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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bab063e5-c6d9-4e05-9b38-85853dd5015b | level-up-the-deepfake-detection-a-method-to | 2303.00608 | null | https://arxiv.org/abs/2303.00608v1 | https://arxiv.org/pdf/2303.00608v1.pdf | Level Up the Deepfake Detection: a Method to Effectively Discriminate Images Generated by GAN Architectures and Diffusion Models | The image deepfake detection task has been greatly addressed by the scientific community to discriminate real images from those generated by Artificial Intelligence (AI) models: a binary classification task. In this work, the deepfake detection and recognition task was investigated by collecting a dedicated dataset of pristine images and fake ones generated by 9 different Generative Adversarial Network (GAN) architectures and by 4 additional Diffusion Models (DM). A hierarchical multi-level approach was then introduced to solve three different deepfake detection and recognition tasks: (i) Real Vs AI generated; (ii) GANs Vs DMs; (iii) AI specific architecture recognition. Experimental results demonstrated, in each case, more than 97% classification accuracy, outperforming state-of-the-art methods. | ['Sebastiano Battiato', 'Oliver Giudice', 'Luca Guarnera'] | 2023-03-01 | null | null | null | null | ['face-swapping'] | ['computer-vision'] | [ 4.98270690e-01 1.62032932e-01 1.53520554e-01 1.15937971e-01
-5.33167839e-01 -6.19733870e-01 1.30419254e+00 -4.93554682e-01
-2.63274521e-01 9.10991907e-01 -2.32603446e-01 -1.49215072e-01
1.52421728e-01 -8.94956768e-01 -6.45452917e-01 -1.02550197e+00
2.47218788e-01 7.10293412e-01 6.70383498e-02 -1.40346751e-01
4.87816632e-01 8.55614364e-01 -1.45495296e+00 4.35991317e-01
8.46506953e-01 1.46284568e+00 -3.99267852e-01 1.04396260e+00
1.77799370e-02 1.27534425e+00 -1.11697233e+00 -6.92923605e-01
4.92432863e-01 -6.68530583e-01 -8.13246608e-01 3.29637647e-01
6.66547716e-01 -4.15301174e-01 -4.47992057e-01 1.38872087e+00
3.17802072e-01 -3.24522644e-01 1.15016377e+00 -1.49413455e+00
-1.40747046e+00 1.58775926e-01 -4.05424118e-01 2.87091285e-01
5.06395334e-03 5.57428420e-01 1.93944648e-01 -8.81128669e-01
6.10013366e-01 1.15798700e+00 4.44516420e-01 7.85116851e-01
-1.25000548e+00 -6.55707657e-01 -3.76883149e-01 4.65189368e-01
-1.30013251e+00 -1.58128262e-01 8.96203518e-01 -7.73251772e-01
7.76440084e-01 1.80670694e-01 6.20633245e-01 1.83058834e+00
2.50641197e-01 7.25355506e-01 1.54237509e+00 -3.80892456e-01
2.39397481e-01 5.38411736e-01 1.16160057e-01 4.99007940e-01
4.14486587e-01 4.32352632e-01 -1.36342913e-01 2.92151440e-02
8.25357437e-01 -3.78821641e-01 -2.44696870e-01 -1.50441214e-01
-9.72203553e-01 1.16919863e+00 5.12731731e-01 6.04478240e-01
-6.58761263e-01 1.20712690e-01 2.05813900e-01 4.79936719e-01
3.33202541e-01 5.88739991e-01 8.90800655e-02 2.38356918e-01
-1.03971946e+00 7.13280812e-02 7.18410611e-01 6.05638027e-01
4.91288990e-01 8.34476173e-01 -2.36021399e-01 6.87741339e-01
-4.01586257e-02 6.58743680e-01 9.38807964e-01 -3.61351877e-01
3.21038485e-01 4.67306256e-01 1.26223356e-01 -1.39836407e+00
-9.76866186e-02 -4.76379633e-01 -1.32634854e+00 5.48158228e-01
5.30267537e-01 -2.35116873e-02 -1.25300026e+00 1.05616939e+00
-6.16897419e-02 1.35341257e-01 3.43309045e-01 8.82918239e-01
8.69271159e-01 8.54573905e-01 -2.68119097e-01 2.99344450e-01
1.16098428e+00 -1.19915378e+00 -6.68551862e-01 -2.31056839e-01
2.47814342e-01 -5.93903124e-01 7.72926748e-01 6.81178033e-01
-8.46619248e-01 -6.30914748e-01 -1.31217408e+00 1.77829310e-01
-7.55721450e-01 3.85345310e-01 2.61496961e-01 1.18038619e+00
-1.08863902e+00 3.88632476e-01 -2.71939367e-01 -9.97173712e-02
9.47313905e-01 1.81664526e-01 -3.73514265e-01 5.08846231e-02
-1.15749931e+00 1.09039915e+00 3.84084404e-01 2.14114785e-01
-1.60299528e+00 -2.38767639e-01 -4.07210082e-01 -1.66340858e-01
1.55023128e-01 -6.62580669e-01 7.27830648e-01 -1.88069904e+00
-1.63265657e+00 1.53615022e+00 4.71428126e-01 -1.05546844e+00
1.18670750e+00 -2.01998353e-01 -7.01008260e-01 1.74221605e-01
-3.50243837e-01 4.24151182e-01 1.58977377e+00 -1.64735913e+00
-1.63662702e-01 -4.68911618e-01 -2.56589472e-01 -3.77553165e-01
-3.06951046e-01 -7.17064291e-02 2.27714643e-01 -1.07994533e+00
-5.40408432e-01 -1.06769693e+00 2.42618099e-01 -7.76560977e-02
-8.40137839e-01 1.06685370e-01 1.18470240e+00 -9.52952802e-01
8.87215853e-01 -1.87709963e+00 4.32798445e-01 1.12046324e-01
3.00091863e-01 1.03171730e+00 -3.03177744e-01 2.32649446e-01
-3.88054587e-02 1.90311417e-01 -4.31399971e-01 -1.31596431e-01
-6.24211058e-02 1.29981443e-01 -4.67088014e-01 4.68428105e-01
5.50858736e-01 1.12749898e+00 -6.53287053e-01 3.28908712e-02
2.73260862e-01 5.26314139e-01 -1.68292895e-01 3.97891819e-01
2.58736890e-02 4.44695592e-01 -1.21436961e-01 8.31212819e-01
8.95094573e-01 -1.00810528e-01 -3.08994055e-01 -6.87163398e-02
3.12714607e-01 -3.99918735e-01 -7.27180600e-01 1.04423237e+00
-2.27726296e-01 8.44364643e-01 -1.32167945e-02 -1.21397579e+00
1.16607416e+00 1.78079237e-03 1.81835648e-02 -7.32204735e-01
4.51422244e-01 4.20205176e-01 1.49068937e-01 -4.40743506e-01
6.17301822e-01 1.99278817e-02 -9.20565352e-02 2.82067209e-01
1.77975312e-01 -2.36217961e-01 -2.04100743e-01 -1.95420645e-02
1.12775218e+00 -2.34979376e-01 1.48964562e-02 -3.26689541e-01
7.86931992e-01 2.09690064e-01 -7.57626593e-02 1.03804004e+00
-3.05065840e-01 6.40953720e-01 4.29635406e-01 -8.08210552e-01
-1.10999453e+00 -1.06999755e+00 1.49568453e-01 2.15808213e-01
1.11185014e-01 4.16405171e-01 -1.23462951e+00 -9.47007179e-01
1.36642024e-01 7.29413152e-01 -1.06401944e+00 -5.39762497e-01
-5.06061196e-01 -1.10956097e+00 1.16344905e+00 1.64576113e-01
1.16270983e+00 -1.32707298e+00 -4.77500677e-01 7.45468438e-02
2.05783918e-01 -1.21857977e+00 2.00238936e-02 -2.66735144e-02
-3.14321250e-01 -1.20447278e+00 -1.25310910e+00 -6.89729333e-01
5.42674541e-01 -1.64705396e-01 1.01315856e+00 -2.18597818e-02
-6.76677406e-01 2.92552233e-01 -3.76289517e-01 -2.61081427e-01
-1.18967903e+00 -1.65656999e-01 -1.78891197e-01 5.84134161e-01
1.39339820e-01 -5.92431538e-02 -5.82341254e-01 3.62680018e-01
-1.28282619e+00 -1.01744227e-01 8.69124711e-01 1.18166661e+00
1.88043073e-01 1.10127956e-01 8.19450736e-01 -9.65814292e-01
6.91974640e-01 -3.83046240e-01 -6.22781157e-01 2.10179269e-01
-5.15904903e-01 -1.91955879e-01 6.26338959e-01 -7.56164849e-01
-9.23221827e-01 -7.84523860e-02 -2.67495364e-01 -6.34097755e-01
-3.75962019e-01 -7.97575414e-02 -2.07465634e-01 -6.32001579e-01
7.11987615e-01 6.06354415e-01 3.57823772e-03 -1.35207130e-02
4.25142914e-01 9.21469748e-01 9.36570644e-01 -6.08457625e-02
8.36180866e-01 3.47895712e-01 -1.56458378e-01 -8.32784832e-01
-3.38279277e-01 3.31508577e-01 -5.42577744e-01 -3.67249161e-01
1.12748587e+00 -6.13077223e-01 -2.10183308e-01 1.71211326e+00
-1.19040787e+00 -5.37026107e-01 -3.03667694e-01 -9.20627639e-02
-4.26911086e-01 3.40981752e-01 -7.65067637e-01 -8.21753919e-01
-3.96539807e-01 -1.17185092e+00 9.18144643e-01 3.53784710e-02
1.90398514e-01 -9.75279033e-01 -8.74352157e-02 6.73596680e-01
6.49063885e-01 7.96701252e-01 8.98758233e-01 -6.33726239e-01
-7.02595294e-01 -4.68282312e-01 -4.11669970e-01 9.55432117e-01
8.31829500e-04 9.59616527e-02 -1.21183825e+00 -6.59257919e-02
1.25861391e-01 -4.37086940e-01 1.10322118e+00 1.25819772e-01
1.08185577e+00 -6.08438671e-01 4.32522446e-02 4.37749296e-01
1.37469923e+00 4.73177284e-01 1.30268621e+00 5.08961201e-01
7.31289208e-01 3.48220915e-01 1.33397043e-01 1.46868110e-01
-1.62446797e-01 7.36015379e-01 6.87733769e-01 -3.59716594e-01
-4.53256488e-01 -1.48972888e-02 4.01714653e-01 1.51965797e-01
1.40708357e-01 -8.94552648e-01 -8.94708335e-01 4.20655370e-01
-1.57243979e+00 -1.03278387e+00 -4.65545863e-01 1.92473960e+00
1.31720170e-01 5.00654392e-02 1.91584200e-01 4.47029352e-01
9.13363338e-01 1.01512261e-01 -6.42655969e-01 -7.21454680e-01
-8.02695811e-01 2.88417637e-01 5.65248847e-01 1.09533198e-01
-1.34879768e+00 1.16986132e+00 6.10752058e+00 1.10015368e+00
-1.41000807e+00 1.87505439e-01 1.01478434e+00 4.23635542e-01
-9.33506116e-02 -6.23524368e-01 -3.44624370e-01 8.56977403e-01
8.03013146e-01 1.97739705e-01 4.84184712e-01 6.73814178e-01
-3.32173228e-01 8.23289305e-02 -5.75255811e-01 1.01856184e+00
4.59233373e-01 -1.42894065e+00 4.66272593e-01 2.29887605e-01
1.08012164e+00 1.63066182e-02 3.45733106e-01 1.76970541e-01
3.18174660e-01 -1.38127494e+00 7.91462004e-01 6.79044485e-01
8.93562078e-01 -5.00440657e-01 8.45759213e-01 3.99335325e-01
-6.02510810e-01 -2.34982044e-01 -9.70426127e-02 2.80533940e-01
-4.52603623e-02 6.33955181e-01 -4.96885657e-01 4.84203070e-01
4.54439551e-01 5.40216267e-01 -6.79163635e-01 6.26688957e-01
-2.76995242e-01 5.81458151e-01 1.49155289e-01 1.71702821e-02
5.09419560e-01 -1.53993085e-01 5.99758267e-01 1.22273278e+00
4.10256445e-01 -4.19158340e-01 -4.18744385e-01 1.16087747e+00
-1.85510993e-01 -3.23590457e-01 -8.21586490e-01 -4.43776518e-01
6.06999174e-02 1.20838499e+00 -8.67380440e-01 -4.94824976e-01
6.51973560e-02 1.78443313e+00 4.89424802e-02 1.16333298e-01
-9.99285579e-01 -2.12981984e-01 5.28156340e-01 1.36143086e-03
3.99685055e-01 1.26967162e-01 -5.35005704e-02 -1.40656185e+00
-2.34458119e-01 -9.26896393e-01 2.86857605e-01 -9.36379969e-01
-1.66820896e+00 1.12566471e+00 -4.70707387e-01 -1.02700162e+00
-3.16001832e-01 -1.06229961e+00 -4.56046283e-01 6.85183465e-01
-1.46231055e+00 -1.37713468e+00 -5.15179396e-01 6.23462200e-01
3.90700877e-01 -7.62014091e-01 8.02301824e-01 4.15851712e-01
-5.69374561e-01 5.54543555e-01 2.94416040e-01 3.42978656e-01
2.72732824e-01 -1.08254850e+00 5.10232568e-01 9.33993995e-01
1.64289445e-01 -2.33597949e-01 2.76224077e-01 -4.76450354e-01
-1.30033898e+00 -1.23123026e+00 3.96936744e-01 -4.15301293e-01
8.13688815e-01 -2.11642727e-01 -9.65976000e-01 3.48091364e-01
3.11938375e-01 2.21873671e-01 2.67393380e-01 -1.18160176e+00
-3.62295985e-01 2.07702994e-01 -1.75665748e+00 1.01252988e-01
7.93662310e-01 -5.82774341e-01 -3.10204864e-01 1.52587250e-01
4.75420337e-03 -2.28717640e-01 -6.75618887e-01 2.78543860e-01
4.92448896e-01 -1.17052877e+00 1.22615290e+00 -5.56385815e-01
8.55300426e-01 -1.34463832e-01 1.01535365e-01 -1.43830538e+00
-2.69393981e-01 -2.63897717e-01 -3.97379041e-01 1.13832819e+00
-4.60811332e-02 -8.90732884e-01 7.74176419e-01 1.98512718e-01
2.90126260e-02 -4.36319351e-01 -9.83386755e-01 -9.25012887e-01
2.80484587e-01 -5.41709363e-02 4.41632688e-01 1.11671710e+00
-1.11872315e+00 2.15039536e-01 -9.12771523e-01 6.65822476e-02
4.96839672e-01 -1.01826459e-01 8.92037868e-01 -1.14510882e+00
-2.53859639e-01 -9.53125775e-01 -1.04416203e+00 -6.81025982e-01
2.18785092e-01 -8.65550041e-01 -3.98370832e-01 -1.11998582e+00
-1.15779027e-01 -3.00158173e-01 -1.77795842e-01 2.70297498e-01
1.16981700e-01 8.57189953e-01 3.30648005e-01 4.04420525e-01
1.19417556e-01 5.29334903e-01 1.06364727e+00 -5.81153452e-01
3.78635257e-01 -1.08587518e-01 -3.90720189e-01 5.83158672e-01
6.90679312e-01 -4.72188175e-01 -2.99545005e-02 -3.28142583e-01
-2.49878079e-01 1.66084971e-02 1.10493445e+00 -1.27456129e+00
-3.04307342e-01 2.13668138e-01 6.05198801e-01 -3.11116338e-01
2.79106885e-01 -6.62822843e-01 4.00207669e-01 8.92526209e-01
-2.30221614e-01 -1.55775562e-01 2.34779164e-01 4.99160677e-01
-3.46944422e-01 -2.74887979e-01 1.26171565e+00 -1.08160771e-01
-8.50191474e-01 4.39610146e-02 -6.79935992e-01 -7.55420402e-02
1.33946097e+00 -2.81427115e-01 -7.62276590e-01 -3.52111399e-01
-7.93866158e-01 -5.44743180e-01 3.82247239e-01 5.09096980e-01
6.97038710e-01 -1.35715532e+00 -8.95985603e-01 3.78015786e-01
3.45810689e-02 -4.38646436e-01 3.24815452e-01 5.23591518e-01
-7.82213449e-01 1.96923494e-01 -7.11930096e-01 -4.13289487e-01
-1.11726880e+00 5.98713219e-01 7.11187303e-01 -4.08854872e-01
-3.50431055e-01 8.90580773e-01 2.50920475e-01 -1.15517996e-01
-1.35310709e-01 9.38213840e-02 -1.79759607e-01 -2.80495547e-02
5.12467027e-01 5.33485293e-01 3.03452790e-01 -1.03900075e+00
-1.84543744e-01 3.63835871e-01 2.60520410e-02 3.15433294e-01
1.01230931e+00 3.16206485e-01 1.09049961e-01 -8.62375498e-02
1.14040601e+00 -3.04939896e-01 -1.14061284e+00 4.01782356e-02
-4.22912352e-02 -4.63836581e-01 2.01620251e-01 -1.34901869e+00
-1.31570160e+00 9.75979388e-01 9.30938423e-01 7.25835323e-01
1.22112560e+00 -2.53984988e-01 8.38782251e-01 6.98107481e-02
4.03228164e-01 -7.04770029e-01 2.86326766e-01 2.67674148e-01
1.23076212e+00 -1.12274194e+00 -4.81714100e-01 -1.37371987e-01
-7.33134687e-01 1.10726118e+00 4.79907930e-01 -6.14765704e-01
3.32354456e-01 2.27191761e-01 1.74124449e-01 -1.93126917e-01
-2.10034177e-01 -3.82919163e-02 4.57110077e-01 7.52828598e-01
-2.64484704e-01 1.35520101e-01 2.93811341e-03 4.59232211e-01
7.99414888e-02 3.90676074e-02 6.10225141e-01 6.16406083e-01
1.16887279e-01 -9.72643793e-01 -4.64849919e-01 3.91977400e-01
-4.29835916e-01 9.28781331e-02 -1.32729614e+00 8.84232640e-01
1.97546557e-01 7.81958818e-01 -4.45971079e-02 -5.57312429e-01
1.32987410e-01 -2.47659326e-01 5.73419213e-01 1.14498492e-02
-1.07411265e+00 -5.08355081e-01 -5.14427237e-02 -2.17725068e-01
-3.43446136e-01 -2.92613089e-01 -6.28530145e-01 -2.90412247e-01
-2.88692147e-01 -1.16336264e-01 6.83396280e-01 7.82818854e-01
3.19816262e-01 5.18162429e-01 7.75091112e-01 -1.08641255e+00
-5.30702651e-01 -9.33508098e-01 -5.27166784e-01 6.25044405e-01
2.84644425e-01 -5.25745749e-01 -6.37322843e-01 8.64371732e-02] | [12.46102523803711, 1.074063777923584] |
5856db94-4f39-4826-8659-eba41e31f996 | type-enhanced-ensemble-triple-representation | 2305.01556 | null | https://arxiv.org/abs/2305.01556v1 | https://arxiv.org/pdf/2305.01556v1.pdf | Type-enhanced Ensemble Triple Representation via Triple-aware Attention for Cross-lingual Entity Alignment | Entity alignment(EA) is a crucial task for integrating cross-lingual and cross-domain knowledge graphs(KGs), which aims to discover entities referring to the same real-world object from different KGs. Most existing methods generate aligning entity representation by mining the relevance of triple elements via embedding-based methods, paying little attention to triple indivisibility and entity role diversity. In this paper, a novel framework named TTEA -- Type-enhanced Ensemble Triple Representation via Triple-aware Attention for Cross-lingual Entity Alignment is proposed to overcome the above issues considering ensemble triple specificity and entity role features. Specifically, the ensemble triple representation is derived by regarding relation as information carrier between semantic space and type space, and hence the noise influence during spatial transformation and information propagation can be smoothly controlled via specificity-aware triple attention. Moreover, our framework uses triple-ware entity enhancement to model the role diversity of triple elements. Extensive experiments on three real-world cross-lingual datasets demonstrate that our framework outperforms state-of-the-art methods. | ['Min Yang', 'Xueyan Zhao', 'Haihang Wang', 'Chengxiang Tan', 'Zhishuo Zhang'] | 2023-05-02 | null | null | null | null | ['entity-alignment', 'specificity', 'entity-alignment'] | ['knowledge-base', 'natural-language-processing', 'natural-language-processing'] | [-0.31905043 0.12525897 -0.50471383 -0.40628967 -0.75003153 -0.5653738
0.500777 0.3637303 -0.45931542 0.688959 0.54784167 0.01414781
-0.4663602 -0.95503193 -0.9050132 -0.5292895 0.09514716 0.5043149
0.20721108 -0.63851714 -0.04171581 -0.10849088 -1.3793038 0.2843405
1.4671763 0.8263725 -0.06161733 -0.18534926 -0.47485444 0.5371505
-0.41324073 -0.95654273 0.04412583 -0.04212354 -0.7239459 -0.3612716
0.40873733 0.5019454 -0.15297642 1.1731647 0.6000498 -0.16949415
0.5452167 -1.5436792 -1.3061258 0.9494646 -0.6007389 0.10044342
0.22083639 -0.3216841 1.3881232 -1.1497296 0.69626796 1.2923284
0.82902825 0.09407239 -1.0157819 -0.67253524 0.42370412 0.8349715
-1.75406 -0.2149578 0.90001607 -0.24773596 0.9399918 0.287496
0.5893877 0.78445137 -0.19970933 0.79433846 0.74937844 -0.52771693
-0.38251925 0.4312001 0.17679404 0.5327548 0.75005585 -0.2753725
-0.5011003 -0.02729814 0.2875419 -0.48802698 -0.32107785 -0.62508905
-1.620723 0.40569037 0.7528363 0.52595705 -0.36490843 -0.14328408
0.52618194 0.06906354 0.4582478 0.4366438 -0.8121248 0.29788578
-0.13034238 0.2790805 0.3835112 1.5107194 0.9749184 -0.10439692
-0.15655269 0.820836 0.48642203 0.38922513 0.61676955 -0.22392926
1.0009646 1.3102169 0.16653818 -1.3808129 -0.46883458 -0.76622295
-0.7330487 -0.6755957 0.05873871 0.0994918 -0.4571698 2.0507567
0.8660668 0.29323128 0.38230035 0.6061264 1.2315689 0.41131538
0.49323195 -0.15640111 1.8818438 -0.87489545 -1.1258835 -0.16397151
1.1278303 -0.43561897 0.957336 -0.48475888 -0.6922582 -0.551734
-1.0945128 -0.268166 -1.0075256 0.17571408 0.58106005 0.500078
-0.43140078 0.15044212 -0.28318048 -0.17979428 0.18327707 0.35386416
-0.7170672 0.08670763 -1.9606837 1.0974853 1.0681478 0.42732027
0.26438183 -1.2066222 -1.187493 0.04704412 0.6969412 -1.0613077
0.36082694 -0.4971096 -0.71647257 0.8403831 -0.2313883 -0.21072762
0.13407822 -0.22806995 -1.2797258 -0.4405842 0.5776544 0.21784435
0.21001445 -1.4250218 -0.82143396 -0.7913914 -0.04928811 0.70403385
-0.52408814 -0.0503407 -0.7012933 -0.8127009 0.3062368 -0.6983923
0.16980119 -0.5940193 -0.58649355 -0.48407313 0.51513493 -0.79143816
1.7805402 -1.868763 0.33321422 0.2440198 0.10949793 0.1979042
-0.04551572 0.27798963 -0.26459253 0.37812555 -0.16915727 0.07286907
0.36714506 0.17572747 -0.05660937 0.15085135 0.19334593 1.2936842
-0.9272427 -0.82409656 -0.05501749 0.47286847 -0.4015527 -0.13808423
-0.02575737 0.21224134 -0.5191705 0.7218939 0.83249897 -0.19651224
0.6431714 -1.0436976 -0.00883237 0.35526392 -1.3817558 1.7319316
-0.5254463 -0.00601989 -0.42346132 -0.80480075 0.7828877 0.13118844
0.4161295 -1.0177311 -0.12091431 0.4841156 -0.01911875 -0.51632756
1.1220878 0.22678687 -0.43976423 0.02389609 0.17488123 0.6156053
0.22857684 0.18529531 0.3489432 0.44089383 0.6084003 -0.40492418
0.85374165 0.05600589 1.1320347 0.15889879 0.03542053 -0.06358106
0.16249417 -0.39206266 -0.83692306 -0.8048903 -0.2527861 1.0661924
0.84296054 -0.76947206 -0.46847376 -0.9644772 0.25034818 0.6931378
-0.8010672 -0.27845126 -0.7425301 -1.1517091 0.51566786 0.68294203
0.6550648 -0.6717479 0.25515252 0.31181008 -0.64396197 -1.3537835
-0.5796048 -0.21721819 -0.3146202 -1.1061083 -0.26168713 -0.9978538
0.6780483 0.0219977 1.3019773 -0.09527025 0.03448332 0.2114136
-0.29221603 -0.30011895 -0.01019412 0.3962775 0.23679122 0.38166317
0.83265954 -0.5160189 -0.521069 0.529432 -0.5792992 0.02135816
0.4149835 0.8657017 0.9041622 0.11278987 0.8145962 -1.1447875
0.4216811 -0.77521586 -0.41593567 1.0392982 -0.71396166 0.29218054
0.44631243 -0.18093872 -1.2943776 -0.3668921 0.23810077 -0.03977919
0.1567175 0.7702427 -1.0224771 0.15995535 0.39525172 0.3848297
-0.7621608 -0.40741053 0.7486097 0.41270277 0.628142 -0.86544245
0.82582664 0.2313165 -0.09614133 -0.3282107 -0.90585434 -0.4831836
-0.9130105 0.14392228 0.7899123 -1.2834446 -0.5496527 0.34126574
-1.1461656 0.5689972 -0.17159197 0.47909078 -0.12200114 0.1800572
0.00887372 -0.36684212 -0.2387547 -0.73533475 1.0399921 0.2978626
0.03747489 -1.2761827 0.04715494 0.43261048 0.2077661 0.10560217
1.1963147 -0.92001885 -0.6696978 -0.00608428 -0.29175815 -0.22555782
0.3897576 -0.1719116 -0.5557023 0.06154682 -0.53697956 0.21615718
0.5181023 -0.02157367 0.9307724 -0.48940057 -0.5725248 0.8271048
1.5405477 -0.03835937 0.64958787 0.76478505 1.4618847 0.7834484
0.96267724 0.06972623 1.4048944 1.2243581 0.18117616 -0.1383668
0.01149226 -0.57509947 -0.10899591 1.0880089 -0.21320572 -0.31694558
-0.7116482 0.9495968 -2.0970693 -1.0784649 -0.43927488 2.0422506
0.951763 -0.30135494 0.07464302 -0.1607367 0.9245577 -0.07140965
-0.46053898 0.2716121 -0.59296775 -0.4777471 0.5387043 0.2567804
-1.1898551 1.0874963 4.3178773 1.0911016 -0.6341483 0.09942418
0.17189845 0.4606841 -0.9732344 0.06497261 -1.2295426 0.7085894
0.37347746 -0.7248684 -0.0877037 0.5701227 -0.42354578 0.4383631
-0.7710804 0.91027915 0.05705805 -1.2893865 0.2737312 0.0522395
0.6083983 -0.38068548 -0.02607205 0.44414812 0.3917315 -0.61284506
0.7500341 0.32641378 0.78841704 -0.86266977 0.7928831 -0.12305842
-2.0120509 0.14038765 -0.25009862 0.8338878 0.21914095 0.45832604
-0.60671586 1.5923231 0.8260077 0.9578652 -0.79022276 0.6735692
-0.3209364 0.07134236 -0.24892841 0.29335675 -0.08007017 -0.19910611
0.7269669 1.143921 0.45703432 -0.16887082 -0.10547474 0.8248953
-0.30160493 0.5883745 -0.5560742 0.24110766 1.0775509 1.1608624
-0.21716437 -0.28767204 -0.57580733 0.8441185 0.63078576 0.25219992
-1.0289689 -0.50080824 0.7909342 -0.14025065 0.4191982 0.30341902
-0.26313922 -1.5407863 0.48749074 -0.6022156 0.85478127 -0.7001438
-1.4121472 0.70711684 0.10530739 -1.5256817 -0.01599297 -0.2433155
-0.1948506 0.7896419 -1.8139138 -1.8297821 -0.14032787 0.64166105
0.02057175 -0.22529013 0.72075444 0.80634874 -0.7785535 1.0348167
0.01265259 0.18482396 0.79573566 -1.3640422 0.45216897 0.92762727
0.21188551 1.0564915 0.46893522 -0.81570846 -1.2981052 -1.3819757
1.3852253 -0.7203316 0.700011 -0.26341432 -1.2308226 0.9732579
0.24203436 0.2748298 0.98318255 0.5313046 -0.7291561 -0.30802125
-0.8810694 0.6691274 1.4917666 -0.5465567 -0.77336013 -0.04030452
0.9849871 -0.4205596 -1.3220837 0.8529561 0.49535483 -0.39918384
1.1991246 -0.8571646 0.05128112 -0.88918054 -0.31555992 -1.6092051
-0.49498844 -0.26133698 -0.31364658 1.8513628 0.6713194 -0.7052225
0.33390012 0.44130906 -0.30412054 -0.5100641 -0.8641003 -0.8855601
-0.033348 -0.0242345 1.416663 1.637081 0.07077289 0.5624892
-0.3785297 0.63032365 0.6247424 0.30803165 0.67500645 -1.2099411
0.11250405 -0.22754209 -0.61681867 -0.7264229 0.40048403 -1.1861309
-0.44077566 -1.4641565 0.05769064 -0.80495733 -0.5634125 0.37593365
-0.6695013 -0.02319142 0.00742671 0.08750275 -0.8660385 0.9314223
1.0443759 -0.14807366 0.03555181 -0.5300409 -1.1756845 0.58928865
0.3669564 -0.5053499 -0.46791255 -0.69533277 0.73108554 -0.40868673
0.26211384 -0.50534976 0.42161834 -0.13580437 0.0880395 -0.5714403
0.08273362 -1.1345358 0.43949905 -0.13656181 -0.19079079 0.25267598
0.21190329 0.7881919 -0.5837125 0.20442207 0.15649623 0.05798276
-1.2766201 0.3447456 0.505422 0.4146058 1.1205018 -0.24953036
-0.7385128 0.35480043 -0.59570235 0.62717134 0.30591395 0.7853471
0.16427329 -2.1121747 -0.8997204 0.19515921 0.9218 0.08616044
0.67051613 0.77796465 0.10586084 0.30329818 -0.07247157 -0.41130283
-1.3737319 0.47948036 0.3419526 -0.51169556 -0.2339146 0.7898021
0.34564844 -0.97167796 -0.12591526 0.14726701 -0.626003 0.31701794
0.29706106 0.249232 0.36359182 -1.2815741 -0.77584594 0.91025186
-0.26152486 0.2406213 1.2766536 -0.4749254 -0.34765923 0.31254378
1.0946443 0.31667703 -0.4369267 -0.7508736 0.31769374 -0.576709
-0.29462916 -0.7762757 -1.0178447 0.34235305 0.2907674 -0.02405466
0.9838126 0.07702273 0.5728662 0.16628656 0.4547433 -1.1779703
-0.5151795 0.3633201 0.86923647 -1.2567626 -0.10139025 -0.9635302
-0.8749136 0.559761 1.0806237 0.40169203 0.64201254 -0.23739788
-0.13148655 -0.4529625 -0.5483024 -0.39957178 0.7929916 0.70464915
0.4446816 0.17397325 -0.44593066 0.98724 -0.16131873 -0.3062004
-0.02060154 0.6421083 0.18241826 -1.2437305 -0.0262819 0.12791526
-0.30459988 -0.5230615 -0.22274908 0.9726556 0.5026717 0.44204625
-0.01318656 -0.49272606 0.65455097 0.08562904 0.43882528 -0.26978427
-0.6205349 -0.4595678 0.43257722 -0.32436535 -0.66881865 -0.5203009
-1.1355532 -0.26945245 -0.6308658 0.26277435 0.46496075 0.9082358
0.95411485 0.6657994 0.55012196 -0.04424934 0.01418186 -0.7776612
-0.5436073 0.70878357 0.02979775 -0.9045312 -0.07765246 -0.09176821] | [8.760917663574219, 7.978930473327637] |
d078f676-6139-46e1-a2c8-c82b307ef855 | algorithmic-trading-with-fitted-q-iteration | 1805.07478 | null | http://arxiv.org/abs/1805.07478v1 | http://arxiv.org/pdf/1805.07478v1.pdf | Algorithmic Trading with Fitted Q Iteration and Heston Model | We present the use of the fitted Q iteration in algorithmic trading. We show
that the fitted Q iteration helps alleviate the dimension problem that the
basic Q-learning algorithm faces in application to trading. Furthermore, we
introduce a procedure including model fitting and data simulation to enrich
training data as the lack of data is often a problem in realistic application.
We experiment our method on both simulated environment that permits arbitrage
opportunity and real-world environment by using prices of 450 stocks. In the
former environment, the method performs well, implying that our method works in
theory. To perform well in the real-world environment, the agents trained might
require more training (iteration) and more meaningful variables with predictive
value. | [] | 2018-05-18 | null | null | null | null | ['algorithmic-trading'] | ['time-series'] | [-4.94615495e-01 8.80105942e-02 -3.12502861e-01 -1.44463718e-01
-4.48627740e-01 -7.22799480e-01 4.75171715e-01 -4.61655766e-01
-7.35929966e-01 1.30657125e+00 -3.78385186e-01 -8.25901449e-01
-1.45911783e-01 -8.95517945e-01 -6.55892849e-01 -4.22551572e-01
-3.84173751e-01 7.45930135e-01 2.64716297e-01 -2.80885577e-01
5.77107787e-01 2.65351802e-01 -1.16911387e+00 -2.46718436e-01
8.60965848e-01 1.25636399e+00 -9.94588807e-02 5.04948616e-01
-1.67335272e-01 9.89818871e-01 -9.02061880e-01 -7.38092482e-01
1.26815176e+00 -5.45237839e-01 -3.15088481e-01 -1.49833292e-01
-4.19566125e-01 -6.41752899e-01 2.92421848e-01 1.08893538e+00
1.36806652e-01 1.51956037e-01 4.75644290e-01 -1.48944509e+00
-4.17015851e-01 6.56482577e-01 -6.65673614e-01 3.38852048e-01
-5.17117567e-02 4.34820771e-01 9.76179957e-01 -5.35299838e-01
4.30440426e-01 1.05220592e+00 5.90292871e-01 2.62447625e-01
-1.15317011e+00 -9.46869850e-01 -2.05236837e-01 -3.56304824e-01
-6.25743330e-01 -2.05584019e-02 8.02233100e-01 -1.64363727e-01
9.48617220e-01 1.68583736e-01 1.22612023e+00 6.30559623e-01
5.67912817e-01 5.58144808e-01 1.53375769e+00 -3.24798048e-01
6.67030752e-01 4.28390682e-01 -2.01343909e-01 5.04561253e-02
4.83526379e-01 1.21204317e+00 -3.56220216e-01 -4.59711224e-01
1.42777598e+00 3.51750758e-03 4.58591014e-01 -6.21657789e-01
-1.01847422e+00 1.47322822e+00 2.60814041e-01 1.56829059e-02
-6.80839956e-01 3.68360162e-01 2.25188553e-01 1.16918731e+00
3.34451824e-01 1.05980408e+00 -9.15780008e-01 -4.18199003e-01
-9.74124610e-01 8.09366703e-01 1.15750110e+00 5.94063282e-01
4.57765430e-01 4.76077825e-01 2.29532897e-01 4.95375335e-01
4.76969481e-01 5.62650025e-01 8.42644155e-01 -1.61927152e+00
4.13852960e-01 3.77668023e-01 7.89827228e-01 -4.44219708e-01
-2.41652414e-01 -6.98186696e-01 -2.10061803e-01 7.00463712e-01
8.75865519e-01 -6.26375914e-01 -6.48889244e-01 1.63908494e+00
9.36373174e-02 9.12599862e-02 4.35021490e-01 6.94263756e-01
-2.98400939e-01 5.43562412e-01 -1.82733148e-01 -8.79984081e-01
9.38193500e-01 -9.16020215e-01 -7.78129697e-01 2.51112282e-02
4.68579441e-01 -6.93098664e-01 9.89422381e-01 6.19196355e-01
-1.30522978e+00 -2.91062713e-01 -7.69960761e-01 8.66916478e-01
-2.37197384e-01 -8.15266550e-01 1.27040339e+00 8.85799944e-01
-8.83422196e-01 8.23572993e-01 -4.99355704e-01 1.65589571e-01
2.19810069e-01 6.86437786e-01 3.22103560e-01 8.95760417e-01
-1.55451548e+00 9.84071374e-01 4.33360189e-01 -1.50738791e-01
-7.27559566e-01 -5.74053586e-01 -3.52533489e-01 4.53519560e-02
5.78036010e-01 -5.82057774e-01 1.79677057e+00 -1.52702534e+00
-1.86161804e+00 2.33649284e-01 5.83010197e-01 -1.12399006e+00
1.06198573e+00 -1.61354661e-01 -2.88280874e-01 -2.05486596e-01
-1.78784013e-01 5.39574087e-01 7.95550108e-01 -1.04751039e+00
-6.48931324e-01 -4.68515158e-02 6.12211898e-02 2.59375781e-01
3.34446549e-01 2.73173060e-02 4.73075479e-01 -1.02628136e+00
-1.06958181e-01 -7.39822388e-01 -6.19997561e-01 -3.24236214e-01
4.52694595e-01 6.97434992e-02 3.08823079e-01 -2.46484697e-01
9.98759270e-01 -1.67050827e+00 -7.46444523e-01 6.84730828e-01
-1.02754846e-01 -4.53453995e-02 1.83362558e-01 7.12835312e-01
-1.35547981e-01 2.15686038e-01 -2.11255923e-01 1.70839712e-01
3.67898464e-01 4.60327029e-01 -5.11688113e-01 1.35452002e-01
-6.35712594e-02 1.13295162e+00 -7.28381336e-01 -4.29914594e-01
-7.77836666e-02 -5.71258008e-01 -7.62331128e-01 3.04149419e-01
-5.12487650e-01 3.14081162e-01 -5.19887805e-01 5.30956268e-01
5.82164228e-01 1.50788517e-03 1.92646123e-02 6.42866969e-01
-1.73762321e-01 1.99847873e-02 -1.55052602e+00 1.06690717e+00
-7.60758296e-02 1.58454135e-01 -2.62930691e-02 -8.95888090e-01
9.03272867e-01 1.94394052e-01 4.18999553e-01 -1.14910436e+00
1.02227293e-01 4.39270377e-01 4.85139370e-01 -2.39821509e-01
3.83889258e-01 -8.87493551e-01 2.29588021e-02 1.14671195e+00
-3.34127635e-01 -3.79158527e-01 1.00964807e-01 -2.27692991e-01
7.23970950e-01 2.68391877e-01 4.61530089e-01 -5.18422365e-01
-1.11849383e-02 2.77247012e-01 8.98105025e-01 9.81985033e-01
-5.68126082e-01 -2.14170933e-01 8.68166268e-01 -6.81820452e-01
-1.15932465e+00 -1.02730501e+00 -1.17959552e-01 9.86738920e-01
9.41898860e-03 3.16918224e-01 -4.42489713e-01 -6.51547253e-01
6.19409025e-01 7.29215026e-01 -5.92044294e-01 2.55163074e-01
-3.77084017e-01 -1.11299717e+00 1.11314006e-01 2.96846271e-01
5.38007140e-01 -1.35443985e+00 -1.19205379e+00 5.38513422e-01
7.13464439e-01 -2.83697248e-01 -1.81874201e-01 4.34462816e-01
-1.21006238e+00 -8.99766147e-01 -4.18344557e-01 -2.73279518e-01
2.57875651e-01 -2.15288475e-01 1.36249065e+00 -2.72958627e-04
3.12666565e-01 -4.63097766e-02 -1.78230882e-01 -8.52249384e-01
-5.47223449e-01 -3.97567213e-01 1.43106189e-02 -4.05693412e-01
3.73794019e-01 -4.25477117e-01 -7.60466456e-01 4.18527991e-01
-8.98361325e-01 3.12499329e-03 6.32538259e-01 1.27364087e+00
1.77800268e-01 1.61050200e-01 1.22641730e+00 -1.05351782e+00
1.06651199e+00 -4.66114372e-01 -1.42821026e+00 1.30617693e-01
-1.16057980e+00 3.17454040e-01 5.47349572e-01 -6.16525471e-01
-1.01872301e+00 -1.43216357e-01 2.78312415e-01 -2.19829470e-01
4.48282391e-01 6.24651968e-01 2.77770162e-01 -2.44607832e-02
5.02160013e-01 -1.21443734e-01 4.74668175e-01 -3.73785526e-01
1.48957312e-01 3.97651762e-01 4.11767811e-02 -5.08107364e-01
9.10017371e-01 -9.10626631e-03 9.26184505e-02 4.01057117e-02
-9.47489366e-02 1.26925230e-01 -3.18796605e-01 1.20513424e-01
1.95521519e-01 -6.07028961e-01 -8.97281885e-01 3.51202160e-01
-5.19317627e-01 -7.71908879e-01 -7.90191948e-01 6.79052711e-01
-1.09120309e+00 -9.29634720e-02 -5.93830228e-01 -1.25467539e+00
-1.43830240e-01 -9.77187037e-01 1.75483957e-01 2.67553478e-01
-1.39468104e-01 -1.23760927e+00 5.47990859e-01 6.69380352e-02
5.55455506e-01 2.18037248e-01 6.55394077e-01 -1.13208413e+00
-7.32198536e-01 1.09823823e-01 7.49283880e-02 1.16514884e-01
1.50517467e-02 -2.70065367e-02 -7.85407722e-01 -3.75034809e-01
5.13888478e-01 -3.85588616e-01 3.54354650e-01 4.43401277e-01
6.24634862e-01 -4.75348324e-01 2.71981418e-01 2.25593582e-01
1.43487108e+00 8.35897803e-01 1.66352808e-01 7.09279954e-01
-2.34003723e-01 7.36856818e-01 1.13311505e+00 7.11101830e-01
-1.95820685e-02 4.41136003e-01 3.31437856e-01 -1.71139479e-01
8.19337547e-01 -4.12103564e-01 3.58562857e-01 5.47062457e-01
1.57846138e-01 3.54150623e-01 -7.90389061e-01 2.27176994e-01
-2.02412510e+00 -1.02599657e+00 3.04786623e-01 2.26011086e+00
1.08672166e+00 6.73081934e-01 8.03377986e-01 3.22147436e-03
3.50615025e-01 -3.08655471e-01 -1.02722740e+00 -8.88246715e-01
-3.84464711e-02 3.59345794e-01 7.83015668e-01 5.54265440e-01
-7.24894047e-01 7.83929527e-01 7.99329472e+00 5.86451590e-01
-8.24307978e-01 -2.27819420e-02 8.96963954e-01 -1.25633091e-01
-5.22040009e-01 2.93049663e-01 -2.27591053e-01 6.25562847e-01
1.34283721e+00 -6.30829751e-01 4.99209374e-01 8.13502848e-01
4.99387026e-01 -4.21280354e-01 -9.23973739e-01 7.29874074e-01
-8.20217788e-01 -1.18351316e+00 -1.43884853e-01 3.52561563e-01
7.90317833e-01 -3.49029452e-01 3.01794201e-01 5.07508636e-01
8.33054781e-01 -1.08785605e+00 7.39310205e-01 4.71040010e-01
2.35400990e-01 -9.87248659e-01 1.08112001e+00 6.25567436e-01
-5.54269493e-01 -4.46796954e-01 -4.26188946e-01 -6.13508880e-01
-1.22494891e-01 2.92691380e-01 -7.51154780e-01 2.84035444e-01
2.63519764e-01 2.87927747e-01 -3.43709469e-01 1.08099043e+00
4.52230386e-02 4.78187770e-01 -4.98113245e-01 -2.87886024e-01
5.62714577e-01 -7.71598399e-01 1.04399659e-01 5.69324970e-01
3.40263814e-01 2.96204165e-02 -1.15747482e-01 1.04802012e+00
9.80174467e-02 2.03563049e-01 -6.97841942e-01 -3.52262482e-02
4.28904533e-01 7.53734529e-01 -8.29519868e-01 -2.84647793e-01
-6.00907862e-01 4.87517655e-01 -1.23350881e-01 4.84281093e-01
-7.11784661e-01 -1.39855459e-01 4.30555582e-01 -5.86918555e-02
1.31931379e-01 3.49144377e-02 -5.02988160e-01 -9.65292990e-01
-1.41287416e-01 -1.14928651e+00 4.37796265e-01 -3.86826038e-01
-1.43182552e+00 1.03960626e-01 3.21887024e-02 -1.29062033e+00
-1.00677371e+00 -6.22807443e-01 -5.71905613e-01 8.74951005e-01
-1.49194312e+00 -4.73116785e-01 6.80228293e-01 3.83655161e-01
4.13927466e-01 -5.03907204e-01 5.33930957e-01 -2.26600453e-01
-2.80887991e-01 3.97943020e-01 5.20240664e-01 -5.34924902e-02
4.80099052e-01 -1.58383620e+00 5.05060613e-01 4.55636919e-01
2.53259271e-01 6.65034175e-01 9.26971853e-01 -8.46527040e-01
-1.15008485e+00 -3.87173057e-01 2.93729305e-01 -4.60108906e-01
1.20539153e+00 -1.54017508e-01 -7.54821599e-01 5.36887169e-01
3.66301179e-01 -2.94550598e-01 6.23612761e-01 -2.34587148e-01
1.39446765e-01 -3.13886583e-01 -1.31455374e+00 4.10308480e-01
4.67845857e-01 -2.85530418e-01 -1.11925030e+00 5.47099952e-03
5.45447409e-01 -1.66020587e-01 -8.88569951e-01 1.63939640e-01
7.28908300e-01 -1.19640911e+00 5.33055663e-01 -8.15585196e-01
-7.25879297e-02 5.80830835e-02 2.08616197e-01 -1.32054901e+00
1.01722620e-01 -1.40698242e+00 -1.03829809e-01 7.12795794e-01
7.89353311e-01 -1.15654659e+00 1.01677620e+00 1.03463340e+00
6.31252289e-01 -7.13187516e-01 -1.08514738e+00 -1.02908885e+00
7.41852164e-01 -2.33256862e-01 1.05664146e+00 9.03528392e-01
1.83419049e-01 -1.81585684e-01 -3.61210972e-01 -6.41806424e-01
8.12738359e-01 5.45412421e-01 7.42788911e-01 -1.25884163e+00
-6.57868981e-01 -5.83695233e-01 1.63917646e-01 -8.26602995e-01
5.34583703e-02 -1.93905115e-01 -3.79096240e-01 -6.79169476e-01
1.62624002e-01 -6.63771451e-01 -6.02902293e-01 2.13693250e-02
-9.18464139e-02 -6.62026107e-02 4.33598667e-01 4.35586125e-01
-2.92011976e-01 4.21498805e-01 1.35901463e+00 3.66128176e-01
-5.87151885e-01 4.53194767e-01 -6.60128653e-01 6.39803410e-01
1.09953916e+00 -4.72628444e-01 -6.20336831e-01 2.51181781e-01
5.88748038e-01 5.16584754e-01 1.81847066e-01 -3.82575005e-01
-1.89132858e-02 -7.86905348e-01 4.22812760e-01 -5.46221793e-01
3.80387646e-03 -1.15464890e+00 5.08536756e-01 1.02031267e+00
-3.29125494e-01 6.95485055e-01 4.98460717e-02 3.08871299e-01
-2.54174083e-01 -5.08181751e-01 7.18625307e-01 -5.22215366e-01
-3.67059141e-01 1.06556110e-01 -2.96727657e-01 2.16525972e-01
1.30494332e+00 -5.40159702e-01 -1.43170133e-01 -7.54101694e-01
-5.90505540e-01 5.68470001e-01 7.48429716e-01 -3.84306870e-02
4.35635656e-01 -1.24357677e+00 -3.73860836e-01 4.26775843e-01
-4.55558866e-01 -5.46943903e-01 -6.04878008e-01 4.95863765e-01
-7.90561557e-01 4.01878893e-01 -6.77985013e-01 4.03692573e-02
-4.40910012e-01 7.91497052e-01 6.98597670e-01 -5.39453626e-01
-2.05448478e-01 3.01230222e-01 2.59155691e-01 -1.52543634e-01
6.18978105e-02 -5.07196128e-01 2.57804315e-03 2.01895639e-01
2.48132870e-01 2.41782159e-01 -4.31213856e-01 8.53994340e-02
2.00092494e-01 2.76856452e-01 9.81647894e-02 -8.39928865e-01
1.42345119e+00 -5.24099469e-02 1.30346864e-01 6.99112773e-01
4.10403073e-01 -2.06114978e-01 -1.76357722e+00 -1.26878517e-02
5.71072280e-01 -6.15902841e-01 -2.11190715e-01 -8.24344456e-01
-1.05438125e+00 5.91725588e-01 6.36472404e-01 7.70543456e-01
9.01478767e-01 -5.54639518e-01 5.76786339e-01 5.16288102e-01
5.83334923e-01 -1.53770030e+00 -9.65445265e-02 2.47928917e-01
5.81701815e-01 -1.32982183e+00 -2.03752681e-03 2.74349064e-01
-9.86619353e-01 7.77126133e-01 3.54986727e-01 -4.90500867e-01
8.80600810e-01 3.44326794e-01 5.58376849e-01 -3.23785432e-02
-1.11108446e+00 5.93302436e-02 -3.28983605e-01 4.29649025e-01
-4.10054773e-02 1.19788617e-01 -7.20050156e-01 8.38490963e-01
-6.84907854e-01 2.10470632e-01 6.83301806e-01 1.11763918e+00
-4.79620129e-01 -1.32686186e+00 -4.39359426e-01 6.62886262e-01
-9.04250979e-01 -8.59463681e-03 -4.88067180e-01 1.41694260e+00
-1.38036594e-01 7.11208224e-01 3.27262282e-01 2.43739754e-01
2.19095662e-01 1.85001627e-01 1.77257299e-01 -2.89674759e-01
-1.10232723e+00 6.01466596e-01 -1.08008578e-01 -6.22337997e-01
-5.94123185e-01 -7.50902355e-01 -1.18638372e+00 -4.33354199e-01
-4.01304364e-01 6.28513873e-01 3.14894944e-01 6.15012825e-01
-1.26904488e-01 -1.80392712e-01 1.05652297e+00 -3.11539829e-01
-1.37198770e+00 -8.20272088e-01 -1.27768946e+00 4.23488170e-01
3.55987608e-01 -9.06090081e-01 -6.00238264e-01 -2.63699710e-01] | [4.445273399353027, 3.8426642417907715] |
945535b0-49a1-4543-bdfd-0270d84a3195 | half-real-half-fake-distillation-for-class | 2104.00875 | null | https://arxiv.org/abs/2104.00875v1 | https://arxiv.org/pdf/2104.00875v1.pdf | Half-Real Half-Fake Distillation for Class-Incremental Semantic Segmentation | Despite their success for semantic segmentation, convolutional neural networks are ill-equipped for incremental learning, \ie, adapting the original segmentation model as new classes are available but the initial training data is not retained. Actually, they are vulnerable to catastrophic forgetting problem. We try to address this issue by "inverting" the trained segmentation network to synthesize input images starting from random noise. To avoid setting detailed pixel-wise segmentation maps as the supervision manually, we propose the SegInversion to synthesize images using the image-level labels. To increase the diversity of synthetic images, the Scale-Aware Aggregation module is integrated into SegInversion for controlling the scale (the number of pixels) of synthetic objects. Along with real images of new classes, the synthesized images will be fed into the distillation-based framework to train the new segmentation model which retains the information about previously learned classes, whilst updating the current model to learn the new ones. The proposed method significantly outperforms other incremental learning methods and obtains state-of-the-art performance on the PASCAL VOC 2012 and ADE20K datasets. The code and models will be made publicly available. | ['Xian-Sheng Hua', 'Wenyu Liu', 'Jianqiang Huang', 'Mingyuan Tao', 'Xinggang Wang', 'Wentian Hao', 'Zilong Huang'] | 2021-04-02 | null | null | null | null | ['class-incremental-semantic-segmentation'] | ['computer-vision'] | [ 7.85773993e-01 2.41982996e-01 -4.82358485e-02 -6.27723336e-01
-4.77321863e-01 -5.68702221e-01 3.69142234e-01 -1.96738884e-01
-6.51317120e-01 9.12981749e-01 -4.20423597e-01 -1.30814224e-01
3.26270163e-01 -1.05291319e+00 -1.15295005e+00 -9.64949310e-01
3.97648394e-01 4.60068434e-01 7.49034286e-01 1.57897174e-02
2.17560336e-01 4.34681326e-01 -1.70167243e+00 3.56452256e-01
1.28022063e+00 9.07960415e-01 5.10758042e-01 5.73148251e-01
-4.01748866e-01 7.10726917e-01 -6.96878612e-01 -2.53748208e-01
2.84265041e-01 -6.59524500e-01 -7.51214206e-01 5.36974132e-01
5.07938743e-01 -2.91147381e-01 -2.15056196e-01 1.31713009e+00
2.18535915e-01 2.17223883e-01 3.03469449e-01 -1.14838326e+00
-5.16086876e-01 7.36975491e-01 -3.93520206e-01 -1.24975115e-01
-1.96164086e-01 3.87833774e-01 5.17054081e-01 -9.22417700e-01
8.22139025e-01 1.01077080e+00 5.00962079e-01 7.48031020e-01
-1.25771880e+00 -6.12444997e-01 5.63989401e-01 3.19885820e-01
-1.27813220e+00 -4.41650450e-01 9.43694890e-01 -7.83993676e-02
3.33316475e-01 1.12359978e-01 7.76854217e-01 9.32000518e-01
-1.32970944e-01 9.61935222e-01 1.19609010e+00 -3.76631469e-01
4.66388494e-01 4.24608231e-01 -8.53611976e-02 6.55868411e-01
2.09558368e-01 -9.80752856e-02 -3.15051019e-01 4.09839213e-01
7.12043524e-01 5.03043234e-02 -1.78649440e-01 -5.67646027e-01
-1.16486490e+00 4.95423347e-01 8.55593443e-01 2.90214658e-01
-4.02930588e-01 5.05722426e-02 1.89677000e-01 2.34142795e-01
2.24482283e-01 4.74680990e-01 -6.09341025e-01 2.45514438e-01
-1.12627959e+00 1.53440133e-01 3.81240278e-01 8.38129461e-01
1.20557880e+00 2.07028046e-01 -2.43617967e-01 9.59951878e-01
-7.11416751e-02 1.30912498e-01 6.65249228e-01 -1.06569922e+00
3.04690242e-01 9.04695094e-01 9.54490900e-02 -6.99724615e-01
-1.97650954e-01 -8.19733322e-01 -8.00888002e-01 3.26379955e-01
3.83232117e-01 -2.49618649e-01 -1.57892120e+00 1.64063847e+00
5.35795867e-01 3.86718720e-01 1.78689539e-01 6.55127823e-01
6.15150034e-01 7.72341192e-01 1.07161164e-01 -1.68919474e-01
7.60372996e-01 -1.38674414e+00 -4.82258797e-01 -5.83530724e-01
3.26610208e-01 -4.85063106e-01 9.93425965e-01 3.45280796e-01
-9.12101388e-01 -1.01434004e+00 -1.10938084e+00 2.23589718e-01
-4.61867481e-01 2.01724797e-01 4.24825698e-01 2.89244741e-01
-1.00544322e+00 6.84524059e-01 -9.09535944e-01 -1.16798423e-01
7.82796741e-01 8.39890838e-02 1.99307948e-02 -1.31517291e-01
-1.03751659e+00 3.99588108e-01 9.99321878e-01 2.09369704e-01
-1.12263656e+00 -5.95185339e-01 -6.36375666e-01 -1.04229406e-01
5.72653115e-01 -4.33399737e-01 1.13463116e+00 -1.52096808e+00
-1.46287203e+00 5.83254635e-01 8.82598013e-02 -5.00818491e-01
8.31978798e-01 1.02518983e-01 -1.29743740e-01 6.52061179e-02
2.84244627e-01 1.30498075e+00 1.12894928e+00 -1.71326160e+00
-8.95631015e-01 -1.28919765e-01 1.13910772e-01 3.23346883e-01
-1.34427175e-01 -7.06126630e-01 -6.67931437e-01 -7.77821302e-01
4.65837330e-01 -1.10321939e+00 -4.40160424e-01 1.28596842e-01
-4.56817031e-01 2.04676211e-01 1.08342302e+00 -4.54497546e-01
9.61816192e-01 -2.19144797e+00 1.96655080e-01 -9.99467894e-02
-2.61091232e-01 5.28322220e-01 -1.78465545e-01 -1.90854609e-01
-8.10040534e-02 -1.22274645e-01 -8.43282878e-01 -3.97062659e-01
-4.84456509e-01 4.60258573e-01 -7.34132901e-02 1.25232292e-02
2.15611637e-01 9.21953619e-01 -8.76551092e-01 -4.59690034e-01
3.46461594e-01 1.97838798e-01 -5.30996561e-01 2.42946103e-01
-6.78783059e-01 8.07614565e-01 -2.07995623e-01 5.84233284e-01
8.65712881e-01 -2.09715113e-01 3.79183963e-02 -1.59458771e-01
-7.34166130e-02 -2.41227224e-01 -1.30376852e+00 1.83719218e+00
-3.21252167e-01 2.34629020e-01 -2.07571425e-02 -1.13342535e+00
8.11077178e-01 6.50452599e-02 1.59090877e-01 -5.84395647e-01
7.82699808e-02 7.61643946e-02 -2.90719364e-02 -3.18656296e-01
4.27155256e-01 4.59440015e-02 -1.15882888e-01 1.14733078e-01
5.82675003e-02 -4.84030724e-01 4.21837270e-01 5.67169264e-02
5.68537056e-01 4.19536531e-01 -1.63161531e-01 5.75275309e-02
7.68568158e-01 2.96814293e-01 8.36839795e-01 7.99775183e-01
-6.26185536e-02 7.40834355e-01 3.46595436e-01 -6.40965223e-01
-1.08745921e+00 -1.17119670e+00 -1.23699524e-01 1.01684809e+00
1.85637906e-01 2.04063594e-01 -1.15196061e+00 -9.26306427e-01
-2.30673775e-01 1.00414920e+00 -6.81846142e-01 -3.33564728e-01
-6.50430024e-01 -9.46236670e-01 2.51000047e-01 4.76569504e-01
1.09196508e+00 -1.34961867e+00 -5.99465072e-01 5.29481173e-01
-2.74877548e-01 -9.48867202e-01 -2.94385940e-01 3.47745359e-01
-1.11387622e+00 -1.03338814e+00 -8.22495759e-01 -1.03699732e+00
1.13538206e+00 1.87207101e-04 6.83601797e-01 1.11591361e-01
-2.92933255e-01 -2.01538652e-01 -2.77928948e-01 -2.78756082e-01
-6.69867337e-01 3.75603199e-01 -3.19423020e-01 2.96506017e-01
-1.50950566e-01 -4.16520208e-01 -6.53629243e-01 2.79030561e-01
-1.25290322e+00 4.42831099e-01 6.40132606e-01 9.91506159e-01
9.99234140e-01 4.08141226e-01 7.89735734e-01 -1.29669511e+00
2.06242993e-01 -7.00122043e-02 -5.80974102e-01 1.97334170e-01
-7.05391586e-01 1.01226270e-01 9.09249306e-01 -6.16758525e-01
-1.32701707e+00 4.89321113e-01 -2.72675663e-01 -1.86936185e-01
-2.17347980e-01 1.50992721e-01 -2.73898929e-01 -7.89319798e-02
4.74426836e-01 5.26483715e-01 -1.71643868e-01 -4.11833286e-01
5.79755664e-01 4.52907085e-01 8.99006486e-01 -4.42460060e-01
7.10196733e-01 3.43800783e-01 -4.02939856e-01 -4.42231745e-01
-9.70046401e-01 3.31640989e-02 -9.66176987e-01 -2.20638230e-01
8.62464368e-01 -7.95390189e-01 2.33618334e-01 1.20759499e+00
-8.66203606e-01 -5.76696694e-01 -6.21760011e-01 -1.24172950e-02
-4.78670478e-01 5.47128990e-02 -5.05544662e-01 -3.42501700e-01
-1.07911676e-01 -1.32823968e+00 8.87225151e-01 6.32531106e-01
2.55465180e-01 -6.97604239e-01 -2.74290264e-01 2.64812380e-01
4.95301396e-01 3.00796688e-01 9.89054203e-01 -3.75409752e-01
-7.96181023e-01 -9.28198546e-02 -2.46455103e-01 8.00486922e-01
3.75474006e-01 -6.16586022e-02 -8.78886580e-01 -4.51354563e-01
-1.07833810e-01 -2.11144313e-01 1.04495871e+00 1.67794138e-01
1.57944775e+00 -3.82550120e-01 -4.44899708e-01 7.66227007e-01
1.51653373e+00 5.21905482e-01 5.81139386e-01 4.62704748e-01
8.13606560e-01 4.48592246e-01 4.60345179e-01 1.86369523e-01
2.96760798e-01 2.38211811e-01 5.28400183e-01 -1.16128691e-01
-5.24528265e-01 -3.76035690e-01 -6.91269785e-02 5.91225326e-01
3.41234744e-01 -2.03989699e-01 -6.52383924e-01 6.75456703e-01
-1.67402470e+00 -6.10907614e-01 3.66653442e-01 2.16450715e+00
1.06942821e+00 5.39930463e-01 -2.79015422e-01 9.75577831e-02
8.63717258e-01 2.26163119e-01 -1.12451923e+00 -1.27475694e-01
-8.87319222e-02 1.00914560e-01 5.39721191e-01 5.42645037e-01
-1.10393190e+00 1.45966899e+00 5.69716263e+00 7.40574479e-01
-1.45782697e+00 -8.78150836e-02 1.07261753e+00 1.95543796e-01
-1.72394514e-01 8.64899755e-02 -7.93590844e-01 5.66510856e-01
7.24694073e-01 1.25227168e-01 4.84167248e-01 8.70551050e-01
2.08206624e-02 -3.25647563e-01 -8.06715012e-01 6.22093976e-01
-5.74183725e-02 -1.25379384e+00 3.03486496e-01 -5.52491605e-01
1.26632559e+00 -1.22333512e-01 1.08257458e-02 4.07683611e-01
2.98267186e-01 -6.24042153e-01 7.71155000e-01 7.15554833e-01
7.54662037e-01 -7.05149949e-01 5.83053529e-01 4.78895485e-01
-1.04984391e+00 -1.62350625e-01 -3.79360735e-01 2.72122532e-01
1.60095245e-01 5.30993700e-01 -9.08107758e-01 2.93198824e-01
7.38145709e-01 5.60856283e-01 -1.10123360e+00 1.02792656e+00
-4.50478405e-01 5.28392136e-01 -2.10517794e-01 3.49223614e-01
3.24384212e-01 -1.39751807e-01 3.02687049e-01 7.80943632e-01
2.33355209e-01 -1.64957181e-01 2.25711063e-01 9.01302993e-01
-2.68295944e-01 -2.29341105e-01 -2.49146909e-01 7.32444525e-02
4.58406001e-01 1.03563929e+00 -1.28018105e+00 -7.27048516e-01
-1.05258994e-01 1.42338490e+00 2.62380719e-01 4.80060935e-01
-8.21796238e-01 -4.83825624e-01 2.14938268e-01 1.07313380e-01
6.27465904e-01 -4.98528592e-02 -3.70345086e-01 -9.49533641e-01
-2.24776492e-02 -8.75700831e-01 1.93473041e-01 -7.80432403e-01
-8.67766798e-01 8.92808259e-01 3.88835184e-02 -1.01871419e+00
-1.86655909e-01 -3.59218389e-01 -6.10707581e-01 4.30350572e-01
-1.44905758e+00 -9.67511833e-01 -5.02389908e-01 3.54324222e-01
8.87211680e-01 -5.03193177e-02 5.00053227e-01 2.13575795e-01
-5.98732650e-01 5.40072680e-01 1.47542089e-01 4.17303443e-02
5.62975109e-01 -1.23934209e+00 5.21477103e-01 9.70049858e-01
-4.81759943e-02 2.00181380e-01 5.77081203e-01 -7.38077343e-01
-7.59790540e-01 -1.53111279e+00 4.35239375e-01 -2.03250125e-02
2.86886603e-01 -4.26594049e-01 -1.13294578e+00 5.59868515e-01
5.73713100e-03 1.53702974e-01 4.67927009e-03 -6.79894269e-01
1.07673004e-01 -5.07147670e-01 -1.30385005e+00 7.34123051e-01
1.07049119e+00 -4.37069274e-02 -4.88262534e-01 2.18036160e-01
1.10617399e+00 -4.73214149e-01 -3.70276511e-01 6.50993824e-01
3.28362405e-01 -8.56824756e-01 7.72800505e-01 -1.38345897e-01
6.25176728e-02 -5.28769135e-01 1.11225739e-01 -1.47356880e+00
-7.11638853e-02 -1.89594030e-01 3.45988333e-01 1.27002597e+00
6.11512661e-01 -6.16490960e-01 1.13511336e+00 3.88623267e-01
-1.63460106e-01 -7.37316847e-01 -8.79223824e-01 -4.89435613e-01
2.62269396e-02 -1.97905511e-01 8.08769763e-01 7.42574096e-01
-8.82227778e-01 7.08022490e-02 -1.45775616e-01 9.24696550e-02
6.19357824e-01 2.12127954e-01 7.55495429e-01 -9.62038040e-01
-2.03159466e-01 -2.01201826e-01 -1.23476155e-01 -1.17623937e+00
-1.22638866e-02 -7.96181262e-01 3.83084327e-01 -1.52307940e+00
-8.32005963e-02 -7.21940756e-01 -3.75571370e-01 6.23954952e-01
-3.29797387e-01 4.14158344e-01 2.07145035e-01 1.72480226e-01
-6.07813478e-01 5.72960258e-01 1.73779082e+00 -4.31362540e-01
-4.62158322e-01 2.12441951e-01 -6.74517751e-01 7.50099599e-01
7.59621441e-01 -5.88082492e-01 -6.90104187e-01 -4.46924865e-01
-2.15767384e-01 -3.18025947e-02 2.26478338e-01 -1.43425131e+00
2.71810889e-01 -1.16317421e-01 6.52092099e-01 -6.74873531e-01
8.99529085e-02 -8.35000694e-01 2.20735684e-01 5.64604640e-01
-4.30765331e-01 -1.62508711e-01 2.17886701e-01 5.30052662e-01
-1.29448354e-01 -5.03124356e-01 1.07575202e+00 -6.18552208e-01
-8.78317058e-01 4.62241113e-01 -1.86220080e-01 -3.13633345e-02
1.09164631e+00 -4.50191557e-01 -5.37457876e-02 -6.91242749e-03
-9.76292729e-01 2.06187531e-01 7.66257465e-01 4.76455361e-01
5.13036966e-01 -1.09011745e+00 -5.13936758e-01 5.62937558e-01
3.19573246e-02 7.80126572e-01 3.84972185e-01 1.81483150e-01
-7.11785078e-01 -6.71364665e-02 -2.62759179e-01 -6.40777171e-01
-7.85034776e-01 7.18474030e-01 4.59001482e-01 -6.65192604e-02
-5.04409373e-01 9.70919788e-01 2.17433169e-01 -6.56939864e-01
3.59882742e-01 -3.55529130e-01 -6.45787343e-02 3.25627152e-05
3.70557904e-01 6.76809102e-02 7.49480352e-02 -3.69690210e-01
-9.85259712e-02 4.44306284e-01 -4.66580540e-01 2.67493222e-02
1.31791127e+00 -3.67823452e-01 -2.05340445e-01 5.88715374e-01
1.02053440e+00 -3.92973065e-01 -1.99412835e+00 -3.98169369e-01
-9.21785459e-02 -3.13078970e-01 -2.37127170e-01 -1.04399514e+00
-1.25519180e+00 6.33696735e-01 9.07133400e-01 -2.21984804e-01
1.25610864e+00 -1.88681290e-01 8.49313200e-01 3.26097429e-01
4.75227326e-01 -1.36733520e+00 2.18394905e-01 3.64732236e-01
6.63585722e-01 -1.14947557e+00 -1.67063758e-01 -3.08332115e-01
-5.60451627e-01 1.06513703e+00 9.81076598e-01 -2.26645663e-01
3.59974742e-01 1.62413031e-01 2.10665837e-01 1.78258240e-01
-4.24372822e-01 7.31221810e-02 -1.24439830e-02 4.98837292e-01
8.49565119e-03 -1.98497921e-02 -1.88270137e-01 2.54738510e-01
-3.77123237e-01 5.19033708e-02 5.61086357e-01 9.13465977e-01
-5.52673578e-01 -1.21886039e+00 -1.67535394e-01 3.61393720e-01
-8.69865939e-02 7.50032961e-02 -2.08476782e-01 6.10815942e-01
6.38622582e-01 5.80769002e-01 9.41184089e-02 -2.21427426e-01
2.63608992e-01 2.48272121e-01 3.19343477e-01 -7.32798517e-01
-2.11236134e-01 -1.73153087e-01 -2.66397148e-01 -2.94151276e-01
-3.19897860e-01 -6.85609341e-01 -1.34600568e+00 1.49842039e-01
-2.99194008e-01 1.06033936e-01 6.61428452e-01 9.20789540e-01
1.16493218e-01 1.02102268e+00 7.06914008e-01 -8.14084470e-01
-2.40766138e-01 -7.89727151e-01 -1.92639008e-01 3.56881469e-01
3.27743739e-01 -4.73738313e-01 -2.75977135e-01 3.55815440e-01] | [9.446645736694336, 1.9165418148040771] |
4db80b99-f933-460e-b31f-8a8341fff1ab | seeing-is-believing-pedestrian-trajectory | null | null | http://irtizahasan.com/ | http://irtizahasan.com/WACV_2018_Seeing_is_believing.pdf | “Seeing is Believing”: Pedestrian Trajectory Forecasting Using Visual Frustum of Attention | In this paper we show the importance of the head
pose estimation in the task of trajectory forecasting. This
cue, when produced by an oracle and injected in a novel
socially-based energy minimization approach, allows to get
state-of-the-art performances on four different forecasting
benchmarks, without relying on additional information such
as expected destination and desired speed, which are supposed to be know beforehand for most of the current forecasting techniques. Our approach uses the head pose estimation for two aims: 1) to define a view frustum of attention, highlighting the people a given subject is more interested about, in order to avoid collisions; 2) to give a shorttime estimation of what would be the desired destination
point. Moreover, we show that when the head pose estimation is given by a real detector, though the performance
decreases, it still remains at the level of the top score forecasting systems | ['Alessio Del Bue', 'Theodore Tsesmelis', 'Irtiza Hasan', 'Fabio Galasso', 'Marco Cristani', 'Francesco Setti'] | 2018-03-12 | null | null | null | ieee-winter-conference-on-applications-of-2 | ['head-pose-estimation'] | ['computer-vision'] | [-3.29532713e-01 5.17654181e-01 8.41672868e-02 -3.32448632e-01
-5.99532485e-01 -4.81991619e-01 8.89458656e-01 4.33415532e-01
-6.76159263e-01 6.53518438e-01 2.54611462e-01 6.30068481e-02
-1.56027332e-01 -6.50060415e-01 -1.04849958e+00 -8.30380738e-01
-1.77656293e-01 8.50458741e-01 4.59586233e-01 -3.82656217e-01
2.29834728e-02 8.39387953e-01 -1.99020386e+00 -1.87409818e-01
5.66220343e-01 9.16750610e-01 2.64211416e-01 6.43020451e-01
5.01754701e-01 5.54247260e-01 -4.49760526e-01 -5.50514162e-01
3.80740277e-02 -2.07480207e-01 -5.79246461e-01 -8.68085101e-02
4.04361844e-01 -2.09152043e-01 -5.89488745e-02 8.52492511e-01
6.17434025e-01 2.61979103e-01 8.34031463e-01 -1.26992416e+00
3.31041664e-01 5.21185994e-01 3.71772796e-02 1.22011088e-01
5.09612858e-01 1.85373396e-01 8.28715146e-01 -4.69692945e-01
9.79634643e-01 8.71489286e-01 4.41251904e-01 4.88980591e-01
-9.45632398e-01 -2.81807274e-01 4.12365675e-01 4.81686354e-01
-1.39635944e+00 -5.47202229e-01 6.81259692e-01 -4.53064382e-01
3.74139935e-01 3.45973969e-01 5.50220013e-01 1.17358530e+00
-6.19665943e-02 7.15756476e-01 6.68718576e-01 -1.92299724e-01
6.01893663e-01 6.03165448e-01 6.06870502e-02 3.48445982e-01
1.50587022e-01 1.14104889e-01 -4.31017071e-01 -7.96767920e-02
-7.73978382e-02 -2.52744496e-01 -5.55396974e-01 -6.09045982e-01
-1.07342470e+00 8.40943754e-01 6.52348697e-01 5.67858815e-01
-5.32970786e-01 -2.15225271e-03 8.88493434e-02 -2.72348686e-03
5.17115593e-01 1.91989809e-01 -2.56212115e-01 -2.78018534e-01
-1.11331224e+00 5.28198838e-01 9.82611775e-01 8.40054691e-01
4.93092000e-01 -2.78668255e-01 -2.25403816e-01 3.62201706e-02
3.33052546e-01 7.23736107e-01 1.78637914e-02 -7.06476569e-01
4.30195659e-01 5.24300814e-01 4.47586149e-01 -1.20601606e+00
-7.82058954e-01 -7.03316510e-01 -5.29210806e-01 2.60092676e-01
8.47551644e-01 -2.59885669e-01 -2.59175509e-01 1.87134647e+00
5.86780548e-01 2.19753742e-01 -1.94000691e-01 1.19635940e+00
4.22635883e-01 4.95610625e-01 -2.82725871e-01 -3.01584572e-01
1.35525727e+00 -5.84179282e-01 -4.04265106e-01 -7.29604904e-03
6.70933127e-01 -4.14616019e-01 5.95999122e-01 5.82126558e-01
-8.51059020e-01 -3.82062405e-01 -8.66469800e-01 2.46048659e-01
-5.70508361e-01 2.63338894e-01 1.16195016e-01 9.69248295e-01
-1.14848316e+00 5.51988006e-01 -7.15578258e-01 -5.50417244e-01
1.01803139e-01 3.71103704e-01 -2.41312772e-01 2.06745356e-01
-1.09367561e+00 1.27514446e+00 3.17192711e-02 -8.63067433e-02
-9.41293180e-01 -4.15027231e-01 -5.31266093e-01 2.29970872e-01
4.40986723e-01 -5.73143721e-01 1.04405046e+00 -6.69849873e-01
-1.37330341e+00 6.47617579e-01 -3.65602344e-01 -6.73210084e-01
1.25692916e+00 -2.02918619e-01 -4.37999964e-02 1.37470216e-01
-1.95858970e-01 7.09269583e-01 8.99939716e-01 -1.32906842e+00
-7.87285268e-01 -5.74594796e-01 1.68514282e-01 3.18233997e-01
-1.97482631e-01 -1.78464785e-01 -5.51705241e-01 -1.67828321e-01
-4.23859060e-01 -1.17601216e+00 -2.78849483e-01 -8.03279206e-02
-4.88353014e-01 -2.73110598e-01 7.41583228e-01 -7.50093937e-01
9.69691575e-01 -1.66739166e+00 6.42941654e-01 4.03657347e-01
2.76348621e-01 9.77648795e-02 3.64178181e-01 4.16098088e-01
1.51763380e-01 -3.56056094e-01 1.10814162e-01 -6.82671368e-01
1.96040586e-01 -1.81806579e-01 -1.40951097e-01 9.04167891e-01
-3.66571993e-01 6.23881817e-01 -7.91712880e-01 -2.87214100e-01
4.84705001e-01 5.56700170e-01 -4.73313421e-01 2.83385366e-01
-2.34073490e-01 7.72134304e-01 -3.95926833e-01 2.27584969e-02
6.32415235e-01 2.12957785e-01 -4.69634570e-02 -6.68046921e-02
-3.74099851e-01 -7.15615153e-02 -1.35666800e+00 1.39604580e+00
-3.91519517e-01 5.83958030e-01 5.28857950e-03 -7.47522354e-01
7.77360141e-01 2.36019999e-01 5.51944673e-01 -4.61085290e-01
3.52105379e-01 2.28947811e-02 -2.29415685e-01 -2.89839447e-01
3.42630863e-01 3.64555538e-01 -1.06059834e-01 3.91600877e-01
-1.14837013e-01 3.33170742e-01 1.11244246e-01 -2.98936237e-02
1.09901989e+00 -3.33285294e-02 -6.02219664e-02 -3.64548147e-01
8.34747136e-01 -2.89531142e-01 5.28865680e-02 5.41948020e-01
1.46660820e-01 6.27802908e-01 7.11472690e-01 -3.67657125e-01
-8.94752443e-01 -7.12703943e-01 -3.38274240e-02 1.08096755e+00
8.71763304e-02 -7.73025379e-02 -1.15794706e+00 -8.82671714e-01
-1.70032308e-01 1.02929688e+00 -7.84654081e-01 -8.38175789e-02
-3.90635729e-01 -4.70167994e-01 2.50535250e-01 1.68231279e-01
-1.28395647e-01 -7.48913169e-01 -1.22374070e+00 2.50981152e-02
-2.57705867e-01 -1.09563935e+00 -4.25656527e-01 8.85242522e-02
-4.36295450e-01 -9.93199229e-01 -1.25618565e+00 -1.37576818e-01
6.11935735e-01 -1.22643031e-01 1.10107648e+00 5.07301576e-02
1.12455986e-01 4.75655764e-01 -4.29984689e-01 -4.79478121e-01
-1.53280571e-01 5.06040394e-01 7.11843967e-02 4.24971282e-01
1.47337047e-02 -4.68991905e-01 -6.91167414e-01 4.91121948e-01
-4.12088037e-01 -2.40938008e-01 3.52218509e-01 1.70198083e-01
2.01596677e-01 -1.94151327e-01 1.55320078e-01 -8.35488498e-01
3.02226454e-01 -4.11953092e-01 -8.08126926e-01 2.26452231e-01
-4.62223023e-01 2.21287891e-01 6.06443703e-01 -3.90239745e-01
-6.71679497e-01 3.85976285e-01 -3.84526759e-01 -2.01327756e-01
-5.39634883e-01 -9.25795510e-02 -4.39836055e-01 -7.10528344e-02
5.15178800e-01 1.08944185e-01 -2.22388580e-01 -4.85890090e-01
4.50730473e-01 5.00434458e-01 1.91725656e-01 -1.93393320e-01
6.99211478e-01 5.10430098e-01 1.95680812e-01 -8.79718900e-01
-5.25823951e-01 -5.44951856e-01 -8.64465952e-01 -6.50539637e-01
8.67217183e-01 -5.54493308e-01 -1.45283830e+00 2.87727356e-01
-1.28477848e+00 -1.49183676e-01 -1.93232909e-01 3.57650280e-01
-6.43317878e-01 5.68427555e-02 1.30099848e-01 -1.19272017e+00
-6.96748346e-02 -1.36050212e+00 1.33034861e+00 8.00556242e-02
3.79915498e-02 -9.07390535e-01 -1.02367155e-01 1.36397615e-01
5.31017959e-01 2.98284501e-01 4.93022114e-01 -8.03400278e-01
-7.07260966e-01 -4.54767406e-01 1.01117864e-01 -1.84724659e-01
-5.12975931e-01 -3.81662726e-01 -1.15297747e+00 -1.64689317e-01
-5.23318760e-02 3.41811359e-01 7.24043846e-01 4.75318611e-01
8.61578941e-01 -3.64092976e-01 -5.79579711e-01 3.92587245e-01
1.05699575e+00 -1.01439483e-01 5.91619968e-01 1.07830934e-01
4.50152934e-01 1.12377214e+00 4.89376754e-01 6.27975583e-01
9.10212338e-01 1.44831419e+00 8.97834361e-01 1.44798607e-01
7.69889355e-02 -1.20377168e-01 4.02037531e-01 2.91618735e-01
-3.09742838e-01 -6.57022297e-01 -8.75782132e-01 5.38048148e-01
-2.20696092e+00 -9.75564837e-01 -3.24635595e-01 2.52808809e+00
4.18940075e-02 2.50596821e-01 8.34427476e-01 7.24589005e-02
6.15656614e-01 1.05742529e-01 -3.95781517e-01 -1.71253175e-01
3.03092271e-01 -3.03172708e-01 7.08379209e-01 6.97806478e-01
-1.02442539e+00 4.62759465e-01 5.29756403e+00 6.63533688e-01
-1.18055892e+00 2.90355414e-01 4.58782613e-01 -1.29168972e-01
-7.66854584e-02 -4.83193249e-02 -1.16866648e+00 8.19415331e-01
1.12654936e+00 5.47149740e-02 4.18131977e-01 8.25404644e-01
3.66817743e-01 -3.82240087e-01 -1.23057079e+00 8.39676440e-01
2.91305274e-01 -9.11641300e-01 -3.92859906e-01 3.26096147e-01
1.83002539e-02 -7.84034058e-02 2.52191834e-02 1.27736002e-01
-2.27382109e-01 -8.86228561e-01 9.43852127e-01 1.18546331e+00
1.00795090e-01 -1.01014102e+00 9.55282807e-01 9.93562758e-01
-1.00198019e+00 9.84834805e-02 -1.74330309e-01 1.64528146e-01
4.74161655e-01 6.75885558e-01 -7.59588182e-01 6.01477742e-01
3.37501913e-01 3.06436211e-01 -4.80386883e-01 1.26608205e+00
-2.06150353e-01 4.91916269e-01 -6.09757364e-01 -4.66036290e-01
2.64985263e-01 1.39121801e-01 9.11456227e-01 1.23994780e+00
4.48275656e-01 -2.60594189e-01 1.07992612e-01 6.40594363e-01
1.86882704e-01 2.82002240e-01 -5.57100356e-01 5.55024445e-01
3.38773523e-03 1.19436264e+00 -8.42786312e-01 1.51025295e-01
9.81764197e-02 8.22679579e-01 2.12079555e-01 -4.63477857e-02
-9.32225347e-01 -9.63773727e-02 3.59523505e-01 6.68140888e-01
4.99523818e-01 -1.26486644e-01 1.48342580e-01 -9.48148906e-01
7.61810765e-02 -3.32272619e-01 1.47877291e-01 -6.14957988e-01
-5.19847929e-01 8.02426815e-01 2.42664665e-01 -1.22064018e+00
-7.56363094e-01 -4.47740883e-01 -5.91057003e-01 6.23960376e-01
-1.31747150e+00 -1.08262134e+00 -2.95726478e-01 4.96015877e-01
3.60970438e-01 -7.51056895e-02 6.51421726e-01 4.65951294e-01
-3.16774487e-01 5.26560843e-01 -2.55088490e-02 -3.24817032e-01
3.52443486e-01 -1.26957595e+00 2.57667184e-01 6.34157717e-01
2.63904095e-01 5.65607101e-02 1.34141135e+00 -3.38083655e-01
-1.31002116e+00 -7.84030378e-01 1.15208173e+00 -8.09204161e-01
2.60308743e-01 -5.89951813e-01 -6.36773348e-01 3.67647588e-01
-3.84591669e-02 5.62671423e-02 -7.06590712e-02 1.77556261e-01
3.29301804e-01 -2.54952192e-01 -1.07540536e+00 2.33656704e-01
8.91622663e-01 -4.01772708e-02 -1.93731010e-01 4.73676175e-01
1.66639611e-01 -5.28433800e-01 -4.67566252e-01 -1.92709863e-02
5.25686383e-01 -1.20408392e+00 9.35881555e-01 -2.87906289e-01
-8.64621997e-02 -1.81992948e-01 1.45037144e-01 -1.34350467e+00
1.61742792e-01 -4.82036412e-01 -2.00570434e-01 1.19397283e+00
3.80655855e-01 -4.93450046e-01 8.66857231e-01 6.34358883e-01
2.41655648e-01 -6.01818144e-01 -1.44047976e+00 -6.62602186e-01
-2.73022890e-01 -6.76208496e-01 6.45828784e-01 3.51375401e-01
-2.72530764e-01 2.98300445e-01 -7.43063927e-01 3.09868932e-01
6.93910539e-01 -4.72797714e-02 9.51435924e-01 -1.38924360e+00
-1.15740344e-01 -5.01817942e-01 -7.41817594e-01 -1.05742788e+00
2.19625458e-01 -6.38811588e-01 3.15837264e-02 -1.19656408e+00
-1.14854693e-01 -1.91716358e-01 -6.32952973e-02 -7.48560484e-03
2.68474936e-01 -9.12954882e-02 4.43666697e-01 -1.54844701e-01
-9.03164446e-01 4.65174735e-01 7.29715347e-01 1.44648284e-01
4.91739716e-03 8.12582195e-01 -4.02172893e-01 8.89433980e-01
3.81617457e-01 -7.88155317e-01 -2.10714012e-01 -7.37308189e-02
2.70256788e-01 4.07427937e-01 5.26204765e-01 -1.18427968e+00
7.38422692e-01 1.16889566e-01 1.77402243e-01 -7.36612022e-01
5.89020550e-01 -1.26948357e+00 2.67369032e-01 5.33705235e-01
-2.64642447e-01 -1.63132604e-02 -1.11535996e-01 5.71723878e-01
1.92673907e-01 -6.09098554e-01 4.89556611e-01 2.04852417e-01
-5.54648757e-01 1.41966045e-01 -3.14091027e-01 -1.86786458e-01
1.21964478e+00 3.26327085e-02 -1.52315125e-02 -9.30601656e-01
-9.42772090e-01 2.94913530e-01 3.86365056e-01 3.35773796e-01
1.85570806e-01 -1.03937936e+00 -6.46767378e-01 -2.28930146e-01
8.84834677e-02 -4.97077644e-01 3.60417813e-01 1.13144052e+00
-2.86372960e-01 4.59840506e-01 1.18335985e-01 -7.32034743e-01
-1.36546707e+00 6.20970190e-01 3.61689746e-01 -3.95863980e-01
-5.39270282e-01 5.77296138e-01 6.78914320e-03 -1.68511823e-01
6.54311717e-01 -2.17802539e-01 -5.83339572e-01 3.89182746e-01
5.43050587e-01 5.65992177e-01 3.54427397e-01 -1.03968370e+00
-5.94192147e-01 5.41887105e-01 3.04231226e-01 -1.10551856e-01
1.36081100e+00 -3.65955383e-01 4.59301978e-01 3.60953003e-01
9.79609430e-01 2.41953447e-01 -1.18947947e+00 2.46837139e-01
1.40403956e-01 -1.85850844e-01 2.17181295e-01 -7.06289828e-01
-9.72723484e-01 1.00510848e+00 9.58907068e-01 3.88471961e-01
8.16026151e-01 1.22602440e-01 6.64488077e-01 4.19931054e-01
7.27653265e-01 -9.14462984e-01 -6.33328617e-01 2.44888648e-01
9.35425639e-01 -1.23160851e+00 -1.44702375e-01 -1.96193546e-01
-7.65172899e-01 1.05372286e+00 1.26723275e-01 -1.88132953e-02
7.75548279e-01 2.53943712e-01 -1.72521412e-01 -4.25343178e-02
-6.70487404e-01 -7.60582209e-01 6.33720160e-01 6.27292573e-01
-6.07775562e-02 8.95705596e-02 -3.25074822e-01 5.79895377e-01
-3.24749887e-01 -1.98673591e-01 2.05401748e-01 2.83671230e-01
-5.93426108e-01 -9.47019398e-01 -3.16577196e-01 1.57056913e-01
-3.31758589e-01 4.73002404e-01 -4.00397182e-01 8.26220036e-01
2.22688571e-01 7.50798106e-01 -1.68654770e-01 -1.97954729e-01
7.72365332e-01 -1.18967377e-01 2.84833491e-01 -1.83190376e-01
-7.25981951e-01 -2.13547692e-01 1.07209109e-01 -7.05111444e-01
-3.79550338e-01 -8.79467368e-01 -7.90134728e-01 -3.08807552e-01
-3.11134338e-01 3.07508200e-01 9.16944683e-01 1.21533597e+00
2.03775391e-01 2.87841976e-01 5.25388420e-01 -1.52988386e+00
-4.96537626e-01 -6.38723731e-01 -3.26121420e-01 4.01036590e-01
4.09597069e-01 -7.17878342e-01 -3.38601142e-01 -2.37595543e-01] | [13.74754810333252, 0.33239343762397766] |
e17a12dc-77bc-4661-a8c9-b2b6a15456a0 | inferring-gender-of-a-twitter-user-using | 1405.6667 | null | http://arxiv.org/abs/1405.6667v1 | http://arxiv.org/pdf/1405.6667v1.pdf | Inferring gender of a Twitter user using celebrities it follows | This paper addresses the task of user gender classification in social media,
with an application to Twitter. The approach automatically predicts gender by
leveraging observable information such as the tweet behavior, linguistic
content of the user's Twitter feed and the celebrities followed by the user.
This paper first evaluates linguistic content based features using LIWC
dictionary and popular neighborhood features using Wikipedia and Freebase. Then
augments both features which yielded a significant increase in the accuracy for
gender prediction. Results show that rich linguistic features combined with
popular neighborhood prove valuables and promising for additional user
classification needs. | ['Puneet Singh Ludu'] | 2014-05-26 | null | null | null | null | ['gender-prediction'] | ['computer-vision'] | [-5.12433887e-01 2.78704464e-01 -6.51720524e-01 -6.37344241e-01
-2.66599149e-01 -5.31418443e-01 1.00240791e+00 1.20294869e+00
-8.39745343e-01 8.31293583e-01 4.83586520e-01 -5.34938015e-02
1.24935791e-01 -1.10426605e+00 -3.59083191e-02 -2.43478641e-01
-3.62282336e-01 3.95803660e-01 -8.42631608e-02 -6.72727108e-01
7.49640942e-01 1.95216611e-01 -2.01980543e+00 1.68473944e-01
6.04700685e-01 1.06478333e+00 -3.08724046e-01 5.50973892e-01
-5.24758697e-01 6.90624356e-01 -3.08900177e-01 -6.66129172e-01
-1.45878747e-01 -9.87164900e-02 -8.20553184e-01 -6.85204208e-01
2.30744034e-01 2.60066949e-02 7.61014521e-02 7.55758882e-01
5.04639983e-01 1.89372122e-01 6.41118228e-01 -1.19468892e+00
-2.49975070e-01 9.42122817e-01 -7.31790066e-01 4.54758614e-01
9.89803374e-01 -6.82369053e-01 1.20140445e+00 -7.68804431e-01
8.16578984e-01 1.24972057e+00 9.41583276e-01 3.15485924e-01
-7.85758853e-01 -8.08858693e-01 -8.98775235e-02 5.64073846e-02
-1.41294968e+00 -3.42210680e-01 5.87580860e-01 -4.63929534e-01
7.84163773e-01 5.05080283e-01 5.51687539e-01 8.92489851e-01
-3.04339603e-02 4.47386205e-01 1.16697037e+00 -5.78633726e-01
-1.39408544e-01 6.90142870e-01 6.30411386e-01 8.84497166e-01
3.77704017e-02 -3.57863665e-01 -9.17108119e-01 -5.35848796e-01
-2.33686328e-01 -1.54377833e-01 6.05082810e-01 2.91113615e-01
-8.20705771e-01 1.10954833e+00 7.09277689e-02 6.28205240e-01
-7.64952376e-02 -2.25862950e-01 9.46527004e-01 3.00171494e-01
1.09417331e+00 4.33021218e-01 -5.26003361e-01 -4.86755937e-01
-9.79741991e-01 4.69462901e-01 1.14609265e+00 4.77223605e-01
1.06558025e+00 -4.46531355e-01 2.27756333e-02 8.80356491e-01
4.88462985e-01 5.31291902e-01 8.45756710e-01 -5.30165136e-01
3.09239030e-01 9.79017437e-01 -1.83821246e-02 -1.58529687e+00
-7.04862595e-01 -1.08314909e-01 -1.05467543e-01 -6.23764396e-01
5.49031377e-01 -2.77933389e-01 -3.18891943e-01 1.38175094e+00
6.33757889e-01 -2.83835009e-02 -3.50779474e-01 1.95363268e-01
1.50514817e+00 3.11194539e-01 4.44681942e-01 -4.90083307e-01
1.36510932e+00 -3.89169753e-01 -9.11326885e-01 1.47332549e-01
8.53398919e-01 -6.60389006e-01 6.71505749e-01 1.12369113e-01
-8.34018052e-01 -4.02541608e-01 -6.58683121e-01 1.20418030e-03
-1.30632257e+00 -1.54177090e-02 1.02895856e+00 1.09359205e+00
-6.15734637e-01 8.31736803e-01 -5.30878544e-01 -8.88298154e-01
3.56718600e-01 7.03843951e-01 -2.67772764e-01 3.51780564e-01
-1.17230880e+00 6.42501652e-01 2.41037995e-01 -4.76898164e-01
3.22444141e-01 -6.63700879e-01 -1.11224258e+00 -4.49787468e-01
-2.22989723e-01 -1.64638385e-01 1.01634204e+00 -8.73786867e-01
-1.13417256e+00 1.28004348e+00 -4.11763221e-01 -4.91569906e-01
5.53487420e-01 5.62812090e-02 -7.95216024e-01 -2.28739679e-01
6.39388263e-01 4.02301103e-01 3.31111193e-01 -5.70343792e-01
-1.07152629e+00 -7.69810438e-01 -5.78235835e-02 7.75657520e-02
-1.03664196e+00 3.74833524e-01 -8.80869254e-02 -5.34424663e-01
-7.77165443e-02 -8.21171880e-01 9.51307565e-02 -9.09431696e-01
-4.33008850e-01 -7.57431388e-01 8.06560934e-01 -7.03287721e-01
1.76189387e+00 -2.15288711e+00 -4.32160020e-01 6.58717334e-01
3.78721416e-01 -2.91401565e-01 4.85558242e-01 7.98872590e-01
3.21721822e-01 3.30941111e-01 5.87804317e-01 -5.08761704e-01
2.94489920e-01 2.03333143e-02 -8.36072117e-02 5.92246890e-01
-5.81628621e-01 7.18128741e-01 -9.89782274e-01 -8.12520266e-01
-2.38195464e-01 2.94145465e-01 -5.08992791e-01 -1.35688469e-01
2.15993911e-01 2.66272992e-01 -6.04745686e-01 5.55766344e-01
3.26508403e-01 2.42598191e-01 7.74366632e-02 -1.34861320e-01
-6.19884074e-01 3.45407307e-01 -7.26801395e-01 1.03387439e+00
-4.40694869e-01 7.50162303e-01 -8.28640610e-02 -7.09261179e-01
1.12556720e+00 -4.34454456e-02 7.50929892e-01 -7.26100862e-01
6.26373887e-01 3.94192785e-01 -3.01345825e-01 -6.56785786e-01
9.13591981e-01 1.97335497e-01 -6.46783829e-01 6.05150878e-01
1.81997381e-02 4.61873472e-01 9.04985368e-01 2.17886463e-01
5.45794249e-01 9.40159410e-02 5.16156137e-01 -6.43599153e-01
7.93030322e-01 -6.70337901e-02 1.64865017e-01 6.07331812e-01
-3.38701010e-01 8.98973718e-02 5.36636591e-01 -4.95657414e-01
-4.28640753e-01 -4.85077679e-01 -2.87211984e-01 2.15205646e+00
-8.19362774e-02 -9.31499481e-01 -6.57252431e-01 -7.25829601e-01
4.07080323e-01 4.60106015e-01 -1.28680730e+00 1.95714489e-01
-4.55693990e-01 -8.75470281e-01 6.58173144e-01 1.56284168e-01
4.96575892e-01 -8.35305274e-01 -1.82728797e-01 -4.06063907e-02
-2.37723321e-01 -8.66929293e-01 -2.51039535e-01 -6.05470017e-02
-5.88912129e-01 -1.10800731e+00 -1.48284808e-01 -8.57194483e-01
2.94299394e-01 -4.68157113e-01 1.07082760e+00 1.29371256e-01
-4.10620928e-01 4.82351959e-01 -3.62750083e-01 -7.86741912e-01
-1.33746192e-01 7.16047168e-01 3.43199402e-01 1.86815903e-01
8.93435538e-01 -5.99327981e-01 -3.37336779e-01 -7.92419985e-02
-2.32660115e-01 -4.97676790e-01 -2.95096099e-01 2.89751947e-01
2.05765180e-02 -9.79343057e-02 8.03836405e-01 -1.53083324e+00
7.82041609e-01 -1.05183291e+00 2.07335502e-01 -3.11586410e-01
-8.00247610e-01 -2.92462260e-01 2.77609915e-01 -1.88816801e-01
-8.47102702e-01 -3.19558159e-02 -2.67916650e-01 5.35787702e-01
9.26416274e-03 8.01058531e-01 3.48203093e-01 -4.48186882e-02
8.56783628e-01 -2.29301434e-02 -1.02787372e-02 -4.87727463e-01
-5.67536918e-04 9.81610477e-01 1.73599973e-01 -4.02197272e-01
4.58473027e-01 3.07303518e-01 -6.82879239e-02 -9.76999104e-01
-9.28815007e-01 -8.27847719e-01 -8.20091128e-01 -3.89674872e-01
6.84130311e-01 -7.88365006e-01 -1.31126821e+00 3.27896684e-01
-3.87797058e-01 3.23443055e-01 8.01530406e-02 2.77025968e-01
-2.23218784e-01 -7.34813651e-03 -5.98646760e-01 -8.55599880e-01
-2.15106606e-01 -3.20275038e-01 7.61971593e-01 3.82487804e-01
-8.49622369e-01 -1.39080155e+00 1.37443289e-01 4.21928614e-01
4.02969778e-01 5.96157551e-01 6.58612490e-01 -1.42227328e+00
4.73027617e-01 -5.69975495e-01 -4.40480299e-02 -5.10625958e-01
9.56107154e-02 2.68430531e-01 -9.54729021e-01 1.00063952e-02
-8.29297841e-01 -4.19202596e-01 6.79942191e-01 1.11014590e-01
9.81044412e-01 -4.82348651e-01 -6.28013015e-01 1.47817597e-01
1.29805708e+00 -3.91897440e-01 3.77648696e-02 5.78186452e-01
7.22631276e-01 8.02933931e-01 6.09266639e-01 9.54324007e-01
9.62683737e-01 3.14633727e-01 6.39391541e-02 2.28412315e-01
4.72279131e-01 -2.51260519e-01 -4.12084116e-03 6.55843675e-01
-4.26693350e-01 3.03856671e-01 -1.10528028e+00 4.24228221e-01
-1.78460383e+00 -1.06697536e+00 -3.45974833e-01 1.78572500e+00
7.92883396e-01 1.08437799e-01 7.43419766e-01 4.69995171e-01
6.42336488e-01 2.58021533e-01 -1.07537523e-01 -9.73528087e-01
1.19570598e-01 1.33907139e-01 6.99615419e-01 5.42650402e-01
-1.41494834e+00 7.40037322e-01 6.54989004e+00 6.92046702e-01
-9.45755064e-01 2.05571696e-01 7.31544733e-01 -8.01523477e-02
5.64376563e-02 -5.59359729e-01 -1.23484898e+00 4.67307329e-01
1.15965867e+00 -4.88601923e-01 2.25332230e-01 6.07423127e-01
2.07528636e-01 -4.04572666e-01 -8.87341022e-01 9.12201345e-01
2.26380646e-01 -1.27125204e+00 -3.31322581e-01 2.83810645e-01
5.73235869e-01 -1.53598599e-02 2.76694715e-01 6.95338130e-01
1.77581310e-02 -8.29837084e-01 6.83340013e-01 4.36192423e-01
6.17669940e-01 -1.22057939e+00 7.32797027e-01 3.72802019e-01
-1.17515802e+00 -3.49671960e-01 3.74487460e-01 -5.13278306e-01
-3.68552893e-01 3.41340750e-01 -9.55307007e-01 1.14967428e-01
9.25235569e-01 1.04897928e+00 -1.06789935e+00 5.59116781e-01
4.72344011e-01 6.62442684e-01 -3.59883517e-01 -4.62361753e-01
1.35446757e-01 -1.41160097e-02 2.00958207e-01 1.68187165e+00
1.23912364e-01 -1.75788730e-01 3.74299735e-01 3.21243554e-02
-1.62900403e-01 1.04602432e+00 -7.65306354e-01 -4.22422707e-01
5.24393618e-01 1.51357853e+00 -1.07906616e+00 -1.32766843e-01
-3.89762551e-01 4.31704342e-01 3.74741107e-01 -6.78956285e-02
-4.80506539e-01 -6.12582028e-01 4.77478713e-01 6.43254399e-01
-1.62535310e-01 5.22286370e-02 -3.49782884e-01 -7.29344845e-01
-5.53001940e-01 -3.68150353e-01 7.46407449e-01 -3.04752286e-03
-1.21278548e+00 2.39994004e-01 -1.30309835e-01 -7.93626726e-01
-4.81265306e-01 -4.13213342e-01 -6.33325815e-01 6.32273078e-01
-1.03936899e+00 -1.62318730e+00 -7.23513812e-02 4.43900466e-01
1.29352570e-01 -5.32436490e-01 1.00726449e+00 6.54726505e-01
-4.13726091e-01 9.04037595e-01 4.34818603e-02 2.47768342e-01
7.66910672e-01 -1.42146277e+00 -8.72779638e-02 -1.41286686e-01
-2.22107992e-01 7.12257385e-01 1.03320956e+00 -7.78277636e-01
-1.14438903e+00 -9.64009762e-01 1.98730159e+00 -7.90978670e-01
1.06729710e+00 -3.76829267e-01 -7.12481514e-02 5.25151074e-01
1.49879158e-01 4.19104174e-02 1.39721072e+00 6.88917518e-01
-3.01655859e-01 -5.36787696e-03 -1.52485967e+00 3.51930529e-01
8.78740907e-01 -6.81475222e-01 -2.74667382e-01 4.43855494e-01
9.07831192e-02 -3.64286214e-01 -1.11582685e+00 1.22089654e-01
9.42194045e-01 -8.06588769e-01 8.16850305e-01 -5.34988046e-01
6.45410717e-01 3.33731681e-01 -2.49038205e-01 -8.12108517e-01
-6.43299296e-02 -4.15503591e-01 -1.32888347e-01 1.81070244e+00
6.94545209e-01 -5.09933352e-01 8.63655448e-01 7.36664534e-01
3.84334177e-01 -6.10853672e-01 -5.89289308e-01 -8.92836004e-02
1.76692717e-02 -2.86442399e-01 5.19970775e-01 1.23041558e+00
5.84554076e-01 3.21139902e-01 -1.47565797e-01 -4.48568165e-01
3.20210755e-01 8.57083574e-02 6.96321249e-01 -1.73360229e+00
2.09017977e-01 -5.64673960e-01 -5.81541002e-01 -3.65456976e-02
5.31271040e-01 -1.02859092e+00 -4.95379210e-01 -1.05414474e+00
2.87151605e-01 -4.08383459e-01 -6.58556726e-03 2.03651696e-01
1.24497823e-01 1.09510887e+00 -2.04894230e-01 -5.96777424e-02
-9.83223855e-01 -4.22147252e-02 6.55662417e-01 -8.30119550e-02
-4.52373326e-01 2.05782324e-01 -8.07048023e-01 9.39712107e-01
7.08535731e-01 -2.98986822e-01 -2.85563176e-03 3.13321501e-01
9.09379721e-01 -5.08489370e-01 -1.84365496e-01 -6.56867385e-01
1.33232519e-01 3.69426720e-02 4.99565005e-01 -6.42352402e-01
3.13048869e-01 -4.22715813e-01 -4.38890994e-01 3.39718133e-01
-4.55558985e-01 9.32271406e-02 8.39106068e-02 5.47672153e-01
-3.31090391e-01 -1.98280126e-01 2.65907049e-01 -1.44647866e-01
-6.25622690e-01 2.40491897e-01 -5.68414509e-01 1.04610212e-01
1.04309678e+00 -3.70290637e-01 3.67231704e-02 -2.38745332e-01
-1.38264048e+00 1.25007674e-01 2.51159281e-01 5.05749524e-01
-1.72118708e-01 -1.24359286e+00 -5.66687346e-01 3.69886369e-01
3.02405596e-01 -1.02848029e+00 -2.33268544e-01 7.82798529e-01
-1.87483341e-01 3.16795945e-01 -1.40614495e-01 -2.74540961e-01
-1.82434666e+00 6.10738471e-02 -3.28465216e-02 -6.44244924e-02
4.98194136e-02 9.38298106e-01 -7.03276336e-01 -8.90294671e-01
3.35385978e-01 1.29073486e-01 -1.30008817e+00 1.29961801e+00
5.22564769e-01 7.77858734e-01 1.71625897e-01 -1.30078304e+00
-4.97066438e-01 3.21456969e-01 3.34789120e-02 1.95893869e-02
1.47444820e+00 -4.50729877e-01 -6.19981527e-01 1.06175292e+00
1.58190143e+00 6.01656556e-01 -1.39782935e-01 -1.65548488e-01
5.75057149e-01 -5.96740186e-01 -1.26590282e-01 -5.02243936e-01
-8.56282949e-01 2.83227861e-01 5.69886267e-01 8.59284937e-01
5.27401745e-01 6.18047602e-02 7.88274944e-01 3.04589808e-01
3.82534802e-01 -1.64358139e+00 -2.59055793e-01 8.54318440e-01
1.89909905e-01 -1.61672580e+00 2.18945071e-01 -4.39933449e-01
-4.06245768e-01 1.12262368e+00 4.24242944e-01 4.98094596e-02
1.48922932e+00 -2.46562567e-02 1.76565070e-02 -2.76911318e-01
-3.03881913e-01 -1.41043887e-01 3.16779971e-01 3.33520293e-01
1.07820594e+00 2.07082495e-01 -1.02224898e+00 1.07935822e+00
-8.53616059e-01 -2.19070047e-01 3.65051597e-01 8.94899428e-01
-4.97174382e-01 -1.15337026e+00 -2.70166606e-01 1.04730570e+00
-1.23815680e+00 1.30704965e-03 -4.67034847e-01 6.05885744e-01
5.61996222e-01 9.65982854e-01 2.64364004e-01 -4.52824652e-01
-2.51577646e-02 1.94775805e-01 3.31744015e-01 -7.52219737e-01
-1.19428456e+00 -4.22906369e-01 6.55330718e-01 -4.84345376e-01
-7.12702155e-01 -1.13904488e+00 -1.34294999e+00 -8.68338346e-01
1.19461734e-02 4.88842219e-01 9.42204893e-01 1.06628489e+00
1.52779594e-01 -9.48716849e-02 8.50932956e-01 -8.58103693e-01
1.54780582e-01 -1.00227451e+00 -9.26009357e-01 4.14861798e-01
2.35774666e-01 -6.04520977e-01 -3.61082196e-01 6.98494762e-02] | [9.449480056762695, 10.345113754272461] |
b8c02ddb-f846-4530-9ba9-f876863fbedf | mrnet-multiple-input-receptive-field-network | 2301.12972 | null | https://arxiv.org/abs/2301.12972v3 | https://arxiv.org/pdf/2301.12972v3.pdf | Human Vision Based 3D Point Cloud Semantic Segmentation of Large-Scale Outdoor Scene | This paper proposes EyeNet, a novel semantic segmentation network for point clouds that addresses the critical yet often overlooked parameter of coverage area size. Inspired by human peripheral vision, EyeNet overcomes the limitations of conventional networks by introducing a simple but efficient multi-contour input and a parallel processing network with connection blocks between parallel streams. The proposed approach effectively addresses the challenges of dense point clouds, as demonstrated by our ablation studies and state-of-the-art performance on Large-Scale Outdoor datasets. | ['Gunho Sohn', 'Maryam Jameela', 'Yeongjeong Jeong', 'Sunghwan Yoo'] | 2023-01-30 | null | null | null | null | ['point-cloud-segmentation'] | ['computer-vision'] | [ 9.52669084e-02 2.09869854e-02 2.01276094e-01 -1.49913281e-01
-4.76737395e-02 -5.71905911e-01 3.96799862e-01 2.42686003e-01
-7.82844901e-01 5.91337979e-01 -6.60599947e-01 -3.99797350e-01
-4.69357856e-02 -1.05082333e+00 -5.97442985e-01 -2.71033049e-01
-8.22092220e-02 5.27903616e-01 1.18543661e+00 -2.11261973e-01
2.39154279e-01 9.59408045e-01 -1.97066653e+00 -1.12038068e-01
9.50253606e-01 1.33010423e+00 1.42888457e-01 5.68798423e-01
-6.61556244e-01 8.20612907e-02 -6.64060414e-01 -7.15792552e-02
5.99198580e-01 3.30138672e-03 -4.96770352e-01 -8.00719336e-02
6.23090029e-01 -1.12236030e-01 1.29537284e-02 9.94544089e-01
4.24252242e-01 -4.24606912e-02 4.24796671e-01 -1.38016236e+00
4.27070633e-02 -8.82492438e-02 -8.00831139e-01 4.55415279e-01
2.51982752e-02 3.01914662e-01 8.07895184e-01 -9.00424600e-01
4.01807904e-01 1.05112600e+00 1.07751560e+00 3.00457835e-01
-8.78328681e-01 -9.08346713e-01 2.08358541e-01 -2.78001249e-01
-1.59966218e+00 -2.54737020e-01 4.44194496e-01 -9.62858796e-02
1.19328153e+00 1.75737500e-01 1.12150609e+00 3.42318565e-01
-1.25901485e-02 5.21641314e-01 1.02090335e+00 -7.36191198e-02
4.33473825e-01 -3.45904268e-02 -2.49702353e-02 5.25572419e-01
6.58540249e-01 1.96775511e-01 -4.89201277e-01 -4.22443487e-02
1.17631769e+00 -1.03574507e-01 -3.41794044e-01 -3.85651618e-01
-9.45781887e-01 9.14135516e-01 8.38969886e-01 1.07384704e-01
-2.83177882e-01 5.85601032e-01 1.29648615e-02 1.60080969e-01
6.99015379e-01 2.61149287e-01 -4.81011391e-01 2.25073516e-01
-1.50411808e+00 1.79003909e-01 7.33514547e-01 1.32688749e+00
8.85598540e-01 9.17707384e-02 2.78220564e-01 3.05018783e-01
7.39249349e-01 8.97018909e-01 -3.12022865e-01 -9.42757785e-01
1.62392333e-01 7.64375627e-01 4.66760620e-02 -6.40559971e-01
-7.01197207e-01 -5.98089814e-01 -5.31071007e-01 6.83287978e-01
2.51303345e-01 -2.06928313e-01 -1.27526259e+00 9.85939324e-01
4.82067496e-01 4.04321790e-01 1.71089694e-01 9.57670450e-01
1.16598928e+00 4.43452448e-01 1.81423530e-01 1.53844163e-01
1.17537403e+00 -9.20295417e-01 -3.35685015e-01 -6.39856160e-01
-1.72322750e-01 -7.14773417e-01 6.74617171e-01 2.69988090e-01
-1.18860388e+00 -2.73082346e-01 -1.14974380e+00 3.29667665e-02
-5.28729558e-01 -1.92521647e-01 1.07027936e+00 6.93976283e-01
-1.42529798e+00 6.19798124e-01 -7.48216271e-01 -7.54257917e-01
1.00517082e+00 6.11755192e-01 4.59694117e-02 1.77915379e-01
-5.87720513e-01 5.24221897e-01 3.60325158e-01 8.98472294e-02
-4.82670486e-01 -9.11553621e-01 -6.91011965e-01 1.05822295e-01
4.89764601e-01 -9.90368426e-01 1.28235865e+00 -8.89999211e-01
-1.59277999e+00 7.37679064e-01 -5.36927022e-02 -6.10138416e-01
5.97209930e-01 -2.20490411e-01 -2.08970070e-01 5.66462040e-01
3.36148747e-04 1.12912488e+00 7.66722858e-01 -1.29917347e+00
-8.89400184e-01 -3.32144171e-01 -1.69898301e-01 2.30894923e-01
1.67406961e-01 7.71737695e-02 -6.98016346e-01 -3.71524662e-01
3.18398893e-01 -6.61541760e-01 -5.62042832e-01 6.20125115e-01
-1.62679106e-01 -1.88941255e-01 9.58883345e-01 1.85024261e-01
5.83388269e-01 -2.05639791e+00 -4.03481632e-01 5.71330249e-01
4.31888729e-01 3.00278783e-01 -7.18406662e-02 2.33934313e-01
3.49436730e-01 1.14911996e-01 -4.74662811e-01 -5.96437514e-01
-2.33760878e-01 2.56453425e-01 -1.27256289e-01 5.37982941e-01
2.62022942e-01 8.48194122e-01 -8.84293735e-01 -7.30967700e-01
5.10124087e-01 4.91647869e-01 -2.38987058e-01 -6.76360428e-02
-4.74077582e-01 1.94204882e-01 -3.76952887e-01 9.39433753e-01
1.25401127e+00 -4.46159601e-01 -4.03953403e-01 2.21538525e-02
-4.86797482e-01 -1.63210347e-01 -1.25282228e+00 1.85039532e+00
2.39885394e-02 7.81769693e-01 3.49140942e-01 -3.54653060e-01
9.74472344e-01 6.45387247e-02 6.13934755e-01 -4.47409272e-01
3.76507252e-01 2.37687439e-01 -2.46847510e-01 -1.52994702e-02
6.65755451e-01 -2.34667316e-01 2.74470419e-01 2.04697967e-01
9.47971791e-02 -6.74008012e-01 -1.07076377e-01 1.57566771e-01
9.56040263e-01 5.54161817e-02 1.88501924e-01 -4.70522702e-01
2.32048050e-01 5.90258360e-01 4.09752011e-01 7.83919096e-01
-3.30816865e-01 8.61919582e-01 1.63210988e-01 -3.44094157e-01
-8.31939399e-01 -1.20407093e+00 -2.69652277e-01 5.30151010e-01
7.74520040e-01 -3.63978386e-01 -6.08127415e-01 -4.13205296e-01
3.08207870e-01 2.31013492e-01 -2.81229377e-01 5.84141672e-01
-1.77497253e-01 -5.03354728e-01 6.28987312e-01 6.16597056e-01
7.55661488e-01 -1.02959538e+00 -1.12508464e+00 7.26735517e-02
2.38765985e-01 -1.49669921e+00 1.47136897e-01 1.55785546e-01
-1.16721773e+00 -1.24559820e+00 -5.49463749e-01 -4.79281992e-01
5.52669704e-01 8.50793123e-01 1.35456884e+00 4.53953207e-01
-2.42609069e-01 2.86781400e-01 -1.61801249e-01 -9.13058877e-01
1.94630578e-01 1.45627409e-01 -2.79318571e-01 -3.77399683e-01
4.70869929e-01 -6.04354322e-01 -9.59584475e-01 2.20894203e-01
-9.20860648e-01 6.21038899e-02 5.03301799e-01 8.84189233e-02
7.36056089e-01 -9.12143290e-02 3.15802932e-01 -6.25623286e-01
4.10235226e-01 -4.06415701e-01 -9.60956872e-01 -3.69372815e-02
-4.85355139e-01 -4.17235821e-01 1.71582073e-01 1.63795769e-01
-6.73386633e-01 1.26438364e-01 -3.19176018e-01 -5.04852772e-01
-3.62671494e-01 -1.10880518e-02 2.50545591e-01 -8.28764021e-01
4.90838736e-01 -2.74747461e-02 5.42392619e-02 -2.08731353e-01
3.64342570e-01 5.30143201e-01 5.51093876e-01 -3.15572768e-01
9.39951539e-01 1.18121290e+00 1.45035014e-01 -1.14622211e+00
-5.65647781e-01 -9.41271544e-01 -8.59282136e-01 -4.56344038e-01
8.31446707e-01 -1.05968165e+00 -8.47480536e-01 5.04503965e-01
-1.35392034e+00 -2.05418512e-01 -6.76603138e-01 1.87546715e-01
-4.08333182e-01 1.48567230e-01 -2.70956993e-01 -7.13740826e-01
-5.82490981e-01 -7.09068477e-01 1.21676087e+00 6.69325769e-01
1.62692189e-01 -8.13637495e-01 -9.45806727e-02 -9.21971127e-02
7.01368630e-01 3.61726254e-01 2.01904625e-01 -2.71471322e-01
-1.23553073e+00 1.08145215e-01 -8.29064727e-01 1.03410818e-01
-3.71368378e-01 2.76051342e-01 -1.15884066e+00 -1.93712160e-01
-2.50763625e-01 -5.33944704e-02 1.00242269e+00 5.22901893e-01
9.86583948e-01 5.16761243e-01 -6.89277291e-01 1.08634603e+00
1.89862728e+00 -8.69305581e-02 6.07327104e-01 3.96896899e-01
4.31190640e-01 3.07115853e-01 4.67005461e-01 2.79998362e-01
3.07562262e-01 1.29805893e-01 9.38888729e-01 -5.00272930e-01
-1.91344947e-01 3.58013809e-02 -3.20811629e-01 3.83151233e-01
-3.01917404e-01 -4.60352182e-01 -1.01817667e+00 7.38842070e-01
-1.80399752e+00 -6.06538773e-01 -5.61411679e-01 1.86154759e+00
1.34096950e-01 3.38239133e-01 -4.92048934e-02 -1.70475557e-01
2.58618236e-01 3.36633921e-01 -5.31761110e-01 -1.61899447e-01
-3.81523967e-01 7.55072713e-01 1.10682225e+00 1.48516372e-01
-1.15958941e+00 1.34747040e+00 7.44397879e+00 7.89886117e-01
-1.01168346e+00 2.76877165e-01 -9.41556990e-02 -1.68886572e-01
-3.13631922e-01 7.61647942e-03 -7.68959045e-01 2.18042642e-01
7.10797250e-01 7.90037140e-02 1.61858322e-03 6.67769015e-01
8.39349106e-02 -6.01500869e-01 -6.00959301e-01 9.47226107e-01
3.48874703e-02 -1.69623566e+00 -1.91933095e-01 8.42286870e-02
5.97704172e-01 9.63914633e-01 -2.41454959e-01 -2.76758671e-01
3.97822261e-01 -1.02515066e+00 7.24822402e-01 3.09811831e-01
1.00951016e+00 -6.18831992e-01 8.21170092e-01 1.98106408e-01
-1.48150980e+00 1.37628153e-01 -5.22676289e-01 -1.06311992e-01
3.00762326e-01 4.99612004e-01 -5.85431159e-01 5.41431189e-01
1.12077653e+00 6.75079942e-01 -6.47222579e-01 1.68852115e+00
-3.13079685e-01 3.98174703e-01 -1.09718287e+00 2.84992997e-02
5.71968913e-01 -1.28253579e-01 5.29963851e-01 1.27019072e+00
5.01358032e-01 2.67855883e-01 2.32982375e-02 1.16960537e+00
2.98117520e-03 -1.35576949e-01 -9.01309192e-01 3.80785286e-01
5.79337060e-01 1.34035826e+00 -1.37943578e+00 -2.10003033e-01
-4.86142874e-01 7.21618950e-01 1.42150903e-02 4.17433023e-01
-5.90201855e-01 -4.02968049e-01 8.40353072e-01 1.51124254e-01
6.63991988e-01 -4.78551686e-01 -7.17127144e-01 -6.58695996e-01
-2.40191445e-01 -1.43052325e-01 2.63390951e-02 -7.69672871e-01
-1.03609014e+00 7.96057820e-01 -5.61397374e-02 -1.35791445e+00
4.35316622e-01 -5.85567355e-01 -7.74805903e-01 8.54615986e-01
-2.20752072e+00 -1.36072636e+00 -1.06268251e+00 7.42386758e-01
4.97734755e-01 6.76893890e-02 5.30450583e-01 9.78303328e-02
-2.35821500e-01 9.29115266e-02 -9.55593660e-02 -1.52348027e-01
1.99180260e-01 -1.22223294e+00 9.43232417e-01 9.57456529e-01
-5.09835705e-02 1.81341633e-01 3.89168233e-01 -6.80431724e-01
-8.65661442e-01 -1.04962194e+00 3.34950745e-01 -2.40202859e-01
4.93343204e-01 -3.45308006e-01 -8.29549551e-01 3.47408950e-01
3.19411457e-01 2.76654214e-01 3.49377781e-01 -3.66289973e-01
1.75584748e-01 6.34704679e-02 -1.40225971e+00 2.85773814e-01
1.24353206e+00 -2.19057992e-01 -4.79695767e-01 1.82701811e-01
1.01286685e+00 -6.78298891e-01 -5.55804908e-01 5.30896008e-01
2.56067425e-01 -1.11818886e+00 1.00680673e+00 -4.86992821e-02
3.50004584e-02 -5.50187171e-01 1.61812171e-01 -1.10516131e+00
-3.58129293e-02 -5.62904298e-01 2.75934278e-03 7.20439434e-01
2.42487714e-01 -6.23481214e-01 1.27206194e+00 1.34609684e-01
-3.48605126e-01 -4.65322614e-01 -1.14330578e+00 -7.06690669e-01
-3.11519176e-01 -7.15899587e-01 7.82700479e-01 6.79086447e-01
-6.21188760e-01 1.11631706e-01 3.04206252e-01 5.07643521e-01
9.33827817e-01 1.13953859e-01 7.88153291e-01 -1.76395297e+00
3.57663035e-01 -4.06145185e-01 -4.82362360e-01 -1.17784488e+00
-2.33733937e-01 -5.71301699e-01 1.78103030e-01 -1.81469738e+00
-3.80513698e-01 -8.72101724e-01 -4.02217023e-02 1.74540639e-01
3.12060028e-01 6.14416599e-01 3.95513624e-01 2.83559382e-01
-7.21778333e-01 3.84225845e-01 1.19126880e+00 9.75219831e-02
-1.72587618e-01 1.66330904e-01 -4.65366513e-01 1.01702154e+00
8.28814566e-01 -6.10902786e-01 -3.66581202e-01 -6.07190013e-01
3.11240792e-01 -3.71118963e-01 6.42718971e-01 -1.68124545e+00
7.52310276e-01 -1.53247446e-01 3.05942923e-01 -1.23314500e+00
4.98965859e-01 -1.29402649e+00 -4.29485589e-02 3.02358091e-01
5.51639855e-01 5.73121458e-02 6.83561862e-01 6.91751957e-01
-2.35622659e-01 -1.11079559e-01 7.72658408e-01 -2.83758521e-01
-1.06800485e+00 4.47714657e-01 -8.57183635e-02 -2.96474509e-02
1.37144017e+00 -8.40705812e-01 -7.31236696e-01 1.05855271e-01
-5.31610191e-01 5.82087874e-01 8.17823946e-01 2.98994392e-01
9.90307212e-01 -7.78424501e-01 -4.80145603e-01 5.88235497e-01
1.85654715e-01 8.18494737e-01 3.53536904e-02 6.19557798e-01
-1.24344552e+00 3.42713892e-01 -2.40227506e-01 -1.07356501e+00
-1.06908727e+00 7.08700716e-02 6.49629653e-01 2.68578887e-01
-9.85973299e-01 1.05299878e+00 -9.08793509e-02 -2.50791401e-01
2.06829935e-01 -6.33815587e-01 -8.57905596e-02 -1.01425141e-01
1.05470285e-01 2.48835370e-01 1.78179398e-01 -3.21967214e-01
-4.94642556e-01 9.47072506e-01 3.40552688e-01 4.31632111e-03
1.39433050e+00 -4.73850816e-02 -2.04075351e-01 3.26816261e-01
4.75976408e-01 -3.20844412e-01 -1.46166885e+00 -2.06775203e-01
-1.67446196e-01 -5.83647549e-01 4.79470432e-01 -7.00260341e-01
-1.24081600e+00 8.45386326e-01 7.21219003e-01 6.62592798e-02
1.04616868e+00 2.17282921e-01 9.99080956e-01 2.80943215e-01
7.02605128e-01 -1.07094419e+00 -2.39707559e-01 5.81298947e-01
5.53545594e-01 -1.39977574e+00 2.38766879e-01 -9.14120913e-01
-8.95992294e-02 1.06017065e+00 8.26639891e-01 -2.08778247e-01
9.86575007e-01 5.47336519e-01 2.26999894e-01 -9.95072186e-01
-3.97132188e-01 -5.96191168e-01 -3.92825641e-02 7.64148116e-01
-1.80167496e-01 -5.54071814e-02 -1.64226741e-02 6.29965365e-02
-1.69179723e-01 3.05968255e-01 3.42963725e-01 9.66969967e-01
-8.13544869e-01 -6.12223685e-01 -4.91261750e-01 4.54047889e-01
-9.49874520e-02 -1.67551249e-01 -3.28616858e-01 1.20854914e+00
2.41693228e-01 8.03092420e-01 8.85155201e-01 -1.96287006e-01
5.20119071e-01 -3.65617990e-01 3.10681105e-01 -6.86360836e-01
-7.45730817e-01 -6.64865524e-02 -1.81152835e-01 -8.05001676e-01
-8.48470151e-01 -5.20624816e-01 -1.52382052e+00 -3.77721667e-01
-4.08445626e-01 -1.50437350e-03 9.51423049e-01 7.22707510e-01
4.91747350e-01 5.66938937e-01 3.25388938e-01 -1.27421510e+00
6.78715855e-02 -8.18639398e-01 -6.81185782e-01 -9.27879885e-02
5.14459789e-01 -6.58796489e-01 -3.88665766e-01 -3.89822036e-01] | [7.985296249389648, -3.1652908325195312] |
cf7434fb-456d-441d-9691-02ff7ca863dd | learning-preferences-for-referring-expression | null | null | https://aclanthology.org/W12-1503 | https://aclanthology.org/W12-1503.pdf | Learning Preferences for Referring Expression Generation: Effects of Domain, Language and Algorithm | null | ['Mari{\\"e}t Theune', 'Emiel Krahmer', 'Ruud Koolen'] | 2012-05-01 | null | null | null | ws-2012-5 | ['referring-expression-generation'] | ['computer-vision'] | [-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] | [-7.357715129852295, 3.6744203567504883] |
572b390b-3f5a-48e1-ba1b-b185ed19df03 | gan-prior-embedded-network-for-blind-face | 2105.06070 | null | https://arxiv.org/abs/2105.06070v1 | https://arxiv.org/pdf/2105.06070v1.pdf | GAN Prior Embedded Network for Blind Face Restoration in the Wild | Blind face restoration (BFR) from severely degraded face images in the wild is a very challenging problem. Due to the high illness of the problem and the complex unknown degradation, directly training a deep neural network (DNN) usually cannot lead to acceptable results. Existing generative adversarial network (GAN) based methods can produce better results but tend to generate over-smoothed restorations. In this work, we propose a new method by first learning a GAN for high-quality face image generation and embedding it into a U-shaped DNN as a prior decoder, then fine-tuning the GAN prior embedded DNN with a set of synthesized low-quality face images. The GAN blocks are designed to ensure that the latent code and noise input to the GAN can be respectively generated from the deep and shallow features of the DNN, controlling the global face structure, local face details and background of the reconstructed image. The proposed GAN prior embedded network (GPEN) is easy-to-implement, and it can generate visually photo-realistic results. Our experiments demonstrated that the proposed GPEN achieves significantly superior results to state-of-the-art BFR methods both quantitatively and qualitatively, especially for the restoration of severely degraded face images in the wild. The source code and models can be found at https://github.com/yangxy/GPEN. | ['Lei Zhang', 'Xuansong Xie', 'Peiran Ren', 'Tao Yang'] | 2021-05-13 | null | http://openaccess.thecvf.com//content/CVPR2021/html/Yang_GAN_Prior_Embedded_Network_for_Blind_Face_Restoration_in_the_CVPR_2021_paper.html | http://openaccess.thecvf.com//content/CVPR2021/papers/Yang_GAN_Prior_Embedded_Network_for_Blind_Face_Restoration_in_the_CVPR_2021_paper.pdf | cvpr-2021-1 | ['blind-face-restoration'] | ['computer-vision'] | [ 2.22048119e-01 -3.27031724e-02 4.21154141e-01 -1.74698144e-01
-7.00604737e-01 -2.49254942e-01 2.86004096e-01 -1.02635550e+00
2.63390899e-01 8.30819309e-01 4.69177127e-01 -2.85478476e-02
3.87719572e-01 -9.66651022e-01 -7.60973454e-01 -1.09472299e+00
4.80030239e-01 6.50953874e-02 -2.68812984e-01 -3.13443750e-01
-2.95544505e-01 6.70913994e-01 -1.53782284e+00 2.58163691e-01
9.23459351e-01 8.37648571e-01 2.45757252e-01 5.61423540e-01
9.06566754e-02 7.48091459e-01 -7.57212520e-01 -5.42405486e-01
3.79253447e-01 -9.34378445e-01 -2.99076945e-01 2.52690703e-01
3.80981833e-01 -6.84631228e-01 -7.74205327e-01 1.26045847e+00
8.08914423e-01 -1.03375636e-01 6.02324128e-01 -1.12484813e+00
-1.19380295e+00 -2.19005570e-02 -5.89853168e-01 -1.71206653e-01
2.50251383e-01 5.56471229e-01 2.48972356e-01 -8.56624067e-01
3.92484099e-01 1.57032597e+00 4.77665067e-01 1.22335005e+00
-1.27418399e+00 -9.36653674e-01 -2.63166457e-01 6.44365698e-02
-1.19958758e+00 -8.93414378e-01 8.58397603e-01 -2.72333443e-01
2.87508190e-01 1.92896515e-01 4.85130757e-01 1.34896958e+00
1.06306978e-01 3.67110103e-01 1.15322709e+00 -2.20406026e-01
1.51759028e-01 -2.20784038e-01 -7.38290548e-01 6.11721992e-01
1.22717097e-01 4.47779506e-01 -2.76471853e-01 8.76028314e-02
1.22057927e+00 1.78907499e-01 -7.53317654e-01 1.25363976e-01
-6.67665184e-01 5.69781661e-01 6.38152599e-01 8.93210694e-02
-5.12141049e-01 1.59277767e-01 -6.80932626e-02 1.30710781e-01
5.10453403e-01 -1.14809163e-01 -5.39372151e-04 2.82978356e-01
-8.32898796e-01 -1.38427932e-02 4.12256151e-01 6.31763637e-01
6.99598253e-01 6.17404222e-01 -3.36529672e-01 1.14167678e+00
5.93244553e-01 7.90983915e-01 4.00287151e-01 -1.09938407e+00
2.58239090e-01 3.40459675e-01 1.47660345e-01 -9.32655454e-01
2.96995789e-01 -2.72393167e-01 -1.20956206e+00 6.89154267e-01
2.65620679e-01 -2.85818070e-01 -1.35119033e+00 1.71555293e+00
3.88871819e-01 6.92050904e-02 1.79741681e-01 1.00735116e+00
1.01134014e+00 1.06179225e+00 -1.46152362e-01 -2.86359757e-01
1.08082068e+00 -9.73073006e-01 -1.06314397e+00 -4.59121913e-01
-2.81558424e-01 -1.00189972e+00 1.07878637e+00 2.17849135e-01
-1.22009778e+00 -7.45269299e-01 -8.94367814e-01 -1.39543727e-01
1.98667109e-01 4.56194490e-01 7.83548951e-02 6.32818639e-01
-1.36369693e+00 3.68287504e-01 -7.00032592e-01 -9.96656865e-02
8.16498578e-01 1.50860280e-01 -5.31406581e-01 -7.19118536e-01
-8.01517725e-01 5.41857243e-01 -1.46211371e-01 6.66623414e-01
-1.61270046e+00 -5.26605070e-01 -8.22434604e-01 9.64468420e-02
9.06842649e-02 -8.96588385e-01 8.90329242e-01 -1.20302761e+00
-1.81410754e+00 6.94133282e-01 -2.71968573e-01 1.29887938e-01
6.11862957e-01 -3.19960862e-02 -4.17839110e-01 1.77412063e-01
-9.58576351e-02 5.77811360e-01 1.27083111e+00 -1.67791212e+00
-6.52893707e-02 -4.19911712e-01 -1.96621418e-01 5.13999239e-02
-2.18678728e-01 7.59688616e-02 -5.09302974e-01 -9.69553173e-01
-3.70628648e-02 -5.68795323e-01 1.45785103e-03 2.45553136e-01
-2.24782720e-01 3.89609784e-01 9.47491944e-01 -1.37890816e+00
7.76010752e-01 -2.33557057e+00 1.26648039e-01 -2.74220079e-01
1.37228906e-01 5.69337130e-01 -5.07791817e-01 2.78365582e-01
-2.51136571e-01 1.48336627e-02 -4.81507719e-01 -5.03163874e-01
-3.30083787e-01 2.73741305e-01 -3.56138468e-01 5.67325592e-01
6.83301985e-02 9.12006855e-01 -6.48723543e-01 -1.28194422e-01
2.31807768e-01 1.19659376e+00 -3.89668494e-01 7.44962633e-01
-1.89177543e-01 8.47150326e-01 -3.58991250e-02 8.05857480e-01
1.02893162e+00 5.33228107e-02 2.88641863e-02 -2.66048998e-01
3.80529433e-01 -2.00338453e-01 -8.72344375e-01 1.26769316e+00
-5.48630476e-01 6.61703825e-01 5.83186388e-01 -6.64248943e-01
1.14736295e+00 4.83534157e-01 -2.81917676e-02 -7.43775487e-01
1.18828341e-01 1.75309777e-01 -1.39053255e-01 -5.30900180e-01
-1.56554431e-01 -4.19443250e-01 5.35873771e-01 2.32150197e-01
5.38685843e-02 -1.06118880e-01 -2.14432389e-01 -1.01060316e-01
9.20416474e-01 9.15297791e-02 -1.56778142e-01 7.31029436e-02
6.45336330e-01 -6.16672814e-01 7.02663600e-01 8.04639608e-02
4.70353663e-02 1.08709455e+00 3.28525484e-01 -2.81401515e-01
-1.19175255e+00 -1.08482945e+00 1.93168864e-01 5.06217301e-01
-4.17215228e-02 -2.80227792e-02 -1.09094906e+00 -4.44147587e-01
-3.67576867e-01 4.46097195e-01 -5.64486086e-01 -3.27833921e-01
-5.32869995e-01 -5.89870334e-01 3.60524535e-01 3.51262718e-01
9.54698205e-01 -1.46338892e+00 2.02286407e-01 2.32393537e-02
-3.75509322e-01 -9.59867597e-01 -6.40677631e-01 -4.68129933e-01
-7.16797233e-01 -9.43045378e-01 -1.12658310e+00 -9.95754838e-01
1.23115575e+00 2.07843959e-01 9.13346469e-01 3.34732383e-01
-3.69690329e-01 -8.05965513e-02 -1.93063244e-01 2.10042354e-02
-7.92369366e-01 -6.95907831e-01 -6.84281886e-02 4.10603553e-01
-1.50433034e-01 -7.30361581e-01 -9.44314241e-01 4.65882182e-01
-1.18638444e+00 1.25172839e-01 5.44238985e-01 1.07933033e+00
4.76573110e-01 3.74273032e-01 5.06954551e-01 -5.75070560e-01
5.09715676e-01 -2.04269022e-01 -6.78243518e-01 1.61694989e-01
-2.78395772e-01 -2.52476335e-01 7.70466626e-01 -3.57800364e-01
-1.42832649e+00 -3.45172510e-02 -5.79757512e-01 -5.43173313e-01
-2.76875436e-01 -5.39160445e-02 -9.09697592e-01 -2.16372252e-01
5.50663829e-01 4.50794160e-01 1.52862057e-01 -6.37002826e-01
2.88277358e-01 7.30838716e-01 6.57340944e-01 -4.20673698e-01
1.00346529e+00 6.19026065e-01 -1.64155632e-01 -6.82072461e-01
-5.37755430e-01 2.37320393e-01 -1.44231707e-01 -3.64535481e-01
8.24783981e-01 -1.11519945e+00 -4.97763604e-01 1.04593229e+00
-1.13986516e+00 -7.80848742e-01 -1.71792522e-01 -9.25501529e-03
-3.78069580e-01 2.70616949e-01 -8.22856128e-01 -7.81016946e-01
-5.25427878e-01 -1.18728864e+00 9.25792396e-01 5.80648363e-01
5.24055719e-01 -7.48660326e-01 -1.66856796e-01 6.43262863e-01
7.31331825e-01 4.49989617e-01 7.93252051e-01 3.29760402e-01
-6.08732283e-01 -7.92446434e-02 -3.39248210e-01 9.97159123e-01
5.52143514e-01 1.81148816e-02 -1.12665021e+00 -6.16078556e-01
3.45856488e-01 -2.21942127e-01 8.47119927e-01 4.77575541e-01
1.13864207e+00 -7.24908233e-01 -4.89396080e-02 8.91138613e-01
1.60866714e+00 2.21942231e-01 1.19875371e+00 -1.37881190e-01
8.57224524e-01 5.79003930e-01 2.71925598e-01 1.71004757e-01
-1.40660359e-02 6.19277060e-01 6.27029538e-01 -5.06494045e-01
-8.42903674e-01 -5.05452871e-01 6.44713819e-01 4.48796988e-01
-9.00249481e-02 -4.46595013e-01 -6.04018211e-01 5.38508236e-01
-1.42369878e+00 -8.69175613e-01 9.87819880e-02 2.00131178e+00
9.06503081e-01 -3.46890450e-01 -2.54071593e-01 3.90784405e-02
9.42698717e-01 -8.58359225e-03 -5.21223843e-01 1.02086738e-02
-2.14042589e-01 3.03489119e-01 1.30898327e-01 6.65381968e-01
-4.98731077e-01 9.08292711e-01 5.68483925e+00 8.93011689e-01
-1.23215139e+00 3.55083138e-01 9.89671767e-01 -8.01497921e-02
-3.74582440e-01 -2.48274177e-01 -6.04988456e-01 6.86076522e-01
7.09599674e-01 1.52745977e-01 8.71136427e-01 5.22735953e-01
4.15849358e-01 2.05144629e-01 -7.39726007e-01 1.23787475e+00
2.02611744e-01 -1.08324265e+00 2.19857663e-01 2.46882394e-01
1.04216218e+00 -3.29618663e-01 3.01407754e-01 -1.39921725e-01
4.15225118e-01 -1.47199416e+00 5.49653232e-01 6.95402503e-01
1.20220566e+00 -8.12098801e-01 6.91187263e-01 9.42297801e-02
-8.59319389e-01 -1.41577557e-01 -6.29936039e-01 3.00782472e-01
2.71675825e-01 8.21559548e-01 -3.25333685e-01 3.21747512e-01
8.39703560e-01 5.30330837e-01 -4.44686294e-01 8.23191881e-01
-8.18400800e-01 7.86844254e-01 1.28529936e-01 7.08268881e-01
-3.08792055e-01 -3.07044864e-01 5.62128842e-01 7.49326527e-01
5.40346920e-01 2.56866127e-01 -3.75295430e-01 1.16312408e+00
-4.55306619e-01 -2.35850602e-01 -5.52330375e-01 1.20064765e-02
1.93386823e-01 1.31850255e+00 -4.45853412e-01 -1.47136047e-01
-2.04956964e-01 1.25447345e+00 -3.43759864e-04 7.22645164e-01
-7.61221528e-01 -1.87786832e-01 8.68369401e-01 2.91889131e-01
3.97661775e-01 3.14160287e-02 1.73328016e-02 -1.13112557e+00
2.70252019e-01 -1.22284424e+00 -2.97471415e-03 -1.17630422e+00
-1.44424760e+00 1.06794608e+00 -5.94642401e-01 -1.06598437e+00
-5.73605706e-04 -5.60965419e-01 -7.25707650e-01 1.26248634e+00
-1.51249743e+00 -1.15964782e+00 -7.30320811e-01 7.70083904e-01
4.19884235e-01 -3.95655811e-01 8.14386368e-01 4.81032878e-01
-7.12181449e-01 5.71354508e-01 2.18717799e-01 2.74647713e-01
7.20542490e-01 -7.73403645e-01 3.94559681e-01 1.27683043e+00
-2.22893789e-01 3.59264731e-01 6.44699633e-01 -6.82788908e-01
-1.27706087e+00 -1.29940975e+00 2.70462096e-01 -1.25680760e-01
-4.74522710e-02 -4.29852545e-01 -9.41223562e-01 4.48999375e-01
4.03585851e-01 3.49372059e-01 3.77970725e-01 -6.55336976e-01
-2.60959089e-01 -4.37859178e-01 -1.58550942e+00 5.43680608e-01
9.22928393e-01 -5.67956984e-01 -1.08779863e-01 1.85657278e-01
6.01693392e-01 -3.82677376e-01 -5.82658350e-01 3.57045323e-01
3.47301304e-01 -1.00080943e+00 9.68939304e-01 -2.84195296e-03
7.63614178e-01 -6.35720253e-01 -1.43284172e-01 -1.52143347e+00
-1.98559299e-01 -6.24968350e-01 -1.19490042e-01 1.65553725e+00
3.77702489e-02 -6.93265080e-01 6.34484529e-01 3.21875244e-01
-4.07253802e-02 -4.85150278e-01 -6.41381502e-01 -5.57075381e-01
-1.46116942e-01 2.05994129e-01 7.81933248e-01 5.38209856e-01
-9.15206909e-01 1.75898254e-01 -5.82502663e-01 3.90201747e-01
8.15795541e-01 -1.74772039e-01 7.05056548e-01 -7.63128340e-01
-2.65591651e-01 -1.20050997e-01 -3.14441323e-01 -9.10167038e-01
1.08494423e-01 -5.78011453e-01 2.41740346e-01 -1.82848012e+00
9.62737277e-02 -1.66748375e-01 1.81501105e-01 6.33447826e-01
-1.69507846e-01 7.72512496e-01 6.29354194e-02 2.03414723e-01
2.13775665e-01 9.67989266e-01 1.70201421e+00 -1.32585883e-01
6.84046522e-02 -3.64885740e-02 -9.50627625e-01 4.44536179e-01
6.79782569e-01 -4.00687993e-01 -3.58829945e-01 -6.26024246e-01
-1.91580981e-01 2.64780462e-01 5.91048181e-01 -9.48902726e-01
-1.07522923e-02 -3.43986452e-02 8.56774032e-01 -6.61692172e-02
4.43186492e-01 -8.33657622e-01 5.90734839e-01 3.65092397e-01
9.24734324e-02 -3.58722508e-01 3.16997856e-01 4.21037585e-01
-4.26808655e-01 4.98761646e-02 1.32308793e+00 -2.30908364e-01
-1.32965565e-01 5.06208241e-01 1.29537638e-02 -2.39142925e-01
7.68059850e-01 -3.88824083e-02 -4.84218210e-01 -7.19300270e-01
-5.88429213e-01 -1.94962069e-01 7.84894228e-01 3.79753619e-01
1.00150931e+00 -1.47953594e+00 -1.09036183e+00 6.07320607e-01
-3.72550696e-01 1.10193767e-01 6.66146338e-01 2.80637980e-01
-7.60990500e-01 -1.27121240e-01 -5.23914576e-01 -2.83264339e-01
-1.28714263e+00 5.85222900e-01 6.46474838e-01 1.43560603e-01
-6.79597497e-01 8.38495970e-01 6.52046621e-01 -3.47853661e-01
1.50203064e-01 2.86568284e-01 -2.49086935e-02 -4.21097040e-01
8.19238126e-01 2.52474457e-01 4.98413295e-03 -7.77362108e-01
-2.91703790e-02 6.10171139e-01 2.60242015e-01 -1.13345021e-02
1.56608260e+00 -2.76958644e-01 -5.65363228e-01 -4.20732796e-01
1.11689019e+00 1.54477030e-01 -1.68203735e+00 3.46261375e-02
-9.80333507e-01 -8.90501857e-01 1.70241013e-01 -8.98461819e-01
-1.88758957e+00 9.03173923e-01 9.06813979e-01 -1.91800520e-01
1.69293499e+00 -5.76408766e-02 7.83877075e-01 -4.30578977e-01
1.78176254e-01 -4.38994855e-01 3.42954278e-01 -7.51047730e-02
1.34574354e+00 -9.30790007e-01 -2.10078642e-01 -3.77533644e-01
-4.03534979e-01 1.02718198e+00 7.83744514e-01 -1.34505644e-01
4.93898928e-01 2.65832275e-01 3.72097462e-01 -7.09811375e-02
-4.33921635e-01 1.27472833e-01 1.69625759e-01 8.91976833e-01
2.76353657e-01 -1.17242672e-01 1.44917890e-01 4.82441902e-01
-1.70097560e-01 9.64680314e-02 5.17778158e-01 3.93454462e-01
-3.79339233e-02 -1.11964548e+00 -6.34763837e-01 1.29721180e-01
-5.12593925e-01 -3.87864336e-02 -1.07305028e-01 2.31418863e-01
2.67258674e-01 1.07122624e+00 -2.56894112e-01 -2.42286772e-01
2.21162185e-01 -2.77182519e-01 4.68286335e-01 -4.75988090e-01
-1.71035022e-01 1.77904874e-01 -3.43099684e-01 -5.74686587e-01
-2.60416687e-01 -2.69504935e-01 -8.33656013e-01 -4.59358394e-01
-8.63308832e-02 -1.62152037e-01 5.17315924e-01 6.35227263e-01
4.22210604e-01 6.50446236e-01 8.99851620e-01 -9.03290808e-01
-2.40867063e-01 -1.06751573e+00 -6.28963947e-01 2.94679731e-01
5.59369087e-01 -3.45571697e-01 -6.41275048e-01 4.41172153e-01] | [12.811806678771973, -0.08628809452056885] |
35eb19b6-c201-4d5e-8d60-663d24019be6 | acid-action-conditional-implicit-visual | 2203.06856 | null | https://arxiv.org/abs/2203.06856v3 | https://arxiv.org/pdf/2203.06856v3.pdf | ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation | Manipulating volumetric deformable objects in the real world, like plush toys and pizza dough, bring substantial challenges due to infinite shape variations, non-rigid motions, and partial observability. We introduce ACID, an action-conditional visual dynamics model for volumetric deformable objects based on structured implicit neural representations. ACID integrates two new techniques: implicit representations for action-conditional dynamics and geodesics-based contrastive learning. To represent deformable dynamics from partial RGB-D observations, we learn implicit representations of occupancy and flow-based forward dynamics. To accurately identify state change under large non-rigid deformations, we learn a correspondence embedding field through a novel geodesics-based contrastive loss. To evaluate our approach, we develop a simulation framework for manipulating complex deformable shapes in realistic scenes and a benchmark containing over 17,000 action trajectories with six types of plush toys and 78 variants. Our model achieves the best performance in geometry, correspondence, and dynamics predictions over existing approaches. The ACID dynamics models are successfully employed to goal-conditioned deformable manipulation tasks, resulting in a 30% increase in task success rate over the strongest baseline. Furthermore, we apply the simulation-trained ACID model directly to real-world objects and show success in manipulating them into target configurations. For more results and information, please visit https://b0ku1.github.io/acid/ . | ['Yuke Zhu', 'Anima Anandkumar', 'Silvio Savarese', 'Leonidas J. Guibas', 'Christopher Choy', 'Zhenyu Jiang', 'Bokui Shen'] | 2022-03-14 | null | null | null | null | ['deformable-object-manipulation'] | ['robots'] | [-1.68756694e-01 -8.25370029e-02 1.56968143e-02 -6.31444454e-02
-6.75106883e-01 -8.19634318e-01 6.15527034e-01 -3.50898534e-01
-1.10698164e-01 6.06550336e-01 2.73940355e-01 7.35405236e-02
-7.02219009e-02 -7.01378107e-01 -1.04617298e+00 -8.14396918e-01
-3.78534406e-01 7.55744636e-01 4.40332651e-01 -3.18858087e-01
1.10682711e-01 9.80079770e-01 -1.17400992e+00 2.79909402e-01
6.42447472e-01 6.63033128e-01 2.82534570e-01 9.57365870e-01
2.87352830e-01 6.91120088e-01 -6.68649450e-02 -1.04299061e-01
4.51920509e-01 1.00660816e-01 -8.62294674e-01 -2.65644103e-01
6.94689691e-01 -7.97214210e-01 -9.65870619e-01 5.55451572e-01
4.89300907e-01 5.95842600e-01 9.68400538e-01 -1.13104010e+00
-1.07940304e+00 1.09952569e-01 -2.33562171e-01 2.64691621e-01
2.55487710e-01 8.96151125e-01 8.10154557e-01 -9.78511631e-01
1.11048138e+00 1.68823302e+00 5.52327931e-01 8.74072433e-01
-1.24603868e+00 -3.89597893e-01 4.35470700e-01 -1.64777592e-01
-1.06189382e+00 -3.18751544e-01 5.47113001e-01 -7.11961985e-01
1.20326400e+00 2.86968529e-01 9.93471146e-01 1.38524830e+00
3.91636789e-01 8.90003026e-01 8.31130028e-01 2.73785949e-01
1.58009604e-01 -5.23843467e-01 -2.29768246e-01 1.14182615e+00
-4.65915762e-02 3.04644644e-01 -2.10006922e-01 -1.27190500e-01
1.37584507e+00 1.10586341e-02 -2.88534522e-01 -8.13252807e-01
-1.46240044e+00 5.91010809e-01 7.64046788e-01 -1.67166322e-01
-1.49659634e-01 9.67930317e-01 1.29275113e-01 -1.31245419e-01
5.82937658e-01 4.66112167e-01 -4.47147191e-01 -1.99608952e-01
-4.24444884e-01 8.98014545e-01 7.41953611e-01 1.02931750e+00
3.33444268e-01 2.83419967e-01 -5.02014041e-01 2.51099706e-01
3.85456145e-01 8.74879360e-01 -5.70566766e-02 -1.40637577e+00
3.57805163e-01 1.95806846e-01 3.66153032e-01 -9.92169857e-01
-4.09226507e-01 1.11257441e-01 -4.91804421e-01 4.73613799e-01
4.51245695e-01 1.90715224e-01 -1.44982958e+00 1.74617970e+00
6.04354858e-01 4.13794637e-01 -3.93927842e-01 9.80748594e-01
8.19264054e-01 8.39060009e-01 1.79633051e-01 2.29754806e-01
6.93405151e-01 -9.79660273e-01 -5.87204516e-01 3.61348957e-01
4.58348930e-01 -2.89922088e-01 1.21204340e+00 -2.51830257e-02
-1.38496828e+00 -2.44906574e-01 -5.91703176e-01 -4.43325996e-01
-3.31660688e-01 -1.75224409e-01 5.78333259e-01 -1.48545578e-01
-1.08483112e+00 1.02015126e+00 -1.64222181e+00 -9.12656188e-02
7.00183153e-01 4.20602381e-01 -2.02854097e-01 1.61248352e-02
-8.41066599e-01 7.81871617e-01 4.12136726e-02 1.30726695e-01
-1.53497279e+00 -1.14719999e+00 -8.82509232e-01 -3.12432885e-01
1.60469159e-01 -9.11325991e-01 1.08354747e+00 -2.88419247e-01
-1.81189871e+00 8.38188827e-01 6.42616153e-02 -1.00466214e-01
9.41822410e-01 -4.46363419e-01 2.61167824e-01 1.73740074e-01
-2.18553215e-01 8.39561582e-01 8.39129925e-01 -1.27926195e+00
1.71567246e-01 -1.12062655e-01 3.23800802e-01 3.15319330e-01
1.06809065e-01 -3.39189768e-01 -3.26514781e-01 -8.99124384e-01
-4.08298485e-02 -1.43403864e+00 -3.17331493e-01 7.73236156e-01
-4.06900823e-01 -1.18950196e-01 1.08429897e+00 -7.79259562e-01
6.16194308e-01 -1.83217955e+00 9.59294081e-01 -8.51111785e-02
3.53035718e-01 3.17238122e-01 -3.74688148e-01 2.12609813e-01
2.72125959e-01 1.47384256e-01 -3.37686300e-01 -2.45124087e-01
1.94371134e-01 3.88419986e-01 -4.28797930e-01 5.15834928e-01
4.17748183e-01 1.65306354e+00 -1.16546285e+00 -1.11648500e-01
5.16906321e-01 7.35621631e-01 -7.84593046e-01 2.67502248e-01
-7.39731371e-01 1.07664216e+00 -6.76529169e-01 8.65902424e-01
5.18060207e-01 -2.50169933e-01 -2.32545286e-01 -3.00580829e-01
-1.18945323e-01 1.47102013e-01 -9.10767674e-01 1.92244923e+00
-2.40876213e-01 4.15550441e-01 2.43909657e-02 -7.02073991e-01
4.86613542e-01 4.07857560e-02 7.54713476e-01 -4.19905275e-01
3.19648944e-02 4.06325571e-02 -1.94831505e-01 -7.30103135e-01
3.54387313e-01 1.84062019e-01 1.18184924e-01 1.70681894e-01
-9.92888734e-02 -9.42111135e-01 -2.08975911e-01 2.02597007e-01
1.28439498e+00 9.02587235e-01 -2.60766417e-01 -3.17348003e-01
-3.17916390e-03 -6.98536336e-02 2.66113162e-01 4.31722075e-01
-2.88233668e-01 7.18405843e-01 2.25410402e-01 -7.24568248e-01
-1.30235100e+00 -1.70070386e+00 -5.34282736e-02 9.07040238e-01
3.77659440e-01 -1.26091436e-01 -4.34873611e-01 -4.15366203e-01
5.49584270e-01 5.11542320e-01 -8.82883072e-01 -2.88223147e-01
-1.08212483e+00 -4.89393204e-01 2.85433859e-01 7.06491649e-01
2.49183595e-01 -1.47079444e+00 -4.61387694e-01 1.99914724e-01
-1.14286236e-01 -1.00151658e+00 -5.73336840e-01 -3.71462703e-01
-8.40016007e-01 -9.16797698e-01 -8.81397605e-01 -4.86285150e-01
5.32283962e-01 1.23455077e-01 1.00083125e+00 -5.10353036e-02
-7.93107510e-01 9.12665367e-01 -4.08669151e-02 -2.19066106e-02
-3.94252270e-01 -2.91263312e-02 1.37961939e-01 -4.61285561e-01
-5.75700283e-01 -6.61492765e-01 -9.06398952e-01 2.94907033e-01
-7.39121199e-01 1.05159350e-01 1.43523738e-01 4.19630945e-01
8.29216778e-01 -8.55179250e-01 7.72751570e-02 -3.96468252e-01
2.27144748e-01 -4.69588578e-01 -5.64174712e-01 9.74579826e-02
7.56191835e-02 2.16752857e-01 1.71363235e-01 -9.00254071e-01
-9.87141132e-01 1.46988869e-01 6.42885640e-03 -9.65185046e-01
2.16536894e-01 3.08017433e-02 1.52792662e-01 -3.67166817e-01
6.88010514e-01 -1.21165048e-02 -1.08657531e-01 -3.57325315e-01
7.41168499e-01 -1.46967217e-01 3.29996884e-01 -1.02164066e+00
1.12421322e+00 8.53040874e-01 1.36875480e-01 -6.43816590e-01
-6.77897930e-01 -2.66427025e-02 -8.18927586e-01 -3.55851024e-01
1.11527026e+00 -7.28314579e-01 -9.66926873e-01 7.55547941e-01
-1.06625867e+00 -1.24595773e+00 -5.27055740e-01 4.62062567e-01
-1.08693612e+00 1.50210008e-01 -9.17979181e-01 -5.56892276e-01
-2.57325441e-01 -1.28083110e+00 1.44237757e+00 3.33792567e-02
-9.84269902e-02 -1.02330768e+00 2.72098690e-01 1.29114360e-01
6.14427865e-01 9.06606555e-01 8.01830232e-01 -2.01673210e-02
-1.24910533e+00 2.16106176e-01 1.46255782e-02 1.81116447e-01
2.46233717e-01 3.74396682e-01 -6.22010529e-01 -5.87312281e-01
-5.59766114e-01 -6.40270650e-01 9.35981870e-01 5.96016049e-01
1.64464474e+00 -2.07153693e-01 -4.19892669e-01 1.04732788e+00
1.09393585e+00 -4.52537723e-02 5.74979782e-01 -1.13599777e-01
1.30768609e+00 2.93870151e-01 5.17235756e-01 5.32554924e-01
3.69740248e-01 7.45358288e-01 8.35008800e-01 1.58270985e-01
-3.95019114e-01 -2.24902451e-01 4.84515280e-01 9.32074308e-01
-7.14371085e-01 -2.83075750e-01 -8.72755229e-01 5.72785437e-01
-1.68953097e+00 -9.64721441e-01 -7.77452663e-02 1.97237778e+00
8.21224034e-01 -6.57413080e-02 5.49379922e-02 -7.17055976e-01
3.42176557e-01 3.44709247e-01 -1.17940748e+00 -2.34976411e-01
1.34500667e-01 3.83193702e-01 2.74443120e-01 6.66966379e-01
-1.17020023e+00 1.33534801e+00 6.02306366e+00 5.88661849e-01
-1.21753097e+00 9.94343534e-02 3.69342387e-01 -5.33030331e-01
-6.39093637e-01 -2.07808346e-01 -6.46675646e-01 3.49330962e-01
5.27886808e-01 -2.10255235e-02 6.87767923e-01 4.89134133e-01
3.96901935e-01 2.86589444e-01 -1.12098348e+00 6.99237645e-01
-1.75178364e-01 -1.62360418e+00 3.26014727e-01 1.00051180e-01
9.27678287e-01 2.80780256e-01 4.09132838e-01 3.40651065e-01
7.69802570e-01 -1.13138270e+00 8.80135000e-01 9.44282949e-01
8.19388151e-01 -2.80462116e-01 -2.32708186e-01 1.20675772e-01
-1.35300696e+00 1.30144849e-01 -2.74300754e-01 1.91156596e-01
3.95705909e-01 3.38097550e-02 -4.31692392e-01 3.17023844e-01
7.66860723e-01 1.01134241e+00 -1.59233250e-02 7.84888685e-01
-4.37316634e-02 3.88641953e-01 -5.17259061e-01 8.33191350e-02
3.12465847e-01 -2.93241203e-01 1.04471636e+00 1.07939899e+00
1.55899808e-01 3.37226450e-01 2.54376113e-01 1.24439538e+00
-1.41388819e-01 -3.65477651e-01 -7.58062601e-01 -6.01558425e-02
1.26411408e-01 1.12090480e+00 -5.66393256e-01 -2.60149300e-01
8.29112250e-03 1.08028829e+00 6.20378256e-01 6.22020781e-01
-1.36168075e+00 2.52931952e-01 1.09004319e+00 3.79739881e-01
4.04212177e-01 -8.84187400e-01 3.85987669e-01 -1.31555974e+00
8.74646157e-02 -4.78801578e-01 -1.93986371e-01 -9.15425599e-01
-1.22207510e+00 1.60081744e-01 4.00271684e-01 -1.06051767e+00
9.92333051e-03 -7.06727803e-01 -3.70361328e-01 7.33578861e-01
-1.22411084e+00 -1.45433164e+00 -5.41659594e-01 5.93672395e-01
5.70153475e-01 3.35271746e-01 6.28163695e-01 4.63323854e-02
-1.93903089e-01 2.15570182e-01 1.24271847e-01 1.64665207e-01
5.50062895e-01 -1.24898863e+00 8.39849591e-01 3.22269112e-01
-9.14232507e-02 3.73919487e-01 4.61743742e-01 -8.68279040e-01
-1.70534468e+00 -1.50579858e+00 -1.89975098e-01 -9.92176652e-01
6.91372335e-01 -5.50289631e-01 -1.14632249e+00 1.03166902e+00
-2.87803590e-01 7.51090169e-01 -5.56040294e-02 -6.02662504e-01
-2.48725832e-01 3.95772696e-01 -1.16702843e+00 8.12752604e-01
1.87476277e+00 -4.52918887e-01 -2.98629642e-01 6.79397702e-01
1.08367407e+00 -1.12139928e+00 -1.08285260e+00 7.22197652e-01
7.58500218e-01 -4.35709089e-01 1.29717135e+00 -1.09732652e+00
5.33507466e-01 -1.72625333e-01 -1.72070712e-01 -1.27978897e+00
-4.75792795e-01 -7.76083469e-01 -6.77627027e-01 5.67778230e-01
6.65207431e-02 -5.14966190e-01 6.81664824e-01 7.67108083e-01
-3.31566274e-01 -1.10800612e+00 -8.55309427e-01 -9.29921985e-01
5.87362289e-01 -5.81236891e-02 2.80647606e-01 1.01357293e+00
-6.89216137e-01 -3.97943377e-01 -3.10389668e-01 1.60766378e-01
5.04460633e-01 5.50742261e-02 7.17529833e-01 -8.46892536e-01
-3.60673130e-01 -2.48904571e-01 -4.78404582e-01 -1.34303093e+00
3.84996295e-01 -1.07104516e+00 1.93817783e-02 -1.66162598e+00
1.67316094e-01 -7.54855096e-01 2.98139676e-02 6.00069046e-01
-5.94923310e-02 1.99086905e-01 4.30236936e-01 2.75203049e-01
-4.29335982e-01 1.01047528e+00 2.09141231e+00 -3.67416650e-01
-3.68580669e-01 -1.43541902e-01 1.85221821e-01 7.58652985e-01
6.64861023e-01 -3.18613559e-01 -5.08243382e-01 -7.03555167e-01
9.04009789e-02 1.74418285e-01 8.46711576e-01 -8.26956511e-01
-2.48565346e-01 -6.27792656e-01 2.11576253e-01 -3.66881907e-01
7.58161128e-01 -3.58433217e-01 2.68033892e-01 6.96302056e-01
-4.46090102e-01 1.15476072e-01 4.36654568e-01 7.99435079e-01
4.26741719e-01 3.64690900e-01 8.19276273e-01 -2.95384377e-01
-6.05093002e-01 1.17501009e+00 -2.26789936e-01 4.14006889e-01
1.13277471e+00 -2.19459273e-03 -3.23147357e-01 -2.06674784e-01
-1.30939198e+00 1.00060865e-01 6.54174924e-01 6.89255059e-01
8.07658553e-01 -1.41928577e+00 -6.99832022e-01 -7.95222446e-02
-1.26066178e-01 4.67929363e-01 3.05367470e-01 7.12451339e-01
-9.83989418e-01 1.37198837e-02 -3.00974280e-01 -6.88837528e-01
-9.26235676e-01 3.78736705e-01 6.47803962e-01 -2.15309083e-01
-9.96161461e-01 9.74225104e-01 5.55903673e-01 -6.99698091e-01
2.90674958e-02 -9.95645642e-01 3.17526311e-01 -5.21857262e-01
9.75751504e-02 4.75798488e-01 -2.54468232e-01 -6.06434166e-01
-2.83052593e-01 8.75098288e-01 1.25083253e-01 -8.26551095e-02
1.39710176e+00 3.32499772e-01 6.90885857e-02 5.55477977e-01
1.20793557e+00 -1.84548646e-01 -1.92236006e+00 6.04309654e-03
-6.67123199e-01 -4.89021897e-01 -3.49572092e-01 -5.80483794e-01
-1.16483057e+00 9.31058884e-01 4.89078254e-01 -2.36760363e-01
3.87454510e-01 1.77271098e-01 7.59829640e-01 5.15745938e-01
4.80058759e-01 -6.49682999e-01 6.68792427e-01 7.38057017e-01
1.48925531e+00 -1.07738745e+00 3.94086577e-02 -5.52967131e-01
-4.06949073e-01 9.56048965e-01 8.12818587e-01 -7.34724104e-01
9.01834726e-01 3.70875627e-01 -3.98629993e-01 -3.75971615e-01
-7.57788658e-01 1.00435622e-01 3.54410708e-01 6.79883838e-01
4.19208780e-02 2.45094568e-01 2.45525762e-01 -2.57457912e-01
7.34166801e-02 -7.14072213e-02 2.62005538e-01 9.85655010e-01
-2.08012477e-01 -6.28153563e-01 2.81541590e-02 3.67132038e-01
-9.87483636e-02 1.29139990e-01 -1.68558046e-01 9.57274437e-01
-2.52755046e-01 8.29692036e-02 2.46528551e-01 -1.30369766e-02
4.13598746e-01 -2.66428053e-01 1.05739689e+00 -5.71383536e-01
-3.22036356e-01 -3.02501470e-01 -2.38314137e-01 -1.20117462e+00
-4.68893886e-01 -7.72300661e-01 -1.61363649e+00 -5.45874536e-01
1.05596438e-01 -6.69585347e-01 4.15976018e-01 7.59672582e-01
5.14248371e-01 6.24444962e-01 3.00012767e-01 -1.68981445e+00
-7.69329190e-01 -6.76972568e-01 -1.98723003e-01 7.87112951e-01
5.19358754e-01 -1.12300837e+00 -3.89481723e-01 1.50559977e-01] | [4.9885382652282715, 0.29269570112228394] |
40fbfd47-5c29-4398-b786-99638d2111c9 | perplexity-from-plm-is-unreliable-for | 2210.05892 | null | https://arxiv.org/abs/2210.05892v2 | https://arxiv.org/pdf/2210.05892v2.pdf | Perplexity from PLM Is Unreliable for Evaluating Text Quality | Recently, amounts of works utilize perplexity~(PPL) to evaluate the quality of the generated text. They suppose that if the value of PPL is smaller, the quality(i.e. fluency) of the text to be evaluated is better. However, we find that the PPL referee is unqualified and it cannot evaluate the generated text fairly for the following reasons: (i) The PPL of short text is larger than long text, which goes against common sense, (ii) The repeated text span could damage the performance of PPL, and (iii) The punctuation marks could affect the performance of PPL heavily. Experiments show that the PPL is unreliable for evaluating the quality of given text. Last, we discuss the key problems with evaluating text quality using language models. | ['Xuying Meng', 'Aixin Sun', 'Jiawen Deng', 'Yequan Wang'] | 2022-10-12 | null | null | null | null | ['common-sense-reasoning'] | ['reasoning'] | [-2.10923642e-01 -2.23739091e-02 -3.65499891e-02 -2.30803922e-01
-7.86203325e-01 -8.60483587e-01 4.00196493e-01 3.46290499e-01
-3.57803911e-01 9.79024708e-01 4.31879610e-01 -5.77060103e-01
-8.33653882e-02 -7.16957211e-01 -3.55723143e-01 -3.63918126e-01
5.05792797e-01 3.60459030e-01 3.37870300e-01 -1.90128461e-01
7.41572618e-01 5.10346651e-01 -1.34523618e+00 1.16774388e-01
1.26851916e+00 4.82576758e-01 3.11792195e-01 8.48368108e-01
-4.94737327e-01 5.66974044e-01 -1.21814942e+00 -6.59299016e-01
-9.92693976e-02 -6.26189828e-01 -1.22966063e+00 1.38579920e-01
1.89503565e-01 -1.83086619e-01 -3.69938135e-01 1.44456220e+00
2.76536584e-01 -1.96995083e-02 7.27532566e-01 -1.25450611e+00
-5.54582536e-01 8.62943828e-01 -2.00470775e-01 3.01987112e-01
6.68560922e-01 1.21863239e-01 9.73526359e-01 -5.66932678e-01
5.15981793e-01 1.56689596e+00 3.49607944e-01 2.32698277e-01
-8.50091875e-01 -4.26084489e-01 1.15929820e-01 -3.13192129e-01
-1.41143858e+00 -4.89908010e-01 3.43899876e-01 -3.02533507e-01
8.33373845e-01 2.98280776e-01 4.74129289e-01 8.46681178e-01
6.62668943e-01 5.81888318e-01 1.02967310e+00 -7.13894367e-01
9.90248397e-02 1.84492528e-01 3.33597243e-01 7.13971317e-01
5.96872926e-01 -3.22128057e-01 -5.67492902e-01 -2.16302484e-01
4.04871941e-01 -4.50728536e-01 -1.29606798e-01 5.98828256e-01
-1.14176881e+00 5.18515229e-01 -2.11082593e-01 7.45114684e-01
-1.70639217e-01 -8.84063914e-02 2.14446187e-01 4.43308085e-01
3.53088111e-01 8.21923971e-01 -3.78935903e-01 -7.32654154e-01
-9.65139389e-01 2.26555899e-01 1.15248251e+00 1.07297540e+00
5.50227821e-01 -9.84350368e-02 -3.76006961e-01 8.50358903e-01
3.93036067e-01 8.42614412e-01 6.29000902e-01 -1.08764696e+00
7.54726112e-01 5.48344731e-01 3.42356473e-01 -8.59046638e-01
-1.61997974e-01 -1.18812006e-02 -3.09526473e-01 4.42192405e-02
7.82764316e-01 -2.92992890e-01 -6.84502542e-01 1.55502284e+00
-4.31786954e-01 -8.19101334e-01 -6.04434088e-02 4.44424123e-01
7.33880997e-01 9.23815787e-01 4.42244597e-02 -5.59872985e-01
1.12698102e+00 -6.70237064e-01 -1.16224492e+00 -2.16959208e-01
7.38735080e-01 -1.32515812e+00 1.39842260e+00 4.49285656e-01
-1.33204770e+00 -4.47773486e-01 -9.88453627e-01 1.39186576e-01
-1.52679414e-01 2.60129496e-02 3.03388804e-01 8.21747303e-01
-1.13036132e+00 5.70120394e-01 -5.04673421e-01 -5.46365201e-01
-2.87272036e-01 -4.95196655e-02 -3.54108810e-02 -2.58989614e-02
-1.47268295e+00 9.16127384e-01 3.57816905e-01 -1.90083176e-01
-4.27571505e-01 8.17029085e-03 -6.17577970e-01 8.46414790e-02
1.36824613e-02 -3.71393651e-01 1.24847150e+00 -9.00462329e-01
-1.32094491e+00 5.60425520e-01 -4.27449435e-01 2.45347649e-01
6.16179287e-01 -9.91111174e-02 -6.66227341e-01 1.82864502e-01
3.33826572e-01 3.07445675e-01 6.09301984e-01 -9.91457462e-01
-7.22117364e-01 -3.40013117e-01 -4.95215170e-02 4.59391028e-01
-2.15303347e-01 1.22059032e-01 -7.76624084e-01 -6.54548109e-01
2.08781868e-01 -7.14490712e-01 2.30359048e-01 -4.40893710e-01
-6.17281973e-01 -5.46648026e-01 6.27071440e-01 -7.07064688e-01
1.94810510e+00 -2.21350622e+00 -5.58027864e-01 3.03299010e-01
1.30867526e-01 4.24673140e-01 -2.89811015e-01 5.65989614e-01
1.21602185e-01 9.87524927e-01 1.57211229e-01 2.00382009e-01
1.52855711e-02 1.62502244e-01 -4.49627526e-02 1.92918479e-01
2.20447499e-02 7.24929333e-01 -8.63584042e-01 -7.86089599e-01
-2.55777836e-01 -3.33767496e-02 -2.63777316e-01 1.03779577e-01
-3.83999012e-02 -2.09556058e-01 -5.10254622e-01 5.07721841e-01
3.43861312e-01 -1.27793610e-01 -8.06917101e-02 2.25523621e-01
-2.84233391e-01 5.71594179e-01 -1.16153741e+00 1.06516111e+00
-3.78525704e-01 8.12315583e-01 -3.87365788e-01 -1.28313556e-01
7.87775636e-01 4.17561173e-01 -5.28891385e-02 -5.99832714e-01
-2.14352936e-01 1.71458706e-01 9.48849991e-02 -7.34366179e-01
9.04340625e-01 -3.04246377e-02 5.09967394e-02 8.82760823e-01
-3.37043434e-01 -3.51669043e-01 7.86625504e-01 5.76489210e-01
1.06676054e+00 -2.01090410e-01 1.23004980e-01 -3.01395863e-01
1.97424099e-01 -1.21033244e-01 5.54123223e-01 9.78362024e-01
-4.89107072e-01 2.81175464e-01 9.87388074e-01 3.88132751e-01
-1.20680392e+00 -9.55927670e-01 -1.50215507e-01 1.05211687e+00
1.47057965e-01 -4.37990665e-01 -9.88760769e-01 -7.29580641e-01
-1.79687381e-01 1.16249895e+00 -8.72296914e-02 -7.03410283e-02
-2.55543202e-01 -5.82385600e-01 9.15957332e-01 3.86131018e-01
2.33018026e-01 -9.93379533e-01 -1.72149897e-01 2.42744610e-01
-8.24254811e-01 -8.60310197e-01 -6.44136429e-01 -1.96816087e-01
-1.00838959e+00 -8.39972079e-01 -6.01132751e-01 -6.97083712e-01
7.39641786e-01 4.10581559e-01 1.13576162e+00 4.71425772e-01
4.66407031e-01 2.61350125e-01 -7.42926657e-01 -2.33967841e-01
-9.58432198e-01 5.80905937e-02 5.97121678e-02 -8.05542707e-01
3.83965194e-01 1.09378928e-02 -2.13047534e-01 3.69582087e-01
-9.28069890e-01 -2.92328924e-01 5.91642439e-01 5.36659300e-01
1.80601642e-01 6.02149606e-01 5.98843515e-01 -6.79279447e-01
1.32894564e+00 -1.72666267e-01 -2.75605798e-01 5.18164337e-01
-1.05414939e+00 3.73480231e-01 4.24893707e-01 -3.35451186e-01
-1.09443760e+00 -6.80398047e-01 -3.65566432e-01 3.83723766e-01
-2.05110162e-01 4.68282312e-01 -3.44661176e-01 2.32601553e-01
6.20640099e-01 2.87554096e-02 -1.78838298e-01 -4.09547746e-01
-6.98930249e-02 1.04829586e+00 1.40073344e-01 -4.01117980e-01
5.03052711e-01 -1.79945499e-01 -3.63547534e-01 -8.53905201e-01
-6.35124922e-01 -3.19555193e-01 -3.13124299e-01 -2.78224230e-01
6.47962213e-01 -5.07072270e-01 -5.52352726e-01 1.94437310e-01
-1.36480153e+00 -9.16150138e-02 1.47000879e-01 6.79493129e-01
-3.49756181e-01 9.19056177e-01 -7.81529248e-01 -9.04678822e-01
-1.57549903e-01 -1.28686023e+00 7.70514727e-01 3.02757770e-01
-7.00947046e-01 -8.81230712e-01 -1.78561792e-01 3.05413038e-01
2.11568661e-02 -3.97425920e-01 1.29957545e+00 -6.06799364e-01
-1.82998292e-02 -4.57459241e-01 -2.72780716e-01 5.23611069e-01
5.71326502e-02 7.29075670e-01 -6.19450092e-01 -1.29821345e-01
2.42762566e-02 -2.02046469e-01 3.46730888e-01 2.54351705e-01
7.34077632e-01 -4.57005590e-01 -1.60757437e-01 -2.72124503e-02
1.07968080e+00 5.37416041e-01 7.43487954e-01 2.64024734e-01
3.38868797e-01 5.48035562e-01 7.07943678e-01 4.08786714e-01
2.84987062e-01 2.90160358e-01 -1.89445078e-01 1.18971087e-01
-7.50493631e-02 -3.85455430e-01 7.91106343e-01 1.28683603e+00
2.00814992e-01 -9.46697712e-01 -9.68563020e-01 3.74314964e-01
-1.47054219e+00 -9.48034465e-01 -4.29715037e-01 2.10746717e+00
8.69907498e-01 4.46810424e-01 -1.60297051e-01 4.16563332e-01
9.47793245e-01 5.79788610e-02 -1.88809365e-01 -8.31412256e-01
-2.14727610e-01 -3.17582548e-01 3.03903222e-01 7.37611175e-01
-3.16222817e-01 9.28040087e-01 7.90643883e+00 7.66112864e-01
-7.87362337e-01 -1.41328976e-01 6.51164055e-01 1.47068873e-01
-5.92835486e-01 4.36362401e-02 -8.99013281e-01 7.56230712e-01
9.42838848e-01 -6.80239737e-01 1.46492779e-01 3.85147184e-01
5.03318310e-01 -5.32089651e-01 -8.52429688e-01 7.04848230e-01
8.99742991e-02 -5.10985255e-01 3.60347182e-01 -1.52769489e-02
4.57318693e-01 -2.20878974e-01 -5.12848608e-02 3.10874194e-01
2.77308941e-01 -7.29626179e-01 8.78507853e-01 6.45399868e-01
5.89208663e-01 -9.46688175e-01 8.69591773e-01 5.61748564e-01
-7.59540856e-01 3.07455122e-01 -5.26305795e-01 -3.19765136e-02
5.64353727e-02 9.11247134e-01 -6.94595873e-01 2.41484702e-01
3.99075985e-01 7.76833855e-03 -9.06692147e-01 9.07724679e-01
-6.05142415e-01 8.19455624e-01 -1.61114886e-01 -5.12648404e-01
4.12596375e-01 -1.57444894e-01 6.60150707e-01 1.33874488e+00
4.64504927e-01 3.74885909e-02 -4.18636650e-02 6.62031233e-01
-1.88111886e-01 2.54976422e-01 -2.75373876e-01 -6.32893205e-01
6.55902803e-01 7.70663261e-01 -7.40325093e-01 -5.17057598e-01
-3.44179064e-01 7.87905335e-01 -7.28233084e-02 5.76673329e-01
-2.80801535e-01 -7.66968906e-01 2.93486565e-01 3.35369334e-02
-1.59980804e-01 -1.16204046e-01 -3.44594091e-01 -9.46465075e-01
1.71404809e-01 -9.74308968e-01 2.45052561e-01 -9.54710603e-01
-1.19504726e+00 7.58512437e-01 -2.43703321e-01 -1.10729599e+00
-4.36502993e-01 -3.82596910e-01 -3.18134546e-01 1.10422921e+00
-9.94079769e-01 -2.48922095e-01 1.66496620e-01 1.89949036e-01
6.47537172e-01 -7.10123405e-02 5.28338671e-01 1.34388477e-01
-5.56664407e-01 6.47540987e-01 1.30398691e-01 2.09523380e-01
8.97840679e-01 -1.21790743e+00 2.49443054e-01 1.21023846e+00
-1.76211074e-01 7.38702118e-01 9.78818059e-01 -9.99054313e-01
-1.02417302e+00 -7.20030129e-01 1.78913307e+00 -6.39026523e-01
6.04876161e-01 1.57894135e-01 -8.89533520e-01 1.37488127e-01
1.29786462e-01 -8.85371864e-01 6.89483166e-01 1.96463019e-01
-1.56346396e-01 4.37921695e-02 -1.13118017e+00 7.40243673e-01
5.74012041e-01 -6.34936333e-01 -7.86994755e-01 4.07476544e-01
6.99375868e-01 -8.92744660e-02 -9.07297134e-01 -1.50332421e-01
6.34019613e-01 -8.95270646e-01 2.76842535e-01 -3.45393956e-01
4.77143764e-01 -2.84379393e-01 -1.39935117e-03 -1.29283857e+00
-4.85588908e-01 -4.35907841e-01 2.62254536e-01 1.46046984e+00
8.16069901e-01 -3.52192193e-01 1.92294300e-01 1.09143293e+00
1.60064593e-01 -3.34352285e-01 -4.82146621e-01 -1.01525617e+00
2.26354927e-01 -4.82295543e-01 6.48034811e-01 8.48443270e-01
4.95186418e-01 5.08017540e-01 -6.36419877e-02 -1.17340431e-01
6.27131090e-02 -2.18478084e-01 1.47097304e-01 -1.18262553e+00
5.42156771e-02 -6.95980430e-01 -1.23770414e-02 -1.03439152e+00
1.99747104e-02 -6.41065121e-01 3.47740322e-01 -1.83737993e+00
1.57506615e-01 -3.68362516e-01 -5.53040616e-02 2.90521264e-01
-5.53420544e-01 -2.05520123e-01 3.45970154e-01 3.20604056e-01
-5.66023052e-01 1.23066016e-01 1.42203498e+00 8.20799395e-02
-2.31898114e-01 4.68025208e-02 -9.31326687e-01 6.75487101e-01
7.86633611e-01 -6.05750382e-01 -3.05570960e-01 -5.35806835e-01
6.55647993e-01 3.96390945e-01 -3.37074131e-01 -7.66974509e-01
1.42126396e-01 -3.22598010e-01 4.12614465e-01 -5.43547630e-01
-3.09548110e-01 -4.86495614e-01 -1.17138550e-01 4.41613495e-01
-4.85285372e-01 6.44519746e-01 -1.01507954e-01 2.24963665e-01
-2.59059995e-01 -8.70576262e-01 6.66113138e-01 -2.43556082e-01
-2.70383686e-01 3.80450003e-02 -9.97236609e-01 8.37283581e-02
3.36420685e-01 -2.49446273e-01 -4.14747268e-01 -5.77328622e-01
-2.22358152e-01 1.15053944e-01 8.32541943e-01 3.09779853e-01
3.04331154e-01 -1.08199024e+00 -6.80138528e-01 -1.27072319e-01
1.82987869e-01 -6.09807193e-01 -3.08879495e-01 5.56862593e-01
-6.59556210e-01 4.64676231e-01 1.38232604e-01 -2.09749341e-01
-1.14346695e+00 2.50978321e-01 -4.38242815e-02 -2.34253809e-01
-2.77196556e-01 6.03736997e-01 -1.88136429e-01 7.40251318e-02
4.10017669e-01 -2.47359589e-01 -2.26113260e-01 1.67218357e-01
6.53586626e-01 6.30862594e-01 1.71328902e-01 -7.30679750e-01
-2.89069384e-01 2.21110061e-01 -9.70585346e-02 -7.12031841e-01
6.83047533e-01 -5.61189771e-01 -3.28367680e-01 6.61153972e-01
9.75774586e-01 2.88104266e-01 -5.76239049e-01 2.77687442e-02
7.26561397e-02 -4.71803784e-01 1.88880697e-01 -9.36389446e-01
-5.13381958e-01 7.15617895e-01 1.83772832e-01 4.18691158e-01
8.43795776e-01 -2.65205324e-01 6.75295115e-01 6.86793566e-01
2.90305138e-01 -1.68023610e+00 9.19698104e-02 9.79179084e-01
6.26245975e-01 -9.34078991e-01 -4.70596291e-02 -7.84850419e-02
-8.84691834e-01 1.22818005e+00 3.95291656e-01 6.36412024e-01
3.51384372e-01 2.91010618e-01 2.10999817e-01 9.56281349e-02
-8.82886052e-01 -6.36655614e-02 2.23210618e-01 2.00767145e-01
9.95126724e-01 3.61681767e-02 -9.96858776e-01 3.41340780e-01
-5.62834680e-01 -1.61283389e-01 8.78621638e-01 8.09658647e-01
-8.23274791e-01 -8.97049248e-01 -6.02350771e-01 6.50110424e-01
-6.16537094e-01 -1.78319350e-01 -6.01649702e-01 4.40175653e-01
1.27057508e-02 1.63863993e+00 -2.00656373e-02 -1.85374364e-01
3.27264845e-01 2.42002919e-01 3.24726790e-01 -5.44257104e-01
-4.29676473e-01 2.35316202e-01 2.70689875e-01 -4.42592531e-01
-2.06398740e-01 -4.51071233e-01 -1.16114259e+00 -6.79822445e-01
-4.54426914e-01 5.38252652e-01 5.48193336e-01 1.17486072e+00
-4.42514829e-02 2.51020938e-01 6.09624684e-01 2.22078443e-01
-4.34330732e-01 -1.09757662e+00 -9.16476727e-01 3.90354246e-01
5.91116771e-02 -2.40481228e-01 -6.57819331e-01 1.56704634e-01] | [11.594110488891602, 9.461009979248047] |
8c09f9f8-6c7d-4c9a-a9d7-cb6b077f865d | pneumonia-detection-in-chest-radiographs | 1811.08939 | null | http://arxiv.org/abs/1811.08939v1 | http://arxiv.org/pdf/1811.08939v1.pdf | Pneumonia Detection in Chest Radiographs | In this work, we describe our approach to pneumonia classification and
localization in chest radiographs. This method uses only \emph{open-source}
deep learning object detection and is based on CoupleNet, a fully convolutional
network which incorporates global and local features for object detection. Our
approach achieves robustness through critical modifications of the training
process and a novel ensembling algorithm which merges bounding boxes from
several models. We tested our detection algorithm tested on a dataset of 3000
chest radiographs as part of the 2018 RSNA Pneumonia Challenge; our solution
was recognized as a winning entry in a contest which attracted more than 1400
participants worldwide. | ['The DeepRadiology Team'] | 2018-11-21 | null | null | null | null | ['pneumonia-detection'] | ['medical'] | [ 2.86647379e-01 5.84319904e-02 3.76460521e-04 -1.47645846e-01
-1.16074586e+00 -4.58344817e-01 1.69505626e-01 3.49456221e-01
-7.02230692e-01 5.08130789e-01 2.21795321e-01 -5.60692847e-01
2.08129082e-02 -4.43077415e-01 -7.13891625e-01 -3.77113998e-01
-1.63011625e-01 5.86618423e-01 8.43506396e-01 -1.33996666e-03
-1.32855982e-01 7.20225155e-01 -9.47828829e-01 6.06716871e-01
9.46217328e-02 9.02531564e-01 -6.20861016e-02 1.63467991e+00
2.28995249e-01 1.03829980e+00 -5.11313379e-01 -2.57994294e-01
2.88147181e-01 -8.78746063e-02 -1.11266983e+00 -4.95657116e-01
7.80161560e-01 -8.04852843e-01 -4.01683837e-01 4.80330735e-01
1.09107912e+00 -4.30878967e-01 6.20221794e-01 -5.77936172e-01
-2.56750822e-01 3.88215214e-01 -3.72215062e-01 1.24750662e+00
6.49030879e-02 1.86062958e-02 1.10034156e+00 -8.77333641e-01
5.32803357e-01 6.40331745e-01 1.46744812e+00 6.37119412e-01
-8.97892654e-01 -5.49357235e-01 -6.36289418e-01 -3.12483050e-02
-1.47799897e+00 -2.82545954e-01 -8.65397230e-02 -5.06950736e-01
1.23080969e+00 4.44835007e-01 7.13426769e-01 9.71080542e-01
6.58451989e-02 6.58488572e-01 4.31532949e-01 -3.69926631e-01
6.95134029e-02 -1.10491989e-02 1.65400565e-01 1.13821173e+00
4.86334741e-01 -1.82684220e-03 -2.07037032e-01 -9.69006360e-01
1.08324552e+00 4.03088629e-02 -1.66706175e-01 -4.97667998e-01
-1.35162246e+00 8.82704675e-01 6.31495297e-01 2.79075027e-01
-1.31626517e-01 3.18875313e-01 2.93151319e-01 -4.03110832e-01
1.21151701e-01 2.92580336e-01 -2.49085888e-01 7.23470747e-02
-7.94717669e-01 1.59227639e-01 6.59024119e-01 4.05059814e-01
-3.84547524e-02 -6.02969766e-01 -5.34540951e-01 7.60709703e-01
2.77446032e-01 3.87920290e-01 3.46807629e-01 -7.98992038e-01
1.72694609e-01 5.29460728e-01 2.65550893e-02 -6.81075811e-01
-1.02065444e+00 -5.72848558e-01 -5.05135536e-01 -1.34765342e-01
3.11733663e-01 -2.12890446e-01 -1.08232188e+00 1.20783854e+00
4.11221117e-01 4.17137444e-01 -4.36084658e-01 7.23220229e-01
1.32806575e+00 -4.55954410e-02 1.52754530e-01 4.54328895e-01
1.51646733e+00 -9.64270473e-01 -1.50793314e-01 2.31435046e-01
8.42979074e-01 -7.79062152e-01 3.73365760e-01 2.30821028e-01
-1.16521382e+00 -2.62410790e-01 -1.24014592e+00 -3.03369127e-02
-2.75504261e-01 2.13112190e-01 2.48128310e-01 9.22181189e-01
-1.48161054e+00 3.08151662e-01 -9.52140152e-01 -7.40965545e-01
8.83064628e-01 5.78870773e-01 -9.22600105e-02 6.31808117e-02
-1.01331377e+00 1.09183013e+00 2.56869882e-01 -1.58734426e-01
-6.85431480e-01 -7.01407850e-01 -2.06771761e-01 -1.86906263e-01
1.40955791e-01 -1.16581094e+00 1.55255997e+00 -1.19716808e-01
-8.28317285e-01 1.31250751e+00 1.78782448e-01 -8.07824790e-01
5.81678808e-01 -2.05422118e-01 -3.32062572e-01 7.70581007e-01
3.42997489e-03 7.53625453e-01 7.23586321e-01 -4.97507155e-01
-8.10892105e-01 -5.42333350e-02 -1.24539584e-01 -9.28201750e-02
-2.47116789e-01 5.66557765e-01 -3.19841981e-01 -6.97013855e-01
7.36863092e-02 -6.91119671e-01 -4.27190095e-01 2.38429800e-01
-2.31749892e-01 -2.84862429e-01 6.79118574e-01 -5.94179034e-01
9.90384579e-01 -1.71289480e+00 -5.28229475e-01 3.31757516e-01
9.31151211e-01 3.48038703e-01 1.45309329e-01 -6.28881305e-02
-1.28927290e-01 4.41926867e-01 4.43399698e-02 -1.49363503e-01
-3.04500699e-01 -2.02266023e-01 -3.33233085e-03 6.81831598e-01
1.54545888e-01 1.04657316e+00 -8.60437393e-01 -8.91111553e-01
2.12630808e-01 5.85809827e-01 -6.71566486e-01 2.46449843e-01
1.53276116e-01 1.61610693e-01 -4.38748449e-01 6.27876282e-01
5.70122421e-01 -8.76311898e-01 -5.87956384e-02 -1.25102922e-01
7.31535554e-02 5.32539189e-01 -9.47968781e-01 1.69116068e+00
6.14857785e-02 2.60822028e-01 1.72118813e-01 -7.39253700e-01
3.44609380e-01 6.04326189e-01 8.94212067e-01 1.72226548e-01
4.09801304e-01 2.84237385e-01 -1.45699112e-02 -5.04964650e-01
3.27904783e-02 -4.26017307e-02 3.32670122e-01 4.78191614e-01
1.01390496e-01 -1.19353466e-01 -5.27955592e-02 4.47571367e-01
1.99975979e+00 -2.61351734e-01 5.43551922e-01 -2.51671463e-01
4.19216692e-01 1.28634810e-01 9.00769979e-03 1.55300725e+00
-8.00215542e-01 1.23728263e+00 1.44393519e-01 -7.31121898e-01
-1.11386704e+00 -1.44379365e+00 -6.88302875e-01 9.37414646e-01
-4.35866803e-01 -5.01883149e-01 -6.89211071e-01 -1.08405232e+00
-1.67566240e-01 -1.58578455e-01 -7.92819381e-01 7.52361864e-02
-8.40747416e-01 -1.12751460e+00 1.25854146e+00 8.94720137e-01
3.08214515e-01 -1.08450377e+00 -1.17006910e+00 1.31894588e-01
-1.73700228e-01 -8.77484143e-01 -4.37021583e-01 3.16493213e-01
-7.00063944e-01 -1.58017051e+00 -1.09843278e+00 -9.32190776e-01
3.13705266e-01 7.84999430e-02 1.23047876e+00 5.31291664e-01
-1.35607064e+00 5.60970187e-01 -1.95790082e-01 -6.95270598e-01
-3.80324125e-01 2.71164060e-01 -2.47943625e-01 -6.96902752e-01
5.05795836e-01 9.77905244e-02 -9.59905207e-01 3.16068344e-02
-6.70990825e-01 -3.04123789e-01 5.49934208e-01 7.39375889e-01
3.64971638e-01 -3.89240056e-01 4.62831080e-01 -6.69659972e-01
4.01559353e-01 -5.21645248e-01 -3.57471675e-01 1.49971813e-01
-1.44668445e-01 -5.86255550e-01 -2.49186773e-02 1.84154734e-01
-4.09633338e-01 1.99187741e-01 -6.69248879e-01 -1.61451340e-01
-1.75120413e-01 -1.61598891e-01 7.20078766e-01 -4.23006892e-01
9.60381210e-01 -1.17957011e-01 -1.24377832e-01 -3.49897295e-01
2.17931300e-01 8.20791006e-01 6.69241667e-01 -6.03712760e-02
5.31491220e-01 7.80383468e-01 1.03684418e-01 -7.29044616e-01
-9.17962909e-01 -1.20003152e+00 -7.42832482e-01 3.00847162e-02
1.19613540e+00 -8.03894639e-01 -6.09211266e-01 4.14191514e-01
-1.22972202e+00 -6.11400679e-02 -2.07524180e-01 5.05044341e-01
-2.62130588e-01 4.07634437e-01 -7.43785024e-01 -2.72036403e-01
-7.24106312e-01 -8.82712662e-01 1.17173362e+00 -2.77654920e-02
-3.87344658e-01 -7.92613924e-01 7.17516720e-01 4.53893721e-01
6.98567092e-01 8.98820311e-02 5.65820932e-01 -1.05704558e+00
-4.15091515e-01 -5.08689940e-01 -7.46783018e-01 3.50844473e-01
5.60480431e-02 8.63690600e-02 -1.20483875e+00 -4.21240896e-01
-1.18357353e-01 -5.42627990e-01 1.22041583e+00 6.53436899e-01
1.54212344e+00 1.03576697e-01 -7.57413924e-01 4.89599288e-01
1.10089040e+00 -1.71118990e-01 4.31016117e-01 3.48440647e-01
6.20643675e-01 6.26458973e-02 -8.32114816e-02 3.50616515e-01
1.56104758e-01 3.61391127e-01 4.58961159e-01 -5.88606298e-01
-3.83225888e-01 3.12885195e-01 -5.16164660e-01 2.63048679e-01
-6.43508807e-02 -1.39562264e-01 -1.40533245e+00 4.95759040e-01
-1.50417793e+00 -7.94066012e-01 -2.67737299e-01 1.88620317e+00
7.77618587e-01 2.13320106e-01 4.36123192e-01 -2.67292619e-01
7.41222918e-01 1.11147799e-02 -2.22090319e-01 -3.59574668e-02
1.25958502e-01 9.98269618e-01 5.64194024e-01 1.26920953e-01
-1.79054475e+00 3.14495981e-01 8.57905769e+00 6.06691003e-01
-9.18607235e-01 5.56542754e-01 4.57252741e-01 -2.78729767e-01
4.09201682e-01 -6.52971447e-01 -8.30886126e-01 -4.86659557e-02
8.57432365e-01 4.13206905e-01 -2.11028427e-01 7.61483431e-01
-2.56575048e-01 7.08824173e-02 -8.70898187e-01 5.93631625e-01
3.00787628e-01 -1.82826400e+00 -3.20735753e-01 -2.18170688e-01
4.43141967e-01 9.67396915e-01 1.31916087e-02 1.46806598e-01
3.34277153e-01 -1.30592239e+00 2.15944499e-01 2.21445769e-01
6.37497663e-01 -3.81806940e-01 9.76787269e-01 -5.25457561e-02
-1.18414676e+00 1.38726626e-02 -2.21721008e-01 3.53835911e-01
-1.87246025e-01 3.46561313e-01 -1.67741704e+00 9.91477817e-02
1.25477064e+00 4.21375513e-01 -8.53428066e-01 1.59243381e+00
8.19081441e-02 8.62558484e-01 -6.57287240e-01 -1.00736089e-01
8.84416178e-02 7.51787484e-01 7.88001895e-01 1.74306202e+00
-7.55721629e-02 3.20542783e-01 1.88647479e-01 7.99807489e-01
-2.13263631e-01 1.69421688e-01 -3.85537982e-01 3.00536752e-01
1.38729006e-01 1.40888655e+00 -9.33512628e-01 -5.53774178e-01
-3.77140611e-01 4.64651257e-01 3.32532674e-01 -8.39715973e-02
-1.08284903e+00 -2.81113982e-01 7.75745660e-02 1.97674349e-01
6.52901530e-01 2.87794560e-01 -3.68282527e-01 -7.95724213e-01
-3.85518461e-01 -5.46524763e-01 8.77828181e-01 -7.37485707e-01
-1.20505285e+00 4.93936479e-01 -3.06171417e-01 -8.89164925e-01
1.19347274e-01 -8.01836729e-01 -7.54163325e-01 6.88276350e-01
-1.05716014e+00 -9.61050749e-01 -3.44715714e-01 4.59023327e-01
7.37551749e-02 4.35585342e-02 9.34196770e-01 4.42221016e-01
-5.36940813e-01 6.50729239e-01 -1.66874286e-02 3.41352344e-01
7.78248370e-01 -1.37955558e+00 5.34230053e-01 5.26665330e-01
-5.12494668e-02 8.42940807e-01 2.55291700e-01 -6.06132627e-01
-6.21074378e-01 -1.21627867e+00 8.85329783e-01 -9.78847861e-01
6.95069194e-01 -1.83571205e-01 -7.36117840e-01 7.92183757e-01
2.28804983e-02 3.74098122e-01 8.84581864e-01 -1.19936243e-01
-3.19317520e-01 3.59793276e-01 -1.37563121e+00 1.41408443e-01
9.45553780e-01 -2.54322559e-01 -8.17196608e-01 7.59510338e-01
5.87209046e-01 -7.26682544e-01 -7.81128764e-01 9.70898509e-01
7.31530845e-01 -9.76023734e-01 1.40121186e+00 -7.08285809e-01
1.30949989e-01 -1.02845490e-01 8.97888269e-04 -3.71430814e-01
-5.67471743e-01 -2.74021804e-01 -2.06925586e-01 4.37479109e-01
3.49049956e-01 -6.16040111e-01 1.09755385e+00 -1.38403878e-01
-8.93396959e-02 -1.02500319e+00 -1.08340549e+00 -3.61392766e-01
1.53837219e-01 -1.53032690e-01 1.95218369e-01 3.83797526e-01
-2.31997237e-01 -1.33046314e-01 2.04820111e-01 1.32955566e-01
6.36971056e-01 -3.56258482e-01 4.52059239e-01 -9.89661276e-01
-5.59308827e-01 -6.77098334e-01 -3.86426181e-01 -6.94673836e-01
-6.09142900e-01 -1.04183662e+00 3.36943418e-02 -1.65559149e+00
8.46129119e-01 -4.55605119e-01 -8.20116639e-01 6.35747254e-01
-2.09070981e-01 1.07306278e+00 -1.06204078e-01 2.89081991e-01
-9.33055103e-01 -4.15826887e-01 7.22838342e-01 -1.18869610e-01
1.79359838e-01 3.83696884e-01 -4.52792048e-01 8.02805126e-01
8.76767039e-01 -7.04776168e-01 2.67766118e-01 -1.07022241e-01
1.56253666e-01 -4.54004616e-01 8.61829460e-01 -1.30470264e+00
9.25264284e-02 4.26035672e-01 7.86694527e-01 -1.17521632e+00
2.38661990e-01 -4.54736352e-01 -3.36490154e-01 1.02393675e+00
-2.88397968e-01 -1.71626449e-01 3.69455099e-01 4.16188747e-01
4.78177816e-01 -3.14770669e-01 9.98506248e-01 -3.86786222e-01
-2.70690054e-01 1.02078795e-01 -4.95777488e-01 1.39695048e-01
9.49445903e-01 4.16560881e-02 -5.99922776e-01 7.56053403e-02
-7.56672621e-01 1.18153341e-01 1.71406657e-01 1.74216181e-01
3.44381958e-01 -9.23612595e-01 -9.12712038e-01 6.53898939e-02
1.63798317e-01 1.02495566e-01 4.83220397e-03 1.18064857e+00
-1.17367601e+00 9.10111606e-01 1.79812267e-01 -1.18131125e+00
-1.54071724e+00 3.50677490e-01 7.94612467e-01 -4.96761411e-01
-7.72463083e-01 1.41582692e+00 1.11031488e-01 -6.06744289e-01
4.81047839e-01 -3.24427336e-01 -1.83365867e-01 -5.02385318e-01
6.89763606e-01 7.78195500e-01 4.01613057e-01 -2.30718285e-01
-8.36849749e-01 3.03104043e-01 -2.85221934e-01 1.24523975e-01
9.14340675e-01 1.65830880e-01 -2.87242774e-02 9.26713571e-02
1.22247052e+00 -1.78868213e-04 -6.24541879e-01 -8.85396451e-02
-1.06862232e-01 5.14892973e-02 1.81897834e-01 -1.00720358e+00
-6.15127087e-01 6.92127824e-01 1.08785105e+00 1.90033242e-01
6.87863231e-01 3.83318484e-01 9.39956427e-01 4.72866207e-01
-1.00593708e-01 -6.68940187e-01 4.96738791e-01 4.02115881e-01
5.53635299e-01 -1.11946273e+00 2.70830631e-01 -2.76200891e-01
1.07554369e-01 1.15652680e+00 5.33617020e-01 -1.70222148e-01
8.96261454e-01 4.45509940e-01 2.22906068e-01 -5.31338871e-01
-4.57359493e-01 -6.30336329e-02 4.85261172e-01 5.24595201e-01
6.69259012e-01 -8.92258883e-02 -3.16452593e-01 4.27407563e-01
-7.02298572e-03 2.58529246e-01 1.63416237e-01 1.31016278e+00
-8.40217054e-01 -6.59454405e-01 -5.25665760e-01 8.57131362e-01
-9.59251404e-01 -2.22771764e-01 -4.47363228e-01 6.98447645e-01
4.40138251e-01 6.11697793e-01 -1.02548704e-01 1.72151718e-02
1.19461738e-01 -1.16198316e-01 6.22093141e-01 -8.96260619e-01
-8.65098059e-01 5.67955859e-02 -3.24076600e-02 -5.81294000e-01
-2.63474524e-01 -5.49024284e-01 -1.54727948e+00 1.29893392e-01
-4.68151450e-01 -2.23355904e-01 4.57399756e-01 7.49467015e-01
1.52280673e-01 8.41384768e-01 3.18533361e-01 -5.93112350e-01
-7.01870978e-01 -8.91353130e-01 -4.03741241e-01 -9.22428817e-02
5.99927425e-01 -3.82604659e-01 -3.13889772e-01 -2.50837117e-01] | [15.228771209716797, -2.108893394470215] |
eedfc39e-fa3e-4e09-990b-a26bd451d136 | an-attention-driven-two-stage-clustering | null | null | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5955_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123730018.pdf | An Attention-driven Two-stage Clustering Method for Unsupervised Person Re-Identification | The progressive clustering method and its variants, which iteratively generate pseudo labels for unlabeled data and perform feature learning, have shown great process in unsupervised person re-identification (re-id). However, they have an intrinsic problem of modeling the in-camera variability of images successfully, that is, pedestrian features extracted from the same camera tend to be clustered into the same class. This often results in a non-convergent model in the real world application of clustering based re-id models, leading to degenerated performance. In the present study, we propose an attention-driven two-stage clustering (ADTC) method to solve this problem. Specifically, our method consists of two strategies. Firstly, we use an unsupervised attention kernel to shift the learned features from the image background to the pedestrian foreground, which results in more informative clusters. Secondly, to aid the learning of the attention driven clustering model, we separate the clustering process into two stages. We first use kmeans to generate the centroids of clusters (stage 1) and then apply the k-reciprocal Jaccard distance (KRJD) metric to re-assign data points to each cluster (stage 2). By iteratively learning with the two strategies, the attentive regions are gradually shifted from the background to the foreground and the features become more discriminative. Using two benchmark datasets Market1501 and DukeMTMC, we demonstrate that our model outperforms other state-of-the-art unsupervised approaches for person re-id. | ['Xiao Liu', 'Zilong Ji', 'Xiaohan Lin', 'Si Wu', 'Xiaolong Zou', 'Tiejun Huang'] | null | null | null | null | eccv-2020-8 | ['unsupervised-person-re-identification'] | ['computer-vision'] | [ 4.10293788e-02 -3.48215699e-01 1.00665607e-01 -3.61436576e-01
-3.68736863e-01 -3.63763183e-01 6.72331452e-01 -2.37237085e-02
-5.50566971e-01 4.53900516e-01 2.91245878e-01 2.88412571e-01
-2.14869659e-02 -5.41085303e-01 -2.96804041e-01 -1.06314754e+00
3.29883873e-01 6.42167807e-01 3.00232768e-01 3.10292631e-01
2.89850086e-01 3.34546894e-01 -1.69039619e+00 1.41210556e-01
1.02619529e+00 4.07625765e-01 2.17210814e-01 4.91248429e-01
-8.67449418e-02 6.41983449e-01 -5.29926419e-01 -4.36545521e-01
7.36037269e-02 -6.07806683e-01 -9.48123813e-01 6.22398615e-01
1.15907662e-01 -2.55315956e-02 -2.51566261e-01 1.29127991e+00
4.08943176e-01 5.00267029e-01 8.89356017e-01 -1.35390687e+00
-7.17440188e-01 4.18143183e-01 -9.07182157e-01 2.57703125e-01
1.64049685e-01 7.46290833e-02 6.78013861e-01 -1.01586723e+00
3.47580940e-01 1.40883899e+00 5.18092096e-01 8.22116554e-01
-1.33994639e+00 -4.57357556e-01 2.78760701e-01 5.03038764e-01
-1.71587574e+00 -3.47531885e-01 7.98679113e-01 -7.04765320e-01
3.69888008e-01 2.26429746e-01 7.51817822e-01 7.81159401e-01
-3.61406267e-01 7.79136598e-01 1.01110208e+00 -4.80349183e-01
2.06519425e-01 3.73404771e-01 4.21607137e-01 3.37049305e-01
2.30675921e-01 -5.58957048e-02 -6.99994192e-02 1.65518478e-01
5.08556962e-01 3.61468911e-01 -1.07645608e-01 -4.21830893e-01
-1.06314361e+00 6.99349761e-01 4.95264322e-01 4.98135448e-01
-2.59070724e-01 -6.27915636e-02 1.94194704e-01 -1.19743325e-01
3.04413825e-01 2.02575222e-01 3.27352919e-02 2.00475886e-01
-9.84905303e-01 1.49190918e-01 3.27482015e-01 7.92766452e-01
9.27501738e-01 -4.88788426e-01 -2.98721910e-01 8.95176768e-01
4.18030769e-01 2.38777012e-01 8.26687038e-01 -7.74002254e-01
1.70641884e-01 9.19029593e-01 1.45713478e-01 -1.14955950e+00
-2.77360499e-01 -2.95942992e-01 -9.81906652e-01 -2.72625629e-02
5.68650901e-01 -1.53436571e-01 -9.85874176e-01 1.53673792e+00
4.39366132e-01 3.84146899e-01 7.39194974e-02 1.01298285e+00
6.42939508e-01 5.32132447e-01 3.17056388e-01 -1.29665107e-01
1.22672737e+00 -1.18761981e+00 -4.75248814e-01 -1.78476065e-01
4.23182338e-01 -5.04990399e-01 7.74592996e-01 7.25195631e-02
-7.52431810e-01 -1.10851395e+00 -7.69454002e-01 2.89447159e-01
-4.00148541e-01 2.25556448e-01 1.23325527e-01 6.33207798e-01
-9.43886936e-01 4.27878588e-01 -7.39309669e-01 -7.65190661e-01
4.53184128e-01 3.57252479e-01 -2.42337212e-01 -1.79887339e-01
-7.98751116e-01 4.47890460e-01 6.22529387e-01 4.00624312e-02
-7.55167305e-01 -4.03992534e-01 -5.34445405e-01 4.55150381e-02
3.32945198e-01 -4.64533657e-01 7.07059979e-01 -1.36651802e+00
-1.34070265e+00 1.03412986e+00 -4.09585983e-01 -1.77645847e-01
3.87626052e-01 -1.09388888e-01 -4.00015473e-01 3.76523770e-02
3.17924410e-01 8.43840897e-01 8.74337256e-01 -1.75633287e+00
-9.47902083e-01 -3.18184197e-01 -2.48170286e-01 3.02519143e-01
-3.27276021e-01 3.61034535e-02 -9.45802808e-01 -5.36291063e-01
-2.50173360e-02 -1.07591784e+00 -3.52560848e-01 -6.26600862e-01
-5.69188714e-01 -4.58240867e-01 7.86254406e-01 -6.14246845e-01
1.29258502e+00 -2.42747784e+00 3.94935548e-01 4.50403184e-01
3.86619836e-01 4.47171152e-01 1.30045131e-01 -1.96562726e-02
-1.78844288e-01 1.13809094e-01 -1.65331841e-01 -5.59574604e-01
-1.92843691e-01 5.58972582e-02 2.42285326e-01 4.04390544e-01
1.03359960e-01 7.95370996e-01 -1.04399192e+00 -8.53796422e-01
4.74025846e-01 2.26961315e-01 -4.91361469e-01 3.32614571e-01
3.40003580e-01 8.34636986e-01 -2.26612598e-01 4.13227856e-01
6.21454000e-01 -4.40091431e-01 1.44611657e-01 -2.58712381e-01
-1.40995577e-01 -4.57959622e-01 -1.20842946e+00 1.16071784e+00
9.52623412e-02 5.42423368e-01 -2.65667528e-01 -1.16564214e+00
7.30318129e-01 5.82443085e-03 5.76568723e-01 -4.35259223e-01
1.15101643e-01 -2.34331995e-01 1.04110092e-01 -4.16040391e-01
3.46647471e-01 1.47233590e-01 1.10444752e-02 3.38108033e-01
1.56960208e-02 5.49505115e-01 2.97663599e-01 1.60366505e-01
5.54512382e-01 -1.31250069e-01 1.52884260e-01 -3.12013865e-01
9.07815337e-01 3.99981253e-02 6.12892151e-01 8.13749790e-01
-5.33368170e-01 7.41472006e-01 1.95542514e-01 -3.82876217e-01
-1.07597089e+00 -1.06757355e+00 1.13748990e-01 1.08096361e+00
3.96203309e-01 -1.99833259e-01 -1.22456431e+00 -7.88042963e-01
-1.45395070e-01 5.14955282e-01 -7.26921737e-01 -2.67609626e-01
-4.99690264e-01 -1.06838238e+00 1.95032120e-01 5.55773497e-01
7.77720034e-01 -1.02253866e+00 -3.67929518e-01 5.41747846e-02
-3.69459450e-01 -8.19530249e-01 -7.38053858e-01 -2.75978968e-02
-4.91653711e-01 -1.17711461e+00 -9.65453088e-01 -1.04096174e+00
1.12923753e+00 5.56492269e-01 8.86621535e-01 3.58171523e-01
-2.54983574e-01 4.50262100e-01 -6.01993799e-01 -1.46932073e-03
-1.80020615e-01 3.40175815e-02 2.26763740e-01 6.18153572e-01
9.02618945e-01 -1.10536546e-01 -6.69941187e-01 6.29150212e-01
-6.55520916e-01 -6.96545541e-02 4.67116743e-01 8.01789284e-01
5.99014819e-01 4.29552585e-01 4.73659992e-01 -8.55779171e-01
3.60702336e-01 -4.31623310e-01 -3.73193204e-01 2.93792009e-01
-5.97185433e-01 -1.01800449e-01 5.94783306e-01 -6.19183600e-01
-1.07954514e+00 4.10344541e-01 2.14127734e-01 -4.98097062e-01
-5.47662318e-01 1.80299029e-01 -4.53238547e-01 1.26258850e-01
4.52436775e-01 3.87469113e-01 -1.04255959e-01 -3.50924343e-01
3.70039999e-01 8.91295850e-01 7.44068325e-01 -3.67856383e-01
1.00875020e+00 5.13183892e-01 -4.64624375e-01 -8.39331508e-01
-6.90987885e-01 -8.42245519e-01 -1.29659462e+00 -4.31974322e-01
1.36306036e+00 -8.18331897e-01 -5.51664531e-01 6.28280997e-01
-7.56904483e-01 -2.21360847e-01 -2.34281600e-01 4.40486819e-01
-2.93945789e-01 6.83893800e-01 -3.59753788e-01 -8.37481141e-01
-3.37407775e-02 -1.13251364e+00 7.69906998e-01 7.20296919e-01
-1.80892512e-01 -8.57691765e-01 1.30927535e-02 4.18009400e-01
6.45342693e-02 2.49992181e-02 8.05693448e-01 -8.26502919e-01
-3.32304031e-01 -1.58021778e-01 -3.81564409e-01 1.96255505e-01
4.15879935e-01 -8.80972967e-02 -9.23507750e-01 -4.64206338e-01
-3.08981597e-01 5.68103716e-02 8.58179092e-01 3.64979088e-01
1.18715596e+00 -1.89340845e-01 -7.66308188e-01 6.14662826e-01
1.15710342e+00 4.02017921e-01 7.00144947e-01 4.14988816e-01
9.95624363e-01 7.81584263e-01 5.12237966e-01 2.87922114e-01
4.88801599e-01 6.65479481e-01 1.16570368e-02 -2.83505887e-01
-1.44207224e-01 -2.07015485e-01 2.51742482e-01 7.21387327e-01
-3.24898571e-01 -1.00987770e-01 -7.74402022e-01 6.61613584e-01
-1.98472440e+00 -1.07968521e+00 -1.05389588e-01 2.38552642e+00
4.93130088e-01 -5.79301082e-02 6.23536289e-01 1.00948237e-01
1.37150884e+00 -3.09033990e-01 -4.20588881e-01 2.23865956e-01
1.00644797e-01 -3.56518000e-01 3.12876582e-01 3.38120997e-01
-1.39109504e+00 1.09729970e+00 5.79733515e+00 6.96923673e-01
-7.55423009e-01 6.96873367e-02 8.60168636e-01 1.17565781e-01
3.54991436e-01 1.69140883e-02 -8.59830081e-01 9.29743707e-01
6.30747437e-01 -2.87157018e-02 4.89692777e-01 7.15733767e-01
7.36628026e-02 -1.10238791e-01 -1.08338726e+00 1.29426479e+00
1.93405449e-01 -7.51344502e-01 6.63549155e-02 1.01793759e-01
8.47416162e-01 -4.61985886e-01 -6.38441890e-02 1.96179315e-01
4.86919761e-01 -9.51855898e-01 5.70919514e-01 7.13721097e-01
5.14175892e-01 -9.87424791e-01 8.89201283e-01 1.96949631e-01
-1.44339538e+00 -2.80610710e-01 -5.33395171e-01 3.44683468e-01
9.46200266e-02 2.62631267e-01 -6.09698832e-01 4.29842085e-01
1.08085918e+00 7.55091131e-01 -9.77967858e-01 1.23239481e+00
3.56117673e-02 4.17951584e-01 -6.25180360e-03 7.24889114e-02
5.85560128e-02 -4.49670762e-01 4.09968466e-01 1.21352375e+00
1.48427695e-01 1.17744498e-01 4.08151448e-01 8.76435459e-01
1.94228724e-01 3.87640228e-03 -2.00501710e-01 1.89560503e-01
4.68530774e-01 1.24516737e+00 -1.06499231e+00 -5.80666602e-01
-5.07529855e-01 1.40704048e+00 3.59988898e-01 5.28521717e-01
-8.00280452e-01 -2.93831378e-01 3.81472766e-01 1.97893798e-01
4.22020227e-01 -8.09819773e-02 8.25732425e-02 -9.80449855e-01
-3.60043347e-01 -6.93817019e-01 6.49276078e-01 -5.76865435e-01
-1.61818647e+00 4.94035393e-01 1.36775076e-01 -1.14258015e+00
-4.58404385e-02 -3.33372146e-01 -6.57963455e-01 6.86811388e-01
-1.22094989e+00 -1.13808572e+00 -7.56962836e-01 8.42802525e-01
6.05944991e-01 -2.84301281e-01 3.78615707e-01 5.17732739e-01
-9.13217485e-01 7.65088916e-01 3.36067557e-01 6.54806435e-01
8.05541098e-01 -1.36541867e+00 9.22313556e-02 9.73460913e-01
-3.54397250e-03 6.82926774e-01 3.84254366e-01 -7.47431219e-01
-6.74152374e-01 -1.41003883e+00 6.63460255e-01 -4.78506684e-01
2.82668293e-01 -3.09980512e-01 -7.88000524e-01 6.87369704e-01
-1.13255891e-03 -2.10247308e-01 8.66521776e-01 -6.38287738e-02
7.33455122e-02 -1.69710904e-01 -1.02400637e+00 6.84670627e-01
8.35026979e-01 -2.31144190e-01 -5.76502442e-01 1.38697222e-01
4.24904168e-01 1.97779953e-01 -7.21344233e-01 2.54862420e-02
2.88738757e-01 -9.16046858e-01 1.08582497e+00 -4.78572696e-01
3.52343917e-02 -6.89995408e-01 -2.21121013e-02 -1.36243021e+00
-9.78045940e-01 -3.60171080e-01 2.01854974e-01 1.71221626e+00
1.21573173e-01 -3.81910205e-01 7.58098543e-01 5.70558667e-01
1.42254516e-01 -1.72539845e-01 -7.44731426e-01 -4.94928896e-01
-2.97295637e-02 1.58394620e-01 5.84136903e-01 9.79951382e-01
-3.78980003e-02 3.67218792e-01 -3.70134860e-01 2.60971278e-01
9.36994672e-01 -5.57202697e-02 8.86650741e-01 -1.44280386e+00
-1.69067793e-02 -4.71323848e-01 -5.42392969e-01 -9.91337299e-01
5.11180684e-02 -7.62466490e-01 2.06920221e-01 -1.25803876e+00
7.77061999e-01 -5.27930558e-01 -2.65780658e-01 1.89472064e-01
-6.65997207e-01 2.08572283e-01 3.02014232e-01 7.04133391e-01
-9.76655781e-01 4.11552459e-01 7.94146657e-01 -2.45877534e-01
-4.96164441e-01 9.30662155e-02 -7.35607684e-01 6.84205055e-01
6.69197798e-01 -4.45563734e-01 -2.26498589e-01 -1.23426802e-01
-4.68073934e-01 -4.82893318e-01 5.11781931e-01 -1.39736593e+00
5.00115693e-01 -4.34624497e-03 8.81948948e-01 -6.39429986e-01
3.44102979e-02 -9.89993930e-01 1.56451210e-01 4.92035747e-01
-2.50743061e-01 9.31451619e-02 -1.92460522e-01 6.81483090e-01
-6.12485036e-02 -4.14364070e-01 1.09818077e+00 -3.21333259e-01
-7.95797169e-01 2.84484416e-01 -6.39475346e-01 -1.65783372e-02
1.27658081e+00 -4.39389676e-01 4.94623110e-02 -1.74501330e-01
-1.00764191e+00 4.13593650e-01 7.35664368e-01 3.64703774e-01
3.72306138e-01 -1.45784831e+00 -7.19902158e-01 2.83216596e-01
1.26535311e-01 -2.81987172e-02 3.43943685e-01 8.12344313e-01
-2.21683383e-01 2.50339448e-01 -8.21319893e-02 -9.50287700e-01
-1.28739262e+00 1.01410794e+00 4.56815839e-01 -2.65830219e-01
-5.50837517e-01 5.45620382e-01 4.66049671e-01 -3.09461206e-01
2.57209241e-01 2.64655381e-01 -6.97123945e-01 1.80964693e-01
6.25520110e-01 5.58991492e-01 -4.39649016e-01 -1.08158946e+00
-4.13870245e-01 7.89139271e-01 -3.04904938e-01 7.90341794e-02
1.01373363e+00 -5.37002981e-01 -5.90337440e-02 2.68327385e-01
1.04716802e+00 -2.36495972e-01 -1.31676877e+00 -2.92318881e-01
2.10786253e-01 -5.32953620e-01 -2.98623562e-01 -4.61139053e-01
-1.15083659e+00 5.84660530e-01 1.12342548e+00 2.56694168e-01
1.02270818e+00 1.90580502e-01 5.92323363e-01 6.94074929e-02
3.73312756e-02 -1.43297732e+00 3.52735519e-01 2.40453750e-01
1.80365160e-01 -1.27947962e+00 -1.57294184e-01 -3.45599860e-01
-9.18085158e-01 7.81469882e-01 7.88054109e-01 -1.48795232e-01
4.98895317e-01 -1.16438471e-01 3.28668095e-02 -5.83558306e-02
-6.83559151e-03 -5.23347259e-01 2.98896879e-01 1.00948346e+00
1.63769960e-01 6.51612356e-02 2.28779437e-03 7.04754949e-01
1.05048334e-02 -2.07387313e-01 2.33445033e-01 5.76615512e-01
-5.31364799e-01 -8.92101169e-01 -7.09451199e-01 3.92796159e-01
-2.43819833e-01 9.97893587e-02 -5.52940965e-01 6.46676123e-01
3.85110676e-01 1.21320760e+00 3.33348751e-01 -5.73014319e-01
8.88161287e-02 1.09116860e-01 2.82007575e-01 -4.77567315e-01
-4.43712026e-01 2.68748581e-01 -4.21320170e-01 -2.57480055e-01
-7.56950378e-01 -9.48854685e-01 -1.12117982e+00 -2.38640472e-01
-3.71355116e-01 3.44958335e-01 4.07153927e-02 1.02598000e+00
3.02422464e-01 4.74231035e-01 7.41608381e-01 -9.99805987e-01
1.06783314e-02 -8.84959817e-01 -5.00727177e-01 9.80812848e-01
1.47292940e-02 -8.02166283e-01 -3.86614680e-01 4.43305433e-01] | [14.860269546508789, 1.1668992042541504] |
d7997301-a37c-48b7-8569-31848cf2f1fb | can-locational-disparity-of-prosumer-energy | 2207.10248 | null | https://arxiv.org/abs/2207.10248v3 | https://arxiv.org/pdf/2207.10248v3.pdf | Can locational disparity of prosumer energy optimization due to inverter rules be limited? | To mitigate issues related to the growth of variable smart loads and distributed generation, distribution system operators (DSO) now make it binding for prosumers with inverters to operate under pre-set rules. In particular, the maximum active and reactive power set points for prosumers are based on local voltage measurements to ensure that inverter output does not cause voltage violations. However, such actions, as observed in this work, restrict the range available for local energy management, with more adverse losses on arbitrage profits for prosumers located farther away from the substation. The goal of the paper is three-fold: (a) to develop an optimal local energy optimization algorithm for activation of load flexibility and inverter-interfaced solar PV and energy storage under time-varying electricity prices; (b) to quantify the locational impact on prosumer arbitrage gains due to inverter injection rules prevalent in different energy markets; (c) to propose a computationally efficient hybrid inverter control policy which provides voltage regulation while substantially reducing locational disparity. Using numerical simulations on three identical prosumers located at different parts of a radial feeder, we show that our control policy is able to minimize locational disparity in arbitrage gains between customers at the beginning and end of the feeder to 1.4%, while PV curtailment is reduced by 91.7% compared to the base case with restrictive volt-Var and volt-watt policy. | ['Deepjyoti Deka', 'Dirk Van Hertem', 'Ana Bušić', 'Md Umar Hashmi'] | 2022-07-21 | null | null | null | null | ['energy-management'] | ['time-series'] | [-2.47341707e-01 1.77518204e-01 -7.85608739e-02 1.66520223e-01
-3.61951917e-01 -1.39351594e+00 1.95547760e-01 4.72497970e-01
3.84850085e-01 1.18751383e+00 -2.11968288e-01 -5.09957969e-01
-7.09647655e-01 -1.04312861e+00 -1.82154760e-01 -1.00350928e+00
-2.24209622e-01 3.76270562e-01 -4.31936443e-01 -2.88724899e-01
2.44537786e-01 9.10984159e-01 -9.30418193e-01 -3.93790275e-01
1.19750690e+00 1.26049268e+00 -2.66382331e-03 7.24080205e-02
5.30546725e-01 6.87675402e-02 -1.07159281e+00 2.04743475e-01
6.45536304e-01 -4.87584025e-01 1.83834322e-02 -1.08939141e-01
-7.83074260e-01 -5.48061490e-01 2.65528351e-01 1.18980658e+00
7.04497218e-01 2.35477567e-01 7.63063073e-01 -1.59901309e+00
-5.74671865e-01 9.99211669e-01 -7.21651971e-01 3.94826710e-01
9.98210609e-02 3.25413793e-01 1.24865627e+00 -8.41287524e-02
3.65084130e-03 5.83081603e-01 5.65758487e-03 -1.26385212e-01
-1.46750414e+00 -5.09037137e-01 1.69494078e-01 -8.27391595e-02
-1.48230255e+00 6.31436855e-02 8.39600027e-01 -1.42734572e-01
1.24463999e+00 7.03487515e-01 1.19338453e+00 -1.12428199e-02
3.17439288e-01 2.42923111e-01 1.02432108e+00 -5.25304019e-01
5.50015211e-01 7.70989526e-03 -2.46520355e-01 -3.82795602e-01
6.95192754e-01 -1.25454888e-01 3.29887271e-01 -3.03864419e-01
5.24451733e-01 -5.22020400e-01 -7.69282818e-01 -4.93379027e-01
-4.64940518e-01 8.49116087e-01 4.56858784e-01 5.94512701e-01
-5.30763328e-01 -3.83057177e-01 8.13840553e-02 4.32340801e-01
2.82915443e-01 3.94216031e-01 -4.74688321e-01 2.02527329e-01
-7.17162848e-01 1.35254443e-01 9.01460111e-01 9.28184569e-01
4.91922572e-02 6.52356327e-01 1.86632965e-02 4.38551366e-01
3.11084509e-01 7.30784416e-01 2.85584390e-01 -7.97913134e-01
3.31003398e-01 4.21794355e-01 5.19405007e-01 -4.24873650e-01
-2.05604285e-01 -1.14650667e+00 -6.40876591e-01 6.99834287e-01
4.94962096e-01 -6.58469498e-01 -1.88892961e-01 1.55725884e+00
-8.97202864e-02 -5.60210109e-01 -6.50746673e-02 7.10798442e-01
-5.81608653e-01 8.63033056e-01 -3.63678575e-01 -9.00208235e-01
1.34298551e+00 -3.38999242e-01 -7.90651441e-01 3.35837066e-01
5.18409133e-01 -5.72134614e-01 3.61287653e-01 2.13626891e-01
-1.52093065e+00 2.32281297e-01 -1.20480001e+00 6.43451571e-01
-5.36016107e-01 -1.88516945e-01 -2.09239408e-01 7.07338929e-01
-9.90585685e-01 4.48001713e-01 -5.19516349e-01 1.46543520e-04
2.07749531e-01 2.53481299e-01 3.25256884e-01 7.56770909e-01
-1.14557695e+00 1.22326791e+00 4.99141783e-01 4.69743907e-01
-7.74779245e-02 -8.92521679e-01 -5.88994026e-01 9.09427881e-01
5.15040755e-01 -6.48482680e-01 1.19922185e+00 -9.34121072e-01
-1.47208476e+00 -1.57518655e-01 3.45067680e-01 -9.49147940e-01
5.06548226e-01 4.03137565e-01 -4.74016249e-01 -4.14226875e-02
4.84709023e-03 -1.33084923e-01 -2.27155015e-02 -1.15913427e+00
-9.31053877e-01 -3.90640885e-01 -4.51956615e-02 7.23047495e-01
-4.01373859e-03 -4.35948610e-01 9.15347517e-01 -7.16526926e-01
-2.34082371e-01 -5.60444832e-01 -2.73505777e-01 -5.42142034e-01
-3.44199836e-01 -5.19588113e-01 8.90309274e-01 -6.88598096e-01
9.28546846e-01 -1.70100045e+00 4.05259058e-02 7.19719529e-01
-4.31419402e-01 -3.91656272e-02 3.40869993e-01 8.61376524e-01
-4.49659705e-01 9.88900661e-02 -2.41221070e-01 3.13001633e-01
6.27946198e-01 4.82939929e-01 -1.97715536e-01 3.68228108e-01
-1.44162223e-01 6.58677697e-01 -7.15911865e-01 4.28592920e-01
6.00090325e-01 -9.04178917e-02 -1.88328102e-01 -4.15140927e-01
-1.65447041e-01 1.72412336e-01 -2.48764619e-01 6.80337191e-01
7.58045614e-01 6.09651618e-02 5.09577334e-01 -4.12908830e-02
-5.50398707e-01 2.12680232e-02 -1.38089573e+00 9.99511480e-01
-5.49504757e-01 3.48899215e-01 4.53512043e-01 -1.39156795e+00
4.42983538e-01 1.93854451e-01 7.54867315e-01 -8.16637516e-01
3.39808650e-02 3.91177326e-01 2.59858906e-01 1.14960991e-01
-2.08888063e-03 -8.32633302e-02 3.18327583e-02 3.45775276e-01
-1.51343018e-01 -9.72221345e-02 5.38395345e-01 -1.10198073e-01
3.70837212e-01 -4.07615274e-01 4.80447531e-01 -1.00145864e+00
6.45125031e-01 -4.50450152e-01 8.77127826e-01 -7.88546503e-02
8.90757050e-03 -3.42208773e-01 7.41689980e-01 5.08078575e-01
-8.14627826e-01 -1.30055189e+00 -4.24734890e-01 3.03508967e-01
9.31826085e-02 3.08265626e-01 -5.19822478e-01 -2.58757830e-01
5.81105649e-01 1.84119713e+00 5.56076579e-02 2.22066894e-01
-4.03301477e-01 -9.34816062e-01 -3.91894221e-01 3.63709778e-01
2.18791381e-01 -2.34601811e-01 -8.61616313e-01 1.23617962e-01
3.38042200e-01 -5.67619801e-01 -5.17749548e-01 5.57566285e-01
-3.70795548e-01 -8.72164369e-01 -8.83945465e-01 -3.30633700e-01
9.83805716e-01 -2.02160776e-01 6.66506410e-01 -3.32561225e-01
1.50034904e-01 2.13590458e-01 8.95168353e-03 -4.14085269e-01
-1.84251331e-02 9.65396389e-02 -9.60248187e-02 -4.31884497e-01
-1.92977726e-01 -8.53086650e-01 -8.60480666e-01 4.27884907e-01
-6.05192542e-01 -2.20220149e-01 8.85315016e-02 5.92539370e-01
4.02923465e-01 9.43932176e-01 1.38900959e+00 -1.67282850e-01
7.39594162e-01 -6.10110104e-01 -1.56374872e+00 3.34219545e-01
-1.17056561e+00 -3.17640632e-01 9.82312143e-01 2.17198655e-01
-1.11517036e+00 -2.93366760e-01 2.24089161e-01 1.10510640e-01
1.00653365e-01 3.89840007e-01 -6.43416226e-01 -1.92226797e-01
-3.51151317e-01 -8.13502297e-02 -6.08158112e-02 -5.27280986e-01
3.02404374e-01 4.03947830e-01 2.78930008e-01 -2.96988666e-01
1.16229033e+00 6.16094358e-02 3.06943715e-01 -3.76831740e-01
1.07973091e-01 1.22327745e-01 -2.01392725e-01 -1.68894857e-01
3.53479445e-01 -7.91925907e-01 -1.39745522e+00 3.43173474e-01
-4.21218544e-01 -2.87058592e-01 -6.35452509e-01 3.53902251e-01
-4.19034898e-01 4.78671819e-01 -2.64218897e-01 -1.16773951e+00
-4.79110241e-01 -1.00480795e+00 -2.02058838e-03 7.14809716e-01
4.80072424e-02 -1.16685557e+00 -3.72088194e-01 1.73613757e-01
6.32759988e-01 6.98574245e-01 1.07326710e+00 -4.82694715e-01
-8.51331890e-01 3.08087021e-01 1.72643870e-01 6.86689198e-01
5.11791468e-01 5.52780591e-02 -2.83246458e-01 -9.23201621e-01
4.14434224e-02 4.84913528e-01 -2.73905724e-01 6.33052468e-01
5.50007582e-01 -7.22460330e-01 -2.75030851e-01 2.08979756e-01
2.08636880e+00 1.10577333e+00 9.34913084e-02 3.46836805e-01
-3.50121111e-01 4.85815376e-01 4.94219780e-01 6.77388728e-01
3.25054467e-01 7.10904181e-01 6.37696505e-01 2.28187159e-01
7.25419641e-01 5.46207689e-02 1.63300082e-01 3.35164398e-01
1.49397731e-01 -7.71440685e-01 -2.82601744e-01 6.75302029e-01
-1.67426920e+00 -7.91544318e-01 1.55907840e-01 2.36138558e+00
2.52654642e-01 1.77108690e-01 2.64750928e-01 2.63812780e-01
7.78395712e-01 -5.89462519e-02 -5.97064912e-01 -8.33262563e-01
-6.13055766e-01 5.93319386e-02 1.11637747e+00 3.74822199e-01
-1.52279720e-01 -4.75555837e-01 4.68496513e+00 8.14019263e-01
-8.81262720e-01 6.32791221e-02 8.35132003e-01 -5.66865683e-01
-5.47774136e-01 1.83776245e-01 -3.87826353e-01 1.04006350e+00
1.05922151e+00 -1.23573542e+00 6.55841708e-01 4.40263689e-01
8.82881761e-01 -5.62430322e-01 -9.53435302e-01 3.47319543e-01
-5.22827685e-01 -1.14768767e+00 -4.88589495e-01 5.58863640e-01
1.10826802e+00 -1.19428732e-01 -1.77436054e-01 3.61874364e-02
5.96093349e-02 -5.30258656e-01 8.79755497e-01 3.37820768e-01
-3.38388570e-02 -1.56167161e+00 9.16073680e-01 4.55342561e-01
-1.26329732e+00 -5.38645983e-01 1.30277961e-01 -3.93977500e-02
1.08356118e+00 7.35751152e-01 -3.77127618e-01 1.16453338e+00
5.15422523e-01 -1.25939578e-01 1.81346953e-01 1.02739894e+00
-3.11485112e-01 1.79855689e-01 -7.55581796e-01 -6.84800977e-03
1.66679144e-01 -9.80487049e-01 5.51027000e-01 3.71773541e-01
6.02538645e-01 3.89469087e-01 -1.31786354e-02 1.16828263e+00
-5.51344194e-02 -9.90177765e-02 -3.75077009e-01 2.26769909e-01
1.01211071e+00 1.16575253e+00 -7.25619078e-01 -6.90272897e-02
-2.76729017e-01 4.81846094e-01 -6.39480948e-01 6.90387785e-01
-7.17588425e-01 -4.72720414e-01 5.80314219e-01 1.03423066e-01
2.37148851e-01 6.71861917e-02 -8.47228408e-01 -7.61686862e-01
2.35529318e-01 -3.72379065e-01 6.37984991e-01 -7.21235216e-01
-1.39106679e+00 -3.71932447e-01 2.27686256e-01 -8.80128562e-01
-9.31341529e-01 -2.44143918e-01 -1.05164301e+00 1.69847906e+00
-1.82052469e+00 -5.17109752e-01 5.85358977e-01 1.59363344e-01
3.99658799e-01 -1.64034199e-02 4.62996095e-01 4.54863131e-01
-7.84793139e-01 4.39297318e-01 9.31770563e-01 -4.01599221e-02
-4.25616771e-01 -1.49564016e+00 -2.66298771e-01 1.08532119e+00
-4.33688432e-01 2.88340271e-01 7.82219529e-01 -2.77695596e-01
-1.38989770e+00 -3.22898746e-01 5.00000000e-01 5.10619938e-01
8.61579001e-01 -1.27487853e-01 -6.50669336e-01 5.48976958e-01
1.31380916e+00 -6.54342830e-01 5.68842471e-01 -5.80075622e-01
6.33325934e-01 -4.24651980e-01 -1.67161059e+00 6.45427346e-01
2.95050323e-01 -3.14862788e-01 -3.59318107e-01 2.35016406e-01
-1.52953779e-02 -2.04438284e-01 -1.45654809e+00 4.25683677e-01
3.36228758e-01 -4.79110360e-01 7.16904879e-01 2.89278030e-01
-6.10524654e-01 -5.22476375e-01 -1.64297193e-01 -2.00033927e+00
-1.47668645e-01 -1.15924132e+00 -1.86818942e-01 1.44617164e+00
5.49652755e-01 -1.66730773e+00 2.86119580e-01 5.82244217e-01
-1.51499256e-01 -8.04769695e-01 -1.76228547e+00 -9.89285350e-01
5.59203804e-01 4.12670970e-01 9.18509543e-01 9.93839800e-01
5.93351543e-01 2.00536519e-01 4.46636617e-01 7.63181567e-01
9.63418663e-01 3.97296339e-01 -1.11276232e-01 -6.74622536e-01
-2.06170514e-01 -1.03038585e+00 1.87928438e-01 -5.31037629e-01
-1.05787285e-01 -6.10503078e-01 -6.21548295e-01 -1.74189758e+00
-6.09097242e-01 -1.73478872e-01 -5.85767686e-01 3.90946329e-01
5.44993460e-01 -2.57235885e-01 4.13919955e-01 -4.60546166e-02
7.53053606e-01 6.21749461e-01 8.08741868e-01 -1.49187639e-01
-9.79320407e-02 4.05503392e-01 -4.68776911e-01 5.01250863e-01
9.53171253e-01 2.48789340e-01 -9.49836552e-01 2.79373936e-02
2.38185450e-01 5.92335880e-01 8.69278386e-02 -5.67541361e-01
6.36576340e-02 -2.53091335e-01 1.98046252e-01 -1.06346226e+00
-2.23995775e-01 -1.47102869e+00 7.76395500e-01 8.77728522e-01
1.61474839e-01 3.07698697e-01 -7.91992620e-02 3.00965965e-01
1.82245269e-01 -4.38576043e-01 6.62413716e-01 3.85759801e-01
-2.19362214e-01 -3.01050305e-01 -6.47999644e-01 -4.04135525e-01
1.81807232e+00 -1.70747846e-01 -7.39025533e-01 -4.39989269e-01
-7.95455039e-01 1.27618039e+00 7.23944485e-01 2.72975057e-01
-2.91399091e-01 -1.00910008e+00 -4.24696267e-01 2.93520857e-02
-5.11488974e-01 -2.11455077e-01 3.15011680e-01 7.06490457e-01
-3.17865729e-01 8.26344013e-01 -8.69089067e-02 -3.31751227e-01
-7.39196181e-01 4.00186062e-01 9.32284176e-01 -2.08873898e-01
-3.78260106e-01 1.70278683e-01 -2.82560170e-01 3.45104992e-01
-2.01388419e-01 -6.26178682e-01 1.07537314e-01 6.91479564e-01
-6.31224215e-02 7.57137954e-01 2.50226676e-01 -1.12995349e-01
-2.15510562e-01 1.73096031e-01 3.81073952e-01 1.11990320e-02
1.17634141e+00 -4.78560537e-01 4.41918895e-03 1.67446196e-01
7.49001861e-01 8.96078795e-02 -1.14144349e+00 4.92776275e-01
-2.63539553e-01 -2.72441477e-01 3.38816345e-02 -1.30960441e+00
-1.38797343e+00 -3.16029452e-02 4.78705734e-01 1.35507405e+00
1.44827497e+00 -5.48783600e-01 5.69620669e-01 -1.66028574e-01
5.98492682e-01 -1.47476673e+00 -1.03611791e+00 -2.17770785e-01
7.30189562e-01 -2.09220678e-01 -6.41790628e-02 -1.93453744e-01
1.12981326e-03 8.11871052e-01 -3.86891179e-02 -1.34257093e-01
4.99052346e-01 3.45069468e-01 -5.27583003e-01 3.06213140e-01
-5.86379230e-01 1.85537085e-01 -1.66420579e-01 1.96696877e-01
3.37825231e-02 4.54461724e-01 -1.12403190e+00 3.32845539e-01
-3.02714966e-02 -1.74860060e-01 8.70553136e-01 1.06389022e+00
-2.83654094e-01 -9.43763673e-01 -4.11392182e-01 5.03083348e-01
-3.81026417e-01 2.75363445e-01 2.12526709e-01 9.61160362e-01
3.73321861e-01 9.23226416e-01 4.82070565e-01 9.93622363e-01
7.81266749e-01 3.32189761e-02 2.38301829e-01 -1.51929528e-01
-5.48001945e-01 4.24179018e-01 2.74008006e-01 2.35311583e-01
1.79941691e-02 -8.84307027e-01 -1.53064358e+00 -4.82975811e-01
-7.80005991e-01 8.47893894e-01 6.30556643e-01 8.90965521e-01
1.12171821e-01 6.31645918e-01 1.19090748e+00 -5.35531938e-01
-1.09238446e+00 -6.06666386e-01 -1.33866370e+00 -3.13917547e-01
-1.58660397e-01 -4.10351843e-01 -8.33885074e-01 -6.52888894e-01] | [5.66974401473999, 2.5290186405181885] |
70d11641-6b3c-4d95-ae7c-1a0155f4225a | local-shrunk-discriminant-analysis-lsda | 1705.01206 | null | http://arxiv.org/abs/1705.01206v1 | http://arxiv.org/pdf/1705.01206v1.pdf | Local Shrunk Discriminant Analysis (LSDA) | Dimensionality reduction is a crucial step for pattern recognition and data
mining tasks to overcome the curse of dimensionality. Principal component
analysis (PCA) is a traditional technique for unsupervised dimensionality
reduction, which is often employed to seek a projection to best represent the
data in a least-squares sense, but if the original data is nonlinear structure,
the performance of PCA will quickly drop. An supervised dimensionality
reduction algorithm called Linear discriminant analysis (LDA) seeks for an
embedding transformation, which can work well with Gaussian distribution data
or single-modal data, but for non-Gaussian distribution data or multimodal
data, it gives undesired results. What is worse, the dimension of LDA cannot be
more than the number of classes. In order to solve these issues, Local shrunk
discriminant analysis (LSDA) is proposed in this work to process the
non-Gaussian distribution data or multimodal data, which not only incorporate
both the linear and nonlinear structures of original data, but also learn the
pattern shrinking to make the data more flexible to fit the manifold structure.
Further, LSDA has more strong generalization performance, whose objective
function will become local LDA and traditional LDA when different extreme
parameters are utilized respectively. What is more, a new efficient
optimization algorithm is introduced to solve the non-convex objective function
with low computational cost. Compared with other related approaches, such as
PCA, LDA and local LDA, the proposed method can derive a subspace which is more
suitable for non-Gaussian distribution and real data. Promising experimental
results on different kinds of data sets demonstrate the effectiveness of the
proposed approach. | ['Guotai Zhang', 'Hua Zhang', 'Feiping Nie', 'Zan Gao'] | 2017-05-03 | null | null | null | null | ['supervised-dimensionality-reduction'] | ['computer-vision'] | [-2.17034101e-01 -5.41354775e-01 -1.20813839e-01 -1.94886759e-01
-3.01971883e-01 -4.58126903e-01 3.08325469e-01 -1.67402685e-01
-8.62455368e-02 4.08245265e-01 3.76668960e-01 -9.20350924e-02
-4.91677046e-01 -5.88661790e-01 1.17675647e-01 -1.22939074e+00
1.19279206e-01 3.40770304e-01 4.24018763e-02 -7.18462691e-02
2.34233007e-01 7.04130948e-01 -1.41751957e+00 -1.76651955e-01
1.08123899e+00 7.36261666e-01 2.04495683e-01 1.51096322e-02
-3.85436207e-01 9.75997299e-02 -1.15205817e-01 1.38352469e-01
2.28976160e-01 -4.10690993e-01 -1.65139541e-01 4.72776204e-01
-3.48934941e-02 -9.21125412e-02 -4.09226120e-01 1.31293619e+00
4.86460209e-01 2.64323086e-01 1.05176044e+00 -1.27966106e+00
-7.13922322e-01 5.73127232e-02 -8.58684957e-01 1.04696698e-01
4.36482430e-02 -6.33329749e-02 5.36602378e-01 -9.67054546e-01
2.27346346e-01 1.69529951e+00 4.03350741e-01 3.51414412e-01
-1.22400987e+00 -5.63310087e-01 -4.59560864e-02 2.20012218e-01
-1.61720121e+00 -2.08156273e-01 1.35414112e+00 -4.05443043e-01
2.65758574e-01 3.36355954e-01 4.69762415e-01 7.09356666e-01
1.19384691e-01 6.67374074e-01 1.21984661e+00 -3.20616782e-01
2.24337295e-01 2.77588993e-01 3.00812960e-01 2.18140870e-01
3.20683092e-01 -1.65423572e-01 3.92755345e-02 -2.93021739e-01
3.30516666e-01 4.65762675e-01 -3.99285257e-01 -8.58156264e-01
-1.07653713e+00 8.28957140e-01 1.83951125e-01 3.83508384e-01
-4.50798899e-01 -6.12582684e-01 3.24354351e-01 1.39347091e-01
1.62503913e-01 4.22420055e-02 -2.19108313e-01 -1.72659844e-01
-7.14266002e-01 1.64353311e-01 5.96252024e-01 6.60690963e-01
9.83835995e-01 1.30734578e-01 2.23587722e-01 9.29336667e-01
6.59278929e-01 6.60333693e-01 1.04647779e+00 -5.71882069e-01
5.17141044e-01 1.14285147e+00 8.89304373e-03 -1.53273284e+00
-6.06020331e-01 -2.49882072e-01 -1.11125147e+00 2.04117194e-01
2.60984272e-01 -9.15945470e-02 -5.96716404e-01 1.42360890e+00
5.19339383e-01 -9.43656415e-02 3.20228189e-01 1.15443373e+00
6.15576029e-01 8.88117135e-01 -1.11534216e-01 -8.23283970e-01
1.32010734e+00 -4.97341096e-01 -9.87440109e-01 -7.40861446e-02
4.22684252e-01 -9.33678210e-01 1.20448196e+00 4.63821262e-01
-4.48361844e-01 -4.89541948e-01 -9.85616922e-01 1.96101591e-01
-2.46350452e-01 2.71584511e-01 5.17966986e-01 6.20423853e-01
-3.81318927e-01 1.72446012e-01 -7.64868557e-01 -4.86040652e-01
2.03741953e-01 3.06466460e-01 -5.91645658e-01 -2.43297264e-01
-8.79540563e-01 5.99199891e-01 6.53197527e-01 2.82324910e-01
-3.75936955e-01 -2.64088541e-01 -7.60291219e-01 2.83863191e-02
2.37459555e-01 5.32755964e-02 3.20702970e-01 -6.44851029e-01
-1.40658581e+00 3.59920055e-01 -2.67478675e-01 1.77279234e-01
1.20908439e-01 3.46166268e-02 -7.03211963e-01 -8.48862752e-02
-1.98157191e-01 1.07271641e-01 1.03737438e+00 -1.12366903e+00
-2.63825893e-01 -7.81965554e-01 -6.12917125e-01 4.96538550e-01
-9.91087914e-01 -1.73646212e-02 -3.06035221e-01 -4.28830296e-01
7.90843725e-01 -1.10251510e+00 -5.59329689e-02 -3.78599346e-01
-2.99133450e-01 -4.57481593e-01 1.57376730e+00 -6.76031470e-01
1.43622124e+00 -2.63835287e+00 5.31224191e-01 4.64990437e-01
7.19735026e-02 3.38669211e-01 4.80782182e-04 4.46016967e-01
-2.77025998e-01 -8.56800601e-02 -4.45262343e-01 2.32570041e-02
-1.13775395e-01 2.67895609e-01 -1.19689673e-01 6.34367466e-01
4.51378115e-02 3.76640230e-01 -4.97354627e-01 -5.97852051e-01
2.35718071e-01 4.62758511e-01 -3.71392637e-01 8.30951855e-02
2.79222190e-01 4.54434276e-01 -6.99977875e-01 5.95500112e-01
1.09227157e+00 9.28728282e-02 6.20745458e-02 -5.73962450e-01
-1.19896613e-01 -4.74236190e-01 -1.85013127e+00 1.48249638e+00
4.20055389e-02 3.01739722e-01 1.77384660e-01 -1.27434814e+00
1.36551642e+00 1.18731521e-01 5.64866841e-01 -3.14099342e-01
1.55686110e-01 2.68092424e-01 2.01091528e-01 -9.06112015e-01
5.14443107e-02 -1.62985355e-01 7.94549584e-02 2.51565635e-01
-2.89922088e-01 1.41247094e-01 2.00478226e-01 -1.21440999e-01
6.30717456e-01 -6.38259128e-02 1.69060782e-01 -4.76280391e-01
1.10401976e+00 -8.96952003e-02 9.25368845e-01 -1.98194474e-01
-2.97649447e-02 3.04467440e-01 4.98033822e-01 -4.37899858e-01
-1.00736606e+00 -7.77607441e-01 -4.04133797e-01 4.70145464e-01
3.95943582e-01 -2.99070060e-01 -4.86038506e-01 -6.07259274e-01
1.80848129e-02 5.12547314e-01 -9.91741493e-02 -3.80323470e-01
-5.32449782e-01 -1.12716925e+00 -7.73335900e-03 8.54359642e-02
6.49534822e-01 -7.86927521e-01 1.21723920e-01 3.56816128e-02
4.92519401e-02 -6.72410786e-01 -4.54458892e-01 -2.69445479e-01
-1.12745905e+00 -1.09416234e+00 -7.38329828e-01 -9.11309123e-01
9.63866711e-01 4.69712436e-01 4.93419096e-02 -1.89890668e-01
-7.18243793e-02 1.07509576e-01 -3.58243972e-01 -5.71104400e-02
-2.44564041e-01 1.69607978e-02 6.33521676e-01 4.92491484e-01
8.84993553e-01 -7.74713099e-01 -5.01912296e-01 5.11981070e-01
-1.22155797e+00 -2.96710521e-01 7.48355508e-01 8.40919018e-01
6.15674615e-01 9.35633838e-01 5.66773236e-01 -4.24711138e-01
1.10252905e+00 -4.37756836e-01 -4.08448845e-01 1.04290843e-01
-8.38681519e-01 1.13568582e-01 9.27839100e-01 -7.37224281e-01
-9.92940426e-01 1.61019951e-01 2.34268531e-01 -6.18849576e-01
-2.34126195e-01 6.58022344e-01 -6.85175359e-01 -6.74427450e-02
6.10207617e-01 8.31487715e-01 5.20795822e-01 -9.38399613e-01
9.65856537e-02 1.12025738e+00 1.98584363e-01 -4.91906464e-01
9.67179954e-01 3.47356111e-01 3.90351564e-01 -8.68421674e-01
-1.37833074e-01 -6.18333220e-01 -7.56510735e-01 1.07845969e-01
6.75393581e-01 -6.09156907e-01 -5.93350828e-01 4.13441896e-01
-7.44904876e-01 5.79192519e-01 9.76800174e-02 9.51491892e-01
-2.58428186e-01 9.09208357e-01 -1.40180454e-01 -9.74516153e-01
-2.24017471e-01 -1.19199085e+00 6.32968307e-01 4.58115458e-01
1.44898027e-01 -9.25455749e-01 3.70795950e-02 1.10956794e-02
2.49889955e-01 2.14363664e-01 1.16031957e+00 -7.19659567e-01
-4.43445742e-02 -5.54126620e-01 -1.35011375e-01 6.18988454e-01
5.91101289e-01 5.63309109e-03 -4.67547446e-01 -5.22744060e-01
3.94781977e-01 6.32268190e-02 3.24569762e-01 -7.43686855e-02
1.05707037e+00 -4.98562485e-01 -3.62222254e-01 5.68993151e-01
1.34580147e+00 5.19808054e-01 6.78193033e-01 4.08159167e-01
9.02469337e-01 8.28587890e-01 7.59333730e-01 3.59923393e-01
2.22021490e-01 5.66932142e-01 2.93474704e-01 3.26611996e-02
2.11943582e-01 -1.79218769e-01 2.44457230e-01 1.21700728e+00
1.49659425e-01 2.18434736e-01 -9.31461453e-01 2.51941741e-01
-1.87411416e+00 -8.34834158e-01 -3.22707981e-01 2.33591032e+00
6.29519820e-01 -1.50413319e-01 1.63636848e-01 4.76008922e-01
7.98759162e-01 8.72085337e-03 -6.25900805e-01 -2.55592525e-01
-2.78321207e-01 -4.27276701e-01 1.45203173e-01 2.28519052e-01
-1.12488711e+00 6.12602711e-01 5.25913668e+00 1.16137123e+00
-1.28680229e+00 -1.48495153e-01 1.68915316e-01 2.58350998e-01
-3.49328220e-01 1.79542303e-01 -7.20130384e-01 8.65319967e-01
3.46123606e-01 -2.19710231e-01 6.28841460e-01 1.04701138e+00
5.31604767e-01 2.39113644e-01 -7.70995319e-01 1.50356138e+00
1.01546288e-01 -6.01486623e-01 1.49344265e-01 3.89264137e-01
5.80370426e-01 -5.50560534e-01 9.57873762e-02 2.51093030e-01
-4.62933809e-01 -7.32094944e-01 -9.57977846e-02 6.48279130e-01
3.57676804e-01 -9.97400701e-01 7.66774356e-01 7.81799734e-01
-1.00274837e+00 -3.58324617e-01 -7.54585683e-01 7.39565566e-02
-3.80990133e-02 6.19273067e-01 -4.18703437e-01 4.66927379e-01
5.40296733e-01 8.98608744e-01 -6.26631856e-01 1.10660040e+00
5.87227270e-02 3.45385730e-01 -5.88534474e-01 3.75179499e-02
1.81755930e-01 -8.76292169e-01 8.95775318e-01 7.29595780e-01
6.17858112e-01 2.34594703e-01 3.80724847e-01 5.95312059e-01
3.90818954e-01 7.65344620e-01 -6.63841307e-01 -2.94493794e-01
5.11675596e-01 1.40098429e+00 -5.11908591e-01 5.02432697e-03
-3.32722545e-01 7.67732918e-01 1.65160820e-02 5.27163982e-01
-3.26029927e-01 -5.25416553e-01 4.14912671e-01 1.77418232e-01
5.13434075e-02 -4.97376949e-01 -1.53385790e-03 -1.28455865e+00
2.24521846e-01 -1.01382065e+00 4.18920964e-01 -4.14947420e-01
-1.39834797e+00 3.18088204e-01 6.46354184e-02 -1.69327676e+00
-1.21410459e-01 -5.67014635e-01 -7.20110655e-01 9.34807003e-01
-1.24728918e+00 -1.09616613e+00 -3.38776171e-01 7.80381620e-01
2.99009413e-01 -6.41982615e-01 8.13274086e-01 3.92239094e-01
-8.52522254e-01 3.60768557e-01 7.95746267e-01 -1.70543998e-01
7.55035996e-01 -9.41310406e-01 -6.05813861e-01 8.35043669e-01
-2.79803127e-01 8.14990163e-01 7.47508168e-01 -5.81427157e-01
-1.85320127e+00 -6.57461882e-01 4.87690419e-01 4.28280570e-02
4.87676203e-01 -7.10161477e-02 -1.17170465e+00 2.65353888e-01
-2.47518212e-01 -1.28297448e-01 8.29649210e-01 2.04857122e-02
-3.26737650e-02 -5.75130820e-01 -1.23179579e+00 4.73103702e-01
3.53852540e-01 -1.68045223e-01 -6.57848716e-01 3.01324159e-01
4.07170594e-01 -1.15058877e-01 -1.15659583e+00 4.69636589e-01
4.05401200e-01 -7.28494942e-01 8.22055101e-01 -5.74040174e-01
3.12635750e-02 -8.89670491e-01 -1.60320029e-01 -1.23243809e+00
-5.60557187e-01 -4.67100084e-01 -2.52219468e-01 1.54420829e+00
-1.10992163e-01 -7.34324455e-01 7.57640481e-01 6.37184978e-01
5.62088154e-02 -6.41112566e-01 -9.46448982e-01 -9.12991524e-01
-2.23488323e-02 -1.85969402e-03 7.57519543e-01 1.10847676e+00
1.87856391e-01 4.09341365e-01 -4.42025930e-01 2.01263621e-01
8.28451574e-01 1.45845577e-01 9.11354184e-01 -1.46787941e+00
3.70110646e-02 -4.47691560e-01 -7.54639030e-01 -8.19666207e-01
1.32787362e-01 -7.96197832e-01 -2.71507204e-01 -1.29822910e+00
4.70618643e-02 -5.78449309e-01 -2.00921386e-01 2.86055952e-01
-1.96974128e-01 -1.97652385e-01 -2.09877156e-02 9.06062186e-01
-1.71242639e-01 9.01724637e-01 1.33525443e+00 -2.24497929e-01
-7.78659642e-01 -2.14791503e-02 -6.63367033e-01 6.18780971e-01
6.05901361e-01 -3.75109792e-01 -6.59559965e-01 -1.03659444e-01
-8.89421552e-02 -1.12983897e-01 -9.02648047e-02 -8.35405469e-01
2.08931953e-01 -2.34864563e-01 4.09847081e-01 -5.32237828e-01
2.70835996e-01 -1.29686022e+00 3.33315730e-01 2.77624726e-01
1.34222493e-01 -1.61383584e-01 2.92582586e-02 5.77173948e-01
-4.37168926e-01 -3.16938937e-01 6.52694046e-01 2.43881121e-01
-6.84615433e-01 3.83417845e-01 -1.07323036e-01 -3.66185427e-01
1.22386575e+00 -4.20871109e-01 -1.60118312e-01 -2.26989105e-01
-7.99462140e-01 3.68387461e-01 5.24134159e-01 5.25140464e-01
6.96012855e-01 -1.95665014e+00 -7.32676923e-01 4.62519497e-01
2.42094725e-01 5.20798676e-02 4.61510479e-01 1.10919106e+00
-4.92672741e-01 2.92677432e-01 -1.35649756e-01 -7.29645967e-01
-1.08992767e+00 9.37692523e-01 -9.27807018e-03 1.17012806e-01
-6.25221193e-01 1.91511258e-01 1.43422738e-01 -4.88257200e-01
-3.06214150e-02 2.11189583e-01 -7.27082610e-01 2.58690506e-01
6.29283130e-01 5.92684269e-01 -3.33855540e-01 -1.03800058e+00
-3.61450940e-01 9.96169388e-01 -1.17350612e-02 2.04430625e-01
1.27425182e+00 -3.71435285e-01 -5.96763074e-01 2.95222938e-01
1.52624035e+00 8.83194953e-02 -9.39292967e-01 -4.05129194e-01
-6.14560619e-02 -6.04104936e-01 2.36379400e-01 -1.16646759e-01
-8.23605061e-01 9.16075587e-01 9.30816352e-01 4.55366999e-01
1.18991911e+00 -3.51004064e-01 7.34410524e-01 3.96754950e-01
8.97955596e-02 -1.11225045e+00 -7.97514170e-02 1.54358551e-01
9.73365247e-01 -1.31034458e+00 8.63585323e-02 -3.35646123e-01
-7.22359478e-01 1.47291374e+00 6.35466278e-01 -1.42503962e-01
8.39302957e-01 -2.40445614e-01 -2.33121574e-01 -1.75820544e-01
-7.29080196e-03 7.55729824e-02 4.50689763e-01 5.32345593e-01
2.73920465e-02 -9.39034075e-02 -8.34282756e-01 8.46577227e-01
-5.14662042e-02 -3.57348144e-01 1.65576339e-01 6.65416360e-01
-6.02943540e-01 -1.13280439e+00 -8.68084967e-01 3.18014592e-01
-1.13392726e-01 3.20704281e-01 -1.37110829e-01 6.66080534e-01
1.89419344e-01 8.59091699e-01 -4.20949049e-02 -4.34611440e-01
3.34406346e-01 1.69412598e-01 -7.72943273e-02 -3.39877248e-01
3.71054739e-01 5.75906336e-01 -4.42341596e-01 -2.51624584e-01
-3.54450911e-01 -8.35407019e-01 -1.40575433e+00 -2.74425775e-01
-3.28671753e-01 3.27015340e-01 7.22967446e-01 8.45614910e-01
2.43726581e-01 7.44928420e-02 1.04698241e+00 -5.93396246e-01
-6.97936475e-01 -1.00771892e+00 -9.02683437e-01 5.90675056e-01
8.00552592e-02 -6.40676141e-01 -7.05441058e-01 -9.39742476e-02] | [7.911818027496338, 4.262103080749512] |
b6abcc62-f7d8-40ed-84fc-f3c219757ad9 | from-independent-prediction-to-re-ordered | 1906.01230 | null | https://arxiv.org/abs/1906.01230v1 | https://arxiv.org/pdf/1906.01230v1.pdf | From Independent Prediction to Re-ordered Prediction: Integrating Relative Position and Global Label Information to Emotion Cause Identification | Emotion cause identification aims at identifying the potential causes that lead to a certain emotion expression in text. Several techniques including rule based methods and traditional machine learning methods have been proposed to address this problem based on manually designed rules and features. More recently, some deep learning methods have also been applied to this task, with the attempt to automatically capture the causal relationship of emotion and its causes embodied in the text. In this work, we find that in addition to the content of the text, there are another two kinds of information, namely relative position and global labels, that are also very important for emotion cause identification. To integrate such information, we propose a model based on the neural network architecture to encode the three elements ($i.e.$, text content, relative position and global label), in an unified and end-to-end fashion. We introduce a relative position augmented embedding learning algorithm, and transform the task from an independent prediction problem to a reordered prediction problem, where the dynamic global label information is incorporated. Experimental results on a benchmark emotion cause dataset show that our model achieves new state-of-the-art performance and performs significantly better than a number of competitive baselines. Further analysis shows the effectiveness of the relative position augmented embedding learning algorithm and the reordered prediction mechanism with dynamic global labels. | ['Zixiang Ding', 'Rui Xia', 'Huihui He', 'Mengran Zhang'] | 2019-06-04 | null | null | null | null | ['emotion-cause-extraction'] | ['natural-language-processing'] | [ 1.38464928e-01 -8.26263726e-02 -2.82761157e-01 -6.53931022e-01
-3.70554656e-01 -2.78329909e-01 6.10595822e-01 3.55700940e-01
-2.00538948e-01 3.48934710e-01 6.17533982e-01 5.74989170e-02
-3.49756420e-01 -7.39975691e-01 -4.54312414e-01 -6.65631652e-01
-3.17479335e-02 1.95950195e-01 -1.65967658e-01 -3.20780724e-01
2.87362486e-01 -1.69327687e-02 -1.70971847e+00 3.27600092e-01
6.49011672e-01 1.28074157e+00 -1.71744451e-01 3.00497562e-01
-5.80459654e-01 1.34612870e+00 -2.81900048e-01 -4.53926504e-01
-1.41221955e-01 -4.11466718e-01 -7.85627127e-01 -1.67153671e-01
-1.89142376e-02 -1.32733986e-01 -1.11518659e-01 8.58395576e-01
5.18421531e-01 1.37330949e-01 7.17830777e-01 -1.53997064e+00
-6.60625219e-01 7.08916783e-01 -5.85605025e-01 -1.40650347e-02
5.90923429e-01 -3.13297719e-01 1.43684709e+00 -8.56461287e-01
2.95471013e-01 1.38967061e+00 6.11021399e-01 2.62699991e-01
-7.44958103e-01 -6.81619227e-01 4.75069761e-01 6.62065566e-01
-9.89279330e-01 -5.69372848e-02 1.34569180e+00 -5.26762903e-01
1.04795861e+00 1.09404720e-01 4.54130173e-01 1.20481682e+00
4.28950220e-01 8.06957901e-01 1.00862825e+00 -5.31759322e-01
2.41446689e-01 1.80188268e-01 4.89400923e-01 7.41197228e-01
-2.73798347e-01 3.83146782e-03 -5.45419514e-01 -4.01600391e-01
1.98365018e-01 1.87642708e-01 -2.61425525e-01 -3.18539768e-01
-9.02536690e-01 1.05846477e+00 4.83310372e-01 4.77141887e-01
-5.25097966e-01 3.41240615e-01 6.83424473e-01 1.40345944e-02
7.59974301e-01 3.78462344e-01 -9.82373238e-01 -3.10966313e-01
-2.68226385e-01 1.63694724e-01 8.97776961e-01 4.31035668e-01
8.19226027e-01 -1.71219394e-01 -1.73442915e-01 9.22735512e-01
4.13972616e-01 2.32606679e-01 7.49965310e-01 -2.68861085e-01
3.12413484e-01 1.20966446e+00 -1.33750692e-01 -1.73094642e+00
-7.07789421e-01 -3.24482232e-01 -9.00213778e-01 -2.14251578e-01
-8.36980268e-02 -3.57191086e-01 -7.49113142e-01 1.99276590e+00
5.12696922e-01 4.45295691e-01 5.96960671e-02 9.39082682e-01
9.43901956e-01 1.03655076e+00 1.29182845e-01 -2.15733930e-01
1.46460927e+00 -9.39528406e-01 -1.17713630e+00 -1.29081264e-01
7.11503029e-01 -6.60927653e-01 1.12490165e+00 4.61842448e-01
-3.52074891e-01 -4.03728992e-01 -8.15615416e-01 -1.75306723e-01
-7.58385360e-01 2.78263152e-01 8.27392220e-01 3.84277672e-01
-6.68126523e-01 3.47529799e-01 -1.78227603e-01 -1.95264012e-01
-9.45244133e-02 2.99596310e-01 -2.31344849e-01 1.75865054e-01
-1.87801158e+00 6.25430822e-01 4.75478262e-01 2.33744383e-01
-3.26607853e-01 -6.76872373e-01 -1.03022850e+00 2.62937039e-01
5.57382643e-01 -3.63516271e-01 9.56255496e-01 -1.09217119e+00
-1.48877025e+00 4.90721226e-01 -2.80076742e-01 3.05692498e-02
-2.03530714e-01 -4.08694714e-01 -5.77959061e-01 -3.12977135e-02
-3.84610482e-02 2.21925423e-01 8.34476590e-01 -1.37287092e+00
-6.64532721e-01 -4.77388173e-01 -5.32685071e-02 2.12173924e-01
-8.73327911e-01 1.91837788e-01 -4.45245177e-01 -4.59997088e-01
-1.79611817e-01 -7.87264705e-01 -5.79254404e-02 -3.67703080e-01
-3.93189758e-01 -8.12819481e-01 9.90267873e-01 -5.72957695e-01
1.65065205e+00 -2.07140660e+00 3.42377245e-01 2.27838263e-01
4.26433325e-01 2.94265449e-02 -3.46056819e-02 4.74850684e-01
-3.35442930e-01 2.41524145e-01 -1.09422378e-01 -2.22641766e-01
4.08728570e-01 1.78291351e-01 -5.90890229e-01 2.84195766e-02
1.24949224e-01 8.48763824e-01 -9.25777316e-01 -3.66441607e-01
1.10187650e-01 5.32705307e-01 -4.21599478e-01 3.79793346e-01
-1.58025920e-01 2.94038150e-02 -5.28060079e-01 3.35711241e-01
3.25924784e-01 -1.72565579e-01 1.90014601e-01 -3.26266378e-01
8.20978731e-02 2.34547630e-01 -1.11444998e+00 1.36514854e+00
-4.56254750e-01 2.60983407e-01 -2.50665963e-01 -9.91693556e-01
1.26344645e+00 5.95302820e-01 6.48971379e-01 -5.26442349e-01
4.39277649e-01 -6.73845261e-02 -4.52446193e-03 -8.71012747e-01
4.20274109e-01 -3.17177325e-01 -5.07061064e-01 4.89645064e-01
-8.00718069e-02 2.73729175e-01 -7.39382058e-02 1.62853763e-01
1.23771203e+00 -1.45227000e-01 3.68468612e-01 1.60113543e-01
6.39247358e-01 -2.95366645e-01 9.21540558e-01 1.81545392e-01
-3.02855283e-01 1.08912967e-01 9.14477706e-01 -7.10351884e-01
-6.21339262e-01 -3.17412525e-01 1.17432652e-02 1.27800429e+00
2.03877240e-01 -6.38007998e-01 -4.88492399e-01 -9.70718384e-01
5.92917986e-02 6.52353644e-01 -1.13297224e+00 -5.09769022e-01
-3.64169449e-01 -8.20327520e-01 2.74446070e-01 5.55982292e-01
5.58115005e-01 -1.32541919e+00 -4.56594765e-01 3.08379680e-01
-2.81614870e-01 -1.02440453e+00 -1.59592390e-01 4.57757473e-01
-4.13011968e-01 -8.76997232e-01 -1.26797155e-01 -7.74020135e-01
4.03693527e-01 -9.71899629e-02 9.04094815e-01 4.30783480e-02
-1.59526512e-01 4.04532194e-01 -8.38821650e-01 -5.91999292e-01
1.34931490e-01 -2.48296075e-02 9.52911377e-02 5.74311674e-01
5.98028958e-01 -5.27556360e-01 -4.30749655e-01 1.00043960e-01
-1.05090654e+00 -1.86162982e-02 6.46702051e-01 9.00257707e-01
5.37472904e-01 4.11371648e-01 6.54589415e-01 -8.83069992e-01
8.58306289e-01 -7.28298306e-01 7.73955211e-02 1.63995832e-01
-7.70399213e-01 1.37393430e-01 7.53845334e-01 -3.40020895e-01
-1.15144026e+00 1.77789807e-01 -1.78843930e-01 -5.39731145e-01
-3.04357201e-01 1.01322150e+00 -6.20680392e-01 3.70026112e-01
1.88203812e-01 2.29447708e-01 -1.41694307e-01 -4.59693432e-01
5.70168614e-01 6.73894048e-01 1.48892403e-01 -4.00618285e-01
5.39650679e-01 2.60537982e-01 -1.02171935e-01 -3.00353438e-01
-1.03854561e+00 -5.51281929e-01 -5.26053786e-01 -2.13791177e-01
8.52252007e-01 -5.94674468e-01 -5.25369108e-01 3.98797750e-01
-1.36761379e+00 -5.16848937e-02 4.89238650e-02 3.83440435e-01
-3.82531643e-01 1.67104363e-01 -5.68696141e-01 -7.29953051e-01
-4.30448174e-01 -9.19351578e-01 1.20202684e+00 1.32534608e-01
-3.51509243e-01 -1.21052301e+00 2.11120635e-01 1.30342230e-01
1.64354444e-01 3.96639258e-01 1.37833178e+00 -9.09371495e-01
1.17951639e-01 -3.63780975e-01 -2.13469759e-01 4.62221317e-02
3.71938378e-01 -2.89035030e-02 -8.49536598e-01 2.01680481e-01
6.14639930e-02 -3.99990201e-01 8.79702032e-01 5.64357005e-02
1.08347273e+00 -4.75521892e-01 -3.66305381e-01 2.97574162e-01
1.32110119e+00 5.31771898e-01 5.54250419e-01 2.02156812e-01
1.00600195e+00 8.31460118e-01 6.50746882e-01 8.23968828e-01
6.17276728e-01 7.28216231e-01 7.10607708e-01 -2.76539505e-01
2.18190044e-01 -2.74685144e-01 2.98318714e-01 8.36262107e-01
3.10981005e-01 -2.91078866e-01 -8.23454618e-01 3.78590733e-01
-2.14552116e+00 -9.91108179e-01 -3.06559235e-01 1.57597542e+00
9.45731759e-01 -2.74415463e-01 -1.03224784e-01 4.81926054e-01
6.76055551e-01 2.36526951e-01 -4.69733864e-01 -7.99977064e-01
9.11063105e-02 -1.72055215e-01 -2.04922825e-01 4.08663303e-01
-1.27494788e+00 1.05135882e+00 5.69181776e+00 7.87980258e-01
-1.29000771e+00 2.54504494e-02 6.61177456e-01 1.78047821e-01
-4.73495841e-01 -1.50336176e-01 -6.89499736e-01 5.53449929e-01
5.75374305e-01 -5.64260595e-02 1.70982853e-01 8.27856779e-01
3.45582277e-01 2.34131321e-01 -9.93527174e-01 1.06503773e+00
3.36322486e-01 -8.68994594e-01 4.74426560e-02 -3.32790799e-02
5.96080422e-01 -6.53348386e-01 4.92173620e-02 6.23912990e-01
-1.05040222e-02 -7.56518006e-01 5.43392777e-01 5.78263342e-01
4.47402000e-01 -9.73079801e-01 1.03528452e+00 1.46706581e-01
-1.21590889e+00 -3.89269382e-01 -3.25903445e-01 -5.17467678e-01
-2.15618988e-03 9.79394138e-01 -6.79063737e-01 4.89131570e-01
6.49560034e-01 9.64917958e-01 -4.47998226e-01 5.26350796e-01
-7.63789237e-01 7.30095685e-01 -3.24438438e-02 -4.78165537e-01
1.07702918e-01 2.02618018e-01 3.62001866e-01 1.11063242e+00
5.83164394e-02 2.95453608e-01 1.23975895e-01 8.59617412e-01
-1.50751576e-01 5.64106584e-01 -5.00180542e-01 9.40999314e-02
2.28882492e-01 1.54651868e+00 -5.90956092e-01 -2.81195790e-01
-1.46347031e-01 9.55583513e-01 4.68787968e-01 2.08124816e-01
-1.04561317e+00 -6.05323613e-01 6.77335978e-01 -3.33694339e-01
2.63445020e-01 1.51142120e-01 -2.20072135e-01 -1.07205808e+00
1.05196640e-01 -7.68920898e-01 4.01582718e-01 -7.54137814e-01
-1.57511938e+00 6.29320562e-01 -2.15515509e-01 -9.80658770e-01
-2.67444909e-01 -6.07983947e-01 -8.51853013e-01 5.58207273e-01
-1.62236094e+00 -1.11011648e+00 -2.05100760e-01 6.10697865e-01
4.14486229e-01 -7.85829592e-03 1.07484186e+00 2.36502513e-01
-9.29299355e-01 6.02542758e-01 -8.02585557e-02 2.89077997e-01
6.68841958e-01 -1.42981482e+00 -3.55997205e-01 6.45233631e-01
2.02595547e-01 5.01105070e-01 5.95715702e-01 -6.79726243e-01
-1.48152483e+00 -1.04601693e+00 1.31290722e+00 -3.94461185e-01
7.43995667e-01 -4.37594950e-01 -8.10124695e-01 4.17520046e-01
3.02091181e-01 -1.40957579e-01 1.05397928e+00 6.96687043e-01
-5.56087852e-01 -2.54878104e-01 -9.40608025e-01 2.73751348e-01
7.30599463e-01 -2.89371729e-01 -8.10589671e-01 9.86053869e-02
1.00702786e+00 -5.43903075e-02 -6.36243045e-01 5.31481504e-01
5.34736872e-01 -8.07656646e-01 5.43064892e-01 -5.89983523e-01
1.17585945e+00 -1.86650395e-01 -1.13534018e-01 -1.40675426e+00
-6.62905753e-01 -3.58741790e-01 -2.13100493e-01 1.71130741e+00
4.41014498e-01 -3.72458100e-01 4.13118899e-01 8.69307697e-01
-5.80520332e-02 -1.27149987e+00 -8.37806821e-01 -4.07205224e-01
-9.91700664e-02 -6.48565054e-01 6.73074186e-01 1.18949533e+00
4.13432419e-01 8.55865002e-01 -6.57272637e-01 9.99179929e-02
1.01894870e-01 5.02795219e-01 5.59710205e-01 -1.37438452e+00
-1.63464516e-01 -4.84226286e-01 -4.71486419e-01 -7.71928668e-01
5.18522441e-01 -9.66349602e-01 2.00899348e-01 -1.59464252e+00
3.95863950e-01 -3.13437253e-01 -7.20456183e-01 9.44369316e-01
-7.23868668e-01 -1.61938787e-01 8.02847221e-02 8.61915499e-02
-8.14463079e-01 1.03882277e+00 8.36311519e-01 -7.99347609e-02
-3.47190917e-01 -6.09443069e-01 -8.81355107e-01 8.36243689e-01
7.38250792e-01 -5.33615232e-01 -3.87836635e-01 -2.81119972e-01
6.90057695e-01 -2.82743573e-01 3.13745290e-01 -5.55859506e-01
1.09119192e-01 -2.53510773e-01 2.54987091e-01 -3.95166725e-01
1.32139593e-01 -1.06678784e+00 -4.79764044e-01 1.09235875e-01
-5.70645750e-01 -6.68530464e-02 1.74493611e-01 6.55711532e-01
-4.40025270e-01 -1.23006448e-01 1.62407696e-01 4.31865335e-01
-1.05056751e+00 2.83201694e-01 -2.38584280e-01 -2.26620615e-01
9.55467820e-01 2.13820904e-01 -1.04257703e-01 -4.91780728e-01
-3.61235976e-01 2.71019220e-01 -2.50969678e-01 7.64209330e-01
7.69718289e-01 -1.50173450e+00 -4.40526873e-01 -9.90899629e-04
2.73457617e-01 -4.30379212e-01 2.05797642e-01 7.73673773e-01
1.90889403e-01 3.56634885e-01 1.99256659e-01 -1.90554038e-01
-1.22575271e+00 8.41216385e-01 1.10703625e-01 -7.32407689e-01
-3.90098780e-01 9.00061190e-01 2.48901278e-01 -6.18922174e-01
2.58874387e-01 -3.47745448e-01 -7.03202248e-01 4.33228314e-01
5.09853601e-01 1.00770183e-01 -1.01895712e-01 -6.84684873e-01
-3.90670449e-01 9.08059120e-01 -6.11013658e-02 1.14914708e-01
1.37861764e+00 -1.71712324e-01 -3.56570929e-01 7.01769531e-01
1.52556658e+00 1.31803732e-02 -7.47091353e-01 -3.73105705e-01
-6.86403587e-02 -1.43371612e-01 3.69451374e-01 -1.18731999e+00
-1.23639238e+00 9.66281891e-01 5.27531922e-01 3.55437905e-01
1.39570761e+00 2.55477224e-02 9.17868793e-01 1.40798822e-01
1.54353023e-01 -9.81617451e-01 3.34115237e-01 8.10029209e-01
1.04541731e+00 -1.22558439e+00 -3.36002409e-01 -6.04033470e-01
-6.26274824e-01 1.22282255e+00 6.74170971e-01 1.27800489e-02
7.65417397e-01 2.65168667e-01 2.40774184e-01 -4.21641678e-01
-9.91492510e-01 -2.60549515e-01 4.05440420e-01 1.06673233e-01
6.07546508e-01 1.15175126e-02 -6.51004910e-01 1.37056267e+00
-1.05047226e-01 -5.13674766e-02 5.82550652e-02 7.76907921e-01
-3.88748646e-01 -1.20772600e+00 -4.15902525e-01 4.40249979e-01
-5.02125680e-01 -1.57301202e-01 -8.98835599e-01 5.58454633e-01
6.95197225e-01 1.20595694e+00 -4.53422181e-02 -9.20776725e-01
2.69844711e-01 4.03974146e-01 -9.45323333e-02 -4.72654045e-01
-6.22270823e-01 1.16227731e-01 -1.12375885e-01 -5.23473561e-01
-2.63507158e-01 -4.83429968e-01 -1.73434687e+00 1.35822045e-02
-2.86571205e-01 2.18299955e-01 6.19726598e-01 1.08383214e+00
5.47645986e-01 8.34479988e-01 1.04355395e+00 -5.87678254e-01
-2.50031948e-01 -9.27933335e-01 -6.87444627e-01 7.70011187e-01
1.15228117e-01 -7.43919373e-01 -5.88521779e-01 -4.03069369e-02] | [12.627114295959473, 6.215687274932861] |
f4eaa925-4d9e-458c-9c31-bb8af201a7a6 | validation-of-massively-parallel-adaptive | 2305.01334 | null | https://arxiv.org/abs/2305.01334v1 | https://arxiv.org/pdf/2305.01334v1.pdf | Validation of massively-parallel adaptive testing using dynamic control matching | A/B testing is a widely-used paradigm within marketing optimization because it promises identification of causal effects and because it is implemented out of the box in most messaging delivery software platforms. Modern businesses, however, often run many A/B/n tests at the same time and in parallel, and package many content variations into the same messages, not all of which are part of an explicit test. Whether as the result of many teams testing at the same time, or as part of a more sophisticated reinforcement learning (RL) approach that continuously adapts tests and test condition assignment based on previous results, dynamic parallel testing cannot be evaluated the same way traditional A/B tests are evaluated. This paper presents a method for disentangling the causal effects of the various tests under conditions of continuous test adaptation, using a matched-synthetic control group that adapts alongside the tests. | ['Schaun Wheeler'] | 2023-05-02 | null | null | null | null | ['marketing'] | ['miscellaneous'] | [ 4.24482465e-01 -1.96666569e-01 -3.41634363e-01 -4.15344328e-01
-3.87173295e-01 -8.52474570e-01 2.62110591e-01 6.15171194e-01
-4.14306134e-01 7.68857598e-01 -5.50312048e-04 -5.93186438e-01
-5.89334548e-01 -9.57366943e-01 -1.04876757e+00 -5.17208338e-01
-1.59531921e-01 1.09838963e+00 4.29900825e-01 -3.28353882e-01
2.65346527e-01 2.78897494e-01 -1.66940892e+00 4.15471256e-01
6.97565019e-01 4.04876620e-01 6.34785593e-02 9.36422348e-01
4.94679958e-02 4.29554343e-01 -9.96024072e-01 -6.06551707e-01
7.46759400e-02 -8.83208215e-01 -5.74625432e-01 3.37430120e-01
2.31083646e-01 -3.47710162e-01 3.00026536e-01 9.05488908e-01
4.84435350e-01 -1.79148391e-01 -5.86043224e-02 -1.42771542e+00
1.30903840e-01 8.63276899e-01 -3.27385217e-01 -6.56094551e-02
7.89391458e-01 2.97500789e-01 9.83605325e-01 1.26833707e-01
5.85897386e-01 1.21623886e+00 3.66230786e-01 -1.40870273e-01
-1.81484115e+00 -8.37185621e-01 1.55240878e-01 2.37007797e-01
-9.42175269e-01 -6.15569018e-02 3.51139814e-01 -3.58408153e-01
5.85857451e-01 5.95854163e-01 1.12045586e+00 1.30076039e+00
6.73864782e-01 3.22933525e-01 1.27710891e+00 -3.72868925e-01
4.83903676e-01 4.21118736e-01 -1.26279414e-01 3.84785295e-01
3.94294053e-01 4.56869721e-01 -4.14553642e-01 -3.04513305e-01
2.63200492e-01 -2.82176435e-01 8.14121068e-02 -3.57392848e-01
-8.03777874e-01 1.03924394e+00 -2.09772199e-01 1.99118614e-01
-3.50065976e-01 -1.07931495e-01 3.15993309e-01 8.63881171e-01
3.20604071e-02 6.18848860e-01 -8.12352955e-01 -5.34089983e-01
-5.99251091e-01 7.26146638e-01 1.22227705e+00 3.38108689e-01
6.54183149e-01 -2.28692234e-01 -4.20447260e-01 6.11055613e-01
2.60340691e-01 2.82292545e-01 6.52886450e-01 -6.65739417e-01
-2.83257794e-02 7.63797045e-01 1.58627313e-02 -5.19054055e-01
-2.49444827e-01 -4.96767551e-01 5.78101017e-02 3.51140857e-01
4.41894025e-01 -5.56855619e-01 -5.25627434e-01 1.50262523e+00
6.79887712e-01 9.23011750e-02 -4.23413366e-01 5.44694185e-01
-3.07499785e-02 2.95026034e-01 7.89949819e-02 -2.75290489e-01
9.27134275e-01 -4.89877433e-01 -5.60221910e-01 -1.31122306e-01
7.14355052e-01 -9.93654430e-01 9.79621112e-01 9.29063976e-01
-9.58038509e-01 -6.03588641e-01 -1.27066231e+00 7.88611472e-01
-3.96649271e-01 -7.40231872e-01 5.43692648e-01 1.25377965e+00
-9.38477457e-01 8.09255421e-01 -4.04492021e-01 1.33718140e-02
-1.66829884e-01 6.89952075e-01 5.26476540e-02 -2.87436932e-01
-1.09484541e+00 5.09216249e-01 -6.37782067e-02 8.97888932e-03
-9.29859757e-01 -4.80119139e-01 -5.29243529e-01 9.85748023e-02
6.39706731e-01 -2.45698750e-01 1.36558223e+00 -9.93802249e-01
-1.82657278e+00 1.51622146e-01 1.79348037e-01 3.68839167e-02
5.35322905e-01 1.76917427e-04 -6.10001624e-01 -4.30198222e-01
2.56540656e-01 2.13354722e-01 6.98589146e-01 -8.05481970e-01
-7.10898817e-01 -5.56349695e-01 2.71348774e-01 -1.04554288e-01
2.75384128e-01 1.67709291e-01 -1.25234306e-01 -1.50593370e-01
-2.73450673e-01 -9.38138247e-01 -1.99352011e-01 -8.61190438e-01
-3.57169151e-01 -1.88064687e-02 3.08469743e-01 -6.30656958e-01
1.20889342e+00 -2.03211355e+00 2.13512331e-01 8.11588287e-01
-2.53805995e-01 -1.46480680e-01 -2.93433338e-01 7.03262389e-01
-2.26445541e-01 3.24583799e-01 3.83896559e-01 5.22298455e-01
1.99874341e-01 8.95686075e-02 1.65880263e-01 1.44047081e-01
1.31518230e-01 5.41071296e-01 -8.40336025e-01 -1.44085854e-01
-1.77533284e-01 -2.64781564e-01 -7.76323318e-01 5.25664948e-02
-6.91497386e-01 5.67635238e-01 -3.95489663e-01 3.70685577e-01
2.81095982e-01 -6.78755343e-02 7.71998823e-01 4.42261577e-01
-4.55440618e-02 1.48361802e-01 -1.45185363e+00 8.23558629e-01
-7.09725693e-02 2.53124684e-01 -2.14142740e-01 -1.00266683e+00
6.28848732e-01 3.57200623e-01 5.53484201e-01 -1.02709484e+00
2.04868123e-01 1.81079417e-01 9.89815772e-01 -7.51095355e-01
1.98938936e-01 -1.27303777e-02 -1.59794226e-01 7.30870485e-01
-1.14447162e-01 -1.61127165e-01 7.98726499e-01 -2.40651891e-01
1.60004008e+00 3.66615742e-01 8.57392922e-02 2.84766942e-01
2.64418006e-01 1.54075369e-01 7.78344393e-01 1.06733978e+00
-1.32218180e-02 -1.68025002e-01 1.17812741e+00 -1.94205806e-01
-1.02942097e+00 -8.57096314e-01 -1.79140583e-01 1.27192748e+00
-1.59530282e-01 -3.73662829e-01 -5.16096652e-01 -6.34845793e-01
4.45134848e-01 9.06125844e-01 -6.38118804e-01 -2.50489891e-01
-2.20954940e-01 -7.27306902e-01 3.12077463e-01 -3.28459181e-02
1.11687444e-01 -1.00195837e+00 -3.20827603e-01 6.37890995e-01
4.48044956e-01 -5.45839489e-01 -1.69576615e-01 2.98551112e-01
-5.35342634e-01 -1.24908948e+00 3.79948765e-02 -2.40525439e-01
2.55551994e-01 -1.71424806e-01 9.10705626e-01 1.90826312e-01
-1.76214442e-01 2.98571318e-01 -6.89940035e-01 -6.14797354e-01
-9.22845602e-01 -4.03240561e-01 -4.10597354e-01 1.24480769e-01
3.68608952e-01 -3.66432965e-01 -1.21957451e-01 7.87100554e-01
-9.88883078e-01 -3.67050380e-01 8.68959248e-01 7.73086369e-01
1.63042888e-01 4.14585024e-01 6.25677705e-01 -1.12917256e+00
7.97694147e-01 -5.01911759e-01 -9.03890371e-01 4.46435094e-01
-8.36966097e-01 -1.07908726e-01 1.17088892e-01 -9.23398256e-01
-6.13706052e-01 -3.25743884e-01 -1.13485910e-01 1.28952146e-01
-9.63128284e-02 9.09907758e-01 -8.47104266e-02 -5.17474636e-02
6.58802450e-01 -4.59505096e-02 2.96213061e-01 -1.31212706e-02
-1.73293918e-01 4.88870502e-01 -5.28899729e-01 -4.81795996e-01
6.15616858e-01 -3.72705638e-01 -1.11461788e-01 -5.03116965e-01
-3.39247376e-01 -1.57138616e-01 -1.57222748e-01 -5.45641363e-01
8.19130123e-01 -4.34920609e-01 -1.02971840e+00 1.69443086e-01
-5.86982369e-01 -8.60569954e-01 -2.04384804e-01 6.59484327e-01
-2.08440796e-01 -3.09246033e-01 -2.73981273e-01 -4.52871412e-01
6.49607241e-01 -1.67813694e+00 6.20775044e-01 2.99197406e-01
-6.06304407e-01 -6.07050061e-01 3.79258662e-01 6.08682811e-01
2.27893576e-01 2.49333873e-01 1.23256409e+00 -1.07490456e+00
-6.12846792e-01 -8.12941313e-01 5.81320107e-01 2.69824564e-01
2.85958708e-03 2.01198444e-01 -3.87681186e-01 -2.86821097e-01
-5.43739796e-02 -2.00153351e-01 -7.80398026e-02 3.89663696e-01
7.75961459e-01 -2.93873399e-01 1.98707134e-02 -1.09787285e-02
1.07024622e+00 7.55828500e-01 7.54558921e-01 4.84896392e-01
5.69893345e-02 7.20002949e-01 6.32518232e-01 3.56691808e-01
-1.83592830e-02 7.36076355e-01 2.31563747e-01 1.33208290e-01
3.28146338e-01 -4.51217480e-02 6.87155426e-01 5.37292778e-01
4.51068908e-01 -2.20547140e-01 -5.26269436e-01 -6.10288605e-02
-1.62156832e+00 -1.04669344e+00 -1.76699936e-01 2.49269247e+00
9.74577665e-01 6.01959705e-01 4.26680654e-01 2.90943563e-01
8.13820601e-01 -5.34258842e-01 -5.34598947e-01 -9.62030411e-01
1.96919441e-01 6.03615344e-01 4.12047297e-01 5.12587607e-01
-2.99331397e-01 2.59245217e-01 6.65512800e+00 4.71075922e-01
-1.01758039e+00 -4.82589006e-03 7.31777906e-01 -1.45709291e-01
-4.02927607e-01 4.34051871e-01 -7.26691604e-01 5.16898930e-01
1.30984998e+00 -1.77100793e-01 6.18791580e-01 4.56683159e-01
4.23231900e-01 -6.65287077e-01 -1.40079319e+00 3.18842493e-02
-3.75030539e-03 -9.98063684e-01 -2.12371975e-01 4.84199733e-01
6.36826694e-01 -2.89850801e-01 -7.40216896e-02 5.48587263e-01
5.64580977e-01 -7.09714353e-01 7.63575971e-01 1.14907391e-01
8.61888602e-02 -7.43516922e-01 9.17800725e-01 3.43702674e-01
-2.03113034e-01 -4.65091348e-01 -6.72879955e-03 -3.46959114e-01
-1.07055902e-01 4.87052917e-01 -1.25826180e+00 3.17049712e-01
6.65766299e-01 -9.53797400e-02 -7.82906771e-01 1.25297785e+00
-3.06204915e-01 8.38408232e-01 1.67176872e-01 -6.61119282e-01
-6.90178499e-02 -3.97153080e-01 4.96110827e-01 6.00307107e-01
1.38919204e-01 -3.74115586e-01 4.06406581e-01 5.69857836e-01
2.55423605e-01 2.75792718e-01 -2.35499680e-01 -4.06247884e-01
2.05557168e-01 9.66002822e-01 -8.20272982e-01 -2.16919720e-01
-3.93868357e-01 3.67955714e-01 -1.74594179e-01 3.24964702e-01
-8.33831191e-01 -2.45649680e-01 4.68803018e-01 3.88037890e-01
4.37085032e-01 1.63094878e-01 2.94293985e-02 -3.39855373e-01
-2.53539681e-01 -1.63025022e+00 1.12738699e-01 -6.68739140e-01
-1.12009633e+00 -1.01429172e-01 1.46941841e-01 -8.63956869e-01
-4.73154992e-01 -5.59642255e-01 -3.93355846e-01 7.26673543e-01
-8.40447605e-01 -3.08436811e-01 6.22566491e-02 3.36621761e-01
2.84722537e-01 -6.53826892e-02 9.00511742e-01 2.61904925e-01
-7.95854509e-01 3.77742290e-01 5.81614710e-02 -2.18722194e-01
8.32800150e-01 -1.10338581e+00 -2.04701617e-01 6.04176581e-01
-1.66674145e-02 5.19924700e-01 8.45581770e-01 -1.18479967e+00
-1.40230739e+00 -3.45644116e-01 6.30753696e-01 -5.64234257e-02
9.82406974e-01 -4.38379109e-01 -7.41327286e-01 3.87948036e-01
2.33476251e-01 -8.85229170e-01 1.06732965e+00 6.21153653e-01
2.15671957e-01 -5.01448631e-01 -8.14893007e-01 8.40698957e-01
2.88614601e-01 -9.31983739e-02 -1.06349140e-01 5.12856424e-01
8.32156777e-01 -2.89392918e-01 -8.92294824e-01 1.96366742e-01
6.91863775e-01 -1.27112353e+00 3.44884008e-01 -5.45446217e-01
3.88970017e-01 2.76676565e-03 -9.36080515e-03 -1.33699238e+00
-1.75480947e-01 -7.56979048e-01 5.70975959e-01 1.10664892e+00
7.84675181e-01 -8.43643904e-01 6.34889424e-01 6.32405818e-01
1.07624792e-01 -6.84207559e-01 -7.42182136e-01 -6.80303216e-01
-5.39299250e-01 -4.30541128e-01 7.73601592e-01 7.06671178e-01
-1.00793332e-01 4.64221358e-01 1.31367818e-01 1.36639178e-01
2.72179991e-01 -3.04803532e-02 9.97265279e-01 -1.25195360e+00
-1.18270063e+00 -5.83174646e-01 -5.46078205e-01 -1.36418432e-01
-1.48092732e-01 -6.55017018e-01 7.15775043e-02 -8.51116955e-01
7.48335049e-02 -3.41231525e-01 -4.39877771e-02 3.95856768e-01
-3.78203504e-02 -1.13415010e-01 -2.51301169e-01 -3.50439847e-01
-1.37814134e-01 -1.62025243e-01 1.32576954e+00 -2.58065835e-02
-5.48277795e-01 5.38462996e-01 -6.73919320e-01 2.88055688e-01
6.52912080e-01 -7.22428560e-01 -6.06313229e-01 7.48562142e-02
8.49977434e-01 3.61706316e-01 3.04843456e-01 -6.63473666e-01
1.70300245e-01 -4.47374165e-01 6.83518231e-01 -3.41438167e-02
-2.24408820e-01 -6.24161899e-01 6.31700635e-01 7.18598127e-01
-4.10461873e-01 5.55272579e-01 3.31389636e-01 4.92230862e-01
-2.96574514e-02 -6.83907688e-01 1.95624650e-01 1.06130131e-02
-3.41564745e-01 -1.87402382e-01 -5.15403390e-01 -2.71007448e-01
1.12648535e+00 -3.93872768e-01 -3.20856273e-01 -4.07267660e-01
-7.26476610e-01 1.50414839e-01 8.53856653e-02 2.12234408e-01
2.98436224e-01 -8.49728405e-01 -7.63487041e-01 4.60821033e-01
-2.32985064e-01 -6.35435402e-01 1.58491075e-01 1.04449201e+00
-4.96965766e-01 -6.82515651e-02 -3.07802200e-01 -5.14285684e-01
-1.21557844e+00 3.52880776e-01 1.47331436e-03 -4.69425172e-01
-1.89444907e-02 5.75381100e-01 -1.82986066e-01 -2.80642122e-01
1.60183802e-01 1.97031960e-01 -1.68129474e-01 3.31497878e-01
3.30260307e-01 1.23097345e-01 3.24315429e-01 1.75035462e-01
1.03772044e-01 4.82363477e-02 -5.98266013e-02 -6.79673553e-01
1.38581610e+00 2.21695557e-01 -2.56613225e-01 8.35693717e-01
6.64333165e-01 2.69971848e-01 -8.88842821e-01 3.24831456e-01
1.00674622e-01 -7.00312555e-01 -1.65994659e-01 -1.29957020e+00
-5.18859267e-01 6.66764155e-02 5.10462344e-01 6.32935286e-01
8.97582591e-01 -2.40362406e-01 2.16889381e-03 2.41790876e-01
1.59598932e-01 -1.35017002e+00 3.11522454e-01 -6.57423660e-02
8.04471016e-01 -7.43878126e-01 2.62892574e-01 -1.68668166e-01
-4.50940728e-01 7.39328563e-01 4.45599645e-01 9.91068874e-03
3.45312446e-01 3.78280669e-01 -3.15928191e-01 -1.78223494e-02
-9.59243238e-01 -5.74948313e-03 -7.86371678e-02 4.86143231e-01
4.15664941e-01 5.47651015e-02 -5.85464537e-01 -3.73322866e-03
-1.53754145e-01 -8.90514404e-02 6.79133117e-01 1.00596273e+00
-2.73117572e-01 -1.93059230e+00 -5.12466013e-01 8.44985366e-01
-2.07305625e-01 1.76390007e-01 -2.06798330e-01 1.18313444e+00
3.72514457e-01 1.08503735e+00 8.97867903e-02 -6.45669878e-01
6.23113394e-01 4.34616536e-01 6.53003931e-01 -5.94292700e-01
-1.01659846e+00 5.22904575e-01 2.98168540e-01 -5.26857615e-01
-8.20361078e-02 -1.24221766e+00 -8.45942259e-01 -5.42288601e-01
-3.50108594e-01 2.22179979e-01 9.25624847e-01 1.13466907e+00
7.09841922e-02 9.88644361e-01 8.95910621e-01 -4.43804353e-01
-8.43512118e-01 -9.50598121e-01 -6.38841987e-01 4.45172906e-01
-1.31507248e-01 -6.71947122e-01 -2.38622099e-01 -3.74181151e-01] | [4.771016597747803, 2.544118881225586] |
d9f587ea-2e20-4c96-b3ba-bec835ff2b3c | privacy-preserving-adversarial-facial | 2305.05391 | null | https://arxiv.org/abs/2305.05391v1 | https://arxiv.org/pdf/2305.05391v1.pdf | Privacy-preserving Adversarial Facial Features | Face recognition service providers protect face privacy by extracting compact and discriminative facial features (representations) from images, and storing the facial features for real-time recognition. However, such features can still be exploited to recover the appearance of the original face by building a reconstruction network. Although several privacy-preserving methods have been proposed, the enhancement of face privacy protection is at the expense of accuracy degradation. In this paper, we propose an adversarial features-based face privacy protection (AdvFace) approach to generate privacy-preserving adversarial features, which can disrupt the mapping from adversarial features to facial images to defend against reconstruction attacks. To this end, we design a shadow model which simulates the attackers' behavior to capture the mapping function from facial features to images and generate adversarial latent noise to disrupt the mapping. The adversarial features rather than the original features are stored in the server's database to prevent leaked features from exposing facial information. Moreover, the AdvFace requires no changes to the face recognition network and can be implemented as a privacy-enhancing plugin in deployed face recognition systems. Extensive experimental results demonstrate that AdvFace outperforms the state-of-the-art face privacy-preserving methods in defending against reconstruction attacks while maintaining face recognition accuracy. | ['Kui Ren', 'Kaixin Liu', 'Wei Yuan', 'Peng Sun', 'Yan Wang', 'Jiahui Hu', 'Wenwen Zhang', 'Shuaifan Jin', 'He Wang', 'Zhibo Wang'] | 2023-05-08 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Wang_Privacy-Preserving_Adversarial_Facial_Features_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Wang_Privacy-Preserving_Adversarial_Facial_Features_CVPR_2023_paper.pdf | cvpr-2023-1 | ['face-recognition'] | ['computer-vision'] | [ 2.41938144e-01 1.52466938e-01 3.11349273e-01 -7.38643587e-01
-5.62282145e-01 -1.08969975e+00 3.09264898e-01 -6.99138999e-01
-1.30858511e-01 3.39783311e-01 -1.04059726e-01 -1.30676687e-01
2.14490399e-01 -1.03077638e+00 -8.85466874e-01 -1.12418437e+00
-1.27374455e-01 -3.86673123e-01 -2.46923387e-01 4.64566574e-02
-1.04443431e-01 1.22126710e+00 -1.67145383e+00 6.07326329e-01
3.77897412e-01 1.34561789e+00 -6.03263736e-01 2.54645973e-01
1.32641971e-01 4.45038676e-01 -6.33084893e-01 -9.10130799e-01
9.47494090e-01 -9.95357782e-02 -4.42466229e-01 -1.69353083e-01
5.45762241e-01 -9.91344392e-01 -9.67631936e-01 1.29700983e+00
3.48990262e-01 -3.17577183e-01 9.02726594e-03 -1.88214421e+00
-8.42615247e-01 -9.84732583e-02 -3.01532388e-01 -2.71972358e-01
3.79694104e-01 2.95848012e-01 6.38798177e-02 -8.79332900e-01
4.25416201e-01 1.40001714e+00 5.03538191e-01 1.05669105e+00
-8.97473752e-01 -1.36791873e+00 -7.04569295e-02 1.71567291e-01
-1.91467452e+00 -1.09377337e+00 7.28944004e-01 3.88056389e-03
3.32134724e-01 9.19705331e-01 3.40446532e-01 1.04008949e+00
1.42733261e-01 3.81575137e-01 1.07770574e+00 -1.08981557e-01
3.84944677e-02 5.30722857e-01 -3.58738691e-01 7.70602107e-01
3.10480535e-01 4.21273321e-01 -5.59407830e-01 -1.00955451e+00
7.89493859e-01 4.60069865e-01 -5.85587502e-01 -2.23260984e-01
-1.60538048e-01 5.99160373e-01 3.18733484e-01 -2.80848026e-01
-3.77980173e-01 4.58204001e-02 2.64555693e-01 6.50899947e-01
2.59676754e-01 -4.57999766e-01 -2.34404430e-01 5.03670931e-01
-4.08733726e-01 2.22147137e-01 9.14641559e-01 9.43245888e-01
8.43833327e-01 -7.20067099e-02 -1.28303498e-01 3.67841274e-01
6.03154361e-01 6.52692378e-01 2.22574890e-01 -9.20345128e-01
1.29680023e-01 4.68323827e-01 2.53785439e-02 -1.50893688e+00
5.22243917e-01 1.54953599e-01 -6.12462699e-01 4.84465092e-01
1.61294967e-01 -2.44876534e-01 -4.06979173e-01 1.85265636e+00
5.69996476e-01 2.74912626e-01 2.36128435e-01 8.21899772e-01
5.31616211e-01 5.02390087e-01 -8.98454860e-02 -1.51461363e-01
1.38995731e+00 -4.07174796e-01 -7.53517389e-01 2.84917075e-02
2.61603501e-02 -5.49192309e-01 7.13662624e-01 5.87954298e-02
-8.38876426e-01 -2.57432550e-01 -9.66617286e-01 6.61708713e-02
-3.66162091e-01 -1.07322916e-01 5.97161770e-01 1.33380711e+00
-1.19073868e+00 4.11357641e-01 -7.45648861e-01 8.44820812e-02
1.01760566e+00 9.29755032e-01 -1.07635474e+00 -3.10849547e-01
-1.13393521e+00 1.41132429e-01 -2.06549123e-01 3.58297527e-01
-1.21118987e+00 -6.86066985e-01 -8.35403442e-01 3.67098063e-01
1.88593179e-01 -3.53981376e-01 8.27165663e-01 -1.35589790e+00
-1.39952791e+00 9.86127794e-01 -2.07902472e-02 -3.66938740e-01
6.85856640e-01 1.45236850e-01 -8.56324077e-01 2.97827601e-01
-2.20811963e-01 2.58018941e-01 1.28539777e+00 -1.20556545e+00
-2.70397931e-01 -9.96271312e-01 -5.62499054e-02 -2.62760460e-01
-8.30581784e-01 3.48943651e-01 -2.88060337e-01 -4.69168991e-01
-9.42090154e-02 -8.42953146e-01 1.34345621e-01 9.16457832e-01
-2.18964189e-01 3.10419917e-01 1.69278324e+00 -7.94991612e-01
7.16901720e-01 -2.77259803e+00 -7.36186922e-01 5.28334737e-01
1.10621095e-01 5.15352726e-01 -3.52426648e-01 3.45525146e-01
-1.20985784e-01 2.16354683e-01 -3.47011164e-02 -3.44013095e-01
-1.06882982e-01 3.95377696e-01 -7.05439448e-01 1.06447768e+00
1.71503276e-01 7.38772810e-01 -3.03486228e-01 -1.21113129e-01
-6.01048023e-02 1.10221279e+00 -6.06700540e-01 3.80859017e-01
1.94493756e-01 2.89162844e-01 -7.11109161e-01 8.17070305e-01
1.70563853e+00 4.54592317e-01 4.09949243e-01 9.16975215e-02
3.29127371e-01 -1.88764095e-01 -1.17556298e+00 1.09506989e+00
-5.32031246e-02 2.51351476e-01 8.50299895e-01 -4.70481694e-01
9.50254321e-01 5.66517353e-01 2.98403054e-01 -2.43105441e-01
3.12368989e-01 -7.49087855e-02 -3.28707129e-01 -4.43816543e-01
-1.37670949e-01 1.79337859e-01 8.86621401e-02 4.94282305e-01
-1.89592421e-01 6.98471725e-01 -9.59816694e-01 -2.09834009e-01
1.10191774e+00 -1.32434189e-01 -2.17348516e-01 -9.05332938e-02
8.91614735e-01 -7.49797583e-01 8.38947654e-01 4.36197907e-01
-3.82816285e-01 2.08089069e-01 2.61516660e-01 -5.84535837e-01
-4.14185256e-01 -1.04196644e+00 -5.65602519e-02 8.95361125e-01
1.59236416e-02 -4.75055188e-01 -1.13701212e+00 -1.19379711e+00
5.28774619e-01 1.83206886e-01 -6.05592430e-01 -5.21214902e-01
-4.96336073e-01 1.81829312e-03 1.23948359e+00 1.49333209e-01
9.30049181e-01 -7.21662998e-01 -1.73522070e-01 -3.06260020e-01
1.21644743e-01 -7.94579566e-01 -6.96739078e-01 -5.66092849e-01
-4.04942423e-01 -1.26283121e+00 -1.60477221e-01 -7.02146411e-01
1.19420135e+00 5.55543840e-01 2.53296256e-01 4.10558164e-01
-5.38310707e-01 5.33610642e-01 1.31156683e-01 -5.05327582e-01
-4.79099870e-01 -6.34467244e-01 2.16903418e-01 8.92518640e-01
4.55782890e-01 -6.74226403e-01 -7.51323044e-01 3.25568289e-01
-1.31670439e+00 -7.88083911e-01 9.02950168e-02 6.62515759e-01
4.20879215e-01 2.88540274e-01 2.41106182e-01 -1.01264083e+00
4.75059986e-01 -4.65290666e-01 -7.02880263e-01 2.30948925e-01
-4.68088806e-01 -3.31380934e-01 9.66674745e-01 -4.67988580e-01
-1.13203335e+00 4.59474534e-01 -2.70176709e-01 -9.03964221e-01
-2.73801833e-01 -2.81322211e-01 -1.07353103e+00 -9.42411423e-01
3.01197708e-01 6.03214622e-01 6.92464292e-01 -5.36710143e-01
4.17078674e-01 9.89256024e-01 6.17879689e-01 -3.38302642e-01
1.05744743e+00 8.66172314e-01 1.23905115e-01 -4.18319374e-01
-1.03744388e-01 6.40371144e-02 -1.00891389e-01 -1.59107640e-01
1.69719145e-01 -9.59680676e-01 -1.33511782e+00 6.96467221e-01
-1.00773156e+00 6.56441689e-01 -9.47478339e-02 -7.95333385e-02
-4.74409848e-01 5.28657675e-01 -4.61479217e-01 -8.63851070e-01
-5.39986551e-01 -1.04857624e+00 8.20295274e-01 3.43901873e-01
4.90877390e-01 -3.81401032e-01 -3.99704814e-01 2.64645904e-01
6.90154374e-01 5.48878253e-01 4.66630816e-01 -6.10309958e-01
-8.37125838e-01 -8.59102309e-01 -1.67841557e-02 6.65226400e-01
4.83370543e-01 -7.11333677e-02 -1.37950909e+00 -7.00282991e-01
6.73968375e-01 -1.02866299e-01 2.67194062e-01 -1.24421358e-01
1.75369740e+00 -1.32519495e+00 -3.30480009e-01 1.15369058e+00
1.30737567e+00 2.35413298e-01 1.10559809e+00 -7.63059184e-02
4.14788306e-01 8.25804710e-01 2.47348502e-01 7.37526238e-01
6.49537146e-02 3.89437914e-01 7.85525858e-01 -3.73863243e-02
3.85999262e-01 -5.34413099e-01 6.14534020e-01 -1.46187454e-01
3.88418198e-01 6.49322420e-02 -1.67853609e-01 -2.51933467e-02
-1.61619961e+00 -1.13693070e+00 4.02002513e-01 2.30342388e+00
7.06902266e-01 -6.47839308e-01 -9.22852382e-02 -2.43708596e-01
7.48359919e-01 1.29512131e-01 -7.40436435e-01 -3.61975878e-01
5.80291227e-02 1.44764051e-01 6.42483830e-01 2.38647699e-01
-9.48457479e-01 9.42863584e-01 5.48542023e+00 5.62883556e-01
-1.32219958e+00 3.31612796e-01 6.91713452e-01 -2.57258892e-01
-2.23555356e-01 1.13364175e-01 -6.09855890e-01 4.81847823e-01
8.52067769e-01 -3.90302360e-01 8.28414738e-01 1.30633307e+00
-1.17934626e-02 8.09459090e-01 -9.46136951e-01 1.14372933e+00
1.18985660e-01 -1.22648013e+00 1.49084866e-01 4.94035691e-01
4.38854098e-02 -5.30775785e-01 3.70165110e-01 -1.38478195e-02
2.12907404e-01 -1.03381109e+00 3.83275807e-01 6.12862349e-01
1.09945405e+00 -1.24697137e+00 3.58486444e-01 2.95540124e-01
-9.99962866e-01 -2.57274985e-01 -7.42005348e-01 2.87513852e-01
-3.35342407e-01 9.86233428e-02 -5.89691162e-01 4.36481833e-01
8.86879444e-01 4.43037674e-02 -2.96868473e-01 3.02295357e-01
-5.32034449e-02 5.21519363e-01 -4.95158970e-01 3.77451390e-01
-9.26693454e-02 -2.31749564e-02 3.65582645e-01 7.52612948e-01
2.70843267e-01 3.71038049e-01 -7.44111016e-02 1.13482583e+00
-7.33487189e-01 1.07328601e-01 -1.18769670e+00 -7.58133365e-06
8.68696511e-01 1.27257645e+00 7.98155367e-02 2.13622004e-01
-3.26991677e-01 1.42467391e+00 1.11724265e-01 1.75487980e-01
-7.76891232e-01 -4.08370793e-01 1.47172868e+00 3.12606096e-01
1.82776421e-01 1.50815845e-01 2.39977300e-01 -9.95436549e-01
4.48682755e-01 -9.93088245e-01 3.57676893e-01 -2.24301144e-01
-1.33025658e+00 7.11452305e-01 -5.54140687e-01 -9.60615695e-01
-2.95986068e-02 -2.30345130e-01 -5.67119598e-01 1.17259169e+00
-1.40933681e+00 -1.40259683e+00 -2.54692137e-01 1.42419207e+00
-1.35761872e-01 -4.66884077e-01 1.22561586e+00 1.95137024e-01
-4.68852222e-01 1.30808675e+00 1.13452658e-01 4.71337348e-01
4.94814724e-01 -2.47586146e-01 4.09159124e-01 8.43033731e-01
-1.67571053e-01 1.03491914e+00 1.66841075e-01 -6.09602749e-01
-2.15616465e+00 -1.46511006e+00 4.88893300e-01 -1.39441296e-01
-2.28583254e-02 -7.84197927e-01 -1.07620049e+00 8.02648127e-01
-6.47431687e-02 8.98619235e-01 1.21834207e+00 -7.39082098e-01
-1.00911403e+00 -5.21478415e-01 -2.24857473e+00 4.40455198e-01
9.22651529e-01 -1.07783687e+00 2.28059903e-01 3.55328530e-01
6.38440132e-01 8.84498209e-02 -7.13041127e-01 1.39488727e-01
9.30998802e-01 -8.89231682e-01 9.86037791e-01 -7.75020063e-01
-2.64026612e-01 -3.11057478e-01 -4.51665580e-01 -5.39978504e-01
-1.45882741e-01 -1.14298153e+00 -1.56966224e-01 1.71494734e+00
-1.52394190e-01 -1.21725595e+00 1.05743897e+00 1.19908404e+00
6.56584263e-01 -2.43748635e-01 -1.42831361e+00 -8.47278953e-01
-1.14921920e-01 2.94305552e-02 1.40340841e+00 9.69238281e-01
-3.93409431e-01 -8.04414392e-01 -5.30385792e-01 8.26229930e-01
8.61943841e-01 -3.14267784e-01 8.57036412e-01 -8.74398589e-01
1.87713522e-02 2.65124023e-01 -6.98186934e-01 -4.36412960e-01
6.75037801e-01 -7.99227118e-01 -1.72714233e-01 -4.05451119e-01
4.96969782e-02 -3.27544928e-01 -3.71305346e-01 8.71197104e-01
2.57740974e-01 1.81695074e-01 1.18750788e-01 3.35947394e-01
2.39490435e-01 6.52942836e-01 8.00175488e-01 -1.18690073e-01
2.11743683e-01 2.70355523e-01 -1.10599899e+00 3.98270667e-01
6.68656051e-01 -7.76352763e-01 -5.27765095e-01 -2.13793099e-01
-6.36779845e-01 2.06968680e-01 6.39394641e-01 -7.26089656e-01
3.73402894e-01 -2.65694320e-01 5.31465888e-01 5.30525064e-03
3.05038691e-01 -1.57602108e+00 5.55934489e-01 4.84775960e-01
-1.55320868e-01 4.71355319e-02 2.37648487e-01 6.02866530e-01
-7.53747821e-02 1.09804176e-01 8.92194808e-01 -7.87698478e-02
-2.00085372e-01 7.92665422e-01 -6.53754249e-02 -6.76007211e-01
1.43250239e+00 -3.70719790e-01 -4.13121581e-01 -3.05846721e-01
-6.51392043e-01 -1.56527966e-01 8.13152432e-01 4.86494511e-01
9.99980748e-01 -1.32485664e+00 -6.94895029e-01 1.18181837e+00
-3.35927457e-02 -4.65694129e-01 4.23956215e-01 -7.19654113e-02
-4.85344559e-01 -4.63577211e-02 -3.99937302e-01 -1.39206033e-02
-1.82459915e+00 8.58712196e-01 5.40859640e-01 4.53736603e-01
-5.76383948e-01 7.47902870e-01 3.22645962e-01 -4.51251775e-01
4.04085904e-01 6.67212188e-01 3.84006232e-01 -4.83862460e-01
1.13656318e+00 2.01000616e-01 8.34837481e-02 -7.80529976e-01
-5.53147495e-01 1.43403336e-01 -3.10724795e-01 2.00507537e-01
1.17899823e+00 -4.00826871e-01 -5.01687407e-01 -7.86443949e-01
1.63557649e+00 3.07322323e-01 -1.36823261e+00 -1.79009572e-01
-4.79339540e-01 -1.33702898e+00 -7.92643279e-02 -5.12778401e-01
-1.68907988e+00 4.33208793e-01 1.04757631e+00 9.74092856e-02
1.45324218e+00 -3.71035904e-01 7.25709021e-01 1.45889431e-01
7.21357465e-01 -5.70751905e-01 -5.82203329e-01 -2.46547237e-01
9.90557551e-01 -8.47411513e-01 -4.05783147e-01 -9.67451394e-01
-3.74763578e-01 1.09085715e+00 6.14728451e-01 -1.92406893e-01
1.12647808e+00 5.89231610e-01 1.35166615e-01 1.85755081e-02
-6.27933323e-01 6.58583105e-01 -1.78089350e-01 1.01810765e+00
-3.80724728e-01 -1.59591511e-02 1.57950819e-01 9.37960088e-01
-5.60800619e-02 1.10738896e-01 1.31098807e-01 1.22911596e+00
6.29247427e-02 -1.41610122e+00 -5.34761131e-01 1.06750280e-01
-7.89430737e-01 1.86349377e-01 -7.06962109e-01 3.79787982e-01
2.55424172e-01 8.94166172e-01 -1.20265558e-01 -5.33517957e-01
3.43164027e-01 1.12028264e-01 1.96130529e-01 -2.39615366e-01
-9.32007372e-01 -3.05845350e-01 -3.43690544e-01 -1.02996850e+00
7.53336474e-02 -6.56276643e-01 -9.40180957e-01 -9.61231470e-01
-1.51057020e-01 9.50926393e-02 7.81883121e-01 3.79716188e-01
1.01801360e+00 -1.48021623e-01 1.61626565e+00 -3.07465285e-01
-9.48804080e-01 -1.93048224e-01 -9.06804979e-01 3.86447102e-01
4.83633399e-01 -1.79760024e-01 -4.53452915e-01 5.37238307e-02] | [12.815507888793945, 0.9517271518707275] |
2198132b-5853-42a7-9649-ce0664b15bf8 | unsupervised-monocular-depth-reconstruction | 2012.15680 | null | https://arxiv.org/abs/2012.15680v3 | https://arxiv.org/pdf/2012.15680v3.pdf | Unsupervised Monocular Depth Reconstruction of Non-Rigid Scenes | Monocular depth reconstruction of complex and dynamic scenes is a highly challenging problem. While for rigid scenes learning-based methods have been offering promising results even in unsupervised cases, there exists little to no literature addressing the same for dynamic and deformable scenes. In this work, we present an unsupervised monocular framework for dense depth estimation of dynamic scenes, which jointly reconstructs rigid and non-rigid parts without explicitly modelling the camera motion. Using dense correspondences, we derive a training objective that aims to opportunistically preserve pairwise distances between reconstructed 3D points. In this process, the dense depth map is learned implicitly using the as-rigid-as-possible hypothesis. Our method provides promising results, demonstrating its capability of reconstructing 3D from challenging videos of non-rigid scenes. Furthermore, the proposed method also provides unsupervised motion segmentation results as an auxiliary output. | ['Luc van Gool', 'Martin R. Oswald', 'Ajad Chhatkuli', 'Thomas Probst', 'Danda Pani Paudel', 'Ayça Takmaz'] | 2020-12-31 | null | null | null | null | ['motion-segmentation'] | ['computer-vision'] | [ 1.93843886e-01 7.30517581e-02 -3.80637459e-02 -3.66991758e-01
-4.83542293e-01 -6.66029751e-01 4.75719422e-01 -6.28466070e-01
-2.88845748e-01 6.30898178e-01 2.57369101e-01 1.56807318e-01
-2.10108254e-02 -6.11281753e-01 -6.73139989e-01 -8.65813315e-01
3.82216752e-01 9.00490224e-01 3.71107727e-01 3.35164249e-01
2.44470432e-01 7.93797910e-01 -1.46601272e+00 3.35820280e-02
5.02686799e-01 4.44352567e-01 5.02012134e-01 7.71871746e-01
1.19938388e-01 7.01552749e-01 1.49199516e-01 -1.78252414e-01
6.06262565e-01 -2.87376076e-01 -9.85659599e-01 6.83732569e-01
6.76185310e-01 -8.21034372e-01 -6.42297924e-01 8.72746587e-01
2.80826122e-01 2.78849691e-01 4.37802225e-01 -6.10042393e-01
8.25689659e-02 1.38075585e-02 -5.05653977e-01 -2.79555656e-02
8.37882578e-01 1.29340917e-01 7.86115706e-01 -8.44144940e-01
1.21681154e+00 1.12994468e+00 3.06356698e-01 6.55604482e-01
-1.38817489e+00 -1.94518715e-01 1.62730321e-01 1.70021564e-01
-1.26954317e+00 -5.99321485e-01 9.93426919e-01 -5.40032387e-01
9.32246149e-01 1.58023849e-01 7.68980682e-01 9.90103543e-01
9.58681181e-02 8.37848485e-01 1.02994180e+00 -3.34286869e-01
2.05173343e-01 -2.03789070e-01 -2.13033438e-01 6.21871352e-01
7.37074614e-02 2.27109432e-01 -5.91203153e-01 1.42115459e-01
1.14512086e+00 1.63800463e-01 -4.75763679e-01 -8.38445723e-01
-1.23341429e+00 4.52030748e-01 2.78249290e-02 2.41541237e-01
-3.26920301e-01 2.04875708e-01 -1.09444536e-01 1.29566520e-01
4.68164980e-01 4.28242385e-02 -3.53484362e-01 -2.60834992e-01
-1.07996082e+00 3.27796131e-01 8.26172113e-01 9.65107143e-01
9.45351243e-01 8.22939426e-02 4.48157966e-01 4.99450803e-01
3.53206217e-01 3.96769643e-01 1.61898762e-01 -1.51126397e+00
2.40123615e-01 3.72372001e-01 1.55045047e-01 -1.01695669e+00
-3.32959145e-01 -3.39442454e-02 -6.53776169e-01 3.08287531e-01
4.60040271e-01 2.50941664e-01 -8.90609980e-01 1.51823556e+00
7.60475755e-01 2.96857655e-01 -7.78132007e-02 1.15724635e+00
6.59847438e-01 4.17693108e-01 -5.63032806e-01 -4.07873958e-01
6.28093600e-01 -9.99627709e-01 -7.28054464e-01 -2.74203867e-01
1.53105959e-01 -8.92476022e-01 5.40360868e-01 4.86872882e-01
-1.44353747e+00 -3.64931107e-01 -5.26864052e-01 -5.28506935e-01
3.37625086e-01 -2.96587169e-01 5.38270354e-01 3.58645916e-01
-1.24773014e+00 5.18651962e-01 -1.25294757e+00 -4.85417962e-01
1.48311466e-01 4.31804627e-01 -7.48253167e-01 -5.41425645e-01
-4.14456099e-01 6.87511623e-01 2.85047770e-01 1.46858528e-01
-1.20878446e+00 -4.17916864e-01 -1.03806126e+00 -4.54079747e-01
4.39831078e-01 -1.17094254e+00 9.75464582e-01 -7.87215590e-01
-1.81304073e+00 1.23319340e+00 -5.54802239e-01 -2.32401535e-01
8.95152509e-01 -2.82318681e-01 3.57520133e-01 6.08479798e-01
-1.10629186e-01 7.45756984e-01 8.74312401e-01 -1.62630045e+00
-3.96516323e-01 -4.71011966e-01 3.02367538e-01 5.87648332e-01
1.89003751e-01 -3.58195782e-01 -9.01519597e-01 -4.35720086e-01
7.64263153e-01 -1.07732856e+00 -2.89448500e-01 2.17048064e-01
-5.11278629e-01 3.07687908e-01 7.94733524e-01 -6.43073440e-01
7.54252493e-01 -1.93840802e+00 8.35794568e-01 8.59950483e-02
1.37525529e-01 -2.27836505e-01 4.64002267e-02 1.86984882e-01
2.64713377e-01 -3.72609735e-01 -5.59931695e-01 -8.54972720e-01
-1.94290429e-01 6.98390186e-01 -5.29326275e-02 8.37913811e-01
-1.32513866e-01 8.69368970e-01 -8.04298103e-01 -4.55479264e-01
7.75833547e-01 5.80352545e-01 -9.21162188e-01 4.30968523e-01
-1.91793501e-01 1.17594576e+00 -3.97525549e-01 8.38656068e-01
8.54192019e-01 -1.76528782e-01 3.40126008e-01 -2.07794875e-01
-3.06762129e-01 -2.23384853e-02 -1.35125744e+00 2.24492311e+00
-1.90426961e-01 5.90387642e-01 3.67718220e-01 -9.46821988e-01
5.48472822e-01 1.37675434e-01 8.83666813e-01 -4.79804784e-01
6.99625388e-02 2.38195658e-01 -3.62327963e-01 -6.78145647e-01
5.27296007e-01 -4.45512325e-01 3.92131865e-01 2.25296110e-01
-8.32568035e-02 -7.57878721e-01 -1.77209690e-01 5.64312302e-02
1.05836749e+00 7.56844044e-01 7.85768107e-02 -4.97525744e-02
5.81790388e-01 -4.72691841e-02 5.33383548e-01 4.24471527e-01
8.48098695e-02 1.11527550e+00 -1.45990197e-02 -3.39694381e-01
-1.10708380e+00 -1.14174724e+00 -2.76182890e-01 7.44121447e-02
5.40225625e-01 -9.27969292e-02 -6.57526314e-01 -1.45806402e-01
-1.30005807e-01 3.38129222e-01 -4.00076210e-01 3.28383118e-01
-7.41243422e-01 -3.53057951e-01 -1.63566872e-01 1.88170001e-01
3.38995844e-01 -8.44510794e-01 -5.81633031e-01 2.48285577e-01
-4.72500086e-01 -1.68118620e+00 -3.42867613e-01 7.69625679e-02
-1.30750477e+00 -1.16240895e+00 -6.52568102e-01 -7.84708500e-01
8.69553506e-01 6.64087117e-01 9.99198794e-01 -7.66094849e-02
-2.60457903e-01 8.80507350e-01 -5.62525243e-02 4.03341651e-01
-1.36433005e-01 -2.93162972e-01 -2.45746430e-02 1.94244400e-01
-7.72416219e-02 -8.92104864e-01 -8.00592601e-01 5.34510851e-01
-1.03086555e+00 3.46527547e-01 1.33216575e-01 6.08524084e-01
1.08152473e+00 -8.86612460e-02 -3.16596687e-01 -8.16096365e-01
-4.03136402e-01 -3.05684596e-01 -6.21564984e-01 -2.39413396e-01
-2.68017411e-01 -4.79449183e-02 2.84778714e-01 -2.61075020e-01
-1.18270957e+00 6.03691399e-01 -1.95873499e-01 -7.98123658e-01
-3.07135105e-01 7.25127533e-02 -4.22471613e-01 -3.62541050e-01
1.08461015e-01 3.89262378e-01 -6.67391345e-02 -5.64052939e-01
2.60725468e-01 1.46116018e-01 6.69077754e-01 -6.45202994e-01
1.11286223e+00 1.38420689e+00 1.56221554e-01 -9.55623806e-01
-8.35743129e-01 -7.86376774e-01 -1.25874913e+00 -3.31691980e-01
1.21641135e+00 -1.09257388e+00 -5.93471944e-01 6.11276567e-01
-1.09775615e+00 -6.10246718e-01 -3.60165685e-01 6.56423330e-01
-1.05760443e+00 8.55662048e-01 -5.78640938e-01 -7.12211907e-01
6.95162863e-02 -1.21027935e+00 1.36616254e+00 -2.82086208e-02
-4.31584790e-02 -1.27471209e+00 2.86423177e-01 7.90245533e-01
-2.18929835e-02 6.29216850e-01 4.19218898e-01 2.92855948e-01
-1.44752383e+00 2.54483111e-02 1.25541180e-01 2.03931034e-01
1.41865939e-01 6.08200096e-02 -1.08303797e+00 -3.12268883e-01
3.94627184e-01 -1.32780999e-01 7.41980135e-01 5.85382819e-01
8.86980355e-01 -5.32742999e-02 -1.54111281e-01 1.22751760e+00
1.58920574e+00 1.38412509e-02 9.55901027e-01 3.68280947e-01
1.16194105e+00 8.94576073e-01 5.92653155e-01 4.06383485e-01
6.15307212e-01 8.69842172e-01 7.94562876e-01 -3.19338264e-03
-1.07632712e-01 -1.48757562e-01 3.08149427e-01 9.24259901e-01
-3.73712718e-01 -1.69226438e-01 -7.79471338e-01 5.19470215e-01
-1.80222929e+00 -1.16021299e+00 -3.01697671e-01 2.25949574e+00
6.70065880e-01 -6.43071085e-02 -2.17384055e-01 9.20161307e-02
3.83908182e-01 2.03513741e-01 -6.34298742e-01 6.54779598e-02
-4.66544539e-01 1.13134615e-01 2.00936005e-01 9.73310769e-01
-8.69863391e-01 1.08256900e+00 6.02639627e+00 2.24089593e-01
-8.82596552e-01 4.16110791e-02 2.32268974e-01 -2.77467638e-01
-7.09498525e-01 3.76466930e-01 -6.04903102e-01 1.46855533e-01
3.65234733e-01 8.58383849e-02 4.65805441e-01 4.74890828e-01
5.48499823e-01 -5.23983538e-01 -1.22920740e+00 1.27391386e+00
1.45292848e-01 -1.16273069e+00 1.61466062e-01 4.19880033e-01
1.19107783e+00 -4.74043339e-02 -1.38965979e-01 -4.25179183e-01
1.55658526e-02 -8.41432631e-01 9.01366472e-01 7.92256296e-01
6.12727940e-01 -5.74625492e-01 3.73449445e-01 5.66251218e-01
-1.00893474e+00 1.57774672e-01 -4.30506647e-01 -4.39201333e-02
6.55888140e-01 8.06243956e-01 -3.12295079e-01 7.07114577e-01
6.25012219e-01 1.28890097e+00 -1.41166493e-01 1.04155028e+00
-1.11590333e-01 1.28744856e-01 -3.59956056e-01 7.64485061e-01
1.28994986e-01 -6.98837817e-01 7.74269521e-01 9.14264619e-01
2.09648684e-01 3.77960563e-01 2.17019558e-01 7.25604773e-01
1.20372482e-01 -1.40585721e-01 -8.64645720e-01 3.03507984e-01
-1.41362309e-01 1.14617193e+00 -7.37289429e-01 3.91220450e-02
-4.27621037e-01 1.44110262e+00 2.32778266e-01 4.47573036e-01
-5.28635383e-01 5.50629616e-01 7.65688896e-01 4.47289526e-01
2.62126088e-01 -8.61770034e-01 -1.39505014e-01 -1.62660623e+00
1.46851048e-01 -5.13821483e-01 1.70614094e-01 -8.58406484e-01
-9.48116481e-01 2.44900793e-01 2.52368823e-02 -1.26781118e+00
-3.05875242e-01 -3.98000985e-01 -3.66978467e-01 5.76575220e-01
-1.81343985e+00 -9.77278411e-01 -6.57626927e-01 9.68635976e-01
7.82104731e-01 3.74241829e-01 4.85875189e-01 4.09072071e-01
-2.03544527e-01 -4.91069220e-02 2.36912638e-01 -2.76471049e-01
6.31990671e-01 -1.15904188e+00 7.45327845e-02 8.78673077e-01
1.44889116e-01 4.88987118e-01 6.27182961e-01 -6.35900259e-01
-1.88945138e+00 -7.93677270e-01 4.87703681e-01 -6.58223808e-01
4.00992423e-01 -1.89841464e-01 -8.79524827e-01 6.76891565e-01
-1.24965243e-01 1.69843569e-01 3.63888890e-01 -4.80147779e-01
1.04577005e-01 1.82078838e-01 -1.14260852e+00 4.10483211e-01
1.55570436e+00 -7.00879037e-01 -3.24015021e-01 3.58669490e-01
4.85522300e-01 -9.39546287e-01 -7.80093014e-01 2.85467505e-01
5.86454630e-01 -1.26226711e+00 1.27382588e+00 -5.91041110e-02
5.97493351e-01 -5.02105057e-01 -4.82916951e-01 -7.80420303e-01
2.90867183e-02 -7.14350581e-01 -3.33135784e-01 8.96625638e-01
-2.53392994e-01 -3.34163070e-01 1.16546082e+00 6.76444769e-01
-3.37993473e-01 -3.98359388e-01 -1.15471423e+00 -5.57187557e-01
-1.34947315e-01 -4.54233319e-01 -1.32558808e-01 9.97952402e-01
-6.85478866e-01 -1.21201491e-02 -5.59802115e-01 3.29592228e-01
1.02462757e+00 3.31630737e-01 1.11671650e+00 -1.03922832e+00
-5.12486100e-01 -2.77987868e-02 -6.33066654e-01 -1.64470613e+00
5.20219266e-01 -8.07741404e-01 5.56548089e-02 -1.62194097e+00
3.57990682e-01 -3.14039886e-01 4.14979994e-01 -1.32786362e-02
6.69171289e-02 3.31579059e-01 -1.06525652e-01 6.02484763e-01
-4.04861063e-01 5.48212528e-01 1.68167841e+00 9.70063880e-02
-1.64414600e-01 -8.13762844e-02 -9.98375639e-02 9.60989714e-01
4.23507333e-01 -3.38527501e-01 -5.27944088e-01 -7.36072004e-01
2.80489456e-02 3.81457418e-01 5.18600166e-01 -6.97050393e-01
3.23629111e-01 -4.65793192e-01 1.91296116e-01 -9.01622951e-01
6.22112870e-01 -1.07651556e+00 7.57089376e-01 2.33637944e-01
2.05015391e-01 -1.16142541e-01 -4.47600745e-02 8.44498277e-01
-2.73311108e-01 -2.25106895e-01 9.50967252e-01 -3.71876538e-01
-8.45539808e-01 5.79278946e-01 -8.41900408e-02 4.77195159e-02
9.68751490e-01 -7.12452233e-01 2.30416775e-01 -3.55789483e-01
-1.05263245e+00 4.54950053e-03 1.12364757e+00 1.58724308e-01
8.92323971e-01 -9.51721549e-01 -5.37599981e-01 1.91211298e-01
-1.21260412e-01 7.69216239e-01 4.64448094e-01 7.73275793e-01
-1.02577937e+00 2.72847593e-01 -2.41919868e-02 -1.10692751e+00
-1.29324365e+00 3.64552468e-01 5.48872769e-01 -1.05829649e-01
-1.11754322e+00 5.53882539e-01 5.49754620e-01 -5.68179727e-01
1.56004578e-01 -1.48025051e-01 7.03979284e-02 -2.24387184e-01
2.04581723e-01 2.85811782e-01 -1.34843722e-01 -8.52207899e-01
-2.00878739e-01 1.23437190e+00 1.39765263e-01 -4.03575838e-01
1.54536176e+00 -7.21585274e-01 -2.85224468e-01 4.42763835e-01
1.23486900e+00 1.53723612e-01 -1.75562704e+00 -2.52083272e-01
-2.13605151e-01 -9.49542761e-01 -7.02290535e-02 -6.31142184e-02
-1.04233527e+00 8.73314559e-01 2.27811709e-01 -3.47967118e-01
1.11741602e+00 1.03283979e-01 6.61131382e-01 2.82927722e-01
7.86487877e-01 -7.47399867e-01 3.01746249e-01 6.28000617e-01
6.85845017e-01 -1.31246209e+00 1.61439598e-01 -6.86057210e-01
-3.14175695e-01 1.21181214e+00 4.44934100e-01 -8.17451328e-02
5.64267516e-01 1.48949847e-01 -1.01703018e-01 -1.93101585e-01
-4.13823396e-01 -9.47882757e-02 2.16583654e-01 7.27078259e-01
1.55924097e-01 -2.72688538e-01 -8.63587484e-02 -4.18614000e-01
-1.36994332e-01 -9.92791578e-02 7.13261306e-01 9.46945190e-01
-1.98530614e-01 -1.16133237e+00 -3.78411353e-01 -7.70206377e-02
-2.55992293e-01 9.59781185e-02 -2.53348470e-01 7.52993762e-01
-1.49250925e-01 7.82970965e-01 4.98850010e-02 -1.64414227e-01
3.43155831e-01 -3.08149427e-01 9.47588563e-01 -7.82896519e-01
-2.47532085e-01 4.54828054e-01 -8.94123241e-02 -9.87974465e-01
-1.01498604e+00 -1.03228819e+00 -1.32538033e+00 -3.13642740e-01
-8.88355915e-03 -1.87327430e-01 6.47877097e-01 9.58790004e-01
-4.11069617e-02 1.21295236e-01 7.47343421e-01 -1.45603859e+00
-6.32759482e-02 -2.93543041e-01 -5.77601612e-01 5.95421851e-01
4.77310270e-01 -6.28159165e-01 -6.63735569e-01 3.52787673e-01] | [8.628686904907227, -2.2203540802001953] |
b149d7eb-bce6-4b76-abab-096ffa564d52 | global-priors-guided-modulation-network-for | 2208.06885 | null | https://arxiv.org/abs/2208.06885v2 | https://arxiv.org/pdf/2208.06885v2.pdf | Global Priors Guided Modulation Network for Joint Super-Resolution and Inverse Tone-Mapping | Joint super-resolution and inverse tone-mapping (SR-ITM) aims to enhance the visual quality of videos that have quality deficiencies in resolution and dynamic range. This problem arises when using 4K high dynamic range (HDR) TVs to watch a low-resolution standard dynamic range (LR SDR) video. Previous methods that rely on learning local information typically cannot do well in preserving color conformity and long-range structural similarity, resulting in unnatural color transition and texture artifacts. In order to tackle these challenges, we propose a global priors guided modulation network (GPGMNet) for joint SR-ITM. In particular, we design a global priors extraction module (GPEM) to extract color conformity prior and structural similarity prior that are beneficial for ITM and SR tasks, respectively. To further exploit the global priors and preserve spatial information, we devise multiple global priors guided spatial-wise modulation blocks (GSMBs) with a few parameters for intermediate feature modulation, in which the modulation parameters are generated by the shared global priors and the spatial features map from the spatial pyramid convolution block (SPCB). With these elaborate designs, the GPGMNet can achieve higher visual quality with lower computational complexity. Extensive experiments demonstrate that our proposed GPGMNet is superior to the state-of-the-art methods. Specifically, our proposed model exceeds the state-of-the-art by 0.64 dB in PSNR, with 69$\%$ fewer parameters and 3.1$\times$ speedup. The code will be released soon. | ['Yurong Dai', 'Xing Wen', 'Ming Sun', 'Jinjia Zhou', 'Chang Wu', 'Li Xu', 'Shaoyi Long', 'Gang He'] | 2022-08-14 | null | null | null | null | ['tone-mapping', 'inverse-tone-mapping'] | ['computer-vision', 'computer-vision'] | [ 5.39687216e-01 -5.80776095e-01 -1.75478086e-01 -1.44553274e-01
-7.84535587e-01 -4.38739061e-02 2.25382283e-01 -7.61640310e-01
-1.82670802e-01 6.67274058e-01 3.14573854e-01 -1.59376740e-01
-2.14114755e-01 -7.21484780e-01 -5.37035763e-01 -7.34140754e-01
-1.28563613e-01 -6.17783070e-01 6.01048172e-01 -3.43140662e-01
3.43958080e-01 2.78601676e-01 -1.52368402e+00 4.23251092e-01
1.10993576e+00 1.19656551e+00 6.21364236e-01 5.46205759e-01
1.15249269e-01 8.32300305e-01 -2.95166969e-01 -5.17845154e-02
5.52314878e-01 -5.16802013e-01 -3.87514293e-01 1.95201170e-02
4.46533024e-01 -6.77345395e-01 -6.85758352e-01 1.32062197e+00
6.00553453e-01 3.00019532e-01 2.41944805e-01 -8.72378290e-01
-9.11663592e-01 1.75755009e-01 -1.13847637e+00 5.10160446e-01
2.79887795e-01 2.60433763e-01 7.25713909e-01 -8.98992538e-01
3.59118879e-01 1.38608253e+00 4.28962141e-01 3.30366194e-01
-1.21830535e+00 -1.04272902e+00 9.89762098e-02 5.89626849e-01
-1.60165548e+00 -5.51562190e-01 8.74898911e-01 6.15794510e-02
5.84114552e-01 2.89407939e-01 2.94032335e-01 6.65049314e-01
2.86436290e-01 2.74015456e-01 1.46927226e+00 -2.18263149e-01
-4.37648483e-02 -2.56649077e-01 -2.95783401e-01 6.21867657e-01
7.63841122e-02 3.58438283e-01 -7.48476923e-01 2.27108732e-01
1.37576032e+00 -1.99476361e-01 -7.18063474e-01 4.60511670e-02
-1.02580893e+00 4.07813340e-01 3.85705501e-01 2.69094169e-01
-1.57207340e-01 2.06892997e-01 -1.00166641e-01 3.27771962e-01
2.47928455e-01 1.47656975e-02 -2.58906096e-01 -1.03500791e-01
-9.11722183e-01 -2.07850635e-01 2.33658820e-01 1.04582214e+00
7.30009675e-01 2.34722093e-01 -2.42144644e-01 1.25524843e+00
3.95465940e-01 5.86198568e-01 2.64847368e-01 -1.39915097e+00
4.13380623e-01 1.64241269e-01 2.00337559e-01 -1.29000771e+00
-4.59195711e-02 -4.27056313e-01 -1.20441663e+00 4.40790981e-01
-1.26738548e-02 2.01246575e-01 -9.59726334e-01 1.63304174e+00
1.26002535e-01 4.59758997e-01 3.77955362e-02 1.21956360e+00
8.58763874e-01 9.99774098e-01 -1.16212726e-01 -4.95050639e-01
1.36143899e+00 -8.32775772e-01 -8.89763772e-01 -1.62283093e-01
-1.60482734e-01 -1.10239422e+00 1.14142787e+00 6.21171892e-01
-1.36755705e+00 -1.12451088e+00 -1.39605772e+00 -1.60693839e-01
2.86968797e-01 1.04204625e-01 1.89626783e-01 6.98439956e-01
-1.17641950e+00 7.06906497e-01 -5.48590183e-01 8.33519474e-02
2.89335132e-01 3.13151687e-01 8.63624737e-02 -5.08273959e-01
-1.28703964e+00 7.06552148e-01 1.83878228e-01 7.62189701e-02
-7.66534865e-01 -7.44636238e-01 -6.80949926e-01 -2.41916571e-02
5.51272452e-01 -4.65471238e-01 7.68125236e-01 -8.81408870e-01
-1.80670822e+00 4.48409081e-01 -8.51416886e-02 -3.10756881e-02
1.92923695e-01 -9.64619294e-02 -8.75408530e-01 4.47636664e-01
-2.04273760e-01 5.62418640e-01 1.07675803e+00 -1.43258440e+00
-7.81489015e-01 -7.74530396e-02 -9.02575999e-02 3.88830423e-01
-2.14527443e-01 3.58582795e-01 -9.74466264e-01 -9.84040082e-01
3.27728719e-01 -4.33963686e-01 -1.23777658e-01 1.13211282e-01
-8.07178393e-02 4.29892570e-01 9.16245878e-01 -1.16350186e+00
1.46152222e+00 -2.35482025e+00 -7.04927370e-02 1.05975479e-01
1.16402291e-01 4.00508165e-01 -2.78225899e-01 -2.21087933e-01
-1.90300178e-02 9.04231984e-03 -1.41070232e-01 4.61782515e-02
-1.82106987e-01 -3.39488662e-03 -9.41610560e-02 4.26767409e-01
-7.71805122e-02 5.13770700e-01 -6.91754103e-01 -5.09019256e-01
3.44169140e-01 8.53602469e-01 -3.85652155e-01 1.12110935e-01
1.00901701e-01 5.43363571e-01 -3.60039592e-01 6.13330960e-01
1.21153426e+00 -3.06986004e-01 8.20354894e-02 -6.79696023e-01
-2.59116858e-01 -2.63817552e-02 -1.58374560e+00 1.63668263e+00
-5.00344992e-01 4.50384945e-01 3.25833887e-01 -4.26601022e-01
1.15081501e+00 6.88729808e-02 3.32380861e-01 -1.27717745e+00
2.58225463e-02 3.40870380e-01 -8.63250047e-02 -4.03486311e-01
5.54777443e-01 -1.12625301e-01 3.65577132e-01 -2.23619416e-02
-2.31358364e-01 2.77246296e-01 -3.93231250e-02 -8.82557686e-03
8.28648984e-01 3.18798721e-01 1.80930749e-01 -1.97997123e-01
9.13990140e-01 -6.30953848e-01 9.18488920e-01 4.28969771e-01
-8.17014426e-02 8.49708259e-01 1.50727749e-01 -1.27377585e-01
-1.13841379e+00 -1.25147939e+00 3.63723282e-03 9.51176524e-01
6.59558058e-01 -2.20160693e-01 -3.84727240e-01 5.86162321e-02
-5.45665622e-01 4.91520703e-01 -1.38598412e-01 -1.51443109e-01
-8.26266527e-01 -6.85274839e-01 9.45540667e-02 3.43404889e-01
1.26767278e+00 -7.35809505e-01 -2.78191835e-01 1.50890499e-01
-3.76631737e-01 -1.29720640e+00 -7.68100619e-01 -4.61017311e-01
-7.04426646e-01 -7.62541234e-01 -8.88883054e-01 -6.86675847e-01
3.23058516e-01 5.67045033e-01 9.54078376e-01 -8.08808357e-02
-1.80433467e-01 -6.70273602e-02 -4.61886793e-01 3.89466763e-01
-2.87741691e-01 -4.03533578e-01 -1.34089723e-01 3.29983205e-01
-6.32017180e-02 -9.57371175e-01 -1.14218986e+00 7.03902423e-01
-1.02147841e+00 4.23001796e-01 8.49158764e-01 6.23755813e-01
8.69433641e-01 4.51018125e-01 4.32300657e-01 -3.75307411e-01
3.21351409e-01 -1.51878938e-01 -7.74114847e-01 6.72649518e-02
-6.18943632e-01 -2.46313751e-01 7.89056301e-01 -4.29105163e-01
-1.46718729e+00 -2.95724303e-01 -7.65111297e-02 -5.47678947e-01
9.29508954e-02 4.14323919e-02 -5.85900068e-01 -4.49184179e-01
3.52950990e-01 5.27473748e-01 -3.05236410e-02 -6.64597452e-01
2.79216707e-01 6.86903775e-01 7.63191402e-01 -4.76436555e-01
9.90183771e-01 6.36922181e-01 1.43277809e-01 -7.06392527e-01
-5.87374747e-01 -2.78295070e-01 -5.99084310e-02 -2.78294206e-01
9.80634391e-01 -1.27433753e+00 -5.32707512e-01 4.97814506e-01
-6.57772303e-01 -3.39553744e-01 1.06122486e-01 5.12153506e-01
-5.89971900e-01 6.89020455e-01 -8.45193386e-01 -5.68209112e-01
-2.99125016e-01 -1.21091044e+00 6.57415390e-01 5.90088964e-01
5.42437911e-01 -5.41118979e-01 -3.56824994e-01 3.52954298e-01
9.18865740e-01 9.35015231e-02 6.78926229e-01 3.49242091e-01
-1.07709944e+00 5.44523954e-01 -7.66804039e-01 6.07423246e-01
3.11678261e-01 -3.68095458e-01 -7.54276633e-01 -4.94559765e-01
1.35275394e-01 2.47044697e-01 8.21789682e-01 5.73753178e-01
1.40999115e+00 -1.86944291e-01 -1.20482519e-02 1.16705167e+00
1.87467933e+00 4.76484627e-01 1.23154402e+00 4.67844129e-01
7.05656409e-01 2.83386797e-01 8.72264802e-01 5.26814163e-01
1.77470580e-01 9.22962606e-01 2.88551092e-01 -3.78458053e-01
-6.11560285e-01 -1.16039902e-01 4.84063983e-01 6.25113785e-01
-2.25681782e-01 -9.82593372e-02 -2.83366352e-01 2.63056278e-01
-1.47423041e+00 -8.01236331e-01 5.10963704e-03 2.18124771e+00
9.46254313e-01 3.91321480e-02 -1.76833436e-01 5.65533452e-02
9.20792997e-01 4.20529246e-01 -4.66108829e-01 -1.20703384e-01
-4.18305010e-01 3.55466157e-01 6.79023385e-01 4.65047181e-01
-8.76650929e-01 7.17932284e-01 5.12124348e+00 1.48294115e+00
-9.62519944e-01 2.05167353e-01 8.65043283e-01 4.22276556e-02
-2.06835642e-01 -3.74254398e-02 -6.86974049e-01 6.88583016e-01
7.67778754e-01 1.41230255e-01 8.30751836e-01 4.01509911e-01
5.82151651e-01 -1.95199102e-01 -5.44264019e-01 1.34343243e+00
6.84399679e-02 -1.11357534e+00 -1.24197984e-02 -2.68639834e-03
7.92517960e-01 -4.11357790e-01 4.66297299e-01 -7.80900661e-03
1.00141369e-01 -1.02757323e+00 3.85357589e-01 6.55272543e-01
1.36196828e+00 -9.97691453e-01 4.38226819e-01 -1.26650915e-01
-1.54520988e+00 -1.71081021e-01 -4.87237483e-01 3.66645515e-01
3.14990550e-01 4.07781333e-01 1.42458692e-01 7.79037118e-01
1.07223368e+00 6.65424883e-01 -4.28361237e-01 9.78647053e-01
-1.09407596e-01 3.81722331e-01 -7.33202472e-02 5.62490344e-01
-6.96708113e-02 -3.68840992e-01 6.21926963e-01 1.06229985e+00
5.33825755e-01 5.12721539e-01 -1.65087264e-02 8.74866903e-01
7.59544969e-02 2.31445543e-02 4.69662696e-02 4.07181263e-01
4.18086767e-01 1.25779736e+00 -4.18006450e-01 -2.03889430e-01
-6.55840456e-01 1.14548004e+00 -4.34320182e-01 5.38644969e-01
-1.00677776e+00 -5.06682456e-01 7.07694829e-01 2.01578692e-01
6.28436804e-01 -1.68309718e-01 -1.51798755e-01 -9.41510379e-01
6.37212470e-02 -1.16655660e+00 2.25243852e-01 -1.08126521e+00
-1.24370682e+00 5.62264800e-01 -4.70912531e-02 -1.64963663e+00
3.21312010e-01 -4.02731597e-01 -2.64151126e-01 9.99210715e-01
-2.04719281e+00 -1.03927755e+00 -5.95594883e-01 8.47943544e-01
4.93541479e-01 -4.76003550e-02 9.83328670e-02 6.51191831e-01
-3.85463029e-01 6.17808223e-01 1.37428403e-01 -2.47474201e-02
8.84051919e-01 -7.96060085e-01 -2.41229916e-03 1.20245790e+00
-5.12805700e-01 4.14572984e-01 6.46218300e-01 -5.24286270e-01
-1.43592095e+00 -1.27643454e+00 1.67357266e-01 3.71759146e-01
3.27808172e-01 4.55701426e-02 -9.82538521e-01 1.81321591e-01
1.72866702e-01 1.58903107e-01 4.50368196e-01 -5.42548180e-01
-3.62458825e-01 -5.33318937e-01 -1.27614176e+00 6.82987690e-01
1.10120523e+00 -3.22708368e-01 -8.54894444e-02 -2.21557766e-01
1.00713301e+00 -4.89001304e-01 -1.12219727e+00 5.46800673e-01
3.97866756e-01 -1.26790321e+00 1.24233687e+00 3.51805419e-01
5.29048920e-01 -1.03454149e+00 -6.12094343e-01 -8.56225312e-01
-6.88264012e-01 -8.66060257e-01 -2.08307803e-01 1.32234526e+00
3.33025977e-02 -5.44083118e-01 3.36191505e-01 1.91158712e-01
-2.91423261e-01 -6.35063231e-01 -8.29667985e-01 -7.96180725e-01
-3.50952059e-01 -2.42173791e-01 5.72417736e-01 7.65260458e-01
-5.30804038e-01 8.56596008e-02 -8.31472933e-01 4.50505614e-01
9.29924607e-01 4.71090302e-02 3.96654487e-01 -7.19416201e-01
-6.02151096e-01 -3.32297355e-01 -2.62949169e-01 -1.38644695e+00
-3.97157758e-01 -2.97582984e-01 -2.42183637e-02 -1.40993488e+00
4.30110216e-01 -3.98647994e-01 -5.84918082e-01 3.25191095e-02
-2.52663404e-01 7.14624941e-01 3.52596849e-01 9.91394892e-02
-7.63740242e-01 5.51906526e-01 1.64920163e+00 8.36249217e-02
-3.74334395e-01 -3.98847967e-01 -8.57716799e-01 6.41920328e-01
7.48117626e-01 -4.04244326e-02 -3.79658699e-01 -3.87805104e-01
5.54824658e-02 4.47236329e-01 3.15763444e-01 -1.22489178e+00
1.35771498e-01 -2.78181314e-01 6.78718448e-01 -6.55352890e-01
5.69113135e-01 -7.59166837e-01 4.38030720e-01 2.15552434e-01
-9.65292975e-02 -2.54583478e-01 1.18378736e-01 6.49089277e-01
-2.99799621e-01 2.45637268e-01 1.31582475e+00 -9.53948572e-02
-1.04617488e+00 4.80013877e-01 -1.72002554e-01 -1.23645507e-01
7.31206119e-01 -4.84969556e-01 -4.79362100e-01 -4.24569428e-01
-4.42655832e-01 2.57545002e-02 6.50715113e-01 3.58241946e-01
1.07014334e+00 -1.41407752e+00 -8.05968642e-01 2.15213224e-01
-2.21686304e-01 -2.45693162e-01 9.49303925e-01 8.44677210e-01
-5.92814863e-01 -4.48946394e-02 -4.71843421e-01 -4.23316389e-01
-1.26442659e+00 5.75272918e-01 3.52366447e-01 -1.56174496e-01
-7.33465612e-01 6.86184287e-01 3.46342146e-01 3.09822708e-01
1.91428384e-03 -7.41262361e-02 -3.54367375e-01 -5.86289883e-01
8.53620291e-01 6.37452841e-01 -3.04819167e-01 -6.96705520e-01
-8.92414898e-02 9.91886020e-01 -4.82264645e-02 -8.08351859e-02
1.26165640e+00 -6.78948402e-01 -1.60195291e-01 -6.84744194e-02
1.17124724e+00 2.62294441e-01 -1.61316788e+00 -4.87690449e-01
-5.61196089e-01 -1.11714947e+00 3.50023210e-01 -7.79432297e-01
-1.36534190e+00 6.21328413e-01 1.11895597e+00 -1.86744347e-01
1.94610906e+00 -3.08324307e-01 1.04751837e+00 -3.79988670e-01
4.19735044e-01 -1.05690527e+00 4.00576264e-01 2.40446821e-01
7.69556344e-01 -9.31447268e-01 1.99859619e-01 -7.06087828e-01
-5.04007280e-01 1.03621912e+00 7.62069643e-01 -1.23289280e-01
4.84059840e-01 1.80504277e-01 -8.06370899e-02 2.34198600e-01
-5.90025246e-01 -1.95680201e-01 4.65235651e-01 6.89273119e-01
2.26058185e-01 -2.16415167e-01 -3.10101330e-01 4.89005655e-01
1.27022713e-01 2.87845805e-02 5.75312316e-01 4.98879164e-01
-7.16494143e-01 -9.09159482e-01 -5.25781870e-01 2.41500035e-01
-7.02665091e-01 -3.43755245e-01 3.93180698e-01 4.98575240e-01
4.23954844e-01 1.18784845e+00 -1.29817814e-01 -6.37505472e-01
1.85227647e-01 -6.30252004e-01 5.29731095e-01 -3.46325338e-02
5.99066466e-02 5.81599534e-01 -4.89015505e-02 -9.48295772e-01
-5.75203001e-01 -1.99146345e-01 -1.13367534e+00 -4.46234405e-01
-1.38243541e-01 -3.06385726e-01 3.84986579e-01 4.42633629e-01
3.87099057e-01 7.57232487e-01 8.75563443e-01 -6.86090589e-01
-1.43984348e-01 -7.59801626e-01 -8.17144096e-01 2.02330753e-01
3.46162051e-01 -5.09285569e-01 -3.58852834e-01 1.61365941e-01] | [11.041099548339844, -2.0616400241851807] |
c42d2d91-b309-4462-a0ee-ca9bb9d45b42 | nsnet-non-saliency-suppression-sampler-for | 2207.10388 | null | https://arxiv.org/abs/2207.10388v1 | https://arxiv.org/pdf/2207.10388v1.pdf | NSNet: Non-saliency Suppression Sampler for Efficient Video Recognition | It is challenging for artificial intelligence systems to achieve accurate video recognition under the scenario of low computation costs. Adaptive inference based efficient video recognition methods typically preview videos and focus on salient parts to reduce computation costs. Most existing works focus on complex networks learning with video classification based objectives. Taking all frames as positive samples, few of them pay attention to the discrimination between positive samples (salient frames) and negative samples (non-salient frames) in supervisions. To fill this gap, in this paper, we propose a novel Non-saliency Suppression Network (NSNet), which effectively suppresses the responses of non-salient frames. Specifically, on the frame level, effective pseudo labels that can distinguish between salient and non-salient frames are generated to guide the frame saliency learning. On the video level, a temporal attention module is learned under dual video-level supervisions on both the salient and the non-salient representations. Saliency measurements from both two levels are combined for exploitation of multi-granularity complementary information. Extensive experiments conducted on four well-known benchmarks verify our NSNet not only achieves the state-of-the-art accuracy-efficiency trade-off but also present a significantly faster (2.4~4.3x) practical inference speed than state-of-the-art methods. Our project page is at https://lawrencexia2008.github.io/projects/nsnet . | ['Wanli Ouyang', 'Xiaoran Fan', 'Haosen Yang', 'Dongliang He', 'Rui Su', 'Haoran Wang', 'Wenhao Wu', 'Boyang xia'] | 2022-07-21 | null | null | null | null | ['video-classification'] | ['computer-vision'] | [ 5.56927025e-01 -2.65065610e-01 -7.31737196e-01 -3.45096588e-01
-5.20055592e-01 2.04957295e-02 3.16167414e-01 -1.97944880e-01
-3.93421918e-01 8.17287922e-01 1.74880400e-01 6.42493740e-02
2.60768473e-01 -4.97630715e-01 -7.78342605e-01 -7.64878988e-01
3.32162380e-02 -2.39254758e-01 7.27600634e-01 -3.50577161e-02
3.88127714e-01 7.59971216e-02 -1.87366796e+00 4.50493783e-01
8.28264713e-01 1.24337161e+00 5.09644389e-01 4.90483433e-01
1.43378496e-01 1.05325973e+00 -3.94695073e-01 6.21719025e-02
2.24866346e-01 -4.65365112e-01 -4.48033869e-01 4.66594100e-02
5.52251577e-01 -4.37666565e-01 -5.69635570e-01 1.42956758e+00
4.42517370e-01 2.83788681e-01 1.53415069e-01 -1.54862654e+00
-6.24648869e-01 6.04108453e-01 -8.03850651e-01 9.54651535e-01
1.76937595e-01 4.01291281e-01 8.43890786e-01 -1.11478674e+00
4.75759685e-01 1.21508384e+00 1.81200340e-01 7.38630295e-01
-8.66718829e-01 -8.74356151e-01 5.49371183e-01 8.70409429e-01
-1.29728448e+00 -6.29667401e-01 9.79820728e-01 -1.49189413e-01
6.21068656e-01 3.92423123e-01 6.84879661e-01 1.01192439e+00
1.08813480e-01 1.27657294e+00 7.90246606e-01 -1.37703404e-01
2.53653079e-01 -5.42443618e-02 1.20477431e-01 7.13057041e-01
1.08408689e-01 -5.94319776e-03 -9.81592417e-01 2.70987958e-01
9.46749806e-01 3.65729839e-01 -5.17888248e-01 -1.83181256e-01
-1.28597772e+00 6.40147746e-01 4.94980454e-01 1.77275077e-01
-5.50170481e-01 1.33535489e-01 4.50817972e-01 6.80288533e-04
3.92495602e-01 -6.73170537e-02 -3.36898953e-01 1.25874141e-02
-1.07071102e+00 2.91338041e-02 2.69731909e-01 9.59563553e-01
7.47006357e-01 5.54641604e-01 -6.65386498e-01 6.18494272e-01
2.57993132e-01 4.56061333e-01 5.50856113e-01 -8.18835020e-01
4.25427467e-01 5.37951410e-01 -8.90576839e-02 -1.24873924e+00
-1.11269085e-02 -5.54964364e-01 -1.12197471e+00 9.22937226e-03
6.68829232e-02 -6.50708750e-02 -1.03672218e+00 1.71225870e+00
3.40807021e-01 8.03277135e-01 -2.04355698e-02 1.49308121e+00
9.85765755e-01 7.19002604e-01 3.17484587e-01 -5.26981175e-01
1.35054588e+00 -1.40499485e+00 -6.78811014e-01 -3.19619596e-01
5.29130809e-02 -6.40144944e-01 9.53436375e-01 4.81575765e-02
-1.22959065e+00 -7.66305685e-01 -1.11248362e+00 1.04997689e-02
-3.45506631e-02 1.97075933e-01 5.06287217e-01 4.07902300e-02
-1.03272343e+00 2.58034945e-01 -7.49241114e-01 -5.37130795e-02
7.25077033e-01 3.42379659e-01 7.28318170e-02 1.26488572e-02
-1.39193726e+00 4.94702250e-01 3.72613102e-01 1.23785265e-01
-1.30493641e+00 -6.54579937e-01 -8.84257138e-01 2.21834555e-01
7.52717853e-01 -4.70415503e-01 1.07429659e+00 -1.63814139e+00
-1.13088095e+00 5.34469604e-01 -4.56557155e-01 -3.99397761e-01
2.89797068e-01 -2.14667663e-01 -5.00657558e-01 5.31545460e-01
2.33930677e-01 9.74682271e-01 1.29641593e+00 -9.12724435e-01
-9.95912135e-01 -1.09008856e-01 1.12642244e-01 4.28127885e-01
-4.53412235e-01 2.60703444e-01 -6.08064532e-01 -9.68617857e-01
1.37285329e-02 -6.57882631e-01 -4.36586253e-02 2.65027016e-01
-3.31824541e-01 -3.20596218e-01 1.20708275e+00 -6.19189560e-01
1.27687168e+00 -2.08299446e+00 1.61822379e-01 -2.68385142e-01
3.50413084e-01 6.23492956e-01 -1.83101133e-01 -3.33503067e-01
-5.60277291e-02 -1.87965587e-01 -9.52104405e-02 -3.93459313e-02
-2.90710717e-01 -1.38105482e-01 -3.39356214e-01 4.51751590e-01
5.89502156e-01 7.84155905e-01 -1.06545162e+00 -6.90411925e-01
3.25986832e-01 4.99098122e-01 -5.08285999e-01 1.15430407e-01
-1.59187183e-01 2.27781862e-01 -5.72721124e-01 1.09727371e+00
5.77804804e-01 -4.27381665e-01 5.41818701e-03 -3.55919272e-01
-1.59785762e-01 9.90716070e-02 -1.07451880e+00 1.38937414e+00
1.33611992e-01 7.40373254e-01 1.94752693e-01 -1.27885163e+00
5.69244444e-01 2.08196506e-01 3.62580091e-01 -7.75932491e-01
1.37865081e-01 6.15502149e-02 -6.45326078e-02 -2.98897237e-01
5.44785857e-01 1.54929131e-01 2.87384689e-01 1.59721132e-02
1.61003083e-01 5.84566593e-01 3.04451644e-01 1.09575197e-01
7.53880382e-01 1.05192699e-01 3.41633886e-01 -4.85874921e-01
8.71984124e-01 -1.66507110e-01 1.14304173e+00 7.49207079e-01
-7.60748744e-01 5.78073740e-01 3.47126186e-01 -4.11784798e-01
-7.57668078e-01 -9.28398252e-01 2.25970671e-01 1.51873553e+00
8.02358329e-01 -1.93567142e-01 -7.89091408e-01 -6.82050169e-01
-1.65262714e-01 4.34843153e-01 -5.31087756e-01 -2.54797161e-01
-6.34272158e-01 -5.82267284e-01 2.22351924e-01 5.33212364e-01
7.77520537e-01 -1.30057538e+00 -8.72339964e-01 -5.75284511e-02
-1.96046293e-01 -1.03726733e+00 -7.90136397e-01 -1.99626863e-01
-7.08771586e-01 -9.35727596e-01 -8.44206452e-01 -1.07161629e+00
7.01347411e-01 7.95221806e-01 9.34749663e-01 4.34766769e-01
-5.63625712e-03 1.61278248e-02 -3.07142735e-01 -4.49136525e-01
2.25115880e-01 -1.10003827e-02 2.05285862e-01 3.03867072e-01
5.12983143e-01 -3.69085491e-01 -7.81855226e-01 5.04507959e-01
-9.16676819e-01 5.93037128e-01 6.41010821e-01 9.14471865e-01
7.21104264e-01 -1.55130997e-01 8.11149001e-01 -3.23117822e-01
6.36581406e-02 -6.40612900e-01 -4.87888485e-01 2.99459547e-01
-2.95872003e-01 -1.68533653e-01 6.97302699e-01 -6.33527339e-01
-9.85687256e-01 -8.69279429e-02 2.68116355e-01 -9.15185988e-01
-1.06795393e-01 1.91996515e-01 -1.25983357e-01 -8.83986056e-02
1.06661521e-01 6.11511588e-01 -9.31857973e-02 4.82674502e-02
-1.47590980e-01 4.96964961e-01 5.40810645e-01 -2.61428952e-01
7.08437681e-01 5.16489744e-01 -7.57272765e-02 -8.38727891e-01
-1.10279536e+00 -3.24317098e-01 -2.42528707e-01 -6.19640231e-01
7.17833519e-01 -1.21278846e+00 -5.38915932e-01 4.65698123e-01
-8.30699623e-01 -1.68554857e-01 -1.38482526e-01 4.78136510e-01
-3.56521010e-01 2.78274924e-01 -5.82350373e-01 -7.65111327e-01
-5.31447470e-01 -1.35221267e+00 1.01430774e+00 8.02962244e-01
1.53890416e-01 -6.44549012e-01 -6.28885329e-01 2.41477191e-01
4.90479171e-01 -3.78494598e-02 3.32043618e-01 -3.94651443e-01
-1.01213872e+00 3.06243092e-01 -5.49527526e-01 2.65202105e-01
7.03655630e-02 3.21200974e-02 -8.75082374e-01 -3.41459572e-01
4.41562459e-02 -2.35875130e-01 1.10501087e+00 6.01788640e-01
1.42068124e+00 -3.69323850e-01 -2.28475183e-01 6.07330978e-01
1.18770599e+00 2.09930345e-01 5.88930070e-01 2.26922497e-01
8.21004272e-01 2.88267821e-01 1.02663505e+00 4.45187151e-01
3.63116026e-01 7.41629243e-01 4.56958860e-01 -1.43840993e-02
-2.41043299e-01 -8.55765715e-02 5.89619279e-01 7.61618853e-01
-4.64972965e-02 -1.73488721e-01 -5.86935043e-01 6.17362440e-01
-2.14914584e+00 -1.27942395e+00 8.73889029e-02 2.05163121e+00
9.79508340e-01 3.08097035e-01 8.46567899e-02 -2.25770921e-02
1.18124318e+00 5.34989059e-01 -8.65739703e-01 1.96661606e-01
-3.98665071e-01 -1.08843938e-01 2.70638973e-01 3.03738385e-01
-1.47726917e+00 9.36949730e-01 4.89769506e+00 1.22021115e+00
-1.36000907e+00 1.21640243e-01 1.04894519e+00 -5.23178279e-01
-4.54729646e-02 -8.93230811e-02 -8.99535477e-01 8.95785332e-01
7.21759200e-01 -2.94126064e-01 4.60764796e-01 1.00819027e+00
3.71090800e-01 -2.15225756e-01 -8.72072101e-01 1.24498713e+00
3.40030968e-01 -1.62793374e+00 2.60397673e-01 -4.76168782e-01
8.04581165e-01 4.42337021e-02 1.16970934e-01 3.06198508e-01
-2.79198140e-01 -7.03737915e-01 1.04911268e+00 7.57040560e-01
7.19515264e-01 -7.49981463e-01 6.86374605e-01 1.59021929e-01
-1.46108174e+00 -1.66869104e-01 -3.35436046e-01 -2.44736895e-01
2.10040018e-01 5.73223650e-01 -2.70445943e-01 3.03860694e-01
8.22097003e-01 1.24728537e+00 -4.94256794e-01 8.76302004e-01
-2.17481866e-01 6.92510843e-01 -6.80308342e-02 -9.38724726e-02
2.84899056e-01 -3.69473994e-02 7.31584966e-01 1.20196354e+00
1.01099744e-01 2.80410707e-01 4.20924485e-01 7.02407360e-01
-1.48727447e-01 -2.01211929e-01 -1.97107926e-01 1.61780447e-01
4.73711461e-01 1.22280920e+00 -8.50498676e-01 -8.25513899e-01
-5.03461003e-01 7.30871499e-01 1.12757161e-01 3.82523775e-01
-1.15309632e+00 -3.95259857e-01 8.46156836e-01 -2.02486262e-01
4.68066573e-01 1.49133354e-01 -2.67049849e-01 -1.48776126e+00
9.08980146e-02 -9.12294388e-01 3.85292232e-01 -8.20089340e-01
-9.22679782e-01 3.61269295e-01 -1.22195773e-01 -1.31462646e+00
-6.36833087e-02 -2.77696401e-01 -5.35244703e-01 7.28552520e-01
-1.85685861e+00 -8.05942655e-01 -5.70235312e-01 6.67946696e-01
1.10636985e+00 -2.20893458e-01 1.94443345e-01 4.18468684e-01
-9.25765812e-01 5.36484241e-01 -2.98825115e-01 1.80855334e-01
5.28201759e-01 -7.83837676e-01 6.64601475e-02 1.31474543e+00
-1.72772110e-01 3.58834356e-01 6.48763537e-01 -6.78731680e-01
-1.46180868e+00 -1.26482832e+00 5.60409844e-01 6.31933659e-02
4.61577833e-01 -1.13911226e-01 -9.99220252e-01 3.20887417e-01
1.84042171e-01 2.89862990e-01 2.94722766e-01 -5.63600600e-01
-8.70171934e-02 -2.91731834e-01 -9.84805226e-01 7.92642891e-01
1.09011853e+00 -5.41494071e-01 -4.55252141e-01 1.32423624e-01
8.19772720e-01 -3.32578361e-01 -3.74795437e-01 6.33612454e-01
4.17627633e-01 -9.93842542e-01 9.87080038e-01 -4.68657047e-01
6.78294718e-01 -6.06808186e-01 -1.67320296e-01 -7.76521623e-01
-4.40727532e-01 -4.87485439e-01 -5.94016254e-01 9.71778870e-01
-7.97529966e-02 -3.30510408e-01 8.47134888e-01 2.83619672e-01
-2.32045487e-01 -9.88937318e-01 -8.51379991e-01 -4.33183849e-01
-7.20810652e-01 -2.03090072e-01 2.59471744e-01 9.07559812e-01
-1.36105210e-01 4.39541638e-01 -5.61376214e-01 2.52667487e-01
7.68340409e-01 2.59633541e-01 2.61279374e-01 -9.13007140e-01
3.38622071e-02 -5.81050158e-01 -5.62337875e-01 -1.12068808e+00
2.23377481e-01 -5.47992706e-01 1.19692594e-01 -1.03794694e+00
6.09807909e-01 -7.92953093e-03 -8.20444286e-01 6.19724929e-01
-5.31509578e-01 4.54318941e-01 3.57371747e-01 2.28955299e-01
-1.22637165e+00 7.10110605e-01 1.23512089e+00 -2.25852296e-01
9.62720998e-03 -2.94028610e-01 -7.00958490e-01 8.53139937e-01
9.22715783e-01 -2.22823918e-01 -5.27835727e-01 -4.44469631e-01
-3.99591863e-01 5.20286635e-02 5.57898045e-01 -1.27512705e+00
4.00307477e-01 -5.66968620e-01 4.97870833e-01 -6.25024080e-01
3.27754617e-01 -4.42204118e-01 -1.93972945e-01 5.12126982e-01
-4.76125628e-01 -6.04403913e-02 1.54681981e-01 5.99960685e-01
-3.69604051e-01 -9.02783871e-03 9.78812993e-01 -4.13333662e-02
-1.28376532e+00 5.02959132e-01 -2.45064378e-01 1.59667790e-01
1.16466188e+00 -2.03394488e-01 -4.14464056e-01 -3.26832503e-01
-3.40589672e-01 3.84181023e-01 3.26857716e-01 6.17877424e-01
1.01680291e+00 -1.33632910e+00 -6.71205282e-01 3.48475367e-01
-1.35983422e-01 -1.54909521e-01 6.54116273e-01 9.87425268e-01
-2.71850914e-01 5.31526029e-01 -4.18959349e-01 -7.38673389e-01
-1.40038419e+00 5.57000756e-01 1.60104319e-01 1.56067804e-01
-3.08419228e-01 9.01762307e-01 6.03055477e-01 2.99251854e-01
3.72687638e-01 -1.24680154e-01 -3.87017995e-01 4.71907891e-02
1.02302599e+00 4.02561128e-01 -4.28711355e-01 -9.01205719e-01
-5.50691545e-01 1.95890516e-01 -1.54996604e-01 3.68000418e-01
1.24873412e+00 -1.47183329e-01 -7.74333403e-02 2.91043162e-01
9.57350969e-01 -5.01365900e-01 -1.74838436e+00 -4.04342353e-01
-2.46463597e-01 -7.67606616e-01 2.92828560e-01 -4.56474811e-01
-1.47309875e+00 6.38229311e-01 6.11442566e-01 2.85972804e-02
1.53999984e+00 -2.40919784e-01 7.40666032e-01 1.07620813e-01
2.59468734e-01 -1.18150616e+00 1.74390346e-01 4.88496423e-01
8.07343483e-01 -1.46636343e+00 2.34392025e-02 -3.96207005e-01
-7.47012913e-01 8.35030377e-01 9.98174965e-01 -2.23100916e-01
5.28825819e-01 6.96880743e-02 -2.06536829e-01 3.82009819e-02
-1.05756390e+00 -1.83476910e-01 4.43628341e-01 3.61613214e-01
1.96729392e-01 1.41282296e-02 -2.11747751e-01 4.88513410e-01
4.43115890e-01 1.91909015e-01 5.21474421e-01 9.85894442e-01
-6.24048054e-01 -3.48032594e-01 -2.25733712e-01 7.01861799e-01
-5.08709013e-01 -3.80754024e-01 1.47478864e-01 3.62570137e-01
7.20144436e-02 8.91381919e-01 2.25085363e-01 -4.30406123e-01
-2.49044280e-02 -3.08029830e-01 2.26105284e-02 -4.10206795e-01
-3.09194386e-01 1.01342238e-01 -1.77634448e-01 -7.79164612e-01
-9.11826372e-01 -7.78773546e-01 -1.21560824e+00 -2.68546909e-01
-2.27729827e-01 1.01080999e-01 1.43063709e-01 7.95961857e-01
5.79040527e-01 7.33525753e-01 6.00563467e-01 -1.35644710e+00
-3.73941213e-01 -7.61397541e-01 -4.65050101e-01 3.40071142e-01
5.90768933e-01 -8.26265991e-01 -3.45258474e-01 1.70686394e-01] | [9.516412734985352, -0.31090736389160156] |
21dd5f9e-6fc2-45cb-8e71-cdd8a436d684 | dual-teacher-exploiting-intra-domain-and | 2101.02375 | null | https://arxiv.org/abs/2101.02375v1 | https://arxiv.org/pdf/2101.02375v1.pdf | Dual-Teacher++: Exploiting Intra-domain and Inter-domain Knowledge with Reliable Transfer for Cardiac Segmentation | Annotation scarcity is a long-standing problem in medical image analysis area. To efficiently leverage limited annotations, abundant unlabeled data are additionally exploited in semi-supervised learning, while well-established cross-modality data are investigated in domain adaptation. In this paper, we aim to explore the feasibility of concurrently leveraging both unlabeled data and cross-modality data for annotation-efficient cardiac segmentation. To this end, we propose a cutting-edge semi-supervised domain adaptation framework, namely Dual-Teacher++. Besides directly learning from limited labeled target domain data (e.g., CT) via a student model adopted by previous literature, we design novel dual teacher models, including an inter-domain teacher model to explore cross-modality priors from source domain (e.g., MR) and an intra-domain teacher model to investigate the knowledge beneath unlabeled target domain. In this way, the dual teacher models would transfer acquired inter- and intra-domain knowledge to the student model for further integration and exploitation. Moreover, to encourage reliable dual-domain knowledge transfer, we enhance the inter-domain knowledge transfer on the samples with higher similarity to target domain after appearance alignment, and also strengthen intra-domain knowledge transfer of unlabeled target data with higher prediction confidence. In this way, the student model can obtain reliable dual-domain knowledge and yield improved performance on target domain data. We extensively evaluated the feasibility of our method on the MM-WHS 2017 challenge dataset. The experiments have demonstrated the superiority of our framework over other semi-supervised learning and domain adaptation methods. Moreover, our performance gains could be yielded in bidirections,i.e., adapting from MR to CT, and from CT to MR. | ['Pheng-Ann Heng', 'Lequan Yu', 'Shujun Wang', 'Kang Li'] | 2021-01-07 | null | null | null | null | ['cardiac-segmentation'] | ['medical'] | [ 4.39392924e-01 4.69326556e-01 -4.66539025e-01 -4.56459880e-01
-9.83796120e-01 -5.59501946e-01 2.50428677e-01 -1.41858971e-02
-5.08641481e-01 9.55692291e-01 -1.35694453e-02 -1.01985477e-01
-2.16872641e-03 -5.55479467e-01 -6.45888388e-01 -8.60389292e-01
2.85858333e-01 4.37987566e-01 4.30410802e-01 9.79163423e-02
-3.45719188e-01 8.49436745e-02 -9.39320207e-01 2.32072785e-01
1.24490094e+00 1.04317403e+00 4.69543278e-01 1.31903782e-01
-8.12902525e-02 5.09227037e-01 -1.83773547e-01 -2.05538318e-01
5.41533269e-02 -5.45393229e-01 -8.33579004e-01 4.31190431e-01
1.61468357e-01 -3.74298930e-01 -1.52899891e-01 9.82077181e-01
6.73639417e-01 -3.26966867e-02 7.23458350e-01 -9.18084919e-01
-5.10072649e-01 3.37497354e-01 -9.62331951e-01 2.94056803e-01
-1.85640991e-01 2.78348416e-01 5.95936477e-01 -8.30290139e-01
6.52447522e-01 7.52461135e-01 4.71597552e-01 5.65894842e-01
-1.15227473e+00 -8.23878169e-01 3.15116048e-01 4.27238606e-02
-1.22424483e+00 -2.78335303e-01 1.09374237e+00 -4.54199255e-01
1.78180322e-01 -9.48797539e-02 4.15412843e-01 1.19187152e+00
-3.06024432e-01 1.26447916e+00 1.30728590e+00 -4.12547201e-01
-2.55136490e-02 4.12503779e-01 2.57762466e-02 6.92124605e-01
-7.54803047e-03 1.52980849e-01 -3.46646756e-01 -1.24698281e-01
8.87696981e-01 -1.08721741e-01 -4.82784212e-01 -6.39417768e-01
-1.39159262e+00 5.71060419e-01 4.26748991e-01 3.71563047e-01
-4.53338236e-01 -4.99556482e-01 5.52124619e-01 -1.06967706e-02
6.85131788e-01 5.16276807e-02 -8.05205166e-01 1.61322564e-01
-9.73588228e-01 -3.93643200e-01 4.34081048e-01 1.14867878e+00
7.87608504e-01 -1.73064023e-02 -3.02760720e-01 1.15138900e+00
3.86345774e-01 5.02578020e-01 8.00327659e-01 -5.73588610e-01
6.51548684e-01 6.06546998e-01 -2.14698166e-01 -3.19694310e-01
-4.30443823e-01 -7.06501603e-01 -1.05261338e+00 -1.14616349e-01
6.95726871e-01 -3.61624002e-01 -1.17340016e+00 1.86116159e+00
7.18827069e-01 6.14650071e-01 1.98996857e-01 1.05724561e+00
9.04999375e-01 2.56771982e-01 3.56405884e-01 -5.74788690e-01
1.60686421e+00 -1.09166646e+00 -5.99640846e-01 -1.42754853e-01
8.82309794e-01 -6.17385209e-01 1.04554760e+00 3.13848555e-01
-8.19463253e-01 -8.10306668e-01 -8.44866276e-01 2.61219740e-01
9.75465700e-02 4.53440309e-01 3.97509694e-01 4.89559889e-01
-5.38094699e-01 2.33071327e-01 -1.07951152e+00 -1.76526353e-01
8.40919316e-01 3.41595531e-01 -4.86716837e-01 -3.26757580e-01
-1.15809011e+00 7.37677217e-01 8.37782860e-01 2.07154825e-02
-9.81915176e-01 -9.59150553e-01 -7.86373556e-01 -3.04713011e-01
7.49119520e-01 -6.36157691e-01 1.11106026e+00 -1.28343713e+00
-1.44996083e+00 1.00055540e+00 8.79096016e-02 -2.71234900e-01
4.87867713e-01 -8.77877623e-02 -4.59584951e-01 4.85715896e-01
2.01477960e-01 7.21807539e-01 8.92380416e-01 -1.35688531e+00
-6.66847169e-01 -5.83815336e-01 -1.73838928e-01 4.26067621e-01
-5.77484727e-01 -4.51484740e-01 -5.61034203e-01 -8.77588987e-01
1.43037438e-01 -1.05797458e+00 -1.23295411e-01 3.06879403e-03
-3.04052800e-01 -1.37759820e-01 7.99170136e-01 -8.09951901e-01
9.78276491e-01 -2.21315241e+00 1.11298740e-01 1.76269680e-01
3.17118764e-01 4.71978605e-01 -6.67376816e-02 -3.91550660e-01
-2.12873608e-01 -1.63733751e-01 -6.21877074e-01 -6.82000816e-02
-3.72488052e-01 4.60359663e-01 4.38330248e-02 4.57847893e-01
4.14618671e-01 9.29166675e-01 -1.00626600e+00 -1.02670169e+00
5.13250269e-02 2.30032936e-01 -4.70731497e-01 4.34551537e-01
-6.84365407e-02 1.26908708e+00 -9.88333404e-01 7.01974571e-01
7.40264118e-01 -5.28528035e-01 3.04443389e-01 -5.46298087e-01
2.96091765e-01 -1.81004256e-01 -9.66979206e-01 2.10274577e+00
-4.80056196e-01 1.85854267e-02 1.85038686e-01 -1.39969063e+00
8.69452178e-01 5.77348948e-01 7.26583838e-01 -8.60447586e-01
-1.48547385e-02 3.49430442e-01 7.56580606e-02 -6.87443078e-01
-3.45553309e-02 -5.29688776e-01 2.70819426e-01 2.70254493e-01
4.33355361e-01 4.97308075e-02 -1.03604086e-01 9.72143710e-02
6.00116968e-01 4.97906089e-01 2.75399297e-01 -2.01227441e-01
7.69628167e-01 1.80808771e-02 7.93313444e-01 4.20517713e-01
-4.83507246e-01 6.56243801e-01 1.21791929e-01 -5.95870502e-02
-6.47531152e-01 -1.02352798e+00 -3.27028662e-01 9.86020982e-01
3.58379364e-01 1.12228826e-01 -6.05974019e-01 -1.38135958e+00
-2.12139741e-01 3.92577142e-01 -5.90571821e-01 -3.38533908e-01
-6.46351516e-01 -9.21830356e-01 6.19941175e-01 8.81114542e-01
6.26927972e-01 -9.25886154e-01 -4.52364653e-01 2.89713770e-01
-4.49196428e-01 -1.20496953e+00 -5.63514709e-01 4.18791652e-01
-1.37151098e+00 -1.08379722e+00 -1.36343789e+00 -8.72429669e-01
8.13073695e-01 4.28441679e-03 1.10096872e+00 -1.60426766e-01
-6.41120076e-02 5.47971547e-01 -4.58546221e-01 -2.14220092e-01
-2.17334405e-01 2.20339388e-01 -1.39730617e-01 2.07537189e-01
1.49613112e-01 -5.32191455e-01 -7.17252612e-01 5.27885914e-01
-9.86549735e-01 1.16225362e-01 9.28069115e-01 1.25311971e+00
9.25588965e-01 -1.90451086e-01 8.06154668e-01 -1.19431150e+00
7.07213879e-02 -5.81952989e-01 -3.55763018e-01 4.79011148e-01
-5.46990931e-01 -1.05102789e-02 4.23540115e-01 -7.70126998e-01
-1.59756660e+00 4.08281952e-01 -1.71077847e-01 -5.04878521e-01
-3.58499140e-01 7.41110146e-01 -4.42354888e-01 9.54439715e-02
6.19013906e-01 4.05156612e-01 7.06815049e-02 -4.53078389e-01
3.53707969e-01 5.77646971e-01 6.11619949e-01 -1.06179512e+00
6.59372032e-01 5.58577478e-01 -2.34220639e-01 -4.72316653e-01
-9.76610363e-01 -6.20485365e-01 -9.31764483e-01 -2.14044265e-02
9.44379866e-01 -1.10256541e+00 -1.14170171e-01 5.26475132e-01
-8.43603730e-01 -4.49524730e-01 -3.84334564e-01 8.20161581e-01
-4.97002751e-01 7.01993644e-01 -4.16163325e-01 -4.66521502e-01
-2.33131781e-01 -1.27322996e+00 1.10577071e+00 3.71729106e-01
1.44369453e-01 -1.30080795e+00 3.37198041e-02 5.38619757e-01
4.07816954e-02 1.22085392e-01 6.66280866e-01 -9.91288900e-01
-2.37873808e-01 3.22770417e-01 -4.49527174e-01 4.95615423e-01
3.27915132e-01 -6.21943235e-01 -9.96777356e-01 -3.66073191e-01
8.42178091e-02 -7.09877729e-01 8.65035594e-01 4.10894632e-01
1.23486996e+00 1.28185362e-01 -4.96984899e-01 5.91597855e-01
1.06465185e+00 1.82740241e-02 3.07370871e-01 1.84886009e-01
7.82361627e-01 6.94464266e-01 1.06391490e+00 4.45818901e-01
5.26637018e-01 6.98394537e-01 2.39958912e-01 -5.14234841e-01
-2.33960658e-01 -1.69994339e-01 3.69424447e-02 7.69348323e-01
-9.27721933e-02 5.36168665e-02 -1.05040050e+00 5.91931820e-01
-1.74418831e+00 -3.46146822e-01 5.54193221e-02 1.99822056e+00
1.27143788e+00 8.80749747e-02 2.28884056e-01 -2.00770780e-01
7.05973029e-01 -1.82665497e-01 -8.03130329e-01 5.23292124e-01
1.35818636e-02 1.35191351e-01 5.19381881e-01 6.38112575e-02
-1.31512594e+00 7.74624944e-01 4.35969114e+00 1.16804159e+00
-1.17738557e+00 4.98733789e-01 8.36974502e-01 3.10843229e-01
-1.53772131e-01 -1.44340336e-01 -6.93045318e-01 4.74640608e-01
6.40697241e-01 1.03198059e-01 -1.60445556e-01 8.21293175e-01
4.72483300e-02 -9.67121944e-02 -9.81669903e-01 7.79508829e-01
-6.94896057e-02 -8.94991755e-01 -2.42703632e-01 1.34373918e-01
7.65632987e-01 -1.48649335e-01 6.46612607e-03 6.39839172e-01
9.77524072e-02 -5.91460764e-01 2.96048343e-01 2.49543443e-01
1.07021451e+00 -4.69112068e-01 8.36126924e-01 5.56783259e-01
-1.12539256e+00 2.20142037e-01 -9.89214629e-02 6.11722350e-01
2.90789187e-01 7.64281154e-01 -7.80854046e-01 1.14633155e+00
5.51819980e-01 9.66635764e-01 -4.82983023e-01 8.80596936e-01
-2.23784059e-01 9.00519431e-01 -2.56300896e-01 6.94064736e-01
1.40097708e-01 -2.27252498e-01 2.52936363e-01 1.06333888e+00
1.80054516e-01 4.78989571e-01 6.18901849e-01 6.55051529e-01
-4.28328030e-02 1.14521161e-01 -2.82183975e-01 1.97408020e-01
2.64326543e-01 1.26274490e+00 -6.67914450e-01 -6.17288649e-01
-4.98463005e-01 8.94570947e-01 2.46683285e-01 4.56578463e-01
-1.04074037e+00 3.81193236e-02 -7.41176903e-02 -2.45392304e-02
3.19651455e-01 6.62046373e-02 -2.79428780e-01 -1.36130691e+00
3.27613875e-02 -7.91919768e-01 8.20935726e-01 -5.08373380e-01
-1.55242670e+00 6.29702210e-01 2.17710808e-01 -1.58685112e+00
6.63465932e-02 -4.47539896e-01 -3.41561347e-01 9.73873556e-01
-2.09664989e+00 -1.55887401e+00 -4.00515974e-01 9.14663136e-01
4.53400373e-01 -1.33384213e-01 5.47460377e-01 6.72288299e-01
-4.83140856e-01 8.20146680e-01 5.96622471e-03 2.50418007e-01
1.11658776e+00 -1.17417979e+00 -4.72717822e-01 4.50379521e-01
-7.24411570e-03 4.31269288e-01 3.19186524e-02 -6.75192237e-01
-9.83699441e-01 -1.26011920e+00 -1.53263081e-02 -2.24408478e-01
5.41750789e-01 1.61729500e-01 -1.31556475e+00 6.40156925e-01
-1.08673833e-01 6.02380931e-01 8.49768341e-01 7.88882077e-02
-2.16314107e-01 -1.38441131e-01 -1.24324477e+00 2.05663919e-01
8.27002943e-01 -4.39198941e-01 -6.39835536e-01 2.32934341e-01
6.76252365e-01 -7.91087151e-01 -1.27206600e+00 8.08745265e-01
4.34292793e-01 -5.14955461e-01 9.83055651e-01 -5.20153821e-01
3.79825503e-01 -3.73104244e-01 5.06137162e-02 -1.24569070e+00
-2.86184419e-02 -1.03170291e-01 -2.77419686e-01 1.49953592e+00
3.80163580e-01 -4.73381996e-01 9.82149065e-01 3.42959046e-01
-4.81926113e-01 -8.14099133e-01 -9.53641772e-01 -7.47702897e-01
3.83059531e-01 -3.10477108e-01 1.38105482e-01 1.25154078e+00
-1.43517047e-01 2.83814222e-01 -3.84538203e-01 3.65543902e-01
5.56312025e-01 1.58402607e-01 5.23908317e-01 -1.03748834e+00
-5.65828979e-01 -6.40561134e-02 -3.10749747e-02 -1.33398449e+00
2.60263413e-01 -1.06675506e+00 3.24398652e-02 -1.13845623e+00
4.19154853e-01 -8.13290775e-01 -6.83509409e-01 6.35548234e-01
-6.69690371e-01 4.60273683e-01 6.69474378e-02 3.49592000e-01
-7.42221832e-01 8.17158043e-01 1.88201499e+00 -1.91806540e-01
-1.87493905e-01 1.34706676e-01 -6.55736208e-01 7.05189586e-01
7.09336162e-01 -5.24544001e-01 -6.06191039e-01 -3.68169457e-01
-5.43315589e-01 3.28395128e-01 4.50406075e-01 -6.54353440e-01
9.34219807e-02 -3.02521698e-03 4.32419002e-01 -5.01524210e-01
7.70224407e-02 -1.03123617e+00 -3.30286711e-01 2.83115178e-01
-1.60973057e-01 -6.76740348e-01 2.69265532e-01 8.87977540e-01
-4.61019367e-01 -1.64557904e-01 9.64099050e-01 -1.57182381e-01
-8.09504271e-01 4.61721927e-01 1.87893480e-01 4.54007834e-01
1.07401931e+00 -2.37722218e-01 -8.63386542e-02 4.17447761e-02
-1.28750050e+00 5.92266202e-01 1.29484728e-01 2.30730802e-01
5.14676929e-01 -1.23267353e+00 -7.03262925e-01 3.49867344e-02
3.99290442e-01 4.40546155e-01 6.12078607e-01 1.44133139e+00
1.35861486e-01 1.52913377e-01 -3.12339395e-01 -1.09525704e+00
-1.00716555e+00 7.02143371e-01 2.95513958e-01 -6.67634308e-01
-4.93063092e-01 7.25888610e-01 8.08257818e-01 -7.82467127e-01
5.27446829e-02 -1.80217594e-01 -2.55506873e-01 1.10787131e-01
3.35232496e-01 4.69605140e-02 1.46194637e-01 -5.54846048e-01
-4.62054431e-01 6.52161539e-01 -2.12796986e-01 9.03960690e-02
1.13799584e+00 -2.36309066e-01 2.99971998e-01 1.96250111e-01
1.05460799e+00 -2.49533132e-01 -1.57529438e+00 -7.75088847e-01
1.58768430e-01 -1.43752068e-01 5.29757654e-03 -1.10130835e+00
-1.38568270e+00 1.03850842e+00 8.76259685e-01 -5.18800080e-01
1.42314887e+00 1.66105002e-01 7.56686568e-01 -8.39924663e-02
3.01209599e-01 -9.21877027e-01 3.05929869e-01 1.00723155e-01
4.63918269e-01 -1.81768811e+00 -1.36615848e-02 -6.44835949e-01
-1.17644644e+00 9.70528841e-01 9.16707635e-01 3.56760144e-01
7.11325526e-01 3.64835635e-02 2.18289122e-01 -1.21837251e-01
-3.81823570e-01 -2.67067730e-01 6.06540978e-01 7.78628409e-01
5.09732425e-01 4.39196499e-03 -1.64067686e-01 9.74505782e-01
5.36145270e-01 3.21843565e-01 1.01374879e-01 8.46390367e-01
-1.66226894e-01 -1.25686800e+00 -3.64982307e-01 3.71951312e-01
-4.04320091e-01 -1.07933179e-01 1.76543504e-01 8.41768324e-01
4.34919566e-01 7.01012373e-01 -3.89822513e-01 -6.52347272e-03
3.03711861e-01 -3.46930400e-02 4.61050153e-01 -8.16768348e-01
-4.24095660e-01 4.67557460e-01 -1.04627661e-01 -1.42809793e-01
-7.23640859e-01 -5.14796555e-01 -1.35986578e+00 4.97436404e-01
-5.93670368e-01 1.94683060e-01 2.84081727e-01 1.18818521e+00
1.99150443e-01 7.47210264e-01 5.95404506e-01 -6.25080705e-01
-6.67317271e-01 -9.26089108e-01 -5.53780317e-01 2.76524723e-01
2.14913324e-01 -8.30500662e-01 8.20640326e-02 5.09283721e-01] | [14.650004386901855, -2.026695966720581] |
2a937af6-e9c0-4976-b24c-86d376145a94 | predicting-gender-from-iris-texture-may-be | 1811.10066 | null | http://arxiv.org/abs/1811.10066v1 | http://arxiv.org/pdf/1811.10066v1.pdf | Predicting Gender from Iris Texture May Be Harder Than It Seems | Predicting gender from iris images has been reported by several researchers
as an application of machine learning in biometrics. Recent works on this topic
have suggested that the preponderance of the gender cues is located in the
periocular region rather than in the iris texture itself. This paper focuses on
teasing out whether the information for gender prediction is in the texture of
the iris stroma, the periocular region, or both. We present a larger dataset
for gender from iris, and evaluate gender prediction accuracy using linear SVM
and CNN, comparing hand-crafted and deep features. We use probabilistic
occlusion masking to gain insight on the problem. Results suggest the
discriminative power of the iris texture for gender is weaker than previously
thought, and that the gender-related information is primarily in the periocular
region. | ['Kevin Bowyer', 'Andrey Kuehlkamp'] | 2018-11-25 | null | null | null | null | ['gender-prediction'] | ['computer-vision'] | [ 5.10207079e-02 2.91672498e-01 -5.46506643e-01 -5.03655314e-01
-1.94435809e-02 -4.94178832e-01 5.74928939e-01 3.84439856e-01
-2.49107167e-01 4.19338822e-01 4.32489365e-01 -3.54453623e-01
-9.54245105e-02 -4.24811304e-01 -3.24649483e-01 -1.12064457e+00
1.00164071e-01 3.36956084e-01 -3.33243221e-01 1.53990716e-01
5.83767235e-01 5.05465865e-01 -1.75163567e+00 1.96920067e-01
6.31877184e-01 9.24440205e-01 -3.74838471e-01 5.16396582e-01
1.87157378e-01 3.30659628e-01 -6.35782599e-01 -4.94812489e-01
2.64718771e-01 -5.43220282e-01 -5.02426982e-01 1.40191749e-01
1.02771401e+00 -3.29895645e-01 -6.11567274e-02 1.04667842e+00
4.79791313e-01 -3.80913436e-01 7.81869113e-01 -7.62108743e-01
-3.92582744e-01 1.59588546e-01 -1.15401840e+00 2.75913179e-01
3.29853557e-02 1.33974701e-01 8.99682760e-01 -4.91941452e-01
5.39603293e-01 1.08354926e+00 4.86080050e-01 5.68548083e-01
-1.24404871e+00 -7.06763506e-01 -3.11720073e-01 -6.53930567e-03
-1.47279894e+00 -4.87004310e-01 4.86462682e-01 -8.76164675e-01
3.67415994e-01 5.38506687e-01 7.95460224e-01 8.44212770e-01
5.40329814e-01 5.91772616e-01 2.02458215e+00 -4.49258149e-01
-1.99704692e-01 5.06860793e-01 -9.01177302e-02 5.97358763e-01
3.30464810e-01 7.36573040e-01 -7.05291569e-01 -2.09066093e-01
7.01668203e-01 -4.60297316e-01 -1.35750547e-02 -6.61143288e-02
-7.92730927e-01 7.32231796e-01 -3.81409749e-02 2.50184894e-01
-7.23286942e-02 -2.64617354e-01 3.37074965e-01 -1.86448134e-02
6.35935783e-01 4.61585939e-01 -6.39995039e-01 -2.38943323e-01
-1.31560063e+00 -2.72375578e-03 6.24872983e-01 1.34327546e-01
4.29803520e-01 -3.89950067e-01 -2.87175626e-01 7.28634179e-01
4.83089626e-01 3.65432978e-01 1.74887210e-01 -7.75597930e-01
3.46119292e-02 6.00599527e-01 -8.45300183e-02 -8.78640413e-01
-2.85847068e-01 -4.63415265e-01 -4.75840598e-01 4.13584352e-01
1.13070357e+00 -5.21004163e-02 -8.73643696e-01 1.43767178e+00
5.03713667e-01 -2.64293980e-02 -5.35804987e-01 1.13583362e+00
9.82808828e-01 -4.84230183e-02 1.31334603e-01 5.62440716e-02
1.58313358e+00 -4.56029534e-01 -3.02204013e-01 -1.82692975e-01
3.12274098e-01 -1.11353111e+00 5.61655700e-01 4.06344086e-01
-6.89058244e-01 -4.30840820e-01 -7.51794279e-01 -1.84903204e-01
-1.71516478e-01 7.33099878e-01 7.89988220e-01 1.16785228e+00
-7.58987904e-01 6.75482094e-01 -7.11118102e-01 -4.80729729e-01
3.53460491e-01 7.66001642e-01 -4.32479471e-01 3.19477439e-01
-5.19772708e-01 1.02614892e+00 -1.31382242e-01 2.08463296e-01
-6.83775544e-02 -4.40482378e-01 -9.46969688e-01 -2.25630507e-01
-3.60038936e-01 -5.58235705e-01 7.56592870e-01 -1.17433453e+00
-1.29785061e+00 1.47455561e+00 -7.01909781e-01 -5.01860082e-02
2.43973494e-01 2.75097877e-01 -2.13463575e-01 2.11192578e-01
-7.96065927e-02 5.45459807e-01 9.69554424e-01 -1.02737641e+00
-7.35494673e-01 -1.06917799e+00 -3.47983003e-01 -4.99869101e-02
7.54422098e-02 3.62592548e-01 -5.17368428e-02 -5.71776390e-01
2.43146569e-01 -1.06464589e+00 2.38465071e-02 -1.79578811e-01
-4.22591984e-01 -4.83791620e-01 3.79743516e-01 -9.21953976e-01
1.07694638e+00 -2.13857818e+00 -1.83656216e-01 5.15517116e-01
6.07032001e-01 1.04350351e-01 1.22620441e-01 3.10314387e-01
-3.03161144e-01 -6.42951159e-03 3.92371327e-01 -3.10295910e-01
-1.74564525e-01 6.32023364e-02 -3.18942726e-01 1.05301976e+00
1.45035073e-01 7.18735993e-01 -3.42305541e-01 -5.67381024e-01
1.37008846e-01 3.92171383e-01 -2.71684349e-01 -3.83290052e-01
2.12538287e-01 1.00356960e+00 -2.09731415e-01 1.17837024e+00
8.75484526e-01 -2.06001773e-02 2.65309304e-01 -1.31374538e-01
-1.94946647e-01 2.98468977e-01 -7.70694733e-01 1.21375000e+00
1.14398815e-01 1.07628286e+00 1.29508944e-02 -6.66347682e-01
8.37765872e-01 -1.94302406e-02 3.28269035e-01 -6.55181527e-01
4.40672398e-01 2.71681100e-01 7.06490040e-01 -4.72730488e-01
4.01268154e-01 -3.26286435e-01 3.72187108e-01 2.86319762e-01
9.86932591e-02 2.38338113e-01 8.31073299e-02 -4.77671683e-01
3.18245739e-01 1.71320051e-01 2.22790629e-01 -4.03693914e-01
2.38380432e-01 -1.23863652e-01 4.70636904e-01 5.61267495e-01
-3.99515629e-01 6.99783444e-01 9.14194763e-01 -4.37319249e-01
-9.05962288e-01 -6.08174860e-01 -1.11758566e+00 7.80033529e-01
2.37324461e-01 -4.18561786e-01 -7.02468514e-01 -6.23757064e-01
3.43515784e-01 1.07985824e-01 -1.02304447e+00 8.21895804e-03
-1.83905274e-01 -1.03055859e+00 3.23692858e-01 2.89033651e-01
4.89658378e-02 -3.36326659e-01 -3.18311334e-01 -4.15418237e-01
1.66283086e-01 -7.13125527e-01 -2.76417464e-01 -1.27032846e-01
-9.67258930e-01 -1.26036704e+00 -5.04929483e-01 -5.50110996e-01
8.99887741e-01 -4.02169704e-01 9.95620430e-01 3.93495634e-02
-4.99487251e-01 1.13696858e-01 1.75065458e-01 -6.34173095e-01
-5.43978885e-02 -9.53325108e-02 4.34767939e-02 3.39462578e-01
1.14808166e+00 -2.90000856e-01 -8.58900368e-01 3.48664254e-01
-1.19790778e-01 -2.75613457e-01 6.66894495e-01 9.74990964e-01
4.20149326e-01 1.27908140e-01 -1.14842013e-01 -8.88304889e-01
9.89257321e-02 -4.85472679e-01 -5.06221533e-01 -1.56335130e-01
-7.52068520e-01 -1.52539521e-01 -1.14094354e-01 -3.95566255e-01
-6.86008513e-01 -1.00410633e-01 -1.11344390e-01 -1.15540773e-01
-4.09134865e-01 3.81777197e-01 9.70023796e-02 -4.74203736e-01
4.73978907e-01 7.62567148e-02 4.90064412e-01 -4.91793543e-01
-2.83656269e-01 8.61148596e-01 2.25849658e-01 -8.45147669e-01
4.23425347e-01 6.85913503e-01 4.08176869e-01 -8.24970186e-01
-8.51648271e-01 -5.29389501e-01 -4.44647402e-01 -7.56566897e-02
7.91622162e-01 -7.45672286e-01 -1.02713287e+00 2.92815804e-01
-6.52187884e-01 -1.16138101e-01 -2.57874101e-01 8.65320146e-01
-3.02857161e-01 1.81399107e-01 -7.46137440e-01 -7.89486825e-01
6.59105405e-02 -1.23672819e+00 1.24852109e+00 6.09127641e-01
-6.19049430e-01 -1.06826580e+00 1.28043056e-01 8.10870409e-01
1.60052568e-01 2.38645643e-01 8.38279307e-01 -7.14215100e-01
-4.66896832e-01 -3.12539548e-01 -5.11719406e-01 6.60068989e-02
7.51200467e-02 5.56354702e-01 -1.35260463e+00 -1.45397916e-01
-6.18464202e-02 -1.27212167e-01 1.08794284e+00 9.24270988e-01
1.22105491e+00 -1.00259252e-01 -3.88528824e-01 7.27859676e-01
1.22481132e+00 1.46325529e-01 6.87846541e-01 1.46313921e-01
4.05546457e-01 1.28455949e+00 6.24789357e-01 3.61477822e-01
4.38069195e-01 5.41020215e-01 2.28977710e-01 -5.54330230e-01
-1.35466397e-01 -1.53176174e-01 -2.04009339e-01 8.99956152e-02
-4.62548107e-01 3.31301719e-01 -9.34962511e-01 6.07651830e-01
-1.47307992e+00 -5.42726457e-01 -3.00643116e-01 2.42495370e+00
8.24725091e-01 -1.77162066e-01 3.11440378e-01 -1.11961566e-01
6.47847712e-01 -1.08666591e-01 -3.94169539e-01 -5.17918110e-01
-2.60983318e-01 4.76626515e-01 6.67240262e-01 3.89175624e-01
-1.08481395e+00 5.79706430e-01 7.38434649e+00 8.59160423e-01
-1.67867875e+00 -4.50029016e-01 1.26069033e+00 -2.82235354e-01
8.42886716e-02 1.16618894e-01 -1.02932262e+00 5.68791032e-01
6.92652643e-01 2.73949653e-01 1.77837789e-01 5.12219906e-01
8.89058486e-02 -6.70114696e-01 -1.04439342e+00 8.94720018e-01
1.07269548e-01 -8.92690599e-01 -5.40082753e-01 8.21595967e-01
4.07083750e-01 -1.08034179e-01 6.71018839e-01 -2.40003124e-01
-4.85117823e-01 -1.58184314e+00 3.78228515e-01 5.37460625e-01
9.73187506e-01 -5.16997874e-01 1.02567899e+00 -1.43704787e-01
-6.09613180e-01 -1.16966046e-01 -1.75332338e-01 -2.69076854e-01
-6.74919665e-01 5.43729365e-01 -1.06051600e+00 -1.42568916e-01
7.40283549e-01 7.42964149e-01 -1.02566803e+00 1.21048379e+00
-8.04080814e-02 8.10348511e-01 -1.66188300e-01 1.75100431e-01
-2.81212240e-01 -3.92950177e-01 6.43169880e-01 7.85640955e-01
2.11050138e-01 -1.42265841e-01 -2.63375491e-01 9.78474557e-01
4.28290993e-01 3.96887392e-01 -4.66365308e-01 -4.41212595e-01
-4.81537618e-02 1.43937063e+00 -9.18502629e-01 3.09681781e-02
-6.47052050e-01 3.94628763e-01 -2.77488649e-01 3.28238308e-01
-2.34029561e-01 -2.19191208e-01 9.28580225e-01 4.49701846e-01
1.09618261e-01 4.65634614e-02 -9.38550830e-01 -9.84088838e-01
-1.09431669e-01 -7.51927316e-01 1.96450576e-01 -4.00710285e-01
-1.06860888e+00 1.02845713e-01 -3.96130204e-01 -1.10300601e+00
-1.07332624e-01 -1.03443301e+00 -4.81942028e-01 1.40716207e+00
-1.27342713e+00 -1.39922166e+00 -7.52505958e-02 9.93801728e-02
-2.54928708e-01 -4.37492996e-01 8.24157715e-01 1.16302744e-01
-6.64513350e-01 6.76970720e-01 -1.16038054e-01 1.81600094e-01
1.08668292e+00 -1.49030352e+00 -2.20947742e-01 4.18120295e-01
1.13812432e-01 1.09258342e+00 9.50129867e-01 -5.24032474e-01
-1.03178287e+00 -4.22824800e-01 1.22159088e+00 -8.47785830e-01
4.80201006e-01 -1.33399382e-01 -4.14574385e-01 3.13572288e-01
3.81695032e-01 -6.77862242e-02 1.28973365e+00 7.37751722e-01
-4.28258061e-01 -5.85368462e-02 -1.22704422e+00 3.13618153e-01
3.01894248e-01 -7.18660772e-01 -3.65617007e-01 5.36192991e-02
-2.38612145e-01 -7.67256737e-01 -1.13926744e+00 5.80069482e-01
9.26700830e-01 -1.16703522e+00 6.55113637e-01 -5.08572340e-01
7.93247461e-01 -2.96999991e-01 3.99202816e-02 -8.85203242e-01
9.31129232e-03 -2.31911883e-01 8.62609036e-03 1.15898228e+00
2.77822137e-01 -6.23524010e-01 1.18360138e+00 6.49633706e-01
1.57056466e-01 -1.05592120e+00 -9.00686681e-01 -1.86807111e-01
2.55055308e-01 1.40152067e-01 4.81547803e-01 9.88836110e-01
-3.67334895e-02 1.14387058e-01 6.20418508e-03 1.42169312e-01
4.91443753e-01 7.08317935e-01 6.66967392e-01 -1.30913079e+00
-4.76180732e-01 -5.94714403e-01 -7.24775493e-01 -5.05606174e-01
3.02149802e-01 -6.70866966e-01 -4.86541659e-01 -9.72945690e-01
3.83822829e-01 -4.02225494e-01 -2.57324398e-01 4.75266993e-01
-3.66694964e-02 7.86645651e-01 -1.53455213e-01 2.08557695e-02
2.29700148e-01 -1.48912728e-01 1.62068224e+00 -1.79405361e-01
-1.10642664e-01 3.47467750e-01 -1.05101025e+00 7.92064786e-01
7.14947581e-01 -1.49032235e-01 -5.97870834e-02 2.70250700e-02
2.45484978e-01 1.41920120e-01 4.82044160e-01 -3.43779117e-01
1.45079866e-01 -1.39243051e-01 8.72627497e-01 -4.72375244e-01
4.17301297e-01 -4.51121062e-01 -2.70366371e-01 1.54247746e-01
4.11587283e-02 -5.85204720e-01 3.57691914e-01 -4.65449914e-02
-4.28216815e-01 -6.27729744e-02 8.38942051e-01 3.51448655e-02
-2.20351189e-01 4.41083685e-02 -2.08904430e-01 -1.40162989e-01
6.44861519e-01 -5.81119478e-01 -4.23209667e-01 -7.25721568e-02
-1.08809674e+00 -1.94782704e-01 7.77805209e-01 2.12135911e-01
1.01302035e-01 -8.18792403e-01 -5.63742578e-01 6.32824659e-01
2.82196760e-01 -7.82389522e-01 1.76039934e-01 1.54234731e+00
-3.69162381e-01 6.34848177e-01 -2.25978926e-01 -9.07268107e-01
-1.67123735e+00 1.66172281e-01 5.89755237e-01 2.81342983e-01
-4.48170491e-02 1.13185775e+00 2.47919962e-01 -2.55669951e-01
1.69399723e-01 -1.58782318e-01 -5.53371787e-01 4.56407756e-01
4.93876249e-01 2.56516844e-01 4.20503691e-02 -8.30461442e-01
-3.00172448e-01 9.10829246e-01 -4.09069508e-02 8.98900330e-02
9.67551351e-01 -1.35105357e-01 -8.58381569e-01 3.33332986e-01
9.48490918e-01 6.52970433e-01 -8.35079432e-01 -4.32815496e-03
-1.78299725e-01 -1.08911407e+00 1.52290270e-01 -1.00828433e+00
-1.10984719e+00 8.76615882e-01 1.04739749e+00 3.02300416e-02
1.07970941e+00 1.49914458e-01 2.35811248e-01 -4.64064509e-01
1.97904840e-01 -1.09939408e+00 -6.40194416e-01 1.58688352e-02
5.37223101e-01 -1.48099637e+00 4.50400412e-02 -3.47011775e-01
-4.93130177e-01 1.14002430e+00 5.79690874e-01 -2.94024986e-03
8.43934834e-01 -4.45489585e-02 2.33285129e-01 -2.14007631e-01
-3.82451504e-01 -3.68737429e-01 9.96506393e-01 4.46738422e-01
1.03307784e+00 2.32931837e-01 -6.71425104e-01 5.02829432e-01
-6.94222629e-01 -1.92617640e-01 3.88539046e-01 2.57003367e-01
8.91033858e-02 -1.47206795e+00 -4.14658159e-01 1.01000154e+00
-9.55119789e-01 -1.20427854e-01 -5.94455481e-01 4.45397526e-01
8.49622726e-01 8.94191742e-01 4.41633493e-01 -3.93395305e-01
-2.95820206e-01 -2.39969045e-02 9.09623742e-01 -6.90327585e-01
-4.68406737e-01 5.31677365e-01 1.28855035e-01 -5.20368457e-01
-3.97030562e-01 -1.01799011e+00 -4.91963089e-01 -2.61543214e-01
-2.43092164e-01 9.90097374e-02 7.77568996e-01 8.70419383e-01
2.36426800e-01 -1.58125743e-01 4.03071195e-01 -4.34075981e-01
-3.82529199e-02 -8.97995949e-01 -1.28057575e+00 -1.72315072e-02
6.67197466e-01 -5.38995206e-01 -4.51746345e-01 -2.07187578e-01] | [3.7451012134552, -3.6296439170837402] |
5f85ddb1-0d77-4fd2-8c1f-4e389a5095a7 | clinical-concept-extraction-for-document | 1906.03380 | null | https://arxiv.org/abs/1906.03380v1 | https://arxiv.org/pdf/1906.03380v1.pdf | Clinical Concept Extraction for Document-Level Coding | The text of clinical notes can be a valuable source of patient information and clinical assessments. Historically, the primary approach for exploiting clinical notes has been information extraction: linking spans of text to concepts in a detailed domain ontology. However, recent work has demonstrated the potential of supervised machine learning to extract document-level codes directly from the raw text of clinical notes. We propose to bridge the gap between the two approaches with two novel syntheses: (1) treating extracted concepts as features, which are used to supplement or replace the text of the note; (2) treating extracted concepts as labels, which are used to learn a better representation of the text. Unfortunately, the resulting concepts do not yield performance gains on the document-level clinical coding task. We explore possible explanations and future research directions. | ['Sarah Wiegreffe', 'Sherry Yan', 'Jimeng Sun', 'Jacob Eisenstein', 'Edward Choi'] | 2019-06-08 | clinical-concept-extraction-for-document-1 | https://aclanthology.org/W19-5028 | https://aclanthology.org/W19-5028.pdf | ws-2019-8 | ['clinical-concept-extraction'] | ['medical'] | [ 4.97145683e-01 6.68926716e-01 -4.51317608e-01 -3.68797511e-01
-9.09510374e-01 -5.28333545e-01 4.11937207e-01 1.26896679e+00
-3.87483627e-01 6.77393317e-01 9.08346117e-01 -3.93531919e-01
-3.90894294e-01 -6.75484300e-01 -1.29787400e-02 -4.88156348e-01
4.38108146e-02 4.23294455e-01 -1.37439653e-01 1.35966837e-01
2.98478872e-01 4.41457868e-01 -1.24466848e+00 7.59220600e-01
7.47144759e-01 9.87562060e-01 -1.62058845e-01 3.13932180e-01
-5.46043336e-01 1.20314670e+00 -5.44814587e-01 -2.89608836e-01
3.13555673e-02 -7.24049330e-01 -1.02435589e+00 2.10405812e-01
-5.73392659e-02 -1.29789487e-01 -2.62658708e-02 9.11314964e-01
9.88820121e-02 -3.36314380e-01 7.91995525e-01 -8.56978714e-01
-4.01636571e-01 6.96700215e-01 -1.50926560e-01 -2.83212364e-02
3.98937792e-01 -2.66786456e-01 1.12728608e+00 -5.22889018e-01
8.95630062e-01 8.32033157e-01 5.90787232e-01 6.37516618e-01
-1.02215421e+00 -4.46336657e-01 -1.11803688e-01 -2.08496124e-01
-1.36667192e+00 -4.45004165e-01 3.89674395e-01 -7.54712582e-01
9.74008620e-01 2.57332414e-01 6.90858841e-01 6.77902699e-01
2.41867229e-01 5.05345941e-01 9.44533050e-01 -7.28153706e-01
2.09200546e-01 4.31152821e-01 2.64168561e-01 8.05981994e-01
5.74004650e-01 -6.41598850e-02 -3.92324358e-01 -6.87472641e-01
4.21384215e-01 2.84504771e-01 -1.90485060e-01 -1.71427995e-01
-1.14794362e+00 9.06831920e-01 1.70168713e-01 5.23093820e-01
-4.56881642e-01 -2.85568804e-01 6.08805060e-01 2.56988943e-01
3.66475821e-01 8.58353436e-01 -5.57357371e-01 -5.24763912e-02
-1.01298296e+00 1.78150803e-01 8.96203101e-01 9.47432339e-01
4.46040034e-01 -5.98051906e-01 -1.21072784e-01 6.31082773e-01
2.73378491e-01 -8.48622322e-02 7.41837084e-01 -6.58838987e-01
4.35779512e-01 1.05113339e+00 1.00221157e-01 -7.20376432e-01
-6.74604595e-01 -2.78877676e-01 -4.04906034e-01 -3.01340103e-01
2.80632496e-01 -1.96710855e-01 -8.92858148e-01 1.31047833e+00
1.59965113e-01 -1.99386939e-01 3.91429722e-01 3.63224238e-01
1.02439618e+00 3.05045452e-02 4.04590666e-01 -2.67123252e-01
1.64929962e+00 -6.70140624e-01 -9.15723979e-01 -9.79526564e-02
1.26486528e+00 -6.64188802e-01 2.92797118e-01 1.27279669e-01
-8.55168581e-01 -7.55690709e-02 -9.00902927e-01 -2.04449639e-01
-5.10161102e-01 2.23926470e-01 5.28124273e-01 4.04160172e-01
-7.78281033e-01 5.94509184e-01 -9.63728607e-01 -4.92661864e-01
5.71271598e-01 1.65672138e-01 -4.53365684e-01 -4.36022431e-02
-9.33873236e-01 8.06591690e-01 5.62297821e-01 -3.98310214e-01
-6.45980835e-02 -8.84783268e-01 -1.10595047e+00 3.58859092e-01
4.52235490e-01 -8.05716336e-01 1.05834842e+00 -7.14005172e-01
-8.20694447e-01 1.06075978e+00 -1.72370568e-01 -3.91765863e-01
1.78250954e-01 1.01292506e-01 -5.18757164e-01 3.94143760e-01
1.77822456e-01 4.90850627e-01 3.18128854e-01 -1.04332781e+00
-9.38817263e-01 -4.74878669e-01 -1.42964944e-01 -7.27353394e-02
-5.61707139e-01 -3.17788385e-02 -2.90064812e-01 -9.26060319e-01
3.20462018e-01 -1.01643109e+00 -2.82069534e-01 5.70476651e-02
-4.66266066e-01 -2.33921215e-01 3.78816605e-01 -7.54202425e-01
1.60715544e+00 -2.29255319e+00 -1.19428836e-01 3.46746147e-01
6.68591857e-01 1.66408449e-01 1.67306557e-01 7.19616294e-01
-2.39994049e-01 3.88660133e-01 -2.88107395e-01 -1.05059572e-01
-3.33814502e-01 2.16480657e-01 -3.71348679e-01 9.72548276e-02
3.37208986e-01 8.44149828e-01 -9.66951549e-01 -6.93470418e-01
-1.05669156e-01 3.57633948e-01 -6.38015568e-01 4.29510251e-02
-4.03638259e-02 3.51965725e-01 -7.51547396e-01 5.98471284e-01
1.62668005e-01 -4.10251349e-01 5.21859109e-01 -2.60306031e-01
1.91124514e-01 8.56257617e-01 -7.77171314e-01 1.56950653e+00
-1.75915867e-01 4.42576081e-01 -2.12003842e-01 -8.82112443e-01
6.84709191e-01 6.50063694e-01 1.20855033e+00 -2.11577147e-01
7.64320046e-02 1.32415637e-01 -1.00962874e-02 -7.63450027e-01
2.23114297e-01 -5.48124075e-01 -1.09705091e-01 4.24980789e-01
-1.57664448e-01 -1.27651561e-02 1.09263785e-01 2.54275918e-01
1.41951382e+00 -1.48228914e-01 8.96402061e-01 -1.88284293e-01
5.32540977e-01 4.83591050e-01 5.64736068e-01 4.09113765e-01
-4.52630147e-02 4.96210456e-01 6.86035335e-01 -3.92391026e-01
-7.86175370e-01 -8.05191040e-01 -5.50751030e-01 5.33274353e-01
-4.56803173e-01 -1.03474104e+00 -4.61757153e-01 -9.29356039e-01
2.54892588e-01 5.18272281e-01 -6.66349411e-01 -7.10387900e-02
-3.20081234e-01 -6.39472425e-01 5.75934768e-01 7.98734725e-01
-2.23491386e-01 -7.39805281e-01 -7.59291053e-01 4.09652621e-01
-3.27927202e-01 -1.20405161e+00 -2.70398557e-01 4.23931479e-01
-1.25454926e+00 -1.38364053e+00 -2.97261447e-01 -7.18886077e-01
9.47313249e-01 -1.64091304e-01 1.01235831e+00 5.06877601e-01
-3.57848734e-01 3.15788090e-01 -6.25689209e-01 -5.58274686e-01
-7.12416172e-01 9.87947360e-02 -1.96739048e-01 -3.32297355e-01
7.62931228e-01 -2.12670475e-01 -4.25641328e-01 -1.88841790e-01
-1.27319062e+00 9.64515260e-04 5.96740425e-01 8.47257972e-01
4.14201379e-01 -3.78951728e-02 5.57585716e-01 -1.40515518e+00
6.93725586e-01 -5.19632936e-01 -1.11473560e-01 1.60823464e-01
-9.88840640e-01 3.84990841e-01 4.46886748e-01 -1.07544605e-02
-7.52767980e-01 1.42674506e-01 -2.59654641e-01 -1.25281755e-02
-2.39227921e-01 1.08175242e+00 2.63373852e-01 4.05073911e-01
5.95328450e-01 -8.25057775e-02 7.85622969e-02 -6.10285819e-01
1.13843188e-01 1.04582512e+00 3.01955104e-01 -4.27880049e-01
5.60646653e-01 4.88043100e-01 1.46796539e-01 -4.38173920e-01
-1.04845345e+00 -9.56502497e-01 -9.26107168e-01 4.44404185e-01
9.60984528e-01 -8.89849126e-01 -2.31946796e-01 -3.18472862e-01
-6.44565523e-01 9.46925059e-02 -5.93872428e-01 5.97383201e-01
-4.56586093e-01 3.67921799e-01 -7.10013211e-01 -4.06760842e-01
-1.51207387e-01 -8.92576218e-01 1.13692176e+00 -1.26080155e-01
-7.50724554e-01 -1.10937750e+00 1.51398331e-01 4.96309340e-01
-1.25597328e-01 3.95382941e-01 1.63658881e+00 -1.23442328e+00
-5.87781332e-02 -5.53488076e-01 -2.07726583e-01 -1.80512145e-02
8.12941730e-01 -1.01710670e-01 -8.99291873e-01 -3.25154126e-01
7.39396065e-02 -6.05333783e-02 7.28131771e-01 7.38663077e-02
1.07443380e+00 -4.32106823e-01 -7.99182832e-01 4.90189612e-01
1.40118265e+00 3.96896511e-01 4.68222886e-01 2.41687372e-01
4.41187918e-01 7.54544437e-01 4.24014866e-01 4.70960498e-01
3.02177697e-01 5.38907707e-01 -1.96118489e-01 -1.13597162e-01
-1.22598782e-01 -2.41198078e-01 -1.41478151e-01 9.55040872e-01
2.15308562e-01 8.02722573e-02 -1.25775659e+00 7.17387021e-01
-1.71301198e+00 -5.85344374e-01 5.36815412e-02 1.88959682e+00
1.10663116e+00 9.23663080e-02 -5.44225760e-02 2.16563404e-01
2.50580043e-01 -4.08069432e-01 -3.31580311e-01 -1.14782199e-01
3.58241767e-01 2.18313068e-01 3.70085180e-01 7.86995590e-02
-8.59158874e-01 4.63062108e-01 6.75367212e+00 2.12221980e-01
-9.10598636e-01 -3.86305787e-02 3.31164777e-01 -1.35953456e-01
-1.64086536e-01 1.67983994e-01 -7.18263865e-01 3.82803708e-01
1.00051606e+00 -3.01742017e-01 -1.69644535e-01 5.95966756e-01
1.44196391e-01 -5.38565554e-02 -1.58233869e+00 8.17898631e-01
1.41458482e-01 -1.51182246e+00 2.92778075e-01 4.45095241e-01
5.98688960e-01 -3.37456465e-01 -3.52812290e-01 1.51998803e-01
2.75406569e-01 -8.46987724e-01 2.88623750e-01 4.80677277e-01
9.33579147e-01 -3.01484704e-01 1.03121793e+00 6.18362725e-02
-1.19476414e+00 -2.36848801e-01 -9.63526890e-02 7.14478269e-02
-1.44813210e-01 5.28280079e-01 -1.21516371e+00 7.57864594e-01
4.60478455e-01 8.72236431e-01 -6.43368900e-01 1.08169770e+00
-2.95818504e-02 5.09250760e-01 6.47094846e-02 3.74989957e-01
2.60124952e-01 3.46856639e-02 2.90761024e-01 1.29472399e+00
2.69294649e-01 3.58290851e-01 4.02286351e-01 5.59320271e-01
-1.42321005e-01 3.44013691e-01 -6.35703087e-01 -6.51668787e-01
3.99178147e-01 1.03720212e+00 -9.88240540e-01 -6.34718359e-01
-7.53077686e-01 5.06759524e-01 1.11341573e-01 1.31317019e-01
-2.24582523e-01 -4.75278080e-01 6.86734974e-01 4.75931764e-01
2.50990033e-01 1.51483998e-01 -4.62078363e-01 -1.25457263e+00
-7.60143697e-02 -8.49307954e-01 9.45972204e-01 -6.15085602e-01
-1.28859448e+00 5.02276123e-01 -5.57420477e-02 -1.40131879e+00
-4.85574096e-01 -6.69622660e-01 -8.00126139e-03 7.84473896e-01
-1.43141115e+00 -8.65934193e-01 -3.08370978e-01 3.18174064e-01
3.22043478e-01 -1.73410356e-01 1.24597538e+00 3.12088579e-01
-1.32571012e-01 4.08822685e-01 2.41385788e-01 7.42801905e-01
9.11985755e-01 -1.21326196e+00 -4.81036790e-02 2.51651615e-01
4.59798016e-02 8.53046238e-01 3.66794080e-01 -8.61606061e-01
-9.19431508e-01 -1.15053535e+00 1.44360602e+00 -6.86413407e-01
6.32534087e-01 -4.26538028e-02 -1.05530453e+00 7.98825026e-01
-1.61674574e-01 -1.76974103e-01 1.49234033e+00 1.05659075e-01
-4.24594313e-01 4.74783443e-02 -1.22466624e+00 3.29830974e-01
7.14105785e-01 -8.52445006e-01 -1.04944754e+00 2.55341172e-01
5.26840150e-01 -2.87565976e-01 -1.30631912e+00 3.21460605e-01
4.98878151e-01 -3.34654212e-01 7.75890946e-01 -1.01199412e+00
6.29871011e-01 -5.97891659e-02 -2.51546614e-02 -1.22782588e+00
-2.16159895e-01 -1.89018130e-01 4.97730263e-02 1.06485963e+00
5.99887908e-01 -5.47333360e-01 7.45394468e-01 8.63388360e-01
-4.35271375e-02 -8.57256711e-01 -6.32109761e-01 -5.22456467e-01
1.80360153e-01 -1.97691604e-01 7.08027720e-01 1.23598790e+00
7.72469640e-01 2.02272996e-01 1.83127731e-01 -1.56033918e-01
1.78265914e-01 8.31920132e-02 1.29265815e-01 -1.63876843e+00
2.42930534e-03 -3.46314669e-01 -5.95885217e-01 -4.83050466e-01
-3.40530723e-02 -1.17366171e+00 -2.02718773e-04 -1.91978693e+00
6.11069024e-01 -5.98068237e-01 -4.42970097e-01 8.97373199e-01
-1.91372663e-01 -1.41101722e-02 1.49079457e-01 5.12970567e-01
-1.58707634e-01 -3.33125815e-02 8.29084098e-01 -1.76190600e-01
-3.36807102e-01 -1.05853029e-01 -1.18347883e+00 7.28773654e-01
6.58460915e-01 -1.02143395e+00 -4.51590300e-01 -1.06762871e-01
2.25941107e-01 2.86602676e-01 4.55388501e-02 -7.91618764e-01
2.46303961e-01 -2.06525341e-01 2.13789836e-01 -3.54885966e-01
-9.87716913e-02 -1.05142128e+00 -8.41908976e-02 7.26526618e-01
-7.42990196e-01 8.79954547e-02 2.25565612e-01 5.64092219e-01
-4.48826045e-01 -6.04810894e-01 5.06620705e-01 -3.23290855e-01
-2.28124321e-01 -1.01365417e-01 -6.76664114e-01 8.98807123e-02
7.78787136e-01 -1.28716186e-01 -1.75569341e-01 -5.78669533e-02
-9.99409795e-01 1.35699697e-02 4.31201279e-01 3.71964127e-01
3.45966697e-01 -1.17571545e+00 -5.57460070e-01 1.10700846e-01
5.14463067e-01 -2.06305593e-01 -2.36569747e-01 7.45074749e-01
-4.53323931e-01 1.04699039e+00 -1.02188446e-01 -4.05729771e-01
-1.45254040e+00 7.62889445e-01 1.91015363e-01 -5.37732780e-01
-8.12608838e-01 2.03136325e-01 1.66781783e-01 -8.46827850e-02
2.58439690e-01 -6.18132412e-01 -3.95157725e-01 4.50995594e-01
6.51952386e-01 -6.42494634e-02 4.80289489e-01 -4.09388512e-01
-4.91303772e-01 2.15984076e-01 -3.70136440e-01 -9.77529213e-03
1.63956499e+00 -1.40984714e-01 -1.47563204e-01 3.24624836e-01
1.04098642e+00 2.00555280e-01 -6.37740910e-01 -4.63468820e-01
5.97264290e-01 -2.73220688e-01 5.43547943e-02 -9.32946384e-01
-8.43418121e-01 7.04756916e-01 3.27686667e-01 1.87268808e-01
1.15122223e+00 1.75224572e-01 6.19573414e-01 4.81114417e-01
8.22190121e-02 -8.73870671e-01 -1.04802534e-01 2.16797888e-01
4.69968498e-01 -1.14985454e+00 2.89984941e-01 -7.30233550e-01
-6.34651899e-01 1.37278473e+00 1.66691720e-01 4.25883830e-01
8.70398939e-01 5.71775019e-01 3.17058474e-01 -5.59096634e-01
-8.44922543e-01 -2.71237791e-01 4.44722146e-01 5.20697296e-01
9.20472324e-01 -5.31547107e-02 -4.67343211e-01 8.52178395e-01
-5.03688306e-02 3.62748384e-01 5.64522326e-01 1.45553815e+00
-2.66985685e-01 -1.46147013e+00 -2.40435854e-01 9.85019505e-01
-8.04313064e-01 -4.03306007e-01 -5.46585321e-01 6.41329408e-01
3.40620607e-01 9.60640967e-01 2.43916474e-02 -1.65217489e-01
3.34431618e-01 6.19143724e-01 1.85889900e-01 -1.29150617e+00
-8.34993660e-01 1.79757491e-01 1.25129238e-01 -2.75946081e-01
-5.52670538e-01 -7.43395030e-01 -1.49727583e+00 1.96237907e-01
-1.48756862e-01 4.96164292e-01 3.50183994e-01 1.24474669e+00
4.87617195e-01 6.87053084e-01 1.56761140e-01 5.70005737e-02
-4.68000770e-01 -7.50053465e-01 -3.75567168e-01 7.17277467e-01
5.52966893e-01 -5.05747020e-01 -3.80637757e-02 5.70076048e-01] | [8.393926620483398, 8.575933456420898] |
b5e70bf2-c2a4-4ec6-abbb-ff6c6ac519e2 | physical-pooling-functions-in-graph-neural | 2207.13779 | null | https://arxiv.org/abs/2207.13779v1 | https://arxiv.org/pdf/2207.13779v1.pdf | Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction | Graph neural networks (GNNs) are emerging in chemical engineering for the end-to-end learning of physicochemical properties based on molecular graphs. A key element of GNNs is the pooling function which combines atom feature vectors into molecular fingerprints. Most previous works use a standard pooling function to predict a variety of properties. However, unsuitable pooling functions can lead to unphysical GNNs that poorly generalize. We compare and select meaningful GNN pooling methods based on physical knowledge about the learned properties. The impact of physical pooling functions is demonstrated with molecular properties calculated from quantum mechanical computations. We also compare our results to the recent set2set pooling approach. We recommend using sum pooling for the prediction of properties that depend on molecular size and compare pooling functions for properties that are molecular size-independent. Overall, we show that the use of physical pooling functions significantly enhances generalization. | ['Alexander Mitsos', 'Kai Leonhard', 'Manuel Dahmen', 'Martin Grohe', 'Jana M. Weber', 'Jan G. Rittig', 'Artur M. Schweidtmann'] | 2022-07-27 | null | null | null | null | ['molecular-property-prediction'] | ['miscellaneous'] | [ 3.78893465e-01 -1.92815781e-01 -3.21594119e-01 -2.38759682e-01
-3.98415148e-01 -7.43205190e-01 4.87064898e-01 7.15432823e-01
-4.44825560e-01 1.19661987e+00 1.01380534e-01 -2.57686824e-01
-4.72096741e-01 -1.14835274e+00 -1.00661540e+00 -9.20777977e-01
-4.43900615e-01 -2.56969094e-01 3.81661624e-01 -3.37334335e-01
5.02852499e-01 1.03137636e+00 -1.25698709e+00 4.98445392e-01
7.65031517e-01 9.97119904e-01 4.20573819e-03 5.24619102e-01
1.37446165e-01 3.91770929e-01 -4.86722380e-01 -2.92407513e-01
3.11825156e-01 -3.02045733e-01 -6.85886562e-01 -9.39802647e-01
7.86523402e-01 3.05593699e-01 -3.58454764e-01 1.07114947e+00
7.80276299e-01 6.99327350e-01 1.01286125e+00 -7.82928050e-01
-1.15777409e+00 4.49200928e-01 1.88768014e-01 -4.57288064e-02
4.39702868e-01 2.86490321e-01 1.38367391e+00 -6.83478534e-01
7.86109984e-01 1.06652284e+00 9.14137542e-01 4.41582561e-01
-1.59748626e+00 -5.71362853e-01 -1.52712539e-01 2.98606187e-01
-1.20644712e+00 -7.43446276e-02 5.77006280e-01 -2.39824012e-01
1.72254729e+00 3.45441461e-01 3.56891662e-01 8.71683002e-01
9.07992959e-01 -4.97290827e-02 9.21379268e-01 -2.35072821e-01
4.28696752e-01 -3.08846176e-01 2.47826025e-01 6.06591344e-01
7.36145794e-01 2.64462382e-01 -7.71441519e-01 -5.50206661e-01
3.56223226e-01 1.43496409e-01 -3.38353902e-01 -3.08436960e-01
-9.88605440e-01 7.92734563e-01 1.08802283e+00 3.78307849e-02
-4.55782056e-01 4.15677845e-01 2.03198791e-01 3.24558288e-01
2.51695663e-01 1.40873265e+00 -7.86673963e-01 3.58936012e-01
-5.48755825e-01 5.51104844e-01 8.66141558e-01 5.62476516e-01
1.09924901e+00 -2.25351796e-01 -2.58451760e-01 4.91773605e-01
5.47250248e-02 2.95603633e-01 3.09414893e-01 -4.45761919e-01
4.98388410e-02 6.97231293e-01 5.41744679e-02 -7.86442935e-01
-8.28007340e-01 2.31574047e-02 -5.82767069e-01 4.72689301e-01
5.03680825e-01 -1.10760070e-01 -1.14831066e+00 1.65043998e+00
-1.50727823e-01 -1.88488275e-01 2.09336042e-01 4.16898608e-01
1.28821802e+00 6.40147030e-01 4.92594123e-01 6.68503270e-02
9.10447955e-01 -5.55405915e-01 -3.13991994e-01 3.43274891e-01
7.58340716e-01 -4.80143845e-01 7.21886575e-01 3.94877911e-01
-8.92183423e-01 -4.66151029e-01 -1.44111145e+00 -1.11350656e-01
-1.32519758e+00 -4.03856248e-01 1.06661510e+00 1.02845335e+00
-9.44698572e-01 1.81196094e+00 -4.81435895e-01 -1.00901581e-01
4.65007156e-01 1.18883550e+00 -7.80043840e-01 9.35311243e-02
-1.47823727e+00 1.01229262e+00 9.01699483e-01 -3.83853912e-04
-2.27037787e-01 -1.02832508e+00 -7.46584356e-01 1.70413256e-01
1.80308148e-02 -6.35332704e-01 7.20638692e-01 -4.45379555e-01
-1.71799827e+00 1.84126854e-01 5.62387332e-02 -4.64488357e-01
-9.96154547e-02 1.04526572e-01 -2.59876221e-01 -2.76102740e-02
-5.84655404e-01 8.19949210e-01 2.62348980e-01 -7.50205636e-01
1.73288569e-01 5.65818734e-02 1.10343359e-01 -1.96633339e-01
-1.21688642e-01 -3.53085667e-01 5.05819321e-01 -3.15900624e-01
-1.83284618e-02 -7.27898538e-01 -4.86815393e-01 -4.45426226e-01
-5.81344664e-01 -2.09521621e-01 2.64480710e-01 -3.15062284e-01
9.81619537e-01 -1.63966370e+00 2.44559616e-01 7.09610939e-01
3.90390962e-01 3.78763288e-01 -3.87110829e-01 9.89776552e-01
-4.12463754e-01 6.20395839e-01 -1.12626649e-01 3.26321453e-01
1.54765144e-01 -2.18997806e-01 -1.08243190e-01 4.01655406e-01
5.07147253e-01 1.18223858e+00 -7.38225520e-01 1.99878797e-01
1.23903804e-01 7.37457454e-01 -9.43975568e-01 4.58426811e-02
-5.07183254e-01 1.02559045e-01 -3.90667409e-01 5.58374524e-01
9.11658466e-01 -2.66307622e-01 2.24831223e-01 -4.22469348e-01
-1.80896759e-01 5.89696884e-01 -7.15556681e-01 1.39880419e+00
1.22820862e-01 2.24555477e-01 -7.93363631e-01 -5.32781482e-01
1.06397212e+00 1.33110270e-01 3.52456659e-01 -6.51950061e-01
4.23541442e-02 3.79419684e-01 5.76933742e-01 -1.51877731e-01
5.06642401e-01 -5.22204816e-01 1.52619258e-01 1.21091112e-01
6.83942318e-01 -2.42169023e-01 3.12983721e-01 -2.23018959e-01
1.14894104e+00 3.53981107e-01 4.57899988e-01 -6.06815398e-01
5.39896965e-01 -4.90758628e-01 3.43659639e-01 1.01650989e+00
-8.80237594e-02 6.88177288e-01 8.60996068e-01 -7.33039916e-01
-1.11036766e+00 -9.74982142e-01 -2.65327573e-01 1.19626033e+00
2.41179299e-02 -7.68808067e-01 -4.54821914e-01 -4.82563734e-01
2.07780570e-01 3.08488101e-01 -8.25082839e-01 -5.50887942e-01
-3.30819696e-01 -1.12183893e+00 5.21118522e-01 4.34806734e-01
1.02784909e-01 -1.44734657e+00 -1.15437254e-01 4.01189268e-01
7.23824561e-01 -7.59411216e-01 -1.56862617e-01 7.93606400e-01
-6.88801050e-01 -9.45217669e-01 -6.21584594e-01 -3.67824197e-01
2.70084918e-01 -1.66849762e-01 9.52631056e-01 2.70180367e-02
-2.59443820e-01 -9.80663523e-02 -1.03798755e-01 -6.38216317e-01
-3.13133866e-01 5.01399279e-01 1.52860627e-01 -2.87984401e-01
4.81164277e-01 -8.15194845e-01 -7.44609594e-01 -2.46990994e-02
-8.32403839e-01 -2.75813669e-01 5.83548963e-01 6.39226258e-01
6.17335916e-01 -3.48138034e-01 7.27171004e-01 -8.98894548e-01
9.13987100e-01 -2.40954384e-01 -3.98139507e-01 4.28967774e-01
-3.13407809e-01 7.38408089e-01 9.23656702e-01 -4.12147343e-01
-5.69359958e-01 4.07997631e-02 -9.57170874e-02 9.94371623e-02
-6.02762215e-02 5.56699872e-01 -2.31093735e-01 -7.94662535e-01
1.00939989e+00 -6.14250861e-02 -1.96949899e-01 -2.66352922e-01
3.49272162e-01 1.18749943e-02 -9.35556293e-02 -8.45842123e-01
1.62035868e-01 -3.26793194e-02 7.77079046e-01 -9.19673204e-01
-3.58880252e-01 -1.73303708e-01 -7.04639018e-01 2.48611629e-01
8.79544437e-01 -3.68973076e-01 -1.44087791e+00 2.45761424e-01
-1.13978648e+00 -3.24096560e-01 -1.09164461e-01 5.74369192e-01
-6.25228465e-01 3.63860756e-01 -6.06074929e-01 -4.92866963e-01
-5.00759482e-01 -1.35908175e+00 6.81631565e-01 4.35354322e-01
-2.05997527e-01 -9.96111929e-01 1.96630344e-01 -3.19993347e-01
5.51649153e-01 6.69938922e-01 1.24244738e+00 -9.39707577e-01
-7.08707571e-01 -5.37658155e-01 -3.93409371e-01 2.01952025e-01
3.11043501e-01 1.15342461e-01 -1.22311282e+00 -1.58804119e-01
-8.51103604e-01 -3.14758301e-01 1.33345687e+00 5.42185962e-01
1.13285816e+00 -1.53125986e-01 -2.34873831e-01 6.46335483e-01
1.49928355e+00 3.85813206e-01 7.69701064e-01 -1.76187251e-02
9.82369542e-01 3.88056010e-01 -3.35999370e-01 6.39139563e-02
-4.41919953e-01 3.22919816e-01 3.58757108e-01 2.48626303e-02
1.06656579e-02 -2.65265256e-01 3.59947801e-01 1.50255710e-01
-8.04575920e-01 -3.77842426e-01 -6.66080713e-01 -2.78101891e-01
-1.61297715e+00 -9.37577963e-01 6.44488931e-02 2.48641229e+00
8.83126974e-01 3.14362645e-01 1.68085009e-01 -2.35498488e-01
4.61509258e-01 1.10409468e-01 -5.70931971e-01 -8.31564605e-01
-3.51326644e-01 1.15436828e+00 1.04275143e+00 6.80292010e-01
-9.63698983e-01 9.18436348e-01 7.12009668e+00 7.65615225e-01
-1.27288878e+00 -4.00076121e-01 4.96236771e-01 3.02822534e-02
-4.68299687e-01 -7.51851797e-02 -8.14412117e-01 2.07313135e-01
1.07936442e+00 -8.50502253e-02 3.75787765e-01 4.26577508e-01
-1.99217469e-01 6.49969727e-02 -1.25273383e+00 6.62953377e-01
-2.90073633e-01 -1.85050356e+00 4.80897248e-01 1.31389305e-01
8.38635802e-01 1.55078605e-01 6.85918033e-02 3.81826772e-03
-5.61951883e-02 -1.66969919e+00 1.85605079e-01 7.57130802e-01
4.87209678e-01 -9.28615570e-01 6.19546235e-01 -3.57358724e-01
-1.02975214e+00 1.98318169e-01 -8.33036005e-01 -2.04393372e-01
-3.12958837e-01 3.61381322e-01 -8.31024766e-01 7.27581918e-01
2.50861913e-01 5.78207612e-01 -6.71159446e-01 1.28854203e+00
-8.04619417e-02 2.82031566e-01 -4.07593876e-01 -7.35162318e-01
4.38339204e-01 -4.42341208e-01 1.89411208e-01 1.29839587e+00
7.78330564e-02 -7.12355897e-02 -4.96325158e-02 1.08409643e+00
-3.57564569e-01 3.83541018e-01 -7.73290038e-01 -5.40209293e-01
-2.19079964e-02 9.52707946e-01 -7.42886007e-01 -4.34643403e-02
-2.78366208e-01 7.08180785e-01 3.44348341e-01 6.09522939e-01
-4.56944138e-01 -1.00932932e+00 9.64969635e-01 -9.11627263e-02
4.95378882e-01 -3.85406494e-01 -1.27434775e-01 -6.67989016e-01
-1.89520523e-01 -4.35609609e-01 5.04801003e-03 -5.02866507e-01
-1.42058539e+00 4.58846509e-01 -1.40884407e-02 -5.80037415e-01
3.02558571e-01 -1.65643740e+00 -6.72549248e-01 1.22209775e+00
-1.36420512e+00 -9.79548991e-01 1.54917777e-01 5.79333901e-02
-4.81029421e-01 2.96160509e-03 1.14076388e+00 -5.32316826e-02
-2.81839281e-01 5.97986817e-01 1.15083337e-01 -3.45188975e-01
7.26440191e-01 -1.42260289e+00 5.74554682e-01 2.06231490e-01
-2.57089920e-02 1.09831500e+00 8.37720454e-01 -6.91354454e-01
-1.35639381e+00 -8.10391426e-01 8.46808434e-01 -6.69474661e-01
5.13352573e-01 -6.00840390e-01 -1.16137409e+00 7.02225342e-02
1.00586392e-01 2.96058685e-01 1.16969109e+00 2.97846138e-01
-7.50967801e-01 2.16267779e-01 -1.22015965e+00 5.32439590e-01
1.15438068e+00 -5.80451727e-01 -2.38809526e-01 4.97974753e-01
8.22292268e-01 -1.43339217e-01 -1.19518542e+00 5.32276034e-01
8.82120967e-01 -9.93035972e-01 1.23884356e+00 -1.32653487e+00
2.66580611e-01 -1.45078853e-01 -2.90548354e-01 -1.28967035e+00
-6.65494502e-01 -7.08700955e-01 3.48366678e-01 2.45147750e-01
1.01876581e+00 -1.06479251e+00 7.27947474e-01 7.97003806e-01
-1.67630836e-02 -7.88217604e-01 -7.64202178e-01 -1.05034828e+00
5.83666444e-01 -1.77739277e-01 8.09549928e-01 7.32215703e-01
3.63070339e-01 2.91037887e-01 -1.80351377e-01 9.35503468e-02
1.56569928e-01 -1.14738829e-01 2.84422904e-01 -1.40352869e+00
-3.95599812e-01 -6.74583852e-01 -8.78556907e-01 -4.70067322e-01
1.32029071e-01 -1.22137189e+00 -2.11702451e-01 -1.23040688e+00
6.69637471e-02 -9.27950349e-03 -1.06479657e+00 5.12078464e-01
-1.23436272e-01 2.91720331e-01 1.61895305e-01 -3.77507508e-01
-4.03491884e-01 4.45046902e-01 1.31213009e+00 -2.33314827e-01
-5.70875943e-01 -2.08783209e-01 -5.62069416e-01 1.45267934e-01
1.11530983e+00 -3.68068397e-01 -1.37384757e-01 4.97497559e-01
7.80355752e-01 -5.58735669e-01 2.57215112e-01 -1.13321495e+00
-3.22784521e-02 -2.89122969e-01 6.47388220e-01 -2.30317444e-01
4.20540214e-01 -3.48344445e-01 -4.56941463e-02 5.43626845e-01
-3.77459407e-01 -2.56081969e-01 6.42138481e-01 4.55158591e-01
7.43218362e-02 -3.16342175e-01 5.33312976e-01 -1.69209525e-01
-4.65647459e-01 6.51648223e-01 -1.87427029e-01 -4.92006212e-01
5.11011124e-01 -4.78560060e-01 -3.73271048e-01 -4.49422523e-02
-7.94777989e-01 -4.02434319e-01 3.53181928e-01 7.49774352e-02
5.00522077e-01 -1.25794065e+00 -3.57713550e-01 2.20398039e-01
1.79341853e-01 -5.67809999e-01 1.80207029e-01 4.53053087e-01
-7.73159802e-01 5.69399357e-01 -5.18068135e-01 -6.35052146e-03
-1.06060541e+00 6.76536798e-01 6.93101645e-01 -1.49269745e-01
1.49650825e-02 9.76782322e-01 1.78858623e-01 -5.23142993e-01
-1.70942321e-01 -7.68913269e-01 5.94495749e-03 8.93810093e-02
5.00780880e-01 3.66086513e-01 4.76423562e-01 -1.86097562e-01
-4.41465855e-01 5.63066483e-01 -2.05981314e-01 3.48327756e-01
1.66483223e+00 9.51908529e-01 -1.88844770e-01 1.89680830e-01
1.40482175e+00 -6.42272457e-02 -1.13542449e+00 1.72089357e-02
-9.47514027e-02 -3.45876366e-02 -1.87610224e-01 -8.97521436e-01
-4.30013031e-01 8.22692513e-01 5.86395204e-01 3.45762372e-01
5.77126503e-01 -2.50943512e-01 3.59859407e-01 1.16653156e+00
1.27200305e-01 -9.17788327e-01 -1.34934574e-01 7.51733840e-01
9.19972599e-01 -1.10457742e+00 4.75450635e-01 -4.41125035e-01
-8.63328427e-02 1.57153928e+00 2.11651698e-01 -4.86815065e-01
7.79802382e-01 -2.05431521e-01 -5.31244397e-01 -4.14236814e-01
-3.48832875e-01 -2.50481218e-01 7.67908156e-01 6.86902583e-01
9.63978231e-01 2.99108535e-01 -3.09982091e-01 4.50857431e-01
-9.58615690e-02 -1.13398954e-01 3.18421811e-01 8.88259351e-01
-5.09303808e-01 -1.58005261e+00 6.95374534e-02 4.60979760e-01
-4.06087995e-01 -6.29906774e-01 -1.04273772e+00 6.28212869e-01
3.09260219e-01 4.96220976e-01 -3.06401372e-01 -4.86710042e-01
4.20336425e-01 4.80415791e-01 1.05278599e+00 -5.91775954e-01
-9.10507798e-01 -5.78284979e-01 1.78771559e-02 -5.72611153e-01
-2.86296368e-01 -1.71667233e-01 -1.28077948e+00 -3.55494976e-01
-4.37623411e-01 6.61522150e-02 5.07947505e-01 6.80502176e-01
5.66523552e-01 4.03504491e-01 2.22971410e-01 -1.17403865e+00
-3.07185411e-01 -8.61825287e-01 -5.72692454e-01 3.87989253e-01
4.02143955e-01 -6.74887836e-01 -1.66195914e-01 -3.58721852e-01] | [5.143467903137207, 5.646833896636963] |
ab7e3951-9a58-4cbe-9ce7-845300d13af9 | deep-perceptual-preprocessing-for-video | null | null | http://openaccess.thecvf.com//content/CVPR2021/html/Chadha_Deep_Perceptual_Preprocessing_for_Video_Coding_CVPR_2021_paper.html | http://openaccess.thecvf.com//content/CVPR2021/papers/Chadha_Deep_Perceptual_Preprocessing_for_Video_Coding_CVPR_2021_paper.pdf | Deep Perceptual Preprocessing for Video Coding | We introduce the concept of rate-aware deep perceptual preprocessing (DPP) for video encoding. DPP makes a single pass over each input frame in order to enhance its visual quality when the video is to be compressed with any codec at any bitrate. The resulting bitstreams can be decoded and displayed at the client side without any post-processing component. DPP comprises a convolutional neural network that is trained via a composite set of loss functions that incorporates: (i) a perceptual loss based on a trained no reference image quality assessment model, (ii) a reference based fidelity loss expressing L1 and structural similarity aspects, (iii) a motion-based rate loss via block-based transform, quantization and entropy estimates that converts the essential components of standard hybrid video encoder designs into a trainable framework. Extensive testing using multiple quality metrics and AVC, AV1 and VVC encoders shows that DPP+encoder reduces, on average, the bitrate of the corresponding encoder by 11%. This marks the first time a server-side neural processing component achieves such savings over the state-of-the-art in video coding. | ['Yiannis Andreopoulos', 'Aaron Chadha'] | 2021-06-19 | null | null | null | cvpr-2021-1 | ['no-reference-image-quality-assessment'] | ['computer-vision'] | [ 5.98154724e-01 2.71520354e-02 -2.11214915e-01 -4.21070993e-01
-8.46984804e-01 -2.61159390e-01 4.10281479e-01 3.24605331e-02
-3.79828364e-01 3.96922916e-01 2.67062902e-01 -5.30059993e-01
1.46107867e-01 -8.06534410e-01 -1.04896259e+00 -4.71973121e-01
-3.15643102e-01 6.12990698e-03 3.22418630e-01 -2.85390288e-01
2.22818911e-01 3.71312618e-01 -1.76998174e+00 9.07574177e-01
5.31862020e-01 1.83521748e+00 3.00660700e-01 1.35154319e+00
3.35451871e-01 1.39998758e+00 -4.12926048e-01 -6.13002300e-01
5.15497863e-01 -4.32388932e-01 -7.93581843e-01 6.42970428e-02
4.54175711e-01 -1.04058695e+00 -7.15166152e-01 1.01979446e+00
5.77485859e-01 -1.88329682e-01 5.33787608e-01 -9.86978889e-01
-6.09204888e-01 3.93766373e-01 -1.93131596e-01 3.03067625e-01
3.59199286e-01 4.69104707e-01 9.11055863e-01 -8.16931069e-01
5.97835839e-01 1.28717542e+00 5.89493454e-01 4.11928296e-01
-1.00413358e+00 -2.43107840e-01 -4.81086284e-01 4.56154943e-01
-1.05531454e+00 -7.32151628e-01 4.34982032e-01 -3.46605420e-01
1.41319871e+00 1.61307663e-01 5.06808102e-01 8.57903004e-01
4.97555286e-01 4.57599252e-01 3.16497236e-01 -2.20964849e-01
4.95276630e-01 -1.83333293e-01 -6.90395832e-01 5.21397948e-01
-3.07754666e-01 3.04450423e-01 -3.45839441e-01 4.62380260e-01
9.70569313e-01 -2.84703255e-01 -4.43366647e-01 -2.97668427e-01
-8.51917565e-01 5.42813957e-01 5.31280339e-01 -1.42385975e-01
-4.77564394e-01 5.44697940e-01 7.91190982e-01 6.63934588e-01
3.33053052e-01 -1.74230784e-02 -2.27731377e-01 -5.54555953e-01
-1.46225393e+00 1.07240871e-01 7.07050204e-01 8.44746113e-01
5.02642035e-01 3.87932509e-01 -2.78177500e-01 8.42367589e-01
4.49774206e-01 3.79158109e-01 3.81523550e-01 -1.53406215e+00
7.37092316e-01 2.13769689e-01 -5.20449765e-02 -9.42082763e-01
1.16352953e-01 -2.12503374e-01 -8.78939748e-01 7.41798997e-01
-1.94878533e-01 3.28221507e-02 -8.18346977e-01 1.44347906e+00
-2.61638969e-01 1.03535736e-02 1.19048603e-01 1.10376585e+00
7.65211046e-01 1.06745362e+00 5.31804003e-03 -2.66388208e-01
1.05350506e+00 -1.07539427e+00 -6.12898290e-01 1.32782817e-01
4.22730327e-01 -7.60022819e-01 6.61595106e-01 5.79026282e-01
-2.05381107e+00 -1.02513719e+00 -1.62728703e+00 -4.32265818e-01
7.42434114e-02 -7.38692358e-02 6.70655593e-02 6.21206522e-01
-1.70589066e+00 9.31395113e-01 -7.93365061e-01 6.06159009e-02
3.69316846e-01 5.33307374e-01 -1.45291567e-01 -1.44911289e-01
-1.07950270e+00 7.98531950e-01 4.76778924e-01 -2.14259520e-01
-1.41944754e+00 -9.02543902e-01 -1.00219154e+00 4.79688346e-01
-4.61776219e-02 -7.22814500e-01 1.20848262e+00 -1.57826352e+00
-1.76321292e+00 6.37223542e-01 8.80498961e-02 -7.99969256e-01
7.20714927e-01 -1.67429581e-01 -4.84672248e-01 6.89348459e-01
-2.88529843e-01 9.30989563e-01 1.21721160e+00 -1.08331132e+00
-8.23293567e-01 1.72227636e-01 2.13298634e-01 2.61531115e-01
5.07379100e-02 2.33295366e-01 -7.65857041e-01 -6.31816685e-01
-4.31298614e-01 -3.64661664e-01 2.36106396e-01 6.14337921e-01
9.21583772e-02 2.34465152e-01 1.09026766e+00 -1.13366950e+00
1.17547309e+00 -2.27243400e+00 1.55601501e-01 -1.22510701e-01
2.97120482e-01 6.43798530e-01 -4.75862890e-01 2.57833987e-01
-2.78755665e-01 1.85213104e-01 -2.25765646e-01 -3.61605167e-01
-2.04681098e-01 -1.68261339e-03 -1.65707797e-01 2.64043301e-01
6.05279684e-01 8.03174317e-01 -8.50319088e-01 -3.14812064e-01
5.71535289e-01 9.49080706e-01 -1.10466886e+00 6.50870979e-01
-1.80552676e-01 -3.95448953e-02 3.00635695e-01 5.03730476e-01
8.32227945e-01 -1.92336127e-01 4.66224402e-02 -4.65868920e-01
-1.58972993e-01 5.17054141e-01 -9.29969430e-01 1.74520218e+00
-5.21409273e-01 1.01530325e+00 2.52139837e-01 -1.04516685e+00
6.80198431e-01 6.18251026e-01 4.78772193e-01 -1.00862992e+00
2.24229082e-01 2.93782234e-01 -6.16783537e-02 -4.47314411e-01
8.35123897e-01 2.47144416e-01 5.10121465e-01 7.15745986e-02
5.19878387e-01 1.74174249e-01 3.39037985e-01 1.08413495e-01
1.46195841e+00 2.04360008e-01 5.92840929e-03 -2.58557871e-02
5.78260303e-01 -5.75304389e-01 3.30177218e-01 4.64968175e-01
-3.20875823e-01 1.03212941e+00 4.65877503e-01 -4.92458194e-01
-1.92383325e+00 -1.32451844e+00 -1.57141984e-02 1.04192650e+00
5.39414734e-02 -4.14799839e-01 -7.84351528e-01 -2.34094173e-01
-3.53244931e-01 5.59087634e-01 -2.90120065e-01 -4.04940635e-01
-4.84943718e-01 1.97543725e-02 4.26985562e-01 4.74391252e-01
8.49018097e-01 -1.01749980e+00 -9.24189508e-01 4.36083496e-01
-1.61376923e-01 -1.15477991e+00 -4.05774087e-01 2.52650917e-01
-8.97076190e-01 -8.05616617e-01 -8.55628848e-01 -6.71328843e-01
1.56744719e-01 1.03116538e-02 1.23237967e+00 1.37305483e-01
-1.12492666e-01 6.70683607e-02 -5.05359650e-01 2.10756481e-01
-9.12254035e-01 -2.80798733e-01 -3.18540901e-01 -9.71988775e-03
-2.26633444e-01 -7.25168526e-01 -1.05064476e+00 6.87463135e-02
-1.05986261e+00 2.77125955e-01 5.49649000e-01 6.21521175e-01
4.61677730e-01 3.43744904e-02 -1.56389140e-02 -1.76864177e-01
2.64785022e-01 -3.88249457e-01 -5.29478550e-01 5.52498586e-02
-4.51962173e-01 4.77628335e-02 7.99345553e-01 -1.18975878e-01
-9.26841021e-01 -2.17121482e-01 -5.60559690e-01 -6.60692632e-01
5.33717126e-02 2.76828974e-01 -2.59907544e-01 -1.12748049e-01
5.83773375e-01 3.96484435e-01 -1.57516405e-01 -2.27530956e-01
2.70255357e-01 7.41398931e-01 9.03128624e-01 -1.64111644e-01
5.05038977e-01 2.07558617e-01 1.74882635e-02 -5.68966210e-01
-1.71197966e-01 -1.52872592e-01 -5.04254341e-01 -4.48790759e-01
1.08732057e+00 -1.19547451e+00 -7.18097031e-01 3.13583523e-01
-1.35455918e+00 -5.61305642e-01 -5.12666464e-01 3.65640998e-01
-9.86988664e-01 2.71944940e-01 -9.47396994e-01 -6.13482893e-01
-4.16424364e-01 -1.54195070e+00 1.08135343e+00 2.88300328e-02
2.07198083e-01 -7.49327898e-01 -1.59347698e-01 2.43027762e-01
7.35236228e-01 1.30467370e-01 9.18956399e-01 -1.21919811e-01
-7.32302308e-01 2.72077143e-01 -6.71131074e-01 1.05210185e+00
-1.63115308e-01 2.81289220e-01 -9.16529238e-01 -4.67124522e-01
-1.26307696e-01 -5.82773745e-01 8.96659136e-01 5.49984992e-01
1.22406769e+00 -5.58744013e-01 4.77733463e-01 1.25574279e+00
1.86612010e+00 5.59325516e-01 1.31737471e+00 2.47452185e-01
4.19277519e-01 -1.62052006e-01 2.94396803e-02 7.71072268e-01
1.62302032e-01 6.87486947e-01 9.32112753e-01 -2.08508536e-01
-5.48960030e-01 -1.32038742e-01 6.58660293e-01 8.56699646e-01
-3.99985015e-01 -5.07658958e-01 -5.69911182e-01 2.67369032e-01
-1.53523874e+00 -1.26926851e+00 2.49535635e-01 2.09064651e+00
9.49920058e-01 2.85251290e-01 -1.08171336e-01 4.94714856e-01
4.73076731e-01 3.42012376e-01 -4.70739633e-01 -1.07688224e+00
1.54281463e-02 3.12750131e-01 6.14136577e-01 4.86944586e-01
-1.05068898e+00 6.09568179e-01 6.37239265e+00 6.89834893e-01
-1.22519112e+00 -1.30975498e-02 9.32518125e-01 -1.39712542e-01
-1.61811069e-01 -2.21613914e-01 -2.04274431e-01 5.78100145e-01
1.57025385e+00 7.31844306e-02 7.71729708e-01 1.00927114e+00
4.53517795e-01 7.52169415e-02 -1.37281013e+00 1.19132102e+00
8.41589943e-02 -1.61983025e+00 4.35064584e-01 1.44526675e-01
6.54772401e-01 9.85991284e-02 2.67804623e-01 2.31463388e-01
6.50582835e-02 -1.21996880e+00 1.21530116e+00 5.29970586e-01
1.38708186e+00 -8.58642578e-01 7.82506704e-01 -1.38663277e-01
-1.29972672e+00 -1.85274243e-01 -6.32756591e-01 1.67146605e-02
2.46304587e-01 2.46805802e-01 -3.72839987e-01 4.96997386e-01
7.80734479e-01 7.73441672e-01 -4.01292980e-01 1.05360341e+00
1.55494764e-01 5.71139753e-01 9.01985243e-02 7.30818033e-01
3.37016761e-01 1.55993015e-01 3.45916599e-01 1.36917102e+00
5.70215166e-01 7.26365903e-03 -3.18400502e-01 7.35410988e-01
-4.18370664e-01 -1.55303746e-01 -2.04844162e-01 1.66886255e-01
1.60310835e-01 7.82136440e-01 -2.73952991e-01 -4.65330690e-01
-5.07303774e-01 1.45506454e+00 -1.52522381e-02 3.73816699e-01
-9.24283385e-01 -3.90305519e-01 8.18078458e-01 1.64138794e-01
6.95621192e-01 1.96024738e-02 -1.09244294e-01 -8.81119788e-01
-4.87185046e-02 -1.01034749e+00 -1.58894941e-01 -1.19539011e+00
-5.85405648e-01 7.42004752e-01 -3.78147960e-01 -1.34542453e+00
-5.20642638e-01 -6.79231882e-01 -3.63965064e-01 9.07611489e-01
-1.69040787e+00 -6.54565215e-01 -4.07702416e-01 6.24772012e-01
8.24895620e-01 -3.21473300e-01 4.88264680e-01 6.92197800e-01
-2.52220958e-01 7.51129806e-01 1.97140574e-01 1.32044613e-01
4.18629974e-01 -9.68420506e-01 3.88378054e-01 1.12553775e+00
-4.64446723e-01 -1.49757219e-02 6.87053800e-01 -2.53340453e-01
-1.43331146e+00 -1.29737782e+00 7.49450386e-01 2.97845364e-01
3.49442691e-01 -1.69053957e-01 -8.48162889e-01 3.13214004e-01
5.14420748e-01 3.56253415e-01 2.88817078e-01 -7.93543637e-01
-4.47460681e-01 -3.10984880e-01 -1.22139454e+00 3.68496597e-01
8.41821611e-01 -6.65142834e-01 -2.01913401e-01 -9.66417119e-02
9.70815778e-01 -4.02517229e-01 -1.15134633e+00 5.00760496e-01
6.47737861e-01 -1.55446398e+00 1.01918209e+00 -2.59637922e-01
1.43874490e+00 -1.47684440e-01 -4.98120248e-01 -9.46748793e-01
-4.63070005e-01 -5.00205934e-01 -4.75018263e-01 1.00661838e+00
2.93528557e-01 2.29796797e-01 6.22909009e-01 4.85112935e-01
-4.24979448e-01 -5.99883974e-01 -1.06023967e+00 -6.26394153e-01
-1.66284204e-01 -7.32573569e-01 3.17959160e-01 3.16065550e-01
-2.84430832e-01 -4.71351370e-02 -5.29715419e-01 1.18113738e-02
4.33538824e-01 -6.82970464e-01 4.10360456e-01 -6.68183208e-01
-4.94435310e-01 -5.86259902e-01 -8.08248103e-01 -1.41321838e+00
-4.02020305e-01 -6.26992226e-01 1.24055400e-01 -1.54057360e+00
2.06244856e-01 -1.38890654e-01 -3.54223639e-01 1.56001538e-01
2.99993843e-01 3.10970008e-01 4.56362605e-01 1.96834877e-01
-7.97908187e-01 6.38875604e-01 1.10197651e+00 -1.93218350e-01
-2.41487985e-03 -4.56548244e-01 -1.87479869e-01 3.36353362e-01
5.20095408e-01 -1.49422631e-01 -5.64570963e-01 -7.37140834e-01
3.07004273e-01 5.68098009e-01 4.98732567e-01 -1.53630650e+00
9.97372065e-03 1.28091127e-01 5.22773147e-01 -4.28969502e-01
3.76544982e-01 -8.95639896e-01 1.27725571e-01 5.86903214e-01
-6.47932589e-01 1.86099887e-01 7.37885982e-02 2.79540390e-01
-4.39210117e-01 -1.01229511e-01 1.12631702e+00 1.86894745e-01
-8.99309754e-01 3.78080606e-01 -3.90359014e-01 -3.29383154e-04
6.69003129e-01 -5.02758205e-01 -1.78136751e-01 -6.68075502e-01
-3.77600640e-01 -3.13319474e-01 6.25024080e-01 2.74395227e-01
1.08129406e+00 -1.39992011e+00 -9.53157961e-01 3.45821440e-01
-2.02303573e-01 -2.33764574e-01 3.14588100e-01 4.00553674e-01
-1.19092309e+00 3.46794575e-01 -6.70502782e-01 -6.05723262e-01
-1.06040633e+00 7.25770116e-01 4.79719996e-01 -3.45539421e-01
-5.32921195e-01 8.10854137e-01 1.54478565e-01 4.71636206e-01
3.60083222e-01 -3.85598600e-01 -4.82193707e-03 -4.23997402e-01
8.21303725e-01 4.35255021e-01 2.52112627e-01 -8.79201591e-01
-1.32406682e-01 1.64215162e-01 1.98432803e-01 -2.48491928e-01
1.27345073e+00 -2.71682918e-01 2.38281816e-01 5.79612628e-02
1.81616461e+00 -6.48834646e-01 -2.03922606e+00 1.04582883e-01
-4.34664220e-01 -4.60348487e-01 4.17734772e-01 -8.38934124e-01
-1.50963497e+00 1.01839495e+00 1.07534385e+00 4.70467545e-02
1.65036154e+00 -4.26558286e-01 9.41529870e-01 -1.27106473e-01
1.82366654e-01 -1.13648522e+00 8.06677900e-03 5.45011997e-01
1.08603919e+00 -1.09812796e+00 -1.76989928e-01 -6.17481098e-02
-4.48625743e-01 1.39614141e+00 8.39172751e-02 -2.58621395e-01
6.20449126e-01 4.81320500e-01 -1.76251337e-01 3.81461054e-01
-1.24067724e+00 1.39591902e-01 4.34585899e-01 7.80563056e-01
5.63013554e-01 -3.06187153e-01 -1.07228503e-01 2.16292366e-02
-1.52654156e-01 3.20452154e-01 4.56550568e-01 6.60169363e-01
-5.02837658e-01 -8.01991761e-01 2.63106525e-02 2.53643095e-01
-5.66328287e-01 -4.03931648e-01 4.00777787e-01 3.77567649e-01
3.58447731e-01 9.66160178e-01 4.39129382e-01 -7.02611268e-01
1.29463121e-01 -3.40999216e-01 2.93388397e-01 -1.60519436e-01
-6.27722740e-01 -9.86394733e-02 2.60627586e-02 -1.09513032e+00
-3.17626417e-01 -2.14967310e-01 -1.00655365e+00 -6.13735914e-01
4.21790749e-01 -3.58077407e-01 8.84356737e-01 7.37339079e-01
3.20890695e-01 8.45631957e-01 7.18442798e-01 -1.16542184e+00
-2.88715184e-01 -6.36304319e-01 -2.67709255e-01 5.30424714e-01
6.78207934e-01 -1.50724575e-01 -2.43918031e-01 7.34743714e-01] | [11.382092475891113, -1.596691370010376] |
3236009b-7361-46ec-b0da-32d79215797e | tvnet-temporal-voting-network-for-action | 2201.00434 | null | https://arxiv.org/abs/2201.00434v1 | https://arxiv.org/pdf/2201.00434v1.pdf | TVNet: Temporal Voting Network for Action Localization | We propose a Temporal Voting Network (TVNet) for action localization in untrimmed videos. This incorporates a novel Voting Evidence Module to locate temporal boundaries, more accurately, where temporal contextual evidence is accumulated to predict frame-level probabilities of start and end action boundaries. Our action-independent evidence module is incorporated within a pipeline to calculate confidence scores and action classes. We achieve an average mAP of 34.6% on ActivityNet-1.3, particularly outperforming previous methods with the highest IoU of 0.95. TVNet also achieves mAP of 56.0% when combined with PGCN and 59.1% with MUSES at 0.5 IoU on THUMOS14 and outperforms prior work at all thresholds. Our code is available at https://github.com/hanielwang/TVNet. | ['Toby Perrett', 'Majid Mirmehdi', 'Dima Damen', 'Hanyuan Wang'] | 2022-01-02 | null | null | null | null | ['action-localization'] | ['computer-vision'] | [ 1.80170998e-01 5.26799336e-02 -7.08109736e-01 -1.68278694e-01
-8.57571065e-01 -7.32743800e-01 8.04471731e-01 -2.94999599e-01
-6.46488905e-01 7.30231822e-01 5.77697992e-01 3.32718855e-03
1.90048888e-01 -3.75023514e-01 -4.57063109e-01 -2.71927148e-01
-3.51059675e-01 -1.06803201e-01 1.09571719e+00 1.95166320e-01
2.78681308e-01 -2.09809989e-02 -1.16264248e+00 6.02590263e-01
4.05027062e-01 1.02372897e+00 -2.31633596e-02 1.25137734e+00
6.06396496e-01 1.27780008e+00 -6.22329414e-01 -2.26798251e-01
2.67045736e-01 -4.18977380e-01 -8.68132472e-01 -3.15362275e-01
7.54828572e-01 -6.25816345e-01 -6.93097413e-01 6.62285864e-01
3.23143929e-01 2.33228400e-01 3.36372942e-01 -1.33720195e+00
-1.23760715e-01 6.31611407e-01 -6.28925800e-01 8.17575932e-01
4.82813060e-01 5.30478776e-01 1.09228802e+00 -7.47397542e-01
9.40721452e-01 8.64590108e-01 7.61542439e-01 4.74765360e-01
-8.64910662e-01 -6.18456542e-01 6.78038523e-02 5.31379759e-01
-1.32327449e+00 -7.05407739e-01 -5.95744466e-03 -3.67199630e-01
1.22388029e+00 1.54873982e-01 7.55891919e-01 1.38536203e+00
3.51349145e-01 9.34250474e-01 8.07438731e-01 6.10299036e-02
2.46508598e-01 -7.50173450e-01 -2.86165386e-01 7.26891220e-01
5.60359731e-02 -8.93977210e-02 -1.07269132e+00 1.35365561e-01
9.45031762e-01 -2.56778240e-01 3.92948685e-04 2.75385678e-01
-1.62757492e+00 3.20204288e-01 3.10090214e-01 3.26341808e-01
-3.82441550e-01 9.77330804e-01 4.69110996e-01 -2.76728362e-01
3.75810772e-01 1.03391178e-01 -5.59769630e-01 -8.85999441e-01
-1.30706131e+00 1.60924360e-01 4.24105108e-01 9.02656615e-01
2.51485378e-01 -3.74555998e-02 -6.19769573e-01 4.23613161e-01
2.41219550e-01 2.49518186e-01 1.10010356e-01 -1.91112280e+00
4.55910027e-01 4.42375571e-01 2.95699030e-01 -7.19860792e-01
-3.09504479e-01 -1.66827172e-01 -2.28268802e-01 2.32553452e-01
6.90641284e-01 -2.35513523e-01 -9.68189240e-01 1.64134121e+00
2.57146388e-01 9.20766532e-01 -2.18807206e-01 9.58467185e-01
7.80344903e-01 4.96327817e-01 3.82802188e-01 1.17942698e-01
1.28844488e+00 -1.15449536e+00 -6.17700338e-01 -4.55911070e-01
6.58963382e-01 -5.73432624e-01 6.91156685e-01 4.72865313e-01
-1.13195848e+00 -5.13318896e-01 -9.48053181e-01 -1.52556032e-01
1.14612445e-01 3.46741885e-01 5.02741516e-01 2.75713414e-01
-1.34515572e+00 6.69151485e-01 -1.21166277e+00 -5.59948742e-01
6.70002699e-01 2.43009664e-02 -3.19345802e-01 1.79202124e-01
-1.10102510e+00 8.69127929e-01 5.06422162e-01 -2.40440387e-03
-1.17360198e+00 -3.77206355e-01 -7.21092701e-01 -3.42129380e-01
5.81943989e-01 -5.43096900e-01 1.71727645e+00 -7.44476914e-01
-1.30270123e+00 5.64118922e-01 -2.45999277e-01 -8.39373767e-01
9.63092089e-01 -4.01188135e-01 -4.52742010e-01 5.85417628e-01
4.19932276e-01 1.08140135e+00 3.75980884e-01 -4.32728022e-01
-1.06180251e+00 2.49781206e-01 1.79224953e-01 2.83369750e-01
1.82349369e-01 2.25723937e-01 -1.06097853e+00 -5.98398447e-01
7.88756162e-02 -8.48704040e-01 -2.03449845e-01 2.33637378e-01
-7.65734911e-02 -2.87582427e-01 6.84876978e-01 -8.95436049e-01
1.41405261e+00 -1.95367825e+00 -1.49414822e-01 -1.25992194e-01
2.52175242e-01 1.34771049e-01 -1.43297181e-01 1.59286961e-01
2.59199917e-01 1.14588164e-01 -7.41037279e-02 -1.91563472e-01
-1.05449788e-01 1.37041166e-01 1.07708111e-01 5.71366847e-01
2.76960999e-01 1.19514084e+00 -1.25664866e+00 -8.10890794e-01
4.49206889e-01 3.09729695e-01 -5.95123351e-01 -2.34429896e-01
-3.72477323e-01 5.88770807e-01 -2.81518996e-01 9.64322031e-01
1.18707798e-01 -3.64549547e-01 4.34115976e-01 -6.69043660e-02
-4.58496183e-01 3.07157904e-01 -1.16575468e+00 2.08373785e+00
1.29010394e-01 1.13832104e+00 -2.68168747e-01 -3.33490700e-01
4.24328089e-01 3.69430542e-01 6.70215249e-01 -4.47698325e-01
1.74154520e-01 -1.16352156e-01 -1.84440613e-02 -4.41772759e-01
8.20195258e-01 5.31680465e-01 -2.87445635e-01 1.07931323e-01
3.17333013e-01 4.45942044e-01 5.78255892e-01 4.98990059e-01
2.07428885e+00 7.74898350e-01 4.46097881e-01 7.28001967e-02
1.18243679e-01 -1.43958647e-02 1.04601300e+00 9.17310119e-01
-9.09403861e-01 7.73723125e-01 6.39910221e-01 -4.36739862e-01
-7.89156199e-01 -1.17385423e+00 7.92956874e-02 1.19678783e+00
1.97273076e-01 -9.85443652e-01 -5.99038839e-01 -8.52697730e-01
-2.88789511e-01 6.04986429e-01 -6.94218218e-01 2.30983451e-01
-7.09085226e-01 -1.38614476e-01 9.94466245e-01 9.31654811e-01
9.50922728e-01 -1.17610335e+00 -8.03707898e-01 2.38020465e-01
-6.79089844e-01 -1.38068175e+00 -5.66564143e-01 -1.52962282e-01
-7.89063096e-01 -1.25144005e+00 -4.77582157e-01 -2.43416592e-01
5.81807718e-02 1.12152979e-01 1.16542494e+00 4.50643674e-02
-7.75940642e-02 3.67522627e-01 -5.95854640e-01 -3.74100432e-02
-6.26851767e-02 -7.34898746e-02 3.77206169e-02 -3.49576771e-01
4.01663542e-01 -5.13991237e-01 -9.78408277e-01 8.04986954e-01
-5.32275915e-01 1.85032353e-01 3.67060840e-01 2.44174406e-01
6.21250868e-01 -4.19989705e-01 1.63138643e-01 -1.67849824e-01
-7.00731426e-02 -6.01393342e-01 -5.32313585e-01 1.36170447e-01
-2.28830636e-01 -3.56218696e-01 -8.70297402e-02 -4.39688623e-01
-9.88345683e-01 1.51581421e-01 6.90345541e-02 -4.20736223e-01
-2.69510806e-01 9.67905670e-02 3.60110134e-01 2.72283942e-01
7.71213472e-01 -1.22051686e-01 -4.85516101e-01 -1.04487903e-01
3.67698103e-01 3.22288901e-01 9.61650312e-01 -2.33372644e-01
1.65060297e-01 7.30276346e-01 -1.60164386e-01 -4.20687884e-01
-8.67970526e-01 -6.48781419e-01 -8.02680850e-01 -8.54242086e-01
1.23378968e+00 -1.11717880e+00 -7.41050184e-01 3.66664886e-01
-1.08945715e+00 -8.64602149e-01 -1.45580158e-01 7.46718228e-01
-7.38639355e-01 4.49915826e-01 -8.13418806e-01 -5.45566559e-01
-1.33053780e-01 -6.71682417e-01 1.09677374e+00 2.94688761e-01
-8.10578108e-01 -6.48740888e-01 2.78814316e-01 5.67975879e-01
-1.73620563e-02 4.14149672e-01 -5.08304775e-01 -3.47255558e-01
-6.73845112e-01 2.34991312e-02 -1.70717523e-01 7.45172203e-02
-2.25015610e-01 4.46238458e-01 -8.60795736e-01 1.52749764e-02
-6.55445218e-01 -2.06119910e-01 1.12375510e+00 7.52818227e-01
1.01945400e+00 -1.23504035e-01 -4.05811161e-01 4.26957875e-01
9.31679189e-01 1.22853287e-01 8.56578290e-01 4.57247138e-01
3.55562568e-01 2.44804118e-02 1.00091255e+00 7.86732435e-01
3.19882125e-01 8.30338955e-01 5.20469368e-01 2.10094854e-01
-4.31750566e-01 -2.39621609e-01 6.84760451e-01 3.55772942e-01
-6.06751382e-01 -5.79914451e-01 -1.06606996e+00 6.01475835e-01
-2.28478074e+00 -1.47866809e+00 -3.52789462e-01 1.70682275e+00
5.74644327e-01 4.42022860e-01 3.49393338e-01 -2.38793895e-01
8.96226823e-01 5.77750921e-01 -5.22505403e-01 8.71858280e-03
-5.88621572e-02 6.98726103e-02 7.80291438e-01 3.47861588e-01
-1.50174642e+00 1.22167897e+00 6.49552822e+00 8.13660383e-01
-4.54376131e-01 3.74098480e-01 4.41087365e-01 -5.65886378e-01
3.81319493e-01 2.88550586e-01 -7.84817338e-01 6.76032364e-01
1.03590870e+00 2.50484943e-01 1.05784737e-01 6.68348372e-01
6.55516088e-01 -8.45286846e-01 -8.29272985e-01 8.46290648e-01
-1.49700001e-01 -1.53135908e+00 -6.43691778e-01 5.94670363e-02
8.44935715e-01 6.83204651e-01 -3.03141624e-01 2.62369573e-01
6.79408669e-01 -6.45031691e-01 1.07993782e+00 6.47294044e-01
8.08340132e-01 -4.58613783e-01 5.89458644e-01 8.67248774e-02
-1.46766651e+00 6.97787181e-02 -4.64956760e-02 -3.48023564e-01
5.91767371e-01 3.11182290e-01 -9.50536191e-01 1.72800303e-01
1.01274276e+00 1.24967682e+00 -5.74857593e-01 1.19978678e+00
-8.24284852e-01 9.53491926e-01 -4.72821325e-01 1.11852936e-01
4.17702466e-01 2.41654739e-01 5.79567730e-01 1.46537507e+00
3.72311831e-01 3.30874234e-01 1.13122351e-01 2.64187962e-01
-1.31034076e-01 -4.64338034e-01 -3.28314185e-01 2.00425223e-01
5.99177599e-01 1.34277260e+00 -1.06882620e+00 -5.03677905e-01
-2.56623507e-01 1.16841137e+00 1.42329440e-01 1.45249411e-01
-1.54880130e+00 -3.23143154e-02 6.28544867e-01 -1.33877113e-01
5.12340724e-01 -4.99138892e-01 -2.24240590e-02 -1.14126337e+00
9.05075595e-02 -4.62298304e-01 7.59229720e-01 -1.04653096e+00
-5.52076936e-01 1.84819624e-01 7.53722414e-02 -1.53891325e+00
-1.57816306e-01 -2.94346035e-01 -7.27159441e-01 2.51546830e-01
-8.92217994e-01 -9.65854228e-01 -3.88842672e-01 4.14821655e-01
8.06198061e-01 2.11888880e-01 3.57885987e-01 2.04249963e-01
-6.80744350e-01 2.81324416e-01 -4.05812144e-01 3.73200893e-01
8.91367495e-01 -1.17481470e+00 7.50534475e-01 1.34404445e+00
2.35496476e-01 1.59728140e-01 6.31356120e-01 -1.07684338e+00
-8.57130826e-01 -1.21349597e+00 8.71070385e-01 -1.04583967e+00
9.20991957e-01 -1.36250541e-01 -3.92393053e-01 1.02715707e+00
3.14125806e-01 3.88708204e-01 4.85409886e-01 -3.25889103e-02
-2.87467331e-01 2.91510075e-01 -9.62077081e-01 7.26686180e-01
1.55856824e+00 -2.59874344e-01 -4.75436568e-01 2.66575456e-01
5.27999103e-01 -6.01729393e-01 -1.06398642e+00 4.59852487e-01
9.96267378e-01 -1.11835778e+00 6.99300230e-01 -2.55294442e-01
4.92628813e-01 -7.72160769e-01 -2.38046587e-01 -6.47691488e-01
-5.85241437e-01 -5.99000514e-01 -4.88788933e-01 9.01146948e-01
4.59412873e-01 -2.23170951e-01 9.77798045e-01 3.47651362e-01
-1.28390834e-01 -4.80712712e-01 -1.23057473e+00 -8.82807434e-01
-6.06029868e-01 -1.03782213e+00 -2.42439564e-02 7.88670599e-01
1.13232560e-01 -4.45646979e-02 -5.54036915e-01 9.37257484e-02
3.62385124e-01 -4.61174220e-01 7.14784205e-01 -5.85273683e-01
-2.86309808e-01 -3.75676602e-01 -7.00723946e-01 -1.18576801e+00
-1.46152914e-01 -6.45024776e-01 1.45193696e-01 -1.71464133e+00
2.32917115e-01 3.96743640e-02 -5.52195489e-01 9.12965477e-01
1.00141183e-01 8.44276667e-01 2.83299237e-01 3.40808541e-01
-1.53390515e+00 2.59109795e-01 9.32601035e-01 1.40569627e-01
-9.12390351e-02 -2.24677995e-01 -1.49222597e-01 1.09735632e+00
1.36916375e+00 -6.02351487e-01 -2.48230752e-02 -3.74834299e-01
1.19953103e-01 -1.01993568e-02 6.09349668e-01 -1.59200501e+00
3.56755972e-01 -3.10677230e-01 6.87744319e-01 -1.01442051e+00
3.59530360e-01 -2.33861014e-01 2.44503349e-01 5.24927616e-01
-3.21267962e-01 2.12823157e-03 2.40103945e-01 6.94545805e-01
5.44797555e-02 3.64502743e-02 5.42990208e-01 -7.00854585e-02
-1.49227679e+00 1.87871456e-01 -7.32241333e-01 1.07897483e-01
1.20510948e+00 -4.86614287e-01 -6.48725390e-01 -3.77175659e-01
-8.59428883e-01 4.07856673e-01 4.99301672e-01 4.42387819e-01
4.60177332e-01 -1.38861573e+00 -6.50865376e-01 -4.88426179e-01
8.05157647e-02 -4.42933470e-01 3.62585515e-01 1.24291384e+00
-6.75492942e-01 2.11133227e-01 -1.80214122e-01 -7.11741626e-01
-1.38173759e+00 -1.88298836e-01 2.18765199e-01 -1.09952092e-01
-4.49335009e-01 8.99834633e-01 -2.54389882e-01 7.45152682e-02
1.46585166e-01 -5.11045039e-01 -2.58458015e-02 -9.45784003e-02
6.12443805e-01 9.62459624e-01 -3.96335185e-01 -5.96509278e-01
-7.04855144e-01 2.50455141e-01 3.03275406e-01 -5.20012796e-01
1.05515623e+00 8.20895880e-02 1.74372077e-01 2.67007083e-01
7.43833423e-01 -1.78544875e-02 -1.94878399e+00 -1.52294375e-02
1.76146567e-01 -4.43805575e-01 3.57035547e-02 -1.02722573e+00
-7.57836044e-01 1.99745119e-01 4.64303493e-01 -2.35152259e-01
9.12489891e-01 2.52100974e-01 5.80322862e-01 2.58264512e-01
4.34000552e-01 -1.41757441e+00 2.90180415e-01 6.55992448e-01
6.38762236e-01 -1.14827764e+00 3.37095737e-01 -1.15390435e-01
-5.93607783e-01 9.47616637e-01 8.30923855e-01 -8.26212540e-02
2.41729513e-01 3.08156759e-01 -2.23289028e-01 -1.78691313e-01
-1.02266347e+00 -3.56059045e-01 3.06542099e-01 2.75249273e-01
4.07501340e-01 7.82975927e-02 -4.54374433e-01 2.26885766e-01
2.16795400e-01 4.54251260e-01 4.47508425e-01 1.17730093e+00
-5.78472495e-01 -7.24936604e-01 -1.30205244e-01 3.27924460e-01
-7.01051295e-01 8.71937070e-03 -4.31065887e-01 7.37976968e-01
3.95178646e-01 1.16453362e+00 1.97934136e-01 -7.60295153e-01
1.71181545e-01 -1.95845172e-01 4.08347726e-01 -4.33643758e-01
-4.82195586e-01 1.08616546e-01 6.46349967e-01 -1.35917330e+00
-9.25418437e-01 -9.74198341e-01 -1.34789383e+00 -3.09480488e-01
-7.18229041e-02 -2.91858077e-01 2.94103712e-01 5.63242078e-01
5.83453417e-01 3.41533244e-01 9.92399752e-02 -9.68285024e-01
2.92011589e-01 -1.09790695e+00 -1.99212149e-01 -1.11940995e-01
-1.51829630e-01 -5.86375177e-01 -2.79856533e-01 2.50813365e-01] | [8.271923065185547, 0.3623332977294922] |
f4619326-c4b7-4182-a52e-d0a2a411e6ea | dynamic-object-tracking-and-masking-for | 2008.00072 | null | https://arxiv.org/abs/2008.00072v1 | https://arxiv.org/pdf/2008.00072v1.pdf | Dynamic Object Tracking and Masking for Visual SLAM | In dynamic environments, performance of visual SLAM techniques can be impaired by visual features taken from moving objects. One solution is to identify those objects so that their visual features can be removed for localization and mapping. This paper presents a simple and fast pipeline that uses deep neural networks, extended Kalman filters and visual SLAM to improve both localization and mapping in dynamic environments (around 14 fps on a GTX 1080). Results on the dynamic sequences from the TUM dataset using RTAB-Map as visual SLAM suggest that the approach achieves similar localization performance compared to other state-of-the-art methods, while also providing the position of the tracked dynamic objects, a 3D map free of those dynamic objects, better loop closure detection with the whole pipeline able to run on a robot moving at moderate speed. | ['François Michaud', 'Pier-Marc Comtois-Rivet', 'François Grondin', 'Jean-Samuel Lauzon', 'Mathieu Labbé', 'Jonathan Vincent'] | 2020-07-31 | null | null | null | null | ['loop-closure-detection'] | ['computer-vision'] | [-3.72492701e-01 -3.67409557e-01 1.16056427e-01 -2.43656561e-01
-4.10330407e-02 -6.83924019e-01 7.31961966e-01 2.72639424e-01
-1.09446049e+00 7.23935068e-01 -3.87041807e-01 -2.31221154e-01
-3.73135917e-02 -3.45597893e-01 -8.37363899e-01 -4.05684382e-01
-6.56613469e-01 8.47756982e-01 9.45214212e-01 -4.36597615e-01
4.30506468e-01 1.09169507e+00 -1.60024559e+00 -2.72038430e-01
3.67729098e-01 9.00911570e-01 8.85472298e-01 9.75572646e-01
5.89455552e-02 7.11532891e-01 -4.26801771e-01 5.32838583e-01
4.27299768e-01 3.72981548e-01 -4.29956347e-01 -2.49627545e-01
8.66839528e-01 -4.55384880e-01 -4.37380701e-01 8.59899819e-01
4.06883657e-01 3.85811329e-01 2.48540044e-01 -1.37722409e+00
-8.79457593e-02 -7.51714408e-02 -4.03664052e-01 4.88078862e-01
5.70391536e-01 3.98660570e-01 3.44802797e-01 -1.01753104e+00
8.79295409e-01 1.37681818e+00 1.06342530e+00 -1.09578885e-01
-1.05212855e+00 -4.73758906e-01 -2.36044332e-01 3.96682560e-01
-1.55913925e+00 -4.85781342e-01 -4.16895635e-02 -6.36034846e-01
1.55905962e+00 -1.27284795e-01 6.13321006e-01 8.02186191e-01
6.97858870e-01 1.43703163e-01 6.93035364e-01 -2.69674391e-01
1.88586861e-01 1.36747658e-01 1.03148362e-02 1.04151618e+00
4.57963258e-01 3.71667117e-01 -6.23161197e-01 3.15073803e-02
6.66233957e-01 8.22045356e-02 -1.73381194e-01 -1.03306568e+00
-1.57876122e+00 7.58827329e-01 7.25086153e-01 1.34193912e-01
-4.38030392e-01 5.11893690e-01 4.70641166e-01 2.85191506e-01
2.80246860e-03 1.10507801e-01 -5.26239336e-01 -1.68319449e-01
-6.64749920e-01 3.06375980e-01 5.10832131e-01 1.04392743e+00
1.37307549e+00 1.79458693e-01 1.52022004e-01 5.90827800e-02
5.00800669e-01 1.15601695e+00 5.37953854e-01 -8.37970555e-01
1.77082479e-01 3.95365000e-01 6.16680622e-01 -1.32813966e+00
-9.45294142e-01 -1.63608477e-01 -2.78599471e-01 9.10247803e-01
2.68215269e-01 -2.51441859e-02 -1.27146327e+00 1.04849422e+00
3.97582740e-01 4.85320278e-02 1.79624289e-01 1.17362237e+00
7.68561304e-01 5.71235955e-01 -3.18956703e-01 3.88635099e-01
1.07796395e+00 -1.07031798e+00 -7.65993476e-01 -9.49347913e-01
6.64918780e-01 -8.36906374e-01 4.28699523e-01 3.22529107e-01
-4.06229466e-01 -9.38662469e-01 -1.40445340e+00 -9.64715555e-02
-5.44144332e-01 4.83429343e-01 6.29369557e-01 3.16583037e-01
-1.42512298e+00 7.40250587e-01 -1.27480054e+00 -1.03461027e+00
-9.76051018e-02 5.16901731e-01 -7.85700977e-01 1.83549404e-01
-8.77636671e-01 1.56454217e+00 8.12630653e-01 2.08105102e-01
-1.31913805e+00 -2.58816302e-01 -1.14346802e+00 -1.38026997e-01
2.90732503e-01 -4.70110387e-01 1.03946745e+00 -8.91440630e-01
-1.41026413e+00 6.79768562e-01 -2.88620412e-01 -9.24104393e-01
8.37514222e-01 -5.59261322e-01 -8.84128958e-02 7.99845234e-02
3.21127564e-01 8.39895964e-01 7.41010427e-01 -1.12687707e+00
-1.19331837e+00 -3.21034223e-01 -3.90609682e-01 4.30730700e-01
4.86821324e-01 -2.76740938e-01 -3.04627210e-01 3.60750735e-01
4.98833209e-01 -1.13049471e+00 -3.27830583e-01 2.27306440e-01
4.80374768e-02 3.96437570e-02 1.27019203e+00 -5.21499097e-01
1.30857870e-01 -2.11402726e+00 -8.11664686e-02 2.01566499e-02
-1.44689485e-01 2.62199253e-01 1.53398380e-01 5.62145114e-01
1.96044758e-01 -5.73640108e-01 5.32592773e-01 -5.82849503e-01
-4.95060422e-02 2.06137717e-01 -9.08273458e-02 1.13637626e+00
-4.21637028e-01 6.92692220e-01 -8.90299499e-01 -2.08928436e-01
8.90191853e-01 4.28732127e-01 2.55841374e-01 -3.63194682e-02
6.79642111e-02 4.74027485e-01 -1.91567466e-01 5.78748465e-01
9.53655899e-01 1.62624970e-01 -1.71562001e-01 1.94760397e-01
-6.47092760e-01 -7.02075586e-02 -1.43223476e+00 2.15406203e+00
-2.59732425e-01 1.37863767e+00 2.85424352e-01 -5.19773364e-01
1.27277601e+00 -2.55252123e-01 1.31441414e-01 -7.73133278e-01
1.44392952e-01 3.98896754e-01 -4.17045444e-01 -4.40174967e-01
1.11484969e+00 3.61859709e-01 1.29791990e-01 -1.50752783e-01
1.44684955e-01 1.34432063e-01 6.98606670e-02 1.56734988e-01
1.27737916e+00 4.24525827e-01 3.20975780e-01 -4.10533935e-01
5.21926165e-01 7.67269552e-01 3.60107481e-01 1.16795766e+00
-4.79333669e-01 3.73890638e-01 -2.93731540e-01 -9.90734279e-01
-1.05721128e+00 -1.18764675e+00 1.85817182e-01 9.18991208e-01
7.96027601e-01 -6.99415877e-02 4.02692817e-02 -3.93707931e-01
3.04035336e-01 2.34470725e-01 -5.20026624e-01 1.34027019e-01
-6.19823039e-01 -1.12973936e-01 4.10315305e-01 1.07533984e-01
4.41659749e-01 -9.82704937e-01 -1.65255797e+00 2.11593762e-01
4.76780199e-02 -1.10430419e+00 3.51847082e-01 6.08068764e-01
-6.54899716e-01 -9.57398236e-01 -4.20484424e-01 -6.69390857e-01
4.06717926e-01 7.76206434e-01 7.92446196e-01 -1.38334453e-01
-3.31732005e-01 2.22132444e-01 -4.33300883e-01 -4.18670833e-01
-2.40927920e-01 -1.32472202e-01 2.46614978e-01 -4.83942509e-01
1.85421616e-01 -1.49507180e-01 -3.89169663e-01 2.11998686e-01
-8.63267183e-02 4.97067794e-02 5.04597485e-01 5.29711425e-01
4.17380482e-01 -2.66599238e-01 -2.65694708e-01 -5.14442995e-02
-1.79653242e-01 -2.78012991e-01 -1.28153479e+00 -1.21249191e-01
-4.84833807e-01 -2.50249002e-02 3.30558300e-01 -3.54503989e-01
-7.13020861e-01 7.31368840e-01 1.77121043e-01 -5.28958261e-01
-4.06890869e-01 1.34005845e-01 5.07391691e-01 -8.20575714e-01
8.88787210e-01 3.53783756e-01 1.61256164e-01 -3.48426163e-01
2.38921180e-01 4.24183369e-01 7.45844066e-01 2.35160172e-01
8.67903233e-01 1.02183819e+00 3.15755278e-01 -7.77672112e-01
-1.74130633e-01 -8.95360291e-01 -8.81867409e-01 -3.39158893e-01
7.27439165e-01 -1.26443326e+00 -7.20747113e-01 2.90945560e-01
-1.24223244e+00 -4.17653829e-01 1.71134904e-01 7.80623376e-01
-6.55080795e-01 4.27286059e-01 -2.19035029e-01 -7.00777173e-01
-2.79418647e-01 -1.15182233e+00 1.09776199e+00 4.56739187e-01
1.03412092e-01 -8.45383048e-01 3.85512382e-01 -3.15859646e-01
5.60290396e-01 3.41858059e-01 -1.06736563e-01 -4.64932203e-01
-9.61342573e-01 -3.41581613e-01 -2.03484520e-01 -2.85220951e-01
-9.52054858e-02 -1.95082992e-01 -6.74008429e-01 -7.97526062e-01
-3.90687674e-01 -4.12845314e-02 9.10113931e-01 3.42396557e-01
-1.49255455e-01 2.25959852e-01 -1.00575387e+00 8.73416901e-01
1.87865424e+00 2.91016221e-01 2.94375360e-01 1.11365569e+00
5.80894172e-01 1.05292805e-01 1.17243397e+00 4.39540923e-01
3.38561386e-01 7.06677675e-01 1.03222227e+00 -9.68935937e-02
6.39890805e-02 -2.50528157e-02 4.10843730e-01 -2.63754219e-01
2.56665945e-01 -9.48855430e-02 -1.17184293e+00 7.00017154e-01
-2.28881788e+00 -4.99561369e-01 -5.92800379e-01 2.15805340e+00
-3.05635452e-01 1.03370436e-01 -2.74911702e-01 -4.01194811e-01
6.85401201e-01 4.44636419e-02 -1.47764251e-01 -1.75240710e-01
-4.93693836e-02 -4.01322126e-01 1.33452106e+00 7.66384602e-01
-1.27818108e+00 1.24801207e+00 6.02537203e+00 2.95741886e-01
-1.42409563e+00 3.23476702e-01 -5.10091305e-01 4.16620187e-02
7.38892078e-01 4.18405920e-01 -1.14988530e+00 2.00135306e-01
9.96208489e-01 4.13063653e-02 2.22390339e-01 1.26831758e+00
3.78892213e-01 -9.05233741e-01 -7.87187099e-01 1.06532681e+00
1.46338224e-01 -1.24964750e+00 -5.55980086e-01 6.44496782e-03
4.30197358e-01 9.96488869e-01 -2.87168831e-01 2.03158647e-01
4.17570442e-01 -7.76798487e-01 1.13861680e+00 5.86943090e-01
2.18598038e-01 -8.29457223e-01 1.10497296e+00 5.90649545e-01
-1.21055448e+00 -1.24924980e-01 -8.85131955e-01 -3.99629086e-01
3.22894335e-01 7.09077045e-02 -1.60764968e+00 7.20047593e-01
1.10823345e+00 5.63294053e-01 -1.05672419e+00 1.48789799e+00
-4.17759567e-02 -3.77320141e-01 -7.33171642e-01 -1.82215005e-01
6.99485660e-01 2.61412591e-01 7.55629659e-01 1.34818244e+00
7.72107899e-01 -7.23953426e-01 5.01621544e-01 3.88050020e-01
9.40988004e-01 -1.69275716e-01 -9.66187656e-01 7.22431600e-01
3.33687276e-01 1.36173022e+00 -1.00617659e+00 -3.50674093e-01
-8.68546739e-02 1.13111115e+00 5.11470020e-01 1.73723876e-01
-7.09228992e-01 -3.92787963e-01 5.48748493e-01 -1.32471502e-01
5.81039965e-01 -9.36345577e-01 2.91873783e-01 -7.91563451e-01
-1.67301610e-01 -2.61086971e-01 -1.73614398e-02 -1.31355095e+00
-3.47113818e-01 7.22882688e-01 -1.30298048e-01 -1.28236580e+00
-4.12390411e-01 -8.39714587e-01 -4.61455919e-02 9.38352406e-01
-1.32845783e+00 -1.14770675e+00 -9.13318932e-01 5.24443746e-01
2.84285575e-01 -2.69697934e-01 5.48278451e-01 2.51037572e-02
3.12532097e-01 -1.38809398e-01 4.80300575e-01 -6.09136708e-02
7.98709035e-01 -1.15781057e+00 6.21856153e-01 1.26007795e+00
3.00048769e-01 3.91417474e-01 1.20423937e+00 -9.19026554e-01
-1.62894177e+00 -8.06202888e-01 7.50698507e-01 -5.47564745e-01
5.16534507e-01 -5.80317497e-01 -6.54854238e-01 1.02929127e+00
2.07078010e-01 1.65442899e-01 -4.71908331e-01 -2.42285013e-01
3.11274111e-01 -8.15816894e-02 -1.06306887e+00 2.22744852e-01
7.55052209e-01 -1.13790005e-01 -4.99777108e-01 4.25195247e-01
5.58274150e-01 -1.08013725e+00 -1.71881899e-01 3.57476890e-01
4.69626576e-01 -1.44868529e+00 9.16657925e-01 1.60187721e-01
-8.08557212e-01 -8.94934714e-01 -2.57807914e-02 -1.31313205e+00
-4.21551198e-01 -5.20694494e-01 1.14291877e-01 5.55897176e-01
-7.57637993e-02 -5.82791030e-01 8.76767218e-01 -2.65919149e-01
-3.04565072e-01 3.79443586e-01 -1.34739172e+00 -9.72620010e-01
-8.34652781e-01 -2.89991140e-01 8.22030157e-02 4.85958368e-01
-4.55440223e-01 1.63364932e-01 -5.31448543e-01 6.95583224e-01
5.31183422e-01 -1.85731411e-01 1.32271326e+00 -1.29987919e+00
2.25026086e-01 9.13716108e-02 -1.14082718e+00 -8.75085652e-01
1.91455632e-01 -5.09105265e-01 5.21937370e-01 -1.68623853e+00
-2.70932913e-01 -3.81883085e-01 1.65603995e-01 5.52572072e-01
4.32806671e-01 2.43390903e-01 2.21421972e-01 2.53940076e-01
-9.36562538e-01 2.55249500e-01 5.77282965e-01 1.09232977e-01
-6.85518757e-02 -3.61453414e-01 5.21871090e-01 6.59857690e-01
4.80707169e-01 -7.13819146e-01 -7.56289512e-02 -5.22854745e-01
1.90734282e-01 2.83966474e-02 7.24258721e-01 -1.78409696e+00
7.03546524e-01 1.58323348e-01 7.25376725e-01 -1.38405585e+00
5.81304908e-01 -1.18148470e+00 4.11729366e-01 1.11303723e+00
4.12841797e-01 6.18343830e-01 6.55352890e-01 6.26637816e-01
3.51886526e-02 -4.33718055e-01 6.53237700e-01 -3.71569932e-01
-1.82898629e+00 -1.94284450e-02 -7.31033266e-01 -7.40069032e-01
1.22064638e+00 -3.98968607e-01 -3.06726962e-01 -3.05382520e-01
-8.50612521e-01 2.89533645e-01 8.90525043e-01 6.11648321e-01
5.97206652e-01 -1.03026187e+00 -4.12955403e-01 4.11073893e-01
1.40899658e-01 5.69159612e-02 3.28689009e-01 9.09956098e-01
-1.44868374e+00 8.71834576e-01 -6.59626901e-01 -1.28923976e+00
-1.49181008e+00 7.38093555e-01 5.89707375e-01 1.26052901e-01
-9.13954735e-01 6.52720451e-01 -1.63155720e-01 -4.06763285e-01
3.95127654e-01 -3.08118701e-01 -4.94835526e-02 -2.40648493e-01
6.28645480e-01 4.12022322e-01 2.38322720e-01 -9.05457675e-01
-9.17591751e-01 5.59384406e-01 2.48498350e-01 -2.62758911e-01
1.06269038e+00 -7.91954100e-01 8.26446572e-04 5.77768028e-01
8.59009326e-01 -1.10682294e-01 -1.64342141e+00 -5.24613857e-02
2.10953906e-01 -7.19497859e-01 1.22153826e-01 -7.01217175e-01
-4.68792915e-01 6.39425099e-01 1.53244615e+00 -8.47599953e-02
4.51080322e-01 -2.02261031e-01 9.74055286e-03 8.75700116e-01
9.44414496e-01 -8.60704362e-01 -7.01835454e-02 1.10929370e+00
6.23431444e-01 -1.48507583e+00 1.35216787e-01 3.66579778e-02
-5.47600508e-01 1.41713595e+00 7.15094984e-01 -4.98319894e-01
3.56765576e-02 5.03063381e-01 5.84957480e-01 -1.90519914e-02
-3.66922498e-01 -5.09251416e-01 -7.31066689e-02 1.02476561e+00
-2.80028909e-01 -3.04405451e-01 1.26778916e-01 -5.16492248e-01
-6.08484820e-02 -2.24366829e-01 6.65462673e-01 1.26119673e+00
-1.01837111e+00 -2.39686415e-01 -6.05111599e-01 -3.10206801e-01
-1.91620573e-01 1.75775185e-01 -7.81635717e-02 1.33705235e+00
2.89046258e-01 7.49578834e-01 3.42435062e-01 -2.39163071e-01
2.83202201e-01 -1.75859094e-01 4.00173396e-01 -3.62011462e-01
-5.63048720e-01 3.48582491e-03 7.85987750e-02 -1.06327629e+00
-2.04903007e-01 -6.16248965e-01 -1.44693482e+00 -2.18507782e-01
-3.28548610e-01 -1.47342887e-02 1.32757127e+00 8.93017530e-01
4.64362264e-01 3.20391923e-01 -4.74660238e-03 -1.64905834e+00
-2.45061234e-01 -1.15024495e+00 -5.37807345e-01 -9.29491967e-02
9.99555707e-01 -9.72616374e-01 -2.38384500e-01 -2.48539761e-01] | [7.366080284118652, -2.0457417964935303] |
49f7ab05-d2c3-4370-ae43-2c9889d4d48e | federatednilm-a-distributed-and-privacy | 2108.03591 | null | https://arxiv.org/abs/2108.03591v1 | https://arxiv.org/pdf/2108.03591v1.pdf | FederatedNILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring based on Federated Deep Learning | Non-intrusive load monitoring (NILM), which usually utilizes machine learning methods and is effective in disaggregating smart meter readings from the household-level into appliance-level consumptions, can help to analyze electricity consumption behaviours of users and enable practical smart energy and smart grid applications. However, smart meters are privately owned and distributed, which make real-world applications of NILM challenging. To this end, this paper develops a distributed and privacy-preserving federated deep learning framework for NILM (FederatedNILM), which combines federated learning with a state-of-the-art deep learning architecture to conduct NILM for the classification of typical states of household appliances. Through extensive comparative experiments, the effectiveness of the proposed FederatedNILM framework is demonstrated. | ['Xizhong Chen', 'Qian Wang', 'Fanlin Meng', 'Shuang Dai'] | 2021-08-08 | null | null | null | null | ['non-intrusive-load-monitoring', 'non-intrusive-load-monitoring', 'non-intrusive-load-monitoring'] | ['knowledge-base', 'miscellaneous', 'time-series'] | [-4.43498999e-01 -2.42379621e-01 -2.77173519e-01 -7.62041211e-01
-7.47054458e-01 -4.01149958e-01 6.12754762e-01 -1.57314941e-01
3.76406424e-02 7.90634274e-01 2.73363709e-01 -4.52435583e-01
1.78242251e-01 -1.02841592e+00 -2.95925945e-01 -1.11014700e+00
-2.29785413e-01 2.46044829e-01 -7.25156963e-01 3.51143926e-01
-2.82896906e-01 2.94527501e-01 -1.04932487e+00 2.38715142e-01
9.69258606e-01 1.38206029e+00 -4.46077168e-01 1.61530226e-01
2.17308909e-01 1.14895260e+00 -6.60675645e-01 -4.45010930e-01
2.55641341e-01 -3.23205531e-01 -7.36896276e-01 -1.83695823e-01
2.05563996e-02 -1.13205004e+00 -4.36192542e-01 1.34755063e+00
6.37717605e-01 4.58625983e-03 5.16823649e-01 -2.07046986e+00
-7.45775580e-01 1.07238626e+00 -4.22787845e-01 -1.90747917e-01
2.12970421e-01 5.19536555e-01 9.13227975e-01 1.24010712e-01
-4.03325170e-01 9.93507147e-01 5.99682570e-01 2.10659459e-01
-1.09443295e+00 -1.12401807e+00 1.38727322e-01 7.48142898e-01
-1.23966634e+00 -3.03348720e-01 8.79413426e-01 -1.82336923e-02
1.31900144e+00 5.10013044e-01 4.83887881e-01 1.12647891e+00
4.98450935e-01 1.30740333e+00 1.29018092e+00 4.71296534e-02
7.50389636e-01 5.08342013e-02 1.42498121e-01 -3.45998071e-02
5.10395825e-01 6.82329834e-02 -1.42799661e-01 -4.62391794e-01
-5.72411530e-02 5.42963147e-01 -1.30921513e-01 -2.00152650e-01
-6.01505339e-01 8.28296304e-01 4.37924564e-01 4.24472451e-01
-5.56308329e-01 5.05368710e-02 1.01843727e+00 2.60917962e-01
5.07256567e-01 -1.52699262e-01 -7.96847641e-01 -1.16572697e-02
-1.00507629e+00 -1.95901513e-01 1.19044363e+00 7.53184676e-01
7.92725205e-01 5.42476535e-01 6.96878508e-02 1.75845265e-01
3.89537990e-01 5.47568142e-01 9.94987547e-01 -7.94212222e-01
7.89581388e-02 9.06548917e-01 -6.01072749e-03 -5.04619122e-01
-6.55756891e-01 1.26982808e-01 -1.50715864e+00 2.00053006e-01
-2.04387203e-01 -5.26349902e-01 -1.31262958e-01 1.43216503e+00
2.73308635e-01 3.83181363e-01 2.14487642e-01 4.90678221e-01
4.64642495e-01 6.94729209e-01 3.38691175e-01 -3.20239961e-01
1.36112213e+00 -6.72507524e-01 -1.01521695e+00 2.92272657e-01
7.02352166e-01 1.50096133e-01 5.39090157e-01 4.74985659e-01
-6.63385749e-01 -1.07162163e-01 -1.06763828e+00 3.29104997e-02
-8.24907005e-01 -2.40673572e-01 6.52142584e-01 7.77695775e-01
-7.63857543e-01 6.08663976e-01 -1.00150156e+00 -6.47969171e-02
1.04404032e+00 5.38577557e-01 -3.28509331e-01 1.58060297e-01
-1.29268444e+00 8.54467452e-01 6.76630080e-01 -2.86020003e-02
-9.98493433e-01 -6.04382694e-01 -9.94798303e-01 4.10062194e-01
3.88124376e-03 -2.64814377e-01 1.67946768e+00 -4.81298089e-01
-1.46494877e+00 3.54424745e-01 3.83714944e-01 -1.17145240e+00
4.86638576e-01 -1.21494271e-01 -9.19260263e-01 -2.54294574e-01
-7.24680200e-02 -1.45716369e-01 7.68736362e-01 -8.48164320e-01
-9.19548750e-01 -7.05364406e-01 -4.98826712e-01 -2.64328331e-01
-5.13688087e-01 -4.23228711e-01 6.82666123e-01 -1.70222148e-01
-6.61609292e-01 -2.12276980e-01 5.75361438e-02 -6.35547876e-01
-5.64635098e-01 -7.54302084e-01 1.73377275e+00 -1.09572959e+00
1.00442863e+00 -2.04762554e+00 -7.83487022e-01 1.26873523e-01
1.76683486e-01 5.36473811e-01 1.65082514e-01 3.92757803e-01
-1.53447270e-01 -1.83721185e-01 -7.85804838e-02 -5.32430708e-01
9.34993505e-01 2.60316044e-01 -2.14079186e-01 9.05279577e-01
-5.30995607e-01 1.51003397e+00 -8.59255254e-01 -1.47271812e-01
1.22030354e+00 5.45704186e-01 1.91878989e-01 4.73085403e-01
-2.65182793e-01 3.28542650e-01 -4.32654917e-01 6.71175599e-01
9.72355485e-01 -2.22661316e-01 3.07236016e-01 -4.61168200e-01
1.10247046e-01 4.06234831e-01 -9.41734850e-01 1.27814937e+00
-7.67695606e-01 3.37693214e-01 2.27979407e-01 -1.27092028e+00
7.86354780e-01 6.74034953e-01 9.02906597e-01 -1.00938869e+00
6.72466397e-01 -8.26959461e-02 -4.98971701e-01 -2.65037924e-01
-9.02542397e-02 2.38806382e-01 -2.83826590e-01 8.88160765e-01
-5.46360668e-03 1.74787492e-01 -3.22151482e-01 -2.01473981e-01
1.23268390e+00 -2.29063317e-01 9.61408019e-01 -2.07367718e-01
6.54499769e-01 -7.10406780e-01 6.30071938e-01 3.51851493e-01
-6.49649858e-01 -5.05027831e-01 -4.75622341e-02 -8.35249603e-01
-5.76683283e-01 -9.29735482e-01 -1.27167851e-01 8.99278939e-01
-3.01551580e-01 -1.61866531e-01 -8.02281022e-01 -1.01008546e+00
4.27127570e-01 1.56517637e+00 -2.55070955e-01 -4.97690082e-01
-3.26555014e-01 -9.19846416e-01 4.65934604e-01 5.88518143e-01
1.22346294e+00 -1.24063265e+00 -7.84589529e-01 3.74941230e-01
-1.38360336e-01 -8.27438533e-01 -3.37061048e-01 5.76278865e-01
-2.10580453e-01 -1.26333308e+00 -3.59622799e-02 -6.42441869e-01
1.77570432e-01 -5.73690385e-02 1.24760091e+00 -6.75607145e-01
-1.35268569e-01 2.83842415e-01 -1.18011702e-02 -5.04752278e-01
-3.73612612e-01 3.37288231e-01 2.35290617e-01 3.93552542e-01
1.40782249e+00 -1.15310133e+00 -8.25578511e-01 1.77693013e-02
-8.12417448e-01 -3.79513234e-01 3.20141017e-01 4.57522750e-01
1.73803076e-01 8.60549808e-01 1.06924474e+00 -7.51288533e-01
6.21023715e-01 -7.71478415e-01 -1.04790354e+00 6.45289347e-02
-1.14098144e+00 -3.82220775e-01 1.26091564e+00 -1.20206103e-01
-9.27567303e-01 5.69056086e-02 -2.76363164e-01 -2.27941364e-01
-7.20470667e-01 -2.52310216e-01 -1.08769691e+00 1.27283543e-01
-1.85378447e-01 5.64683616e-01 -2.97045529e-01 -8.46378148e-01
6.09031856e-01 1.31341922e+00 9.98539090e-01 -3.23037989e-02
6.26315534e-01 3.64602059e-01 -1.81212172e-01 -3.62662345e-01
-4.65552270e-01 -3.74669522e-01 -4.35140550e-01 2.99033552e-01
8.64627838e-01 -1.24721563e+00 -1.61913252e+00 1.10567009e+00
-7.87044704e-01 -3.39366347e-01 -6.75398707e-01 1.96592823e-01
-5.89795649e-01 3.30341399e-01 -7.22508490e-01 -1.03755713e+00
-1.14971697e+00 -9.57637012e-01 8.35209608e-01 3.35288912e-01
-3.42539042e-01 -1.18371964e+00 9.20381472e-02 2.77575344e-01
5.24416149e-01 3.35344642e-01 9.33320999e-01 -1.29960907e+00
-5.53254426e-01 -6.39112592e-01 -2.08503641e-02 8.59294593e-01
7.88244247e-01 -8.56437624e-01 -1.25367224e+00 -8.95590603e-01
4.78683084e-01 -5.05684137e-01 2.34978944e-01 2.71285743e-01
1.54946268e+00 -1.20286441e+00 -1.81053981e-01 9.46493685e-01
1.63273418e+00 3.34117830e-01 6.24324918e-01 3.41185361e-01
7.94918478e-01 -9.17952806e-02 -2.28806958e-01 9.35276508e-01
9.19107616e-01 -2.55637281e-02 8.66774678e-01 5.40403798e-02
5.83227694e-01 -3.91265690e-01 3.18460822e-01 8.03430021e-01
8.23328376e-01 -2.90719420e-01 -2.65783966e-01 6.44079924e-01
-1.96992385e+00 -9.62069333e-01 3.57424200e-01 1.76240551e+00
6.32852793e-01 -4.67619896e-01 2.84736633e-01 4.37330246e-01
3.93343598e-01 4.55306441e-01 -1.48206234e+00 -4.78615433e-01
-7.83830956e-02 1.06809847e-01 7.03859270e-01 6.93200156e-02
-1.27799904e+00 1.98729247e-01 5.62495708e+00 7.18467355e-01
-9.72269297e-01 4.60794836e-01 7.48460889e-01 1.00865766e-01
-8.30648839e-03 -5.49161077e-01 -4.36199635e-01 1.08634436e+00
1.24584639e+00 -5.63444138e-01 7.72001624e-01 1.23228192e+00
2.76721925e-01 1.57958835e-01 -1.54694235e+00 1.30607808e+00
-3.66937608e-01 -9.46661770e-01 -2.56901532e-01 3.19557488e-01
9.69216585e-01 4.03741837e-01 -2.28551012e-02 3.16919118e-01
1.25032496e+00 -1.08858740e+00 -6.98462948e-02 2.05960467e-01
5.10084987e-01 -1.26264775e+00 9.74806786e-01 5.25380135e-01
-1.44935417e+00 -5.68974316e-01 3.73261757e-02 -1.68014362e-01
3.86870583e-03 6.20029390e-01 -4.29157078e-01 7.67819285e-01
1.11743820e+00 8.64563584e-01 -2.69457102e-01 5.64902246e-01
-8.72167870e-02 7.85309136e-01 -4.54412550e-01 1.43259034e-01
1.23250708e-01 -3.93391281e-01 -1.38293788e-01 1.04515660e+00
1.05138356e-02 -2.11893424e-01 3.72196376e-01 8.23550999e-01
-5.07202625e-01 -1.71010777e-01 -7.00068414e-01 2.18568742e-01
6.41917765e-01 1.59889388e+00 2.09907219e-02 -2.64273584e-01
-7.90385664e-01 1.18135464e+00 8.95571522e-03 2.43530616e-01
-4.79846776e-01 -2.00527132e-01 1.16693878e+00 -3.59030128e-01
4.11298066e-01 3.62991571e-01 -3.13427836e-01 -1.33143401e+00
-2.40610853e-01 -9.69548285e-01 7.23419309e-01 -3.57812434e-01
-2.15681410e+00 -3.57796513e-02 -2.13522524e-01 -8.67055714e-01
-8.12059879e-01 -1.92806929e-01 -1.33608150e+00 6.74542427e-01
-1.61430597e+00 -1.44680309e+00 -9.18621197e-02 1.11134279e+00
1.93035528e-01 -2.97051400e-01 1.13968551e+00 3.38026434e-01
-8.12816143e-01 9.11982894e-01 9.76504922e-01 6.05070114e-01
4.00702609e-03 -1.44274676e+00 7.27745175e-01 7.62965202e-01
-3.99309732e-02 -2.01633647e-01 1.61492139e-01 -2.63570338e-01
-1.54295719e+00 -1.78173792e+00 4.96860087e-01 -6.63685799e-02
5.83140373e-01 -4.58468556e-01 -8.17865133e-01 1.10426247e+00
8.39339614e-01 3.33842263e-02 9.61631715e-01 -4.25042301e-01
-2.60130733e-01 -7.12324440e-01 -2.07419205e+00 2.55528390e-02
2.87107974e-01 -7.66752899e-01 -4.73846823e-01 4.65803027e-01
4.74913448e-01 4.06186193e-01 -1.27001607e+00 1.33612096e-01
1.84610710e-01 -9.02752280e-01 6.50330245e-01 -3.72076154e-01
-5.38117707e-01 -2.03489631e-01 -4.27884132e-01 -1.63509285e+00
-4.81259197e-01 -9.59176898e-01 -1.18907714e+00 1.79974329e+00
-5.44953942e-01 -1.26399446e+00 7.00507820e-01 8.52552950e-01
3.67330045e-01 -4.08238530e-01 -1.40117300e+00 -6.52730286e-01
3.82066518e-01 -4.50028241e-01 1.94440770e+00 1.00754201e+00
2.50966042e-01 2.37876981e-01 -4.37162399e-01 4.63150352e-01
1.16911972e+00 2.37357423e-01 5.21833241e-01 -1.03386664e+00
1.40928909e-01 -3.21874231e-01 -5.23749173e-01 -6.38734698e-01
6.97354317e-01 -7.38019943e-01 -2.88152754e-01 -1.46310925e+00
1.30103100e-02 1.08425692e-01 -9.68983173e-01 9.32137370e-01
4.58794922e-01 1.21714368e-01 1.42743617e-01 -8.57334062e-02
-6.95978582e-01 8.11503291e-01 2.63745964e-01 -7.20557034e-01
1.64696246e-01 2.50157386e-01 -8.50814164e-01 7.60417521e-01
1.36784029e+00 1.11682817e-01 -3.47708225e-01 -1.86308295e-01
-4.81422335e-01 -2.67822206e-01 3.20830911e-01 -8.86971831e-01
9.26967934e-02 -1.55085381e-02 6.64242506e-01 -1.21268916e+00
-1.12787329e-01 -1.45953584e+00 2.75096685e-01 6.99534595e-01
3.49478386e-02 -9.15863812e-02 -1.47914469e-01 2.36894146e-01
1.56898856e-01 3.33264291e-01 7.62961388e-01 -2.39799589e-01
-7.44780064e-01 5.43916643e-01 -3.64270002e-01 -2.63548791e-01
1.23074853e+00 3.32155973e-01 -3.56279045e-01 -6.28082573e-01
-2.00317845e-01 8.95880520e-01 3.24800372e-01 3.63057166e-01
9.43993106e-02 -1.70895612e+00 -6.45269454e-01 5.36885798e-01
-2.32283488e-01 1.44742563e-01 1.06678106e-01 2.37747535e-01
2.42985174e-01 6.00354254e-01 1.08302459e-01 -4.09455210e-01
-7.14626074e-01 1.01031935e+00 5.61770141e-01 -3.76529962e-01
-8.51276398e-01 2.24782266e-02 6.60453737e-02 -5.91530979e-01
7.38998771e-01 -3.93303216e-01 2.03906372e-01 5.69869094e-02
8.41065288e-01 1.09807622e+00 4.37698543e-01 -5.48600733e-01
-5.37935376e-01 -1.41184136e-01 -2.61667725e-02 7.43677855e-01
1.40437269e+00 -4.43502843e-01 -3.65258425e-01 4.02386576e-01
1.81145477e+00 -8.95083845e-01 -1.24848664e+00 -1.95242539e-01
-1.93484142e-01 -7.54539296e-02 3.45740974e-01 -1.08980715e+00
-1.50549388e+00 5.53251803e-01 1.02098095e+00 4.34288800e-01
1.54164577e+00 -2.57763565e-01 1.61812890e+00 4.20523912e-01
6.89088285e-01 -1.03916657e+00 -7.56880283e-01 -1.69602394e-01
2.38847127e-03 -1.33294570e+00 -8.26967135e-02 5.88742554e-01
-1.65459201e-01 5.64156711e-01 5.30953586e-01 5.12398705e-02
9.90821123e-01 6.47193789e-01 7.52618834e-02 2.16840297e-01
-6.21361613e-01 3.28734398e-01 -3.60762149e-01 1.10444999e+00
-3.42182279e-01 6.50645912e-01 1.92048326e-01 9.35437262e-01
-3.46537799e-01 3.02321970e-01 1.83819812e-02 9.09579873e-01
1.66881904e-01 -8.29846144e-01 -3.28805029e-01 8.84862721e-01
-5.24693668e-01 2.55793929e-01 -3.34395953e-02 2.74229050e-01
3.60707730e-01 1.27141821e+00 2.33862624e-01 -3.93132031e-01
5.63807711e-02 3.12912285e-01 -2.87820883e-02 2.87213653e-01
-6.14379287e-01 -3.50684702e-01 -5.38764536e-01 -6.08511627e-01
-1.75889328e-01 -6.45327628e-01 -1.03164995e+00 -9.32785153e-01
-1.51272804e-01 6.47799820e-02 3.92789841e-01 1.06402087e+00
2.85521746e-01 3.24091733e-01 1.48687375e+00 -8.22730124e-01
-1.20703554e+00 -9.49858963e-01 -1.07013500e+00 6.08155906e-01
7.48260379e-01 1.14271797e-01 -4.64626133e-01 -2.59637475e-01] | [5.8642659187316895, 2.779656410217285] |
41bfba85-1fc6-4494-817b-b26660f86001 | virtualpose-learning-generalizable-3d-human | 2207.09949 | null | https://arxiv.org/abs/2207.09949v1 | https://arxiv.org/pdf/2207.09949v1.pdf | VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual Data | While monocular 3D pose estimation seems to have achieved very accurate results on the public datasets, their generalization ability is largely overlooked. In this work, we perform a systematic evaluation of the existing methods and find that they get notably larger errors when tested on different cameras, human poses and appearance. To address the problem, we introduce VirtualPose, a two-stage learning framework to exploit the hidden "free lunch" specific to this task, i.e. generating infinite number of poses and cameras for training models at no cost. To that end, the first stage transforms images to abstract geometry representations (AGR), and then the second maps them to 3D poses. It addresses the generalization issue from two aspects: (1) the first stage can be trained on diverse 2D datasets to reduce the risk of over-fitting to limited appearance; (2) the second stage can be trained on diverse AGR synthesized from a large number of virtual cameras and poses. It outperforms the SOTA methods without using any paired images and 3D poses from the benchmarks, which paves the way for practical applications. Code is available at https://github.com/wkom/VirtualPose. | ['Yizhou Wang', 'Wenjun Zeng', 'Xiaoxuan Ma', 'Chunyu Wang', 'Jiajun Su'] | 2022-07-20 | null | null | null | null | ['3d-pose-estimation', '3d-multi-person-pose-estimation-absolute', '3d-multi-person-pose-estimation'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [-5.62102441e-03 5.15907705e-02 -2.41831057e-02 -3.38811457e-01
-7.59660721e-01 -6.74321115e-01 6.10691786e-01 -5.45824528e-01
-1.17149279e-01 4.80016738e-01 1.06534339e-01 -1.34901881e-01
2.42869183e-01 -5.33406675e-01 -1.06028366e+00 -6.64766073e-01
2.52312779e-01 4.72387075e-01 1.56476647e-01 -1.91290714e-02
3.32342461e-02 4.04188544e-01 -1.54761076e+00 4.39185742e-03
6.12933278e-01 9.66076195e-01 7.55281225e-02 5.05474269e-01
4.03430730e-01 4.85135555e-01 -2.63941884e-01 -8.04681182e-01
6.97638631e-01 -3.11510473e-01 -5.23598731e-01 4.13795710e-01
9.42432225e-01 -5.96996427e-01 -3.56918216e-01 9.95741427e-01
5.55883765e-01 -6.52449951e-02 5.21885931e-01 -1.26805282e+00
-5.72574019e-01 9.23671871e-02 -5.56261182e-01 -3.40338200e-01
5.99401414e-01 2.89470881e-01 8.39148045e-01 -1.23123300e+00
7.17225075e-01 1.33433306e+00 6.88312888e-01 5.52141666e-01
-1.18606544e+00 -5.96721053e-01 4.66820896e-02 7.07928538e-02
-1.59114790e+00 -3.70076358e-01 8.35529208e-01 -5.29967606e-01
5.61356843e-01 1.40573263e-01 5.91601074e-01 1.53919125e+00
1.56916566e-02 7.91636169e-01 1.08467948e+00 -2.97630459e-01
3.56926434e-02 1.53925553e-01 -2.54693538e-01 5.99962950e-01
2.52752364e-01 1.76271617e-01 -4.36078787e-01 -9.58298892e-03
9.75224018e-01 6.29098564e-02 -3.27724487e-01 -9.16548908e-01
-1.24914491e+00 7.37644494e-01 5.64611852e-01 -2.06705630e-01
-2.22532511e-01 5.55002838e-02 2.85152555e-01 2.71234304e-01
5.12566388e-01 3.89211088e-01 -4.64958072e-01 1.35455579e-01
-6.58308208e-01 2.85084695e-01 6.02845669e-01 1.19836271e+00
8.62975717e-01 -2.07395405e-01 1.97997317e-01 7.82259047e-01
2.37586305e-01 6.04756594e-01 1.84684575e-01 -1.00970876e+00
6.78325176e-01 6.09216094e-01 8.62058774e-02 -1.01768196e+00
-3.69842470e-01 -4.68819290e-01 -7.21782804e-01 2.40515411e-01
6.29596829e-01 -7.17196390e-02 -7.23986268e-01 1.69328070e+00
5.82008779e-01 3.92715186e-02 -1.24773256e-01 1.17815030e+00
9.26798582e-01 4.27289486e-01 -3.53510827e-01 2.69544035e-01
1.11996543e+00 -1.16595817e+00 -2.79449970e-01 -3.84416789e-01
3.95400405e-01 -9.73927021e-01 1.11798036e+00 4.67882842e-01
-1.03732944e+00 -6.96867526e-01 -1.16039813e+00 -2.81221747e-01
-2.46341199e-01 4.29562271e-01 5.50019145e-01 6.79342210e-01
-1.10859013e+00 4.95959997e-01 -7.20067203e-01 -4.63168561e-01
1.93804383e-01 2.98195541e-01 -5.40183544e-01 -3.87295991e-01
-9.10915911e-01 7.39827514e-01 2.08136156e-01 2.68977642e-01
-7.63743758e-01 -4.53268319e-01 -1.07362306e+00 -3.20069820e-01
7.94572592e-01 -9.40953791e-01 1.12117958e+00 -1.11117649e+00
-1.55610740e+00 9.87727404e-01 2.00189780e-02 -1.15296645e-02
9.80505228e-01 -5.37107944e-01 -3.25563140e-02 3.16220522e-02
-4.54051867e-02 8.01334083e-01 8.58708918e-01 -1.39129698e+00
-1.58077627e-01 -5.77752948e-01 2.02030301e-01 4.42293644e-01
-4.97567505e-02 -2.81698644e-01 -1.06737936e+00 -5.46676278e-01
3.41274053e-01 -1.31669211e+00 -1.62100926e-01 2.24139556e-01
-5.36198020e-01 4.90181670e-02 4.77656990e-01 -6.22042298e-01
5.97557485e-01 -2.08294439e+00 4.64312047e-01 9.18714702e-03
4.02310453e-02 1.39066443e-01 -8.06894302e-02 3.66902053e-01
-4.96735834e-02 -2.01231375e-01 1.87826931e-01 -5.64152598e-01
9.08758417e-02 4.27487865e-02 -9.38747078e-03 6.67572498e-01
2.25548938e-01 8.18789780e-01 -7.81093657e-01 -3.17386329e-01
5.14155269e-01 4.53646123e-01 -6.67612135e-01 1.83016822e-01
-6.39750808e-02 6.41703963e-01 -3.18519264e-01 6.34965897e-01
8.82559538e-01 -4.07223672e-01 2.60322720e-01 -3.46688449e-01
1.47649437e-01 1.82085946e-01 -1.45201027e+00 1.88471591e+00
-2.71324873e-01 3.25588614e-01 -9.47894230e-02 -7.26686239e-01
8.70860100e-01 2.25739151e-01 4.15775537e-01 -6.89011872e-01
2.16395438e-01 2.65400290e-01 -3.46460521e-01 -3.82634789e-01
3.21010739e-01 7.98632577e-02 -1.86362714e-01 1.62631899e-01
1.44078404e-01 -2.02332452e-01 -9.62416604e-02 -8.20888020e-03
6.79131508e-01 7.22875178e-01 2.67364025e-01 -5.56150861e-02
5.93512774e-01 1.50477337e-02 6.02142751e-01 3.67316961e-01
6.67142943e-02 9.87954676e-01 2.75436461e-01 -6.84441805e-01
-1.23355639e+00 -1.26983976e+00 9.40210093e-03 6.83103979e-01
3.96158963e-01 -4.31097060e-01 -7.06647575e-01 -6.20537996e-01
5.84217627e-03 3.48572493e-01 -5.80866814e-01 -1.29797176e-01
-4.94248092e-01 -5.35026610e-01 2.12733135e-01 5.97617924e-01
4.94753689e-01 -6.49005711e-01 -4.82179612e-01 -2.36688852e-01
-2.19161794e-01 -1.41362667e+00 -5.68583250e-01 -1.61310375e-01
-8.16189587e-01 -1.21578074e+00 -8.31797183e-01 -5.21405041e-01
7.85734057e-01 5.09864986e-01 1.28493679e+00 8.49514976e-02
-1.04307629e-01 3.64934444e-01 -5.19751608e-01 -2.82499969e-01
-2.58154154e-01 1.25565678e-01 1.93667278e-01 8.15379843e-02
3.41429740e-01 -5.63271165e-01 -7.76788235e-01 6.78480685e-01
-6.53957903e-01 4.44866210e-01 7.70227969e-01 6.80930138e-01
6.16757929e-01 -3.38082582e-01 2.05547959e-01 -8.39250088e-01
-4.47745211e-02 -2.76802063e-01 -7.34223306e-01 7.99554959e-02
-3.42461467e-01 -1.75050586e-01 6.23311579e-01 -3.21122527e-01
-8.03406537e-01 5.21123290e-01 -1.62758663e-01 -6.21043146e-01
-1.08444132e-01 1.03313833e-01 -4.26980078e-01 -9.65314358e-02
6.40291810e-01 2.00899363e-01 8.47198889e-02 -7.20692813e-01
4.43050355e-01 5.36420703e-01 5.90011358e-01 -5.86871743e-01
1.08038104e+00 4.41617727e-01 6.16274029e-02 -7.65357792e-01
-8.80371928e-01 -5.15945673e-01 -9.92404461e-01 -2.05291942e-01
8.31655622e-01 -1.31425250e+00 -4.41015393e-01 4.99435455e-01
-9.40533519e-01 -3.39770973e-01 3.43917571e-02 6.88280284e-01
-7.30640471e-01 4.75986272e-01 -4.57145512e-01 -5.13946295e-01
-1.35407522e-01 -1.27358222e+00 1.39404714e+00 2.11543456e-01
-6.14096336e-02 -7.54524529e-01 -4.36111391e-02 6.06326103e-01
-7.56435245e-02 4.36089128e-01 4.59397256e-01 -3.51542085e-01
-8.10259879e-01 -2.81007379e-01 -2.07398281e-01 4.76624489e-01
7.97426179e-02 -1.48257166e-01 -1.05574846e+00 -5.28559864e-01
-7.41972625e-02 -5.15626729e-01 4.15053993e-01 1.60433844e-01
1.15542614e+00 -9.88379344e-02 -9.83898193e-02 9.37686026e-01
1.44003081e+00 -2.20503926e-01 6.84519410e-01 2.72811800e-01
8.82608056e-01 5.27270973e-01 5.57496309e-01 1.85728028e-01
5.23216486e-01 1.07830441e+00 6.55845463e-01 -3.12399477e-01
-2.56693661e-01 -5.28512895e-01 4.19542283e-01 7.44982779e-01
-2.22851142e-01 1.45158488e-02 -7.45894909e-01 2.56916344e-01
-1.73018253e+00 -7.14924335e-01 -1.22778885e-01 2.47022748e+00
5.03322899e-01 -5.48304468e-02 3.32665622e-01 -8.16554874e-02
5.50009727e-01 3.74197699e-02 -6.16429865e-01 -2.77863275e-02
6.54163025e-03 -1.76176359e-03 5.30486345e-01 1.95648164e-01
-1.02084970e+00 7.40813732e-01 5.59266949e+00 5.35170734e-01
-1.09226060e+00 8.08558688e-02 6.32421076e-01 -2.58448124e-01
-5.37520088e-02 -4.82339226e-03 -7.95494437e-01 3.77462626e-01
4.74259049e-01 2.80024707e-01 3.61818939e-01 1.02615142e+00
-7.10264733e-03 3.89922187e-02 -1.29151404e+00 1.13373387e+00
2.78536737e-01 -9.99243855e-01 1.39484152e-01 1.90464363e-01
7.69275963e-01 7.28357537e-03 -5.64290322e-02 2.73731023e-01
3.87009159e-02 -9.69509780e-01 9.74660575e-01 4.17288274e-01
8.25574696e-01 -5.32660425e-01 7.78165340e-01 5.56080222e-01
-1.13829029e+00 7.96185657e-02 -6.13452852e-01 -1.96481701e-02
4.16687354e-02 3.86201113e-01 -6.36529207e-01 1.05481303e+00
7.48167157e-01 6.63671315e-01 -9.05577958e-01 1.08561742e+00
-4.01321083e-01 9.32285041e-02 -3.67312491e-01 9.93375182e-02
6.81200847e-02 -3.69638711e-01 2.70146608e-01 7.91561782e-01
4.60659951e-01 -2.63790339e-01 3.01722616e-01 8.17548871e-01
1.16321985e-02 7.39637986e-02 -6.57833397e-01 3.34606498e-01
2.72130549e-01 1.33276820e+00 -5.13880551e-01 -2.29260381e-02
-7.46163130e-01 1.12886739e+00 3.42804343e-01 2.82279342e-01
-9.64934647e-01 1.31764606e-01 3.03654641e-01 2.47407407e-01
2.57010847e-01 -3.57740790e-01 -5.36822074e-04 -1.36820948e+00
2.98953027e-01 -1.04555452e+00 2.98499823e-01 -9.49556410e-01
-1.26065063e+00 4.92805570e-01 1.27424553e-01 -1.46818054e+00
-2.16951102e-01 -9.04734075e-01 -3.34608227e-01 7.83598721e-01
-1.31707942e+00 -1.39116490e+00 -6.30083501e-01 6.36138678e-01
5.47298491e-01 1.80441499e-01 5.70377886e-01 4.24623728e-01
-6.48412168e-01 7.55169690e-01 -7.60481879e-02 1.85860068e-01
9.45015371e-01 -1.13234520e+00 5.46610355e-01 6.83021188e-01
2.82544047e-01 4.19415057e-01 5.30224800e-01 -3.22832823e-01
-1.73008013e+00 -9.89982486e-01 5.91759920e-01 -8.54274035e-01
2.68633485e-01 -6.41016543e-01 -5.39966047e-01 8.40288758e-01
-1.29347280e-01 7.01256618e-02 4.75603253e-01 4.77428287e-02
-3.65331680e-01 -6.57326952e-02 -8.15086722e-01 7.07909644e-01
1.25096643e+00 -2.99075484e-01 -3.28316271e-01 3.24361712e-01
5.40973485e-01 -7.28543520e-01 -8.23747396e-01 4.16644037e-01
6.09399080e-01 -1.20804965e+00 1.28306544e+00 -1.43497348e-01
5.51300526e-01 -2.90102929e-01 -3.67170155e-01 -1.16866279e+00
-1.64748698e-01 -5.67241728e-01 3.11921760e-02 1.00493681e+00
3.67679656e-01 -5.45024395e-01 7.76523769e-01 4.38717306e-01
-9.59701389e-02 -8.75208259e-01 -8.09669197e-01 -9.09004152e-01
1.42192870e-01 -1.68925196e-01 6.36550188e-01 7.83447266e-01
-4.46376115e-01 4.34027493e-01 -6.64308012e-01 2.04508707e-01
6.15821660e-01 2.17382014e-01 1.49488318e+00 -1.13852334e+00
-4.40531939e-01 -7.48142377e-02 -4.02734250e-01 -1.44016230e+00
-1.39818802e-01 -8.30464721e-01 -7.96034783e-02 -1.12804437e+00
4.24749970e-01 -2.68102527e-01 2.02817023e-01 2.20347837e-01
-2.21902505e-01 5.53164542e-01 2.52220720e-01 3.20077866e-01
-5.11561334e-01 5.84384739e-01 1.52672744e+00 2.37079710e-01
4.24347147e-02 1.49520755e-01 -6.31943405e-01 8.95464420e-01
6.51765227e-01 -1.45490184e-01 -5.24788022e-01 -5.14688253e-01
3.36638927e-01 -4.23573405e-02 7.70954013e-01 -1.04492116e+00
-5.30268159e-03 -2.59953178e-02 6.90550625e-01 -6.61686897e-01
5.92041135e-01 -8.98690999e-01 4.75126982e-01 2.67460734e-01
9.64848101e-02 1.53234497e-01 4.58335690e-03 5.80890775e-01
1.02956660e-01 -1.04104690e-01 7.36147523e-01 -3.41704130e-01
-6.07663691e-01 4.20772344e-01 2.50880867e-01 -5.97376376e-02
1.01800394e+00 -4.05433595e-01 -1.13493890e-01 -4.47811037e-01
-5.37549257e-01 1.73251316e-01 1.03843224e+00 5.40964663e-01
3.54089856e-01 -1.57576334e+00 -5.95928371e-01 3.72803122e-01
2.41553962e-01 3.43653440e-01 2.14386538e-01 9.04270351e-01
-6.80573881e-01 2.65818149e-01 -1.31217942e-01 -9.47119832e-01
-1.18336880e+00 5.66359818e-01 4.12093997e-01 -7.49455094e-02
-7.76463866e-01 6.31600916e-01 3.69339615e-01 -7.42367685e-01
2.72900224e-01 -7.25688785e-02 1.08464077e-01 -1.48709103e-01
2.61312991e-01 2.09432721e-01 1.55832902e-01 -8.56542051e-01
-2.69568950e-01 9.73775446e-01 4.08399701e-02 1.42058998e-01
1.30899918e+00 -2.20815122e-01 2.86758274e-01 3.49330962e-01
1.23518229e+00 5.45637980e-02 -1.67751694e+00 -2.84113944e-01
-2.86450565e-01 -7.88540602e-01 -2.57682294e-01 -5.36008835e-01
-1.10658753e+00 7.77585685e-01 4.70533550e-01 -1.37538522e-01
1.02577329e+00 1.43151596e-01 7.73538768e-01 2.83855110e-01
6.19240880e-01 -9.55660045e-01 3.04335445e-01 2.99446046e-01
8.84139299e-01 -1.32875669e+00 1.97151899e-01 -7.13022649e-01
-7.03480303e-01 1.04746592e+00 6.49075747e-01 -2.33031660e-01
3.51713121e-01 -1.19863011e-01 1.85907856e-01 -3.13015103e-01
-4.22428012e-01 -8.14340450e-03 4.89806950e-01 5.32916605e-01
3.49655896e-01 -1.22539541e-02 -3.99191454e-02 4.94305700e-01
-4.83636141e-01 -1.26710534e-01 4.14066076e-01 5.99269271e-01
-2.27699373e-02 -1.09957254e+00 -4.65660602e-01 7.78131783e-02
-2.29855657e-01 2.88665444e-01 -6.48615956e-01 1.07084143e+00
9.06277001e-02 7.60574460e-01 -1.82004854e-01 -5.01225233e-01
5.21957815e-01 -2.52943859e-02 7.31694937e-01 -6.82565153e-01
-3.06006104e-01 1.21493600e-01 -2.33848440e-03 -8.27039599e-01
-4.74245340e-01 -7.87167490e-01 -5.11286199e-01 -3.54198366e-01
-3.63537699e-01 -2.03315035e-01 5.09910345e-01 7.35827506e-01
3.12050879e-01 2.36871168e-01 7.81876445e-01 -1.38657272e+00
-9.20650899e-01 -8.22567940e-01 -4.27357316e-01 7.56090164e-01
1.05250597e-01 -9.20281231e-01 -4.56990838e-01 7.58333057e-02] | [7.9364752769470215, -2.298448085784912] |
aa680ae7-0436-44dc-a69a-9d35597bac92 | ell-2-norm-flow-diffusion-in-near-linear-time | 2105.14629 | null | https://arxiv.org/abs/2105.14629v2 | https://arxiv.org/pdf/2105.14629v2.pdf | $\ell_2$-norm Flow Diffusion in Near-Linear Time | Diffusion is a fundamental graph procedure and has been a basic building block in a wide range of theoretical and empirical applications such as graph partitioning and semi-supervised learning on graphs. In this paper, we study computationally efficient diffusion primitives beyond random walk. We design an $\widetilde{O}(m)$-time randomized algorithm for the $\ell_2$-norm flow diffusion problem, a recently proposed diffusion model based on network flow with demonstrated graph clustering related applications both in theory and in practice. Examples include finding locally-biased low conductance cuts. Using a known connection between the optimal dual solution of the flow diffusion problem and the local cut structure, our algorithm gives an alternative approach for finding such cuts in nearly linear time. From a technical point of view, our algorithm contributes a novel way of dealing with inequality constraints in graph optimization problems. It adapts the high-level algorithmic framework of nearly linear time Laplacian system solvers, but requires several new tools: vertex elimination under constraints, a new family of graph ultra-sparsifiers, and accelerated proximal gradient methods with inexact proximal mapping computation. | ['Di Wang', 'Richard Peng', 'Li Chen'] | 2021-05-30 | null | null | null | null | ['graph-partitioning'] | ['graphs'] | [ 1.65706560e-01 4.56606477e-01 -3.63301843e-01 4.94020917e-02
-4.40987796e-01 -5.31212270e-01 2.53002322e-03 3.48339289e-01
-1.53693795e-01 6.56366825e-01 -2.17214897e-02 -4.39511627e-01
-5.79085827e-01 -1.12867343e+00 -4.83209848e-01 -7.46403039e-01
-6.25571609e-01 7.11934686e-01 1.17008276e-01 -2.92014003e-01
3.83372217e-01 6.86798692e-01 -8.11184227e-01 -2.09903732e-01
1.21067774e+00 7.43585169e-01 -8.66301060e-02 6.04631901e-01
-3.71691406e-01 6.68374896e-01 1.23577870e-01 -4.13842380e-01
5.97574234e-01 -7.96777308e-01 -1.02777088e+00 3.74802232e-01
2.93902278e-01 3.22375149e-01 -4.87387151e-01 1.28651571e+00
5.64712226e-01 2.99297601e-01 4.32027102e-01 -1.20022130e+00
-6.01468921e-01 9.85617280e-01 -1.24407780e+00 3.89465988e-01
4.33155686e-01 -5.60391247e-02 1.02333510e+00 -7.14731872e-01
1.01923752e+00 9.37082887e-01 8.29587102e-01 2.68787652e-01
-1.52278888e+00 -2.55731702e-01 3.37803960e-01 2.36377120e-01
-1.69119620e+00 -3.15905660e-02 9.10319626e-01 -4.83048856e-01
8.34131598e-01 5.59314072e-01 1.09131145e+00 3.45593840e-01
-4.27077077e-02 6.02598548e-01 1.00153041e+00 -3.64262134e-01
3.44965309e-01 9.52030718e-02 1.32661626e-01 1.16716111e+00
6.42980337e-01 -4.18261439e-01 -4.91254956e-01 -2.37653553e-01
7.45401919e-01 -2.51057953e-01 -6.76593959e-01 -7.64650583e-01
-9.47819471e-01 1.17189777e+00 6.46054387e-01 4.77311879e-01
-2.62047261e-01 3.20025563e-01 2.44621605e-01 3.72391433e-01
6.73447132e-01 3.34477201e-02 -5.21395728e-02 1.71345308e-01
-1.02064264e+00 1.29988859e-03 1.25700581e+00 9.50523078e-01
9.68459189e-01 7.64534771e-02 1.42416880e-01 5.33555388e-01
3.30996037e-01 5.99589825e-01 -1.75066993e-01 -8.83967996e-01
5.43808877e-01 7.74129272e-01 -3.68046671e-01 -1.58462548e+00
-4.98826921e-01 -6.57418847e-01 -1.24308240e+00 -5.58901690e-02
5.30232549e-01 -3.01089697e-02 -5.04264951e-01 1.50768554e+00
7.66182125e-01 2.29015678e-01 -4.69221592e-01 8.68096173e-01
3.83212388e-01 6.63010418e-01 -5.94323218e-01 -8.51660848e-01
6.96469784e-01 -9.41183448e-01 -6.26901209e-01 -4.74436134e-02
1.10127151e+00 -6.34258270e-01 7.96607673e-01 5.48800945e-01
-1.44610572e+00 1.18919596e-01 -7.38668382e-01 -1.32022858e-01
-1.11096144e-01 -3.83295864e-01 9.33698058e-01 7.88039804e-01
-1.46343195e+00 8.02760243e-01 -6.99694455e-01 -5.52998900e-01
3.81494015e-01 4.82051075e-01 -3.32470894e-01 -3.13524961e-01
-6.49059832e-01 5.91717839e-01 -8.96670520e-02 2.84091532e-01
-4.71106887e-01 -6.89624727e-01 -7.18160331e-01 7.98361897e-02
7.46748507e-01 -7.33215630e-01 3.42805535e-01 -5.42888522e-01
-1.31269050e+00 1.03151977e+00 -1.14875600e-01 -4.59238052e-01
6.84999406e-01 2.84807920e-01 3.88610945e-03 2.43090704e-01
1.08598977e-01 8.65110457e-02 7.41681039e-01 -8.19513440e-01
-5.97442314e-02 -6.21546268e-01 -1.86572641e-01 2.96788305e-01
-4.14085776e-01 -4.62194055e-01 -3.55814785e-01 -3.95005375e-01
4.55185682e-01 -9.26344395e-01 -8.41194570e-01 9.09829214e-02
-4.66851413e-01 -6.17350489e-02 5.58380544e-01 -4.16590422e-01
1.56559765e+00 -1.79111123e+00 9.01438594e-01 1.08190274e+00
7.77242899e-01 -7.70200342e-02 6.87996149e-02 8.16231072e-01
1.58446040e-02 9.28878635e-02 -7.30767608e-01 2.06181332e-02
-9.39622521e-02 9.44387615e-02 8.35711882e-02 9.78856504e-01
-5.71751356e-01 8.24330151e-01 -9.67881560e-01 -4.73369867e-01
8.54215920e-02 3.76398206e-01 -7.47814655e-01 -2.85971701e-01
8.81061554e-02 1.66647241e-01 -4.26711619e-01 2.87220627e-01
8.79423559e-01 -4.54982817e-01 4.88143086e-01 -1.51695758e-01
-1.03249811e-01 -3.84688556e-01 -1.83592522e+00 2.17974973e+00
-3.46296102e-01 4.00589585e-01 9.24664259e-01 -1.46693659e+00
7.71637082e-01 -1.23939343e-01 8.91038835e-01 -3.25419307e-01
9.67419744e-02 3.93049985e-01 -7.90327340e-02 -4.33855057e-01
1.44333020e-01 1.76975187e-02 2.28387222e-01 7.96024501e-01
-1.79870769e-01 -2.86569327e-01 6.61093116e-01 9.46874619e-01
1.53832841e+00 -3.25175881e-01 2.50047237e-01 -8.86636138e-01
6.32605851e-01 1.26984417e-01 3.71619672e-01 4.72175062e-01
3.37023847e-02 2.92827249e-01 8.06501567e-01 -3.68504852e-01
-6.44504726e-01 -7.63940811e-01 8.25520158e-02 6.40093446e-01
2.90269107e-01 -6.52934372e-01 -9.87519562e-01 -6.62767529e-01
1.07104078e-01 1.45216122e-01 -7.29387641e-01 -5.41959628e-02
-6.21674418e-01 -9.65347290e-01 7.68894479e-02 2.42379531e-01
2.22263828e-01 -3.88587028e-01 -5.32221012e-02 2.23088250e-01
6.14476465e-02 -8.21881473e-01 -7.76406467e-01 5.34298569e-02
-1.03971601e+00 -1.27019131e+00 -6.44706130e-01 -8.10427606e-01
1.08892190e+00 5.66920280e-01 9.58944023e-01 4.59940195e-01
-7.93817103e-01 5.94253540e-01 -5.15657961e-02 2.50198305e-01
6.08417504e-02 2.35288173e-01 -1.05155952e-01 3.46619487e-01
-1.23352356e-01 -8.05940449e-01 -7.39108920e-01 1.82981163e-01
-7.38115609e-01 -8.08189884e-02 3.16264272e-01 6.56393230e-01
8.16483974e-01 8.99125189e-02 2.92077243e-01 -1.29134846e+00
8.74444544e-01 -6.60804510e-01 -7.42686570e-01 1.16164476e-01
-7.85016119e-01 1.59603119e-01 5.05293250e-01 -1.34720266e-01
-6.40220404e-01 2.43076488e-01 -4.65049669e-02 -3.15324038e-01
6.72872484e-01 7.29617774e-01 -4.62921374e-02 -6.77271903e-01
8.18117678e-01 -1.28378291e-02 -3.84410024e-02 -3.17146629e-01
8.23442936e-01 1.70487478e-01 -2.54559470e-03 -5.55248201e-01
1.01188958e+00 1.02964759e+00 5.05539298e-01 -1.00745845e+00
-5.37887692e-01 -7.20217526e-01 -5.88424265e-01 -3.12055916e-01
6.57677889e-01 -3.79190981e-01 -8.56264234e-01 6.20039478e-02
-8.49808276e-01 -6.08789265e-01 -5.86400449e-01 3.14039379e-01
-4.23410684e-01 7.06788063e-01 -7.10165739e-01 -7.50026703e-01
-2.99921066e-01 -9.18660760e-01 6.98194265e-01 -7.57619888e-02
8.11990164e-03 -1.54240167e+00 2.79792011e-01 1.80711553e-01
5.19429445e-01 5.26895761e-01 7.49708652e-01 -8.12363327e-02
-7.15626061e-01 2.12420803e-02 -2.12198064e-01 -2.97996048e-02
-1.93421364e-01 -5.34695461e-02 -2.10134596e-01 -6.48892045e-01
1.81037202e-01 1.23232499e-01 9.29559231e-01 5.74488163e-01
9.38291788e-01 -2.25497156e-01 -6.75910056e-01 9.46122766e-01
1.81392109e+00 -4.44319546e-01 3.89658630e-01 -3.46116960e-01
1.03706098e+00 6.14090323e-01 2.00957701e-01 3.84918213e-01
2.37054318e-01 3.80418539e-01 2.98361331e-01 -3.34400892e-01
-2.92749941e-01 -4.65297364e-02 6.10992173e-03 1.27311504e+00
-2.35771075e-01 -2.21494302e-01 -8.75420809e-01 6.66975379e-01
-2.07441092e+00 -9.45713699e-01 -9.44054186e-01 2.29800987e+00
4.00987893e-01 -3.09410803e-02 2.04955637e-01 3.60314488e-01
1.03863323e+00 9.75953862e-02 -5.35518169e-01 -5.01100361e-01
-5.53862900e-02 3.53142232e-01 8.22338045e-01 1.05595064e+00
-4.12329942e-01 8.97076130e-01 5.72333813e+00 1.09403729e+00
-9.23274219e-01 4.50991839e-01 3.45455706e-01 -1.44602656e-01
-6.86167777e-01 2.07039937e-01 -4.07571971e-01 1.52229920e-01
4.65542704e-01 -5.71403205e-01 9.23152149e-01 7.49457777e-01
1.61718935e-01 -2.88283408e-01 -9.09725010e-01 1.09870744e+00
2.26708084e-01 -1.56975222e+00 -2.14467138e-01 5.22857845e-01
1.11791635e+00 -5.16521819e-02 -1.06204450e-01 -2.89832830e-01
2.96195477e-01 -8.79075766e-01 2.65060127e-01 1.47826253e-02
8.35265696e-01 -7.37833679e-01 2.05073401e-01 3.17655146e-01
-1.62503433e+00 -4.94121388e-02 -3.12556326e-01 -1.54427424e-01
5.88547528e-01 1.22846198e+00 -2.29339465e-01 6.26168132e-01
3.91905993e-01 7.51442373e-01 3.00010722e-02 9.78332937e-01
-8.27316418e-02 4.28987235e-01 -6.73964977e-01 1.16177224e-01
2.03107238e-01 -9.26278174e-01 6.83169603e-01 1.08508146e+00
3.76944900e-01 2.73577780e-01 3.18848401e-01 8.24248612e-01
-2.88362294e-01 6.46803796e-01 -9.23153520e-01 8.58124346e-02
1.61433741e-01 1.57554567e+00 -1.49406481e+00 -1.84992567e-01
-3.16098213e-01 1.00764060e+00 5.76245904e-01 4.08270538e-01
-8.48064721e-01 -3.83148015e-01 2.00829268e-01 5.25164843e-01
2.95019716e-01 -4.98600155e-01 -4.10184711e-01 -1.26667619e+00
1.26451463e-01 -5.22905707e-01 5.27907312e-01 -1.20016970e-01
-1.08215678e+00 2.75365025e-01 -3.68167847e-01 -5.85837066e-01
3.06050450e-01 -3.57500106e-01 -6.51416719e-01 5.98752677e-01
-1.26752782e+00 -7.56069303e-01 -4.79859024e-01 9.22449291e-01
1.99934840e-01 5.08747339e-01 4.46870536e-01 5.26715636e-01
-6.47626758e-01 2.41406098e-01 9.38415676e-02 -1.64255932e-01
2.42757604e-01 -1.40536427e+00 1.91319585e-01 1.12207150e+00
3.06485683e-01 4.93454665e-01 5.62451720e-01 -7.68010557e-01
-2.18313694e+00 -8.41225207e-01 6.34123504e-01 -1.08414637e-02
1.01730692e+00 -4.62848783e-01 -8.16373110e-01 5.95834851e-01
1.07367389e-01 2.65021175e-01 5.01860678e-01 4.07757014e-02
2.05736365e-02 -3.73686820e-01 -1.30303252e+00 3.60509068e-01
1.75036871e+00 -3.74912888e-01 3.52482110e-01 9.42980051e-01
2.43941799e-01 -6.08425617e-01 -8.85952950e-01 5.51476702e-02
6.67511970e-02 -9.50802982e-01 9.71696675e-01 -1.60001978e-01
-5.48373125e-02 -2.50793248e-01 2.70852178e-01 -1.36463666e+00
-4.02273089e-01 -1.44940674e+00 -3.35491151e-01 8.28974247e-01
4.49426502e-01 -7.73303390e-01 9.50471759e-01 2.96780586e-01
-8.96010771e-02 -1.04010177e+00 -8.68990362e-01 -7.21763313e-01
-5.03345057e-02 -3.43588591e-01 6.21347036e-03 1.29948413e+00
3.93612504e-01 4.91015792e-01 -1.71245784e-01 -8.74472316e-04
9.61299717e-01 1.68392718e-01 6.31101489e-01 -1.18765724e+00
-5.83772957e-01 -6.44928932e-01 -4.06134099e-01 -1.22304368e+00
-1.16552360e-01 -1.44046128e+00 -3.72943491e-01 -1.93358827e+00
1.60677470e-02 -6.92469418e-01 1.56010047e-01 6.19372539e-02
2.23885924e-01 3.01333040e-01 -6.44357651e-02 -1.09332196e-01
-5.46296954e-01 1.88289508e-01 1.29648829e+00 -1.42583102e-01
-4.75003302e-01 -1.08865924e-01 -6.52129114e-01 5.44042110e-01
5.63418388e-01 -4.87010509e-01 -7.23387122e-01 -6.31078899e-01
8.57190549e-01 1.91028938e-01 -2.78780609e-01 -7.23348618e-01
6.45979464e-01 -1.16672993e-01 -4.07924503e-01 -1.29746914e-01
1.17883973e-01 -8.32586467e-01 2.67063558e-01 7.83812106e-01
-7.42554739e-02 1.43728107e-01 -2.67951399e-01 7.35064864e-01
1.46430671e-01 -1.89413056e-01 7.98234046e-01 -2.60530651e-01
-3.51116508e-01 5.97958505e-01 -1.76781654e-01 3.38317037e-01
1.48055851e+00 -3.62570763e-01 -1.92555591e-01 -4.43574607e-01
-1.00454545e+00 3.07234555e-01 5.50063968e-01 -3.22323471e-01
4.83817071e-01 -1.05704308e+00 -7.69163668e-01 7.21384073e-03
-4.54997361e-01 1.27994671e-01 3.94760638e-01 1.57686746e+00
-8.35546136e-01 -1.48171268e-03 2.30728582e-01 -6.48623049e-01
-1.01806474e+00 7.51612365e-01 2.35033318e-01 -3.98618817e-01
-7.91618586e-01 1.27222347e+00 -2.22492777e-02 2.83795539e-02
5.05761839e-02 -1.80701420e-01 3.97194356e-01 -1.54845705e-02
2.62126654e-01 9.91736591e-01 9.97467563e-02 -3.44780266e-01
-3.56440902e-01 9.68145788e-01 1.04440786e-01 -7.75861293e-02
1.44425881e+00 -3.73001844e-01 -6.94362640e-01 1.68440849e-01
1.18872106e+00 5.03916800e-01 -7.73234963e-01 -1.96159929e-02
2.15153419e-03 -5.22815883e-01 1.52958825e-01 -1.88899457e-01
-1.61541581e+00 8.04597020e-01 1.43360049e-01 8.13663065e-01
1.03272307e+00 1.20197892e-01 8.94317746e-01 2.96610951e-01
4.90118295e-01 -1.24275517e+00 -1.82892352e-01 1.08888909e-01
7.65974522e-01 -8.14517915e-01 2.67533004e-01 -1.21092403e+00
-1.23668052e-01 8.98697674e-01 3.09796661e-01 -4.39159781e-01
7.74407923e-01 4.96655464e-01 -3.49094063e-01 -5.12760460e-01
-3.56900692e-01 -3.73796642e-01 -2.06279196e-02 4.23737526e-01
3.19123209e-01 3.53402621e-03 -9.69210625e-01 -2.42448837e-01
1.06847130e-01 -3.62826169e-01 6.57350183e-01 6.51636779e-01
-4.32789683e-01 -1.21283805e+00 -8.63634795e-03 5.24488866e-01
2.66948137e-02 -5.45369908e-02 -4.75578010e-01 6.74471021e-01
-7.48310685e-02 6.87200189e-01 -3.23112935e-01 -8.27001929e-02
8.30997452e-02 -4.28175926e-01 7.82271028e-01 -5.86995780e-01
-3.40818077e-01 -2.38326117e-02 5.99526509e-04 -7.51610458e-01
-3.92888695e-01 -5.95300436e-01 -1.43429744e+00 -6.45918489e-01
-5.86086035e-01 5.08476675e-01 6.61441147e-01 7.47303903e-01
4.40377623e-01 2.43196636e-01 6.36583805e-01 -7.29884803e-01
-2.42642179e-01 -4.52940881e-01 -9.54061806e-01 3.08129728e-01
-1.82945266e-01 -4.11934227e-01 -5.16577661e-01 -3.03081661e-01] | [7.06540060043335, 5.151228904724121] |
7b4b19ad-3143-456a-85bf-b6fad3adfeba | vlab-enhancing-video-language-pre-training-by | 2305.13167 | null | https://arxiv.org/abs/2305.13167v1 | https://arxiv.org/pdf/2305.13167v1.pdf | VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending | Large-scale image-text contrastive pre-training models, such as CLIP, have been demonstrated to effectively learn high-quality multimodal representations. However, there is limited research on learning video-text representations for general video multimodal tasks based on these powerful features. Towards this goal, we propose a novel video-text pre-training method dubbed VLAB: Video Language pre-training by feature Adapting and Blending, which transfers CLIP representations to video pre-training tasks and develops unified video multimodal models for a wide range of video-text tasks. Specifically, VLAB is founded on two key strategies: feature adapting and feature blending. In the former, we introduce a new video adapter module to address CLIP's deficiency in modeling temporal information and extend the model's capability to encompass both contrastive and generative tasks. In the latter, we propose an end-to-end training method that further enhances the model's performance by exploiting the complementarity of image and video features. We validate the effectiveness and versatility of VLAB through extensive experiments on highly competitive video multimodal tasks, including video text retrieval, video captioning, and video question answering. Remarkably, VLAB outperforms competing methods significantly and sets new records in video question answering on MSRVTT, MSVD, and TGIF datasets. It achieves an accuracy of 49.6, 61.0, and 79.0, respectively. Codes and models will be released. | ['Jiashi Feng', 'Jing Liu', 'Yi Yang', 'Dongmei Fu', 'Zikang Liu', 'Xiaojie Jin', 'Zhicheng Huang', 'Fan Ma', 'Sihan Chen', 'Xingjian He'] | 2023-05-22 | null | null | null | null | ['video-captioning', 'video-text-retrieval', 'video-question-answering', 'video-retrieval'] | ['computer-vision', 'computer-vision', 'computer-vision', 'computer-vision'] | [ 1.87872365e-01 -5.43233216e-01 -3.56351346e-01 -3.54542464e-01
-1.01695919e+00 -4.28786427e-01 6.57464266e-01 -3.27590168e-01
-3.70135039e-01 4.59211469e-01 3.52235734e-01 -1.53278321e-01
8.28426480e-02 -2.48959452e-01 -1.00956345e+00 -6.35913730e-01
2.58100808e-01 6.40801266e-02 1.27872944e-01 -1.47817269e-01
-1.09258063e-01 -1.29861668e-01 -1.58913183e+00 8.75510514e-01
7.62765765e-01 1.14300692e+00 3.54873359e-01 8.71874571e-01
-2.32490778e-01 1.13103485e+00 -3.19449216e-01 -6.59336090e-01
-2.08601564e-01 -4.88219529e-01 -6.28220737e-01 3.55167270e-01
7.09080040e-01 -7.36207604e-01 -9.80359316e-01 5.82300901e-01
4.56733555e-01 3.12631369e-01 5.58076501e-01 -1.46713066e+00
-8.09442759e-01 5.17514169e-01 -5.05445063e-01 2.78668612e-01
7.63230801e-01 1.89152494e-01 1.04745901e+00 -1.12810981e+00
6.23847067e-01 1.30183983e+00 4.43104386e-01 7.08765030e-01
-7.65394866e-01 -6.84287131e-01 3.40943515e-01 5.17049432e-01
-1.25167501e+00 -5.93586564e-01 7.35579193e-01 -4.87466633e-01
8.77377212e-01 3.02384377e-01 5.66456020e-01 1.58374751e+00
-5.95877431e-02 1.41138101e+00 5.49328864e-01 -1.96996555e-01
-1.83330670e-01 -4.97196577e-02 -1.17495082e-01 8.40874016e-01
-3.07808667e-01 -7.33157694e-02 -9.08782423e-01 -6.55900547e-03
6.09659970e-01 2.87587762e-01 -5.12008727e-01 -3.20374906e-01
-1.41531324e+00 7.92008877e-01 1.42562881e-01 2.90211290e-01
-2.45806828e-01 3.52282882e-01 6.19960964e-01 3.25205743e-01
2.72490114e-01 -9.40663666e-02 -2.36806124e-01 -3.91527325e-01
-8.25315833e-01 2.06088424e-02 4.83694047e-01 1.19597983e+00
6.26823187e-01 1.96482807e-01 -5.59174240e-01 9.90553319e-01
3.15727919e-01 7.10672498e-01 6.22598767e-01 -8.64963055e-01
7.22344041e-01 4.20934051e-01 -2.61649042e-01 -1.01918590e+00
-6.86360970e-02 1.13286739e-02 -6.92180812e-01 -7.82295287e-01
5.36055164e-03 -1.44544095e-01 -1.02578723e+00 1.65122294e+00
7.55526870e-02 4.73352998e-01 2.07976773e-01 9.93134379e-01
1.40602601e+00 1.15909982e+00 2.86254376e-01 -2.97609001e-01
1.29609120e+00 -1.25387549e+00 -8.50903571e-01 4.89461236e-02
5.16448677e-01 -6.99968636e-01 1.05754578e+00 1.42122611e-01
-1.17182195e+00 -7.26263821e-01 -6.92519009e-01 -1.90845042e-01
-5.20267673e-02 1.97066814e-01 6.74619496e-01 3.82598191e-01
-1.10451281e+00 -9.80273588e-04 -6.86579823e-01 -4.57893163e-01
3.71183455e-01 2.68203855e-01 -4.25531149e-01 -4.73964185e-01
-1.12462449e+00 2.14515179e-01 4.78145093e-01 7.00540841e-02
-1.04651475e+00 -5.67584455e-01 -1.05583572e+00 1.65970642e-02
6.47902548e-01 -9.66116548e-01 1.32242632e+00 -1.40794957e+00
-1.56225955e+00 5.97545624e-01 -3.53440434e-01 -2.32036933e-01
3.44950885e-01 -2.96108067e-01 -5.65520048e-01 9.20171916e-01
-1.25154197e-01 1.03329599e+00 1.23414016e+00 -1.15153956e+00
-6.28616214e-01 -7.04152435e-02 1.31320193e-01 4.84781414e-01
-8.14613521e-01 9.49918106e-02 -1.24526942e+00 -7.75269568e-01
-3.21720719e-01 -7.80265152e-01 1.89422324e-01 -7.84336999e-02
-2.58408226e-02 -2.20386252e-01 1.03696311e+00 -7.16111481e-01
1.28980756e+00 -2.37385821e+00 3.93067420e-01 -9.70351920e-02
2.11633980e-01 3.23253810e-01 -5.81693470e-01 5.65661132e-01
2.62748413e-02 -1.54407602e-02 5.66162914e-02 -4.35211748e-01
1.68911908e-02 2.99303353e-01 -2.63290286e-01 1.05843201e-01
2.79770225e-01 1.23623729e+00 -7.87498653e-01 -7.58685827e-01
3.21595699e-01 6.20982528e-01 -7.21796811e-01 3.32024038e-01
-4.17038381e-01 2.15981752e-01 -5.23470521e-01 9.23478961e-01
3.00048888e-01 -4.02245939e-01 8.45306367e-02 -4.29874986e-01
1.81502998e-01 -3.70594025e-01 -7.33513117e-01 1.95168078e+00
-1.44744694e-01 8.75204146e-01 -5.05677946e-02 -1.04488921e+00
5.25339305e-01 6.21098459e-01 7.26890385e-01 -8.60039532e-01
1.82802662e-01 3.96846561e-03 -5.87719738e-01 -1.09570372e+00
7.27446377e-01 6.81991875e-02 5.55091072e-04 1.27092555e-01
4.72000957e-01 2.33418688e-01 4.52310175e-01 5.77886045e-01
8.79347444e-01 2.48565987e-01 -5.11923283e-02 3.18568528e-01
7.16031730e-01 -2.29029313e-01 9.32784900e-02 6.26942396e-01
-1.81685850e-01 7.01941788e-01 3.70032519e-01 -7.32040703e-02
-7.21044898e-01 -9.55070734e-01 1.61197111e-01 1.59119427e+00
1.91783279e-01 -7.69713283e-01 -5.43870807e-01 -7.42078900e-01
-4.21188883e-02 2.28827640e-01 -5.35826743e-01 -3.04713160e-01
-5.16175866e-01 -4.14047122e-01 4.68583465e-01 6.76669598e-01
5.53279042e-01 -8.70531917e-01 -2.38698889e-02 3.82817313e-02
-7.78280854e-01 -1.64611137e+00 -9.36837673e-01 -5.15880823e-01
-7.67644048e-01 -1.00087202e+00 -9.37186599e-01 -1.07889140e+00
5.17975748e-01 9.14159000e-01 8.69591236e-01 2.13547036e-01
-7.18012080e-02 1.18625283e+00 -8.76065791e-01 1.37949139e-01
-2.34709933e-01 -5.66579625e-02 -1.77967340e-01 4.17381018e-01
1.21639699e-01 -2.61401564e-01 -4.99157816e-01 5.00208914e-01
-1.37595356e+00 2.06466600e-01 7.28232145e-01 9.16374266e-01
5.23362577e-01 -3.96021128e-01 4.31017488e-01 -3.73188049e-01
4.07082230e-01 -6.90420449e-01 -1.77994952e-01 4.47913229e-01
5.01533691e-03 -1.75056010e-01 4.11617279e-01 -8.25790524e-01
-1.09380031e+00 6.16701990e-02 -2.06935123e-01 -1.02018321e+00
4.69621830e-02 7.62482226e-01 -1.48797482e-01 -9.45602879e-02
1.74121529e-01 5.53546965e-01 5.11184484e-02 -2.46365458e-01
4.06482637e-01 6.47289932e-01 7.61313379e-01 -5.92058003e-01
7.35031784e-01 3.47249955e-01 -4.75950986e-01 -1.08707070e+00
-6.05402648e-01 -7.16199338e-01 -2.62059301e-01 -5.20289481e-01
9.86766100e-01 -1.37719321e+00 -7.00189710e-01 3.95355493e-01
-9.49753940e-01 -1.89292118e-01 1.17447756e-01 6.62798107e-01
-6.10583782e-01 8.00514460e-01 -6.28732443e-01 -4.75558937e-01
-2.75798947e-01 -1.14653587e+00 1.29652989e+00 1.73790827e-01
3.13941807e-01 -9.20494258e-01 -1.38259470e-01 7.78760374e-01
9.85353440e-02 1.41678248e-02 6.11928523e-01 -4.64246035e-01
-7.14951932e-01 3.60498182e-03 -3.29696178e-01 4.03170526e-01
-2.20879182e-01 1.64234385e-01 -7.71104634e-01 -5.19051254e-01
-2.77211934e-01 -7.13156879e-01 1.14891315e+00 2.65335917e-01
1.20571017e+00 -2.31311351e-01 -2.71109790e-01 7.48976290e-01
1.25907803e+00 2.94402450e-01 7.41100430e-01 1.43294737e-01
8.79654229e-01 2.98967242e-01 5.30778170e-01 4.82930452e-01
5.75713456e-01 7.66812801e-01 3.18868160e-01 1.04243927e-01
-1.34524912e-01 -4.13955837e-01 8.86868060e-01 1.12234318e+00
1.81806499e-05 -5.34704566e-01 -6.16145134e-01 4.15286630e-01
-2.09213853e+00 -1.23737693e+00 3.43422312e-03 1.69083643e+00
5.77642322e-01 -2.87362456e-01 2.06300333e-01 -1.93864793e-01
6.26543164e-01 2.70989597e-01 -3.36131245e-01 1.16267920e-01
-1.37429893e-01 -2.53330767e-01 -8.75039324e-02 1.06142677e-01
-1.30395424e+00 9.98455286e-01 5.66907263e+00 8.78082871e-01
-9.67465520e-01 1.24498695e-01 3.82869452e-01 -1.49316952e-01
-3.23233128e-01 -2.96946824e-01 -7.13704944e-01 5.05450964e-01
9.78053987e-01 -1.17126554e-01 3.04116249e-01 6.55618191e-01
2.24706922e-02 1.41013950e-01 -1.11059880e+00 1.46889353e+00
7.69837141e-01 -1.45100582e+00 6.41242623e-01 -2.99294412e-01
5.96293032e-01 -2.21800342e-01 1.55161828e-01 7.70920992e-01
-3.14095587e-01 -7.62644291e-01 8.31265748e-01 3.96021336e-01
9.22373176e-01 -6.34643972e-01 6.90582812e-01 -7.09438836e-03
-1.46134090e+00 -2.82357305e-01 -1.15448996e-01 3.27392548e-01
3.71572644e-01 -3.47019844e-02 -5.01856923e-01 8.66357148e-01
6.78254247e-01 1.13968909e+00 -7.17169404e-01 9.88661230e-01
1.58016488e-01 6.27394974e-01 -1.12595391e-02 -2.76309857e-03
5.22331536e-01 4.03232686e-02 3.32733512e-01 1.46597385e+00
3.64555776e-01 2.36055419e-01 3.39192003e-01 3.13010186e-01
-3.18930149e-01 3.25306177e-01 -5.21305740e-01 -4.47920978e-01
9.74015892e-02 1.08066010e+00 -2.61840940e-01 -3.87380183e-01
-8.47652137e-01 1.05949736e+00 1.16014861e-01 6.84184551e-01
-1.21548355e+00 -1.06987365e-01 3.31370652e-01 -3.44525903e-01
6.22941911e-01 -2.90627778e-01 5.75602531e-01 -1.65974820e+00
8.79180133e-02 -1.16275334e+00 6.32695675e-01 -1.14036572e+00
-1.18478227e+00 6.40734255e-01 2.31279492e-01 -1.20199084e+00
-3.06736708e-01 -6.31392300e-01 -2.30733812e-01 8.69901553e-02
-1.44535041e+00 -1.45843983e+00 -6.79578602e-01 1.27480054e+00
9.95554090e-01 -3.48251879e-01 3.55913550e-01 6.27165914e-01
-6.77071869e-01 8.25948477e-01 1.90608531e-01 2.34501094e-01
8.09196115e-01 -6.27806067e-01 -1.42724842e-01 6.85028374e-01
3.32737327e-01 2.71222651e-01 2.30459407e-01 -3.86078089e-01
-2.03819084e+00 -1.14186144e+00 4.98061359e-01 -2.99106389e-01
7.88386166e-01 -3.44624788e-01 -7.99423516e-01 8.26487780e-01
3.13766152e-01 -2.24969715e-01 7.95925617e-01 -2.41949245e-01
-4.66156483e-01 -1.11774236e-01 -5.35739660e-01 6.20890379e-01
1.01831365e+00 -7.69089162e-01 -5.33481359e-01 4.82571721e-01
1.01757348e+00 -3.70375574e-01 -9.31613922e-01 4.58549023e-01
6.01254940e-01 -6.55883133e-01 1.10008228e+00 -7.41845548e-01
6.56212330e-01 2.80626230e-02 -5.03429353e-01 -7.52925992e-01
-9.24521312e-02 -8.26305509e-01 -4.38171446e-01 1.40406406e+00
1.58256084e-01 -1.18476488e-01 5.10865629e-01 1.25660345e-01
-3.66833955e-01 -6.01905704e-01 -7.84128189e-01 -6.27877295e-01
-2.63418466e-01 -5.44270635e-01 2.23924786e-01 9.55052793e-01
6.77388674e-03 4.75135744e-01 -7.44666576e-01 -6.57111481e-02
2.52564102e-01 1.61208771e-02 8.78193498e-01 -7.41412699e-01
-3.40867996e-01 -3.86546642e-01 -3.01858604e-01 -1.50928676e+00
4.12262738e-01 -8.85794401e-01 -9.39654885e-04 -1.30813551e+00
6.93603814e-01 1.87922537e-01 -1.81498915e-01 3.85387123e-01
-3.37146223e-01 3.37474227e-01 4.60286856e-01 3.17461193e-01
-1.19834363e+00 8.30605328e-01 1.29807448e+00 -2.52914160e-01
-4.54447269e-02 -2.64612198e-01 -4.88962203e-01 5.14778733e-01
4.42853838e-01 -9.74163972e-03 -5.74266255e-01 -7.02240109e-01
2.41409410e-02 4.25221354e-01 4.14523631e-01 -7.75994658e-01
1.24723576e-01 -1.17540278e-01 2.98598975e-01 -6.18830800e-01
6.33032084e-01 -7.16283739e-01 1.08445445e-02 2.96945181e-02
-4.57937896e-01 1.90573201e-01 3.47046912e-01 9.00642335e-01
-5.38153470e-01 7.68764764e-02 4.10636723e-01 1.32257804e-01
-1.16004014e+00 6.10957503e-01 -4.27558959e-01 7.86850154e-02
1.04611409e+00 -1.58443928e-01 -4.38717902e-01 -7.73633778e-01
-5.93818486e-01 5.54642022e-01 2.05593690e-01 8.66145074e-01
1.10110164e+00 -1.49893355e+00 -7.38808811e-01 1.35621354e-01
3.67615849e-01 -5.17383039e-01 6.12937152e-01 1.00617909e+00
-3.03204983e-01 5.14167666e-01 -2.99536642e-02 -8.97673726e-01
-1.51700222e+00 7.31212199e-01 7.64729604e-02 -4.53023845e-03
-5.57168067e-01 6.77725613e-01 4.79434043e-01 1.15291752e-01
5.39283633e-01 -1.72055811e-01 -2.26678520e-01 7.61373788e-02
6.60579264e-01 7.64920339e-02 -2.93198109e-01 -8.58461261e-01
-1.27656981e-01 6.24444544e-01 -2.71082073e-01 -1.85192898e-02
1.09056497e+00 -3.83526683e-01 2.09196910e-01 2.64643401e-01
1.49634945e+00 -3.43220472e-01 -1.30845785e+00 -3.33062410e-01
-3.36671233e-01 -5.03305972e-01 -9.56732631e-02 -5.84693789e-01
-1.19372487e+00 8.75644684e-01 4.69114631e-01 -1.69155166e-01
1.37686563e+00 1.55426502e-01 1.05651224e+00 5.83153546e-01
2.57068891e-02 -8.54907036e-01 8.29132318e-01 5.64487875e-01
8.74866903e-01 -1.34634840e+00 -2.16816679e-01 -2.75449514e-01
-9.47561622e-01 1.13329637e+00 6.50001168e-01 3.76605541e-01
2.91103631e-01 -1.91247955e-01 -1.87218502e-01 1.69074424e-02
-1.05038762e+00 -2.04953402e-01 6.54970467e-01 4.34361696e-01
1.95639461e-01 -2.88129568e-01 -7.97828436e-02 6.26217008e-01
2.67190039e-01 1.88061044e-01 3.35986197e-01 1.01046765e+00
-3.65175962e-01 -7.72111773e-01 -2.38503814e-01 2.07930371e-01
-4.14646029e-01 -2.43418857e-01 -2.17748016e-01 9.35469747e-01
-2.30722100e-01 1.05994141e+00 -2.54393183e-02 -7.13044882e-01
1.62743270e-01 1.19831875e-01 5.22287071e-01 -2.30924100e-01
-4.07820970e-01 4.21778083e-01 1.46303609e-01 -6.38233662e-01
-8.09989989e-01 -6.06344700e-01 -9.87278879e-01 -2.77992457e-01
-2.65718549e-01 1.08413182e-01 4.83180821e-01 9.56544757e-01
4.68843967e-01 4.40667838e-01 6.11804426e-01 -8.97366047e-01
-2.11508021e-01 -6.65871322e-01 -2.19137311e-01 6.26962841e-01
3.02058458e-01 -6.87631547e-01 -2.54044116e-01 5.15674114e-01] | [10.290420532226562, 0.8875619173049927] |
da22bc51-ccdd-4b45-b05e-b60e59e344d4 | delving-deep-into-regularity-a-simple-but | 2204.05544 | null | https://arxiv.org/abs/2204.05544v2 | https://arxiv.org/pdf/2204.05544v2.pdf | Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognition | Recent years have witnessed the improving performance of Chinese Named Entity Recognition (NER) from proposing new frameworks or incorporating word lexicons. However, the inner composition of entity mentions in character-level Chinese NER has been rarely studied. Actually, most mentions of regular types have strong name regularity. For example, entities end with indicator words such as "company" or "bank" usually belong to organization. In this paper, we propose a simple but effective method for investigating the regularity of entity spans in Chinese NER, dubbed as Regularity-Inspired reCOgnition Network (RICON). Specifically, the proposed model consists of two branches: a regularity-aware module and a regularityagnostic module. The regularity-aware module captures the internal regularity of each span for better entity type prediction, while the regularity-agnostic module is employed to locate the boundary of entities and relieve the excessive attention to span regularity. An orthogonality space is further constructed to encourage two modules to extract different aspects of regularity features. To verify the effectiveness of our method, we conduct extensive experiments on three benchmark datasets and a practical medical dataset. The experimental results show that our RICON significantly outperforms previous state-of-the-art methods, including various lexicon-based methods. | ['Nicholas Jing Yuan', 'Baoxing Huai', 'Yi Zheng', 'Zhefeng Wang', 'Xiaoye Qu', 'Yingjie Gu'] | 2022-04-12 | null | https://aclanthology.org/2022.findings-naacl.143 | https://aclanthology.org/2022.findings-naacl.143.pdf | findings-naacl-2022-7 | ['type-prediction', 'chinese-named-entity-recognition'] | ['computer-code', 'natural-language-processing'] | [-3.15254569e-01 -1.73227966e-01 -2.05968142e-01 -2.51099706e-01
-4.70670253e-01 -3.82770687e-01 1.37420923e-01 3.06660891e-01
-6.12973034e-01 6.08010232e-01 5.06314158e-01 -1.11555889e-01
-8.45407248e-02 -8.94179702e-01 -2.49536440e-01 -6.59168661e-01
1.42691553e-01 5.63576408e-02 1.22665830e-01 -1.49630755e-01
3.42349261e-01 4.12216634e-01 -8.17308903e-01 1.85682327e-02
1.11465561e+00 8.17870438e-01 1.79248691e-01 -1.51390508e-01
-6.19559586e-01 6.80125237e-01 -5.80278099e-01 -3.43531370e-01
-3.52420472e-02 -2.91910768e-01 -7.22048819e-01 1.07550979e-01
-3.70448053e-01 2.12283239e-01 -4.25996751e-01 1.08984709e+00
6.72326267e-01 5.09192534e-02 4.97427911e-01 -4.58162010e-01
-9.11354005e-01 8.54255378e-01 -5.99739254e-01 2.80130923e-01
1.85546055e-01 -3.39589380e-02 1.13192487e+00 -9.76621509e-01
6.59459472e-01 8.91370893e-01 8.30033541e-01 4.47217315e-01
-5.92537344e-01 -6.09307289e-01 3.11868727e-01 1.49397060e-01
-1.67892766e+00 -1.36833668e-01 7.21582890e-01 -2.42132135e-02
6.79060161e-01 1.01152606e-01 2.18946680e-01 5.08693695e-01
-7.42217079e-02 8.28952014e-01 8.95208955e-01 -2.30342925e-01
4.85115219e-03 1.93165272e-01 3.44511837e-01 7.76513875e-01
6.12029076e-01 -4.27390873e-01 5.24652712e-02 -4.77356948e-02
6.73791885e-01 1.64587006e-01 -3.84773940e-01 8.49268883e-02
-1.37950373e+00 5.34906924e-01 5.50728381e-01 8.04492831e-01
-4.76784945e-01 -5.11017144e-01 6.40098751e-01 -1.38156742e-01
3.39887649e-01 5.58613241e-01 -7.08189607e-01 9.43337232e-02
-6.91977501e-01 -3.16942513e-01 8.57202530e-01 1.28303051e+00
7.65934646e-01 -2.16971934e-01 -3.86396885e-01 9.55613673e-01
1.63794473e-01 8.45357254e-02 7.68949091e-01 -1.04835570e-01
5.81579030e-01 1.18804657e+00 -1.44072637e-01 -1.24208939e+00
-7.47066438e-01 -5.74923813e-01 -1.20982099e+00 -1.02364087e+00
8.52104574e-02 -4.48573679e-01 -7.30936050e-01 1.37883997e+00
3.97178769e-01 4.18920845e-01 1.37353033e-01 7.33027756e-01
1.21841598e+00 7.11867571e-01 3.04080278e-01 -3.19929868e-01
1.87102568e+00 -8.58754516e-01 -8.08161557e-01 1.47033811e-01
9.15856540e-01 -8.10780406e-01 7.73227632e-01 -1.44694030e-01
-5.66183031e-01 -4.14156824e-01 -7.48126805e-01 1.21685518e-02
-5.59238791e-01 6.52089834e-01 6.33956254e-01 6.64318502e-01
-3.23175162e-01 4.20584440e-01 -6.85023963e-01 -1.79235697e-01
3.31726193e-01 7.72178918e-02 -3.23913336e-01 6.13069348e-02
-1.55606353e+00 7.23235607e-01 8.19309950e-01 3.81385326e-01
-1.54209957e-01 -6.29707992e-01 -1.07769167e+00 1.81093931e-01
4.87117976e-01 -4.06441838e-01 7.67652810e-01 -4.85905945e-01
-1.03321171e+00 7.72619307e-01 -1.72023505e-01 -1.75806493e-01
3.37564084e-03 -5.78003749e-02 -1.09351182e+00 3.22298706e-02
1.90978408e-01 1.32694483e-01 9.04548168e-03 -8.37802649e-01
-7.27384090e-01 -4.53575328e-02 -1.54943913e-01 1.28123671e-01
-5.80675960e-01 1.02651656e-01 -8.38592172e-01 -9.50219572e-01
2.15063691e-01 -5.96992910e-01 -4.92919177e-01 -5.48122942e-01
-8.88327062e-01 -5.54792464e-01 3.04802239e-01 -5.69501579e-01
2.04827046e+00 -2.19027972e+00 -3.62908602e-01 3.41904581e-01
1.50513589e-01 3.86878073e-01 -6.80365711e-02 4.53157067e-01
-1.26919553e-01 4.85416144e-01 -2.53935337e-01 1.58106849e-01
-1.01233579e-01 7.90583938e-02 -2.99639776e-02 3.90814573e-01
2.84991324e-01 8.26682508e-01 -9.47627962e-01 -8.91587019e-01
-2.69613355e-01 2.39367500e-01 -2.91504651e-01 1.36568576e-01
4.80934829e-02 2.91032404e-01 -1.00365090e+00 9.19311404e-01
8.15189004e-01 -4.53133792e-01 4.40268904e-01 -4.63536441e-01
-4.10347015e-01 4.75433707e-01 -1.30146742e+00 1.32363355e+00
-3.43703270e-01 8.73648934e-03 -4.48368132e-01 -8.11157346e-01
1.14096677e+00 3.85456383e-01 4.22714770e-01 -4.67698395e-01
2.66169012e-01 3.71099293e-01 1.02188336e-02 -6.35551155e-01
6.77762568e-01 -6.64735660e-02 -3.05300832e-01 2.19139047e-02
-2.25925267e-01 5.64398885e-01 3.64979059e-01 7.95281380e-02
1.09719062e+00 -9.98474434e-02 5.60179293e-01 -4.78969842e-01
9.28141415e-01 5.30007249e-03 1.37371755e+00 2.86932856e-01
-1.73574403e-01 5.67591131e-01 5.12363136e-01 -4.13853407e-01
-8.03901553e-01 -5.48916340e-01 -3.18670958e-01 5.67723274e-01
4.67391551e-01 -5.42742610e-01 -7.66468227e-01 -1.05143917e+00
-2.58629382e-01 5.08942366e-01 -6.31610394e-01 9.69039369e-03
-8.89959812e-01 -1.05341721e+00 9.20733750e-01 7.39727557e-01
8.48160207e-01 -1.33801007e+00 -2.94163134e-02 3.08707148e-01
-3.74433190e-01 -1.16204619e+00 -1.06786203e+00 -9.22378227e-02
-6.79185271e-01 -1.14591825e+00 -8.70645344e-01 -1.22187841e+00
1.00178075e+00 1.54325604e-01 9.40048277e-01 4.02858466e-01
-8.30072016e-02 -1.17930964e-01 -6.82157159e-01 -2.68209666e-01
2.20174730e-01 5.01896501e-01 -1.20656498e-01 1.02177069e-01
7.34269202e-01 -2.46947408e-01 -7.06471562e-01 5.83681583e-01
-9.82277870e-01 -2.42335901e-01 1.09164155e+00 7.80995846e-01
7.37259269e-01 2.37624660e-01 6.66042387e-01 -1.32036376e+00
4.97941375e-01 -7.91859090e-01 -3.14240903e-01 5.03438592e-01
-6.41846418e-01 2.51715779e-01 9.29234207e-01 -5.16041696e-01
-1.14666653e+00 1.94041152e-02 -3.17252338e-01 1.01925395e-02
-2.28655115e-01 9.64332044e-01 -7.07430422e-01 3.81387413e-01
1.98651984e-01 5.87194681e-01 -6.66741252e-01 -7.33837068e-01
7.84547180e-02 7.62239397e-01 4.46281016e-01 -6.87417150e-01
6.47417367e-01 1.24742173e-01 -2.59313822e-01 -6.36405826e-01
-9.47375655e-01 -8.35936904e-01 -4.71401870e-01 2.73588449e-01
9.13439691e-01 -9.70805049e-01 -6.53201044e-01 3.26866895e-01
-1.17865479e+00 3.82536709e-01 -1.03753343e-01 6.03134751e-01
9.36263874e-02 6.16467059e-01 -9.14154291e-01 -4.55521554e-01
-5.26194572e-01 -8.56448472e-01 7.81596184e-01 8.02901268e-01
1.75525591e-01 -1.03248858e+00 2.17684537e-01 -3.82130779e-02
1.41118288e-01 4.66895923e-02 9.90239799e-01 -1.08823931e+00
-2.91489750e-01 -2.35697135e-01 -4.64867949e-01 -5.50695173e-02
3.75252962e-01 -1.69241443e-01 -4.41825002e-01 2.29206696e-01
-1.36789918e-01 1.67548686e-01 7.92331398e-01 -1.01980031e-01
1.26404321e+00 -4.80213344e-01 -4.51030433e-01 6.26676977e-01
1.54081416e+00 1.69815555e-01 8.16737652e-01 6.75390542e-01
8.54113460e-01 4.62794095e-01 7.26233661e-01 4.89170641e-01
6.04937553e-01 3.86103779e-01 -8.63567516e-02 -2.16860563e-01
1.81096613e-01 -3.93288821e-01 7.36827403e-02 1.27580643e+00
-2.20898673e-01 -1.00299016e-01 -8.52604389e-01 7.81339884e-01
-1.62140167e+00 -8.16914976e-01 -1.86522588e-01 1.77736700e+00
1.20735860e+00 5.98410107e-02 -3.95213999e-02 -1.97387874e-01
1.14390957e+00 9.54278708e-02 -4.85353410e-01 2.40413961e-03
-3.01662356e-01 -2.56289579e-02 4.83585268e-01 -2.61254251e-01
-1.31523740e+00 1.01957810e+00 4.79834366e+00 1.34132469e+00
-7.84871459e-01 -1.72481656e-01 6.51073873e-01 7.09712148e-01
-3.35760504e-01 -2.21131910e-02 -1.23555434e+00 7.03310788e-01
4.47098136e-01 -2.87609071e-01 -1.98305860e-01 9.37049806e-01
3.13487053e-02 3.71356070e-01 -6.13480926e-01 8.38352919e-01
-2.21878886e-02 -1.30179322e+00 1.12508379e-01 2.21312027e-02
6.70625269e-01 -2.77116954e-01 -2.67713398e-01 3.74662966e-01
8.20836648e-02 -6.78494155e-01 2.16456652e-01 7.04322457e-01
7.29500830e-01 -9.27914917e-01 1.19936669e+00 3.13928515e-01
-1.86279535e+00 2.82995284e-01 -5.82290292e-01 4.95816290e-01
5.12699932e-02 9.16518092e-01 -3.84060860e-01 1.10664797e+00
3.93349558e-01 8.40060174e-01 -4.56907421e-01 1.32222688e+00
-4.56748962e-01 7.13582039e-01 -1.09318428e-01 -2.93294370e-01
4.36001599e-01 -2.04240113e-01 3.24350417e-01 1.75837326e+00
2.01636270e-01 5.84839523e-01 1.88251644e-01 6.25183046e-01
-4.33992624e-01 7.13659763e-01 -2.42146194e-01 -2.18644589e-02
7.21524060e-01 1.62272274e+00 -9.94043231e-01 -1.99403256e-01
-5.49305201e-01 7.52211928e-01 4.41268981e-01 9.66574550e-02
-8.70997369e-01 -9.83693302e-01 2.37058595e-01 -2.76172251e-01
6.07734025e-01 -1.23489104e-01 -4.17722344e-01 -1.47365212e+00
1.52197545e-02 -8.12732518e-01 6.40548706e-01 -1.65533692e-01
-1.56819510e+00 8.38787615e-01 -4.80332226e-01 -1.55443096e+00
5.70673466e-01 -4.32640016e-01 -8.12889338e-01 7.56879866e-01
-1.57748234e+00 -9.36337531e-01 -8.68715495e-02 4.64873791e-01
4.30723846e-01 -1.92276761e-01 7.74467766e-01 5.47355473e-01
-1.20797217e+00 9.14351463e-01 5.63152134e-02 8.98207843e-01
6.52106464e-01 -1.15359163e+00 1.94425687e-01 9.31764722e-01
3.50612476e-02 1.19183183e+00 2.45797515e-01 -7.94209957e-01
-1.16906297e+00 -1.23484612e+00 1.33451855e+00 -1.02640353e-01
6.01752222e-01 8.44241455e-02 -1.02343023e+00 4.10121143e-01
1.59340929e-02 1.46175370e-01 9.10547972e-01 2.87416369e-01
-3.47295582e-01 -7.72233978e-02 -9.30149555e-01 5.56020856e-01
9.40388322e-01 -2.27960676e-01 -9.01193202e-01 1.74296468e-01
7.11737633e-01 -2.71522135e-01 -1.07105684e+00 5.92203379e-01
3.03692758e-01 -4.36238199e-01 7.46659935e-01 -4.58430231e-01
4.73439276e-01 -5.72863877e-01 1.82855219e-01 -1.05654180e+00
-5.15130877e-01 -3.95249993e-01 -4.78211120e-02 1.69192386e+00
5.42963147e-01 -5.47707260e-01 6.77950978e-01 4.35873955e-01
-2.57401645e-01 -1.13818264e+00 -5.13427258e-01 -8.54693353e-01
-5.22241741e-02 -5.11130020e-02 8.63382995e-01 1.30506623e+00
2.13541731e-01 3.61638814e-01 -2.39252582e-01 2.52390534e-01
7.71120116e-02 2.51245946e-01 2.32062608e-01 -8.59061480e-01
9.09864828e-02 -6.05009615e-01 -2.43210852e-01 -1.30905032e+00
-1.18702240e-02 -8.33541036e-01 8.17293599e-02 -1.52337170e+00
4.04713571e-01 -8.34677875e-01 -5.70615053e-01 5.57691395e-01
-7.93619633e-01 -1.36121079e-01 -6.68012872e-02 4.55910206e-01
-1.01914990e+00 6.09886229e-01 1.20687139e+00 2.14530993e-02
-2.24592105e-01 -1.54856434e-02 -1.00567317e+00 9.39786494e-01
7.36379325e-01 -5.03105044e-01 1.45466268e-01 -3.28642637e-01
3.43455881e-01 -2.23892882e-01 -2.40514681e-01 -6.88381791e-01
6.02198362e-01 -1.21334136e-01 2.84593940e-01 -7.28567243e-01
-5.71028054e-01 -7.30199695e-01 -9.11341459e-02 3.56802016e-01
-3.08192611e-01 1.41190067e-01 -2.21888963e-02 6.04424953e-01
-3.57454419e-01 -3.96386206e-01 4.87753093e-01 -2.13992149e-01
-9.24823344e-01 5.59587955e-01 -8.24089497e-02 3.81430745e-01
7.68195629e-01 5.09715416e-02 -3.32090825e-01 2.88400084e-01
-3.78629923e-01 5.06303847e-01 2.30533153e-01 2.22495168e-01
6.10087872e-01 -1.33736658e+00 -7.78592646e-01 -1.26764104e-01
3.28066587e-01 9.56990197e-02 3.92683774e-01 8.11261773e-01
-6.47814333e-01 4.13324147e-01 3.03781003e-01 -6.07718751e-02
-8.89498353e-01 6.94358289e-01 2.77120471e-01 -8.34791362e-01
-7.07241118e-01 6.13742411e-01 3.11685324e-01 -6.00167215e-01
1.38819918e-01 -1.46824822e-01 -8.57105613e-01 3.31432745e-02
5.95070541e-01 3.11756462e-01 -1.12518303e-01 -7.14234114e-01
-5.73264539e-01 6.38202906e-01 -3.67071480e-01 5.11441231e-01
1.18263507e+00 -1.29418939e-01 -3.88552487e-01 2.36887261e-01
9.55800354e-01 4.53137100e-01 -6.54343545e-01 -5.72392404e-01
5.61219275e-01 5.19776158e-02 -3.34983736e-01 -5.82119167e-01
-1.29052413e+00 4.74978387e-01 1.43972591e-01 1.79033637e-01
1.33427966e+00 -1.46438077e-01 1.22231936e+00 4.91463184e-01
3.83215517e-01 -1.13061011e+00 -3.56529713e-01 7.63349593e-01
2.41794586e-01 -8.80847871e-01 8.01237002e-02 -7.22510755e-01
-7.83785164e-01 1.03436375e+00 6.64500237e-01 -1.29101366e-01
8.26627910e-01 1.44268379e-01 -3.61050405e-02 -1.88615412e-01
-3.50161612e-01 -4.55605149e-01 5.95948339e-01 9.46068168e-02
6.26467049e-01 -6.49501802e-03 -1.02938557e+00 1.33818483e+00
1.52594239e-01 -2.43138447e-01 1.82516992e-01 6.73653483e-01
-4.29600984e-01 -1.15578699e+00 -1.50324911e-01 4.00509059e-01
-9.42154288e-01 -5.93695819e-01 -7.61287808e-02 7.20139384e-01
4.85652149e-01 8.41640234e-01 -1.19782425e-01 -3.38210523e-01
4.96801585e-01 -2.45870709e-01 -1.45869181e-01 -7.27193952e-01
-8.33717585e-01 1.52624235e-01 1.51123196e-01 -1.83237299e-01
-5.80056250e-01 -5.81206322e-01 -1.69818950e+00 -2.53462419e-02
-7.66918659e-01 7.38053679e-01 1.97377235e-01 1.06319773e+00
4.20619190e-01 5.58506131e-01 9.90784883e-01 3.32674906e-02
-1.50339663e-01 -1.00396407e+00 -8.01473618e-01 3.71559262e-01
-1.95320472e-01 -3.63976389e-01 -1.34659663e-01 -7.53779784e-02] | [9.566482543945312, 9.583312034606934] |
4cd958b9-4f48-4272-94af-4502149db193 | dpmc-weighted-model-counting-by-dynamic | 2008.08748 | null | https://arxiv.org/abs/2008.08748v1 | https://arxiv.org/pdf/2008.08748v1.pdf | DPMC: Weighted Model Counting by Dynamic Programming on Project-Join Trees | We propose a unifying dynamic-programming framework to compute exact literal-weighted model counts of formulas in conjunctive normal form. At the center of our framework are project-join trees, which specify efficient project-join orders to apply additive projections (variable eliminations) and joins (clause multiplications). In this framework, model counting is performed in two phases. First, the planning phase constructs a project-join tree from a formula. Second, the execution phase computes the model count of the formula, employing dynamic programming as guided by the project-join tree. We empirically evaluate various methods for the planning phase and compare constraint-satisfaction heuristics with tree-decomposition tools. We also investigate the performance of different data structures for the execution phase and compare algebraic decision diagrams with tensors. We show that our dynamic-programming model-counting framework DPMC is competitive with the state-of-the-art exact weighted model counters cachet, c2d, d4, and miniC2D. | ['Vu H. N. Phan', 'Jeffrey M. Dudek', 'Moshe Y. Vardi'] | 2020-08-20 | null | null | null | null | ['tree-decomposition'] | ['graphs'] | [ 3.08984458e-01 2.44818076e-01 -5.54828882e-01 -2.21279025e-01
-7.95269191e-01 -5.86088777e-01 4.11590546e-01 4.96770889e-01
-1.77234322e-01 4.34183478e-01 -3.98272723e-02 -8.93461943e-01
-1.12237290e-01 -1.31008124e+00 -5.54160297e-01 -3.94452177e-02
-2.55005628e-01 1.35429931e+00 7.09824800e-01 -2.02761125e-02
2.72128731e-01 4.85610396e-01 -1.36455977e+00 9.00246799e-01
5.76804399e-01 1.01400793e+00 -3.23769033e-01 7.78048813e-01
-4.80748832e-01 8.26974690e-01 5.40890284e-02 -5.57804585e-01
4.38993126e-01 -9.60584208e-02 -1.09803474e+00 -5.00769801e-02
1.47595882e-01 -3.78255218e-01 2.05882981e-01 9.73251581e-01
-3.29230160e-01 -4.17304039e-01 3.08529854e-01 -1.66655087e+00
3.96065354e-01 1.11549616e+00 -9.32373822e-01 -2.43961625e-02
5.47989964e-01 9.46134776e-02 1.27378500e+00 -7.63524413e-01
9.25786257e-01 1.42477834e+00 3.63640249e-01 2.84147590e-01
-1.69155526e+00 -4.62566674e-01 3.57178569e-01 3.23921472e-01
-1.49905813e+00 -1.97899356e-01 3.59181553e-01 -3.19386691e-01
1.65883458e+00 7.21428573e-01 7.99766064e-01 9.31057483e-02
3.84999335e-01 6.94477499e-01 1.15199339e+00 -8.74646485e-01
5.35036206e-01 -1.27639040e-01 6.38276756e-01 9.91642594e-01
5.73646307e-01 2.73592234e-01 -5.88490188e-01 -6.77904844e-01
1.13775820e-01 -3.63867342e-01 2.22148106e-01 -5.42016685e-01
-8.54327738e-01 7.94843674e-01 -1.57492310e-01 1.79034646e-03
-1.13153175e-01 6.97786987e-01 6.50888145e-01 3.21283042e-01
1.74896121e-01 2.24748567e-01 -5.96887469e-01 -1.54731959e-01
-1.08975542e+00 8.58809233e-01 1.25225508e+00 1.33694673e+00
6.35448039e-01 -5.51814973e-01 -3.53621304e-01 -1.07184790e-01
3.45642000e-01 4.57376093e-01 -4.55181658e-01 -1.04463649e+00
6.74338639e-01 9.35043514e-01 3.87047715e-02 -6.18670881e-01
-5.02960265e-01 -3.01903427e-01 -2.52101749e-01 3.13167572e-01
3.41014594e-01 1.44362122e-01 -5.94048440e-01 1.48458743e+00
6.44850314e-01 -1.13277890e-01 -3.00805509e-01 3.88598919e-01
-1.19018860e-01 6.80202723e-01 -4.22851928e-02 -6.17405355e-01
1.34978044e+00 -1.15726340e+00 -2.36837521e-01 5.04745170e-02
1.35751641e+00 -4.61550504e-01 4.77230936e-01 8.58644843e-01
-1.78455269e+00 1.09945506e-01 -9.95223820e-01 -6.92794472e-02
1.03414334e-01 -2.78689176e-01 1.05315781e+00 4.92087662e-01
-1.04813743e+00 3.60093057e-01 -1.48767900e+00 3.19673151e-01
-7.83964805e-03 5.28904378e-01 -2.72174776e-02 -3.94595444e-01
-5.29044151e-01 1.03535414e+00 4.00829077e-01 -2.65348315e-01
-8.77169490e-01 -1.07043135e+00 -8.31299722e-01 3.83680433e-01
9.06676412e-01 -7.33291328e-01 1.77389491e+00 -4.26263630e-01
-9.73960400e-01 9.62341011e-01 -5.94191909e-01 -7.84723282e-01
4.64688152e-01 2.30879173e-01 -7.41954595e-02 -1.31400436e-01
-2.23373637e-01 2.49259576e-01 -1.08509893e-02 -1.04067051e+00
-8.82024407e-01 -4.32361782e-01 5.91698587e-01 -2.16730177e-01
3.72565567e-01 2.81319469e-01 -6.00450337e-01 2.37591892e-01
2.75842816e-01 -1.03935659e+00 -5.93513966e-01 2.64295470e-02
-4.91304159e-01 -2.46235341e-01 2.23777294e-01 -1.92886427e-01
1.98176575e+00 -1.77814138e+00 5.11110365e-01 7.41377890e-01
4.00454998e-01 -2.65800178e-01 7.10539222e-02 6.30887568e-01
5.89124486e-02 2.01633185e-01 -2.32554600e-01 -2.24193618e-01
5.00672758e-01 3.16030055e-01 -3.35920125e-01 2.15919867e-01
-4.87567112e-02 7.38229871e-01 -6.93426013e-01 -8.45032930e-01
4.78574932e-02 -4.34876889e-01 -1.33668196e+00 -1.65208623e-01
-1.10554671e+00 -7.22124279e-01 -2.65376985e-01 6.59731925e-01
1.01326990e+00 2.25555543e-02 9.47514892e-01 -9.47526768e-02
-5.41691184e-01 7.04282999e-01 -1.52991724e+00 1.48964214e+00
-6.66208804e-01 1.11792013e-02 4.03004169e-01 -3.72989625e-01
2.51872182e-01 -2.42277771e-01 2.46979371e-01 -8.08512747e-01
-1.36618400e-02 4.63005871e-01 -8.35178606e-03 -5.81087219e-03
5.64437151e-01 1.50629552e-03 -4.02100623e-01 7.88498402e-01
-2.40975410e-01 -5.24102747e-01 1.02192056e+00 4.06848818e-01
1.46248996e+00 1.31993309e-01 4.11224365e-01 -6.07502639e-01
7.18098581e-01 5.43878973e-01 6.28111482e-01 4.46345299e-01
5.25987625e-01 -3.92238833e-02 1.41637242e+00 -6.97141349e-01
-8.65659952e-01 -8.15731108e-01 -3.65812480e-02 9.24142897e-01
1.84328016e-03 -1.26843190e+00 -9.02266383e-01 -4.99536484e-01
-1.47472546e-01 1.17319381e+00 -4.71329868e-01 -2.56718025e-02
-7.65688777e-01 -4.33651775e-01 1.79354519e-01 6.75936580e-01
1.87712520e-01 -2.39865005e-01 -1.13839400e+00 4.33361083e-01
1.82396129e-01 -7.88124442e-01 -3.54951471e-01 5.74016452e-01
-9.86910820e-01 -1.24539411e+00 5.18028915e-01 -3.48119825e-01
7.66201079e-01 -9.16176066e-02 1.55867898e+00 5.14598906e-01
-4.83128019e-02 -6.09376542e-02 -8.72506425e-02 -3.74219835e-01
-4.22865033e-01 7.88892731e-02 -3.34462047e-01 -6.06949449e-01
4.95453894e-01 -3.87506932e-01 -2.78286934e-02 2.13070258e-01
-7.62810051e-01 4.95972931e-01 1.51733041e-01 6.98510170e-01
1.16629207e+00 3.18220764e-01 -8.61660659e-01 -1.24989843e+00
2.21786663e-01 -1.70015618e-01 -1.59407151e+00 6.40400112e-01
-7.02384710e-01 4.57162976e-01 3.48169535e-01 5.81119657e-02
-7.19770253e-01 1.70327514e-01 9.53700393e-02 -1.29904807e-01
5.97221315e-01 1.04189157e+00 -2.03777269e-01 1.25829533e-01
4.77448732e-01 -2.96222419e-01 -3.68794650e-01 -4.47330996e-02
2.27024347e-01 -4.00500521e-02 3.80599827e-01 -1.14875305e+00
8.96807134e-01 2.71900743e-01 7.32432365e-01 -1.15366969e-02
-5.37788153e-01 -1.62616998e-01 -3.73060316e-01 1.36778146e-01
4.10257638e-01 -5.62967598e-01 -7.32717931e-01 1.63389847e-01
-1.50066245e+00 -5.85874379e-01 -4.74183083e-01 -1.04793618e-02
-4.74259138e-01 -5.55242486e-02 -5.82338333e-01 -1.06636322e+00
-2.24157318e-01 -1.25897408e+00 1.19389975e+00 -4.00585502e-01
-4.84774560e-01 -5.01520753e-01 4.61099237e-01 1.94580816e-02
1.65020749e-01 3.97484154e-01 1.55731893e+00 -4.53616381e-01
-1.08327818e+00 -1.69779733e-01 -1.79201752e-01 -2.14920834e-01
-8.68938029e-01 3.81325454e-01 -4.59419936e-01 1.57013014e-01
-2.07817242e-01 -6.43425360e-02 3.83241713e-01 3.15646976e-01
1.12307954e+00 -4.86595988e-01 -7.43211806e-01 3.95546198e-01
1.65810525e+00 1.19180139e-02 7.18934178e-01 1.07223824e-01
2.63783559e-02 3.76562476e-01 7.91971326e-01 4.99023139e-01
5.81045389e-01 8.88686240e-01 5.03398299e-01 4.31697875e-01
2.04552814e-01 -2.25187868e-01 7.52689466e-02 6.68268919e-01
-1.48569837e-01 -4.68919203e-02 -1.21855772e+00 4.33605015e-01
-1.69293094e+00 -8.45174193e-01 -6.63137138e-01 2.16390157e+00
1.01712608e+00 7.05181718e-01 2.73733616e-01 5.37843466e-01
8.99453759e-02 -2.88135797e-01 7.11945305e-03 -1.16499293e+00
6.03794336e-01 6.90100789e-01 7.59777963e-01 1.15279269e+00
-5.00398755e-01 8.74412596e-01 6.13284588e+00 7.60502934e-01
-6.50503159e-01 2.04225302e-01 2.75833517e-01 -4.28606331e-01
-8.25460315e-01 4.59118783e-01 -1.05644464e+00 -5.92775755e-02
1.22253001e+00 -4.90961552e-01 6.80440307e-01 1.33730745e+00
-2.99238980e-01 -5.56832850e-01 -1.66114938e+00 3.64559442e-01
-3.52153748e-01 -1.50819349e+00 -3.17214847e-01 2.80458957e-01
7.46902704e-01 -1.88935310e-01 -1.76825002e-01 4.68635321e-01
5.36093593e-01 -7.10883558e-01 1.13571835e+00 2.92473674e-01
6.69870377e-01 -1.08141768e+00 6.54850662e-01 2.36598596e-01
-1.42308307e+00 2.60640699e-02 -1.17045566e-01 -3.27006340e-01
5.58701694e-01 8.49521041e-01 -6.28517091e-01 4.30700660e-01
3.49130183e-01 -2.40707844e-01 -2.42604226e-01 9.27932441e-01
-1.55769691e-01 2.97312587e-01 -7.47330368e-01 3.65823414e-03
1.09677531e-01 -2.41706580e-01 2.50984460e-01 1.21770215e+00
7.57319853e-02 2.17449769e-01 2.16760471e-01 9.73866582e-01
1.38992369e-01 -2.35770956e-01 -1.44183263e-01 -3.49108465e-02
5.18253088e-01 1.05727935e+00 -7.82326102e-01 -4.31881756e-01
-5.69951057e-01 2.48875931e-01 2.89316356e-01 -9.31989402e-02
-1.07408750e+00 -2.60596225e-05 4.34793919e-01 4.41792697e-01
1.05086476e-01 -5.76021433e-01 -8.46413195e-01 -8.26287627e-01
3.57180595e-01 -1.11755121e+00 4.21112955e-01 -4.39531147e-01
-3.51790994e-01 4.65914935e-01 6.94432378e-01 -4.84077781e-01
-4.26479459e-01 -6.69038296e-01 -5.43792784e-01 6.76758885e-01
-1.22321677e+00 -8.67686152e-01 -1.85566291e-01 2.18152791e-01
2.45148003e-01 5.45012772e-01 8.91205132e-01 1.23708479e-01
-4.48410153e-01 5.62483966e-01 -5.51175356e-01 -6.37868285e-01
-4.10563856e-01 -1.32135928e+00 6.02702916e-01 1.04204214e+00
-8.78215302e-03 7.98509121e-01 6.99792564e-01 -5.95151722e-01
-2.04422688e+00 -8.46112907e-01 1.18984747e+00 -2.28832960e-01
8.01644742e-01 -5.28680265e-01 -4.91909355e-01 9.11274433e-01
-2.52977628e-02 -1.99314758e-01 2.09082216e-01 3.25797468e-01
-4.25952435e-01 -3.20698529e-01 -1.10285592e+00 6.42235339e-01
1.16973603e+00 -4.58637416e-01 -1.25707388e-01 5.37854433e-01
8.14641297e-01 -1.00079489e+00 -7.00785577e-01 2.51554072e-01
6.62136436e-01 -9.06069458e-01 5.30411959e-01 -4.31992471e-01
5.91437221e-01 -5.35522282e-01 -3.95169020e-01 -5.77489257e-01
-2.96759337e-01 -6.75095201e-01 -7.77661264e-01 8.11870337e-01
9.77161527e-01 -4.15530562e-01 7.35080004e-01 1.20038557e+00
-3.33014548e-01 -1.08847678e+00 -1.02866483e+00 -7.25546598e-01
2.77088471e-02 -9.62441027e-01 9.08096969e-01 2.98325837e-01
4.50166762e-01 2.26065189e-01 2.56843686e-01 -2.45869812e-02
4.56775397e-01 5.15831649e-01 7.44125664e-01 -1.06125677e+00
-8.36426139e-01 -5.46672642e-01 -3.54006998e-02 -5.91629207e-01
3.95756699e-02 -1.17530549e+00 -3.29271525e-01 -1.40853095e+00
4.07146722e-01 -4.27230448e-01 3.35732102e-01 6.88050210e-01
5.25235772e-01 -3.61277491e-01 1.90576613e-01 -2.89326191e-01
-8.06632459e-01 -1.53430939e-01 8.42161119e-01 -2.51000345e-01
-1.92291781e-01 -1.99099347e-01 -3.32219154e-01 6.65430903e-01
2.49570340e-01 -6.77613795e-01 -3.43470961e-01 -5.91547668e-01
1.02253532e+00 3.63005221e-01 3.76558900e-02 -1.05030584e+00
4.86952156e-01 -6.71156406e-01 -4.39861566e-01 -9.00017917e-01
-5.56693748e-02 -9.65862870e-01 8.31932902e-01 9.59556222e-01
-3.53654355e-01 5.14029682e-01 5.01921237e-01 9.21476558e-02
-2.87458301e-02 -6.13882661e-01 6.32939816e-01 -9.19297636e-02
-2.71282315e-01 1.59702390e-01 -2.62606949e-01 2.42600981e-02
1.20731199e+00 2.54522786e-02 -3.29485834e-01 3.59407097e-01
-4.55454677e-01 5.73913455e-01 6.24816418e-01 -4.01246071e-01
1.79749921e-01 -1.16310561e+00 -3.69888186e-01 -6.06084093e-02
1.41249463e-01 3.64288509e-01 -2.85990927e-02 1.11916709e+00
-1.06208158e+00 7.61969209e-01 1.43904656e-01 -4.34786767e-01
-1.35512865e+00 1.02502763e+00 1.65901899e-01 -1.20972109e+00
-1.72684297e-01 7.96786785e-01 6.63866252e-02 -2.42776603e-01
1.66731291e-02 -1.14836121e+00 6.59333944e-01 -1.79551035e-01
7.67480075e-01 6.94407046e-01 4.22360063e-01 9.26271603e-02
-7.97245204e-01 2.92525232e-01 -1.27424821e-01 -4.03298557e-01
1.27617860e+00 4.73367572e-01 -7.12638497e-01 -5.37946373e-02
7.90005982e-01 1.72077417e-01 -4.37563717e-01 -1.38471678e-01
3.66771102e-01 -3.73171598e-01 1.87457740e-01 -7.55554736e-01
-8.93380284e-01 4.14794087e-01 -8.56716633e-02 2.02186793e-01
1.28543890e+00 -1.21241577e-01 5.30341089e-01 4.34099525e-01
1.23724353e+00 -1.31069791e+00 -5.09605587e-01 5.29439032e-01
8.37834597e-01 -1.66638419e-01 4.78486061e-01 -9.47719991e-01
-2.49418139e-01 9.62811470e-01 6.06114328e-01 -1.50247976e-01
3.58877420e-01 1.12566018e+00 -7.82883823e-01 -3.26482564e-01
-1.35006261e+00 -3.39722112e-02 -8.62736851e-02 1.39098555e-01
1.72143772e-01 2.40587309e-01 -7.55996048e-01 6.55940413e-01
-2.92478651e-01 2.46436507e-01 6.83558702e-01 1.29808724e+00
-2.85952955e-01 -1.58166540e+00 -3.14867496e-01 3.37485403e-01
-1.52858272e-01 -2.07788795e-01 -2.68929422e-01 1.21952212e+00
1.29526466e-01 7.94509113e-01 3.52099948e-02 -4.16099876e-01
4.77100641e-01 1.49882272e-01 1.09549057e+00 -9.13150668e-01
-7.21785605e-01 -6.39902353e-02 8.97512734e-01 -9.85003114e-01
-2.51085218e-02 -7.68739462e-01 -1.34540009e+00 -7.00258136e-01
-6.11470520e-01 1.68577746e-01 6.13272965e-01 7.94482529e-01
1.79607436e-01 4.58533943e-01 2.54708499e-01 -5.06890476e-01
-7.63820827e-01 -3.74860585e-01 -4.12629962e-01 -4.11595702e-01
-3.64044935e-01 -6.33176684e-01 -1.24651387e-01 -2.99351186e-01] | [8.624218940734863, 6.772404670715332] |
4dfb5320-c0ac-4adb-82fe-98e752f33621 | learning-based-heuristic-for-combinatorial | 2306.03434 | null | https://arxiv.org/abs/2306.03434v1 | https://arxiv.org/pdf/2306.03434v1.pdf | Learning-Based Heuristic for Combinatorial Optimization of the Minimum Dominating Set Problem using Graph Convolutional Networks | A dominating set of a graph $\mathcal{G=(V, E)}$ is a subset of vertices $S\subseteq\mathcal{V}$ such that every vertex $v\in \mathcal{V} \setminus S$ outside the dominating set is adjacent to a vertex $u\in S$ within the set. The minimum dominating set problem seeks to find a dominating set of minimum cardinality and is a well-established NP-hard combinatorial optimization problem. We propose a novel learning-based heuristic approach to compute solutions for the minimum dominating set problem using graph convolutional networks. We conduct an extensive experimental evaluation of the proposed method on a combination of randomly generated graphs and real-world graph datasets. Our results indicate that the proposed learning-based approach can outperform a classical greedy approximation algorithm. Furthermore, we demonstrate the generalization capability of the graph convolutional network across datasets and its ability to scale to graphs of higher order than those on which it was trained. Finally, we utilize the proposed learning-based heuristic in an iterative greedy algorithm, achieving state-of-the-art performance in the computation of dominating sets. | ['Xenofon Koutsoukos', 'Mudassir Shabbir', 'Abihith Kothapalli'] | 2023-06-06 | null | null | null | null | ['combinatorial-optimization'] | ['methodology'] | [ 4.90387157e-02 3.01152945e-01 -7.80190229e-02 -2.63321489e-01
-5.11553466e-01 -8.93543661e-01 -2.93944299e-01 7.00174332e-01
-4.12516505e-01 5.93766928e-01 -6.86400831e-01 -5.85806847e-01
-6.94054902e-01 -1.51284897e+00 -1.03076839e+00 -5.44992507e-01
-7.53678679e-01 7.36976504e-01 1.21445365e-01 -1.91020653e-01
-9.60570499e-02 7.64981389e-01 -1.56059873e+00 -5.07365018e-02
7.34517932e-01 1.19124639e+00 2.19994858e-01 6.35445237e-01
-1.67275846e-01 5.09235263e-01 -5.23378015e-01 -5.71750283e-01
6.92397952e-01 -2.37085328e-01 -1.00332403e+00 2.69578397e-01
4.16266590e-01 -1.41886610e-03 -5.02003670e-01 1.13879240e+00
1.50007814e-01 3.21999602e-02 3.45109373e-01 -1.32323563e+00
-5.42522550e-01 8.31383407e-01 -5.60069621e-01 3.25000226e-01
1.61348641e-01 -1.28539041e-01 1.28257346e+00 -2.44862512e-01
6.41603887e-01 7.88756430e-01 5.41181266e-01 1.79438666e-01
-9.40134048e-01 -5.54891944e-01 1.95533603e-01 1.21404991e-01
-1.66302133e+00 1.01156928e-01 7.97090530e-01 -2.08945312e-02
1.19645441e+00 5.00148833e-01 7.47039139e-01 -9.08307433e-02
1.07079342e-01 4.32282031e-01 8.67160857e-01 -5.16667068e-01
4.43403661e-01 -3.82858068e-01 1.47337034e-01 1.48976040e+00
7.50849426e-01 -1.64654963e-02 -1.92578547e-02 -5.61674917e-03
3.87241125e-01 -9.24865529e-02 -9.11380574e-02 -4.17695463e-01
-5.79779744e-01 9.79878366e-01 9.64698672e-01 2.77640760e-01
-3.82013083e-01 8.34381282e-01 3.23777944e-01 2.72559762e-01
3.38635117e-01 4.04183388e-01 -4.76588130e-01 4.93208855e-01
-9.74061370e-01 1.00598805e-01 9.62596416e-01 1.09342575e+00
1.07632220e+00 4.30479944e-02 1.50788814e-01 2.82679141e-01
7.09951967e-02 2.47872859e-01 -3.99968684e-01 -9.82314527e-01
4.40334469e-01 1.25762808e+00 -2.98688173e-01 -1.22870672e+00
-6.40517294e-01 -6.18106961e-01 -9.77395236e-01 8.11772570e-02
3.81444663e-01 -1.04096062e-01 -9.70032930e-01 1.74350953e+00
3.26870859e-01 5.29402569e-02 -1.55493885e-01 7.40504622e-01
9.40410316e-01 5.26076138e-01 -2.22550347e-01 -5.17221272e-01
9.23593402e-01 -6.47734284e-01 -1.72756776e-01 -9.97205228e-02
7.42569387e-01 -3.82240295e-01 5.14776468e-01 4.21959609e-01
-1.27255201e+00 -1.11019649e-01 -1.22303498e+00 2.27587268e-01
-4.90340531e-01 -6.48213252e-02 1.04887223e+00 8.46446872e-01
-1.39019799e+00 8.39356303e-01 -5.32202125e-01 -1.34356514e-01
5.61605096e-01 6.99276984e-01 -4.81956363e-01 -4.92812723e-01
-8.38604748e-01 3.54953736e-01 7.77217209e-01 4.69194911e-02
-9.36882734e-01 -3.36807191e-01 -1.04695618e+00 3.07145953e-01
6.20892882e-01 -5.12115240e-01 7.52749443e-01 -1.05084014e+00
-4.68228459e-01 1.15413833e+00 -7.86863361e-03 -7.13609934e-01
1.07692003e-01 6.21524215e-01 -3.02717805e-01 5.10973275e-01
-8.33312050e-02 3.20562810e-01 4.10556763e-01 -1.23264956e+00
-6.20554864e-01 -5.84120929e-01 6.65227175e-01 2.26862933e-02
-4.76290852e-01 -1.74879402e-01 -7.80794501e-01 -1.94671080e-01
3.37570578e-01 -9.72744167e-01 -5.31880081e-01 -2.07114100e-01
-4.41243380e-01 -3.70705962e-01 2.45716274e-01 -8.51705819e-02
1.63757932e+00 -1.71114469e+00 1.57529309e-01 8.26225579e-01
9.55640376e-01 3.18418682e-01 -2.74547879e-02 6.82697773e-01
-9.05846208e-02 2.64057964e-01 -2.87597537e-01 -7.27090091e-02
-2.69825812e-02 5.78811407e-01 3.65462303e-01 7.02745855e-01
-2.71133542e-01 6.43133819e-01 -8.45070362e-01 -4.74350691e-01
7.49712512e-02 3.15461531e-02 -5.89441955e-01 -3.70779522e-02
-5.35269320e-01 -3.18291754e-01 -2.86297590e-01 6.15994334e-01
1.03005886e+00 -7.26844966e-01 7.58194387e-01 1.38931841e-01
4.42993455e-02 -4.85967584e-02 -1.61646783e+00 1.33275056e+00
-6.45481944e-02 1.67253450e-01 2.80163378e-01 -1.41276872e+00
9.57120836e-01 -1.64714068e-01 8.26182246e-01 -6.81311667e-01
4.28053766e-01 3.69926065e-01 2.51399547e-01 -1.12029187e-01
4.47453439e-01 2.40415245e-01 -1.28799349e-01 6.08373404e-01
4.11703624e-02 2.88969785e-01 8.99152040e-01 5.44367254e-01
1.70609689e+00 -3.81702393e-01 5.32714799e-02 -5.53376794e-01
5.77359080e-01 4.36326396e-03 5.05041122e-01 7.67222464e-01
-1.61043629e-01 1.69745252e-01 6.18864000e-01 -7.94818580e-01
-7.50624180e-01 -7.17421412e-01 2.49463066e-01 9.87238944e-01
2.53366232e-01 -5.61518073e-01 -1.04884183e+00 -7.68881857e-01
1.93267986e-01 1.31338641e-01 -7.01203465e-01 -6.54469430e-02
-5.92359126e-01 -5.26857078e-01 3.83888334e-01 3.64833593e-01
5.00755250e-01 -8.62313390e-01 -6.33718789e-01 3.44475031e-01
1.02395579e-01 -1.04154050e+00 -4.06387746e-01 4.24702585e-01
-8.49089146e-01 -1.76759219e+00 -4.52066734e-02 -1.24806154e+00
1.10390711e+00 4.47271794e-01 1.40436089e+00 8.44935715e-01
-3.09139371e-01 4.33132321e-01 -3.50877494e-01 -1.52289450e-01
-1.77085862e-01 2.88279027e-01 -7.64288530e-02 -1.77782476e-01
4.12607253e-01 -6.11827433e-01 -6.31596088e-01 1.16163865e-02
-9.84445155e-01 -3.60613614e-01 3.90844494e-01 3.63740504e-01
1.04050207e+00 7.47525990e-01 2.91622758e-01 -1.20569134e+00
5.92814267e-01 -6.00976527e-01 -9.89422798e-01 2.37761870e-01
-8.40474606e-01 1.69758007e-01 1.01046503e+00 7.76048973e-02
-1.11399747e-01 2.91383773e-01 2.59382501e-02 -5.36905050e-01
1.61988124e-01 8.79446983e-01 -2.21652389e-02 -3.16087753e-01
4.84522700e-01 2.55776912e-01 -1.66536480e-01 -1.83143348e-01
3.18573982e-01 1.20045945e-01 3.60836357e-01 -4.69042599e-01
6.82440639e-01 5.83573937e-01 5.69139242e-01 -4.69124675e-01
-4.23523784e-01 -3.03832084e-01 -4.66443598e-01 -4.08514738e-01
4.21475023e-01 -6.25487089e-01 -1.16758072e+00 1.24344401e-01
-1.03208244e+00 -1.01828799e-01 1.32073881e-02 5.24358563e-02
-3.92850488e-01 3.79617095e-01 -4.29853350e-01 -7.80176282e-01
-5.11221707e-01 -8.93141031e-01 5.76766014e-01 1.10451594e-01
2.69310594e-01 -9.99221385e-01 -1.63473204e-01 1.93094894e-01
-6.99612051e-02 6.93122983e-01 1.29844391e+00 -8.05536509e-01
-8.78908098e-01 -3.31727058e-01 -2.74784058e-01 2.10872814e-01
-5.86222447e-02 -1.33759513e-01 -3.11583310e-01 -7.08374262e-01
-6.94109797e-01 -1.52586058e-01 9.93888259e-01 5.28541327e-01
1.31384540e+00 -4.68157768e-01 -4.82088655e-01 7.54064381e-01
2.09736514e+00 2.33449012e-01 5.22289693e-01 3.32002714e-02
6.94118142e-01 2.15463907e-01 2.80322582e-01 5.05206048e-01
4.75981653e-01 1.59147494e-02 1.02154720e+00 -1.49992391e-01
5.70433401e-02 3.96070722e-03 -2.30239928e-01 6.64229035e-01
-1.08775072e-01 -8.11485589e-01 -1.03122389e+00 8.03954184e-01
-1.58788884e+00 -6.63725436e-01 -4.45767462e-01 2.15915012e+00
3.45272362e-01 3.21525812e-01 1.26331434e-01 4.63762999e-01
8.36379230e-01 8.19603503e-02 -3.83447886e-01 -8.48479986e-01
-8.31945986e-03 6.99832737e-01 8.92786443e-01 4.84951347e-01
-9.02772963e-01 9.24373090e-01 5.61666632e+00 6.34072423e-01
-7.43275225e-01 -1.71418220e-01 6.41552389e-01 -4.35750075e-02
-5.23728013e-01 -8.14977810e-02 -4.26352829e-01 2.94157684e-01
7.57664263e-01 -2.16190174e-01 9.81582642e-01 8.34230900e-01
-1.56401619e-01 -1.85975716e-01 -1.16398251e+00 9.00319815e-01
7.21691400e-02 -1.71889424e+00 -2.57593691e-01 3.18410426e-01
9.16109502e-01 -7.40566617e-03 -3.25091220e-02 5.19445054e-02
7.24746943e-01 -1.23557091e+00 4.96571481e-01 -1.07575402e-01
1.07557154e+00 -1.34940255e+00 4.74304765e-01 4.30779815e-01
-1.87441492e+00 -2.61028945e-01 -3.62516433e-01 -1.68005362e-01
-2.78155476e-01 6.85740590e-01 -7.83492625e-01 7.90754378e-01
8.73620689e-01 1.38111696e-01 -3.24101627e-01 8.18049133e-01
1.79860685e-02 3.69780958e-01 -4.85763639e-01 -3.11396658e-01
5.46748281e-01 -2.53797054e-01 4.52586889e-01 9.71670151e-01
1.23916201e-01 5.04647970e-01 5.52168310e-01 7.51413584e-01
-6.49248540e-01 1.55501664e-01 -9.67438936e-01 -3.52324188e-01
6.82700276e-01 1.35911918e+00 -1.29061782e+00 -1.46709785e-01
-1.88030466e-01 5.81884921e-01 8.61772776e-01 1.19268276e-01
-8.17606449e-01 -6.62538052e-01 5.85585952e-01 2.94677198e-01
7.01586246e-01 -4.65153128e-01 -6.95312470e-02 -4.01077390e-01
1.15130581e-01 -7.66105711e-01 9.44986641e-01 -3.19695681e-01
-7.83405840e-01 8.28781128e-01 -7.26719573e-02 -8.40193748e-01
1.73672616e-01 -7.20458329e-01 -5.30311704e-01 6.34853899e-01
-1.43592775e+00 -9.09165859e-01 -3.79219264e-01 8.52749825e-01
-7.50803798e-02 -1.07974395e-01 7.25055873e-01 2.87066311e-01
-3.80845070e-01 6.37564421e-01 6.47342429e-02 1.37260243e-01
-3.11171114e-01 -1.31851983e+00 1.21401280e-01 1.13002765e+00
-5.16857766e-03 4.39973325e-01 4.03390616e-01 -6.37101769e-01
-1.94894230e+00 -1.22106051e+00 7.50470817e-01 2.19847918e-01
2.35709265e-01 -2.53537267e-01 -4.88217413e-01 7.64936745e-01
1.99597746e-01 2.99456090e-01 6.81600571e-01 -1.03651481e-02
-3.36299181e-01 -3.55637193e-01 -1.49904728e+00 2.84456491e-01
1.40583241e+00 3.12186144e-02 1.37201145e-01 4.82513279e-01
7.14956820e-01 -6.42758310e-01 -8.99623036e-01 3.01388323e-01
1.53284341e-01 -9.51495349e-01 6.93743467e-01 -7.27342665e-01
4.12881941e-01 -1.83844790e-01 -2.78622955e-01 -1.21669567e+00
-5.41073263e-01 -8.66813719e-01 -3.18207949e-01 7.49466479e-01
3.69122446e-01 -4.79442209e-01 1.21067619e+00 1.00343205e-01
-2.29277492e-01 -1.10367966e+00 -1.14657736e+00 -7.56135404e-01
1.36620507e-01 -5.05157709e-01 9.74878013e-01 7.46185899e-01
-2.30676934e-01 1.01667263e-01 6.60015196e-02 4.74936634e-01
9.31365132e-01 6.75914526e-01 6.04151428e-01 -1.42891312e+00
-2.34818965e-01 -3.11460316e-01 -3.62683475e-01 -6.61231875e-01
2.35941902e-01 -1.50245214e+00 -1.26211569e-01 -2.02337551e+00
6.85114786e-02 -8.20261002e-01 -4.31811512e-01 5.86323380e-01
2.32832298e-01 1.86763063e-01 4.71166000e-02 -3.74389768e-01
-9.48220134e-01 -7.11278021e-02 1.27616203e+00 -2.31816188e-01
-4.08755727e-02 -2.61398226e-01 -8.86230469e-01 5.25235713e-01
7.95015514e-01 -6.77926719e-01 -5.40524602e-01 -5.80774426e-01
7.31252193e-01 2.26073205e-01 8.23944248e-03 -8.48684967e-01
1.83930337e-01 -1.54481724e-01 1.47730082e-01 -4.42578077e-01
-8.39313120e-02 -9.95402813e-01 2.41091520e-01 8.04030240e-01
-4.64419574e-02 4.95749086e-01 2.58913547e-01 5.61863303e-01
2.25189507e-01 -4.35388796e-02 9.23988581e-01 -3.82932991e-01
-7.45281518e-01 7.50310898e-01 4.62598801e-02 2.11064920e-01
1.33852053e+00 -3.76382411e-01 -3.20172638e-01 -2.19138637e-01
-3.63691986e-01 5.12182891e-01 3.56657833e-01 2.40870882e-02
8.23606193e-01 -1.16633177e+00 -7.28427708e-01 1.35531068e-01
2.27214590e-01 8.45578313e-02 8.85839835e-02 5.44135094e-01
-1.04701173e+00 2.11541012e-01 -1.11931317e-01 -2.65744537e-01
-1.35794306e+00 8.56374502e-01 4.37777460e-01 -5.11371553e-01
-4.68401790e-01 1.20524502e+00 -4.44668770e-01 -3.96340847e-01
3.17410916e-01 -3.18664253e-01 -1.33305229e-02 -2.51075447e-01
1.85373366e-01 6.10304177e-01 3.53674740e-01 -6.69030190e-01
-6.26642227e-01 7.16790482e-02 3.71455727e-03 4.00990188e-01
1.36151516e+00 9.92716327e-02 -5.41124582e-01 -3.17099750e-01
1.38697696e+00 -1.81369126e-01 -7.25175500e-01 -1.75750077e-01
-1.76043957e-01 -4.23938483e-01 4.05340604e-02 -5.31960785e-01
-1.72919774e+00 3.97462577e-01 4.97495800e-01 7.02983737e-01
1.41228831e+00 1.87372435e-02 9.71043110e-01 5.81581652e-01
7.13921964e-01 -1.29618168e+00 -8.17022249e-02 4.86637861e-01
4.69760627e-01 -9.24678206e-01 1.22273989e-01 -5.58465660e-01
-1.58868968e-01 1.10121453e+00 5.73161244e-01 -5.14556885e-01
7.29690790e-01 3.21004301e-01 -3.94865632e-01 -6.09095752e-01
-7.02455819e-01 -5.93545377e-01 4.15882692e-02 5.33194542e-01
9.09806117e-02 2.84351200e-01 -6.05372906e-01 5.17035067e-01
-2.20048010e-01 -7.41938874e-02 4.47636217e-01 1.10930836e+00
-6.80071771e-01 -9.66547489e-01 -2.12900620e-02 6.61257505e-01
-4.11392599e-01 -6.46784306e-02 -5.43464065e-01 8.45456004e-01
5.19542158e-01 1.05799496e+00 2.79665560e-01 -5.35600245e-01
1.41558200e-01 -4.36413884e-01 8.31088006e-01 -5.41838288e-01
-6.61082268e-01 -2.14502871e-01 1.96253896e-01 -5.80851912e-01
-1.38036489e-01 -1.47405967e-01 -1.83635819e+00 -8.77360284e-01
-2.51730591e-01 1.91207856e-01 4.23899472e-01 8.02578628e-01
2.73204327e-01 5.38459301e-01 8.19189072e-01 -1.10865213e-01
-1.96554422e-01 -4.55556691e-01 -9.74082351e-01 2.04632133e-01
6.90538213e-02 -3.54781121e-01 -1.59448355e-01 -4.09501284e-01] | [6.868957042694092, 5.664711952209473] |
cb733028-f775-49d3-8efd-873514430600 | competency-aware-neural-machine-translation | 2211.13865 | null | https://arxiv.org/abs/2211.13865v1 | https://arxiv.org/pdf/2211.13865v1.pdf | Competency-Aware Neural Machine Translation: Can Machine Translation Know its Own Translation Quality? | Neural machine translation (NMT) is often criticized for failures that happen without awareness. The lack of competency awareness makes NMT untrustworthy. This is in sharp contrast to human translators who give feedback or conduct further investigations whenever they are in doubt about predictions. To fill this gap, we propose a novel competency-aware NMT by extending conventional NMT with a self-estimator, offering abilities to translate a source sentence and estimate its competency. The self-estimator encodes the information of the decoding procedure and then examines whether it can reconstruct the original semantics of the source sentence. Experimental results on four translation tasks demonstrate that the proposed method not only carries out translation tasks intact but also delivers outstanding performance on quality estimation. Without depending on any reference or annotated data typically required by state-of-the-art metric and quality estimation methods, our model yields an even higher correlation with human quality judgments than a variety of aforementioned methods, such as BLEURT, COMET, and BERTScore. Quantitative and qualitative analyses show better robustness of competency awareness in our model. | ['Jun Xie', 'Luo Si', 'Kai Fan', 'Dayiheng Liu', 'Haoran Wei', 'Baosong Yang', 'Pei Zhang'] | 2022-11-25 | null | null | null | null | ['nmt'] | ['computer-code'] | [ 3.06446612e-01 2.74685055e-01 -2.56419390e-01 -3.99082482e-01
-1.20255458e+00 -7.27288425e-01 6.99583530e-01 1.60197496e-01
-4.71377760e-01 8.98100972e-01 2.20912844e-01 -4.65730309e-01
1.44868031e-01 -4.03980732e-01 -9.64061797e-01 -1.55709028e-01
6.02503359e-01 7.46127784e-01 -2.95746982e-01 -3.87553990e-01
5.41362047e-01 -6.20132983e-02 -1.14863718e+00 2.74796605e-01
1.66341901e+00 8.60349298e-01 3.72650117e-01 5.20687044e-01
-7.46245831e-02 8.16495776e-01 -8.82152736e-01 -1.17849290e+00
1.98963284e-01 -6.15019739e-01 -9.07711744e-01 -2.10755602e-01
4.14175630e-01 -3.65357161e-01 7.02983811e-02 1.33349943e+00
3.87901902e-01 -3.30059856e-01 4.98642385e-01 -9.33166087e-01
-1.09547269e+00 9.42180574e-01 -1.60329118e-01 1.56105250e-01
7.11890638e-01 3.85927647e-01 9.92490649e-01 -9.66234624e-01
6.04332983e-01 9.48371828e-01 5.25414288e-01 6.37423813e-01
-9.15684164e-01 -4.59087461e-01 -1.12055182e-01 2.64427245e-01
-9.20367897e-01 -5.94379842e-01 4.65598196e-01 -3.19709659e-01
8.15868437e-01 4.45761830e-01 5.09276152e-01 1.50915194e+00
4.74298179e-01 7.57911623e-01 1.66460943e+00 -4.34686244e-01
2.19171256e-01 5.50850928e-01 -1.51199862e-01 6.50774837e-01
1.28700718e-01 1.33519337e-01 -9.88699138e-01 7.21666217e-03
3.40247720e-01 -3.87929291e-01 -4.25073802e-01 -1.22740576e-02
-1.64468718e+00 2.94898391e-01 2.48126388e-02 3.54205579e-01
-2.71328211e-01 -1.71077251e-01 3.39922637e-01 9.64709103e-01
5.75943649e-01 8.22644889e-01 -4.18525845e-01 -8.18854809e-01
-1.40714800e+00 -1.08927868e-01 8.72024179e-01 1.12344706e+00
4.94177133e-01 -1.87231805e-02 -2.70048499e-01 5.51558018e-01
-1.34770215e-01 6.97312295e-01 7.72104561e-01 -9.63710785e-01
7.50423849e-01 7.53787160e-01 2.89598256e-01 -7.80641735e-01
3.48026417e-02 -9.47859645e-01 -6.68106735e-01 2.21699812e-02
3.50493610e-01 2.66946435e-01 -6.29171908e-01 1.69740570e+00
-1.65431961e-01 -3.73228848e-01 4.17665914e-02 1.21702373e+00
4.62124527e-01 3.64409089e-01 -3.15815091e-01 -4.76212531e-01
1.09530187e+00 -1.14020514e+00 -8.85342181e-01 -3.10006827e-01
5.96111119e-01 -9.99612510e-01 1.64571571e+00 6.60945654e-01
-1.37253499e+00 -6.29156291e-01 -1.22725189e+00 2.06850171e-02
-2.34009661e-02 1.75247416e-01 5.09462595e-01 9.18670774e-01
-1.16063094e+00 9.83012974e-01 -6.76876366e-01 -2.40798667e-01
2.17867732e-01 2.72676289e-01 -4.58214730e-01 1.19228423e-01
-1.28612423e+00 1.62376773e+00 3.56816594e-03 1.73881859e-01
-8.89872372e-01 -3.89836103e-01 -6.14291847e-01 -4.12498154e-02
2.96736479e-01 -8.43707085e-01 1.49317515e+00 -1.35013521e+00
-1.80452526e+00 8.66938829e-01 -2.73035824e-01 -3.17210674e-01
1.04217708e+00 -3.80706936e-01 -4.64659721e-01 -1.56532899e-02
1.59562662e-01 2.74983138e-01 9.10898447e-01 -8.97326648e-01
-2.69453913e-01 -2.50194281e-01 1.06118307e-01 2.90691525e-01
-4.18612927e-01 6.04664497e-02 -2.76841462e-01 -5.68524539e-01
1.34877056e-01 -8.11875045e-01 1.92084596e-01 -8.08714554e-02
-2.72963107e-01 9.83704627e-02 1.89243019e-01 -8.36304843e-01
1.33124924e+00 -1.64347780e+00 4.43886310e-01 -1.09164156e-01
2.30583757e-01 3.34414572e-01 -3.06077808e-01 5.99618495e-01
3.73641223e-01 1.40628621e-01 -2.64709920e-01 -2.72573382e-01
1.84070364e-01 2.52556261e-02 -7.15274811e-02 4.61378306e-01
2.01873168e-01 1.12950850e+00 -9.72266972e-01 -4.74160939e-01
-1.31117150e-01 1.04347244e-01 -2.64382571e-01 3.07303250e-01
-7.30067864e-02 6.01820290e-01 -3.01060200e-01 8.74223888e-01
4.09888268e-01 -4.88173306e-01 2.24160478e-01 1.49838492e-01
6.73720464e-02 6.44170523e-01 -6.09096289e-01 2.08383751e+00
-5.81155002e-01 6.87247753e-01 -2.09776565e-01 -8.18466425e-01
8.87090743e-01 4.88752335e-01 -2.68981516e-01 -1.19141889e+00
1.60777286e-01 6.87011182e-01 1.84526786e-01 -4.95771170e-01
7.63857484e-01 -2.46107012e-01 -1.41400069e-01 6.95448279e-01
1.70106113e-01 -9.46522728e-02 1.09640166e-01 2.44561777e-01
1.10520291e+00 4.46679503e-01 3.50746900e-01 -3.73159617e-01
5.77254951e-01 6.94699511e-02 5.30104458e-01 7.70834446e-01
-4.98985350e-01 5.34620285e-01 3.25565249e-01 -2.69261837e-01
-1.23639870e+00 -1.02271116e+00 1.80042073e-01 9.65781271e-01
1.46091536e-01 -3.89331758e-01 -1.17828989e+00 -7.90994167e-01
-3.51981252e-01 8.75575781e-01 -5.56584299e-01 -3.12980145e-01
-3.93135607e-01 -4.43013340e-01 5.90601683e-01 4.12531376e-01
3.68850440e-01 -8.50505114e-01 -5.48891604e-01 1.23513587e-01
-8.06309283e-01 -1.10058177e+00 -4.86829638e-01 -5.35857156e-02
-1.17157388e+00 -5.49263120e-01 -5.68165183e-01 -5.19794941e-01
5.91647744e-01 -2.42700707e-02 1.40124905e+00 2.48990491e-01
3.82080793e-01 -3.81658524e-02 -5.19299686e-01 -1.34429082e-01
-1.10068655e+00 1.98099554e-01 3.10886472e-01 -3.95271122e-01
4.87786055e-01 -5.96023798e-01 -5.96920192e-01 5.35122454e-01
-5.41496754e-01 2.23968863e-01 1.00027835e+00 9.14643884e-01
2.31369212e-01 -4.69728380e-01 6.60121679e-01 -8.88378084e-01
1.05750763e+00 -8.67135525e-02 -2.24928185e-01 5.41400075e-01
-1.29363883e+00 1.90098286e-01 7.31164336e-01 -4.62523162e-01
-9.11823750e-01 -5.21146297e-01 8.39969516e-02 -9.31387246e-02
1.25035971e-01 4.25351113e-01 -4.85251211e-02 -4.54280525e-02
8.67171764e-01 5.61992109e-01 6.09912165e-02 -3.17970663e-01
1.46986559e-01 8.56623411e-01 6.68647707e-01 -7.10377753e-01
9.58578110e-01 -6.21974953e-02 -4.55479980e-01 -3.72062810e-02
-9.06228900e-01 1.25744361e-02 -5.36166072e-01 -3.98821235e-01
2.73068726e-01 -8.29877555e-01 -6.46222651e-01 1.34759560e-01
-1.31302106e+00 9.37231928e-02 -3.22384462e-02 4.76877451e-01
-8.42326760e-01 5.35972118e-01 -8.93918633e-01 -7.65432656e-01
-5.96751809e-01 -1.37014306e+00 9.39698815e-01 4.98654228e-03
-6.06382847e-01 -7.80111969e-01 -1.19587630e-01 1.05207229e+00
7.13813245e-01 -6.93726540e-02 8.33602905e-01 -5.98140001e-01
-5.48152447e-01 -4.08248156e-01 -1.09101154e-01 6.10254645e-01
-1.03070289e-01 -3.65316927e-01 -9.08995152e-01 -2.61746347e-01
3.44877005e-01 -5.33752918e-01 4.90820229e-01 -2.04372600e-01
6.39469266e-01 -5.27440488e-01 2.81562060e-01 3.93338531e-01
1.29070294e+00 -1.94939226e-01 6.65487528e-01 6.19098604e-01
1.45613313e-01 6.01692021e-01 8.20186257e-01 1.13141797e-01
3.59752208e-01 5.98703861e-01 3.87692839e-01 2.54126638e-01
1.42233819e-02 -4.93172437e-01 7.41601646e-01 1.45959079e+00
-4.60462689e-01 -3.24757278e-01 -8.79169524e-01 2.18353257e-01
-1.84905767e+00 -7.78987467e-01 -3.04265064e-03 2.15838599e+00
1.11388516e+00 4.10814703e-01 -2.37050697e-01 8.52013305e-02
6.44896626e-01 -1.14034891e-01 -4.85645562e-01 -8.31602752e-01
-1.64869428e-01 8.92190337e-02 2.41554067e-01 3.93746525e-01
-4.62357491e-01 1.15744007e+00 6.82308960e+00 8.89656305e-01
-8.43733549e-01 4.53305185e-01 5.54515123e-01 2.00832710e-02
-4.87242162e-01 8.44347700e-02 -1.97208375e-01 5.07551134e-01
1.21125031e+00 -2.16710880e-01 6.60756350e-01 5.94848096e-01
2.68029690e-01 -1.00307815e-01 -1.39900279e+00 7.01677859e-01
1.83706984e-01 -1.02040708e+00 1.12744376e-01 8.93283188e-02
6.85131133e-01 -2.25600988e-01 2.40334034e-01 3.52420479e-01
1.43353771e-02 -1.08963764e+00 1.11138356e+00 6.89164877e-01
9.22747374e-01 -5.96142352e-01 9.46073174e-01 8.85555804e-01
-3.10086578e-01 5.97249605e-02 -5.57727098e-01 -4.85610813e-01
-1.62469316e-02 6.71011209e-01 -8.35963190e-01 6.55270815e-01
3.09483767e-01 2.72142410e-01 -5.43432474e-01 5.52374959e-01
-5.74348390e-01 7.60112584e-01 2.91809946e-01 -2.63586223e-01
8.54744613e-02 -2.52808005e-01 6.57809794e-01 1.15198350e+00
5.28763354e-01 -3.10635269e-01 -3.62339050e-01 1.03854799e+00
-2.71586955e-01 4.25004870e-01 -3.94065052e-01 -4.96862769e-01
3.89418989e-01 1.05617547e+00 -2.18346626e-01 -4.33321416e-01
-2.29747012e-01 1.59039104e+00 5.82297444e-01 1.70672610e-01
-8.28767180e-01 5.63382320e-02 4.25113320e-01 3.82587798e-02
-1.88195154e-01 -2.00378522e-01 -5.86574018e-01 -1.54373252e+00
6.71785295e-01 -1.41089582e+00 -3.02638084e-01 -8.76243711e-01
-1.13389933e+00 9.59187329e-01 -5.14152288e-01 -1.59677148e+00
-3.95497173e-01 -5.00710785e-01 -2.25623310e-01 9.15533125e-01
-1.48562241e+00 -9.78996992e-01 3.96377295e-02 1.02311216e-01
6.32391751e-01 -2.25750372e-01 9.53264952e-01 -2.24824325e-04
-2.36530423e-01 9.94903564e-01 -2.98559349e-02 -2.90883183e-02
9.33376312e-01 -1.15566158e+00 4.78477508e-01 9.76405561e-01
5.23570664e-02 9.36382234e-01 1.00951242e+00 -6.45653665e-01
-1.61980200e+00 -5.98734617e-01 1.38577485e+00 -9.55196321e-01
6.06959164e-01 -3.59750271e-01 -8.09516191e-01 2.41048262e-01
3.91163558e-01 -3.85191172e-01 6.28977835e-01 1.35658011e-01
-6.68506801e-01 -7.40383938e-02 -1.06328237e+00 4.41118687e-01
1.25025976e+00 -7.03855217e-01 -8.69443834e-01 3.74746889e-01
8.35875750e-01 -4.75174665e-01 -7.91841865e-01 3.26714486e-01
7.18904436e-01 -1.18261468e+00 4.53423053e-01 -6.33392632e-01
9.30343866e-01 -3.10390326e-03 -2.85038888e-01 -1.51586771e+00
-2.59178251e-01 -7.67720699e-01 -1.10843651e-01 9.47723269e-01
8.77795815e-01 -4.82350051e-01 6.98311925e-01 6.59917891e-01
-3.60544890e-01 -7.65906274e-01 -9.32770312e-01 -1.06254852e+00
1.71616614e-01 -4.46825087e-01 7.20121443e-01 9.57793951e-01
4.29250449e-01 3.09827030e-01 -6.79049373e-01 -9.91216227e-02
7.17656732e-01 2.66990006e-01 5.67852378e-01 -1.11120856e+00
-4.60948676e-01 -5.30026257e-01 -3.83745968e-01 -9.15092587e-01
1.60101458e-01 -9.61604595e-01 9.62375700e-02 -1.43149924e+00
5.14892578e-01 1.21519372e-01 -2.27113709e-01 2.49872163e-01
-3.65466595e-01 2.48611480e-01 -4.77403961e-03 5.20385385e-01
-7.73585260e-01 5.33406198e-01 1.62819910e+00 -1.00159831e-01
1.67729080e-01 -1.19220838e-01 -1.06487966e+00 4.49449658e-01
7.90847540e-01 -5.37632465e-01 -2.57453173e-01 -7.77982175e-01
6.55228555e-01 3.79949272e-01 1.02176793e-01 -1.03717589e+00
3.07638526e-01 -1.25994861e-01 2.58476764e-01 -1.05485171e-01
1.91192850e-01 -6.58548653e-01 1.35489076e-01 4.67005730e-01
-5.62762737e-01 4.80995774e-01 -2.99663514e-01 5.28564274e-01
-2.89163291e-01 -2.44219303e-01 5.66863358e-01 -3.97035092e-01
-3.25883001e-01 -7.18198717e-02 -2.63181478e-01 -1.13056377e-02
4.85777676e-01 -4.12999541e-01 -6.44291341e-01 -5.97301722e-01
-4.26518172e-01 -1.52112148e-03 9.02755678e-01 5.01019359e-01
6.34459734e-01 -1.17498636e+00 -9.21939135e-01 3.12352106e-02
3.52754384e-01 -7.17766762e-01 -1.55865885e-02 1.17799008e+00
-4.64197218e-01 5.10742664e-01 -3.47856998e-01 -4.65415329e-01
-9.50912833e-01 4.23711360e-01 6.31597042e-02 -2.83661604e-01
-3.42482686e-01 6.08081400e-01 -3.29731494e-01 -5.42837322e-01
1.02717541e-01 -1.41507909e-01 2.80290246e-01 -2.80789554e-01
5.41378617e-01 2.58779079e-01 3.84853631e-01 -5.23745418e-01
-2.78862715e-01 2.58897275e-01 -1.72449589e-01 -4.23574269e-01
9.37065005e-01 -2.92567641e-01 -2.92035669e-01 4.25419331e-01
7.28047371e-01 8.01794697e-03 -9.09664571e-01 -2.76935220e-01
6.66373000e-02 -6.55837357e-01 -1.65749788e-01 -1.53819752e+00
-5.00775397e-01 1.04014778e+00 3.25504184e-01 -1.73153117e-01
1.10885453e+00 -2.42535889e-01 9.66474712e-01 5.70621431e-01
8.58098745e-01 -1.47774100e+00 1.29909635e-01 3.50840777e-01
7.84888268e-01 -1.41379380e+00 -1.41360566e-01 -1.83635220e-01
-8.42588902e-01 1.04355979e+00 6.16642177e-01 2.85297155e-01
-1.63997978e-01 8.70403349e-02 3.94114047e-01 1.68796718e-01
-1.16580069e+00 2.05170810e-01 3.98166358e-01 4.27462071e-01
7.45417833e-01 3.10517579e-01 -7.23359287e-01 6.66044295e-01
-6.95443153e-01 -2.44869739e-02 6.93823636e-01 6.77987039e-01
-6.81595922e-01 -1.23852766e+00 -2.01445103e-01 2.30943844e-01
-4.99720961e-01 -3.20940971e-01 -7.08667219e-01 4.91951793e-01
-1.34082422e-01 1.17705703e+00 -5.12069583e-01 -8.09786260e-01
2.62352794e-01 2.77843565e-01 6.65061414e-01 -5.20597696e-01
-9.36329663e-01 -2.27936536e-01 2.30576962e-01 -6.41901135e-01
-3.94174069e-01 -4.54710424e-01 -7.86719918e-01 -4.88962144e-01
-4.65982735e-01 4.07315254e-01 9.65270281e-01 1.09738755e+00
2.99726993e-01 1.23478882e-01 5.54300249e-01 -2.74105251e-01
-1.11072767e+00 -1.22985375e+00 -1.21234693e-01 3.77278835e-01
2.07388759e-01 -2.64117956e-01 -3.38611931e-01 -1.43688828e-01] | [11.634576797485352, 10.122751235961914] |
932821e2-d685-48d8-aa76-8614205f9b94 | emulation-of-physical-processes-with-emukit | 2110.13293 | null | https://arxiv.org/abs/2110.13293v1 | https://arxiv.org/pdf/2110.13293v1.pdf | Emulation of physical processes with Emukit | Decision making in uncertain scenarios is an ubiquitous challenge in real world systems. Tools to deal with this challenge include simulations to gather information and statistical emulation to quantify uncertainty. The machine learning community has developed a number of methods to facilitate decision making, but so far they are scattered in multiple different toolkits, and generally rely on a fixed backend. In this paper, we present Emukit, a highly adaptable Python toolkit for enriching decision making under uncertainty. Emukit allows users to: (i) use state of the art methods including Bayesian optimization, multi-fidelity emulation, experimental design, Bayesian quadrature and sensitivity analysis; (ii) easily prototype new decision making methods for new problems. Emukit is agnostic to the underlying modeling framework and enables users to use their own custom models. We show how Emukit can be used on three exemplary case studies. | ['Javier Gonzalez', 'Neil D. Lawrence', 'Cliff McCollum', 'Maren Mahsereci', 'Mark Pullin', 'Andrei Paleyes'] | 2021-10-25 | null | null | null | null | ['decision-making-under-uncertainty', 'decision-making-under-uncertainty'] | ['medical', 'reasoning'] | [-5.30387223e-01 -1.56312332e-01 8.38588476e-02 -4.95426774e-01
-8.70645642e-01 -5.09125948e-01 8.15380454e-01 2.47063398e-01
-1.34553120e-01 8.53925407e-01 -2.80459914e-02 -8.70926917e-01
-5.34757257e-01 -8.37027133e-01 -2.49837667e-01 -5.84429741e-01
-2.16893807e-01 8.82493436e-01 1.13730349e-01 -1.24510065e-01
3.80135089e-01 5.86904764e-01 -1.48563743e+00 5.24247065e-02
8.14288676e-01 9.99499500e-01 -2.78720587e-01 6.43197834e-01
5.76162674e-02 6.14339948e-01 -4.01703864e-01 -8.37524310e-02
3.48811626e-01 1.65972576e-01 -4.46914345e-01 -6.74810112e-01
-3.22228760e-01 -3.69614571e-01 1.95867151e-01 5.53990424e-01
9.00506079e-01 2.26187438e-01 9.11959350e-01 -1.47877395e+00
2.02264234e-01 8.97550285e-01 -2.76831746e-01 9.61870402e-02
4.60063934e-01 6.97537124e-01 3.83175731e-01 -6.66410387e-01
1.44433603e-01 1.46664858e+00 9.23889160e-01 4.62995954e-02
-1.48251975e+00 -7.98811495e-01 -9.27446689e-03 6.52389228e-02
-1.52641845e+00 -4.96979773e-01 4.40299213e-01 -7.45261073e-01
1.29480553e+00 4.00862038e-01 4.88758594e-01 8.25686216e-01
6.98964357e-01 4.94931489e-01 1.71126199e+00 -3.56927067e-01
1.02358615e+00 1.74224168e-01 -1.24766357e-01 1.23136804e-01
-7.01027662e-02 8.92714620e-01 -2.84143865e-01 -6.02893770e-01
4.31457937e-01 -3.95234942e-01 2.68838167e-01 -4.50855434e-01
-1.06970727e+00 9.12718892e-01 1.12032898e-01 -1.35997474e-01
-1.72110796e-01 5.19400299e-01 2.32428789e-01 2.68511146e-01
1.75962478e-01 4.97319371e-01 -7.12096632e-01 -2.57743150e-01
-9.37578917e-01 9.40925598e-01 1.18806767e+00 7.48804748e-01
6.68689549e-01 1.37509510e-01 -3.77628446e-01 4.75790620e-01
1.07089043e+00 4.35691625e-01 2.46551987e-02 -1.28971899e+00
1.22749157e-01 -9.95412394e-02 6.93126738e-01 -6.21562421e-01
-7.19920874e-01 -3.30553889e-01 -4.40469354e-01 8.87121260e-01
1.94410235e-01 -7.31557131e-01 -9.23706412e-01 1.23526549e+00
4.80748147e-01 -4.42734212e-02 1.13922385e-02 6.87972665e-01
3.15819472e-01 7.07674086e-01 2.04199895e-01 -4.91280071e-02
8.06640685e-01 -2.17034087e-01 -6.14626288e-01 -2.56794393e-01
2.54304618e-01 -9.52721477e-01 5.61284781e-01 7.56908655e-01
-9.77041602e-01 -1.22117870e-01 -1.27630293e+00 6.00439966e-01
-6.05168223e-01 -5.43521345e-01 7.57034242e-01 9.89063799e-01
-9.11442220e-01 9.02132571e-01 -1.00245643e+00 -1.61295645e-02
1.43421113e-01 3.11937302e-01 3.90876591e-01 1.76958330e-02
-1.44686925e+00 1.59760606e+00 3.77928257e-01 -1.61827970e-02
-1.18890297e+00 -1.11567819e+00 -1.00692153e+00 -2.30218321e-01
4.38827246e-01 -9.81010616e-01 1.68553054e+00 -5.85305430e-02
-1.91735733e+00 1.66693956e-01 4.77687299e-01 -3.89769584e-01
9.39408898e-01 -1.92111749e-02 -5.32549918e-01 -6.91087604e-01
4.37232591e-02 3.27354699e-01 6.62776947e-01 -1.01944685e+00
-4.69312161e-01 -9.58255157e-02 -1.17763869e-01 8.11918378e-02
6.17588580e-01 3.51036400e-01 -1.62486322e-02 -5.97664237e-01
-2.39248037e-01 -7.57495821e-01 -8.43699992e-01 -1.86446086e-01
-5.32127321e-01 1.71321481e-01 5.55200458e-01 -4.23319995e-01
1.30457926e+00 -1.47484708e+00 -1.88286617e-01 6.79069519e-01
-4.80841756e-01 -2.69119442e-01 5.66285253e-01 8.85308146e-01
1.24941915e-02 2.88855612e-01 -8.12282145e-01 -2.85975903e-01
8.56963277e-01 1.86378688e-01 -1.80836141e-01 3.40484232e-01
1.99080318e-01 5.06822228e-01 -7.92456985e-01 -4.65128154e-01
9.33728695e-01 1.52638853e-01 -3.71144325e-01 6.48179203e-02
-4.78841811e-01 5.03126979e-01 -4.29445386e-01 8.56601655e-01
8.83190095e-01 1.87550649e-01 3.21750820e-01 1.24186583e-01
-5.10661006e-01 3.85066688e-01 -2.05708241e+00 1.62377155e+00
-7.63421953e-01 1.35733560e-01 3.24399948e-01 -7.33257294e-01
5.39774895e-01 2.13159725e-01 4.57324356e-01 -1.00808613e-01
4.60191309e-01 2.03155562e-01 -1.51942015e-01 -3.39246362e-01
1.12438306e-01 -2.83310801e-01 -5.20209968e-01 7.99814701e-01
5.28784841e-02 -1.01894605e+00 7.71414563e-02 -2.55872458e-01
9.91332233e-01 5.31202257e-01 7.74111927e-01 -6.71798170e-01
-7.80492052e-02 6.03042506e-02 6.29912913e-01 8.27732146e-01
-7.21751340e-03 3.55476171e-01 2.12736085e-01 -3.30802917e-01
-9.45047915e-01 -1.34083426e+00 -9.62367058e-01 7.65851319e-01
-2.11819649e-01 -2.92496413e-01 -3.78673762e-01 -1.00930773e-01
7.09327936e-01 1.36355698e+00 -4.07375067e-01 9.02502462e-02
7.43250996e-02 -1.30050373e+00 1.91706896e-01 5.07321954e-01
3.76811981e-01 -6.87931061e-01 -7.04761922e-01 5.35308063e-01
6.06590211e-01 -6.44857168e-01 1.44539639e-01 4.18190688e-01
-6.38954103e-01 -6.14892423e-01 -1.25177145e-01 3.67286801e-01
-3.71690542e-02 -7.14480996e-01 1.33105576e+00 -5.11114657e-01
-4.83551115e-01 4.37202841e-01 1.16525374e-01 -8.52886260e-01
-6.14585519e-01 -4.92198616e-01 2.72036463e-01 -5.35627007e-01
3.47782224e-02 -8.56278896e-01 -2.55714327e-01 5.02308249e-01
-7.78968811e-01 -1.10203259e-01 2.38732070e-01 4.39641416e-01
4.63849992e-01 1.22548930e-01 4.00248706e-01 -5.08351505e-01
9.71156418e-01 -7.59618402e-01 -1.33542085e+00 1.00155704e-01
-1.03211772e+00 3.58744204e-01 1.25486836e-01 -9.17690620e-03
-1.10185349e+00 5.28390147e-02 -3.00578296e-01 -1.38997987e-01
-2.18553349e-01 1.00564945e+00 -2.38568202e-01 -6.70035630e-02
6.30634248e-01 -5.44807673e-01 -1.81422979e-01 -4.17689502e-01
4.79781091e-01 7.13298738e-01 1.65531382e-01 -1.02550066e+00
5.83344460e-01 1.07947782e-01 7.27512911e-02 -1.79114386e-01
-1.19510405e-01 1.18707709e-01 -3.55647445e-01 -3.34594041e-01
4.17906940e-01 -7.36123383e-01 -8.78908098e-01 3.96941602e-01
-5.17035604e-01 -7.70094991e-01 -3.05026650e-01 5.99066854e-01
-5.41306913e-01 -2.55566575e-02 -1.29551426e-01 -1.21451414e+00
-1.33570656e-01 -1.37796831e+00 7.59767234e-01 2.63684958e-01
-5.92497408e-01 -1.02155149e+00 4.14729863e-01 -1.81165993e-01
8.91936600e-01 6.23725235e-01 6.94141865e-01 -3.00810009e-01
-4.70842153e-01 -2.45960996e-01 2.11739436e-01 2.25877692e-03
-2.62960553e-01 6.02938235e-01 -1.14307714e+00 -1.30769715e-01
-1.81171671e-01 -1.91120952e-01 4.92783993e-01 7.06835508e-01
1.01511168e+00 -1.51753858e-01 -4.99677360e-01 4.65735972e-01
1.21483505e+00 1.63031623e-01 4.15904671e-01 5.00108480e-01
-1.20158464e-01 5.66650271e-01 7.64639616e-01 9.61259305e-01
6.01725459e-01 8.65345538e-01 5.79854429e-01 1.99889332e-01
6.54772878e-01 1.59231588e-01 2.71527857e-01 1.62890702e-01
2.71363527e-01 -3.93066630e-02 -1.39471841e+00 2.67682821e-01
-2.08518720e+00 -7.02498555e-01 1.84642561e-02 2.29395223e+00
9.86920655e-01 2.52662182e-01 -1.86034396e-01 -7.24333674e-02
3.31633627e-01 -2.40554601e-01 -8.03120852e-01 -8.94226909e-01
3.35415900e-01 1.90867484e-01 5.69086373e-01 6.80111647e-01
-1.20693076e+00 4.22215641e-01 8.06053162e+00 9.33725834e-01
-8.20348978e-01 1.07359737e-01 6.41685724e-01 -2.19060853e-01
-3.96708846e-01 3.24686944e-01 -6.95043266e-01 4.68620270e-01
1.13355148e+00 -5.47253609e-01 3.07599217e-01 8.63402963e-01
5.47081470e-01 -6.39660478e-01 -1.15344000e+00 6.01135731e-01
-6.89304411e-01 -1.42517424e+00 -5.74237943e-01 -1.32428139e-01
7.45636165e-01 2.94354647e-01 -2.15994176e-02 5.65838635e-01
1.40843546e+00 -1.37117553e+00 7.50123501e-01 7.54085362e-01
5.00655651e-01 -9.30423677e-01 9.04037297e-01 3.43632013e-01
-6.58735156e-01 -1.76915005e-01 6.49253875e-02 -2.52410531e-01
4.60043371e-01 1.12511313e+00 -9.37006950e-01 8.10470164e-01
1.05556977e+00 2.74026453e-01 -3.32184911e-01 1.42822468e+00
-1.71769306e-01 4.69878465e-01 -1.09940863e+00 6.37812838e-02
-6.26244992e-02 -1.36760771e-01 6.01328611e-01 1.28200471e+00
4.10450757e-01 -1.54363245e-01 3.02361816e-01 1.12568986e+00
6.45645678e-01 -3.37011874e-01 -4.06454802e-01 4.22728568e-01
6.04342163e-01 1.11752927e+00 -3.15254420e-01 -2.13480387e-02
5.07572107e-02 7.28259012e-02 -3.29669684e-01 2.54924357e-01
-8.76855314e-01 -3.27864915e-01 9.59085107e-01 -3.24756163e-03
4.17105183e-02 -3.38781863e-01 -4.62324530e-01 -7.80199170e-01
-2.78808653e-01 -9.76193070e-01 4.98801053e-01 -1.13920450e+00
-1.31112373e+00 1.26247808e-01 7.78587699e-01 -1.07417512e+00
-8.82505059e-01 -6.24117613e-01 -7.79726863e-01 1.19418406e+00
-1.15384567e+00 -7.79428005e-01 -2.71224836e-03 3.66251975e-01
3.68849970e-02 -7.71989152e-02 1.02619946e+00 1.73004061e-01
-6.31143451e-01 4.22943234e-02 3.58408600e-01 -4.61199790e-01
7.34420419e-01 -1.50828278e+00 4.17035252e-01 7.18716264e-01
-5.26177227e-01 6.77418947e-01 1.28496420e+00 -6.53262794e-01
-1.32576180e+00 -8.91606152e-01 2.51532812e-02 -7.02385843e-01
9.21691835e-01 -1.97511911e-01 -3.70019376e-01 5.30500770e-01
3.20372403e-01 -1.45028904e-01 6.48919404e-01 2.52898067e-01
8.93080831e-02 -2.39838302e-01 -1.58965993e+00 6.04794264e-01
2.73790419e-01 -2.63327777e-01 -5.29061437e-01 1.51485026e-01
2.39645213e-01 -6.30464852e-01 -1.23859644e+00 7.92844236e-01
7.22404301e-01 -1.04606473e+00 9.63788271e-01 -2.99457818e-01
-8.45155418e-02 -8.68442714e-01 -2.02479854e-01 -1.58294129e+00
1.23444512e-01 -1.06078625e+00 -3.43658119e-01 1.30573642e+00
6.76620841e-01 -8.80561292e-01 1.87221438e-01 1.15323031e+00
-1.92247882e-01 -6.49649978e-01 -1.13148379e+00 -6.96288586e-01
3.74904424e-01 -1.22574806e+00 1.12209547e+00 8.25051010e-01
1.07012652e-01 -3.26244384e-01 -9.22648236e-02 3.52290571e-01
8.37235510e-01 1.13072596e-01 6.46825910e-01 -1.13608301e+00
-5.78902543e-01 -5.99312365e-01 -2.24316090e-01 -2.93459862e-01
-3.36482733e-01 -5.16453922e-01 1.37727350e-01 -1.43849134e+00
-1.44688681e-01 -9.16495621e-01 -2.98956126e-01 4.64313000e-01
1.28473356e-01 -3.01660568e-01 -1.00978151e-01 -1.31560326e-01
-1.54819444e-01 5.18585861e-01 5.14363229e-01 -1.89785644e-01
-2.17874616e-01 4.31390941e-01 -6.31173193e-01 8.50932419e-01
8.85637581e-01 -7.03864515e-01 -1.67488903e-01 -1.40918925e-01
5.66798329e-01 5.72298691e-02 5.02522528e-01 -1.31489289e+00
1.93795860e-01 -6.61617875e-01 5.52780211e-01 -7.28555799e-01
1.70386344e-01 -7.19550550e-01 8.33735347e-01 2.75051296e-01
-9.84335504e-03 1.18660629e-01 8.54349256e-01 3.53093684e-01
7.52834454e-02 -3.77246082e-01 6.96201921e-01 3.11847217e-02
-6.19547129e-01 8.36702660e-02 -9.98491168e-01 -2.82614380e-01
1.13965654e+00 2.58777589e-01 -1.82899863e-01 -4.62847859e-01
-9.43278491e-01 8.86860132e-01 6.05563045e-01 1.60177916e-01
1.51979506e-01 -1.10236859e+00 -6.99812770e-01 -1.95274055e-01
-2.43052579e-02 -1.68570541e-02 -2.44581373e-03 6.01753294e-01
-4.34606433e-01 2.12777734e-01 -5.01176668e-03 -6.12893403e-01
-5.41745365e-01 4.73852038e-01 8.83173108e-01 -4.17625010e-01
-6.97175860e-02 5.39776921e-01 -5.02671838e-01 -9.71749544e-01
-8.63134265e-02 -6.57988548e-01 2.48895228e-01 3.03709898e-02
5.42555332e-01 4.52416599e-01 4.69573349e-01 1.49843305e-01
-5.61976194e-01 4.44272608e-01 4.74919647e-01 -6.69685304e-01
1.21278930e+00 -9.26654786e-02 7.85740167e-02 5.77119350e-01
3.39774370e-01 -2.00700060e-01 -1.50600922e+00 1.81436524e-01
2.41591141e-01 -3.04576844e-01 5.04598916e-01 -1.48404574e+00
-5.51846802e-01 7.44847357e-01 7.60402620e-01 1.24460377e-01
9.49307263e-01 -4.13495183e-01 -5.84684275e-02 5.62963545e-01
6.74859703e-01 -1.32005322e+00 -7.95214176e-01 4.15574014e-01
1.15814435e+00 -1.10349488e+00 6.27438128e-01 2.50407914e-03
-6.07035339e-01 9.89539564e-01 1.37588114e-01 5.32230269e-03
1.33777368e+00 9.81239855e-01 1.30555540e-01 9.58825499e-02
-9.60545778e-01 -2.13005662e-01 -3.32859196e-02 7.66398132e-01
1.65084228e-01 1.38624340e-01 9.19749141e-02 7.96561420e-01
-1.93768635e-01 2.23992363e-01 3.44087332e-01 1.24275529e+00
-1.70274973e-01 -1.28362679e+00 -9.77232218e-01 6.09589219e-01
-3.28092039e-01 -8.80565345e-02 1.20495565e-01 7.58270204e-01
1.96180288e-02 1.17684674e+00 -1.87106892e-01 -2.35054672e-01
2.96249211e-01 -8.53996724e-03 4.17303175e-01 -5.13207376e-01
-7.53030896e-01 -3.45682092e-02 5.25886893e-01 -7.83133507e-01
1.13935128e-01 -1.06987607e+00 -1.05061829e+00 -5.51084578e-01
-2.36740131e-02 1.28295526e-01 1.11897016e+00 9.47381616e-01
3.80243570e-01 6.14818633e-01 3.04607183e-01 -1.26843750e+00
-8.76751184e-01 -1.04966974e+00 -6.14091456e-01 -5.27822971e-01
2.20905412e-02 -1.03581619e+00 -4.96691585e-01 -3.88788253e-01] | [6.15205717086792, 3.66279935836792] |
dfe4aff7-646f-42f8-a9bb-492292057879 | orthogonal-subspace-decomposition-a-new | null | null | https://openreview.net/forum?id=sr68jSUakP | https://openreview.net/pdf?id=sr68jSUakP | Orthogonal Subspace Decomposition: A New Perspective of Learning Discriminative Features for Face Clustering | Face clustering is an important task, due to its wide applications in practice. Graph-based face clustering methods have recently made a great progress and achieved new state-of-the-art results. Learning discriminative node features is the key to further improve the performance of graph-based face clustering. To this end, most previous methods focus on new loss functions, such as margin-based or center loss. In this paper, we propose subspace learning as a new way to learn discriminative node features, which is implemented by a new orthogonal subspace decomposition (OSD) module. In graph-based face clustering, OSD leads to more discriminative node features, which better reflect the relationship between each pair of faces, thereby boosting the accuracy of face clustering. Extensive experiments show that OSD outperforms state-of-the-art results with a healthy margin. | ['Zhongchao shi', 'Thomas Lukasiewicz', 'JianFeng Wang'] | 2021-01-01 | null | null | null | null | ['face-clustering'] | ['computer-vision'] | [-3.51645231e-01 -3.15895855e-01 -3.12243164e-01 -3.93688709e-01
-2.95821697e-01 -1.39617130e-01 5.04373908e-01 -8.25075582e-02
4.15275656e-02 1.19621724e-01 2.18866378e-01 1.91102132e-01
-2.61526525e-01 -5.71457148e-01 -1.93429977e-01 -1.03114188e+00
-7.34084323e-02 3.41697276e-01 1.35912746e-01 1.23426877e-01
1.89542454e-02 6.49582446e-01 -1.51442730e+00 -8.09201226e-02
7.85436809e-01 8.22949588e-01 -1.05901182e-01 -7.64196813e-02
-1.29413724e-01 2.15569526e-01 -9.90138873e-02 -3.40030730e-01
8.66249055e-02 -4.87767845e-01 -3.92850041e-01 3.48105162e-01
2.83306926e-01 1.35055184e-01 -5.98932505e-01 1.10263824e+00
5.27377427e-01 1.95144117e-01 7.55820572e-01 -1.59986711e+00
-3.77039105e-01 2.71402866e-01 -9.61068451e-01 -2.44557813e-01
2.79685646e-01 -2.02448159e-01 8.36281180e-01 -9.75070715e-01
3.87465358e-01 1.75177062e+00 6.18194878e-01 6.76848710e-01
-1.30546153e+00 -9.30666864e-01 2.63578117e-01 6.48925483e-01
-1.82955587e+00 -5.65092087e-01 1.24555516e+00 -4.57181424e-01
2.39112988e-01 1.61558077e-01 5.75071633e-01 6.62297726e-01
-1.76402152e-01 8.10273290e-01 9.93089914e-01 -2.71602482e-01
2.52371758e-01 -1.01598158e-01 -4.89801839e-02 8.70602131e-01
3.17785323e-01 -2.65783012e-01 -4.77228224e-01 -2.57413834e-01
6.59589350e-01 4.16239470e-01 -3.82749438e-01 -9.50194120e-01
-5.87416768e-01 9.41291511e-01 5.63813984e-01 4.83343601e-01
-1.83170021e-01 1.24536548e-03 2.81300992e-01 -2.33274430e-01
5.54244637e-01 -2.53481865e-01 4.55045477e-02 1.94204688e-01
-1.01425660e+00 -5.21041863e-02 5.31862497e-01 5.21289885e-01
8.99209857e-01 -2.23641068e-01 -1.77372813e-01 9.50421512e-01
8.24309826e-01 3.90637577e-01 2.78471231e-01 -8.81787658e-01
1.21145323e-02 1.04016912e+00 -5.06648004e-01 -1.38086569e+00
-4.17210132e-01 -4.60960448e-01 -1.20615244e+00 3.17901410e-02
1.55563414e-01 1.26600653e-01 -7.51537442e-01 1.69561946e+00
7.17656732e-01 6.58260226e-01 -2.08784401e-01 7.89156377e-01
7.48869300e-01 4.74894524e-01 -1.36452481e-01 -5.52440763e-01
1.17292058e+00 -7.23707199e-01 -7.28508115e-01 6.24337122e-02
4.46088284e-01 -6.91605508e-01 7.46062338e-01 2.75546044e-01
-4.42446083e-01 -6.06149316e-01 -6.83473289e-01 4.48883682e-01
3.49680558e-02 7.22532049e-02 6.38022184e-01 8.60835016e-01
-1.08577943e+00 4.27710503e-01 -9.62718189e-01 -4.80054975e-01
6.53852224e-01 5.13598621e-01 -6.25316620e-01 -5.31605661e-01
-7.04810441e-01 2.40748882e-01 1.22188300e-01 6.82304949e-02
-6.35318816e-01 -4.56386417e-01 -9.64264631e-01 1.38231948e-01
6.74491227e-01 -4.54942018e-01 6.17382705e-01 -4.13954884e-01
-1.35612154e+00 8.28278840e-01 -4.88104343e-01 1.03574641e-01
1.65958941e-01 8.17914605e-02 -4.44725126e-01 2.34950408e-01
8.04074481e-02 4.64725584e-01 1.20107174e+00 -1.52847719e+00
-2.20070139e-01 -1.02262735e+00 -5.45535445e-01 -1.25068668e-02
-9.64962065e-01 1.38689775e-03 -1.02348423e+00 -5.00408292e-01
4.51668918e-01 -1.04068017e+00 -2.14440539e-01 -7.41157383e-02
-4.01679724e-01 -8.96651328e-01 1.23883832e+00 -4.81488794e-01
1.41349626e+00 -2.39437580e+00 3.30135882e-01 4.34749514e-01
4.60500211e-01 3.54062527e-01 -3.25498059e-02 2.79953420e-01
-2.62914598e-02 -2.02036984e-02 -3.51515204e-01 -6.01377070e-01
-1.27163962e-01 9.98027921e-02 2.29928225e-01 6.98480308e-01
1.03559028e-02 5.08801877e-01 -7.24980235e-01 -6.79140866e-01
2.81956673e-01 7.41471887e-01 -5.86858571e-01 1.44672766e-01
8.11149329e-02 5.38869083e-01 -4.81706858e-01 4.82694745e-01
1.00591254e+00 -2.04096109e-01 5.23496389e-01 -2.41367161e-01
1.94857433e-01 -4.95241642e-01 -1.39558125e+00 1.64183760e+00
-1.19658433e-01 3.47274274e-01 3.95355046e-01 -1.16040182e+00
9.68405068e-01 2.65028000e-01 7.14122117e-01 -1.45116568e-01
1.31000385e-01 -3.62803452e-02 -1.38064146e-01 -3.08689743e-01
-2.12861702e-01 4.62315790e-02 3.46368253e-01 2.19740272e-01
2.70998273e-02 2.68888354e-01 1.55932486e-01 3.61178130e-01
8.66254747e-01 -1.88359454e-01 1.28180489e-01 -2.94099480e-01
1.08413970e+00 -6.30388916e-01 9.53800142e-01 -1.06924258e-01
-2.09507257e-01 4.39418465e-01 5.35245895e-01 -7.66855553e-02
-4.11063284e-01 -7.84951866e-01 -1.64078891e-01 7.35059679e-01
2.55016834e-01 -7.58172989e-01 -1.06383502e+00 -1.00199914e+00
1.90166250e-01 1.71804816e-01 -6.21492922e-01 -2.84939677e-01
-5.63232303e-01 -6.53419375e-01 1.21358067e-01 4.91987556e-01
5.27838945e-01 -6.66770637e-01 2.15645462e-01 -6.62581250e-02
-1.04044557e-01 -1.09708035e+00 -6.73429489e-01 -3.63921821e-01
-1.04377520e+00 -1.19826162e+00 -8.23587060e-01 -8.79767835e-01
1.04425824e+00 6.82159483e-01 7.42784142e-01 3.80959272e-01
-3.77016753e-01 5.62252879e-01 -4.48510915e-01 5.65275475e-02
4.25196886e-02 -1.38675412e-02 3.76012802e-01 7.03096628e-01
4.92718875e-01 -6.20887697e-01 -6.55014396e-01 5.11533201e-01
-8.20972919e-01 -4.28039283e-01 6.50437772e-01 7.35366166e-01
6.10904038e-01 4.04344171e-01 3.90454024e-01 -8.44098628e-01
3.94045472e-01 -3.83351058e-01 -4.98943269e-01 2.83684820e-01
-7.42181301e-01 5.10777868e-02 7.50881970e-01 -3.37639712e-02
-9.50288236e-01 3.27766329e-01 9.58202779e-02 -8.92788351e-01
-2.65522182e-01 3.55543852e-01 -7.99729645e-01 -3.23806763e-01
2.68691689e-01 2.69121021e-01 2.39987791e-01 -7.06069112e-01
3.61805558e-01 6.43282115e-01 2.72919029e-01 -4.23129141e-01
1.10858512e+00 6.03499711e-01 4.24409926e-01 -9.85718787e-01
-4.52780694e-01 -8.80015910e-01 -8.56782198e-01 -4.08288181e-01
7.57972538e-01 -8.44817579e-01 -8.69639695e-01 4.61852223e-01
-7.82914639e-01 2.93011665e-02 3.48540574e-01 5.31960368e-01
-2.16190338e-01 8.47359538e-01 -3.40129256e-01 -8.52262676e-01
-6.90599978e-02 -1.14590549e+00 9.12804306e-01 4.03908223e-01
2.79798806e-01 -9.74585056e-01 5.24797104e-02 4.28929776e-01
-2.87254732e-02 1.17024317e-01 8.45017731e-01 -4.35685277e-01
-4.32000160e-01 -1.87705532e-01 -2.52199650e-01 3.18801612e-01
2.72282869e-01 9.06236842e-02 -8.26198995e-01 -7.26426005e-01
-3.64895202e-02 1.90073289e-02 1.04806972e+00 3.90523225e-01
1.28362358e+00 -2.75802054e-02 -8.50049734e-01 6.70137882e-01
1.25198364e+00 3.29179615e-02 4.50066566e-01 -2.24356309e-01
9.74424303e-01 7.12073565e-01 5.49399436e-01 5.19744992e-01
3.07657003e-01 9.01161015e-01 4.65582460e-01 -3.84016335e-02
-2.18098000e-01 -2.10585222e-01 3.21677476e-01 7.79966652e-01
9.35860269e-04 8.33730623e-02 -8.98788273e-01 3.15144658e-01
-2.11582470e+00 -8.53836238e-01 -1.72677726e-01 2.23748899e+00
4.02380139e-01 -2.74580061e-01 4.53848630e-01 2.62433529e-01
1.15517795e+00 2.73528069e-01 -5.03593326e-01 3.37232530e-01
2.11360574e-01 -1.73212476e-02 -7.72230625e-02 2.27775052e-01
-1.15310788e+00 1.06314051e+00 5.44166231e+00 1.19843066e+00
-9.24222171e-01 5.00762276e-02 6.09158933e-01 2.57921815e-01
-2.10941896e-01 -6.68363199e-02 -9.28449392e-01 5.12626350e-01
3.50061089e-01 -3.06086875e-02 4.34000701e-01 9.69872892e-01
2.49943987e-01 1.86682552e-01 -1.02830851e+00 1.51753294e+00
4.53459710e-01 -9.65418100e-01 3.15061957e-02 3.87386173e-01
8.05527389e-01 -5.59947431e-01 1.95413753e-01 1.29359037e-01
-2.31473818e-02 -9.95602310e-01 -8.88393372e-02 2.44391501e-01
7.61914432e-01 -1.06099725e+00 6.37823522e-01 1.68757424e-01
-1.62515998e+00 -1.89953372e-02 -5.16384780e-01 2.30288476e-01
-1.03658743e-01 9.88750160e-01 -5.10877192e-01 7.14964211e-01
7.41644442e-01 1.06737292e+00 -6.47063851e-01 1.11682510e+00
-3.39680314e-01 7.67068863e-01 -2.34193370e-01 1.14228845e-01
-4.60712649e-02 -5.80138803e-01 4.51129496e-01 8.53874326e-01
1.90373406e-01 1.53383479e-01 4.18655843e-01 5.91257095e-01
-3.52462441e-01 4.06712919e-01 -6.19830966e-01 1.17039017e-01
5.95958292e-01 1.73077750e+00 -9.58419681e-01 4.74237315e-02
-5.58110833e-01 8.73266041e-01 3.74628067e-01 1.96586996e-01
-5.57005823e-01 -1.72914341e-01 8.11903000e-01 1.88240230e-01
4.25472885e-01 -3.74613732e-01 1.27058432e-01 -1.10205984e+00
3.18128988e-02 -7.13584900e-01 4.91853684e-01 1.61178652e-02
-1.32122445e+00 2.15938345e-01 -2.65772164e-01 -1.13008678e+00
-4.79337797e-02 -5.17856181e-01 -7.75331140e-01 4.64289635e-01
-1.19478166e+00 -1.15247822e+00 -5.78342736e-01 8.72868061e-01
2.35632107e-01 -4.30191845e-01 6.94453061e-01 4.28565890e-01
-1.02122700e+00 7.55188704e-01 3.96609932e-01 3.85239810e-01
8.86157036e-01 -8.86171043e-01 -2.40922496e-01 8.25027108e-01
4.15524483e-01 6.25159562e-01 2.86663771e-01 -5.09298146e-01
-1.61119473e+00 -1.11445272e+00 3.46970558e-01 -1.07908286e-01
2.38300294e-01 -3.34185928e-01 -8.72424662e-01 3.24148595e-01
-7.54768401e-02 1.83967307e-01 1.06471789e+00 4.27375615e-01
-5.03230572e-01 -6.45862818e-01 -1.09267485e+00 4.51782405e-01
1.15257049e+00 -4.75497603e-01 -5.88537268e-02 2.94662029e-01
3.57619226e-01 3.09054822e-01 -8.76266003e-01 6.03218198e-01
3.40459168e-01 -1.09225309e+00 8.86861742e-01 -2.28430778e-01
-9.33719352e-02 -6.51042283e-01 5.44246659e-02 -1.34948182e+00
-6.27291143e-01 -4.61190343e-01 -4.15457070e-01 1.67098713e+00
-1.52719185e-01 -5.30663252e-01 1.09523618e+00 2.43250698e-01
9.92900059e-02 -8.50257993e-01 -9.41696644e-01 -8.76518369e-01
-2.10481122e-01 -1.08324274e-01 5.08532882e-01 1.01889992e+00
-2.84133176e-03 4.41422671e-01 -2.17272103e-01 9.32002887e-02
1.03524053e+00 2.54943579e-01 8.29297423e-01 -1.72562075e+00
9.60615724e-02 -5.61275780e-01 -9.12472904e-01 -8.41081500e-01
6.68171763e-01 -1.01108718e+00 -2.09903598e-01 -1.50317478e+00
6.16116583e-01 -3.21006060e-01 -3.18224192e-01 3.39148939e-01
-5.27177632e-01 3.69447470e-01 2.64421672e-01 2.72732913e-01
-8.23538363e-01 9.64796185e-01 1.05443656e+00 -1.37950450e-01
-1.38045192e-01 6.18173033e-02 -7.12817192e-01 7.08771586e-01
6.76299274e-01 -3.06481153e-01 -2.85421759e-01 -8.36407617e-02
-5.75211048e-01 -1.98028296e-01 1.43606201e-01 -1.23859680e+00
4.24835026e-01 8.85051861e-02 6.06549442e-01 -4.93213505e-01
4.07059252e-01 -9.72227037e-01 2.59591471e-02 6.31807268e-01
2.09616229e-01 -3.67102623e-01 -1.16795145e-01 9.76837814e-01
-4.53994393e-01 6.64854869e-02 9.28160727e-01 1.46510273e-01
-7.25218713e-01 7.72519290e-01 8.91790763e-02 -1.68034047e-01
1.32328331e+00 -8.48369002e-02 1.85010478e-01 -3.83262277e-01
-7.30990708e-01 3.33153218e-01 5.05783796e-01 3.81206572e-01
7.54271030e-01 -1.52484739e+00 -7.61806369e-01 3.32006782e-01
9.85087007e-02 -1.95132807e-01 3.32104832e-01 8.89440358e-01
-5.92192821e-02 3.79098684e-01 1.09249890e-01 -8.52008045e-01
-1.70564723e+00 7.45178401e-01 -2.83410773e-02 -9.52608883e-02
-3.44983578e-01 8.22062314e-01 3.29441309e-01 -4.52637434e-01
2.85969496e-01 5.71795583e-01 -4.95208114e-01 1.81343734e-01
3.85085911e-01 6.76776707e-01 -4.63956669e-02 -9.21642900e-01
-6.58278584e-01 1.08579123e+00 4.46251333e-02 2.61100411e-01
1.24730790e+00 4.36380273e-03 -4.52765793e-01 3.54435183e-02
1.36790502e+00 9.55385119e-02 -1.03924847e+00 -3.33285213e-01
2.78690271e-03 -8.00511956e-01 1.04326673e-01 -7.34564513e-02
-1.51810181e+00 1.01375198e+00 7.61852026e-01 3.13756280e-02
1.21559358e+00 2.16819406e-01 6.64700925e-01 1.26306668e-01
5.19783199e-01 -8.85248542e-01 3.93185467e-01 1.62280113e-01
5.51123142e-01 -1.34124541e+00 1.21441558e-01 -9.61876571e-01
-1.87795475e-01 1.08742785e+00 8.06169391e-01 6.72655255e-02
1.06330943e+00 -1.54718027e-01 -1.66739777e-01 -1.61967888e-01
-2.57710248e-01 -3.38685185e-01 4.49990362e-01 6.13877535e-01
5.56237638e-01 1.97377503e-01 -3.44441146e-01 4.74523336e-01
2.81650275e-01 -3.65984797e-01 -3.08506429e-01 4.19073969e-01
-3.84128481e-01 -1.50363576e+00 -5.87510526e-01 4.69431967e-01
-1.76927313e-01 2.53351629e-01 -4.73333567e-01 4.89073455e-01
-2.09394526e-02 1.21053553e+00 -1.95181057e-01 -5.83858073e-01
6.48545995e-02 4.19857316e-02 4.87921238e-01 -6.11943543e-01
5.73193320e-05 2.88208187e-01 -5.71867645e-01 -6.47393286e-01
-5.46616256e-01 -8.33142698e-01 -1.26382756e+00 -4.72797245e-01
-4.89810139e-01 4.63259488e-01 4.54405934e-01 6.49362803e-01
6.04226530e-01 2.38604710e-01 1.11348951e+00 -8.88211429e-01
-3.07580382e-01 -7.25850999e-01 -8.33745599e-01 5.46452522e-01
-2.32071623e-01 -9.05758500e-01 -2.80566454e-01 -1.37784749e-01] | [13.468725204467773, 1.0762628316879272] |
efb4f6d5-6504-430a-bed3-f255c2d07b08 | hand-gesture-recognition-of-dumb-person-using | 2201.12622 | null | https://arxiv.org/abs/2201.12622v1 | https://arxiv.org/pdf/2201.12622v1.pdf | Hand Gesture Recognition of Dumb Person Using one Against All Neural Network | We propose a new technique for recognition of dumb person hand gesture in real world environment. In this technique, the hand image containing the gesture is preprocessed and then hand region is segmented by convergent the RGB color image to L.a.b color space. Only few statistical features are used to classify the segmented image to different classes. Artificial Neural Network is trained in sequential manner using one against all. When the system gets trained, it becomes capable of recognition of each class in parallel manner. The result of proposed technique is much better than existing techniques. | ['Sajjad Ahmed', 'Lan Hong', 'Muhammad Asim Khan'] | 2022-01-29 | null | null | null | null | ['gesture-recognition'] | ['computer-vision'] | [ 3.74973625e-01 -7.36219764e-01 -4.17543799e-01 -4.66493428e-01
-2.02261768e-02 -9.34352398e-01 3.53388578e-01 -3.82270813e-01
-8.84572566e-01 6.34984255e-01 -3.04739505e-01 -3.57094020e-01
2.07931057e-01 -7.37070560e-01 -4.93077450e-02 -8.68013322e-01
3.57186288e-01 5.88868380e-01 4.09821689e-01 1.79080665e-01
3.82815033e-01 8.60829830e-01 -1.36245573e+00 2.35573858e-01
-1.36022586e-02 7.58228421e-01 1.64290920e-01 1.39224219e+00
-2.27315128e-01 6.62384808e-01 -6.63777828e-01 2.74030536e-01
7.56703556e-01 -7.75887549e-01 -1.07843983e+00 1.84990332e-01
3.54659446e-02 -4.23838973e-01 -2.67515689e-01 1.04488230e+00
4.88859296e-01 5.19676864e-01 9.69548404e-01 -9.22846854e-01
-2.31541246e-01 1.40423894e-01 -9.39887464e-01 5.60180485e-01
5.58023810e-01 1.01408727e-01 5.90365410e-01 -7.36699581e-01
5.09097695e-01 1.15249348e+00 1.52753457e-01 6.81888819e-01
-8.31014931e-01 -7.81728268e-01 -9.76411775e-02 2.03174353e-01
-1.34667873e+00 2.20024049e-01 7.67813444e-01 -2.30833486e-01
9.78890002e-01 5.15317500e-01 7.74343133e-01 4.76920873e-01
-1.25128642e-01 9.31220651e-01 1.69117415e+00 -6.81359589e-01
9.60454717e-02 -3.18143703e-02 8.65587592e-01 7.30780005e-01
1.06842980e-01 2.25456238e-01 -2.40440205e-01 1.75632790e-01
6.59277022e-01 4.57255840e-01 -1.30650429e-02 2.44083375e-01
-1.10280073e+00 1.09454542e-01 4.45410788e-01 7.13545084e-01
-5.11840463e-01 -1.96159214e-01 1.97143659e-01 2.42145345e-01
-6.09238803e-01 -8.19240883e-02 -3.42819601e-01 -1.65083468e-01
-1.14993513e+00 -6.36747200e-03 8.07173789e-01 6.98511064e-01
2.97858626e-01 -2.04996705e-01 2.31667697e-01 6.06176674e-01
4.39439148e-01 8.91049862e-01 5.31994224e-01 -3.77630413e-01
2.64227390e-01 7.30375707e-01 1.32079735e-01 -5.38184881e-01
-5.86090326e-01 3.59212101e-01 -4.86855954e-01 9.53296065e-01
9.02726710e-01 -2.94625193e-01 -1.65833759e+00 7.30083108e-01
4.55647439e-01 -1.61475420e-01 4.03702796e-01 1.21757102e+00
7.54441798e-01 9.10108745e-01 2.42955789e-01 2.67012487e-03
1.42236960e+00 -6.06670737e-01 -4.85077143e-01 8.87680352e-02
-4.44450587e-01 -9.51945484e-01 1.03856790e+00 9.73088205e-01
-6.93038046e-01 -6.17979228e-01 -1.02158535e+00 2.18373522e-01
-4.80714291e-01 2.53906220e-01 6.17052317e-01 1.05417418e+00
-7.13702679e-01 2.33709574e-01 -1.00204074e+00 -7.64689088e-01
1.97308078e-01 7.83195913e-01 -2.78485209e-01 1.17583126e-01
-5.44176459e-01 6.19372606e-01 8.78224015e-01 4.84295696e-01
-3.99951547e-01 5.97478926e-01 -2.72801727e-01 -5.44771314e-01
-1.79610457e-02 1.72425047e-01 9.11162555e-01 -1.46410918e+00
-1.84517121e+00 7.80462205e-01 -3.99043798e-01 2.31544599e-01
4.99902517e-01 1.69579417e-01 -2.78012991e-01 2.64820486e-01
-4.57169026e-01 2.67170340e-01 1.05067301e+00 -1.19826841e+00
-1.04765415e+00 -6.99968219e-01 -2.49152809e-01 5.19656539e-01
1.08164862e-01 5.36807120e-01 -4.25856352e-01 -4.03974354e-01
5.30727863e-01 -7.77837634e-01 1.97761536e-01 -4.81128305e-01
-4.35061902e-01 -4.10236180e-01 1.18961513e+00 -8.12811732e-01
7.49925435e-01 -2.01774526e+00 3.63592505e-02 8.66723835e-01
-2.97682256e-01 5.07119060e-01 1.30167469e-01 1.22536778e-01
1.40036464e-01 -1.88209787e-01 -3.85535471e-02 4.54335868e-01
-4.50685143e-01 3.83597195e-01 1.19244695e-01 4.53040689e-01
-2.58428723e-01 4.36771005e-01 -6.63199723e-01 -8.78634155e-01
3.49456459e-01 4.42573726e-01 -1.55273527e-02 2.82675236e-01
2.88568467e-01 7.40723073e-01 -6.34298623e-01 1.13226950e+00
7.30861783e-01 2.04028502e-01 2.96205163e-01 -8.36917832e-02
-1.08889170e-01 -4.32970971e-01 -1.52804542e+00 9.87484038e-01
-1.53133065e-01 7.25757420e-01 -1.93162382e-01 -8.72521758e-01
8.17230105e-01 5.85636735e-01 1.64272249e-01 -3.01591903e-01
6.81851566e-01 9.55843031e-02 1.48775041e-01 -1.01006854e+00
1.38454631e-01 -2.99600333e-01 3.20002228e-01 1.01710725e+00
-1.71584189e-01 2.21283183e-01 1.71085402e-01 -4.20635879e-01
7.49839425e-01 3.40730160e-01 4.59896743e-01 1.88250631e-01
5.86575031e-01 4.73099470e-01 1.42767802e-01 8.44699323e-01
-6.35521829e-01 3.45852524e-01 -2.11932629e-01 -4.59666669e-01
-8.80372703e-01 -1.11902797e+00 3.18318754e-02 1.27738667e+00
2.65151858e-01 8.27446401e-01 -7.70315111e-01 -7.26102889e-01
7.21833110e-02 1.28398687e-01 -5.14530063e-01 6.02015316e-01
-1.01547515e+00 -6.19434834e-01 4.88942534e-01 7.47616708e-01
7.53976941e-01 -1.64281332e+00 -1.29861963e+00 -1.07260579e-02
5.34400344e-01 -6.01201236e-01 -2.35379264e-01 1.31058488e-02
-1.10392094e+00 -1.30971706e+00 -9.93866384e-01 -1.21004629e+00
8.20908248e-01 1.30821273e-01 3.68074059e-01 4.98104215e-01
-5.51799119e-01 1.82284907e-01 -7.54995465e-01 -4.17234182e-01
-5.45355317e-04 -5.99917732e-02 -4.74768616e-02 -1.76072240e-01
8.48174870e-01 -1.92073375e-01 -8.10574174e-01 3.65640670e-02
-7.34511673e-01 -4.26572919e-01 7.07071424e-01 6.99038982e-01
2.20372155e-01 3.16524029e-01 -1.28950700e-01 -6.43863201e-01
5.99564552e-01 1.58956110e-01 -4.90072966e-01 4.33102220e-01
-3.55052024e-01 -5.98423518e-02 4.70238984e-01 -7.21091568e-01
-1.22352648e+00 7.64701784e-01 1.77183121e-01 2.35231847e-01
-6.46301389e-01 1.77619234e-01 4.74733375e-02 -1.53853014e-01
3.12881947e-01 5.40413916e-01 -2.57563144e-01 -6.32726312e-01
1.62515536e-01 1.42026448e+00 7.11240828e-01 -3.89051050e-01
7.42304623e-01 4.18269634e-01 -2.03978449e-01 -9.27940607e-01
1.42088220e-01 -8.17140520e-01 -1.19515383e+00 -5.84297299e-01
1.23544526e+00 -3.69001441e-02 -1.04789674e+00 8.71574521e-01
-1.02223802e+00 -1.70487657e-01 3.75269324e-01 7.25587547e-01
4.33758199e-02 1.88194245e-01 -4.75083143e-01 -1.56875074e+00
-4.90375578e-01 -9.61728275e-01 5.79843879e-01 8.40238452e-01
-7.80836120e-02 -4.00185883e-01 -2.15953030e-02 1.11170448e-01
-5.10558411e-02 1.78833008e-01 8.04354846e-01 -7.97629714e-01
-1.86139509e-01 -7.47665942e-01 -4.15529639e-01 2.03172877e-01
6.55115604e-01 1.26314849e-01 -9.40753758e-01 -9.82795209e-02
-2.95030940e-02 -8.88443962e-02 6.52015805e-01 1.51834175e-01
7.55763829e-01 -1.59811750e-01 -4.13902283e-01 2.29114592e-01
1.64693797e+00 1.16776061e+00 4.10282433e-01 3.33167583e-01
7.29328692e-01 2.43007615e-01 4.21926051e-01 6.98231459e-02
8.08408037e-02 1.01557128e-01 -3.76027346e-01 -2.79074460e-01
-6.60155863e-02 2.17602223e-01 4.32653818e-03 3.43417257e-01
-7.72676826e-01 -1.47260487e-01 -1.07724190e+00 1.67294934e-01
-1.36519289e+00 -1.02235198e+00 -3.32054198e-02 1.79832578e+00
7.60490000e-01 -3.02374244e-01 5.78635693e-01 7.16914237e-01
7.33964324e-01 -1.47219479e-01 -4.62559044e-01 -5.02478838e-01
1.28555283e-01 1.01805210e+00 6.67906582e-01 6.73838794e-01
-1.00458550e+00 1.25008309e+00 6.63996220e+00 8.43782276e-02
-1.69892728e+00 2.18833722e-02 3.82073462e-01 3.02292965e-02
6.20283186e-01 -1.22470573e-01 -4.06258106e-01 2.48705044e-01
1.83635980e-01 3.95607799e-01 8.13900888e-01 6.61567152e-01
1.09752946e-01 -7.17991233e-01 -8.27234209e-01 1.23885393e+00
1.04698516e-01 -5.16497374e-01 1.78137831e-02 -2.17574209e-01
4.55845356e-01 -4.13426518e-01 -1.37593105e-01 -1.40770227e-01
7.72897601e-02 -1.14989722e+00 6.12241805e-01 6.45070374e-01
4.86006260e-01 -6.43022358e-01 7.56164670e-01 2.31223226e-01
-1.26255512e+00 -1.90151587e-01 -5.36691844e-02 -2.33024046e-01
-6.25051036e-02 -4.48599339e-01 -1.01052725e+00 1.09762410e-02
7.80716956e-01 -4.45732400e-02 -4.04198736e-01 9.36827719e-01
-4.83916365e-02 7.07000852e-01 -6.31557405e-01 -4.75187600e-01
3.93848300e-01 -3.59418035e-01 3.19304168e-01 1.43200219e+00
6.85228854e-02 8.56776595e-01 3.66959907e-02 8.57283771e-02
4.26484764e-01 3.90264899e-01 -4.02762979e-01 -1.74229428e-01
2.16898382e-01 7.74752855e-01 -1.46004558e+00 -8.31804752e-01
-2.10437417e-01 1.63136530e+00 -3.90386283e-01 5.68616748e-01
-1.68709055e-01 -9.13557351e-01 -2.82394022e-01 -4.08835500e-01
2.79407591e-01 -3.70258659e-01 -4.00792867e-01 -6.94191933e-01
-7.99317881e-02 -7.56765962e-01 7.28239477e-01 -5.60855925e-01
-7.30676770e-01 8.45455647e-01 -7.83194825e-02 -8.83692145e-01
-1.69905007e-01 -1.18856680e+00 -6.90186620e-01 1.08904874e+00
-1.00073969e+00 -1.24622679e+00 -4.29190308e-01 9.20699358e-01
6.80756032e-01 -4.42946404e-01 7.38733470e-01 -2.29062829e-02
-5.21738470e-01 4.20601159e-01 8.04387778e-02 7.24433362e-01
5.12120605e-01 -1.36409295e+00 -1.68493360e-01 9.60203409e-01
1.76464021e-01 8.29608858e-01 5.89814723e-01 -7.28765786e-01
-1.44657683e+00 -3.03499699e-01 5.76358080e-01 -2.96888649e-01
2.12412011e-02 6.68582618e-02 -4.50390965e-01 6.57462001e-01
3.73722166e-01 -1.51347239e-02 5.40461540e-01 -2.21422255e-01
-1.79938883e-01 -1.44452274e-01 -1.54670858e+00 1.81615978e-01
3.73192400e-01 -3.55941594e-01 -7.48557270e-01 -2.51724180e-02
-4.52470690e-01 -5.41588783e-01 -5.45809925e-01 -1.35326535e-01
1.36907804e+00 -7.73474753e-01 7.51729071e-01 -8.04300964e-01
-2.91835696e-01 -5.73412418e-01 -1.72755003e-01 -5.32500446e-01
3.28233272e-01 -2.91771144e-01 4.89296317e-01 8.15096915e-01
4.73714650e-01 -5.60774028e-01 1.11394715e+00 6.47447288e-01
8.25460315e-01 -9.55531672e-02 -7.84502447e-01 -4.88419831e-01
-1.30551249e-01 -1.85062349e-01 6.35337412e-01 6.75604701e-01
3.11892986e-01 -4.22911681e-02 -1.67501852e-01 1.90000758e-01
6.89353406e-01 2.81045407e-01 6.31811440e-01 -1.09614539e+00
-1.82994455e-01 -4.19029862e-01 -4.24867332e-01 -6.83570862e-01
-3.46894771e-01 -7.18176067e-01 2.40162805e-01 -1.34167480e+00
4.92747664e-01 -4.11648065e-01 -7.15943873e-01 5.41644037e-01
-3.42427462e-01 8.12464178e-01 3.30973387e-01 5.57812214e-01
-1.00592561e-02 -5.57345808e-01 1.06926060e+00 -1.01511113e-01
-7.33616233e-01 3.00178736e-01 2.67133504e-01 5.39359689e-01
9.56049442e-01 -2.30115384e-01 -6.60249442e-02 -2.01919526e-01
-5.17151117e-01 1.58880740e-01 2.77572453e-01 -9.41635370e-01
2.42069572e-01 -5.98064363e-01 9.31263149e-01 -8.26073349e-01
8.36807042e-02 -1.11476505e+00 -7.79901771e-03 7.05553532e-01
-8.38722289e-02 1.95078060e-01 -8.80225524e-02 3.10235411e-01
1.57814011e-01 -4.06466872e-01 8.66390109e-01 -3.70787978e-01
-8.93123507e-01 -2.52518713e-01 -4.40600812e-01 -6.84546351e-01
9.66098070e-01 -8.44481707e-01 3.17403913e-01 -7.65095651e-02
-8.96319211e-01 -2.08010852e-01 2.08245233e-01 -8.50129053e-02
5.92935801e-01 -1.02421939e+00 -1.27132982e-01 2.25104704e-01
-2.36099511e-01 -4.37442183e-01 -1.56273261e-01 5.81956089e-01
-1.18010032e+00 3.14431846e-01 -8.44377220e-01 -4.90316868e-01
-1.89678431e+00 2.90329725e-01 2.29439154e-01 3.63723010e-01
-7.64170349e-01 8.79258811e-01 -8.44819605e-01 -1.31619852e-02
4.48879242e-01 -4.71328348e-01 -4.20373142e-01 -3.02552938e-01
7.56371140e-01 3.82213116e-01 -4.44711983e-01 -1.01736486e+00
-5.82778990e-01 9.77983773e-01 6.05653450e-02 -8.68966937e-01
1.19558275e+00 2.13565052e-01 -3.01105767e-01 5.12755394e-01
1.01025891e+00 -3.22870985e-02 -8.87261510e-01 6.70747310e-02
9.30321366e-02 -6.69220209e-01 -1.69451758e-01 -1.24083900e+00
-1.08828497e+00 7.77873755e-01 1.47224772e+00 -2.26730034e-02
1.38637149e+00 -3.04053277e-01 7.52288163e-01 6.17041886e-01
3.88513267e-01 -1.30636036e+00 -2.45595649e-01 3.54707479e-01
4.68295187e-01 -1.31659651e+00 2.63703346e-01 1.32659256e-01
-8.93207073e-01 1.56275892e+00 3.18401307e-01 -5.66286445e-01
8.22990537e-01 2.23141104e-01 7.81931818e-01 -2.27901489e-01
2.45253444e-01 -4.76527959e-01 2.36013323e-01 7.90198863e-01
3.90187621e-01 3.14001709e-01 -6.00713909e-01 6.11008182e-02
-2.54288584e-01 3.39822650e-01 1.57813057e-01 1.41900420e+00
-6.69351816e-01 -1.22236741e+00 -1.02565587e+00 2.56326109e-01
-3.78939450e-01 2.54266858e-01 -6.14914358e-01 1.12160623e+00
1.78686202e-01 8.80742848e-01 4.47554998e-02 -6.47356868e-01
1.03663445e-01 4.13709879e-01 1.00247622e+00 -2.03122318e-01
-6.75096214e-01 2.43395358e-01 -4.07384574e-01 -1.78758770e-01
-7.02421784e-01 -7.41681933e-01 -1.68953419e+00 3.72074619e-02
-1.09587811e-01 9.69398841e-02 8.75435650e-01 1.10155356e+00
-8.61441910e-01 -7.37815127e-02 5.10859668e-01 -8.83026779e-01
-2.31263116e-01 -1.01340914e+00 -5.73725224e-01 3.43826234e-01
4.64742869e-01 -4.20300663e-01 5.11897430e-02 4.37817633e-01] | [6.480772972106934, -0.295287549495697] |
21401265-6205-4841-800d-bd40266cf7d7 | enhanced-neural-beamformer-with-spatial | 2306.15942 | null | https://arxiv.org/abs/2306.15942v1 | https://arxiv.org/pdf/2306.15942v1.pdf | Enhanced Neural Beamformer with Spatial Information for Target Speech Extraction | Recently, deep learning-based beamforming algorithms have shown promising performance in target speech extraction tasks. However, most systems do not fully utilize spatial information. In this paper, we propose a target speech extraction network that utilizes spatial information to enhance the performance of neural beamformer. To achieve this, we first use the UNet-TCN structure to model input features and improve the estimation accuracy of the speech pre-separation module by avoiding information loss caused by direct dimensionality reduction in other models. Furthermore, we introduce a multi-head cross-attention mechanism that enhances the neural beamformer's perception of spatial information by making full use of the spatial information received by the array. Experimental results demonstrate that our approach, which incorporates a more reasonable target mask estimation network and a spatial information-based cross-attention mechanism into the neural beamformer, effectively improves speech separation performance. | ['Yujun Wang', 'Dazhi Gao', 'Qinwen Guo', 'Wenbo Zhu', 'Peng Gao', 'Junnan Wu', 'Aoqi Guo'] | 2023-06-28 | null | null | null | null | ['dimensionality-reduction', 'speech-separation', 'speech-extraction'] | ['methodology', 'speech', 'speech'] | [-3.73158976e-03 -1.62721619e-01 4.09250818e-02 -4.09559876e-01
-9.15447056e-01 -1.55184686e-01 1.46885052e-01 -5.45135438e-01
-2.25175321e-01 3.64615411e-01 8.48259985e-01 -2.64444351e-01
-3.17492574e-01 -5.49975336e-01 -3.98396015e-01 -8.23551238e-01
3.02624077e-01 -2.19560921e-01 1.70829311e-01 4.98114191e-02
-2.45532431e-02 5.00924528e-01 -1.34007537e+00 2.66638845e-01
1.07278097e+00 9.66868162e-01 8.17182958e-01 5.71672618e-01
9.99065209e-03 5.27987838e-01 -8.79292071e-01 1.01787433e-01
1.13686159e-01 -3.88353735e-01 1.60787180e-02 -1.37049347e-01
2.20081776e-01 -5.27770817e-01 -8.01501036e-01 1.00513721e+00
1.10951293e+00 3.21330726e-01 4.57984090e-01 -8.40017974e-01
-4.99126911e-01 9.97281969e-01 -5.77006519e-01 4.98104632e-01
5.27936267e-03 1.18072052e-03 7.77372062e-01 -1.27574539e+00
-3.17286104e-01 1.26051402e+00 6.01274073e-01 3.68845999e-01
-7.17503726e-01 -1.14052904e+00 1.61655530e-01 2.84789413e-01
-1.56360638e+00 -1.09025645e+00 1.11828339e+00 4.39105975e-03
9.77252424e-01 4.47309226e-01 4.52275455e-01 7.20060408e-01
-3.45719121e-02 1.08337212e+00 7.99298525e-01 -4.17396843e-01
-3.34555423e-03 -1.36783183e-01 8.05346072e-02 4.44028437e-01
2.01430805e-02 3.39354128e-01 -9.76477325e-01 2.76813895e-01
8.59893084e-01 -2.34847412e-01 -6.58587635e-01 7.21723773e-03
-8.45768392e-01 4.53117758e-01 7.30397105e-01 9.15825963e-01
-4.20937866e-01 9.33764279e-02 -2.24132493e-01 -1.65500835e-01
5.13884962e-01 5.67776263e-01 -1.71975300e-01 1.72587648e-01
-1.39435315e+00 -2.52918720e-01 2.50510097e-01 8.95344198e-01
2.79762805e-01 7.06231356e-01 -6.40472770e-01 1.24239826e+00
6.36519194e-01 8.85980666e-01 5.70677757e-01 -7.00421929e-01
7.07970083e-01 -3.39366117e-04 -2.11888224e-01 -1.02465999e+00
-6.23975456e-01 -1.38787508e+00 -8.31132948e-01 -8.95086303e-02
2.59564519e-02 -4.68426347e-01 -1.06633651e+00 1.96137941e+00
-2.11009476e-02 3.96685660e-01 1.29989892e-01 1.24424255e+00
8.41595709e-01 8.05777252e-01 -2.82867223e-01 -3.49094152e-01
1.04866505e+00 -1.18871057e+00 -1.13137829e+00 -3.85213166e-01
2.19079405e-01 -6.21648908e-01 4.33051944e-01 3.27581108e-01
-1.34889185e+00 -8.33293915e-01 -1.25438213e+00 1.64732471e-01
-1.65178999e-01 4.78269637e-01 4.06776398e-01 9.44682121e-01
-1.07060027e+00 1.47940163e-02 -8.34644139e-01 5.08609302e-02
4.17994052e-01 5.35963535e-01 -5.70601933e-02 -8.90044346e-02
-1.07805133e+00 6.94832027e-01 1.10422544e-01 3.93168986e-01
-7.42994547e-01 -7.25706339e-01 -9.08993244e-01 6.99489236e-01
1.78271055e-01 -6.58241570e-01 1.17953086e+00 -5.26845634e-01
-1.49100018e+00 -3.35842401e-01 -6.14000380e-01 -3.42364848e-01
-3.65793288e-01 -2.49574825e-01 -7.19375014e-01 1.08180754e-01
-1.44074127e-01 8.08841407e-01 1.04882264e+00 -1.33618844e+00
-5.76746583e-01 -4.11668450e-01 -3.85430366e-01 5.23180723e-01
-6.77255332e-01 -2.59136688e-02 -5.77712297e-01 -1.07138956e+00
4.72303808e-01 -4.88353580e-01 -1.98679492e-01 -4.12016720e-01
-4.99435812e-01 1.59415886e-01 5.13219953e-01 -9.09639060e-01
1.67084146e+00 -2.50591183e+00 1.66428536e-01 3.25939506e-01
2.23329842e-01 6.62331700e-01 -5.07346630e-01 1.14540473e-01
-1.14434302e-01 -1.78932771e-01 -2.52399389e-02 -5.67048252e-01
-5.15116528e-02 -1.57804757e-01 -2.67155409e-01 2.46315882e-01
1.44975722e-01 7.27842510e-01 -4.86554891e-01 -2.62940317e-01
3.72876942e-01 6.69594407e-01 -8.95300388e-01 4.55209404e-01
3.56153131e-01 3.65326583e-01 -2.68783569e-01 3.03574085e-01
9.80432689e-01 1.79837570e-01 4.71351370e-02 -5.01721978e-01
-2.19961196e-01 4.74747628e-01 -1.08735335e+00 1.85724354e+00
-6.92398071e-01 7.78524697e-01 5.24939358e-01 -6.79338574e-01
6.64393604e-01 4.84757870e-01 3.45656514e-01 -9.79628563e-01
1.77855104e-01 1.26768380e-01 5.16666770e-01 -3.56286019e-01
1.86081752e-01 -4.25570756e-02 3.43299508e-01 1.75826758e-01
2.32391208e-01 1.21425599e-01 -3.36074263e-01 -1.07176006e-01
1.07080102e+00 -4.41707999e-01 1.28127877e-02 -1.00519046e-01
5.86288452e-01 -6.25095546e-01 5.28966725e-01 7.79364944e-01
8.61041993e-02 6.64290786e-01 -4.03825969e-01 3.26147407e-01
-4.51921493e-01 -1.02748168e+00 -1.01128198e-01 1.24348760e+00
2.97128428e-02 -3.64454776e-01 -9.15153205e-01 -1.73638508e-01
-2.84884572e-01 1.01750851e+00 -2.07676262e-01 -2.99645364e-01
-6.49705827e-01 -7.42796421e-01 5.09168804e-01 8.51147056e-01
5.83621264e-01 -5.60992897e-01 -3.47670794e-01 3.71599317e-01
-2.49930143e-01 -9.39194143e-01 -8.62112761e-01 3.60707372e-01
-4.35693115e-01 -3.19835961e-01 -7.79495180e-01 -6.05791807e-01
6.14883423e-01 9.15279865e-01 2.04270139e-01 -1.75461099e-01
1.50958270e-01 2.08310843e-01 -2.61894256e-01 -4.87567425e-01
1.48406863e-01 1.79728672e-01 1.79328457e-01 1.66022971e-01
1.63661301e-01 -7.60320306e-01 -5.43442190e-01 2.43215576e-01
-6.53766334e-01 1.69008523e-01 1.08910000e+00 7.59491146e-01
-1.18359298e-01 4.95397568e-01 7.01564252e-01 -1.51006114e-02
7.19699502e-01 -3.08718115e-01 -2.27129802e-01 -7.25275725e-02
-3.63058597e-01 2.53469795e-01 3.46328557e-01 -3.81845772e-01
-1.53453350e+00 -1.22326888e-01 -6.62244976e-01 -5.24995685e-01
-4.02787235e-03 5.49903274e-01 -7.06317246e-01 -2.30707098e-02
1.05313629e-01 4.09713358e-01 -1.38378635e-01 -6.43873215e-01
2.51246333e-01 1.08101010e+00 4.32744980e-01 -3.71629794e-05
7.90519297e-01 1.34075060e-01 -2.22250000e-01 -9.73547816e-01
-6.89293027e-01 -6.47706509e-01 -5.11822343e-01 -4.41421103e-03
8.60470176e-01 -1.08700359e+00 -4.53252375e-01 5.02557576e-01
-1.28469157e+00 -1.09909892e-01 2.59653598e-01 1.01721919e+00
-7.18173087e-02 6.84539452e-02 -3.59939218e-01 -1.19726765e+00
-2.97370195e-01 -1.24693131e+00 1.02656162e+00 1.79666311e-01
2.43388209e-02 -5.64447343e-01 -2.64275253e-01 3.76492530e-01
1.01229966e+00 -8.21474135e-01 6.14567578e-01 -6.26031041e-01
-6.51234627e-01 1.70082524e-01 -2.22898871e-01 1.84597418e-01
3.15729558e-01 -8.05973291e-01 -1.40866613e+00 -1.83243543e-01
2.72221118e-01 4.56561416e-01 1.04555249e+00 9.61083710e-01
1.08906674e+00 -3.60517830e-01 -5.95967770e-01 7.60141194e-01
9.94188786e-01 6.19603455e-01 5.45573175e-01 -3.11101049e-01
7.31977344e-01 5.00905812e-01 3.04025739e-01 3.58459294e-01
1.97134554e-01 8.97666991e-01 2.73975253e-01 -4.77892250e-01
-8.31843734e-01 -3.37226614e-02 1.76754698e-01 1.33694053e+00
3.61291617e-01 -5.84422946e-01 -6.23945951e-01 5.55105567e-01
-1.64761531e+00 -1.00408006e+00 1.80006459e-01 1.97031677e+00
6.86588883e-01 1.50290560e-02 -2.52130151e-01 2.09865034e-01
5.44546068e-01 2.26681307e-01 -3.69906604e-01 -1.07899994e-01
-1.76098078e-01 3.22549999e-01 3.07957053e-01 8.26826155e-01
-9.34073210e-01 7.52046347e-01 6.22301674e+00 1.13309777e+00
-1.08170617e+00 2.92260855e-01 2.47690305e-01 -4.72287297e-01
-3.91249299e-01 -7.15912044e-01 -7.72408724e-01 4.24067587e-01
8.09938133e-01 1.94473773e-01 5.90936959e-01 3.83807898e-01
3.83980095e-01 2.06946321e-02 -9.42047477e-01 1.14093006e+00
3.31830472e-01 -1.00891709e+00 -2.02892721e-01 1.33482143e-01
2.02854097e-01 -1.77531406e-01 3.71600389e-01 1.54917568e-01
-4.44446243e-02 -1.15888798e+00 8.08348894e-01 5.42274594e-01
5.43364346e-01 -7.31086373e-01 6.33897007e-01 4.73639876e-01
-1.37952387e+00 -5.51306069e-01 -8.33109394e-02 -9.02503636e-03
1.71111137e-01 8.17075193e-01 -8.95451128e-01 5.44646859e-01
4.62820828e-01 1.87014937e-01 -3.87751371e-01 1.40956938e+00
-2.04885796e-01 7.32843399e-01 -3.26554537e-01 1.36455335e-02
8.24907199e-02 1.37681603e-01 7.62005925e-01 1.34732544e+00
5.95080078e-01 4.69844669e-01 -2.00994343e-01 6.99869394e-01
9.43672881e-02 -8.94696116e-02 -5.76286614e-01 2.50472546e-01
8.73565674e-01 1.02324915e+00 -2.63674438e-01 1.26608297e-01
-4.87089515e-01 7.30537593e-01 1.31474182e-01 7.08604217e-01
-9.57058251e-01 -4.69255835e-01 6.93765640e-01 -9.30770040e-02
6.49120688e-01 -5.23877740e-01 -4.17248487e-01 -7.73337126e-01
-1.45749107e-01 -7.09599733e-01 -2.68941432e-01 -1.16615236e+00
-6.83775246e-01 8.14466774e-01 -1.33296311e-01 -9.19753075e-01
-1.02171749e-01 -6.34189308e-01 -4.01384622e-01 1.15993857e+00
-1.40077567e+00 -1.25498199e+00 4.46579047e-02 4.43396688e-01
7.98929036e-01 -3.14607531e-01 4.66849267e-01 6.71070635e-01
-8.16912770e-01 1.04942811e+00 -4.53303382e-02 1.48717567e-01
5.27282298e-01 -8.81036639e-01 1.54159078e-02 1.24446464e+00
3.13741088e-01 8.17560434e-01 5.50271094e-01 -4.00357902e-01
-1.30665946e+00 -1.07339811e+00 6.32126272e-01 -1.03240393e-01
2.50210553e-01 -5.16889632e-01 -7.70537257e-01 4.07175392e-01
6.12374187e-01 -4.13981766e-01 9.33300495e-01 6.51008561e-02
-8.65931362e-02 -4.89537448e-01 -6.77330017e-01 6.60298228e-01
1.11006749e+00 -4.15006965e-01 -7.54654467e-01 -3.69956605e-02
7.62251139e-01 -3.61826450e-01 -3.38374197e-01 5.27679026e-01
4.89908636e-01 -6.62321210e-01 1.27962804e+00 -1.08137406e-01
-1.41116992e-01 -4.46199179e-01 -4.55858529e-01 -1.70513487e+00
-9.26179409e-01 -4.28027958e-01 -1.53190851e-01 1.40108299e+00
6.22776151e-01 -5.04047692e-01 3.99600923e-01 3.05725992e-01
-7.55513430e-01 -5.66399336e-01 -1.09167492e+00 -6.88649893e-01
-1.41796559e-01 -6.89617157e-01 8.04601490e-01 4.69572484e-01
1.55838072e-01 6.13654852e-01 -3.86226326e-01 7.58456707e-01
4.56981122e-01 -8.10769945e-02 3.14020157e-01 -8.07106674e-01
-4.81133968e-01 -7.21955121e-01 5.93976378e-02 -1.61952233e+00
7.97147900e-02 -6.42601967e-01 4.24405545e-01 -1.69571006e+00
-4.93678600e-02 -3.58531058e-01 -4.46062684e-01 4.04452205e-01
-3.27057630e-01 -3.10987346e-02 3.81402791e-01 -8.31208453e-02
-3.39611590e-01 8.80996466e-01 1.15572309e+00 -2.04885319e-01
-1.84147239e-01 2.47170687e-01 -9.65247869e-01 5.51646054e-01
6.35292828e-01 -3.10217083e-01 -6.13607585e-01 -1.05656195e+00
-3.20438147e-01 2.21124530e-01 1.89601518e-02 -1.45319343e+00
8.45997095e-01 1.46894634e-01 6.04298055e-01 -7.69627750e-01
8.74931097e-01 -1.12874329e+00 -3.16486321e-02 2.01604947e-01
-3.57174158e-01 -4.25221622e-01 5.48634350e-01 3.87573212e-01
-2.43391484e-01 -1.46190107e-01 6.15297198e-01 3.85674447e-01
-3.41026664e-01 2.37980671e-03 -6.27280712e-01 -5.50021172e-01
5.93372345e-01 -2.08092984e-02 -1.91506773e-01 -5.49659073e-01
-6.34513915e-01 1.21041752e-01 -3.50957274e-01 3.08034986e-01
8.46493423e-01 -1.54875231e+00 -5.31805515e-01 6.59994721e-01
-4.28774446e-01 -3.27290803e-01 2.66402900e-01 9.03875113e-01
1.91249058e-01 9.78731096e-01 2.54543535e-02 -4.81701791e-01
-1.01824033e+00 6.67235374e-01 4.93959099e-01 1.42751455e-01
-2.21356541e-01 1.26080811e+00 6.00920022e-01 -1.04577281e-01
5.21122575e-01 -4.74219382e-01 -4.25786465e-01 -1.81757957e-01
7.92244077e-01 2.48873696e-01 8.04721639e-02 -7.31246889e-01
-5.36599517e-01 5.97649395e-01 2.57341683e-01 -5.63839555e-01
1.13679492e+00 -4.32144880e-01 1.43397957e-01 6.34594588e-03
1.00482631e+00 6.28325522e-01 -1.12750697e+00 -4.02283370e-01
-3.61309677e-01 -5.39411962e-01 7.78362453e-01 -1.06229889e+00
-1.29778469e+00 1.23536384e+00 7.33091474e-01 9.06775072e-02
1.69867086e+00 -7.48359561e-02 7.45720685e-01 1.05552539e-01
1.48130879e-01 -7.37834275e-01 1.47623122e-01 4.45856363e-01
9.81907248e-01 -9.07770753e-01 -3.21896225e-01 -6.09179318e-01
-2.45783895e-01 8.73387873e-01 8.24448586e-01 4.35770124e-01
7.79865444e-01 7.31557429e-01 3.38599123e-02 6.22672327e-02
-5.59391797e-01 -5.35120070e-01 6.66309357e-01 6.73373103e-01
3.45802128e-01 4.13271645e-03 1.04047611e-01 1.09942544e+00
-2.62831658e-01 -5.20474434e-01 -1.00343198e-01 4.73206282e-01
-8.84154916e-01 -8.66923928e-01 -6.90493166e-01 2.93776214e-01
-2.31704354e-01 -6.59095109e-01 -1.50916472e-01 1.74101725e-01
8.14252868e-02 1.50944567e+00 1.74202055e-01 -6.95509732e-01
3.48491460e-01 -6.33446723e-02 4.98003423e-01 -6.45757258e-01
-3.03864360e-01 8.15264285e-01 9.69758332e-02 -3.35554928e-01
-2.33596355e-01 -3.87754798e-01 -1.09300160e+00 1.10706218e-01
-6.91557527e-01 2.77744293e-01 7.53829360e-01 1.13442028e+00
6.38967633e-01 1.27985692e+00 7.04269826e-01 -9.50588405e-01
-2.75243431e-01 -1.25772524e+00 -5.47761440e-01 -4.02721614e-01
5.50618589e-01 -7.17273891e-01 -1.23095065e-01 -3.32958162e-01] | [14.896368026733398, 5.866588592529297] |
7c5eef92-cbd8-4cb0-92ba-c27db0c921d0 | robust-breast-cancer-detection-in-mammography | 1912.11027 | null | https://arxiv.org/abs/1912.11027v2 | https://arxiv.org/pdf/1912.11027v2.pdf | Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach | Breast cancer remains a global challenge, causing over 1 million deaths globally in 2018. To achieve earlier breast cancer detection, screening x-ray mammography is recommended by health organizations worldwide and has been estimated to decrease breast cancer mortality by 20-40%. Nevertheless, significant false positive and false negative rates, as well as high interpretation costs, leave opportunities for improving quality and access. To address these limitations, there has been much recent interest in applying deep learning to mammography; however, obtaining large amounts of annotated data poses a challenge for training deep learning models for this purpose, as does ensuring generalization beyond the populations represented in the training dataset. Here, we present an annotation-efficient deep learning approach that 1) achieves state-of-the-art performance in mammogram classification, 2) successfully extends to digital breast tomosynthesis (DBT; "3D mammography"), 3) detects cancers in clinically-negative prior mammograms of cancer patients, 4) generalizes well to a population with low screening rates, and 5) outperforms five-out-of-five full-time breast imaging specialists by improving absolute sensitivity by an average of 14%. Our results demonstrate promise towards software that can improve the accuracy of and access to screening mammography worldwide. | ['Jerrold L. Boxerman', 'Jorge Onieva Onieva', 'William Lotter', 'A. Gregory Sorensen', 'Abdul Rahman Diab', 'Mack Bandler', 'Bryan Haslam', 'Meiyun Wang', 'Kevin Wu', 'Jiye G. Kim', 'Gopal Vijayaraghavan', 'Eric Wu', 'Giorgia Grisot'] | 2019-12-23 | null | null | null | null | ['breast-cancer-detection', 'breast-cancer-detection'] | ['knowledge-base', 'medical'] | [ 3.91494930e-01 5.65269232e-01 -4.58546162e-01 -6.27014816e-01
-1.53035641e+00 -1.32900268e-01 2.71877926e-02 7.36040354e-01
-5.22063971e-01 4.95923728e-01 5.52427284e-02 -9.79627609e-01
5.87912090e-02 -9.65185642e-01 -8.26043844e-01 -4.76920068e-01
-2.63170391e-01 6.98852777e-01 2.99552411e-01 2.62526840e-01
-5.04044235e-01 5.91458917e-01 -8.07117939e-01 6.58880234e-01
5.22201955e-01 1.06371176e+00 1.57474056e-01 8.55631590e-01
3.28998536e-01 7.53182590e-01 -1.09095871e-01 -5.97201407e-01
3.30056809e-02 -5.33531427e-01 -8.30206275e-01 7.06408685e-03
5.42249978e-01 -1.04424798e+00 -2.90591896e-01 7.62105942e-01
5.78792155e-01 -7.22861826e-01 5.71407080e-01 -2.82991618e-01
-5.42193770e-01 5.27381241e-01 -7.42201328e-01 3.82657558e-01
-1.67587012e-01 4.17415937e-03 2.82627612e-01 -3.21222246e-01
2.94165015e-01 7.99453139e-01 1.10038328e+00 9.82032061e-01
-9.91047382e-01 -6.26309216e-01 -6.04245126e-01 -2.96420723e-01
-8.98627877e-01 -3.85144889e-01 -6.50731400e-02 -2.77098358e-01
6.43281102e-01 5.90603352e-01 1.01909506e+00 8.61043274e-01
6.38314128e-01 7.30363548e-01 7.64320612e-01 -3.64956796e-01
1.12264492e-01 -8.36586133e-02 -1.31419003e-02 7.66913414e-01
6.57095969e-01 -1.69161916e-01 2.39695814e-02 -3.92527282e-01
8.92575324e-01 5.83644919e-02 6.34103175e-03 -2.65362442e-01
-1.07465112e+00 7.73085296e-01 5.04847586e-01 2.62146354e-01
-3.12169045e-01 2.96453446e-01 6.77575767e-01 -2.08048880e-01
3.95912737e-01 2.69092232e-01 -2.81754822e-01 1.43907204e-01
-9.66457963e-01 4.11458127e-02 5.83975375e-01 4.74951684e-01
1.73938513e-01 -2.44208053e-01 -8.25010166e-02 7.19614685e-01
1.18811494e-02 6.39561534e-01 5.66587746e-01 -7.90074587e-01
1.10969327e-01 7.57753074e-01 5.95537983e-02 -8.23161483e-01
-8.01138282e-01 -6.64102793e-01 -1.15124488e+00 -1.31927609e-01
3.69427323e-01 -9.73310396e-02 -1.30101001e+00 1.27050900e+00
2.51407117e-01 -4.09267515e-01 -1.82389468e-01 7.51506567e-01
7.71313310e-01 1.86692297e-01 4.71742839e-01 -1.72907531e-01
1.63425982e+00 -1.87892079e-01 -4.54399139e-01 -5.65163791e-01
1.08815718e+00 -3.42487723e-01 6.21275246e-01 1.94059551e-01
-1.31399870e+00 -4.19475168e-01 -1.10323226e+00 -1.54353082e-01
1.19150795e-01 4.70597029e-01 8.50140750e-01 1.18538976e+00
-9.36414480e-01 2.54307240e-01 -1.80586886e+00 -6.60684884e-01
1.14745116e+00 5.56161880e-01 -4.23487991e-01 -5.96589625e-01
-7.08571255e-01 8.72271061e-01 2.53822148e-01 -8.61257240e-02
-9.76863801e-01 -9.32909608e-01 -8.05408597e-01 -2.08764244e-02
2.74584085e-01 -6.45923972e-01 1.63274539e+00 -8.89381707e-01
-7.58077562e-01 1.28689587e+00 -1.04641870e-01 -7.23835588e-01
7.36273944e-01 -5.61295412e-02 -3.08101386e-01 3.20852965e-01
2.73357183e-01 7.78210104e-01 4.10022996e-02 -7.72760272e-01
-7.50959396e-01 -6.66056275e-01 -3.91780287e-01 1.48972031e-02
-6.53330028e-01 3.41064744e-02 -7.13626325e-01 -1.99660644e-01
3.77775222e-01 -8.68715942e-01 -6.35526359e-01 4.05696779e-01
-1.67237166e-02 2.14549273e-01 5.90312302e-01 -1.21729946e+00
8.43491733e-01 -2.14954829e+00 -5.92560649e-01 -3.44210602e-02
3.29582483e-01 3.07183385e-01 4.44343567e-01 -3.43216777e-01
-1.38646122e-02 2.71824121e-01 -1.20809481e-01 1.76611841e-01
-6.07144952e-01 2.00098634e-01 5.10807216e-01 6.04104161e-01
5.07443190e-01 1.07965434e+00 -1.06191611e+00 -6.04191363e-01
1.93698958e-01 4.39009607e-01 -5.25598288e-01 -2.10637182e-01
1.24604352e-01 4.89735097e-01 -4.83895481e-01 1.00128281e+00
5.62475502e-01 -8.72191906e-01 7.04044044e-01 -2.80533254e-01
3.27509910e-01 1.54972123e-02 -7.00542331e-01 1.27167594e+00
-1.75695509e-01 4.42884862e-01 1.10680617e-01 -9.93462205e-01
4.92890894e-01 2.41003603e-01 6.92824781e-01 -8.24815094e-01
1.99475899e-01 5.00056267e-01 4.29969847e-01 -6.76277757e-01
1.66690484e-01 -2.65444547e-01 1.67734444e-01 5.33050969e-02
-1.98802799e-01 2.17131171e-02 -1.15560759e-02 7.93343224e-03
1.48911893e+00 -3.41751009e-01 7.16698408e-01 -4.63894457e-01
-2.78838124e-04 3.40366542e-01 4.41208988e-01 9.30897474e-01
-1.68282837e-01 5.73937774e-01 5.59406579e-01 -7.00326741e-01
-1.15561080e+00 -9.18705881e-01 -5.82232714e-01 7.27541327e-01
-2.71218538e-01 3.14815432e-01 -6.32935762e-01 -6.53797626e-01
1.76523641e-01 5.22502542e-01 -8.52943480e-01 -6.37630001e-02
-6.90748453e-01 -1.34741890e+00 6.20173872e-01 1.03054917e+00
7.22390950e-01 -4.00743961e-01 -9.14322436e-01 2.60511130e-01
-7.98537210e-02 -8.59494865e-01 1.31349906e-01 3.77304941e-01
-1.17319536e+00 -1.27242231e+00 -1.25318229e+00 -7.93813229e-01
7.61165559e-01 5.10391220e-02 1.12412763e+00 5.20393252e-02
-9.47994888e-01 3.57317924e-01 -1.55732676e-01 -6.14910901e-01
-8.94329488e-01 4.26535569e-02 -3.31418723e-01 -3.83036017e-01
6.35393381e-01 3.00235093e-01 -7.95566559e-01 1.04891755e-01
-8.91823590e-01 1.58811286e-02 1.10600495e+00 8.54382396e-01
9.07646418e-01 -2.12316498e-01 6.32603884e-01 -1.15118170e+00
5.48978671e-02 -5.69280446e-01 -4.32110190e-01 1.74205214e-01
-1.70179605e-01 -4.67005253e-01 -1.69192888e-02 -2.94535190e-01
-1.04139841e+00 1.73552617e-01 -2.31743976e-01 2.30875239e-01
3.20065618e-02 5.77259958e-01 2.75839448e-01 -1.26045272e-01
1.04411066e+00 -1.01729827e-02 1.21959820e-01 -2.78732419e-01
-4.66933101e-01 6.15288496e-01 6.17578387e-01 1.05390422e-01
1.08737051e-02 7.39986718e-01 3.78515452e-01 -8.72763336e-01
-1.00483727e+00 -2.91588575e-01 -3.60552013e-01 -1.66666076e-01
1.11585951e+00 -1.12798345e+00 -4.69161779e-01 3.52143973e-01
-5.94138920e-01 -3.72686028e-01 -1.34066731e-01 6.67809367e-01
-1.00694709e-02 2.30549425e-01 -8.40326905e-01 -6.19256616e-01
-3.52462560e-01 -1.19361758e+00 1.19090831e+00 1.56324700e-01
-2.53272116e-01 -8.68022859e-01 -5.21552026e-01 3.48731250e-01
3.35890025e-01 5.63216209e-01 1.10745537e+00 -6.36119783e-01
-3.80811423e-01 -7.97926068e-01 -5.68813443e-01 4.15405869e-01
4.00108844e-01 -4.19587284e-01 -7.28841126e-01 -3.96988720e-01
-4.25864086e-02 -4.96938646e-01 9.83335972e-01 1.23918486e+00
1.68906426e+00 4.20346677e-01 -1.00561142e+00 5.24510860e-01
1.26032794e+00 2.87496388e-01 5.06308854e-01 2.68887609e-01
2.26624385e-01 1.87101081e-01 3.78854871e-01 1.89043567e-01
9.30284634e-02 -4.83529642e-02 5.26276350e-01 -6.10635698e-01
-2.88014144e-01 3.93056124e-03 -5.17473340e-01 1.77146122e-01
-8.33902583e-02 -4.03705053e-02 -1.42504251e+00 6.84188306e-01
-1.28438699e+00 -5.23384869e-01 -2.57818699e-01 2.08410215e+00
8.61262560e-01 3.91081631e-01 -1.52052268e-01 -2.68548522e-02
5.09204149e-01 -4.83391732e-01 -8.33006442e-01 6.36430532e-02
9.34801698e-02 3.75220001e-01 9.52140212e-01 -4.80876453e-02
-1.21500826e+00 2.67051399e-01 7.01572895e+00 4.07922685e-01
-1.26725280e+00 3.59904587e-01 1.73416901e+00 -4.26478498e-02
2.86524087e-01 -5.47008634e-01 -6.91089928e-01 9.41402763e-02
9.65997934e-01 1.74338132e-01 -4.27084029e-01 1.04703021e+00
1.47010116e-02 -4.75143641e-01 -1.36604536e+00 6.43849134e-01
-6.76314309e-02 -1.48877513e+00 -8.56534541e-02 2.32302055e-01
7.64311016e-01 1.24454685e-02 2.94719674e-02 1.42998114e-01
2.35286132e-02 -1.25146818e+00 1.54533356e-01 3.62061620e-01
1.37197518e+00 -6.32157624e-01 1.22983646e+00 3.79847348e-01
-6.18540227e-01 -4.80765142e-02 -4.25904900e-01 2.79086679e-01
-2.84818113e-01 7.83829987e-01 -1.23973882e+00 3.34619403e-01
1.06324363e+00 1.85748950e-01 -8.27186465e-01 1.16853476e+00
4.57962334e-01 9.84986782e-01 -3.10850829e-01 -4.42499891e-02
8.75754058e-02 5.94433665e-01 -3.41605932e-01 1.29925883e+00
6.50720358e-01 3.74117106e-01 5.36750630e-02 3.11965644e-01
-3.49690884e-01 -2.44572088e-02 -2.34294936e-01 -9.91217941e-02
1.84926286e-01 1.02040923e+00 -1.04701018e+00 -3.80666435e-01
-6.22819781e-01 6.24186635e-01 -1.83608741e-01 -1.37500867e-01
-6.90172791e-01 1.12682655e-01 -2.09618583e-01 5.41011810e-01
-1.66593324e-02 3.14253747e-01 -3.56729418e-01 -4.27525491e-01
-8.07205513e-02 -9.34030533e-01 4.41818655e-01 -3.91684800e-01
-9.75450993e-01 2.43329629e-01 -1.32950127e-01 -8.70007336e-01
-2.30096549e-01 -9.00700927e-01 -6.32320344e-02 8.27773571e-01
-1.29836607e+00 -1.24266267e+00 -6.62480593e-01 -2.47277189e-02
3.75369132e-01 -5.97732663e-02 1.12358034e+00 4.50729579e-01
-1.55550644e-01 7.08760619e-01 3.19182247e-01 4.40496325e-01
6.04470074e-01 -1.08103597e+00 2.83930272e-01 2.97000647e-01
-7.71958232e-01 1.25445917e-01 2.58953631e-01 -7.54331112e-01
-1.59260595e+00 -1.38861978e+00 6.46034658e-01 -3.45817894e-01
3.62112582e-01 1.50721803e-01 -7.30002463e-01 8.83442402e-01
-3.31861615e-01 3.92482668e-01 9.19298649e-01 -8.82482156e-02
1.43658563e-01 -1.98942542e-01 -1.49794757e+00 3.10580671e-01
6.15351677e-01 8.00293311e-02 -4.67771702e-02 7.06023097e-01
1.87881619e-01 -9.40857053e-01 -8.61845732e-01 8.34523618e-01
7.24350333e-01 -1.02381539e+00 7.82505691e-01 -4.64712501e-01
6.70192897e-01 5.73745906e-01 -7.98360407e-02 -6.77167892e-01
-3.82293940e-01 7.70844668e-02 6.22376613e-02 6.18660510e-01
3.90351325e-01 -3.80851716e-01 1.31291378e+00 6.64093256e-01
-1.94520995e-01 -1.04838634e+00 -9.89793777e-01 -3.57340455e-01
3.52806985e-01 -3.48297924e-01 2.55320102e-01 7.05580831e-01
-4.04773563e-01 -3.06480497e-01 9.21987891e-02 3.21760565e-01
5.28454244e-01 -4.51333165e-01 3.78760606e-01 -1.05131578e+00
-5.13384938e-01 -2.28571400e-01 -5.26272476e-01 -9.60739076e-01
-6.62844718e-01 -7.17712283e-01 -2.28183433e-01 -1.74232817e+00
8.50841701e-01 -3.67340147e-01 -1.10779211e-01 4.30131525e-01
-2.96640486e-01 6.38975680e-01 -4.63419706e-01 -1.55496269e-01
-2.65876591e-01 -3.59569728e-01 1.44144166e+00 -2.92233735e-01
1.80418834e-01 2.40453616e-01 -9.64544654e-01 8.12496305e-01
5.67179978e-01 -4.06086236e-01 1.26709670e-01 -7.25509703e-01
1.75501704e-01 5.84006190e-01 5.69561481e-01 -1.31186509e+00
-1.23996086e-01 1.07960496e-03 1.27849054e+00 -6.99849069e-01
2.32188255e-01 -5.69222867e-01 1.56682745e-01 1.21736455e+00
-2.83369601e-01 -5.69862247e-01 6.11290634e-01 4.49326426e-01
6.41746670e-02 -2.81260550e-01 1.07948673e+00 -5.40616572e-01
-2.92985350e-01 8.77393931e-02 -5.20578146e-01 -2.05556259e-01
1.00905418e+00 -2.22999722e-01 5.57966344e-02 -7.96635747e-02
-7.19590247e-01 2.85268039e-01 1.48742944e-01 1.49030611e-05
2.86611587e-01 -1.15203953e+00 -1.03802681e+00 -2.45165229e-02
1.87941805e-01 2.75165021e-01 4.04765606e-01 8.52876186e-01
-9.84003365e-01 5.16852319e-01 1.05750352e-01 -9.57542896e-01
-1.32141411e+00 2.86674835e-02 6.38189554e-01 -4.07125771e-01
-5.74569941e-01 1.17743778e+00 6.89175576e-02 -1.09736055e-01
2.57759720e-01 -5.09612620e-01 1.73942283e-01 -2.63081223e-01
7.38024831e-01 1.85373470e-01 4.29324746e-01 -6.35531023e-02
-3.00776452e-01 -4.76587527e-02 -5.84060848e-01 3.57808560e-01
1.37678993e+00 4.67822552e-01 1.06371477e-01 1.15052715e-01
9.73751009e-01 -3.58543605e-01 -9.69086826e-01 1.50772184e-02
-4.19721566e-02 -1.97282255e-01 3.79027814e-01 -1.07559013e+00
-9.01984692e-01 8.13159049e-01 1.11479878e+00 3.05431843e-01
1.17114472e+00 4.72558260e-01 6.77951038e-01 4.68285084e-01
2.26068571e-01 -6.10337555e-01 4.12568711e-02 -2.07328692e-01
3.69521141e-01 -1.73522079e+00 2.80577272e-01 -1.58658236e-01
-3.54779005e-01 1.28253222e+00 5.03717959e-01 1.36626750e-01
6.73970103e-01 4.70704049e-01 -2.89373938e-02 -1.42942831e-01
-2.43776724e-01 3.07897478e-01 1.02724597e-01 5.77667296e-01
1.00714552e+00 3.17154408e-01 -3.57232273e-01 6.75187945e-01
2.71912485e-01 4.18557048e-01 2.05957383e-01 1.14494276e+00
-7.10727632e-01 -6.99253917e-01 -4.77455050e-01 1.34378791e+00
-1.00283372e+00 1.25649765e-01 -1.90375373e-01 1.12261772e+00
1.89489692e-01 6.34269357e-01 2.47102931e-01 2.72024810e-01
1.76217347e-01 -1.99357733e-01 5.89161515e-01 -8.08242202e-01
-3.19814533e-01 3.43233138e-01 2.38048747e-01 -3.12447548e-01
-2.75590837e-01 -7.58537769e-01 -1.25436652e+00 5.09298965e-02
-3.43420446e-01 -2.94365883e-01 8.18355143e-01 8.49596977e-01
1.04347110e-01 9.01583135e-01 1.07267173e-02 -5.86576879e-01
-8.95850599e-01 -1.13340998e+00 -4.69263881e-01 1.62129719e-02
3.56561244e-01 -6.28843829e-02 1.40271649e-01 2.79919684e-01] | [15.211962699890137, -2.506608724594116] |
09d07679-e54e-4eef-a8da-72a9874b83fd | benchmarking-robustness-in-object-detection | 1907.07484 | null | https://arxiv.org/abs/1907.07484v2 | https://arxiv.org/pdf/1907.07484v2.pdf | Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming | The ability to detect objects regardless of image distortions or weather conditions is crucial for real-world applications of deep learning like autonomous driving. We here provide an easy-to-use benchmark to assess how object detection models perform when image quality degrades. The three resulting benchmark datasets, termed Pascal-C, Coco-C and Cityscapes-C, contain a large variety of image corruptions. We show that a range of standard object detection models suffer a severe performance loss on corrupted images (down to 30--60\% of the original performance). However, a simple data augmentation trick---stylizing the training images---leads to a substantial increase in robustness across corruption type, severity and dataset. We envision our comprehensive benchmark to track future progress towards building robust object detection models. Benchmark, code and data are publicly available. | ['Wieland Brendel', 'Robert Geirhos', 'Oliver Bringmann', 'Matthias Bethge', 'Benjamin Mitzkus', 'Evgenia Rusak', 'Claudio Michaelis', 'Alexander S. Ecker'] | 2019-07-17 | null | https://openreview.net/forum?id=ryljMpNtwr | https://openreview.net/pdf?id=ryljMpNtwr | null | ['robust-object-detection'] | ['computer-vision'] | [ 2.50708014e-01 -3.92502725e-01 1.70759499e-01 -4.44943994e-01
-8.57005239e-01 -6.87601805e-01 7.87156284e-01 -1.22588105e-01
-6.53658628e-01 5.11905372e-01 -3.35003078e-01 -3.90231609e-01
3.86276245e-01 -4.10767525e-01 -1.01311481e+00 -6.43999338e-01
-3.49518299e-01 -2.05935556e-02 5.19627094e-01 -2.58046716e-01
1.77571326e-01 6.42991185e-01 -1.96337748e+00 2.50379831e-01
5.12195110e-01 7.96131968e-01 1.47196520e-02 1.16382122e+00
4.49391276e-01 6.83706045e-01 -9.66936469e-01 -4.86222416e-01
6.22596800e-01 4.01816107e-02 -4.82378840e-01 2.08847970e-01
1.16733384e+00 -5.27718127e-01 -4.12114263e-01 1.24745297e+00
5.86208701e-01 -1.14695631e-01 5.53535044e-01 -1.53537822e+00
-6.76894903e-01 -5.34974150e-02 -6.32333279e-01 8.07967365e-01
2.52879336e-02 8.40918243e-01 5.83227634e-01 -9.21220183e-01
5.15119851e-01 1.30050695e+00 8.84879291e-01 5.91876149e-01
-1.11846876e+00 -7.87324071e-01 -3.99141982e-02 3.62768680e-01
-1.12634218e+00 -7.49938965e-01 2.79768139e-01 -5.31841576e-01
1.09505272e+00 3.24239492e-01 2.20666438e-01 1.12820864e+00
2.64739990e-01 7.05534101e-01 1.18692100e+00 -1.34576529e-01
3.11005153e-02 1.44573212e-01 2.76228279e-01 6.25717759e-01
6.89457595e-01 4.53450292e-01 -3.87908936e-01 1.43030182e-01
4.34825778e-01 -3.77220780e-01 -9.47109088e-02 -3.35929871e-01
-1.18156862e+00 5.01110673e-01 6.20235205e-01 -2.00194657e-01
1.47692069e-01 5.39097846e-01 6.32700264e-01 4.38779920e-01
3.16945732e-01 5.34471750e-01 -3.68233293e-01 -1.18708067e-01
-6.08493328e-01 6.72703981e-01 4.84629691e-01 1.13137555e+00
6.78668439e-01 4.36586499e-01 -1.56752348e-01 7.20558584e-01
8.89699440e-03 6.64137661e-01 1.34932697e-01 -1.28744042e+00
5.79844236e-01 1.37579545e-01 4.88940120e-01 -9.62748826e-01
-3.41375440e-01 -6.37529135e-01 -7.11154163e-01 7.61926711e-01
5.33424735e-01 -1.56342462e-01 -1.25309432e+00 1.61763453e+00
1.82702824e-01 1.44623354e-01 1.52102724e-01 8.29415321e-01
9.59472418e-01 4.28606421e-01 8.58643577e-02 1.30729184e-01
1.28606641e+00 -8.15847218e-01 -6.05494440e-01 -6.33896649e-01
5.98421395e-01 -7.72878647e-01 1.17199254e+00 4.74250227e-01
-1.02587712e+00 -8.02243114e-01 -1.41169012e+00 -1.20604135e-01
-5.23910761e-01 6.35581696e-03 3.85236084e-01 9.54367757e-01
-1.08130872e+00 2.87613481e-01 -6.38940632e-01 -4.52073455e-01
7.01049387e-01 2.03425616e-01 -4.59851027e-01 -3.46903980e-01
-7.48820066e-01 1.19231725e+00 3.42434078e-01 -9.84010398e-02
-1.49365568e+00 -7.27097631e-01 -8.18032324e-01 -3.61947298e-01
1.44938439e-01 -3.32356125e-01 1.49164450e+00 -8.54488373e-01
-7.02964902e-01 1.14638758e+00 -2.09784042e-02 -7.32351065e-01
8.62380624e-01 -4.08437043e-01 -5.88415086e-01 -1.46363974e-01
1.77627698e-01 1.04841745e+00 1.05033016e+00 -1.68148291e+00
-1.00386548e+00 -1.54420793e-01 8.07111189e-02 8.27698782e-02
-7.56096840e-02 4.46582109e-01 -7.42100000e-01 -6.70293033e-01
-3.46551925e-01 -9.42511737e-01 -1.82585329e-01 3.27352315e-01
-3.68250817e-01 9.24080238e-02 1.25571954e+00 -3.50301176e-01
5.92847586e-01 -2.13344789e+00 -4.94576514e-01 -2.95305759e-01
1.89175010e-01 5.93050063e-01 -5.62402010e-01 -1.04753077e-01
-2.14739710e-01 1.31781250e-01 -2.99333274e-01 -4.21375215e-01
-7.85028487e-02 3.46932113e-01 -3.15851212e-01 8.89296234e-01
6.31796777e-01 8.49972665e-01 -8.46806526e-01 -1.96837232e-01
4.70413655e-01 2.71396667e-01 -4.52878386e-01 6.92760339e-04
-2.51241550e-02 1.30260333e-01 2.34758571e-01 7.10716009e-01
8.35402906e-01 1.37924552e-01 -5.45928955e-01 4.31769751e-02
-1.04592303e-02 2.65918020e-03 -1.04665148e+00 1.17019570e+00
-1.44237325e-01 1.19681633e+00 2.12163538e-01 -6.99250877e-01
5.98439634e-01 -8.55727196e-02 7.28348095e-05 -1.11232436e+00
3.24286632e-02 8.50350335e-02 3.50149632e-01 -5.19103587e-01
6.04835033e-01 3.59912097e-01 -3.74425277e-02 2.74283346e-02
5.93445078e-03 -3.16379488e-01 5.61198235e-01 2.05328196e-01
1.25972402e+00 -3.22093815e-01 -4.30493169e-02 -3.00316691e-01
1.45119548e-01 1.90472335e-01 5.33204019e-01 1.27690756e+00
-7.45725513e-01 8.15748513e-01 4.56884295e-01 -7.21951723e-01
-1.38844490e+00 -1.02044833e+00 -4.34986323e-01 1.02969980e+00
2.20748350e-01 -5.06165959e-02 -9.42834914e-01 -5.53621948e-01
3.10157359e-01 6.73144400e-01 -7.99917042e-01 -2.41299540e-01
-4.38238025e-01 -1.20435381e+00 1.03392923e+00 6.77539647e-01
6.47118390e-01 -1.07933414e+00 -7.70298004e-01 -1.31771088e-01
4.14029397e-02 -1.48956180e+00 -1.70453459e-01 3.12406927e-01
-5.10657012e-01 -1.10022593e+00 -4.70945954e-01 -5.25967479e-01
5.32082200e-01 7.69012094e-01 1.45916736e+00 2.94423223e-01
-7.81115234e-01 3.43925357e-01 -2.01373547e-01 -9.68862712e-01
-5.96263051e-01 -4.05914664e-01 2.76256442e-01 -2.90823132e-01
3.87522012e-01 9.36711058e-02 -5.77246726e-01 5.96050799e-01
-9.65562761e-01 -3.24130088e-01 5.24098694e-01 4.88960832e-01
3.19869727e-01 2.53032334e-02 2.60567784e-01 -6.27938390e-01
3.84332985e-01 -3.71084481e-01 -8.43181729e-01 -1.80062756e-01
-4.08700585e-01 -2.43953690e-01 3.07120323e-01 -2.49821246e-01
-8.11236680e-01 8.15301463e-02 -7.73836449e-02 -2.88956225e-01
-5.34962296e-01 -1.23208769e-01 -1.13155685e-01 -3.51529658e-01
1.08321869e+00 3.81657109e-02 -3.02997708e-01 -2.56115854e-01
4.80456233e-01 5.44512153e-01 1.23364270e+00 -3.04473519e-01
1.17358434e+00 6.80222452e-01 -2.32135922e-01 -8.35005045e-01
-7.46034324e-01 -6.46589577e-01 -3.60499352e-01 -2.45399535e-01
7.83380568e-01 -1.22555399e+00 -2.86968529e-01 8.70085418e-01
-1.28181207e+00 -5.51228344e-01 -6.01606593e-02 1.07830547e-01
-4.19971317e-01 3.46165359e-01 -4.71308887e-01 -6.98902845e-01
3.15589234e-02 -1.39111853e+00 1.11163628e+00 8.13163891e-02
2.35816002e-01 -4.17147607e-01 -8.42392072e-02 4.56613392e-01
3.37780237e-01 3.79532993e-01 4.51838136e-01 -2.97649235e-01
-6.87268794e-01 -2.61103958e-01 -7.77510643e-01 5.80192327e-01
-8.61619040e-02 2.25359917e-01 -1.30264521e+00 -5.88978529e-01
-2.28513241e-01 -4.76615250e-01 1.21768701e+00 1.48962408e-01
1.33916783e+00 -1.95303828e-01 -9.19772163e-02 8.00447166e-01
1.45055664e+00 -9.27320048e-02 8.44032884e-01 7.47435987e-01
6.82943642e-01 3.55469972e-01 6.73903823e-01 1.91212907e-01
1.99520096e-01 5.62607050e-01 9.35306549e-01 -3.89346182e-01
-4.94510949e-01 2.32322246e-01 3.74339730e-01 3.01680751e-02
5.30238412e-02 -3.76920402e-01 -1.07475221e+00 8.39106023e-01
-1.55946362e+00 -1.07435501e+00 -5.20578563e-01 2.14651370e+00
7.12594807e-01 5.64098239e-01 1.97356999e-01 2.94918090e-01
4.51390445e-01 1.72896519e-01 -7.22446322e-01 -3.68405700e-01
-3.06295067e-01 -1.81030214e-01 1.06418943e+00 2.54881442e-01
-1.44265699e+00 7.82662272e-01 8.01919651e+00 6.02555513e-01
-9.90320981e-01 1.56222016e-01 7.68313348e-01 -2.88869649e-01
3.03821146e-01 -5.86451709e-01 -9.39692140e-01 5.24745405e-01
1.05711889e+00 2.34862134e-01 1.21895865e-01 1.01885772e+00
3.18385303e-01 -2.82626390e-01 -1.06102586e+00 1.02102101e+00
1.85508922e-01 -1.24719787e+00 -2.02772766e-01 -1.37006223e-01
1.00228775e+00 7.79633820e-01 3.65602851e-01 3.29117745e-01
6.48203790e-01 -1.09081268e+00 9.68908429e-01 3.78961936e-02
8.93725812e-01 -6.09298468e-01 7.03063905e-01 1.60538331e-01
-8.38348925e-01 -2.41560385e-01 -6.69742048e-01 1.48190483e-02
-2.16107011e-01 6.14303172e-01 -6.94199741e-01 -2.07882957e-03
1.33955657e+00 5.25067329e-01 -1.29201639e+00 1.36153948e+00
-3.02712265e-02 6.46430016e-01 -1.79557800e-01 3.43196064e-01
1.99108675e-01 4.27107960e-01 5.71595013e-01 1.74445355e+00
-1.76286828e-02 -2.47678101e-01 -7.00498372e-02 6.71138406e-01
-1.12997614e-01 -4.93776530e-01 -7.65958667e-01 5.10742426e-01
3.11169535e-01 1.11745632e+00 -6.38233006e-01 -4.54170346e-01
-6.07044220e-01 8.46877158e-01 2.91220039e-01 4.76132870e-01
-1.06878412e+00 -3.27516019e-01 1.20964932e+00 -9.00411140e-03
3.49737585e-01 -4.45928991e-01 -5.18661380e-01 -8.94407392e-01
1.30182236e-01 -1.24811602e+00 -8.77784006e-03 -8.99603724e-01
-1.12409103e+00 2.93000549e-01 6.30754828e-02 -1.17299473e+00
1.67047694e-01 -9.67166960e-01 -5.98989904e-01 5.15845001e-01
-1.85474288e+00 -8.88043880e-01 -7.61808336e-01 4.29801822e-01
6.59155786e-01 -1.92896798e-01 3.44228715e-01 4.28937614e-01
-8.68372321e-01 6.83193386e-01 2.62282431e-01 3.41061324e-01
8.09605777e-01 -1.44827700e+00 1.07406867e+00 1.29998267e+00
1.87176585e-01 2.05825984e-01 1.18712449e+00 -3.11624289e-01
-1.33212197e+00 -1.69904876e+00 3.25519592e-01 -1.07693362e+00
4.58997995e-01 -4.49431181e-01 -9.48371470e-01 6.22866273e-01
3.23827356e-01 5.41184604e-01 1.40442505e-01 -1.31858036e-01
-7.23298252e-01 -3.44253808e-01 -1.08835936e+00 6.55761898e-01
1.06441760e+00 -3.62164140e-01 -3.94089729e-01 5.05119443e-01
6.75436378e-01 -4.92244869e-01 -4.20761585e-01 5.23008764e-01
3.74466509e-01 -1.37732208e+00 1.08601499e+00 -6.15771711e-01
2.48469308e-01 -5.62238395e-01 -1.97495937e-01 -1.11809552e+00
-3.33517045e-01 -4.94338721e-01 2.35631084e-03 9.29456234e-01
4.16768759e-01 -5.36347330e-01 7.22663462e-01 4.12535906e-01
-2.92567611e-01 -1.77850336e-01 -8.31724823e-01 -1.06673300e+00
4.62721772e-02 -9.02419269e-01 2.93868154e-01 6.46702170e-01
-7.17384577e-01 -2.69129992e-01 -2.57397383e-01 5.19418776e-01
8.84004951e-01 -5.44139326e-01 1.27382338e+00 -9.07508969e-01
-9.48715303e-03 -5.36927700e-01 -7.21348643e-01 -7.53754795e-01
-3.04025739e-01 -3.04507136e-01 4.51740652e-01 -1.20936131e+00
2.40989178e-01 -3.57012063e-01 -3.97311777e-01 5.22940338e-01
-4.75015104e-01 9.73259747e-01 2.21872866e-01 2.69061446e-01
-9.35411751e-01 1.11804985e-01 1.02776694e+00 -3.71594369e-01
2.93221533e-01 -2.11730257e-01 -5.95570266e-01 6.50519729e-01
7.97716618e-01 -6.15402162e-01 -1.97368950e-01 -8.65854263e-01
4.35135029e-02 -6.23533964e-01 8.11085105e-01 -1.45446420e+00
-8.36038888e-02 -5.97851761e-02 6.22064769e-01 -5.58637679e-01
2.79200703e-01 -5.31464696e-01 -2.57518083e-01 5.76379418e-01
-2.72090793e-01 3.00571740e-01 6.65876150e-01 6.87065065e-01
-8.07369575e-02 -1.82782765e-02 1.17901421e+00 -1.46001697e-01
-1.08282900e+00 2.03718245e-01 -4.56688762e-01 2.75400102e-01
1.11525655e+00 -3.46571386e-01 -7.21207380e-01 -1.84635624e-01
-1.91953540e-01 1.63492814e-01 6.98567986e-01 8.73483121e-01
3.90144616e-01 -1.19754040e+00 -9.76942301e-01 2.20747232e-01
5.55495441e-01 1.02589754e-02 -4.34946828e-02 5.28348386e-01
-8.52357268e-01 4.10599977e-01 -3.53763431e-01 -9.60891306e-01
-1.44685900e+00 5.53193152e-01 5.93806207e-01 2.72721738e-01
-3.93539727e-01 1.10436416e+00 3.42827201e-01 -2.24374339e-01
5.46204150e-01 -4.56659406e-01 2.30008677e-01 -2.61020690e-01
7.60004997e-01 3.70596170e-01 4.97475684e-01 -7.49029815e-01
-4.17273164e-01 2.68883675e-01 -1.36325315e-01 7.05460235e-02
9.90792572e-01 -3.86559628e-02 3.01726967e-01 -2.35144654e-03
1.12939739e+00 -3.98042887e-01 -1.71509635e+00 -1.22135364e-01
-1.31383300e-01 -6.36987209e-01 1.02414697e-01 -7.94519305e-01
-1.07734156e+00 8.01767528e-01 1.05995917e+00 1.95575863e-01
1.00168908e+00 -1.60856590e-01 3.24451685e-01 6.03812754e-01
2.28418246e-01 -9.60114837e-01 1.80911183e-01 5.33781707e-01
1.06283867e+00 -1.73781955e+00 7.60664865e-02 -3.95548940e-02
-4.74068403e-01 6.28748000e-01 9.48966682e-01 -2.19711393e-01
4.24732447e-01 6.16661906e-01 4.74988759e-01 -6.55901581e-02
-7.71455824e-01 -3.96954477e-01 2.40171075e-01 1.07781959e+00
7.78650539e-03 -1.17686078e-01 3.25018078e-01 -8.50424618e-02
-2.39533573e-01 -3.48720551e-01 6.97029948e-01 8.99310172e-01
-6.75732732e-01 -5.71257055e-01 -7.48748243e-01 4.07517970e-01
-5.38430154e-01 7.89538920e-02 -4.53201085e-01 8.42790842e-01
4.16943580e-01 1.19172716e+00 2.31242537e-01 -1.72529414e-01
4.54383969e-01 -3.40623140e-01 3.50279450e-01 -5.80233634e-01
-3.70599389e-01 -2.47632906e-01 1.31533191e-01 -8.29934001e-01
-3.98148388e-01 -7.56546557e-01 -8.33766282e-01 -4.39403117e-01
-3.30636352e-01 -5.72480500e-01 8.51017773e-01 7.12667406e-01
2.26634115e-01 5.39388180e-01 3.27427775e-01 -1.16141617e+00
-5.10107815e-01 -8.99497509e-01 -2.73673415e-01 6.77036703e-01
8.83815885e-01 -6.56402886e-01 -5.21659255e-01 2.81484514e-01] | [8.156719207763672, -1.4017155170440674] |
f2fef493-2a35-4950-989d-bc7c4aa03b98 | generalizable-person-re-identification-via-1 | 2212.02398 | null | https://arxiv.org/abs/2212.02398v1 | https://arxiv.org/pdf/2212.02398v1.pdf | Generalizable Person Re-Identification via Viewpoint Alignment and Fusion | In the current person Re-identification (ReID) methods, most domain generalization works focus on dealing with style differences between domains while largely ignoring unpredictable camera view change, which we identify as another major factor leading to a poor generalization of ReID methods. To tackle the viewpoint change, this work proposes to use a 3D dense pose estimation model and a texture mapping module to map the pedestrian images to canonical view images. Due to the imperfection of the texture mapping module, the canonical view images may lose the discriminative detail clues from the original images, and thus directly using them for ReID will inevitably result in poor performance. To handle this issue, we propose to fuse the original image and canonical view image via a transformer-based module. The key insight of this design is that the cross-attention mechanism in the transformer could be an ideal solution to align the discriminative texture clues from the original image with the canonical view image, which could compensate for the low-quality texture information of the canonical view image. Through extensive experiments, we show that our method can lead to superior performance over the existing approaches in various evaluation settings. | ['Yanning Zhang', 'Peng Wang', 'Shizhou Zhang', 'Ruiqi Wu', 'Guosheng Lin', 'Liying Gao', 'Lingqiao Liu', 'Bingliang Jiao'] | 2022-12-05 | null | null | null | null | ['person-re-identification', 'generalizable-person-re-identification'] | ['computer-vision', 'computer-vision'] | [-1.76217884e-01 -3.27306271e-01 1.13732517e-01 -3.92065883e-01
-2.42506489e-01 -5.00466168e-01 4.39475209e-01 -5.11005938e-01
-2.06137285e-01 4.97710109e-01 3.01585019e-01 2.54026264e-01
3.55017453e-01 -5.92417955e-01 -6.31159246e-01 -7.78942883e-01
6.35819554e-01 2.44373128e-01 2.57139951e-01 -3.56011927e-01
1.13711864e-01 1.63583711e-01 -1.59786546e+00 1.61032319e-01
9.40953732e-01 8.01868498e-01 3.15547317e-01 3.47644091e-02
-1.93179637e-01 1.13881432e-01 -6.08406901e-01 -7.03664362e-01
5.17428994e-01 -1.87113658e-01 -3.79353762e-01 2.77585834e-01
6.10470414e-01 -6.56779528e-01 -5.69427788e-01 1.36533284e+00
6.45791948e-01 6.90436587e-02 4.09154534e-01 -1.06553400e+00
-7.38535523e-01 4.86608557e-02 -8.75812829e-01 8.42326209e-02
7.33619094e-01 -2.65447684e-02 4.41383362e-01 -1.02694798e+00
6.48111165e-01 1.73909473e+00 4.98054862e-01 5.64030647e-01
-1.12447035e+00 -7.38776982e-01 7.36896455e-01 6.08470500e-01
-1.55002356e+00 -4.86919671e-01 1.05399299e+00 -2.61181742e-01
3.59077871e-01 1.91660374e-01 8.54339302e-01 1.39179265e+00
1.67902350e-01 8.83651614e-01 1.36066318e+00 -8.12488273e-02
-1.19174376e-01 5.86008847e-01 -1.49270790e-02 3.47172439e-01
4.69805717e-01 1.55657560e-01 -4.96992052e-01 1.72882840e-01
8.43275666e-01 3.23779613e-01 -4.88688350e-01 -6.20875001e-01
-1.01782751e+00 2.49205574e-01 6.22975230e-01 -1.46829695e-01
-7.16849742e-03 -4.88559127e-01 4.08206761e-01 2.64367402e-01
4.97981429e-01 7.76961595e-02 -1.77459449e-01 1.01336546e-01
-2.96975017e-01 3.54032993e-01 3.45193595e-01 1.20838189e+00
6.97430372e-01 -1.92663789e-01 -1.84130073e-02 8.80428851e-01
3.08443099e-01 6.60754621e-01 4.78891790e-01 -3.51397365e-01
8.07220161e-01 7.99072385e-01 3.06282192e-01 -1.25819850e+00
-2.37608954e-01 -5.82131863e-01 -8.50788534e-01 -5.98271005e-02
6.06522560e-01 8.49805102e-02 -5.98028779e-01 1.75611365e+00
4.95202482e-01 -3.91448289e-02 -1.76480234e-01 1.41868794e+00
7.38153398e-01 1.26176819e-01 -8.09732154e-02 2.34419331e-02
1.46812546e+00 -8.33092928e-01 -5.44949770e-01 -4.27835107e-01
2.56043673e-01 -8.42692494e-01 1.13380218e+00 2.98100859e-01
-6.47470534e-01 -1.04406440e+00 -1.21380830e+00 -5.71466237e-02
-3.51618618e-01 3.46482068e-01 2.36860082e-01 6.95396125e-01
-6.86397970e-01 2.52226025e-01 -5.11588335e-01 -7.07837343e-01
1.58698395e-01 1.07023858e-01 -5.59035003e-01 -4.36971724e-01
-1.11165249e+00 8.44118714e-01 2.13193804e-01 4.97348547e-01
-3.68932784e-01 -3.44558716e-01 -7.00987697e-01 -1.63278461e-01
3.09121341e-01 -8.55776012e-01 7.33050227e-01 -1.18433630e+00
-1.35849690e+00 7.54082620e-01 -4.74153548e-01 1.48875147e-01
8.03538978e-01 -4.70135033e-01 -4.81724679e-01 -1.09240964e-01
3.71743321e-01 4.17195767e-01 9.23948884e-01 -1.53413045e+00
-5.63117385e-01 -9.56251442e-01 9.78275090e-02 6.77651644e-01
-4.05364543e-01 -2.98843235e-01 -6.67238474e-01 -7.95276821e-01
4.46364164e-01 -9.76464272e-01 8.17438066e-02 -2.10858375e-01
-3.88564318e-01 1.77642563e-03 9.40620244e-01 -8.24311256e-01
8.33075404e-01 -2.15840650e+00 3.24428052e-01 -5.49828745e-02
1.88734159e-01 9.81320068e-02 2.08823383e-02 1.25107825e-01
-1.32251203e-01 -1.98066041e-01 5.44544518e-01 -4.38655466e-01
-3.05272520e-01 7.38407373e-02 -3.02026182e-01 6.50170267e-01
-3.95387001e-02 7.74741530e-01 -8.65700603e-01 -3.21722567e-01
2.23937407e-01 4.05035615e-01 -2.82915622e-01 3.64532828e-01
2.67264575e-01 8.95521700e-01 -5.56834221e-01 5.73449552e-01
1.33333886e+00 9.08941180e-02 1.45620123e-01 -5.06162882e-01
4.83420491e-02 4.00994308e-02 -1.16121089e+00 1.77007341e+00
-2.16771603e-01 3.78249705e-01 1.24299429e-01 -8.83917451e-01
1.02879405e+00 1.24527358e-01 2.39890426e-01 -9.03058529e-01
1.48736462e-01 -2.92274840e-02 -2.27607146e-01 -4.88341659e-01
5.04425943e-01 1.51271131e-02 4.12223265e-02 1.08041577e-01
-3.26415837e-01 4.30539459e-01 -2.66020328e-01 -6.36753663e-02
3.12134236e-01 4.10377920e-01 -2.33096555e-02 -1.72971204e-01
8.17496419e-01 -2.55823195e-01 9.16885912e-01 4.79500711e-01
-4.01774496e-01 7.25170195e-01 2.98588783e-01 -8.59014511e-01
-1.14315593e+00 -1.05804479e+00 -7.13039264e-02 7.71991909e-01
9.28193331e-01 -2.78791040e-01 -8.46799672e-01 -7.40251422e-01
-6.62672520e-02 1.31926522e-01 -5.55670261e-01 -3.31856400e-01
-5.88646054e-01 -6.98154807e-01 2.55594015e-01 5.75419724e-01
1.18553329e+00 -2.03364193e-01 -2.23704264e-01 2.60193944e-02
-6.16360486e-01 -1.31637955e+00 -7.22457349e-01 -4.51769590e-01
-7.38607407e-01 -1.04975975e+00 -9.51976359e-01 -5.84274709e-01
8.91299605e-01 1.13704741e+00 6.83224499e-01 3.38045582e-02
3.87985185e-02 7.39667043e-02 -5.51499307e-01 -2.32656732e-01
9.80292708e-02 6.61228923e-03 5.41715562e-01 4.58713919e-01
6.62347317e-01 -4.45294708e-01 -8.82371247e-01 7.86209881e-01
-3.81693184e-01 3.73179257e-01 4.39364254e-01 1.17605448e+00
3.02706301e-01 1.17436066e-01 3.23703527e-01 -5.37725031e-01
2.50900179e-01 -1.65918395e-01 -5.00171244e-01 2.30634481e-01
-5.63438237e-01 -2.12673977e-01 7.09207356e-01 -5.12367070e-01
-1.43088591e+00 6.88086525e-02 2.46491525e-02 -5.03290534e-01
-1.97558954e-01 -1.34725999e-02 -1.00651264e+00 -1.20088764e-01
3.68726760e-01 4.57256407e-01 1.04713775e-01 -8.27596724e-01
4.76701930e-02 6.15469098e-01 3.99517089e-01 -6.78025782e-01
9.52608526e-01 7.47388124e-01 -2.04251990e-01 -5.70331514e-01
-7.87204385e-01 -5.10376096e-01 -1.02719712e+00 -2.51368821e-01
8.14108789e-01 -1.33702481e+00 -4.87784922e-01 6.73827350e-01
-1.25572467e+00 3.51359248e-01 3.19975287e-01 4.56652105e-01
-1.58603430e-01 8.38356495e-01 -3.31194192e-01 -6.20943785e-01
2.38745455e-02 -1.42812669e+00 1.33724284e+00 5.48642516e-01
1.31879091e-01 -6.62388861e-01 -2.78071284e-01 5.96554518e-01
2.23719344e-01 -1.55512333e-01 8.33535671e-01 -2.06255406e-01
-5.03409386e-01 -2.40996972e-01 -5.99143982e-01 2.00526401e-01
2.74651259e-01 -5.79966187e-01 -1.29662800e+00 -6.02512896e-01
2.18208998e-01 1.48146361e-01 6.26448333e-01 1.76102236e-01
9.26630974e-01 -7.39408061e-02 -5.80431700e-01 9.09355164e-01
1.22346485e+00 1.67770877e-01 6.59711838e-01 5.89249074e-01
1.16512847e+00 8.03655028e-01 6.99550986e-01 2.98661888e-01
7.35579073e-01 1.27912724e+00 1.69843748e-01 -2.47638494e-01
-1.34705782e-01 -6.36578798e-01 5.00545740e-01 5.80469966e-01
-1.64362326e-01 1.98154580e-02 -4.93583888e-01 2.79643297e-01
-1.90950525e+00 -8.77545714e-01 2.75153872e-02 2.47351956e+00
2.61433005e-01 1.75904613e-02 2.07810611e-01 -3.48294117e-02
9.09431875e-01 -5.96674420e-02 -6.77412689e-01 6.43662140e-02
-2.12137207e-01 -6.69405162e-01 4.65637147e-01 5.92831112e-02
-1.10733628e+00 8.48037839e-01 5.78146791e+00 6.93906188e-01
-1.15093160e+00 -5.73028736e-02 4.90105629e-01 8.11883882e-02
-7.79527426e-02 3.73825543e-02 -8.82845700e-01 7.47318029e-01
1.37364522e-01 3.34774777e-02 2.84357578e-01 9.42761123e-01
2.51112819e-01 -4.08214182e-02 -1.16381776e+00 1.46000564e+00
2.40158781e-01 -5.15855968e-01 1.99623764e-01 2.84926951e-01
4.40122455e-01 -5.79829752e-01 2.22430080e-01 1.96303666e-01
-1.65916145e-01 -7.96870470e-01 7.45784581e-01 4.08194184e-01
7.68912077e-01 -6.39162540e-01 1.04138875e+00 3.45400274e-01
-1.50997186e+00 -1.34039849e-01 -8.31131518e-01 -2.05746457e-01
-1.73101611e-02 3.74041080e-01 -6.10145867e-01 1.08666682e+00
1.07096481e+00 9.47824359e-01 -8.21661711e-01 8.69793296e-01
6.27795160e-02 -6.48039132e-02 -1.19431473e-01 3.12869549e-01
-3.89804870e-01 -3.38493884e-01 7.74854660e-01 8.23588610e-01
2.96133161e-01 -1.44239724e-01 4.07335371e-01 7.77006686e-01
2.88904905e-01 4.52970304e-02 -8.37341905e-01 5.55614710e-01
4.08090621e-01 9.23420966e-01 -5.50680637e-01 -3.94425809e-01
-6.38001561e-01 1.36390316e+00 2.19007343e-01 5.66320419e-01
-5.85281253e-01 -1.57169029e-02 8.76990795e-01 3.41027468e-01
1.73318103e-01 -1.77431673e-01 -4.88681823e-01 -1.88053095e+00
3.93358380e-01 -9.52411473e-01 2.05580279e-01 -6.40027046e-01
-1.45540667e+00 5.93080401e-01 8.61008465e-02 -1.65452814e+00
1.78177938e-01 -5.85119665e-01 -4.11273926e-01 1.09020758e+00
-1.27432072e+00 -1.43602979e+00 -7.22581327e-01 6.16136551e-01
7.27295339e-01 -4.38086092e-01 4.99167144e-01 4.80618715e-01
-9.00551677e-01 1.08401275e+00 1.13056146e-01 1.28279358e-01
1.17246807e+00 -1.12729979e+00 4.63431060e-01 9.41187978e-01
-3.58223706e-01 8.13392341e-01 6.75558686e-01 -7.41960049e-01
-1.66627467e+00 -1.00909400e+00 3.73999685e-01 -6.81757450e-01
1.86451543e-02 -5.49855590e-01 -9.12788451e-01 4.56162214e-01
-1.57730579e-01 -2.72644311e-01 3.52975219e-01 8.22692364e-02
-5.90466499e-01 -4.79218274e-01 -9.57293034e-01 7.46676147e-01
1.31976533e+00 -4.54604566e-01 -6.01420343e-01 -2.15206191e-01
3.51815164e-01 -5.97494543e-01 -6.09588802e-01 2.70732999e-01
9.23229098e-01 -1.01709414e+00 1.16514874e+00 -1.95250243e-01
-1.19079230e-02 -5.74864507e-01 -1.10472254e-01 -1.40900409e+00
-4.61316228e-01 -1.36849657e-01 3.53649646e-01 1.45901990e+00
-2.84430593e-01 -8.09104562e-01 6.99442267e-01 5.62021255e-01
2.51320392e-01 -3.36218536e-01 -1.01417184e+00 -7.35258222e-01
-1.93912685e-02 3.56088914e-02 9.59394038e-01 6.94238067e-01
-1.15297899e-01 3.68570268e-01 -6.95674062e-01 3.25268388e-01
7.85974264e-01 2.07200885e-01 1.18067920e+00 -1.36395586e+00
-1.54044166e-01 -2.33873278e-01 -5.45560062e-01 -1.56431544e+00
6.50019497e-02 -5.07323265e-01 -1.20635323e-01 -1.03738952e+00
5.69935560e-01 -4.56685245e-01 -3.95024056e-03 -9.14143622e-02
-4.82634068e-01 5.47896028e-02 2.41376728e-01 4.64706004e-01
-3.50580305e-01 8.09811592e-01 1.49802184e+00 -2.72009104e-01
-1.94560215e-01 -2.17051171e-02 -1.01823461e+00 6.28531933e-01
4.15767044e-01 -2.64138486e-02 -4.91643399e-01 -7.04585612e-01
-8.10249969e-02 -1.86126441e-01 6.60572290e-01 -9.00192261e-01
2.22865745e-01 -1.22928709e-01 9.43241835e-01 -5.63300014e-01
4.44347680e-01 -9.32321429e-01 1.27947345e-01 1.58245400e-01
1.47577241e-01 2.93910176e-01 5.41658215e-02 8.63669157e-01
-1.98185965e-01 2.71365225e-01 7.67165124e-01 -2.35534683e-01
-8.11508775e-01 3.19008917e-01 1.84227768e-02 -3.60762686e-01
7.50880957e-01 -6.50767684e-01 -3.92612040e-01 -3.44417989e-01
-3.59135956e-01 2.62693554e-01 9.92691398e-01 7.88419545e-01
6.59590304e-01 -1.60934949e+00 -5.58136225e-01 6.21842682e-01
2.17937216e-01 -5.13071194e-02 6.50856197e-01 7.84404337e-01
-1.22723676e-01 3.50967884e-01 -4.60604429e-01 -7.08561957e-01
-1.25534081e+00 7.67333627e-01 5.23379326e-01 -6.73708087e-03
-8.99183750e-01 5.33515573e-01 8.99021268e-01 -2.78919399e-01
1.63423643e-01 1.37981206e-01 -3.42130780e-01 -1.27086341e-01
7.52526343e-01 3.22801203e-01 1.36251387e-03 -1.03152013e+00
-4.68399853e-01 1.10394657e+00 -4.39530581e-01 8.21115635e-03
8.86988282e-01 -8.50195646e-01 2.11557850e-01 1.80593684e-01
1.14914191e+00 -3.75848301e-02 -1.34503257e+00 -4.36613888e-01
-4.19258058e-01 -1.04873836e+00 -2.84246773e-01 -3.64685982e-01
-9.13097560e-01 1.02538908e+00 1.02225101e+00 -3.21397305e-01
1.11746049e+00 -3.32167476e-01 8.40802729e-01 1.74155623e-01
7.75736451e-01 -1.22110558e+00 6.72295839e-02 3.03943425e-01
7.20847070e-01 -1.50086558e+00 3.12293712e-02 -6.97242796e-01
-7.09063530e-01 1.11343360e+00 1.07778645e+00 2.57936064e-02
4.15346622e-01 -2.77218938e-01 1.11570492e-01 1.10322766e-01
-3.17914754e-01 -8.10953230e-02 3.05021614e-01 9.65426087e-01
1.12854742e-01 3.14258635e-02 -4.67662886e-02 8.67254078e-01
-2.81813651e-01 -3.21851134e-01 3.04875910e-01 4.52999592e-01
-8.64058584e-02 -1.35564756e+00 -7.77372777e-01 9.01065543e-02
-1.96813539e-01 3.62865388e-01 -5.15404761e-01 5.71978509e-01
2.63672531e-01 1.00062954e+00 -1.01882897e-01 -9.04060304e-01
6.79490626e-01 -4.33005430e-02 5.69042563e-01 -3.84611964e-01
-1.63903266e-01 2.95864016e-01 -1.51558980e-01 -4.72529292e-01
-2.30531588e-01 -6.93080068e-01 -5.25112510e-01 -5.90515256e-01
-2.33077288e-01 -1.52649105e-01 1.92668810e-01 9.77089405e-01
3.29124004e-01 1.23741873e-01 7.30523348e-01 -1.02228129e+00
-4.49067682e-01 -8.20366263e-01 -5.99283457e-01 7.79680729e-01
2.46683791e-01 -1.20745075e+00 -5.28398007e-02 -1.60328835e-01] | [14.706416130065918, 0.9547355771064758] |
1a5c8b98-b735-4a72-8334-8d2bc4afb54e | towards-modern-card-games-with-large-scale | 2206.12700 | null | https://arxiv.org/abs/2206.12700v2 | https://arxiv.org/pdf/2206.12700v2.pdf | Towards Modern Card Games with Large-Scale Action Spaces Through Action Representation | Axie infinity is a complicated card game with a huge-scale action space. This makes it difficult to solve this challenge using generic Reinforcement Learning (RL) algorithms. We propose a hybrid RL framework to learn action representations and game strategies. To avoid evaluating every action in the large feasible action set, our method evaluates actions in a fixed-size set which is determined using action representations. We compare the performance of our method with the other two baseline methods in terms of their sample efficiency and the winning rates of the trained models. We empirically show that our method achieves an overall best winning rate and the best sample efficiency among the three methods. | ['Yan Zhang', 'Huan Lu', 'Xiongjie Xie', 'Yuanyuan Qin', 'Yiting Xie', 'Site Li', 'Tianyu Shi', 'Zhiyuan Yao'] | 2022-06-25 | null | null | null | null | ['card-games'] | ['playing-games'] | [-2.99211424e-02 1.42313600e-01 -5.53326666e-01 3.30517352e-01
-9.61427450e-01 -6.46145284e-01 5.06363988e-01 -4.87719387e-01
-8.36714804e-01 1.01887393e+00 3.79292905e-01 -2.16367573e-01
-3.19370955e-01 -9.22087789e-01 -4.16617334e-01 -5.46488166e-01
-4.03263457e-02 6.49932086e-01 3.49153608e-01 -5.31161189e-01
4.40174162e-01 1.32581532e-01 -1.54849029e+00 1.74619555e-01
5.70212364e-01 9.59017456e-01 1.17179580e-01 9.49899852e-01
1.88810945e-01 1.43330550e+00 -8.10680509e-01 -2.88957506e-01
6.44468784e-01 -7.11712837e-01 -9.65050519e-01 -1.12353265e-01
-3.88971478e-01 -8.19503784e-01 -4.97663260e-01 7.29309142e-01
5.85179150e-01 6.54057205e-01 4.47113812e-01 -1.20724666e+00
-2.06637561e-01 6.80407763e-01 -4.56915110e-01 9.67767239e-02
5.00429034e-01 4.24830794e-01 1.12252009e+00 -3.32939267e-01
5.13156891e-01 1.28768063e+00 1.88177481e-01 8.93493891e-01
-1.04510903e+00 -5.79349279e-01 2.53975987e-01 2.01739371e-01
-9.50810194e-01 -2.42019370e-01 4.01357114e-01 2.25268081e-02
1.22063267e+00 -4.13871258e-02 8.74221623e-01 1.03087401e+00
-2.00235266e-02 1.08700907e+00 1.00315130e+00 -3.08113426e-01
7.26935446e-01 -6.47518158e-01 -4.12150145e-01 5.73299170e-01
-1.61977947e-01 4.79043961e-01 -4.03330326e-01 -7.46355206e-02
1.31820583e+00 4.01431620e-02 3.70937511e-02 -4.83764499e-01
-9.82359409e-01 1.20292842e+00 1.77374989e-01 3.51361409e-02
-5.70680737e-01 7.06495643e-01 3.05983484e-01 4.65792596e-01
-1.94919463e-02 8.28137040e-01 -4.24652100e-01 -9.05449212e-01
-5.11567950e-01 6.60994530e-01 7.39384890e-01 5.47995269e-01
2.64551371e-01 2.02613637e-01 -4.44100678e-01 8.06363940e-01
-5.42621687e-02 2.15296254e-01 7.04602599e-01 -1.69049144e+00
6.73258364e-01 4.98185903e-01 6.16055489e-01 -4.90873098e-01
-4.34716403e-01 -7.63949305e-02 -2.56656915e-01 7.21240163e-01
5.03840923e-01 -3.79517198e-01 -4.63239133e-01 2.00133896e+00
2.52166927e-01 2.24552274e-01 2.16531917e-01 6.81193829e-01
3.74316275e-01 6.04597449e-01 8.35277438e-02 -2.45938212e-01
7.81750619e-01 -1.18322933e+00 -5.25011837e-01 -3.95810068e-01
7.56160259e-01 -1.86581329e-01 1.14707196e+00 4.37714875e-01
-1.38419724e+00 -2.07366049e-01 -9.64486957e-01 2.33974680e-01
1.24655858e-01 1.66454375e-01 9.81241107e-01 4.84740227e-01
-9.66606081e-01 8.80419672e-01 -7.59924889e-01 1.00308865e-01
5.73061347e-01 6.14959598e-01 -5.45252822e-02 -4.31710668e-02
-1.09264433e+00 9.72439587e-01 6.34164333e-01 -2.75189906e-01
-1.16223216e+00 -3.63020003e-01 -7.53640294e-01 2.48425052e-01
1.08781564e+00 -2.61685133e-01 1.88619781e+00 -6.16193712e-01
-2.32565880e+00 2.71456778e-01 3.32132876e-01 -5.59071839e-01
7.25122571e-01 -2.49529779e-01 1.84370697e-01 5.69878295e-02
-1.95079856e-02 6.49741411e-01 4.67250526e-01 -6.20182514e-01
-8.20520461e-01 7.64252990e-02 8.04796815e-01 6.57244265e-01
1.98509209e-02 -6.84961211e-03 -4.03827190e-01 -4.54377204e-01
-2.75012940e-01 -1.02870440e+00 -6.91566348e-01 -3.27098548e-01
1.53017119e-01 -4.86014485e-01 9.50461254e-03 -2.58440793e-01
1.31722271e+00 -1.87053919e+00 2.29252264e-01 -1.36032850e-01
1.42163232e-01 2.69611716e-01 -5.24361610e-01 4.92504716e-01
2.60642231e-01 -5.13543859e-02 2.57125646e-01 1.66105658e-01
3.15960050e-01 4.51490104e-01 -2.71909356e-01 1.81126431e-01
-1.02081701e-01 1.19908285e+00 -1.13355243e+00 -2.27990255e-01
2.77526200e-01 -1.29954994e-01 -1.03011549e+00 4.51826632e-01
-3.42739165e-01 2.47514054e-01 -6.77287400e-01 3.86117518e-01
9.28563476e-02 -6.73444644e-02 6.77322149e-01 5.87349892e-01
3.36789608e-01 4.40512687e-01 -1.43254304e+00 1.51532388e+00
-4.18790162e-01 4.10321504e-02 -3.90455008e-01 -9.63894367e-01
7.15102315e-01 3.00125122e-01 7.24219859e-01 -1.00216866e+00
1.25274301e-01 1.06436893e-01 2.14902923e-01 -1.07749254e-01
5.96590042e-01 -1.03921555e-01 -4.48926330e-01 8.97475839e-01
8.31444189e-02 -1.66687459e-01 4.50715661e-01 3.45526077e-03
1.49670136e+00 5.91739893e-01 7.97402740e-01 1.63058460e-01
1.77363038e-01 -9.49886516e-02 5.79809129e-01 1.14418244e+00
-3.90359074e-01 7.89838582e-02 1.00176263e+00 -6.22745395e-01
-8.05225790e-01 -9.82278109e-01 5.86273491e-01 1.58259618e+00
-2.91859005e-02 -5.87337613e-01 -5.35808206e-01 -8.54024887e-01
-1.53940976e-01 5.98886609e-01 -7.92863667e-01 -4.43509996e-01
-7.49498844e-01 -3.21675628e-01 4.50568855e-01 9.16167736e-01
5.83431125e-01 -1.59647262e+00 -9.58401203e-01 4.21430230e-01
-1.87267125e-01 -7.57608593e-01 -3.91549706e-01 6.70266300e-02
-8.02467287e-01 -1.31864333e+00 -5.10177493e-01 -4.81325209e-01
2.69844264e-01 1.37292922e-01 1.17046368e+00 -1.06455117e-01
-4.25630212e-02 3.29429805e-01 -3.97140145e-01 -2.33647630e-01
-2.34284386e-01 -2.05440193e-01 8.99764150e-02 -5.97638130e-01
1.96703345e-01 -3.04666966e-01 -6.98453724e-01 4.13563609e-01
-6.62458777e-01 -4.49659303e-02 4.50749159e-01 7.88498700e-01
4.40526843e-01 9.00620520e-02 6.28100514e-01 -5.41175783e-01
1.14524162e+00 -3.34487975e-01 -8.52326155e-01 2.44218677e-01
-4.21277583e-01 3.36207569e-01 5.60305357e-01 -7.35519767e-01
-7.47453094e-01 4.84536663e-02 -2.24218462e-02 -2.55850673e-01
3.66434097e-01 3.21135402e-01 7.24046156e-02 2.35664159e-01
7.36658096e-01 1.96185231e-01 4.41364124e-02 -1.71588838e-01
5.51487923e-01 3.21136117e-01 3.49115580e-01 -7.79878795e-01
3.99821669e-01 -1.04046248e-01 -1.09440319e-01 -4.98505160e-02
-7.42845595e-01 -1.04667842e-01 -2.18743458e-01 -3.11520338e-01
5.83437383e-01 -7.76504695e-01 -1.33603013e+00 2.19600976e-01
-6.40794337e-01 -9.72935438e-01 -7.11417317e-01 5.37083745e-01
-1.33410490e+00 1.36665076e-01 -7.17555106e-01 -1.10166395e+00
-6.32052049e-02 -1.15222955e+00 8.55810225e-01 2.12918594e-01
-3.07150006e-01 -6.04202867e-01 4.48802173e-01 2.32269064e-01
2.89552569e-01 9.65256318e-02 5.67260802e-01 -4.96005177e-01
-3.66913050e-01 -1.06328242e-01 1.45328164e-01 3.51841487e-02
7.51175359e-02 -4.33512628e-01 -3.99872005e-01 -3.48397881e-01
-2.19301671e-01 -1.06685257e+00 7.04194546e-01 4.62655067e-01
1.39864028e+00 -3.16938937e-01 1.98080227e-01 2.59402037e-01
1.36561418e+00 6.28922164e-01 9.59753990e-01 6.10727668e-01
9.65031087e-02 1.18597895e-01 9.59351480e-01 9.50375140e-01
1.84399933e-01 9.13760066e-01 4.27220136e-01 3.55685055e-01
3.09731066e-01 -5.77652395e-01 6.80668533e-01 2.12278187e-01
-5.16205251e-01 -2.07524404e-01 -5.67471981e-01 2.77424335e-01
-2.38808107e+00 -1.40948915e+00 8.66389513e-01 2.35560298e+00
9.40926731e-01 1.88243061e-01 5.83518744e-01 1.65403590e-01
3.52825761e-01 2.73970813e-01 -7.89895058e-01 -6.82812333e-01
2.72493958e-01 7.79603601e-01 3.52402955e-01 4.88980770e-01
-1.12262559e+00 1.34097385e+00 8.02485371e+00 1.07000744e+00
-4.51219559e-01 -1.21069655e-01 4.09876019e-01 -7.40033388e-01
9.29382741e-02 -2.15092599e-01 -5.43424189e-01 2.82533646e-01
1.00800169e+00 -3.62624407e-01 1.07034576e+00 1.15755343e+00
1.86853066e-01 -2.43804082e-01 -9.94828463e-01 1.00866890e+00
-2.15838268e-01 -1.41854763e+00 -2.33728841e-01 3.15052271e-01
7.22538233e-01 -1.52383193e-01 -8.03294033e-02 1.19675875e+00
1.32040298e+00 -1.26314282e+00 5.56564331e-01 1.89081341e-01
7.80176878e-01 -1.01372266e+00 5.49219310e-01 4.06025797e-01
-1.11984181e+00 -5.92774034e-01 -4.50217068e-01 -6.07436299e-01
-1.09124810e-01 -4.41134244e-01 -5.81581295e-01 5.06180041e-02
3.12654972e-01 5.61093152e-01 -2.47103736e-01 9.26591814e-01
-5.69081903e-01 5.08749604e-01 -1.46590933e-01 -3.71483982e-01
5.61173677e-01 -3.60686183e-01 -4.14384268e-02 4.39783275e-01
2.16286451e-01 3.95352989e-01 5.24785817e-01 6.43038273e-01
-9.58241299e-02 -5.18391952e-02 -5.45693159e-01 -3.93837273e-01
4.74396288e-01 8.75654340e-01 -5.78784823e-01 -1.59294680e-01
-2.38204166e-01 7.63645411e-01 6.66768789e-01 1.24793045e-01
-1.06281638e+00 -1.01127505e-01 8.53819370e-01 -3.21429253e-01
5.01483560e-01 -1.29428983e-01 2.17354447e-01 -1.06201577e+00
-1.13802880e-01 -1.10870612e+00 5.44454277e-01 -6.39467239e-01
-8.52630675e-01 2.51131147e-01 -5.49632683e-02 -1.41528440e+00
-1.04975462e+00 -6.50598466e-01 -5.29532075e-01 3.75015646e-01
-1.05062008e+00 -5.16566277e-01 2.01458126e-01 6.12478137e-01
7.34795690e-01 -3.77999187e-01 9.01012540e-01 -2.37439275e-01
-6.03694201e-01 5.74557662e-01 2.50251263e-01 1.93996489e-01
1.39640123e-01 -1.24496984e+00 2.79326081e-01 4.34282482e-01
-9.00404826e-02 7.24385828e-02 2.82630861e-01 -3.95614952e-01
-1.30462313e+00 -6.59929037e-01 1.18176073e-01 -3.45211238e-01
7.14758635e-01 -8.81796181e-02 -2.39091650e-01 7.51941860e-01
-1.76481992e-01 -5.22559583e-02 5.96408844e-01 2.59580851e-01
-1.71921760e-01 1.80937767e-01 -1.02332568e+00 1.03424740e+00
1.14976346e+00 -4.34808582e-01 -6.85772359e-01 2.04427928e-01
4.71536875e-01 -4.64962959e-01 -6.94268167e-01 5.29185124e-02
6.13691092e-01 -8.06432009e-01 1.00599670e+00 -1.25254405e+00
7.79895246e-01 4.47873548e-02 -1.16368644e-01 -1.42788851e+00
-5.08111000e-01 -6.53799057e-01 -4.11365628e-01 6.22710586e-01
1.98017269e-01 -5.67316711e-01 1.07814741e+00 6.98273420e-01
3.29031318e-01 -1.03398204e+00 -1.03656805e+00 -1.00539696e+00
2.06017360e-01 -4.21512306e-01 8.22286487e-01 3.24055672e-01
4.78431344e-01 2.13074341e-01 -6.92711473e-01 -5.43619275e-01
2.39820272e-01 3.98462236e-01 8.68594050e-01 -9.49113607e-01
-8.63425732e-01 -7.03987598e-01 -3.02181840e-01 -1.12795222e+00
2.42513597e-01 -4.93647337e-01 4.28333245e-02 -1.49672556e+00
2.84498453e-01 -2.69389242e-01 -6.68665886e-01 6.54780149e-01
-1.39734730e-01 -7.93681592e-02 4.11982238e-01 -7.84877222e-04
-1.25778127e+00 6.65669680e-01 1.35262668e+00 1.71453059e-02
-3.81264299e-01 1.89865142e-01 -8.52787375e-01 6.76253319e-01
1.15346825e+00 -3.61719847e-01 -7.25907087e-01 -1.03437372e-01
2.82546788e-01 5.52730620e-01 -7.50681534e-02 -1.00480568e+00
-1.73175856e-01 -8.32716465e-01 2.29101419e-01 -5.54358065e-02
3.69400382e-01 -2.94540763e-01 -1.74638271e-01 7.21251786e-01
-7.14415371e-01 1.01176493e-01 -5.50394505e-02 5.94501138e-01
8.46221745e-02 -2.92455107e-01 7.28444219e-01 -4.79516000e-01
-8.30949187e-01 3.55520636e-01 -5.45278072e-01 3.49431157e-01
1.28719962e+00 -1.61516830e-01 -2.11686775e-01 -7.25465596e-01
-5.64038575e-01 3.08243483e-01 1.83201894e-01 4.54874486e-01
6.43988252e-01 -1.50812292e+00 -4.61792767e-01 -1.15139335e-01
-4.66104597e-02 -3.53381425e-01 3.19719538e-02 4.36071694e-01
-3.67635787e-01 2.37087548e-01 -6.50261343e-01 1.84864625e-01
-1.05428779e+00 6.49823904e-01 5.66407204e-01 -1.02095008e+00
-6.11412287e-01 5.81500709e-01 7.19150305e-02 -4.81761366e-01
3.22020888e-01 -1.51921153e-01 -5.36942005e-01 -2.96538800e-01
8.13869238e-01 5.42945266e-01 -5.21381855e-01 -1.23814441e-01
-5.16603440e-02 1.38834894e-01 9.36220586e-02 -3.49515587e-01
1.47950077e+00 4.28175926e-01 3.84288400e-01 4.47386838e-02
6.15705907e-01 -3.04936349e-01 -1.68728900e+00 -1.12243600e-01
-9.87413824e-02 -7.22701132e-01 6.61763828e-03 -8.06751728e-01
-1.05346882e+00 3.74387681e-01 4.52540994e-01 -8.20523202e-02
1.05123043e+00 -2.52042472e-01 5.15677631e-01 7.47466981e-01
8.41463685e-01 -1.51860809e+00 5.56062460e-01 6.56565249e-01
7.87115335e-01 -1.08536649e+00 2.14901976e-02 1.50433064e-01
-1.14297485e+00 9.24330890e-01 8.62196922e-01 -6.01587296e-01
1.74175709e-01 1.06780380e-01 -2.62320429e-01 -1.53356278e-03
-1.14201474e+00 -6.41229868e-01 -2.18412086e-01 6.47609770e-01
7.59989768e-02 1.95953846e-01 -5.21734059e-01 8.41525435e-01
-1.81247622e-01 3.80607069e-01 5.80762506e-01 1.09581661e+00
-5.82295954e-01 -1.47654200e+00 -6.78051189e-02 5.37079811e-01
-4.36784089e-01 2.87552565e-01 -3.95112216e-01 7.82505989e-01
-3.33727747e-01 1.01257122e+00 -8.73814523e-02 -5.41974783e-01
3.98111910e-01 -9.69385877e-02 7.67970085e-01 -5.28379858e-01
-6.14003897e-01 -8.86289105e-02 1.19636878e-01 -1.22846508e+00
-1.76412940e-01 -4.48382080e-01 -1.38892460e+00 -4.48612601e-01
1.02459408e-01 -2.33913027e-02 5.97500727e-02 1.06397367e+00
1.74333304e-01 4.78571355e-01 7.97798038e-01 -8.69076014e-01
-1.19835055e+00 -7.87636876e-01 -7.78688312e-01 4.17641371e-01
-1.47125348e-01 -1.07680917e+00 7.83553720e-02 -6.78117633e-01] | [3.8327620029449463, 1.611063838005066] |
72fd2c65-5e41-4ec6-844a-258af88d07f4 | signet-convolutional-siamese-network-for | 1707.02131 | null | http://arxiv.org/abs/1707.02131v2 | http://arxiv.org/pdf/1707.02131v2.pdf | SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification | Offline signature verification is one of the most challenging tasks in
biometrics and document forensics. Unlike other verification problems, it needs
to model minute but critical details between genuine and forged signatures,
because a skilled falsification might often resembles the real signature with
small deformation. This verification task is even harder in writer independent
scenarios which is undeniably fiscal for realistic cases. In this paper, we
model an offline writer independent signature verification task with a
convolutional Siamese network. Siamese networks are twin networks with shared
weights, which can be trained to learn a feature space where similar
observations are placed in proximity. This is achieved by exposing the network
to a pair of similar and dissimilar observations and minimizing the Euclidean
distance between similar pairs while simultaneously maximizing it between
dissimilar pairs. Experiments conducted on cross-domain datasets emphasize the
capability of our network to model forgery in different languages (scripts) and
handwriting styles. Moreover, our designed Siamese network, named SigNet,
exceeds the state-of-the-art results on most of the benchmark signature
datasets, which paves the way for further research in this direction. | ['Umapada Pal', 'J. Ignacio Toledo', 'Anjan Dutta', 'Sounak Dey', 'Josep Llados', 'Suman K. Ghosh'] | 2017-07-07 | null | null | null | null | ['handwriting-verification'] | ['computer-vision'] | [ 4.21447903e-01 -2.15652153e-01 2.54864812e-01 -7.58878291e-01
-4.39643353e-01 -8.25860262e-01 7.73181617e-01 -3.57049495e-01
-2.56971270e-01 3.66824061e-01 -1.45632282e-01 -1.06111526e-01
-3.81295353e-01 -4.92519975e-01 -5.71820021e-01 -8.55609715e-01
-2.85715330e-02 5.15197694e-01 -8.25067014e-02 -2.49570131e-01
5.00099897e-01 7.99198568e-01 -1.17690825e+00 3.17509770e-01
6.67857051e-01 8.84208798e-01 -4.34019834e-01 6.11076057e-01
2.11089179e-01 2.77979463e-01 -4.97235358e-01 -1.22205460e+00
4.57480043e-01 -4.00910437e-01 -6.75865531e-01 -9.53626186e-02
1.03988194e+00 -3.83333355e-01 -5.46723008e-01 1.12005818e+00
5.35033584e-01 -1.57079175e-01 5.09871542e-01 -1.46334529e+00
-1.07490563e+00 6.44141436e-01 -5.50391495e-01 -2.66545445e-01
8.18076134e-02 1.45129502e-01 9.03287351e-01 -8.42755914e-01
6.98561192e-01 1.15237033e+00 9.21615005e-01 6.88320577e-01
-9.16696072e-01 -8.37719977e-01 -1.50198966e-01 4.39240247e-01
-1.32971323e+00 -4.85706687e-01 9.56868827e-01 -1.45297080e-01
1.74013928e-01 2.70668358e-01 1.08738080e-01 1.44550133e+00
2.18845289e-02 8.07276130e-01 1.05717123e+00 -2.02595264e-01
-1.58692256e-01 1.01739645e-01 1.60543308e-01 6.22005165e-01
3.87351155e-01 2.95134664e-01 -7.89335132e-01 -1.46474659e-01
4.30559516e-01 1.72199205e-01 -3.74200284e-01 -3.93416107e-01
-1.14056861e+00 4.67623025e-01 1.75699964e-01 3.25573504e-01
9.14342850e-02 9.07222182e-02 3.22870046e-01 5.27438581e-01
-7.80954733e-02 3.70269924e-01 -1.24478370e-01 -6.03379384e-02
-1.30884933e+00 3.80245000e-01 9.04326856e-01 8.27668786e-01
3.31609964e-01 -1.80046656e-03 -1.11050747e-01 5.41477501e-01
1.84739918e-01 6.14425540e-01 2.68976867e-01 -5.32846451e-01
6.04420185e-01 5.46877623e-01 1.83654398e-01 -1.23162484e+00
8.90406966e-03 -3.27198744e-01 -1.00653851e+00 3.20514411e-01
1.04206967e+00 1.31935582e-01 -8.34267497e-01 1.50532186e+00
-3.01458482e-02 3.54821920e-01 -1.17113478e-01 1.14751101e+00
4.76430357e-01 1.52799496e-02 -5.62691569e-01 4.69574243e-01
1.20470703e+00 -7.63270259e-01 -5.82885742e-01 -4.77374792e-02
1.42812580e-01 -1.00761056e+00 8.15680683e-01 4.82733339e-01
-8.38707507e-01 -4.36203778e-01 -1.08850861e+00 -6.84304461e-02
-5.78558564e-01 3.18171710e-01 3.99299234e-01 1.08386600e+00
-8.60293150e-01 1.17347097e+00 -5.79702020e-01 -3.18240076e-01
7.82160521e-01 2.89661020e-01 -7.98824131e-01 -1.98854521e-01
-1.15809977e+00 8.92714262e-01 9.91387665e-02 8.16232324e-01
-8.34822178e-01 -7.21527517e-01 -6.74101472e-01 3.77126187e-02
2.06299439e-01 -2.46234965e-02 8.49638939e-01 -7.52125621e-01
-1.39912581e+00 1.07328928e+00 4.09516953e-02 -3.96921039e-01
1.14642549e+00 -1.15659766e-01 -8.79623532e-01 -1.70031548e-01
-3.76256138e-01 -8.37571099e-02 1.31331325e+00 -1.29323685e+00
-6.00550473e-02 -6.86253965e-01 -3.30142021e-01 -4.77407962e-01
-3.29302549e-01 3.34039330e-01 -3.75127077e-01 -6.69906974e-01
1.52001262e-01 -9.52345908e-01 2.73464471e-01 5.21662593e-01
-5.86553931e-01 2.51503587e-01 1.35244179e+00 -9.56728041e-01
8.20948482e-01 -2.21955800e+00 -5.26147038e-02 6.93244874e-01
2.27614045e-01 5.98628521e-01 -3.87887746e-01 4.71310943e-01
1.59982368e-02 -6.33739606e-02 -4.94599909e-01 -4.77639914e-01
4.16008770e-01 5.92288300e-02 -6.24700427e-01 9.94169116e-01
4.09681231e-01 1.06585264e+00 -8.89190257e-01 -2.12076843e-01
-2.44700551e-01 6.04034066e-01 1.96024887e-02 -2.08325572e-02
1.87911943e-01 3.69756728e-01 -2.38121405e-01 9.73805428e-01
1.22635603e+00 -6.59470558e-02 4.25345957e-01 -2.11231142e-01
2.44297117e-01 -7.26693347e-02 -1.34706652e+00 1.57617164e+00
-1.77384183e-01 8.80116820e-01 2.49456659e-01 -8.73050869e-01
1.21304393e+00 7.42237642e-02 1.84676759e-02 -5.78392923e-01
2.15759963e-01 3.70239049e-01 1.32322177e-01 -3.60980392e-01
6.79553390e-01 -1.66412026e-01 6.16375953e-02 9.61722255e-01
-5.24100624e-02 1.15742058e-01 -1.85588673e-01 1.59441441e-01
8.45367610e-01 1.11069903e-01 -3.88728023e-01 1.21962158e-02
6.51489615e-01 -7.13750601e-01 4.95360434e-01 8.05414498e-01
-3.39777321e-01 8.11274529e-01 5.27739465e-01 -5.61887145e-01
-1.07003629e+00 -1.18716311e+00 -1.52895629e-01 6.29991829e-01
3.44292402e-01 -9.27666277e-02 -5.81934571e-01 -9.60350454e-01
5.67822814e-01 2.36371815e-01 -7.09356725e-01 -1.18010364e-01
-7.06685483e-01 -5.44879675e-01 1.41039193e+00 6.30512595e-01
6.17462039e-01 -8.52129579e-01 -2.53731251e-01 -1.40139997e-01
2.00815111e-01 -1.09285247e+00 -7.24262595e-01 -1.92013681e-01
-5.87168396e-01 -1.44633615e+00 -8.28046978e-01 -6.25340223e-01
8.33885550e-01 1.00583524e-01 6.42598808e-01 3.96459818e-01
-4.27721381e-01 1.43178953e-02 -2.18645990e-01 -3.15204710e-01
-3.46197844e-01 -1.45116791e-01 2.28639334e-01 8.14149737e-01
4.11742836e-01 -3.68188143e-01 -4.06768531e-01 4.76400346e-01
-1.07893145e+00 -4.77139026e-01 5.10689795e-01 1.19827938e+00
1.11197263e-01 -8.07061121e-02 1.16160110e-01 -9.45436239e-01
6.55885935e-01 2.09856350e-02 -5.87917149e-01 7.89912045e-01
-5.75644433e-01 1.34859651e-01 8.18756640e-01 -4.47396189e-01
-1.07007146e+00 -1.72195017e-01 3.91880453e-01 -4.71644551e-01
1.37461007e-01 1.17887795e-01 -3.15645218e-01 -6.69224858e-01
4.88108754e-01 5.28679073e-01 2.15707883e-01 -6.03822947e-01
3.55849385e-01 6.06287956e-01 9.00957048e-01 -6.81550443e-01
1.41114199e+00 7.66368926e-01 2.22061783e-01 -4.56649542e-01
-3.38364393e-01 -2.57759154e-01 -1.01781273e+00 -1.11089751e-01
1.75941467e-01 -1.79857746e-01 -1.00968575e+00 1.20033610e+00
-1.13545573e+00 -5.46711124e-02 1.13060288e-02 4.65492941e-02
-2.63255268e-01 9.66647446e-01 -4.49094921e-01 -8.23466361e-01
-3.02766562e-01 -9.78512228e-01 1.03892386e+00 3.04659724e-01
-1.20191813e-01 -1.05073977e+00 -7.76400045e-02 3.93239051e-01
5.72417796e-01 3.28658342e-01 6.59090042e-01 -8.58201265e-01
-5.22699594e-01 -8.16748142e-01 -5.71574926e-01 4.89989817e-01
2.41389424e-01 3.57943684e-01 -1.12683642e+00 -4.63857323e-01
-2.25484058e-01 -3.78364295e-01 1.07664037e+00 -3.10630649e-01
1.39572704e+00 -2.56985277e-01 -1.61905095e-01 9.30999100e-01
1.23245335e+00 -2.06289694e-01 8.72738004e-01 1.37780607e-01
6.92153037e-01 6.04001582e-01 2.68333495e-01 2.99586833e-01
8.56543854e-02 6.82372510e-01 3.73441011e-01 -9.88900587e-02
-1.17655462e-02 -3.93683314e-01 1.97906017e-01 3.07164103e-01
-1.31626233e-01 -2.17203632e-01 -9.78828192e-01 4.58050668e-01
-1.69452631e+00 -1.30901539e+00 -2.30096489e-01 2.23190546e+00
5.13203919e-01 -1.64436936e-01 -2.17642948e-01 3.03989232e-01
8.32551122e-01 2.75199860e-01 -5.55501163e-01 -4.06414777e-01
-5.59041262e-01 5.05835533e-01 5.42711854e-01 2.79306263e-01
-1.12765300e+00 8.13734531e-01 5.71049976e+00 6.57928884e-01
-1.23897099e+00 -1.00244299e-01 3.11311126e-01 1.84009108e-03
-1.44182459e-01 5.73478937e-02 -6.05060399e-01 7.46061683e-01
5.54172397e-01 -2.55281162e-02 4.22472626e-01 4.66291487e-01
4.42789420e-02 2.70159394e-01 -1.25717902e+00 9.14525747e-01
4.01892155e-01 -1.41354001e+00 3.51131987e-03 6.79867938e-02
7.12593675e-01 -4.12732631e-01 4.97307599e-01 -2.02728346e-01
1.94261655e-01 -1.43999720e+00 6.24592066e-01 8.16700399e-01
9.74270642e-01 -5.41734457e-01 9.37380612e-01 -2.04544924e-02
-8.31305683e-01 -2.47013522e-03 -3.65121335e-01 2.99661160e-01
1.44611746e-01 4.16039854e-01 -6.84127450e-01 7.27182567e-01
4.45723891e-01 7.22095788e-01 -6.20269239e-01 1.07014179e+00
-2.57451355e-01 3.68924677e-01 -1.91220880e-01 1.61340147e-01
2.06287742e-01 -3.81269336e-01 2.23826557e-01 1.29755485e+00
3.60688686e-01 -3.17986667e-01 -4.36028123e-01 1.14796317e+00
-4.18718278e-01 -3.13200206e-01 -5.19855678e-01 -3.02873552e-01
4.08313692e-01 1.26481688e+00 -4.71144468e-01 -1.35773942e-01
5.12833633e-02 1.45353150e+00 4.74942625e-02 2.49797702e-01
-7.62945533e-01 -7.79366255e-01 7.69086242e-01 -1.55655831e-01
3.34981501e-01 -2.14042932e-01 -4.34189141e-01 -1.26287818e+00
5.09673476e-01 -9.77299452e-01 3.14630359e-01 -3.77826989e-01
-1.67011595e+00 4.17921424e-01 -6.38915718e-01 -1.33007622e+00
1.32540405e-01 -9.60520625e-01 -1.17194235e+00 1.19522524e+00
-1.70309985e+00 -1.52023435e+00 -4.88081247e-01 6.83993816e-01
-6.56745657e-02 -4.41549867e-01 7.53261983e-01 3.07035744e-01
-5.38183451e-01 1.33635902e+00 5.01406014e-01 7.01927304e-01
1.11415422e+00 -9.68906820e-01 8.64563763e-01 9.06016231e-01
2.28721470e-01 9.47067857e-01 3.08438152e-01 -6.09191597e-01
-1.59132743e+00 -8.74822617e-01 1.30488348e+00 -6.46245420e-01
8.84470165e-01 -5.42486608e-01 -1.12128592e+00 5.56422830e-01
-2.11979061e-01 2.82587945e-01 7.50531673e-01 -9.82784033e-02
-1.12158167e+00 -2.28573918e-01 -1.39702427e+00 3.77043575e-01
1.16184914e+00 -9.97862697e-01 -2.62324035e-01 2.85570860e-01
-2.62101680e-01 -3.60998362e-01 -7.39735126e-01 5.12195043e-02
1.29704428e+00 -1.02875078e+00 8.69263768e-01 -1.06545222e+00
5.06172776e-01 -3.26941460e-01 2.73990482e-02 -1.00495088e+00
6.81302771e-02 -8.46692264e-01 -1.80009678e-01 1.40926504e+00
2.92888373e-01 -5.08106291e-01 1.07756126e+00 6.78249776e-01
3.80719781e-01 -4.62073356e-01 -9.96671557e-01 -1.21083868e+00
1.78100333e-01 -2.85898596e-01 1.08108556e+00 1.21976638e+00
-1.88798875e-01 -6.18168533e-01 -6.84993982e-01 2.37615272e-01
1.13176191e+00 3.13649505e-01 7.52697051e-01 -1.12452435e+00
-1.52822793e-01 -6.51832223e-01 -7.10671067e-01 -5.69610655e-01
3.85981470e-01 -9.80934441e-01 -1.64557993e-01 -7.70178676e-01
1.01053625e-01 -4.62208629e-01 -2.27932543e-01 4.03734088e-01
-4.13739271e-02 4.52992946e-01 3.01290870e-01 3.26772854e-02
-1.79430500e-01 3.74400675e-01 1.11653173e+00 -6.08659029e-01
2.73925811e-01 1.52545735e-01 -6.59624577e-01 4.18340981e-01
6.90615416e-01 -3.18032295e-01 -4.03815741e-03 -5.67025959e-01
-5.66466041e-02 -3.02999467e-01 7.70756900e-01 -5.83394647e-01
5.62789977e-01 -1.91095769e-01 5.43782234e-01 -3.26689661e-01
2.55228102e-01 -8.51831615e-01 1.62835941e-01 4.00473446e-01
-3.07267874e-01 -1.18671730e-01 -1.51775137e-01 4.07211989e-01
-2.21142441e-01 -2.92499155e-01 7.75590837e-01 9.06893834e-02
-5.45064628e-01 4.94664013e-01 2.52706319e-01 -1.93926647e-01
6.97335303e-01 -6.54935539e-01 -5.79617262e-01 -2.32041016e-01
-4.32148397e-01 1.11015953e-01 5.96240759e-01 5.72405875e-01
9.09581959e-01 -1.32958436e+00 -9.72808659e-01 6.18205190e-01
3.20133179e-01 -4.27723020e-01 3.60495269e-01 7.31518269e-01
-5.16723514e-01 2.46166378e-01 -4.09452111e-01 -2.73074239e-01
-1.48029113e+00 1.11504354e-01 5.34754515e-01 -1.17611393e-01
-4.78884995e-01 9.41948175e-01 -4.13393915e-01 -6.47083938e-01
2.45910227e-01 2.95656361e-02 2.17034116e-01 -6.97930902e-02
7.58582294e-01 6.03576303e-01 2.03310981e-01 -7.76083469e-01
-5.45465171e-01 6.38665974e-01 -3.89159143e-01 1.23422094e-01
1.38364947e+00 4.34148401e-01 -2.39931330e-01 -2.67259389e-01
1.25166678e+00 3.77781428e-02 -1.22341490e+00 -3.92183185e-01
2.70126373e-01 -1.02483082e+00 -4.06340688e-01 -9.01061058e-01
-1.32531929e+00 9.53927755e-01 5.07612050e-01 -1.92091316e-01
7.97312081e-01 -3.58537197e-01 8.95195544e-01 4.65360016e-01
2.17642963e-01 -1.25524521e+00 -7.24105677e-03 4.88817394e-01
9.13505971e-01 -1.32976770e+00 -5.48802540e-02 2.13465746e-02
-5.79915822e-01 1.48954761e+00 3.16616595e-01 -1.31066382e-01
5.83444476e-01 1.61260098e-01 2.46963054e-01 -2.69267589e-01
-1.58449426e-01 3.67265493e-01 4.82843339e-01 8.11550379e-01
2.35588074e-01 1.07645266e-01 -1.44468024e-01 6.44503772e-01
-3.69153410e-01 -1.11232005e-01 4.88850653e-01 8.58598351e-01
2.75727481e-01 -1.54366755e+00 -5.56807518e-01 3.41990441e-01
-3.34712327e-01 1.43242612e-01 -9.51091409e-01 6.08384907e-01
1.87022597e-01 6.49038613e-01 -1.20340593e-01 -4.66336429e-01
3.04721057e-01 2.13934138e-01 7.05487669e-01 4.48903674e-03
-9.21626329e-01 -6.77699089e-01 -2.69789517e-01 -5.45587599e-01
-1.16262995e-01 -7.90850282e-01 -7.60932565e-01 -7.49363780e-01
-2.37437531e-01 -3.08935493e-01 8.59408259e-01 9.70667839e-01
1.62895069e-01 -1.04360588e-01 7.09274650e-01 -5.87811112e-01
-1.18409467e+00 -5.97664058e-01 -9.82028663e-01 9.27981019e-01
3.97331953e-01 -4.43882614e-01 -2.24555463e-01 1.08233877e-02] | [12.74160099029541, 1.2266607284545898] |
4f2a5bb5-cbd5-4a7c-9d42-0e9a8c15dc65 | ciao-a-contrastive-adaptation-mechanism-for | 2208.07221 | null | https://arxiv.org/abs/2208.07221v1 | https://arxiv.org/pdf/2208.07221v1.pdf | CIAO! A Contrastive Adaptation Mechanism for Non-Universal Facial Expression Recognition | Current facial expression recognition systems demand an expensive re-training routine when deployed to different scenarios than they were trained for. Biasing them towards learning specific facial characteristics, instead of performing typical transfer learning methods, might help these systems to maintain high performance in different tasks, but with a reduced training effort. In this paper, we propose Contrastive Inhibitory Adaptati On (CIAO), a mechanism that adapts the last layer of facial encoders to depict specific affective characteristics on different datasets. CIAO presents an improvement in facial expression recognition performance over six different datasets with very unique affective representations, in particular when compared with state-of-the-art models. In our discussions, we make an in-depth analysis of how the learned high-level facial features are represented, and how they contribute to each individual dataset's characteristics. We finalize our study by discussing how CIAO positions itself within the range of recent findings on non-universal facial expressions perception, and its impact on facial expression recognition research. | ['Alessandra Sciutti', 'Pablo Barros'] | 2022-08-10 | null | null | null | null | ['facial-expression-recognition'] | ['computer-vision'] | [ 3.28991294e-01 4.86386828e-02 -1.62962928e-01 -1.20356798e+00
-1.44771621e-01 -2.96151549e-01 3.95757079e-01 -3.70489031e-01
-4.00781304e-01 5.03982365e-01 2.10181668e-01 4.32031125e-01
1.54724166e-01 -4.55385625e-01 -4.48928505e-01 -6.81539476e-01
-2.01863080e-01 1.93795204e-01 -6.52434528e-01 -5.47181547e-01
-1.19617723e-01 8.54320407e-01 -1.83581150e+00 7.91407526e-01
3.07906140e-02 1.44329989e+00 -4.42032307e-01 4.46131974e-01
-1.12049669e-01 9.16181743e-01 -6.81451678e-01 -8.15645099e-01
-7.04263747e-02 -5.24239421e-01 -7.92243421e-01 7.72221163e-02
6.78371489e-01 -2.25513667e-01 -7.84024969e-02 9.72326100e-01
4.95222509e-01 8.75206292e-02 8.92684102e-01 -1.50121593e+00
-7.59763420e-01 1.17398970e-01 -4.70317394e-01 6.91678375e-02
3.11346143e-01 -4.51534800e-02 7.34464884e-01 -1.02780783e+00
8.06533575e-01 1.21154130e+00 7.36273110e-01 1.25155807e+00
-1.18595994e+00 -1.05779922e+00 2.88120031e-01 2.55361855e-01
-1.43606663e+00 -9.63045597e-01 9.32655156e-01 -3.15072715e-01
1.05686235e+00 2.23256111e-01 7.05983400e-01 1.38932705e+00
5.57174347e-02 7.67101109e-01 1.26134109e+00 -2.59011656e-01
4.37176116e-02 2.48856112e-01 -3.03639084e-01 5.02000332e-01
-3.84431958e-01 -1.46854535e-01 -8.82117510e-01 -9.17773321e-02
3.83945495e-01 -2.32637361e-01 -3.99612933e-02 -2.37557963e-01
-3.00667554e-01 7.57178605e-01 4.95615542e-01 5.35134852e-01
-6.13189399e-01 2.70750850e-01 6.79097772e-01 5.40491998e-01
6.43830836e-01 3.89631629e-01 -4.69117105e-01 -2.49378681e-01
-6.37383223e-01 -2.52042878e-02 4.95553315e-01 6.54148221e-01
1.08968437e+00 4.11817253e-01 -2.09668741e-01 1.08107471e+00
8.14734399e-02 2.92630434e-01 4.22837436e-01 -9.13143694e-01
-3.34192723e-01 3.02566141e-01 -2.60964125e-01 -1.22133255e+00
-5.23170829e-01 -4.87852208e-02 -6.63671851e-01 4.52637851e-01
3.64441648e-02 -3.82704347e-01 -7.46782422e-01 2.36870027e+00
-4.87160534e-02 -2.32184045e-02 1.37148485e-01 7.58029580e-01
7.19351709e-01 5.68842530e-01 5.75583160e-01 -1.28223464e-01
1.27900243e+00 -7.10874796e-01 -7.96450615e-01 -2.80136347e-01
7.20007658e-01 -5.30430555e-01 7.84695029e-01 3.92059565e-01
-8.41391504e-01 -4.62239861e-01 -7.93058932e-01 1.35270521e-01
-5.33267975e-01 1.71469778e-01 1.20074153e+00 7.89718270e-01
-1.24124014e+00 3.59465599e-01 -2.40599841e-01 -6.26456738e-01
8.03567767e-01 6.01988256e-01 -8.21523905e-01 2.97501445e-01
-1.14598322e+00 1.11266434e+00 -4.67703957e-03 2.25369811e-01
-6.52204514e-01 -6.01195753e-01 -8.48543465e-01 1.42662629e-01
-1.05466567e-01 -4.28241462e-01 1.37559831e+00 -2.32982254e+00
-2.04659414e+00 1.31736505e+00 -2.73811460e-01 4.05949950e-02
-1.20960444e-01 -1.41596705e-01 -7.37479806e-01 1.70748487e-01
-3.15061033e-01 1.00295210e+00 9.83380854e-01 -1.22664726e+00
-1.45249858e-01 -5.75945854e-01 -1.68468624e-01 8.73525441e-02
-5.41201532e-01 4.06319499e-01 -1.79312840e-01 -4.42770153e-01
-4.31738555e-01 -1.03263271e+00 -3.99906002e-02 3.05638045e-01
3.51074517e-01 -3.99869800e-01 6.86615288e-01 -1.43784881e-01
1.04077995e+00 -2.40804768e+00 2.36171007e-01 3.36434186e-01
-1.45643115e-01 3.86796057e-01 -3.78733903e-01 4.15511459e-01
-6.01118088e-01 -1.49864778e-02 -3.63044627e-02 -4.41872627e-01
4.27901745e-02 3.78218144e-01 -1.72458947e-01 2.34564871e-01
7.90213764e-01 9.29196835e-01 -7.54145563e-01 -2.02084586e-01
-1.55426547e-01 6.22062325e-01 -6.08694077e-01 3.61847609e-01
1.03317827e-01 3.92522275e-01 -3.27950388e-01 7.72507906e-01
6.91692531e-01 1.39858156e-01 3.56777877e-01 -2.64850080e-01
2.09628075e-01 -3.28584045e-01 -4.61476505e-01 1.50702381e+00
-6.42578483e-01 8.59293044e-01 2.69253403e-01 -1.12887275e+00
1.28345406e+00 3.97188485e-01 5.43512166e-01 -9.53835011e-01
4.41559076e-01 8.19222555e-02 3.16236652e-02 -6.48494780e-01
2.69916147e-01 -6.91289961e-01 -5.26158363e-02 4.07705098e-01
5.63383520e-01 1.08132705e-01 -2.72897869e-01 -2.41757512e-01
5.71952164e-01 2.00346187e-01 3.37310106e-01 -1.31108388e-01
5.43189585e-01 -5.95018506e-01 4.18725222e-01 3.23521972e-01
-5.77632904e-01 3.48965943e-01 7.12330461e-01 -6.55562520e-01
-6.66149676e-01 -5.94490469e-01 -1.37015611e-01 1.78714180e+00
-5.11558115e-01 -3.82141501e-01 -8.50331724e-01 -5.96982539e-01
-5.23401424e-03 4.86580163e-01 -1.40315378e+00 -7.18501747e-01
-2.23613650e-01 -7.98955679e-01 9.18909252e-01 5.69933414e-01
1.87842831e-01 -1.44601369e+00 -6.42060399e-01 -1.01316907e-01
8.99965167e-02 -1.02344191e+00 1.14510916e-01 3.81119490e-01
-5.88425517e-01 -6.16372406e-01 -6.50395155e-01 -6.55289054e-01
6.64323688e-01 -1.86147362e-01 1.34745705e+00 5.84418662e-02
-1.56554133e-01 5.81008852e-01 -4.78551507e-01 -7.68722892e-01
-2.96058923e-01 -1.32250026e-01 1.72310174e-01 6.13239288e-01
1.01538646e+00 -6.23498797e-01 -4.25318927e-01 4.97345999e-02
-9.26245987e-01 -3.99740219e-01 6.57336652e-01 8.33883286e-01
2.31293783e-01 -6.35913193e-01 7.90600955e-01 -9.30576324e-01
7.70194232e-01 -7.35253274e-01 2.36423478e-01 1.13034740e-01
-4.43777174e-01 -1.75465658e-01 3.90821904e-01 -4.30657148e-01
-1.14392817e+00 1.34449989e-01 -4.25359339e-01 -6.61585569e-01
-1.96365774e-01 4.19122398e-01 -5.66117186e-03 -2.85384655e-01
6.81564867e-01 6.19222410e-02 4.86088783e-01 -8.21470618e-02
3.28511208e-01 7.19551444e-01 3.74668807e-01 -6.33531332e-01
1.52378783e-01 4.17218029e-01 -7.27318004e-02 -6.42175913e-01
-7.25807905e-01 -6.77349493e-02 -7.78815567e-01 -5.27567685e-01
7.76836097e-01 -7.99675763e-01 -7.62825727e-01 6.87527299e-01
-9.59670186e-01 -4.72171456e-01 -1.80073217e-01 4.25210595e-02
-7.57374883e-01 -2.00240299e-01 -5.04156709e-01 -9.20129657e-01
-1.80471972e-01 -9.25447106e-01 1.13349497e+00 4.24975008e-01
-7.35439062e-01 -8.84644389e-01 2.25608110e-01 -8.65045339e-02
6.83813393e-01 2.16053292e-01 7.17614233e-01 -4.53024089e-01
3.81512582e-01 -8.55322406e-02 -1.65451095e-01 5.53639531e-01
2.79605657e-01 2.93855101e-01 -1.64333463e+00 -7.57625550e-02
-1.98161155e-01 -9.57576513e-01 7.03063309e-01 1.14053868e-01
1.45408261e+00 -2.42349789e-01 -1.14475399e-01 8.02613258e-01
1.10924673e+00 1.98519722e-01 8.95435452e-01 2.92458951e-01
1.31133646e-01 9.84446585e-01 4.80642676e-01 5.96879542e-01
4.71378341e-02 9.50438559e-01 4.59841341e-01 -3.02189827e-01
-4.61086780e-02 -8.76372382e-02 5.82292080e-01 3.88209611e-01
-4.21574026e-01 1.08949579e-01 -4.69150990e-01 2.57142037e-01
-1.53830481e+00 -1.06487989e+00 6.05994940e-01 1.56127393e+00
9.82550502e-01 -5.74270427e-01 2.16173053e-01 -4.02663469e-01
3.15266967e-01 3.17196161e-01 -5.63018858e-01 -1.38801765e+00
-4.34416026e-01 7.48518407e-01 -9.07584801e-02 2.30733037e-01
-9.64403272e-01 1.21872163e+00 7.55699062e+00 6.04439735e-01
-1.87123477e+00 -7.52411783e-02 1.04281902e+00 -2.30935752e-01
-8.82952586e-02 -5.06140888e-01 -2.45113611e-01 1.92597076e-01
1.17099166e+00 4.78830747e-02 2.39988953e-01 1.12195373e+00
-1.37393028e-01 1.29359275e-01 -1.21336591e+00 1.35520864e+00
4.91346389e-01 -1.03619492e+00 1.47137180e-01 -2.96887815e-01
4.43412095e-01 -1.88253790e-01 5.73502719e-01 5.92326164e-01
-1.14515387e-01 -1.61434782e+00 5.12826383e-01 6.87343776e-01
9.79822934e-01 -8.09814632e-01 7.39045382e-01 -4.51620162e-01
-6.63448691e-01 -1.11520886e-01 -3.67796570e-01 -3.47434819e-01
-1.54026702e-01 -1.31491303e-01 -6.06273115e-01 1.32499009e-01
1.07257760e+00 7.04606295e-01 -5.12519777e-01 1.95049420e-01
2.75998395e-02 4.81777400e-01 2.95674410e-02 -2.59777188e-01
3.13042074e-01 -1.56493619e-01 4.02409323e-02 1.70898259e+00
2.58478045e-01 2.27575392e-01 -4.47370172e-01 7.03466356e-01
-1.71831787e-01 3.58216017e-01 -7.92415500e-01 -7.32563585e-02
1.03109464e-01 1.41264713e+00 -1.07044242e-01 -3.08964878e-01
-4.09136176e-01 1.27755332e+00 6.90564811e-01 4.51593697e-01
-6.18219793e-01 -1.01660348e-01 1.38393259e+00 -2.49014989e-01
1.26007646e-01 1.41387656e-01 -2.69446522e-02 -8.53307545e-01
-2.11328030e-01 -1.09617949e+00 2.73434639e-01 -1.08435237e+00
-1.48494565e+00 9.76196885e-01 -4.20970172e-02 -8.07854116e-01
-4.62244332e-01 -9.57676053e-01 -5.21972597e-01 7.13726401e-01
-1.46646011e+00 -1.25209498e+00 -2.76638150e-01 6.83894396e-01
1.93312213e-01 -3.96744370e-01 1.48217213e+00 2.36989513e-01
-5.61528265e-01 1.08186102e+00 -2.64108449e-01 2.98727602e-01
1.11452520e+00 -7.25215673e-01 -1.89911261e-01 1.87796116e-01
1.74278826e-01 5.36971629e-01 5.85554123e-01 1.53016910e-01
-1.11920369e+00 -7.78891742e-01 8.24226439e-01 -3.99423271e-01
5.06989479e-01 -3.27680528e-01 -1.01234102e+00 7.78879404e-01
5.08247733e-01 2.09530458e-01 1.46628916e+00 5.45870125e-01
-7.72780240e-01 -3.67414415e-01 -1.19707739e+00 6.08793259e-01
1.01475906e+00 -7.66379356e-01 -1.98515043e-01 -1.10658959e-01
-1.12315588e-01 -4.18254249e-02 -9.39683735e-01 4.66113150e-01
1.07284105e+00 -1.28969061e+00 6.39317691e-01 -1.32932162e+00
5.67808807e-01 1.34312838e-01 -3.96957308e-01 -1.49995756e+00
-5.89662135e-01 -6.17550611e-01 2.07975909e-01 1.19927740e+00
2.59031653e-01 -5.58722079e-01 8.22656989e-01 6.84382558e-01
1.02708206e-01 -1.07677197e+00 -9.66912329e-01 -3.32498133e-01
2.76397884e-01 -4.23628211e-01 7.15229630e-01 1.21333635e+00
2.09320217e-01 3.49241585e-01 -4.92773861e-01 -2.99854398e-01
-1.09040283e-01 -1.18553638e-01 9.06936169e-01 -9.90095615e-01
1.36486799e-01 -7.73068130e-01 -8.94870043e-01 -4.29523706e-01
8.68212700e-01 -9.38123047e-01 -1.18580759e-01 -6.66162133e-01
2.83936143e-01 -3.15121144e-01 -6.26327872e-01 9.92616117e-01
-5.52728884e-02 6.56103492e-01 2.88561165e-01 -8.94377232e-02
-4.92222369e-01 8.58692765e-01 8.89062464e-01 -9.67371240e-02
1.11800507e-01 -2.67643571e-01 -1.04500365e+00 6.85634077e-01
7.75148571e-01 -2.17999458e-01 -3.85487974e-01 -3.93276572e-01
1.72670752e-01 -3.67488384e-01 6.65776208e-02 -8.34276795e-01
-1.66911796e-01 -1.85415089e-01 8.17918777e-01 3.50203007e-01
7.35654533e-01 -7.50808775e-01 2.38765571e-02 3.01239695e-02
-4.11721736e-01 1.60836980e-01 7.21940756e-01 8.61935914e-02
-5.51795483e-01 -1.22690775e-01 1.00595617e+00 -5.85237592e-02
-1.16825795e+00 3.80216539e-01 -7.94093311e-01 -3.87461841e-01
9.94393051e-01 -4.14112031e-01 5.82306124e-02 -8.50852430e-01
-1.03303242e+00 -2.44344831e-01 4.66594815e-01 7.21672237e-01
5.24391830e-01 -1.62432051e+00 -7.10093737e-01 3.43515038e-01
6.32383466e-01 -7.30774224e-01 4.90979195e-01 6.63746417e-01
-1.00346327e-01 1.43014356e-01 -1.00219452e+00 -4.96179819e-01
-1.36906099e+00 3.07983756e-01 7.19243288e-01 2.16301098e-01
1.20961266e-02 1.18019462e+00 3.43868613e-01 -3.78642142e-01
-1.41025096e-01 2.59037018e-01 -4.37847078e-01 4.25484717e-01
5.57974577e-01 -2.96368003e-01 3.56282387e-03 -1.19763494e+00
-5.11343837e-01 6.55568898e-01 -1.39033645e-01 4.88303043e-02
1.32330334e+00 1.89067442e-02 -2.91933775e-01 5.52529633e-01
1.46983576e+00 -1.96941540e-01 -1.14703238e+00 -1.25108749e-01
-7.48951435e-02 -3.29208046e-01 -2.06800133e-01 -8.79762709e-01
-1.28343046e+00 8.89787853e-01 8.00652266e-01 -3.79319578e-01
1.68482792e+00 1.12730376e-01 2.45915234e-01 3.80650401e-01
1.69710621e-01 -1.18348432e+00 3.51048499e-01 5.50198793e-01
1.08329499e+00 -1.19019246e+00 -1.67817324e-01 -1.83766752e-01
-1.14516687e+00 1.39037490e+00 8.53044033e-01 -1.19289063e-01
7.05027640e-01 1.71991244e-01 6.43109083e-01 -3.33181709e-01
-1.01905143e+00 -1.55645594e-01 1.95151985e-01 9.33161974e-01
9.76357877e-01 5.50116077e-02 1.39351904e-01 6.52528286e-01
-2.62206197e-01 2.50356317e-01 1.38257459e-01 6.80052459e-01
-8.21269378e-02 -1.21563840e+00 2.16047708e-02 2.04418421e-01
-6.22226536e-01 1.78458661e-01 -8.84280622e-01 7.99709141e-01
2.03525916e-01 6.51573002e-01 4.76394475e-01 -5.47212243e-01
2.78716296e-01 5.94197333e-01 8.06527257e-01 -5.70510447e-01
-6.30720675e-01 -3.96934271e-01 1.94488332e-01 -7.49681294e-01
-8.82328451e-01 -7.53842831e-01 -9.83563006e-01 -7.85206854e-02
2.12162688e-01 1.82626043e-02 5.03568053e-01 7.44887412e-01
6.86958253e-01 2.59405762e-01 7.63895094e-01 -1.02093482e+00
-2.00877368e-01 -1.05650198e+00 -4.90844429e-01 8.38289142e-01
2.28522763e-01 -9.21168089e-01 -5.74756600e-02 1.32111395e-02] | [13.568479537963867, 1.7688807249069214] |
16421c30-aabc-4b86-8c80-a34a7c59a2a6 | adapting-to-continuous-covariate-shift-via | 2302.02552 | null | https://arxiv.org/abs/2302.02552v1 | https://arxiv.org/pdf/2302.02552v1.pdf | Adapting to Continuous Covariate Shift via Online Density Ratio Estimation | Dealing with distribution shifts is one of the central challenges for modern machine learning. One fundamental situation is the \emph{covariate shift}, where the input distributions of data change from training to testing stages while the input-conditional output distribution remains unchanged. In this paper, we initiate the study of a more challenging scenario -- \emph{continuous} covariate shift -- in which the test data appear sequentially, and their distributions can shift continuously. Our goal is to adaptively train the predictor such that its prediction risk accumulated over time can be minimized. Starting with the importance-weighted learning, we show the method works effectively if the time-varying density ratios of test and train inputs can be accurately estimated. However, existing density ratio estimation methods would fail due to data scarcity at each time step. To this end, we propose an online method that can appropriately reuse historical information. Our density ratio estimation method is proven to perform well by enjoying a dynamic regret bound, which finally leads to an excess risk guarantee for the predictor. Empirical results also validate the effectiveness. | ['Masashi Sugiyama', 'Peng Zhao', 'Zhen-Yu Zhang', 'Yu-Jie Zhang'] | 2023-02-06 | null | null | null | null | ['density-ratio-estimation'] | ['methodology'] | [ 2.96299368e-01 6.97673932e-02 -2.70146072e-01 -4.89521891e-01
-8.97252262e-01 -5.31630337e-01 1.14172086e-01 1.32217094e-01
-3.73958409e-01 1.12140429e+00 -3.78208816e-01 -4.04177547e-01
-5.38439751e-01 -6.23676956e-01 -9.63127851e-01 -8.69411409e-01
-8.35770667e-02 5.16265094e-01 -1.00341812e-01 2.31069311e-01
1.53083190e-01 2.16947749e-01 -1.28873110e+00 -3.06882024e-01
1.15907836e+00 1.18700075e+00 8.93308520e-02 5.90820014e-01
6.53374493e-02 3.72476101e-01 -5.22920191e-01 -7.25313365e-01
4.31952506e-01 -4.07118142e-01 -3.88396978e-01 5.75991385e-02
2.26033449e-01 -2.85467267e-01 -1.10622086e-01 1.36901164e+00
4.02001917e-01 2.66827762e-01 7.15877056e-01 -1.50150919e+00
-2.88891166e-01 5.98480523e-01 -8.84291828e-01 1.77422106e-01
-3.42685133e-01 -2.43464664e-01 9.10195172e-01 -7.54523456e-01
8.37529823e-02 8.61749172e-01 6.51076555e-01 6.98419809e-01
-1.20166159e+00 -7.84285486e-01 7.24567652e-01 1.64720029e-01
-1.19254088e+00 -8.66385549e-02 6.84390545e-01 -4.81236696e-01
2.64222473e-01 1.04215585e-01 4.76280361e-01 9.09742951e-01
3.90567541e-01 9.98960257e-01 7.71910191e-01 -2.70683855e-01
4.91460681e-01 4.22730833e-01 -4.38958891e-02 3.81089449e-01
3.34900290e-01 -1.05145492e-01 -3.99209678e-01 -2.24136233e-01
4.92234111e-01 2.99703717e-01 -4.21308696e-01 -6.22143865e-01
-6.40914917e-01 7.00487792e-01 -9.92226079e-02 5.70204519e-02
-1.57496765e-01 1.02735981e-01 2.67729312e-01 5.49734890e-01
8.36257219e-01 2.16011554e-02 -8.66886020e-01 -2.17952177e-01
-1.02834547e+00 3.18512648e-01 8.28970551e-01 1.07183135e+00
4.25342262e-01 -7.34682754e-02 -3.41239274e-01 6.76239669e-01
1.60758078e-01 5.48790753e-01 2.11393327e-01 -5.31549096e-01
9.33751523e-01 1.51903227e-01 4.74538177e-01 -6.10935509e-01
-1.34783104e-01 -8.68339419e-01 -9.88460600e-01 2.34825872e-02
8.23239625e-01 -5.52702606e-01 -6.64870501e-01 2.04287505e+00
5.04819751e-01 3.94835949e-01 -2.40608364e-01 5.01028478e-01
-5.23729026e-01 6.13561928e-01 -4.91713993e-02 -6.88299119e-01
8.49275708e-01 -5.67302287e-01 -7.62714088e-01 -1.84512332e-01
3.71741831e-01 -4.02744144e-01 1.02004385e+00 6.19223595e-01
-1.20281625e+00 -2.44526416e-01 -1.04414427e+00 5.89416206e-01
1.14485234e-01 -5.08410204e-03 1.39677107e-01 6.68173134e-01
-6.69607759e-01 8.47190142e-01 -7.50483692e-01 1.68896258e-01
6.21701658e-01 3.80104423e-01 1.44150415e-02 -8.49714794e-04
-1.06998360e+00 5.47387123e-01 3.21894169e-01 1.59853831e-01
-7.92055368e-01 -1.35757422e+00 -6.02399945e-01 2.52507776e-01
6.52882099e-01 -4.79938924e-01 1.70757389e+00 -1.00070965e+00
-1.47172940e+00 3.10184330e-01 -5.15790060e-02 -5.77420950e-01
1.01525497e+00 -3.49978030e-01 -2.93362215e-02 -3.17005694e-01
-2.33004317e-02 -1.02480240e-01 1.17231607e+00 -1.05016792e+00
-1.21792877e+00 -5.03784895e-01 -2.73616344e-01 9.08753574e-02
-6.15786433e-01 -3.71889532e-01 -3.88872534e-01 -7.18357563e-01
-3.33804160e-01 -7.17378438e-01 -3.09123576e-01 -2.13275831e-02
-3.00392538e-01 -3.40750217e-02 5.34371495e-01 -4.26572412e-01
1.55485761e+00 -2.06267643e+00 7.91436136e-02 3.47827882e-01
-1.88899338e-02 7.23224208e-02 2.78429657e-01 2.26796135e-01
5.79891279e-02 3.76213863e-02 -5.08296669e-01 -5.20440578e-01
-3.86124961e-02 1.37838259e-01 -5.98718464e-01 5.84537923e-01
1.36413172e-01 5.87199569e-01 -9.55844581e-01 -2.29457080e-01
-7.85768777e-02 2.02682927e-01 -7.03023255e-01 2.33306557e-01
-2.06904054e-01 3.89362961e-01 -5.49807072e-01 4.36191082e-01
8.84230435e-01 -2.76508451e-01 1.95739627e-01 1.70742497e-01
1.31860912e-01 -4.20535892e-01 -1.33169019e+00 1.20207465e+00
-6.41967356e-01 2.09386647e-01 2.34841660e-01 -1.23368561e+00
6.87475622e-01 -9.31899063e-03 4.75768685e-01 -3.82522970e-01
8.50907713e-03 2.08741456e-01 -1.64208531e-01 -2.70662516e-01
2.36385748e-01 -5.03496289e-01 -2.42410153e-01 2.55911112e-01
-1.32218286e-01 1.12608962e-01 -5.45075573e-02 -2.26228997e-01
9.45999742e-01 -5.10383956e-02 2.11565778e-01 -2.74050146e-01
4.42585558e-01 -4.22685087e-01 9.57852781e-01 7.20761418e-01
-2.00501963e-01 2.92134494e-01 9.30188894e-01 2.37463787e-02
-1.03768456e+00 -1.33716702e+00 -3.04440916e-01 8.56100261e-01
7.29201585e-02 9.67986435e-02 -6.16985083e-01 -9.83501673e-01
4.51457679e-01 8.72506797e-01 -7.93706954e-01 -4.21137184e-01
-3.85955811e-01 -8.68538201e-01 -9.54473615e-02 5.46602845e-01
2.41397262e-01 -3.98839056e-01 -5.13150632e-01 3.80757809e-01
2.82551795e-01 -5.31491995e-01 -7.45086253e-01 3.40599746e-01
-1.06375837e+00 -9.36115026e-01 -1.12507296e+00 -5.19532979e-01
8.16158533e-01 -1.08968958e-01 8.67375672e-01 -5.75143039e-01
-1.55724123e-01 4.66763049e-01 -8.94347057e-02 -6.98752642e-01
-5.11301048e-02 1.89427957e-01 1.56891737e-02 2.98283339e-01
-5.16541936e-02 -6.08419120e-01 -8.70245457e-01 4.55594540e-01
-9.52530205e-01 -2.14556858e-01 5.10351598e-01 9.97497618e-01
8.33536327e-01 3.27083617e-01 1.12840676e+00 -1.30826700e+00
5.29624224e-01 -8.43594730e-01 -9.45154130e-01 5.83460212e-01
-9.54356015e-01 8.33939537e-02 9.72731709e-01 -7.60516047e-01
-1.22407472e+00 7.34895235e-03 1.92938954e-01 -5.94972789e-01
4.37401474e-01 4.37070310e-01 -3.38426292e-01 3.40526640e-01
1.88905358e-01 1.34324849e-01 -7.67597044e-03 -5.72846770e-01
8.36038440e-02 4.95533854e-01 5.23710310e-01 -6.84872031e-01
1.07870793e+00 2.20038682e-01 2.47641578e-01 -2.24423096e-01
-1.28124714e+00 -3.08850616e-01 -4.68803912e-01 -3.36040914e-01
1.77006140e-01 -6.95794106e-01 -7.42942750e-01 5.36838651e-01
-6.08553767e-01 -5.22364914e-01 -6.33297920e-01 4.90844518e-01
-5.85893333e-01 2.10143834e-01 -2.37943038e-01 -1.42604291e+00
-2.58615851e-01 -5.98203421e-01 7.70436466e-01 3.60458553e-01
3.56000900e-01 -1.25789225e+00 1.05600864e-01 -1.81777868e-02
3.82522374e-01 3.13679308e-01 9.72016513e-01 -6.27441347e-01
-1.92941755e-01 -3.62482548e-01 1.35645196e-02 6.09318495e-01
2.76231915e-01 -2.28055090e-01 -6.68069601e-01 -6.05883598e-01
2.78561175e-01 -1.61615789e-01 7.98458576e-01 5.06459236e-01
1.73865461e+00 -4.93046373e-01 -3.07641357e-01 4.05538529e-01
1.43459153e+00 3.52688849e-01 2.32995376e-01 5.36054298e-02
3.66701156e-01 5.95261335e-01 9.80827928e-01 9.34986353e-01
1.38304725e-01 3.22015911e-01 4.72837269e-01 4.02989239e-01
6.29921973e-01 -4.59672898e-01 3.15978765e-01 6.12719059e-01
5.96761823e-01 -4.18675452e-01 -7.70809650e-01 6.17388010e-01
-2.01182795e+00 -8.33090305e-01 1.57895893e-01 2.80793643e+00
1.04774809e+00 2.19998449e-01 1.43977493e-01 8.04203600e-02
8.95357788e-01 -2.53038228e-01 -1.15956593e+00 -7.93947205e-02
3.57969761e-01 1.43087313e-01 6.77636325e-01 3.83517385e-01
-1.01864839e+00 1.92203194e-01 5.86791897e+00 9.98221040e-01
-9.63271081e-01 5.80743290e-02 1.02947843e+00 -5.27780414e-01
-3.70368898e-01 -2.35509157e-01 -9.34868574e-01 9.63467419e-01
1.03010190e+00 -6.96879685e-01 2.78686196e-01 9.72954154e-01
5.33435717e-02 -3.08380350e-02 -1.23906696e+00 7.95876920e-01
-1.13771580e-01 -8.37986827e-01 -3.53415519e-01 1.89558826e-02
8.93388987e-01 -4.62682754e-01 6.09562039e-01 6.23942971e-01
1.15389243e-01 -6.57610059e-01 6.49464428e-01 8.51370633e-01
1.06017292e+00 -1.23535705e+00 6.69538975e-01 5.89176893e-01
-1.04769444e+00 -4.52643275e-01 -4.89182621e-01 2.04252675e-01
1.40877485e-01 9.72087145e-01 -6.19965315e-01 5.69438756e-01
3.70848984e-01 4.84042197e-01 -1.41803116e-01 1.40663302e+00
3.65431719e-02 7.99179077e-01 -2.86018819e-01 -8.62415582e-02
-1.17363654e-01 -3.18980843e-01 4.34336811e-01 8.48379254e-01
6.51335180e-01 -3.36719573e-01 -1.23636611e-02 5.88828862e-01
-2.84206241e-01 5.52161820e-02 -4.96581346e-01 3.30698341e-01
6.02171719e-01 1.08936262e+00 -4.94409949e-01 -1.42527260e-02
-3.43504488e-01 8.85397553e-01 4.68284249e-01 2.92524099e-01
-1.14129424e+00 -4.34685737e-01 5.65998733e-01 1.21778794e-01
4.82957333e-01 1.69768572e-01 -1.01430140e-01 -1.14096141e+00
4.11889106e-01 -3.67572635e-01 6.78707898e-01 -2.62395777e-02
-1.86659575e+00 5.79487234e-02 2.14896694e-01 -1.25082672e+00
-2.52608031e-01 -4.74713445e-01 -7.19252050e-01 7.47402966e-01
-1.58956158e+00 -6.14558458e-01 1.68778479e-01 5.12024403e-01
6.68072224e-01 2.88208257e-02 2.39380136e-01 5.25068283e-01
-8.33581269e-01 1.25037134e+00 8.36170316e-01 -3.95318776e-01
6.47698045e-01 -1.59793520e+00 2.47760583e-02 7.08353877e-01
-2.36044437e-01 2.11866111e-01 6.95482075e-01 -6.71693206e-01
-1.37102520e+00 -1.45214677e+00 4.03013378e-01 -3.15890580e-01
9.67554629e-01 -4.08278614e-01 -1.04546511e+00 4.34434772e-01
-3.96554321e-01 8.79668146e-02 7.22083211e-01 9.85275060e-02
5.29998690e-02 -5.72933674e-01 -1.31088269e+00 4.64274019e-01
9.08183694e-01 -1.21130079e-01 -2.47920558e-01 3.35651398e-01
5.78219295e-01 -3.99226069e-01 -8.01147759e-01 5.33574760e-01
4.70351547e-01 -4.76425588e-01 5.72494447e-01 -8.58268321e-01
2.53085643e-01 5.53580932e-03 -3.72013412e-02 -1.38932455e+00
1.60825290e-02 -1.00673723e+00 -6.89205229e-01 1.48981082e+00
6.94842219e-01 -9.13742840e-01 9.05066609e-01 8.86221111e-01
1.56142294e-01 -1.08370781e+00 -1.38202751e+00 -9.64302480e-01
3.92502815e-01 -4.07670408e-01 4.47315276e-01 5.66409588e-01
-5.90030551e-02 6.28011152e-02 -5.73657334e-01 8.87581259e-02
8.28278601e-01 1.12605400e-01 5.67460895e-01 -1.24596047e+00
-5.88105798e-01 -3.54708701e-01 -8.65500048e-02 -1.08749485e+00
2.36279249e-01 -6.59820259e-01 2.92624593e-01 -1.01289070e+00
3.83430421e-01 -4.70948339e-01 -6.67836010e-01 2.61135936e-01
-6.49423182e-01 -4.33484048e-01 1.01915058e-02 -7.06592500e-02
-6.80060267e-01 9.39565241e-01 1.27036679e+00 2.20273554e-01
-2.16996461e-01 8.57256711e-01 -8.32298040e-01 5.04025936e-01
9.69930887e-01 -5.46871305e-01 -9.55011249e-01 -1.23992255e-02
2.90535897e-01 2.16796026e-01 3.41300964e-02 -8.35642338e-01
2.08920643e-01 -2.88391501e-01 3.92670900e-01 -5.91996789e-01
-4.95252572e-02 -1.03476179e+00 -4.36456921e-03 4.25557077e-01
-4.47671503e-01 -4.50542644e-02 1.95394501e-01 1.29366171e+00
5.36747351e-02 -3.45949024e-01 8.32289219e-01 4.56855953e-01
6.20335825e-02 7.68683672e-01 -2.39440948e-01 4.64629829e-01
1.36196077e+00 1.83362126e-01 -9.28286463e-02 -3.54792476e-01
-5.39963603e-01 7.11351931e-01 1.26375616e-01 1.72981873e-01
3.95025492e-01 -1.30907583e+00 -5.03477335e-01 4.58741449e-02
-1.13953881e-01 2.55169183e-01 5.56107223e-01 9.16462004e-01
1.31953076e-01 4.09770682e-02 2.12883428e-01 -4.45042223e-01
-8.66674900e-01 7.12310493e-01 3.53833824e-01 -5.53839266e-01
-3.97570461e-01 8.87712896e-01 2.68289238e-01 -8.07975456e-02
4.99000758e-01 -3.45451653e-01 1.31267905e-01 2.38213867e-01
6.22225761e-01 4.14444298e-01 9.39871091e-03 2.43549585e-01
-4.31736512e-03 3.37678730e-01 -4.53495026e-01 -9.63836536e-02
1.40547931e+00 -3.04454833e-01 3.83883387e-01 8.90305698e-01
1.16697752e+00 -9.64809731e-02 -1.94021606e+00 -4.09463555e-01
3.77743281e-02 -7.51805604e-01 -2.43294179e-01 -6.92780972e-01
-1.12449360e+00 8.24784160e-01 5.87228477e-01 3.97388607e-01
1.36625874e+00 -1.80996612e-01 7.69123733e-01 1.75416663e-01
3.95256191e-01 -1.31508827e+00 -1.06671691e-01 4.01245743e-01
5.93744278e-01 -1.06575179e+00 -1.50305241e-01 -3.54258642e-02
-5.92889726e-01 9.03823972e-01 7.28426397e-01 3.15607004e-02
9.56906199e-01 4.20218199e-01 -5.86763918e-01 3.81181419e-01
-9.74817932e-01 1.70596465e-01 3.51266354e-01 3.73758674e-01
7.81002790e-02 5.89983687e-02 -7.73517862e-02 9.96979892e-01
-4.50452045e-02 -1.17429256e-01 1.71915159e-01 9.15318966e-01
-2.68136442e-01 -1.18634868e+00 -1.51741654e-01 9.40283895e-01
-6.41950309e-01 2.40098894e-01 -7.44761676e-02 7.69842684e-01
-1.79778725e-01 5.09824812e-01 1.62728146e-01 -8.37302655e-02
5.00538111e-01 1.41171381e-01 5.14554143e-01 -4.96859431e-01
-2.24499851e-01 -3.73578966e-02 -3.66247475e-01 -1.83240309e-01
1.00832202e-01 -9.77197766e-01 -9.44864035e-01 -2.81830907e-01
-3.95079046e-01 2.79534400e-01 4.43853199e-01 8.02748919e-01
1.48998141e-01 5.91471851e-01 1.21908307e+00 -4.32796329e-01
-1.46575987e+00 -7.43221521e-01 -8.60183060e-01 2.44810842e-02
4.77679372e-01 -6.69941902e-01 -6.80899739e-01 -1.00652426e-01] | [8.164678573608398, 3.866518974304199] |
452908fb-8bc8-47ad-9c22-ddc2b47aafb6 | how-much-can-clip-benefit-vision-and-language | 2107.06383 | null | https://arxiv.org/abs/2107.06383v1 | https://arxiv.org/pdf/2107.06383v1.pdf | How Much Can CLIP Benefit Vision-and-Language Tasks? | Most existing Vision-and-Language (V&L) models rely on pre-trained visual encoders, using a relatively small set of manually-annotated data (as compared to web-crawled data), to perceive the visual world. However, it has been observed that large-scale pretraining usually can result in better generalization performance, e.g., CLIP (Contrastive Language-Image Pre-training), trained on a massive amount of image-caption pairs, has shown a strong zero-shot capability on various vision tasks. To further study the advantage brought by CLIP, we propose to use CLIP as the visual encoder in various V&L models in two typical scenarios: 1) plugging CLIP into task-specific fine-tuning; 2) combining CLIP with V&L pre-training and transferring to downstream tasks. We show that CLIP significantly outperforms widely-used visual encoders trained with in-domain annotated data, such as BottomUp-TopDown. We achieve competitive or better results on diverse V&L tasks, while establishing new state-of-the-art results on Visual Question Answering, Visual Entailment, and V&L Navigation tasks. We release our code at https://github.com/clip-vil/CLIP-ViL. | ['Kurt Keutzer', 'Zhewei Yao', 'Kai-Wei Chang', 'Anna Rohrbach', 'Mohit Bansal', 'Hao Tan', 'Liunian Harold Li', 'Sheng Shen'] | 2021-07-13 | null | null | null | null | ['visual-entailment'] | ['reasoning'] | [-3.09484396e-02 6.96474388e-02 -1.44736782e-01 -3.17988932e-01
-9.12328243e-01 -7.73782969e-01 7.67026365e-01 1.23852283e-01
-6.34772122e-01 2.90657282e-01 2.39087418e-01 -5.62561035e-01
6.09231055e-01 -4.92882311e-01 -1.29030466e+00 -1.77779570e-01
3.90337467e-01 3.09978873e-01 3.59917521e-01 -2.52198845e-01
6.61565959e-02 -6.62397519e-02 -1.41843247e+00 6.87984586e-01
6.70494974e-01 1.07552624e+00 6.63456857e-01 8.78249884e-01
-2.84643143e-01 1.26001000e+00 -3.10804695e-01 -7.67171621e-01
2.03989923e-01 -4.08752948e-01 -8.12317312e-01 1.02688141e-01
7.61452556e-01 -4.65624124e-01 -5.22061110e-01 9.63002026e-01
3.49455327e-01 1.13781448e-02 5.76034784e-01 -1.42376959e+00
-1.60629845e+00 3.64299685e-01 -6.45940185e-01 2.42538661e-01
3.73087049e-01 6.02533102e-01 1.13612533e+00 -1.38506377e+00
8.80166292e-01 1.42793763e+00 5.65250039e-01 5.91381252e-01
-1.10110211e+00 -2.74439394e-01 2.78327852e-01 5.90582490e-01
-1.30479848e+00 -5.24056554e-01 6.85790002e-01 -5.66419005e-01
1.23951006e+00 -1.27666861e-01 3.98879379e-01 1.39070249e+00
-9.84619707e-02 1.14420545e+00 9.55172122e-01 -5.35602272e-01
-3.63717973e-02 2.48987839e-01 -2.27245651e-02 8.45858514e-01
5.73367700e-02 5.83520010e-02 -4.35588926e-01 3.71210724e-01
4.79965419e-01 -1.05319075e-01 -4.61148053e-01 -4.81009603e-01
-1.17066789e+00 7.61086524e-01 1.03633654e+00 1.30466476e-01
-2.07910866e-01 3.44607472e-01 7.18734622e-01 3.83535713e-01
2.59079456e-01 3.56088698e-01 -4.25665677e-01 1.11384146e-01
-7.47338176e-01 -4.38779965e-02 5.51554322e-01 1.14075506e+00
8.29942346e-01 6.87834527e-03 -5.21367729e-01 8.07983637e-01
2.65815943e-01 5.86964786e-01 3.99263620e-01 -8.55543852e-01
8.14887106e-01 3.82842809e-01 -8.04073643e-03 -5.67040145e-01
-1.42180309e-01 -2.65919626e-01 -6.83444440e-01 2.03720734e-01
5.70346177e-01 2.34917831e-02 -1.25202847e+00 1.81525540e+00
-5.31707965e-02 -1.04577076e-02 2.91736841e-01 1.01594722e+00
1.19827187e+00 8.36044908e-01 3.00249696e-01 1.89787284e-01
1.47503304e+00 -1.60342956e+00 -5.18302977e-01 -7.03266263e-01
6.13197565e-01 -6.34113014e-01 1.71452045e+00 1.43259749e-01
-1.12766755e+00 -9.88110542e-01 -8.51793051e-01 -7.51687050e-01
-6.55137181e-01 2.64517903e-01 3.11677426e-01 1.48384437e-01
-1.26776814e+00 9.67417955e-02 -5.88443220e-01 -5.72047949e-01
6.50458694e-01 -3.22762489e-01 -4.84304577e-01 -4.60645020e-01
-1.15768766e+00 9.93481219e-01 2.97254175e-01 1.48830324e-01
-1.51772475e+00 -6.16798341e-01 -1.19904542e+00 7.97794685e-02
5.65033078e-01 -9.18541491e-01 1.34053576e+00 -1.23910236e+00
-1.02271390e+00 1.15676403e+00 -1.53227359e-01 -5.61223507e-01
6.66280150e-01 -3.82509917e-01 -8.82627256e-03 3.93601030e-01
1.91472948e-01 1.12790120e+00 8.25357020e-01 -1.53840625e+00
-2.89590925e-01 -2.06617743e-01 4.31698501e-01 1.75655946e-01
-2.66778171e-01 -1.40643626e-01 -1.09126246e+00 -3.20074439e-01
-5.75492442e-01 -7.26998091e-01 -5.06128147e-02 3.84581089e-01
-3.04802477e-01 -3.79942805e-01 6.53004825e-01 -8.98465455e-01
8.01217437e-01 -2.06696916e+00 4.82361466e-02 -3.75365168e-01
2.39310145e-01 6.03299141e-01 -6.39570594e-01 6.68517053e-01
1.30416408e-01 3.05897743e-02 -2.49547347e-01 -5.51397920e-01
6.56915829e-02 3.28678697e-01 -2.82295913e-01 1.82515040e-01
3.50521773e-01 1.55051577e+00 -9.11328316e-01 -6.75384283e-01
4.29308742e-01 4.22999233e-01 -6.70531213e-01 4.50241446e-01
-5.29690564e-01 2.94395983e-01 -7.69871622e-02 7.21124470e-01
4.47783202e-01 -7.59548187e-01 -6.88622845e-03 -3.41569513e-01
5.05371690e-02 -1.03399768e-01 -4.28178310e-01 2.01960731e+00
-8.61832142e-01 1.17294669e+00 -2.43762396e-02 -1.19172347e+00
6.03123784e-01 2.19810799e-01 -1.84784979e-01 -1.25030947e+00
8.24285522e-02 -1.13999918e-01 -1.38783649e-01 -1.00764585e+00
2.24751949e-01 1.95997179e-01 -6.86013773e-02 7.61668012e-02
5.08807003e-01 -1.19080292e-02 3.79811972e-01 6.08990133e-01
8.66296649e-01 3.10733795e-01 3.14918667e-01 1.68441221e-01
5.79182088e-01 9.26309451e-02 1.13342270e-01 9.69315410e-01
-4.91351694e-01 7.04934597e-01 6.25634193e-01 -7.92467222e-02
-1.28563619e+00 -1.11109006e+00 6.34834245e-02 1.39115918e+00
2.52104908e-01 -4.10733730e-01 -7.62336731e-01 -7.05818176e-01
1.23185448e-01 8.42120409e-01 -8.41186047e-01 -8.25206339e-02
-3.14880848e-01 -1.20302714e-01 6.21149719e-01 9.11432624e-01
6.20411217e-01 -1.39867926e+00 -5.29906094e-01 -8.63712355e-02
-1.42809883e-01 -1.64625621e+00 -4.12566304e-01 4.07121330e-03
-2.65966386e-01 -9.81815338e-01 -9.15553689e-01 -9.81211841e-01
6.36732340e-01 5.18645585e-01 1.57033646e+00 1.64754927e-01
-2.62612581e-01 7.68715739e-01 -6.38415754e-01 -3.99721861e-01
-2.85169423e-01 -1.33497089e-01 -4.92994249e-01 -1.30987793e-01
1.96349695e-01 -2.31385410e-01 -7.81809509e-01 -2.96922657e-03
-9.17266965e-01 2.21240044e-01 7.87619233e-01 9.73815680e-01
4.62785602e-01 -7.80024350e-01 4.64099914e-01 -8.14284086e-01
6.14480436e-01 -3.60391825e-01 -4.14855629e-01 6.53164148e-01
-3.08270603e-01 8.94434378e-02 7.09108055e-01 -3.56617063e-01
-9.70148027e-01 -5.72642609e-02 -2.98318386e-01 -9.89718914e-01
-1.52491704e-01 5.45721531e-01 -1.66367721e-02 1.00835286e-01
8.05007696e-01 4.10042524e-01 -1.21599346e-01 -4.44774240e-01
1.11162674e+00 6.72661781e-01 8.79177094e-01 -3.92150074e-01
6.90850079e-01 4.35017228e-01 -4.83072728e-01 -6.71556354e-01
-1.08568621e+00 -5.33702016e-01 -6.29840195e-01 -2.32292980e-01
1.29071200e+00 -1.23633003e+00 -5.88905334e-01 2.20536262e-01
-1.31256104e+00 -7.72119224e-01 -7.12048933e-02 9.20046493e-02
-5.68636894e-01 4.21854377e-01 -5.96888304e-01 -6.00167394e-01
-5.01785934e-01 -1.07851350e+00 1.21154618e+00 1.03149228e-01
2.33199865e-01 -9.29823518e-01 2.91205943e-02 5.78486681e-01
2.80309528e-01 -3.71362269e-02 7.65264392e-01 -4.23226535e-01
-5.69690645e-01 4.96556684e-02 -9.24813449e-01 7.02311456e-01
-3.90268147e-01 -1.52498677e-01 -1.16690528e+00 -4.33929116e-01
-4.33400363e-01 -1.02366209e+00 1.27285898e+00 1.79078862e-01
1.51518667e+00 -1.79423735e-01 -2.43512005e-01 7.09202111e-01
1.74428594e+00 -7.71396384e-02 6.42200112e-01 2.01615915e-01
1.00997901e+00 4.74712998e-01 5.21338105e-01 1.23173006e-01
7.46944070e-01 5.49757838e-01 7.60542333e-01 -3.00005883e-01
-5.01488030e-01 -6.32300436e-01 4.50754881e-01 6.44899428e-01
-1.05053773e-02 -5.09826541e-01 -1.09489083e+00 8.59728575e-01
-2.03475499e+00 -8.80726874e-01 1.18000902e-01 1.77218533e+00
6.90931499e-01 2.90452186e-02 5.10733463e-02 -4.10460502e-01
5.69550097e-01 2.64951706e-01 -6.27754033e-01 -3.40206832e-01
-3.58174630e-02 1.30536586e-01 5.14278412e-01 5.45016229e-01
-9.99512196e-01 1.23386204e+00 5.56905937e+00 6.40206099e-01
-1.17910969e+00 5.77997565e-01 4.60889995e-01 -1.67236347e-02
-3.19358736e-01 -2.23430004e-02 -4.41922545e-01 3.83453339e-01
6.79873407e-01 6.62936717e-02 2.98819602e-01 1.11135137e+00
-7.50146583e-02 1.04850464e-01 -1.23427022e+00 1.23068559e+00
5.15973330e-01 -1.41855681e+00 3.00268173e-01 -3.20366859e-01
6.13576591e-01 5.48063993e-01 3.87202464e-02 7.61603653e-01
2.65354514e-01 -1.02815378e+00 9.39529121e-01 3.28318775e-01
1.09252954e+00 -3.11670452e-01 5.64294636e-01 3.14528674e-01
-1.19356120e+00 -8.23080018e-02 -5.51677585e-01 4.13704850e-02
2.87773669e-01 1.68113470e-01 -6.28985405e-01 4.20725405e-01
8.04092050e-01 8.90272260e-01 -1.00609028e+00 8.81221414e-01
-5.64566016e-01 4.94219631e-01 1.53427213e-01 1.85560696e-02
4.48823422e-01 1.81564420e-01 1.45139143e-01 1.39584816e+00
4.00113836e-02 -2.24734634e-01 2.47481510e-01 9.67239916e-01
-3.14385533e-01 2.12797467e-02 -7.52447307e-01 -1.13958851e-01
2.82218605e-01 1.16513085e+00 -2.18859717e-01 -7.16129124e-01
-1.06110430e+00 1.29186714e+00 8.33818436e-01 6.97823048e-01
-1.04910350e+00 -3.53631556e-01 4.01707113e-01 2.32110955e-02
6.04324579e-01 -2.42216215e-01 9.06643197e-02 -1.36502671e+00
-6.70670643e-02 -7.99987733e-01 3.75071585e-01 -1.58713269e+00
-1.38994503e+00 7.01679051e-01 -1.67653769e-01 -9.60884035e-01
-2.05842137e-01 -1.07744956e+00 -5.66082597e-01 6.17522597e-01
-1.88845575e+00 -1.52765334e+00 -7.07081139e-01 8.78287673e-01
8.78664255e-01 3.84046175e-02 3.63172293e-01 2.38878414e-01
-4.53687191e-01 6.80777311e-01 -1.62685275e-01 3.96429330e-01
8.19763541e-01 -1.34714496e+00 5.59094787e-01 9.75689650e-01
5.38989484e-01 2.75013804e-01 4.50905979e-01 -2.46822521e-01
-1.41970110e+00 -1.16588855e+00 6.99858069e-01 -7.49529064e-01
7.53845811e-01 -7.26107299e-01 -9.83361542e-01 1.00154960e+00
7.50573635e-01 3.66393477e-01 3.47295374e-01 -7.26115629e-02
-8.07924986e-01 5.07757924e-02 -7.28405535e-01 6.46265566e-01
1.25087738e+00 -1.05142832e+00 -8.16934645e-01 4.99597639e-01
9.34863746e-01 -2.69966364e-01 -5.75777352e-01 2.11783513e-01
4.24810469e-01 -9.42467034e-01 1.29662240e+00 -7.83107877e-01
9.02036965e-01 -2.35437006e-01 -2.12602884e-01 -1.18926299e+00
-2.52947986e-01 -1.63219914e-01 -7.11340234e-02 1.06455433e+00
4.43122149e-01 -3.00292194e-01 3.15348029e-01 1.86987773e-01
-2.74423003e-01 -7.65522063e-01 -4.98616040e-01 -6.88676894e-01
1.74908310e-01 -5.35842717e-01 -4.01203670e-02 8.02048743e-01
-1.72708452e-01 6.17241979e-01 -5.32649577e-01 3.97604890e-02
5.37473857e-01 1.17579915e-01 1.07024395e+00 -7.07710385e-01
-4.55984682e-01 -3.23928595e-01 -1.27664268e-01 -1.34314656e+00
2.22877041e-01 -1.12537801e+00 1.25724062e-01 -1.94629776e+00
3.87319416e-01 1.21617712e-01 -3.66140723e-01 6.58502042e-01
-4.29645717e-01 6.07869923e-01 5.73113918e-01 2.10690334e-01
-1.07798386e+00 5.42019129e-01 1.61624753e+00 -3.34466070e-01
1.67632878e-01 -6.59366310e-01 -6.60866380e-01 6.23767436e-01
4.94239151e-01 2.38541956e-03 -5.44992864e-01 -8.80557120e-01
3.03322911e-01 4.50589433e-02 6.86610878e-01 -7.96008348e-01
9.02392343e-02 8.47996995e-02 4.60246861e-01 -4.70727861e-01
3.57481033e-01 -5.15457392e-01 -5.76661527e-01 3.31849158e-01
-5.11210501e-01 1.59548685e-01 1.96881086e-01 6.78067327e-01
-4.75084007e-01 -1.46131217e-01 7.18945026e-01 -4.28874254e-01
-1.44735134e+00 3.08208406e-01 -7.29300380e-02 4.71577168e-01
9.46137488e-01 5.45331761e-02 -7.57972658e-01 -6.09809339e-01
-6.92163169e-01 5.06725788e-01 4.84472990e-01 6.61185145e-01
6.36635602e-01 -1.18043780e+00 -7.19380200e-01 -7.89522007e-02
7.80916035e-01 -1.24167845e-01 4.39769953e-01 7.88725913e-01
-6.35463595e-01 5.65611660e-01 -2.78458059e-01 -8.15729737e-01
-1.15313268e+00 1.12814343e+00 1.99682400e-01 -8.11446533e-02
-6.86001182e-01 1.12929797e+00 7.44851470e-01 -2.02401221e-01
2.33264729e-01 -4.15305406e-01 -1.38972793e-02 -2.92858332e-02
4.57464188e-01 -1.41673028e-01 -1.96351960e-01 -5.30009687e-01
-4.36025679e-01 5.94955266e-01 2.57371832e-02 -1.18999481e-01
9.69031751e-01 -3.03377330e-01 1.94995955e-01 2.95408309e-01
1.44807327e+00 -3.51531506e-01 -1.55632222e+00 -4.54429030e-01
-2.63203233e-01 -3.40050727e-01 -2.12953631e-02 -8.30448985e-01
-1.12556601e+00 1.45184672e+00 4.09771979e-01 5.58919907e-02
1.07364953e+00 4.40399379e-01 6.91901743e-01 5.72227478e-01
1.95536822e-01 -9.72982347e-01 5.36053777e-01 4.35629249e-01
1.20562971e+00 -1.69845200e+00 -3.59331846e-01 -1.74096048e-01
-1.11613142e+00 7.81886637e-01 8.97657871e-01 -2.36446366e-01
3.97354424e-01 -1.41997263e-01 3.55936974e-01 -8.41709971e-02
-1.09414685e+00 -8.32469523e-01 4.12272573e-01 8.30074131e-01
3.66956145e-01 -1.05929151e-01 6.99145496e-02 3.70250374e-01
1.07361630e-01 2.64378283e-02 2.99616367e-01 6.71810150e-01
-3.24197561e-01 -8.06357503e-01 -2.19626501e-02 1.68475196e-01
-1.10056095e-01 -4.20514762e-01 -4.20051306e-01 9.58936095e-01
1.34236962e-01 8.22338641e-01 1.89507008e-01 -1.12689532e-01
3.05518717e-01 1.28801420e-01 6.94805622e-01 -4.94413316e-01
-3.40678155e-01 -2.22102731e-01 1.28936097e-01 -8.42628181e-01
-3.24141979e-01 -2.39769682e-01 -9.32789385e-01 8.92019570e-02
7.85598233e-02 -2.65276402e-01 5.85201144e-01 9.87542570e-01
4.26633596e-01 6.37010992e-01 9.65614170e-02 -8.52465272e-01
-3.56073052e-01 -1.03091073e+00 -1.16138890e-01 9.24447000e-01
5.00006378e-01 -6.22740328e-01 -2.49154851e-01 2.49809086e-01] | [10.75590705871582, 1.6552002429962158] |
7b3c0005-a92f-4dec-aae6-710eb3654b94 | partition-based-stability-of-coalitional | 2304.10651 | null | https://arxiv.org/abs/2304.10651v1 | https://arxiv.org/pdf/2304.10651v1.pdf | Partition-based Stability of Coalitional Games | We are concerned with the stability of a coalitional game, i.e., a transferable-utility (TU) cooperative game. First, the concept of core can be weakened so that the blocking of changes is limited to only those with multilateral backings. This principle of consensual blocking, as well as the traditional core-defining principle of unilateral blocking and one straddling in between, can all be applied to partition-allocation pairs. Each such pair is made up of a partition of the grand coalition and a corresponding allocation vector whose components are individually rational and efficient for the various constituent coalitions of the given partition. For the resulting strong, medium, and weak stability concepts, the first is core-compatible in that the traditional core exactly contains those allocations that are associated through this strong stability concept with the all-consolidated partition consisting of only the grand coalition. Probably more importantly, the latter medium and weak stability concepts are universal. By this, we mean that any game, no matter how ``poor'' it is, has its fair share of stable solutions. There is also a steepest ascent method to guide the convergence process to a mediumly stable partition-allocation pair from any starting partition. | ['Jian Yang'] | 2023-04-20 | null | null | null | null | ['blocking'] | ['natural-language-processing'] | [-1.55608803e-01 6.87652826e-01 -1.51363626e-01 3.68601531e-01
-3.54975373e-01 -1.12267363e+00 5.26041090e-01 -3.14755812e-02
-4.97210205e-01 1.27445924e+00 3.46686423e-01 -5.61716318e-01
-9.05548692e-01 -1.06219053e+00 -1.77205011e-01 -1.10354555e+00
-2.03462616e-01 8.38328063e-01 3.63768190e-01 -7.92032659e-01
-1.14224933e-01 1.78323001e-01 -1.36006522e+00 -1.40739679e-01
9.75000083e-01 8.70368004e-01 3.08085978e-02 4.44380432e-01
8.30721408e-02 8.72243106e-01 -3.68363231e-01 -6.28492355e-01
6.83643043e-01 -3.21415186e-01 -9.92293835e-01 -1.34115711e-01
-7.63242066e-01 7.94453546e-02 -6.87635764e-02 1.04407525e+00
2.22056806e-01 5.17352112e-02 7.48922825e-01 -1.61729491e+00
-2.34585688e-01 1.01382041e+00 -8.15919518e-01 -2.07322568e-01
2.76609629e-01 -3.59666735e-01 1.46486580e+00 -2.80478954e-01
8.30991864e-01 8.89858305e-01 3.27503115e-01 5.32137215e-01
-1.46844459e+00 -4.85631317e-01 7.50641301e-02 -2.15254143e-01
-1.19418621e+00 -2.57556111e-01 3.23611587e-01 -3.99847895e-01
6.15643859e-01 9.42828774e-01 9.66572106e-01 4.71725836e-02
2.35609546e-01 2.74925828e-01 1.20654655e+00 -4.67487037e-01
2.69430906e-01 -6.28530933e-03 -6.84694499e-02 4.23348583e-02
7.64112651e-01 1.92683920e-01 6.29174784e-02 -3.43200505e-01
4.83783573e-01 -4.88218248e-01 -5.76267064e-01 -1.14057422e+00
-8.76635611e-01 7.99414456e-01 3.10883671e-01 4.93066192e-01
-2.98271388e-01 -3.83334011e-02 3.86795819e-01 5.31914175e-01
2.67148912e-01 6.32077515e-01 -4.36588794e-01 2.14899465e-01
-8.12158585e-01 5.41929781e-01 1.08056462e+00 5.95654130e-01
9.25149024e-01 -2.20832273e-01 2.07863435e-01 3.03192198e-01
6.06497638e-02 2.31064707e-01 -6.07837737e-02 -1.43671620e+00
3.37123454e-01 5.82855940e-01 4.29562479e-01 -8.40908825e-01
-6.36875629e-01 -7.06514537e-01 -9.34182286e-01 6.58806860e-01
5.72899282e-01 -2.85051346e-01 -3.90943438e-02 2.30156517e+00
3.24065536e-01 -5.00591397e-01 1.57066658e-01 5.98052740e-01
2.60553390e-01 5.98457456e-01 -2.48982921e-01 -9.74903286e-01
9.51069295e-01 -2.19003171e-01 -3.87035251e-01 8.44746754e-02
5.31141341e-01 -5.31536579e-01 3.42751861e-01 1.19062647e-01
-1.51451504e+00 3.06372702e-01 -8.89823616e-01 5.80339253e-01
3.56381200e-02 -6.18009150e-01 6.72527552e-01 6.91749394e-01
-1.52394390e+00 4.58047390e-01 -2.55975693e-01 -1.60051435e-01
-4.87260483e-02 7.04286277e-01 -6.42091215e-01 4.02004719e-01
-1.19603026e+00 1.14824128e+00 5.28461277e-01 -4.81573753e-02
-3.82448435e-01 -5.93371034e-01 -5.07072806e-01 4.63507861e-01
7.41533518e-01 -7.12469339e-01 1.05324936e+00 -1.32195401e+00
-9.60979819e-01 9.54522014e-01 4.35732335e-01 -1.24549128e-01
7.06165493e-01 7.68156946e-01 7.62926182e-03 -8.68781731e-02
5.62412381e-01 3.16774428e-01 1.21141396e-01 -1.60850537e+00
-9.56609786e-01 -2.15251595e-01 4.97889280e-01 7.41130173e-01
-2.91562319e-01 4.15815204e-01 7.85658583e-02 -1.74481288e-01
3.27718139e-01 -8.89768183e-01 -5.07032275e-01 -3.40131730e-01
-2.79867470e-01 -3.57671410e-01 1.71408489e-01 -3.51817548e-01
1.44847441e+00 -1.90326691e+00 5.01599610e-01 7.69560397e-01
5.38816631e-01 -4.24102426e-01 1.02164759e-03 5.28142273e-01
-5.10232925e-01 2.16820598e-01 -1.73535511e-01 2.39415690e-01
3.99455845e-01 1.32404879e-01 -8.21975544e-02 6.88366532e-01
-5.20049572e-01 6.42524958e-01 -7.76311457e-01 -3.32939297e-01
-2.19396606e-01 -5.45686960e-01 -9.92193997e-01 -2.61473984e-01
2.01645091e-01 6.78640790e-05 -2.72457629e-01 3.82675603e-02
6.90990269e-01 1.14770651e-01 9.52731013e-01 2.85958469e-01
-6.57656789e-01 1.04939178e-01 -1.69403708e+00 1.09114015e+00
1.71495557e-01 1.13010861e-01 8.32311213e-01 -1.12084258e+00
5.14506400e-01 5.53111374e-01 1.10002446e+00 -3.10366392e-01
3.38995218e-01 5.75625241e-01 6.07112527e-01 1.50649652e-01
7.80264437e-01 -4.45272565e-01 -4.97432798e-01 1.01760900e+00
-1.72061726e-01 -1.81698218e-01 5.50538719e-01 8.10759902e-01
9.46396053e-01 -1.96631894e-01 7.21148133e-01 -1.09396851e+00
5.12295842e-01 -2.74218706e-04 9.75691497e-01 5.74428439e-01
-3.99748534e-01 7.76658580e-02 1.16200376e+00 -1.82399843e-02
-1.26715207e+00 -1.30366266e+00 4.40626182e-02 1.11028433e+00
3.00152153e-01 -3.37025523e-01 -7.39277482e-01 -1.93967283e-01
-3.55994701e-02 2.67820179e-01 -7.84693837e-01 -3.17230076e-02
-3.06040734e-01 -6.39105082e-01 4.74814512e-02 1.16658881e-01
2.95724452e-01 -7.00472414e-01 -4.54965144e-01 3.91797423e-01
-5.10115862e-01 -3.27366054e-01 -5.71176410e-01 2.88582325e-01
-4.09412175e-01 -1.43769097e+00 -6.79412365e-01 -7.74885297e-01
5.67619383e-01 2.64377892e-01 8.95000339e-01 2.37158015e-01
3.40563983e-01 1.40125290e-01 -2.30425879e-01 -2.52317846e-01
-4.09757107e-01 -1.55752629e-01 3.73660535e-01 -9.03190225e-02
-3.93613428e-01 -6.67910457e-01 -3.46140474e-01 3.05301696e-01
-7.10880220e-01 3.92522626e-02 -1.24302275e-01 7.03044057e-01
8.52229595e-02 4.58211780e-01 8.11325192e-01 -4.01296526e-01
9.49165404e-01 -5.02616286e-01 -5.32284379e-01 4.46064591e-01
-4.97436851e-01 -2.78552085e-01 3.30038458e-01 -1.58004612e-02
-1.06965685e+00 -3.43700796e-01 1.99195653e-01 4.04997766e-01
4.93209243e-01 7.39869535e-01 -5.93288779e-01 -1.09447092e-02
6.12316966e-01 4.14142571e-03 1.63529485e-01 -2.06735451e-02
5.34809887e-01 6.17071927e-01 5.65766215e-01 -9.15970504e-01
8.06201637e-01 4.81714875e-01 3.42036560e-02 -3.70291591e-01
-9.82359573e-02 -2.54724026e-01 -4.63598549e-01 -5.92559397e-01
6.69342399e-01 -6.47771835e-01 -1.19727147e+00 5.10610044e-01
-8.58163357e-01 -4.48687859e-02 -8.12812269e-01 3.38726491e-01
-9.93069053e-01 4.55565751e-01 -4.59895402e-01 -1.05385458e+00
-3.02522015e-02 -8.78581941e-01 -5.20885773e-02 2.79662441e-02
-4.11367148e-01 -7.64163494e-01 3.40875149e-01 1.43879443e-01
3.96323740e-01 2.03965247e-01 8.79944384e-01 -4.43791866e-01
-3.67906123e-01 2.71879137e-02 -3.87518629e-02 8.33952576e-02
1.73174024e-01 1.25150695e-01 -2.21987039e-01 -7.45402157e-01
1.14892952e-01 -1.42270252e-01 3.86170536e-01 6.27561569e-01
1.13846041e-01 -5.06864667e-01 -3.83081347e-01 7.90775642e-02
1.45027769e+00 4.97666806e-01 5.91658354e-01 6.05220079e-01
-6.66481629e-03 8.73528242e-01 4.41459626e-01 4.21154976e-01
6.27724230e-01 7.08776295e-01 4.37838078e-01 -1.09585777e-01
6.34850025e-01 2.70432264e-01 1.23397313e-01 8.50396454e-01
-6.81686521e-01 4.55467291e-02 -6.59215748e-01 6.73367441e-01
-2.18549037e+00 -1.45062447e+00 -6.20026775e-02 2.37130857e+00
9.72580075e-01 2.08219722e-01 5.27127922e-01 5.14290035e-01
7.93401122e-01 -1.41198626e-02 -6.74747070e-03 -8.00475359e-01
-4.48230296e-01 1.29721865e-01 4.40932810e-01 6.92668736e-01
-8.56524229e-01 4.41029727e-01 6.40744305e+00 1.01665223e+00
-5.15865207e-01 1.55074954e-01 3.93272549e-01 -3.24074626e-01
-7.82331944e-01 3.73962283e-01 -1.16349213e-01 3.89749587e-01
3.40383738e-01 -1.03979790e+00 4.90177780e-01 5.18657386e-01
4.03311253e-01 -4.36433792e-01 -5.49352825e-01 2.36589924e-01
-4.47553396e-01 -1.42745388e+00 -3.73709917e-01 4.57541615e-01
1.14784992e+00 -3.80716413e-01 -2.42596105e-01 -1.72497407e-02
1.13120925e+00 -7.25618780e-01 1.25218701e+00 1.15086451e-01
9.35903668e-01 -1.33858323e+00 5.72128594e-01 5.77570975e-01
-1.52934682e+00 -3.81572634e-01 -1.52854174e-02 -5.89925349e-01
2.50621557e-01 1.79243192e-01 1.93174303e-01 1.05089033e+00
6.02344692e-01 2.66588740e-02 3.42627347e-01 1.00006819e+00
-4.59627211e-02 -2.29286100e-03 -2.99426228e-01 3.11565369e-01
3.58185947e-01 -7.34052122e-01 6.52836204e-01 4.59435135e-01
2.35209644e-01 7.40216374e-01 2.38766253e-01 5.65174878e-01
9.68011171e-02 2.06852525e-01 -5.17708421e-01 6.53680146e-01
6.05429649e-01 1.21500516e+00 -1.01936531e+00 -1.50127053e-01
-2.54571170e-01 2.63678104e-01 8.42615142e-02 3.22710723e-01
-6.32136405e-01 -2.39965394e-01 1.12093985e+00 1.97207868e-01
-1.24866711e-02 3.19344513e-02 -4.36345011e-01 -1.06325102e+00
-2.74445683e-01 -8.45637202e-01 6.99822128e-01 -6.11434460e-01
-9.03919458e-01 5.08195400e-01 1.03695817e-01 -1.12311256e+00
-2.09344298e-01 -1.70097128e-01 -1.01239371e+00 1.00211084e+00
-9.74973083e-01 -9.30347502e-01 5.51862776e-01 8.90419066e-01
-2.93736219e-01 -5.88026177e-03 6.58784568e-01 8.47678110e-02
-3.12217206e-01 2.87648320e-01 4.93468136e-01 -1.11856714e-01
4.16580737e-02 -1.19451344e+00 -4.93215531e-01 1.08152735e+00
-3.84199768e-01 5.91934681e-01 8.61417413e-01 -5.47894895e-01
-6.36383712e-01 -5.12653470e-01 1.11204433e+00 -6.90068156e-02
1.09243143e+00 -2.32914418e-01 -3.76010209e-01 7.10351050e-01
4.80461627e-01 -7.76938140e-01 4.41191822e-01 3.04285318e-01
3.30547728e-02 -2.56172836e-01 -1.07617772e+00 8.39365780e-01
1.03470671e+00 -1.26961485e-01 -5.87140322e-01 -1.62722077e-02
4.56730068e-01 -6.44152984e-02 -7.42765605e-01 4.16006178e-01
5.41612625e-01 -9.40460205e-01 8.01412642e-01 -5.85773528e-01
2.63848394e-01 -4.84465152e-01 -1.87775061e-01 -1.49833763e+00
-1.06276631e+00 -7.92080700e-01 7.16595531e-01 1.12716269e+00
5.06206393e-01 -9.28687513e-01 9.15496230e-01 6.46642506e-01
-1.63657755e-01 -5.97912610e-01 -1.51630688e+00 -9.98677492e-01
7.92856038e-01 -2.03016307e-02 7.15885520e-01 1.04285741e+00
9.21349287e-01 2.68750578e-01 -3.80551249e-01 -4.03030097e-01
8.82371724e-01 4.17182416e-01 4.88327026e-01 -1.50029314e+00
-3.53039175e-01 -9.12384152e-01 -1.43822923e-01 -3.50077868e-01
-6.28314540e-03 -9.40417111e-01 -2.56448209e-01 -1.61185968e+00
5.77805459e-01 -8.29294443e-01 -8.47544372e-02 3.49626660e-01
2.56491959e-01 4.79280315e-02 7.88165987e-01 5.40881395e-01
-4.49384212e-01 1.92087069e-01 1.24771845e+00 -7.24821389e-02
-3.12041312e-01 1.74257815e-01 -1.44238913e+00 6.61301970e-01
7.96204209e-01 -3.42326164e-01 -3.67760599e-01 2.76833594e-01
5.91140747e-01 4.61284369e-01 -4.28702720e-02 -4.59306031e-01
4.60535645e-01 -6.44782603e-01 -3.42422724e-01 -1.84017479e-01
-2.86282580e-02 -7.92562485e-01 9.16637003e-01 9.76634741e-01
-1.68771774e-01 -1.27271399e-01 -1.67987496e-01 1.43141389e-01
1.15397260e-01 -2.60939747e-01 8.38643253e-01 -2.04283908e-01
-3.41039091e-01 3.98993641e-02 -7.19839096e-01 7.86856711e-02
1.52830875e+00 -6.55366421e-01 -3.99082839e-01 -7.67316222e-01
-8.45768690e-01 5.47464788e-01 6.93039417e-01 -1.65860429e-01
2.10656654e-02 -1.45996809e+00 -1.08241463e+00 -3.02821994e-01
-2.26087287e-01 -2.82782108e-01 1.71506792e-01 9.84145939e-01
-1.93091065e-01 4.61990654e-01 -6.74038768e-01 -3.69156525e-02
-1.39452147e+00 5.06445050e-01 6.39395118e-01 -6.63418710e-01
-1.23557277e-01 6.35439336e-01 7.31091380e-01 -4.58442181e-01
-1.41021401e-01 1.75091699e-01 -3.30226183e-01 4.67179447e-01
1.89691156e-01 4.47634339e-01 -2.11520001e-01 -9.05672610e-01
-5.33782601e-01 2.08411381e-01 3.64044338e-01 -5.01813829e-01
1.45280612e+00 -4.05345559e-01 -1.07797277e+00 -1.30815729e-01
5.25310814e-01 2.61879623e-01 -8.27160239e-01 3.67135322e-03
-1.19513325e-01 -2.66412109e-01 -4.02198642e-01 -6.45085692e-01
-1.19487011e+00 -1.09733365e-01 -2.61797816e-01 8.46278667e-01
1.29242587e+00 1.01413243e-01 -2.06822097e-01 -1.78404212e-01
8.80326569e-01 -1.10626996e+00 -5.55481434e-01 5.12015700e-01
9.42609310e-01 -2.75431693e-01 -4.48826812e-02 -3.72715354e-01
-5.13255954e-01 6.61812901e-01 3.58278155e-01 -8.24628770e-02
7.15520382e-01 5.10487854e-01 -3.45509350e-01 -5.03451861e-02
-8.16530585e-01 -4.01666850e-01 -2.58512378e-01 7.86324143e-01
-1.41202724e-02 5.67815423e-01 -1.24282753e+00 1.02626586e+00
-4.68210638e-01 -2.00483128e-01 9.96109903e-01 6.43766105e-01
-7.19962001e-01 -1.27013326e+00 -6.78793907e-01 6.44181311e-01
-1.87536195e-01 -1.18887564e-02 -5.02625346e-01 1.09035087e+00
3.69338691e-01 1.04673350e+00 3.79777133e-01 -1.89904094e-01
3.51907521e-01 -5.20215750e-01 3.74809057e-01 -3.99293244e-01
-6.39015257e-01 2.81402171e-01 2.69767046e-01 -2.99427271e-01
-4.31758821e-01 -8.74899626e-01 -1.03699291e+00 -1.29916227e+00
-7.15144396e-01 9.16482389e-01 -2.51074612e-01 6.88434958e-01
-3.67982388e-01 2.02135295e-01 9.36719418e-01 -5.95139205e-01
-6.40572906e-01 -5.00839949e-01 -1.47833693e+00 1.41679481e-01
-2.57922739e-01 -5.38447857e-01 -5.02077281e-01 -4.95106667e-01] | [4.216564655303955, 2.7838425636291504] |
7e52b570-18f9-4385-99c4-c8382d9be702 | perceptual-quality-assessment-of-smartphone | null | null | http://openaccess.thecvf.com/content_CVPR_2020/html/Fang_Perceptual_Quality_Assessment_of_Smartphone_Photography_CVPR_2020_paper.html | http://openaccess.thecvf.com/content_CVPR_2020/papers/Fang_Perceptual_Quality_Assessment_of_Smartphone_Photography_CVPR_2020_paper.pdf | Perceptual Quality Assessment of Smartphone Photography | As smartphones become people's primary cameras to take photos, the quality of their cameras and the associated computational photography modules has become a de facto standard in evaluating and ranking smartphones in the consumer market. We conduct so far the most comprehensive study of perceptual quality assessment of smartphone photography. We introduce the Smartphone Photography Attribute and Quality (SPAQ) database, consisting of 11,125 pictures taken by 66 smartphones, where each image is attached with so far the richest annotations. Specifically, we collect a series of human opinions for each image, including image quality, image attributes (brightness, colorfulness, contrast, noisiness, and sharpness), and scene category labels (animal, cityscape, human, indoor scene, landscape, night scene, plant, still life, and others) in a well-controlled laboratory environment. The exchangeable image file format (EXIF) data for all images are also recorded to aid deeper analysis. We also make the first attempts using the database to train blind image quality assessment (BIQA) models constructed by baseline and multi-task deep neural networks. The results provide useful insights on how EXIF data, image attributes and high-level semantics interact with image quality, how next-generation BIQA models can be designed, and how better computational photography systems can be optimized on mobile devices. The database along with the proposed BIQA models are available at https://github.com/h4nwei/SPAQ.
| [' Zhou Wang', ' Kede Ma', ' Yan Zeng', ' Hanwei Zhu', 'Yuming Fang'] | 2020-06-01 | null | null | null | cvpr-2020-6 | ['blind-image-quality-assessment'] | ['computer-vision'] | [ 1.27623543e-01 -6.83270693e-01 -4.30875607e-02 -4.82062936e-01
-7.85175800e-01 -6.38161302e-01 2.32580423e-01 -5.90175251e-03
-3.36725652e-01 4.36908603e-01 2.99735039e-01 -3.95783961e-01
-1.83809176e-02 -5.62426090e-01 -7.38628685e-01 -5.52498996e-01
3.78585577e-01 -2.08098024e-01 9.60433856e-03 -1.11704409e-01
3.91858220e-01 3.60012889e-01 -1.92864788e+00 3.80545378e-01
1.02263892e+00 1.45618689e+00 3.43860298e-01 1.06342804e+00
4.64557528e-01 7.23195016e-01 -7.58636177e-01 -1.02595866e+00
2.45252520e-01 -3.03899348e-02 -5.73120415e-01 2.77762234e-01
9.20417130e-01 -1.03220797e+00 -1.69777647e-01 1.12378335e+00
8.33029568e-01 -7.96759278e-02 4.92056698e-01 -1.56077123e+00
-1.16119325e+00 -3.77059847e-01 -1.34857178e-01 4.05947506e-01
5.52138329e-01 7.95126200e-01 7.75303662e-01 -7.81279981e-01
1.06367357e-01 8.91740859e-01 5.79233825e-01 1.23715267e-01
-5.94376981e-01 -6.14440143e-01 -2.99003363e-01 7.05716193e-01
-1.20096779e+00 -8.12093973e-01 4.08248663e-01 -3.23308855e-01
8.93342972e-01 2.85057962e-01 9.65141058e-01 1.05850875e+00
3.57652962e-01 4.97350663e-01 1.46270013e+00 -1.31251588e-01
3.16107243e-01 3.09837788e-01 -2.20456943e-01 8.41583073e-01
1.32119656e-01 -1.02106728e-01 -3.91679257e-01 5.95873296e-02
7.14643419e-01 2.83211440e-01 -3.96387011e-01 -1.59887433e-01
-8.53625953e-01 3.97346139e-01 5.71818709e-01 6.23136908e-02
-2.88522929e-01 -2.49182642e-03 2.38126013e-02 3.22458863e-01
3.34804803e-01 4.04066056e-01 -4.94988829e-01 -2.81609327e-01
-7.35402405e-01 -1.64861843e-01 2.73821473e-01 9.66065645e-01
7.70326674e-01 -2.46817216e-01 -7.72386715e-02 1.13419235e+00
1.34911373e-01 8.93260658e-01 4.94848818e-01 -1.49736810e+00
3.99343997e-01 4.95875329e-01 3.95914525e-01 -1.21769524e+00
-1.72104686e-01 1.78776681e-02 -6.99551761e-01 2.65596420e-01
1.80668369e-01 1.28244311e-01 -6.45711422e-01 1.22702491e+00
-1.49755105e-02 -9.02103558e-02 -2.13252127e-01 9.67395842e-01
1.03444314e+00 7.00685203e-01 2.18284860e-01 5.29648848e-02
1.64406526e+00 -9.27202702e-01 -6.08278334e-01 -2.20552504e-01
2.92634904e-01 -9.30067658e-01 1.65903783e+00 6.02414429e-01
-1.27775168e+00 -9.58094299e-01 -1.12381434e+00 -3.47755969e-01
-6.93423331e-01 5.07566452e-01 5.87912381e-01 1.03895116e+00
-1.52088273e+00 4.14414912e-01 -3.34547311e-01 -4.83352363e-01
7.43383169e-01 2.23135054e-01 -4.31310624e-01 -4.44030374e-01
-9.98520792e-01 8.15189838e-01 -1.28397197e-01 -8.32628980e-02
-1.05452335e+00 -4.48111951e-01 -7.80373991e-01 -2.57922467e-02
6.03040420e-02 -9.57651854e-01 1.27806187e+00 -1.21825600e+00
-1.73573649e+00 1.21991229e+00 -1.75618112e-01 -9.19129401e-02
2.02469639e-02 -5.77463992e-02 -8.88056934e-01 5.92315555e-01
1.17605381e-01 7.14037001e-01 9.67104018e-01 -1.08329070e+00
-7.78044164e-01 -5.27386904e-01 5.34759045e-01 4.53349799e-01
-6.29324615e-01 2.22184002e-01 -7.15162277e-01 -1.55935794e-01
-5.64787149e-01 -7.90246010e-01 2.80524164e-01 4.34803993e-01
-2.42392197e-01 7.25699589e-02 4.70631629e-01 -9.46641684e-01
1.03778660e+00 -2.17110395e+00 -4.18316573e-01 -3.30656976e-01
1.75340891e-01 5.88057399e-01 -2.58486629e-01 9.52239484e-02
2.37209976e-01 2.04045266e-01 -3.96621861e-02 -4.36018288e-01
-9.08045024e-02 -4.80091237e-02 1.38567761e-01 5.37917137e-01
4.44315188e-02 9.77923453e-01 -8.03270042e-01 -5.96340775e-01
7.48837113e-01 4.44548428e-01 -3.60819012e-01 4.37110156e-01
2.58180320e-01 1.68781742e-01 -1.49852410e-01 1.03938365e+00
8.30306888e-01 -4.88429010e-01 -3.83507907e-01 -6.62656903e-01
6.72462583e-03 -1.12693213e-01 -9.15947795e-01 1.50625253e+00
-9.11669374e-01 8.36313605e-01 9.91715938e-02 -2.54727989e-01
4.66232210e-01 5.07455058e-02 3.11409682e-01 -1.20231414e+00
1.52791172e-01 6.42479807e-02 -4.20975327e-01 -9.11480844e-01
7.57958710e-01 4.36472833e-01 1.20157540e-01 1.33669958e-01
1.47015184e-01 -5.02350211e-01 7.13119283e-02 1.31680174e-02
8.17224562e-01 -2.92275488e-01 2.79047698e-01 1.40776798e-01
5.62449992e-01 -3.62804443e-01 1.14544250e-01 4.45267528e-01
-7.63016760e-01 1.03004420e+00 1.15410825e-02 -3.30143273e-01
-1.26412129e+00 -1.31084132e+00 3.32007110e-02 1.17567170e+00
4.97839034e-01 -2.80774444e-01 -7.99058199e-01 -9.89439562e-02
-3.13984960e-01 4.18207645e-01 -2.87911505e-01 -1.23280272e-01
1.94622371e-02 -6.09508455e-01 3.36392939e-01 2.59608269e-01
1.06232250e+00 -1.02661657e+00 -5.87395430e-01 -4.82539743e-01
-5.15940785e-01 -1.23794377e+00 -6.88220620e-01 -4.73366916e-01
-4.84026551e-01 -1.23022974e+00 -8.82878125e-01 -5.78191698e-01
3.66196364e-01 7.48067319e-01 1.34706879e+00 1.57925144e-01
-1.63084790e-01 7.45699286e-01 -3.86535108e-01 -2.54893512e-01
-1.64154574e-01 -4.10900503e-01 1.06128361e-02 5.50289080e-02
9.56427753e-02 -2.70797044e-01 -1.31815755e+00 5.63069344e-01
-1.00072801e+00 1.21519594e-02 6.79974496e-01 4.12801474e-01
6.37715161e-01 4.02244210e-01 -8.11170414e-02 -2.98055798e-01
7.96757519e-01 -1.98060915e-01 -5.10506690e-01 3.23892534e-01
-5.80385685e-01 -8.18392098e-01 5.46721399e-01 -3.14291269e-02
-1.13322234e+00 -2.45892644e-01 -2.90617555e-01 -3.34804654e-01
-4.99575734e-01 -7.41676241e-02 -5.85631847e-01 -3.51153851e-01
5.28020024e-01 1.58166677e-01 -2.79600054e-01 -1.18040025e-01
5.54160237e-01 1.19813657e+00 7.95067847e-01 -8.06816272e-04
2.08238244e-01 6.22049689e-01 -3.82118285e-01 -1.05421972e+00
-6.39822066e-01 -6.70237899e-01 -3.74765337e-01 -6.23683572e-01
9.68468368e-01 -1.17913616e+00 -9.99999702e-01 1.02500033e+00
-9.50614452e-01 -4.16732609e-01 1.24404272e-02 2.13893011e-01
-5.65315366e-01 5.79546034e-01 -7.41375268e-01 -8.08157206e-01
-4.82841283e-01 -1.40257835e+00 1.50378799e+00 3.72219622e-01
1.74632460e-01 -6.31436050e-01 -4.27581400e-01 1.06027353e+00
3.10894370e-01 -1.36414871e-01 7.31919110e-01 1.57518297e-01
-6.08914733e-01 3.28022754e-03 -6.66990101e-01 7.73648322e-01
1.17697671e-01 5.82673624e-02 -1.15353668e+00 -1.35085523e-01
1.75415233e-01 -5.23182511e-01 5.23399770e-01 8.30464244e-01
1.46646476e+00 -3.66464317e-01 1.32478908e-01 9.48462367e-01
1.51241004e+00 3.09501499e-01 1.04466748e+00 3.48178029e-01
7.04526305e-01 4.55830395e-01 5.14429212e-01 2.97763586e-01
6.96463704e-01 7.17487335e-01 6.13863051e-01 -3.67014706e-01
-3.78928244e-01 -5.86621538e-02 6.26602650e-01 7.94267416e-01
-7.06874998e-03 -6.27155244e-01 -7.24577785e-01 4.28497702e-01
-1.10549283e+00 -8.51130843e-01 -7.26340190e-02 2.16660905e+00
4.52707022e-01 -1.60049826e-01 2.81504393e-01 1.37506753e-01
7.50515282e-01 7.70666869e-03 -6.19309783e-01 -2.86146939e-01
-5.11964440e-01 -1.61568701e-01 7.80041873e-01 1.98633775e-01
-1.25200975e+00 6.74547195e-01 6.44500303e+00 8.31725657e-01
-9.60442841e-01 1.74195752e-01 1.20967603e+00 -1.09855630e-01
-3.11687812e-02 -3.13373357e-01 -4.14491057e-01 8.98631752e-01
1.03420210e+00 3.15470576e-01 7.34128773e-01 7.79550493e-01
4.69156146e-01 -4.33284193e-01 -8.59026670e-01 1.69332087e+00
3.73877376e-01 -1.12977350e+00 9.77764353e-02 -1.19415373e-02
6.56271636e-01 8.37470442e-02 7.20665812e-01 -2.26583913e-01
1.34421185e-01 -1.04067719e+00 6.62788332e-01 6.63911998e-01
1.15206504e+00 -3.67309332e-01 7.90699065e-01 -2.86388725e-01
-8.67825687e-01 -4.61042106e-01 -4.21867430e-01 2.63423077e-03
1.47830293e-01 4.42330539e-01 -3.84570032e-01 3.48623633e-01
1.27161312e+00 9.30650473e-01 -1.29230547e+00 1.22371471e+00
-2.67986432e-02 3.47411633e-01 9.51045007e-02 2.68203579e-02
-1.67433694e-01 -3.19631010e-01 1.32338330e-01 8.54964733e-01
7.02635169e-01 1.96138263e-01 -3.41150433e-01 5.17529249e-01
-1.31190732e-01 7.09407255e-02 -4.89065230e-01 9.15421620e-02
4.77886915e-01 1.26178873e+00 -6.51616693e-01 -3.96185994e-01
-6.37079597e-01 1.33243513e+00 -2.70733953e-01 4.24829721e-01
-7.63174772e-01 -2.16857105e-01 9.17227745e-01 4.58668657e-02
6.84699789e-02 2.12574042e-02 -2.09867537e-01 -1.08179593e+00
1.31482795e-01 -1.16271532e+00 2.42566153e-01 -1.88240921e+00
-1.37026584e+00 5.69669962e-01 -2.84340948e-01 -1.37428439e+00
2.78687090e-01 -1.00267851e+00 -3.34024489e-01 6.26490355e-01
-1.43271446e+00 -1.10735714e+00 -8.89608145e-01 9.61881757e-01
5.80504596e-01 -2.22824991e-01 6.70741022e-01 6.21771753e-01
-6.35074615e-01 5.72122514e-01 2.70142019e-01 1.59570761e-02
8.37440550e-01 -1.06310856e+00 3.11080873e-01 7.31668115e-01
-3.84222679e-02 2.90854454e-01 3.77872556e-01 -2.54860699e-01
-1.24864507e+00 -1.02618611e+00 3.08338076e-01 -7.00290740e-01
3.65933776e-01 -5.98437199e-03 -4.26650316e-01 6.86797202e-02
2.55273044e-01 -2.40354702e-01 6.52555287e-01 -1.66848332e-01
-1.52387768e-01 -4.95861024e-01 -1.16217577e+00 5.88936627e-01
9.40166712e-01 -9.00574744e-01 -5.31721115e-02 4.15666044e-01
6.80557251e-01 -1.70293152e-01 -9.38875496e-01 6.22208118e-02
7.42501915e-01 -1.55671620e+00 1.27151942e+00 1.66492641e-01
5.09772182e-01 -2.91302711e-01 -3.60409468e-01 -1.34990144e+00
-2.18604788e-01 -2.46805385e-01 2.77021497e-01 1.23150849e+00
1.97698101e-01 -4.61002231e-01 5.26984036e-01 6.01988375e-01
-2.42773861e-01 -5.67784429e-01 -7.05243051e-01 -5.44134974e-01
-3.31691176e-01 -5.47595680e-01 9.36382592e-01 4.05192554e-01
-5.94155431e-01 1.33227497e-01 -5.79293668e-01 7.80045316e-02
3.84661615e-01 -9.08171833e-02 7.38190114e-01 -9.26064670e-01
-1.40046224e-01 -6.10746682e-01 -5.55544019e-01 -8.10259163e-01
-2.55775303e-01 -4.18901294e-01 -2.61746138e-01 -1.67461240e+00
3.18041533e-01 -1.88728079e-01 -2.37089768e-01 1.70798320e-02
-1.99249923e-01 5.29488385e-01 2.16457963e-01 4.29706246e-01
-1.13054645e+00 3.87208372e-01 1.34797513e+00 -3.25165987e-01
-3.06426850e-03 4.96285073e-02 -7.23261714e-01 7.56618798e-01
7.64251709e-01 1.23252109e-01 -5.29079676e-01 -8.21910143e-01
4.04911906e-01 2.19488088e-02 7.09067166e-01 -1.33259690e+00
3.26297998e-01 7.06822798e-02 7.45191514e-01 -1.36839658e-01
7.92455018e-01 -9.33066368e-01 2.69269496e-01 1.84139013e-01
-1.00550123e-01 3.65734816e-01 1.76615957e-02 4.55820382e-01
-2.18646258e-01 1.45688027e-01 8.42465460e-01 -2.15592876e-01
-1.11599100e+00 4.77182329e-01 -3.03768843e-01 -1.54081136e-01
7.01438069e-01 -6.22119606e-01 -6.49931252e-01 -8.45036745e-01
-2.72277951e-01 -2.59317756e-02 9.92984951e-01 3.16874444e-01
9.86318648e-01 -1.20996201e+00 -3.23025465e-01 1.83072627e-01
4.42033947e-01 -5.80134690e-01 8.22171211e-01 5.86574137e-01
-7.09205866e-01 3.13415021e-01 -8.59380960e-01 -4.53670830e-01
-1.21891177e+00 7.13096797e-01 3.24810743e-01 2.90607125e-01
-6.67931512e-02 6.88121438e-01 1.87151700e-01 -5.47252856e-02
1.24628350e-01 -4.27182227e-01 -3.02679896e-01 -1.51141793e-01
5.71688294e-01 7.73701847e-01 2.42847025e-01 -1.03684866e+00
-2.31629744e-01 7.75074899e-01 4.55176413e-01 8.31090286e-02
1.00753260e+00 -7.46459961e-01 -2.51530781e-02 2.94401973e-01
1.39652550e+00 -2.87624657e-01 -1.12045825e+00 2.42608413e-01
-6.74423158e-01 -7.56395698e-01 1.83518708e-01 -9.93472636e-01
-1.12851095e+00 9.60069835e-01 1.25671446e+00 1.42728254e-01
1.79137480e+00 -1.21571139e-01 9.01135027e-01 1.92980736e-01
4.07199770e-01 -1.26283622e+00 3.48181844e-01 -3.74442264e-02
8.47598433e-01 -1.68750000e+00 2.04814784e-02 -2.39303321e-01
-9.34005618e-01 6.40273333e-01 5.44364393e-01 2.86771417e-01
5.55500686e-01 -3.51862192e-01 1.79452509e-01 -1.56952426e-01
-2.66527981e-01 -3.43035221e-01 3.45121890e-01 9.96095061e-01
1.28607765e-01 1.41373068e-01 4.47552055e-01 3.53788078e-01
-4.44810748e-01 3.34710086e-04 5.22700191e-01 3.09561193e-01
-3.15841138e-01 -6.14736795e-01 -4.08076823e-01 7.78444827e-01
-4.50805813e-01 -2.31914639e-01 -4.06851053e-01 4.22889471e-01
5.19866705e-01 1.71130550e+00 -4.57112398e-03 -5.37087023e-01
3.86744320e-01 -5.07815957e-01 3.32607001e-01 -1.77382857e-01
-2.75646955e-01 -5.03739715e-01 6.29531443e-02 -9.14514661e-01
-5.78452229e-01 -3.87917280e-01 -1.72305241e-01 -5.44876456e-01
-6.65434673e-02 -2.52968520e-01 7.72603512e-01 5.24679840e-01
5.43625712e-01 2.75100559e-01 5.26770234e-01 -8.23536396e-01
2.35522732e-01 -8.45297635e-01 -6.20935380e-01 7.21052468e-01
5.24212599e-01 -5.99034965e-01 -3.61423254e-01 4.15773332e-01] | [11.805438995361328, -1.8460917472839355] |
2ab59c8a-e501-4d1a-a3e2-c9c190826887 | learning-where-to-learn | null | null | https://openreview.net/forum?id=RLp_rHS4LMV | https://openreview.net/pdf?id=RLp_rHS4LMV | Learning where to learn | Finding neural network weights that generalize well from small datasets is difficult. A promising approach is to (meta-)learn a weight initialization from a collection of tasks, such that a small number of weight changes results in low generalization error. We show that this form of meta-learning can be improved by letting the learning algorithm decide which weights to change, i.e., by learning where to learn. We find that patterned sparsity emerges from this process. Lower-level features tend to be frozen, while weights close to the output remain plastic. This selective sparsity enables running longer sequences of weight updates with-out overfitting, resulting in better generalization in the miniImageNet benchmark. Our findings shed light on an ongoing debate on whether meta-learning can discover adaptable features, and suggest that sparse learning can outperform simpler feature reuse schemes. | ['Johannes von Oswald', 'Joao Sacramento', 'Nicolas Zucchet', 'Dominic Zhao'] | 2021-03-13 | null | null | null | iclr-workshop-learning-to-learn-2021-5 | ['sparse-learning'] | ['methodology'] | [ 4.09850806e-01 6.72514662e-02 -2.58011490e-01 -3.99983168e-01
-1.64532304e-01 -5.16923904e-01 3.76897097e-01 2.49179244e-01
-6.92388296e-01 6.74219608e-01 2.99333811e-01 4.88729998e-02
-2.97550976e-01 -7.68827736e-01 -7.89722800e-01 -8.43238652e-01
-2.29629904e-01 2.07673818e-01 3.51380110e-01 -3.25948864e-01
4.96002555e-01 4.50835228e-01 -1.58931112e+00 5.43205559e-01
6.60287201e-01 7.78926849e-01 3.97349030e-01 4.85760421e-01
-7.30304047e-02 4.20419604e-01 -3.27060699e-01 -2.92220831e-01
4.56352562e-01 -4.27865356e-01 -8.56506228e-01 -8.98027048e-02
6.38860226e-01 3.84173617e-02 -1.25228524e-01 1.00083661e+00
2.66919464e-01 3.77974868e-01 6.16556823e-01 -9.53031063e-01
-6.87754512e-01 8.49848092e-01 -4.19754624e-01 5.58016837e-01
-1.06920175e-01 2.90685982e-01 1.10098588e+00 -7.09119320e-01
7.64395833e-01 9.49832618e-01 9.97125149e-01 7.97272444e-01
-1.63427377e+00 -6.44391716e-01 5.75115383e-01 -6.49607405e-02
-1.00620210e+00 -5.83798707e-01 6.55184388e-01 -3.55445027e-01
1.15899456e+00 1.55092239e-01 9.69288707e-01 1.12349343e+00
4.58672017e-01 5.56179821e-01 9.97281373e-01 -4.26223516e-01
3.83389980e-01 4.66364808e-02 2.52528131e-01 8.92742336e-01
7.05070138e-01 1.84101343e-01 -7.01433659e-01 -2.90791422e-01
7.46383965e-01 3.02167833e-01 -2.88245797e-01 -4.85764086e-01
-1.08434153e+00 7.25190997e-01 5.08252203e-01 4.94726092e-01
-3.64883184e-01 2.04882666e-01 3.56772780e-01 8.74662578e-01
3.18574905e-01 1.06125581e+00 -9.44678009e-01 1.04656309e-01
-1.04668975e+00 2.73752391e-01 6.66558802e-01 4.54840481e-01
1.29883218e+00 2.32477501e-01 -9.45408717e-02 8.80748391e-01
-5.27523682e-02 1.14444427e-01 8.37611973e-01 -1.10638285e+00
2.59898990e-01 5.23081541e-01 -1.99891821e-01 -8.40720415e-01
-6.00506723e-01 -6.96869552e-01 -6.63081408e-01 3.91923666e-01
5.49441576e-01 -4.86266822e-01 -1.00076199e+00 2.05131865e+00
-4.27905805e-02 1.69812888e-01 -2.10305735e-01 6.69036150e-01
2.91375965e-01 5.16119242e-01 1.24884926e-01 -1.53402597e-01
9.04516757e-01 -8.54220271e-01 -1.44077480e-01 -5.83140671e-01
7.83987939e-01 -3.53023887e-01 9.50476050e-01 5.34602165e-01
-1.11935258e+00 -5.26116252e-01 -1.01967251e+00 2.02769369e-01
-4.07430470e-01 -3.30417484e-01 1.02470493e+00 5.54779112e-01
-1.18317962e+00 1.19729662e+00 -8.25182617e-01 -3.69498104e-01
6.55199826e-01 6.79441333e-01 -3.93721819e-01 1.37797564e-01
-8.51062953e-01 9.23821032e-01 5.90272546e-01 -1.98730826e-01
-7.21963048e-01 -1.09950006e+00 -5.73116302e-01 1.57780573e-01
2.08378911e-01 -8.05279076e-01 1.04615223e+00 -1.63802934e+00
-1.27753162e+00 8.15686166e-01 -1.81547955e-01 -5.75935364e-01
4.20714319e-02 4.67783287e-02 -1.27795637e-01 -4.03210223e-02
-2.91927785e-01 9.49542463e-01 1.25669670e+00 -1.28262079e+00
-6.85965657e-01 -2.67487109e-01 -4.03729379e-02 -6.13659713e-03
-8.05334449e-01 -3.32429260e-01 -6.41760603e-02 -8.09336722e-01
2.43823498e-01 -9.92473245e-01 -5.25474668e-01 3.30019817e-02
9.02227387e-02 -1.81335092e-01 4.31024551e-01 -1.44788384e-01
1.32652223e+00 -1.98524332e+00 3.22359473e-01 5.10565579e-01
5.80552876e-01 1.57608047e-01 -3.91891569e-01 2.28333339e-01
-3.65754843e-01 3.04051097e-02 -1.51980013e-01 -4.11373451e-02
-4.32388663e-01 2.85204828e-01 -2.66837567e-01 3.48741710e-01
2.27999330e-01 9.42621946e-01 -9.77970123e-01 -1.20096363e-01
-2.75623858e-01 6.95592538e-02 -9.54637885e-01 -1.92885399e-01
-1.71162307e-01 4.40594107e-02 -4.79186386e-01 5.99406302e-01
3.13826263e-01 -4.76931512e-01 2.01806754e-01 -1.49917960e-01
-1.85938388e-01 2.54996747e-01 -1.10804999e+00 1.70355642e+00
-4.32032436e-01 6.06293023e-01 -9.46412086e-02 -1.30679774e+00
7.78406680e-01 5.87358698e-02 6.89589262e-01 -4.32238162e-01
6.66239113e-02 1.52758911e-01 4.47137654e-01 -3.82954448e-01
2.13111833e-01 -1.94790885e-01 2.56094784e-01 7.09087372e-01
5.51779151e-01 -2.67501753e-02 2.54822135e-01 1.49880275e-02
1.27597857e+00 -2.03195754e-02 1.93885401e-01 -5.22362053e-01
-1.72364879e-02 1.04308732e-01 6.50193512e-01 9.70893323e-01
-5.01267277e-02 5.12386501e-01 3.08513582e-01 -8.31612349e-01
-1.11345005e+00 -8.19708347e-01 -8.93964395e-02 1.63659847e+00
-3.69896472e-01 -3.86689425e-01 -6.75284326e-01 -5.99205256e-01
2.62578428e-01 2.89156258e-01 -1.10174644e+00 -6.29997551e-01
-7.50114501e-01 -7.92194247e-01 1.56032145e-01 5.27452350e-01
8.88896435e-02 -1.16584325e+00 -6.80561006e-01 4.13097650e-01
4.38180149e-01 -3.71758223e-01 -4.91446346e-01 9.67405617e-01
-1.63413930e+00 -8.62592876e-01 -7.78821409e-01 -9.34573770e-01
1.05649245e+00 3.71641397e-01 1.18739843e+00 4.52266246e-01
-1.52905390e-01 2.61699438e-01 -1.72796860e-01 -2.87754267e-01
-9.17714462e-02 6.79595828e-01 2.34373599e-01 -1.38367206e-01
2.75831223e-01 -1.06748950e+00 -5.71606159e-01 9.89124179e-02
-8.16126227e-01 -9.54316258e-02 6.67811692e-01 1.06250477e+00
4.24621642e-01 -2.74260581e-01 8.13844562e-01 -1.32713544e+00
8.39414239e-01 -5.74544191e-01 -3.32984328e-01 3.21516365e-01
-1.02861714e+00 5.97212315e-01 7.70208657e-01 -9.02604043e-01
-8.17531943e-01 2.97744662e-01 4.46636230e-02 -2.47585684e-01
1.37870863e-01 3.55546504e-01 3.62816066e-01 -4.76476610e-01
1.10566115e+00 9.53847244e-02 6.74522296e-02 -3.78834814e-01
3.54699075e-01 1.49338199e-02 1.25545889e-01 -9.19243038e-01
7.14214146e-01 3.78783554e-01 -2.01198891e-01 -5.56128085e-01
-9.99029994e-01 -2.23734811e-01 -5.91009140e-01 -3.19171026e-02
2.72066742e-01 -6.42140806e-01 -4.90594536e-01 1.08783379e-01
-6.53985679e-01 -7.66801178e-01 -6.88173413e-01 2.36461386e-01
-4.18265194e-01 -8.09823871e-02 -4.85658556e-01 -2.82788724e-01
-2.52223492e-01 -8.69604111e-01 4.60388809e-01 3.56096357e-01
-5.85319042e-01 -1.17520583e+00 2.89326191e-01 -3.84624124e-01
6.66565478e-01 -1.15993179e-01 8.94126177e-01 -5.90734303e-01
-2.52939254e-01 1.07269876e-01 1.81624770e-01 1.94784909e-01
3.06181788e-01 -4.57076505e-02 -9.72150266e-01 -5.17377734e-01
-1.31249383e-01 -5.57539880e-01 1.50321114e+00 4.33047801e-01
1.32709289e+00 -3.50281358e-01 -5.79064786e-01 9.50696290e-01
1.21227920e+00 -4.63822968e-02 3.67191076e-01 4.48642224e-01
4.65952188e-01 2.50203550e-01 -1.62250862e-01 3.87696803e-01
6.93599805e-02 1.95060208e-01 2.12309863e-02 8.59733000e-02
-2.06063449e-01 -1.08833015e-01 2.03360513e-01 7.53563941e-01
-2.98989028e-01 2.97367901e-01 -7.26688862e-01 4.24627393e-01
-1.74489343e+00 -1.19938719e+00 4.40427959e-01 2.10206795e+00
1.36361754e+00 4.95962411e-01 1.12365596e-01 1.85227785e-02
3.89937639e-01 2.37054422e-01 -8.57930243e-01 -4.22592431e-01
-1.65712699e-01 6.87196255e-01 5.46200871e-01 3.67965549e-01
-7.68238246e-01 1.00802839e+00 7.84781313e+00 4.39139307e-01
-1.32363999e+00 1.70214579e-01 6.21293843e-01 -3.79061192e-01
-6.29587889e-01 2.54360642e-02 -8.63216758e-01 2.79805541e-01
9.80146289e-01 -1.18316844e-01 8.01535487e-01 7.41574168e-01
-1.04818694e-01 2.15182547e-02 -1.09413493e+00 5.47152996e-01
-7.87665024e-02 -1.68596518e+00 8.49049985e-02 -9.12290215e-02
1.23693752e+00 2.93518901e-01 2.24351496e-01 3.09160650e-01
6.02650523e-01 -8.88833463e-01 5.41043580e-01 7.23406494e-01
5.47331393e-01 -5.91845810e-01 1.24601886e-01 3.01043838e-01
-9.83159125e-01 -5.89922130e-01 -7.93787837e-01 -1.31932855e-01
-3.30867738e-01 7.05223382e-01 -3.84342909e-01 -2.44116560e-01
5.84572911e-01 7.83341169e-01 -7.97693908e-01 1.37489796e+00
5.34666851e-02 7.16675401e-01 -2.78917253e-01 -1.21097930e-01
2.35641748e-01 -8.10930580e-02 2.73722976e-01 1.15368438e+00
3.14983815e-01 7.77349323e-02 1.30590692e-01 7.06731677e-01
-2.93267518e-01 -7.79222101e-02 -6.72826648e-01 3.21567506e-02
3.61905217e-01 1.24114895e+00 -8.98928165e-01 -1.84396192e-01
-3.11659902e-01 8.99181008e-01 8.10416877e-01 4.95988667e-01
-1.90359905e-01 -3.19197565e-01 7.06622243e-01 1.33282930e-01
5.25436640e-01 -2.88003415e-01 -4.91445988e-01 -1.18752432e+00
-2.53419697e-01 -8.02653730e-01 4.64945734e-01 -5.04744053e-01
-1.14649546e+00 3.81074131e-01 -2.32025236e-01 -8.77619684e-01
-6.62832484e-02 -6.63678646e-01 -7.70291209e-01 5.31806350e-01
-1.27518141e+00 -5.99920392e-01 -3.78374383e-02 4.33043897e-01
5.43161333e-01 -3.17824692e-01 8.10401618e-01 -3.34019028e-02
-4.15711552e-01 7.70588100e-01 1.81881577e-01 -1.08576618e-01
6.72704935e-01 -1.02480245e+00 2.98769593e-01 4.03456181e-01
6.32564425e-01 9.99049425e-01 5.96148252e-01 -5.01591027e-01
-1.42071629e+00 -8.35040510e-01 7.56049633e-01 -3.13425094e-01
7.42946267e-01 -3.00990433e-01 -1.16370320e+00 6.94858551e-01
2.19615683e-01 2.86940962e-01 6.16576493e-01 5.53595304e-01
-5.57295918e-01 -3.78303945e-01 -1.06363654e+00 5.44979215e-01
1.30900609e+00 -2.21707180e-01 -7.80723929e-01 2.07376257e-01
5.68713307e-01 -1.30486608e-01 -6.74497306e-01 -8.72707739e-02
6.35162473e-01 -8.55627239e-01 9.32623386e-01 -1.08772600e+00
3.25545758e-01 4.63171862e-02 7.95705691e-02 -1.85617316e+00
-8.38125110e-01 -7.66729236e-01 -3.08151662e-01 7.90386498e-01
8.25902641e-01 -8.03520024e-01 8.57097805e-01 5.86287260e-01
-1.43457383e-01 -9.25715208e-01 -7.46493876e-01 -6.57690883e-01
3.63353401e-01 -1.59943700e-01 3.74565274e-01 9.80510175e-01
1.17081031e-01 4.57660444e-02 7.61187449e-02 -1.78396508e-01
4.54309374e-01 1.82224438e-02 1.24802463e-01 -1.60690057e+00
-2.60687977e-01 -7.27909207e-01 -1.48331895e-01 -8.68757606e-01
4.73285913e-01 -1.14813924e+00 -2.49392942e-01 -1.06530356e+00
2.82696694e-01 -5.98025620e-01 -7.83302307e-01 9.53120470e-01
-1.60167187e-01 2.38775209e-01 -5.01221651e-03 2.97506750e-01
-5.12252331e-01 2.89923698e-01 1.21751475e+00 -2.11271465e-01
-3.09985071e-01 3.30197364e-02 -1.12418079e+00 7.19859302e-01
1.00757539e+00 -9.36945796e-01 -4.51190323e-01 -6.14035904e-01
5.80669284e-01 -4.91039902e-01 2.19888799e-02 -1.00703490e+00
3.43703777e-01 -4.61385787e-01 8.42895985e-01 9.85476077e-02
3.66444811e-02 -7.16031551e-01 -2.57595479e-01 6.31523311e-01
-6.25908852e-01 2.23495081e-01 2.78098434e-01 3.62116545e-01
1.97633743e-01 -7.56173432e-01 8.88297319e-01 -4.87650782e-01
-6.53331280e-01 3.33761871e-01 -4.90312576e-01 2.51955837e-01
6.17373705e-01 -4.28828478e-01 -8.95625874e-02 1.55194616e-02
-9.20254827e-01 8.21564719e-02 3.76658112e-01 2.70499170e-01
4.86319870e-01 -1.32377303e+00 -4.58449215e-01 3.39470416e-01
3.78403207e-03 -4.22591150e-01 -1.05979420e-01 6.05974197e-01
-5.05834706e-02 4.21564765e-02 -4.19842780e-01 -3.69197279e-01
-7.24475205e-01 3.45911831e-01 5.48347592e-01 -2.78197159e-03
-7.47033000e-01 1.19201112e+00 -2.26132214e-01 -3.29346538e-01
2.66935587e-01 -4.64626402e-01 -1.09671950e-02 3.10624927e-01
5.31382263e-01 1.78260088e-01 1.52371809e-01 4.69724052e-02
-1.48444787e-01 5.14799893e-01 -5.35847068e-01 8.90920032e-03
1.88733017e+00 1.67689800e-01 -5.29938750e-02 4.50853527e-01
1.11376703e+00 -1.25303224e-01 -1.74007237e+00 -3.88675243e-01
2.33178884e-01 -3.28299016e-01 1.66820660e-01 -6.83317006e-01
-1.40061378e+00 5.37110448e-01 5.59798777e-01 2.52353251e-01
1.12293458e+00 -1.32522091e-01 5.98126888e-01 1.09932542e+00
3.72667372e-01 -1.41833425e+00 2.81003237e-01 6.40582442e-01
6.46132767e-01 -1.11768091e+00 2.07488328e-01 4.71383810e-01
-5.24412811e-01 1.46733153e+00 7.23427892e-01 -4.62497711e-01
9.44576263e-01 4.30807173e-01 -2.63735414e-01 -2.58072227e-01
-1.13838613e+00 -1.23717919e-01 2.09650993e-01 6.67393446e-01
5.11792064e-01 -2.02129707e-01 5.60187101e-02 5.80138266e-01
-1.73429608e-01 3.25027667e-02 3.59682798e-01 9.48862433e-01
-9.16163862e-01 -1.18830633e+00 -1.50406867e-01 9.46587682e-01
-2.28591368e-01 -2.36047775e-01 -2.81344771e-01 4.76678938e-01
2.45729625e-01 4.79143143e-01 1.66360930e-01 -3.31416935e-01
2.31115684e-01 4.20835406e-01 8.00340831e-01 -8.45712006e-01
-9.90374506e-01 -2.70704061e-01 -2.56616443e-01 -5.30580819e-01
-3.90380353e-01 -7.40338027e-01 -1.20734096e+00 -1.64296314e-01
-2.81464487e-01 1.75281838e-01 2.58948028e-01 9.36700344e-01
3.38433892e-01 4.60043550e-01 6.25668645e-01 -9.80806053e-01
-7.92392194e-01 -7.27970421e-01 -4.79997098e-01 3.46852511e-01
5.07059872e-01 -5.83019435e-01 -3.89188409e-01 2.53387034e-01] | [8.632560729980469, 3.3115792274475098] |
aae5615c-988f-48b1-8b94-be4dff6d7227 | intra-batch-supervision-for-panoptic-1 | 2304.08222 | null | https://arxiv.org/abs/2304.08222v1 | https://arxiv.org/pdf/2304.08222v1.pdf | Intra-Batch Supervision for Panoptic Segmentation on High-Resolution Images | Unified panoptic segmentation methods are achieving state-of-the-art results on several datasets. To achieve these results on high-resolution datasets, these methods apply crop-based training. In this work, we find that, although crop-based training is advantageous in general, it also has a harmful side-effect. Specifically, it limits the ability of unified networks to discriminate between large object instances, causing them to make predictions that are confused between multiple instances. To solve this, we propose Intra-Batch Supervision (IBS), which improves a network's ability to discriminate between instances by introducing additional supervision using multiple images from the same batch. We show that, with our IBS, we successfully address the confusion problem and consistently improve the performance of unified networks. For the high-resolution Cityscapes and Mapillary Vistas datasets, we achieve improvements of up to +2.5 on the Panoptic Quality for thing classes, and even more considerable gains of up to +5.8 on both the pixel accuracy and pixel precision, which we identify as better metrics to capture the confusion problem. | ['Gijs Dubbelman', 'Daan de Geus'] | 2023-04-17 | intra-batch-supervision-for-panoptic | https://openaccess.thecvf.com/content/WACV2023/html/de_Geus_Intra-Batch_Supervision_for_Panoptic_Segmentation_on_High-Resolution_Images_WACV_2023_paper.html | https://openaccess.thecvf.com/content/WACV2023/papers/de_Geus_Intra-Batch_Supervision_for_Panoptic_Segmentation_on_High-Resolution_Images_WACV_2023_paper.pdf | ieee-cvf-winter-conference-on-applications-of-2 | ['panoptic-segmentation'] | ['computer-vision'] | [ 1.26639515e-01 -2.15868264e-01 -3.04794997e-01 -4.83048320e-01
-1.04787517e+00 -6.44880772e-01 4.39273208e-01 3.82086379e-03
-3.38131100e-01 6.37996733e-01 -2.77671218e-01 -3.92403215e-01
-4.16229181e-02 -8.92431915e-01 -6.21935904e-01 -8.59230697e-01
-6.55490309e-02 2.66205728e-01 4.25214261e-01 -1.67975336e-01
-4.22599986e-02 4.70569998e-01 -1.48308229e+00 2.28955552e-01
1.18138576e+00 1.16791070e+00 1.18132249e-01 4.11267966e-01
1.78125333e-02 5.31778276e-01 -3.66548300e-01 -2.64138520e-01
6.23390079e-01 -2.51116633e-01 -6.28089726e-01 2.25972772e-01
9.03760612e-01 -4.55958784e-01 4.97940369e-02 1.15667665e+00
1.85577214e-01 -1.49458542e-03 5.75087786e-01 -9.34157908e-01
-4.75749195e-01 5.12442946e-01 -1.05123270e+00 2.93930531e-01
-4.63664830e-01 1.76688105e-01 1.35229075e+00 -4.66029108e-01
2.62502640e-01 1.10954189e+00 8.66759539e-01 1.19799729e-02
-1.38760090e+00 -7.79984653e-01 3.52767348e-01 -2.12096065e-01
-1.28657806e+00 -3.89726877e-01 2.46859103e-01 -5.60525239e-01
7.14038849e-01 3.55790913e-01 4.59664702e-01 3.39552969e-01
7.03062713e-02 6.01789355e-01 1.27264130e+00 -2.11353779e-01
-6.41530082e-02 2.11104035e-01 3.16959023e-01 3.33219826e-01
3.34614277e-01 1.18412308e-01 4.33482341e-02 1.64967224e-01
9.31488395e-01 -6.25552386e-02 -3.84749651e-01 -9.60014686e-02
-8.12365294e-01 9.91508603e-01 9.90283251e-01 3.45595837e-01
-3.80011469e-01 -2.75289789e-02 -3.65493037e-02 2.10621729e-01
1.00862718e+00 6.33351624e-01 -6.68276191e-01 3.01761895e-01
-1.24495864e+00 2.37745583e-01 4.55331862e-01 4.68270749e-01
9.65328455e-01 -3.56236733e-02 3.77681898e-03 1.11173093e+00
1.04932621e-01 7.79421508e-01 1.28605589e-01 -1.14291215e+00
5.26695371e-01 5.23583949e-01 2.75110096e-01 -9.73045647e-01
-6.33021355e-01 -7.50520468e-01 -8.19660783e-01 3.69084656e-01
5.34101248e-01 -3.41271520e-01 -1.28946328e+00 1.70904291e+00
1.43645033e-01 3.08055654e-02 1.35854363e-01 1.01015496e+00
5.42897165e-01 8.02707434e-01 1.96563199e-01 -6.14079833e-02
1.26983297e+00 -9.87490356e-01 -4.50187117e-01 -6.74950600e-01
6.59621298e-01 -6.63990676e-01 8.94366741e-01 1.42945603e-01
-7.01485276e-01 -5.66155851e-01 -1.03029442e+00 4.77353036e-01
-5.53252399e-01 8.82313922e-02 6.31190777e-01 5.96612036e-01
-9.49748874e-01 7.00252593e-01 -7.98508883e-01 -4.23412919e-01
4.22060579e-01 1.29326344e-01 -1.29781604e-01 3.19371298e-02
-1.07380354e+00 8.63440454e-01 3.17774653e-01 5.06298877e-02
-4.83953625e-01 -9.44430828e-01 -7.93212116e-01 3.46352339e-01
4.01149005e-01 -2.10432395e-01 1.05035305e+00 -1.12261868e+00
-9.80249822e-01 7.77067006e-01 1.21155664e-01 -7.32041299e-01
4.10480380e-01 -1.95849702e-01 -4.10495490e-01 1.32886752e-01
3.32772791e-01 1.10055315e+00 6.59546852e-01 -1.39494693e+00
-1.00780308e+00 -4.97503638e-01 1.08087398e-01 1.30203426e-01
-1.51185855e-01 2.89220549e-02 -5.07383406e-01 -6.13679111e-01
4.21736568e-01 -1.14658833e+00 -4.27495539e-01 -1.33032158e-01
-1.20738417e-01 1.15685530e-01 6.40210569e-01 -8.10730040e-01
9.13645625e-01 -2.24396944e+00 -3.65698308e-01 1.59603029e-01
1.75446227e-01 4.49196756e-01 -2.45404735e-01 -2.56534219e-01
-1.99749712e-02 3.97433192e-01 -6.06708109e-01 -1.80887491e-01
-3.89577955e-01 4.19750333e-01 -2.79603601e-01 2.74774760e-01
6.76024079e-01 6.16108894e-01 -5.04566431e-01 -2.11835831e-01
2.08186492e-01 3.33477825e-01 -4.41933632e-01 -2.14004628e-02
-3.16284388e-01 3.90136808e-01 -1.48118228e-01 3.96747291e-01
1.13409388e+00 -4.96999681e-01 1.77315310e-01 4.76277545e-02
-3.02055806e-01 1.94922596e-01 -1.16828001e+00 1.06225872e+00
-5.53131580e-01 7.78765082e-01 1.95164293e-01 -8.00899327e-01
7.48875499e-01 8.82625356e-02 2.46466458e-01 -8.48829985e-01
-9.20357853e-02 3.21318001e-01 1.53827623e-01 -2.40445092e-01
5.91953337e-01 -1.18787803e-01 2.71354705e-01 3.17971677e-01
-8.21985975e-02 -1.65746227e-01 2.57159352e-01 -1.34528548e-01
5.19230783e-01 -2.03805462e-01 -1.03604905e-01 -4.47582394e-01
1.73025757e-01 3.21212292e-01 6.68903053e-01 9.63212252e-01
-1.90137565e-01 8.17472219e-01 5.02106488e-01 -3.64663035e-01
-1.00435114e+00 -8.82236302e-01 -6.03678823e-01 1.03217483e+00
6.71294183e-02 2.74467729e-02 -4.87394303e-01 -6.56869471e-01
1.93197116e-01 5.11738956e-01 -6.20036960e-01 3.28964591e-01
-3.50530624e-01 -1.48799598e+00 4.50750232e-01 8.21008384e-01
8.68015647e-01 -6.01685405e-01 -6.44287705e-01 8.14128891e-02
-1.87161997e-01 -1.41874063e+00 1.04725221e-02 4.94784743e-01
-1.02676761e+00 -9.74812925e-01 -9.45850074e-01 -2.92053133e-01
4.58064079e-01 6.61273241e-01 1.08883286e+00 -3.92607711e-02
-1.42842725e-01 -2.69341111e-01 -3.71888578e-01 -3.10986757e-01
-2.60185152e-01 2.91421592e-01 -3.36375892e-01 -1.24552436e-01
1.47303358e-01 -3.22865158e-01 -4.24625665e-01 5.17124414e-01
-8.76480281e-01 -1.09696127e-02 4.18640405e-01 6.88486099e-01
4.01726216e-01 2.01429129e-01 4.24922884e-01 -8.09428692e-01
3.42012122e-02 -4.08301085e-01 -1.11743593e+00 2.16724381e-01
-7.56143451e-01 -1.15002111e-01 2.76521802e-01 -1.17147245e-01
-1.06810939e+00 5.33134751e-02 1.91469758e-03 -2.86131263e-01
-2.67870575e-01 5.99848688e-01 4.14532602e-01 -2.06841797e-01
6.87676191e-01 -1.70724720e-01 -1.28266677e-01 -6.69494092e-01
3.45199853e-01 7.35557020e-01 4.05049056e-01 -1.63349822e-01
6.92092299e-01 5.07180750e-01 -2.36246303e-01 -8.26402903e-01
-1.38289917e+00 -6.30316496e-01 -6.66748583e-01 -2.87643857e-02
1.14189315e+00 -1.48985445e+00 1.63647354e-01 5.34130752e-01
-7.83206880e-01 -5.76933861e-01 1.40026256e-01 4.73225415e-01
-7.93345831e-03 1.66731805e-01 -5.65316260e-01 -8.05025101e-01
-1.40948966e-01 -1.23185742e+00 8.57971907e-01 4.13159400e-01
2.30961546e-01 -8.88279200e-01 -6.67720959e-02 3.43744278e-01
6.02773547e-01 2.99930960e-01 7.71269619e-01 -3.81548792e-01
-5.95687807e-01 -3.02172434e-02 -7.80491769e-01 5.36714375e-01
2.74550468e-01 2.97358185e-01 -1.20527446e+00 -1.40429616e-01
-2.00140387e-01 -1.83463708e-01 1.42561448e+00 5.69338918e-01
9.55980837e-01 4.29741628e-02 -2.88550735e-01 7.00288653e-01
1.55774558e+00 2.86060065e-01 6.22249901e-01 4.80003834e-01
5.08299768e-01 7.85438359e-01 6.02330208e-01 1.70167089e-01
2.33081147e-01 5.74966133e-01 4.77594554e-01 -5.53661883e-01
-4.40605357e-02 2.64304191e-01 -6.84457496e-02 1.79789543e-01
-8.98643434e-02 -1.46384209e-01 -1.13325489e+00 7.50709772e-01
-1.91228366e+00 -6.41734540e-01 -4.21844274e-01 2.20776558e+00
6.53619349e-01 7.51185864e-02 2.19578221e-02 4.01281118e-02
7.36293197e-01 4.79393750e-01 -4.08375174e-01 -6.08572327e-02
-3.35743040e-01 1.24605618e-01 1.04535604e+00 4.64189827e-01
-1.49252248e+00 1.18784976e+00 6.78242111e+00 5.64984381e-01
-1.52670133e+00 1.59390613e-01 1.12105870e+00 3.40490341e-02
1.35673732e-01 -1.18277363e-01 -8.96859586e-01 2.20240176e-01
9.44015682e-01 4.30094928e-01 1.86566159e-01 6.92497432e-01
1.54247254e-01 -4.98028606e-01 -6.40386701e-01 6.57491565e-01
-1.70414805e-01 -1.29784191e+00 -5.30507453e-02 1.06837265e-01
1.19425595e+00 6.05535805e-01 1.69654369e-01 1.40655801e-01
4.58127052e-01 -9.59810615e-01 3.56468588e-01 -9.15839747e-02
5.94887853e-01 -7.09286869e-01 8.95181835e-01 2.30388463e-01
-9.10203636e-01 -6.56669065e-02 -6.49737298e-01 -1.08363919e-01
6.95838546e-03 8.88771832e-01 -5.02023697e-01 6.30777121e-01
9.77159023e-01 6.06175363e-01 -7.36601472e-01 1.23301423e+00
-1.51197881e-01 6.88888013e-01 -6.03838980e-01 5.67365944e-01
7.63061106e-01 -2.84258664e-01 1.02895230e-01 1.07167137e+00
3.03382486e-01 1.59091175e-01 5.71233146e-02 9.05384600e-01
3.90476808e-02 4.95672822e-02 -4.41911876e-01 2.09919170e-01
1.59259051e-01 1.29435754e+00 -8.11089039e-01 -4.54725057e-01
-3.79551679e-01 5.82836449e-01 1.59452528e-01 3.15020800e-01
-9.11543906e-01 -1.29167110e-01 7.78148949e-01 -1.03760790e-02
6.22834384e-01 -1.34723693e-01 -5.81586063e-01 -1.13779676e+00
-1.18569829e-01 -6.72006607e-01 3.67005318e-01 -7.65860558e-01
-1.12601256e+00 4.48040098e-01 -9.79149565e-02 -1.08267581e+00
1.01777397e-01 -6.97316587e-01 -6.06380343e-01 8.87432516e-01
-1.91971076e+00 -9.84479904e-01 -5.04723310e-01 1.28492117e-01
3.64199638e-01 2.62888521e-01 5.78955173e-01 4.88133192e-01
-8.40060115e-01 3.10256213e-01 4.55283493e-01 3.01600814e-01
8.21143866e-01 -1.18625402e+00 4.61403638e-01 9.03642833e-01
3.35694820e-01 1.41346514e-01 5.77980876e-01 -3.62167090e-01
-6.25946581e-01 -1.30921602e+00 7.10550845e-01 -2.78510004e-01
7.40179718e-01 5.96762858e-02 -1.08757269e+00 8.40240657e-01
-5.50360717e-02 -2.47714110e-03 4.48749155e-01 4.19532031e-01
-6.16443872e-01 -3.02253425e-01 -1.08255970e+00 3.06456417e-01
5.74378192e-01 -3.65481108e-01 -4.25997317e-01 3.93675596e-01
6.66841626e-01 -3.42496186e-01 -8.96086633e-01 7.51286447e-01
4.43211317e-01 -1.20871532e+00 7.51884401e-01 -3.49837542e-01
7.44296730e-01 -1.92937270e-01 -2.78154075e-01 -1.51856315e+00
-4.20870960e-01 3.19771580e-02 5.06332397e-01 1.17080534e+00
8.31099749e-01 -8.41285586e-01 4.64399040e-01 4.23046798e-01
3.24139409e-02 -2.88170218e-01 -7.49695957e-01 -9.81861115e-01
4.91884410e-01 -4.18013960e-01 6.57566011e-01 1.21979654e+00
-5.00868857e-01 2.42304713e-01 -3.01578343e-01 7.03935862e-01
5.39041042e-01 4.07123953e-01 5.59697092e-01 -1.31013811e+00
-1.57822832e-01 -5.74062526e-01 -4.58406806e-02 -1.08001518e+00
-6.46263883e-02 -5.06814003e-01 2.44350106e-01 -1.34720707e+00
9.21674073e-02 -8.84540975e-01 -4.03716534e-01 5.97963631e-01
-4.45193887e-01 7.09326267e-01 4.66746002e-01 4.59451735e-01
-3.12651306e-01 1.77584335e-01 1.13061452e+00 -1.15561187e-01
-3.25246066e-01 4.62996252e-02 -6.65885985e-01 6.21225893e-01
1.03893030e+00 -4.75487262e-01 3.26404418e-03 -8.35830331e-01
-3.98106650e-02 -2.53605209e-02 3.96131009e-01 -1.31865871e+00
-2.71121830e-01 -1.73960254e-01 4.91565675e-01 -6.49635553e-01
2.15126067e-01 -7.18438566e-01 1.78551895e-03 3.82291496e-01
-1.74904943e-01 -2.66180247e-01 5.54510891e-01 2.71888077e-01
-3.04943651e-01 -1.51220024e-01 1.20110095e+00 -1.54321939e-01
-6.59231484e-01 1.83598310e-01 -2.30432421e-01 -2.53458545e-02
7.29414523e-01 1.56058162e-01 -6.17731571e-01 -2.61744529e-01
-5.32464921e-01 6.39303863e-01 4.67862219e-01 3.43243629e-01
-1.78008512e-01 -8.51037502e-01 -7.30811954e-01 2.43675888e-01
2.03989640e-01 1.71913773e-01 1.75904214e-01 9.72725987e-01
-5.27208447e-01 5.21579862e-01 -2.19763771e-01 -8.77338648e-01
-1.06234491e+00 1.08236022e-01 6.37612164e-01 -4.53616053e-01
-4.18749839e-01 7.91641057e-01 4.41768080e-01 -4.32748586e-01
-3.82443778e-02 -6.19872570e-01 -2.27542654e-01 3.38121325e-01
4.81765270e-01 9.34217647e-02 9.06519592e-02 -4.23104137e-01
-1.14645474e-01 6.75019443e-01 -1.09312966e-01 7.23262578e-02
1.39526713e+00 -2.43250951e-02 -4.04709168e-02 3.71502191e-01
9.46942627e-01 -3.38405758e-01 -1.59951031e+00 -2.63195872e-01
-1.18803263e-01 -6.11704528e-01 4.32855934e-01 -1.02462196e+00
-1.55982435e+00 9.08096433e-01 7.72104442e-01 5.04488409e-01
1.00163770e+00 -4.57524098e-02 6.63695753e-01 3.48468006e-01
-6.31596819e-02 -9.72838104e-01 -4.32688862e-01 6.83148503e-01
4.49520648e-01 -1.81020975e+00 -3.41267399e-02 -5.80768824e-01
-5.99312901e-01 8.77563000e-01 6.44624531e-01 -2.73717083e-02
6.17230177e-01 8.62485766e-02 4.74166393e-01 -1.70335934e-01
-4.57343966e-01 -5.49335957e-01 1.65822476e-01 4.17251796e-01
2.76596040e-01 3.00869256e-01 4.05967794e-02 1.78018764e-01
4.39088268e-04 -2.29219243e-01 3.32620740e-01 5.83429396e-01
-8.33464384e-01 -5.91899872e-01 -5.37002146e-01 6.11996353e-01
-5.53516209e-01 -3.47144395e-01 -1.44631341e-01 9.59050775e-01
9.40095186e-02 1.00616312e+00 5.69025159e-01 -1.57371163e-01
1.33610845e-01 1.69277086e-03 1.50709331e-01 -4.32287633e-01
-6.26426458e-01 1.87344551e-01 1.81598470e-01 -3.60740364e-01
-7.13670850e-01 -4.58114028e-01 -8.45812201e-01 -3.22290450e-01
-4.72012371e-01 6.00053072e-02 6.18603885e-01 9.33957636e-01
1.03801742e-01 3.80477667e-01 7.14657068e-01 -8.79018247e-01
-6.43192887e-01 -1.13717282e+00 -7.71479428e-01 1.62581980e-01
5.19707680e-01 -5.86029232e-01 -6.91412449e-01 -1.58010989e-01] | [9.520251274108887, -1.3613134622573853] |
5ca0fcec-2ad1-445c-af2a-d4b0fd6e92d8 | learning-3d-semantics-from-pose-noisy-2d | 2204.08084 | null | https://arxiv.org/abs/2204.08084v3 | https://arxiv.org/pdf/2204.08084v3.pdf | Learning 3D Semantics from Pose-Noisy 2D Images with Hierarchical Full Attention Network | We propose a novel framework to learn 3D point cloud semantics from 2D multi-view image observations containing pose error. On the one hand, directly learning from the massive, unstructured and unordered 3D point cloud is computationally and algorithmically more difficult than learning from compactly-organized and context-rich 2D RGB images. On the other hand, both LiDAR point cloud and RGB images are captured in standard automated-driving datasets. This motivates us to conduct a "task transfer" paradigm so that 3D semantic segmentation benefits from aggregating 2D semantic cues, albeit pose noises are contained in 2D image observations. Among all difficulties, pose noise and erroneous prediction from 2D semantic segmentation approaches are the main challenges for the task transfer. To alleviate the influence of those factor, we perceive each 3D point using multi-view images and for each single image a patch observation is associated. Moreover, the semantic labels of a block of neighboring 3D points are predicted simultaneously, enabling us to exploit the point structure prior to further improve the performance. A hierarchical full attention network~(HiFANet) is designed to sequentially aggregates patch, bag-of-frames and inter-point semantic cues, with hierarchical attention mechanism tailored for different level of semantic cues. Also, each preceding attention block largely reduces the feature size before feeding to the next attention block, making our framework slim. Experiment results on Semantic-KITTI show that the proposed framework outperforms existing 3D point cloud based methods significantly, it requires much less training data and exhibits tolerance to pose noise. The code is available at https://github.com/yuhanghe01/HiFANet. | ['Long Chen', 'Junkun Xie', 'Lin Chen', 'Yuhang He'] | 2022-04-17 | null | null | null | null | ['2d-semantic-segmentation'] | ['computer-vision'] | [ 9.47056487e-02 1.07882001e-01 -6.82088286e-02 -5.31207502e-01
-7.05064416e-01 -4.32863772e-01 2.03747511e-01 -6.26915181e-03
-1.53028548e-01 2.55446553e-01 -2.08227888e-01 -9.64294523e-02
4.96657565e-02 -7.81674743e-01 -1.09663892e+00 -5.80412388e-01
4.44127917e-01 6.54958487e-01 4.47976500e-01 -1.06162801e-01
2.33089700e-01 6.59715116e-01 -1.80685949e+00 -1.98542457e-02
8.45297158e-01 1.27703762e+00 8.86147916e-01 1.19237237e-01
-4.74552006e-01 2.67132133e-01 -6.89770430e-02 -8.22194442e-02
4.79153872e-01 2.33036160e-01 -5.64884007e-01 5.25599301e-01
6.83815598e-01 -4.91541207e-01 -2.41672903e-01 1.21673822e+00
4.22997504e-01 6.96307197e-02 3.84326607e-01 -1.37245083e+00
-4.96036500e-01 -6.36971518e-02 -8.63854408e-01 -7.34707341e-02
2.16889560e-01 1.45001546e-01 9.48421657e-01 -1.25253570e+00
3.80642951e-01 1.42785132e+00 5.99836349e-01 2.64859974e-01
-8.46415043e-01 -6.91325784e-01 5.94635189e-01 1.87004879e-01
-1.37353861e+00 -8.42874274e-02 1.22260249e+00 -5.00409544e-01
8.66746902e-01 5.88764511e-02 7.34649956e-01 9.66515183e-01
-1.76400810e-01 9.53469336e-01 1.14103520e+00 2.52978168e-02
1.03943028e-01 3.32708545e-02 1.68032825e-01 7.08256483e-01
9.64734256e-02 -2.87551042e-02 -4.25407737e-01 9.03232396e-02
9.38626647e-01 6.47533417e-01 -2.88352162e-01 -7.38818288e-01
-1.06202543e+00 6.54709876e-01 7.80176818e-01 -4.28399518e-02
-4.20070529e-01 3.00514370e-01 1.40024781e-01 -9.68973264e-02
6.45574152e-01 -2.24478930e-01 -7.19685912e-01 1.12796985e-01
-4.70303327e-01 1.67382374e-01 1.62596449e-01 1.43556404e+00
1.47359467e+00 -1.41955033e-01 3.96988362e-01 7.43177593e-01
4.89824951e-01 8.40762556e-01 1.79610118e-01 -1.04320860e+00
7.26767063e-01 9.39478397e-01 1.03144154e-01 -1.07290602e+00
-3.21981877e-01 -3.68116558e-01 -6.72047794e-01 2.00855181e-01
-6.12803362e-02 3.30776721e-01 -1.21838355e+00 1.35434818e+00
6.17996573e-01 3.07180911e-01 -3.35290343e-01 1.21224976e+00
8.34939837e-01 5.37422717e-01 -1.47416919e-01 2.28655408e-04
1.27207673e+00 -9.08967674e-01 -4.14204568e-01 -5.08310080e-01
2.62512445e-01 -5.09956658e-01 1.19420338e+00 9.25104171e-02
-8.74751449e-01 -8.34819973e-01 -9.20696914e-01 -4.89251047e-01
-4.12600458e-01 -1.13629267e-01 4.51158702e-01 1.41513422e-01
-7.48304486e-01 2.86268950e-01 -9.66035366e-01 -2.12274581e-01
6.59038246e-01 3.63279819e-01 -3.66633385e-01 -3.75672370e-01
-7.99895346e-01 4.77330267e-01 4.15323108e-01 2.05698922e-01
-7.61803091e-01 -7.02208281e-01 -9.36454475e-01 -1.03360347e-01
5.43475032e-01 -7.65987933e-01 9.11652863e-01 -6.76389337e-01
-1.09715021e+00 9.47210848e-01 -3.92627060e-01 8.16840120e-03
3.92334521e-01 -5.52636325e-01 1.10965505e-01 1.69532657e-01
4.75830704e-01 9.82506931e-01 8.54688585e-01 -1.77922142e+00
-7.51219153e-01 -9.03989255e-01 7.11032227e-02 5.51629782e-01
6.53649867e-02 -5.07100403e-01 -8.07817280e-01 -2.83534527e-01
6.92897022e-01 -9.59977925e-01 -2.90660977e-01 -5.93103021e-02
-3.87395382e-01 -3.19440156e-01 1.13998771e+00 -3.49178463e-01
4.33833003e-01 -2.29221225e+00 1.63452223e-01 -1.34552438e-02
1.83331117e-01 -1.19441204e-01 6.96173683e-02 1.06603995e-01
1.33596152e-01 1.02796406e-01 -3.92506987e-01 -5.39075851e-01
-5.38096800e-02 5.47888339e-01 -3.76723200e-01 3.41617882e-01
2.97154069e-01 9.17959094e-01 -9.01961803e-01 -3.89348149e-01
5.83699942e-01 4.55758184e-01 -6.77551150e-01 3.06929290e-01
-4.54284340e-01 7.92508006e-01 -9.36048687e-01 9.34796214e-01
9.92818713e-01 -3.91602904e-01 -5.34627140e-01 -3.61863375e-01
-1.02319591e-01 8.47955346e-02 -1.07071054e+00 2.30394101e+00
-4.34545130e-01 6.43166453e-02 1.00041494e-01 -9.38519895e-01
1.06088638e+00 1.10948168e-01 6.18564606e-01 -4.89231914e-01
1.50026456e-01 3.05986822e-01 -6.43597662e-01 -6.14090741e-01
3.52113664e-01 -9.89677981e-02 -1.48092985e-01 6.41818643e-02
1.36506930e-01 -5.61064363e-01 -4.87212688e-01 -7.95323998e-02
7.38509655e-01 4.12228465e-01 -2.32360489e-03 1.55980244e-01
4.72754389e-01 2.60162652e-01 8.44677985e-01 4.66858000e-01
-2.01697350e-01 8.31958652e-01 -6.11758865e-02 -5.58694899e-01
-9.27034438e-01 -1.20008349e+00 -1.39832377e-01 7.03400612e-01
8.33059847e-01 -1.36361241e-01 -3.68189543e-01 -7.49463081e-01
2.96414942e-01 4.26218241e-01 -3.19553852e-01 8.52590501e-02
-5.41956544e-01 -4.01711911e-01 -1.28912598e-01 6.35175347e-01
6.30459726e-01 -7.58861303e-01 -6.84967160e-01 7.51490369e-02
-2.88555771e-01 -1.38927102e+00 -2.92132258e-01 2.34421045e-01
-1.18830705e+00 -1.00395036e+00 -4.42126483e-01 -6.66722775e-01
6.77700698e-01 8.54600728e-01 1.14003861e+00 5.58850951e-02
-8.52594301e-02 5.34862876e-01 -4.47409272e-01 -5.09669185e-01
3.17471534e-01 -2.80556958e-02 8.86508003e-02 1.25105858e-01
6.90407217e-01 -8.41756165e-01 -7.22961664e-01 3.52752745e-01
-6.34757221e-01 3.00344408e-01 6.90311372e-01 7.17394888e-01
1.12536192e+00 -1.42286032e-01 2.06415802e-01 -6.54856920e-01
-2.52621353e-01 -5.67895293e-01 -5.71912825e-01 -2.38437176e-01
-2.00276569e-01 -3.29967737e-01 3.23236227e-01 7.17453286e-02
-8.59774232e-01 5.72388232e-01 -1.66880935e-01 -1.16051781e+00
-6.80433691e-01 1.17009334e-01 -5.58514297e-01 -3.06271911e-02
1.06672548e-01 2.87564605e-01 -7.75411800e-02 -6.65645957e-01
4.04011577e-01 6.62467659e-01 3.42913061e-01 -5.91166735e-01
9.01033819e-01 7.71276414e-01 -7.02006444e-02 -7.37544417e-01
-1.01491213e+00 -6.63458467e-01 -8.80926669e-01 -2.13441551e-01
1.10491085e+00 -1.37759495e+00 -6.02460384e-01 2.97292441e-01
-1.22782981e+00 -7.41983652e-02 -9.62481052e-02 4.62729156e-01
-7.54364669e-01 3.68886471e-01 -3.14738303e-01 -7.30334938e-01
-1.22941166e-01 -1.42358828e+00 1.68487787e+00 1.30262583e-01
2.31280759e-01 -5.16531765e-01 -3.14818650e-01 8.43736291e-01
-2.15941235e-01 3.30135673e-01 8.59603047e-01 -3.10393840e-01
-1.21638680e+00 -1.34442234e-02 -4.82574195e-01 3.11895758e-01
9.80858207e-02 -4.36167330e-01 -1.09689784e+00 -1.55226886e-01
3.31533790e-01 -3.64160180e-01 6.60771310e-01 3.45604688e-01
1.45991147e+00 2.17632025e-01 -4.31356043e-01 8.02199483e-01
1.61413777e+00 1.06940679e-01 6.08157106e-02 2.56250203e-01
1.38138413e+00 7.20760107e-01 8.80727887e-01 2.94594020e-01
7.83487737e-01 6.46838963e-01 1.02789664e+00 -1.63393468e-01
4.75687683e-02 -4.15271193e-01 1.08316004e-01 9.18766201e-01
-1.43454988e-02 -1.37197198e-02 -1.05446506e+00 5.74101150e-01
-1.88893807e+00 -5.30744493e-01 -2.50885189e-01 1.95855021e+00
3.11336279e-01 8.04008245e-02 -1.73933357e-01 2.34682579e-02
6.86289668e-01 1.84289739e-01 -8.84027064e-01 2.42024511e-01
3.17326672e-02 -5.68857528e-02 6.07050955e-01 5.24594486e-01
-9.24321651e-01 1.04050553e+00 4.11395788e+00 7.53568888e-01
-1.02296174e+00 2.05180779e-01 4.50141966e-01 -9.38690826e-02
-5.01334786e-01 2.01722067e-02 -8.52393866e-01 5.38165033e-01
2.67807990e-01 3.35262537e-01 1.93316966e-01 8.34993005e-01
2.49602839e-01 6.88907225e-03 -9.98635828e-01 1.35287058e+00
-7.86549412e-03 -9.65420485e-01 2.06316337e-01 1.37264818e-01
5.69091260e-01 5.72474897e-01 -2.56027207e-02 7.27261305e-02
1.08770870e-01 -7.26237833e-01 8.66047144e-01 2.51681715e-01
5.63165724e-01 -7.04909801e-01 6.46771610e-01 5.89993775e-01
-1.31968296e+00 -1.86988294e-01 -5.54312408e-01 -5.77888824e-02
3.12130183e-01 7.63402283e-01 -4.80070949e-01 8.66887927e-01
1.13036239e+00 1.11089599e+00 -4.23575640e-01 7.34292388e-01
-1.21079713e-01 1.32518113e-01 -5.02749860e-01 3.54833275e-01
5.52319705e-01 -4.67994004e-01 6.61902010e-01 5.50796330e-01
5.94642341e-01 3.34636927e-01 5.14099777e-01 9.39011633e-01
7.82123730e-02 -1.05802074e-01 -8.17854047e-01 4.19337243e-01
6.30560338e-01 1.11140597e+00 -6.85913086e-01 -2.70878822e-01
-7.27206171e-01 9.49312091e-01 3.65793467e-01 4.01406825e-01
-7.39462376e-01 5.16013801e-02 7.18723834e-01 1.66764408e-01
5.86260617e-01 -4.15068507e-01 -6.02676272e-01 -1.27679551e+00
3.11262697e-01 -3.72744530e-01 4.60911430e-02 -1.18140113e+00
-1.25105906e+00 4.73682821e-01 -1.58226117e-02 -1.52873814e+00
2.58928031e-01 -5.44774354e-01 -2.11896911e-01 9.22252297e-01
-1.75870490e+00 -1.25849295e+00 -8.20309222e-01 6.92337334e-01
8.83881330e-01 2.22177356e-01 4.41776782e-01 2.71900654e-01
-3.66059959e-01 -6.74258247e-02 -2.53931701e-01 -9.99306589e-02
4.58656818e-01 -1.25260949e+00 3.62328142e-01 5.48098803e-01
6.30082488e-02 3.06311131e-01 3.37209165e-01 -6.43387139e-01
-1.52089155e+00 -1.25014591e+00 4.79194015e-01 -6.70250416e-01
3.08683693e-01 -5.27156055e-01 -9.79732454e-01 6.72903001e-01
-1.84289336e-01 1.96375147e-01 4.23270017e-01 -1.13488927e-01
-1.94658607e-01 -2.15005159e-01 -9.45689201e-01 2.68982232e-01
1.50109506e+00 -5.64837456e-01 -7.33106971e-01 3.24324638e-01
1.09481108e+00 -6.98704958e-01 -8.68518293e-01 8.08493197e-01
7.04161972e-02 -1.07175410e+00 1.26718163e+00 -3.93299535e-02
4.02727216e-01 -7.37433970e-01 -4.69679147e-01 -1.07709217e+00
-1.49667546e-01 -1.33450553e-01 -6.00398034e-02 1.08784163e+00
4.94952500e-02 -5.59563756e-01 1.02339602e+00 4.89133745e-01
-6.64313197e-01 -8.07084560e-01 -1.07101297e+00 -5.70380986e-01
-3.35845761e-02 -5.96463382e-01 7.90380001e-01 8.36919129e-01
-6.77981973e-01 4.54315543e-01 -1.92348510e-01 6.85280442e-01
8.66520345e-01 5.95891356e-01 9.86964583e-01 -1.36669707e+00
-4.26061489e-02 -1.59028575e-01 -6.24788105e-01 -1.59202254e+00
1.50123909e-01 -9.09828126e-01 1.41467348e-01 -1.41676700e+00
-8.13897550e-02 -7.87631512e-01 -2.25407824e-01 4.00427639e-01
-3.25261503e-01 2.23896101e-01 3.49748135e-01 4.24149454e-01
-4.63183463e-01 8.88534248e-01 1.32579768e+00 -1.53729424e-01
-1.34129673e-01 -7.20389783e-02 -4.30904537e-01 8.05283308e-01
5.85530639e-01 -4.33803767e-01 -6.12415910e-01 -9.11658287e-01
-7.85613433e-03 1.17716454e-01 7.10080385e-01 -9.34241831e-01
2.18178749e-01 -1.21615887e-01 4.40438122e-01 -1.32344770e+00
7.15343595e-01 -1.32492816e+00 1.00131333e-01 7.26985112e-02
3.00609767e-01 -1.16585975e-03 1.41130775e-01 9.66457903e-01
-2.77807534e-01 8.31259340e-02 4.71594632e-01 -4.60928470e-01
-1.04518712e+00 8.78502131e-01 2.45898053e-01 -8.78610387e-02
9.87120509e-01 -4.78116184e-01 1.08709447e-01 9.25288424e-02
-6.78501368e-01 5.09625196e-01 8.36461246e-01 6.35893524e-01
7.87938058e-01 -1.40907729e+00 -3.63653570e-01 4.84412879e-01
3.75001997e-01 1.11576188e+00 7.00324178e-01 7.41885841e-01
-4.19843942e-01 3.46428335e-01 -2.16411889e-01 -1.28018355e+00
-9.05588448e-01 6.43954217e-01 1.26959756e-01 3.66244465e-01
-8.99614871e-01 8.89199793e-01 6.58066034e-01 -7.56458640e-01
7.14982674e-02 -5.13958335e-01 1.22812185e-02 -8.74072015e-02
5.07123917e-02 1.13921642e-01 1.30967930e-01 -8.50523114e-01
-3.33981067e-01 1.28462481e+00 -4.03169915e-02 2.20095888e-01
1.33535600e+00 -5.83470523e-01 -3.67838480e-02 6.44683003e-01
1.28501952e+00 -3.44274163e-01 -1.67327905e+00 -3.62587571e-01
-2.65922308e-01 -7.49197125e-01 2.45560080e-01 -3.50808591e-01
-1.11232400e+00 1.17967021e+00 5.60013533e-01 3.28786708e-02
1.10356498e+00 1.94419548e-01 1.00345361e+00 1.44661516e-01
6.90617681e-01 -8.59575152e-01 -4.43621650e-02 4.92408484e-01
7.15601027e-01 -1.49298763e+00 -1.47003785e-01 -7.32731462e-01
-4.94943351e-01 8.15170288e-01 8.63160908e-01 -2.62533695e-01
6.20881319e-01 -1.21606939e-01 7.59320185e-02 -4.62063491e-01
-4.21988040e-01 -3.84773195e-01 6.92982227e-02 5.76747358e-01
-1.50051698e-01 -5.47537282e-02 3.41239780e-01 4.73582983e-01
-6.84118196e-02 -1.09229468e-01 1.21179320e-01 7.80552864e-01
-5.35369039e-01 -8.63218844e-01 -4.69649732e-01 2.77915359e-01
2.64004879e-02 8.42211023e-02 -1.27926573e-01 6.72243059e-01
4.77658838e-01 7.01960802e-01 3.07763606e-01 -4.79715645e-01
4.47937787e-01 5.74453212e-02 2.49702096e-01 -7.26959348e-01
-1.02304377e-01 2.08935931e-01 -4.00678903e-01 -8.08861554e-01
-5.99868655e-01 -6.82767630e-01 -1.37657869e+00 -2.79503763e-02
-1.94346011e-01 -8.67281333e-02 6.10461235e-01 9.21820223e-01
6.40567064e-01 3.40445220e-01 7.91549027e-01 -1.41115284e+00
-1.57264665e-01 -6.98168695e-01 -4.44100469e-01 4.57589239e-01
4.36310709e-01 -1.10525477e+00 -3.43991667e-01 -3.29278745e-02] | [8.17686939239502, -3.0482428073883057] |
e0e730f6-ecfa-40a9-9470-5db0188f430e | 190807519 | 1908.07519 | null | https://arxiv.org/abs/1908.07519v1 | https://arxiv.org/pdf/1908.07519v1.pdf | Multi-Modal Recognition of Worker Activity for Human-Centered Intelligent Manufacturing | In a human-centered intelligent manufacturing system, sensing and understanding of the worker's activity are the primary tasks. In this paper, we propose a novel multi-modal approach for worker activity recognition by leveraging information from different sensors and in different modalities. Specifically, a smart armband and a visual camera are applied to capture Inertial Measurement Unit (IMU) signals and videos, respectively. For the IMU signals, we design two novel feature transform mechanisms, in both frequency and spatial domains, to assemble the captured IMU signals as images, which allow using convolutional neural networks to learn the most discriminative features. Along with the above two modalities, we propose two other modalities for the video data, at the video frame and video clip levels, respectively. Each of the four modalities returns a probability distribution on activity prediction. Then, these probability distributions are fused to output the worker activity classification result. A worker activity dataset of 6 activities is established, which at present contains 6 common activities in assembly tasks, i.e., grab a tool/part, hammer a nail, use a power-screwdriver, rest arms, turn a screwdriver, and use a wrench. The developed multi-modal approach is evaluated on this dataset and achieves recognition accuracies as high as 97% and 100% in the leave-one-out and half-half experiments, respectively. | ['Zhaozheng Yin', 'Ming C. Leu', 'Wenjin Tao'] | 2019-08-20 | null | null | null | null | ['activity-prediction', 'activity-prediction'] | ['computer-vision', 'time-series'] | [ 6.18699253e-01 -3.32554311e-01 -1.92692116e-01 -1.25992611e-01
-4.52403456e-01 -3.48924428e-01 4.49896693e-01 -2.52934694e-01
-2.37443388e-01 4.18488920e-01 1.29764304e-01 2.10205093e-01
-5.65790534e-01 -4.82566476e-01 -6.65277243e-01 -8.05408955e-01
3.16900373e-01 1.23362258e-01 -2.98330467e-02 2.22098306e-01
1.97924748e-01 4.94991153e-01 -1.91358256e+00 3.62916321e-01
3.54101151e-01 1.35790586e+00 4.36826557e-01 9.06355917e-01
1.22391149e-01 1.09364772e+00 -5.96224546e-01 1.06149390e-01
2.39792597e-02 -3.66008192e-01 -4.77362722e-01 5.22874236e-01
-2.06222489e-01 -2.11305141e-01 -3.59132260e-01 6.85191214e-01
3.65771353e-01 2.37994611e-01 5.22249758e-01 -1.15314233e+00
-4.91589040e-01 3.09639126e-01 -5.63775480e-01 -3.35593312e-03
9.96690869e-01 1.20660558e-01 4.63430017e-01 -7.31182635e-01
4.62976277e-01 9.79415953e-01 3.96020889e-01 2.81401545e-01
-8.04022312e-01 -4.48205829e-01 -5.59611171e-02 3.17462981e-01
-1.07639217e+00 -1.73773780e-01 1.02227819e+00 -6.84351385e-01
8.25477660e-01 2.61412859e-01 8.64668190e-01 1.48732293e+00
5.67822516e-01 1.02939570e+00 1.05978286e+00 -4.08436149e-01
2.06142180e-02 -2.45032221e-01 -7.84141719e-02 6.87355459e-01
-6.70303628e-02 -5.21343127e-02 -7.70823538e-01 1.30724059e-02
9.33406115e-01 1.00414348e+00 -2.80594170e-01 -3.13924551e-01
-1.74433780e+00 1.44344538e-01 2.33535707e-01 4.68862444e-01
-6.58537984e-01 -3.99683937e-02 3.23328674e-01 6.40707016e-02
4.79456410e-02 1.45247310e-01 -3.70444566e-01 -4.87448514e-01
-4.15461332e-01 2.32298095e-02 7.64167011e-01 1.08231127e+00
7.46303320e-01 -3.08932483e-01 -3.10211748e-01 6.28987491e-01
4.17101800e-01 6.32118285e-01 7.65252769e-01 -8.46861005e-01
6.22384787e-01 7.43370414e-01 2.91602761e-01 -1.00172579e+00
-5.38227856e-01 -1.77246645e-01 -8.37020814e-01 1.00656450e-01
2.05440313e-01 -2.56529897e-01 -7.70768642e-01 1.29396737e+00
3.03901464e-01 5.05170524e-01 6.88692108e-02 1.09573126e+00
5.12455642e-01 5.20515144e-01 -1.68708578e-01 -3.89767140e-01
1.67807949e+00 -8.64469767e-01 -1.00749445e+00 -2.90125698e-01
3.21995378e-01 -7.97364354e-01 1.01423287e+00 6.43644631e-01
-7.25584745e-01 -1.05825329e+00 -1.34678793e+00 1.48851246e-01
-2.48909742e-01 8.01030457e-01 4.17282313e-01 3.91021460e-01
-1.64451972e-01 5.78797817e-01 -1.34769475e+00 -2.27486029e-01
-3.12549621e-02 2.03393728e-01 -6.98232472e-01 -1.50595710e-01
-6.50587201e-01 6.68330550e-01 3.82800967e-01 3.62685621e-01
-8.95172119e-01 -1.49890751e-01 -1.03478491e+00 -9.27017853e-02
4.64411497e-01 -6.28465772e-01 1.10586882e+00 -6.83845520e-01
-1.71159077e+00 4.75837409e-01 -2.57111825e-02 -3.09065748e-02
3.95831287e-01 -5.17403305e-01 -6.75846040e-01 1.00979984e-01
-5.31011596e-02 -1.62914678e-01 9.84757960e-01 -1.07112074e+00
-8.86843204e-01 -6.67108178e-01 -4.81955260e-02 1.72981039e-01
-3.52366984e-01 -1.76027402e-01 -4.87363368e-01 -4.69799608e-01
2.86964178e-01 -1.01357830e+00 3.17651302e-01 -6.03502631e-01
-3.96906495e-01 -1.40293226e-01 8.67121577e-01 -7.21300900e-01
1.03285766e+00 -2.37174869e+00 4.27615613e-01 7.04618841e-02
1.08851474e-02 -6.61509410e-02 2.38485232e-01 3.35453749e-01
1.57759398e-01 -7.13059306e-01 -5.17837368e-02 -3.78969997e-01
-3.44526172e-02 2.64356494e-01 1.59217164e-01 4.33973074e-01
1.45518273e-01 7.10483611e-01 -8.19221437e-01 -3.43261749e-01
7.21558571e-01 4.01459724e-01 -9.20096710e-02 5.21555305e-01
3.36629331e-01 7.96446443e-01 -5.99793911e-01 9.54786837e-01
3.04172397e-01 -9.49192699e-03 2.07233578e-01 -4.22446400e-01
-6.54996857e-02 -2.26799771e-01 -1.47062123e+00 2.13961411e+00
-7.77236640e-01 2.30799362e-01 1.20799787e-01 -1.01186621e+00
1.00087178e+00 4.32832509e-01 7.61904657e-01 -3.69096220e-01
4.46032673e-01 1.01495199e-01 -3.44598234e-01 -1.06132448e+00
2.09504604e-01 2.50643551e-01 -3.04628223e-01 3.22415888e-01
3.80840689e-01 2.59117991e-01 1.03403032e-01 -4.65526819e-01
1.37692511e+00 5.77274501e-01 2.26189569e-01 2.22455710e-01
6.86382651e-01 -2.52099246e-01 5.06875575e-01 4.46380109e-01
-1.83294803e-01 6.54347062e-01 1.53427914e-01 -4.56613272e-01
-6.10943258e-01 -1.14359820e+00 3.63786399e-01 1.11212969e+00
4.88023877e-01 -1.02277488e-01 -6.39005601e-01 -4.87645328e-01
7.15686940e-03 2.18200475e-01 -5.68538249e-01 -3.22570264e-01
-5.81989050e-01 -3.68290663e-01 2.65391499e-01 8.02713692e-01
5.47829866e-01 -1.10065627e+00 -1.03781366e+00 1.44214317e-01
-1.84291422e-01 -1.13993227e+00 -2.31837034e-01 3.80235851e-01
-6.79421365e-01 -1.47438705e+00 -6.17228270e-01 -7.92276680e-01
5.96868634e-01 4.11205471e-01 4.57998931e-01 -2.93230355e-01
-3.98929328e-01 6.80534542e-01 -5.51287770e-01 -3.51485282e-01
8.91126022e-02 -4.66629975e-02 2.69743890e-01 5.97602606e-01
3.84654254e-01 -6.51101589e-01 -6.22684956e-01 4.01845127e-01
-7.05757678e-01 -6.47841170e-02 1.02159345e+00 8.36989284e-01
6.91450834e-01 -1.14718713e-01 9.66520011e-02 -3.56604189e-01
5.38834214e-01 -4.62704211e-01 -1.29837483e-01 3.28464150e-01
-1.96648031e-01 -1.49086937e-01 5.41105270e-01 -7.48940825e-01
-1.15454578e+00 6.16247654e-01 5.80261052e-02 -8.59334767e-01
-5.11285424e-01 5.56325793e-01 -3.49233299e-01 1.94166034e-01
5.34207106e-01 4.28332120e-01 1.50508061e-01 -6.67228162e-01
6.88355193e-02 1.05334687e+00 8.46396685e-01 -4.66417104e-01
4.97968048e-01 3.27393383e-01 -1.75667107e-01 -7.63999403e-01
-5.39862156e-01 -7.00914443e-01 -6.72392607e-01 -6.63620174e-01
1.06928766e+00 -1.01655340e+00 -1.21214521e+00 7.39977658e-01
-1.04434359e+00 2.35642254e-01 -8.70373100e-02 1.13261557e+00
-8.03617299e-01 1.96871653e-01 -6.89072371e-01 -9.26214874e-01
-8.36901590e-02 -1.31461060e+00 1.44416142e+00 5.25808036e-01
-1.52582332e-01 -3.12148660e-01 -1.82604015e-01 6.35535955e-01
-3.15028429e-02 4.98705596e-01 3.53341639e-01 -5.53147376e-01
-2.41476446e-01 -6.07659638e-01 2.46391937e-01 3.40969384e-01
4.60244387e-01 -2.40896180e-01 -9.39102113e-01 -2.60607213e-01
3.10918152e-01 -2.11974084e-01 3.80900621e-01 1.53910235e-01
1.19004250e+00 6.50212243e-02 -5.27437329e-01 5.67004204e-01
9.70235348e-01 5.45630038e-01 4.85727519e-01 9.97359529e-02
8.55478227e-01 3.75046819e-01 9.90604758e-01 7.04982400e-01
1.60763398e-01 5.63565493e-01 5.83900273e-01 3.27007264e-01
3.11880946e-01 -2.47486264e-01 5.13463199e-01 1.02083731e+00
-5.92014790e-01 -1.54540852e-01 -5.95341563e-01 1.74526915e-01
-1.98964012e+00 -8.77981305e-01 1.59913182e-01 2.02011514e+00
2.48025864e-01 6.35213181e-02 9.58879013e-03 5.90756714e-01
7.74654090e-01 1.97718874e-01 -6.50773704e-01 1.94065243e-01
3.48159581e-01 -9.69843939e-02 3.98047268e-01 4.56739962e-02
-1.25604534e+00 2.19073653e-01 5.39277983e+00 3.98858011e-01
-1.05053282e+00 2.14014292e-01 -2.04891944e-03 -2.05339596e-01
3.63796860e-01 -3.18276733e-01 -5.54762304e-01 6.62566781e-01
6.04891121e-01 3.18719625e-01 6.04165018e-01 1.03366601e+00
5.75566627e-02 -2.78961688e-01 -1.21017182e+00 1.45962584e+00
3.19188207e-01 -9.22999084e-01 -4.01683927e-01 -3.95874977e-02
3.62570435e-01 -5.33634961e-01 -2.43815482e-01 2.22815618e-01
-2.03243181e-01 -6.99498117e-01 8.62855673e-01 1.08780515e+00
3.68651003e-01 -7.24779785e-01 7.62042463e-01 8.08986366e-01
-1.41028190e+00 -5.88394880e-01 -5.99933118e-02 -4.15819198e-01
2.15076014e-01 5.64954877e-01 -4.78118688e-01 9.75621164e-01
8.08291137e-01 6.72959030e-01 -2.45227903e-01 5.13366818e-01
-1.70050785e-01 2.19870627e-01 -1.30709261e-01 -8.36550444e-02
-2.88420260e-01 -2.19204187e-01 2.63602734e-01 8.36596906e-01
7.87145853e-01 6.22171611e-02 4.29950833e-01 5.99383414e-01
1.90321580e-01 -2.19459757e-01 -7.02879786e-01 -8.35964456e-02
3.38733256e-01 1.33223915e+00 -5.77515125e-01 -1.76128954e-01
-5.32954097e-01 1.19009626e+00 3.27172279e-02 2.39701554e-01
-7.96623349e-01 -6.57161355e-01 5.85158825e-01 -1.89597234e-01
6.92949072e-02 -6.15419269e-01 -1.14143314e-02 -1.14771891e+00
4.18124050e-01 -6.47889197e-01 2.12040901e-01 -9.60335732e-01
-1.00728965e+00 1.77882865e-01 5.19184582e-02 -1.54462755e+00
-6.29092872e-01 -8.96924734e-01 -3.17739964e-01 7.47063577e-01
-7.90322423e-01 -1.35276270e+00 -9.28476155e-01 7.80977905e-01
6.96357012e-01 -2.95223117e-01 6.15681946e-01 3.98427129e-01
-7.28191078e-01 1.21680170e-01 -1.12834476e-01 1.94145650e-01
4.61122245e-01 -8.94625366e-01 -1.50571436e-01 7.80342281e-01
3.61196071e-01 7.17637897e-01 3.93506974e-01 -5.81903279e-01
-2.12129521e+00 -7.25677073e-01 3.31969529e-01 -4.28977460e-01
3.02310258e-01 -2.73710996e-01 -3.76507521e-01 8.78897905e-01
-9.60628018e-02 2.04837635e-01 6.80009663e-01 -1.99479729e-01
1.42713934e-01 -2.40412548e-01 -1.02569997e+00 1.13625646e-01
1.17733157e+00 -6.63774848e-01 -9.07553673e-01 1.56198308e-01
4.92686480e-01 -8.32192540e-01 -1.29822254e+00 5.27812481e-01
9.99523282e-01 -9.88974690e-01 1.02801669e+00 -3.50570947e-01
4.15117592e-01 -6.11787796e-01 -2.57195920e-01 -1.21905160e+00
-4.74025249e-01 -3.31836551e-01 -5.27347147e-01 1.17982161e+00
-9.30618793e-02 -5.32971382e-01 4.87876713e-01 2.00548545e-02
-2.78058618e-01 -5.99535525e-01 -8.62669706e-01 -6.37575209e-01
-1.06588519e+00 -5.75021148e-01 7.73058176e-01 5.93163729e-01
2.35551655e-01 1.09453835e-01 -5.43223381e-01 3.11949372e-01
1.86083555e-01 6.94356188e-02 8.86427999e-01 -1.18970132e+00
-3.49827528e-01 7.36603932e-03 -6.85321331e-01 -1.02412248e+00
-2.03989353e-02 -5.30319214e-01 1.99834958e-01 -1.34531295e+00
4.01762500e-03 2.11836070e-01 -6.53620362e-01 3.22890043e-01
1.18152350e-02 3.15352790e-02 1.79521009e-01 2.54033566e-01
-2.90858597e-01 3.37023228e-01 1.19587469e+00 -3.69255304e-01
-2.02083558e-01 3.46597552e-01 -1.95696086e-01 6.59182966e-01
4.74862218e-01 -4.71711606e-02 -4.31440055e-01 -4.43350464e-01
-7.96024203e-02 4.85527456e-01 5.34520447e-01 -1.62179160e+00
2.48181507e-01 -2.99799293e-01 9.01049376e-01 -5.22024810e-01
5.75060010e-01 -1.06860816e+00 5.08334458e-01 6.91263139e-01
-1.66011989e-01 1.88224778e-01 -2.68442035e-01 8.17586184e-01
-3.60809833e-01 -1.08749457e-01 3.06229651e-01 -1.24579519e-01
-7.46610582e-01 1.48435548e-01 -2.60184914e-01 -6.75422609e-01
1.33119738e+00 -3.72096270e-01 -1.50070325e-01 7.48437494e-02
-9.57687676e-01 -2.66374983e-02 1.09122738e-01 8.82951558e-01
5.87879360e-01 -1.58234322e+00 -7.97749534e-02 6.77690089e-01
3.85438174e-01 2.48778593e-02 5.22876740e-01 1.10828531e+00
-4.02356476e-01 1.82625100e-01 -4.67447102e-01 -8.44155192e-01
-1.01846635e+00 6.05368197e-01 1.39206901e-01 -1.25728860e-01
-4.28695232e-01 5.05296707e-01 -3.48774523e-01 -3.80085737e-01
2.48590186e-01 -5.71265280e-01 -4.58620250e-01 2.42388129e-01
5.82046866e-01 6.56050026e-01 1.33831218e-01 -5.95215559e-01
-4.88359034e-01 7.25570440e-01 5.72506487e-01 -2.56174728e-02
1.15853429e+00 -1.63797930e-01 1.18836313e-01 7.77211666e-01
1.07376242e+00 -1.21102355e-01 -1.32166183e+00 -6.21599481e-02
-7.80113861e-02 -6.44031584e-01 -3.83532196e-01 -5.03941178e-01
-9.01939631e-01 8.29383433e-01 9.15353775e-01 3.55057418e-01
1.16405857e+00 -1.92004368e-02 7.18969285e-01 4.01152432e-01
6.40909314e-01 -1.18598008e+00 2.92001098e-01 3.61414909e-01
8.05947006e-01 -1.04411018e+00 -1.42388761e-01 -2.40365997e-01
-6.26428485e-01 1.05397272e+00 5.20595610e-01 7.69761158e-03
5.64617217e-01 3.53414774e-01 -2.72075646e-02 -1.14114128e-01
-3.46420884e-01 -2.56591588e-01 7.47025311e-02 7.53382564e-01
2.64078140e-01 2.68733829e-01 -1.80501655e-01 9.06819820e-01
3.88729237e-02 4.42861021e-01 1.35586262e-01 1.35061133e+00
-4.62924659e-01 -7.16387630e-01 -7.20163345e-01 5.29934704e-01
-2.59833872e-01 8.36891294e-01 -1.57938339e-02 4.53701973e-01
4.64660913e-01 1.17120790e+00 6.47320002e-02 -1.08156407e+00
7.99689472e-01 2.75866956e-01 5.51615179e-01 -4.07923490e-01
-4.09704834e-01 -1.14713609e-01 -8.15197751e-02 -8.70677173e-01
-5.80517292e-01 -7.24438250e-01 -1.06836927e+00 1.23640455e-01
-1.56417564e-01 -2.17825845e-01 7.41054356e-01 1.36039054e+00
4.60597992e-01 9.01146233e-01 7.77594805e-01 -1.41156745e+00
-5.34400225e-01 -1.35275853e+00 -7.70126939e-01 5.51867306e-01
2.11902842e-01 -1.14757502e+00 -1.57514751e-01 2.07247183e-01] | [7.866721153259277, 0.4866173565387726] |
a4fcf4d3-0635-49bd-a244-881704bb6f20 | toward-a-realistic-model-of-speech-processing | 2206.01685 | null | https://arxiv.org/abs/2206.01685v2 | https://arxiv.org/pdf/2206.01685v2.pdf | Toward a realistic model of speech processing in the brain with self-supervised learning | Several deep neural networks have recently been shown to generate activations similar to those of the brain in response to the same input. These algorithms, however, remain largely implausible: they require (1) extraordinarily large amounts of data, (2) unobtainable supervised labels, (3) textual rather than raw sensory input, and / or (4) implausibly large memory (e.g. thousands of contextual words). These elements highlight the need to identify algorithms that, under these limitations, would suffice to account for both behavioral and brain responses. Focusing on the issue of speech processing, we here hypothesize that self-supervised algorithms trained on the raw waveform constitute a promising candidate. Specifically, we compare a recent self-supervised architecture, Wav2Vec 2.0, to the brain activity of 412 English, French, and Mandarin individuals recorded with functional Magnetic Resonance Imaging (fMRI), while they listened to ~1h of audio books. Our results are four-fold. First, we show that this algorithm learns brain-like representations with as little as 600 hours of unlabelled speech -- a quantity comparable to what infants can be exposed to during language acquisition. Second, its functional hierarchy aligns with the cortical hierarchy of speech processing. Third, different training regimes reveal a functional specialization akin to the cortex: Wav2Vec 2.0 learns sound-generic, speech-specific and language-specific representations similar to those of the prefrontal and temporal cortices. Fourth, we confirm the similarity of this specialization with the behavior of 386 additional participants. These elements, resulting from the largest neuroimaging benchmark to date, show how self-supervised learning can account for a rich organization of speech processing in the brain, and thus delineate a path to identify the laws of language acquisition which shape the human brain. | ['Jean-Remi King', 'Christophe Pallier', 'Ewan Dunbar', 'Alexandre Gramfort', 'Yves Boubenec', 'Pierre Orhan', 'Charlotte Caucheteux', 'Juliette Millet'] | 2022-06-03 | null | null | null | null | ['language-acquisition'] | ['natural-language-processing'] | [ 2.88221419e-01 2.69526571e-01 1.14973478e-01 -5.60162127e-01
-3.43766600e-01 -5.84021688e-01 7.78948486e-01 1.77618831e-01
-6.04053974e-01 5.16437650e-01 5.71285307e-01 -3.80231559e-01
-9.43822786e-02 -5.90294600e-01 -6.90418184e-01 -3.83585781e-01
-2.09906548e-01 4.58631217e-01 1.14829145e-01 -3.68382365e-01
1.28729507e-01 3.33309740e-01 -1.64204013e+00 4.18742031e-01
7.46055007e-01 7.65681624e-01 4.95258540e-01 4.60747927e-01
5.30444272e-02 6.20863199e-01 -4.43285018e-01 -1.21587917e-01
-1.82354912e-01 -5.11320114e-01 -9.75913942e-01 -1.17591128e-01
5.58663607e-01 -2.12448373e-01 -3.73964220e-01 9.26026702e-01
5.56439698e-01 3.69029313e-01 7.21340537e-01 -5.50600827e-01
-8.28297615e-01 1.00409424e+00 -7.17035085e-02 8.26355696e-01
1.61275655e-01 3.37963402e-01 1.05997539e+00 -9.31522667e-01
5.65731406e-01 1.12869537e+00 3.50717276e-01 7.40657032e-01
-1.36708117e+00 -6.02052152e-01 -8.85603298e-03 1.35118626e-02
-1.09619653e+00 -1.00282300e+00 6.15198553e-01 -7.45252311e-01
1.24531829e+00 -2.21958011e-02 9.95389223e-01 1.65311682e+00
2.39919275e-01 3.51399422e-01 1.33895171e+00 -3.39910090e-01
2.94970572e-01 1.94561213e-01 2.66265839e-01 5.39184391e-01
5.17858267e-02 4.76927102e-01 -9.65365648e-01 5.48772179e-02
6.93722963e-01 -3.61671120e-01 -3.13965291e-01 1.94869459e-01
-1.49007964e+00 7.27214992e-01 2.60944158e-01 9.27209496e-01
-3.85045707e-01 1.71957821e-01 6.39186263e-01 4.53102350e-01
3.59197229e-01 7.35432267e-01 -5.73508620e-01 -1.51655644e-01
-1.06794739e+00 -3.64849716e-01 5.27975261e-01 4.51891422e-01
5.16878903e-01 6.52844906e-01 2.43253976e-01 1.12244928e+00
2.36572847e-01 4.23098654e-01 1.11529720e+00 -6.80796087e-01
1.87493354e-01 -5.16824685e-02 -5.92086375e-01 -9.51041460e-01
-6.69035554e-01 -5.66594541e-01 -7.09562063e-01 1.24954529e-01
3.78200173e-01 -4.42652442e-02 -6.18489146e-01 2.22013712e+00
-1.93391964e-01 -2.33451366e-01 -6.54124096e-02 7.21774459e-01
7.59162009e-01 5.13108969e-01 1.67364985e-01 -2.94429570e-01
1.36784148e+00 -5.42430103e-01 -5.20529330e-01 -6.18535340e-01
2.37867370e-01 -2.37988159e-01 1.34804308e+00 4.22754526e-01
-1.34563339e+00 -6.99833393e-01 -1.10989749e+00 1.56730667e-01
-5.08114815e-01 -3.71865541e-01 9.32932675e-01 7.65161157e-01
-1.34222186e+00 5.74150503e-01 -7.61004925e-01 -5.58392048e-01
2.87636578e-01 4.22226965e-01 -6.16615713e-01 5.12617230e-01
-1.32406211e+00 9.99499977e-01 4.11319286e-01 -1.37423918e-01
-1.11069679e+00 -6.94983780e-01 -8.10683131e-01 2.27615133e-01
1.22461114e-02 -4.16429937e-01 1.26805985e+00 -1.31842422e+00
-1.37536263e+00 1.12690079e+00 -8.82749557e-02 -3.72673452e-01
-2.25900158e-01 1.38663471e-01 -6.48045361e-01 4.21916515e-01
1.04979180e-01 7.61989653e-01 8.45874488e-01 -8.18715274e-01
-1.28162727e-01 -5.30928552e-01 -3.67344320e-01 -4.59974911e-03
-5.57838619e-01 2.28850216e-01 1.69694096e-01 -9.30299163e-01
1.28346264e-01 -6.15101397e-01 1.00840136e-01 -3.67199361e-01
4.87639615e-03 -2.93352813e-01 1.07520455e-02 -8.11809421e-01
9.21398699e-01 -2.44355750e+00 6.44896254e-02 1.72086671e-01
4.36929673e-01 -1.46100178e-01 -3.09213072e-01 2.97329932e-01
-4.56810296e-01 3.39880109e-01 -3.90087426e-01 1.21239446e-01
6.20472319e-02 9.83747244e-02 -3.15333188e-01 7.40205348e-01
1.59874335e-01 1.13259470e+00 -9.08178031e-01 -1.61903545e-01
-1.46876261e-01 3.37241828e-01 -6.00118756e-01 2.70538330e-02
-3.19378451e-02 5.42045414e-01 1.61125645e-01 3.42267334e-01
9.61280540e-02 -7.75479376e-02 1.76957205e-01 2.31381468e-02
-2.60640442e-01 7.35758483e-01 -5.56512058e-01 1.70776665e+00
-3.62445623e-01 9.96955931e-01 2.17994601e-01 -1.34892106e+00
5.91048777e-01 5.91448247e-01 1.90003514e-01 -1.11285079e+00
4.44695592e-01 3.35700005e-01 6.97984457e-01 -5.77645957e-01
-2.23720834e-01 -5.08252025e-01 1.31495502e-02 7.47890651e-01
8.42593014e-01 -2.87952244e-01 2.66005322e-02 1.22037388e-01
1.10177374e+00 -4.74981397e-01 2.70202100e-01 -6.96931481e-01
3.12468737e-01 -4.26076502e-01 4.03056085e-01 7.85307169e-01
-1.33652970e-01 5.05469024e-01 3.78368676e-01 -2.45310709e-01
-9.58444834e-01 -1.28526950e+00 -2.87232071e-01 1.43429947e+00
-6.66425705e-01 -5.97366616e-02 -8.24796557e-01 -7.58657530e-02
-4.00046557e-01 8.16800654e-01 -6.95747137e-01 -4.05697078e-01
-5.63129306e-01 -4.25170004e-01 7.53708720e-01 6.60231888e-01
4.87218685e-02 -1.63309312e+00 -7.94538736e-01 3.13751400e-01
9.89993587e-02 -1.08629513e+00 -3.32907617e-01 4.82499182e-01
-7.72710800e-01 -6.91295505e-01 -5.07470131e-01 -9.37106073e-01
4.71053898e-01 -6.60374984e-02 1.13038588e+00 1.79630384e-01
-3.61156821e-01 6.78443074e-01 -1.33948714e-01 -3.28351468e-01
-3.81916910e-01 5.99751100e-02 6.00354373e-01 -1.60367593e-01
6.06224425e-02 -1.18684626e+00 -3.69817346e-01 -8.46122652e-02
-8.29954088e-01 -1.58525363e-01 6.61466777e-01 9.79949951e-01
2.27289096e-01 -9.85706598e-02 1.02976823e+00 -7.53785670e-01
8.33397329e-01 -7.08916426e-01 -2.96386480e-01 1.33691831e-02
-5.00306427e-01 -5.27817309e-02 6.60262465e-01 -5.83800375e-01
-9.85713363e-01 -8.99294093e-02 -2.87570268e-01 1.01688430e-01
-5.73019564e-01 5.02547979e-01 1.07883513e-01 1.19949937e-01
9.57497895e-01 4.63381201e-01 7.98742548e-02 -1.92676008e-01
5.09094179e-01 5.86490750e-01 9.13620472e-01 -6.86541975e-01
7.06344783e-01 2.55165279e-01 -5.20229518e-01 -1.30660093e+00
-5.32226920e-01 -4.73292470e-02 -7.96923995e-01 -7.15339109e-02
1.23219025e+00 -7.13578105e-01 -7.17942417e-01 2.79377222e-01
-1.18628728e+00 -6.22520030e-01 -4.19843614e-01 8.86905730e-01
-6.28607392e-01 2.11394235e-01 -7.67009914e-01 -8.07686448e-01
-3.74791503e-01 -8.50457311e-01 5.37997603e-01 -6.98610246e-02
-6.75320804e-01 -9.91625547e-01 1.08223148e-01 2.78603494e-01
6.07295096e-01 -1.41720265e-01 1.25281537e+00 -1.16290331e+00
3.76659520e-02 2.52075374e-01 4.95917313e-02 4.41725492e-01
1.03491209e-01 -2.77331352e-01 -1.35148442e+00 -1.24822780e-01
3.56669366e-01 -6.68697298e-01 8.66570354e-01 2.96749324e-01
1.05752528e+00 -1.95450276e-01 1.42296910e-01 4.87261176e-01
8.12783182e-01 3.72661382e-01 1.93333283e-01 -1.81705058e-01
1.82526842e-01 1.02019036e+00 -3.67636472e-01 -3.42961624e-02
6.09438084e-02 2.20517442e-01 1.96431000e-02 9.11625549e-02
-2.28770792e-01 -2.67718166e-01 5.86176872e-01 1.44191456e+00
1.22480042e-01 1.12310022e-01 -1.06968081e+00 7.91895330e-01
-1.15003085e+00 -1.19253850e+00 7.82227889e-02 2.13974404e+00
1.01260090e+00 2.81636357e-01 1.49906114e-01 2.22211391e-01
3.63385081e-01 2.05261320e-01 -5.89696109e-01 -7.42963374e-01
-3.74633342e-01 9.16202903e-01 -8.60921219e-02 4.36358243e-01
-6.62709653e-01 1.07080281e+00 7.39428997e+00 4.08300757e-01
-1.37072003e+00 4.65013564e-01 4.53167647e-01 -1.18469834e-01
-4.44131255e-01 -4.51151699e-01 -5.95755577e-02 2.99138784e-01
1.64087093e+00 -2.64074147e-01 1.03125322e+00 5.37951052e-01
1.02100343e-01 1.05118394e-01 -1.34144104e+00 8.70461345e-01
2.44458646e-01 -1.17248261e+00 -2.98512518e-01 -2.85171699e-02
3.03569436e-01 4.25721645e-01 2.18899801e-01 3.17475349e-01
4.10755873e-02 -1.49256110e+00 9.45778251e-01 2.60115415e-01
9.29038763e-01 -2.46356919e-01 6.92985728e-02 4.88157749e-01
-7.67348588e-01 -1.01584353e-01 -2.84921736e-01 -2.51209676e-01
1.11090422e-01 3.91895175e-01 -7.14179754e-01 -2.75143027e-01
6.57303154e-01 3.22879583e-01 -5.19122124e-01 5.36399126e-01
-3.21930110e-01 1.02361584e+00 -1.91357270e-01 -8.94185528e-02
1.05359592e-01 3.08004826e-01 3.59051079e-01 1.27026427e+00
1.36265770e-01 3.32466483e-01 -5.06848454e-01 1.08323467e+00
2.50842646e-02 4.41115767e-01 -8.44851017e-01 -4.61582631e-01
4.42655951e-01 1.02620554e+00 -7.86867559e-01 -2.34458759e-01
-6.14762306e-01 8.42908323e-01 4.87574309e-01 2.80460179e-01
-3.73052031e-01 -1.57942086e-01 4.58481044e-01 2.43937578e-02
-9.90379080e-02 -4.80173796e-01 -3.91693294e-01 -1.04302049e+00
-2.05518559e-01 -9.36439157e-01 -4.74242643e-02 -7.62593031e-01
-1.40657258e+00 8.91909957e-01 -2.13007629e-01 -4.73509878e-01
-3.53218108e-01 -6.95966601e-01 -5.72597027e-01 8.38905573e-01
-9.44304287e-01 -5.66526592e-01 8.52124542e-02 6.89026237e-01
7.40414679e-01 -4.02850866e-01 1.02561867e+00 3.27040911e-01
-4.13984001e-01 5.05555570e-01 -3.65730643e-01 1.56106010e-01
3.61669451e-01 -1.10508120e+00 5.48087239e-01 5.99815845e-01
7.68054485e-01 9.82107520e-01 2.55816430e-01 -4.29300129e-01
-1.13309407e+00 -5.02371669e-01 9.04070616e-01 -4.31383699e-01
8.46967578e-01 -8.34017754e-01 -1.06643510e+00 5.78782141e-01
5.37867248e-01 -1.22651763e-01 9.63769734e-01 1.85198203e-01
-5.13643920e-01 1.01746451e-02 -9.52017188e-01 5.28491378e-01
1.34030449e+00 -1.03540087e+00 -1.17632699e+00 4.98634249e-01
9.44726765e-01 1.63689569e-01 -6.74231529e-01 8.74539241e-02
6.82555735e-01 -9.21900094e-01 8.81742239e-01 -9.32720721e-01
3.85632515e-01 2.27530569e-01 -2.13650003e-01 -1.44212437e+00
-6.07590079e-01 -4.23208982e-01 1.29389256e-01 1.04455769e+00
7.15085566e-01 -7.43269801e-01 1.50097504e-01 4.71181720e-01
-3.23476106e-01 -5.26452363e-01 -1.15588522e+00 -7.07326770e-01
3.99077415e-01 -6.44343317e-01 3.65351886e-01 1.12667596e+00
2.60557234e-01 5.06334722e-01 8.55432302e-02 -1.27587467e-01
2.79506505e-01 -5.01107514e-01 8.30501765e-02 -1.52466857e+00
-3.02959472e-01 -7.15890467e-01 -2.03962639e-01 -5.56949675e-01
7.84835160e-01 -1.37478971e+00 1.24090193e-02 -1.17941642e+00
7.07644969e-02 -1.01475924e-01 -5.01053274e-01 5.66648364e-01
2.99887955e-01 -8.36163852e-03 -5.09109460e-02 -1.30328750e-02
5.95225878e-02 3.57243240e-01 8.62496316e-01 -1.22010775e-01
-4.51576188e-02 -4.07959193e-01 -1.00020015e+00 8.49919319e-01
8.84073734e-01 -3.21200043e-01 -5.73248327e-01 -6.47558630e-01
3.08436990e-01 9.16699618e-02 2.98484653e-01 -1.05311596e+00
2.32596248e-01 -8.93086046e-02 4.73117858e-01 7.92758986e-02
2.23511815e-01 -5.48565269e-01 -2.36781567e-01 4.76851106e-01
-5.65449774e-01 6.26081973e-02 2.13717058e-01 2.05514595e-01
-1.86226830e-01 -2.50251263e-01 8.61188114e-01 -4.88681108e-01
-7.44765580e-01 2.82695424e-02 -1.06379402e+00 3.79836857e-01
4.52983648e-01 2.94686388e-02 -3.60239744e-01 -3.87036383e-01
-9.02367532e-01 -2.90798932e-01 -7.30091557e-02 5.48588753e-01
6.10787094e-01 -1.10174441e+00 -5.84051669e-01 4.83651608e-01
-1.90203622e-01 -5.54930806e-01 1.22587100e-01 8.14235985e-01
-1.25819743e-01 5.85768580e-01 -3.14685583e-01 -3.49697232e-01
-6.08037472e-01 5.74652910e-01 2.44604394e-01 4.94421095e-01
-5.68080306e-01 1.09473908e+00 4.58399832e-01 -4.71188545e-01
1.96228400e-02 -3.17175329e-01 -2.72693515e-01 4.23841566e-01
6.18278861e-01 2.71715112e-02 1.05082840e-01 -7.06339836e-01
-3.79790425e-01 1.78836480e-01 2.11864382e-01 -6.46543145e-01
1.57061839e+00 2.29811430e-01 -4.02534723e-01 8.95448089e-01
1.05397165e+00 2.72431850e-01 -5.45958161e-01 -4.93132360e-02
9.94619075e-03 4.08567116e-02 9.68526118e-04 -6.92067683e-01
-1.15357506e+00 1.23323274e+00 4.89900619e-01 1.87308729e-01
9.81634736e-01 2.53959596e-01 6.04022264e-01 4.26024556e-01
3.17760408e-01 -1.32084417e+00 2.51854956e-01 6.01256251e-01
1.13081563e+00 -8.68316829e-01 -3.97702545e-01 7.12290257e-02
-5.33240616e-01 9.44298923e-01 6.81623459e-01 -3.08602210e-02
6.79616392e-01 2.25500092e-01 -1.07059069e-01 -4.00329262e-01
-9.80540037e-01 -1.95415542e-01 2.76694804e-01 6.24266803e-01
8.01801920e-01 2.03201011e-01 -3.88887823e-01 1.05651081e+00
-7.43751109e-01 -4.49198693e-01 3.90226305e-01 5.85886657e-01
-5.41966319e-01 -7.91514158e-01 -2.55472004e-01 5.76141298e-01
-3.92871410e-01 -4.12925422e-01 -4.28697318e-01 5.44739187e-01
1.49843633e-01 9.62592840e-01 1.77391425e-01 -3.26756388e-01
2.27409035e-01 6.31469309e-01 4.87719923e-01 -1.15004110e+00
-7.86554158e-01 9.11732540e-02 1.65952891e-02 -4.40243423e-01
-2.12364241e-01 -8.96058142e-01 -1.38270915e+00 1.48601428e-01
-3.08061857e-02 -1.90992709e-02 5.16924798e-01 9.02290285e-01
6.97222278e-02 4.90057558e-01 3.06108147e-01 -7.18335688e-01
-4.02907491e-01 -1.18855584e+00 -7.28521526e-01 3.87316883e-01
3.36332411e-01 -6.00431442e-01 -5.96044302e-01 6.32765442e-02] | [10.333003044128418, 8.51891040802002] |
375f0ee9-f94b-459f-825a-667aaefc94ed | r2-d2-color-inspired-convolutional-neural | 1705.04448 | null | http://arxiv.org/abs/1705.04448v5 | http://arxiv.org/pdf/1705.04448v5.pdf | R2-D2: ColoR-inspired Convolutional NeuRal Network (CNN)-based AndroiD Malware Detections | The influence of Deep Learning on image identification and natural language
processing has attracted enormous attention globally. The convolution neural
network that can learn without prior extraction of features fits well in
response to the rapid iteration of Android malware. The traditional solution
for detecting Android malware requires continuous learning through
pre-extracted features to maintain high performance of identifying the malware.
In order to reduce the manpower of feature engineering prior to the condition
of not to extract pre-selected features, we have developed a coloR-inspired
convolutional neuRal networks (CNN)-based AndroiD malware Detection (R2-D2)
system. The system can convert the bytecode of classes.dex from Android archive
file to rgb color code and store it as a color image with fixed size. The color
image is input to the convolutional neural network for automatic feature
extraction and training. The data was collected from Jan. 2017 to Aug 2017.
During the period of time, we have collected approximately 2 million of benign
and malicious Android apps for our experiments with the help from our research
partner Leopard Mobile Inc. Our experiment results demonstrate that the
proposed system has accurate security analysis on contracts. Furthermore, we
keep our research results and experiment materials on http://R2D2.TWMAN.ORG. | ['Hung-Yu Kao', 'TonTon Hsien-De Huang'] | 2017-05-12 | null | null | null | null | ['android-malware-detection'] | ['miscellaneous'] | [ 6.04560077e-02 -5.50809205e-01 -2.45642781e-01 -3.55971009e-01
-3.06340545e-01 -5.82196712e-01 2.67370403e-01 -4.22508448e-01
-5.26189864e-01 1.77514642e-01 -4.30472434e-01 -8.73001873e-01
3.26468527e-01 -7.31995583e-01 -6.13947093e-01 -3.05911839e-01
-2.40959704e-01 -2.90552080e-01 7.85027742e-02 -9.17876810e-02
3.79643947e-01 3.90486658e-01 -1.38828015e+00 5.74005246e-01
6.88592374e-01 1.49261320e+00 5.75862899e-02 8.83162856e-01
-1.69355080e-01 7.55950689e-01 -6.99455380e-01 -5.22675276e-01
6.95423663e-01 8.52601379e-02 -5.79687893e-01 -4.09946740e-01
-1.61144182e-01 -7.65201390e-01 -3.47424567e-01 1.45619285e+00
2.62874126e-01 -5.14985561e-01 3.73260945e-01 -1.35917366e+00
-7.93820560e-01 3.94377619e-01 -7.99198210e-01 3.30053985e-01
2.24766415e-02 2.67991126e-01 2.95608163e-01 -8.86064112e-01
2.07269341e-01 1.12304950e+00 8.25611472e-01 5.84469557e-01
-3.16574693e-01 -1.05546248e+00 -2.89633393e-01 4.13862854e-01
-1.44637942e+00 -1.64557308e-01 9.16844964e-01 -5.46121895e-01
7.78857529e-01 1.66655377e-01 7.87927151e-01 1.23529828e+00
4.60315466e-01 6.15145922e-01 1.06513202e+00 -5.60963601e-02
-6.61856309e-02 2.66064823e-01 4.43926007e-01 1.03617442e+00
3.47508401e-01 6.57987222e-02 -5.63479923e-02 -2.58051038e-01
4.49476689e-01 7.62140989e-01 1.31202266e-01 3.48651201e-01
-5.75234950e-01 9.17753935e-01 4.47071046e-01 1.58083588e-01
-2.79869121e-02 1.48453027e-01 7.53243744e-01 3.04326832e-01
2.30288833e-01 3.04744616e-02 -5.98381400e-01 -4.72690672e-01
-6.94188297e-01 -3.44840735e-01 5.56512892e-01 8.03583622e-01
8.96678567e-01 2.04643548e-01 3.77564192e-01 6.33637428e-01
3.50381851e-01 6.87336981e-01 8.80427659e-01 -7.36288846e-01
2.41906613e-01 9.99407589e-01 -3.82972747e-01 -1.33993733e+00
-7.64551386e-02 9.93830990e-03 -7.35856891e-01 1.58483684e-01
2.37187877e-01 -4.69714314e-01 -8.34043741e-01 1.13408494e+00
-3.88041162e-03 1.37586161e-01 -6.54207636e-03 4.82480019e-01
6.98697865e-01 8.42927933e-01 -2.68043786e-01 -3.16031948e-02
1.60862625e+00 -6.15744531e-01 -3.77908021e-01 -1.68188080e-01
5.68197668e-01 -7.05886960e-01 1.51291800e+00 5.59849977e-01
-3.43267947e-01 -7.43374050e-01 -1.31063318e+00 2.48650257e-02
-9.12420392e-01 5.36943495e-01 6.47261977e-01 1.16131306e+00
-8.07909310e-01 1.29975647e-01 -8.68489861e-01 -7.59731084e-02
8.75788152e-01 6.91017568e-01 -1.59014985e-01 1.68961853e-01
-9.12607551e-01 7.26288781e-02 3.00563723e-01 2.28113443e-01
-1.07172728e+00 -9.60646197e-02 -4.84859675e-01 5.01425304e-02
4.44065511e-01 3.22886020e-01 1.24036717e+00 -1.37892342e+00
-1.43943954e+00 6.67514265e-01 1.90686747e-01 -4.54017669e-01
1.86367929e-01 -3.73180181e-01 -6.57893002e-01 4.16861363e-02
-1.07410729e-01 3.85249287e-01 1.17006266e+00 -9.74088967e-01
-5.59396029e-01 -4.02710110e-01 8.46051052e-03 -4.67318296e-01
-1.03648221e+00 3.87896359e-01 -5.83404541e-01 -3.82367820e-01
-5.42496562e-01 -1.16557908e+00 3.68691385e-01 -3.03822249e-01
-5.08258462e-01 -1.44263670e-01 1.76297426e+00 -8.59475195e-01
1.13964987e+00 -2.48289394e+00 -7.08680570e-01 2.81999618e-01
3.56340259e-01 7.44842172e-01 -9.84920487e-02 -4.56526019e-02
-1.84887499e-01 4.79624480e-01 -1.99516177e-01 1.09214291e-01
-3.12457383e-01 -1.09929562e-01 -3.58918250e-01 3.07491541e-01
2.79742986e-01 9.41102922e-01 -5.29984891e-01 -5.32989383e-01
-1.26207635e-01 6.38156176e-01 -4.66872185e-01 2.29166165e-01
-5.60860522e-02 -2.75540259e-02 -5.22415578e-01 9.08025146e-01
9.90214705e-01 -2.89214492e-01 8.71251896e-02 -2.21537590e-01
-3.98542508e-02 2.35095441e-01 -6.07201457e-01 1.06526017e+00
-4.95759338e-01 9.37429726e-01 1.01760060e-01 -8.36593151e-01
8.46167386e-01 -1.38569474e-01 5.33579528e-01 -5.72588801e-01
6.39318705e-01 1.54031798e-01 3.70694190e-01 -7.85654902e-01
3.56866360e-01 7.44042456e-01 -1.20092086e-01 7.60434091e-01
-2.87782133e-01 3.39137703e-01 -1.88829258e-01 1.83671355e-01
1.07579088e+00 -2.21646458e-01 -7.50261098e-02 -5.63115366e-02
7.00554132e-01 -5.66025672e-04 4.45077211e-01 3.23399693e-01
-3.95482719e-01 -1.29366115e-01 6.93682313e-01 -6.42478168e-01
-7.14681566e-01 -5.96020699e-01 1.83377579e-01 1.17235827e+00
-4.40011993e-02 -4.98498082e-01 -1.21287644e+00 -1.12664986e+00
-2.75997847e-01 -4.05618064e-02 -7.53864765e-01 -3.75158370e-01
-7.92248905e-01 -5.34262359e-01 8.54541779e-01 2.94285208e-01
1.21580148e+00 -1.19575846e+00 -6.96123600e-01 -2.32549623e-01
1.93348855e-01 -8.76273751e-01 -6.33620024e-01 8.58432725e-02
-4.53713775e-01 -1.56182921e+00 -3.56727749e-01 -1.06069434e+00
7.60224879e-01 4.17720377e-01 4.94710416e-01 5.46064794e-01
-4.89684463e-01 2.95639396e-01 -3.57045770e-01 -6.81868255e-01
-2.84845859e-01 2.54341841e-01 1.65988147e-01 1.26615420e-01
8.54320109e-01 -1.48143128e-01 -5.35815001e-01 1.29470095e-01
-8.65816414e-01 -3.61209542e-01 6.96508408e-01 6.33814216e-01
2.12572813e-01 3.52109194e-01 2.43110642e-01 -8.31172407e-01
1.00302017e+00 -5.29625773e-01 -7.94589579e-01 -5.04862852e-02
-5.29052556e-01 -3.49329859e-01 9.16527867e-01 -8.20932984e-01
-7.05183029e-01 1.73356593e-01 -1.98424175e-01 -3.56953263e-01
1.19497962e-02 3.88185620e-01 -2.24432051e-01 -1.43316999e-01
5.35192847e-01 3.87318969e-01 2.61653215e-01 -2.00915635e-01
6.77332655e-02 1.44683468e+00 3.84132922e-01 -1.48497224e-01
8.28631759e-01 2.75255114e-01 -4.68163729e-01 -8.77990484e-01
-2.24584058e-01 9.61698741e-02 -2.87346721e-01 -1.06894001e-01
1.03193235e+00 -7.51450837e-01 -1.18325627e+00 9.18227792e-01
-1.08103848e+00 -3.30314577e-01 4.10124779e-01 1.54305100e-01
1.19810507e-01 5.12187779e-01 -8.01446319e-01 -7.66792715e-01
-6.18879616e-01 -1.52835357e+00 7.00001657e-01 3.63949895e-01
3.69713336e-01 -5.03858745e-01 -3.14363569e-01 7.48312846e-02
5.60076237e-01 -3.68063860e-02 7.68498421e-01 -6.36841416e-01
-4.40152794e-01 -3.56545508e-01 -6.16001010e-01 6.56806588e-01
4.57659811e-01 6.09432161e-01 -1.04562736e+00 -3.02753627e-01
5.14680028e-01 -1.73143774e-01 7.50052273e-01 1.43935829e-01
1.98233581e+00 -8.02117825e-01 -2.20933244e-01 7.75446534e-01
1.22751796e+00 7.46145666e-01 6.83236480e-01 3.60741168e-01
9.22362208e-01 3.71261507e-01 4.57209170e-01 2.12912932e-01
2.91747808e-01 2.61027277e-01 6.85295820e-01 -7.74223506e-02
1.78143606e-01 -1.85682401e-02 7.82383680e-01 8.02570105e-01
3.68080661e-02 1.44508362e-01 -9.81440425e-01 7.04397261e-02
-1.31160080e+00 -8.25514615e-01 8.17410424e-02 1.93117321e+00
6.96291506e-01 4.02441472e-01 3.66358876e-01 7.81940892e-02
7.49506176e-01 -1.94668710e-01 -5.69468975e-01 -6.31877542e-01
3.60783607e-01 1.70337513e-01 5.74188888e-01 1.61168858e-01
-1.19112337e+00 8.92497301e-01 5.47613955e+00 9.90762293e-01
-1.87079394e+00 3.08701068e-01 9.29095030e-01 3.07663769e-01
2.27196068e-01 -2.79690534e-01 -5.51573098e-01 9.30619419e-01
1.15967965e+00 2.04099521e-01 7.88061023e-01 1.29478621e+00
-7.43837422e-03 1.29506752e-01 -5.75393379e-01 1.31283438e+00
-7.20865577e-02 -1.18525171e+00 -1.49971023e-01 4.88001764e-01
4.95648146e-01 1.28062665e-01 6.08799517e-01 4.65876251e-01
-2.61237305e-02 -1.12750280e+00 2.62232453e-01 2.31357768e-01
1.18257654e+00 -9.62243140e-01 8.02915871e-01 8.75183418e-02
-1.28795111e+00 -8.20675433e-01 -4.18713599e-01 2.94446573e-02
-7.10984230e-01 3.14832568e-01 -1.02152848e+00 -2.94570345e-02
1.00690627e+00 7.04379082e-01 -9.24498439e-01 4.18082505e-01
1.47739768e-01 9.77652609e-01 -9.71320719e-02 -3.57997090e-01
1.40674248e-01 -5.99092953e-02 -1.20091558e-01 1.15055966e+00
4.14783180e-01 -1.94242045e-01 -1.30860716e-01 6.86436236e-01
-3.47742140e-01 1.20185822e-01 -7.95413196e-01 -6.35531843e-01
5.58593869e-01 1.51047158e+00 -7.47086525e-01 -5.39048553e-01
-4.59719181e-01 7.86453545e-01 5.19976765e-02 5.35955392e-02
-1.04031873e+00 -8.11001599e-01 5.84810972e-01 1.98473454e-01
2.22427011e-01 -5.86914539e-01 -2.71839529e-01 -7.99230218e-01
-9.24817398e-02 -1.28192580e+00 4.11802754e-02 -4.49035585e-01
-9.54010010e-01 8.88378024e-01 -2.67894864e-01 -1.26350260e+00
-1.75325170e-01 -1.25415111e+00 -9.68781829e-01 4.71842974e-01
-1.06129622e+00 -9.80346620e-01 -5.36697149e-01 8.61157238e-01
5.12301862e-01 -8.67670894e-01 5.88358462e-01 4.70219821e-01
-8.87391567e-01 8.35374296e-01 -2.25145388e-02 6.76477909e-01
4.39837813e-01 -9.02430832e-01 5.10491133e-01 9.37991560e-01
-1.49107426e-01 1.08977568e+00 -2.65176129e-02 -1.00022674e+00
-1.84051383e+00 -1.09881675e+00 2.07833961e-01 -2.40512133e-01
5.95893681e-01 -5.77769518e-01 -7.12680757e-01 5.76988816e-01
3.25887680e-01 2.47982796e-02 6.27485275e-01 -6.13469183e-01
-5.19675374e-01 -5.00651062e-01 -1.19869006e+00 4.56530452e-01
5.81143677e-01 -8.54221046e-01 2.42512614e-01 2.15433255e-01
7.14571118e-01 -6.11094199e-02 -4.14701909e-01 2.24447042e-01
6.21954441e-01 -8.66289139e-01 7.93525100e-01 -3.08067769e-01
3.48870456e-01 -3.08939517e-01 -5.64420857e-02 -4.58949178e-01
2.19670027e-01 -6.43129408e-01 -1.40279278e-01 8.53424549e-01
3.67184699e-01 -7.11894512e-01 8.38755429e-01 2.35220626e-01
-2.54504159e-02 -8.82996261e-01 -6.37399077e-01 -6.16792083e-01
-2.30104029e-01 -5.92836559e-01 8.85073841e-01 8.55813444e-01
-3.42693061e-01 -9.89009961e-02 -3.37024897e-01 4.27581966e-02
1.50998518e-01 -2.41337195e-01 9.61782098e-01 -1.02919185e+00
-1.30508691e-01 -4.38185304e-01 -2.69442499e-01 -8.17096293e-01
5.58975711e-02 -7.14932978e-01 -2.75000036e-01 -6.90822661e-01
3.49731892e-01 -2.96630025e-01 -2.43484542e-01 8.16806614e-01
6.98262677e-02 5.45883715e-01 -3.25002968e-02 3.50903153e-01
-3.32885981e-01 1.67837977e-01 8.33983779e-01 -4.37673211e-01
-3.18775445e-01 6.47168681e-02 -7.87728488e-01 7.95310199e-01
1.23448169e+00 -4.67875391e-01 -4.44539845e-01 -3.61456811e-01
1.06532410e-01 -5.57732165e-01 3.66172105e-01 -9.24586654e-01
-1.38556555e-01 1.94296557e-02 6.79342330e-01 -4.66940969e-01
2.92396933e-01 -1.07784319e+00 -1.20012835e-01 9.42676008e-01
-2.51048021e-02 5.39850235e-01 2.80278474e-01 2.57574320e-01
1.07609376e-01 -1.95363820e-01 4.83886510e-01 -1.43254533e-01
-8.17125380e-01 2.99173415e-01 -5.42675614e-01 -3.54772896e-01
1.00488985e+00 -3.87698203e-01 -6.16094470e-01 -3.31306070e-01
-1.04092911e-01 -3.19275558e-01 4.48513597e-01 5.34174740e-01
8.25657189e-01 -1.25712311e+00 -1.88398272e-01 5.71746945e-01
-1.46134034e-01 -5.41625559e-01 -1.08952709e-01 5.60315728e-01
-9.28821743e-01 2.81833142e-01 -5.53372860e-01 -4.98191506e-01
-1.54208899e+00 7.14300275e-01 3.30126017e-01 -1.09399948e-02
-2.11984128e-01 6.22562468e-01 -2.82319695e-01 -3.23194951e-01
2.79923886e-01 -2.22398713e-01 -3.75934839e-01 -3.64805967e-01
7.63508439e-01 3.59603822e-01 -9.45542306e-02 -6.31462455e-01
-6.43791020e-01 3.63236904e-01 -3.60081643e-01 2.40627825e-01
1.18972206e+00 2.73087651e-01 -4.01899010e-01 -1.02020189e-01
1.72060955e+00 4.42447543e-01 -9.96475339e-01 4.06804830e-01
-1.30031794e-01 -3.54383349e-01 -1.98927537e-01 -5.80159962e-01
-1.50615704e+00 1.10122442e+00 1.38389337e+00 6.51915431e-01
1.15807760e+00 -4.22579765e-01 1.09421408e+00 6.15461230e-01
3.99963334e-02 -1.02458656e+00 4.67466861e-01 4.60103422e-01
5.20172000e-01 -1.41414130e+00 -2.34905049e-01 -2.37506673e-01
-3.54090601e-01 1.31531847e+00 9.77708936e-01 -2.28250757e-01
9.14812386e-01 4.28987861e-01 2.78758556e-01 -3.49538952e-01
-7.73502663e-02 2.13125214e-01 1.76851705e-01 8.50082040e-01
2.84322739e-01 1.07771218e-01 -1.56006292e-01 7.78053701e-01
-3.35974902e-01 -1.76764920e-01 4.43694949e-01 9.82731700e-01
-4.07290816e-01 -1.19995320e+00 -3.82236511e-01 7.06769347e-01
-8.17643702e-01 -1.48688912e-01 -7.93983638e-01 7.22330451e-01
5.22802711e-01 9.62689161e-01 -9.18086525e-03 -1.23203325e+00
-3.60102892e-01 -1.82655588e-01 -9.05061066e-02 -3.86473596e-01
-5.92806697e-01 -1.69992670e-01 -3.67491215e-01 -4.55156744e-01
9.41179097e-02 -2.11194307e-01 -1.31683350e+00 -4.07006562e-01
-1.62278056e-01 4.61000949e-02 1.06192422e+00 6.20640755e-01
5.93793690e-01 3.20223451e-01 9.75819767e-01 -7.92748570e-01
-2.85174549e-01 -9.65234876e-01 -4.47127186e-02 7.68783465e-02
4.40269619e-01 -3.82968366e-01 -1.09648794e-01 -1.45379128e-02] | [14.421274185180664, 9.6759033203125] |
61aa7bc3-41bf-45e5-8d9e-7c1054db69ac | bi-directional-recurrent-neural-ordinary | 2112.12809 | null | https://arxiv.org/abs/2112.12809v1 | https://arxiv.org/pdf/2112.12809v1.pdf | Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification | Classification of posts in social media such as Twitter is difficult due to the noisy and short nature of texts. Sequence classification models based on recurrent neural networks (RNN) are popular for classifying posts that are sequential in nature. RNNs assume the hidden representation dynamics to evolve in a discrete manner and do not consider the exact time of the posting. In this work, we propose to use recurrent neural ordinary differential equations (RNODE) for social media post classification which consider the time of posting and allow the computation of hidden representation to evolve in a time-sensitive continuous manner. In addition, we propose a novel model, Bi-directional RNODE (Bi-RNODE), which can consider the information flow in both the forward and backward directions of posting times to predict the post label. Our experiments demonstrate that RNODE and Bi-RNODE are effective for the problem of stance classification of rumours in social media. | ['P. K. Srijith', 'Srinivas Anumasa', 'Maunika Tamire'] | 2021-12-23 | null | https://aclanthology.org/2022.wit-1.3 | https://aclanthology.org/2022.wit-1.3.pdf | wit-acl-2022-5 | ['rumour-detection'] | ['natural-language-processing'] | [ 1.51032507e-01 -2.38212094e-01 -2.39373147e-01 -2.71533728e-01
3.15580308e-01 -4.03893203e-01 6.67012513e-01 1.14977941e-01
-4.70471054e-01 7.24260151e-01 3.23617816e-01 -5.41520536e-01
2.69921154e-01 -9.78411853e-01 -3.92978132e-01 -6.83993638e-01
-1.47209093e-01 2.44762734e-01 6.35746345e-02 -6.70810819e-01
2.88229764e-01 3.99149120e-01 -1.61957800e+00 4.36307043e-01
3.04444879e-01 8.36108387e-01 -9.76318717e-02 1.05442262e+00
-3.90683353e-01 1.39077640e+00 -5.90678990e-01 6.67704269e-02
-1.52390853e-01 -7.71192729e-01 -8.48700464e-01 -2.50106335e-01
-7.41529644e-01 -7.71272257e-02 -8.21469367e-01 9.88420725e-01
3.75501007e-01 4.20777500e-01 9.72037494e-01 -1.22483981e+00
-5.33173263e-01 8.20259213e-01 -4.30760682e-01 6.58263505e-01
1.90806523e-01 -3.82312924e-01 9.31728125e-01 -5.61080933e-01
8.09600174e-01 1.06687582e+00 1.04477286e+00 5.84295809e-01
-8.97686481e-01 -3.07886004e-01 3.76430660e-01 3.50936115e-01
-9.41280842e-01 9.79466140e-02 9.93244827e-01 -7.64728069e-01
7.24840462e-01 4.86969411e-01 7.59550214e-01 1.40010393e+00
5.83600640e-01 9.55784023e-01 9.84649718e-01 -1.45489827e-01
1.18297905e-01 -1.29834816e-01 6.72669947e-01 4.80149060e-01
-4.87124085e-01 -2.45904494e-02 -3.82082283e-01 -4.19480771e-01
2.84669399e-01 5.34241319e-01 -1.12984486e-01 5.42013705e-01
-1.02988768e+00 1.23781538e+00 2.89076984e-01 4.43848222e-01
-5.60548127e-01 -6.84315637e-02 8.47354352e-01 7.50178635e-01
1.05919623e+00 1.79773450e-01 -2.19959766e-01 -1.67732388e-01
-9.80331659e-01 1.90834984e-01 1.06484056e+00 3.85623068e-01
5.87223947e-01 1.68988064e-01 -1.95994273e-01 6.70218050e-01
1.35304764e-01 9.36303362e-02 1.18075657e+00 -5.14654636e-01
1.22220919e-01 6.04941607e-01 1.50536811e-02 -1.42232120e+00
-8.60826969e-01 -4.97557044e-01 -1.24453437e+00 -2.35927209e-01
2.02641815e-01 -5.04082978e-01 -7.50230253e-01 1.46438909e+00
2.44590431e-01 2.26578847e-01 6.66043907e-02 5.13205886e-01
8.47160935e-01 1.32586086e+00 -3.39149535e-01 -8.49407673e-01
1.02053070e+00 -8.21190238e-01 -9.50102925e-01 3.80307853e-01
8.07877004e-01 -3.28851193e-01 4.05335277e-01 9.19379294e-03
-9.48791265e-01 -1.56058386e-01 -7.57517338e-01 -2.13461332e-02
-7.31870174e-01 -3.78677130e-01 9.35881734e-02 8.32314268e-02
-8.90862763e-01 9.70564485e-01 -8.08927417e-01 4.10646647e-02
-1.86227530e-01 1.23029597e-01 3.76571774e-01 6.86973929e-01
-1.73345184e+00 6.25873148e-01 1.49665758e-01 6.28187478e-01
-6.87214911e-01 -2.84615517e-01 -5.84116220e-01 -2.22519428e-01
-2.42143571e-02 -1.99212283e-01 1.52642429e+00 -1.30530834e+00
-1.60852838e+00 6.49566352e-01 -3.69759053e-01 -6.50295496e-01
8.44469666e-01 4.30187404e-01 -5.92256129e-01 -1.13145880e-01
-6.70438781e-02 -2.10943356e-01 8.87706757e-01 -7.43600309e-01
-4.20076162e-01 -1.65076092e-01 -2.60504484e-01 1.51359633e-01
-3.52023363e-01 1.55445650e-01 2.82480180e-01 -8.01824212e-01
1.78297862e-01 -1.17926252e+00 -3.74893993e-01 -5.46707392e-01
-5.51191926e-01 -5.76498091e-01 1.13537085e+00 -9.10916388e-01
1.63345516e+00 -1.88945818e+00 2.90862501e-01 5.25834411e-02
4.53684717e-01 1.26247138e-01 2.69328535e-01 7.18851447e-01
8.07485729e-03 3.01734060e-01 -3.35010827e-01 -2.59893686e-01
-2.13003114e-01 2.48107418e-01 -5.22893488e-01 7.00556636e-01
-3.77760530e-01 8.34811747e-01 -1.01201439e+00 -2.31179997e-01
-4.59895909e-01 5.68883657e-01 -1.14829235e-01 1.23168223e-01
-4.00253862e-01 3.13694298e-01 -4.95572716e-01 8.05557966e-02
2.69413680e-01 -4.99349266e-01 1.88995019e-01 3.19414258e-01
-5.77720284e-01 4.80661660e-01 -7.33451962e-01 5.37805915e-01
-3.91552150e-01 1.16045809e+00 -1.87779531e-01 -1.08791459e+00
9.13663805e-01 5.61908364e-01 6.16309524e-01 -3.72171015e-01
5.15598595e-01 9.05018151e-02 -1.03131384e-01 -4.69508529e-01
9.03630197e-01 -1.50799632e-01 -2.48617735e-02 1.16498685e+00
-5.78342855e-01 7.41776168e-01 1.80956423e-01 1.20742656e-01
9.56762135e-01 -3.05397838e-01 1.59496456e-01 1.13499731e-01
4.34982866e-01 -3.95949125e-01 6.72006190e-01 6.97694123e-01
-7.99036697e-02 6.37533605e-01 9.17563856e-01 -5.96261680e-01
-1.09833109e+00 -2.73208261e-01 3.89738381e-02 1.30074358e+00
-8.98233950e-02 -2.74223089e-01 -5.42852342e-01 -4.37383384e-01
-1.96675673e-01 3.84604722e-01 -9.91741002e-01 -5.73437959e-02
-8.75691950e-01 -1.18833184e+00 5.65846562e-01 4.06629592e-01
3.57492417e-01 -1.43541098e+00 -5.10242879e-01 5.92773020e-01
-4.93868083e-01 -6.92087412e-01 -5.29662609e-01 2.14495838e-01
-7.93777406e-01 -7.36965656e-01 -1.07558751e+00 -9.20403481e-01
5.59764206e-01 -1.50645860e-02 5.30750394e-01 1.33015886e-01
1.22846134e-01 -1.30667137e-02 -4.25056100e-01 -2.25311562e-01
-7.64910221e-01 4.00645465e-01 3.09642237e-02 4.93098795e-01
5.02994545e-02 -5.76093376e-01 -3.72528732e-01 3.76070768e-01
-9.65660274e-01 7.72754773e-02 -1.72589839e-01 8.39644670e-01
2.13651523e-01 4.50154766e-02 6.43995464e-01 -1.24101937e+00
1.22916460e+00 -1.11621463e+00 -2.32087672e-01 9.63857099e-02
-6.83349073e-01 6.62539676e-02 7.38275945e-01 -7.72067308e-01
-7.96669185e-01 -4.32273060e-01 -1.47803754e-01 -1.30221784e-01
3.90781164e-01 1.07731700e+00 8.69383454e-01 3.93937141e-01
5.07515132e-01 6.24121428e-01 2.15666354e-01 -5.95041752e-01
-1.48497313e-01 1.07450676e+00 -4.25621355e-03 5.00531010e-02
1.62350953e-01 4.24290985e-01 -1.56669155e-01 -1.05585957e+00
-6.07301056e-01 -6.16925478e-01 -3.92980248e-01 -4.70635861e-01
7.73049414e-01 -4.66893047e-01 -1.17556000e+00 1.02087200e+00
-1.29709828e+00 -3.56521517e-01 4.79806997e-02 3.20358127e-01
-4.45508569e-01 4.41291273e-01 -1.47954798e+00 -1.14071059e+00
-5.67901373e-01 -7.42971182e-01 1.93167850e-01 -4.17968966e-02
-2.94701159e-01 -1.35253692e+00 3.13079864e-01 -2.99617916e-01
4.73283172e-01 4.92746085e-01 9.11303163e-01 -7.52402902e-01
9.40989405e-02 -2.93624431e-01 2.86773648e-02 1.94589481e-01
-8.78184959e-02 2.90103108e-01 -6.69319868e-01 -1.10087022e-01
4.01286840e-01 9.23807919e-02 9.72632110e-01 5.58594644e-01
9.56536770e-01 -8.44752192e-01 -2.79724002e-01 3.65482390e-01
9.29606080e-01 2.38367036e-01 4.48044628e-01 4.41404134e-01
6.30793393e-01 7.86924303e-01 1.67115182e-01 6.14466727e-01
4.38185185e-01 1.73001707e-01 4.04920131e-01 1.10035270e-01
5.98271728e-01 -1.56173781e-01 6.72880948e-01 1.61689174e+00
-2.67526805e-01 -4.54261154e-01 -8.53325665e-01 4.56207573e-01
-2.18720222e+00 -1.29899228e+00 -6.08607352e-01 1.81881964e+00
8.14882874e-01 1.56216040e-01 5.17207861e-01 5.06844401e-01
1.21359646e+00 4.75556105e-01 -5.90159118e-01 -7.99979150e-01
-2.33918190e-01 -4.56559807e-01 5.64823091e-01 6.56338930e-01
-7.76505232e-01 3.30263644e-01 6.46805859e+00 2.55492538e-01
-1.46886718e+00 1.44930303e-01 6.18217707e-01 1.10613443e-01
-2.53953338e-01 -2.76057124e-01 -8.03398728e-01 9.66079116e-01
1.35936952e+00 -3.00427079e-01 3.87166649e-01 4.30863976e-01
4.08177614e-01 4.01218474e-01 -6.34505630e-01 6.63672864e-01
4.94519807e-02 -1.49609995e+00 -1.76507965e-01 8.11694339e-02
7.90070057e-01 3.17450345e-01 6.51393086e-02 2.27925345e-01
1.81546047e-01 -7.32880950e-01 5.90523779e-01 7.82904744e-01
3.55721205e-01 -6.94170058e-01 7.81121254e-01 7.89347589e-01
-1.06234372e+00 -1.40445009e-01 -1.11788355e-01 -4.73831981e-01
3.68635625e-01 5.20100176e-01 -1.02254510e+00 2.02718541e-01
4.15527433e-01 1.22418404e+00 -8.95855129e-02 6.46936834e-01
6.61377087e-02 8.86365116e-01 -1.78464711e-01 -7.86075771e-01
4.19018865e-01 -1.33323058e-01 8.15271735e-01 1.26367581e+00
2.19175771e-01 -2.19282974e-02 8.75636637e-02 4.43118244e-01
-1.92647338e-01 1.29574686e-02 -4.48340029e-01 -5.06198168e-01
8.42853263e-02 8.06864202e-01 -9.61933672e-01 -2.06963643e-01
1.16446698e-02 9.62370336e-01 9.72424969e-02 6.55741692e-01
-6.86955333e-01 -5.54558277e-01 3.95881504e-01 2.14394271e-01
6.20291084e-02 -2.99912840e-01 7.35691413e-02 -1.17844152e+00
-1.02423817e-01 -4.75544393e-01 4.34838593e-01 -5.31350911e-01
-1.35299563e+00 1.01938212e+00 -4.08092350e-01 -1.22626054e+00
-5.71867049e-01 -4.71502781e-01 -6.11125052e-01 6.98046625e-01
-1.60914719e+00 -6.72218382e-01 2.30262637e-01 7.00540543e-01
4.85505402e-01 3.24945003e-02 6.08429432e-01 1.45867869e-01
-5.96995890e-01 3.24289382e-01 5.69519579e-01 4.80585933e-01
-1.82229504e-02 -9.62715685e-01 4.07268941e-01 3.07418823e-01
-4.20051277e-01 5.01037121e-01 9.88639474e-01 -7.86535025e-01
-9.22040820e-01 -1.01086748e+00 1.40729725e+00 -1.04909457e-01
9.40426886e-01 -2.44965196e-01 -1.02011561e+00 8.79969537e-01
-6.32768497e-03 -3.50544453e-01 6.18915796e-01 -2.13136971e-02
-7.70113245e-02 4.35395509e-01 -7.90691614e-01 5.62071919e-01
6.81454420e-01 -8.48272324e-01 -4.52945232e-01 4.65559214e-01
8.10429394e-01 -2.23059222e-01 -5.06634176e-01 1.24662571e-01
4.93189275e-01 -5.11251986e-01 3.90122712e-01 -8.40721190e-01
6.72971904e-01 3.49559486e-02 1.45425767e-01 -1.21705270e+00
-3.14232945e-01 -1.04466701e+00 -4.29384887e-01 7.76249349e-01
5.12004316e-01 -1.04431450e+00 7.37381577e-01 1.28634358e-02
2.29575902e-01 -8.97790194e-01 -7.44474709e-01 -4.25288975e-01
-1.00495540e-01 -2.94443518e-01 2.94611454e-01 1.22470939e+00
2.43684351e-01 4.70501542e-01 -8.68875921e-01 -1.38410136e-01
1.46733224e-01 1.18107922e-01 -1.77179300e-03 -1.61568475e+00
-3.02155521e-02 -5.40736496e-01 -4.14005786e-01 -1.09762883e+00
4.67445403e-01 -9.88466203e-01 2.90995147e-02 -1.39209235e+00
5.01195639e-02 -3.62596124e-01 -3.25045645e-01 2.92703528e-02
3.30306679e-01 1.36244744e-02 -9.90168229e-02 7.38183677e-01
-3.62346292e-01 5.57413042e-01 9.79402006e-01 -1.96951896e-01
-4.43879038e-01 5.67235708e-01 -1.20732926e-01 6.89581871e-01
8.32320452e-01 -7.86837995e-01 -1.06726654e-01 3.82667258e-02
9.76242959e-01 3.88654709e-01 1.63452793e-02 -3.62828463e-01
4.68810737e-01 -1.22150198e-01 -7.48942494e-02 -9.86407042e-01
3.96557570e-01 -3.63495857e-01 -3.51128466e-02 6.14957511e-01
-9.79721665e-01 5.35954177e-01 -4.09812450e-01 9.35017884e-01
-3.27461869e-01 -3.90812665e-01 4.71189767e-01 -3.30846608e-01
-6.23156652e-02 4.23278958e-01 -1.25094295e+00 -3.70699167e-02
7.46421456e-01 -5.34670353e-02 -7.79380202e-02 -8.68930101e-01
-1.12748909e+00 1.77573711e-01 1.59475894e-03 3.35619509e-01
5.60419738e-01 -1.17278802e+00 -7.28892446e-01 -2.71459091e-02
-3.26715976e-01 -3.99242640e-01 2.74780840e-01 9.17214274e-01
-5.10226429e-01 2.20380902e-01 8.00572485e-02 -3.44616175e-01
-1.34692323e+00 4.96758491e-01 5.50885797e-01 -4.52906281e-01
-6.43146396e-01 6.08666062e-01 -2.56986320e-01 -6.71784818e-01
2.66792715e-01 -1.26902193e-01 -7.83556283e-01 8.20139647e-01
7.21625507e-01 7.39456594e-01 -4.64152992e-02 -1.02394414e+00
1.72729209e-01 9.03806910e-02 -3.40468764e-01 -2.04643041e-01
1.43190956e+00 -2.76283175e-01 -5.40882885e-01 1.45005322e+00
1.75263762e+00 -4.58910376e-01 -7.60616958e-01 -4.25955743e-01
6.86862171e-02 3.49767089e-01 1.02884732e-01 -1.29040584e-01
-8.30806613e-01 8.07969749e-01 2.02216506e-01 1.03677022e+00
5.45344889e-01 -4.21474934e-01 1.18911469e+00 2.87132829e-01
-3.04940253e-01 -1.29579687e+00 -4.46666256e-02 1.24172318e+00
5.97333431e-01 -6.63763821e-01 -3.49562734e-01 1.52942583e-01
-5.08037031e-01 1.41326845e+00 -2.98176724e-02 -1.56286787e-02
1.10733593e+00 7.53258169e-02 1.01194819e-02 -1.31458387e-01
-9.63011742e-01 2.02794045e-01 -1.16929322e-01 -5.94613478e-02
6.25067413e-01 3.82220410e-02 -6.59986913e-01 2.35268205e-01
-1.80803433e-01 -1.84590723e-02 9.94621575e-01 1.20717490e+00
-2.78258681e-01 -5.61029494e-01 -1.69342130e-01 5.70510387e-01
-7.95711279e-01 -6.47824630e-02 -3.63252282e-01 4.01948318e-02
-5.04450679e-01 7.73430586e-01 2.69195437e-01 -5.78323066e-01
-2.25710556e-01 2.23244697e-01 -3.27796012e-01 -3.30747187e-01
-8.06424558e-01 -2.22026587e-01 8.61983299e-02 1.13092564e-01
-4.36831564e-01 -8.87888074e-01 -1.43244326e+00 -6.64383769e-01
-3.45567673e-01 5.50737023e-01 9.33160484e-01 1.07703698e+00
2.19596252e-01 6.25774801e-01 1.16104937e+00 -8.98443401e-01
-6.34152830e-01 -1.03493774e+00 -5.79022706e-01 2.57051855e-01
1.07688320e+00 -2.28319913e-01 -8.26197147e-01 -5.59672043e-02] | [7.127151966094971, 3.4479501247406006] |
6a0861f0-fda8-4381-804f-65a4ee6c82f5 | toward-a-corpus-of-cantonese-verbal-comments | null | null | https://aclanthology.org/Y15-2002 | https://aclanthology.org/Y15-2002.pdf | Toward a Corpus of Cantonese Verbal Comments and their Classification by Multi-dimensional Analysis | null | ['Oi Yee Kwong'] | 2015-10-01 | toward-a-corpus-of-cantonese-verbal-comments-1 | https://aclanthology.org/Y15-2002 | https://aclanthology.org/Y15-2002.pdf | paclic-2015-10 | ['subjectivity-analysis'] | ['natural-language-processing'] | [-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] | [-7.482332706451416, 3.583852767944336] |
721e33c7-6def-4f81-9439-6e8616e4ee25 | structure-sensitive-graph-dictionary | 2306.10505 | null | https://arxiv.org/abs/2306.10505v1 | https://arxiv.org/pdf/2306.10505v1.pdf | Structure-Sensitive Graph Dictionary Embedding for Graph Classification | Graph structure expression plays a vital role in distinguishing various graphs. In this work, we propose a Structure-Sensitive Graph Dictionary Embedding (SS-GDE) framework to transform input graphs into the embedding space of a graph dictionary for the graph classification task. Instead of a plain use of a base graph dictionary, we propose the variational graph dictionary adaptation (VGDA) to generate a personalized dictionary (named adapted graph dictionary) for catering to each input graph. In particular, for the adaptation, the Bernoulli sampling is introduced to adjust substructures of base graph keys according to each input, which increases the expression capacity of the base dictionary tremendously. To make cross-graph measurement sensitive as well as stable, multi-sensitivity Wasserstein encoding is proposed to produce the embeddings by designing multi-scale attention on optimal transport. To optimize the framework, we introduce mutual information as the objective, which further deduces to variational inference of the adapted graph dictionary. We perform our SS-GDE on multiple datasets of graph classification, and the experimental results demonstrate the effectiveness and superiority over the state-of-the-art methods. | ['Zhen Cui', 'Chuanwei Zhou', 'Wenting Zhao', 'Xudong Wang', 'Tong Zhang', 'Guangbu Liu'] | 2023-06-18 | null | null | null | null | ['graph-classification', 'classification-1'] | ['graphs', 'methodology'] | [-1.35334674e-02 -4.25418280e-02 -6.61087334e-02 -2.82679170e-01
-3.37919176e-01 -4.80714470e-01 4.03222978e-01 1.36844724e-01
-2.07324088e-01 3.30938697e-01 2.52487510e-01 -2.69974113e-01
-2.54029989e-01 -1.06079412e+00 -4.71529335e-01 -1.01669347e+00
1.45606786e-01 2.12814718e-01 1.02338240e-01 -3.28522742e-01
4.67947721e-02 3.03980052e-01 -8.22148263e-01 -2.83131063e-01
9.17901158e-01 8.12001050e-01 3.63530189e-01 3.12732339e-01
-2.02687070e-01 3.46219033e-01 -2.63100117e-01 -5.32829762e-01
1.60502374e-01 -6.75665259e-01 -3.18587542e-01 1.98861286e-01
1.16747908e-01 -1.30582184e-01 -7.92323709e-01 1.47120237e+00
5.80402017e-01 3.24479103e-01 8.35071266e-01 -1.32722485e+00
-1.43780315e+00 7.77389824e-01 -4.21731710e-01 3.51228356e-01
1.38889208e-01 2.25275218e-01 1.54604399e+00 -6.19531155e-01
4.92405444e-01 1.32225323e+00 3.58782053e-01 5.08660018e-01
-1.20734727e+00 -5.51853955e-01 4.56488967e-01 2.13712156e-01
-1.62288809e+00 -1.90960795e-01 1.28076136e+00 -4.31378156e-01
5.09897768e-01 2.52012849e-01 8.48750770e-01 1.02343452e+00
2.05771551e-01 6.34006917e-01 6.55696690e-01 -1.73525989e-01
2.92920228e-02 3.77439186e-02 8.63714665e-02 1.21716177e+00
2.91976929e-01 -1.25281215e-01 -2.23148353e-02 -4.21008542e-02
8.12306881e-01 1.51472881e-01 -4.23682153e-01 -5.94237328e-01
-1.26051843e+00 1.07783723e+00 7.62860715e-01 3.20187628e-01
-3.13861638e-01 2.48228282e-01 4.52294677e-01 3.30550909e-01
3.52439553e-01 2.52583295e-01 -7.45926127e-02 3.02758962e-01
-2.37426728e-01 -6.16469719e-02 4.11837548e-01 1.09581685e+00
9.24403727e-01 1.39740497e-01 -5.35118163e-01 7.74344385e-01
7.16584861e-01 4.12648290e-01 4.83547539e-01 -3.55800450e-01
4.73321021e-01 9.66571510e-01 -4.43172246e-01 -1.55261219e+00
-1.91839129e-01 -6.20827317e-01 -1.08147931e+00 -4.83536810e-01
4.63671237e-02 2.16356754e-01 -8.56347799e-01 1.92940068e+00
5.53045809e-01 3.67205322e-01 -1.03121020e-01 9.53398526e-01
8.75487864e-01 6.71035171e-01 -9.40841287e-02 -3.38324428e-01
1.28366232e+00 -8.33845675e-01 -7.43238449e-01 3.74849960e-02
7.26234257e-01 -1.97976813e-01 1.31168187e+00 4.22866270e-03
-4.36050981e-01 -4.57220554e-01 -1.08421099e+00 -1.43874094e-01
-1.89168409e-01 -2.78858215e-01 6.00577593e-01 4.55771178e-01
-7.29987621e-01 3.41722727e-01 -6.29883111e-01 -2.35598981e-01
4.19136077e-01 2.65930712e-01 -3.98625612e-01 -1.82693720e-01
-1.34405589e+00 3.73419136e-01 5.24278700e-01 1.96305871e-01
-8.29436362e-01 -3.82469743e-01 -1.16293442e+00 1.47619247e-02
3.55044007e-01 -7.57370830e-01 3.09534460e-01 -7.11597860e-01
-1.46606255e+00 7.18848526e-01 8.46276358e-02 -1.06364310e-01
2.22816601e-01 6.84685111e-01 -4.67180341e-01 1.26475334e-01
1.89440265e-01 2.22844392e-01 9.76472318e-01 -1.03690827e+00
-1.92263380e-01 -3.85540158e-01 2.79595256e-01 2.90722132e-01
-5.74692190e-01 -4.92248863e-01 -6.96773052e-01 -9.14544821e-01
2.34817460e-01 -8.06383550e-01 -1.43004939e-01 -1.71767250e-01
-6.08101070e-01 -3.20679396e-01 4.72422093e-01 -6.68041110e-01
1.70757663e+00 -2.41698742e+00 8.16642225e-01 4.23387498e-01
6.38507545e-01 -6.24970235e-02 -3.78564179e-01 4.58293825e-01
5.60752749e-02 2.36127228e-01 -5.40110767e-01 -2.92515665e-01
2.96043247e-01 5.49045086e-01 -8.82584825e-02 6.40564919e-01
1.36942431e-01 1.01301336e+00 -1.13368773e+00 -5.54338157e-01
1.38221964e-01 4.78957593e-01 -7.04626977e-01 3.00328583e-01
-1.64842770e-01 6.17961228e-01 -9.01974201e-01 3.88856828e-01
7.11119115e-01 -4.25321192e-01 2.25900546e-01 -5.01422286e-01
3.30047101e-01 -4.59482484e-02 -1.12744260e+00 1.91052949e+00
-2.46487647e-01 -3.98547798e-02 -1.17311627e-01 -1.28015673e+00
1.06117558e+00 -2.11370081e-01 3.48405421e-01 -6.21887565e-01
2.72584349e-01 1.08143695e-01 1.17603496e-01 -3.94715577e-01
1.72624230e-01 -1.19061861e-02 -2.53540277e-01 2.66372144e-01
1.94678918e-01 7.01095760e-02 1.49456993e-01 5.22686660e-01
1.01478434e+00 -1.91976339e-01 2.41577476e-01 -4.88190889e-01
9.41375792e-01 -5.42924225e-01 6.59085035e-01 2.85668015e-01
-3.10387909e-01 4.57667053e-01 6.45787895e-01 -2.81126648e-01
-8.08071196e-01 -9.82466578e-01 5.75426668e-02 9.38435853e-01
5.80935478e-01 -5.80219507e-01 -7.45818198e-01 -1.01932502e+00
1.73318863e-01 4.32735085e-01 -7.98827231e-01 -6.73313022e-01
-3.23374510e-01 -8.91058564e-01 2.17182875e-01 2.20596567e-01
5.79150736e-01 -7.63946831e-01 4.45011079e-01 1.93181023e-01
-2.92236195e-03 -9.28359628e-01 -1.17438495e+00 -1.33123651e-01
-4.82074082e-01 -9.19542730e-01 -4.64472800e-01 -1.03643835e+00
8.98911357e-01 3.10216308e-01 5.88469386e-01 4.16279882e-01
4.71628308e-02 4.34534132e-01 -5.70988119e-01 2.79909045e-01
-3.05957317e-01 2.82299876e-01 4.12117429e-02 5.39494038e-01
1.40330955e-01 -8.29443336e-01 -7.09239483e-01 1.72517672e-01
-1.01032174e+00 -3.47189158e-02 5.14172494e-01 1.04317772e+00
9.41874146e-01 4.60361391e-02 4.42649424e-01 -9.77089643e-01
9.38356221e-01 -7.40673006e-01 -5.49405515e-01 2.21293077e-01
-8.81908476e-01 3.67017388e-01 9.00305092e-01 -4.26476985e-01
-3.79030287e-01 -2.71681488e-01 -1.17085494e-01 -6.29906833e-01
4.76281494e-01 7.73779929e-01 -6.40622139e-01 -2.50736952e-01
2.60680974e-01 6.14719331e-01 2.24924944e-02 -2.81300038e-01
7.35847533e-01 3.77964824e-01 2.36934945e-01 -5.11781633e-01
9.36086655e-01 2.23551482e-01 1.21317618e-01 -6.70134306e-01
-6.20253026e-01 -1.94736689e-01 -4.63625282e-01 -2.48299073e-02
9.82774377e-01 -6.51970863e-01 -5.38610697e-01 3.76632422e-01
-8.86543751e-01 -2.09839538e-01 -8.53627399e-02 2.71057695e-01
-2.91971415e-01 6.83478415e-01 -5.22294283e-01 -4.75554317e-01
-2.21982837e-01 -1.39920831e+00 1.13620162e+00 2.12185029e-02
4.49754417e-01 -1.41651547e+00 1.64745793e-01 -1.70999970e-02
7.74812624e-02 3.84763300e-01 1.07870829e+00 -6.00558102e-01
-7.27724791e-01 1.67860519e-02 -3.64122570e-01 4.35327828e-01
3.29556227e-01 -1.77780569e-01 -4.74767506e-01 -5.90796530e-01
-1.81339875e-01 6.13591187e-02 8.05025280e-01 5.05772643e-02
1.24102795e+00 -4.61232066e-01 -3.20814878e-01 1.12787914e+00
1.54785550e+00 2.69930959e-02 4.21982378e-01 9.58269313e-02
1.49799073e+00 9.35839266e-02 3.68292660e-01 2.91079104e-01
7.56036401e-01 5.51936328e-01 4.49556589e-01 2.29970247e-01
-2.80044489e-02 -7.34755635e-01 3.06893468e-01 1.54491591e+00
2.01893136e-01 -4.81744915e-01 -4.86252785e-01 4.76338089e-01
-1.70266008e+00 -6.48150563e-01 -7.08082020e-02 1.94905400e+00
5.36862075e-01 -4.42024134e-03 -3.05454265e-02 -9.90748778e-02
8.94124687e-01 7.06402540e-01 -6.82332158e-01 -1.76169805e-03
-4.11349609e-02 -6.61079288e-02 4.14637953e-01 8.09702516e-01
-8.82961333e-01 1.00714898e+00 4.88961601e+00 1.20402908e+00
-1.11088634e+00 2.65114367e-01 2.50460327e-01 5.04682660e-01
-9.74646628e-01 1.59118429e-01 -3.97166491e-01 8.60377908e-01
3.75490010e-01 -3.70557845e-01 9.88106132e-01 6.52753651e-01
-1.24227025e-01 6.59002483e-01 -7.73518503e-01 1.14780891e+00
2.98984498e-02 -1.04793429e+00 4.75465149e-01 1.90858722e-01
5.57671487e-01 -2.09423408e-01 -6.99010585e-03 3.79017472e-01
1.97520703e-01 -6.84936106e-01 5.16074121e-01 5.55274010e-01
8.70891690e-01 -7.15740442e-01 4.53618556e-01 1.29344150e-01
-1.70058668e+00 8.97448659e-02 -6.64629638e-01 3.56836021e-01
2.53425185e-02 5.25019705e-01 -3.70777398e-01 8.71552706e-01
2.15563715e-01 1.15580523e+00 -5.55610359e-01 5.10101020e-01
-4.74279612e-01 5.20750582e-01 -3.78799103e-02 -2.29467601e-01
2.61019617e-01 -8.34736347e-01 8.67979467e-01 8.61070037e-01
2.17949957e-01 1.64061069e-01 4.45883274e-01 9.12308931e-01
-4.63533938e-01 3.40594530e-01 -6.38556302e-01 -3.76988173e-01
6.95673287e-01 1.36820197e+00 -5.64678788e-01 -1.56093508e-01
-2.14126110e-01 1.42805684e+00 6.57559693e-01 3.95853162e-01
-9.70244646e-01 -6.01363957e-01 6.86181545e-01 -2.29545325e-01
5.32564640e-01 -2.77400523e-01 2.77985215e-01 -1.49134433e+00
6.64613992e-02 -7.98952639e-01 5.45016825e-01 -3.96435320e-01
-1.63012302e+00 5.62021792e-01 -1.54195815e-01 -1.14609754e+00
3.55475426e-01 -4.77170914e-01 -6.40807033e-01 8.41727376e-01
-1.48475718e+00 -1.43110371e+00 -4.68782246e-01 8.38383496e-01
-8.64623673e-03 -2.57961750e-01 6.31234109e-01 5.51782906e-01
-8.27034354e-01 9.37103748e-01 1.78492785e-01 2.96205312e-01
3.64551306e-01 -1.31827068e+00 5.21250010e-01 8.71623218e-01
2.51721293e-01 8.12351108e-01 4.04859394e-01 -5.43974936e-01
-1.93592501e+00 -1.42156351e+00 3.11698228e-01 -3.05591404e-01
1.03378129e+00 -6.49436831e-01 -1.04118955e+00 7.81759501e-01
-1.79667398e-01 3.00853163e-01 6.56028569e-01 -1.34900525e-01
-5.36647201e-01 -3.97682637e-01 -1.08255708e+00 5.88842213e-01
1.57447326e+00 -9.28978145e-01 -3.74498963e-01 4.13940281e-01
1.22659409e+00 -4.05470580e-01 -1.16615176e+00 1.84706271e-01
3.27096730e-01 -5.25829732e-01 7.33261943e-01 -6.71749890e-01
1.07842438e-01 -5.54182887e-01 -3.24569345e-01 -1.53818476e+00
-7.31733620e-01 -7.31485844e-01 -1.69045538e-01 1.44147646e+00
2.35808685e-01 -1.10385942e+00 4.16458070e-01 1.57978423e-02
-2.38882348e-01 -9.02996898e-01 -8.27521980e-01 -5.89853585e-01
-9.16655064e-02 -2.10851640e-01 1.03692997e+00 1.28755260e+00
-2.85783201e-01 6.24806523e-01 -2.46203765e-01 4.72391963e-01
6.86702907e-01 2.23530278e-01 8.56021523e-01 -9.95523751e-01
-4.89774674e-01 -6.01633906e-01 -9.62510705e-01 -1.25301981e+00
3.74621987e-01 -1.54656518e+00 -2.87167788e-01 -1.56989121e+00
8.13147798e-02 -4.67478991e-01 -7.09707975e-01 1.43267334e-01
-5.92125833e-01 1.01269791e-02 -5.47883809e-02 1.38467014e-01
-6.30639136e-01 1.05425656e+00 1.64820313e+00 -4.28189814e-01
-3.83746885e-02 -3.35495144e-01 -1.15040874e+00 8.68563727e-02
3.95200521e-01 -3.93566102e-01 -8.07570994e-01 -5.05222380e-01
1.94018155e-01 -1.66151971e-01 1.99430734e-01 -5.63086033e-01
-6.98626786e-02 -7.64736012e-02 -1.23894483e-01 -1.34234885e-02
-6.42697811e-02 -6.67243242e-01 1.71989709e-01 4.07323420e-01
-2.56883442e-01 3.30492593e-02 -2.86199778e-01 1.14910185e+00
-6.32641464e-02 -5.98344803e-02 7.95220971e-01 1.22276857e-01
-7.45822728e-01 1.11431158e+00 3.66107404e-01 3.00159693e-01
8.43719661e-01 7.38208927e-03 -8.16768482e-02 -9.92802158e-02
-7.02480912e-01 4.42279637e-01 6.30527556e-01 3.72411340e-01
6.42418325e-01 -1.88428116e+00 -5.79856515e-01 3.96529615e-01
4.79348272e-01 2.32352316e-02 3.10951710e-01 7.23475337e-01
-3.58211517e-01 -1.59800738e-01 5.71586974e-02 -4.83896643e-01
-7.13988602e-01 7.20815063e-01 4.07071710e-01 -2.28655890e-01
-7.62392044e-01 9.48201656e-01 4.41868484e-01 -5.07574856e-01
-8.20938945e-02 -5.03983855e-01 -2.22748995e-01 -2.46909428e-02
1.61065757e-01 1.04060406e-02 -2.39138007e-01 -6.93620384e-01
-3.45997095e-01 6.85695887e-01 2.87600700e-02 2.28196710e-01
1.08942640e+00 -2.74224967e-01 -3.91009241e-01 4.08907980e-01
1.56510448e+00 1.51648089e-01 -1.10994220e+00 -3.24886590e-01
-4.30799931e-01 -5.37362456e-01 2.29819000e-01 -8.46941248e-02
-1.36139894e+00 7.31207132e-01 4.05754358e-01 5.00610650e-01
1.02192187e+00 -1.31912483e-02 9.85459328e-01 1.44118845e-01
4.12788987e-01 -5.54759562e-01 3.20208445e-02 2.54030466e-01
8.90366912e-01 -1.16969526e+00 -1.23713046e-01 -3.76328290e-01
-6.55321300e-01 8.39039624e-01 4.18219537e-01 -4.75639999e-01
7.81631589e-01 -5.07667124e-01 -3.88843089e-01 -4.91327703e-01
-2.39417270e-01 -3.57982069e-01 4.54136968e-01 6.33138835e-01
8.69773142e-03 3.11041296e-01 -4.62627828e-01 7.22844243e-01
-1.30661335e-02 -5.49628615e-01 1.41506717e-01 3.46722007e-01
-2.37872243e-01 -1.11686337e+00 3.25105995e-01 5.28887093e-01
3.22085954e-02 -2.16273829e-01 -3.81876051e-01 6.38993263e-01
6.54960647e-02 6.60707176e-01 -1.35386363e-01 -8.24691951e-01
2.97141224e-01 -3.91582936e-01 4.88350362e-01 -7.36126006e-01
-1.70217559e-01 -2.04329014e-01 -2.00669959e-01 -3.17457825e-01
-2.18344659e-01 -4.59754378e-01 -1.33644402e+00 -2.79366344e-01
-5.42752683e-01 3.71702433e-01 1.80234522e-01 8.77429903e-01
5.14032125e-01 7.01465964e-01 1.03890598e+00 -4.89360511e-01
-5.47877610e-01 -7.94638276e-01 -9.08669651e-01 6.63236618e-01
3.40501934e-01 -8.21949661e-01 -6.29048228e-01 -3.33096504e-01] | [7.280083179473877, 6.296138763427734] |
33c00c17-4816-4ec8-b14d-6a912123348c | orca-a-few-shot-benchmark-for-chinese | 2302.13619 | null | https://arxiv.org/abs/2302.13619v1 | https://arxiv.org/pdf/2302.13619v1.pdf | Orca: A Few-shot Benchmark for Chinese Conversational Machine Reading Comprehension | The conversational machine reading comprehension (CMRC) task aims to answer questions in conversations, which has been a hot research topic in recent years because of its wide applications. However, existing CMRC benchmarks in which each conversation is assigned a static passage are inconsistent with real scenarios. Thus, model's comprehension ability towards real scenarios are hard to evaluate reasonably. To this end, we propose the first Chinese CMRC benchmark Orca and further provide zero-shot/few-shot settings to evaluate model's generalization ability towards diverse domains. We collect 831 hot-topic driven conversations with 4,742 turns in total. Each turn of a conversation is assigned with a response-related passage, aiming to evaluate model's comprehension ability more reasonably. The topics of conversations are collected from social media platform and cover 33 domains, trying to be consistent with real scenarios. Importantly, answers in Orca are all well-annotated natural responses rather than the specific spans or short phrase in previous datasets. Besides, we implement three strong baselines to tackle the challenge in Orca. The results indicate the great challenge of our CMRC benchmark. Our datatset and checkpoints are available at https://github.com/nuochenpku/Orca. | ['Jia Li', 'Baoyuan Wang', 'Jiaxing Zhang', 'Ruyi Gan', 'Jianfeng Liu', 'Qi Yang', 'Xinshi Lin', 'Junqing He', 'Yinan Bao', 'Hongguang Li', 'Nuo Chen'] | 2023-02-27 | null | null | null | null | ['reading-comprehension', 'machine-reading-comprehension'] | ['natural-language-processing', 'natural-language-processing'] | [ 2.39323854e-01 1.14955544e-01 7.37384260e-02 -5.50812840e-01
-1.16339636e+00 -5.62136114e-01 8.48587632e-01 1.16190389e-01
-2.97913820e-01 7.90729761e-01 7.59910524e-01 -2.52640158e-01
1.39757991e-01 -5.89183807e-01 -5.03890812e-01 -3.78234357e-01
3.19414139e-01 6.66941285e-01 3.15191329e-01 -6.71426475e-01
3.53620559e-01 -6.26322329e-01 -1.38291514e+00 7.93620348e-01
1.23458791e+00 7.21560717e-01 4.66241181e-01 9.59412992e-01
-2.84994364e-01 8.90875161e-01 -9.72210824e-01 -6.14667773e-01
-3.43344539e-01 -8.13222528e-01 -1.27975833e+00 -7.27209300e-02
2.45523870e-01 -2.95368135e-01 -2.03232810e-01 7.09555507e-01
6.67391002e-01 4.05953288e-01 5.27005672e-01 -1.22314775e+00
-7.54951477e-01 7.38728821e-01 -1.81577563e-01 3.16037059e-01
1.01127410e+00 4.25347835e-01 1.01266527e+00 -7.07154036e-01
5.12679279e-01 1.49814165e+00 2.41125688e-01 8.80964696e-01
-6.95024908e-01 -4.92764682e-01 4.54076111e-01 5.89007497e-01
-7.55241036e-01 -4.47804481e-01 6.24801517e-01 -2.23972097e-01
8.57707620e-01 4.38856483e-01 3.14046383e-01 1.85751867e+00
-4.35421355e-02 1.05919957e+00 9.13677812e-01 -2.62901455e-01
3.00936639e-01 7.14202821e-02 6.51759684e-01 -5.22518717e-02
-4.49990571e-01 -5.08305907e-01 -6.77901506e-01 3.53886299e-02
-1.69941276e-01 -1.25903443e-01 -7.46333182e-01 4.52409148e-01
-1.29533625e+00 7.79455841e-01 1.68424785e-01 7.79306889e-02
-3.13300312e-01 -3.19724321e-01 5.80685139e-01 6.17469788e-01
5.42041898e-01 3.94177556e-01 -5.61671317e-01 -8.07307780e-01
-7.22335279e-02 6.68934226e-01 1.20511675e+00 1.23952961e+00
3.79823029e-01 -6.18975580e-01 -7.02611148e-01 1.25605059e+00
-7.75071308e-02 6.14340901e-01 6.29345775e-01 -1.11641335e+00
1.11639512e+00 6.71204448e-01 2.06188604e-01 -9.91921782e-01
-2.57440418e-01 -2.19851762e-01 -1.04604292e+00 -7.97884941e-01
5.95011294e-01 -3.43415052e-01 -1.72282785e-01 1.77411008e+00
1.99868679e-01 1.06628843e-01 4.22530890e-01 8.38945508e-01
1.40711069e+00 1.05067158e+00 -2.70981360e-02 -2.33233720e-01
1.63909876e+00 -1.26288652e+00 -8.70438695e-01 -2.93891221e-01
5.06273031e-01 -7.13593900e-01 1.86564481e+00 2.95165598e-01
-9.35730219e-01 -4.96710390e-01 -5.27506709e-01 -2.03687459e-01
-1.61679506e-01 -3.25725615e-01 9.68981087e-02 2.36446872e-01
-7.41588116e-01 -1.27516732e-01 -2.54435509e-01 -4.43638265e-01
-4.38626260e-02 -5.84216237e-01 1.19421473e-02 -4.12949383e-01
-1.71620989e+00 7.67231762e-01 2.73971446e-02 1.04179785e-01
-8.66344571e-01 -7.25283027e-01 -6.01305962e-01 7.62408227e-02
5.87526619e-01 -3.78660321e-01 2.06383801e+00 -6.59152389e-01
-1.72698593e+00 7.78411269e-01 -5.12028575e-01 -3.93325269e-01
7.49613404e-01 -4.58777875e-01 -4.10408229e-01 1.44113213e-01
9.82311964e-02 5.82071066e-01 2.35177726e-01 -8.93462777e-01
-4.77096677e-01 6.81730807e-02 4.87188637e-01 4.07182932e-01
-9.69879776e-02 -2.34498940e-02 -5.48160255e-01 -3.66189063e-01
-2.76660800e-01 -7.79718578e-01 5.76420277e-02 -8.10312271e-01
-5.81826031e-01 -7.84954906e-01 4.56341505e-01 -6.98684454e-01
1.34601808e+00 -1.86796701e+00 1.25796152e-02 -5.59928775e-01
9.96047258e-02 6.76926374e-02 -5.63021660e-01 9.11044359e-01
2.80435562e-01 1.84980512e-01 -2.79795736e-01 -4.87754375e-01
1.21275634e-01 -3.44439223e-02 -4.47483718e-01 -1.15275070e-01
1.67544127e-01 9.10912395e-01 -1.01072037e+00 -2.65592366e-01
-1.69896543e-01 1.50525235e-02 -5.35164714e-01 6.71488523e-01
-7.79198408e-01 7.25498378e-01 -5.94245911e-01 3.38671088e-01
6.66978300e-01 -3.24367970e-01 -2.17777133e-01 3.58763129e-01
2.05992818e-01 7.80400455e-01 -4.74835962e-01 1.74358678e+00
-5.45711160e-01 7.42821455e-01 -2.41750851e-01 -6.93066120e-01
9.94860053e-01 4.78197694e-01 -1.13456091e-02 -1.04606855e+00
2.62000486e-02 -1.35417730e-01 2.14350633e-02 -8.24907303e-01
6.56755745e-01 1.11377217e-01 -4.81126517e-01 7.17342854e-01
-2.39603847e-01 -2.43592992e-01 2.70231664e-01 5.81353009e-01
1.19703889e+00 -4.36379969e-01 7.07352832e-02 -1.38557181e-01
7.29229510e-01 5.90498224e-02 5.93067825e-01 8.36622119e-01
-4.67313975e-01 8.70839775e-01 8.97491574e-01 -1.06426693e-01
-5.53780794e-01 -8.69172931e-01 6.02721982e-02 1.30607843e+00
2.64842689e-01 -4.45022941e-01 -1.04337347e+00 -6.30866528e-01
-4.38417554e-01 1.05636954e+00 -5.46349168e-01 -5.31561747e-02
-4.69754279e-01 -4.25657332e-01 4.06667829e-01 1.74561173e-01
9.29525316e-01 -1.37174356e+00 -3.79716396e-01 3.33446354e-01
-1.17508709e+00 -1.28159571e+00 -7.15995848e-01 -4.98712152e-01
-2.77643859e-01 -1.35423517e+00 -8.46034408e-01 -6.84336305e-01
7.73549750e-02 5.97281098e-01 1.70314753e+00 8.02074149e-02
2.44278312e-01 4.72426713e-01 -1.10715961e+00 -5.71216464e-01
-5.10636091e-01 5.07379651e-01 -3.15363884e-01 -1.76969260e-01
7.46242046e-01 -3.09846163e-01 -6.54061496e-01 7.71228790e-01
-5.77025652e-01 3.67761493e-01 1.33866623e-01 6.71608269e-01
1.20262794e-01 -3.98085594e-01 1.18482494e+00 -1.06733799e+00
1.34768975e+00 -1.00527263e+00 -1.07947685e-01 4.41225559e-01
-5.69903217e-02 -5.52591264e-01 6.49702609e-01 -3.92720789e-01
-1.35108459e+00 -8.31274748e-01 -2.69874334e-01 1.23540804e-01
-4.40150678e-01 5.86170077e-01 -3.65263104e-01 1.03795218e+00
6.99611545e-01 2.62169600e-01 -4.41114530e-02 -5.03276408e-01
1.15331337e-01 1.08492815e+00 5.46275377e-01 -9.79136467e-01
2.48230144e-01 -3.38071883e-01 -1.00088286e+00 -7.93649197e-01
-1.17367792e+00 -6.19669497e-01 -1.43721953e-01 -5.39918542e-01
8.59281421e-01 -1.03243697e+00 -1.02688611e+00 7.68253565e-01
-1.56417513e+00 -6.89696252e-01 2.95318544e-01 2.53324151e-01
-4.58270252e-01 1.08544156e-01 -7.31429338e-01 -7.89709985e-01
-5.94279170e-01 -1.15509665e+00 9.01917458e-01 3.89529914e-01
-5.43594360e-01 -8.13998342e-01 1.46813393e-01 8.43861759e-01
5.51845253e-01 5.04122153e-02 7.79485643e-01 -8.12931180e-01
-3.28984082e-01 -5.54487258e-02 -1.43000409e-01 3.41969490e-01
-1.37472495e-01 -8.37211311e-02 -1.10081923e+00 -1.52861685e-01
1.80997223e-01 -7.46038079e-01 6.40929818e-01 -8.33114311e-02
1.36792564e+00 -4.87107605e-01 1.45557001e-01 -1.43007740e-01
7.32894301e-01 1.86832756e-01 7.32490182e-01 1.59258157e-01
1.72610626e-01 1.08701956e+00 8.50183725e-01 4.05316979e-01
1.05100811e+00 4.53144491e-01 2.95265198e-01 4.91722226e-01
1.26614571e-01 -3.82149816e-01 5.62551320e-01 1.43824673e+00
1.63409010e-01 -8.33415210e-01 -1.22232211e+00 6.06490672e-01
-1.88349986e+00 -1.02777028e+00 -4.68362927e-01 1.79427266e+00
1.02176273e+00 1.65456355e-01 4.14916202e-02 -2.01022476e-01
8.32710505e-01 2.73678958e-01 -6.46176279e-01 -4.34480697e-01
-1.41942412e-01 -2.62873203e-01 -3.98706138e-01 5.66702902e-01
-6.42773390e-01 7.31215060e-01 5.23888636e+00 7.00315952e-01
-5.91679096e-01 2.01327324e-01 9.11781549e-01 -3.74048464e-02
-4.97150391e-01 -2.05972269e-01 -7.52097487e-01 9.31777954e-01
1.15170979e+00 -5.09632826e-01 2.51458228e-01 6.39955461e-01
4.46588516e-01 -2.67242074e-01 -1.14106858e+00 8.14912438e-01
7.81379417e-02 -1.03060102e+00 -1.11517861e-01 -3.94110769e-01
7.04885125e-01 6.38055652e-02 -5.82527816e-02 1.00519395e+00
4.06943530e-01 -1.00970864e+00 3.58173549e-01 6.66486084e-01
4.77376610e-01 -5.46612501e-01 9.96160507e-01 9.09380555e-01
-6.87233448e-01 1.19225912e-01 -4.61799026e-01 -4.18237746e-01
3.15837383e-01 4.03037399e-01 -8.17635775e-01 3.40610147e-01
8.04889560e-01 7.27764189e-01 -4.82983679e-01 7.37391829e-01
-3.44616771e-01 1.07603061e+00 -5.33714890e-02 -5.45246601e-01
3.54770511e-01 -1.71099141e-01 3.89408082e-01 1.38471532e+00
1.45303041e-01 5.32369733e-01 2.16965467e-01 6.27153277e-01
-4.40647006e-01 2.08333731e-01 -2.75054127e-01 2.34342456e-01
9.59283352e-01 8.60073864e-01 -1.94951445e-02 -4.04677391e-01
-5.16262412e-01 7.09768772e-01 3.05545926e-01 5.19353688e-01
-8.57308030e-01 -3.34471762e-01 7.37570822e-01 -5.88244423e-02
-3.43016356e-01 2.06200957e-01 -1.32490262e-01 -1.35135019e+00
3.65890175e-01 -1.43769586e+00 3.95768315e-01 -8.38821769e-01
-1.61234021e+00 6.64123654e-01 4.48907465e-02 -1.31576228e+00
-3.46369714e-01 -6.24053553e-02 -1.22956681e+00 9.90437746e-01
-1.50642693e+00 -6.50245547e-01 -9.37366188e-01 5.28882146e-01
1.38941693e+00 -1.30589515e-01 7.91865051e-01 6.96515739e-02
-8.22986603e-01 7.16890275e-01 -2.10277326e-02 6.56560436e-02
1.12642908e+00 -1.16938519e+00 7.20113575e-01 5.00388443e-01
-6.03861928e-01 5.63668728e-01 9.46076632e-01 -3.29235345e-01
-1.15879238e+00 -9.67399478e-01 1.06759477e+00 -7.24676788e-01
6.44078553e-01 -4.88138556e-01 -1.44568026e+00 5.55922151e-01
8.34293664e-01 -6.81890965e-01 6.46848917e-01 3.77684981e-01
-1.60291225e-01 6.22695498e-03 -8.28684151e-01 6.29881442e-01
9.33242142e-01 -6.09522581e-01 -8.14446330e-01 6.00962222e-01
1.26393080e+00 -5.62010646e-01 -6.71339989e-01 1.88076675e-01
1.57689601e-01 -1.01520097e+00 5.32636166e-01 -7.14396477e-01
1.02623069e+00 2.35654369e-01 -1.34145290e-01 -1.61640131e+00
1.58464089e-01 -6.54075980e-01 2.57480312e-02 1.62256300e+00
5.42505980e-01 -6.84233546e-01 4.32845116e-01 6.86432123e-01
-3.44981790e-01 -7.80549884e-01 -6.70341015e-01 -4.01293963e-01
4.16194022e-01 -4.64323491e-01 8.59027028e-01 8.93396020e-01
2.62442976e-01 8.07937980e-01 -3.61570507e-01 -2.15198338e-01
2.21205428e-01 1.06114656e-01 1.22883534e+00 -9.91330862e-01
-2.45368898e-01 -4.81814265e-01 3.31543207e-01 -1.57461607e+00
2.81053096e-01 -5.63263774e-01 3.18221927e-01 -1.53558958e+00
3.21404874e-01 -2.35036746e-01 1.35327145e-01 1.67953297e-01
-6.56063437e-01 -5.02226830e-01 2.10207775e-01 1.34030730e-01
-9.80995893e-01 8.97518218e-01 1.58017981e+00 -2.01153412e-01
-3.32052410e-02 2.72970915e-01 -8.31363678e-01 4.83845353e-01
1.06130743e+00 -3.15205753e-02 -6.89026833e-01 -6.24690175e-01
5.39786927e-02 5.21226525e-01 1.18331566e-01 -6.11812234e-01
3.49273473e-01 -2.59330690e-01 -3.52719545e-01 -7.38097310e-01
1.85375184e-01 -6.70834631e-02 -3.52432907e-01 1.42045282e-02
-9.68795300e-01 2.08599895e-01 2.47967988e-03 6.56678855e-01
-5.27649820e-01 -1.49017096e-01 4.51395363e-01 -6.69705719e-02
-7.23935962e-01 7.45366067e-02 -4.00125921e-01 7.79193521e-01
8.19007516e-01 1.93941712e-01 -8.75746250e-01 -1.11121750e+00
-3.69633645e-01 1.00082469e+00 1.76980346e-01 9.59699273e-01
5.05040765e-01 -9.63895440e-01 -1.31947637e+00 -3.45950335e-01
5.70384383e-01 5.01179934e-01 8.74709487e-01 6.72320127e-01
-3.66595089e-01 5.09275675e-01 9.40849259e-02 -6.44971371e-01
-1.14830995e+00 2.72776455e-01 1.90592110e-01 -2.24898964e-01
-6.44083858e-01 7.97779202e-01 3.87213171e-01 -7.48041689e-01
4.85877216e-01 -3.52421045e-01 -4.35477525e-01 1.65657967e-01
9.61186945e-01 3.85730922e-01 -1.12486146e-02 -1.78242177e-01
-1.33907109e-01 8.73429403e-02 -3.05688918e-01 4.36377861e-02
9.83520746e-01 -5.49569726e-01 7.32017308e-02 6.99549258e-01
1.23767734e+00 -2.51946598e-01 -1.19120860e+00 -5.06797791e-01
4.29021642e-02 -3.32593560e-01 -6.14870369e-01 -1.11351216e+00
-5.72352052e-01 1.00558305e+00 -1.88185386e-02 3.84275198e-01
9.47473049e-01 9.09129679e-02 1.12547660e+00 6.90971971e-01
2.67201424e-01 -9.98780370e-01 3.24655145e-01 1.08623183e+00
1.47886348e+00 -1.57424295e+00 -6.46676660e-01 -2.63926983e-01
-1.17329764e+00 7.49605298e-01 1.02034509e+00 3.09979737e-01
2.59779036e-01 -2.35390633e-01 4.21270519e-01 1.16813838e-01
-1.52357984e+00 9.91621241e-02 -1.48096401e-02 3.14442754e-01
6.82030499e-01 2.21352071e-01 -4.38948542e-01 9.89546776e-01
-6.27654791e-01 -3.13079894e-01 8.09611320e-01 4.86431330e-01
-4.43419755e-01 -7.59827733e-01 -8.56503472e-02 2.88899273e-01
-2.02193469e-01 4.88823913e-02 -5.80433547e-01 5.76670468e-01
-6.09835863e-01 1.63352895e+00 3.21779065e-02 -3.69016021e-01
6.50151730e-01 9.95761082e-02 -3.34898055e-01 -6.51836872e-01
-6.23661697e-01 -3.89418811e-01 4.37993705e-01 -5.08511841e-01
-9.58740115e-02 -6.65754199e-01 -9.26381588e-01 -6.77127600e-01
-1.60258897e-02 5.21324635e-01 2.18485594e-01 9.11259532e-01
4.11200553e-01 5.94497800e-01 7.88196564e-01 -3.00691038e-01
-6.50700450e-01 -1.57805431e+00 1.53481904e-02 6.25510454e-01
2.43476123e-01 -3.43477726e-01 -4.48787689e-01 -7.63359591e-02] | [11.999550819396973, 8.075698852539062] |
8c455773-8122-4320-959b-ddf5d9dc8217 | spatial-language-representation-with-multi | 2008.09236 | null | https://arxiv.org/abs/2008.09236v1 | https://arxiv.org/pdf/2008.09236v1.pdf | Spatial Language Representation with Multi-Level Geocoding | We present a multi-level geocoding model (MLG) that learns to associate texts to geographic locations. The Earth's surface is represented using space-filling curves that decompose the sphere into a hierarchy of similarly sized, non-overlapping cells. MLG balances generalization and accuracy by combining losses across multiple levels and predicting cells at each level simultaneously. Without using any dataset-specific tuning, we show that MLG obtains state-of-the-art results for toponym resolution on three English datasets. Furthermore, it obtains large gains without any knowledge base metadata, demonstrating that it can effectively learn the connection between text spans and coordinates - and thus can be extended to toponymns not present in knowledge bases. | ['Li Zhang', 'Eugene Ie', 'Jason Baldridge', 'Sayali Kulkarni', 'Shailee Jain', 'Mohammad Javad Hosseini'] | 2020-08-21 | null | null | null | null | ['toponym-resolution'] | ['natural-language-processing'] | [-4.48364675e-01 2.98467368e-01 -6.26805604e-01 -1.06978215e-01
-9.69231725e-01 -8.85535479e-01 6.33539915e-01 5.75058699e-01
-3.96873295e-01 8.54072273e-01 6.52758300e-01 -2.13909745e-01
-2.89673030e-01 -1.19948339e+00 -9.23446953e-01 -1.02505431e-01
-1.36060432e-01 8.98551106e-01 3.38370204e-01 -1.91035643e-01
2.43476331e-01 4.70451474e-01 -1.27581465e+00 3.97217959e-01
1.33475089e+00 7.84463167e-01 -9.17660370e-02 3.50046843e-01
-4.44985062e-01 7.59840429e-01 -4.97456014e-01 -6.25060320e-01
1.86124086e-01 4.15725380e-01 -8.55125666e-01 -6.91783667e-01
1.08064032e+00 -1.76704720e-01 -8.12129974e-01 8.53598833e-01
1.85610950e-01 -7.33582303e-02 1.02435660e+00 -9.90159571e-01
-1.08212769e+00 9.75712061e-01 -5.89947283e-01 1.92494467e-01
4.13544267e-01 -5.04570723e-01 1.46682382e+00 -9.91724014e-01
6.13318801e-01 1.18314302e+00 1.28039193e+00 -1.01473071e-01
-1.19401240e+00 -7.21947849e-01 2.02469796e-01 -3.98118347e-02
-2.11045170e+00 -9.63994786e-02 1.20182531e-02 -5.94729543e-01
1.32120013e+00 3.41158301e-01 4.84526634e-01 6.01826906e-01
-1.24766603e-01 6.20528936e-01 6.55266881e-01 -3.23993802e-01
4.96951938e-02 -1.08677320e-01 1.54928416e-01 7.10477710e-01
7.82322466e-01 -3.98692369e-01 -9.41236258e-01 -3.90388608e-01
8.98017883e-01 -1.49235472e-01 -1.02396987e-01 -3.05945456e-01
-1.14201760e+00 6.36073112e-01 7.39813924e-01 3.26639771e-01
-1.17641605e-01 4.30950016e-01 6.77807406e-02 -9.91770253e-03
5.77403426e-01 8.94366026e-01 -5.26212811e-01 -6.83994824e-03
-1.41798401e+00 2.73132652e-01 1.02196836e+00 1.56163704e+00
9.00286973e-01 -3.18844467e-01 -1.04880653e-01 6.97036684e-01
-1.42451584e-01 7.36152112e-01 2.89477378e-01 -9.44239855e-01
1.00046706e+00 9.16046143e-01 2.64248163e-01 -1.26562715e+00
-7.62581825e-01 -6.03757262e-01 -5.59315443e-01 -6.51343644e-01
4.46593076e-01 -3.54346782e-02 -7.29017496e-01 1.79678237e+00
-9.11251307e-02 5.36844909e-01 -6.91803694e-02 4.36446398e-01
7.66864240e-01 5.59727132e-01 1.66098759e-01 4.44358975e-01
1.44808877e+00 -4.39123422e-01 -2.39537746e-01 -3.74885440e-01
9.93456423e-01 -1.15145907e-01 1.05094242e+00 8.29026997e-02
-9.43176687e-01 -1.55690536e-01 -9.85933721e-01 -5.99707901e-01
-1.03533423e+00 2.00029716e-01 9.14449930e-01 7.62373209e-01
-1.26558661e+00 4.09381181e-01 -6.15740538e-01 -5.27903259e-01
4.52464223e-01 2.40592107e-01 -4.53680575e-01 6.69609681e-02
-1.63446832e+00 9.97246623e-01 5.20174503e-01 -6.28155410e-01
-1.40769079e-01 -1.18508303e+00 -8.82630944e-01 3.70092630e-01
-3.96830887e-02 -8.29838037e-01 6.35663331e-01 -1.59325123e-01
-4.77218837e-01 9.21318591e-01 -1.95504487e-01 -7.11383581e-01
3.27477545e-01 -3.29577714e-01 -6.24782562e-01 4.70718816e-02
3.81723702e-01 8.79509211e-01 2.16609091e-01 -9.66640234e-01
-9.21296120e-01 -5.01629949e-01 1.59397051e-01 3.66090029e-01
-7.99199045e-01 -4.01446670e-01 -7.10682809e-01 -8.54745924e-01
4.62361962e-01 -7.56362557e-01 3.41545045e-01 -4.54655737e-02
-3.34964216e-01 -2.98865467e-01 5.96563630e-02 -1.04451478e+00
1.90623367e+00 -1.84877992e+00 1.60566624e-02 4.91677910e-01
3.02449584e-01 -3.69074941e-01 -5.51436022e-02 4.69053745e-01
3.20895374e-01 3.86545539e-01 -3.31747122e-02 -1.60680935e-01
2.65918255e-01 1.26040280e-01 -6.98134184e-01 5.17456353e-01
-2.71383971e-01 1.04852414e+00 -9.03678656e-01 -5.77006221e-01
-1.07226998e-01 2.95635074e-01 -8.50479603e-01 -5.39541006e-01
-1.76101819e-01 -3.10827672e-01 -3.29951018e-01 7.13811636e-01
5.61921060e-01 -5.91968477e-01 1.68392718e-01 4.17924337e-02
1.19841069e-01 4.45221901e-01 -1.04415667e+00 1.93951333e+00
-6.13321006e-01 7.48752832e-01 -2.66959399e-01 -4.31934208e-01
7.33111799e-01 -7.62086585e-02 3.99139255e-01 -5.76116025e-01
-5.51253080e-01 4.91249502e-01 -7.51810491e-01 -7.92361349e-02
1.11053252e+00 3.70637506e-01 -6.87631965e-01 2.24997312e-01
6.16390295e-02 -9.05194581e-02 3.28166620e-03 5.43425024e-01
1.00200844e+00 -1.41773254e-01 3.40486407e-01 -5.11606932e-01
2.46043518e-01 1.07405268e-01 3.66859436e-01 9.92453814e-01
4.54350144e-01 4.44688678e-01 4.79057729e-01 -3.78895432e-01
-1.31236875e+00 -1.28324485e+00 -5.67111015e-01 1.41664553e+00
2.49028265e-01 -6.12844944e-01 -7.35120952e-01 -3.82679820e-01
9.87372100e-01 9.54239726e-01 -7.03670979e-01 5.53447530e-02
-4.99827921e-01 -5.90383291e-01 1.17198658e+00 8.65495503e-01
2.48780087e-01 -2.30029479e-01 -1.79589346e-01 -3.61084193e-02
-4.84616905e-01 -1.08877957e+00 -5.18077075e-01 1.00924462e-01
-7.46828377e-01 -9.34651673e-01 -6.96074963e-01 -7.03267336e-01
6.05916739e-01 1.07216030e-01 1.46942580e+00 4.04566973e-02
-2.12612823e-01 3.25823843e-01 -2.34754190e-01 -1.37976229e-01
1.95527539e-01 1.04364693e+00 2.92950302e-01 -6.84465766e-01
6.76911056e-01 -7.13506579e-01 -5.21090865e-01 1.38422519e-01
-4.12150323e-01 -2.54692197e-01 2.60191351e-01 5.65474927e-01
3.78480285e-01 -2.73759544e-01 7.26967156e-01 -8.61502707e-01
3.45533103e-01 -8.53822172e-01 -7.87392855e-01 4.98757690e-01
-5.07070124e-01 2.34164551e-01 4.90612626e-01 1.07665891e-02
-5.64154744e-01 -1.33066177e-01 2.56147772e-01 9.90718231e-03
1.45217627e-01 6.01643682e-01 -8.11930075e-02 -1.35590136e-01
9.20679629e-01 2.24806339e-01 -6.80236578e-01 -5.80206811e-01
1.01492417e+00 9.66685593e-01 8.63420725e-01 -9.29513693e-01
7.02626944e-01 4.65916574e-01 -1.74988717e-01 -7.28845298e-01
-1.03521216e+00 -5.61047673e-01 -9.39883530e-01 3.78603190e-01
7.48288155e-01 -1.56168830e+00 -6.44433439e-01 9.23515037e-02
-9.97220576e-01 -2.82517701e-01 -1.76911950e-01 2.72685170e-01
-5.07536829e-01 1.79916084e-01 -6.09418333e-01 -3.90205920e-01
-1.01077355e-01 -2.24241525e-01 1.13672304e+00 9.34668481e-02
-3.72431010e-01 -1.18534899e+00 -3.71571048e-03 1.20629631e-01
2.63617933e-01 -3.79928015e-02 1.25420654e+00 -8.77754927e-01
-7.78858066e-01 -2.89884686e-01 -5.35257041e-01 -4.28924829e-01
-1.24897271e-01 -4.82197553e-01 -7.96186090e-01 -2.82396764e-01
-8.60541880e-01 -2.72596508e-01 1.16139734e+00 3.12256873e-01
1.34876323e+00 -6.12032831e-01 -8.03198278e-01 1.22089434e+00
1.47736847e+00 -5.20937145e-01 4.99718457e-01 6.24968827e-01
7.53741026e-01 4.72895741e-01 2.40886241e-01 5.76694965e-01
9.72401321e-01 5.93437195e-01 2.79464126e-01 3.92240882e-02
-4.36873548e-03 -8.11606228e-01 -2.66116977e-01 4.96464103e-01
3.16014856e-01 -4.17677194e-01 -1.35154319e+00 8.90980184e-01
-1.72022772e+00 -1.05543756e+00 -6.13616705e-02 2.05551434e+00
1.17512250e+00 -1.11934744e-01 1.69617198e-02 -2.97585577e-01
6.30703628e-01 2.53253579e-01 -6.65007830e-01 1.91730052e-01
-6.17592573e-01 2.84077059e-02 1.45412338e+00 7.21589804e-01
-1.25696623e+00 1.29381812e+00 7.82759953e+00 1.03669894e+00
-7.55538940e-01 -2.91868746e-02 3.98983687e-01 -3.01016271e-01
-7.51127183e-01 -1.99507445e-01 -1.11406565e+00 6.17523015e-01
5.90861797e-01 -4.33701605e-01 6.56456530e-01 8.24728906e-01
-5.09426236e-01 5.52208833e-02 -9.75789070e-01 1.01229417e+00
8.34183395e-02 -1.75362217e+00 2.52256036e-01 3.67397517e-02
1.04964828e+00 3.55454654e-01 1.95694819e-01 2.97272056e-01
8.10588777e-01 -1.40048301e+00 8.97267222e-01 5.35473824e-01
1.46369469e+00 -7.54956245e-01 4.25229400e-01 3.66652727e-01
-1.56456923e+00 -4.19166565e-01 -6.93302095e-01 4.84204404e-02
-1.22585230e-01 4.09334242e-01 -6.71517491e-01 5.52722037e-01
5.58817625e-01 6.48259878e-01 -8.59654486e-01 1.14200485e+00
-1.47305280e-01 3.84472370e-01 -6.68365836e-01 1.77449167e-01
1.49946824e-01 1.40818685e-01 1.83118284e-01 1.44869637e+00
7.85721600e-01 1.57875061e-01 2.06019245e-02 9.00407374e-01
-6.12946451e-01 9.01373252e-02 -6.13396049e-01 2.39203140e-01
1.70688987e+00 6.63683116e-01 -4.37145442e-01 -4.12259847e-01
-5.00313342e-01 7.50048101e-01 7.57056415e-01 4.88286346e-01
-7.60100901e-01 -7.72805631e-01 7.61208832e-01 4.25521255e-01
3.82463098e-01 -2.50143617e-01 -1.02757132e+00 -1.21100259e+00
-1.83784664e-01 -3.99491668e-01 9.02674675e-01 -8.77685249e-01
-1.34545875e+00 4.23565842e-02 1.12876825e-01 -1.03178120e+00
-5.93285710e-02 -5.50307691e-01 1.04127668e-01 1.12789130e+00
-1.40514398e+00 -1.23197913e+00 -2.72595912e-01 4.66327667e-01
-1.21678501e-01 -3.19960415e-01 8.00823987e-01 3.67858052e-01
-7.26190656e-02 1.11194992e+00 6.84761047e-01 4.43542600e-01
7.74029315e-01 -1.67335546e+00 9.70208406e-01 5.58055758e-01
3.43672305e-01 9.57284093e-01 3.88025701e-01 -8.74505043e-01
-9.58713233e-01 -1.14937615e+00 1.24081945e+00 -1.02285886e+00
8.76424491e-01 -5.55883050e-01 -9.18747246e-01 9.99603510e-01
-2.98027903e-01 1.18913008e-02 6.84121192e-01 7.24034965e-01
-1.08429909e+00 -7.95489550e-02 -1.18904579e+00 3.97917151e-01
1.39890146e+00 -9.24390554e-01 -8.37768137e-01 2.77027488e-01
8.25374901e-01 -6.89832747e-01 -1.19273269e+00 1.46018744e-01
5.64563990e-01 -3.81676406e-01 1.35955083e+00 -6.28591299e-01
2.07317054e-01 -1.94179997e-01 -3.75859112e-01 -1.20672011e+00
-5.75049460e-01 -3.01477313e-01 -3.42292577e-01 9.76265490e-01
7.10048258e-01 -7.83581138e-01 1.05256569e+00 6.24586523e-01
-9.79241878e-02 -4.85642374e-01 -1.15848100e+00 -8.80562127e-01
7.51003921e-01 -2.16632947e-01 1.24247038e+00 1.37118435e+00
5.51092684e-01 -4.69229035e-02 -2.47526675e-01 4.42258269e-01
4.81101096e-01 2.70725451e-02 5.02264738e-01 -1.61428475e+00
1.69912934e-01 -5.78608751e-01 -3.96255165e-01 -1.41311729e+00
2.30424672e-01 -1.35032248e+00 -3.84292334e-01 -1.74394095e+00
1.61129072e-01 -9.22294617e-01 -6.63742572e-02 6.21503890e-01
-1.27566680e-01 2.02621877e-01 -3.40170339e-02 5.07085145e-01
-7.50492215e-01 1.69937238e-01 5.99677205e-01 -7.54514933e-02
-2.09655762e-02 -5.54104149e-01 -9.68247533e-01 6.27769053e-01
5.09323776e-01 -4.11673009e-01 -1.98691636e-01 -8.49918485e-01
8.79966497e-01 -5.02322353e-02 1.42032698e-01 -1.13000834e+00
7.29075074e-01 -4.21707295e-02 6.90532923e-01 -9.62834477e-01
1.67509660e-01 -6.25011206e-01 3.99858356e-02 1.27010524e-01
-5.04028857e-01 1.47360593e-01 1.42603427e-01 7.47275114e-01
-2.30302643e-02 2.96592042e-02 4.49656904e-01 -1.08962394e-02
-6.69181406e-01 2.18637139e-01 -2.15285998e-02 6.47102594e-01
5.92580259e-01 -2.04865113e-01 -7.50062823e-01 -2.24521130e-01
-5.32947779e-01 5.02511621e-01 1.01853955e+00 2.79256761e-01
-2.12898180e-02 -1.43839979e+00 -6.37560725e-01 -8.24982226e-02
4.37693805e-01 8.39240029e-02 2.50516478e-02 3.32280964e-01
-8.22324455e-01 1.03176451e+00 7.33386874e-02 -3.82249832e-01
-5.20982563e-01 4.23551738e-01 4.54429567e-01 -3.47191006e-01
-7.33580291e-01 1.00577557e+00 5.68561368e-02 -6.90463901e-01
5.13651729e-01 -4.04714465e-01 -9.22143608e-02 4.35576051e-01
4.35452282e-01 5.47043085e-01 1.01868585e-01 -5.24069607e-01
-4.67768341e-01 7.27560699e-01 1.87637120e-01 -3.56882289e-02
1.14763403e+00 -2.52431720e-01 -7.41013810e-02 2.77565062e-01
9.99972343e-01 2.30474263e-01 -1.04836023e+00 -4.99027193e-01
4.27553862e-01 -4.60529387e-01 -2.35149592e-01 -8.85730028e-01
-6.68793797e-01 5.51663339e-01 5.97270392e-02 4.66908002e-03
5.92569590e-01 1.98634610e-01 8.21981430e-01 7.60589659e-01
8.13537359e-01 -1.32813549e+00 -8.77852738e-02 9.62172389e-01
6.24125719e-01 -6.44373178e-01 2.10954458e-01 -3.00168604e-01
-3.72037470e-01 7.95545280e-01 3.20663989e-01 -7.45766163e-02
7.09245205e-01 4.08037066e-01 -3.94418448e-01 -1.22744612e-01
-5.52375257e-01 -2.08352119e-01 4.52392578e-01 8.08832705e-01
3.33994657e-01 2.70554423e-01 -5.60277104e-02 9.57685709e-01
-8.02329242e-01 -1.64620131e-01 2.48773709e-01 4.11071777e-01
-8.45381141e-01 -5.13078153e-01 -4.34803843e-01 9.00943339e-01
-2.65833884e-01 -6.61063850e-01 -2.31244087e-01 9.82685626e-01
6.90644309e-02 3.68082523e-01 5.61121702e-01 -3.60748142e-01
1.36432216e-01 2.14155450e-01 3.52186561e-01 -6.42562091e-01
-3.86302143e-01 -6.25454962e-01 1.16911784e-01 -4.29287374e-01
3.09465230e-01 -6.78598821e-01 -1.34903371e+00 -7.26881385e-01
-1.22891031e-01 1.83031216e-01 3.31868947e-01 4.92785871e-01
6.44971967e-01 1.28061876e-01 1.64864615e-01 -4.15135235e-01
-4.88601565e-01 -8.26427877e-01 -8.50849628e-01 2.46263370e-01
2.23777190e-01 -6.02519095e-01 -3.71800810e-01 -2.77645439e-01] | [9.326783180236816, 8.92342758178711] |
3c45a20c-982a-408f-9f07-428cf00e5fd2 | minervas-massive-interior-environments | 2107.06149 | null | https://arxiv.org/abs/2107.06149v4 | https://arxiv.org/pdf/2107.06149v4.pdf | MINERVAS: Massive INterior EnviRonments VirtuAl Synthesis | With the rapid development of data-driven techniques, data has played an essential role in various computer vision tasks. Many realistic and synthetic datasets have been proposed to address different problems. However, there are lots of unresolved challenges: (1) the creation of dataset is usually a tedious process with manual annotations, (2) most datasets are only designed for a single specific task, (3) the modification or randomization of the 3D scene is difficult, and (4) the release of commercial 3D data may encounter copyright issue. This paper presents MINERVAS, a Massive INterior EnviRonments VirtuAl Synthesis system, to facilitate the 3D scene modification and the 2D image synthesis for various vision tasks. In particular, we design a programmable pipeline with Domain-Specific Language, allowing users to (1) select scenes from the commercial indoor scene database, (2) synthesize scenes for different tasks with customized rules, and (3) render various imagery data, such as visual color, geometric structures, semantic label. Our system eases the difficulty of customizing massive numbers of scenes for different tasks and relieves users from manipulating fine-grained scene configurations by providing user-controllable randomness using multi-level samplers. Most importantly, it empowers users to access commercial scene databases with millions of indoor scenes and protects the copyright of core data assets, e.g., 3D CAD models. We demonstrate the validity and flexibility of our system by using our synthesized data to improve the performance on different kinds of computer vision tasks. | ['Hujun Bao', 'Yuchi Huo', 'Rui Wang', 'Rui Tang', 'Jiaxiang Zheng', 'Jia Zheng', 'Hao Zhang', 'Haocheng Ren'] | 2021-07-13 | null | null | null | null | ['2d-semantic-segmentation'] | ['computer-vision'] | [ 2.42513761e-01 -7.94353902e-01 4.74180162e-01 -4.15110141e-01
-3.78914535e-01 -8.47910941e-01 4.91148740e-01 -2.74782032e-01
-2.58824736e-01 3.92081022e-01 -1.23244546e-01 -3.79156590e-01
7.10505322e-02 -9.13382888e-01 -6.06635869e-01 -6.02275670e-01
2.86314309e-01 5.09564638e-01 6.13649845e-01 -1.80867746e-01
4.07544494e-01 8.94902885e-01 -2.21782923e+00 2.65796054e-02
1.00319695e+00 1.03612757e+00 8.94604743e-01 5.85384727e-01
-3.72556090e-01 4.23501164e-01 -7.38501728e-01 1.27125746e-02
7.29765356e-01 -1.10427804e-01 -2.81703562e-01 3.73689502e-01
6.12308979e-01 -3.76227587e-01 -1.51921138e-02 1.20642686e+00
6.68698132e-01 4.80988249e-02 2.51755297e-01 -1.42425513e+00
-3.86502028e-01 -4.07534726e-02 -6.28995776e-01 -2.11594284e-01
2.34511927e-01 6.79508746e-01 3.07498157e-01 -8.37916613e-01
6.09175026e-01 1.30601072e+00 4.65933859e-01 2.97993809e-01
-1.18307137e+00 -8.55667114e-01 4.18409742e-02 -6.28936067e-02
-1.58502936e+00 -3.73663753e-01 9.48961139e-01 -6.89720929e-01
6.25694394e-01 6.04027808e-01 7.25882053e-01 1.06339812e+00
-4.13269587e-02 3.10241342e-01 1.35119724e+00 -7.45608583e-02
4.31515396e-01 9.00114775e-02 -4.24514897e-02 7.50933290e-01
2.11635038e-01 -1.08827092e-01 -2.60835081e-01 -2.97172368e-01
9.11811233e-01 2.84929834e-02 -1.14307895e-01 -7.03424931e-01
-1.37286794e+00 5.98437369e-01 1.92781880e-01 -2.86232233e-01
-1.67565420e-01 -1.17128063e-03 3.54244232e-01 -2.83438787e-02
8.02294984e-02 4.86982495e-01 -6.71996832e-01 1.02240965e-01
-7.03322530e-01 5.83983839e-01 5.11603892e-01 1.30406821e+00
9.34371769e-01 -4.38515954e-02 -6.44918084e-02 8.98080349e-01
1.54035598e-01 8.63824725e-01 3.23131502e-01 -1.17163455e+00
3.84754688e-01 6.61104381e-01 1.51414245e-01 -1.14751887e+00
-3.83423805e-01 -5.26874959e-02 -1.11169815e+00 4.76113886e-01
9.25145745e-02 7.30745941e-02 -1.05668235e+00 1.50016475e+00
6.50958121e-01 -8.08849558e-02 -3.36035579e-01 9.00080740e-01
1.03378320e+00 7.09749162e-01 -1.34625956e-01 1.31306380e-01
1.36978292e+00 -7.07581282e-01 -2.96195596e-01 -1.31857976e-01
5.54381423e-02 -1.12610149e+00 1.69947851e+00 4.20556903e-01
-7.42511451e-01 -9.97364461e-01 -1.01460826e+00 -2.34136775e-01
-4.61890459e-01 5.76489232e-02 8.30710590e-01 7.93101668e-01
-8.70993793e-01 8.41205269e-02 -6.15466774e-01 -3.28865290e-01
5.34518778e-01 2.00523555e-01 -1.47435695e-01 -3.17294985e-01
-7.98132777e-01 2.84258693e-01 3.52102041e-01 -1.19599670e-01
-1.01432073e+00 -7.67267525e-01 -8.50862384e-01 -2.43368924e-01
4.32385057e-01 -1.02355552e+00 8.59804451e-01 -5.06633878e-01
-1.53743339e+00 8.57857525e-01 1.55126259e-01 1.40990078e-01
6.18356884e-01 -2.97350287e-02 -1.82007566e-01 -2.31442854e-01
4.04081106e-01 7.75042474e-01 8.09211493e-01 -1.41841853e+00
-4.94020104e-01 -2.48594135e-01 7.11839870e-02 3.02784294e-01
-2.26108190e-02 -3.51503342e-02 -9.98670459e-01 -7.55192995e-01
1.70716405e-01 -1.04548991e+00 -6.20564580e-01 3.41941118e-01
-6.61692977e-01 1.88131690e-01 1.13741231e+00 -1.02484912e-01
7.95822442e-01 -2.51036358e+00 -2.63532579e-01 6.20281808e-02
2.76790801e-02 1.52437717e-01 -4.34491001e-02 1.16960779e-01
1.54346183e-01 2.81066805e-01 -3.07660162e-01 -3.62357229e-01
-2.07563024e-02 2.19458148e-01 -4.33794379e-01 2.36192256e-01
-9.82908905e-02 4.22295511e-01 -6.87381446e-01 -6.68251812e-01
8.40690076e-01 1.91127583e-01 -8.72228146e-01 4.27378863e-01
-5.60711086e-01 5.41222751e-01 -6.60543323e-01 6.71857655e-01
1.15696156e+00 -3.00984830e-01 -1.08220175e-01 -3.23724031e-01
-4.46620345e-01 1.30330041e-01 -1.76649237e+00 1.96844161e+00
-3.98050278e-01 3.95412236e-01 2.40687728e-02 -3.75253588e-01
1.03299999e+00 -1.90653905e-01 3.51804942e-01 -5.04675388e-01
-1.45124104e-02 -1.09426714e-01 -5.31575263e-01 -5.22705257e-01
7.50938594e-01 3.36105198e-01 -3.57506275e-01 4.81404305e-01
-4.82449889e-01 -1.11649132e+00 1.92713797e-01 9.50418562e-02
8.75999629e-01 3.62755686e-01 1.92472696e-01 -1.90614179e-01
2.55322397e-01 4.34643745e-01 6.04502857e-01 8.62526536e-01
1.00693084e-01 8.67919326e-01 1.12309679e-01 -5.08525372e-01
-1.19340527e+00 -1.20565474e+00 -2.80063540e-01 7.44825721e-01
5.04274011e-01 -3.35799605e-01 -4.71766859e-01 -1.57689691e-01
-7.27480203e-02 7.27050006e-01 -1.64282620e-01 1.99674800e-01
-3.12594801e-01 -7.84534931e-01 3.36810917e-01 1.42196074e-01
1.13696671e+00 -9.45641041e-01 -9.22118962e-01 -1.93117857e-01
-5.94542399e-02 -1.14461434e+00 -6.22403204e-01 -3.55404355e-02
-6.84069991e-01 -1.01783288e+00 -1.40886247e-01 -7.71054447e-01
7.83143401e-01 9.44313943e-01 9.96493995e-01 -5.86662926e-02
-6.13907754e-01 1.29877508e-01 -2.20289826e-01 -2.60647833e-01
-2.24127218e-01 -5.80075420e-02 2.33596005e-02 -1.66170359e-01
-1.13751911e-01 -6.37266815e-01 -4.88878340e-01 5.70511818e-01
-1.12367880e+00 6.88615263e-01 6.30345941e-02 5.12645543e-01
9.93233919e-01 6.46734059e-01 -1.18068457e-01 -8.74651849e-01
4.59076494e-01 -1.25528172e-01 -1.16392994e+00 7.42623508e-02
-3.02206039e-01 -4.47688363e-02 8.42326820e-01 -4.12906110e-01
-1.21191454e+00 5.15625298e-01 1.61504120e-01 -5.45575261e-01
-4.36632067e-01 9.98732671e-02 -6.30057871e-01 4.64187935e-03
7.41034746e-01 2.06161350e-01 -1.91944078e-01 -5.58215797e-01
5.80303609e-01 7.56762981e-01 5.51990628e-01 -8.11836481e-01
1.08528686e+00 4.41759616e-01 -1.99603732e-03 -9.22747374e-01
-5.52484214e-01 -7.27546290e-02 -4.97415334e-01 -1.93547696e-01
8.20437789e-01 -1.02227747e+00 -6.10689938e-01 8.61426592e-01
-1.18802035e+00 -5.43511450e-01 -1.62685037e-01 2.22416684e-01
-3.86788011e-01 2.47543529e-01 -1.58691078e-01 -4.06410515e-01
-1.77648723e-01 -1.70444643e+00 1.14835918e+00 4.48936462e-01
5.74095137e-02 -2.71770537e-01 -1.56139404e-01 3.74359220e-01
3.52720827e-01 4.44651961e-01 1.05469429e+00 2.59999722e-01
-1.25315309e+00 6.52850792e-02 -3.48918259e-01 1.53758258e-01
3.78274828e-01 5.42412460e-01 -9.25308108e-01 -6.55424893e-02
-8.16415697e-02 -4.41716492e-01 2.50413656e-01 3.22575182e-01
1.86068523e+00 7.98955187e-02 -2.08939463e-01 1.06822789e+00
1.39686203e+00 2.43136153e-01 6.71158731e-01 3.16221625e-01
7.92092800e-01 4.65898901e-01 7.00926304e-01 7.45428979e-01
5.12334347e-01 7.07501769e-01 4.76692706e-01 -1.50890410e-01
-1.65425524e-01 -3.50781888e-01 -9.76302028e-02 7.06139207e-01
1.24076389e-01 -1.66758388e-01 -7.64469683e-01 1.15537971e-01
-1.59855914e+00 -7.96134055e-01 -3.17806184e-01 2.24527502e+00
8.03037345e-01 8.32720101e-02 -2.74157822e-01 -2.40819484e-01
7.60050118e-01 3.30601364e-01 -8.37222874e-01 3.05349380e-02
-2.34620169e-01 1.70202017e-01 6.46061182e-01 9.84567851e-02
-1.06889427e+00 1.11911380e+00 6.06528616e+00 8.04237247e-01
-1.17603397e+00 -2.03463063e-01 5.72456479e-01 -1.64485514e-01
-3.57567698e-01 1.08147748e-01 -6.68958843e-01 6.52534425e-01
9.41499248e-02 -5.36109656e-02 6.79483593e-01 1.19436240e+00
3.23566377e-01 -2.93479145e-01 -7.37660170e-01 1.45469022e+00
-7.71049634e-02 -1.52636075e+00 2.72269487e-01 -4.92157266e-02
8.15315783e-01 1.08502001e-01 9.90274474e-02 2.62836809e-03
7.35346019e-01 -8.10581446e-01 8.78398478e-01 4.72673774e-01
1.19546390e+00 -6.17611647e-01 1.09735541e-01 3.88554484e-01
-1.16740799e+00 3.13217729e-01 -4.77011830e-01 1.94658767e-02
2.88311020e-02 6.66619837e-01 -6.78527236e-01 4.00913924e-01
1.14046860e+00 3.85477364e-01 -8.77453446e-01 1.05906355e+00
-6.28539100e-02 1.82230383e-01 -6.40634060e-01 -7.48038664e-02
-2.24297598e-01 -4.57920283e-01 3.04396421e-01 7.30816185e-01
4.03531313e-01 -2.97828913e-02 4.43294823e-01 9.34761047e-01
-2.15619113e-02 -5.37142307e-02 -7.72968829e-01 3.27005029e-01
8.38980794e-01 1.25471973e+00 -8.58583152e-01 -4.05298769e-02
-1.76439166e-01 1.00017405e+00 -2.50760932e-02 2.19152853e-01
-9.77174580e-01 -4.83405352e-01 8.79211843e-01 1.28306687e-01
2.25123033e-01 -7.45036006e-01 -5.34791172e-01 -1.07059765e+00
5.61564276e-03 -1.12809932e+00 3.52609307e-02 -1.29964924e+00
-1.07755005e+00 5.07409632e-01 1.65314320e-02 -1.42292392e+00
1.54809043e-01 -5.03886163e-01 -2.50554949e-01 8.91101241e-01
-1.01741445e+00 -7.20628083e-01 -9.65745151e-01 9.94738340e-01
6.17155969e-01 -1.85341254e-01 7.41245687e-01 4.94416595e-01
-6.18161798e-01 7.41223991e-02 1.25381127e-02 -2.34532245e-02
6.92559302e-01 -9.69710290e-01 7.18289554e-01 7.75666296e-01
-4.30314876e-02 5.60043752e-01 5.80871582e-01 -5.97613811e-01
-1.69824827e+00 -1.28071558e+00 2.17487216e-01 -4.26613718e-01
3.06119323e-01 -6.14315748e-01 -4.38806027e-01 3.13662916e-01
-2.90916681e-01 9.72628966e-02 5.90207934e-01 -3.15532118e-01
-2.40695357e-01 -3.85786653e-01 -1.21236897e+00 1.03983974e+00
1.31082296e+00 -4.22649980e-01 -4.91084866e-02 5.18129706e-01
9.40064490e-01 -7.07670271e-01 -4.09434170e-01 3.59598219e-01
2.65835881e-01 -1.17300844e+00 1.19021690e+00 -1.42944232e-01
3.25626582e-01 -1.09504735e+00 -5.86959660e-01 -1.02088487e+00
-2.65563488e-01 -4.73836899e-01 4.75522786e-01 1.18837345e+00
2.91022006e-02 -5.36265373e-01 5.76091170e-01 8.65798533e-01
-2.29248926e-01 -3.00362676e-01 -6.19043291e-01 -4.09443349e-01
-6.80942714e-01 -7.82386780e-01 1.13867068e+00 8.63827646e-01
-1.06475353e+00 2.23300233e-01 -3.55185509e-01 4.53804404e-01
5.98179877e-01 5.72900355e-01 1.65906024e+00 -1.17228675e+00
-3.39712083e-01 -3.39867383e-01 -2.53031880e-01 -1.25817335e+00
-4.21616763e-01 -6.14022791e-01 -5.98123996e-03 -1.46881771e+00
7.60158971e-02 -1.08495164e+00 3.20608974e-01 2.64944166e-01
-2.70566624e-02 1.42397001e-01 1.55364797e-01 3.08569759e-01
-4.00411129e-01 5.51969290e-01 1.44673121e+00 -1.38258487e-01
-2.97319561e-01 -4.79248054e-02 -6.69577539e-01 7.36663043e-01
6.87380254e-01 -4.01941746e-01 -7.58895099e-01 -6.73879504e-01
1.86415508e-01 -2.41645858e-01 6.57595932e-01 -1.23960721e+00
7.26337656e-02 -6.40250564e-01 5.74426830e-01 -9.81254160e-01
3.08423251e-01 -8.97485614e-01 6.92279637e-01 2.75883347e-01
1.37314916e-01 4.83680852e-02 1.88532576e-01 2.61870772e-01
2.26614758e-01 -5.60280979e-02 8.01919520e-01 -4.12222475e-01
-8.78556907e-01 5.47656655e-01 -1.00762978e-01 -4.39492092e-02
1.09268963e+00 -2.75554508e-01 -3.22340518e-01 9.77487937e-02
-1.24008328e-01 1.92682534e-01 1.08228803e+00 4.73336935e-01
4.53582019e-01 -1.25443685e+00 -3.32133889e-01 5.88001072e-01
2.37398252e-01 8.29346478e-01 4.36102211e-01 -4.22969684e-02
-1.16199708e+00 -8.66980851e-02 -2.34731972e-01 -8.25923562e-01
-1.25168204e+00 7.63326466e-01 1.50461584e-01 1.27987042e-01
-6.89110935e-01 6.73415661e-01 4.36403126e-01 -7.43824244e-01
-3.26699466e-02 -3.60589534e-01 2.83970386e-01 -2.05984145e-01
3.49976599e-01 1.63175538e-01 3.67394648e-02 -2.96967506e-01
-3.30609500e-01 7.24948108e-01 1.75555959e-01 1.05913077e-02
1.28382897e+00 -5.54428101e-02 -1.04856774e-01 2.44000033e-01
8.83095384e-01 1.07187927e-01 -1.65534151e+00 -2.80428175e-02
-6.40907288e-01 -8.86396825e-01 5.75313941e-02 -6.61964536e-01
-1.08512020e+00 6.55252159e-01 6.51628137e-01 1.49065197e-01
1.25596750e+00 -1.87622741e-01 6.94107890e-01 3.43824089e-01
9.78600979e-01 -1.09303379e+00 -6.44228458e-02 4.04145688e-01
7.96117961e-01 -1.20086825e+00 2.29708865e-01 -4.77891862e-01
-6.67872310e-01 9.72938359e-01 6.66527689e-01 9.41459239e-02
6.72979534e-01 5.42423666e-01 1.46546096e-01 -2.54991204e-01
-3.54511291e-01 -5.85961826e-02 -5.89885265e-02 7.81996965e-01
-6.97939992e-02 1.97614327e-01 1.62638664e-01 2.27570280e-01
-6.06439948e-01 -4.10418995e-02 3.37639540e-01 8.71125460e-01
-3.05561066e-01 -1.06111419e+00 -6.47368371e-01 4.39788729e-01
2.43048370e-01 -9.45165679e-02 -7.62318969e-02 7.11273670e-01
5.15334249e-01 8.50986660e-01 9.54316258e-02 -4.33303922e-01
3.46557170e-01 -4.39693600e-01 3.63835990e-01 -7.97128439e-01
-1.50152162e-01 -7.16695264e-02 -6.93359673e-02 -5.76619625e-01
-1.98085874e-01 -5.96166015e-01 -9.48217511e-01 -4.75176662e-01
3.83122414e-02 -3.29639971e-01 8.47680151e-01 4.74889159e-01
7.30475366e-01 4.41922128e-01 8.50571275e-01 -1.02580225e+00
-1.31248638e-01 -5.49864709e-01 -5.09931028e-01 4.74815369e-01
-7.64426440e-02 -7.83963442e-01 -1.32883176e-01 3.40342730e-01] | [9.205510139465332, -3.071375608444214] |
54c066b4-739d-4d33-8b1f-23f9d807a84d | transformation-invariant-network-for-few-shot | 2303.06817 | null | https://arxiv.org/abs/2303.06817v2 | https://arxiv.org/pdf/2303.06817v2.pdf | Transformation-Invariant Network for Few-Shot Object Detection in Remote Sensing Images | Object detection in remote sensing images relies on a large amount of labeled data for training. However, the increasing number of new categories and class imbalance make exhaustive annotation impractical. Few-shot object detection (FSOD) addresses this issue by leveraging meta-learning on seen base classes and fine-tuning on novel classes with limited labeled samples. Nonetheless, the substantial scale and orientation variations of objects in remote sensing images pose significant challenges to existing few-shot object detection methods. To overcome these challenges, we propose integrating a feature pyramid network and utilizing prototype features to enhance query features, thereby improving existing FSOD methods. We refer to this modified FSOD approach as a Strong Baseline, which has demonstrated significant performance improvements compared to the original baselines. Furthermore, we tackle the issue of spatial misalignment caused by orientation variations between the query and support images by introducing a Transformation-Invariant Network (TINet). TINet ensures geometric invariance and explicitly aligns the features of the query and support branches, resulting in additional performance gains while maintaining the same inference speed as the Strong Baseline. Extensive experiments on three widely used remote sensing object detection datasets, i.e., NWPU VHR-10.v2, DIOR, and HRRSD demonstrated the effectiveness of the proposed method. | ['Heng-Chao Li', 'Zongxin Gan', 'Turgay Celik', 'Xun Xu', 'Nanqing Liu'] | 2023-03-13 | null | null | null | null | ['few-shot-object-detection'] | ['computer-vision'] | [ 0.46006462 -0.4478689 -0.2242193 -0.4087382 -0.8394173 -0.43982652
0.51224214 0.10564432 -0.41909558 0.37379724 -0.11261969 -0.06446829
-0.3208784 -0.8854872 -0.5269628 -0.7746474 0.05490774 -0.04815278
0.6553715 -0.07412183 0.13948011 0.7078745 -1.8427715 0.02084668
0.8994558 0.9964376 0.34293565 0.4132877 0.12286953 0.54619104
-0.39763075 0.06534269 0.6984668 0.01957506 -0.41751036 0.2521506
0.9177162 -0.74388254 -0.41343248 1.0138042 0.79117924 0.4624226
0.5357039 -1.062457 -0.7069078 0.24829915 -0.9649043 0.7217778
-0.28595498 0.29717067 1.1317567 -1.4229947 0.39238515 1.074779
0.7769543 0.18938139 -1.2234828 -0.7636515 0.41870183 0.3450254
-1.8604547 -0.48635554 0.47704917 -0.4419877 0.89320743 0.1928558
0.3689067 0.5707479 -0.5017972 0.7899018 0.8183241 -0.29279032
0.35709926 0.11397755 0.33683065 0.41265583 0.39224184 0.28960043
-0.22072838 -0.07741439 0.5594634 0.5460237 -0.20785078 -0.37775669
-1.0358925 0.81768537 0.8726056 0.04522691 -0.4330963 -0.01295198
0.23472293 -0.1182145 0.62085164 0.2033135 -0.38954625 0.5308328
-0.94822216 0.17606491 0.27084965 0.9913031 0.96835256 0.10949131
-0.6258152 0.8925938 0.17207316 0.9033959 -0.03791213 -0.62564933
0.4283151 0.7734302 0.23996639 -1.1777263 -0.3947733 -0.80245996
-0.73675835 0.1430124 -0.00671568 0.06293338 -1.2129825 1.4818201
0.6937485 0.25550824 -0.16326459 0.9674545 0.94005823 0.82582814
0.0710814 0.01027633 1.2000147 -0.8742185 -0.3641135 -0.48011258
0.2892192 -0.42424712 1.1024108 -0.10440832 -0.43713358 -0.64247954
-1.1377082 0.07859813 -0.41046157 0.41059834 0.6680801 0.48894593
-0.5566625 0.29342827 -0.8291315 -0.38473263 0.8687282 0.02112709
0.13660698 -0.34205195 -0.8490713 0.51705766 0.4838852 0.29711318
-0.94096947 -1.0197234 -0.83032215 0.15165654 0.7984082 -0.17405136
1.0750986 -0.47131312 -0.8975116 0.5119018 0.04117658 -0.16139893
0.54241824 -0.36440524 -0.44654405 0.19256829 0.3262343 0.82606786
0.78777313 -1.0495912 -1.0891312 -0.49528468 0.11023314 0.16848995
-0.41098776 0.01013491 -0.3238459 -0.62973356 0.3437531 -0.6636457
-0.23204441 0.5930474 -0.24372104 -0.17575175 1.0939457 -0.29816544
1.0431793 -2.354352 -0.29183674 -0.02956512 0.18885851 0.56569827
-0.3580098 0.2333678 0.20068069 -0.10128036 -0.2829154 0.14904791
-0.13175647 0.24354343 -0.56177354 0.66081434 0.42137256 0.893944
-0.9906374 -0.415047 0.38891256 0.43306336 -0.3631525 0.07144804
-0.29216787 0.18011364 -0.5119835 1.1061485 0.8973713 -0.45543304
-0.23912185 -0.46245924 -0.2915567 -0.14458965 -1.4369612 1.2575178
-0.19852218 0.45154813 -0.19282632 -0.9275705 0.96460104 -0.0961648
0.35017282 -0.8357393 -0.05435292 0.06024161 -0.2839942 -0.51948315
0.4990387 -0.09902766 0.2231719 0.2776919 -0.23047787 0.18768384
0.16381809 0.18159974 0.74183846 0.12976693 0.4819022 -0.00815105
0.18732135 0.08070804 0.7684264 1.3348101 -0.399796 0.54303294
-0.29144734 -0.6133262 -0.87650853 -1.0419407 -0.44904733 1.4947175
0.4206625 -0.0419259 -0.10289591 -0.58680713 0.16391343 0.5003607
-0.6647226 -0.0590391 -0.2722785 -1.1602867 0.46155936 0.78885436
0.7093484 -0.6920344 -0.9134399 0.3125827 -0.1066664 -1.3003165
-0.27042857 0.06634537 -0.81297994 -0.92364174 -0.5552411 -0.5065595
0.47054982 1.300782 0.6460475 0.12001539 -0.96094626 0.03000557
-0.57827663 -0.5535533 0.19111833 0.03514534 -0.11380809 0.14385381
0.36376414 -0.49685854 -0.9007037 0.4404694 -1.0793374 -0.08710952
0.7934379 0.8130042 0.6134714 0.04548448 0.69666773 -0.6532814
-0.36091134 -0.42754722 -0.78541803 0.39000914 -0.6637199 -0.3280124
0.23724496 -0.3527762 -1.1686392 0.12208253 0.33420175 -0.29916206
-0.03749612 0.38626993 -0.06592523 -0.16381136 0.96677065 0.24641794
-0.25985268 -0.4920195 0.4299421 0.9081942 0.5402169 -0.17735904
1.137068 0.97886884 -0.25858644 -1.1423115 -1.4015068 -1.0240941
-0.6099344 0.03415324 0.55225015 -1.3073804 -0.08706519 0.5732232
-0.84623855 -0.10062587 -0.38133323 0.5115675 -0.02802396 0.22392134
-0.28591093 -0.9276339 -0.6336969 -0.6254283 1.2380421 0.31018645
0.46701202 -0.38781375 -0.12771796 0.16246648 0.58065903 0.199879
0.6341423 -0.42808187 -0.84118015 -0.3279103 -0.84887123 0.25506386
0.25901592 0.01034967 -1.0726513 -0.46925795 -0.3267468 -0.4640848
1.1190244 0.37689763 0.9286825 -0.04227509 -0.41862142 0.69734526
1.6075392 -0.06706081 0.33949786 0.2769393 0.7999943 0.3921441
0.88658196 0.74959934 0.2746144 0.7535208 0.37705407 -0.2846627
-0.12119721 0.01682389 0.01277735 0.11781389 -0.01769323 -0.02247105
-0.8192199 0.6378915 -1.8456177 -1.0565122 0.03014963 1.9480134
0.57483125 -0.15204579 -0.12160288 0.01816782 0.8383964 0.35859874
-0.94805044 0.7676311 -0.19105364 -0.01219189 0.6771513 0.11716142
-1.4617043 0.88756543 5.699066 0.7543572 -1.176489 0.20443606
0.27463582 -0.2521413 0.19170676 -0.00702361 -1.2804582 0.0401394
0.30090123 -0.13790947 0.29167366 0.9247002 0.25642616 -0.08097628
-0.8069543 0.8487101 0.16516015 -1.181487 0.08146783 -0.15430783
0.858789 0.592015 -0.11700048 0.53667176 0.08636764 -0.5191362
0.72742695 0.2263838 0.80830777 -0.3833009 0.58300227 0.41894358
-1.4967722 -0.3689816 -0.79533124 -0.04484078 -0.01534203 0.54187334
-0.75787085 0.60982007 0.8391176 0.8738812 -0.87365717 1.3076692
-0.06233734 0.50926167 -0.47547752 0.20357302 0.29747254 0.18800546
0.5933168 1.0223881 0.23806451 0.28550482 0.6259566 0.92196035
0.06585626 -0.05585217 -0.3806081 0.03323174 0.77086514 1.4849405
-0.77004933 -0.35074466 -0.48619014 0.5949027 0.17177968 0.2946723
-0.8806258 -0.4728031 0.3800202 0.05972226 0.8086829 -0.0394235
0.10581209 -1.2015812 0.12231631 -0.6706832 0.59716165 -0.49299106
-1.3504782 0.26782513 0.22465685 -1.3633289 0.3566524 -0.37134203
-0.56803864 0.4904711 -1.9717622 -1.4986913 -0.85425454 0.28111997
0.5666827 0.13182688 0.51220715 0.5612094 -0.60978353 0.48232228
0.17236261 0.07732157 0.4716673 -0.9381101 0.38547263 1.0490984
0.19412689 0.33710244 0.3516398 -0.48381487 -1.4287574 -1.7323788
0.3733826 -0.23765458 0.47028166 -0.29232103 -1.231313 0.56446016
-0.6403609 0.65348065 0.609356 -0.18836832 -0.6287239 -0.51566786
-0.8936435 0.17570654 1.2166326 -0.3350068 -0.50750643 0.51177406
0.7614461 -0.23014595 -0.40576375 0.7219022 0.52930826 -0.67612135
1.223021 -0.43106228 0.12664436 -0.66200787 -0.5215371 -0.7902117
-0.5701767 -0.02380775 -0.02822492 1.1604806 0.11051992 -0.43268615
0.5432551 0.2123414 -0.05688952 -0.4345092 -0.81547534 -1.1322803
-0.34058174 -0.18281962 0.5264891 0.8780628 -0.7074957 0.4046943
-0.3881094 0.7213805 0.9751435 0.5638701 0.9170581 -1.3355902
-0.30310708 -0.18634439 -0.3817618 -0.97637767 -0.35329568 -0.8519666
0.46216884 -1.5116645 0.57551175 -0.59392107 -0.37505907 0.7261568
-0.5007568 0.62416565 0.13943945 0.4798682 -0.78639054 0.8382675
0.84925157 -0.35486102 -0.32133186 -0.06200805 -0.5960151 0.6066281
0.6105967 -0.57752395 -0.23717603 -0.6148376 0.09195997 -0.35598588
0.6880536 -1.1526276 0.3635203 -0.30000055 0.4545702 -1.0611978
0.04011413 -0.6495359 -0.216461 0.49546698 -0.06548464 -0.50502604
0.14490755 1.0135443 0.07459556 -0.04463658 1.0663141 0.03445457
-1.1587466 0.60441774 0.05928761 -0.02667114 1.1102649 -0.30008674
-0.4532836 0.11229166 -0.36413068 0.4049795 0.0898452 0.46960026
0.49814206 -1.0644852 -0.9274337 0.17484899 0.7760611 0.30624396
0.4872604 0.86455536 -0.20717077 0.19214988 0.05241556 -0.9113454
-1.0734068 0.39321542 0.37374926 0.14355811 -0.8889033 0.7550176
0.33545706 -0.5326701 0.21500878 -0.1612408 -0.0773363 0.31884715
0.9537812 0.601936 0.10622071 -0.36811158 -0.5058835 0.5251598
-0.3295145 0.3449263 1.6302286 -0.26153573 0.19395758 0.36935344
0.7603852 -0.23372911 -1.5639666 -1.0125389 -0.11219859 -0.7194872
0.2706339 -0.71907383 -1.0149318 0.7959963 0.9836004 -0.14993648
0.92888933 0.07059474 0.5079814 0.82578295 0.30755955 -1.0226433
0.26684698 0.4714207 0.56279844 -1.6502384 0.32714215 -0.47326523
-0.20689249 0.8482539 0.691365 0.07963805 0.5519342 -0.11952488
0.04552144 -0.36981675 -0.3387842 -0.44918185 0.3377755 0.45433438
-0.17806815 0.0100935 -0.04477277 0.26926193 0.48548734 0.14009252
0.19738191 1.2993549 -0.92283946 -0.36725128 -0.34453166 0.5540554
-0.2022928 -0.30096686 -0.02688777 0.7417954 0.09171475 0.88218325
0.12658353 -0.2630725 0.46051684 -0.3602676 0.1701959 -0.9248675
-0.23432937 0.03980757 -0.38036183 -0.36174515 -0.57697666 -0.5198263
-1.1477771 0.1523975 -0.8508716 -0.23837149 0.39955902 0.89210993
0.6157732 0.29642537 0.8861445 -0.8591221 -1.2431505 -1.0667677
-0.64994305 0.27866432 0.41596684 -0.83082014 -0.53009814 -0.11677453] | [9.031524658203125, -0.8801636099815369] |
1d77dfd9-ff9f-42b5-ac19-6729547093c8 | xai-in-computational-linguistics | 2305.04631 | null | https://arxiv.org/abs/2305.04631v1 | https://arxiv.org/pdf/2305.04631v1.pdf | XAI in Computational Linguistics: Understanding Political Leanings in the Slovenian Parliament | The work covers the development and explainability of machine learning models for predicting political leanings through parliamentary transcriptions. We concentrate on the Slovenian parliament and the heated debate on the European migrant crisis, with transcriptions from 2014 to 2020. We develop both classical machine learning and transformer language models to predict the left- or right-leaning of parliamentarians based on their given speeches on the topic of migrants. With both types of models showing great predictive success, we continue with explaining their decisions. Using explainability techniques, we identify keywords and phrases that have the strongest influence in predicting political leanings on the topic, with left-leaning parliamentarians using concepts such as people and unity and speak about refugees, and right-leaning parliamentarians using concepts such as nationality and focus more on illegal migrants. This research is an example that understanding the reasoning behind predictions can not just be beneficial for AI engineers to improve their models, but it can also be helpful as a tool in the qualitative analysis steps in interdisciplinary research. | ['Senja Pollak', 'Bojan Evkoski'] | 2023-05-08 | null | null | null | null | ['unity'] | ['computer-vision'] | [-5.70575111e-02 8.75096858e-01 -6.66752100e-01 -5.41305661e-01
-4.22469527e-01 -6.90108538e-01 9.88991022e-01 3.67396951e-01
-4.87264752e-01 6.84486628e-01 1.55532861e+00 -1.19127059e+00
-1.90837517e-01 -8.40216279e-01 -3.95974696e-01 -5.75540066e-01
3.48129988e-01 7.49598861e-01 -8.19211721e-01 -7.36625731e-01
3.58944476e-01 8.16715807e-02 -1.13955319e+00 8.06829512e-01
7.99396634e-01 2.46489793e-01 -2.54730701e-01 4.12142664e-01
-4.10814494e-01 1.35692060e+00 -2.26803288e-01 -8.10467839e-01
5.75019903e-02 -5.82233906e-01 -1.33943248e+00 -4.89693046e-01
6.37915954e-02 2.96360999e-01 -2.33415961e-01 6.58369839e-01
3.96290839e-01 -4.32928562e-01 7.90373981e-01 -5.92345536e-01
-3.48718822e-01 1.45588970e+00 -1.67893961e-01 6.60357624e-02
5.90016663e-01 -2.84413248e-01 1.38272500e+00 -5.52354276e-01
8.05348217e-01 1.52705634e+00 1.01282573e+00 3.11724752e-01
-1.29315543e+00 -6.34425640e-01 1.76312104e-01 1.61628574e-01
-9.26559389e-01 -4.87366706e-01 4.18862969e-01 -1.09275424e+00
6.50466919e-01 8.71661901e-01 1.13555884e+00 1.02973950e+00
2.68589377e-01 5.36266506e-01 1.39825070e+00 -7.74452329e-01
-1.73278555e-01 5.11450291e-01 4.27126177e-02 6.03823662e-01
2.73107022e-01 -2.14627340e-01 -4.75262105e-01 -8.74109790e-02
1.54384822e-02 -2.08771676e-01 -5.69095798e-02 3.73174727e-01
-1.42123532e+00 1.33102894e+00 1.98634416e-01 7.69325614e-01
-3.35320801e-01 -2.03838438e-01 4.38995868e-01 5.37728310e-01
5.48229098e-01 7.01264501e-01 -6.52412891e-01 -4.75104928e-01
-1.32287061e+00 4.10979003e-01 1.19126916e+00 2.71453202e-01
6.77967370e-01 -2.70573735e-01 -1.32172227e-01 5.05210280e-01
3.27923566e-01 5.06569862e-01 3.06771994e-01 -1.02718902e+00
6.14173889e-01 7.58898735e-01 1.33887187e-01 -1.30504584e+00
-7.18906760e-01 -4.79630321e-01 -7.76934087e-01 -3.60138357e-01
4.14290100e-01 -4.13314641e-01 -6.69311523e-01 1.43984711e+00
-1.01981089e-01 -9.13318932e-01 1.86865553e-01 7.81028450e-01
9.11404908e-01 8.80446672e-01 1.84063166e-01 -4.72773135e-01
1.41034079e+00 -5.14658391e-01 -6.61838591e-01 -3.94845665e-01
1.12383699e+00 -7.39042044e-01 8.44085276e-01 2.40649030e-01
-8.71738315e-01 -2.72360831e-01 -4.09150690e-01 -2.64369488e-01
-3.08434516e-01 1.82403728e-01 7.71737218e-01 8.12855482e-01
-7.49005854e-01 6.39253020e-01 -5.96668184e-01 -7.18591213e-01
1.86226875e-01 1.66296259e-01 -2.30340019e-01 3.05180252e-01
-1.34432030e+00 1.23370910e+00 -3.01801171e-02 1.48962125e-01
-5.24426624e-02 -4.68694896e-01 -8.32736194e-01 -2.63510317e-01
-1.79452568e-01 -7.08615601e-01 9.97809529e-01 -1.05036485e+00
-1.00286186e+00 1.38943887e+00 -3.30522150e-01 -5.58932483e-01
7.04435527e-01 -1.20355301e-01 -3.86572808e-01 -5.72409689e-01
6.94040418e-01 4.11709815e-01 8.84659067e-02 -8.99575710e-01
-1.12282860e+00 -2.55916476e-01 9.73018631e-02 1.37876838e-01
-2.28720263e-01 3.62582356e-01 5.42640805e-01 -3.96718353e-01
5.20329833e-01 -8.66418898e-01 -3.40810835e-01 -8.29737186e-01
-3.38803053e-01 -2.72682756e-01 2.32375249e-01 -1.21770811e+00
1.62584615e+00 -1.65033972e+00 2.78834075e-01 3.04408848e-01
1.45992208e-02 -1.73764348e-01 5.60899973e-01 1.02583790e+00
-3.55203189e-02 5.66161871e-01 6.63220063e-02 3.64271283e-01
2.95102149e-01 3.61496538e-01 -6.59143627e-01 6.07313335e-01
-9.61865112e-02 6.34845257e-01 -8.29039216e-01 -5.59294164e-01
1.11466479e-02 8.64088237e-02 -7.53680706e-01 -4.99978691e-01
2.75321811e-01 6.76270485e-01 -2.52872974e-01 3.20013732e-01
7.65902475e-02 2.75877148e-01 6.60861909e-01 -1.20984286e-01
-8.28341961e-01 9.41776514e-01 -5.93507051e-01 1.03450787e+00
-7.21839190e-01 1.12902391e+00 1.89316317e-01 -1.17981148e+00
1.07761252e+00 3.39959264e-01 2.66920000e-01 -8.61281633e-01
1.55670404e-01 5.17001808e-01 4.33975428e-01 -7.59390950e-01
5.59027493e-01 -7.51889527e-01 -5.37698150e-01 5.80005527e-01
-4.85152334e-01 -2.46505275e-01 2.14201048e-01 -1.62391439e-02
6.42931283e-01 1.27912253e-01 5.43399155e-01 -7.87192285e-01
5.59901237e-01 6.14439547e-02 9.02322590e-01 4.70494300e-01
2.33924434e-01 1.88531548e-01 7.37605333e-01 -1.21306872e+00
-1.28452635e+00 -2.37643689e-01 -2.27587104e-01 1.40900922e+00
-3.93539757e-01 -8.06463361e-01 -4.98397529e-01 -1.87941968e-01
-1.88502684e-01 1.23589921e+00 -7.56028354e-01 1.98754072e-01
-7.59028673e-01 -6.54502153e-01 3.83361250e-01 1.45345107e-01
1.11681521e-01 -8.00249219e-01 -8.43222260e-01 1.50509849e-01
-9.98662829e-01 -8.13295066e-01 4.37115729e-01 3.87180537e-01
-7.47817576e-01 -7.00069666e-01 -5.53612173e-01 -9.04994190e-01
5.17121613e-01 -2.55134791e-01 1.08191240e+00 2.91853808e-02
2.27643564e-01 -1.31077439e-01 -3.33463848e-01 -8.71721208e-01
-9.50260937e-01 5.18179834e-01 2.62462616e-01 -2.75325596e-01
3.50858986e-01 -4.40306723e-01 -1.49437353e-01 7.97377899e-02
-3.13522339e-01 7.21368968e-01 2.57202566e-01 6.27638698e-01
-1.25325143e-01 -1.11256368e-01 1.19146772e-01 -1.18287742e+00
6.21716797e-01 -5.75359702e-01 1.45829782e-01 1.56191930e-01
-6.91269219e-01 1.30544543e-01 4.63709921e-01 1.52751133e-01
-9.47776794e-01 -5.06690264e-01 -2.95962721e-01 8.78616452e-01
3.26268375e-02 9.54496443e-01 1.09185651e-01 4.89079922e-01
9.16824937e-01 -2.41789203e-02 -3.77149194e-01 -4.62116033e-01
3.47359419e-01 1.11863303e+00 2.65267760e-01 -5.46566725e-01
8.00355792e-01 4.61685330e-01 -1.59862801e-01 -1.03613174e+00
-9.21297491e-01 -3.48284066e-01 -7.65258074e-01 -3.77113193e-01
7.57816255e-01 -1.09171283e+00 -6.98841751e-01 -1.70343637e-01
-9.82271016e-01 -3.24083894e-01 -2.89326727e-01 6.18399978e-01
-7.62018621e-01 -9.30416733e-02 -5.59112668e-01 -1.06516492e+00
-3.48701298e-01 -6.77051842e-01 7.81457722e-01 7.91380275e-03
-1.26972115e+00 -1.24547040e+00 2.21548438e-01 9.88725245e-01
8.80032778e-02 4.31853771e-01 1.50310910e+00 -6.39339864e-01
3.27011824e-01 1.14453927e-01 1.48288116e-01 -2.36683786e-01
1.40091911e-01 6.56796396e-02 -4.83490795e-01 -4.69506644e-02
1.09463865e-02 -2.92001758e-02 7.30699480e-01 3.69128346e-01
3.22907567e-01 -1.08940840e+00 -4.36147451e-01 3.82540226e-01
1.03789198e+00 -1.56427100e-01 5.26447058e-01 1.00471282e+00
4.38693941e-01 1.16686130e+00 7.48428047e-01 3.58087003e-01
6.74106121e-01 6.05887651e-01 -1.27444535e-01 -2.73085505e-01
1.93159074e-01 -5.56310356e-01 4.78072792e-01 1.14922845e+00
-6.67413294e-01 3.10730994e-01 -1.63239157e+00 7.34638333e-01
-2.01294923e+00 -1.28662133e+00 -6.55241072e-01 1.64766252e+00
8.76057625e-01 -5.68156876e-03 2.87505567e-01 4.89430726e-01
4.71941888e-01 3.17283422e-01 6.30598843e-01 -1.20959735e+00
-1.98083863e-01 -4.79733048e-04 4.87785846e-01 8.76066744e-01
-9.75024462e-01 1.13327265e+00 6.20820475e+00 3.21333081e-01
-9.84654129e-01 -6.69420585e-02 6.88085020e-01 1.47292167e-01
-9.41306949e-01 4.28138882e-01 -6.57258928e-01 3.77602637e-01
1.01143181e+00 -3.51200938e-01 2.03491062e-01 4.96556759e-01
8.40761304e-01 -8.26880410e-02 -8.46260726e-01 5.88203013e-01
-1.85240835e-01 -1.45735157e+00 -1.23839714e-02 2.58571744e-01
8.06152642e-01 -2.64932513e-01 -2.12115005e-01 2.22888201e-01
3.78854215e-01 -1.29496074e+00 1.36347079e+00 6.55455828e-01
4.50174838e-01 -5.70644379e-01 1.17122185e+00 7.77593374e-01
-5.39180636e-01 -4.33811039e-01 -3.54015499e-01 -1.08553112e+00
2.14148536e-01 3.73468071e-01 -1.03087211e+00 5.32334983e-01
5.60554564e-01 5.97200155e-01 -2.26754710e-01 4.77624863e-01
-5.20674884e-01 1.10944200e+00 -7.17210695e-02 -1.14731923e-01
4.88299668e-01 -3.96446198e-01 4.42320764e-01 1.69271564e+00
4.53241050e-01 3.81555796e-01 -1.68625906e-01 4.35128063e-01
4.21804786e-01 4.78814542e-01 -5.69648325e-01 -1.19316183e-01
8.45706686e-02 9.66414571e-01 -7.92419732e-01 -7.58661032e-02
-2.37214684e-01 4.23010409e-01 -7.71441013e-02 3.55752826e-01
-5.92735231e-01 -9.45734829e-02 4.63980764e-01 7.81580746e-01
-9.03618634e-02 -2.70552076e-02 -6.58121586e-01 -8.23429883e-01
-3.79674017e-01 -1.22336102e+00 2.77855933e-01 -2.94304579e-01
-5.88054061e-01 2.47806400e-01 -9.44991708e-02 -8.12807202e-01
-3.77870977e-01 -4.27773178e-01 -4.72601175e-01 7.42511511e-01
-7.93462873e-01 -1.49859869e+00 2.14932188e-01 -1.42768323e-01
1.78917140e-01 -2.49110058e-01 1.02743173e+00 1.92893967e-02
-7.22965971e-02 -9.99856964e-02 -4.54277452e-03 3.09235871e-01
3.47535044e-01 -1.04082060e+00 3.38788450e-01 3.71511787e-01
5.25089920e-01 6.24881864e-01 1.37257302e+00 -5.36725342e-01
-7.74423420e-01 -6.18718565e-01 2.13701797e+00 -5.62659860e-01
6.53136849e-01 -2.52208322e-01 -1.25376746e-01 8.19178879e-01
2.74554998e-01 -1.11952007e+00 1.08578837e+00 9.59733069e-01
5.99709190e-02 1.03397727e-01 -6.48955882e-01 8.00463259e-01
9.09004629e-01 -4.65144575e-01 -1.02418983e+00 6.09109044e-01
1.52420327e-01 -1.50351152e-01 -7.06936359e-01 2.20553741e-01
9.49426711e-01 -1.05243385e+00 5.87085009e-01 -1.17122173e+00
6.69961989e-01 6.02971353e-02 -1.00927226e-01 -1.18375432e+00
-8.25506508e-01 -5.92517436e-01 6.34139299e-01 1.25462496e+00
9.14492846e-01 -2.82301992e-01 8.56040537e-01 4.98263806e-01
7.09353611e-02 -6.35870874e-01 -1.05319631e+00 -2.04587504e-01
4.31363523e-01 -3.87239695e-01 2.93835670e-01 1.29126143e+00
5.90066314e-01 5.01594663e-01 -5.46826482e-01 -2.93449581e-01
-5.55496886e-02 4.06746387e-01 8.77103865e-01 -1.45426190e+00
1.90616965e-01 -5.22424936e-01 -4.66397494e-01 -5.10356784e-01
2.11563691e-01 -1.08807528e+00 -3.64677459e-01 -2.18687248e+00
2.25097820e-01 -8.74817297e-02 4.41544443e-01 4.58252192e-01
3.23063254e-01 -7.04604015e-02 2.77801096e-01 3.13338429e-01
-4.49657924e-02 1.55032009e-01 9.08868313e-01 -2.62487024e-01
-4.31589633e-01 4.31116492e-01 -1.16325510e+00 1.20414937e+00
7.48221219e-01 -6.88786924e-01 1.63174257e-01 -4.05315965e-01
1.30549490e+00 -5.29334694e-02 1.99161291e-01 -7.24463463e-01
7.69350156e-02 -4.98466194e-01 3.24363708e-01 -2.89557427e-01
-1.06013991e-01 -6.19914889e-01 4.85794187e-01 1.00463474e+00
-6.83559656e-01 -1.10972626e-02 -7.46584535e-02 -9.30424258e-02
-2.70261198e-01 -2.07883984e-01 1.94512784e-01 -3.45109910e-01
-1.75893322e-01 -4.00398821e-01 -8.62964272e-01 -1.54053746e-02
5.80670238e-01 -4.05692369e-01 9.97475255e-03 -9.80752289e-01
-9.90541875e-01 1.88357294e-01 4.76534724e-01 3.75993699e-01
3.67445089e-02 -1.31184065e+00 -1.26137841e+00 -2.34742507e-01
-2.21689656e-01 -6.98541462e-01 -1.53478935e-01 1.06508934e+00
-8.31408978e-01 9.26002204e-01 -7.44303837e-02 1.30543308e-02
-1.40023112e+00 3.21572297e-03 1.15399681e-01 -3.26475620e-01
-4.14688945e-01 6.82178438e-01 -4.26859260e-02 -8.48211527e-01
-7.28646517e-02 -3.11713457e-01 -4.86837417e-01 8.24502766e-01
4.94497223e-03 5.31512797e-01 -3.69258702e-01 -1.08732283e+00
-4.65843141e-01 5.98293006e-01 2.86757231e-01 -4.18402463e-01
1.60261703e+00 -3.34700674e-01 -4.09100473e-01 9.16540265e-01
7.46457994e-01 5.25154173e-01 -2.63931781e-01 1.86043218e-01
3.10346365e-01 -2.61499256e-01 -1.17652901e-01 -7.88431704e-01
-2.63018727e-01 1.00321591e+00 3.90063897e-02 5.04469216e-01
4.56678063e-01 1.44330084e-01 3.89908761e-01 2.83051968e-01
3.64662677e-01 -1.61235416e+00 -6.76551938e-01 5.54243147e-01
9.79653060e-01 -8.86201739e-01 3.62773538e-01 -8.18296373e-02
-7.67573357e-01 1.26526284e+00 -1.38918161e-01 4.84139353e-01
3.21252167e-01 -6.81688786e-02 4.86805022e-01 -2.36619502e-01
-6.16850376e-01 5.53201325e-02 1.61100879e-01 2.65703499e-01
1.14905715e+00 6.73138440e-01 -1.13791502e+00 9.21209633e-01
-1.25001955e+00 -1.81697011e-01 3.99436593e-01 3.49207461e-01
-6.70915365e-01 -1.14044201e+00 -4.73791659e-01 4.61749017e-01
-6.86484575e-01 -2.49381229e-01 -9.22840476e-01 9.46304798e-01
6.49035454e-01 9.22802925e-01 1.13133304e-01 -6.46547437e-01
1.46331817e-01 1.58736736e-01 1.51564345e-01 -4.42458451e-01
-8.49039018e-01 -2.34364927e-01 8.86003017e-01 8.57248623e-03
-7.17019856e-01 -1.04711926e+00 -9.61984873e-01 -8.22044253e-01
-3.02299391e-02 6.95439875e-01 6.37315571e-01 1.15284467e+00
-1.49396256e-01 2.18818597e-02 4.97865200e-01 -3.78027290e-01
-1.70071408e-01 -1.08490467e+00 -3.14544559e-01 3.77660692e-02
1.24307923e-01 -7.10767061e-02 -3.53973180e-01 -5.57558611e-02] | [9.098142623901367, 9.882983207702637] |
5f7a762f-d816-4081-bf77-8f1e504d39a7 | funqg-molecular-representation-learning-via | 2207.08597 | null | https://arxiv.org/abs/2207.08597v2 | https://arxiv.org/pdf/2207.08597v2.pdf | FunQG: Molecular Representation Learning Via Quotient Graphs | Learning expressive molecular representations is crucial to facilitate the accurate prediction of molecular properties. Despite the significant advancement of graph neural networks (GNNs) in molecular representation learning, they generally face limitations such as neighbors-explosion, under-reaching, over-smoothing, and over-squashing. Also, GNNs usually have high computational costs because of the large-scale number of parameters. Typically, such limitations emerge or increase when facing relatively large-size graphs or using a deeper GNN model architecture. An idea to overcome these problems is to simplify a molecular graph into a small, rich, and informative one, which is more efficient and less challenging to train GNNs. To this end, we propose a novel molecular graph coarsening framework named FunQG utilizing Functional groups, as influential building blocks of a molecule to determine its properties, based on a graph-theoretic concept called Quotient Graph. By experiments, we show that the resulting informative graphs are much smaller than the molecular graphs and thus are good candidates for training GNNs. We apply the FunQG on popular molecular property prediction benchmarks and then compare the performance of some popular baseline GNNs on the obtained datasets with the performance of several state-of-the-art baselines on the original datasets. By experiments, this method significantly outperforms previous baselines on various datasets, besides its dramatic reduction in the number of parameters and low computational costs. Therefore, the FunQG can be used as a simple, cost-effective, and robust method for solving the molecular representation learning problem. | ['Yavar Taheri Yeganeh', 'Ali Hojatnia', 'Zahra Taheri', 'Hossein Hajiabolhassan'] | 2022-07-18 | null | null | null | null | ['molecular-property-prediction'] | ['miscellaneous'] | [ 4.48581636e-01 -7.22035468e-02 -5.49886584e-01 -1.17907882e-01
-4.49338883e-01 -3.24391216e-01 3.53702903e-01 7.00437963e-01
-1.57850683e-01 1.08728433e+00 5.93847558e-02 -4.46667016e-01
-2.46865109e-01 -1.21294594e+00 -8.45676780e-01 -1.03051257e+00
-1.50011435e-01 3.05721819e-01 1.91540435e-01 -3.85723770e-01
2.98939466e-01 6.75307989e-01 -1.25443149e+00 -8.16939101e-02
1.15368676e+00 8.66308153e-01 1.46255448e-01 2.25372642e-01
-1.89768046e-01 8.18458319e-01 -3.38263661e-01 -4.07316566e-01
-1.28382102e-01 -4.45637643e-01 -6.53776169e-01 -2.91988939e-01
3.23885530e-01 1.08662330e-01 -6.00481629e-01 1.18561471e+00
6.26163840e-01 6.33954108e-01 8.14482093e-01 -8.42547536e-01
-8.07845056e-01 6.68007910e-01 -5.74440479e-01 4.55542980e-03
4.08144355e-01 8.07398260e-02 1.18027341e+00 -5.20316362e-01
6.65975511e-01 1.30433357e+00 6.70084238e-01 4.81317163e-01
-1.45772147e+00 -8.37112844e-01 3.18651676e-01 2.38404706e-01
-1.31132245e+00 -2.55308241e-01 8.33524108e-01 -2.63798952e-01
1.01786423e+00 1.42576173e-01 5.41719735e-01 1.14724588e+00
1.90684780e-01 3.48849297e-01 6.24732494e-01 -5.21422178e-02
2.68773943e-01 -4.59827036e-01 3.25674981e-01 8.67964923e-01
5.92400014e-01 -1.48530394e-01 -1.68128744e-01 -4.40121591e-01
7.52469361e-01 4.00938421e-01 -6.29174888e-01 -3.90173733e-01
-9.01238382e-01 1.01218069e+00 1.11658275e+00 2.16441840e-01
-4.77469206e-01 3.52616787e-01 4.64758396e-01 1.01517946e-01
4.31562096e-01 7.21527398e-01 -1.17910288e-01 1.93454027e-01
-4.53830421e-01 1.42049462e-01 5.13295949e-01 6.95971131e-01
8.19422722e-01 1.46183535e-01 -5.04889116e-02 7.19486952e-01
1.09838635e-01 -5.53040020e-02 3.90872389e-01 -1.85057297e-01
5.83214283e-01 9.63356137e-01 -3.28889340e-01 -1.29701793e+00
-5.97740769e-01 -5.87337434e-01 -1.39207220e+00 -2.76237547e-01
2.07388252e-01 2.38534853e-01 -1.04962778e+00 1.82312334e+00
3.06044132e-01 2.64068097e-01 3.34146693e-02 6.56743348e-01
1.13492560e+00 9.98073936e-01 5.93434751e-01 -3.27415764e-01
1.06396639e+00 -8.85736644e-01 -5.21271408e-01 1.12369239e-01
8.96552563e-01 -3.49913359e-01 8.24506879e-01 3.61357182e-01
-6.38994217e-01 -5.66671550e-01 -1.16678846e+00 -1.05570026e-01
-6.55151367e-01 -1.95299044e-01 1.38049722e+00 5.66555321e-01
-7.16681242e-01 1.24291730e+00 -5.78005135e-01 -1.52756855e-01
7.49609888e-01 6.92098081e-01 -5.77324748e-01 -3.02940726e-01
-1.27901483e+00 5.12688696e-01 9.41045403e-01 4.93659414e-02
-7.73028553e-01 -7.17021227e-01 -1.01027215e+00 1.93369702e-01
4.86033142e-01 -7.02661514e-01 5.32639682e-01 -6.47656262e-01
-1.39796591e+00 2.79319346e-01 1.05815962e-01 -3.84160876e-01
7.33616576e-02 1.38507098e-01 -3.70404899e-01 5.31160571e-02
-2.42111847e-01 3.43312144e-01 6.42605662e-01 -9.29670453e-01
1.11585790e-02 -3.14191878e-01 2.19526291e-01 1.04214959e-02
-2.37313166e-01 -4.08385932e-01 -2.56082535e-01 -6.92671597e-01
1.59482732e-02 -7.66551554e-01 -6.41724825e-01 -2.39948690e-01
-5.59818208e-01 -5.12545526e-01 3.69000286e-01 -3.33511502e-01
1.43422353e+00 -1.90931880e+00 4.95818704e-01 3.75387400e-01
7.25139737e-01 5.40212512e-01 -3.67810041e-01 5.81630647e-01
-4.62400019e-01 3.77563685e-01 -2.46063337e-01 2.03339592e-01
-3.70898962e-01 8.00556093e-02 -1.13207757e-01 4.19759393e-01
1.36782723e-02 9.95127201e-01 -1.24013495e+00 -2.41703033e-01
1.77796990e-01 6.67965889e-01 -5.89301884e-01 1.92675397e-01
-5.03476322e-01 3.09728444e-01 -7.45464802e-01 6.67676687e-01
7.53225267e-01 -6.06157959e-01 4.66808558e-01 -4.20851976e-01
2.47374251e-01 4.36638683e-01 -8.48910153e-01 1.60994053e+00
-1.93194747e-01 1.16294563e-01 -4.58365589e-01 -1.35026550e+00
1.11078691e+00 5.35961576e-02 2.99199730e-01 -5.93164384e-01
9.31908190e-02 3.09718132e-01 1.93477660e-01 -1.66915298e-01
2.43600130e-01 -1.95759833e-01 3.51531595e-01 2.19447747e-01
1.36357352e-01 2.26049304e-01 3.65224123e-01 2.94831604e-01
9.47574556e-01 2.21971348e-02 7.45344877e-01 -1.32037342e-01
7.28764176e-01 -4.43137616e-01 5.38347304e-01 4.72668350e-01
2.08107248e-01 1.41409904e-01 7.54646659e-01 -6.40299439e-01
-6.28668904e-01 -5.99421144e-01 4.94861268e-02 1.12042773e+00
1.78674147e-01 -9.31992352e-01 -5.37854970e-01 -7.71040261e-01
-2.84156930e-02 4.28563297e-01 -6.42458320e-01 -5.50463498e-01
-5.73771179e-01 -1.13202357e+00 3.47979248e-01 3.89972329e-01
2.82799810e-01 -1.06318510e+00 2.92841733e-01 5.28156400e-01
1.19308040e-01 -7.85788774e-01 -3.65449250e-01 2.70951152e-01
-1.03084064e+00 -1.27686477e+00 -6.34078681e-01 -5.89703918e-01
8.02903235e-01 5.44940412e-01 1.08798075e+00 4.21751887e-01
-1.61927477e-01 -4.09888268e-01 -3.39206755e-01 -1.89682603e-01
-3.03324938e-01 3.39863181e-01 -4.64821756e-02 -5.33005968e-02
7.28566200e-02 -9.04293895e-01 -9.00906563e-01 5.74372821e-02
-1.05526495e+00 7.11253509e-02 7.15901375e-01 9.17711556e-01
9.24390018e-01 8.18911940e-02 8.61833453e-01 -1.22730339e+00
6.46555364e-01 -6.02069080e-01 -4.93387401e-01 2.77962118e-01
-6.53816402e-01 4.81577694e-01 1.30531871e+00 -5.03844440e-01
-4.85616505e-01 -1.72733497e-02 -3.25389355e-01 -3.38887036e-01
2.92615056e-01 8.99651647e-01 -3.41924697e-01 -6.59541667e-01
7.40831494e-01 3.01737487e-01 -1.70983419e-01 -5.14755428e-01
4.25724387e-01 2.40719110e-01 4.33641225e-02 -7.02055871e-01
6.13356233e-01 -1.28426477e-02 6.79430187e-01 -8.42521548e-01
-7.05424249e-01 -3.37916106e-01 -3.84638399e-01 2.88602889e-01
4.91037011e-01 -6.79179668e-01 -9.89073336e-01 1.31374434e-01
-1.04492164e+00 3.87263745e-02 1.58741310e-01 2.77130336e-01
-2.52834171e-01 9.01707530e-01 -5.85966945e-01 -5.08460820e-01
-7.27725148e-01 -1.29811597e+00 7.06235707e-01 2.74377286e-01
1.04087532e-01 -1.14334595e+00 1.00389086e-01 2.24507645e-01
2.78430134e-01 6.95576012e-01 1.51817644e+00 -7.96992719e-01
-6.02769256e-01 -1.47274867e-01 -3.68208289e-01 1.09601654e-01
3.72970790e-01 -4.03730087e-02 -7.51156688e-01 -5.27105689e-01
-5.87076485e-01 -4.41455305e-01 1.18521714e+00 2.69229978e-01
1.61919570e+00 -4.66628522e-01 -6.06230080e-01 8.96479249e-01
1.48535478e+00 2.09012881e-01 6.38770580e-01 1.28991697e-02
1.09541512e+00 2.91578561e-01 2.55570114e-01 1.89179450e-01
7.65594095e-02 6.13951325e-01 6.22433722e-01 -1.85306579e-01
-1.14501575e-02 -6.35778368e-01 2.41745979e-01 1.01263404e+00
-7.24587142e-01 -5.80045462e-01 -5.24313509e-01 -1.93407293e-02
-1.95504105e+00 -8.67859304e-01 -7.21402839e-02 2.27358580e+00
8.06943834e-01 6.70559984e-03 1.74379617e-01 -2.87181064e-02
6.85608149e-01 4.26787645e-01 -7.51851678e-01 -3.36724371e-01
-6.46688864e-02 5.50831497e-01 4.63068366e-01 2.57944793e-01
-1.01915193e+00 1.07586741e+00 5.70852709e+00 1.21532214e+00
-1.16133678e+00 -4.14415449e-01 7.12729812e-01 4.07467335e-01
-3.23263854e-01 -4.63542379e-02 -6.55151784e-01 4.29640144e-01
9.99100149e-01 -2.42265001e-01 5.13397872e-01 9.77142751e-01
-7.06257969e-02 4.00879413e-01 -1.14522588e+00 1.17718780e+00
-4.22939397e-02 -1.83466566e+00 7.67768681e-01 1.41077757e-01
5.16754270e-01 -1.65369526e-01 -1.70062140e-01 3.08970124e-01
1.19493484e-01 -1.47145224e+00 2.82817353e-02 2.75643855e-01
8.74857306e-01 -1.04050338e+00 6.81373298e-01 7.71154910e-02
-1.50830364e+00 2.78743058e-01 -9.62227941e-01 7.09250476e-03
-2.24708110e-01 5.06326377e-01 -6.11987233e-01 1.10385883e+00
3.96053866e-02 1.10196364e+00 -5.23607850e-01 1.01230729e+00
-2.95076966e-01 5.26030898e-01 -4.51129228e-02 -3.95676315e-01
3.94271076e-01 -6.16650283e-01 1.99125171e-01 1.05286360e+00
2.05265760e-01 2.53981829e-01 3.43040109e-01 8.45644593e-01
-7.33288169e-01 4.23627496e-01 -7.80353248e-01 -4.90300864e-01
2.10513428e-01 1.28039908e+00 -6.63445175e-01 -2.97164172e-01
-3.04003447e-01 6.59738004e-01 7.40599513e-01 3.96530449e-01
-7.64406860e-01 -6.70700788e-01 6.39178514e-01 7.68520981e-02
1.90833554e-01 1.33469356e-02 3.16745907e-01 -1.12382138e+00
-3.19095254e-01 -1.08858800e+00 5.84507406e-01 -4.42078739e-01
-1.36630142e+00 7.90750742e-01 -3.48301947e-01 -1.01772380e+00
1.12130329e-01 -9.07361925e-01 -4.97156769e-01 6.96648657e-01
-1.69751847e+00 -9.24444199e-01 -3.02118421e-01 5.01932859e-01
1.86041504e-01 -2.18465030e-02 9.71541047e-01 3.41318250e-01
-8.63696814e-01 5.94915032e-01 2.50548631e-01 -1.15746297e-01
4.44392562e-01 -1.07957423e+00 3.36066723e-01 4.10684466e-01
8.64306167e-02 9.58983183e-01 3.85687292e-01 -6.31837010e-01
-1.60826492e+00 -1.32258427e+00 3.89616191e-01 -1.54104948e-01
7.52404153e-01 -4.45288509e-01 -1.22520351e+00 4.55766618e-01
-3.77433538e-01 1.61315739e-01 8.83744359e-01 2.82665104e-01
-6.09580398e-01 -7.81109557e-02 -8.43219876e-01 5.60103595e-01
1.32376909e+00 -4.38264668e-01 -2.98700690e-01 7.16653585e-01
9.36387420e-01 -1.59265250e-01 -1.02253664e+00 4.69013870e-01
3.82077962e-01 -7.80714750e-01 1.20976436e+00 -1.02670228e+00
3.92097265e-01 -2.29918227e-01 3.16099077e-03 -1.39153230e+00
-7.47865438e-01 -9.21928704e-01 -2.07831815e-01 8.35131884e-01
4.18254942e-01 -8.29722345e-01 8.00865054e-01 1.10871106e-01
-1.39147535e-01 -1.14035225e+00 -7.29368269e-01 -6.75536036e-01
1.77657809e-02 6.43000081e-02 7.97485650e-01 9.87261117e-01
2.96072178e-02 8.34820151e-01 -5.47661543e-01 -1.87180504e-01
5.81063151e-01 2.76573479e-01 7.02828586e-01 -1.49898660e+00
-2.66523153e-01 -5.69445431e-01 -8.56347024e-01 -1.11739421e+00
2.09323630e-01 -1.26995707e+00 -4.00070071e-01 -1.46721327e+00
4.17274177e-01 -2.97030717e-01 -6.54134393e-01 4.93285179e-01
-4.94233161e-01 -5.21726869e-02 -2.81062312e-02 1.89339563e-01
-7.10889995e-01 7.98627496e-01 1.63432515e+00 -3.57348859e-01
-3.29126418e-01 -1.28460592e-02 -9.40532923e-01 4.77072984e-01
6.84603035e-01 -3.74884754e-01 -4.81796622e-01 2.04834446e-01
4.41850245e-01 -3.40983607e-02 -1.07388407e-01 -8.40281904e-01
4.06936854e-02 -2.82359421e-01 3.88264716e-01 -3.46745878e-01
2.87090689e-01 -4.28682894e-01 2.80681670e-01 6.29597962e-01
-1.54942915e-01 -1.94123849e-01 1.27611801e-01 9.73099172e-01
-1.96642473e-01 -7.92367384e-02 8.65854442e-01 -1.91840187e-01
-4.67255682e-01 9.84810770e-01 1.70398906e-01 -2.44771168e-01
8.98389637e-01 -2.95239776e-01 -5.70190549e-01 -2.35939547e-01
-3.19925815e-01 4.47012559e-02 4.18091118e-01 1.20652407e-01
7.42361784e-01 -1.32491887e+00 -3.36028844e-01 3.33385244e-02
2.94768244e-01 1.12720206e-01 2.44662151e-01 6.19853616e-01
-7.09857821e-01 5.46617448e-01 -1.82333320e-01 -1.96490452e-01
-1.12985611e+00 8.97159636e-01 2.41722882e-01 -6.27763748e-01
-6.43872976e-01 7.23197222e-01 6.63075030e-01 -3.04880053e-01
1.39308393e-01 -4.46113139e-01 -3.91376704e-01 -1.18391244e-02
5.02592325e-01 3.45405966e-01 1.33005735e-02 -5.38909912e-01
-3.21137011e-01 7.71967828e-01 -3.35085988e-01 1.09966946e+00
1.57151866e+00 5.33439457e-01 -3.15416992e-01 3.88676854e-04
1.24079001e+00 -1.37536719e-01 -9.08217788e-01 -1.85710818e-01
-1.84537515e-01 -2.00256556e-01 -1.74288582e-02 -3.58723044e-01
-1.07792747e+00 9.59906638e-01 2.23747373e-01 1.82212949e-01
8.99010420e-01 -7.80066550e-02 7.59635150e-01 7.71783233e-01
2.76362836e-01 -5.77386975e-01 1.07520044e-01 3.01149428e-01
8.03814113e-01 -1.08405328e+00 5.79832375e-01 -7.38198817e-01
-3.06000501e-01 1.32826030e+00 4.66614872e-01 -1.21094391e-01
4.24642980e-01 -6.36551201e-01 -5.66773176e-01 -4.20046121e-01
-5.46449065e-01 -1.20461702e-01 5.68555176e-01 6.19880617e-01
6.76924825e-01 2.08765134e-01 -2.87914485e-01 4.86571580e-01
9.43992287e-02 -1.78970233e-01 1.79726675e-01 5.40735245e-01
-4.64179397e-01 -1.30808699e+00 1.37478441e-01 6.04194820e-01
-4.21219915e-01 -3.32229674e-01 -5.61326146e-01 7.86850095e-01
-4.87993509e-02 6.12653255e-01 -6.40002847e-01 -4.54483241e-01
2.67695397e-01 -2.16039881e-01 5.59156716e-01 -6.58021390e-01
-4.15426403e-01 -2.16726780e-01 6.12397306e-02 -6.87211573e-01
-5.05860746e-01 9.31988880e-02 -1.27036691e+00 -5.62065005e-01
-5.06110847e-01 3.53301793e-01 2.07146436e-01 6.41589165e-01
6.07867062e-01 6.11574471e-01 5.43220401e-01 -8.02059233e-01
-5.14619887e-01 -8.73642266e-01 -5.35153985e-01 6.12122595e-01
1.71064138e-01 -8.56312752e-01 -2.21046448e-01 -4.78762150e-01] | [5.142967700958252, 5.907784938812256] |
f3d69b3b-79ef-4d6f-a712-d5d205e05f94 | elegansnet-a-brief-scientific-report-and | 2304.13538 | null | https://arxiv.org/abs/2304.13538v1 | https://arxiv.org/pdf/2304.13538v1.pdf | ElegansNet: a brief scientific report and initial experiments | This research report introduces ElegansNet, a neural network that mimics real-world neuronal network circuitry, with the goal of better understanding the interplay between connectome topology and deep learning systems. The proposed approach utilizes the powerful representational capabilities of living beings' neuronal circuitry to design and generate improved deep learning systems with a topology similar to natural networks. The Caenorhabditis elegans connectome is used as a reference due to its completeness, reasonable size, and functional neuron classes annotations. It is demonstrated that the connectome of simple organisms exhibits specific functional relationships between neurons, and once transformed into learnable tensor networks and integrated into modern architectures, it offers bio-plausible structures that efficiently solve complex tasks. The performance of the models is demonstrated against randomly wired networks and compared to artificial networks ranked on global benchmarks. In the first case, ElegansNet outperforms randomly wired networks. Interestingly, ElegansNet models show slightly similar performance with only those based on the Watts-Strogatz small-world property. When compared to state-of-the-art artificial neural networks, such as transformers or attention-based autoencoders, ElegansNet outperforms well-known deep learning and traditional models in both supervised image classification tasks and unsupervised hand-written digits reconstruction, achieving top-1 accuracy of 99.99% on Cifar10 and 99.84% on MNIST Unsup on the validation sets. | ['Roberto Tagliaferri', 'Pietro Liò', 'Andrea Terlizzi', 'Francesco Bardozzo'] | 2023-04-06 | null | null | null | null | ['tensor-networks'] | ['methodology'] | [-1.88602671e-01 1.57358691e-01 3.46090808e-03 -7.26101622e-02
7.09682345e-01 -4.43316519e-01 5.72501421e-01 -2.34915972e-01
-4.76373911e-01 1.02070189e+00 -1.35875285e-01 -3.07044864e-01
-5.75297892e-01 -8.80855560e-01 -8.68700564e-01 -7.29605258e-01
-6.12060905e-01 5.15746653e-01 3.42631072e-01 -4.23650563e-01
1.48574591e-01 5.19229472e-01 -1.21624517e+00 3.02692771e-01
7.95023739e-01 1.17516804e+00 2.36087009e-01 6.10278964e-01
-8.75246301e-02 9.42494810e-01 -3.78952295e-01 -7.19357908e-01
2.87349820e-01 -1.32029861e-01 -1.00066137e+00 -4.20617908e-01
5.43338716e-01 6.06338046e-02 -7.14709640e-01 1.13043714e+00
2.34466329e-01 -2.47055188e-01 6.48771226e-01 -1.16923177e+00
-1.00920594e+00 1.10908258e+00 2.44959001e-03 6.60608232e-01
-2.30169713e-01 3.98284882e-01 1.16109848e+00 -6.96983695e-01
6.77686393e-01 1.20057905e+00 1.06207740e+00 4.89685386e-01
-1.44632304e+00 -8.57666314e-01 -1.53314676e-02 2.74179459e-01
-1.09669197e+00 -8.75097066e-02 4.56093252e-01 -5.48806310e-01
1.44745684e+00 -3.64225656e-01 1.18920708e+00 1.28114676e+00
6.27099752e-01 1.97161555e-01 1.07875550e+00 3.81681472e-02
3.35975140e-01 -3.51908147e-01 2.05960795e-01 1.06711161e+00
6.74413264e-01 -5.75124919e-02 -4.23613459e-01 6.79350123e-02
1.03743470e+00 1.63792342e-01 -1.90965489e-01 -1.07532889e-01
-1.81114006e+00 3.57314557e-01 1.19985807e+00 6.64677143e-01
-5.71234286e-01 7.46061802e-01 5.33276677e-01 5.26033938e-01
2.18879618e-02 8.27765942e-01 -5.56146383e-01 1.24074951e-01
-6.15728676e-01 -2.35800799e-02 8.94838870e-01 6.62227511e-01
6.64245367e-01 5.90801716e-01 3.62645864e-01 7.06179202e-01
2.00610399e-01 2.71764070e-01 8.00295174e-01 -1.03198218e+00
2.80232817e-01 1.02900052e+00 -6.71047091e-01 -1.10662091e+00
-6.93584621e-01 -9.61519957e-01 -1.52295077e+00 1.42431349e-01
5.39133132e-01 2.09966805e-02 -5.44071853e-01 1.59668255e+00
-9.34540331e-02 2.34274551e-01 1.63755998e-01 7.58667886e-01
7.47895837e-01 5.22314250e-01 -2.05408335e-02 4.16016281e-01
1.19415104e+00 -7.88324773e-01 -2.35229224e-01 5.72469011e-02
4.77186233e-01 -1.27872573e-02 6.91642404e-01 5.46803772e-01
-9.32378769e-01 -4.72684801e-01 -1.21112430e+00 -9.94164720e-02
-8.67051899e-01 4.59431037e-02 1.10376251e+00 4.47618693e-01
-1.43322098e+00 1.02795696e+00 -7.42147446e-01 -5.02311230e-01
8.21775079e-01 7.45083988e-01 -6.04162514e-01 7.82816634e-02
-1.06813431e+00 8.88097525e-01 7.51732469e-01 -1.51289582e-01
-1.19702864e+00 -7.90004790e-01 -1.95502102e-01 3.46362293e-01
-2.20210806e-01 -1.08262539e+00 7.88482904e-01 -9.19803619e-01
-1.42509055e+00 5.23357868e-01 5.70039511e-01 -1.07425976e+00
1.00817144e-01 2.27888063e-01 -1.36716217e-01 4.11232293e-01
-2.94923544e-01 1.21608269e+00 3.27593416e-01 -6.99794888e-01
-1.41340137e-01 -1.80660903e-01 3.51842701e-01 -3.25294822e-01
-7.34478772e-01 -3.82172048e-01 1.31784186e-01 -6.60610795e-01
6.18243665e-02 -9.20056701e-01 -1.68684810e-01 5.61732948e-01
-7.28615582e-01 -2.12930962e-01 6.09339893e-01 -2.80987591e-01
6.00241780e-01 -1.67204475e+00 4.24672633e-01 1.92224666e-01
8.81187379e-01 2.77542442e-01 -4.98196870e-01 2.07914665e-01
-3.99393231e-01 2.59002179e-01 -7.97818825e-02 9.23226550e-02
-2.80537188e-01 3.05797935e-01 -2.66448362e-03 4.59372044e-01
3.30645710e-01 9.68611896e-01 -9.83694255e-01 -1.46723688e-01
-2.00542924e-03 6.14649951e-01 -6.88736379e-01 -3.77966136e-01
-1.96519956e-01 2.41629943e-01 -2.27910265e-01 6.33162022e-01
1.99872136e-01 -5.80538213e-01 2.69496739e-01 -3.74392420e-01
1.55223235e-01 4.26463246e-01 -4.21076536e-01 1.64758062e+00
-1.47142321e-01 1.03269637e+00 -2.29768634e-01 -1.51391387e+00
1.05650353e+00 2.12491825e-01 5.25659382e-01 -6.72614872e-01
2.14028269e-01 2.20042929e-01 7.41259992e-01 -1.93487436e-01
-1.92999586e-01 2.28785038e-01 3.13063592e-01 3.33619624e-01
8.41641188e-01 9.72295254e-02 4.41337556e-01 3.68067294e-01
1.49676466e+00 -2.05095902e-01 1.73683867e-01 -7.86168933e-01
2.53133178e-01 -7.27044493e-02 2.59954602e-01 4.35330272e-01
-9.43959057e-02 7.52142295e-02 7.00322151e-01 -8.26573968e-01
-1.41394472e+00 -1.05358291e+00 -1.85871944e-01 9.60038006e-01
-2.03372955e-01 -8.90026838e-02 -1.01915741e+00 -2.36738414e-01
-3.12943086e-02 7.48016387e-02 -9.18935597e-01 -1.77956372e-01
-3.28016520e-01 -8.27091813e-01 1.34014988e+00 4.05648649e-01
9.25257206e-01 -1.11922872e+00 -5.40473878e-01 2.40880132e-01
8.79869759e-02 -1.09687185e+00 2.69871235e-01 4.52671438e-01
-1.30699384e+00 -1.34706676e+00 -7.08168626e-01 -8.21560085e-01
5.47010005e-01 -3.25537473e-02 1.18911135e+00 2.55459070e-01
-3.71930361e-01 -4.30076532e-02 3.94072421e-02 -9.78127196e-02
-2.05739081e-01 3.64143670e-01 4.04423594e-01 -2.53569841e-01
4.28815596e-02 -1.12787831e+00 -6.46019518e-01 3.51558328e-01
-7.79093444e-01 8.87614191e-02 8.38384926e-01 1.12767720e+00
4.21856731e-01 1.58978462e-01 7.26097345e-01 -5.77917635e-01
5.79927981e-01 -8.83968651e-01 -3.87207508e-01 1.22608460e-01
-6.10396683e-01 2.32911229e-01 9.39520061e-01 -7.21194029e-01
-4.17828619e-01 -6.60854951e-02 1.70754626e-01 -3.65588725e-01
3.04323714e-02 5.18312871e-01 1.52641550e-01 -4.45046335e-01
9.60807502e-01 3.99788886e-01 5.40628247e-02 -4.23390627e-01
2.66454294e-02 1.07060492e-01 5.71999431e-01 -6.08181536e-01
5.82480729e-01 3.56277645e-01 4.16549504e-01 -7.19814718e-01
-3.47850263e-01 5.41115999e-02 -8.64289880e-01 -3.05596858e-01
6.85832620e-01 -6.83275521e-01 -1.03616619e+00 5.43906033e-01
-1.26905203e+00 -4.56243992e-01 -1.40330076e-01 3.83568436e-01
-3.54798734e-01 4.97029163e-02 -1.09161007e+00 -2.57457167e-01
-4.61037844e-01 -8.95608783e-01 3.74865353e-01 8.72772634e-02
-1.16385072e-01 -1.26641607e+00 1.14083171e-01 1.45782724e-01
8.10855687e-01 3.10259581e-01 1.40184009e+00 -6.15914345e-01
-6.90456450e-01 -1.64689515e-02 -5.50726235e-01 3.87127399e-01
-2.15271652e-01 1.83272704e-01 -9.34511244e-01 -1.31761376e-02
-5.40989041e-01 -4.35819834e-01 1.06886637e+00 1.63871348e-01
1.19493997e+00 -6.40261948e-01 -3.30869913e-01 6.38395727e-01
1.39294779e+00 -8.90468433e-02 7.64248133e-01 4.15199339e-01
5.71758687e-01 6.41751289e-01 -7.66740084e-01 -1.32992100e-02
3.72324377e-01 1.11788444e-01 1.01322067e+00 7.33627528e-02
-3.80334169e-01 2.01080758e-02 2.65116036e-01 1.17033303e+00
-5.97297907e-01 -2.41294429e-01 -1.21425426e+00 4.19494689e-01
-1.57473254e+00 -1.05933845e+00 -1.84794903e-01 1.59840047e+00
6.45780504e-01 3.83044302e-01 4.30250876e-02 4.52359706e-01
6.58903539e-01 -4.21265751e-01 -8.84656250e-01 -3.16172034e-01
-6.01241291e-01 3.24179500e-01 4.54039156e-01 -2.97416776e-01
-8.14828694e-01 6.78168416e-01 7.04336834e+00 4.03458089e-01
-1.32718849e+00 1.55740649e-01 6.63123071e-01 -1.08617947e-01
8.34351033e-02 -3.85624617e-01 -3.72776896e-01 3.75706285e-01
1.27616942e+00 1.15245670e-01 9.32548225e-01 7.83365071e-01
-1.09250732e-01 4.28909302e-01 -1.16429746e+00 8.47993135e-01
-3.80517542e-01 -1.88715506e+00 2.83834696e-01 3.45569849e-01
8.32679927e-01 8.45632076e-01 1.74584731e-01 3.86873066e-01
5.33063471e-01 -1.32434571e+00 6.65549338e-01 8.05203795e-01
6.26105428e-01 -3.77317846e-01 7.39822447e-01 2.63624191e-01
-1.03890133e+00 -5.13232470e-01 -8.40237975e-01 -4.21795726e-01
-5.33777893e-01 8.39869916e-01 -6.82483912e-01 1.96701977e-02
9.91502166e-01 1.11716759e+00 -7.31915414e-01 1.49911845e+00
1.30882010e-01 7.74236262e-01 -4.22298193e-01 -4.30621803e-01
4.36960280e-01 5.54298274e-02 3.38073313e-01 1.31225967e+00
2.76210099e-01 -1.46150187e-01 -2.88694799e-01 1.44581938e+00
-7.21844494e-01 -1.68801293e-01 -8.31186116e-01 -4.39735413e-01
4.37398016e-01 1.38935912e+00 -9.20687258e-01 -4.45006490e-01
-8.36847872e-02 5.24736226e-01 6.24869227e-01 4.17975396e-01
-6.33388042e-01 -3.70036393e-01 8.16703141e-01 1.07716866e-01
2.67541528e-01 -2.93225676e-01 -4.21145797e-01 -1.02248585e+00
-4.47969556e-01 -7.03937948e-01 -1.14087932e-01 -8.63460958e-01
-1.52277648e+00 8.76375139e-01 -5.01208007e-01 -9.67176795e-01
1.81118011e-01 -1.21785486e+00 -8.28380466e-01 4.01038617e-01
-1.21872652e+00 -9.14490461e-01 -2.12890133e-01 7.46289611e-01
1.68382570e-01 -5.52928209e-01 9.63946104e-01 3.36969674e-01
-7.59113073e-01 3.26839358e-01 2.62305349e-01 4.20386672e-01
-4.73983400e-02 -1.22752881e+00 5.31425297e-01 4.55003679e-01
1.21927999e-01 9.47584391e-01 3.26170415e-01 -3.09581131e-01
-1.43572962e+00 -1.29685104e+00 4.43182528e-01 5.23233004e-02
1.06492519e+00 -3.54400486e-01 -8.53631794e-01 4.67541158e-01
3.81621510e-01 4.14290518e-01 4.36490148e-01 -9.76349711e-02
-7.93775022e-01 -2.73169696e-01 -1.25325203e+00 4.99508411e-01
1.36467135e+00 -4.80171859e-01 -5.17102063e-01 3.50407392e-01
6.24131262e-01 3.41859818e-01 -1.21867800e+00 5.33040911e-02
7.38917291e-01 -9.51036632e-01 1.05623996e+00 -8.69717658e-01
7.34054923e-01 -1.04506016e-01 -1.38060227e-01 -1.50769317e+00
-7.16925442e-01 -4.75268096e-01 -2.61796951e-01 7.10818827e-01
5.45198202e-01 -8.78798246e-01 7.17644095e-01 2.69388016e-02
-2.37819448e-01 -8.84690106e-01 -1.04788411e+00 -9.11450982e-01
2.96185613e-01 -4.10428271e-02 5.60341239e-01 1.12036061e+00
1.12924404e-01 5.59594154e-01 1.62039608e-01 -3.13793302e-01
6.80299997e-01 -4.25052553e-01 2.92346179e-01 -1.82582188e+00
-2.36357704e-01 -1.00246465e+00 -1.04778063e+00 -7.56981969e-01
2.49180853e-01 -1.14163446e+00 -4.45277303e-01 -1.38922310e+00
1.46061406e-01 -6.52762771e-01 -7.03448176e-01 8.26148152e-01
6.79016173e-01 6.19140267e-01 5.68442382e-02 2.60049969e-01
-6.14451766e-01 3.70425284e-01 1.42483318e+00 -5.90267956e-01
3.70585591e-01 -3.57599258e-01 -6.24953389e-01 8.34132493e-01
9.96004641e-01 -3.84599417e-01 -2.84273505e-01 -5.77627063e-01
5.28048635e-01 -3.03175330e-01 6.55631721e-01 -1.64571655e+00
4.06880289e-01 2.07828954e-01 5.91111898e-01 -3.32184397e-02
4.55217034e-01 -7.40767419e-01 1.24043867e-01 1.06308722e+00
-5.74208975e-01 2.65053183e-01 6.60797656e-02 5.47057569e-01
4.27073501e-02 6.88336119e-02 6.72226846e-01 -2.95898378e-01
-4.52942103e-01 3.25604349e-01 -7.35767186e-01 -4.86228801e-02
8.34045410e-01 -3.66766661e-01 -9.53088343e-01 -2.72157369e-04
-5.39711356e-01 -2.17118353e-01 1.51316091e-01 1.24675699e-01
6.80761516e-01 -1.11761785e+00 -5.12810349e-01 -1.88457638e-01
-1.68939933e-01 -3.22390616e-01 -1.51048511e-01 8.53802800e-01
-8.74372423e-01 7.28839695e-01 -1.05772853e+00 -6.89757049e-01
-5.06338060e-01 3.97007763e-01 7.47090757e-01 -2.17898220e-01
-4.86179531e-01 9.46397960e-01 2.02246699e-02 -6.57352567e-01
2.02180550e-01 -9.49010611e-01 -2.46992782e-01 -3.91927928e-01
2.44618505e-01 4.43345696e-01 -7.14453496e-03 -5.24360538e-01
-2.44081154e-01 3.11809689e-01 1.81734011e-01 6.23755634e-01
1.65936601e+00 2.22962752e-01 -5.61964333e-01 3.38449895e-01
1.02406800e+00 -7.91660011e-01 -1.02780020e+00 -1.87318429e-01
7.92412758e-02 4.09207851e-01 1.24230914e-01 -1.03809011e+00
-1.47653413e+00 1.19763708e+00 6.25203192e-01 3.45784068e-01
8.24398875e-01 -2.96224028e-01 7.67314911e-01 1.28907168e+00
5.99368870e-01 -5.53559363e-01 4.80194628e-01 8.59498203e-01
8.23826194e-01 -7.85497129e-01 -1.95940718e-01 -1.44640028e-01
-1.51790425e-01 1.53931963e+00 7.63641357e-01 -6.27149522e-01
8.15238357e-01 3.32589269e-01 -6.01554096e-01 -3.92607987e-01
-1.14340138e+00 2.40971953e-01 1.57211766e-01 7.63445735e-01
4.07519281e-01 1.07543491e-01 3.75105053e-01 3.93018663e-01
-4.43854690e-01 1.44790098e-01 5.27802587e-01 3.18922311e-01
-5.77320576e-01 -4.35928017e-01 -2.66280826e-02 7.18407452e-01
-4.96812820e-01 -3.58065158e-01 -5.53168237e-01 6.51489794e-01
3.30249935e-01 4.51600432e-01 1.72770664e-01 -6.55631959e-01
-1.57768741e-01 -3.32013071e-02 4.78178561e-01 -3.59136671e-01
-9.48404312e-01 -6.54815316e-01 -2.24083252e-02 -5.07239282e-01
-4.09979135e-01 8.30187201e-02 -1.35386360e+00 -7.44666576e-01
-2.46761516e-01 -1.50168955e-01 9.15492892e-01 9.57073212e-01
4.84471262e-01 8.04308474e-01 1.35200635e-01 -1.25056803e+00
-2.84023762e-01 -1.14644682e+00 -3.82071435e-01 1.36736482e-01
1.88955113e-01 -7.65541017e-01 -3.41303572e-02 1.61377206e-01] | [9.274300575256348, 2.6163768768310547] |
633799e2-8d63-4d4e-b3e2-33cee3ab9ca9 | rgb-t-object-trackingbenchmark-and-baseline | 1805.08982 | null | http://arxiv.org/abs/1805.08982v1 | http://arxiv.org/pdf/1805.08982v1.pdf | RGB-T Object Tracking:Benchmark and Baseline | RGB-Thermal (RGB-T) object tracking receives more and more attention due to
the strongly complementary benefits of thermal information to visible data.
However, RGB-T research is limited by lacking a comprehensive evaluation
platform. In this paper, we propose a large-scale video benchmark dataset for
RGB-T tracking.It has three major advantages over existing ones: 1) Its size is
sufficiently large for large-scale performance evaluation (total frame number:
234K, maximum frame per sequence: 8K). 2) The alignment between RGB-T sequence
pairs is highly accurate, which does not need pre- or post-processing. 3) The
occlusion levels are annotated for occlusion-sensitive performance analysis of
different tracking algorithms.Moreover, we propose a novel graph-based approach
to learn a robust object representation for RGB-T tracking. In particular, the
tracked object is represented with a graph with image patches as nodes. This
graph including graph structure, node weights and edge weights is dynamically
learned in a unified ADMM (alternating direction method of multipliers)-based
optimization framework, in which the modality weights are also incorporated for
adaptive fusion of multiple source data.Extensive experiments on the
large-scale dataset are executed to demonstrate the effectiveness of the
proposed tracker against other state-of-the-art tracking methods. We also
provide new insights and potential research directions to the field of RGB-T
object tracking. | ['Jin Tang', 'Xinyan Liang', 'Yijuan Lu', 'Nan Zhao', 'Chenglong Li'] | 2018-05-23 | null | null | null | null | ['rgb-t-tracking'] | ['computer-vision'] | [-7.30640143e-02 -5.91839314e-01 -1.83288142e-01 -1.59354165e-01
-5.07989645e-01 -3.88081074e-01 2.14976028e-01 -3.25447887e-01
-4.20175284e-01 3.53730440e-01 -4.58256528e-02 6.59081759e-03
7.94712454e-02 -4.29095745e-01 -5.78576028e-01 -1.05172133e+00
5.11449538e-02 5.14094122e-02 5.29801011e-01 -8.29864070e-02
-1.60794124e-01 4.18609619e-01 -1.38123965e+00 -2.23874450e-01
7.37754941e-01 1.41216516e+00 2.15318337e-01 5.43079078e-01
1.65635720e-01 6.28818810e-01 -3.24243754e-01 -4.20154780e-01
6.41722500e-01 -2.72574455e-01 -1.23947255e-01 3.42385650e-01
8.07206273e-01 -2.58495122e-01 -6.47766829e-01 1.03445399e+00
6.18359685e-01 2.73318738e-01 1.38183206e-01 -1.60230339e+00
-5.25477827e-01 5.39382026e-02 -8.77363503e-01 2.66249299e-01
1.41858235e-01 7.11139321e-01 5.57417989e-01 -6.60627067e-01
6.13616586e-01 1.08244956e+00 7.38688290e-01 5.02440214e-01
-8.90639782e-01 -8.25286090e-01 3.42750937e-01 2.96064138e-01
-1.19405198e+00 -1.49918571e-01 9.12552476e-01 -4.63822663e-01
6.33618891e-01 4.07316744e-01 1.31483650e+00 9.32368040e-01
3.58675390e-01 8.24971616e-01 9.54166591e-01 -1.07911140e-01
-2.70434339e-02 -2.60627866e-01 -9.30514336e-02 8.72734070e-01
5.13310254e-01 2.98155308e-01 -6.14949524e-01 -1.32694095e-01
8.50015879e-01 1.75989166e-01 -3.73830080e-01 -7.55148470e-01
-1.49682665e+00 4.84389335e-01 7.44805336e-01 2.80962139e-01
-2.48714358e-01 6.02392256e-01 4.68383402e-01 -2.90781949e-02
3.99574578e-01 -1.69324115e-01 -2.80521691e-01 8.26853607e-03
-7.61048794e-01 5.36726825e-02 1.66030094e-01 1.15760803e+00
5.23371816e-01 4.32812184e-01 -3.49661291e-01 3.08788568e-01
8.56482327e-01 1.02042770e+00 3.08581352e-01 -8.74168456e-01
5.66027522e-01 7.01538742e-01 1.52389199e-01 -1.22693896e+00
-4.49320823e-01 -5.22591233e-01 -9.02358294e-01 2.61140913e-01
5.38044155e-01 -1.16893947e-01 -7.04360068e-01 1.55285597e+00
7.50337780e-01 5.80677748e-01 -1.63572192e-01 1.41424012e+00
9.87608671e-01 4.84247565e-01 6.07895963e-02 -4.23260659e-01
1.54625785e+00 -9.49478626e-01 -8.21169972e-01 -2.37641305e-01
2.78155386e-01 -8.92061412e-01 5.03120840e-01 -4.60562436e-03
-8.71658504e-01 -7.38365769e-01 -9.10241485e-01 1.22801974e-01
-6.01878576e-02 3.15919071e-01 8.19710195e-01 8.43531966e-01
-8.07603717e-01 1.69097975e-01 -1.02288449e+00 -3.40921521e-01
3.61897171e-01 3.65657777e-01 -1.90044880e-01 -3.01091857e-02
-1.05559611e+00 8.07920754e-01 4.25904572e-01 7.68209338e-01
-8.31805646e-01 -6.46054149e-01 -8.23108733e-01 -4.59430993e-01
6.08616352e-01 -8.68386269e-01 7.76169777e-01 -7.15564966e-01
-1.47097707e+00 6.52815700e-01 8.35213345e-04 -3.15528363e-02
6.05232000e-01 -1.65564239e-01 -4.91551667e-01 1.35576069e-01
-1.38021156e-01 5.07833898e-01 1.08482599e+00 -1.19234157e+00
-6.15409076e-01 -5.75750709e-01 -2.22294450e-01 1.55470937e-01
-5.69839418e-01 1.01732709e-01 -1.14058411e+00 -7.98541725e-01
2.51876980e-01 -1.22557330e+00 -3.09549958e-01 4.03420240e-01
-2.36467406e-01 -1.15409270e-01 1.13747132e+00 -5.93110561e-01
1.19541240e+00 -1.93554425e+00 3.50958407e-01 1.92105640e-02
4.69549328e-01 4.04918432e-01 -1.68950185e-02 -2.73213559e-03
2.25046068e-01 -4.23186004e-01 -4.48728800e-02 -2.82302707e-01
-8.44343007e-02 8.40393752e-02 1.50713131e-01 8.62888873e-01
-2.50404060e-01 1.25319338e+00 -1.01835012e+00 -8.09749603e-01
7.05545425e-01 6.58098459e-01 -3.16395164e-02 9.93153751e-02
-1.25683770e-01 7.54913032e-01 -8.99698913e-01 9.35542881e-01
8.00743043e-01 -2.17645407e-01 -1.57359652e-02 -9.06918466e-01
-3.31586242e-01 -5.11394441e-01 -1.20730972e+00 1.86178899e+00
-7.80582801e-02 6.74782336e-01 5.76239973e-02 -5.89190722e-01
7.05601394e-01 2.09118977e-01 1.06355274e+00 -6.05359793e-01
5.24958491e-01 -1.41846715e-02 -1.64323777e-01 -5.65185547e-01
5.75627208e-01 1.66297019e-01 1.00310758e-01 2.63957560e-01
-2.23007828e-01 2.03551948e-01 1.87716395e-01 1.11482978e-01
9.60411012e-01 5.15265524e-01 -1.16553612e-01 2.75989249e-02
5.55317163e-01 1.94540963e-01 1.02999413e+00 3.44823033e-01
-5.56597829e-01 3.74438137e-01 -1.68843925e-01 -5.10378599e-01
-8.45558763e-01 -7.94268250e-01 -4.83780578e-02 7.14968443e-01
8.10269475e-01 -4.12565231e-01 -3.74301046e-01 -5.86488485e-01
2.86997825e-01 -3.21665257e-02 -6.66847646e-01 -8.20903927e-02
-7.93929815e-01 -7.55232394e-01 3.31570446e-01 6.70743585e-01
6.83031976e-01 -8.61404717e-01 -9.97142196e-01 1.50679395e-01
-3.19937587e-01 -1.31257427e+00 -7.26471841e-01 -2.13632584e-01
-1.30222309e+00 -1.26107371e+00 -7.88398743e-01 -5.35243452e-01
6.70485556e-01 6.97731435e-01 7.75468409e-01 8.42659846e-02
-3.88897240e-01 8.93055677e-01 -3.10023993e-01 -8.39401186e-02
-1.46111492e-02 -4.23375994e-01 1.44102022e-01 2.50888705e-01
1.10300511e-01 2.75280084e-02 -9.33423221e-01 6.34388208e-01
-7.79090643e-01 6.36567399e-02 6.25021398e-01 4.73595172e-01
7.47435093e-01 6.61424547e-02 -1.15106925e-01 -1.67027384e-01
-5.10068350e-02 -4.72355708e-02 -1.01263165e+00 5.38204074e-01
-3.27427775e-01 -2.51738280e-01 2.20916465e-01 -7.07401872e-01
-1.07663202e+00 4.10600871e-01 4.09603834e-01 -9.67502594e-01
4.28211629e-01 1.46698460e-01 -1.53444618e-01 -7.76144028e-01
1.35517284e-01 2.17928305e-01 3.97171006e-02 -2.91736364e-01
4.75114286e-01 9.76883322e-02 5.24405062e-01 -4.99200016e-01
1.33172655e+00 6.64447129e-01 1.26817182e-01 -6.69801235e-01
-5.35006285e-01 -6.70458019e-01 -5.84876716e-01 -1.03333330e+00
1.00915706e+00 -9.61467266e-01 -1.17335725e+00 6.70413315e-01
-8.30720425e-01 -1.64652646e-01 -5.58942817e-02 8.42528582e-01
-2.99369067e-01 6.35092974e-01 -5.93561172e-01 -8.85656536e-01
-4.54101413e-01 -1.22650135e+00 1.18427372e+00 5.76904356e-01
5.51838279e-01 -1.01518381e+00 -3.12895514e-02 6.26291871e-01
4.15457726e-01 5.37459075e-01 3.83687727e-02 2.82744855e-01
-1.05199957e+00 -1.77231237e-01 -2.54134059e-01 1.16771303e-01
1.38032258e-01 8.94209296e-02 -6.80343747e-01 -6.84858441e-01
-4.21390776e-03 -1.68381140e-01 7.04064548e-01 6.37096882e-01
9.37338054e-01 5.34700453e-02 -6.01529598e-01 7.99954534e-01
1.60803461e+00 4.04991806e-02 3.76971692e-01 5.54440141e-01
1.32778013e+00 1.09941617e-01 1.11687708e+00 4.42330778e-01
3.22900534e-01 1.12895143e+00 6.43500149e-01 -1.82525277e-01
-2.00092390e-01 2.04319045e-01 5.07525921e-01 9.55334663e-01
-4.38775808e-01 -4.39793207e-02 -6.73030913e-01 1.42573893e-01
-2.13670874e+00 -8.78851175e-01 -5.23363352e-01 2.21334505e+00
3.98558497e-01 1.46672055e-02 3.14837366e-01 -1.70757607e-01
8.07148874e-01 2.22646102e-01 -7.10955024e-01 6.08433366e-01
-1.18223250e-01 -3.16648334e-01 8.20942163e-01 -4.91196103e-02
-1.23162901e+00 7.29288161e-01 5.25455475e+00 7.86737204e-01
-1.10135305e+00 2.57659435e-01 1.54228449e-01 -2.17462674e-01
1.21666662e-01 1.63316801e-02 -7.59573638e-01 5.03713191e-01
3.47707361e-01 -1.35444984e-01 9.30933058e-02 6.79013312e-01
1.85973957e-01 -7.94805214e-02 -7.58533001e-01 1.29607069e+00
9.17989910e-02 -1.25502133e+00 -3.68092865e-01 1.10770874e-01
6.32934213e-01 9.40558985e-02 8.53928700e-02 -1.85014270e-02
-3.90319452e-02 -3.07398736e-01 9.59954321e-01 5.67415774e-01
6.06474638e-01 -4.02647555e-01 5.95880687e-01 -1.55720726e-01
-2.05918288e+00 2.78549716e-02 -4.49580312e-01 4.23178732e-01
2.64410794e-01 3.89510065e-01 -1.46380410e-01 1.04923511e+00
9.68854666e-01 1.08497560e+00 -7.42855847e-01 1.38245428e+00
4.79963189e-03 4.01524991e-01 -3.76973331e-01 -5.49707077e-02
1.09316953e-01 -3.45085800e-01 6.44247591e-01 9.85447347e-01
2.97773600e-01 2.43014142e-01 5.07177353e-01 4.84460264e-01
1.64234579e-01 -8.61280039e-02 -3.44128937e-01 2.71489263e-01
3.97436440e-01 1.68493342e+00 -9.23089206e-01 -2.43093938e-01
-6.47834420e-01 6.47362769e-01 -5.01438528e-02 4.09569502e-01
-1.15929282e+00 1.94265842e-01 5.32470345e-01 -1.53558478e-01
4.94911611e-01 -3.92882317e-01 1.31394625e-01 -1.28531110e+00
1.45819783e-01 -6.11622870e-01 4.09387350e-01 -1.00209582e+00
-1.20097589e+00 4.26284939e-01 -4.70446907e-02 -1.92219341e+00
2.78171480e-01 -5.75988770e-01 -3.09628308e-01 5.65468073e-01
-1.45823050e+00 -1.41989362e+00 -8.27740788e-01 7.95976400e-01
1.39470175e-01 -9.01977122e-02 2.13852599e-01 5.58109105e-01
-8.79514694e-01 5.16138136e-01 1.08379908e-01 3.79099578e-01
5.68188787e-01 -8.68829906e-01 1.27191439e-01 1.05606544e+00
3.75509895e-02 6.02183998e-01 5.58393478e-01 -8.35314274e-01
-2.39620543e+00 -1.29100132e+00 7.99523517e-02 -5.91578841e-01
7.38735199e-01 -1.77864566e-01 -6.47922397e-01 6.15630984e-01
1.22936428e-01 6.48446381e-01 4.24289227e-01 -3.09532523e-01
-1.33266881e-01 -3.99966031e-01 -8.61301839e-01 2.61343181e-01
1.00071597e+00 -1.52421240e-02 -2.47493371e-01 3.47137153e-01
6.36612952e-01 -9.44234490e-01 -1.22610044e+00 3.06212783e-01
7.65439153e-01 -8.56805086e-01 1.22625661e+00 -8.48425329e-02
-2.18312904e-01 -9.44347203e-01 2.02390049e-02 -8.69842768e-01
-3.74065578e-01 -5.02839625e-01 -5.03197730e-01 1.22918832e+00
-2.18290657e-01 -4.96807158e-01 9.47353899e-01 6.02859437e-01
-1.98440313e-01 -6.93931103e-01 -1.08468807e+00 -9.49155331e-01
-7.00137973e-01 -4.98633444e-01 3.58771920e-01 7.67354071e-01
-5.26753068e-01 2.40549585e-03 -7.47386813e-01 2.28933260e-01
1.28500772e+00 4.96324003e-01 9.49902296e-01 -1.04701614e+00
-1.28965005e-01 -3.17874908e-01 -7.51311302e-01 -1.01118112e+00
-2.20260561e-01 -7.65861809e-01 -3.55663113e-02 -1.35849917e+00
2.62256324e-01 -6.70105815e-01 -4.02863264e-01 3.57204258e-01
-4.45201278e-01 5.17983079e-01 5.57265759e-01 3.98652226e-01
-1.05262733e+00 9.58413541e-01 1.61923611e+00 -2.41226897e-01
9.69967898e-03 -5.24856262e-02 -1.49681360e-01 4.57347453e-01
3.91860753e-01 -4.42529470e-01 -1.62802458e-01 -5.53495765e-01
2.15424672e-02 2.59471565e-01 5.69247484e-01 -1.14341915e+00
4.89985943e-01 -1.66147903e-01 5.96739531e-01 -8.12199831e-01
4.49181318e-01 -1.30449653e+00 5.39238930e-01 6.87468290e-01
2.19927371e-01 1.61993086e-01 2.22308233e-01 9.43896115e-01
-4.87472191e-02 2.93050081e-01 6.46617115e-01 8.48983154e-02
-1.02471554e+00 8.36644590e-01 1.25911295e-01 6.60553500e-02
1.35891974e+00 -5.56926966e-01 -2.15234295e-01 8.04790668e-03
-3.41551691e-01 5.81471264e-01 6.49629951e-01 6.69740379e-01
6.65143907e-01 -1.80769622e+00 -5.29885530e-01 -1.80587098e-01
3.64523560e-01 -1.45434514e-01 4.15197968e-01 1.26854956e+00
-3.84178072e-01 2.34631956e-01 -3.01682442e-01 -1.11606991e+00
-1.51245487e+00 6.33232355e-01 2.93224543e-01 -2.08489001e-02
-1.01345217e+00 6.97823226e-01 -6.86217844e-02 -1.06003255e-01
3.80696565e-01 -3.74115229e-01 -1.73933208e-02 -8.97202492e-02
4.16683167e-01 5.18032968e-01 -9.33944657e-02 -1.08631063e+00
-8.05010021e-01 1.13469315e+00 3.79683763e-01 2.45813608e-01
1.24739051e+00 -1.73489854e-01 3.42184887e-03 2.71801353e-01
9.52336550e-01 -3.22774321e-01 -1.58520162e+00 -3.71956319e-01
-3.01350027e-01 -8.74336004e-01 2.41646007e-01 -2.51696378e-01
-1.92202187e+00 4.52212036e-01 1.03729200e+00 -9.09039825e-02
1.19309628e+00 -1.70135573e-01 1.00436068e+00 1.60009533e-01
5.75738847e-01 -9.20164287e-01 3.04688454e-01 3.59440669e-02
5.42217314e-01 -1.34039176e+00 4.80769575e-01 -4.07559127e-01
-5.52446365e-01 1.04248476e+00 8.19656849e-01 6.91643432e-02
3.02167326e-01 1.25228837e-01 2.00291991e-01 -3.01999092e-01
-4.61577594e-01 -4.16365266e-01 4.99104142e-01 5.45914710e-01
3.21616113e-01 -1.66372493e-01 -9.45851579e-02 -1.10743577e-02
2.67720461e-01 1.37702664e-02 -1.98473372e-02 1.02105069e+00
-2.65338987e-01 -9.02380884e-01 -9.12271440e-01 3.20443630e-01
-5.30903824e-02 3.60525161e-01 -6.11874573e-02 9.14919138e-01
1.13086589e-01 9.72158194e-01 -4.18954313e-01 -5.03527164e-01
3.70368510e-01 -4.76256013e-01 8.93139362e-01 -6.66026995e-02
-7.36872256e-01 4.28030580e-01 -3.33621591e-01 -9.18179333e-01
-1.03758121e+00 -8.54412556e-01 -1.10519719e+00 -3.93907130e-01
-6.76505506e-01 1.01693356e-02 7.31182337e-01 7.64155328e-01
2.59325832e-01 7.56255507e-01 4.59305614e-01 -1.22717905e+00
-1.73376128e-02 -6.08492374e-01 -3.77754092e-01 4.86643523e-01
1.85536236e-01 -1.09918213e+00 -8.87486637e-02 4.81484570e-02] | [6.345104217529297, -2.210825204849243] |
9f1db407-0afb-4b04-a13a-e4c75dd1b9be | video-summarization-with-attention-based | 1708.09545 | null | http://arxiv.org/abs/1708.09545v2 | http://arxiv.org/pdf/1708.09545v2.pdf | Video Summarization with Attention-Based Encoder-Decoder Networks | This paper addresses the problem of supervised video summarization by
formulating it as a sequence-to-sequence learning problem, where the input is a
sequence of original video frames, the output is a keyshot sequence. Our key
idea is to learn a deep summarization network with attention mechanism to mimic
the way of selecting the keyshots of human. To this end, we propose a novel
video summarization framework named Attentive encoder-decoder networks for
Video Summarization (AVS), in which the encoder uses a Bidirectional Long
Short-Term Memory (BiLSTM) to encode the contextual information among the input
video frames. As for the decoder, two attention-based LSTM networks are
explored by using additive and multiplicative objective functions,
respectively. Extensive experiments are conducted on three video summarization
benchmark datasets, i.e., SumMe, and TVSum. The results demonstrate the
superiority of the proposed AVS-based approaches against the state-of-the-art
approaches,with remarkable improvements from 0.8% to 3% on two
datasets,respectively.. | ['Xuelong. Li', 'Yanwei Pang', 'Kailin Xiong', 'Zhong Ji'] | 2017-08-31 | null | null | null | null | ['supervised-video-summarization'] | ['computer-vision'] | [ 6.45198107e-01 4.41627670e-03 -2.57115364e-01 -2.59953409e-01
-8.76390278e-01 6.53843358e-02 5.21159768e-01 -9.94535536e-02
-3.98464829e-01 7.91699886e-01 8.30563962e-01 4.66404529e-03
4.42788392e-01 -2.51370430e-01 -1.05489957e+00 -7.34530449e-01
7.78004751e-02 -2.82783508e-01 3.62911582e-01 -9.93439630e-02
5.93471467e-01 -2.65516877e-01 -1.32831740e+00 6.76573157e-01
1.01479137e+00 9.25944149e-01 5.57442844e-01 9.19634998e-01
-7.55888745e-02 1.42102075e+00 -6.97615921e-01 -2.53758252e-01
-1.62672862e-01 -9.91778672e-01 -8.16714227e-01 2.84316361e-01
5.85702419e-01 -7.42802203e-01 -8.74389231e-01 1.05373645e+00
6.40948474e-01 4.35761660e-01 5.11459291e-01 -8.85572851e-01
-9.85493124e-01 7.35640585e-01 -7.32627153e-01 4.80850399e-01
5.78152359e-01 2.45938644e-01 9.57258701e-01 -6.92758441e-01
5.00385463e-01 1.15147138e+00 3.60143691e-01 5.73532045e-01
-6.78528547e-01 -3.61836165e-01 3.31999868e-01 7.94176459e-01
-9.54648495e-01 -7.10635960e-01 6.71980143e-01 -2.00378671e-01
1.13041675e+00 3.14909965e-01 6.43472433e-01 1.11132634e+00
4.82188433e-01 1.32676399e+00 3.56146038e-01 -9.75512937e-02
8.09748694e-02 -3.42022598e-01 2.21078366e-01 6.25261843e-01
8.77183825e-02 -5.80319107e-01 -6.27174318e-01 1.01611353e-01
6.15397811e-01 2.82308400e-01 -4.96493220e-01 9.19949040e-02
-1.28449130e+00 5.52814722e-01 4.54099834e-01 1.19972289e-01
-7.69642055e-01 2.65602767e-01 1.06769717e+00 2.56242275e-01
6.43264294e-01 8.63265991e-02 -2.58059055e-02 1.91153854e-03
-1.22906661e+00 1.81031361e-01 3.87195021e-01 1.07113862e+00
4.38316166e-01 4.69815791e-01 -7.46850908e-01 7.87562430e-01
2.05538556e-01 3.52542222e-01 9.86606419e-01 -1.02698505e+00
8.79175782e-01 2.46678337e-01 7.59199485e-02 -9.38611925e-01
6.54081181e-02 -2.06984580e-01 -1.18720388e+00 -5.08562922e-01
-5.62235773e-01 -3.00914705e-01 -8.90562534e-01 1.54363263e+00
-2.14410380e-01 7.28438973e-01 4.38051134e-01 8.68950784e-01
1.45897019e+00 1.42797172e+00 4.97808009e-02 -7.93735325e-01
1.05312037e+00 -1.65558982e+00 -1.01550770e+00 -1.68416142e-01
2.96511561e-01 -4.57173079e-01 9.90825057e-01 1.21298410e-01
-1.63941598e+00 -6.97604597e-01 -1.19877350e+00 -1.57051176e-01
2.52977788e-01 7.20176771e-02 -1.63696930e-02 -2.25882232e-01
-1.29172635e+00 5.93815982e-01 -8.11742425e-01 -4.97406423e-01
5.03647625e-01 1.58470318e-01 -2.14501485e-01 1.98785663e-01
-1.10379899e+00 5.10816038e-01 8.10260475e-01 1.08448781e-01
-1.01885200e+00 -3.12449783e-01 -9.61257875e-01 4.62225765e-01
4.84250575e-01 -1.12629712e+00 1.69824278e+00 -1.45202434e+00
-1.71911645e+00 5.85183918e-01 -4.61476922e-01 -7.80497491e-01
3.10892284e-01 -5.31561553e-01 -1.32495552e-01 4.80859637e-01
1.54748976e-01 5.48709691e-01 9.48197842e-01 -1.13105237e+00
-7.79770970e-01 -1.55735184e-02 -1.32114246e-01 5.30973673e-01
-3.02321166e-01 1.32774949e-01 -5.47721148e-01 -9.49108779e-01
-3.36114854e-01 -5.12626290e-01 -1.71878934e-01 -8.20130289e-01
-8.92821610e-01 -1.52993113e-01 8.85184586e-01 -1.28253353e+00
1.74158645e+00 -1.91429961e+00 6.55925512e-01 -5.71134448e-01
1.19593017e-01 7.17605114e-01 -2.15019047e-01 6.23191953e-01
-1.36296544e-03 2.51421332e-02 -4.38940704e-01 -5.95025539e-01
-2.19359264e-01 -6.98056966e-02 -5.08058131e-01 1.33974269e-01
-3.90457339e-03 1.05444157e+00 -9.29173410e-01 -5.57897985e-01
1.21757455e-01 1.61009446e-01 -3.81418079e-01 6.59350574e-01
-4.07605439e-01 3.50135207e-01 -4.03794557e-01 3.31878513e-01
3.99437338e-01 -1.70000494e-01 2.86848135e-02 -2.13361904e-01
-1.33491099e-01 2.55797952e-01 -5.76457620e-01 2.02057886e+00
-4.34661359e-02 6.99953377e-01 -2.38214150e-01 -1.17356420e+00
5.59812069e-01 4.62684572e-01 1.34069011e-01 -6.45220518e-01
2.62979597e-01 -5.33926394e-03 -3.12752485e-01 -1.00412691e+00
8.99165213e-01 6.54475689e-02 6.36573369e-03 3.99759948e-01
2.14241713e-01 4.09746468e-01 4.26847190e-01 4.70947325e-01
1.00831687e+00 2.36758992e-01 6.08976603e-01 1.37034887e-02
8.38130355e-01 -2.58319050e-01 6.83666825e-01 6.24734223e-01
4.24255710e-03 6.44601762e-01 7.53730834e-01 -1.98173717e-01
-1.16400290e+00 -7.08051264e-01 8.15313220e-01 1.25924110e+00
2.55183905e-01 -5.64463377e-01 -1.16990840e+00 -5.73812604e-01
-5.37159503e-01 8.49230409e-01 -3.62731874e-01 -3.77333343e-01
-8.37785423e-01 -4.12790209e-01 3.54507506e-01 5.99000156e-01
1.02812612e+00 -1.43642867e+00 -7.36865699e-01 1.31044596e-01
-4.89062637e-01 -1.09750605e+00 -9.23808038e-01 -5.79436183e-01
-1.05355287e+00 -7.52471387e-01 -1.08651006e+00 -1.21883404e+00
4.17821884e-01 5.76698184e-01 8.87500584e-01 -7.65115246e-02
2.89149165e-01 1.56165078e-01 -5.07127523e-01 -1.21369004e-01
-3.79436463e-01 2.37492606e-01 -1.60267279e-01 2.34442532e-01
-9.85726193e-02 -6.38704658e-01 -8.28283072e-01 -1.92746088e-01
-1.03917694e+00 6.96555614e-01 1.01449847e+00 7.26697624e-01
7.02321708e-01 -3.82623285e-01 8.92901242e-01 -9.26195741e-01
8.13219190e-01 -7.30180025e-01 3.34905945e-02 4.28958803e-01
2.81582456e-02 -3.80856474e-03 1.03829575e+00 -1.28226206e-01
-1.22014344e+00 -2.24487722e-01 -5.82010113e-02 -5.47062933e-01
5.97308390e-02 6.58078313e-01 -2.17151076e-01 4.07212496e-01
9.79637429e-02 8.93819034e-01 -1.49470016e-01 -3.89497668e-01
3.04647774e-01 8.45174015e-01 9.12783980e-01 -2.21079905e-02
2.38437384e-01 1.74758494e-01 -3.66170794e-01 -9.68801677e-01
-8.51046920e-01 -3.02014053e-01 -3.44003201e-01 -2.37151965e-01
1.04634941e+00 -9.86967146e-01 -5.68330050e-01 7.45686769e-01
-1.45491016e+00 -3.19923788e-01 -1.15516499e-01 3.48166227e-01
-8.59490335e-01 8.76511514e-01 -8.18373024e-01 -3.93802822e-01
-9.98721719e-01 -1.24204040e+00 9.99974191e-01 5.00493407e-01
-1.56682506e-02 -8.38777661e-01 -3.88353551e-03 3.57744604e-01
2.64538914e-01 3.65480214e-01 7.96841025e-01 -7.43128538e-01
-6.32481992e-01 8.39439481e-02 -2.51534581e-01 6.16333544e-01
4.11713682e-02 9.49679464e-02 -4.93361086e-01 -3.70941132e-01
1.09177567e-01 -3.49906266e-01 1.42935932e+00 6.53528035e-01
1.40641427e+00 -9.38004434e-01 -7.21821189e-02 5.88057458e-01
1.23830581e+00 3.82726938e-01 9.09924090e-01 2.03585327e-01
9.12456274e-01 2.49659032e-01 5.26464641e-01 4.87624079e-01
5.56536198e-01 3.63256365e-01 4.25857902e-01 1.53827459e-01
-8.80378485e-02 -4.49144155e-01 7.18563259e-01 1.40379822e+00
-1.83380991e-01 -6.24368191e-01 -4.43349630e-01 3.68664205e-01
-2.39909840e+00 -1.31932640e+00 -8.22046399e-02 2.03348899e+00
5.72941720e-01 5.95041700e-02 1.96631715e-01 -2.03910545e-01
1.09281981e+00 9.15861428e-01 -7.67487049e-01 -5.69367647e-01
-6.57454208e-02 -3.44282627e-01 2.92884082e-01 3.00014436e-01
-1.19381547e+00 1.05096459e+00 5.59096956e+00 8.64968717e-01
-1.14097214e+00 1.02613397e-01 8.51945639e-01 -2.52507120e-01
-9.63739902e-02 -3.31775725e-01 -2.82873541e-01 9.01007593e-01
1.01641512e+00 -4.24655974e-01 2.83937484e-01 4.97420430e-01
6.56349659e-01 -8.77194107e-02 -9.37786937e-01 1.10651720e+00
7.78230727e-01 -1.48342454e+00 6.81344032e-01 -6.08205020e-01
9.97625887e-01 -5.83051816e-02 6.18210100e-02 4.63172346e-01
-1.90612882e-01 -8.56057644e-01 7.57204652e-01 8.20783317e-01
7.16883719e-01 -8.33593965e-01 8.31925511e-01 3.27844709e-01
-1.16603112e+00 -1.18521608e-01 -3.97687793e-01 -5.99230360e-03
5.54750204e-01 7.26457164e-02 -3.25623691e-01 8.75792980e-01
5.06886542e-01 1.29037035e+00 -3.04467082e-01 1.09702361e+00
-3.26001137e-01 8.26036453e-01 4.33037043e-01 -3.45664844e-02
5.41585028e-01 -2.94192195e-01 8.37054551e-01 1.53592718e+00
3.86966079e-01 2.98411578e-01 1.29588217e-01 3.07829410e-01
-4.69405293e-01 1.54197276e-01 -4.51677799e-01 -2.27895547e-02
2.28477418e-01 9.98237133e-01 -2.95282990e-01 -8.62867177e-01
-4.04421479e-01 1.39757526e+00 7.33947232e-02 6.17146730e-01
-1.08268917e+00 -7.01338649e-01 1.59628198e-01 -7.39991143e-02
5.55540681e-01 9.05971155e-02 1.49224490e-01 -1.36344242e+00
1.78583100e-01 -9.12641346e-01 3.83195847e-01 -1.09118474e+00
-7.67173231e-01 4.93043482e-01 5.59878796e-02 -1.17002392e+00
-3.07659388e-01 1.48936450e-01 -1.26841164e+00 4.82827872e-01
-1.45602965e+00 -1.12416649e+00 -4.84699577e-01 3.02122325e-01
1.33579886e+00 -3.46916437e-01 1.57306805e-01 1.60162687e-01
-9.26899910e-01 3.42311710e-01 4.71014202e-01 -5.35559505e-02
6.62028670e-01 -9.10891652e-01 6.14415050e-01 1.06003308e+00
-2.37334460e-01 2.94779807e-01 8.55462134e-01 -6.73406780e-01
-1.36423922e+00 -1.46914887e+00 7.70931005e-01 2.69987375e-01
4.75432843e-01 1.79936498e-01 -9.87704396e-01 1.05694902e+00
1.01961565e+00 -5.92470646e-01 5.76566160e-01 -7.55832672e-01
1.19384341e-01 -3.67180184e-02 -7.16317713e-01 7.33753562e-01
1.10472631e+00 -1.28853500e-01 -9.95038986e-01 2.43687183e-01
1.30922806e+00 -4.69252616e-01 -3.86231780e-01 3.55788350e-01
3.07136565e-01 -1.04927063e+00 7.31686950e-01 -9.16010022e-01
1.12405646e+00 -2.29370371e-01 -1.04977839e-01 -1.57095325e+00
-4.39289987e-01 -8.52042079e-01 -5.89487553e-01 1.22366619e+00
-8.50150883e-02 -3.41025859e-01 4.94442403e-01 -1.06473237e-01
-7.76820421e-01 -9.37846184e-01 -6.20695293e-01 -4.55789596e-01
-4.81027782e-01 2.65245080e-01 2.86191583e-01 4.74307299e-01
-3.46801542e-02 7.66921759e-01 -8.28039587e-01 -1.87922955e-01
3.89404148e-01 4.13498320e-02 7.48832047e-01 -4.72755700e-01
-1.99272677e-01 -4.68106180e-01 -3.42094958e-01 -1.53388643e+00
5.27844906e-01 -7.34662294e-01 8.31327885e-02 -2.07832742e+00
7.34085083e-01 7.67269492e-01 -3.34924430e-01 7.44266957e-02
-5.58700800e-01 -1.21522166e-01 3.77831727e-01 2.53691137e-01
-1.48395085e+00 1.12179494e+00 1.06263971e+00 -2.84450978e-01
-2.44864345e-01 -1.97909791e-02 -8.25450718e-01 8.21966588e-01
8.43129635e-01 -1.02670431e-01 -5.13386250e-01 -8.94504547e-01
-1.59302995e-01 5.50977349e-01 2.85833120e-01 -1.00815058e+00
4.37351286e-01 -1.53064013e-01 4.38362956e-02 -9.37487543e-01
1.75460234e-01 -1.38651699e-01 -9.57419872e-02 6.07285202e-01
-7.80344725e-01 2.81665236e-01 -1.04344757e-02 7.85841227e-01
-4.91162002e-01 -2.41493031e-01 5.83217084e-01 -2.47042224e-01
-1.01504838e+00 4.70408857e-01 -4.83132184e-01 2.38243297e-01
1.08850670e+00 -1.07077271e-01 -4.32297945e-01 -6.76339865e-01
-3.58096719e-01 5.21895170e-01 2.35019773e-01 2.47862577e-01
9.88686979e-01 -1.38680732e+00 -1.11953819e+00 -1.67998955e-01
-9.17725265e-02 1.52939245e-01 7.39683390e-01 7.21518636e-01
-8.16932201e-01 6.49177074e-01 -3.39334100e-01 -3.74347329e-01
-1.57530820e+00 5.49939036e-01 6.75561056e-02 -1.07234709e-01
-6.49363935e-01 8.06727767e-01 3.71086866e-01 3.44123214e-01
3.62201840e-01 -2.87571102e-01 -5.28225899e-01 4.16835584e-02
8.20310116e-01 6.95443451e-01 -3.25008869e-01 -7.77528405e-01
3.54430117e-02 3.16862255e-01 -3.95612806e-01 1.25002801e-01
1.40511227e+00 -3.64687443e-01 -3.22294801e-01 5.41515648e-01
1.35942650e+00 -4.60457265e-01 -1.27221549e+00 -3.91539752e-01
-2.04666257e-01 -2.88621247e-01 -3.06463510e-01 -2.92149633e-01
-1.07077992e+00 7.72744715e-01 2.67934203e-02 1.53811514e-01
1.26341128e+00 -1.99588716e-01 1.55593109e+00 5.20726562e-01
-2.14901581e-01 -1.08343446e+00 4.00564998e-01 5.30614972e-01
1.02264512e+00 -1.06092143e+00 -4.11355533e-02 1.35141402e-01
-1.06823623e+00 9.24283028e-01 6.33489490e-01 -5.42056382e-01
-1.58380330e-01 -4.40320939e-01 -5.16679466e-01 1.05528399e-01
-1.04974508e+00 1.60233110e-01 1.17993973e-01 1.52098939e-01
4.05498832e-01 -1.09779045e-01 -4.48140979e-01 7.05245435e-01
6.47801980e-02 1.99084163e-01 7.62234867e-01 7.43500531e-01
-8.55888426e-01 -5.12771904e-01 -1.90883338e-01 7.11457312e-01
-6.21462047e-01 -1.60328954e-01 -3.65670353e-01 2.93129295e-01
-2.82317460e-01 8.19028080e-01 1.43179566e-01 -5.13401270e-01
3.40812355e-01 -1.36228368e-01 1.78742051e-01 -7.21012890e-01
-4.95759666e-01 -5.52371778e-02 -3.99494804e-02 -4.85192180e-01
-6.02875769e-01 -5.43813050e-01 -1.20636249e+00 -3.38300616e-01
1.42015010e-01 2.76501656e-01 1.72247544e-01 8.66988719e-01
4.87702072e-01 1.13373923e+00 7.78723240e-01 -1.28216970e+00
-6.60455704e-01 -1.08789158e+00 -2.31134668e-01 4.13545847e-01
6.25125289e-01 -5.60813248e-02 -3.40097882e-02 4.55941498e-01] | [10.42518138885498, 0.4338070750236511] |
a9d723dd-4ece-4330-8344-c306c680d7ab | meta-generative-flow-networks-with | 2306.09742 | null | https://arxiv.org/abs/2306.09742v1 | https://arxiv.org/pdf/2306.09742v1.pdf | Meta Generative Flow Networks with Personalization for Task-Specific Adaptation | Multi-task reinforcement learning and meta-reinforcement learning have been developed to quickly adapt to new tasks, but they tend to focus on tasks with higher rewards and more frequent occurrences, leading to poor performance on tasks with sparse rewards. To address this issue, GFlowNets can be integrated into meta-learning algorithms (GFlowMeta) by leveraging the advantages of GFlowNets on tasks with sparse rewards. However, GFlowMeta suffers from performance degradation when encountering heterogeneous transitions from distinct tasks. To overcome this challenge, this paper proposes a personalized approach named pGFlowMeta, which combines task-specific personalized policies with a meta policy. Each personalized policy balances the loss on its personalized task and the difference from the meta policy, while the meta policy aims to minimize the average loss of all tasks. The theoretical analysis shows that the algorithm converges at a sublinear rate. Extensive experiments demonstrate that the proposed algorithm outperforms state-of-the-art reinforcement learning algorithms in discrete environments. | ['Yinchuan Li', 'Olga Gadyatskaya', 'Haozhi Wang', 'Wei Xi', 'Xu Zhang', 'Xinyuan Ji'] | 2023-06-16 | null | null | null | null | ['meta-learning'] | ['methodology'] | [-3.09978537e-02 -5.01069315e-02 -3.34229052e-01 7.05235824e-03
-7.78516531e-01 5.99585250e-02 3.49749267e-01 1.67356715e-01
-7.12979734e-01 1.26863039e+00 -1.32479146e-01 1.45045802e-01
-3.86002719e-01 -4.93596941e-01 -6.93598032e-01 -7.72069097e-01
-1.26582190e-01 5.68006873e-01 3.33724976e-01 -1.42748609e-01
2.38030434e-01 -1.62055343e-01 -1.66041076e+00 1.30227655e-01
1.39785731e+00 7.90348947e-01 8.59601498e-01 4.25004363e-01
-3.06589514e-01 6.52353525e-01 -6.36435330e-01 -2.15023726e-01
2.31220186e-01 -2.08636642e-01 -6.72033489e-01 -1.71178892e-01
6.55206218e-02 -2.80155063e-01 -2.66829520e-01 9.75192130e-01
6.01064503e-01 3.88231665e-01 4.85772252e-01 -1.65702546e+00
-3.36380988e-01 8.00877988e-01 -7.30095923e-01 3.06964517e-01
-1.05268382e-01 2.29489028e-01 8.62380266e-01 -4.61801827e-01
2.39896640e-01 1.20483267e+00 4.01609868e-01 7.09503531e-01
-1.18411100e+00 -5.96116602e-01 7.24766850e-01 2.90870488e-01
-7.39394367e-01 -2.38947794e-01 5.63351393e-01 -2.70127028e-01
1.10678983e+00 -2.78940678e-01 5.26876092e-01 1.33864164e+00
4.86362547e-01 1.10073209e+00 1.31543243e+00 -2.15023041e-01
3.40058774e-01 4.90615554e-02 -2.42159784e-01 4.54384685e-01
2.66532898e-01 2.12901801e-01 -6.35650039e-01 -8.95989314e-02
7.12414265e-01 1.61830336e-01 1.99214891e-01 -4.77388978e-01
-1.14296389e+00 5.64398050e-01 2.48556405e-01 2.29568094e-01
-7.19828010e-01 4.75817770e-01 7.15504050e-01 6.07158005e-01
4.71633941e-01 3.30107868e-01 -5.18704236e-01 -4.80235130e-01
-6.94849014e-01 5.82230628e-01 4.26529706e-01 9.19943869e-01
1.01417983e+00 3.15177351e-01 -7.18004763e-01 1.02857065e+00
-3.58650833e-02 3.30496132e-01 7.68018484e-01 -1.02156973e+00
6.79853678e-01 3.21605235e-01 3.79195601e-01 -2.83415139e-01
-4.45275277e-01 -6.69233859e-01 -5.55617511e-01 2.81990051e-01
3.74252170e-01 -5.45542896e-01 -6.31462932e-01 1.89042568e+00
3.91851515e-01 5.55361956e-02 1.68426950e-02 6.23230696e-01
-7.03336895e-02 6.05142236e-01 4.67681110e-01 -4.40793395e-01
8.36027682e-01 -1.22115374e+00 -7.66333103e-01 -4.83868182e-01
5.29074430e-01 -5.66942990e-01 1.17367542e+00 4.06466722e-01
-1.14811099e+00 -7.23172426e-01 -8.05785298e-01 6.99521959e-01
-9.81828570e-03 -1.34848177e-01 3.78465235e-01 5.13642490e-01
-8.22942972e-01 7.02576280e-01 -7.35313654e-01 -1.16684459e-01
4.82077420e-01 2.10126340e-01 2.49651611e-01 -1.14331156e-01
-1.14445925e+00 9.18779194e-01 5.54068387e-01 -2.94997841e-01
-1.34962964e+00 -7.59278536e-01 -4.05405283e-01 2.17332616e-01
9.79605734e-01 -7.46007562e-01 1.62983942e+00 -1.08334684e+00
-1.75831604e+00 4.18961532e-02 2.08254103e-02 -5.94846249e-01
9.49000120e-01 -5.07548392e-01 -1.43086940e-01 -1.81230277e-01
2.93034941e-01 4.41670865e-01 1.18728256e+00 -1.11588657e+00
-1.23116434e+00 -2.35368997e-01 4.29492369e-02 5.94997287e-01
-4.89537805e-01 -4.98265833e-01 4.23562899e-02 -5.15123069e-01
-6.69830024e-01 -7.21354365e-01 -4.45506483e-01 -5.89695632e-01
-1.41668648e-01 -6.44397259e-01 7.52572954e-01 7.27879989e-04
9.87909079e-01 -2.09530997e+00 1.30053535e-01 -2.52741218e-01
1.21111661e-01 2.98105180e-01 -3.72772664e-01 5.71415126e-01
4.59455192e-01 -2.70036817e-01 9.90648270e-02 -3.80942255e-01
1.23137400e-01 3.81434083e-01 -9.47565362e-02 1.66933928e-02
-1.38333365e-01 6.97105885e-01 -1.30663967e+00 -3.57716143e-01
6.64250627e-02 -2.52001882e-01 -4.40543085e-01 2.78434515e-01
-5.56751072e-01 3.45918357e-01 -7.48485506e-01 4.38062072e-01
4.97555465e-01 -9.07070190e-02 3.42508346e-01 4.29378331e-01
-1.20279104e-01 7.41425157e-02 -9.85879660e-01 1.67061770e+00
-7.78820038e-01 4.65619564e-03 1.59398749e-01 -1.24697256e+00
9.63772535e-01 4.05355334e-01 8.64185691e-01 -9.63384867e-01
-2.11763844e-01 2.96110481e-01 -3.04390285e-02 -4.88220930e-01
6.67914867e-01 -1.00179099e-01 1.09026982e-02 3.97608042e-01
1.74747735e-01 4.41601247e-01 3.17158520e-01 1.12355784e-01
1.16065288e+00 5.27250469e-01 9.93923694e-02 -2.08337098e-01
2.28748590e-01 -5.11435233e-02 8.18140745e-01 1.23660505e+00
-5.69725096e-01 -2.35841453e-01 4.14469212e-01 -4.24614906e-01
-8.46198559e-01 -1.04496455e+00 3.07067215e-01 1.61213470e+00
2.43290365e-01 -2.04898417e-01 -6.32669687e-01 -9.40354466e-01
3.55306715e-01 5.53069234e-01 -4.71973777e-01 -2.85773695e-01
-4.80974466e-01 -7.37846971e-01 1.42543778e-01 2.58596867e-01
8.13482821e-01 -1.45430911e+00 -9.61210966e-01 7.62775779e-01
-2.48944208e-01 -1.00571668e+00 -4.94117856e-01 3.20484579e-01
-9.68308091e-01 -9.23192263e-01 -1.12225401e+00 -6.10296607e-01
3.97977322e-01 4.19506848e-01 1.03628373e+00 -3.24589610e-01
-6.54273778e-02 4.32009101e-01 -4.06878024e-01 -4.12781298e-01
-2.79516131e-01 5.22079647e-01 3.21015358e-01 7.47952387e-02
-2.26018336e-02 -5.79077125e-01 -6.30536675e-01 3.43265921e-01
-6.94316864e-01 -9.74014699e-02 8.08520079e-01 1.14151216e+00
6.13759756e-01 1.35203704e-01 1.35638976e+00 -9.46804821e-01
1.08051562e+00 -6.28849924e-01 -6.08187795e-01 4.70857322e-01
-1.07552660e+00 2.89383471e-01 1.07272828e+00 -6.79002047e-01
-1.34611404e+00 -6.67315274e-02 2.41784096e-01 -4.67846364e-01
1.30060194e-02 3.96915972e-01 1.72801822e-01 1.67794570e-01
6.45861030e-01 4.23306823e-01 6.81102276e-02 -4.25134569e-01
2.18905523e-01 4.19062376e-01 1.68437839e-01 -9.99948263e-01
4.51796979e-01 5.84681779e-02 -6.37879744e-02 -4.56829518e-01
-9.05542135e-01 -3.71060401e-01 -9.27215740e-02 -5.40675521e-01
3.99027973e-01 -8.15747201e-01 -8.24228823e-01 6.32084310e-01
-6.66575491e-01 -8.39329660e-01 -4.72871512e-01 5.38011611e-01
-1.14388239e+00 1.88818201e-01 -2.06106231e-01 -1.09509838e+00
-2.54957855e-01 -1.10503292e+00 4.77386475e-01 4.62217093e-01
2.58983046e-01 -8.69125903e-01 2.37936631e-01 6.08161651e-02
5.34845054e-01 -6.60831481e-02 8.49384904e-01 -3.14205736e-01
-5.13111711e-01 2.84084737e-01 4.37698923e-02 2.53812283e-01
2.77292967e-01 -4.90539283e-01 -7.69460320e-01 -5.94081938e-01
-2.22913936e-01 -8.06345999e-01 9.09270227e-01 5.81997395e-01
1.19075835e+00 -3.33547592e-01 -1.90322891e-01 2.61695445e-01
1.52537870e+00 3.00239384e-01 3.77758145e-01 7.70827651e-01
3.11495334e-01 4.09073055e-01 1.01163244e+00 8.78097177e-01
3.45985860e-01 5.89204252e-01 7.90743589e-01 3.40873867e-01
8.36909562e-02 -3.22266936e-01 7.62289762e-01 4.10835564e-01
5.06180637e-02 -1.05236076e-01 -6.19062304e-01 7.24521160e-01
-2.43283319e+00 -9.69000876e-01 3.19810599e-01 2.30405450e+00
7.27054775e-01 3.78744096e-01 5.39789736e-01 -1.44462168e-01
6.65051401e-01 1.87324867e-01 -1.08599508e+00 -5.48337579e-01
2.07490578e-01 -1.69338435e-02 4.83360529e-01 1.90371096e-01
-8.37456822e-01 1.03565300e+00 6.54697609e+00 1.13530517e+00
-8.17654133e-01 3.49729091e-01 3.51799816e-01 -3.62423986e-01
-5.44031858e-02 -1.44277260e-01 -9.13560867e-01 5.83420038e-01
7.66951919e-01 -6.11723125e-01 7.04674304e-01 1.03385770e+00
1.48792177e-01 -3.00571948e-01 -7.92983174e-01 7.08025217e-01
-4.30726320e-01 -9.25466299e-01 -1.58529699e-01 -2.12627817e-02
9.13958967e-01 2.53834635e-01 2.78057754e-01 8.80826592e-01
7.42774129e-01 -5.43860495e-01 6.76402211e-01 4.56505686e-01
5.34504354e-01 -1.04214776e+00 4.22753841e-01 7.21202254e-01
-1.06347442e+00 -4.65151936e-01 -6.89572096e-01 -9.33499932e-02
-2.35876851e-02 5.57159483e-01 -8.53878796e-01 7.50311732e-01
6.97717607e-01 5.57218075e-01 -1.97422072e-01 1.27842617e+00
-7.46228769e-02 3.46046835e-01 3.96588743e-02 -3.05476606e-01
5.31723261e-01 -7.83823058e-03 5.68034887e-01 8.26221466e-01
4.42875355e-01 -5.46294868e-01 7.20615208e-01 6.25002682e-01
5.69094345e-03 1.37983605e-01 -5.46129286e-01 1.19785883e-01
4.65054482e-01 1.31270981e+00 -2.48383597e-01 -2.87713736e-01
-3.12241048e-01 8.54388893e-01 7.72471607e-01 4.03946608e-01
-7.17281640e-01 -3.01914513e-01 7.65787959e-01 -1.76313687e-02
2.28609383e-01 -1.43581346e-01 -6.70498013e-02 -7.95125186e-01
5.36016114e-02 -6.98013604e-01 4.55078959e-01 -3.51338148e-01
-1.46560729e+00 4.63418812e-01 2.99602747e-02 -1.23961556e+00
-3.51072013e-01 -1.19753331e-01 -5.61681747e-01 7.93699980e-01
-1.92728305e+00 -5.85321069e-01 -1.40908182e-01 7.17923284e-01
8.55434597e-01 -4.58812565e-01 4.36235666e-01 1.02182060e-01
-6.41024351e-01 7.54644454e-01 5.74035347e-01 -5.54170251e-01
9.19067979e-01 -1.24770355e+00 1.08155593e-01 4.38482195e-01
-3.72593313e-01 -1.28371716e-01 4.86007512e-01 -6.54933333e-01
-1.08060300e+00 -1.23165178e+00 4.65126902e-01 1.80745736e-01
4.10338163e-01 -3.60104479e-02 -8.50818634e-01 4.01750684e-01
2.78020769e-01 -1.87916756e-01 2.50510752e-01 4.61701900e-01
-5.26008792e-02 -3.92607301e-01 -1.09267032e+00 5.63654780e-01
9.71434653e-01 -2.44104546e-02 -2.90407956e-01 3.97302598e-01
5.49400270e-01 -2.77626961e-01 -7.39322484e-01 8.65539834e-02
3.98661435e-01 -9.95188773e-01 6.62330151e-01 -5.44995070e-01
3.79720300e-01 1.17928773e-01 2.38128051e-01 -1.96207154e+00
-6.02807522e-01 -7.87503839e-01 -3.19225371e-01 9.41890121e-01
2.97791183e-01 -8.10421169e-01 7.38680780e-01 9.99041274e-02
-3.04508179e-01 -7.18278527e-01 -1.15027308e+00 -1.44702029e+00
1.55382544e-01 6.63069263e-02 5.18861890e-01 6.13838017e-01
1.05943508e-01 9.48513895e-02 -8.71296525e-01 -2.28672981e-01
9.89330649e-01 7.71690905e-02 6.03169858e-01 -1.15776515e+00
-3.96450460e-01 -3.66863221e-01 2.84941375e-01 -9.65415657e-01
2.57200837e-01 -7.83251166e-01 2.62225688e-01 -1.51669800e+00
2.15199664e-01 -9.49847579e-01 -7.99343050e-01 6.42251909e-01
-5.12278438e-01 -4.94316101e-01 3.43549430e-01 2.86456078e-01
-1.07566404e+00 9.78641331e-01 1.68927157e+00 -1.52897820e-01
-5.24516284e-01 2.34400183e-01 -5.30710399e-01 3.52899969e-01
1.20469093e+00 -8.41975391e-01 -6.15965903e-01 -4.92272198e-01
3.76398340e-02 3.04068595e-01 -1.39471784e-01 -1.26519060e+00
1.68148309e-01 -5.74257791e-01 1.87062532e-01 -3.44973654e-01
2.06540674e-01 -5.96658945e-01 -1.42996266e-01 7.39637733e-01
-4.68096077e-01 1.47009224e-01 1.04158849e-01 9.94259894e-01
4.89301644e-02 -3.26278567e-01 8.00316691e-01 -3.00298691e-01
-6.84148192e-01 4.42577600e-01 -6.48576677e-01 2.78448194e-01
1.28306472e+00 -2.35714074e-02 -4.28422749e-01 -2.48728693e-01
-7.05252409e-01 8.73962998e-01 1.28325552e-01 5.71175814e-01
5.66967726e-01 -1.33464539e+00 -6.90367460e-01 -1.04056433e-01
2.81738322e-02 -1.21063478e-01 6.88235462e-01 6.60162508e-01
2.67313302e-01 2.27713287e-01 -7.93255925e-01 -3.81629139e-01
-8.64502311e-01 5.40956676e-01 3.48569781e-01 -9.50805366e-01
-5.05249381e-01 4.18796688e-01 1.79869324e-01 -2.92717844e-01
3.44109267e-01 2.75364872e-02 -1.37362152e-01 5.92958815e-02
2.59503603e-01 7.11058021e-01 -5.86150587e-02 1.01227991e-01
-2.11944524e-02 1.00872129e-01 -5.50670981e-01 -1.68079376e-01
1.24715674e+00 -9.80065912e-02 4.86899942e-01 5.23410022e-01
4.57216799e-01 -5.26195288e-01 -1.92144930e+00 -6.06208324e-01
-6.31245002e-02 -6.57067120e-01 4.43000486e-03 -9.22578335e-01
-9.89399433e-01 7.15303957e-01 6.23019397e-01 2.87875235e-01
1.04222500e+00 -4.64674294e-01 8.27851772e-01 4.24307168e-01
7.01863110e-01 -1.68903995e+00 6.81854069e-01 6.87422514e-01
5.06695271e-01 -1.03693700e+00 -2.71101743e-01 1.49426296e-01
-1.00706685e+00 8.06940377e-01 1.11347187e+00 -1.36999905e-01
3.32578748e-01 -7.12655112e-02 -2.44004980e-01 3.39659035e-01
-1.15941846e+00 -4.14445788e-01 -3.68659198e-01 8.55820775e-01
-1.07717536e-01 2.14933187e-01 -3.35246652e-01 3.88937771e-01
3.97620857e-01 2.58465350e-01 3.83947134e-01 1.11690104e+00
-7.02521503e-01 -1.55225313e+00 -2.56638974e-01 7.89394975e-01
-4.79697883e-01 1.54811636e-01 1.86748907e-01 5.14860690e-01
-1.02290856e-02 7.60346651e-01 -4.94648889e-02 -2.77703583e-01
3.15684199e-01 2.18359903e-01 6.65512085e-01 -4.54884261e-01
-8.36267769e-01 2.03505427e-01 -1.71575874e-01 -4.97471809e-01
-3.40026945e-01 -6.41884208e-01 -1.01605463e+00 -1.62539467e-01
-1.95005722e-02 2.24645689e-01 4.12147373e-01 8.37168872e-01
4.47314143e-01 9.60895479e-01 9.29496169e-01 -6.31682158e-01
-1.13054991e+00 -9.02903616e-01 -9.28921819e-01 2.02575073e-01
3.26211274e-01 -9.90126371e-01 7.68086463e-02 -4.85832185e-01] | [3.963625431060791, 2.1230554580688477] |
19fd7783-a597-48b6-ac89-7ead8a2c537c | human-centric-image-cropping-with-partition | 2207.10269 | null | https://arxiv.org/abs/2207.10269v1 | https://arxiv.org/pdf/2207.10269v1.pdf | Human-centric Image Cropping with Partition-aware and Content-preserving Features | Image cropping aims to find visually appealing crops in an image, which is an important yet challenging task. In this paper, we consider a specific and practical application: human-centric image cropping, which focuses on the depiction of a person. To this end, we propose a human-centric image cropping method with two novel feature designs for the candidate crop: partition-aware feature and content-preserving feature. For partition-aware feature, we divide the whole image into nine partitions based on the human bounding box and treat different partitions in a candidate crop differently conditioned on the human information. For content-preserving feature, we predict a heatmap indicating the important content to be included in a good crop, and extract the geometric relation between the heatmap and a candidate crop. Extensive experiments demonstrate that our method can perform favorably against state-of-the-art image cropping methods on human-centric image cropping task. Code is available at https://github.com/bcmi/Human-Centric-Image-Cropping. | ['Liqing Zhang', 'Xing Zhao', 'Li Niu', 'Bo Zhang'] | 2022-07-21 | null | null | null | null | ['image-cropping'] | ['computer-vision'] | [ 3.40060592e-01 -5.54592982e-02 -1.65247675e-02 -3.39926593e-02
-4.55620408e-01 -5.53806484e-01 3.51331979e-01 3.73338252e-01
6.42426684e-03 1.49965987e-01 1.85248032e-01 -9.49428454e-02
2.70477235e-01 -9.30099249e-01 -8.52590322e-01 -6.24037802e-01
2.22117588e-01 -5.37991188e-02 1.60339430e-01 -1.91563711e-01
2.93430269e-01 2.64107138e-01 -1.65099990e+00 4.37723577e-01
9.11388636e-01 7.27452695e-01 5.08822322e-01 5.54283381e-01
1.84343413e-01 3.26605290e-01 -5.37220061e-01 -1.41272083e-01
3.67999971e-01 -5.99871099e-01 -5.48815191e-01 6.17236316e-01
4.42238212e-01 -1.44980811e-02 1.07840084e-01 1.15767658e+00
2.41632700e-01 -2.89494932e-01 8.10132742e-01 -1.59983289e+00
-8.03048491e-01 4.07845914e-01 -1.32457411e+00 -2.96129912e-01
3.73416424e-01 1.50582433e-01 8.03478420e-01 -1.15182054e+00
8.52000713e-01 1.31170595e+00 3.87824476e-01 9.64590684e-02
-1.16660333e+00 -7.75778711e-01 2.21658930e-01 9.62399319e-03
-1.38049972e+00 7.03507587e-02 1.06747830e+00 -6.75109327e-01
-3.91094200e-02 5.62518656e-01 1.05993366e+00 4.40653026e-01
1.46006674e-01 1.15364110e+00 1.34107220e+00 -6.96112096e-01
1.07714199e-01 1.73426479e-01 1.41410176e-02 7.79643297e-01
4.08882707e-01 -7.70246685e-02 -4.97668147e-01 -4.01842222e-02
8.35167050e-01 2.89247543e-01 -3.54587466e-01 -8.66170228e-01
-1.49535739e+00 6.43615425e-01 9.56255794e-01 1.72267020e-01
-5.34509242e-01 2.47975606e-02 -4.02522460e-02 -1.96721360e-01
4.91460472e-01 5.14979899e-01 -1.38239330e-02 5.24510562e-01
-1.18581212e+00 6.27440989e-01 2.81452179e-01 9.29871738e-01
1.07510436e+00 -3.97998482e-01 -3.52374166e-01 5.13398707e-01
-1.09273285e-01 7.29731739e-01 -3.84484269e-02 -6.39710844e-01
2.63924092e-01 9.52232540e-01 3.07589382e-01 -1.27762604e+00
-3.61313462e-01 -2.30873048e-01 -9.91485298e-01 4.18263614e-01
4.60782200e-01 -3.02472323e-01 -1.10571814e+00 1.26374149e+00
5.83166718e-01 -1.10153683e-01 -2.64096498e-01 1.20369160e+00
7.31807768e-01 5.79591095e-01 2.13612407e-01 1.34785071e-01
1.86050880e+00 -1.24183333e+00 -5.26794016e-01 -2.25285515e-01
2.09275559e-01 -9.64774966e-01 1.23836875e+00 2.63752252e-01
-9.54899311e-01 -5.31597435e-01 -1.17910469e+00 -7.23059997e-02
-5.44528961e-01 7.03423202e-01 2.84091085e-01 4.69691664e-01
-8.87992561e-01 1.40393123e-01 -1.98184595e-01 -5.48027396e-01
2.41706148e-01 -2.34058708e-01 -3.61027330e-01 -2.88236916e-01
-8.10937703e-01 5.25836468e-01 5.44136763e-01 -1.89853758e-01
-5.59116364e-01 -7.98982680e-01 -9.87446606e-01 2.44367436e-01
3.52887362e-01 -5.83628058e-01 8.15542340e-01 -1.04148769e+00
-6.71888232e-01 1.06019330e+00 -2.68705666e-01 -2.12483168e-01
5.10142565e-01 -1.38975531e-01 -3.77840661e-02 3.03679824e-01
2.50114173e-01 1.13377345e+00 1.24192584e+00 -1.87179101e+00
-8.14275205e-01 -1.49196640e-01 -1.11451708e-01 4.24939424e-01
-3.03089648e-01 -1.88181907e-01 -5.94302237e-01 -9.83015478e-01
-1.84831712e-02 -9.73876119e-01 -2.06340209e-01 3.79981816e-01
-8.42652202e-01 1.22771293e-01 9.56725299e-01 -9.38175559e-01
1.36080194e+00 -2.25766468e+00 -1.34977296e-01 2.95900673e-01
3.11802566e-01 7.44547322e-02 -1.87826216e-01 5.15935540e-01
-6.51593953e-02 2.55430281e-01 -5.87575257e-01 -5.83567992e-02
-1.89106688e-01 -6.08850181e-01 -5.96909784e-03 4.06474084e-01
5.29944241e-01 1.11017883e+00 -8.90731573e-01 -7.53518522e-01
3.80756080e-01 5.60686409e-01 -1.92616016e-01 9.23014432e-02
-1.16668276e-01 3.04019392e-01 -3.93471569e-01 9.78407919e-01
1.12732208e+00 -2.72959560e-01 1.23453408e-01 -4.35046822e-01
-1.53260008e-01 -6.43329918e-01 -9.61359799e-01 1.45398784e+00
-1.76491782e-01 6.18182778e-01 -1.14788979e-01 -3.93302798e-01
1.04721665e+00 -1.42164901e-01 4.01211500e-01 -5.20494640e-01
7.40846768e-02 -5.23083135e-02 -4.15957272e-01 -2.16422081e-01
8.86301935e-01 2.75833189e-01 -1.59985989e-01 5.16377509e-01
-5.49626470e-01 -2.24123091e-01 3.31437677e-01 1.40162602e-01
5.82573473e-01 2.21068695e-01 5.80206037e-01 -5.56398988e-01
2.97798157e-01 2.95880646e-01 2.82915115e-01 3.59920472e-01
-2.24711031e-01 1.10873973e+00 4.81087387e-01 -4.19793546e-01
-1.12629831e+00 -8.53849947e-01 1.30867794e-01 1.04087818e+00
7.97392666e-01 -2.30477527e-01 -1.21890438e+00 -5.82222104e-01
2.29754820e-01 5.18492579e-01 -1.03024209e+00 1.39159113e-01
-4.54801977e-01 -5.33712387e-01 -1.34796977e-01 2.80024290e-01
5.80531180e-01 -1.29394805e+00 -1.07995772e+00 -1.12197928e-01
-5.96403718e-01 -8.60887647e-01 -9.10211027e-01 -7.93365911e-02
-2.51024216e-01 -1.32682931e+00 -1.48263061e+00 -1.17621207e+00
1.09690535e+00 9.66119409e-01 1.12836862e+00 3.05642039e-01
-5.88854134e-01 1.79438278e-01 -5.59351504e-01 -6.40304327e-01
-5.23903482e-02 8.52365568e-02 -5.60428143e-01 1.51876166e-01
2.23552465e-01 -2.29774024e-02 -1.07319605e+00 3.91086459e-01
-9.85766709e-01 6.01868808e-01 7.29168117e-01 7.31800556e-01
6.45820975e-01 1.37235314e-01 1.06911294e-01 -7.47600675e-01
6.88624561e-01 -4.68611419e-01 -2.53087074e-01 6.92277253e-01
-2.51532286e-01 -1.33324265e-01 1.96577325e-01 -4.60266888e-01
-8.09504569e-01 5.03640056e-01 7.17855334e-01 -3.19304109e-01
1.36662750e-02 3.11969370e-01 -1.80189893e-01 -2.75737140e-02
5.89900196e-01 2.44084984e-01 -5.18803746e-02 -2.11860716e-01
7.72110462e-01 4.50587094e-01 5.05156696e-01 -3.18235010e-01
1.06964576e+00 4.68391865e-01 -9.44278389e-02 -7.25885689e-01
-4.02933747e-01 -5.73722363e-01 -7.61856437e-01 -5.27704597e-01
9.36124682e-01 -8.76716912e-01 -5.47441304e-01 4.91344601e-01
-1.04949236e+00 -3.21008205e-01 -1.51584417e-01 -9.88342613e-02
-4.45512712e-01 2.67594457e-01 -4.94481511e-02 -8.14629793e-01
-6.11809671e-01 -9.28060651e-01 1.50181556e+00 5.99678159e-01
-2.20773201e-02 -4.23028946e-01 -2.52363861e-01 1.19970471e-01
1.55320346e-01 8.43304992e-01 8.48350823e-01 1.51943475e-01
-6.32628143e-01 -2.21774206e-01 -7.59964645e-01 -7.57777616e-02
1.43175706e-01 1.89083040e-01 -8.34114373e-01 -2.87161618e-01
-7.57730365e-01 -8.25223029e-02 9.64929521e-01 5.87815225e-01
9.72024143e-01 -1.71498910e-01 -6.64219081e-01 2.72441387e-01
1.48508692e+00 6.29823208e-02 6.38252974e-01 3.41165632e-01
7.54846156e-01 9.10867929e-01 1.19521248e+00 5.00945747e-01
3.61501187e-01 4.51487839e-01 4.67293054e-01 -9.00722325e-01
-2.63582230e-01 -6.65536404e-01 1.75451823e-02 7.00149089e-02
1.82641611e-01 -4.04419780e-01 -7.92033851e-01 9.00833905e-01
-1.80080295e+00 -5.59157848e-01 -5.87685481e-02 2.13319468e+00
4.49201703e-01 -1.90426469e-01 4.55150098e-01 1.34004563e-01
1.23551798e+00 1.87655821e-01 -5.58139861e-01 -4.82207946e-02
-2.47652635e-01 -1.13906160e-01 6.77105606e-01 9.04666334e-02
-1.38941491e+00 1.04340053e+00 5.48711300e+00 9.54298317e-01
-1.03153515e+00 -2.44437411e-01 1.16824496e+00 1.94306523e-01
-2.48036265e-01 -1.06336653e-01 -4.84414935e-01 5.47899187e-01
-3.37374047e-03 -3.62566739e-01 1.47459477e-01 7.30730951e-01
1.55144885e-01 -5.65851510e-01 -6.34683728e-01 1.01079381e+00
1.61090255e-01 -1.04792953e+00 1.35045350e-01 2.01361626e-02
8.18360209e-01 -8.56673717e-01 3.72297585e-01 -2.49001488e-01
7.86856189e-02 -9.52557027e-01 1.01435637e+00 4.08660263e-01
9.78666186e-01 -8.12667727e-01 2.94022292e-01 9.47803911e-03
-1.81095421e+00 -7.77844787e-02 -2.48593688e-01 1.86874583e-01
1.42744258e-01 6.90326512e-01 -6.53548121e-01 4.42657650e-01
8.86207402e-01 6.80076659e-01 -8.81078184e-01 1.20639503e+00
-1.92917258e-01 2.50812113e-01 3.11148930e-02 1.02555263e-03
7.45351464e-02 -1.78899065e-01 3.19938213e-01 1.30553639e+00
5.85025728e-01 -4.59734835e-02 3.29146743e-01 8.71031642e-01
-6.39966950e-02 4.50424254e-01 -6.12148345e-01 8.07912797e-02
5.59560061e-01 1.52135718e+00 -1.18216538e+00 -3.06471676e-01
-6.65187612e-02 1.22376060e+00 1.00489579e-01 2.82323658e-01
-6.50462806e-01 -5.07578909e-01 4.16472644e-01 5.92134297e-01
4.59113449e-01 3.41224372e-02 -3.80861223e-01 -8.14940274e-01
2.45232120e-01 -8.92233253e-01 2.27204278e-01 -1.14972496e+00
-9.44840670e-01 5.54437160e-01 -9.98237450e-03 -1.64853001e+00
2.14223832e-01 -3.90720040e-01 -6.76844656e-01 7.72292733e-01
-1.39566970e+00 -1.77762938e+00 -8.70673358e-01 2.59922743e-01
5.28063715e-01 2.33933315e-01 4.96015817e-01 -1.66025922e-01
-3.13599885e-01 4.72550333e-01 -7.48762563e-02 1.72595218e-01
9.08910453e-01 -1.09632885e+00 8.16775501e-01 1.09633219e+00
5.54308482e-02 2.41482258e-01 7.38421202e-01 -7.96418071e-01
-1.04584992e+00 -1.28936243e+00 7.97657847e-01 -9.86788124e-02
2.02164382e-01 -4.74041164e-01 -6.18669331e-01 2.15617493e-01
4.64350462e-01 -1.07254587e-01 1.30404904e-01 -3.86055857e-01
-3.71891499e-01 9.34806019e-02 -1.27039909e+00 8.43978643e-01
8.45304012e-01 -4.38308716e-02 5.91908395e-03 2.79659718e-01
7.95393527e-01 -3.31370652e-01 -5.36273003e-01 2.64925778e-01
7.66848564e-01 -8.70882750e-01 1.19009697e+00 1.47233419e-02
6.53024912e-01 -5.66741884e-01 2.01722845e-01 -1.44410229e+00
-5.58899701e-01 -4.92296398e-01 1.92348033e-01 1.07303178e+00
2.43780062e-01 -2.17924416e-01 7.77780235e-01 3.15143108e-01
4.64688271e-01 -8.09311450e-01 -1.86132416e-01 -5.19334435e-01
6.62010070e-03 3.69598180e-01 9.03922319e-01 8.67196977e-01
1.14741564e-01 -1.15049757e-01 -7.81375408e-01 1.49671435e-01
6.99429572e-01 5.04816294e-01 9.69722807e-01 -1.07186747e+00
1.73954070e-01 -3.78083766e-01 -1.85299203e-01 -7.11562634e-01
-4.46317524e-01 -4.39567417e-01 1.44215152e-01 -1.60967970e+00
6.87017977e-01 -3.20194781e-01 -1.82460248e-01 5.75371087e-01
-7.53717124e-01 5.67928910e-01 7.80987203e-01 7.98137337e-02
-4.15272683e-01 3.29283595e-01 1.56547678e+00 -3.30758750e-01
-2.35534981e-01 -4.18471694e-01 -1.00945640e+00 4.02727842e-01
1.07648098e+00 -2.92498678e-01 -2.21372738e-01 -5.15555628e-02
-2.19359055e-01 -9.47293416e-02 5.06479502e-01 -1.15387285e+00
1.05259188e-01 -3.15605044e-01 6.68387055e-01 -8.69581580e-01
2.94932365e-01 -7.51640379e-01 1.75728917e-01 7.20921457e-01
-2.78899133e-01 1.54393718e-01 1.25412285e-01 5.23455560e-01
-9.60262790e-02 8.90647173e-02 7.99751759e-01 -1.25921905e-01
-9.50535178e-01 1.20295800e-01 -1.02539532e-01 -1.69604510e-01
1.42009664e+00 -2.02640966e-01 -4.82749075e-01 -4.87804890e-01
-2.84679532e-01 3.48753214e-01 8.86641741e-01 5.93048990e-01
7.27376223e-01 -1.33695138e+00 -9.67334628e-01 1.28184885e-01
6.06429815e-01 -1.78440705e-01 3.81689548e-01 5.72667062e-01
-7.33879209e-01 2.22904220e-01 -5.05227983e-01 -5.23531258e-01
-1.85857403e+00 9.18487549e-01 -1.10251851e-01 -3.01097780e-01
-7.37425208e-01 5.34390152e-01 9.36855495e-01 -9.64291617e-02
-7.57398233e-02 -3.28433394e-01 -2.60443419e-01 3.10072787e-02
6.15882576e-01 3.00782770e-01 -3.33414286e-01 -7.65582085e-01
-2.60141730e-01 9.12495732e-01 -1.17711127e-02 -4.16797586e-02
9.22228158e-01 -2.36511573e-01 1.50018290e-01 2.86837406e-02
9.59609210e-01 -1.79800317e-01 -1.42792356e+00 -3.18613976e-01
-1.87235579e-01 -7.99746573e-01 -2.83281505e-01 -1.02557969e+00
-1.26543546e+00 7.60883808e-01 8.01660001e-01 8.99026841e-02
1.47938168e+00 -1.95196494e-01 7.06777573e-01 -2.51091212e-01
4.13313210e-01 -8.38489830e-01 1.79857016e-01 -1.87435791e-01
1.24443161e+00 -1.30170178e+00 3.44264627e-01 -8.94145250e-01
-1.01916766e+00 8.15528333e-01 5.80537140e-01 -3.17984581e-01
6.30573690e-01 1.15261495e-01 2.87104458e-01 -2.32740745e-01
-1.46475926e-01 -4.99203324e-01 6.26825035e-01 8.32783222e-01
3.19024980e-01 5.56999147e-01 -3.45378995e-01 3.29412669e-01
-1.55761689e-01 -1.09740131e-01 4.44356561e-01 1.02078009e+00
-6.24716163e-01 -7.97174871e-01 -8.33080292e-01 3.26496571e-01
1.15809992e-01 -1.74980968e-01 -6.58497930e-01 8.86760056e-01
2.49561504e-01 8.68721247e-01 -4.19429652e-02 -3.86189312e-01
2.41938204e-01 -2.67424762e-01 3.15568000e-01 -2.05191344e-01
-6.14502728e-01 2.43381366e-01 -2.67674029e-01 -3.57361943e-01
-2.62117684e-01 -5.84525168e-01 -8.74327242e-01 -3.50309968e-01
-9.46811810e-02 -2.28449866e-01 6.08815789e-01 2.23010093e-01
4.50263023e-01 3.38513076e-01 6.45339131e-01 -1.23075843e+00
3.11626881e-01 -7.71345854e-01 -7.99780846e-01 5.73246658e-01
2.17714548e-01 -7.29656637e-01 1.47656817e-02 4.41891104e-01] | [11.331032752990723, -1.0477385520935059] |
f11bbcf9-3752-4ca6-8aa4-e80083b33bc0 | code-mvp-learning-to-represent-source-code | 2205.02029 | null | https://arxiv.org/abs/2205.02029v1 | https://arxiv.org/pdf/2205.02029v1.pdf | CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training | Recent years have witnessed increasing interest in code representation learning, which aims to represent the semantics of source code into distributed vectors. Currently, various works have been proposed to represent the complex semantics of source code from different views, including plain text, Abstract Syntax Tree (AST), and several kinds of code graphs (e.g., Control/Data Flow Graph). However, most of them only consider a single view of source code independently, ignoring the correspondences among different views. In this paper, we propose to integrate different views with the natural-language description of source code into a unified framework with Multi-View contrastive Pre-training, and name our model as CODE-MVP. Specifically, we first extract multiple code views using compiler tools, and learn the complementary information among them under a contrastive learning framework. Inspired by the type checking in compilation, we also design a fine-grained type inference objective in the pre-training. Experiments on three downstream tasks over five datasets demonstrate the superiority of CODE-MVP when compared with several state-of-the-art baselines. For example, we achieve 2.4/2.3/1.1 gain in terms of MRR/MAP/Accuracy metrics on natural language code retrieval, code similarity, and code defect detection tasks, respectively. | ['Jin Liu', 'Hao Wu', 'Li Li', 'Pingyi Zhou', 'Jiawei Wang', 'Yao Wan', 'Yasheng Wang', 'Xin Wang'] | 2022-05-04 | null | https://aclanthology.org/2022.findings-naacl.80 | https://aclanthology.org/2022.findings-naacl.80.pdf | findings-naacl-2022-7 | ['defect-detection'] | ['computer-vision'] | [-3.80813591e-02 -4.08199131e-01 -5.89356303e-01 -4.42235708e-01
-8.49448264e-01 -8.21299732e-01 4.56109881e-01 5.18453121e-01
1.74035758e-01 -1.80207014e-01 4.61070985e-01 -3.72656584e-01
2.03160256e-01 -7.77996242e-01 -7.61092722e-01 -2.53268480e-01
2.11394802e-01 -2.06875399e-01 2.09436148e-01 -2.51814902e-01
5.33955038e-01 -3.08158785e-01 -1.55440831e+00 7.03752935e-01
8.56233597e-01 6.91420078e-01 3.33809108e-01 4.04954046e-01
-6.66064799e-01 1.19116402e+00 -5.03734469e-01 -6.50695682e-01
-3.76401573e-01 -1.83556840e-01 -7.27493584e-01 -6.91295266e-02
4.63538647e-01 -4.53471467e-02 -2.59878904e-01 1.37780917e+00
1.04047872e-01 -3.35722834e-01 4.23351198e-01 -1.36782742e+00
-1.04755557e+00 8.40591788e-01 -9.58141565e-01 -1.86173357e-02
5.08620381e-01 -6.56653419e-02 1.35498917e+00 -1.07030416e+00
6.48529112e-01 1.28480482e+00 4.01761681e-01 4.73969728e-01
-1.12040091e+00 -4.23217326e-01 3.37113947e-01 2.92885035e-01
-1.03171587e+00 -1.85091794e-01 8.21093142e-01 -7.97671020e-01
1.04627359e+00 1.13336936e-01 2.58378685e-01 9.78637099e-01
4.05877322e-01 1.01577795e+00 8.00144970e-01 -1.67364269e-01
8.93530101e-02 1.39656603e-01 4.98265058e-01 1.06700420e+00
3.49981815e-01 -3.09201896e-01 -2.44770214e-01 -5.76758027e-01
1.78602457e-01 3.65846038e-01 -3.19393933e-01 -9.53776181e-01
-1.27238727e+00 8.84599447e-01 5.36066234e-01 2.26554185e-01
2.20115870e-01 3.02950382e-01 1.21011710e+00 3.82396549e-01
2.20322058e-01 1.22714035e-01 -5.08901894e-01 -1.27480328e-01
-6.24602437e-01 -6.94704130e-02 6.90088093e-01 1.40937781e+00
9.62419510e-01 1.23623632e-01 -1.68976877e-02 1.10448492e+00
6.65151834e-01 5.66713512e-01 6.65856779e-01 -5.26530564e-01
1.14699590e+00 1.26603520e+00 -4.94575113e-01 -1.11000729e+00
-3.86878625e-02 -4.22096729e-01 -8.22911441e-01 7.25999177e-02
-2.33468458e-01 2.65423417e-01 -5.96614063e-01 1.52269876e+00
1.34620778e-02 -1.65437281e-01 3.17604482e-01 5.75635731e-01
9.58804369e-01 7.40310311e-01 -2.13153109e-01 2.01710269e-01
1.37887836e+00 -1.26732850e+00 -3.36705923e-01 -5.08094132e-01
1.10549343e+00 -6.16636097e-01 1.08155751e+00 2.37946004e-01
-7.40567982e-01 -6.49142742e-01 -1.18912733e+00 -1.24313369e-01
-4.09722954e-01 4.27203536e-01 6.60569906e-01 4.62940961e-01
-8.54303956e-01 2.81662434e-01 -8.46322000e-01 -7.35574663e-02
3.08690369e-01 -9.83014628e-02 -5.09361982e-01 -3.50617826e-01
-6.48721874e-01 3.27991575e-01 4.05796379e-01 -2.95962870e-01
-1.09175813e+00 -8.27715516e-01 -1.24849200e+00 3.33773166e-01
5.05085409e-01 -5.08352280e-01 1.06912708e+00 -9.83403623e-01
-8.65601063e-01 8.53716016e-01 -2.55986869e-01 1.39869690e-01
-1.87010705e-01 -1.28975287e-01 -5.91157138e-01 -2.58290529e-01
3.22115123e-01 -1.05036579e-01 5.89065015e-01 -1.54621136e+00
-5.59312105e-01 -4.23199117e-01 5.83115697e-01 -2.00521275e-01
-4.48225021e-01 2.58541793e-01 -7.24220991e-01 -6.26558959e-01
6.02772553e-03 -7.92360485e-01 9.20431539e-02 1.38782877e-02
-3.11349452e-01 -2.48126879e-01 8.33332658e-01 -7.93849409e-01
1.53066933e+00 -2.57105708e+00 6.95672631e-01 -1.19185574e-01
6.17040694e-01 6.21129796e-02 -2.01114088e-01 6.57063365e-01
-2.16600493e-01 3.27553213e-01 -5.73625684e-01 -4.21620198e-02
1.71349630e-01 1.15491547e-01 -5.37262976e-01 4.79982853e-01
5.09677418e-02 8.18568051e-01 -1.14839673e+00 -3.82246494e-01
-2.09083378e-01 1.60570174e-01 -8.80490422e-01 2.78052449e-01
-3.48779470e-01 -1.30975783e-01 -7.42930830e-01 7.34552443e-01
6.07654274e-01 -5.20833135e-01 3.01118106e-01 -4.95594814e-02
-4.13856022e-02 2.34945297e-01 -9.22384560e-01 2.22296238e+00
-1.05239737e+00 5.57790637e-01 1.20731210e-03 -1.04018235e+00
8.52108419e-01 1.88051701e-01 4.69985465e-03 -5.89354992e-01
-2.71505803e-01 3.53475094e-01 -4.95621152e-02 -7.09727287e-01
3.38427842e-01 2.25804090e-01 -6.46770895e-01 5.78120053e-01
2.33075023e-01 1.06455497e-01 1.77756146e-01 4.65007514e-01
1.07544959e+00 3.87694895e-01 5.04791975e-01 -3.22001725e-01
9.03151393e-01 -1.49431363e-01 6.69087648e-01 3.80799323e-01
2.28017300e-01 4.71381247e-01 1.05687916e+00 -3.42958093e-01
-7.36570299e-01 -9.46719170e-01 2.33609006e-01 1.23125410e+00
4.21830773e-01 -1.16949344e+00 -5.58028162e-01 -1.12768126e+00
1.32815093e-02 4.64399874e-01 -5.31911731e-01 -3.45796227e-01
-8.94143105e-01 -5.31749785e-01 5.70966244e-01 8.84534836e-01
3.62241805e-01 -5.80730617e-01 -5.39015174e-01 5.26469462e-02
-1.17437631e-01 -7.26083159e-01 -6.53473794e-01 -1.24508008e-01
-7.76908755e-01 -1.25229657e+00 -4.10732359e-01 -8.90217841e-01
5.48664987e-01 4.46546108e-01 1.45538557e+00 5.43873012e-01
-2.91335378e-02 3.19401830e-01 -5.62615514e-01 1.26142934e-01
-7.91077554e-01 -1.24962898e-02 -5.00566840e-01 -1.47105560e-01
1.25875250e-01 -4.45165813e-01 -3.26803416e-01 4.74298932e-02
-1.04168880e+00 8.78209900e-03 6.25332952e-01 9.76484179e-01
4.45205361e-01 -2.44460478e-01 1.26462922e-01 -1.13186753e+00
2.94512182e-01 -9.68958676e-01 -6.82471275e-01 5.61507821e-01
-5.70755839e-01 3.95604044e-01 1.06134105e+00 -9.10472497e-02
-1.11930120e+00 -2.49631718e-01 8.61975644e-03 -5.76361716e-01
5.63176274e-02 1.09608388e+00 -4.71059322e-01 9.98774543e-02
5.56832373e-01 6.35637879e-01 -2.80353367e-01 -5.21820307e-01
4.35908377e-01 7.85491824e-01 2.60944188e-01 -8.96570027e-01
8.52236271e-01 3.47365588e-01 -3.47746730e-01 -3.05536121e-01
-5.94004929e-01 -5.61502218e-01 -3.64099115e-01 2.43166998e-01
6.31785154e-01 -9.82370615e-01 -2.01578826e-01 4.30665433e-01
-1.27196801e+00 1.07240997e-01 2.93468446e-01 8.48970935e-02
-5.15819252e-01 6.05521023e-01 -5.27850449e-01 -1.81707114e-01
-1.29037678e-01 -1.67477345e+00 1.31526935e+00 -1.13734245e-01
9.23327357e-02 -9.87145305e-01 1.44658983e-01 1.86949059e-01
4.32357609e-01 1.23223290e-01 1.66300368e+00 -4.76626307e-01
-7.15659440e-01 1.58826336e-01 -3.41230780e-01 3.87525350e-01
2.49580756e-01 1.52969852e-01 -9.56759572e-01 -5.16373634e-01
3.28076258e-02 -3.46656322e-01 8.31454575e-01 -2.73003101e-01
1.38431168e+00 -3.20912242e-01 -6.13316774e-01 8.47746015e-01
1.86658752e+00 1.81375176e-01 4.41728532e-01 1.40343085e-01
1.10849655e+00 5.21422446e-01 4.28004384e-01 3.89295161e-01
5.61019599e-01 5.81773221e-01 8.09703827e-01 3.28298271e-01
4.37862165e-02 -4.49314952e-01 5.47176480e-01 1.38367450e+00
4.38808739e-01 -1.51331022e-01 -1.12140906e+00 6.74025536e-01
-1.79480493e+00 -8.37538838e-01 -1.70975819e-01 2.02708983e+00
5.38797438e-01 -4.73115928e-02 -1.72252148e-01 -1.30599752e-01
7.20819354e-01 5.58364213e-01 -4.95213568e-01 -3.64137053e-01
4.02008533e-01 -2.62340337e-01 3.14467162e-01 1.45041063e-01
-1.03430831e+00 5.15318990e-01 4.58017111e+00 8.05812001e-01
-1.09005821e+00 2.63242304e-01 2.49664307e-01 3.84904295e-01
-9.48094606e-01 4.58212793e-01 -4.77097124e-01 4.93309289e-01
7.92816043e-01 -6.51621640e-01 4.05745089e-01 1.28192341e+00
-6.18745506e-01 3.85087788e-01 -1.42485189e+00 1.02499366e+00
3.94837946e-01 -1.42063570e+00 2.56997764e-01 -1.24986961e-01
6.53148890e-01 1.10431843e-01 -1.77097544e-01 8.41286242e-01
1.04691185e-01 -7.53655970e-01 8.65499735e-01 2.36212596e-01
8.67119253e-01 -5.83814263e-01 6.40945435e-01 3.50425810e-01
-1.83775878e+00 -2.05419093e-01 -2.99396783e-01 2.31753245e-01
-4.05846059e-01 2.84421593e-01 -1.50089310e-02 1.07124734e+00
6.10506058e-01 1.30479288e+00 -9.68396127e-01 8.49163830e-01
-4.39675972e-02 3.15370739e-01 5.13999343e-01 -1.29104584e-01
1.83435202e-01 -5.32472990e-02 2.59353936e-01 1.33421588e+00
4.09078091e-01 -4.61584151e-01 2.52778322e-01 1.27063453e+00
-3.66288185e-01 6.91576973e-02 -7.90444791e-01 -1.24407545e-01
3.96588355e-01 1.21846366e+00 -3.86977762e-01 -5.45350373e-01
-1.17766869e+00 7.91241884e-01 4.99065012e-01 1.97366938e-01
-9.06896949e-01 -6.99548125e-01 7.89535642e-01 -3.51172000e-01
3.36782336e-01 2.85948180e-02 1.00343749e-01 -1.72288299e+00
5.70742190e-01 -1.20956087e+00 4.69098717e-01 -6.47092104e-01
-1.12878168e+00 6.03687704e-01 1.78187132e-01 -1.51821828e+00
-2.00130671e-01 -6.96809292e-01 -6.83589935e-01 8.36073160e-01
-1.45791590e+00 -9.44425344e-01 -2.49058247e-01 2.57041216e-01
8.70660901e-01 -4.72509384e-01 8.20046127e-01 4.11184818e-01
-4.52311218e-01 6.48391128e-01 2.75781870e-01 3.68730426e-01
4.56437498e-01 -1.44436216e+00 7.39131033e-01 9.61298585e-01
1.28161058e-01 1.15845847e+00 1.43051490e-01 -3.93806785e-01
-2.11467147e+00 -1.26226699e+00 5.24519444e-01 -4.72684681e-01
9.10472512e-01 -4.90173340e-01 -1.23836279e+00 8.19568515e-01
3.46236408e-01 3.19294274e-01 5.63048422e-01 7.31988102e-02
-1.22419918e+00 -8.05724263e-02 -7.18061447e-01 4.29896861e-01
9.45401788e-01 -9.42471743e-01 -7.05012858e-01 1.61762029e-01
8.61851692e-01 -5.16552448e-01 -9.93586123e-01 2.37436205e-01
3.32840383e-01 -1.05059004e+00 9.06264067e-01 -6.00426853e-01
1.06526399e+00 -3.92901838e-01 -5.32068670e-01 -1.43220663e+00
-4.16794300e-01 -9.74665135e-02 -1.05039865e-01 1.57944286e+00
2.26346925e-01 -4.72365439e-01 3.68153304e-01 -7.34136328e-02
-5.07219136e-01 -7.16456234e-01 -5.28865397e-01 -6.95312083e-01
1.74473241e-01 -3.36067677e-01 6.83604240e-01 1.15086889e+00
2.53462464e-01 4.43573922e-01 -3.22441496e-02 2.86088437e-01
4.98769164e-01 8.24884534e-01 7.15274751e-01 -1.09858859e+00
-7.23534465e-01 -6.41732156e-01 -6.23590410e-01 -9.69090879e-01
5.88436067e-01 -1.51784253e+00 -1.36439353e-01 -1.55556405e+00
7.10090935e-01 -1.78512394e-01 -3.76971096e-01 4.22719002e-01
-3.50158393e-01 -5.46581805e-01 7.60665014e-02 2.93903500e-01
-4.48169112e-01 5.42050242e-01 8.60701621e-01 -7.16960430e-01
4.22556281e-01 -3.63416135e-01 -8.78568232e-01 7.43910789e-01
5.35390377e-01 -6.09801650e-01 -6.91787779e-01 -1.06834805e+00
4.95936602e-01 5.12242019e-01 4.06112760e-01 -8.57017100e-01
1.23187803e-01 -1.86043903e-01 -3.21996033e-01 -2.50956029e-01
-5.13684265e-02 -7.43763328e-01 -4.46611550e-03 4.98209715e-01
-3.95343632e-01 4.65681970e-01 1.76546350e-01 8.41001749e-01
-6.34510636e-01 -6.20269418e-01 4.70923960e-01 -4.04548794e-01
-1.22832584e+00 2.67557114e-01 -2.10395046e-02 4.39256877e-01
6.99594736e-01 3.22055966e-01 -9.42515373e-01 3.17019522e-01
-6.65046126e-02 1.88984454e-01 7.97543764e-01 1.05743110e+00
7.35278547e-01 -1.39935136e+00 -6.48676932e-01 3.61203104e-01
1.04027009e+00 -3.05845559e-01 2.07358390e-01 4.79973644e-01
-4.28847671e-01 1.83924556e-01 -9.34904963e-02 -6.15583181e-01
-1.20794773e+00 9.54807699e-01 1.96958467e-01 -2.29778960e-01
-7.10093796e-01 6.09623194e-01 6.40344083e-01 -6.49905443e-01
-1.22545836e-02 -3.93887430e-01 -2.04895332e-01 -5.20359129e-02
5.73991179e-01 1.73198059e-01 1.00610755e-01 -5.88445604e-01
-6.50572836e-01 8.13552797e-01 -2.64476955e-01 4.59147334e-01
1.21218169e+00 2.99435318e-01 -6.32406652e-01 7.36378849e-01
1.85900354e+00 2.15466514e-01 -8.37545812e-01 -3.58694971e-01
3.43159646e-01 -6.16809309e-01 -1.27135664e-01 -4.86273587e-01
-1.40913653e+00 1.18066382e+00 3.59685302e-01 1.59734875e-01
8.81645203e-01 1.72675624e-01 5.19991636e-01 4.25744385e-01
6.31813467e-01 -5.01239181e-01 1.41570300e-01 5.86110651e-01
8.45667303e-01 -1.17297614e+00 -2.35817820e-01 -4.15625840e-01
-5.12803972e-01 1.27572298e+00 7.97287643e-01 -5.58223799e-02
3.68073016e-01 3.85621786e-01 -1.19099356e-01 -4.10483897e-01
-1.03677177e+00 1.71526581e-01 2.13597417e-01 4.08076525e-01
7.72819996e-01 3.39743769e-04 -1.56459003e-03 5.36128402e-01
3.79795730e-01 -1.87397376e-01 7.52087295e-01 1.21467245e+00
-2.35025480e-01 -1.24534631e+00 3.74254235e-03 6.19043469e-01
-3.59608650e-01 -3.13276291e-01 -1.07831888e-01 7.25917697e-01
-9.90993679e-02 7.25710571e-01 -2.98724949e-01 -6.21342540e-01
4.96177822e-01 -2.03349199e-02 2.04349458e-01 -1.12925601e+00
-7.33590484e-01 -2.78097659e-01 -2.34959021e-01 -7.61483252e-01
-2.25655958e-01 -5.47704875e-01 -1.20717418e+00 1.41956527e-02
-1.67687908e-01 1.44481674e-01 4.17815328e-01 6.73734844e-01
5.21903336e-01 8.02999735e-01 7.20956385e-01 -3.51287842e-01
-7.07768619e-01 -5.30456007e-01 -3.71414989e-01 5.45282781e-01
5.05401731e-01 -5.96317291e-01 -4.50621814e-01 1.69970825e-01] | [7.503148555755615, 7.9898505210876465] |
98486603-11fc-4095-9fa3-32bdb0431451 | self-supervised-learning-for-few-shot-image | 1911.06045 | null | https://arxiv.org/abs/1911.06045v3 | https://arxiv.org/pdf/1911.06045v3.pdf | Self-Supervised Learning For Few-Shot Image Classification | Few-shot image classification aims to classify unseen classes with limited labelled samples. Recent works benefit from the meta-learning process with episodic tasks and can fast adapt to class from training to testing. Due to the limited number of samples for each task, the initial embedding network for meta-learning becomes an essential component and can largely affect the performance in practice. To this end, most of the existing methods highly rely on the efficient embedding network. Due to the limited labelled data, the scale of embedding network is constrained under a supervised learning(SL) manner which becomes a bottleneck of the few-shot learning methods. In this paper, we proposed to train a more generalized embedding network with self-supervised learning (SSL) which can provide robust representation for downstream tasks by learning from the data itself. We evaluate our work by extensive comparisons with previous baseline methods on two few-shot classification datasets ({\em i.e.,} MiniImageNet and CUB) and achieve better performance over baselines. Tests on four datasets in cross-domain few-shot learning classification show that the proposed method achieves state-of-the-art results and further prove the robustness of the proposed model. Our code is available at \hyperref[https://github.com/phecy/SSL-FEW-SHOT.]{https://github.com/phecy/SSL-FEW-SHOT.} | ['Hui Xue', 'Yuan He', 'Yuhong Li', 'Yuefeng Chen', 'Da Chen', 'Feng Mao'] | 2019-11-14 | null | null | null | null | ['cross-domain-few-shot', 'cross-domain-few-shot-learning', 'unsupervised-few-shot-image-classification'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [-1.01971216e-01 -6.08723015e-02 -5.05151212e-01 -3.73678714e-01
-7.46512413e-01 -6.28492087e-02 6.04489684e-01 -6.35195300e-02
-4.98286366e-01 6.62817419e-01 1.53693045e-02 1.22164048e-01
-5.19129187e-02 -7.71022856e-01 -6.04577482e-01 -7.35711694e-01
1.19733311e-01 2.04845443e-01 5.09475172e-01 -2.42264315e-01
9.06459801e-03 6.38458729e-02 -1.86475492e+00 4.02099550e-01
6.39354885e-01 1.01976562e+00 4.42667335e-01 5.26095390e-01
-1.22990765e-01 9.03551280e-01 -4.20174599e-01 -3.05582225e-01
2.17271283e-01 -6.04618728e-01 -7.41328895e-01 -5.85755371e-02
1.12679169e-01 -4.04801816e-01 -6.44128621e-01 1.00637507e+00
8.77610743e-01 4.66440797e-01 6.82936490e-01 -1.50375915e+00
-7.07992136e-01 3.80930483e-01 -2.59743154e-01 5.07462442e-01
-2.41098851e-01 3.79174858e-01 8.60080659e-01 -1.24391520e+00
7.93421984e-01 7.45058119e-01 5.76606870e-01 1.02941847e+00
-9.75801885e-01 -7.42049456e-01 2.54295599e-02 8.10621619e-01
-1.23257315e+00 -7.76990592e-01 8.00255120e-01 -2.29653969e-01
9.44175482e-01 -1.19933039e-01 5.10830283e-01 1.49103558e+00
3.83513011e-02 9.57782388e-01 1.05875683e+00 -4.74338382e-01
6.51858091e-01 3.01728904e-01 4.61519837e-01 6.30726159e-01
-4.06395048e-02 1.17126122e-01 -5.99173427e-01 1.32552564e-01
4.08529729e-01 4.61782694e-01 -2.71896809e-01 -4.17478681e-01
-9.01331961e-01 9.71342325e-01 5.72153151e-01 3.91653568e-01
-1.47549540e-01 1.08795613e-01 7.61958420e-01 4.70079094e-01
7.50522792e-01 2.64009029e-01 -3.04642677e-01 -3.07003021e-01
-8.23592067e-01 -1.31707251e-01 6.89818680e-01 1.08679783e+00
8.68660212e-01 7.65687823e-02 -2.84662724e-01 1.20189810e+00
-1.55811042e-01 -1.53479967e-02 1.05663717e+00 -7.82870770e-01
3.27602506e-01 4.86226857e-01 -1.84993282e-01 -4.65934008e-01
-2.17256859e-01 -5.77552736e-01 -8.75871241e-01 1.25810489e-01
1.32376090e-01 -1.93721399e-01 -1.04281592e+00 1.58641183e+00
3.04642349e-01 6.23119652e-01 1.10143468e-01 7.02400863e-01
1.14316142e+00 7.80534744e-01 1.52596802e-01 -2.17918009e-01
1.13349140e+00 -1.44343901e+00 -6.55953288e-01 -3.61918569e-01
9.10962641e-01 -3.66943032e-01 1.22994637e+00 6.30775690e-02
-6.75282300e-01 -8.17897975e-01 -1.25282371e+00 -3.30457538e-02
-8.15511763e-01 -3.71748991e-02 3.77715737e-01 3.64678741e-01
-8.25540602e-01 7.78513372e-01 -8.13217282e-01 -5.65449238e-01
8.40259910e-01 4.07223264e-03 -2.98442304e-01 -4.72377300e-01
-1.39862847e+00 7.74087369e-01 6.99692667e-01 -2.35482469e-01
-1.07417417e+00 -6.70655251e-01 -8.84767294e-01 1.37007400e-01
4.63734984e-01 -4.48793918e-01 1.29870415e+00 -6.33383989e-01
-1.42186189e+00 7.58599162e-01 -6.07718639e-02 -4.50837344e-01
4.60553795e-01 -1.09364837e-01 -3.29056680e-01 3.68411750e-01
1.85173050e-01 7.99528897e-01 9.55439746e-01 -8.86713505e-01
-4.47963446e-01 -3.01218003e-01 2.86131427e-02 1.07429229e-01
-8.23838592e-01 -2.76418209e-01 -4.86587524e-01 -5.27933121e-01
-2.40338787e-01 -8.03573132e-01 -4.16460773e-03 -1.47548961e-02
2.96511985e-02 -4.33364540e-01 1.02169037e+00 -2.17516288e-01
1.25703406e+00 -2.41623592e+00 -1.64111257e-02 -7.34703064e-01
7.15039223e-02 5.29473126e-01 -2.45552972e-01 5.76048434e-01
-2.16510251e-01 -5.66983819e-02 -9.58437845e-02 -5.67355454e-01
3.26562859e-02 2.52255887e-01 -2.05040336e-01 4.99783665e-01
1.99895129e-01 1.15792894e+00 -1.13971531e+00 -5.10851085e-01
4.52830374e-01 3.71779412e-01 -1.58664405e-01 3.28015774e-01
-7.94145651e-03 -1.61422733e-02 -2.13978425e-01 7.56047130e-01
3.92206877e-01 -5.48827291e-01 -2.61911273e-01 -2.07650036e-01
8.49562585e-02 -2.04147220e-01 -9.92432058e-01 1.99568951e+00
-5.77674210e-01 4.49413031e-01 -3.84028018e-01 -1.37112296e+00
6.70113683e-01 4.25144076e-01 2.81481534e-01 -7.51166880e-01
3.06871295e-01 1.89943403e-01 -1.52223766e-01 -5.44201910e-01
5.63422628e-02 9.68558528e-03 6.66292310e-02 5.23680806e-01
7.25890279e-01 1.67370453e-01 3.69419426e-01 2.36683309e-01
1.22971833e+00 1.41979441e-01 4.87771541e-01 8.59242678e-03
1.31090775e-01 6.30077794e-02 6.62512302e-01 8.28269422e-01
-7.29420900e-01 6.72070742e-01 2.05836251e-01 -5.20104229e-01
-1.19426048e+00 -8.81756485e-01 -4.05631214e-01 1.37058878e+00
1.43034011e-01 -4.01222765e-01 -5.71349740e-01 -8.34324718e-01
-2.65536278e-01 8.82711828e-01 -8.37844312e-01 -6.52788877e-01
-1.62198931e-01 -9.82053280e-01 2.44863749e-01 6.30646586e-01
7.10088134e-01 -1.21286047e+00 -7.60163069e-01 2.52076447e-01
3.70870084e-02 -1.01181173e+00 -1.83629781e-01 4.84531045e-01
-9.50767279e-01 -1.07486677e+00 -1.01940155e+00 -8.24619949e-01
5.36894143e-01 4.50690180e-01 7.91419744e-01 -3.67502309e-02
-6.69677615e-01 3.06727529e-01 -8.44033182e-01 -4.59885478e-01
-4.66158241e-02 2.96634555e-01 -1.36936530e-02 -8.09627548e-02
6.87965393e-01 -6.71476007e-01 -8.63133550e-01 3.60639185e-01
-9.24085319e-01 5.07737510e-02 6.15020216e-01 1.33212137e+00
4.27234799e-01 2.06818711e-02 8.94555926e-01 -1.00596452e+00
4.49620038e-01 -8.21348310e-01 -1.72969267e-01 2.70726621e-01
-7.12959170e-01 -1.49344638e-01 8.37798417e-01 -6.28389239e-01
-9.22064364e-01 -5.65982573e-02 4.12515886e-02 -8.21529031e-01
-2.97857791e-01 2.24304780e-01 2.05486678e-02 2.23871514e-01
8.27570140e-01 4.74105299e-01 -1.24614697e-03 -4.56785589e-01
4.80216026e-01 9.55452800e-01 9.81172696e-02 -1.22512594e-01
5.47147393e-01 4.72373962e-01 -4.03227985e-01 -8.91079962e-01
-1.09443378e+00 -8.30295146e-01 -7.89893031e-01 -1.88316166e-01
6.59947336e-01 -1.10871136e+00 -1.76101848e-01 4.42756921e-01
-8.23361397e-01 -5.16331673e-01 -5.54335773e-01 4.76535439e-01
-6.52363956e-01 6.93075284e-02 -7.37423182e-01 -6.99583828e-01
-4.41954732e-01 -1.06219351e+00 8.97042453e-01 2.06930235e-01
-1.22995615e-01 -1.04245722e+00 1.18424363e-01 2.62650520e-01
4.74534869e-01 3.96139286e-02 6.99983597e-01 -8.38903427e-01
-2.74701118e-01 -3.61423314e-01 -2.23106906e-01 4.56672043e-01
8.01173523e-02 -4.76491839e-01 -1.39068007e+00 -5.17876804e-01
7.46867284e-02 -9.18611288e-01 1.21000886e+00 2.68116236e-01
1.24341202e+00 -2.35746726e-02 -4.16779727e-01 7.30998933e-01
1.60124075e+00 4.23037559e-02 6.55449986e-01 4.82369840e-01
4.04323429e-01 3.59169424e-01 8.01186502e-01 5.45125961e-01
4.75276932e-02 4.61866289e-01 2.97085881e-01 2.65279084e-01
-4.49080944e-01 -8.76564234e-02 2.56200522e-01 1.02278149e+00
1.32556915e-01 -1.02443032e-01 -8.15230727e-01 8.10164034e-01
-2.12223697e+00 -1.20406353e+00 4.89545316e-01 2.01866651e+00
8.41078997e-01 1.84974506e-01 -3.56330699e-03 1.65632144e-01
6.80428267e-01 4.14970189e-01 -8.63204002e-01 -1.34959832e-01
1.23928137e-01 2.97161102e-01 2.98311442e-01 1.13118201e-01
-1.16338944e+00 1.04065192e+00 4.93900633e+00 1.18371034e+00
-1.00945807e+00 7.08880424e-01 5.94046056e-01 -4.91255760e-01
4.01167691e-01 -9.07214060e-02 -1.13646543e+00 7.19440162e-01
1.07057798e+00 -3.60145479e-01 1.89523518e-01 1.20360434e+00
-1.05260514e-01 1.14704971e-03 -9.60809171e-01 1.08670259e+00
2.45058686e-01 -1.35082710e+00 -1.57652557e-01 -2.15735853e-01
8.34218085e-01 3.65193367e-01 6.25371784e-02 9.52030361e-01
9.44065377e-02 -7.04121709e-01 3.14959943e-01 2.97994435e-01
9.87139463e-01 -6.41214669e-01 8.17885697e-01 5.96141815e-01
-1.07181513e+00 -3.87659460e-01 -8.76105130e-01 5.99450916e-02
7.04482868e-02 5.31374812e-01 -7.44735956e-01 4.41295892e-01
8.44150543e-01 1.04941249e+00 -6.98749244e-01 1.05283773e+00
-2.96965122e-01 6.70786679e-01 6.72079250e-02 -1.14175826e-01
1.66476160e-01 2.10881397e-01 3.98537099e-01 1.01224899e+00
2.45013639e-01 1.99370220e-01 1.30579904e-01 6.23541236e-01
-2.31256753e-01 1.66475326e-01 -7.84895360e-01 -1.36914209e-01
5.40159523e-01 1.23310792e+00 -7.45464385e-01 -5.25455594e-01
-5.53679347e-01 1.20817614e+00 6.44360244e-01 3.43200415e-01
-7.83778727e-01 -7.88305104e-01 3.53161216e-01 -2.74935644e-02
4.57659900e-01 1.19537719e-01 1.06329061e-01 -1.41913664e+00
-7.51655400e-02 -6.34209037e-01 5.20236790e-01 -6.56896472e-01
-1.48559916e+00 7.51099765e-01 4.03060205e-02 -1.53846967e+00
-2.46685892e-01 -5.02925694e-01 -7.61213541e-01 5.10845304e-01
-1.62082076e+00 -1.06630147e+00 -4.36582267e-01 5.00746012e-01
1.19274437e+00 -4.93555456e-01 9.59281385e-01 3.00345898e-01
-7.75181293e-01 6.65908813e-01 3.54299039e-01 1.55759230e-01
9.20129538e-01 -9.54241812e-01 2.03093395e-01 6.14583969e-01
9.14145857e-02 4.50367659e-01 3.85579109e-01 -5.06246984e-01
-1.10188329e+00 -1.29021215e+00 4.92369860e-01 -3.27788472e-01
6.93546951e-01 -4.98300374e-01 -9.84772027e-01 5.77430308e-01
2.40867645e-01 4.77334172e-01 8.83975804e-01 2.88533047e-02
-2.87194014e-01 -2.43800953e-01 -9.51287866e-01 4.93639112e-01
1.12305570e+00 -5.40761948e-01 -7.34984219e-01 4.20941442e-01
8.38732004e-01 3.41608860e-02 -7.27005124e-01 2.72678941e-01
4.49240386e-01 -9.61814761e-01 8.14865112e-01 -6.41789138e-01
5.80905020e-01 3.26943286e-02 -1.82276145e-01 -1.51814044e+00
-4.16531473e-01 -2.15936691e-01 -5.67643464e-01 1.13893902e+00
2.62338042e-01 -6.14523411e-01 7.75156498e-01 3.66345823e-01
-1.60277799e-01 -9.97391701e-01 -8.81019175e-01 -1.11487269e+00
-5.81400618e-02 -3.85961026e-01 3.12976211e-01 1.05551147e+00
7.26286620e-02 5.07619262e-01 -4.68394041e-01 -1.47412494e-01
8.99146616e-01 5.61903715e-02 6.01178706e-01 -1.09211946e+00
-4.24318969e-01 -2.14048654e-01 -5.18014848e-01 -5.50276041e-01
2.35582322e-01 -1.12526453e+00 -1.62815228e-01 -1.50717843e+00
4.26638454e-01 -1.37087658e-01 -6.73335552e-01 7.15460360e-01
-1.85748085e-01 3.07582736e-01 2.27909267e-01 4.16078091e-01
-9.89573002e-01 9.55765188e-01 9.52219844e-01 -2.06475720e-01
-1.57069013e-01 -7.45002851e-02 -3.84400934e-01 4.56353396e-01
1.01679778e+00 -7.10624456e-01 -6.75982118e-01 -2.71847278e-01
-1.95643947e-01 -3.05549562e-01 2.48853579e-01 -1.18087578e+00
4.91148323e-01 1.11945465e-01 4.58392620e-01 -3.82389277e-01
5.98198652e-01 -5.28079033e-01 -3.12423795e-01 5.63861251e-01
-2.25762010e-01 -3.74477893e-01 9.13005546e-02 6.36674047e-01
-3.05561543e-01 -6.65889502e-01 1.00407588e+00 -4.65835154e-01
-1.29187822e+00 6.36527598e-01 1.24932460e-01 2.70245254e-01
1.37056386e+00 -2.57638395e-01 -5.45343161e-01 -1.37495145e-01
-9.05067325e-01 2.82657593e-01 3.92663211e-01 5.42065263e-01
7.94135153e-01 -1.50630307e+00 -4.43564117e-01 8.37173760e-02
6.40966177e-01 -1.93862617e-01 5.56178391e-01 8.60061049e-01
-1.72243372e-01 2.49485925e-01 -3.19492966e-01 -4.85474467e-01
-9.84686852e-01 7.44163811e-01 1.40040755e-01 2.84338128e-02
-6.76361561e-01 8.24524343e-01 -4.55811694e-02 -3.42283994e-01
3.53008419e-01 2.75538206e-01 -2.00791717e-01 4.24065679e-01
8.41688931e-01 6.64951980e-01 -1.05902061e-01 -3.22630882e-01
-1.00928880e-01 2.99395561e-01 -3.68587166e-01 1.58153057e-01
1.72291887e+00 -4.42703068e-02 2.74746358e-01 9.73311424e-01
1.69833684e+00 -9.17767644e-01 -1.27874255e+00 -4.40633237e-01
-2.60833383e-01 -4.55211490e-01 1.86553165e-01 -4.55206841e-01
-8.61426294e-01 1.19861948e+00 9.47140932e-01 -1.39323190e-01
8.86540890e-01 9.27914754e-02 8.21177900e-01 5.25252879e-01
3.84155631e-01 -1.45150220e+00 4.45392460e-01 3.98574203e-01
5.69924235e-01 -1.78114510e+00 -2.83260420e-02 3.59071046e-02
-6.68653905e-01 1.04398251e+00 7.96619356e-01 -1.85592785e-01
9.24359381e-01 -4.43689972e-02 -3.86271812e-03 -2.10027382e-01
-1.07206941e+00 -3.72571439e-01 5.87356761e-02 4.23024446e-01
2.16300160e-01 -2.64582276e-01 -2.00385824e-01 6.23390555e-01
2.67055452e-01 3.43567431e-01 2.95445025e-01 1.25762391e+00
-5.76570570e-01 -1.05254018e+00 2.01109663e-01 5.72313726e-01
-1.58218861e-01 -1.14536837e-01 -1.67300310e-02 7.09860802e-01
1.28873169e-01 7.92367399e-01 -1.34519100e-01 -2.56090313e-01
2.93010235e-01 5.20894945e-01 3.31291884e-01 -1.01137984e+00
-1.72402039e-01 -2.10791528e-01 -3.45058680e-01 -5.91512620e-01
-2.49771461e-01 -3.76251012e-01 -9.06334877e-01 -2.37581581e-02
-3.66126180e-01 3.30953486e-02 4.10652995e-01 6.65128231e-01
5.48141897e-01 5.01606882e-01 7.47041821e-01 -8.18803430e-01
-9.24786925e-01 -1.24716377e+00 -7.46036172e-01 5.87281764e-01
8.69465172e-02 -8.35985243e-01 -6.73207343e-01 -2.20884103e-02] | [10.009986877441406, 2.9817123413085938] |
7bd01f26-a994-4d1b-9baf-29ab1951429f | relaxed-forced-choice-improves-performance-of | 2305.00220 | null | https://arxiv.org/abs/2305.00220v1 | https://arxiv.org/pdf/2305.00220v1.pdf | Relaxed forced choice improves performance of visual quality assessment methods | In image quality assessment, a collective visual quality score for an image or video is obtained from the individual ratings of many subjects. One commonly used format for these experiments is the two-alternative forced choice method. Two stimuli with the same content but differing visual quality are presented sequentially or side-by-side. Subjects are asked to select the one of better quality, and when uncertain, they are required to guess. The relaxed alternative forced choice format aims to reduce the cognitive load and the noise in the responses due to the guessing by providing a third response option, namely, ``not sure''. This work presents a large and comprehensive crowdsourcing experiment to compare these two response formats: the one with the ``not sure'' option and the one without it. To provide unambiguous ground truth for quality evaluation, subjects were shown pairs of images with differing numbers of dots and asked each time to choose the one with more dots. Our crowdsourcing study involved 254 participants and was conducted using a within-subject design. Each participant was asked to respond to 40 pair comparisons with and without the ``not sure'' response option and completed a questionnaire to evaluate their cognitive load for each testing condition. The experimental results show that the inclusion of the ``not sure'' response option in the forced choice method reduced mental load and led to models with better data fit and correspondence to ground truth. We also tested for the equivalence of the models and found that they were different. The dataset is available at http://database.mmsp-kn.de/cogvqa-database.html. | ['Dietmar Saupe', 'Raouf Hamzaoui', 'Ulf-Dietrich Reips', 'Harald Reiterer', 'Johannes Zagermann', 'Mohsen Jenadeleh'] | 2023-04-29 | null | null | null | null | ['image-quality-assessment'] | ['computer-vision'] | [ 9.31717604e-02 -2.67642200e-01 1.92452490e-01 -4.67902362e-01
-6.47253335e-01 -7.76821733e-01 1.94255203e-01 3.57007116e-01
-7.69010484e-01 7.43083775e-01 6.75512031e-02 -2.70211130e-01
-1.31502792e-01 -5.13706028e-01 -4.71043944e-01 -6.19127035e-01
3.63419652e-01 2.15477064e-01 3.51433039e-01 -2.69537624e-02
5.63749254e-01 1.82554483e-01 -1.79601943e+00 3.00176680e-01
9.14798975e-01 1.03900003e+00 5.94797552e-01 5.52124977e-01
-6.52042851e-02 6.44552052e-01 -7.97094345e-01 -6.60653174e-01
5.33205271e-01 -7.45060265e-01 -6.42646015e-01 3.47451091e-01
4.94140238e-01 -3.96953911e-01 1.36888444e-01 9.74299312e-01
7.85923302e-01 4.44557160e-01 3.33782762e-01 -1.31104124e+00
-6.92319274e-01 3.32933739e-02 -5.37866652e-01 1.19917817e-01
1.04224753e+00 5.90415895e-01 7.20091581e-01 -8.58915627e-01
6.13430381e-01 1.05550408e+00 1.53886184e-01 5.34932911e-01
-1.50051892e+00 -6.57801688e-01 -6.97364062e-02 4.81516302e-01
-1.53092027e+00 -5.58072686e-01 5.57772100e-01 -7.47163832e-01
3.27464551e-01 3.56227487e-01 6.22861803e-01 7.86456883e-01
1.04797389e-02 1.78552419e-01 1.88149190e+00 -4.70610619e-01
5.49974918e-01 6.96251690e-01 -1.09202527e-01 3.80478531e-01
3.41257274e-01 3.28927666e-01 -5.61705291e-01 -2.01928705e-01
7.06661105e-01 -2.71575928e-01 -4.66895461e-01 -1.53007925e-01
-1.18239915e+00 6.80130064e-01 3.92832249e-01 3.09831411e-01
-4.52440053e-01 -3.09302449e-01 2.22618226e-02 4.70862746e-01
6.76200315e-02 5.48507929e-01 -2.72503663e-02 -5.02297990e-02
-7.23740637e-01 4.11129206e-01 6.44100249e-01 4.36033189e-01
7.25835204e-01 -3.09624910e-01 -6.99887335e-01 6.91912949e-01
2.73800522e-01 5.55318773e-01 4.25602168e-01 -1.21720231e+00
3.70747954e-01 4.80457574e-01 8.97161782e-01 -1.32619858e+00
-1.80143386e-01 4.14461344e-02 -4.42710102e-01 9.86068487e-01
9.54978049e-01 -1.51558116e-01 -6.41612291e-01 1.65568364e+00
2.43727699e-01 -4.43449646e-01 -2.89206296e-01 1.58523846e+00
6.31366253e-01 3.08843613e-01 1.97866380e-01 -4.89743799e-01
1.69425607e+00 -4.07796502e-01 -8.72981608e-01 -1.11024454e-01
2.90829420e-01 -9.84191120e-01 1.58578873e+00 4.48296785e-01
-1.14621305e+00 -8.70632887e-01 -9.73431706e-01 1.80531055e-01
-7.21903145e-02 5.38800284e-02 3.21756862e-02 9.20567691e-01
-1.00000978e+00 6.65662289e-01 -1.30668402e-01 -1.35183558e-01
1.02269143e-01 7.42472112e-02 -5.20828128e-01 -2.70693362e-01
-1.25944304e+00 9.77276921e-01 -1.42384782e-01 -5.34867495e-02
-5.88589609e-01 -6.22985885e-02 -6.64883375e-01 -8.63486081e-02
4.03596759e-01 -5.41708171e-01 1.20689094e+00 -1.50457931e+00
-1.53087533e+00 1.05136442e+00 -4.26708758e-01 -1.23827301e-01
6.95205331e-01 1.59247413e-01 -3.69918972e-01 3.04364026e-01
3.33911568e-01 6.77541256e-01 8.98621738e-01 -1.30878329e+00
-2.69223690e-01 -4.91250992e-01 1.79730430e-01 4.84977990e-01
3.59251916e-01 3.64456922e-01 -8.79672840e-02 -5.92374265e-01
9.38058496e-02 -9.92711723e-01 2.11969973e-03 2.11818382e-01
3.01905349e-02 -1.03670113e-01 -1.10681318e-02 -6.38136804e-01
1.11296666e+00 -2.15359187e+00 -2.36274198e-01 1.32064089e-01
2.44614750e-01 2.69917157e-02 -1.45366564e-01 5.30217230e-01
-1.76243573e-01 2.03833103e-01 8.14756602e-02 -2.31213406e-01
1.06506348e-01 -1.54211730e-01 3.67008567e-01 5.57961643e-01
2.89628785e-02 3.93812150e-01 -6.76176190e-01 -4.73352432e-01
1.27826393e-01 1.25054911e-01 -1.65318400e-01 4.53021616e-01
2.87138373e-02 6.10110819e-01 1.40912727e-01 3.60635221e-01
7.62152493e-01 -1.23060435e-01 -2.79055163e-02 -1.47758976e-01
-1.99321330e-01 1.79523483e-01 -1.61706126e+00 1.08774841e+00
3.39425467e-02 6.11021638e-01 -8.14930424e-02 -2.81960726e-01
9.25325632e-01 5.66968262e-01 -1.09256776e-02 -1.28318357e+00
1.52023599e-01 2.27410942e-01 2.16003463e-01 -7.21389234e-01
4.46018904e-01 -3.11883867e-01 1.09918728e-01 4.71641839e-01
-5.20403862e-01 -1.46158352e-01 3.64451855e-01 7.69686699e-02
7.37699270e-01 -1.15059532e-01 4.27964807e-01 -1.89869285e-01
4.55143869e-01 -1.46283880e-01 5.51637530e-01 8.29201579e-01
-7.00064719e-01 6.70759916e-01 4.97861415e-01 -3.47974390e-01
-7.85266876e-01 -1.05913091e+00 2.18010858e-01 9.35174167e-01
3.94984037e-01 8.99973363e-02 -7.11582124e-01 -2.65105098e-01
-1.91968083e-01 8.32280576e-01 -6.18267000e-01 2.48859927e-01
-3.08859423e-02 -3.09984330e-02 -5.23353415e-03 2.13391230e-01
5.80480754e-01 -1.08621323e+00 -8.60979736e-01 -1.89221203e-01
-6.10444307e-01 -7.51215756e-01 -8.30438316e-01 -4.24784213e-01
-4.43828225e-01 -1.08836591e+00 -8.73460948e-01 -3.59536409e-01
6.40744865e-01 5.38028002e-01 1.06846929e+00 2.52353251e-01
1.50921131e-02 2.89821178e-01 -5.47021508e-01 -2.71362960e-01
-2.55852580e-01 -7.41898894e-01 1.18706279e-01 2.09158704e-01
4.06063050e-01 -2.25602966e-02 -9.98553932e-01 9.72243547e-01
-9.07833815e-01 -1.43259421e-01 3.88875932e-01 5.34366310e-01
5.95305741e-01 -1.89735144e-02 3.20278257e-01 -4.29510117e-01
9.53439653e-01 -2.18877241e-01 -5.78935146e-01 9.99489278e-02
-6.76574469e-01 -1.46335632e-01 2.35024855e-01 -5.79221725e-01
-8.44187737e-01 -1.37469560e-01 1.65251613e-01 -1.62660047e-01
-5.61424017e-01 2.92739600e-01 -2.10468024e-01 -1.83280990e-01
9.26230669e-01 -1.76391989e-01 6.40705526e-02 -1.64319545e-01
-4.33617383e-02 5.71124017e-01 3.08183134e-01 -3.08776200e-01
6.31680548e-01 1.68424323e-01 -2.81397849e-01 -4.04362231e-01
-3.40948850e-01 -3.02105278e-01 -3.08503181e-01 -6.54056668e-01
1.11448669e+00 -7.23272443e-01 -9.72634256e-01 5.48250794e-01
-9.35855031e-01 -2.06649572e-01 -2.32521966e-01 7.39302218e-01
-4.00562555e-01 4.60675895e-01 -1.97228506e-01 -1.08413959e+00
4.09581978e-03 -1.32537127e+00 4.71004218e-01 5.37713230e-01
-4.88342762e-01 -4.49830085e-01 -5.67150451e-02 5.95448673e-01
3.70588154e-01 1.48546159e-01 4.84611899e-01 -4.99297827e-01
-3.35431010e-01 -2.78509051e-01 -1.92087755e-01 2.12210745e-01
1.26375645e-01 -2.06642345e-01 -7.75685906e-01 -3.66244048e-01
2.18651220e-01 -2.73827940e-01 1.43976837e-01 3.26191545e-01
5.42003334e-01 -3.21183324e-01 2.50064522e-01 -1.17745593e-01
1.47475553e+00 4.77535218e-01 1.02579558e+00 2.64366627e-01
8.85150507e-02 8.92708957e-01 7.02596366e-01 2.81392962e-01
4.09469664e-01 9.26574528e-01 2.79076576e-01 9.62755363e-03
9.62662250e-02 -6.14921823e-02 4.29504871e-01 2.91640610e-01
-1.95815578e-01 -5.16962409e-01 -6.54235363e-01 3.83629233e-01
-1.33797371e+00 -1.13240588e+00 -3.04205000e-01 2.79860616e+00
6.01871014e-01 -2.46730633e-02 4.01703924e-01 3.41449082e-01
1.01592624e+00 -1.25206843e-01 -2.27231637e-01 -4.61422443e-01
-4.28783149e-02 -9.29911360e-02 1.92286134e-01 5.94747245e-01
-5.06503880e-01 3.08235019e-01 5.77145576e+00 7.04982936e-01
-8.31903756e-01 -6.33021221e-02 7.33575344e-01 -1.65275425e-01
-1.31894782e-01 1.67088598e-01 -3.74840736e-01 7.97998965e-01
9.17364240e-01 -1.41758114e-01 5.35076797e-01 1.75132111e-01
8.49345505e-01 -1.20343530e+00 -8.24786484e-01 1.09786713e+00
-4.20775637e-02 -7.62346804e-01 -1.83006883e-01 -4.48257625e-02
4.01840031e-01 -5.73232710e-01 -1.06715299e-01 -2.24028692e-01
3.15310946e-03 -1.03489053e+00 1.05935955e+00 8.89052570e-01
8.86702597e-01 -3.75431389e-01 7.83817291e-01 3.90200406e-01
-8.67096424e-01 1.81299821e-02 -1.30560607e-01 -6.56451106e-01
1.79500565e-01 3.69497597e-01 -4.75808024e-01 2.99928039e-01
8.88508379e-01 -3.53428751e-01 -7.20524073e-01 1.20874023e+00
-2.45769754e-01 3.07491511e-01 -2.35584453e-02 -2.44516253e-01
-2.65593767e-01 -4.09420162e-01 3.88499469e-01 6.37085319e-01
4.20008183e-01 3.96629035e-01 -2.51132026e-02 8.00295949e-01
2.73789287e-01 3.64488482e-01 -3.52543443e-01 1.32443652e-01
7.30054855e-01 8.98531795e-01 -8.64210129e-01 -1.93366006e-01
-3.73122662e-01 1.19332063e+00 1.24007873e-01 4.37679499e-01
-6.36617541e-01 -5.41088045e-01 1.58945128e-01 5.76513469e-01
6.22280128e-02 -6.32174537e-02 -3.02090436e-01 -6.01119578e-01
3.17605019e-01 -1.05192685e+00 2.82545507e-01 -1.33526194e+00
-1.30526912e+00 6.17275536e-01 1.88994780e-01 -1.27106035e+00
-1.14259981e-02 -4.98972267e-01 -3.68463755e-01 1.54113758e+00
-9.06805873e-01 -3.55125159e-01 -6.52055383e-01 6.49837255e-01
3.23195934e-01 2.34824032e-01 6.42841637e-01 1.78094938e-01
-1.82718456e-01 5.22559226e-01 -4.14683372e-01 -8.50552395e-02
1.03713417e+00 -1.16034794e+00 -2.25596249e-01 5.47733307e-01
-2.88124949e-01 5.76693594e-01 9.92456794e-01 -6.26449466e-01
-8.40621173e-01 -2.43835807e-01 1.13360083e+00 -4.01087046e-01
1.15433231e-01 -1.69721276e-01 -1.00765061e+00 -7.61659816e-02
3.06105167e-01 -2.80316114e-01 9.55956459e-01 -4.31706905e-01
-5.89031279e-02 -9.54006240e-03 -1.54350209e+00 6.43803596e-01
5.73907077e-01 -5.18706739e-01 -5.25868356e-01 -3.52531597e-02
4.56033647e-01 -1.90473676e-01 -7.23524570e-01 -2.04797927e-02
7.10949421e-01 -1.45487213e+00 4.45706517e-01 -7.05205128e-02
3.89630288e-01 -7.21136034e-01 -2.70908713e-01 -1.28348839e+00
-6.41209185e-01 -4.58508313e-01 5.65195262e-01 1.07696509e+00
3.44645023e-01 -6.53455317e-01 4.50984925e-01 9.61230576e-01
3.48787218e-01 -4.17635411e-01 -9.47652578e-01 -7.21990049e-01
-1.54802695e-01 -1.66722298e-01 4.93476480e-01 5.90956390e-01
2.92602014e-02 2.08372608e-01 -3.37700397e-01 2.75426432e-02
2.70908564e-01 -5.46167232e-02 6.81621432e-01 -1.00953317e+00
-3.40408146e-01 -3.29477906e-01 -2.90927559e-01 -6.43008471e-01
-5.56633592e-01 -1.80325896e-01 2.13287830e-01 -1.49980462e+00
1.77055493e-01 -1.03596993e-01 8.44298899e-02 1.25081018e-01
-5.55539429e-01 3.88920814e-01 4.62484598e-01 3.04259509e-01
-3.63663107e-01 1.65368065e-01 1.32549751e+00 2.42406055e-01
-2.28246182e-01 1.08197927e-01 -7.67051518e-01 3.75684619e-01
8.27108264e-01 -4.70437706e-01 -3.81811202e-01 -3.59393805e-01
3.88503760e-01 5.46018183e-01 6.23539329e-01 -1.10092556e+00
2.15329468e-01 -3.27848852e-01 6.45742536e-01 -1.40193194e-01
3.39074999e-01 -8.33603144e-01 5.18844962e-01 4.09450114e-01
-2.58366883e-01 5.73892236e-01 1.45605311e-01 3.64224911e-01
5.00023142e-02 -6.40698552e-01 8.56456578e-01 -3.52064669e-01
-5.62497973e-01 -1.86612695e-01 -5.49963593e-01 -2.11526483e-01
1.03653026e+00 -5.76141477e-01 -2.16837510e-01 -7.82043993e-01
-9.08115149e-01 2.79548783e-02 8.30904722e-01 1.04897857e-01
6.47735953e-01 -1.44127691e+00 -7.82597244e-01 -7.65467286e-02
2.01778874e-01 -8.06110024e-01 5.06629646e-01 9.38796282e-01
-4.15759653e-01 1.56422257e-02 -3.27343315e-01 -2.44034186e-01
-1.38599432e+00 8.08929145e-01 3.64229769e-01 -4.94219735e-02
1.18940711e-01 6.53094351e-01 -1.08823501e-01 4.45658341e-02
1.11203663e-01 7.30734468e-02 -3.70333970e-01 1.10600308e-01
8.05946589e-01 6.85273349e-01 2.67077293e-02 -9.08003688e-01
-3.36699307e-01 4.69127804e-01 3.78407687e-01 -6.44207597e-01
4.65235323e-01 -4.86782700e-01 6.85080364e-02 6.72292590e-01
7.16476738e-01 3.02173227e-01 -1.17552936e+00 -2.18327530e-02
-3.66100818e-01 -1.14997518e+00 -2.26546347e-01 -1.20727444e+00
-6.21541023e-01 5.54210901e-01 1.12785137e+00 3.13024580e-01
1.27578938e+00 -3.40675205e-01 4.66233231e-02 6.85229227e-02
4.12608981e-01 -1.09708214e+00 2.11518228e-01 -1.25507221e-01
1.10774100e+00 -1.47814584e+00 -3.89617682e-02 -2.55298674e-01
-1.04955101e+00 7.72069037e-01 6.42746329e-01 6.44737035e-02
1.15779229e-01 -2.73090154e-01 2.94656187e-01 -2.04163179e-01
-4.62634057e-01 -2.46521816e-01 5.10990441e-01 8.65387261e-01
5.58253825e-01 1.22930370e-01 -8.53275120e-01 5.35135388e-01
-1.18197560e-01 1.82230502e-01 5.54440796e-01 7.47788012e-01
-5.25047541e-01 -9.09722030e-01 -9.72191095e-01 4.39862579e-01
-1.58831581e-01 1.90693080e-01 -4.66614991e-01 4.77355570e-01
4.11480427e-01 1.58429742e+00 1.10429384e-01 -3.48601133e-01
6.50969267e-01 -5.20149060e-02 4.77019608e-01 -4.27850306e-01
-6.32722437e-01 -5.42940125e-02 -1.59229916e-02 -5.70313215e-01
-4.56263602e-01 -8.15837979e-01 -8.43517900e-01 -6.05090022e-01
-3.68239194e-01 3.43573272e-01 4.73325759e-01 8.13937962e-01
2.00624108e-01 1.91609919e-01 6.88014269e-01 -9.37118769e-01
-4.56694573e-01 -1.00881267e+00 -6.00382626e-01 8.19282770e-01
6.13222346e-02 -6.77820444e-01 -4.43792105e-01 3.59140150e-02] | [11.802483558654785, -1.8525745868682861] |
1637addd-cf03-4510-b765-5722b1e60eba | simple-thermal-noise-estimation-of-switched-1 | 1908.08109 | null | http://arxiv.org/abs/1908.08109v1 | http://arxiv.org/pdf/1908.08109v1.pdf | Simple Thermal Noise Estimation of Switched Capacitor Circuits Based on OTAs -- Part II: SC Filters | In Part I of this paper, we have shown how to calculate the thermal noise
voltage variances in switched-capacitor (SC) circuits using operational
transconductance amplifiers (OTAs) with capacitive feedback by using the
extended Bode theorem. The method allows a precise estimation of the thermal
noise voltage variances by simple circuit inspection without the calculation of
any transfer functions nor integrals. While Part I focuses on SC amplifiers and
track&hold circuits, Part II shows how to use the extended Bode theorem for SC
filters. It validates the method on the basic integrator and then on a
first-order low-pass filter by comparing the analytical results to transient
noise simulations showing an excellent match. | [] | 2019-08-21 | null | null | null | null | ['noise-estimation'] | ['medical'] | [ 2.91196436e-01 -3.12796831e-01 3.09888393e-01 7.86868706e-02
-2.87677199e-01 -7.89898038e-01 1.45823866e-01 1.48037314e-01
-5.18953383e-01 7.63074994e-01 -5.95752537e-01 -6.50173783e-01
-1.77043244e-01 -2.41440207e-01 -2.06587285e-01 -5.16121328e-01
1.00237586e-01 -1.83869481e-01 5.44727802e-01 -3.26810777e-01
5.95824346e-02 7.08920538e-01 -1.07022452e+00 2.40383074e-02
7.90532827e-01 1.39374971e+00 -5.20147324e-01 8.86856914e-01
4.13906544e-01 6.07690990e-01 -9.73271012e-01 -1.20597698e-01
-1.90268427e-01 -7.21290469e-01 -4.49448526e-01 -6.67510390e-01
-7.24595562e-02 -1.49184376e-01 -1.69940025e-01 1.20069158e+00
5.25743544e-01 -7.76873082e-02 1.08216834e+00 -1.25525546e+00
-1.33891284e-01 8.86478424e-01 4.55198847e-02 3.15375805e-01
4.23370302e-01 2.16166377e-02 4.69090462e-01 -5.29105246e-01
1.68660246e-02 9.98475671e-01 1.19328666e+00 7.62823895e-02
-1.91552031e+00 -8.69943917e-01 -2.74928123e-01 -3.20713311e-01
-1.71111810e+00 -3.62179160e-01 4.13111418e-01 -3.77652496e-01
1.44846487e+00 4.78612483e-01 9.18655813e-01 1.81734413e-01
7.29575634e-01 2.41553187e-01 1.03410876e+00 -6.05419099e-01
5.57444692e-01 5.31438470e-01 7.15325534e-01 1.44344777e-01
6.57657027e-01 -1.20746002e-01 2.65573561e-01 -6.67351425e-01
1.10612571e+00 -2.95881361e-01 -3.16975564e-01 1.93265438e-01
-5.16184747e-01 2.36421064e-01 2.97224909e-01 7.50470996e-01
-1.20436542e-01 8.82233143e-01 5.11110127e-01 4.34240639e-01
-2.93354988e-01 4.98301506e-01 1.77307404e-03 -8.65849629e-02
-8.49706352e-01 -4.08688784e-02 1.20991886e+00 1.04149950e+00
-4.25930135e-02 6.97643340e-01 1.90355331e-01 2.61683136e-01
4.71204996e-01 7.83701360e-01 4.27526474e-01 -6.57720447e-01
-2.05786616e-01 2.91597396e-01 4.51153040e-01 -3.42409313e-01
-6.73469901e-01 -3.64388674e-01 -7.11266696e-01 3.11956704e-01
5.52837908e-01 -4.26720619e-01 -8.59148860e-01 1.10546350e+00
-6.16759896e-01 -3.13932776e-01 -7.27371275e-02 3.57591063e-01
3.10536832e-01 5.24512589e-01 -1.95452064e-01 -6.75706267e-01
1.30958247e+00 -1.60462245e-01 -1.40966928e+00 8.07100683e-02
-1.80485681e-01 -7.20025241e-01 5.78510404e-01 6.13454759e-01
-1.11287773e+00 -5.53848505e-01 -1.44478452e+00 9.09887478e-02
2.04848088e-02 3.64142030e-01 -2.04350334e-02 1.47360039e+00
-1.15758169e+00 6.79958582e-01 -8.71908724e-01 -8.06539133e-02
-1.06187418e-01 5.87354004e-01 4.58537936e-01 9.38739181e-01
-1.25051284e+00 8.91795754e-01 -1.83082633e-02 3.63427103e-01
-2.03461647e-01 -6.19889855e-01 -2.37772867e-01 3.41447800e-01
-8.37366953e-02 -4.48321849e-01 1.35845697e+00 -1.12330055e+00
-1.94669724e+00 8.30709264e-02 -1.76680133e-01 -5.97458303e-01
3.23461562e-01 -1.36537060e-01 -7.86203086e-01 2.27071688e-01
-7.91576624e-01 -4.41886067e-01 7.71427751e-01 -7.33651221e-01
-3.37988138e-02 3.52003053e-02 -4.45215702e-01 -7.93635905e-01
8.16046819e-02 -2.09969599e-02 5.30721843e-01 -3.43721122e-01
4.80837345e-01 -5.67771554e-01 -3.99184853e-01 -1.02942348e-01
-2.70994246e-01 3.93409014e-01 2.26610318e-01 -1.34423658e-01
1.72042561e+00 -2.23711205e+00 -5.23270071e-01 9.16543186e-01
-3.01933885e-01 5.35456896e-01 7.37027287e-01 8.86299908e-01
-1.93294778e-01 1.23225063e-01 -9.03042406e-02 5.58168888e-01
-8.10432136e-02 -5.84808826e-01 -3.98777813e-01 5.86314321e-01
4.78424251e-01 4.80663687e-01 -4.97788131e-01 5.98744601e-02
1.00422762e-01 5.97215712e-01 -2.29847819e-01 -3.70479137e-01
5.62780797e-01 -1.31463021e-01 -2.34449744e-01 3.10575396e-01
7.40091324e-01 -1.26176551e-01 5.37554443e-01 -5.32638609e-01
-4.50184107e-01 5.06902874e-01 -1.77186072e+00 7.84835696e-01
-2.10251451e-01 9.56906736e-01 3.81172329e-01 -5.22212505e-01
1.14022517e+00 6.93423867e-01 -1.59457296e-01 -5.29307187e-01
7.83231020e-01 8.34221780e-01 1.73936352e-01 -1.86615273e-01
2.33144477e-01 -8.13124299e-01 -6.28157109e-02 1.41809732e-01
1.14704229e-01 -7.08562076e-01 -1.88097283e-01 2.87482262e-01
6.66443408e-01 -1.41468018e-01 6.45692587e-01 -1.03647602e+00
7.64647663e-01 -6.50886148e-02 2.42764160e-01 3.76686275e-01
-2.81809628e-01 6.82884306e-02 7.67569363e-01 2.52427876e-01
-8.10953140e-01 -1.00386059e+00 -5.33206344e-01 5.41044585e-02
7.97139108e-02 -2.77629644e-01 -7.03650892e-01 8.85691226e-01
2.60764956e-01 7.00960577e-01 -2.62724221e-01 -1.48281649e-01
-2.59200990e-01 -3.30235869e-01 1.21806383e+00 8.30823183e-01
1.29253000e-01 -1.05738789e-01 -9.36120212e-01 4.68054354e-01
3.80045623e-01 -8.96092176e-01 -1.18294008e-01 8.84947479e-01
-1.11525285e+00 -6.29632413e-01 -4.61171091e-01 -7.10370243e-01
4.20571864e-01 -5.16192794e-01 4.83737290e-01 -4.70903255e-02
-5.66926241e-01 5.04551947e-01 2.00707078e-01 -6.56416833e-01
-4.98074085e-01 -6.12834990e-01 3.27576727e-01 -3.11202824e-01
4.52736884e-01 -6.70190156e-01 -5.85442603e-01 4.72510636e-01
-5.57758689e-01 -9.55069482e-01 1.35296762e-01 2.85241127e-01
2.43075028e-01 -1.48243364e-02 8.25299382e-01 -4.76208240e-01
7.30947852e-01 3.07744801e-01 -1.32271302e+00 -6.75899684e-02
-5.58813214e-01 6.93012029e-02 1.09065580e+00 -4.46379423e-01
-8.44809175e-01 3.14000726e-01 -3.54987890e-01 -2.06635147e-01
5.47055781e-01 8.81573185e-02 -4.99411337e-02 -2.91688323e-01
1.02522731e+00 -1.68876976e-01 3.25830638e-01 -3.64098310e-01
-1.43867567e-01 9.55970645e-01 7.16423154e-01 -1.61913306e-01
4.95813996e-01 3.24864537e-01 2.77574778e-01 -1.12345421e+00
4.71590579e-01 -1.94970906e-01 -4.74269927e-01 -1.35979533e-01
2.69329250e-01 -1.03202641e+00 -1.59237504e+00 6.38524592e-01
-9.03312683e-01 -2.06489474e-01 -2.98316181e-01 8.49689543e-01
-4.37963039e-01 1.07772924e-01 -1.19042861e+00 -1.87970197e+00
-5.62179446e-01 -1.13874030e+00 2.76550621e-01 3.75393242e-01
-4.71486121e-01 -1.02332997e+00 -2.64870137e-01 -6.40015662e-01
5.42515934e-01 2.28282049e-01 6.47824049e-01 -2.03003302e-01
-4.43856984e-01 -5.89177310e-01 2.84269512e-01 5.82774401e-01
-3.34617108e-01 5.66197217e-01 -1.35729635e+00 -3.62652391e-01
4.40523326e-01 3.23160738e-01 5.89230716e-01 6.73319101e-01
2.04438537e-01 1.41869381e-01 -6.78540409e-01 4.02820036e-02
2.24434614e+00 6.49575114e-01 1.08538997e+00 -3.30763817e-01
-1.46042362e-01 -1.95514008e-01 1.46774098e-01 2.72652715e-01
-6.52339756e-01 9.72833633e-02 -4.49129343e-02 1.79459557e-01
6.66966558e-01 -2.15871613e-02 4.06992137e-01 6.17853940e-01
-8.88302326e-02 -1.79591209e-01 -3.48539770e-01 2.33128533e-01
-1.11172974e+00 -6.90856159e-01 -1.14129686e+00 2.48286724e+00
5.50703406e-01 3.45403880e-01 2.45906249e-01 7.26771474e-01
5.99808097e-01 -7.46816099e-01 -2.93263435e-01 -1.10162401e+00
1.16176814e-01 7.09808767e-01 1.03949487e+00 7.57692039e-01
-5.15817702e-01 -8.21027011e-02 8.11412621e+00 5.70289731e-01
-1.32949567e+00 -1.68440059e-01 1.98322702e-02 1.43832937e-01
-1.55950025e-01 1.23221830e-01 -8.00760090e-01 2.82674134e-01
1.51701462e+00 -5.30813634e-01 3.72702293e-02 5.38569808e-01
2.08139122e-01 -7.72889733e-01 -1.17570817e+00 6.92703843e-01
-5.77237248e-01 -7.43165314e-01 -4.70440686e-01 -3.64827394e-01
3.35715681e-01 -7.67035365e-01 -1.65120006e-01 7.83474222e-02
-4.75915879e-01 -8.58813286e-01 7.34976292e-01 8.65227878e-01
8.75805259e-01 -5.97013116e-01 7.92023361e-01 2.49561146e-01
-1.47166288e+00 -3.64568412e-01 -4.70281780e-01 -5.72889209e-01
2.17926472e-01 7.38833547e-01 -3.61017078e-01 2.78414726e-01
2.84512609e-01 -2.64842808e-01 -1.05558969e-01 1.35389972e+00
3.03614661e-02 7.05549240e-01 -7.78314531e-01 -7.06187010e-01
-7.82726109e-02 -2.95803577e-01 2.47874051e-01 1.15875995e+00
1.83238432e-01 6.58095837e-01 -7.38717258e-01 1.29091108e+00
5.24527311e-01 -1.69548333e-01 2.50381023e-01 -1.76318929e-01
6.05675101e-01 9.14084077e-01 -6.15186214e-01 -4.94102150e-01
-2.75045216e-01 5.62574923e-01 -8.39065790e-01 5.20833313e-01
-6.56135976e-01 -1.36133265e+00 4.63659197e-01 5.27163982e-01
3.05682957e-01 -2.36895472e-01 -6.53549612e-01 -5.58825374e-01
-1.74430370e-01 -4.05695200e-01 -1.06809080e-01 -6.60262644e-01
-8.31992507e-01 5.58973908e-01 -5.44134080e-02 -1.48629034e+00
-2.62822509e-01 -7.99778700e-01 -8.46451938e-01 1.45180964e+00
-7.76743531e-01 -1.15013838e-01 1.43577591e-01 4.01388139e-01
-5.88973761e-01 4.20908451e-01 7.34146893e-01 4.24613565e-01
-9.96390730e-02 7.31082737e-01 6.31180286e-01 2.09561773e-02
2.94668317e-01 -1.06383455e+00 4.14165080e-01 7.13544309e-01
-9.68012512e-01 1.15647399e+00 1.22811353e+00 -3.34439367e-01
-1.45794833e+00 -2.35481516e-01 7.78546989e-01 1.95068657e-01
7.40974486e-01 -4.36458856e-01 -1.22192657e+00 5.89353144e-01
2.03913674e-01 -6.10008650e-02 3.85138839e-01 -5.91384888e-01
1.04929715e-01 -4.11900610e-01 -1.37906277e+00 2.57825762e-01
2.29357511e-01 -7.02397525e-01 -5.57674110e-01 -3.18966091e-01
4.13827360e-01 -4.63158816e-01 -1.15740609e+00 7.85525814e-02
1.05754054e+00 -7.57523715e-01 5.36088705e-01 1.79062635e-01
-4.03631687e-01 -7.35806763e-01 -8.99023414e-02 -9.94849622e-01
-3.40388417e-01 -1.01065457e+00 5.89930952e-01 9.52918351e-01
7.27760553e-01 -1.28503525e+00 1.42935533e-02 8.46673250e-01
1.22737914e-01 -3.96619439e-01 -9.06586885e-01 -1.07734418e+00
2.25576118e-01 -8.76153037e-02 1.50863007e-01 2.29787529e-01
9.68553424e-01 3.29725295e-01 2.05988795e-01 1.41789630e-01
1.95684075e-01 -4.62072939e-01 3.00069340e-02 -1.27656603e+00
-3.26013327e-01 -4.75504488e-01 -7.60118544e-01 -9.73720610e-01
-7.72545099e-01 -1.26350239e-01 1.39751539e-01 -1.19377828e+00
-3.55946988e-01 3.82777490e-02 -3.64804536e-01 -1.61971956e-01
-9.11568105e-02 1.53676644e-01 -1.68395132e-01 -1.57657146e-01
2.85748839e-01 -7.93622807e-02 4.76862371e-01 2.40118548e-01
-4.77943599e-01 4.09399837e-01 -5.01869023e-02 5.91597974e-01
3.69363755e-01 -2.56913960e-01 -3.23916256e-01 4.26472336e-01
4.43352729e-01 2.02841774e-01 5.40071726e-01 -1.54993987e+00
5.16151786e-01 3.77977371e-01 4.14728612e-01 -6.17234051e-01
2.96024859e-01 -1.15856755e+00 9.00497079e-01 1.11746192e+00
1.26604633e-02 4.63910997e-02 6.80254102e-01 4.92982954e-01
-2.14270413e-01 -6.04209781e-01 1.17943454e+00 1.82404175e-01
-1.29848778e-01 -8.37708771e-01 -1.25354469e+00 -2.25297064e-01
7.17250764e-01 -5.64382076e-01 -2.67511189e-01 -3.32970977e-01
-9.97469246e-01 1.64416850e-01 4.06851768e-01 -6.38090909e-01
4.00940001e-01 -1.07550251e+00 5.51388562e-02 5.38789034e-01
-4.03121680e-01 -6.44425035e-01 3.95960510e-01 1.32106042e+00
-7.36647010e-01 7.83468068e-01 -2.55165040e-01 -7.12126195e-01
-1.36905777e+00 4.04649228e-01 1.27928054e+00 2.58559227e-01
-1.13451637e-01 6.79550886e-01 -6.12112761e-01 6.73879385e-01
1.31385610e-01 -1.14037216e+00 1.97498545e-01 1.39141366e-01
7.40495205e-01 6.08919144e-01 2.05090836e-01 2.91439835e-02
-7.41512597e-01 8.66294086e-01 6.13638163e-01 -2.99680084e-01
6.23549223e-01 -9.02111903e-02 -1.89084321e-01 1.15874314e+00
1.18620765e+00 -4.21583354e-02 -6.53337121e-01 1.04289345e-01
-2.12955758e-01 -1.50541291e-01 -2.68922389e-01 -5.79009712e-01
-5.80120802e-01 1.17991173e+00 7.35611081e-01 5.97867310e-01
1.37946546e+00 -7.62264550e-01 4.42302793e-01 4.89213377e-01
3.91368091e-01 -1.20762062e+00 -2.92810202e-01 2.00317249e-01
6.00966156e-01 5.80281392e-02 4.55555499e-01 -8.63114834e-01
-2.86263883e-01 1.43902814e+00 7.37201348e-02 -6.30407393e-01
1.17536724e+00 1.04061687e+00 8.12431127e-02 3.90848517e-01
-6.70596242e-01 1.24315783e-01 -1.09097667e-01 4.48027313e-01
9.11700904e-01 5.15916273e-02 -7.54465342e-01 9.19478178e-01
2.66485780e-01 6.14565730e-01 1.13258743e+00 1.03314602e+00
-8.91427159e-01 -7.58683681e-01 -6.29823029e-01 5.93576193e-01
-6.66423440e-01 2.23818302e-01 -3.71645302e-01 7.66713321e-01
-6.22935236e-01 1.00580812e+00 4.75745440e-01 -1.32976085e-01
9.43423510e-01 4.29966927e-01 6.91343546e-01 1.18549943e-01
-1.30455399e+00 5.92149615e-01 1.16999611e-01 -3.45116913e-01
2.00468116e-02 -2.35500365e-01 -1.66347134e+00 -3.27095598e-01
-1.00525022e+00 2.92170167e-01 7.66309202e-01 5.04907489e-01
3.49574070e-03 9.99945819e-01 1.70270726e-01 -3.33887339e-01
-8.92622411e-01 -8.53084624e-01 -1.32607722e+00 -5.11218965e-01
5.55152833e-01 -3.84424865e-01 -6.02299035e-01 -1.54668525e-01] | [13.935396194458008, 3.2039825916290283] |
3d071943-a96b-4d21-8197-4c488d875eaa | single-underwater-image-restoration-by | 2103.09697 | null | https://arxiv.org/abs/2103.09697v2 | https://arxiv.org/pdf/2103.09697v2.pdf | Single Underwater Image Restoration by Contrastive Learning | Underwater image restoration attracts significant attention due to its importance in unveiling the underwater world. This paper elaborates on a novel method that achieves state-of-the-art results for underwater image restoration based on the unsupervised image-to-image translation framework. We design our method by leveraging from contrastive learning and generative adversarial networks to maximize mutual information between raw and restored images. Additionally, we release a large-scale real underwater image dataset to support both paired and unpaired training modules. Extensive experiments with comparisons to recent approaches further demonstrate the superiority of our proposed method. | ['Mohammad Ali Armin', 'Lars Petersson', 'Ran Wei', 'Saeed Anwar', 'Janet Anstee', 'Elizabeth Botha', 'Tim Malthus', 'Mehrdad Shoeiby', 'Junlin Han'] | 2021-03-17 | null | null | null | null | ['underwater-image-restoration'] | ['computer-vision'] | [ 7.09686399e-01 2.48208493e-01 7.41903245e-01 -5.94358385e-01
-9.00777519e-01 -2.04887778e-01 3.82761240e-01 -3.58774036e-01
-8.02750587e-01 6.86232984e-01 3.65517169e-01 -1.25099584e-01
-7.75762424e-02 -9.34066951e-01 -1.07098949e+00 -9.54743445e-01
-3.16851109e-01 -1.89560696e-01 -1.19029976e-01 -3.88301462e-01
3.32084715e-01 2.11656079e-01 -1.54549372e+00 5.10924263e-03
1.15309429e+00 5.74857831e-01 4.87914622e-01 9.91931915e-01
2.10544229e-01 9.07301366e-01 -4.32277739e-01 -5.48083305e-01
6.45910621e-01 -6.97188616e-01 -4.76332784e-01 1.68941393e-01
7.28471100e-01 -8.23281348e-01 -7.04622686e-01 1.27657020e+00
9.05312002e-01 3.53104234e-01 4.30372149e-01 -6.92028761e-01
-1.01626444e+00 3.79692793e-01 -1.92007244e-01 1.85971275e-01
1.71846807e-01 -1.74422301e-02 8.83901060e-01 -7.88923562e-01
4.77649093e-01 1.02156329e+00 5.95481396e-01 7.43485689e-01
-1.01653445e+00 -6.02189779e-01 -6.56314641e-02 1.51957661e-01
-9.23180282e-01 -5.92396379e-01 6.54192984e-01 -1.59442410e-01
6.14115059e-01 2.88949665e-02 7.12653816e-01 6.39810503e-01
2.68114954e-01 7.87409723e-01 1.34493279e+00 -4.42018151e-01
1.89430833e-01 -3.45451742e-01 -4.88127857e-01 4.79103237e-01
-8.19639117e-02 3.44937652e-01 -5.09451866e-01 1.60642073e-01
8.28390718e-01 1.51949227e-01 -5.66536784e-01 -3.83286402e-02
-6.36546195e-01 7.44024515e-01 7.30034292e-01 -2.36675620e-01
-2.18206376e-01 1.67987674e-01 8.33301470e-02 4.99972254e-01
4.90620464e-01 2.56625533e-01 -9.95456278e-02 1.72549114e-01
-8.18814576e-01 6.18719943e-02 6.78324401e-01 7.52874911e-01
9.98265028e-01 4.53783572e-01 4.34276789e-01 8.74881685e-01
6.50918722e-01 7.64281929e-01 4.15084958e-01 -1.21984470e+00
1.69585556e-01 8.46157596e-03 -3.76554541e-02 -6.49389923e-01
-1.33773580e-01 -1.96240440e-01 -8.65129352e-01 5.20007312e-01
-2.42847964e-01 -6.46125227e-02 -1.04235649e+00 1.50653827e+00
-6.74909772e-03 5.08408785e-01 8.58247280e-01 9.36910391e-01
1.18377924e+00 7.79714704e-01 -2.58518934e-01 -1.04860172e-01
5.63658357e-01 -9.12271261e-01 -8.25043619e-01 -3.98331285e-01
-1.23240501e-01 -5.40728450e-01 7.68833339e-01 1.23423897e-01
-1.12180734e+00 -3.64569694e-01 -1.32520843e+00 -1.40181273e-01
1.05736993e-01 -4.58388865e-01 3.67130011e-01 5.41919947e-01
-1.28495502e+00 5.49003184e-01 -8.49002123e-01 -1.86214283e-01
3.76498282e-01 3.12954277e-01 -7.06502378e-01 -3.92438918e-01
-9.57301497e-01 7.73048639e-01 2.35903680e-01 5.19476652e-01
-1.31970608e+00 -3.89385641e-01 -1.44626033e+00 -3.65536898e-01
-1.64259002e-01 -4.41693634e-01 1.19636381e+00 -6.80783927e-01
-1.80997121e+00 6.04978025e-01 5.29810041e-02 -4.72957999e-01
5.45411050e-01 -3.08840275e-01 -2.48122774e-02 3.80346209e-01
9.76928025e-02 5.59053302e-01 7.57673323e-01 -1.78600311e+00
-5.26299357e-01 -3.07669401e-01 1.49969691e-02 3.76699924e-01
-4.36232686e-01 -2.42259249e-01 -3.82716656e-01 -5.40491760e-01
5.97186744e-01 -7.18071222e-01 -4.53854889e-01 2.02194318e-01
-3.09751779e-01 5.77270687e-01 8.03752184e-01 -8.88758659e-01
3.18151444e-01 -1.90836835e+00 3.14281732e-01 -1.49110734e-01
-4.27583344e-02 1.23722658e-01 -3.70345592e-01 7.17365444e-01
2.10433051e-01 -1.27099037e-01 -8.85249913e-01 -9.33428884e-01
-2.06540674e-01 9.29372370e-01 -4.70047027e-01 9.45164263e-01
-2.41311211e-02 7.29225457e-01 -1.06998849e+00 -4.08380270e-01
4.57924247e-01 5.74905157e-01 -6.78777754e-01 8.46592546e-01
4.57367778e-01 9.22159255e-01 -3.44875157e-02 8.58777404e-01
9.54654217e-01 3.59813362e-01 1.35490775e-01 -2.36128300e-01
-2.23565310e-01 -1.47797570e-01 -7.45622933e-01 1.73850513e+00
-5.25100172e-01 7.40112841e-01 3.95296067e-01 -1.11614287e+00
8.97687435e-01 8.42467248e-02 2.58269370e-01 -8.77994359e-01
1.37233296e-02 2.39830896e-01 -3.37086320e-01 -8.63946557e-01
7.69304156e-01 -8.13210964e-01 2.16148764e-01 5.29760793e-02
2.75939614e-01 -4.90697801e-01 9.22984406e-02 2.39214733e-01
8.04273784e-01 3.84571910e-01 3.41170281e-02 -2.78574228e-01
2.08180696e-01 -5.95580816e-01 5.77902555e-01 8.00035775e-01
-1.62754804e-01 1.08250284e+00 -2.32404962e-01 -2.42071643e-01
-1.13961625e+00 -1.24157417e+00 -2.99124509e-01 6.06305420e-01
6.90122724e-01 3.55931342e-01 -5.84379911e-01 -3.44654232e-01
-1.64481357e-01 3.34396809e-01 -8.36544216e-01 9.11326185e-02
-4.42714036e-01 -9.66959715e-01 7.57210016e-01 4.88608152e-01
6.62170589e-01 -1.15724003e+00 -3.23775023e-01 1.39458030e-01
-3.27221632e-01 -1.32208145e+00 -1.09555505e-01 1.71894468e-02
-1.08171391e+00 -8.93635869e-01 -9.37666178e-01 -1.18122113e+00
9.29738462e-01 5.54149628e-01 8.53155732e-01 2.66292602e-01
-2.08750188e-01 4.02091265e-01 -6.61549509e-01 -2.02765286e-01
-6.20083153e-01 -7.27361441e-01 1.14310130e-01 5.99771403e-02
-5.32621443e-01 -9.02921140e-01 -7.82651722e-01 2.49465525e-01
-1.61346412e+00 -2.25029230e-01 6.56296313e-01 1.01106739e+00
4.76518780e-01 -2.79695004e-01 4.28467244e-01 -6.21676624e-01
2.84968853e-01 -4.28565085e-01 -4.73924607e-01 -2.25469917e-02
-3.88221771e-01 -2.68572792e-02 3.24268997e-01 -7.99596235e-02
-1.04467857e+00 6.29409477e-02 -6.78602815e-01 -7.11237267e-02
2.18222782e-01 6.44609928e-01 -1.64854601e-01 -6.87089443e-01
3.82555127e-01 6.77891612e-01 3.74572694e-01 -4.64990377e-01
2.54358351e-01 7.64325917e-01 1.11634994e+00 -2.80951202e-01
1.19268358e+00 1.05478990e+00 -3.54475021e-01 -1.07352400e+00
-6.93452537e-01 -4.40476626e-01 -5.23554862e-01 -3.20337534e-01
8.30109298e-01 -1.33500934e+00 -7.03874767e-01 8.73661876e-01
-8.98661256e-01 -5.23052573e-01 -1.59876227e-01 4.39928919e-01
-4.66171056e-01 9.44318593e-01 -1.01514053e+00 -9.38709736e-01
-5.70385396e-01 -1.26476729e+00 9.49209332e-01 4.89082932e-01
9.06392038e-01 -9.71418679e-01 4.12972659e-01 3.50892097e-01
5.24543226e-01 2.77628183e-01 -5.64159676e-02 -1.15683869e-01
-5.59787154e-01 -1.19928613e-01 -3.26816589e-01 9.23522770e-01
1.98728785e-01 -2.97250837e-01 -9.71665144e-01 -5.88067114e-01
2.46163905e-02 -5.25236189e-01 1.19650936e+00 2.13662997e-01
5.81129193e-01 -3.33619475e-01 2.66378462e-01 1.11949408e+00
1.64496493e+00 -1.55204967e-01 1.41427028e+00 6.84655964e-01
6.77546084e-01 6.23950005e-01 3.10964048e-01 4.62669879e-01
6.33005857e-01 2.31059283e-01 1.10552847e+00 -3.87488335e-01
9.45842192e-02 -3.26870799e-01 4.57205564e-01 9.37097251e-01
-2.25615934e-01 -2.62017310e-01 -3.16455871e-01 8.56946886e-01
-1.55507493e+00 -8.93716931e-01 1.30848095e-01 2.02764940e+00
6.70304775e-01 -4.05681878e-01 -7.20778108e-01 -8.62889066e-02
5.21650851e-01 2.69154102e-01 -3.68039370e-01 9.47028026e-02
-4.44848627e-01 7.36854896e-02 7.17908442e-01 7.74084210e-01
-1.19230676e+00 7.72865355e-01 6.86864614e+00 2.51757562e-01
-8.10846984e-01 -8.07550251e-02 3.44668031e-01 5.59479535e-01
-4.78068680e-01 2.49445364e-02 -3.11873585e-01 1.85467571e-01
5.21341801e-01 1.67911008e-01 3.65649641e-01 5.57383001e-01
1.95041269e-01 5.72392978e-02 -5.28037310e-01 6.90762937e-01
5.05384982e-01 -1.18076909e+00 1.23420291e-01 1.41349986e-01
1.25075257e+00 3.32772285e-01 -1.27576753e-01 -1.04861185e-01
4.62174177e-01 -9.59415257e-01 9.19158399e-01 5.69304109e-01
6.85081244e-01 -5.07237732e-01 1.18122756e+00 1.33188650e-01
-9.08768356e-01 -3.06480546e-02 -5.04459023e-01 -3.20554495e-01
5.67479908e-01 2.24038810e-01 -4.20538932e-01 5.75099230e-01
1.04930913e+00 9.32577193e-01 -6.68335259e-02 1.24928331e+00
-7.17986166e-01 5.12564242e-01 -2.47545794e-01 3.47776502e-01
9.69444066e-02 -4.62919921e-01 5.89421749e-01 1.14740324e+00
4.60214376e-01 3.78291965e-01 1.47082791e-01 4.90420371e-01
-3.42213303e-01 5.04513942e-02 -7.09962964e-01 3.38728875e-01
1.90174177e-01 1.05130649e+00 -3.90185684e-01 -1.82398364e-01
-4.45718080e-01 1.24771202e+00 6.19732067e-02 3.74562144e-01
-3.74723822e-01 -3.91204774e-01 7.21709490e-01 -2.59481549e-01
3.85070920e-01 -4.17281300e-01 -9.79545992e-03 -1.26311517e+00
-1.40442804e-01 -5.85581303e-01 2.22147126e-02 -7.76487827e-01
-1.46849418e+00 8.05545628e-01 -3.28227997e-01 -1.71487010e+00
2.28176285e-02 -3.84776473e-01 -6.64728701e-01 7.47922480e-01
-2.46395206e+00 -1.25967586e+00 -8.20039034e-01 4.17418838e-01
5.72232544e-01 4.63387184e-02 8.02506328e-01 3.25145513e-01
-1.58199832e-01 5.44754207e-01 5.82738459e-01 4.41607982e-01
6.18221879e-01 -1.27928281e+00 4.40401018e-01 1.38596857e+00
-1.36050954e-01 5.25983930e-01 1.11242080e+00 -5.04534841e-01
-1.75741780e+00 -9.95743454e-01 2.93788642e-01 6.74708188e-02
6.23668373e-01 8.41775835e-02 -9.51379418e-01 7.15567708e-01
4.89333361e-01 2.44507030e-01 7.78124154e-01 -7.40284801e-01
-2.25377053e-01 -1.74948156e-01 -1.29328632e+00 4.46112096e-01
7.38664508e-01 -4.00305927e-01 -5.76277494e-01 6.83083162e-02
6.57613218e-01 -6.15422010e-01 -9.69857693e-01 7.41765738e-01
5.65202355e-01 -1.09740472e+00 1.06663752e+00 7.15221688e-02
9.65524554e-01 -4.52995032e-01 -5.55739403e-01 -1.32370627e+00
2.67416835e-01 -7.34294057e-01 3.23412091e-01 8.71389985e-01
1.85525283e-01 -7.85358548e-01 5.82911193e-01 2.27982640e-01
-7.01423764e-01 -1.33582085e-01 -1.07489407e+00 -5.54846525e-01
6.66049272e-02 -3.08127373e-01 1.08912311e-01 6.34088814e-01
-1.73206627e-01 -5.90734929e-02 -1.03497660e+00 8.26869667e-01
1.34776950e+00 1.48599371e-01 9.07905281e-01 -7.85887599e-01
-3.82653832e-01 1.68956980e-01 -7.44623423e-01 -1.46010733e+00
8.26283693e-02 -5.77652633e-01 1.00203073e+00 -1.96680450e+00
3.44153464e-01 5.76768909e-03 -1.68347135e-01 5.61956823e-01
-3.32071304e-01 1.34695745e+00 1.39756620e-01 2.96820968e-01
-3.70970368e-01 1.13189054e+00 1.32715034e+00 -2.41195381e-01
2.23658513e-02 -1.88550100e-01 -6.88040078e-01 4.63509381e-01
5.60697913e-01 -3.14803243e-01 -3.84462513e-02 -8.32336009e-01
-4.33271974e-02 1.21700451e-01 3.76139730e-01 -9.06221271e-01
2.42136523e-01 3.99174839e-02 -1.68350656e-02 -1.04609065e-01
3.96764994e-01 -5.78187227e-01 -2.22124442e-01 6.05985224e-01
-1.61245957e-01 -2.06722394e-01 1.42209217e-01 9.05558348e-01
-6.11732900e-01 -3.55739564e-01 1.03347135e+00 -2.43922889e-01
-9.85956013e-01 1.96306482e-01 -2.52666473e-01 -2.36301154e-01
4.25890177e-01 -1.81979731e-01 -2.89701879e-01 -8.22287798e-01
-4.99515295e-01 1.70462295e-01 6.66163325e-01 2.09383354e-01
1.26061606e+00 -7.08438575e-01 -1.27443326e+00 2.51287311e-01
1.88848659e-01 3.29664093e-03 4.89896029e-01 5.51851034e-01
-1.08115983e+00 -6.34960294e-01 -2.11252242e-01 -4.55284566e-01
-1.19036222e+00 -2.72573624e-02 4.23214734e-01 1.51869461e-01
-1.12689972e+00 9.77343261e-01 1.71567649e-01 -8.74906361e-01
-5.63975275e-02 1.72044575e-01 -1.94547877e-01 -5.49706042e-01
8.62889528e-01 2.88278937e-01 -2.09255740e-01 -8.68138731e-01
-2.65541617e-02 6.47605419e-01 1.54148161e-01 -3.74490201e-01
1.80117846e+00 -5.35109282e-01 -4.49535966e-01 1.00877872e-02
1.37019765e+00 -7.21001476e-02 -1.80972230e+00 -1.54092282e-01
-7.48136759e-01 -6.61998212e-01 2.09575653e-01 -3.56071472e-01
-1.29788470e+00 7.77810454e-01 7.95004129e-01 4.51265555e-03
1.25194275e+00 -1.45327032e-01 8.94964159e-01 5.14191687e-01
4.91791308e-01 -5.79053044e-01 1.95828974e-01 5.40208876e-01
7.95291007e-01 -1.64197600e+00 2.42792100e-01 -1.57465816e-01
-4.26141471e-01 1.07690454e+00 2.20846519e-01 -4.77302104e-01
4.72302794e-01 5.21930814e-01 7.79171705e-01 9.21043307e-02
3.88731882e-02 -3.16099107e-01 -1.45554617e-01 6.67724192e-01
9.71713662e-02 -1.74936324e-01 -2.82420129e-01 2.25157022e-01
-3.90340351e-02 -1.93316132e-01 1.02780271e+00 1.29211736e+00
-6.11084640e-01 -1.07153535e+00 -3.04153025e-01 -3.13696377e-02
-5.62101483e-01 -5.04077733e-01 2.98002660e-01 4.12524283e-01
-3.48430634e-01 1.08034885e+00 -1.39211208e-01 -4.78696048e-01
2.03195348e-01 -7.48539448e-01 4.30743098e-01 -2.89427102e-01
-1.45922735e-01 9.07863677e-02 -3.31812710e-01 -2.70787060e-01
-1.03977668e+00 -5.14720738e-01 -1.40837419e+00 2.23983735e-01
-3.12322378e-01 3.80039841e-01 9.36471701e-01 1.08958614e+00
-6.41776696e-02 4.56832886e-01 1.01413012e+00 -1.75844097e+00
-4.03113335e-01 -1.26757812e+00 -6.70578718e-01 3.96396637e-01
6.24164402e-01 -2.39458844e-01 -7.81516194e-01 3.98858160e-01] | [10.695380210876465, -3.5464460849761963] |
6fe7d085-4d06-4f8d-8df5-209ad9d66537 | domain-aligned-prefix-averaging-for-domain | 2305.16820 | null | https://arxiv.org/abs/2305.16820v2 | https://arxiv.org/pdf/2305.16820v2.pdf | Domain Aligned Prefix Averaging for Domain Generalization in Abstractive Summarization | Domain generalization is hitherto an underexplored area applied in abstractive summarization. Moreover, most existing works on domain generalization have sophisticated training algorithms. In this paper, we propose a lightweight, weight averaging based, Domain Aligned Prefix Averaging approach to domain generalization for abstractive summarization. Given a number of source domains, our method first trains a prefix for each one of them. These source prefixes generate summaries for a small number of target domain documents. The similarity of the generated summaries to their corresponding documents is used for calculating weights required to average source prefixes. In DAPA, prefix tuning allows for lightweight finetuning, and weight averaging allows for the computationally efficient addition of new source domains. When evaluated on four diverse summarization domains, DAPA shows comparable or better performance against the baselines, demonstrating the effectiveness of its prefix averaging scheme. | ['Pradeepika Verma', 'Sukomal Pal', 'Pranav Ajit Nair'] | 2023-05-26 | null | null | null | null | ['abstractive-text-summarization'] | ['natural-language-processing'] | [ 6.12903476e-01 1.16825037e-01 -7.56961107e-01 -3.51799488e-01
-9.94370818e-01 -7.76906967e-01 8.11192334e-01 8.34206045e-01
-3.23039770e-01 1.12931836e+00 8.99643898e-01 1.54117391e-01
-1.97291553e-01 -6.67345941e-01 -5.40504038e-01 -2.93520629e-01
-1.36744855e-02 8.74474585e-01 3.97648394e-01 -2.06035241e-01
7.26882041e-01 2.25714311e-01 -1.67685974e+00 4.35634017e-01
1.66399157e+00 6.60766006e-01 2.43011713e-01 7.41872907e-01
-4.19566989e-01 1.95914343e-01 -1.19867837e+00 -8.01401362e-02
-1.27753392e-01 -4.79483902e-01 -9.95789468e-01 8.63796845e-02
7.57902801e-01 -4.95429277e-01 -2.05746382e-01 7.72022069e-01
5.32657504e-01 5.98362923e-01 1.00290477e+00 -7.25732505e-01
-4.04690683e-01 9.19402897e-01 -4.00639832e-01 5.54083824e-01
7.17972755e-01 -3.06625098e-01 1.13310564e+00 -5.19065082e-01
7.99651563e-01 1.08546174e+00 3.86947811e-01 6.01973355e-01
-1.11875677e+00 -5.45081258e-01 3.62839818e-01 -6.50455058e-02
-8.85936201e-01 -4.95394319e-01 5.28792441e-01 -1.74593031e-02
1.30306792e+00 1.75866246e-01 4.76692170e-01 1.06701767e+00
-8.67163949e-03 9.34071124e-01 3.60349178e-01 -2.72319049e-01
6.14267588e-01 -4.06920910e-02 5.57770193e-01 -3.56282070e-02
8.88639092e-01 -5.67507029e-01 -6.93520844e-01 -6.72322452e-01
2.74192542e-01 -1.43202081e-01 -2.56760985e-01 -1.41686082e-01
-1.10322452e+00 6.56528890e-01 -6.51218416e-03 2.51221091e-01
-6.20850682e-01 -2.02759519e-01 7.95331240e-01 3.04136157e-01
8.35951984e-01 8.94217789e-01 -4.28690046e-01 -2.72397459e-01
-1.38577425e+00 7.87423551e-01 9.04211938e-01 1.25000811e+00
5.94241917e-01 -2.84838453e-02 -5.81509948e-01 1.06942296e+00
-3.85821164e-01 5.22601902e-01 8.28655422e-01 -1.02843809e+00
8.10229003e-01 8.83120775e-01 3.00179601e-01 -6.48435175e-01
-2.09693551e-01 -4.90227550e-01 -6.82802439e-01 -5.55357397e-01
1.26301259e-01 -1.17290251e-01 -7.23954320e-01 1.58656120e+00
8.72584581e-02 1.37239993e-01 4.57743019e-01 2.61684209e-01
7.45029688e-01 8.95031452e-01 1.00418374e-01 -5.15233278e-01
1.00245619e+00 -7.82486200e-01 -5.34891367e-01 -3.97797853e-01
6.34636223e-01 -5.60010433e-01 1.11634135e+00 3.65305781e-01
-1.29601562e+00 -3.19353789e-01 -1.15714633e+00 5.20451134e-03
-1.60743847e-01 1.21386260e-01 2.59489536e-01 3.52955580e-01
-7.41586149e-01 1.11616647e+00 -6.08191669e-01 -7.76333690e-01
5.14565170e-01 2.36489981e-01 -1.01070225e-01 -2.34169453e-01
-1.08589888e+00 6.78413451e-01 1.06595159e+00 -1.10047126e+00
-5.27600884e-01 -1.02923250e+00 -6.73515141e-01 3.02004546e-01
2.43886605e-01 -1.04695189e+00 1.57888281e+00 -5.33574700e-01
-1.29584539e+00 5.40506780e-01 -4.36757028e-01 -8.87120605e-01
1.72100052e-01 -6.68686867e-01 -3.78500581e-01 3.39950740e-01
3.25089127e-01 5.48775792e-01 8.70358050e-01 -9.10675943e-01
-1.07136106e+00 -2.05497831e-01 -1.84231341e-01 6.35901093e-01
-8.10235679e-01 -2.74078280e-01 -1.60230249e-01 -8.63126397e-01
-1.10730521e-01 -3.50217342e-01 -6.57892749e-02 -8.33103955e-01
-3.77037048e-01 -6.45869076e-01 7.71291554e-01 -6.60549462e-01
1.95080423e+00 -2.06644154e+00 2.33003929e-01 -1.47424582e-02
8.96770284e-02 5.35792053e-01 -2.32272640e-01 7.69496500e-01
2.49859095e-01 4.01893351e-03 -5.52872300e-01 -7.31416792e-02
-5.20891175e-02 1.88612789e-01 -7.84940481e-01 -1.87272970e-02
1.15524968e-02 4.46290553e-01 -1.26376379e+00 -5.16612470e-01
-1.88088063e-02 -9.25036669e-02 -7.21895576e-01 1.27107307e-01
-5.57304442e-01 1.83748364e-01 -5.12389898e-01 2.77732551e-01
5.65406203e-01 -1.47536527e-02 1.80968970e-01 6.43835366e-02
5.57389632e-02 6.90354645e-01 -1.01202977e+00 1.89391315e+00
-2.95064092e-01 3.77410084e-01 -4.42569107e-01 -1.02020085e+00
1.11839759e+00 1.25576884e-01 3.56623024e-01 -3.42801988e-01
-1.44536152e-01 5.95657825e-01 -3.91996473e-01 -2.15654686e-01
1.11367130e+00 1.74551457e-01 -4.82463300e-01 7.65529931e-01
2.10541829e-01 -4.36852336e-01 9.18994606e-01 7.04504848e-01
1.09305382e+00 -7.07496479e-02 7.76317894e-01 -3.41838807e-01
6.15582407e-01 4.03814822e-01 4.49888468e-01 1.04158235e+00
2.00976953e-01 5.28469801e-01 3.47175628e-01 -1.68063298e-01
-1.14950693e+00 -1.11220717e+00 1.88286602e-02 1.34802771e+00
8.46325234e-02 -6.70406699e-01 -7.85916626e-01 -6.76747024e-01
2.48115584e-01 1.26571059e+00 -2.26177812e-01 -5.16460598e-01
-7.99489737e-01 -4.57139552e-01 6.15336478e-01 5.70189178e-01
6.12987995e-01 -8.84959519e-01 -7.43417561e-01 4.94097859e-01
-3.87029916e-01 -8.58700454e-01 -6.46162093e-01 -1.27801031e-01
-1.49505365e+00 -7.01426446e-01 -1.09706771e+00 -8.51678550e-01
3.11272949e-01 2.84943432e-01 1.22704792e+00 -4.76208359e-01
2.98313260e-01 4.75181669e-01 -4.90191877e-01 -6.23095214e-01
-7.93448389e-01 8.19915056e-01 2.46662498e-01 -5.03449261e-01
3.96746963e-01 -8.14712584e-01 -4.37426984e-01 -4.92537506e-02
-1.03215408e+00 -3.82342041e-01 7.02318907e-01 5.91392636e-01
5.33166766e-01 -1.85035661e-01 1.02450216e+00 -1.01195145e+00
1.54071474e+00 -5.64785957e-01 -1.06446713e-01 4.36697185e-01
-4.23345387e-01 2.78955013e-01 7.74465561e-01 -6.50726497e-01
-1.28079581e+00 -3.81656885e-01 3.38643372e-01 9.70573947e-02
-2.32806340e-01 6.54457211e-01 1.17227279e-01 6.62534177e-01
1.13666832e+00 5.24900079e-01 -6.33421540e-03 -5.17020643e-01
4.43524033e-01 7.96590626e-01 8.37456763e-01 -7.82803059e-01
4.66667473e-01 1.86609149e-01 -4.41532820e-01 -1.06892848e+00
-8.04665625e-01 -7.41362810e-01 -3.95929158e-01 2.76272714e-01
2.52230197e-01 -7.88822591e-01 5.49005829e-02 1.36622563e-01
-1.18771470e+00 -8.21534023e-02 -7.07982659e-01 2.70919651e-01
-5.67939699e-01 7.44495809e-01 -9.50684994e-02 -3.79028499e-01
-9.18614984e-01 -3.50644290e-01 9.86963630e-01 4.86479998e-01
-8.73015940e-01 -9.11102533e-01 3.07125688e-01 -1.11968808e-01
5.17899692e-01 1.19589008e-01 1.11643183e+00 -1.33310294e+00
5.29270321e-02 -4.61772531e-01 5.09035923e-02 4.02655929e-01
2.62909442e-01 -2.01265067e-01 -5.08279443e-01 -4.00378793e-01
-2.85468400e-01 -1.32890254e-01 1.09714913e+00 5.16425908e-01
9.77357566e-01 -5.94869852e-01 -7.00723350e-01 2.22279012e-01
8.70706260e-01 5.43556586e-02 2.68520176e-01 4.56340373e-01
1.05369657e-01 3.39971662e-01 9.34422135e-01 9.71244335e-01
1.00036867e-01 3.39550853e-01 -1.61981151e-01 4.39896435e-01
-1.78847447e-01 -2.48413682e-01 3.77802908e-01 7.42281079e-01
3.34314369e-02 -4.94780004e-01 -7.27944255e-01 9.53685164e-01
-1.77104306e+00 -1.14112222e+00 2.45870650e-01 2.42215943e+00
1.00986493e+00 1.38897792e-01 3.97650659e-01 9.05004218e-02
8.15889895e-01 2.21697599e-01 -8.77167881e-01 -7.04486966e-01
-2.24431783e-01 4.36581820e-01 3.43497932e-01 1.51508093e-01
-9.59738314e-01 9.47370231e-01 6.30256653e+00 9.57475245e-01
-8.42815042e-01 -3.63700420e-01 5.55281453e-02 -3.66827041e-01
-4.27609384e-01 -1.06617346e-01 -9.29950893e-01 3.70209277e-01
8.90318215e-01 -1.23400617e+00 1.18665770e-01 1.00480056e+00
7.15537071e-02 -3.86458457e-01 -1.15916693e+00 5.27807891e-01
1.78892955e-01 -1.38282907e+00 7.98723578e-01 -2.95013458e-01
1.11491024e+00 -9.23407674e-02 -4.21142802e-02 4.84651774e-01
3.53477180e-01 -4.85759497e-01 2.74833649e-01 9.55034122e-02
7.22961962e-01 -1.01256478e+00 5.71858466e-01 4.49310124e-01
-6.94444716e-01 -2.82345682e-01 -6.97328687e-01 2.28285715e-02
2.23612547e-01 6.74544334e-01 -1.14190304e+00 8.12392771e-01
3.83775920e-01 7.99329281e-01 -4.42207724e-01 1.08166492e+00
-9.51680392e-02 6.93463206e-01 -3.98308367e-01 -1.42833561e-01
1.98178500e-01 2.49244645e-03 1.05276132e+00 1.50146437e+00
5.25561392e-01 6.61875829e-02 1.45556837e-01 2.59128720e-01
-3.42334241e-01 2.98965544e-01 -5.81706226e-01 -1.87862545e-01
9.81642962e-01 8.27299953e-01 -3.99377942e-01 -9.34759259e-01
1.21314898e-02 9.01560962e-01 1.74494445e-01 3.47823977e-01
-5.12045443e-01 -9.06992853e-01 7.07437634e-01 1.76851586e-01
4.09286946e-01 -7.86750689e-02 -4.24934834e-01 -1.18224835e+00
1.84784140e-02 -9.34103906e-01 9.21770811e-01 -2.74832755e-01
-1.14067268e+00 4.35493857e-01 7.01599181e-01 -1.28425479e+00
-4.58220333e-01 4.08221781e-02 -1.00567353e+00 5.46174407e-01
-1.34536576e+00 -5.17041504e-01 -2.72717685e-01 3.30657661e-01
9.66383219e-01 -2.80719191e-01 9.27931786e-01 -1.20685346e-01
-3.42813581e-01 5.81259072e-01 5.55696547e-01 -4.32024956e-01
1.05618489e+00 -1.25639951e+00 6.19705081e-01 8.06521475e-01
-1.91966727e-01 7.55043507e-01 1.17099845e+00 -9.80380177e-01
-8.05561423e-01 -1.24658132e+00 1.14739299e+00 -1.92448661e-01
3.69328231e-01 9.65655521e-02 -1.26091635e+00 5.75879157e-01
4.97325093e-01 -8.45794499e-01 7.28097200e-01 9.68919620e-02
-2.64218509e-01 -1.39492810e-01 -1.27881646e+00 5.78592598e-01
1.03264546e+00 1.37737498e-01 -1.30779982e+00 4.45904195e-01
7.17895329e-01 -3.38758200e-01 -7.85946429e-01 2.80627877e-01
4.16854769e-01 -7.02203453e-01 9.43845451e-01 -5.40541410e-01
6.16676211e-01 -5.19759655e-02 3.29986066e-02 -1.77891624e+00
-2.02403784e-01 -6.38992667e-01 -4.77492660e-01 1.45083809e+00
3.36363673e-01 -7.01074302e-01 7.06536293e-01 2.17770591e-01
-3.21166188e-01 -4.22655046e-01 -6.74435854e-01 -1.09395885e+00
3.47888410e-01 1.46378785e-01 8.94484699e-01 5.97885847e-01
3.39741617e-01 6.40666306e-01 -1.92780290e-02 -1.90953389e-01
7.06800640e-01 2.66459882e-01 9.41855550e-01 -1.56849718e+00
-9.45651755e-02 -6.43342853e-01 7.86731094e-02 -1.28839695e+00
1.69864863e-01 -9.07132745e-01 -2.79809356e-01 -1.92078876e+00
1.95540980e-01 9.92274880e-02 -2.98379716e-02 1.01568654e-01
-3.70604664e-01 -3.88825029e-01 -1.12317882e-01 3.01189393e-01
-8.50919485e-01 5.13247252e-01 9.21976507e-01 -2.69790173e-01
-8.04326594e-01 2.33465642e-01 -9.03813004e-01 5.23061454e-01
1.15893710e+00 -4.83523518e-01 -6.50820017e-01 -4.48416829e-01
-2.39038035e-01 -1.56379059e-01 -3.28812361e-01 -1.29977787e+00
3.03269744e-01 -1.11575812e-01 1.84997872e-01 -9.26156342e-01
-7.92406648e-02 -1.61713034e-01 -2.66789973e-01 3.03863674e-01
-5.58531821e-01 -5.13689779e-02 4.80521858e-01 7.10852623e-01
-4.24892724e-01 -3.49976659e-01 6.57438755e-01 -1.28634036e-01
-7.20385849e-01 1.74169485e-02 -3.95407885e-01 6.42837882e-01
8.94344270e-01 -6.28930032e-01 -2.93502003e-01 -3.40326428e-01
-3.90407056e-01 3.82953137e-01 5.24993598e-01 2.97259212e-01
5.45405984e-01 -9.99812663e-01 -1.00048649e+00 -1.63596556e-01
4.06376570e-01 3.01001072e-01 2.40966752e-01 2.83927917e-01
-2.96932697e-01 4.94656116e-01 -1.97826847e-01 -4.96270984e-01
-1.33411324e+00 2.97989875e-01 -3.31519634e-01 -6.14353478e-01
-5.71992934e-01 6.93580747e-01 -3.20705362e-02 -2.14209467e-01
2.43000254e-01 -4.37925696e-01 -3.88314664e-01 3.77162039e-01
7.43816733e-01 9.28541601e-01 1.41465798e-01 -1.12044960e-01
-2.58708566e-01 3.79781902e-01 -7.12614119e-01 -1.36068463e-01
1.47963166e+00 4.37584519e-03 1.18671253e-01 1.84908971e-01
8.97925258e-01 -7.07759038e-02 -9.55033123e-01 -5.07569373e-01
4.60981965e-01 -1.92677870e-01 -3.46996695e-01 -6.61809385e-01
-1.46562889e-01 4.86851215e-01 -2.07613334e-01 1.25962913e-01
1.36134362e+00 6.74538165e-02 9.90359068e-01 6.89196765e-01
1.37155339e-01 -1.34096968e+00 1.92100480e-01 8.57381642e-01
9.13389504e-01 -5.99895597e-01 4.53911930e-01 -2.14635924e-01
-8.53434503e-01 1.11513722e+00 4.71325815e-01 -3.99859130e-01
-8.88484195e-02 -2.52483845e-01 -3.99758488e-01 1.03505611e-01
-7.54139543e-01 9.61196795e-02 2.79978424e-01 8.30118537e-01
2.28973255e-01 -9.11490917e-02 -7.90792406e-01 5.38376272e-01
-4.19882804e-01 -2.25665029e-02 6.67790473e-01 1.02760696e+00
-1.13871002e+00 -1.13185716e+00 -2.53539413e-01 8.67383122e-01
-4.13029402e-01 -3.80563699e-02 -6.11851096e-01 5.84992230e-01
-4.89746809e-01 8.83898795e-01 1.35613441e-01 4.92935404e-02
6.88480794e-01 3.41456056e-01 4.28211808e-01 -1.04165602e+00
-6.24817610e-01 -1.97000861e-01 1.77897274e-01 -1.64015099e-01
-2.72229135e-01 -9.60313201e-01 -1.24327946e+00 -3.66534412e-01
-1.12420805e-01 4.76356894e-01 2.59196550e-01 6.94614291e-01
7.49880195e-01 3.61291200e-01 4.00128812e-01 -7.16478348e-01
-1.00187635e+00 -1.25363564e+00 -4.77150083e-01 5.97288013e-01
2.13652909e-01 -5.34036040e-01 -8.57208669e-02 -1.50275258e-02] | [12.40915584564209, 9.420913696289062] |
96a6ede5-8178-45ab-b48f-56160d3e6d92 | identity-masking-effectiveness-and-gesture | 2301.08408 | null | https://arxiv.org/abs/2301.08408v1 | https://arxiv.org/pdf/2301.08408v1.pdf | Identity masking effectiveness and gesture recognition: Effects of eye enhancement in seeing through the mask | Face identity masking algorithms developed in recent years aim to protect the privacy of people in video recordings. These algorithms are designed to interfere with identification, while preserving information about facial actions. An important challenge is to preserve subtle actions in the eye region, while obscuring the salient identity cues from the eyes. We evaluated the effectiveness of identity-masking algorithms based on Canny filters, applied with and without eye enhancement, for interfering with identification and preserving facial actions. In Experiments 1 and 2, we tested human participants' ability to match the facial identity of a driver in a low resolution video to a high resolution facial image. Results showed that both masking methods impaired identification, and that eye enhancement did not alter the effectiveness of the Canny filter mask. In Experiment 3, we tested action preservation and found that neither method interfered significantly with driver action perception. We conclude that relatively simple, filter-based masking algorithms, which are suitable for application to low quality video, can be used in privacy protection without compromising action perception. | ["Alice J. O'Toole", 'Thomas Karnowski', 'Madeline Rachow'] | 2023-01-20 | null | null | null | null | ['gesture-recognition'] | ['computer-vision'] | [ 6.60827816e-01 -1.48624152e-01 3.07761133e-01 -3.71571481e-01
-1.41470805e-01 -7.87791908e-01 3.92629266e-01 -1.98436573e-01
-8.88691664e-01 4.87195760e-01 1.47778749e-01 -4.16886151e-01
1.34490713e-01 -3.62620920e-01 -3.84298176e-01 -7.37697959e-01
8.16607624e-02 -7.28462279e-01 2.20364362e-01 -7.74895598e-05
5.51627576e-01 1.08798516e+00 -2.20856166e+00 5.55917084e-01
2.84865439e-01 8.56858253e-01 -3.62529427e-01 7.36676276e-01
3.34443033e-01 1.01795518e+00 -8.59503210e-01 -4.99405503e-01
6.34020209e-01 -6.03613794e-01 -2.50857711e-01 2.19191164e-01
1.05643010e+00 -7.10999131e-01 -4.01519865e-01 1.16720057e+00
6.50332153e-01 -1.03808567e-03 1.79258376e-01 -1.34371209e+00
-2.09830329e-01 -2.60533422e-01 -5.20620584e-01 3.26182991e-01
6.05302393e-01 2.81293154e-01 1.19428754e-01 -6.09767497e-01
4.54472899e-01 1.30698514e+00 7.23638237e-01 9.14499342e-01
-1.39931846e+00 -1.10969150e+00 -2.37211034e-01 4.40287232e-01
-1.85495055e+00 -1.36280918e+00 5.14292598e-01 -3.66928399e-01
6.90513730e-01 8.40826333e-01 2.92443871e-01 5.60457706e-01
3.53837907e-01 -7.10049421e-02 1.27822137e+00 -5.11856019e-01
-2.21603006e-01 5.97913742e-01 -1.74405292e-01 5.81067920e-01
4.70553696e-01 8.36211681e-01 -5.91695189e-01 -3.38110566e-01
5.95534742e-01 -3.98291528e-01 -6.27559066e-01 8.23567212e-02
-6.78165257e-01 4.31026071e-01 -1.36672258e-01 2.45413020e-01
-2.71867305e-01 -1.48080617e-01 2.51181126e-01 3.06073427e-01
3.57003808e-01 2.37956926e-01 2.08554909e-01 3.00234016e-02
-4.46558386e-01 9.23354402e-02 6.57616377e-01 6.42677069e-01
5.87222993e-01 -1.15558945e-01 -4.08598602e-01 3.88103366e-01
9.18554515e-02 4.30200249e-01 1.51296839e-01 -1.05392039e+00
-8.90569985e-02 2.45698109e-01 4.05393094e-01 -1.18749774e+00
-2.11140677e-01 2.12808147e-01 -1.63808957e-01 1.18355107e+00
6.42598867e-01 -4.00099069e-01 -6.78036094e-01 1.66371572e+00
3.70079368e-01 1.63842037e-01 -1.47532690e-02 9.90682244e-01
6.02336407e-01 1.17653303e-01 1.70742318e-01 -5.75897455e-01
1.54888868e+00 -1.78169549e-01 -1.20701838e+00 -8.60551447e-02
2.99322337e-01 -1.18115711e+00 5.92311919e-01 2.67859578e-01
-1.17302275e+00 -9.66785371e-01 -1.02638376e+00 -5.86311743e-02
-1.62757054e-01 -1.89279336e-02 1.61296040e-01 1.59741664e+00
-1.20017469e+00 4.01415825e-01 -3.41693848e-01 -1.40369534e-01
3.12585771e-01 7.16683686e-01 -8.38279068e-01 6.74006268e-02
-9.79610801e-01 1.15411711e+00 -6.45584390e-02 2.01790988e-01
-2.90944099e-01 -3.77355307e-01 -1.00012338e+00 -1.49713606e-01
1.38165370e-01 -2.66209573e-01 1.12101614e+00 -1.49664962e+00
-1.27733386e+00 1.42133951e+00 -6.14728749e-01 -5.47052145e-01
5.35908222e-01 -1.52724341e-01 -1.01784420e+00 3.72617066e-01
-1.73129559e-01 6.45712137e-01 1.42357934e+00 -1.15978587e+00
-7.51369059e-01 -6.95310950e-01 -1.88637435e-01 1.54811218e-01
-2.41455231e-02 8.18225265e-01 -1.27540231e-01 -3.47858220e-01
-3.96614552e-01 -7.08007038e-01 2.09342331e-01 3.09104025e-01
1.90147102e-01 4.27413553e-01 1.27069426e+00 -9.12162900e-01
1.13051617e+00 -2.80482268e+00 -7.95571148e-01 2.16381386e-01
1.26465723e-01 7.26045787e-01 -1.08200066e-01 3.77756208e-02
-2.32875302e-01 6.17030151e-02 6.76906928e-02 -1.74265891e-01
-2.26343900e-01 3.74039263e-02 -1.43923785e-03 1.06288397e+00
4.53480706e-02 5.15051484e-01 -3.65649045e-01 -4.57297742e-01
2.94259012e-01 8.04673076e-01 -1.39536992e-01 6.81262240e-02
5.11380374e-01 1.30023256e-01 3.00620377e-01 4.67543155e-01
1.15357089e+00 7.87147701e-01 -5.40656783e-03 -1.79733217e-01
-4.40790981e-01 -4.65828665e-02 -1.05637908e+00 7.45030165e-01
-2.14279313e-02 1.08622372e+00 7.56640077e-01 -1.43543512e-01
8.97710860e-01 5.51080346e-01 8.79052728e-02 -7.87015557e-01
4.24537241e-01 -3.75423841e-02 4.93832618e-01 -6.61005199e-01
5.33391237e-01 -4.68981296e-01 5.11554718e-01 4.75331157e-01
-5.66205025e-01 3.00257802e-01 -7.60540292e-02 -2.96086103e-01
7.14707017e-01 -3.60979885e-01 2.57127613e-01 -2.28986725e-01
8.71923506e-01 -4.62102175e-01 4.02848482e-01 4.18700308e-01
-6.96182489e-01 4.84614402e-01 2.14063272e-01 -3.35819781e-01
-5.35417318e-01 -6.95584059e-01 -1.77815139e-01 8.45783472e-01
2.71797895e-01 -1.20744020e-01 -1.14911366e+00 -3.40567410e-01
1.41122267e-01 7.43145823e-01 -6.70654893e-01 -5.09196162e-01
-4.52142805e-01 -3.00067157e-01 7.78293848e-01 1.99534118e-01
5.94220817e-01 -8.63884091e-01 -9.75651562e-01 -1.20154150e-01
-8.66117030e-02 -1.10273254e+00 -9.81255591e-01 -5.07211328e-01
-4.67477441e-01 -1.22372198e+00 -2.42129728e-01 -6.67392015e-01
1.02342618e+00 7.32401252e-01 5.04604936e-01 4.44912642e-01
-5.51052272e-01 6.41915739e-01 -9.44195837e-02 -7.31186450e-01
-7.19412744e-01 -8.80648613e-01 2.46701285e-01 8.52950990e-01
1.05171621e+00 -1.72249943e-01 -4.80280042e-01 7.23242164e-01
-8.20801735e-01 -5.65740108e-01 3.92304212e-01 2.89198875e-01
2.84006670e-02 5.58768213e-01 6.56185821e-02 -6.18792892e-01
6.67394638e-01 5.05451143e-01 -6.22560263e-01 -5.21925390e-02
-3.99213403e-01 -3.46570402e-01 2.73437589e-01 -4.45837617e-01
-1.18488646e+00 2.30106518e-01 1.64912418e-02 -3.66989315e-01
-5.75678170e-01 -5.66321850e-01 -5.34051239e-01 -1.02630925e+00
8.19280446e-01 1.06877394e-01 7.18879282e-01 -2.21441403e-01
-6.88526556e-02 9.13356245e-01 7.79305518e-01 1.41130030e-01
7.25048482e-01 9.67321515e-01 1.06451891e-01 -1.11586177e+00
-8.51822346e-02 -6.11972272e-01 -6.02826774e-01 -5.13562799e-01
7.95035660e-01 -7.65231431e-01 -1.10750639e+00 7.83626020e-01
-9.27300811e-01 1.74155176e-01 -4.66706678e-02 5.31237483e-01
-3.38462263e-01 6.87671125e-01 -1.76732257e-01 -1.24726081e+00
-1.82796810e-02 -7.31101215e-01 7.88221538e-01 1.91668123e-01
-2.62254298e-01 -5.84702909e-01 -3.01670730e-01 3.87412071e-01
4.09086287e-01 1.09685779e-01 3.32573801e-01 -1.47117272e-01
-2.25640699e-01 -7.03023136e-01 -4.76955175e-02 5.61427295e-01
6.81546152e-01 2.23845951e-02 -1.54436409e+00 -3.56785953e-01
5.08025527e-01 2.53621787e-01 6.23864293e-01 3.09098303e-01
8.19854140e-01 -4.59428012e-01 -1.74306482e-01 5.27595341e-01
1.01797616e+00 6.60459638e-01 1.37784064e+00 1.00082189e-01
2.08478302e-01 1.11387396e+00 5.12051523e-01 5.64317368e-02
-5.43038905e-01 7.62619376e-01 1.62881881e-01 -4.11982238e-01
-1.31157011e-01 3.63960378e-02 4.72469509e-01 -4.92401212e-01
-2.24479944e-01 3.80352549e-02 -2.54220307e-01 3.65320981e-01
-1.33122301e+00 -1.30107248e+00 -2.50708193e-01 2.64502382e+00
4.76316720e-01 7.05450028e-02 3.80839914e-01 4.08994734e-01
1.15534270e+00 -1.14097156e-01 -2.43493617e-01 -6.40555978e-01
-1.87090829e-01 1.78799927e-01 8.03522289e-01 8.07739556e-01
-1.15020394e+00 6.12883985e-01 7.06084013e+00 2.61496782e-01
-1.09238482e+00 -7.58944675e-02 4.26530391e-01 -2.93609440e-01
7.59966373e-02 -2.68455386e-01 -8.60390484e-01 3.46161872e-01
9.94158685e-01 -2.70358831e-01 1.88800946e-01 3.22284371e-01
6.40492082e-01 -3.57122898e-01 -8.41063619e-01 1.08022678e+00
4.05741006e-01 -8.02641749e-01 -2.58384883e-01 3.56625825e-01
-7.71727879e-03 -1.00863802e+00 2.95708120e-01 -4.19944435e-01
-4.09471452e-01 -1.20136869e+00 5.49130321e-01 3.20144355e-01
8.10533822e-01 -9.92003143e-01 6.21873498e-01 -4.49892506e-02
-1.00370586e+00 -4.38079871e-02 -3.83417845e-01 -5.68157375e-01
1.30439699e-01 -1.99837908e-01 -7.68486977e-01 -6.02947660e-02
5.90000451e-01 1.02833480e-01 -4.97647166e-01 9.04059052e-01
-1.59739494e-01 1.48424134e-01 -1.48009703e-01 2.68807054e-01
-1.97218031e-01 -1.24385990e-01 5.64089119e-01 1.16543961e+00
-6.30416274e-02 4.98763174e-01 -5.45300543e-01 7.24072218e-01
2.61007071e-01 -2.79625822e-02 -8.76977026e-01 6.68938532e-02
2.82738835e-01 9.56277788e-01 -4.92745996e-01 3.98310535e-02
-6.74346924e-01 1.09754646e+00 -6.51082158e-01 3.12142164e-01
-5.87383807e-01 -5.83672762e-01 1.42059791e+00 5.27532518e-01
2.57312834e-01 -3.43766659e-02 -2.63120830e-01 -4.04359937e-01
2.08705842e-01 -1.07776511e+00 3.48272741e-01 -6.46529198e-01
-6.79421663e-01 5.27016580e-01 -9.03158411e-02 -1.26136935e+00
-3.10045071e-02 -6.24696791e-01 -4.06805128e-01 1.37997842e+00
-1.19837666e+00 -7.94871092e-01 -2.17449382e-01 8.68702829e-01
9.10670310e-02 -1.07480057e-01 6.60795927e-01 2.21228704e-01
-3.34345788e-01 9.56721246e-01 -3.29307437e-01 2.82990247e-01
7.82069623e-01 -5.82604945e-01 3.23915899e-01 1.22892773e+00
8.80575702e-02 7.49973416e-01 8.29542160e-01 -5.65961301e-01
-1.13824248e+00 -6.72192454e-01 1.07574618e+00 -5.04245996e-01
-5.53008541e-02 -3.82444471e-01 -9.74960566e-01 3.80601317e-01
2.95397609e-01 -2.45510489e-01 9.03766036e-01 -4.66663122e-01
-3.26125354e-01 -1.82926908e-01 -1.61681473e+00 6.21217012e-01
8.36382329e-01 -9.82331812e-01 -5.14753282e-01 -1.99672490e-01
1.80931091e-01 -1.16003968e-01 -3.82933825e-01 3.34808081e-01
1.01907110e+00 -1.24080777e+00 1.07145476e+00 -6.20845020e-01
-5.21929741e-01 -6.14708304e-01 6.30059987e-02 -6.24195695e-01
-4.82019663e-01 -1.09729218e+00 5.80065131e-01 1.05114961e+00
1.69451967e-01 -8.94611239e-01 7.09971011e-01 1.12871039e+00
3.43663782e-01 4.62188601e-01 -8.28624845e-01 -8.84453833e-01
-5.22598803e-01 2.34295372e-02 3.45632643e-01 4.74316388e-01
-6.72907308e-02 -1.23863913e-01 -5.02887726e-01 5.69378912e-01
6.15841389e-01 -3.60464841e-01 8.86991084e-01 -8.20657969e-01
5.71769364e-02 -3.13188910e-01 -1.03694808e+00 -2.60236204e-01
1.28095612e-01 7.50357360e-02 -8.86456817e-02 -6.77680850e-01
-3.15869063e-01 4.80024904e-01 -1.59174800e-01 3.18743259e-01
-3.39320898e-01 5.74163556e-01 2.43108436e-01 -1.54903099e-01
3.62219870e-01 -7.12615997e-02 8.22273195e-01 5.86541444e-02
-1.91024944e-01 2.50341713e-01 -8.79434943e-01 5.71969271e-01
7.78605402e-01 -4.07357723e-01 -4.68247503e-01 -7.22450064e-03
-3.84641588e-01 -3.35496277e-01 6.52954936e-01 -1.11894929e+00
4.42519754e-01 3.85777764e-02 5.61175048e-01 -1.95800647e-01
5.76456308e-01 -1.17439795e+00 4.61562812e-01 6.55712128e-01
-7.47084767e-02 3.58639695e-02 9.30613160e-01 3.09254915e-01
-2.55630374e-01 -2.66380906e-01 1.23441923e+00 -1.11756809e-01
-1.04198706e+00 -1.05143987e-01 -8.21349621e-01 -4.79703069e-01
1.22203422e+00 -8.27769995e-01 -3.30694556e-01 -5.87988138e-01
-6.83768034e-01 -4.85533923e-01 9.37125623e-01 3.83317024e-01
7.52581358e-01 -9.43163812e-01 -8.10007989e-01 9.28673685e-01
-9.88685191e-02 -1.05333829e+00 3.67211550e-01 7.12663651e-01
-6.43229902e-01 3.01697224e-01 -6.49190187e-01 -2.78977185e-01
-2.37723947e+00 1.04846787e+00 7.09707856e-01 8.75395060e-01
-4.22621787e-01 9.22642469e-01 3.95351857e-01 4.97470260e-01
3.95681977e-01 1.07569106e-01 -2.48714104e-01 -1.40225112e-01
1.42459154e+00 5.78400850e-01 1.20720565e-01 -1.09634638e+00
-4.97135609e-01 6.78922892e-01 -1.04821771e-01 -1.89659908e-01
4.18245524e-01 -3.89932424e-01 -1.12865187e-01 -6.60104826e-02
1.20454943e+00 5.23715198e-01 -1.14883757e+00 1.49740875e-01
-2.53234416e-01 -1.39233100e+00 2.20823988e-01 -5.28408706e-01
-1.00123608e+00 7.20489860e-01 1.00804448e+00 2.34534204e-01
1.61506689e+00 -5.56319058e-01 2.62782931e-01 -1.27737477e-01
2.89882511e-01 -7.89931178e-01 -6.01446569e-01 -3.77444863e-01
6.58322692e-01 -1.00281405e+00 -4.54850607e-02 -8.06616127e-01
-4.40745324e-01 1.01525486e+00 4.79039788e-01 3.84186178e-01
4.51311678e-01 3.87007028e-01 5.47576666e-01 -6.27380237e-02
-5.13462901e-01 -4.26575661e-01 3.51770103e-01 1.05462873e+00
1.87550664e-01 -1.62397563e-01 -3.70213181e-01 -1.21016391e-01
-7.18649328e-02 1.10256441e-01 4.78905022e-01 1.02222502e+00
-4.49203044e-01 -1.10047901e+00 -1.03424990e+00 1.82967082e-01
-6.18851542e-01 1.53334633e-01 -1.06452358e+00 8.50576103e-01
4.29764330e-01 1.40171540e+00 2.15142787e-01 -3.95973623e-01
6.08469605e-01 1.24097206e-01 6.07483625e-01 -1.78124383e-01
-6.97088540e-01 4.85537946e-02 3.03641587e-01 -7.87035108e-01
-5.41981936e-01 -9.15572464e-01 -4.94104207e-01 -6.96031332e-01
-1.35807991e-01 1.35473579e-01 4.24623013e-01 5.13813913e-01
4.16469067e-01 8.53033736e-03 5.63464940e-01 -3.91154200e-01
-3.40726703e-01 -6.67751372e-01 -1.09146106e+00 3.14234316e-01
7.61545539e-01 -4.60243791e-01 -6.21026993e-01 3.21063399e-01] | [13.042136192321777, 1.046260952949524] |
40180553-e186-4416-a5e5-2268e8264fa4 | single-image-reflection-suppression | null | null | http://openaccess.thecvf.com/content_cvpr_2017/html/Arvanitopoulos_Single_Image_Reflection_CVPR_2017_paper.html | http://openaccess.thecvf.com/content_cvpr_2017/papers/Arvanitopoulos_Single_Image_Reflection_CVPR_2017_paper.pdf | Single Image Reflection Suppression | Reflections are a common artifact in images taken through glass windows. Automatically removing the reflection artifacts after the picture is taken is an ill-posed problem. Attempts to solve this problem using optimization schemes therefore rely on various prior assumptions from the physical world. Instead of removing reflections from a single image, which has met with limited success so far, we propose a novel approach to suppress reflections. It is based on a Laplacian data fidelity term and an l-zero gradient sparsity term imposed on the output. With experiments on artificial and real-world images we show that our reflection suppression method performs better than the state-of-the-art reflection removal techniques.
| ['Sabine Susstrunk', 'Radhakrishna Achanta', 'Nikolaos Arvanitopoulos'] | 2017-07-01 | null | null | null | cvpr-2017-7 | ['reflection-removal'] | ['computer-vision'] | [ 8.92651320e-01 -1.05883837e-01 6.33020461e-01 -2.70413041e-01
-7.09210694e-01 5.86812152e-03 4.65444535e-01 -4.05282348e-01
-4.66966718e-01 5.93866289e-01 2.40084350e-01 -9.18961614e-02
5.75340800e-02 -4.40729052e-01 -5.00924587e-01 -9.08045053e-01
2.37345561e-01 -4.24752682e-01 2.43404865e-01 7.48674348e-02
6.02967858e-01 3.22642177e-01 -1.28778434e+00 3.35428804e-01
7.51404822e-01 6.30625784e-01 1.09793956e-03 5.28777480e-01
2.41759360e-01 5.54017127e-01 -4.84765857e-01 -5.68107963e-02
5.87865770e-01 -7.04165399e-01 -3.49758446e-01 4.60045993e-01
7.63816476e-01 -2.16649294e-01 -3.66918236e-01 1.16596258e+00
4.55167979e-01 2.35419109e-01 4.97704715e-01 -6.93840325e-01
-5.94773054e-01 2.03705616e-02 -8.25811207e-01 6.60229847e-02
5.79213202e-01 -4.86767478e-03 5.35450280e-01 -1.21487141e+00
5.54248869e-01 9.23214018e-01 9.79035020e-01 4.17637765e-01
-1.47611260e+00 -3.40984195e-01 -4.89965789e-02 -3.84690017e-02
-1.41774094e+00 -7.80846596e-01 1.03261399e+00 -1.57347932e-01
8.86786342e-01 4.75603998e-01 4.11817133e-01 7.56664693e-01
3.16616416e-01 4.34159219e-01 1.35534441e+00 -7.83569455e-01
-8.64491984e-02 2.69154578e-01 1.38348326e-01 7.17512429e-01
4.60803270e-01 -9.63154249e-03 -6.75220132e-01 -1.81806684e-01
8.03452134e-01 2.48474497e-02 -7.91853368e-01 -1.56550661e-01
-9.39178944e-01 4.73029107e-01 2.12322503e-01 3.10121089e-01
-4.07201588e-01 1.08710460e-01 -2.70062774e-01 3.38083893e-01
6.71198785e-01 4.01877135e-01 1.19668081e-01 3.57877880e-01
-1.01519990e+00 5.78483157e-02 8.65542471e-01 6.34695351e-01
7.39494085e-01 5.66396713e-02 1.07158616e-01 9.00783837e-01
5.30561268e-01 6.36637986e-01 7.43820518e-02 -7.12113976e-01
3.02643538e-01 4.54819709e-01 3.18788201e-01 -1.03050137e+00
-3.60350013e-01 -1.60418525e-01 -8.68491173e-01 7.32247591e-01
4.59976494e-01 -2.29400247e-01 -1.17951715e+00 1.25449193e+00
2.14977145e-01 4.64072764e-01 4.74556955e-03 1.06022060e+00
6.61018252e-01 6.53628886e-01 -6.58041477e-01 -4.13396239e-01
8.99487376e-01 -6.97430432e-01 -9.87344921e-01 -1.34004921e-01
-8.37167725e-02 -1.37459266e+00 8.13411415e-01 9.41969275e-01
-1.24083638e+00 -3.55231524e-01 -1.26396561e+00 -1.44573227e-01
2.17567217e-02 7.73696825e-02 2.38452926e-01 9.82871771e-01
-8.34865391e-01 4.72240776e-01 -7.16307402e-01 -1.61014661e-01
1.23794645e-01 2.28243515e-01 -3.87253731e-01 -2.74461359e-01
-5.46909571e-01 1.02197385e+00 -4.46195155e-01 4.92412031e-01
-4.81696069e-01 -4.80940729e-01 -6.69838250e-01 -2.64944762e-01
4.65981692e-01 -5.14565349e-01 7.06241012e-01 -9.62951958e-01
-1.90900767e+00 8.71189654e-01 -4.61630404e-01 -9.11455303e-02
4.54496354e-01 -6.41828179e-01 -4.27329957e-01 1.20617203e-01
-4.92334276e-01 -2.98609734e-01 1.47591746e+00 -1.66662812e+00
-1.14576124e-01 -1.94927275e-01 -3.01201969e-01 1.61111400e-01
-1.33812398e-01 1.67943779e-02 -4.51693445e-01 -5.68885744e-01
6.39541805e-01 -1.08187354e+00 -4.21956927e-01 1.18454015e-02
-4.21753585e-01 5.88226914e-01 9.00610268e-01 -8.12745929e-01
9.57741022e-01 -2.21161842e+00 -4.65506762e-02 5.59450448e-01
2.06734315e-01 4.85078096e-01 -1.51243150e-01 5.97599328e-01
-1.21791564e-01 -2.36628383e-01 -4.82152700e-01 -5.98111093e-01
-3.09582978e-01 -1.19503312e-01 -2.71964192e-01 1.06763804e+00
9.43274572e-02 2.14091375e-01 -5.62119842e-01 -6.45422116e-02
5.50768197e-01 1.12881947e+00 -4.99781102e-01 2.35271201e-01
3.07475328e-01 6.21620655e-01 -2.33206853e-01 2.53206491e-01
1.07285690e+00 -5.09444624e-02 -2.73667332e-02 -2.65490949e-01
-4.47006166e-01 2.49009818e-01 -1.64774609e+00 1.51443839e+00
-5.00419021e-01 7.29730546e-01 3.66566300e-01 -8.31980407e-01
9.16243553e-01 4.32098150e-01 5.29633522e-01 -7.78863490e-01
-8.49661529e-02 2.35864148e-01 -9.98769701e-02 -7.43947625e-01
4.23967957e-01 -4.98125523e-01 4.84224588e-01 4.13519293e-01
-3.06319028e-01 -2.36665964e-01 -5.32919820e-03 -1.34266064e-01
1.27070105e+00 3.09622496e-01 1.62577227e-01 -3.74606341e-01
7.64403164e-01 -2.95895904e-01 5.10519326e-01 7.61748731e-01
1.62812859e-01 1.28832090e+00 -8.88800696e-02 -3.97018224e-01
-8.98630202e-01 -1.02829587e+00 -1.65805429e-01 4.05175447e-01
2.69353300e-01 -2.80899942e-01 -7.88198292e-01 -2.58217305e-01
-3.06601018e-01 5.38109303e-01 -3.76034319e-01 1.71095934e-02
-8.43100190e-01 -9.96113718e-01 7.18596131e-02 -6.19834885e-02
6.71480238e-01 -8.97182286e-01 -8.72410834e-01 2.39337400e-01
-3.13252151e-01 -1.32289445e+00 -4.13244694e-01 -2.35284362e-02
-8.09220374e-01 -1.14780128e+00 -8.83733690e-01 -5.29688656e-01
1.04769754e+00 7.15804160e-01 1.14883292e+00 2.62176394e-01
-7.53535092e-01 5.98283648e-01 -2.25781605e-01 -4.29975837e-01
-1.83159336e-01 -6.05791509e-01 -2.62629420e-01 5.41298747e-01
2.12209091e-01 -5.88816583e-01 -7.54491389e-01 2.51327693e-01
-1.00051427e+00 4.79241610e-02 5.92516184e-01 6.33780122e-01
3.70983154e-01 1.10074967e-01 -5.53769469e-02 -1.01819932e+00
6.54761612e-01 1.29920468e-01 -6.65603220e-01 -8.90942197e-03
-4.12568182e-01 7.88362324e-02 5.72521091e-01 -2.66629279e-01
-1.42544115e+00 3.09532702e-01 -4.31459658e-02 -2.69440055e-01
-1.50071517e-01 1.45836219e-01 3.55157033e-02 -5.55771828e-01
7.14655042e-01 1.12330586e-01 -1.37113303e-01 -6.48913920e-01
3.91627885e-02 3.55357528e-01 4.32857662e-01 -6.29091710e-02
9.30569649e-01 9.35149372e-01 2.87661165e-01 -1.72797596e+00
-8.45368922e-01 -8.02748799e-01 -5.40856421e-01 -2.60217607e-01
7.29868352e-01 -5.51276684e-01 -6.12605989e-01 6.39141977e-01
-1.06239414e+00 -2.67817557e-01 -1.25198931e-01 6.12590730e-01
-4.03045088e-01 6.03377819e-01 -3.96425486e-01 -1.05597675e+00
-1.98719010e-01 -8.90493095e-01 7.84413278e-01 1.36383548e-01
8.97948369e-02 -8.60722423e-01 3.94557238e-01 2.21505791e-01
6.62242353e-01 5.73267862e-02 2.85225511e-01 2.73990452e-01
-8.25601161e-01 -1.98573247e-01 -3.28919739e-01 6.51713073e-01
3.71397376e-01 -1.52364103e-02 -1.27142704e+00 -3.29046935e-01
7.84075558e-01 1.46664307e-01 1.21428490e+00 4.90176082e-01
8.26004148e-01 -4.67257202e-03 -1.49336487e-01 7.09382296e-01
1.85530102e+00 -7.43898898e-02 1.16112864e+00 7.77065307e-02
6.00732744e-01 4.74361569e-01 3.72480839e-01 3.66593808e-01
-2.14127228e-01 6.28948987e-01 4.54767317e-01 -6.33297145e-01
-4.57931042e-01 2.56325752e-01 2.96086043e-01 6.36416256e-01
-4.97901797e-01 -4.08411831e-01 -5.61285138e-01 3.54361385e-01
-1.73885953e+00 -1.04387712e+00 -6.18734479e-01 2.66504598e+00
4.60888863e-01 9.56780538e-02 -3.13048214e-01 4.02969986e-01
3.37391615e-01 2.66076297e-01 -1.57363623e-01 -3.32528263e-01
-1.22432165e-01 3.41603726e-01 6.82944238e-01 9.68554616e-01
-1.05126154e+00 4.75453496e-01 7.37890053e+00 6.54202551e-02
-1.20186901e+00 -6.37746751e-02 1.54072139e-02 3.72195765e-02
-2.90222317e-01 2.52897069e-02 -6.04198754e-01 1.65641025e-01
4.65674251e-01 4.63061512e-01 5.17497003e-01 5.77469468e-02
4.77902681e-01 -4.91741151e-01 -8.39029253e-01 1.19983137e+00
5.15270293e-01 -7.40681112e-01 -3.58562976e-01 1.18940594e-02
7.79439509e-01 -1.80844709e-01 1.65457770e-01 -4.79751796e-01
3.36380973e-02 -1.10196400e+00 2.51316369e-01 9.17312384e-01
3.86269867e-01 -4.82270241e-01 4.28959489e-01 5.24537526e-02
-8.08713973e-01 2.87379891e-01 -4.49018508e-01 -1.27298266e-01
3.03193510e-01 1.17959785e+00 -5.22723258e-01 4.64893192e-01
6.32118702e-01 6.08639836e-01 -1.21471249e-01 1.34427774e+00
-5.59668601e-01 6.56936169e-01 -6.00469708e-01 4.66999203e-01
9.74224135e-02 -7.01223850e-01 8.61291766e-01 1.45412719e+00
3.25192243e-01 4.39594626e-01 4.40697111e-02 7.23894298e-01
1.63722873e-01 -8.07726756e-02 -7.67576694e-01 5.01927912e-01
-4.30467516e-01 1.22928441e+00 -5.47187328e-01 -8.92528594e-02
-9.30440485e-01 1.28062534e+00 -9.00015607e-02 8.07175100e-01
-4.65713114e-01 -4.06176805e-01 6.22325957e-01 3.17937464e-01
2.95561880e-01 -4.93176341e-01 -3.68563116e-01 -1.32937086e+00
3.97458881e-01 -8.29915941e-01 6.48251623e-02 -7.46138453e-01
-1.11927927e+00 4.52806979e-01 -3.03391725e-01 -1.40559328e+00
3.28660905e-01 -6.24743640e-01 -6.62865520e-01 1.09539628e+00
-1.84872961e+00 -7.40595400e-01 -5.83076239e-01 7.77118444e-01
3.35088283e-01 2.80485421e-01 7.85348237e-01 4.30281341e-01
-3.29779536e-01 9.26652625e-02 3.01203609e-01 -1.83539882e-01
8.87046337e-01 -1.08276105e+00 1.67916700e-01 1.29220390e+00
3.44245732e-01 7.48915076e-01 1.31608701e+00 -3.47143203e-01
-1.56048131e+00 -4.66471970e-01 8.05719435e-01 -1.80493132e-03
2.29377300e-01 -2.12878987e-01 -1.22820878e+00 6.74105585e-01
6.15679085e-01 5.17336093e-02 6.66276336e-01 -4.81465347e-02
-1.98400795e-01 -5.37927523e-02 -1.02273738e+00 5.72994828e-01
8.61792684e-01 -3.63475084e-01 -5.31261265e-01 2.68482327e-01
-1.39537364e-01 -3.85265291e-01 -4.19310868e-01 2.75843650e-01
5.58229506e-01 -1.27930641e+00 1.15435684e+00 -3.30408439e-02
2.23541990e-01 -4.06113327e-01 -6.91226800e-04 -1.31313527e+00
-2.12153837e-01 -1.02307904e+00 3.61798078e-01 8.08479071e-01
3.20527077e-01 -8.39519799e-01 7.33442843e-01 7.48693287e-01
-1.36388227e-01 -1.34075746e-01 -6.46312296e-01 -5.82159758e-01
-4.47135091e-01 -2.48959139e-01 -1.53364122e-01 7.35148311e-01
-1.51243448e-01 3.08650196e-01 -8.71533751e-01 3.95057529e-01
1.22062671e+00 2.67458171e-01 9.44799125e-01 -1.04996634e+00
-1.75142527e-01 -1.07266605e-01 -1.56611040e-01 -1.07750165e+00
-2.44912863e-01 -3.49714935e-01 5.05999446e-01 -1.61558461e+00
1.26896473e-02 -3.33309561e-01 -3.74308467e-01 2.17209741e-01
-2.24655822e-01 7.27297962e-01 4.85663190e-02 -3.86904404e-02
-2.54087985e-01 4.46384221e-01 1.19616961e+00 1.59548163e-01
-5.06772995e-01 8.76388773e-02 -3.47650766e-01 1.22465956e+00
6.01588607e-01 -6.45290673e-01 -2.64316887e-01 -4.70690578e-01
2.95794845e-01 -1.79805055e-01 5.14373422e-01 -1.08666122e+00
1.88055113e-01 1.76588241e-02 2.12921813e-01 -4.44012731e-01
7.67582476e-01 -1.04693580e+00 3.08894694e-01 3.23020935e-01
-9.57976207e-02 -3.54290187e-01 2.12293435e-02 4.78462756e-01
-1.59355223e-01 -4.20675695e-01 1.06434023e+00 -3.58238220e-01
-3.19718510e-01 -1.62023157e-01 -5.29284775e-01 -1.23301432e-01
5.27852714e-01 -2.92893052e-01 -2.26238340e-01 -3.35774630e-01
-7.99909413e-01 -3.36261272e-01 5.56962609e-01 7.26348013e-02
1.03520715e+00 -7.75685847e-01 -9.61297572e-01 5.71452558e-01
-2.37863749e-01 -2.73847669e-01 1.25846371e-01 1.02728581e+00
-5.90339184e-01 -3.53356227e-02 -3.84659842e-02 -4.37585622e-01
-1.74005854e+00 3.34154159e-01 3.65272373e-01 -1.63726866e-01
-1.23091340e+00 6.39153421e-01 2.51226813e-01 9.53145698e-02
8.79836455e-02 -2.50245094e-01 -9.33560729e-02 -4.18249577e-01
7.31378436e-01 5.22636890e-01 2.56883830e-01 -5.75312853e-01
-1.80524036e-01 9.96529460e-01 1.13914907e-01 -3.75433564e-01
1.51155233e+00 -3.32024306e-01 -9.98726040e-02 4.65117753e-01
1.03047180e+00 5.90090752e-01 -1.14564550e+00 -3.66606623e-01
-2.54952759e-01 -1.10417962e+00 2.10239142e-01 -5.37828267e-01
-1.12073910e+00 8.14178944e-01 4.37575549e-01 4.33792353e-01
1.33311903e+00 -6.68905199e-01 6.78012550e-01 3.48277777e-01
1.84616640e-01 -1.04379320e+00 2.61140168e-01 1.52987733e-01
1.10184097e+00 -1.34057963e+00 6.20840251e-01 -8.93675148e-01
-2.54086047e-01 1.06926942e+00 -6.07043691e-03 -5.93055904e-01
9.23411429e-01 4.52718884e-01 4.98434871e-01 -1.57298416e-01
-3.52995783e-01 -2.01865256e-01 4.36709195e-01 3.80595982e-01
5.77977479e-01 -4.38899040e-01 -4.96628463e-01 -2.67103046e-01
3.47374201e-01 5.99189959e-02 8.30954015e-01 1.07937598e+00
-4.27106351e-01 -1.14683795e+00 -8.55154574e-01 1.66395336e-01
-9.05661762e-01 -1.89788848e-01 -3.21548969e-01 5.20738602e-01
-2.39003688e-01 1.20175350e+00 -4.37080324e-01 1.69216752e-01
4.98794496e-01 -1.17383428e-01 7.12812722e-01 -5.24575889e-01
-5.80739379e-01 5.14509439e-01 7.50712156e-02 -7.88050115e-01
-9.95551229e-01 -6.17830813e-01 -9.75769758e-01 2.72141420e-03
-5.17091811e-01 -2.42184237e-01 7.13200867e-01 6.92173421e-01
7.18474835e-02 5.34084141e-01 5.76049864e-01 -1.09879148e+00
-3.00385743e-01 -7.84217894e-01 -7.84061372e-01 7.39714205e-01
6.82517052e-01 -4.09179688e-01 -7.52373099e-01 3.36981714e-01] | [10.576534271240234, -2.753453493118286] |
98b34394-f497-4d76-a0e0-3a2d86aaeb91 | a-temporal-knowledge-graph-completion-method | 2108.13024 | null | https://arxiv.org/abs/2108.13024v2 | https://arxiv.org/pdf/2108.13024v2.pdf | A Temporal Knowledge Graph Completion Method Based on Balanced Timestamp Distribution | Completion through the embedding representation of the knowledge graph (KGE) has been a research hotspot in recent years. Realistic knowledge graphs are mostly related to time, while most of the existing KGE algorithms ignore the time information. A few existing methods directly or indirectly encode the time information, ignoring the balance of timestamp distribution, which greatly limits the performance of temporal knowledge graph completion (KGC). In this paper, a temporal KGC method is proposed based on the direct encoding time information framework, and a given time slice is treated as the finest granularity for balanced timestamp distribution. A large number of experiments on temporal knowledge graph datasets extracted from the real world demonstrate the effectiveness of our method. | ['Yuhong Zhang', 'Kangzheng Liu'] | 2021-08-30 | null | null | null | null | ['temporal-knowledge-graph-completion'] | ['knowledge-base'] | [-4.11334008e-01 -2.20281139e-01 -6.95382357e-01 -1.25763029e-01
2.01699004e-01 -4.94154245e-01 4.64990944e-01 4.95714068e-01
-3.84893864e-01 5.47195673e-01 2.89707780e-01 -1.68870687e-01
-6.82533324e-01 -1.34241164e+00 -3.60683322e-01 -5.19141138e-01
-4.78373677e-01 1.65624157e-01 7.08156288e-01 -1.37042567e-01
9.09589231e-02 1.78263590e-01 -9.62304056e-01 -1.20661616e-01
6.03177547e-01 1.01358473e+00 -2.05295846e-01 1.48916647e-01
-3.06218058e-01 8.68549466e-01 -6.76583230e-01 -3.69833857e-01
1.76741213e-01 -1.56467885e-01 -5.58329999e-01 -4.45195049e-01
-2.62856454e-01 -3.74900430e-01 -1.19396150e+00 8.49928617e-01
2.27513343e-01 1.68008655e-01 2.39712954e-01 -1.82038045e+00
-7.44169772e-01 9.58153307e-01 -5.19564748e-01 3.38131517e-01
1.21047527e-01 -1.17318511e-01 7.82874107e-01 -1.75509825e-01
7.15242684e-01 1.07128310e+00 7.26860404e-01 3.86459343e-02
-7.47169375e-01 -7.86675930e-01 3.33172381e-01 9.25129235e-01
-1.75955904e+00 1.04480386e-01 1.11293375e+00 -2.11271778e-01
8.96798074e-01 -6.25295267e-02 1.00207937e+00 6.90240264e-01
1.94364473e-01 4.83355701e-01 8.83535564e-01 -2.39402547e-01
1.99377909e-01 -1.86408028e-01 3.43956143e-01 4.50211734e-01
5.79636216e-01 2.77029961e-01 -6.74920440e-01 -3.17355961e-01
7.62184441e-01 1.76937506e-01 -4.47136223e-01 -2.87203819e-01
-1.41579199e+00 6.04930580e-01 3.75668794e-01 2.72476077e-01
-1.72227979e-01 5.28228939e-01 9.09032524e-01 4.55807000e-01
3.92413884e-01 -2.79625684e-01 -2.57565349e-01 -3.31490248e-01
-8.78903806e-01 1.37089193e-01 8.32134366e-01 1.17775881e+00
5.81683218e-01 8.20464045e-02 -1.03452034e-01 8.23675543e-02
3.17950875e-01 2.90044487e-01 3.28168273e-01 -6.06048346e-01
5.48995316e-01 8.05578530e-01 1.44298449e-01 -1.66494620e+00
-1.36595920e-01 -2.81217426e-01 -6.26223326e-01 -4.72613364e-01
2.33529747e-01 1.15175575e-01 -5.70035338e-01 1.73724973e+00
5.52701771e-01 8.25100660e-01 1.00896619e-01 7.04497755e-01
5.15165389e-01 8.79595399e-01 -1.18058316e-01 -5.65519214e-01
1.13920867e+00 -4.81639415e-01 -1.07988322e+00 2.89219618e-01
5.66705883e-01 -3.09950203e-01 4.44858789e-01 1.69042826e-01
-4.63239074e-01 -9.04084444e-02 -1.16791093e+00 4.53852043e-02
-6.66172802e-01 -3.76402855e-01 9.21119928e-01 6.36833966e-01
-8.84242237e-01 5.32174766e-01 -1.02161193e+00 -3.22191119e-01
-5.68621717e-02 5.71833886e-02 -2.93722272e-01 -2.51222610e-01
-1.79591978e+00 6.12563312e-01 1.13262188e+00 1.92807183e-01
-5.81747770e-01 -6.22441530e-01 -7.58619785e-01 9.16134939e-02
7.26714373e-01 -2.17185095e-01 7.73633122e-01 -1.74334750e-01
-1.13670456e+00 2.16794625e-01 1.01185024e-01 -5.93660176e-01
4.54362541e-01 7.13316873e-02 -1.06679523e+00 2.85842359e-01
-1.40977040e-01 -4.59736697e-02 5.12593210e-01 -8.75751257e-01
-3.77890110e-01 -3.11543524e-01 2.70492554e-01 -2.18800738e-01
-6.72153234e-01 -2.47547120e-01 -7.86945343e-01 -7.11288869e-01
7.44309425e-02 -5.68788767e-01 -5.49344942e-02 -2.44144410e-01
-1.56175330e-01 -3.65319610e-01 1.31276309e+00 -7.90388048e-01
2.07270026e+00 -2.30905795e+00 1.43379778e-01 4.07147974e-01
2.67812490e-01 -4.10740031e-03 1.17237620e-01 1.05954814e+00
3.69206853e-02 -5.70128299e-02 6.30296692e-02 2.31261283e-01
2.46438920e-01 5.20414889e-01 -5.87537348e-01 6.14354789e-01
-4.88065273e-01 9.83050346e-01 -1.30370188e+00 -8.57440829e-01
1.69158354e-01 3.96610111e-01 -1.31002158e-01 -1.77888975e-01
-3.80380452e-01 -1.56422406e-01 -7.07295239e-01 6.09098554e-01
6.50482655e-01 -3.75239104e-01 6.09431922e-01 -5.56182861e-01
-9.31985080e-02 -4.53773215e-02 -1.29890335e+00 1.72876108e+00
-2.14263797e-01 2.39218220e-01 -4.44388062e-01 -7.77670264e-01
8.35003555e-01 4.70220506e-01 7.40154266e-01 -7.80512512e-01
1.22218803e-01 3.10944766e-02 -2.89635748e-01 -3.03577632e-01
6.82473958e-01 2.07449764e-01 -1.71903819e-01 6.43294394e-01
-2.40726009e-01 3.13436776e-01 2.93469697e-01 5.97108006e-01
1.19626069e+00 3.46597210e-02 3.80437523e-01 2.55347565e-02
1.04950853e-01 8.29472169e-02 9.98704970e-01 1.92791432e-01
-5.24735272e-01 -2.49339920e-02 7.18796968e-01 -4.78214055e-01
-8.14605176e-01 -8.77789974e-01 2.77372718e-01 4.62159723e-01
5.76745808e-01 -1.22157288e+00 -2.62070715e-01 -7.99030185e-01
3.78184736e-01 5.72753370e-01 -6.42349780e-01 -5.33894777e-01
-5.31365037e-01 -4.01794106e-01 7.36267626e-01 7.72230089e-01
5.72472095e-01 -6.11957014e-01 -4.57940191e-01 5.02374291e-01
-3.91735137e-01 -1.20135736e+00 -6.30864799e-01 -4.05506998e-01
-9.05806839e-01 -1.24632788e+00 -2.31128961e-01 -4.75985765e-01
4.03736800e-01 6.02509081e-01 6.59166515e-01 4.50985692e-02
-1.05745673e-01 6.09199762e-01 -6.47307336e-01 -1.81180403e-01
2.31349289e-01 -2.00259909e-01 1.09208480e-01 1.00937352e-01
4.41579729e-01 -8.58606040e-01 -7.60447621e-01 2.45211795e-01
-1.11113262e+00 2.19643060e-02 1.97612107e-01 6.04086399e-01
6.50702059e-01 7.99953222e-01 6.36451423e-01 -6.63317680e-01
6.15907371e-01 -7.24252164e-01 -8.71932685e-01 5.12767911e-01
-1.04920089e+00 -1.93291903e-02 6.43585324e-01 -6.81894779e-01
-7.46813834e-01 -4.60189760e-01 6.04982674e-01 -7.92821229e-01
6.13083482e-01 1.03756225e+00 -3.21683109e-01 -2.21696328e-02
9.87551287e-02 5.39135218e-01 -3.06891263e-01 -2.15536356e-01
5.41725695e-01 3.55124831e-01 5.13443708e-01 -8.67045462e-01
7.29076684e-01 7.18130350e-01 9.77639630e-02 -3.10615212e-01
-3.58186722e-01 -4.57929015e-01 -3.58396679e-01 -3.30426514e-01
3.92109841e-01 -6.74075425e-01 -8.58316958e-01 2.54061669e-01
-1.15068769e+00 -1.58348128e-01 -1.98868454e-01 8.26015174e-01
-2.33687639e-01 7.37139881e-01 -5.68823457e-01 -6.76793993e-01
-2.10565075e-01 -5.72336078e-01 6.12190306e-01 1.09993741e-01
1.31427869e-01 -1.12121630e+00 2.48332262e-01 -1.21225111e-01
3.39597851e-01 6.90227389e-01 1.03043962e+00 -3.13722074e-01
-9.21038628e-01 -3.72224331e-01 -3.73486847e-01 -1.11009747e-01
2.26497456e-01 1.09173991e-01 -4.08944279e-01 -3.52563262e-01
-2.68676937e-01 1.22765988e-01 6.29775703e-01 -1.00831263e-01
1.17489314e+00 -4.25614208e-01 -5.71686149e-01 5.57029903e-01
1.82130909e+00 3.49553913e-01 7.57385373e-01 3.46380711e-01
6.46169960e-01 2.49051884e-01 8.98842275e-01 7.82122314e-01
7.77527511e-01 5.44720888e-01 4.08564985e-01 6.96972251e-01
-7.23157302e-02 -6.65650964e-01 2.42303908e-01 1.28469276e+00
-2.17522830e-01 -3.40697676e-01 -8.77326846e-01 1.07685804e+00
-2.24756527e+00 -1.16590357e+00 7.55536545e-04 2.23472381e+00
9.60280061e-01 1.40535325e-01 -1.24467656e-01 3.62148136e-01
8.47906411e-01 5.33533454e-01 -4.51582879e-01 3.05185327e-03
7.66754150e-02 -1.25851214e-01 8.34062874e-01 2.53214419e-01
-6.75888181e-01 6.96183860e-01 6.11067772e+00 1.05426228e+00
-9.43605721e-01 2.18792066e-01 -1.79430827e-01 5.05803600e-02
-5.08221149e-01 6.00588799e-01 -5.61419249e-01 8.26632679e-01
9.41156685e-01 -1.10816956e+00 4.87132818e-01 8.36108208e-01
1.69044465e-01 1.62964612e-01 -8.55779290e-01 1.17013037e+00
-1.08080253e-01 -1.22942114e+00 8.38692710e-02 2.65419614e-02
5.39138615e-01 -3.76425266e-01 -3.22689831e-01 3.84564072e-01
3.45773190e-01 -6.36507392e-01 6.06334984e-01 7.09254026e-01
8.86521518e-01 -9.16413248e-01 5.97856462e-01 5.80458380e-02
-1.97713625e+00 1.19921170e-01 -3.75900716e-01 3.51743810e-02
4.93788362e-01 1.08663070e+00 -5.91940761e-01 1.41214180e+00
6.49601936e-01 1.00455689e+00 -4.15415317e-01 1.05791020e+00
-2.34300390e-01 8.28113437e-01 -5.42357981e-01 -8.67355894e-03
8.89143273e-02 -2.02280417e-01 4.83133048e-01 1.09978569e+00
2.89033532e-01 2.24879235e-01 2.20982969e-01 4.44392413e-01
-1.14147514e-01 -1.01945668e-01 -6.52657390e-01 -4.60980833e-01
9.90831971e-01 9.42597330e-01 -8.36061299e-01 -2.82447875e-01
-6.13461912e-01 7.53879189e-01 1.36244521e-01 5.53450465e-01
-1.27754426e+00 -9.30931330e-01 3.03644389e-01 -1.01779297e-01
3.57749879e-01 -6.85384154e-01 2.37114057e-01 -1.19549501e+00
2.36916900e-01 -3.89824957e-01 9.39462841e-01 -5.03756523e-01
-1.21089220e+00 7.42340386e-02 4.44383144e-01 -1.35054219e+00
1.25306502e-01 -1.69735834e-01 -5.90414405e-01 5.85929334e-01
-1.61882520e+00 -1.09141040e+00 -4.31766421e-01 8.62235785e-01
-2.30939016e-01 2.12394103e-01 4.96008843e-01 5.51344812e-01
-4.57381546e-01 6.34226382e-01 1.22543611e-01 1.90472394e-01
7.02217162e-01 -1.01260185e+00 1.18763559e-01 9.15700853e-01
-9.30498019e-02 9.24171686e-01 5.10233343e-01 -1.09324205e+00
-1.82679784e+00 -1.33923423e+00 8.73036504e-01 3.36647779e-02
1.02083933e+00 -9.50093865e-02 -1.08583868e+00 9.65526581e-01
5.20748124e-02 2.79039741e-01 5.45474768e-01 -1.92404203e-02
-7.78953135e-01 -6.28185034e-01 -9.08009887e-01 4.95664120e-01
1.15295386e+00 -7.35155165e-01 -6.30897880e-01 3.04926246e-01
1.28137779e+00 -2.67284662e-01 -1.29918730e+00 4.93502915e-01
5.60962975e-01 -5.42236984e-01 8.41142118e-01 -4.21360165e-01
-2.67640110e-02 -8.07748735e-01 -1.68753892e-01 -9.68352377e-01
-2.20705882e-01 -5.55180728e-01 -1.02558088e+00 1.34546971e+00
-2.36383110e-01 -8.72432828e-01 6.50561512e-01 1.57095611e-01
2.21484587e-01 -5.92659354e-01 -1.01301169e+00 -1.40033305e+00
-5.62469482e-01 -3.16280484e-01 1.12782443e+00 1.39653337e+00
2.59314239e-01 -1.46463618e-01 -4.53965366e-01 2.93457359e-01
6.90862715e-01 4.92765039e-01 5.63770056e-01 -1.06860769e+00
-2.45404646e-01 -1.74832106e-01 -8.91840160e-01 -6.02587223e-01
-1.06933445e-01 -9.08182800e-01 -5.45740247e-01 -1.79730189e+00
4.48494367e-02 -3.77715021e-01 -6.61892831e-01 5.76189995e-01
2.28012130e-01 -4.31265831e-01 -1.42220557e-01 1.49172947e-01
-7.15120614e-01 8.22463751e-01 1.11400151e+00 -2.65963852e-01
5.00163399e-02 -5.49421251e-01 -3.04458290e-01 1.96904868e-01
6.11956596e-01 -4.58204001e-01 -1.12460649e+00 -4.25914913e-01
5.04075527e-01 3.79627496e-01 2.79842883e-01 -7.65382171e-01
7.06397235e-01 -6.40739024e-01 -1.64031282e-01 -7.69997597e-01
1.89558879e-01 -1.05383718e+00 6.40573204e-01 5.35903931e-01
1.98938444e-01 2.34885931e-01 2.38963261e-01 1.25782084e+00
-4.94243294e-01 1.92596823e-01 1.48053557e-01 1.91699803e-01
-1.24685037e+00 7.63618827e-01 3.76054883e-01 2.82607041e-02
1.33461630e+00 -1.73592538e-01 -6.26248538e-01 -2.26283327e-01
-4.30795908e-01 5.40019095e-01 3.74541909e-01 3.81255716e-01
7.80126452e-01 -1.78579235e+00 -3.02493066e-01 -4.41178143e-01
4.29835320e-01 -5.88965267e-02 3.75844806e-01 8.65717649e-01
-5.22720575e-01 4.90816593e-01 7.47174919e-02 -1.64767176e-01
-8.30928504e-01 1.08708763e+00 -5.30865975e-02 -4.68647450e-01
-9.50244606e-01 1.07876018e-01 -2.02424109e-01 7.06661120e-02
2.18798012e-01 -2.48462573e-01 -7.47663528e-02 1.56669810e-01
5.02816141e-01 6.98118925e-01 -3.34259570e-02 -2.63162017e-01
-5.47109306e-01 5.57508349e-01 -7.74995014e-02 -1.12749048e-01
1.22712874e+00 -6.82345256e-02 -3.57972324e-01 6.04748189e-01
1.05039036e+00 5.99671416e-02 -8.14757526e-01 -5.06391883e-01
-6.79680379e-03 -7.72077262e-01 1.46389855e-02 -4.22465414e-01
-1.19513655e+00 4.88096684e-01 1.58361793e-01 1.92630440e-01
1.20836854e+00 -3.52339774e-01 1.23531103e+00 3.34393144e-01
9.64382291e-01 -1.08450949e+00 -9.97930989e-02 3.67982328e-01
4.54062045e-01 -5.99829197e-01 2.14192629e-01 -5.73833406e-01
-3.38678032e-01 1.05150437e+00 5.60000598e-01 7.22839609e-02
9.50266838e-01 4.49392609e-02 -2.99481094e-01 -2.54363924e-01
-7.96768129e-01 -2.76176445e-02 -2.77761608e-01 5.38857460e-01
-1.56504735e-01 2.32456967e-01 -9.12986577e-01 9.34074163e-01
9.58437622e-02 3.42359841e-01 5.36439240e-01 1.26307416e+00
-5.43161519e-02 -1.22653389e+00 -1.58272237e-01 1.89725086e-01
-8.17880481e-02 1.42075866e-01 -3.94185968e-02 9.92494941e-01
5.35264313e-02 8.54629099e-01 -2.61083871e-01 -7.71852136e-01
2.51193106e-01 -7.01412857e-02 3.80555362e-01 -2.42155135e-01
-1.22534102e-02 -3.99820536e-01 -1.01105548e-01 -6.91904366e-01
-2.28924751e-01 -3.94303292e-01 -1.50985825e+00 -7.53889441e-01
-3.91127974e-01 4.97180730e-01 2.84387469e-01 4.82080013e-01
4.92367893e-01 5.22139549e-01 5.86964548e-01 -2.87687164e-02
-2.80474573e-01 -4.76488054e-01 -9.58258152e-01 3.75118971e-01
-2.31408607e-02 -9.90107715e-01 -2.07794115e-01 3.36472020e-02] | [8.56711196899414, 7.901711940765381] |
8f8101c8-5a74-4557-81ef-c4287f6441a0 | forms-of-anaphoric-reference-to | null | null | https://aclanthology.org/W18-2406 | https://aclanthology.org/W18-2406.pdf | Forms of Anaphoric Reference to Organisational Named Entities: Hoping to widen appeal, they diversified | Proper names of organisations are a special case of collective nouns. Their meaning can be conceptualised as a collective unit or as a plurality of persons, allowing for different morphological marking of coreferent anaphoric pronouns. This paper explores the variability of references to organisation names with 1) a corpus analysis and 2) two crowd-sourced story continuation experiments. The first shows that the preference for singular vs. plural conceptualisation is dependent on the level of formality of a text. In the second, we observe a strong preference for the plural they otherwise typical of informal speech. Using edited corpus data instead of constructed sentences as stimuli reduces this preference. | ["Sharid Lo{\\'a}iciga", 'Luca Bevacqua', 'Christian Hardmeier', 'Hannah Rohde'] | 2018-07-01 | null | null | null | ws-2018-7 | ['story-continuation'] | ['computer-vision'] | [ 2.54079886e-02 3.65695983e-01 -1.38447016e-01 -3.61558944e-01
-4.99742180e-01 -8.70653450e-01 1.30435073e+00 3.91980708e-01
-8.72000635e-01 9.93658185e-01 1.02464795e+00 -1.70229405e-01
-3.93609911e-01 -7.01037824e-01 -2.46074006e-01 -7.14191437e-01
3.46245110e-01 8.35513175e-01 5.00998616e-01 -5.67672729e-01
5.03850520e-01 6.86422110e-01 -1.42973626e+00 2.67649293e-01
2.18304142e-01 3.53788137e-02 2.82790750e-01 1.86549231e-01
-6.49649680e-01 6.63107753e-01 -1.10866117e+00 -5.59723198e-01
-1.36502281e-01 -3.08816105e-01 -1.10834157e+00 2.83717483e-01
3.60165685e-01 1.35293350e-01 -1.71148896e-01 9.05042231e-01
5.94397426e-01 2.69530177e-01 6.06077015e-01 -8.71198714e-01
-6.39059305e-01 9.69815016e-01 -1.81894749e-01 5.59647441e-01
7.55917847e-01 -6.25899211e-02 1.31909883e+00 -5.51806390e-01
1.15473700e+00 1.86373150e+00 3.73246580e-01 5.63421011e-01
-1.43129218e+00 -1.39938295e-01 -3.87990661e-02 -3.43860835e-01
-1.44622290e+00 -7.99334943e-01 4.18314278e-01 -6.06798589e-01
1.16533589e+00 3.24075490e-01 4.47287172e-01 1.22069526e+00
9.72171351e-02 1.81900293e-01 1.12443554e+00 -7.84722388e-01
1.16841063e-01 2.18019158e-01 3.64266366e-01 -1.32067710e-01
6.71142817e-01 -9.81967896e-02 -5.05803108e-01 -5.15772820e-01
6.50241077e-01 -5.43325186e-01 -2.90637195e-01 -3.87092121e-03
-1.50584185e+00 9.48765159e-01 -8.80699083e-02 1.04247868e+00
-3.27356339e-01 8.71423334e-02 6.51861072e-01 2.91348577e-01
-3.04858591e-02 7.10748017e-01 -2.92865574e-01 -2.15644568e-01
-2.43583471e-01 5.73440254e-01 1.10435164e+00 9.28704679e-01
1.59169674e-01 -3.27551216e-01 -6.45668358e-02 1.05204606e+00
2.88162857e-01 2.77315348e-01 6.79025769e-01 -1.12336469e+00
4.80433375e-01 5.04940212e-01 4.89751101e-01 -7.47025609e-01
-3.73502016e-01 1.68966234e-01 1.22700579e-01 -1.35925636e-01
9.51616108e-01 2.22193226e-01 -2.99229249e-02 2.00226712e+00
2.53554434e-01 -9.47309196e-01 4.25056547e-01 6.20694935e-01
9.02226806e-01 3.82803530e-01 5.41697860e-01 -7.56270587e-01
1.96458614e+00 -3.87789071e-01 -1.08165097e+00 -3.96676809e-01
6.87602639e-01 -7.79049933e-01 1.01680088e+00 -6.78022876e-02
-1.17639399e+00 1.00778550e-01 -6.98469877e-01 -1.85449660e-01
-4.29424584e-01 -3.08721185e-01 4.79136974e-01 7.51138687e-01
-7.51973808e-01 3.94143015e-01 -4.10164505e-01 -1.02517581e+00
-4.71562482e-02 3.15816462e-01 -5.28217554e-01 3.97848845e-01
-1.06228578e+00 1.15093255e+00 7.67716944e-01 -3.58177423e-01
1.71622410e-01 1.55646905e-01 -7.60140479e-01 -1.56977028e-01
6.88340142e-02 -4.82674003e-01 1.24974453e+00 -1.07584798e+00
-1.08426714e+00 1.69915962e+00 -8.22999030e-02 -1.35123834e-01
2.72596806e-01 -1.52028173e-01 -7.24886417e-01 2.02515602e-01
6.23751283e-01 4.34963018e-01 3.10224921e-01 -1.16523087e+00
-8.38024437e-01 -3.42471302e-01 3.99481982e-01 3.71023089e-01
7.46603832e-02 9.45611238e-01 2.96051025e-01 -7.73522079e-01
3.78986806e-01 -6.63494170e-01 2.53261000e-01 -5.55809855e-01
-2.62930065e-01 -9.54205751e-01 3.70326012e-01 -3.53526235e-01
1.37646854e+00 -2.28480506e+00 4.31101993e-02 -1.61888435e-01
6.60261661e-02 -2.76215345e-01 2.47751921e-01 9.30316806e-01
-2.41781309e-01 3.52139175e-01 1.80774890e-02 1.10741578e-01
4.76135075e-01 7.57358551e-01 -2.18843594e-01 6.02858722e-01
2.06230357e-01 5.49147069e-01 -8.51443768e-01 -7.49013960e-01
-3.37080628e-01 1.59596458e-01 -1.40243813e-01 -4.01048690e-01
1.12087429e-01 6.42404482e-02 -3.09644967e-01 3.59242409e-01
3.37331772e-01 4.96182367e-02 5.58468401e-01 -3.13216150e-02
-7.19546318e-01 8.71038079e-01 -1.30561841e+00 1.21677589e+00
1.58396475e-02 5.50775528e-01 2.03676283e-01 -6.70023561e-01
6.85102046e-01 8.03100467e-01 -2.62011558e-01 -4.48437512e-01
2.39481390e-01 6.77275419e-01 3.34591687e-01 -5.00579417e-01
6.10355675e-01 -7.52271950e-01 -5.55530190e-01 3.63647372e-01
-1.05095416e-01 -1.26185626e-01 6.17842376e-01 1.55096099e-01
8.82598281e-01 -8.18577260e-02 1.04196656e+00 -8.49048972e-01
4.69588488e-01 -7.54703656e-02 8.33646774e-01 6.30505025e-01
-1.73293203e-01 3.48856062e-01 7.49314547e-01 -3.86089295e-01
-8.60875607e-01 -1.16192698e+00 -8.35501015e-01 1.17061496e+00
2.45727301e-01 -1.09620094e-01 -6.35496438e-01 -3.00953120e-01
-1.15040861e-01 1.40634429e+00 -3.24190140e-01 2.40408704e-01
-9.17135000e-01 -6.20710015e-01 6.13421738e-01 5.55323601e-01
-1.38200164e-01 -1.60322428e+00 -1.04517555e+00 3.66659224e-01
-2.16075018e-01 -1.11253297e+00 -2.74728775e-01 2.44120300e-01
-6.93548441e-01 -7.67042458e-01 -1.68343365e-01 -9.42564666e-01
2.90513724e-01 -1.45274878e-01 1.24069154e+00 3.11788589e-01
3.37891430e-01 6.33029640e-01 -4.05966401e-01 -3.54228884e-01
-7.94203401e-01 -2.03816161e-01 3.97592396e-01 -2.69010127e-01
8.08463991e-01 -6.17303550e-01 4.59489003e-02 1.52436763e-01
-1.09682763e+00 -5.11371911e-01 1.95182607e-01 7.61149764e-01
1.51390970e-01 -3.55084479e-01 4.80491877e-01 -9.44048941e-01
8.95773947e-01 -3.58907551e-01 -1.41487032e-01 7.08123073e-02
-2.41847843e-01 1.09604798e-01 2.15195846e-02 -5.67549169e-01
-1.28425121e+00 -3.65053535e-01 1.46568537e-01 6.67995036e-01
-5.37433028e-01 3.47212523e-01 -4.04238403e-01 4.69432294e-01
8.94197226e-01 -3.27680051e-01 -1.46908760e-01 -5.17738819e-01
1.22682706e-01 7.38597035e-01 5.72268069e-01 -1.02434719e+00
6.07874990e-01 3.70473236e-01 -2.22177953e-01 -1.22975039e+00
-7.05865204e-01 -4.65049356e-01 -8.13201070e-01 -3.23985727e-03
1.09414601e+00 -7.28233099e-01 -4.88988459e-01 -1.06293045e-01
-1.63462257e+00 7.31906248e-03 -6.84576631e-01 5.98868668e-01
-6.13333225e-01 3.57933253e-01 -6.95865571e-01 -6.86456680e-01
9.81448963e-02 -6.80012345e-01 9.91053104e-01 1.13130629e-01
-1.05905175e+00 -1.07150257e+00 1.99505374e-01 2.42401212e-01
-4.58301790e-02 4.63758856e-01 9.34736252e-01 -1.39540982e+00
3.99642028e-02 -2.76118666e-01 -4.00909968e-02 -2.64808595e-01
2.47136652e-01 1.11855911e-02 -7.34782875e-01 -2.92831417e-02
3.33129227e-01 -2.71411508e-01 2.51951367e-01 -1.31203877e-02
-4.00473446e-01 -5.99506021e-01 -3.67420137e-01 -2.15028435e-01
1.45692372e+00 3.91276836e-01 8.03560793e-01 9.30081964e-01
2.24227354e-01 1.08263052e+00 3.58219177e-01 2.23367304e-01
1.27980068e-01 7.41478145e-01 -2.90873110e-01 6.50483429e-01
-9.28763151e-02 2.04202458e-01 2.86390573e-01 7.92162716e-01
-6.93235248e-02 -2.29946122e-01 -1.08794022e+00 9.27314997e-01
-1.58713627e+00 -1.29959130e+00 -5.13084710e-01 1.92631149e+00
9.33160543e-01 2.12034807e-01 1.99652046e-01 1.32270992e-01
1.16987228e+00 2.79418558e-01 3.73761535e-01 -5.95762670e-01
-6.28596127e-01 -1.35652184e-01 1.16722509e-01 5.83205402e-01
-7.79166520e-01 9.19743180e-01 6.62101316e+00 8.77540171e-01
-5.55118382e-01 2.52628565e-01 -1.35852858e-01 8.20711851e-02
-3.85994941e-01 2.63565272e-01 -7.80479193e-01 4.08917367e-01
7.59169817e-01 -3.64847481e-01 1.77779436e-01 2.09898233e-01
-9.21764821e-02 -4.41360414e-01 -1.23162258e+00 5.87418318e-01
-1.54113606e-01 -8.83177400e-01 7.84471631e-02 3.03843748e-02
9.53871831e-02 -3.08262497e-01 -6.00570083e-01 -1.36509567e-01
1.21893018e-01 -7.93925405e-01 1.41225934e+00 3.11863095e-01
4.91420031e-01 -3.71271938e-01 8.02679718e-01 2.34293699e-01
-8.00875604e-01 3.88281955e-03 -3.36591542e-01 -3.93477410e-01
5.91763616e-01 -2.88198620e-01 -3.00606281e-01 1.50324479e-01
5.46407104e-01 -1.78270012e-01 -5.08333027e-01 6.99551642e-01
-4.48627859e-01 5.58611393e-01 -5.38059950e-01 -1.92562833e-01
1.28530607e-01 -1.58457518e-01 1.19492364e+00 1.45461452e+00
-5.37622571e-02 5.53466260e-01 -8.32358524e-02 6.41870379e-01
3.46145689e-01 4.13500637e-01 -5.60184777e-01 -2.92849869e-01
8.18104506e-01 1.01010013e+00 -1.21191752e+00 -5.59845492e-02
-6.23557985e-01 7.07891047e-01 2.18955845e-01 1.98292732e-01
-2.89135337e-01 -4.88261342e-01 3.12171042e-01 4.13479239e-01
1.43833190e-01 7.47800320e-02 -7.05625489e-02 -7.66084969e-01
-1.11417435e-02 -5.72752237e-01 4.77861136e-01 -6.92340672e-01
-1.44828808e+00 5.07491231e-01 5.06784201e-01 -8.24394047e-01
-1.53008789e-01 -5.86761594e-01 -5.51504970e-01 8.50527763e-01
-6.40540540e-01 -9.59033787e-01 2.23747253e-01 1.49724782e-01
3.12768906e-01 -2.15678543e-01 1.10012865e+00 -6.86268136e-02
-3.76675278e-01 1.89200923e-01 -1.31009594e-01 6.15868308e-02
8.08602452e-01 -1.28849936e+00 1.64867237e-01 4.09305066e-01
1.04347914e-02 9.79092419e-01 1.27434433e+00 -4.97886598e-01
-5.62371910e-01 -1.44355044e-01 1.85384667e+00 -8.19332361e-01
1.05489647e+00 2.13084146e-02 -9.50047135e-01 8.34214568e-01
7.06752419e-01 -3.95483226e-01 7.84791112e-01 1.48002490e-01
-3.70017827e-01 2.95458257e-01 -1.28710771e+00 7.05455482e-01
1.29315579e+00 -5.03075838e-01 -1.55859816e+00 4.38713282e-01
1.10369587e+00 -3.27458642e-02 -9.61065769e-01 -1.29788190e-01
3.35824907e-01 -9.58874822e-01 8.73377383e-01 -6.70031726e-01
1.31749466e-01 -2.14907929e-01 -4.69500512e-01 -8.08805287e-01
-6.83540702e-01 -6.50182545e-01 5.44608653e-01 1.85701156e+00
3.65279108e-01 -9.33190823e-01 3.36365476e-02 8.37141693e-01
-2.44039949e-02 2.33011264e-02 -1.35714424e+00 -8.54709089e-01
2.99250245e-01 5.69007099e-02 4.48561877e-01 1.31711376e+00
5.07404804e-01 8.85053456e-01 4.82343823e-01 -2.81217098e-01
3.99943322e-01 -1.40699700e-01 2.04727381e-01 -1.77226639e+00
-1.49064139e-01 -5.83572268e-01 -6.44168198e-01 -4.79637027e-01
3.68857741e-01 -6.48737311e-01 -1.58362836e-01 -1.46264553e+00
1.20321393e-03 -1.73983768e-01 4.57041383e-01 1.68560147e-01
1.72868371e-01 -1.40650854e-01 1.84085533e-01 4.41364646e-01
-4.68214005e-01 2.23726392e-01 8.19358468e-01 2.36182436e-01
-4.32161719e-01 -3.34706545e-01 -9.10561860e-01 1.03124952e+00
7.55168319e-01 -7.63939083e-01 2.59503052e-02 -2.53368646e-01
6.42817974e-01 1.54994294e-01 2.77454674e-01 -6.19173288e-01
3.83492261e-02 -4.87241685e-01 -2.54103273e-01 8.40654969e-03
3.58288102e-02 -6.08876586e-01 3.54797721e-01 2.98009217e-01
-2.39505753e-01 2.13285059e-01 2.73815066e-01 5.15466750e-01
-1.51003748e-01 -9.52046633e-01 5.89678824e-01 -4.16298628e-01
-5.22784889e-01 -8.54185522e-01 -8.37589085e-01 5.83728492e-01
7.73656964e-01 -6.80975556e-01 -3.20307434e-01 -3.77105945e-03
-7.78495371e-01 -1.38978928e-01 7.95366466e-01 2.15252265e-01
4.45346124e-02 -1.39835083e+00 -6.94880724e-01 -5.75906098e-01
2.23508671e-01 -2.75103539e-01 -2.80533463e-01 8.03695917e-01
-7.35210776e-01 3.63979816e-01 -1.47371650e-01 -8.04320499e-02
-1.22522163e+00 7.12301791e-01 1.63733065e-01 1.97879329e-01
-5.41406274e-01 7.46585071e-01 3.98103088e-01 -3.71542603e-01
-1.14147171e-01 1.51542425e-01 -6.12145603e-01 6.13106966e-01
4.06134039e-01 4.35224742e-01 -3.54833603e-01 -1.56767619e+00
-6.16657495e-01 1.97599977e-01 9.73289609e-02 -6.21717989e-01
1.22523260e+00 -4.03896213e-01 -7.81724274e-01 1.14136112e+00
7.93668866e-01 6.73886895e-01 -5.09763062e-01 -1.56107426e-01
5.40313542e-01 -2.96819031e-01 -5.85570097e-01 -4.19367671e-01
-9.51916501e-02 6.63247555e-02 5.88811003e-02 6.93765104e-01
5.03484726e-01 5.85836411e-01 2.68273264e-01 4.20148730e-01
5.43723047e-01 -1.33556569e+00 -3.40509504e-01 4.95255798e-01
1.34451890e+00 -5.59065700e-01 7.74941742e-02 -5.16109288e-01
-7.81324327e-01 1.15179038e+00 3.10681164e-01 4.19429317e-02
2.35660180e-01 5.62707894e-02 9.16255862e-02 -6.83727920e-01
-6.41835093e-01 -1.78534180e-01 -9.67976153e-02 5.34699321e-01
8.26097310e-01 1.54064164e-01 -1.51996207e+00 9.14573967e-01
-6.18910789e-01 -6.98037028e-01 9.44420397e-01 1.04778802e+00
-5.69370806e-01 -1.04770362e+00 -8.60788286e-01 1.96507737e-01
-7.50535786e-01 -8.31593052e-02 -7.71356583e-01 1.20412302e+00
2.10885808e-01 1.00941718e+00 4.45768565e-01 3.38164657e-01
6.92930043e-01 4.59797859e-01 5.82636714e-01 -9.07305896e-01
-8.14652681e-01 2.16785118e-01 8.69221926e-01 3.50629427e-02
-8.96718740e-01 -1.33600950e+00 -1.39958417e+00 -2.34778479e-01
-6.15582407e-01 3.99470985e-01 1.05805226e-01 1.12062597e+00
-3.87226105e-01 3.66926268e-02 -3.63419443e-01 -6.62827790e-01
-5.60030639e-01 -1.08941889e+00 -1.07518673e+00 7.97583282e-01
2.31378712e-02 -9.06647444e-01 -7.59293795e-01 9.40271467e-02] | [10.171425819396973, 9.300381660461426] |
bc9dbb94-4f14-4dec-992e-0484f07edd62 | effect-of-different-splitting-criteria-on-the | 2210.14501 | null | https://arxiv.org/abs/2210.14501v1 | https://arxiv.org/pdf/2210.14501v1.pdf | Effect of different splitting criteria on the performance of speech emotion recognition | Traditional speech emotion recognition (SER) evaluations have been performed merely on a speaker-independent condition; some of them even did not evaluate their result on this condition. This paper highlights the importance of splitting training and test data for SER by script, known as sentence-open or text-independent criteria. The results show that employing sentence-open criteria degraded the performance of SER. This finding implies the difficulties of recognizing emotion from speech in different linguistic information embedded in acoustic information. Surprisingly, text-independent criteria consistently performed worse than speaker+text-independent criteria. The full order of difficulties for splitting criteria on SER performances from the most difficult to the easiest is text-independent, speaker+text-independent, speaker-independent, and speaker+text-dependent. The gap between speaker+text-independent and text-independent was smaller than other criteria, strengthening the difficulties of recognizing emotion from speech in different sentences. | ['Akira Sasou', 'Bagus Tris Atmaja'] | 2022-10-26 | null | null | null | null | ['speech-emotion-recognition'] | ['speech'] | [-3.24154622e-03 -3.05575937e-01 5.28925300e-01 -6.92043722e-01
-9.92760420e-01 -6.72049224e-01 3.49979848e-01 -4.30759527e-02
-7.38538504e-01 6.09456241e-01 3.74339968e-01 -3.83810282e-01
1.79982241e-02 7.50815794e-02 -1.95324510e-01 -7.20016241e-01
2.48489454e-02 1.22602157e-01 4.86943759e-02 -5.26370645e-01
3.18308324e-01 2.98633665e-01 -2.00566220e+00 4.68805879e-01
6.57929122e-01 8.13927829e-01 2.06209272e-01 9.66019452e-01
-4.28300619e-01 6.64029837e-01 -1.20033991e+00 -2.75322407e-01
-1.46674380e-01 -7.47872114e-01 -6.95241272e-01 -2.20294446e-02
1.69642106e-01 1.60571575e-01 2.12743878e-01 9.22934294e-01
8.76820862e-01 1.49716467e-01 4.32866663e-01 -1.10752761e+00
-4.79979396e-01 3.30211192e-01 3.17793153e-02 4.89547402e-01
7.52942860e-01 -2.99593389e-01 6.99165642e-01 -9.53289449e-01
4.78283197e-01 1.28761935e+00 5.66158831e-01 6.07861042e-01
-1.08112395e+00 -5.35527349e-01 2.47129588e-03 2.82016695e-01
-1.31620383e+00 -1.10113895e+00 8.69847715e-01 -3.85441273e-01
1.26393747e+00 8.13393176e-01 3.77837121e-01 1.27279401e+00
-1.68388244e-02 5.24146676e-01 1.50587308e+00 -6.67044997e-01
3.91678602e-01 6.79095924e-01 3.47365886e-01 -1.06973328e-01
-3.03873658e-01 1.10169001e-01 -8.09764743e-01 -1.04079120e-01
1.99177682e-01 -6.92955494e-01 -3.60675901e-01 3.24060142e-01
-9.51429605e-01 5.34012675e-01 -4.58272636e-01 8.90799582e-01
-2.57127255e-01 -6.10326707e-01 1.00377119e+00 1.10466158e+00
6.26183867e-01 3.52170318e-01 -8.69257033e-01 -7.38585830e-01
-1.05211270e+00 -4.67020601e-01 1.07533383e+00 5.11681736e-01
2.83658415e-01 5.89737356e-01 1.72421321e-01 1.27588439e+00
2.88991094e-01 6.10575080e-01 6.84157312e-01 -4.58589435e-01
3.83970827e-01 -6.95846695e-03 3.32830176e-02 -8.17648649e-01
-3.71710777e-01 -2.42801875e-01 -2.65747190e-01 2.41147771e-01
4.98572171e-01 -3.39163870e-01 -6.82734072e-01 1.88845074e+00
9.91004184e-02 -4.51936662e-01 4.84313965e-01 8.04122031e-01
1.06175148e+00 8.07296693e-01 2.58493602e-01 -7.63303220e-01
1.39027846e+00 -6.63817286e-01 -1.19679868e+00 -2.64681816e-01
6.08473420e-01 -1.09913599e+00 1.21913517e+00 6.68364763e-01
-9.21371460e-01 -6.05307281e-01 -1.10905635e+00 3.79698128e-01
-6.30811036e-01 1.99562237e-01 1.19983569e-01 1.29353511e+00
-1.32127702e+00 1.07204281e-01 -3.20477456e-01 -4.45952296e-01
-4.56092834e-01 1.69995204e-01 -6.86221778e-01 5.95137239e-01
-1.49936259e+00 1.26984906e+00 9.10358950e-02 1.86717302e-01
-3.40701044e-01 -7.36459345e-02 -1.07437754e+00 -4.75760028e-02
1.63849071e-01 9.57323089e-02 1.25760090e+00 -1.59235382e+00
-1.86483610e+00 9.64787722e-01 -6.17366374e-01 -1.52950227e-01
2.06597507e-01 1.18301101e-01 -1.32995105e+00 2.92537510e-01
-2.07898542e-01 -8.34970027e-02 1.12859499e+00 -1.37021518e+00
-2.49222755e-01 -5.11110842e-01 -6.42171383e-01 2.76219428e-01
-2.46826887e-01 9.22447801e-01 2.20806897e-01 -5.28347075e-01
2.48847738e-01 -3.84391397e-01 3.41934204e-01 -6.01590335e-01
-9.06435996e-02 -4.20258909e-01 9.00584042e-01 -9.99857426e-01
1.38777339e+00 -2.66141438e+00 -1.52619049e-01 -4.96751666e-02
-9.46055949e-02 3.63912284e-01 -1.23986736e-01 6.35023236e-01
-6.69124424e-01 2.92915165e-01 8.90518948e-02 -4.37917292e-01
2.86072463e-01 2.86086500e-01 -8.53645056e-02 1.72967747e-01
2.63616472e-01 4.33649868e-01 -4.41189289e-01 -6.24107182e-01
3.16112906e-01 6.28704965e-01 3.18873115e-02 -1.15547784e-01
3.67422134e-01 4.92802024e-01 -5.83712347e-02 5.31830847e-01
5.71745992e-01 4.99230057e-01 -2.45970637e-02 1.18617848e-01
-4.37569618e-01 6.96384609e-01 -1.21442151e+00 1.04859722e+00
-6.39276683e-01 9.88088310e-01 8.12637091e-01 -1.07485390e+00
1.07012761e+00 9.48527515e-01 7.00556412e-02 -8.00861359e-01
2.15145171e-01 4.85323638e-01 2.13473216e-01 -9.20403838e-01
6.07603967e-01 -6.64181888e-01 -1.55287087e-01 1.05252393e-01
5.57395220e-02 -3.63473952e-01 4.01694067e-02 -1.14709437e-01
7.02421904e-01 -2.80295342e-01 1.83482602e-01 -2.56943405e-01
7.31046975e-01 -5.94293475e-01 4.77665305e-01 4.24135566e-01
-8.21907163e-01 6.62200630e-01 5.82364559e-01 2.07964867e-01
-5.63623488e-01 -8.94794226e-01 -5.27121961e-01 1.27578485e+00
-1.53682202e-01 -3.66999179e-01 -6.87550962e-01 -6.28555477e-01
-4.30615187e-01 1.16988623e+00 -3.91392022e-01 1.80349238e-02
-7.19606578e-02 -3.65261167e-01 7.74029016e-01 1.63132325e-01
5.14080599e-02 -1.17488360e+00 -3.82491231e-01 1.95696473e-01
-4.56340432e-01 -9.94119585e-01 -3.01801324e-01 6.70275390e-01
-5.11038840e-01 -2.57211745e-01 -7.25382626e-01 -6.68607056e-01
3.59345764e-01 -1.00940108e-01 8.60622227e-01 -2.26541564e-01
1.67328656e-01 6.62848353e-01 -7.80941129e-01 -5.59246063e-01
-9.27428722e-01 -4.83202964e-01 1.43518880e-01 8.98224264e-02
4.83168513e-01 -3.67403328e-01 9.38155204e-02 6.04023397e-01
-8.36686611e-01 -6.07487679e-01 4.00376529e-01 6.87044919e-01
-1.20866805e-01 1.46538734e-01 1.11081254e+00 -9.16256234e-02
7.66260505e-01 -2.18939319e-01 2.90380388e-01 2.15080678e-01
-2.48383284e-01 -9.49583799e-02 5.43700099e-01 -5.00256717e-01
-1.03870201e+00 -2.79398978e-01 -7.23015964e-01 -1.19496226e-01
-8.06105971e-01 5.73717773e-01 -4.60451514e-01 -1.83034148e-02
5.80512404e-01 3.64830852e-01 1.38685837e-01 -2.64325947e-01
-4.43544954e-01 1.25432432e+00 1.84100255e-01 -2.72041827e-01
2.45729670e-01 -7.43204206e-02 -8.56971800e-01 -1.55915344e+00
-3.96204710e-01 -6.79468811e-01 -3.82190347e-01 -5.66274107e-01
9.55179274e-01 -7.00489879e-01 -3.35356951e-01 6.95673704e-01
-1.10982907e+00 3.50435190e-02 -2.77414888e-01 7.97611356e-01
-1.78294078e-01 7.35182643e-01 -5.25334418e-01 -1.44596016e+00
-9.53567177e-02 -1.16874599e+00 1.05610764e+00 -2.66227871e-02
-6.83640301e-01 -9.80754018e-01 -5.55984117e-02 5.82654297e-01
4.40265566e-01 -2.15829074e-01 4.22958463e-01 -1.25417459e+00
6.03097439e-01 -4.16888744e-01 5.85573129e-02 9.76255417e-01
1.69716686e-01 2.30857998e-01 -1.39006233e+00 -7.27798566e-02
5.44991255e-01 -4.53246415e-01 5.65430284e-01 1.08347721e-01
4.10238892e-01 3.82465348e-02 3.57544601e-01 -1.69769332e-01
9.52574193e-01 5.93624234e-01 7.92389750e-01 1.66587606e-01
-3.61351743e-02 9.02611673e-01 3.97131234e-01 2.14842379e-01
2.23717242e-01 5.19874036e-01 -8.48190635e-02 -2.25369230e-01
1.14622585e-01 2.31670603e-01 1.15800571e+00 1.22652042e+00
3.58551264e-01 -3.62028271e-01 -6.91621900e-01 5.64476967e-01
-1.15107524e+00 -1.04953671e+00 -4.03705359e-01 2.23596382e+00
6.74892664e-01 1.75556228e-01 9.18692052e-02 7.49751329e-01
9.35955942e-01 2.42652521e-01 -5.10316007e-02 -1.30715287e+00
-5.26121974e-01 5.78908883e-02 -1.76545396e-01 6.01171970e-01
-9.53455031e-01 6.51005089e-01 6.66512299e+00 9.67654228e-01
-1.31224561e+00 1.59266695e-01 4.27924186e-01 -3.98401842e-02
-2.28682280e-01 -1.61657944e-01 -4.10483599e-01 5.45055509e-01
1.39031494e+00 -1.42270058e-01 9.11979377e-02 6.68814659e-01
4.91333336e-01 -5.62544703e-01 -1.04801702e+00 1.20365226e+00
4.45305735e-01 -1.86492205e-01 -3.34591150e-01 -3.56052756e-01
7.84435868e-02 -1.36335403e-01 -1.17924109e-01 5.55961251e-01
-4.94071513e-01 -7.42733479e-01 1.06490743e+00 3.81956883e-02
7.39445925e-01 -4.82181996e-01 8.56405020e-01 2.95653641e-01
-9.64855433e-01 2.40956172e-01 9.72479731e-02 -3.11572015e-01
2.76227117e-01 4.94870633e-01 -4.20788705e-01 6.99308038e-01
8.44883144e-01 3.28898579e-01 -4.84257340e-01 5.29710710e-01
-4.05998453e-02 9.53028679e-01 -3.17428172e-01 -2.39058733e-01
-4.83403131e-02 -1.46215990e-01 9.24250543e-01 1.63587296e+00
2.98315614e-01 -2.16364056e-01 -3.45415682e-01 2.89827108e-01
6.57457888e-01 4.53331172e-01 -6.08406305e-01 -3.78573656e-01
3.33215982e-01 1.09631467e+00 -7.48983443e-01 -2.70642608e-01
-4.33380961e-01 1.16431534e+00 -1.48715407e-01 4.39654171e-01
-6.21137261e-01 -6.67220414e-01 3.65741968e-01 -3.90142381e-01
2.42934465e-01 -2.27817178e-01 -3.65638405e-01 -9.44605649e-01
3.84624660e-01 -1.05571520e+00 3.47903401e-01 -8.58495355e-01
-1.29442704e+00 8.90665531e-01 -2.14337245e-01 -9.54604506e-01
-1.83063105e-01 -6.62011087e-01 -6.40877724e-01 9.42549348e-01
-1.08711219e+00 -5.63611448e-01 2.30122551e-01 4.95025545e-01
6.39991701e-01 -9.56883430e-02 1.06487834e+00 3.89575660e-01
-6.07977211e-01 7.00810850e-01 1.17234662e-01 -4.18823259e-03
1.02965236e+00 -1.15312350e+00 -3.30544144e-01 6.74328804e-01
4.30279523e-02 5.54341197e-01 1.07103634e+00 -2.84523129e-01
-9.61956680e-01 2.91830325e-03 1.49170208e+00 -6.37169659e-01
6.72940612e-01 -5.11914551e-01 -9.47689712e-01 1.89472884e-01
5.17662823e-01 -6.55472040e-01 9.59685445e-01 3.21925312e-01
-4.03496236e-01 -1.29093647e-01 -1.16741729e+00 5.27189434e-01
5.51789224e-01 -9.57887828e-01 -1.00334930e+00 -1.07500024e-01
5.44923246e-01 -4.93888482e-02 -8.11393678e-01 1.95730716e-01
5.07458746e-01 -1.25972676e+00 6.47293270e-01 -3.98813128e-01
1.31895632e-01 2.43910067e-02 -3.42421710e-01 -1.29238725e+00
1.34893134e-01 -6.51498735e-01 7.45260954e-01 1.50875807e+00
7.98182249e-01 -1.18669319e+00 1.82784289e-01 7.20295548e-01
-5.03967524e-01 -1.68881029e-01 -1.43136811e+00 -9.40095842e-01
1.28310218e-01 -8.63830745e-01 9.08932686e-02 1.24815583e+00
4.59668398e-01 3.78938317e-01 -1.40484750e-01 6.14672191e-02
-7.84788057e-02 -4.34236377e-01 3.26312631e-01 -1.04338634e+00
-1.86650559e-01 -6.30689681e-01 -6.17956221e-01 -6.07973754e-01
2.92875290e-01 -4.48563367e-01 1.89380839e-01 -1.27180552e+00
-2.57297009e-01 -1.06266066e-01 -2.92149037e-01 4.14585561e-01
-2.06152096e-01 -8.28608200e-02 2.91701853e-01 -2.04164252e-01
-4.51087981e-01 5.96635878e-01 9.14094508e-01 1.48629054e-01
-2.56678849e-01 -8.18153247e-02 -5.54199278e-01 5.88909626e-01
8.86116385e-01 -3.46053898e-01 -3.47419083e-01 -1.22815512e-01
1.83200777e-01 4.16775137e-01 2.28249535e-01 -9.78334367e-01
1.08233273e-01 1.41584158e-01 1.98251501e-01 -5.28010249e-01
5.83345473e-01 -9.06275511e-01 3.63194231e-05 7.08388165e-02
-2.52043813e-01 -1.04168274e-01 7.30514109e-01 1.24316499e-01
-6.51324332e-01 -3.75584662e-01 6.24616027e-01 1.18217446e-01
-7.69516885e-01 -6.20710671e-01 -1.09258163e+00 1.36457458e-01
8.69088352e-01 -6.92690432e-01 -1.01320893e-01 -7.94630051e-01
-1.26385927e+00 -1.22476712e-01 5.31185605e-03 6.22089326e-01
5.31086862e-01 -8.62134099e-01 -7.94412076e-01 4.53248560e-01
5.63581809e-02 -8.11830759e-01 4.50327128e-01 1.23362029e+00
-4.77025695e-02 4.26074684e-01 5.77316569e-05 -4.50925142e-01
-1.96680927e+00 3.01300138e-01 4.17202383e-01 7.62836039e-02
1.35501996e-02 9.77779627e-01 1.42819388e-02 -5.75201988e-01
4.86621618e-01 -9.47613716e-02 -2.56426066e-01 5.48458338e-01
4.35237437e-01 3.57729048e-01 4.38186944e-01 -1.06676960e+00
-5.10655344e-01 3.27124208e-01 6.53119609e-02 -6.96547806e-01
9.39612210e-01 -4.63881493e-01 -2.36668006e-01 1.31616783e+00
1.14403212e+00 3.68947387e-01 -4.05529112e-01 1.35672778e-01
2.50093509e-02 -1.82000414e-01 1.72030613e-01 -1.10478580e+00
-3.47641885e-01 8.81781578e-01 4.18629467e-01 8.67341697e-01
1.24509704e+00 -1.13807678e-01 2.96732992e-01 1.72947600e-01
3.63751441e-01 -1.60813332e+00 -3.24615300e-01 7.55867362e-01
1.17667317e+00 -1.27555335e+00 -5.45063198e-01 -3.49782139e-01
-9.08186555e-01 1.08001864e+00 3.30557436e-01 6.12584233e-01
6.89598560e-01 3.55578989e-01 5.52030981e-01 -4.28932048e-02
-7.26539016e-01 -2.03567758e-01 3.07660967e-01 5.26058853e-01
8.69983256e-01 -2.42321356e-03 -5.30276179e-01 7.87449419e-01
-4.31758702e-01 -2.62246788e-01 2.40948915e-01 8.68324995e-01
-3.08474392e-01 -1.07327545e+00 -8.54320347e-01 2.82480538e-01
-4.82616574e-01 -1.28059164e-01 -9.69061434e-01 7.15521812e-01
-1.89876854e-01 1.71575761e+00 -4.78850417e-02 -5.55410028e-01
3.24453533e-01 8.02991033e-01 1.79510146e-01 -2.78203577e-01
-8.46810699e-01 2.61410624e-01 8.61672997e-01 -3.40843707e-01
-4.73643064e-01 -1.05919421e+00 -1.06010473e+00 -8.15979838e-02
-5.32334983e-01 6.67779803e-01 1.10621750e+00 1.06819785e+00
2.16853872e-01 5.04089952e-01 7.95530558e-01 -6.01950824e-01
-5.41138709e-01 -1.23176730e+00 -7.81780124e-01 3.45733672e-01
5.22375822e-01 -2.61897326e-01 -1.15506268e+00 -7.88760856e-02] | [13.96747875213623, 5.884884357452393] |
bf493986-b525-49a5-9b34-4e229a4192cb | causal-order-identification-to-address | 2108.04947 | null | https://arxiv.org/abs/2108.04947v2 | https://arxiv.org/pdf/2108.04947v2.pdf | Causal Order Identification to Address Confounding: Binary Variables | This paper considers an extension of the linear non-Gaussian acyclic model (LiNGAM) that determines the causal order among variables from a dataset when the variables are expressed by a set of linear equations, including noise. In particular, we assume that the variables are binary. The existing LiNGAM assumes that no confounding is present, which is restrictive in practice. Based on the concept of independent component analysis (ICA), this paper proposes an extended framework in which the mutual information among the noises is minimized. Another significant contribution is to reduce the realization of the shortest path problem. The distance between each pair of nodes expresses an associated mutual information value, and the path with the minimum sum (KL divergence) is sought. Although $p!$ mutual information values should be compared, this paper dramatically reduces the computation when no confounding is present. The proposed algorithm finds the globally optimal solution, while the existing locally greedily seek the order based on hypothesis testing. We use the best estimator in the sense of Bayes/MDL that correctly detects independence for mutual information estimation. Experiments using artificial and actual data show that the proposed version of LiNGAM achieves significantly better performance, particularly when confounding is present. | ['Yusuke Inaoka', 'Joe Suzuki'] | 2021-08-10 | null | null | null | null | ['mutual-information-estimation'] | ['methodology'] | [ 9.61593091e-02 -2.02435739e-02 -1.91484168e-01 -3.24469596e-01
-3.10470581e-01 -4.08074319e-01 2.70582944e-01 -2.33682580e-02
-4.81988102e-01 8.51731360e-01 -1.09415529e-02 -3.70027751e-01
-9.16427076e-01 -9.22899067e-01 -5.60980380e-01 -9.40505326e-01
-4.03784037e-01 4.20198143e-01 -1.00683749e-01 2.05383599e-01
3.49230707e-01 3.27712476e-01 -1.39112651e+00 -5.13794422e-01
1.13793135e+00 7.26496220e-01 3.21426243e-01 6.03460550e-01
-1.75088108e-01 5.66686511e-01 -5.10954857e-01 -4.09886152e-01
2.91636378e-01 -8.17217529e-01 -6.45106018e-01 -1.25805557e-01
-1.53565437e-01 8.55056569e-02 6.08614907e-02 1.23809314e+00
3.39975893e-01 6.83436170e-02 1.05536401e+00 -1.63149512e+00
-4.87278908e-01 6.74756110e-01 -7.03330100e-01 2.49055892e-01
1.33020058e-02 -2.88651466e-01 1.02672422e+00 -6.38965487e-01
2.39319578e-01 1.35137558e+00 5.61297417e-01 -5.26949950e-02
-1.25871909e+00 -9.41520393e-01 1.77575037e-01 3.17245930e-01
-1.89534676e+00 3.19768377e-02 6.70888186e-01 -3.39273632e-01
5.27280092e-01 4.95672733e-01 2.99385399e-01 5.93404949e-01
5.42235553e-01 4.64999974e-01 1.09142911e+00 -5.42367160e-01
5.14996767e-01 1.84311196e-01 4.05612528e-01 4.59248513e-01
7.94335246e-01 -9.64421406e-03 -4.19045448e-01 -5.24747372e-01
4.32360232e-01 -1.16367020e-01 -1.89771473e-01 -2.53994972e-01
-8.90500128e-01 7.89124906e-01 -5.80654033e-02 5.67175031e-01
-4.48738009e-01 -1.17075011e-01 -2.31907666e-01 2.75143653e-01
1.34399086e-01 3.09969544e-01 -3.74231845e-01 8.69550859e-04
-8.39179754e-01 8.10776725e-02 1.01073158e+00 9.01326954e-01
8.39774609e-01 -2.02158228e-01 2.22943321e-01 4.59121048e-01
7.06039786e-01 6.77263021e-01 2.51617491e-01 -7.57321000e-01
2.77063847e-01 6.37479603e-01 1.25413820e-01 -1.63831484e+00
-4.16373521e-01 -7.24207461e-01 -9.02005613e-01 -2.85365861e-02
5.68955123e-01 -4.04756308e-01 -4.74536985e-01 1.95175493e+00
2.71756142e-01 4.47222620e-01 4.88003939e-02 7.48914003e-01
4.51198250e-01 4.41643685e-01 4.32000607e-02 -7.97318637e-01
1.03809977e+00 -1.52677298e-01 -1.24082732e+00 -1.36740059e-01
3.62270057e-01 -7.33696878e-01 4.71078306e-01 5.65445185e-01
-7.41595149e-01 -3.03176790e-01 -9.64256108e-01 5.75222731e-01
-2.28349671e-01 -2.23998502e-01 7.14995503e-01 8.55027974e-01
-9.67144430e-01 3.12940449e-01 -7.23396242e-01 -2.83333302e-01
-1.47688925e-01 5.36361933e-01 -2.31049299e-01 6.39871657e-02
-1.25013316e+00 6.81152880e-01 2.59095579e-01 3.27593118e-01
-4.77983624e-01 -3.90417844e-01 -5.17438591e-01 -2.85076741e-02
4.81601357e-01 -4.26120162e-01 6.49040461e-01 -8.77333641e-01
-1.02609670e+00 1.77278608e-01 -5.13701260e-01 -1.89125329e-01
4.51679200e-01 3.19631398e-02 -4.54458863e-01 -1.05694540e-01
2.81935930e-01 1.06064072e-02 4.56489503e-01 -1.36806452e+00
-5.80316126e-01 -5.63031614e-01 -2.89587677e-01 -1.98065285e-02
-4.78487551e-01 1.21897124e-01 -6.58032179e-01 -2.92510241e-01
5.14532685e-01 -8.73885810e-01 -4.76111114e-01 -3.63304377e-01
-6.01348877e-01 -1.67705387e-01 5.55113375e-01 -6.12475634e-01
1.68391097e+00 -1.95421958e+00 2.28330359e-01 8.39138150e-01
2.10417926e-01 -3.93079102e-01 5.15019856e-02 5.83825588e-01
-2.01575831e-01 2.24510357e-01 -6.20795131e-01 -6.52282536e-02
-3.56948376e-01 3.64282429e-01 2.01073274e-01 7.94792652e-01
-5.93905561e-02 3.94335002e-01 -6.56972229e-01 -8.61981750e-01
-1.15798697e-01 2.28763357e-01 -4.22011733e-01 2.23712727e-01
2.16363728e-01 4.09227520e-01 -4.75213766e-01 1.89137921e-01
9.23889399e-01 -2.34432578e-01 3.99351180e-01 -7.16689005e-02
-4.07151997e-01 -3.18078041e-01 -2.00287557e+00 1.16083920e+00
-2.93658435e-01 3.46966326e-01 -5.31173637e-03 -1.20699096e+00
1.09102929e+00 3.45678061e-01 6.64930046e-01 -2.73137152e-01
3.78714055e-01 -1.20806124e-03 4.27141368e-01 -5.70233762e-01
-4.23204713e-02 1.56856105e-02 2.46615820e-02 1.74297377e-01
-2.10163772e-01 2.98833489e-01 2.47135669e-01 3.21266949e-01
1.15782142e+00 -4.04672384e-01 6.59376383e-01 -5.37454665e-01
4.84796286e-01 -2.70993859e-01 9.76725876e-01 9.96056259e-01
-6.22492400e-04 3.89285922e-01 9.62542295e-01 2.70396769e-01
-3.85687172e-01 -1.21432805e+00 -2.89086491e-01 3.11986774e-01
3.34315449e-01 -2.22772673e-01 -4.80070919e-01 -4.35115397e-01
-1.39650153e-02 7.78534949e-01 -7.75451422e-01 1.24151796e-01
-1.98153093e-01 -1.27201116e+00 2.80234784e-01 1.00573905e-01
4.56933409e-01 -3.51836681e-01 -2.84226805e-01 1.55629769e-01
-2.15978801e-01 -5.96550703e-01 6.45329431e-02 3.09980512e-01
-8.15385520e-01 -1.26482022e+00 -2.70376831e-01 -4.54568118e-01
7.80980587e-01 7.88752884e-02 6.10565126e-01 -1.86111227e-01
-9.71194208e-02 1.77385926e-01 -2.14498535e-01 -3.72878194e-01
-1.48638263e-01 -5.00976264e-01 5.86021617e-02 3.46339434e-01
4.77940559e-01 -7.22764492e-01 -5.05125642e-01 4.71661419e-01
-7.23179281e-01 -4.99130160e-01 6.50909603e-01 5.79989374e-01
6.76886141e-01 7.50498831e-01 5.53361654e-01 -7.02565014e-01
5.22116959e-01 -8.83715093e-01 -7.07696199e-01 2.26109356e-01
-8.78410876e-01 1.55746430e-01 5.12440979e-01 -3.02890182e-01
-1.12404346e+00 4.29158174e-02 3.43315244e-01 -6.90115243e-02
-2.23400876e-01 7.05787122e-01 -7.41245925e-01 1.68639272e-01
4.27285969e-01 -5.81659749e-02 -1.41765028e-01 -5.98527193e-01
2.81984955e-01 6.77060783e-01 3.68004739e-01 -1.97726592e-01
6.39645517e-01 5.25295734e-01 5.41143298e-01 -8.89192939e-01
-2.51120597e-01 -5.45310020e-01 -6.46481991e-01 -2.69587338e-01
7.89420068e-01 -4.00281519e-01 -9.48062718e-01 2.33257428e-01
-1.00305939e+00 4.40524697e-01 1.93025842e-01 1.04206705e+00
-2.71971792e-01 5.06424665e-01 -7.50888512e-02 -1.31262338e+00
9.85003337e-02 -1.09982717e+00 3.27719688e-01 7.18870088e-02
-4.73206609e-01 -9.41369236e-01 1.81310207e-01 -1.02878369e-01
1.76916327e-02 1.75097808e-01 1.00975955e+00 -9.12776411e-01
-3.91542703e-01 -3.27916384e-01 -8.57048035e-02 8.64022151e-02
3.06336999e-01 1.18138768e-01 -6.10699594e-01 -2.87062805e-02
1.96264967e-01 5.91206372e-01 4.66025531e-01 7.32661843e-01
9.10408258e-01 -4.37876016e-01 -5.43263137e-01 4.35115576e-01
1.53735983e+00 8.01866293e-01 3.98790181e-01 1.06080718e-01
5.73719800e-01 7.90802181e-01 5.50997078e-01 5.28746247e-01
3.32787573e-01 3.84445697e-01 5.67107379e-01 -5.91731630e-02
3.79743248e-01 -2.80285534e-02 -1.48022790e-02 9.55974519e-01
2.36842960e-01 -6.71339154e-01 -9.85841632e-01 4.34878021e-01
-1.83483708e+00 -9.02914286e-01 -7.73310542e-01 2.38786840e+00
5.98634601e-01 -4.43083011e-02 -1.32522658e-01 3.61508399e-01
7.27363527e-01 -2.91083395e-01 -3.41664612e-01 -2.30024219e-01
-2.15257198e-01 -4.02589608e-03 8.23167205e-01 8.59069943e-01
-9.58399415e-01 2.42472991e-01 6.55677843e+00 5.86972415e-01
-7.74585187e-01 8.46842453e-02 4.22576576e-01 1.06344856e-01
-3.12746167e-01 2.52288431e-01 -7.34257698e-01 6.32819831e-01
8.95670891e-01 -4.12450194e-01 -6.17652535e-02 5.78512132e-01
7.31378019e-01 -5.72467685e-01 -7.87416220e-01 7.14068592e-01
7.62262717e-02 -3.67765993e-01 -3.24390560e-01 3.26754123e-01
6.25983357e-01 -5.31075418e-01 1.04085922e-01 -3.23823303e-01
4.72206950e-01 -8.18479657e-01 2.69499838e-01 8.75780880e-01
2.01588497e-01 -1.03054631e+00 8.97613227e-01 4.98227149e-01
-1.08499300e+00 -8.68066400e-02 -2.25112483e-01 -2.64698744e-01
4.13071439e-02 9.80299950e-01 -7.40519822e-01 7.43802130e-01
5.40564597e-01 5.44726670e-01 -3.75983924e-01 1.26469409e+00
-2.56708443e-01 8.59318554e-01 -4.86410052e-01 -2.78203815e-01
-4.62209322e-02 -5.49573720e-01 7.28982389e-01 1.10683024e+00
4.68058348e-01 2.24615023e-01 9.80516449e-02 7.61993110e-01
4.02412146e-01 4.98683840e-01 -5.98793864e-01 2.38730177e-01
6.94449544e-01 8.49296689e-01 -1.04723811e+00 -9.11287740e-02
-5.38664222e-01 8.32371533e-01 -1.50080156e-02 4.48494524e-01
-6.75872922e-01 -3.17942381e-01 5.16823411e-01 -1.92192942e-01
1.24245510e-01 -1.94672674e-01 -5.71508825e-01 -6.97039783e-01
-3.05531882e-02 -7.27227628e-01 5.69013178e-01 -2.09548250e-01
-1.22472298e+00 2.33459502e-01 3.78429413e-01 -1.12143743e+00
-2.30840251e-01 -2.09053293e-01 -5.69103479e-01 1.07110965e+00
-9.50160682e-01 -5.05492508e-01 -2.00162083e-02 4.59574848e-01
1.01053685e-01 1.66540191e-01 6.28778160e-01 4.14667606e-01
-8.52592707e-01 4.89870936e-01 3.46816123e-01 -5.64771071e-02
5.62462687e-01 -1.14075243e+00 -1.43176049e-01 1.27018237e+00
-1.56022906e-01 9.24279869e-01 1.10700810e+00 -1.07362187e+00
-1.28673971e+00 -6.89091146e-01 1.13280094e+00 -1.97190717e-01
7.08354890e-01 -1.39506206e-01 -8.20985913e-01 4.18318301e-01
-9.74913910e-02 -3.44956636e-01 9.27787006e-01 2.74698973e-01
-8.68050382e-02 -1.12220451e-01 -1.07247710e+00 6.00604296e-01
8.68925333e-01 4.71857861e-02 -4.28227007e-01 2.01609150e-01
4.60354716e-01 4.99125570e-01 -8.26008797e-01 4.74659264e-01
5.21065593e-01 -9.57970440e-01 6.70532346e-01 -5.08753419e-01
1.06574565e-01 -5.89585841e-01 -1.89591378e-01 -1.04766130e+00
-4.04372066e-01 -3.76468390e-01 2.67359048e-01 1.35435593e+00
6.39257848e-01 -6.32122993e-01 5.85317910e-01 7.85153031e-01
4.37160224e-01 -4.50369656e-01 -1.19928718e+00 -9.14683700e-01
-2.22706199e-01 -7.21798897e-01 3.65452737e-01 1.00839782e+00
-4.31029871e-02 1.75730929e-01 -4.99184310e-01 6.26727104e-01
1.04390764e+00 -4.66092266e-02 5.73056459e-01 -1.42659807e+00
-4.79190856e-01 -2.02323213e-01 -5.81762910e-01 -7.44113326e-01
1.85189858e-01 -6.41549110e-01 1.46601573e-01 -1.50121093e+00
2.71674216e-01 -4.95249569e-01 -2.83451438e-01 1.50556833e-01
-2.85038292e-01 -3.50680888e-01 -1.28700495e-01 7.66301081e-02
-2.60863572e-01 2.97489315e-01 7.63038933e-01 1.07418269e-01
-5.03952265e-01 2.80590445e-01 -7.85319507e-01 8.60855639e-01
6.21806860e-01 -7.87458897e-01 -5.22787809e-01 -4.90887351e-02
2.08575979e-01 2.69899905e-01 5.21782301e-02 -6.95297360e-01
4.54337895e-01 -2.54281044e-01 2.18360931e-01 -6.75710082e-01
8.65667835e-02 -1.22651839e+00 6.98750317e-01 4.46944892e-01
-2.61034191e-01 2.47517228e-01 -9.12697539e-02 7.83780098e-01
-3.56068686e-02 -4.43056971e-01 3.85214210e-01 8.65021199e-02
-4.06268746e-01 -7.00861141e-02 -5.16957641e-01 -3.81636858e-01
1.00827217e+00 -2.97750775e-02 8.92247781e-02 -5.90206265e-01
-7.17813373e-01 1.99211597e-01 -5.48423640e-02 7.92464241e-02
4.65831488e-01 -9.96370196e-01 -6.85842872e-01 1.95868369e-02
-2.21015871e-01 -4.22061533e-01 2.14747161e-01 1.04917276e+00
3.06867827e-02 4.57991540e-01 2.46286467e-01 -3.94225508e-01
-1.33278573e+00 6.50607586e-01 1.01259828e-01 -7.73518980e-02
-1.37918264e-01 8.31707656e-01 2.22354442e-01 1.09697962e-02
2.01299474e-01 3.97300720e-02 -5.24295270e-01 2.72275150e-01
4.86839235e-01 7.99094021e-01 -1.06146738e-01 -6.87055945e-01
-4.75436836e-01 4.81383115e-01 2.43813604e-01 -3.70779395e-01
1.10761166e+00 -4.38549340e-01 -6.23621047e-01 5.80712020e-01
1.39967370e+00 3.98713440e-01 -6.08943164e-01 -1.90614969e-01
1.44990683e-01 -5.73541462e-01 1.63745642e-01 -5.77503920e-01
-8.75510812e-01 3.26341450e-01 7.69832313e-01 2.41359770e-01
1.21887839e+00 -3.84569243e-02 -3.51013727e-02 2.06827655e-01
3.21910262e-01 -6.36889040e-01 -4.76951003e-01 2.31154844e-01
4.83049154e-01 -9.68213499e-01 8.59094560e-02 -5.73267281e-01
-2.42501110e-01 8.31447303e-01 5.52832603e-01 5.19072041e-02
1.13895059e+00 6.22366250e-01 -4.53465879e-02 -7.54104555e-02
-4.96367306e-01 -3.33331078e-01 1.09802328e-01 4.89516914e-01
4.27449197e-01 7.64709413e-02 -1.24968302e+00 7.81854808e-01
-2.50716805e-01 -3.70579004e-01 3.95786136e-01 6.90205812e-01
-3.37036073e-01 -9.81723189e-01 -7.93608665e-01 4.90619630e-01
-5.55537641e-01 -6.04974926e-02 -3.41477841e-01 8.98566246e-01
2.16996938e-01 1.56871200e+00 1.89335316e-01 -2.82935619e-01
2.83468604e-01 -1.61900550e-01 -6.13960288e-02 -1.81013629e-01
-1.82290331e-01 2.51490772e-01 -1.52930185e-01 -4.74571347e-01
-4.82274443e-01 -7.59248376e-01 -1.20626533e+00 -1.54301390e-01
-5.97769022e-01 6.40167296e-01 7.55684257e-01 1.03457546e+00
8.77981931e-02 4.13124740e-01 7.61396766e-01 1.69332285e-04
-2.76102126e-01 -7.52145052e-01 -8.33116412e-01 -2.09677201e-02
1.08353160e-01 -8.23044002e-01 -9.17378664e-01 -1.53379351e-01] | [7.73684549331665, 4.9553608894348145] |
9fd2d631-a6bf-42d8-8d55-d5f17dbee520 | infinite-time-horizon-safety-of-bayesian | 2111.03165 | null | https://arxiv.org/abs/2111.03165v1 | https://arxiv.org/pdf/2111.03165v1.pdf | Infinite Time Horizon Safety of Bayesian Neural Networks | Bayesian neural networks (BNNs) place distributions over the weights of a neural network to model uncertainty in the data and the network's prediction. We consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with infinite time horizon systems. Compared to the existing sampling-based approaches, which are inapplicable to the infinite time horizon setting, we train a separate deterministic neural network that serves as an infinite time horizon safety certificate. In particular, we show that the certificate network guarantees the safety of the system over a subset of the BNN weight posterior's support. Our method first computes a safe weight set and then alters the BNN's weight posterior to reject samples outside this set. Moreover, we show how to extend our approach to a safe-exploration reinforcement learning setting, in order to avoid unsafe trajectories during the training of the policy. We evaluate our approach on a series of reinforcement learning benchmarks, including non-Lyapunovian safety specifications. | ['Thomas A. Henzinger', 'Krishnendu Chatterjee', 'Đorđe Žikelić', 'Mathias Lechner'] | 2021-11-04 | null | http://proceedings.neurips.cc/paper/2021/hash/544defa9fddff50c53b71c43e0da72be-Abstract.html | http://proceedings.neurips.cc/paper/2021/file/544defa9fddff50c53b71c43e0da72be-Paper.pdf | neurips-2021-12 | ['safe-exploration'] | ['robots'] | [ 3.01526666e-01 7.89045513e-01 -3.31813961e-01 -1.54726774e-01
-6.83725893e-01 -6.17249012e-01 3.67679983e-01 5.35274250e-03
-4.18496639e-01 9.45925832e-01 -2.74869144e-01 -9.05424178e-01
-6.60533309e-01 -9.83391702e-01 -1.31529725e+00 -8.00777435e-01
-6.06202364e-01 4.22386706e-01 4.37241048e-01 -9.49737430e-02
-7.80464932e-02 2.80308306e-01 -1.20097971e+00 -1.98268831e-01
5.49211860e-01 1.09233820e+00 -4.63734716e-01 6.69606984e-01
8.15783262e-01 7.03138292e-01 -4.21325445e-01 1.37728930e-01
4.86602873e-01 8.66316780e-02 -5.23017645e-01 -3.48445535e-01
2.09669068e-01 -8.41940999e-01 -5.85966825e-01 1.63546598e+00
1.05322950e-01 3.35061431e-01 3.78773957e-01 -1.64862812e+00
8.35570917e-02 1.08708811e+00 1.02457754e-01 -4.59532231e-01
-2.80818254e-01 5.85494637e-01 6.24686480e-01 4.77658361e-02
1.69595674e-01 1.35741031e+00 7.38530278e-01 9.12450731e-01
-1.35948682e+00 -7.69928277e-01 4.15080488e-01 -2.27655634e-01
-1.05913818e+00 -2.81414300e-01 3.33062679e-01 -5.32465875e-01
7.12719560e-01 -5.80974445e-02 5.94606757e-01 1.15822446e+00
4.84082639e-01 4.52497363e-01 1.04126525e+00 -1.96138680e-01
8.79916906e-01 -9.73667800e-02 2.19529718e-01 5.63726962e-01
4.04974371e-01 1.12262177e+00 4.97567654e-02 -4.43675905e-01
5.48482835e-01 -2.91212425e-02 -8.44457150e-02 -5.25510550e-01
-9.38688040e-01 9.41906154e-01 -7.93628320e-02 -5.26682556e-01
-1.50071248e-01 9.50855196e-01 5.63433707e-01 5.65190136e-01
8.95067379e-02 3.48702550e-01 -5.79846323e-01 -1.29977927e-01
-5.94367564e-01 5.27171969e-01 1.15786219e+00 9.36134338e-01
3.51630628e-01 5.38868666e-01 -3.16157788e-01 -8.43043104e-02
4.16193515e-01 5.53623974e-01 -9.67794508e-02 -1.42598724e+00
2.47350231e-01 5.09357564e-02 5.40200531e-01 -4.22582179e-01
-5.31739742e-02 -2.34997392e-01 -5.43500364e-01 9.86831665e-01
6.16440058e-01 -7.80291080e-01 -8.34662497e-01 2.09675312e+00
3.47105801e-01 5.72702169e-01 3.05190176e-01 6.13571644e-01
-4.25325364e-01 6.99076295e-01 -2.67943889e-01 -3.18805814e-01
7.19764411e-01 -4.16557610e-01 -4.55890894e-01 7.39520714e-02
4.70414966e-01 2.04310119e-01 6.32877767e-01 9.16952133e-01
-1.03195703e+00 -9.44573432e-02 -1.39561415e+00 8.32623005e-01
-9.38945264e-02 -2.54223824e-01 1.55027583e-01 8.03145051e-01
-1.05108380e+00 1.12069964e+00 -1.11884582e+00 2.74970204e-01
2.85491407e-01 7.40066051e-01 1.88576579e-01 3.86775732e-01
-1.54109967e+00 9.36394811e-01 9.39220905e-01 2.30507702e-01
-2.08214378e+00 -6.83525264e-01 -7.21964478e-01 7.54126832e-02
1.06646681e+00 -1.78648904e-01 1.69295609e+00 -7.21491933e-01
-1.68963253e+00 -2.15622827e-01 7.20046401e-01 -1.18681431e+00
7.60661006e-01 -9.50566456e-02 -1.27044946e-01 -3.52042988e-02
-7.10070133e-01 5.31023920e-01 1.16646588e+00 -9.98940349e-01
-7.44376540e-01 3.27194780e-02 5.97043812e-01 -3.29897434e-01
-2.66160548e-01 -3.00109178e-01 2.32333884e-01 -2.30342597e-01
-5.29458880e-01 -1.16038632e+00 -6.10109329e-01 1.29038086e-02
-4.97345924e-01 -2.73867100e-01 8.86029005e-01 -2.70000249e-01
1.02425623e+00 -1.99383259e+00 -5.66009656e-02 7.15931416e-01
8.54475424e-03 1.31751597e-01 2.06523433e-01 2.74907678e-01
7.79722780e-02 -7.12923557e-02 -2.56393731e-01 1.29933313e-01
4.94140476e-01 4.53646660e-01 -9.05410469e-01 8.41352820e-01
1.16903685e-01 2.03428149e-01 -7.33853996e-01 -5.57403453e-02
5.00528254e-02 6.39805719e-02 -7.05908298e-01 1.02808639e-01
-9.81698751e-01 1.75329819e-02 -5.66712022e-01 -1.59696102e-01
3.53376925e-01 2.82585025e-01 2.79593199e-01 5.59843659e-01
1.73998792e-02 7.41944388e-02 -1.41577041e+00 9.97778177e-01
-1.96338192e-01 1.85542360e-01 2.04082981e-01 -9.41672802e-01
8.60486746e-01 4.97986436e-01 3.34172606e-01 -5.11049367e-02
5.01149952e-01 -1.27893118e-02 5.90692610e-02 -1.02432013e-01
2.61913687e-01 -3.17145884e-01 -3.00154597e-01 5.06380498e-01
-3.81113030e-03 -6.68341145e-02 -1.62856355e-01 -2.66126208e-02
1.13419592e+00 2.73648083e-01 -1.12320803e-01 -5.23556709e-01
3.87940675e-01 -2.09558874e-01 8.92243028e-01 1.05856037e+00
-2.49095112e-01 -1.94443926e-01 1.24048281e+00 -2.75992006e-01
-1.11125493e+00 -1.09962666e+00 5.65920249e-02 6.27216399e-01
-1.35460809e-01 -5.28099351e-02 -9.89303112e-01 -8.03903520e-01
1.98477253e-01 1.10615790e+00 -8.04604292e-01 -7.95914412e-01
-2.33260542e-01 -7.95096755e-02 8.69498432e-01 4.42214608e-01
1.09496549e-01 -7.36947656e-01 -1.02296031e+00 2.74546444e-01
6.43880606e-01 -5.91443300e-01 -3.95405859e-01 4.04063255e-01
-7.59758711e-01 -1.07601559e+00 -5.06023802e-02 -2.80952096e-01
5.65000355e-01 -7.56000519e-01 4.97472078e-01 -3.74381244e-01
2.37553596e-01 5.69092929e-01 4.34051216e-01 -7.11115956e-01
-9.36490715e-01 -1.55677125e-01 4.06133115e-01 -2.83398122e-01
-1.22119561e-01 -2.47852981e-01 -3.06247264e-01 2.15282142e-01
-8.63801122e-01 -1.78652495e-01 -1.90233305e-01 8.53210926e-01
4.34361875e-01 4.73067582e-01 6.67198479e-01 -7.59465456e-01
7.27619767e-01 -3.81304085e-01 -1.89533901e+00 3.52928936e-01
-8.82475436e-01 4.59276170e-01 7.85978258e-01 -7.31457829e-01
-8.13895643e-01 2.13597208e-01 2.48851731e-01 -6.70135677e-01
1.01895407e-02 3.45072180e-01 2.77378503e-02 8.81539732e-02
4.63593394e-01 -1.58088416e-01 5.73719740e-01 5.36189638e-02
7.36806020e-02 2.13289037e-01 5.18337309e-01 -1.22791791e+00
7.88768589e-01 7.30542392e-02 4.40049738e-01 -4.20420393e-02
-6.71380639e-01 3.33876222e-01 -4.59943712e-02 -5.27616918e-01
4.53099400e-01 -6.21467352e-01 -1.70922780e+00 2.97395825e-01
-7.98117459e-01 -8.56593847e-01 -6.79323256e-01 5.80244839e-01
-1.15203142e+00 -3.09976954e-02 -5.54175317e-01 -1.61995900e+00
-1.25322521e-01 -1.25388491e+00 5.59696794e-01 8.28695595e-02
4.24493998e-02 -7.96054661e-01 3.56391221e-01 -5.90022504e-01
2.53568143e-01 4.71453786e-01 9.46185827e-01 -8.54727030e-01
-4.28159416e-01 -2.00996548e-01 2.61419952e-01 7.00708568e-01
-5.64932704e-01 2.20510736e-01 -9.19683397e-01 -5.12273729e-01
1.99533999e-01 -6.91526890e-01 7.09169924e-01 4.40265089e-01
1.22481716e+00 -9.10917222e-01 -7.16499537e-02 2.55595237e-01
1.28670132e+00 5.72790563e-01 3.67396772e-01 2.00187206e-01
1.34516191e-02 6.59679890e-01 7.75805056e-01 6.19366884e-01
-4.26662154e-02 2.51973242e-01 1.04010320e+00 6.01723850e-01
8.86546195e-01 -4.22223508e-01 9.22262490e-01 -7.96127394e-02
2.81135738e-01 1.73850864e-01 -7.58462191e-01 3.55102658e-01
-2.07468653e+00 -9.25977230e-01 5.34805477e-01 2.72348022e+00
1.20925868e+00 6.57760322e-01 3.90316963e-01 1.55044928e-01
5.64862370e-01 -2.87778616e-01 -1.00892186e+00 -7.20375657e-01
5.81718504e-01 -7.20345974e-03 9.84634578e-01 7.75804818e-01
-9.57017183e-01 4.26326454e-01 5.95547104e+00 6.97428107e-01
-1.02047908e+00 -1.86978802e-01 5.91115236e-01 -1.50178894e-01
-2.60830343e-01 1.91990018e-01 -1.10692537e+00 3.58724743e-01
1.69916737e+00 -3.20291609e-01 8.14182281e-01 1.19898212e+00
2.70711064e-01 2.13409420e-02 -1.37930894e+00 5.02602160e-02
-6.51099980e-01 -1.10500145e+00 -5.71962535e-01 1.57353193e-01
6.35202467e-01 -5.43986112e-02 2.34683245e-01 7.37324834e-01
1.16234875e+00 -1.10745788e+00 1.09984493e+00 5.81870258e-01
7.27683544e-01 -1.31675684e+00 5.43538511e-01 6.78348899e-01
-5.14823616e-01 -5.27687311e-01 -1.80296749e-01 -7.77414292e-02
4.44955891e-03 3.35908979e-01 -1.04437590e+00 8.75103846e-02
3.64096761e-01 3.07007074e-01 -8.20155740e-02 9.34575260e-01
-7.72985294e-02 9.92068529e-01 -5.09472251e-01 -1.61074296e-01
5.53918242e-01 -2.37959743e-01 6.04956210e-01 7.55817235e-01
2.29855046e-01 -3.43390435e-01 4.51077551e-01 9.12738323e-01
2.59818733e-01 -8.67873311e-01 -8.63744915e-01 -1.25643641e-01
4.37350869e-01 8.31430793e-01 -3.55693847e-01 -3.76019299e-01
1.76017862e-02 -8.09346363e-02 1.51312292e-01 4.98308480e-01
-1.15778494e+00 -3.99809152e-01 6.34552240e-01 -4.89047021e-01
2.51696736e-01 -1.76744387e-01 -1.28638536e-01 -5.23694754e-01
-2.33170331e-01 -1.06333327e+00 5.23854673e-01 -2.68637776e-01
-9.10020888e-01 1.63606107e-01 4.04102355e-01 -9.94550109e-01
-8.10961306e-01 -6.87234342e-01 -4.39127743e-01 6.81962192e-01
-1.00390661e+00 -4.30426985e-01 5.37791669e-01 5.54271460e-01
2.20091827e-02 -2.31977366e-02 7.57856548e-01 -3.19902390e-01
-6.53431237e-01 3.59232068e-01 2.58156747e-01 -5.36208972e-02
3.74190509e-01 -1.45863163e+00 1.83542058e-01 8.42463553e-01
-5.52788138e-01 4.82487500e-01 1.21700907e+00 -5.78115404e-01
-1.57202053e+00 -1.51184678e+00 -6.68071285e-02 -6.81026801e-02
1.10962224e+00 -2.83640653e-01 -7.98394442e-01 9.23886716e-01
1.22030601e-01 1.38646409e-01 -1.74169272e-01 -6.95981532e-02
-4.09787476e-01 -3.04166436e-01 -1.19892001e+00 7.55529881e-01
5.45066833e-01 -2.15063319e-01 -4.10931408e-01 1.33243531e-01
1.10586059e+00 -5.76762795e-01 -9.43558037e-01 4.94454265e-01
7.24867046e-01 -3.70328516e-01 6.24901056e-01 -1.04377317e+00
1.11623637e-01 -4.07545179e-01 -1.18214644e-01 -1.38522947e+00
1.75367922e-01 -1.22764552e+00 -6.30846202e-01 8.12674701e-01
4.03349519e-01 -8.13739300e-01 6.62482917e-01 6.91158533e-01
-3.19179565e-01 -8.30004454e-01 -1.40176058e+00 -1.09449887e+00
5.61869383e-01 -7.16941357e-01 5.17620146e-01 3.20278317e-01
2.42043495e-01 -3.46587062e-01 -5.92498600e-01 5.11162043e-01
9.40149844e-01 -2.13751733e-01 2.91976035e-01 -1.05865550e+00
-7.45183945e-01 -4.09503251e-01 2.43248828e-02 -4.14538950e-01
5.47865808e-01 -4.33551610e-01 8.03477526e-01 -7.06244946e-01
-1.66917443e-01 -3.42379838e-01 -5.17090917e-01 5.53384244e-01
4.72668916e-01 -5.52897751e-01 4.03076299e-02 -5.93934834e-01
-8.10384452e-01 5.87089479e-01 8.74417543e-01 -2.21396267e-01
-8.21102262e-02 5.28006792e-01 -2.87953198e-01 7.48658419e-01
9.69070256e-01 -6.12444699e-01 -9.10546541e-01 8.74246061e-02
3.68310779e-01 5.87656200e-01 6.07040167e-01 -9.62124467e-01
3.86668026e-01 -7.15809643e-01 -1.93494096e-01 -5.72044730e-01
2.19672136e-02 -1.14593959e+00 1.87476203e-01 1.11085320e+00
-1.00135052e+00 -1.35791600e-01 2.49539107e-01 1.00750124e+00
2.20119625e-01 -4.47665513e-01 8.03106844e-01 2.52551585e-01
-1.52206272e-01 4.82374042e-01 -7.19853163e-01 6.84006661e-02
1.12325478e+00 3.05698037e-01 -3.78736734e-01 -4.27572429e-01
-7.15833366e-01 7.53559113e-01 1.63567156e-01 1.29390731e-01
6.38463974e-01 -9.27161992e-01 -1.24820501e-01 2.36724332e-01
-2.07842648e-01 1.70629546e-01 5.36543243e-02 6.60503745e-01
1.38707370e-01 3.26499104e-01 6.77031698e-03 -4.40999210e-01
-7.34668553e-01 7.30364919e-01 8.13817501e-01 -1.68245926e-01
-4.93007481e-01 1.31567210e-01 -1.86519474e-01 -3.78524780e-01
9.14979994e-01 -7.54581273e-01 9.40691382e-02 -4.39004213e-01
4.18821037e-01 4.18725014e-01 -2.24864557e-02 2.39452362e-01
-1.69614032e-02 -2.21931159e-01 7.25895911e-02 -6.43002748e-01
1.08486509e+00 3.22651088e-01 1.28538623e-01 6.12912238e-01
5.94674647e-01 -5.76055527e-01 -2.15004945e+00 -2.29907017e-02
2.49233440e-01 4.91722673e-02 6.47798851e-02 -6.34547412e-01
-7.62834847e-01 6.70674145e-01 5.98919094e-01 3.44020307e-01
8.65132153e-01 -5.13344467e-01 2.67099559e-01 8.91941547e-01
6.29312217e-01 -1.41177893e+00 -4.01406318e-01 9.00462925e-01
6.07869446e-01 -6.73768938e-01 -2.76355326e-01 3.54444891e-01
-4.43441272e-01 1.27571642e+00 7.48903275e-01 -5.87314546e-01
7.99043059e-01 8.24057758e-01 -5.87805033e-01 3.27591032e-01
-1.53680027e+00 4.17238235e-01 -9.80877876e-02 5.12679279e-01
-3.48007739e-01 9.51667950e-02 1.63913772e-01 6.82989657e-01
1.83338579e-02 4.15052414e-01 7.97291577e-01 1.03413427e+00
-7.69154191e-01 -6.59783840e-01 -4.15296823e-01 3.80646735e-01
-4.38204318e-01 3.43895674e-01 1.52219296e-01 7.59677410e-01
-2.59831011e-01 7.38793314e-01 -5.04763275e-02 -3.73553246e-01
2.52342790e-01 1.60483137e-01 2.95826733e-01 -3.80880207e-01
-3.97508532e-01 3.04265600e-02 3.62238497e-01 -7.47818291e-01
1.49970606e-01 -5.64785361e-01 -1.26386189e+00 -2.82232404e-01
-2.16767266e-01 1.96299404e-01 5.21279156e-01 1.02262616e+00
-4.28289175e-02 5.71577787e-01 6.86337829e-01 -4.09288406e-01
-1.96530676e+00 -7.14613676e-01 -6.52731955e-01 -3.97631198e-01
7.47349262e-01 -5.61796963e-01 -4.52913195e-01 -1.70985371e-01] | [4.5551228523254395, 2.225177049636841] |
7794d63f-34f8-4ec2-8fcb-e498a13df0ca | seetheseams-localized-detection-of-seam | 2108.12534 | null | https://arxiv.org/abs/2108.12534v1 | https://arxiv.org/pdf/2108.12534v1.pdf | SeeTheSeams: Localized Detection of Seam Carving based Image Forgery in Satellite Imagery | Seam carving is a popular technique for content aware image retargeting. It can be used to deliberately manipulate images, for example, change the GPS locations of a building or insert/remove roads in a satellite image. This paper proposes a novel approach for detecting and localizing seams in such images. While there are methods to detect seam carving based manipulations, this is the first time that robust localization and detection of seam carving forgery is made possible. We also propose a seam localization score (SLS) metric to evaluate the effectiveness of localization. The proposed method is evaluated extensively on a large collection of images from different sources, demonstrating a high level of detection and localization performance across these datasets. The datasets curated during this work will be released to the public. | ['B. S. Manjunath', 'Shivkumar Chandrasekaran', 'Lakshmanan Nataraj', 'Erik Rosten', 'Chandrakanth Gudavalli'] | 2021-08-28 | null | null | null | null | ['image-retargeting'] | ['computer-vision'] | [ 6.05549395e-01 -2.11204827e-01 -3.96227390e-02 -2.73174703e-01
-8.61364186e-01 -8.61847878e-01 8.13710392e-01 1.67277399e-02
-4.43745911e-01 6.19108558e-01 2.42647007e-01 -1.08722113e-01
2.26206146e-03 -6.89340055e-01 -7.79377520e-01 -7.25291193e-01
1.49079293e-01 -3.14600527e-01 6.69135511e-01 -2.87460417e-01
9.88269687e-01 8.78186047e-01 -1.76450455e+00 4.48049866e-02
5.75906575e-01 4.70075518e-01 5.96864820e-01 7.00245559e-01
1.40423164e-01 2.92823017e-01 -9.74145770e-01 -2.45362401e-01
3.85707498e-01 -2.46423855e-01 -6.07296288e-01 4.05047327e-01
6.86836064e-01 -2.94317633e-01 -1.47786200e-01 1.22763979e+00
5.61243415e-01 3.21592271e-01 3.19379896e-01 -1.01780677e+00
-7.71290183e-01 3.83701682e-01 -8.92668784e-01 5.62702537e-01
5.71335971e-01 1.53370602e-02 3.35031122e-01 -9.66682374e-01
6.83768809e-01 9.67080891e-01 5.65196633e-01 -7.69610563e-03
-1.13353944e+00 -6.10148787e-01 -2.27067158e-01 1.38154298e-01
-1.82298100e+00 -7.04918027e-01 7.10593045e-01 -3.02284688e-01
4.21811491e-01 7.60235190e-01 1.41194135e-01 7.70700037e-01
8.68200287e-02 2.47393593e-01 1.16718197e+00 -8.37055385e-01
2.64364153e-01 2.93048590e-01 -2.15347677e-01 6.06806338e-01
2.83117026e-01 1.15445301e-01 -5.99562407e-01 -1.77907765e-01
5.68201542e-01 -1.68318883e-01 -4.30859119e-01 -3.02912146e-01
-1.24133694e+00 7.14396656e-01 3.72269064e-01 3.92275810e-01
-6.94424808e-02 1.92141011e-01 3.11356068e-01 2.18118340e-01
5.15398443e-01 4.78395402e-01 1.45904750e-01 2.00282549e-03
-1.12394381e+00 8.56956467e-02 1.64689079e-01 1.03652930e+00
8.83747101e-01 -4.47345749e-02 -2.55730510e-01 7.60676026e-01
-1.62711397e-01 3.36602986e-01 4.48986620e-01 -1.08943903e+00
8.80811289e-02 3.45355392e-01 3.41938704e-01 -1.51049459e+00
-1.85609430e-01 1.22273989e-01 -4.50436234e-01 4.64973509e-01
4.71327035e-03 2.27201432e-01 -9.42371428e-01 1.31973934e+00
4.11331713e-01 2.04747975e-01 -3.46033216e-01 9.62068021e-01
5.65975726e-01 4.70543921e-01 -2.54883736e-01 1.55976579e-01
1.44899189e+00 -7.65344620e-01 -7.34062314e-01 -3.69847178e-01
4.71013486e-01 -1.16735375e+00 1.06378686e+00 1.76316068e-01
-7.94808447e-01 -4.29272115e-01 -1.08070219e+00 3.67739052e-02
-8.17324996e-01 9.08309296e-02 3.62327784e-01 1.05743527e+00
-1.20941746e+00 2.67402947e-01 -2.82609284e-01 -8.57935786e-01
1.53727442e-01 1.15446066e-02 -4.07795519e-01 -1.78118572e-01
-9.58427012e-01 1.02399015e+00 5.10369718e-01 -1.72471181e-01
-7.72523165e-01 -4.82255101e-01 -5.88993847e-01 -3.31706345e-01
3.84004056e-01 -1.94336295e-01 9.60399449e-01 -7.92364120e-01
-1.06341398e+00 1.22657621e+00 -1.19852416e-01 -3.09829503e-01
4.95442003e-01 2.23012920e-02 -7.67497540e-01 1.12950645e-01
5.25363505e-01 5.88001192e-01 1.18539310e+00 -1.57161486e+00
-7.88611293e-01 -2.37553000e-01 1.11771040e-01 7.18369484e-02
-1.81567028e-01 2.82978922e-01 -5.62289655e-01 -1.12364662e+00
1.06570885e-01 -8.78563166e-01 5.12088649e-03 1.02875821e-01
-7.07406819e-01 2.92194128e-01 1.19477677e+00 -8.00019979e-01
1.07424092e+00 -2.37068653e+00 -1.45746544e-01 2.13401869e-01
-2.44307548e-01 2.19980106e-01 -1.28533497e-01 7.41586268e-01
2.61304118e-02 3.40716690e-01 -4.07609284e-01 -3.22873741e-01
-3.19698215e-01 1.19765729e-01 -2.92516857e-01 6.38744891e-01
-2.18281180e-01 5.20171463e-01 -7.33400106e-01 -3.63239497e-01
5.32446682e-01 4.04607117e-01 4.43099327e-02 -1.77854434e-01
2.76215076e-01 3.89405489e-01 2.44547520e-02 8.61394823e-01
8.95393908e-01 3.79514545e-01 -2.94890493e-01 -3.09147239e-01
-4.51503485e-01 -7.46650100e-02 -1.20037901e+00 1.78754473e+00
-3.09687316e-01 9.02903736e-01 -1.47143111e-01 -6.10887468e-01
9.07368243e-01 4.30410057e-02 3.39821279e-02 -7.89273858e-01
-1.74880356e-01 1.95915420e-02 -7.65214443e-01 -5.11538923e-01
1.27249229e+00 3.23425293e-01 -2.92995900e-01 4.66133058e-01
-4.24166918e-01 -1.87339038e-01 2.40032613e-01 1.86413422e-01
9.95273173e-01 -1.33054599e-01 2.91630358e-01 -4.02243167e-01
4.66795862e-01 2.41958976e-01 7.38059878e-02 1.06256878e+00
-1.62905768e-01 9.27829206e-01 -3.30405861e-01 -3.65108937e-01
-1.05578685e+00 -9.37545121e-01 -1.96192458e-01 1.10540235e+00
6.48362517e-01 -2.40833595e-01 -7.51966953e-01 -5.26305497e-01
-7.63204023e-02 1.13065386e+00 -6.97840869e-01 -3.57213616e-01
-4.15687233e-01 -5.88252783e-01 6.46890700e-01 -3.76060745e-03
8.20676565e-01 -7.36657023e-01 -8.43829513e-01 -1.13607235e-01
-3.60586941e-01 -9.77922559e-01 -7.57445216e-01 -1.90850720e-01
-5.50045907e-01 -1.01081848e+00 -5.65404892e-01 -7.41190016e-01
7.98878849e-01 1.10509908e+00 7.58888483e-01 3.62881571e-01
-6.12255096e-01 4.56042737e-01 -5.68106651e-01 -1.19686648e-01
-4.42897469e-01 -8.54548290e-02 -5.02267331e-02 2.66684033e-02
9.19835046e-02 -2.59964228e-01 -8.94980490e-01 6.60763860e-01
-1.30871058e+00 -1.62809864e-01 2.58692473e-01 2.65825421e-01
3.67889583e-01 4.36973810e-01 1.99841827e-01 -6.40883446e-01
7.14644611e-01 -2.97842294e-01 -4.82032090e-01 2.96743810e-01
-5.44761121e-01 -2.82205164e-01 -4.24955189e-02 -1.74587876e-01
-9.80649590e-01 9.60039720e-02 7.24561438e-02 -3.42326090e-02
-3.89997065e-01 2.67646343e-01 5.91267273e-02 -7.74972796e-01
8.36513638e-01 2.97103405e-01 -3.01743120e-01 -5.59805453e-01
7.10211813e-01 6.71517313e-01 1.06543887e+00 -9.40357745e-02
1.06719637e+00 8.79770875e-01 -2.63864398e-01 -9.83336508e-01
-2.60740250e-01 -5.19505680e-01 -6.02563143e-01 -3.81408811e-01
5.64077377e-01 -7.21367121e-01 -7.63107389e-02 2.02260107e-01
-8.85330796e-01 2.83670556e-02 -1.14813097e-01 4.26759981e-02
-2.17148557e-01 7.50831127e-01 -5.66610955e-02 -6.56225860e-01
-7.77892545e-02 -9.13528740e-01 1.12554002e+00 3.34090561e-01
-2.01856837e-01 -7.76413381e-01 3.52870347e-03 2.67939806e-01
6.40097141e-01 4.87065703e-01 3.63596708e-01 -8.99820477e-02
-5.79134762e-01 -4.47592854e-01 -2.14484051e-01 -1.68657541e-01
6.68474555e-01 1.04913771e-01 -9.29607987e-01 -4.20928419e-01
-1.30466059e-01 2.33381405e-01 8.11192572e-01 1.22808203e-01
1.04802167e+00 -3.07692260e-01 -5.14338195e-01 3.80646765e-01
1.54478157e+00 3.42350185e-01 1.03264463e+00 9.87164557e-01
3.51449221e-01 4.68123138e-01 8.32449138e-01 3.99104863e-01
1.96786329e-01 1.00138307e+00 5.74210167e-01 -2.33254552e-01
-3.04618448e-01 -1.44165933e-01 2.39677191e-01 1.72888085e-01
9.89573374e-02 -3.50744009e-01 -7.72010744e-01 8.35891128e-01
-1.62101173e+00 -8.85244966e-01 -3.51256520e-01 2.47693658e+00
4.28620368e-01 -1.40383691e-01 -1.32355183e-01 1.25789735e-02
1.12020314e+00 2.77310461e-01 -2.20454291e-01 -3.78479779e-01
-3.00929457e-01 -1.87385857e-01 1.09376347e+00 4.98514205e-01
-1.12485170e+00 9.77057278e-01 6.88900948e+00 8.75364184e-01
-8.74960959e-01 2.83829451e-01 2.41881400e-01 1.83321834e-01
-2.37841010e-01 2.41443604e-01 -4.58121330e-01 7.05958784e-01
4.33942258e-01 -3.75518873e-02 3.28909427e-01 6.54653251e-01
4.36201483e-01 -8.23808014e-01 -3.79021466e-01 8.67956460e-01
4.23030347e-01 -1.32197213e+00 -1.06905155e-01 -1.93272635e-01
6.48939908e-01 -1.97548643e-01 1.45520702e-01 -4.15926993e-01
2.67500937e-01 -6.22685373e-01 7.18971908e-01 5.72500408e-01
7.75084555e-01 -8.10869575e-01 4.35068607e-01 1.30860418e-01
-9.70904291e-01 2.26653323e-01 -4.26147252e-01 2.06209898e-01
3.36537451e-01 4.97804761e-01 -8.15755546e-01 5.17711759e-01
1.15981805e+00 2.14190215e-01 -1.27706504e+00 1.43984127e+00
-1.39040664e-01 3.59353095e-01 -2.30397552e-01 3.04827809e-01
-1.98322441e-02 -2.10635364e-01 8.17727447e-01 1.28931689e+00
6.08058035e-01 -2.44461641e-01 -1.53008610e-01 6.95909858e-01
9.87118855e-02 1.60726588e-02 -9.92951393e-01 2.16669068e-01
7.69030035e-01 1.18182206e+00 -1.04531741e+00 -1.12019397e-01
-2.68016309e-01 1.61404073e+00 -1.20498441e-01 2.98024744e-01
-8.78013194e-01 -6.80052161e-01 4.97239530e-01 1.26418754e-01
3.84055257e-01 -3.37799370e-01 -6.72455654e-02 -8.40369046e-01
-2.19906084e-02 -5.77006459e-01 3.26203376e-01 -1.12123621e+00
-7.31491804e-01 2.61290133e-01 3.11410904e-01 -1.06853330e+00
2.58557618e-01 -1.54657392e-02 -5.82258761e-01 4.93788123e-01
-1.31811976e+00 -1.10664260e+00 -7.20894516e-01 4.98001009e-01
6.44437671e-01 -5.97145297e-02 7.02539802e-01 3.86435211e-01
-4.73323703e-01 5.81572592e-01 2.64502496e-01 -9.89679620e-02
9.60775793e-01 -8.18632483e-01 7.61286378e-01 1.39743185e+00
1.94969580e-01 6.43664241e-01 1.11278379e+00 -7.07409978e-01
-1.26019418e+00 -1.17830241e+00 5.80091417e-01 -3.80505800e-01
2.64714420e-01 -3.95278931e-01 -9.40286219e-01 6.76784933e-01
4.69655573e-01 -2.82606632e-01 3.50325227e-01 -4.99056101e-01
-2.80701548e-01 1.43582672e-01 -1.46634889e+00 7.30250359e-01
1.09238327e+00 -4.69704121e-01 -4.66189295e-01 5.74404180e-01
4.60680246e-01 -3.66609573e-01 -6.77242815e-01 2.48044744e-01
2.12825745e-01 -1.15621459e+00 1.20117950e+00 2.29665697e-01
-1.18015386e-01 -9.08899486e-01 -3.46453190e-01 -1.22352421e+00
-3.24874640e-01 -6.59336746e-01 3.32582086e-01 1.59156454e+00
8.45171362e-02 -5.46659529e-01 5.85276484e-01 5.15797436e-01
-1.10947192e-01 3.26959699e-01 -1.03208816e+00 -8.04621935e-01
-5.08213937e-01 -1.46676421e-01 7.00142264e-01 1.14969432e+00
-2.97704816e-01 -2.71900505e-01 -6.97802424e-01 4.16629195e-01
6.88760877e-01 -3.78074795e-02 9.56110775e-01 -5.77277839e-01
1.54440373e-01 -2.56958723e-01 -7.91673779e-01 -5.46395183e-01
-3.15620124e-01 -6.72308981e-01 8.92255232e-02 -1.43770337e+00
4.84026931e-02 -3.62744957e-01 1.39421239e-01 3.50042671e-01
-1.64528295e-01 7.78851271e-01 -3.65477018e-02 4.12890285e-01
-3.99425566e-01 2.63952315e-01 5.76465070e-01 -1.83415636e-01
-8.26213881e-02 -3.13091874e-01 -6.15396082e-01 4.89510268e-01
1.45260012e+00 -6.74211740e-01 -2.53738403e-01 -4.63125736e-01
4.74057207e-03 -3.48292977e-01 7.47461915e-01 -1.12421882e+00
3.53897482e-01 -2.16008231e-01 2.00793505e-01 -7.03580320e-01
2.48087183e-01 -8.04239511e-01 5.29177248e-01 3.85558397e-01
-1.44374847e-01 2.78300107e-01 3.45389634e-01 8.27826023e-01
-1.91005133e-02 -4.83788908e-01 8.32792640e-01 -2.38265336e-01
-1.42779458e+00 -2.74988204e-01 -6.46753013e-01 -3.81350845e-01
1.39845884e+00 -6.59500539e-01 -5.91429889e-01 -4.37470168e-01
-1.53139099e-01 -2.62855589e-01 1.02894306e+00 7.55268335e-01
7.59720206e-01 -1.36900342e+00 -4.74377662e-01 2.15953723e-01
5.32169819e-01 -4.89676714e-01 1.01053365e-01 6.29685640e-01
-8.34835768e-01 -4.49457839e-02 -2.60209769e-01 -4.33053970e-01
-1.48645234e+00 7.14263499e-01 2.22913712e-01 6.53830111e-01
-7.73422122e-01 5.88373065e-01 -8.37241262e-02 -3.86283457e-01
-1.02257974e-01 1.70094028e-01 4.83434945e-02 -2.14095756e-01
7.98165023e-01 5.65037310e-01 3.00003201e-01 -9.64394927e-01
-4.70152885e-01 6.39226854e-01 -1.02610402e-01 -1.95390329e-01
8.88832152e-01 -8.85373652e-01 -2.39962831e-01 2.61969537e-01
1.05092800e+00 2.40675494e-01 -8.91053915e-01 -1.49376348e-01
3.04540962e-01 -1.13166213e+00 1.63377434e-01 -6.47807539e-01
-9.11040008e-01 2.51151055e-01 1.17129588e+00 2.23352611e-01
1.14916754e+00 7.30345072e-03 5.17121553e-01 1.87091455e-01
6.02251291e-01 -1.25167763e+00 -6.55532703e-02 -1.68837026e-01
9.69304383e-01 -1.19989932e+00 3.11227530e-01 -5.21969378e-01
-5.47127008e-01 9.48977709e-01 2.71834999e-01 2.43403092e-02
3.33768278e-01 2.57978559e-01 2.42956411e-02 -2.12351367e-01
5.72737195e-02 -2.17715174e-01 -5.00134155e-02 8.78421545e-01
6.36737198e-02 -6.08975850e-02 -3.51522267e-01 -4.69428241e-01
-4.28167768e-02 -2.45829299e-01 9.22924817e-01 1.33565938e+00
-7.82680571e-01 -9.67670679e-01 -8.17774296e-01 1.29044265e-01
-3.09500843e-01 -1.05445916e-02 -7.11936295e-01 8.50343466e-01
-1.00913808e-01 1.30057204e+00 -5.38872033e-02 -3.91619891e-01
3.95397365e-01 -1.20678455e-01 2.25356326e-01 -2.90179491e-01
-3.26829046e-01 -2.45609939e-01 6.99240118e-02 -6.43380821e-01
-7.69949973e-01 -6.09522820e-01 -8.41356099e-01 -4.69867378e-01
-4.32289273e-01 -1.37443647e-01 9.03600395e-01 4.42588806e-01
5.21983445e-01 1.36613101e-01 6.45745397e-01 -9.01769161e-01
9.51340050e-02 -5.79589784e-01 -7.51774609e-01 5.97267032e-01
3.73354197e-01 -6.38879478e-01 -4.77857739e-01 3.61591637e-01] | [11.148996353149414, -1.1957578659057617] |
65f9ea5b-64c4-4dde-a09b-cfd061b00fa4 | limitations-of-deep-neural-networks-a | 2012.15754 | null | https://arxiv.org/abs/2012.15754v1 | https://arxiv.org/pdf/2012.15754v1.pdf | Limitations of Deep Neural Networks: a discussion of G. Marcus' critical appraisal of deep learning | Deep neural networks have triggered a revolution in artificial intelligence, having been applied with great results in medical imaging, semi-autonomous vehicles, ecommerce, genetics research, speech recognition, particle physics, experimental art, economic forecasting, environmental science, industrial manufacturing, and a wide variety of applications in nearly every field. This sudden success, though, may have intoxicated the research community and blinded them to the potential pitfalls of assigning deep learning a higher status than warranted. Also, research directed at alleviating the weaknesses of deep learning may seem less attractive to scientists and engineers, who focus on the low-hanging fruit of finding more and more applications for deep learning models, thus letting short-term benefits hamper long-term scientific progress. Gary Marcus wrote a paper entitled Deep Learning: A Critical Appraisal, and here we discuss Marcus' core ideas, as well as attempt a general assessment of the subject. This study examines some of the limitations of deep neural networks, with the intention of pointing towards potential paths for future research, and of clearing up some metaphysical misconceptions, held by numerous researchers, that may misdirect them. | ['Stefanos Tsimenidis'] | 2020-12-22 | null | null | null | null | ['misconceptions'] | ['miscellaneous'] | [ 1.44102469e-01 3.58037889e-01 -2.74827212e-01 -2.84312308e-01
-1.19261913e-01 -1.84682116e-01 5.72869956e-01 3.91721427e-02
-6.15220428e-01 7.11206853e-01 3.01318884e-01 -7.79604673e-01
-3.52767348e-01 -7.63527632e-01 -4.57566023e-01 -8.12245846e-01
-2.78506503e-02 2.38417342e-01 -6.81556314e-02 -1.60808042e-01
5.90734601e-01 6.35347247e-01 -1.24063110e+00 1.34728640e-01
4.57592309e-01 7.88680911e-01 2.15827357e-02 1.64022073e-01
-1.17071815e-01 1.13268387e+00 -6.86880112e-01 -5.38431108e-01
-2.51189291e-01 -1.54402539e-01 -8.14106584e-01 -2.15795830e-01
-8.48950148e-02 -7.62591884e-02 -2.16525763e-01 1.01997638e+00
5.15076458e-01 -5.22660241e-02 4.76887316e-01 -8.46375942e-01
-9.45708334e-01 3.44790578e-01 -4.51554656e-01 3.80750477e-01
-2.45305464e-01 3.17544192e-01 7.63114274e-01 -4.51242894e-01
4.05126154e-01 1.10255134e+00 7.20996618e-01 6.47443533e-01
-6.51329696e-01 -6.12626314e-01 1.17850944e-01 2.66190529e-01
-9.61424828e-01 -4.21219349e-01 5.85458100e-01 -6.20441914e-01
1.01831996e+00 2.24041149e-01 5.98656416e-01 1.40990424e+00
8.82842064e-01 5.57124197e-01 1.07673883e+00 -1.66160643e-01
3.32451910e-01 9.77327861e-03 8.92956257e-02 6.85983419e-01
5.22806227e-01 2.95546889e-01 -1.26886845e-01 2.55275872e-02
5.68196893e-01 -1.28207952e-01 -9.10674036e-02 1.15247823e-01
-1.07076287e+00 1.01638162e+00 3.28303874e-01 8.50842476e-01
-5.42574406e-01 -5.08226827e-02 6.01585209e-01 2.61599392e-01
3.57706159e-01 6.90279484e-01 -5.40077031e-01 -2.11831897e-01
-4.54091400e-01 3.43760878e-01 6.99189544e-01 1.71013787e-01
3.47661048e-01 4.02950048e-01 4.45098549e-01 5.94503403e-01
1.38431221e-01 2.99527287e-01 8.41899395e-01 -1.05690992e+00
-1.93045825e-01 4.10116404e-01 -5.09431511e-02 -1.26761043e+00
-8.35628271e-01 -6.15755498e-01 -1.04067099e+00 3.36404264e-01
1.71676069e-01 -2.65106201e-01 -6.31132245e-01 1.39947140e+00
-6.90546408e-02 -1.88923851e-01 1.07538044e-01 1.00125766e+00
8.63924444e-01 4.49442565e-01 2.89483488e-01 9.98008437e-03
1.24119210e+00 -5.49886346e-01 -6.50154173e-01 -4.44681346e-01
4.41111803e-01 -7.02078700e-01 8.83232653e-01 7.62365222e-01
-8.96910846e-01 -5.03065228e-01 -1.03677166e+00 9.11549106e-02
-5.13081014e-01 -2.76307732e-01 1.07237184e+00 7.91696489e-01
-6.78404093e-01 7.69216895e-01 -1.12440240e+00 -5.21937549e-01
4.51545864e-01 3.68725270e-01 -1.20126300e-01 4.99304682e-02
-1.18702531e+00 1.36278176e+00 3.34172755e-01 3.11431497e-01
-5.32067776e-01 -2.41415843e-01 -7.38469720e-01 -5.26158232e-03
3.68468851e-01 -5.57599783e-01 1.08668089e+00 -8.51695180e-01
-1.33142900e+00 8.75912666e-01 3.98958847e-02 -7.47360885e-01
8.48384723e-02 -1.86138507e-02 -9.03073192e-01 -1.85947359e-01
8.06155279e-02 6.00764155e-01 3.91883790e-01 -8.44244242e-01
-5.56440592e-01 -5.83770216e-01 4.59647141e-02 6.84356540e-02
-2.12661639e-01 4.89886180e-02 1.31635293e-01 -4.80854154e-01
9.59914923e-02 -7.61522353e-01 -3.77333134e-01 -3.42998207e-01
-9.56474096e-02 -4.49027002e-01 7.27191687e-01 -3.24160188e-01
6.80937409e-01 -2.04520226e+00 -1.42152861e-01 -1.67307869e-01
3.46299052e-01 4.29642379e-01 -2.24670246e-02 3.26060891e-01
-6.66747689e-02 3.25115144e-01 -3.14975716e-02 4.18388814e-01
-1.88420862e-01 2.74119139e-01 -1.92715079e-01 5.14426947e-01
3.08551639e-01 1.06018794e+00 -9.85234797e-01 -4.61855419e-02
5.56243360e-01 6.48795605e-01 -1.76726654e-02 -3.88902396e-01
-3.57680172e-02 2.94048578e-01 -5.46569943e-01 5.45152426e-01
2.82985777e-01 -3.76002371e-01 1.85468659e-01 7.58813787e-03
-2.50769973e-01 4.92924631e-01 -5.69612265e-01 1.17405295e+00
-3.32049698e-01 1.05991006e+00 -1.65896129e-03 -1.44598198e+00
7.77947724e-01 3.11476529e-01 5.60517430e-01 -1.05822802e+00
4.04053569e-01 2.38447368e-01 5.14796853e-01 -9.14608538e-01
3.80209565e-01 -5.70544004e-01 1.52401522e-01 3.52021754e-01
-2.17360109e-01 1.42808050e-01 -2.25878730e-01 -2.49939591e-01
8.81660759e-01 -4.15055938e-02 1.78526133e-01 -2.79851943e-01
3.20750803e-01 -2.89142504e-02 3.67284149e-01 5.72419524e-01
-5.01129627e-01 2.12250084e-01 5.04569829e-01 -9.41137612e-01
-7.61486292e-01 -7.28776217e-01 -2.80221462e-01 9.00447369e-01
-1.35218069e-01 1.22817531e-02 -6.15724862e-01 -3.51157039e-01
-2.58106172e-01 7.56365120e-01 -6.92902803e-01 -3.81926656e-01
-4.54610676e-01 -1.18116939e+00 5.56769848e-01 4.43282545e-01
3.70888203e-01 -1.33433259e+00 -1.05012918e+00 1.14011705e-01
8.41360167e-02 -1.09169161e+00 5.34350574e-01 3.92910242e-01
-9.48636770e-01 -1.03077805e+00 -6.13940001e-01 -6.95771754e-01
1.86623126e-01 1.55699894e-01 8.69454145e-01 1.89300597e-01
-1.41993985e-01 5.22332639e-02 -1.22981533e-01 -9.21261907e-01
-6.19445026e-01 1.90951809e-01 1.45737261e-01 -5.86770952e-01
9.31236744e-01 -4.88292009e-01 -5.08878052e-01 8.52751285e-02
-8.34524810e-01 -2.95071274e-01 8.11638594e-01 7.57509291e-01
-1.63616642e-01 4.19766866e-02 1.15318334e+00 -9.58828926e-01
6.37612879e-01 -5.49860120e-01 -6.72689453e-02 -1.18831560e-01
-9.98081863e-01 -2.16334715e-01 4.33261454e-01 -1.47197679e-01
-7.86553025e-01 -7.96888053e-01 -5.35042763e-01 1.05825275e-01
-2.67834276e-01 6.81918681e-01 5.36916591e-02 -8.09883997e-02
1.01212621e+00 6.16402179e-02 2.85134017e-01 -2.61725277e-01
-1.31276483e-03 7.62598395e-01 5.25587857e-01 -3.13791573e-01
3.36692870e-01 4.06049639e-01 -7.78809488e-02 -1.33198583e+00
-7.74312496e-01 -1.02438934e-01 -2.24586010e-01 -5.52663058e-02
8.71110082e-01 -5.83870232e-01 -7.19519317e-01 3.83089632e-01
-1.12590671e+00 -1.13082096e-01 -1.31367087e-01 5.76825023e-01
-2.17352971e-01 3.17126542e-01 -5.60967445e-01 -4.83147204e-01
-1.04093097e-01 -1.23485625e+00 4.06334251e-01 3.87663126e-01
-5.29738963e-01 -1.24843848e+00 -1.74770907e-01 6.10965312e-01
6.34522915e-01 2.15209439e-01 1.12757862e+00 -6.51026726e-01
-2.95742244e-01 -3.64740640e-01 -1.25721186e-01 5.58531642e-01
3.30845535e-01 -1.34754136e-01 -1.34541380e+00 1.20772205e-01
3.73708338e-01 -4.94585663e-01 7.58200645e-01 5.77667117e-01
1.31931472e+00 -1.75121427e-01 -2.50598401e-01 3.14018339e-01
1.09805882e+00 6.95492327e-01 6.89315557e-01 6.28147364e-01
4.62677717e-01 6.93245113e-01 3.50124128e-02 5.38320467e-02
2.24597082e-01 1.30977869e-01 4.66209352e-01 -2.33027771e-01
-1.28611373e-02 2.93629736e-01 1.95324659e-01 6.76893950e-01
-2.40582526e-01 -2.64644623e-01 -9.69455421e-01 3.78850490e-01
-1.51374221e+00 -1.07133269e+00 -1.79068252e-01 1.89804411e+00
3.11555207e-01 5.61162710e-01 6.15722174e-03 1.07269973e-01
4.58476126e-01 3.09746325e-01 -5.22498608e-01 -8.75864685e-01
-1.23936117e-01 2.65723467e-01 2.90373832e-01 3.80358815e-01
-8.60486686e-01 7.92940378e-01 7.39010429e+00 5.24564266e-01
-1.55852771e+00 -2.50160322e-02 8.45621705e-01 1.72176719e-01
-2.86622852e-01 -3.18262070e-01 -2.88883805e-01 4.95395988e-01
1.24487579e+00 -1.50199667e-01 2.07880154e-01 7.79783964e-01
4.44254816e-01 -2.41228834e-01 -8.11014295e-01 5.25683284e-01
3.29196006e-02 -1.63409555e+00 -1.32911250e-01 1.99738175e-01
4.73213643e-01 4.54916567e-01 2.43848592e-01 2.97191650e-01
9.22041852e-03 -1.29555154e+00 2.73527473e-01 1.67875051e-01
2.06000909e-01 -7.86397576e-01 9.27099109e-01 3.97390038e-01
-1.53944641e-01 -1.74326494e-01 -4.55501944e-01 -7.26070881e-01
-1.76298618e-01 6.05162144e-01 -8.19583952e-01 2.87202716e-01
4.62201804e-01 2.00783059e-01 -3.12115997e-01 7.18854427e-01
7.17248693e-02 8.91642869e-01 -2.28248490e-03 -2.98663408e-01
6.12877369e-01 3.66213694e-02 2.97501981e-01 1.11014163e+00
-1.40577585e-01 2.52688862e-02 -3.90602171e-01 8.35997880e-01
1.63891628e-01 -8.84442478e-02 -7.10204840e-01 -4.98299479e-01
1.70937002e-01 1.11609328e+00 -1.06315100e+00 -1.34874910e-01
-6.81686997e-01 5.20819962e-01 -1.53574973e-01 3.30383569e-01
-5.62167704e-01 -4.29047614e-01 5.30489326e-01 1.40322760e-01
-1.32777855e-01 -6.35879263e-02 -9.09156203e-01 -8.92244697e-01
-1.88192934e-01 -9.60885286e-01 9.33028944e-03 -5.73791742e-01
-8.64774644e-01 4.60215241e-01 -2.49041602e-01 -6.62570894e-01
-2.29483470e-01 -9.21740651e-01 -6.07497096e-01 7.39617884e-01
-1.35852313e+00 -8.38978231e-01 6.10106997e-02 -2.23250881e-01
5.45661211e-01 -4.72234428e-01 8.58479977e-01 2.87321031e-01
-6.23244643e-01 1.42486855e-01 1.45059526e-01 1.47801653e-01
4.71519083e-01 -7.63147533e-01 4.83973920e-01 4.55978781e-01
7.63991848e-02 6.46826088e-01 9.14820313e-01 -3.36494446e-01
-1.16751313e+00 -8.33489656e-01 1.03962481e+00 -5.34710407e-01
6.99391901e-01 1.20453559e-01 -8.81845653e-01 7.23161757e-01
3.78549308e-01 -5.16191959e-01 5.91137230e-01 5.60782075e-01
5.82274720e-02 5.66596873e-02 -9.09253657e-01 6.10248387e-01
2.58212477e-01 -2.94316292e-01 -6.97543800e-01 3.54059100e-01
4.22587395e-01 -1.74530849e-01 -6.78895116e-01 4.15384740e-01
8.36402178e-01 -1.10018098e+00 8.17235887e-01 -7.29818285e-01
7.69879162e-01 2.22562090e-01 8.70853886e-02 -9.62627947e-01
-3.98423612e-01 -2.82122105e-01 2.54739910e-01 7.13958204e-01
2.83291280e-01 -7.36929059e-01 1.03217113e+00 5.69248974e-01
-4.07448471e-01 -1.18945444e+00 -8.76639605e-01 -5.85918605e-01
5.92426240e-01 -5.93486011e-01 3.57499301e-01 1.10487771e+00
2.07517315e-02 6.26636267e-01 -1.23309165e-01 -9.44036171e-02
3.56256783e-01 -2.74953067e-01 3.15099984e-01 -1.29714608e+00
2.73893718e-02 -8.07470620e-01 -5.79719245e-01 -5.15303969e-01
9.27920789e-02 -6.86316729e-01 -2.39513338e-01 -1.57315803e+00
8.22249502e-02 -1.38709038e-01 -4.29668814e-01 4.62126851e-01
1.28735930e-01 2.73734748e-01 -4.62422483e-02 -1.54312681e-02
-2.45475173e-01 1.02136724e-01 1.26513171e+00 -3.43929261e-01
3.30392160e-02 3.00810970e-02 -1.50700212e+00 1.17846441e+00
9.30301726e-01 -1.93289846e-01 -3.78003627e-01 -4.72632706e-01
4.96662110e-01 -2.99560338e-01 5.11129498e-01 -1.07547319e+00
2.53928695e-02 -4.35121864e-01 7.28041708e-01 -1.69644415e-01
1.64036363e-01 -6.62280560e-01 -6.03274480e-02 7.28098214e-01
-3.25366348e-01 -6.55344054e-02 3.22823256e-01 1.15217388e-01
-5.34447767e-02 -3.56791258e-01 9.10581529e-01 -4.14674282e-01
-8.67816448e-01 -4.25012298e-02 -8.38354468e-01 -1.49958879e-01
8.96172523e-01 -3.34734350e-01 -3.41761470e-01 -3.00441831e-01
-6.53020978e-01 2.05177292e-01 3.75361145e-01 6.05115831e-01
4.62463915e-01 -8.47211659e-01 -3.50401908e-01 5.65634444e-02
-2.05046117e-01 -4.50877659e-02 4.88973826e-01 7.28494525e-01
-4.63195264e-01 7.33246028e-01 -2.82071233e-01 -3.51403117e-01
-7.13680923e-01 5.60367942e-01 3.84726346e-01 1.34702235e-01
-8.64208400e-01 7.26069093e-01 2.11891174e-01 -2.51569271e-01
3.37233156e-01 -3.21643978e-01 -3.61972243e-01 -6.51486367e-02
4.12755013e-01 5.30650437e-01 3.34938824e-01 -3.23393583e-01
-4.72194046e-01 2.40623608e-01 -3.33593547e-01 4.79684956e-03
1.36800516e+00 1.88192576e-01 1.09071285e-02 7.05004096e-01
8.93200994e-01 -3.76341075e-01 -6.98022544e-01 2.07446560e-01
7.85692185e-02 6.11498393e-02 3.92176151e-01 -1.11319816e+00
-8.51223409e-01 1.22187245e+00 5.41610599e-01 2.91396111e-01
9.39367175e-01 -1.37225911e-01 8.45642328e-01 7.23103344e-01
2.43394613e-01 -1.19388700e+00 -3.72066014e-02 5.09759665e-01
5.96255064e-01 -1.32186997e+00 1.92227498e-01 2.26319879e-01
-6.01078331e-01 1.23144424e+00 3.32018167e-01 1.22763410e-01
5.13380349e-01 3.29977542e-01 2.56097555e-01 -4.81106550e-01
-7.56967902e-01 7.19160661e-02 -1.07595541e-01 6.57151163e-01
9.12218153e-01 6.39818667e-04 -6.56067073e-01 3.36766928e-01
-1.40651762e-01 3.44545573e-01 5.85520923e-01 6.78680837e-01
-7.95032978e-01 -1.02492642e+00 -3.08621258e-01 6.76865995e-01
-8.84575546e-01 2.50549261e-02 -3.03405821e-01 1.01249158e+00
3.58333230e-01 7.79964745e-01 1.96905151e-01 -4.42336053e-01
-3.09454761e-02 1.22021057e-01 4.20752853e-01 -3.20477486e-01
-2.89714754e-01 3.75054367e-02 1.45758137e-01 -2.77416259e-01
-4.69298661e-01 -5.52933156e-01 -1.18393958e+00 -4.59791273e-01
-7.65028149e-02 2.95588195e-01 9.58890617e-01 1.31994915e+00
2.32690677e-01 5.31650960e-01 3.36615354e-01 -5.25795579e-01
-6.34597778e-01 -9.95224833e-01 -4.40833330e-01 -1.29147649e-01
4.53090727e-01 -4.50435489e-01 -1.06451899e-01 -1.57254338e-01] | [8.985457420349121, 6.430929660797119] |
e75c7908-4c97-4e0d-b03e-6e1aa7477622 | illumination-invariant-active-camera | 2204.06580 | null | https://arxiv.org/abs/2204.06580v1 | https://arxiv.org/pdf/2204.06580v1.pdf | Illumination-Invariant Active Camera Relocalization for Fine-Grained Change Detection in the Wild | Active camera relocalization (ACR) is a new problem in computer vision that significantly reduces the false alarm caused by image distortions due to camera pose misalignment in fine-grained change detection (FGCD). Despite the fruitful achievements that ACR can support, it still remains a challenging problem caused by the unstable results of relative pose estimation, especially for outdoor scenes, where the lighting condition is out of control, i.e., the twice observations may have highly varied illuminations. This paper studies an illumination-invariant active camera relocalization method, it improves both in relative pose estimation and scale estimation. We use plane segments as an intermediate representation to facilitate feature matching, thus further boosting pose estimation robustness and reliability under lighting variances. Moreover, we construct a linear system to obtain the absolute scale in each ACR iteration by minimizing the image warping error, thus, significantly reduce the time consume of ACR process, it is nearly $1.6$ times faster than the state-of-the-art ACR strategy. Our work greatly expands the feasibility of real-world fine-grained change monitoring tasks for cultural heritages. Extensive experiments tests and real-world applications verify the effectiveness and robustness of the proposed pose estimation method using for ACR tasks. | ['Qian Zhang', 'Wei Feng', 'Nan Li'] | 2022-04-13 | null | null | null | null | ['camera-relocalization'] | ['computer-vision'] | [ 4.26657736e-01 -3.38160485e-01 9.99113545e-02 -2.31451720e-01
-7.18775928e-01 -7.04309881e-01 1.99134022e-01 -1.73416317e-01
-6.20844424e-01 4.27313656e-01 1.43570155e-01 2.30717972e-01
-3.00068762e-02 -6.04639471e-01 -8.01209688e-01 -9.62540627e-01
3.17405522e-01 1.69852786e-02 5.43990612e-01 -2.69618124e-01
5.30625045e-01 7.27953613e-01 -1.48699009e+00 -4.21114594e-01
9.09049988e-01 9.51375544e-01 3.34186345e-01 5.51609695e-01
3.36584359e-01 3.02541167e-01 -3.94126564e-01 -3.09444845e-01
4.31334764e-01 2.69632876e-01 -2.01296911e-01 4.87040907e-01
9.11547482e-01 -6.71701312e-01 -2.19102234e-01 1.26561821e+00
6.67852938e-01 1.97325304e-01 1.81946859e-01 -1.19435287e+00
-3.18992376e-01 -1.90027148e-01 -1.16648376e+00 3.40561897e-01
4.85345989e-01 1.09125361e-01 5.61810851e-01 -9.37513113e-01
5.39748251e-01 1.33712137e+00 8.64880025e-01 1.58215836e-01
-1.11990643e+00 -8.44654381e-01 5.26722670e-01 2.45335907e-01
-1.53882670e+00 -6.26730323e-01 7.68339992e-01 -2.23436803e-01
5.88011384e-01 4.08446550e-01 7.69631624e-01 7.89666176e-01
1.11416847e-01 5.75944066e-01 8.45422626e-01 -4.85843033e-01
1.57483704e-02 -1.66664794e-01 -1.05789036e-01 8.49623144e-01
5.90868592e-01 -3.83711830e-02 -4.78019327e-01 -1.12728611e-01
1.14430654e+00 2.61804253e-01 -6.33847237e-01 -6.17482185e-01
-1.51481807e+00 5.37875891e-01 4.72500771e-01 -2.48679280e-01
-6.08558618e-02 8.40771869e-02 1.93916410e-01 -5.49302213e-02
2.78214335e-01 2.92244405e-01 -3.33477497e-01 -7.05095306e-02
-7.20786095e-01 8.13662037e-02 1.73262641e-01 1.11427832e+00
7.23925829e-01 -8.27790648e-02 3.05205882e-01 8.30268025e-01
4.71229732e-01 9.04877722e-01 4.70461696e-01 -8.15801740e-01
5.70592463e-01 7.99762011e-01 2.21623197e-01 -1.48432803e+00
-3.81761402e-01 -3.98131788e-01 -7.27564216e-01 2.78066695e-01
2.07282558e-01 6.57260269e-02 -5.42995036e-01 1.34506714e+00
5.80018103e-01 1.06213048e-01 -3.09032708e-01 1.10944164e+00
4.55278546e-01 4.98682708e-01 -4.64007795e-01 -6.32293880e-01
1.14360023e+00 -8.92512560e-01 -7.16465235e-01 -5.11253417e-01
1.64526775e-01 -1.16256154e+00 1.07962298e+00 6.17955148e-01
-7.67212033e-01 -6.00754499e-01 -1.32944524e+00 -1.88793745e-02
-9.17479619e-02 3.51020575e-01 6.60855711e-01 6.19860828e-01
-7.19872236e-01 -2.85305101e-02 -8.61294150e-01 -4.40020621e-01
7.11763054e-02 4.82736915e-01 -6.91467106e-01 -1.18376259e-02
-7.40200102e-01 6.46436036e-01 1.47884384e-01 5.75878441e-01
-5.94876349e-01 -4.65307325e-01 -7.67440796e-01 -2.59749562e-01
6.60141349e-01 -3.92235935e-01 9.94816720e-01 -1.03782976e+00
-1.50602257e+00 7.04396605e-01 -1.07751898e-01 2.36759912e-02
7.51846671e-01 -5.94556272e-01 -3.49968612e-01 -4.66448888e-02
1.61200866e-01 4.24076945e-01 8.60801876e-01 -1.14724457e+00
-7.44131982e-01 -6.41685247e-01 3.99503298e-02 6.86456859e-01
-2.67476380e-01 -1.07296959e-01 -1.06244791e+00 -7.03623891e-01
7.18274891e-01 -1.31522262e+00 -2.15594187e-01 5.31264126e-01
-1.20315284e-01 2.12976068e-01 9.89176810e-01 -6.64573312e-01
1.22595096e+00 -2.28324389e+00 4.28158082e-02 9.94975716e-02
-3.16709615e-02 2.17803307e-02 1.76720455e-01 8.79410207e-02
3.03801317e-02 -3.15488368e-01 -1.79561540e-01 -1.94032997e-01
-3.99940252e-01 1.73883941e-02 -2.80611873e-01 9.91495013e-01
-1.40304983e-01 2.89494395e-01 -6.88814104e-01 -5.12651205e-01
4.91663039e-01 2.36505836e-01 -3.95764172e-01 2.11295813e-01
3.74279171e-01 2.88720459e-01 -2.68196851e-01 7.77288079e-01
1.24093437e+00 1.09666765e-01 -2.36090735e-01 -6.37049735e-01
-4.21467483e-01 -5.50097823e-01 -1.94211268e+00 1.84554517e+00
-3.64444673e-01 6.60942316e-01 -7.53794685e-02 -6.57079995e-01
1.07551527e+00 -1.75479695e-01 3.94903660e-01 -6.72723055e-01
-2.96796672e-02 1.96534336e-01 -4.86149639e-01 -4.83237237e-01
7.23962545e-01 3.22681665e-01 -4.04706039e-02 -8.74622762e-02
-4.49851513e-01 -1.29571944e-01 -5.09198271e-02 3.89527045e-02
7.62488723e-01 2.96784669e-01 5.19045711e-01 -1.93258405e-01
8.14079165e-01 -2.33609647e-01 8.89739096e-01 3.53891760e-01
-3.08031261e-01 8.52595210e-01 -1.28826946e-01 -2.69791752e-01
-7.78745115e-01 -1.12151110e+00 -6.37691841e-02 7.45331883e-01
9.06448245e-01 -2.85602491e-02 -4.89678949e-01 -5.99819362e-01
-5.05338944e-02 5.67382239e-02 -4.43564653e-01 -1.02463074e-01
-8.79143238e-01 -9.24173117e-01 4.55330551e-01 5.65365016e-01
1.04454017e+00 -2.61920989e-01 -4.94076937e-01 8.35462734e-02
-3.70194554e-01 -1.21744037e+00 -7.28347540e-01 -3.48144710e-01
-8.62597287e-01 -1.24819624e+00 -6.54791772e-01 -8.38932991e-01
9.39405262e-01 9.53966796e-01 6.65071011e-01 -4.24006321e-02
-4.80348140e-01 4.11819220e-01 -3.21353495e-01 -1.68134078e-01
4.13050830e-01 -3.03159982e-01 2.80467957e-01 2.19526276e-01
3.20693292e-02 -2.58953124e-01 -9.85134363e-01 7.47488141e-01
-7.31614769e-01 8.66053477e-02 6.24692082e-01 6.53541803e-01
7.45384574e-01 1.14998028e-01 -1.32354721e-02 -5.65687358e-01
1.60710469e-01 1.40147775e-01 -9.98645604e-01 3.61438036e-01
-7.47215688e-01 -1.10318050e-01 3.34469855e-01 -4.75349933e-01
-1.42873013e+00 4.67708349e-01 2.65165806e-01 -1.49471462e-01
9.37413424e-02 -1.34616147e-03 -3.96236479e-01 -5.45423746e-01
6.19913995e-01 1.97266325e-01 -1.00068897e-01 -3.43164176e-01
1.35884017e-01 7.48406708e-01 8.37593198e-01 -2.26905823e-01
1.19667387e+00 7.94901550e-01 7.62278214e-02 -9.41275239e-01
-4.65274066e-01 -7.27788091e-01 -6.54391706e-01 -5.77005267e-01
7.45443046e-01 -1.34427452e+00 -8.73450935e-01 7.78445661e-01
-1.07833457e+00 3.44650716e-01 3.42875093e-01 7.89759219e-01
-4.08496052e-01 7.40442574e-01 -1.54018939e-01 -7.18042254e-01
-4.73785371e-01 -1.29854310e+00 1.38831997e+00 5.38178802e-01
1.42981932e-01 -6.73787057e-01 8.76832977e-02 4.74325031e-01
1.42328903e-01 4.35115755e-01 2.62252629e-01 3.89092654e-01
-8.81326735e-01 -1.60728216e-01 -1.92394495e-01 7.48274848e-02
1.04523398e-01 3.37009609e-01 -7.19219744e-01 -6.91911340e-01
-4.25801538e-02 1.27315030e-01 4.57328230e-01 2.05423206e-01
9.47810948e-01 -1.23875313e-01 -4.30398107e-01 8.55706334e-01
1.77077353e+00 2.80577719e-01 7.83062398e-01 8.35286260e-01
7.98364162e-01 2.56580949e-01 1.27486157e+00 4.80404198e-01
1.90644071e-01 1.12615597e+00 5.03440201e-01 -3.49982798e-01
-1.36621580e-01 -8.09676722e-02 6.02559745e-01 7.35180140e-01
-3.12288225e-01 2.00771238e-03 -7.97477007e-01 2.02431589e-01
-1.87723470e+00 -7.62418449e-01 -3.39655429e-01 2.43385863e+00
6.37127221e-01 7.06867799e-02 -3.01264286e-01 1.97429121e-01
1.03374660e+00 6.67739958e-02 -6.86849892e-01 1.78001046e-01
-1.65393442e-01 -2.88438022e-01 1.09662199e+00 4.54730093e-01
-1.19605994e+00 7.81670213e-01 5.40442467e+00 8.74453545e-01
-1.21827507e+00 -1.46594763e-01 1.83738440e-01 6.89293221e-02
2.37868741e-01 6.04072735e-02 -1.04307985e+00 4.47027653e-01
-7.69383684e-02 1.35891244e-01 4.47670162e-01 1.03469598e+00
3.27317506e-01 -3.95055622e-01 -7.56207645e-01 1.49268568e+00
4.41780299e-01 -8.66333008e-01 -5.42239472e-02 -1.09149136e-01
5.96871614e-01 -2.03435600e-01 -1.31391078e-01 -1.46124274e-01
-9.00252536e-02 -3.14779788e-01 8.83190393e-01 5.60576558e-01
9.12851095e-01 -7.20151126e-01 7.24384367e-01 2.81049609e-01
-1.46707416e+00 -1.08289942e-01 -6.00729465e-01 1.97205693e-02
1.14809096e-01 4.19398844e-01 -6.50419176e-01 4.45035547e-01
8.55643153e-01 6.66376531e-01 -1.02990901e+00 1.11471152e+00
-6.63489848e-02 2.05467284e-01 -3.64273250e-01 2.54565358e-01
-1.55047491e-01 -2.85937369e-01 6.89496040e-01 1.10619676e+00
3.13249856e-01 8.76312703e-02 1.73332617e-01 1.22929513e-01
2.31089935e-01 1.58116117e-01 -3.33559215e-01 4.84145015e-01
5.77194571e-01 1.35825145e+00 -8.45405102e-01 9.35390070e-02
-4.68241423e-01 1.25981951e+00 1.18367545e-01 3.10682684e-01
-1.09447610e+00 -4.81837571e-01 3.96527767e-01 1.53979227e-01
1.03641249e-01 -5.17576158e-01 -1.03547787e-02 -1.44491792e+00
3.87175620e-01 -7.70094573e-01 2.28192762e-01 -9.50718462e-01
-8.48026574e-01 1.91809222e-01 -6.26638085e-02 -1.86842799e+00
2.07251132e-01 -4.97208863e-01 -3.29933703e-01 4.59221721e-01
-1.26447237e+00 -1.20221913e+00 -1.05521715e+00 8.26920450e-01
8.24850798e-01 -2.21045204e-02 6.16292655e-01 5.38255036e-01
-7.05411136e-01 8.40835452e-01 3.84945393e-01 9.04411748e-02
1.12628996e+00 -8.87961268e-01 1.97245866e-01 1.38655126e+00
-2.22659245e-01 6.79892778e-01 7.77115703e-01 -5.99482596e-01
-1.84359384e+00 -8.75861287e-01 7.07112029e-02 -1.05127335e-01
3.29383850e-01 -4.88386661e-01 -3.05698037e-01 6.37411177e-01
-3.57983291e-01 7.03631341e-02 3.69866222e-01 -1.18638620e-01
-2.48501509e-01 -7.46194601e-01 -1.17629921e+00 5.26129246e-01
1.33166575e+00 -2.17506766e-01 -3.47181022e-01 2.16821909e-01
6.66913629e-01 -6.23862863e-01 -7.19131947e-01 5.74699998e-01
8.26579094e-01 -1.02912378e+00 1.18825603e+00 2.75071353e-01
-1.05060063e-01 -8.26908290e-01 -3.03954422e-01 -9.57833290e-01
-5.71051657e-01 -3.54496688e-01 2.45299473e-01 1.40822077e+00
-6.30551204e-02 -7.19123125e-01 6.01393104e-01 4.27612752e-01
-1.74318314e-01 -2.69407213e-01 -9.62581217e-01 -5.96844614e-01
-8.75497699e-01 -4.80598509e-02 3.62747192e-01 8.89307857e-01
-4.62592036e-01 2.45617405e-01 -3.17485303e-01 6.60869300e-01
8.75516593e-01 -3.83697078e-02 1.24228764e+00 -1.15681958e+00
-2.23170519e-01 5.14980331e-02 -8.57776642e-01 -1.27854168e+00
-4.50146973e-01 2.53916346e-02 6.70457035e-02 -1.30432141e+00
1.03738032e-01 -3.86532158e-01 1.26686484e-01 8.69280398e-02
-3.15780699e-01 5.00975370e-01 1.20426841e-01 3.78021806e-01
-5.60901523e-01 4.83042210e-01 1.13567853e+00 -1.86706960e-01
-9.81015712e-02 -1.86813354e-01 -4.71802443e-01 9.32982445e-01
3.45645666e-01 -1.80096254e-01 -4.53890353e-01 -7.17843533e-01
4.21949118e-01 -1.86143704e-02 2.39787325e-01 -1.24759400e+00
3.13142359e-01 -3.97561699e-01 7.03335583e-01 -7.05906332e-01
4.66396630e-01 -1.19434750e+00 4.45321947e-01 4.94697005e-01
1.63832560e-01 2.44940981e-01 7.22594783e-02 7.61918783e-01
-2.25562781e-01 -1.34209190e-02 9.61060524e-01 -1.14668474e-01
-1.05981135e+00 3.51880878e-01 9.09043029e-02 -2.73251921e-01
1.20256603e+00 -6.64783478e-01 -4.70821649e-01 -1.42771631e-01
-2.81965405e-01 -1.60135352e-03 6.79908574e-01 5.34234762e-01
6.81502163e-01 -1.43460369e+00 -5.73989391e-01 3.56485903e-01
4.33841258e-01 2.88674235e-01 4.97651547e-01 9.48718905e-01
-1.14196599e+00 1.21849151e-02 -1.92430675e-01 -8.79723668e-01
-1.77050006e+00 4.36539739e-01 1.28951877e-01 1.39476359e-01
-4.88386065e-01 7.80794919e-01 2.90185064e-01 -7.72133172e-02
1.90086573e-01 -1.93612993e-01 -2.60665536e-01 1.29868954e-01
5.37604570e-01 8.35718691e-01 3.10546219e-01 -8.37433100e-01
-5.64654946e-01 1.27293456e+00 -2.06874639e-01 -1.26350850e-01
1.18263149e+00 -7.50149786e-01 6.01560250e-03 2.02293262e-01
1.14551485e+00 4.70004439e-01 -1.48767233e+00 -1.83777392e-01
-5.40174067e-01 -9.98463452e-01 2.07560882e-01 -4.16272372e-01
-1.02161610e+00 4.48655277e-01 1.40848911e+00 -2.63556451e-01
1.28590226e+00 -5.23340464e-01 4.89987820e-01 5.03620684e-01
6.59798741e-01 -1.32088578e+00 1.28385291e-01 1.18184641e-01
1.02285671e+00 -1.29301572e+00 5.36617696e-01 -6.69156611e-01
-4.32209611e-01 1.33690453e+00 8.76011610e-01 -2.25806475e-01
3.01695913e-01 1.53437808e-01 1.23521984e-01 1.03462271e-01
2.30292436e-02 1.09726503e-01 -1.60261765e-02 4.22108114e-01
7.22572133e-02 -6.06679469e-02 -4.16331112e-01 6.37662709e-02
-2.12444797e-01 -2.89940864e-01 5.95453441e-01 8.97440255e-01
-6.27202809e-01 -6.98167503e-01 -1.00852239e+00 -1.87654551e-02
-5.19317947e-02 2.25149453e-01 -1.47995412e-01 8.59485328e-01
2.73136556e-01 8.87447894e-01 1.66637212e-01 -3.78188968e-01
6.11342430e-01 -6.67783141e-01 4.52383846e-01 -2.13689610e-01
-1.54758990e-01 2.20970422e-01 -1.78814322e-01 -6.82786405e-01
-4.77096736e-01 -8.34676147e-01 -1.07979476e+00 -2.70597667e-01
-8.85893822e-01 -3.06965411e-01 6.73921764e-01 5.35758615e-01
1.53334022e-01 1.53978735e-01 9.97000098e-01 -8.16254795e-01
-2.95185894e-01 -8.44085157e-01 -4.44379598e-01 3.95173669e-01
3.37248415e-01 -9.54816699e-01 -5.61519146e-01 1.64762750e-01] | [7.7593278884887695, -2.1599037647247314] |
cb644fd7-81b3-4ede-90b3-36134f1f42fe | a-unified-framework-for-domain-adaptive-pose | 2204.00172 | null | https://arxiv.org/abs/2204.00172v3 | https://arxiv.org/pdf/2204.00172v3.pdf | A Unified Framework for Domain Adaptive Pose Estimation | While pose estimation is an important computer vision task, it requires expensive annotation and suffers from domain shift. In this paper, we investigate the problem of domain adaptive 2D pose estimation that transfers knowledge learned on a synthetic source domain to a target domain without supervision. While several domain adaptive pose estimation models have been proposed recently, they are not generic but only focus on either human pose or animal pose estimation, and thus their effectiveness is somewhat limited to specific scenarios. In this work, we propose a unified framework that generalizes well on various domain adaptive pose estimation problems. We propose to align representations using both input-level and output-level cues (pixels and pose labels, respectively), which facilitates the knowledge transfer from the source domain to the unlabeled target domain. Our experiments show that our method achieves state-of-the-art performance under various domain shifts. Our method outperforms existing baselines on human pose estimation by up to 4.5 percent points (pp), hand pose estimation by up to 7.4 pp, and animal pose estimation by up to 4.8 pp for dogs and 3.3 pp for sheep. These results suggest that our method is able to mitigate domain shift on diverse tasks and even unseen domains and objects (e.g., trained on horse and tested on dog). Our code will be publicly available at: https://github.com/VisionLearningGroup/UDA_PoseEstimation. | ['Stan Sclaroff', 'Margrit Betke', 'Kate Saenko', 'Kaihong Wang', 'Donghyun Kim'] | 2022-04-01 | null | null | null | null | ['animal-pose-estimation'] | ['computer-vision'] | [ 1.05139539e-01 6.89813197e-02 -2.19301492e-01 -4.21164155e-01
-9.18077648e-01 -7.23038793e-01 4.26917523e-01 -3.03738475e-01
-4.42355692e-01 6.87308311e-01 -6.89965934e-02 2.67885655e-01
3.93837601e-01 -3.86294037e-01 -9.79377747e-01 -6.85856342e-01
2.54202902e-01 8.95450413e-01 5.69587529e-01 -2.66798586e-01
-5.26400134e-02 5.31995118e-01 -1.26658630e+00 8.06418881e-02
5.33163190e-01 9.47772801e-01 4.19343203e-01 5.88549018e-01
3.54165673e-01 1.92057401e-01 -6.05072141e-01 -2.95145035e-01
4.68438655e-01 -2.68176161e-02 -8.09167743e-01 2.08104670e-01
8.72411132e-01 -8.22641969e-01 -3.48983884e-01 8.90467167e-01
8.17797124e-01 -7.72090256e-02 8.37861180e-01 -1.31235909e+00
-6.44795537e-01 1.25274554e-01 -9.40597832e-01 8.54735076e-02
2.77170539e-01 4.00555015e-01 6.66284621e-01 -1.08309805e+00
8.08075845e-01 1.40030527e+00 7.75441825e-01 7.51823664e-01
-1.37389576e+00 -8.04119766e-01 2.71768183e-01 1.46258026e-01
-1.27058434e+00 -3.48396182e-01 6.96988642e-01 -6.28735662e-01
7.69603491e-01 -2.86277026e-01 4.94641036e-01 1.57766950e+00
-2.06570663e-02 1.05876303e+00 1.10059500e+00 -2.64535189e-01
1.00305021e-01 -7.61222541e-02 -1.56344444e-01 4.79388714e-01
3.22991729e-01 1.49299130e-01 -6.96190178e-01 9.21653882e-02
1.03403568e+00 -3.49176645e-01 -5.16743809e-02 -9.84999061e-01
-1.29833174e+00 7.41604924e-01 5.74434996e-01 -2.56939411e-01
-3.67152154e-01 2.33097181e-01 4.94993448e-01 5.16753197e-02
5.84299803e-01 4.72132325e-01 -8.29741895e-01 2.02727392e-01
-6.56838059e-01 6.90004528e-01 6.25339448e-01 1.40353620e+00
4.90431339e-01 -1.14532262e-01 -2.72560328e-01 9.50827003e-01
3.89439225e-01 1.03206170e+00 9.49758664e-02 -1.10546327e+00
5.71086705e-01 1.23491272e-01 4.51097310e-01 -8.61147225e-01
-6.17307484e-01 -4.51953620e-01 -3.96855593e-01 1.65101841e-01
8.01338375e-01 -2.62817442e-01 -1.19113243e+00 1.93735385e+00
6.04384243e-01 -1.70782626e-01 -2.24227354e-01 1.23988819e+00
1.05829823e+00 4.64595377e-01 3.92446280e-01 2.14650482e-01
1.52562916e+00 -1.21730757e+00 -3.59711230e-01 -9.21860993e-01
2.30252251e-01 -7.66952276e-01 1.10115695e+00 3.07410777e-01
-9.68270183e-01 -7.24963069e-01 -9.96472716e-01 -1.29185647e-01
-1.40042808e-02 3.44607264e-01 3.83592278e-01 3.60645771e-01
-8.15862179e-01 3.01375180e-01 -9.07732427e-01 -7.89135993e-01
3.77590030e-01 1.71422064e-01 -4.63453263e-01 -5.93530647e-02
-1.07700217e+00 1.14221489e+00 3.10479403e-01 -1.44447491e-01
-1.01867425e+00 -5.73982716e-01 -9.09170091e-01 -4.58725870e-01
5.25896132e-01 -8.64189684e-01 1.65849674e+00 -6.28404617e-01
-1.48267651e+00 1.27098918e+00 8.18474665e-02 -4.89424288e-01
8.60487700e-01 -8.04672480e-01 -9.04994085e-03 2.51845390e-01
4.74774510e-01 1.25748658e+00 1.03951502e+00 -1.36670780e+00
-4.72943097e-01 -6.02364302e-01 -7.41262287e-02 4.76761192e-01
-3.55272442e-02 -5.92108183e-02 -9.13942933e-01 -9.41183031e-01
2.61787832e-01 -1.36931455e+00 -3.84500436e-02 5.79858780e-01
-2.01084569e-01 -1.47737950e-01 7.66240358e-01 -8.85057092e-01
6.13388360e-01 -1.90084565e+00 3.47983688e-01 -3.10857385e-01
1.49183556e-01 1.39209509e-01 -1.93315580e-01 1.42685413e-01
1.71105579e-01 -4.67319340e-01 -3.20497751e-01 -3.08195055e-01
9.09625292e-02 -1.28669813e-02 -1.05420612e-01 6.56525075e-01
3.49540293e-01 9.59827602e-01 -8.23136747e-01 -5.99467456e-01
2.22614706e-01 3.49680334e-01 -7.14767098e-01 3.59169364e-01
-3.58811200e-01 8.04086030e-01 -3.32373738e-01 8.65155458e-01
9.96227443e-01 -2.70808429e-01 2.26200625e-01 -3.94109875e-01
3.28251660e-01 7.66326189e-02 -1.09962404e+00 1.95235407e+00
-2.82300025e-01 5.17383397e-01 1.12660497e-01 -8.16749096e-01
8.86823058e-01 5.07896617e-02 4.83315557e-01 -4.58861560e-01
9.06564295e-02 1.61579370e-01 -1.21367335e-01 -3.89516562e-01
3.27535689e-01 -6.10704571e-02 -3.85875553e-01 1.90277070e-01
3.39030087e-01 -4.43915784e-01 1.51926782e-02 -2.25924194e-01
7.46701062e-01 7.45797038e-01 4.82561082e-01 -1.59799546e-01
1.54521435e-01 3.11545640e-01 5.30545235e-01 4.83399838e-01
-7.90078163e-01 9.12716389e-01 1.83149651e-01 -2.65649885e-01
-1.21585524e+00 -1.40920258e+00 -2.56404549e-01 1.59829295e+00
4.68737781e-01 4.12479378e-02 -8.61380041e-01 -9.04390216e-01
4.15370911e-01 3.64896446e-01 -5.19044876e-01 -1.38653412e-01
-8.22665513e-01 -4.05563146e-01 4.23325896e-01 1.07177520e+00
8.35538685e-01 -1.02159417e+00 -6.32984698e-01 1.40117720e-01
-3.65111560e-01 -1.30408609e+00 -5.56846082e-01 1.32303074e-01
-8.36897433e-01 -9.32645500e-01 -1.27685213e+00 -9.29513514e-01
4.68408823e-01 1.67832106e-01 1.22623241e+00 -7.00139642e-01
-2.27512628e-01 4.10100788e-01 -2.74526060e-01 -5.91203034e-01
-1.08404927e-01 2.33245432e-01 2.99841821e-01 -5.19737303e-01
5.23843169e-01 -2.06883788e-01 -9.63636518e-01 7.84430563e-01
-3.28412473e-01 -4.80939634e-02 7.70429432e-01 8.38818610e-01
7.48098612e-01 -8.13721120e-01 6.12819314e-01 -7.62852728e-01
2.40768060e-01 -2.78355181e-01 -5.54650247e-01 1.55636519e-01
-3.08470905e-01 1.52920872e-01 1.55359268e-01 -7.03125298e-01
-1.23114371e+00 6.16373658e-01 8.35126117e-02 -5.04579246e-01
-3.45664442e-01 -5.81756830e-02 -2.45485544e-01 1.67794377e-02
1.18399119e+00 -9.83202830e-02 7.79652297e-02 -6.14270270e-01
5.72997749e-01 5.96366644e-01 7.49207199e-01 -6.98375762e-01
1.00183606e+00 4.36434120e-01 -2.47141689e-01 -5.32806933e-01
-7.83774495e-01 -5.26653469e-01 -8.26918483e-01 -1.62783518e-01
9.82264280e-01 -1.28126395e+00 -3.97816449e-01 7.27331400e-01
-1.20341539e+00 -4.45787519e-01 7.52120465e-02 4.90327924e-01
-8.67364347e-01 3.54273170e-01 -5.55059969e-01 -4.47175443e-01
-3.78350019e-01 -1.03581953e+00 1.58980012e+00 -8.20496306e-02
-6.15822852e-01 -5.09892106e-01 -1.18475311e-01 6.55718029e-01
1.86962888e-01 2.92547345e-01 2.75202662e-01 -4.04249519e-01
-3.97819698e-01 -8.68894011e-02 -3.86584759e-01 3.06524009e-01
-1.05900958e-01 -4.88832861e-01 -9.94400859e-01 -5.80742121e-01
-1.47242397e-01 -7.80849218e-01 7.26819038e-01 6.30370259e-01
1.00953758e+00 4.03199270e-02 -5.64924717e-01 5.12370050e-01
9.52374578e-01 -2.43064631e-02 3.02207291e-01 3.47495407e-01
6.86166942e-01 7.71821499e-01 1.16477013e+00 4.89636868e-01
3.94598454e-01 1.03936052e+00 3.73319238e-01 -4.08623973e-03
-5.05708277e-01 -3.53488594e-01 2.30954215e-01 8.07334334e-02
-2.07602128e-01 -5.43617234e-02 -1.12393820e+00 5.77215970e-01
-1.80106008e+00 -6.63291693e-01 1.56688094e-01 1.91045928e+00
9.72518921e-01 6.33518174e-02 5.38784683e-01 -3.14700544e-01
8.65609825e-01 -1.37771806e-03 -1.06868446e+00 3.88904586e-02
2.89348155e-01 1.36003658e-01 8.25134397e-01 8.22598115e-02
-1.55830884e+00 1.21264064e+00 6.25984335e+00 5.54034591e-01
-9.66685891e-01 2.06551269e-01 2.51542151e-01 -9.59300697e-02
4.07592565e-01 -4.85955536e-01 -8.91852200e-01 2.98193693e-01
2.28344336e-01 5.42345829e-02 1.75091237e-01 1.48187554e+00
-2.26117089e-01 1.51761873e-02 -1.41857362e+00 1.22828376e+00
5.35868146e-02 -5.87455511e-01 -2.67143011e-01 -1.80410221e-01
7.06434548e-01 -5.29496640e-04 2.55256712e-01 4.62906629e-01
2.32172534e-01 -9.05447960e-01 9.65889096e-01 6.05029799e-02
1.10350871e+00 -4.01609540e-01 5.99713266e-01 3.75949740e-01
-1.16020298e+00 1.44541800e-01 -2.44465083e-01 1.71226531e-01
4.49903607e-02 9.94118750e-02 -1.11541831e+00 6.80490583e-02
1.10781789e+00 5.80705702e-01 -4.89347905e-01 8.64655256e-01
-4.35906202e-01 2.45365635e-01 -3.90596896e-01 3.53195593e-02
-1.17948428e-01 3.92025113e-01 5.01441121e-01 1.23071516e+00
1.17228352e-01 -8.97711515e-02 1.99228883e-01 7.35015452e-01
-1.39219224e-01 -5.42531349e-02 -4.70124185e-01 3.20186079e-01
6.57149911e-01 9.28827047e-01 -5.31327367e-01 -1.43418118e-01
-2.45320097e-01 1.28499901e+00 3.09322715e-01 2.88614094e-01
-1.16380572e+00 -2.43780106e-01 8.40025365e-01 2.30010256e-01
5.00814438e-01 -2.98614711e-01 -4.72356409e-01 -1.03171206e+00
2.52224296e-01 -8.43084633e-01 2.65978605e-01 -6.76462889e-01
-1.47694564e+00 2.55686253e-01 4.20891523e-01 -1.49915922e+00
-4.61964130e-01 -1.00601912e+00 9.60676447e-02 7.89744854e-01
-1.29921305e+00 -1.32246983e+00 -5.51746309e-01 4.09211308e-01
7.67092347e-01 -7.74044842e-02 6.02978647e-01 1.89734936e-01
-1.80147022e-01 8.74155581e-01 -3.12039331e-02 2.10326925e-01
1.27044547e+00 -1.13496101e+00 7.53818572e-01 4.65577990e-01
-2.35270306e-01 4.54733908e-01 9.42656815e-01 -6.40560567e-01
-1.24926662e+00 -1.05393016e+00 4.73761261e-01 -9.28452194e-01
3.85985136e-01 -5.25240362e-01 -6.91933334e-01 7.32083023e-01
-6.89716637e-02 2.14183435e-01 1.98856771e-01 1.01050563e-01
-6.11148655e-01 -2.91281734e-02 -1.44267297e+00 4.73553061e-01
1.56267118e+00 -3.64942878e-01 -6.98039889e-01 4.45537716e-01
5.77695012e-01 -9.35924590e-01 -8.03558767e-01 6.66036427e-01
7.54529238e-01 -7.21304059e-01 1.24649119e+00 -4.27024692e-01
5.02279937e-01 -3.54019701e-01 -2.55684227e-01 -1.23744261e+00
-4.86780673e-01 -1.00073265e-03 -2.65537590e-01 8.02559018e-01
2.81196564e-01 -5.09585619e-01 1.01903832e+00 3.53667170e-01
5.19485027e-02 -4.78333265e-01 -7.47153163e-01 -1.01698339e+00
3.15433621e-01 -2.40276396e-01 2.81346947e-01 5.73397577e-01
-4.24430639e-01 5.30465364e-01 -4.50753629e-01 3.43530446e-01
8.26526463e-01 1.90166354e-01 1.16188920e+00 -1.15642989e+00
-5.01107335e-01 -2.29894564e-01 -3.66550714e-01 -1.53614569e+00
1.59970865e-01 -6.04440689e-01 3.98852348e-01 -1.55087435e+00
2.66682714e-01 -1.15724251e-01 1.56335071e-01 5.30563772e-01
-1.25447705e-01 4.15285826e-01 2.12497488e-01 3.67541283e-01
-4.44720030e-01 3.34352255e-01 1.36196864e+00 -2.22181767e-01
-6.40423372e-02 5.35522476e-02 -6.01870000e-01 7.87924349e-01
9.12267387e-01 -3.00393969e-01 -3.34718823e-01 -5.99279404e-01
-3.08427215e-01 -1.82074547e-01 6.52100980e-01 -1.11074579e+00
-1.43774241e-01 -1.81002110e-01 6.84855223e-01 -6.02521479e-01
5.97206235e-01 -7.36817658e-01 -1.07122824e-01 5.61442792e-01
-1.24996431e-01 -4.43911940e-01 3.92475814e-01 6.85386002e-01
6.35787398e-02 9.75148305e-02 1.11165977e+00 -1.61147907e-01
-1.26007462e+00 3.38234007e-01 2.47475743e-01 3.45353991e-01
1.25498235e+00 -2.33033851e-01 -2.23258287e-01 -3.31643134e-01
-7.75719225e-01 3.86355102e-01 5.38757324e-01 6.15897477e-01
4.72365797e-01 -1.39262938e+00 -8.92144382e-01 -8.68561640e-02
6.60985053e-01 2.30168074e-01 1.96986422e-01 5.55885375e-01
-7.15334833e-01 4.36811119e-01 -3.97815019e-01 -1.03319502e+00
-1.31812549e+00 4.98780191e-01 3.14692557e-01 3.87978218e-02
-4.55584705e-01 1.13451445e+00 5.67202508e-01 -6.87545419e-01
4.90141779e-01 -3.12931210e-01 1.22156091e-01 -2.39617843e-02
2.30154380e-01 4.06608522e-01 -3.79856899e-02 -7.16739535e-01
-6.74075067e-01 9.40905869e-01 -9.25499499e-02 2.18815822e-02
1.23887932e+00 -2.90314928e-02 5.77833414e-01 7.41010010e-02
1.10342443e+00 -4.51929390e-01 -1.87198436e+00 -4.67064112e-01
-1.29449219e-01 -4.99115318e-01 -3.91960323e-01 -9.87950444e-01
-8.66198242e-01 8.42951655e-01 8.75443339e-01 -4.35519189e-01
1.05184293e+00 6.37701273e-01 7.81083941e-01 4.36087817e-01
6.98387682e-01 -1.40439904e+00 5.57086587e-01 4.88294095e-01
1.36463296e+00 -1.60469306e+00 1.02977872e-01 -6.39203906e-01
-1.02314031e+00 7.25144804e-01 1.20636821e+00 -1.02239616e-01
2.99715310e-01 2.31133819e-01 1.22765407e-01 -2.84347404e-02
-2.60628134e-01 -3.67844731e-01 3.80269200e-01 1.11831772e+00
4.92344469e-01 2.56633103e-01 -1.27322793e-01 4.87992376e-01
-2.11984843e-01 -2.45610792e-02 -1.98856503e-01 9.23233151e-01
-4.93544370e-01 -9.32897270e-01 -7.09983289e-01 1.51297003e-01
-9.74804908e-02 2.82718807e-01 -5.17525971e-01 9.43544686e-01
1.99454680e-01 6.00388944e-01 -1.30019456e-01 -2.51448274e-01
7.04176664e-01 1.28791586e-01 8.28356922e-01 -8.44276428e-01
-1.13363869e-01 1.15637220e-01 1.29277125e-01 -5.36407173e-01
-4.42539781e-01 -7.48062670e-01 -1.16445088e+00 -1.72365874e-01
-2.13209435e-01 -6.32398605e-01 4.83414441e-01 5.28195202e-01
2.87345678e-01 2.35880911e-01 1.54842585e-01 -1.25179923e+00
-9.57833469e-01 -1.18330896e+00 -4.94703114e-01 5.38397849e-01
1.81365088e-01 -1.19988465e+00 -7.96803012e-02 1.97301641e-01] | [7.207331657409668, -0.9849103689193726] |
cd23c570-4686-4f05-8052-d71667319fa5 | backdoor-defense-via-deconfounded | 2303.06818 | null | https://arxiv.org/abs/2303.06818v1 | https://arxiv.org/pdf/2303.06818v1.pdf | Backdoor Defense via Deconfounded Representation Learning | Deep neural networks (DNNs) are recently shown to be vulnerable to backdoor attacks, where attackers embed hidden backdoors in the DNN model by injecting a few poisoned examples into the training dataset. While extensive efforts have been made to detect and remove backdoors from backdoored DNNs, it is still not clear whether a backdoor-free clean model can be directly obtained from poisoned datasets. In this paper, we first construct a causal graph to model the generation process of poisoned data and find that the backdoor attack acts as the confounder, which brings spurious associations between the input images and target labels, making the model predictions less reliable. Inspired by the causal understanding, we propose the Causality-inspired Backdoor Defense (CBD), to learn deconfounded representations for reliable classification. Specifically, a backdoored model is intentionally trained to capture the confounding effects. The other clean model dedicates to capturing the desired causal effects by minimizing the mutual information with the confounding representations from the backdoored model and employing a sample-wise re-weighting scheme. Extensive experiments on multiple benchmark datasets against 6 state-of-the-art attacks verify that our proposed defense method is effective in reducing backdoor threats while maintaining high accuracy in predicting benign samples. Further analysis shows that CBD can also resist potential adaptive attacks. The code is available at \url{https://github.com/zaixizhang/CBD}. | ['Qingyong Hu', 'Zepu Lu', 'Zhicai Wang', 'Qi Liu', 'Zaixi Zhang'] | 2023-03-13 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Zhang_Backdoor_Defense_via_Deconfounded_Representation_Learning_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Zhang_Backdoor_Defense_via_Deconfounded_Representation_Learning_CVPR_2023_paper.pdf | cvpr-2023-1 | ['backdoor-attack'] | ['adversarial'] | [ 1.81396365e-01 5.76400682e-02 -3.65782261e-01 6.75366260e-03
-4.65599984e-01 -9.98972774e-01 7.73605525e-01 -6.96679950e-02
-3.17819156e-02 7.38301694e-01 7.45978579e-02 -7.19879866e-01
-6.72255382e-02 -8.67863357e-01 -1.09855926e+00 -1.02927005e+00
-1.64738402e-01 -1.79719433e-01 1.68428659e-01 -1.08388782e-01
1.38302878e-01 5.57832420e-01 -7.82976329e-01 1.83604717e-01
6.08486116e-01 6.06702149e-01 -9.88533571e-02 3.01682621e-01
1.48065388e-01 8.60867739e-01 -9.46023822e-01 -8.10518920e-01
6.19783044e-01 -3.28534663e-01 -2.66638160e-01 -5.45839846e-01
4.91480321e-01 -6.47745609e-01 -1.00838447e+00 1.50968683e+00
1.89129263e-01 -3.60943526e-01 4.78852481e-01 -1.58320224e+00
-9.00227785e-01 7.16754615e-01 -6.50146663e-01 3.85324389e-01
-7.01133758e-02 4.90428388e-01 9.18912888e-01 -5.97170889e-01
3.03494483e-01 1.27311122e+00 4.03480053e-01 1.08026397e+00
-1.13284123e+00 -1.59365976e+00 1.86162442e-01 -2.24982463e-02
-1.24490523e+00 -2.55236059e-01 8.06980550e-01 -2.78957069e-01
5.37262797e-01 4.56529379e-01 2.78080374e-01 1.86919332e+00
5.59757352e-01 6.65169358e-01 8.46676171e-01 -5.69144785e-02
1.74766928e-01 3.04429531e-01 4.22001392e-01 7.54917562e-01
7.43891299e-01 7.71268308e-01 -5.91952741e-01 -7.17796922e-01
5.80432653e-01 3.86296600e-01 -5.10673046e-01 -1.35723606e-01
-5.63776255e-01 1.11480391e+00 6.88666463e-01 1.33495718e-01
-1.76388934e-01 3.29024285e-01 2.84648806e-01 2.25914687e-01
1.87034577e-01 4.23206985e-01 -3.84523362e-01 5.89668751e-01
-5.06436884e-01 2.97814190e-01 6.96875751e-01 6.95226729e-01
4.70192194e-01 1.31111786e-01 -6.78087249e-02 2.26987690e-01
3.39114934e-01 4.44986433e-01 1.89957976e-01 -3.12864035e-01
5.69944203e-01 4.74478066e-01 -2.09136158e-01 -1.09350145e+00
5.91065027e-02 -6.67599797e-01 -9.43250716e-01 1.80301309e-01
2.91154385e-01 -2.84960866e-01 -9.90145385e-01 2.13710117e+00
3.52606684e-01 5.49058199e-01 6.58938363e-02 6.78391576e-01
4.74668801e-01 5.92912853e-01 2.32474446e-01 5.10866055e-03
1.27676630e+00 -5.84216058e-01 -6.93796754e-01 -1.77586615e-01
5.15857041e-01 -8.41744915e-02 7.81604767e-01 5.76872945e-01
-3.64299148e-01 5.43130189e-02 -1.51943147e+00 3.32193583e-01
-3.98788512e-01 -5.03227830e-01 7.23670304e-01 1.16668081e+00
-5.35616159e-01 4.41895843e-01 -8.31865847e-01 1.73133224e-01
9.60286617e-01 4.43979859e-01 -5.24292290e-01 -3.81884247e-01
-1.66982293e+00 6.03112519e-01 2.65280902e-01 4.32960801e-02
-1.89951205e+00 -9.91813064e-01 -4.16882366e-01 -9.65565220e-02
4.84450012e-01 -5.18656611e-01 7.70266593e-01 -4.07213271e-01
-1.00754809e+00 3.28769505e-01 3.16513300e-01 -8.37615013e-01
5.00258565e-01 -2.90239662e-01 -4.07822371e-01 1.06410876e-01
-8.01473483e-02 2.60281622e-01 1.14751351e+00 -1.40070546e+00
-3.03097755e-01 -6.45632625e-01 1.01538427e-01 -2.76596218e-01
-9.32898641e-01 4.58032861e-02 -4.56095263e-02 -8.30079734e-01
-2.89966345e-01 -8.22164774e-01 -2.98298925e-01 -4.97734733e-02
-1.02072823e+00 9.01982114e-02 1.19352901e+00 -5.08493185e-01
1.12805760e+00 -2.19707060e+00 -1.49747550e-01 1.61892906e-01
8.29630196e-01 5.82799792e-01 -1.58893704e-01 4.50689822e-01
-2.42383018e-01 6.04952395e-01 -2.35543191e-01 -2.20838785e-01
-1.14256851e-01 2.48063445e-01 -1.10033619e+00 7.69883394e-01
4.59227264e-02 7.04785347e-01 -8.35574865e-01 1.46564871e-01
4.71114554e-03 6.90978825e-01 -4.17601079e-01 1.49914339e-01
-1.63005412e-01 2.23276332e-01 -6.59346700e-01 5.80275297e-01
1.05530822e+00 9.78728607e-02 5.52089736e-02 -8.07844251e-02
3.84392619e-01 3.21783811e-01 -6.73930883e-01 9.39169824e-01
4.47258994e-04 3.62176627e-01 -6.59832209e-02 -5.70458174e-01
9.20872509e-01 2.75671303e-01 -8.91229254e-04 -4.63352531e-01
3.63409758e-01 1.12021692e-01 4.21238095e-02 -9.24053639e-02
-3.32342112e-03 -3.74997526e-01 -1.26321957e-01 3.32980931e-01
1.13364466e-01 4.52110201e-01 -3.98534119e-01 5.59408188e-01
1.46865690e+00 -5.78758478e-01 1.06020503e-01 -2.37056896e-01
3.12738627e-01 -1.18083686e-01 7.54863560e-01 9.72800910e-01
-2.81104147e-01 1.47938624e-01 7.77322292e-01 -4.68419433e-01
-6.02254033e-01 -1.36798263e+00 -1.02167509e-01 5.63218951e-01
2.16560394e-01 -4.25347298e-01 -9.27217305e-01 -1.22746992e+00
2.27396488e-01 8.71703207e-01 -8.50324154e-01 -8.36224735e-01
-1.89949691e-01 -8.49547505e-01 1.28020310e+00 2.72025377e-01
4.57011074e-01 -5.82739830e-01 -2.70902246e-01 -1.70103803e-01
1.94632322e-01 -8.30785096e-01 -4.54718947e-01 4.43861544e-01
-7.79815793e-01 -1.26020205e+00 -2.61096627e-01 -1.46516353e-01
5.83498716e-01 2.69496173e-01 4.06222016e-01 2.40163326e-01
-4.00551736e-01 -2.70826727e-01 -7.84262568e-02 -5.73508918e-01
-4.55803186e-01 -2.45192543e-01 4.61628258e-01 -2.67262254e-02
4.68200594e-01 -6.95614100e-01 -4.06046122e-01 2.26359576e-01
-1.17265654e+00 -3.92708868e-01 5.32852948e-01 8.10741723e-01
3.42710942e-01 3.83363247e-01 5.80656528e-01 -1.04197538e+00
6.43356800e-01 -8.77934635e-01 -7.17295825e-01 -6.43189549e-02
-3.60741287e-01 1.08544558e-01 9.90365565e-01 -8.00852120e-01
-6.57747090e-01 -6.20430596e-02 -2.60852814e-01 -1.13135207e+00
-2.03516856e-02 6.50302600e-03 -7.25034952e-01 -8.57851058e-02
8.92603040e-01 2.16424182e-01 -2.57768154e-01 -4.11232233e-01
4.88061547e-01 2.62615383e-01 5.10048926e-01 -4.94881153e-01
1.38832653e+00 5.96509993e-01 8.79958831e-03 -6.50679827e-01
-8.32296252e-01 9.22675431e-02 -8.17665607e-02 5.74617982e-02
6.29407704e-01 -6.94542885e-01 -5.75398982e-01 5.65170765e-01
-1.14119577e+00 -7.95798525e-02 9.91699398e-02 2.31804729e-01
1.21095173e-01 2.32239783e-01 -6.63478196e-01 -8.92473280e-01
-4.12651569e-01 -1.10520148e+00 4.54680085e-01 2.02178389e-01
1.05367690e-01 -9.05310154e-01 1.01294264e-01 3.16758007e-01
8.34757388e-02 5.34692585e-01 1.13938272e+00 -1.23803306e+00
-8.40811074e-01 -5.66315711e-01 5.58204837e-02 5.01462698e-01
2.42829055e-01 -1.96617544e-01 -1.27376199e+00 -3.32724839e-01
5.84841490e-01 -2.47233540e-01 1.04473162e+00 5.26041351e-02
1.10949397e+00 -8.56448472e-01 -6.15637898e-01 7.48295665e-01
1.39842570e+00 4.05393332e-01 7.70867646e-01 1.41973406e-01
9.77615118e-01 3.86380851e-01 1.22885026e-01 3.02609056e-01
-1.49944440e-01 2.98175007e-01 1.00764513e+00 1.04241885e-01
2.17375398e-01 -8.94893706e-01 4.95004505e-01 2.16671184e-01
5.63644230e-01 -5.35932660e-01 -7.47630060e-01 2.72143960e-01
-1.42767334e+00 -9.01274323e-01 -2.27210462e-01 2.26838064e+00
8.19274008e-01 4.18454409e-01 -5.68362400e-02 1.37226745e-01
6.81310177e-01 3.29190552e-01 -8.06438804e-01 -8.85489881e-02
-1.34712353e-01 9.51365232e-02 8.03916931e-01 5.20154059e-01
-1.08047569e+00 1.04512644e+00 5.29630089e+00 9.72851336e-01
-9.64627087e-01 3.28128755e-01 7.99640059e-01 -2.77185649e-01
-4.43288296e-01 1.29954144e-01 -1.13790846e+00 4.03472722e-01
8.47292602e-01 -8.87007862e-02 3.56179953e-01 7.97409117e-01
1.91631950e-02 5.34986794e-01 -1.12036622e+00 5.45545638e-01
-2.64017191e-02 -1.44069934e+00 4.06940401e-01 6.06605113e-01
5.25789201e-01 -9.20500979e-03 3.73524725e-01 1.17964700e-01
7.47783363e-01 -1.09705019e+00 6.66533113e-01 3.31266016e-01
5.12365103e-01 -1.16743791e+00 4.14905727e-01 6.55535698e-01
-7.28446662e-01 -3.60755682e-01 -4.93185967e-01 1.90111130e-01
-3.19210529e-01 7.84916282e-01 -8.33464801e-01 3.87809396e-01
6.91932023e-01 2.93219954e-01 -3.98619503e-01 4.79187310e-01
-6.52358174e-01 9.08013344e-01 -1.62150234e-01 1.92314833e-02
2.43073881e-01 1.56183494e-02 8.81860554e-01 9.62223470e-01
-1.11870825e-01 1.14809768e-02 -2.18242854e-01 1.41324711e+00
-4.39161688e-01 -3.96341920e-01 -1.15238273e+00 -2.46802554e-01
7.33582497e-01 1.19958699e+00 -5.12129188e-01 4.33944315e-02
6.08370826e-02 8.28166783e-01 3.17786962e-01 2.76035368e-01
-1.05497313e+00 -3.25195760e-01 1.09249640e+00 -2.11483259e-02
1.00082234e-01 -4.89534922e-02 -2.96296626e-01 -1.00109899e+00
-1.80218667e-01 -1.07780862e+00 4.17791337e-01 -3.14485103e-01
-1.56832814e+00 6.38919353e-01 -1.37020409e-01 -8.50866795e-01
2.68996596e-01 -6.13059521e-01 -8.30080569e-01 9.26598012e-01
-1.25958264e+00 -8.62529159e-01 1.84447482e-01 8.46055150e-01
1.93973988e-01 -2.63616025e-01 6.78171456e-01 1.55798450e-01
-1.07342350e+00 9.70230043e-01 -1.13635443e-01 3.46685022e-01
3.82560313e-01 -8.66137743e-01 4.68580037e-01 1.27455580e+00
2.76030153e-01 1.29034019e+00 7.56435215e-01 -1.03784990e+00
-1.58527029e+00 -1.34317982e+00 4.26605940e-01 -7.19361365e-01
8.94587517e-01 -9.66165423e-01 -1.16769218e+00 6.36689246e-01
5.80597669e-02 1.15265250e-01 7.87748814e-01 -3.87120575e-01
-1.08651340e+00 -1.34538084e-01 -1.34117544e+00 7.19277501e-01
1.02121627e+00 -5.53783238e-01 -4.69027489e-01 3.86356503e-01
1.21975267e+00 7.71140754e-02 -2.77292401e-01 1.27895162e-01
2.79335856e-01 -7.71910489e-01 1.10006809e+00 -8.13464522e-01
3.86959851e-01 -2.37341389e-01 -2.89740354e-01 -1.13554609e+00
-9.15237144e-02 -8.11367154e-01 -5.11463583e-01 1.28323567e+00
3.41177732e-01 -9.07039404e-01 8.64286602e-01 3.32691520e-01
1.10795133e-01 -7.34726310e-01 -1.00867331e+00 -1.02363312e+00
3.11857373e-01 -4.89196330e-01 6.47355974e-01 1.03521764e+00
-2.32290938e-01 2.28339508e-01 -8.16223145e-01 8.81386697e-01
1.21652842e+00 -5.90694189e-01 6.36325777e-01 -1.05105627e+00
-3.32243085e-01 -1.99132785e-01 -2.76717991e-01 -6.25340164e-01
2.51639992e-01 -8.84743512e-01 -2.63610482e-01 -8.26932013e-01
1.91558331e-01 -2.79073119e-01 -5.88089764e-01 7.53534317e-01
-3.11741203e-01 1.97325766e-01 2.08418742e-01 2.27687702e-01
7.92968720e-02 6.03135586e-01 9.05035555e-01 -2.35438600e-01
3.28984261e-02 3.34494822e-02 -1.25272167e+00 6.29380345e-01
9.03343737e-01 -1.20734286e+00 -7.63805807e-01 -1.76814765e-01
2.10958421e-02 -1.42993540e-01 6.76162183e-01 -7.00837016e-01
2.17454553e-01 -1.43381119e-01 2.13508561e-01 -3.87547940e-01
2.77285218e-01 -7.80694485e-01 8.08935463e-02 8.98833930e-01
-2.82494396e-01 -1.65187314e-01 3.21858287e-01 1.02439237e+00
2.03405097e-01 -2.02223241e-01 8.52236748e-01 -4.30943817e-02
-1.41027361e-01 6.31733954e-01 -3.06380063e-01 -1.23640433e-01
1.06738889e+00 1.80596516e-01 -7.23346770e-01 -8.28686878e-02
-2.27606684e-01 5.60892038e-02 1.31461814e-01 5.09141266e-01
9.28340495e-01 -1.14649415e+00 -5.01718521e-01 3.72116029e-01
-6.44519925e-02 -3.61986279e-01 2.72680432e-01 3.35908353e-01
-1.14333071e-01 4.18545991e-01 2.04782747e-02 -1.62076011e-01
-1.23637021e+00 9.96750832e-01 4.54912961e-01 -3.42661202e-01
-6.13911569e-01 1.08239663e+00 7.69510567e-01 -2.69510061e-01
3.43758702e-01 -3.78533378e-02 1.51532501e-01 -2.62501597e-01
8.22189987e-01 1.49662316e-01 -9.51490775e-02 -2.39284024e-01
-5.40579379e-01 -1.05922937e-01 -5.32131374e-01 1.00351602e-01
1.20398271e+00 3.68038416e-01 -1.37947816e-02 -1.00581490e-01
1.37439942e+00 1.37834698e-01 -1.36822617e+00 -3.84301804e-02
-7.25059882e-02 -6.27327025e-01 1.45964116e-01 -8.38933885e-01
-1.29257774e+00 9.53030884e-01 4.85364228e-01 1.05241515e-01
1.05546081e+00 1.49654234e-02 7.54892051e-01 2.80703247e-01
2.92663842e-01 -1.39468551e-01 3.50042492e-01 2.21756026e-01
7.80291557e-01 -5.87575316e-01 -2.41958827e-01 -3.95366758e-01
-4.22120005e-01 6.21268153e-01 6.48662806e-01 -4.42370445e-01
6.09287977e-01 5.44061840e-01 -1.82465062e-01 -2.94990301e-01
-9.76495862e-01 6.36001289e-01 -1.75611243e-01 7.29968011e-01
-3.82433325e-01 7.89953992e-02 1.45857543e-01 1.12759113e+00
-1.99315339e-01 -4.07119036e-01 6.07442856e-01 6.86677873e-01
-2.36755505e-01 -1.16439044e+00 -4.82375652e-01 3.04882139e-01
-6.14217877e-01 -3.10176045e-01 -7.96363115e-01 7.43589461e-01
1.65211946e-01 9.63140547e-01 -3.73774230e-01 -1.03282166e+00
2.22948372e-01 -7.43420795e-03 1.56003952e-01 -5.67309678e-01
-6.50966346e-01 -2.44748548e-01 -3.01147878e-01 -4.87874240e-01
4.91501302e-01 -3.48177493e-01 -9.99690950e-01 -4.20232236e-01
-5.56175649e-01 5.36050498e-02 5.42405546e-01 7.13149667e-01
2.68719643e-01 4.93311077e-01 1.01015723e+00 -3.03277016e-01
-9.73757327e-01 -5.97685218e-01 -5.97761989e-01 1.15147725e-01
6.73928320e-01 -8.34686399e-01 -9.25558805e-01 -4.49436009e-01] | [5.855088233947754, 7.683503150939941] |
857358be-f92f-4dcc-8ff0-a92e3616e37f | which-has-better-visual-quality-the-clear | null | null | https://ieeexplore.ieee.org/document/8489929 | https://www.researchgate.net/publication/328240901_Which_Has_Better_Visual_Quality_The_Clear_Blue_Sky_or_a_Blurry_Animal | Which Has Better Visual Quality: The Clear Blue Sky or a Blurry Animal? | Image content variation is a typical and challenging problem in no-reference image quality assessment (NR-IQA). This work pays special attention to the impact of image content variation on NR-IQA methods. To better analyze this impact, we focus on blur-dominated distortions to exclude the impacts of distortion-type variations. We empirically show that current NR-IQA methods are inconsistent with human visual perception when predicting the relative quality of image pairs with different image contents. In view of deep semantic features of pretrained image classification neural networks always containing discriminative image content information, we put forward a new NR-IQA method based on semantic feature aggregation (SFA) to alleviate the impact of image content variation. Specifically, instead of resizing the image, we first crop multiple overlapping patches over the entire distorted image to avoid introducing geometric deformations. Then, according to an adaptive layer selection procedure, we extract deep semantic features by leveraging the power of a pretrained image classification model for its inherent content-aware property. After that, the local patch features are aggregated using several statistical structures. Finally, a linear regression model is trained for mapping the aggregated global features to image-quality scores. The proposed method, SFA, is compared with nine representative blur-specific NR-IQA methods, two general-purpose NR-IQA methods, and two extra full-reference IQA methods on Gaussian blur images (with and without Gaussian noise/JPEG compression) and realistic blur images from multiple databases, including LIVE, TID2008, TID2013, MLIVE1, MLIVE2, BID, and CLIVE. Experimental results show that SFA is superior to the state-of-the-art NR methods on all seven databases. It is also verified that deep semantic features play a crucial role in addressing image content variation, and this provides a new perspective for NR-IQA. | ['Weisi Lin', 'Tingting Jiang', 'Ming Jiang', 'Dingquan Li'] | 2018-10-11 | null | null | null | ieee-transactions-on-multimedia-2018-10 | ['image-quality-estimation', 'blind-image-quality-assessment', 'no-reference-image-quality-assessment'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [ 2.22200498e-01 -7.37473965e-01 8.62105712e-02 -2.83264339e-01
-8.07851791e-01 -2.65480936e-01 4.23797041e-01 -3.35975051e-01
-1.70263588e-01 6.27185225e-01 4.06021267e-01 5.24088144e-02
-4.85607028e-01 -6.33344293e-01 -7.28936195e-01 -9.29070175e-01
4.72360514e-02 -3.46205473e-01 4.94299531e-02 -1.72360912e-01
5.22403955e-01 4.82377619e-01 -1.63869369e+00 1.73504010e-01
1.32488978e+00 1.44201207e+00 4.45124924e-01 5.80456436e-01
2.58752972e-01 7.67392933e-01 -7.71781385e-01 -4.14461225e-01
4.12122101e-01 -4.94360387e-01 -5.82918823e-01 2.98167616e-01
7.10628688e-01 -6.03943050e-01 -4.49980229e-01 1.30123031e+00
7.17501342e-01 1.34970710e-01 6.97650492e-01 -1.01582384e+00
-1.26916492e+00 5.27655706e-02 -5.87403715e-01 4.79060531e-01
3.36569458e-01 5.20951152e-01 8.78345191e-01 -1.02184677e+00
4.01071876e-01 1.23050392e+00 5.62903047e-01 1.01989336e-01
-1.25274062e+00 -4.01890159e-01 -1.46888897e-01 6.97217762e-01
-1.33056879e+00 -5.02614915e-01 8.06438982e-01 -5.44083834e-01
6.21295035e-01 2.74634987e-01 3.18713218e-01 9.20044482e-01
4.98686433e-01 5.22164106e-01 1.48648477e+00 -2.64915317e-01
2.97110170e-01 -1.78138047e-01 7.74154887e-02 4.15844083e-01
1.19410545e-01 1.32123545e-01 -4.33317840e-01 8.68953392e-02
7.52293646e-01 -8.39784741e-02 -7.37853825e-01 -2.32141331e-01
-1.25929582e+00 4.32880521e-01 6.58530712e-01 3.45878482e-01
-4.19116437e-01 -1.63139729e-03 2.09877521e-01 3.32774282e-01
3.74301076e-01 4.10313934e-01 -4.01695102e-01 -1.12429753e-01
-9.34162259e-01 1.67525738e-01 2.31490448e-01 7.30930746e-01
9.19767261e-01 1.31442517e-01 -6.51456952e-01 1.20848906e+00
5.34667857e-02 6.70917809e-01 5.64447820e-01 -1.19128287e+00
2.72777945e-01 3.71689647e-01 3.21611494e-01 -1.23509037e+00
-9.81001407e-02 -6.24977708e-01 -1.09770560e+00 3.68713945e-01
2.81085521e-01 3.61841053e-01 -8.86498690e-01 1.44808877e+00
-1.11908250e-01 1.27553254e-01 1.07390001e-01 1.28813267e+00
7.64910758e-01 5.23616672e-01 -1.11337438e-01 -2.71127999e-01
1.34506655e+00 -1.02373505e+00 -7.94988513e-01 1.84164748e-01
5.42821027e-02 -9.83652472e-01 1.23365152e+00 5.22444367e-01
-1.11536622e+00 -1.16974902e+00 -1.08941245e+00 -1.61816582e-01
-3.09914678e-01 4.40988809e-01 1.97156399e-01 6.28216565e-01
-1.30795956e+00 5.68225443e-01 -2.10245788e-01 -5.58295585e-02
5.17213941e-01 3.44678424e-02 -2.42146522e-01 -4.99394268e-01
-1.30029356e+00 1.01483428e+00 9.68671665e-02 2.67887503e-01
-1.00175202e+00 -8.04850698e-01 -8.77920210e-01 1.22120649e-01
1.91961691e-01 -8.53327036e-01 8.81058693e-01 -1.17331684e+00
-1.48964620e+00 4.80472296e-01 -2.99348861e-01 -2.83534944e-01
4.13436502e-01 -3.37000340e-01 -6.29863441e-01 2.76468515e-01
9.74714682e-02 4.61362422e-01 1.23022830e+00 -1.47726917e+00
-2.72006184e-01 -2.38813519e-01 1.92885205e-01 2.63381958e-01
-1.24570869e-01 1.35894015e-01 -4.57723886e-01 -9.00873601e-01
-1.61285728e-01 -4.97484922e-01 1.71242177e-01 -8.36838502e-03
-3.32365304e-01 -4.37959982e-03 6.46620631e-01 -9.11766768e-01
1.23087668e+00 -2.29284787e+00 1.78953767e-01 -5.94232976e-02
8.20116922e-02 3.85877192e-01 -5.08048713e-01 7.23075718e-02
1.13582816e-02 -3.69604751e-02 -3.69350702e-01 -1.00827888e-01
-7.18754828e-02 -6.66552484e-02 -1.53306767e-01 4.89924848e-01
2.78951466e-01 8.67858827e-01 -8.14158320e-01 -3.94936413e-01
5.72906792e-01 3.89165252e-01 -3.24785620e-01 4.03703243e-01
-6.31212862e-03 4.52471912e-01 -1.46021068e-01 7.72863269e-01
1.15801823e+00 -3.15237939e-01 -4.15592730e-01 -8.39839578e-01
-9.30131003e-02 -1.22793779e-01 -9.43452060e-01 1.60105705e+00
-7.29364991e-01 5.16373694e-01 -7.47898296e-02 -8.49660456e-01
8.19102705e-01 4.28373702e-02 3.79632980e-01 -1.02011156e+00
-3.62497084e-02 3.10695112e-01 4.59115580e-02 -7.10592866e-01
4.09080416e-01 1.86429963e-01 2.81460971e-01 -1.94404814e-02
2.30056524e-01 -7.73958042e-02 7.58957490e-02 1.03682755e-02
8.85296643e-01 2.94172261e-02 2.13568881e-01 -2.51185060e-01
9.42586660e-01 -4.91616011e-01 3.80003750e-01 8.39968145e-01
-4.43338722e-01 1.18032253e+00 1.19145662e-01 -2.59587020e-01
-1.06122339e+00 -1.27952790e+00 -3.41543376e-01 7.28744030e-01
6.88404441e-01 -9.63172317e-02 -8.45174372e-01 -5.09460449e-01
-1.20300531e-01 5.59884191e-01 -6.11164391e-01 -1.92143589e-01
-3.21934342e-01 -8.93584490e-01 2.19204396e-01 2.52392083e-01
1.18320704e+00 -9.96505737e-01 -2.40263805e-01 -9.45095867e-02
-4.10260886e-01 -1.16436684e+00 -7.61547267e-01 -4.01570290e-01
-5.28554797e-01 -1.12513435e+00 -1.03491294e+00 -4.00112063e-01
4.30014282e-01 5.96401751e-01 1.09337449e+00 -3.84044088e-02
-2.44535342e-01 3.50927889e-01 -3.62054795e-01 2.49343231e-01
-3.14418525e-01 -3.01117152e-01 -9.98657420e-02 3.57223064e-01
3.61636989e-02 -4.75002646e-01 -1.17290938e+00 5.41677058e-01
-9.38851774e-01 -6.00054339e-02 9.29078817e-01 9.76229548e-01
3.11911017e-01 3.08542073e-01 5.52701294e-01 -2.20015883e-01
6.40029252e-01 -4.20543522e-01 -4.69878823e-01 2.28317305e-01
-7.34768689e-01 -1.42606780e-01 6.37913346e-01 -2.85525799e-01
-1.36178851e+00 -5.18590212e-01 -1.11938797e-01 -6.37702405e-01
-2.23929048e-01 3.31483245e-01 -5.07631063e-01 -1.93882748e-01
6.86029673e-01 5.06233037e-01 -8.03519711e-02 -5.21044850e-01
3.82241815e-01 8.12308371e-01 7.44194090e-01 -3.13793153e-01
8.61213744e-01 2.72783846e-01 -1.02382049e-01 -7.91675746e-01
-7.86112666e-01 -5.10070264e-01 -3.16259652e-01 -2.47325435e-01
8.84659588e-01 -1.11446714e+00 -4.41268265e-01 1.04192328e+00
-1.18744206e+00 -1.49239317e-01 -8.99448618e-02 4.25692230e-01
-5.09125888e-01 6.95746839e-01 -6.95165992e-01 -4.75769281e-01
-3.45981598e-01 -1.54874718e+00 1.08287036e+00 3.63907009e-01
2.99159467e-01 -7.29095280e-01 -1.69047132e-01 7.07891583e-01
8.31721067e-01 -1.32343769e-01 8.29785049e-01 -6.32616580e-02
-7.66855717e-01 3.26353014e-01 -8.64303172e-01 9.10617530e-01
4.98918563e-01 -2.10922807e-01 -1.05211389e+00 -2.62753248e-01
2.01620504e-01 -1.48115262e-01 8.39556754e-01 6.57142401e-01
1.49821734e+00 -4.76419479e-01 2.99076438e-01 7.93665767e-01
1.65153718e+00 1.05249286e-01 1.13216317e+00 4.81595546e-01
7.48643994e-01 1.99707329e-01 6.01995826e-01 2.08838046e-01
2.68267632e-01 9.89050627e-01 6.01915836e-01 -2.80938447e-01
-5.98136604e-01 1.57703832e-01 5.03187418e-01 5.93812168e-01
-1.27482638e-01 -2.15395108e-01 -3.14483196e-01 5.25236130e-01
-1.50279641e+00 -9.20342028e-01 -7.96525180e-02 2.06640911e+00
8.94084573e-01 -2.03792930e-01 -1.88802376e-01 1.14153914e-01
7.39187121e-01 3.67387712e-01 -5.48780799e-01 -2.67590970e-01
-5.05342960e-01 1.66779131e-01 3.99920881e-01 2.16465995e-01
-1.18179440e+00 5.65740466e-01 5.51976013e+00 1.24465728e+00
-1.17984617e+00 1.71504736e-01 9.44317222e-01 2.13568121e-01
-1.83054477e-01 -2.79405504e-01 -2.54052371e-01 8.87609839e-01
8.88112009e-01 7.26465555e-03 7.85678089e-01 6.71905875e-01
5.56531310e-01 -2.91415036e-01 -7.71703780e-01 1.23937201e+00
2.44867221e-01 -1.19122398e+00 1.54544652e-01 -5.81087582e-02
1.02277172e+00 -1.77850593e-02 4.11824286e-01 5.84715605e-02
-1.14694417e-01 -1.09011471e+00 7.84298301e-01 7.44081199e-01
9.67316747e-01 -3.84109408e-01 1.10156941e+00 -1.28592163e-01
-7.97056198e-01 -1.81586310e-01 -4.56964582e-01 1.55761883e-01
-2.64467262e-02 9.08521950e-01 8.87682545e-04 1.00505626e+00
1.05841327e+00 8.46481025e-01 -9.81143892e-01 1.18262482e+00
-5.83514050e-02 4.19311434e-01 3.43586415e-01 5.88755667e-01
2.60366332e-02 -2.27732405e-01 5.16083837e-01 1.12171924e+00
6.92185760e-01 2.25055348e-02 -2.37711981e-01 1.00786865e+00
-1.27354354e-01 -6.04681224e-02 -3.30761641e-01 4.48804349e-01
2.21885204e-01 1.24632740e+00 -1.95366949e-01 -2.97564805e-01
-6.18669212e-01 1.28645360e+00 -2.23195612e-01 6.25525117e-01
-8.52874577e-01 -2.78094471e-01 8.90456855e-01 -2.53051966e-02
5.41085482e-01 1.40508229e-03 -1.65353417e-01 -1.35356641e+00
1.35257587e-01 -1.06124413e+00 -3.53796668e-02 -1.36024010e+00
-1.53605187e+00 5.85744679e-01 -5.81813827e-02 -1.44880438e+00
6.05016798e-02 -5.75831294e-01 -5.67554414e-01 1.13220620e+00
-1.77906096e+00 -1.05879891e+00 -6.91982388e-01 7.22300589e-01
6.91683829e-01 -7.75382519e-02 3.21846962e-01 3.75464499e-01
-4.83530074e-01 5.63027680e-01 2.98710644e-01 2.69818101e-02
8.46521020e-01 -1.21742904e+00 9.01672393e-02 1.11163020e+00
-2.02840537e-01 6.24927163e-01 6.49565220e-01 -3.12128723e-01
-1.33618224e+00 -1.30463886e+00 3.82734478e-01 -1.61563545e-01
4.83377010e-01 9.03165340e-03 -1.16883886e+00 -6.72605180e-04
4.57382560e-01 3.76368076e-01 1.12027176e-01 -4.47085887e-01
-4.42594469e-01 -5.40393889e-01 -1.23230481e+00 4.22287792e-01
1.01744413e+00 -6.42890096e-01 -4.81793463e-01 -4.27613519e-02
8.38591397e-01 -2.39445195e-01 -1.01391006e+00 6.77865624e-01
3.70653778e-01 -1.41135335e+00 1.22189844e+00 2.26189077e-01
7.62292802e-01 -7.36522079e-01 -2.99991012e-01 -1.52494442e+00
-4.40326720e-01 -3.83751869e-01 -9.60092172e-02 1.19240737e+00
-1.06018238e-01 -5.74298024e-01 1.55189395e-01 1.85618773e-01
-3.16054821e-01 -5.50231636e-01 -7.55348980e-01 -9.19825971e-01
-8.05893168e-02 -8.55904445e-02 7.05505073e-01 7.52735913e-01
-6.68281615e-01 -9.44214407e-03 -4.99614149e-01 2.42976099e-01
7.42123902e-01 1.10757768e-01 6.87083840e-01 -7.66071498e-01
-2.33711943e-01 -5.54596424e-01 -5.50055563e-01 -9.78659272e-01
-1.17151685e-01 -4.63329673e-01 6.01713965e-03 -1.46418846e+00
4.58000660e-01 -2.33915746e-01 -6.62693799e-01 -5.97617473e-04
-4.17946309e-01 5.96307695e-01 1.65739492e-01 4.82399821e-01
-6.00847840e-01 7.70723224e-01 1.58030975e+00 -3.75014246e-01
1.04686327e-01 -1.73236489e-01 -6.46052659e-01 3.53611112e-01
6.12566411e-01 7.72922561e-02 -4.20816839e-01 -3.77976060e-01
-1.02343522e-01 -5.44240251e-02 7.99810767e-01 -1.12769246e+00
5.57885680e-04 -2.36673653e-01 6.08433425e-01 -3.63773227e-01
1.34172797e-01 -6.81954086e-01 2.15730444e-01 1.09431535e-01
-2.51535088e-01 -1.77041009e-01 2.90411692e-02 5.63703179e-01
-6.19156122e-01 -1.65349886e-01 1.02822590e+00 1.01931375e-02
-9.14015412e-01 2.04978898e-01 -1.45045757e-01 -6.24481104e-02
6.13335431e-01 -3.41062218e-01 -6.96000695e-01 -3.59510839e-01
-3.66506249e-01 -1.95853606e-01 6.99845016e-01 4.24755454e-01
8.34653378e-01 -1.31005085e+00 -7.38176823e-01 1.40897855e-01
2.80960530e-01 -2.40300730e-01 8.16145062e-01 9.89341438e-01
-3.99024695e-01 2.50986874e-01 -3.11745703e-01 -7.72337079e-01
-1.05926979e+00 7.49314547e-01 4.52852696e-01 -7.77489021e-02
-3.66864830e-01 4.78423983e-01 5.09393394e-01 6.56036586e-02
-7.62465298e-02 -4.05177474e-01 -2.24704504e-01 -3.16580266e-01
5.39599955e-01 4.47735280e-01 3.66306275e-01 -9.05298889e-01
-2.12847725e-01 8.04172933e-01 1.60484657e-01 1.64966062e-01
1.07829869e+00 -6.46581054e-01 -2.41306186e-01 8.57897997e-02
1.41443801e+00 2.98348218e-02 -1.40480375e+00 -3.13037217e-01
-2.07634136e-01 -9.61784065e-01 2.16066539e-01 -1.06455123e+00
-1.34888375e+00 8.35506558e-01 1.07412589e+00 4.57323976e-02
1.82491589e+00 -1.23931862e-01 6.19549751e-01 -1.96132839e-01
3.08351547e-01 -6.97383821e-01 4.77985173e-01 1.95564806e-01
1.26614702e+00 -1.36097801e+00 3.05739548e-02 -1.74403086e-01
-5.26697993e-01 9.48976278e-01 5.60576499e-01 -3.22976224e-02
4.44401443e-01 -2.53226399e-01 5.03491946e-02 1.19986884e-01
-3.88217717e-01 -1.71791121e-01 6.55774415e-01 6.42083883e-01
1.83491662e-01 -2.38560006e-01 -1.69613212e-01 3.80280435e-01
6.27289340e-02 1.30723417e-01 6.00140572e-01 2.40806580e-01
-2.48813793e-01 -6.60434484e-01 -5.30081689e-01 3.34031999e-01
-5.18468440e-01 -3.49288583e-01 1.93902448e-01 5.69786012e-01
4.06240076e-01 1.07677650e+00 -6.52992353e-02 -4.20970470e-01
3.02390397e-01 -3.55875343e-01 5.01345396e-01 -1.11680515e-01
-3.80451649e-01 8.83398391e-03 -2.13338271e-01 -8.10666621e-01
-6.09347999e-01 -5.07784367e-01 -5.66839695e-01 -2.31906697e-01
-3.08808893e-01 -2.34070241e-01 5.83853185e-01 8.28623474e-01
4.02518570e-01 6.00154996e-01 8.35472643e-01 -9.90457177e-01
-4.74266768e-01 -1.09397304e+00 -4.88735169e-01 6.94119394e-01
5.99251747e-01 -7.68397748e-01 -7.59080291e-01 2.21529812e-01] | [11.7786865234375, -1.916977047920227] |
bd4f03e3-92ad-42cd-bea3-cd8277931d31 | multi-class-cell-detection-using-spatial-1 | 2110.04886 | null | https://arxiv.org/abs/2110.04886v2 | https://arxiv.org/pdf/2110.04886v2.pdf | Multi-Class Cell Detection Using Spatial Context Representation | In digital pathology, both detection and classification of cells are important for automatic diagnostic and prognostic tasks. Classifying cells into subtypes, such as tumor cells, lymphocytes or stromal cells is particularly challenging. Existing methods focus on morphological appearance of individual cells, whereas in practice pathologists often infer cell classes through their spatial context. In this paper, we propose a novel method for both detection and classification that explicitly incorporates spatial contextual information. We use the spatial statistical function to describe local density in both a multi-class and a multi-scale manner. Through representation learning and deep clustering techniques, we learn advanced cell representation with both appearance and spatial context. On various benchmarks, our method achieves better performance than state-of-the-arts, especially on the classification task. We also create a new dataset for multi-class cell detection and classification in breast cancer and we make both our code and data publicly available. | ['Chao Chen', 'Joel Saltz', 'Dimitris Samaras', 'Tahsin Kurc', 'Rajarsi Gupta', 'Eric Yee', 'Felicia Allard', 'John Van Arnam', 'David Belinsky', 'Shahira Abousamra'] | 2021-10-10 | multi-class-cell-detection-using-spatial | http://openaccess.thecvf.com//content/ICCV2021/html/Abousamra_Multi-Class_Cell_Detection_Using_Spatial_Context_Representation_ICCV_2021_paper.html | http://openaccess.thecvf.com//content/ICCV2021/papers/Abousamra_Multi-Class_Cell_Detection_Using_Spatial_Context_Representation_ICCV_2021_paper.pdf | iccv-2021-1 | ['cell-detection'] | ['computer-vision'] | [ 7.38846585e-02 -2.97637135e-01 -3.06982458e-01 -2.95264542e-01
-1.23434460e+00 -5.67092478e-01 7.04037249e-01 9.84766483e-01
-3.91025275e-01 6.44112885e-01 7.67464936e-02 -3.42311949e-01
1.46875978e-02 -9.05626237e-01 -2.10425884e-01 -1.22833824e+00
2.52004154e-02 8.59474123e-01 2.14981675e-01 3.02664012e-01
1.80115551e-01 9.82429504e-01 -1.00434470e+00 4.99948293e-01
5.43724298e-01 9.33803797e-01 1.68707624e-01 1.05494809e+00
-2.72293210e-01 8.77478123e-01 -2.96981007e-01 2.65515059e-01
-3.53303432e-01 -1.97163045e-01 -8.16745996e-01 7.32856337e-04
3.15084726e-01 1.18326910e-01 -1.43445730e-01 8.91017914e-01
4.67613488e-01 -2.46826425e-01 1.34125590e+00 -6.09276891e-01
-4.36482459e-01 -6.59097880e-02 -1.05408311e+00 4.23532277e-01
-8.15406516e-02 -5.66951632e-02 7.82839954e-01 -6.95585251e-01
8.72412801e-01 8.42297375e-01 7.10229039e-01 3.73237222e-01
-1.59762704e+00 -4.16567445e-01 -2.06330214e-02 1.61821216e-01
-1.78865564e+00 -2.83237934e-01 4.37116414e-01 -6.99066103e-01
6.31791532e-01 3.21581721e-01 4.18740690e-01 7.56973207e-01
4.82493579e-01 9.38352942e-01 1.18687201e+00 -3.71081591e-01
3.91211867e-01 8.89265835e-02 2.42955148e-01 6.86724842e-01
1.95834473e-01 -3.72958302e-01 2.75333412e-02 -2.94530243e-01
9.64465857e-01 4.71025676e-01 -1.07948706e-01 -1.88969210e-01
-1.21686769e+00 7.19566345e-01 4.32376772e-01 5.93989611e-01
-2.25051388e-01 3.09146911e-01 3.86794865e-01 -2.59198159e-01
6.76639676e-01 -7.64657371e-03 -1.20272212e-01 3.46769486e-03
-9.55777228e-01 -4.02870923e-02 5.11625051e-01 3.22059453e-01
6.54669404e-01 -6.92532778e-01 -2.75101036e-01 1.06174326e+00
2.35475406e-01 2.78661847e-01 6.76713049e-01 -4.80048627e-01
-3.79574150e-01 8.52032542e-01 -1.46335468e-01 -1.07850099e+00
-7.90996552e-01 -6.40390456e-01 -1.12921858e+00 3.07593733e-01
7.45489478e-01 3.08070093e-01 -1.04298210e+00 1.31739008e+00
6.87062085e-01 5.91085911e-01 -1.53249383e-01 6.88934267e-01
7.74118125e-01 5.11634767e-01 1.01424366e-01 -1.11409910e-01
1.52359116e+00 -6.25398517e-01 -7.16836989e-01 -6.75249891e-03
1.40176523e+00 -4.80816901e-01 6.56765342e-01 1.71961293e-01
-7.33071566e-01 -9.94682014e-02 -6.29827440e-01 -1.98148221e-01
-5.41072190e-01 3.56420994e-01 6.59490943e-01 2.36693650e-01
-1.08014226e+00 3.54446799e-01 -1.20019817e+00 -5.90083838e-01
9.16626990e-01 1.99502543e-01 -5.77727318e-01 -1.13467097e-01
-2.89107352e-01 5.42947292e-01 -2.70891607e-01 -2.59515673e-01
-5.18668175e-01 -7.78771639e-01 -8.03445280e-01 -2.19573468e-01
-3.29920858e-01 -5.99632382e-01 1.00494659e+00 -5.77563643e-01
-1.04525805e+00 1.42296958e+00 -5.56370020e-01 -2.65467584e-01
3.67968410e-01 4.06383693e-01 -2.07147002e-01 3.57501149e-01
1.38699993e-01 4.72649306e-01 1.23390324e-01 -1.36114168e+00
-9.02517617e-01 -6.07982457e-01 -4.78775710e-01 -2.15502307e-02
-1.25672832e-01 -2.87218869e-01 -5.17526209e-01 -5.70661783e-01
1.65700689e-01 -8.55486035e-01 -4.01803493e-01 5.53310752e-01
-4.82307851e-01 -1.21318296e-01 9.67189848e-01 -5.53116024e-01
9.75516260e-01 -2.23429847e+00 1.79435924e-01 3.34880322e-01
3.32385004e-01 -1.40531301e-01 8.99966359e-02 -8.61820057e-02
1.46188632e-01 1.83834694e-02 -1.81075916e-01 -5.68174422e-01
-2.40348220e-01 2.01108769e-01 1.19709574e-01 1.12133741e+00
1.39915109e-01 1.04601181e+00 -1.02061391e+00 -9.24474776e-01
5.65251447e-02 8.04257035e-01 -4.58539128e-01 -8.07895511e-02
1.62359998e-01 6.39107108e-01 -4.49565977e-01 1.07045686e+00
6.48557544e-01 -7.07280040e-01 4.11739856e-01 -1.26500428e-01
2.44298518e-01 -1.12629697e-01 -7.55475521e-01 1.36499572e+00
-6.47758722e-01 8.02111149e-01 4.62258011e-01 -8.96858394e-01
6.01593971e-01 6.30984977e-02 6.54202461e-01 -4.59698498e-01
9.42167714e-02 2.68567294e-01 -1.07171714e-01 -1.38613090e-01
3.14505100e-01 -2.56735235e-01 7.33974501e-02 4.15641010e-01
-3.61291349e-01 4.59891595e-02 1.41910672e-01 1.91412464e-01
1.34722126e+00 -3.31746876e-01 5.39385200e-01 -5.28804421e-01
4.18061197e-01 -4.28704657e-02 5.35953164e-01 4.64670986e-01
-2.10328549e-01 9.03035820e-01 8.76035333e-01 -4.32978272e-01
-5.71231663e-01 -1.07699692e+00 -6.24337256e-01 8.57101262e-01
1.66903079e-01 -1.03328682e-01 -3.20470542e-01 -8.64707291e-01
4.76191700e-01 1.60982996e-01 -1.18187153e+00 7.76931345e-02
-5.12761116e-01 -1.14444280e+00 3.97485524e-01 7.77437150e-01
-7.30435401e-02 -6.44827366e-01 -1.60128981e-01 1.06749035e-01
4.64995429e-02 -9.80065942e-01 -4.82517034e-01 2.62486994e-01
-7.99822152e-01 -1.23535144e+00 -6.73158884e-01 -1.01688790e+00
1.16800499e+00 1.96644649e-01 9.00940597e-01 4.85908598e-01
-1.14441085e+00 1.58975631e-01 -2.21167073e-01 -1.95044756e-01
-4.30867344e-01 4.63403277e-02 -2.42032588e-01 2.30467528e-01
4.12211180e-01 -4.02753353e-01 -9.57236588e-01 2.67557561e-01
-7.97727525e-01 4.90339613e-03 7.89214551e-01 1.07835674e+00
1.26398170e+00 -8.31288844e-02 3.04395020e-01 -1.35269988e+00
1.25724688e-01 -8.10222208e-01 -2.59316623e-01 2.05963794e-02
-7.26093575e-02 -1.39045298e-01 4.53611851e-01 -2.54797071e-01
-7.08585680e-01 2.69085586e-01 -1.59920529e-01 -5.45375943e-02
-4.29449201e-01 5.93573630e-01 1.78642824e-01 -2.88583934e-01
6.81477427e-01 3.01187009e-01 1.36316940e-01 -3.54923874e-01
-1.45896822e-01 7.77038038e-01 4.96511370e-01 -3.29905212e-01
3.74154508e-01 1.19780946e+00 4.61796403e-01 -8.83997440e-01
-6.49365008e-01 -8.52161229e-01 -7.12723196e-01 -1.92973185e-02
7.40993261e-01 -8.23144674e-01 -6.05783761e-01 5.53713083e-01
-7.96799481e-01 -7.37386584e-01 -1.79444224e-01 2.73225248e-01
-4.76409882e-01 2.79322654e-01 -1.13298345e+00 -5.24631560e-01
-2.71700020e-03 -9.10615265e-01 1.71807098e+00 1.90181896e-01
-3.39782178e-01 -1.55494082e+00 3.83081347e-01 1.64505899e-01
3.38063806e-01 5.32215178e-01 1.01897538e+00 -5.07064164e-01
-4.92253274e-01 -4.60618675e-01 -4.29808050e-01 -4.40476060e-01
5.01641095e-01 3.24608684e-01 -9.69487488e-01 -3.68788570e-01
-6.16068065e-01 -1.33274883e-01 1.26915574e+00 7.83875763e-01
1.77773249e+00 -3.76665927e-02 -1.30533469e+00 1.03585243e+00
1.48316348e+00 -1.34956136e-01 6.14127755e-01 1.57792643e-01
7.69853711e-01 6.15391374e-01 5.27523577e-01 4.11667198e-01
2.32654512e-01 6.34735465e-01 2.69877583e-01 -5.11850059e-01
-3.44796062e-01 2.13579744e-01 -3.53836864e-01 4.40668434e-01
1.00520030e-01 -1.37875304e-01 -1.20697474e+00 8.72571051e-01
-1.82998109e+00 -8.74730945e-01 -1.00268245e-01 1.91595125e+00
1.04051542e+00 -1.58616632e-01 -3.64759713e-02 1.07726723e-01
6.82597160e-01 -1.34033427e-01 -4.81055617e-01 2.54965499e-02
-6.63263500e-02 4.89274040e-02 5.60825765e-01 5.52194536e-01
-1.35681081e+00 5.43260038e-01 6.43136406e+00 1.23244989e+00
-1.29684520e+00 2.62872055e-02 1.56384385e+00 -1.51681751e-01
-1.58548847e-01 -4.58554536e-01 -9.10697281e-01 3.64495754e-01
5.34180105e-01 2.41729438e-01 -2.68082768e-01 4.85133439e-01
3.00670937e-02 -3.64596844e-01 -1.23927295e+00 1.12434959e+00
-1.86913505e-01 -1.70998371e+00 -2.98452266e-02 6.44268215e-01
7.10616887e-01 -6.89950362e-02 9.25415456e-02 2.75103841e-02
3.35802972e-01 -1.50127769e+00 1.53929457e-01 7.71864831e-01
1.06481254e+00 -6.78684771e-01 9.55241621e-01 2.39936218e-01
-1.31084192e+00 1.05022557e-01 -1.65432990e-01 3.41405571e-01
-1.81644708e-01 8.21521223e-01 -8.90053749e-01 1.60903513e-01
2.79589683e-01 1.14037883e+00 -8.10446322e-01 1.10170150e+00
3.74373287e-01 5.92878640e-01 -2.85507649e-01 -1.31659105e-01
1.50775781e-03 -1.07052952e-01 1.30307883e-01 1.79070807e+00
4.64576811e-01 1.04767748e-03 2.50366747e-01 5.44496357e-01
6.15231134e-02 1.58220038e-01 -3.66595536e-01 5.43256477e-02
3.99868786e-01 1.87809634e+00 -1.30052054e+00 -1.73446864e-01
-2.83196211e-01 8.20865393e-01 6.38306677e-01 3.02762121e-01
-6.04279637e-01 -2.77738422e-01 9.17056441e-01 5.79520047e-01
1.58622950e-01 -1.43133476e-01 -4.97839391e-01 -7.00945854e-01
-3.47958982e-01 -2.34881043e-01 5.11109531e-01 -1.32028490e-01
-1.57204652e+00 2.44306967e-01 -4.69980627e-01 -1.10636878e+00
-4.39304337e-02 -9.75739539e-01 -6.99290574e-01 5.55474222e-01
-1.67783368e+00 -1.26572084e+00 -5.07750988e-01 1.76917687e-01
1.84062541e-01 5.60913831e-02 1.02832615e+00 2.10829124e-01
-5.22629857e-01 5.19685268e-01 6.20724916e-01 4.05910611e-01
7.17145622e-01 -1.63549054e+00 -5.99098206e-02 -3.64113264e-02
-1.28505453e-01 4.07870471e-01 4.06561434e-01 -4.24091965e-01
-1.20756996e+00 -1.44194221e+00 5.46957731e-01 -4.61218297e-01
6.92029715e-01 -4.80993778e-01 -9.34812248e-01 4.01101857e-01
-2.07980320e-01 8.29907715e-01 1.15896487e+00 5.98804578e-02
-8.77751857e-02 -1.83743238e-01 -1.30861664e+00 5.92337132e-01
7.35825956e-01 -6.92712426e-01 4.00689751e-01 6.31402910e-01
-2.17073858e-02 -5.40307045e-01 -9.89529669e-01 2.66533494e-01
5.00070512e-01 -7.94985533e-01 9.87604976e-01 -1.21934041e-01
2.81448036e-01 -3.96132052e-01 -6.19777888e-02 -1.27682984e+00
-6.96536601e-01 1.64864436e-02 -9.52060074e-02 8.80664289e-01
4.37543154e-01 -6.40613854e-01 1.14765334e+00 -5.77828735e-02
-1.12764016e-01 -1.30604160e+00 -1.03545749e+00 -5.17104268e-01
4.80201453e-01 8.34544003e-02 3.19503307e-01 9.52671587e-01
1.57225698e-01 9.24868807e-02 3.35872561e-01 8.74335468e-02
5.26451945e-01 2.63621598e-01 5.73792577e-01 -1.29837692e+00
-2.72888899e-01 -8.15596879e-01 -1.01820135e+00 -8.18753839e-01
2.63203591e-01 -1.12443173e+00 -1.07344970e-01 -1.64797497e+00
6.47590816e-01 -7.26839364e-01 -5.28161824e-01 2.98716784e-01
-2.12261304e-01 6.36572957e-01 -5.09105742e-01 3.52067262e-01
-7.32767045e-01 6.83723539e-02 1.29900134e+00 -4.53613549e-01
1.38586789e-01 -3.51092905e-01 -6.61571860e-01 5.51985860e-01
6.73430145e-01 -2.63335854e-01 5.34440801e-02 -5.06460890e-02
5.36531257e-03 -6.10350817e-02 5.89256227e-01 -1.15625811e+00
3.62768173e-01 -2.74303406e-01 9.25887406e-01 -6.90632820e-01
5.89183569e-01 -5.19004345e-01 5.03580552e-03 4.33477730e-01
-3.81752789e-01 -4.28461701e-01 2.51203388e-01 9.15690422e-01
-2.52645999e-01 1.16550088e-01 1.11985338e+00 -4.13615839e-04
-3.11777800e-01 4.79734808e-01 -5.81152022e-01 -2.38252237e-01
1.33533597e+00 -2.62799859e-01 -5.86427152e-01 -1.82200387e-01
-7.20378816e-01 2.15632752e-01 7.79979706e-01 -3.12008142e-01
5.31448543e-01 -1.37011158e+00 -8.84715080e-01 7.60917515e-02
4.38952476e-01 2.23333493e-01 2.99873680e-01 1.25933111e+00
-9.82752323e-01 2.20854849e-01 1.74757391e-01 -1.02860510e+00
-1.40507519e+00 2.19435126e-01 6.02398694e-01 -5.65268278e-01
-4.00443703e-01 1.00752223e+00 7.61156201e-01 -3.42712492e-01
6.95831031e-02 -4.08916801e-01 -3.78897429e-01 -1.98206194e-02
7.32138395e-01 9.41959247e-02 -4.72304411e-03 -8.55016947e-01
-5.43395936e-01 6.69036031e-01 -5.06951451e-01 2.95757174e-01
1.19461966e+00 1.04005069e-01 -2.87761569e-01 7.27546513e-01
1.48260427e+00 1.08313560e-01 -1.23355758e+00 -2.82187343e-01
-1.68439951e-02 -4.96818513e-01 3.24203163e-01 -6.60997152e-01
-1.10727012e+00 8.91955733e-01 6.20120764e-01 1.45216882e-01
9.01797295e-01 4.14328039e-01 6.06289566e-01 9.25332606e-02
1.42036334e-01 -9.87223804e-01 7.97048733e-02 3.41908514e-01
4.71025437e-01 -1.36182189e+00 2.02417761e-01 -5.83559394e-01
-2.98139125e-01 1.06347930e+00 3.64885211e-01 -1.86793268e-01
9.67461646e-01 6.82651579e-01 3.47474724e-01 -2.64448076e-01
-9.53256905e-01 -6.80314377e-02 1.46463335e-01 6.90264463e-01
9.38753843e-01 3.21602434e-01 1.35668784e-01 4.91426945e-01
2.81036705e-01 -1.72195822e-01 3.64457458e-01 9.70389128e-01
-4.63138491e-01 -9.81527448e-01 -3.11549306e-01 8.61502409e-01
-6.88959956e-01 8.68476108e-02 -4.66612965e-01 6.46410346e-01
-1.50415376e-01 4.45301741e-01 6.39712274e-01 5.54558961e-03
-2.30168357e-01 -4.69198704e-01 4.67022121e-01 -7.78030217e-01
-2.14160368e-01 1.45005316e-01 -1.95290431e-01 -3.09837818e-01
-1.13397092e-01 -9.03840661e-01 -1.56462419e+00 -2.28501976e-01
-1.45284757e-01 -1.30758345e-01 4.94314224e-01 6.99980736e-01
3.26529682e-01 5.43511033e-01 4.62831974e-01 -7.47764945e-01
-5.92619963e-02 -9.24531221e-01 -1.15223062e+00 3.58357012e-01
6.01146460e-01 -5.25227726e-01 -2.87300348e-01 9.60220620e-02] | [14.999223709106445, -3.0634548664093018] |
a593602e-563d-4529-8bfc-1883cc31fc57 | thurstonian-boltzmann-machines-learning-from | 1408.0055 | null | http://arxiv.org/abs/1408.0055v1 | http://arxiv.org/pdf/1408.0055v1.pdf | Thurstonian Boltzmann Machines: Learning from Multiple Inequalities | We introduce Thurstonian Boltzmann Machines (TBM), a unified architecture
that can naturally incorporate a wide range of data inputs at the same time.
Our motivation rests in the Thurstonian view that many discrete data types can
be considered as being generated from a subset of underlying latent continuous
variables, and in the observation that each realisation of a discrete type
imposes certain inequalities on those variables. Thus learning and inference in
TBM reduce to making sense of a set of inequalities. Our proposed TBM naturally
supports the following types: Gaussian, intervals, censored, binary,
categorical, muticategorical, ordinal, (in)-complete rank with and without
ties. We demonstrate the versatility and capacity of the proposed model on
three applications of very different natures; namely handwritten digit
recognition, collaborative filtering and complex social survey analysis. | ['Svetha Venkatesh', 'Truyen Tran', 'Dinh Phung'] | 2014-08-01 | null | null | null | null | ['handwritten-digit-recognition'] | ['computer-vision'] | [ 1.88727841e-01 1.72732010e-01 -5.81363142e-01 -7.71135628e-01
-1.34650961e-01 -5.48391521e-01 1.03543139e+00 2.94969324e-02
-5.11851907e-01 1.12552130e+00 3.11388284e-01 -6.71815455e-01
-7.64899433e-01 -1.12500370e+00 -7.08088458e-01 -6.24694109e-01
-3.18963766e-01 1.14749396e+00 -3.47491622e-01 1.60912409e-01
2.51057833e-01 5.13493121e-01 -1.44213235e+00 2.93878883e-01
6.87416315e-01 1.13127530e+00 -2.20970154e-01 8.50348949e-01
-3.97267610e-01 9.33975756e-01 -3.47527772e-01 -8.01713705e-01
-7.89630860e-02 6.21283650e-02 -7.45364606e-01 -2.42162138e-01
2.28145584e-01 -2.76467860e-01 -9.70458016e-02 1.09781218e+00
-8.51650313e-02 2.31979519e-01 1.56540680e+00 -1.73469555e+00
-1.07159579e+00 8.01745117e-01 -4.92580205e-01 -1.83693230e-01
1.15420721e-01 -4.22154605e-01 1.25631976e+00 -8.26555789e-01
8.19059163e-02 1.49981356e+00 8.42125893e-01 4.74105477e-01
-1.59819233e+00 -5.67802668e-01 5.34675121e-02 9.77436155e-02
-1.03967547e+00 -2.21490711e-01 5.74077368e-01 -6.28656030e-01
5.79764962e-01 7.65568554e-01 4.49699789e-01 1.42038155e+00
3.93336564e-01 5.71230650e-01 1.34839046e+00 -4.43180799e-01
6.91314161e-01 2.40703583e-01 5.80483794e-01 3.55579823e-01
3.88475746e-01 5.16478047e-02 -3.94537777e-01 -7.38728702e-01
7.83064842e-01 3.37327391e-01 4.19992119e-01 -3.61798197e-01
-9.78761554e-01 1.26106238e+00 2.68031191e-02 1.02542769e-02
-3.59840542e-01 3.15235823e-01 1.77091748e-01 3.76198620e-01
4.48923409e-01 -2.38789376e-02 -4.94034082e-01 1.37082562e-01
-1.06937504e+00 1.23756714e-01 1.12595606e+00 1.02542543e+00
5.45004189e-01 -3.44829887e-01 -2.09442407e-01 7.12117910e-01
6.78749919e-01 2.95334458e-01 4.70579147e-01 -7.93541014e-01
3.79457057e-01 2.02657223e-01 5.63115001e-01 -7.83964455e-01
-3.25747937e-01 -9.13881883e-02 -1.46421385e+00 4.49792594e-01
5.95913410e-01 -1.04935750e-01 -9.67275977e-01 1.98072934e+00
3.35537568e-02 1.04529627e-01 -5.13003245e-02 2.21206531e-01
5.21651447e-01 6.41870201e-01 8.69607925e-02 -8.19332674e-02
1.04482305e+00 -3.11895192e-01 -6.81713939e-01 1.14962170e-02
-2.17168242e-01 -1.73680440e-01 6.87093019e-01 8.56633365e-01
-1.08886266e+00 -5.46944916e-01 -8.49076092e-01 2.41045561e-02
-5.92044830e-01 -3.61082375e-01 1.13917267e+00 9.24519122e-01
-9.88711953e-01 6.70581341e-01 -8.55121493e-01 -1.04061499e-01
6.07407689e-01 5.48933089e-01 -1.90866232e-01 1.23744205e-01
-1.24070001e+00 6.59248531e-01 2.26191357e-01 1.67825297e-01
-8.61075580e-01 -3.13660175e-01 -2.79465646e-01 9.13515836e-02
6.38649836e-02 -7.43922651e-01 7.96648324e-01 -8.27040672e-01
-1.38749564e+00 1.00974250e+00 -3.60268950e-02 -5.89641213e-01
7.43685126e-01 -9.09913778e-02 -2.96153247e-01 -6.67663872e-01
-3.07031840e-01 4.49071616e-01 8.17096412e-01 -8.52724612e-01
-6.55689240e-01 -6.29411459e-01 1.58490598e-01 -9.34109986e-02
-3.84885520e-01 -1.77572519e-01 2.44915053e-01 -4.22924548e-01
7.55820125e-02 -7.22243130e-01 -2.58501232e-01 -5.12523651e-02
-5.16281188e-01 -6.35834932e-01 8.35234001e-02 -4.28995132e-01
1.00793338e+00 -1.72229922e+00 6.14266992e-01 3.11441988e-01
2.02760115e-01 -4.55743432e-01 2.71357507e-01 4.55456257e-01
1.37415722e-01 4.30149496e-01 -2.08203837e-01 -3.80359799e-01
5.17518461e-01 8.36661875e-01 -6.28867030e-01 5.98382473e-01
-1.70214742e-01 6.99328840e-01 -6.05946243e-01 -5.64662278e-01
1.69228002e-01 -3.87844183e-02 -6.75503492e-01 2.01531783e-01
-3.04467261e-01 2.41936594e-01 -2.70156682e-01 4.34520394e-01
6.44883215e-01 -4.06953990e-02 2.01887801e-01 3.49553764e-01
-3.02714594e-02 -2.28022095e-02 -1.34728193e+00 1.23584473e+00
-3.63423258e-01 2.58674085e-01 4.61220965e-02 -1.27540505e+00
8.99682641e-01 1.93612993e-01 2.69579947e-01 -4.01243567e-02
1.94892526e-01 7.40048811e-02 -1.55225378e-02 -4.03105974e-01
3.65806192e-01 -3.46627116e-01 -3.07069749e-01 3.28001112e-01
2.88710654e-01 8.28600302e-02 -2.66819537e-01 -2.26776034e-01
6.27554715e-01 -1.97027862e-01 3.41654211e-01 -5.41545212e-01
2.52931088e-01 -5.56451857e-01 5.36602914e-01 1.56958902e+00
-1.05294883e-01 9.68027934e-02 8.59198153e-01 -5.38358569e-01
-1.19210768e+00 -1.67399180e+00 -5.18404543e-01 1.38046396e+00
-1.76055387e-01 5.06258667e-01 -2.40721226e-01 -3.86618763e-01
2.94530123e-01 8.22904527e-01 -1.04530525e+00 4.56340499e-02
1.12638727e-01 -1.10385847e+00 7.10559368e-01 4.42934334e-01
2.02031046e-01 -1.10025716e+00 -4.50642526e-01 1.10408500e-01
1.17625808e-02 -3.24030936e-01 1.20689593e-01 6.22985959e-01
-1.04291844e+00 -6.44583762e-01 -4.82241631e-01 -6.77185416e-01
2.19258472e-01 -7.05870748e-01 1.40656948e+00 -4.53230530e-01
-2.14221776e-01 1.42100096e-01 -5.84993362e-02 -5.45905590e-01
-4.65877026e-01 -9.95675921e-02 2.32575521e-01 2.53179073e-01
5.38941979e-01 -1.02037477e+00 -3.90670776e-01 -1.74551588e-02
-9.08560157e-01 2.17309192e-01 3.53810936e-01 1.06814170e+00
2.37230569e-01 2.86652178e-01 7.04754174e-01 -9.50093687e-01
5.95124304e-01 -1.06641841e+00 -3.87312710e-01 3.96198332e-01
-3.76075298e-01 7.25235268e-02 5.60189545e-01 -8.26221287e-01
-9.59094644e-01 -2.82574862e-01 -9.03403759e-02 -1.68831777e-02
-5.56478858e-01 8.26312542e-01 -4.69677359e-01 6.66659951e-01
4.18361157e-01 3.06597441e-01 -1.00742705e-01 -4.96003032e-01
6.73245430e-01 1.03607547e+00 6.41047895e-01 -1.03422928e+00
2.81663626e-01 7.55210400e-01 2.26982936e-01 -7.32723057e-01
-6.45225823e-01 -7.47235268e-02 -8.43449235e-01 7.76155619e-03
8.22619736e-01 -3.41344446e-01 -9.87543344e-01 6.92372203e-01
-9.83529508e-01 -2.80658871e-01 -1.04658976e-01 3.65768909e-01
-6.70574605e-01 1.55938014e-01 -6.85044289e-01 -1.41956913e+00
-8.49214420e-02 -5.16665041e-01 4.03536588e-01 8.44628960e-02
-4.11635906e-01 -1.24609768e+00 -8.01972672e-03 2.46700093e-01
3.35555643e-01 4.65970129e-01 1.44467974e+00 -8.18560481e-01
-9.03184265e-02 -3.92295301e-01 2.14387134e-01 4.28507596e-01
9.82387513e-02 7.26045370e-02 -8.12765479e-01 -2.55994827e-01
1.11637004e-01 -6.20120823e-01 8.99309874e-01 6.09192848e-01
1.43612325e+00 -5.24336517e-01 -4.33424897e-02 5.66001952e-01
1.38981068e+00 3.22289795e-01 5.50362408e-01 9.82017517e-02
2.51190215e-01 6.39150143e-01 6.72976896e-02 6.67992115e-01
2.16546744e-01 2.16655031e-01 8.53801310e-01 -3.64226811e-02
7.16253996e-01 -1.58290923e-01 1.51249588e-01 5.07593572e-01
-1.81233540e-01 -3.87579411e-01 -7.45323837e-01 5.89937449e-01
-2.08978581e+00 -1.34201300e+00 -1.64715886e-01 2.40019011e+00
1.10789716e+00 3.83050472e-01 1.14938505e-01 9.66296643e-02
8.33243489e-01 -8.02475885e-02 -8.44472647e-01 -6.56633675e-01
-1.17931969e-01 3.07277650e-01 5.89874089e-01 5.70884645e-01
-1.16577399e+00 4.20192838e-01 6.60144472e+00 9.07567441e-01
-7.93227017e-01 1.36757299e-01 8.94566715e-01 6.16280315e-03
-4.17599708e-01 -2.53310412e-01 -5.67425430e-01 6.31368339e-01
8.57372463e-01 -1.93331525e-01 6.76255524e-01 7.69331217e-01
-1.50111377e-01 -2.15329733e-02 -1.56358147e+00 7.88188517e-01
-3.02769303e-01 -1.11365974e+00 7.28454068e-02 3.78659457e-01
6.93896294e-01 1.68647822e-02 5.58135390e-01 4.31014299e-01
1.17107201e+00 -1.59886122e+00 8.71987581e-01 8.91269147e-01
8.31601381e-01 -9.25240397e-01 4.54385221e-01 7.27691591e-01
-5.84608197e-01 -3.15272868e-01 -6.16098225e-01 -6.13735020e-01
-2.32218921e-01 5.48112750e-01 -4.41913486e-01 3.17250699e-01
4.95461434e-01 2.65357792e-01 -1.11571915e-01 7.05118477e-01
2.64186531e-01 9.03925478e-01 -3.09467047e-01 -3.78925204e-01
2.46104643e-01 -4.97067571e-01 1.62004024e-01 1.07047153e+00
3.60492110e-01 -7.55320787e-02 1.52988449e-01 1.07102537e+00
8.90220106e-02 -2.03260317e-01 -4.22342569e-01 1.56077102e-01
7.01470613e-01 1.00969028e+00 -7.67729998e-01 -4.36438769e-01
-4.91546184e-01 6.45559907e-01 3.78029853e-01 4.37105834e-01
-1.08451998e+00 -1.32953852e-01 6.66989982e-01 -1.40552506e-01
1.35724455e-01 -1.71734899e-01 -7.47825325e-01 -1.19770360e+00
-3.73421282e-01 -6.50331557e-01 6.70614958e-01 -4.85592425e-01
-1.92881143e+00 2.19534025e-01 8.75431374e-02 -5.16745985e-01
-1.75662890e-01 -9.34119344e-01 -4.71108586e-01 1.17544949e+00
-8.60365391e-01 -1.26126337e+00 6.48944974e-02 8.31148386e-01
2.28564397e-01 -1.76539734e-01 1.15564287e+00 2.54431106e-02
-3.03208530e-01 3.96690488e-01 7.75103271e-01 2.13095099e-01
2.53192663e-01 -1.68008018e+00 2.88665831e-01 1.99438155e-01
3.50284189e-01 9.09903824e-01 7.90038347e-01 -5.31185329e-01
-1.18512547e+00 -1.02756631e+00 5.23097456e-01 -6.91600919e-01
7.55437434e-01 -7.88032651e-01 -6.29112661e-01 8.13637972e-01
-3.09740715e-02 -3.16817671e-01 9.66458738e-01 7.94925570e-01
-3.80963087e-01 5.81295602e-02 -1.32193100e+00 5.07766902e-01
8.07590902e-01 -6.33572996e-01 -1.01045084e+00 1.77602753e-01
2.07020581e-01 3.12676579e-02 -1.04129899e+00 3.43905995e-03
1.05230713e+00 -1.05916321e+00 1.13246369e+00 -1.32147264e+00
7.17062294e-01 1.33715391e-01 -6.19953930e-01 -1.02581906e+00
-7.72310376e-01 -1.84527069e-01 -2.60325700e-01 1.33337688e+00
1.52553827e-01 -7.63536751e-01 7.94453681e-01 8.85923147e-01
2.64735490e-01 -8.29264283e-01 -1.55692530e+00 -7.79895604e-01
6.36248887e-01 -6.71492100e-01 9.13705528e-01 1.05100191e+00
-5.43460697e-02 8.51684660e-02 -8.19591165e-01 1.74160928e-01
9.74260211e-01 3.26969534e-01 4.98239517e-01 -1.88291919e+00
-6.65917277e-01 -4.73458469e-01 -3.32564980e-01 -8.53117764e-01
2.75429577e-01 -1.04323971e+00 -8.18750914e-03 -1.37743855e+00
5.40972412e-01 -6.77711427e-01 -8.61327231e-01 1.66444540e-01
2.27238029e-01 8.72471705e-02 -3.02158624e-01 2.46182054e-01
-3.51756364e-01 4.13163126e-01 5.15662014e-01 -2.01203406e-01
1.10657122e-02 4.24202055e-01 -6.77752197e-01 9.83688176e-01
6.51313841e-01 -3.42237920e-01 -3.23572576e-01 -2.56834626e-01
5.69548488e-01 4.86747652e-01 5.23246825e-01 -5.96975863e-01
1.06425755e-01 -8.24278176e-01 7.52410352e-01 -6.41928852e-01
4.32550102e-01 -7.95354784e-01 4.13622230e-01 5.31011105e-01
-7.83401906e-01 -2.39236161e-01 -2.41911605e-01 7.30496168e-01
1.91150069e-01 -2.47471765e-01 7.40953326e-01 -1.78823233e-01
-3.37418318e-01 2.85639167e-01 -5.25970042e-01 3.53420302e-02
6.23358607e-01 -9.30719972e-02 -7.50682727e-02 -5.54785013e-01
-9.25272584e-01 -1.73532404e-02 7.28557482e-02 3.10193807e-01
3.57180208e-01 -1.39318335e+00 -6.98744655e-01 1.80248573e-01
-2.33445629e-01 -1.68294087e-01 9.17470008e-02 4.58742529e-01
7.99863264e-02 3.72730732e-01 -6.15580678e-01 -5.22950828e-01
-8.91657829e-01 6.63987637e-01 1.84585541e-01 -3.33631307e-01
-5.05295061e-02 9.74643409e-01 2.27892458e-01 -5.43374538e-01
4.08462971e-01 -5.80467701e-01 -3.19211513e-01 2.31132641e-01
1.47519276e-01 5.39441466e-01 -4.11090136e-01 -3.00322652e-01
-2.73004502e-01 1.67555101e-02 2.71806538e-01 -4.56832886e-01
1.49455142e+00 4.33568330e-03 -4.58451718e-01 1.11170602e+00
8.04146469e-01 -1.54824510e-01 -1.04240549e+00 -9.75394249e-02
1.54376402e-01 -2.00882971e-01 -1.78564861e-01 -9.20058429e-01
-1.55003712e-01 9.47147071e-01 3.93637329e-01 7.65599489e-01
7.40617454e-01 -2.64327656e-02 1.65670767e-01 3.22560519e-01
6.25991285e-01 -1.03245389e+00 -4.06591028e-01 4.45422590e-01
8.60051215e-01 -9.09396052e-01 -2.64475912e-01 1.99200138e-01
-1.52481705e-01 1.12593806e+00 1.23267002e-01 -2.65269607e-01
7.40792274e-01 2.68502295e-01 -5.66916406e-01 2.27805078e-01
-8.54326189e-01 3.32145661e-01 2.77634650e-01 6.94784105e-01
5.60597479e-01 5.52854002e-01 -3.26193124e-01 1.03749502e+00
-3.16435963e-01 2.67448306e-01 5.16127765e-01 4.58336860e-01
-3.24797839e-01 -8.78759742e-01 -6.19661987e-01 1.09096706e+00
-6.22189105e-01 -1.02431178e-01 -1.49751261e-01 6.42997563e-01
4.59284335e-01 9.03968215e-01 4.02450770e-01 -1.62412196e-01
-1.44950196e-01 2.63302326e-01 6.43576443e-01 -4.57639962e-01
-1.16387464e-01 -3.12242299e-01 -1.47708684e-01 1.17386527e-01
-2.12976798e-01 -6.64339721e-01 -7.69939899e-01 -5.18640399e-01
-1.23392195e-01 2.22103402e-01 6.23262346e-01 8.62153530e-01
-2.53289074e-01 1.98971242e-01 4.25513566e-01 -7.23543048e-01
-1.11599422e+00 -1.28231847e+00 -9.71574128e-01 5.73722601e-01
4.09521818e-01 -7.61483788e-01 -5.31784654e-01 1.63740981e-02] | [7.731123924255371, 4.278194904327393] |
892bf451-9107-4b9d-8896-bdb355d0c165 | conditional-augmentation-for-aspect-term | 2004.14769 | null | https://arxiv.org/abs/2004.14769v2 | https://arxiv.org/pdf/2004.14769v2.pdf | Conditional Augmentation for Aspect Term Extraction via Masked Sequence-to-Sequence Generation | Aspect term extraction aims to extract aspect terms from review texts as opinion targets for sentiment analysis. One of the big challenges with this task is the lack of sufficient annotated data. While data augmentation is potentially an effective technique to address the above issue, it is uncontrollable as it may change aspect words and aspect labels unexpectedly. In this paper, we formulate the data augmentation as a conditional generation task: generating a new sentence while preserving the original opinion targets and labels. We propose a masked sequence-to-sequence method for conditional augmentation of aspect term extraction. Unlike existing augmentation approaches, ours is controllable and allows us to generate more diversified sentences. Experimental results confirm that our method alleviates the data scarcity problem significantly. It also effectively boosts the performances of several current models for aspect term extraction. | ['Yan Song', 'Qing Ling', 'Kun Li', 'Chengbo Chen', 'Xiaojun Quan'] | 2020-04-30 | conditional-augmentation-for-aspect-term-1 | https://aclanthology.org/2020.acl-main.631 | https://aclanthology.org/2020.acl-main.631.pdf | acl-2020-6 | ['extract-aspect'] | ['natural-language-processing'] | [ 6.21046245e-01 4.31610674e-01 -4.83662069e-01 -3.73498082e-01
-9.07186925e-01 -8.88288975e-01 6.47080123e-01 2.17967495e-01
-1.69129953e-01 9.19585228e-01 3.28386545e-01 -4.15923983e-01
5.10219812e-01 -7.51275182e-01 -4.41217184e-01 -5.11706531e-01
3.69824469e-01 3.22540790e-01 -1.21630564e-01 -6.27232194e-01
3.68329614e-01 1.49598673e-01 -1.51344013e+00 3.80397379e-01
9.60946202e-01 6.74074173e-01 -1.56780943e-01 4.72816557e-01
-5.08047581e-01 6.68187976e-01 -9.98403251e-01 -7.12928712e-01
2.93801963e-01 -5.64361453e-01 -6.45859361e-01 4.17675525e-01
1.56957999e-01 -4.57841754e-02 3.83043587e-01 1.01223207e+00
3.68058801e-01 -1.14943236e-01 5.99627376e-01 -1.25571668e+00
-6.54306829e-01 8.28886807e-01 -8.76099408e-01 -5.76309934e-02
2.63168603e-01 -3.88299152e-02 1.43914187e+00 -8.65101337e-01
6.10457301e-01 9.04987514e-01 4.46729302e-01 7.36830831e-01
-1.06350958e+00 -4.19277608e-01 5.69488406e-01 -3.03358078e-01
-8.31314743e-01 -5.25507927e-01 9.55456674e-01 -2.00987443e-01
1.02321446e+00 5.09871602e-01 8.51301193e-01 9.95478630e-01
2.15760060e-02 1.07928383e+00 1.00138319e+00 -6.38709366e-01
2.63329178e-01 4.71290827e-01 3.11827332e-01 4.62794900e-01
4.44795400e-01 -3.02906454e-01 -6.42732382e-01 -1.83961600e-01
3.00759673e-01 -2.29051441e-01 -2.30099455e-01 -1.08353741e-01
-1.08073378e+00 8.56718659e-01 -1.88234434e-01 3.04707557e-01
-4.46834296e-01 -1.45628631e-01 4.63847131e-01 2.54339367e-01
8.83322001e-01 9.01646018e-01 -9.96006370e-01 -1.91911519e-01
-6.33225381e-01 2.18254045e-01 9.21810567e-01 1.16668332e+00
7.79946923e-01 4.03186768e-01 -3.93173009e-01 5.84557593e-01
-4.47875746e-02 6.33373141e-01 4.96802002e-01 -3.97468507e-01
4.93322998e-01 1.06492412e+00 1.83933362e-01 -8.09197485e-01
-3.73713046e-01 -5.73789418e-01 -5.23535371e-01 1.15458034e-01
5.88398986e-02 -4.20907021e-01 -1.13155520e+00 1.68870175e+00
4.02063310e-01 -4.43020791e-01 6.53128251e-02 5.20287335e-01
6.88267112e-01 5.33868372e-01 1.18615881e-01 -4.89285588e-01
1.78786421e+00 -1.12863243e+00 -1.17057967e+00 -7.75455177e-01
6.03558302e-01 -9.42707121e-01 1.17035556e+00 1.59170166e-01
-8.32307398e-01 -1.12419873e-01 -1.10007763e+00 1.24116674e-01
-4.55348551e-01 2.23648399e-01 1.10980475e+00 8.28460693e-01
-6.76968873e-01 -1.36063829e-01 -6.06195092e-01 1.16545230e-01
3.07786494e-01 4.41597313e-01 -3.04868996e-01 2.47358456e-01
-1.16425490e+00 7.30411172e-01 2.12733015e-01 2.56915577e-03
-2.74389565e-01 -7.73282826e-01 -1.08313286e+00 -5.07288873e-02
6.13136590e-01 -6.73658371e-01 1.43200481e+00 -1.22011542e+00
-1.30062699e+00 6.01442516e-01 -6.41214013e-01 -2.12862685e-01
-1.60113478e-03 -3.03821445e-01 -3.87343407e-01 -2.19358176e-01
2.94705838e-01 6.63384378e-01 1.12374842e+00 -1.33169711e+00
-6.22117817e-01 -2.60358334e-01 2.54557818e-01 2.43053809e-01
-6.83353007e-01 1.65214743e-02 -4.60056186e-01 -9.74137127e-01
-1.47296190e-01 -9.81510878e-01 -6.61975026e-01 -6.05317235e-01
-5.64381480e-01 -3.29078808e-02 6.84635162e-01 -3.85239542e-01
1.35319412e+00 -1.80201185e+00 -9.65692028e-02 4.25451435e-03
2.05282792e-01 4.08182085e-01 -3.13903749e-01 3.76846224e-01
-1.38368741e-01 4.39050138e-01 -4.94474798e-01 -4.95008707e-01
-2.11322337e-01 7.25735202e-02 -6.00097716e-01 -1.71850622e-01
6.39267325e-01 1.21996951e+00 -8.67368400e-01 -4.30215776e-01
-1.10523202e-01 4.73376125e-01 -5.28360307e-01 2.17480272e-01
-6.69664681e-01 3.18550199e-01 -4.28849012e-01 7.92846262e-01
5.74767828e-01 -1.05463535e-01 1.40451282e-01 -1.72422186e-01
3.98230664e-02 6.05452895e-01 -8.97478402e-01 1.28100753e+00
-5.80761969e-01 5.10217965e-01 -2.33243674e-01 -6.53528035e-01
9.47997868e-01 4.54534531e-01 4.00511086e-01 -4.20074135e-01
1.44959986e-01 2.02535838e-03 -1.15225278e-01 -3.58402222e-01
9.79621053e-01 -6.55555665e-01 -3.70076239e-01 7.56696522e-01
-1.26747817e-01 -4.61360484e-01 5.98950386e-01 1.50332585e-01
9.40811455e-01 -4.98565957e-02 6.23967171e-01 -4.39033695e-02
5.18689156e-01 2.00125560e-01 8.90199006e-01 4.73973423e-01
1.48144394e-01 6.72021449e-01 7.69255936e-01 -2.80168802e-01
-9.28215742e-01 -5.45058131e-01 2.35710099e-01 9.28569078e-01
-2.30406389e-01 -7.57536113e-01 -5.62784016e-01 -1.21143150e+00
-3.99517655e-01 8.45507860e-01 -6.97192192e-01 -1.70753971e-01
-6.46585166e-01 -1.06750190e+00 2.60748118e-01 4.65630472e-01
1.80153161e-01 -1.14413071e+00 -1.52814567e-01 1.80663496e-01
-5.63627183e-01 -1.25433290e+00 -6.12367213e-01 1.85714036e-01
-6.80923462e-01 -9.13548470e-01 -2.49161527e-01 -7.97763526e-01
1.09857059e+00 3.54003757e-01 1.35125804e+00 -5.71146198e-02
-1.37619087e-02 4.69605848e-02 -6.08249843e-01 -9.06379461e-01
-5.33000708e-01 3.66434515e-01 -1.40864208e-01 -1.90947354e-02
8.42734039e-01 -4.60500956e-01 -4.36366051e-01 -6.30409569e-02
-1.27016175e+00 -8.17375912e-05 7.13045657e-01 7.00143874e-01
6.09505475e-01 1.18874907e-01 8.03098977e-01 -1.55905306e+00
1.02527273e+00 -8.22667703e-02 -5.56611598e-01 9.05145109e-02
-9.76932108e-01 1.32956862e-01 6.40574634e-01 -5.12852848e-01
-1.02128196e+00 2.24999487e-01 -2.05986217e-01 3.94620180e-01
4.37821150e-02 6.39261842e-01 -3.24631155e-01 3.02101582e-01
4.29065764e-01 2.39936829e-01 -1.32072017e-01 -2.98336953e-01
5.89946628e-01 5.83810508e-01 -3.68784964e-02 -2.36884996e-01
1.08106744e+00 4.59144443e-01 -1.44064829e-01 -8.45840335e-01
-1.35253716e+00 -4.02526617e-01 -6.60126388e-01 -2.61872094e-02
6.77137494e-01 -1.01780427e+00 -2.69925594e-01 2.34649613e-01
-1.23267734e+00 2.42536411e-01 -6.29877031e-01 -6.76254928e-02
-3.64719070e-02 3.15191239e-01 -3.00465018e-01 -9.29193139e-01
-7.59331167e-01 -9.93166804e-01 1.26124680e+00 1.23590425e-01
-5.96560955e-01 -8.89532030e-01 1.27943724e-01 4.93909180e-01
4.52591687e-01 1.71783999e-01 9.07915771e-01 -6.41683340e-01
-5.29632926e-01 -6.40410960e-01 1.87643632e-01 5.00352144e-01
6.66952729e-01 -8.05258751e-02 -8.79154742e-01 4.91430201e-02
2.96267420e-01 -1.59174502e-01 7.08818495e-01 -2.09634677e-02
6.66781902e-01 -6.82116210e-01 -1.68702612e-03 7.59389019e-03
1.07923210e+00 1.76317126e-01 4.75322843e-01 3.63163561e-01
8.25082123e-01 6.19963527e-01 7.83481359e-01 3.47555876e-01
4.83210415e-01 5.25432348e-01 1.76750213e-01 -2.25480601e-01
-1.30585641e-01 -1.83061436e-01 5.68872511e-01 1.08274543e+00
3.28197569e-01 -3.37222815e-01 -6.25858545e-01 8.54385674e-01
-1.61244416e+00 -7.16100693e-01 -2.57604659e-01 1.84269047e+00
1.20535874e+00 2.51039386e-01 -1.54865738e-02 3.84186089e-01
4.09623235e-01 3.93827587e-01 -2.82918453e-01 -5.52456737e-01
-3.43581259e-01 2.37858176e-01 1.82208288e-02 6.51888609e-01
-1.10120618e+00 1.13493431e+00 6.19563723e+00 5.38125336e-01
-8.89060616e-01 5.86714409e-03 5.84645092e-01 -1.40203893e-01
-8.85342240e-01 2.56120235e-01 -1.00678229e+00 2.15925112e-01
6.53284371e-01 -2.17476413e-01 -3.54741625e-02 8.16956699e-01
1.46462381e-01 -1.54317111e-01 -9.90494072e-01 4.77903754e-01
4.49035555e-01 -1.10652542e+00 5.36332607e-01 -7.28589967e-02
9.90590513e-01 -4.33018982e-01 7.85907581e-02 3.74271929e-01
1.11600317e-01 -8.18509519e-01 3.90176862e-01 4.49801721e-02
5.81737638e-01 -8.56268585e-01 8.41359794e-01 1.85635179e-01
-1.12480223e+00 2.00165644e-01 -3.15307155e-02 -3.48430097e-01
4.95439529e-01 1.22200131e+00 -9.47041571e-01 3.30674648e-01
2.75746509e-02 4.03574497e-01 -7.29976654e-01 5.21719754e-01
-8.61374557e-01 6.85242712e-01 -5.79782464e-02 -2.80200094e-01
5.46426475e-02 -2.77952999e-01 8.07049751e-01 1.08292913e+00
-6.02459274e-02 -1.03961520e-01 7.00178444e-02 4.51982766e-01
-1.66967943e-01 3.64767313e-01 -9.53281760e-01 -4.16971058e-01
2.00779125e-01 1.53469419e+00 -7.29443312e-01 -3.73947889e-01
-5.23863912e-01 8.86084974e-01 2.50104338e-01 3.87865633e-01
-4.60463911e-01 -4.11160856e-01 7.42303431e-01 -4.84436005e-02
5.34370661e-01 -1.56352326e-01 -7.85074472e-01 -1.46792269e+00
5.07061005e-01 -1.37820828e+00 2.32790649e-01 -4.54457819e-01
-1.16131341e+00 8.68483245e-01 -4.00202870e-01 -1.36842549e+00
-4.68859076e-01 -4.30968344e-01 -4.33720171e-01 6.16328239e-01
-1.58377123e+00 -1.36207247e+00 7.79818892e-02 2.09084377e-02
9.20543969e-01 -2.04631165e-01 9.36030030e-01 1.87493339e-01
-4.28419024e-01 6.91083252e-01 -5.81449687e-01 1.08297102e-01
4.83714700e-01 -1.33230364e+00 6.73002422e-01 1.18282127e+00
3.53162766e-01 9.24834847e-01 1.01813555e+00 -8.09774458e-01
-1.36244369e+00 -1.13049293e+00 1.33502793e+00 -8.11147928e-01
7.64922917e-01 -6.74819648e-01 -6.68383002e-01 6.92730784e-01
3.62108409e-01 -6.04384720e-01 1.03560364e+00 3.91731501e-01
-3.85847479e-01 -2.96358299e-02 -7.19822586e-01 9.81536865e-01
6.14328623e-01 -4.23257917e-01 -6.20848358e-01 4.10268366e-01
1.07450938e+00 -2.27763116e-01 -4.86167103e-01 6.53568327e-01
2.16226846e-01 -5.03807962e-01 6.23134911e-01 -7.43686199e-01
6.51345491e-01 -4.78037864e-01 7.10308254e-02 -1.44139028e+00
1.49898320e-01 -7.36223102e-01 -3.39113683e-01 1.80276644e+00
1.19119680e+00 -4.92978007e-01 9.53133702e-01 8.03246558e-01
1.78444177e-01 -7.94912636e-01 -6.34838700e-01 -6.49981022e-01
-8.97973180e-02 -5.47281861e-01 8.34230781e-01 8.62513185e-01
2.21307740e-01 1.21981239e+00 -6.88196957e-01 -4.87092556e-03
3.85344625e-01 5.50764203e-01 7.73319364e-01 -7.67559409e-01
-3.16996843e-01 -2.38944113e-01 -5.35106547e-02 -9.67049360e-01
3.22689354e-01 -6.84158325e-01 2.12804079e-01 -1.55137217e+00
3.15532982e-01 -2.43947595e-01 2.56350823e-02 7.12592065e-01
-7.64917672e-01 3.29560429e-01 -1.52503597e-02 -2.28711426e-01
-4.35905397e-01 9.19423521e-01 1.20138931e+00 -2.73879737e-01
-4.24805075e-01 4.56932813e-01 -1.48159730e+00 6.74222767e-01
1.00951540e+00 -6.58978641e-01 -6.49618328e-01 -3.49494845e-01
7.98869252e-01 -4.56339300e-01 -2.74972528e-01 -3.40004832e-01
-2.23699987e-01 -8.37392807e-02 -8.77837762e-02 -6.93269849e-01
2.57791311e-01 -8.26255262e-01 -5.20528078e-01 1.14762433e-01
-1.81584090e-01 3.54881704e-01 3.13203275e-01 4.82036144e-01
-4.22335356e-01 -3.17233860e-01 2.49262124e-01 -1.89834744e-01
-3.12550545e-01 1.60506561e-01 -6.83739722e-01 2.26025298e-01
7.81767488e-01 1.76445886e-01 -4.84053373e-01 -5.84790885e-01
-2.58397251e-01 1.78079784e-01 3.89957130e-01 7.20844746e-01
5.79182267e-01 -1.16870916e+00 -6.11224771e-01 2.07223684e-01
3.39502215e-01 4.60809246e-02 -2.64310956e-01 5.35491526e-01
6.51031546e-03 4.42193538e-01 3.66291672e-01 -1.63187116e-01
-1.44972420e+00 6.58904910e-01 -1.56614736e-01 -6.10468626e-01
-3.26159209e-01 6.83766186e-01 2.35593855e-01 -6.72615290e-01
-6.13270402e-02 -9.60671306e-02 -5.80820739e-01 3.96629006e-01
6.66998863e-01 -2.02097952e-01 3.32465470e-01 -4.78747815e-01
-1.98601574e-01 2.96104193e-01 -5.06101191e-01 -3.30284417e-01
1.46367455e+00 -1.88812777e-01 -5.55551052e-01 4.76779729e-01
8.72765422e-01 5.37461221e-01 -6.91368818e-01 -4.42346185e-03
1.17781743e-01 -2.78787047e-01 -1.35367393e-01 -8.70730400e-01
-9.60775912e-01 5.55209160e-01 -7.25828931e-02 4.66813684e-01
1.24438572e+00 -3.13271619e-02 1.03231740e+00 4.70066816e-01
5.02731949e-02 -9.50663149e-01 8.69635940e-02 7.51100481e-01
7.68871009e-01 -1.43058205e+00 2.49991760e-01 -8.69331241e-01
-9.69033122e-01 7.14013875e-01 9.14200485e-01 4.17595536e-01
4.59542513e-01 5.16836226e-01 5.72579086e-01 -3.42860311e-01
-9.90669608e-01 -4.60627526e-01 3.38862687e-01 5.46199322e-01
6.64663970e-01 -5.78459688e-02 -7.07915902e-01 6.40918255e-01
-4.77919966e-01 -4.45300311e-01 9.03583109e-01 1.18278575e+00
-2.51090497e-01 -1.63900220e+00 -1.03074424e-01 6.55095696e-01
-7.60382116e-01 -6.71059489e-01 -7.67846882e-01 5.55227697e-01
-1.26675636e-01 1.18911123e+00 -3.54266018e-01 -2.51431376e-01
3.81147414e-01 2.00745240e-01 8.73495340e-02 -1.02345991e+00
-7.64867187e-01 1.03378333e-01 6.45065606e-01 -4.12851386e-02
-4.68942672e-01 -6.44969583e-01 -1.11227965e+00 2.31274903e-01
-6.15440607e-01 5.11792362e-01 8.15139472e-01 1.10405219e+00
4.51101840e-01 7.26465464e-01 7.74174392e-01 -3.54611248e-01
-2.40260839e-01 -1.02641046e+00 -2.42489114e-01 3.70375991e-01
4.78275478e-01 -2.36956075e-01 -4.08761621e-01 2.24376515e-01] | [11.420455932617188, 6.738393783569336] |
742dacc8-b901-41aa-91bf-0aedcf20354b | federated-learning-based-active | 2104.07158 | null | https://arxiv.org/abs/2104.07158v1 | https://arxiv.org/pdf/2104.07158v1.pdf | Federated Learning-based Active Authentication on Mobile Devices | User active authentication on mobile devices aims to learn a model that can correctly recognize the enrolled user based on device sensor information. Due to lack of negative class data, it is often modeled as a one-class classification problem. In practice, mobile devices are connected to a central server, e.g, all android-based devices are connected to Google server through internet. This device-server structure can be exploited by recently proposed Federated Learning (FL) and Split Learning (SL) frameworks to perform collaborative learning over the data distributed among multiple devices. Using FL/SL frameworks, we can alleviate the lack of negative data problem by training a user authentication model over multiple user data distributed across devices. To this end, we propose a novel user active authentication training, termed as Federated Active Authentication (FAA), that utilizes the principles of FL/SL. We first show that existing FL/SL methods are suboptimal for FAA as they rely on the data to be distributed homogeneously (i.e. IID) across devices, which is not true in the case of FAA. Subsequently, we propose a novel method that is able to tackle heterogeneous/non-IID distribution of data in FAA. Specifically, we first extract feature statistics such as mean and variance corresponding to data from each user which are later combined in a central server to learn a multi-class classifier and sent back to the individual devices. We conduct extensive experiments using three active authentication benchmark datasets (MOBIO, UMDAA-01, UMDAA-02) and show that such approach performs better than state-of-the-art one-class based FAA methods and is also able to outperform traditional FL/SL methods. | ['Vishal M. Patel', 'Poojan Oza'] | 2021-04-14 | null | null | null | null | ['one-class-classification'] | ['miscellaneous'] | [ 2.70747751e-01 -2.94774741e-01 -4.05764639e-01 6.26711398e-02
-1.01480913e+00 -7.59673893e-01 3.66481155e-01 3.37633133e-01
-3.30523312e-01 7.19841301e-01 -4.41928923e-01 -8.03345680e-01
-3.91373158e-01 -7.97709227e-01 -5.62833548e-01 -9.00048852e-01
-1.15270019e-01 1.28563866e-01 1.73962042e-01 1.08296461e-02
-2.07427666e-01 3.70285928e-01 -1.57698822e+00 2.30783060e-01
7.62197316e-01 1.29286504e+00 -2.92911410e-01 6.00768030e-01
-1.17123269e-01 6.96209490e-01 -6.52119458e-01 -3.22834730e-01
2.44302824e-01 -2.14470133e-01 -7.86693573e-01 -4.50791195e-02
-9.47805271e-02 -6.94967955e-02 3.37711632e-01 8.31956804e-01
6.35312378e-01 -7.69895092e-02 5.07389843e-01 -1.62789333e+00
5.71445413e-02 4.14541751e-01 -5.89849412e-01 -1.23780154e-01
6.29061282e-01 -1.90842211e-01 8.94395590e-01 -5.24110198e-01
-2.13623289e-02 8.02579522e-01 8.35933983e-01 7.14697361e-01
-1.05010986e+00 -7.64954925e-01 3.12750846e-01 -2.52388362e-02
-1.42779207e+00 -4.54636544e-01 8.93677115e-01 -3.04489225e-01
3.82606119e-01 6.22294128e-01 6.07706308e-01 1.20628929e+00
-1.33397490e-01 1.12790811e+00 9.90486979e-01 -4.24311638e-01
7.19254434e-01 1.46637157e-01 3.02799195e-01 4.78199214e-01
5.19326508e-01 -3.53644550e-01 -3.46512347e-01 -8.56647015e-01
-4.93563451e-02 4.82745647e-01 -1.88808858e-01 -6.52610004e-01
-8.42148960e-01 6.38379037e-01 -1.32760599e-01 3.07095349e-01
-4.94801700e-01 -6.19638443e-01 4.10646260e-01 1.82294354e-01
2.10451245e-01 -1.44879436e-02 -8.42893243e-01 -2.28574276e-01
-7.11794972e-01 -1.31936818e-01 1.13982403e+00 4.07229960e-01
8.18882942e-01 -1.81530312e-01 1.78221360e-01 5.94217360e-01
5.57271421e-01 5.29457569e-01 8.25083673e-01 -4.28985476e-01
4.49256241e-01 7.75525033e-01 3.11069459e-01 -8.45000327e-01
-2.83548951e-01 -2.38867924e-01 -1.01886320e+00 2.20471293e-01
4.70450699e-01 -3.67048413e-01 -3.27761829e-01 1.74280655e+00
5.35269916e-01 6.65333629e-01 3.41424406e-01 9.18027163e-02
3.64955932e-01 2.42864132e-01 2.16123894e-01 -5.36125302e-01
1.16036510e+00 -4.71694052e-01 -6.28655672e-01 1.25373200e-01
8.59750628e-01 -5.23582637e-01 1.19606578e+00 7.47590244e-01
-7.56085157e-01 -5.18763840e-01 -1.18433487e+00 6.52133167e-01
-7.04059660e-01 1.91402674e-01 5.65027833e-01 1.45525575e+00
-8.92673016e-01 3.36617082e-01 -1.01512802e+00 -1.88333720e-01
8.32697153e-01 9.36648846e-01 -4.29408908e-01 2.19450653e-01
-9.48595166e-01 3.80960922e-03 1.97127134e-01 -1.11101583e-01
-7.02308297e-01 -5.22946239e-01 -7.97561646e-01 1.37370974e-02
4.58492428e-01 -5.45830846e-01 1.05063045e+00 -9.30848777e-01
-1.58966613e+00 4.42769229e-01 -7.65987784e-02 -3.15583646e-01
3.26066285e-01 -1.47856042e-01 -6.53862357e-01 -1.93970293e-01
-1.61095500e-01 -2.61711568e-01 8.70453835e-01 -1.49239421e+00
-7.96792269e-01 -6.54981852e-01 2.30197862e-01 -2.86066562e-01
-9.94722724e-01 -1.67382479e-01 -1.07833765e-01 -3.28188986e-01
-2.30081633e-01 -1.02325356e+00 5.04117422e-02 -3.41629982e-01
-5.65130055e-01 -4.02597725e-01 1.41356611e+00 -4.38401192e-01
1.50767708e+00 -2.25541067e+00 -3.57384652e-01 6.15092397e-01
3.82232666e-01 7.55392373e-01 5.90375438e-02 2.49727607e-01
-1.08915932e-01 2.00519547e-01 -1.25296950e-01 -7.53341615e-01
-4.41945754e-02 1.58996090e-01 -5.87600321e-02 4.44002360e-01
-2.48989463e-01 5.23583889e-01 -8.21357250e-01 -4.05026555e-01
1.65687844e-01 5.70736885e-01 -3.76494825e-01 3.09325606e-01
1.67666018e-01 3.91085058e-01 -6.92104995e-01 9.03852701e-01
8.80376637e-01 -4.76048291e-01 4.63748127e-01 3.61246429e-02
-2.03381460e-02 4.34548892e-02 -1.39781654e+00 1.39892244e+00
-7.52170563e-01 -1.19243689e-01 2.95413256e-01 -1.14059985e+00
7.43476391e-01 6.70547545e-01 1.01912582e+00 -3.14181000e-01
2.75782198e-01 3.22722763e-01 -1.61120608e-01 -3.63770008e-01
7.60732517e-02 4.06462640e-01 -1.93396911e-01 7.05668569e-01
-1.29152566e-01 7.95502782e-01 -2.31643260e-01 8.21799561e-02
1.34798872e+00 -3.00930530e-01 4.72889662e-01 -7.56385475e-02
1.02312207e+00 -7.81142235e-01 5.26089251e-01 9.69779372e-01
-3.40161592e-01 2.85082817e-01 2.94124663e-01 -1.47485241e-01
-2.86674708e-01 -9.47870672e-01 2.14836076e-01 1.12787819e+00
1.20461546e-01 -7.99973428e-01 -7.56958365e-01 -1.35746109e+00
-1.59346670e-01 3.43364663e-02 -5.95271409e-01 -1.98109090e-01
-2.14877754e-01 -8.83747280e-01 5.26179552e-01 3.42468977e-01
5.38163722e-01 -5.90874910e-01 -5.26336849e-01 3.82841416e-02
8.42131954e-03 -9.44118083e-01 -1.08545758e-01 2.10013732e-01
-5.36555827e-01 -1.43412650e+00 -4.94220972e-01 -5.55752456e-01
3.55242074e-01 3.12527508e-01 7.35928118e-01 2.02740714e-01
1.38548046e-01 7.79531300e-01 -4.43339437e-01 -5.38470685e-01
-1.46648541e-01 5.80073655e-01 3.39933544e-01 9.53455389e-01
3.09483767e-01 -7.01179564e-01 -5.65275848e-01 4.79530036e-01
-1.00391459e+00 -5.92755437e-01 4.43728983e-01 6.87504768e-01
3.95763189e-01 5.08196771e-01 7.25089908e-01 -1.19286811e+00
6.67223036e-01 -8.32009375e-01 -4.05956030e-01 6.15158260e-01
-5.67727327e-01 -3.53913724e-01 8.32209408e-01 -1.00316489e+00
-7.01644838e-01 5.28935671e-01 -4.62123901e-01 -2.09438741e-01
-2.08084598e-01 3.17952156e-01 -1.05442083e+00 -2.94523120e-01
4.86342728e-01 7.37763122e-02 -9.74985883e-02 -5.84772527e-01
-2.79234290e-01 1.22634971e+00 2.16154203e-01 -5.87367475e-01
8.92906606e-01 4.34585094e-01 -1.14815541e-01 -7.20606565e-01
-5.14727175e-01 -6.59327269e-01 -4.48139220e-01 4.27671745e-02
5.05451381e-01 -8.03193212e-01 -1.34463799e+00 8.70308697e-01
-6.15973771e-01 -3.39597523e-01 -1.90872803e-01 4.77859855e-01
-2.98483729e-01 5.29098570e-01 -1.30047157e-01 -1.29925120e+00
-5.35637140e-01 -1.06106114e+00 9.91565704e-01 3.82804215e-01
-2.23036379e-01 -1.19582582e+00 7.45686740e-02 3.43322039e-01
5.13152540e-01 1.56049743e-01 7.78761506e-01 -1.36282563e+00
-1.07614197e-01 -5.12452841e-01 3.72685879e-01 3.16130400e-01
7.11810052e-01 -1.73682064e-01 -1.17533159e+00 -5.83046019e-01
1.62883967e-01 -3.15492719e-01 1.84548900e-01 2.20755339e-02
1.45783579e+00 -4.71891195e-01 -5.23762226e-01 2.43246093e-01
1.13459826e+00 3.14590484e-01 5.11073709e-01 2.20152795e-01
6.07069671e-01 1.13198824e-01 4.52032268e-01 7.52949595e-01
5.74166000e-01 8.09036255e-01 4.49077100e-01 -1.86033994e-01
4.40639436e-01 -1.16104677e-01 4.87644523e-01 5.94969869e-01
1.37659341e-01 -2.87561744e-01 -7.60047257e-01 2.91400433e-01
-1.91306126e+00 -6.65633619e-01 1.12114757e-01 2.74234605e+00
7.02182949e-01 2.48859167e-01 7.68919110e-01 1.05224538e+00
4.60872531e-01 -1.20751597e-01 -4.87622023e-01 -4.01023030e-02
5.22093847e-02 4.55405176e-01 3.11280370e-01 2.56766528e-01
-1.30237246e+00 2.37910405e-01 4.73315001e+00 1.06712949e+00
-1.33496523e+00 5.04356980e-01 5.62234819e-01 4.02894199e-01
-1.26432572e-02 -1.82119593e-01 -6.78118646e-01 7.06646323e-01
1.05469751e+00 1.55799121e-01 2.04634234e-01 9.08441603e-01
2.55552474e-02 4.17855196e-02 -8.69592547e-01 1.38806009e+00
-2.20286161e-01 -9.12861466e-01 -3.56968254e-01 3.24760795e-01
6.05970502e-01 -3.91346782e-01 1.21407568e-01 3.65209132e-01
9.45951194e-02 -4.72210974e-01 1.70650259e-01 3.68755937e-01
5.81474006e-01 -7.45264649e-01 7.91109800e-01 6.81503117e-01
-1.43000948e+00 -4.61308837e-01 1.71917453e-01 2.18146622e-01
-2.91897953e-01 4.61462647e-01 -3.72099340e-01 8.86437714e-01
7.73256660e-01 5.94808280e-01 -8.65338624e-01 1.03653646e+00
3.14186573e-01 8.19803298e-01 -4.15478468e-01 1.23024747e-01
-2.93772936e-01 2.41134197e-01 7.25820363e-02 6.02177918e-01
4.64045495e-01 -2.03702807e-01 4.58786279e-01 -5.24234325e-02
-1.27807081e-01 4.44770068e-01 -5.86255312e-01 7.82785714e-02
4.89960164e-01 1.32166684e+00 -5.82300723e-01 -2.43811056e-01
-7.43536651e-01 7.66052485e-01 -7.64408484e-02 1.58671930e-01
-5.87629795e-01 -3.76024365e-01 6.23502493e-01 1.64213449e-01
2.02457786e-01 -1.56839192e-02 5.68799824e-02 -1.39973378e+00
-1.66704264e-02 -1.20884418e+00 7.57673383e-01 -3.42270173e-02
-1.51639974e+00 5.71882010e-01 -2.53423780e-01 -1.55404544e+00
-3.48312080e-01 -5.60342312e-01 -7.28748381e-01 5.96231639e-01
-1.25387979e+00 -1.37072158e+00 -2.83257246e-01 1.43951392e+00
6.78325668e-02 -3.85413378e-01 1.28558683e+00 6.61729157e-01
-7.32598305e-01 1.13549614e+00 8.78575295e-02 3.11828703e-01
4.87373620e-01 -1.09805250e+00 -1.06808700e-01 7.08000064e-01
1.05463788e-01 9.41495180e-01 9.42817307e-04 -5.67722559e-01
-1.57026315e+00 -9.10852134e-01 5.77132106e-01 -4.28614050e-01
4.84244198e-01 -5.57887375e-01 -8.63432765e-01 4.21157479e-01
-6.80912584e-02 4.77524340e-01 1.40532053e+00 2.78256595e-01
-3.05833161e-01 -5.05665600e-01 -1.55375254e+00 1.50776610e-01
5.71226418e-01 -6.82702601e-01 1.45026013e-01 8.59171972e-02
1.13938197e-01 7.58358762e-02 -9.71678078e-01 5.79419792e-01
6.94953740e-01 -8.62945139e-01 9.27445769e-01 -5.64559639e-01
-6.69364810e-01 -2.96871483e-01 -2.36826435e-01 -8.10369074e-01
2.80797631e-01 -1.11629844e+00 -7.75936604e-01 1.59434712e+00
3.17316651e-01 -9.75701988e-01 1.04604959e+00 5.90161443e-01
4.15855974e-01 -7.86402881e-01 -1.00574756e+00 -7.65680134e-01
-2.13681698e-01 -4.82961535e-01 9.03859198e-01 1.11090100e+00
-9.39339399e-02 1.81353480e-01 -4.26856339e-01 2.49259382e-01
6.28809929e-01 -2.75573611e-01 9.36236262e-01 -1.70098388e+00
-5.16790986e-01 -9.69540775e-02 -3.47568899e-01 -6.67269409e-01
1.97058022e-01 -5.03819048e-01 -4.65336323e-01 -8.72529864e-01
-1.05602056e-01 -1.00818610e+00 -6.86593652e-01 8.61088932e-01
-2.41926219e-02 4.27294284e-01 6.30406514e-02 1.42524704e-01
-8.62402439e-01 1.83696687e-01 3.72014344e-01 -1.86704114e-01
-6.67083025e-01 1.07918096e+00 -8.24916601e-01 5.59338033e-01
9.83056068e-01 -3.30886453e-01 -6.64227366e-01 2.35041454e-01
2.01628312e-01 -2.93751694e-02 2.22196326e-01 -1.35512185e+00
2.69051820e-01 8.43561515e-02 4.06926185e-01 -4.74998087e-01
2.72223234e-01 -1.35910690e+00 5.68039417e-02 3.30533743e-01
-1.21877000e-01 5.25933355e-02 4.78253178e-02 5.19715488e-01
3.68819498e-02 7.97109678e-02 5.14534056e-01 2.65221030e-01
-5.74852787e-02 3.26035202e-01 -4.22237277e-01 -2.35269800e-01
1.00270236e+00 -6.39727563e-02 -1.01098165e-01 -3.26756507e-01
-7.98286557e-01 -1.97315082e-01 3.39775622e-01 3.54915082e-01
4.01253670e-01 -1.21592033e+00 -8.04361328e-02 5.55029988e-01
9.40303504e-02 -1.14627309e-01 2.96262652e-01 9.73979354e-01
2.42235973e-01 1.10583104e-01 2.13233978e-02 -6.01441741e-01
-1.61773789e+00 6.41780972e-01 2.57400542e-01 -5.26522756e-01
-2.94784233e-02 1.69533610e-01 -2.89983273e-01 -5.41601539e-01
4.67870951e-01 1.10872678e-01 -3.11413050e-01 1.72896147e-01
7.73185432e-01 3.50354224e-01 5.08793890e-01 -7.48086572e-01
-5.52060246e-01 4.75646347e-01 -9.65484302e-04 1.79399088e-01
1.01763988e+00 -2.19874188e-01 1.65727660e-01 3.55557710e-01
1.37479246e+00 6.39689207e-01 -8.61959636e-01 -1.50317997e-01
1.14592150e-01 -3.16981435e-01 -3.28426123e-01 -6.04649663e-01
-1.29071820e+00 7.04138875e-01 1.31902313e+00 7.78711736e-01
1.47451448e+00 -2.43452519e-01 8.27334642e-01 3.52168143e-01
4.53655541e-01 -6.61982954e-01 9.71036628e-02 1.84568465e-01
-2.11345449e-01 -1.26944530e+00 -2.30454907e-01 -2.48943701e-01
-3.22643578e-01 7.73248017e-01 4.36513156e-01 4.54721719e-01
1.21762598e+00 3.61915052e-01 1.10582530e-01 2.41866365e-01
-4.00047004e-01 -2.18072504e-01 1.01478018e-01 8.60126019e-01
8.88020396e-02 -4.27028239e-02 -9.92230773e-02 1.21042097e+00
1.89642265e-01 2.01575354e-01 1.32605910e-01 1.28013492e+00
1.12478398e-01 -1.83301556e+00 -4.11103576e-01 2.68287659e-01
-7.86899924e-01 3.41733575e-01 -2.48197794e-01 5.19467175e-01
3.78352642e-01 1.32907188e+00 -3.33580106e-01 -7.75347233e-01
9.91058573e-02 3.21152717e-01 9.75688770e-02 -3.67651790e-01
-8.14809084e-01 -2.59721465e-02 -3.56154472e-01 -3.44917685e-01
-6.13304734e-01 -5.76662362e-01 -9.95325863e-01 -1.10160574e-01
-3.41152042e-01 4.23542082e-01 7.29435861e-01 1.00079596e+00
4.86750782e-01 2.09133327e-01 1.22827733e+00 -6.64466977e-01
-3.62421066e-01 -5.69835842e-01 -5.41500449e-01 3.68857354e-01
5.04343927e-01 -6.12812936e-01 -4.44116920e-01 -2.05445081e-01] | [5.893285751342773, 6.3076171875] |
747cd456-4f96-46ef-a2ef-e1a794b3cfc6 | deep-neural-networks-architectures-from-the | 2306.03406 | null | https://arxiv.org/abs/2306.03406v1 | https://arxiv.org/pdf/2306.03406v1.pdf | Deep neural networks architectures from the perspective of manifold learning | Despite significant advances in the field of deep learning in ap-plications to various areas, an explanation of the learning pro-cess of neural network models remains an important open ques-tion. The purpose of this paper is a comprehensive comparison and description of neural network architectures in terms of ge-ometry and topology. We focus on the internal representation of neural networks and on the dynamics of changes in the topology and geometry of a data manifold on different layers. In this paper, we use the concepts of topological data analysis (TDA) and persistent homological fractal dimension. We present a wide range of experiments with various datasets and configurations of convolutional neural network (CNNs) architectures and Transformers in CV and NLP tasks. Our work is a contribution to the development of the important field of explainable and interpretable AI within the framework of geometrical deep learning. | ['German Magai'] | 2023-06-06 | null | null | null | null | ['topological-data-analysis'] | ['graphs'] | [-1.06743865e-01 3.08163851e-01 3.05269361e-01 -2.98209786e-01
4.49679315e-01 -6.30098343e-01 9.03187454e-01 2.41605014e-01
1.09197438e-01 3.33317339e-01 1.32188439e-01 -5.95909953e-01
-5.17878652e-01 -1.06929326e+00 -9.73623335e-01 -4.80601519e-01
-7.65832841e-01 7.15365410e-01 8.55063275e-02 -7.48750329e-01
3.98445666e-01 1.12477112e+00 -1.24018681e+00 3.80788028e-01
6.34938776e-01 1.17122960e+00 -2.91919589e-01 7.86531270e-01
-1.44301102e-01 7.93455541e-01 -2.73406804e-01 -2.64375210e-01
1.66625127e-01 -1.04510315e-01 -1.20581102e+00 -3.26425880e-01
8.15303743e-01 2.43373260e-01 -6.99965298e-01 6.39815152e-01
6.88604340e-02 2.10738257e-02 1.06316590e+00 -1.10496867e+00
-1.01686001e+00 5.74779093e-01 3.61368037e-03 7.24482059e-01
-3.85446310e-01 -1.56847969e-01 1.13999164e+00 -7.47172654e-01
6.51644409e-01 1.37536240e+00 9.95246112e-01 7.32024312e-02
-1.40823650e+00 -1.46018386e-01 -1.36626512e-01 4.20254499e-01
-1.17163551e+00 -1.01787783e-01 9.74866688e-01 -5.95948398e-01
9.48789597e-01 9.93210822e-02 8.64839077e-01 8.94498467e-01
7.42998660e-01 4.56185162e-01 8.62683356e-01 -4.58247840e-01
1.67241514e-01 -4.20846641e-01 1.84426099e-01 1.14592314e+00
3.02070647e-01 2.89799869e-01 -7.22027570e-02 3.40580374e-01
1.41726804e+00 -2.89531440e-01 3.22290540e-01 -8.82447362e-01
-1.25927722e+00 9.10065114e-01 1.10136807e+00 5.72948456e-01
-1.74706280e-01 4.62434709e-01 2.91373819e-01 4.86646414e-01
3.86061132e-01 9.52723205e-01 -6.94624364e-01 2.96730608e-01
-5.99254310e-01 2.34197721e-01 6.79927409e-01 3.99827629e-01
4.62851524e-01 3.63629699e-01 4.61372465e-01 3.76344085e-01
-3.52426246e-02 -1.43179726e-02 9.17079449e-02 -1.00509763e+00
2.48230681e-01 6.51400566e-01 -4.38709229e-01 -1.63313448e+00
-8.49425733e-01 -6.51997864e-01 -1.25784743e+00 2.65541732e-01
5.87887049e-01 2.33325824e-01 -5.90401173e-01 1.42592037e+00
-2.20778197e-01 1.20148428e-01 -2.13520661e-01 4.73728389e-01
8.19778800e-01 4.70429987e-01 -2.08509162e-01 4.44187373e-01
1.03098953e+00 -6.90622687e-01 -2.64057130e-01 2.89263099e-01
7.67566919e-01 -3.06522250e-01 8.74063432e-01 1.90971330e-01
-1.09689879e+00 -7.53314197e-01 -1.12614334e+00 -2.30070665e-01
-9.32951987e-01 -5.53954840e-02 8.55722547e-01 1.15644015e-01
-1.26769543e+00 1.16614735e+00 -8.44639719e-01 -5.53442061e-01
9.03688431e-01 6.14263892e-01 -2.43806109e-01 4.73731548e-01
-9.33010340e-01 9.78321016e-01 4.93711889e-01 -1.06636018e-01
-4.49502617e-01 -8.54329228e-01 -6.31467164e-01 1.86658844e-01
-3.36400092e-01 -7.41911590e-01 9.26833928e-01 -8.59139621e-01
-1.04456246e+00 9.41077471e-01 5.79066217e-01 -8.13420594e-01
3.67341220e-01 9.64032412e-02 -3.20498288e-01 7.46869445e-02
-4.51907992e-01 1.00289154e+00 4.52104956e-01 -9.45298016e-01
-2.33423077e-02 -3.65891069e-01 -1.82068460e-02 -2.80039668e-01
-1.44210279e-01 -5.35818279e-01 5.72404802e-01 -7.53266871e-01
3.74249458e-01 -7.49147773e-01 3.94614637e-02 1.48519069e-01
-3.19606185e-01 -2.91576803e-01 9.94592190e-01 -2.68423796e-01
7.06702769e-01 -1.71726549e+00 5.32621026e-01 1.43153831e-01
6.68173492e-01 3.45577657e-01 -1.51191294e-01 2.86406368e-01
-5.67996562e-01 4.96820778e-01 -2.05425061e-02 3.01725417e-03
-2.13696972e-01 2.24305600e-01 -7.09942341e-01 5.43547988e-01
4.28539664e-01 1.34676230e+00 -6.49379492e-01 -3.24217916e-01
5.78513682e-01 4.39930081e-01 -4.61137891e-01 -1.98507592e-01
-4.11841720e-01 6.89894557e-01 -1.23019993e-01 3.42739671e-01
3.96057308e-01 -3.23417664e-01 -1.18049577e-01 -1.77607343e-01
-3.49954486e-01 2.76775718e-01 -5.14063239e-01 1.39882326e+00
-4.06722307e-01 1.41756320e+00 -3.78519505e-01 -1.62286425e+00
1.01028705e+00 -8.37898478e-02 3.81112933e-01 -7.49872029e-01
4.41352397e-01 1.46270946e-01 3.69373232e-01 -3.44777375e-01
3.46803218e-01 1.80169627e-01 2.98998579e-02 3.30830961e-01
2.18600914e-01 -9.11491457e-03 -1.12144478e-01 -3.10867820e-02
8.23594689e-01 -1.50674954e-01 2.03947589e-01 -7.49586880e-01
4.83885229e-01 6.99651465e-02 -3.65156472e-01 5.54349601e-01
-1.17384918e-01 3.43079537e-01 8.19787025e-01 -1.53644645e+00
-1.65533412e+00 -1.10591567e+00 -5.23762643e-01 1.03730953e+00
-2.50331294e-02 -2.81032681e-01 -6.65942907e-01 -7.09579214e-02
-8.98671746e-02 3.09525102e-01 -1.18140078e+00 -2.43323267e-01
-1.07371366e+00 -5.55210888e-01 8.99796665e-01 4.19523269e-01
7.03045666e-01 -1.46946371e+00 -6.86301053e-01 1.27175182e-01
2.11125776e-01 -9.39320385e-01 3.01895261e-01 1.19088911e-01
-1.42403138e+00 -1.18808353e+00 -1.68530673e-01 -9.81726110e-01
4.96269941e-01 -3.85833569e-02 1.32362247e+00 2.50075161e-01
-5.84086597e-01 8.55020955e-02 3.92461047e-02 -4.73628879e-01
-4.75806832e-01 6.73780501e-01 1.75371319e-01 -4.79788601e-01
1.91725548e-02 -9.58945632e-01 -5.42063773e-01 1.88494831e-01
-7.88666666e-01 1.84197307e-01 4.42484975e-01 5.47519267e-01
4.64981437e-01 5.61705604e-02 2.75517553e-01 -3.67228121e-01
6.18462265e-01 -4.67735082e-01 -5.24250507e-01 1.81565315e-01
-4.33011293e-01 5.58944643e-01 9.29799736e-01 -2.29983777e-01
-3.07450175e-01 -3.32522392e-01 1.61496922e-02 -3.53379816e-01
-3.90251249e-01 3.44096094e-01 2.08284572e-01 -5.06786585e-01
7.95775652e-01 -4.24425639e-02 1.02910280e-01 -4.63183224e-01
5.66675186e-01 -6.88101575e-02 6.16573751e-01 -6.40611231e-01
6.04995489e-01 4.88118142e-01 8.36048365e-01 -1.14215732e+00
-6.30756080e-01 2.40943477e-01 -1.19088900e+00 -9.30697471e-02
6.47445261e-01 -1.08008295e-01 -7.66473770e-01 5.01844883e-01
-1.26283371e+00 -4.01046127e-01 -3.22120667e-01 -2.42616180e-02
-8.52483094e-01 2.14682799e-02 -5.47443449e-01 -2.02514514e-01
-2.38012776e-01 -1.04231250e+00 5.72784364e-01 -2.76094135e-02
-2.18160689e-01 -1.70557320e+00 2.24783972e-01 -1.45258754e-01
5.35816848e-01 8.33914399e-01 1.55970132e+00 -4.80317831e-01
-6.09187663e-01 -5.03094010e-02 -4.41905767e-01 -1.49939284e-01
-2.42814034e-01 2.05176204e-01 -7.54296839e-01 5.78130633e-02
-3.61739993e-01 -1.77751392e-01 1.07202029e+00 6.79961920e-01
1.64074111e+00 -3.54610473e-01 -2.19016150e-01 8.51207972e-01
1.28491390e+00 -1.74311936e-01 5.64222515e-01 5.11240840e-01
7.05574095e-01 8.23943913e-01 -2.72552103e-01 -1.50357515e-01
3.75414401e-01 5.92130840e-01 8.72254848e-01 -2.00853407e-01
-2.84910113e-01 -2.75826544e-01 -1.26483485e-01 7.91161716e-01
-4.51873034e-01 -3.34046073e-02 -1.42583442e+00 3.34691346e-01
-1.69781482e+00 -1.01094735e+00 -3.22684854e-01 1.49563491e+00
6.92717731e-02 7.65086636e-02 3.22090596e-01 2.22579315e-01
6.09069824e-01 2.25352719e-01 -5.31485200e-01 -8.56591046e-01
-3.44088316e-01 3.00057918e-01 4.19721395e-01 4.78141874e-01
-1.09572124e+00 1.02445376e+00 6.97841454e+00 3.11609685e-01
-1.22904432e+00 -3.37965965e-01 7.49268711e-01 3.43691349e-01
-4.35503423e-02 -2.97288924e-01 -1.70163184e-01 6.97898939e-02
1.01057911e+00 2.71401167e-01 6.64665282e-01 5.77933490e-01
3.69194336e-02 4.58560199e-01 -1.20217347e+00 7.41540909e-01
-1.78075150e-01 -2.06631827e+00 2.99921036e-01 4.08993244e-01
6.16658688e-01 5.10654509e-01 4.59163487e-01 4.40421775e-02
9.93965715e-02 -1.56649923e+00 8.06101859e-01 8.13417971e-01
8.97877812e-01 -7.51749396e-01 5.68393469e-01 1.21542983e-01
-1.19390500e+00 -2.18126535e-01 -4.88667101e-01 -3.81574690e-01
-3.75172943e-01 1.54433236e-01 -6.03955925e-01 3.57596278e-01
7.53761053e-01 9.49052334e-01 -8.27021360e-01 8.48431528e-01
2.09471449e-01 3.82417798e-01 -9.34113935e-02 -1.07604347e-01
3.64688784e-01 -3.17655176e-01 5.06646097e-01 1.12839532e+00
2.68148892e-02 3.11663393e-02 -2.32296646e-01 1.28935182e+00
-2.21732169e-01 -3.55977379e-03 -8.78731191e-01 -2.38110989e-01
1.54315427e-01 1.04101384e+00 -1.07574189e+00 2.71110293e-02
1.71621278e-01 1.93897381e-01 6.94073558e-01 4.35366929e-02
-5.16322613e-01 -3.26052606e-01 5.69661736e-01 4.18776691e-01
3.94737422e-01 -7.00983167e-01 -9.52645421e-01 -8.69286716e-01
-2.85765976e-01 -3.16751361e-01 6.22469038e-02 -7.01536953e-01
-1.03095293e+00 5.42520523e-01 1.19512342e-01 -7.22700059e-01
1.10675789e-01 -1.11384535e+00 -1.13303769e+00 4.72605914e-01
-1.18017292e+00 -1.07578063e+00 -1.78684220e-01 3.22927386e-01
1.81368381e-01 -4.72564876e-01 9.30461287e-01 -2.99950123e-01
-2.20346913e-01 1.72903270e-01 2.93390572e-01 2.97331840e-01
-1.43470526e-01 -1.33529079e+00 1.06516659e+00 1.30663648e-01
3.89874429e-01 5.17126143e-01 8.78137767e-01 -2.17836559e-01
-1.05872059e+00 -9.85985756e-01 7.60696769e-01 -6.36285186e-01
1.04414856e+00 -4.81224060e-01 -8.82060409e-01 5.96426070e-01
6.77064285e-02 5.06856963e-02 3.39506686e-01 2.13713020e-01
-3.26865405e-01 5.59927784e-02 -8.29329491e-01 5.45064092e-01
1.18898392e+00 -4.27717000e-01 -7.16832101e-01 3.41207832e-01
6.74025834e-01 -1.85035512e-01 -9.17951941e-01 4.62202132e-01
6.44041300e-01 -1.09510076e+00 1.36419535e+00 -1.11965609e+00
6.04652822e-01 1.15574419e-01 3.67422514e-02 -1.21436191e+00
-5.30749619e-01 -3.68826121e-01 -4.08285379e-01 4.32472944e-01
1.19334295e-01 -4.48206484e-01 6.42643511e-01 -1.01310141e-01
-2.52662331e-01 -1.10491276e+00 -8.86314571e-01 -5.22553563e-01
9.90715265e-01 -3.79542202e-01 6.04465365e-01 9.35393035e-01
-1.61845401e-01 3.19378346e-01 1.53279379e-01 -2.11794078e-01
5.65427482e-01 -5.99956736e-02 3.36616397e-01 -2.03210831e+00
2.53451079e-01 -9.18855786e-01 -8.14627111e-01 -5.31590343e-01
2.86454558e-01 -1.11691320e+00 -6.21250570e-01 -1.28670526e+00
-4.34232324e-01 -3.64086896e-01 -1.68497056e-01 2.10459545e-01
7.80317307e-01 2.14218751e-01 1.14422841e-02 5.11416554e-01
-5.31209707e-01 4.93885994e-01 1.32174754e+00 -7.70431310e-02
-1.62662894e-01 -1.99810833e-01 -3.24969321e-01 8.27123165e-01
1.35690868e+00 -8.52458999e-02 -3.05918187e-01 -6.45506561e-01
6.24407828e-01 -2.16476306e-01 9.31758106e-01 -1.19644082e+00
-1.91980451e-02 1.55614838e-01 7.10634768e-01 -7.19529212e-01
1.79124828e-02 -5.88047326e-01 -2.90169477e-01 7.41960347e-01
-7.05896676e-01 6.58328533e-01 3.44307005e-01 4.18721169e-01
1.64036021e-01 3.30867469e-01 9.58583772e-01 -2.33645380e-01
-4.00845021e-01 4.50682372e-01 -2.37950221e-01 1.64767250e-01
7.71134734e-01 -3.39200169e-01 -5.76849759e-01 -1.42530680e-01
-9.83460009e-01 -5.85762262e-02 4.98299956e-01 6.13240898e-01
4.80888009e-01 -1.39839911e+00 -3.87773007e-01 1.77533999e-01
-1.17446929e-01 -5.45942150e-02 8.52630064e-02 6.65836632e-01
-1.15077698e+00 9.41125989e-01 -9.36051130e-01 -5.74542522e-01
-8.29423070e-01 5.26460469e-01 7.98967361e-01 -1.32291034e-01
-7.36834288e-01 4.97842640e-01 1.42293572e-01 -5.97765326e-01
2.79195905e-01 -5.06176114e-01 -5.40471435e-01 -2.11130947e-01
3.14874537e-02 5.00642121e-01 -5.38140675e-03 -9.92773473e-01
-6.85857385e-02 6.54456973e-01 1.36567459e-01 3.38456899e-01
1.62946963e+00 1.32612661e-01 -4.34560835e-01 5.87775230e-01
1.34724510e+00 -8.36053967e-01 -9.84517753e-01 -6.30767941e-02
1.72014251e-01 2.02296644e-01 -6.11614473e-02 -5.54092348e-01
-9.94469821e-01 1.46692240e+00 6.35091960e-01 5.91769874e-01
5.03407359e-01 4.20772344e-01 5.00082672e-01 7.76694477e-01
1.03991412e-01 -8.43038976e-01 4.93454337e-01 1.04928231e+00
1.22452068e+00 -9.67797458e-01 -1.82624295e-01 -1.01285771e-01
5.35844453e-02 1.78158557e+00 4.69095379e-01 -8.56222570e-01
1.07346952e+00 -2.41862789e-01 -3.99717659e-01 -8.06645870e-01
-4.50501710e-01 2.60685772e-01 6.51288867e-01 5.51342905e-01
4.39219415e-01 1.66931063e-01 2.92530954e-01 4.18051481e-02
-8.58333170e-01 -3.88893783e-01 5.53181469e-01 4.46797073e-01
-6.55419946e-01 -6.10687256e-01 -3.71522568e-02 2.60407448e-01
-2.13851452e-01 -9.54362471e-03 -8.37531805e-01 9.83125865e-01
3.91190976e-01 2.80567706e-01 5.43699503e-01 -5.56269884e-01
-3.66067141e-02 -3.23734768e-02 7.91032970e-01 -2.28931606e-01
-1.91469565e-01 -6.72514319e-01 -1.94588825e-01 -3.12521189e-01
-4.21218008e-01 -6.30719781e-01 -1.22474265e+00 -8.60390484e-01
3.57182175e-02 -2.42160439e-01 7.50641465e-01 1.14036584e+00
3.93727362e-01 7.35850096e-01 3.68886083e-01 -9.46253121e-01
-4.70724925e-02 -8.25861812e-01 -4.41830516e-01 9.43182558e-02
5.51763594e-01 -8.31899881e-01 -1.90684155e-01 -1.36526749e-01] | [6.801983833312988, 5.9997100830078125] |
25416736-a047-44be-ac91-4131daf02cc3 | identification-of-ischemic-heart-disease-by | 2010.15893 | null | https://arxiv.org/abs/2010.15893v1 | https://arxiv.org/pdf/2010.15893v1.pdf | Identification of Ischemic Heart Disease by using machine learning technique based on parameters measuring Heart Rate Variability | The diagnosis of heart diseases is a difficult task generally addressed by an appropriate examination of patients clinical data. Recently, the use of heart rate variability (HRV) analysis as well as of some machine learning algorithms, has proved to be a valuable support in the diagnosis process. However, till now, ischemic heart disease (IHD) has been diagnosed on the basis of Artificial Neural Networks (ANN) applied only to signs, symptoms and sequential ECG and coronary angiography, an invasive tool, while could be probably identified in a non-invasive way by using parameters extracted from HRV, a signal easily obtained from the ECG. In this study, 18 non-invasive features (age, gender, left ventricular ejection fraction and 15 obtained from HRV) of 243 subjects (156 normal subjects and 87 IHD patients) were used to train and validate a series of several ANN, different for number of input and hidden nodes. The best result was obtained using 7 input parameters and 7 hidden nodes with an accuracy of 98.9% and 82% for the training and validation dataset, respectively. | ['Agostino Accardo', 'Gianfranco Sinagra', 'Miloš Ajčević', 'Aleksandar Miladinović', 'Beatrice De Paola', 'Luca Restivo', 'Marco Merlo', 'Giulia Silveri'] | 2020-10-29 | null | null | null | null | ['heart-rate-variability'] | ['medical'] | [ 1.14471495e-01 3.55069875e-03 8.07661489e-02 -2.92656839e-01
2.28626817e-01 -3.27529371e-01 4.25640270e-02 5.95413327e-01
-6.75312459e-01 1.03266430e+00 -4.31783944e-01 -5.03330529e-01
-4.46007103e-01 -7.16769040e-01 2.89407492e-01 -7.28525519e-01
-3.72672111e-01 8.39069963e-01 -1.06310584e-01 7.99241662e-02
-4.61896807e-02 8.38945448e-01 -1.56246686e+00 -2.38117889e-01
8.47644985e-01 8.93231273e-01 -4.08504419e-02 7.07490385e-01
2.06104457e-01 3.11311245e-01 -6.56703770e-01 2.20081564e-02
7.93497488e-02 -8.91336083e-01 -4.53893423e-01 -2.12930828e-01
-3.05039227e-01 -1.70358986e-01 2.19208002e-01 4.55929041e-01
8.62835050e-01 -4.35251705e-02 6.77012742e-01 -6.95820689e-01
7.72848949e-02 3.74642104e-01 4.19747531e-02 3.81438375e-01
4.84657893e-03 1.07066020e-01 3.72030586e-01 -5.08172810e-01
4.12451386e-01 5.46326160e-01 7.04494953e-01 4.33066428e-01
-1.47253752e+00 -3.78640801e-01 -7.91238546e-01 3.00261915e-01
-1.26194119e+00 -8.34657699e-02 7.42749393e-01 -6.36800587e-01
5.01919210e-01 3.21749330e-01 1.16802502e+00 6.80941939e-01
2.40204319e-01 -3.19397211e-01 1.45107067e+00 -5.10809124e-01
2.60596633e-01 6.06192589e-01 4.32878941e-01 3.54243696e-01
8.42419624e-01 3.41922998e-01 3.29500854e-01 -3.09961379e-01
7.80721605e-01 -1.73978247e-02 -2.80870140e-01 1.46398488e-02
-1.07658362e+00 7.12101161e-01 -4.48211655e-03 9.66202617e-01
-6.99714184e-01 -4.94890541e-01 6.23826623e-01 5.35653830e-01
1.50099084e-01 4.78680193e-01 -8.56568038e-01 -2.17008293e-01
-7.28787720e-01 -7.62073845e-02 9.37026560e-01 -1.42694622e-01
3.98277640e-01 3.17052752e-01 2.31537726e-02 5.82937181e-01
1.61669329e-01 7.73722827e-01 6.57828927e-01 -6.32885993e-01
-1.09503791e-01 7.89473891e-01 -6.01622537e-02 -1.27740562e+00
-8.31094563e-01 -8.06837440e-01 -1.36042321e+00 4.30444956e-01
7.52208233e-01 -3.53785008e-01 -4.35885519e-01 1.38556659e+00
2.81799078e-01 -1.00494064e-01 1.28460214e-01 8.66092265e-01
6.57689452e-01 1.67572305e-01 3.21965367e-01 -9.35690641e-01
1.37082517e+00 2.79459544e-02 -7.18993843e-01 3.25351596e-01
4.98066872e-01 -4.88250613e-01 5.80005944e-01 6.83705628e-01
-7.71468639e-01 -7.36131310e-01 -8.63519669e-01 4.46913689e-01
-3.66086811e-01 5.89526713e-01 1.46863654e-01 8.98649573e-01
-5.10495365e-01 1.10492861e+00 -6.88661814e-01 -4.83734876e-01
9.34001431e-03 3.10011744e-01 -4.73872930e-01 4.54446882e-01
-1.23344517e+00 1.05570698e+00 6.93791926e-01 3.34130645e-01
1.11646935e-01 -3.70261461e-01 -3.79704922e-01 2.07984336e-02
1.66477803e-02 -9.51530159e-01 2.54912108e-01 -8.16176951e-01
-1.48417020e+00 1.04764926e+00 1.45021006e-01 -4.53644782e-01
5.74506104e-01 1.11965500e-01 -4.93435562e-01 5.06011665e-01
-4.03400391e-01 -1.11421712e-01 6.42224371e-01 -7.67908156e-01
-5.63867874e-02 -8.03791583e-01 -5.19425571e-01 -3.02249342e-01
-9.78820324e-02 -1.44881815e-01 4.27972376e-01 -3.25828135e-01
4.91474748e-01 -8.67443860e-01 -7.90034756e-02 -2.82090664e-01
-2.48029947e-01 1.15018770e-01 6.62698209e-01 -1.26053858e+00
1.16568363e+00 -2.02137995e+00 2.10708156e-01 6.92442715e-01
3.67535174e-01 6.99778199e-01 5.92794418e-01 1.79203033e-01
-2.00746089e-01 2.33016044e-01 -2.31786311e-01 2.04795390e-01
-2.24323750e-01 4.34929013e-01 2.56230265e-01 4.50112879e-01
-1.08805969e-01 4.57267523e-01 -4.71260965e-01 -7.32748032e-01
6.79023087e-01 7.26040006e-01 -1.84232108e-02 1.93616331e-01
2.34539956e-01 9.32154119e-01 -3.57862920e-01 2.36966103e-01
4.30767179e-01 -5.98050691e-02 5.24088800e-01 -1.18520543e-01
-8.40539411e-02 -3.62855345e-01 -1.01727903e+00 9.26006258e-01
-1.64868370e-01 5.04223108e-01 -2.20395744e-01 -1.30844140e+00
1.59878552e+00 9.83100235e-01 5.95158219e-01 -6.99720502e-01
5.09982049e-01 4.45365757e-01 4.96361524e-01 -8.83570433e-01
-5.03457606e-01 -1.71940908e-01 4.27184701e-01 2.44604498e-01
-2.11177588e-01 3.13728571e-01 3.26872110e-01 -6.40671611e-01
6.03187501e-01 -2.68566459e-01 7.74310231e-01 -1.73526302e-01
1.08779228e+00 -2.19648346e-01 4.07289237e-01 5.38093328e-01
-2.52970487e-01 3.78963500e-01 7.69816458e-01 -9.26071763e-01
-1.11870384e+00 -6.78970337e-01 -5.92276394e-01 -7.17573985e-03
-4.99820590e-01 2.70825267e-01 -3.79458696e-01 -2.29844630e-01
5.26654124e-02 3.25442791e-01 -4.65638071e-01 -1.43211439e-01
-6.66285872e-01 -9.48717475e-01 4.73009437e-01 1.50901541e-01
4.23141301e-01 -1.15153050e+00 -1.15232134e+00 5.15314698e-01
1.23951495e-01 -7.33352363e-01 8.24493706e-01 1.13367118e-01
-1.58036852e+00 -1.31548905e+00 -8.75297606e-01 -3.47692043e-01
3.53059292e-01 -5.03901899e-01 1.07678521e+00 4.96591508e-01
-7.55285621e-01 -4.61805463e-02 -2.28213295e-01 -5.10623336e-01
-8.79926324e-01 3.27515990e-01 3.74968536e-02 2.00142898e-02
7.33820572e-02 -1.26991940e+00 -5.43172956e-01 2.79072702e-01
-3.91738325e-01 -2.67214268e-01 9.26588058e-01 5.18083036e-01
4.31930751e-01 -1.82146683e-01 9.38708305e-01 -7.99216568e-01
3.80679905e-01 -2.25721091e-01 -5.25504053e-01 -9.29649994e-02
-1.06779838e+00 -2.87413567e-01 6.88361049e-01 -5.68941124e-02
-3.93199027e-01 -2.91290402e-01 -3.80650729e-01 -2.24796653e-01
-8.11183155e-01 4.08302158e-01 -1.33141009e-02 1.09866768e-01
8.90483260e-01 3.01900536e-01 6.15264297e-01 -6.54721141e-01
-3.43856156e-01 4.20033097e-01 3.97922099e-01 -2.81482309e-01
6.87013507e-01 2.30687181e-03 6.98247194e-01 -1.16023088e+00
-3.42582643e-01 -2.40089953e-01 -9.15429473e-01 -2.82731086e-01
9.29781735e-01 -3.74002039e-01 -1.01726973e+00 4.58557904e-01
-9.88260448e-01 1.29052877e-01 -3.81700635e-01 1.00184107e+00
-2.13822514e-01 3.51811349e-01 -3.57827634e-01 -1.08647954e+00
-8.20439577e-01 -5.08048534e-01 1.73996359e-01 1.62950099e-01
-4.15477157e-01 -1.09005415e+00 1.78000554e-01 8.38047937e-02
6.29825473e-01 1.03749955e+00 1.21712506e+00 -8.80609810e-01
1.25819489e-01 -5.76261103e-01 2.16224808e-02 6.32789671e-01
1.89441502e-01 1.13961138e-02 -7.51567066e-01 -5.88632002e-02
1.77587926e-01 1.71542883e-01 3.94664884e-01 5.68802536e-01
6.32631123e-01 1.49614498e-01 -4.99266759e-02 2.27982238e-01
1.60479903e+00 6.17566288e-01 6.52255595e-01 2.25937784e-01
2.84354568e-01 3.40668440e-01 1.55618593e-01 6.17543638e-01
-1.66410610e-01 5.16800404e-01 2.13504642e-01 -1.80046231e-01
2.18188509e-01 6.00458741e-01 -2.44633719e-01 6.47019267e-01
-1.00930405e+00 1.69109598e-01 -8.72689366e-01 2.31853742e-02
-1.36276901e+00 -1.16491795e+00 -7.62383163e-01 2.64688659e+00
7.12136388e-01 3.77169311e-01 4.82414424e-01 9.82343316e-01
6.61466718e-01 -2.67625242e-01 -1.98675811e-01 -4.79079992e-01
-1.95471093e-01 4.74008590e-01 3.34137194e-02 1.67727590e-01
-8.14849019e-01 -2.38492340e-01 6.04013205e+00 -1.46239311e-01
-1.41976249e+00 -2.50192076e-01 6.38200283e-01 3.73616666e-01
2.87910879e-01 -2.47492209e-01 -4.29371983e-01 5.58243394e-01
1.17907667e+00 2.93115154e-03 1.90988883e-01 6.98404729e-01
5.67025423e-01 -1.90103829e-01 -6.05382025e-01 1.02157867e+00
-1.15408607e-01 -7.74249732e-01 -4.38716412e-01 2.04922492e-03
1.22641385e-01 -5.78198254e-01 -2.23347709e-01 1.54951900e-01
-1.09708214e+00 -8.15928817e-01 -1.29230827e-01 9.41316783e-01
6.05466127e-01 -5.80887794e-01 1.38731658e+00 3.63282651e-01
-7.20526695e-01 -2.18792990e-01 4.38228548e-02 -2.97312260e-01
-4.39133495e-02 1.04108441e+00 -8.46418977e-01 6.13625228e-01
3.42768878e-01 4.39438581e-01 -4.42524284e-01 1.09827530e+00
-6.66416576e-03 7.78786361e-01 -3.85838658e-01 7.60939624e-03
-2.73102790e-01 -4.57955986e-01 7.75454283e-01 6.72266304e-01
2.71668226e-01 1.03389375e-01 -1.22240491e-01 9.35976267e-01
6.80653930e-01 5.61426401e-01 -4.36395258e-01 1.43047273e-01
2.08018139e-01 1.28340721e+00 -8.36968124e-01 -4.30877030e-01
6.96958452e-02 2.42788553e-01 -4.23055410e-01 1.12872131e-01
-6.28369272e-01 -6.31167233e-01 2.41210312e-01 5.23411334e-01
-1.27062127e-01 -9.69917104e-02 -4.39784706e-01 -7.61769295e-01
-3.15216519e-02 -6.91279352e-01 3.82097900e-01 -3.27890635e-01
-7.21599102e-01 7.21781552e-01 1.14571758e-01 -1.18006968e+00
-6.41371965e-01 -6.00780606e-01 -6.57974660e-01 1.36524296e+00
-1.15953553e+00 -5.29256046e-01 -5.37214100e-01 2.69212753e-01
-1.51149914e-01 -2.19125539e-01 1.27327430e+00 5.34378648e-01
-6.57735527e-01 8.18513408e-02 1.97416986e-03 1.34098023e-01
4.55095679e-01 -1.29100668e+00 -5.90755820e-01 3.30959111e-01
-6.04978561e-01 2.28598803e-01 9.05129790e-01 -3.75674665e-01
-6.33552432e-01 -4.71714407e-01 1.42039633e+00 1.12009592e-01
4.21352461e-02 3.31886888e-01 -8.31992090e-01 2.41627499e-01
-6.76018968e-02 8.85110572e-02 9.20820713e-01 -1.45533592e-01
3.36690217e-01 -2.65031308e-01 -1.31421053e+00 3.96327935e-02
3.01277131e-01 -8.35727081e-02 -6.32887959e-01 -2.57359538e-02
9.15352628e-03 -2.13129610e-01 -1.55658329e+00 5.70288658e-01
9.16757762e-01 -1.35106432e+00 1.09276605e+00 -5.52361548e-01
5.76490425e-02 -1.48856252e-01 3.65966141e-01 -9.04676676e-01
-2.25406021e-01 -3.22102875e-01 8.18203390e-02 9.25584376e-01
2.25684553e-01 -1.10149610e+00 5.47275603e-01 5.53646922e-01
2.34642655e-01 -6.63700581e-01 -7.64550209e-01 -5.40199399e-01
-3.26474220e-01 1.53202310e-01 1.91373035e-01 9.33787107e-01
-1.59535021e-01 3.58488113e-01 -2.29410157e-01 -1.77758425e-01
6.44783676e-01 1.10642396e-01 4.90914047e-01 -2.17136097e+00
-3.94112855e-01 -3.07774663e-01 -8.46880674e-01 4.63188589e-01
-2.52303779e-01 -5.78512192e-01 -8.16199183e-01 -1.37753224e+00
-3.06429565e-01 -4.76130724e-01 -3.84241849e-01 3.28686714e-01
7.32838223e-03 3.46164823e-01 7.85702169e-02 2.14025006e-01
4.93874848e-01 -5.80873638e-02 1.02224815e+00 3.38194102e-01
-7.41447806e-01 5.96554637e-01 -9.70852450e-02 6.66184068e-01
9.70272660e-01 -5.84669113e-01 -4.52808231e-01 4.73983467e-01
1.31490126e-01 6.00804508e-01 4.69461828e-01 -1.34580600e+00
-3.73421282e-01 2.47640446e-01 9.00205672e-01 -4.59242195e-01
2.53869802e-01 -1.18798339e+00 7.96965778e-01 1.17597377e+00
-3.24393921e-02 7.71965608e-02 5.35902306e-02 7.54088163e-02
-2.58475274e-01 -4.01825458e-01 8.03523958e-01 -1.87282100e-01
-1.87459394e-01 -5.97516522e-02 -4.71969396e-01 -1.16751179e-01
1.07945931e+00 -4.52502310e-01 -4.51672338e-02 -3.57993729e-02
-1.62134647e+00 -3.74597311e-01 2.03663204e-02 -3.59671205e-01
3.19211662e-01 -1.00459099e+00 -7.67089128e-01 3.18274021e-01
-1.58411399e-01 -3.55838746e-01 5.92564046e-01 1.57038665e+00
-9.03980136e-01 4.14507776e-01 -7.07621217e-01 -6.00365639e-01
-1.59534228e+00 4.84924853e-01 4.97686803e-01 -2.82412499e-01
-7.76330233e-01 -1.81579441e-01 -8.93431902e-01 1.07376419e-01
3.17059979e-02 -2.43180782e-01 -1.01855314e+00 4.44547504e-01
3.70844841e-01 8.07820320e-01 1.55627549e-01 -4.82317001e-01
-2.78237224e-01 8.12177002e-01 4.81216580e-01 1.44069105e-01
1.12387514e+00 -4.11285162e-02 -2.94997305e-01 6.29371405e-01
9.84347105e-01 -1.96393088e-01 -1.29102275e-01 -1.39285112e-02
-1.83335498e-01 -1.26429528e-01 -1.04505643e-01 -1.02115309e+00
-1.01474512e+00 1.00780439e+00 9.84921634e-01 7.71580338e-01
1.21565711e+00 -5.47624290e-01 3.74600440e-01 4.25025970e-01
1.37342200e-01 -7.45797992e-01 -5.62513769e-01 -1.92176625e-01
6.63950682e-01 -9.72182035e-01 4.23348062e-02 -3.09294224e-01
-2.05034375e-01 1.70354486e+00 4.67341579e-02 -4.81930152e-02
8.88534904e-01 -1.53973803e-01 1.45700917e-01 1.14415877e-01
-4.35192704e-01 -5.47750294e-02 -3.64230312e-02 5.11752069e-01
5.38601995e-01 8.85768086e-02 -1.15006173e+00 4.56479728e-01
1.11736335e-01 5.96524775e-01 2.74962783e-01 7.80634522e-01
-5.47391415e-01 -1.03791201e+00 -5.93819678e-01 6.37985885e-01
-6.54118896e-01 2.34809160e-01 -1.84578113e-02 1.17754281e+00
3.15178841e-01 6.74634397e-01 -3.52502838e-02 -7.70296678e-02
4.33710217e-01 6.43497527e-01 4.78873700e-01 -1.17806986e-01
-7.46509850e-01 -2.14073360e-01 1.30465582e-01 -5.72811961e-02
-5.62312245e-01 -6.70006752e-01 -1.13138449e+00 -2.17737079e-01
-6.67058676e-02 3.60682458e-01 8.59224141e-01 1.05711281e+00
2.16700509e-01 5.92103064e-01 7.96311617e-01 -4.86380309e-01
-6.88419223e-01 -1.21121025e+00 -1.16805530e+00 2.85315067e-01
2.73783952e-01 -4.22178209e-01 -7.22966373e-01 1.38744563e-01] | [14.111681938171387, 3.1528944969177246] |
2694bb2b-7b0e-4742-9cdd-70b2c62e9e28 | skin-lesion-segmentation-and-classification-2 | 1908.05730 | null | https://arxiv.org/abs/1908.05730v1 | https://arxiv.org/pdf/1908.05730v1.pdf | Skin Lesion Segmentation and Classification for ISIC 2018 by Combining Deep CNN and Handcrafted Features | This short report describes our submission to the ISIC 2018 Challenge in Skin Lesion Analysis Towards Melanoma Detection for Task1 and Task 3. This work has been accomplished by a team of researchers at the University of Dayton Signal and Image Processing Lab. Our proposed approach is computationally efficient are combines information from both deep learning and handcrafted features. For Task3, we form a new type of image features, called hybrid features, which has stronger discrimination ability than single method features. These features are utilized as inputs to a decision-making model that is based on a multiclass Support Vector Machine (SVM) classifier. The proposed technique is evaluated on online validation databases. Our score was 0.841 with SVM classifier on the validation dataset. | ['Redha Ali', 'Temesguen Messay Kebede', 'Russell C. Hardie', 'Manawaduge Supun De Silva'] | 2019-08-14 | null | null | null | null | ['skin-lesion-segmentation'] | ['medical'] | [ 7.67444968e-01 -2.78238207e-01 -3.42352211e-01 -4.28901374e-01
-9.57834899e-01 -3.05076182e-01 5.84404171e-01 1.79868549e-01
-6.70859873e-01 5.99653840e-01 1.22762166e-01 -2.80174673e-01
-5.18625304e-02 -3.78765047e-01 -4.00739536e-02 -7.48092830e-01
1.54712826e-01 -5.08260250e-01 2.62590796e-01 -3.08264587e-02
2.67313600e-01 4.94160205e-01 -1.13743818e+00 9.27844048e-01
7.33409226e-01 1.18506539e+00 -1.23157449e-01 1.31280172e+00
3.62115771e-01 5.75387180e-01 -3.72743845e-01 -3.02943558e-01
3.73401791e-01 -4.00001824e-01 -5.99321663e-01 2.74546176e-01
5.36718190e-01 1.21264495e-01 -1.91417560e-01 8.95966172e-01
7.90886521e-01 -2.20124766e-01 8.94954801e-01 -1.08149016e+00
-2.79237702e-02 1.59378871e-01 -5.97655714e-01 5.88084280e-01
2.51313210e-01 2.08256334e-01 6.21474504e-01 -7.69641757e-01
5.61201572e-01 7.92473376e-01 1.03316951e+00 6.00348294e-01
-9.81968045e-01 -4.66844201e-01 -2.10480407e-01 4.52123702e-01
-1.25119495e+00 -3.68343055e-01 4.85450029e-01 -5.17951012e-01
9.18267965e-01 5.36432624e-01 6.73838377e-01 1.23799419e+00
3.40235233e-01 8.32575798e-01 1.59566057e+00 -6.92232370e-01
2.23350942e-01 5.98610640e-01 3.42938602e-01 8.57831478e-01
-5.96680902e-02 2.85824955e-01 -6.01313829e-01 -2.12605625e-01
4.89452451e-01 -1.21258140e-01 -1.60852924e-01 3.42831522e-01
-9.61076677e-01 1.00573397e+00 4.35088396e-01 2.00400770e-01
-5.86113870e-01 2.10920107e-02 4.81585473e-01 4.66097593e-01
4.39840615e-01 2.80153882e-02 -3.71708333e-01 4.01961990e-02
-8.73735368e-01 -1.40791312e-01 5.15387952e-01 2.27156952e-01
7.80019462e-02 -1.54354379e-01 -5.66020787e-01 1.05347729e+00
3.45781803e-01 3.55623275e-01 8.48120391e-01 -4.43855494e-01
-4.21356186e-02 6.32668138e-01 -3.76846582e-01 -6.96529448e-01
-7.34179854e-01 -5.92224538e-01 -7.96057820e-01 2.23849818e-01
2.45631546e-01 -4.41881806e-01 -1.24383998e+00 1.06303954e+00
1.90664500e-01 2.55911529e-01 1.30635336e-01 9.59047675e-01
1.02816653e+00 2.76803374e-01 2.04144195e-01 9.50589925e-02
1.29552174e+00 -1.08490670e+00 -4.95597005e-01 1.65610015e-01
6.66749716e-01 -9.28312540e-01 4.50562447e-01 8.05658519e-01
-6.47330165e-01 -5.24547696e-01 -1.15060544e+00 3.18465292e-01
-5.08832872e-01 6.10903442e-01 6.76808596e-01 1.14024496e+00
-1.04783928e+00 1.75769851e-01 -5.97565830e-01 -8.72008562e-01
5.22625387e-01 4.64351594e-01 -5.39398611e-01 -8.54276717e-02
-7.88693309e-01 1.09569740e+00 1.06829502e-01 -6.35329336e-02
-7.02985346e-01 -4.17092860e-01 -7.23842323e-01 -5.75094581e-01
-1.64050564e-01 -4.67106909e-01 9.26412821e-01 -1.35259140e+00
-1.49982619e+00 1.03094959e+00 -2.66930073e-01 -7.47411370e-01
5.18896878e-01 2.20179096e-01 -7.53895760e-01 3.61691058e-01
2.53316481e-02 5.46442449e-01 1.20380199e+00 -8.79249156e-01
-1.00388169e+00 -4.08836216e-01 -3.11991721e-01 2.44206175e-01
-3.77392083e-01 1.99028909e-01 -1.22942239e-01 -6.93738878e-01
-1.57708168e-01 -1.00471151e+00 -1.76535740e-01 7.65474960e-02
-6.55553520e-01 -7.90763423e-02 6.59021139e-01 -8.08136821e-01
9.95760441e-01 -2.10897899e+00 -2.30158627e-01 5.66654801e-01
3.54602747e-02 5.37778676e-01 -1.78947568e-01 4.19874460e-01
-3.32358330e-01 -4.68742102e-03 1.47632780e-02 -1.92036817e-03
-4.03160393e-01 -2.23066688e-01 1.03575088e-01 5.44611812e-01
4.59330678e-01 7.66191900e-01 -5.46421170e-01 -5.00924051e-01
2.93501258e-01 3.42714489e-01 6.01967983e-02 -2.92148113e-01
4.42483336e-01 1.61065713e-01 -2.57830620e-01 1.06098711e+00
5.68206072e-01 -1.02654882e-01 -8.25123489e-02 -5.01282454e-01
5.96799962e-02 -2.85602927e-01 -9.64372993e-01 1.38272929e+00
-3.48917097e-01 8.89553070e-01 -2.01234639e-01 -1.06739354e+00
6.48936629e-01 3.15167308e-01 2.94820547e-01 -3.28814209e-01
2.81408221e-01 -8.74047279e-02 2.80080795e-01 -8.77592742e-01
-4.73436341e-02 -8.87656137e-02 3.05136740e-01 2.62298062e-02
3.46504092e-01 8.44149515e-02 2.23689884e-01 1.48931354e-01
1.49968302e+00 -2.46650949e-01 5.93724728e-01 -1.39287233e-01
7.54655659e-01 2.53475785e-01 2.97000408e-01 6.81291819e-01
-7.51976132e-01 4.15774524e-01 2.21854985e-01 -4.37540203e-01
-5.94350755e-01 -9.23416138e-01 -6.29646719e-01 9.48987365e-01
-3.01800966e-01 -2.37269789e-01 -5.65033793e-01 -9.82649446e-01
1.42661974e-01 6.18175417e-02 -9.94888306e-01 -5.96599765e-02
-2.69064419e-02 -1.00760257e+00 7.29451954e-01 5.05009770e-01
4.76740658e-01 -7.75907278e-01 -4.87272680e-01 -6.67382926e-02
2.90649861e-01 -1.08547330e+00 -2.63677388e-01 2.50879467e-01
-6.16616249e-01 -1.41106176e+00 -9.04048502e-01 -8.22058380e-01
6.45600617e-01 1.86118394e-01 2.56373703e-01 -4.03857231e-02
-1.07618749e+00 4.27902997e-01 -4.46549028e-01 -8.67510498e-01
-1.34719819e-01 -1.28600493e-01 -7.99887627e-02 5.98665833e-01
4.53588992e-01 2.15354770e-01 -5.62666178e-01 4.44283634e-02
-7.27683902e-01 -2.16304697e-02 1.06565273e+00 1.27327299e+00
4.09199238e-01 8.40297937e-02 6.97611749e-01 -8.13473463e-01
6.76889122e-01 -2.86854416e-01 -2.39386171e-01 1.56542405e-01
-2.03863457e-01 -4.30014908e-01 2.94100374e-01 -3.30804169e-01
-9.24264729e-01 6.35008812e-01 -6.55139461e-02 5.56575926e-03
-3.18431228e-01 5.92744648e-01 3.60724151e-01 -8.15015435e-01
9.54517365e-01 2.35880822e-01 1.77306965e-01 -4.65353131e-02
3.12759914e-03 1.12974942e+00 3.33080769e-01 1.11417368e-01
5.16594052e-01 4.98914093e-01 3.42715919e-01 -1.19495499e+00
-9.56141114e-01 -8.71921420e-01 -7.05746293e-01 -4.07748282e-01
7.86557376e-01 -9.08530176e-01 -3.03897828e-01 1.08971179e+00
-6.99173808e-01 -1.20189264e-01 8.18078294e-02 7.12815642e-01
-1.57582492e-01 3.04906070e-01 -3.89272988e-01 -9.03645098e-01
-3.98824990e-01 -9.00255382e-01 1.06307280e+00 5.23690581e-01
-3.55336666e-01 -1.21160114e+00 -8.00649170e-03 6.19476676e-01
4.80043322e-01 6.41835928e-01 4.13561285e-01 -7.29278266e-01
1.90647125e-01 -8.45565021e-01 -3.65155041e-01 5.95548987e-01
1.66474998e-01 2.71750569e-01 -1.28914225e+00 -3.73441488e-01
-2.86953390e-01 -4.11981165e-01 1.36178923e+00 5.97653985e-01
1.20645130e+00 1.45312414e-01 -4.78255570e-01 4.95460421e-01
1.52993047e+00 9.63664278e-02 3.65424722e-01 2.66402364e-01
1.74081996e-01 4.80503917e-01 4.90982205e-01 3.07692200e-01
3.24708641e-01 5.41295528e-01 2.48598352e-01 -3.72195244e-01
-3.74614775e-01 1.55108973e-01 2.45815516e-01 3.27817053e-01
-1.31215587e-01 9.72512439e-02 -8.78757060e-01 5.77451646e-01
-1.63223302e+00 -8.04298580e-01 -4.52445149e-01 1.95883095e+00
7.05757320e-01 3.20248194e-02 2.90226132e-01 5.70810676e-01
7.11179376e-01 -2.07348868e-01 -3.29668790e-01 -6.25156403e-01
-1.09507419e-01 5.52289784e-01 6.05556488e-01 2.74843991e-01
-1.65749645e+00 6.81055307e-01 6.68528271e+00 8.75703990e-01
-1.51065207e+00 -9.47313085e-02 6.21844769e-01 -3.12665701e-02
3.39424074e-01 -4.17211920e-01 -5.98830223e-01 4.84795749e-01
9.56114709e-01 -2.39533875e-02 1.11492909e-03 3.59827340e-01
8.12763944e-02 -5.61616719e-01 -7.97462702e-01 1.06482327e+00
4.55982983e-01 -1.32606196e+00 -2.12713048e-01 7.88597688e-02
5.74287534e-01 6.02972433e-02 3.75211447e-01 5.22665717e-02
-5.78326397e-02 -1.34502769e+00 -4.17877585e-02 8.31890821e-01
7.67385364e-01 -5.73529303e-01 1.01671064e+00 2.04218581e-01
-7.66833186e-01 -3.10378104e-01 -5.78679070e-02 4.79643233e-02
-4.15649414e-01 5.37181318e-01 -1.21929860e+00 4.80453759e-01
6.04734480e-01 8.16345632e-01 -8.60781252e-01 1.40137196e+00
-1.56520173e-01 8.36934149e-01 -9.83746126e-02 -2.46042013e-01
2.70786792e-01 4.36627090e-01 3.18701923e-01 1.52852440e+00
1.93114374e-02 3.36553715e-02 2.79211998e-02 1.09157048e-01
3.67778569e-01 1.46644503e-01 -5.01875103e-01 -5.07036224e-02
1.51300013e-01 1.78308225e+00 -5.98027170e-01 -1.64532900e-01
-4.22331214e-01 9.79291856e-01 -5.97770102e-02 7.37537816e-03
-4.82240945e-01 -6.64033234e-01 1.86185941e-01 -1.58521608e-01
2.65567470e-02 8.69986415e-02 -4.99120712e-01 -9.12748575e-01
-2.17178628e-01 -7.42613792e-01 6.34148240e-01 -4.38560337e-01
-1.42639828e+00 4.74643201e-01 -4.56123263e-01 -1.11011720e+00
2.57246438e-02 -9.78758931e-01 -1.11296725e+00 1.11455929e+00
-1.59918427e+00 -1.49615538e+00 -6.61849141e-01 8.21550190e-01
4.16796774e-01 -7.11864650e-01 1.01720560e+00 5.69134131e-02
-7.99168885e-01 8.75195563e-01 -1.30032282e-02 1.94122121e-01
9.11122203e-01 -1.27170217e+00 -1.09553829e-01 8.92675877e-01
8.10818449e-02 2.14781463e-02 1.03507303e-01 -4.15411472e-01
-1.41504645e+00 -1.30037189e+00 8.57531488e-01 -2.70901203e-01
7.17596650e-01 1.27163455e-01 -1.94913000e-01 1.67777717e-01
2.25879669e-01 2.56556630e-01 1.47881317e+00 -1.75201237e-01
-3.87932695e-02 -5.76241128e-02 -1.51036334e+00 -1.97351780e-02
3.01890492e-01 -4.70004618e-01 -2.38719374e-01 5.77913880e-01
-1.04609847e-01 -2.99857050e-01 -9.63837624e-01 4.02725369e-01
8.15104306e-01 -4.82065678e-01 7.80379534e-01 -7.49109864e-01
3.04018378e-01 -1.37015924e-01 -3.15020174e-01 -1.39595985e+00
-2.03402698e-01 -2.46598944e-01 1.99657679e-01 6.66502595e-01
5.11472881e-01 -5.45540690e-01 6.97755992e-01 6.61783442e-02
1.20301157e-01 -1.03987455e+00 -1.02491617e+00 -6.47061408e-01
-1.90658242e-01 -4.24028337e-01 -2.90380865e-01 9.19924378e-01
1.32685483e-01 2.97970921e-01 -2.08761320e-01 9.73379910e-02
7.16079056e-01 -1.63014725e-01 4.86213386e-01 -1.11108541e+00
-1.69420496e-01 -3.39741617e-01 -1.06343365e+00 3.70041910e-03
-1.37198269e-01 -1.05360329e+00 -3.96888733e-01 -1.43115354e+00
2.59333104e-01 -1.43122539e-01 -6.35702193e-01 7.74299026e-01
-1.46531940e-01 8.48514736e-01 1.24402806e-01 -1.21114239e-01
-2.22663134e-01 -1.32959470e-01 9.39864516e-01 -3.71996850e-01
-6.09515309e-02 4.41427588e-01 -8.26488316e-01 7.26932526e-01
9.92621124e-01 -9.53974277e-02 -7.84672610e-03 -9.45493504e-02
-4.97371167e-01 -3.18588922e-03 6.50571823e-01 -1.25906456e+00
4.28238988e-01 -9.37812477e-02 9.62243259e-01 -3.67456377e-01
5.39032519e-01 -5.04414141e-01 -3.82745087e-01 8.16332817e-01
-4.68869448e-01 -6.31471872e-01 2.24615023e-01 4.83193278e-01
-3.20165157e-01 -1.81188837e-01 1.17104077e+00 1.24378487e-01
-8.45140994e-01 1.19552277e-01 -4.81762916e-01 -4.86733317e-01
1.56068397e+00 -3.77499282e-01 -3.12869459e-01 -6.93620965e-02
-1.22749257e+00 1.49958119e-01 -1.00642316e-01 2.65581042e-01
7.78844178e-01 -1.27939820e+00 -1.05112886e+00 3.12354177e-01
3.01363766e-01 -8.57031345e-01 1.45820200e-01 1.16537535e+00
-4.01479363e-01 5.17353356e-01 -5.30560017e-01 -7.35925853e-01
-1.84437680e+00 -8.55278447e-02 4.56226438e-01 -1.55740112e-01
-2.14744404e-01 1.13659787e+00 -4.61311847e-01 -2.05904424e-01
1.24071911e-01 -6.77550659e-02 -5.42810500e-01 1.75782546e-01
7.39100575e-01 4.73438680e-01 2.67194241e-01 -5.61590791e-01
-5.52213311e-01 5.23176014e-01 -3.18554223e-01 -9.70943645e-02
1.11752939e+00 2.89579898e-01 1.17226422e-01 1.74988881e-01
1.22366250e+00 -2.92979181e-01 -7.42065251e-01 -2.23688588e-01
-4.35755439e-02 -4.46890652e-01 4.85725462e-01 -1.41645277e+00
-8.64437103e-01 9.13769722e-01 1.30957913e+00 7.72477090e-02
1.36144674e+00 -3.95754904e-01 4.99091536e-01 3.66408259e-01
-4.74694893e-02 -1.34647393e+00 -4.50368896e-02 3.03770542e-01
8.25256884e-01 -1.62444317e+00 3.14137735e-03 -4.61085647e-01
-9.18675423e-01 1.35106254e+00 5.79457760e-01 -4.05652553e-01
9.35543776e-01 3.24971110e-01 2.37534761e-01 7.77664483e-02
-8.78843486e-01 -4.60727900e-01 6.85684085e-01 1.06585121e+00
4.29333508e-01 2.61913300e-01 -7.01173961e-01 7.99166083e-01
2.12554619e-01 2.44770467e-01 4.27271575e-01 8.97708476e-01
-4.21008497e-01 -1.07376814e+00 -1.49750710e-01 1.02070475e+00
-6.65632844e-01 -1.16182700e-01 -6.54413164e-01 6.08600557e-01
3.29753250e-01 9.60613251e-01 -3.50210398e-01 -6.02560520e-01
3.59992795e-02 -1.11505821e-01 5.36955118e-01 -5.02953947e-01
-7.15976894e-01 -1.13995925e-01 3.12524557e-01 -4.63144928e-01
-4.22351748e-01 -5.33618927e-01 -7.70911396e-01 3.34785640e-01
-2.39727020e-01 -2.36841097e-01 1.14222443e+00 8.82113397e-01
1.04567036e-01 5.94072700e-01 8.91979396e-01 -4.60354418e-01
-5.40294349e-01 -1.11098981e+00 -6.92968130e-01 1.33773416e-01
3.88264000e-01 -4.44112867e-01 -7.71731958e-02 1.67390659e-01] | [15.690048217773438, -2.97685170173645] |
5f8fb1ea-77d2-4172-aa4d-5f5db14bbf80 | a-novel-mask-r-cnn-model-to-segment | 2204.01201 | null | https://arxiv.org/abs/2204.01201v1 | https://arxiv.org/pdf/2204.01201v1.pdf | A Novel Mask R-CNN Model to Segment Heterogeneous Brain Tumors through Image Subtraction | The segmentation of diseases is a popular topic explored by researchers in the field of machine learning. Brain tumors are extremely dangerous and require the utmost precision to segment for a successful surgery. Patients with tumors usually take 4 MRI scans, T1, T1gd, T2, and FLAIR, which are then sent to radiologists to segment and analyze for possible future surgery. To create a second segmentation, it would be beneficial to both radiologists and patients in being more confident in their conclusions. We propose using a method performed by radiologists called image segmentation and applying it to machine learning models to prove a better segmentation. Using Mask R-CNN, its ResNet backbone being pre-trained on the RSNA pneumonia detection challenge dataset, we can train a model on the Brats2020 Brain Tumor dataset. Center for Biomedical Image Computing & Analytics provides MRI data on patients with and without brain tumors and the corresponding segmentations. We can see how well the method of image subtraction works by comparing it to models without image subtraction through DICE coefficient (F1 score), recall, and precision on the untouched test set. Our model performed with a DICE coefficient of 0.75 in comparison to 0.69 without image subtraction. To further emphasize the usefulness of image subtraction, we compare our final model to current state-of-the-art models to segment tumors from MRI scans. | ['Sanskriti Singh'] | 2022-04-04 | null | null | null | null | ['pneumonia-detection'] | ['medical'] | [ 4.81774747e-01 6.54026151e-01 -8.92700776e-02 -5.17672539e-01
-9.12779093e-01 -3.15478146e-01 3.64845365e-01 2.18939230e-01
-8.71048868e-01 5.74853361e-01 1.90368101e-01 -5.44580579e-01
1.31455347e-01 -5.39349258e-01 -5.27358651e-01 -7.13821769e-01
7.38055557e-02 8.04977596e-01 6.16282701e-01 1.88413501e-01
6.97822124e-02 4.86680776e-01 -8.02648008e-01 3.55360031e-01
8.73043478e-01 9.15990829e-01 3.89655232e-01 6.49274111e-01
-1.56618401e-01 6.31668210e-01 -4.71753955e-01 -2.43028715e-01
3.90132666e-01 -3.29656631e-01 -1.05102277e+00 -9.53894854e-02
2.81105220e-01 -3.67836207e-01 -1.85794011e-01 1.20650899e+00
4.51296866e-01 -2.32782483e-01 8.57805431e-01 -7.28298843e-01
-2.73172736e-01 1.02072954e+00 -7.00514317e-01 5.83540142e-01
-1.83639392e-01 2.93525398e-01 3.47334087e-01 -4.15269971e-01
6.75697803e-01 6.25352621e-01 6.87818706e-01 6.79579735e-01
-9.40466821e-01 -7.27099359e-01 -2.42277741e-01 1.25325233e-01
-1.10844529e+00 -1.14381708e-01 2.14136168e-01 -5.58208346e-01
6.83881938e-01 5.21772563e-01 8.86868179e-01 7.11019695e-01
4.57070112e-01 7.29974627e-01 1.26125300e+00 -2.50451326e-01
1.59133837e-01 -6.67153373e-02 3.49370956e-01 6.69758558e-01
1.23681545e-01 -9.99295488e-02 3.25680137e-01 2.29124829e-01
6.78600430e-01 1.99596003e-01 -4.52187359e-01 -1.68269232e-01
-1.62382162e+00 6.22398138e-01 8.65366518e-01 6.85235918e-01
-4.65640157e-01 2.91122161e-02 3.40451479e-01 -1.93130365e-03
3.98758203e-01 2.05646709e-01 -1.31300569e-01 3.72779340e-01
-1.38119161e+00 -1.65452555e-01 3.36419374e-01 3.06274086e-01
6.70576170e-02 -4.09045875e-01 -3.28078836e-01 8.27881753e-01
1.76466927e-01 1.54871956e-01 1.21387208e+00 -6.64458811e-01
-6.36753961e-02 5.36692858e-01 -3.99057746e-01 -3.63983661e-01
-8.28110158e-01 -5.95613062e-01 -9.68373239e-01 1.88433513e-01
6.11301482e-01 2.35124212e-02 -1.54473889e+00 1.31864977e+00
1.07920095e-01 2.48753220e-01 -5.96764795e-02 9.46334720e-01
1.00364697e+00 2.56244019e-02 9.17542428e-02 -9.78325382e-02
1.37359273e+00 -1.23834920e+00 -4.06159222e-01 -1.53082147e-01
1.09700465e+00 -4.95008081e-01 7.30322659e-01 4.77253437e-01
-1.14315879e+00 -1.65913641e-01 -8.56582403e-01 1.90453902e-01
-3.02569479e-01 -1.02535985e-01 4.50333446e-01 7.42242157e-01
-1.36866856e+00 5.37778199e-01 -1.21736562e+00 -4.82681334e-01
7.89591730e-01 6.74818516e-01 -4.64273453e-01 -4.02772948e-02
-8.83836150e-01 1.29426801e+00 4.68572825e-01 -2.09665373e-01
-1.01048315e+00 -9.93940949e-01 -4.35389638e-01 -2.18686774e-01
2.24337265e-01 -6.11082137e-01 1.29304278e+00 -8.81124020e-01
-1.00496709e+00 1.32611549e+00 1.26076937e-01 -9.99766588e-01
7.95369327e-01 3.08409780e-01 -2.23482326e-01 4.39594924e-01
1.51973933e-01 1.12893319e+00 4.25764352e-01 -8.72804284e-01
-5.82291365e-01 -6.90348983e-01 -3.90573800e-01 3.61605510e-02
1.66166738e-01 7.28856586e-03 -4.26695287e-01 -4.82041717e-01
2.99709320e-01 -1.01959562e+00 -5.31480908e-01 -6.91099688e-02
-5.58063447e-01 1.65426716e-01 6.76912844e-01 -1.17519093e+00
5.69914103e-01 -1.90484571e+00 -1.39557496e-01 4.30420250e-01
6.56084538e-01 3.47026646e-01 -7.79254213e-02 -8.60313475e-01
-5.56755364e-01 3.48131984e-01 -6.96614206e-01 -1.65973082e-02
-5.45820475e-01 -1.11284778e-01 4.09389853e-01 5.11502206e-01
-9.80090275e-02 1.07780921e+00 -6.48052990e-01 -5.28852582e-01
2.45499805e-01 3.81820858e-01 -3.93857986e-01 -1.99197549e-02
1.82345435e-01 8.37798119e-01 -3.02986354e-01 4.12937343e-01
6.13459766e-01 -2.82862157e-01 6.81582540e-02 -2.42588997e-01
1.20349497e-01 -9.17735230e-03 -4.49534863e-01 1.57779515e+00
-1.87606260e-01 5.57003021e-01 1.25757366e-01 -1.36842811e+00
6.63958311e-01 3.46719176e-01 9.50804651e-01 -8.54327261e-01
4.58433956e-01 2.53271699e-01 6.02775037e-01 -4.70122695e-01
-2.25493416e-01 -3.58779371e-01 3.90098810e-01 4.11521465e-01
-2.72114873e-01 -4.95643616e-01 1.49693310e-01 1.62842676e-01
1.50846958e+00 -4.30562288e-01 1.59760103e-01 -2.92089164e-01
5.88454187e-01 8.39173049e-02 1.31378800e-01 6.30619764e-01
-6.70271814e-01 8.09074461e-01 3.37271065e-01 -2.55345672e-01
-9.00950074e-01 -1.15720749e+00 -4.24947560e-01 4.59064543e-01
-1.98283374e-01 2.30432197e-01 -1.14355826e+00 -1.01439416e+00
-2.34829575e-01 7.64334738e-01 -8.26979160e-01 -1.75210923e-01
-5.39192796e-01 -1.00362873e+00 6.40217423e-01 4.32396114e-01
5.73147118e-01 -9.61297989e-01 -8.55816901e-01 8.99645239e-02
-2.93458939e-01 -1.04049969e+00 -4.13728625e-01 1.86494693e-01
-1.08356619e+00 -1.23213398e+00 -1.32189226e+00 -7.45085478e-01
7.59407640e-01 1.06134087e-01 1.00234687e+00 2.28723541e-01
-6.20228529e-01 3.32958400e-01 -1.60115391e-01 -5.31290174e-01
-7.57647157e-01 4.21009138e-02 -3.49696308e-01 -4.69791919e-01
2.25895628e-01 -3.97485524e-01 -8.63804340e-01 3.43718976e-01
-1.08823228e+00 3.75567585e-01 9.21308339e-01 5.81894040e-01
8.06343794e-01 -1.67760640e-01 3.14687669e-01 -9.59464848e-01
4.18289542e-01 -4.19380575e-01 -3.96832347e-01 3.15130115e-01
-5.19366145e-01 -2.21156552e-01 2.36928269e-01 -2.53118038e-01
-6.18971109e-01 1.25148878e-01 -2.49364376e-01 -2.41680473e-01
-2.90826768e-01 3.00497800e-01 4.10106808e-01 -1.99149325e-01
6.97185278e-01 4.63387519e-02 4.60173070e-01 -1.08346213e-02
1.45337090e-01 4.78653014e-01 7.61295140e-01 2.02821910e-01
2.47775868e-01 7.18446553e-01 9.72784609e-02 -5.50973713e-01
-7.68858314e-01 -4.95092154e-01 -8.30153883e-01 -3.28690350e-01
1.24855244e+00 -4.33515042e-01 -3.61738741e-01 3.62548441e-01
-7.37816572e-01 -4.99395311e-01 -3.09703529e-01 6.95052266e-01
-5.41411817e-01 4.14932072e-01 -4.53450382e-01 -1.70174405e-01
-6.59073412e-01 -1.71810412e+00 8.25764060e-01 1.98676452e-01
-2.41821289e-01 -1.00202537e+00 -8.92037079e-02 7.65328586e-01
6.26003981e-01 2.34334663e-01 8.73578191e-01 -1.17735958e+00
-2.97743589e-01 -2.10586220e-01 -4.10903662e-01 4.12476212e-01
1.23536736e-01 -2.55339354e-01 -7.26415217e-01 -9.11959931e-02
1.32238850e-01 4.14872058e-02 1.17395794e+00 1.03397810e+00
1.68075657e+00 2.70833850e-01 -6.78408921e-01 5.36228955e-01
1.06457567e+00 3.98887575e-01 7.32510984e-01 2.73085207e-01
6.50951028e-01 4.12175328e-01 2.15774819e-01 -1.38779640e-01
3.28319043e-01 3.96672934e-01 5.95410049e-01 -4.37711000e-01
-4.80773926e-01 4.69241738e-01 -9.54671130e-02 7.56285608e-01
5.15148938e-02 1.27994254e-01 -1.36242878e+00 6.11610591e-01
-1.33474112e+00 -6.11628175e-01 -3.17833871e-01 2.12489438e+00
8.58269751e-01 3.46572071e-01 5.32815680e-02 1.52114198e-01
8.39657128e-01 -2.32976630e-01 -5.02822220e-01 -2.45342508e-01
7.06561133e-02 4.75968003e-01 9.08335090e-01 3.75194699e-01
-1.07527173e+00 7.86206484e-01 6.50923061e+00 7.59579778e-01
-1.49637187e+00 3.74739408e-01 1.23504329e+00 -6.20879047e-02
-1.86428782e-02 -2.29770660e-01 -2.94896781e-01 4.47637826e-01
1.19814479e+00 1.36443898e-01 2.70533234e-01 4.29300547e-01
2.68483222e-01 -6.65803492e-01 -1.00314093e+00 8.24640512e-01
7.12122470e-02 -1.35129797e+00 -2.08925888e-01 4.04622080e-03
5.80133677e-01 6.39050066e-01 3.04963607e-02 1.69664174e-01
2.90199697e-01 -1.38158834e+00 3.00979495e-01 6.98108196e-01
7.63536096e-01 -3.48275244e-01 1.00848877e+00 2.90953845e-01
-5.50886214e-01 2.97753185e-01 -1.37585355e-02 5.78994095e-01
-5.11428975e-02 7.42957056e-01 -1.44969523e+00 2.57987708e-01
6.21276498e-01 4.43569154e-01 -7.45182633e-01 1.35824382e+00
2.08064020e-02 7.84826279e-01 -3.14157635e-01 3.07880104e-01
2.10340381e-01 -1.23630248e-01 3.62554163e-01 1.15126109e+00
3.96122068e-01 1.43822953e-01 -9.55551118e-02 8.92000735e-01
-7.15146139e-02 1.57913595e-01 -2.21123755e-01 1.32936031e-01
-7.85353035e-02 1.41688788e+00 -1.41637123e+00 -6.67926848e-01
-3.47528428e-01 7.69693911e-01 -8.58733505e-02 -1.58576906e-01
-8.50996852e-01 2.64897458e-02 -7.24309310e-02 2.38139749e-01
-3.60948294e-02 1.31515786e-01 -6.00770473e-01 -7.71691978e-01
-3.81014913e-01 -7.74109125e-01 3.61281455e-01 -8.50886881e-01
-9.45486188e-01 5.46624243e-01 -1.50178075e-01 -6.85367048e-01
2.42487388e-03 -6.03106141e-01 -7.31884003e-01 7.98109829e-01
-1.39487100e+00 -7.46604860e-01 -5.22105277e-01 5.03903151e-01
3.72461349e-01 7.34938905e-02 5.41807353e-01 2.45259464e-01
-4.62326378e-01 3.65824580e-01 -1.23096988e-01 4.12211686e-01
7.21550047e-01 -1.24171436e+00 2.53159165e-01 6.03290915e-01
-2.16419354e-01 1.35058329e-01 4.83614087e-01 -7.36640453e-01
-7.55224526e-01 -1.20266283e+00 3.58178586e-01 -2.82231271e-01
5.83382189e-01 4.80605036e-01 -9.25859392e-01 7.09262371e-01
9.77060720e-02 1.43894225e-01 7.02109694e-01 -7.09009707e-01
1.40404701e-01 1.98495850e-01 -1.63962829e+00 5.36119521e-01
6.58997476e-01 -7.55687729e-02 -7.43398845e-01 5.75488389e-01
5.29716969e-01 -5.42856455e-01 -9.99418974e-01 8.51240516e-01
4.61898983e-01 -1.02562439e+00 9.40685689e-01 -3.34673256e-01
3.76563281e-01 2.99867075e-02 1.09399311e-01 -1.38305509e+00
-5.19404607e-03 1.51361689e-01 6.25197411e-01 4.20340985e-01
6.45354569e-01 -6.60781860e-01 9.27220166e-01 7.80241966e-01
-2.55130768e-01 -9.51422513e-01 -7.30566680e-01 -5.47589958e-01
6.13121748e-01 -5.73135078e-01 3.79654735e-01 8.49197328e-01
-1.63916931e-01 -3.20561975e-01 4.44787592e-01 -7.34920949e-02
5.28320253e-01 -3.66363734e-01 4.16662216e-01 -1.23827887e+00
6.81521297e-02 -9.62028980e-01 -5.01974642e-01 -5.29737711e-01
-3.42019182e-03 -1.52594852e+00 -1.47557616e-01 -1.92809331e+00
5.64394534e-01 -3.66432875e-01 -5.43880045e-01 4.90810364e-01
-5.05450480e-02 5.28680742e-01 3.29754911e-02 3.12046617e-01
-3.42583746e-01 -7.25156516e-02 1.64658141e+00 -3.64496291e-01
-5.54296002e-03 3.44864652e-02 -5.21010220e-01 9.74032402e-01
1.02228522e+00 -5.16504824e-01 -1.08047001e-01 -1.89763859e-01
-4.39809889e-01 3.17831814e-01 4.36011732e-01 -1.21778703e+00
1.53237224e-01 1.34164408e-01 5.80823302e-01 -7.41647601e-01
7.21727386e-02 -8.49728882e-01 -1.66637152e-02 9.98777092e-01
-4.26569760e-01 -3.96616943e-02 1.42511249e-01 -2.26975214e-02
-7.35768154e-02 -3.54288101e-01 1.18858981e+00 -5.01471281e-01
-2.61566073e-01 4.23823178e-01 -5.92460454e-01 -2.60254350e-02
1.22865832e+00 -2.18610719e-01 -2.39340529e-01 -3.06348532e-01
-1.30256772e+00 1.71509057e-01 3.35302174e-01 5.44318072e-02
6.33601010e-01 -8.28847528e-01 -6.96673810e-01 -1.68239921e-02
-2.81388193e-01 5.50165214e-02 2.37475276e-01 1.72441351e+00
-8.33721519e-01 4.51956421e-01 -3.44751716e-01 -9.19350326e-01
-1.36312914e+00 4.03856874e-01 7.31776536e-01 -5.75882077e-01
-7.04034030e-01 8.63863945e-01 2.77029008e-01 -4.51147735e-01
1.22509703e-01 -8.00217748e-01 -3.12836617e-01 -1.53902873e-01
5.59928477e-01 1.20606527e-01 4.29537266e-01 -5.91497064e-01
-3.32894683e-01 4.76153046e-01 -3.78550589e-01 -1.72791377e-01
1.17713213e+00 1.54574513e-01 -3.03853422e-01 -7.09246248e-02
1.09361303e+00 -2.43870527e-01 -7.37992227e-01 -1.57534540e-01
1.52516559e-01 -2.25464236e-02 3.90380681e-01 -1.20122981e+00
-1.72614276e+00 8.52546513e-01 1.13687646e+00 2.91511655e-01
1.11380303e+00 1.30860150e-01 8.46717894e-01 4.85798754e-02
9.83996596e-03 -7.53022790e-01 -9.47558433e-02 3.58202815e-01
6.24919355e-01 -1.40036058e+00 -2.15285629e-01 -3.16922367e-01
-6.51290178e-01 9.96114075e-01 4.07992125e-01 -1.56098023e-01
7.84924984e-01 5.57949066e-01 2.40971237e-01 -1.65071204e-01
-2.97018409e-01 -1.55436769e-01 4.01878297e-01 5.92270434e-01
5.90850592e-01 4.11490858e-01 -3.57658923e-01 5.55828393e-01
-3.71493816e-01 1.57310277e-01 5.01916707e-01 5.93760073e-01
-6.02509081e-01 -9.22095120e-01 -4.00645137e-01 9.87642825e-01
-7.58300483e-01 -1.18875392e-01 -4.58444774e-01 8.32743704e-01
1.24527812e-01 6.25362694e-01 1.37847602e-01 -7.47569352e-02
6.15363419e-02 1.00639433e-01 4.92887110e-01 -5.22410870e-01
-7.62556911e-01 -5.05217053e-02 -2.11090282e-01 -5.01916707e-01
-4.72008020e-01 -5.98276675e-01 -1.84807861e+00 9.89331380e-02
-2.40862012e-01 -9.72029045e-02 1.05096126e+00 1.09747863e+00
-4.58682328e-02 9.66421008e-01 1.53072879e-01 -7.10748255e-01
-2.99689230e-02 -9.72410023e-01 -2.95377910e-01 3.63166302e-01
2.36800741e-02 -4.50724512e-01 -2.25263089e-01 -6.97274506e-02] | [14.539889335632324, -2.3694849014282227] |
8d74a741-ea94-4200-87ae-f2cacc0b8ff3 | trans2k-unlocking-the-power-of-deep-models | 2210.03436 | null | https://arxiv.org/abs/2210.03436v1 | https://arxiv.org/pdf/2210.03436v1.pdf | Trans2k: Unlocking the Power of Deep Models for Transparent Object Tracking | Visual object tracking has focused predominantly on opaque objects, while transparent object tracking received very little attention. Motivated by the uniqueness of transparent objects in that their appearance is directly affected by the background, the first dedicated evaluation dataset has emerged recently. We contribute to this effort by proposing the first transparent object tracking training dataset Trans2k that consists of over 2k sequences with 104,343 images overall, annotated by bounding boxes and segmentation masks. Noting that transparent objects can be realistically rendered by modern renderers, we quantify domain-specific attributes and render the dataset containing visual attributes and tracking situations not covered in the existing object training datasets. We observe a consistent performance boost (up to 16%) across a diverse set of modern tracking architectures when trained using Trans2k, and show insights not previously possible due to the lack of appropriate training sets. The dataset and the rendering engine will be publicly released to unlock the power of modern learning-based trackers and foster new designs in transparent object tracking. | ['Matej Kristan', 'Jiri Matas', 'Ziga Trojer', 'Alan Lukezic'] | 2022-10-07 | null | null | null | null | ['transparent-objects', 'visual-object-tracking'] | ['computer-vision', 'computer-vision'] | [ 1.36989981e-01 -9.18855071e-02 2.45114695e-03 -1.93070158e-01
-4.76390541e-01 -1.02172506e+00 6.57119155e-01 -2.22252190e-01
-2.41699785e-01 5.45693457e-01 2.55659539e-02 -2.16478571e-01
3.66579324e-01 -2.13404506e-01 -8.57791424e-01 -5.84829271e-01
-2.86755443e-01 5.74555039e-01 7.63325512e-01 1.50264129e-01
-2.60570377e-01 3.80053222e-01 -1.63410091e+00 4.18127984e-01
4.78939056e-01 1.25041533e+00 -4.61648032e-02 9.10894632e-01
-6.47114292e-02 8.14091861e-01 -6.54344082e-01 -6.61151111e-01
5.59090972e-01 1.70515597e-01 -4.80843037e-01 8.10790155e-03
1.43703640e+00 -4.94111925e-01 -1.95369154e-01 6.89465642e-01
3.97693872e-01 -7.28163645e-02 5.85632503e-01 -1.38499987e+00
-8.68502975e-01 1.86577246e-01 -4.65530545e-01 4.44931328e-01
8.76682252e-02 6.71839774e-01 7.16033041e-01 -6.66848004e-01
8.35645437e-01 1.13595414e+00 1.05185115e+00 9.14586782e-01
-1.28989410e+00 -8.28021228e-01 4.53446925e-01 -2.96451747e-01
-7.93898702e-01 -6.56128466e-01 2.03326419e-01 -9.49624479e-01
7.59534776e-01 5.57250142e-01 9.24461365e-01 1.41053247e+00
1.18977487e-01 8.01395237e-01 1.13189173e+00 -2.53324844e-02
-2.44634002e-02 2.88736850e-01 1.53424710e-01 6.91296637e-01
5.39595008e-01 5.24978817e-01 -4.90343362e-01 -2.12447435e-01
6.13839388e-01 -3.29288721e-01 -2.07370877e-01 -8.90758455e-01
-1.28693664e+00 4.28959250e-01 4.23757553e-01 -2.97525436e-01
8.39569867e-02 6.93298042e-01 5.81137598e-01 6.98509514e-02
5.61816871e-01 2.67728031e-01 -5.16693830e-01 -2.55827934e-01
-8.31645072e-01 2.71859825e-01 5.96459448e-01 1.27420640e+00
3.27576220e-01 4.54758912e-01 -4.97260958e-01 2.99478322e-01
5.24080396e-01 8.35124195e-01 -6.66936487e-02 -1.05020058e+00
4.08604234e-01 4.39443737e-01 4.38595921e-01 -3.69328618e-01
-2.88712233e-01 -3.60019386e-01 7.50302225e-02 7.21796393e-01
8.05437446e-01 -1.40671059e-01 -1.02507138e+00 1.59952271e+00
7.59740233e-01 1.95534021e-01 -2.62476653e-01 9.66320217e-01
1.13763845e+00 1.92168891e-01 4.38057512e-01 2.80639678e-01
1.45300901e+00 -8.89113843e-01 -3.78442049e-01 -1.24621369e-01
5.94310760e-01 -9.14188743e-01 1.05687666e+00 3.56418163e-01
-9.21076655e-01 -5.24817824e-01 -9.45980906e-01 -6.74802661e-02
-3.13178629e-01 6.67516589e-02 9.98184979e-01 1.21918356e+00
-1.18335569e+00 3.07212323e-01 -8.79825771e-01 -4.44159776e-01
8.71822834e-01 4.60508168e-01 -2.01710150e-01 3.16080809e-01
-5.87795079e-01 8.98082793e-01 5.49737550e-02 -9.60272271e-03
-1.30193925e+00 -1.36281145e+00 -4.14914012e-01 -4.17769849e-01
4.03705448e-01 -7.82103717e-01 1.38464773e+00 -7.77747393e-01
-1.23001063e+00 1.12926364e+00 1.91688418e-01 -4.39357907e-01
1.14613223e+00 -5.59677303e-01 -4.52315152e-01 6.27736151e-02
-6.16223179e-02 7.00434566e-01 1.11961031e+00 -1.53759980e+00
-5.23263872e-01 -1.08906135e-01 2.12627262e-01 -1.89148977e-01
-3.74770820e-01 4.61867303e-01 -6.08661115e-01 -5.69477975e-01
-6.66934967e-01 -1.22321987e+00 1.00678578e-01 7.50831902e-01
-3.74571770e-01 6.12348318e-02 1.29998541e+00 -4.42707926e-01
5.22248328e-01 -2.02831054e+00 -4.28358674e-01 -3.32058668e-01
7.09380269e-01 6.32155538e-01 -1.21298291e-01 5.57003506e-02
2.10335776e-02 -1.34557545e-01 6.59873039e-02 -5.25359273e-01
1.97818562e-01 -7.43158087e-02 -5.08644998e-01 6.86572254e-01
1.58797055e-01 1.10075581e+00 -8.99519205e-01 -8.11219394e-01
4.46437657e-01 6.01317048e-01 -4.15776283e-01 -1.16456337e-01
-6.05807662e-01 5.34258723e-01 -5.24994254e-01 8.82193625e-01
7.30184376e-01 -3.70121777e-01 -2.13675275e-01 -1.63805008e-01
-3.20324987e-01 -4.56493013e-02 -8.06742907e-01 1.36476231e+00
-1.46549493e-01 1.20898294e+00 7.74020702e-02 -6.13033250e-02
6.00272954e-01 2.99155951e-01 7.73307502e-01 -5.03135443e-01
2.51514822e-01 -1.72673374e-01 4.28896323e-02 -3.29570085e-01
6.64530277e-01 2.22918332e-01 2.78791159e-01 4.24896747e-01
-2.33477995e-01 1.68795973e-01 1.42022386e-01 2.38811105e-01
1.18884289e+00 7.70818472e-01 -4.34869230e-01 -3.21890414e-01
-1.69593588e-01 3.56664211e-01 4.51592356e-01 9.23588634e-01
-5.54584563e-01 7.34023273e-01 -3.53816751e-04 -8.53174984e-01
-1.15059900e+00 -1.37074876e+00 -5.01729369e-01 1.24751294e+00
2.82548934e-01 -3.52940440e-01 -6.05017841e-01 -7.41276622e-01
4.47929829e-01 2.36175925e-01 -8.81893158e-01 4.57426086e-02
-6.45943284e-01 -6.37301803e-01 6.14998639e-01 7.53051460e-01
3.48507226e-01 -1.05148852e+00 -1.04713106e+00 1.60967007e-01
3.51405799e-01 -1.43940961e+00 -4.49303657e-01 6.78963885e-02
-8.67370605e-01 -1.23126125e+00 -7.16959834e-01 -1.80633724e-01
2.81643569e-01 3.08482558e-01 1.50016844e+00 1.70856491e-01
-5.43048024e-01 7.08496392e-01 -1.80497512e-01 -6.00260913e-01
-4.61463630e-01 -1.62520021e-01 2.92477340e-01 -2.14798629e-01
4.35318761e-02 -1.54435456e-01 -7.67472208e-01 3.44256133e-01
-4.30067450e-01 5.10821901e-02 2.70879984e-01 5.75669296e-02
1.75079226e-01 -7.64469743e-01 9.49207507e-03 -9.98812556e-01
-1.75828397e-01 -1.81209102e-01 -1.14777875e+00 2.67949522e-01
-1.93153337e-01 -2.23405883e-01 2.47104719e-01 -8.12806010e-01
-1.11456907e+00 1.68166503e-01 3.62886667e-01 -6.73777521e-01
5.75329252e-02 -4.49631870e-01 9.27898958e-02 -6.71610057e-01
6.85815752e-01 -2.06571504e-01 -4.23670381e-01 -4.84141529e-01
4.36489910e-01 1.71064362e-01 6.29096270e-01 -7.85019159e-01
1.20315826e+00 9.38532352e-01 -2.66443789e-01 -5.81368566e-01
-7.61260688e-01 -2.91708589e-01 -4.23762023e-01 -6.79562211e-01
9.91044760e-01 -9.72121716e-01 -1.28595734e+00 3.11646372e-01
-8.85585308e-01 -7.31949151e-01 -5.32439828e-01 5.00734270e-01
-4.88976061e-01 3.46876949e-01 -4.70498651e-01 -8.88287067e-01
-2.86927581e-01 -1.12682486e+00 1.21609712e+00 1.25005335e-01
-3.23808819e-01 -7.70546556e-01 2.50563741e-01 3.70947957e-01
4.72350270e-01 4.21253800e-01 4.33357269e-01 -2.20922172e-01
-1.31238186e+00 -1.33329049e-01 -4.42648351e-01 -5.39849661e-02
-1.31290564e-02 4.96833116e-01 -1.42077577e+00 -4.99455631e-01
-5.40677845e-01 -4.14629281e-01 9.65679526e-01 3.44258279e-01
9.59549129e-01 6.10376038e-02 -7.17120230e-01 8.41809869e-01
1.19638669e+00 -4.92145270e-02 3.01586270e-01 4.65735078e-01
1.06443083e+00 2.85237223e-01 3.58869970e-01 2.63067514e-01
1.35142133e-01 1.04714847e+00 6.91182852e-01 -1.95707604e-01
-7.27521837e-01 5.36626801e-02 3.27589124e-01 2.29610980e-01
-2.31045932e-01 -2.81632602e-01 -9.23552692e-01 3.99582863e-01
-1.54282475e+00 -9.55660880e-01 -5.19726098e-01 2.17365885e+00
7.32064843e-01 3.49925339e-01 3.05511057e-01 -4.92310643e-01
4.83891606e-01 1.44655257e-01 -7.32228994e-01 -1.81157872e-01
-1.66677888e-02 -5.54438643e-02 7.60534644e-01 2.34440476e-01
-1.39783716e+00 8.65658104e-01 7.51109028e+00 4.57359880e-01
-1.08451939e+00 1.94353059e-01 6.75164610e-02 -4.14756626e-01
-2.56262094e-01 1.27669320e-01 -1.20555675e+00 6.19715750e-01
7.21121430e-01 1.88688606e-01 2.17975061e-02 8.60180259e-01
-7.54685402e-02 -6.74483180e-02 -1.27869523e+00 7.89669871e-01
-2.74791062e-01 -1.26282489e+00 -1.36265472e-01 2.82457948e-01
7.76742995e-01 4.22978401e-01 6.21615767e-01 2.91554838e-01
8.16298842e-01 -8.19203615e-01 1.18428731e+00 4.28359270e-01
7.26537168e-01 3.68784480e-02 -8.75974670e-02 -1.15942299e-01
-1.53041899e+00 1.09920323e-01 -3.16676110e-01 2.38563925e-01
4.41976786e-02 2.49476135e-01 -7.49001324e-01 2.14560226e-01
1.17307067e+00 6.79724276e-01 -9.18524027e-01 1.60324585e+00
3.14750493e-01 8.06583583e-01 -4.91001159e-01 1.25964925e-01
1.93583637e-01 5.56672849e-02 7.01035380e-01 1.28566968e+00
-1.37953475e-01 -4.36081856e-01 1.96577609e-01 9.66261148e-01
-7.76909068e-02 -3.06250125e-01 -4.42554504e-01 3.81029285e-02
3.14257860e-01 1.38994491e+00 -9.27952588e-01 -4.70861465e-01
-6.27496541e-01 4.76945490e-01 3.15554887e-01 4.41254735e-01
-1.29596865e+00 3.21476281e-01 9.38431561e-01 2.03562081e-01
3.56932819e-01 -1.78553835e-01 -2.24425972e-01 -1.07768786e+00
1.53253257e-01 -6.47434056e-01 2.04796791e-01 -8.97503674e-01
-1.22502208e+00 6.27847433e-01 3.11389565e-03 -1.44499362e+00
2.99897552e-01 -8.01132202e-01 -2.24147886e-01 7.58784235e-01
-1.40983915e+00 -1.37656391e+00 -6.15988672e-01 2.89229035e-01
2.93258905e-01 -3.85985151e-02 5.78915715e-01 5.41564286e-01
-3.05169284e-01 6.19754612e-01 2.99372315e-01 1.34302258e-01
8.66518319e-01 -1.21021938e+00 8.46377969e-01 5.99456847e-01
2.47177929e-01 5.90586782e-01 9.02441323e-01 -7.39393055e-01
-1.44280767e+00 -1.13756645e+00 6.24938384e-02 -1.63832641e+00
6.62571251e-01 -8.50937605e-01 -8.40040743e-01 1.06089497e+00
6.30592406e-02 5.79310536e-01 4.01284516e-01 8.58139768e-02
-7.04155862e-01 3.21703665e-02 -8.99336040e-01 7.07836449e-01
1.36455476e+00 -3.00567269e-01 -2.32595578e-01 4.31692302e-01
7.65907884e-01 -8.62017274e-01 -7.98109412e-01 5.39921403e-01
9.55094934e-01 -9.02405262e-01 1.31059909e+00 -7.01543450e-01
2.38900874e-02 -4.06433523e-01 4.84650843e-02 -6.69035196e-01
-1.59747601e-01 -5.99605083e-01 -4.67152417e-01 1.33294058e+00
2.24598661e-01 -5.09341061e-01 1.29074407e+00 9.19281304e-01
-4.81381416e-01 -4.34839934e-01 -8.31446826e-01 -1.01414454e+00
-1.23168185e-01 -4.54080403e-01 4.82664615e-01 7.28303373e-01
-8.64181578e-01 -3.85895699e-01 -4.84099388e-01 1.15732126e-01
1.02044058e+00 3.57540399e-01 1.09232104e+00 -1.41932893e+00
-2.72226363e-01 -3.40855420e-01 -4.92269516e-01 -9.02731955e-01
-1.24900252e-01 -7.43882775e-01 -3.27013060e-02 -1.26345253e+00
4.24719006e-01 -1.06723905e+00 3.43634784e-02 5.22624254e-01
-2.68815279e-01 8.00587296e-01 4.64529335e-01 3.43879670e-01
-1.05662584e+00 6.09914541e-01 1.46925771e+00 -2.31574714e-01
1.17113248e-01 6.91336244e-02 -3.36879551e-01 7.20809162e-01
4.25586700e-01 -5.87022185e-01 -2.36687660e-01 -7.42257059e-01
3.40878330e-02 -4.17019725e-01 7.84927666e-01 -1.32615840e+00
-9.13625509e-02 4.79463562e-02 8.69940698e-01 -7.02114463e-01
7.62726307e-01 -1.05395758e+00 4.47376251e-01 3.60311061e-01
-1.41580686e-01 4.37803939e-02 6.85410440e-01 5.77657282e-01
4.79180336e-01 1.58431351e-01 7.40751624e-01 -1.30765792e-02
-8.93999279e-01 6.18740678e-01 -1.86910897e-01 4.81240630e-01
1.10263550e+00 -7.32905746e-01 -7.32376099e-01 1.35164484e-01
-5.82849979e-01 1.87414318e-01 9.01876092e-01 7.18569338e-01
1.40023649e-01 -1.24640381e+00 -5.58988273e-01 -2.31451809e-01
3.02886426e-01 -3.35975498e-01 1.36705250e-01 6.05537176e-01
-6.28088892e-01 2.91849554e-01 -3.46738845e-01 -9.04803336e-01
-1.50762975e+00 7.08662510e-01 3.32989335e-01 1.40149668e-01
-1.18911064e+00 9.66893911e-01 5.73791444e-01 -1.90921977e-01
2.94883907e-01 -3.82761985e-01 1.99285299e-01 -2.50662893e-01
3.97953629e-01 3.53859544e-01 8.04764852e-02 -6.82892025e-01
-5.56421340e-01 6.07411265e-01 -1.64223656e-01 1.58974648e-01
1.00159168e+00 1.67856827e-01 4.74983722e-01 3.66039991e-01
9.02050853e-01 7.80196786e-02 -2.02276850e+00 -1.32937148e-01
6.52244985e-02 -5.95972657e-01 -2.86904722e-01 -6.78554595e-01
-1.27447307e+00 7.56407857e-01 1.00916278e+00 6.32666945e-02
4.16209042e-01 1.31515279e-01 6.28961861e-01 7.24943578e-02
4.09830749e-01 -7.19368458e-01 1.86557680e-01 2.64115602e-01
4.14179415e-01 -1.29917383e+00 1.63488090e-01 -5.74100733e-01
-4.22228694e-01 6.70697331e-01 1.00589383e+00 3.18598887e-03
2.09909633e-01 7.86285698e-01 5.19911468e-01 -3.79234910e-01
-7.17315733e-01 -2.07106680e-01 2.69596666e-01 1.10194457e+00
4.83320475e-01 -1.05261385e-01 4.89569157e-01 -6.93849921e-02
-2.69192487e-01 -3.76772806e-02 1.50429234e-01 9.72245932e-01
-2.29454309e-01 -8.20889413e-01 -5.63649356e-01 3.96067709e-01
-4.46211308e-01 -2.45229434e-02 -3.69811207e-01 1.01432729e+00
7.22937137e-02 6.97178900e-01 8.87064934e-02 9.64866281e-02
1.39117107e-01 -2.24426150e-01 8.76620770e-01 -5.34204721e-01
-9.21236396e-01 -3.31166536e-01 9.54498798e-02 -7.08966494e-01
-4.39114839e-01 -7.58960485e-01 -9.73544538e-01 -3.31826478e-01
-2.54857749e-01 -1.98424727e-01 6.50020659e-01 5.01076877e-01
1.64194942e-01 7.67041087e-01 -1.84676513e-01 -1.17080188e+00
-3.30850065e-01 -5.90265334e-01 -2.19116688e-01 3.54879349e-01
6.73501492e-01 -1.03315783e+00 1.84291508e-02 2.99083859e-01] | [6.362607955932617, -2.0277228355407715] |
d71e91c1-da63-4c87-ae28-b7586613e4d4 | variational-quantum-circuits-for-quantum | 1912.07286 | null | https://arxiv.org/abs/1912.07286v2 | https://arxiv.org/pdf/1912.07286v2.pdf | Variational Quantum Circuits for Quantum State Tomography | Quantum state tomography is a key process in most quantum experiments. In this work, we employ quantum machine learning for state tomography. Given an unknown quantum state, it can be learned by maximizing the fidelity between the output of a variational quantum circuit and this state. The number of parameters of the variational quantum circuit grows linearly with the number of qubits and the circuit depth, so that only polynomial measurements are required, even for highly-entangled states. After that, a subsequent classical circuit simulator is used to transform the information of the target quantum state from the variational quantum circuit into a familiar format. We demonstrate our method by performing numerical simulations for the tomography of the ground state of a one-dimensional quantum spin chain, using a variational quantum circuit simulator. Our method is suitable for near-term quantum computing platforms, and could be used for relatively large-scale quantum state tomography for experimentally relevant quantum states. | ['He-Liang Huang', 'Anqi Huang', 'Xiang Fu', 'Junjie Wu', 'Xuejun Yang', 'Shichuan Xue', 'Xiaogang Qiang', 'Ping Xu', 'Yong Liu', 'Mingtang Deng', 'Dongyang Wang', 'Chu Guo'] | 2019-12-16 | null | null | null | null | ['quantum-state-tomography'] | ['medical'] | [ 4.53794956e-01 -4.95212190e-02 -3.46607082e-02 -1.08399428e-01
-7.99350381e-01 -7.22623110e-01 3.11623931e-01 7.50426948e-02
-5.14842093e-01 7.90772259e-01 -4.43756193e-01 -7.87908494e-01
1.33779868e-01 -1.20460498e+00 -6.85471952e-01 -1.00069284e+00
-5.96488453e-02 6.34943604e-01 -8.99009481e-02 -2.78669089e-01
5.60974836e-01 4.76747036e-01 -8.20913434e-01 1.53059676e-01
4.06376958e-01 4.86250311e-01 -1.00735344e-01 8.74796093e-01
3.02724093e-01 5.47052741e-01 -9.50542018e-02 -7.07233027e-02
2.24636436e-01 -9.43538606e-01 -1.20974946e+00 -2.29916483e-01
-7.68844187e-02 -3.78620386e-01 -1.15057707e+00 1.63182938e+00
2.03341842e-01 2.02696487e-01 5.86220264e-01 -6.42697811e-01
-1.39358178e-01 5.80025494e-01 1.79998785e-01 1.51073352e-01
3.25291455e-01 4.90506768e-01 1.37873602e+00 -3.14260632e-01
6.32594347e-01 9.21207130e-01 1.07377931e-01 5.31641006e-01
-2.01766014e+00 -7.18056500e-01 -9.90978956e-01 4.87258196e-01
-1.63145459e+00 -5.52242160e-01 6.63036764e-01 -2.67052799e-01
1.28799152e+00 -2.69714028e-01 7.88078666e-01 4.69321162e-01
6.34578824e-01 -4.03509662e-02 1.48271084e+00 -8.50541592e-01
5.75715244e-01 2.28887334e-01 2.12446272e-01 1.12317801e+00
8.45397860e-02 8.53695035e-01 -3.68276536e-01 -4.41740334e-01
7.68196583e-01 -1.78934216e-01 -7.52868056e-02 -4.88251150e-01
-1.33023429e+00 1.02888870e+00 5.22781610e-01 2.04854697e-01
-2.35845581e-01 6.34782553e-01 1.35574192e-01 6.87292099e-01
-3.51811558e-01 6.43153727e-01 -1.58908531e-01 -2.03353539e-01
-8.80995452e-01 2.04894722e-01 1.04919100e+00 5.93512714e-01
1.46936941e+00 -3.34636152e-01 1.40502408e-01 -1.63315579e-01
2.66930550e-01 9.19841290e-01 -3.59141409e-01 -1.39588106e+00
-6.83904290e-02 -6.84501603e-03 2.23454013e-01 -2.07096457e-01
-1.24727689e-01 3.83316845e-01 -8.75767469e-01 4.52393107e-02
4.07264411e-01 -2.72721231e-01 -7.53551483e-01 1.56141973e+00
1.67394966e-01 2.66625762e-01 2.36128554e-01 7.82177806e-01
3.51447850e-01 9.71397102e-01 -4.45279926e-01 -4.55195814e-01
1.13404214e+00 -4.35686558e-01 -5.03890038e-01 -1.08685479e-01
9.89396393e-01 -6.27827764e-01 3.97879958e-01 2.09463805e-01
-1.07763028e+00 -3.84855658e-01 -1.16376698e+00 -2.51893792e-02
-3.07651944e-02 -5.26280046e-01 8.44893336e-01 9.51969862e-01
-9.90985930e-01 1.40979373e+00 -1.11588466e+00 -1.18612535e-01
-9.97133926e-03 6.88691258e-01 -4.60493684e-01 -3.80950242e-01
-1.23716927e+00 8.90696049e-01 7.89025426e-01 9.88174751e-02
-1.01716447e+00 -1.58358470e-01 -5.84926903e-01 1.07198991e-01
1.57222137e-01 -8.72071922e-01 1.17800355e+00 -9.28448215e-02
-1.94917655e+00 7.95855939e-01 -5.45068383e-01 -1.53500706e-01
-3.82492244e-01 6.72495842e-01 -2.91011810e-01 2.19119176e-01
-1.79721624e-01 5.66394664e-02 4.80899930e-01 -6.21887624e-01
6.74911514e-02 -4.33778405e-01 2.55114734e-01 -2.21606344e-01
4.84175801e-01 -3.03656429e-01 2.54738498e-02 8.62583816e-01
8.18661869e-01 -1.48475397e+00 -5.42205453e-01 -6.01295590e-01
-5.78463912e-01 3.71136405e-02 2.50301421e-01 2.39670262e-01
7.72806048e-01 -2.10915422e+00 4.63864356e-01 5.73438883e-01
2.23451674e-01 -6.23705890e-03 2.12036874e-02 8.35141063e-01
-6.27490655e-02 -1.10495232e-01 -2.28519171e-01 -1.94835544e-01
6.44511729e-02 3.83952439e-01 -1.68254837e-01 7.91946173e-01
4.34977338e-02 1.04549146e+00 -9.86298084e-01 -2.75639087e-01
2.19070733e-01 1.16665922e-01 -1.06230986e+00 1.97805777e-01
4.24393974e-02 9.63935494e-01 -5.84754229e-01 1.11680798e-01
7.00369120e-01 -6.10047340e-01 6.26286268e-01 -2.76619583e-01
-2.56482720e-01 8.07111442e-01 -1.29910481e+00 1.76743007e+00
-1.88433066e-01 4.10899639e-01 6.27886131e-02 -1.10199833e+00
4.40847278e-01 4.21163142e-01 3.02566200e-01 -6.95806265e-01
5.61590075e-01 4.92185980e-01 4.61045802e-01 -4.57963467e-01
6.63372636e-01 -9.25226510e-01 -3.97969127e-01 8.83155286e-01
4.38223392e-01 -9.43951607e-01 2.68514276e-01 5.35896420e-01
1.09972119e+00 -2.63028145e-01 3.86852205e-01 -2.34065697e-01
4.63216543e-01 3.08412034e-02 2.33874708e-01 1.06737506e+00
-3.91763508e-01 1.10851899e-02 7.11390018e-01 -1.55220583e-01
-1.54186237e+00 -1.29215765e+00 -4.50152367e-01 3.60758364e-01
5.19541383e-01 -7.09259272e-01 -6.50388718e-01 4.73094918e-03
-2.80532002e-01 6.86520219e-01 -1.38953745e-01 -4.60296035e-01
-2.93232292e-01 -7.04477131e-01 3.83850276e-01 -1.01449259e-01
2.74534196e-01 -1.02543545e+00 7.97065720e-02 3.25723380e-01
4.87976559e-02 -1.11029494e+00 -5.82024381e-02 5.44898689e-01
-1.08118129e+00 -1.02488089e+00 2.39612639e-01 -5.11418402e-01
6.20128632e-01 -1.73991006e-02 7.83158600e-01 -8.15944970e-02
-2.63777941e-01 -2.75500361e-02 1.43538713e-01 3.58646631e-01
-1.04971302e+00 -1.77191004e-01 3.19339603e-01 -2.34966546e-01
5.84550917e-01 -4.91190255e-01 -4.27657485e-01 -3.83661568e-01
-6.69386744e-01 -1.18073247e-01 4.03419167e-01 1.12171900e+00
6.68227136e-01 3.58071506e-01 -2.22802222e-01 -9.74591851e-01
2.80960917e-01 -2.61491358e-01 -1.15276504e+00 -1.10083230e-01
-4.52070802e-01 7.04412997e-01 6.31339252e-01 6.71699345e-02
-6.94723487e-01 1.33288518e-01 -9.46348235e-02 1.59905329e-01
-7.13884234e-02 5.23590744e-01 3.00246716e-01 -4.30399865e-01
7.55718112e-01 4.93635237e-01 -6.82478398e-02 -1.55840725e-01
5.77155292e-01 6.58407211e-01 3.28598559e-01 -7.50160456e-01
1.14335763e+00 3.67513150e-01 8.75586510e-01 -7.94518650e-01
-8.10561478e-01 -3.65368068e-01 -1.20996428e+00 4.04506505e-01
8.10571134e-01 -6.61878467e-01 -1.37900019e+00 3.90778124e-01
-1.19442701e+00 -2.27238879e-01 -7.43322596e-02 8.68196666e-01
-6.53445780e-01 5.86222947e-01 -1.09645998e+00 -9.24079120e-01
-7.74872601e-02 -1.48953032e+00 8.41596127e-01 3.30495894e-01
2.41336375e-01 -1.09623897e+00 5.23543596e-01 2.52719492e-01
2.97369272e-01 -2.64464647e-01 1.18175137e+00 6.74667805e-02
-1.36817658e+00 -4.31562811e-01 -2.12304130e-01 3.26862574e-01
-2.51472533e-01 -2.59293586e-01 -7.96078026e-01 -7.27758765e-01
-4.42385264e-02 -7.19788015e-01 8.12853456e-01 -3.00642140e-02
6.62972450e-01 1.26058042e-01 -3.30258161e-01 5.81306100e-01
1.56449747e+00 -5.07521490e-03 6.51736379e-01 -2.39010230e-01
6.26278639e-01 -1.51247486e-01 2.10214383e-03 1.28599361e-01
1.78121030e-01 3.68682176e-01 3.18353362e-02 4.65091676e-01
5.31506002e-01 -2.41830736e-01 4.59578544e-01 1.26684868e+00
-8.60533714e-02 2.28503123e-01 -5.80137074e-01 2.87736394e-02
-1.26499081e+00 -1.20669866e+00 -3.45139176e-01 2.46663404e+00
9.21024203e-01 1.25786200e-01 -4.09430921e-01 1.18518569e-01
4.02074873e-01 9.97471586e-02 -4.36395794e-01 -6.79444313e-01
2.80222446e-01 1.00581861e+00 6.15009904e-01 7.66315758e-01
-8.03724170e-01 1.14491951e+00 7.32324266e+00 3.52103919e-01
-1.04167926e+00 3.08631152e-01 -1.90189660e-01 2.63860822e-02
-2.48402804e-01 9.93269265e-01 -4.93125498e-01 2.16672450e-01
1.50438678e+00 -2.64322132e-01 1.25415766e+00 3.08395863e-01
-7.60689378e-02 -3.73746306e-01 -1.47296500e+00 1.06623161e+00
-6.67274415e-01 -1.53161621e+00 -3.92002583e-01 3.88291508e-01
9.68689144e-01 4.29029018e-01 -1.89290553e-01 6.29236698e-01
1.02964358e-03 -9.26407039e-01 1.61409110e-01 3.32928926e-01
9.44962919e-01 -6.74430549e-01 6.65670335e-01 5.58907330e-01
-8.27228248e-01 1.45836219e-01 -6.42503381e-01 -4.52308357e-01
3.65783691e-01 4.05866265e-01 -6.35791183e-01 2.35985175e-01
-8.79165996e-03 2.38426626e-01 -2.13712882e-02 6.10977530e-01
-1.74142614e-01 7.99065113e-01 -4.75365311e-01 -2.00043097e-01
3.45500827e-01 -8.94358456e-01 3.18069845e-01 6.44538105e-01
2.56454855e-01 6.64573312e-01 1.45512044e-01 1.35611379e+00
-3.59375536e-01 -2.46466666e-01 -6.86145306e-01 -5.80165327e-01
5.38760960e-01 1.15012646e+00 -3.53219956e-01 -5.65197289e-01
-2.39564583e-01 1.08599031e+00 3.00592363e-01 3.25952828e-01
-4.26868826e-01 -4.80562329e-01 4.05794173e-01 -2.36385286e-01
1.84277445e-01 -5.69856942e-01 1.90087572e-01 -1.58890176e+00
-3.70766222e-01 -5.37471950e-01 -1.31753758e-01 -3.77178371e-01
-8.43815684e-01 2.06139684e-01 -2.26174518e-01 -7.49190211e-01
-3.58324170e-01 -6.89263761e-01 -5.91302216e-01 1.19999468e+00
-1.36505485e+00 -4.17126685e-01 2.55299300e-01 5.11634052e-01
-7.72873163e-01 7.70061463e-02 1.46024525e+00 6.00716546e-02
-7.12113857e-01 2.38506198e-01 7.18919277e-01 1.15167081e-01
2.72666335e-01 -1.25949538e+00 4.67047751e-01 7.23926127e-01
2.62371629e-01 1.02562308e+00 8.36073399e-01 -2.58479089e-01
-2.21410894e+00 -6.09586358e-01 8.08486462e-01 -3.51813555e-01
9.55122292e-01 -4.19895649e-01 -8.24117005e-01 8.00243318e-01
4.50057983e-02 3.98762405e-01 6.70603991e-01 2.55966842e-01
-3.85444432e-01 1.76452920e-01 -1.10756707e+00 2.13998705e-01
6.57770038e-01 -1.70476246e+00 -4.15230989e-01 7.03028977e-01
3.44534993e-01 -3.92809749e-01 -1.17320514e+00 -1.19367287e-01
5.18485665e-01 -8.68899286e-01 5.86678267e-01 -6.81341290e-01
6.21966645e-02 -4.26988453e-01 -3.20776969e-01 -1.20998204e+00
-6.23628378e-01 -9.89460826e-01 -1.65370956e-01 1.90007463e-01
4.21314478e-01 -6.42636776e-01 9.98190343e-01 4.83481228e-01
2.68667161e-01 -5.25467061e-02 -1.07199395e+00 -5.65088332e-01
4.58673507e-01 -2.66028970e-01 2.80559212e-01 6.71275675e-01
5.21546900e-01 7.87778080e-01 -2.94489920e-01 5.52040637e-01
9.92592156e-01 4.83625054e-01 7.46684790e-01 -9.11931813e-01
-8.02992344e-01 -1.90611228e-01 -6.06285334e-01 -1.20912766e+00
2.23362431e-01 -1.30427742e+00 1.16857298e-01 -8.18742275e-01
6.98594987e-01 -1.84494212e-01 -3.77462238e-01 -1.58925340e-01
-1.15511492e-01 3.81998301e-01 1.17463514e-01 1.99946344e-01
-6.11663163e-01 5.50484359e-01 1.34338641e+00 -1.08697772e-01
-1.01108171e-01 6.48239022e-03 -1.14448935e-01 3.20339531e-01
6.25651479e-01 -8.66861343e-01 1.19903266e-01 8.06154758e-02
3.30731064e-01 6.44735813e-01 3.92889798e-01 -8.86316776e-01
3.98435295e-01 -1.80193380e-01 -1.63694650e-01 -4.63710904e-01
6.99568093e-01 -1.74050480e-01 1.82012618e-01 7.92569339e-01
-5.50457649e-02 -5.76097965e-01 -2.57680476e-01 4.92408723e-01
-9.82835814e-02 -5.15836596e-01 1.26805639e+00 -1.95291594e-01
-4.94527608e-01 3.70376170e-01 -4.66278791e-01 -2.71891356e-01
6.13508821e-01 2.88047343e-01 -1.42375141e-01 -1.68093830e-01
-8.46009135e-01 -2.54541457e-01 7.55952179e-01 -4.85979944e-01
2.82809466e-01 -1.33278227e+00 -3.20513070e-01 6.61287665e-01
2.03297615e-01 -3.64745766e-01 4.51377153e-01 8.76534998e-01
-6.89248919e-01 7.95632303e-01 7.51343369e-03 -6.71488822e-01
-6.81860268e-01 5.64169884e-01 5.93978643e-01 -1.87322557e-01
-2.93742657e-01 5.14613211e-01 -2.20816970e-01 -6.14235580e-01
-6.06904030e-01 -1.97219223e-01 5.70167780e-01 -7.04932690e-01
5.52659214e-01 1.50512531e-01 -1.49392724e-01 -9.35284793e-01
-1.51775196e-01 4.23514426e-01 -6.97081536e-03 -3.39298636e-01
8.54548275e-01 -4.14626785e-02 -7.09577501e-01 5.99568248e-01
1.69912040e+00 -2.20149800e-01 -8.26785266e-01 -7.13405788e-01
-2.77926415e-01 -1.78566188e-01 4.59053963e-01 -5.05645908e-02
-6.22421145e-01 1.14260983e+00 6.08879149e-01 2.51682997e-01
3.75131816e-01 1.98426396e-01 9.91317987e-01 1.30635226e+00
1.15649402e+00 -8.82335246e-01 -3.36597979e-01 8.36717486e-01
-3.20375144e-01 -1.41811740e+00 2.84841452e-02 6.43250123e-02
1.51665816e-02 1.23110867e+00 -1.98148951e-01 -2.63719141e-01
7.19326794e-01 -5.30455932e-02 -3.81785601e-01 -5.14135182e-01
-6.32936478e-01 -9.68159810e-02 7.92928264e-02 1.77027956e-01
2.45314166e-01 6.21334612e-01 1.86574906e-01 -2.04090640e-01
-2.91396976e-01 -7.45919812e-03 1.04059803e+00 9.05737281e-01
-6.81612194e-01 -1.59575915e+00 -3.27970177e-01 2.57731318e-01
-1.90994352e-01 -3.05875510e-01 1.14973247e-01 1.82655334e-01
-1.47126064e-01 1.07669854e+00 -2.73963157e-02 -3.86518747e-01
1.82924762e-01 3.59911263e-01 1.32582426e+00 -1.02130580e+00
4.58372869e-02 -3.33647996e-01 -2.02892497e-01 -9.12591934e-01
-2.62284487e-01 -6.90117538e-01 -1.48057401e+00 -1.20700037e+00
-6.66087627e-01 5.30955434e-01 7.17280209e-01 1.26470590e+00
1.69567168e-01 5.14062382e-02 8.72139633e-01 -7.96765387e-01
-8.70742559e-01 -8.76499593e-01 -1.12305152e+00 2.17325553e-01
4.65354383e-01 -3.84840727e-01 -3.70014876e-01 -2.21558109e-01] | [5.6367106437683105, 4.869591236114502] |
ce7373db-c763-42f5-87f5-dc3f4b4a8582 | incremental-loop-closure-verification-by | 1509.07611 | null | http://arxiv.org/abs/1509.07611v1 | http://arxiv.org/pdf/1509.07611v1.pdf | Incremental Loop Closure Verification by Guided Sampling | Loop closure detection, the task of identifying locations revisited by a
robot in a sequence of odometry and perceptual observations, is typically
formulated as a combination of two subtasks: (1) bag-of-words image retrieval
and (2) post-verification using RANSAC geometric verification. The main
contribution of this study is the proposal of a novel post-verification
framework that achieves good precision recall trade-off in loop closure
detection. This study is motivated by the fact that not all loop closure
hypotheses are equally plausible (e.g., owing to mutual consistency between
loop closure constraints) and that if we have evidence that one hypothesis is
more plausible than the others, then it should be verified more frequently. We
demonstrate that the problem of loop closure detection can be viewed as an
instance of a multi-model hypothesize-and-verify framework and build guided
sampling strategies on the framework where loop closures proposed using image
retrieval are verified in a planned order (rather than in a conventional
uniform order) to operate in a constant time. Experimental results using a
stereo SLAM system confirm that the proposed strategy, the use of loop closure
constraints and robot trajectory hypotheses as a guide, achieves promising
results despite the fact that there exists a significant number of false
positive constraints and hypotheses. | ['Kanji Tanaka'] | 2015-09-25 | null | null | null | null | ['loop-closure-detection'] | ['computer-vision'] | [ 2.82269210e-01 1.00010149e-01 -1.60102308e-01 -2.64349520e-01
-6.73428297e-01 -5.58657527e-01 9.40832615e-01 4.85300332e-01
-4.73373652e-01 6.09588385e-01 -1.48385227e-01 -3.64359140e-01
-4.61731225e-01 -5.67640305e-01 -8.32779586e-01 -4.83965456e-01
-2.04598442e-01 8.90503824e-01 5.20867646e-01 -3.14100325e-01
7.08000660e-01 8.11861396e-01 -1.94451451e+00 -3.88092458e-01
5.67774475e-01 7.49625146e-01 5.72250605e-01 6.72820449e-01
3.93276334e-01 7.48325288e-01 -1.98244542e-01 1.43071085e-01
3.87122661e-01 -2.96202004e-01 -1.02305043e+00 3.80402029e-01
5.97068608e-01 -2.93607682e-01 1.00263603e-01 1.33045709e+00
9.25702751e-02 3.22034448e-01 5.57870686e-01 -1.40046704e+00
-9.97274071e-02 -1.00115635e-01 -2.55731016e-01 -4.58835885e-02
8.86910081e-01 -5.02791926e-02 1.09380245e+00 -1.04259908e+00
8.14212203e-01 1.18790805e+00 5.01841664e-01 -1.56219333e-01
-1.26653731e+00 -3.86295021e-01 1.76569484e-02 1.91140279e-01
-1.64978445e+00 -3.87011737e-01 3.65418434e-01 -5.37240982e-01
9.63235259e-01 2.60485053e-01 4.98285055e-01 3.78743380e-01
6.13067865e-01 2.74003029e-01 9.36122119e-01 -7.41756618e-01
3.80924314e-01 3.70262742e-01 1.07398190e-01 1.00077391e+00
5.32510698e-01 4.08929557e-01 -5.75859308e-01 -2.30550960e-01
6.51839018e-01 2.11021560e-03 -3.16188425e-01 -1.11875427e+00
-1.40333831e+00 8.91406536e-01 4.26161230e-01 1.72053039e-01
-3.97149652e-01 -4.73194048e-02 2.32157886e-01 2.21641228e-01
2.33468190e-02 6.29072368e-01 -1.27130195e-01 2.07214355e-01
-7.81427801e-01 4.69970673e-01 7.40295053e-01 1.28288114e+00
1.19576538e+00 -5.05457520e-01 4.64140654e-01 3.05249512e-01
6.47095680e-01 5.81009269e-01 4.50705945e-01 -6.80837154e-01
2.22785801e-01 5.78022063e-01 4.76498336e-01 -1.19101667e+00
-4.34079558e-01 -3.98644246e-02 -3.37234586e-01 5.46394527e-01
1.50338635e-01 3.80019486e-01 -6.70935810e-01 1.43038142e+00
5.09106874e-01 -6.06012270e-02 1.88011229e-02 1.04469717e+00
2.25707829e-01 3.74953091e-01 -3.89797211e-01 -2.78461218e-01
1.29065812e+00 -8.11741173e-01 -6.99940026e-01 -2.35593215e-01
8.05494308e-01 -1.07316101e+00 5.46034575e-01 4.89043176e-01
-6.69811487e-01 -7.65369833e-01 -1.34485686e+00 4.77414876e-02
-4.94434595e-01 1.80687495e-02 3.64983797e-01 2.18083084e-01
-1.16170490e+00 4.02289957e-01 -5.17080843e-01 -9.96902585e-01
-6.07250690e-01 3.18115473e-01 -6.46423876e-01 5.02682589e-02
-8.62203419e-01 1.45100176e+00 7.28745341e-01 1.63534179e-01
-9.43516672e-01 2.11763501e-01 -1.22424483e+00 -4.41794157e-01
4.98441488e-01 -5.09126425e-01 1.11414135e+00 -5.73890448e-01
-1.02203166e+00 1.08544540e+00 -4.70021158e-01 -6.46125078e-01
7.07784295e-01 -2.68079221e-01 -2.16626212e-01 1.67874947e-01
3.42841446e-01 6.38918340e-01 8.46927524e-01 -1.64152062e+00
-1.00556862e+00 -4.11861122e-01 8.55922699e-02 4.14032698e-01
6.27045751e-01 -2.32913956e-01 -3.27295512e-01 7.70336539e-02
9.95744467e-01 -1.43918455e+00 -3.89866471e-01 5.92499459e-03
-4.51975942e-01 -1.16169237e-01 6.75991237e-01 -2.52170175e-01
9.75011647e-01 -1.83762813e+00 1.26674980e-01 5.69403887e-01
2.37751864e-02 -1.24197364e-01 2.20310301e-01 7.55471587e-01
-1.07532740e-01 -2.93339074e-01 -7.46403858e-02 -5.36751807e-01
-6.84889704e-02 4.21897590e-01 -5.82577229e-01 1.07616842e+00
-8.04626122e-02 2.21063539e-01 -1.05146301e+00 -5.91525555e-01
8.63380492e-01 -4.65416498e-02 -1.69405118e-01 1.14360284e-02
3.08154710e-02 4.45315689e-01 -2.68934369e-01 5.11044443e-01
6.46930456e-01 -4.87883203e-02 4.76970151e-02 -1.44612551e-01
-7.71938205e-01 3.96093547e-01 -1.71158969e+00 1.66580021e+00
-2.66826898e-01 6.27965808e-01 -1.84119910e-01 -8.13611746e-01
1.09701681e+00 1.28403485e-01 3.21474463e-01 -5.35663426e-01
3.25416438e-02 6.15241110e-01 -2.84337491e-01 -5.03522515e-01
1.24559033e+00 7.22704977e-02 -2.01239601e-01 2.21707806e-01
-5.43676428e-02 -4.90276694e-01 1.98086172e-01 8.00363272e-02
7.70937204e-01 3.44933659e-01 8.88680995e-01 -3.83748114e-01
6.42503977e-01 6.64691687e-01 3.55133057e-01 1.11988318e+00
-3.64819586e-01 6.05032623e-01 -5.45496009e-02 -4.22420830e-01
-1.11491072e+00 -9.19071853e-01 -2.70416677e-01 4.89195943e-01
1.04179084e+00 -3.55356663e-01 -1.94399372e-01 -3.65750641e-01
1.23879455e-01 4.75810975e-01 -5.29923081e-01 4.58744913e-02
-3.88751030e-01 -1.79867208e-01 2.66443133e-01 1.39471116e-02
4.64764237e-01 -7.86077082e-01 -1.34152675e+00 2.06862837e-01
-1.28708363e-01 -9.15106893e-01 -1.19502090e-01 4.89256829e-01
-8.30843210e-01 -1.51743329e+00 -1.99363232e-01 -9.80355918e-01
9.25567925e-01 8.69643390e-01 7.14003563e-01 2.18361080e-01
-1.23981282e-01 6.12555504e-01 -5.74189007e-01 -2.49024317e-01
-5.58135629e-01 -5.50244212e-01 4.86706704e-01 -2.73288608e-01
2.81003475e-01 -6.40312210e-02 -2.80421287e-01 5.33162951e-01
-6.88657641e-01 6.93371668e-02 5.99186957e-01 8.65867615e-01
7.79324055e-01 1.82086453e-01 -4.39320020e-02 -3.85589778e-01
2.39911661e-01 -1.23951517e-01 -9.90240276e-01 2.72992194e-01
-8.29838216e-01 1.04950711e-01 1.15198374e-01 -1.39569387e-01
-6.15158796e-01 4.20606464e-01 2.05911174e-01 -4.59893167e-01
-2.55850255e-01 5.27033746e-01 3.14108491e-01 -4.84510601e-01
7.81342983e-01 3.45880777e-01 2.75197536e-01 -1.55131400e-01
3.18933696e-01 4.41553712e-01 5.20343423e-01 -2.84618258e-01
9.59410429e-01 7.82179952e-01 3.21759284e-01 -1.00462496e+00
-2.38328576e-01 -1.25156355e+00 -8.90837133e-01 -4.39068705e-01
6.25092566e-01 -1.05829334e+00 -7.21289933e-01 4.82156910e-02
-1.27276647e+00 1.72386050e-01 -8.21358562e-02 7.75709450e-01
-8.31724465e-01 7.25971103e-01 -9.79859680e-02 -1.17141473e+00
1.42364159e-01 -1.40050375e+00 1.31887627e+00 -1.03222355e-01
-4.35405016e-01 -7.20004439e-01 2.16528341e-01 9.29542072e-03
-1.98966652e-01 8.41914266e-02 3.47490996e-01 -6.08338654e-01
-8.79589140e-01 -4.23310816e-01 -1.70657575e-01 -3.15832198e-02
1.53161392e-01 -2.97877602e-02 -7.62756467e-01 -4.94882464e-01
1.77083522e-01 -2.08160296e-01 5.07048368e-01 1.81845486e-01
8.25541243e-02 -1.01490296e-01 -5.52331567e-01 8.91073793e-02
1.86191428e+00 2.48615846e-01 5.59606731e-01 7.90048480e-01
3.02033037e-01 8.26631069e-01 1.37427354e+00 4.40695345e-01
3.98751765e-01 8.89076948e-01 7.97196925e-01 1.23697981e-01
3.67976189e-01 -3.58693063e-01 1.47099733e-01 4.79325712e-01
2.31217146e-01 3.59271578e-02 -9.82378542e-01 7.14349985e-01
-2.16762662e+00 -8.03524911e-01 -5.51904500e-01 2.72857857e+00
1.07156888e-01 2.22111747e-01 -1.09787002e-01 2.66464353e-01
7.49931872e-01 -4.86036204e-02 -8.30359384e-02 -3.13540667e-01
5.88095002e-02 -5.17126262e-01 9.18897629e-01 9.67428565e-01
-1.20314193e+00 6.85283601e-01 5.95735502e+00 3.00194919e-01
-8.85000587e-01 -6.70548901e-02 -2.99702436e-01 6.56898558e-01
-2.47175954e-02 4.76539314e-01 -1.03331554e+00 1.00595787e-01
3.64527911e-01 1.10738859e-01 1.43927857e-01 8.13712180e-01
3.19127440e-01 -1.07902110e+00 -1.20709753e+00 9.09191549e-01
3.51943016e-01 -1.05072868e+00 -1.88230034e-02 2.63743311e-01
5.36899805e-01 9.07470360e-02 -1.73985943e-01 -4.53658290e-02
3.23506445e-01 -4.53770071e-01 1.27627027e+00 2.66341865e-01
1.71938509e-01 -3.88252020e-01 7.56287575e-01 6.61189854e-01
-1.34601045e+00 8.50839168e-03 -3.38041931e-01 -2.94414192e-01
2.58513838e-01 3.72864574e-01 -1.27261353e+00 9.28243101e-01
5.02182543e-01 5.31127334e-01 -3.39489549e-01 1.43481779e+00
-2.24656031e-01 -3.50062162e-01 -4.25571829e-01 -1.13056198e-01
4.01673675e-01 -2.94420004e-01 8.73885274e-01 9.88859296e-01
4.65169519e-01 -2.84960419e-01 5.22810221e-01 6.18510544e-01
7.99765825e-01 5.48054613e-02 -1.16204965e+00 6.26845360e-01
4.96040165e-01 8.23829234e-01 -7.76432574e-01 -2.86467373e-01
-2.26284862e-01 9.18145120e-01 3.99183445e-02 1.32497728e-01
-7.07240045e-01 -1.73139378e-01 4.47004467e-01 -1.47379801e-01
2.43983254e-01 -5.68256676e-01 -2.74945982e-02 -8.46824110e-01
5.64004481e-02 -5.10207236e-01 1.98394507e-01 -1.12129366e+00
-6.62895203e-01 4.99754071e-01 1.77282780e-01 -1.92020869e+00
-4.85466033e-01 -4.85755473e-01 -2.22526491e-02 8.40387762e-01
-1.63686848e+00 -9.83651340e-01 -3.04780692e-01 4.79114145e-01
5.56883335e-01 3.67483079e-01 8.23406994e-01 4.41449806e-02
-7.28360489e-02 -1.91474557e-01 6.99581858e-03 -3.58654410e-01
7.71058857e-01 -1.16604948e+00 -8.36052150e-02 1.11886668e+00
2.03111529e-01 8.92617822e-01 1.41002965e+00 -8.39357138e-01
-1.42138743e+00 -8.75147760e-01 1.32027352e+00 -4.49060887e-01
6.42172515e-01 -1.86464250e-01 -5.98634064e-01 8.36321533e-01
-1.68244272e-01 -1.65212348e-01 -2.66213771e-02 -5.96321113e-02
-1.05445519e-01 1.82179287e-01 -1.06730497e+00 6.00399494e-01
7.08826363e-01 -7.39999652e-01 -9.99394894e-01 5.54575741e-01
4.24216986e-01 -6.71824157e-01 -5.12266397e-01 5.18555880e-01
5.14048755e-01 -1.13073599e+00 8.36292863e-01 1.49915785e-01
-1.19128190e-01 -9.06720221e-01 -3.46181840e-01 -9.71526980e-01
6.92841336e-02 -4.33945119e-01 2.87239790e-01 8.14170182e-01
9.18082148e-02 -6.48773491e-01 5.06651163e-01 2.16391966e-01
-1.96445704e-01 -2.13642001e-01 -1.11728179e+00 -1.07646155e+00
-7.56793797e-01 -4.69570607e-01 1.78285077e-01 8.41825724e-01
2.36300617e-01 1.64148614e-01 -3.47981095e-01 7.67179370e-01
6.50152147e-01 2.48805195e-01 1.16369653e+00 -1.27180684e+00
-3.81298130e-03 -8.04610848e-02 -7.91525960e-01 -1.29842281e+00
-6.36686534e-02 -4.72521245e-01 9.09863830e-01 -1.44486177e+00
-1.77429661e-01 -5.79623818e-01 1.18503898e-01 4.59790342e-02
3.78076077e-01 -5.28932549e-02 7.52774552e-02 6.63435221e-01
-7.48411715e-01 3.32643718e-01 7.80982077e-01 3.34276780e-02
-2.82002062e-01 -9.99342278e-02 1.10570952e-01 7.24831164e-01
3.13843548e-01 -4.09460425e-01 -3.66288751e-01 -8.18175748e-02
3.26318473e-01 2.45431498e-01 6.35614097e-01 -1.17112482e+00
6.82165027e-01 -1.64964888e-02 -2.33017743e-01 -1.08166051e+00
5.84020913e-01 -1.25977707e+00 3.27651531e-01 7.70250797e-01
-1.11063108e-01 4.42988068e-01 3.21268514e-02 8.64524782e-01
-2.66582817e-01 -5.63655019e-01 5.38925469e-01 -1.82481751e-01
-1.46551251e+00 -3.25283170e-01 -5.99986494e-01 -6.97589040e-01
1.11810780e+00 -6.90806389e-01 -1.70029506e-01 -2.03567594e-01
-5.26771128e-01 2.59074241e-01 8.58463466e-01 4.14276153e-01
6.64057255e-01 -1.04446483e+00 -2.08321795e-01 3.17321718e-01
7.37130225e-01 1.18547142e-01 -1.41852111e-01 1.04399240e+00
-7.60367334e-01 7.80404687e-01 -2.14692950e-02 -1.13185918e+00
-1.33438039e+00 6.69711053e-01 3.14238518e-01 -2.41531014e-01
-6.34419084e-01 5.42515218e-01 1.09872706e-01 -5.00149608e-01
3.40641886e-01 -4.83929306e-01 -1.14486031e-01 -2.83532608e-02
2.85017222e-01 1.91122487e-01 1.83792830e-01 -1.17536521e+00
-5.00304341e-01 8.05861294e-01 1.52689233e-01 -2.47517407e-01
7.31197953e-01 -7.11761653e-01 -1.91205174e-01 6.64655209e-01
8.63127351e-01 -6.57040626e-02 -9.78508770e-01 -2.10357249e-01
2.15083614e-01 -5.90742409e-01 -1.49326026e-01 -3.16540509e-01
-5.38423471e-02 2.53177464e-01 7.61586845e-01 3.28670502e-01
6.02262378e-01 -5.82277961e-02 1.61632597e-01 7.15699315e-01
1.18483949e+00 -1.07898545e+00 -1.16289988e-01 6.95874512e-01
9.54478621e-01 -1.49983275e+00 3.12229306e-01 -5.18498540e-01
-2.59142488e-01 1.00819623e+00 4.08875257e-01 -3.24510396e-01
4.16447908e-01 -1.72949031e-01 -2.01745346e-01 -3.68693531e-01
-4.26068693e-01 -5.47360539e-01 1.07860565e-01 4.60674167e-01
2.72240005e-02 -9.18979198e-02 -3.31998408e-01 -5.17117798e-01
-1.97217185e-02 -8.46252367e-02 5.98116159e-01 1.25156200e+00
-9.37746167e-01 -7.27114022e-01 -8.26973438e-01 -5.43134250e-02
3.55163842e-01 2.52879530e-01 -9.16808546e-02 1.25149870e+00
2.02888653e-01 1.18191755e+00 6.12042509e-02 -4.93863851e-01
3.81270558e-01 -2.75858849e-01 4.47554648e-01 -6.79561496e-01
-2.38943443e-01 -3.08020879e-02 1.79970264e-01 -6.80417538e-01
-6.51487291e-01 -7.39375412e-01 -1.30525744e+00 -4.60705869e-02
-7.36230850e-01 2.71781236e-01 8.99914742e-01 1.16083097e+00
1.28100049e-02 1.28231257e-01 5.08710384e-01 -1.08497000e+00
-6.18663013e-01 -7.32355356e-01 -7.64166713e-01 3.73023778e-01
7.33441651e-01 -1.11841476e+00 -5.72976589e-01 -1.55395279e-02] | [7.324501037597656, -2.0479114055633545] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.