021986e-01 -1.14499903e+00 1.66694689e+00
-2.97378600e-01 6.65402487e-02 1.18634276e-01 5.86574435e-01
5.67134678e-01 1.00279772e+00 3.29302609e-01 -2.32140850e-02
1.50685334e+00 -1.19417512e+00 -8.24331820e-01 -3.36808830e-01
1.07588875e+00 -1.05493784e+00 1.48210466e+00 3.70680988e-01
-1.14254045e+00 -6.61456943e-01 -8.32994699e-01 -3.23386639e-01
-3.89920026e-01 4.90383059e-01 5.07409513e-01 8.97408426e-01
-1.03769457e+00 3.48121792e-01 -1.07146573e+00 2.27983762e-02
-2.70806765e-03 1.74981683e-01 -3.25262919e-02 -5.99751659e-02
-1.42410731e+00 6.11800075e-01 7.74464071e-01 1.29389754e-02
-5.25810063e-01 -7.66868591e-01 -1.05496657e+00 3.34530830e-01
1.58079132e-01 -2.28151038e-01 1.53988504e+00 -1.17079949e+00
-1.71936464e+00 6.38690710e-01 -7.13029921e-01 -2.57869154e-01
2.31156319e-01 -6.04552984e-01 -2.73190409e-01 -5.33918180e-02
5.54147772e-02 7.82406747e-01 4.25469249e-01 -9.66933846e-01
-9.84867394e-01 2.95963198e-01 -2.96900958e-01 2.80499250e-01
-6.48183048e-01 2.04080299e-01 -8.81334186e-01 -1.14990067e+00
-2.11135074e-02 -8.16927791e-01 -2.79844910e-01 -6.72559798e-01
-7.66230285e-01 -3.95220816e-01 5.23037970e-01 -7.21445024e-01
1.55609512e+00 -2.13755345e+00 -8.41502771e-02 1.05809048e-01
-8.05961192e-02 6.30882978e-01 -2.44477987e-01 5.62067568e-01
1.24075867e-01 7.15188920e-01 -2.62956977e-01 -6.71687424e-01
-2.74959970e-02 3.75903279e-01 -4.33694035e-01 3.22534633e-03
4.84559834e-01 1.27872574e+00 -1.02967596e+00 -3.16236913e-01
6.72720224e-02 1.67626902e-01 -7.86315143e-01 1.93502828e-02
-3.10050935e-01 1.58608645e-01 -3.48990500e-01 5.06110668e-01
6.67411149e-01 2.37462267e-01 3.90570939e-01 3.39882016e-01
-4.95553315e-01 8.96469474e-01 -9.36305761e-01 1.48717773e+00
-7.46716797e-01 5.51152050e-01 -2.55895436e-01 -7.92995691e-01
6.98392630e-01 5.56321800e-01 3.54574546e-02 -3.71938169e-01
-6.90538213e-02 5.44884980e-01 1.37877062e-01 8.34951270e-03
1.07836509e+00 -2.47224301e-01 -3.80740672e-01 5.77047408e-01
1.13205977e-01 -2.74560392e-01 3.13168883e-01 2.08568886e-01
5.39422810e-01 4.33515236e-02 3.29533726e-01 -2.23518685e-01
2.96517640e-01 -8.94142911e-02 8.77532959e-01 7.30835140e-01
1.33876771e-01 7.65771806e-01 5.64330876e-01 2.97211587e-01
-1.11666334e+00 -1.23152697e+00 -2.55658873e-03 1.16317892e+00
-6.05399758e-02 -7.05698192e-01 -1.03175128e+00 -4.54077244e-01
-1.97005924e-03 8.79218400e-01 -1.51887342e-01 -5.98083623e-02
-1.08362782e+00 -2.13507041e-01 1.04049218e+00 9.82341945e-01
2.57226110e-01 -1.28727448e+00 1.24182990e-02 6.15895927e-01
-1.68758929e-01 -1.22986555e+00 -1.10638046e+00 2.51709938e-01
-6.65643513e-01 -3.44659567e-01 -1.00562251e+00 -1.42660356e+00
7.28155673e-01 2.17114493e-01 6.57075167e-01 3.15463930e-01
2.26404294e-01 -1.19139761e-01 -7.62147307e-01 -4.32460219e-01
-4.46705133e-01 5.14103770e-01 1.46168172e-01 -2.59310693e-01
6.23175025e-01 -1.25575021e-01 -1.54097214e-01 -3.40710655e-02
-9.72607374e-01 1.51534483e-01 5.57716668e-01 6.93203330e-01
7.14443624e-01 -1.89693004e-01 5.92401683e-01 -1.27847040e+00
6.18953466e-01 -2.87710160e-01 -3.24498594e-01 2.60428667e-01
-2.17041984e-01 5.05924895e-02 1.28644645e+00 -6.62032783e-01
-1.24800754e+00 3.72959077e-02 -5.14908016e-01 1.38955154e-02
-1.45876274e-01 8.80696774e-01 -4.94092315e-01 3.18343163e-01
1.58069432e-01 5.35061598e-01 -4.28211451e-01 -7.24469662e-01
6.87888026e-01 8.91955554e-01 5.41182101e-01 -8.57477248e-01
6.74306631e-01 1.79134965e-01 -8.36887658e-01 -1.14654613e+00
-4.89840895e-01 -5.55708528e-01 -8.75638127e-01 3.12583625e-01
9.78524208e-01 -9.74977911e-01 -4.31617320e-01 8.29995096e-01
-1.39027202e+00 -6.88767433e-01 -2.01001629e-01 7.43641973e-01
-1.38553351e-01 7.52443910e-01 -1.29138803e+00 -5.73632777e-01
-2.65303582e-01 -1.05659521e+00 5.62916696e-01 3.94513637e-01
-4.02531296e-01 -1.00823116e+00 -2.94169724e-01 -1.02286704e-01
2.94127166e-01 -5.62159061e-01 1.09085512e+00 -5.56959271e-01
-4.78836685e-01 2.94450019e-02 -1.74349740e-01 8.36707175e-01
4.12157327e-01 1.93571016e-01 -7.55526662e-01 -6.07288107e-02
-4.15781826e-01 -2.12156072e-01 1.08742511e+00 3.09742153e-01
1.20099556e+00 -3.28480870e-01 -1.71800748e-01 8.38942170e-01
1.19807017e+00 3.43234628e-01 6.03578746e-01 9.59699303e-02
1.11352205e+00 2.28882447e-01 4.54733044e-01 4.18024629e-01
4.97359633e-01 9.80885550e-02 -1.63979322e-01 -2.35134542e-01
-2.17759505e-01 -6.59722745e-01 7.16746449e-01 1.58515871e+00
1.40738741e-01 -3.91246587e-01 -1.00456882e+00 8.27690840e-01
-1.60417569e+00 -4.32935953e-01 -1.74255759e-01 2.05054116e+00
1.42667949e+00 2.23879501e-01 -3.29739302e-01 -1.45533040e-01
8.23307395e-01 -5.48958182e-02 -2.34444097e-01 -8.39049518e-01
-2.24209607e-01 7.16218233e-01 8.47661614e-01 8.66006196e-01
-7.70262361e-01 1.97985888e+00 5.23008394e+00 1.04714191e+00
-1.23810709e+00 -2.54867040e-02 4.70713049e-01 2.59039700e-01
-8.03580225e-01 2.11101711e-01 -1.26442444e+00 5.16255438e-01
6.59783542e-01 -3.52073371e-01 3.56216311e-01 6.28841877e-01
3.24287206e-01 -5.46091273e-02 -1.05444360e+00 5.32683015e-01
-1.64409757e-01 -1.18154943e+00 4.89073217e-01 -1.98099688e-01
9.76002157e-01 -3.20053101e-02 9.19710919e-02 4.39443201e-01
4.50644135e-01 -1.02776396e+00 1.06132340e+00 7.02564046e-02
1.12030816e+00 -9.66531575e-01 5.36828578e-01 4.13421184e-01
-1.44739175e+00 3.63412499e-01 -6.44234896e-01 -1.98538572e-01
3.80837411e-01 2.85572320e-01 -7.24555552e-01 4.58861440e-01
1.83085710e-01 6.96128368e-01 -2.76475936e-01 9.53250408e-01
-8.53003085e-01 1.28336251e+00 -1.83527187e-01 -2.81188309e-01
6.30610645e-01 -3.82816851e-01 1.88327298e-01 1.92900753e+00
4.51596141e-01 1.36155203e-01 1.10582039e-01 8.01548541e-01
-3.55455786e-01 2.79134363e-01 -1.49231385e-02 -5.09045184e-01
9.32080507e-01 8.00098956e-01 -8.32459569e-01 -6.31882310e-01
-5.68230569e-01 1.31785595e+00 5.27191639e-01 6.79880202e-01
-5.30725121e-01 -1.03587830e+00 9.90347087e-01 -3.14935088e-01
5.70430577e-01 -6.33788168e-01 -6.46907687e-01 -1.38784790e+00
1.99284554e-02 -7.98242092e-01 1.21105552e-01 -2.32791886e-01
-1.00743937e+00 4.25448626e-01 -3.17006171e-01 -9.44642663e-01
-1.50548086e-01 -7.91178882e-01 -8.04202795e-01 1.40351140e+00
-1.67400181e+00 -1.17374742e+00 3.42215121e-01 1.97923571e-01
8.12681437e-01 1.40062943e-01 8.36376488e-01 2.76047885e-01
-6.51375175e-01 1.07696891e+00 3.17167640e-01 7.41145551e-01
8.83223712e-01 -1.44538212e+00 9.99382257e-01 1.22273183e+00
2.38639653e-01 1.21302867e+00 1.13951087e-01 -8.31798434e-01
-1.05435467e+00 -1.24805784e+00 1.49864459e+00 -1.92367315e-01
6.31955266e-01 -7.62278616e-01 -1.14248264e+00 1.03556788e+00
2.99621105e-01 -4.45501179e-01 8.30086648e-01 1.37822449e-01
-2.02870652e-01 1.84280992e-01 -3.98942649e-01 1.01393569e+00
7.06843078e-01 -7.27938414e-01 -6.25197887e-01 1.48203569e-02
1.17269182e+00 -4.00762111e-01 -5.71440876e-01 -9.18602049e-02
3.90143633e-01 -3.73797268e-01 4.38066810e-01 -5.80792308e-01
5.01071870e-01 -2.05482259e-01 5.31673692e-02 -1.58461440e+00
-4.41372335e-01 -7.77744710e-01 2.66355127e-01 1.53668952e+00
9.00349975e-01 -6.86755538e-01 7.15394735e-01 4.05122966e-01
-6.08950615e-01 -5.30892193e-01 -5.26027620e-01 -1.07157290e+00
7.52113402e-01 -8.17409933e-01 6.87766969e-01 1.02893662e+00
5.22297382e-01 1.04872398e-01 -3.33407998e-01 -8.05793628e-02
5.75974919e-02 -7.01245517e-02 4.07889843e-01 -3.77875149e-01
-2.91650712e-01 -6.84125066e-01 2.32454538e-01 -1.72972786e+00
3.57079625e-01 -1.20075691e+00 3.89449388e-01 -1.35546827e+00
-1.09760510e-02 -7.46786296e-01 -2.83692300e-01 6.65426493e-01
-6.94432676e-01 2.37953424e-01 4.50617582e-01 -3.46403271e-02
-1.97441936e-01 5.21321952e-01 1.14179218e+00 2.01978087e-01
-3.45230877e-01 7.24819377e-02 -7.44332969e-01 6.02652788e-01
1.07236660e+00 -4.49575096e-01 -3.45130451e-02 -1.02912390e+00
-7.59755000e-02 -2.48259112e-01 -4.20865715e-01 -6.29163861e-01
1.50453836e-01 -3.11680675e-01 1.89745247e-01 -4.46912736e-01
3.41478474e-02 -2.47645587e-01 -4.72453207e-01 6.98146045e-01
-3.73898536e-01 1.30011484e-01 2.80875534e-01 -2.61214245e-02
-3.24874401e-01 -6.54355466e-01 6.74533665e-01 -2.55194426e-01
-8.32238972e-01 2.54895657e-01 -1.07586741e+00 2.71536618e-01
6.81628883e-01 -2.64987946e-01 2.57663266e-03 -2.21696451e-01
-2.06750676e-01 3.67909312e-01 4.82716322e-01 4.22739953e-01
4.81733948e-01 -1.20113075e+00 -7.88999021e-01 3.52932721e-01
-1.03846818e-01 5.16306050e-02 -5.70506714e-02 3.89780939e-01
-7.91408718e-01 7.69401729e-01 -5.43725453e-02 -8.08892325e-02
-1.07506120e+00 2.92939842e-01 3.69705074e-02 -3.74547094e-02
-3.54381591e-01 1.17264175e+00 3.53438318e-01 -5.16816258e-01
2.54970163e-01 -9.27366257e-01 1.09504417e-01 -2.75737140e-02
5.23291051e-01 7.05622882e-02 -6.79033846e-02 -4.46279794e-01
-2.76502162e-01 4.18641329e-01 -4.34132725e-01 -3.10205966e-01
8.80800843e-01 -9.95060056e-02 -3.28617603e-01 4.12347347e-01
1.14487970e+00 6.02377534e-01 -9.99082863e-01 -5.14450908e-01
2.51891166e-01 -1.43746018e-01 -4.00869519e-01 -3.70577872e-01
-7.43499935e-01 1.06804383e+00 -5.14071524e-01 -1.10110357e-01
7.86842227e-01 -1.56642109e-01 1.31859887e+00 4.61658269e-01
-4.54330221e-02 -1.53102887e+00 -1.75007463e-01 1.31812537e+00
2.98031598e-01 -8.00388515e-01 -4.79744971e-01 -6.62313461e-01
-9.49476004e-01 1.20114088e+00 7.24395275e-01 -2.06389993e-01
6.03673041e-01 4.58594978e-01 4.15294081e-01 5.98571897e-01
-4.93800640e-01 -3.14599037e-01 1.03832096e-01 4.35734957e-01
1.07176125e+00 5.20515442e-01 -7.33622193e-01 1.00218689e+00
-5.22637546e-01 -3.59880656e-01 6.74490094e-01 8.11365426e-01
-5.74297428e-01 -1.59655976e+00 -1.31751776e-01 3.70313615e-01
-7.37211585e-01 -8.55211914e-01 -3.46271694e-01 5.73387802e-01
1.73429683e-01 8.10356677e-01 2.63081521e-01 -2.34164193e-01
1.12620048e-01 1.14204995e-01 1.47387207e-01 -1.32416236e+00
-7.18288898e-01 3.15792650e-01 -3.86910187e-03 -9.54572707e-02
3.73860180e-01 -6.70667291e-01 -1.80964625e+00 -2.48775378e-01
-3.77865762e-01 4.36786205e-01 3.41475487e-01 1.02025962e+00
-1.99522208e-02 4.36133921e-01 4.74169165e-01 -7.05227375e-01
-4.48944092e-01 -1.02181625e+00 -6.80139363e-01 1.05306834e-01
1.63691044e-01 2.21969396e-01 4.79329489e-02 2.91010529e-01] | [10.204487800598145, 10.178444862365723] |
927eac8f-85be-4dcd-baef-e0cb14a87ff1 | a-benchmark-for-gait-recognition-under | 2107.08990 | null | https://arxiv.org/abs/2107.08990v1 | https://arxiv.org/pdf/2107.08990v1.pdf | A Benchmark for Gait Recognition under Occlusion Collected by Multi-Kinect SDAS | Human gait is one of important biometric characteristics for human identification at a distance. In practice, occlusion usually occurs and seriously affects accuracy of gait recognition. However, there is no available database to support in-depth research of this problem, and state-of-arts gait recognition methods have not paid enough attention to it, thus this paper focuses on gait recognition under occlusion. We collect a new gait recognition database called OG RGB+D database, which breaks through the limitation of other gait databases and includes multimodal gait data of various occlusions (self-occlusion, active occlusion, and passive occlusion) by our multiple synchronous Azure Kinect DK sensors data acquisition system (multi-Kinect SDAS) that can be also applied in security situations. Because Azure Kinect DK can simultaneously collect multimodal data to support different types of gait recognition algorithms, especially enables us to effectively obtain camera-centric multi-person 3D poses, and multi-view is better to deal with occlusion than single-view. In particular, the OG RGB+D database provides accurate silhouettes and the optimized human 3D joints data (OJ) by fusing data collected by multi-Kinects which are more accurate in human pose representation under occlusion. We also use the OJ data to train an advanced 3D multi-person pose estimation model to improve its accuracy of pose estimation under occlusion for universality. Besides, as human pose is less sensitive to occlusion than human appearance, we propose a novel gait recognition method SkeletonGait based on human dual skeleton model using a framework of siamese spatio-temporal graph convolutional networks (siamese ST-GCN). The evaluation results demonstrate that SkeletonGait has competitive performance compared with state-of-art gait recognition methods on OG RGB+D database and popular CAISA-B database. | ['Xinbo Zhao', 'Na Li'] | 2021-07-19 | null | null | null | null | ['3d-multi-person-pose-estimation'] | ['computer-vision'] | [-4.78566408e-01 -8.62485707e-01 -2.49582559e-01 -4.08449024e-03
-4.36690837e-01 -1.48117140e-01 -7.23493006e-03 -4.66038227e-01
-6.17928386e-01 4.14645761e-01 1.31446049e-01 4.23190922e-01
1.70195714e-01 -7.40707517e-01 -1.41459689e-01 -9.20029402e-01
-2.85749882e-02 7.06988931e-01 1.46565959e-01 -3.58851939e-01
-2.98740357e-01 6.56524062e-01 -1.60670221e+00 -2.99419731e-01
5.11517942e-01 8.79569948e-01 -2.06222132e-01 6.09628916e-01
3.73236001e-01 -1.00148365e-01 -6.46541119e-01 -6.88728631e-01
3.49693358e-01 -1.45861089e-01 -2.26935357e-01 2.06056863e-01
5.35184443e-01 -6.24293923e-01 -7.63920188e-01 7.39124477e-01
1.06644106e+00 9.77721512e-02 5.42710125e-01 -1.57280242e+00
-4.20620948e-01 -4.04319316e-01 -9.11433637e-01 2.42714569e-01
9.25389290e-01 5.75897038e-01 5.50193906e-01 -7.21408308e-01
4.24363464e-01 1.33747935e+00 8.57891738e-01 6.85378134e-01
-5.52477241e-01 -5.25726736e-01 -2.54847586e-01 4.27497417e-01
-1.62536752e+00 -1.63168132e-01 9.04646456e-01 -4.70268093e-02
1.07007790e+00 2.82893568e-01 1.19676363e+00 1.49873281e+00
2.28038758e-01 8.31173420e-01 7.80694604e-01 -8.50164890e-02
-1.24979235e-01 -7.85223067e-01 3.23737077e-02 9.96192217e-01
8.07305396e-01 1.32705957e-01 -7.84183383e-01 -1.16906939e-02
1.08707809e+00 4.22352612e-01 -2.85960168e-01 -5.05475044e-01
-1.20711327e+00 3.32507879e-01 3.46836537e-01 1.40608042e-01
-3.50074589e-01 2.41224781e-01 5.63506722e-01 6.48690388e-02
4.55109999e-02 -5.29163003e-01 -1.28089160e-01 -6.05737746e-01
-6.13887668e-01 3.26102704e-01 5.07591128e-01 7.66762435e-01
4.47293133e-01 2.48300165e-01 2.65329540e-01 8.65448177e-01
6.68912113e-01 1.28297424e+00 8.27936649e-01 -4.37007427e-01
9.09909129e-01 7.57131577e-01 -8.68298560e-02 -1.32124555e+00
-6.46362722e-01 -4.20735441e-02 -1.08103561e+00 -1.71354160e-01
6.48060739e-01 1.47743434e-01 -8.65350902e-01 1.26608348e+00
4.48709100e-01 1.47575527e-01 -2.32076526e-01 1.34877849e+00
1.02727044e+00 1.40196607e-01 2.74471776e-03 -1.09188937e-01
1.74902511e+00 -6.25318289e-01 -8.14863086e-01 -2.36150369e-01
5.89476645e-01 -5.23879766e-01 1.03332233e+00 3.96132797e-01
-5.39858639e-01 -7.17924953e-01 -1.20524991e+00 1.22802146e-02
-4.55393374e-01 3.71147603e-01 6.95398390e-01 1.34841692e+00
-6.54842317e-01 3.08081895e-01 -1.35037780e+00 -7.27718472e-01
2.41444290e-01 5.58993220e-01 -9.93894875e-01 -3.42977613e-01
-1.21851408e+00 9.09751773e-01 2.40174636e-01 5.73407590e-01
-3.96734864e-01 1.54604763e-01 -1.21365499e+00 -4.37322736e-01
2.68634945e-01 -9.63718176e-01 5.60132444e-01 -6.64494634e-02
-1.47557318e+00 1.05545354e+00 -1.08987413e-01 4.03525308e-02
5.81241131e-01 -4.01136547e-01 -7.09452927e-01 3.95204991e-01
1.30922690e-01 1.14336252e-01 8.02962303e-01 -7.00273573e-01
-2.66502742e-02 -1.22988081e+00 -4.30226535e-01 4.96226341e-01
-6.11360967e-01 -1.07646756e-01 -9.77393270e-01 -5.64239264e-01
4.05430883e-01 -9.89119112e-01 7.75726214e-02 2.46200692e-02
-3.04103702e-01 -2.17030391e-01 1.01986170e+00 -9.70053732e-01
1.12138200e+00 -1.81958497e+00 1.73677146e-01 1.91652566e-01
1.55162722e-01 3.83880913e-01 9.42165405e-02 2.50537902e-01
5.58669642e-02 -2.81752259e-01 7.94730335e-02 -6.53712094e-01
1.43689513e-01 6.61641240e-01 4.49453950e-01 9.21030223e-01
-3.04451168e-01 1.05419934e+00 -5.62749684e-01 -8.96373749e-01
5.09161294e-01 5.66636086e-01 -2.59207934e-01 1.20148569e-01
6.45890594e-01 3.77158374e-01 -6.15637779e-01 1.45230496e+00
7.74000049e-01 3.83357964e-02 -1.49340391e-01 -5.72481275e-01
4.11085367e-01 -5.20619571e-01 -1.58738792e+00 1.98019063e+00
4.62000482e-02 -4.12082821e-02 -1.72006488e-01 -9.71940875e-01
9.48405385e-01 3.81660312e-01 8.51558924e-01 -5.67727625e-01
3.25588435e-01 2.86919385e-01 -4.19670135e-01 -9.40504074e-01
3.16731781e-01 4.02158350e-02 -1.42242536e-01 1.53767839e-01
1.08396724e-01 2.75000095e-01 1.56471193e-01 -2.86758780e-01
9.30524111e-01 4.66585845e-01 3.17852646e-01 4.21852291e-01
5.94920635e-01 -2.84135133e-01 7.83355296e-01 3.58859241e-01
-8.55752528e-01 8.81158471e-01 -6.10058047e-02 -6.92926347e-01
-9.09829021e-01 -1.30179894e+00 1.27423257e-01 4.45937902e-01
3.62561315e-01 -4.78914291e-01 -5.33413768e-01 -4.87474591e-01
2.50113219e-01 -5.36702275e-01 -4.33062047e-01 -1.96923703e-01
-9.22486842e-01 -1.07767856e+00 1.12639725e+00 8.50426316e-01
1.29161799e+00 -7.02696323e-01 -6.36008501e-01 6.01884816e-03
-6.41388535e-01 -1.29463077e+00 -6.90791905e-01 -5.49523890e-01
-9.39767778e-01 -1.45510960e+00 -1.17333984e+00 -4.83380288e-01
4.11157638e-01 2.23493561e-01 6.10090137e-01 3.68059613e-02
-5.04911363e-01 8.57408166e-01 -3.26943725e-01 1.99897707e-01
3.53628904e-01 -1.78831797e-02 7.70671010e-01 1.08280294e-01
7.45933235e-01 -5.94851077e-01 -7.70858467e-01 6.35239065e-01
-6.14598036e-01 -3.03458422e-01 3.96852523e-01 7.65928984e-01
3.24494570e-01 -9.46659744e-02 4.84262072e-02 2.02133387e-01
3.97388250e-01 1.68806911e-02 -1.28312828e-02 3.12581837e-01
-1.85637966e-01 -4.23820436e-01 2.98843533e-01 -4.29420829e-01
-7.13170528e-01 1.54516637e-01 -3.08950096e-01 -8.05373430e-01
-2.72752970e-01 3.30984265e-01 -6.27707422e-01 -3.74552816e-01
4.63926762e-01 4.56976742e-01 3.43865454e-01 -5.17198682e-01
8.80352687e-03 7.10246563e-01 8.34052026e-01 -8.45379412e-01
9.07560349e-01 5.39462447e-01 3.47911745e-01 -1.00041783e+00
7.45426938e-02 -7.57581174e-01 -1.00624549e+00 -6.12600744e-01
9.31449413e-01 -1.00085044e+00 -1.32490540e+00 1.25668240e+00
-9.23630834e-01 3.36006731e-01 1.99159414e-01 7.71513462e-01
-6.35117292e-01 1.14785480e+00 -8.46625447e-01 -8.83418322e-01
-4.16496038e-01 -1.18425047e+00 1.43151939e+00 3.37699652e-01
5.00459969e-02 -7.36740828e-01 -1.29244728e-02 8.41199636e-01
-5.61211035e-02 7.23560750e-01 9.73446667e-02 -1.48624748e-01
-2.64079422e-01 -7.33234048e-01 1.36165679e-01 -4.11509126e-02
3.00756961e-01 -1.49758875e-01 -7.22077310e-01 -4.80548918e-01
-1.69888422e-01 -2.85433471e-01 6.23007476e-01 3.19620341e-01
5.24528146e-01 5.46842478e-02 -3.95807981e-01 8.18672597e-01
1.21646929e+00 1.77620221e-02 9.11550879e-01 6.01818919e-01
1.24105036e+00 3.63345802e-01 6.67399585e-01 4.77385253e-01
7.36535490e-01 1.17502964e+00 3.22003603e-01 -2.07952037e-03
-6.27362728e-02 -2.02222556e-01 4.99807268e-01 1.07783818e+00
-9.14184391e-01 6.93527311e-02 -1.04162943e+00 2.45131701e-01
-1.96458709e+00 -9.43793118e-01 -2.63694286e-01 2.27683711e+00
3.61260623e-01 -1.81215242e-01 7.05437124e-01 5.23498356e-01
8.27606976e-01 9.44946930e-02 -5.37592828e-01 3.89023125e-01
-3.52299184e-01 2.22455457e-01 5.18802404e-01 -7.33411387e-02
-1.27633572e+00 6.30014777e-01 5.00175333e+00 8.13612521e-01
-8.57654989e-01 1.41275395e-02 6.75571635e-02 -8.67299885e-02
4.92287338e-01 -4.49400514e-01 -8.46056461e-01 5.18687308e-01
5.77245235e-01 1.64769560e-01 -2.98813656e-02 8.02884698e-01
1.70903116e-01 -1.68822318e-01 -7.68121600e-01 1.80904937e+00
2.81369597e-01 -6.93650782e-01 2.51468811e-02 3.38247269e-01
1.46678751e-02 -4.04112816e-01 -7.50061274e-02 1.88950002e-01
-2.85534829e-01 -8.94550502e-01 1.74099445e-01 4.23053801e-01
8.47105086e-01 -7.31316328e-01 9.56052601e-01 2.26962864e-01
-1.89663088e+00 1.61709100e-01 -3.26204747e-01 -2.40811706e-02
2.18995228e-01 2.44679570e-01 -2.85784423e-01 1.10267007e+00
9.17245686e-01 9.89267766e-01 -7.50984073e-01 1.13663483e+00
-1.08696736e-01 1.32611945e-01 -5.88759184e-01 -3.71386632e-02
-3.20136994e-01 -2.65938789e-01 4.39928114e-01 8.85507822e-01
5.38877130e-01 1.54182419e-01 4.62188095e-01 2.62817413e-01
2.74535269e-01 3.65397185e-02 -6.81236625e-01 1.12331927e-01
2.02261850e-01 9.98429477e-01 -7.31881261e-01 -1.72793999e-01
-4.58541125e-01 1.33014262e+00 -8.41988102e-02 4.10632253e-01
-8.65124166e-01 -1.46605104e-01 8.21202517e-01 -5.00891432e-02
-4.43693958e-02 -8.17776561e-01 -1.52028278e-01 -1.88879895e+00
3.73407990e-01 -8.98798525e-01 8.03275406e-01 -7.66485333e-01
-1.28759718e+00 4.03200351e-02 4.80730459e-02 -1.62029433e+00
-1.16963752e-01 -9.26891744e-01 -3.43792766e-01 7.98646331e-01
-9.07034457e-01 -1.66989958e+00 -6.55234158e-01 1.14077461e+00
1.54143602e-01 -2.24031001e-01 9.04513419e-01 6.93039596e-01
-9.42344368e-01 8.52381110e-01 -4.01799649e-01 7.24470556e-01
8.02756786e-01 -9.15015161e-01 4.81442302e-01 9.55070913e-01
-4.68663052e-02 8.13763857e-01 4.78193253e-01 -1.02654815e+00
-2.17804098e+00 -5.54522634e-01 5.17227769e-01 -6.34394825e-01
2.59684265e-01 -9.23511013e-02 -4.98664081e-01 5.29832006e-01
-5.09148240e-01 2.52127081e-01 7.68190801e-01 -1.21212102e-01
-2.42345735e-01 -2.53699511e-01 -1.28508639e+00 5.50856471e-01
1.42520690e+00 -3.76947105e-01 -6.25623643e-01 3.30982357e-02
1.33394480e-01 -7.69964933e-01 -1.16986942e+00 5.13777375e-01
9.34458792e-01 -7.69124508e-01 1.42986739e+00 -2.99685985e-01
-1.54816568e-01 -5.54539859e-01 -2.68911958e-01 -8.39457333e-01
7.44536445e-02 -2.21674964e-01 -5.16063631e-01 9.82920289e-01
-7.18232870e-01 -7.57054389e-01 1.39126742e+00 5.24891496e-01
1.12091981e-01 -4.48894024e-01 -1.41234243e+00 -1.10901475e+00
-4.40586925e-01 -3.72350574e-01 6.37754202e-01 7.86666512e-01
1.02521013e-02 -1.35172114e-01 -7.44008660e-01 3.41083944e-01
1.17002356e+00 -1.14927858e-01 1.23595595e+00 -1.15352845e+00
-6.21306859e-02 -2.18336284e-01 -1.27744865e+00 -1.01767457e+00
-1.88526973e-01 -4.49112684e-01 -4.80007976e-01 -1.33532536e+00
-9.30441450e-03 1.03812315e-01 1.16668269e-03 6.10244632e-01
-2.05956280e-01 6.64709330e-01 1.45752147e-01 5.02829373e-01
-4.54240978e-01 8.80674243e-01 1.41894197e+00 -1.73456535e-01
-1.18626701e-03 -3.05529144e-02 5.05561419e-02 5.18801987e-01
4.44586426e-01 3.58518250e-02 -6.30875975e-02 -8.23878869e-02
-2.19170094e-01 3.53211999e-01 6.63288057e-01 -1.40870047e+00
4.05040413e-01 2.95282658e-02 8.91664207e-01 -8.24764490e-01
7.95794427e-01 -7.94532657e-01 3.54986101e-01 8.32882404e-01
7.54382491e-01 3.95153970e-01 5.42707406e-02 5.24578750e-01
-2.74474919e-01 3.48751277e-01 3.72987181e-01 -3.15765232e-01
-9.93055105e-01 9.12485719e-01 -2.26801544e-01 -1.01000771e-01
7.66508281e-01 -1.15165997e+00 -2.71343052e-01 -2.44071275e-01
-8.74936461e-01 1.14837334e-01 5.04064798e-01 5.34784675e-01
9.91418719e-01 -1.93334258e+00 -4.40992624e-01 4.34252083e-01
3.55758131e-01 -2.31360778e-01 4.81676280e-01 1.01030135e+00
-7.88167536e-01 3.29667598e-01 -6.40956402e-01 -8.95286262e-01
-1.56151915e+00 6.90921098e-02 5.26853323e-01 -2.79584885e-01
-6.65673614e-01 3.79015863e-01 -4.13976669e-01 -5.36722660e-01
1.63557753e-01 4.44686748e-02 -2.24476814e-01 3.71390879e-02
2.90578038e-01 5.98417640e-01 1.70436382e-01 -1.10542893e+00
-7.07723022e-01 1.15602565e+00 3.73680472e-01 -3.52193266e-02
1.10069418e+00 -2.45198876e-01 9.13836956e-02 2.69580781e-01
1.08616102e+00 -4.74146396e-01 -9.76457179e-01 -1.56025495e-02
-3.68364066e-01 -7.93560028e-01 -5.02301693e-01 -2.58508772e-01
-1.17351234e+00 9.56923723e-01 1.01000535e+00 -2.76644737e-01
1.07706904e+00 -5.61100364e-01 1.18600619e+00 4.28255945e-01
9.27406132e-01 -1.21174955e+00 5.07781208e-01 2.89311498e-01
5.84176481e-01 -1.25003481e+00 1.56672940e-01 -4.74788934e-01
-4.19740349e-01 1.36980069e+00 9.07814682e-01 -4.73680161e-02
3.57444882e-01 -6.08041622e-02 2.77508982e-02 -2.52936155e-01
1.98943421e-01 -3.63915652e-01 3.58950734e-01 1.09457815e+00
2.06919417e-01 1.48724481e-01 -2.55733848e-01 5.57705820e-01
-2.33934432e-01 4.37998474e-02 1.10446751e-01 1.03243327e+00
-2.08567038e-01 -1.18988109e+00 -9.67103243e-01 1.66649461e-01
-1.67459980e-01 4.48070794e-01 -6.76085874e-02 1.12436616e+00
1.11124568e-01 7.80197084e-01 -4.01862502e-01 -6.64013147e-01
5.57070613e-01 1.13140501e-01 8.54380131e-01 -9.21406075e-02
-3.22356045e-01 5.99127561e-02 3.13045308e-02 -7.93468595e-01
-5.65321326e-01 -9.03837264e-01 -1.04188454e+00 -7.32057154e-01
-6.63931668e-02 -2.14751616e-01 4.93819147e-01 9.78198826e-01
-6.19098544e-02 1.40823945e-01 2.06696689e-01 -1.18956530e+00
-3.41295898e-01 -7.54150391e-01 -9.17182803e-01 6.47275269e-01
1.45261632e-02 -1.14525950e+00 -5.49544767e-02 4.95921709e-02] | [14.243080139160156, 1.4397118091583252] |
e7cdbf2c-24ae-40df-a0a7-ea9ecb851a07 | one-line-of-code-data-mollification-improves | 2305.18900 | null | https://arxiv.org/abs/2305.18900v1 | https://arxiv.org/pdf/2305.18900v1.pdf | One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models | Generative Models (GMs) have attracted considerable attention due to their tremendous success in various domains, such as computer vision where they are capable to generate impressive realistic-looking images. Likelihood-based GMs are attractive due to the possibility to generate new data by a single model evaluation. However, they typically achieve lower sample quality compared to state-of-the-art score-based diffusion models (DMs). This paper provides a significant step in the direction of addressing this limitation. The idea is to borrow one of the strengths of score-based DMs, which is the ability to perform accurate density estimation in low-density regions and to address manifold overfitting by means of data mollification. We connect data mollification through the addition of Gaussian noise to Gaussian homotopy, which is a well-known technique to improve optimization. Data mollification can be implemented by adding one line of code in the optimization loop, and we demonstrate that this provides a boost in generation quality of likelihood-based GMs, without computational overheads. We report results on image data sets with popular likelihood-based GMs, including variants of variational autoencoders and normalizing flows, showing large improvements in FID score. | ['Maurizio Filippone', 'Pietro Michiardi', 'Giulio Franzese', 'Ba-Hien Tran'] | 2023-05-30 | null | null | null | null | ['density-estimation'] | ['methodology'] | [-8.82598087e-02 1.18508033e-01 3.45262885e-02 -5.66799752e-02
-9.11203861e-01 -2.22262174e-01 9.17317927e-01 -1.44995838e-01
-2.75039583e-01 7.46612787e-01 2.22465113e-01 -1.51605889e-01
-8.94705206e-02 -9.62179959e-01 -6.61605716e-01 -8.70353341e-01
-4.52582575e-02 6.60672247e-01 2.07090229e-01 -1.28091633e-01
2.07777128e-01 5.85319579e-01 -1.44667625e+00 -2.53938943e-01
1.31035066e+00 6.91170692e-01 2.13584870e-01 7.64431298e-01
-1.51966557e-01 5.71539700e-01 -6.39239907e-01 -5.35163939e-01
8.56973529e-02 -6.83197379e-01 -4.26212430e-01 2.04283565e-01
4.40972328e-01 -3.99460852e-01 -1.95200935e-01 9.11963761e-01
5.20174265e-01 2.46966034e-01 1.04966795e+00 -1.24282670e+00
-6.46853924e-01 2.84512192e-01 -5.41980565e-01 2.51949541e-02
-9.22320262e-02 1.56263888e-01 7.91743338e-01 -1.00514364e+00
8.06726158e-01 1.32685232e+00 5.34076631e-01 6.50475204e-01
-1.60854638e+00 -4.72972631e-01 -2.25706488e-01 7.86513463e-02
-1.40865433e+00 -3.97367537e-01 7.61384249e-01 -5.23074269e-01
9.17032838e-01 -2.70548575e-02 6.85211301e-01 9.10508931e-01
1.16259731e-01 9.32208061e-01 1.03086758e+00 -4.53614861e-01
6.04639471e-01 2.88059473e-01 -3.46702605e-01 6.97245717e-01
3.29456739e-02 1.78259760e-01 -4.59527284e-01 -1.60771608e-01
1.08666241e+00 -2.23493412e-01 -2.10069284e-01 -6.19616389e-01
-1.08487689e+00 1.27674639e+00 6.30205512e-01 1.61885843e-01
-5.09671330e-01 3.02094817e-01 8.56503099e-02 -5.50987609e-02
7.56061137e-01 3.58438432e-01 1.58520520e-01 -3.48016381e-01
-1.37341511e+00 5.25236666e-01 7.76999116e-01 7.68500865e-01
7.38157332e-01 5.98275602e-01 -1.23519108e-01 8.20367157e-01
4.60912704e-01 5.86836457e-01 5.99674225e-01 -1.27764869e+00
1.58048168e-01 4.12792414e-01 -1.18637283e-03 -7.61540592e-01
-7.36856908e-02 -5.86703360e-01 -9.94046092e-01 6.60706937e-01
2.45725155e-01 -2.03961894e-01 -1.11135674e+00 1.82483435e+00
4.00162399e-01 3.30309927e-01 9.79447514e-02 7.27136254e-01
4.73147690e-01 8.97419214e-01 -1.06539741e-01 -1.11471631e-01
9.15336013e-01 -9.48887825e-01 -4.92014259e-01 8.24051350e-02
5.10151505e-01 -6.63670480e-01 9.75150883e-01 4.85784054e-01
-1.31573737e+00 -4.89209175e-01 -9.89347994e-01 6.03645593e-02
-1.31149277e-01 -1.40208468e-01 6.06205940e-01 8.81081879e-01
-1.35567999e+00 7.76079237e-01 -1.06818318e+00 -2.45749727e-01
5.81184089e-01 2.09788963e-01 -1.42033145e-01 6.04738966e-02
-7.76794016e-01 8.51351142e-01 2.39498794e-01 -3.52170676e-01
-9.39501405e-01 -8.63169193e-01 -9.48455453e-01 1.72748774e-01
2.01545462e-01 -8.60997975e-01 1.08970916e+00 -7.79042602e-01
-1.73561347e+00 3.46152037e-01 -2.38970369e-01 -6.79128051e-01
6.21910989e-01 1.82309784e-02 -5.47970086e-02 2.57688969e-01
-9.80310664e-02 1.06068218e+00 1.10894394e+00 -1.17788374e+00
-1.99083254e-01 6.63975105e-02 -2.48449728e-01 1.11142933e-01
-5.22115529e-01 -2.61143088e-01 -2.52290696e-01 -8.54853213e-01
-1.76614657e-01 -8.88293862e-01 -3.82218599e-01 7.77430311e-02
-2.18977049e-01 -4.92587835e-02 8.43056858e-01 -6.47589862e-01
1.15350068e+00 -1.97076797e+00 4.86573845e-01 1.45854473e-01
2.38484800e-01 5.60882807e-01 -1.59145102e-01 3.80724490e-01
2.03785419e-01 2.25876406e-01 -5.36139131e-01 -8.17878127e-01
4.16686572e-02 2.81354606e-01 -2.39969671e-01 1.83144540e-01
5.30174732e-01 1.03932583e+00 -7.58012176e-01 -4.54368383e-01
5.11847258e-01 8.70304108e-01 -8.81713390e-01 -6.31621297e-05
-3.80124271e-01 4.31708872e-01 4.44645323e-02 8.97129104e-02
6.22383356e-01 -2.99271524e-01 -1.56597719e-01 -4.78669293e-02
-7.35014528e-02 1.25487119e-01 -1.44105744e+00 1.52611721e+00
-5.40505111e-01 6.28662884e-01 4.15875763e-02 -8.83903146e-01
8.21716964e-01 1.39304355e-01 4.04253334e-01 -1.77383319e-01
-2.03803889e-02 2.50979662e-01 -8.14858079e-02 -1.21806264e-02
6.00934744e-01 -4.18863446e-01 3.35264087e-01 4.34994906e-01
2.67068982e-01 -6.12958670e-01 5.85164607e-01 4.84248668e-01
7.05895126e-01 1.31646186e-01 9.06692147e-02 -2.80629277e-01
4.34932470e-01 -4.04761694e-02 3.36974889e-01 5.76241493e-01
2.35867172e-01 9.29118156e-01 2.75294065e-01 -2.91905012e-02
-1.22690165e+00 -1.26828015e+00 -1.15910359e-02 4.11593467e-01
-1.94962338e-01 -4.71969455e-01 -1.03468883e+00 -3.71879429e-01
-1.75733700e-01 7.63359129e-01 -5.01954019e-01 -1.75183192e-02
-5.61101079e-01 -1.05731928e+00 3.47886711e-01 6.99094415e-01
6.87899530e-01 -7.70633280e-01 -4.41482157e-01 3.50300878e-01
-5.64488135e-02 -6.88816071e-01 -4.60937113e-01 -1.43005133e-01
-1.13166237e+00 -7.41586149e-01 -1.32056403e+00 -5.22148252e-01
7.07402647e-01 1.52873024e-01 9.84967113e-01 -1.44115910e-01
-3.31895292e-01 3.63173842e-01 -6.53116331e-02 -3.16196233e-01
-8.87710631e-01 2.09636584e-01 2.07658410e-02 2.70593278e-02
-3.77068818e-02 -6.35232568e-01 -6.25250340e-01 2.65767723e-01
-1.20019686e+00 1.15637027e-01 6.07396841e-01 9.89597321e-01
6.70474052e-01 7.82383010e-02 5.13033330e-01 -5.86935401e-01
7.56829977e-01 -4.13147867e-01 -7.42855251e-01 -1.25025913e-01
-8.30517530e-01 2.66791314e-01 6.48843467e-01 -4.37581241e-01
-1.23549724e+00 -1.71930239e-01 -3.94885927e-01 -5.41893601e-01
-2.75977012e-02 4.93114799e-01 2.16063917e-01 -1.80441707e-01
6.61893845e-01 2.36847430e-01 3.79041225e-01 -5.30527532e-01
5.91406226e-01 3.95906419e-01 3.72419894e-01 -4.50823992e-01
8.93430233e-01 6.30462408e-01 2.31132552e-01 -9.48791265e-01
-3.76984537e-01 -3.16641212e-01 -3.66960466e-01 -2.20775411e-01
8.80541801e-01 -7.35974014e-01 -2.96107769e-01 6.12356246e-01
-9.11254525e-01 -4.28166181e-01 -5.41695774e-01 5.00168681e-01
-7.34847307e-01 3.06306660e-01 -7.08870173e-01 -8.20144057e-01
-2.86795229e-01 -1.24834347e+00 9.71219122e-01 4.31406349e-01
-1.17506608e-01 -1.33386052e+00 1.57617465e-01 5.48957139e-02
8.22677195e-01 1.87053010e-01 8.43876362e-01 -2.11784586e-01
-6.82960629e-01 -4.96792281e-03 -3.70390862e-02 6.56240642e-01
-5.18787839e-02 1.23447828e-01 -8.08382094e-01 -4.33427393e-01
2.93335784e-02 -2.12152436e-01 9.28570330e-01 7.28282452e-01
6.47609293e-01 -1.93860918e-01 -2.32695967e-01 6.27663136e-01
1.54251957e+00 -2.80971304e-02 6.60063028e-01 -4.12769690e-02
5.00462353e-01 3.42365146e-01 1.73730478e-01 3.42012018e-01
1.28146514e-01 8.70712578e-01 3.68697882e-01 -2.89366245e-01
-5.60566366e-01 -2.88617462e-01 3.97784770e-01 9.56503510e-01
-1.45533949e-01 -1.57938033e-01 -6.66657507e-01 5.50642610e-01
-1.76483989e+00 -9.95107114e-01 -3.38817477e-01 2.20401335e+00
6.96422100e-01 -7.65574127e-02 4.17306095e-01 1.77608281e-01
5.34823835e-01 7.42566213e-02 -5.07932067e-01 -2.32308567e-01
-1.52315795e-01 2.54869670e-01 2.71690011e-01 8.67826998e-01
-8.31711829e-01 7.59698391e-01 6.70525789e+00 1.12323618e+00
-1.01845300e+00 2.59386420e-01 6.65443659e-01 -2.83850193e-01
-4.02464688e-01 -1.63611114e-01 -7.91607976e-01 4.77928191e-01
9.53503191e-01 -2.46923283e-01 4.12673563e-01 9.47446823e-01
2.37993792e-01 -2.71925926e-01 -7.62530506e-01 9.22746599e-01
2.65714705e-01 -1.65398169e+00 1.57085419e-01 3.04684341e-01
9.70832646e-01 5.02746776e-02 3.03692967e-01 1.89663634e-01
4.27752495e-01 -9.63521004e-01 6.46035194e-01 4.58059609e-01
5.08294225e-01 -8.58602166e-01 5.64046800e-01 4.12336707e-01
-9.01189864e-01 2.88295954e-01 -5.24785519e-01 1.29311830e-01
5.89568973e-01 8.77520025e-01 -8.66228998e-01 3.67297232e-01
4.64696169e-01 5.06305695e-01 -3.81572992e-01 1.20615780e+00
-1.46901801e-01 7.31566489e-01 -5.30145288e-01 -2.72069592e-02
1.85591593e-01 -4.98798490e-01 7.46486962e-01 1.06463397e+00
6.07162058e-01 -3.77157241e-01 -1.40034288e-01 1.40343893e+00
7.01381341e-02 -2.24301387e-02 -4.59477216e-01 1.20416462e-01
2.44868428e-01 1.09998822e+00 -6.23093605e-01 -4.05155092e-01
-2.99745798e-01 1.04371452e+00 2.06370756e-01 2.50461876e-01
-8.35185170e-01 -3.27015102e-01 4.61037546e-01 2.21981511e-01
4.97475147e-01 -5.27630866e-01 -1.42896309e-01 -1.09758937e+00
-1.72624230e-01 -5.95223069e-01 7.57078454e-02 -6.03943765e-01
-1.07553923e+00 4.14126962e-01 1.40349299e-01 -1.01531541e+00
-5.47962248e-01 -4.39975500e-01 -4.82881308e-01 1.04626989e+00
-1.51250792e+00 -1.03122675e+00 -3.16958904e-01 4.05612916e-01
6.08290792e-01 -1.22748889e-01 7.91411757e-01 3.63279074e-01
-2.12669209e-01 3.88208717e-01 3.74995977e-01 -2.07351118e-01
5.36422670e-01 -1.43899500e+00 5.88283658e-01 9.37583029e-01
3.83971483e-01 6.33974254e-01 7.62606680e-01 -6.06296778e-01
-1.08408463e+00 -9.89787757e-01 6.09698057e-01 -1.92453220e-01
3.90025944e-01 -3.35618705e-01 -9.38016832e-01 3.18876177e-01
1.82700574e-01 -2.23829553e-01 4.89029378e-01 -2.16371268e-01
2.04229876e-02 1.32013261e-01 -1.12347138e+00 6.84678435e-01
7.88665354e-01 -1.45796463e-01 -2.97252685e-01 1.70412734e-01
3.67719322e-01 -2.94456363e-01 -8.75948071e-01 1.70745194e-01
2.08210319e-01 -1.26601362e+00 1.09979379e+00 -1.16591029e-01
5.02441466e-01 -2.87287682e-01 1.44149408e-01 -1.69058585e+00
-2.97062665e-01 -8.42075527e-01 -4.47090715e-01 1.32036376e+00
4.04076725e-01 -6.50110066e-01 9.94901776e-01 4.74225700e-01
-4.44292910e-02 -7.52732456e-01 -9.92021620e-01 -9.98360813e-01
4.34230059e-01 -3.10689002e-01 4.72032726e-01 3.95211607e-01
-2.25167036e-01 2.06999943e-01 -4.85086679e-01 -2.22527251e-01
7.37469435e-01 -1.74036592e-01 9.15469110e-01 -1.18956578e+00
-6.18125319e-01 -6.87603891e-01 -3.83017987e-01 -1.31189573e+00
-1.15577616e-01 -9.03481185e-01 -4.22131158e-02 -1.75366795e+00
-8.83764960e-03 -4.36355203e-01 1.81709170e-01 5.97431463e-05
-2.59588122e-01 5.54684997e-01 3.60323519e-01 3.06760818e-01
-2.07755879e-01 8.99794936e-01 1.25922716e+00 -1.62324961e-02
-2.63809144e-01 -1.63599193e-01 -4.28301036e-01 6.10123277e-01
7.76048362e-01 -3.71063352e-01 -6.42755270e-01 -2.70870537e-01
9.46413428e-02 -1.28468081e-01 4.28627819e-01 -1.29183614e+00
8.53242055e-02 -1.12417825e-02 2.78140724e-01 -4.32883739e-01
6.44806385e-01 -4.87575620e-01 1.59354448e-01 5.63235521e-01
-5.92644922e-02 7.30154989e-03 1.59132168e-01 6.40903771e-01
-3.11986506e-01 -4.30702716e-01 1.09471345e+00 -1.71763629e-01
-4.88111764e-01 1.92353100e-01 -4.89718288e-01 8.77982229e-02
1.04447007e+00 -2.08652735e-01 -1.63260594e-01 -7.11482108e-01
-5.88975251e-01 -2.73334980e-01 6.58533573e-01 1.36424571e-01
6.57172203e-01 -1.34880543e+00 -7.49102831e-01 3.95302564e-01
-3.69087756e-01 1.61100715e-01 1.00267746e-01 9.04069424e-01
-6.11700833e-01 1.93187967e-01 2.09338106e-02 -7.31918812e-01
-1.03307784e+00 3.77959073e-01 3.77458870e-01 -3.01759988e-01
-6.85072124e-01 8.46554339e-01 1.68838546e-01 -1.57680094e-01
4.78349626e-02 -8.63725841e-02 1.05726406e-01 -1.02365784e-01
6.18851185e-01 6.97789729e-01 1.67615861e-02 -5.06444037e-01
6.03146479e-03 4.70677167e-01 -5.85955381e-02 -5.37202597e-01
1.32581735e+00 -3.50150578e-02 2.56308675e-01 1.45037830e-01
1.08033371e+00 -3.93753033e-03 -1.58477032e+00 1.67877541e-03
-2.59995222e-01 -3.89575809e-01 3.67295802e-01 -6.55129015e-01
-1.15320611e+00 1.08158302e+00 4.67709243e-01 2.41018236e-01
8.68458927e-01 -1.14908218e-02 8.60289395e-01 -1.52243242e-01
2.23592415e-01 -1.05075514e+00 2.90079653e-01 2.88138956e-01
7.58076370e-01 -1.04367840e+00 -1.06605276e-01 -3.25442374e-01
-5.70821345e-01 8.64142954e-01 3.23252976e-01 -3.53587717e-01
6.17796183e-01 3.77196252e-01 -4.02354114e-02 -7.58851692e-02
-4.76753950e-01 -1.55994788e-01 2.49198794e-01 8.29142332e-01
2.71619797e-01 -1.74881265e-01 -2.21193522e-01 8.76121074e-02
-1.89403996e-01 4.50904183e-02 5.90414345e-01 7.44059682e-01
-3.95147294e-01 -1.26482463e+00 -3.27379912e-01 5.42331398e-01
-2.45538652e-01 -2.28349283e-01 -1.27204144e-02 6.81530595e-01
-2.76566088e-01 8.73566091e-01 8.54224712e-02 2.14790795e-02
-2.51759235e-02 1.44699171e-01 6.09807253e-01 -4.36023563e-01
-2.83248723e-01 2.11013958e-01 -2.34391198e-01 -3.81638169e-01
-4.70690966e-01 -7.85637200e-01 -1.10120082e+00 -5.12080491e-01
-5.03483891e-01 1.70658737e-01 8.66886199e-01 8.15476239e-01
6.07526362e-01 5.33544362e-01 2.60866076e-01 -1.20050693e+00
-6.32167578e-01 -9.21493530e-01 -5.73364139e-01 5.00853300e-01
1.62962854e-01 -7.75702775e-01 -4.74260837e-01 1.40026331e-01] | [11.236185073852539, -0.21785937249660492] |
90861bf4-4809-4866-9e43-badbb9a65d30 | mdenet-multi-modal-dual-embedding-networks | 2305.01245 | null | https://arxiv.org/abs/2305.01245v1 | https://arxiv.org/pdf/2305.01245v1.pdf | MDENet: Multi-modal Dual-embedding Networks for Malware Open-set Recognition | Malware open-set recognition (MOSR) aims at jointly classifying malware samples from known families and detect the ones from novel unknown families, respectively. Existing works mostly rely on a well-trained classifier considering the predicted probabilities of each known family with a threshold-based detection to achieve the MOSR. However, our observation reveals that the feature distributions of malware samples are extremely similar to each other even between known and unknown families. Thus the obtained classifier may produce overly high probabilities of testing unknown samples toward known families and degrade the model performance. In this paper, we propose the Multi-modal Dual-Embedding Networks, dubbed MDENet, to take advantage of comprehensive malware features (i.e., malware images and malware sentences) from different modalities to enhance the diversity of malware feature space, which is more representative and discriminative for down-stream recognition. Last, to further guarantee the open-set recognition, we dually embed the fused multi-modal representation into one primary space and an associated sub-space, i.e., discriminative and exclusive spaces, with contrastive sampling and rho-bounded enclosing sphere regularizations, which resort to classification and detection, respectively. Moreover, we also enrich our previously proposed large-scaled malware dataset MAL-100 with multi-modal characteristics and contribute an improved version dubbed MAL-100+. Experimental results on the widely used malware dataset Mailing and the proposed MAL-100+ demonstrate the effectiveness of our method. | ['Song Guo', 'Yuxia Sun', 'Yufeng Zhan', 'Wenchao Xu', 'Yuanyuan Xu', 'Jingcai Guo'] | 2023-05-02 | null | null | null | null | ['open-set-learning'] | ['miscellaneous'] | [ 2.68212259e-01 -5.99660575e-01 -1.33684248e-01 -1.06738620e-01
-6.05555654e-01 -6.64699793e-01 6.06003404e-01 3.30781303e-02
-5.83016463e-02 5.64884841e-01 -2.28737578e-01 -2.15805829e-01
-7.37950951e-02 -7.50765502e-01 -7.15824783e-01 -1.07084394e+00
-1.78214461e-01 1.97588712e-01 1.18133366e-01 -1.53412363e-02
4.65411544e-02 5.66807449e-01 -1.57592559e+00 3.02565336e-01
9.60640192e-01 9.76448715e-01 1.18827641e-01 4.80683267e-01
-9.41383690e-02 4.95774716e-01 -5.86268663e-01 -1.95336446e-01
2.24590242e-01 -1.52800605e-01 -1.52882487e-01 1.58396497e-01
-3.48766223e-02 -3.36519361e-01 -5.57146847e-01 1.26706433e+00
-3.14076319e-02 -1.35757864e-01 1.03016949e+00 -1.48575461e+00
-7.86267161e-01 4.23892885e-01 -6.20056987e-01 2.88417429e-01
3.12409669e-01 3.47457886e-01 7.50311613e-01 -8.78329396e-01
5.70788145e-01 1.31429875e+00 5.90291083e-01 5.54960191e-01
-1.04837847e+00 -8.53649974e-01 1.03474788e-01 4.63118821e-01
-1.56904829e+00 -2.95520127e-01 9.72912610e-01 -6.51628196e-01
5.78215182e-01 4.56043839e-01 4.31669623e-01 1.49734545e+00
1.58991128e-01 4.93420213e-01 1.19740283e+00 1.91042855e-01
-4.27550562e-02 5.19265413e-01 4.27003026e-01 7.64475286e-01
4.72605765e-01 2.15138018e-01 1.45609342e-02 -4.61913794e-01
2.87935883e-01 6.70645416e-01 -6.98072195e-01 -1.97279245e-01
-1.11672997e+00 8.57727468e-01 1.74226508e-01 4.99478102e-01
-2.13110492e-01 -5.81865728e-01 7.42269754e-01 8.20923597e-02
3.49705517e-01 -1.20805129e-01 -3.03623974e-01 1.16696142e-01
-6.33939505e-01 -2.64735490e-01 5.96388817e-01 6.33325040e-01
8.35427999e-01 2.09006608e-01 2.15313248e-02 6.76714361e-01
4.68151689e-01 7.71024108e-01 6.84969187e-01 -1.66140758e-02
5.03860950e-01 7.28908658e-01 -1.98490128e-01 -1.41391647e+00
-9.15477797e-03 -4.38164979e-01 -8.74712646e-01 -1.01322241e-01
2.95083165e-01 9.34992805e-02 -5.84812641e-01 1.68124235e+00
4.02237564e-01 5.70071518e-01 3.45286548e-01 6.01990581e-01
6.91710472e-01 9.89514768e-01 -2.65577525e-01 -4.98288125e-01
1.26505101e+00 -6.05905652e-01 -5.56795537e-01 1.50573283e-01
3.10960770e-01 -4.18572098e-01 9.86195505e-01 3.40223640e-01
-1.49163932e-01 -4.09759134e-01 -1.19327784e+00 6.13680899e-01
-5.36769748e-01 2.17686281e-01 1.66605085e-01 7.49853492e-01
-3.77585292e-01 4.77885455e-01 -7.64341772e-01 -2.37538040e-01
6.01518810e-01 1.70689940e-01 -6.20122969e-01 -2.10722104e-01
-8.88494253e-01 3.43322903e-01 6.04277551e-01 2.24746782e-02
-1.32449973e+00 -4.02351081e-01 -7.52121150e-01 5.22351563e-02
4.25676346e-01 -1.75468251e-02 2.43809789e-01 -7.60031819e-01
-1.10655367e+00 5.60293198e-01 -7.57546350e-02 -1.98486656e-01
2.65767038e-01 2.70544320e-01 -7.60273576e-01 3.24915707e-01
-1.99110821e-01 7.74731934e-02 1.38637090e+00 -1.59227347e+00
-3.93243462e-01 -7.63887644e-01 -7.01793060e-02 -3.48901063e-01
-1.20640576e+00 -2.69712862e-02 -1.15486480e-01 -6.59618080e-01
-2.90533267e-02 -7.63359427e-01 2.98135698e-01 -4.88006800e-01
-6.30725622e-01 -1.65791109e-01 1.53395975e+00 -9.57077205e-01
1.43858421e+00 -2.44403505e+00 1.67315245e-01 2.71494389e-01
4.36655909e-01 3.36606979e-01 -2.28155777e-01 1.36901215e-01
-2.37407923e-01 -2.61591636e-02 -4.96150434e-01 -1.30597100e-01
-3.84699218e-02 3.48145247e-01 -6.00060403e-01 9.01147962e-01
4.57877636e-01 3.81328911e-01 -8.33095253e-01 -5.36356270e-01
2.48896867e-01 7.14369357e-01 -3.17499906e-01 2.81946212e-01
-6.14540428e-02 5.55213273e-01 -5.17758310e-01 1.05150890e+00
9.28507447e-01 -1.06285095e-01 -7.49481320e-02 -3.25761348e-01
2.01937705e-01 -3.24992090e-01 -1.00466430e+00 7.17461288e-01
-4.29832816e-01 2.91206837e-01 3.11123490e-01 -1.08679903e+00
1.08046150e+00 1.21422537e-01 4.71018553e-01 1.01631917e-01
4.57274407e-01 3.61534506e-01 4.69009997e-03 -5.97483575e-01
1.32711798e-01 1.75550073e-01 1.81562036e-01 2.03069940e-01
8.71160477e-02 3.82665306e-01 2.72643976e-02 -1.59076117e-02
1.13649261e+00 -2.58238107e-01 1.57731339e-01 -1.51854828e-01
1.15617764e+00 -1.78114519e-01 6.94603443e-01 2.58121043e-01
-4.05195177e-01 1.56767935e-01 5.80320716e-01 -6.17341511e-02
-8.18436801e-01 -1.00946701e+00 -4.90375698e-01 7.97995329e-01
2.57438004e-01 -3.18592250e-01 -6.84366524e-01 -1.33450043e+00
6.28233403e-02 4.62911516e-01 -5.94087541e-01 -2.20172837e-01
-6.01033151e-01 -8.96155894e-01 6.30621552e-01 2.90728748e-01
1.60709187e-01 -7.11794674e-01 -2.59885162e-01 -1.38104081e-01
-1.46857491e-02 -9.78716135e-01 -5.01126230e-01 1.77088574e-01
-5.63115299e-01 -1.55274248e+00 -5.43805599e-01 -7.24342167e-01
7.26111650e-01 2.11527288e-01 4.62262183e-01 -1.78632393e-01
-1.83170199e-01 4.72814322e-01 -5.59643030e-01 7.09299296e-02
-7.42350340e-01 -3.05735469e-01 4.58899438e-01 5.93882740e-01
3.87880117e-01 -6.76058054e-01 -1.10401273e-01 3.82152855e-01
-1.14463627e+00 -4.93137002e-01 5.09809673e-01 1.05963409e+00
4.41498369e-01 3.01425546e-01 7.34658778e-01 -4.32346284e-01
4.24535275e-01 -9.69967067e-01 -5.08345902e-01 3.03182662e-01
-2.79882878e-01 -2.51021087e-01 1.42077672e+00 -8.12786996e-01
-7.87141085e-01 -1.70773938e-01 -1.07759841e-01 -1.11046195e+00
-1.51918992e-01 1.63049370e-01 -5.72340131e-01 -2.63713568e-01
4.52083796e-01 7.79360831e-01 1.41671494e-01 -2.69894928e-01
1.34711266e-01 1.06584609e+00 4.10121918e-01 -2.88244665e-01
1.20795774e+00 5.72258472e-01 -9.13318545e-02 -9.34204817e-01
-7.10050538e-02 -4.36619133e-01 -2.36770183e-01 -1.39979273e-01
6.20817602e-01 -6.04386747e-01 -7.56452382e-01 5.15409470e-01
-1.10156441e+00 4.78525877e-01 -1.10335141e-01 4.36837703e-01
-1.69504210e-01 9.22740161e-01 -6.12963736e-01 -9.51831460e-01
-3.62646908e-01 -1.53252327e+00 9.62950230e-01 5.63061871e-02
2.99398094e-01 -9.17936862e-01 -7.10570812e-02 1.34566531e-01
-3.44715193e-02 4.34174508e-01 9.11987603e-01 -1.37500572e+00
-4.57057118e-01 -4.66083497e-01 -2.68817574e-01 7.31078029e-01
3.47887486e-01 3.16080630e-01 -8.99433315e-01 -6.13044322e-01
3.26390266e-01 -3.14266294e-01 1.01955760e+00 -9.15245935e-02
1.22960293e+00 -4.52423006e-01 -5.92412531e-01 6.37178063e-01
1.50341809e+00 4.09808546e-01 1.19681358e-01 -7.37869665e-02
8.85156453e-01 5.50057650e-01 5.41362464e-01 7.37436771e-01
2.01290492e-02 2.90809453e-01 6.39067352e-01 6.34593308e-01
4.06010777e-01 -8.97022188e-02 8.42953324e-01 1.19645727e+00
2.95859009e-01 -3.22408557e-01 -7.21358597e-01 2.81736434e-01
-1.40398586e+00 -9.05359685e-01 5.89597039e-02 2.23455667e+00
4.38831300e-01 7.19043836e-02 9.23871920e-02 3.31190586e-01
1.04897869e+00 3.46761584e-01 -6.16543889e-01 -1.00343898e-02
-3.95913124e-01 -4.31445614e-02 2.88293600e-01 1.48511544e-01
-1.34278727e+00 2.80357182e-01 5.07707071e+00 1.61085570e+00
-1.19132757e+00 3.59729081e-01 5.57711542e-01 2.21759647e-01
-4.20050681e-01 -2.19005346e-01 -7.99279213e-01 8.32138479e-01
7.73182094e-01 -5.65433949e-02 6.51139677e-01 9.07013953e-01
-3.68399546e-02 3.24193329e-01 -9.27888811e-01 1.16283536e+00
4.66134071e-01 -9.66050386e-01 1.46089852e-01 1.71697408e-01
4.71494049e-01 -3.03408593e-01 2.73200452e-01 5.28969049e-01
-2.14020923e-01 -7.71908283e-01 3.76654297e-01 4.21592116e-01
8.17580938e-01 -7.71616697e-01 7.04216003e-01 5.20594358e-01
-1.54445732e+00 -6.01577818e-01 -2.44567916e-01 3.95645380e-01
-2.49217063e-01 4.11252052e-01 -5.14223695e-01 8.54929984e-01
3.72870773e-01 1.04384851e+00 -6.46471620e-01 6.15299225e-01
3.00080746e-01 6.50663078e-01 -3.58445346e-01 -8.63365978e-02
6.50658607e-02 -3.89808178e-01 1.03470719e+00 1.06623256e+00
3.67523134e-01 -2.21620619e-01 4.46138799e-01 9.06769216e-01
8.16414133e-02 1.99256644e-01 -8.28055084e-01 -4.90178734e-01
5.48230529e-01 1.34418094e+00 -6.03446543e-01 -4.70306486e-01
-3.59477162e-01 7.29609191e-01 1.52243495e-01 1.80601284e-01
-1.23436534e+00 -5.21871924e-01 7.19883800e-01 -1.98074639e-01
3.70314151e-01 -7.47737065e-02 9.55947265e-02 -1.54184353e+00
1.97682992e-01 -9.89080310e-01 4.10734624e-01 -1.76140927e-02
-1.70061922e+00 9.29684937e-01 -9.08412188e-02 -1.59341812e+00
8.40998963e-02 -9.67791736e-01 -6.98869586e-01 5.65180779e-01
-1.27534878e+00 -1.27035284e+00 -2.81264812e-01 6.77359045e-01
3.60768944e-01 -5.35764694e-01 6.49242342e-01 5.14278769e-01
-1.10750985e+00 8.13248634e-01 7.98784137e-01 1.18017554e-01
3.72601420e-01 -7.00763762e-01 -3.95614922e-01 7.95791090e-01
-1.27810895e-01 5.44246554e-01 4.50209588e-01 -7.87170947e-01
-1.72559178e+00 -1.41113472e+00 7.09045827e-02 -2.31505424e-01
8.63693953e-01 -4.58593220e-01 -1.09763038e+00 4.75359738e-01
-1.85016513e-01 2.15688616e-01 5.08473039e-01 -4.42647487e-01
-6.76417232e-01 -2.06670433e-01 -1.46077597e+00 2.84019381e-01
7.71432102e-01 -6.61802828e-01 -4.86612618e-01 4.73389238e-01
8.39086890e-01 7.24922717e-02 -8.94982517e-01 7.54066885e-01
4.27793354e-01 -9.73256469e-01 1.09317803e+00 -5.02940655e-01
2.52778590e-01 -3.31734151e-01 -5.44525743e-01 -9.69180942e-01
-8.03878680e-02 -1.60692111e-01 -5.17919600e-01 1.47777033e+00
-2.50157595e-01 -1.02734494e+00 4.09459323e-01 -3.67667228e-01
-1.75765455e-01 -1.08979082e+00 -1.11636722e+00 -1.01373875e+00
-7.74360523e-02 -4.10295814e-01 6.02389038e-01 9.67280209e-01
-5.65979518e-02 -8.69618207e-02 -3.60895872e-01 4.48559582e-01
6.86013579e-01 6.47254055e-03 4.43938226e-01 -1.03250861e+00
-3.90709698e-01 -4.05753970e-01 -6.17281437e-01 -6.23950839e-01
6.02111638e-01 -9.61096585e-01 -2.30118364e-01 -6.50970578e-01
3.76407117e-01 -4.21175778e-01 -4.50914294e-01 1.61378067e-02
-1.51799709e-01 2.93930531e-01 1.73738357e-02 4.19363141e-01
-3.74328464e-01 8.69952261e-01 9.79715407e-01 -5.13473332e-01
-4.46811169e-02 -1.10569172e-01 -2.25144938e-01 7.70389974e-01
5.66593051e-01 -1.91171244e-01 -2.71623552e-01 1.81544989e-01
-4.99392331e-01 -3.10202651e-02 5.56221664e-01 -1.10287690e+00
-2.90404379e-01 -1.16165318e-01 3.64658475e-01 -7.43373632e-01
5.11353493e-01 -9.94865894e-01 -3.61067019e-02 6.16549730e-01
1.68435439e-01 -2.46388838e-01 1.72603413e-01 1.00278425e+00
-2.18969360e-01 -2.34951034e-01 8.64346981e-01 2.60360032e-01
-4.58416015e-01 5.69308579e-01 -2.76744485e-01 -1.12674788e-01
1.46445906e+00 -3.38744700e-01 -4.06892002e-01 1.46965563e-01
-5.30958533e-01 1.72050763e-02 5.20087361e-01 3.20945114e-01
8.69209528e-01 -1.39871514e+00 -6.32683098e-01 4.22439456e-01
3.12247634e-01 -5.24970591e-01 5.34326077e-01 9.54585731e-01
-2.47070357e-01 4.35149640e-01 -1.80259377e-01 -7.79369175e-01
-1.41658640e+00 1.04771626e+00 5.56940958e-02 -3.31135333e-01
-3.17377120e-01 6.77098930e-01 2.35696718e-01 -5.85918903e-01
1.81663230e-01 -7.99918249e-02 -6.01439595e-01 6.17404357e-02
6.40631378e-01 5.55927992e-01 -2.67649025e-01 -1.18264246e+00
-6.41161442e-01 4.72420692e-01 9.68413427e-02 5.32429695e-01
1.11770594e+00 1.52023703e-01 -4.42731023e-01 4.93894786e-01
1.67248964e+00 2.53363490e-01 -9.43607628e-01 -2.15454027e-01
-4.01929945e-01 -6.80761218e-01 -4.46128458e-01 -1.83517143e-01
-8.23220074e-01 9.25926387e-01 8.35632026e-01 4.26903844e-01
1.19400263e+00 -5.47428727e-02 9.21349883e-01 2.94225276e-01
2.88338482e-01 -4.43082333e-01 1.02959871e-01 3.81954342e-01
6.34601474e-01 -1.19082201e+00 -4.15756077e-01 -5.52028656e-01
-2.67922252e-01 1.28934133e+00 7.13903010e-01 -1.75153285e-01
5.59411645e-01 1.46765709e-01 -4.65504080e-01 8.69443342e-02
-5.49368739e-01 6.30416945e-02 1.79538250e-01 8.02652955e-01
-9.73438174e-02 3.12658817e-01 -7.15283826e-02 9.64772582e-01
2.73472160e-01 -5.28195918e-01 2.22430989e-01 6.67538941e-01
-4.14744347e-01 -7.81403005e-01 -1.09670401e+00 8.59708011e-01
-1.51438549e-01 8.79599079e-02 -2.21031785e-01 4.31527942e-01
4.99379396e-01 9.10778821e-01 -3.07695735e-02 -1.02285218e+00
-1.37565956e-01 1.08749762e-01 3.84843379e-01 -3.78159970e-01
-3.38086337e-01 -1.45040900e-01 -2.64059514e-01 -2.06368238e-01
9.70602557e-02 -6.40766263e-01 -1.05727935e+00 -3.21916521e-01
-5.88063478e-01 2.51210406e-02 3.30442309e-01 8.14316213e-01
2.30750695e-01 6.25274479e-01 1.23944783e+00 -9.14721072e-01
-1.14638865e+00 -9.01858985e-01 -6.04479611e-01 5.24744987e-01
4.20453131e-01 -9.01430607e-01 -7.64822364e-01 -2.63556063e-01] | [14.386828422546387, 9.609318733215332] |
170e0b63-3766-4d2e-9dc3-7e1fb973734b | on-the-interaction-between-annotation-quality | null | null | https://aclanthology.org/2021.ranlp-main.99 | https://aclanthology.org/2021.ranlp-main.99.pdf | On the Interaction between Annotation Quality and Classifier Performance in Abusive Language Detection | Abusive language detection has become an important tool for the cultivation of safe online platforms. We investigate the interaction of annotation quality and classifier performance. We use a new, fine-grained annotation scheme that allows us to distinguish between abusive language and colloquial uses of profanity that are not meant to harm. Our results show a tendency of crowd workers to overuse the abusive class, which creates an unrealistic class balance and affects classification accuracy. We also investigate different methods of distinguishing between explicit and implicit abuse and show lexicon-based approaches either over- or under-estimate the proportion of explicit abuse in data sets. | ['Sandra Kübler', 'Alexandra O’Neil', 'Holly Lopez Long'] | null | null | https://aclanthology.org/2021.ranlp-1.99 | https://aclanthology.org/2021.ranlp-1.99.pdf | ranlp-2021-9 | ['abusive-language'] | ['natural-language-processing'] | [-1.93607256e-01 -1.51137903e-01 -2.56042272e-01 -3.24687272e-01
-5.24972141e-01 -8.57688606e-01 8.13965440e-01 1.75559670e-01
-8.47015500e-01 9.61206019e-01 2.73123384e-01 -2.65003145e-01
2.47974783e-01 -6.30356014e-01 -1.25384536e-02 -5.41460514e-01
3.99174273e-01 3.26088101e-01 4.61584376e-03 -3.79155785e-01
4.77330774e-01 4.16701972e-01 -1.06929088e+00 2.27784559e-01
8.09778869e-01 5.45148730e-01 -6.73497379e-01 4.82029855e-01
-3.95816296e-01 1.10207772e+00 -1.32547235e+00 -1.23091614e+00
1.65620103e-01 -3.16173881e-01 -9.25514877e-01 -6.92379922e-02
7.38658667e-01 -2.50556380e-01 -1.65777251e-01 1.38261664e+00
6.87575579e-01 -3.35042745e-01 7.01048255e-01 -1.15474725e+00
-6.77721560e-01 8.93890560e-01 -8.46373856e-01 9.33676422e-01
6.20032966e-01 2.97404498e-01 7.33548820e-01 -5.40918171e-01
9.04053569e-01 1.46430933e+00 9.80250955e-01 5.40277421e-01
-1.18009782e+00 -1.16376948e+00 -1.32415771e-01 -1.83451414e-01
-1.68169951e+00 -6.16153598e-01 6.42111003e-01 -1.05213749e+00
6.98516369e-01 3.13635379e-01 4.72069025e-01 1.57961154e+00
1.72215864e-01 2.14844614e-01 1.47954273e+00 -3.25352937e-01
-2.70145405e-02 4.64792073e-01 7.41925180e-01 7.09908605e-01
9.79330242e-01 -3.28038394e-01 -6.17735505e-01 -9.74552035e-01
1.97684035e-01 -2.05140144e-01 -9.74706486e-02 3.45255136e-01
-5.24812579e-01 1.36289775e+00 9.52730551e-02 8.20698321e-01
-1.92394257e-01 -5.48753794e-03 8.44576359e-01 2.22629979e-01
7.93924034e-01 9.68343377e-01 9.80826691e-02 -5.05160451e-01
-9.59297955e-01 4.25062597e-01 1.07497036e+00 4.11439598e-01
3.89565676e-01 -6.06001467e-02 -2.35906407e-01 1.17776167e+00
-1.50360435e-01 2.78878391e-01 8.09615016e-01 -9.13372278e-01
3.12648982e-01 6.58200264e-01 1.33064821e-01 -1.21291220e+00
-2.43705347e-01 -2.15093687e-01 -2.51419693e-01 3.20304222e-02
7.98844576e-01 -3.64392191e-01 -3.11566651e-01 1.48375618e+00
2.12370202e-01 -4.80704844e-01 -6.06241524e-01 7.51325846e-01
3.34788203e-01 8.32105428e-02 5.83883524e-01 -4.25424427e-01
1.40335584e+00 -3.67716223e-01 -1.25436044e+00 -3.06078732e-01
1.20507169e+00 -6.08344734e-01 1.31731737e+00 4.93120164e-01
-9.30253506e-01 1.33184269e-01 -9.62100625e-01 -6.10247888e-02
-6.81226015e-01 -5.32424510e-01 6.05586708e-01 1.39697218e+00
-5.40053248e-01 5.29982209e-01 -2.08855033e-01 -3.36379796e-01
7.41503835e-01 4.53231931e-02 -3.61016154e-01 2.31455088e-01
-1.16726935e+00 1.28483677e+00 1.17268570e-01 -5.20866334e-01
-3.04063469e-01 -4.47428137e-01 -7.00095952e-01 -5.10679781e-01
3.97369832e-01 1.17607079e-01 1.13985193e+00 -1.32749879e+00
-8.93063664e-01 1.64316595e+00 1.44564658e-01 -3.91929209e-01
6.90188766e-01 -4.99966234e-01 -4.91746694e-01 -5.79052195e-02
4.48987782e-01 -3.00141592e-02 8.01679254e-01 -1.13522363e+00
-1.53410494e-01 -6.51733994e-01 1.35032669e-01 -7.88834877e-03
-6.14455462e-01 7.52828300e-01 5.01275003e-01 -7.48436987e-01
-4.55323815e-01 -7.95131445e-01 2.37891823e-01 -1.37427106e-01
-7.34124780e-01 -3.29844713e-01 8.13129604e-01 -8.26083541e-01
1.58605027e+00 -2.16486692e+00 -2.84354389e-01 7.38357008e-02
6.82667732e-01 6.00142002e-01 4.86969531e-01 7.21502528e-02
3.11520964e-01 1.00698984e+00 -1.53652176e-01 -3.53384674e-01
-2.37905001e-03 4.65222478e-01 -3.13918084e-01 9.09556627e-01
3.31538096e-02 5.66771269e-01 -9.07005012e-01 -8.72550547e-01
-3.44010800e-01 2.14217559e-01 -2.72265196e-01 8.18008184e-02
3.54151726e-01 5.43733500e-02 -1.51639596e-01 7.98019528e-01
5.53499699e-01 1.84676155e-01 2.19359517e-01 3.57549965e-01
-2.24986613e-01 6.52396500e-01 -5.53887665e-01 9.18658197e-01
-2.96939492e-01 8.90416384e-01 3.36482078e-01 -1.94115415e-01
7.18698621e-01 4.62640170e-03 -1.65258303e-01 -4.95239139e-01
6.69885278e-01 3.50871116e-01 2.19827592e-01 -7.02984214e-01
6.26705647e-01 -6.22817039e-01 -3.00594300e-01 5.97330034e-01
-3.90166305e-02 -7.71537572e-02 1.30253121e-01 1.48146838e-01
1.06385136e+00 -2.70178288e-01 8.77843201e-01 -6.12828553e-01
2.42241696e-01 -3.73851694e-02 4.50677156e-01 8.40938270e-01
-7.32734919e-01 1.68144867e-01 9.76004303e-01 -3.22541207e-01
-8.01101029e-01 -6.63792670e-01 -2.59367675e-01 1.54716384e+00
-1.13101497e-01 -1.34594172e-01 -9.85949099e-01 -1.18983912e+00
1.53060973e-01 1.04881763e+00 -6.94796443e-01 -3.11818123e-01
-3.94817084e-01 -1.00958836e+00 1.45154810e+00 1.16611332e-01
3.25358570e-01 -7.29299724e-01 -6.68226063e-01 -2.29584113e-01
-2.30704382e-01 -1.15577376e+00 -4.33666497e-01 -1.07570952e-02
-2.89155394e-01 -1.13549495e+00 -3.94674897e-01 -4.84644771e-02
2.51604140e-01 -7.12525845e-02 1.21133041e+00 8.20902288e-01
-2.14520693e-01 4.45763282e-02 -4.76184160e-01 -6.48481190e-01
-7.71490276e-01 2.22070858e-01 2.97518820e-01 3.72887999e-02
9.00742590e-01 -3.15551579e-01 7.17418222e-03 1.51020169e-01
-7.10933805e-01 -8.31352472e-01 5.21759652e-02 3.62502158e-01
-2.23406389e-01 -5.30640304e-01 5.39840400e-01 -1.59409392e+00
1.16915023e+00 -9.08597946e-01 -1.37904629e-01 -2.39903003e-01
-6.00215554e-01 -2.16657564e-01 8.82356167e-02 -9.09522593e-01
-1.05770195e+00 -3.48871768e-01 -4.41198260e-01 -2.13804886e-01
-2.15736061e-01 3.74488905e-02 -1.60337817e-02 -2.17164218e-01
1.23089397e+00 -4.05308574e-01 -6.42885566e-02 -6.50551498e-01
2.52603274e-03 1.15657270e+00 1.92115992e-01 -4.02436942e-01
5.80696285e-01 4.64005411e-01 -5.15611768e-01 -1.04934359e+00
-1.26546037e+00 -6.08382702e-01 -8.54402602e-01 -9.33894441e-02
8.48588884e-01 -5.88750780e-01 -4.56645727e-01 4.54336315e-01
-1.35005772e+00 -2.80514896e-01 -2.02675909e-01 -7.25647733e-02
-2.15995051e-02 6.74734414e-01 -8.02140713e-01 -1.23425055e+00
-2.71799237e-01 -8.52580786e-01 8.18108261e-01 -1.95072964e-01
-1.13633847e+00 -9.76128519e-01 3.31991583e-01 4.77340937e-01
2.29462400e-01 5.75090885e-01 6.20487690e-01 -1.47090805e+00
7.07399607e-01 -3.79927903e-01 -1.55554831e-01 2.14932010e-01
-7.87361115e-02 1.88597560e-01 -1.16503775e+00 3.41595933e-02
1.26377121e-01 -6.86231434e-01 4.35558766e-01 -3.41454864e-01
7.62658715e-01 -8.48493576e-01 -3.85780662e-01 7.43305832e-02
1.12209618e+00 -7.86821544e-02 5.79244673e-01 4.01499331e-01
7.41833091e-01 7.60520756e-01 4.09465224e-01 5.02494574e-01
-6.09337725e-03 8.12584639e-01 7.98897967e-02 4.26525801e-01
5.58491088e-02 -1.51144326e-01 4.29598838e-01 2.90143937e-01
6.40898123e-02 -2.41447419e-01 -1.18155801e+00 5.47624469e-01
-1.20950627e+00 -1.07879734e+00 -5.43223262e-01 1.89290905e+00
1.22631228e+00 3.17467570e-01 5.58411002e-01 4.60340738e-01
8.37200820e-01 1.02467306e-01 3.36391404e-02 -9.90055203e-01
-2.06841566e-02 1.53002366e-01 5.86116672e-01 7.08091378e-01
-9.47091281e-01 9.54461992e-01 7.68691254e+00 9.87950742e-01
-9.90303814e-01 7.84103513e-01 5.14708936e-01 -1.67858243e-01
1.84405129e-02 -5.51180363e-01 -7.96045184e-01 8.19571793e-01
9.72264349e-01 -2.13186927e-02 1.34959459e-01 9.70263362e-01
-7.03406855e-02 -2.16934875e-01 -8.04476917e-01 8.73113036e-01
4.43815529e-01 -7.90955663e-01 8.25339630e-02 3.98511469e-01
3.76409441e-01 -1.37720808e-01 -2.28866398e-01 3.48129272e-01
4.87865478e-01 -1.07309401e+00 1.08758843e+00 2.11789072e-01
7.80424118e-01 -5.48844695e-01 1.00907540e+00 5.30550718e-01
-2.04121545e-01 -3.17627966e-01 -2.20711648e-01 -7.69488335e-01
1.32658809e-01 7.21741259e-01 -6.87570095e-01 -3.08843672e-01
7.11416483e-01 1.87383309e-01 -8.23282480e-01 5.32214880e-01
-2.62315929e-01 7.66236782e-01 -1.22732282e-01 -1.24845386e-01
8.65794495e-02 9.00275335e-02 7.02055514e-01 1.61932445e+00
-2.32925177e-01 5.85014932e-02 -1.55021735e-02 8.52980375e-01
-2.80027866e-01 1.06360085e-01 -1.21690714e+00 -4.02789980e-01
6.30241334e-01 1.29106975e+00 -6.36444926e-01 -4.04653221e-01
-1.90573528e-01 9.28019226e-01 7.15753675e-01 -2.31192127e-01
-6.21952415e-01 -1.75820783e-01 8.82805049e-01 5.92526853e-01
-4.55725163e-01 -2.42160484e-01 -6.73986733e-01 -9.94497418e-01
-3.97126228e-01 -9.38702464e-01 6.45603061e-01 -4.60975885e-01
-1.64691591e+00 3.99846107e-01 6.24225214e-02 -5.43521404e-01
-2.96617031e-01 -6.71912670e-01 -4.47002023e-01 7.36021757e-01
-8.79642904e-01 -8.60999227e-01 -2.50387251e-01 8.36619064e-02
3.22428852e-01 1.23195633e-01 5.57483196e-01 3.98740828e-01
-6.16847038e-01 7.34505653e-01 -6.00797176e-01 5.01714110e-01
7.24618733e-01 -1.00314450e+00 -3.33506092e-02 6.31393611e-01
-3.21054086e-02 7.19077766e-01 9.32569563e-01 -9.53880847e-01
-3.71632069e-01 -8.80243361e-01 1.06656659e+00 -1.27834702e+00
9.97760832e-01 -4.67227399e-01 -9.93151128e-01 7.88177669e-01
1.20068625e-01 -1.67357981e-01 1.15086949e+00 1.74431443e-01
-9.43919539e-01 5.54363012e-01 -1.56557453e+00 4.20830846e-01
1.37536216e+00 -7.50558853e-01 -7.44758546e-01 3.13841313e-01
5.15097201e-01 1.88162196e-02 -6.36270821e-01 -1.83481559e-01
4.61853743e-01 -1.09689426e+00 5.31124234e-01 -8.02930236e-01
4.00653690e-01 5.07147074e-01 2.00770479e-02 -1.04948330e+00
-2.28054047e-01 -5.45551896e-01 3.68037559e-02 1.57427204e+00
3.02166700e-01 -8.28847826e-01 1.34563684e-01 7.67603576e-01
2.31799409e-01 -3.43973905e-01 -9.84594643e-01 -8.66296470e-01
5.00190794e-01 -2.88307905e-01 2.27664024e-01 1.74606192e+00
3.74011278e-01 4.31366324e-01 -1.99354336e-01 -3.04091960e-01
3.12312275e-01 -5.63855290e-01 5.65358818e-01 -1.27207923e+00
1.71776712e-01 -7.00964987e-01 -4.75641638e-01 -1.96222186e-01
4.91065979e-01 -6.61986113e-01 -2.14601800e-01 -5.40160179e-01
4.26333547e-01 -3.36926490e-01 3.88915777e-01 4.76280689e-01
-1.51271626e-01 1.00738776e+00 1.28265738e-01 3.48274678e-01
-6.69128239e-01 -1.22209147e-01 6.39203787e-01 1.34408176e-01
-1.08191267e-01 -4.44563389e-01 -9.63799536e-01 1.19503784e+00
7.15626657e-01 -8.29437137e-01 1.87010974e-01 -1.63182110e-01
6.53421819e-01 -5.90433300e-01 4.28017318e-01 -6.70732737e-01
-5.85251212e-01 -3.24802756e-01 3.95735614e-02 2.64190495e-01
3.27673852e-01 -5.08476198e-01 -2.31680155e-01 6.71478450e-01
-5.53482890e-01 -1.37609756e-03 -8.94146338e-02 3.17465067e-01
2.36781746e-01 -9.08426583e-01 1.05878532e+00 -4.39207345e-01
2.34290529e-02 -2.11051211e-01 -8.52090001e-01 5.54618061e-01
1.07245433e+00 -2.16904059e-01 -4.34289813e-01 -3.13594252e-01
-5.06743908e-01 -3.79013121e-01 8.07506144e-01 2.49934554e-01
-1.43121496e-01 -1.04601145e+00 -6.82041049e-01 -3.23315769e-01
1.64133489e-01 -7.97307312e-01 -4.06480551e-01 8.25209022e-01
-6.49522066e-01 -4.89856526e-02 -1.58130854e-01 -5.82883283e-02
-1.43971562e+00 5.63427508e-01 5.20652115e-01 -2.99796790e-01
-7.41399974e-02 7.66507864e-01 -1.02868766e-01 -2.26339817e-01
-1.64014310e-01 2.89169699e-01 -4.60738719e-01 5.08653402e-01
7.49373198e-01 9.10313725e-01 -5.90018742e-02 -1.30982530e+00
-5.02495289e-01 -1.48495540e-01 -7.81999603e-02 -6.10229373e-02
7.40373075e-01 -1.86255231e-01 -4.17946279e-01 9.42643166e-01
1.05566788e+00 5.89346111e-01 -3.43403369e-01 2.13649520e-03
3.75590920e-01 -8.63115430e-01 -1.36964396e-01 -7.67896593e-01
-4.53025609e-01 7.71318913e-01 2.88535833e-01 8.86188447e-01
2.43380144e-01 3.73075306e-02 6.07521892e-01 5.88502772e-02
4.14038897e-01 -1.17988598e+00 2.20622420e-01 3.73762608e-01
8.84666920e-01 -1.04815698e+00 3.43670845e-01 -8.31568420e-01
-8.85732830e-01 4.93199557e-01 8.21476936e-01 -2.13596284e-01
3.18578780e-01 5.39579034e-01 1.90268785e-01 -5.74257195e-01
-2.60499030e-01 -6.57829791e-02 6.58538863e-02 6.87844038e-01
7.40739882e-01 1.79036662e-01 -1.13661563e+00 1.00847280e+00
-6.11916482e-01 -3.53324831e-01 8.25026512e-01 8.56391072e-01
-3.24683160e-01 -5.95888495e-01 -5.93967378e-01 7.30105162e-01
-1.22898853e+00 8.24402049e-02 -1.46644270e+00 1.07810712e+00
5.08838177e-01 8.37545931e-01 1.22065023e-01 -4.11747277e-01
6.15645126e-02 6.15342557e-01 3.13045263e-01 -9.18237984e-01
-1.22804034e+00 -5.02945721e-01 8.37412536e-01 -3.47374767e-01
-3.01267296e-01 -6.43062711e-01 -8.80223513e-01 -6.92251742e-01
-6.61001444e-01 4.64971643e-03 4.15515482e-01 1.21654308e+00
8.75316635e-02 -2.36549631e-01 1.21078253e-01 -6.40320241e-01
-7.50981033e-01 -1.31639826e+00 -6.06965721e-01 1.01109421e+00
3.00845176e-01 -1.02583373e+00 -6.61603570e-01 -2.07145125e-01] | [8.685145378112793, 10.456568717956543] |
bd82caeb-48ee-4630-bedb-905e766beb2a | convolutional-neural-network-based-efficient | 2203.11537 | null | https://arxiv.org/abs/2203.11537v2 | https://arxiv.org/pdf/2203.11537v2.pdf | Convolutional Neural Network-based Efficient Dense Point Cloud Generation using Unsigned Distance Fields | Dense point cloud generation from a sparse or incomplete point cloud is a crucial and challenging problem in 3D computer vision and computer graphics. So far, the existing methods are either computationally too expensive, suffer from limited resolution, or both. In addition, some methods are strictly limited to watertight surfaces -- another major obstacle for a number of applications. To address these issues, we propose a lightweight Convolutional Neural Network that learns and predicts the unsigned distance field for arbitrary 3D shapes for dense point cloud generation using the recently emerged concept of implicit function learning. Experiments demonstrate that the proposed architecture outperforms the state of the art by 87% less model parameters, 36% reduced inference time and improved generated point cloud accuracy. | ['Jani Boutellier', 'Abol Basher'] | 2022-03-22 | null | null | null | null | ['point-cloud-generation'] | ['computer-vision'] | [ 6.85404167e-02 -1.33171231e-01 2.68839926e-01 -2.09395438e-01
-6.83374703e-01 -2.87694693e-01 4.52280164e-01 -8.95731077e-02
-1.17246918e-01 7.32664645e-01 -4.62801576e-01 -3.23110908e-01
-1.20265037e-01 -1.07421196e+00 -9.06018674e-01 -4.51402336e-01
-2.20507085e-02 9.06991124e-01 2.46624887e-01 -2.32036516e-01
3.90847176e-01 1.09038997e+00 -1.74420607e+00 -8.31210241e-02
1.04138458e+00 1.22748101e+00 1.82884827e-01 3.22105646e-01
-4.66474205e-01 7.81044364e-02 -3.12032342e-01 -1.90193981e-01
4.50427383e-01 3.32492650e-01 -3.33530009e-01 -4.93830480e-02
6.40851080e-01 -5.79454184e-01 -6.45456687e-02 9.95472372e-01
4.74668980e-01 -9.15707424e-02 6.57243788e-01 -1.15690386e+00
-5.39781809e-01 -1.18717298e-01 -6.68689966e-01 -3.10027480e-01
9.13125798e-02 1.38388472e-02 4.55417752e-01 -1.37525129e+00
4.50130880e-01 1.27678680e+00 9.90342140e-01 4.34788048e-01
-1.04272282e+00 -8.28876317e-01 2.83152070e-02 -5.66326194e-02
-1.61358953e+00 -1.30115062e-01 1.04265213e+00 -4.32231277e-01
8.84714186e-01 1.73083365e-01 6.86302423e-01 6.49668932e-01
-7.61855096e-02 3.78870636e-01 8.99759293e-01 -1.77601889e-01
2.86906570e-01 -1.72098741e-01 -2.63880223e-01 6.32946730e-01
5.60153961e-01 2.41257966e-01 -4.15220819e-02 -3.66857052e-01
1.44376898e+00 1.10614978e-01 -1.27338916e-01 -7.27129102e-01
-1.00985169e+00 9.01348948e-01 6.73530579e-01 -3.37797077e-03
-3.97278845e-01 1.89715490e-01 -3.17105465e-02 2.44249078e-03
8.02662015e-01 3.16120952e-01 -4.68620569e-01 -4.34289835e-02
-8.89584243e-01 8.16672802e-01 7.40735471e-01 1.17094660e+00
1.13315153e+00 1.42820418e-01 4.53197360e-01 4.73565429e-01
5.26649356e-01 6.83271110e-01 -2.21105874e-01 -1.00524068e+00
3.73070151e-01 8.89098048e-01 4.05543596e-01 -1.13647211e+00
-4.19136316e-01 -5.09352267e-01 -1.03314829e+00 8.27847600e-01
1.24760576e-01 -1.32385455e-02 -9.59764779e-01 1.08677423e+00
6.71540260e-01 5.88371813e-01 -4.15939599e-01 1.07289457e+00
9.29849744e-01 7.14712799e-01 -2.91693419e-01 8.28450844e-02
7.80254602e-01 -4.25252497e-01 -2.63601571e-01 1.57115869e-02
2.35325575e-01 -7.75812685e-01 7.36558378e-01 3.66873622e-01
-1.27409995e+00 -5.26104629e-01 -1.04251623e+00 -2.66755700e-01
-9.58108231e-02 -4.34955396e-02 7.20783412e-01 3.01501691e-01
-9.67125475e-01 8.01882148e-01 -8.61664414e-01 7.14301169e-02
7.02945948e-01 6.17525220e-01 -2.06086300e-02 -1.85490534e-01
-7.90560722e-01 6.13199055e-01 -1.46526266e-02 1.96587190e-01
-4.45794106e-01 -1.19035113e+00 -8.34809601e-01 8.57305154e-02
1.73446015e-02 -1.11831665e+00 1.20162690e+00 -4.65652734e-01
-1.53382552e+00 7.40586400e-01 -1.09381348e-01 -3.61809134e-01
5.83478689e-01 -4.39869702e-01 8.61167610e-02 -1.16943493e-01
5.62858172e-02 6.52005255e-01 8.22283387e-01 -1.49659896e+00
-5.24788141e-01 -5.86714566e-01 -4.00125161e-02 2.93985039e-01
1.35805443e-01 -4.37088817e-01 -3.66758764e-01 -3.75445247e-01
3.67379069e-01 -7.77166486e-01 -5.92027545e-01 5.11478543e-01
-1.09078258e-01 -4.24776196e-01 1.24126327e+00 -2.75223523e-01
4.83560145e-01 -1.99022162e+00 -1.11418039e-01 2.43221700e-01
3.28873515e-01 3.80138755e-01 1.64418787e-01 2.31845514e-03
2.19488531e-01 1.01437449e-01 -4.56482559e-01 -3.79977912e-01
-4.01574224e-02 1.65417612e-01 -4.68766540e-01 4.34387267e-01
3.78300548e-01 8.17059934e-01 -8.57699156e-01 -3.81911010e-01
7.14163482e-01 1.04932785e+00 -6.27075672e-01 1.13446303e-01
-4.65127110e-01 5.34360230e-01 -7.58453488e-01 7.78477371e-01
1.18195415e+00 -4.34510976e-01 -2.95443207e-01 -1.17419094e-01
-2.82397032e-01 1.43855631e-01 -1.26957941e+00 2.04081464e+00
-3.71646196e-01 4.07343179e-01 1.61395043e-01 -7.33398974e-01
1.23050714e+00 1.50044411e-01 7.91439474e-01 -3.76190245e-01
1.51318043e-01 4.99955177e-01 -2.89868116e-01 -2.42966712e-01
4.90963727e-01 -2.48229921e-01 3.01433146e-01 1.55876474e-02
-5.18032312e-01 -7.82385349e-01 -5.99586904e-01 -1.93031520e-01
1.00099528e+00 5.53346217e-01 -3.40402648e-02 6.81264549e-02
4.10468638e-01 2.65519679e-01 5.55116653e-01 3.75469834e-01
1.37989745e-01 9.57574606e-01 -1.00144118e-01 -6.76695168e-01
-1.20281076e+00 -1.14394641e+00 -3.33720714e-01 2.86032200e-01
3.77719522e-01 -1.33055136e-01 -5.02844274e-01 -1.92552015e-01
4.23992991e-01 4.36087340e-01 -2.45724812e-01 1.74333364e-01
-9.65321302e-01 -3.93744051e-01 1.52284831e-01 5.67067146e-01
4.39382076e-01 -8.59768987e-01 -5.57945788e-01 1.64143309e-01
1.08997852e-01 -1.16392756e+00 6.09919354e-02 -3.39663625e-01
-1.47315633e+00 -9.05437469e-01 -6.69661224e-01 -7.19736636e-01
9.41920400e-01 5.31540871e-01 1.42356408e+00 2.31569290e-01
-1.64106607e-01 -2.07608100e-03 -1.68446332e-01 -6.89317942e-01
-7.00601637e-02 1.13550693e-01 -5.69343120e-02 -2.34544247e-01
4.93275434e-01 -8.43921542e-01 -7.63009965e-01 2.75932908e-01
-6.83341742e-01 1.56954974e-01 6.09092355e-01 5.71567655e-01
9.76020396e-01 -1.62535235e-02 3.03980142e-01 -6.36171818e-01
2.88999408e-01 -4.22055393e-01 -1.11336315e+00 -3.98286641e-01
-3.94423008e-01 -1.36132479e-01 3.82276386e-01 -1.15915842e-01
-8.64342749e-01 4.50437218e-01 -5.54751635e-01 -9.88280177e-01
-4.44790572e-01 2.60201335e-01 -1.13093100e-01 -4.69257623e-01
6.39127433e-01 6.99129552e-02 5.54796606e-02 -6.81557417e-01
1.73137039e-01 3.80064875e-01 4.36197400e-01 -6.54648602e-01
1.19687486e+00 9.87546265e-01 3.93250883e-01 -1.05385840e+00
-5.57192504e-01 -3.16926956e-01 -8.33787620e-01 3.49315293e-02
7.12358713e-01 -9.37053382e-01 -6.79149389e-01 3.52294385e-01
-1.64447737e+00 -1.44126117e-01 -2.74768829e-01 3.59845638e-01
-4.44502234e-01 4.04215038e-01 -2.72637248e-01 -8.14073324e-01
-6.20018959e-01 -1.09507346e+00 1.51946557e+00 1.46757498e-01
9.63634104e-02 -7.14749336e-01 -3.22389696e-03 8.22209269e-02
5.10784864e-01 7.37407625e-01 9.11022186e-01 1.38066277e-01
-1.16690302e+00 -3.11053067e-01 -5.33454955e-01 3.27689461e-02
1.03535809e-01 9.40260589e-02 -8.21908712e-01 -7.27609396e-02
8.20271596e-02 -1.18484870e-01 3.97675782e-01 5.99674404e-01
1.40971243e+00 4.99144532e-02 -5.45685828e-01 1.02798903e+00
1.62812614e+00 -1.30061079e-02 5.30780494e-01 1.83418617e-01
8.41953039e-01 3.27010602e-01 5.35191774e-01 5.30108273e-01
3.85524362e-01 5.96032858e-01 9.59650159e-01 -1.12355419e-01
4.66761738e-02 -2.81755656e-01 -2.17957020e-01 7.18152106e-01
-4.77461606e-01 1.86055318e-01 -1.01281464e+00 4.57804531e-01
-1.81411111e+00 -6.98074996e-01 -5.91020823e-01 2.11814594e+00
4.76977557e-01 2.10015953e-01 -2.21555427e-01 1.96582451e-01
5.46652079e-01 -1.44331098e-01 -7.29117692e-01 -6.14858344e-02
7.52104223e-02 6.42444789e-01 3.66160899e-01 3.63084584e-01
-8.79616380e-01 9.14252043e-01 6.19832373e+00 4.99086797e-01
-1.18169379e+00 1.00464700e-03 1.80493906e-01 -6.35843575e-02
-4.81104106e-01 -7.83650279e-02 -8.48628163e-01 3.13169748e-01
4.24398929e-01 -6.93562180e-02 7.73349330e-02 1.22099030e+00
1.66541964e-01 2.72351891e-01 -9.78474081e-01 1.35571086e+00
-6.33979142e-02 -1.69408631e+00 2.20458105e-01 3.33277971e-01
7.93872535e-01 4.96989191e-01 3.70391160e-02 1.37883544e-01
2.89332539e-01 -1.12654626e+00 5.58799386e-01 4.77427155e-01
1.02618110e+00 -9.01032329e-01 5.05445600e-01 6.18657231e-01
-1.07012093e+00 4.32382315e-01 -7.74124384e-01 -4.08568263e-01
3.36607873e-01 9.39447403e-01 -7.56525338e-01 3.97726119e-01
7.91953564e-01 6.30399048e-01 -4.34303880e-02 1.32300925e+00
2.60469913e-02 2.64944822e-01 -6.41614139e-01 -6.38700183e-03
2.53447562e-01 -3.73978883e-01 7.03450382e-01 5.98697305e-01
6.42704010e-01 2.42611825e-01 1.05451189e-01 1.23281050e+00
-9.56562907e-02 -1.70039341e-01 -9.99766648e-01 5.15161812e-01
5.25272667e-01 1.23366499e+00 -5.38089633e-01 -3.43139209e-02
-4.25616652e-01 6.25679731e-01 2.89653361e-01 2.52160698e-01
-7.49155462e-01 -3.70460451e-01 8.95236731e-01 6.18052244e-01
3.49323511e-01 -8.07073832e-01 -6.43256485e-01 -9.59881067e-01
2.57832166e-02 -2.96945989e-01 -2.70351827e-01 -9.46463048e-01
-1.36590314e+00 5.75630069e-01 -1.45203754e-01 -1.52041197e+00
-1.68437749e-01 -7.87194550e-01 -4.70876336e-01 1.02482533e+00
-1.96198905e+00 -1.16030884e+00 -7.39917696e-01 6.33211017e-01
5.32465219e-01 5.70845604e-02 7.41524339e-01 4.73703176e-01
6.37705475e-02 1.39694527e-01 8.66592955e-03 -6.49546310e-02
2.53904700e-01 -1.09650481e+00 9.61072922e-01 3.55356276e-01
-9.08771604e-02 4.56337780e-01 3.28771323e-01 -6.83166385e-01
-1.62020528e+00 -1.28397226e+00 5.39617836e-01 -5.13974309e-01
1.27572775e-01 -4.06984061e-01 -1.18115699e+00 3.88094306e-01
-2.97887862e-01 3.22786510e-01 2.35868454e-01 1.81681421e-02
-1.91600360e-02 -2.23082677e-02 -1.24160719e+00 5.67892730e-01
1.20566845e+00 -1.31361276e-01 -4.74373817e-01 2.65422076e-01
8.53850603e-01 -9.53710318e-01 -7.49480665e-01 7.48259962e-01
3.86804372e-01 -9.80265379e-01 1.27399397e+00 -2.63246953e-01
4.47681099e-01 -4.84059662e-01 -1.32825375e-01 -1.13571107e+00
-5.10127366e-01 -5.63371181e-01 -3.40865433e-01 7.76417911e-01
3.10590994e-02 -4.12402987e-01 1.34909821e+00 5.07170022e-01
-5.16071916e-01 -8.92084777e-01 -1.15880263e+00 -5.52486718e-01
3.76387179e-01 -6.21213078e-01 1.10007298e+00 9.45739746e-01
-7.30793715e-01 2.03932717e-01 -3.60344574e-02 4.35825437e-01
1.02120137e+00 3.69949132e-01 1.03224325e+00 -1.84462023e+00
2.75943965e-01 -3.99426341e-01 -4.37056005e-01 -1.27516031e+00
8.71534422e-02 -6.84226274e-01 -7.49081671e-02 -1.75823736e+00
-4.44904268e-01 -1.11905229e+00 1.30563855e-01 7.88345709e-02
5.55614494e-02 3.41108382e-01 -1.08197838e-01 2.85455704e-01
-1.26804322e-01 6.26314402e-01 1.38046241e+00 -1.01534853e-04
-1.73464760e-01 1.49807975e-01 -4.53894615e-01 9.36011016e-01
7.27276564e-01 -2.16848552e-01 -3.63327384e-01 -1.06255484e+00
4.85824436e-01 -3.39966975e-02 6.20407045e-01 -1.11913157e+00
8.58904421e-02 -2.56098539e-01 5.44706881e-01 -1.24620831e+00
6.52899027e-01 -1.15425408e+00 2.32823506e-01 2.87915975e-01
4.47758615e-01 4.58309613e-02 3.13208759e-01 4.44478571e-01
-1.20892804e-02 5.95086403e-02 6.64423823e-01 -3.94444078e-01
-5.21671355e-01 8.65247011e-01 3.12612534e-01 -2.12482274e-01
9.60591435e-01 -4.42400843e-01 4.31097392e-03 -9.49971192e-03
-2.43209571e-01 6.64906874e-02 7.11081088e-01 4.00170922e-01
1.15581107e+00 -1.64639008e+00 -8.38868856e-01 4.79015559e-01
-1.82219490e-01 1.16090918e+00 2.23503426e-01 3.70423853e-01
-9.57906067e-01 4.29450601e-01 -1.24803357e-01 -1.07973790e+00
-8.03039312e-01 2.97877312e-01 2.79877990e-01 3.71414386e-02
-1.08497643e+00 7.55505562e-01 1.57412127e-01 -7.36299336e-01
1.33826747e-03 -5.06902874e-01 1.50705710e-01 -5.70646524e-01
1.41396224e-01 4.18286473e-01 3.31500709e-01 -7.23340750e-01
-2.27164447e-01 1.07232797e+00 1.38524860e-01 2.95943141e-01
1.52590394e+00 2.79666096e-01 5.97018264e-02 1.55948028e-01
1.03234494e+00 -1.98260844e-01 -1.41016209e+00 -2.94910550e-01
-3.59908849e-01 -7.69773364e-01 1.65564910e-01 -3.81602913e-01
-9.15276825e-01 1.10846639e+00 5.24795949e-01 6.41874373e-02
6.40174568e-01 -1.70607999e-01 1.10013139e+00 3.39715123e-01
7.78530419e-01 -6.33254886e-01 -3.20992470e-01 7.23270833e-01
1.04355609e+00 -1.30730689e+00 2.24353954e-01 -6.96958125e-01
-2.38167010e-02 9.74387467e-01 7.62937725e-01 -6.29108131e-01
9.59531546e-01 3.59923899e-01 -1.27196386e-01 -4.59953308e-01
-4.32140827e-01 7.49771073e-02 2.62603343e-01 8.44132721e-01
3.08537543e-01 -2.08610743e-01 4.88425381e-02 2.11519957e-01
-3.69597137e-01 3.46904159e-01 9.72320139e-02 8.99424255e-01
-4.34128433e-01 -9.81762469e-01 -6.43209159e-01 5.84912777e-01
-1.43579781e-01 1.77865922e-01 -1.87198326e-01 7.89183736e-01
2.56784916e-01 4.40650225e-01 3.65696430e-01 -1.91347748e-01
5.18539429e-01 -2.46761143e-01 5.56468189e-01 -6.49056971e-01
-2.72107661e-01 -2.29744483e-02 -3.85438502e-01 -4.82982010e-01
-3.95836443e-01 -5.57449222e-01 -1.45115829e+00 -5.25451183e-01
-3.75371575e-01 2.72407606e-02 9.81164932e-01 6.75781190e-01
8.51482451e-01 2.59184569e-01 6.17041111e-01 -1.54164207e+00
-4.56909806e-01 -7.62488902e-01 -4.02897537e-01 2.73464948e-01
3.36877286e-01 -9.82786417e-01 -1.94464579e-01 -2.24114999e-01] | [8.370190620422363, -3.4836010932922363] |
46c32fd8-7bf7-4852-9af5-315666c43e9d | p-noc-adversarial-cam-generation-for-weakly | 2305.12522 | null | https://arxiv.org/abs/2305.12522v1 | https://arxiv.org/pdf/2305.12522v1.pdf | P-NOC: Adversarial CAM Generation for Weakly Supervised Semantic Segmentation | To mitigate the necessity for large amounts of supervised segmentation annotation sets, multiple Weakly Supervised Semantic Segmentation (WSSS) strategies have been devised. These will often rely on advanced data and model regularization strategies to instigate the development of useful properties (e.g., prediction completeness and fidelity to semantic boundaries) in segmentation priors, notwithstanding the lack of annotated information. In this work, we first create a strong baseline by analyzing complementary WSSS techniques and regularizing strategies, considering their strengths and limitations. We then propose a new Class-specific Adversarial Erasing strategy, comprising two adversarial CAM generating networks being gradually refined to produce robust semantic segmentation proposals. Empirical results suggest that our approach induces substantial improvement in the effectiveness of the baseline, resulting in a noticeable improvement over both Pascal VOC 2012 and MS COCO 2014 datasets. | ['Zanoni Dias', 'Helio Pedrini', 'Lucas David'] | 2023-05-21 | null | null | null | null | ['weakly-supervised-semantic-segmentation'] | ['computer-vision'] | [ 7.36771405e-01 7.16793060e-01 -2.33416319e-01 -4.18524772e-01
-1.01183331e+00 -7.82170296e-01 8.28573227e-01 -1.01158887e-01
-4.33178812e-01 5.78628600e-01 2.00822316e-02 -1.43697694e-01
1.14945747e-01 -4.62577969e-01 -8.52322519e-01 -5.24217665e-01
3.75415653e-01 2.89749295e-01 6.40087485e-01 -2.09167272e-01
1.64618209e-01 2.66191393e-01 -1.16308582e+00 -1.33483494e-02
1.24412715e+00 9.57434237e-01 9.10088271e-02 4.95752990e-01
-6.29377812e-02 7.92890608e-01 -6.30893469e-01 -6.42603636e-01
5.38120091e-01 -3.76602590e-01 -1.00894165e+00 2.94720203e-01
5.16304672e-01 -6.62228540e-02 -9.36985612e-02 1.13826287e+00
2.80403972e-01 2.22194389e-01 5.28138518e-01 -1.04616797e+00
-2.86264211e-01 6.63639247e-01 -4.87103760e-01 -9.15665478e-02
8.72575492e-02 4.01198596e-01 9.87519801e-01 -5.88334084e-01
7.54812300e-01 9.86252010e-01 8.74870300e-01 7.69635201e-01
-1.32100868e+00 -3.76599550e-01 3.63837510e-01 -1.89155564e-01
-1.05507398e+00 -5.29605269e-01 9.04746175e-01 -2.66793400e-01
6.50831223e-01 2.46890396e-01 3.33927661e-01 1.32052553e+00
-4.70403731e-01 1.08224297e+00 1.22313690e+00 -5.21722674e-01
3.33132923e-01 2.74165303e-01 8.05242807e-02 5.48705578e-01
1.32382169e-01 -6.64715320e-02 -2.38050967e-01 2.63156369e-03
5.89799881e-01 -5.14379025e-01 -4.21362258e-02 -4.75967824e-01
-7.29765296e-01 6.85359001e-01 3.70538265e-01 2.00698227e-01
-1.39493391e-01 -3.05410475e-02 4.87079531e-01 -6.61558881e-02
7.04479396e-01 6.85388565e-01 -5.28829575e-01 2.92248148e-02
-1.19499791e+00 3.22080374e-01 6.38516068e-01 1.05356860e+00
7.21402168e-01 1.32549465e-01 -2.51594484e-01 9.21877921e-01
1.97917059e-01 2.20573395e-01 1.97388381e-01 -1.21296513e+00
4.51978207e-01 4.47836727e-01 7.91840628e-02 -6.78786337e-01
-2.19820872e-01 -4.41708207e-01 -4.34338301e-01 9.06981621e-03
5.52659035e-01 -1.70000881e-01 -1.46749258e+00 1.85185862e+00
3.82169485e-01 3.50927740e-01 3.44297215e-02 7.48844862e-01
4.21513528e-01 4.19635117e-01 6.03306532e-01 2.00009033e-01
9.43599820e-01 -1.12006474e+00 -5.23118854e-01 -4.79324430e-01
5.25302172e-01 -5.70036709e-01 1.35334885e+00 2.11646572e-01
-1.13820231e+00 -5.80389261e-01 -9.70574081e-01 -3.82632166e-02
-2.62316197e-01 2.49897852e-03 7.44083285e-01 6.90606296e-01
-9.09834325e-01 6.14227176e-01 -1.14034128e+00 -1.61445364e-01
8.57812881e-01 2.92257726e-01 -9.61515456e-02 -4.96267714e-03
-8.52438331e-01 7.32603848e-01 5.77209949e-01 1.22417472e-01
-8.92807722e-01 -8.55120718e-01 -9.21100914e-01 -2.25095913e-01
7.30923116e-01 -4.73257035e-01 1.12996054e+00 -1.43734944e+00
-1.46631932e+00 1.05053794e+00 1.85532764e-01 -7.01561868e-01
8.69479835e-01 -3.40824693e-01 3.56092565e-02 2.14716971e-01
1.90847501e-01 1.12735844e+00 8.73315573e-01 -1.58721626e+00
-5.29840291e-01 -1.76564664e-01 1.92687005e-01 7.44457617e-02
-2.04847634e-01 -6.10544756e-02 -8.41650546e-01 -1.04064929e+00
1.69498324e-02 -1.07430530e+00 -6.85891688e-01 -9.10317749e-02
-6.83748722e-01 -1.04525395e-01 8.53386581e-01 -8.01994026e-01
7.81781495e-01 -2.02248287e+00 1.05800778e-01 2.43870124e-01
-7.55050853e-02 6.71515584e-01 -3.59004140e-01 -1.83258697e-01
2.39782408e-01 3.49650294e-01 -9.40039396e-01 -5.96843779e-01
-5.70817180e-02 4.05215889e-01 -3.10889095e-01 2.88115889e-01
6.52770638e-01 1.02027452e+00 -8.08365405e-01 -6.25017345e-01
2.75238901e-01 3.12405199e-01 -7.31417298e-01 4.16969389e-01
-7.01245308e-01 6.81093693e-01 -5.11009395e-01 7.97216415e-01
6.09005630e-01 -2.15815619e-01 5.26125059e-02 4.70886156e-02
2.36653388e-01 2.01918289e-01 -8.79011750e-01 1.80677772e+00
-2.81610608e-01 3.27479839e-01 3.45079273e-01 -1.19244349e+00
5.50523400e-01 1.05556466e-01 4.54536706e-01 -5.33544779e-01
2.05407292e-01 8.82237032e-02 -1.87214732e-01 -2.95609444e-01
4.76801038e-01 -1.53263897e-01 -3.80570516e-02 1.88016891e-03
2.06555516e-01 -4.86719996e-01 2.19321191e-01 2.94272929e-01
9.32662129e-01 5.88448763e-01 -2.45057836e-01 -3.24018955e-01
4.91045982e-01 2.74879098e-01 8.31005394e-01 8.11923027e-01
-5.62555075e-01 9.03328478e-01 5.02707899e-01 1.68990437e-02
-1.14546990e+00 -8.96960795e-01 -3.19141522e-02 9.50053215e-01
2.10397586e-01 -2.51393557e-01 -1.26589012e+00 -1.28087091e+00
-1.71258554e-01 7.99212813e-01 -6.08879268e-01 -1.37954727e-01
-7.08395541e-01 -8.12283814e-01 8.65443289e-01 9.05034840e-01
6.62879407e-01 -1.12990975e+00 -2.29580805e-01 7.00675100e-02
-1.78394988e-01 -1.62261736e+00 -3.47326517e-01 2.00265810e-01
-8.21221948e-01 -1.04494691e+00 -7.73435771e-01 -6.62640214e-01
7.20040500e-01 -1.60359621e-01 1.11154199e+00 1.37049153e-01
-9.35703963e-02 2.09648773e-01 -4.07055587e-01 -3.84468824e-01
-4.97887820e-01 3.44036549e-01 -2.79007137e-01 -2.02230021e-01
-5.99951819e-02 -2.96214283e-01 -4.74847555e-01 2.00198367e-01
-1.09330404e+00 1.14921227e-01 5.03784716e-01 7.92785823e-01
7.43360937e-01 -3.23405504e-01 5.85579276e-01 -1.45904124e+00
3.43542814e-01 -2.54734188e-01 -6.90957367e-01 2.31647864e-01
-7.01342404e-01 -7.33081847e-02 7.31392503e-01 -3.84006441e-01
-1.37045527e+00 2.55594283e-01 -4.59502071e-01 -4.06902552e-01
-4.81903583e-01 3.28780949e-01 -3.57756317e-01 -2.56445915e-01
5.76505721e-01 3.60137038e-02 -1.93664208e-01 -4.01206136e-01
5.55525601e-01 3.28321308e-01 6.98743939e-01 -8.53895962e-01
9.46403503e-01 4.73873645e-01 -3.04769963e-01 -6.24927640e-01
-1.24615300e+00 -2.93325692e-01 -7.08986580e-01 1.13883607e-01
9.94652629e-01 -8.22814465e-01 4.44605537e-02 6.27613842e-01
-8.62106323e-01 -8.54525566e-01 -4.87814307e-01 3.48680504e-02
-6.65966749e-01 5.81958294e-01 -7.83321857e-01 -5.43875575e-01
-1.75486922e-01 -1.11370397e+00 9.94262695e-01 2.05444664e-01
-3.26208651e-01 -9.59068656e-01 -7.04760775e-02 8.77823234e-01
3.54210466e-01 4.61884558e-01 6.32683933e-01 -7.52587199e-01
-6.06698930e-01 -1.35905191e-01 -3.34110677e-01 7.94558585e-01
-2.77171712e-02 -3.10817678e-02 -1.11521757e+00 -1.55288368e-01
-2.49106765e-01 -6.29126608e-01 9.98960733e-01 3.56037498e-01
1.45360863e+00 -1.40175790e-01 -1.87352583e-01 8.34582031e-01
1.20100749e+00 4.38001193e-03 5.58137357e-01 2.63587862e-01
1.02094257e+00 6.85845315e-01 6.55334592e-01 -1.27987256e-02
1.51352003e-01 4.70377684e-01 3.95599604e-01 -3.62748444e-01
-3.81505013e-01 -3.41076314e-01 8.09775814e-02 4.70888615e-01
-9.43145901e-02 -4.35275435e-01 -8.82003784e-01 6.76906526e-01
-1.75418055e+00 -4.36582625e-01 7.52496300e-03 1.85192025e+00
1.00686026e+00 5.52946508e-01 1.02965713e-01 -1.81117505e-02
5.87196827e-01 3.83754045e-01 -6.67616606e-01 -2.09787324e-01
-1.73604846e-01 5.16352415e-01 7.47694612e-01 3.77630383e-01
-1.37083304e+00 1.57641506e+00 6.99527740e+00 1.00284922e+00
-8.73553813e-01 8.41995925e-02 8.86333346e-01 3.11369747e-01
-3.60988110e-01 1.23580910e-01 -4.70030725e-01 4.59572405e-01
7.80849695e-01 4.09141451e-01 1.97230190e-01 7.76661694e-01
4.55670916e-02 3.94733474e-02 -7.30299175e-01 3.40004027e-01
-1.25622511e-01 -1.28724432e+00 7.90788233e-02 -1.96991518e-01
1.09003556e+00 3.15881930e-02 1.38003910e-02 3.22585106e-01
5.36993742e-01 -9.07772541e-01 8.36294174e-01 1.96179718e-01
6.83510065e-01 -6.27976358e-01 6.87979817e-01 2.53134966e-01
-8.57799947e-01 2.40152836e-01 -2.58071627e-02 1.07067235e-01
3.10673922e-01 3.84662986e-01 -5.74305058e-01 6.34913921e-01
4.95174140e-01 6.28726900e-01 -6.13562346e-01 7.03176498e-01
-5.57800591e-01 1.09875727e+00 -2.80661672e-01 4.42148179e-01
5.73813379e-01 -3.08755636e-01 5.12568951e-01 1.22306120e+00
-2.76435286e-01 -1.68059301e-02 3.72410953e-01 9.99240935e-01
-2.57875532e-01 -1.02812789e-01 -3.24839354e-01 -1.99579954e-01
2.78156132e-01 1.20475137e+00 -1.14884007e+00 -4.00709778e-01
-3.96328121e-01 1.02304292e+00 3.26515347e-01 4.56699789e-01
-1.04378021e+00 -6.90017641e-02 4.77156222e-01 7.12139830e-02
3.20328265e-01 -1.52030855e-01 -7.86551237e-01 -1.04720664e+00
4.26263995e-02 -1.10782480e+00 3.28400910e-01 -4.41043615e-01
-1.23125529e+00 4.86218542e-01 -6.97918385e-02 -7.51794219e-01
-1.38610527e-02 -4.05109674e-01 -6.77924037e-01 5.74811339e-01
-1.55499840e+00 -1.56188178e+00 -8.82399753e-02 4.15233046e-01
7.44596779e-01 3.67797539e-02 4.89511609e-01 1.86541632e-01
-7.54123867e-01 7.12745845e-01 -3.18891466e-01 1.72895133e-01
6.32270336e-01 -1.46954894e+00 5.33374429e-01 1.19925547e+00
1.18333630e-01 3.64431530e-01 6.74604833e-01 -7.71344125e-01
-8.25063705e-01 -1.20430958e+00 3.14986080e-01 -6.06471777e-01
5.90244412e-01 -4.46256280e-01 -1.01719213e+00 8.20906103e-01
6.12439662e-02 1.31138831e-01 3.19205999e-01 9.30335838e-03
-3.00820082e-01 1.85436413e-01 -1.29281127e+00 7.33839095e-01
1.11502147e+00 -5.07082105e-01 -5.09716332e-01 1.64478227e-01
9.12167668e-01 -5.71839213e-01 -5.53769052e-01 8.76710832e-01
1.83674335e-01 -8.18550944e-01 1.03758025e+00 -5.90699732e-01
4.71825689e-01 -2.30484426e-01 4.79195453e-02 -9.95760143e-01
8.80245268e-02 -7.72067904e-01 2.34823190e-02 1.52179062e+00
4.76360470e-01 -4.09087867e-01 1.23313570e+00 9.58805203e-01
-4.63343292e-01 -6.89402044e-01 -6.63736582e-01 -7.96247542e-01
2.41178796e-01 -5.55646598e-01 2.61917889e-01 1.09020805e+00
-4.56335038e-01 5.57199717e-02 -2.85219252e-01 1.21444233e-01
5.62198877e-01 -2.23301455e-01 8.31101358e-01 -8.64708841e-01
-2.88259149e-01 -4.29504216e-01 -1.69979215e-01 -1.05645108e+00
5.27030528e-01 -7.95355737e-01 3.20118606e-01 -1.25691891e+00
8.21401626e-02 -6.86754167e-01 -4.25172269e-01 7.11561680e-01
-5.44920921e-01 4.47607666e-01 1.95483431e-01 3.89231667e-02
-6.91237509e-01 5.03643334e-01 1.35874271e+00 -1.72765806e-01
-2.81602383e-01 6.75690100e-02 -8.19291294e-01 1.05220842e+00
7.95826554e-01 -4.38534468e-01 -4.91767436e-01 -3.77275944e-01
-1.76134929e-01 -2.52312273e-01 5.65769374e-01 -9.84000683e-01
-1.87309042e-01 -1.83643863e-01 8.87811407e-02 -2.94349790e-01
2.21588254e-01 -5.71248174e-01 -2.02351168e-01 2.96944439e-01
-5.68503499e-01 -4.75857109e-01 3.70093346e-01 6.95486546e-01
-2.90060341e-01 -2.15424508e-01 9.99655545e-01 -6.91486523e-02
-8.86954606e-01 1.76400885e-01 6.56236857e-02 4.71586704e-01
1.02481353e+00 -2.43823424e-01 -1.12825029e-01 -5.61762713e-02
-6.36009634e-01 3.67944181e-01 5.88879526e-01 3.94356281e-01
1.76927686e-01 -7.78111219e-01 -5.02483964e-01 -4.23566409e-04
-9.15200915e-03 4.45246875e-01 4.11814488e-02 6.09351754e-01
-5.38669646e-01 1.00502633e-01 -9.97423977e-02 -4.88461316e-01
-9.82105315e-01 3.58230174e-01 2.05661058e-01 -4.28179085e-01
-6.68838620e-01 1.05401766e+00 1.92633390e-01 -5.33285439e-01
3.95643532e-01 -3.00833344e-01 4.76303473e-02 -1.99656382e-01
-4.73912880e-02 1.95334971e-01 9.16008651e-02 -5.30283988e-01
-3.03458720e-01 3.16372514e-01 -1.67152956e-01 -5.29433675e-02
1.26935709e+00 -7.99720734e-02 2.30250433e-01 -2.84262169e-02
8.21108878e-01 1.71021566e-01 -1.92346334e+00 2.19055545e-02
3.71693611e-01 -3.05780649e-01 -2.15374585e-03 -1.08614373e+00
-1.21317673e+00 5.76381564e-01 3.16940814e-01 6.86343238e-02
1.06819737e+00 1.31623030e-01 1.10187054e+00 6.22887909e-02
1.83681712e-01 -1.29250181e+00 -1.81635767e-02 4.39879447e-01
4.66322392e-01 -1.49816179e+00 -2.34278247e-01 -8.69933903e-01
-7.56701410e-01 5.92133582e-01 7.52020657e-01 -3.23268026e-01
3.27710181e-01 3.56064230e-01 2.36308172e-01 -7.87685588e-02
-1.41554713e-01 -4.80098784e-01 3.62910777e-01 6.86519861e-01
2.99938411e-01 -9.20021012e-02 -3.25821280e-01 8.18236947e-01
-1.08722402e-02 -2.51751482e-01 1.49175942e-01 8.95442188e-01
-7.64577836e-02 -1.20085919e+00 -5.08703105e-02 1.94985271e-01
-7.72393405e-01 -6.68832064e-02 -5.86687684e-01 9.34812605e-01
2.44905502e-01 8.89601827e-01 -1.70768514e-01 -1.38925344e-01
3.28094214e-01 8.34537596e-02 3.48022521e-01 -6.18512571e-01
-6.00600004e-01 1.39487326e-01 1.79493383e-01 -6.51880264e-01
-6.66940689e-01 -5.87965608e-01 -1.27619874e+00 2.62386292e-01
-4.96263802e-01 -1.61522254e-01 4.19622481e-01 1.20999479e+00
2.69344360e-01 6.32072926e-01 2.21971259e-01 -8.53349805e-01
-5.27203321e-01 -8.49731982e-01 -2.18150124e-01 7.95198560e-01
8.06940794e-02 -4.94963139e-01 -2.94700801e-01 2.99002469e-01] | [9.60326099395752, 0.6987987160682678] |
1266f905-e4a8-4baa-a3a0-e8c4157073e0 | augmenting-reddit-posts-to-determine-wellness | 2306.04059 | null | https://arxiv.org/abs/2306.04059v1 | https://arxiv.org/pdf/2306.04059v1.pdf | Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental Health | Amid ongoing health crisis, there is a growing necessity to discern possible signs of Wellness Dimensions (WD) manifested in self-narrated text. As the distribution of WD on social media data is intrinsically imbalanced, we experiment the generative NLP models for data augmentation to enable further improvement in the pre-screening task of classifying WD. To this end, we propose a simple yet effective data augmentation approach through prompt-based Generative NLP models, and evaluate the ROUGE scores and syntactic/semantic similarity among existing interpretations and augmented data. Our approach with ChatGPT model surpasses all the other methods and achieves improvement over baselines such as Easy-Data Augmentation and Backtranslation. Introducing data augmentation to generate more training samples and balanced dataset, results in the improved F-score and the Matthew's Correlation Coefficient for upto 13.11% and 15.95%, respectively. | ['Sunghwan Sohn', 'Vijay Mago', 'Muskan Garg', 'Chandreen Liyanage'] | 2023-06-06 | null | null | null | null | ['semantic-textual-similarity', 'semantic-similarity'] | ['natural-language-processing', 'natural-language-processing'] | [ 3.08539718e-01 7.10886300e-01 -9.34964046e-02 -4.68676567e-01
-9.19180632e-01 -2.25886732e-01 8.58830214e-01 5.80898762e-01
-3.23511988e-01 8.20858657e-01 1.07077980e+00 -2.12962314e-01
1.25178089e-02 -7.16301739e-01 -1.54230982e-01 -4.97709095e-01
3.23732384e-02 6.71312749e-01 -1.93348184e-01 -3.64229977e-01
1.77291799e-02 -2.16188237e-01 -1.07145691e+00 2.97364861e-01
1.28528130e+00 6.61212206e-01 -1.43067658e-01 6.63149178e-01
-3.32057118e-01 9.63826954e-01 -7.52596498e-01 -6.67157054e-01
-2.68539160e-01 -7.98675478e-01 -1.05006325e+00 2.43253484e-01
7.19344467e-02 -2.54659802e-01 -5.71424738e-02 9.42268312e-01
8.27825665e-01 -1.69535294e-01 5.03229737e-01 -1.14094532e+00
-9.85303521e-01 7.54966259e-01 -5.48840523e-01 1.97513491e-01
6.39781237e-01 1.08589448e-01 8.98046613e-01 -7.10738540e-01
7.67999113e-01 1.16252089e+00 8.20214748e-01 6.33177876e-01
-1.19094014e+00 -4.22128856e-01 -1.78804755e-01 1.52057603e-01
-1.07013547e+00 -3.25329632e-01 6.72622979e-01 -3.84404689e-01
9.03906584e-01 4.93628621e-01 6.73577607e-01 1.42653072e+00
-2.86488652e-01 5.72890401e-01 1.26521444e+00 -4.06183422e-01
2.40218565e-02 1.09990900e-02 2.01181680e-01 6.42517030e-01
2.36218542e-01 -5.41643083e-01 -5.56442916e-01 -3.11550349e-01
4.16403621e-01 -9.22853053e-02 -1.79288924e-01 4.05022502e-01
-1.39890671e+00 8.94090235e-01 1.71837255e-01 2.55585730e-01
-6.29009247e-01 -3.87999475e-01 5.18371642e-01 5.35775609e-02
9.63588595e-01 7.32159793e-01 -4.52514231e-01 -3.99636835e-01
-8.11523259e-01 2.61737674e-01 6.18891597e-01 6.38803780e-01
2.41746530e-01 -1.81346551e-01 -4.73880887e-01 9.66791153e-01
1.45031810e-01 5.44168413e-01 7.43728638e-01 -7.31872201e-01
7.14314997e-01 1.09117401e+00 -1.81609288e-01 -1.16680133e+00
-7.65194714e-01 -6.82815611e-01 -1.12087595e+00 -8.34409595e-01
1.97206452e-01 -3.64337951e-01 -9.15169358e-01 1.97776806e+00
4.95196402e-01 2.22569946e-02 2.79616773e-01 5.97347915e-01
1.13392687e+00 4.97789830e-01 3.33837658e-01 -3.83221984e-01
1.52562976e+00 -6.91285133e-01 -1.21139038e+00 -3.08021039e-01
8.77278090e-01 -7.28633642e-01 1.54778075e+00 1.96309596e-01
-8.69755030e-01 -2.11128995e-01 -8.26882184e-01 -1.54944345e-01
-7.31375664e-02 -1.66116226e-02 4.42821264e-01 5.62929988e-01
-9.14381325e-01 3.82629991e-01 -7.84043193e-01 -5.76764345e-01
6.08513653e-01 1.65046617e-01 -3.84134650e-01 -1.11527182e-02
-1.25221288e+00 6.50664568e-01 5.66258132e-01 -2.46015564e-01
-3.12844127e-01 -8.44898164e-01 -8.48073602e-01 -2.55197853e-01
2.16838837e-01 -7.78717518e-01 1.10281038e+00 -4.99136984e-01
-1.12764919e+00 1.04441404e+00 4.88580763e-02 -3.83299768e-01
4.42023128e-01 -2.26385012e-01 -6.38081372e-01 7.88940787e-02
1.23726040e-01 5.93651175e-01 1.84386581e-01 -9.09382522e-01
-1.97184339e-01 -4.06163722e-01 -2.57747114e-01 1.59785196e-01
-7.93545544e-01 1.49527416e-01 -1.06786340e-01 -7.38074183e-01
2.11407378e-01 -7.21726894e-01 -3.14619780e-01 -4.76282805e-01
-8.76697600e-01 -1.90157548e-01 4.59591210e-01 -1.18233836e+00
1.52885652e+00 -1.79146838e+00 -1.49752066e-01 -4.06381004e-02
6.58242345e-01 2.58524746e-01 -1.42945454e-01 5.64493477e-01
4.03960757e-02 4.27178055e-01 -2.86520630e-01 -4.96435821e-01
-2.95725781e-02 5.06611764e-01 -1.13937639e-01 2.26984814e-01
6.06277406e-01 9.52941060e-01 -1.02188563e+00 -5.57397008e-01
-2.50813454e-01 3.79302144e-01 -8.35415006e-01 4.19493675e-01
-1.68216482e-01 7.12936759e-01 -3.26515764e-01 4.13018018e-01
4.77399141e-01 -6.38993204e-01 3.54183167e-01 5.08459993e-02
9.18789506e-02 6.81458414e-01 -8.14046919e-01 1.53136170e+00
-2.27877070e-04 4.14172947e-01 -6.16202474e-01 -7.99659133e-01
1.11424267e+00 3.20021629e-01 4.31671470e-01 -8.56600761e-01
3.32328156e-02 3.39381918e-02 1.65454194e-01 -9.24914420e-01
6.51056170e-01 -2.96566248e-01 -2.74481773e-01 4.58333820e-01
5.97562306e-02 2.35842273e-01 1.70081109e-01 3.54175389e-01
1.16312778e+00 -2.14052647e-01 4.44983929e-01 -2.15924487e-01
2.66288310e-01 5.88094369e-02 5.80429852e-01 4.10014004e-01
1.15788795e-01 6.79440558e-01 7.48951674e-01 -2.43321240e-01
-1.11138737e+00 -5.84586263e-01 -1.14342771e-01 9.34443474e-01
-3.48157227e-01 -6.74623013e-01 -8.07571411e-01 -6.62992477e-01
-3.77740473e-01 7.95185149e-01 -7.79638112e-01 -2.50209183e-01
-3.96825343e-01 -1.52309275e+00 8.22786212e-01 5.40678084e-01
6.33244276e-01 -8.35109353e-01 -2.80228108e-01 2.84502536e-01
-7.80123353e-01 -1.30796850e+00 -2.26291001e-01 2.99109984e-02
-8.23368132e-01 -9.64519739e-01 -6.07876480e-01 -4.69020456e-01
6.95687234e-01 -2.51180053e-01 1.12676549e+00 3.90687399e-02
-1.40375942e-01 -1.56444252e-01 -6.21999264e-01 -4.46094900e-01
-8.47774267e-01 3.33838493e-01 -6.36083931e-02 -2.44925067e-01
3.69757175e-01 -3.89449477e-01 -7.38053560e-01 -6.92974553e-02
-9.59296286e-01 4.64578241e-01 4.03671861e-01 8.60597312e-01
3.17909271e-01 -3.22630316e-01 9.70415056e-01 -1.12250412e+00
9.54552770e-01 -7.79073834e-01 2.58668184e-01 4.58907783e-02
-1.09714651e+00 7.28807524e-02 2.94247508e-01 -5.05723655e-01
-9.63812888e-01 -4.53655750e-01 -5.49026430e-01 3.74024689e-01
-1.36525556e-01 7.83955574e-01 -4.74218652e-02 6.97288275e-01
8.38058829e-01 1.33135602e-01 1.94854930e-01 -7.38976717e-01
3.53226244e-01 9.42949414e-01 6.46203637e-01 -1.16218619e-01
5.98910630e-01 4.12497483e-02 -4.06937897e-01 -6.20707333e-01
-1.12926388e+00 -3.93661678e-01 -4.25091416e-01 1.06290407e-01
9.28080618e-01 -9.12946284e-01 -3.15659523e-01 4.84789133e-01
-1.08710682e+00 -2.47764781e-01 -3.25685918e-01 3.35623562e-01
-1.74622789e-01 3.65148008e-01 -6.89395368e-01 -6.70051754e-01
-7.01956928e-01 -5.76968193e-01 9.08345342e-01 1.05186403e-01
-8.27111542e-01 -1.04272950e+00 3.64343256e-01 7.07421958e-01
3.86811048e-01 6.54628694e-01 1.12471867e+00 -1.35429704e+00
2.75213271e-01 -2.46103838e-01 -3.27261746e-01 2.38712147e-01
2.45128319e-01 -1.69691175e-01 -8.04270625e-01 3.42805348e-02
-7.89112002e-02 -3.73037219e-01 4.24674153e-01 -1.76652759e-01
8.97800684e-01 -9.40342307e-01 1.08345263e-01 1.95981041e-01
1.18119097e+00 -1.36501146e-02 6.99372113e-01 2.11634815e-01
6.41154349e-01 6.51842833e-01 4.13813710e-01 9.22586143e-01
9.58551109e-01 2.93117613e-01 1.54795885e-01 -5.22271991e-01
-2.41474167e-01 -3.83660614e-01 2.23958775e-01 1.28324473e+00
-7.22644106e-02 -4.36280251e-01 -1.30555463e+00 5.97650528e-01
-1.64042914e+00 -7.40529597e-01 -4.79417443e-01 1.78871274e+00
1.24260867e+00 6.46193177e-02 4.04789865e-01 3.38666528e-01
4.70879436e-01 9.45271924e-02 -3.77457082e-01 -2.45881259e-01
-2.98253208e-01 1.31935537e-01 1.35039106e-01 2.74482608e-01
-8.61206889e-01 7.33776629e-01 6.25796700e+00 4.68830734e-01
-8.49731386e-01 3.12491268e-01 9.90043461e-01 1.20641373e-01
-5.40528178e-01 -4.08745766e-01 -6.51116908e-01 5.51529169e-01
1.22301054e+00 -1.25756919e-01 6.28060177e-02 3.79345059e-01
3.77719849e-01 1.79031491e-02 -7.65382648e-01 6.89263821e-01
3.26532066e-01 -1.17492950e+00 -1.00329690e-01 2.23242164e-01
7.63204157e-01 6.18113019e-02 1.35022569e-02 3.58613312e-01
3.68456244e-01 -7.98063159e-01 3.64690930e-01 4.29658085e-01
7.15761960e-01 -5.17154276e-01 1.13331020e+00 4.32733208e-01
-4.17905569e-01 1.07695691e-01 3.93703207e-02 -1.27811447e-01
1.36214525e-01 7.97768116e-01 -1.38806665e+00 4.62871671e-01
3.22701216e-01 5.06221294e-01 -8.72912049e-01 7.92962551e-01
-3.37722450e-01 8.87412131e-01 -1.08792879e-01 -1.00984104e-01
1.40521660e-01 3.07233147e-02 2.73497880e-01 1.33540070e+00
2.83626825e-01 2.66755641e-01 5.97377978e-02 7.88862765e-01
-2.83922642e-01 4.85481590e-01 -1.51252940e-01 -5.26810527e-01
3.23433936e-01 1.15837026e+00 -5.58722377e-01 -5.09192646e-01
-2.67567515e-01 9.24846411e-01 2.25803539e-01 1.87421683e-02
-8.24026942e-01 -4.47256528e-02 2.98728526e-01 3.07559431e-01
-3.06773543e-01 -5.48737273e-02 -3.97314638e-01 -1.05650008e+00
-9.04125348e-02 -1.05556560e+00 4.99816447e-01 -5.18276691e-01
-1.42530811e+00 7.78593123e-01 -1.90347612e-01 -9.03693140e-01
-5.10797799e-01 -7.63399014e-03 -4.30343300e-01 5.45365155e-01
-1.41323686e+00 -1.23699009e+00 -5.46341836e-01 2.64965475e-01
4.66160268e-01 1.06486551e-01 1.06163716e+00 4.97436523e-01
-8.01783562e-01 6.12774551e-01 -1.81185335e-01 1.94429383e-01
8.12911153e-01 -1.38652027e+00 5.46387970e-01 6.06076062e-01
-1.06279753e-01 5.30420065e-01 9.09126520e-01 -1.00667131e+00
-9.69396472e-01 -1.27768576e+00 1.41731679e+00 -4.08633977e-01
7.69877493e-01 -3.10636848e-01 -1.10141528e+00 3.94960940e-01
3.02528292e-01 -5.26252866e-01 1.24902844e+00 3.20907682e-01
-2.46510908e-01 2.89074749e-01 -1.38346303e+00 6.28659785e-01
1.08958519e+00 -3.93880904e-01 -7.66566515e-01 7.05036223e-01
9.21445966e-01 -2.93206602e-01 -1.18670166e+00 3.64697665e-01
1.60040095e-01 -6.24721408e-01 7.91116416e-01 -9.58037913e-01
8.38763654e-01 1.60784334e-01 -1.92959502e-01 -1.20600224e+00
-1.62906602e-01 -7.52786160e-01 -5.52994236e-02 1.64522147e+00
6.45822465e-01 -5.86544096e-01 7.06821382e-01 8.13173473e-01
-2.38624200e-01 -8.35965514e-01 -6.73272252e-01 -5.17720044e-01
-7.19787180e-02 -2.96217084e-01 7.14118123e-01 1.42363024e+00
3.57454151e-01 6.03677750e-01 -5.23988724e-01 -1.05477974e-01
3.05728436e-01 -2.27088675e-01 6.04954898e-01 -1.17648327e+00
-2.12652609e-01 -1.14322819e-01 -1.77181333e-01 -5.14941275e-01
-2.42590412e-01 -1.06225026e+00 -2.60354578e-01 -1.81755316e+00
6.77439928e-01 -2.91861862e-01 -9.20530334e-02 7.43990362e-01
-5.28262317e-01 4.84037548e-01 -2.84339990e-02 8.38447660e-02
-6.27220511e-01 6.44639373e-01 1.30658841e+00 1.98460385e-01
-3.76311749e-01 -3.58197927e-01 -1.15584528e+00 7.49636233e-01
1.02974439e+00 -5.00557005e-01 -3.65991265e-01 -3.22375566e-01
4.31643486e-01 3.41324657e-02 2.74622530e-01 -6.99100375e-01
-1.38330579e-01 -1.70589965e-02 2.08741784e-01 -4.29487914e-01
7.41675794e-02 -1.52097538e-01 1.32019833e-01 5.54940641e-01
-6.75733089e-01 3.85007322e-01 -2.47956309e-02 3.87618184e-01
-3.49341184e-02 4.64740023e-02 5.72949231e-01 2.71847062e-02
-1.32414177e-01 1.12498060e-01 -2.58720070e-01 5.59483051e-01
5.93579352e-01 -6.67773979e-03 -7.45739281e-01 -4.61531013e-01
-8.65526319e-01 1.41945943e-01 1.35479882e-01 3.67902279e-01
4.71591055e-01 -1.36373246e+00 -1.07806158e+00 1.92513630e-01
1.65256530e-01 -9.88539830e-02 2.88245529e-01 1.21128833e+00
-3.20276231e-01 1.13804556e-01 -7.57670477e-02 -2.86099821e-01
-1.25114322e+00 2.50286609e-01 -2.24067479e-01 -6.17409408e-01
-6.03665531e-01 7.65784323e-01 -1.98135898e-01 -4.45984304e-01
-1.06351534e-02 -5.67036688e-01 -3.17628264e-01 2.89553672e-01
5.90205193e-01 5.24942160e-01 1.43900007e-01 -5.96247554e-01
-2.13717759e-01 -4.09558881e-03 -1.50074176e-02 2.48727947e-03
1.68890083e+00 -2.46717677e-01 -9.57899839e-02 3.23107094e-01
1.19915450e+00 -1.60861872e-02 -6.90737486e-01 -3.69442075e-01
3.74241769e-01 -1.50052339e-01 -5.91310598e-02 -1.21950924e+00
-6.26228571e-01 6.72120631e-01 5.50641239e-01 4.83122528e-01
1.06104517e+00 3.58918577e-01 1.09095526e+00 7.16388226e-02
-2.40854636e-01 -9.96378481e-01 3.95559698e-01 4.47462857e-01
9.92078364e-01 -1.30031002e+00 -9.47891623e-02 -3.89699817e-01
-1.01521742e+00 7.77706921e-01 3.48314434e-01 2.31824681e-01
2.06039771e-01 2.36919060e-01 1.32949173e-01 -3.92892271e-01
-8.42195809e-01 -1.72517538e-01 5.38990498e-01 5.51196158e-01
6.52948737e-01 1.11595586e-01 -6.23111963e-01 9.66594398e-01
-5.84998250e-01 -9.94570777e-02 5.19617081e-01 4.04406875e-01
-3.86002481e-01 -1.08081579e+00 -1.22805312e-01 6.42523348e-01
-8.16959262e-01 -2.94545740e-01 -6.13409460e-01 7.01858997e-01
2.09713146e-01 9.41562533e-01 9.50107798e-02 -5.34100175e-01
2.61321694e-01 3.34520370e-01 9.36368704e-02 -7.56358862e-01
-6.76499069e-01 3.43488574e-01 7.09113657e-01 -2.39729285e-01
-6.17778122e-01 -7.80418813e-01 -1.35966456e+00 -2.31152460e-01
-2.17366457e-01 -2.58710352e-03 5.09474874e-01 1.03712058e+00
5.58409750e-01 6.24079049e-01 4.94289398e-01 3.62582766e-02
-5.47234952e-01 -1.32562971e+00 -2.25952417e-01 7.24600255e-01
2.87142783e-01 -2.70336092e-01 -7.88348094e-02 9.35634896e-02] | [8.582746505737305, 8.669063568115234] |
652142a3-b8a5-4e1b-865f-dbf3ab83e395 | joint-coordinate-regression-and-association | 2307.01004 | null | https://arxiv.org/abs/2307.01004v1 | https://arxiv.org/pdf/2307.01004v1.pdf | Joint Coordinate Regression and Association For Multi-Person Pose Estimation, A Pure Neural Network Approach | We introduce a novel one-stage end-to-end multi-person 2D pose estimation algorithm, known as Joint Coordinate Regression and Association (JCRA), that produces human pose joints and associations without requiring any post-processing. The proposed algorithm is fast, accurate, effective, and simple. The one-stage end-to-end network architecture significantly improves the inference speed of JCRA. Meanwhile, we devised a symmetric network structure for both the encoder and decoder, which ensures high accuracy in identifying keypoints. It follows an architecture that directly outputs part positions via a transformer network, resulting in a significant improvement in performance. Extensive experiments on the MS COCO and CrowdPose benchmarks demonstrate that JCRA outperforms state-of-the-art approaches in both accuracy and efficiency. Moreover, JCRA demonstrates 69.2 mAP and is 78\% faster at inference acceleration than previous state-of-the-art bottom-up algorithms. The code for this algorithm will be publicly available. | ['YuFeng Yao', 'Li Zhang', 'Wangpeng An', 'Yunshi Xie', 'Dongyang Yu'] | 2023-07-03 | null | null | null | null | ['pose-estimation', 'multi-person-pose-estimation'] | ['computer-vision', 'computer-vision'] | [-2.77488112e-01 -1.54496143e-02 -3.99697982e-02 -3.95683736e-01
-9.11058128e-01 -8.16580653e-02 3.65389794e-01 -3.50988299e-01
-6.93179190e-01 5.45756519e-01 3.47293049e-01 2.82629609e-01
2.23925129e-01 -6.00416958e-01 -1.09649038e+00 -2.07412377e-01
8.02596286e-03 8.96269441e-01 2.37417877e-01 -2.43933752e-01
-2.21009940e-01 3.04333270e-01 -1.42785645e+00 -1.05641492e-01
5.74131548e-01 1.08091772e+00 -2.11775228e-02 7.35830784e-01
5.40005445e-01 6.12092733e-01 -5.14409840e-01 -8.99811804e-01
2.98700452e-01 -7.56408200e-02 -5.06135285e-01 -3.30971003e-01
9.21299279e-01 -6.66318536e-01 -6.80250704e-01 7.91804552e-01
1.25138271e+00 1.66526794e-01 4.13453251e-01 -1.19858325e+00
-3.39547962e-01 3.24089736e-01 -7.18154132e-01 -2.52484918e-01
7.51442552e-01 -6.90703318e-02 8.87330472e-01 -1.18350053e+00
5.74232042e-01 1.54121161e+00 1.14575744e+00 5.13675094e-01
-9.54731524e-01 -7.37121046e-01 7.72552714e-02 1.42339841e-01
-1.67080975e+00 -3.13748002e-01 6.51578128e-01 -2.38029271e-01
9.45220172e-01 9.89785604e-03 9.15860772e-01 1.18715060e+00
3.29766512e-01 1.11113214e+00 5.99224865e-01 -3.73304814e-01
-1.78891391e-01 -5.20347536e-01 -1.53273895e-01 1.03687513e+00
4.10025477e-01 6.89561618e-03 -8.77098083e-01 -7.61397257e-02
1.07360697e+00 -3.02003194e-02 1.58621728e-01 -3.60777438e-01
-1.33060884e+00 4.71221000e-01 6.69057667e-01 -2.97089070e-01
-5.54745734e-01 8.12067747e-01 5.24991930e-01 -8.46897513e-02
3.35267246e-01 5.31602837e-03 -3.99289012e-01 -3.74756157e-01
-8.65758002e-01 9.44569230e-01 6.60514295e-01 1.17291129e+00
8.06129053e-02 -2.44980142e-01 -3.24312061e-01 8.06591630e-01
4.74175960e-01 7.10298777e-01 2.26953272e-02 -1.03127825e+00
7.10277498e-01 4.11770433e-01 2.07504079e-01 -1.10923946e+00
-6.14150465e-01 -6.16186202e-01 -7.92686164e-01 2.73720119e-02
4.30898398e-01 -3.17528635e-01 -8.11263025e-01 1.77844691e+00
6.24526322e-01 8.36089812e-03 -3.05957377e-01 1.32529891e+00
9.24003780e-01 2.56783754e-01 -6.59973621e-02 3.79129142e-01
1.61123335e+00 -1.37873995e+00 -7.98913360e-01 -3.57123643e-01
1.84097424e-01 -7.10013986e-01 7.12840855e-01 4.36162561e-01
-1.39205754e+00 -1.05449855e+00 -1.02652371e+00 -6.02763236e-01
-3.75307761e-02 7.25544274e-01 7.64932811e-01 3.46608192e-01
-7.37781227e-01 5.93648672e-01 -1.13121557e+00 -1.63436741e-01
2.03137115e-01 5.75402498e-01 -4.28638488e-01 3.55518349e-02
-1.13502657e+00 9.24234331e-01 2.25875109e-01 4.83993888e-01
-6.71060205e-01 -5.49158454e-01 -9.61921096e-01 -2.09352344e-01
5.87812185e-01 -1.19266498e+00 1.51827312e+00 -1.94275096e-01
-1.75308549e+00 4.93269354e-01 -3.74451488e-01 -3.83414567e-01
1.11243033e+00 -1.36619580e+00 -2.17045173e-01 1.64952204e-01
3.34146678e-01 9.22549009e-01 6.05715036e-01 -9.07364130e-01
-7.15185523e-01 -5.07161796e-01 -2.27028579e-01 4.09292668e-01
7.28143677e-02 4.15667966e-02 -1.39296937e+00 -8.40414882e-01
8.94748196e-02 -1.25717092e+00 -2.38869414e-01 4.32559818e-01
-7.63191223e-01 -3.20220649e-01 1.81115374e-01 -1.02267730e+00
1.07071543e+00 -1.62402654e+00 3.80029321e-01 2.49715790e-01
2.89359450e-01 9.17931572e-02 2.38162979e-01 4.33525354e-01
2.34193116e-01 -6.13687813e-01 1.00698017e-01 -8.74311745e-01
3.60139191e-01 -1.09418429e-01 1.17445014e-01 7.43290722e-01
-1.44541308e-01 1.09036887e+00 -6.47808254e-01 -6.53771520e-01
2.94789135e-01 8.88558209e-01 -7.72262216e-01 2.46581271e-01
2.95903459e-02 2.71896094e-01 -2.58682132e-01 7.42518604e-01
4.88161862e-01 -1.85348839e-01 8.96388441e-02 -5.01962304e-01
5.84613606e-02 3.17280918e-01 -1.41821682e+00 2.29593062e+00
-2.22503603e-01 4.97186899e-01 -2.34591782e-01 -3.23249042e-01
7.91627944e-01 2.63537228e-01 3.55222613e-01 -4.92653847e-01
3.40942025e-01 1.07854947e-01 -3.29052657e-01 -2.04597518e-01
6.98907018e-01 4.12149131e-01 -3.51473778e-01 3.34543698e-02
2.48187775e-04 3.67707223e-01 1.51809305e-01 -1.27186719e-02
6.70790613e-01 8.68504345e-01 1.59892648e-01 5.94518818e-02
4.54844505e-01 -2.09016651e-01 6.76706135e-01 5.36623895e-01
-1.58566073e-01 7.85905004e-01 6.25008941e-02 -5.54735541e-01
-1.06814790e+00 -1.23771143e+00 1.64336935e-01 1.18775892e+00
2.76762247e-01 -8.10606062e-01 -8.66636515e-01 -2.73732275e-01
3.40370595e-01 1.24750175e-01 -5.41211307e-01 9.40614343e-02
-9.71189797e-01 -3.58749092e-01 9.62726891e-01 1.16305375e+00
9.72801030e-01 -5.69281340e-01 -5.85073292e-01 2.22584382e-01
-5.46963036e-01 -1.43988860e+00 -7.12285757e-01 -4.54712480e-01
-6.34060383e-01 -9.75169301e-01 -9.48668242e-01 -7.78058171e-01
6.68881297e-01 -1.17768936e-01 1.08292341e+00 -2.33574733e-01
-3.61143500e-01 8.37874636e-02 -3.94086614e-02 -3.34183723e-01
2.06798285e-01 2.91818351e-01 4.16896969e-01 -3.69894058e-01
4.03471142e-01 -3.75174552e-01 -9.31686759e-01 2.83980668e-01
6.21767109e-03 2.03773960e-01 8.35760176e-01 6.69039965e-01
8.14664006e-01 -4.14189994e-01 2.26425365e-01 -4.07319993e-01
4.02441621e-01 2.95712054e-01 -4.72536772e-01 6.14161305e-02
-3.60865951e-01 1.13978617e-01 4.05103087e-01 -7.39570409e-02
-9.77124155e-01 5.40332139e-01 -5.87037027e-01 -3.36807400e-01
-3.22879329e-02 1.42428756e-01 -9.22191069e-02 -7.28017986e-02
5.04325509e-01 7.04074949e-02 2.09303021e-01 -8.41331959e-01
5.86017013e-01 5.53722322e-01 1.23572969e+00 -6.08309150e-01
9.52487707e-01 4.04544830e-01 1.36611030e-01 -5.40532351e-01
-7.37333298e-01 -5.60566127e-01 -9.41365182e-01 -3.45560044e-01
9.70201492e-01 -1.55260849e+00 -1.28332233e+00 6.75554216e-01
-1.29824734e+00 4.34875190e-02 2.56447911e-01 6.11070275e-01
-6.55646980e-01 3.05406690e-01 -8.59170377e-01 -6.86819673e-01
-8.81060660e-01 -1.00628698e+00 1.50820935e+00 1.24238007e-01
-4.33790922e-01 -5.38273215e-01 7.76399225e-02 5.87463379e-01
3.95597294e-02 4.90761727e-01 9.77543518e-02 -1.88798308e-01
-4.03614432e-01 -5.78815103e-01 -4.03322726e-02 3.73405442e-02
-3.16361785e-01 -2.65872598e-01 -6.85910165e-01 -4.83079135e-01
-7.54671276e-01 -3.86504859e-01 6.57601774e-01 3.89085174e-01
9.93117988e-01 -1.40459359e-01 -4.57623988e-01 6.81876063e-01
1.04205191e+00 -4.10072714e-01 5.76734722e-01 4.29630429e-01
1.09868574e+00 3.73076618e-01 7.09496319e-01 4.91346449e-01
9.02494669e-01 1.23151934e+00 1.50736272e-01 -2.75951594e-01
-2.70504862e-01 -5.73978841e-01 4.33902174e-01 7.40779579e-01
-6.68020427e-01 2.58735359e-01 -6.32829309e-01 2.91081548e-01
-2.16288304e+00 -9.26029265e-01 -3.96557860e-02 1.95628881e+00
8.89172792e-01 2.62723416e-01 6.73059165e-01 2.91075371e-02
6.93657935e-01 2.78221797e-02 -4.83537376e-01 6.95139691e-02
3.46107632e-01 1.73485190e-01 6.36436403e-01 3.89109164e-01
-1.38614380e+00 1.06082726e+00 6.47439432e+00 6.44463301e-01
-5.43154955e-01 -5.74946962e-02 1.78814262e-01 -4.43362653e-01
5.97327173e-01 -6.94853008e-01 -1.19675505e+00 2.00912774e-01
5.78818202e-01 2.93282270e-01 2.88258106e-01 1.32891393e+00
3.53704579e-02 1.73170552e-01 -1.19177663e+00 1.32331610e+00
1.72402531e-01 -1.14154398e+00 -1.45980060e-01 -1.52893215e-01
3.17301661e-01 -7.18365833e-02 -1.95297733e-01 2.57940263e-01
1.92580983e-01 -7.33753204e-01 1.13941967e+00 5.96196592e-01
8.86189342e-01 -1.24238575e+00 7.89631069e-01 1.76509842e-01
-1.64881682e+00 1.16423085e-01 -3.28007460e-01 -1.62545353e-01
4.46565092e-01 2.57367671e-01 -4.33248132e-01 7.35511422e-01
8.50247502e-01 5.91902018e-01 -6.51685655e-01 9.94773328e-01
-5.70068181e-01 8.57084841e-02 -3.43659550e-01 -1.54319778e-01
-9.38646421e-02 2.08744124e-01 4.43349153e-01 1.32496953e+00
9.23695788e-02 -1.44150019e-01 4.90929246e-01 4.47953105e-01
-8.69575217e-02 -2.42505729e-01 -1.12604849e-01 4.46502447e-01
6.48632586e-01 1.04189312e+00 -3.55838239e-01 -4.26062226e-01
-2.32231066e-01 1.38039792e+00 4.36168313e-01 -2.14535967e-02
-1.25887036e+00 -6.86095893e-01 8.82743835e-01 1.45206777e-02
4.61004645e-01 -4.41000342e-01 -1.75695300e-01 -9.79326189e-01
3.60022187e-01 -8.78254414e-01 1.82255059e-01 -5.66981196e-01
-1.15350783e+00 5.12264192e-01 8.24834630e-02 -1.21848047e+00
-5.91734648e-01 -7.46867955e-01 -8.72929469e-02 5.66072762e-01
-1.01891851e+00 -1.49594879e+00 -5.73673189e-01 6.22064054e-01
2.80750573e-01 1.24993231e-02 7.49399900e-01 5.84738314e-01
-6.52095497e-01 1.21131933e+00 -2.32645631e-01 6.59594357e-01
7.70042121e-01 -1.26713932e+00 1.06976867e+00 9.49936509e-01
-6.51869178e-02 8.21361721e-01 7.57785618e-01 -7.63345242e-01
-1.79135299e+00 -1.12206089e+00 1.04340899e+00 -4.98588026e-01
7.65063167e-02 -6.96055055e-01 -1.62735060e-01 7.72083104e-01
-8.55732933e-02 -4.41393368e-02 4.54290688e-01 3.29809576e-01
-3.71497124e-01 -2.34560162e-01 -8.77503335e-01 9.28573251e-01
1.49869573e+00 -3.67760777e-01 -8.58900368e-01 3.52722615e-01
7.92934418e-01 -1.19830906e+00 -9.66897130e-01 3.20285082e-01
1.16773093e+00 -7.20156252e-01 1.58897030e+00 -3.30270618e-01
3.82331133e-01 -3.91731083e-01 -1.03379875e-01 -8.94687831e-01
-6.55678391e-01 -7.78706968e-01 -6.99883878e-01 7.28494108e-01
1.49859518e-01 -3.07460755e-01 8.49728465e-01 5.07626772e-01
-8.60818326e-02 -9.66452837e-01 -9.65300739e-01 -7.33139336e-01
-3.81154776e-01 -4.43431944e-01 5.41846812e-01 2.37115026e-01
-3.28359604e-01 4.83872145e-01 -9.19873953e-01 2.88058877e-01
1.02471864e+00 -5.40531352e-02 1.40842426e+00 -1.05021155e+00
-5.25440514e-01 -7.35336989e-02 -5.73617101e-01 -1.59505701e+00
-1.52273953e-01 -4.27121878e-01 2.12800324e-01 -1.73532963e+00
6.32071868e-02 7.70486519e-02 1.32372782e-01 4.31499332e-01
-3.99648279e-01 6.88038468e-01 3.76826286e-01 9.67690274e-02
-8.30801308e-01 7.42991805e-01 1.27642500e+00 1.61978737e-01
-8.58515427e-02 7.37723485e-02 -4.32593703e-01 8.50986004e-01
4.01178628e-01 -2.05889896e-01 2.03513671e-02 -5.19357502e-01
8.34655166e-02 -2.09254608e-01 6.20039463e-01 -1.58643460e+00
3.97751719e-01 5.09338439e-01 1.05596292e+00 -1.23519254e+00
9.47952509e-01 -4.96852875e-01 1.29204661e-01 7.78334975e-01
-2.29642063e-01 5.29959500e-01 -2.72688153e-03 6.05506063e-01
7.39391446e-02 4.33021933e-01 4.72608715e-01 4.54117097e-02
-7.04834819e-01 4.05517459e-01 1.09656259e-01 2.48024217e-03
8.04450214e-01 -9.80950147e-02 -6.35455176e-02 -3.95750880e-01
-6.33810878e-01 2.75714248e-01 1.10696964e-01 5.21714866e-01
5.83355844e-01 -1.76831055e+00 -7.40609884e-01 -8.28301013e-02
-7.93645456e-02 2.23499373e-01 5.60469776e-02 7.42765725e-01
-9.05020595e-01 5.38901806e-01 -1.91275552e-01 -6.05847955e-01
-1.34468722e+00 1.14692800e-01 2.38156408e-01 -2.39830852e-01
-9.74863887e-01 1.01839054e+00 -4.88805324e-01 -6.25361145e-01
6.17898226e-01 -7.96993896e-02 1.02270149e-01 -2.44458020e-01
7.47582912e-01 8.42725217e-01 -9.11060348e-02 -7.97708690e-01
-6.95268869e-01 8.42510700e-01 -7.76285455e-02 -2.31593207e-01
1.18944263e+00 9.43843424e-02 1.83711588e-01 1.50371626e-01
1.08148015e+00 -4.50576395e-02 -1.43858266e+00 -2.07564399e-01
-4.04384792e-01 -5.06407797e-01 -1.46319106e-01 -8.66233528e-01
-9.27194774e-01 6.11433923e-01 5.92168152e-01 -5.71665287e-01
8.03607762e-01 -2.29061425e-01 1.19809949e+00 7.02642739e-01
5.64337790e-01 -1.38690853e+00 1.68037713e-01 5.45713544e-01
1.00715530e+00 -9.75021422e-01 4.18109328e-01 -5.79441726e-01
-4.98922318e-01 9.94106531e-01 8.66501331e-01 -4.29938197e-01
3.78813565e-01 2.60844082e-01 -1.98329445e-02 -1.68836266e-01
-4.04469520e-01 -1.51075929e-01 7.25724995e-01 4.54583853e-01
6.48350239e-01 1.16392106e-01 -2.72871435e-01 7.14708030e-01
-7.34159529e-01 1.29504904e-01 -3.17365110e-01 1.02920794e+00
-1.77760422e-01 -8.80387425e-01 -5.21590412e-01 2.61204615e-02
-5.53144217e-01 8.96535888e-02 -2.85462916e-01 1.10179293e+00
4.89611775e-02 6.80040717e-01 -7.92840403e-03 -7.11231232e-01
7.16926754e-01 3.58999185e-02 8.13799798e-01 -9.03732702e-02
-6.19014561e-01 2.22277299e-01 4.02880490e-01 -1.01255250e+00
-2.21015647e-01 -6.58850849e-01 -1.36208236e+00 -6.29278541e-01
-2.98825353e-01 -2.26198077e-01 5.79897285e-01 8.34363997e-01
7.14108288e-01 7.36085296e-01 7.76640251e-02 -1.37662899e+00
-6.25191510e-01 -1.11165309e+00 -3.23792696e-02 2.99450576e-01
6.67811409e-02 -1.04610455e+00 4.48478997e-01 -1.14939362e-01] | [7.1260480880737305, -0.7069253921508789] |
60ed4492-22eb-409b-9968-795b8cce028e | scene-text-recognition-with-semantics | 2210.10836 | null | https://arxiv.org/abs/2210.10836v1 | https://arxiv.org/pdf/2210.10836v1.pdf | Scene Text Recognition with Semantics | Scene Text Recognition (STR) models have achieved high performance in recent years on benchmark datasets where text images are presented with minimal noise. Traditional STR recognition pipelines take a cropped image as sole input and attempt to identify the characters present. This infrastructure can fail in instances where the input image is noisy or the text is partially obscured. This paper proposes using semantic information from the greater scene to contextualise predictions. We generate semantic vectors using object tags and fuse this information into a transformer-based architecture. The results demonstrate that our multimodal approach yields higher performance than traditional benchmark models, particularly on noisy instances. | ['Lucia Specia', 'Zixu Wang', 'Yishu Miao', 'Joshua Cesare Placidi'] | 2022-10-19 | null | null | null | null | ['scene-text-recognition'] | ['computer-vision'] | [ 9.31761503e-01 -2.47060269e-01 1.16228580e-01 -6.81138098e-01
-9.84214902e-01 -9.17349517e-01 1.06052637e+00 1.68020651e-01
-3.27552408e-01 2.50713170e-01 4.75564539e-01 -2.15770066e-01
2.16878146e-01 -3.63919735e-01 -7.29067802e-01 -4.13905501e-01
7.58706987e-01 6.53717875e-01 5.04433751e-01 -1.43586829e-01
5.87850928e-01 2.54940182e-01 -1.52945721e+00 1.21476698e+00
2.58000612e-01 9.52189088e-01 2.71340549e-01 8.54585528e-01
-6.44184828e-01 9.92359877e-01 -8.06668162e-01 -4.92580414e-01
8.22207779e-02 -1.33478820e-01 -1.00174809e+00 5.09670556e-01
8.48361671e-01 -1.92055210e-01 -4.37216640e-01 9.08862174e-01
2.88764928e-02 -9.50578973e-02 4.05494928e-01 -1.26398635e+00
-5.09024680e-01 6.77934408e-01 -3.33817899e-01 -2.33445913e-02
7.71956503e-01 1.56996489e-01 1.10787678e+00 -1.19955873e+00
8.96123409e-01 1.57305384e+00 6.15197122e-01 2.14099064e-01
-1.61987734e+00 -2.76471734e-01 2.95499682e-01 2.95102715e-01
-1.22060812e+00 -3.94531697e-01 5.75196743e-01 -3.19068104e-01
1.25664890e+00 4.05917674e-01 1.53006151e-01 1.65131426e+00
1.46493927e-01 1.22881734e+00 9.00982201e-01 -5.65381885e-01
7.15144649e-02 1.27068251e-01 2.14885414e-01 4.02798444e-01
1.00703694e-01 -2.84206897e-01 -1.01231050e+00 1.15645632e-01
8.20837244e-02 1.23949051e-01 1.87928081e-01 -2.98120201e-01
-1.61067903e+00 6.11578405e-01 1.87671840e-01 1.64807111e-01
-1.05756775e-01 1.68197632e-01 5.44896901e-01 3.17836046e-01
2.07638398e-01 4.23858941e-01 -1.95374414e-01 -2.12703899e-01
-1.25741005e+00 1.49679869e-01 6.79087102e-01 9.71631110e-01
6.37313843e-01 -6.51832223e-02 -3.73694330e-01 8.87967229e-01
2.47310370e-01 6.46503150e-01 4.42835689e-01 -6.58312619e-01
7.56273568e-01 9.02032495e-01 6.21869713e-02 -8.49924803e-01
-1.51621193e-01 3.99209298e-02 -1.19451225e-01 1.88471731e-02
3.14154983e-01 3.37250888e-01 -1.55163455e+00 9.08114672e-01
-1.23716809e-01 -1.50500953e-01 2.81440914e-01 9.77593482e-01
9.41391468e-01 5.14123797e-01 3.77781093e-01 5.61125636e-01
1.18112528e+00 -8.03016067e-01 -7.88276672e-01 -6.13747001e-01
6.14166737e-01 -1.25604105e+00 1.03846836e+00 5.01283109e-01
-6.84643328e-01 -2.53652930e-01 -1.05939174e+00 -2.46280640e-01
-7.76743412e-01 2.39820391e-01 2.61533201e-01 7.11115003e-01
-1.15146780e+00 3.14210743e-01 -6.84893489e-01 -8.65987420e-01
4.70829308e-01 2.47762561e-01 -6.80335462e-01 -4.65488434e-01
-5.83494067e-01 9.51875925e-01 5.51042438e-01 4.63218912e-02
-8.24876130e-01 -2.71635801e-01 -9.32965755e-01 -1.40944347e-01
4.08193529e-01 -2.87597507e-01 1.31366563e+00 -1.19477260e+00
-1.07501304e+00 7.73857415e-01 -3.76676708e-01 -4.17805761e-01
5.24592519e-01 -2.48840690e-01 -3.61612052e-01 4.59458679e-01
6.41466975e-02 9.40243542e-01 1.01111579e+00 -1.35722244e+00
-7.79606402e-01 -3.96681190e-01 -2.60319114e-01 4.24117684e-01
-1.18799068e-01 3.77295762e-01 -5.80199957e-01 -5.84843874e-01
4.69555587e-01 -5.72039545e-01 6.71763793e-02 -2.22134009e-01
-6.72029197e-01 -7.85900429e-02 1.46710193e+00 -5.15173674e-01
5.91735303e-01 -2.07156253e+00 -6.07846379e-02 2.36007228e-01
2.65870336e-02 1.08342387e-01 -3.21238369e-01 7.56585181e-01
9.39350724e-02 1.76154584e-01 1.90522298e-02 -4.79422241e-01
2.14354262e-01 4.31879908e-01 -7.65958190e-01 5.44306450e-02
5.63745618e-01 1.05980682e+00 -6.02231264e-01 -6.78202271e-01
5.83407521e-01 4.77016568e-01 -1.96385160e-01 2.29050387e-02
-4.44653034e-01 -1.62958294e-01 -3.50279897e-01 8.80295575e-01
5.07747233e-01 -2.85167456e-01 1.74147710e-01 -2.90986806e-01
8.78296793e-02 1.91233128e-01 -1.16680753e+00 1.63812208e+00
7.66020492e-02 1.18040371e+00 -2.79403299e-01 -1.01113474e+00
1.07949126e+00 -1.45197113e-03 1.96772933e-01 -8.72622490e-01
-3.98209840e-02 -6.02543801e-02 -4.76178199e-01 -4.89493459e-01
9.48248446e-01 -3.19095911e-04 -1.32581517e-01 2.40097478e-01
8.66140202e-02 -3.20353746e-01 3.94592322e-02 5.96497118e-01
1.41732454e+00 3.66158605e-01 -3.98708105e-01 1.48562431e-01
1.72427282e-01 7.20401466e-01 5.08406833e-02 9.53118443e-01
1.27503835e-02 1.00387859e+00 5.81874847e-01 -5.67870021e-01
-1.26989794e+00 -1.15895176e+00 -4.52049151e-02 1.26954567e+00
2.97285676e-01 -6.68005586e-01 -6.52662694e-01 -7.07833111e-01
1.19261788e-02 7.89392233e-01 -5.89202106e-01 2.37680618e-02
-2.22674906e-01 -4.21364516e-01 7.98655033e-01 7.51288474e-01
2.83727735e-01 -9.27984416e-01 -6.17608130e-01 1.89196244e-02
-2.92438895e-01 -1.48941338e+00 -1.59944817e-01 4.17430788e-01
-5.98411977e-01 -8.79750609e-01 -3.13156933e-01 -7.39704430e-01
6.58199728e-01 3.24962318e-01 9.44280803e-01 -5.09963967e-02
-5.36187470e-01 7.89086878e-01 -5.34480929e-01 -2.99385220e-01
-1.86275452e-01 -3.09534639e-01 -4.04169142e-01 2.25735530e-01
8.31885397e-01 3.87866050e-01 -2.09307715e-01 4.66765702e-01
-1.01678038e+00 3.98966879e-01 4.44418192e-01 9.90447879e-01
4.54839289e-01 -1.07832626e-01 2.72003165e-03 -7.59547651e-01
3.38714719e-01 -2.79153109e-01 -2.91117698e-01 3.85752946e-01
-2.34778926e-01 -9.61429533e-03 3.32917064e-01 -3.82876635e-01
-1.26191115e+00 5.13095438e-01 3.48959625e-01 -4.41736758e-01
-5.88412285e-01 3.95954072e-01 5.49747199e-02 6.74301535e-02
6.81133986e-01 4.55847204e-01 -1.92212209e-01 -4.61394459e-01
5.08353971e-02 9.52627957e-01 6.40838504e-01 -6.38117075e-01
5.24187505e-01 6.70436740e-01 -1.87781230e-01 -9.13311839e-01
-8.79670680e-01 -5.95408857e-01 -8.50423753e-01 -2.86233693e-01
6.11032069e-01 -9.46069837e-01 -3.67813498e-01 2.45292217e-01
-1.01624644e+00 -2.53475100e-01 -4.48209792e-02 3.65145087e-01
-4.71618891e-01 3.31661910e-01 -3.60751092e-01 -8.20088863e-01
3.47627397e-03 -1.24647439e+00 1.61507440e+00 7.35417530e-02
-2.24515930e-01 -7.84017324e-01 -4.77199167e-01 6.44240975e-01
3.05422544e-01 9.69739445e-03 6.55986726e-01 -1.02061462e+00
-7.80661821e-01 -2.80863643e-01 -5.77677131e-01 -1.37073711e-01
-2.00592726e-01 2.15476111e-01 -1.16168404e+00 -2.38923468e-02
-6.11490548e-01 -5.48821330e-01 9.38107133e-01 -2.92209405e-02
9.13316667e-01 8.15297440e-02 -5.08569837e-01 3.37856472e-01
1.48373628e+00 5.54867573e-02 6.11124158e-01 4.69667166e-01
7.46549308e-01 6.82788312e-01 7.19767690e-01 2.14183956e-01
2.63711393e-01 6.08568847e-01 4.18675750e-01 -1.35709355e-02
-2.01194182e-01 -5.22524655e-01 4.50506896e-01 6.15646020e-02
6.57528877e-01 -7.09174871e-01 -1.44143271e+00 6.32381260e-01
-2.05421352e+00 -8.99571538e-01 -2.41512403e-01 1.76508832e+00
4.34829414e-01 2.04127356e-01 -2.80781299e-01 9.94614363e-02
7.14049041e-01 -5.09997308e-02 -4.27135110e-01 -4.82180566e-01
-6.34349346e-01 -1.30765243e-02 5.58511555e-01 3.33931029e-01
-1.15871692e+00 1.41829169e+00 7.69318008e+00 5.71321428e-01
-1.12297893e+00 -1.81098118e-01 4.81155246e-01 -1.84828460e-01
-4.07776296e-01 1.83887914e-01 -8.89529347e-01 2.48923227e-01
1.02116573e+00 1.73764780e-01 1.79181308e-01 6.37277722e-01
8.30783248e-02 -4.21969682e-01 -1.31716990e+00 1.13066566e+00
6.43774986e-01 -1.41228473e+00 4.89290237e-01 -2.28475511e-01
2.82042414e-01 3.08126599e-01 1.76485121e-01 3.75651270e-02
6.45257235e-01 -1.39534175e+00 1.01702797e+00 6.39166892e-01
6.98410630e-01 -4.38249111e-01 7.27897644e-01 2.91558746e-02
-9.34084892e-01 1.53852077e-02 -4.09901947e-01 1.75730780e-01
-1.33940801e-01 2.91724987e-02 -1.41926324e+00 2.81884044e-01
9.48365748e-01 8.16278696e-01 -1.15681088e+00 1.03062189e+00
2.63028890e-02 6.64821506e-01 -5.28920293e-01 -2.13019669e-01
5.21142662e-01 2.11837962e-01 5.04976869e-01 1.71775496e+00
2.03886211e-01 -1.79173648e-01 4.66145307e-01 6.53869271e-01
1.12583280e-01 1.81595385e-01 -8.84310842e-01 -1.27153501e-01
1.79859936e-01 1.10054719e+00 -1.00359321e+00 -4.29024249e-01
-5.16691387e-01 1.20853162e+00 1.49413077e-02 4.75517809e-01
-4.23041672e-01 -3.72855008e-01 3.62232924e-01 -1.09314859e-01
4.53479081e-01 -1.61291048e-01 -6.04009807e-01 -1.15972471e+00
7.65379593e-02 -7.72577763e-01 6.34682059e-01 -1.47685206e+00
-9.84756112e-01 3.71127397e-01 -1.41117066e-01 -9.31732893e-01
5.36732897e-02 -9.65575576e-01 -2.97106862e-01 6.61703289e-01
-1.10612047e+00 -1.68432522e+00 -2.80349553e-01 6.56826556e-01
1.01597357e+00 -3.02189112e-01 7.11596012e-01 -2.30438083e-01
-4.18624252e-01 4.25819963e-01 2.57347882e-01 3.49733591e-01
8.60289097e-01 -1.36368775e+00 2.83339322e-01 1.06919289e+00
6.33663356e-01 4.34304416e-01 8.83375883e-01 -9.26879287e-01
-1.84116149e+00 -9.62512136e-01 9.07910228e-01 -1.08344948e+00
7.37406015e-01 -6.43969059e-01 -8.66462469e-01 8.24140668e-01
4.35390681e-01 -5.38032129e-02 6.09365106e-01 4.12153564e-02
-9.11881268e-01 1.86919838e-01 -1.04748738e+00 6.72890067e-01
6.77411199e-01 -7.62305439e-01 -8.33379626e-01 4.12804842e-01
3.76846880e-01 -4.30420607e-01 -6.34682834e-01 3.01011410e-02
5.16699553e-01 -6.01182282e-01 7.68436909e-01 -8.06391835e-01
4.08048213e-01 -5.20672143e-01 -6.28167570e-01 -9.53849673e-01
2.36341283e-02 -3.07833433e-01 4.83825505e-01 1.04894161e+00
5.83112776e-01 -6.44235313e-02 8.56067479e-01 8.32813144e-01
-2.74204426e-02 2.35891685e-01 -8.55549932e-01 -5.16414464e-01
-2.79999286e-01 -8.62477958e-01 4.00823742e-01 8.65763307e-01
3.15932989e-01 4.54689175e-01 -1.61915630e-01 7.27721900e-02
5.41009724e-01 -9.51409806e-03 6.59871697e-01 -1.02507472e+00
3.74844313e-01 -3.75003010e-01 -8.73358428e-01 -7.07671106e-01
1.05397515e-01 -8.33840132e-01 2.77009159e-01 -1.59426522e+00
4.88157302e-01 -5.11837490e-02 -2.58052945e-01 9.72073317e-01
1.58072203e-01 5.03618181e-01 3.30266923e-01 1.74170211e-01
-1.12866890e+00 1.85844705e-01 6.56054556e-01 -4.54110622e-01
1.97105125e-01 -6.91015303e-01 -5.33606350e-01 4.95249510e-01
7.06322908e-01 -2.39054665e-01 -1.44255877e-01 -7.54322588e-01
1.87469572e-01 -2.67219514e-01 6.41918719e-01 -9.11692858e-01
5.53484917e-01 -2.04793245e-01 9.97456133e-01 -1.04309809e+00
5.26049256e-01 -1.08044708e+00 1.02435172e-01 3.51297185e-02
-7.44194031e-01 2.38177320e-03 3.69959474e-01 7.26559103e-01
-2.91388214e-01 -5.77394441e-02 5.10503531e-01 7.25626275e-02
-1.01189852e+00 -2.77500898e-01 -6.51638865e-01 -3.40656281e-01
7.73934186e-01 -7.03748405e-01 -8.44899058e-01 -2.90261805e-01
-5.68406343e-01 1.85213238e-01 7.42121458e-01 8.60503912e-01
9.36257958e-01 -1.03912210e+00 -6.00109935e-01 2.72831261e-01
5.88371873e-01 -4.43307281e-01 2.65499074e-02 5.36652684e-01
-5.73326290e-01 6.40152335e-01 -2.02312842e-01 -1.19117188e+00
-1.56945503e+00 4.33994144e-01 2.14810461e-01 2.83517092e-01
-1.03224421e+00 5.22704780e-01 1.80441723e-03 -2.66412318e-01
3.62404883e-01 -8.69869515e-02 -1.28658623e-01 6.58794641e-02
6.16046727e-01 -1.00879021e-01 2.45779604e-01 -9.64607000e-01
-4.13802296e-01 3.86038065e-01 -4.16152686e-01 -4.15531605e-01
1.26641154e+00 -2.82945424e-01 1.88541561e-01 4.97218639e-01
9.04870331e-01 -4.43113148e-01 -1.14744484e+00 -6.59710348e-01
4.49763387e-01 -7.13888705e-01 2.88572282e-01 -1.13673568e+00
-5.14226794e-01 9.45739746e-01 6.05063081e-01 -3.98966037e-02
8.38867545e-01 1.89494759e-01 3.59111190e-01 7.98192501e-01
1.10043965e-01 -1.51330411e+00 2.35906035e-01 7.03343332e-01
6.31058514e-01 -1.42756104e+00 -1.59614623e-01 -1.54178470e-01
-1.07557201e+00 1.41533267e+00 5.72205484e-01 3.46274227e-01
8.79371837e-02 4.30603594e-01 2.60496616e-01 -2.30923548e-01
-1.15148652e+00 -3.60986471e-01 2.43393853e-01 6.79896593e-01
3.00383717e-01 2.76579317e-02 4.41001952e-01 2.03673512e-01
-6.33420497e-02 -4.08958018e-01 6.10111773e-01 1.16046619e+00
-6.69491768e-01 -1.03990340e+00 -8.19074333e-01 6.29150867e-01
-6.12515330e-01 -2.12678343e-01 -1.09400213e+00 4.73612815e-01
-3.00437540e-01 1.12580073e+00 3.10499728e-01 -4.01564389e-01
3.51745814e-01 5.56103051e-01 2.19938055e-01 -6.47109985e-01
-6.78269863e-01 3.03222030e-01 2.43256435e-01 -7.36315608e-01
-2.81281084e-01 -9.07113254e-01 -1.08538294e+00 -7.87377730e-02
-5.81552312e-02 -1.36389226e-01 1.04447436e+00 9.90020275e-01
3.77559483e-01 2.69809097e-01 2.36964777e-01 -6.76686585e-01
-1.64562821e-01 -7.06650972e-01 -1.81652382e-01 6.47951484e-01
2.78545439e-01 -3.90999347e-01 -7.82221705e-02 6.35159612e-01] | [11.800008773803711, 2.203481912612915] |
9b2f53a4-d7de-434a-a756-99315d358701 | word-centrality-constrained-representation | null | null | https://aclanthology.org/2021.bionlp-1.17 | https://aclanthology.org/2021.bionlp-1.17.pdf | Word centrality constrained representation for keyphrase extraction | To keep pace with the increased generation and digitization of documents, automated methods that can improve search, discovery and mining of the vast body of literature are essential. Keyphrases provide a concise representation by identifying salient concepts in a document. Various supervised approaches model keyphrase extraction using local context to predict the label for each token and perform much better than the unsupervised counterparts. Unfortunately, this method fails for short documents where the context is unclear. Moreover, keyphrases, which are usually the gist of a document, need to be the central theme. We propose a new extraction model that introduces a centrality constraint to enrich the word representation of a Bidirectional long short-term memory. Performance evaluation on 2 publicly available datasets demonstrate our model outperforms existing state-of-the art approaches. | ['Joyce Ho', 'Zelalem Gero'] | null | null | null | null | naacl-bionlp-2021-6 | ['keyphrase-extraction'] | ['natural-language-processing'] | [-5.74488975e-02 -1.14332475e-01 -9.73788798e-01 1.56760558e-01
-6.74819291e-01 -6.80263460e-01 9.68391061e-01 9.09284294e-01
-6.44089758e-01 8.31759512e-01 8.26896548e-01 -2.76205599e-01
-2.56135732e-01 -8.48031938e-01 -3.30469966e-01 -3.04457396e-01
-4.74670567e-02 1.83908239e-01 3.22901130e-01 -1.03786692e-01
9.25248444e-01 3.61796319e-01 -1.27601087e+00 6.16825461e-01
5.94619632e-01 1.04670548e+00 4.95937645e-01 2.65461564e-01
-9.40218925e-01 9.11827505e-01 -5.17864943e-01 -2.81873941e-01
-1.86810911e-01 -9.27270278e-02 -1.16047263e+00 -3.13470989e-01
3.60240072e-01 4.12579067e-03 -4.44392174e-01 1.04740763e+00
6.01800941e-02 -7.44054792e-04 4.24466193e-01 -9.01160359e-01
-5.68371773e-01 1.05372083e+00 -9.19540405e-01 4.97565508e-01
4.30165440e-01 -9.48073089e-01 1.76364946e+00 -1.38936162e+00
9.67431843e-01 1.03672123e+00 4.74231094e-01 -1.18644901e-01
-7.72456169e-01 -6.52925909e-01 4.65693325e-01 3.57466310e-01
-1.69403720e+00 -1.15351945e-01 8.38600278e-01 -1.65896729e-01
1.09732223e+00 3.28252286e-01 6.45406902e-01 9.58280861e-01
1.12957306e-01 9.02000308e-01 7.98742473e-01 -6.46847010e-01
-1.36277378e-01 -4.15585702e-03 6.22762740e-01 6.23558164e-01
6.21280432e-01 -4.57788974e-01 -1.09479940e+00 -4.47720915e-01
2.07405463e-01 2.79225647e-01 -8.92727077e-02 7.61753041e-03
-1.39289725e+00 8.21624577e-01 -4.09135781e-03 5.94775319e-01
-5.96824229e-01 -4.45146346e-03 4.67872858e-01 -4.48343926e-04
5.33261716e-01 6.98059201e-01 -3.05496454e-01 -3.51426452e-01
-1.51499963e+00 4.41785395e-01 9.39377785e-01 9.89039660e-01
7.13977098e-01 -6.94134712e-01 -4.57867891e-01 7.50091255e-01
1.09506927e-01 1.41937211e-01 6.39729023e-01 -5.59271872e-01
6.14528418e-01 9.71177161e-01 7.09323809e-02 -1.38592982e+00
-3.56062621e-01 -8.02390039e-01 -7.36432076e-01 -6.56733096e-01
-6.24403879e-02 2.24987507e-01 -7.23665535e-01 1.20944560e+00
1.77059203e-01 1.17362253e-02 -2.68916488e-01 3.32650393e-01
8.60686123e-01 8.43988538e-01 -4.88485917e-02 -5.39045095e-01
1.54473877e+00 -9.31814432e-01 -1.12473893e+00 -2.70585954e-01
5.46203077e-01 -1.09685802e+00 8.37494254e-01 4.60370272e-01
-8.40550780e-01 -1.02904789e-01 -9.97106493e-01 -2.87855774e-01
-9.47680950e-01 8.78325254e-02 7.77279437e-01 2.73111850e-01
-5.38987517e-01 5.22326708e-01 -4.47890520e-01 -2.55916953e-01
3.84996951e-01 -2.16993481e-01 -1.17401004e-01 -6.65880665e-02
-1.24993491e+00 7.53790975e-01 7.10628986e-01 -3.13916564e-01
-2.12078452e-01 -8.34446490e-01 -4.39120501e-01 1.59708336e-01
8.98054719e-01 -3.73162925e-01 9.59821820e-01 -2.19178081e-01
-6.49366260e-01 8.15762341e-01 -4.47037041e-01 -4.23552513e-01
-6.01302125e-02 -5.11526942e-01 -5.00414670e-01 4.84053344e-01
4.35682774e-01 2.75633812e-01 7.42645144e-01 -1.07718384e+00
-1.02421176e+00 -1.97234303e-01 -1.20228313e-01 3.94413993e-03
-1.02822340e+00 3.34992945e-01 -8.08108687e-01 -1.18835223e+00
2.49139354e-01 -6.65583849e-01 1.74736660e-02 -4.52643245e-01
-7.20370531e-01 -5.41279972e-01 1.02943766e+00 -5.45210660e-01
2.21978951e+00 -1.97349298e+00 -8.79335329e-02 4.99265790e-01
5.63597143e-01 -8.28118250e-02 2.65872806e-01 1.03787458e+00
1.00597978e-01 5.46792924e-01 2.12228268e-01 -1.06242791e-01
-4.85577807e-02 1.37106612e-01 -9.99712169e-01 5.97895645e-02
-3.88066560e-01 8.53173673e-01 -1.10807216e+00 -9.57223475e-01
-4.20144320e-01 6.25553355e-02 -1.74277440e-01 -4.53478694e-02
-1.49223864e-01 -2.34878540e-01 -7.87575185e-01 7.75571764e-01
2.39142850e-01 -6.30499542e-01 2.76737753e-02 -4.54148620e-01
-4.03983444e-01 5.76620281e-01 -1.18108904e+00 1.51618671e+00
-2.30064824e-01 5.52753806e-01 -1.21173039e-01 -9.47860241e-01
6.28800690e-01 2.45731443e-01 7.85207808e-01 -3.92698258e-01
-1.13070153e-01 1.93995357e-01 -5.40076673e-01 -2.85321683e-01
1.18457532e+00 2.17559487e-01 -1.91457540e-01 6.02724135e-01
-1.04836777e-01 1.23129092e-01 7.06265628e-01 8.89689445e-01
9.29875374e-01 -4.10568148e-01 5.16442120e-01 -4.18579608e-01
3.50456297e-01 3.64135727e-02 3.45562339e-01 1.00572705e+00
4.37475264e-01 4.35458064e-01 3.94371092e-01 -2.67089903e-01
-7.67974913e-01 -5.86428642e-01 -4.24313471e-02 1.15418899e+00
8.98975506e-02 -1.42382503e+00 -4.39713418e-01 -7.36244142e-01
2.67434508e-01 5.02809823e-01 -6.31028712e-01 4.96388972e-03
-4.35061157e-01 -6.58857286e-01 5.16844273e-01 4.05513167e-01
2.00405806e-01 -6.17175162e-01 -4.75716680e-01 2.81182051e-01
-5.10494471e-01 -1.43696678e+00 -6.03563428e-01 2.26606786e-01
-6.80058420e-01 -9.79720235e-01 -7.03943372e-01 -7.20137417e-01
5.79375803e-01 5.40299475e-01 1.31280959e+00 3.65918785e-01
-2.72222012e-01 2.88609892e-01 -6.67357266e-01 -4.26256210e-01
1.84459552e-01 6.09846115e-01 -1.55548491e-02 -2.02481046e-01
5.10483563e-01 -4.91596192e-01 -5.79307199e-01 -1.53974637e-01
-9.37650621e-01 7.67943263e-02 6.18478596e-01 9.34125602e-01
6.99118733e-01 4.58850741e-01 5.32423496e-01 -9.37940419e-01
1.00935233e+00 -6.51098371e-01 -1.93526909e-01 4.41909224e-01
-1.34675395e+00 2.69110590e-01 3.18356484e-01 -4.24342841e-01
-9.37776148e-01 -3.57541978e-01 3.46063912e-01 2.38979906e-02
2.58179575e-01 1.28806353e+00 4.18498576e-01 3.73546958e-01
2.79034257e-01 3.07919294e-01 -7.12900937e-01 -8.73468339e-01
6.20619595e-01 7.48795986e-01 5.36637962e-01 -7.55515039e-01
7.59811580e-01 5.96252799e-01 1.47252321e-01 -1.02008653e+00
-1.29546010e+00 -1.14418817e+00 -4.77117032e-01 -1.27154469e-01
4.04099733e-01 -9.21792328e-01 -3.12684029e-01 -8.54407251e-02
-1.21642113e+00 5.11634707e-01 -1.76803946e-01 4.06403810e-01
1.75763473e-01 5.00902116e-01 -5.44577360e-01 -6.65552855e-01
-5.90268016e-01 -4.93455768e-01 9.64847744e-01 1.16188489e-01
-7.06167161e-01 -7.59536028e-01 8.42745006e-02 1.07301474e-01
1.53946534e-01 -1.30194083e-01 1.09129345e+00 -9.33464885e-01
-3.68617415e-01 -5.19932330e-01 -3.50340992e-01 -1.78214878e-01
4.06987071e-01 -6.36152625e-02 -5.27355492e-01 -9.26146358e-02
-4.14637774e-01 -1.94665819e-01 1.35962355e+00 -3.33266035e-02
1.55801511e+00 -8.50943267e-01 -9.24647927e-01 2.18705639e-01
1.09571791e+00 -6.71691447e-02 2.45913655e-01 5.99617541e-01
6.88982785e-01 5.77704728e-01 5.89323997e-01 6.81690216e-01
5.61987340e-01 3.57268065e-01 9.33197588e-02 8.13035741e-02
-9.95565671e-03 -6.58850014e-01 2.24991813e-02 1.12017119e+00
-8.62749666e-02 -8.20653439e-02 -1.01979518e+00 8.51736307e-01
-1.80209446e+00 -1.18177700e+00 -1.19880937e-01 1.79813290e+00
1.40825188e+00 5.70462227e-01 2.05903240e-02 3.17939073e-01
4.28881973e-01 4.71211076e-01 7.01611713e-02 6.57167137e-02
-3.03861201e-01 1.22569896e-01 6.78018332e-01 2.60758251e-01
-9.11645651e-01 1.09926462e+00 6.88577700e+00 1.11278915e+00
-9.20289516e-01 -1.62076727e-01 3.24771821e-01 -7.19030434e-03
-3.69125664e-01 1.35991126e-01 -1.30457354e+00 3.03567529e-01
6.72431290e-01 -6.39114261e-01 1.18460543e-02 7.56874442e-01
1.31379828e-01 -3.72379631e-01 -9.33537900e-01 1.07750440e+00
2.37386197e-01 -1.77092373e+00 3.90760869e-01 4.07613739e-02
7.65832841e-01 -1.84874132e-01 1.23141944e-01 -1.41605899e-01
2.07777679e-01 -8.00319970e-01 6.89148068e-01 6.50846660e-01
4.44026768e-01 -7.42148280e-01 5.21810710e-01 3.30182642e-01
-1.44939578e+00 -4.53807861e-02 -1.73264012e-01 -3.21885087e-02
-4.07135673e-02 1.00136948e+00 -5.77570379e-01 4.83834445e-01
8.45508635e-01 7.89794803e-01 -7.15172231e-01 9.00753915e-01
-2.72400618e-01 6.92473412e-01 -1.49582341e-01 -4.22262430e-01
4.89798158e-01 7.88911954e-02 5.58753490e-01 1.88545668e+00
3.17082167e-01 7.66112581e-02 3.42479855e-01 5.98842621e-01
-4.97830689e-01 4.60323542e-01 -5.60376942e-01 -7.02917159e-01
8.10980558e-01 1.45255923e+00 -1.26660442e+00 -6.53138638e-01
-4.94410247e-01 7.47058690e-01 1.27325714e-01 4.09795642e-01
-8.49250853e-02 -7.80132592e-01 4.50871199e-01 -2.30000704e-03
3.25004518e-01 -4.79449689e-01 -3.74446332e-01 -1.09113002e+00
2.00411469e-01 -7.36345947e-01 6.70644343e-01 -4.95347530e-01
-1.28031719e+00 2.91695863e-01 2.32300133e-01 -9.33853507e-01
-2.67216146e-01 -4.41409200e-01 -2.70490378e-01 5.79723597e-01
-1.63811576e+00 -1.15663433e+00 6.12841435e-02 3.51944029e-01
5.28270245e-01 -1.48386240e-01 8.53018463e-01 2.04903364e-01
-2.51405656e-01 2.50391543e-01 2.48620838e-01 2.85843968e-01
7.28079855e-01 -1.30469584e+00 2.19064891e-01 8.20394278e-01
6.48019850e-01 1.19816422e+00 6.98644221e-01 -9.21875358e-01
-1.49132347e+00 -7.44620025e-01 1.52528632e+00 -3.14067721e-01
1.10174036e+00 -3.26481730e-01 -8.52331877e-01 4.01685148e-01
3.61237794e-01 -1.56735733e-01 9.10619140e-01 4.86549050e-01
-7.34465241e-01 -1.65406570e-01 -4.25430596e-01 6.92697346e-01
9.83562708e-01 -8.38879704e-01 -1.12252295e+00 3.10057372e-01
7.23983586e-01 -1.01645023e-01 -6.82553947e-01 6.44579008e-02
6.71876907e-01 -2.66913742e-01 1.23130453e+00 -5.50183117e-01
4.51734364e-01 -1.41567230e-01 -5.20313568e-02 -1.04954779e+00
-2.66239196e-01 -8.20675492e-01 -8.27653766e-01 1.31370008e+00
4.72897917e-01 -1.59589097e-01 6.18204594e-01 1.96489573e-01
2.59329349e-01 -8.38743150e-01 -7.31082916e-01 -8.38795900e-01
-2.50657573e-02 -5.23936033e-01 5.50975621e-01 1.15806818e+00
7.56822169e-01 7.05630302e-01 -3.01698208e-01 -2.98952460e-01
6.25326991e-01 4.67913151e-01 2.50319123e-01 -1.55234945e+00
3.83089900e-01 -8.46217573e-01 6.29557818e-02 -1.19480979e+00
1.94339380e-01 -1.15490186e+00 -4.43061113e-01 -1.77078915e+00
6.38157606e-01 -1.65597200e-01 -5.67371428e-01 4.66428071e-01
-2.82345653e-01 6.98910281e-02 -1.35594711e-01 4.09465998e-01
-8.68565977e-01 2.95442104e-01 9.05156314e-01 -4.47716475e-01
-7.84591064e-02 -2.96188653e-01 -1.08754957e+00 8.59598279e-01
4.61944580e-01 -6.25895858e-01 -2.65420169e-01 -6.23460747e-02
1.01232946e+00 -4.24986750e-01 1.99818145e-02 -4.76365656e-01
8.61545920e-01 -4.91390407e-01 3.19133401e-01 -1.09818780e+00
3.38831171e-02 -8.58862996e-01 -3.88320982e-01 1.51352927e-01
-5.61571300e-01 3.83167267e-01 -3.98207344e-02 5.23491025e-01
-4.46085960e-01 -3.20433855e-01 1.47287801e-01 -2.68386811e-01
-6.56231225e-01 2.30961695e-01 -5.13300359e-01 2.37751320e-01
3.23698729e-01 1.81095719e-01 -2.34848112e-01 -2.92814761e-01
-1.89604059e-01 2.30339929e-01 -4.15836908e-02 6.98263526e-01
9.35373724e-01 -1.43971920e+00 -5.65497100e-01 -3.06548178e-01
3.94936711e-01 -2.29420483e-01 -4.93706703e-01 5.57451308e-01
-5.73973432e-02 8.28107655e-01 4.05680984e-01 1.39055654e-01
-1.30423009e+00 7.45648563e-01 -3.68770689e-01 -5.67318916e-01
-7.81956196e-01 6.53525114e-01 -1.67596057e-01 3.16258103e-01
4.54351097e-01 -6.30475461e-01 -6.41718864e-01 8.66217017e-01
1.05577564e+00 4.14574713e-01 1.33847415e-01 -5.94436467e-01
-3.48889977e-01 4.14530605e-01 -4.65078503e-01 -1.52140543e-01
1.39394796e+00 -4.83161688e-01 -7.09255457e-01 7.62162685e-01
1.14978731e+00 3.93310845e-01 -2.79753894e-01 -7.79341698e-01
9.47978914e-01 -4.75281239e-01 5.22557676e-01 -6.06434822e-01
-7.09380090e-01 4.81174648e-01 1.91393327e-02 5.97174108e-01
8.62178087e-01 1.95500210e-01 1.01809657e+00 8.27181637e-01
4.85820882e-02 -1.72385967e+00 2.38584146e-01 8.19098234e-01
8.12231302e-01 -9.13120449e-01 5.77242672e-01 -4.18948263e-01
-1.55585572e-01 1.40739024e+00 1.89736247e-01 4.65359151e-01
9.26890671e-01 3.87823462e-01 -2.21489787e-01 -5.25831342e-01
-7.00939417e-01 -2.01538607e-01 6.18169665e-01 -8.76486972e-02
5.94882071e-01 -2.66556114e-01 -7.15443134e-01 1.03304982e+00
-2.91832179e-01 -2.09215432e-01 2.42659807e-01 1.25750136e+00
-6.68469191e-01 -1.25214016e+00 -4.58589911e-01 6.16187692e-01
-1.15677130e+00 -5.30378044e-01 -6.62380219e-01 3.60304445e-01
-7.46959224e-02 9.87428963e-01 -1.51901230e-01 -2.96976238e-01
-1.59980338e-02 3.75063211e-01 2.55981809e-03 -7.49798954e-01
-3.82121444e-01 2.60542214e-01 2.03713819e-01 -4.67403293e-01
-5.01917839e-01 -4.56280529e-01 -1.34701204e+00 -2.65159994e-01
-3.71473551e-01 6.47946000e-01 6.56239688e-01 1.17217791e+00
4.28580135e-01 4.77912396e-01 4.63274658e-01 -2.83288836e-01
-2.46871233e-01 -9.70315695e-01 -6.09594524e-01 1.81369230e-01
5.06563663e-01 -6.34308279e-01 2.88927928e-02 3.58186334e-01] | [12.155657768249512, 8.88770580291748] |
e5130f28-3f75-4884-ac89-4d01a334507d | biomedical-event-extraction-as-multi-turn | null | null | https://aclanthology.org/2020.louhi-1.10 | https://aclanthology.org/2020.louhi-1.10.pdf | Biomedical Event Extraction as Multi-turn Question Answering | Biomedical event extraction from natural text is a challenging task as it searches for complex and often nested structures describing specific relationships between multiple molecular entities, such as genes, proteins, or cellular components. It usually is implemented by a complex pipeline of individual tools to solve the different relation extraction subtasks. We present an alternative approach where the detection of relationships between entities is described uniformly as questions, which are iteratively answered by a question answering (QA) system based on the domain-specific language model SciBERT. This model outperforms two strong baselines in two biomedical event extraction corpora in a Knowledge Base Population setting, and also achieves competitive performance in BioNLP challenge evaluation settings. | ['Ulf Leser', 'Leon Weber', 'Xing David Wang'] | null | null | null | null | emnlp-louhi-2020-11 | ['knowledge-base-population'] | ['natural-language-processing'] | [ 3.13651860e-01 5.30167460e-01 -1.34217858e-01 -2.35060483e-01
-1.34863698e+00 -6.90840423e-01 5.09802997e-01 1.12396395e+00
-6.54656410e-01 1.34394991e+00 2.38112584e-01 -3.80789578e-01
-2.39339486e-01 -6.21435404e-01 -8.40503752e-01 -4.77942079e-01
3.50831496e-03 1.05614138e+00 4.54094350e-01 -4.69060726e-02
-1.15173742e-01 3.84470999e-01 -7.81620026e-01 4.50273722e-01
6.90303802e-01 6.99258447e-01 -2.30912149e-01 7.53649473e-01
-2.68176317e-01 1.13380647e+00 -6.01134539e-01 -8.03545058e-01
-4.51281399e-01 -3.66379350e-01 -1.35699880e+00 -5.45391381e-01
1.32867441e-01 3.81875336e-01 -1.67722508e-01 8.04187477e-01
5.28261960e-01 -1.56166196e-01 6.98579669e-01 -8.80570054e-01
-1.90850466e-01 6.47174776e-01 -2.90555447e-01 5.45442104e-01
7.43506610e-01 -2.91474294e-02 1.36326861e+00 -8.28602731e-01
1.30227423e+00 1.14371002e+00 5.72997808e-01 4.59548533e-01
-1.39089942e+00 -4.43992257e-01 -1.99906722e-01 3.23852837e-01
-1.47799242e+00 -3.24943066e-01 -3.26706842e-02 -2.82409430e-01
1.68539429e+00 3.90278339e-01 6.14243783e-02 9.27743077e-01
4.75529313e-01 5.49349785e-01 4.20164645e-01 -2.95266122e-01
1.80170760e-01 -8.67379755e-02 6.63999856e-01 8.68883431e-01
4.08689648e-01 -5.47967911e-01 -5.47533929e-01 -8.60386193e-01
7.43936449e-02 -2.88701802e-01 -2.83178329e-01 2.55818993e-01
-1.25717044e+00 5.64058065e-01 2.59797014e-02 3.61689240e-01
-6.70481920e-01 2.16607824e-02 5.82793653e-01 1.91083908e-01
3.41529459e-01 9.02514696e-01 -1.11791587e+00 3.07394743e-01
-7.85995483e-01 4.08424616e-01 1.41331983e+00 9.49072719e-01
5.18191636e-01 -1.01550150e+00 -4.07519221e-01 6.03307486e-01
2.80003250e-01 -2.74727196e-01 3.60007942e-01 -5.06749749e-01
3.99779588e-01 7.04207659e-01 1.74146891e-01 -5.84234118e-01
-8.10181439e-01 -2.38420650e-01 -4.68019426e-01 -6.68651879e-01
5.19930065e-01 -4.46144909e-01 -8.97242725e-01 1.70036376e+00
8.28037679e-01 2.94624567e-01 4.25610721e-01 4.04351473e-01
1.56469154e+00 5.60662568e-01 9.13342714e-01 -1.92248061e-01
2.28998089e+00 -6.51449084e-01 -1.13003194e+00 -1.98396951e-01
6.69898450e-01 -6.83298886e-01 5.23586981e-02 1.64979488e-01
-1.15974534e+00 3.98751460e-02 -6.38827145e-01 -7.17010856e-01
-8.92500341e-01 -6.40485523e-05 5.87815046e-01 7.75445774e-02
-7.85039425e-01 3.46513897e-01 -7.98061669e-01 -6.61403596e-01
3.30401361e-01 3.50714594e-01 -5.60420394e-01 8.10156465e-02
-1.62823212e+00 1.35523927e+00 6.78478599e-01 4.02357318e-02
-6.59115911e-01 -1.13169611e+00 -1.00713539e+00 2.36613154e-01
5.72869658e-01 -1.21303582e+00 1.15036237e+00 1.01576053e-01
-9.02126551e-01 1.39485776e+00 -4.60665494e-01 -7.28270173e-01
1.29417730e-02 -2.84786046e-01 -4.10261959e-01 4.39145625e-01
3.12318861e-01 4.30250615e-01 5.05505130e-02 -5.37805259e-01
-5.93321979e-01 -4.70218003e-01 -7.76333809e-02 -1.78446904e-01
4.23775762e-01 5.91799259e-01 -4.96454000e-01 -2.73745269e-01
-7.96071738e-02 -5.22384524e-01 -6.39691949e-01 -1.37205631e-01
-7.79217064e-01 -7.49275446e-01 2.87514925e-01 -9.28066194e-01
1.13011014e+00 -1.77723396e+00 2.29412779e-01 4.26903330e-02
4.31498557e-01 8.50598365e-02 1.30859062e-01 6.56331301e-01
-4.90526468e-01 1.90477937e-01 -2.77061522e-01 5.37379459e-02
-5.83943576e-02 3.09786856e-01 -2.09108055e-01 2.16470838e-01
9.23891366e-01 1.24015951e+00 -1.10103726e+00 -9.28771794e-01
-4.93716985e-01 3.56712788e-01 -2.13007644e-01 1.77862689e-01
-7.34980643e-01 1.04207709e-01 -6.89077735e-01 8.70362341e-01
3.10014427e-01 -7.63497531e-01 5.73013067e-01 -3.76660615e-01
2.62150645e-01 6.93880737e-01 -8.36735606e-01 1.62798274e+00
1.57575741e-01 1.52396038e-01 1.33323237e-01 -1.09398520e+00
5.80116451e-01 8.22783530e-01 4.72455621e-01 1.76280458e-02
-2.99988706e-02 1.49129733e-01 -1.33444667e-01 -7.69864142e-01
1.16665557e-03 -3.33790421e-01 -1.98534966e-01 2.37879008e-02
7.06906140e-01 1.00794382e-01 3.97102177e-01 6.05737209e-01
1.87906253e+00 2.08799198e-01 9.75839734e-01 -2.12977067e-01
7.05351293e-01 2.33678564e-01 8.57685506e-01 7.59923100e-01
-6.97670281e-02 2.00625852e-01 8.86475623e-01 -3.43227863e-01
-4.25113916e-01 -1.03334701e+00 -4.15324390e-01 7.64711678e-01
-2.56521136e-01 -9.03517008e-01 -3.76289248e-01 -9.79991019e-01
-1.19852573e-01 4.98540550e-01 -7.29153574e-01 8.07180628e-02
-5.80235302e-01 -1.22131121e+00 8.71384084e-01 2.49324277e-01
-5.54095546e-04 -1.00448012e+00 -2.99299955e-01 5.90000212e-01
-5.31641901e-01 -1.59093475e+00 -2.20135599e-01 7.62907028e-01
-4.96590227e-01 -1.60309267e+00 -4.79048818e-01 -7.66167223e-01
4.03233051e-01 -6.62006319e-01 1.64249408e+00 1.37911262e-02
-8.06287885e-01 5.61430976e-02 -8.47398117e-02 -8.14116597e-01
-3.49730074e-01 8.15586597e-02 -4.56878632e-01 -2.46125132e-01
8.35167110e-01 -2.04484373e-01 -4.86494780e-01 -3.46391276e-02
-1.00781298e+00 -1.89126983e-01 5.69623291e-01 7.88432181e-01
8.76761198e-01 -2.38892660e-01 8.42885137e-01 -1.26497018e+00
4.59047318e-01 -9.53956783e-01 -3.21246326e-01 7.60566711e-01
-2.14886412e-01 2.44732454e-01 2.84397960e-01 -2.14224428e-01
-1.05907643e+00 2.77883530e-01 -3.77935797e-01 4.08556104e-01
-3.58634025e-01 8.92768085e-01 -3.94785076e-01 4.83983308e-01
7.12846339e-01 1.58739895e-01 -5.03848672e-01 -4.31979865e-01
4.36855912e-01 2.55245864e-01 6.00130081e-01 -7.02192962e-01
4.06869113e-01 2.34417930e-01 1.87157869e-01 -7.06461310e-01
-1.14674509e+00 -7.01725304e-01 -4.22643006e-01 4.31376338e-01
1.19449699e+00 -8.97105634e-01 -7.95290172e-01 -6.76956028e-02
-1.45322394e+00 6.90550283e-02 -2.92875409e-01 3.99586797e-01
-1.73830763e-01 2.98254132e-01 -1.11285853e+00 -3.26739401e-01
-6.20924115e-01 -7.16266513e-01 1.38543904e+00 1.59017220e-01
-5.30674636e-01 -8.60675097e-01 4.08230096e-01 3.57210308e-01
-3.19131941e-01 4.03548896e-01 1.42131150e+00 -1.30727625e+00
-4.11556959e-01 -2.63356149e-01 -2.50620902e-01 -4.65866536e-01
7.59203285e-02 -9.04118270e-02 -5.68959117e-01 3.06352109e-01
-4.12405789e-01 -4.78944868e-01 9.53875244e-01 3.14050727e-02
8.11849117e-01 -3.42033237e-01 -9.70890582e-01 2.09909797e-01
1.05452299e+00 -7.51093701e-02 6.47780001e-01 5.10744974e-02
2.24825859e-01 7.62638986e-01 5.04196167e-01 1.18363529e-01
5.38420379e-01 3.08231533e-01 1.02626076e-02 -1.34756416e-01
1.14099026e-01 4.37294468e-02 -7.54175708e-02 1.84491634e-01
8.24291334e-02 -4.43105549e-01 -1.09915733e+00 6.38967633e-01
-1.98864901e+00 -8.27951550e-01 -4.17981267e-01 1.53903615e+00
1.63922429e+00 -3.74882296e-02 -2.03920975e-01 -3.58055055e-01
5.18895328e-01 -3.80758077e-01 -5.88739038e-01 -1.32991299e-01
-3.04053903e-01 6.87484741e-01 1.99699461e-01 3.03231478e-01
-1.09877574e+00 1.13553691e+00 6.96273565e+00 6.55697942e-01
-3.77848059e-01 1.10328577e-01 5.66391587e-01 1.33054376e-01
5.85575253e-02 8.78614113e-02 -1.09793210e+00 7.15831667e-02
1.26207983e+00 -2.11562335e-01 -3.18907440e-01 2.24615365e-01
-1.04186669e-01 -2.01791286e-01 -1.39518499e+00 6.07723236e-01
-1.84501916e-01 -1.67753339e+00 -2.13196538e-02 -1.20153382e-01
1.77080259e-01 1.94733471e-01 -5.76246083e-01 2.47562557e-01
8.31195951e-01 -9.35189784e-01 1.68932348e-01 8.26939762e-01
2.92373627e-01 -3.19429427e-01 8.22208822e-01 3.47287834e-01
-9.54567730e-01 2.80446380e-01 -3.23013902e-01 5.51582634e-01
2.13149056e-01 8.53230059e-01 -1.23091173e+00 9.38181102e-01
7.21099138e-01 5.03795207e-01 -4.12671685e-01 1.08323908e+00
-5.43183267e-01 8.72186303e-01 -3.57533067e-01 1.15458341e-02
-7.78260753e-02 2.79750109e-01 5.08215368e-01 1.79593503e+00
-1.45972580e-01 6.84264362e-01 -3.46361846e-02 8.50381255e-01
-4.69876945e-01 3.39065850e-01 -2.53533542e-01 -2.51619369e-01
1.31927773e-01 1.62792575e+00 -6.25336945e-01 -6.13770425e-01
-3.13936859e-01 7.53984332e-01 6.77389622e-01 3.26360434e-01
-7.70096123e-01 -5.87442636e-01 4.43316251e-01 -1.61153227e-01
2.87794918e-01 2.98666596e-01 2.77282029e-01 -1.28966475e+00
-2.50380576e-01 -8.64575982e-01 1.32697332e+00 -7.72382140e-01
-1.53651726e+00 4.45754379e-01 -1.93140894e-01 -4.19338375e-01
-2.45271266e-01 -4.86602396e-01 -2.89302319e-01 9.07216012e-01
-1.43697965e+00 -1.07929587e+00 1.84593260e-01 5.31331658e-01
2.02861130e-01 4.11645353e-01 1.14545095e+00 4.00778055e-01
-8.14093471e-01 3.51738960e-01 -2.98908383e-01 3.15673947e-01
9.70579207e-01 -1.44400275e+00 3.33754629e-01 4.79948461e-01
-3.76629904e-02 9.35964942e-01 7.56239414e-01 -7.87790716e-01
-1.15123701e+00 -1.22400773e+00 1.83860815e+00 -8.17788839e-01
8.98599982e-01 -4.57158655e-01 -1.25323665e+00 9.53345895e-01
2.77361661e-01 6.36524707e-02 1.29573071e+00 9.47319567e-02
-4.37736005e-01 4.22200322e-01 -1.25013030e+00 1.90567851e-01
8.38820815e-01 -3.96950632e-01 -1.08096921e+00 9.24938202e-01
8.50789130e-01 -4.24815893e-01 -1.35115540e+00 5.03949285e-01
1.61502764e-01 9.26832482e-02 1.18956757e+00 -1.55115139e+00
4.03641462e-01 -3.64319086e-01 1.93839744e-01 -7.67778456e-01
-1.09837621e-01 -8.75892401e-01 -4.46585476e-01 1.11606026e+00
1.07777047e+00 -4.89472300e-01 3.90989304e-01 7.84626424e-01
2.06668794e-01 -5.93749762e-01 -1.11563385e+00 -1.19688883e-01
-9.53291580e-02 4.19931784e-02 3.82118553e-01 1.16505027e+00
3.68457645e-01 1.09750712e+00 2.32991949e-01 4.42677617e-01
4.42385972e-01 8.63795280e-02 2.84099698e-01 -1.45840085e+00
-3.43353987e-01 -5.22972597e-03 -2.91927636e-01 -5.78940570e-01
2.38489509e-01 -9.94482875e-01 1.06322303e-01 -1.84571922e+00
4.55456525e-01 -1.05289547e-02 -4.41760391e-01 7.36511588e-01
-6.01659000e-01 -3.45895737e-02 -6.20066047e-01 -1.43010736e-01
-1.05068767e+00 9.76297632e-02 6.34100497e-01 -2.30899721e-01
6.28231764e-02 -2.04313040e-01 -8.44251335e-01 6.80953205e-01
3.55504245e-01 -8.58876705e-01 1.03573278e-01 4.01885994e-02
7.63110161e-01 4.82246339e-01 3.58300030e-01 -5.01396954e-01
5.66678822e-01 5.23655415e-02 2.92062402e-01 -7.43160248e-01
5.52893169e-02 -4.52713758e-01 2.82540560e-01 4.90997195e-01
-6.07266307e-01 -1.32576361e-01 3.02797168e-01 8.10669959e-01
-1.77672789e-01 -2.38629743e-01 5.59625983e-01 -3.43179405e-01
-1.37046188e-01 2.43011937e-01 -5.00992715e-01 3.57813030e-01
8.74551177e-01 3.77487302e-01 -5.07800579e-01 6.66044429e-02
-1.43011332e+00 5.89704633e-01 -4.07175064e-01 1.67693809e-01
3.57236773e-01 -6.51562035e-01 -1.08411121e+00 -5.15354574e-01
2.38370165e-01 4.88627926e-02 -2.28913538e-02 1.00163949e+00
-3.29806626e-01 7.02482343e-01 4.30737823e-01 -1.92393482e-01
-1.39584196e+00 6.61726892e-01 5.31256080e-01 -9.13182080e-01
-3.74319613e-01 1.09603333e+00 2.97170132e-01 -5.47867596e-01
4.12658229e-02 -3.17353725e-01 -4.71614927e-01 1.89128473e-01
6.74753785e-01 -6.60026819e-02 3.09391409e-01 -3.02071810e-01
-9.53728497e-01 3.94318365e-02 -2.96825528e-01 2.31672481e-01
1.44171095e+00 9.18906927e-02 -6.62564874e-01 7.76448920e-02
9.36260521e-01 -8.82620886e-02 -3.88220698e-01 -5.81709743e-01
7.74879515e-01 5.28004110e-01 -3.96853268e-01 -1.24901545e+00
-4.79933143e-01 3.62322986e-01 -9.39548165e-02 -6.43752655e-03
7.12251127e-01 7.14730144e-01 6.18088782e-01 6.62537515e-01
4.29741479e-02 -7.03187287e-01 -4.04527545e-01 5.13715446e-01
7.56412089e-01 -1.01009440e+00 6.91383258e-02 -8.67278278e-01
-1.94303691e-01 1.01890767e+00 5.41018009e-01 3.58473599e-01
6.72356546e-01 4.19865996e-01 -2.56417692e-01 -7.75438607e-01
-1.30387068e+00 -4.48842555e-01 4.95317400e-01 9.90137979e-02
7.83842742e-01 -2.12084338e-01 -7.45182395e-01 9.95181084e-01
2.31477261e-01 7.77492523e-02 1.96616501e-02 9.28544939e-01
-1.35034025e-01 -1.30755627e+00 4.03920673e-02 5.23270547e-01
-1.31024969e+00 -6.38795793e-01 -8.28245759e-01 6.82955742e-01
1.76941484e-01 9.81850326e-01 -2.84458697e-01 2.65228808e-01
3.59999418e-01 5.14729083e-01 3.78672421e-01 -8.65468681e-01
-1.03419626e+00 5.45693263e-02 4.88058686e-01 -5.49520969e-01
-4.92903292e-01 -7.95479715e-01 -1.75025535e+00 4.92147923e-01
-3.99003983e-01 7.10469544e-01 1.66515097e-01 1.15198517e+00
6.98694229e-01 7.60230184e-01 -2.46523857e-01 4.35171038e-01
-1.12591825e-01 -8.69934261e-01 -1.62329674e-01 2.08806679e-01
1.56250179e-01 -2.29358524e-01 1.02387771e-01 2.88456619e-01] | [8.649373054504395, 8.900046348571777] |
f791a791-2d81-4fee-b325-303bbfba7aa9 | paint-by-example-exemplar-based-image-editing | 2211.13227 | null | https://arxiv.org/abs/2211.13227v1 | https://arxiv.org/pdf/2211.13227v1.pdf | Paint by Example: Exemplar-based Image Editing with Diffusion Models | Language-guided image editing has achieved great success recently. In this paper, for the first time, we investigate exemplar-guided image editing for more precise control. We achieve this goal by leveraging self-supervised training to disentangle and re-organize the source image and the exemplar. However, the naive approach will cause obvious fusing artifacts. We carefully analyze it and propose an information bottleneck and strong augmentations to avoid the trivial solution of directly copying and pasting the exemplar image. Meanwhile, to ensure the controllability of the editing process, we design an arbitrary shape mask for the exemplar image and leverage the classifier-free guidance to increase the similarity to the exemplar image. The whole framework involves a single forward of the diffusion model without any iterative optimization. We demonstrate that our method achieves an impressive performance and enables controllable editing on in-the-wild images with high fidelity. | ['Fang Wen', 'Dong Chen', 'Xiaoyan Sun', 'Xuejin Chen', 'Ting Zhang', 'Bo Zhang', 'Shuyang Gu', 'Binxin Yang'] | 2022-11-23 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Yang_Paint_by_Example_Exemplar-Based_Image_Editing_With_Diffusion_Models_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Yang_Paint_by_Example_Exemplar-Based_Image_Editing_With_Diffusion_Models_CVPR_2023_paper.pdf | cvpr-2023-1 | ['image-manipulation'] | ['computer-vision'] | [ 4.73061055e-01 1.51569933e-01 9.47375074e-02 -2.74788380e-01
-5.15194654e-01 -7.30669022e-01 8.79053235e-01 1.92472301e-02
-4.93821204e-01 5.10875225e-01 5.14268577e-02 -1.06821574e-01
-1.33395404e-01 -5.30017376e-01 -8.68514240e-01 -7.87789941e-01
3.93848121e-01 2.45210305e-01 -2.50524245e-02 -9.15664062e-02
2.81999379e-01 5.66926301e-01 -1.33879852e+00 7.03110965e-03
1.09442663e+00 6.49473906e-01 5.66072226e-01 5.01218736e-01
-9.78309438e-02 5.34465432e-01 -4.50348198e-01 -2.66825914e-01
4.22785282e-01 -4.01398927e-01 -5.45788109e-01 7.74063528e-01
6.07892692e-01 -1.54264703e-01 -3.23326319e-01 1.07258236e+00
3.24881494e-01 5.74847832e-02 5.61407566e-01 -1.02694535e+00
-1.02006567e+00 3.21973592e-01 -7.64515460e-01 -1.16354100e-01
1.81930840e-01 4.79361624e-01 6.51288450e-01 -8.51726413e-01
9.48315203e-01 7.94345558e-01 2.84628689e-01 4.83562917e-01
-1.50501919e+00 -5.56173921e-01 3.75940710e-01 -3.13210219e-01
-1.49468875e+00 -6.45776868e-01 8.58722985e-01 -5.44246137e-01
3.59785527e-01 1.20275706e-01 8.02697659e-01 1.05298328e+00
-7.14338198e-02 6.45194829e-01 1.30928242e+00 -4.69568193e-01
2.55129844e-01 2.10429564e-01 -2.48294517e-01 1.08910620e+00
1.22502604e-02 1.05579004e-01 -2.62373000e-01 1.11670554e-01
1.17240810e+00 4.06017274e-01 -4.58424538e-01 -7.08946705e-01
-1.56883001e+00 5.23770690e-01 5.12166560e-01 2.29232877e-01
-3.23962241e-01 1.25188187e-01 8.56954977e-03 2.85504490e-01
3.22989613e-01 7.54166901e-01 -2.47517899e-01 1.97416544e-01
-1.13730526e+00 7.99322352e-02 4.78619903e-01 1.15742517e+00
8.81081820e-01 9.95638315e-03 -3.43230814e-01 6.77321136e-01
-1.37723565e-01 4.05227482e-01 2.76446164e-01 -1.24933028e+00
1.29867986e-01 4.81593192e-01 2.28277087e-01 -8.23958278e-01
-6.73500448e-03 -6.04693294e-01 -9.33226883e-01 4.18246239e-01
4.93648827e-01 5.78593928e-03 -1.15330374e+00 1.71268499e+00
3.54542017e-01 1.43389627e-01 -2.94670492e-01 8.94413531e-01
8.61580968e-02 4.55090135e-01 -2.81512253e-02 -2.56592721e-01
9.90709543e-01 -1.28908026e+00 -6.27123237e-01 -8.08677897e-02
2.92814702e-01 -5.85819423e-01 1.46257675e+00 3.50049764e-01
-1.04124522e+00 -4.68793184e-01 -1.14759707e+00 -8.73448700e-02
-1.22065328e-01 2.62843192e-01 5.12674809e-01 2.03434154e-01
-8.38838696e-01 6.73658371e-01 -7.97878146e-01 -3.64562541e-01
4.94542599e-01 2.76067138e-01 -5.90951383e-01 -2.51298081e-02
-5.65219223e-01 6.16309285e-01 1.50879622e-01 -8.18963051e-02
-9.70353365e-01 -7.56519735e-01 -6.86464906e-01 -1.21307917e-01
7.22452939e-01 -9.63824511e-01 8.54840398e-01 -1.16979074e+00
-1.84786248e+00 8.79343271e-01 -4.69720960e-02 -2.51497597e-01
7.32981682e-01 -1.29944459e-01 3.81159671e-02 -4.53464985e-02
7.71723390e-02 8.01795065e-01 1.43638337e+00 -1.51414382e+00
-2.95131445e-01 -2.21904531e-01 2.19641060e-01 1.03831828e-01
-4.16211456e-01 -3.41195166e-01 -6.54339314e-01 -1.04913926e+00
7.32127875e-02 -1.10953724e+00 -3.18618953e-01 4.55854893e-01
-4.52906042e-01 4.49679732e-01 4.95222628e-01 -2.11352617e-01
1.14066505e+00 -2.38694119e+00 2.98023045e-01 9.88339111e-02
5.72800517e-01 2.73213983e-01 -3.52329910e-01 4.04997975e-01
1.01784959e-01 1.51956946e-01 -6.75631642e-01 -6.53333008e-01
-1.54464707e-01 3.51308435e-01 -3.49573851e-01 4.40412372e-01
2.18770802e-01 1.02562273e+00 -9.71504748e-01 -5.64143419e-01
1.81073427e-01 4.95719820e-01 -7.45278418e-01 2.57356316e-01
-4.43045974e-01 9.23445582e-01 -5.07230461e-01 2.16684103e-01
6.05232358e-01 -3.60907078e-01 2.79715750e-02 -4.30414826e-01
-2.53073364e-01 -1.97659418e-01 -9.72877026e-01 2.17521024e+00
-6.04157448e-01 3.48816127e-01 3.18165213e-01 -8.43583167e-01
7.04574168e-01 -4.22845371e-02 3.07168543e-01 -4.86838490e-01
-9.14783478e-02 6.70018420e-02 -3.62281576e-02 -4.03155416e-01
3.79963279e-01 -1.23701021e-01 1.61630228e-01 6.45805299e-01
2.50516590e-02 -2.58437604e-01 -3.06109544e-02 2.66229570e-01
7.72965312e-01 4.71425116e-01 2.97819972e-01 -2.86757916e-01
4.19361383e-01 -4.72466461e-02 3.68966222e-01 8.37216377e-01
-5.64156733e-02 9.64372337e-01 1.58532590e-01 -2.61042625e-01
-1.14740670e+00 -1.09746230e+00 1.46762028e-01 8.09162140e-01
1.59054726e-01 -4.15402114e-01 -8.79365683e-01 -7.18733132e-01
-2.25909632e-02 5.62201679e-01 -7.39248872e-01 -9.81207788e-02
-4.19812143e-01 -4.49328810e-01 2.90803254e-01 3.06162089e-01
5.87084353e-01 -6.74082994e-01 -3.07090223e-01 8.25013891e-02
5.56630194e-02 -1.07572699e+00 -1.01742733e+00 -5.64089864e-02
-6.30189717e-01 -6.44159377e-01 -7.58212924e-01 -7.12313473e-01
1.16315854e+00 3.82195234e-01 7.17919827e-01 3.00418407e-01
-2.93692380e-01 3.66565555e-01 -8.63401741e-02 2.57670172e-02
-4.24485594e-01 -3.58543023e-02 -1.16489597e-01 4.24977243e-01
-4.57512200e-01 -8.77257049e-01 -8.34653199e-01 1.86989337e-01
-1.06802106e+00 4.25897121e-01 7.25310683e-01 9.31786358e-01
8.33926022e-01 -2.10545123e-01 4.38056350e-01 -8.91543090e-01
5.98541319e-01 -2.39512771e-02 -6.56466901e-01 4.11392212e-01
-5.68432450e-01 3.91983211e-01 7.60131180e-01 -6.19253457e-01
-1.04930770e+00 4.60673720e-01 2.39863038e-01 -6.70884073e-01
-6.07211329e-02 2.08988905e-01 -1.36599556e-01 -2.88364381e-01
5.72018385e-01 4.26107258e-01 1.49562195e-01 -4.54213321e-01
9.73898411e-01 5.10625899e-01 7.03179538e-01 -7.37055182e-01
9.32992578e-01 7.92621613e-01 -1.99441895e-01 -7.71251380e-01
-8.63527715e-01 -3.71824317e-02 -8.62386882e-01 -9.16161686e-02
7.78495252e-01 -8.11242461e-01 -5.33046544e-01 1.98476866e-01
-1.12139201e+00 -5.64277232e-01 -5.40089846e-01 1.82931051e-01
-5.87653160e-01 3.16030174e-01 -4.53251749e-01 -4.15085584e-01
-1.32655606e-01 -1.22244990e+00 1.10675764e+00 -9.25484970e-02
-7.81845972e-02 -7.47525811e-01 -1.03402831e-01 1.62496477e-01
5.37459970e-01 1.96673736e-01 7.38736510e-01 -3.03676337e-01
-1.06162620e+00 -4.45602797e-02 -3.07551682e-01 2.21443176e-01
2.62073755e-01 6.05036728e-02 -7.64000416e-01 -2.68098116e-01
3.73488627e-02 -1.30442932e-01 8.91412139e-01 -4.06274386e-02
1.30547118e+00 -3.00008357e-01 -2.32242852e-01 9.04240668e-01
1.30961597e+00 -1.52652130e-01 3.65453660e-01 1.90500602e-01
8.63862395e-01 4.84708846e-01 2.95992881e-01 3.66834790e-01
2.44824097e-01 6.59345329e-01 1.40709877e-01 -8.74611661e-02
-3.67375761e-01 -4.93342012e-01 1.26316756e-01 7.79261589e-01
-3.40725854e-02 -1.96222663e-01 -5.75141370e-01 3.61811668e-01
-1.72870028e+00 -7.56284297e-01 3.78378958e-01 2.32649565e+00
8.72708678e-01 -3.21531035e-02 -1.85878292e-01 -2.56244749e-01
6.95872903e-01 4.51978207e-01 -5.88393807e-01 3.66187990e-02
8.11665729e-02 -1.07191406e-01 3.01884502e-01 7.55176306e-01
-1.00958514e+00 1.14432967e+00 6.36067963e+00 7.85082936e-01
-1.32853937e+00 9.14604589e-02 5.25931954e-01 -2.96841532e-01
-5.37514448e-01 2.35063195e-01 -3.72069567e-01 3.49435478e-01
2.74656564e-01 -2.14405805e-01 9.53864038e-01 5.00519276e-01
2.73566544e-01 2.36257352e-02 -1.07012117e+00 8.26999605e-01
-1.56173026e-02 -1.36088276e+00 3.62523884e-01 7.83780515e-02
9.13371921e-01 -1.78037688e-01 1.28513902e-01 -1.37731791e-01
2.25079373e-01 -7.36376464e-01 7.70497799e-01 7.99078941e-01
8.98259342e-01 -4.14889216e-01 -1.85270771e-01 4.48855549e-01
-8.23489487e-01 -1.25554027e-02 -1.92263499e-01 -2.34533530e-02
2.52144873e-01 7.77637422e-01 -2.46337488e-01 3.67299050e-01
1.48676470e-01 6.42507732e-01 -5.96723199e-01 7.64208436e-01
-2.18345910e-01 2.24245876e-01 -2.54406095e-01 3.29626739e-01
1.80594400e-01 -5.64441442e-01 6.71282768e-01 1.05181289e+00
2.83851415e-01 1.24481104e-01 3.56931508e-01 1.14173865e+00
-2.16198236e-01 -2.16184724e-02 -7.26742268e-01 -1.83999583e-01
5.07146299e-01 1.24894977e+00 -7.18791842e-01 -3.65036935e-01
-3.00018370e-01 1.58484793e+00 7.30874836e-01 5.75357974e-01
-8.07176709e-01 -2.44501144e-01 4.78275746e-01 1.62168354e-01
4.53709334e-01 -5.58222711e-01 -3.00894469e-01 -1.39527869e+00
1.30368456e-01 -7.32880533e-01 -2.32543752e-01 -8.30453992e-01
-1.15632689e+00 6.36058688e-01 -2.26172894e-01 -1.06833053e+00
1.40829310e-01 -3.30530435e-01 -5.40471256e-01 7.43488252e-01
-1.36878037e+00 -1.25974584e+00 -3.84149849e-01 6.95311487e-01
3.51638794e-01 4.11166139e-02 6.20082259e-01 2.24956349e-01
-6.56266570e-01 6.63162827e-01 1.92998111e-01 -7.50378370e-02
9.38669503e-01 -1.21737266e+00 1.68844238e-01 7.59136736e-01
2.73119748e-01 1.00769758e+00 5.77816963e-01 -5.43493569e-01
-1.50937974e+00 -1.20328128e+00 4.42737281e-01 -4.39137012e-01
7.16082156e-01 -5.38026094e-01 -9.49391365e-01 6.25139475e-01
3.17736864e-01 1.84246540e-01 3.17183644e-01 -2.99766958e-01
-5.02487123e-01 -2.50297695e-01 -9.25684631e-01 9.66224372e-01
1.43401635e+00 -7.04398751e-01 -3.33121836e-01 3.26222122e-01
8.67291570e-01 -2.25106448e-01 -8.02597463e-01 1.94839150e-01
4.77101982e-01 -7.69270957e-01 9.72711921e-01 -3.42921734e-01
4.43824649e-01 -5.80736279e-01 1.13599040e-01 -1.37260723e+00
-3.76392543e-01 -1.05361938e+00 1.13479868e-01 1.26789260e+00
3.26603532e-01 -5.91458261e-01 5.97241104e-01 5.33494473e-01
-8.23176131e-02 -7.28643060e-01 -4.36403275e-01 -7.57643163e-01
-6.81448206e-02 -1.35249689e-01 7.18492329e-01 8.66070032e-01
-1.26836732e-01 3.50504130e-01 -4.54343796e-01 1.58941790e-01
6.58760846e-01 4.16568458e-01 9.23703730e-01 -8.05464923e-01
-5.16906261e-01 -4.47395235e-01 -9.45460126e-02 -1.36926067e+00
9.83698890e-02 -8.49162102e-01 1.26200467e-01 -1.21877813e+00
2.43896127e-01 -5.36748946e-01 -2.04091430e-01 3.12782288e-01
-2.55274236e-01 3.13381463e-01 3.98676276e-01 4.70159471e-01
-7.03517377e-01 7.11322248e-01 1.78749156e+00 -1.26822948e-01
-2.00680554e-01 -4.06987935e-01 -8.52323771e-01 5.65970063e-01
6.58979237e-01 -3.48721206e-01 -6.08917475e-01 -7.97749341e-01
-7.07271174e-02 1.05149811e-02 4.91846919e-01 -7.76586473e-01
3.85826439e-01 -2.61775672e-01 9.82450992e-02 5.04739992e-02
2.55839765e-01 -8.05976570e-01 2.29237005e-01 1.36591986e-01
-6.43475056e-01 -5.49757555e-02 -1.22467794e-01 9.24656928e-01
-1.19813807e-01 -1.89968217e-02 8.32759321e-01 -1.41508073e-01
-4.42477524e-01 6.18952513e-01 -1.38872936e-01 -1.02393113e-01
1.00394249e+00 -1.18102685e-01 -1.70349166e-01 -3.96304220e-01
-8.84946585e-01 8.28391016e-02 1.09785807e+00 2.20112011e-01
4.73332465e-01 -1.15579259e+00 -4.90905344e-01 4.20821130e-01
2.64583319e-01 5.77854030e-02 8.71648192e-02 8.41639459e-01
-3.80596131e-01 1.99781470e-02 -8.19075406e-02 -5.44114590e-01
-7.75136292e-01 9.76007998e-01 4.20637280e-01 -1.53437272e-01
-7.14327812e-01 4.03216302e-01 5.52501619e-01 -3.76697063e-01
1.15177028e-01 -9.70565528e-02 2.36374110e-01 -2.76070148e-01
4.25789684e-01 -5.01442961e-02 -2.82600164e-01 -3.83174300e-01
-4.51571718e-02 6.93850219e-01 -3.09642226e-01 -3.62579763e-01
1.19978678e+00 -4.60066319e-01 -1.46426201e-01 2.58600026e-01
1.25603843e+00 1.47744879e-01 -1.83091199e+00 -3.19216371e-01
-1.50230661e-01 -5.68882465e-01 1.33366376e-01 -7.50855803e-01
-1.21959794e+00 8.56516957e-01 2.99386561e-01 -1.84227712e-02
1.09537888e+00 -1.27462745e-01 6.54654980e-01 4.13689613e-01
3.74100447e-01 -8.92849445e-01 1.78107426e-01 2.44908899e-01
1.07841372e+00 -1.17893016e+00 7.47346133e-02 -4.72431034e-01
-6.34644330e-01 8.59998047e-01 4.03761387e-01 -3.02028000e-01
6.42183304e-01 2.50328660e-01 3.41441557e-02 -1.72214225e-01
-5.42355537e-01 -1.58810481e-01 1.50344387e-01 5.66773415e-01
3.04422319e-01 -8.72239172e-02 -2.77652085e-01 2.33143464e-01
1.02186196e-01 2.44107231e-01 3.20615739e-01 8.56656253e-01
-1.88705489e-01 -1.17106783e+00 -1.17882110e-01 2.52724826e-01
-1.36619613e-01 -1.74685255e-01 -3.37594360e-01 7.06988156e-01
3.28351185e-03 5.38869441e-01 -4.13469672e-02 -2.58233070e-01
2.60864466e-01 -6.21289946e-02 7.37464964e-01 -5.14829397e-01
-3.91927928e-01 2.28906497e-01 -3.08414638e-01 -6.21036708e-01
-4.88471806e-01 -4.72529441e-01 -1.10566235e+00 -9.71872285e-02
-3.55162084e-01 -6.50549158e-02 5.38227022e-01 8.57206941e-01
8.65458667e-01 3.32064182e-01 6.78113341e-01 -9.87136781e-01
-4.87574428e-01 -5.82306564e-01 -4.61723745e-01 5.67216873e-01
5.02932370e-01 -5.08727431e-01 -3.02575499e-01 3.45935374e-01] | [11.498918533325195, -0.4153451919555664] |
156bb9eb-a8b6-4c67-9fdd-c5d83860b273 | pose-controllable-talking-face-generation-by | 2104.11116 | null | https://arxiv.org/abs/2104.11116v1 | https://arxiv.org/pdf/2104.11116v1.pdf | Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation | While accurate lip synchronization has been achieved for arbitrary-subject audio-driven talking face generation, the problem of how to efficiently drive the head pose remains. Previous methods rely on pre-estimated structural information such as landmarks and 3D parameters, aiming to generate personalized rhythmic movements. However, the inaccuracy of such estimated information under extreme conditions would lead to degradation problems. In this paper, we propose a clean yet effective framework to generate pose-controllable talking faces. We operate on raw face images, using only a single photo as an identity reference. The key is to modularize audio-visual representations by devising an implicit low-dimension pose code. Substantially, both speech content and head pose information lie in a joint non-identity embedding space. While speech content information can be defined by learning the intrinsic synchronization between audio-visual modalities, we identify that a pose code will be complementarily learned in a modulated convolution-based reconstruction framework. Extensive experiments show that our method generates accurately lip-synced talking faces whose poses are controllable by other videos. Moreover, our model has multiple advanced capabilities including extreme view robustness and talking face frontalization. Code, models, and demo videos are available at https://hangz-nju-cuhk.github.io/projects/PC-AVS. | ['Ziwei Liu', 'Xiaogang Wang', 'Chen Change Loy', 'Wayne Wu', 'Yasheng Sun', 'Hang Zhou'] | 2021-04-22 | null | http://openaccess.thecvf.com//content/CVPR2021/html/Zhou_Pose-Controllable_Talking_Face_Generation_by_Implicitly_Modularized_Audio-Visual_Representation_CVPR_2021_paper.html | http://openaccess.thecvf.com//content/CVPR2021/papers/Zhou_Pose-Controllable_Talking_Face_Generation_by_Implicitly_Modularized_Audio-Visual_Representation_CVPR_2021_paper.pdf | cvpr-2021-1 | ['talking-face-generation'] | ['computer-vision'] | [ 3.50279696e-02 2.66259700e-01 8.60842131e-03 -4.07490045e-01
-9.99468088e-01 -5.16266406e-01 5.36443949e-01 -9.20362949e-01
2.06508100e-01 4.90014702e-01 6.29021287e-01 3.80085737e-01
2.05955282e-01 -3.53338867e-01 -7.50929534e-01 -9.08737361e-01
2.10399806e-01 2.17235178e-01 -4.43423241e-01 -2.86375642e-01
2.05442160e-02 3.86171073e-01 -1.88471091e+00 1.60081550e-01
5.45518816e-01 9.72741127e-01 2.32277438e-01 4.80840892e-01
1.25914052e-01 2.34277859e-01 -4.73895043e-01 -4.71356273e-01
3.05455327e-01 -4.17268753e-01 -4.09157485e-01 2.23891154e-01
5.84469438e-01 -3.82431775e-01 -4.51111466e-01 9.30998206e-01
9.82916832e-01 -7.57621676e-02 5.47577143e-01 -1.54178786e+00
-4.83891547e-01 4.34453905e-01 -3.36436331e-01 -5.43847978e-01
7.97115922e-01 3.35635602e-01 5.96700788e-01 -1.22513855e+00
7.31871724e-01 1.33030808e+00 6.08905375e-01 9.64925408e-01
-1.16145623e+00 -9.71416652e-01 -4.35671322e-02 2.19307125e-01
-1.79962742e+00 -1.27758980e+00 1.17861080e+00 -3.65043610e-01
1.40482545e-01 3.69542867e-01 7.28687942e-01 1.52827227e+00
-2.65310884e-01 4.91173267e-01 8.07868600e-01 -2.55194157e-01
-3.49143450e-03 1.50042966e-01 -6.66345716e-01 5.12377262e-01
-2.17391998e-01 7.33621605e-03 -9.78436172e-01 2.44051982e-02
7.26873219e-01 -1.95317090e-01 -7.98527181e-01 -5.37962794e-01
-1.21132672e+00 6.89994633e-01 1.50818646e-01 2.23072574e-01
-5.07685542e-02 9.11120847e-02 1.88915610e-01 1.28761455e-01
3.67272317e-01 4.08133306e-02 -2.07451209e-01 -1.11588478e-01
-9.03309703e-01 1.82517231e-01 5.83707511e-01 1.19851017e+00
8.08331430e-01 2.91104645e-01 -1.34550929e-01 8.43062699e-01
3.19524676e-01 7.85477877e-01 4.29041207e-01 -1.29306805e+00
4.27435249e-01 -1.50127895e-02 1.13075184e-04 -1.16070902e+00
-2.72917897e-01 -1.04541250e-01 -8.87814164e-01 -5.57285361e-02
2.52822459e-01 -2.59655505e-01 -5.48498869e-01 2.28331280e+00
6.41964853e-01 3.20446908e-01 -1.45059496e-01 9.37605500e-01
8.39059055e-01 4.23047096e-01 -3.90997380e-01 -4.39383835e-01
1.29959214e+00 -5.87034345e-01 -1.10612369e+00 1.57278702e-01
9.93062854e-02 -8.69229615e-01 1.03566313e+00 2.13861749e-01
-1.21752000e+00 -7.29517877e-01 -7.66019821e-01 -1.56721205e-01
2.28501819e-02 3.40162843e-01 2.65515774e-01 6.38150513e-01
-1.41042018e+00 1.22542083e-01 -4.24148172e-01 -2.32456505e-01
1.90581799e-01 4.38191473e-01 -7.19804704e-01 1.64565101e-01
-1.20400834e+00 5.26311696e-01 -6.42506555e-02 3.17363173e-01
-8.98732424e-01 -6.61397874e-01 -1.15418208e+00 -1.86143205e-01
2.29917333e-01 -8.56310606e-01 1.06406677e+00 -9.01838422e-01
-2.05014944e+00 8.38979721e-01 -5.70244193e-01 1.26149908e-01
7.39103913e-01 -1.00701615e-01 -3.46605301e-01 4.17582244e-01
4.25007902e-02 9.84228075e-01 1.44510758e+00 -1.55799401e+00
-3.17422040e-02 -4.08602804e-01 -1.56722665e-01 4.20530528e-01
-7.87756562e-01 -5.97030558e-02 -7.99631238e-01 -6.34829760e-01
1.19404964e-01 -1.03963721e+00 2.72345722e-01 3.98253262e-01
-4.57796544e-01 1.64424852e-02 7.89301991e-01 -7.92129517e-01
9.49590385e-01 -2.19745088e+00 3.08482230e-01 -6.42807037e-02
1.51995406e-01 -7.03418627e-02 -2.05645055e-01 3.76347244e-01
-1.80560231e-01 1.72233656e-02 6.11746265e-03 -8.72110248e-01
4.12745215e-02 -2.16810465e-01 -4.22614336e-01 7.38493562e-01
7.90358335e-02 7.31500089e-01 -6.20822847e-01 -7.34334111e-01
2.26374671e-01 1.18009758e+00 -8.35604250e-01 3.09208721e-01
1.30000800e-01 9.31433201e-01 -2.64741272e-01 6.86249912e-01
8.39236975e-01 1.47358790e-01 2.13430732e-01 -6.46271765e-01
4.61904891e-02 1.38536870e-01 -1.32404828e+00 1.99213040e+00
-6.64992869e-01 5.29797554e-01 5.30508697e-01 -6.82968497e-01
8.86736155e-01 6.46169364e-01 5.79955637e-01 -2.85289258e-01
1.51878998e-01 1.00150555e-01 -4.56201643e-01 -6.62566423e-01
2.55819112e-01 -2.97433790e-02 -1.65432261e-03 1.27153158e-01
1.27551332e-01 -3.48550469e-01 -3.24816376e-01 8.00330099e-03
4.63288635e-01 2.59373099e-01 -7.96789080e-02 -8.58165231e-03
6.04375482e-01 -7.68582523e-01 5.86011410e-01 2.98650414e-02
-9.69465822e-02 1.13044345e+00 2.59633809e-01 9.70539749e-02
-8.75203013e-01 -1.16488934e+00 -4.25752461e-01 8.19790244e-01
1.28219187e-01 -6.02539957e-01 -1.12162375e+00 -2.10548282e-01
-2.80722678e-01 3.97615135e-01 -5.44111729e-01 -4.96451445e-02
-6.79999948e-01 -1.43179074e-01 5.65247059e-01 1.37169093e-01
4.05327618e-01 -8.15565348e-01 -8.69213492e-02 -6.73033223e-02
-5.82108557e-01 -1.15587044e+00 -1.12812519e+00 -5.68449795e-01
-3.50258470e-01 -8.86702299e-01 -9.90525067e-01 -7.13141680e-01
7.84314334e-01 2.86867648e-01 7.16008365e-01 -1.77527726e-01
-2.61107117e-01 6.34443402e-01 -7.09028393e-02 -1.88836500e-01
-1.92940906e-01 -1.38787106e-01 6.09035075e-01 6.19203627e-01
-1.29553974e-01 -9.34021533e-01 -8.61344516e-01 4.51592773e-01
-5.68768322e-01 2.62791753e-01 1.54077381e-01 8.14338028e-01
4.00165647e-01 -3.94992471e-01 6.40007257e-01 -2.23310560e-01
3.84767473e-01 -2.57083893e-01 -3.76923978e-01 3.90532501e-02
-1.32528543e-01 -2.42682025e-01 5.03291965e-01 -6.50641441e-01
-1.14334357e+00 3.73235106e-01 -3.26809406e-01 -9.20564771e-01
-1.08985893e-01 -1.92874715e-01 -9.17488575e-01 3.03680450e-02
3.68610770e-01 4.00629461e-01 4.07109380e-01 -3.25988889e-01
6.27642572e-01 8.56717110e-01 6.11025810e-01 -6.24492705e-01
1.03295040e+00 6.26610219e-01 -1.90241501e-01 -1.13980877e+00
-3.61054689e-01 -8.09462592e-02 -6.11087799e-01 -5.44894457e-01
7.56184101e-01 -1.22654247e+00 -1.12647474e+00 5.64636350e-01
-1.15735388e+00 -1.29904881e-01 1.16453106e-02 3.27744544e-01
-8.08401823e-01 4.12889630e-01 -3.22018057e-01 -7.34728217e-01
-2.80327052e-01 -1.34386027e+00 1.46705997e+00 1.04709873e-02
-2.50389159e-01 -6.31628931e-01 -4.77284640e-02 6.36046410e-01
3.07195425e-01 1.73343405e-01 2.00700685e-01 5.38008893e-03
-6.19690955e-01 -3.85560021e-02 2.97052979e-01 2.33893245e-01
3.70418340e-01 7.79305920e-02 -1.43341160e+00 -4.11125571e-01
2.30527535e-01 -3.55114460e-01 4.89565283e-01 3.63595575e-01
1.30116343e+00 -7.08183110e-01 -2.59376198e-01 1.08745646e+00
8.66988719e-01 -9.96827185e-02 5.29720783e-01 -4.03590977e-01
8.71532857e-01 9.92615461e-01 3.41945559e-01 5.28484821e-01
6.47923410e-01 1.22060156e+00 3.50388438e-01 1.02294907e-01
-4.18048710e-01 -6.25417411e-01 6.67402625e-01 9.98891473e-01
-3.76964472e-02 -2.88592577e-02 -5.76151788e-01 3.58505815e-01
-1.52351999e+00 -1.15854633e+00 3.77980590e-01 2.16947651e+00
1.17400420e+00 -4.29446310e-01 1.09262615e-01 2.08996087e-01
8.98801506e-01 1.43904895e-01 -4.79228348e-01 2.03011453e-01
-9.95071977e-02 -2.75147930e-02 -6.91982433e-02 6.75998271e-01
-7.75135458e-01 8.58903766e-01 5.30268145e+00 8.44044745e-01
-1.49880481e+00 2.10949227e-01 4.78175610e-01 -4.74303693e-01
-5.39147973e-01 -2.64248610e-01 -8.69981706e-01 6.42518878e-01
7.33979166e-01 -2.45183095e-01 5.02136707e-01 8.21121633e-01
5.40337026e-01 4.29843187e-01 -1.12622786e+00 1.47146952e+00
4.29365754e-01 -1.27288651e+00 1.08503684e-01 2.12847233e-01
4.90796715e-01 -4.79431391e-01 3.50953460e-01 4.42467891e-02
-3.53355020e-01 -1.04596436e+00 9.82468486e-01 6.52533054e-01
1.55769730e+00 -7.40142286e-01 -5.28354489e-04 1.37959838e-01
-1.29888976e+00 8.50765854e-02 -1.60829619e-01 3.00180793e-01
2.21058145e-01 3.52088898e-01 -8.35907578e-01 4.48495746e-01
7.38461971e-01 5.63839614e-01 -2.06841961e-01 6.04612648e-01
-2.18516454e-01 1.93841219e-01 -3.35478514e-01 3.75320017e-01
-5.53583026e-01 -1.28529653e-01 5.78893006e-01 7.96015322e-01
6.04771793e-01 1.37944566e-02 -7.29889944e-02 8.77921879e-01
-2.21038252e-01 9.61864144e-02 -9.61055934e-01 3.18731338e-01
7.17363656e-01 1.42707145e+00 -1.41907662e-01 4.02591266e-02
-1.03991508e-01 9.24498916e-01 5.04460977e-03 4.06265616e-01
-9.61440265e-01 -1.01744235e-01 1.16422665e+00 3.48040879e-01
1.35791302e-01 -2.05249950e-01 -1.85412001e-02 -1.41789520e+00
1.31468758e-01 -1.01096094e+00 -1.99085191e-01 -8.81970406e-01
-8.94523978e-01 7.11196601e-01 -4.28678142e-03 -1.54667640e+00
-6.12334609e-01 -3.17075670e-01 -6.21564090e-01 7.89890110e-01
-1.23176575e+00 -1.51479197e+00 -4.92046893e-01 1.12007618e+00
5.35550117e-01 -1.09763950e-01 8.85946512e-01 4.42639291e-01
-5.36004841e-01 1.22763228e+00 -2.81930238e-01 1.03729837e-01
1.10377312e+00 -7.42049813e-01 1.79122351e-02 3.98957044e-01
1.20934352e-01 6.02589846e-01 7.64353633e-01 -2.67390370e-01
-1.74190652e+00 -9.38034415e-01 6.49999440e-01 -4.99380499e-01
2.92232364e-01 -8.41265082e-01 -6.15445435e-01 5.30948043e-01
1.88371986e-01 6.65034279e-02 6.10206485e-01 -2.56015629e-01
-2.92405814e-01 -4.48191047e-01 -1.04822826e+00 8.34199727e-01
1.33945954e+00 -8.33846271e-01 -1.70238927e-01 3.21209580e-01
7.15239227e-01 -4.79611248e-01 -8.31153929e-01 3.99687707e-01
7.53925264e-01 -1.00219071e+00 1.09261525e+00 -8.62897839e-03
1.56267732e-01 -3.88626963e-01 -1.31655470e-01 -1.11959755e+00
1.41688108e-01 -1.19480205e+00 -2.86001451e-02 1.74646163e+00
6.04613386e-02 -6.45267487e-01 6.18904889e-01 3.89001876e-01
-1.12768948e-01 -6.28579915e-01 -1.15251100e+00 -5.10866880e-01
-4.15276103e-02 -4.88476902e-01 7.99118459e-01 9.09962893e-01
4.95638438e-02 3.30206543e-01 -7.13583529e-01 3.12398821e-01
8.14860880e-01 4.05807123e-02 1.16020703e+00 -9.61893141e-01
-2.09188573e-02 -2.64661044e-01 -2.80052483e-01 -1.05120718e+00
5.38626134e-01 -6.78502798e-01 -2.39497330e-02 -1.01106262e+00
-7.76101798e-02 -2.24443242e-01 2.73691058e-01 3.57124597e-01
1.05316073e-01 4.00027275e-01 2.36184686e-01 2.93965846e-01
-5.08145764e-02 1.06346726e+00 1.42498362e+00 4.26974567e-03
-1.37020186e-01 -1.18140476e-02 -5.76965868e-01 6.58814311e-01
7.81885445e-01 -9.74005088e-02 -6.68774784e-01 -3.66663665e-01
-7.12083951e-02 4.88232523e-01 4.64176267e-01 -8.87728393e-01
3.17305237e-01 -5.65732308e-02 3.63794357e-01 -3.11633199e-01
1.11094916e+00 -6.59721673e-01 4.30038929e-01 7.44032040e-02
-2.20827073e-01 -1.77952051e-01 5.53590879e-02 3.51366222e-01
-2.34579951e-01 2.04970747e-01 7.82686651e-01 6.16338626e-02
-1.47630066e-01 6.19534612e-01 4.78011928e-02 -5.05156666e-02
9.37281787e-01 -3.70376259e-01 4.53903563e-02 -9.94651377e-01
-7.99003839e-01 4.07168083e-03 6.33473516e-01 6.36392951e-01
7.04035103e-01 -1.62814116e+00 -6.91980124e-01 5.95241427e-01
4.41805236e-02 -6.28363946e-03 5.82941473e-01 7.67896295e-01
-8.70237350e-02 2.13189468e-01 -9.70320255e-02 -8.22991431e-01
-1.35503423e+00 4.73594040e-01 3.30921799e-01 5.47312140e-01
-6.08688533e-01 7.80407131e-01 5.12340426e-01 -3.41426969e-01
3.76278222e-01 1.86443195e-01 -1.37606084e-01 3.98331195e-01
5.51087976e-01 1.42155932e-02 -1.34448886e-01 -1.07370174e+00
-3.04715842e-01 1.00182128e+00 3.32350492e-01 -3.47692251e-01
1.17974114e+00 -4.90104020e-01 1.20252810e-01 2.45184183e-01
1.44760108e+00 4.17891651e-01 -1.43944967e+00 8.31725895e-02
-6.45884156e-01 -5.16716003e-01 -1.99039474e-01 -1.54158771e-01
-1.32150292e+00 1.06190002e+00 5.20131350e-01 -2.26075396e-01
1.27516770e+00 1.45352241e-02 6.09619021e-01 1.17947556e-01
5.40426254e-01 -8.35730910e-01 3.32630724e-01 1.10193148e-01
1.50316548e+00 -1.10655880e+00 -4.16481018e-01 -5.99391758e-01
-6.26464605e-01 1.05837500e+00 5.72101295e-01 4.31818217e-01
7.96905875e-01 2.66173691e-01 2.38139048e-01 1.58014461e-01
-6.07845306e-01 -1.15413070e-01 2.33801425e-01 9.05021787e-01
3.12106431e-01 -8.40614885e-02 1.10619098e-01 5.15149415e-01
-8.35513413e-01 -1.58949330e-01 3.60654831e-01 3.46375704e-01
3.95838022e-02 -9.60234523e-01 -6.97247028e-01 -2.02766642e-01
-2.53189862e-01 -1.36892376e-02 -9.36674476e-02 5.76467395e-01
1.08625904e-01 9.83209789e-01 -7.94973038e-03 -5.35879135e-01
1.35368899e-01 1.84969336e-01 5.23259461e-01 -4.03946370e-01
-6.46367371e-02 3.26088846e-01 -7.45039135e-02 -6.92912519e-01
-2.57411867e-01 -6.68226242e-01 -8.84052694e-01 -4.20326024e-01
-1.01533972e-01 -2.63252072e-02 6.92669988e-01 4.46513772e-01
6.09890938e-01 2.35264316e-01 1.03796732e+00 -1.53724825e+00
-4.94625688e-01 -9.54339385e-01 -3.67650777e-01 4.61559862e-01
5.36876917e-01 -8.33635509e-01 -7.20404148e-01 3.25376928e-01] | [13.195780754089355, -0.39867645502090454] |
01469439-2216-4475-9d39-d1191f663791 | stock-trend-prediction-a-semantic | 2303.09323 | null | https://arxiv.org/abs/2303.09323v1 | https://arxiv.org/pdf/2303.09323v1.pdf | Stock Trend Prediction: A Semantic Segmentation Approach | Market financial forecasting is a trending area in deep learning. Deep learning models are capable of tackling the classic challenges in stock market data, such as its extremely complicated dynamics as well as long-term temporal correlation. To capture the temporal relationship among these time series, recurrent neural networks are employed. However, it is difficult for recurrent models to learn to keep track of long-term information. Convolutional Neural Networks have been utilized to better capture the dynamics and extract features for both short- and long-term forecasting. However, semantic segmentation and its well-designed fully convolutional networks have never been studied for time-series dense classification. We present a novel approach to predict long-term daily stock price change trends with fully 2D-convolutional encoder-decoders. We generate input frames with daily prices for a time-frame of T days. The aim is to predict future trends by pixel-wise classification of the current price frame. We propose a hierarchical CNN structure to encode multiple price frames to multiscale latent representation in parallel using Atrous Spatial Pyramid Pooling blocks and take that temporal coarse feature stacks into account in the decoding stages. Our hierarchical structure of CNNs makes it capable of capturing both long and short-term temporal relationships effectively. The effect of increasing the input time horizon via incrementing parallel encoders has been studied with interesting and substantial changes in the output segmentation masks. We achieve overall accuracy and AUC of %78.18 and 0.88 for joint trend prediction over the next 20 days, surpassing other semantic segmentation approaches. We compared our proposed model with several deep models specifically designed for technical analysis and found that for different output horizons, our proposed models outperformed other models. | ['Nader Bagherzadeh', 'Shima Nabiee'] | 2023-03-09 | null | null | null | null | ['stock-trend-prediction'] | ['time-series'] | [-3.80365014e-01 -4.49715912e-01 -1.50286049e-01 -2.53038317e-01
-4.70674545e-01 -7.57120550e-01 7.44249403e-01 -2.80083209e-01
-2.09229425e-01 5.32113969e-01 2.92737335e-01 -3.86887670e-01
1.12978630e-01 -1.02735388e+00 -6.86933815e-01 -5.27648330e-01
-5.63317657e-01 -2.81299818e-02 1.91163465e-01 -2.20178008e-01
3.30568820e-01 3.42371911e-01 -1.53295970e+00 5.29946327e-01
3.14264327e-01 1.70855653e+00 9.88535360e-02 7.81389654e-01
-5.15153587e-01 1.12570703e+00 -5.39791465e-01 -3.69732916e-01
7.89324641e-01 -1.43294886e-01 -3.14593792e-01 1.58141688e-01
1.19370155e-01 -5.42286098e-01 -3.77480358e-01 7.42255270e-01
2.42391303e-01 -1.97781771e-01 4.08075899e-01 -8.41205180e-01
-6.22788310e-01 7.08095074e-01 -7.52908826e-01 9.12767351e-01
-1.55281082e-01 5.62721118e-02 1.05952346e+00 -6.46264136e-01
5.23898363e-01 8.10039282e-01 9.09492910e-01 7.78686106e-02
-9.72204387e-01 -8.52236807e-01 2.98207551e-01 3.19937989e-02
-8.08493972e-01 -1.34724110e-01 9.29907262e-01 -7.57377267e-01
1.32215357e+00 3.76815610e-02 9.05973911e-01 8.03764343e-01
8.91747177e-01 7.37072945e-01 1.12527335e+00 9.48052630e-02
2.14632004e-02 -3.55821103e-01 1.44483700e-01 3.35811466e-01
-1.86177984e-01 2.88587034e-01 -4.01517242e-01 1.61913559e-01
9.92171943e-01 4.94446874e-01 1.70030549e-01 3.96870553e-01
-1.25729203e+00 6.85272098e-01 3.46949697e-01 6.76154852e-01
-6.85986102e-01 5.24635792e-01 5.62316775e-01 7.60442972e-01
9.21585560e-01 2.92373896e-01 -9.50842440e-01 -2.89951324e-01
-1.58363557e+00 4.25616443e-01 6.83788955e-01 4.75441545e-01
5.92627704e-01 5.69124877e-01 -1.63618371e-01 3.65573645e-01
-5.69049716e-02 3.18203032e-01 1.14146161e+00 -6.43387794e-01
4.57958788e-01 5.82304895e-01 8.19630250e-02 -1.02177620e+00
-7.06797361e-01 -1.04242706e+00 -9.78807867e-01 4.59439248e-01
3.80521595e-01 -4.72805679e-01 -1.09043014e+00 1.25467777e+00
-2.40307450e-01 6.20535314e-01 2.51845598e-01 5.62989652e-01
4.18845028e-01 1.16125870e+00 -9.60807800e-02 -4.38633084e-01
1.41155529e+00 -8.87308300e-01 -6.91986442e-01 1.63368434e-01
4.85358208e-01 -9.70822811e-01 5.14856339e-01 8.01168233e-02
-1.10452783e+00 -7.46695459e-01 -9.57875252e-01 5.66270240e-02
-6.37072623e-01 1.66537374e-01 5.99930465e-01 3.00719589e-01
-1.00277197e+00 9.14971173e-01 -9.68868792e-01 2.72385687e-01
2.55263597e-01 3.38814735e-01 2.02987149e-01 8.35485101e-01
-1.38350654e+00 5.88864982e-01 3.09831023e-01 3.74997944e-01
-6.50461912e-01 -8.51335466e-01 -5.36380589e-01 1.88655362e-01
-1.55915096e-01 -4.92803752e-01 1.38745141e+00 -1.14115381e+00
-1.55457211e+00 6.15770221e-01 -1.19159594e-01 -1.22050965e+00
7.16517985e-01 -9.57219303e-02 -6.56309307e-01 -1.75303385e-01
1.09234266e-02 5.50655723e-01 1.07445741e+00 -2.49153614e-01
-9.21674311e-01 -2.15685457e-01 -3.97204012e-02 1.18898772e-01
-3.13290119e-01 3.29194404e-02 -1.25822246e-01 -1.35131884e+00
1.77835777e-01 -6.58259928e-01 -3.68943840e-01 -3.05739641e-01
1.86279729e-01 1.62899960e-02 1.10030353e+00 -9.51275110e-01
1.28368878e+00 -1.81757009e+00 -3.81914169e-01 -1.53153926e-01
2.91036330e-02 -2.46652942e-02 1.82940930e-01 1.58754706e-01
-2.63472050e-01 2.45379098e-02 -2.50579536e-01 -3.43699455e-01
7.42813339e-03 5.95526211e-02 -1.06851149e+00 1.91182390e-01
2.27947116e-01 1.42839217e+00 -3.44022244e-01 3.30965668e-02
2.52613157e-01 3.06080133e-01 -2.30330929e-01 6.15819544e-02
-4.92351502e-01 4.18405145e-01 -1.84347704e-01 4.27778125e-01
6.11127734e-01 -3.23906004e-01 -2.71121234e-01 1.19973840e-02
-6.16249740e-01 3.11947465e-01 -8.95511448e-01 1.39125550e+00
-5.13504684e-01 7.71227121e-01 -4.71270204e-01 -1.07546949e+00
1.12559772e+00 5.80155373e-01 7.70293891e-01 -1.24580836e+00
5.04128262e-02 5.51005900e-01 -2.75515586e-01 -1.76940531e-01
6.63794458e-01 -5.09553552e-01 -2.24477291e-01 3.54983240e-01
-1.73172310e-01 1.46855593e-01 1.39477447e-01 -5.18038452e-01
7.40504861e-01 2.48640046e-01 -5.85280731e-02 -2.10754752e-01
3.91440004e-01 2.28317469e-01 6.27064228e-01 2.98200071e-01
4.38486636e-02 7.13478386e-01 5.85189462e-01 -1.22452700e+00
-1.29781914e+00 -6.60063148e-01 -1.76026955e-01 6.62359953e-01
-2.98962027e-01 -1.59154553e-02 -2.89766014e-01 -2.34502137e-01
-3.69007364e-02 4.08596188e-01 -6.48061991e-01 4.06415313e-01
-7.77660131e-01 -1.15989971e+00 3.59991610e-01 6.13059402e-01
8.24590743e-01 -1.17902648e+00 -1.08610940e+00 7.29883850e-01
1.89167872e-01 -1.16084945e+00 -2.64824986e-01 2.51169175e-01
-1.25997126e+00 -6.73345745e-01 -1.44205785e+00 -6.17395222e-01
5.07516339e-02 -2.40888238e-01 1.04553592e+00 -5.36986530e-01
-1.18704982e-01 -1.56619608e-01 -1.63921162e-01 -3.69300485e-01
5.14784781e-03 2.38726929e-01 -3.74040484e-01 1.34700611e-01
2.62305051e-01 -6.84408963e-01 -8.24850678e-01 1.06601655e-01
-8.10596228e-01 2.75585085e-01 3.66501927e-01 6.42462373e-01
5.64945519e-01 3.59199852e-01 6.48224175e-01 -4.70416099e-01
6.17894828e-01 -5.55714905e-01 -1.12684667e+00 -2.21796818e-02
-5.73408425e-01 5.57148196e-02 6.76097453e-01 -2.11645082e-01
-9.59248066e-01 -1.53314203e-01 -2.94659317e-01 -5.73090494e-01
2.23655775e-01 7.29349673e-01 7.35702395e-01 5.60978234e-01
-5.48690446e-02 5.16206086e-01 -2.37159804e-01 -4.77439731e-01
7.10660545e-03 3.74115169e-01 4.37985837e-01 -1.95612609e-01
5.23352683e-01 6.12051249e-01 -1.10447630e-01 -5.46906412e-01
-6.88171685e-01 -3.85282665e-01 -5.57989717e-01 -9.47971493e-02
1.05631864e+00 -1.23809719e+00 -4.64607805e-01 1.04575622e+00
-1.10628033e+00 -2.65044451e-01 -4.26343143e-01 4.42403644e-01
-5.34918904e-01 5.11657484e-02 -1.02848840e+00 -8.87875319e-01
-6.39982760e-01 -9.79579687e-01 8.71678174e-01 1.05728523e-03
-1.29484877e-01 -1.26743364e+00 1.48934081e-01 -1.02930605e-01
7.15790749e-01 6.79224551e-01 6.78430378e-01 -4.73017216e-01
-6.49014711e-01 -3.85483831e-01 -2.71623015e-01 4.01486307e-01
9.74709913e-02 -1.91685960e-01 -9.84742582e-01 -1.87734049e-03
3.12824428e-01 2.29698613e-01 1.26100993e+00 8.49072933e-01
9.19304848e-01 -3.31138372e-01 1.35018483e-01 7.55725265e-01
1.44902158e+00 6.45704925e-01 6.85152531e-01 5.91939569e-01
5.00379682e-01 4.62539762e-01 1.53463602e-01 4.99825150e-01
3.26073766e-01 3.53380531e-01 2.14134917e-01 -6.94307387e-02
9.26108211e-02 -3.69187333e-02 5.61828256e-01 9.72422421e-01
-2.00370312e-01 1.52122185e-01 -8.82211268e-01 5.60885310e-01
-1.83777165e+00 -1.22016764e+00 -5.72803952e-02 1.76465893e+00
5.12808502e-01 6.05149329e-01 1.30586460e-01 1.59171939e-01
4.34880793e-01 5.98615050e-01 -6.47716641e-01 -4.75297332e-01
-3.92153382e-01 1.28014475e-01 7.74614215e-01 2.57308573e-01
-1.44809604e+00 7.16254771e-01 6.26511574e+00 5.88448882e-01
-1.60230982e+00 -2.24972125e-02 1.28081393e+00 -1.76806767e-02
-2.99709886e-01 -2.17335209e-01 -1.02641523e+00 6.71987772e-01
1.31242406e+00 -1.91894665e-01 -6.78766519e-02 7.27568030e-01
4.42709357e-01 3.32338750e-01 -5.75384140e-01 8.51212680e-01
-4.02963161e-01 -1.99664974e+00 1.27369910e-01 7.47088566e-02
1.09136820e+00 1.33036584e-01 4.67570990e-01 3.49236339e-01
2.68468540e-02 -9.43731308e-01 1.09667301e+00 8.32220674e-01
4.11295444e-01 -7.53776371e-01 8.85183930e-01 2.47339666e-01
-1.66221285e+00 -4.15952563e-01 -2.20980749e-01 -6.02277637e-01
3.13828051e-01 7.34914780e-01 -2.80183464e-01 4.72969085e-01
7.86336303e-01 1.25433850e+00 -1.67175069e-01 7.02971339e-01
4.22490120e-01 5.38149118e-01 -4.70539749e-01 2.73555994e-01
8.99544001e-01 -2.02930510e-01 2.91206956e-01 1.10708332e+00
8.40113997e-01 -2.82357651e-04 -3.31649147e-02 7.87618637e-01
1.33629292e-01 -2.86376644e-02 -4.24099714e-01 -2.22974688e-01
-3.84941608e-01 6.69224858e-01 -9.71437633e-01 -5.68769336e-01
-7.79355168e-01 9.37578976e-01 -2.19668224e-01 4.64386344e-01
-9.07369852e-01 -9.81549993e-02 7.30981171e-01 2.42033169e-01
7.22120404e-01 -4.90056843e-01 -5.76237023e-01 -1.53508890e+00
2.08894745e-01 -3.51279706e-01 6.04294837e-01 -5.72658062e-01
-1.06293321e+00 8.53288591e-01 -1.84579343e-01 -1.57145011e+00
-4.73240286e-01 -6.67943537e-01 -7.50039160e-01 1.02516663e+00
-1.99306810e+00 -1.15757656e+00 2.25601122e-01 4.46647018e-01
1.13445795e+00 -4.19788748e-01 5.08659720e-01 2.19265088e-01
-5.13621330e-01 2.60760589e-05 4.02353615e-01 2.62721568e-01
-2.81630643e-02 -1.12742758e+00 9.57091391e-01 1.02897418e+00
1.12286471e-01 2.40323886e-01 6.10632837e-01 -7.02538013e-01
-8.00330281e-01 -1.21263933e+00 9.43017423e-01 -2.14860588e-02
1.13430381e+00 -1.44413158e-01 -8.87499988e-01 7.52217114e-01
2.84476817e-01 -1.53461536e-02 2.47376263e-01 -4.11024868e-01
-2.53166318e-01 -2.41050065e-01 -6.55299783e-01 2.77319074e-01
3.80789906e-01 -4.36941892e-01 -8.63332868e-01 -6.98337853e-02
6.99888110e-01 -3.50153834e-01 -6.92729712e-01 3.01726490e-01
6.92255735e-01 -1.18786037e+00 8.15743566e-01 -2.43145544e-02
7.61496007e-01 -1.30675212e-01 -8.31880569e-02 -8.73937964e-01
-1.62987098e-01 -6.95328236e-01 -2.84585148e-01 7.96394348e-01
6.09486580e-01 -7.50038683e-01 9.59484518e-01 3.87555391e-01
-5.11596352e-02 -8.22314322e-01 -9.64299142e-01 -7.66238093e-01
3.55337232e-01 -7.10380495e-01 8.47931623e-01 9.15043950e-01
-3.03072363e-01 -9.74589735e-02 -4.97704297e-01 1.91707298e-01
3.29425037e-01 7.57193983e-01 1.50728017e-01 -1.07429302e+00
-1.70556456e-01 -8.54432583e-01 -4.89391029e-01 -1.24418521e+00
2.20177695e-02 -6.07645392e-01 -6.51163161e-01 -1.39926350e+00
-3.50435644e-01 -1.03402376e-01 -6.40560508e-01 1.17366962e-01
2.83435166e-01 3.78741562e-01 2.06213035e-02 6.06740773e-01
-5.05274944e-02 4.45520699e-01 1.14949977e+00 -1.99766368e-01
-2.47049049e-01 2.29156569e-01 2.22760141e-02 7.03202069e-01
9.32629347e-01 -1.24796771e-01 -2.40025938e-01 -3.18583548e-01
3.79120857e-01 3.35241288e-01 4.14692998e-01 -1.12678289e+00
2.13590100e-01 7.80642480e-02 7.27294862e-01 -1.17786264e+00
1.91196382e-01 -8.74199688e-01 4.73377615e-01 7.99317420e-01
-2.40528211e-01 6.83444142e-01 4.22465742e-01 4.99727547e-01
-7.97369242e-01 6.65006787e-02 4.70385194e-01 -5.01708090e-01
-1.22499728e+00 4.56472754e-01 -5.66463053e-01 -3.86912256e-01
1.14029396e+00 -4.42401797e-01 5.67864105e-02 -4.35231090e-01
-1.02090263e+00 1.31136730e-01 1.26821212e-02 6.33318186e-01
3.43248457e-01 -1.14667761e+00 -6.29371822e-01 3.30284148e-01
-3.49068880e-01 -3.08759391e-01 3.61036479e-01 7.66952455e-01
-9.01196480e-01 8.64071727e-01 -3.64007324e-01 -4.29227114e-01
-7.08000541e-01 5.34919381e-01 7.12437570e-01 -6.69269025e-01
-1.01863623e+00 6.19581759e-01 3.24001074e-01 1.00614980e-01
3.37200500e-02 -1.18134093e+00 -4.23161626e-01 7.27378964e-01
5.68592489e-01 2.02578038e-01 5.97335584e-02 -5.36937416e-01
8.60401765e-02 1.05672181e+00 -5.64869791e-02 -1.52496062e-02
1.69176698e+00 -2.49283433e-01 6.30558410e-04 8.68909597e-01
1.37344944e+00 -5.69124103e-01 -1.67861855e+00 -7.67566860e-02
4.73517001e-01 8.62941444e-02 1.36092305e-01 -3.77854079e-01
-1.45159435e+00 9.84039009e-01 6.94262326e-01 5.31505108e-01
1.20346475e+00 -4.72756147e-01 1.46914983e+00 1.75444074e-02
1.72608688e-01 -9.77993190e-01 -1.72972098e-01 7.17713892e-01
6.77177966e-01 -1.06012440e+00 -3.32248002e-01 8.31960812e-02
-5.25881708e-01 1.57862747e+00 -6.69852570e-02 -5.69186032e-01
1.09507370e+00 4.44413543e-01 3.54307592e-01 -2.60577887e-01
-1.06310487e+00 -1.75484583e-01 2.99931228e-01 -2.81832337e-01
5.72324693e-01 1.64738856e-02 6.45003887e-03 4.83042628e-01
-4.83433306e-01 1.45838961e-01 3.01821977e-01 7.40812480e-01
-2.96274751e-01 -6.87584877e-01 -2.16546580e-01 5.13041437e-01
-1.06242883e+00 -1.05777085e-01 4.49679673e-01 5.47103226e-01
4.12586518e-02 4.37923908e-01 7.83495426e-01 -1.32175952e-01
1.82076231e-01 3.10585529e-01 -1.76132604e-01 -2.62743533e-01
-8.88866544e-01 5.20682454e-01 -2.14430362e-01 -3.43894064e-01
-5.44850290e-01 -7.78594315e-01 -1.14001524e+00 -2.11016491e-01
2.52482802e-01 -4.92924601e-02 5.06463408e-01 8.94831598e-01
2.05231577e-01 6.95171773e-01 7.22701550e-01 -8.95508468e-01
-3.48060906e-01 -6.93989575e-01 -7.58897424e-01 2.68901438e-01
8.00272942e-01 -2.85423964e-01 -2.81895161e-01 5.17830312e-01] | [4.4412126541137695, 4.242918491363525] |
da092d61-415e-422b-b56e-41f0b907c61a | never-a-dull-moment-distributional-properties | 2303.17809 | null | https://arxiv.org/abs/2303.17809v1 | https://arxiv.org/pdf/2303.17809v1.pdf | Never a Dull Moment: Distributional Properties as a Baseline for Time-Series Classification | The variety of complex algorithmic approaches for tackling time-series classification problems has grown considerably over the past decades, including the development of sophisticated but challenging-to-interpret deep-learning-based methods. But without comparison to simpler methods it can be difficult to determine when such complexity is required to obtain strong performance on a given problem. Here we evaluate the performance of an extremely simple classification approach -- a linear classifier in the space of two simple features that ignore the sequential ordering of the data: the mean and standard deviation of time-series values. Across a large repository of 128 univariate time-series classification problems, this simple distributional moment-based approach outperformed chance on 69 problems, and reached 100% accuracy on two problems. With a neuroimaging time-series case study, we find that a simple linear model based on the mean and standard deviation performs better at classifying individuals with schizophrenia than a model that additionally includes features of the time-series dynamics. Comparing the performance of simple distributional features of a time series provides important context for interpreting the performance of complex time-series classification models, which may not always be required to obtain high accuracy. | ['Ben D. Fulcher', 'Annie G. Bryant', 'Trent Henderson'] | 2023-03-31 | null | null | null | null | ['time-series-classification'] | ['time-series'] | [ 3.58826011e-01 -3.93821001e-01 -1.02370001e-01 -5.60394466e-01
-6.54419482e-01 -5.84069550e-01 9.75895107e-01 7.20459402e-01
-6.38605952e-01 5.64558804e-01 1.69210896e-01 -7.34308302e-01
-6.86607420e-01 -3.12287688e-01 -1.75166517e-01 -8.07452202e-01
-6.11429691e-01 4.49663341e-01 -2.51162589e-01 -1.81513637e-01
3.44042420e-01 4.77327436e-01 -1.52103496e+00 3.79375666e-01
5.07439435e-01 1.17576170e+00 -1.26909196e-01 3.34679574e-01
-7.00403452e-02 2.49105096e-01 -6.12973511e-01 8.72466788e-02
3.31928246e-02 -4.09793913e-01 -4.83793080e-01 -2.78438091e-01
1.26837611e-01 -2.13348061e-01 1.05131743e-02 6.50452614e-01
5.44325531e-01 -4.06591734e-03 9.36324120e-01 -1.14742529e+00
-4.74128455e-01 3.52382421e-01 -4.14934665e-01 8.35210860e-01
3.44179481e-01 1.96667239e-01 1.27758801e+00 -1.61393180e-01
4.06889588e-01 1.02272058e+00 1.12344360e+00 -1.21543527e-01
-1.60854900e+00 -3.76094729e-01 7.34511912e-02 1.25742659e-01
-9.65907633e-01 -3.41008842e-01 6.39732718e-01 -8.55531216e-01
1.18900537e+00 2.38480523e-01 8.50514472e-01 1.10267663e+00
5.20058930e-01 2.55059272e-01 1.41127384e+00 -2.83333898e-01
3.06746930e-01 -3.69857669e-01 4.90708470e-01 2.49046490e-01
2.09153593e-01 1.80086270e-01 -1.93534985e-01 -7.49332666e-01
4.28827375e-01 1.09911703e-01 1.55790448e-02 -3.85545306e-02
-1.36313295e+00 7.00700700e-01 4.20720652e-02 8.65606368e-01
-3.57456595e-01 -9.35207680e-02 9.31561410e-01 7.39955127e-01
9.00525689e-01 6.59870684e-01 -7.60566056e-01 -5.43114722e-01
-1.10728800e+00 4.91651416e-01 5.96458673e-01 -4.64830287e-02
8.81181657e-02 1.37959803e-02 -1.36336416e-01 7.27125049e-01
-2.36003682e-01 2.00611413e-01 8.39058816e-01 -5.75798213e-01
1.37395173e-01 3.86150390e-01 1.08283609e-02 -1.08051014e+00
-9.19657230e-01 -5.34405887e-01 -6.56092584e-01 9.74765345e-02
9.42669928e-01 -2.90142924e-01 -7.77056634e-01 1.76272070e+00
-7.69549096e-03 -5.23333922e-02 -2.82430649e-01 5.85341215e-01
2.12452665e-01 2.95010358e-01 9.78402570e-02 -6.19811475e-01
1.11631608e+00 1.20271467e-01 -5.83828568e-01 -1.94321368e-02
1.03219509e+00 -3.83166820e-01 9.17262316e-01 3.64361286e-01
-7.98619032e-01 -9.53416824e-02 -8.22832227e-01 1.51137814e-01
-4.58786219e-01 -2.02366039e-01 7.74042606e-01 4.39118326e-01
-8.80038559e-01 1.04237592e+00 -1.02970648e+00 -5.65095186e-01
4.03968275e-01 3.67835760e-01 -4.99666154e-01 2.86921531e-01
-9.75321472e-01 1.05941546e+00 2.18319207e-01 -1.40526772e-01
-2.77529627e-01 -1.12730515e+00 -5.15326560e-01 5.75034320e-02
-2.97040015e-01 -4.69278634e-01 1.26634347e+00 -9.64249074e-01
-8.40052843e-01 8.49669337e-01 -1.53875902e-01 -4.55188423e-01
6.40153587e-01 2.01600298e-01 -4.28225458e-01 -1.28497750e-01
2.60006011e-01 4.46264492e-03 8.64751041e-01 -4.47003067e-01
-3.38328242e-01 -6.19653046e-01 -1.85672671e-01 -2.01466247e-01
-2.76674598e-01 1.78318962e-01 6.88848913e-01 -6.12739623e-01
2.05807641e-01 -8.66433680e-01 -1.08446069e-01 -3.85055691e-02
-8.63944292e-02 -5.65868735e-01 6.10783219e-01 -5.47574878e-01
1.21914649e+00 -2.43525314e+00 -2.12930381e-01 5.71095645e-02
3.06495875e-01 2.14266367e-02 -4.03978042e-02 6.68804526e-01
-8.15982223e-01 1.69496998e-01 -3.38825762e-01 -3.49034555e-02
4.01146635e-02 -9.44195613e-02 -4.93590474e-01 8.78740013e-01
4.35281932e-01 7.25619793e-01 -9.88752544e-01 6.70815259e-02
9.93196592e-02 3.37678403e-01 -4.65440392e-01 -3.03258806e-01
-4.58131917e-02 4.05357718e-01 -1.35282189e-01 3.45424384e-01
1.31890312e-01 -3.65208775e-01 1.31082579e-01 6.42216280e-02
-1.23663761e-01 5.60568273e-01 -5.83196700e-01 1.20463014e+00
-1.26787320e-01 1.09640121e+00 -5.41059375e-01 -1.44188249e+00
6.78180754e-01 3.77695292e-01 1.01725352e+00 -8.48712265e-01
2.11385787e-01 4.58859295e-01 8.93282056e-01 -5.74147284e-01
-2.20989227e-01 -4.22609895e-01 -5.20026572e-02 8.13587606e-01
-1.60605818e-01 -1.21811256e-02 4.51825969e-02 -3.62030506e-01
1.48224664e+00 -2.22170681e-01 3.83488476e-01 -4.75488275e-01
5.15460856e-02 6.19118884e-02 3.18260193e-01 6.32636249e-01
-2.47246698e-01 4.53952700e-01 1.01883030e+00 -7.59311318e-01
-1.22065949e+00 -9.79677439e-01 -8.01898479e-01 1.03830826e+00
-8.45658302e-01 -4.57237363e-01 -2.93495059e-01 -2.27069393e-01
3.39027196e-01 7.01587021e-01 -8.50483656e-01 -2.39481881e-01
-1.74111515e-01 -1.27062237e+00 5.73939264e-01 3.92349124e-01
-1.29528984e-01 -7.59138346e-01 -8.05534899e-01 1.82341039e-01
1.01175584e-01 -7.54523635e-01 2.90688276e-02 4.67175812e-01
-1.07127941e+00 -8.88249040e-01 -5.69976747e-01 -4.24621046e-01
4.27033782e-01 -2.93360930e-02 8.16992104e-01 -1.36401743e-01
-5.35217941e-01 4.77658212e-01 -2.22768903e-01 -7.27631211e-01
-9.34323743e-02 -5.71180284e-02 1.53566688e-01 -3.49606164e-02
6.35810971e-01 -9.76735890e-01 -4.77141470e-01 -2.43855253e-01
-7.69413412e-01 -5.03770828e-01 3.22303295e-01 9.87352312e-01
2.31304839e-01 1.49118245e-01 8.41242075e-01 -4.10686105e-01
9.12625909e-01 -9.88777101e-01 -1.55820146e-01 -1.34931549e-01
-5.67263484e-01 -4.61696349e-02 6.41512215e-01 -8.48874807e-01
-1.77157417e-01 -3.21355104e-01 5.94846494e-02 -2.59248108e-01
-8.10756832e-02 9.85371530e-01 6.35811567e-01 3.14175844e-01
6.39878750e-01 3.71956348e-01 3.88194382e-01 -5.55622578e-01
-9.98621657e-02 5.72026372e-01 2.31312752e-01 -5.03357947e-01
3.12778473e-01 5.34219444e-01 2.03779638e-01 -1.19290507e+00
-8.16041827e-01 -4.03728038e-01 -7.82860041e-01 -3.84912044e-02
6.48295999e-01 -6.43340528e-01 -5.64623177e-01 5.59201539e-01
-1.01987231e+00 -2.30781227e-01 -1.97707295e-01 6.44754648e-01
-6.83820903e-01 -2.33109724e-02 -2.79840261e-01 -7.40436733e-01
3.77928205e-02 -8.88823032e-01 1.08376503e+00 -4.76664901e-01
-9.43198621e-01 -1.39374197e+00 2.64224470e-01 -2.73474574e-01
5.38449049e-01 7.49569356e-01 1.52569234e+00 -1.30617177e+00
2.51617610e-01 -4.55200106e-01 -6.41833618e-02 1.42532647e-01
4.38131630e-01 7.99525753e-02 -9.05907393e-01 -2.42649540e-01
4.13440824e-01 -6.15003742e-02 8.27079594e-01 6.12907529e-01
1.33618212e+00 -5.62129319e-02 -2.78817892e-01 4.48585570e-01
1.07632089e+00 3.14020783e-01 1.70311362e-01 3.90480965e-01
2.87833303e-01 6.73774600e-01 2.05974042e-01 6.66125119e-01
2.45436504e-01 4.76797044e-01 6.75958069e-03 1.80909842e-01
4.36064214e-01 1.91371694e-01 2.81200320e-01 6.30153060e-01
-1.50024876e-01 2.18866631e-01 -1.36554265e+00 6.76825285e-01
-1.72624123e+00 -1.29225683e+00 -1.87408268e-01 2.23912883e+00
6.66210771e-01 3.79428208e-01 4.76961523e-01 5.84419370e-01
3.49179387e-01 3.79437029e-01 -7.79858291e-01 -5.16994953e-01
-3.28040905e-02 2.35256955e-01 5.22442199e-02 8.21943674e-03
-1.12933230e+00 6.87411577e-02 7.51645803e+00 4.49310929e-01
-1.51737392e+00 -4.03013139e-04 7.16275454e-01 -2.80059189e-01
-1.24643862e-01 -2.96312034e-01 -1.30488306e-01 6.64458573e-01
1.47967637e+00 -7.14435995e-01 2.64659464e-01 4.99812961e-01
6.48127735e-01 -1.14357226e-01 -1.68243170e+00 1.06810093e+00
-1.01917453e-01 -1.12400079e+00 -2.68207282e-01 2.46238172e-01
3.74978304e-01 3.01752657e-01 3.12191904e-01 9.42828357e-02
-1.94310129e-01 -1.26839912e+00 5.99230707e-01 5.75021088e-01
6.49296045e-01 -3.09721351e-01 4.64533687e-01 4.46287662e-01
-7.27099061e-01 -4.45450008e-01 -2.69869938e-02 -6.00049675e-01
-8.67857039e-02 8.75681937e-01 -6.75115883e-01 1.52664423e-01
6.55080080e-01 9.76910532e-01 -3.17119330e-01 1.17857897e+00
5.06651282e-01 6.92658067e-01 -5.48390627e-01 8.00293125e-03
3.67472738e-01 -5.42640351e-02 5.99262118e-01 1.17299724e+00
3.99864763e-01 1.47151649e-01 7.79379439e-03 6.25089765e-01
5.15112042e-01 7.44222701e-02 -1.03799057e+00 -5.73208213e-01
1.67112157e-01 9.46777761e-01 -7.49815285e-01 -1.27295241e-01
-5.61866403e-01 3.33326548e-01 3.10856074e-01 1.48124591e-01
-5.24185717e-01 -3.23279738e-01 8.31465006e-01 3.39562386e-01
4.74820435e-02 -6.37998760e-01 -4.33750153e-01 -9.94083047e-01
2.18043908e-01 -9.42968726e-01 5.44417560e-01 -6.09818697e-01
-1.67451632e+00 3.99097204e-01 1.14914596e-01 -1.13276303e+00
-5.11371434e-01 -6.70286417e-01 -7.43713021e-01 9.23942983e-01
-9.36492145e-01 -6.41444206e-01 1.65993318e-01 4.21369374e-01
2.37740129e-01 -1.22533724e-01 9.07347322e-01 1.94060236e-01
-2.96939135e-01 1.91504627e-01 4.52650905e-01 -6.64878730e-03
6.01200581e-01 -1.23972011e+00 2.33800858e-01 3.32425773e-01
4.11273073e-03 7.61741400e-01 8.38612318e-01 -6.14159822e-01
-1.16033244e+00 -7.58495331e-01 9.57144558e-01 -6.44760311e-01
1.34296024e+00 -2.22824201e-01 -1.04208601e+00 7.38126814e-01
-9.49856117e-02 -1.67321324e-01 9.66943562e-01 3.91525388e-01
-4.64467913e-01 -5.92548549e-02 -9.78600204e-01 5.51084161e-01
9.12191689e-01 -8.71430635e-01 -9.98340011e-01 6.57572806e-01
2.89219022e-01 1.27284363e-01 -1.14044154e+00 4.10739899e-01
8.53073299e-01 -8.45576882e-01 7.63309121e-01 -1.16744781e+00
4.86294657e-01 1.41017452e-01 -1.70368731e-01 -1.48753726e+00
-4.09702659e-01 -5.50709963e-01 2.72420317e-01 7.15615094e-01
2.53496230e-01 -9.61396933e-01 2.08332717e-01 7.27306128e-01
1.03051156e-01 -1.01924157e+00 -9.71192181e-01 -9.55949068e-01
3.96558046e-01 -6.34759188e-01 6.10092163e-01 1.20402980e+00
3.45088065e-01 7.79796168e-02 2.97398418e-01 -2.34679535e-01
4.08435225e-01 4.22791429e-02 1.23062178e-01 -1.65177333e+00
-2.43296400e-02 -9.35850859e-01 -9.31780636e-01 -1.26433209e-01
2.65452296e-01 -1.06350636e+00 -4.12071526e-01 -1.28265822e+00
9.02324636e-03 -3.71753812e-01 -5.88324428e-01 4.75725949e-01
8.60439911e-02 -1.23529136e-01 -1.64474517e-01 2.54076481e-01
-1.15345111e-02 3.16566736e-01 8.23261082e-01 -1.05270840e-01
-2.24862605e-01 7.04013556e-02 -5.57984531e-01 7.87712574e-01
7.87630260e-01 -4.54831958e-01 -6.60579443e-01 -2.99693674e-01
1.07039094e-01 1.77253887e-01 5.37400305e-01 -9.07739580e-01
-1.18228998e-02 -2.17858940e-01 7.32327223e-01 -4.20570254e-01
2.10506991e-01 -4.92485911e-01 1.52870774e-01 5.82837582e-01
-5.91889441e-01 5.94242275e-01 3.53336662e-01 4.00747478e-01
-2.74354406e-02 4.70939763e-02 4.96110588e-01 -6.93730786e-02
-3.50787044e-01 1.88119501e-01 -5.03413916e-01 7.39995986e-02
9.63921368e-01 -9.73145440e-02 -3.26720417e-01 -3.45797926e-01
-1.00627172e+00 -2.20059291e-01 1.64537057e-01 5.04941285e-01
2.07731083e-01 -1.13785803e+00 -6.49100125e-01 2.36367911e-01
7.94688910e-02 -7.56172776e-01 -4.45050932e-02 1.32973659e+00
-2.07352489e-01 5.50353885e-01 -4.88891125e-01 -8.71252775e-01
-1.08461964e+00 4.23532844e-01 4.58210588e-01 -6.77368566e-02
-7.63665438e-01 3.17013800e-01 1.14202583e-02 -2.05288023e-01
-3.93797308e-02 -5.78367829e-01 -5.41669875e-02 5.96947610e-01
6.36195660e-01 2.66254306e-01 2.84658462e-01 -4.75283027e-01
-4.93673354e-01 2.78993487e-01 -1.38207510e-01 -2.61752516e-01
1.78316462e+00 2.42847070e-01 -3.17980111e-01 1.29287899e+00
1.33439612e+00 -5.80007672e-01 -6.85075998e-01 6.05989769e-02
3.72252673e-01 -2.95122415e-01 5.83918579e-02 -6.74312651e-01
-4.82589960e-01 8.70311916e-01 4.78434712e-01 8.81264925e-01
9.65450287e-01 -2.56544411e-01 3.31332892e-01 3.60805213e-01
3.31070513e-01 -6.93762779e-01 -3.16768110e-01 5.53640246e-01
8.82121503e-01 -1.06387103e+00 1.27533227e-01 3.33810836e-01
-1.94561109e-01 1.24331129e+00 -5.79763390e-02 -2.71731138e-01
1.07305872e+00 -1.79412495e-03 -2.36258000e-01 -2.42225111e-01
-1.05173731e+00 -7.82133564e-02 3.31332654e-01 5.04544914e-01
7.06230164e-01 5.98441213e-02 -5.13519526e-01 5.61294973e-01
-4.91831928e-01 -9.37601030e-02 3.92207533e-01 8.46596777e-01
-1.73758671e-01 -9.65426505e-01 -1.91925332e-01 1.29504812e+00
-7.44519353e-01 -2.40667481e-02 -2.55180120e-01 9.09143686e-01
-8.96325260e-02 7.71645129e-01 5.75705290e-01 -2.59709924e-01
7.15652406e-02 5.82625210e-01 4.13103640e-01 -6.10247850e-01
-5.01891136e-01 -3.18256021e-02 1.90356940e-01 -5.04476786e-01
-3.60088974e-01 -1.39624047e+00 -9.53579426e-01 -4.10779774e-01
1.20076865e-01 -4.73961718e-02 7.26523161e-01 1.33368289e+00
2.75194675e-01 3.75439286e-01 4.48208511e-01 -8.36109519e-01
-7.97258496e-01 -8.73772085e-01 -6.10358953e-01 4.77728724e-01
9.33426678e-01 -6.89906478e-01 -6.37891650e-01 -1.07084490e-01] | [7.2756195068359375, 3.3372461795806885] |
4aa71f3a-405a-4f15-bd50-c7e5a1ade51d | disentanglement-via-latent-quantization | 2305.18378 | null | https://arxiv.org/abs/2305.18378v1 | https://arxiv.org/pdf/2305.18378v1.pdf | Disentanglement via Latent Quantization | In disentangled representation learning, a model is asked to tease apart a dataset's underlying sources of variation and represent them independently of one another. Since the model is provided with no ground truth information about these sources, inductive biases take a paramount role in enabling disentanglement. In this work, we construct an inductive bias towards compositionally encoding and decoding data by enforcing a harsh communication bottleneck. Concretely, we do this by (i) quantizing the latent space into learnable discrete codes with a separate scalar codebook per dimension and (ii) applying strong model regularization via an unusually high weight decay. Intuitively, the quantization forces the encoder to use a small number of latent values across many datapoints, which in turn enables the decoder to assign a consistent meaning to each value. Regularization then serves to drive the model towards this parsimonious strategy. We demonstrate the broad applicability of this approach by adding it to both basic data-reconstructing (vanilla autoencoder) and latent-reconstructing (InfoGAN) generative models. In order to reliably assess these models, we also propose InfoMEC, new metrics for disentanglement that are cohesively grounded in information theory and fix well-established shortcomings in previous metrics. Together with regularization, latent quantization dramatically improves the modularity and explicitness of learned representations on a representative suite of benchmark datasets. In particular, our quantized-latent autoencoder (QLAE) consistently outperforms strong methods from prior work in these key disentanglement properties without compromising data reconstruction. | ['Chelsea Finn', 'Jiajun Wu', 'James C. R. Whittington', 'Will Dorrell', 'Kyle Hsu'] | 2023-05-28 | null | null | null | null | ['disentanglement'] | ['methodology'] | [ 3.95624667e-01 3.51977050e-01 -3.66451740e-01 -1.42536849e-01
-6.71458185e-01 -9.69589710e-01 1.15069377e+00 -7.39767477e-02
-1.54092237e-01 7.12335050e-01 7.81419992e-01 -2.75321960e-01
-2.52087563e-01 -8.08971405e-01 -7.31714308e-01 -9.39104140e-01
-9.16199759e-02 5.34248292e-01 -6.95436418e-01 -1.11750089e-01
-4.00239648e-03 2.11328030e-01 -1.35845244e+00 1.80204868e-01
5.74392378e-01 5.06896019e-01 -9.25327316e-02 6.36641562e-01
2.07764134e-01 9.02426839e-01 -3.28785956e-01 -6.22483552e-01
2.69137174e-01 -7.14849055e-01 -6.83101833e-01 2.97794193e-02
2.96493977e-01 -4.62157905e-01 -4.04809088e-01 9.03924584e-01
1.69504598e-01 -3.72498363e-01 9.93598521e-01 -1.16939831e+00
-8.69898558e-01 9.80117917e-01 -2.86993414e-01 4.62442264e-02
9.85951796e-02 1.89508975e-01 1.75493932e+00 -7.31738091e-01
6.26562595e-01 1.17304921e+00 3.64548504e-01 5.04808545e-01
-2.13485336e+00 -6.69098914e-01 7.68758077e-03 -3.30200940e-01
-1.30173790e+00 -7.99864650e-01 8.71037424e-01 -7.52640545e-01
7.62949288e-01 4.10098851e-01 8.06499183e-01 1.55907774e+00
2.96387728e-02 6.19544923e-01 9.95666504e-01 -2.92813689e-01
4.32109028e-01 1.03655636e-01 -1.09692484e-01 6.03398085e-01
6.75843120e-01 4.22096014e-01 -5.89007735e-01 -2.95163602e-01
8.52414131e-01 8.62514228e-02 -3.26510966e-01 -8.66700113e-01
-1.45025575e+00 1.10347772e+00 4.73380595e-01 1.91311762e-01
-2.09848568e-01 4.97763395e-01 2.15107039e-01 4.63245809e-01
2.85881966e-01 7.19382048e-01 -2.79669732e-01 -2.03108415e-02
-8.87932658e-01 1.92501172e-01 8.48915935e-01 8.24886858e-01
8.08449507e-01 1.25723884e-01 6.56719282e-02 3.87833774e-01
5.31707287e-01 2.98333436e-01 3.64768237e-01 -1.05666304e+00
4.23295438e-01 5.52420855e-01 -7.73246139e-02 -1.14594662e+00
1.17794015e-01 -5.44582665e-01 -1.13084698e+00 2.93786108e-01
2.90332317e-01 -3.47463577e-03 -7.37324953e-01 2.22369814e+00
-1.47541746e-01 6.16917647e-02 2.52791733e-01 8.28129947e-01
3.67953181e-01 3.93956751e-01 -7.73311257e-02 -8.71034339e-03
1.31533062e+00 -3.62902701e-01 -5.24202943e-01 -2.73580045e-01
4.26447421e-01 -3.07397902e-01 8.02856565e-01 4.46304083e-01
-1.02952635e+00 -2.61754274e-01 -1.33535492e+00 -2.54068077e-01
-7.20145628e-02 -4.50780056e-02 8.75480115e-01 6.82048321e-01
-1.01340652e+00 5.12641966e-01 -1.00638068e+00 1.05236284e-01
4.92274046e-01 4.05912906e-01 -6.83204412e-01 2.97144484e-02
-1.03809738e+00 6.75099790e-01 3.66106540e-01 -1.35581970e-01
-1.30286252e+00 -5.12713432e-01 -8.79407525e-01 1.97549209e-01
1.51859388e-01 -1.21780062e+00 6.63353741e-01 -9.87484038e-01
-1.33757341e+00 7.53168583e-01 9.43021923e-02 -4.45435911e-01
2.90075570e-01 -4.99155484e-02 4.35007177e-02 4.51873913e-02
-1.14929743e-01 6.84057593e-01 9.92947102e-01 -1.47684431e+00
1.58639580e-01 -3.20107847e-01 2.27401435e-01 1.21233061e-01
-3.62850904e-01 -4.66783673e-01 -4.48921584e-02 -7.07824290e-01
3.13114822e-01 -8.43232393e-01 -1.49673987e-02 1.09481037e-01
-5.62183917e-01 2.03252569e-01 2.10536838e-01 -3.53160352e-01
1.04320753e+00 -2.16410947e+00 1.00964928e+00 1.36634454e-01
1.03244853e+00 -2.50680268e-01 -2.08514914e-01 5.69093943e-01
-2.98810244e-01 4.44803953e-01 -3.86059076e-01 -7.32441127e-01
2.36163303e-01 6.49120629e-01 -5.20926714e-01 6.31251633e-01
3.59360725e-01 1.08438659e+00 -9.22642052e-01 -1.50698662e-01
2.23779753e-02 6.51690662e-01 -1.20053399e+00 2.82652348e-01
-1.33356124e-01 4.07542020e-01 -1.28761396e-01 2.14955091e-01
3.88378501e-01 -4.49019790e-01 5.18774390e-01 -1.41922146e-01
2.71504372e-01 7.88607717e-01 -1.05866432e+00 1.97922325e+00
-3.21651578e-01 7.87806094e-01 2.11485866e-02 -9.83185589e-01
5.90832829e-01 3.73907179e-01 3.09447736e-01 -1.95857555e-01
1.69517338e-01 2.00971309e-02 2.01024354e-01 -2.21633866e-01
2.66039103e-01 -4.34820265e-01 -1.86759949e-01 7.57647932e-01
4.68016088e-01 -8.49448740e-02 -1.64301932e-01 6.33344710e-01
1.05718219e+00 -6.16265461e-02 5.24531424e-01 -1.93821460e-01
4.90242876e-02 -4.25658792e-01 5.41044295e-01 6.32787645e-01
1.13602690e-01 7.03621566e-01 7.92850792e-01 -1.67425066e-01
-1.33003569e+00 -1.51817369e+00 -8.87764469e-02 7.41192162e-01
-3.06536496e-01 -7.67033935e-01 -4.68645662e-01 -5.55598259e-01
1.47660524e-01 8.00442994e-01 -1.05981982e+00 -4.05064940e-01
-1.83668107e-01 -7.09418237e-01 8.10330510e-01 3.39214355e-01
-2.88617215e-03 -3.73274565e-01 -3.85465473e-01 -8.17263722e-02
-2.56792307e-01 -6.04941666e-01 -1.74396902e-01 6.55485690e-01
-8.08260739e-01 -8.85500193e-01 -2.53218204e-01 -2.87480295e-01
7.35405028e-01 2.16724183e-02 1.35650337e+00 -1.48253456e-01
-4.90478724e-02 1.08247928e-01 -1.07925467e-01 1.26250386e-01
-5.47154427e-01 7.40626827e-02 6.06293418e-02 -8.55285153e-02
3.68339360e-01 -1.12163556e+00 -5.35738349e-01 -9.01641324e-02
-1.11362457e+00 3.13823670e-01 7.52397835e-01 1.05712783e+00
2.09308803e-01 -2.70833164e-01 2.79890627e-01 -8.29087973e-01
7.09928155e-01 -9.43578005e-01 -3.77213001e-01 -8.95392969e-02
-7.08937943e-01 6.63405120e-01 4.99183297e-01 -3.89185756e-01
-5.53471446e-01 -2.01020822e-01 1.82003379e-01 -5.13825476e-01
-3.24815884e-02 4.41005498e-01 -3.32462221e-01 2.97247082e-01
7.94762015e-01 4.27917182e-01 2.02583238e-01 -4.87959236e-01
9.63569224e-01 4.07204270e-01 3.66937220e-01 -7.40898967e-01
9.21333194e-01 4.97127861e-01 -1.74378201e-01 -4.02909905e-01
-5.42670250e-01 4.03794684e-02 -7.70757973e-01 3.73277098e-01
7.72035301e-01 -1.19556141e+00 -7.08731592e-01 -1.28078535e-01
-1.05331004e+00 3.88597511e-03 -5.34214139e-01 4.73415166e-01
-6.11030221e-01 1.38280392e-01 -4.97647882e-01 -6.66203082e-01
7.51676634e-02 -1.14395678e+00 9.61122453e-01 -5.34762681e-01
-5.75660288e-01 -1.14992809e+00 5.15093088e-01 2.43211210e-01
2.30242893e-01 3.10784817e-01 1.07058465e+00 -6.16331995e-01
-7.46064007e-01 1.00790195e-01 -5.13808951e-02 3.91514659e-01
1.95406765e-01 -2.27140754e-01 -1.09438431e+00 -3.90074641e-01
5.90682663e-02 -4.65681791e-01 1.23884714e+00 -7.99194053e-02
7.79088736e-01 -7.41431952e-01 -1.36264443e-01 9.14409399e-01
1.43295944e+00 -3.88312668e-01 4.55229342e-01 -9.31369290e-02
7.91599214e-01 5.04018307e-01 -5.52045465e-01 4.56191719e-01
6.12319648e-01 4.59879339e-01 6.01085961e-01 2.01436639e-01
-4.60015051e-02 -6.06151044e-01 4.28387791e-01 1.16561913e+00
-1.07385688e-01 -2.94056028e-01 -6.63547039e-01 5.20188391e-01
-1.58102787e+00 -1.00639737e+00 2.59776741e-01 2.10748267e+00
1.27085412e+00 3.53230089e-02 -1.68972816e-02 3.00495982e-01
1.24542471e-02 5.14959216e-01 -4.97540712e-01 -2.80608624e-01
-2.48080820e-01 1.34510785e-01 3.47233742e-01 6.03387058e-01
-7.83383906e-01 5.37280142e-01 6.60466528e+00 4.75452155e-01
-9.05515790e-01 2.29809768e-02 4.13889140e-01 -4.50178087e-01
-1.26625371e+00 2.92518228e-01 -3.58087450e-01 4.79038864e-01
1.00683272e+00 -5.13430610e-02 9.26326215e-01 4.56741929e-01
-2.12984517e-01 1.94845706e-01 -1.75261784e+00 8.74852538e-01
4.21700068e-02 -1.45689774e+00 3.69237274e-01 3.95274878e-01
6.42518938e-01 7.05101416e-02 2.87913948e-01 -5.13885543e-02
9.13740575e-01 -1.46096504e+00 8.18848133e-01 4.75258023e-01
8.28669310e-01 -5.76808393e-01 1.68608263e-01 3.72182012e-01
-7.12667763e-01 -3.08526065e-02 -3.95475954e-01 -4.01555866e-01
-1.81689262e-01 7.21821070e-01 -6.36918664e-01 4.88137186e-01
3.78598794e-02 8.57953191e-01 -3.62733305e-01 2.74256349e-01
-6.03605390e-01 7.58527696e-01 -2.26069152e-01 2.41681844e-01
8.83515477e-02 -3.10994297e-01 6.30875707e-01 1.08628106e+00
-5.89836128e-02 -1.36447065e-02 -1.63810715e-01 1.58551085e+00
-3.19753766e-01 -4.28959310e-01 -9.05872047e-01 -4.33405817e-01
6.52810276e-01 1.00043094e+00 -2.49398783e-01 -2.51176417e-01
-2.98893869e-01 1.04017150e+00 6.23432219e-01 5.29214859e-01
-5.14289677e-01 3.94728705e-02 1.19521952e+00 -2.13887617e-01
3.01267058e-01 -5.40300310e-01 -5.38483381e-01 -1.67217350e+00
-1.95291162e-01 -9.62940037e-01 5.89589328e-02 -4.65840191e-01
-1.26762760e+00 3.19130957e-01 -7.92255551e-02 -1.09483838e+00
-6.74065173e-01 -3.84943277e-01 -1.31985724e-01 1.05529130e+00
-1.37396598e+00 -1.16617870e+00 1.62619054e-01 4.46368754e-01
1.24438182e-01 -1.37544215e-01 1.16634011e+00 3.81026641e-02
-5.89003801e-01 6.35266483e-01 2.38405928e-01 2.40765721e-01
4.29387450e-01 -1.49365151e+00 4.05791551e-01 7.97863841e-01
7.30342448e-01 1.33121765e+00 7.61113524e-01 -3.36589515e-01
-1.66300344e+00 -8.66884172e-01 6.86765015e-01 -8.50856841e-01
8.44704509e-01 -9.39245284e-01 -6.30032957e-01 1.06931722e+00
2.64616638e-01 -4.79983427e-02 1.14434040e+00 2.59943455e-01
-1.07439470e+00 2.29766101e-01 -7.94055820e-01 5.94777644e-01
1.08195472e+00 -9.89838243e-01 -8.50518286e-01 -1.29752725e-01
7.31646001e-01 3.55281085e-02 -8.68789971e-01 -9.27515924e-02
8.39902222e-01 -1.10295689e+00 1.07796490e+00 -7.99670458e-01
8.90331566e-01 -2.14270338e-01 -5.26377082e-01 -1.45766342e+00
-6.21850669e-01 -6.94130898e-01 -3.91028583e-01 1.10812378e+00
3.03701133e-01 -7.21760631e-01 6.25839233e-01 4.80152607e-01
2.67068595e-01 -6.86545789e-01 -7.11026609e-01 -4.82962817e-01
4.95151460e-01 -4.51394558e-01 5.70922971e-01 1.23696446e+00
1.15716502e-01 4.86718744e-01 -5.43292701e-01 1.74186379e-01
8.49982560e-01 6.40247017e-02 7.14465022e-01 -1.20710111e+00
-7.30281293e-01 -4.81544048e-01 -5.62348485e-01 -1.33689690e+00
1.20700911e-01 -1.37146080e+00 -2.93184340e-01 -1.05710900e+00
5.44105291e-01 -3.93991977e-01 -3.30499113e-01 5.14346421e-01
-5.51869534e-02 3.87160659e-01 1.61968917e-01 5.91941774e-01
-2.49332920e-01 7.22890556e-01 9.07680571e-01 -1.37400627e-01
2.16090143e-01 -5.32469749e-01 -1.31172049e+00 5.38993716e-01
5.34083605e-01 -6.40317023e-01 -6.72784090e-01 -7.41772294e-01
7.86047280e-01 -3.28168571e-02 7.63828397e-01 -5.36214113e-01
1.71731129e-01 -1.24661133e-01 4.28939760e-01 7.30038583e-02
3.93988490e-01 -7.61302114e-01 3.44617903e-01 4.03398216e-01
-7.57514238e-01 -1.31918579e-01 -1.70506805e-01 6.81521297e-01
-5.41370213e-02 1.81632176e-01 4.68238205e-01 -9.51661915e-02
-1.13219157e-01 1.05504535e-01 -2.83823609e-01 2.79513806e-01
6.10741079e-01 -1.25083432e-01 -2.55574465e-01 -4.03108746e-01
-6.67228043e-01 -1.42469585e-01 7.01417744e-01 2.67455548e-01
5.71565032e-01 -1.44698620e+00 -7.86372542e-01 7.74263442e-01
2.14560971e-01 -1.33350134e-01 -2.81258970e-01 6.49597526e-01
-9.10075530e-02 4.24606711e-01 -2.04354152e-01 -5.25401533e-01
-7.79467702e-01 4.65895832e-01 2.08632052e-01 -8.91479254e-02
-4.24625903e-01 8.89692843e-01 4.05083686e-01 -3.67228508e-01
-2.49873307e-02 -4.86539990e-01 1.15121201e-01 2.20622107e-01
2.48523593e-01 1.36656135e-01 -2.35790670e-01 -5.08842230e-01
-2.62831807e-01 2.09941968e-01 -1.95122268e-02 -3.50489080e-01
1.43950355e+00 -2.15009332e-01 -2.38294914e-01 7.03865707e-01
1.46580362e+00 2.85814285e-01 -1.44481456e+00 -2.75082201e-01
-1.99267104e-01 -3.88963997e-01 1.37151122e-01 -7.01754689e-01
-8.45155001e-01 1.03609538e+00 3.20200436e-02 2.78873593e-01
8.41856658e-01 1.50873929e-01 2.11513147e-01 2.20559940e-01
2.85077065e-01 -3.14212441e-01 2.47967288e-01 2.60841578e-01
8.61006796e-01 -1.08222032e+00 4.59275283e-02 -1.98052749e-02
-4.63046372e-01 9.54892159e-01 -1.11060336e-01 -3.90575916e-01
4.41920459e-01 5.23904264e-01 -3.05199564e-01 -3.38404745e-01
-1.18641341e+00 -2.10269894e-02 4.83233541e-01 4.53848571e-01
4.94874537e-01 2.59338021e-01 2.53671408e-02 5.34972131e-01
-5.97285628e-01 -2.76225686e-01 4.36284423e-01 4.72707331e-01
-1.69750825e-01 -1.12141991e+00 -3.63063179e-02 2.87662774e-01
-3.02927226e-01 -3.88706237e-01 -5.98402083e-01 7.28411376e-01
1.30079523e-01 7.59277761e-01 1.73017353e-01 -5.27010322e-01
-3.09801996e-01 2.03619781e-03 5.14896214e-01 -6.68827295e-01
-2.60907620e-01 1.50587945e-03 -4.51891497e-02 -5.44020355e-01
-2.72846788e-01 -6.31029606e-01 -7.89127886e-01 -4.61905807e-01
-2.03458533e-01 9.33704600e-02 5.32192767e-01 8.83124769e-01
5.51839054e-01 5.43205976e-01 5.56934953e-01 -6.95601642e-01
-8.56279314e-01 -7.67506361e-01 -4.18059766e-01 5.31885028e-01
7.83893585e-01 -6.40253663e-01 -6.77027464e-01 1.26830816e-01] | [9.24084186553955, 4.810962200164795] |
5f3e2bc3-3bb2-4fb7-b8f9-ff573c08f01f | implicit-view-time-interpolation-of-stereo | 2303.17181 | null | https://arxiv.org/abs/2303.17181v1 | https://arxiv.org/pdf/2303.17181v1.pdf | Implicit View-Time Interpolation of Stereo Videos using Multi-Plane Disparities and Non-Uniform Coordinates | In this paper, we propose an approach for view-time interpolation of stereo videos. Specifically, we build upon X-Fields that approximates an interpolatable mapping between the input coordinates and 2D RGB images using a convolutional decoder. Our main contribution is to analyze and identify the sources of the problems with using X-Fields in our application and propose novel techniques to overcome these challenges. Specifically, we observe that X-Fields struggles to implicitly interpolate the disparities for large baseline cameras. Therefore, we propose multi-plane disparities to reduce the spatial distance of the objects in the stereo views. Moreover, we propose non-uniform time coordinates to handle the non-linear and sudden motion spikes in videos. We additionally introduce several simple, but important, improvements over X-Fields. We demonstrate that our approach is able to produce better results than the state of the art, while running in near real-time rates and having low memory and storage costs. | ['Nima Khademi Kalantari', 'Andrii Tsarov', 'Avinash Paliwal'] | 2023-03-30 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Paliwal_Implicit_View-Time_Interpolation_of_Stereo_Videos_Using_Multi-Plane_Disparities_and_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Paliwal_Implicit_View-Time_Interpolation_of_Stereo_Videos_Using_Multi-Plane_Disparities_and_CVPR_2023_paper.pdf | cvpr-2023-1 | ['video-enhancement', 'video-frame-interpolation'] | ['computer-vision', 'computer-vision'] | [ 1.15420133e-01 -2.85039097e-01 2.13123053e-01 -3.81418645e-01
-6.87197566e-01 -5.58809876e-01 5.65782189e-01 -2.47000739e-01
-2.72874296e-01 6.68952942e-01 4.86196168e-02 -1.25097290e-01
7.23872706e-02 -5.60042262e-01 -1.13003802e+00 -2.26050988e-01
8.49477574e-02 1.65010437e-01 6.37915611e-01 -8.55698362e-02
5.76605558e-01 6.70872808e-01 -1.90125668e+00 4.44109470e-01
6.74831033e-01 1.13256824e+00 1.38597310e-01 8.15641284e-01
1.58332348e-01 7.50115514e-01 -2.97326773e-01 -3.45336765e-01
5.84747136e-01 -5.21823585e-01 -8.39329362e-01 1.95853710e-01
1.08947551e+00 -7.82888651e-01 -4.37704504e-01 8.11909378e-01
2.90799022e-01 -1.84514769e-03 1.90923035e-01 -1.14186192e+00
-2.62262136e-01 -2.20700353e-01 -6.45395517e-01 6.64875805e-02
7.73621321e-01 1.32313848e-01 3.02264094e-01 -9.36177850e-01
9.33616221e-01 1.17618167e+00 1.05005157e+00 5.02208054e-01
-1.19919693e+00 -3.54272634e-01 -7.66915977e-02 3.22473258e-01
-1.50584877e+00 -5.57187557e-01 5.21732926e-01 -4.96782720e-01
1.00777924e+00 4.35337037e-01 6.80542946e-01 7.06888318e-01
2.29056001e-01 3.37267548e-01 1.14002419e+00 -5.23180485e-01
1.13221131e-01 -1.22090332e-01 -2.50767082e-01 5.52447617e-01
-1.05910420e-01 2.81169534e-01 -7.91918814e-01 1.13431690e-02
1.39559519e+00 -4.86410595e-02 -4.81470019e-01 -6.09328210e-01
-1.39442062e+00 3.61921489e-01 3.82805884e-01 1.03657030e-01
-2.71127671e-01 3.95671725e-01 1.77423149e-01 6.19766228e-02
4.46278065e-01 1.55013189e-01 -4.36240673e-01 -3.14190507e-01
-1.08056879e+00 3.77086043e-01 3.15106928e-01 1.24879146e+00
9.66627657e-01 -3.09377760e-01 1.91852093e-01 2.73877621e-01
1.29355460e-01 3.38590562e-01 4.41002138e-02 -1.75090122e+00
6.06894076e-01 2.29354203e-01 3.84947836e-01 -1.00677192e+00
-2.29638517e-01 1.98006123e-01 -4.36285198e-01 6.71786427e-01
6.52490020e-01 1.47561178e-01 -6.51215553e-01 1.45503640e+00
2.93638378e-01 4.26675022e-01 -1.38153180e-01 1.03512335e+00
3.79776806e-01 5.98769546e-01 -2.61457562e-01 -1.45616308e-01
9.70132351e-01 -9.21885848e-01 -5.76459527e-01 -1.12989828e-01
2.87382007e-01 -8.99418533e-01 1.02341938e+00 3.55690479e-01
-1.56263459e+00 -6.50931656e-01 -9.67359185e-01 -5.57141662e-01
-4.74663600e-02 5.53642064e-02 4.94642079e-01 3.47842246e-01
-1.46311426e+00 1.01592386e+00 -9.98249590e-01 -3.27072561e-01
1.01293072e-01 4.97670978e-01 -4.50039059e-01 2.40205768e-02
-6.43225491e-01 9.23022330e-01 1.82997938e-02 -8.00377578e-02
-3.81218433e-01 -9.13575649e-01 -7.79833674e-01 -5.80366142e-02
2.23786652e-01 -8.00614357e-01 1.36685979e+00 -1.09770513e+00
-1.55495095e+00 9.29243326e-01 -4.45290983e-01 -1.55787423e-01
7.56532133e-01 -5.14622390e-01 1.37701409e-03 2.46941641e-01
-3.15620154e-02 9.17325318e-01 4.08859462e-01 -1.39701474e+00
-8.26566219e-01 -3.62467587e-01 3.09616238e-01 2.76642382e-01
-7.51029477e-02 -1.36367440e-01 -8.16134810e-01 -4.67835039e-01
2.16956735e-01 -9.34210360e-01 -2.65861511e-01 6.39392197e-01
-1.38194293e-01 2.30190679e-01 7.89196074e-01 -5.59413314e-01
8.78567994e-01 -2.24706674e+00 1.70419425e-01 -1.00808786e-02
9.28782448e-02 1.07573599e-01 2.94037879e-01 2.07298324e-01
8.98867752e-03 -3.10226828e-01 -2.38742195e-02 -6.54706478e-01
-2.27584824e-01 3.56661111e-01 -4.92517024e-01 5.08612871e-01
-1.73801053e-02 5.57210624e-01 -9.21675026e-01 -3.12629342e-01
6.23504341e-01 9.23369229e-01 -7.31319547e-01 2.24036649e-01
1.13181137e-02 8.15513372e-01 8.85199979e-02 3.31932276e-01
1.01416063e+00 -2.68525332e-02 7.03993067e-02 -3.30852389e-01
-6.21352375e-01 4.76494491e-01 -1.30278957e+00 2.12651443e+00
-3.89316827e-01 9.50114548e-01 9.58975852e-02 -3.45567286e-01
5.03280580e-01 1.42704949e-01 5.95054209e-01 -7.44795322e-01
-4.83832210e-02 4.91794318e-01 -6.70466959e-01 -2.80569255e-01
6.91592574e-01 -8.03119782e-03 4.31412429e-01 1.60789371e-01
-1.11508956e-02 -1.89946190e-01 5.96700758e-02 -1.82343796e-01
7.46983409e-01 6.05141342e-01 2.35257924e-01 -2.56736845e-01
6.58395886e-01 -1.86068118e-02 4.42165822e-01 3.25473189e-01
2.27773841e-02 1.13070953e+00 4.45428312e-01 -7.84189105e-01
-1.26685631e+00 -1.11517560e+00 -7.34526291e-02 5.45541048e-01
6.67844176e-01 -6.15592301e-01 -7.78501332e-01 -3.46174300e-01
-1.45480558e-01 4.23316002e-01 -3.84802133e-01 3.22792411e-01
-9.52485919e-01 1.26180621e-02 2.36797437e-01 8.49645019e-01
4.34958518e-01 -5.67812383e-01 -1.20865524e+00 2.82029454e-02
-2.34711289e-01 -1.24214923e+00 -6.21220171e-01 2.20644455e-02
-1.18561935e+00 -1.12144184e+00 -7.60197520e-01 -5.58512628e-01
7.31024325e-01 5.33228517e-01 1.28215027e+00 -1.61639042e-02
-1.62760615e-02 3.48461181e-01 -1.47217698e-02 1.23626590e-01
-9.43764746e-02 -3.15163910e-01 -3.66085172e-02 -2.38744438e-01
2.67622530e-01 -5.57121754e-01 -8.96731019e-01 4.76309121e-01
-9.64421809e-01 3.67610663e-01 -5.39955758e-02 5.33831477e-01
7.93761969e-01 -4.16803539e-01 -3.44528049e-01 -4.19912249e-01
1.81796644e-02 1.00946669e-02 -1.08259773e+00 -5.62223140e-03
-4.19609636e-01 1.04012355e-01 6.02047145e-01 -1.87898293e-01
-8.78873944e-01 4.48673129e-01 -2.34398305e-01 -6.46155715e-01
-6.69838339e-02 -2.10990503e-01 1.89870432e-01 -4.19407934e-01
5.72568297e-01 -7.65826255e-02 -8.26696157e-02 -5.19264042e-01
3.15658003e-01 3.07080150e-01 7.79754162e-01 -3.69592756e-01
5.41708648e-01 9.39515710e-01 1.66714787e-01 -5.24661779e-01
-5.86787999e-01 -4.04187530e-01 -9.70357180e-01 -3.45375150e-01
8.87905002e-01 -9.80084062e-01 -7.44206011e-01 3.91201347e-01
-1.53853154e+00 -3.95244926e-01 -3.25343907e-01 5.28587520e-01
-1.06132472e+00 5.22657692e-01 -6.65206730e-01 -4.63194907e-01
1.07767038e-01 -1.40809953e+00 1.44300437e+00 2.56822407e-01
-1.40854284e-01 -8.59282136e-01 2.73246974e-01 -2.94366740e-02
4.03642625e-01 3.61936063e-01 3.35933149e-01 4.35319066e-01
-1.12225282e+00 2.34502628e-01 -2.54528016e-01 1.08381413e-01
3.46650034e-02 1.04072191e-01 -1.05461025e+00 -1.94470316e-01
1.49996206e-01 -6.91283643e-02 4.37873930e-01 4.49871987e-01
1.20770681e+00 -1.06137715e-01 -2.52827674e-01 1.19405425e+00
1.72917068e+00 1.22198969e-01 9.67265069e-01 5.67884803e-01
6.75671160e-01 6.34043992e-01 6.27473474e-01 3.97663772e-01
6.09737396e-01 1.18967795e+00 4.88161802e-01 -1.47341684e-01
-2.76695102e-01 -1.85558125e-01 3.07836562e-01 6.32161856e-01
-5.85550547e-01 1.43715858e-01 -7.45131493e-01 4.53594089e-01
-1.86058736e+00 -9.24163163e-01 -5.67217648e-01 2.60231304e+00
6.81826115e-01 -1.86572030e-01 6.51928484e-02 1.59614697e-01
5.31097353e-01 -7.95171112e-02 -2.53311068e-01 -3.56830388e-01
-1.01537481e-01 1.97800443e-01 8.30210626e-01 8.88648033e-01
-1.01687491e+00 6.56228244e-01 7.30881596e+00 1.74105957e-01
-1.39574873e+00 1.35578811e-01 3.71455133e-01 -2.17829615e-01
-2.42236972e-01 8.85516182e-02 -6.16155744e-01 5.00970483e-01
7.36130714e-01 1.81600507e-02 6.20486557e-01 7.34933615e-01
9.41349417e-02 -2.29544729e-01 -1.39957023e+00 1.34654903e+00
1.82180122e-01 -1.50237811e+00 -3.44866246e-01 3.08944229e-02
9.06817138e-01 1.42223179e-01 2.88753938e-02 -3.70494395e-01
-1.62908480e-01 -7.67690957e-01 1.10498989e+00 5.28281808e-01
1.17651033e+00 -6.73280358e-01 4.81645912e-01 1.92443043e-01
-1.13691759e+00 2.42044553e-01 -4.21404958e-01 -2.82053590e-01
3.64838779e-01 3.18763852e-01 -3.14211845e-01 5.92758536e-01
9.03269529e-01 6.08448803e-01 -5.85252345e-01 1.20312810e+00
-4.14997041e-02 -2.38186121e-01 -4.26260769e-01 5.35367906e-01
1.53525487e-01 -2.15003505e-01 1.73685342e-01 1.00847888e+00
7.93543577e-01 6.54809996e-02 -1.61181584e-01 7.24185824e-01
2.21435264e-01 -2.93796927e-01 -7.95669079e-01 7.04378605e-01
1.05616622e-01 6.72421157e-01 -5.61979651e-01 -5.13313532e-01
-7.09655464e-01 1.34229457e+00 2.42230788e-01 3.43087703e-01
-1.03170836e+00 -1.25210106e-01 8.06582332e-01 5.46609342e-01
3.74459356e-01 -5.80491066e-01 -5.51344097e-01 -1.38853180e+00
4.25947964e-01 -6.02808416e-01 6.93835989e-02 -1.11341679e+00
-7.52865016e-01 7.36497819e-01 7.53599927e-02 -1.70743072e+00
-5.78681648e-01 -7.41685748e-01 -1.17085226e-01 8.94379973e-01
-1.83458865e+00 -7.50219226e-01 -6.93766356e-01 7.69690037e-01
4.52531517e-01 5.25286078e-01 8.33953202e-01 5.56622207e-01
2.41658136e-01 2.72391260e-01 2.66927928e-01 -3.36064637e-01
8.99313331e-01 -1.18315852e+00 6.58827960e-01 9.41522837e-01
-3.04984413e-02 5.15866280e-01 6.82247758e-01 -2.94391066e-01
-1.47969425e+00 -7.67344832e-01 1.10192490e+00 -6.72243059e-01
1.84062883e-01 -2.10730046e-01 -7.37091124e-01 9.68354702e-01
2.98572302e-01 3.43148738e-01 2.66951680e-01 -3.29531163e-01
-3.04854691e-01 -2.48069599e-01 -1.13432813e+00 5.29945731e-01
1.08408070e+00 -6.57034159e-01 -3.41727048e-01 1.62127346e-01
3.39392036e-01 -1.11810219e+00 -6.13266289e-01 1.81544915e-01
6.21843636e-01 -1.84316838e+00 1.25727832e+00 -8.78415182e-02
6.51778340e-01 -6.09512269e-01 -1.60121620e-01 -1.03451133e+00
-2.00639501e-01 -7.32786298e-01 -1.91549137e-01 7.78499424e-01
-1.58433050e-01 -4.11142379e-01 9.06161487e-01 8.27783823e-01
-1.09890856e-01 -4.36132640e-01 -1.20589197e+00 -7.10439086e-01
-1.95714101e-01 -3.66615683e-01 4.25869256e-01 7.34889328e-01
-7.37952143e-02 -8.94476026e-02 -5.46132624e-01 1.75217420e-01
6.93964422e-01 1.99695632e-01 9.46510613e-01 -8.00782323e-01
-2.52301753e-01 -1.80011988e-01 -6.77664638e-01 -1.55915833e+00
-3.32630485e-01 -2.48105273e-01 8.93047750e-02 -1.25560522e+00
-8.69366899e-02 -4.28910881e-01 1.38184339e-01 -2.47737975e-03
-1.35449365e-01 7.20164359e-01 4.37999278e-01 1.49629265e-01
-4.56953257e-01 1.69462398e-01 1.18631458e+00 2.74005145e-01
-1.63959607e-01 -2.02783823e-01 -2.05715105e-01 8.33660722e-01
4.80034709e-01 -2.57356018e-01 -2.82781869e-01 -1.16531992e+00
2.12202653e-01 2.76845753e-01 5.86227596e-01 -1.31470513e+00
3.66345227e-01 -1.12277947e-01 5.06766975e-01 -9.98676181e-01
6.95951581e-01 -1.09839928e+00 6.18612409e-01 2.69849688e-01
-4.54870344e-04 5.34682691e-01 2.30557576e-01 1.44039661e-01
-2.14782670e-01 -1.17070034e-01 8.53817105e-01 -1.60823464e-01
-6.45064235e-01 1.55261919e-01 -2.38168873e-02 -2.47469008e-01
1.13454843e+00 -4.07396585e-01 -1.90681815e-01 -3.70184660e-01
-4.70631421e-01 -5.38244061e-02 1.24994683e+00 2.30504394e-01
6.65445030e-01 -1.52659833e+00 -3.33540708e-01 5.09153664e-01
-6.52048439e-02 1.68689772e-01 2.51132727e-01 8.17257822e-01
-1.36419916e+00 5.13966262e-01 -4.27332222e-01 -9.92829502e-01
-1.27942657e+00 5.87921321e-01 3.09844315e-01 8.05557594e-02
-6.87001467e-01 6.27438962e-01 2.79457480e-01 -1.08556740e-01
3.42681080e-01 -6.62848353e-01 2.69304544e-01 -4.74205732e-01
7.37271786e-01 5.58939219e-01 1.31282523e-01 -7.66123712e-01
-4.65305060e-01 1.22388446e+00 3.59213978e-01 -2.97485024e-01
1.26610684e+00 -4.10908341e-01 -1.21907726e-01 3.72865349e-01
1.22968411e+00 2.34200329e-01 -1.89136398e+00 1.13900296e-01
-1.62737638e-01 -1.09414554e+00 -1.41165987e-01 -4.28188473e-01
-1.01391387e+00 1.02211082e+00 6.62286103e-01 8.09046626e-02
1.33361769e+00 -9.59212333e-02 9.10590410e-01 -6.27462640e-02
5.04027188e-01 -8.00041616e-01 -3.38816464e-01 5.11030316e-01
6.99331045e-01 -1.07225752e+00 9.20412168e-02 -7.40798652e-01
-2.91134238e-01 1.48938489e+00 6.34260297e-01 -2.92882025e-01
2.77404010e-01 4.37995106e-01 2.81910956e-01 -3.73225249e-02
-5.52773595e-01 3.71676986e-03 1.38424769e-01 7.67377257e-01
5.08445978e-01 -4.05462652e-01 -2.44111568e-01 -3.28037709e-01
-3.35460603e-02 3.11931252e-01 5.21064103e-01 8.89239192e-01
-7.13133663e-02 -1.27177036e+00 -6.79897428e-01 -2.90308744e-01
-4.05128926e-01 -8.36080778e-03 -1.64578259e-01 7.73699045e-01
2.68028378e-01 6.04002118e-01 3.69761258e-01 -3.16796511e-01
5.40494263e-01 -3.09127152e-01 9.25470710e-01 -1.29161417e-01
-4.55620289e-01 2.07899481e-01 -1.74659103e-01 -1.22481549e+00
-7.92372882e-01 -4.97880429e-01 -1.07249331e+00 -5.00486612e-01
-3.82061512e-03 -2.70039797e-01 5.56510925e-01 6.24553800e-01
5.33482909e-01 2.06033766e-01 6.67669535e-01 -1.44766557e+00
-2.51235396e-01 -3.48447055e-01 -1.23586327e-01 5.80004156e-01
6.32834613e-01 -5.81143618e-01 -3.20933491e-01 4.93591696e-01] | [8.947684288024902, -2.4884588718414307] |
8d6bdd3c-0333-49e2-b301-95ed8c977755 | heartspot-privatized-and-explainable-data | 2210.02241 | null | https://arxiv.org/abs/2210.02241v1 | https://arxiv.org/pdf/2210.02241v1.pdf | HeartSpot: Privatized and Explainable Data Compression for Cardiomegaly Detection | Advances in data-driven deep learning for chest X-ray image analysis underscore the need for explainability, privacy, large datasets and significant computational resources. We frame privacy and explainability as a lossy single-image compression problem to reduce both computational and data requirements without training. For Cardiomegaly detection in chest X-ray images, we propose HeartSpot and four spatial bias priors. HeartSpot priors define how to sample pixels based on domain knowledge from medical literature and from machines. HeartSpot privatizes chest X-ray images by discarding up to 97% of pixels, such as those that reveal the shape of the thoracic cage, bones, small lesions and other sensitive features. HeartSpot priors are ante-hoc explainable and give a human-interpretable image of the preserved spatial features that clearly outlines the heart. HeartSpot offers strong compression, with up to 32x fewer pixels and 11x smaller filesize. Cardiomegaly detectors using HeartSpot are up to 9x faster to train or at least as accurate (up to +.01 AUC ROC) when compared to a baseline DenseNet121. HeartSpot is post-hoc explainable by re-using existing attribution methods without requiring access to the original non-privatized image. In summary, HeartSpot improves speed and accuracy, reduces image size, improves privacy and ensures explainability. Source code: https://www.github.com/adgaudio/HeartSpot | ['Aurélio Campilho', 'Christos Faloutsos', 'Asim Smailagic', 'Alex Gaudio', 'Shreshta Mohan', 'Elvin Johnson'] | 2022-10-05 | null | null | null | null | ['data-compression'] | ['time-series'] | [ 2.38823116e-01 6.69354975e-01 -2.68502444e-01 -6.28113091e-01
-8.83074760e-01 -5.49543619e-01 -9.68302265e-02 3.48258942e-01
-3.39863151e-01 7.57619083e-01 3.22402388e-01 -4.69845086e-01
-1.14106476e-01 -6.26733005e-01 -8.98988664e-01 -4.58057314e-01
9.32449698e-02 5.46314120e-01 -2.41168484e-01 3.88661355e-01
-2.68627107e-01 5.50966740e-01 -9.44358528e-01 4.25675660e-01
5.05681694e-01 9.84522641e-01 -1.32757336e-01 1.09169841e+00
3.91190559e-01 9.80698228e-01 -2.17845604e-01 -5.58276594e-01
5.26374698e-01 -3.65825444e-01 -1.00016451e+00 3.92602421e-02
7.25951552e-01 -1.07669449e+00 -6.72556102e-01 6.12047255e-01
6.23498559e-01 -4.93110240e-01 3.40993255e-01 -1.09998536e+00
-6.60935223e-01 5.92103779e-01 -5.99994361e-01 3.45938802e-01
-9.62447971e-02 3.19599360e-01 7.85030067e-01 -8.08208525e-01
6.98240638e-01 6.08176768e-01 1.10982239e+00 7.21761763e-01
-1.20025635e+00 -7.00396359e-01 -7.20795691e-01 -2.29246885e-01
-1.26732552e+00 -2.08891720e-01 3.56485069e-01 -3.57703120e-01
6.21380091e-01 9.91059065e-01 6.22885942e-01 9.45027947e-01
2.75378376e-01 4.13190931e-01 8.07039678e-01 -2.34919339e-01
-2.69437302e-02 2.75949650e-02 9.12991315e-02 1.08662832e+00
4.32293504e-01 6.40286505e-02 -3.42954725e-01 -3.80297512e-01
1.06252944e+00 6.31950915e-01 -4.26535130e-01 -4.19033319e-01
-1.30027521e+00 8.08013499e-01 5.41953623e-01 -2.02586100e-01
-3.60749841e-01 4.23935622e-01 5.02672017e-01 1.92775317e-02
2.88792521e-01 5.19240141e-01 -4.88893360e-01 8.41144100e-02
-1.14209187e+00 1.29512191e-01 4.62311715e-01 1.09040308e+00
5.56587100e-01 -2.34509602e-01 -1.32726222e-01 4.18531507e-01
-5.24100885e-02 5.98971426e-01 2.23522782e-01 -1.26297450e+00
5.63065588e-01 4.45345402e-01 -3.83772880e-01 -9.18345869e-01
-5.94389498e-01 -2.68966824e-01 -1.32790589e+00 1.12265587e-01
3.98140043e-01 -2.16398552e-01 -1.04668796e+00 1.50188303e+00
3.23181063e-01 -1.78126901e-01 -3.26190501e-01 1.10668635e+00
9.47830081e-01 3.43832433e-01 1.67358443e-01 1.96782857e-01
1.78134096e+00 -6.06145859e-01 -3.13394397e-01 7.51667693e-02
6.49110973e-01 -5.41428626e-01 1.15082777e+00 3.11458200e-01
-1.27420163e+00 -2.36299977e-01 -9.42119479e-01 -5.20940304e-01
6.79565743e-02 1.47119805e-01 4.99318451e-01 6.54855669e-01
-9.59292114e-01 8.05277050e-01 -1.00937021e+00 -1.91306546e-01
1.21117115e+00 5.05449057e-01 -7.10871398e-01 -1.04575299e-01
-8.39766502e-01 5.20889699e-01 1.91446736e-01 -3.72107178e-01
-7.45810211e-01 -1.31428158e+00 -7.64495015e-01 2.91189760e-01
2.50140220e-01 -1.10047805e+00 9.20940697e-01 -7.32840776e-01
-5.42792618e-01 1.34020805e+00 2.57784933e-01 -8.39840353e-01
9.80383694e-01 -2.38630474e-01 -5.17478436e-02 7.90319502e-01
7.02274591e-02 9.70656395e-01 8.12801540e-01 -7.94663012e-01
-3.07905614e-01 -2.52886504e-01 -2.67149389e-01 -3.27322111e-02
-3.61474872e-01 -1.66045085e-01 -4.84974563e-01 -9.63676572e-01
6.06099255e-02 -1.11273313e+00 -1.32786825e-01 9.98549998e-01
-8.29942107e-01 5.03535271e-01 8.44269156e-01 -1.07332373e+00
7.94158280e-01 -2.26996851e+00 -6.25388086e-01 1.21849857e-01
1.19516385e+00 2.26913974e-01 2.49962002e-01 -9.09352303e-02
-4.10505772e-01 6.40287876e-01 -5.85199952e-01 -3.50705445e-01
-1.88698813e-01 4.14149582e-01 -1.50514573e-01 7.67798066e-01
1.62029296e-01 1.02260971e+00 -5.70261002e-01 -9.47319627e-01
4.72251624e-01 7.25406229e-01 -7.61719763e-01 8.54183510e-02
1.88279599e-01 4.69542414e-01 -2.83754408e-01 6.47741497e-01
9.44334388e-01 -7.12879181e-01 9.45044532e-02 -6.83470517e-02
4.17277098e-01 -1.36445742e-02 -7.52632141e-01 1.60587060e+00
-2.05717981e-01 7.72401214e-01 1.07575171e-01 -5.07751882e-01
6.81286216e-01 4.84470010e-01 7.28323340e-01 -2.83574343e-01
2.31976539e-01 6.65826537e-03 -4.38639820e-01 -5.58576524e-01
1.83721185e-01 -3.17775071e-01 8.95585269e-02 7.22665966e-01
-2.10457847e-01 -1.06027201e-01 -3.73124570e-01 3.75596642e-01
1.40355670e+00 -3.64598095e-01 3.58687878e-01 -1.91211358e-01
8.87594000e-02 2.11286601e-02 5.76046169e-01 7.90855408e-01
-3.17261785e-01 1.54899859e+00 4.91527855e-01 -1.02426481e+00
-1.53614175e+00 -1.10168886e+00 -3.07388514e-01 7.50526965e-01
-1.73111796e-01 -1.66721493e-01 -8.18393171e-01 -9.64643955e-01
1.28445596e-01 5.65200627e-01 -7.64808476e-01 1.64578762e-02
-8.59520793e-01 -4.27505821e-01 8.90659869e-01 7.49157310e-01
3.93975139e-01 -1.00941777e+00 -1.06441271e+00 -1.99067444e-01
-2.97618806e-01 -7.95415938e-01 -7.57977605e-01 2.74101973e-01
-9.36516345e-01 -1.29303896e+00 -9.11895931e-01 -4.67701614e-01
1.06125867e+00 -2.11508229e-01 1.36753368e+00 6.79938734e-01
-1.11383259e+00 2.30835527e-01 -2.80474294e-02 -4.50411469e-01
-4.52004611e-01 3.74489464e-02 -2.77063847e-01 -5.17093301e-01
-1.27845705e-01 -4.12971109e-01 -9.76737142e-01 3.30003388e-02
-8.63000870e-01 2.13817790e-01 4.09991741e-01 9.46934044e-01
1.05761409e+00 -1.48783654e-01 -6.17988929e-02 -1.38540339e+00
1.31696403e-01 -4.30434376e-01 -1.36876002e-01 4.63707782e-02
-7.93004394e-01 -1.17736533e-01 7.34912038e-01 -2.53891367e-02
-7.71174848e-01 3.52517605e-01 7.87786860e-03 -7.91074574e-01
-2.58535117e-01 -2.16612041e-01 2.38801390e-01 8.00594538e-02
8.45022738e-01 8.68963003e-02 3.74257654e-01 -3.36133540e-01
3.43013257e-01 3.92681271e-01 9.31590497e-01 -2.36686289e-01
6.69991851e-01 8.79544258e-01 9.94566530e-02 -5.34204304e-01
-6.87017500e-01 -1.95612863e-01 -7.01079369e-01 1.91202119e-01
1.04201615e+00 -7.75270045e-01 -7.26424038e-01 -2.12498784e-01
-9.20249820e-01 5.92855625e-02 -9.35096204e-01 5.12771308e-01
-4.66460049e-01 5.64756751e-01 -7.95748055e-01 -2.25910515e-01
-1.06116915e+00 -8.89698327e-01 8.63414228e-01 -2.73230020e-02
-5.42634785e-01 -7.60072768e-01 -2.35113397e-01 5.97982585e-01
2.39670470e-01 7.52117038e-01 1.03792655e+00 -7.53209472e-01
-6.24866903e-01 -3.20530087e-01 -4.58160132e-01 4.21347171e-01
-4.09379341e-02 -7.41916448e-02 -9.27220702e-01 -3.18116874e-01
1.63209602e-01 -3.45216662e-01 6.88380361e-01 6.85801923e-01
1.86046457e+00 -6.70227587e-01 -2.48754084e-01 1.26076734e+00
1.32405770e+00 -3.21527958e-01 5.46614647e-01 6.49041906e-02
7.68109560e-01 3.91029000e-01 2.85185486e-01 7.69550741e-01
2.75207102e-01 -3.15571204e-02 7.40234017e-01 -9.21865284e-01
-3.75052989e-01 -2.95867264e-01 -5.69706738e-01 2.26533934e-01
1.58053353e-01 -2.08312318e-01 -1.06566882e+00 5.77444255e-01
-1.34149742e+00 -7.84522414e-01 -5.61994255e-01 2.01332998e+00
8.09704661e-01 -2.09217355e-01 2.43791565e-02 -6.57006279e-02
7.97561526e-01 -2.50640139e-02 -7.93432593e-01 -2.17964694e-01
-3.56173404e-02 4.18291807e-01 1.08384728e+00 2.24029586e-01
-1.13811886e+00 2.54757851e-01 6.49224710e+00 3.31118345e-01
-1.07826650e+00 3.05912226e-01 1.33586884e+00 -5.29969096e-01
-3.10737550e-01 -1.26346350e-01 -8.64044875e-02 4.79702562e-01
5.40194929e-01 -8.04877505e-02 1.84852749e-01 1.11772525e+00
-1.14243235e-02 2.75797874e-01 -1.21883988e+00 1.18123603e+00
-3.57939377e-02 -1.96672571e+00 -1.45225346e-01 2.23463625e-01
4.17329878e-01 1.34658173e-01 2.31582016e-01 -3.40773344e-01
-5.47790267e-02 -1.31745803e+00 5.78713775e-01 4.89535660e-01
1.53611112e+00 -7.72526145e-01 7.65836120e-01 1.04704924e-01
-7.35103250e-01 8.40359405e-02 -5.47755361e-01 3.48192543e-01
-1.01237372e-01 5.56030691e-01 -1.31153417e+00 1.85272634e-01
1.02025104e+00 4.04612243e-01 -4.91548896e-01 6.88054562e-01
-3.37890163e-02 7.42255032e-01 -5.43890238e-01 3.53897035e-01
-8.39696452e-02 3.69727343e-01 4.03857768e-01 1.13397503e+00
2.42936000e-01 5.37965596e-01 -2.13961169e-01 1.01148295e+00
-4.34734762e-01 1.94077268e-02 -4.03155357e-01 3.70999306e-01
4.71844226e-01 1.15535772e+00 -7.46104896e-01 -5.25979400e-01
-6.43794984e-02 9.29246247e-01 -1.29759982e-01 -1.77625895e-01
-1.05248058e+00 -2.42099524e-01 3.92738998e-01 7.49986827e-01
3.42776388e-01 4.27254796e-01 -1.04816878e+00 -9.06095266e-01
6.59435987e-02 -8.64717424e-01 7.90706515e-01 -8.63397419e-01
-1.03233361e+00 6.81198537e-01 -3.32034767e-01 -1.22530496e+00
5.87391257e-02 -2.72700340e-01 -4.26201969e-01 7.28266597e-01
-1.13641393e+00 -1.19667470e+00 -6.80940866e-01 6.60633087e-01
2.38574311e-01 1.77908279e-02 9.61320400e-01 3.02985430e-01
-3.85885596e-01 8.67963016e-01 1.11423070e-02 4.12844777e-01
6.31829619e-01 -1.40170932e+00 4.98201013e-01 6.50351882e-01
-6.68196008e-02 6.03417575e-01 4.86814559e-01 -5.80130756e-01
-1.11100030e+00 -1.26184201e+00 7.92314708e-01 -7.57371008e-01
-1.97799169e-02 -2.69301236e-01 -9.01635230e-01 7.59737074e-01
1.40601685e-02 7.50251412e-01 8.30641568e-01 -3.26430976e-01
-3.18988889e-01 -1.25784919e-01 -1.69593322e+00 1.75852820e-01
6.38732314e-01 -3.90760690e-01 -3.63604397e-01 7.49310374e-01
5.26960909e-01 -7.55621493e-01 -1.12082577e+00 1.88084140e-01
4.35251951e-01 -1.11303818e+00 1.16178679e+00 -3.64843786e-01
7.77033746e-01 -1.31774480e-02 1.23794340e-01 -4.46937054e-01
-2.97692835e-01 -6.66271806e-01 1.06146209e-01 9.00038242e-01
3.17487061e-01 -5.46836138e-01 1.43654358e+00 1.11726058e+00
6.62130341e-02 -7.93442905e-01 -1.00680685e+00 -2.42285445e-01
1.33944064e-01 -4.27553505e-01 7.42982209e-01 1.27772009e+00
-2.20999092e-01 -3.56759965e-01 -5.54428041e-01 2.02447742e-01
7.89107442e-01 -9.90318507e-02 6.29804552e-01 -9.24932539e-01
-2.69458979e-01 -2.35522632e-02 -3.81914079e-01 -5.01493037e-01
-3.36967647e-01 -1.04147303e+00 -3.00662071e-01 -1.26939285e+00
5.82125068e-01 -7.53254294e-01 -2.05717772e-01 1.06008613e+00
-2.90368441e-02 6.63387537e-01 3.06118995e-01 4.84365523e-01
-2.03747362e-01 -7.83027336e-02 1.15662050e+00 -7.90320411e-02
1.96926534e-01 -1.56682089e-01 -8.51540565e-01 7.34297991e-01
8.46469581e-01 -1.05206883e+00 -3.25834692e-01 -6.14681065e-01
-6.06684247e-03 4.17397410e-01 8.63242567e-01 -8.77059519e-01
-4.31239158e-02 1.44381389e-01 9.21670854e-01 -6.44328535e-01
1.93891793e-01 -1.00640440e+00 3.73311847e-01 9.34676290e-01
-4.51434314e-01 3.49277109e-02 1.61628962e-01 3.46482396e-01
1.53555244e-01 -4.73142974e-02 9.76216674e-01 -4.46069568e-01
-2.43065413e-02 5.14173269e-01 -2.51136441e-02 2.33402282e-01
1.15973723e+00 -4.39273745e-01 -2.83345133e-01 -3.62537384e-01
-9.03412282e-01 -2.38617845e-02 6.46288514e-01 -7.29547143e-02
7.70510197e-01 -9.10997570e-01 -8.91966939e-01 4.23107445e-01
-1.24930203e-01 3.58990371e-01 6.66223586e-01 8.08276951e-01
-1.46166265e+00 2.83871323e-01 -2.40672603e-01 -8.93698633e-01
-1.74419320e+00 5.51243901e-01 4.54092503e-01 -1.61391329e-02
-1.37607288e+00 1.08457720e+00 3.98590714e-01 -4.47596014e-01
1.97757855e-01 -5.76457679e-01 6.53067529e-01 -5.29459476e-01
3.81254762e-01 4.28052157e-01 -5.76775894e-02 -2.55564392e-01
-5.59403718e-01 2.70535350e-01 -1.88151687e-01 4.02333230e-01
1.52797675e+00 -5.59480302e-02 3.49438265e-02 -3.65432233e-01
1.36111104e+00 -1.84770525e-02 -1.45599723e+00 6.17067479e-02
-6.04945600e-01 -6.92438185e-01 1.71655416e-01 -9.32386339e-01
-1.41377068e+00 9.93349850e-01 8.62885773e-01 4.20173481e-02
1.20126379e+00 7.35839382e-02 9.66991544e-01 -9.47018340e-02
-1.94606215e-01 -7.68572807e-01 -1.41693860e-01 -2.94395536e-01
7.91605234e-01 -1.18765771e+00 6.25729203e-01 -4.07648325e-01
-7.77515233e-01 1.16276670e+00 3.82158756e-01 -4.86241430e-02
6.24007463e-01 4.88581955e-01 1.14437461e-01 -3.31132591e-01
-4.19382244e-01 6.73031986e-01 9.61530656e-02 5.92373550e-01
1.80695727e-01 2.54504025e-01 7.18920678e-03 5.25125146e-01
-4.91190940e-01 -2.86015812e-02 4.85831589e-01 8.44639003e-01
1.12962993e-02 -5.67460835e-01 -6.52109385e-01 8.52934837e-01
-7.78573096e-01 -2.84884542e-01 -3.70820642e-01 1.00298262e+00
2.72670418e-01 3.28792721e-01 2.78713077e-01 -1.02509096e-01
1.11890048e-01 -3.05702269e-01 5.35612181e-02 -4.51843262e-01
-7.67311215e-01 -1.00012183e-01 -2.02369973e-01 -6.33467734e-01
2.53046662e-01 -5.51018715e-01 -1.53342688e+00 -7.13549256e-01
-1.64533153e-01 -3.34142268e-01 5.09520173e-01 5.46062350e-01
6.63749933e-01 4.40834671e-01 4.64705497e-01 -1.16800569e-01
-4.60155755e-01 -4.57081676e-01 -4.54601854e-01 5.30081213e-01
6.45004869e-01 1.40801072e-01 -3.11192691e-01 4.67350304e-01] | [14.538337707519531, -2.0729820728302] |
e390d84e-779b-4962-8f68-0f9c260fe8ba | simts-rethinking-contrastive-representation | 2303.18205 | null | https://arxiv.org/abs/2303.18205v1 | https://arxiv.org/pdf/2303.18205v1.pdf | SimTS: Rethinking Contrastive Representation Learning for Time Series Forecasting | Contrastive learning methods have shown an impressive ability to learn meaningful representations for image or time series classification. However, these methods are less effective for time series forecasting, as optimization of instance discrimination is not directly applicable to predicting the future state from the history context. Moreover, the construction of positive and negative pairs in current technologies strongly relies on specific time series characteristics, restricting their generalization across diverse types of time series data. To address these limitations, we propose SimTS, a simple representation learning approach for improving time series forecasting by learning to predict the future from the past in the latent space. SimTS does not rely on negative pairs or specific assumptions about the characteristics of the particular time series. Our extensive experiments on several benchmark time series forecasting datasets show that SimTS achieves competitive performance compared to existing contrastive learning methods. Furthermore, we show the shortcomings of the current contrastive learning framework used for time series forecasting through a detailed ablation study. Overall, our work suggests that SimTS is a promising alternative to other contrastive learning approaches for time series forecasting. | ['Michael Krauthammer', 'Ahmed Allam', 'Amina Mollaysa', 'Manuel Schürch', 'Xingyu Chen', 'Xiaochen Zheng'] | 2023-03-31 | null | null | null | null | ['time-series-classification'] | ['time-series'] | [ 2.37643123e-01 -5.83599329e-01 -6.10493481e-01 -4.16299343e-01
-5.48372746e-01 -6.74600482e-01 1.14945543e+00 1.87853307e-01
-4.39317077e-02 4.39015985e-01 1.29811734e-01 -5.59224069e-01
-2.35599622e-01 -6.33314610e-01 -4.59745318e-01 -7.94580281e-01
-5.94380200e-01 1.43818736e-01 -1.55947462e-01 -4.20709312e-01
3.47365201e-01 6.88038409e-01 -1.65460289e+00 2.52920687e-01
5.18919051e-01 1.58274865e+00 -3.72753888e-02 4.27688986e-01
-2.42486820e-01 1.08234799e+00 -7.32557833e-01 -1.08011356e-02
2.74838150e-01 -2.66753018e-01 -3.14918548e-01 -2.91503072e-01
2.99572349e-01 -2.47600880e-02 -3.76580089e-01 4.85529393e-01
7.58144036e-02 6.62013367e-02 9.73200977e-01 -1.81457376e+00
-4.98412371e-01 4.04080629e-01 -4.12347645e-01 7.01644838e-01
1.35879666e-01 -1.15935043e-01 9.51249421e-01 -6.53164685e-01
2.99058467e-01 1.03548014e+00 8.85130525e-01 3.84631574e-01
-1.09508884e+00 -1.00802064e+00 6.69131160e-01 4.44495529e-01
-8.28840971e-01 -2.12681293e-01 1.46025789e+00 -6.36867821e-01
1.10785770e+00 4.75835204e-01 8.14411402e-01 1.38935840e+00
6.73373997e-01 8.89591992e-01 1.43305111e+00 -3.89364451e-01
3.20370078e-01 -1.40383378e-01 1.76733211e-01 1.66031316e-01
-5.82834184e-01 3.41088057e-01 -4.36871916e-01 -2.17275709e-01
4.72551823e-01 4.00060236e-01 1.00893892e-01 -3.86900634e-01
-1.46321356e+00 5.87827444e-01 4.12093461e-01 7.92830050e-01
-4.54626352e-01 1.76504806e-01 7.96688199e-01 1.01778769e+00
1.05971539e+00 4.79364246e-01 -6.19381249e-01 -4.46143337e-02
-9.71240938e-01 1.28920570e-01 5.09314716e-01 4.82387006e-01
4.30117220e-01 5.63322186e-01 -2.57001877e-01 3.84060085e-01
-2.40176246e-01 4.81560886e-01 7.85312474e-01 -5.57880223e-01
3.73100817e-01 3.51772785e-01 -4.55312915e-02 -1.15963471e+00
-4.20604229e-01 -7.32194245e-01 -1.01731527e+00 -5.40538393e-02
2.30354920e-01 4.50894311e-02 -9.68428671e-01 1.77817369e+00
-2.84692138e-01 8.66424441e-01 1.65358916e-01 2.98847884e-01
4.57118124e-01 1.28703618e+00 2.52276242e-01 -8.97398591e-01
6.65841043e-01 -8.33120286e-01 -7.25945771e-01 -1.20016232e-01
5.21698594e-01 -6.81865275e-01 8.85146976e-01 3.39470923e-01
-5.96273601e-01 -6.28777087e-01 -9.19673502e-01 4.51987952e-01
-7.62960672e-01 1.34869283e-02 1.06849849e+00 4.10851687e-01
-8.24361682e-01 6.26258075e-01 -8.48754227e-01 -1.09503195e-01
9.20179635e-02 1.64445147e-01 -2.05720626e-02 3.58772337e-01
-1.24320507e+00 8.92744958e-01 3.56640339e-01 -1.02012999e-01
-7.77612507e-01 -9.10202563e-01 -7.18794167e-01 4.56606373e-02
-1.37327909e-01 -2.74550259e-01 1.24610651e+00 -1.22746634e+00
-1.28338611e+00 6.08536124e-01 -1.29065618e-01 -7.71316111e-01
5.67584395e-01 5.99086136e-02 -1.09153628e+00 -3.40768218e-01
-7.63539448e-02 3.85966092e-01 1.22553861e+00 -9.27022576e-01
-4.65055883e-01 -1.80550590e-01 -1.11496642e-01 -1.60237938e-01
-7.30600417e-01 -2.03109100e-01 6.74882010e-02 -1.08212006e+00
1.85524866e-01 -8.19350958e-01 -4.20254081e-01 -3.17453705e-02
2.26641953e-01 -6.92916512e-01 1.25869799e+00 -4.95332420e-01
1.48987257e+00 -2.16507435e+00 -1.44001544e-01 2.36270651e-01
-1.44617185e-01 9.09287781e-02 -2.44076133e-01 7.76953399e-01
-6.92157686e-01 -2.84120262e-01 3.10019348e-02 -1.14820920e-01
-4.10504751e-02 2.56034344e-01 -1.39055789e+00 3.28516424e-01
2.64176250e-01 8.86184275e-01 -1.11887169e+00 -1.47752985e-01
4.64902133e-01 2.78432637e-01 1.45863015e-02 1.79658666e-01
-2.35990718e-01 5.66130638e-01 -3.52716386e-01 5.18923998e-01
4.61104125e-01 -4.35229421e-01 2.13017270e-01 -2.75981426e-01
-3.24177325e-01 3.08949202e-01 -4.92152125e-01 1.35557747e+00
-6.87483549e-01 8.49416375e-01 -1.01035142e+00 -1.54181683e+00
1.22141743e+00 4.04561043e-01 9.45100129e-01 -1.19714475e+00
-1.46966755e-01 3.17312539e-01 -3.04444581e-01 -2.99694240e-01
3.85595441e-01 -3.01782995e-01 -1.78994641e-01 4.40414637e-01
1.36563377e-02 -1.35195509e-01 1.61758270e-02 -2.07603931e-01
6.78717315e-01 1.28372371e-01 2.75185943e-01 -1.64804205e-01
4.04983044e-01 -4.04588617e-02 6.49647355e-01 4.70834285e-01
-1.18902840e-01 2.58951873e-01 4.63930875e-01 -9.94085133e-01
-9.45464671e-01 -1.14200115e+00 -8.71018991e-02 1.24583483e+00
-2.18715981e-01 -5.65934122e-01 1.76877633e-01 -7.63513327e-01
-1.76744223e-01 8.86780977e-01 -6.88831270e-01 -1.45605892e-01
-7.54444420e-01 -8.10464919e-01 8.03958327e-02 8.26117754e-01
-2.50762352e-03 -9.40714717e-01 -4.90884721e-01 2.85454184e-01
-1.08912855e-01 -6.53417587e-01 -2.17507243e-01 2.58198053e-01
-1.15588427e+00 -6.48275197e-01 -9.25719321e-01 -8.75124454e-01
3.64534229e-01 3.10404092e-01 1.33287466e+00 -5.04094779e-01
1.25050351e-01 6.45785511e-01 -1.77415580e-01 -7.03926027e-01
-4.38956916e-01 -1.06126271e-01 5.42650782e-02 2.72967424e-02
2.34432489e-01 -8.77277195e-01 -5.26269376e-01 1.66940674e-01
-7.32564211e-01 -1.26145724e-02 1.29771948e-01 9.53842759e-01
4.71021295e-01 2.44748592e-01 1.05909073e+00 -5.13032079e-01
6.33312166e-01 -8.37423861e-01 -6.05489314e-01 6.12945974e-01
-1.01991308e+00 -1.18025541e-01 8.28206241e-01 -9.84610975e-01
-8.90702903e-01 -8.08139443e-02 1.68500304e-01 -6.59981847e-01
2.86342293e-01 7.04212904e-01 6.57983124e-01 3.23613107e-01
5.30555010e-01 7.07115531e-01 -4.92466614e-02 -3.18821400e-01
1.39089659e-01 3.21473509e-01 5.54562509e-01 -3.90496105e-01
6.90379858e-01 5.11679232e-01 1.34321243e-01 -5.91057122e-01
-8.25953305e-01 -4.85927969e-01 -4.60399091e-01 -5.32688975e-01
2.90264010e-01 -9.71835494e-01 -4.30654258e-01 5.46958506e-01
-7.42678642e-01 -1.23713657e-01 -3.94857258e-01 5.73312998e-01
-7.55362093e-01 2.42231965e-01 -4.51658696e-01 -1.05972707e+00
-3.12893808e-01 -6.76471889e-01 9.10624027e-01 -1.55751690e-01
-2.97998339e-01 -1.51585007e+00 1.33960724e-01 -2.63905585e-01
6.57199264e-01 4.88580912e-01 1.19729829e+00 -5.47494531e-01
-2.35490471e-01 -4.30612147e-01 1.11728124e-01 3.43815118e-01
2.50975251e-01 2.95291133e-02 -1.03751671e+00 -4.70413655e-01
1.78924501e-01 -2.79010355e-01 9.22601879e-01 3.99181336e-01
1.55993438e+00 -2.76467055e-01 -3.84707123e-01 3.78072679e-01
1.21376669e+00 5.82235813e-01 4.98302639e-01 3.41797382e-01
3.85556310e-01 6.81539774e-01 9.38182294e-01 6.69440567e-01
2.72310376e-01 5.20386398e-01 3.11767280e-01 -1.58497036e-01
2.21146435e-01 -3.91793847e-01 5.62971592e-01 1.12348235e+00
-2.96170115e-02 -2.96894968e-01 -9.87866282e-01 5.91681182e-01
-1.91589153e+00 -1.25453174e+00 1.18782952e-01 2.15621567e+00
4.97947663e-01 1.10809371e-01 2.30885535e-01 4.43771958e-01
4.81853008e-01 6.66007638e-01 -8.34381521e-01 -4.04987484e-02
-2.85569429e-01 9.61013213e-02 2.17117861e-01 -2.30844930e-01
-1.36071229e+00 5.21182179e-01 7.46962547e+00 8.32356751e-01
-1.94468641e+00 -6.75961897e-02 8.32607031e-01 1.89298496e-01
-4.93743896e-01 -1.12567291e-01 -2.32802674e-01 4.56340104e-01
1.11284614e+00 -5.97028673e-01 1.25074282e-01 6.83460712e-01
-7.82175735e-02 7.08610594e-01 -1.28374028e+00 1.44460773e+00
-4.04431708e-02 -1.55564106e+00 1.58346236e-01 -2.97447264e-01
7.83045113e-01 1.44508123e-01 6.27171516e-01 6.03948951e-01
-2.08634734e-01 -8.89995754e-01 8.71391058e-01 7.72117555e-01
5.15117884e-01 -5.93408704e-01 4.15224046e-01 3.69123191e-01
-1.31075466e+00 -4.26446557e-01 -6.68664053e-02 -3.56596708e-01
4.18331064e-02 4.49231088e-01 -7.11327493e-01 5.39395511e-01
6.09819472e-01 1.37022293e+00 -4.44074363e-01 7.68744648e-01
3.62722009e-01 8.84194791e-01 -1.65004373e-01 1.81608140e-01
3.08065385e-01 6.13350943e-02 4.68866467e-01 1.11004150e+00
7.78141499e-01 -3.89994889e-01 3.43499511e-01 3.50003302e-01
3.65803480e-01 1.81970537e-01 -8.57287765e-01 -4.32988495e-01
2.98867166e-01 8.45630586e-01 -6.50430679e-01 -4.52068359e-01
-6.14233732e-01 5.84373713e-01 2.83994973e-02 3.52547139e-01
-7.35648453e-01 1.35265350e-01 3.60416740e-01 -1.45053938e-01
1.20864578e-01 -2.70939320e-01 6.01970218e-03 -1.42745233e+00
2.15794668e-01 -7.45952487e-01 8.72368932e-01 -7.47999549e-01
-1.82595885e+00 8.22889805e-01 1.90676153e-01 -2.13865638e+00
-8.66011322e-01 -5.58898330e-01 -7.62640357e-01 6.83013201e-01
-1.68164384e+00 -1.42355585e+00 9.65272263e-02 6.44842684e-01
7.01341987e-01 -5.41355193e-01 1.00460672e+00 3.53961401e-02
-1.57636702e-01 3.08976531e-01 3.15147758e-01 -3.27569723e-01
6.33449316e-01 -1.16527867e+00 6.43116415e-01 6.41500294e-01
7.41619766e-02 3.13214868e-01 7.55171716e-01 -3.50764334e-01
-1.21891701e+00 -1.11276305e+00 1.02641177e+00 -2.39125654e-01
1.08586061e+00 -1.63106620e-01 -9.52467442e-01 6.98160827e-01
2.30383560e-01 6.41084835e-02 8.88314605e-01 2.61712343e-01
-8.02559197e-01 -5.56325078e-01 -7.87469625e-01 5.48894346e-01
7.57650852e-01 -8.37809801e-01 -5.80619097e-01 5.48742890e-01
4.30332243e-01 2.18641870e-02 -9.80340302e-01 6.13065541e-01
6.98229969e-01 -7.15350688e-01 1.09146619e+00 -7.29867280e-01
3.54898363e-01 -5.03452606e-02 -2.93756723e-01 -1.30282855e+00
-5.35806000e-01 -6.62448585e-01 -4.51165289e-01 1.11676407e+00
1.56857684e-01 -8.31496537e-01 4.88612175e-01 2.35180199e-01
-1.24814458e-01 -6.26884520e-01 -8.36451948e-01 -1.30250037e+00
3.33494216e-01 -6.37917340e-01 8.12035143e-01 1.50037467e+00
-5.25622033e-02 2.40911826e-01 -8.55652869e-01 -6.11123592e-02
3.23830545e-01 6.91113293e-01 4.11378741e-01 -1.42228043e+00
-1.09167755e-01 -6.05288267e-01 -4.59508777e-01 -8.93394887e-01
5.92157185e-01 -9.07176554e-01 -3.51123691e-01 -1.00509989e+00
-1.65982127e-01 -6.70466840e-01 -1.04076552e+00 3.08878005e-01
1.84945926e-01 4.37108688e-02 1.54888242e-01 4.89795893e-01
-2.78046101e-01 6.47481441e-01 1.12804556e+00 -5.97363114e-01
-1.30819410e-01 4.38059598e-01 -1.74142018e-01 4.56926316e-01
8.84847999e-01 -1.76021129e-01 -8.84937823e-01 -1.68200135e-01
1.65661663e-01 5.52936316e-01 3.08828503e-01 -1.02808499e+00
1.24531329e-01 -4.63871628e-01 3.75648141e-01 -9.30888295e-01
5.00204980e-01 -1.00039315e+00 3.79149497e-01 6.09998286e-01
-5.66729844e-01 5.76274753e-01 2.43269786e-01 7.30373859e-01
-5.80708027e-01 2.18636155e-01 3.15700203e-01 1.02877900e-01
-1.21507204e+00 3.81955892e-01 -4.24050927e-01 -4.87531364e-01
1.03826749e+00 -2.77936548e-01 -1.97721496e-01 -6.68316483e-01
-6.33098543e-01 6.20618984e-02 -1.63369980e-02 9.41879928e-01
4.09392297e-01 -1.54836631e+00 -5.13706982e-01 2.93021351e-01
4.94540185e-01 -9.09150779e-01 3.81577194e-01 7.14940906e-01
7.21090063e-02 5.66773713e-01 -5.29819191e-01 -7.19392061e-01
-1.12020814e+00 1.04275095e+00 2.12660357e-01 -4.57942605e-01
-5.73195875e-01 2.37823188e-01 4.22467619e-01 -1.97570696e-01
3.34749699e-01 -5.86343646e-01 -5.02465546e-01 3.98346007e-01
5.99786520e-01 3.08030844e-01 9.74991322e-02 -5.62589526e-01
-2.74716526e-01 4.89380836e-01 -1.15687005e-01 2.31976099e-02
1.77242291e+00 3.98853309e-02 -5.69028482e-02 1.19275415e+00
1.34814012e+00 -4.70649511e-01 -1.09892297e+00 -3.61514062e-01
2.79643148e-01 -2.79736042e-01 6.19520023e-02 -7.19598114e-01
-9.79742646e-01 8.54317486e-01 9.20784652e-01 6.62713468e-01
1.67483723e+00 -2.06447735e-01 7.49674499e-01 3.51852238e-01
4.60035712e-01 -8.36618602e-01 1.48198351e-01 5.04301727e-01
1.10121226e+00 -1.32440972e+00 -2.19533414e-01 -2.29305342e-01
-4.29387033e-01 1.43913889e+00 3.12817961e-01 -1.63254544e-01
1.05971742e+00 -9.64146573e-04 2.22945169e-01 3.12485471e-02
-1.25829148e+00 6.82031438e-02 6.81859136e-01 5.31906843e-01
6.82440639e-01 2.70140052e-01 -1.46993876e-01 8.98276195e-02
-2.34595224e-01 -1.01207562e-01 -1.11124869e-02 1.02684128e+00
2.34257877e-01 -1.22617149e+00 -7.79691488e-02 5.70531785e-01
-4.14805382e-01 2.76525766e-01 -5.56569062e-02 6.05366945e-01
-1.70756027e-01 8.23673785e-01 5.41632414e-01 -4.88630742e-01
1.40664905e-01 1.55868113e-01 4.33148265e-01 -2.54970759e-01
-6.14058018e-01 1.39758617e-01 -1.51313335e-01 -3.44990969e-01
-7.50216544e-01 -7.68541634e-01 -6.74478233e-01 -5.49444109e-02
-3.04282177e-03 -7.34681310e-03 4.84469503e-01 8.01043689e-01
2.76196152e-01 4.45804656e-01 1.12637615e+00 -8.66541684e-01
-4.14167345e-01 -7.35245347e-01 -3.88467401e-01 5.08132041e-01
6.94715083e-01 -6.35904849e-01 -2.65233189e-01 1.77971020e-01] | [7.121694564819336, 2.988954782485962] |
7e1163b1-d0b5-45f1-a9da-42d5a1c1264b | rapid-training-of-very-large-ensembles-of | 1809.04270 | null | https://arxiv.org/abs/1809.04270v2 | https://arxiv.org/pdf/1809.04270v2.pdf | MotherNets: Rapid Deep Ensemble Learning | Ensembles of deep neural networks significantly improve generalization accuracy. However, training neural network ensembles requires a large amount of computational resources and time. State-of-the-art approaches either train all networks from scratch leading to prohibitive training cost that allows only very small ensemble sizes in practice, or generate ensembles by training a monolithic architecture, which results in lower model diversity and decreased prediction accuracy. We propose MotherNets to enable higher accuracy and practical training cost for large and diverse neural network ensembles: A MotherNet captures the structural similarity across some or all members of a deep neural network ensemble which allows us to share data movement and computation costs across these networks. We first train a single or a small set of MotherNets and, subsequently, we generate the target ensemble networks by transferring the function from the trained MotherNet(s). Then, we continue to train these ensemble networks, which now converge drastically faster compared to training from scratch. MotherNets handle ensembles with diverse architectures by clustering ensemble networks of similar architecture and training a separate MotherNet for every cluster. MotherNets also use clustering to control the accuracy vs. training cost tradeoff. We show that compared to state-of-the-art approaches such as Snapshot Ensembles, Knowledge Distillation, and TreeNets, MotherNets provide a new Pareto frontier for the accuracy-training cost tradeoff. Crucially, training cost and accuracy improvements continue to scale as we increase the ensemble size (2 to 3 percent reduced absolute test error rate and up to 35 percent faster training compared to Snapshot Ensembles). We verify these benefits over numerous neural network architectures and large data sets. | ['Brian Hentschel', 'Yuze Liao', 'Stratos Idreos', 'Sanyuan Chen', 'Abdul Wasay'] | 2018-09-12 | null | null | null | null | ['clustering-ensemble'] | ['graphs'] | [ 5.38346544e-02 -1.23486027e-01 3.01833183e-01 -4.16852444e-01
-5.25228679e-01 -7.64470458e-01 2.73881197e-01 -2.52622247e-01
-5.12235165e-01 9.89295840e-01 -3.53275806e-01 -3.29174489e-01
-3.31134349e-01 -9.27834451e-01 -8.06867301e-01 -8.84257793e-01
-7.46517023e-03 7.30455637e-01 -5.88955618e-02 -1.92668006e-01
-2.37986878e-01 5.34825802e-01 -1.72384155e+00 2.91181117e-01
1.23892713e+00 9.93206322e-01 -1.47592917e-01 7.62944102e-01
1.39570713e-01 6.71776295e-01 -8.00218582e-01 -2.67289817e-01
3.86297196e-01 -4.81472880e-01 -4.74850863e-01 -3.05176169e-01
7.76560605e-01 -1.10238060e-01 -2.95937628e-01 6.22840464e-01
6.82845354e-01 3.31159174e-01 5.78735948e-01 -1.30300963e+00
-4.59855556e-01 8.40596080e-01 -2.43361548e-01 3.54119949e-02
-6.51074588e-01 2.31063291e-01 7.87749648e-01 -7.83359528e-01
2.36212790e-01 7.20280230e-01 1.15179455e+00 8.10509086e-01
-1.43595886e+00 -1.02236807e+00 2.17125610e-01 -1.44320920e-01
-1.43461835e+00 -6.88821137e-01 2.72831380e-01 -2.56362438e-01
1.14758778e+00 3.57858539e-01 6.85830653e-01 1.21590161e+00
7.05229864e-02 4.40985024e-01 8.11032474e-01 -1.71040297e-01
4.40384656e-01 1.53459981e-01 3.08305204e-01 5.75587213e-01
5.73008239e-01 1.91240653e-01 -1.01697221e-01 -8.64880532e-02
5.98696828e-01 3.20163578e-01 -9.40792486e-02 -1.46382883e-01
-7.63190091e-01 6.42475903e-01 4.57378030e-01 3.65136176e-01
-5.01888454e-01 5.13456762e-01 3.53086978e-01 6.26669765e-01
4.48814332e-01 7.30550349e-01 -7.39016712e-01 -3.97224799e-02
-1.21445858e+00 1.14026777e-01 1.01251161e+00 7.64146984e-01
8.97374213e-01 5.73850334e-01 2.35897943e-01 9.49221611e-01
-2.10260183e-01 4.18898553e-01 4.72548574e-01 -1.12752068e+00
3.92779440e-01 8.36571753e-01 -2.54760891e-01 -6.74376309e-01
-3.67947340e-01 -1.14227915e+00 -1.37455916e+00 4.75069731e-01
2.17226774e-01 -8.11124980e-01 -1.10673082e+00 1.87636137e+00
2.37618789e-01 3.31997246e-01 2.41411820e-01 3.24016839e-01
4.43947643e-01 5.66594124e-01 -1.37147531e-01 8.61689672e-02
8.33097160e-01 -9.57410336e-01 1.18590511e-01 -2.08270937e-01
9.55565095e-01 -2.16701716e-01 5.77818096e-01 3.94187927e-01
-9.91928935e-01 -7.08617806e-01 -1.12275946e+00 4.81055588e-01
-4.67535943e-01 2.49912634e-01 4.31911767e-01 7.88203716e-01
-1.42790926e+00 8.78263891e-01 -1.02819276e+00 -9.97846350e-02
6.16023064e-01 9.72783089e-01 -3.16456944e-01 -4.10714895e-02
-8.07752311e-01 7.84235954e-01 7.83725321e-01 7.65935257e-02
-8.73461545e-01 -9.97329116e-01 -5.65050602e-01 4.17037666e-01
6.17933981e-02 -1.12177086e+00 9.49952304e-01 -1.46167600e+00
-1.45667911e+00 6.04763255e-02 1.83602497e-01 -5.96339524e-01
1.70918837e-01 -2.29690239e-01 -5.68002284e-01 -4.39703375e-01
-3.62378806e-01 7.50768661e-01 5.89049995e-01 -1.34063327e+00
-7.49804199e-01 -3.17568988e-01 -2.11577520e-01 1.26858307e-02
-6.28730655e-01 -4.08785433e-01 9.95438546e-03 -4.52721983e-01
-1.23023987e-01 -1.22794950e+00 -3.85258347e-01 -6.60124719e-01
-2.10530058e-01 -8.03048536e-02 1.00004697e+00 -3.26151520e-01
1.38815272e+00 -1.98809743e+00 2.37444878e-01 4.75038469e-01
5.98998666e-01 3.60154659e-01 -5.38418412e-01 2.32932374e-01
-1.61565393e-01 2.75468528e-01 -3.74458313e-01 -4.44285601e-01
-1.36188671e-01 4.74982351e-01 -1.83291376e-01 -7.78767169e-02
2.61264801e-01 8.46478224e-01 -5.60772896e-01 -1.27192557e-01
-4.63331640e-02 5.75472832e-01 -8.42270553e-01 -1.34352803e-01
-1.84004441e-01 3.91299933e-01 -2.47311637e-01 3.19279790e-01
3.93482834e-01 -5.21967113e-01 4.85789955e-01 -4.92958389e-02
1.38040498e-01 6.92910403e-02 -1.07009864e+00 1.23172355e+00
-8.79148483e-01 5.31244218e-01 -1.16923526e-01 -1.22678554e+00
9.02396083e-01 2.11609319e-01 4.63795573e-01 -2.15661749e-01
1.94810167e-01 4.70568210e-01 5.23226976e-01 1.82197526e-01
4.12671775e-01 9.57223773e-02 -8.00621584e-02 7.09833682e-01
3.79861593e-01 2.72235662e-01 2.16459483e-01 -4.11218368e-02
1.33113217e+00 -1.13684379e-01 -1.25230789e-01 -1.66084528e-01
1.73064396e-01 -3.69374752e-02 5.48512757e-01 9.33948100e-01
4.37769443e-01 2.43103713e-01 7.59935379e-02 -8.14029276e-01
-1.30596697e+00 -9.21373665e-01 3.76039073e-02 1.50416994e+00
-4.46366102e-01 -3.51144433e-01 -8.54925036e-01 -8.06366265e-01
1.20701000e-01 7.97038078e-01 -8.17814529e-01 -3.42114925e-01
-8.00046921e-01 -9.34999824e-01 8.13953280e-01 9.15374577e-01
7.10932612e-01 -9.50301647e-01 -4.57786947e-01 3.46259028e-01
2.94894695e-01 -7.53178179e-01 -2.01660961e-01 4.70237434e-01
-1.24295318e+00 -8.35819781e-01 -4.05821800e-01 -5.13064623e-01
8.20530593e-01 -2.01666698e-01 1.50402534e+00 3.70066255e-01
-1.19381472e-01 1.36667967e-01 -2.97677256e-02 -4.41975504e-01
-5.18053412e-01 6.41022921e-01 4.69551325e-01 -4.56194654e-02
1.04265288e-01 -1.25516093e+00 -6.59494340e-01 3.14221978e-01
-7.35403240e-01 -9.62189361e-02 7.52845049e-01 1.01924753e+00
4.12941396e-01 1.19549602e-01 8.84568870e-01 -9.61020172e-01
4.99344915e-01 -6.80910408e-01 -5.76097786e-01 4.48546231e-01
-7.83964097e-01 2.73991495e-01 9.53791618e-01 -6.42974854e-01
-7.93311357e-01 5.37940301e-02 -4.69098915e-04 -7.22701848e-01
-1.00338891e-01 5.06827772e-01 2.30273396e-01 2.94701792e-02
1.06198239e+00 2.90454030e-01 1.66650377e-02 -3.05262178e-01
2.92116731e-01 4.72883672e-01 4.16450918e-01 -7.30965495e-01
5.34433484e-01 2.12778579e-02 -9.89933759e-02 -3.67779881e-01
-6.94144368e-01 1.18462719e-01 -6.93060458e-01 6.12471439e-02
4.64116782e-01 -9.80671465e-01 -8.08553576e-01 3.35073054e-01
-1.00490808e+00 -6.98522270e-01 -3.19088340e-01 2.64337927e-01
-8.10202491e-03 -5.03053963e-01 -4.25484687e-01 -6.98570013e-01
-8.25211048e-01 -9.47301626e-01 6.59693182e-01 1.56927690e-01
-3.86983305e-01 -1.14301884e+00 1.02731206e-01 -1.40037581e-01
8.56105626e-01 4.25254345e-01 8.25691819e-01 -9.80794191e-01
-4.97632802e-01 -1.48472846e-01 4.93369736e-02 6.93474472e-01
1.15980633e-01 1.14412956e-01 -8.87203336e-01 -4.66142923e-01
-3.73503774e-01 -2.55380690e-01 1.11371160e+00 3.21794271e-01
1.29376495e+00 -5.09019434e-01 -5.69965065e-01 7.29467571e-01
1.37535012e+00 3.35986018e-01 3.94144565e-01 -8.00764374e-03
8.73916268e-01 2.60353595e-01 -3.70882511e-01 1.21929154e-01
1.69164106e-01 2.76508510e-01 1.17236264e-01 -4.57312390e-02
3.22823487e-02 1.13588415e-01 2.93879241e-01 1.15423131e+00
-4.80314314e-01 -2.95056999e-01 -1.18611062e+00 4.01748270e-01
-1.95458019e+00 -1.06098604e+00 2.86715597e-01 2.23123956e+00
8.25562954e-01 -1.20975766e-02 2.25146130e-01 2.68426798e-02
4.19013888e-01 -3.08616877e-01 -9.62450087e-01 -3.37852061e-01
3.13114189e-02 6.28262937e-01 3.55517328e-01 2.39721969e-01
-8.22199643e-01 7.08352625e-01 6.58729935e+00 7.98540890e-01
-1.41131139e+00 2.48592585e-01 1.05153847e+00 -6.66006505e-01
-1.81642696e-01 -1.48257807e-01 -9.24891591e-01 4.90226686e-01
1.53984475e+00 -3.23619358e-02 5.44933319e-01 1.07606065e+00
-3.82889688e-01 2.00263605e-01 -1.34448779e+00 8.79782259e-01
-1.22951731e-01 -1.68001878e+00 -1.49567882e-02 2.87765086e-01
1.25120687e+00 5.56430519e-01 1.26660271e-02 7.23306239e-01
1.00064850e+00 -1.39503610e+00 2.80678868e-01 5.06703973e-01
8.72047961e-01 -1.11625850e+00 7.53554046e-01 5.45967340e-01
-1.04506004e+00 -4.42495018e-01 -3.88716429e-01 6.73749223e-02
-3.45708519e-01 7.55243361e-01 -5.73955774e-01 5.10781884e-01
8.85710835e-01 3.80255908e-01 -5.84603429e-01 6.51982188e-01
3.98234963e-01 8.30661774e-01 -5.98065019e-01 -9.13272277e-02
2.39569142e-01 -3.00687760e-01 1.75839141e-01 1.02511382e+00
6.95240498e-01 1.87413543e-01 9.16955397e-02 8.01848590e-01
-4.85634089e-01 -4.29310679e-01 -7.74421275e-01 3.37565085e-03
8.82394731e-01 1.31792128e+00 -4.11514759e-01 -6.40068769e-01
4.13499214e-02 7.46751606e-01 7.19257116e-01 4.57700849e-01
-8.21574807e-01 -3.93768936e-01 7.34684050e-01 -9.02616084e-02
4.06703979e-01 -1.27220720e-01 -5.80218911e-01 -8.98410499e-01
-2.22553611e-01 -1.02824104e+00 3.27579290e-01 -4.41217661e-01
-1.32772958e+00 1.16761100e+00 -2.22405612e-01 -1.03735471e+00
-5.78192174e-01 -5.46148658e-01 -9.10249591e-01 8.87784183e-01
-6.02753997e-01 -9.37651932e-01 -4.96323735e-01 3.84184837e-01
2.54678309e-01 -5.43057024e-01 1.05192816e+00 2.40507990e-01
-8.37564051e-01 1.02711892e+00 6.65496767e-01 3.13199192e-01
4.18699235e-01 -1.07293761e+00 5.30901074e-01 5.58656573e-01
1.84479311e-01 8.38148415e-01 2.55783796e-01 -2.87500679e-01
-1.17246437e+00 -1.53531408e+00 3.66246939e-01 -9.14190054e-01
3.80963355e-01 -2.63870746e-01 -1.01119936e+00 9.02856886e-01
2.05189958e-01 1.50441676e-01 8.71430933e-01 6.46056116e-01
-4.79070097e-01 -5.79411566e-01 -8.74359906e-01 6.19801223e-01
1.14381695e+00 -2.41495878e-01 -9.00920704e-02 -4.16923612e-02
5.58040857e-01 -3.00557971e-01 -1.10419643e+00 5.91716409e-01
9.12580132e-01 -1.01914191e+00 7.98520565e-01 -7.24117517e-01
5.90466380e-01 -2.72315163e-02 -5.08043058e-02 -1.83752191e+00
-3.05885077e-01 -3.97635698e-01 -2.85346657e-01 1.05888033e+00
9.48009253e-01 -1.02824903e+00 8.73511255e-01 6.59219384e-01
-4.15573627e-01 -1.10005808e+00 -7.36182570e-01 -8.22531462e-01
3.93980622e-01 -2.79091179e-01 9.72779751e-01 1.04712522e+00
-5.68675339e-01 5.56633890e-01 -1.45233562e-02 -6.68359827e-03
4.98883039e-01 2.99911536e-02 8.39835525e-01 -1.50071275e+00
-4.77300644e-01 -6.54326558e-01 -1.36299983e-01 -6.14557803e-01
1.29951283e-01 -9.43210781e-01 -1.00015059e-01 -1.13296306e+00
1.16293626e-02 -1.10227704e+00 -6.10658348e-01 8.16111028e-01
-1.99882016e-01 2.94991672e-01 1.46028459e-01 2.42480829e-01
-6.22993112e-01 3.87099922e-01 7.66110837e-01 1.10717444e-03
-4.88903105e-01 -1.02208152e-01 -8.86222124e-01 5.67133486e-01
1.00431335e+00 -4.87301290e-01 -6.43929124e-01 -7.56340265e-01
1.31472051e-01 -9.87096280e-02 3.76830757e-01 -1.51248002e+00
3.78562599e-01 1.11059487e-01 9.50093150e-01 -2.99693733e-01
2.55633682e-01 -7.94630527e-01 7.07537472e-01 3.98125172e-01
-7.30158761e-02 3.64753038e-01 5.17947197e-01 3.83253664e-01
-4.73273955e-02 1.18664689e-01 7.70615280e-01 -2.06476748e-02
-2.21713096e-01 4.63588089e-01 -9.42194313e-02 -7.80280083e-02
9.65995848e-01 -4.44384545e-01 -4.41267729e-01 -1.26506895e-01
-8.22765827e-01 2.71733344e-01 2.79299378e-01 2.08977833e-01
3.91756535e-01 -1.37848186e+00 -8.74265969e-01 2.47813702e-01
-3.66606563e-01 3.05742860e-01 4.14203912e-01 8.67744803e-01
-3.51333857e-01 1.25823721e-01 -2.92899847e-01 -8.11741531e-01
-1.22306895e+00 1.15835726e-01 7.70275414e-01 -4.39561933e-01
-2.50432402e-01 9.60302114e-01 1.43330872e-01 -9.05899405e-01
-8.33010003e-02 -3.35156685e-03 1.98822260e-01 -1.92458674e-01
3.45574647e-01 4.47239846e-01 1.91658854e-01 -5.69386706e-02
-3.30009520e-01 3.61602247e-01 -3.31109077e-01 1.76352397e-01
1.57006598e+00 4.59313810e-01 -1.33083522e-01 2.26311684e-01
1.09933829e+00 -3.96348536e-01 -1.22219372e+00 -1.11031637e-01
-1.66730672e-01 2.44543850e-01 1.64456163e-02 -1.02437842e+00
-1.33595967e+00 7.08687901e-01 6.02293015e-01 1.67138502e-01
1.35749245e+00 -2.22954988e-01 5.80406129e-01 8.30753863e-01
3.38428706e-01 -1.01902521e+00 -4.80170101e-02 8.06311667e-01
7.77131081e-01 -1.02355671e+00 -9.66047719e-02 2.90647984e-01
-4.49914485e-01 1.01894629e+00 1.08910751e+00 -3.79934490e-01
6.50568426e-01 6.64444983e-01 -2.76590753e-02 -8.42006579e-02
-1.28753412e+00 2.35323176e-01 3.37109625e-01 3.41507524e-01
4.00090933e-01 1.06097512e-01 4.06229585e-01 6.68822408e-01
-5.74267030e-01 -5.35356998e-02 -3.31138232e-04 6.55959964e-01
-4.10633028e-01 -1.10915422e+00 -9.74982977e-02 1.05521989e+00
-1.39817700e-01 -4.22724575e-01 -3.13099265e-01 9.30939674e-01
3.68600339e-01 7.15698600e-01 5.78885138e-01 -9.92628992e-01
2.16475636e-01 4.06518012e-01 4.80678350e-01 -5.85514247e-01
-9.60776567e-01 -4.49395418e-01 1.53482050e-01 -3.38695943e-01
-1.79480702e-01 -1.63270190e-01 -9.86893535e-01 -7.73050725e-01
-4.97882336e-01 2.80290514e-01 5.19097209e-01 9.82207894e-01
1.03261101e+00 8.32019091e-01 6.03256226e-01 -9.84996319e-01
-7.64894783e-01 -1.12963831e+00 -3.49033862e-01 4.06365171e-02
1.77169830e-01 -3.22488874e-01 -3.54789078e-01 -4.77758832e-02] | [8.69322395324707, 3.2504377365112305] |
4ec5a2ee-7ae6-47d3-acec-0cede2c08059 | ganwriting-content-conditioned-generation-of | 2003.02567 | null | https://arxiv.org/abs/2003.02567v2 | https://arxiv.org/pdf/2003.02567v2.pdf | GANwriting: Content-Conditioned Generation of Styled Handwritten Word Images | Although current image generation methods have reached impressive quality levels, they are still unable to produce plausible yet diverse images of handwritten words. On the contrary, when writing by hand, a great variability is observed across different writers, and even when analyzing words scribbled by the same individual, involuntary variations are conspicuous. In this work, we take a step closer to producing realistic and varied artificially rendered handwritten words. We propose a novel method that is able to produce credible handwritten word images by conditioning the generative process with both calligraphic style features and textual content. Our generator is guided by three complementary learning objectives: to produce realistic images, to imitate a certain handwriting style and to convey a specific textual content. Our model is unconstrained to any predefined vocabulary, being able to render whatever input word. Given a sample writer, it is also able to mimic its calligraphic features in a few-shot setup. We significantly advance over prior art and demonstrate with qualitative, quantitative and human-based evaluations the realistic aspect of our synthetically produced images. | ['Alicia Fornés', 'Marçal Rusiñol', 'Mauricio Villegas', 'Yaxing Wang', 'Pau Riba', 'Lei Kang'] | 2020-03-05 | null | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4304_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123680273.pdf | eccv-2020-8 | ['handwritten-word-generation'] | ['computer-vision'] | [ 6.51834905e-01 3.58753391e-02 3.56882542e-01 -1.09243043e-01
-5.58305502e-01 -8.85353148e-01 1.34309566e+00 -3.34895641e-01
-1.29567400e-01 9.01346266e-01 1.75060898e-01 1.44784555e-01
6.63744733e-02 -7.64834225e-01 -8.02179754e-01 -7.06544042e-01
6.09073699e-01 7.79569685e-01 -1.74514145e-01 -4.18143004e-01
4.44187552e-01 7.55188644e-01 -1.63509548e+00 2.71664709e-01
7.26163685e-01 4.95492697e-01 4.07689631e-01 9.80356157e-01
-9.61612985e-02 9.82965291e-01 -9.93754685e-01 -6.85200632e-01
1.71429902e-01 -9.14847255e-01 -5.49999595e-01 1.01250553e+00
6.01619601e-01 -1.57835335e-01 -3.43484059e-02 9.60530877e-01
4.93053496e-01 -1.03340395e-01 1.05039191e+00 -9.92968678e-01
-1.02014160e+00 7.57857621e-01 -3.56258243e-01 -4.99989569e-01
5.59247971e-01 6.63948417e-01 7.25968480e-01 -8.44628274e-01
1.14413941e+00 1.16585755e+00 1.79887980e-01 6.33813143e-01
-1.62033641e+00 -1.88157812e-01 -1.75511882e-01 -2.92465389e-01
-1.14466166e+00 -3.57167542e-01 7.49190927e-01 -5.17919898e-01
3.75283748e-01 2.91704953e-01 6.41671181e-01 1.73330522e+00
1.57844871e-01 7.58090615e-01 1.41771531e+00 -6.58880830e-01
3.39739203e-01 3.89090717e-01 -4.05743182e-01 5.40535927e-01
3.88243087e-02 1.27216801e-01 -4.83175188e-01 2.68918425e-01
9.06399250e-01 -2.28470340e-01 -3.40880424e-01 -3.79360527e-01
-1.42129183e+00 6.78784370e-01 6.37423024e-02 4.68315333e-01
-4.20304269e-01 2.13634223e-01 1.15369841e-01 2.32517332e-01
1.97755955e-02 8.65993738e-01 2.52857894e-01 -1.43910527e-01
-1.28926563e+00 4.55490470e-01 9.63841379e-01 1.06791151e+00
5.38111925e-01 3.53661984e-01 -4.93860990e-01 7.74075568e-01
-2.07380280e-01 8.19290459e-01 6.97369933e-01 -7.90400922e-01
4.94702831e-02 2.31704593e-01 3.75045568e-01 -1.02159607e+00
1.36289060e-01 -2.90341884e-01 -9.22511399e-01 7.52747416e-01
4.89735693e-01 1.48408907e-02 -1.21449554e+00 1.35623646e+00
-2.86198705e-01 -2.95910805e-01 1.66073114e-01 8.84347200e-01
4.48972374e-01 7.53127396e-01 -2.53690153e-01 -1.29483417e-01
1.27090025e+00 -9.71726716e-01 -8.07141244e-01 -2.40483940e-01
-6.48869351e-02 -1.01877487e+00 1.48627019e+00 7.37412810e-01
-1.42105472e+00 -6.65562212e-01 -1.26017940e+00 7.07110018e-02
-1.68413624e-01 2.32389122e-01 -2.48912722e-02 6.90727293e-01
-9.75993037e-01 5.80950260e-01 -3.43859017e-01 -2.08560482e-01
2.52672672e-01 -1.94201648e-01 -3.79421055e-01 1.82296261e-02
-8.38439643e-01 1.08162892e+00 4.03214037e-01 -4.47110832e-02
-1.19783413e+00 -3.77838612e-01 -6.68199956e-01 -1.13352686e-01
2.92358875e-01 -5.62447727e-01 1.14817059e+00 -1.38202572e+00
-1.85482848e+00 1.11205769e+00 1.03358053e-01 -2.71503210e-01
1.27600372e+00 1.83139831e-01 -3.21132720e-01 8.88293460e-02
-2.15742588e-01 6.99092507e-01 1.35526085e+00 -1.96301270e+00
-1.37904704e-01 1.40506640e-01 -1.99174687e-01 9.09080133e-02
-1.70554996e-01 -1.62927568e-01 -4.01290417e-01 -9.74491775e-01
-3.44057798e-01 -7.59675324e-01 -1.58923984e-01 1.25745973e-02
-6.88460767e-01 4.17052567e-01 6.85748041e-01 -4.54167217e-01
6.32138729e-01 -1.98344290e+00 3.63838464e-01 1.48678839e-01
8.03772956e-02 3.00942451e-01 -4.53281134e-01 7.26351380e-01
2.87900776e-01 1.94539011e-01 -4.44742739e-01 -5.02147913e-01
1.77725330e-01 2.46427596e-01 -6.58808172e-01 2.13871285e-01
3.68323684e-01 1.06112206e+00 -9.96824801e-01 -4.30676579e-01
3.53275537e-01 6.04037523e-01 -2.44934157e-01 2.03642890e-01
-5.92043519e-01 5.60589433e-01 -2.39695400e-01 4.69132662e-01
4.75408792e-01 -1.76967129e-01 1.63279757e-01 3.47913243e-02
3.07761948e-03 -5.50421417e-01 -1.02937245e+00 1.48015010e+00
-7.98134923e-01 8.79867554e-01 -3.36355716e-01 -6.20639086e-01
1.31385338e+00 1.80594489e-01 -2.76416987e-01 -7.25227118e-01
3.01704764e-01 4.33585793e-01 -2.58558929e-01 -4.90567058e-01
8.33009720e-01 -3.69415849e-01 -7.49664158e-02 8.42977285e-01
-1.09481916e-03 -9.69975173e-01 3.91575724e-01 8.02984312e-02
7.64055014e-01 6.25681728e-02 2.14493573e-01 -1.66961864e-01
4.58821207e-01 -1.39671803e-01 -3.34274530e-01 1.02410758e+00
3.50479752e-01 1.31667137e+00 6.04413986e-01 -3.73913944e-01
-1.61915207e+00 -1.15097034e+00 1.14726774e-01 4.37107831e-01
1.84799582e-01 2.06086248e-01 -8.92200410e-01 -3.25634837e-01
-2.36682415e-01 1.05071974e+00 -8.25114548e-01 -6.07742853e-02
-4.13275748e-01 -2.18685821e-01 6.50432289e-01 1.71383291e-01
4.58769292e-01 -1.53944063e+00 -8.94416571e-01 2.65109599e-01
3.31666432e-02 -1.08886695e+00 -4.75917280e-01 -1.61289215e-01
-3.81535858e-01 -6.49146974e-01 -1.32513154e+00 -7.18503475e-01
8.11594665e-01 -1.90331802e-01 1.34051621e+00 -4.77189086e-02
-6.91757202e-01 3.34646881e-01 -4.10293341e-01 -3.95597339e-01
-1.05503547e+00 -1.80077985e-01 -2.40796074e-01 3.42175692e-01
-3.62174004e-01 -4.85241413e-01 -4.02211815e-01 1.85890466e-01
-1.47143388e+00 2.85730660e-01 7.43111134e-01 1.01050436e+00
3.72700810e-01 -2.85674185e-01 2.44324654e-01 -8.66868615e-01
9.99387741e-01 1.23213321e-01 -3.06107134e-01 4.79815423e-01
-3.75385225e-01 3.33172917e-01 1.08356416e+00 -8.53990257e-01
-1.06352556e+00 5.88847771e-02 1.93668559e-01 -3.89761209e-01
-2.78198987e-01 9.24137533e-02 2.13686917e-02 1.07883342e-01
1.03698075e+00 8.07729483e-01 5.29262125e-02 -1.14048906e-01
6.84638143e-01 6.01131916e-01 7.93736875e-01 -7.41352439e-01
9.09402132e-01 5.55668831e-01 -2.22962037e-01 -9.95247602e-01
-3.23619187e-01 4.01586562e-01 -5.89943588e-01 -5.17524064e-01
6.85325205e-01 -4.55678195e-01 -5.43517113e-01 8.31670702e-01
-1.23196471e+00 -6.25512064e-01 -6.49782777e-01 -2.04212256e-02
-9.23539162e-01 3.02823097e-01 -2.87053108e-01 -7.51645684e-01
-4.54043634e-02 -1.27948308e+00 1.33548379e+00 1.62427083e-01
-3.70374560e-01 -8.30605626e-01 1.31718963e-01 3.30573209e-02
4.62045938e-01 5.98958433e-01 7.18973517e-01 -3.46677214e-01
-4.56572026e-01 -3.57820362e-01 -1.58588976e-01 4.16935503e-01
3.06509286e-01 4.43278700e-01 -7.95881569e-01 -1.70450121e-01
-2.50840098e-01 -5.75075686e-01 6.34413302e-01 -1.01245515e-01
9.04464364e-01 -4.82382804e-01 1.47454619e-01 3.17002118e-01
1.49379182e+00 1.65057436e-01 8.51837873e-01 1.11543775e-01
4.35127079e-01 5.53976655e-01 1.73396081e-01 4.79211509e-01
-3.03547978e-01 7.39835918e-01 2.39973798e-01 -1.61920458e-01
-4.16200370e-01 -4.90743488e-01 1.96394965e-01 3.82611960e-01
-3.18117887e-01 -8.16979527e-01 -8.30421567e-01 5.78231275e-01
-1.39491165e+00 -1.08483672e+00 4.87374477e-02 1.94365919e+00
9.94634926e-01 9.46001634e-02 -4.10882272e-02 2.07223907e-01
7.75201261e-01 3.60075444e-01 -2.96959966e-01 -6.16030097e-01
-4.72524345e-01 3.66662294e-01 2.23504826e-01 5.06911755e-01
-4.93580908e-01 9.21345890e-01 6.50071335e+00 8.05093765e-01
-1.47628164e+00 -3.07723433e-01 7.09646404e-01 -1.25315174e-01
-5.92345059e-01 -2.02607602e-01 -4.64531988e-01 5.63980937e-01
4.02755678e-01 -5.04740953e-01 5.22994757e-01 4.62751955e-01
1.69867650e-01 -1.04821667e-01 -1.15398979e+00 1.02988255e+00
5.44169664e-01 -1.50266373e+00 7.16226935e-01 -5.77924922e-02
1.14600122e+00 -8.25133562e-01 4.71014380e-01 -1.69642329e-01
3.82012069e-01 -1.65546358e+00 1.16918159e+00 1.04586864e+00
1.02894199e+00 -6.64628744e-01 4.14978594e-01 4.57423717e-01
-4.74948227e-01 1.65770575e-01 -1.73518449e-01 1.29468516e-01
4.03149873e-01 4.63072300e-01 -7.81860888e-01 4.02315319e-01
-7.97042325e-02 3.37817311e-01 -5.90586126e-01 5.54741859e-01
-3.09529752e-01 2.54665613e-01 2.29056433e-01 -4.27557707e-01
5.03278613e-01 -2.19436333e-01 3.83332461e-01 1.32339323e+00
5.40306628e-01 -1.80495396e-01 -1.26840398e-01 1.19984174e+00
-2.30994835e-01 1.09120011e-01 -6.87183082e-01 -3.36645424e-01
1.64465338e-01 1.20885527e+00 -8.63925457e-01 -4.60193157e-01
2.08676398e-01 1.58504498e+00 6.56802431e-02 4.52020824e-01
-8.17315638e-01 -5.01728654e-01 5.01820631e-02 9.73603502e-02
2.97332793e-01 -1.94022924e-01 -4.55629975e-01 -1.05196655e+00
1.28071047e-02 -1.32257724e+00 -5.77746928e-01 -1.16278887e+00
-1.21241271e+00 9.04344022e-01 -3.05814266e-01 -1.09368622e+00
-4.19531941e-01 -6.42851412e-01 -6.76157594e-01 1.03035903e+00
-9.14338529e-01 -1.34007812e+00 -5.03815413e-01 4.33981925e-01
8.35137725e-01 -3.65034163e-01 6.68975472e-01 -1.23052306e-01
-3.62941399e-02 4.18644160e-01 1.73082888e-01 5.97116258e-03
6.64906502e-01 -1.20433736e+00 4.76028264e-01 7.53853977e-01
4.77638394e-01 3.08180988e-01 1.26517510e+00 -4.35105056e-01
-1.22931051e+00 -9.51559365e-01 7.32600331e-01 -3.67444932e-01
5.76961577e-01 -4.45250928e-01 -6.75898552e-01 4.45517272e-01
4.74797666e-01 -1.78856522e-01 -4.67024036e-02 -6.32023394e-01
-3.12328219e-01 1.25651434e-01 -9.17255640e-01 9.51129615e-01
8.05219471e-01 -4.40426260e-01 -5.55487216e-01 3.07633221e-01
1.60648808e-01 -2.38886595e-01 -4.28165674e-01 8.45286772e-02
6.91119850e-01 -1.09599710e+00 7.77337253e-01 -4.48592722e-01
1.20139503e+00 -2.03591496e-01 3.32148224e-02 -1.55490279e+00
1.53937228e-02 -6.93599880e-01 2.80744791e-01 1.20544648e+00
4.91718411e-01 -3.12530786e-01 5.97111404e-01 2.52669364e-01
1.96989477e-01 -4.20943141e-01 -4.41810340e-01 -1.05631828e+00
1.41224846e-01 -8.67719650e-02 5.71668029e-01 7.56705582e-01
-2.15131596e-01 1.70428917e-01 -9.37593937e-01 -2.60292053e-01
6.04529023e-01 2.63235062e-01 1.00038218e+00 -8.60725164e-01
-5.00482142e-01 -6.85518205e-01 -4.31889772e-01 -7.96963871e-01
-3.42469364e-02 -6.71028078e-01 4.53681916e-01 -1.28640556e+00
3.16999286e-01 -4.63969931e-02 3.89312118e-01 -7.17860460e-02
2.00488195e-02 6.89910591e-01 4.40301925e-01 8.96930546e-02
-1.66552722e-01 3.94410849e-01 1.77781296e+00 -2.40287110e-01
7.07345605e-02 -3.03647369e-01 -4.98684883e-01 3.78139883e-01
5.99021196e-01 -1.15100428e-01 -3.86911303e-01 -3.30907196e-01
2.32105166e-01 1.79913610e-01 6.08366191e-01 -9.58069265e-01
6.74767420e-02 -2.35301360e-01 5.99760056e-01 -1.85824677e-01
2.18829066e-01 -4.54615861e-01 5.78334153e-01 5.65759659e-01
-6.56790137e-01 -1.74862310e-01 -6.05173558e-02 3.59123915e-01
-2.55666584e-01 -4.96282518e-01 1.07876086e+00 -4.74408567e-01
-4.11749989e-01 -5.66764623e-02 -6.20903671e-01 5.70095405e-02
1.02770388e+00 -3.87179732e-01 -1.82936490e-01 -6.99326932e-01
-6.84912741e-01 -3.14220309e-01 9.70240295e-01 4.06665921e-01
6.86838627e-01 -1.20805335e+00 -1.06641400e+00 1.52584612e-01
7.17249736e-02 -4.32136804e-01 1.78226367e-01 1.37542680e-01
-1.05015433e+00 1.47149235e-01 -5.17163396e-01 -5.40037692e-01
-1.14782393e+00 6.41762316e-01 2.59999007e-01 -2.04344615e-01
-5.86347520e-01 5.04853129e-01 9.50665772e-02 -1.45594999e-01
1.18170105e-01 -1.86236575e-02 1.39448643e-01 9.60827768e-02
5.69388628e-01 4.88209948e-02 -3.45144123e-02 -4.40191507e-01
2.71822214e-01 7.11388409e-01 -8.75668414e-03 -6.83953106e-01
1.06309962e+00 1.67032644e-01 2.02443093e-01 5.29291511e-01
8.76543224e-01 2.57157952e-01 -1.56192970e+00 -7.20475893e-03
-2.15294123e-01 -6.05280876e-01 -4.73859906e-01 -1.04425955e+00
-9.66747582e-01 8.46031547e-01 2.47433588e-01 3.29132289e-01
9.42458987e-01 -1.71757132e-01 4.71088439e-01 4.00674194e-01
4.30142224e-01 -1.03722143e+00 7.05247998e-01 2.72443384e-01
1.43806279e+00 -9.45634902e-01 -8.11970234e-02 -4.84329835e-02
-1.00710750e+00 1.36675322e+00 1.76502898e-01 -3.44873756e-01
-8.36560130e-02 4.95647162e-01 3.19893032e-01 -9.44000110e-02
-6.21410131e-01 9.96481031e-02 2.74466902e-01 6.24281704e-01
2.54561782e-01 -5.65775074e-02 -3.38625699e-01 -2.56847627e-02
-5.33824742e-01 5.25762960e-02 1.10208118e+00 8.05261075e-01
-3.29138041e-01 -1.00440145e+00 -4.70902532e-01 1.38369292e-01
-1.92670390e-01 2.43776441e-02 -7.27970958e-01 8.36302459e-01
-1.16261184e-01 6.55556798e-01 1.46383375e-01 -1.45151407e-01
3.34345102e-01 5.88098764e-02 7.97606289e-01 -3.92077237e-01
-5.17364204e-01 -2.46286094e-01 -1.80823609e-01 -1.52360544e-01
-2.97380596e-01 -5.33280671e-01 -7.17319667e-01 -3.67896616e-01
4.15944606e-02 -1.26234040e-01 7.68032372e-01 7.79678762e-01
-1.17146082e-01 6.10418916e-01 7.49593914e-01 -1.18456864e+00
-5.32604992e-01 -8.03221405e-01 -7.78995812e-01 7.29345500e-01
2.41889149e-01 -2.48216003e-01 -4.20730829e-01 5.85251629e-01] | [11.654012680053711, -0.0624605193734169] |
311e6813-5546-455d-8ff9-ee4efe7e0569 | locov-low-dimension-covariance-voting | 2204.00204 | null | https://arxiv.org/abs/2204.00204v1 | https://arxiv.org/pdf/2204.00204v1.pdf | LoCoV: low dimension covariance voting algorithm for portfolio optimization | Minimum-variance portfolio optimizations rely on accurate covariance estimator to obtain optimal portfolios. However, it usually suffers from large error from sample covariance matrix when the sample size $n$ is not significantly larger than the number of assets $p$. We analyze the random matrix aspects of portfolio optimization and identify the order of errors in sample optimal portfolio weight and show portfolio risk are underestimated when using samples. We also provide LoCoV (low dimension covariance voting) algorithm to reduce error inherited from random samples. From various experiments, LoCoV is shown to outperform the classical method by a large margin. | ['Ionel Popescu', 'Juntao Duan'] | 2022-04-01 | null | null | null | null | ['portfolio-optimization'] | ['time-series'] | [-2.45177999e-01 -1.04257483e-02 -1.56497851e-01 -1.65096238e-01
-1.08163452e+00 -1.01257920e+00 3.77546847e-01 -4.76428926e-01
-2.60223508e-01 1.03690541e+00 1.84786439e-01 -5.08448720e-01
-8.03594351e-01 -7.60385096e-01 -6.01835191e-01 -6.13996148e-01
2.52940808e-03 6.08534455e-01 -2.27416486e-01 1.59162998e-01
6.14910781e-01 3.95236611e-01 -9.93052185e-01 -1.16093598e-01
7.60502756e-01 1.43148637e+00 -3.03305954e-01 4.36699122e-01
1.97220650e-02 6.17885649e-01 -4.66756374e-01 -8.37487757e-01
1.25804162e+00 -3.84113163e-01 -8.35737064e-02 -1.57011062e-01
3.65574032e-01 -3.25319141e-01 8.74366611e-02 1.39818656e+00
5.51229954e-01 1.88535646e-01 1.05187285e+00 -8.56921136e-01
-3.48636866e-01 1.19064331e+00 -4.56995875e-01 2.73436636e-01
-1.60584692e-02 1.25530124e-01 1.43466604e+00 -1.03308070e+00
3.65154475e-01 1.17873573e+00 9.52522099e-01 5.05752712e-02
-1.13467431e+00 -9.83042419e-01 -1.49111636e-02 -3.94747883e-01
-1.25898063e+00 -3.76190215e-01 6.11336052e-01 -7.50520229e-01
1.02434766e+00 4.59810764e-01 4.92611200e-01 6.38178706e-01
4.19927716e-01 2.73028404e-01 1.11532652e+00 -1.44246370e-01
2.85197258e-01 4.88570839e-01 2.28270546e-01 3.09450209e-01
1.02439356e+00 8.87831092e-01 -4.39249158e-01 -4.25838053e-01
6.11967564e-01 -1.33388981e-01 -1.51736423e-01 -4.72569436e-01
-7.45216489e-01 1.05582762e+00 -2.44959041e-01 -1.01758540e-01
-3.06552231e-01 4.02649969e-01 8.16936418e-02 5.63021958e-01
2.35536784e-01 9.01833117e-01 -6.64119482e-01 -2.54280031e-01
-8.10879707e-01 5.93301833e-01 9.81827199e-01 1.08151567e+00
3.96697551e-01 4.28598970e-01 -3.26646954e-01 4.77542222e-01
2.88524538e-01 1.29964137e+00 7.99117610e-02 -1.32835424e+00
1.11195362e+00 3.97556365e-01 4.18232650e-01 -8.77289891e-01
-2.15205669e-01 -7.00214684e-01 -7.37310648e-01 4.80641156e-01
5.94716132e-01 -7.29040921e-01 -1.24761477e-01 1.25648105e+00
-6.96163177e-02 -1.18413694e-01 -1.31852506e-03 5.28425336e-01
1.81488786e-02 2.99566209e-01 -6.68819189e-01 -5.40081143e-01
7.51012862e-01 -6.69618845e-01 -6.64779246e-01 -2.63235211e-01
4.41594213e-01 -6.80318177e-01 6.09035015e-01 4.83080417e-01
-1.28294957e+00 -2.12413222e-02 -1.19818926e+00 9.11512196e-01
7.98682868e-02 -1.64998621e-01 7.64647484e-01 1.50671470e+00
-3.90224844e-01 1.20885205e+00 -2.49468356e-01 7.23618031e-01
6.47168815e-01 5.69445968e-01 1.08251683e-01 5.62018037e-01
-9.01016831e-01 8.89059007e-01 2.78203726e-01 1.84218660e-01
-5.26842356e-01 -1.29889750e+00 -4.92231935e-01 3.53846043e-01
4.87971187e-01 -5.81429005e-01 9.87225652e-01 -5.65432549e-01
-1.58619213e+00 -1.49625978e-02 3.30522597e-01 -7.11034417e-01
7.96372354e-01 -5.88607371e-01 -2.92640668e-03 -2.14568675e-01
-3.98593456e-01 -4.13035005e-01 9.67413962e-01 -5.94690979e-01
-5.93977749e-01 -1.11534446e-01 -3.08080226e-01 -5.05392216e-02
-2.85840094e-01 2.61888374e-02 3.26599538e-01 -7.84768760e-01
-1.92801848e-01 -1.02703559e+00 -5.54454982e-01 -5.72383344e-01
-2.85112530e-01 4.43728030e-01 1.31391600e-01 -3.33404064e-01
1.51211309e+00 -1.81662917e+00 -1.92735538e-01 8.25984418e-01
3.80431279e-03 -5.47223799e-02 1.74665466e-01 4.11804080e-01
-3.24110091e-01 2.69319683e-01 -1.00527689e-01 1.28494248e-01
5.27199745e-01 -2.87503809e-01 -7.40068614e-01 5.16670406e-01
-2.31222138e-01 8.59947145e-01 -5.09063125e-01 -6.09478354e-02
1.52708650e-01 -3.04287970e-01 -9.11911786e-01 1.45273373e-01
1.61558002e-01 -1.83824733e-01 -4.97066408e-01 5.28808892e-01
7.17958510e-01 -2.93048829e-01 2.90654927e-01 -1.78021342e-01
1.75946150e-02 1.11756317e-01 -1.87779176e+00 7.07534492e-01
-1.83483958e-01 4.56292450e-01 -1.94323614e-01 -7.87998557e-01
6.95266068e-01 1.29387081e-01 4.82699990e-01 -9.27057937e-02
4.13589865e-01 4.25271660e-01 3.02751213e-01 8.75866413e-02
2.98251629e-01 -6.28305554e-01 -1.57735884e-01 8.32240820e-01
-1.95228964e-01 -1.74076080e-01 2.24151880e-01 -2.63756275e-01
1.10678935e+00 -4.30520564e-01 4.72054631e-01 -7.08582401e-01
4.15133148e-01 -2.87713736e-01 8.09579194e-01 1.10770106e+00
-2.09509656e-02 5.01591861e-01 7.92638779e-01 -4.74725366e-02
-9.25500095e-01 -1.21291935e+00 -2.48838931e-01 3.18478912e-01
-3.77038121e-01 -1.50619954e-01 -4.57266390e-01 -8.61919582e-01
8.33156407e-01 7.74447739e-01 -6.36087775e-01 1.06057487e-01
-3.92698318e-01 -1.39473605e+00 6.75615901e-03 7.25387692e-01
1.52536452e-01 -6.50210798e-01 -1.48678109e-01 2.65293449e-01
6.73583448e-01 -6.41610682e-01 -8.49176705e-01 1.03985228e-01
-9.25806403e-01 -1.37017214e+00 -6.85019910e-01 1.98495016e-01
5.85194230e-01 -4.65581231e-02 1.17218935e+00 -5.01974881e-01
-1.48739785e-01 2.53520161e-01 -3.54131088e-02 -8.59723568e-01
1.15127545e-02 -2.53270209e-01 3.83877695e-01 -7.90157318e-02
1.11206837e-01 -4.45725143e-01 -5.77995360e-01 3.64723593e-01
-8.93371105e-02 -7.66603947e-01 6.30844355e-01 1.08733571e+00
3.59414577e-01 3.35340351e-01 6.54766738e-01 -1.19899547e+00
1.02953458e+00 -2.43561447e-01 -1.49219537e+00 4.32944506e-01
-1.27968884e+00 4.28500831e-01 3.62851530e-01 -5.48387468e-01
-9.76921320e-01 -4.17133719e-01 2.73564011e-01 -4.89525080e-01
1.01555145e+00 3.20566028e-01 -5.87608963e-02 -1.65314868e-01
4.35401529e-01 -3.08652371e-01 2.67518517e-02 -4.79731381e-01
1.63146511e-01 3.56992424e-01 -2.28374317e-01 -6.00533664e-01
1.11555934e+00 1.36126131e-01 4.52989817e-01 -1.77777663e-01
-1.07266819e+00 8.08608681e-02 -3.26910168e-01 -1.65377390e-02
3.29765707e-01 -6.27109289e-01 -9.91129816e-01 1.32307976e-01
-3.29156905e-01 -3.84189457e-01 -8.45928013e-01 9.95198727e-01
-6.19211435e-01 8.60487521e-02 -3.06736022e-01 -1.31068242e+00
-7.31917024e-01 -1.10092342e+00 4.11995471e-01 5.50594069e-02
-2.96701729e-01 -1.12961471e+00 2.44619936e-01 -2.77380459e-03
3.42128277e-01 1.64872393e-01 7.04513669e-01 -9.40149605e-01
-6.89127982e-01 -5.14773905e-01 -1.78592876e-01 6.41290605e-01
-4.20879535e-02 -5.45608578e-03 -4.32764471e-01 -3.34805667e-01
4.49465543e-01 2.84117490e-01 4.60687429e-01 8.29161942e-01
8.51433754e-01 -5.26941419e-01 -1.80866048e-02 7.86651492e-01
1.59973359e+00 3.08810830e-01 3.04298371e-01 3.96179169e-01
2.12866470e-01 6.79391205e-01 9.54088867e-01 9.30670977e-01
-4.81121480e-01 2.50635564e-01 -9.70060676e-02 6.52332604e-01
3.98737848e-01 -2.03327443e-02 4.75016445e-01 7.54625738e-01
1.29208704e-02 8.19091052e-02 -6.69595897e-01 1.71436206e-01
-1.83259964e+00 -1.17462397e+00 -1.50055170e-01 2.51391029e+00
5.39096951e-01 5.93884826e-01 5.38196005e-02 -2.84639746e-01
3.29203665e-01 1.46354288e-01 -6.62634850e-01 -2.66172796e-01
-1.56453058e-01 3.15598696e-01 1.45445347e+00 7.41288304e-01
-8.80448818e-01 3.78227234e-01 8.41231632e+00 9.52113330e-01
-2.26682082e-01 -1.10706471e-01 4.25701946e-01 -7.89819241e-01
-5.46642423e-01 1.27238050e-01 -1.56393743e+00 6.93736732e-01
9.40908015e-01 -7.92623758e-01 3.15083295e-01 1.09313965e+00
-1.13022871e-01 5.47636971e-02 -1.20439982e+00 1.01979804e+00
-1.56687453e-01 -1.61526799e+00 -3.07264179e-01 5.43489218e-01
1.01728117e+00 -3.61947626e-01 5.04538715e-01 4.73169953e-01
6.12320840e-01 -1.01799631e+00 5.47268689e-01 8.78213227e-01
4.50832784e-01 -1.14355516e+00 1.10755312e+00 2.61092097e-01
-1.01843214e+00 -4.10024911e-01 -8.88147056e-01 -3.21114361e-02
3.22527111e-01 9.74815547e-01 -4.48101193e-01 2.78358459e-01
5.94328225e-01 6.89491570e-01 -2.77727574e-01 8.05231392e-01
6.10139184e-02 4.32123929e-01 -5.29236972e-01 -1.85607642e-01
-4.13803943e-02 -9.34362292e-01 7.72278666e-01 7.06521869e-01
8.22774768e-01 2.12033004e-01 -4.56035703e-01 8.66814494e-01
7.62917921e-02 9.74744260e-02 -6.86717808e-01 -2.13267729e-01
4.76234645e-01 7.54961312e-01 -9.60080400e-02 -2.67057508e-01
-4.97959822e-01 1.32287413e-01 -4.37457487e-02 1.26333222e-01
-6.79909706e-01 -4.71512288e-01 8.77772689e-01 -9.54772905e-02
6.63931847e-01 -2.79247202e-02 -5.45092940e-01 -1.05056632e+00
4.15910408e-02 -9.60996747e-01 3.18369746e-01 -2.18698978e-01
-1.57507730e+00 8.84593502e-02 2.70927787e-01 -1.55337572e+00
-4.48831677e-01 -1.05770218e+00 -5.41046441e-01 1.08856714e+00
-8.32855761e-01 -1.21795550e-01 5.50323427e-01 1.04516307e-02
2.13109627e-01 -1.03550756e+00 5.35730660e-01 5.04913069e-02
-9.46096659e-01 1.05304515e+00 8.58959496e-01 -1.37885045e-02
5.14469087e-01 -1.39505887e+00 2.50285268e-01 7.86931038e-01
-1.45180538e-01 9.29821551e-01 8.94941807e-01 -8.63488793e-01
-1.50295746e+00 -8.30902934e-01 3.29769433e-01 -7.83609748e-01
1.15358448e+00 -1.35109082e-01 -4.23291862e-01 7.63283014e-01
1.08068891e-01 -2.56780475e-01 1.01880181e+00 4.06141490e-01
-9.19452757e-02 -4.57414299e-01 -1.17954063e+00 7.26932406e-01
8.65530431e-01 -1.30058169e-01 -6.67117178e-01 2.94160992e-01
4.38043863e-01 -1.71208635e-01 -1.37421846e+00 5.53082287e-01
9.23236549e-01 -1.15885735e+00 1.26569915e+00 -4.59047735e-01
1.48619460e-02 2.08360657e-01 -3.82438213e-01 -1.01788116e+00
-1.76480770e-01 -9.62892711e-01 -3.27736676e-01 1.25174940e+00
8.66471887e-01 -1.20988452e+00 1.18357110e+00 1.08355081e+00
4.09431398e-01 -6.16624355e-01 -7.64674008e-01 -1.39593244e+00
4.47396785e-01 -5.30973732e-01 7.81865656e-01 3.86773229e-01
-9.17201564e-02 7.25572482e-02 -6.02509677e-01 -4.10594791e-02
1.31504810e+00 3.54377538e-01 7.84204483e-01 -1.06486630e+00
-8.60208571e-01 -8.68595719e-01 8.57733488e-02 -7.60353029e-01
4.06301059e-02 -7.13238299e-01 -2.90983647e-01 -7.57979929e-01
3.27994466e-01 -5.11762738e-01 -4.74181473e-01 -2.75466681e-01
-3.18047404e-01 -2.24453017e-01 3.86053175e-01 -2.59964298e-02
-2.76979327e-01 4.80759829e-01 1.02861416e+00 -1.21809348e-01
-1.30475983e-01 3.73397738e-01 -9.80211556e-01 8.81118298e-01
7.69183934e-01 -8.69868398e-01 -3.97081614e-01 3.65191936e-01
6.96498930e-01 3.99140418e-01 -4.00555134e-01 -7.16209710e-01
-1.80612892e-01 -5.08175194e-01 4.55633432e-01 -8.90808642e-01
7.74227129e-03 -7.79057801e-01 6.19990230e-01 5.73669195e-01
-3.40838820e-01 1.17505886e-01 -2.74062492e-02 5.97487748e-01
9.76487994e-02 -9.98196065e-01 5.78144133e-01 -5.21509796e-02
2.27384508e-01 2.43256643e-01 -2.11881846e-01 2.98445612e-01
9.61936235e-01 8.68661255e-02 -2.33907372e-01 -2.08203733e-01
-5.72671771e-01 3.17020386e-01 2.28907228e-01 -1.32005408e-01
3.62326205e-01 -1.60514176e+00 -6.45303726e-01 7.80109614e-02
-4.22430217e-01 -5.57385027e-01 9.98154059e-02 8.19529891e-01
-4.40114677e-01 6.77238286e-01 3.84086967e-01 2.95702908e-02
-1.12155342e+00 5.49917936e-01 5.07953942e-01 -7.76806951e-01
-4.45821971e-01 1.20351124e+00 2.07792222e-01 -2.29219809e-01
2.17539236e-01 -2.11820096e-01 6.87081600e-04 2.01614574e-01
8.83645296e-01 9.37234163e-01 -2.40729615e-01 2.58687176e-02
-1.61994055e-01 9.77621853e-01 1.01157930e-02 -4.49454725e-01
1.23181307e+00 3.08883097e-02 -1.07650773e-03 4.28955674e-01
1.21169019e+00 3.68260682e-01 -1.52693999e+00 1.96364522e-02
2.80188531e-01 -1.04175031e+00 -3.70225161e-01 -4.28814739e-01
-1.21599066e+00 6.58928633e-01 6.41054571e-01 3.42125408e-02
6.63125336e-01 -5.68453908e-01 5.99479258e-01 6.73619390e-01
5.36369205e-01 -1.26605082e+00 -1.14457712e-01 4.23148870e-01
1.08341300e+00 -1.08620250e+00 8.36773932e-01 -2.35305652e-01
-7.89270878e-01 8.91032577e-01 1.11131653e-01 -8.25209141e-01
1.39536572e+00 5.34778833e-01 -1.83327436e-01 -5.91173023e-02
-7.98254013e-01 1.38635412e-01 6.84109926e-01 3.87123823e-01
-7.88537711e-02 6.78306669e-02 -4.63191330e-01 1.09154546e+00
-6.92009032e-01 -5.81445277e-01 3.85812163e-01 6.14894450e-01
-5.07304370e-01 -1.36017478e+00 -5.15813172e-01 1.02878249e+00
-9.48867798e-01 -1.98942989e-01 -1.24998823e-01 9.11592126e-01
-5.54102421e-01 7.40798414e-01 1.91446487e-02 -2.58353800e-01
6.82934165e-01 -1.23989627e-01 5.76263964e-01 -4.34316903e-01
-1.03224301e+00 2.70520985e-01 2.57313251e-01 -7.28876114e-01
-4.24218029e-02 -1.41324675e+00 -5.24784863e-01 -4.72288311e-01
-6.01433039e-01 2.59072870e-01 2.15618461e-01 6.70293570e-01
-8.72717947e-02 4.31729257e-01 1.00915527e+00 -6.11769855e-01
-1.55709600e+00 -8.16737652e-01 -1.30918145e+00 4.91978526e-02
-4.00501341e-02 -7.99543083e-01 -1.11189568e+00 -4.60293978e-01] | [4.986756324768066, 3.9770050048828125] |
7051561f-67cf-4f84-80cd-3da58e05e4c5 | class-overwhelms-mutual-conditional-blended | 2302.01516 | null | https://arxiv.org/abs/2302.01516v2 | https://arxiv.org/pdf/2302.01516v2.pdf | Class Overwhelms: Mutual Conditional Blended-Target Domain Adaptation | Current methods of blended targets domain adaptation (BTDA) usually infer or consider domain label information but underemphasize hybrid categorical feature structures of targets, which yields limited performance, especially under the label distribution shift. We demonstrate that domain labels are not directly necessary for BTDA if categorical distributions of various domains are sufficiently aligned even facing the imbalance of domains and the label distribution shift of classes. However, we observe that the cluster assumption in BTDA does not comprehensively hold. The hybrid categorical feature space hinders the modeling of categorical distributions and the generation of reliable pseudo labels for categorical alignment. To address these, we propose a categorical domain discriminator guided by uncertainty to explicitly model and directly align categorical distributions $P(Z|Y)$. Simultaneously, we utilize the low-level features to augment the single source features with diverse target styles to rectify the biased classifier $P(Y|Z)$ among diverse targets. Such a mutual conditional alignment of $P(Z|Y)$ and $P(Y|Z)$ forms a mutual reinforced mechanism. Our approach outperforms the state-of-the-art in BTDA even compared with methods utilizing domain labels, especially under the label distribution shift, and in single target DA on DomainNet. Source codes are available at \url{https://github.com/Pengchengpcx/Class-overwhelms-Mutual-Conditional-Blended-Target-Domain-Adaptation}. | ['Charles Ling', 'Boyu Wang', 'Pengcheng Xu'] | 2023-02-03 | null | null | null | null | ['blended-target-domain-adaptation', 'multi-target-domain-adaptation'] | ['computer-vision', 'computer-vision'] | [ 6.62648007e-02 -1.74925253e-01 -6.44602180e-01 -8.39439571e-01
-9.72346306e-01 -1.06021452e+00 5.58339894e-01 1.49360169e-02
-6.45192936e-02 9.41088259e-01 3.59339826e-02 -1.99652135e-01
-2.18386084e-01 -6.57474935e-01 -7.11332560e-01 -8.96723986e-01
3.01758587e-01 8.09150219e-01 -7.89058432e-02 -9.91122127e-02
7.33895227e-02 2.64769435e-01 -1.58017647e+00 3.27501476e-01
1.20314324e+00 9.34487343e-01 1.16448998e-02 1.39756262e-01
-4.66618627e-01 3.10188740e-01 -6.44950032e-01 -5.32611310e-01
3.58199090e-01 -2.96214521e-01 -4.00046617e-01 3.97146419e-02
7.30686069e-01 -3.69589418e-01 9.56451800e-03 1.39967215e+00
3.41835588e-01 -1.26641825e-01 1.40070963e+00 -1.61040151e+00
-1.03789890e+00 7.07270741e-01 -9.60415721e-01 8.54896940e-03
-9.25390571e-02 2.03961179e-01 1.21776021e+00 -9.79502976e-01
3.99059951e-01 1.27347696e+00 6.65375412e-01 6.39577389e-01
-1.74978733e+00 -1.31649208e+00 7.24043846e-01 1.54614866e-01
-1.46106899e+00 -3.54794592e-01 9.70795810e-01 -6.73548996e-01
6.53889716e-01 1.05894461e-01 1.69752225e-01 1.56712151e+00
-2.09322706e-01 7.23468304e-01 1.19240582e+00 -3.57308716e-01
2.25781351e-01 4.74034190e-01 4.75435257e-01 5.74572710e-03
3.15857649e-01 4.38968271e-01 -4.25276607e-01 -4.39315736e-01
7.15281844e-01 1.44059017e-01 3.31794143e-01 -7.13773966e-01
-1.04633164e+00 9.49530542e-01 2.13860109e-01 8.32716823e-02
-2.52970189e-01 -2.49478817e-01 3.17635536e-01 3.61520141e-01
5.63675404e-01 2.90076405e-01 -8.96550775e-01 1.34681478e-01
-7.08063781e-01 4.81738329e-01 4.96241897e-01 1.42597389e+00
9.49068010e-01 1.13240622e-01 -1.90489814e-01 1.25870025e+00
1.90555736e-01 8.05168629e-01 2.95857579e-01 -9.97238755e-01
4.87964392e-01 7.59154201e-01 2.68308043e-01 -6.68861806e-01
-2.54173249e-01 -5.50968051e-01 -8.34898770e-01 2.20414191e-01
9.49473441e-01 -1.44204736e-01 -8.81589949e-01 2.28132868e+00
3.95404786e-01 -1.05720155e-01 6.09651282e-02 6.81470931e-01
4.79378849e-01 3.44973356e-01 3.61764371e-01 -1.29556552e-01
1.31749594e+00 -5.14812171e-01 -4.46317405e-01 -3.61381233e-01
5.44250607e-01 -6.54564023e-01 1.35566556e+00 3.75525087e-01
-6.18163288e-01 -7.57019162e-01 -8.26441228e-01 2.10397050e-01
-3.95131409e-01 2.86340654e-01 3.63867909e-01 7.44254231e-01
-6.24363005e-01 1.66592866e-01 -3.66640389e-01 -2.99811631e-01
5.73980093e-01 5.23034811e-01 -3.23361129e-01 -1.64262891e-01
-1.21979880e+00 6.83358788e-01 2.68117726e-01 -3.88227880e-01
-8.63465011e-01 -7.96620011e-01 -6.84580028e-01 -4.29471172e-02
2.28589743e-01 -4.72296923e-01 1.17282462e+00 -1.25797987e+00
-1.24542344e+00 1.07058847e+00 -2.77027518e-01 -1.31759018e-01
3.10517281e-01 -1.70005575e-01 -5.29977143e-01 -3.90147954e-01
3.73299509e-01 9.88107741e-01 9.14531648e-01 -1.40864468e+00
-8.74403000e-01 -6.92548037e-01 -2.96315670e-01 3.06740105e-01
-4.57002401e-01 -1.68060064e-01 1.75243497e-01 -6.75026298e-01
8.21748152e-02 -8.42175364e-01 9.92419124e-02 -2.09907532e-01
-4.08244103e-01 -5.92325330e-01 5.42050600e-01 -4.12781715e-01
1.10182369e+00 -2.36394620e+00 1.25957523e-02 2.66492486e-01
2.34944806e-01 1.93075408e-04 -2.43084282e-01 1.51167408e-01
-3.54410678e-01 -2.15280373e-02 -3.20648283e-01 -2.00198859e-01
2.70604551e-01 2.32056230e-01 -7.05330670e-01 4.23495591e-01
3.34909171e-01 4.03216749e-01 -6.68109000e-01 -2.66861022e-01
6.12087958e-02 1.07709244e-01 -6.99270606e-01 2.80613899e-01
-4.27910864e-01 6.09186947e-01 -2.40590811e-01 9.82850671e-01
1.10987842e+00 -2.32200697e-01 4.00118083e-01 -6.22598827e-02
8.02587345e-02 2.44466722e-01 -1.18625307e+00 1.38881290e+00
1.45855501e-01 1.00404717e-01 -2.84161512e-02 -1.23969376e+00
1.46391308e+00 -1.42496526e-01 6.24981642e-01 -7.24742234e-01
2.37010382e-02 5.18140674e-01 1.55558079e-01 1.09520182e-01
5.09149060e-02 -3.69826078e-01 -4.95183647e-01 2.06077188e-01
2.19744980e-01 -2.90522072e-02 -2.76210010e-01 -8.87625366e-02
8.27230513e-01 2.16592044e-01 2.14612618e-01 -3.26465130e-01
3.22508931e-01 3.33201677e-01 8.84848177e-01 8.40814352e-01
-5.46495259e-01 4.63567019e-01 7.65976906e-01 -8.71393010e-02
-1.26985896e+00 -1.61965275e+00 -4.37082171e-01 1.57466829e+00
2.14808419e-01 2.70794988e-01 -4.63997573e-01 -1.04994535e+00
3.68733287e-01 9.73420620e-01 -6.28447771e-01 -2.92656481e-01
-2.63782471e-01 -7.67715096e-01 6.00973725e-01 5.56063056e-01
2.28019923e-01 -6.85835838e-01 2.61584699e-01 1.43153638e-01
-2.16126934e-01 -7.93572068e-01 -4.01010662e-01 5.69527626e-01
-7.96663642e-01 -9.92719829e-01 -7.58962154e-01 -7.07951427e-01
5.57110906e-01 -1.09971520e-02 1.25750196e+00 -6.63606882e-01
2.22055435e-01 1.52458996e-01 -3.44038904e-01 -4.66576576e-01
-2.59929061e-01 1.35689318e-01 3.63966197e-01 -1.35076389e-01
1.13267076e+00 -9.34199572e-01 -4.31267351e-01 7.83449829e-01
-6.23780370e-01 -2.55614996e-01 5.93388796e-01 1.18959939e+00
5.88028014e-01 -4.02393937e-02 1.02822638e+00 -1.18704355e+00
3.29114288e-01 -8.98901284e-01 -5.78359008e-01 2.33968437e-01
-6.39928341e-01 -1.56997398e-01 5.33756495e-01 -1.11026859e+00
-1.18230641e+00 4.00913469e-02 -3.48841771e-02 -5.84941804e-01
-6.91415846e-01 4.72570211e-02 -5.92399478e-01 5.61451137e-01
1.08489263e+00 1.24258913e-01 3.47454399e-02 -5.74448526e-01
4.39865798e-01 7.52518594e-01 4.92752224e-01 -1.08530831e+00
7.29540348e-01 4.24344093e-01 -5.46166182e-01 -2.16322049e-01
-7.49422133e-01 -4.56658363e-01 -8.16620469e-01 1.81653187e-01
4.55142975e-01 -1.32985687e+00 -2.81881183e-01 5.47742546e-01
-8.66554260e-01 -3.62119645e-01 -3.23497027e-01 5.00011981e-01
-5.72602332e-01 1.19774953e-01 -2.37017021e-01 -5.91411293e-01
3.80443931e-02 -9.34350610e-01 8.61844242e-01 1.47255823e-01
-4.35588509e-01 -8.84446561e-01 -3.25149000e-02 1.31686971e-01
2.05037385e-01 5.43807410e-02 1.29141915e+00 -1.28745949e+00
-1.21600173e-01 1.36827797e-01 -4.97845054e-01 5.70900619e-01
3.83107662e-01 -7.85506964e-02 -1.00557613e+00 -1.92410171e-01
-1.06250711e-01 -4.41002369e-01 5.10163069e-01 6.59607232e-01
1.08888113e+00 -1.39006838e-01 -2.83462018e-01 4.63230878e-01
1.18802106e+00 3.36588502e-01 3.16463262e-01 7.95197040e-02
6.65235579e-01 9.20474529e-01 9.47165668e-01 6.38574123e-01
5.28289974e-01 6.66344106e-01 2.77827799e-01 -3.46348970e-03
-1.01316750e-01 -3.01139712e-01 5.35183847e-01 2.70971864e-01
4.59697455e-01 7.17212036e-02 -1.03768051e+00 7.06689477e-01
-1.69016027e+00 -7.00924397e-01 -4.16585505e-02 2.16652417e+00
1.28624713e+00 1.15208149e-01 5.18262446e-01 -2.78459102e-01
1.08187687e+00 -1.74645483e-01 -1.10320067e+00 -2.23438457e-01
-2.98560202e-01 6.64721802e-02 4.85043794e-01 3.86809945e-01
-1.02836168e+00 1.03620124e+00 5.61941051e+00 1.24059010e+00
-9.53430176e-01 1.21105671e-01 6.94664776e-01 -2.66696475e-02
-4.12605971e-01 -3.43488418e-02 -1.30632198e+00 6.79574788e-01
5.80591202e-01 -3.45572270e-02 2.31309175e-01 1.23331928e+00
-3.34277809e-01 1.88571345e-02 -1.37869060e+00 9.67534244e-01
-2.04408780e-01 -7.51418114e-01 1.17401127e-02 3.10372382e-01
7.46638298e-01 -9.55996662e-02 5.41758358e-01 8.44183087e-01
9.29455459e-01 -8.46755445e-01 7.63922453e-01 -4.84751612e-02
1.29095280e+00 -6.43400908e-01 3.67025137e-01 4.64709461e-01
-8.92851114e-01 -3.56229216e-01 -6.10507846e-01 -2.44245399e-02
-2.92894602e-01 7.17057586e-01 -7.33190477e-01 2.54919708e-01
8.35725427e-01 7.91155815e-01 -4.85175282e-01 4.11097735e-01
5.37936427e-02 6.09713495e-01 -2.94022381e-01 4.26786542e-01
-4.60511930e-02 -6.95308894e-02 4.93364960e-01 9.63600099e-01
4.84587699e-01 -8.35223719e-02 1.91741899e-01 1.06053579e+00
1.71972036e-01 -1.40178483e-02 -7.96364307e-01 1.33393612e-02
9.71264243e-01 7.93482959e-01 -2.84053683e-01 -4.40458357e-01
-4.38237697e-01 6.20995343e-01 4.44560528e-01 5.62846124e-01
-1.00821984e+00 1.71941459e-01 1.08594537e+00 1.34618700e-01
2.35033378e-01 -3.44251022e-02 -9.50087845e-01 -1.34772468e+00
-9.50814709e-02 -1.18614352e+00 8.35848868e-01 -2.96974540e-01
-2.26102757e+00 2.74500042e-01 3.68698061e-01 -1.61977065e+00
-2.67836243e-01 -6.62864447e-01 -1.53416321e-01 1.13459623e+00
-1.44720066e+00 -1.28457856e+00 3.31577808e-02 1.04008210e+00
5.22511363e-01 -4.70652938e-01 8.48067284e-01 3.67093712e-01
-4.13332313e-01 1.02989888e+00 3.52195710e-01 4.41301428e-02
1.46555746e+00 -1.27527189e+00 5.31878397e-02 4.06894177e-01
-1.95334405e-01 7.02903807e-01 6.37561738e-01 -7.67172992e-01
-7.57135212e-01 -1.05303562e+00 6.63932979e-01 -7.74209499e-01
6.28943026e-01 -6.34239852e-01 -1.15594816e+00 8.07199240e-01
-7.55481645e-02 -6.20176978e-02 1.06968224e+00 5.19262612e-01
-1.12438250e+00 -2.85105616e-01 -1.42417014e+00 3.75764459e-01
1.15002275e+00 -4.27084327e-01 -7.16093183e-01 1.26623198e-01
6.71725631e-01 -2.13277131e-01 -8.83619010e-01 6.73385262e-01
5.82626283e-01 -8.99313807e-01 1.15216446e+00 -5.77821255e-01
3.56399417e-01 -1.98351920e-01 -6.25118077e-01 -1.28212190e+00
-5.52498817e-01 1.35842934e-01 1.96939394e-01 1.69204617e+00
5.21811426e-01 -8.95459175e-01 7.88271546e-01 7.43057489e-01
-7.53644528e-03 -1.98981121e-01 -1.01807380e+00 -9.54300284e-01
7.62368023e-01 -3.00994068e-01 7.71756351e-01 1.37098968e+00
-1.29819393e-01 2.56614864e-01 -2.08593383e-01 2.51770705e-01
7.88949251e-01 1.31268144e-01 8.36757958e-01 -1.38049531e+00
-2.74481505e-01 -5.52809775e-01 5.48168235e-02 -1.01545715e+00
4.47268933e-01 -7.99460948e-01 -1.29523590e-01 -8.33172262e-01
2.95205116e-01 -1.10593271e+00 -5.09505689e-01 6.02614641e-01
-1.76142782e-01 -2.86714975e-02 -4.86256648e-03 5.19422412e-01
-3.41274887e-01 5.04150987e-01 9.35465872e-01 -1.72955498e-01
-2.97357321e-01 -2.86179371e-02 -1.23640025e+00 5.67220867e-01
8.70303392e-01 -6.90262437e-01 -4.70070124e-01 -2.76466340e-01
-1.43867448e-01 -1.87826335e-01 3.03223699e-01 -7.19046354e-01
-6.44880757e-02 -5.95122099e-01 7.60919988e-01 -6.25903726e-01
3.19415122e-01 -1.02478695e+00 1.44899756e-01 1.01215236e-01
-2.88212985e-01 -1.95311531e-01 2.79201716e-01 5.35120904e-01
-2.45709583e-01 2.75524020e-01 9.88086164e-01 1.13177255e-01
-6.52917504e-01 1.72157928e-01 -7.17289522e-02 1.16221413e-01
9.70925748e-01 -3.18924874e-01 -6.54855788e-01 -4.23204638e-02
-7.33828664e-01 2.33738482e-01 6.23142540e-01 4.01191384e-01
2.44222149e-01 -1.52942050e+00 -8.28581810e-01 4.50098962e-01
4.38148201e-01 1.53205916e-01 4.18690711e-01 6.51400089e-01
2.94889927e-01 5.78141883e-02 -5.54452181e-01 -1.06956768e+00
-1.02808774e+00 4.99143183e-01 2.45037630e-01 -3.36247951e-01
-6.14563264e-02 8.91124785e-01 9.14846241e-01 -9.74671662e-01
2.78945357e-01 -7.11921677e-02 -2.46788070e-01 2.63258338e-01
1.45338565e-01 1.19913906e-01 -2.48196974e-01 -4.35760200e-01
-4.76299584e-01 4.53110576e-01 -3.85229707e-01 -1.13511629e-01
1.18059206e+00 -2.61662453e-01 8.68008509e-02 4.82893288e-01
9.10128832e-01 -4.65418771e-02 -1.59489644e+00 -5.70184827e-01
2.69602723e-02 -5.78828931e-01 -7.11694956e-01 -1.20504522e+00
-6.08645499e-01 1.04646039e+00 7.28624225e-01 2.24633161e-02
1.22094309e+00 2.00653493e-01 3.32032323e-01 -1.69777066e-01
2.83208340e-01 -1.08914256e+00 2.36059099e-01 6.01847947e-01
6.76726043e-01 -1.40764403e+00 -2.67182529e-01 -5.02017200e-01
-1.10837996e+00 6.65447712e-01 1.10801780e+00 -1.66403651e-01
5.75054169e-01 1.28307983e-01 2.15812340e-01 8.69914591e-02
-6.63084686e-01 -1.94731534e-01 1.88972518e-01 1.13710177e+00
2.79967636e-01 3.95917952e-01 -6.45868033e-02 1.07118726e+00
-3.47940102e-02 -4.40096438e-01 2.36833226e-02 5.24825454e-01
-3.19139153e-01 -1.59230626e+00 -7.14866638e-01 4.82761174e-01
-2.92519152e-01 -1.12575509e-01 -4.90320385e-01 7.58817613e-01
4.39147115e-01 8.30723763e-01 3.25765371e-01 -4.19856817e-01
3.95861775e-01 3.89197022e-01 4.23141420e-01 -7.70627320e-01
-3.60393822e-01 2.90850997e-01 -1.24787696e-01 -5.35016134e-02
-2.04031795e-01 -9.25167799e-01 -1.00105727e+00 -3.94828379e-01
-5.52095957e-02 -8.82342830e-02 4.41011637e-01 5.76702237e-01
4.72387373e-01 7.60350302e-02 7.19384015e-01 -5.78661978e-01
-9.50427651e-01 -1.05163467e+00 -8.81122112e-01 6.41874433e-01
1.83984920e-01 -1.26244330e+00 -4.93681937e-01 1.25221953e-01] | [10.340092658996582, 3.1289420127868652] |
9e8c1f2a-bd82-4f3d-86ac-3e7127443a03 | adversarially-guided-portrait-matting | 2305.02981 | null | https://arxiv.org/abs/2305.02981v2 | https://arxiv.org/pdf/2305.02981v2.pdf | Adversarially-Guided Portrait Matting | We present a method for generating alpha mattes using a limited data source. We pretrain a novel transformerbased model (StyleMatte) on portrait datasets. We utilize this model to provide image-mask pairs for the StyleGAN3-based network (StyleMatteGAN). This network is trained unsupervisedly and generates previously unseen imagemask training pairs that are fed back to StyleMatte. We demonstrate that the performance of the matte pulling network improves during this cycle and obtains top results on the human portraits and state-of-the-art metrics on animals dataset. Furthermore, StyleMatteGAN provides high-resolution, privacy-preserving portraits with alpha mattes, making it suitable for various image composition tasks. Our code is available at https://github.com/chroneus/stylematte | ['Karen Efremyan', 'Sergej Chicherin'] | 2023-05-04 | null | null | null | null | ['image-matting'] | ['computer-vision'] | [ 6.48005903e-01 3.66268903e-02 -9.59673896e-02 -5.76332867e-01
-5.44240654e-01 -7.27493107e-01 8.08422744e-01 -6.97646737e-01
-1.99314758e-01 6.53292358e-01 1.14203699e-01 -6.60698339e-02
5.14088213e-01 -1.03034234e+00 -1.01174545e+00 -5.43973744e-01
2.89672434e-01 4.42534804e-01 -2.23491281e-01 -2.73449868e-01
-3.47972155e-01 2.97033131e-01 -1.32941198e+00 8.78615320e-01
6.81344092e-01 8.76091719e-01 -1.21222228e-01 7.64845371e-01
2.83760577e-01 4.95327175e-01 -5.66784084e-01 -1.14626503e+00
1.03701484e+00 -8.07078302e-01 -5.84141076e-01 2.93360382e-01
1.11613345e+00 -5.31650066e-01 -7.78708577e-01 1.00305200e+00
1.57322809e-01 -2.55409986e-01 4.55259591e-01 -1.60469210e+00
-9.06016767e-01 7.65974760e-01 -5.95780730e-01 -2.04283506e-01
-2.27309298e-02 6.97910190e-01 9.71616268e-01 -8.73602867e-01
9.94273305e-01 1.29549062e+00 5.30963957e-01 8.51076126e-01
-1.59174454e+00 -1.06779313e+00 -2.04101607e-01 -6.05787411e-02
-1.43333352e+00 -7.52236009e-01 6.93911493e-01 -2.46130228e-01
3.28546494e-01 5.12468636e-01 9.05439198e-01 1.52819753e+00
1.30197316e-01 1.05656469e+00 1.46625888e+00 -3.52927782e-02
-1.15411662e-01 1.96380273e-01 -5.27581394e-01 8.54695022e-01
5.23920171e-02 1.70641914e-01 -6.66527152e-01 -2.95216199e-02
9.06691790e-01 -2.35852227e-02 -1.75885692e-01 -3.62416387e-01
-1.29387164e+00 6.02295458e-01 7.99836755e-01 7.11788088e-02
-2.17900783e-01 3.96088153e-01 1.23969428e-01 6.15266800e-01
5.28431952e-01 4.45858657e-01 1.64706871e-01 3.43142539e-01
-1.24987555e+00 2.62841523e-01 5.11976361e-01 1.29663920e+00
8.26540172e-01 2.08322376e-01 -3.06463957e-01 7.15234280e-01
-6.39741868e-02 8.98613393e-01 6.15381775e-03 -9.35623765e-01
3.24557334e-01 5.01145482e-01 -3.90234619e-01 -8.33035648e-01
3.16415429e-01 -4.63298500e-01 -1.22170734e+00 4.44506019e-01
2.63545185e-01 -6.89037591e-02 -1.52248013e+00 1.68145406e+00
2.26530358e-01 7.87343085e-02 -7.18635917e-02 8.25939894e-01
8.14856708e-01 7.32193351e-01 -2.33732760e-01 3.44867676e-01
1.39149737e+00 -1.18862367e+00 -6.07078552e-01 -3.88791800e-01
2.35636458e-01 -5.78775823e-01 1.06118190e+00 3.61250281e-01
-1.16113198e+00 -4.49728966e-01 -1.12078774e+00 -3.29672366e-01
-3.79062384e-01 1.55049384e-01 3.89319807e-01 6.48722589e-01
-1.33667457e+00 6.36557519e-01 -6.48140132e-01 -4.78379846e-01
1.12570727e+00 1.77649245e-01 -6.72685981e-01 -2.29153961e-01
-6.95483327e-01 5.10956466e-01 3.66389722e-01 2.36534160e-02
-1.55949640e+00 -8.19891930e-01 -8.78228545e-01 -2.22384244e-01
2.30690017e-01 -1.09810126e+00 9.56777930e-01 -1.52198482e+00
-1.35795665e+00 1.36697984e+00 1.13192901e-01 -7.40459561e-01
9.52253461e-01 9.29133669e-02 -3.82520616e-01 2.01401010e-01
1.13578129e-03 1.41713977e+00 1.26975155e+00 -1.49335659e+00
-4.00347888e-01 -3.84335108e-02 -2.26285875e-01 4.81183343e-02
-3.03080410e-01 -2.48415142e-01 -4.86080676e-01 -9.62059975e-01
-5.17759502e-01 -1.14964151e+00 1.85436953e-03 5.92871308e-01
-8.67989004e-01 5.06408334e-01 9.21736956e-01 -6.48612142e-01
8.02916288e-01 -2.16772985e+00 1.87464595e-01 4.22948867e-01
3.86609018e-01 3.78671527e-01 -5.93060315e-01 3.35906267e-01
-2.29523987e-01 3.50154757e-01 -7.86254644e-01 -6.19116008e-01
-1.41898274e-01 1.61464587e-01 -3.38156998e-01 3.22858542e-01
3.53526235e-01 1.24034405e+00 -6.91899598e-01 -4.11818057e-01
1.00180253e-01 4.37987626e-01 -5.09047270e-01 3.26271862e-01
-4.99937117e-01 4.87075537e-01 -1.99449230e-02 9.50924754e-01
1.02614009e+00 -1.69497803e-01 2.59434193e-01 -4.07425970e-01
2.64234126e-01 -1.84350684e-01 -4.87624258e-01 1.86034834e+00
-6.31970093e-02 7.79758155e-01 5.63620143e-02 -3.85706693e-01
9.09651160e-01 -3.32284579e-03 3.02026868e-01 -5.74117720e-01
3.16449255e-01 1.18152127e-02 -2.22075716e-01 -1.24626458e-01
4.39238429e-01 -5.30497404e-04 -1.43851846e-01 4.83721048e-01
4.05420631e-01 -2.45135590e-01 2.07583994e-01 2.85784811e-01
1.17254412e+00 2.09052011e-01 1.29048582e-02 -2.10602134e-01
2.18582794e-01 2.75465399e-02 5.19508600e-01 5.61281085e-01
3.95902880e-02 9.65408504e-01 2.49630302e-01 -7.29505658e-01
-1.75593102e+00 -1.38684928e+00 1.24796182e-01 7.12682307e-01
-1.62473455e-01 -7.10336566e-01 -9.65439022e-01 -1.01165712e+00
7.89124966e-02 6.06961548e-01 -1.06538534e+00 -5.35072051e-02
-5.13416588e-01 -4.00751859e-01 8.65782320e-01 8.69041830e-02
1.04847908e+00 -9.92226601e-01 -9.20417458e-02 -3.67411077e-01
-2.26050124e-01 -9.16715443e-01 -7.94006169e-01 -3.41256946e-01
-4.85704362e-01 -9.10862267e-01 -7.85304487e-01 -6.33791745e-01
9.76728141e-01 2.12835595e-01 1.22346115e+00 1.81066498e-01
-2.76999861e-01 2.30907783e-01 -1.16327867e-01 -4.05124485e-01
-7.47734129e-01 3.32633317e-01 -1.98374838e-01 4.51625794e-01
1.26072377e-01 -8.63395512e-01 -7.75089502e-01 3.57808381e-01
-1.30891609e+00 6.45621300e-01 6.91211045e-01 8.10139716e-01
7.83440053e-01 -3.05742770e-01 5.87644577e-02 -1.13891792e+00
1.48970127e-01 -2.79957533e-01 -6.27877712e-01 2.35848933e-01
-4.02811199e-01 -1.07373923e-01 6.36226356e-01 -3.34433138e-01
-9.71365690e-01 2.02154353e-01 -1.54550701e-01 -8.84111702e-01
-8.74131992e-02 -1.84709266e-01 -2.78031349e-01 -1.95536062e-01
7.13080287e-01 3.61210078e-01 3.91567409e-01 -3.02985251e-01
4.53272611e-01 3.81174028e-01 8.20009530e-01 -3.39205086e-01
1.52741134e+00 8.50661039e-01 -5.04585803e-02 -5.74359119e-01
-6.99436963e-01 3.89671981e-01 -3.95930737e-01 -2.64946669e-01
8.89277399e-01 -1.10607839e+00 -4.74132150e-01 7.30971336e-01
-6.00720346e-01 -6.67793930e-01 -5.64364851e-01 -2.18933925e-01
-5.36445856e-01 -3.01641319e-02 -5.37664175e-01 -2.58807719e-01
-8.01373780e-01 -8.97462368e-01 9.57973540e-01 1.57521710e-01
-6.90433308e-02 -7.56217539e-01 -7.20078824e-03 5.79629600e-01
3.97514164e-01 7.52197683e-01 5.00795901e-01 -2.77193815e-01
-9.36965883e-01 9.22529921e-02 -1.19153999e-01 4.50858891e-01
1.40015781e-01 -2.67467070e-02 -1.13119650e+00 -5.43585777e-01
-3.92359525e-01 -4.81055230e-01 1.18514860e+00 6.62176237e-02
1.36489487e+00 -7.32059598e-01 -2.14396417e-01 1.37871933e+00
1.33998644e+00 -2.09307164e-01 1.15655935e+00 3.19549620e-01
1.00369549e+00 3.53440285e-01 3.31223160e-01 1.65734574e-01
2.78202653e-01 4.72369432e-01 4.43026006e-01 -4.23030734e-01
-4.85077947e-01 -8.84009540e-01 4.68235672e-01 3.94442737e-01
7.40847215e-02 -5.81598282e-01 -4.75788623e-01 6.56583071e-01
-1.65946364e+00 -1.07364035e+00 1.95624217e-01 1.88202214e+00
1.06093907e+00 -1.34171367e-01 2.70960540e-01 -3.39184940e-01
7.50782371e-01 4.38769788e-01 -7.63095498e-01 -2.92237431e-01
-5.53258657e-01 2.09896296e-01 6.95295811e-01 2.09001556e-01
-1.06229436e+00 1.23772144e+00 6.41770935e+00 9.20118034e-01
-1.09522355e+00 -4.14168183e-03 1.11364067e+00 -2.34204471e-01
-8.04202676e-01 8.31945706e-03 -4.93450373e-01 4.84182209e-01
6.10494912e-01 -2.30493948e-01 7.85668433e-01 6.98424757e-01
-1.69042528e-01 2.12224811e-01 -1.12853146e+00 9.86339092e-01
2.23132074e-01 -1.61750960e+00 5.49319506e-01 3.21345538e-01
9.62635934e-01 -3.18991244e-02 5.02155244e-01 -1.03004113e-01
5.58400452e-01 -1.19395757e+00 7.85249233e-01 2.90040344e-01
1.58457589e+00 -6.71366930e-01 3.33136410e-01 -1.93714291e-01
-8.45431149e-01 2.14736581e-01 -2.19196722e-01 3.87633860e-01
8.23344514e-02 4.87704039e-01 -1.18808329e+00 4.59362835e-01
6.44749641e-01 9.58295047e-01 -8.93591225e-01 8.32073092e-01
-3.05325955e-01 6.29577100e-01 -3.42171669e-01 4.40139204e-01
3.94213721e-02 -2.76429087e-01 7.24123836e-01 1.04836059e+00
4.25410151e-01 -1.94495067e-01 -1.35630101e-01 1.16213369e+00
-8.44734013e-01 -3.43664348e-01 -9.32786763e-01 -3.09205264e-01
5.35608888e-01 1.57864106e+00 -5.31612754e-01 -4.70597416e-01
2.44012162e-01 1.39381206e+00 1.49286404e-01 1.83424056e-01
-8.26306224e-01 -9.99148116e-02 9.74640429e-01 3.87052506e-01
4.62256521e-01 9.70883071e-02 -3.35831851e-01 -1.41747499e+00
-1.96174130e-01 -1.46563804e+00 4.80896086e-01 -9.85250771e-01
-1.40870166e+00 8.28433335e-01 6.44934773e-02 -1.43826056e+00
-6.14469871e-02 -4.27308500e-01 -6.92571044e-01 4.29829150e-01
-1.12798452e+00 -1.88310635e+00 -4.61712956e-01 7.69461870e-01
4.07336801e-01 -3.10852021e-01 8.05621386e-01 1.14930399e-01
-4.44401175e-01 1.12257767e+00 -9.68309343e-02 4.96435404e-01
9.88169312e-01 -1.11663103e+00 1.02182329e+00 1.13535333e+00
1.90743312e-01 3.23284000e-01 6.08132601e-01 -7.57052124e-01
-1.49161434e+00 -1.57546854e+00 3.11440259e-01 -5.12033880e-01
3.02130461e-01 -9.38685119e-01 -5.44213235e-01 1.10168767e+00
9.07887220e-01 -3.78777236e-02 6.49651945e-01 -4.06598538e-01
-7.67084718e-01 -5.22465229e-01 -1.47924244e+00 8.65540683e-01
1.41181207e+00 -4.10691857e-01 -9.06404033e-02 2.31739432e-01
6.35681391e-01 -6.19862318e-01 -9.11805153e-01 7.87709206e-02
7.77220488e-01 -8.96728098e-01 8.27890098e-01 -2.09873945e-01
8.00756454e-01 -5.96807301e-01 1.18841097e-01 -1.52374554e+00
-3.97336245e-01 -9.87007499e-01 1.72086164e-01 1.32628345e+00
5.30591369e-01 -5.60635626e-01 9.51159358e-01 3.17058980e-01
7.23981336e-02 -3.49156976e-01 -6.83274806e-01 -6.68313503e-01
-1.67287271e-02 1.14125349e-01 1.05238080e+00 1.06163394e+00
-6.66491866e-01 2.67509878e-01 -9.59991097e-01 -2.14574412e-01
1.08647108e+00 9.43773463e-02 1.25337052e+00 -5.81535876e-01
-1.79476514e-01 -1.15095740e-02 -4.72471744e-01 -7.72980332e-01
-2.93290261e-02 -1.10839176e+00 -1.14521876e-01 -1.01835370e+00
3.10427934e-01 -3.33631366e-01 -2.99537256e-02 9.61924791e-01
1.32974451e-02 1.11587358e+00 5.84431231e-01 1.59178302e-01
-2.71592647e-01 5.48547089e-01 1.61956680e+00 -5.65137923e-01
2.03561455e-01 -3.15197676e-01 -8.37779522e-01 2.81600267e-01
9.88562524e-01 -5.64564764e-01 -4.14526492e-01 -7.67731071e-01
1.00352719e-01 -4.51928139e-01 5.40913641e-01 -1.14185727e+00
-3.53487767e-02 -1.27224565e-01 8.83071542e-01 -5.81872940e-01
5.56466758e-01 -7.79145896e-01 7.75950134e-01 3.13502252e-01
-4.87705886e-01 8.52021351e-02 2.12163866e-01 2.90417790e-01
4.61782813e-02 3.29913378e-01 8.73931885e-01 -3.46006483e-01
-4.22254533e-01 8.31894934e-01 -1.62784785e-01 7.68896053e-03
9.96056437e-01 -2.33398929e-01 -5.61023355e-01 -6.26413226e-01
-3.25857103e-01 1.92987338e-01 1.10589206e+00 4.21985060e-01
7.62020469e-01 -1.71587503e+00 -1.09464097e+00 4.26127136e-01
2.60447353e-01 3.40102129e-02 2.12214932e-01 3.41126353e-01
-6.20379031e-01 -2.06803098e-01 -7.74472356e-01 -6.02524281e-01
-1.53388715e+00 5.15538990e-01 3.26816827e-01 -3.95374149e-02
-6.75430536e-01 9.67342615e-01 5.51926434e-01 -4.16954815e-01
-1.45575672e-01 -5.57900667e-02 3.63124043e-01 -2.40190759e-01
6.75676405e-01 -1.10136613e-01 -3.35992873e-01 -6.32804036e-01
-1.16484419e-01 2.47771695e-01 -3.39013815e-01 -2.76404232e-01
1.44542050e+00 3.56697068e-02 -2.18758956e-01 -4.38366942e-02
1.21501696e+00 -6.42113388e-02 -1.49443483e+00 -2.25549757e-01
-7.11832821e-01 -9.02337730e-01 -1.77758157e-01 -8.41921329e-01
-1.37041497e+00 6.07738137e-01 6.31755948e-01 -2.19593987e-01
1.41367543e+00 -3.16429824e-01 1.11964810e+00 2.98410475e-01
1.90523341e-01 -7.82911479e-01 1.06829613e-01 5.99168167e-02
1.12619376e+00 -1.04455376e+00 1.50984168e-01 -3.86536747e-01
-7.68830538e-01 8.54262292e-01 7.73187518e-01 -2.84068048e-01
2.65543461e-01 3.77044171e-01 2.82328963e-01 -3.46030220e-02
-8.77366543e-01 -1.22065246e-02 2.71257371e-01 8.11297238e-01
-1.44194350e-01 1.47870153e-01 2.86203533e-01 -1.24476254e-01
-6.74564838e-01 5.25788814e-02 4.41102177e-01 9.19988155e-01
1.36313692e-01 -1.39616799e+00 -4.57871139e-01 4.97697592e-01
-2.98341751e-01 -1.81394219e-01 -9.22790289e-01 6.46748781e-01
2.71473527e-01 6.28821731e-01 1.58231765e-01 -8.81387711e-01
1.01898223e-01 -1.98260531e-01 5.98600090e-01 -2.91165203e-01
-8.60777020e-01 -1.30196884e-01 3.32851589e-01 -6.13316834e-01
-3.13739270e-01 -3.99472356e-01 -3.61890554e-01 -1.02845752e+00
1.51959866e-01 -8.43250155e-02 3.66131216e-01 4.59545612e-01
7.94872522e-01 2.46396959e-01 8.29181433e-01 -6.85555220e-01
1.34639949e-01 -8.00566077e-01 -1.40488029e-01 6.47129357e-01
2.91629910e-01 2.44576912e-02 -4.70576137e-02 4.48759258e-01] | [11.817042350769043, -0.3354453146457672] |
2cdbd0f1-58a0-4012-ae6a-528690c21b71 | alt-an-automatic-system-for-long-tail | 2305.11390 | null | https://arxiv.org/abs/2305.11390v1 | https://arxiv.org/pdf/2305.11390v1.pdf | ALT: An Automatic System for Long Tail Scenario Modeling | In this paper, we consider the problem of long tail scenario modeling with budget limitation, i.e., insufficient human resources for model training stage and limited time and computing resources for model inference stage. This problem is widely encountered in various applications, yet has received deficient attention so far. We present an automatic system named ALT to deal with this problem. Several efforts are taken to improve the algorithms used in our system, such as employing various automatic machine learning related techniques, adopting the meta learning philosophy, and proposing an essential budget-limited neural architecture search method, etc. Moreover, to build the system, many optimizations are performed from a systematic perspective, and essential modules are armed, making the system more feasible and efficient. We perform abundant experiments to validate the effectiveness of our system and demonstrate the usefulness of the critical modules in our system. Moreover, online results are provided, which fully verified the efficacy of our system. | ['Longfei Li', 'Qitao Shi', 'Meng Li', 'Xinxing Yang', 'Yue Zhang', 'Yankun Ren', 'Jun Zhou', 'Ya-Lin Zhang'] | 2023-05-19 | null | null | null | null | ['architecture-search', 'philosophy'] | ['methodology', 'miscellaneous'] | [-9.43308622e-02 -2.01636955e-01 -5.57457268e-01 -3.51756871e-01
-2.95556158e-01 -4.78363670e-02 3.39488447e-01 -2.74381191e-01
-6.30561471e-01 7.01528966e-01 -2.28243992e-01 -5.59504330e-01
-2.60948241e-01 -7.90949106e-01 -5.01195967e-01 -6.68608367e-01
2.36942038e-01 3.79371136e-01 3.03835329e-03 -2.02165514e-01
4.71055210e-01 2.16138676e-01 -1.43569183e+00 -2.30601802e-01
1.01264608e+00 1.09361684e+00 3.81564558e-01 1.60632491e-01
-1.51683554e-01 9.33090985e-01 -3.74915451e-01 -6.11787558e-01
1.24786727e-01 -3.67293745e-01 -6.29500031e-01 7.78045654e-02
-3.42731029e-01 -3.10834467e-01 -2.23029360e-01 9.73400533e-01
6.92806363e-01 1.90601543e-01 4.91334915e-01 -1.22394872e+00
-7.07543120e-02 7.56972611e-01 -6.89627588e-01 1.88956380e-01
-2.28911147e-01 1.00462377e-01 8.64373267e-01 -7.12463200e-01
-4.66820486e-02 9.70355332e-01 3.20198447e-01 4.56592947e-01
-5.56334734e-01 -9.84968245e-01 4.10237402e-01 5.14654994e-01
-1.56577456e+00 -5.46296895e-01 9.89855587e-01 -1.92003146e-01
8.63763392e-01 2.02072635e-01 6.75524831e-01 9.13643539e-01
1.45874053e-01 8.68377209e-01 9.58888173e-01 -6.93226099e-01
4.15596843e-01 4.85474974e-01 2.07205608e-01 7.80743897e-01
4.11100626e-01 8.78229961e-02 -2.58741081e-01 -1.21309139e-01
6.59436822e-01 2.52579331e-01 6.05624355e-02 -5.05753085e-02
-8.38199437e-01 7.93598413e-01 5.68202585e-02 2.94281244e-01
-3.10193568e-01 1.34078637e-01 1.83152139e-01 3.75577225e-03
6.69674575e-01 1.52503818e-01 -5.35501719e-01 -6.19465820e-02
-1.09337926e+00 1.11822203e-01 6.30176067e-01 1.14661419e+00
4.61542994e-01 1.08532824e-01 5.47893718e-02 8.01278651e-01
4.85094815e-01 3.13285828e-01 7.34144211e-01 -7.84502387e-01
6.06081188e-01 7.63151109e-01 1.20295122e-01 -9.97252584e-01
-4.25987035e-01 -6.99676275e-01 -1.12195277e+00 -4.21399444e-01
-5.75953759e-02 -3.62974495e-01 -4.13259834e-01 1.77948368e+00
4.22433436e-01 3.85578901e-01 -2.55987048e-01 7.31032014e-01
4.38987345e-01 6.67546153e-01 1.47429839e-01 -6.61392689e-01
1.36114001e+00 -1.32456982e+00 -7.64748693e-01 -1.78988785e-01
7.58932292e-01 -4.33678836e-01 9.82029140e-01 4.63493139e-01
-1.23309553e+00 -4.57247287e-01 -9.47029114e-01 4.42999542e-01
-3.28152329e-01 3.49855423e-01 1.06828141e+00 7.47103512e-01
-5.16084254e-01 3.38887304e-01 -6.49486721e-01 -9.84772891e-02
1.21947207e-01 3.84289861e-01 1.96346343e-01 8.70309472e-02
-1.27501416e+00 8.27738047e-01 7.49049783e-01 4.54574615e-01
-5.86980402e-01 -2.81065404e-01 -5.83117545e-01 3.48313838e-01
7.18189061e-01 -8.90600383e-01 1.33580732e+00 -7.81968057e-01
-1.42864907e+00 3.74191374e-01 -8.26153234e-02 -6.05597198e-01
5.45786500e-01 -5.92630953e-02 -5.93047976e-01 -1.10505663e-01
-5.24367630e-01 1.81351990e-01 6.08220279e-01 -9.04825151e-01
-9.04875219e-01 -1.75160572e-01 2.31135786e-01 1.09114915e-01
-9.97614503e-01 2.03416511e-01 -7.27081776e-01 -6.29424214e-01
-1.32875502e-01 -7.89724112e-01 -6.91549063e-01 -5.45585513e-01
-3.03705931e-01 -3.26459885e-01 2.13849232e-01 -5.98917186e-01
2.17093515e+00 -1.79948115e+00 7.80940875e-02 4.45845783e-01
4.05530557e-02 2.69485563e-01 2.56820917e-01 3.01575989e-01
1.63564324e-01 2.93042660e-01 -3.47815692e-01 -2.85652667e-01
5.49832322e-02 1.45387515e-01 -2.60816872e-01 6.51721731e-02
-1.78203538e-01 7.67688096e-01 -3.29872906e-01 -1.00652277e+00
5.07813971e-03 -1.00424446e-01 -6.30354524e-01 4.20256943e-01
-4.31566060e-01 5.08425198e-02 -8.68001580e-01 7.63199985e-01
5.56512356e-01 -3.75338554e-01 2.53623039e-01 -9.18215979e-03
-9.57953408e-02 2.05454566e-02 -1.26359546e+00 1.25094259e+00
-7.61769831e-01 -2.05521867e-01 -4.61391248e-02 -1.28515089e+00
7.74702311e-01 1.90701798e-01 4.08724755e-01 -6.52819037e-01
4.37876821e-01 2.78089851e-01 -6.56494573e-02 -7.69271851e-01
4.61526424e-01 4.09411304e-02 -3.21941487e-02 4.58377063e-01
-2.16201618e-01 3.47409487e-01 3.48579228e-01 -3.30814943e-02
5.82113147e-01 1.49181485e-01 4.85560298e-01 -1.60934672e-01
7.37191319e-01 -3.09729464e-02 6.74905598e-01 6.33356512e-01
3.27815861e-02 7.19250590e-02 2.49912471e-01 -3.90998214e-01
-8.64021122e-01 -1.33427694e-01 8.41265544e-02 9.90739048e-01
6.04030453e-02 -4.34249133e-01 -8.72524083e-01 -5.81269622e-01
-3.03153604e-01 6.58754408e-01 -4.21057731e-01 -2.15606570e-01
-6.87784135e-01 -1.24267733e+00 3.05572301e-01 5.22106409e-01
7.61821389e-01 -9.74641025e-01 -6.22549355e-01 4.24021184e-01
-1.94623902e-01 -8.24067175e-01 -2.96073884e-01 6.46525121e-04
-1.16830218e+00 -7.83805668e-01 -7.06643820e-01 -5.87035120e-01
6.20282233e-01 3.88866186e-01 9.62238491e-01 4.21516716e-01
-1.90630600e-01 -9.10400078e-02 -2.29309753e-01 -5.60530186e-01
-4.68762685e-03 4.21102762e-01 1.34122163e-01 -1.44748196e-01
1.24672413e-01 -5.34194171e-01 -6.11345708e-01 5.14887273e-01
-9.50365424e-01 3.61560404e-01 1.00885642e+00 9.62381601e-01
3.36829573e-01 3.74793768e-01 9.20213103e-01 -8.96867752e-01
7.30885804e-01 -6.01787627e-01 -8.58756781e-01 4.96658117e-01
-1.12664664e+00 -3.35463770e-02 7.62380660e-01 -4.02915955e-01
-1.15421867e+00 -1.63993657e-01 -3.70172411e-01 -2.77891189e-01
1.04220755e-01 8.21956396e-01 -5.88529408e-01 6.99001327e-02
1.59554839e-01 3.46571118e-01 -1.64644837e-01 -6.35304749e-01
1.05556034e-01 9.94355559e-01 6.53854981e-02 -5.76582849e-01
5.89794636e-01 5.14047369e-02 -4.87605389e-03 -3.41621310e-01
-9.36752915e-01 -3.37872118e-01 -1.77512318e-01 -1.01448141e-01
3.46233755e-01 -8.54343057e-01 -9.21887755e-01 4.05080914e-01
-8.46456587e-01 -1.04762763e-01 2.21875876e-01 5.59350610e-01
-4.08574820e-01 3.73062581e-01 -4.07613426e-01 -1.15240109e+00
-6.28143787e-01 -9.61563110e-01 4.78031278e-01 4.51751798e-01
3.13707143e-01 -1.13388109e+00 -5.05313240e-02 5.95353186e-01
5.00431716e-01 -3.09800446e-01 1.11202443e+00 -7.29757249e-01
-4.84459162e-01 -9.88645032e-02 -3.68409953e-03 2.22985759e-01
-2.14541852e-01 2.41326094e-02 -8.73621225e-01 -2.56214470e-01
1.55324310e-01 -2.23467082e-01 7.45638728e-01 3.36373091e-01
1.92003131e+00 -5.88324130e-01 -4.93177503e-01 5.38616836e-01
1.35306001e+00 4.56305891e-01 3.57440114e-01 5.24627090e-01
3.05314392e-01 6.56650305e-01 9.05846655e-01 7.29865193e-01
5.19744039e-01 7.09268987e-01 4.83821869e-01 -1.99275926e-01
6.37643039e-01 -2.23069146e-01 1.55873030e-01 1.23806882e+00
-2.83621997e-01 -5.09984732e-01 -7.56127715e-01 3.09696734e-01
-2.16593266e+00 -8.97022843e-01 2.16340184e-01 2.04899073e+00
7.84894347e-01 3.85476828e-01 1.38404474e-01 5.95876873e-02
6.05862737e-01 5.47476523e-02 -5.34430623e-01 -1.16163701e-01
9.44605693e-02 -1.52653918e-01 3.30832243e-01 8.10069516e-02
-8.47255230e-01 8.28983068e-01 6.51610327e+00 1.34899032e+00
-9.36380148e-01 5.97279891e-02 7.71621346e-01 -1.95213169e-01
-3.00820857e-01 7.13860020e-02 -9.40412581e-01 7.64681101e-01
1.07003856e+00 -3.30706060e-01 5.14908969e-01 1.09654772e+00
3.27103913e-01 3.97134908e-02 -7.72520840e-01 1.01278973e+00
-9.13098548e-03 -1.26094520e+00 -9.19604823e-02 1.96447089e-01
4.16323215e-01 -4.95467961e-01 4.64571677e-02 7.59230912e-01
-8.07242282e-03 -9.02289450e-01 5.38478911e-01 5.84840238e-01
4.11582530e-01 -1.12648213e+00 1.02092409e+00 1.01846409e+00
-1.01475525e+00 -3.61030698e-01 -6.15252435e-01 -2.55258262e-01
2.08776575e-02 6.47970319e-01 -5.71103871e-01 9.80226517e-01
3.69805098e-01 3.53329450e-01 -6.21221483e-01 1.21651554e+00
-1.25242978e-01 9.84972060e-01 -2.52056569e-01 -4.06479120e-01
9.23790187e-02 -2.67957300e-01 2.79344674e-02 1.05596125e+00
4.56743985e-01 9.62990299e-02 1.58566922e-01 6.50085509e-01
-6.81441128e-02 4.51291203e-01 -3.05015534e-01 3.09100002e-02
6.14219129e-01 1.45029497e+00 -3.34033340e-01 -5.08341432e-01
-3.14776510e-01 2.50420243e-01 2.04266265e-01 1.98878616e-01
-1.26421201e+00 -2.59452671e-01 -3.04133892e-02 -7.99320713e-02
-9.31255221e-02 1.11662671e-02 -3.31249982e-01 -1.29976177e+00
4.42486964e-02 -9.51180935e-01 5.39432645e-01 -6.71139300e-01
-9.83996212e-01 3.90131086e-01 2.23527387e-01 -1.11498010e+00
-4.27730232e-01 -3.08810353e-01 -7.89882600e-01 6.24019027e-01
-1.67094898e+00 -1.01354444e+00 -1.25703067e-01 4.77762640e-01
5.16388774e-01 -3.49069774e-01 5.79974413e-01 5.50017953e-01
-1.25573897e+00 8.28773499e-01 2.15300754e-01 -3.25502008e-01
4.62948084e-01 -6.61531389e-01 -2.48859599e-02 8.43874395e-01
-1.21679619e-01 9.04731989e-01 5.30357540e-01 -3.47871363e-01
-1.46620607e+00 -9.79741633e-01 8.51465702e-01 1.58046737e-01
5.73967218e-01 -2.66439259e-01 -5.99559665e-01 5.89382648e-01
1.25847384e-01 -4.11881447e-01 7.66661286e-01 1.38276085e-01
1.13940559e-01 -2.65427351e-01 -8.81278932e-01 7.58533657e-01
1.05145419e+00 1.20142110e-01 -5.58496416e-01 3.55922908e-01
7.87589967e-01 -1.65389806e-01 -6.55641615e-01 5.67191899e-01
5.71802020e-01 -7.10416317e-01 8.32626164e-01 -8.38467658e-01
3.84726763e-01 -1.38039291e-01 -8.75497460e-02 -1.01775646e+00
-3.30875427e-01 -5.11278987e-01 -5.95629871e-01 1.46856558e+00
4.56622958e-01 -7.48759866e-01 7.48514533e-01 5.88957906e-01
6.95545226e-02 -1.23719478e+00 -8.26789498e-01 -7.98913360e-01
-4.67772707e-02 -3.51602226e-01 9.40565705e-01 7.34842956e-01
-9.95242149e-02 2.79127777e-01 -7.80429900e-01 1.75167657e-02
3.93788725e-01 5.26084065e-01 7.72225857e-01 -1.13179100e+00
-5.11352897e-01 -4.91404653e-01 2.53237933e-01 -1.08920860e+00
1.00119375e-01 -5.76342821e-01 -2.81246066e-01 -1.18044198e+00
6.16688132e-01 -6.03611767e-01 -6.91991329e-01 4.76828814e-01
-3.41111779e-01 -2.47099459e-01 3.22911404e-02 4.81690615e-01
-8.05216014e-01 7.17005372e-01 9.84446228e-01 5.67056425e-03
5.08249775e-02 3.92065614e-01 -1.10139632e+00 1.05774736e+00
1.05351460e+00 -5.34005523e-01 -4.00915176e-01 -2.64822304e-01
4.47386563e-01 1.91330418e-01 6.50891662e-02 -7.47720361e-01
3.21767509e-01 -6.49263859e-01 2.21188322e-01 -6.06189668e-01
2.05243021e-01 -1.15609896e+00 1.77176595e-01 6.96547985e-01
-2.15157554e-01 2.08823457e-01 -3.33563648e-02 3.40836257e-01
-1.19196080e-01 -6.48002565e-01 5.45604885e-01 -1.44308642e-01
-5.34738123e-01 4.46022540e-01 -1.19796708e-01 -1.56499878e-01
1.10904145e+00 1.85410962e-01 -1.18171170e-01 -2.21548989e-01
-3.29479724e-01 6.22374296e-01 2.18921036e-01 3.42401080e-02
3.54674011e-01 -1.20554006e+00 -3.93340558e-01 9.21136066e-02
1.55949024e-02 -1.17060401e-01 3.69155139e-01 9.46431041e-01
-2.93014914e-01 6.22431159e-01 -9.11266282e-02 -1.09962918e-01
-1.03852367e+00 7.87187636e-01 2.15865940e-01 -7.65590847e-01
-2.40119189e-01 4.69501108e-01 -9.66520384e-02 -3.68987948e-01
4.51331854e-01 -1.55919164e-01 -3.60343963e-01 5.14031388e-02
4.67989624e-01 5.21984994e-01 -5.83996512e-02 -2.92666201e-02
-2.09040925e-01 4.63896126e-01 -5.80321439e-02 -1.00200035e-01
1.23938060e+00 -2.42181316e-01 -1.40208248e-02 2.44502440e-01
5.46613634e-01 -2.73905374e-04 -8.46205771e-01 -3.46375406e-01
-5.65285161e-02 -2.49791607e-01 8.76344591e-02 -7.45646417e-01
-9.50818956e-01 1.10721111e+00 3.32140207e-01 2.61739612e-01
1.32449687e+00 -5.58430612e-01 8.66426826e-01 4.99186546e-01
6.72106147e-01 -1.17588663e+00 -2.34431967e-01 3.89626294e-01
3.76485288e-01 -1.15202808e+00 1.88006610e-01 -1.02680132e-01
-5.13862789e-01 9.09857213e-01 8.75312150e-01 3.37300599e-01
5.06344736e-01 1.35163993e-01 -2.91007429e-01 1.55913234e-01
-1.20286548e+00 5.32964356e-02 3.04165091e-02 -1.19905427e-01
1.60345182e-01 -7.87955672e-02 -7.14215338e-01 1.21673465e+00
-1.12383984e-01 2.16921344e-01 2.70962745e-01 9.04353738e-01
-7.10411549e-01 -1.07241988e+00 -2.72811383e-01 4.03271019e-01
-6.48972869e-01 -1.31097898e-01 2.87659895e-02 8.07799160e-01
2.19056085e-01 1.02337313e+00 -3.18211764e-01 -4.69485492e-01
2.16749415e-01 8.69160965e-02 1.63232863e-01 -2.41866812e-01
-6.00825012e-01 3.51851046e-01 -2.50557009e-02 -2.31580317e-01
-3.71410370e-01 -2.29162171e-01 -8.87747645e-01 -4.11735862e-01
-8.12683046e-01 4.27119225e-01 8.70658815e-01 1.04179394e+00
2.59897888e-01 6.78292394e-01 1.00618231e+00 -4.65070635e-01
-1.08605266e+00 -1.06777263e+00 -4.32376683e-01 -2.53259748e-01
-3.00141633e-01 -6.44653380e-01 -3.89918417e-01 -1.82803378e-01] | [9.173364639282227, 4.019974708557129] |
0758dcaa-538c-4c9f-a1ab-aa250d0eb9dd | deeptitle-leveraging-bert-to-generate-search | 2107.10935 | null | https://arxiv.org/abs/2107.10935v1 | https://arxiv.org/pdf/2107.10935v1.pdf | DeepTitle -- Leveraging BERT to generate Search Engine Optimized Headlines | Automated headline generation for online news articles is not a trivial task - machine generated titles need to be grammatically correct, informative, capture attention and generate search traffic without being "click baits" or "fake news". In this paper we showcase how a pre-trained language model can be leveraged to create an abstractive news headline generator for German language. We incorporate state of the art fine-tuning techniques for abstractive text summarization, i.e. we use different optimizers for the encoder and decoder where the former is pre-trained and the latter is trained from scratch. We modify the headline generation to incorporate frequently sought keywords relevant for search engine optimization. We conduct experiments on a German news data set and achieve a ROUGE-L-gram F-score of 40.02. Furthermore, we address the limitations of ROUGE for measuring the quality of text summarization by introducing a sentence similarity metric and human evaluation. | ['Javier Poveda-Panter', 'Aamna Najmi', 'Viktor Malesevic', 'Sarah Lück', 'Hanna Behnke', 'Cristian Anastasiu'] | 2021-07-22 | null | null | null | null | ['headline-generation'] | ['natural-language-processing'] | [ 3.22091579e-01 7.17026412e-01 -3.44999790e-01 -2.14911669e-01
-1.39457309e+00 -6.92772865e-01 7.59117365e-01 1.87266394e-01
-5.74833870e-01 1.11548257e+00 9.20650125e-01 -3.05833876e-01
1.87172607e-01 -4.60905641e-01 -9.38898385e-01 2.03224551e-03
4.09759253e-01 6.25038564e-01 7.49476850e-02 -4.49834883e-01
6.42058074e-01 -7.26565113e-03 -1.07252908e+00 4.66408879e-01
1.23994482e+00 3.93379331e-01 2.65144676e-01 1.25267720e+00
1.31624835e-02 9.30229604e-01 -1.29369462e+00 -8.36748719e-01
-8.40647072e-02 -7.58658469e-01 -1.11478734e+00 -5.28298654e-02
5.31024992e-01 -3.25905323e-01 -4.55377728e-01 8.38381767e-01
7.35390723e-01 -4.99611869e-02 7.06081569e-01 -7.43947625e-01
-6.34351909e-01 1.17991102e+00 -3.46490264e-01 4.45728421e-01
6.10539794e-01 4.96829823e-02 1.39695311e+00 -4.59443629e-01
9.00307178e-01 1.16627550e+00 3.60151827e-01 6.22402906e-01
-1.08625090e+00 -2.22408175e-01 -7.38463178e-02 -1.51385516e-01
-8.38391483e-01 -7.17837512e-01 4.98128504e-01 -4.02653009e-01
1.26707029e+00 6.57331586e-01 4.03357923e-01 1.42997038e+00
5.27356029e-01 1.13922858e+00 4.86208290e-01 -5.68724513e-01
1.67753007e-02 3.82686466e-01 1.24367438e-01 5.50423682e-01
4.05312419e-01 -3.76136005e-01 -6.18836403e-01 -1.54933766e-01
1.43966973e-01 -6.31316483e-01 -3.37124705e-01 1.96294785e-01
-1.34016311e+00 1.14916849e+00 8.52935463e-02 1.51931107e-01
-5.08778334e-01 2.61012465e-01 6.10397637e-01 2.91118264e-01
7.31158316e-01 1.26241136e+00 -3.03120434e-01 -3.75648975e-01
-1.41007102e+00 6.17945731e-01 1.40521145e+00 1.16404819e+00
1.30787522e-01 2.26400662e-02 -9.15354133e-01 8.61471772e-01
-1.76011212e-02 5.81691325e-01 7.68842101e-01 -9.39491570e-01
9.00347710e-01 2.33497739e-01 2.91213274e-01 -7.57853091e-01
-1.16674704e-02 -7.40278244e-01 -4.23612744e-01 -6.26172900e-01
8.78305510e-02 -6.19068682e-01 -7.21520722e-01 1.32274604e+00
-2.91929454e-01 -5.43485761e-01 2.23541498e-01 5.12056053e-01
7.92351305e-01 8.87519598e-01 -2.86921710e-01 -2.63230205e-01
1.34447145e+00 -1.51493061e+00 -8.18156421e-01 -5.12753427e-01
8.09435368e-01 -1.01433837e+00 1.16198790e+00 8.48428011e-02
-1.57902980e+00 -1.16912007e-01 -1.07439542e+00 -1.84524491e-01
-4.85754833e-02 4.89269495e-01 1.55826867e-01 4.23728496e-01
-8.79307389e-01 5.40774226e-01 -5.85917056e-01 -2.75074214e-01
1.33584112e-01 -1.35838985e-04 6.36440516e-02 3.64188284e-01
-1.17800152e+00 8.78561258e-01 4.31526512e-01 -5.16654074e-01
-7.16588914e-01 -4.03653264e-01 -7.09279776e-01 2.33676776e-01
3.40779215e-01 -1.05381882e+00 1.85773277e+00 -6.94941878e-01
-1.64683425e+00 6.91771805e-01 -2.56365359e-01 -8.49289238e-01
6.53129280e-01 -5.21046340e-01 -1.94476217e-01 3.51940542e-01
5.64734638e-01 5.40282965e-01 6.61924243e-01 -9.05826032e-01
-6.70117319e-01 2.44121909e-01 -1.01409383e-01 4.41030115e-01
-2.55319178e-01 1.96901381e-01 -4.20452714e-01 -1.06606793e+00
-6.12081170e-01 -8.43263984e-01 -2.38275856e-01 -8.57479215e-01
-1.08318365e+00 -7.02992156e-02 2.18615502e-01 -1.13061774e+00
1.76821768e+00 -1.59065986e+00 4.14724536e-02 9.71973166e-02
-2.54266746e-02 1.90370724e-01 -1.98810190e-01 6.77756727e-01
3.39387089e-01 5.13225913e-01 1.62662603e-02 -2.44375989e-01
1.52077168e-01 -3.01651597e-01 -5.65031171e-01 -4.27779220e-02
9.32527930e-02 1.18192792e+00 -1.00264907e+00 -4.57938373e-01
-4.10634100e-01 -1.47945970e-01 -8.14101160e-01 1.82398885e-01
-6.83805227e-01 3.25180516e-02 -6.41135931e-01 2.73741812e-01
-4.02104817e-02 -3.89078677e-01 -2.89987296e-01 1.53085172e-01
-2.19440818e-01 9.62702036e-01 -5.66054344e-01 1.44188058e+00
-5.04360735e-01 8.21445882e-01 -1.51828572e-01 -4.46406692e-01
6.27815604e-01 2.47844771e-01 -2.94330828e-02 -5.88566720e-01
2.45827213e-01 3.63664597e-01 -1.99155554e-01 -5.42141557e-01
1.24811673e+00 3.41407925e-01 -3.85811627e-01 7.94768035e-01
9.90422666e-02 -2.94079661e-01 6.67314589e-01 5.38933516e-01
1.30807579e+00 -2.08200872e-01 2.26263091e-01 -1.72350854e-01
3.89825433e-01 4.09115344e-01 -6.73157675e-03 1.26309741e+00
3.84744614e-01 7.08114326e-01 7.05395818e-01 1.87483758e-01
-1.37047958e+00 -4.95621264e-01 2.48160571e-01 1.17455804e+00
-2.72357047e-01 -6.86591208e-01 -1.27995312e+00 -7.82414079e-01
-2.36846045e-01 1.59015298e+00 -1.42157719e-01 -3.41806620e-01
-7.88992643e-01 -6.26978219e-01 9.48831916e-01 1.80541605e-01
2.78722435e-01 -9.32278872e-01 -5.17519116e-01 5.00156701e-01
-6.11787915e-01 -1.15431249e+00 -1.04300952e+00 -7.53030702e-02
-5.12925446e-01 -5.87508142e-01 -9.97848988e-01 -7.16918468e-01
4.46915299e-01 1.01593472e-01 1.34610832e+00 -9.13137347e-02
4.66353819e-02 2.95462936e-01 -4.89697397e-01 -5.69644749e-01
-1.03720593e+00 8.31035554e-01 -2.35372558e-01 -4.41254169e-01
6.25977665e-02 -1.99912488e-02 -5.73160648e-01 -1.98570304e-02
-7.89966643e-01 2.36770213e-01 8.60183656e-01 9.38206792e-01
2.03639269e-01 -4.35329556e-01 8.57766867e-01 -1.03282285e+00
1.51067758e+00 -3.91876698e-01 -2.94134796e-01 4.70846266e-01
-7.03618050e-01 3.70384991e-01 7.32596934e-01 -2.64233470e-01
-9.82986867e-01 -3.56932729e-01 -3.28787148e-01 2.01829731e-01
2.28460982e-01 5.64471245e-01 1.57014653e-01 3.69740963e-01
9.83465195e-01 3.62964988e-01 -7.20706508e-02 -5.30541241e-01
5.50769031e-01 1.00170958e+00 4.00320232e-01 -2.00451314e-01
5.04520953e-01 -6.15710579e-02 -6.13240719e-01 -8.69046926e-01
-1.10005176e+00 -4.67848301e-01 -1.86199360e-02 1.87810175e-02
7.57785141e-01 -8.77968848e-01 -1.98429227e-01 7.03557208e-02
-1.42782462e+00 -2.90219814e-01 -4.89212155e-01 3.87373626e-01
-5.81869006e-01 3.99778217e-01 -7.53277898e-01 -4.35918778e-01
-9.92897809e-01 -9.11323309e-01 1.24294150e+00 1.42459840e-01
-6.85220778e-01 -7.58497834e-01 2.82786220e-01 5.71631610e-01
4.33769464e-01 -4.90963720e-02 6.58542752e-01 -1.21399283e+00
-2.60079503e-01 -5.23738027e-01 -4.59860777e-03 3.86786550e-01
-2.24250987e-01 -6.08108304e-02 -6.06509924e-01 -1.06155559e-01
1.79268653e-04 -2.98007905e-01 9.99729931e-01 3.53664905e-01
7.92153120e-01 -1.23794103e+00 -3.52928400e-01 2.57630706e-01
8.84192705e-01 -1.07885145e-01 5.54811776e-01 5.51620722e-01
5.45382619e-01 4.89170194e-01 5.69651604e-01 4.24237818e-01
5.33512712e-01 6.67140603e-01 -2.10796162e-01 2.17442319e-01
-1.74255490e-01 -7.64219403e-01 5.37550569e-01 1.06175375e+00
3.01973194e-01 -9.76290226e-01 -6.66479051e-01 5.57673097e-01
-1.75535238e+00 -1.20912278e+00 -2.75608432e-02 1.84870863e+00
1.22308791e+00 4.18386549e-01 8.24979246e-02 -3.10165077e-01
6.96092248e-01 2.19347492e-01 -2.41590366e-01 -6.92691267e-01
-1.14714541e-01 1.65492252e-01 8.69063139e-01 7.99329281e-01
-9.04798210e-01 1.25177646e+00 6.44999981e+00 9.18838441e-01
-9.73802090e-01 2.39099916e-02 5.39064407e-01 -2.33118221e-01
-6.12708271e-01 2.36319676e-02 -9.82055962e-01 5.78464687e-01
1.18686604e+00 -6.25838697e-01 2.58543402e-01 9.20449018e-01
4.90404427e-01 -6.23049177e-02 -9.38303351e-01 5.98149538e-01
3.35356683e-01 -1.58028471e+00 3.37103844e-01 -2.18019336e-02
7.98124671e-01 -6.83944393e-03 -2.74523884e-01 4.29909766e-01
4.86660212e-01 -8.30425322e-01 9.06482160e-01 6.47312522e-01
6.37839079e-01 -5.18531382e-01 6.61423802e-01 6.50643587e-01
-2.77938068e-01 1.59001485e-01 -2.08148837e-01 2.32977882e-01
6.47766769e-01 5.63799977e-01 -1.34822726e+00 3.72164100e-01
9.74130332e-02 4.52180773e-01 -7.94087231e-01 1.04036045e+00
-3.27212691e-01 8.85155261e-01 -1.68627530e-01 -6.87236130e-01
3.95509183e-01 1.35040477e-01 1.17755997e+00 1.69329774e+00
3.59113008e-01 -3.90390724e-01 -6.15507513e-02 7.56799579e-01
-4.38703865e-01 2.24645674e-01 -4.08469677e-01 -3.47233951e-01
2.49702200e-01 1.06613564e+00 -3.50098759e-01 -5.99269569e-01
9.08732861e-02 1.26321793e+00 9.96345654e-02 2.58557618e-01
-7.84244418e-01 -8.46794069e-01 -3.54711972e-02 1.98900983e-01
3.26388329e-01 -2.78079361e-02 -2.75336951e-01 -1.51481247e+00
3.89429629e-02 -1.22559810e+00 2.27417648e-02 -8.13872039e-01
-9.06637311e-01 7.08816826e-01 -8.34730826e-03 -9.12577033e-01
-8.17655563e-01 -6.09141663e-02 -6.98840559e-01 6.95746183e-01
-1.30846369e+00 -7.15091527e-01 7.91748464e-02 -4.50352281e-02
1.02407384e+00 -3.43057781e-01 5.41596174e-01 1.85275853e-01
-6.35156035e-01 8.69928479e-01 3.55810434e-01 -3.29129063e-02
7.71266162e-01 -1.34406865e+00 8.20351064e-01 9.16966259e-01
2.11789068e-02 6.32414997e-01 1.14499009e+00 -8.93777132e-01
-1.14541435e+00 -1.08126497e+00 1.43058097e+00 -4.39985961e-01
7.91951895e-01 -4.01739299e-01 -4.42520589e-01 5.69851816e-01
6.66033566e-01 -1.07188654e+00 5.14851332e-01 -2.00485453e-01
1.01230994e-01 1.89569965e-01 -7.72392690e-01 9.84873950e-01
7.64462113e-01 -2.89484859e-01 -8.58840227e-01 8.10329974e-01
1.04820526e+00 -4.85259891e-01 -5.06346166e-01 5.67519404e-02
3.06664616e-01 -4.64064121e-01 6.53603137e-01 -6.49254084e-01
8.42021406e-01 1.06474474e-01 3.58008623e-01 -1.59641445e+00
-2.20414981e-01 -1.07285738e+00 -2.53025055e-01 1.24773788e+00
9.58311558e-01 -4.05902207e-01 5.56523919e-01 3.49543810e-01
-4.77235615e-01 -6.19271755e-01 -5.48415661e-01 -6.76232874e-01
-4.24775928e-02 9.14497972e-02 2.68617600e-01 3.21770489e-01
3.29573601e-01 1.09262526e+00 -5.06193340e-01 -4.81818318e-01
2.31186584e-01 -1.85183972e-01 8.72563183e-01 -6.39730394e-01
-3.67552519e-01 -6.43404782e-01 1.85774177e-01 -1.51934028e+00
1.73144311e-01 -9.61819649e-01 2.18037561e-01 -1.66941059e+00
2.03964964e-01 1.04269125e-01 4.92534280e-01 6.62594065e-02
-3.21554095e-01 -1.99130818e-01 -5.78569761e-03 4.06910688e-01
-8.55366707e-01 6.00503206e-01 1.13656461e+00 -1.42818689e-01
-2.39291459e-01 3.05059135e-01 -1.19401634e+00 4.37345773e-01
8.50475967e-01 -5.36787987e-01 -2.77521610e-01 -4.34191793e-01
4.64173377e-01 2.53097653e-01 1.03398196e-01 -7.39092946e-01
3.44533622e-01 1.03975765e-01 -7.12313876e-02 -5.97421110e-01
2.70191301e-03 -5.52381352e-02 -3.60763162e-01 3.72354954e-01
-1.00388038e+00 3.01143825e-01 -9.78074595e-02 6.67518795e-01
-2.46373445e-01 -7.48740733e-01 3.92922163e-01 -3.11491281e-01
-1.84465561e-03 -2.19082355e-01 -6.92506790e-01 7.07427800e-01
6.67741299e-01 3.25561985e-02 -5.34668267e-01 -9.00716782e-01
-1.07435308e-01 3.50283593e-01 3.82269710e-01 3.98535311e-01
3.36964011e-01 -8.26922834e-01 -1.03767252e+00 -3.72557729e-01
-1.34860262e-01 -2.76733965e-01 -3.08149189e-01 6.01178527e-01
-8.34015369e-01 9.27989364e-01 2.34526828e-01 -9.65489075e-02
-9.95309711e-01 1.68141037e-01 -6.29090890e-03 -7.56103277e-01
-4.27782744e-01 7.14407980e-01 -2.19705656e-01 -1.38217136e-01
2.59328783e-01 -1.81091696e-01 -2.93388575e-01 1.34805232e-01
5.91457963e-01 4.40545142e-01 1.95423290e-01 -4.04455960e-01
7.26403147e-02 -3.42019387e-02 -5.03908455e-01 -5.72452724e-01
1.14097726e+00 -1.96196720e-01 1.38867544e-02 1.40236005e-01
1.21753049e+00 5.56675494e-01 -5.81359029e-01 8.23767260e-02
3.11854661e-01 -6.43129833e-03 -4.71315198e-02 -1.01980078e+00
-4.24214482e-01 3.75802904e-01 -3.07679087e-01 4.82736051e-01
5.42293847e-01 4.29630391e-02 1.24971581e+00 8.09007227e-01
-2.44607568e-01 -1.55998099e+00 2.30061397e-01 9.42079067e-01
1.09737957e+00 -8.67451608e-01 7.12875649e-02 -4.77362461e-02
-1.09128344e+00 1.03523099e+00 3.14408422e-01 -8.74819979e-02
-2.49797590e-02 -5.65699860e-02 -2.71449834e-01 -2.29740798e-01
-8.74413848e-01 7.74159953e-02 5.66095591e-01 -8.41483101e-02
6.38356090e-01 -1.60415873e-01 -7.59237230e-01 6.35969758e-01
-1.00006115e+00 -1.57175943e-01 8.94593298e-01 8.05886030e-01
-6.53306842e-01 -8.63820314e-01 -8.16857070e-02 8.76501322e-01
-9.31044817e-01 -4.22878355e-01 -6.87727630e-01 3.47964585e-01
-7.52512574e-01 1.04267979e+00 -1.66042060e-01 -2.87826508e-01
4.83445853e-01 1.79407433e-01 8.17486048e-02 -9.01896834e-01
-8.79283130e-01 9.49955806e-02 9.11184549e-01 -1.48803219e-01
8.31029937e-02 -6.10868871e-01 -7.46518254e-01 -2.20572919e-01
-6.69921100e-01 5.52504539e-01 7.79621243e-01 7.65512347e-01
7.46778846e-01 5.79098403e-01 5.23514032e-01 -5.73191643e-01
-1.05762029e+00 -1.28026032e+00 8.99348184e-02 2.20290631e-01
2.81773359e-01 9.20827538e-02 -5.55962801e-01 8.24692920e-02] | [12.36206340789795, 9.310722351074219] |
b8895004-ee1d-418e-9fad-ea7444180beb | inferring-multidimensional-rates-of-aging | 1807.04709 | null | http://arxiv.org/abs/1807.04709v3 | http://arxiv.org/pdf/1807.04709v3.pdf | Inferring Multidimensional Rates of Aging from Cross-Sectional Data | Modeling how individuals evolve over time is a fundamental problem in the
natural and social sciences. However, existing datasets are often
cross-sectional with each individual observed only once, making it impossible
to apply traditional time-series methods. Motivated by the study of human
aging, we present an interpretable latent-variable model that learns temporal
dynamics from cross-sectional data. Our model represents each individual's
features over time as a nonlinear function of a low-dimensional,
linearly-evolving latent state. We prove that when this nonlinear function is
constrained to be order-isomorphic, the model family is identifiable solely
from cross-sectional data provided the distribution of time-independent
variation is known. On the UK Biobank human health dataset, our model
reconstructs the observed data while learning interpretable rates of aging
associated with diseases, mortality, and aging risk factors. | ['Jure Leskovec', 'Daphne Koller', 'Pang Wei Koh', 'Tatsunori Hashimoto', 'Nicholas Eriksson', 'Percy Liang', 'Emma Pierson'] | 2018-07-12 | null | null | null | null | ['human-aging'] | ['miscellaneous'] | [ 1.49514750e-01 1.82210878e-01 -4.71015483e-01 -2.98564076e-01
-2.08930120e-01 -5.14000952e-01 5.84742367e-01 2.38302350e-01
-3.64642590e-01 1.11624599e+00 7.40164816e-01 -3.10254186e-01
-3.86127919e-01 -6.88541889e-01 -6.70852482e-01 -7.47304320e-01
-7.47837842e-01 7.91822731e-01 -5.22574306e-01 1.24137856e-01
-4.56381708e-01 8.32040329e-03 -1.11185217e+00 -2.89890558e-01
8.55326593e-01 3.52757186e-01 -2.89389074e-01 9.55402315e-01
2.67897844e-01 2.04733565e-01 -2.71783590e-01 -1.34693682e-01
1.08583786e-01 -4.39487010e-01 -4.31848019e-01 6.03613332e-02
3.78011286e-01 -3.99301797e-02 -6.35111690e-01 6.95736766e-01
1.61773056e-01 -2.56558418e-01 1.06250596e+00 -1.43453407e+00
-9.14635718e-01 4.21247005e-01 -2.41227493e-01 1.69467092e-01
4.55022492e-02 5.20378258e-03 1.05867207e+00 9.28978994e-02
5.69955826e-01 1.41988420e+00 1.00086522e+00 8.33992004e-01
-1.96052933e+00 -2.75274307e-01 2.88915783e-01 -3.02756578e-01
-8.94842327e-01 -1.60908356e-01 6.36556804e-01 -9.42738235e-01
3.37384373e-01 1.58828005e-01 1.01227558e+00 1.43401241e+00
8.87562096e-01 3.92639011e-01 1.03229821e+00 -1.05318226e-01
3.43833417e-01 -4.96024638e-01 5.04758656e-01 9.83561873e-01
4.16022003e-01 3.03424507e-01 -3.97119462e-01 -6.27130270e-01
8.70981038e-01 5.63881993e-01 -3.25972848e-02 -4.35806632e-01
-1.20093632e+00 5.36034882e-01 -1.57409847e-01 9.35025588e-02
-5.31732321e-01 5.31327784e-01 3.20293576e-01 4.75746423e-01
8.42523754e-01 -9.31194052e-02 -9.96714354e-01 -4.98729721e-02
-8.39847684e-01 2.85607100e-01 7.97331512e-01 3.85164768e-01
5.64770401e-01 6.41612848e-03 5.80866486e-02 3.20302755e-01
3.48318398e-01 7.51379192e-01 4.77995336e-01 -1.09920454e+00
1.21602966e-02 7.18533337e-01 3.01991224e-01 -6.01102650e-01
-6.89928234e-01 -4.18594182e-01 -1.26879430e+00 -1.47106284e-02
8.21545243e-01 -3.10344458e-01 -9.22599256e-01 2.57194066e+00
1.52718693e-01 3.22138280e-01 -9.47672874e-02 1.40790164e-01
-1.35292813e-01 3.48067939e-01 4.16279703e-01 -8.76878083e-01
1.37854040e+00 -1.70127735e-01 -8.29269946e-01 -3.68764326e-02
4.01866764e-01 2.12176353e-01 6.96364760e-01 1.37310669e-01
-1.10923970e+00 -3.58096927e-01 -6.12211287e-01 -4.33878265e-02
-2.82401174e-01 -1.45959824e-01 6.94798708e-01 5.47968090e-01
-1.08971274e+00 5.71347177e-01 -1.56507933e+00 -5.28613567e-01
4.42691654e-01 3.91891301e-01 -3.66916120e-01 2.24799171e-01
-1.14849532e+00 4.39611197e-01 -6.68942481e-02 -9.17024985e-02
-1.00355852e+00 -1.24911916e+00 -5.69895566e-01 -1.14738062e-01
6.69034664e-03 -1.30109894e+00 1.03113616e+00 -7.21413314e-01
-8.83235633e-01 7.57400811e-01 -5.86379886e-01 -6.93580925e-01
7.74596810e-01 -1.44276202e-01 -6.55745387e-01 -3.62964980e-02
1.68579429e-01 1.97530482e-02 7.82335162e-01 -8.68407667e-01
-2.15302259e-01 -8.36269617e-01 -3.51914316e-01 -2.68963128e-01
-4.40269977e-01 -6.21156931e-01 1.79446861e-01 -6.04773760e-01
-7.34062493e-03 -1.04856932e+00 -4.43927824e-01 4.95590627e-01
-2.06532508e-01 -1.68668434e-01 6.02925301e-01 -1.06324303e+00
1.55131912e+00 -1.89508975e+00 5.69020271e-01 -2.94230431e-01
7.00422108e-01 -5.26187658e-01 1.71392178e-03 5.29913306e-01
-2.74239987e-01 4.14932877e-01 -6.36669040e-01 -6.11204624e-01
-6.21414855e-02 6.36644185e-01 -2.26989225e-01 9.33268845e-01
-6.26718067e-03 9.86092091e-01 -1.07913208e+00 -2.81436414e-01
-2.07612678e-01 4.33155000e-01 -4.40502524e-01 -2.62832016e-01
-4.18413311e-01 5.67467213e-01 -5.20220518e-01 4.47267771e-01
2.11628452e-01 -4.96203333e-01 3.55160475e-01 2.34119594e-01
-7.51460716e-02 -2.09766090e-01 -6.23185217e-01 1.47746253e+00
-1.47533163e-01 4.26758528e-01 -4.32062000e-01 -1.19742250e+00
4.38985318e-01 6.52730882e-01 1.12395978e+00 -3.04044753e-01
-1.36799127e-01 -4.60208543e-02 -4.19276301e-03 -5.46822667e-01
-1.96678698e-01 -5.07548273e-01 -3.29967588e-01 5.64672291e-01
-1.36922702e-01 8.69207025e-01 9.45186168e-02 2.08207905e-01
1.51758122e+00 -1.06249191e-01 2.56236047e-01 -3.99532497e-01
2.08116665e-01 -2.75371492e-01 1.00012863e+00 5.64823806e-01
-2.69118845e-01 1.39880955e-01 8.25507104e-01 -7.66108632e-01
-1.48950863e+00 -1.67536867e+00 -3.60557139e-01 4.83269721e-01
-5.80632627e-01 -3.99637163e-01 -4.51156467e-01 -4.79862034e-01
3.79643828e-01 1.74772799e-01 -1.37768531e+00 -4.67091739e-01
-4.20064062e-01 -1.20130646e+00 1.89221770e-01 4.44824308e-01
4.14036177e-02 -5.60059249e-01 -4.58323747e-01 4.25935894e-01
-3.03716630e-01 -3.71574730e-01 -6.46596134e-01 4.33980934e-02
-1.28842068e+00 -1.11079788e+00 -8.72253597e-01 -4.14505363e-01
9.74768758e-01 -3.96642268e-01 1.25814760e+00 -6.80879205e-02
-6.72560632e-01 8.65894258e-01 2.79673427e-01 -2.63077289e-01
-5.10099411e-01 -3.82605605e-02 6.32111907e-01 1.85391590e-01
7.12034479e-02 -8.16429615e-01 -8.99515748e-01 -9.58575532e-02
-9.29042161e-01 -1.62661165e-01 1.60427243e-01 9.06315148e-01
5.12134433e-01 2.67105520e-01 6.91316664e-01 -7.07202494e-01
2.10721761e-01 -8.40547740e-01 -4.38043743e-01 5.41011930e-01
-7.82179356e-01 5.10358810e-01 4.75216538e-01 -1.00844336e+00
-7.84896553e-01 1.27470106e-01 7.58410454e-01 -3.43382396e-02
8.21330696e-02 6.72628999e-01 -8.77979696e-02 7.98151374e-01
3.27274740e-01 3.54594469e-01 3.88327211e-01 -6.15996480e-01
2.43808717e-01 1.81207821e-01 5.88317573e-01 -5.90343237e-01
7.37088025e-01 9.39243972e-01 5.61827242e-01 -8.40916872e-01
-7.37480044e-01 -9.21536237e-02 -9.65568244e-01 -1.70188546e-01
9.28219974e-01 -1.05572116e+00 -9.21308637e-01 6.10141039e-01
-5.98728597e-01 -6.61635876e-01 -4.17061299e-01 3.69227678e-01
-7.38335669e-01 1.46941885e-01 -6.05147660e-01 -1.23132205e+00
-2.65273880e-02 -2.33224019e-01 1.09212589e+00 -1.61702768e-03
-5.42259753e-01 -1.89521992e+00 6.65986180e-01 -7.06449226e-02
8.04490820e-02 6.77800953e-01 1.46273065e+00 -2.86554024e-02
-2.48247400e-01 -3.72819483e-01 3.24542552e-01 5.80036491e-02
5.74663043e-01 7.33318701e-02 -2.58642972e-01 -4.49803442e-01
-1.37541279e-01 1.63929552e-01 7.03081846e-01 1.02242410e+00
9.75885928e-01 -5.74079514e-01 -6.05735481e-01 4.65835512e-01
1.23763728e+00 -1.69742212e-01 2.23032847e-01 -1.82699978e-01
5.03192306e-01 7.11718738e-01 -1.67984813e-01 4.59025711e-01
7.74290800e-01 3.78226072e-01 1.18417025e-01 3.00144143e-02
2.88858742e-01 -4.16237682e-01 5.55697560e-01 6.37844920e-01
-1.85771152e-01 -1.30161420e-01 -7.99857616e-01 7.12794244e-01
-1.97749352e+00 -1.36342359e+00 -3.84483069e-01 2.45578074e+00
8.70172501e-01 4.86469492e-02 7.18313336e-01 2.12045200e-02
4.44419712e-01 -1.38169140e-01 -1.12183249e+00 1.55946463e-01
-3.94732475e-01 8.03158581e-02 6.76720619e-01 6.77796543e-01
-8.47680926e-01 1.62228838e-01 7.56216192e+00 -3.50241452e-01
-7.66313195e-01 3.04972194e-02 7.65208542e-01 -2.38188952e-01
-4.64952976e-01 -2.80564930e-02 -5.95178962e-01 7.06982851e-01
1.48605943e+00 -7.24333882e-01 2.33013332e-01 3.95565778e-02
5.88437974e-01 2.55606651e-01 -1.20458734e+00 5.33578753e-01
-2.29488075e-01 -8.09539974e-01 -2.66973108e-01 7.30872810e-01
7.96728492e-01 -3.04584265e-01 2.55701572e-01 3.02376803e-02
8.42497706e-01 -7.79558957e-01 5.22835076e-01 1.33755457e+00
8.46252441e-01 -3.52841526e-01 1.79361254e-02 4.56884950e-01
-1.02171123e+00 -3.90264809e-01 -6.52601793e-02 -2.57079661e-01
5.25619507e-01 7.40816474e-01 -2.72853941e-01 1.05238385e-01
4.20929223e-01 1.18140101e+00 -5.28217077e-01 7.37609208e-01
2.63864279e-01 1.06713951e+00 -3.25241804e-01 6.29545510e-01
-4.11906421e-01 -3.59201223e-01 4.81743634e-01 4.51580673e-01
5.19099236e-01 -6.25567511e-03 1.16214536e-01 8.07294965e-01
1.76389515e-01 -6.01747751e-01 -3.74169976e-01 -4.87703174e-01
1.57005012e-01 7.61260629e-01 -5.13121843e-01 -3.78902286e-01
-5.09416103e-01 1.03981698e+00 8.25225189e-02 6.28487110e-01
-5.53356528e-01 4.60291237e-01 1.03557873e+00 5.40064931e-01
2.44964771e-02 -6.89840078e-01 -1.74171448e-01 -1.41787231e+00
-6.76907450e-02 -5.09332180e-01 8.20598662e-01 -3.63537729e-01
-1.77608430e+00 -6.04758970e-03 9.70468670e-02 -8.24477673e-01
-4.19843346e-01 -5.06669223e-01 -3.80369753e-01 1.00191808e+00
-7.34635770e-01 -1.10970592e+00 2.19341010e-01 3.96550268e-01
2.92243272e-01 2.95903254e-02 8.94889355e-01 9.42173973e-03
-7.16271758e-01 2.41541833e-01 3.07927936e-01 -8.44311118e-02
3.50306153e-01 -1.60193610e+00 7.70984054e-01 4.63221699e-01
-1.59321949e-01 9.64042008e-01 9.89031434e-01 -1.25626743e+00
-1.36144054e+00 -1.08155489e+00 1.12574053e+00 -8.93851221e-01
1.02543986e+00 -5.90427279e-01 -1.12028027e+00 9.78838325e-01
-3.82064730e-01 8.93448219e-02 8.55575681e-01 3.68325293e-01
-2.52815068e-01 3.92430983e-02 -9.08181608e-01 6.24189138e-01
1.30099320e+00 -7.00734377e-01 -3.69337231e-01 1.91256985e-01
7.31279790e-01 3.51891160e-01 -1.07487309e+00 1.66459233e-02
9.54372108e-01 -2.58014649e-01 1.22459173e+00 -1.40836322e+00
3.65344107e-01 -1.24483421e-01 8.51139128e-02 -1.16005468e+00
-5.28969288e-01 -6.89031422e-01 -6.63771093e-01 1.06088161e+00
1.53588846e-01 -7.61165023e-01 7.94867992e-01 1.01120591e+00
4.40709829e-01 -2.79860318e-01 -9.84787703e-01 -1.01873183e+00
3.86127472e-01 2.21316218e-01 3.47431123e-01 9.18698847e-01
-1.64470643e-01 2.26484731e-01 -7.21961915e-01 2.68505037e-01
1.15162480e+00 -2.57926524e-01 4.15841907e-01 -1.99895060e+00
-4.42803860e-01 -1.39757693e-01 -4.27117169e-01 -6.09749496e-01
3.63797903e-01 -6.15858674e-01 -2.16976702e-01 -1.23457348e+00
6.46144629e-01 -2.29504526e-01 -4.13620442e-01 2.27337599e-01
-3.82777393e-01 -3.21101189e-01 -2.60446787e-01 1.28208771e-01
-1.41264841e-01 5.75297177e-01 8.93289030e-01 -8.69186893e-02
-1.18017957e-01 2.86242813e-01 -5.69959462e-01 4.51271951e-01
7.57538140e-01 -5.68180680e-01 -5.96181214e-01 -7.05531314e-02
3.23157400e-01 5.22447348e-01 7.78337181e-01 -7.49413073e-01
-9.11462083e-02 -4.38058108e-01 5.01551330e-01 -4.74269092e-01
2.76990920e-01 -7.92029262e-01 7.10430920e-01 1.06016886e+00
-5.13254464e-01 5.11233628e-01 -1.69953063e-01 1.16412258e+00
4.96305227e-01 4.39591408e-01 4.17786181e-01 -1.33759990e-01
7.68843293e-02 8.25886548e-01 -5.94993889e-01 1.22828677e-01
5.69365799e-01 1.83161989e-01 -3.22706968e-01 -5.64678609e-01
-1.15397155e+00 2.46919155e-01 6.16215348e-01 2.67976344e-01
1.00499233e-02 -1.30923009e+00 -7.51638174e-01 -1.93891593e-03
-4.11053635e-02 -4.59828943e-01 6.11486554e-01 6.73402607e-01
1.87893137e-01 2.33772144e-01 -1.62953034e-01 -4.06374037e-01
-1.23456371e+00 8.80189002e-01 4.36168164e-01 -2.78547496e-01
-6.74042106e-01 2.03146145e-01 2.64779836e-01 -2.12887123e-01
-6.06024750e-02 -2.51944453e-01 1.94142282e-01 1.87390253e-01
4.93248701e-01 4.89958286e-01 -7.86022425e-01 -5.86909354e-01
4.94811102e-04 4.21117395e-01 7.01131970e-02 -4.72000569e-01
1.60130942e+00 -4.90233302e-01 -1.54810131e-01 1.46419549e+00
1.25379872e+00 -4.38577801e-01 -1.65170312e+00 -3.45104277e-01
1.89439893e-01 7.92137682e-02 -3.74129921e-01 -6.64208949e-01
-6.69602275e-01 7.03286469e-01 7.33358920e-01 4.70820159e-01
9.11462128e-01 1.70480371e-01 5.06080806e-01 -1.98508605e-01
1.78911552e-01 -6.94615722e-01 -8.70924722e-03 7.09537417e-02
6.52546704e-01 -1.00064516e+00 7.69786909e-02 -3.91664617e-02
1.53560296e-01 7.82208443e-01 1.24846585e-01 -9.86526236e-02
1.04687989e+00 9.38832015e-02 -2.79350221e-01 -7.86504894e-02
-1.32904124e+00 1.31994665e-01 3.71007085e-01 6.12137496e-01
4.40111130e-01 4.47754443e-01 -4.04273361e-01 4.94026989e-01
-2.76413500e-01 3.48203719e-01 4.65180248e-01 8.02386999e-01
-2.09456101e-01 -1.31347644e+00 -2.05801040e-01 7.40146577e-01
-5.18356264e-01 1.23956107e-01 -1.15671292e-01 5.49492359e-01
-2.70084944e-02 3.56109768e-01 4.76001889e-01 2.67108202e-01
6.96407184e-02 5.24362624e-01 5.62619030e-01 -4.06080544e-01
2.36092374e-01 -2.20519349e-01 -2.89875627e-01 -2.24095941e-01
-4.75784749e-01 -1.51222122e+00 -1.05539358e+00 -3.92652839e-01
4.37900960e-01 -1.91496730e-01 2.70061404e-01 9.62484539e-01
2.70992815e-01 6.10336483e-01 4.41780716e-01 -1.50379673e-01
-5.43710232e-01 -7.01125979e-01 -6.96255922e-01 4.95583624e-01
1.00640666e+00 -6.11020446e-01 -6.57609940e-01 9.81157541e-01] | [7.820483684539795, 5.47482442855835] |
3f9dfb7f-f601-4e3c-bc58-538ae4761497 | cardinality-estimation-over-knowledge-graphs | 2303.01140 | null | https://arxiv.org/abs/2303.01140v1 | https://arxiv.org/pdf/2303.01140v1.pdf | Cardinality Estimation over Knowledge Graphs with Embeddings and Graph Neural Networks | Cardinality Estimation over Knowledge Graphs (KG) is crucial for query optimization, yet remains a challenging task due to the semi-structured nature and complex correlations of typical Knowledge Graphs. In this work, we propose GNCE, a novel approach that leverages knowledge graph embeddings and Graph Neural Networks (GNN) to accurately predict the cardinality of conjunctive queries. GNCE first creates semantically meaningful embeddings for all entities in the KG, which are then integrated into the given query, which is processed by a GNN to estimate the cardinality of the query. We evaluate GNCE on several KGs in terms of q-Error and demonstrate that it outperforms state-of-the-art approaches based on sampling, summaries, and (machine) learning in terms of estimation accuracy while also having lower execution time and less parameters. Additionally, we show that GNCE can inductively generalise to unseen entities, making it suitable for use in dynamic query processing scenarios. Our proposed approach has the potential to significantly improve query optimization and related applications that rely on accurate cardinality estimates of conjunctive queries. | ['Maribel Acosta', 'Tim Schwabe'] | 2023-03-02 | null | null | null | null | ['knowledge-graph-embeddings', 'knowledge-graph-embeddings'] | ['graphs', 'methodology'] | [-1.56102031e-01 1.70460984e-01 -2.20214635e-01 -1.51538318e-02
-5.01637578e-01 -6.94288969e-01 3.40885252e-01 1.09440529e+00
-5.32091141e-01 5.39721489e-01 1.93767458e-01 -2.32947290e-01
-5.99075973e-01 -1.45377755e+00 -8.32743645e-01 -9.56687629e-02
-3.73898894e-01 1.07990670e+00 4.80374455e-01 -1.98028758e-01
5.18017299e-02 5.67324936e-01 -1.56018722e+00 -1.33611888e-01
8.36210191e-01 1.32681298e+00 -1.84717044e-01 7.21194506e-01
-2.62087226e-01 6.90467000e-01 -5.42210579e-01 -5.59337854e-01
-3.45484377e-03 3.09967667e-01 -8.27870369e-01 -3.69895041e-01
5.46564758e-01 -2.70079136e-01 -4.77946371e-01 8.33772182e-01
4.91748035e-01 3.72096986e-01 5.46372831e-01 -1.11980057e+00
-7.30414689e-01 7.18830049e-01 7.01169623e-03 2.71030545e-01
4.71783310e-01 -2.70979613e-01 1.66792119e+00 -8.34384978e-01
5.50272107e-01 1.04859233e+00 4.67649370e-01 -3.51788811e-02
-1.22449577e+00 -3.98571432e-01 1.26376320e-02 3.67659748e-01
-1.66255701e+00 -2.41640627e-01 3.06964666e-01 -9.23066959e-02
1.38188076e+00 3.40742171e-01 7.43680537e-01 2.70309150e-01
-3.03468823e-01 6.09661996e-01 3.51975918e-01 -3.92994434e-01
4.24951941e-01 1.94413498e-01 3.95938978e-02 9.35741663e-01
7.12203622e-01 -9.60727632e-02 -5.79638183e-01 -4.91776437e-01
5.15469909e-01 -1.00762121e-01 -2.54583418e-01 -7.30789304e-01
-1.01577663e+00 8.12317729e-01 7.88350046e-01 3.89027670e-02
-6.53945446e-01 5.65536439e-01 3.69581789e-01 1.71432391e-01
3.65558714e-01 8.11078072e-01 -4.87826049e-01 -1.24641493e-01
-8.03605199e-01 3.75847280e-01 1.38874280e+00 1.15417635e+00
9.09697771e-01 -2.28381246e-01 -4.11810935e-01 5.61561942e-01
2.51989454e-01 3.65603179e-01 -1.24537542e-01 -5.94579101e-01
4.52351063e-01 1.20982647e+00 3.82735878e-02 -1.19057500e+00
-3.76561970e-01 -6.06374264e-01 -3.13112646e-01 -4.72030431e-01
-1.89987514e-02 1.91222474e-01 -7.46331096e-01 1.42796779e+00
5.26706815e-01 4.30017859e-02 1.63289800e-01 6.06092155e-01
9.19607699e-01 3.56351823e-01 1.11915730e-01 7.35284612e-02
1.28331101e+00 -7.07306385e-01 -3.67000699e-01 9.88838747e-02
8.59744430e-01 -2.17304677e-01 8.86722982e-01 2.02729017e-01
-9.26783621e-01 -1.63942307e-01 -9.31739390e-01 -1.89733371e-01
-8.92669737e-01 -1.57052830e-01 8.41037750e-01 8.07119668e-01
-1.19921148e+00 4.05654877e-01 -7.41924345e-01 -4.57581758e-01
5.03062785e-01 6.47526383e-01 -1.45035148e-01 -4.51635450e-01
-1.29664361e+00 7.44019389e-01 1.14575624e+00 -2.07008451e-01
-6.44182622e-01 -8.53414416e-01 -1.14115596e+00 5.59129715e-01
1.04082596e+00 -9.82198894e-01 8.98272932e-01 4.05792631e-02
-9.13607597e-01 2.88919240e-01 -4.75198515e-02 -6.08267963e-01
9.63997617e-02 -2.11382449e-01 -4.71494704e-01 1.82494819e-01
-2.20160663e-01 4.41687852e-01 4.63437706e-01 -1.07348979e+00
-5.77305079e-01 -3.40334624e-01 4.23583627e-01 3.42115402e-01
-5.88366508e-01 -3.82522941e-01 -9.68274117e-01 -2.78164208e-01
-7.71692693e-02 -6.26040280e-01 -4.99117225e-02 -2.28932738e-01
-5.97075582e-01 -6.80730045e-01 5.94843924e-01 -4.32585686e-01
1.84731388e+00 -1.87724781e+00 1.52603328e-01 7.68289089e-01
6.61526203e-01 2.58413106e-01 1.42839206e-02 8.93340051e-01
5.42953730e-01 2.68896252e-01 1.18654761e-02 -1.85459152e-01
3.44105631e-01 3.90930712e-01 -9.56765190e-02 1.67006269e-01
3.15094441e-01 1.38611782e+00 -1.19179726e+00 -6.03553951e-01
1.25832185e-01 2.13236749e-01 -6.69690788e-01 1.35311797e-01
-8.78312349e-01 -2.72275090e-01 -4.21476156e-01 9.59514618e-01
3.28642100e-01 -6.71730578e-01 3.30431640e-01 -4.05578822e-01
4.67380077e-01 1.18853018e-01 -1.19540131e+00 1.24090743e+00
-4.29087520e-01 2.35802993e-01 -2.68364906e-01 -9.22205329e-01
6.84819996e-01 -1.51642263e-02 3.46380532e-01 -5.37472904e-01
-3.55405807e-02 2.36412436e-01 -4.12211418e-01 -5.25468290e-01
1.04393756e+00 4.02919114e-01 -3.33317101e-01 4.38039154e-01
1.04145840e-01 -2.07561955e-01 4.43174154e-01 6.19704366e-01
1.27742863e+00 -3.37432295e-01 4.48219538e-01 1.11496344e-01
4.87296104e-01 3.14746350e-02 1.34415105e-01 9.03564751e-01
3.21355313e-01 6.34860527e-03 6.06420279e-01 -2.09439099e-01
-7.85093725e-01 -1.04090929e+00 2.47036740e-01 1.28054488e+00
3.28949690e-01 -7.51912713e-01 -3.95486623e-01 -8.77463460e-01
7.40845561e-01 8.82864654e-01 -5.40041447e-01 -2.24398285e-01
-1.99970454e-01 -1.72765017e-01 5.53810418e-01 7.50348628e-01
-3.94255780e-02 -1.01607108e+00 -3.66266757e-01 3.75425339e-01
1.34367391e-01 -1.38371837e+00 -4.56864864e-01 -1.30351663e-01
-6.53994441e-01 -1.39166319e+00 -1.65161893e-01 -4.90176618e-01
5.47669172e-01 3.37204523e-02 1.48611093e+00 2.92799950e-01
-2.12579414e-01 9.28999782e-01 -4.43571538e-01 -5.73979139e-01
-1.96778819e-01 3.57484341e-01 -2.48868763e-02 -1.58836514e-01
6.71186447e-01 -4.96033579e-01 -5.03448725e-01 6.12780266e-02
-1.27033007e+00 -6.27058327e-01 6.75346792e-01 6.00636303e-01
1.01626122e+00 4.40149128e-01 5.10833979e-01 -1.19638014e+00
1.01318312e+00 -6.68654323e-01 -9.99398172e-01 6.93919897e-01
-1.15206528e+00 4.51907247e-01 4.96520936e-01 -1.84682310e-01
-4.87477690e-01 -4.11429197e-01 3.01064134e-01 -5.72025895e-01
3.00065935e-01 1.10096347e+00 9.65185836e-02 -3.10768694e-01
6.87385142e-01 2.15483382e-01 -2.51848131e-01 -2.86045492e-01
7.33266830e-01 3.69866461e-01 4.83234137e-01 -6.06861413e-01
8.20963740e-01 2.59646505e-01 2.96907455e-01 -7.36413240e-01
-7.35808492e-01 -9.24049139e-01 -2.94754475e-01 5.90396263e-02
4.49651241e-01 -8.15032840e-01 -9.59658802e-01 -5.01023121e-02
-7.68669784e-01 2.99491622e-02 -4.85119641e-01 3.36488694e-01
-2.83345371e-01 4.72947359e-01 -2.51282841e-01 -7.69799352e-01
-4.76366550e-01 -7.30250597e-01 1.11828232e+00 2.62915581e-01
2.88873669e-02 -1.27742577e+00 2.44511645e-02 3.84769887e-01
5.80498159e-01 2.28253245e-01 1.35215592e+00 -1.17009676e+00
-1.11655211e+00 -4.88034129e-01 -5.94308197e-01 1.69521391e-01
-1.19389622e-02 -1.59335926e-01 -5.86720049e-01 -4.50312048e-01
-7.78432190e-01 -4.96570438e-01 8.82499516e-01 2.79797558e-02
1.22727275e+00 -4.95057791e-01 -3.56187344e-01 5.56554019e-01
1.87269771e+00 -4.83258635e-01 4.35156047e-01 1.20321639e-01
6.82527900e-01 3.40343714e-01 6.06095612e-01 6.45948410e-01
8.26642990e-01 4.02665675e-01 8.58241618e-01 3.03523362e-01
1.72122374e-01 -4.99215364e-01 -1.19939581e-01 6.62715912e-01
1.31374463e-01 -6.33045018e-01 -9.32745099e-01 9.59241211e-01
-1.72397006e+00 -6.39508843e-01 1.75226837e-01 2.21189642e+00
6.56204998e-01 1.33377209e-01 9.84189212e-02 -2.65739672e-02
4.36730117e-01 1.97736621e-01 -6.51746869e-01 -4.07216102e-01
1.11057654e-01 6.48930132e-01 8.14865530e-01 1.89734593e-01
-8.94214034e-01 1.04596591e+00 5.93994236e+00 6.78146601e-01
-6.59931779e-01 -1.53326243e-01 -1.12805791e-01 -5.52430283e-04
-5.92141569e-01 4.48950380e-02 -9.23178196e-01 4.59700748e-02
9.65193927e-01 -5.39597809e-01 5.94108820e-01 8.07752430e-01
-4.37502444e-01 -2.18764529e-01 -1.26128852e+00 8.40012610e-01
1.65944859e-01 -1.48083270e+00 2.47632742e-01 1.13990352e-01
6.51599526e-01 1.28358856e-01 -8.70460048e-02 6.86938882e-01
4.11099017e-01 -1.09291208e+00 1.41633213e-01 6.81580305e-01
8.51167321e-01 -8.23544979e-01 8.84193480e-01 2.94187009e-01
-1.39653027e+00 -1.63313121e-01 -4.46087718e-01 4.48532492e-01
-6.39357120e-02 5.91625690e-01 -1.47176373e+00 1.01078403e+00
6.13977790e-01 3.40322018e-01 -7.09443212e-01 1.16612160e+00
-1.20172031e-01 3.49971622e-01 -7.58915007e-01 -4.70941126e-01
7.02849701e-02 2.99634580e-02 4.13229972e-01 9.98284698e-01
2.91863412e-01 -1.47927850e-01 3.92086416e-01 9.48945940e-01
-7.10192323e-01 3.48617762e-01 -4.30551529e-01 -7.05489516e-01
9.74073410e-01 1.16160321e+00 -3.73538554e-01 -4.94023174e-01
-3.59853774e-01 6.23603761e-01 7.27528930e-01 3.90284032e-01
-6.35636032e-01 -6.20648682e-01 4.57755685e-01 1.15189627e-01
8.46033573e-01 -1.12770051e-01 2.60414720e-01 -9.06765938e-01
4.78545249e-01 -5.26812732e-01 8.83149326e-01 -3.46945405e-01
-1.21364820e+00 4.02990431e-01 8.99873227e-02 -8.11383963e-01
-2.20014960e-01 -3.96416962e-01 -2.41917133e-01 6.98060215e-01
-1.85513330e+00 -1.11516166e+00 -5.39453506e-01 5.08384526e-01
-2.14018911e-01 2.68178266e-02 9.24573660e-01 1.58827677e-01
-3.70837301e-01 8.29135656e-01 1.06920429e-01 8.32087249e-02
3.98895830e-01 -1.47539341e+00 3.28322202e-01 4.34600264e-01
3.85418475e-01 5.86944342e-01 3.59494269e-01 -6.60584331e-01
-1.70321190e+00 -1.42678022e+00 8.99358630e-01 -5.24937034e-01
8.37859988e-01 -2.56867588e-01 -9.47831810e-01 5.72063088e-01
-3.29404056e-01 4.76167709e-01 8.10730040e-01 5.48058867e-01
-4.95391905e-01 -2.12875441e-01 -1.09121287e+00 1.40126914e-01
9.34863448e-01 -7.47450769e-01 -5.39089024e-01 4.00053293e-01
1.06663311e+00 -4.58295166e-01 -1.57768703e+00 4.36532706e-01
4.65351373e-01 -7.93681204e-01 9.73164678e-01 -7.72106647e-01
-1.79700986e-01 -1.97383404e-01 -2.45790809e-01 -1.00514841e+00
-8.34816620e-02 -3.05834174e-01 -9.90378439e-01 8.97865713e-01
5.94197631e-01 -7.90437758e-01 1.13929629e+00 5.75118244e-01
1.93425730e-01 -1.09785485e+00 -7.48780549e-01 -8.81435215e-01
-5.05155087e-01 -4.43929911e-01 9.62039769e-01 7.02526033e-01
-1.08166382e-01 1.19806997e-01 1.41094193e-01 6.29183471e-01
6.08821452e-01 3.07755321e-01 8.50242674e-01 -1.33915293e+00
-3.52123350e-01 -2.80458748e-01 -8.16522241e-01 -1.00369084e+00
-2.99271122e-02 -9.55391824e-01 -3.77797872e-01 -1.84729064e+00
-1.11001469e-01 -7.26249456e-01 -4.30349827e-01 3.78912270e-01
-2.77181506e-01 -1.92186475e-01 -1.30653650e-01 1.90336574e-02
-1.04770696e+00 6.62593246e-01 8.23927581e-01 -2.65400708e-01
-3.76779199e-01 -3.76591310e-02 -6.47897482e-01 5.15640266e-02
5.16686082e-01 -4.29015189e-01 -5.31975746e-01 -3.53816330e-01
7.66460478e-01 2.23975517e-02 3.14441144e-01 -1.06011164e+00
6.85539365e-01 5.94577417e-02 1.08438484e-01 -7.54965305e-01
3.15107405e-01 -8.09744895e-01 -2.33908650e-02 1.70378610e-01
-1.82497144e-01 7.98297599e-02 1.95680171e-01 1.18801939e+00
-4.14167047e-01 -6.81514069e-02 1.03943951e-01 1.77453551e-02
-8.20879400e-01 6.85784221e-01 3.77852768e-01 4.97039855e-01
9.94428754e-01 -2.34664157e-01 -3.21391016e-01 -4.41325486e-01
-5.59879899e-01 7.59913087e-01 5.03589511e-01 1.11489691e-01
8.13860536e-01 -1.14328098e+00 -5.03043652e-01 4.56597693e-02
7.43530393e-01 4.85032469e-01 -1.31998947e-02 7.52892911e-01
-7.60565162e-01 7.12562025e-01 5.33891320e-01 -5.12458146e-01
-9.99823928e-01 7.62823761e-01 2.37113722e-02 -7.09600031e-01
-1.75357729e-01 9.73996758e-01 -3.93998057e-01 -5.60379326e-01
5.33446610e-01 -5.45183778e-01 -2.25830361e-01 7.43945986e-02
1.33221865e-01 4.15407270e-01 2.68615514e-01 -2.88186163e-01
-3.62052113e-01 1.09041087e-01 -1.79145828e-01 4.32002932e-01
1.35159481e+00 2.19773471e-01 -2.91649103e-01 3.26630026e-02
1.20099413e+00 1.07607916e-01 -5.22459090e-01 -8.75869632e-01
3.34943295e-01 -4.95385826e-01 1.97384302e-02 -6.39501214e-01
-9.36721325e-01 3.47642988e-01 1.73768550e-01 4.96577531e-01
1.11499858e+00 4.04246062e-01 9.40203190e-01 8.95962000e-01
4.50987607e-01 -1.07847178e+00 -5.26734367e-02 3.61887813e-01
4.88161951e-01 -1.08698571e+00 3.90471637e-01 -3.98833454e-01
-2.42702648e-01 1.11160958e+00 3.92076790e-01 1.52598932e-01
6.16566300e-01 -2.88709551e-01 -5.10557175e-01 -8.08858395e-01
-8.59433949e-01 -4.84178990e-01 5.89824796e-01 6.16833627e-01
-1.80502251e-01 5.06846309e-02 2.35038131e-01 2.48971343e-01
-1.67432427e-01 7.85243418e-03 2.03748375e-01 1.01769924e+00
-4.57328558e-01 -1.09242499e+00 2.79456601e-02 1.04228568e+00
-3.29982102e-01 -3.01039726e-01 -4.51238930e-01 8.61331105e-01
-1.33333623e-01 7.54167259e-01 -7.92531297e-02 -4.57851112e-01
6.23718321e-01 2.11218232e-03 4.48478371e-01 -9.46722269e-01
-5.15493989e-01 -6.15805030e-01 4.36748803e-01 -6.25727534e-01
-1.58505753e-01 -1.78857639e-01 -1.13953912e+00 -3.35328639e-01
-8.04440618e-01 4.17834461e-01 5.05302310e-01 5.83098471e-01
7.69329667e-01 3.88920158e-01 2.78306693e-01 -1.30608842e-01
-7.69474089e-01 -7.73733854e-01 -6.15005255e-01 5.11131585e-01
1.72658235e-01 -6.98810399e-01 -2.22148880e-01 -5.24088740e-01] | [9.115498542785645, 7.7447028160095215] |
919a66c3-462a-4c2d-bfcc-31c7da74a97c | cluster-guided-unsupervised-domain-adaptation | 2303.15944 | null | https://arxiv.org/abs/2303.15944v1 | https://arxiv.org/pdf/2303.15944v1.pdf | Cluster-Guided Unsupervised Domain Adaptation for Deep Speaker Embedding | Recent studies have shown that pseudo labels can contribute to unsupervised domain adaptation (UDA) for speaker verification. Inspired by the self-training strategies that use an existing classifier to label the unlabeled data for retraining, we propose a cluster-guided UDA framework that labels the target domain data by clustering and combines the labeled source domain data and pseudo-labeled target domain data to train a speaker embedding network. To improve the cluster quality, we train a speaker embedding network dedicated for clustering by minimizing the contrastive center loss. The goal is to reduce the distance between an embedding and its assigned cluster center while enlarging the distance between the embedding and the other cluster centers. Using VoxCeleb2 as the source domain and CN-Celeb1 as the target domain, we demonstrate that the proposed method can achieve an equal error rate (EER) of 8.10% on the CN-Celeb1 evaluation set without using any labels from the target domain. This result outperforms the supervised baseline by 39.6% and is the state-of-the-art UDA performance on this corpus. | ['Man-Wai Mak', 'Feng Hong', 'Haiquan Mao'] | 2023-03-28 | null | null | null | null | ['speaker-verification'] | ['speech'] | [-2.06802897e-02 3.37827325e-01 -4.88485023e-02 -8.46133947e-01
-1.17113090e+00 -5.75794876e-01 5.25839925e-01 -2.38603782e-02
-4.51501697e-01 4.07403320e-01 2.02448353e-01 -2.92566359e-01
1.79049805e-01 -1.23685233e-01 -4.53742534e-01 -9.53553200e-01
6.28154427e-02 6.11797929e-01 -4.89175282e-02 3.77208926e-02
-2.11190566e-01 3.56577337e-01 -1.38591397e+00 1.61422700e-01
9.21487570e-01 8.58210862e-01 1.37770906e-01 2.93877929e-01
2.68508997e-02 1.98189616e-01 -9.39680755e-01 -3.61583292e-01
9.92409885e-02 -5.70950806e-01 -9.44765687e-01 2.23221898e-01
4.17085320e-01 1.18036829e-01 -2.34475315e-01 1.02261209e+00
7.94841766e-01 3.14055830e-01 7.54393816e-01 -1.25254989e+00
-7.53186643e-01 1.01770341e+00 -2.96854228e-01 5.95781393e-02
-1.51648177e-02 -3.29759210e-01 8.54727745e-01 -1.10319018e+00
5.13419747e-01 1.21704018e+00 4.37871456e-01 1.36665618e+00
-1.28062630e+00 -1.03670883e+00 2.84732342e-01 3.41297954e-01
-1.62176359e+00 -9.09296036e-01 1.16461098e+00 -3.03757191e-01
5.33090293e-01 1.49707586e-01 -5.95930330e-02 1.24538851e+00
-7.97792554e-01 6.08371794e-01 8.29175353e-01 -8.83002639e-01
5.14706552e-01 6.46268129e-01 4.51746732e-01 2.43047684e-01
-2.51661420e-01 1.98363125e-01 -6.70370221e-01 -2.48942841e-02
-1.82945013e-01 -4.99073297e-01 -3.05060595e-01 -3.91308755e-01
-1.06416953e+00 9.98139918e-01 3.35811347e-01 2.57472694e-01
2.46072207e-02 -4.83686745e-01 4.96533334e-01 2.05504954e-01
5.34218788e-01 2.48157799e-01 -4.48861837e-01 1.37503400e-01
-9.56853747e-01 -2.92560846e-01 6.17565870e-01 9.92802143e-01
7.05861807e-01 2.75106758e-01 1.03797996e-02 1.43025982e+00
6.36351705e-01 5.56371212e-01 8.63652706e-01 -7.32669175e-01
4.26101208e-01 5.59191167e-01 -3.99745293e-02 -3.18170130e-01
-6.81190612e-03 -2.83015043e-01 -6.31822288e-01 1.59535363e-01
4.05285031e-01 -2.04030618e-01 -9.15160596e-01 2.02062511e+00
5.51439404e-01 3.87895137e-01 5.72152853e-01 9.11367178e-01
9.59910274e-01 7.33867943e-01 6.17423691e-02 -2.44179875e-01
1.16989338e+00 -1.09130239e+00 -7.40237415e-01 -2.34481081e-01
6.81580007e-01 -7.19275951e-01 1.13623130e+00 1.13006882e-01
-6.88496947e-01 -7.92695999e-01 -1.41736269e+00 2.80788690e-01
-3.95957023e-01 3.50139529e-01 -1.83377862e-01 1.03231096e+00
-1.09975755e+00 9.69917849e-02 -5.96803844e-01 -5.13172746e-01
2.52161086e-01 3.61236393e-01 -3.60792279e-01 -1.56721577e-01
-1.31806254e+00 6.94317162e-01 4.61589694e-01 -9.56496298e-02
-1.11907816e+00 -6.85002267e-01 -9.34966326e-01 -9.36862547e-03
-3.50783952e-02 1.43397495e-01 1.05708981e+00 -8.31554174e-01
-1.82245076e+00 1.21921241e+00 -3.47728610e-01 -4.75396603e-01
1.39714167e-01 1.93507686e-01 -9.14908171e-01 -7.61391148e-02
6.57941699e-02 8.84365022e-01 9.54037488e-01 -1.34605861e+00
-4.08393621e-01 -5.69919765e-01 -6.41211092e-01 2.05723032e-01
-8.01316500e-01 9.36804116e-02 -4.00239974e-01 -5.66089272e-01
2.08915845e-01 -1.03563809e+00 2.06441820e-01 -5.77357173e-01
-5.73881745e-01 -6.95231557e-01 1.27103698e+00 -7.44510412e-01
1.23762357e+00 -2.81221867e+00 1.19977169e-01 3.21018487e-01
-1.00921042e-01 4.18855011e-01 -2.99459547e-01 -7.05483258e-02
-4.12385553e-01 -3.63028497e-02 -3.96206617e-01 -8.01054001e-01
2.79777169e-01 -1.96544155e-02 -2.44503990e-01 5.22946715e-01
6.70294985e-02 2.87733048e-01 -6.46520257e-01 -4.72864360e-01
6.00196272e-02 5.85874140e-01 -3.71482462e-01 4.21703279e-01
9.75860283e-02 5.54576039e-01 1.54770657e-01 4.25960839e-01
9.18781817e-01 1.13922998e-01 4.52224970e-01 2.13878080e-02
2.46851251e-01 6.17627323e-01 -1.30536699e+00 1.64969993e+00
-2.25993365e-01 8.38315785e-01 3.12851787e-01 -1.06804585e+00
1.41193318e+00 4.44784790e-01 3.20368081e-01 -2.75020629e-01
2.96783773e-03 1.72312424e-01 1.15168169e-01 -6.38205856e-02
2.47289598e-01 -2.76398659e-01 -2.24756509e-01 5.86170316e-01
3.32690626e-01 8.24685097e-02 -3.58199120e-01 2.44674817e-01
7.33925045e-01 -4.42958742e-01 -1.65841535e-01 -3.51626933e-01
8.76977623e-01 -2.74460912e-01 7.25704670e-01 2.49889702e-01
-7.06943989e-01 4.86802608e-01 3.68793122e-02 -3.29100713e-03
-9.67968404e-01 -1.22744679e+00 -4.50366169e-01 1.33960330e+00
6.74318522e-02 -2.33995274e-01 -1.00267684e+00 -9.80091035e-01
-4.46104333e-02 9.81615186e-01 -6.16545022e-01 -3.79391015e-01
-4.80484158e-01 -4.18233335e-01 7.64336348e-01 3.54699790e-01
3.73932451e-01 -1.03809798e+00 3.30298036e-01 1.61416918e-01
-4.65027750e-01 -1.11792076e+00 -9.99083340e-01 3.09020728e-01
-5.28016806e-01 -6.92644358e-01 -6.96185887e-01 -1.41621518e+00
7.34954655e-01 -1.22086830e-01 7.60682166e-01 -3.48203629e-01
1.99864179e-01 3.18536073e-01 -3.66847873e-01 -3.61786544e-01
-9.52930272e-01 2.05195948e-01 5.34412205e-01 3.69400084e-01
8.41462851e-01 -1.46603182e-01 -2.12005302e-01 6.83150828e-01
-5.35531104e-01 -4.77736712e-01 -3.59203108e-02 9.83620465e-01
3.44779879e-01 -9.13884640e-02 1.06807184e+00 -5.91622353e-01
5.06351233e-01 -2.17207357e-01 -4.68969285e-01 2.74436325e-01
-6.94177270e-01 3.01091578e-02 4.10099953e-01 -8.91917527e-01
-1.03243423e+00 3.25975388e-01 4.11234275e-02 -5.34957290e-01
-4.33963627e-01 8.84741768e-02 -7.85842538e-01 2.54975706e-01
8.52423906e-01 2.80087233e-01 9.03734416e-02 -5.16366065e-01
4.41760421e-01 1.48966396e+00 6.38001740e-01 -2.73474663e-01
6.65831506e-01 2.05090791e-01 -7.71045327e-01 -9.19982612e-01
-6.52704597e-01 -8.47329378e-01 -8.43411207e-01 -2.50911146e-01
7.71720588e-01 -9.99213159e-01 -4.49085295e-01 3.23986739e-01
-1.10990846e+00 -2.92355090e-01 -2.90839136e-01 7.03869045e-01
-2.22208560e-01 4.00888622e-01 -2.47694552e-01 -8.22202027e-01
-2.77812243e-01 -1.18713272e+00 8.60560656e-01 3.08292508e-02
-3.24511588e-01 -9.34121966e-01 1.38449296e-01 5.51283121e-01
2.20340207e-01 -2.83052057e-01 7.94581831e-01 -1.29217470e+00
4.38969359e-02 -1.33905858e-01 1.77740306e-01 8.24284613e-01
2.40252137e-01 -4.25751776e-01 -1.53892529e+00 -5.96707404e-01
1.67746052e-01 -2.06800863e-01 6.19118452e-01 2.25017741e-01
7.60905266e-01 -2.05670819e-01 -4.28623587e-01 4.71999973e-01
8.77860785e-01 4.00541961e-01 3.83992881e-01 2.48977959e-01
5.05338013e-01 7.48024583e-01 4.34608608e-01 2.26181507e-01
2.80919611e-01 8.98364842e-01 -3.55113745e-02 1.52672544e-01
-5.09405434e-01 -3.26856345e-01 7.19162524e-01 1.28250909e+00
5.80138326e-01 -6.61669225e-02 -1.00057876e+00 9.62530077e-01
-1.37867200e+00 -7.98390985e-01 2.70872474e-01 2.40282512e+00
1.07563794e+00 -1.03483155e-01 3.27797860e-01 3.36211264e-01
1.30421317e+00 -4.01487648e-02 -6.74994588e-01 -4.13236201e-01
-1.70407772e-01 -9.48280916e-02 4.71412279e-02 8.19567025e-01
-1.26875210e+00 1.05981219e+00 5.86669922e+00 6.95388734e-01
-1.20774770e+00 4.19779480e-01 4.24551696e-01 7.05267414e-02
2.04074867e-02 -3.61910850e-01 -1.05953312e+00 6.13989115e-01
1.43852627e+00 -9.84571055e-02 4.09903556e-01 1.08274710e+00
2.97915302e-02 6.17101729e-01 -1.35295832e+00 1.08582282e+00
4.75494832e-01 -8.15837443e-01 -2.17562690e-01 1.14734702e-01
8.15925837e-01 -8.77461978e-04 2.13992402e-01 6.45624101e-01
3.47829103e-01 -7.48455644e-01 6.14198923e-01 -2.25788653e-01
1.10813510e+00 -8.13376606e-01 6.83570266e-01 2.51814425e-01
-8.86824071e-01 -5.95639981e-02 -5.07493198e-01 5.75163841e-01
-3.00730839e-02 3.27580094e-01 -1.50910723e+00 1.37199402e-01
8.21272194e-01 4.41072911e-01 -4.79184389e-01 8.39725435e-01
-2.99800783e-01 1.12466919e+00 -3.02100420e-01 1.09341085e-01
-2.76102908e-02 -4.52495143e-02 7.15111792e-01 1.14522040e+00
1.29591435e-01 -3.13908875e-01 -1.08679093e-01 7.05340266e-01
-5.15891969e-01 2.63669103e-01 -3.68443072e-01 1.88691884e-01
1.02635622e+00 7.54559219e-01 -2.34986514e-01 -4.39288616e-01
-1.16811551e-01 1.07109928e+00 3.79975051e-01 5.55413723e-01
-9.13513601e-01 -6.48050487e-01 7.51197278e-01 -5.27768992e-02
5.20215333e-01 1.50989175e-01 -2.52443403e-01 -9.66114223e-01
-4.25163731e-02 -8.55108380e-01 4.61173207e-01 -4.08699691e-01
-1.44224918e+00 1.06615186e+00 -2.15930715e-01 -1.41772497e+00
-2.80554116e-01 -3.31158817e-01 -5.55876851e-01 1.08270156e+00
-1.39803493e+00 -1.12643850e+00 -1.79992497e-01 7.60860503e-01
4.67420548e-01 -7.33783543e-01 1.15519428e+00 4.11385953e-01
-5.69510937e-01 1.28569043e+00 4.73837078e-01 5.73368490e-01
1.27098060e+00 -1.19580507e+00 1.67276546e-01 8.33760977e-01
2.39189520e-01 4.95977402e-01 4.49427605e-01 -2.50030667e-01
-6.59208775e-01 -1.21792710e+00 1.26758003e+00 -4.53962117e-01
3.82188767e-01 -8.66811156e-01 -1.12092686e+00 6.70014143e-01
2.85671592e-01 -4.88189496e-02 9.02777791e-01 4.53986913e-01
-7.81606317e-01 -4.22093600e-01 -1.36542523e+00 2.66422302e-01
6.26138568e-01 -7.74946034e-01 -8.47465217e-01 2.14617521e-01
8.52607965e-01 -1.10680096e-01 -7.30407894e-01 2.19647288e-01
5.54410852e-02 -6.28153086e-01 8.62772226e-01 -6.23999953e-01
-3.32843155e-01 -4.89835858e-01 -2.90770739e-01 -1.63142252e+00
-1.88891307e-01 -4.58771110e-01 1.96145833e-01 1.73570752e+00
7.53433049e-01 -5.75532138e-01 8.93861055e-01 5.54035366e-01
-3.30149770e-01 4.81797643e-02 -1.40365970e+00 -1.09798229e+00
3.19055676e-01 -4.00868356e-01 7.62096822e-01 1.33748877e+00
3.19709748e-01 5.37183821e-01 -5.01480922e-02 5.38563728e-01
8.45043898e-01 -1.04759425e-01 6.00875497e-01 -1.26661587e+00
1.70809746e-01 -1.71734601e-01 -4.30796236e-01 -8.73218358e-01
7.75598168e-01 -1.29781258e+00 3.09411824e-01 -9.31765854e-01
-8.60741213e-02 -6.31275535e-01 -5.91743290e-01 5.58416128e-01
-9.50504318e-02 9.86018106e-02 1.42705783e-01 3.14086765e-01
-5.09457767e-01 6.54799104e-01 6.64464474e-01 -4.88805115e-01
-5.35197198e-01 8.39518234e-02 -6.74953699e-01 3.40462565e-01
8.58746767e-01 -6.40141845e-01 -3.23715627e-01 -2.28554755e-01
-9.15732563e-01 -2.99323469e-01 -1.00109711e-01 -9.30455804e-01
3.35635841e-01 3.81339878e-01 9.35759768e-02 -5.86702883e-01
4.01968002e-01 -8.31593394e-01 -3.04239243e-01 1.90126076e-01
-6.41639829e-01 -5.05967438e-01 3.64578992e-01 4.86057520e-01
-4.53708351e-01 -3.02833050e-01 1.27121532e+00 6.15383923e-01
-5.71716607e-01 -6.64051101e-02 -2.68146485e-01 9.47874933e-02
1.10364151e+00 -4.98341955e-02 -9.39530283e-02 -3.35470945e-01
-1.11035335e+00 1.30568072e-01 2.88196832e-01 5.22114217e-01
5.89475334e-01 -1.62734616e+00 -1.05647743e+00 5.49498320e-01
4.01840836e-01 -1.72584489e-01 3.32017064e-01 3.90287340e-01
2.50726454e-02 4.59274262e-01 1.97385117e-01 -8.54663253e-01
-1.55729771e+00 6.77009344e-01 4.38512385e-01 8.62895325e-02
-2.94708937e-01 1.06067431e+00 8.00115690e-02 -1.10536003e+00
7.45703220e-01 -8.63760803e-03 -1.54611841e-01 9.35171079e-03
6.22734785e-01 3.03757548e-01 2.37066984e-01 -9.79793131e-01
-7.33991086e-01 2.28587419e-01 -2.13525414e-01 -3.96291703e-01
1.11134827e+00 -2.95754701e-01 2.30988130e-01 4.03895438e-01
1.50223529e+00 1.63362905e-01 -1.05805731e+00 -4.33795780e-01
1.01923764e-01 -6.78142905e-02 -5.47627881e-02 -1.05100298e+00
-8.35083127e-01 1.02803636e+00 1.06295288e+00 1.03280924e-01
8.95596027e-01 3.77756745e-01 5.02721012e-01 7.10922927e-02
-1.40284210e-01 -1.25268257e+00 1.09214470e-01 3.67033154e-01
8.43451083e-01 -1.43030334e+00 -5.40360570e-01 -2.04423442e-01
-9.89748180e-01 6.07947052e-01 6.36399090e-01 2.82790899e-01
8.86056066e-01 -6.14382587e-02 6.92885458e-01 2.56827891e-01
-3.77124876e-01 8.49256143e-02 3.89814824e-01 9.70105350e-01
2.22073019e-01 4.12000954e-01 2.26807371e-01 9.12729681e-01
-3.30748558e-01 -6.22373879e-01 1.56143367e-01 3.34325582e-01
-2.89403230e-01 -1.26772785e+00 -7.37825930e-01 -9.36129540e-02
-1.96234748e-01 -4.30532098e-02 -4.60547179e-01 5.43392360e-01
-2.89428812e-02 1.41857362e+00 6.50522187e-02 -5.60786009e-01
3.83387774e-01 7.38804221e-01 1.92786027e-02 -6.57508492e-01
-3.50510925e-01 3.26007158e-01 -1.63497925e-01 6.81493133e-02
-3.87535751e-01 -8.34266782e-01 -1.19735265e+00 5.48387915e-02
-5.43672800e-01 6.29089773e-01 9.18638766e-01 5.99647284e-01
4.55337733e-01 2.38280490e-01 1.04112756e+00 -4.27248925e-01
-6.27299547e-01 -1.55974185e+00 -7.24874794e-01 6.45195603e-01
4.31505829e-01 -5.65188944e-01 -8.06933343e-01 3.75676692e-01] | [14.342494010925293, 6.105182647705078] |
ead6fa04-829e-400c-a4f7-f50ef3b0757e | review-of-large-vision-models-and-visual | 2307.00855 | null | https://arxiv.org/abs/2307.00855v1 | https://arxiv.org/pdf/2307.00855v1.pdf | Review of Large Vision Models and Visual Prompt Engineering | Visual prompt engineering is a fundamental technology in the field of visual and image Artificial General Intelligence, serving as a key component for achieving zero-shot capabilities. As the development of large vision models progresses, the importance of prompt engineering becomes increasingly evident. Designing suitable prompts for specific visual tasks has emerged as a meaningful research direction. This review aims to summarize the methods employed in the computer vision domain for large vision models and visual prompt engineering, exploring the latest advancements in visual prompt engineering. We present influential large models in the visual domain and a range of prompt engineering methods employed on these models. It is our hope that this review provides a comprehensive and systematic description of prompt engineering methods based on large visual models, offering valuable insights for future researchers in their exploration of this field. | ['Shu Zhang', 'Tianming Liu', 'Dinggang Shen', 'Yixuan Yuan', 'Bao Ge', 'Xi Jiang', 'Xiang Li', 'Dajiang Zhu', 'Tuo Zhang', 'Yi Pan', 'Enze Shi', 'Songyao Zhang', 'Yiheng Liu', 'Qiushi Yang', 'Haixing Dai', 'Sigang Yu', 'Chong Ma', 'Zihao Wu', 'Lin Zhao', 'Zhengliang Liu', 'Jiaqi Wang'] | 2023-07-03 | null | null | null | null | ['prompt-engineering'] | ['natural-language-processing'] | [ 3.08739454e-01 7.72889927e-02 -3.12751740e-01 -1.14155613e-01
-7.69685656e-02 -5.27285874e-01 7.06940174e-01 3.78737296e-03
-2.75671393e-01 7.59410486e-02 1.47928208e-01 -3.83448124e-01
-1.58239931e-01 -1.88395500e-01 -4.37792569e-01 -4.58513230e-01
2.26577312e-01 2.75558997e-02 2.96387762e-01 1.50886267e-01
7.90881991e-01 8.45352292e-01 -1.99057150e+00 2.37187490e-01
5.24817646e-01 9.71589923e-01 6.33543968e-01 9.83220816e-01
-2.83518791e-01 1.39148533e+00 -6.32112980e-01 -3.08256149e-01
7.87534490e-02 -3.12062204e-01 -6.49933875e-01 5.15810609e-01
7.80880094e-01 -3.58265162e-01 -3.16359550e-01 1.01078272e+00
4.23504978e-01 1.30701810e-01 6.74836099e-01 -1.44930995e+00
-1.10842359e+00 -3.97300087e-02 -6.22204363e-01 5.88462412e-01
4.86539125e-01 6.00039363e-01 8.13467622e-01 -1.10806012e+00
6.23119056e-01 9.85047162e-01 3.65456343e-01 5.14025569e-01
-6.93000078e-01 -6.98061362e-02 4.43566889e-01 8.86879385e-01
-9.79781508e-01 -4.61703390e-01 9.38438356e-01 -7.28576720e-01
1.21044219e+00 3.31897408e-01 1.05084372e+00 9.77848291e-01
1.64623886e-01 9.55744267e-01 1.22326958e+00 -8.31676841e-01
3.10870677e-01 1.70300514e-01 6.34127438e-01 6.02426231e-01
1.61460757e-01 8.29949975e-01 -8.57594967e-01 8.60173553e-02
9.86891210e-01 -1.27586901e-01 -1.97712686e-02 -1.32482737e-01
-9.24515367e-01 7.53552079e-01 2.93569744e-01 8.33445266e-02
-7.32411265e-01 1.54246330e-01 1.42205715e-01 1.46743000e-01
8.12664255e-02 4.65188414e-01 -3.13394777e-02 -1.96819782e-01
-6.09989583e-01 3.78343999e-01 4.95307773e-01 1.11324871e+00
3.98554265e-01 5.90677977e-01 -4.90223050e-01 7.82406509e-01
5.29166520e-01 6.10997915e-01 -7.05180783e-03 -1.35019195e+00
-3.62734556e-01 6.32951379e-01 2.19440982e-01 -8.64686251e-01
-2.47174069e-01 -2.30609134e-01 -5.04489601e-01 8.35266709e-01
7.92765841e-02 1.88327029e-01 -1.18885434e+00 1.00806248e+00
1.82705045e-01 1.99945226e-01 -2.21787363e-01 9.21918988e-01
1.43750203e+00 6.54384136e-01 4.31705981e-01 -4.65450466e-01
1.53442931e+00 -1.28242826e+00 -8.16375017e-01 -5.58373451e-01
-2.91685998e-01 -1.10488856e+00 1.18340468e+00 4.65464056e-01
-1.12002385e+00 -8.83587062e-01 -9.68880653e-01 -3.13960880e-01
-1.64420038e-01 7.60002360e-02 1.02765214e+00 3.25649351e-01
-1.25465608e+00 -1.13834471e-01 -4.22067374e-01 -6.79821670e-01
3.55619490e-01 -1.11346655e-01 3.71344127e-02 -2.42052391e-01
-6.43055201e-01 1.03767633e+00 7.59477764e-02 8.57528672e-03
-9.97507572e-01 -7.79044688e-01 -7.29092598e-01 -2.08811894e-01
4.45870966e-01 -9.23360705e-01 1.77859974e+00 -9.07617569e-01
-1.25976229e+00 1.10397792e+00 -2.70385504e-01 -3.41362000e-01
2.12333083e-01 -1.74817443e-01 -2.37086937e-01 3.15446466e-01
-1.59558147e-01 6.39372170e-01 1.33507848e+00 -1.44504201e+00
-9.48576868e-01 -2.20924124e-01 2.04968020e-01 4.15448785e-01
-2.27855608e-01 6.53218210e-01 -7.42940605e-01 -4.00306165e-01
-5.11385620e-01 -4.81766939e-01 -6.39453411e-01 3.15155238e-01
-5.24766184e-02 -4.47808653e-01 8.25850964e-01 -1.97205842e-01
1.25958467e+00 -1.92814779e+00 -2.17608735e-01 -2.11510390e-01
7.66360044e-01 5.97360909e-01 -1.57278344e-01 3.88819784e-01
1.63013563e-01 -3.24634612e-01 3.37158740e-01 -1.01992905e-01
-2.91145146e-01 7.73455799e-02 -5.20557940e-01 1.15957029e-01
-2.73471256e-03 1.24797797e+00 -9.21771228e-01 -4.99315411e-01
8.84965062e-01 4.34578568e-01 -1.92769449e-02 6.29163206e-01
-2.35399380e-01 1.23400703e-01 -4.84013617e-01 8.30082059e-01
3.07734519e-01 -6.67065501e-01 -2.99716800e-01 -1.61861688e-01
-5.78926027e-01 -5.13723552e-01 -7.52909124e-01 1.16417325e+00
1.24393970e-01 9.83207822e-01 -7.81834647e-02 -6.02467775e-01
9.48575437e-01 3.78694206e-01 3.38308513e-01 -1.07790828e+00
1.10918723e-01 -1.23625331e-01 -2.41655171e-01 -9.42500770e-01
7.46930242e-01 5.36642261e-02 4.98198569e-01 1.31644353e-01
-3.41289908e-01 -2.62025088e-01 3.76004040e-01 4.32454348e-01
7.57528186e-01 -1.70673236e-01 8.17902505e-01 1.84891805e-01
3.67398947e-01 4.00312811e-01 -4.80472371e-02 9.57934499e-01
-5.49441934e-01 5.17214298e-01 3.11451945e-02 -8.29004765e-01
-9.16344404e-01 -1.03020990e+00 1.59436613e-01 8.71811390e-01
3.59184325e-01 -5.81854045e-01 -4.07004356e-01 -2.82049119e-01
-1.89351365e-01 3.87001634e-01 -6.69805408e-01 5.18108681e-02
-2.25616306e-01 -3.13660115e-01 2.40061358e-01 9.05704200e-01
1.43941417e-01 -1.56117952e+00 -1.36429119e+00 -1.19862512e-01
3.15201283e-02 -1.21322644e+00 -2.23857060e-01 9.85908322e-03
-8.84917915e-01 -1.23504508e+00 -8.50831747e-01 -9.42373574e-01
7.58786857e-01 9.77751791e-01 1.15825570e+00 3.35078031e-01
-7.49511182e-01 1.09833634e+00 -4.25345451e-01 -7.91084647e-01
-2.08402619e-01 -5.68321705e-01 -2.34058484e-01 -3.34928781e-01
6.49373293e-01 -1.52438760e-01 -7.28709280e-01 -2.53716651e-02
-7.54221201e-01 3.01705688e-01 5.11297226e-01 7.56477714e-01
6.84108734e-01 -3.74402195e-01 2.78052151e-01 -6.19420290e-01
1.12283623e+00 -1.82797715e-01 -8.28084230e-01 3.78456026e-01
-8.91024470e-01 -3.32797438e-01 4.01163042e-01 -4.92388815e-01
-1.09086478e+00 -1.73548773e-01 4.74647945e-03 -4.61041838e-01
-4.45133418e-01 5.04693687e-01 2.76355624e-01 -3.36017430e-01
9.12724257e-01 1.52545959e-01 -1.55558094e-01 -4.17699665e-01
8.70045304e-01 6.47010922e-01 8.12617958e-01 -3.56101006e-01
4.07723248e-01 3.03271890e-01 1.15611129e-01 -1.25781846e+00
-6.09019160e-01 -7.62934923e-01 -2.50384271e-01 -9.30766165e-01
7.81632364e-01 -3.78600389e-01 -9.01364207e-01 7.03993499e-01
-1.43421364e+00 -3.02103311e-01 -5.61379731e-01 8.24211240e-02
-6.67745173e-01 6.33278191e-01 -5.00491261e-01 -9.05079901e-01
-5.27658582e-01 -1.22808444e+00 7.86074460e-01 9.95754302e-01
-3.43534142e-01 -1.00294960e+00 1.07814884e-02 4.93330538e-01
4.44356710e-01 -2.36503795e-01 8.10775280e-01 -1.34955451e-01
-9.07842815e-01 -2.50594884e-01 -5.89297652e-01 2.22920969e-01
-1.37955949e-01 4.05058652e-01 -1.26736391e+00 1.06666468e-01
-4.27624248e-02 -3.72397035e-01 4.93285835e-01 9.11360681e-01
8.23381305e-01 2.71026604e-02 -3.01040947e-01 4.62536216e-01
1.51569021e+00 6.74748361e-01 6.57207310e-01 4.38088804e-01
8.05859447e-01 7.13864505e-01 9.21275198e-01 6.46850705e-01
3.95886689e-01 5.02655447e-01 4.60502088e-01 -2.58564055e-01
-6.47385359e-01 -1.53132573e-01 9.08068269e-02 6.55167162e-01
-4.96824503e-01 -4.07318473e-02 -1.03046346e+00 4.48955119e-01
-1.88412046e+00 -1.08602667e+00 -3.50905299e-01 1.91024327e+00
4.08325046e-01 -1.55788481e-01 -1.62329338e-02 2.03096177e-02
3.26214254e-01 3.42175633e-01 -6.02629244e-01 -4.54071134e-01
-1.12375338e-02 6.46248180e-03 7.20058903e-02 5.51145196e-01
-8.58629584e-01 1.14277506e+00 7.97016907e+00 5.36234677e-01
-1.28993142e+00 -2.06965089e-01 3.34278703e-01 1.13913238e-01
-1.59525260e-01 2.57438749e-01 -7.73886204e-01 1.06896386e-01
6.42649591e-01 -3.94119024e-01 4.34873074e-01 1.13711929e+00
5.61734021e-01 -4.93036568e-01 -9.27804887e-01 1.42347097e+00
3.17226201e-01 -1.69117081e+00 1.33599430e-01 -2.11244524e-02
6.50509775e-01 -1.39063954e-01 2.71019608e-01 -1.55175179e-01
1.33108452e-01 -1.15930140e+00 8.09410214e-01 6.48432970e-01
8.47889662e-01 -3.38461578e-01 1.94481865e-01 2.19941169e-01
-1.25414467e+00 -1.08841263e-01 -4.40082729e-01 -3.33131373e-01
4.48083788e-01 2.47888923e-01 -6.69425964e-01 2.50992894e-01
8.26757431e-01 8.66935074e-01 -7.93489814e-01 1.47030675e+00
-3.63857716e-01 4.34802651e-01 1.98499978e-01 -7.40154758e-02
6.28718408e-03 -6.82033673e-02 6.64649248e-01 9.87487972e-01
-1.60972625e-01 8.32630172e-02 3.57187003e-01 7.38754869e-01
5.42507470e-01 3.09000667e-02 -8.13580275e-01 -3.28342944e-01
5.52383482e-01 1.30893612e+00 -8.63449991e-01 -4.71309632e-01
-8.17629814e-01 8.25083673e-01 1.72070429e-01 7.03396380e-01
-5.80698013e-01 -2.47959018e-01 4.22574162e-01 9.29577127e-02
5.37045747e-02 -2.32217699e-01 -7.61070251e-01 -7.08406985e-01
-1.72740072e-01 -1.04502702e+00 4.03044730e-01 -1.42887318e+00
-1.19161928e+00 7.27818966e-01 2.80645967e-01 -1.14939988e+00
-4.22607720e-01 -7.92225182e-01 -6.32983387e-01 7.81035721e-01
-1.69228160e+00 -1.40570068e+00 -7.88232148e-01 6.10380590e-01
9.72350895e-01 -2.11245880e-01 7.10842013e-01 -1.79488420e-01
-1.49216220e-01 2.28760585e-01 -3.49157661e-01 -5.02417207e-01
5.23616374e-01 -8.86036456e-01 5.34366727e-01 1.12314045e+00
2.39451453e-01 9.01627004e-01 9.82604504e-01 -6.32587731e-01
-1.59735775e+00 -5.22256255e-01 7.81849146e-01 -5.20487607e-01
3.14625561e-01 2.57373244e-01 -6.91690922e-01 5.21248102e-01
6.06616795e-01 -6.15228526e-02 4.97590631e-01 -1.85202524e-01
-2.13165462e-01 -7.22950697e-02 -6.74553096e-01 9.84068155e-01
9.30697739e-01 -4.91236389e-01 -6.61478281e-01 2.33706683e-02
5.32943308e-01 -2.69496858e-01 -4.13557619e-01 2.84076661e-01
5.94590604e-01 -1.11822057e+00 1.26943481e+00 -4.74561840e-01
1.09852970e-01 -3.36165994e-01 1.62118331e-01 -9.81595635e-01
-5.36563575e-01 -6.90164804e-01 -6.86715722e-01 8.91588390e-01
-2.90396482e-01 -2.36426175e-01 5.77356696e-01 7.38836586e-01
-1.97631240e-01 -7.44463980e-01 -3.79155666e-01 -5.94199717e-01
-5.11592567e-01 -7.74236381e-01 2.15444937e-02 3.23575795e-01
-1.17353417e-01 5.64050019e-01 -5.53240955e-01 -2.25660756e-01
9.23285902e-01 1.19506456e-02 9.37376916e-01 -1.40332639e+00
-7.46091753e-02 -6.71342909e-01 -3.25106621e-01 -1.40718937e+00
-3.12887907e-01 -3.29818279e-01 -9.21833888e-03 -1.98017836e+00
3.02945763e-01 1.99619591e-01 -5.68718091e-02 3.26815486e-01
-2.79453725e-01 3.04517090e-01 4.79646116e-01 2.15059221e-01
-5.76575100e-01 2.43643045e-01 1.61055863e+00 -1.37587547e-01
-9.96548831e-02 2.93565877e-02 -1.19028282e+00 9.10597742e-01
6.13104939e-01 -8.43928084e-02 -9.65743303e-01 -2.85692722e-01
2.69396096e-01 -9.12667066e-02 5.09721696e-01 -6.09424114e-01
6.11942649e-01 -7.02810049e-01 2.79612184e-01 -6.88355744e-01
3.82650882e-01 -7.74701953e-01 -7.17133582e-02 2.39836127e-01
-1.85870528e-01 2.66434669e-01 2.57140368e-01 5.12552440e-01
-2.04984233e-01 -1.78469747e-01 8.85982573e-01 -3.94495249e-01
-1.81585777e+00 2.72837400e-01 -6.91587806e-01 -2.13003736e-02
1.29024875e+00 -7.58365810e-01 -4.64544773e-01 -3.74437571e-01
-4.06640887e-01 9.59937274e-02 5.69555938e-01 7.09141314e-01
1.36416197e+00 -1.08783901e+00 -3.41280878e-01 2.42388889e-01
5.27458310e-01 -3.14012855e-01 5.74523568e-01 7.92219818e-01
-4.13306743e-01 5.68848431e-01 -4.54777271e-01 -6.99424565e-01
-1.78159332e+00 9.58646297e-01 -2.74508726e-02 1.19874582e-01
-9.77559328e-01 8.46676946e-01 4.23441201e-01 6.60352170e-01
7.29876697e-01 -1.45229593e-01 -5.26984334e-01 -2.42112234e-01
1.08859217e+00 6.23558462e-01 -3.02927017e-01 -3.80596101e-01
-3.17404389e-01 9.30255413e-01 -2.93347269e-01 -2.15277523e-01
8.98680270e-01 -3.11864704e-01 -7.98503086e-02 3.71964663e-01
3.68984520e-01 -2.77309358e-01 -1.45241034e+00 6.56952849e-03
-6.46342114e-02 -6.17841840e-01 6.02197088e-02 -9.03093696e-01
-6.86166525e-01 1.09917080e+00 5.85980535e-01 1.20339558e-01
1.40267694e+00 3.21316630e-01 1.84265524e-01 -1.76005270e-02
3.99645835e-01 -1.05017591e+00 6.24423921e-01 6.99981272e-01
1.31634820e+00 -1.38219178e+00 3.96113563e-03 -2.39469171e-01
-1.05484581e+00 1.20824099e+00 8.71876001e-01 4.84022088e-02
6.40772104e-01 4.85349983e-01 7.22973049e-01 -6.47882938e-01
-7.67255425e-01 -4.25936788e-01 5.95919311e-01 1.32538414e+00
3.42020005e-01 -1.66475043e-01 -3.35255921e-01 4.31323141e-01
2.42390469e-01 4.20825094e-01 4.99845445e-01 1.01983619e+00
-6.89409375e-01 -1.06976056e+00 -5.03521621e-01 2.90556520e-01
-1.99211277e-02 -2.47249484e-01 -5.18990099e-01 4.57229257e-01
-1.69542342e-01 1.22656071e+00 -2.18927070e-01 -3.09985191e-01
3.16733152e-01 -2.37438813e-01 7.37387300e-01 -5.89016497e-01
-4.67455953e-01 -1.71034243e-02 -8.66012201e-02 -5.97992241e-01
-4.39570814e-01 -3.60957712e-01 -1.07490885e+00 -2.50660598e-01
-1.68813374e-02 -3.74651343e-01 5.44858575e-01 6.68987751e-01
3.03258002e-01 5.67882895e-01 8.76942202e-02 -8.54527652e-01
-3.11018944e-01 -7.98094511e-01 -4.77993369e-01 2.90086746e-01
3.56189698e-01 -6.95276141e-01 -3.24350856e-02 6.50427818e-01] | [10.390093803405762, 1.626836895942688] |
2991abdd-7afb-41ec-8a00-dfabc3cfb2f7 | fillers-in-spoken-language-understanding | 2301.10761 | null | https://arxiv.org/abs/2301.10761v4 | https://arxiv.org/pdf/2301.10761v4.pdf | Fillers in Spoken Language Understanding: Computational and Psycholinguistic Perspectives | Disfluencies (i.e. interruptions in the regular flow of speech), are ubiquitous to spoken discourse. Fillers ("uh", "um") are disfluencies that occur the most frequently compared to other kinds of disfluencies. Yet, to the best of our knowledge, there isn't a resource that brings together the research perspectives influencing Spoken Language Understanding (SLU) on these speech events. This aim of this article is to survey a breadth of perspectives in a holistic way; i.e. from considering underlying (psycho)linguistic theory, to their annotation and consideration in Automatic Speech Recognition (ASR) and SLU systems, to lastly, their study from a generation standpoint. This article aims to present the perspectives in an approachable way to the SLU and Conversational AI community, and discuss moving forward, what we believe are the trends and challenges in each area. | ['Ioana Vasilescu', 'Chloé Clavel', 'Tanvi Dinkar'] | 2023-01-25 | null | null | null | null | ['spoken-language-understanding', 'spoken-language-understanding'] | ['natural-language-processing', 'speech'] | [ 3.52000177e-01 4.33648348e-01 -3.72970134e-01 -2.86747575e-01
-5.59849501e-01 -8.78509879e-01 5.66532254e-01 1.14868768e-01
-6.16935901e-02 7.29215801e-01 9.29700434e-01 -6.70665681e-01
1.38164926e-02 -1.77295774e-01 -3.99504304e-01 -2.23528251e-01
4.23778445e-02 2.33273461e-01 -2.30998501e-01 -5.39074600e-01
3.56184185e-01 2.16599613e-01 -1.78263128e+00 2.95441777e-01
8.79637122e-01 2.69756645e-01 4.61742640e-01 4.28647608e-01
-3.61921400e-01 1.16289425e+00 -1.02216280e+00 7.83999488e-02
-7.09356070e-01 -7.01400518e-01 -1.38512528e+00 3.22257787e-01
1.38300449e-01 -1.94666117e-01 -1.98831305e-01 7.54059255e-01
3.27377439e-01 4.71676558e-01 2.63750046e-01 -6.75795436e-01
-1.02327967e+00 1.01068997e+00 3.11127931e-01 8.07197392e-01
1.22849739e+00 -4.48249094e-02 8.31940770e-01 -7.45835364e-01
9.70852077e-01 1.38852763e+00 9.33384001e-02 9.91540253e-01
-8.36960495e-01 -1.71996444e-01 6.18124843e-01 1.18152454e-01
-1.15155697e+00 -1.02409959e+00 5.46935856e-01 -5.57356775e-01
1.68230474e+00 5.46854258e-01 5.46785653e-01 1.51507211e+00
-1.68721884e-01 1.00750589e+00 8.88549566e-01 -8.08127105e-01
5.60203269e-02 2.95938641e-01 6.12581670e-01 -2.43031252e-02
-4.23914522e-01 8.47254917e-02 -9.02004600e-01 3.33500445e-01
3.21263582e-01 -4.60397810e-01 -7.72965133e-01 8.25583816e-01
-1.17139184e+00 6.01494312e-01 -2.77077228e-01 1.21715009e+00
-1.45055115e-01 -3.97582114e-01 4.99512255e-01 6.04096174e-01
6.84736907e-01 2.81355292e-01 -2.76771903e-01 -8.30711305e-01
-5.08708119e-01 -7.39273578e-02 1.01179636e+00 9.03372228e-01
3.38483006e-01 3.76951903e-01 -1.32965833e-01 1.17969978e+00
4.40721691e-01 4.56277013e-01 6.41737640e-01 -6.58054590e-01
3.52663606e-01 1.40759766e-01 -4.62781638e-02 -6.66390359e-01
-2.68444479e-01 4.82245162e-02 -1.27429552e-02 -3.77225608e-01
3.23981285e-01 -1.94558159e-01 -7.13944197e-01 1.89315093e+00
-1.18806986e-02 -1.56534851e-01 2.24064291e-01 7.45416939e-01
1.17610168e+00 1.02102447e+00 3.52637589e-01 -1.03307474e+00
1.43391955e+00 -7.17693150e-01 -1.51308477e+00 -6.62454665e-01
8.54464293e-01 -1.10190809e+00 1.62611115e+00 2.60180473e-01
-1.22326839e+00 -3.25338572e-01 -8.90107870e-01 -3.69132787e-01
-5.27235448e-01 -1.46075860e-01 5.06782293e-01 9.63657737e-01
-1.15679598e+00 1.55250698e-01 -7.37868607e-01 -7.01206148e-01
-2.38647833e-01 -9.17439312e-02 -6.11764863e-02 1.80309549e-01
-1.60596788e+00 1.35036492e+00 2.38333344e-01 4.69066873e-02
-3.26136708e-01 -5.36584198e-01 -1.03147149e+00 -3.89074713e-01
6.13309443e-01 7.53957927e-02 1.71725595e+00 -1.16380227e+00
-1.72017610e+00 1.27119458e+00 -7.74731159e-01 -1.63039893e-01
-1.52044892e-01 -3.77802461e-01 -8.77239287e-01 -1.04239032e-01
-2.05311850e-01 1.52980939e-01 1.05480932e-01 -1.06311476e+00
-6.16277933e-01 -2.92699665e-01 1.52382571e-02 4.13199067e-01
-2.66144816e-02 8.16485763e-01 1.78571641e-01 -6.99373662e-01
1.28809452e-01 -5.94817102e-01 4.96565133e-01 -9.14801240e-01
-2.26345107e-01 -9.80734229e-01 7.88536549e-01 -8.16718459e-01
2.06915545e+00 -2.06654382e+00 1.96729988e-01 -3.02782089e-01
-3.32742110e-02 6.36187732e-01 3.53774786e-01 1.09185874e+00
-2.27484092e-01 3.14624071e-01 -1.41112462e-01 -2.69560695e-01
9.24264360e-03 5.75868964e-01 -6.10537350e-01 3.41566652e-01
1.89219043e-02 9.68450248e-01 -1.04220223e+00 1.14189617e-01
5.56297779e-01 4.93914932e-01 -3.51851508e-02 1.78776488e-01
-3.22762758e-01 6.77260220e-01 -1.37740701e-01 7.18978226e-01
9.62944478e-02 3.18314344e-01 2.21419483e-01 3.94136250e-01
-1.03070545e+00 1.31611991e+00 -6.18262291e-01 1.51587868e+00
-4.55435932e-01 9.03448045e-01 -2.61024642e-03 -7.71698833e-01
8.63633692e-01 9.95876372e-01 -2.11748272e-01 -5.25047779e-01
1.42287076e-01 5.24264455e-01 4.11680907e-01 -8.05433393e-01
5.23777127e-01 -2.02242151e-01 -2.38911361e-02 4.66544658e-01
9.92889702e-02 -4.51600067e-02 3.07109594e-01 -8.40615779e-02
7.25029230e-01 -2.02201515e-01 8.19850802e-01 -4.06266481e-01
7.04292059e-01 -1.13900684e-01 1.39918536e-01 6.05905116e-01
-4.17466283e-01 3.34521621e-01 4.27846670e-01 -2.87776083e-01
-5.95465481e-01 -8.93127799e-01 -3.55816901e-01 1.12289643e+00
-3.08789939e-01 -5.00483096e-01 -1.09784710e+00 -1.11184172e-01
-5.60492337e-01 1.46892786e+00 -2.54194349e-01 -2.57320199e-02
-7.15341389e-01 -2.82705694e-01 5.63005209e-01 2.16032892e-01
-9.83925685e-02 -1.81497443e+00 -2.14751825e-01 3.77159238e-01
-5.30822158e-01 -1.17541623e+00 -5.72602689e-01 -1.19045742e-01
-3.06019276e-01 -6.13308251e-01 -2.48830140e-01 -9.47006464e-01
1.30367815e-01 2.71786034e-01 1.04826522e+00 1.10645778e-01
2.67966129e-02 6.84034348e-01 -8.98705125e-01 -3.64522129e-01
-9.90687191e-01 -2.04936400e-01 2.21638769e-01 -4.02772486e-01
8.64998937e-01 -5.50375581e-01 5.22381552e-02 7.96691999e-02
-8.53613436e-01 -3.48357081e-01 3.34959887e-02 3.90554458e-01
2.63570279e-01 -5.66653192e-01 8.03759038e-01 -1.05492520e+00
1.10142231e+00 -6.66913271e-01 2.18611971e-01 3.54332060e-01
-3.18248302e-01 -6.70260787e-01 3.55663180e-01 -3.56643349e-01
-1.22735190e+00 -5.67546964e-01 -6.90015972e-01 -2.85583409e-03
-7.43885159e-01 7.02062786e-01 -3.78591299e-01 2.88160235e-01
7.21773207e-01 4.08463597e-01 3.28665711e-02 -4.87083763e-01
3.70892018e-01 1.22741306e+00 4.13511693e-01 -4.56817299e-01
2.14644410e-02 -7.78785124e-02 -8.50413024e-01 -1.76615298e+00
-8.11180592e-01 -5.51145017e-01 -5.04069269e-01 -5.84070504e-01
9.22853351e-01 -5.61699152e-01 -6.14370346e-01 4.67493206e-01
-1.44885588e+00 -2.95312524e-01 -2.65228182e-01 5.59252381e-01
-7.07164288e-01 4.74058211e-01 -8.92524719e-01 -1.34822488e+00
-7.83416182e-02 -1.16252542e+00 7.11943567e-01 2.39543751e-01
-9.69409585e-01 -1.18411291e+00 -6.70320317e-02 5.36859989e-01
2.87589997e-01 -5.53549118e-02 7.47715831e-01 -7.93554544e-01
-8.03553462e-02 2.82271624e-01 4.39673394e-01 4.20309752e-01
5.35164118e-01 5.32638095e-02 -1.25569248e+00 1.09329909e-01
5.99260747e-01 -3.59543592e-01 2.00350940e-01 4.69446808e-01
3.98881823e-01 -6.26946986e-01 -1.13606542e-01 -8.50979909e-02
7.87499368e-01 1.10931432e+00 6.77398026e-01 -1.06936775e-01
3.82642925e-01 9.49269056e-01 5.45207024e-01 2.75335610e-01
3.71209413e-01 5.81161022e-01 -2.05044627e-01 5.37055373e-01
-5.46206057e-01 -3.81552815e-01 7.87146151e-01 1.49242389e+00
-3.63413915e-02 -7.70239711e-01 -1.16885114e+00 5.57830393e-01
-1.61959314e+00 -9.72862661e-01 -2.44487166e-01 2.12674832e+00
8.16824138e-01 -9.22360197e-02 -2.07196310e-01 1.11335568e-01
9.16497350e-01 4.48477805e-01 -4.10645939e-02 -8.69304717e-01
-3.81235033e-01 2.35818848e-02 -3.60859543e-01 1.10337210e+00
-7.65367925e-01 1.52113223e+00 7.03330660e+00 8.14360440e-01
-1.06327868e+00 2.00260416e-01 4.23097342e-01 1.75191507e-01
-6.49278104e-01 -6.61807507e-02 -7.93806732e-01 4.46042210e-01
1.36564386e+00 -2.97654867e-01 8.50915909e-01 4.64863271e-01
6.28803372e-01 -2.31422216e-01 -1.08255136e+00 8.32379639e-01
4.16757613e-01 -9.96634960e-01 -8.79965946e-02 -2.72844881e-01
1.25158682e-01 -4.68587093e-02 -3.03475056e-02 1.99279308e-01
-6.21918812e-02 -1.13041663e+00 8.46528411e-01 1.67863503e-01
5.38233042e-01 -6.97801411e-01 3.77743542e-01 4.26468730e-01
-7.56697476e-01 3.10143501e-01 -7.96784386e-02 -4.99374211e-01
7.86994338e-01 2.29515716e-01 -7.12004960e-01 3.05370569e-01
5.09515107e-01 5.65638483e-01 2.32360512e-01 2.59385973e-01
-4.93819654e-01 1.01379919e+00 -2.04270080e-01 -3.84800404e-01
2.21724480e-01 -1.73895061e-01 1.13677955e+00 1.40723133e+00
1.37422353e-01 6.00065649e-01 1.28344595e-01 6.94400251e-01
3.50631714e-01 4.49204147e-01 -8.90241742e-01 -5.91318786e-01
9.32541549e-01 5.99716187e-01 -7.23216176e-01 -4.50674333e-02
-7.09054708e-01 9.17149067e-01 2.65853524e-01 3.85195494e-01
-3.10601175e-01 6.46555349e-02 9.48873699e-01 6.56336695e-02
-3.07473063e-01 -3.00730020e-01 -9.36718211e-02 -9.61674869e-01
-2.28918251e-03 -1.07865822e+00 1.46514073e-01 -5.67972064e-01
-1.23888564e+00 9.41330135e-01 1.31028742e-01 -8.13639998e-01
-6.20504081e-01 -3.92971069e-01 -4.89054412e-01 8.46479833e-01
-1.21705902e+00 -9.62151051e-01 3.51737142e-01 2.48085514e-01
1.01401162e+00 1.32057399e-01 1.13632703e+00 2.78747112e-01
-5.96911371e-01 4.16838437e-01 -2.72817641e-01 -2.11742893e-01
4.04617071e-01 -9.06210601e-01 3.84096771e-01 7.59392679e-01
1.94063500e-01 1.03662193e+00 9.52467978e-01 -7.08732426e-01
-1.24100637e+00 -3.53274733e-01 1.72194290e+00 -5.72781742e-01
8.22712481e-01 -2.50056744e-01 -1.12983882e+00 1.12977457e+00
7.29476094e-01 -6.98963881e-01 9.80468273e-01 2.68820763e-01
1.74054757e-01 6.13498330e-01 -8.36695194e-01 8.26620638e-01
1.30718923e+00 -8.04514170e-01 -1.11556888e+00 5.09628713e-01
1.14360237e+00 -6.82358146e-01 -7.60830283e-01 1.21658538e-02
1.96521804e-01 -1.04782188e+00 6.33499503e-01 -5.38265288e-01
1.14377886e-01 -1.11671157e-01 -1.43278241e-01 -1.36042070e+00
-4.14451919e-02 -1.16567981e+00 3.65909748e-02 1.65676880e+00
4.23328489e-01 -9.08188522e-01 -4.77024540e-03 5.75040162e-01
-1.01063156e+00 -4.81676847e-01 -1.30535066e+00 -5.73137760e-01
1.41806915e-01 -8.37112427e-01 1.94369823e-01 1.08610308e+00
8.86640787e-01 4.75939810e-01 -2.27339387e-01 -1.71567976e-01
-1.45754829e-01 -4.52177286e-01 -3.42251770e-02 -9.60322618e-01
1.05905510e-01 -5.29235244e-01 -2.08762512e-01 -1.15468526e+00
3.99573714e-01 -7.98103750e-01 1.54111415e-01 -1.19850516e+00
-5.27290523e-01 1.42100915e-01 2.70714492e-01 3.11352283e-01
7.72698447e-02 -2.71311760e-01 1.35198057e-01 9.95114818e-02
-3.11672147e-02 4.61691588e-01 1.16456616e+00 4.26845014e-01
-7.21211076e-01 -5.02555855e-02 -8.28692019e-01 8.55039537e-01
9.38735485e-01 -1.03943422e-01 -7.21798301e-01 -4.98000264e-01
-1.30961791e-01 2.78923094e-01 -2.35181034e-01 -5.56870222e-01
1.88800111e-01 -3.12752396e-01 -5.58219373e-01 -3.80854279e-01
1.63301021e-01 -2.17390403e-01 -1.98100656e-02 1.16368942e-01
-2.66105324e-01 1.30153717e-02 4.04275864e-01 -1.02827668e-01
-5.53138793e-01 -5.22432804e-01 5.62997937e-01 -2.90394187e-01
-8.29201460e-01 -2.67355472e-01 -1.32738066e+00 2.91112840e-01
1.02069867e+00 -4.31242555e-01 -3.81659150e-01 -6.07045412e-01
-9.31870878e-01 7.29991570e-02 -3.80135775e-02 8.84589314e-01
5.07688940e-01 -8.57590556e-01 -3.94713193e-01 1.38721034e-01
1.63880195e-02 -2.31825873e-01 5.45573652e-01 6.60251319e-01
-3.33368778e-01 1.06452954e+00 2.74078965e-01 -1.10257395e-01
-1.16129947e+00 4.67692167e-01 1.44330055e-01 3.07529628e-01
-5.66069722e-01 8.88394773e-01 1.81146562e-01 -3.07838291e-01
4.79391605e-01 -3.49933714e-01 -6.67153835e-01 3.62469226e-01
9.06711221e-01 4.43957835e-01 1.06176667e-01 -1.18946147e+00
-5.08269727e-01 9.12717357e-02 -1.39988452e-01 -3.77610981e-01
7.59809256e-01 -7.47980237e-01 -4.91510868e-01 1.31594753e+00
8.85341346e-01 1.95208594e-01 -5.43937624e-01 6.12565614e-02
3.76053095e-01 -1.54599324e-01 -5.65120317e-02 -8.77094150e-01
-3.96973640e-01 6.55611575e-01 1.26868799e-01 7.20335245e-01
7.54364669e-01 5.63016176e-01 7.67678201e-01 1.77003041e-01
2.30146684e-02 -1.30260372e+00 -3.77990156e-01 9.00200605e-01
1.26584208e+00 -7.08535612e-01 -8.17010343e-01 -9.93141234e-01
-8.54203582e-01 1.08375621e+00 5.32560766e-01 2.56210744e-01
7.81937003e-01 4.26705956e-01 4.78565514e-01 -7.49218762e-02
-8.38986278e-01 -4.65205520e-01 5.72424233e-02 8.03916693e-01
1.27391839e+00 2.03540847e-01 -1.18057394e+00 5.46938062e-01
-6.14254832e-01 -4.68023345e-02 5.93418956e-01 9.02436554e-01
-7.89911568e-01 -1.33378506e+00 -3.67836744e-01 9.39013883e-02
-5.33469439e-01 -2.96035409e-01 -6.02802455e-01 7.43221581e-01
7.45015815e-02 1.65007555e+00 2.42183775e-01 -1.86701044e-01
4.72374290e-01 4.83990669e-01 2.74441183e-01 -9.49461162e-01
-6.68497860e-01 2.68999338e-01 5.30041754e-01 -3.99660826e-01
-5.89363039e-01 -1.06812000e+00 -1.20860410e+00 -2.88915873e-01
-1.65781811e-01 1.81260958e-01 3.10342044e-01 1.29914296e+00
-1.00125976e-01 5.48861325e-01 2.71298736e-01 -4.74896312e-01
-1.29904568e-01 -1.25050890e+00 -7.00447440e-01 6.14646226e-02
3.54130417e-01 -4.63886052e-01 -6.30553186e-01 3.25824623e-03] | [14.299614906311035, 6.981368541717529] |
0206a02c-1e92-4aab-8ae2-5801e4f2b7c9 | conservative-progressive-collaborative | 2211.16701 | null | https://arxiv.org/abs/2211.16701v2 | https://arxiv.org/pdf/2211.16701v2.pdf | Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation | Pseudo supervision is regarded as the core idea in semi-supervised learning for semantic segmentation, and there is always a tradeoff between utilizing only the high-quality pseudo labels and leveraging all the pseudo labels. Addressing that, we propose a novel learning approach, called Conservative-Progressive Collaborative Learning (CPCL), among which two predictive networks are trained in parallel, and the pseudo supervision is implemented based on both the agreement and disagreement of the two predictions. One network seeks common ground via intersection supervision and is supervised by the high-quality labels to ensure a more reliable supervision, while the other network reserves differences via union supervision and is supervised by all the pseudo labels to keep exploring with curiosity. Thus, the collaboration of conservative evolution and progressive exploration can be achieved. To reduce the influences of the suspicious pseudo labels, the loss is dynamic re-weighted according to the prediction confidence. Extensive experiments demonstrate that CPCL achieves state-of-the-art performance for semi-supervised semantic segmentation. | ['Fei-Yue Wang', 'Mingli Song', 'Yisheng Lv', 'Zunlei Feng', 'Fenghua Zhu', 'Siqi Fan'] | 2022-11-30 | null | null | null | null | ['semi-supervised-semantic-segmentation'] | ['computer-vision'] | [ 1.57201529e-01 5.88088691e-01 -6.21474922e-01 -6.03613555e-01
-6.19351089e-01 -7.87465125e-02 3.36841822e-01 1.97056547e-01
-4.59626317e-01 5.94111562e-01 -6.50194660e-03 1.90340914e-02
-2.90918231e-01 -6.17561817e-01 -3.44683826e-01 -9.70860779e-01
2.38333106e-01 6.33012414e-01 7.65557766e-01 2.56404206e-02
2.39455685e-01 -1.51106745e-01 -1.43345773e+00 1.15779936e-01
1.55774093e+00 1.25153327e+00 1.58842117e-01 -1.86538175e-01
-3.89094055e-01 7.78509796e-01 -1.45326704e-01 -3.54841888e-01
2.78705984e-01 -3.99337202e-01 -8.84658098e-01 1.33190945e-01
-3.00513744e-01 1.05389290e-01 2.39369959e-01 1.35960448e+00
1.50428548e-01 1.16650142e-01 2.60528177e-01 -1.20110047e+00
-1.10896572e-01 1.03578818e+00 -6.93878174e-01 -1.27965927e-01
-6.90689981e-02 -2.50356216e-02 1.25670457e+00 -4.39577043e-01
4.45375770e-01 1.07876432e+00 4.37864959e-01 3.19917262e-01
-1.18024170e+00 -9.03061986e-01 7.36161411e-01 1.82513610e-01
-1.19496346e+00 -1.68111354e-01 9.95249510e-01 -2.71049231e-01
1.21819042e-01 -7.94252157e-02 6.38149917e-01 7.70015776e-01
-2.24178255e-01 9.27554667e-01 1.08869839e+00 -3.80894303e-01
3.13192040e-01 5.75378716e-01 4.53443110e-01 8.72661471e-01
-1.33132925e-02 -4.32584621e-02 -7.16242731e-01 -2.94185709e-02
3.74106258e-01 2.53133513e-02 -2.83879489e-01 -6.37838542e-01
-9.29643333e-01 7.54124463e-01 4.22401845e-01 2.83215135e-01
-2.19387501e-01 -4.06170934e-01 3.98394555e-01 2.81006902e-01
6.25550449e-01 2.87049294e-01 -6.29233479e-01 -1.38393015e-01
-1.10310233e+00 -3.67363125e-01 5.04573703e-01 7.51438439e-01
1.18462813e+00 -3.37410927e-01 3.14699411e-02 9.15624440e-01
6.94219232e-01 -1.33614480e-01 6.85767233e-01 -1.02522624e+00
3.32621127e-01 1.24760199e+00 -1.21049928e-02 -7.45937943e-01
-3.30776372e-03 -6.85987711e-01 -6.24089599e-01 2.81315267e-01
2.80047536e-01 -1.73555717e-01 -8.81130576e-01 1.78189313e+00
6.27155542e-01 1.45359188e-01 -1.96638212e-01 7.93668866e-01
5.21791339e-01 4.49955344e-01 1.51389435e-01 -5.35170376e-01
7.38013208e-01 -1.45303416e+00 -6.42392397e-01 -2.40131572e-01
5.94402432e-01 -3.96954089e-01 8.93128812e-01 3.09888482e-01
-7.32104480e-01 -7.01741338e-01 -1.11677039e+00 1.88425720e-01
-3.27614434e-02 1.29927635e-01 3.72152358e-01 3.83805245e-01
-6.59097314e-01 1.05238044e+00 -9.08065438e-01 3.45991254e-02
5.05672991e-01 2.93716669e-01 -4.12445795e-03 2.60013223e-01
-1.24242902e+00 4.14631307e-01 6.70130908e-01 1.95535511e-01
-6.36036575e-01 -3.99451941e-01 -5.52693188e-01 -2.36122832e-02
7.40883708e-01 -1.14934221e-01 8.87760460e-01 -1.27012193e+00
-1.49385941e+00 8.43180299e-01 1.15622282e-01 -2.82669961e-01
1.03140962e+00 -1.31670088e-01 -3.54499400e-01 -8.98820981e-02
3.50625515e-01 6.95330918e-01 8.44937980e-01 -1.41937160e+00
-1.00143087e+00 -4.47575092e-01 -5.30545563e-02 4.94020015e-01
-6.20591879e-01 -2.89149284e-01 -6.18428648e-01 -1.82190835e-01
6.77006483e-01 -9.27479208e-01 -3.18999827e-01 1.47960275e-01
-4.40496325e-01 -4.78595912e-01 8.46138656e-01 -4.13198262e-01
1.29604423e+00 -2.08645296e+00 2.89322197e-01 5.70709586e-01
2.49213502e-01 3.30977082e-01 1.11435339e-01 -7.17106089e-02
9.22077522e-02 2.52000503e-02 -4.00847584e-01 -6.16501808e-01
-3.96832913e-01 3.44716370e-01 -1.88620239e-01 1.07465141e-01
-8.63085538e-02 5.30396879e-01 -1.17503643e+00 -9.77249861e-01
-1.06950432e-01 2.82271802e-02 -2.08672792e-01 2.37054393e-01
-3.08701456e-01 6.65327966e-01 -9.36421216e-01 5.90355575e-01
4.79878604e-01 -6.57890737e-01 4.58177269e-01 -2.43383393e-01
-6.01431020e-02 1.33872911e-01 -1.31806219e+00 1.70767653e+00
-3.59111540e-02 -9.40954089e-02 2.31776863e-01 -1.04566705e+00
1.28785086e+00 2.72280388e-02 4.67425853e-01 -3.91527653e-01
5.36754504e-02 3.27574044e-01 -2.16504470e-01 -2.42309034e-01
8.64098519e-02 2.24516124e-01 2.88204432e-01 7.22916365e-01
-5.44672385e-02 1.73986377e-03 3.34362872e-02 2.85375625e-01
6.02153897e-01 5.96910834e-01 -3.27247009e-02 -2.35741273e-01
7.40493000e-01 7.88863897e-02 1.17132747e+00 5.75337410e-01
-5.77888370e-01 2.77405232e-01 5.90500236e-01 -1.45423785e-01
-5.27675331e-01 -9.03622746e-01 -4.49024551e-02 1.23485875e+00
6.20262504e-01 -4.13203746e-01 -6.25093937e-01 -1.39617503e+00
-1.01992294e-01 6.26381755e-01 -7.29088426e-01 -4.12008077e-01
-2.99008310e-01 -5.72929740e-01 5.86059019e-02 4.64899451e-01
9.39823687e-01 -1.04033661e+00 -2.76917070e-01 1.50318593e-01
-1.44030601e-01 -5.75024605e-01 -3.07297617e-01 5.05091131e-01
-9.83233094e-01 -1.12204349e+00 -4.36923772e-01 -6.69264317e-01
8.58225465e-01 2.43774220e-01 7.70277500e-01 2.87073374e-01
4.55984682e-01 -1.78893358e-01 -6.01453483e-01 -1.42928928e-01
-4.17624533e-01 1.99549437e-01 -8.77717733e-02 2.06807002e-01
2.12200493e-01 -7.02867389e-01 -3.77487957e-01 6.89029276e-01
-5.34415901e-01 2.82801747e-01 4.73637640e-01 9.75329995e-01
9.39455092e-01 3.36299598e-01 5.61981738e-01 -1.15055430e+00
2.28957638e-01 -4.16427165e-01 -5.02033174e-01 4.79342550e-01
-1.17556477e+00 8.42549652e-03 6.27697647e-01 -3.95921856e-01
-1.35231698e+00 -2.30902806e-02 5.65474220e-02 -5.72299898e-01
1.51127502e-01 5.12986541e-01 -1.90205336e-01 -9.19554830e-02
3.23118925e-01 1.29725724e-01 2.66205948e-02 -5.40875494e-01
1.65060118e-01 5.93338668e-01 2.09638283e-01 -4.34527636e-01
6.97079837e-01 4.92455244e-01 -3.62604499e-01 -1.03980996e-01
-1.56113636e+00 -4.65678185e-01 -7.81260610e-01 -3.76038224e-01
6.72243834e-01 -7.92981803e-01 -2.34997466e-01 5.59112608e-01
-4.86678898e-01 -2.65647709e-01 -4.87662375e-01 4.13961798e-01
-2.82613099e-01 4.26600546e-01 -4.86297458e-01 -8.20230246e-01
-3.83833528e-01 -1.24023807e+00 6.86188281e-01 6.64221287e-01
-2.58983090e-03 -7.81634927e-01 -1.60284653e-01 6.93332553e-01
1.32841289e-01 -6.90356046e-02 7.14530110e-01 -1.06151378e+00
-5.70380151e-01 -1.95064936e-02 -3.88442487e-01 4.96498287e-01
4.04285192e-01 7.08297938e-02 -8.83213043e-01 -2.45756760e-01
1.93140924e-01 -7.09391236e-01 1.08861566e+00 9.73795578e-02
1.17516983e+00 1.01380087e-01 -5.39972663e-01 4.68854129e-01
1.08732188e+00 9.85748842e-02 1.74336344e-01 4.15554941e-01
7.96254992e-01 8.27475250e-01 1.20205891e+00 2.73785025e-01
4.66089219e-01 3.39869976e-01 4.22129899e-01 -2.87218764e-02
2.37625882e-01 -5.54906309e-01 8.44491571e-02 8.74534786e-01
5.19450977e-02 1.94208115e-01 -7.41117418e-01 2.75437981e-01
-2.21318269e+00 -5.07611811e-01 1.76267192e-01 2.26656532e+00
1.08286762e+00 7.19306350e-01 6.41857162e-02 2.04709351e-01
1.02227676e+00 3.95238131e-01 -8.98803532e-01 7.20738098e-02
1.00953162e-01 -4.21117902e-01 2.43259981e-01 2.60414034e-01
-9.90687132e-01 1.03670454e+00 5.18795872e+00 1.22111011e+00
-1.06056547e+00 1.85833454e-01 1.07835317e+00 1.00430198e-01
-2.63588369e-01 3.24975640e-01 -7.23212063e-01 8.64065826e-01
3.53461653e-01 1.57858685e-01 1.11387111e-01 1.14197004e+00
4.92481999e-02 -4.50423956e-01 -7.77845919e-01 4.46957529e-01
-1.00781180e-01 -1.06440926e+00 -1.14223108e-01 -2.11646572e-01
9.08647716e-01 9.45558175e-02 -2.60217220e-01 1.58508316e-01
5.37835121e-01 -3.53354692e-01 6.98163688e-01 4.86381650e-01
4.56871539e-01 -7.39836872e-01 7.70487547e-01 8.01504493e-01
-1.12712991e+00 -2.21641079e-01 -1.00646481e-01 4.29104149e-01
2.10446924e-01 8.30029130e-01 -3.55695397e-01 7.58557200e-01
8.24316740e-01 9.54169810e-01 -3.99293572e-01 7.02421963e-01
-6.66677952e-01 7.38066852e-01 -2.26046249e-01 1.46322668e-01
2.71655887e-01 -7.11230576e-01 4.98241007e-01 6.29582405e-01
-2.01780811e-01 -2.04204381e-01 6.84278011e-01 8.14753711e-01
4.73336540e-02 1.19362354e-01 1.63408756e-01 5.20218983e-02
6.22177958e-01 1.22835076e+00 -9.17403638e-01 -3.97683442e-01
-1.92570746e-01 7.88330019e-01 6.13108099e-01 -6.78335223e-03
-6.91548884e-01 -3.89840193e-02 1.63825735e-01 -8.84492174e-02
2.09099084e-01 1.19633064e-01 -4.20643032e-01 -9.63805974e-01
7.54592568e-02 -4.10267502e-01 5.74681342e-01 -4.85916704e-01
-1.28379571e+00 5.85645914e-01 -1.50144026e-01 -1.27089715e+00
1.47849694e-01 4.73212544e-03 -8.03006589e-01 7.56138861e-01
-1.94330382e+00 -1.23549163e+00 -4.27757442e-01 3.13825995e-01
4.18054163e-01 -8.35984200e-02 4.71202135e-01 6.55519813e-02
-8.40799332e-01 4.88367051e-01 8.58252272e-02 -1.29120111e-01
8.06466579e-01 -1.17068660e+00 -2.43239090e-01 5.35492003e-01
-1.06150106e-01 3.43339473e-01 4.65183049e-01 -9.51686978e-01
-5.26099145e-01 -9.99047458e-01 8.18395555e-01 2.68248320e-01
5.50915241e-01 5.93672693e-02 -1.30585515e+00 4.27564114e-01
-3.82713675e-01 -1.95775088e-02 7.09907353e-01 3.04588288e-01
-3.35561424e-01 -3.34675312e-01 -1.14264190e+00 2.92485535e-01
1.05938578e+00 -1.56861708e-01 -6.23473108e-01 3.38168114e-01
9.90927815e-01 -1.77009642e-01 -7.47356474e-01 6.06728852e-01
3.09717447e-01 -1.20180595e+00 4.67010140e-01 -1.20352164e-01
4.13672745e-01 -5.37459314e-01 3.23240876e-01 -1.22029924e+00
-2.87889838e-01 -3.09234917e-01 1.01633579e-01 1.52297008e+00
5.79880357e-01 -7.00076222e-01 1.21103477e+00 4.25400078e-01
-3.66946124e-02 -1.20323050e+00 -7.41603196e-01 -5.89052022e-01
-2.60527343e-01 -9.59774181e-02 4.75278914e-01 1.19481957e+00
-1.41805140e-04 1.20529503e-01 -4.07750428e-01 -6.17355667e-02
5.83122373e-01 5.95109344e-01 4.06681925e-01 -1.44003582e+00
-3.03566098e-01 -2.77706921e-01 -1.79610215e-02 -1.13120186e+00
2.66177416e-01 -8.09773505e-01 1.47911981e-01 -1.19948041e+00
4.07980680e-01 -1.02047944e+00 -7.13425219e-01 6.39038444e-01
-5.41162491e-01 -1.29643604e-01 -8.45822096e-02 8.08037698e-01
-1.16760683e+00 8.52108002e-01 1.34092247e+00 7.48143420e-02
-6.24453306e-01 2.36700743e-01 -7.48633683e-01 9.33226943e-01
6.36603177e-01 -4.84376758e-01 -5.57868779e-01 -2.55543441e-01
-6.48402693e-06 -1.30711928e-01 -2.23097220e-01 -8.08377504e-01
6.49622858e-01 -3.47545385e-01 2.04030022e-01 -5.85188985e-01
7.94015601e-02 -7.10965276e-01 -1.26210541e-01 3.92616183e-01
-5.74664652e-01 -5.99696457e-01 -4.44815397e-01 7.86057889e-01
-3.32525402e-01 -2.13547409e-01 1.03468227e+00 -2.23251417e-01
-7.12958694e-01 4.13983345e-01 3.03820610e-01 -1.09207882e-02
1.00211608e+00 -4.36459094e-01 -1.18309043e-01 -1.43945977e-01
-8.12551618e-01 9.32518303e-01 5.12836933e-01 3.71855050e-01
3.22403729e-01 -9.64681506e-01 -4.70199466e-01 1.44070432e-01
1.90436974e-01 4.18151140e-01 2.48154804e-01 7.51775086e-01
1.80967510e-01 -1.54693471e-02 -2.26751100e-02 -7.54337490e-01
-1.14296186e+00 2.73534268e-01 1.84295386e-01 -6.59551442e-01
-4.70393687e-01 1.10787725e+00 -7.12610334e-02 -6.75448775e-01
4.74328190e-01 3.54466200e-01 -5.70821881e-01 3.76122475e-01
2.28534877e-01 3.23855639e-01 -1.21615425e-01 -4.19057101e-01
-1.72616944e-01 4.73268330e-01 -4.62884724e-01 1.22227520e-01
1.24209583e+00 -4.02015328e-01 -1.74037606e-01 7.24121988e-01
7.36859202e-01 -9.60993618e-02 -1.66360414e+00 -6.45887673e-01
1.24753520e-01 -4.68126774e-01 2.53867984e-01 -9.55591083e-01
-1.30609095e+00 3.79227519e-01 4.20847028e-01 7.38226548e-02
1.16418827e+00 1.76291987e-02 5.89553595e-01 1.63487196e-01
5.99235892e-01 -1.52088106e+00 2.53783017e-01 3.81608367e-01
3.04277718e-01 -1.39625716e+00 -8.80821887e-03 -7.71078050e-01
-9.26402211e-01 7.36123621e-01 1.02597725e+00 1.10284664e-01
7.42820680e-01 -4.05497029e-02 3.10816020e-02 2.96771377e-02
-7.20195293e-01 -4.50480133e-02 9.96639505e-02 1.49732679e-01
8.18222240e-02 -8.17702487e-02 -3.76098663e-01 6.52781725e-01
2.46440604e-01 -8.38289708e-02 -1.04496032e-01 9.99690890e-01
-6.15883052e-01 -1.29577160e+00 -3.11761927e-02 7.67737627e-01
-1.29661143e-01 2.17244327e-01 -2.74809420e-01 2.59935170e-01
4.68255728e-01 9.13622737e-01 -4.01538499e-02 -4.62696254e-01
-1.14833638e-01 -2.79502682e-02 -1.93455607e-01 -6.74325764e-01
-5.17515182e-01 2.15257555e-01 1.64278671e-02 -6.48044765e-01
-6.41033947e-01 -5.75230479e-01 -1.42711365e+00 1.19427495e-01
-9.76349175e-01 6.44421160e-01 5.47062695e-01 1.21432376e+00
2.33461231e-01 5.29888511e-01 1.09313548e+00 -4.30824101e-01
-8.12945724e-01 -7.66100883e-01 -7.46163428e-01 3.04874063e-01
-1.57906916e-02 -8.15380156e-01 -6.58883572e-01 -2.03552604e-01] | [9.376864433288574, 2.4009881019592285] |
2bc37e90-e308-4628-9ea9-859aba66f937 | bootstrapping-a-romanian-corpus-for-medical | null | null | https://aclanthology.org/R17-1066 | https://aclanthology.org/R17-1066.pdf | Bootstrapping a Romanian Corpus for Medical Named Entity Recognition | Named Entity Recognition (NER) is an important component of natural language processing (NLP), with applicability in biomedical domain, enabling knowledge-discovery from medical texts. Due to the fact that for the Romanian language there are only a few linguistic resources specific to the biomedical domain, it was created a sub-corpus specific to this domain. In this paper we present a newly developed Romanian sub-corpus for medical-domain NER, which is a valuable asset for the field of biomedical text processing. We provide a description of the sub-corpus, informative statistics about data-composition and we evaluate an automatic NER tool on the newly created resource. | ['Maria Mitrofan'] | 2017-09-01 | null | null | null | ranlp-2017-9 | ['medical-named-entity-recognition'] | ['natural-language-processing'] | [ 1.62011579e-01 4.96999741e-01 -8.58263448e-02 -2.94723094e-01
-5.32972038e-01 -2.90876478e-01 4.60832089e-01 8.47483754e-01
-1.22863984e+00 1.13425612e+00 5.93753517e-01 -3.87606949e-01
-3.74515682e-01 -8.06536257e-01 5.75067997e-02 -3.44930649e-01
-2.22363919e-02 8.91800404e-01 2.33028904e-01 -2.38283411e-01
1.69176996e-01 1.01137233e+00 -1.08009899e+00 2.88361937e-01
8.48801911e-01 1.34229481e-01 4.59792256e-01 4.51059461e-01
-6.59829319e-01 7.06210852e-01 -7.49911249e-01 -4.04058278e-01
-3.57466459e-01 -5.73007703e-01 -1.39120150e+00 -2.03044310e-01
-5.42253196e-01 4.06849742e-01 4.98062298e-02 8.66896749e-01
6.11233294e-01 2.13736758e-01 6.96869314e-01 -3.46187323e-01
-5.48659749e-02 6.99820638e-01 1.29178032e-01 2.21936211e-01
4.54892933e-01 -5.94027162e-01 8.05127144e-01 -5.99046171e-01
1.38602829e+00 7.53586411e-01 5.45539320e-01 7.97131121e-01
-7.61280417e-01 -2.01598540e-01 -5.67986846e-01 6.49921894e-02
-1.38526618e+00 -3.44355911e-01 3.24297041e-01 -3.72651160e-01
8.93512726e-01 1.23884752e-01 2.79730558e-01 8.62588406e-01
2.65573204e-01 5.31462610e-01 1.02454150e+00 -7.52532601e-01
3.30463380e-01 4.58439499e-01 2.75530875e-01 4.43966061e-01
4.75968033e-01 -2.09862739e-01 -1.76191926e-02 -2.74591506e-01
5.96852541e-01 -2.70296872e-01 -1.25934035e-01 1.33342594e-01
-1.22564733e+00 5.89135468e-01 -9.30153280e-02 1.58832550e+00
-6.83852673e-01 -5.95961750e-01 9.09016848e-01 1.60016030e-01
2.61807531e-01 7.76849389e-01 -6.71919167e-01 -4.43653762e-01
-8.08952808e-01 -2.70940185e-01 1.37292504e+00 5.53375125e-01
1.87487960e-01 -1.35230377e-01 -1.91674437e-02 9.65518594e-01
-4.07798477e-02 2.69805163e-01 9.26721752e-01 -8.22226778e-02
8.43113214e-02 7.84196675e-01 -9.16826800e-02 -7.85587251e-01
-8.96803319e-01 -2.59513319e-01 -7.95120537e-01 -4.26856756e-01
5.59379160e-01 -2.51766324e-01 -6.35628164e-01 1.30062556e+00
4.49578911e-01 -2.66599804e-01 5.40701330e-01 4.77731556e-01
1.15443683e+00 2.95681626e-01 5.72648644e-01 -5.94695568e-01
1.80650890e+00 -3.98248762e-01 -1.07121849e+00 3.40754211e-01
7.00942636e-01 -1.03255975e+00 2.96938777e-01 3.16794515e-01
-6.59033477e-01 -1.21724062e-01 -4.52837706e-01 -7.67291859e-02
-9.01182294e-01 1.10175051e-01 6.00876629e-01 7.93301165e-01
-8.30137312e-01 5.99232256e-01 -6.41581476e-01 -9.77041721e-01
1.15159132e-01 2.42683306e-01 -8.71186495e-01 5.94462194e-02
-1.37395537e+00 1.34243369e+00 9.68782306e-01 -1.99203834e-01
-1.47446066e-01 -3.33233654e-01 -8.01530898e-01 -1.03750579e-01
3.65206838e-01 -4.63679790e-01 8.24449599e-01 -6.13312900e-01
-1.24580789e+00 1.30834174e+00 -1.45744145e-01 -5.59696913e-01
1.74277887e-01 2.84163028e-01 -1.15895009e+00 3.78049612e-01
1.79567561e-01 1.93337530e-01 1.13496400e-01 -8.28812122e-01
-6.53098047e-01 -2.56229490e-01 -4.79560792e-01 -9.43575278e-02
-1.69696093e-01 4.19482470e-01 -2.02843085e-01 -8.90330434e-01
-3.68135005e-01 -3.76947314e-01 -5.63056767e-01 -7.92408943e-01
-2.05651641e-01 -4.68921244e-01 9.35034603e-02 -9.10913110e-01
1.38475716e+00 -2.10998917e+00 -1.78030401e-01 2.66664505e-01
1.16229489e-01 4.62728918e-01 -5.10140136e-02 8.02102983e-01
-3.85559261e-01 2.14900345e-01 -3.66576672e-01 1.78066060e-01
-2.46584445e-01 6.72158301e-01 1.02311410e-01 3.78292203e-01
1.79846123e-01 4.60179061e-01 -1.07680368e+00 -1.00181055e+00
1.78622216e-01 4.53275830e-01 -2.83066090e-03 -1.19018890e-01
-1.71366278e-02 5.76363623e-01 -9.08404768e-01 5.74433863e-01
2.83272952e-01 2.71930307e-01 2.39036933e-01 2.13205814e-02
-4.68151271e-01 1.89491823e-01 -1.01822984e+00 1.40200448e+00
-3.07052612e-01 3.01732481e-01 -1.39150202e-01 -1.14996231e+00
1.05488491e+00 8.59682024e-01 8.41863990e-01 -2.60193199e-01
5.43003559e-01 4.02928323e-01 -3.44300307e-02 -8.09698045e-01
6.64210081e-01 -6.00591242e-01 -5.37666902e-02 2.00016454e-01
3.35279495e-01 3.81154567e-01 8.74654293e-01 -1.63750798e-01
1.33920074e+00 -8.94995555e-02 1.25247109e+00 -3.38889360e-01
1.00477958e+00 4.36835825e-01 5.44178009e-01 2.52389491e-01
-1.35664403e-01 3.14806283e-01 4.59042996e-01 -4.19087946e-01
-9.69185889e-01 -4.31508631e-01 -7.87817240e-01 6.49799168e-01
-5.37892342e-01 -3.28931272e-01 -6.96435630e-01 -6.36429667e-01
-5.07435083e-01 6.49687886e-01 -4.41534311e-01 5.07000685e-01
-6.19404078e-01 -7.53246486e-01 7.94317722e-01 -1.27206907e-01
3.12873662e-01 -1.64873028e+00 -4.85392570e-01 5.19387662e-01
-2.16463298e-01 -1.30409157e+00 5.31355962e-02 2.67153114e-01
-1.01699102e+00 -1.39123535e+00 -8.99395525e-01 -1.01038492e+00
6.43449366e-01 -5.89157701e-01 1.19691014e+00 -1.13001145e-01
-6.24980390e-01 4.33595985e-01 -7.50274897e-01 -7.13679731e-01
-1.14872944e+00 3.27570438e-01 -2.35573471e-01 -3.42163950e-01
7.31210649e-01 -2.14088216e-01 -4.15896289e-02 -1.06761679e-01
-1.14447749e+00 -4.98688549e-01 9.22129631e-01 6.06638014e-01
5.31069934e-01 1.07908048e-01 5.49910903e-01 -1.47221470e+00
5.81921875e-01 -4.53405648e-01 -2.72570729e-01 2.80904591e-01
-2.97290474e-01 1.71972349e-01 6.34803593e-01 -1.04885541e-01
-1.23308253e+00 1.70461670e-01 -8.77567232e-01 5.61719477e-01
-9.53199565e-01 7.64808118e-01 -2.03741923e-01 4.24984396e-02
8.69650543e-01 5.89605942e-02 -3.24373782e-01 -9.45318997e-01
4.98726331e-02 8.32514405e-01 4.55985695e-01 -2.66753167e-01
2.50594497e-01 1.66144729e-01 3.39700550e-01 -1.30639160e+00
-4.64567780e-01 -1.18195486e+00 -7.20825195e-01 2.32310921e-01
1.25459945e+00 -4.60962296e-01 -5.85867941e-01 -8.24053362e-02
-1.29975367e+00 2.11918592e-01 -5.81430495e-01 9.03316557e-01
-2.05703393e-01 4.39536929e-01 -4.94669378e-01 -7.73897052e-01
-5.87688863e-01 -5.26141346e-01 5.50941288e-01 1.45703360e-01
-4.94406432e-01 -1.21037292e+00 6.59581900e-01 1.77126065e-01
-1.40337981e-02 3.80157173e-01 1.00548387e+00 -1.55652189e+00
5.39322853e-01 -4.17285681e-01 8.61439034e-02 1.18717499e-01
1.90920532e-01 -3.91703159e-01 -6.88950658e-01 2.60211378e-01
2.86484182e-01 3.23287338e-01 5.89296401e-01 -1.31673127e-01
5.11947870e-01 -6.10127151e-02 -5.73895097e-01 -1.95824429e-01
1.56957221e+00 4.38090652e-01 8.56543958e-01 4.39723134e-01
1.25263065e-01 7.85035610e-01 5.17898917e-01 4.16914731e-01
6.89979196e-02 1.98107719e-01 -2.88970202e-01 -1.98267043e-01
7.88903683e-02 1.37722209e-01 -3.47706117e-02 7.96276331e-01
-2.39943117e-01 -5.66925714e-03 -1.13909721e+00 8.39496315e-01
-1.25195360e+00 -8.84652138e-01 -3.06819528e-01 2.06014609e+00
1.14186013e+00 -8.27203691e-02 1.19388171e-01 9.42247137e-02
8.44567299e-01 -2.70714343e-01 2.06434116e-01 -4.20683146e-01
-2.22455531e-01 8.26320350e-01 5.95912337e-01 3.55698854e-01
-1.05158591e+00 7.02693641e-01 6.39791489e+00 8.11672628e-01
-8.52308571e-01 2.30120882e-01 2.28756890e-02 6.12272799e-01
1.11938976e-01 -2.92398214e-01 -7.83321261e-01 1.59502566e-01
1.36994314e+00 -3.41063529e-01 -1.44011259e-01 7.38631189e-01
4.62871611e-01 -2.63236195e-01 -8.14156592e-01 6.85037971e-01
2.09151000e-01 -1.18848383e+00 1.83762878e-01 1.07345775e-01
3.37856501e-01 1.67799920e-01 -8.41505408e-01 6.98386505e-02
3.15702409e-02 -7.44767368e-01 -1.50622977e-02 4.97936696e-01
6.96781158e-01 -8.33692372e-01 1.32792413e+00 2.11819932e-01
-8.49059105e-01 2.86270618e-01 -4.92401600e-01 3.65661889e-01
4.16914225e-01 9.54839945e-01 -1.03346479e+00 9.46046770e-01
3.19870710e-01 3.31584901e-01 -2.59982079e-01 1.20088506e+00
-2.40017861e-01 5.13125598e-01 -1.55408114e-01 -2.27392212e-01
7.72065222e-02 -1.10752352e-01 7.33902931e-01 1.63021564e+00
1.62011072e-01 3.75121772e-01 -1.53305247e-01 4.26216930e-01
-1.36321291e-01 1.09314060e+00 -4.40388352e-01 -5.66456258e-01
1.78576350e-01 1.34455252e+00 -1.17847168e+00 -4.16874111e-01
-2.79886901e-01 9.34005439e-01 5.64264655e-02 -1.67652220e-01
-6.90314546e-02 -9.66339111e-01 2.02298254e-01 -1.58034042e-02
1.02393843e-01 2.64234021e-02 -1.29433215e-01 -9.94748056e-01
-4.38798219e-01 -6.33587658e-01 8.03899944e-01 -2.28401825e-01
-1.20455861e+00 9.83198106e-01 3.91154848e-02 -9.47178423e-01
-3.47023010e-01 -9.13004637e-01 -1.82726219e-01 7.42314696e-01
-1.20449173e+00 -8.28269660e-01 4.16187674e-01 5.35674095e-01
2.49328345e-01 -2.69582868e-01 1.53330123e+00 5.22164524e-01
-3.12568724e-01 7.44331479e-02 2.87943721e-01 4.56420124e-01
8.79784286e-01 -1.28060579e+00 -6.69678599e-02 4.72846061e-01
1.47728279e-01 7.72425771e-01 7.94952750e-01 -7.33260334e-01
-6.22215927e-01 -6.58163071e-01 2.20253205e+00 -2.23241702e-01
7.60618508e-01 1.41953006e-01 -8.25033188e-01 2.16209397e-01
2.93981165e-01 -3.65470916e-01 1.31290376e+00 1.99142308e-03
1.80398211e-01 1.74271584e-01 -1.54151762e+00 3.61820996e-01
5.87075174e-01 -3.26256156e-01 -1.13219953e+00 4.26518083e-01
3.93731445e-01 -2.64441848e-01 -1.44970584e+00 1.00564994e-02
1.10714629e-01 -5.10289967e-01 6.75140262e-01 -5.10451138e-01
2.74041039e-03 -1.46133766e-01 5.31300306e-01 -1.05393016e+00
5.91016635e-02 -6.20596945e-01 6.69295490e-01 1.28830719e+00
5.29800296e-01 -7.05290020e-01 5.38008809e-01 5.20562768e-01
-1.72563419e-01 -1.81973293e-01 -1.12840521e+00 -4.58142042e-01
-5.66722406e-03 -3.99805009e-01 3.61691743e-01 1.10886133e+00
6.77280009e-01 4.59958434e-01 1.03823226e-02 -2.96231508e-01
6.70228973e-02 -3.59891742e-01 1.74003299e-02 -1.52598345e+00
-3.51341628e-02 -3.79266232e-01 -5.90374589e-01 -1.21199578e-01
1.83613032e-01 -8.16057146e-01 1.03498206e-01 -1.70393956e+00
9.64922309e-02 -1.84041083e-01 -2.94333100e-01 6.16868377e-01
1.87665239e-01 1.40733004e-01 -1.63455024e-01 8.87996331e-02
-3.14765304e-01 -1.30087152e-01 8.44872773e-01 3.17959100e-01
-3.64862204e-01 -8.78229514e-02 -4.29692566e-01 6.18493080e-01
7.69841552e-01 -9.55439866e-01 1.96431994e-01 2.00290188e-01
4.22979861e-01 -5.30859679e-02 -3.66755992e-01 -8.18909168e-01
1.31497443e-01 -1.20920002e-01 2.87042230e-01 -5.79861820e-01
-2.98770666e-01 -1.15035248e+00 2.18153566e-01 7.55136013e-01
-1.41403049e-01 -2.29873762e-01 2.04591975e-01 3.13927919e-01
-4.19084936e-01 -1.01201999e+00 6.93020105e-01 -5.76046288e-01
-9.06974733e-01 -9.39970836e-02 -1.00879025e+00 1.20550640e-01
1.03049493e+00 -3.04185003e-02 4.51404564e-02 1.86832666e-01
-1.08219326e+00 -1.57809556e-01 3.94787282e-01 -2.29325034e-02
3.11313480e-01 -8.70759606e-01 -6.73236728e-01 -2.57180959e-01
2.99320251e-01 -1.52001470e-01 4.26199466e-01 8.02509785e-01
-9.66659009e-01 8.70821059e-01 -4.46625829e-01 2.39923105e-01
-1.41507030e+00 8.02964509e-01 1.36015769e-02 -7.89892316e-01
-6.38378620e-01 7.71624893e-02 -3.19356382e-01 -4.44276452e-01
-8.68643746e-02 -1.55786097e-01 -1.19913554e+00 1.93892151e-01
5.94826043e-01 4.91313487e-01 2.97705054e-01 -1.06881404e+00
-4.89110291e-01 1.37339756e-01 2.68961549e-01 -7.87422284e-02
1.32401633e+00 -1.05238177e-01 -6.71342909e-01 4.14869249e-01
1.02016425e+00 3.74258608e-01 2.92641431e-01 -1.95344880e-01
8.06251943e-01 2.69033134e-01 -2.11807117e-01 -8.39921772e-01
-5.15241921e-01 3.85827810e-01 3.15606803e-01 7.83813745e-02
1.05341256e+00 1.22884326e-01 5.55794060e-01 7.31737316e-01
3.40271115e-01 -1.22581494e+00 -7.32262373e-01 7.46062458e-01
6.65076077e-01 -7.59130120e-01 -2.63012275e-02 -5.32294452e-01
-6.10846937e-01 1.42640579e+00 -1.80171087e-01 2.54946828e-01
7.72142470e-01 3.36228549e-01 8.65836814e-02 -2.21787721e-01
-4.18565124e-02 -6.03549302e-01 2.52764851e-01 6.91190898e-01
8.87669146e-01 -3.45293470e-02 -1.46099365e+00 8.28112781e-01
-8.47958215e-03 5.60193956e-01 4.59866166e-01 9.89104033e-01
-3.60447466e-01 -1.65304315e+00 -5.28647125e-01 3.49447131e-01
-1.30185020e+00 -2.10267022e-01 -5.03501475e-01 9.57539797e-01
4.12581772e-01 9.45608199e-01 -1.61574244e-01 2.51747787e-01
4.90126103e-01 1.83105931e-01 3.73570502e-01 -8.29863667e-01
-8.80976677e-01 1.66965544e-01 6.54914320e-01 -2.05817893e-01
-8.48950505e-01 -5.01016021e-01 -1.62747514e+00 -7.92482123e-02
-1.81387901e-01 8.95667851e-01 7.85836697e-01 1.14475513e+00
7.01298788e-02 4.63786751e-01 1.75168216e-01 -1.98522404e-01
4.46986035e-02 -1.08536339e+00 -9.47588146e-01 2.72194296e-01
-1.86163634e-01 -1.44124642e-01 -5.98654849e-03 2.51971304e-01] | [8.583709716796875, 8.749297142028809] |
23cba72a-a6f2-4da0-a759-50d45cd51f68 | openauc-towards-auc-oriented-open-set | 2210.13458 | null | https://arxiv.org/abs/2210.13458v3 | https://arxiv.org/pdf/2210.13458v3.pdf | OpenAUC: Towards AUC-Oriented Open-Set Recognition | Traditional machine learning follows a close-set assumption that the training and test set share the same label space. While in many practical scenarios, it is inevitable that some test samples belong to unknown classes (open-set). To fix this issue, Open-Set Recognition (OSR), whose goal is to make correct predictions on both close-set samples and open-set samples, has attracted rising attention. In this direction, the vast majority of literature focuses on the pattern of open-set samples. However, how to evaluate model performance in this challenging task is still unsolved. In this paper, a systematic analysis reveals that most existing metrics are essentially inconsistent with the aforementioned goal of OSR: (1) For metrics extended from close-set classification, such as Open-set F-score, Youden's index, and Normalized Accuracy, a poor open-set prediction can escape from a low performance score with a superior close-set prediction. (2) Novelty detection AUC, which measures the ranking performance between close-set and open-set samples, ignores the close-set performance. To fix these issues, we propose a novel metric named OpenAUC. Compared with existing metrics, OpenAUC enjoys a concise pairwise formulation that evaluates open-set performance and close-set performance in a coupling manner. Further analysis shows that OpenAUC is free from the aforementioned inconsistency properties. Finally, an end-to-end learning method is proposed to minimize the OpenAUC risk, and the experimental results on popular benchmark datasets speak to its effectiveness. Project Page: https://github.com/wang22ti/OpenAUC. | ['Qingming Huang', 'Xiaochun Cao', 'Yuan He', 'Zhiyong Yang', 'Qianqian Xu', 'Zitai Wang'] | 2022-10-22 | null | null | null | null | ['open-set-learning'] | ['miscellaneous'] | [ 5.83966747e-02 -1.42597124e-01 -3.84530008e-01 -5.91803968e-01
-8.84715378e-01 -5.80333591e-01 3.31976980e-01 3.00648093e-01
-5.82121313e-02 7.45811164e-01 -3.99837404e-01 -8.14129040e-02
-4.55924094e-01 -6.18105829e-01 -4.58264679e-01 -6.52006388e-01
1.12548783e-01 1.82578072e-01 7.14286566e-02 -5.72726950e-02
3.67654026e-01 7.32648894e-02 -1.70428061e+00 1.32242054e-01
1.14101768e+00 1.38580263e+00 -7.68948868e-02 7.05010965e-02
-6.21694848e-02 3.68497968e-01 -6.17354751e-01 -5.63155413e-01
4.60602909e-01 -4.76820886e-01 -5.29093862e-01 -2.52403826e-01
4.78399009e-01 1.40400812e-01 -2.66395267e-02 1.26154459e+00
4.80872303e-01 5.92500195e-02 7.59372354e-01 -1.43117034e+00
-9.77571607e-01 5.02176881e-01 -6.06880367e-01 1.47577897e-01
3.44346017e-01 1.58297360e-01 1.36451805e+00 -1.11095572e+00
3.52777481e-01 6.46950543e-01 8.38984668e-01 3.77968997e-01
-9.99495029e-01 -8.57953787e-01 2.14568496e-01 1.88620999e-01
-1.78677869e+00 -1.34975120e-01 6.50482357e-01 -4.06959414e-01
3.17035198e-01 6.90764368e-01 3.09352040e-01 1.01736605e+00
1.54931575e-01 6.49844229e-01 1.32466376e+00 -3.01092267e-01
2.71476388e-01 3.24204326e-01 6.23188913e-01 3.38670969e-01
5.19002974e-01 2.17848450e-01 -2.41414577e-01 -3.41672613e-03
3.12696755e-01 2.89149404e-01 -5.84383726e-01 -4.27483737e-01
-1.13507581e+00 5.37837744e-01 5.27656674e-01 4.20546353e-01
9.18178856e-02 -5.45723975e-01 3.87171894e-01 5.69095910e-01
4.86290723e-01 4.93891448e-01 -4.74258929e-01 -9.05560628e-02
-8.43294919e-01 6.60173735e-03 8.92537057e-01 8.14102650e-01
6.38164103e-01 -3.42001617e-01 -3.03866833e-01 1.10249913e+00
2.27746457e-01 2.50440717e-01 9.06647742e-01 -3.80333304e-01
2.73168206e-01 7.93327808e-01 -8.66906941e-02 -1.06420720e+00
-1.69282287e-01 -9.94581223e-01 -8.87295365e-01 9.05376300e-03
5.87440610e-01 2.77803868e-01 -5.37326217e-01 1.60074723e+00
4.00657117e-01 2.76180238e-01 1.54821351e-01 9.69988406e-01
1.07681680e+00 4.70930666e-01 -3.65588635e-01 -4.89495456e-01
1.02548802e+00 -1.09189069e+00 -5.34776568e-01 -3.73620689e-02
7.21267939e-01 -6.08482718e-01 1.24209452e+00 5.42221308e-01
-4.92113769e-01 -5.35737395e-01 -1.28938043e+00 2.55021125e-01
-4.68510181e-01 9.52246785e-02 3.94467384e-01 7.42073596e-01
-4.23473567e-01 7.37482369e-01 -2.31753901e-01 -2.22347066e-01
5.23055911e-01 1.17412649e-01 -5.51004410e-01 -3.21308941e-01
-1.05901456e+00 7.67712355e-01 4.74317938e-01 9.66115743e-02
-5.74342310e-01 -8.03407490e-01 -4.99201149e-01 1.79343492e-01
6.45097613e-01 -4.47802991e-01 1.06196320e+00 -1.00378382e+00
-1.09604955e+00 8.89754176e-01 2.34707534e-01 -2.67832994e-01
6.49463892e-01 -1.40561864e-01 -7.07247615e-01 -3.34681481e-01
1.53579518e-01 9.74230841e-02 6.18543208e-01 -1.23954356e+00
-5.19862831e-01 -5.77256024e-01 -2.12601304e-01 1.54782161e-01
-6.81393623e-01 -2.23662868e-01 -2.18276754e-01 -7.54670739e-01
3.99338454e-01 -7.02757597e-01 1.00409472e-02 -1.59110054e-02
-4.19126898e-01 -4.30600464e-01 6.29236698e-01 -1.16737708e-01
1.78941000e+00 -2.31988406e+00 -3.84459794e-01 3.42346340e-01
4.84782964e-01 4.56862062e-01 4.67324965e-02 2.02193841e-01
-5.42074680e-01 2.11579427e-01 -3.19812715e-01 1.34484142e-01
8.27526525e-02 -7.08724372e-03 -4.89513367e-01 4.90545928e-01
-2.92133470e-03 7.20244169e-01 -9.82359469e-01 -4.06709105e-01
-4.72521670e-02 5.61266020e-02 -3.13672006e-01 1.26516027e-02
1.93688851e-02 1.84601724e-01 -3.18707377e-01 9.01937008e-01
5.79333067e-01 -4.96650040e-01 -1.23013772e-01 -4.34876420e-02
7.21408874e-02 -8.96728337e-02 -1.47375464e+00 1.32783830e+00
3.67147848e-03 3.09366733e-01 -4.38277155e-01 -9.43566561e-01
1.33486247e+00 5.20047024e-02 2.96769112e-01 -5.81583560e-01
2.03955293e-01 7.15829313e-01 1.88601315e-01 -2.66939908e-01
3.00859332e-01 -9.21940506e-02 -1.10856973e-01 2.70491302e-01
-1.30716160e-01 3.47606659e-01 5.98302372e-02 -1.08640909e-01
1.01823652e+00 1.27379775e-01 7.92692006e-01 -2.04065159e-01
5.24714410e-01 -1.75725773e-01 7.99605846e-01 7.03899205e-01
-5.77880979e-01 8.83662760e-01 4.41808194e-01 -4.23146844e-01
-5.19892573e-01 -1.10515904e+00 -6.39210999e-01 7.08012283e-01
4.23220009e-01 -4.90191013e-01 -5.11919022e-01 -9.55622315e-01
2.10586548e-01 5.66987932e-01 -7.00599313e-01 -3.59075367e-01
-5.14840707e-02 -6.91613913e-01 5.07985234e-01 1.58969089e-01
2.66519189e-01 -5.64422727e-01 -1.61887571e-01 -1.81021675e-01
-1.71183929e-01 -5.98435700e-01 -6.94205642e-01 6.07227236e-02
-7.75369704e-01 -1.31224847e+00 -7.58077502e-01 -7.40992665e-01
5.67396402e-01 5.16328275e-01 1.02099013e+00 2.40685698e-02
-5.11029959e-02 -9.64523852e-02 -7.03926027e-01 -5.33373475e-01
-2.18195051e-01 -1.16383046e-01 1.81891382e-01 4.40993994e-01
6.36964917e-01 -3.91241312e-01 -5.45010924e-01 9.61422026e-01
-8.15233767e-01 -3.17311972e-01 5.75207233e-01 1.00358105e+00
9.46509361e-01 1.33998156e-01 1.02160776e+00 -7.58607268e-01
3.98592561e-01 -7.68668532e-01 -3.38768154e-01 4.34117466e-01
-1.17605770e+00 -3.21409017e-01 6.83729529e-01 -6.41214192e-01
-5.28497458e-01 -3.83483380e-01 4.72115427e-02 -6.60216212e-01
-1.81489483e-01 5.03606319e-01 -3.16211313e-01 -2.61520240e-02
8.16099048e-01 2.66047239e-01 1.80531800e-01 -4.54875410e-01
-3.97351570e-02 1.13417983e+00 3.41648072e-01 -3.68398458e-01
7.75110722e-01 2.55179435e-01 -2.49407336e-01 -5.74440897e-01
-1.35539210e+00 -6.02334023e-01 -3.41797918e-01 -2.01245472e-01
1.53762132e-01 -8.74256015e-01 -4.03266758e-01 3.61663729e-01
-4.67057019e-01 8.33813548e-02 -5.85187256e-01 5.50597906e-01
-2.93301105e-01 5.47432184e-01 7.39652440e-02 -6.78697467e-01
-4.02252883e-01 -9.99771595e-01 7.86258161e-01 3.32157791e-01
-4.23120856e-01 -7.72497058e-01 1.80865601e-02 4.74488765e-01
7.47788250e-02 3.30218554e-01 4.86542851e-01 -1.41472805e+00
-3.12337369e-01 -5.71900725e-01 -1.03297673e-01 6.83861077e-01
1.89014256e-01 -4.15949225e-02 -1.01373291e+00 -3.22361112e-01
1.15892529e-01 -1.33478299e-01 7.33447850e-01 1.67276010e-01
1.39353383e+00 -9.44911763e-02 -3.19751441e-01 5.62187374e-01
1.44747388e+00 2.13208035e-01 6.25645399e-01 3.40878487e-01
5.13863444e-01 4.94869441e-01 1.10920739e+00 4.24898028e-01
1.61590964e-01 5.70083916e-01 2.84249187e-01 2.40721583e-01
3.76136787e-02 -3.47750425e-01 4.46139812e-01 7.29410589e-01
3.57495666e-01 -2.74871171e-01 -8.99054825e-01 3.17171752e-01
-1.66259384e+00 -9.91149724e-01 -3.72966975e-01 2.67601776e+00
7.41167665e-01 3.15513253e-01 1.53369186e-02 4.99494582e-01
8.62486422e-01 -9.35572535e-02 -6.20719492e-01 -4.82730865e-02
-3.84887695e-01 -1.75085649e-01 4.99944612e-02 -3.15444097e-02
-9.77322400e-01 3.87909472e-01 5.35071850e+00 1.37551069e+00
-1.02241015e+00 2.03638643e-01 9.29006755e-01 -2.51254976e-01
-1.93291739e-01 4.47473451e-02 -9.90915298e-01 8.14849317e-01
6.80395842e-01 -2.87990570e-01 6.30227029e-02 9.78406549e-01
-1.09409891e-01 7.49441981e-02 -1.47108233e+00 1.39274681e+00
4.10137475e-01 -9.75274146e-01 -9.36931744e-02 1.33185744e-01
7.38091886e-01 -9.51279774e-02 1.80325910e-01 6.43277943e-01
-3.49311143e-01 -8.99164498e-01 6.59223378e-01 5.12947500e-01
9.53683674e-01 -6.04922652e-01 8.83449316e-01 5.54159939e-01
-9.12674248e-01 -3.83136183e-01 -1.83381915e-01 -1.80934250e-01
-3.65134299e-01 9.24169421e-01 -4.98742282e-01 7.54572809e-01
6.32670105e-01 9.11426425e-01 -8.11946273e-01 1.41674662e+00
7.36391991e-02 6.30008996e-01 -1.54741034e-01 -7.03987405e-02
-6.76419735e-02 -3.93120378e-01 6.69406474e-01 6.36738420e-01
3.66691560e-01 -1.82793178e-02 2.31696784e-01 8.85233581e-01
-3.62044238e-02 3.88408810e-01 -8.06200027e-01 6.03362545e-02
4.75978911e-01 1.12439334e+00 -6.59190476e-01 -1.17723897e-01
-4.40487564e-01 6.53786480e-01 2.35147059e-01 -3.85001898e-02
-8.83275568e-01 -5.53352535e-01 5.41071594e-01 1.23554245e-01
8.07794482e-02 4.20159608e-01 -5.66675484e-01 -1.28470385e+00
5.25143504e-01 -8.25036049e-01 7.77987838e-01 -5.73274195e-01
-1.79240501e+00 4.14406717e-01 -2.93009222e-01 -2.06113172e+00
3.56771141e-01 -5.44079959e-01 -5.31073749e-01 5.95275223e-01
-1.45229137e+00 -6.69125140e-01 -3.20165634e-01 2.45735884e-01
3.85060996e-01 -2.94600606e-01 6.68124735e-01 4.52145278e-01
-9.34154093e-01 1.13194168e+00 4.85883087e-01 1.65970966e-01
9.32559073e-01 -1.14805806e+00 -1.16709046e-01 7.25264728e-01
2.07888171e-01 7.38553345e-01 5.44391870e-01 -4.59895492e-01
-1.05067146e+00 -1.17237079e+00 7.85786092e-01 -7.33422518e-01
5.34827769e-01 -5.01941293e-02 -1.15863967e+00 4.15123731e-01
-4.80673492e-01 5.26123524e-01 1.20931721e+00 2.20198527e-01
-6.30963027e-01 -5.67758381e-01 -1.08918059e+00 4.60854322e-01
9.53919530e-01 -2.49881729e-01 -7.56719589e-01 3.86503488e-01
5.80199897e-01 -3.74063045e-01 -1.19932461e+00 5.69534063e-01
7.42970824e-01 -9.91311729e-01 6.98682129e-01 -5.47800362e-01
4.02369082e-01 -4.79313284e-01 -3.49889904e-01 -1.24109185e+00
-1.82943389e-01 -3.64100665e-01 -2.87733197e-01 1.42422867e+00
3.55604917e-01 -1.02611959e+00 5.04237115e-01 2.81089902e-01
-3.49471092e-01 -1.30212021e+00 -8.84926736e-01 -1.22364509e+00
1.24914519e-01 -4.28195447e-01 5.97579956e-01 1.20893121e+00
1.42378494e-01 4.29396987e-01 -1.69820428e-01 2.10733816e-01
5.21099269e-01 4.64601487e-01 6.41991854e-01 -1.65080857e+00
-2.68195748e-01 -6.63133204e-01 -5.81567526e-01 -7.82023847e-01
8.12278478e-04 -1.23723304e+00 -1.36549145e-01 -1.15397930e+00
3.72150183e-01 -8.19895864e-01 -7.55058706e-01 3.46444726e-01
-3.55729431e-01 3.87982666e-01 -8.77736788e-03 5.98710299e-01
-9.59654450e-01 6.96089029e-01 1.20327568e+00 2.86074239e-03
-2.12825462e-01 8.39437991e-02 -1.05669689e+00 6.53111577e-01
7.32422411e-01 -4.81662273e-01 -3.28674167e-01 1.09276690e-01
2.72724241e-01 -1.73198670e-01 3.72451425e-01 -1.14457738e+00
2.96175387e-02 -1.62628219e-01 2.68129766e-01 -3.97876263e-01
-9.89275426e-02 -7.13240862e-01 1.27999321e-01 4.04243171e-01
-3.42973322e-01 -2.79692501e-01 -2.44686991e-01 8.62337708e-01
-3.67485732e-01 -3.38456929e-01 8.27797294e-01 2.17302218e-01
-6.26095593e-01 4.65937793e-01 3.65136296e-01 3.83511245e-01
1.51139867e+00 -7.39832520e-01 -3.76338929e-01 8.52097273e-02
-6.43747807e-01 3.42749238e-01 3.88385296e-01 7.00682163e-01
6.05842590e-01 -1.45871592e+00 -7.95583665e-01 2.54850179e-01
8.51119578e-01 -1.02396524e-02 3.75508636e-01 9.92470562e-01
-1.49346083e-01 3.04280967e-01 1.79067507e-01 -7.86439180e-01
-1.28337944e+00 6.02947176e-01 3.60581428e-01 -2.12420553e-01
-3.48060757e-01 8.40345621e-01 2.82299519e-01 -7.29961872e-01
2.45825455e-01 -1.42293826e-01 -2.82024592e-01 1.02791369e-01
6.84380710e-01 4.52939332e-01 2.69851029e-01 -6.05610847e-01
-2.36356303e-01 3.65861684e-01 -2.14192390e-01 6.45842314e-01
1.04147696e+00 -8.80192965e-02 4.48109023e-03 8.47860992e-01
1.30146945e+00 -1.14300795e-01 -8.49819958e-01 -4.64041770e-01
-1.89249128e-01 -7.30017841e-01 -1.01467028e-01 -8.97910297e-01
-6.47634506e-01 6.14869833e-01 8.69787633e-01 2.48307586e-01
1.03052211e+00 -1.24459960e-01 6.76764905e-01 3.34186047e-01
4.65700090e-01 -1.01578259e+00 1.18344076e-01 4.41926390e-01
8.16590250e-01 -1.69065475e+00 -7.70801604e-02 -5.63753009e-01
-5.37151396e-01 8.96138430e-01 8.11859131e-01 2.17230722e-01
7.30345309e-01 -2.11852297e-01 -1.30483121e-01 -2.37865821e-02
-7.21243262e-01 3.06674596e-02 4.30395365e-01 2.90711135e-01
2.80927092e-01 3.10647786e-01 -5.07712662e-01 1.14771080e+00
-1.82810351e-01 5.32250404e-02 3.45123917e-01 6.86732292e-01
-3.39348644e-01 -7.63824284e-01 -4.82366145e-01 1.00461400e+00
-4.34206247e-01 5.28900400e-02 -2.23823667e-01 5.80031574e-01
2.57090211e-01 8.07340026e-01 6.27424056e-03 -6.50900006e-01
2.80766070e-01 1.32479938e-02 6.97140992e-02 -7.12041616e-01
-4.04697269e-01 -4.30810690e-01 -2.21454442e-01 -4.41213399e-01
2.09192634e-02 -6.08790874e-01 -1.00571036e+00 -4.14855219e-02
-8.84192050e-01 2.69845277e-01 2.93233991e-01 8.41319323e-01
4.11101460e-01 3.98079902e-01 9.85995471e-01 -7.02343509e-02
-1.24053144e+00 -8.76466155e-01 -8.53181779e-01 5.10007501e-01
2.38707468e-01 -8.05702746e-01 -6.40703797e-01 -3.52992713e-01] | [9.636224746704102, 3.080015182495117] |
ac71459d-ea85-4817-87f8-75021c71d537 | dse-tts-dual-speaker-embedding-for-cross | 2306.14145 | null | https://arxiv.org/abs/2306.14145v1 | https://arxiv.org/pdf/2306.14145v1.pdf | DSE-TTS: Dual Speaker Embedding for Cross-Lingual Text-to-Speech | Although high-fidelity speech can be obtained for intralingual speech synthesis, cross-lingual text-to-speech (CTTS) is still far from satisfactory as it is difficult to accurately retain the speaker timbres(i.e. speaker similarity) and eliminate the accents from their first language(i.e. nativeness). In this paper, we demonstrated that vector-quantized(VQ) acoustic feature contains less speaker information than mel-spectrogram. Based on this finding, we propose a novel dual speaker embedding TTS (DSE-TTS) framework for CTTS with authentic speaking style. Here, one embedding is fed to the acoustic model to learn the linguistic speaking style, while the other one is integrated into the vocoder to mimic the target speaker's timbre. Experiments show that by combining both embeddings, DSE-TTS significantly outperforms the state-of-the-art SANE-TTS in cross-lingual synthesis, especially in terms of nativeness. | ['Kai Yu', 'Xie Chen', 'Chenpeng Du', 'Yiwei Guo', 'Sen Liu'] | 2023-06-25 | null | null | null | null | ['speech-synthesis'] | ['speech'] | [-7.51569122e-02 -1.34695172e-01 -1.19195189e-02 -4.53853816e-01
-1.08575690e+00 -4.52012569e-01 4.19509917e-01 -1.94931000e-01
-1.23606198e-01 4.51873243e-01 5.23077726e-01 -2.57957667e-01
3.68918926e-01 -3.06941241e-01 -6.36172354e-01 -8.57883513e-01
3.32729846e-01 -6.90395981e-02 -1.77574083e-01 -2.35408932e-01
-2.94529438e-01 1.85624391e-01 -1.57798517e+00 2.86525721e-03
8.81188154e-01 9.65156674e-01 3.78133833e-01 6.14798427e-01
-9.48257819e-02 4.63826448e-01 -8.18053246e-01 -5.39519370e-01
2.46770121e-02 -7.41711557e-01 -3.00754279e-01 -1.76305458e-01
5.29241323e-01 -1.89986736e-01 -3.76510412e-01 1.09336984e+00
7.93268859e-01 2.46180460e-01 6.03369057e-01 -1.08268034e+00
-9.53124404e-01 7.74813414e-01 -7.43486211e-02 -1.07524924e-01
3.04130912e-01 -5.53989783e-02 1.20454192e+00 -1.10544348e+00
2.90616065e-01 1.58636272e+00 4.87432420e-01 5.86284935e-01
-1.31561065e+00 -9.43669081e-01 -2.18750304e-03 1.93565696e-01
-1.50558984e+00 -1.00557566e+00 1.05363154e+00 -1.23894617e-01
6.92781150e-01 5.79779267e-01 3.96811545e-01 1.40328133e+00
1.43283501e-01 7.62428939e-01 1.12621069e+00 -6.71964347e-01
1.76194757e-01 5.60162842e-01 -2.95154035e-01 3.54804695e-01
-5.11229575e-01 2.87455529e-01 -8.63998413e-01 3.25446092e-02
4.36359704e-01 -5.39787173e-01 -4.89910603e-01 -2.02542134e-02
-1.18305850e+00 8.37696135e-01 1.18550733e-01 6.78069472e-01
-2.87819952e-01 -1.65867787e-02 5.59902191e-01 4.76031572e-01
4.28849638e-01 1.16865635e-01 -1.79687798e-01 -2.41210908e-01
-1.02271402e+00 4.23556939e-02 6.60093009e-01 8.34601045e-01
4.76481587e-01 9.45833504e-01 -7.72550479e-02 1.33188391e+00
3.96164626e-01 8.58198583e-01 9.31309640e-01 -6.78783536e-01
1.87643155e-01 -1.68474168e-01 -1.21930845e-01 -8.04437637e-01
2.78106898e-01 -5.58936179e-01 -7.77666748e-01 -6.14083186e-02
1.09714419e-02 -5.11783697e-02 -7.04699159e-01 2.06321621e+00
2.72157609e-01 2.02374309e-01 5.20793021e-01 8.54411960e-01
7.60440230e-01 1.15432823e+00 -1.37932360e-01 -4.27116990e-01
1.26747012e+00 -1.06198514e+00 -1.33756638e+00 -1.77644581e-01
2.76021123e-01 -1.21364605e+00 1.27951884e+00 3.25498611e-01
-1.02790844e+00 -1.12057781e+00 -1.15256369e+00 -9.47454572e-03
-3.13165247e-01 3.59080791e-01 -7.03203231e-02 1.03203881e+00
-9.94747162e-01 3.42187047e-01 -6.22996747e-01 -8.31330866e-02
-3.42753679e-01 9.91819948e-02 -3.45932364e-01 1.65230036e-01
-1.64533496e+00 9.06691551e-01 2.62530059e-01 -1.16135791e-01
-8.58038783e-01 -7.70903885e-01 -1.09258819e+00 -4.91135474e-03
-5.01720347e-02 -1.92802504e-01 1.34380472e+00 -8.43404472e-01
-2.19613695e+00 4.20212567e-01 -5.71715951e-01 -3.41911346e-01
1.65514797e-01 -1.52231708e-01 -1.02132845e+00 -1.86517611e-02
9.28174704e-02 5.34550965e-01 1.20483696e+00 -1.37400699e+00
-5.52708924e-01 -2.27808446e-01 -5.87563276e-01 3.60517651e-01
-6.61795080e-01 1.34965956e-01 -2.33793035e-01 -9.77920830e-01
8.51473808e-02 -9.37362432e-01 3.22994828e-01 -4.00634289e-01
-3.76745999e-01 -3.93811435e-01 9.90815520e-01 -9.76563394e-01
1.48118460e+00 -2.48127985e+00 1.71537861e-01 -1.15602888e-01
-3.41158420e-01 4.83541816e-01 -2.64260396e-02 5.72298586e-01
-1.26222849e-01 -6.31203800e-02 -4.89709191e-02 -7.94165015e-01
3.96485537e-01 2.89749473e-01 -5.52260697e-01 3.86744320e-01
1.51949763e-01 6.51981235e-01 -7.65060484e-01 -4.88889396e-01
5.27785420e-01 8.84757280e-01 -3.92790586e-01 4.11582500e-01
2.57359713e-01 5.66191316e-01 8.29780195e-03 3.66829872e-01
5.61941385e-01 6.94367826e-01 1.20363250e-01 -4.64624912e-01
-2.94216812e-01 6.77807450e-01 -1.09289908e+00 1.66723824e+00
-9.06225204e-01 5.85144401e-01 2.27154672e-01 -6.38962686e-01
1.21533859e+00 9.14605558e-01 2.27442846e-01 -7.22850204e-01
4.42639515e-02 5.33368766e-01 1.63850605e-01 -2.38547415e-01
4.97096747e-01 -6.30915344e-01 -9.11882818e-02 1.21493511e-01
4.11981225e-01 -4.78435457e-01 -1.95712298e-01 -2.61740088e-01
2.94802696e-01 -5.39569408e-02 2.58210301e-01 -3.59442651e-01
7.11408019e-01 -6.81615710e-01 6.12335443e-01 2.40626708e-01
-2.64752507e-01 4.54835832e-01 -7.80136064e-02 1.91657245e-01
-1.06382477e+00 -1.37798321e+00 -2.65181720e-01 1.13700247e+00
-1.30657673e-01 -5.19182742e-01 -1.10779274e+00 -2.64489710e-01
-1.19381562e-01 1.15823281e+00 -2.61340022e-01 -1.96566477e-01
-5.85766196e-01 -5.22806607e-02 8.83369505e-01 3.61020207e-01
9.68779773e-02 -8.45376730e-01 1.23469777e-01 4.95417893e-01
-2.68053949e-01 -1.20706487e+00 -1.15159798e+00 1.27772003e-01
-3.11425805e-01 -8.60561877e-02 -8.62634301e-01 -9.97678757e-01
-3.16415802e-02 2.57546678e-02 6.20040476e-01 -7.37281799e-01
2.00980410e-01 1.33216366e-01 -4.59165424e-01 -4.67572659e-01
-1.05359340e+00 -3.07947900e-02 6.87740445e-01 4.08379883e-01
3.38003486e-01 -6.65634871e-01 -2.64067948e-01 2.68327028e-01
-7.80121267e-01 -2.20352426e-01 2.74649411e-01 9.70277905e-01
6.56221747e-01 2.53730655e-01 9.33583498e-01 -3.35074127e-01
7.70485759e-01 -4.92878780e-02 -3.10223281e-01 1.46463856e-01
-2.81831592e-01 -4.22787927e-02 1.08500528e+00 -6.36266112e-01
-1.22269464e+00 -1.65705681e-01 -7.14810133e-01 -6.56495452e-01
-1.22691832e-01 3.59820962e-01 -5.06690860e-01 1.96099788e-01
3.13838661e-01 6.26507461e-01 -4.21741838e-03 -6.57665312e-01
3.93954068e-01 1.29441500e+00 9.10621345e-01 -4.47966605e-01
7.38412559e-01 -9.73729715e-02 -6.34901285e-01 -1.47613466e+00
-5.54173827e-01 -4.03682351e-01 -4.19319212e-01 1.21455248e-02
8.74306083e-01 -9.94157195e-01 -4.59470779e-01 5.13196468e-01
-1.18039548e+00 3.18782851e-02 -2.86345273e-01 9.61400986e-01
-6.32731080e-01 3.07789922e-01 -6.50873184e-01 -9.94607985e-01
-2.69961596e-01 -1.41490877e+00 1.07660556e+00 -7.18922094e-02
-2.93912619e-01 -1.02384782e+00 1.76223442e-01 2.55374372e-01
5.05148411e-01 -1.53200090e-01 7.67735720e-01 -4.56013143e-01
2.46598739e-02 -5.39840534e-02 3.37949395e-01 1.04649627e+00
6.41853631e-01 -9.63259935e-02 -1.49180925e+00 -4.44574356e-01
5.01053214e-01 -1.95796043e-01 3.26976418e-01 4.13698137e-01
6.95196033e-01 -3.80416512e-01 1.63422331e-01 6.01082921e-01
9.61313367e-01 4.29326653e-01 4.73117650e-01 -2.75937855e-01
7.29487181e-01 6.23130381e-01 4.25967276e-01 1.29826829e-01
1.99300855e-01 9.75272536e-01 -1.55311331e-01 -1.64789423e-01
-5.27563810e-01 -6.07187331e-01 1.00263131e+00 1.98513341e+00
3.85295570e-01 -2.31979072e-01 -3.92686218e-01 5.93592584e-01
-1.30347753e+00 -7.42792428e-01 1.31322354e-01 2.22774935e+00
1.15878034e+00 -8.69177654e-03 -6.59687370e-02 4.97584701e-01
7.40199625e-01 3.68720502e-01 -4.06901300e-01 -8.45574915e-01
-2.39141360e-01 3.31311882e-01 1.49354443e-01 8.01963687e-01
-8.39246631e-01 1.10465753e+00 5.50633144e+00 1.35847175e+00
-1.44897342e+00 3.56457204e-01 2.09811062e-01 2.07047194e-01
-4.01437074e-01 -2.98204780e-01 -8.26355934e-01 4.80556428e-01
1.45033717e+00 -2.25899845e-01 5.82277834e-01 7.21645713e-01
2.91347444e-01 5.58421433e-01 -1.16654944e+00 1.01211596e+00
3.04704309e-01 -7.12386489e-01 6.77254573e-02 -9.17715207e-02
6.22177362e-01 -2.34113187e-01 3.39535296e-01 4.53346461e-01
-6.12263605e-02 -1.12972021e+00 1.18341458e+00 1.07783131e-01
1.11085463e+00 -9.60021079e-01 5.91314197e-01 3.18033040e-01
-1.44032085e+00 3.65723670e-01 -2.05679163e-01 4.25106525e-01
3.03036064e-01 2.43754759e-01 -9.96132195e-01 7.55818009e-01
4.62899834e-01 5.62571287e-01 -1.10266767e-01 4.13485199e-01
-1.05161630e-01 9.15511429e-01 -2.00960800e-01 1.12378135e-01
3.20701540e-01 -1.74981982e-01 7.39949584e-01 1.40534043e+00
6.53052270e-01 -3.81501824e-01 1.71241865e-01 8.35386336e-01
1.03398003e-02 4.21133637e-01 -4.72505778e-01 -3.22966367e-01
7.02243686e-01 7.28782654e-01 2.16960330e-02 -3.30528885e-01
-3.39381725e-01 1.21941161e+00 -7.85376653e-02 4.80369210e-01
-7.37083077e-01 -5.54111779e-01 1.05423653e+00 -3.01851869e-01
4.23725903e-01 -2.60725379e-01 1.72657430e-01 -1.01659667e+00
-2.67225541e-02 -1.13138759e+00 -2.34505951e-01 -5.23673475e-01
-1.38591444e+00 1.04202914e+00 -3.26867372e-01 -1.26434052e+00
-5.20989299e-01 -4.92807806e-01 -3.89039248e-01 1.35387921e+00
-1.51870894e+00 -1.35196471e+00 2.69695997e-01 5.08758426e-01
8.04814100e-01 -2.90187240e-01 1.23142076e+00 5.13464808e-01
-4.49595809e-01 1.07408118e+00 4.21688259e-01 -3.14848386e-02
9.97416258e-01 -1.27754974e+00 5.02136350e-01 7.71773696e-01
2.19390318e-01 6.28792226e-01 8.42220902e-01 -2.56093711e-01
-1.38783538e+00 -1.10427642e+00 1.15156496e+00 -5.64379953e-02
6.96949601e-01 -6.71545744e-01 -1.07308805e+00 5.34033298e-01
4.92761105e-01 -1.74826726e-01 8.88235033e-01 -2.27753639e-01
-3.00914556e-01 -4.29367721e-01 -7.47176230e-01 7.44235992e-01
5.12037396e-01 -1.10668826e+00 -7.75889695e-01 -1.37981430e-01
1.19080913e+00 -2.09568396e-01 -1.12411857e+00 1.98592201e-01
6.39253616e-01 -8.96313608e-01 9.71287072e-01 -5.43810055e-02
-9.86918509e-02 -4.20973808e-01 -8.27206314e-01 -1.79640222e+00
-1.01740323e-01 -8.30795586e-01 2.49562964e-01 1.82413077e+00
2.78086305e-01 -6.49301946e-01 6.80457577e-02 -1.44394845e-01
-5.99065900e-01 -2.84707755e-01 -1.15982413e+00 -1.17939520e+00
2.71921575e-01 -5.50996006e-01 8.44815910e-01 9.99183357e-01
-7.19605908e-02 5.21868289e-01 -7.93504775e-01 4.56409603e-01
3.99560630e-01 -1.50709689e-01 6.39164507e-01 -7.73060441e-01
-3.72462243e-01 -2.63790339e-01 -2.11380988e-01 -1.09415281e+00
4.53179389e-01 -9.01019454e-01 3.31323028e-01 -9.73642468e-01
-5.93412638e-01 -1.96735486e-01 -4.72435117e-01 2.12128796e-02
-1.83752537e-01 1.29628181e-01 2.79355228e-01 -1.84607953e-01
9.22215357e-02 1.17634606e+00 1.26794493e+00 -4.63668369e-02
-3.42163682e-01 -1.17528476e-01 -3.28868717e-01 5.40953398e-01
7.34754860e-01 -3.89371425e-01 -4.12324101e-01 -2.11107358e-01
-7.14454770e-01 3.04982156e-01 -1.02353983e-01 -1.09700596e+00
6.51939213e-02 8.59440640e-02 -6.37213290e-02 -4.25116032e-01
9.14427519e-01 -7.45514214e-01 1.28744021e-01 3.08205754e-01
-4.40435767e-01 -2.16406241e-01 2.81702459e-01 3.08884889e-01
-7.33199179e-01 -1.05536185e-01 8.47757041e-01 2.87336767e-01
-2.31645033e-01 1.33199552e-02 -4.29450095e-01 -6.63626865e-02
5.58109641e-01 -1.24793857e-01 6.37084991e-02 -4.54759955e-01
-3.84207994e-01 -3.40534240e-01 2.52432287e-01 6.76367819e-01
5.49491227e-01 -1.81662631e+00 -1.00438929e+00 7.04194129e-01
2.09774494e-01 -4.94595855e-01 4.27378684e-01 6.06974006e-01
-2.70198118e-02 6.53216243e-01 7.40002543e-02 -5.81125498e-01
-1.29569101e+00 3.98465276e-01 1.91362143e-01 2.47906908e-01
-2.96059281e-01 8.20118368e-01 5.25834203e-01 -6.99434280e-01
4.49404716e-01 -4.09834355e-01 5.12894578e-02 3.22467051e-02
4.98823106e-01 7.88927376e-02 1.89984769e-01 -1.23343956e+00
-3.59590888e-01 5.64794838e-01 3.12831663e-02 -6.17164493e-01
9.50434625e-01 -3.39374036e-01 5.18242158e-02 1.02680504e+00
1.66572714e+00 5.66300511e-01 -1.00122976e+00 -3.00767064e-01
-3.04407746e-01 -4.57495004e-01 4.00419444e-01 -5.43917298e-01
-6.10935330e-01 1.14138031e+00 6.24337435e-01 2.51141310e-01
9.79877174e-01 -2.95518816e-01 1.19019699e+00 -1.57944933e-02
1.60943195e-01 -1.23479712e+00 -6.19706437e-02 4.57442462e-01
1.13933742e+00 -1.09150612e+00 -6.03686392e-01 -3.31656903e-01
-9.80988801e-01 1.00896275e+00 2.15114802e-01 9.17387158e-02
7.37597167e-01 1.80944353e-01 4.67843503e-01 4.61558491e-01
-5.55057168e-01 4.11664657e-02 4.88075256e-01 5.88579535e-01
7.69947052e-01 3.81055295e-01 7.76985809e-02 5.44905961e-01
-1.08489633e+00 -6.70598567e-01 1.50209159e-01 4.01270866e-01
-3.39260995e-01 -1.22359073e+00 -6.58919871e-01 -2.22587034e-01
-5.60361981e-01 -2.49951065e-01 -2.38181770e-01 4.44344729e-01
1.06428690e-01 1.31228876e+00 -1.55954296e-02 -5.79421282e-01
4.01715547e-01 3.87673676e-01 2.24504545e-01 -4.61841285e-01
-4.70809937e-01 6.84426665e-01 9.08606946e-02 -2.73866802e-01
-1.53867826e-01 -4.45001304e-01 -9.33483422e-01 -3.28376889e-01
-4.86001819e-01 4.97802138e-01 1.02653861e+00 6.69754028e-01
-3.90185937e-02 8.71590078e-01 1.01850045e+00 -8.06110382e-01
-7.71794558e-01 -1.16457951e+00 -9.21644628e-01 3.48909914e-01
7.30426371e-01 -3.46131384e-01 -6.19205236e-01 1.97039053e-01] | [14.885265350341797, 6.576304912567139] |
ad07d718-6aaa-4a6f-804b-cd36af13d9e8 | free-on-line-speech-recogniser-based-on-kaldi | null | null | https://aclanthology.org/W14-4315 | https://aclanthology.org/W14-4315.pdf | Free on-line speech recogniser based on Kaldi ASR toolkit producing word posterior lattices | null | ["Filip Jur{\\v{c}}{\\'\\i}{\\v{c}}ek", "Ond{\\v{r}}ej Pl{\\'a}tek"] | 2014-06-01 | null | null | null | ws-2014-6 | ['acoustic-modelling'] | ['speech'] | [-8.63703638e-02 1.71006292e-01 -6.22772932e-01 -4.08054382e-01
-8.41685571e-03 -9.08429027e-01 6.55310392e-01 -6.53472245e-01
-2.85945535e-01 1.06888819e+00 -4.63127941e-02 -1.01159286e+00
-3.91567826e-01 -9.63214397e-01 -4.95059669e-01 -6.31337762e-01
-9.79754329e-01 7.25764990e-01 3.30370307e-01 -6.93831444e-01
7.03166842e-01 7.88774848e-01 -1.68942046e+00 7.18545914e-01
7.04417467e-01 8.52217197e-01 2.49141872e-01 1.14950800e+00
-1.95044339e-01 1.55633950e+00 -7.48382092e-01 -5.46825826e-01
3.13719302e-01 -1.23176083e-01 -7.22945035e-01 -1.01074085e-01
9.28529128e-02 -8.59008506e-02 -2.09758401e-01 9.22211111e-01
5.37373662e-01 4.49454933e-02 1.08379531e+00 -1.42548037e+00
-5.91619551e-01 6.10313773e-01 -4.01565880e-02 1.21627934e-01
1.03678203e+00 -5.39447069e-01 1.19919395e+00 -1.13026452e+00
7.20913768e-01 1.26888943e+00 8.66221786e-01 5.44149756e-01
-1.22286928e+00 -1.94712028e-01 -3.26822817e-01 -9.51717794e-02
-1.46558487e+00 -3.25250506e-01 4.25783843e-02 -2.08119690e-01
1.66093647e+00 1.26596653e+00 1.20609856e+00 1.01401424e+00
1.26658809e+00 8.34431887e-01 1.04267764e+00 -5.13792276e-01
3.35295945e-01 3.66983831e-01 1.54683650e-01 6.33519173e-01
8.40953708e-01 5.26628852e-01 -7.06372619e-01 -9.13127720e-01
9.33553874e-01 -2.94925272e-01 1.71355158e-01 -5.05680561e-01
-9.05919552e-01 6.91228509e-01 1.78732842e-01 3.83959889e-01
-1.39880210e-01 9.89067405e-02 1.26390755e-01 5.30987144e-01
-2.58292928e-02 6.47037446e-01 -9.11868811e-01 -1.33165747e-01
-8.71728659e-01 5.10332465e-01 1.25398111e+00 1.52653182e+00
1.24482810e-01 2.94908643e-01 -9.34252143e-02 3.17179203e-01
8.92314315e-01 1.01808000e+00 4.28362608e-01 -1.36146402e+00
-6.87414408e-02 1.72361732e-01 5.01781464e-01 -8.52631688e-01
-6.33224547e-01 -9.64177120e-03 -8.93263519e-01 4.49267089e-01
3.49161088e-01 4.57367361e-01 -8.02827001e-01 5.07305264e-01
4.33481112e-02 -2.34125629e-01 4.53833073e-01 5.55570945e-02
4.99930978e-01 3.76208365e-01 -1.34477139e-01 -5.73289394e-01
1.06082785e+00 -1.36716676e+00 -1.35299087e+00 2.33215362e-01
9.05734658e-01 -1.07320261e+00 4.35900748e-01 5.33875942e-01
-1.55548143e+00 -1.37560293e-01 -1.08699942e+00 1.78573877e-01
-7.27255583e-01 -3.14239264e-01 8.57801437e-01 1.43120694e+00
-1.60129595e+00 9.73287821e-01 -4.91727620e-01 6.59165755e-02
1.20568443e-02 8.24621081e-01 -2.64718989e-03 4.62812334e-01
-1.33193445e+00 1.08501506e+00 2.22979754e-01 -1.21242590e-01
-1.65216476e-01 -2.13068098e-01 -8.23704481e-01 -5.63443303e-01
-4.78693932e-01 -5.29636025e-01 1.44139910e+00 -2.59346128e-01
-1.65295815e+00 9.71794367e-01 -1.42069459e-01 -1.97814897e-01
6.14786744e-01 -1.28011424e-02 -8.31891418e-01 2.42498964e-01
-1.89849049e-01 5.76383233e-01 9.28263724e-01 -1.35132408e+00
-7.59897232e-01 -1.67359829e-01 -1.23336017e-01 2.66287565e-01
-1.25510961e-01 1.89734384e-01 2.11616129e-01 -1.12999000e-01
3.27147305e-01 -7.20919967e-01 -2.53068686e-01 -5.32041907e-01
-1.46512717e-01 -7.10518599e-01 7.70373225e-01 -4.51523662e-01
1.83705616e+00 -1.67618537e+00 -2.06720144e-01 3.98590982e-01
3.57815564e-01 -1.24705513e-03 2.40583986e-01 1.08380008e+00
-2.76906848e-01 7.32199550e-01 4.11965609e-01 -1.10722095e-01
2.24991128e-01 4.85861301e-01 -4.16602850e-01 3.05609167e-01
-1.29282743e-01 1.15307164e+00 -1.16605783e+00 -5.23096442e-01
4.11106765e-01 9.42391157e-02 -4.58732933e-01 4.79237735e-01
2.99364805e-01 1.47170946e-01 -3.56553018e-01 1.39399457e+00
1.15709066e+00 -1.31984919e-01 1.45911396e-01 5.30878425e-01
-3.79135728e-01 3.55090618e-01 -6.96863770e-01 1.05554795e+00
7.08333924e-02 5.00173986e-01 1.02364108e-01 -7.94621468e-01
3.33247900e-01 8.61540735e-01 4.37155962e-01 -9.67555881e-01
-2.26398129e-02 6.92409754e-01 1.12803578e-01 -6.07703328e-01
7.58228302e-01 3.94563079e-02 -3.64872098e-01 6.40070081e-01
-2.37588286e-01 -6.59476995e-01 9.64643434e-02 3.08100313e-01
6.22585893e-01 -5.18246442e-02 5.62923312e-01 -1.05613089e+00
7.86340594e-01 -1.82965681e-01 -1.81299388e-01 1.03415680e+00
-3.09923887e-01 3.19085121e-01 2.99841821e-01 -6.65102363e-01
-6.45341039e-01 -1.12307119e+00 -4.89381433e-01 1.30636716e+00
3.24267983e-01 -4.39044595e-01 -9.54439282e-01 -2.49762803e-01
1.77620783e-01 6.89606130e-01 -5.90509653e-01 3.84124845e-01
-5.03739953e-01 -8.32535863e-01 7.39044368e-01 3.45434904e-01
-5.07752821e-02 -1.33414865e+00 -6.58416986e-01 1.25490099e-01
-2.20292807e-01 -6.63697243e-01 -6.23428151e-02 4.48765576e-01
-1.35989368e+00 -5.18594682e-01 -6.66252747e-02 -8.20914626e-01
5.87345481e-01 2.46782884e-01 1.27047324e+00 5.39230824e-01
-2.31483161e-01 4.26904231e-01 -1.21292919e-01 -4.95818377e-01
-4.59671497e-01 -8.00336525e-02 5.28869390e-01 -5.87835789e-01
5.19427478e-01 -2.50617653e-01 -7.29350567e-01 5.37953973e-01
-6.88540697e-01 1.62748516e-01 1.79803044e-01 1.04410267e+00
1.35816500e-01 -9.34035778e-02 1.22507080e-01 -6.38007045e-01
8.72274399e-01 -1.69219792e-01 -3.78732830e-01 5.77745810e-02
-6.77108407e-01 -3.74140263e-01 3.21430594e-01 -3.25342178e-01
-1.01981449e+00 -4.87835288e-01 -9.82677937e-02 2.45538145e-01
1.11353043e-02 -1.46784872e-01 6.47139177e-02 -5.24923325e-01
8.02199244e-01 9.25758183e-02 1.99174434e-02 -6.80815242e-03
3.01039815e-01 7.09525108e-01 -6.82967342e-03 -6.68678164e-01
8.44880998e-01 4.91470337e-01 7.98524171e-02 -9.57177758e-01
-1.52186140e-01 -2.60129690e-01 -9.51962709e-01 -6.54426932e-01
6.56643391e-01 -6.78531289e-01 -9.10833478e-01 3.91110867e-01
-9.38691139e-01 -3.38627815e-01 -3.91645581e-01 4.25431967e-01
-1.01278400e+00 2.75717527e-02 -3.90154392e-01 -1.27895141e+00
-5.10977268e-01 -1.02017939e+00 9.43384409e-01 5.30070923e-02
-5.10597289e-01 -1.26927447e+00 5.87685481e-02 2.71537274e-01
1.81734428e-01 -1.73075795e-01 6.90226793e-01 -2.38256708e-01
-4.24233019e-01 -1.53791070e-01 2.34436691e-02 -1.39755070e-01
1.70832314e-02 4.95917559e-01 -9.81751978e-01 -5.31145096e-01
6.65065646e-02 -1.92070693e-01 -1.08835101e-01 6.52520418e-01
5.91872573e-01 -2.29931593e-01 -8.56000841e-01 5.40386558e-01
1.38545322e+00 3.85070026e-01 5.32770038e-01 7.28214979e-01
1.41836226e-01 5.53460240e-01 9.17806149e-01 4.63203549e-01
1.30579369e-02 3.28798652e-01 2.40537539e-01 1.49327129e-01
1.11720070e-01 -1.54819340e-01 3.77893507e-01 1.16112018e+00
-8.18235934e-01 -2.69281328e-01 -5.07867396e-01 4.42987174e-01
-1.72482407e+00 -1.40330648e+00 -4.32368398e-01 6.90478683e-01
6.25676990e-01 1.56016424e-01 -1.48347050e-01 3.35214496e-01
4.99015123e-01 -2.03574806e-01 -1.19133167e-01 -1.06291151e+00
-1.43546045e-01 3.15233678e-01 7.37729073e-01 1.00061214e+00
-7.20721722e-01 1.03317809e+00 1.29781246e+01 1.02230716e+00
2.21112028e-01 1.03134915e-01 5.16071796e-01 3.48020852e-01
-4.36954498e-01 -4.56139445e-02 -1.04416132e+00 2.72933897e-02
1.38140702e+00 -4.30666685e-01 6.85999811e-01 5.44219851e-01
3.44648361e-01 -4.23268199e-01 -1.26188684e+00 5.26221812e-01
9.73738134e-02 -1.40886843e+00 -2.83300440e-04 6.85225725e-01
7.73699820e-01 -5.08050561e-01 6.22419357e-01 3.24184299e-01
6.09259963e-01 -1.14389277e+00 8.60300779e-01 2.53660440e-01
1.03040910e+00 -6.05088234e-01 5.67372203e-01 1.68872893e-01
-1.14389896e+00 -2.20873043e-01 -8.77727985e-01 -1.00755692e+00
3.93533185e-02 -1.81779593e-01 -4.29956943e-01 3.48861217e-01
9.58353162e-01 2.99398601e-01 -3.93658698e-01 9.95779395e-01
-4.78694476e-02 1.04875881e-02 -2.71853864e-01 -4.48467314e-01
4.83122796e-01 -3.54241252e-01 4.66730654e-01 1.00164843e+00
2.48499006e-01 3.51035744e-01 -9.84472036e-02 4.01770771e-01
5.45058846e-01 3.29446048e-02 -1.19659424e+00 -1.78908288e-01
2.83276141e-01 9.16795909e-01 -4.83487815e-01 -4.22520459e-01
-2.00212970e-01 8.62069130e-01 -3.55488248e-02 5.01107454e-01
-6.11489356e-01 -4.35615242e-01 9.72222984e-01 -1.27327025e-01
-1.14700586e-01 -3.48497719e-01 -6.23769283e-01 -7.30352640e-01
-5.89872956e-01 -4.54965204e-01 5.93606755e-02 -5.53365827e-01
-1.39813089e+00 5.79277515e-01 -2.27688253e-02 -1.40553558e+00
-6.99901402e-01 -1.27676582e+00 -4.76714373e-01 4.92853165e-01
-1.11898029e+00 -1.10984349e+00 2.50124663e-01 4.52870727e-01
1.64141744e-01 -5.34416080e-01 1.39563632e+00 3.57715860e-02
1.00637585e-01 9.24474537e-01 6.69434488e-01 -7.37814724e-01
5.56605101e-01 -1.27867436e+00 5.68737745e-01 -1.37897313e-01
-4.31265175e-01 9.05828118e-01 6.28349900e-01 -5.39804697e-01
-1.41196322e+00 -3.66917729e-01 1.08350635e+00 -9.83769417e-01
6.55218959e-01 -3.86345625e-01 4.23767231e-02 7.88592756e-01
7.15902448e-01 -6.18741751e-01 8.21781039e-01 -1.83753878e-01
1.80774391e-01 5.75296998e-01 -1.39248300e+00 6.12354755e-01
1.66275799e+00 -4.63594139e-01 -6.25784039e-01 7.60327101e-01
8.13696027e-01 -6.94087505e-01 -1.30082703e+00 3.34633321e-01
8.65424156e-01 -8.75409484e-01 1.61978090e+00 -1.32660246e+00
-4.43697497e-02 2.81152606e-01 -2.61993498e-01 -9.32519078e-01
-5.96193194e-01 -1.23518765e+00 -5.33532679e-01 -5.83747849e-02
5.96577883e-01 -1.13057327e+00 3.42365682e-01 8.74560475e-01
-2.82833427e-01 -6.42737269e-01 -1.06996536e+00 -1.32016802e+00
-3.35779637e-02 -1.45572275e-01 4.90409225e-01 7.63798356e-01
6.83744550e-01 1.09839931e-01 -6.36873543e-02 -1.00294888e-01
5.33176839e-01 9.55312885e-03 4.41501856e-01 -1.34294486e+00
3.86843324e-01 -5.75816095e-01 -3.07655483e-01 -9.45992947e-01
-8.85957032e-02 -8.12076271e-01 -6.53862000e-01 -1.28511906e+00
-8.32044985e-03 -1.91056758e-01 -1.11109078e-01 -1.65725678e-01
3.67937148e-01 2.13746816e-01 1.20859891e-02 1.03788137e-01
-3.71160030e-01 6.18435517e-02 1.29639816e+00 6.91750320e-05
-1.62315920e-01 4.85058486e-01 -4.81304944e-01 7.84440815e-01
8.58408585e-02 -2.99253196e-01 -6.78878546e-01 6.11881316e-02
6.69384480e-01 4.61409837e-02 3.24159935e-02 -7.42885649e-01
5.37211418e-01 -3.75702560e-01 4.78586555e-01 -1.32223868e+00
1.30741090e-01 -9.61415648e-01 6.95283338e-02 9.40189242e-01
2.74610907e-01 1.20424610e-02 8.66204947e-02 5.39500564e-02
-1.44871444e-01 -5.70943117e-01 9.21121240e-01 -4.07591403e-01
-4.92852688e-01 -5.20386267e-03 -1.03226590e+00 8.97834301e-02
9.92593169e-01 -7.84614205e-01 -3.59281451e-01 -4.20183957e-01
-8.29068601e-01 -1.95836127e-02 6.50830388e-01 3.03609259e-02
7.30431557e-01 -1.51530886e+00 -2.30721906e-01 7.18729138e-01
-3.22939813e-01 -3.74400020e-01 -1.70157343e-01 6.58265352e-01
-1.32361674e+00 1.02442718e+00 -5.41665435e-01 -4.55340147e-01
-1.14228773e+00 4.78126436e-01 4.28307921e-01 -2.41845414e-01
-2.15481281e-01 1.11954463e+00 2.71224789e-02 -8.23025763e-01
1.85185194e-01 -9.21545625e-02 -7.54407048e-01 3.55081353e-03
6.88606799e-01 1.05194807e+00 -2.91290224e-01 -6.04341030e-01
-4.56784427e-01 6.65885091e-01 2.32151806e-01 -2.87484169e-01
9.17833567e-01 -2.19243199e-01 -9.89108324e-01 4.28274393e-01
8.38715494e-01 -1.36269778e-01 -3.69319022e-02 4.16855574e-01
1.25943512e-01 -8.02164078e-01 -4.32406247e-01 -3.55811834e-01
-1.85641110e-01 5.54822803e-01 5.34874737e-01 8.99602413e-01
8.57008278e-01 -3.02566767e-01 8.18335712e-01 9.66778398e-01
5.72402716e-01 -1.68019545e+00 -2.13140488e-01 6.89524531e-01
9.12339568e-01 -9.28350806e-01 5.44190466e-01 -7.27165341e-01
-4.14997995e-01 1.32979155e+00 4.68304873e-01 -1.55325383e-01
1.27306652e+00 5.74917436e-01 1.14069022e-02 -3.70670199e-01
-9.44949508e-01 1.12705544e-01 3.75366658e-01 1.11147714e+00
5.06513238e-01 5.07374525e-01 -9.66500878e-01 3.21953118e-01
-7.28706717e-01 -2.34555230e-01 4.90474731e-01 1.41972518e+00
-6.43810987e-01 -1.20391917e+00 -7.23931909e-01 4.61561680e-01
-5.49773455e-01 -1.16372630e-01 -5.28106689e-01 8.46754074e-01
-5.76629937e-02 1.49448860e+00 -1.97535474e-03 -5.03491640e-01
4.11356747e-01 1.41089618e-01 7.21762300e-01 -1.23501487e-01
-9.04846430e-01 4.15413082e-01 3.84890139e-01 -1.23056793e+00
-8.58632207e-01 -1.05834293e+00 -1.40667629e+00 -1.19437599e+00
-5.12782812e-01 1.89310342e-01 3.83317530e-01 3.90289724e-01
-2.06836104e-01 2.85260603e-02 9.80917513e-01 -1.07949340e+00
-3.90341938e-01 -9.39418614e-01 -1.00026262e+00 -7.84516707e-02
2.89751232e-01 -8.00943017e-01 -7.83523321e-01 2.83909619e-01] | [-7.323112964630127, 3.7125136852264404] |
675f0848-b044-4018-9ee9-5e850c4924db | continual-learning-for-steganalysis | 2209.01326 | null | https://arxiv.org/abs/2209.01326v1 | https://arxiv.org/pdf/2209.01326v1.pdf | Continual Learning for Steganalysis | To detect the existing steganographic algorithms, recent steganalysis methods usually train a Convolutional Neural Network (CNN) model on the dataset consisting of corresponding paired cover/stego-images. However, it is inefficient and impractical for those steganalysis tools to completely retrain the CNN model to make it effective against both the existing steganographic algorithms and a new emerging steganographic algorithm. Thus, existing steganalysis models usually lack dynamic extensibility for new steganographic algorithms, which limits their application in real-world scenarios. To address this issue, we propose an accurate parameter importance estimation (APIE) based-continual learning scheme for steganalysis. In this scheme, when a steganalysis model is trained on the new image dataset generated by the new steganographic algorithm, its network parameters are effectively and efficiently updated with sufficient consideration of their importance evaluated in the previous training process. This approach can guide the steganalysis model to learn the patterns of the new steganographic algorithm without significantly degrading the detectability against the previous steganographic algorithms. Experimental results demonstrate the proposed scheme has promising extensibility for new emerging steganographic algorithms. | ['Zhili Zhou', 'Ruohan Meng', 'Zihao Yin'] | 2022-09-03 | null | null | null | null | ['steganalysis'] | ['computer-vision'] | [ 8.87799680e-01 -5.72063476e-02 -4.10389341e-02 2.15739816e-01
-5.17508537e-02 -3.01787615e-01 5.73288560e-01 -5.03760099e-01
-2.47002229e-01 4.84638602e-01 -4.82725888e-01 -7.12904036e-01
1.31813541e-01 -1.05066824e+00 -6.82490051e-01 -1.09239459e+00
-2.90513307e-01 2.56928414e-01 2.87756383e-01 -5.97834647e-01
5.85066557e-01 3.07413071e-01 -1.54909635e+00 7.48420879e-02
7.08846569e-01 6.45578563e-01 3.31198990e-01 1.14786208e+00
2.93176055e-01 5.71101665e-01 -6.33925498e-01 4.91729863e-02
5.42078376e-01 -8.56223404e-01 -4.87336665e-01 1.50953189e-01
4.72808480e-02 -2.86931902e-01 -6.81367636e-01 1.32339835e+00
1.45183340e-01 -3.83982092e-01 2.36308023e-01 -1.03939021e+00
-3.54411185e-01 8.98988128e-01 -4.63271320e-01 3.71257991e-01
-8.69205147e-02 6.90109670e-01 6.00272357e-01 -5.02675772e-01
4.64524806e-01 1.01946521e+00 7.64515519e-01 5.10362267e-01
-5.98380625e-01 -1.19832623e+00 -1.95071608e-01 2.79307872e-01
-1.00905263e+00 -4.48916554e-01 9.38669741e-01 -1.09827509e-02
6.67627633e-01 2.35833108e-01 9.80604768e-01 7.86600649e-01
2.75838614e-01 5.45663357e-01 9.29128289e-01 -4.29901272e-01
-2.17131823e-01 7.94702321e-02 -4.59736884e-01 1.01685286e+00
5.52862406e-01 7.52922595e-01 1.92260906e-01 1.20365821e-01
7.70021319e-01 -2.66927443e-02 -2.98331678e-01 -3.99897635e-01
-1.21919608e+00 8.61719608e-01 2.85863131e-01 6.91494167e-01
-1.10627614e-01 4.65295941e-01 2.90463537e-01 9.40211177e-01
1.59389824e-01 6.60072565e-01 -1.89132318e-01 2.77985424e-01
-9.60739136e-01 -7.51168355e-02 6.67716742e-01 5.85492074e-01
1.01709032e+00 6.04172766e-01 6.09593153e-01 1.64268941e-01
4.07204121e-01 6.06705368e-01 4.71529871e-01 -3.70024741e-01
4.56007481e-01 6.14345610e-01 -3.21884543e-01 -1.63512206e+00
-5.87363504e-02 -5.99500239e-01 -1.14251733e+00 1.08230315e-01
1.92376792e-01 -2.79008076e-02 -1.08058691e+00 1.15338027e+00
2.74695814e-01 7.30392694e-01 1.97712898e-01 2.41778970e-01
4.84954774e-01 1.04846811e+00 -3.29618931e-01 -3.29857588e-01
9.35217202e-01 -8.16175163e-01 -4.54252452e-01 -4.80725825e-01
9.61509824e-01 -7.49960124e-01 4.42051649e-01 3.37659836e-01
-8.13491940e-01 -7.17783868e-01 -1.58968079e+00 9.07395065e-01
-3.64835083e-01 -3.52011740e-01 3.74313235e-01 1.04275370e+00
-1.01052094e+00 5.82462847e-01 -5.18999815e-01 -2.37851351e-01
3.69821459e-01 7.58865297e-01 -1.06024548e-01 -2.89570302e-01
-1.67676020e+00 7.25737631e-01 1.36573684e+00 1.23633854e-01
-1.29877996e+00 -1.69191465e-01 -7.43641078e-01 1.41255781e-01
4.23971146e-01 -2.03608014e-02 8.74798596e-01 -1.45164204e+00
-1.39868331e+00 6.33328974e-01 5.73596478e-01 -5.39793551e-01
4.70982671e-01 6.90387130e-01 -9.53830659e-01 1.81998774e-01
-4.07849759e-01 2.03189403e-01 1.70183408e+00 -1.26644504e+00
-1.01005542e+00 1.59778297e-01 -2.61276156e-01 -5.33908010e-02
-3.51527125e-01 -2.58578598e-01 -3.31473291e-01 -5.04944444e-01
2.64446259e-01 -1.00901604e+00 -1.94942862e-01 -4.36628461e-01
-1.81068987e-01 1.84685782e-01 1.60914457e+00 -5.71848214e-01
1.37355185e+00 -2.05900359e+00 -2.24918008e-01 7.54344344e-01
2.66940266e-01 1.18699849e+00 -3.35650980e-01 3.21239144e-01
-2.92763591e-01 2.70107925e-01 -1.13457546e-01 4.72630978e-01
-5.62563837e-01 -1.15035288e-02 1.01768292e-01 6.90310478e-01
-2.18795165e-02 8.74953687e-01 -1.04460824e+00 -5.08509636e-01
4.88344282e-01 2.51756757e-01 -3.92357558e-01 1.25884995e-01
-5.97284622e-02 6.08069181e-01 -6.28031790e-01 4.71892536e-01
9.12496984e-01 -5.13847649e-01 8.07981312e-01 -3.50514404e-03
1.09073609e-01 -1.70580059e-01 -1.07934749e+00 7.68301845e-01
-4.00939822e-01 6.78971291e-01 -2.50715792e-01 -1.31737256e+00
1.09926260e+00 4.38327491e-01 3.61212492e-01 -5.29476345e-01
4.71816599e-01 6.20265365e-01 4.17517722e-01 -6.41198099e-01
3.48444223e-01 1.49049014e-01 2.67639160e-02 7.14122713e-01
-6.71240389e-02 -2.96812952e-02 1.19215913e-01 -1.99007004e-01
9.76936579e-01 -2.91210145e-01 6.18027925e-01 2.76272427e-02
1.08248854e+00 -1.11761302e-01 1.82094112e-01 1.11662912e+00
-1.37745798e-01 -3.34329456e-02 1.70561984e-01 -9.02284503e-01
-1.57408345e+00 -1.52064532e-01 3.14968973e-01 7.65617967e-01
3.39085400e-01 7.15538040e-02 -7.61442482e-01 -8.85759890e-01
-6.41884744e-01 1.98942706e-01 -5.91989934e-01 -5.80716848e-01
-1.08257413e+00 -7.93592811e-01 8.41920495e-01 -2.31123820e-01
1.42444026e+00 -1.29867899e+00 -5.82780302e-01 5.69320142e-01
-1.27781540e-01 -7.07770824e-01 -1.95118085e-01 -2.68210918e-01
-8.54634404e-01 -1.44911253e+00 -5.42079449e-01 -1.35067105e+00
7.51594424e-01 5.79047203e-01 4.74784911e-01 9.58935261e-01
2.12778628e-01 -3.22604388e-01 -5.15281141e-01 -6.09519891e-02
-1.54823458e+00 3.28556597e-01 -1.96396783e-01 1.61932588e-01
2.31197014e-01 -3.36994678e-01 -6.15567029e-01 5.33175707e-01
-1.09267473e+00 1.13337196e-01 8.89684618e-01 9.61742878e-01
-3.82824913e-02 8.87133360e-01 2.18190655e-01 -1.10539329e+00
1.93393022e-01 -6.25850379e-01 -7.77159870e-01 3.92929435e-01
-1.15179312e+00 -1.00271860e-02 7.31799662e-01 -7.24301457e-01
-7.54427910e-01 -2.49633014e-01 -7.38695413e-02 -3.21980655e-01
1.38563499e-01 5.74222386e-01 -1.69238344e-01 -6.48829699e-01
4.87938464e-01 8.90260875e-01 2.88763702e-01 8.45696852e-02
-2.05163240e-01 5.92011034e-01 3.83083612e-01 3.88770789e-01
1.63182354e+00 2.98602611e-01 5.29915132e-02 -7.35034227e-01
-1.38217494e-01 -3.73663306e-01 -2.17278063e-01 -2.89739847e-01
3.96340907e-01 -5.47297955e-01 -5.63320458e-01 1.15602839e+00
-1.00208020e+00 -7.41837695e-02 3.54358613e-01 1.90091074e-01
-1.14840776e-01 7.18178213e-01 -1.84600085e-01 -4.52179760e-01
-1.94982708e-01 -1.28687453e+00 2.72343665e-01 1.07616941e-02
1.63358629e-01 -1.37473202e+00 1.60448272e-02 1.52520195e-01
6.07943773e-01 4.29199606e-01 7.78643548e-01 -9.01832998e-01
-7.19322979e-01 -6.56052053e-01 -2.59278893e-01 4.95618582e-01
3.66907656e-01 -1.00479044e-01 -5.94151020e-01 -8.66906583e-01
3.16495866e-01 -3.74489762e-02 9.81308639e-01 1.02144793e-01
1.01710343e+00 -8.16153467e-01 -4.87130076e-01 9.48912680e-01
1.60452986e+00 6.57787442e-01 9.91268873e-01 7.23397613e-01
7.58944154e-01 2.90792495e-01 3.73499751e-01 1.58531800e-01
-7.77660608e-02 -5.86736016e-03 6.20104373e-01 -1.75508991e-01
2.32949555e-01 -2.88174957e-01 3.90241951e-01 8.89619708e-01
-1.86442330e-01 -8.80537152e-01 -8.72496247e-01 3.21128845e-01
-1.36821651e+00 -1.17123377e+00 1.18931025e-01 1.84665871e+00
4.22758788e-01 4.01955813e-01 -4.32108611e-01 6.00307584e-01
1.29569995e+00 7.87655532e-01 -4.93982553e-01 -3.35196584e-01
-9.48891491e-02 1.76587746e-01 8.31489325e-01 2.35367626e-01
-1.28153944e+00 1.05651522e+00 6.07223749e+00 1.01425135e+00
-1.40177715e+00 6.67110085e-02 4.56855386e-01 6.64480567e-01
-1.68259963e-01 1.57735407e-01 -4.56133187e-01 5.72865784e-01
9.90605414e-01 2.13450138e-02 4.04627770e-01 6.43491328e-01
-2.31176689e-02 8.90134722e-02 -4.79756951e-01 9.09143627e-01
2.78425813e-01 -1.61935401e+00 1.97645292e-01 2.71307856e-01
1.11198139e+00 -2.04219207e-01 3.77661288e-01 1.26241207e-01
3.01999301e-01 -8.57699513e-01 4.38251346e-02 -3.34956981e-02
1.11607444e+00 -8.03755879e-01 1.09050274e+00 2.19936267e-01
-1.11147404e+00 -3.33251238e-01 -2.84191638e-01 2.89377183e-01
-2.17018187e-01 -5.38255386e-02 -1.41626167e+00 2.43707076e-01
4.02633727e-01 7.02722430e-01 -3.90303195e-01 6.99685812e-01
-2.86900014e-01 9.97908771e-01 -3.58323418e-02 -1.24314614e-01
7.66781509e-01 2.86580235e-01 8.14897954e-01 8.30760539e-01
7.68071890e-01 -9.75512639e-02 -1.15465991e-01 3.38218689e-01
-9.08637792e-02 -2.07029879e-01 -7.79567122e-01 -4.22758549e-01
4.51889366e-01 8.77047420e-01 -9.29928064e-01 -5.27470827e-01
-9.66358036e-02 5.84965348e-01 -4.11586702e-01 1.45225883e-01
-6.71389163e-01 -4.48256761e-01 5.14082797e-02 1.56125203e-01
7.52053082e-01 6.31210878e-02 1.78371295e-01 -1.01613033e+00
-6.95652485e-01 -1.60364711e+00 3.29032183e-01 -2.17074633e-01
-5.03574133e-01 5.98996282e-01 -3.14784408e-01 -1.58394456e+00
-3.97967011e-01 -3.61321986e-01 -8.02389503e-01 4.14149553e-01
-1.43003166e+00 -1.34060931e+00 -2.48011410e-01 6.01168811e-01
5.56990862e-01 -8.14929128e-01 3.76606256e-01 -8.31442028e-02
-4.35335457e-01 6.77762747e-01 4.34228599e-01 2.82887489e-01
2.79305935e-01 -3.53685528e-01 7.63748050e-01 1.36964917e+00
-4.14895773e-01 2.23516002e-01 1.04816723e+00 -9.05301630e-01
-1.29946744e+00 -1.18232608e+00 5.75360417e-01 1.14499167e-01
6.56138003e-01 7.40093961e-02 -9.39919949e-01 7.06259966e-01
-4.55897637e-02 -2.60930747e-01 1.55781731e-01 -5.25707781e-01
-3.15545827e-01 4.43348326e-02 -1.21604478e+00 5.05099595e-01
6.82456970e-01 -1.20133273e-01 -2.60952085e-01 3.70743312e-02
4.85591829e-01 -1.43272057e-01 -2.96526372e-01 4.75195408e-01
6.37134731e-01 -8.41471195e-01 8.20161760e-01 -2.20219657e-01
4.27893996e-01 -1.95887461e-01 1.73869476e-01 -1.17564523e+00
-2.87929744e-01 -8.80630374e-01 -4.36294287e-01 3.86890471e-01
1.25997424e-01 -9.31325376e-01 9.70136225e-01 -5.07673502e-01
2.46600479e-01 -2.91481376e-01 -7.26795137e-01 -6.52536035e-01
-2.17533723e-01 -8.46890286e-02 1.09219670e+00 1.24652433e+00
-4.26898301e-01 -3.23894888e-01 -1.03487194e+00 5.05782545e-01
8.59780014e-01 -2.78840601e-01 8.75213087e-01 -1.07969189e+00
-1.93763196e-01 -4.96930569e-01 -5.49930096e-01 -7.71356106e-01
-2.72418708e-01 -6.55084074e-01 9.15421396e-02 -7.45793581e-01
-1.21917136e-01 -7.50835001e-01 -5.43787897e-01 2.87168980e-01
-9.72692594e-02 5.76926768e-01 -1.59792289e-01 5.51229715e-01
-4.51505959e-01 -3.15137804e-02 1.47580290e+00 -4.41433340e-01
-2.61953920e-01 2.24802375e-01 -4.85670984e-01 5.93681335e-01
1.16664565e+00 -8.45054746e-01 -4.72654819e-01 -1.25629529e-01
4.61452335e-01 1.40308514e-01 4.28744942e-01 -1.39567864e+00
2.21706897e-01 -2.81965375e-01 1.98622391e-01 -4.20658708e-01
-3.28366250e-01 -8.49611938e-01 5.62208593e-01 1.46978927e+00
-8.64935294e-03 -3.30090016e-01 -1.28933415e-01 7.27207005e-01
-7.06317127e-02 -2.75171340e-01 1.06140304e+00 -4.14909482e-01
-1.21586585e+00 6.51439965e-01 -7.58091509e-01 -3.93134564e-01
1.03972030e+00 -1.07515931e+00 1.13207132e-01 -3.82501453e-01
-3.46696973e-01 -4.03200239e-02 4.85969663e-01 3.24936658e-01
9.92669582e-01 -9.61992562e-01 -8.91710699e-01 8.53567839e-01
1.53379336e-01 -4.65876937e-01 3.77956182e-01 5.72741985e-01
-1.13313425e+00 3.84353340e-01 -6.00426197e-01 -4.07534003e-01
-1.40865386e+00 7.39717066e-01 5.21032631e-01 -7.14623690e-01
-3.75944376e-01 6.07501686e-01 -3.68007235e-02 -1.93685085e-01
-2.01085865e-01 2.10953847e-01 -5.22880495e-01 -3.15197617e-01
5.30110836e-01 2.65754819e-01 -2.19557166e-01 -6.10959113e-01
1.12526357e-01 4.23191935e-01 -4.62987244e-01 3.91669005e-01
1.23573458e+00 -3.79004240e-01 -1.53437391e-01 -1.58617467e-01
1.34386098e+00 -4.25668240e-01 -1.05841494e+00 -4.77834165e-01
-1.74870715e-01 -4.53224808e-01 4.51729633e-02 -3.61397326e-01
-1.39241910e+00 6.72534943e-01 8.71357799e-01 4.52809185e-01
1.15036011e+00 -4.86455113e-01 1.12618959e+00 6.51228428e-01
4.97961968e-01 -1.00896847e+00 2.90797800e-01 5.64032972e-01
2.85034060e-01 -1.34528923e+00 -2.89291851e-02 -3.88273560e-02
-3.32414769e-02 1.39635360e+00 5.08423746e-01 -3.93886894e-01
7.10268915e-01 -1.92418277e-01 -3.58006023e-02 -5.07746756e-01
-3.26470077e-01 2.81579942e-01 -2.61380058e-02 6.49068356e-01
-4.14359927e-01 -2.22338900e-01 6.36784956e-02 -5.64761460e-01
-6.50537685e-02 -1.47260532e-01 5.96664011e-01 8.72251987e-01
-8.99951756e-01 -1.00737870e+00 -5.25425971e-01 3.40287238e-01
-3.34475338e-01 -1.27781093e-01 5.92240840e-02 1.16785240e+00
4.24544007e-01 7.56470919e-01 2.15888973e-02 -9.24345851e-01
-4.42006916e-01 -3.97089869e-01 1.32317305e-01 -3.19828153e-01
-4.47211385e-01 -5.39954342e-02 -2.42071673e-01 -1.14790827e-01
-6.39855742e-01 -2.93346554e-01 -5.62290370e-01 -8.58001292e-01
-6.67390287e-01 2.40429446e-01 4.87079501e-01 1.08585453e+00
-1.40704140e-01 4.31711167e-01 1.31344509e+00 -6.01812303e-01
-3.94275248e-01 -8.03218663e-01 -3.75915259e-01 2.21950665e-01
5.86606503e-01 -1.97594389e-01 -7.12203562e-01 -1.63698830e-02] | [4.247128486633301, 8.111858367919922] |
63c6b5ef-fed2-409a-bf96-b76586856cfd | sparse-representation-based-open-set | 1705.02431 | null | http://arxiv.org/abs/1705.02431v1 | http://arxiv.org/pdf/1705.02431v1.pdf | Sparse Representation-based Open Set Recognition | We propose a generalized Sparse Representation- based Classification (SRC)
algorithm for open set recognition where not all classes presented during
testing are known during training. The SRC algorithm uses class reconstruction
errors for classification. As most of the discriminative information for open
set recognition is hidden in the tail part of the matched and sum of
non-matched reconstruction error distributions, we model the tail of those two
error distributions using the statistical Extreme Value Theory (EVT). Then we
simplify the open set recognition problem into a set of hypothesis testing
problems. The confidence scores corresponding to the tail distributions of a
novel test sample are then fused to determine its identity. The effectiveness
of the proposed method is demonstrated using four publicly available image and
object classification datasets and it is shown that this method can perform
significantly better than many competitive open set recognition algorithms.
Code is public available: https://github.com/hezhangsprinter/SROSR | ['He Zhang', 'Vishal M. Patel'] | 2017-05-06 | null | null | null | null | ['sparse-representation-based-classification'] | ['computer-vision'] | [ 2.72072136e-01 -8.78115818e-02 -3.39737028e-01 -4.66011256e-01
-1.13800669e+00 -7.63845623e-01 3.67448404e-02 3.47089842e-02
2.29327738e-01 8.35138619e-01 -1.83431447e-01 -1.70186356e-01
-1.59835279e-01 -7.54390419e-01 -9.19716299e-01 -6.46260738e-01
2.20101476e-02 5.52378774e-01 -1.54851094e-01 2.50463396e-01
3.18150461e-01 3.59901428e-01 -2.16876364e+00 5.12446105e-01
1.06872225e+00 1.43684697e+00 -1.85100049e-01 5.16722381e-01
-1.96709335e-01 3.26379806e-01 -4.92485136e-01 3.99765279e-03
8.03945243e-01 -2.54607469e-01 -7.30981946e-01 4.47757579e-02
7.23264277e-01 -3.58794592e-02 -3.71588916e-01 1.36876881e+00
4.14590150e-01 2.04610452e-01 9.97559071e-01 -1.27090228e+00
-8.37464392e-01 2.25654647e-01 -4.38476056e-01 4.76953894e-01
5.20004034e-01 -3.17888319e-01 1.04935491e+00 -1.12843502e+00
5.47164679e-01 6.35995805e-01 6.52917206e-01 1.86979771e-01
-1.34260881e+00 -8.42307627e-01 -2.79435933e-01 4.55684215e-01
-1.82098460e+00 -3.42194736e-01 5.29138446e-01 -6.80851102e-01
5.03674269e-01 4.51276302e-01 5.71180224e-01 8.98539901e-01
1.20254278e-01 8.15690994e-01 1.27490199e+00 -3.87289882e-01
4.52833354e-01 3.29315066e-01 7.29033113e-01 6.09678268e-01
5.66225767e-01 3.33078325e-01 -1.15206093e-01 -5.67092836e-01
6.08453214e-01 4.42195892e-01 -6.55095100e-01 -5.11610448e-01
-8.66267204e-01 8.20913851e-01 3.90576154e-01 1.60182551e-01
-2.32148126e-01 -3.89616370e-01 8.09015557e-02 6.06835127e-01
3.08831006e-01 4.93053198e-02 -3.54416549e-01 2.15874463e-01
-9.60319042e-01 -9.93822962e-02 9.16636944e-01 9.57708240e-01
9.11526561e-01 -1.65994450e-01 -1.92485392e-01 1.06757843e+00
5.14180899e-01 4.19855088e-01 5.81323683e-01 -6.34937644e-01
2.43472502e-01 5.97027779e-01 -2.48614490e-01 -8.13922405e-01
2.02600315e-01 -6.10768020e-01 -6.30418956e-01 1.65224463e-01
4.41060841e-01 1.14179291e-01 -9.40096557e-01 1.26524627e+00
4.75539654e-01 6.56350017e-01 2.97244459e-01 7.82726586e-01
9.98867095e-01 7.40696013e-01 -6.30859196e-01 -2.40783244e-01
1.04761600e+00 -6.12832427e-01 -3.14723015e-01 8.49884823e-02
6.33669913e-01 -4.64750975e-01 5.17211556e-01 3.02178264e-01
-4.80253637e-01 -3.48303467e-01 -1.22141933e+00 2.13837907e-01
-1.70983359e-01 1.20184496e-01 4.73314255e-01 6.16367042e-01
-4.44761872e-01 4.47524369e-01 -4.62281913e-01 1.42980432e-02
8.33527923e-01 4.69496727e-01 -7.24367023e-01 -5.22091508e-01
-7.78412282e-01 1.39554858e-01 1.39991745e-01 -1.65648237e-02
-6.27218902e-01 -6.13115847e-01 -1.01644039e+00 1.43611163e-01
5.85982613e-02 -3.09947282e-01 7.79353261e-01 -9.70464826e-01
-9.71434534e-01 1.02001679e+00 -2.06082135e-01 -2.74466306e-01
1.69462115e-01 1.14221081e-01 -3.32010776e-01 5.42466603e-02
1.63156062e-01 7.55135715e-02 9.25320685e-01 -1.23834836e+00
-2.79205620e-01 -6.94776893e-01 -6.04272842e-01 -1.58239469e-01
-1.11115590e-01 -6.19862135e-03 -4.26162556e-02 -7.27077365e-01
7.92933166e-01 -8.24438274e-01 -7.90175498e-02 2.70489842e-01
-3.12139273e-01 -2.86122888e-01 7.58857012e-01 -5.92626572e-01
1.03557622e+00 -2.31283402e+00 -5.81882037e-02 7.78349757e-01
2.83156276e-01 1.02351300e-01 -5.91277815e-02 1.40482143e-01
-5.00831306e-01 -1.91447511e-01 -3.79556745e-01 1.61390826e-01
-2.23833993e-01 2.38705128e-01 -4.88103956e-01 8.71556997e-01
-2.60766298e-01 5.43898821e-01 -4.55629736e-01 -3.08377326e-01
-4.30758633e-02 2.16124907e-01 -3.98938537e-01 1.91380903e-01
6.90796673e-02 2.19457194e-01 -4.02491242e-01 9.56668377e-01
9.62912142e-01 -4.23970789e-01 -1.03061259e-01 2.04359055e-01
2.19298348e-01 -1.56245753e-01 -1.57005882e+00 1.24670708e+00
1.30013585e-01 4.00158495e-01 -2.48262018e-01 -1.08609629e+00
1.26312912e+00 2.92074025e-01 4.84415025e-01 -1.91117823e-01
3.77511621e-01 4.83737648e-01 -5.26099056e-02 -1.61541030e-01
-6.12134412e-02 3.22948769e-02 1.77721128e-01 3.69116873e-01
3.06810409e-01 2.59978503e-01 -6.99996874e-02 -1.49124160e-01
1.03656280e+00 -3.14639568e-01 3.66195649e-01 -2.36627147e-01
5.52163184e-01 -1.26264483e-01 9.30026948e-01 7.44196892e-01
-2.89157659e-01 9.36369777e-01 3.39422196e-01 -3.79368275e-01
-9.04217601e-01 -1.29840827e+00 -8.30706954e-01 3.17502588e-01
1.45800546e-01 -1.59281969e-01 -4.94167536e-01 -8.89578044e-01
4.28509653e-01 4.42237526e-01 -6.16580606e-01 -1.41603291e-01
9.62968245e-02 -3.13878298e-01 3.52452993e-01 5.50529122e-01
1.96120963e-01 -5.50931692e-01 4.46968637e-02 -3.36526185e-01
-1.26620932e-02 -7.27191389e-01 -4.47953343e-01 2.06915379e-01
-9.08074975e-01 -1.41954529e+00 -7.24470317e-01 -1.15019512e+00
9.30571675e-01 3.35049421e-01 5.26904464e-01 3.71048190e-02
-5.54798186e-01 3.19048494e-01 -5.16808689e-01 -2.09559247e-01
-2.13254496e-01 -6.30222440e-01 2.76301920e-01 3.74979615e-01
3.96916449e-01 -4.50807959e-01 -2.38928869e-01 6.01812601e-01
-5.37228167e-01 -5.22502422e-01 2.91682780e-01 1.20700192e+00
1.24874413e+00 2.45774332e-02 4.26487654e-01 -5.95357656e-01
1.90359857e-02 -7.48615384e-01 -8.24532628e-01 3.26525152e-01
-5.17089367e-01 -5.68379723e-02 2.65702248e-01 -5.79139769e-01
-6.17073655e-01 2.57815793e-02 8.39463156e-03 -1.00097215e+00
-2.37262636e-01 3.46385092e-01 -8.03595632e-02 -4.01593983e-01
6.95512652e-01 4.26520646e-01 2.70419866e-01 -4.62119222e-01
-2.42065907e-01 1.22693181e+00 2.76426166e-01 -5.02447963e-01
7.53323317e-01 4.41150457e-01 -1.22184023e-01 -9.25979197e-01
-1.04388571e+00 -8.10181141e-01 -2.78473139e-01 -1.37631670e-01
4.28712279e-01 -1.02825499e+00 -4.22255188e-01 3.11603040e-01
-6.62623227e-01 1.21443100e-01 -6.33875787e-01 7.53615320e-01
-6.38771117e-01 6.08668983e-01 -2.60837734e-01 -8.29263330e-01
-3.29609543e-01 -1.17653000e+00 8.79379749e-01 2.98983365e-01
9.56189036e-02 -6.37929916e-01 3.46968085e-01 7.17572391e-01
-2.61283845e-01 1.00551523e-01 5.97029924e-01 -1.35767555e+00
-4.92371440e-01 -7.79905260e-01 -6.01509064e-02 6.16619825e-01
-2.37490252e-01 -1.78080603e-01 -7.97879219e-01 -4.81780350e-01
1.51446521e-01 -4.70756859e-01 8.48279536e-01 2.21172661e-01
1.37225187e+00 -3.02372932e-01 -4.26302671e-01 8.44192982e-01
1.46885550e+00 -7.47174323e-02 9.37432826e-01 3.92638482e-02
4.42188561e-01 2.92030632e-01 5.96109807e-01 7.17496634e-01
-6.94364533e-02 4.96154457e-01 -1.68684628e-02 2.95925766e-01
5.84878772e-02 -1.57701924e-01 4.01481956e-01 4.83493239e-01
2.78952390e-01 4.36344817e-02 -1.04391873e+00 3.44073564e-01
-1.77089882e+00 -1.30219471e+00 -3.92686754e-01 2.66074276e+00
5.31673372e-01 -2.69760042e-01 -2.21504271e-01 4.16549772e-01
1.04915166e+00 -3.32511723e-01 -5.78626752e-01 -1.93750486e-01
-2.96351641e-01 4.26770031e-01 2.10499793e-01 1.18545704e-01
-9.86945748e-01 3.25882137e-01 6.43877459e+00 8.84253442e-01
-6.78602993e-01 -3.82101052e-02 5.31763196e-01 9.97039750e-02
-2.75871247e-01 1.76188841e-01 -8.72967362e-01 5.03170073e-01
6.13921404e-01 -9.68332589e-02 2.25704566e-01 9.86745834e-01
-4.93916899e-01 -8.92074779e-02 -1.27985346e+00 1.46376395e+00
4.25688386e-01 -1.28304076e+00 -5.29693365e-02 3.04859728e-01
9.65651333e-01 2.68634290e-01 7.18342662e-02 4.30247068e-01
-7.15170205e-02 -9.94866073e-01 5.19827306e-01 6.75367296e-01
8.08607280e-01 -4.19033498e-01 8.84985983e-01 3.40660095e-01
-1.06378794e+00 -4.22460586e-01 -4.88852143e-01 -4.01637442e-02
-5.93593895e-01 6.96733534e-01 -5.39468765e-01 2.91717052e-01
7.45698333e-01 6.56872571e-01 -4.42785650e-01 1.55722737e+00
-6.47118613e-02 7.10765898e-01 -6.16358578e-01 2.80363888e-01
-4.80082184e-01 -4.56843376e-01 8.17610204e-01 3.90338361e-01
4.33934689e-01 2.03300431e-01 4.30257410e-01 1.02129912e+00
-1.70976177e-01 2.32539713e-01 -8.04491758e-01 -1.76832870e-01
5.79774320e-01 8.12332153e-01 -5.14645040e-01 -1.81534588e-01
-6.77425086e-01 9.24981534e-01 4.43581134e-01 2.22509444e-01
-6.20126724e-01 -4.31956708e-01 7.32758462e-01 -1.40189484e-01
6.96970522e-01 1.83518559e-01 -4.43985879e-01 -1.57062519e+00
2.74230003e-01 -8.41394544e-01 9.73349214e-01 -5.45873165e-01
-1.61024010e+00 1.79208040e-01 -3.22557956e-01 -1.52338135e+00
2.65594274e-01 -6.84333503e-01 -6.36705637e-01 6.54807448e-01
-1.11014175e+00 -6.40631318e-01 -8.78280550e-02 6.40066683e-01
3.67865533e-01 -3.86555165e-01 9.01417494e-01 1.85362965e-01
-7.13634551e-01 9.56777692e-01 7.64712453e-01 4.39868152e-01
3.79975557e-01 -8.66113544e-01 -2.32051209e-01 6.95800841e-01
4.52244759e-01 3.27926725e-01 4.11222607e-01 -7.12258458e-01
-1.36784375e+00 -9.15571570e-01 5.44635952e-01 -4.79564697e-01
4.46384758e-01 -1.67852461e-01 -1.06988299e+00 6.63159847e-01
-4.81717348e-01 8.53741527e-01 1.15755343e+00 5.56245372e-02
-7.74523318e-01 -2.29980126e-02 -1.45287001e+00 -1.02904186e-01
7.38916516e-01 -4.50298220e-01 -9.31231081e-01 3.75862569e-01
2.44739801e-01 -2.44837686e-01 -1.21231520e+00 5.97597599e-01
5.39235771e-01 -7.51466513e-01 8.60197484e-01 -5.70500910e-01
2.49769107e-01 -4.65916693e-01 -8.40416968e-01 -8.47841382e-01
-2.50363350e-01 -1.73333362e-01 -3.35418493e-01 1.03662121e+00
3.68126661e-01 -1.00274324e+00 8.32574189e-01 1.64572686e-01
-5.52156307e-02 -9.89320636e-01 -1.28606188e+00 -1.00285769e+00
-1.11180227e-02 -2.35483438e-01 2.97147661e-01 9.78685439e-01
2.33907551e-01 -9.56194475e-03 1.49206504e-01 5.48099697e-01
9.18176949e-01 8.23269725e-01 5.22888601e-01 -1.63126230e+00
-5.50356030e-01 -6.71535684e-03 -1.17626822e+00 -6.82141721e-01
4.00754452e-01 -1.45419741e+00 -7.19643235e-02 -1.16202736e+00
5.34213006e-01 -5.40111899e-01 -5.25697947e-01 5.46962798e-01
6.41985536e-02 3.23940098e-01 -1.68091089e-01 5.10906100e-01
-4.72697437e-01 7.39569545e-01 8.68852675e-01 -1.61482975e-01
-1.39204070e-01 2.84171283e-01 -5.23626089e-01 4.64989334e-01
6.22337759e-01 -5.95378518e-01 -3.64085510e-02 2.77385592e-01
-1.77794099e-01 2.34030694e-01 4.23385382e-01 -1.32785964e+00
1.96120236e-02 9.36174616e-02 7.38220572e-01 -5.69167852e-01
-2.84982696e-02 -8.50923836e-01 2.55021185e-01 4.10680592e-01
-1.56832367e-01 -5.67900658e-01 -2.28153709e-02 9.12759602e-01
-2.70244896e-01 -3.78926754e-01 9.14644301e-01 2.91967303e-01
-4.55315828e-01 6.31893873e-01 -1.71126410e-01 8.86899158e-02
1.46239638e+00 -6.60987914e-01 -1.54411703e-01 5.50751835e-02
-7.30026603e-01 2.59712517e-01 5.16254187e-01 2.33520687e-01
1.01390302e+00 -1.37312388e+00 -6.27815068e-01 7.59969294e-01
6.99039519e-01 -1.80556178e-01 3.61695677e-01 8.42863500e-01
-2.08279520e-01 1.14216484e-01 -6.45488277e-02 -8.01194251e-01
-1.44955885e+00 5.49699843e-01 3.35226536e-01 2.24535972e-01
-7.47968674e-01 1.01507437e+00 -1.19884554e-02 -6.87493086e-01
3.25717241e-01 1.10893801e-01 -1.48355573e-01 -2.16015801e-01
5.85940778e-01 4.28620130e-01 9.98262987e-02 -7.92069972e-01
-3.24854016e-01 5.85093677e-01 -1.48545504e-01 3.43926132e-01
1.37819779e+00 1.79313406e-01 -1.48068681e-01 5.20131171e-01
1.50930226e+00 -1.24359973e-01 -8.05018783e-01 -3.61134917e-01
-4.39836770e-01 -7.18799889e-01 2.53502190e-01 -5.28657734e-01
-6.87395573e-01 4.77644652e-01 9.50345337e-01 -2.00791657e-01
8.61948311e-01 3.83646905e-01 6.54221594e-01 4.87940222e-01
5.99168658e-01 -9.37027156e-01 -2.88471550e-01 5.52060962e-01
8.10837388e-01 -1.36330950e+00 -3.99818681e-02 -6.90195799e-01
-1.51157290e-01 1.04231715e+00 5.01344025e-01 -3.94075096e-01
9.57973361e-01 6.01438694e-02 -1.79079726e-01 -1.37093231e-01
-6.16783798e-01 -9.04765800e-02 5.14045537e-01 5.66285968e-01
2.18643714e-02 1.63027495e-01 -1.21373795e-01 8.21320295e-01
-1.01882689e-01 -1.51174888e-01 3.50969464e-01 1.04831493e+00
-5.58020055e-01 -7.91215658e-01 -8.43594790e-01 1.05139256e+00
-1.69442624e-01 5.30507527e-02 -3.08076918e-01 4.62448671e-02
2.86215097e-02 7.22632766e-01 1.76954538e-01 -4.90640789e-01
-9.15012974e-03 3.49269003e-01 5.64743757e-01 -7.67933190e-01
-1.04681514e-01 -3.54064703e-01 -1.61465526e-01 -5.74926078e-01
2.24158496e-01 -1.01807106e+00 -1.36652565e+00 -7.47854495e-03
-8.98876250e-01 3.92842680e-01 5.09027123e-01 7.52237320e-01
5.21162331e-01 6.89628571e-02 1.02882171e+00 -4.12485927e-01
-1.08741534e+00 -5.88580728e-01 -9.19615448e-01 3.63551885e-01
2.55674660e-01 -1.01513028e+00 -7.35857785e-01 -3.70950222e-01] | [9.683723449707031, 2.934019088745117] |
bcc7ec7e-3f16-43ce-9108-29a2a385bbd5 | deep-learning-based-electroencephalography | 1901.05498 | null | http://arxiv.org/abs/1901.05498v2 | http://arxiv.org/pdf/1901.05498v2.pdf | Deep learning-based electroencephalography analysis: a systematic review | Electroencephalography (EEG) is a complex signal and can require several
years of training to be correctly interpreted. Recently, deep learning (DL) has
shown great promise in helping make sense of EEG signals due to its capacity to
learn good feature representations from raw data. Whether DL truly presents
advantages as compared to more traditional EEG processing approaches, however,
remains an open question. In this work, we review 156 papers that apply DL to
EEG, published between January 2010 and July 2018, and spanning different
application domains such as epilepsy, sleep, brain-computer interfacing, and
cognitive and affective monitoring. We extract trends and highlight interesting
approaches in order to inform future research and formulate recommendations.
Various data items were extracted for each study pertaining to 1) the data, 2)
the preprocessing methodology, 3) the DL design choices, 4) the results, and 5)
the reproducibility of the experiments. Our analysis reveals that the amount of
EEG data used across studies varies from less than ten minutes to thousands of
hours. As for the model, 40% of the studies used convolutional neural networks
(CNNs), while 14% used recurrent neural networks (RNNs), most often with a
total of 3 to 10 layers. Moreover, almost one-half of the studies trained their
models on raw or preprocessed EEG time series. Finally, the median gain in
accuracy of DL approaches over traditional baselines was 5.4% across all
relevant studies. More importantly, however, we noticed studies often suffer
from poor reproducibility: a majority of papers would be hard or impossible to
reproduce given the unavailability of their data and code. To help the field
progress, we provide a list of recommendations for future studies and we make
our summary table of DL and EEG papers available and invite the community to
contribute. | ['Jocelyn Faubert', 'Alexandre Gramfort', 'Tiago H. Falk', 'Hubert Banville', 'Yannick Roy', 'Isabela Albuquerque'] | 2019-01-16 | null | null | null | null | ['brain-decoding', 'brain-decoding'] | ['medical', 'miscellaneous'] | [-9.88869891e-02 -2.34362349e-01 1.21400133e-01 -4.48749810e-01
-5.17593384e-01 -4.80284929e-01 2.99997807e-01 1.51481614e-01
-5.96827805e-01 9.12439287e-01 3.74420762e-01 -3.21028382e-01
-3.46085846e-01 -3.84238154e-01 -6.08325958e-01 -6.60454214e-01
-4.14455026e-01 -1.92972645e-01 -3.94228518e-01 -1.44638699e-02
3.32840294e-01 4.92129773e-01 -1.30682719e+00 3.08396518e-01
6.98781550e-01 1.01371193e+00 1.89132452e-01 1.79667011e-01
1.12440757e-01 6.64408088e-01 -1.10034239e+00 -1.06937058e-01
-8.64076763e-02 -3.16991270e-01 -5.79892397e-01 -3.49421889e-01
-6.25999048e-02 -1.03767954e-01 -4.08243150e-01 8.01779568e-01
9.72580671e-01 2.95005944e-02 3.81956190e-01 -1.21752286e+00
-8.22927952e-01 6.05690718e-01 -2.03325883e-01 8.61060083e-01
3.48373652e-01 3.14167738e-01 4.64605123e-01 -8.16243231e-01
2.43244395e-01 5.42224050e-01 6.90187275e-01 4.68572527e-01
-1.08152711e+00 -1.21998203e+00 9.11558196e-02 4.44089621e-01
-1.38401151e+00 -5.66810310e-01 6.13182485e-01 -5.49675882e-01
1.34446061e+00 -1.08620748e-02 1.08032691e+00 1.66162097e+00
7.05700576e-01 3.14809740e-01 1.51519680e+00 -1.17344998e-01
4.03917462e-01 1.42235786e-01 5.09029686e-01 -7.36072734e-02
3.39984596e-01 -7.23228902e-02 -6.89997077e-01 -1.79833546e-01
4.53557551e-01 1.12158172e-01 -5.47835171e-01 4.26693022e-01
-1.18564343e+00 4.62163657e-01 3.59860003e-01 6.27527297e-01
-7.51344860e-01 -1.26260951e-01 5.88465571e-01 5.42797267e-01
4.32259977e-01 9.06208992e-01 -6.02752209e-01 -5.92432261e-01
-1.07659078e+00 -3.54737379e-02 8.29104006e-01 6.80306613e-01
2.92457759e-01 3.56055468e-01 7.17819296e-03 7.78249681e-01
-2.60523021e-01 2.30346784e-01 8.98003340e-01 -4.45748627e-01
3.80289674e-01 3.86475235e-01 -2.57179439e-01 -9.31229591e-01
-8.34957898e-01 -5.87026656e-01 -1.12305844e+00 -1.24053694e-01
5.40323965e-02 -4.91727203e-01 -6.95311427e-01 1.56100357e+00
-7.43018270e-01 9.52699482e-02 -1.75117016e-01 8.07397008e-01
1.06421566e+00 3.94731849e-01 1.36676669e-01 -2.50154525e-01
1.42284882e+00 -4.58777070e-01 -9.17411506e-01 -4.63073492e-01
2.74262428e-01 -5.36477566e-01 9.73348141e-01 7.75796354e-01
-1.28112483e+00 -3.44278097e-01 -1.19747460e+00 2.24903703e-01
-6.62613809e-01 1.11800939e-01 5.38291454e-01 5.45840025e-01
-1.33921659e+00 5.12916446e-01 -9.71423686e-01 -4.30170327e-01
5.32724500e-01 7.72990763e-01 -2.56458044e-01 3.62668723e-01
-1.31545520e+00 1.20774209e+00 2.59750605e-01 1.01042934e-01
-6.39395297e-01 -7.65363097e-01 -4.83865947e-01 4.22523543e-02
1.91935487e-02 -5.22078037e-01 8.70131791e-01 -8.03993523e-01
-1.30288815e+00 4.75407451e-01 -2.90060192e-01 -7.13148892e-01
-1.23978652e-01 -2.07530037e-01 -6.80870175e-01 8.38002469e-03
-6.15853854e-02 3.28417093e-01 5.51537812e-01 -4.73772287e-01
-4.28485304e-01 -4.24790829e-01 -7.87097737e-02 -2.72107095e-01
-2.91126102e-01 2.90961266e-01 -1.51247308e-01 -9.05891836e-01
-2.01676086e-01 -8.51339042e-01 1.72151942e-02 -6.71707869e-01
-1.10203318e-01 -2.81132817e-01 3.64047170e-01 -7.23612964e-01
1.37313306e+00 -2.27255011e+00 -2.22072173e-02 -7.86791148e-04
4.31642264e-01 2.69451141e-02 3.40901576e-02 3.97252113e-01
-5.74738324e-01 2.02905491e-01 -4.77349088e-02 -1.31876782e-01
2.29383465e-02 -2.26680487e-01 -3.42591405e-01 6.36056423e-01
2.59165734e-01 1.07645988e+00 -7.04933167e-01 2.99517423e-01
2.92975277e-01 6.58269048e-01 1.51888197e-02 1.78736404e-01
5.93012631e-01 3.65724921e-01 3.97995450e-02 5.57700455e-01
4.01220620e-01 -2.50689745e-01 -2.20578954e-01 -2.69280583e-01
-2.77310908e-01 8.04554820e-01 -7.22732604e-01 1.48035479e+00
-6.03086174e-01 1.21311438e+00 -2.38062695e-01 -9.12914455e-01
6.76586270e-01 6.09562159e-01 4.73359406e-01 -9.52278852e-01
3.31732452e-01 2.61179000e-01 4.33641791e-01 -6.08715355e-01
5.97225204e-02 -3.41746844e-02 2.31945202e-01 7.15903044e-01
2.10688040e-01 3.87678072e-02 8.22413154e-03 -1.37582257e-01
1.29969108e+00 -4.13541526e-01 3.76954466e-01 -3.89527619e-01
6.82316124e-02 -5.22503912e-01 4.88924235e-01 6.99622393e-01
-1.60543293e-01 5.54190934e-01 5.26633203e-01 -5.39220989e-01
-7.04217970e-01 -8.05091262e-01 -4.04415578e-01 7.47908473e-01
-4.77293462e-01 -5.07971585e-01 -8.36466789e-01 -1.29551694e-01
-2.85676390e-01 8.48621607e-01 -7.73746729e-01 -3.85041416e-01
-2.87518978e-01 -1.22469103e+00 6.47956192e-01 7.83226013e-01
5.24416983e-01 -1.44694829e+00 -9.55026865e-01 3.72285187e-01
-1.98228881e-01 -1.09924459e+00 3.47827077e-02 7.07585931e-01
-9.16264474e-01 -8.40412676e-01 -6.22059226e-01 -4.79074448e-01
4.57972407e-01 1.79100648e-01 9.90690231e-01 -1.36748448e-01
-1.11535221e-01 2.18607306e-01 -3.52945715e-01 -9.32928979e-01
2.32555106e-01 2.76766390e-01 4.69643414e-01 -3.53193790e-01
9.89087582e-01 -9.85177219e-01 -6.79943442e-01 -8.37011859e-02
-7.74087191e-01 -2.41902277e-01 8.48903596e-01 6.63467467e-01
1.34306565e-01 6.35976046e-02 9.20031607e-01 -4.26463664e-01
1.20583272e+00 -7.65007019e-01 -7.58183077e-02 1.14699826e-01
-8.89102161e-01 -2.68717378e-01 5.82704425e-01 -4.47251499e-01
-4.41288888e-01 -6.97788179e-01 -1.22972168e-01 -1.11373648e-01
-3.30288142e-01 6.76050901e-01 3.64729106e-01 1.27491541e-02
7.02716112e-01 2.64046162e-01 -3.31196815e-01 -2.81926274e-01
-4.67835218e-01 8.36660862e-01 2.80033678e-01 -3.39235365e-01
3.01288545e-01 1.65169239e-01 -6.34520948e-01 -7.99238384e-01
-5.15477896e-01 -4.27016467e-02 -4.71849293e-01 -2.49942113e-02
7.27743626e-01 -9.67789590e-01 -7.29792178e-01 3.83622169e-01
-1.12397254e+00 -4.91964459e-01 1.16674567e-03 9.28440750e-01
-1.73070267e-01 -1.49229243e-01 -6.60886765e-01 -7.15141714e-01
-7.18543530e-01 -1.31996274e+00 6.07184947e-01 1.66645348e-01
-8.65859687e-01 -7.96024740e-01 -1.72283694e-01 -3.90022956e-02
7.47745752e-01 1.77375555e-01 1.05756140e+00 -6.25443578e-01
2.86282077e-02 -2.14252204e-01 -1.70298874e-01 3.19396973e-01
4.99550223e-01 -2.32967570e-01 -1.32659590e+00 -4.91177380e-01
4.69333857e-01 -1.65845990e-01 4.54365969e-01 7.01675713e-01
1.66037118e+00 -1.68641925e-01 -3.91212963e-02 5.62400341e-01
1.03385496e+00 6.31687403e-01 7.68980265e-01 6.69104636e-01
1.86570495e-01 5.06156862e-01 -1.36885718e-01 4.35200125e-01
3.12948376e-01 3.54729295e-01 6.26725331e-02 -6.92540407e-02
1.55987680e-01 3.41829449e-01 5.38719535e-01 1.15480709e+00
-4.10805404e-01 -2.39121672e-02 -1.00295317e+00 5.05190611e-01
-1.32402134e+00 -7.31418431e-01 8.70142505e-02 2.21489310e+00
5.47300577e-01 2.72429109e-01 1.65635630e-01 3.02769572e-01
3.75437826e-01 -5.93057200e-02 -6.67522073e-01 -4.51617241e-01
-2.23324701e-01 5.73762655e-01 2.80654430e-01 -2.80516744e-01
-5.17656207e-01 4.68204260e-01 7.00456715e+00 4.05551374e-01
-1.55365455e+00 2.83789635e-01 5.17309666e-01 -6.23518527e-01
1.23881377e-01 -4.00828004e-01 -2.60239154e-01 8.10443997e-01
1.61307144e+00 -5.32379150e-01 8.83916020e-01 3.29264075e-01
6.06883168e-01 -1.99499801e-01 -1.15577281e+00 1.52033055e+00
9.27011147e-02 -1.12786746e+00 -2.94403166e-01 5.75407036e-02
3.84557217e-01 5.02226710e-01 1.52949840e-01 4.03210253e-01
-2.50101596e-01 -1.43653929e+00 6.75781727e-01 5.58072746e-01
6.61680222e-01 -7.45388627e-01 1.07570255e+00 1.14895679e-01
-8.09461713e-01 -2.31650844e-01 -4.02632743e-01 -5.81185102e-01
-1.60038158e-01 6.54804051e-01 -5.00596464e-01 3.90434593e-01
1.34022212e+00 1.07556820e+00 -7.52709329e-01 1.08236992e+00
-2.41136491e-01 1.03328049e+00 -6.20911531e-02 -2.94047952e-01
1.87095344e-01 -6.38837069e-02 2.22537979e-01 1.41172159e+00
4.24210638e-01 2.83670783e-01 -5.56118131e-01 9.65064704e-01
-1.43136308e-01 -6.42860457e-02 -5.98440111e-01 -3.08362812e-01
5.36671519e-01 1.17925560e+00 -7.05144763e-01 -6.40869141e-02
-6.90034032e-01 6.65420830e-01 2.21907511e-01 6.75372899e-01
-6.09565377e-01 -7.02442944e-01 6.28031015e-01 -8.16045329e-02
-4.05157924e-01 -9.67264697e-02 -6.87766612e-01 -1.10721135e+00
3.13884169e-01 -1.00822794e+00 1.31293744e-01 -1.02625585e+00
-1.34658968e+00 1.01457071e+00 -2.20355280e-02 -1.01361299e+00
-1.41357154e-01 -4.80528027e-01 -5.51688552e-01 9.79096532e-01
-1.17018867e+00 -3.55453521e-01 -3.20798397e-01 5.11383533e-01
5.93684077e-01 -2.89005041e-01 1.02412212e+00 4.51581985e-01
-8.32746446e-01 3.50014836e-01 -1.13062508e-01 1.63707495e-01
8.31040204e-01 -9.21774387e-01 4.28359747e-01 5.26556432e-01
-1.37197748e-01 1.16442907e+00 5.54962635e-01 -2.61151224e-01
-1.43674457e+00 -8.28608096e-01 8.33831191e-01 -4.62889493e-01
7.16666400e-01 -5.56296766e-01 -1.07427526e+00 7.94188797e-01
6.68418467e-01 -4.28863287e-01 1.06616366e+00 3.14999968e-01
1.46783203e-01 -2.84111172e-01 -8.50944757e-01 5.95758855e-01
7.78779268e-01 -6.23127341e-01 -9.02753234e-01 9.22270864e-02
2.35338777e-01 -3.30728859e-01 -9.96964157e-01 2.59042531e-01
6.64399445e-01 -9.64287460e-01 5.79727173e-01 -3.47052723e-01
3.11826259e-01 1.62036881e-01 1.13341339e-01 -1.61732233e+00
-6.12150669e-01 -4.52064246e-01 2.22429279e-02 9.56840634e-01
4.39087808e-01 -9.44384873e-01 2.55344033e-01 8.79674315e-01
-3.78011495e-01 -1.13528681e+00 -6.75305665e-01 -6.06825233e-01
1.53448179e-01 -9.41747606e-01 9.55588579e-01 8.57734621e-01
4.49584991e-01 2.45234758e-01 -9.16771516e-02 -2.21356470e-02
5.55306934e-02 -3.34250867e-01 2.87739486e-01 -1.16276538e+00
2.16725037e-01 -6.66513145e-01 -4.94496673e-01 -4.20825332e-01
2.33008400e-01 -8.68578553e-01 -3.07153612e-01 -1.78932989e+00
2.17639342e-01 -1.19608685e-01 -8.04156959e-01 6.74578846e-01
1.28196344e-01 2.08764911e-01 -7.98918679e-02 1.13863945e-01
-1.29768044e-01 2.83782750e-01 6.46817267e-01 -1.18459128e-01
-3.99209648e-01 -1.28486771e-02 -1.03960419e+00 6.25243485e-01
1.12420881e+00 -4.80657876e-01 -5.24303973e-01 -5.73739946e-01
4.48152453e-01 -1.46900520e-01 3.87415200e-01 -1.21017122e+00
3.82467300e-01 1.94365174e-01 8.84718359e-01 -3.50374192e-01
1.96755275e-01 -6.60244465e-01 2.48444572e-01 2.09677115e-01
-2.58877337e-01 5.97497165e-01 6.70935333e-01 -3.16506252e-03
-2.19254777e-01 7.19814897e-02 3.91686350e-01 -6.14690296e-02
-4.90053296e-01 2.03691125e-01 -9.58752096e-01 1.05721988e-02
7.60143936e-01 -2.62861848e-01 -2.66979843e-01 -5.20755887e-01
-6.80867434e-01 9.04051736e-02 1.23127289e-01 6.57935381e-01
7.13748455e-01 -1.12174249e+00 -5.93339384e-01 3.19449186e-01
-4.92336266e-02 -3.93710464e-01 2.39006773e-01 1.34310496e+00
-3.71048674e-02 7.96733081e-01 -6.07519627e-01 -2.55122632e-01
-7.70097017e-01 3.06034088e-01 3.61418068e-01 3.09811383e-01
-9.52622414e-01 5.18895805e-01 -5.65199517e-02 4.80729267e-02
5.52937746e-01 -7.56783485e-01 -3.25998247e-01 3.70829433e-01
7.99587727e-01 4.24523562e-01 6.95253253e-01 -2.53985614e-01
-6.50121272e-01 3.00831228e-01 -2.72589121e-02 -8.14588964e-02
1.79423869e+00 7.18043372e-02 -3.69475216e-01 9.63206053e-01
1.16644561e+00 -3.75973284e-01 -8.45138848e-01 2.54723281e-01
-9.53027532e-02 6.72331750e-02 1.49835616e-01 -9.81429279e-01
-1.27644575e+00 1.01850438e+00 6.51861966e-01 1.29983544e-01
1.41051686e+00 -2.59831250e-01 5.78457773e-01 4.40983206e-01
7.20429957e-01 -1.07098389e+00 -2.05610886e-01 4.11843657e-01
1.02805889e+00 -8.60672355e-01 1.20067317e-02 3.48797709e-01
-5.14789939e-01 1.42995632e+00 3.05681556e-01 -1.35918126e-01
8.01684499e-01 4.53702599e-01 -7.81679973e-02 -4.50073421e-01
-8.20509315e-01 3.55054617e-01 2.99903899e-01 4.40861821e-01
8.01940680e-01 3.62213738e-02 -3.98570240e-01 1.27493703e+00
-7.49109805e-01 3.66028845e-01 6.34796381e-01 8.22734237e-01
3.96843962e-02 -7.24221647e-01 -1.72657818e-01 1.10940182e+00
-6.73344493e-01 -2.93053150e-01 -3.47905576e-01 7.09750950e-01
1.53912470e-01 1.24449742e+00 4.28274162e-02 -6.37053609e-01
5.27234018e-01 1.97651923e-01 3.55042100e-01 -5.88566720e-01
-9.05756235e-01 -1.60524160e-01 -2.97752202e-01 -5.04806042e-01
-3.99069130e-01 -7.68427849e-01 -1.12191439e+00 -2.78882682e-01
-7.81266168e-02 1.93686068e-01 6.48202121e-01 1.24956203e+00
5.76640606e-01 9.29146945e-01 2.25658029e-01 -7.58198023e-01
1.29185533e-02 -1.32045746e+00 -6.97143137e-01 -1.98041260e-01
4.53709126e-01 -7.57007122e-01 -5.21601975e-01 -1.90511495e-01] | [13.18930721282959, 3.437293767929077] |
abc1a743-927a-4496-bf99-e839141fbdf1 | a-comparison-of-identification-methods-of | null | null | https://aclanthology.org/2020.winlp-1.16 | https://aclanthology.org/2020.winlp-1.16.pdf | A Comparison of Identification Methods of Brazilian Music Styles by Lyrics | In our work, we applied different techniques for the task of genre classification using lyrics. Utilizing our dataset with lyrics of typical genres in Brazil divided into seven classes, we apply some models used in machine learning and deep learning classification tasks. We explore the performance of usual models for text classification using an input in the Portuguese language. We also compare the use of RNN and classic machine learning approaches for text classification, exploring the most used methods in the field. | ['Patrick Guimar{\\~a}es', 'Jader Froes', 'Larissa Freitas', 'Douglas Costa'] | 2020-07-01 | null | null | null | ws-2020-7 | ['genre-classification'] | ['computer-vision'] | [-1.34167075e-01 -1.95802629e-01 -3.37262332e-01 -3.62418413e-01
-3.77862751e-01 -7.39361405e-01 8.96976292e-01 2.14658633e-01
-4.70104188e-01 7.71581531e-01 8.55036914e-01 -1.81317240e-01
2.39353165e-01 -9.27090764e-01 -1.86669156e-01 -5.19483566e-01
5.12360096e-01 6.32755876e-01 -5.21911263e-01 -4.20593172e-01
8.08776319e-01 3.15961927e-01 -1.86096668e+00 1.13824284e+00
6.55236021e-02 1.07689595e+00 -2.11842209e-01 1.11937594e+00
-7.43036985e-01 1.52976751e+00 -1.39988184e+00 -3.70249391e-01
-1.86326653e-01 -4.81020182e-01 -1.32591307e+00 -4.07462984e-01
4.76640970e-01 1.00414179e-01 -5.59178948e-01 5.95169723e-01
7.76918709e-01 3.37346256e-01 1.20521617e+00 -8.68925095e-01
-6.54370189e-01 1.12658823e+00 -9.77834538e-02 3.84714961e-01
9.76662099e-01 -3.43759358e-01 1.03184688e+00 -5.89932859e-01
6.81846619e-01 1.28760171e+00 8.14552367e-01 7.28443563e-01
-7.19211996e-01 -6.82018459e-01 -4.16875631e-01 4.97414887e-01
-1.02487469e+00 -3.77699792e-01 1.06830537e+00 -7.13035643e-01
1.05422175e+00 4.50996846e-01 4.73089874e-01 1.74595952e+00
2.09314182e-01 8.70090365e-01 1.28062475e+00 -7.43386984e-01
1.12310134e-01 1.19541407e-01 4.91492331e-01 2.01117098e-01
-4.50372040e-01 -5.24637938e-01 -5.36088109e-01 -1.43580765e-01
1.92722008e-01 -1.73783094e-01 -1.86217830e-01 5.68530858e-01
-1.05111432e+00 1.23139608e+00 -1.87278390e-02 1.05205321e+00
7.06457570e-02 -1.71628192e-01 1.26906168e+00 6.83510363e-01
7.02732444e-01 9.38342988e-01 -5.52360713e-01 -6.70797288e-01
-1.18440545e+00 1.72083005e-01 1.17418826e+00 6.07887924e-01
-1.58889219e-02 2.56015211e-01 -2.17978254e-01 1.23446417e+00
-1.10099815e-01 -4.14410606e-02 1.30213225e+00 -7.91479945e-01
6.42532110e-01 5.42046070e-01 -3.51363599e-01 -7.20382690e-01
-5.51255345e-01 -3.78016591e-01 -8.97043467e-01 -8.19536000e-02
6.10713184e-01 -4.38129567e-02 -4.05210555e-01 9.39199388e-01
-3.46972525e-01 -2.13910937e-01 2.66699404e-01 3.24724585e-01
1.67443705e+00 1.02576947e+00 -9.37938094e-02 -5.15753925e-01
1.27075779e+00 -1.10616374e+00 -8.81845355e-01 5.74984968e-01
7.71645010e-01 -9.48893368e-01 1.52636373e+00 9.99129057e-01
-9.39225197e-01 -7.93224990e-01 -9.85192120e-01 -5.58135450e-01
-9.04253304e-01 3.75116318e-01 2.94825673e-01 7.48725653e-01
-7.01391816e-01 7.64996111e-01 -7.41251782e-02 -4.64381099e-01
3.50886703e-01 1.79349020e-01 -1.38699055e-01 6.13960207e-01
-1.10429454e+00 8.16891074e-01 6.56124175e-01 -4.10318345e-01
-7.57585406e-01 -2.72381544e-01 -6.30223989e-01 1.24062710e-02
-1.92736760e-01 -1.54761523e-01 1.45757556e+00 -1.28654563e+00
-2.01277971e+00 1.29135680e+00 1.31410599e-01 -4.85687017e-01
3.87061119e-01 -3.34155589e-01 -5.00392020e-01 -9.78734437e-03
-1.58002347e-01 2.47931376e-01 8.69828999e-01 -7.90381670e-01
-3.76769125e-01 -1.26109347e-01 1.47783160e-01 1.11351751e-01
-8.88344049e-01 1.72726244e-01 4.70914453e-01 -1.00559986e+00
-4.14819270e-01 -5.24129510e-01 3.78316969e-01 -7.00589836e-01
-2.04881936e-01 -8.94897699e-01 7.84186125e-01 -7.37955451e-01
1.56160867e+00 -2.00537777e+00 1.14032611e-01 -3.86968672e-01
7.74686784e-02 8.11118558e-02 8.62019435e-02 6.70260847e-01
-1.18782200e-01 2.53348887e-01 2.26697609e-01 -3.99489641e-01
9.24209803e-02 2.30770543e-01 -7.52356291e-01 2.48517543e-01
-4.78274792e-01 7.10317791e-01 -6.98246777e-01 -4.98412937e-01
1.50450990e-01 2.79877990e-01 -2.04039305e-01 3.82095069e-01
-2.91892320e-01 2.15194449e-01 -2.02744573e-01 5.40964007e-01
6.64708531e-03 1.81837574e-01 3.90668288e-02 -1.05674647e-01
-1.21467806e-01 9.98959124e-01 -6.49944127e-01 1.79333305e+00
-9.70927238e-01 1.45653605e+00 -4.52956378e-01 -1.29674029e+00
9.50884640e-01 7.84683049e-01 3.37897778e-01 -2.38310710e-01
6.35931134e-01 2.51154959e-01 -4.15992066e-02 -7.44579673e-01
5.38540304e-01 -1.69738397e-01 -1.90487176e-01 8.27262938e-01
5.73725283e-01 -2.79623568e-01 3.69541138e-01 -3.70220214e-01
8.58451664e-01 3.52586538e-01 8.06049645e-01 -3.99107277e-01
9.12212908e-01 -2.22250167e-02 -1.51421800e-01 9.03272808e-01
-7.60087892e-02 7.69047201e-01 7.00277328e-01 -1.06167209e+00
-1.12218308e+00 -4.13342357e-01 -4.42700177e-01 1.92280889e+00
-8.91358078e-01 -6.92809522e-01 -7.92792320e-01 -8.24141443e-01
-3.82378489e-01 7.03792512e-01 -9.33825135e-01 3.59227747e-01
-7.50782430e-01 -6.90481424e-01 1.13754356e+00 2.65536934e-01
3.11605781e-01 -1.84995949e+00 -6.61904633e-01 8.16078708e-02
-7.23887086e-02 -8.52618575e-01 5.52721918e-02 5.73233306e-01
-7.47222006e-01 -1.01547205e+00 -7.38109767e-01 -9.91644025e-01
-1.23021178e-01 -3.34422827e-01 1.70366359e+00 5.11991866e-02
-5.21030910e-02 2.00927183e-01 -8.47417474e-01 -6.72977507e-01
-9.18559730e-01 7.82624364e-01 -1.04229070e-01 -3.30678761e-01
5.87652087e-01 -5.77058434e-01 2.59827487e-02 -4.20969218e-01
-8.11655164e-01 -2.15160072e-01 -1.33526415e-01 7.43500829e-01
-2.96821654e-01 2.33688988e-02 6.21765316e-01 -1.11664069e+00
1.10214341e+00 -6.00507259e-01 -4.38686199e-02 -1.76323310e-01
-2.08600923e-01 -6.54981062e-02 1.28300321e+00 -7.26679564e-01
-6.58692598e-01 -2.32628584e-01 -6.52613819e-01 -2.00859264e-01
-6.71509862e-01 5.21993995e-01 1.18783206e-01 2.21266538e-01
1.00091434e+00 2.24210963e-01 -3.20870340e-01 -9.12501991e-01
1.97832704e-01 1.43156922e+00 1.48731947e-01 -5.56541979e-01
1.75379232e-01 2.41222769e-01 -2.14755505e-01 -1.07429886e+00
-1.28293622e+00 -4.24719393e-01 -9.23741460e-01 -2.04197004e-01
8.83839726e-01 -5.96396446e-01 -1.02285755e+00 4.45608735e-01
-1.35978365e+00 -9.84199569e-02 -4.60163832e-01 2.92786509e-01
-8.84476364e-01 1.17018633e-01 -9.48925912e-01 -6.77718639e-01
-6.53590620e-01 -6.93286777e-01 9.04476225e-01 -8.91762078e-02
-5.81450701e-01 -1.38398051e+00 5.49283266e-01 1.80250838e-01
1.52603999e-01 1.34791702e-01 1.26648426e+00 -1.19037843e+00
8.96045506e-01 3.43273841e-02 2.77672797e-01 4.14785057e-01
1.03896827e-01 7.51838014e-02 -1.62649572e+00 7.52542764e-02
6.50269210e-01 -8.21853697e-01 9.02940094e-01 2.25235417e-01
1.62328255e+00 -4.66980219e-01 2.09901869e-01 5.01542151e-01
1.24625194e+00 2.83616543e-01 4.98900980e-01 8.71581137e-01
7.80063689e-01 8.81040573e-01 2.13591158e-01 2.55770177e-01
8.87030736e-02 4.82308060e-01 -1.58678312e-02 3.86812508e-01
-5.54466993e-03 1.22200483e-02 5.28167784e-01 1.32079637e+00
-1.49316415e-01 -4.24130857e-01 -1.02353036e+00 2.08133087e-01
-1.70382488e+00 -1.32507670e+00 -1.21413857e-01 1.54447258e+00
1.16656673e+00 1.72041357e-01 5.08400500e-01 9.72403467e-01
3.88870567e-01 4.27784353e-01 8.81719664e-02 -1.22520900e+00
-1.90781727e-01 5.56025684e-01 -1.91708520e-01 2.76787102e-01
-1.49035120e+00 7.96218097e-01 7.82352304e+00 1.11917508e+00
-1.31720030e+00 3.26449960e-01 5.93202412e-01 -4.05292392e-01
2.60343969e-01 -6.58341527e-01 -6.20085597e-01 4.49778378e-01
1.28770888e+00 2.02737480e-01 5.15409350e-01 8.96551967e-01
8.70236754e-02 2.10538059e-01 -1.34863031e+00 1.22289455e+00
7.02231586e-01 -1.36937404e+00 3.53068650e-01 -4.67370450e-01
7.08676696e-01 -1.01707421e-01 -7.44085386e-02 6.93623662e-01
-1.07261717e-01 -1.40089452e+00 5.75403273e-01 3.13632876e-01
7.23772168e-01 -7.25922287e-01 8.00452471e-01 2.92129517e-01
-7.65153885e-01 -2.25159451e-01 -4.75755244e-01 -6.51449502e-01
-4.45313811e-01 9.00813099e-03 -6.55276477e-01 2.57602364e-01
7.70185113e-01 1.26594150e+00 -6.73215270e-01 5.12895882e-01
-5.24469241e-02 1.01173043e+00 4.12014127e-02 -4.92465734e-01
3.97612035e-01 -1.18331350e-01 5.16930282e-01 1.79636908e+00
-3.81200090e-02 -3.63041997e-01 -3.32861133e-02 3.12888235e-01
-1.28809273e-01 6.75598323e-01 -8.21015179e-01 -3.86216380e-02
-1.49550475e-02 1.16992581e+00 -8.14564943e-01 -6.09882891e-01
-3.28327894e-01 6.38204694e-01 1.56276569e-01 3.42049003e-02
-5.20708919e-01 -6.12379670e-01 1.12804934e-01 1.00141373e-02
-1.83206022e-01 8.05212706e-02 -7.02954292e-01 -1.28392398e+00
-3.70705515e-01 -1.14902079e+00 6.85579538e-01 -8.56166422e-01
-1.56205022e+00 9.97544408e-01 3.44311930e-02 -1.31016827e+00
-5.97555757e-01 -1.12397075e+00 -7.57845879e-01 4.01783109e-01
-8.98677707e-01 -1.15123343e+00 -6.34872615e-02 5.13836682e-01
1.39001501e+00 -1.02638483e+00 1.07554626e+00 3.19281012e-01
-9.21464413e-02 2.87942290e-01 3.49994868e-01 4.49269980e-01
7.91292071e-01 -1.56683791e+00 2.06812993e-01 -9.66355056e-02
5.98346591e-01 2.58662224e-01 7.37389863e-01 -7.83344582e-02
-6.69589937e-01 -6.38140738e-01 1.11468673e+00 -7.01761007e-01
9.75103319e-01 -6.09383345e-01 -6.77855372e-01 5.50843358e-01
9.42361712e-01 -7.06873298e-01 1.05293083e+00 2.24189684e-01
-3.84095818e-01 1.78139105e-01 -9.08022642e-01 4.22961861e-01
7.08666086e-01 -8.61579657e-01 -1.03432178e+00 6.39013171e-01
3.90329808e-01 -4.12908942e-02 -9.30523276e-01 9.25909579e-02
8.15521955e-01 -8.23144794e-01 6.29871249e-01 -1.09312582e+00
1.03090429e+00 3.13123733e-01 -1.45840123e-01 -1.27110469e+00
3.27534340e-02 -5.01873553e-01 -2.63218135e-01 1.27795041e+00
1.43200755e-01 -2.26984754e-01 6.34712636e-01 -4.75234389e-01
-1.08483965e-02 -5.40586233e-01 -1.03268540e+00 -3.36324394e-01
7.34817564e-01 -5.56977749e-01 2.67022371e-01 1.29572821e+00
2.31963918e-01 1.00723207e+00 -3.24337333e-01 -9.35454130e-01
-1.38419434e-01 2.19100729e-01 6.66222632e-01 -1.61391234e+00
-2.61412352e-01 -1.07609773e+00 -3.61121774e-01 -4.91860896e-01
7.46610820e-01 -1.03959370e+00 -3.40192884e-01 -1.24210715e+00
2.38453940e-01 1.15592167e-01 -2.24012867e-01 2.62378752e-01
3.54687482e-01 7.32768238e-01 3.50976467e-01 3.89088124e-01
-5.26017547e-01 2.15622887e-01 7.65516639e-01 -4.00844663e-01
-2.43264407e-01 3.02600473e-01 -3.41905743e-01 1.11873889e+00
1.03887224e+00 -5.91801763e-01 -1.14433862e-01 -1.73901200e-01
7.13428557e-01 -3.45263094e-01 -3.25953603e-01 -1.16450286e+00
-2.83203065e-01 1.00446865e-01 4.28891301e-01 -7.48321056e-01
2.91724354e-01 -5.85295618e-01 -4.08164769e-01 4.29737240e-01
-8.52694273e-01 1.45712003e-01 1.23770470e-02 -3.20961952e-01
-5.21642923e-01 -1.07216990e+00 7.45900571e-01 -3.72551113e-01
4.25493196e-02 -4.38947469e-01 -1.07330799e+00 1.58045322e-01
5.13631403e-01 -4.68604080e-02 -3.51155162e-01 -6.35125935e-01
-9.57830369e-01 -5.58197498e-01 1.92959160e-01 8.28161716e-01
2.26156220e-01 -1.25441730e+00 -7.44469583e-01 -1.54108956e-01
-5.52638248e-02 -7.70911157e-01 -6.48764551e-01 4.14337873e-01
-9.66836333e-01 7.13188708e-01 -5.75800657e-01 -2.16027066e-01
-1.34621143e+00 6.08077347e-01 4.81895596e-01 -2.98667312e-01
-2.71113962e-01 2.12457061e-01 -2.79422547e-03 -5.16434669e-01
4.96244162e-01 -2.01382741e-01 -1.43287325e+00 6.43872976e-01
5.68755031e-01 7.83420503e-01 1.30159691e-01 -7.44770885e-01
1.24848396e-01 4.71025527e-01 1.74732432e-01 -1.91475183e-01
1.28760242e+00 1.58506989e-01 -3.94603342e-01 1.59753406e+00
1.41408253e+00 1.69193164e-01 -8.17443505e-02 1.94119751e-01
3.03991407e-01 1.44878253e-01 3.02108489e-02 -7.71826982e-01
-6.66651607e-01 1.30747402e+00 5.23754656e-01 1.04420137e+00
1.02290773e+00 -2.27412522e-01 4.81364489e-01 7.36474514e-01
-1.11073531e-01 -1.45492375e+00 6.77353516e-02 1.18477046e+00
9.32715058e-01 -9.01149809e-01 1.08791627e-01 3.32969010e-01
-4.38262969e-01 1.91672528e+00 2.77831882e-01 -5.50817251e-01
8.02828312e-01 3.41679275e-01 3.32374066e-01 -1.35966957e-01
-8.17501426e-01 1.40962601e-01 5.15711367e-01 2.88715571e-01
1.37725890e+00 -1.53445393e-01 -1.03256547e+00 6.53001785e-01
-1.02708495e+00 -2.45558277e-01 7.96951473e-01 6.39059484e-01
-2.78179407e-01 -1.02107322e+00 -5.40415943e-01 6.65444851e-01
-1.35724068e+00 -2.63366491e-01 -1.01433051e+00 7.36605704e-01
2.00219452e-01 1.01587546e+00 3.53300244e-01 -3.14583242e-01
-1.85223445e-02 3.94144475e-01 5.38019896e-01 -8.75379801e-01
-1.49402094e+00 -1.15212254e-01 2.56523758e-01 4.57740501e-02
-6.99498773e-01 -6.13019109e-01 -7.16411293e-01 -2.50004292e-01
-9.88357328e-03 2.83335268e-01 7.50182629e-01 1.20770514e+00
-3.17752630e-01 5.90615928e-01 7.61567831e-01 -1.01804733e+00
-2.49708802e-01 -1.87107742e+00 -4.44203079e-01 4.30469751e-01
3.67498666e-01 -3.42204720e-01 -4.68411684e-01 4.03679043e-01] | [15.833514213562012, 5.2544074058532715] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.