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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7b2a74f2-070f-4f04-82dd-ac07dd4cd3c7 | handling-divergent-reference-texts-when | 1906.01081 | null | https://arxiv.org/abs/1906.01081v1 | https://arxiv.org/pdf/1906.01081v1.pdf | Handling Divergent Reference Texts when Evaluating Table-to-Text Generation | Automatically constructed datasets for generating text from semi-structured data (tables), such as WikiBio, often contain reference texts that diverge from the information in the corresponding semi-structured data. We show that metrics which rely solely on the reference texts, such as BLEU and ROUGE, show poor correlation with human judgments when those references diverge. We propose a new metric, PARENT, which aligns n-grams from the reference and generated texts to the semi-structured data before computing their precision and recall. Through a large scale human evaluation study of table-to-text models for WikiBio, we show that PARENT correlates with human judgments better than existing text generation metrics. We also adapt and evaluate the information extraction based evaluation proposed by Wiseman et al (2017), and show that PARENT has comparable correlation to it, while being easier to use. We show that PARENT is also applicable when the reference texts are elicited from humans using the data from the WebNLG challenge. | ['Ming-Wei Chang', 'Manaal Faruqui', 'Dipanjan Das', 'Ankur Parikh', 'William W. Cohen', 'Bhuwan Dhingra'] | 2019-06-03 | handling-divergent-reference-texts-when-1 | https://aclanthology.org/P19-1483 | https://aclanthology.org/P19-1483.pdf | acl-2019-7 | ['table-to-text-generation'] | ['natural-language-processing'] | [ 3.27445239e-01 8.37763250e-01 -1.13228681e-02 -2.97684848e-01
-1.26337767e+00 -9.12108779e-01 1.16385293e+00 6.27378047e-01
-5.11751592e-01 1.13914406e+00 8.62544298e-01 -5.08116521e-02
-8.07176977e-02 -8.74191582e-01 -6.53470397e-01 -5.54929003e-02
3.79259020e-01 1.07369161e+00 1.39697060e-01 -4.26707059e-01
3.07446390e-01 -2.93570369e-01 -1.55861413e+00 5.91464400e-01
1.28101194e+00 5.88482082e-01 6.85299039e-02 6.38561904e-01
-3.69965672e-01 8.40475082e-01 -8.68084371e-01 -6.84989452e-01
2.75646031e-01 -6.06987894e-01 -1.23338675e+00 -1.21023208e-01
8.21573138e-01 3.06613203e-02 -8.99888575e-02 7.79518843e-01
5.82623363e-01 1.77588395e-03 9.10260856e-01 -1.22298539e+00
-6.08967960e-01 1.43464506e+00 5.97010553e-02 -1.14923172e-01
7.84705937e-01 -1.86015651e-01 1.32067537e+00 -8.81291330e-01
1.22902572e+00 1.22318351e+00 7.66565204e-01 6.03955150e-01
-1.29600108e+00 -4.49484140e-01 -3.70631218e-01 -1.60535231e-01
-9.49975669e-01 -5.03826201e-01 2.52663791e-01 -5.32523334e-01
1.07497704e+00 3.88490170e-01 2.48519219e-02 1.30983508e+00
-7.69200474e-02 9.12694693e-01 1.10412562e+00 -7.48012424e-01
4.11265306e-02 3.67502779e-01 1.71836242e-01 3.08949530e-01
7.85048783e-01 -1.36231214e-01 -6.91600144e-01 -2.24665210e-01
2.77126897e-02 -7.38356531e-01 -3.37886065e-01 -2.60494381e-01
-1.61203229e+00 7.37667799e-01 -1.48867890e-01 3.53584796e-01
-3.67875665e-01 -2.71307141e-01 6.59959257e-01 1.74260303e-01
5.34844995e-01 1.04279065e+00 -6.10559881e-01 -4.17917818e-01
-1.08749163e+00 7.83931375e-01 1.38941777e+00 1.56812096e+00
5.23215950e-01 -3.86823058e-01 -6.10755026e-01 8.19774568e-01
1.73641980e-01 6.47745311e-01 9.25938070e-01 -7.75004506e-01
1.09507394e+00 6.70023143e-01 5.94818413e-01 -9.42088425e-01
-3.97756457e-01 -3.40809673e-02 -6.04447067e-01 -3.41231585e-01
7.58100986e-01 -2.76787221e-01 -4.87386942e-01 1.60074234e+00
2.19227314e-01 -8.67032349e-01 2.94534117e-01 4.41684484e-01
1.15021563e+00 5.55980444e-01 -6.75268695e-02 -2.00091004e-01
1.08450377e+00 -8.39876711e-01 -7.93868780e-01 -3.57191056e-01
1.04280269e+00 -8.28290820e-01 1.34884357e+00 3.81167650e-01
-1.07182252e+00 -4.10302222e-01 -1.02576745e+00 -3.67696136e-01
-7.05112696e-01 2.82101154e-01 2.51471251e-01 5.66422164e-01
-9.37381089e-01 7.88182199e-01 -3.88145328e-01 -7.13022709e-01
-3.56114581e-02 -1.37086183e-01 -4.53613311e-01 2.07148239e-01
-1.50414264e+00 9.99124706e-01 6.53858423e-01 -4.08921510e-01
-5.37096262e-01 -6.69844389e-01 -8.98937345e-01 -8.64467695e-02
5.10299921e-01 -5.77535987e-01 1.57370317e+00 -5.83453178e-01
-1.17239714e+00 9.37276661e-01 9.07583442e-03 -6.67210042e-01
7.34701276e-01 -2.70516068e-01 -2.97210932e-01 -6.01177700e-02
4.64972734e-01 5.38387597e-01 2.86537856e-01 -1.17485809e+00
-7.71216571e-01 -1.75111800e-01 -1.31006211e-01 2.29185060e-01
-3.51873487e-01 -8.52418989e-02 -3.01202778e-02 -6.70675695e-01
-4.19931591e-01 -8.04230928e-01 -5.90518564e-02 -5.50318837e-01
-9.49248791e-01 -5.41789770e-01 1.75783679e-01 -8.93772662e-01
1.72946179e+00 -1.27366495e+00 -1.19431749e-01 1.45746112e-01
4.28574473e-01 2.01738790e-01 -2.90659457e-01 8.91078532e-01
7.15119317e-02 5.81533015e-01 -2.17876375e-01 -3.49441990e-02
4.56693053e-01 -1.46590397e-01 -2.55616397e-01 -2.86708176e-01
-3.20204869e-02 9.25490499e-01 -1.13809776e+00 -7.61698246e-01
-3.19343388e-01 1.29049718e-02 -3.04468781e-01 1.37800053e-01
-3.79591554e-01 -2.49807835e-01 -2.31156826e-01 3.99994999e-02
2.46903569e-01 -2.71351367e-01 2.22289622e-01 -6.77566081e-02
-3.85360606e-02 9.56234276e-01 -8.91199052e-01 1.48293364e+00
-6.06106102e-01 7.56422341e-01 -3.26393127e-01 -2.48826683e-01
9.33307648e-01 3.96287948e-01 4.95003276e-02 -6.24757051e-01
-1.04454897e-01 2.55045474e-01 -2.09909394e-01 -4.67468113e-01
1.03622639e+00 5.99106923e-02 -3.42263758e-01 8.78028750e-01
2.17890441e-01 -4.97163147e-01 1.10481000e+00 8.27009141e-01
1.36743832e+00 1.95417672e-01 6.54432476e-01 -4.53133494e-01
4.23005670e-01 3.37532222e-01 1.11325547e-01 1.06961346e+00
3.01577538e-01 6.01588130e-01 6.21218443e-01 -7.02691078e-02
-1.35388124e+00 -1.02387583e+00 -6.16663136e-02 9.32643592e-01
-3.61502945e-01 -1.19165516e+00 -1.08875513e+00 -1.18812609e+00
9.09663513e-02 1.18349612e+00 -8.54301393e-01 1.71850473e-01
-2.59960085e-01 -5.15672445e-01 6.80843890e-01 4.26341355e-01
1.35631328e-02 -1.09278393e+00 -5.22732556e-01 4.59186375e-01
-7.76203454e-01 -1.11219168e+00 -7.24389374e-01 1.70783848e-01
-6.15858376e-01 -1.03995907e+00 -4.51598197e-01 -4.89895493e-01
5.43637574e-01 -1.39887944e-01 1.78704047e+00 -1.71519965e-01
1.11843795e-01 3.07731122e-01 -6.80755436e-01 -6.56008840e-01
-1.11049902e+00 5.07031024e-01 -7.94050619e-02 -6.15513325e-01
4.69706684e-01 -1.88610241e-01 -1.00465745e-01 4.20252174e-01
-1.18773258e+00 2.99633652e-01 3.67447048e-01 8.66786718e-01
2.93070018e-01 -1.73238114e-01 7.21623600e-01 -1.54934728e+00
9.85193968e-01 -4.14878279e-01 -3.38874578e-01 4.65816259e-01
-1.16871846e+00 4.70478266e-01 8.81074965e-01 -1.84209004e-01
-1.07511330e+00 -2.03228921e-01 2.07147449e-01 5.40368676e-01
-1.20077990e-01 5.79923272e-01 -2.29053974e-01 6.25796020e-01
1.21547997e+00 2.05627866e-02 -2.58682430e-01 -4.56231952e-01
5.18513799e-01 1.06016588e+00 3.78004342e-01 -6.31226778e-01
1.00779486e+00 9.34312865e-02 -3.85161072e-01 -5.52184820e-01
-1.15774369e+00 -2.35244453e-01 -7.88109839e-01 -1.85547993e-02
5.41104496e-01 -7.26997852e-01 -2.27074042e-01 3.49930301e-02
-1.20806444e+00 -4.50126261e-01 -5.53128660e-01 2.47835144e-01
-6.52224660e-01 4.11859035e-01 -5.06499052e-01 -6.13864183e-01
-6.72744811e-01 -5.01356423e-01 1.17606211e+00 1.46639617e-02
-9.48488891e-01 -1.12621784e+00 3.10194135e-01 4.69007045e-01
2.64787108e-01 3.58960629e-01 1.04222846e+00 -1.37419248e+00
6.31373599e-02 -3.93628657e-01 -1.61695287e-01 2.04155609e-01
3.34535271e-01 1.71880051e-01 -6.07353389e-01 6.20377399e-02
-3.39308023e-01 -6.25757158e-01 6.05967522e-01 -2.30518252e-01
5.74184895e-01 -9.06484425e-01 -2.50573069e-01 -1.67711582e-02
1.15728581e+00 2.49415245e-02 5.68094075e-01 5.15419424e-01
6.84298158e-01 1.14599049e+00 7.71768153e-01 4.60268319e-01
7.64382601e-01 4.28799599e-01 -2.07745701e-01 3.54617834e-01
-1.16202451e-01 -7.70474792e-01 4.71064180e-01 1.10690045e+00
3.05709332e-01 -7.09399164e-01 -1.01232874e+00 6.75915182e-01
-1.68412268e+00 -9.86840189e-01 -3.85957241e-01 2.31070113e+00
1.53719461e+00 3.02623123e-01 1.48934752e-01 1.77068457e-01
6.40094280e-01 -2.92566307e-02 4.44413498e-02 -3.30802411e-01
-2.81730264e-01 2.40853280e-01 3.59618992e-01 5.41763246e-01
-8.79762650e-01 8.60038996e-01 6.90098333e+00 9.03865516e-01
-3.62101167e-01 -8.86570886e-02 3.92699122e-01 -1.42113343e-01
-6.72895014e-01 -9.35575645e-03 -9.75848973e-01 5.22807539e-01
1.39544439e+00 -8.77922535e-01 2.50591397e-01 7.51430392e-01
1.55445576e-01 -7.57585540e-02 -1.66524386e+00 6.62297726e-01
2.84799695e-01 -1.07854092e+00 3.52595240e-01 -4.88192253e-02
8.77342880e-01 -1.51525795e-01 -4.30149883e-01 4.09408420e-01
8.30168605e-01 -9.87872124e-01 8.83508205e-01 3.34692270e-01
6.69421136e-01 -5.60629189e-01 8.02309692e-01 4.04566973e-01
-7.10132062e-01 4.54292804e-01 -3.22782159e-01 1.97644457e-01
1.13251604e-01 7.76734769e-01 -1.40426087e+00 5.46824694e-01
3.27945530e-01 4.88115162e-01 -1.12154484e+00 6.36772335e-01
-3.98948401e-01 5.17465293e-01 -1.27386004e-01 -5.87334752e-01
7.93659911e-02 -1.97225418e-02 5.15201569e-01 1.35007596e+00
3.24867368e-01 -3.49286497e-01 -8.63174871e-02 8.81565928e-01
-2.62966275e-01 6.88765824e-01 -8.99062753e-01 -5.23822844e-01
5.00768781e-01 1.31790221e+00 -5.74974775e-01 -7.51797974e-01
-3.15855235e-01 6.98960125e-01 3.50222528e-01 1.96002368e-02
-3.39548230e-01 -1.01430488e+00 2.21085642e-02 2.72933245e-01
4.87059020e-02 4.64480370e-02 -4.24777389e-01 -1.06765473e+00
3.18747610e-01 -1.20696068e+00 3.98091793e-01 -9.53204989e-01
-1.44654536e+00 9.85827625e-01 2.12461874e-01 -1.36814761e+00
-8.02102208e-01 -4.13924217e-01 -1.58928216e-01 8.33284616e-01
-9.04711723e-01 -6.69982433e-01 -4.08834428e-01 1.16032727e-01
5.24280369e-01 7.52689689e-03 7.58355439e-01 -3.92821096e-02
-2.01819494e-01 6.78786397e-01 1.34353131e-01 3.84000033e-01
1.11117089e+00 -1.81689632e+00 1.01502895e+00 8.63484919e-01
3.37218851e-01 7.39507854e-01 1.02348733e+00 -1.08414125e+00
-9.92903650e-01 -1.13844717e+00 1.62607312e+00 -1.11449373e+00
8.40342641e-01 -5.46940207e-01 -7.19488323e-01 6.49843752e-01
5.45621634e-01 -6.91986978e-01 7.44260848e-01 1.00855984e-01
-4.33251679e-01 2.15809688e-01 -1.05957210e+00 6.78395212e-01
1.12086868e+00 -5.64652741e-01 -8.97144735e-01 6.25690460e-01
7.64434755e-01 -4.82379049e-01 -8.48914921e-01 1.87648296e-01
5.26599586e-01 -7.63551116e-01 3.49123031e-01 -8.19640517e-01
8.90272319e-01 -1.24025926e-01 -2.34310385e-02 -1.68008888e+00
-1.44747391e-01 -8.02299261e-01 -3.01075391e-02 1.62498391e+00
1.11148620e+00 -4.29862678e-01 6.67238235e-01 7.63549030e-01
3.85505334e-02 -4.30784374e-01 -4.68642533e-01 -9.99512196e-01
2.20523700e-01 -1.15354180e-01 6.18669212e-01 8.72356176e-01
4.88990515e-01 7.86202431e-01 -8.33061263e-02 -5.09609878e-01
5.77360213e-01 -1.52493030e-01 9.34425771e-01 -1.48033094e+00
8.00743885e-03 -1.53796464e-01 -2.55037993e-02 -7.25529790e-01
7.59095177e-02 -1.28563666e+00 4.52217817e-01 -1.82091653e+00
2.58984894e-01 -2.53075242e-01 2.71160156e-01 4.52106804e-01
-3.71153712e-01 -1.02818534e-01 1.44564971e-01 1.12044677e-01
-6.76267564e-01 4.47356671e-01 1.08025789e+00 -2.11380888e-02
-1.84911340e-01 -3.15079808e-01 -1.09725916e+00 4.59087849e-01
6.01453841e-01 -7.12148428e-01 -3.54891509e-01 -3.53282034e-01
5.91251671e-01 1.00616645e-02 -1.94667608e-01 -1.04791427e+00
9.54967514e-02 -4.02163854e-03 2.46213347e-01 -4.20299560e-01
-4.48417991e-01 -4.94207531e-01 -7.78850317e-02 7.94912279e-02
-9.35791016e-01 3.34228426e-01 -7.31615499e-02 3.19160700e-01
-1.98380709e-01 -5.74477136e-01 3.17524463e-01 -1.74286291e-01
1.64185688e-02 -1.28576504e-02 -4.83159453e-01 9.49246407e-01
4.38271940e-01 -1.80062186e-02 -6.53862059e-01 -6.10301018e-01
-2.66594678e-01 2.85757631e-01 4.43072736e-01 5.45851350e-01
2.46888548e-01 -1.44046676e+00 -1.05886710e+00 -2.65601724e-01
5.07097363e-01 -8.70498642e-02 -3.50032836e-01 5.74431777e-01
-5.52138925e-01 7.98770428e-01 -1.51823210e-02 -1.18733853e-01
-9.90294278e-01 4.03303027e-01 -2.14594841e-01 -8.48146677e-01
-2.90066510e-01 3.60835135e-01 -2.20278073e-02 -7.94575691e-01
1.06675521e-01 -6.90883756e-01 -1.09880283e-01 4.31776434e-01
7.82509089e-01 6.00603580e-01 4.19762909e-01 -4.05075371e-01
-1.03235515e-02 -9.08845142e-02 -2.82879680e-01 -6.21460199e-01
1.19467795e+00 -2.12650076e-01 -3.58369313e-02 5.74761152e-01
1.00220025e+00 4.82318938e-01 -7.76113927e-01 -4.20379370e-01
7.02668428e-01 -1.70682475e-01 -4.46008295e-01 -1.18771362e+00
-3.77054930e-01 4.23311144e-01 -1.09116949e-01 5.80394983e-01
6.16730928e-01 -6.20486513e-02 8.38106692e-01 8.01781297e-01
5.10877132e-01 -1.43720591e+00 -1.17294542e-01 7.95354426e-01
1.08885622e+00 -1.12648940e+00 -1.12214722e-01 -4.29546058e-01
-8.56176972e-01 1.09909165e+00 7.09308982e-01 3.38171661e-01
2.34075457e-01 3.46457332e-01 1.05576530e-01 -1.05723500e-01
-1.14335883e+00 -1.10200629e-01 5.03283918e-01 8.43022048e-01
8.61463547e-01 -9.93733779e-02 -6.46790445e-01 8.37460220e-01
-1.02394533e+00 -7.21203536e-02 9.40461576e-01 7.57287025e-01
-3.22413206e-01 -1.19709730e+00 -2.00858980e-01 9.29794133e-01
-4.39508468e-01 -4.64746892e-01 -1.00803459e+00 8.11422348e-01
-3.53621453e-01 1.10314476e+00 -1.97128072e-01 -4.15993452e-01
3.42431515e-01 4.66709614e-01 4.43885773e-01 -1.05982625e+00
-8.78605008e-01 -4.79252607e-01 8.01120579e-01 -3.73674721e-01
-2.14174524e-01 -6.83161616e-01 -1.10264909e+00 -9.20361653e-02
-1.91345438e-01 6.91149116e-01 5.54859400e-01 7.83800721e-01
2.71902204e-01 8.15138817e-02 4.21838611e-01 -5.37367344e-01
-6.73031628e-01 -1.46097398e+00 -4.83469635e-01 8.34451795e-01
-8.61743838e-02 -1.75974637e-01 -5.12329042e-01 2.82480568e-01] | [11.64137077331543, 8.996068000793457] |
109a6273-52b1-4aef-8a38-5a095c434a60 | anchor-changing-regularized-natural-policy | 2206.05357 | null | https://arxiv.org/abs/2206.05357v2 | https://arxiv.org/pdf/2206.05357v2.pdf | Anchor-Changing Regularized Natural Policy Gradient for Multi-Objective Reinforcement Learning | We study policy optimization for Markov decision processes (MDPs) with multiple reward value functions, which are to be jointly optimized according to given criteria such as proportional fairness (smooth concave scalarization), hard constraints (constrained MDP), and max-min trade-off. We propose an Anchor-changing Regularized Natural Policy Gradient (ARNPG) framework, which can systematically incorporate ideas from well-performing first-order methods into the design of policy optimization algorithms for multi-objective MDP problems. Theoretically, the designed algorithms based on the ARNPG framework achieve $\tilde{O}(1/T)$ global convergence with exact gradients. Empirically, the ARNPG-guided algorithms also demonstrate superior performance compared to some existing policy gradient-based approaches in both exact gradients and sample-based scenarios. | ['Chao Tian', 'P. R. Kumar', 'Dileep Kalathil', 'Tao Liu', 'Ruida Zhou'] | 2022-06-10 | null | null | null | null | ['multi-objective-reinforcement-learning'] | ['methodology'] | [-9.17489231e-02 6.33186698e-02 -8.13310683e-01 -3.77081990e-01
-8.73131335e-01 -3.37953299e-01 3.56366992e-01 1.98017031e-01
-8.24179590e-01 1.38671052e+00 2.06372008e-01 -7.49983728e-01
-3.70251298e-01 -3.71143341e-01 -3.14728349e-01 -7.72724330e-01
-3.71112168e-01 5.68141639e-01 -1.18217327e-01 -4.43760529e-02
4.86832410e-01 3.21093351e-01 -7.81320333e-01 -5.46351075e-01
1.39566672e+00 1.28665721e+00 1.81579515e-01 6.14488780e-01
9.48415250e-02 1.06886649e+00 -2.32529938e-01 -3.66016448e-01
5.61973691e-01 -2.76848674e-01 -6.47288978e-01 -2.15040043e-01
-1.39218211e-01 -7.04944730e-01 -1.69866115e-01 1.18702674e+00
7.24563062e-01 7.10671842e-01 5.32621801e-01 -1.38030744e+00
-4.36927110e-01 4.69605893e-01 -8.37584913e-01 4.05881375e-01
-1.05431601e-01 5.64862430e-01 1.26332521e+00 -2.80556887e-01
2.73175091e-01 1.84351981e+00 -7.45192617e-02 8.28142703e-01
-1.19127774e+00 -3.05969238e-01 7.71534562e-01 5.56495190e-02
-6.35305941e-01 -2.64671743e-01 8.68695453e-02 -1.35639697e-01
6.15642250e-01 2.33542785e-01 2.22848758e-01 7.09534526e-01
2.74168193e-01 1.07178402e+00 1.32254553e+00 -6.70621991e-02
6.98429108e-01 2.73722149e-02 -1.86770648e-01 6.12878919e-01
1.92218229e-01 4.70055968e-01 -7.57657960e-02 -3.95721704e-01
9.32467043e-01 -1.37895674e-01 -1.60667881e-01 -3.08427662e-01
-1.09754598e+00 9.03636396e-01 7.38445446e-02 -4.01684642e-01
-1.00089025e+00 5.62076688e-01 3.08610201e-01 4.30607587e-01
5.57153881e-01 4.50391591e-01 -4.91099209e-01 -5.81951439e-01
-7.36788392e-01 6.77819431e-01 9.18807507e-01 9.60395992e-01
2.55000353e-01 3.93556774e-01 -1.24260747e+00 4.92155403e-01
6.16598725e-01 7.49943793e-01 1.48536200e-02 -1.66858613e+00
8.52925181e-01 -1.23798437e-01 1.14304030e+00 -5.75123310e-01
-3.97603735e-02 -4.52271610e-01 -5.33810139e-01 4.99254733e-01
6.35533571e-01 -7.59401798e-01 -6.25014901e-01 2.03205419e+00
5.01551390e-01 -2.97043115e-01 8.63760523e-03 1.14326835e+00
-2.51248717e-01 6.58111572e-01 2.05001488e-01 -1.01776195e+00
8.29837501e-01 -8.37060690e-01 -7.78992474e-01 -1.40757859e-01
1.51579753e-01 -4.19104844e-01 1.33359218e+00 1.80781484e-01
-1.35587406e+00 4.08842154e-02 -6.77805841e-01 4.71189737e-01
4.59726512e-01 -1.91984683e-01 2.77387470e-01 7.60617316e-01
-9.94485736e-01 9.16532278e-01 -6.44337714e-01 -4.40132953e-02
6.47044182e-01 3.50931227e-01 7.08348334e-01 3.05008925e-02
-8.25010538e-01 8.96082640e-01 1.89686850e-01 -3.51492316e-02
-1.62081885e+00 -7.41696119e-01 -2.10892275e-01 2.20417723e-01
1.08502591e+00 -6.34819329e-01 1.65541017e+00 -5.45173526e-01
-2.24272871e+00 3.05444390e-01 -1.89558640e-01 -5.92221975e-01
1.18445218e+00 -4.21480596e-01 4.78365533e-02 1.53901026e-01
-6.63550384e-03 3.57829213e-01 1.06827116e+00 -1.19210815e+00
-9.64930296e-01 -1.45716220e-01 3.22828591e-01 7.48419821e-01
-2.42611304e-01 3.40292633e-01 2.67003000e-01 -3.34391892e-01
-7.38447905e-01 -6.42541349e-01 -9.87240374e-01 -3.26384977e-02
-3.94481003e-01 -1.44263729e-01 5.98641872e-01 -6.60055518e-01
1.27389348e+00 -1.73229945e+00 6.17035665e-02 3.57756227e-01
1.74986392e-01 1.96817636e-01 -1.60624847e-01 1.28718704e-01
6.16319597e-01 1.87876269e-01 -1.54109582e-01 -3.14676553e-01
5.74364841e-01 4.10864025e-01 -3.69648606e-01 5.60565293e-01
-1.64257288e-01 7.84737349e-01 -1.18019176e+00 -4.09849018e-01
6.83818012e-02 -3.71057451e-01 -5.38254261e-01 4.50647205e-01
-7.12481320e-01 6.52742565e-01 -9.87233520e-01 5.44582486e-01
4.54666317e-01 -6.27396479e-02 2.03947037e-01 4.91657853e-01
-3.52786660e-01 -1.03275757e-02 -1.17817152e+00 9.32072341e-01
-3.71047080e-01 6.61136732e-02 6.12866402e-01 -1.21568704e+00
6.76610231e-01 2.00413704e-01 8.28109562e-01 -5.20112395e-01
1.99151814e-01 2.30260938e-01 -1.03011049e-01 -1.05726756e-01
5.06308138e-01 -3.96038234e-01 2.13761508e-01 6.71064973e-01
-3.99495155e-01 5.64721972e-02 2.78223187e-01 6.75822496e-02
9.00481999e-01 4.10992019e-02 3.94987434e-01 -7.62891769e-01
4.00780827e-01 -2.41827637e-01 8.67896676e-01 1.08273518e+00
-9.55721319e-01 -1.84790269e-01 9.95014668e-01 3.78451757e-02
-1.09864783e+00 -8.22635472e-01 2.95247823e-01 1.44456112e+00
2.77296007e-01 2.42961019e-01 -3.73357415e-01 -7.23934054e-01
3.94094139e-01 9.38964725e-01 -4.20014352e-01 1.61878422e-01
-3.60516220e-01 -8.50168526e-01 1.65325180e-02 1.90232247e-01
5.57009041e-01 -7.58617043e-01 -7.11049497e-01 6.21050417e-01
1.75420702e-01 -9.55960810e-01 -8.32911074e-01 -5.62648929e-04
-8.29436898e-01 -6.23993099e-01 -1.22793138e+00 -8.80404785e-02
6.26200795e-01 5.04045794e-03 8.11710000e-01 -7.47625887e-01
3.34390819e-01 6.48223758e-01 -5.55329199e-04 -5.64621329e-01
-2.01723129e-01 -2.13107601e-01 4.02862042e-01 2.42254913e-01
-1.80751845e-01 -3.93731236e-01 -8.36757779e-01 5.34857512e-01
-4.36870903e-01 -3.54204267e-01 5.45882463e-01 7.16871917e-01
7.96691895e-01 -2.59679347e-01 7.13149846e-01 -3.60771656e-01
1.47069585e+00 -3.27789009e-01 -1.04806745e+00 4.85637099e-01
-1.04622710e+00 4.08642232e-01 7.29909301e-01 -5.88082552e-01
-1.26330817e+00 -5.51259458e-01 3.97614628e-01 -5.98531127e-01
3.70122164e-01 1.60765737e-01 -1.05933808e-02 -1.01905867e-01
2.85672992e-01 1.81688800e-01 1.73185155e-01 -2.55034089e-01
5.03567040e-01 4.07661259e-01 1.17633693e-01 -1.44267762e+00
4.19178009e-01 3.45362991e-01 1.79717720e-01 -3.03799748e-01
-8.45400095e-01 -7.35319108e-02 1.67976037e-01 -4.01144296e-01
5.76260984e-01 -5.56343257e-01 -1.42155063e+00 9.08503905e-02
-6.50324643e-01 -8.53420913e-01 -6.69757485e-01 8.15634549e-01
-1.04996812e+00 4.27196503e-01 -5.22847593e-01 -1.63310182e+00
-4.69006926e-01 -9.58438993e-01 4.80342805e-01 4.84118521e-01
3.15026760e-01 -9.32743549e-01 6.35976046e-02 -4.75926697e-02
6.60727143e-01 2.66931117e-01 7.98954666e-01 -2.80375451e-01
-4.63560760e-01 2.87224680e-01 -3.17503542e-01 5.05097389e-01
-1.64893772e-02 -2.66948670e-01 -2.81745106e-01 -7.37308145e-01
5.98623343e-02 -4.60157394e-01 5.07089555e-01 9.74891484e-01
1.26112413e+00 -1.06706619e+00 -1.46161675e-01 4.08969522e-01
1.42075491e+00 5.21124423e-01 1.07227340e-01 2.83716530e-01
3.81805062e-01 4.34109300e-01 9.81418610e-01 1.27776313e+00
2.99145520e-01 3.03255349e-01 8.35920393e-01 1.95562974e-01
7.23051190e-01 -1.21318936e-01 7.67253399e-01 2.19322711e-01
-5.13181746e-01 -3.27336878e-01 -5.94154537e-01 4.06817645e-01
-2.32172990e+00 -9.49482799e-01 2.57537603e-01 2.59294939e+00
8.30437660e-01 1.19922347e-01 5.51951826e-01 -5.43067038e-01
9.13420618e-01 2.31864005e-01 -1.32317889e+00 -8.38907778e-01
2.40663458e-02 1.33994119e-02 1.10710716e+00 7.05596209e-01
-9.36797380e-01 8.86276066e-01 6.69885397e+00 1.10654068e+00
-8.05555463e-01 1.35887519e-01 9.97850657e-01 -5.38548887e-01
-2.20887020e-01 -5.61535358e-03 -7.33932793e-01 6.10740006e-01
8.68095756e-01 -8.01069498e-01 9.62414980e-01 9.86372411e-01
1.13533807e+00 -1.23899482e-01 -7.66785920e-01 7.62113988e-01
-8.53983879e-01 -9.00364041e-01 -4.51137215e-01 4.48041230e-01
1.19235933e+00 -1.01403505e-01 3.09322536e-01 4.62352484e-01
1.29671288e+00 -9.12778080e-01 6.36068642e-01 4.59449023e-01
6.81280017e-01 -1.04008293e+00 4.83059675e-01 2.18489468e-01
-9.42692757e-01 -5.88832259e-01 -5.16769588e-01 -1.45685434e-01
5.88608980e-01 6.34919763e-01 -4.14589912e-01 4.15604562e-01
3.25545579e-01 4.75441724e-01 5.52390218e-01 1.03424215e+00
-3.69446397e-01 5.72662592e-01 -4.47940409e-01 -4.61011410e-01
9.16910291e-01 -6.15349531e-01 9.65529442e-01 7.22189307e-01
1.75556362e-01 3.95859815e-02 6.78229153e-01 9.32653308e-01
4.52662259e-02 3.01218510e-01 -3.39000579e-03 -3.70403737e-01
4.18647677e-01 1.11557376e+00 -4.16341633e-01 -3.98088396e-01
7.00854370e-03 6.77452385e-01 1.83297560e-01 7.56489992e-01
-9.45579708e-01 -1.53299153e-01 1.30440605e+00 -3.19074154e-01
3.34864259e-01 -4.04558927e-01 -3.81191730e-01 -9.07725751e-01
1.19225040e-01 -6.95565224e-01 3.23786348e-01 -3.67563479e-02
-1.51589644e+00 -3.95400077e-02 -2.90946737e-02 -9.59379733e-01
-3.34225148e-01 -4.53569472e-01 -7.75246978e-01 8.64401817e-01
-1.81977403e+00 -4.56654161e-01 4.58963543e-01 6.58720195e-01
2.42190406e-01 -1.27244204e-01 3.06020260e-01 1.58015832e-01
-8.73687625e-01 4.52887088e-01 9.52197313e-01 -5.16879082e-01
4.33783591e-01 -1.51339996e+00 -2.83459008e-01 7.50386477e-01
-8.12877476e-01 1.57570288e-01 8.20030212e-01 -5.02868950e-01
-1.25624406e+00 -9.79380727e-01 9.79023203e-02 1.89794049e-01
7.96329200e-01 8.70629847e-02 -3.31121475e-01 2.95152932e-01
-5.06291166e-03 -6.16572537e-02 1.01380952e-01 -1.86488226e-01
3.92656475e-01 -1.55358002e-01 -1.40251017e+00 7.99122393e-01
1.12020636e+00 4.85134311e-02 6.84660599e-02 5.46579719e-01
7.46873081e-01 -3.58331621e-01 -9.83695030e-01 1.09341808e-01
4.07598913e-01 -3.18518370e-01 7.22405493e-01 -1.28349590e+00
3.26432288e-01 5.98865896e-02 -2.89954126e-01 -1.58259952e+00
-2.59947121e-01 -1.55776989e+00 -6.32016897e-01 8.74860346e-01
3.55786860e-01 -8.93468320e-01 5.87761164e-01 9.12763298e-01
3.69941071e-02 -1.02291095e+00 -1.08101189e+00 -1.29705584e+00
3.08590204e-01 -1.15495376e-01 5.04348874e-01 6.01375282e-01
1.15379609e-01 -3.27390619e-02 -9.51628923e-01 -6.66331500e-02
1.01253510e+00 7.33571723e-02 4.68433231e-01 -6.55505478e-01
-6.32199645e-01 -9.07780170e-01 4.04254735e-01 -1.48225045e+00
5.66322468e-02 -3.86425078e-01 1.42832994e-01 -1.59940171e+00
7.49679878e-02 -7.23795354e-01 -6.78108096e-01 2.92069495e-01
-5.40530980e-01 -9.38078642e-01 5.66473842e-01 1.99653089e-01
-9.53848302e-01 1.25170720e+00 1.75890446e+00 -4.18771477e-03
-4.25602555e-01 4.92531300e-01 -8.57257545e-01 2.19342366e-01
1.01380920e+00 -5.21330595e-01 -5.37659168e-01 -1.74098045e-01
-1.20208122e-01 4.81791615e-01 -9.22586247e-02 -4.90308106e-01
-1.77727744e-01 -1.37876451e+00 -2.96207845e-01 -1.80485815e-01
7.69729018e-02 -4.42454487e-01 -5.85246861e-01 7.36224413e-01
-7.41590023e-01 3.72396223e-02 -2.62865543e-01 8.93667817e-01
2.22726941e-01 -7.15398137e-03 1.03561080e+00 -2.47950643e-01
-5.40338218e-01 8.78468215e-01 -4.58933562e-01 5.84392726e-01
1.06955957e+00 2.84388244e-01 -2.79479504e-01 -8.93064201e-01
-5.01567006e-01 1.04187942e+00 -8.71877298e-02 -1.70667991e-01
3.82128924e-01 -1.13511217e+00 -8.41485202e-01 -8.57636690e-01
-5.92958689e-01 -3.32901418e-01 -1.28623113e-01 1.02736139e+00
-1.12195082e-01 5.10835946e-01 -2.22150594e-01 -2.23092332e-01
-6.44856215e-01 4.34346735e-01 4.52443093e-01 -9.92861748e-01
-1.72985211e-01 7.27663934e-01 3.34931863e-03 -3.37533355e-01
3.60083312e-01 -3.01577687e-01 1.77949160e-01 -2.46825710e-01
5.07792473e-01 9.50910449e-01 -5.82473695e-01 2.10824728e-01
-8.51680711e-02 -4.57585193e-02 4.32212278e-02 -7.80999362e-01
1.15912771e+00 -3.48973811e-01 2.80481458e-01 3.53642032e-02
6.39927030e-01 -4.58470404e-01 -2.03317904e+00 -4.59520191e-01
1.24961972e-01 -7.56353259e-01 1.73787177e-01 -8.80714059e-01
-9.13330257e-01 6.54520452e-01 6.26999795e-01 8.03486630e-02
7.10153520e-01 -5.89547157e-01 6.33059263e-01 3.97292495e-01
4.14357811e-01 -1.66821098e+00 1.43110305e-01 6.32361650e-01
5.84507704e-01 -1.17919600e+00 2.46703047e-02 2.29111224e-01
-1.12331188e+00 7.65980959e-01 6.91133797e-01 -1.45219907e-01
4.46686774e-01 -5.87471910e-02 -3.70401442e-01 3.90090615e-01
-9.09324288e-01 -5.01640797e-01 -1.31915078e-01 5.81099808e-01
-1.44906342e-01 5.92956245e-01 -8.96621883e-01 1.14983663e-01
2.53839135e-01 -6.59770425e-03 2.28450641e-01 1.18488908e+00
-7.40246177e-01 -1.10848224e+00 -2.58518904e-01 7.06240892e-01
-6.08059943e-01 5.96378297e-02 8.93188342e-02 3.85569662e-01
-6.61047637e-01 1.04942870e+00 -1.65172145e-01 2.45883912e-01
1.44540787e-01 -3.34259093e-01 4.70580369e-01 -1.09048905e-02
-3.03147584e-01 1.38816059e-01 2.05698714e-01 -8.10894310e-01
-3.28294992e-01 -6.40375435e-01 -1.02876520e+00 -6.54337764e-01
1.27578124e-01 2.05748260e-01 5.88813543e-01 1.11402428e+00
3.78387779e-01 4.23782706e-01 1.07873094e+00 -5.96813500e-01
-1.55833530e+00 -8.06244850e-01 -7.43912697e-01 1.09558664e-01
2.39673063e-01 -6.53185666e-01 -1.11743405e-01 -6.28783345e-01] | [4.266066551208496, 2.6716315746307373] |
01699593-235c-40e6-bc47-1706abe6a9f2 | a-comprehensive-evaluation-of-chatgpt-s-zero | 2303.13547 | null | https://arxiv.org/abs/2303.13547v1 | https://arxiv.org/pdf/2303.13547v1.pdf | A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability | This paper presents the first comprehensive analysis of ChatGPT's Text-to-SQL ability. Given the recent emergence of large-scale conversational language model ChatGPT and its impressive capabilities in both conversational abilities and code generation, we sought to evaluate its Text-to-SQL performance. We conducted experiments on 12 benchmark datasets with different languages, settings, or scenarios, and the results demonstrate that ChatGPT has strong text-to-SQL abilities. Although there is still a gap from the current state-of-the-art (SOTA) model performance, considering that the experiment was conducted in a zero-shot scenario, ChatGPT's performance is still impressive. Notably, in the ADVETA (RPL) scenario, the zero-shot ChatGPT even outperforms the SOTA model that requires fine-tuning on the Spider dataset by 4.1\%, demonstrating its potential for use in practical applications. To support further research in related fields, we have made the data generated by ChatGPT publicly available at https://github.com/THU-BPM/chatgpt-sql. | ['Philip S. Yu', 'Lijie Wen', 'Xuming Hu', 'Aiwei Liu'] | 2023-03-12 | null | null | null | null | ['text-to-sql'] | ['computer-code'] | [-3.54516625e-01 1.17939897e-01 -1.22256301e-01 -3.26676130e-01
-1.06732607e+00 -6.24075651e-01 9.08337653e-01 4.08357605e-02
-2.38310024e-02 5.77186406e-01 4.59025234e-01 -6.36775374e-01
6.15961328e-02 -7.87402749e-01 -4.68275189e-01 -2.28340104e-01
-2.79426515e-01 8.16103578e-01 2.23342896e-01 -5.93765914e-01
4.95690137e-01 -2.15478286e-01 -1.38886678e+00 6.34130597e-01
9.92151082e-01 5.60478568e-01 1.64850473e-01 8.38382244e-01
-5.57186186e-01 1.28269863e+00 -6.79455876e-01 -6.61764860e-01
1.19021110e-01 -2.85990417e-01 -1.09622085e+00 -4.33600396e-01
1.51760221e-01 -2.50525534e-01 -7.14259297e-02 4.42483217e-01
6.22161329e-01 -1.10266328e-01 7.13383928e-02 -1.41099310e+00
-6.03781521e-01 9.05955017e-01 -3.44284266e-01 -2.06423551e-01
7.71883309e-01 5.52375019e-01 1.38090837e+00 -8.43795002e-01
8.85618806e-01 1.30812824e+00 6.50897086e-01 5.02012312e-01
-1.38202512e+00 -3.64842236e-01 -2.70559281e-01 -1.04587995e-01
-1.26935291e+00 -3.68143111e-01 4.10683572e-01 -3.75374556e-01
1.67333698e+00 4.54076231e-01 7.31953084e-01 1.44700539e+00
3.87156248e-01 8.75128925e-01 1.17345941e+00 -2.67098993e-01
1.91909626e-01 2.84629226e-01 -3.37004364e-02 6.75977230e-01
-2.95480251e-01 -2.05129996e-01 -9.21800196e-01 -6.72827542e-01
3.28365415e-01 -4.27883625e-01 1.71079770e-01 -2.00365707e-01
-1.24838638e+00 1.02760303e+00 8.15923631e-05 3.71371686e-01
-2.32445877e-02 2.26711810e-01 7.35822558e-01 5.27069032e-01
5.70007324e-01 6.57825410e-01 -4.25871044e-01 -1.32378697e+00
-5.25599718e-01 4.99880552e-01 1.72225285e+00 1.28657913e+00
4.36219603e-01 -2.32658744e-01 -2.53672361e-01 1.07607055e+00
-2.19372839e-01 1.91499740e-01 3.24575126e-01 -1.14690590e+00
8.04767489e-01 7.93437064e-01 -1.11612655e-01 -6.90307915e-01
-1.12171449e-01 -5.29927015e-02 -2.38369390e-01 -2.57690638e-01
5.10675907e-01 -2.43740186e-01 -6.19128868e-02 1.44753420e+00
-3.12620550e-02 -2.73391485e-01 1.97896749e-01 4.23868865e-01
9.72990453e-01 9.63982582e-01 -1.70451358e-01 -3.25850137e-02
1.34182882e+00 -1.18267775e+00 -2.97884166e-01 -4.19211477e-01
1.03593135e+00 -1.03587914e+00 1.85071218e+00 3.55675638e-01
-1.17829132e+00 -1.14379823e-01 -5.83644748e-01 -8.20950791e-02
-3.12213153e-01 -5.34286164e-02 9.21182394e-01 6.76738620e-01
-1.22959745e+00 2.23885879e-01 -7.20033109e-01 -1.02423346e+00
-5.71471378e-02 -1.70192540e-01 -2.13759020e-01 4.94690519e-03
-9.72138941e-01 9.03095901e-01 1.24227777e-01 -3.79057795e-01
-7.43365228e-01 -6.05740011e-01 -2.98970401e-01 1.43980369e-01
8.01966190e-01 -5.48089921e-01 1.73396528e+00 -1.37088329e-01
-1.80651677e+00 7.48587370e-01 -8.11399221e-02 -4.64554816e-01
7.30884194e-01 -1.64477617e-01 4.54779528e-02 -4.56427708e-02
1.38125271e-01 4.67196018e-01 7.77859688e-02 -7.35933006e-01
-3.53857607e-01 6.32622838e-02 4.42381352e-01 1.23547144e-01
-3.40667129e-01 3.89175624e-01 -6.64610922e-01 -2.99372256e-01
-5.40185511e-01 -1.11634612e+00 5.69249094e-02 -2.24908650e-01
-3.77848685e-01 -5.89797914e-01 5.47458589e-01 -4.23984230e-01
1.20348728e+00 -1.85348809e+00 1.34664439e-02 -2.64868468e-01
1.23922534e-01 -4.80848690e-03 -4.01362658e-01 1.51187015e+00
3.34554702e-01 4.27888989e-01 -1.09923244e-01 -5.27612925e-01
1.16041027e-01 1.82906806e-01 -2.23371252e-01 -2.10186288e-01
1.15510002e-01 1.04086459e+00 -7.48124540e-01 -6.49545252e-01
1.02521136e-01 1.33481681e-01 -9.42322969e-01 5.19862890e-01
-6.80559635e-01 1.84974119e-01 -4.45956975e-01 6.17366552e-01
1.87968776e-01 -3.33475858e-01 3.65881085e-01 4.33987409e-01
-3.81633788e-01 7.22540617e-01 -4.79500592e-01 1.86162102e+00
-7.97011197e-01 6.91476166e-01 -1.65194437e-01 -5.38413405e-01
1.12820303e+00 1.54219449e-01 4.45911944e-01 -7.52866805e-01
-5.99143766e-02 2.67558366e-01 7.42705017e-02 -8.65038753e-01
6.88563287e-01 2.57457197e-01 -3.86034876e-01 8.59351814e-01
5.45017272e-02 -5.83659589e-01 6.70760274e-01 7.07908332e-01
1.41297758e+00 -2.62394957e-02 3.80680524e-02 -4.21287060e-01
1.78009063e-01 2.81679541e-01 6.21632785e-02 1.00418210e+00
9.34719667e-02 3.66364539e-01 1.23432803e+00 -2.62767583e-01
-1.00257397e+00 -8.02895188e-01 6.16356684e-03 1.49078143e+00
-3.51428181e-01 -1.12607849e+00 -7.75072813e-01 -5.22934794e-01
-1.13013908e-01 1.16713059e+00 -4.30166781e-01 2.04230100e-01
-4.79027748e-01 -7.50070214e-01 8.69685948e-01 1.36880875e-01
6.70866191e-01 -1.19092536e+00 -4.98015761e-01 3.28248680e-01
-6.39676869e-01 -1.10902607e+00 -4.26403880e-01 -1.14582978e-01
-6.53298020e-01 -9.78660047e-01 -3.54252666e-01 -5.75814426e-01
-2.17472650e-02 1.41153231e-01 1.53277194e+00 1.34663001e-01
-3.33233297e-01 5.81838310e-01 -7.33159661e-01 -2.61388302e-01
-8.11374247e-01 6.14632487e-01 -5.71645439e-01 -6.09944046e-01
3.81959081e-01 -6.86218202e-01 -3.05018365e-01 3.92545938e-01
-5.06936491e-01 3.72004777e-01 3.00972998e-01 8.36348116e-01
-2.19829246e-01 -2.71586359e-01 5.38923562e-01 -9.53561306e-01
1.29793751e+00 -6.15858197e-01 -4.87511814e-01 1.78633481e-01
-5.57875395e-01 -1.15561560e-01 3.76725346e-01 -2.57898241e-01
-1.15222323e+00 -6.24799371e-01 -3.47261935e-01 3.60116929e-01
2.49780148e-01 8.98720086e-01 2.61685729e-01 1.86464518e-01
8.18047106e-01 4.39435571e-01 3.06174666e-01 -4.13752466e-01
3.55815917e-01 7.95551062e-01 7.98389763e-02 -1.11406219e+00
4.15037155e-01 4.16809618e-02 -6.84885561e-01 -8.94515932e-01
-3.54880214e-01 -2.20831767e-01 1.25697240e-01 -2.03556955e-01
5.76758385e-01 -8.27159464e-01 -1.13953221e+00 4.71855879e-01
-1.14493179e+00 -8.25319886e-01 3.22722308e-02 -6.21808693e-02
-7.36738086e-01 3.50678802e-01 -9.82559323e-01 -8.60751867e-01
-6.56920910e-01 -1.18096542e+00 9.39218640e-01 -1.24988869e-01
-6.38308167e-01 -1.10097921e+00 2.85378695e-01 6.56338692e-01
8.28918874e-01 -1.60180200e-02 1.07835805e+00 -8.75027120e-01
-6.66976988e-01 -3.10341001e-01 -1.67217702e-01 7.47390538e-02
-1.82198226e-01 3.40473145e-01 -6.34363532e-01 -3.25205445e-01
1.57767963e-02 -6.76947713e-01 1.53478563e-01 -2.75876462e-01
8.55493724e-01 -5.55250227e-01 2.48189978e-02 2.48041734e-01
1.25853395e+00 1.03784226e-01 6.18335783e-01 5.24194956e-01
1.92487761e-01 6.43944502e-01 5.66823602e-01 6.98065519e-01
7.69866288e-01 8.43397915e-01 3.22841257e-01 3.15724224e-01
1.39371455e-01 -3.72483283e-01 5.93631625e-01 1.13159049e+00
4.53613028e-02 -4.84729081e-01 -1.33692992e+00 5.52222013e-01
-2.12500906e+00 -9.17229772e-01 -1.32744387e-01 1.85553157e+00
1.04070532e+00 3.32168221e-01 3.78907472e-01 -4.36140209e-01
2.21478403e-01 3.44033092e-01 -2.95318007e-01 -9.13298905e-01
-5.02541214e-02 -3.30641232e-02 -1.27199695e-01 2.24599451e-01
-3.29195291e-01 9.69678402e-01 6.63867760e+00 8.95320892e-01
-9.00493681e-01 1.13477796e-01 4.82635617e-01 -2.84027129e-01
-1.80411354e-01 2.25280732e-01 -6.36437893e-01 6.63989663e-01
1.12677431e+00 -9.05246913e-01 8.51368129e-01 9.43099141e-01
2.41711676e-01 -3.64528745e-01 -1.11353219e+00 7.28436410e-01
-8.46472457e-02 -1.45804346e+00 -1.45941883e-01 3.90274115e-02
4.08287793e-01 5.52384138e-01 -2.76699513e-01 8.53969514e-01
7.43942738e-01 -8.07258189e-01 5.67360997e-01 1.68314159e-01
5.88596344e-01 -4.95061547e-01 7.09759295e-01 6.53909624e-01
-1.04799402e+00 -5.85269555e-03 -2.43517488e-01 -3.27734232e-01
7.81866834e-02 3.60970110e-01 -1.25863087e+00 4.50837851e-01
8.58167827e-01 6.92569852e-01 -7.41607785e-01 7.97936976e-01
6.09535016e-02 8.06412160e-01 -3.38446438e-01 -5.89492023e-01
2.68446237e-01 -3.02298367e-01 5.53492069e-01 1.41759562e+00
4.21856344e-01 -4.22373554e-03 2.37475321e-01 1.04304612e+00
-2.22390257e-02 3.48499924e-01 -7.07639337e-01 -4.56490487e-01
7.21611738e-01 1.34412777e+00 -4.00453269e-01 -4.49585974e-01
-5.50105453e-01 5.62858224e-01 4.84077871e-01 7.25377128e-02
-8.83520603e-01 -4.01876628e-01 6.39030218e-01 1.50187299e-01
7.86221176e-02 -3.96521270e-01 -1.73131362e-01 -1.14883339e+00
2.95922279e-01 -1.34818804e+00 3.24335724e-01 -1.01098967e+00
-1.34240484e+00 8.92960191e-01 2.19314530e-01 -9.51460361e-01
-6.04014635e-01 -2.37512901e-01 -9.24449980e-01 6.13394022e-01
-6.49242997e-01 -1.12551165e+00 -3.68504137e-01 3.93172026e-01
7.92847514e-01 -3.20329189e-01 9.52779949e-01 1.29117936e-01
-5.07392466e-01 5.51699936e-01 1.50094241e-01 1.03171039e-02
7.15735316e-01 -1.13437700e+00 1.01982474e+00 3.65839273e-01
-1.33048967e-01 1.01979828e+00 9.62657332e-01 -5.38380206e-01
-1.86038530e+00 -6.90036774e-01 1.01331913e+00 -8.40680420e-01
1.23060083e+00 -9.35876012e-01 -7.86452711e-01 7.72755921e-01
7.03083873e-01 -6.88947678e-01 4.73976105e-01 4.09343153e-01
-4.01466787e-01 3.69050503e-02 -9.00160611e-01 9.04513240e-01
1.03956747e+00 -7.64585257e-01 -4.68490750e-01 6.72715187e-01
9.11073387e-01 -5.16422570e-01 -1.10595036e+00 -4.07980867e-02
5.27605653e-01 -1.38864040e+00 5.80153048e-01 -3.81791472e-01
8.43601346e-01 2.61931837e-01 -1.62754864e-01 -1.19852829e+00
2.68861473e-01 -1.11488724e+00 3.03863257e-01 1.51385343e+00
4.85720873e-01 -1.11096692e+00 7.25420237e-01 7.52642989e-01
-6.52730986e-02 -8.59010577e-01 -8.82791996e-01 -9.26314592e-01
3.07952464e-01 -4.94475335e-01 6.38967395e-01 7.64914215e-01
6.68658197e-01 5.37959397e-01 -5.16635239e-01 -6.41929686e-01
2.76603043e-01 1.59639254e-01 1.39082885e+00 -8.18428934e-01
-6.42358422e-01 -3.47271383e-01 2.41213754e-01 -1.05004597e+00
-6.08001910e-02 -9.80923891e-01 -4.71631214e-02 -1.48084724e+00
5.66825271e-01 -3.77506375e-01 6.26792669e-01 6.79586828e-01
9.98580977e-02 -1.87026829e-01 4.66408640e-01 2.39724383e-01
-6.78934753e-01 5.87469876e-01 9.77212429e-01 5.11855818e-02
-3.41642767e-01 -1.22618712e-02 -7.25951254e-01 1.99671343e-01
1.01092374e+00 -4.33763385e-01 -4.67262566e-01 -4.40401077e-01
4.51894790e-01 5.33382058e-01 7.01237023e-02 -8.67938340e-01
1.68716952e-01 -9.31368321e-02 -8.05593967e-01 -2.98977315e-01
5.96287608e-01 -1.71953678e-01 2.06211135e-01 3.88430983e-01
-4.69848096e-01 3.82125080e-01 2.82529503e-01 1.31930783e-01
-1.54335037e-01 -1.28950372e-01 2.39968836e-01 -2.67704397e-01
-2.76162416e-01 -7.09905848e-02 -8.77511859e-01 4.90656078e-01
7.92406619e-01 3.54205966e-02 -1.14764619e+00 -7.73660183e-01
-2.48000205e-01 3.97828102e-01 6.25038624e-01 7.21578360e-01
2.80599326e-01 -8.65993440e-01 -8.19556773e-01 6.41676784e-02
5.63858032e-01 -4.94440258e-01 4.87897061e-02 9.23216581e-01
-7.21019149e-01 5.85427463e-01 -1.43574566e-01 -6.62870407e-01
-1.36998963e+00 2.34539583e-01 1.35257974e-01 -4.01404947e-01
-6.03018999e-01 6.12854540e-01 -1.28181040e-01 -8.73364031e-01
9.11388993e-02 -2.35286206e-01 2.84208685e-01 -1.59091681e-01
2.02019185e-01 4.11901593e-01 5.85520342e-02 3.53071354e-02
-1.67808652e-01 1.46044686e-01 -2.33319595e-01 -2.55613655e-01
1.45693326e+00 1.31115794e-01 -5.68015695e-01 6.68305635e-01
1.15583909e+00 1.10746995e-01 -6.90783978e-01 -1.54891402e-01
1.21160254e-01 -5.16648054e-01 -6.14909708e-01 -8.99660170e-01
-7.64762282e-01 7.46962965e-01 -7.99130425e-02 7.04836905e-01
5.32689929e-01 9.68951583e-02 7.30945349e-01 7.10890591e-01
8.22962284e-01 -8.69436622e-01 3.99987608e-01 9.01885569e-01
1.28885424e+00 -1.03369689e+00 -1.73270151e-01 -4.32498574e-01
-1.01650810e+00 1.00818324e+00 7.37879694e-01 6.95277005e-02
2.73319423e-01 4.06667292e-01 2.86350697e-02 -2.94071823e-01
-1.70105040e+00 1.86765581e-01 -4.79825854e-01 2.42301807e-01
7.87432075e-01 1.55464571e-03 -3.81102979e-01 2.72860289e-01
-7.21486628e-01 1.04945466e-01 8.34601521e-01 1.19325244e+00
-1.38649940e-01 -1.38915253e+00 2.59655882e-02 5.56140840e-01
-2.38982335e-01 -3.57886910e-01 -6.84369266e-01 1.01927185e+00
-6.65417731e-01 1.21711040e+00 -1.10020995e-01 -4.44795787e-01
3.38656753e-01 2.38815203e-01 1.00651816e-01 -7.40239680e-01
-1.17364395e+00 -1.24638677e-01 9.84695256e-01 -7.16955900e-01
7.69877955e-02 -6.01104856e-01 -8.53361309e-01 -1.13226712e+00
-1.37549385e-01 5.22455573e-01 6.26126945e-01 4.15086806e-01
7.23462939e-01 2.17659384e-01 3.79299760e-01 -5.24449706e-01
-5.59470713e-01 -1.17353868e+00 -2.84293652e-01 1.65588319e-01
-3.94557387e-01 -2.75416940e-01 -4.03742701e-01 -3.38818878e-01] | [11.885993003845215, 8.286605834960938] |
158bd532-24ac-4966-b771-61cefd6357e5 | target-adaptive-cnn-based-pansharpening | 1709.06054 | null | http://arxiv.org/abs/1709.06054v3 | http://arxiv.org/pdf/1709.06054v3.pdf | Target-adaptive CNN-based pansharpening | We recently proposed a convolutional neural network (CNN) for remote sensing
image pansharpening obtaining a significant performance gain over the state of
the art. In this paper, we explore a number of architectural and training
variations to this baseline, achieving further performance gains with a
lightweight network which trains very fast. Leveraging on this latter property,
we propose a target-adaptive usage modality which ensures a very good
performance also in the presence of a mismatch w.r.t. the training set, and
even across different sensors. The proposed method, published online as an
off-the-shelf software tool, allows users to perform fast and high-quality
CNN-based pansharpening of their own target images on general-purpose hardware. | ['Sergio Vitale', 'Giuseppe Scarpa', 'Davide Cozzolino'] | 2017-09-18 | null | null | null | null | ['pansharpening'] | ['computer-vision'] | [ 7.40421176e-01 -2.17162684e-01 4.48513292e-02 -3.33931774e-01
-5.32558501e-01 -2.51041383e-01 2.11864322e-01 -9.98118743e-02
-6.50617599e-01 2.77300388e-01 -2.42506042e-01 -4.32649642e-01
-1.94155827e-01 -1.25321627e+00 -9.66568172e-01 -7.64573872e-01
-6.80656806e-02 -1.29840925e-01 4.32444841e-01 -4.79220808e-01
-6.15402982e-02 9.16401267e-01 -1.71019459e+00 -4.90493095e-03
6.69066966e-01 1.20540106e+00 2.32610300e-01 7.64294922e-01
3.30516428e-01 3.21761340e-01 -2.58722961e-01 -1.93203464e-01
8.84341359e-01 9.04658064e-02 -3.16365361e-01 -1.35769129e-01
1.04062796e+00 -4.23492491e-01 -1.42799571e-01 9.40977991e-01
5.50012767e-01 3.13262865e-02 3.63472803e-03 -6.74004853e-01
-4.40912187e-01 3.73463482e-01 -5.33695221e-01 4.03092206e-02
-3.28054249e-01 1.46112502e-01 8.87781024e-01 -5.20759225e-01
2.46349826e-01 3.84937912e-01 1.00561190e+00 3.39911610e-01
-1.09402049e+00 -7.87829697e-01 -2.07186267e-01 -6.05576411e-02
-1.20623446e+00 -3.68824154e-01 8.60551059e-01 -1.61020473e-01
9.86833394e-01 2.59743750e-01 7.40596414e-01 7.76218414e-01
1.80364221e-01 3.47410291e-01 1.03270543e+00 -5.48613191e-01
1.12847671e-01 -2.48710498e-01 -2.21114028e-02 4.75369245e-01
1.88301489e-01 4.16392535e-01 1.17735611e-02 4.06951793e-02
1.02014995e+00 -3.61356810e-02 -4.53373224e-01 -1.84825033e-01
-1.16738808e+00 5.19882739e-01 1.07447124e+00 5.16973078e-01
-5.97646117e-01 4.47104543e-01 2.82973558e-01 3.14503610e-01
3.71356219e-01 3.65291506e-01 -6.81850672e-01 2.23869920e-01
-1.24366212e+00 5.65673783e-02 3.78781199e-01 6.62392914e-01
1.13322926e+00 2.73692071e-01 3.48288834e-01 6.70350134e-01
3.35731395e-02 7.42159247e-01 2.56180137e-01 -4.10796225e-01
4.47205216e-01 3.92271578e-01 -2.94677075e-02 -1.11470997e+00
-6.06487572e-01 -7.45684147e-01 -1.19128799e+00 5.97240686e-01
9.91916135e-02 -1.56126529e-01 -9.91897047e-01 1.52695012e+00
2.65954077e-01 2.55548924e-01 4.41228524e-02 9.60865200e-01
6.51346684e-01 7.04814911e-01 -1.44161001e-01 1.64467260e-01
1.25640619e+00 -8.69782925e-01 -2.74199426e-01 -2.22594440e-01
1.85925320e-01 -7.62081146e-01 1.06697953e+00 7.12056398e-01
-6.56965792e-01 -8.97584856e-01 -1.54809856e+00 1.67584509e-01
-3.92333359e-01 4.65276927e-01 8.10419083e-01 9.80942667e-01
-1.14419079e+00 9.26840365e-01 -7.83920944e-01 -5.12026072e-01
3.71672899e-01 4.26712602e-01 -4.87785250e-01 1.61867097e-01
-9.79211926e-01 6.39894545e-01 5.81560254e-01 4.66777205e-01
-6.63526535e-01 -8.66106272e-01 -5.10385752e-01 1.72043905e-01
2.34034851e-01 -5.21566451e-01 1.08989704e+00 -1.40074193e+00
-1.81923842e+00 6.59693480e-01 4.29008842e-01 -6.49621129e-01
5.21016240e-01 -5.99193573e-01 -7.73891687e-01 7.35082328e-02
-5.09525716e-01 5.47188878e-01 1.15402365e+00 -9.45993543e-01
-4.94927645e-01 -2.29561850e-01 1.03487372e-01 -1.96761340e-01
-5.00797987e-01 -3.34892683e-02 -3.52072045e-02 -5.90833187e-01
6.74425885e-02 -7.99821734e-01 -2.61145562e-01 3.11656326e-01
-1.26488373e-01 4.76979196e-01 9.41293478e-01 -6.20378435e-01
7.64467478e-01 -2.11039758e+00 -3.01437497e-01 5.02252996e-01
2.04758439e-03 7.81458616e-01 -2.28378192e-01 3.18683386e-01
-3.90940428e-01 -1.91925958e-01 -5.25884748e-01 -2.49334425e-02
-3.68342936e-01 1.24347225e-01 -2.43627861e-01 7.85422385e-01
2.26087064e-01 7.28609204e-01 -5.79573154e-01 -3.46275792e-02
5.97192705e-01 6.76547468e-01 -2.27881849e-01 2.08326250e-01
-1.59831390e-01 2.65948653e-01 -1.55737862e-01 7.04211831e-01
1.10483658e+00 1.00719713e-01 -3.75619754e-02 -6.11199498e-01
-4.34706211e-01 -3.07616562e-01 -1.23493350e+00 1.63711452e+00
-7.53180563e-01 7.90857494e-01 3.03414881e-01 -9.18202460e-01
1.30594563e+00 1.85127810e-01 3.51357788e-01 -8.01630855e-01
2.82315701e-01 4.56908524e-01 -1.66375101e-01 -1.98092520e-01
7.25624442e-01 -1.36256814e-01 4.45079416e-01 2.61482775e-01
-3.55574228e-02 -7.75885582e-02 -2.61183947e-01 -2.99913555e-01
7.78367817e-01 1.98051497e-01 4.08708602e-01 -6.18736267e-01
5.99433661e-01 -1.00500487e-01 1.95842400e-01 8.20701778e-01
-5.84064089e-02 7.10910439e-01 -2.00301558e-01 -7.86155820e-01
-1.44990015e+00 -7.44294822e-01 -1.82454020e-01 1.05616486e+00
-6.25184253e-02 9.59982425e-02 -7.10598350e-01 -1.39278159e-01
-2.45940447e-01 1.36133775e-01 -7.71696866e-01 1.42233640e-01
-8.61950159e-01 -8.83754671e-01 6.62388742e-01 5.08673668e-01
1.21001005e+00 -9.29523945e-01 -1.17783189e+00 2.64818549e-01
3.18536222e-01 -1.02085626e+00 1.47841277e-03 2.33517975e-01
-1.04236841e+00 -8.72135878e-01 -6.82551444e-01 -5.48982143e-01
2.41554871e-01 4.71245617e-01 9.92051423e-01 4.48120534e-02
-1.58208117e-01 2.20928993e-02 -4.91299510e-01 -4.67772722e-01
-2.97362715e-01 3.46155047e-01 -3.36924195e-01 2.53991902e-01
-1.44469819e-03 -9.24976528e-01 -7.74199724e-01 1.29320994e-01
-1.38935614e+00 1.33816540e-01 8.14344943e-01 5.80812454e-01
4.33131486e-01 1.27269447e-01 1.29837498e-01 -6.87726676e-01
1.94611400e-01 -1.13315560e-01 -1.13475513e+00 2.22278953e-01
-6.91626251e-01 -6.02621026e-02 6.95824862e-01 -3.58036488e-01
-1.06658626e+00 3.08500975e-01 -5.09951413e-01 -2.12934166e-01
-4.02828991e-01 5.93501806e-01 -1.13975704e-01 -7.04566419e-01
1.00117075e+00 8.87681469e-02 -1.03148900e-01 -6.76799655e-01
4.39556032e-01 7.65887976e-01 9.87026334e-01 -2.96796501e-01
1.15663731e+00 7.73172379e-01 2.08003417e-01 -1.11613488e+00
-6.71836674e-01 -6.55884504e-01 -6.35179579e-01 -3.47888917e-01
6.60298109e-01 -9.83658671e-01 -4.49845165e-01 1.00194967e+00
-8.72919083e-01 -6.02735341e-01 -9.71911028e-02 3.60101789e-01
-2.76231498e-01 3.38587821e-01 -1.12689614e-01 -4.93399501e-01
-8.76505196e-01 -7.13570893e-01 9.10179675e-01 4.13905531e-01
4.45402503e-01 -7.91130960e-01 2.77747542e-01 -1.14452593e-01
1.02971137e+00 6.75589979e-01 3.41467798e-01 -2.12640569e-01
-5.46276808e-01 -3.49397659e-01 -5.44863701e-01 6.68835759e-01
-6.43892074e-03 4.23011124e-01 -1.27815878e+00 -4.87354457e-01
6.33101463e-02 -1.13537528e-01 1.09483325e+00 3.29345077e-01
9.93179858e-01 -1.96098581e-01 -6.77687526e-02 1.11188507e+00
2.14435530e+00 -2.92904019e-01 1.32161248e+00 7.21964836e-01
7.74910867e-01 2.00138882e-01 4.35886115e-01 3.17548692e-01
-2.68697500e-01 6.99458420e-01 8.97955775e-01 -5.90982020e-01
3.50061506e-02 5.03861979e-02 3.64241675e-02 1.88404694e-01
-4.13274378e-01 -1.37515798e-01 -8.14656734e-01 6.59516454e-01
-1.57033741e+00 -8.14285040e-01 -2.96158850e-01 2.25982618e+00
4.63291556e-01 2.70656906e-02 -1.78565815e-01 2.62747616e-01
5.53445160e-01 5.04914224e-01 -2.10313261e-01 -2.29361594e-01
-2.40834326e-01 8.51398647e-01 1.25855935e+00 3.96071762e-01
-1.45365691e+00 8.82388711e-01 6.10286427e+00 7.78372288e-01
-1.72460997e+00 1.46503553e-01 1.26356527e-01 3.20742607e-01
5.57017811e-02 -1.10493913e-01 -4.04516041e-01 -1.99315771e-01
8.22966754e-01 3.08935374e-01 2.87569910e-01 9.13031042e-01
7.08363056e-02 -1.56054482e-01 -5.01772583e-01 8.51279914e-01
-7.14610964e-02 -1.36158144e+00 -2.70534575e-01 -9.80792493e-02
7.97109246e-01 7.05777168e-01 5.43337241e-02 -1.99607462e-01
7.95410499e-02 -8.22087109e-01 6.41955197e-01 2.23370820e-01
9.59111571e-01 -7.19654858e-01 9.33384657e-01 7.39348531e-02
-1.34225976e+00 -1.17004216e-01 -4.05050963e-01 -1.61756501e-01
-5.79266772e-02 9.64194179e-01 -5.02554059e-01 9.10016775e-01
8.34887266e-01 5.45626044e-01 -6.34669185e-01 1.09142387e+00
-2.35012338e-01 6.93736672e-01 -6.79087996e-01 2.93487817e-01
4.46490616e-01 -3.18279713e-02 3.14287841e-01 1.46286416e+00
5.06599784e-01 4.89010883e-04 -1.78515881e-01 6.58029318e-01
1.05178043e-01 1.33274481e-01 -3.82828593e-01 2.41155460e-01
-4.06870097e-02 1.48989320e+00 -5.94293296e-01 -2.06284299e-01
-2.61205494e-01 7.44226336e-01 5.94264315e-03 1.13685288e-01
-8.66068006e-01 -6.28648639e-01 4.76683497e-01 -3.24376188e-02
5.50883889e-01 -2.97580630e-01 -2.03687623e-01 -1.14838612e+00
2.35188738e-01 -6.83119893e-01 1.98368937e-01 -6.87572718e-01
-9.08427000e-01 7.97024310e-01 6.48844019e-02 -1.37333584e+00
3.36250693e-01 -8.19791257e-01 -6.22015178e-01 8.45169246e-01
-2.01073670e+00 -1.50117278e+00 -9.16428745e-01 6.67503536e-01
2.99205612e-02 4.36561008e-04 8.58211279e-01 3.05994719e-01
-2.86415368e-01 4.51683462e-01 1.80402026e-01 1.00734115e-01
4.55538750e-01 -8.07931602e-01 7.36128211e-01 1.27693880e+00
1.50397211e-01 2.50272095e-01 7.96352267e-01 -3.24944049e-01
-1.12141359e+00 -1.29738104e+00 5.40640593e-01 2.02548027e-01
4.98719811e-01 -1.83206871e-01 -9.94843066e-01 6.49565399e-01
4.08328921e-01 9.76928025e-02 3.81839305e-01 -1.90088421e-01
-6.43921793e-01 -6.41708493e-01 -1.27860355e+00 3.69323641e-01
7.06897855e-01 -4.16311741e-01 -4.45387453e-01 1.11510515e-01
5.41228354e-01 -5.19338310e-01 -7.43527889e-01 6.98679090e-01
6.87072575e-01 -1.37448490e+00 9.36912477e-01 -3.49246748e-02
4.05708671e-01 -4.37001079e-01 -2.41579920e-01 -1.08091486e+00
-3.48351806e-01 -7.37291336e-01 2.40926787e-01 7.00086772e-01
3.21370542e-01 -8.17300498e-01 6.65017545e-01 1.51203014e-02
-2.72015840e-01 -2.53438860e-01 -8.62908483e-01 -7.40248382e-01
-1.01733834e-01 -6.66040659e-01 7.85844326e-01 6.96040332e-01
-5.35288036e-01 -1.11237586e-01 -6.74138129e-01 6.93740666e-01
7.05515504e-01 1.81907609e-01 9.95360494e-01 -1.21168160e+00
-3.88997972e-01 -1.67803928e-01 -5.60609102e-01 -9.50284421e-01
-3.41614366e-01 -2.83742100e-01 2.25797355e-01 -1.09330750e+00
-2.51443803e-01 -4.79432374e-01 -3.28941852e-01 6.33299351e-01
1.43869430e-01 8.18960190e-01 7.02402741e-02 1.87170804e-01
1.06485765e-02 2.97558874e-01 8.56953561e-01 -1.04706153e-01
-1.50950819e-01 2.63523944e-02 -3.98368686e-01 4.85354424e-01
1.30472803e+00 -4.06683236e-01 1.96200162e-02 -7.38130927e-01
4.01492804e-01 -4.29486513e-01 6.56232715e-01 -1.79116559e+00
1.05642475e-01 -1.29073812e-02 1.36795104e-01 -4.64088172e-01
1.85321167e-01 -1.30402243e+00 6.32463992e-01 5.69117010e-01
-7.32847350e-03 -2.33213082e-01 5.34445524e-01 2.77588844e-01
-1.40457183e-01 -5.65523878e-02 1.29322028e+00 -1.10457167e-01
-7.84149230e-01 3.65737379e-01 -1.26955612e-03 -6.26246631e-01
8.28237355e-01 -3.51233989e-01 -4.02683109e-01 -1.56473041e-01
-3.19997430e-01 -5.71685612e-01 4.94173080e-01 1.64439380e-01
4.76220876e-01 -1.06006420e+00 -7.68968642e-01 4.28345531e-01
2.20113173e-01 -3.70857753e-02 5.21387815e-01 7.06923902e-01
-1.09003305e+00 2.17414498e-01 -7.21790373e-01 -5.33017099e-01
-1.16028631e+00 4.33224976e-01 6.84526801e-01 -1.69262007e-01
-8.30799699e-01 6.52052641e-01 -3.34247768e-01 -4.43092614e-01
-1.94657892e-01 -4.73241776e-01 -1.16271824e-02 -2.77653009e-01
7.59686947e-01 2.33948573e-01 5.51150501e-01 -4.84760374e-01
-1.71749830e-01 7.87261128e-01 2.59030938e-01 1.58063173e-02
1.57581115e+00 1.58513874e-01 -3.11376806e-02 -2.48747729e-02
1.08245051e+00 2.48503238e-02 -1.39233363e+00 -3.77167434e-01
-4.04658645e-01 -7.15431333e-01 5.16059816e-01 -5.86537957e-01
-1.49283266e+00 8.55937362e-01 1.02949119e+00 2.06072330e-01
1.56794846e+00 -4.41484034e-01 8.17638516e-01 5.54999769e-01
2.85153121e-01 -9.85832870e-01 -2.77864903e-01 3.41813952e-01
6.83042288e-01 -1.15532994e+00 2.10359633e-01 -2.86324412e-01
-1.35500655e-01 1.58155954e+00 2.90336341e-01 -5.61863720e-01
7.16676056e-01 2.86288887e-01 4.25344884e-01 -2.77182519e-01
-1.53237849e-01 -4.03523505e-01 8.33942220e-02 8.90308022e-01
1.70404598e-01 3.04942399e-01 8.70438386e-03 -3.10748249e-01
-5.50898984e-02 3.72525603e-01 4.52318132e-01 7.65859127e-01
-5.94117224e-01 -8.45151782e-01 -5.30018568e-01 2.04612598e-01
-4.74492848e-01 -2.17853859e-01 -6.05704729e-03 9.06624794e-01
2.76186287e-01 6.63731813e-01 2.93991733e-02 -4.87106830e-01
5.31103790e-01 -4.30205852e-01 2.65000582e-01 -5.71886487e-02
-1.00180280e+00 -5.57792075e-02 6.66518435e-02 -7.13729322e-01
-9.88061368e-01 -2.88148403e-01 -5.02539873e-01 -4.51937079e-01
-6.08749688e-01 -3.53914052e-01 9.08215284e-01 7.50578582e-01
1.60041302e-01 3.48332256e-01 6.73942983e-01 -1.13974118e+00
-4.58533883e-01 -9.95417774e-01 -5.82491398e-01 5.81254773e-02
4.97136056e-01 -2.85878330e-01 -1.73983082e-01 -3.00465841e-02] | [9.916291236877441, -1.796412467956543] |
31be16b0-59cb-4cc2-904d-466f4a8b0e44 | artgraph-towards-an-artistic-knowledge-graph | 2105.15028 | null | https://arxiv.org/abs/2105.15028v2 | https://arxiv.org/pdf/2105.15028v2.pdf | Integrating Contextual Knowledge to Visual Features for Fine Art Classification | Automatic art analysis has seen an ever-increasing interest from the pattern recognition and computer vision community. However, most of the current work is mainly based solely on digitized artwork images, sometimes supplemented with some metadata and textual comments. A knowledge graph that integrates a rich body of information about artworks, artists, painting schools, etc., in a unified structured framework can provide a valuable resource for more powerful information retrieval and knowledge discovery tools in the artistic domain. To this end, this paper presents ArtGraph: an artistic knowledge graph based on WikiArt and DBpedia. The graph, implemented in Neo4j, already provides knowledge discovery capabilities without having to train a learning system. In addition, the embeddings extracted from the graph are used to inject "contextual" knowledge into a deep learning model to improve the accuracy of artwork attribute prediction tasks. | ['Gennaro Vessio', 'Giovanni Sansaro', 'Giovanna Castellano'] | 2021-05-31 | null | null | null | null | ['art-analysis'] | ['computer-vision'] | [-1.27703369e-01 -1.01824552e-01 -3.28648895e-01 -2.31650203e-01
-3.20991711e-03 -6.13486469e-01 7.73959994e-01 3.80920768e-01
-7.86220431e-02 6.80826008e-01 1.73309475e-01 1.71863988e-01
-3.32171440e-01 -1.38262045e+00 -4.67977494e-01 -4.07203317e-01
4.05956388e-01 5.60184658e-01 2.11886883e-01 -1.17435917e-01
3.47669959e-01 6.16082788e-01 -1.72077227e+00 2.89788216e-01
5.29303253e-01 1.10063100e+00 3.19641083e-01 5.54939732e-02
-9.59062397e-01 1.04267597e+00 -3.80659163e-01 -1.18358171e+00
-6.23567179e-02 9.69720408e-02 -8.75245214e-01 -2.72782035e-02
6.67148292e-01 2.17054367e-01 -3.72053742e-01 1.03503299e+00
3.11801940e-01 -4.05066684e-02 7.01705337e-01 -1.12425637e+00
-1.08865547e+00 7.88252294e-01 -2.01612458e-01 3.49990241e-02
1.97486699e-01 -9.34794545e-02 9.92632210e-01 -7.16909289e-01
1.02759802e+00 1.11225355e+00 5.60807168e-01 1.81891516e-01
-9.38591599e-01 -6.02459252e-01 -1.07345231e-01 6.75651610e-01
-1.48064375e+00 3.25766355e-02 1.19985247e+00 -7.19471753e-01
6.10219836e-01 4.25458215e-02 1.10777271e+00 9.75592256e-01
-1.90855861e-01 6.19420588e-01 8.41616392e-01 -4.86991614e-01
1.34745613e-01 3.44563127e-01 1.07677825e-01 9.96420324e-01
2.12459087e-01 -5.26922822e-01 -6.49866402e-01 2.05307856e-01
1.10186255e+00 3.58641714e-01 3.00134905e-02 -5.84567010e-01
-9.25691187e-01 7.77631044e-01 7.71593809e-01 5.94976902e-01
-4.62642699e-01 2.06321806e-01 3.56709301e-01 2.12133422e-01
4.98188585e-01 6.38168156e-01 -2.07635269e-01 -9.64203626e-02
-6.48257554e-01 5.42763397e-02 7.61722088e-01 7.99561262e-01
1.16551793e+00 2.39048637e-02 1.78281888e-01 1.16724169e+00
2.29321733e-01 5.09519875e-01 2.73474336e-01 -6.95552409e-01
3.48885030e-01 1.39988780e+00 -3.18947613e-01 -1.29923534e+00
-2.21279532e-01 -5.19209802e-01 -6.47402942e-01 1.34975702e-01
2.46793851e-01 3.92888486e-01 -7.11761355e-01 1.13070941e+00
2.60235697e-01 2.40534812e-01 -1.27231985e-01 7.82550156e-01
1.10703385e+00 2.17857093e-01 2.15789065e-01 3.09522659e-01
1.56034446e+00 -7.74422765e-01 -7.85450637e-01 6.34508161e-03
2.14277774e-01 -7.70274699e-01 1.09554434e+00 1.96714267e-01
-7.33837306e-01 -4.33402568e-01 -8.54330480e-01 -3.23530436e-01
-1.07360816e+00 1.12918638e-01 8.06137800e-01 3.11953306e-01
-7.91154504e-01 4.25783217e-01 -5.21360815e-01 -5.70596039e-01
8.98949742e-01 2.30267067e-02 -4.53359723e-01 -3.19543898e-01
-1.00774169e+00 9.76269245e-01 5.43648839e-01 -2.03686371e-01
-4.57824349e-01 -7.61615813e-01 -8.73691142e-01 9.58600733e-03
6.23637736e-01 -7.47683465e-01 6.82770669e-01 -9.53009248e-01
-1.27783084e+00 1.17152321e+00 3.01154017e-01 -4.10542250e-01
1.14402004e-01 -3.29143524e-01 -7.23263979e-01 -2.56869639e-03
1.18146501e-01 4.20850158e-01 7.10562587e-01 -1.18193507e+00
-4.15900618e-01 -8.13191712e-01 1.69496179e-01 1.60514563e-02
-6.93397462e-01 -1.67883724e-01 -8.82647634e-01 -8.61518443e-01
-1.35442674e-01 -6.35034323e-01 2.10349470e-01 -5.58476560e-02
-3.56222570e-01 -5.15277624e-01 7.74645567e-01 -4.20103043e-01
1.43707871e+00 -1.97893941e+00 3.00698787e-01 3.56303543e-01
1.65904745e-01 2.80754358e-01 7.67737180e-02 5.64014137e-01
2.22950086e-01 1.14331961e-01 2.82706115e-02 8.63670632e-02
5.73234782e-02 2.21098647e-01 -1.73044577e-01 -1.75541312e-01
8.07762444e-02 8.79229486e-01 -9.54315782e-01 -6.99675322e-01
5.29355824e-01 7.62653232e-01 -7.80193061e-02 -1.82515576e-01
-4.62084204e-01 4.05305997e-02 -6.97983563e-01 7.86016643e-01
2.58039892e-01 -3.83350760e-01 2.50725120e-01 -5.01959205e-01
-1.65967196e-01 4.52610776e-02 -9.63993192e-01 2.09604883e+00
-7.98321426e-01 7.82772362e-01 -2.99981534e-01 -7.49406993e-01
1.20502925e+00 1.35352984e-01 5.46335340e-01 -7.16450453e-01
7.60146752e-02 -6.14840817e-03 -3.85872662e-01 -6.86775923e-01
3.89700085e-01 -1.93397924e-02 9.91120636e-02 2.79952526e-01
1.38632536e-01 -5.19858813e-03 3.43318582e-01 2.42236704e-01
1.06323612e+00 2.10651785e-01 7.09765702e-02 3.82340513e-02
6.61443949e-01 2.58421659e-01 1.32345214e-01 1.86745569e-01
4.24074471e-01 1.81883290e-01 4.04362977e-02 -9.19431746e-01
-1.05101681e+00 -1.20295334e+00 -2.73953944e-01 9.47214663e-01
1.52953221e-02 -7.08595276e-01 -4.46403801e-01 -6.88628197e-01
3.06052923e-01 5.10589421e-01 -4.65980411e-01 1.07537083e-01
-3.13603371e-01 -1.64297104e-01 3.37573826e-01 4.78675663e-01
8.73269856e-01 -1.46014786e+00 -2.83628047e-01 1.20398663e-01
-7.70613328e-02 -1.03384888e+00 8.80636647e-02 -2.22330973e-01
-7.25682735e-01 -1.28776455e+00 -3.71284783e-01 -1.00742686e+00
4.78927642e-01 -1.50384158e-01 1.42861271e+00 1.19987063e-01
-6.45344675e-01 6.48141503e-01 -6.12002790e-01 -5.86671472e-01
-4.07467447e-02 2.45574519e-01 -2.48770192e-01 1.56098083e-01
8.03832769e-01 -7.39689469e-01 -2.64976114e-01 3.36017050e-02
-9.58217204e-01 2.89999433e-02 6.31169677e-01 3.64995182e-01
6.74719274e-01 3.38673919e-01 5.23460984e-01 -9.53128159e-01
3.05416077e-01 -3.91544908e-01 -4.91657227e-01 4.08644050e-01
-5.64383268e-01 2.85324961e-01 4.96967018e-01 -1.14159420e-01
-1.14405811e+00 1.14635952e-01 -6.79675937e-02 -5.03533721e-01
-3.16778451e-01 6.91893935e-01 -4.66907531e-01 5.41358255e-02
5.47128499e-01 8.27390477e-02 -2.25454926e-01 -1.00296891e+00
7.18426824e-01 6.52717650e-01 6.67227924e-01 -4.78248328e-01
7.29862273e-01 4.44685489e-01 1.12883426e-01 -8.48265827e-01
-1.05526996e+00 -5.30596912e-01 -8.79517376e-01 -3.76222581e-01
8.81011248e-01 -8.10855210e-01 -6.31030798e-01 1.97575048e-01
-9.88884747e-01 -1.32946745e-02 -4.25523520e-01 4.19279635e-01
-3.23867887e-01 7.12351277e-02 -2.78422683e-01 -5.17506063e-01
-2.05964312e-01 -5.38038731e-01 7.66554356e-01 2.64251679e-01
-2.21633363e-05 -1.14000118e+00 9.26425308e-02 6.89805627e-01
1.71355799e-01 3.18228483e-01 1.16720760e+00 -5.35033405e-01
-8.53189766e-01 -2.52375513e-01 -3.57084483e-01 2.66687661e-01
2.66303062e-01 -7.88844973e-02 -8.69948924e-01 5.02171338e-01
-6.24288023e-01 -2.41823748e-01 9.82283473e-01 1.65761728e-02
1.36889422e+00 -3.04382533e-01 -2.94750094e-01 4.59022611e-01
1.82787490e+00 1.19446263e-01 7.94687033e-01 6.82767868e-01
1.21679831e+00 4.64650303e-01 1.76838800e-01 4.30070341e-01
5.66101611e-01 6.94490612e-01 5.27067542e-01 3.47163886e-01
-4.21991140e-01 -3.58364880e-01 -9.43345800e-02 8.22514653e-01
-5.14095426e-01 -1.61949247e-01 -1.18881035e+00 6.29290879e-01
-1.87975371e+00 -1.16867185e+00 -1.22144282e-01 2.03656983e+00
9.01058495e-01 -1.41108572e-01 -1.06935874e-01 2.10551232e-01
6.31678820e-01 9.62580219e-02 -3.33781958e-01 -2.21061796e-01
-1.72837853e-01 4.50817019e-01 2.77167618e-01 6.33620098e-02
-1.16437685e+00 1.28887129e+00 5.25612259e+00 8.79209340e-01
-8.75999451e-01 -4.83111031e-02 -8.35399851e-02 1.51581526e-01
-1.97603121e-01 -7.66509250e-02 -5.22618890e-01 4.50722188e-01
5.15600204e-01 -8.03860873e-02 5.04573226e-01 1.06432462e+00
-3.76115382e-01 2.24023491e-01 -1.02760363e+00 1.37838352e+00
2.09599152e-01 -1.89407682e+00 4.08704340e-01 5.29836006e-02
5.60277760e-01 -2.30114818e-01 -4.95838337e-02 3.22847396e-01
5.96997082e-01 -9.23798323e-01 3.17689836e-01 1.00767112e+00
6.04515016e-01 -8.84275675e-01 8.04261148e-01 -7.90465251e-02
-1.27408171e+00 6.64706528e-02 -3.99657160e-01 -1.23376667e-01
-4.25981265e-03 7.33656347e-01 -6.73512220e-01 7.48799801e-01
8.52742136e-01 1.16913176e+00 -8.36287022e-01 1.12089145e+00
-4.58754212e-01 4.26532865e-01 -3.01514491e-02 -1.23219565e-01
-2.04405412e-02 -1.48924440e-01 2.27637723e-01 9.97656107e-01
2.20325947e-01 -1.38606802e-01 1.61763072e-01 7.33505487e-01
-5.52565813e-01 4.50046152e-01 -8.08617711e-01 -4.69147503e-01
4.82594550e-01 1.46049309e+00 -7.26555228e-01 -3.10037076e-01
-4.38509524e-01 6.63564503e-01 5.08112311e-01 8.53221714e-02
-5.64441204e-01 -5.20367265e-01 5.62459767e-01 3.73463959e-01
3.38417143e-01 -1.89975843e-01 -2.87551731e-01 -1.09479058e+00
-9.39523950e-02 -3.17842096e-01 3.59610051e-01 -1.13691258e+00
-1.64301956e+00 4.12755758e-01 -2.32541889e-01 -1.01080859e+00
-7.39870418e-04 -7.18421638e-01 -4.27902669e-01 3.94275784e-01
-1.39303839e+00 -1.46461666e+00 -5.39187908e-01 7.39841878e-01
3.60416859e-01 -5.53368330e-01 9.54487085e-01 5.47283590e-01
-5.43145120e-01 1.37789831e-01 9.02395174e-02 6.15149677e-01
5.98306000e-01 -1.33981442e+00 -1.26423806e-01 2.34310165e-01
7.50531435e-01 3.95407766e-01 2.64760554e-01 -7.43336618e-01
-1.39411211e+00 -1.24234653e+00 8.46339941e-01 -7.79319346e-01
1.00713849e+00 -5.74664623e-02 -8.66777003e-01 5.70084214e-01
1.91386059e-01 -1.76067606e-01 8.71541321e-01 5.11489511e-01
-6.04940891e-01 -3.80676270e-01 -7.41561949e-01 5.01627684e-01
1.28039300e+00 -6.12677097e-01 -7.96777546e-01 4.18319255e-01
4.26407814e-01 6.99216872e-02 -1.37117493e+00 -6.39957516e-03
5.88038504e-01 -5.39322495e-01 1.21209049e+00 -5.72478294e-01
6.26033545e-01 -2.74893105e-01 -9.01381597e-02 -1.07015276e+00
-3.30193132e-01 1.10754646e-01 -1.37519076e-01 1.56521606e+00
2.43508264e-01 -1.14903830e-01 9.95162070e-01 4.26020384e-01
-1.53933644e-01 -3.03704679e-01 -6.05366945e-01 -8.03544223e-01
-3.93461555e-01 -5.69318473e-01 8.28040540e-01 1.24561632e+00
-1.87734246e-01 7.13691473e-01 -2.06504673e-01 -1.63485542e-01
6.03216887e-01 4.33325142e-01 7.92433262e-01 -2.07187510e+00
1.59805760e-01 -5.53808033e-01 -1.07625782e+00 -1.85841903e-01
1.56311199e-01 -1.37853289e+00 -5.98583043e-01 -2.19226718e+00
1.61287919e-01 -5.76179922e-01 -3.76396209e-01 8.01870346e-01
3.28714073e-01 5.43472111e-01 2.98419565e-01 3.02245617e-01
-7.96576917e-01 4.74446714e-01 1.21708393e+00 -5.26593268e-01
-1.25787959e-01 -3.83340627e-01 -4.42240298e-01 1.05045831e+00
9.50613797e-01 -3.81922394e-01 -2.72376567e-01 -6.94891334e-01
7.22858906e-01 -6.18066609e-01 6.25170171e-01 -1.13814771e+00
2.88019478e-01 -1.92610826e-02 3.92784387e-01 -5.04464507e-01
4.29185420e-01 -1.24490285e+00 4.07483280e-01 5.06208353e-02
-1.09441333e-01 -2.23855913e-01 3.07804365e-02 6.91629767e-01
-4.69813198e-01 -2.60465652e-01 3.56880933e-01 -2.37828970e-01
-1.18751872e+00 3.97540301e-01 1.02095887e-01 2.11543497e-02
8.38748097e-01 -1.29371002e-01 -4.00600910e-01 1.10091142e-01
-1.00726461e+00 -5.36247231e-02 5.85543394e-01 6.64381206e-01
4.86810982e-01 -1.61283088e+00 -3.73082668e-01 4.03633080e-02
5.60737848e-01 -8.25509578e-02 2.19377577e-01 2.35813498e-01
-7.17918634e-01 1.99753001e-01 -5.11647820e-01 -3.03812265e-01
-1.13004470e+00 7.20719278e-01 -2.45527208e-01 -2.16319427e-01
-7.59703040e-01 5.57821691e-01 -3.72260213e-01 -1.84274912e-01
3.03292781e-01 8.06150883e-02 -6.22537851e-01 3.76944363e-01
2.90134609e-01 3.38557988e-01 -3.82792540e-02 -6.14367306e-01
-4.16673899e-01 8.88808489e-01 2.27691084e-01 1.66268125e-01
1.61862373e+00 7.37391189e-02 -3.56162667e-01 6.06969118e-01
8.92872274e-01 3.26059456e-03 -7.03100681e-01 -5.26889503e-01
3.19623977e-01 -5.78290284e-01 2.40139768e-01 -1.10590112e+00
-1.46650314e+00 1.03067303e+00 4.75621641e-01 3.19642723e-01
9.58672643e-01 3.88501167e-01 4.55863178e-01 7.87883997e-01
5.43989241e-01 -1.15721846e+00 2.72223979e-01 2.96263665e-01
9.76292253e-01 -1.09336376e+00 2.54139632e-01 -4.00576144e-01
-6.88188076e-01 1.34013259e+00 4.84697104e-01 -4.58004102e-02
9.28201616e-01 3.91989090e-02 -3.40384878e-02 -7.00172961e-01
-3.12564313e-01 -5.58120310e-01 5.60746372e-01 7.77187824e-01
3.82739663e-01 -8.61157477e-03 -1.20673522e-01 6.93242013e-01
-3.43116850e-01 2.04825237e-01 1.10968493e-01 6.42436862e-01
-6.26641631e-01 -1.32782829e+00 -1.45196915e-01 5.27157903e-01
-3.70576710e-01 -1.70625463e-01 -7.48183250e-01 9.37692821e-01
6.67433679e-01 4.89067167e-01 3.99165362e-01 -2.56319255e-01
3.11248362e-01 2.27440268e-01 5.24796665e-01 -6.53237224e-01
-6.23311341e-01 -2.61726081e-01 5.48693128e-02 -3.11737806e-01
-8.16132128e-01 -2.07824484e-01 -1.05588353e+00 -4.16521609e-01
-5.83275370e-02 1.03919590e-02 8.77828419e-01 7.60314345e-01
3.94664019e-01 6.79607630e-01 1.34895995e-01 -4.34570283e-01
5.35560012e-01 -7.69001424e-01 -7.06034184e-01 6.51863515e-01
-4.76470232e-01 -9.02897656e-01 7.66635686e-02 3.99663955e-01] | [11.237228393554688, 0.4804358184337616] |
e079e46c-8574-4175-9204-19291aa2d2da | federated-transfer-ordered-personalized | 2301.04829 | null | https://arxiv.org/abs/2301.04829v2 | https://arxiv.org/pdf/2301.04829v2.pdf | Federated Transfer-Ordered-Personalized Learning for Driver Monitoring Application | Federated learning (FL) shines through in the internet of things (IoT) with its ability to realize collaborative learning and improve learning efficiency by sharing client model parameters trained on local data. Although FL has been successfully applied to various domains, including driver monitoring applications (DMAs) on the internet of vehicles (IoV), its usages still face some open issues, such as data and system heterogeneity, large-scale parallelism communication resources, malicious attacks, and data poisoning. This paper proposes a federated transfer-ordered-personalized learning (FedTOP) framework to address the above problems and test on two real-world datasets with and without system heterogeneity. The performance of the three extensions, transfer, ordered, and personalized, is compared by an ablation study and achieves 92.32% and 95.96% accuracy on the test clients of two datasets, respectively. Compared to the baseline, there is a 462% improvement in accuracy and a 37.46% reduction in communication resource consumption. The results demonstrate that the proposed FedTOP can be used as a highly accurate, streamlined, privacy-preserving, cybersecurity-oriented, and personalized framework for DMA. | ['Ziran Wang', 'Lu Su', 'Liangqi Yuan'] | 2023-01-12 | null | null | null | null | ['data-poisoning'] | ['adversarial'] | [-3.67634177e-01 -1.89319879e-01 -6.25725865e-01 -5.88012934e-01
-6.48222268e-01 -5.17965317e-01 6.71052039e-01 -3.59713078e-01
-3.10112834e-01 7.06744134e-01 -2.33266726e-02 -6.95062578e-01
-2.67292351e-01 -6.20327115e-01 -6.07221961e-01 -8.67248893e-01
-9.53944400e-03 3.00274700e-01 6.52365983e-01 6.55166656e-02
-2.56065220e-01 6.58873737e-01 -1.89457738e+00 4.06148314e-01
6.48273170e-01 1.44269514e+00 -5.95952928e-01 2.47287050e-01
-3.50067168e-02 9.22861755e-01 -5.60775399e-01 -8.19080412e-01
6.04567707e-01 3.98412764e-01 -6.69169247e-01 -2.83974349e-01
2.53508210e-01 -6.10577643e-01 -5.82306564e-01 8.05118203e-01
5.40202796e-01 -2.45800301e-01 9.82791185e-02 -2.29407763e+00
-1.45627275e-01 4.51191545e-01 -2.95078576e-01 -2.27135167e-01
-4.78420496e-01 4.59204286e-01 3.73306215e-01 -2.84969717e-01
4.59507853e-01 1.17234945e+00 5.05554438e-01 7.01921225e-01
-7.65943229e-01 -1.48640811e+00 -1.39109313e-01 8.62162530e-01
-1.13461018e+00 -6.03863358e-01 3.13794166e-01 -1.76664740e-01
7.35012293e-01 4.68436033e-01 2.63640247e-02 1.06167698e+00
6.00903273e-01 8.30615878e-01 1.09451735e+00 1.54917777e-01
4.57138777e-01 6.10989749e-01 2.74421781e-01 3.01592022e-01
3.38377893e-01 6.32157266e-01 -5.30740798e-01 -4.41176623e-01
-2.62272447e-01 4.04053867e-01 2.45874360e-01 -3.17366421e-01
-8.42814088e-01 5.52217007e-01 2.52258420e-01 -2.62934208e-01
-2.92085916e-01 4.52188440e-02 8.91168416e-01 4.71663088e-01
4.25141692e-01 -2.81771749e-01 -1.01129055e+00 -1.35644823e-01
-3.35633725e-01 -1.00890405e-01 9.46635604e-01 1.18466830e+00
9.75574017e-01 8.14062878e-02 -1.76944122e-01 6.44531399e-02
1.40589803e-01 7.48874009e-01 4.31038201e-01 -1.15051937e+00
4.08336043e-01 5.78047812e-01 1.25022545e-01 -5.67811191e-01
-4.09470171e-01 -7.42258877e-02 -7.03591347e-01 3.55947822e-01
-1.48438588e-01 -4.98456836e-01 -3.05212915e-01 1.56731892e+00
9.05681312e-01 6.90582275e-01 4.14610475e-01 6.17434144e-01
5.71660042e-01 5.94269931e-01 1.96274683e-01 -1.71869993e-01
1.14938843e+00 -1.05125165e+00 -7.76379645e-01 3.14581037e-01
9.27285194e-01 -4.71896440e-01 7.23628342e-01 3.85619998e-01
-6.10199988e-01 -3.86041373e-01 -8.69279623e-01 3.69115531e-01
-4.69254673e-01 -3.03596765e-01 6.44505501e-01 1.20772779e+00
-7.66927898e-01 2.32536733e-01 -6.40999675e-01 -3.42008024e-01
8.83342981e-01 6.80017471e-01 -3.42422724e-01 -1.64492667e-01
-9.65227783e-01 5.94562054e-01 2.23668933e-01 -7.25957394e-01
-1.18131697e+00 -1.08978450e+00 -5.05670905e-02 -2.46130992e-02
5.63711226e-01 -7.07812905e-01 1.25187552e+00 -4.63103145e-01
-1.65339756e+00 3.99960756e-01 1.81677729e-01 -8.31317246e-01
4.46089536e-01 -2.22988069e-01 -9.97989058e-01 -1.61528066e-01
-2.97097683e-01 2.31454059e-01 7.70439684e-01 -9.06736076e-01
-1.13631558e+00 -5.76536894e-01 -9.41827968e-02 -4.80029494e-01
-8.25684369e-01 2.88260132e-01 -2.71663636e-01 1.65733844e-01
-7.80457318e-01 -1.17072177e+00 8.07743222e-02 1.43322826e-03
-1.78599074e-01 -6.28548324e-01 2.00453925e+00 -4.28865254e-01
9.58181381e-01 -2.38777685e+00 -8.71595502e-01 1.69512644e-01
2.69368529e-01 9.22799110e-01 -7.10169598e-02 4.87546235e-01
4.15458351e-01 8.38610679e-02 5.45853972e-01 -2.21484944e-01
2.31066212e-01 5.14493227e-01 -4.61919814e-01 5.29858112e-01
-3.12167734e-01 9.81019437e-01 -5.63421667e-01 -4.05204892e-01
3.65867734e-01 4.89578933e-01 -3.93023461e-01 2.49678358e-01
-7.83000141e-02 6.48537278e-01 -5.86855531e-01 6.57848239e-01
8.78328264e-01 -1.23716220e-01 2.43798167e-01 -3.71418446e-01
-5.05638272e-02 -1.69313177e-02 -9.38823938e-01 1.03372562e+00
-5.54050982e-01 4.26771343e-01 2.08659425e-01 -5.16918898e-01
7.74246991e-01 4.55544382e-01 6.82399690e-01 -1.07858634e+00
4.75555986e-01 4.99976426e-02 -3.61488909e-01 -6.98814154e-01
9.48130991e-03 4.36446667e-01 -3.54083143e-02 7.89525867e-01
-2.72587180e-01 6.15903556e-01 -5.22675693e-01 3.21904659e-01
1.46286631e+00 -4.58586365e-01 -1.80687279e-01 -6.03663139e-02
7.16323018e-01 -2.12356240e-01 6.94957793e-01 4.15092856e-01
-6.94911778e-01 -5.06028950e-01 1.32628754e-01 -6.82481170e-01
-7.12758660e-01 -8.69934559e-01 -1.85080823e-02 1.11890364e+00
3.64503503e-01 -5.28837323e-01 -5.51319778e-01 -1.10029674e+00
3.44255894e-01 1.01607025e+00 -3.19657475e-02 -6.22873664e-01
-3.59519839e-01 -2.34226212e-01 8.29447389e-01 3.34459633e-01
1.00370026e+00 -6.02643788e-01 -5.19358099e-01 -3.19357477e-02
-1.45978043e-02 -1.45264697e+00 -4.04536664e-01 -3.59313190e-01
-5.37198544e-01 -1.21312356e+00 5.05201280e-01 -3.16338301e-01
1.36571929e-01 6.65943027e-01 6.61166131e-01 -1.42222434e-01
-2.20087737e-01 7.53610194e-01 -5.40920272e-02 -8.02107036e-01
-5.10269821e-01 -1.04011051e-01 4.65950340e-01 5.95562935e-01
7.52938807e-01 -3.94562095e-01 -6.70100212e-01 9.04679239e-01
-8.76451790e-01 -4.40964192e-01 4.30541903e-01 6.71897709e-01
4.26324695e-01 3.07787865e-01 9.31656122e-01 -9.47521448e-01
2.06770957e-01 -7.69856870e-01 -8.65822136e-01 1.89305022e-01
-1.39504015e+00 -1.54678822e-01 7.67529130e-01 -3.50645751e-01
-1.22167838e+00 4.43701334e-02 1.16683207e-01 -6.75681591e-01
-4.43778336e-01 -3.41357589e-01 -5.42805076e-01 -4.66682523e-01
5.13860166e-01 -8.22340846e-02 4.11672384e-01 -3.91686767e-01
4.81594115e-01 1.37535799e+00 4.92947310e-01 -2.30900228e-01
9.49805915e-01 7.58162856e-01 -5.88938361e-03 -4.55671906e-01
-4.01159585e-01 -5.36720932e-01 5.48905768e-02 -5.39064482e-02
4.96747881e-01 -1.06179202e+00 -1.43581510e+00 5.16063631e-01
-8.57050955e-01 -1.38212353e-01 -4.76012200e-01 7.29376793e-01
-3.46290767e-01 2.18520418e-01 -3.69808674e-01 -6.52759433e-01
-8.32814038e-01 -1.14920866e+00 5.33072829e-01 3.14178579e-02
4.14051503e-01 -6.56310022e-01 -2.30044976e-01 8.52799177e-01
8.95992398e-01 5.95070124e-02 9.15418446e-01 -1.05855978e+00
-7.79793441e-01 -4.91102278e-01 -2.01206654e-01 6.51036322e-01
-1.89694408e-02 -2.15680897e-01 -1.32763731e+00 -6.57589138e-01
-3.76902595e-02 -4.32890683e-01 1.09068424e-01 -3.96032006e-01
1.52360952e+00 -1.00440395e+00 -6.16858661e-01 7.68478751e-01
1.20714927e+00 2.03219652e-01 6.94120526e-01 1.42345101e-01
5.53569496e-01 6.52224898e-01 6.96703315e-01 6.94670081e-01
5.68515182e-01 5.35169601e-01 1.00597250e+00 3.45798582e-01
-1.10736832e-01 -2.63246387e-01 5.22458255e-01 4.25259411e-01
5.22090018e-01 -2.33865440e-01 -6.11779869e-01 4.07978475e-01
-1.89164972e+00 -8.49436760e-01 -1.31574675e-01 2.26084495e+00
4.48445559e-01 -1.55857444e-01 2.96882510e-01 1.20752655e-01
6.45514131e-01 -2.98199952e-01 -1.21818066e+00 -5.74966073e-01
1.67405710e-01 -4.09516990e-02 1.09962332e+00 -1.21464163e-01
-7.77872920e-01 8.34969759e-01 5.54483557e+00 1.06682825e+00
-1.38282096e+00 7.65866637e-01 4.26292032e-01 -2.13493124e-01
5.29668070e-02 -8.18071142e-02 -9.44050074e-01 5.75051129e-01
1.80658221e+00 -5.27220428e-01 5.47045469e-01 1.24022949e+00
1.65811270e-01 7.39073396e-01 -9.02353346e-01 1.11945796e+00
-4.30502832e-01 -1.51634967e+00 -1.36248812e-01 1.76288679e-01
8.62620354e-01 8.21379721e-01 7.00985268e-02 4.74213213e-01
4.43557501e-01 -7.59657145e-01 4.16262895e-01 2.02598825e-01
9.47896600e-01 -1.15675008e+00 7.69787848e-01 6.48383260e-01
-9.24754679e-01 -6.87395871e-01 -3.18909645e-01 1.65128186e-01
-1.85647100e-01 4.32378441e-01 -8.69608104e-01 5.43204665e-01
1.13692594e+00 3.52120996e-01 -5.43786049e-01 8.52051079e-01
2.15628460e-01 1.04590142e+00 -3.21774572e-01 -1.17697515e-01
-8.58977437e-02 2.05678001e-01 4.28926289e-01 8.48806560e-01
-7.15395138e-02 -1.31254524e-01 1.04124002e-01 3.35800111e-01
-2.62621373e-01 5.15995175e-02 -6.23352826e-01 2.68449068e-01
8.97980392e-01 1.62943327e+00 2.43078887e-01 -3.70843083e-01
-6.07569158e-01 4.74680543e-01 -1.09481238e-01 2.11153895e-01
-9.87435520e-01 -2.53730386e-01 1.22178364e+00 1.28140315e-01
3.27235639e-01 6.41523376e-02 -1.78571150e-01 -7.06032932e-01
-9.47762504e-02 -8.90421391e-01 5.86172283e-01 -2.16451138e-01
-1.46386433e+00 4.54179585e-01 -1.04004189e-01 -1.35205793e+00
-6.00129412e-03 -1.84752807e-01 -5.32159567e-01 2.52735049e-01
-1.69075549e+00 -1.35443068e+00 -3.34502280e-01 1.43904161e+00
2.76208925e-03 -6.36035562e-01 7.59925127e-01 7.09751606e-01
-6.48811162e-01 1.25248766e+00 6.41922057e-01 -4.25249457e-01
7.47259140e-01 -3.92232031e-01 1.57395422e-01 5.08038759e-01
-3.23277116e-01 1.43323258e-01 1.64801985e-01 -2.61679202e-01
-2.09948635e+00 -1.98832548e+00 6.57574296e-01 -4.04795557e-01
5.16690850e-01 -3.64411741e-01 -5.60817778e-01 8.44275773e-01
2.76125431e-01 5.06823540e-01 7.79888630e-01 -3.74259800e-01
-7.25428045e-01 -1.21569622e+00 -1.81007922e+00 1.88046515e-01
8.61085057e-01 -3.89539748e-01 3.06245327e-01 6.13980472e-01
1.13626766e+00 1.04763925e-01 -1.00227249e+00 1.82662189e-01
4.13255960e-01 -9.79887009e-01 5.77625096e-01 -8.53810668e-01
-7.98714519e-01 -2.77144670e-01 -2.53529549e-01 -8.28889608e-01
-4.97601815e-02 -1.36481297e+00 -3.86451393e-01 1.55430615e+00
2.28936020e-02 -1.46471608e+00 8.10023129e-01 9.91180301e-01
-1.68477491e-01 -6.18182659e-01 -1.35321593e+00 -1.16662824e+00
-6.80777356e-02 -6.99188590e-01 1.53542936e+00 6.72917008e-01
-1.66126311e-01 1.62898242e-01 -5.87561250e-01 4.08397377e-01
8.42248857e-01 -9.28815156e-02 1.33455908e+00 -1.17685449e+00
7.57452473e-02 3.21339935e-01 -6.86141312e-01 -5.59284389e-01
3.14025372e-01 -7.94979334e-01 -4.32741821e-01 -8.18147719e-01
-1.90922543e-01 -7.56872118e-01 -5.78675330e-01 9.03014362e-01
7.21596360e-01 -5.47899725e-03 2.67360836e-01 3.90983284e-01
-9.90360916e-01 5.05803823e-01 6.04867637e-01 -3.93480390e-01
-3.03806923e-02 3.05228293e-01 -6.15638733e-01 3.95897508e-01
1.26459467e+00 -5.02265275e-01 -5.96299052e-01 -3.00184101e-01
-3.51085246e-01 -3.07019651e-02 5.71836710e-01 -1.03934503e+00
6.70387030e-01 -3.28697264e-01 -3.02309722e-01 -4.92962867e-01
1.20771201e-02 -1.49430919e+00 6.06419027e-01 7.42843151e-01
1.30532637e-01 -1.82106197e-01 2.31363654e-01 6.82701945e-01
1.82916626e-01 6.82486296e-01 8.43431413e-01 5.39060533e-01
-8.88503253e-01 8.46295536e-01 3.16600166e-02 -2.35371828e-01
1.88050807e+00 4.56662513e-02 -1.08245504e+00 -2.76877582e-01
-6.31963834e-02 5.10170281e-01 2.73884118e-01 8.26821268e-01
5.17320693e-01 -1.34502554e+00 -4.89941001e-01 5.90651333e-01
3.14146578e-01 -5.35250962e-01 3.77717018e-01 9.53514397e-01
9.90972593e-02 6.35502934e-01 -1.20732002e-01 -6.16169930e-01
-1.37378538e+00 1.02852380e+00 2.11162791e-01 5.05869091e-02
-6.84003413e-01 2.42454812e-01 -9.89359915e-02 -6.95093513e-01
7.31503129e-01 2.03049093e-01 2.98876911e-01 -4.00739640e-01
7.36388803e-01 1.16028452e+00 4.43143964e-01 -5.79959929e-01
-5.58047354e-01 1.60377741e-01 -1.65792473e-03 6.41993999e-01
1.03107178e+00 -4.84550148e-01 3.36418077e-02 -1.60040915e-01
1.57329679e+00 -1.55368209e-01 -1.35798514e+00 -5.63617647e-01
-2.97005087e-01 -6.54175818e-01 2.34048188e-01 -9.50150490e-01
-1.63106048e+00 5.26536047e-01 1.20914590e+00 4.64061759e-02
1.00494909e+00 -9.44183916e-02 1.67071581e+00 4.48377132e-01
8.91383946e-01 -8.48851025e-01 -2.88890362e-01 3.93829122e-02
1.67966217e-01 -1.23878181e+00 -2.97119111e-01 -2.02722698e-01
-7.93388307e-01 7.27290690e-01 7.38617182e-01 3.52794647e-01
1.05209374e+00 2.17174441e-01 1.83809936e-01 -7.85158426e-02
-1.27094507e+00 2.47452348e-01 -2.33870208e-01 9.11412776e-01
-6.84587777e-01 1.80014178e-01 -5.43372072e-02 5.74366331e-01
1.31748784e-02 3.26060444e-01 2.16214150e-01 9.95498598e-01
-1.83820099e-01 -1.12975228e+00 -2.16449410e-01 4.37097371e-01
-3.74745637e-01 6.12867177e-01 -8.14987645e-02 4.51730549e-01
3.83928508e-01 1.54020858e+00 -9.41560566e-02 -1.22837090e+00
2.94747859e-01 3.49217169e-02 -3.83881509e-01 1.07698776e-01
-7.82338738e-01 -5.28292954e-01 -4.92821746e-02 -1.23551905e+00
-1.50298357e-01 -2.75307596e-01 -1.30920041e+00 -1.02605045e+00
-3.51261169e-01 2.07199007e-01 1.09240067e+00 7.55562603e-01
1.31908739e+00 1.77968338e-01 1.42704439e+00 -1.73077568e-01
-1.08491671e+00 -2.73262560e-01 -6.70031548e-01 2.71232039e-01
3.33513588e-01 -3.72140139e-01 -5.92495024e-01 -3.48859042e-01] | [5.844934940338135, 6.4198174476623535] |
a5e8e6e8-5679-43e8-a012-7461212a400e | pystachio-python-single-molecule-tracking | 2103.10164 | null | https://arxiv.org/abs/2103.10164v3 | https://arxiv.org/pdf/2103.10164v3.pdf | PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy | As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microcopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized. | ['Mark C Leake', 'Adam J M Wollman', 'Ed J Higgins', 'Jack W Shepherd'] | 2021-03-18 | null | null | null | null | ['art-analysis'] | ['computer-vision'] | [ 2.87413865e-01 -7.79566109e-01 3.97602677e-01 -6.33572638e-02
-8.39624465e-01 -1.12980223e+00 3.06284696e-01 3.96776080e-01
-9.32915092e-01 1.00069416e+00 -5.05582213e-01 -4.53196347e-01
1.05755664e-01 -4.74499822e-01 -5.57871282e-01 -1.06309199e+00
-8.66104513e-02 7.69228935e-01 4.96011347e-01 2.30785578e-01
2.76654601e-01 9.91932392e-01 -1.62089670e+00 7.86668584e-02
3.60711157e-01 5.02651036e-01 1.62114143e-01 1.31295025e+00
2.83387881e-02 4.69186395e-01 -5.07295609e-01 6.20546844e-03
9.85478088e-02 -2.61166424e-01 -4.00834560e-01 -3.65731359e-01
2.55858064e-01 -2.51279455e-02 1.29185244e-01 7.07002282e-01
8.81427407e-01 -2.36376990e-02 4.47026223e-01 -8.99174154e-01
-6.53341189e-02 -3.52198571e-01 -6.32253528e-01 6.12071335e-01
3.89731348e-01 5.78702509e-01 5.09092569e-01 -7.46967733e-01
9.71941173e-01 9.81819332e-01 7.01786458e-01 3.56932610e-01
-1.80184805e+00 -4.52245682e-01 -5.33820391e-01 -3.59025091e-01
-1.20913064e+00 -4.83014345e-01 -5.12554049e-02 -6.35003865e-01
1.24206722e+00 4.16569889e-01 7.57811904e-01 5.22831202e-01
3.04544002e-01 -1.29192350e-02 1.63386607e+00 -3.09624940e-01
1.51505470e-01 -1.05430543e-01 -5.17632961e-02 7.01357007e-01
3.43749166e-01 -3.33282873e-02 -2.31985450e-01 -3.88856977e-01
8.75878751e-01 3.36331993e-01 -2.70176560e-01 -3.17476422e-01
-1.72696972e+00 4.79568154e-01 -2.34032050e-01 4.23259348e-01
-1.42791837e-01 1.14583142e-01 2.17983529e-01 5.69479465e-02
2.80700892e-01 4.47090924e-01 -4.05601621e-01 -6.15392685e-01
-7.30620623e-01 3.53976488e-01 8.15789998e-01 3.57912779e-01
8.58737230e-01 -7.21381843e-01 2.63590157e-01 4.08705413e-01
8.47412348e-02 6.60615683e-01 2.44371817e-01 -1.31208849e+00
-1.48523837e-01 5.82536638e-01 5.82136929e-01 -6.22379780e-01
-7.76313365e-01 2.05202013e-01 -4.65060204e-01 6.90463960e-01
1.06991935e+00 -2.52968669e-01 -5.81637263e-01 1.25738633e+00
5.52155018e-01 -1.59851819e-01 -3.05480808e-01 9.15683091e-01
4.55773175e-01 6.02793515e-01 2.38825567e-02 -5.27154505e-01
1.43612587e+00 -3.50430280e-01 -3.91474068e-01 4.66848433e-01
8.48252237e-01 -9.85732794e-01 1.01874316e+00 4.94620591e-01
-1.04435277e+00 -1.77201629e-01 -7.17226863e-01 -1.61634609e-01
-6.71595156e-01 -1.56561106e-01 7.39078581e-01 8.20982754e-01
-1.06897116e+00 8.34643602e-01 -1.20075583e+00 -6.30729914e-01
5.79906106e-01 7.09221125e-01 -4.64227825e-01 -2.16000732e-02
-4.52877432e-01 7.07601845e-01 -1.11409508e-01 -3.35332185e-01
-4.51830059e-01 -1.00814843e+00 -2.67072439e-01 -2.81038225e-01
-1.21347494e-01 -7.42543399e-01 9.73386765e-01 -2.97059000e-01
-1.70275056e+00 1.31384706e+00 -2.58408278e-01 -4.74507697e-02
3.79581124e-01 4.53085333e-01 -8.28795210e-02 3.16344261e-01
-3.80873121e-02 6.39092863e-01 2.70843301e-02 -8.72097731e-01
-6.04235828e-01 -5.91037512e-01 -2.29079127e-01 -4.31989580e-02
1.49195731e-01 5.29832125e-01 -2.17499033e-01 5.31638712e-02
-4.04730171e-01 -9.54133749e-01 -2.27447778e-01 2.28779107e-01
-2.23874729e-02 1.29221916e-01 8.76798630e-01 -1.86763972e-01
5.80538213e-01 -1.90856802e+00 5.33399545e-02 2.90294215e-02
4.43749160e-01 4.01598185e-01 1.68631822e-01 6.41661406e-01
4.62370329e-02 9.54281017e-02 -1.34644017e-01 -2.46316418e-01
-2.19373643e-01 -5.95216043e-02 1.66059002e-01 9.31094170e-01
-1.66322872e-01 7.17613995e-01 -9.58407044e-01 -4.64181930e-01
3.90084118e-01 7.71790445e-01 -3.33456725e-01 1.09532297e-01
-5.60737140e-02 8.79763722e-01 -1.02679841e-01 7.47460186e-01
7.87171066e-01 -8.58532190e-01 3.42108995e-01 -1.45044789e-01
-8.17091107e-01 -6.71055466e-02 -9.47310686e-01 1.51233280e+00
-1.17507577e-01 7.34138310e-01 2.59468317e-01 -6.17965698e-01
5.72656691e-01 -4.11555693e-02 6.25284135e-01 -4.32140738e-01
1.54707089e-01 2.68155217e-01 3.25714760e-02 -3.88115615e-01
6.23973571e-02 -3.65859896e-01 4.36599374e-01 6.13835812e-01
-2.68491477e-01 -1.95473611e-01 4.48108971e-01 1.13330647e-01
1.38077712e+00 1.33872956e-01 1.59153253e-01 -5.03176212e-01
4.11315143e-01 2.67771482e-01 -1.18240170e-01 5.42084992e-01
-2.59752274e-01 4.70890433e-01 4.34900522e-01 -5.88098645e-01
-1.33079088e+00 -1.07440186e+00 -1.94009796e-01 1.00846791e+00
1.02644034e-01 -3.91711950e-01 -6.08518720e-01 6.59502968e-02
1.82493567e-01 -1.91178888e-01 -3.69969726e-01 7.28667676e-01
-3.19769233e-01 -1.30082309e+00 4.91203308e-01 1.19122684e-01
-3.47196124e-02 -7.16990292e-01 -9.82975006e-01 2.04692513e-01
4.55799282e-01 -1.00143456e+00 3.38879116e-02 2.74242580e-01
-6.17008269e-01 -1.31530845e+00 -8.00330997e-01 -3.07792336e-01
7.02451587e-01 4.46769446e-01 7.82740176e-01 2.85940915e-01
-9.56592202e-01 6.11917734e-01 3.64653207e-02 -4.28054333e-01
-1.93061084e-01 -2.06321001e-01 1.34141102e-01 -3.21332097e-01
4.03257698e-01 -6.48301303e-01 -9.33909118e-01 3.92799705e-01
-8.47257495e-01 -6.74127191e-02 1.45909533e-01 5.81978023e-01
1.02129364e+00 -2.55812138e-01 1.01105310e-02 -9.55827594e-01
5.03175080e-01 -1.03952169e-01 -1.18072295e+00 -1.41626477e-01
-3.93964320e-01 -1.79665878e-01 8.72770667e-01 -1.68493792e-01
-6.70404077e-01 2.50956982e-01 2.24818923e-02 -1.43977389e-01
-3.13933522e-01 2.19236434e-01 2.74409592e-01 -5.42631507e-01
6.48036897e-01 8.10110494e-02 5.26858032e-01 -2.93297082e-01
1.09061822e-01 4.58667427e-01 3.86120647e-01 -5.53757787e-01
3.10072601e-01 1.19086099e+00 3.67660880e-01 -1.08322358e+00
-1.55650884e-01 -6.95936739e-01 -4.82430190e-01 -2.15883464e-01
8.06176424e-01 -7.25215256e-01 -1.67502475e+00 6.39310360e-01
-1.01879358e+00 -7.01361895e-01 -1.02206301e-02 4.93453771e-01
-4.35224622e-01 4.88105208e-01 -7.05323517e-01 -6.74201429e-01
7.02194721e-02 -1.30331194e+00 1.23754001e+00 3.66558522e-01
-4.18081321e-02 -1.13868845e+00 6.41465366e-01 2.89008349e-01
5.08266747e-01 5.10434330e-01 4.76841956e-01 -3.23478132e-01
-7.67440677e-01 -3.16945285e-01 -4.02190000e-01 -2.77834237e-01
4.96758856e-02 6.71666741e-01 -9.84394491e-01 -4.46546257e-01
-3.28489423e-01 -1.57069534e-01 6.22328460e-01 5.15427351e-01
9.72870708e-01 2.47660011e-01 -9.36805964e-01 6.16333544e-01
1.46234405e+00 6.24633543e-02 6.94789350e-01 2.72912741e-01
5.30696630e-01 6.27262533e-01 4.89210457e-01 5.19663215e-01
4.51839194e-02 6.41325831e-01 1.48184225e-01 -2.06238300e-01
1.93942413e-01 4.63614941e-01 1.22121468e-01 5.86051106e-01
-5.62617362e-01 -3.32544357e-01 -1.03856790e+00 1.19652607e-01
-1.66643524e+00 -1.10558951e+00 -6.91415310e-01 2.32482362e+00
7.27708340e-01 -1.99012235e-01 6.07409358e-01 -3.37077290e-01
6.84840083e-01 -3.39917481e-01 -4.24965233e-01 -1.36151314e-01
-1.47738591e-01 3.77928019e-01 7.98251212e-01 6.16154850e-01
-7.47769356e-01 5.99411249e-01 7.25676346e+00 6.61361277e-01
-1.28421926e+00 1.20171368e-01 6.33747578e-01 -3.96742105e-01
-1.49464220e-01 2.16763526e-01 -9.30677116e-01 7.98093736e-01
1.14272666e+00 -5.36185615e-02 6.20975792e-01 2.37801969e-01
4.90739644e-01 -6.97208047e-01 -1.11638987e+00 1.28116834e+00
-5.40908098e-01 -1.80974710e+00 -4.30505216e-01 4.99380916e-01
3.32575858e-01 5.35243213e-01 -1.49207488e-01 -4.14449602e-01
3.10391009e-01 -1.09995627e+00 -7.74511546e-02 7.50791192e-01
8.07038665e-01 -4.62753922e-01 6.49949074e-01 3.85750741e-01
-9.39853847e-01 3.72631192e-01 -3.49844158e-01 -2.91102916e-01
2.01232359e-01 7.13841021e-01 -7.03463614e-01 4.21072654e-02
6.67735338e-01 4.52183634e-01 -5.18514156e-01 9.96905327e-01
4.88613784e-01 1.29646689e-01 -7.39616573e-01 -4.03201282e-01
-5.38070686e-02 -5.42652607e-01 2.19518900e-01 1.47243118e+00
3.40238184e-01 3.84836555e-01 -2.56096035e-01 9.15084302e-01
6.71419501e-02 7.69882500e-02 -5.86973846e-01 -3.25224400e-01
3.74609739e-01 1.74258661e+00 -1.24432325e+00 -3.87062699e-01
-4.84433413e-01 6.90175712e-01 3.43823254e-01 1.41821399e-01
-6.72401369e-01 -5.63911200e-01 8.81713688e-01 2.45157748e-01
2.00117096e-01 -5.30764878e-01 1.81555659e-01 -9.76635098e-01
-4.70796615e-01 -5.73193491e-01 1.10092007e-01 -8.65482092e-01
-1.20148110e+00 -1.15777008e-01 -3.77159327e-01 -8.15341115e-01
1.39329240e-01 -1.16476214e+00 -4.36492682e-01 8.80831718e-01
-1.32601821e+00 -6.33584619e-01 -3.07554036e-01 4.54200268e-01
-2.79644370e-01 3.34030986e-01 9.12063897e-01 3.73138666e-01
-5.34257710e-01 -9.01968628e-02 6.81154728e-01 -1.91494986e-01
8.28948915e-01 -1.16816092e+00 1.37231976e-01 5.00645638e-01
-1.86918583e-02 1.03940725e+00 6.54109120e-01 -4.50632244e-01
-1.80102432e+00 -4.88455683e-01 3.75872523e-01 -9.20763433e-01
9.78852808e-01 -5.06681979e-01 -7.11332560e-01 4.54475880e-01
9.65029076e-02 3.85914624e-01 1.18272698e+00 -2.06952766e-01
3.38914692e-02 1.86980724e-01 -1.15289176e+00 4.58310157e-01
7.67094791e-01 -5.74402869e-01 1.95681199e-01 8.02284241e-01
8.11967030e-02 -4.14887637e-01 -1.19612670e+00 -1.10225029e-01
8.51912141e-01 -1.40564561e+00 8.88440967e-01 -2.80970544e-01
-2.02901036e-01 -6.82018638e-01 9.38919783e-02 -7.11719275e-01
-8.22527558e-02 -1.00605512e+00 3.50967020e-01 7.95534968e-01
2.26787046e-01 -8.62873912e-01 8.21201384e-01 6.12397134e-01
1.97975323e-01 -4.88609254e-01 -9.67474997e-01 -7.42531300e-01
-1.44485682e-01 4.62007225e-02 2.68195987e-01 7.92166948e-01
4.66781348e-01 2.96920627e-01 2.22257018e-01 1.13558751e-02
6.36526287e-01 2.72048026e-01 1.10470283e+00 -1.27345085e+00
-3.72760803e-01 -4.68056619e-01 -5.83640814e-01 -8.58016312e-01
-2.73563415e-01 -6.21336162e-01 -2.48337626e-01 -1.19692099e+00
4.84071493e-01 -2.68007040e-01 -1.07821962e-02 2.54741430e-01
8.29665214e-02 6.52346194e-01 -1.02280147e-01 4.09341574e-01
-8.82061362e-01 -3.18602324e-01 1.11360514e+00 2.34634191e-01
-1.19173981e-01 -3.36310923e-01 -3.32715183e-01 4.77575094e-01
4.33644772e-01 -4.72634673e-01 1.24650046e-01 6.60065636e-02
5.56528866e-01 -1.87936381e-01 6.83260560e-01 -1.20395744e+00
3.89651328e-01 -9.87009518e-03 4.94177878e-01 -3.94784808e-01
3.68665814e-01 -7.39871562e-01 5.14906466e-01 5.64036429e-01
1.10189006e-01 7.31572658e-02 4.21257019e-01 4.34685379e-01
2.79035747e-01 5.94959855e-02 1.04684663e+00 -4.23729062e-01
-8.85274187e-02 2.31416792e-01 -8.22707474e-01 9.16495360e-03
1.19173670e+00 -4.56119925e-01 -7.72946358e-01 -5.57899401e-02
-6.98105574e-01 -3.40685621e-02 1.36251807e+00 -5.49273312e-01
2.07358971e-01 -7.71803021e-01 -2.19268858e-01 1.01188160e-01
9.75701958e-02 -2.03505114e-01 2.66296566e-01 1.40108311e+00
-1.23417878e+00 4.85208392e-01 -3.72212291e-01 -8.65906298e-01
-1.59576118e+00 5.98065436e-01 3.68487805e-01 -1.67052507e-01
-2.68530548e-01 7.21169651e-01 6.04781583e-02 -2.97711611e-01
-4.54594791e-01 -4.26924139e-01 2.36771941e-01 -1.62948534e-01
8.48027408e-01 5.81637859e-01 -3.86248119e-02 -3.04209799e-01
-5.21929145e-01 8.86721492e-01 1.90664101e-02 -1.67670415e-03
1.38853312e+00 -1.85263559e-01 -6.40718997e-01 5.28084040e-01
1.28376353e+00 3.51876378e-01 -1.40257132e+00 5.05748034e-01
-3.76900584e-01 -3.95316005e-01 -2.49740541e-01 -5.68050325e-01
-4.55202401e-01 9.89842832e-01 7.62935460e-01 4.64427918e-01
6.44764006e-01 1.09424420e-01 4.81841683e-01 4.99192327e-01
3.42187375e-01 -7.41888225e-01 -2.70856500e-01 8.74487236e-02
-1.00716323e-01 -1.22573948e+00 3.34656239e-01 -3.63787800e-01
-5.03396476e-03 1.27461827e+00 2.32526422e-01 8.73605236e-02
2.73468167e-01 7.46662438e-01 1.12314239e-01 -6.48967862e-01
-6.76706910e-01 -2.01468281e-02 -5.23356438e-01 8.29661310e-01
6.35735333e-01 -1.07017100e-01 -1.19446166e-01 -1.24948978e-01
3.03738207e-01 2.57690519e-01 7.27397025e-01 1.03139365e+00
-6.03578985e-01 -1.26516581e+00 -4.17669356e-01 4.09322739e-01
-6.82225049e-01 -2.10290160e-02 -3.26402277e-01 9.49318111e-01
-6.86678961e-02 6.62873268e-01 2.07586601e-01 1.50251761e-01
7.82642141e-02 2.26385240e-02 8.08365226e-01 -5.46937168e-01
-3.62624437e-01 1.25013307e-01 -1.66123465e-01 -7.70704627e-01
-9.70663249e-01 -7.71605194e-01 -1.53784811e+00 -7.38094687e-01
-3.15082878e-01 2.09230989e-01 7.55897164e-01 7.28036165e-01
8.12618017e-01 3.85337695e-02 9.76914391e-02 -1.30248439e+00
2.00810641e-01 -3.85417908e-01 -7.71914780e-01 1.42565757e-01
3.05623442e-01 -4.44063425e-01 -4.86554205e-01 3.01529258e-01] | [13.940164566040039, -3.093432664871216] |
1369fb58-2ee0-4752-9441-df7242fbf395 | wlv-rit-at-semeval-2021-task-5-a-neural | 2104.04630 | null | https://arxiv.org/abs/2104.04630v3 | https://arxiv.org/pdf/2104.04630v3.pdf | WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spans | In recent years, the widespread use of social media has led to an increase in the generation of toxic and offensive content on online platforms. In response, social media platforms have worked on developing automatic detection methods and employing human moderators to cope with this deluge of offensive content. While various state-of-the-art statistical models have been applied to detect toxic posts, there are only a few studies that focus on detecting the words or expressions that make a post offensive. This motivates the organization of the SemEval-2021 Task 5: Toxic Spans Detection competition, which has provided participants with a dataset containing toxic spans annotation in English posts. In this paper, we present the WLV-RIT entry for the SemEval-2021 Task 5. Our best performing neural transformer model achieves an $0.68$ F1-Score. Furthermore, we develop an open-source framework for multilingual detection of offensive spans, i.e., MUDES, based on neural transformers that detect toxic spans in texts. | ['Alexander Ororbia', 'Marcos Zampieri', 'Diptanu Sarkar', 'Tharindu Ranasinghe'] | 2021-04-09 | null | https://aclanthology.org/2021.semeval-1.111 | https://aclanthology.org/2021.semeval-1.111.pdf | semeval-2021 | ['toxic-spans-detection'] | ['natural-language-processing'] | [-6.22748509e-02 -3.05218622e-02 1.84110589e-02 -9.28780138e-02
-1.30714321e+00 -5.45721352e-01 3.48885119e-01 4.83222395e-01
-6.54452682e-01 4.63267893e-01 6.54480398e-01 2.28346027e-02
3.45218092e-01 -5.37820756e-01 -4.58006173e-01 -1.27591461e-01
-5.02891131e-02 1.46779060e-01 -1.61853917e-02 -5.94202220e-01
4.05482829e-01 -1.53403774e-01 -1.11202526e+00 6.77546978e-01
9.52658474e-01 8.73474002e-01 -1.73602790e-01 4.27651525e-01
5.81906103e-02 8.58350754e-01 -8.86563718e-01 -8.60705495e-01
2.64636241e-02 -4.66753185e-01 -7.96667099e-01 -4.70870465e-01
8.02225769e-01 -1.31064868e-02 -4.14873391e-01 1.20307291e+00
7.45674670e-01 -7.29968399e-02 5.14142334e-01 -8.72292459e-01
-8.91964495e-01 1.66908932e+00 -7.25340068e-01 6.36612296e-01
4.84432101e-01 6.92599639e-02 1.62383652e+00 -9.02943909e-01
7.40644991e-01 1.23993278e+00 1.00601470e+00 3.06898087e-01
-1.11598814e+00 -8.96426439e-01 -2.05682382e-01 3.63467366e-01
-1.29405832e+00 -3.72734785e-01 8.69848251e-01 -6.07837677e-01
1.03885043e+00 2.60822266e-01 6.30545437e-01 1.85114586e+00
2.60525525e-01 1.05457473e+00 1.21186483e+00 -3.95883262e-01
-3.80028546e-01 -5.91860414e-02 4.65100616e-01 6.02710545e-01
1.66580766e-01 -3.44279468e-01 -1.20624578e+00 -1.78244114e-01
-3.59677225e-01 -4.69984382e-01 -1.28047764e-01 5.53784430e-01
-9.37190533e-01 1.21152651e+00 2.28652433e-01 5.89952528e-01
-3.75491291e-01 1.48210861e-02 1.32555187e+00 4.92760420e-01
1.10063338e+00 7.89245605e-01 -1.84334844e-01 -4.30162877e-01
-1.00673640e+00 4.61991370e-01 8.41075838e-01 5.65146923e-01
1.08671226e-01 -1.39002636e-01 -4.95368421e-01 1.16919148e+00
1.75747693e-01 3.75140935e-01 5.46083391e-01 -3.61842543e-01
8.55192065e-01 5.91633379e-01 -3.04540068e-01 -1.19620454e+00
-5.70626259e-01 -3.64323795e-01 -4.71358031e-01 -3.46782386e-01
4.10014004e-01 -3.86045307e-01 -4.57506359e-01 1.79026747e+00
-2.61933524e-02 -4.28495079e-01 -4.90373343e-01 4.70597088e-01
6.84939802e-01 3.94595861e-01 1.70352340e-01 -5.58172949e-02
1.38341832e+00 -5.31190753e-01 -7.98550487e-01 2.99894903e-02
1.15248334e+00 -9.88627315e-01 1.39996505e+00 7.77314603e-01
-1.01707518e+00 -7.75611252e-02 -1.07156539e+00 -3.09764802e-01
-4.91198629e-01 -3.32662314e-01 4.26849276e-02 8.15941036e-01
-6.47810459e-01 6.65964901e-01 -2.90462255e-01 -3.63079101e-01
4.24461693e-01 -2.68261194e-01 -1.15039267e-01 3.22654247e-01
-1.82163978e+00 1.19472837e+00 1.39018163e-01 -1.13310657e-01
-8.92208934e-01 -9.98788536e-01 -6.98669016e-01 -4.37362969e-01
2.40399376e-01 1.04896866e-01 1.33881104e+00 -7.04699934e-01
-8.17077756e-01 1.30523753e+00 4.41719294e-01 -6.22687995e-01
6.26606107e-01 -9.61515069e-01 -5.84964871e-01 -1.33118391e-01
4.82120425e-01 1.80039987e-01 4.49072331e-01 -3.99071097e-01
-3.21936369e-01 -3.12623292e-01 -1.59713104e-01 -6.72372878e-02
-1.04705822e+00 9.20063019e-01 2.46376470e-01 -6.82461858e-01
-5.28435230e-01 -8.75867546e-01 2.04800889e-01 -6.79776490e-01
-1.07857358e+00 -8.83763731e-01 7.11404562e-01 -1.07678378e+00
1.76189125e+00 -2.09386110e+00 -1.60808768e-02 4.90522310e-02
5.70106089e-01 1.00155853e-01 -9.86823142e-02 9.11449790e-01
1.75161287e-01 6.14398718e-01 7.77769312e-02 -6.03156745e-01
3.98640871e-01 -4.77797717e-01 -7.06534207e-01 6.53115273e-01
-3.23864490e-01 7.21354961e-01 -7.97079623e-01 -6.32969975e-01
-4.48309243e-01 2.96164244e-01 -4.35581326e-01 -1.23855323e-01
-1.10059664e-01 -1.62861764e-01 -3.37696105e-01 5.65353334e-01
1.86411142e-01 1.02212541e-01 -1.30249754e-01 9.20514762e-02
-6.07605994e-01 9.46448505e-01 -2.04314500e-01 1.58228314e+00
-2.13420749e-01 1.09965897e+00 -5.42360283e-02 -4.03287739e-01
8.67965758e-01 2.35539660e-01 5.04805088e-01 -7.79430985e-01
5.60801983e-01 1.95676237e-01 1.09474681e-01 -6.63250566e-01
9.23197687e-01 -1.54080614e-01 -8.80615294e-01 5.42708039e-01
-1.37606040e-01 1.86646342e-01 5.57749271e-01 5.00537515e-01
1.50621641e+00 -1.43237337e-01 1.16583362e-01 -3.21068406e-01
1.74838871e-01 -3.81191005e-03 5.56735516e-01 5.52826166e-01
-5.40864587e-01 5.11581719e-01 6.83411777e-01 -2.50441134e-01
-1.01140392e+00 -5.45031667e-01 -8.20650607e-02 1.52744257e+00
-5.21800220e-01 -8.76260817e-01 -9.63876784e-01 -7.06925392e-01
-4.20080386e-02 8.52615714e-01 -8.10971916e-01 2.04771161e-02
-7.94308245e-01 -6.20474935e-01 1.44476831e+00 1.68072522e-01
5.11318088e-01 -1.43347096e+00 -5.79636812e-01 3.82373691e-01
-8.17244112e-01 -1.11818016e+00 -7.88022637e-01 6.70924336e-02
-1.83191046e-01 -1.03072751e+00 -3.90260637e-01 -4.13441330e-01
-3.56803000e-01 9.58508754e-04 1.19016325e+00 -1.28124431e-01
-3.42234015e-01 -2.52923727e-01 -7.69735754e-01 -7.96428859e-01
-3.77633452e-01 6.08361065e-01 1.98565483e-01 -1.85360998e-01
7.94356108e-01 -4.21093136e-01 -2.16719434e-01 -7.55714104e-02
-5.34967542e-01 -2.64334083e-01 1.36254966e-01 4.45838392e-01
1.83728896e-02 -5.85148156e-01 8.40312421e-01 -1.17855108e+00
1.24888599e+00 -6.82403147e-01 -8.19525048e-02 -1.96645170e-01
-4.58314210e-01 -3.52027059e-01 7.58747578e-01 -4.68911648e-01
-6.58915341e-01 -4.22060192e-01 -2.86159813e-01 -1.87867239e-01
3.01624954e-01 9.60568130e-01 1.38565838e-01 3.70149881e-01
1.26052368e+00 -2.80557722e-01 -3.85936052e-01 -7.11363196e-01
3.00071210e-01 1.01908553e+00 1.83048695e-01 -2.01952666e-01
7.84650922e-01 -1.02075033e-01 -6.38885200e-01 -1.05431473e+00
-1.60113227e+00 -5.90530992e-01 -3.14691961e-01 -4.84979630e-01
8.61254692e-01 -8.46093416e-01 -5.14813662e-01 7.22759843e-01
-1.15322220e+00 -2.18626365e-01 4.74364907e-02 3.99577916e-02
-1.98319659e-01 4.83785272e-01 -1.11014521e+00 -5.96909523e-01
-9.76466238e-01 -5.79050183e-01 5.57827234e-01 -2.45736256e-01
-1.06690562e+00 -6.04988575e-01 6.40656710e-01 7.80479312e-01
4.20082927e-01 5.98408103e-01 7.37945676e-01 -9.16436434e-01
2.25180358e-01 -3.50230366e-01 -4.51384895e-02 3.58297348e-01
-3.80434632e-01 -2.34367885e-02 -9.36739326e-01 -1.46147879e-02
-3.46823990e-01 -1.08654809e+00 9.65995312e-01 2.14243717e-02
8.92094076e-01 -4.84174043e-01 -1.44053206e-01 6.22051321e-02
8.45792651e-01 -3.29504162e-01 6.20338380e-01 5.91265738e-01
7.11449981e-01 6.58485115e-01 5.81937313e-01 7.31978297e-01
3.14438730e-01 5.24182439e-01 3.38881075e-01 2.57446647e-01
2.27942108e-03 -4.33620751e-01 9.27355826e-01 1.05643463e+00
6.02061115e-02 -3.39374602e-01 -9.58001852e-01 7.59501636e-01
-1.51840854e+00 -1.28143966e+00 -6.70962214e-01 1.58648658e+00
1.20262110e+00 2.45598450e-01 4.76434052e-01 2.64911264e-01
7.04381526e-01 5.68713188e-01 -2.60551393e-01 -8.25441658e-01
-1.55162975e-01 6.97048679e-02 3.27357769e-01 9.36206579e-02
-1.25168347e+00 1.05776489e+00 6.26776361e+00 1.04887795e+00
-9.80330646e-01 4.84393984e-01 3.40314865e-01 -4.09783900e-01
-2.09907860e-01 -5.49222052e-01 -1.02985978e+00 6.24060392e-01
1.24518156e+00 -3.21984589e-01 6.84431344e-02 8.47013652e-01
5.72788239e-01 1.44103423e-01 -8.21548045e-01 7.55971789e-01
5.71104825e-01 -8.95194411e-01 -4.09752995e-01 1.51952788e-01
6.35994434e-01 6.76880002e-01 3.00798744e-01 6.77055776e-01
4.63634044e-01 -9.38893914e-01 1.16036880e+00 2.46620789e-01
6.92767859e-01 -7.37231553e-01 5.74643552e-01 4.01195914e-01
-7.14148164e-01 -1.46679608e-02 -1.82240799e-01 -6.46335185e-02
3.65713418e-01 9.57776666e-01 -6.47416651e-01 -1.46757796e-01
9.75459695e-01 7.60814369e-01 -6.87485099e-01 9.27866876e-01
-5.06172955e-01 1.15753937e+00 -9.58083794e-02 -5.29957891e-01
3.41863722e-01 1.14799373e-01 7.07378089e-01 1.67465878e+00
3.00196409e-01 -3.77312720e-01 7.17413262e-04 7.81938136e-01
-6.86897933e-01 5.94164073e-01 -7.40341961e-01 -6.08404458e-01
3.80907148e-01 1.41840827e+00 -3.33271235e-01 -1.57990903e-01
-2.39334255e-01 6.11768961e-01 8.41696322e-01 -2.32019633e-01
-1.01383924e+00 -6.56476080e-01 4.42299217e-01 2.45238394e-01
-2.68510487e-02 -2.12968856e-01 -5.60318291e-01 -9.98646677e-01
-8.00713226e-02 -1.22378659e+00 4.78632957e-01 -4.94573861e-01
-1.67062330e+00 6.32346213e-01 -1.64749771e-01 -8.51688743e-01
2.15257946e-02 -2.46595860e-01 -6.74663067e-01 6.32465422e-01
-1.03477919e+00 -1.12086749e+00 -4.03713360e-02 3.14536899e-01
7.72894204e-01 -1.40399896e-02 5.63145518e-01 5.07971585e-01
-6.97456479e-01 7.91423440e-01 -3.20589006e-01 4.88037616e-01
1.22076190e+00 -1.06963003e+00 4.67602044e-01 9.41361189e-01
6.38196419e-04 4.97762620e-01 1.06597185e+00 -8.85525703e-01
-7.97595143e-01 -1.17928195e+00 1.62265515e+00 -7.40705550e-01
1.46595013e+00 -6.66873693e-01 -7.46425748e-01 7.32917547e-01
6.17622495e-01 -7.29351163e-01 1.02788126e+00 6.66373253e-01
-9.45059419e-01 1.67993143e-01 -8.96683097e-01 6.43445790e-01
1.30192339e+00 -7.45782077e-01 -6.63251638e-01 5.89191020e-01
5.64182699e-01 -1.37342080e-01 -8.21942389e-01 6.88557699e-02
4.52908158e-01 -8.74137998e-01 4.56083477e-01 -5.47302127e-01
1.07203186e+00 3.13576043e-01 -2.94445921e-02 -1.51904809e+00
-3.73216718e-01 -8.57460618e-01 7.85559863e-02 1.44960856e+00
7.75384903e-01 -1.77871883e-01 4.46235418e-01 3.43300641e-01
-6.87632501e-01 -6.20001256e-01 -9.49083567e-01 -5.62948883e-01
3.93816143e-01 -6.25105083e-01 -7.87967071e-02 1.19891429e+00
6.02142215e-01 5.85071862e-01 -7.41494238e-01 -5.18986881e-01
5.60868144e-01 -1.71077728e-01 5.30506432e-01 -1.11108041e+00
3.77299897e-02 -5.87376833e-01 -1.20997280e-01 -6.35532856e-01
2.05076471e-01 -9.90794003e-01 2.04192817e-01 -1.15077746e+00
5.53835928e-01 6.23922944e-02 -3.10245186e-01 6.57738924e-01
1.00453973e-01 8.18172693e-01 1.69793487e-01 7.32456222e-02
-9.20531213e-01 4.47229326e-01 8.26358855e-01 -2.04172239e-01
-1.22042224e-01 -5.34840167e-01 -1.10868537e+00 7.87869692e-01
1.03461266e+00 -7.09414601e-01 2.25714758e-01 -1.78763121e-01
1.05611169e+00 -4.60275561e-01 -4.24839891e-02 -8.04956198e-01
-1.78714484e-01 1.45934716e-01 -8.12138915e-02 -9.00558531e-01
1.15260057e-01 2.29214266e-01 -3.71341944e-01 4.36439484e-01
-7.53637671e-01 2.82976061e-01 -1.14168480e-01 2.30021343e-01
-2.38231700e-02 -2.76490033e-01 7.23716259e-01 -1.44419204e-02
-2.21486449e-01 7.65465051e-02 -9.78136063e-01 6.34864867e-01
7.33166635e-01 9.90922078e-02 -6.82141066e-01 -3.19048971e-01
-3.68610293e-01 6.42696694e-02 1.11473709e-01 6.70860469e-01
3.59849513e-01 -1.06460702e+00 -1.23686850e+00 -5.12677491e-01
3.20850074e-01 -7.40005374e-01 2.90510833e-01 1.16492367e+00
-3.22507113e-01 8.57999548e-02 -7.47104809e-02 8.57739300e-02
-1.66422522e+00 3.56280684e-01 5.53210974e-02 -6.10625803e-01
-7.38075137e-01 9.88909781e-01 -3.56955528e-01 -1.24324948e-01
8.10367987e-02 9.69358832e-02 -4.76343423e-01 7.90180266e-01
7.12501228e-01 7.99994469e-01 6.31870702e-02 -9.16473269e-01
-1.25380799e-01 6.91257790e-02 -4.41794157e-01 -1.22337110e-01
1.32239139e+00 7.69777149e-02 -3.19568753e-01 7.88481236e-01
1.31585813e+00 4.11533147e-01 -2.72318929e-01 -2.53935307e-01
3.98312360e-01 -1.62437201e-01 1.89196900e-04 -9.34012413e-01
-6.43563449e-01 8.06865692e-01 5.22068441e-02 7.25356758e-01
6.18164778e-01 -3.74490507e-02 1.39506865e+00 3.12820137e-01
1.44782946e-01 -1.72906578e+00 4.01555091e-01 1.18746567e+00
1.22986352e+00 -8.19989502e-01 -1.49320588e-01 -2.80224979e-01
-7.32328475e-01 7.38478303e-01 4.61243570e-01 -2.16799721e-01
2.21417859e-01 1.70379117e-01 1.81226954e-01 -5.37381649e-01
-7.25125015e-01 -9.17465799e-03 1.54461429e-01 1.20293513e-01
9.43220675e-01 1.56225219e-01 -9.29294288e-01 6.90944910e-01
-8.24962974e-01 -3.89763355e-01 8.16789746e-01 4.42371130e-01
-7.65106857e-01 -8.33645761e-01 -1.85982972e-01 6.23528719e-01
-1.23861194e+00 -3.64750236e-01 -1.13685977e+00 5.82315087e-01
9.46938097e-02 1.16447008e+00 -3.59814256e-01 -7.83141315e-01
3.29769105e-01 3.21692824e-01 4.75734733e-02 -6.89715147e-01
-1.31714571e+00 -3.40794548e-02 9.16319430e-01 -5.44970572e-01
-7.68934712e-02 -1.09863853e+00 -9.07622278e-01 -6.50413692e-01
-3.16431135e-01 2.07607716e-01 4.85358536e-01 8.20731461e-01
2.35809937e-01 3.15267414e-01 5.28837562e-01 -4.73701239e-01
-7.97164619e-01 -1.66276860e+00 -6.52198493e-01 5.79052567e-01
-9.58330184e-02 -2.99602836e-01 -5.20596743e-01 -2.74777234e-01] | [8.908026695251465, 10.625113487243652] |
069c49a2-efba-44b0-bbc2-2a9d721c772a | a-benchmark-of-nested-named-entity | 2302.10204 | null | https://arxiv.org/abs/2302.10204v1 | https://arxiv.org/pdf/2302.10204v1.pdf | A Benchmark of Nested Named Entity Recognition Approaches in Historical Structured Documents | Named Entity Recognition (NER) is a key step in the creation of structured data from digitised historical documents. Traditional NER approaches deal with flat named entities, whereas entities often are nested. For example, a postal address might contain a street name and a number. This work compares three nested NER approaches, including two state-of-the-art approaches using Transformer-based architectures. We introduce a new Transformer-based approach based on joint labelling and semantic weighting of errors, evaluated on a collection of 19 th-century Paris trade directories. We evaluate approaches regarding the impact of supervised fine-tuning, unsupervised pre-training with noisy texts, and variation of IOB tagging formats. Our results show that while nested NER approaches enable extracting structured data directly, they do not benefit from the extra knowledge provided during training and reach a performance similar to the base approach on flat entities. Even though all 3 approaches perform well in terms of F1 scores, joint labelling is most suitable for hierarchically structured data. Finally, our experiments reveal the superiority of the IO tagging format on such data. | ['Edwin Carlinet', 'Bertrand Duménieu', 'J Chazalon', 'Nathalie Abadie', 'Solenn Tual'] | 2023-02-20 | null | null | null | null | ['unsupervised-pre-training', 'nested-named-entity-recognition'] | ['methodology', 'natural-language-processing'] | [-2.01651022e-01 3.29937786e-01 1.61156863e-01 -4.42204863e-01
-1.03179634e+00 -9.82032120e-01 8.02381039e-01 6.10472083e-01
-1.02330554e+00 8.60674798e-01 5.59951723e-01 -3.21522415e-01
-2.04528525e-01 -8.25441778e-01 -5.90655684e-01 -1.42465666e-01
-2.10799739e-01 7.67457128e-01 5.21715105e-01 -4.18858588e-01
3.49996239e-01 5.20354986e-01 -1.14219403e+00 3.01101267e-01
8.34870696e-01 7.42541432e-01 6.14891499e-02 3.52081776e-01
-7.33935833e-01 8.27295423e-01 -8.93626332e-01 -9.08962071e-01
8.05901736e-03 1.05536595e-01 -1.29167712e+00 -3.26748848e-01
2.63342321e-01 2.55921900e-01 -1.07009374e-01 7.07500339e-01
6.21687591e-01 6.63325191e-02 5.14821231e-01 -7.52696872e-01
-4.04785365e-01 1.15121031e+00 1.90110996e-01 2.46376365e-01
4.03772801e-01 -4.65232611e-01 1.17878175e+00 -8.96528125e-01
1.02888215e+00 8.68308663e-01 1.26037896e+00 3.16389322e-01
-1.22295308e+00 -3.33769202e-01 -1.12249464e-01 -1.61199480e-01
-1.47433984e+00 -5.72649240e-01 2.12183237e-01 -4.19415176e-01
1.16719270e+00 1.50924549e-01 7.30137900e-02 7.24881351e-01
-2.06038833e-01 6.55277610e-01 1.06994963e+00 -6.19641185e-01
2.30331451e-01 3.53068143e-01 3.46307009e-01 4.14162815e-01
3.81584704e-01 -1.76112637e-01 -3.10988814e-01 -3.36423755e-01
3.39634389e-01 -3.45213801e-01 -2.00332720e-02 -2.79321164e-01
-1.17917490e+00 5.96626759e-01 2.53102720e-01 1.10542881e+00
-4.41983432e-01 -2.25473076e-01 5.65440059e-01 1.02565080e-01
2.63861358e-01 1.03130639e+00 -8.96286905e-01 -3.73374969e-01
-1.50580478e+00 6.93917722e-02 1.29368317e+00 1.02736604e+00
7.20236897e-01 -2.65408933e-01 -1.89755276e-01 7.15117097e-01
1.04301505e-01 2.38603607e-01 4.79055345e-01 -6.38342977e-01
7.42539704e-01 8.00680876e-01 4.20401901e-01 -8.74915123e-01
-8.10525477e-01 -4.02308196e-01 -4.73450899e-01 -3.52797836e-01
6.24082565e-01 -2.13992298e-01 -1.12867510e+00 1.34374535e+00
2.21568152e-01 -2.29628950e-01 1.76925138e-01 3.99786025e-01
9.43353653e-01 4.06645328e-01 4.32388127e-01 9.52115562e-03
1.54950988e+00 -5.75644791e-01 -7.94937551e-01 -1.45747647e-01
9.92350578e-01 -8.21034908e-01 6.18156970e-01 1.63688466e-01
-9.07910287e-01 -3.08642387e-01 -6.74485862e-01 -3.18070024e-01
-9.73497748e-01 2.78725505e-01 4.00465310e-01 9.68230903e-01
-9.65431511e-01 9.79106784e-01 -8.79494369e-01 -6.38918519e-01
3.08854617e-02 3.33840549e-01 -6.58819437e-01 2.04115048e-01
-1.49760342e+00 1.05300486e+00 7.31092691e-01 -5.66728786e-02
-3.65068913e-01 -7.24444866e-01 -8.23793888e-01 3.31108034e-01
3.50913882e-01 -1.45475015e-01 1.38310575e+00 -4.09723580e-01
-9.77387547e-01 8.28147829e-01 -8.81849527e-02 -5.63261390e-01
3.60513330e-01 -3.31248254e-01 -6.87656760e-01 -9.56083685e-02
4.18621212e-01 3.18631232e-01 8.60005319e-02 -1.17040157e+00
-8.07854474e-01 -2.72396773e-01 1.27291888e-01 -1.00983612e-01
-4.44708228e-01 4.16669071e-01 -2.43247807e-01 -7.01866210e-01
-4.73013483e-02 -7.29908943e-01 -3.72812241e-01 -8.70767593e-01
-3.90271217e-01 -3.80355805e-01 3.17365676e-01 -8.85521770e-01
1.79744041e+00 -2.00220585e+00 -2.68769354e-01 2.84867704e-01
-8.52303728e-02 3.47428352e-01 1.90969303e-01 8.31809163e-01
-6.62290156e-02 7.63419330e-01 -8.29037502e-02 -2.85668254e-01
3.18314224e-01 1.06725655e-01 -5.42583242e-02 -2.21777856e-02
2.07513288e-01 6.64169729e-01 -9.23392355e-01 -7.00780272e-01
-1.92354470e-01 4.57442582e-01 -2.88018972e-01 -5.20874672e-02
7.15590939e-02 7.46253803e-02 -4.68945771e-01 5.10360599e-01
3.06588829e-01 -2.26312026e-01 5.20182073e-01 -3.86139244e-01
-4.75701213e-01 9.51815128e-01 -1.42480052e+00 1.66048551e+00
-5.28885961e-01 3.33960861e-01 -4.86444235e-02 -6.45458758e-01
9.28023338e-01 7.34116316e-01 3.51619691e-01 -5.72369635e-01
3.89940962e-02 5.32245576e-01 -3.28086078e-01 -2.70045221e-01
1.10425067e+00 -2.17561394e-01 -6.25447571e-01 8.74141231e-02
4.09538746e-01 1.27461150e-01 6.84833348e-01 2.58607596e-01
1.51740122e+00 1.66669652e-01 4.94655013e-01 -2.50753164e-01
3.59122097e-01 3.80599648e-01 7.21952081e-01 7.57372797e-01
1.00913690e-02 4.85040218e-01 3.25249344e-01 -3.61867577e-01
-1.25543153e+00 -6.99655771e-01 -2.72144467e-01 1.13045990e+00
-1.93178952e-01 -8.13714027e-01 -6.93991005e-01 -1.09971797e+00
-3.31441611e-01 9.35921192e-01 -5.16578436e-01 5.17667174e-01
-8.59655917e-01 -5.44495285e-01 1.07812846e+00 4.13375080e-01
3.11952412e-01 -1.08972955e+00 -4.31139410e-01 6.54269874e-01
-4.99486089e-01 -1.20893288e+00 -1.54166579e-01 5.40322542e-01
-8.04636538e-01 -8.43860865e-01 -6.96898282e-01 -7.47738600e-01
3.48073304e-01 -3.42822552e-01 1.55936253e+00 -8.29836130e-02
1.79613918e-01 1.98429838e-01 -6.80214286e-01 -2.05326259e-01
-4.42899942e-01 9.28258061e-01 -1.95484653e-01 -3.47728789e-01
5.48250139e-01 -4.38179791e-01 -1.73821718e-01 3.69894594e-01
-9.94201541e-01 -4.68158543e-01 7.23532140e-01 7.79130697e-01
2.47686461e-01 1.64902329e-01 3.24164778e-01 -1.29372633e+00
3.04211885e-01 -4.29100662e-01 -3.18059415e-01 5.72037280e-01
-6.23823524e-01 4.99001175e-01 5.84641397e-01 -7.72472769e-02
-1.36855543e+00 9.57791060e-02 -4.48732555e-01 4.26760137e-01
-5.53282022e-01 7.10851908e-01 -2.13207781e-01 1.94101140e-01
9.09848154e-01 -1.08916745e-01 -9.90493655e-01 -9.72525001e-01
2.68741906e-01 8.25523615e-01 4.85594332e-01 -7.57484019e-01
7.31069028e-01 2.62888849e-01 -3.59165370e-01 -5.93515337e-01
-9.88672674e-01 -8.41374755e-01 -1.05051196e+00 1.66093990e-01
7.89535820e-01 -8.16931486e-01 -1.50827080e-01 1.47369802e-01
-1.13652742e+00 -8.18630159e-02 -4.91387606e-01 3.56960952e-01
-1.62030563e-01 4.30691153e-01 -8.10323596e-01 -5.85776865e-01
-2.67817825e-01 -6.05667114e-01 1.09628606e+00 1.70398787e-01
-3.34934562e-01 -1.09121239e+00 2.87245780e-01 3.43342870e-01
3.53002012e-01 1.58781320e-01 7.63388276e-01 -1.49110818e+00
-1.73916683e-01 -3.88087064e-01 -3.70683856e-02 1.37894042e-02
-4.64000702e-02 -2.60450244e-01 -7.11162031e-01 -6.52358457e-02
-4.46340024e-01 -1.55207813e-01 5.78819215e-01 -2.77132094e-01
2.01579511e-01 -3.05442452e-01 -4.29295868e-01 1.01514220e-01
1.60559857e+00 2.33536154e-01 8.96441281e-01 9.91019487e-01
6.40287638e-01 6.61811113e-01 6.05643690e-01 3.27451527e-01
6.60382032e-01 4.95707214e-01 -1.24083109e-01 -2.67452765e-02
5.06957546e-02 -3.19808096e-01 1.61550716e-01 7.89423764e-01
-8.24749097e-02 -2.08763048e-01 -1.42823887e+00 1.01938939e+00
-1.40769827e+00 -1.00061214e+00 -3.64231676e-01 2.21213555e+00
1.15051675e+00 3.07676136e-01 9.15888883e-03 2.41870075e-01
8.16038728e-01 -8.88117328e-02 5.93704022e-02 -2.20706463e-01
-2.28857979e-01 4.49484229e-01 8.79904985e-01 1.36386633e-01
-1.26368797e+00 1.04630506e+00 6.40649462e+00 9.07583058e-01
-7.12308347e-01 2.81670988e-01 1.06681541e-01 4.12442088e-01
-2.69273788e-01 2.80691206e-01 -1.44138157e+00 5.25741577e-01
1.44467270e+00 1.07733279e-01 -1.55255482e-01 7.13684440e-01
-1.14966281e-01 -3.42914686e-02 -8.83882761e-01 4.24779326e-01
-1.73280522e-01 -1.19506383e+00 -2.01097965e-01 1.20166764e-01
6.27639830e-01 2.39567578e-01 -6.72659516e-01 5.48215985e-01
7.19215333e-01 -7.32265651e-01 9.08209562e-01 5.85512996e-01
4.84634548e-01 -5.90855181e-01 1.13675141e+00 2.52574444e-01
-1.20308542e+00 5.25205284e-02 -9.52298492e-02 3.35268855e-01
4.35504466e-01 7.36617208e-01 -8.31979573e-01 9.59537625e-01
8.37067187e-01 1.63667172e-01 -8.53381097e-01 1.22956836e+00
-2.82882750e-01 7.27986455e-01 -6.13232791e-01 2.84201019e-02
2.86818773e-01 2.89649785e-01 4.18240756e-01 1.71386743e+00
3.91334087e-01 -1.41442930e-02 7.66125247e-02 2.38145635e-01
-1.77953079e-01 4.32418406e-01 -3.27017963e-01 -1.73374638e-01
7.38480568e-01 1.30955458e+00 -9.67332482e-01 -5.30893385e-01
-4.11657691e-01 7.92107046e-01 4.25768793e-01 -2.37471331e-02
-6.10918522e-01 -8.71544659e-01 -3.90680917e-02 3.90336126e-01
8.51362109e-01 -2.85085797e-01 -3.02755445e-01 -1.20186257e+00
9.77117792e-02 -7.55468249e-01 6.22449875e-01 -5.82860470e-01
-1.14756596e+00 9.44844186e-01 -5.54016344e-02 -1.02322865e+00
-2.25844204e-01 -4.13982630e-01 -9.60129350e-02 4.56501812e-01
-1.32516074e+00 -1.14251959e+00 1.05211906e-01 1.47708401e-01
1.17002793e-01 1.51525155e-01 1.00420976e+00 8.12036335e-01
-2.37629741e-01 5.67611992e-01 3.70105922e-01 8.32082093e-01
9.20008302e-01 -1.64081037e+00 7.08348334e-01 9.66395974e-01
4.00355011e-01 8.08899224e-01 6.46221757e-01 -7.98415601e-01
-6.12523913e-01 -9.05331254e-01 1.90062678e+00 -6.97870493e-01
8.10367525e-01 -3.41212183e-01 -8.74361873e-01 6.55179501e-01
2.13488534e-01 -2.92331845e-01 8.56697977e-01 6.10811174e-01
-3.92605633e-01 1.68216527e-01 -1.14259493e+00 2.00598881e-01
1.03883946e+00 -4.60255533e-01 -1.20992649e+00 8.68754759e-02
4.72533792e-01 -2.63494998e-01 -1.59152794e+00 3.64231974e-01
3.26388776e-01 -8.60046804e-01 6.62781656e-01 -5.69340706e-01
9.82213169e-02 -5.09928346e-01 -4.95386645e-02 -1.14994848e+00
-2.85698801e-01 -4.64569569e-01 3.06429535e-01 2.01932812e+00
9.15529847e-01 -3.98087084e-01 7.03188956e-01 7.94592083e-01
-5.79660870e-02 1.60638168e-02 -1.00601101e+00 -9.44670796e-01
6.57539964e-02 -3.47416788e-01 7.11255610e-01 1.25634289e+00
1.92046702e-01 5.97657800e-01 -1.79650664e-01 1.37265891e-01
2.60302544e-01 -2.99452990e-01 5.09971559e-01 -1.53661180e+00
8.74057412e-02 2.57003736e-02 -5.43114901e-01 -6.80716991e-01
-8.01406279e-02 -7.41324544e-01 1.92518771e-01 -1.79181087e+00
-1.60437360e-01 -9.87849474e-01 -2.87739009e-01 8.54640603e-01
8.54535960e-03 1.21237792e-01 2.92127281e-01 3.54353875e-01
-8.82154882e-01 5.96193075e-02 3.44159245e-01 1.29536971e-01
-2.36844093e-01 -2.71534234e-01 -5.16887963e-01 6.70956969e-01
5.84438324e-01 -9.81838882e-01 2.53471017e-01 -4.57445979e-01
6.45679414e-01 -6.90652058e-02 -8.84379447e-02 -1.24210072e+00
4.79485333e-01 3.20728779e-01 2.42933348e-01 -5.49251199e-01
-1.08696274e-01 -9.77772117e-01 3.58441174e-01 -6.48773611e-02
-1.77233905e-01 1.00815624e-01 1.01682372e-01 2.57284135e-01
-4.85645175e-01 -6.39606595e-01 3.94612223e-01 -3.61656398e-01
-8.76474380e-01 -2.44350508e-01 -4.94366318e-01 4.36991483e-01
5.18353820e-01 -2.11924121e-01 -1.56164348e-01 2.02868536e-01
-9.86166716e-01 1.30399819e-02 4.64900166e-01 2.74498433e-01
-1.51692733e-01 -1.12047613e+00 -4.95171279e-01 -2.97292650e-01
1.19969778e-01 -1.14367649e-01 -9.07836854e-02 6.18438780e-01
-4.93073791e-01 6.59109414e-01 -8.51590186e-02 -1.93334073e-01
-1.07264984e+00 4.15672272e-01 1.62103429e-01 -1.12350774e+00
-2.53071100e-01 4.92817074e-01 -2.50252724e-01 -9.86773312e-01
4.13668863e-02 -3.05743307e-01 -5.95322549e-01 4.98269677e-01
3.75185460e-01 4.05428886e-01 6.51706815e-01 -8.16429794e-01
-4.25519973e-01 2.67803729e-01 -1.39227122e-01 -3.41146201e-01
1.47958267e+00 -1.67663887e-01 -9.97377094e-04 4.82839286e-01
8.74519110e-01 4.06898439e-01 -4.80326146e-01 -3.59515786e-01
1.04497182e+00 -1.15856109e-02 -1.02040946e-01 -1.05929708e+00
-6.79503083e-01 4.48083013e-01 3.59404892e-01 5.22724211e-01
9.26414609e-01 -3.17888558e-02 8.06424618e-01 6.99832022e-01
7.00728238e-01 -1.32551026e+00 -6.64435267e-01 8.43014359e-01
2.62728602e-01 -9.43791747e-01 1.11353546e-02 -3.74786049e-01
-5.55099845e-01 9.94752347e-01 1.50207639e-01 1.87208399e-01
6.08427703e-01 3.52538615e-01 2.33733237e-01 -2.90658712e-01
-3.00410300e-01 -6.32891595e-01 2.54822999e-01 4.01636422e-01
7.61811614e-01 -2.06107318e-01 -5.92265785e-01 7.03051627e-01
-4.24902111e-01 8.01072177e-03 4.13344651e-01 1.29245400e+00
-3.30515027e-01 -1.45627975e+00 -4.35437828e-01 2.86341518e-01
-1.20470047e+00 -4.63202864e-01 -4.08528566e-01 1.05473840e+00
3.11571866e-01 9.75634217e-01 -5.84666617e-04 -1.81231067e-01
7.41929233e-01 5.02087116e-01 9.12604406e-02 -7.96104670e-01
-1.37753105e+00 -1.03839479e-01 8.29032123e-01 -1.72517166e-01
-7.60056794e-01 -7.85695016e-01 -1.24835479e+00 -1.42091945e-01
-6.98427379e-01 9.70279634e-01 8.09964657e-01 1.00975847e+00
4.88937736e-01 2.17008173e-01 3.46822917e-01 -5.24864733e-01
-3.09775025e-01 -1.15666664e+00 -5.47640920e-01 5.08596241e-01
-7.86221251e-02 -5.11488140e-01 -2.55476147e-01 3.24991971e-01] | [9.698198318481445, 9.494241714477539] |
fc1f87b3-0b49-4aac-a526-5dc89a15c3e1 | weakly-supervised-knowledge-transfer-with | 2303.05148 | null | https://arxiv.org/abs/2303.05148v1 | https://arxiv.org/pdf/2303.05148v1.pdf | Weakly Supervised Knowledge Transfer with Probabilistic Logical Reasoning for Object Detection | Training object detection models usually requires instance-level annotations, such as the positions and labels of all objects present in each image. Such supervision is unfortunately not always available and, more often, only image-level information is provided, also known as weak supervision. Recent works have addressed this limitation by leveraging knowledge from a richly annotated domain. However, the scope of weak supervision supported by these approaches has been very restrictive, preventing them to use all available information. In this work, we propose ProbKT, a framework based on probabilistic logical reasoning that allows to train object detection models with arbitrary types of weak supervision. We empirically show on different datasets that using all available information is beneficial as our ProbKT leads to significant improvement on target domain and better generalization compared to existing baselines. We also showcase the ability of our approach to handle complex logic statements as supervision signal. | ['Edward De Brouwer', 'Yves Moreau', 'Adam Arany', 'Martijn Oldenhof'] | 2023-03-09 | null | null | null | null | ['logical-reasoning'] | ['reasoning'] | [ 3.31191570e-01 4.23845738e-01 -4.09968436e-01 -5.73270023e-01
-5.74023902e-01 -7.43642569e-01 7.47321069e-01 2.66179740e-01
-4.42168921e-01 7.33380854e-01 -2.88935304e-01 -4.90255862e-01
7.61241466e-02 -7.92236865e-01 -1.15338957e+00 -3.66429001e-01
1.20437369e-01 4.42825139e-01 9.28823590e-01 -1.05051054e-02
2.65696123e-02 3.84218276e-01 -1.66949201e+00 6.16142511e-01
6.59971952e-01 1.05266118e+00 2.43029088e-01 3.47172350e-01
-3.48143764e-02 1.00110233e+00 -4.78175402e-01 -4.71801579e-01
3.53509516e-01 -1.66252315e-01 -9.45247710e-01 3.01583916e-01
6.79237247e-01 -4.06153828e-01 3.45676132e-02 1.03172314e+00
-7.53335208e-02 -2.45894909e-01 5.13095915e-01 -1.25828540e+00
-2.80172557e-01 7.91961491e-01 -5.60074747e-01 1.90183789e-01
2.41592497e-01 2.14800104e-01 1.30053782e+00 -4.89642590e-01
6.79948807e-01 1.17350066e+00 5.24943769e-01 4.36701238e-01
-1.59206295e+00 -4.80826408e-01 4.34934616e-01 2.47653544e-01
-1.14526343e+00 -3.82942379e-01 6.33635759e-01 -3.03762466e-01
9.04182673e-01 1.98422506e-01 2.73173809e-01 1.06912696e+00
-4.48738366e-01 1.21073520e+00 1.40533412e+00 -6.93752170e-01
1.69983178e-01 6.02578282e-01 3.29554260e-01 8.64361286e-01
3.27921480e-01 -4.15366367e-02 -4.61689800e-01 3.97236310e-02
5.49341321e-01 -1.56425372e-01 -7.46133551e-02 -6.59804702e-01
-1.13556778e+00 6.36077285e-01 6.10552549e-01 3.37117732e-01
-1.14388108e-01 1.42918661e-01 4.25699651e-01 2.62397289e-01
2.58605570e-01 5.19137859e-01 -5.72613120e-01 1.03710808e-01
-8.14895689e-01 1.72210753e-01 7.72253573e-01 1.04209244e+00
7.92153299e-01 -3.51217657e-01 -1.59242228e-01 4.95250672e-01
1.59445971e-01 2.41528273e-01 1.48191690e-01 -1.06839597e+00
4.58925962e-01 8.26752603e-01 3.02818000e-01 -6.84378326e-01
-2.84522891e-01 -3.28768611e-01 -8.74806419e-02 4.56809312e-01
8.08448493e-01 6.24844478e-03 -9.71322000e-01 1.82700372e+00
2.78221011e-01 1.55368015e-01 -6.19922541e-02 8.93794477e-01
4.96340364e-01 1.77059978e-01 6.05815239e-02 5.78534529e-02
1.31572306e+00 -9.15513933e-01 -4.10673141e-01 -3.24216455e-01
7.50992775e-01 -4.15369749e-01 1.38663590e+00 5.97779632e-01
-7.99491763e-01 -2.23705769e-01 -1.08117330e+00 2.17129346e-02
-4.31593448e-01 1.28584921e-01 9.03108895e-01 7.72473693e-01
-8.38459551e-01 4.93796378e-01 -1.01386702e+00 -2.90646523e-01
7.11880088e-01 3.40082586e-01 -4.42149520e-01 -4.44061548e-01
-8.81721020e-01 9.50881183e-01 6.64376140e-01 -2.72466451e-01
-9.24318075e-01 -4.91688848e-01 -9.57439482e-01 6.56115636e-02
9.76310670e-01 -4.24909234e-01 1.40190101e+00 -1.13934326e+00
-1.17147136e+00 1.03102410e+00 -8.11754391e-02 -8.73457313e-01
7.77902663e-01 -3.54650736e-01 1.40516609e-01 2.02522412e-01
3.11583113e-02 8.75660062e-01 7.28167653e-01 -1.19548500e+00
-5.16479731e-01 -3.17847162e-01 8.66726220e-01 -1.17050968e-01
-4.94424075e-01 1.88178599e-01 -5.07530928e-01 -3.28994960e-01
-1.90369770e-01 -8.99071574e-01 -1.19797252e-01 2.41801426e-01
-5.83268523e-01 -3.52060735e-01 9.79145348e-01 -2.95088470e-01
7.35843241e-01 -2.19419789e+00 -4.08068448e-02 4.24113721e-02
-5.71014136e-02 2.69698620e-01 1.79347359e-02 8.81252065e-02
5.17718680e-02 9.28772613e-02 -3.25978339e-01 -3.75320911e-01
1.63406089e-01 6.77702546e-01 -4.51436460e-01 2.15928957e-01
5.24435580e-01 8.36717904e-01 -9.57615018e-01 -7.48795450e-01
2.38251865e-01 2.02309355e-01 -6.35372818e-01 -1.33112118e-01
-8.16820145e-01 2.27265760e-01 -4.34357435e-01 6.71793818e-01
4.37410206e-01 -5.64223766e-01 2.51041263e-01 -1.16267383e-01
2.85534710e-01 4.09581780e-01 -1.19840932e+00 1.50544226e+00
-4.18348998e-01 5.17234564e-01 9.34097320e-02 -1.12209380e+00
4.33092564e-01 2.45292515e-01 1.70009494e-01 -4.32585627e-01
-8.18736926e-02 7.51958564e-02 1.87278315e-02 -3.08908671e-01
5.04662693e-02 -2.21250132e-01 7.59517998e-02 4.17983741e-01
1.16865166e-01 -3.28432918e-02 4.01542008e-01 3.96343261e-01
1.32644415e+00 4.37631220e-01 1.47571057e-01 -1.43917939e-02
3.90530616e-01 3.29396755e-01 5.62447906e-01 1.07854986e+00
-8.14607441e-02 4.77909714e-01 7.63960421e-01 -9.15116221e-02
-8.64338577e-01 -8.76221061e-01 -3.05120468e-01 1.20440888e+00
1.39347494e-01 -5.53276598e-01 -5.83449185e-01 -1.30064607e+00
6.70001358e-02 7.65922606e-01 -6.34019792e-01 7.64453635e-02
-4.48561311e-01 -6.39210463e-01 4.98553455e-01 7.69894600e-01
3.64212304e-01 -1.07929075e+00 -8.35031986e-01 -2.53348462e-02
1.34132758e-01 -1.60064316e+00 1.55762255e-01 5.06092608e-01
-9.31074023e-01 -1.16366565e+00 -2.05554873e-01 -3.43176603e-01
8.17417860e-01 -6.75455388e-03 1.21234131e+00 2.35928774e-01
-2.56667286e-01 2.76231527e-01 -3.35223615e-01 -5.87827146e-01
-3.18050206e-01 -1.39318436e-01 -1.16095737e-01 -9.85893235e-02
2.12660089e-01 -4.35050130e-01 -1.52617976e-01 3.61567914e-01
-1.01604927e+00 1.01867534e-01 7.66357064e-01 7.68817306e-01
3.84789079e-01 2.85309851e-01 3.97606432e-01 -1.41521585e+00
7.08764642e-02 -5.36912084e-02 -9.01256561e-01 2.23044842e-01
-5.31773329e-01 3.33890617e-01 6.07015669e-01 -4.20218587e-01
-1.12695396e+00 3.39415759e-01 1.70453429e-01 -4.54161108e-01
-5.32651484e-01 5.70081770e-01 -3.18044424e-01 -4.82862256e-02
8.03103566e-01 -6.15040120e-03 -2.29751959e-01 -4.39654619e-01
3.44884604e-01 3.42666030e-01 5.21386862e-01 -7.88323164e-01
7.81837165e-01 7.54425824e-01 8.95779058e-02 -4.00048167e-01
-1.34122169e+00 -4.01181042e-01 -7.55424976e-01 2.02981174e-01
6.37267709e-01 -7.34464705e-01 -4.95976567e-01 5.25986254e-02
-8.38421464e-01 -5.96471012e-01 -2.74276108e-01 4.37703073e-01
-5.59098184e-01 3.87222290e-01 -6.50711656e-01 -8.43423188e-01
2.45527193e-01 -1.23877740e+00 1.03740168e+00 -1.74293756e-01
-9.26516429e-02 -7.93237567e-01 -4.76561546e-01 5.50864279e-01
1.87747106e-01 2.40510195e-01 8.31429124e-01 -8.63447964e-01
-9.14986908e-01 -3.52110744e-01 -3.62024993e-01 4.47347403e-01
5.88994399e-02 -1.70917168e-01 -1.15578246e+00 6.74107671e-02
-1.81530371e-01 -7.18111217e-01 1.07330084e+00 3.05397138e-02
1.21970689e+00 -2.91077882e-01 -5.51000118e-01 8.01030099e-02
1.35001826e+00 -4.70453978e-01 3.17332983e-01 3.89118642e-01
6.00186110e-01 7.66444981e-01 7.65696526e-01 1.46424785e-01
2.39084974e-01 9.68020380e-01 6.13374531e-01 -2.84483116e-02
-1.13392323e-01 -1.27934247e-01 4.23266947e-01 -2.25768954e-01
5.61985672e-02 -1.49801392e-02 -1.01334798e+00 6.62951052e-01
-1.95279610e+00 -9.27558601e-01 -1.56469002e-01 2.11145186e+00
1.18638146e+00 6.83226407e-01 2.19784304e-01 3.06590438e-01
4.12847102e-01 -1.77240536e-01 -5.03111422e-01 5.00642285e-02
-3.16756107e-02 4.85074185e-02 6.01502717e-01 3.81001323e-01
-1.26093054e+00 8.54758203e-01 6.35275602e+00 6.19225979e-01
-1.03150666e+00 1.63125336e-01 3.70253384e-01 -2.48427078e-01
-1.59446880e-01 2.47854203e-01 -7.74895549e-01 3.56264472e-01
7.57470548e-01 3.30219150e-01 1.39215350e-01 1.14370155e+00
-9.02602151e-02 -3.67407501e-01 -1.56698191e+00 6.70123219e-01
-1.20988302e-02 -1.10033906e+00 -2.07112774e-01 1.12696700e-01
5.82657814e-01 1.33291230e-01 -1.41704619e-01 4.08632934e-01
7.32784688e-01 -1.05418634e+00 8.10448706e-01 7.70344883e-02
3.88546765e-01 -4.61086124e-01 8.09458375e-01 8.02542090e-01
-6.52797997e-01 -1.01583838e-01 -1.18480086e-01 -1.19311742e-01
4.17447872e-02 7.09105134e-01 -1.21808946e+00 4.67598706e-01
7.28048563e-01 7.16858625e-01 -8.29386175e-01 8.85620117e-01
-6.60232365e-01 9.35013950e-01 -7.22720802e-01 1.86381176e-01
2.54990488e-01 3.04497093e-01 3.39645892e-01 1.34673285e+00
-2.21465766e-01 -9.24032703e-02 4.81286883e-01 8.91164184e-01
-5.64344414e-03 -1.28002912e-01 -6.59951985e-01 4.10515592e-02
9.14135054e-02 1.12618387e+00 -9.45400119e-01 -5.24430990e-01
-7.21563041e-01 7.74543107e-01 4.16914850e-01 1.99267030e-01
-7.48270273e-01 5.14941365e-02 1.93750352e-01 2.60878265e-01
6.90980315e-01 -1.21720530e-01 -3.45054358e-01 -1.21849120e+00
3.26665789e-01 -7.87161231e-01 6.83017075e-01 -7.77098417e-01
-1.18735230e+00 1.38161495e-01 3.05316567e-01 -8.71992528e-01
-1.84754536e-01 -1.06092691e+00 -3.51451844e-01 6.21023715e-01
-1.76158726e+00 -1.41091919e+00 -1.77542359e-01 4.61441606e-01
3.13143343e-01 1.67794496e-01 6.86091304e-01 1.72582403e-01
-3.54159713e-01 5.51055014e-01 -5.09560049e-01 2.25892514e-01
8.27200830e-01 -1.63889050e+00 -1.93405107e-01 8.68568301e-01
4.62899417e-01 6.85862660e-01 9.55209076e-01 -4.09827352e-01
-1.25059855e+00 -8.89806926e-01 5.44224858e-01 -8.69070172e-01
6.87201858e-01 -4.18529838e-01 -1.00914586e+00 1.10297501e+00
6.81848601e-02 4.52306092e-01 3.94803017e-01 5.37125349e-01
-7.74590909e-01 -8.26377571e-02 -1.13758862e+00 3.79331678e-01
9.46907282e-01 -5.15195131e-01 -6.99914396e-01 4.35235947e-01
6.67042315e-01 -3.35288793e-01 -5.77047527e-01 6.17032230e-01
2.73700953e-01 -1.03289330e+00 8.83870482e-01 -6.01701558e-01
4.32213932e-01 -6.16585970e-01 -1.95646748e-01 -7.74543464e-01
5.85516840e-02 -8.46608728e-03 -3.39177370e-01 1.15763187e+00
5.71470320e-01 -4.17368114e-01 8.43701720e-01 7.25721598e-01
-9.71031114e-02 -5.15082717e-01 -7.06492066e-01 -9.57442820e-01
-1.38915062e-01 -7.02907264e-01 2.49823242e-01 1.09630215e+00
9.77924019e-02 3.78054768e-01 -8.22651461e-02 3.81752104e-01
4.54502225e-01 3.44351709e-01 7.66255498e-01 -1.25593483e+00
-7.02440023e-01 -4.46340233e-01 -7.10127056e-01 -9.16647315e-01
4.24231946e-01 -8.98377836e-01 8.46556500e-02 -1.45180643e+00
3.85158122e-01 -5.53615034e-01 -4.42510813e-01 1.14234364e+00
-1.16882540e-01 3.38952154e-01 6.16795197e-02 7.16375262e-02
-8.88888478e-01 6.40771389e-02 8.78408372e-01 -1.96985260e-01
1.39136568e-01 -4.96279486e-02 -5.84568143e-01 9.19010699e-01
5.78288555e-01 -4.40835923e-01 -4.61097836e-01 -4.47824657e-01
2.47999981e-01 -2.82662451e-01 7.20984221e-01 -9.99268353e-01
6.56787232e-02 -2.13867188e-01 3.41093659e-01 -3.49234879e-01
3.35148215e-01 -1.06973577e+00 -2.95375854e-01 2.01668873e-01
-3.96496117e-01 -5.08339643e-01 2.64182121e-01 7.56456137e-01
-2.43129864e-01 -4.53117847e-01 5.76556206e-01 -2.74058491e-01
-8.96785438e-01 -1.50642246e-01 8.73312801e-02 -1.81343973e-01
1.16220009e+00 -8.05052966e-02 -2.00304911e-01 -1.16381943e-01
-7.03346133e-01 2.36861303e-01 7.47590303e-01 2.47115716e-01
1.40383840e-01 -9.79730070e-01 -5.09448946e-01 -1.27558082e-01
4.93453503e-01 1.48038238e-01 -3.21768790e-01 8.76428843e-01
3.35208625e-02 4.85933185e-01 -8.14727470e-02 -7.91336834e-01
-1.39779031e+00 9.35326219e-01 2.46551603e-01 -3.51855159e-01
-6.93611026e-01 7.24462092e-01 3.22347105e-01 -4.36558068e-01
3.18014830e-01 -4.45619076e-01 -1.30560204e-01 -2.27770522e-01
5.01898706e-01 -2.79049367e-01 1.76722303e-01 -3.80115956e-01
-5.42803288e-01 1.00596599e-01 -3.01454037e-01 -1.72680244e-01
1.28364909e+00 1.58952087e-01 -3.55497710e-02 5.34786046e-01
6.40848100e-01 6.38941824e-02 -1.46258426e+00 -4.98346031e-01
4.70881790e-01 -4.61043268e-01 -6.56544417e-02 -1.04519093e+00
-8.33769083e-01 8.48591149e-01 2.99117386e-01 1.48316458e-01
1.01598668e+00 4.49433625e-01 1.96120098e-01 7.65763283e-01
6.79857969e-01 -7.78484404e-01 2.07345933e-01 3.36742282e-01
4.27123845e-01 -1.65053880e+00 -2.86446922e-02 -6.89810514e-01
-4.88030165e-01 8.58252466e-01 8.38222563e-01 3.95287573e-02
2.85598457e-01 4.10342395e-01 -9.11493003e-02 -1.94406912e-01
-9.28174615e-01 -4.61601168e-01 2.18002304e-01 4.72872019e-01
4.19204742e-01 -1.68885440e-01 6.59150481e-02 5.15881777e-01
1.76681086e-01 2.22920865e-01 4.08338964e-01 1.36430180e+00
-4.12335038e-01 -1.28793502e+00 -5.08760214e-01 4.63164747e-01
-7.20445335e-01 -3.30578499e-02 -4.78006601e-01 7.40605116e-01
1.52281344e-01 8.24601352e-01 -2.20073551e-01 1.15308270e-01
2.33179629e-01 1.83051631e-01 7.11660743e-01 -1.08493340e+00
-2.14721948e-01 -2.38118857e-01 2.30992526e-01 -6.05231583e-01
-6.11188293e-01 -6.84599996e-01 -1.35803080e+00 2.48364374e-01
-4.86775160e-01 -3.05365212e-02 4.44504380e-01 1.18834043e+00
1.82437062e-01 3.93031865e-01 -1.74600761e-02 -5.03016949e-01
-5.78047574e-01 -8.42906773e-01 -3.12538087e-01 6.18420839e-01
4.73089516e-01 -8.32038403e-01 -1.85980618e-01 3.77207696e-01] | [9.424728393554688, 1.0603950023651123] |
8941654b-864a-4a22-85e6-feca0dadb83d | can-chatgpt-reproduce-human-generated-labels | 2304.10145 | null | https://arxiv.org/abs/2304.10145v2 | https://arxiv.org/pdf/2304.10145v2.pdf | Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks | The release of ChatGPT has uncovered a range of possibilities whereby large language models (LLMs) can substitute human intelligence. In this paper, we seek to understand whether ChatGPT has the potential to reproduce human-generated label annotations in social computing tasks. Such an achievement could significantly reduce the cost and complexity of social computing research. As such, we use ChatGPT to relabel five seminal datasets covering stance detection (2x), sentiment analysis, hate speech, and bot detection. Our results highlight that ChatGPT does have the potential to handle these data annotation tasks, although a number of challenges remain. ChatGPT obtains an average accuracy 0.609. Performance is highest for the sentiment analysis dataset, with ChatGPT correctly annotating 64.9% of tweets. Yet, we show that performance varies substantially across individual labels. We believe this work can open up new lines of analysis and act as a basis for future research into the exploitation of ChatGPT for human annotation tasks. | ['Gareth Tyson', 'Pan Hui', 'Ehsan-Ul Haq', 'Peixian Zhang', 'Yiming Zhu'] | 2023-04-20 | null | null | null | null | ['stance-detection'] | ['natural-language-processing'] | [-5.79822250e-02 5.84904015e-01 -2.26764694e-01 -4.68921036e-01
-7.58422971e-01 -8.22176158e-01 8.39541674e-01 3.48573536e-01
-5.69771886e-01 6.18081391e-01 1.77167863e-01 -3.37522656e-01
5.27717233e-01 -2.64003932e-01 -2.16611326e-02 -4.27546024e-01
1.19984940e-01 3.75718474e-01 2.50975907e-01 -3.19809884e-01
5.03860235e-01 3.10636133e-05 -1.14213598e+00 5.90496838e-01
5.15749693e-01 7.08693326e-01 -2.81284451e-01 6.19303167e-01
-3.15592960e-02 1.48821580e+00 -8.53217244e-01 -9.67057526e-01
-7.77014196e-02 -1.83377370e-01 -1.29846394e+00 -1.92050532e-01
3.01198900e-01 1.71239942e-01 1.46580398e-01 9.47417498e-01
5.67465425e-01 -1.64997011e-01 4.84524310e-01 -1.49932027e+00
-7.05465317e-01 9.26673830e-01 -6.03979111e-01 3.55326444e-01
3.74028236e-01 2.13605523e-01 1.29884386e+00 -5.57072997e-01
8.39603543e-01 1.19269395e+00 1.02458918e+00 5.59698761e-01
-1.02272284e+00 -6.83809996e-01 -2.56110072e-01 -1.17371731e-01
-9.92339253e-01 -3.55497867e-01 3.67506236e-01 -6.63617671e-01
9.35813844e-01 3.68078142e-01 3.66618246e-01 1.35350823e+00
8.37686136e-02 8.62317622e-01 1.65651643e+00 -4.93370533e-01
1.33807184e-02 3.93024951e-01 5.29040575e-01 7.04727113e-01
-1.82402600e-03 -5.80508411e-01 -8.14899862e-01 -5.44391394e-01
-5.57876788e-02 -3.34682107e-01 2.05507159e-01 4.88891125e-01
-1.18561137e+00 1.20164287e+00 2.27496058e-01 5.61996341e-01
2.36072447e-02 8.37919489e-02 8.49347055e-01 4.00160700e-01
1.25996900e+00 1.02853942e+00 -4.08331603e-01 -6.59675121e-01
-6.39823675e-01 3.49877775e-01 1.24496591e+00 7.67284989e-01
6.48531258e-01 -3.91764641e-01 -1.45400122e-01 8.51429999e-01
1.54897451e-01 3.40739250e-01 3.93327177e-01 -1.24748063e+00
4.23335403e-01 6.64143562e-01 5.36328107e-02 -1.18043113e+00
-6.95208609e-01 4.74263541e-02 -1.44504458e-01 -1.64409325e-01
5.86746335e-01 -6.48583531e-01 -8.95714164e-02 1.42752981e+00
2.57338971e-01 -1.58309534e-01 -2.44855255e-01 5.80938816e-01
7.07332850e-01 4.07692522e-01 3.12187672e-01 4.57461886e-02
1.55015790e+00 -9.54364657e-01 -6.40479386e-01 -3.63758177e-01
1.40658259e+00 -1.09614038e+00 1.07554221e+00 2.77078420e-01
-1.04201472e+00 7.88013823e-03 -5.67141652e-01 -2.29963064e-01
-4.97476757e-01 -2.14432418e-01 9.16474283e-01 8.50843787e-01
-1.00944281e+00 4.57336873e-01 -6.29141986e-01 -7.59412825e-01
4.46249872e-01 3.57015543e-02 -2.43340945e-03 3.44001740e-01
-1.25685847e+00 1.19618356e+00 -1.33276740e-02 -1.68261558e-01
-2.92249382e-01 -3.87544543e-01 -6.08961880e-01 -4.08737153e-01
3.38437200e-01 7.25224689e-02 1.58079362e+00 -9.35832858e-01
-1.10870194e+00 1.53289020e+00 -6.62959293e-02 -6.05101228e-01
6.30415738e-01 -1.03008382e-01 -1.39288902e-01 -7.46500418e-02
5.58514118e-01 4.48048919e-01 4.26307946e-01 -7.46533573e-01
-4.91595805e-01 -2.09496543e-01 1.65086702e-01 -9.48529840e-02
-7.31479943e-01 9.99172390e-01 1.02655850e-01 -3.39430571e-01
-3.68647277e-01 -1.48027956e+00 7.43350293e-03 -4.80275512e-01
-5.12365699e-01 -7.34941125e-01 8.41658890e-01 -5.54028153e-01
1.19248986e+00 -2.05844140e+00 -1.62146077e-01 -9.03571548e-04
6.47090197e-01 3.93046826e-01 3.95741593e-03 8.18375885e-01
2.65557945e-01 6.92420900e-01 1.34482443e-01 -8.61333191e-01
2.19102532e-01 6.98525533e-02 -1.92911997e-01 4.55537140e-01
1.73363283e-01 1.24376690e+00 -1.05832064e+00 -6.55291200e-01
-2.60123849e-01 2.98845381e-01 -4.02032912e-01 -1.71836466e-01
-1.78684473e-01 3.75560880e-01 -5.52916765e-01 5.72220504e-01
9.93314758e-02 -5.22356510e-01 2.85405755e-01 3.54406953e-01
-4.72179949e-01 6.26159549e-01 -2.77797520e-01 1.16652107e+00
-1.28054738e-01 1.15999067e+00 1.23263381e-01 -5.15541434e-01
8.60399842e-01 3.37768584e-01 3.51805627e-01 -4.64758009e-01
5.12556851e-01 1.83163986e-01 1.29483268e-01 -6.62700236e-01
7.14342058e-01 -2.44757712e-01 -4.86539304e-01 1.19320655e+00
-8.42382535e-02 -1.47765532e-01 8.69433358e-02 5.02269149e-01
1.27970123e+00 -2.70069659e-01 5.53423427e-02 -4.05581892e-01
2.09919110e-01 2.52574861e-01 1.88149825e-01 8.35858703e-01
-6.39587998e-01 1.84434056e-01 9.53307092e-01 -4.93123084e-01
-1.09372580e+00 -1.92887977e-01 3.81471254e-02 1.84868884e+00
-3.36221606e-01 -6.44630253e-01 -1.13025999e+00 -8.47796917e-01
-1.00815527e-01 6.00745142e-01 -5.87204278e-01 1.49748370e-01
-4.93957222e-01 -1.05977786e+00 1.05811405e+00 2.20939919e-01
2.77793437e-01 -1.40926361e+00 -4.36518461e-01 -8.04827362e-03
-4.98172998e-01 -1.50807416e+00 -1.29758179e-01 2.00377733e-01
-3.11815441e-01 -1.08797085e+00 -1.81150675e-01 -7.37395227e-01
2.02347323e-01 2.65880585e-01 1.15752566e+00 5.24385750e-01
9.82620344e-02 3.07408988e-01 -7.60850847e-01 -7.33942866e-01
-7.85806954e-01 7.97969043e-01 1.50023028e-03 -2.02321902e-01
9.45777535e-01 -4.62526768e-01 -1.76135913e-01 3.27227324e-01
-5.61404943e-01 -2.62784176e-02 -1.31219074e-01 4.98387396e-01
-4.07621890e-01 -3.26065481e-01 8.00444007e-01 -1.45444667e+00
1.06999612e+00 -8.41060281e-01 -1.21178091e-01 -1.37765601e-01
-5.86486280e-01 -5.32338262e-01 4.20649260e-01 -2.18395814e-01
-8.12109292e-01 -4.77912635e-01 -8.74639861e-03 2.20466152e-01
-7.85748959e-02 5.55381715e-01 5.97549081e-01 -7.89876580e-02
9.36565995e-01 -4.65976834e-01 7.21268430e-02 -4.96856540e-01
1.21859863e-01 1.03860497e+00 8.40674788e-02 -4.63559866e-01
6.02723479e-01 2.46946722e-01 -4.58891571e-01 -7.08077729e-01
-1.51940739e+00 -6.32686317e-01 -5.27587056e-01 -2.47934520e-01
1.10384488e+00 -8.00534129e-01 -1.07947791e+00 4.34710324e-01
-1.17887998e+00 -7.10831046e-01 9.60255489e-02 -4.58083078e-02
-3.25625062e-01 3.72086346e-01 -1.25704467e+00 -9.40732658e-01
-3.84768575e-01 -8.78656447e-01 9.99054372e-01 2.08954606e-02
-1.10556448e+00 -1.30317700e+00 1.57993481e-01 1.19479239e+00
2.53948152e-01 3.62194985e-01 5.06715119e-01 -1.27262533e+00
-1.10847428e-02 -5.22348642e-01 -1.94712266e-01 3.11897099e-01
-2.30034396e-01 1.48109570e-01 -1.33341217e+00 -1.94489077e-01
-7.38019720e-02 -1.08814847e+00 4.29841876e-01 -2.36783624e-01
7.33373642e-01 -2.53315985e-01 -1.53849289e-01 -1.11441918e-01
7.58485377e-01 -1.84375778e-01 3.24618220e-01 5.31583846e-01
7.63858199e-01 7.68692076e-01 6.29935980e-01 4.67337698e-01
5.72324812e-01 4.57704574e-01 1.69523403e-01 8.80740657e-02
1.33173078e-01 -1.63560361e-01 4.51276720e-01 8.88041258e-01
-2.20983341e-01 -3.32269073e-01 -1.39800584e+00 2.59589642e-01
-1.99905050e+00 -1.07066417e+00 -5.64159811e-01 1.48856258e+00
8.74293208e-01 2.62108922e-01 3.20016503e-01 8.26136693e-02
7.04014421e-01 3.67750257e-01 -4.56911325e-02 -8.25285852e-01
-2.50362302e-03 9.16475877e-02 3.97283196e-01 4.48865116e-01
-1.07671869e+00 1.25369251e+00 6.93946695e+00 6.85642719e-01
-9.26749647e-01 5.80100954e-01 7.21097827e-01 5.58041781e-02
9.83625278e-02 3.68223116e-02 -8.88471365e-01 5.85705698e-01
1.31334615e+00 -3.25742103e-02 4.08866912e-01 7.92641819e-01
2.65187562e-01 -1.35779977e-01 -8.76000404e-01 4.52285588e-01
2.26849645e-01 -1.10701001e+00 -7.23524690e-01 2.70671368e-01
8.94709527e-01 5.61671913e-01 -8.91483054e-02 5.34249365e-01
5.48580766e-01 -8.93818200e-01 6.51480198e-01 1.28986076e-01
4.19846922e-01 -4.46029812e-01 9.62342918e-01 7.62911022e-01
-5.37977636e-01 -1.25889778e-01 -1.24829717e-01 -7.82582045e-01
1.10799946e-01 2.96171248e-01 -1.28585017e+00 -1.43781200e-01
6.91664696e-01 9.25226510e-01 -9.47449446e-01 4.08335477e-01
-2.74632424e-01 9.81066048e-01 -7.76417404e-02 -5.04515111e-01
4.58747596e-01 9.40695256e-02 4.06498462e-01 1.50412154e+00
-3.21780443e-01 2.08811499e-02 4.72846806e-01 6.23626947e-01
-3.27270657e-01 1.96516275e-01 -5.86152136e-01 -5.68757892e-01
4.81763512e-01 1.57533300e+00 -1.03251994e+00 -3.55500162e-01
-4.78407472e-01 8.43150377e-01 7.27940977e-01 -2.46386603e-02
-8.32997441e-01 -5.50128408e-02 3.47601444e-01 1.96506038e-01
-3.73217165e-01 -2.11646229e-01 -5.03813446e-01 -1.18108451e+00
-3.44668567e-01 -9.99211431e-01 2.92928398e-01 -8.72343779e-01
-1.55498672e+00 5.36396980e-01 -2.55962551e-01 -5.65576673e-01
-2.17766851e-01 -5.17760336e-01 -5.59725523e-01 5.24075985e-01
-1.03117645e+00 -1.23620474e+00 -2.72272706e-01 2.46298611e-02
4.39776301e-01 -8.17888975e-02 8.85023475e-01 1.17312402e-01
-6.32542670e-01 5.09999156e-01 -3.09552908e-01 5.58484316e-01
1.00858724e+00 -1.22185755e+00 7.01971292e-01 3.56825083e-01
1.22109659e-01 4.81842190e-01 8.60855460e-01 -6.66549027e-01
-7.82311440e-01 -9.21541929e-01 1.50860834e+00 -1.30893433e+00
1.34710741e+00 -4.79286641e-01 -7.23542750e-01 1.10270429e+00
4.65385020e-01 -2.91443676e-01 1.10022962e+00 5.09371519e-01
-5.62817812e-01 6.21571302e-01 -1.07073510e+00 5.23616970e-01
9.31776464e-01 -8.53258252e-01 -4.47002172e-01 8.40059876e-01
6.31390810e-01 -3.01772922e-01 -1.00363648e+00 -2.38963500e-01
3.93656820e-01 -9.88155901e-01 4.24700588e-01 -7.40485668e-01
7.13151276e-01 2.85754830e-01 9.07295868e-02 -1.05620122e+00
-1.00548215e-01 -9.33166206e-01 1.65618867e-01 1.48869884e+00
6.40534163e-01 -9.26305532e-01 7.23325729e-01 1.17161679e+00
-2.03728050e-01 -5.69720328e-01 -5.90850830e-01 -4.68364239e-01
4.01303709e-01 -5.24271071e-01 1.73622608e-01 1.66786981e+00
6.47466362e-01 7.79594779e-01 -4.65805173e-01 -4.57754374e-01
3.95668089e-01 -3.78771037e-01 9.07666147e-01 -1.51236629e+00
3.05087510e-02 -3.02273303e-01 -2.34141842e-01 -4.02700096e-01
7.16183424e-01 -1.07073236e+00 -2.23486483e-01 -1.06828094e+00
4.74984527e-01 -5.99720418e-01 9.89572629e-02 8.67061555e-01
-3.82933691e-02 1.01474893e+00 5.21255136e-01 3.29588056e-01
-1.12051439e+00 -9.84074548e-02 1.08108270e+00 1.14186794e-01
-1.14166541e-02 -1.77490562e-01 -1.05019855e+00 1.08468223e+00
1.18143976e+00 -7.64535725e-01 -1.19209604e-03 -2.67460138e-01
7.14629412e-01 -4.03709710e-01 2.67989188e-01 -6.14106953e-01
1.05600052e-01 -2.30474070e-01 -1.65744036e-01 5.69942296e-02
3.16354811e-01 -3.58590126e-01 -4.44034338e-01 1.37743250e-01
-7.34155774e-01 2.12125510e-01 -1.49196908e-01 2.73638844e-01
4.74710129e-02 -4.94272292e-01 6.11873448e-01 -3.90483469e-01
-3.13890994e-01 -2.24598303e-01 -8.09586525e-01 5.99611104e-01
9.12432730e-01 -6.25615008e-04 -8.22268367e-01 -5.80517054e-01
-6.79395437e-01 2.73581803e-01 7.17884362e-01 4.13091004e-01
-1.63584903e-01 -8.54617298e-01 -7.03067482e-01 -3.61712277e-01
2.48140424e-01 -4.74422932e-01 -2.48665854e-01 1.06412733e+00
-3.63506794e-01 3.60662758e-01 1.08991951e-01 -4.07851666e-01
-1.43515837e+00 1.66976020e-01 9.45748091e-02 -2.89882839e-01
-4.00970906e-01 8.82645845e-01 -3.70639116e-01 -5.17998457e-01
-3.52078304e-02 1.82713315e-01 -1.71522483e-01 4.50717717e-01
6.24009788e-01 4.42863315e-01 -1.22605354e-01 -9.21958089e-01
-1.69328034e-01 -2.52168812e-03 -2.19713479e-01 -7.99297318e-02
1.39107633e+00 -2.66661882e-01 -4.85464245e-01 8.55670094e-01
1.22321820e+00 2.46677786e-01 -5.82923114e-01 -1.21442430e-01
5.41400075e-01 -1.97124794e-01 -2.21356198e-01 -8.82306516e-01
-5.26260436e-01 6.82781756e-01 -3.80265974e-02 8.97007465e-01
3.69573861e-01 2.58798361e-01 8.98728073e-01 4.29446101e-01
6.14863396e-01 -1.16867447e+00 3.45199615e-01 8.42560709e-01
5.11313975e-01 -1.45131838e+00 3.34094502e-02 -3.93793166e-01
-1.02952707e+00 8.93446088e-01 6.78955197e-01 -1.61557123e-02
3.82982284e-01 2.37392560e-01 3.17490071e-01 -7.14945436e-01
-8.82807910e-01 -9.14250240e-02 -1.31144553e-01 3.43560487e-01
1.09523582e+00 2.23963141e-01 -5.48187613e-01 3.57025892e-01
-5.62201381e-01 -2.25826025e-01 8.75583410e-01 9.71850753e-01
-4.51348394e-01 -1.08875489e+00 -2.64006466e-01 3.07410359e-01
-9.56762791e-01 -2.61842251e-01 -1.13543749e+00 6.72240078e-01
5.33345155e-02 1.24114752e+00 -7.69271180e-02 -4.90998417e-01
-6.47679195e-02 5.60167134e-01 -2.31030285e-02 -1.16358840e+00
-1.31762612e+00 -1.99272677e-01 7.62093425e-01 -3.10004264e-01
-6.37857735e-01 -7.41973460e-01 -1.06231403e+00 -7.94265747e-01
-3.67077351e-01 4.43693072e-01 5.10775328e-01 1.03334737e+00
3.04466814e-01 -7.38548636e-02 4.14726883e-01 -7.44651973e-01
-3.19721848e-01 -1.24136162e+00 -4.04263645e-01 4.29839224e-01
2.41125859e-02 -4.52960640e-01 -5.74441433e-01 7.66857639e-02] | [9.161910057067871, 10.097925186157227] |
6fd3efca-065d-400f-a967-2d3519bbb3c3 | hierarchical-reinforcement-learning-with-4 | 2206.12718 | null | https://arxiv.org/abs/2206.12718v1 | https://arxiv.org/pdf/2206.12718v1.pdf | Hierarchical Reinforcement Learning with Opponent Modeling for Distributed Multi-agent Cooperation | Many real-world applications can be formulated as multi-agent cooperation problems, such as network packet routing and coordination of autonomous vehicles. The emergence of deep reinforcement learning (DRL) provides a promising approach for multi-agent cooperation through the interaction of the agents and environments. However, traditional DRL solutions suffer from the high dimensions of multiple agents with continuous action space during policy search. Besides, the dynamicity of agents' policies makes the training non-stationary. To tackle the issues, we propose a hierarchical reinforcement learning approach with high-level decision-making and low-level individual control for efficient policy search. In particular, the cooperation of multiple agents can be learned in high-level discrete action space efficiently. At the same time, the low-level individual control can be reduced to single-agent reinforcement learning. In addition to hierarchical reinforcement learning, we propose an opponent modeling network to model other agents' policies during the learning process. In contrast to end-to-end DRL approaches, our approach reduces the learning complexity by decomposing the overall task into sub-tasks in a hierarchical way. To evaluate the efficiency of our approach, we conduct a real-world case study in the cooperative lane change scenario. Both simulation and real-world experiments show the superiority of our approach in the collision rate and convergence speed. | ['Huafeng Xu', 'Divya Saxena', 'Shan Jiang', 'Jiannong Cao', 'Zhixuan Liang'] | 2022-06-25 | null | null | null | null | ['hierarchical-reinforcement-learning'] | ['methodology'] | [-4.79232848e-01 1.74743887e-02 -2.39737898e-01 4.36637998e-02
-5.77482045e-01 -3.30030084e-01 5.00972867e-01 3.07137966e-01
-9.42457616e-01 1.13249338e+00 -4.22143638e-01 -2.29054585e-01
-4.57692325e-01 -8.21851671e-01 -5.44515491e-01 -1.02487552e+00
-3.15778553e-01 5.79719007e-01 6.12091362e-01 -4.68289822e-01
5.58241792e-02 4.92211491e-01 -1.35126770e+00 -4.34680521e-01
1.25405729e+00 7.41032898e-01 4.26983118e-01 5.57786882e-01
-1.96577366e-02 1.03477263e+00 -6.46218538e-01 -8.99398234e-03
2.43075833e-01 -1.55071601e-01 -4.76039499e-01 3.28866184e-01
-4.14866626e-01 -3.85060608e-01 -2.71807611e-01 1.10807216e+00
6.12721026e-01 4.36223239e-01 2.92980045e-01 -1.88133085e+00
5.25914952e-02 3.42415154e-01 -8.59739363e-01 -5.50715066e-02
-1.78243741e-02 3.85095239e-01 6.92095220e-01 -2.91245371e-01
3.81436676e-01 1.58104277e+00 2.34845281e-01 5.87685704e-01
-1.07240486e+00 -7.43347406e-01 6.13742828e-01 4.60861921e-01
-1.05867195e+00 -6.20928109e-02 7.83038080e-01 -1.26789436e-01
5.92029452e-01 -2.41876870e-01 7.89020121e-01 7.25574136e-01
4.31911498e-01 9.55098748e-01 1.07193947e+00 -1.17290258e-01
6.00439191e-01 -1.75519779e-01 -3.95656943e-01 7.59470999e-01
3.51476878e-01 4.45404440e-01 5.92121035e-02 -2.84290403e-01
7.64542997e-01 -9.96812209e-02 3.49572033e-01 -6.97676063e-01
-9.40052092e-01 1.04990268e+00 4.47374642e-01 -8.71543437e-02
-7.30331719e-01 2.74783790e-01 4.46667165e-01 5.35951853e-01
4.76495698e-02 3.10916930e-01 -1.31147996e-01 -5.58438003e-02
-2.04722524e-01 4.26485568e-01 6.96866810e-01 6.01346254e-01
9.17899251e-01 3.11830372e-01 1.60471141e-01 8.42761338e-01
5.32654345e-01 4.25455302e-01 1.40760332e-01 -1.38803124e+00
3.50060940e-01 4.14169431e-01 3.59461516e-01 -1.00697815e+00
-5.65371096e-01 -3.36201310e-01 -9.11408961e-01 9.15727437e-01
1.92961037e-01 -7.06985474e-01 -3.43333632e-01 1.85578167e+00
6.13767207e-01 3.59221637e-01 6.16286159e-01 7.53052354e-01
2.40633681e-01 8.70249033e-01 1.80173978e-01 -6.69044197e-01
1.08734381e+00 -1.26953578e+00 -6.09540284e-01 -1.83675066e-01
5.37953079e-01 -3.15434158e-01 4.48763102e-01 2.20587924e-01
-1.10988009e+00 -4.35354978e-01 -8.14180315e-01 7.89251208e-01
-1.83815256e-01 -2.06567079e-01 4.91240084e-01 2.01188534e-01
-1.07372308e+00 6.39411062e-02 -7.26918757e-01 -1.31962046e-01
2.94280767e-01 6.93960011e-01 -5.81782572e-02 5.16658835e-02
-1.29128695e+00 7.87387729e-01 5.28925240e-01 -1.12147287e-01
-1.24375415e+00 -2.32602075e-01 -6.50132120e-01 4.10949551e-02
1.23909962e+00 -3.55199188e-01 1.51787210e+00 -9.20236707e-01
-1.94325197e+00 -3.93452756e-02 2.48241052e-01 -3.94836247e-01
5.81395090e-01 1.87823698e-01 -2.66556084e-01 1.36182502e-01
2.15162396e-01 5.85091889e-01 6.30048990e-01 -1.57133698e+00
-1.35781932e+00 2.20598746e-02 6.68624282e-01 6.51742816e-01
-1.15895577e-01 -1.92120895e-01 -3.00261736e-01 -2.48259783e-01
-6.33950651e-01 -1.04040527e+00 -9.27445352e-01 -2.07188964e-01
3.01236302e-01 -6.43984437e-01 1.01382053e+00 1.22600339e-01
8.99529934e-01 -2.08476019e+00 4.00094807e-01 2.24035963e-01
4.01552230e-01 4.32373554e-01 -5.55782318e-01 6.28852665e-01
6.39174283e-01 -9.68621746e-02 2.67505288e-01 -1.31155223e-01
6.78869560e-02 5.37372231e-01 2.33152375e-01 2.81742364e-01
4.38674400e-03 7.30577648e-01 -1.23454058e+00 -6.12866402e-01
1.93661690e-01 1.73394144e-01 -5.92901707e-01 2.90387541e-01
-2.73408324e-01 5.22467256e-01 -9.33297694e-01 2.29150072e-01
6.06451929e-01 1.85898300e-02 3.61660153e-01 2.89589733e-01
-3.94994676e-01 -3.16163212e-01 -1.33432341e+00 1.13159800e+00
-5.87925494e-01 3.29817623e-01 7.14909971e-01 -1.21296144e+00
7.82212496e-01 2.81690210e-01 9.57280755e-01 -1.06107688e+00
4.69270386e-02 1.51821285e-01 4.88559812e-01 -2.89940327e-01
3.25585544e-01 9.66437384e-02 -3.31935793e-01 4.15975869e-01
-1.91077158e-01 -1.09938839e-02 4.47910458e-01 1.04409993e-01
9.82048810e-01 -2.16476187e-01 3.86760235e-01 -1.10865384e-02
7.56366313e-01 2.66230702e-02 9.74774837e-01 9.51073766e-01
-5.37947357e-01 -6.80555046e-01 6.15150809e-01 -3.55026424e-01
-7.20419645e-01 -7.26240516e-01 6.26309395e-01 1.09831202e+00
8.18458021e-01 -2.51640260e-01 -5.78979790e-01 -6.64631486e-01
1.69948518e-01 4.12464619e-01 -4.14168596e-01 -2.01978639e-01
-6.92862689e-01 -6.58680737e-01 2.57334620e-01 5.05153388e-02
8.12098980e-01 -1.31972384e+00 -1.05805981e+00 7.08519220e-01
1.80751711e-01 -1.40265989e+00 -2.34187350e-01 5.28814048e-02
-2.97057241e-01 -1.09845018e+00 -2.27687523e-01 -8.07385683e-01
5.02472520e-01 5.14022946e-01 6.08277202e-01 2.07720041e-01
-9.93246138e-02 5.63224614e-01 -3.37778419e-01 -4.01483893e-01
-6.28229618e-01 5.31125218e-02 2.67016739e-01 1.00614317e-01
-1.42353550e-01 -4.29851979e-01 -5.00926197e-01 5.51708817e-01
-7.50101447e-01 -5.77521287e-02 9.01486754e-01 9.23208117e-01
3.58474284e-01 6.70911670e-01 1.03732502e+00 -3.20575058e-01
1.07174933e+00 -4.92854059e-01 -1.21879268e+00 2.69344091e-01
-3.68700862e-01 -6.96976483e-02 9.15246487e-01 -6.85940146e-01
-1.00273478e+00 -7.41140321e-02 1.81025997e-01 -2.11966008e-01
-1.21127337e-01 6.00951254e-01 -8.22743550e-02 -2.86917150e-01
6.26390576e-02 2.56857336e-01 5.43462753e-01 1.80017605e-01
9.80274230e-02 4.92292017e-01 4.17473428e-02 -7.69340098e-01
9.31757808e-01 7.70740658e-02 2.88218707e-01 -7.87625670e-01
-2.78807551e-01 -4.62031849e-02 -2.19444647e-01 -6.99347794e-01
6.91051483e-01 -9.42502618e-01 -1.70572853e+00 5.65147340e-01
-1.02705872e+00 -6.27008557e-01 -1.57220334e-01 4.85870868e-01
-7.68977165e-01 3.32546383e-01 -4.00966167e-01 -1.07661045e+00
1.36489406e-01 -1.47704470e+00 5.25345981e-01 5.93814909e-01
5.30816197e-01 -1.09864795e+00 1.78340659e-01 3.06805205e-02
5.64830005e-01 1.62806451e-01 8.01613390e-01 -3.38092834e-01
-6.43739402e-01 1.03537038e-01 -1.87263247e-02 -1.39022032e-02
3.71387973e-02 -2.10705876e-01 -9.56109986e-02 -7.33932376e-01
-2.82165557e-01 -6.67772889e-01 3.14216286e-01 2.69561410e-01
7.61928082e-01 -2.57385075e-01 -4.01287109e-01 -1.40786218e-02
1.48094463e+00 8.76018584e-01 2.53817111e-01 6.03623211e-01
4.28366750e-01 6.26669049e-01 1.01048315e+00 7.67121613e-01
8.62072229e-01 8.17485809e-01 9.22801495e-01 -2.28716195e-01
3.75714749e-01 -6.48819506e-02 6.10082626e-01 4.49518085e-01
-1.86443269e-01 -3.87782276e-01 -8.47015321e-01 1.19359098e-01
-2.53774500e+00 -1.24926734e+00 3.48333895e-01 1.91287875e+00
4.08080608e-01 2.21246511e-01 5.76481581e-01 -2.44917393e-01
6.44424319e-01 7.76612684e-02 -7.71179080e-01 -3.83137882e-01
7.25446567e-02 -6.50925815e-01 5.28992832e-01 7.51512289e-01
-1.01813638e+00 1.19454837e+00 5.60333300e+00 1.03701520e+00
-1.09812176e+00 9.01551843e-02 2.88107753e-01 -1.67707913e-02
1.91828191e-01 -2.16493219e-01 -6.95420444e-01 4.34505671e-01
6.80237114e-01 -3.53706211e-01 8.25784206e-01 6.46688700e-01
6.96242690e-01 -4.06265557e-01 -5.35096645e-01 8.38424504e-01
-4.16488349e-01 -1.21853018e+00 -2.52280742e-01 3.68379831e-01
6.51336491e-01 1.44851640e-01 -2.85677910e-01 7.00310409e-01
9.65567589e-01 -6.62106276e-01 5.22584975e-01 2.09392831e-01
1.79660857e-01 -1.32483971e+00 6.06218934e-01 8.58250201e-01
-1.39400816e+00 -8.01910400e-01 -3.03952336e-01 -1.75174430e-01
2.79612243e-01 -1.79895386e-01 -4.97258753e-01 7.74239004e-01
3.77325654e-01 5.43952167e-01 -2.19388336e-01 1.08176780e+00
-5.78011312e-02 2.36935258e-01 -2.18932897e-01 -4.64297771e-01
8.29648614e-01 -5.20154357e-01 6.76437020e-01 6.65379345e-01
-4.93350998e-02 1.99058563e-01 1.13358212e+00 2.77350754e-01
2.69775122e-01 5.51417610e-03 -6.37956977e-01 1.41154081e-01
5.93824387e-01 1.25208414e+00 -6.36046469e-01 -1.51492387e-01
-5.63197255e-01 5.04689753e-01 6.69408083e-01 6.02809250e-01
-1.04728663e+00 -2.98354864e-01 9.03589845e-01 -2.66186237e-01
3.26220483e-01 -4.66607600e-01 4.68090028e-01 -8.08390856e-01
-1.68018669e-01 -9.93762732e-01 3.17769982e-02 -1.22711897e-01
-1.04312503e+00 6.20903313e-01 -1.97860710e-02 -1.36275804e+00
-4.54509318e-01 -2.85118729e-01 -6.68752015e-01 2.57179260e-01
-1.85267460e+00 -8.60104084e-01 -4.61460017e-02 7.54198790e-01
7.31370628e-01 -7.43039370e-01 5.50413787e-01 2.45087698e-01
-8.88062418e-01 4.03193146e-01 3.66314203e-01 -3.04698981e-02
2.82706380e-01 -1.05248630e+00 -3.05063754e-01 5.73285103e-01
-5.60744226e-01 -2.18581289e-01 5.20838022e-01 -4.19047177e-01
-1.46866047e+00 -9.59969759e-01 5.01307957e-02 4.78919804e-01
8.46429110e-01 -2.62366146e-01 -6.31055117e-01 1.05118655e-01
4.84064311e-01 1.53434817e-02 3.77940744e-01 -1.72540307e-01
2.85394073e-01 -3.86388004e-01 -9.69076991e-01 9.05230761e-01
6.14126861e-01 6.95154071e-02 -2.93388534e-02 7.51270130e-02
5.72767794e-01 -1.30518168e-01 -6.38926327e-01 2.81453013e-01
3.37681681e-01 -6.66574359e-01 6.73413932e-01 -6.24591827e-01
2.09422596e-02 -5.10075152e-01 7.15333745e-02 -1.70374358e+00
-4.73638445e-01 -8.13069582e-01 2.77242195e-02 9.85004961e-01
1.32837638e-01 -8.98635149e-01 6.83359504e-01 2.70150751e-01
3.13913561e-02 -9.47680116e-01 -1.23429239e+00 -9.78644133e-01
9.37957093e-02 -3.23880389e-02 3.65254611e-01 5.73310196e-01
-5.70473261e-03 5.73174655e-01 -6.37763798e-01 3.27305526e-01
8.96686733e-01 -5.06128743e-03 9.66913879e-01 -1.25657392e+00
-4.27100599e-01 -6.11606777e-01 -2.54200310e-01 -9.40896571e-01
7.55228937e-01 -4.48045135e-01 3.36680979e-01 -1.59640646e+00
-6.20276742e-02 -7.47431159e-01 -2.97938347e-01 3.58106524e-01
2.53104512e-02 -5.32580495e-01 6.06969476e-01 7.80015215e-02
-1.25303459e+00 9.27081764e-01 1.42959988e+00 -2.23937944e-01
-3.71966332e-01 2.96372026e-01 -3.68919939e-01 7.02991247e-01
1.00500309e+00 -4.40659612e-01 -8.13307881e-01 -4.26951915e-01
-1.51689857e-01 7.74922609e-01 2.51359254e-01 -9.33282554e-01
6.17532253e-01 -8.15410435e-01 -3.76869351e-01 -3.12975943e-01
4.18203354e-01 -1.11033416e+00 -2.23038360e-01 9.74684179e-01
-1.85794279e-01 3.23475540e-01 1.85522631e-01 8.36106062e-01
-4.28557307e-01 -7.82269612e-02 9.43652153e-01 -2.81366594e-02
-9.31031346e-01 5.35444081e-01 -1.04136813e+00 -2.95623690e-02
1.71660352e+00 -7.83273131e-02 -2.48014241e-01 -6.39171362e-01
-5.01526713e-01 1.25046098e+00 2.24660516e-01 4.39884901e-01
5.62530041e-01 -1.26208723e+00 -7.11336493e-01 -6.35279864e-02
-2.18759239e-01 -3.79397757e-02 2.40137354e-01 8.89024556e-01
-1.36181861e-01 9.84068289e-02 -5.90521455e-01 -3.26891959e-01
-1.15044498e+00 5.60326576e-01 6.47172332e-01 -7.08605766e-01
-2.32244417e-01 1.53834611e-01 1.37171388e-01 -4.14752752e-01
3.86097670e-01 3.62315983e-01 -4.34831321e-01 1.11023180e-01
2.84829915e-01 4.24278706e-01 -6.67177379e-01 -5.68631709e-01
-3.55579257e-01 4.63227868e-01 -9.85382497e-02 -2.71284223e-01
1.38152707e+00 -3.50756645e-01 -4.53175120e-02 2.20146887e-02
7.21093178e-01 -3.05021554e-01 -1.53386688e+00 -3.17482680e-01
-5.44479191e-02 -7.78280646e-02 6.02865219e-02 -6.15592301e-01
-1.11023617e+00 4.63158280e-01 3.98958713e-01 4.37740505e-01
9.86687899e-01 -2.99533814e-01 4.15469050e-01 7.25052655e-01
7.55609453e-01 -1.39954841e+00 4.70137298e-01 7.85829365e-01
6.70494020e-01 -1.45921016e+00 -2.95138776e-01 -2.75884271e-01
-8.51213694e-01 1.04432142e+00 1.20482087e+00 -2.63239354e-01
5.92112839e-01 3.07568580e-01 1.01308964e-01 4.97829169e-02
-1.17165267e+00 -3.97679716e-01 -3.80809844e-01 6.14350557e-01
-3.97263855e-01 7.83407316e-02 -3.64893824e-01 1.20335087e-01
4.53958213e-01 -1.28486425e-01 7.12590516e-01 1.04873967e+00
-7.21228540e-01 -1.35030317e+00 -8.26957002e-02 1.28981903e-01
1.59557424e-02 6.45252526e-01 2.65502613e-02 9.13816869e-01
1.05028041e-02 1.20760047e+00 -4.82478291e-02 -2.53794223e-01
4.22660649e-01 -5.74530602e-01 9.14933458e-02 -2.59078175e-01
-3.67061973e-01 2.63646990e-01 -2.18042694e-02 -6.16583228e-01
-6.01679862e-01 -6.82181656e-01 -1.52150142e+00 -2.82545060e-01
1.24332383e-02 5.70572793e-01 2.21342668e-01 1.06402254e+00
4.52712834e-01 6.73886061e-01 1.17610204e+00 -8.56215835e-01
-7.87340879e-01 -4.61246282e-01 -4.30539459e-01 -3.99619155e-02
5.46756029e-01 -1.00921774e+00 -3.33423913e-02 -8.07997644e-01] | [3.76753830909729, 1.9860918521881104] |
fc4a0467-0d57-4457-8962-1c5701b33d13 | rehearsal-free-online-continual-learning-for | 2306.10860 | null | https://arxiv.org/abs/2306.10860v1 | https://arxiv.org/pdf/2306.10860v1.pdf | Rehearsal-Free Online Continual Learning for Automatic Speech Recognition | Fine-tuning an Automatic Speech Recognition (ASR) model to new domains results in degradation on original domains, referred to as Catastrophic Forgetting (CF). Continual Learning (CL) attempts to train ASR models without suffering from CF. While in ASR, offline CL is usually considered, online CL is a more realistic but also more challenging scenario where the model, unlike in offline CL, does not know when a task boundary occurs. Rehearsal-based methods, which store previously seen utterances in a memory, are often considered for online CL, in ASR and other research domains. However, recent research has shown that weight averaging is an effective method for offline CL in ASR. Based on this result, we propose, in this paper, a rehearsal-free method applicable for online CL. Our method outperforms all baselines, including rehearsal-based methods, in two experiments. Our method is a next step towards general CL for ASR, which should enable CL in all scenarios with few if any constraints. | ['Hugo Van hamme', 'Steven Vander Eeckt'] | 2023-06-19 | null | null | null | null | ['automatic-speech-recognition'] | ['speech'] | [ 3.41690779e-01 -1.02946617e-01 1.29984215e-01 -3.02988023e-01
-7.99010873e-01 -4.61964399e-01 8.21933091e-01 -1.85904354e-02
-6.43406570e-01 7.52174556e-01 3.72469097e-01 -4.31453824e-01
1.93209067e-01 -3.24585199e-01 -6.25013769e-01 -4.64785755e-01
2.97435373e-01 4.80514646e-01 4.58400279e-01 -2.84026712e-01
2.57373750e-01 6.32139385e-01 -1.61310351e+00 4.52781677e-01
7.56365001e-01 5.02917290e-01 9.39149439e-01 5.86940527e-01
-1.63355708e-01 9.40514445e-01 -8.33640158e-01 -3.18088144e-01
-8.72149616e-02 -3.66400927e-01 -8.79271567e-01 1.59041703e-01
2.45080516e-01 -2.33621031e-01 -7.11376846e-01 7.16420412e-01
6.74418688e-01 8.39399874e-01 3.25405091e-01 -6.94017172e-01
-8.45077813e-01 8.27062607e-01 -8.04964378e-02 4.10101205e-01
4.77809250e-01 1.16606735e-01 6.16750300e-01 -1.45321560e+00
4.85968709e-01 1.34449458e+00 4.72264290e-01 1.07017064e+00
-1.04716814e+00 -6.35753155e-01 5.93855262e-01 3.34047049e-01
-1.23321712e+00 -1.20303452e+00 5.72359622e-01 -5.91625795e-02
1.42633259e+00 3.81550819e-01 3.74918431e-01 1.52574348e+00
-1.49398908e-01 1.20001745e+00 1.13149929e+00 -6.68823004e-01
4.84343767e-01 5.62422276e-02 3.37437034e-01 -6.91854805e-02
-1.67878484e-03 1.73069030e-01 -1.12896514e+00 1.59391686e-02
4.72802013e-01 1.41336963e-01 -5.13380170e-01 3.29280016e-03
-1.14457703e+00 4.14326698e-01 -9.98793840e-02 4.14259821e-01
-5.30158222e-01 -1.83932051e-01 2.72440314e-01 7.43142426e-01
5.82111001e-01 5.02721727e-01 -4.66410816e-01 -4.95200455e-01
-1.31354165e+00 1.06866832e-03 5.66371799e-01 9.90487993e-01
5.47597289e-01 4.59742218e-01 -5.47573805e-01 1.31098890e+00
-9.90234502e-03 3.42184216e-01 1.13459527e+00 -7.27386355e-01
3.60732228e-01 1.24675497e-01 2.91909009e-01 -3.33331287e-01
-2.21431047e-01 -5.31282246e-01 -5.83835423e-01 -1.58307120e-01
5.58428802e-02 2.42903650e-01 -1.28952551e+00 1.87977850e+00
-2.32601799e-02 4.68623877e-01 3.14784199e-01 7.86684155e-01
5.55190146e-01 6.95786774e-01 1.28902510e-01 -7.89366603e-01
9.33405876e-01 -1.16385543e+00 -1.19825697e+00 -6.59159660e-01
4.32695240e-01 -7.95529485e-01 1.46379745e+00 7.72961676e-01
-1.23157442e+00 -5.57321310e-01 -9.11728859e-01 1.95468757e-02
-3.44435692e-01 -3.28087881e-02 4.45903927e-01 6.57513857e-01
-1.34785032e+00 5.88162661e-01 -8.85269761e-01 -6.48541927e-01
-4.86563817e-02 7.90748522e-02 -2.84143597e-01 -3.05630714e-01
-1.47790027e+00 1.26331866e+00 3.46502304e-01 3.10880661e-01
-1.26574242e+00 -5.61702788e-01 -7.59867311e-01 -9.45677143e-03
6.37842715e-01 -3.87952119e-01 1.74851823e+00 -8.44123125e-01
-1.77598464e+00 7.06477463e-01 -6.71807170e-01 -9.74620104e-01
4.10344273e-01 -6.14306688e-01 -6.80249989e-01 -3.10722888e-01
-5.57111681e-01 4.04807061e-01 1.20947945e+00 -1.21075940e+00
-3.84482205e-01 -2.71133780e-01 1.20630329e-02 3.95881176e-01
-4.41643089e-01 3.84603553e-02 -3.76827836e-01 -8.75814855e-01
2.35126048e-01 -8.24314058e-01 4.05217335e-03 -6.78053319e-01
5.77958077e-02 -3.71459991e-01 7.85637021e-01 -9.67239857e-01
1.78634799e+00 -2.33634186e+00 1.86764017e-01 -2.59222507e-01
-8.55695903e-02 8.00309896e-01 -2.90523916e-01 6.90392494e-01
-2.16647796e-02 -3.82234715e-02 -1.60487026e-01 -8.26786697e-01
-7.18396448e-04 3.02826732e-01 -7.62505293e-01 1.44940481e-01
6.92509189e-02 7.06368923e-01 -8.97191048e-01 5.97819351e-02
3.18401754e-01 3.79794091e-01 -3.01574826e-01 4.60821867e-01
-1.67436540e-01 2.59432763e-01 2.37224907e-01 3.54657114e-01
5.79222679e-01 1.76650837e-01 1.00122802e-01 2.29454443e-01
-1.74691290e-01 6.08780682e-01 -9.06326056e-01 1.92217469e+00
-8.71068537e-01 5.94993889e-01 -1.71512235e-02 -7.60777771e-01
1.20273173e+00 5.50908804e-01 -2.41194099e-01 -9.34064806e-01
-3.69795531e-01 2.43297458e-01 -6.00482617e-03 -8.46668407e-02
1.00883472e+00 -1.64783314e-01 2.40600556e-01 3.93946052e-01
1.28729761e-01 2.48575509e-02 1.03486896e-01 3.02689880e-01
1.42503536e+00 8.42536986e-02 2.86080450e-01 1.36830747e-01
4.30840701e-01 -3.15165371e-01 6.25535011e-01 1.21473503e+00
-4.20439690e-01 8.47700775e-01 -4.10986602e-01 -2.32201532e-01
-8.51312339e-01 -1.14449275e+00 2.23434597e-01 1.24282300e+00
-1.02177799e-01 -3.34998190e-01 -6.20144606e-01 -4.53873485e-01
-2.71853477e-01 1.43206763e+00 -1.31099850e-01 -6.42431378e-01
-8.03356946e-01 -2.23936915e-01 2.01566398e-01 3.61578852e-01
3.10493916e-01 -1.41177440e+00 -2.73297399e-01 5.36733687e-01
-3.13205451e-01 -1.02697682e+00 -6.44963682e-01 3.64077568e-01
-9.00702596e-01 -3.81411880e-01 -1.04400516e+00 -4.89594579e-01
3.06897163e-01 8.15828383e-01 1.06783962e+00 -1.28639387e-02
2.64766246e-01 5.14132261e-01 -8.30150723e-01 -2.36092627e-01
-7.52316892e-01 2.77859509e-01 4.27260637e-01 7.36201778e-02
6.28058672e-01 -5.14241278e-01 -3.98104489e-01 3.27612519e-01
-8.88820708e-01 -4.82362919e-02 6.55301034e-01 9.67711031e-01
4.51385140e-01 -1.42620146e-01 1.07017052e+00 -9.86174941e-01
8.65454912e-01 -3.64342302e-01 -2.25177541e-01 5.71705818e-01
-6.80988789e-01 4.56165932e-02 5.91380715e-01 -7.93311834e-01
-1.32783604e+00 -1.79273933e-01 -2.71870643e-01 -8.98194790e-01
-2.69622356e-01 4.35437173e-01 -1.16798617e-01 3.59937400e-01
6.88000858e-01 8.02286446e-01 -2.41973147e-01 -7.77113914e-01
1.80929646e-01 1.01267421e+00 3.21566105e-01 -4.08565223e-01
4.77465957e-01 2.96103396e-03 -8.47859561e-01 -1.03687894e+00
-9.93643939e-01 -7.04714060e-01 -4.20009971e-01 -3.12958211e-01
2.52702504e-01 -1.01574552e+00 -1.81145370e-02 5.30242443e-01
-1.19650078e+00 -6.67639256e-01 -4.11770731e-01 3.97714555e-01
-6.01798177e-01 3.08993578e-01 -4.51325327e-01 -1.35667515e+00
-1.93963721e-01 -1.02878320e+00 8.04163218e-01 4.07337248e-02
-4.49034691e-01 -8.81684661e-01 -3.43788564e-02 3.50486726e-01
7.74367213e-01 -6.26962245e-01 4.02606905e-01 -9.05170143e-01
-3.28505337e-01 2.35578846e-02 2.50312418e-01 5.88302672e-01
5.47580943e-02 -4.44554716e-01 -1.33470094e+00 -6.98717892e-01
2.59579122e-01 -3.99783432e-01 1.15002429e+00 1.12374909e-01
1.12473369e+00 -4.61776793e-01 -1.77484125e-01 2.07270402e-02
8.87170434e-01 6.06753230e-01 9.51672435e-01 2.93723404e-01
2.03764245e-01 4.24274802e-01 9.46209133e-01 2.88718641e-01
1.50212020e-01 8.29841375e-01 -7.64781386e-02 2.17171490e-01
-6.49833977e-01 -4.51257885e-01 9.91310894e-01 1.40888202e+00
2.24089667e-01 -5.20492494e-01 -9.08864081e-01 8.04013669e-01
-1.87366509e+00 -9.51438189e-01 4.23723519e-01 2.67068100e+00
1.16122496e+00 1.87817276e-01 -1.69294685e-01 2.10993603e-01
8.21288168e-01 1.70551747e-01 -7.03019857e-01 -5.21475792e-01
-2.33086243e-01 3.14424843e-01 4.69676368e-02 6.34997189e-01
-7.27845967e-01 1.29809225e+00 6.06229734e+00 1.10226119e+00
-1.09817660e+00 6.16703868e-01 1.99858382e-01 -1.82249635e-01
-2.47252241e-01 8.56702179e-02 -9.54028785e-01 4.15646672e-01
1.35947013e+00 -1.57630384e-01 7.37119973e-01 7.84674883e-01
3.03305596e-01 -1.02419443e-01 -1.15946376e+00 1.12509716e+00
2.28231370e-01 -9.05462444e-01 2.64270574e-01 -4.40098017e-01
4.32029963e-01 -5.17178699e-02 3.14372152e-01 8.34805310e-01
2.44697422e-01 -8.28428149e-01 9.14561033e-01 6.16498172e-01
7.28665173e-01 -6.41662002e-01 4.10316646e-01 6.82002306e-01
-7.89750397e-01 -1.54599950e-01 -4.62858528e-01 -7.13969916e-02
2.66627014e-01 5.20316780e-01 -9.79454577e-01 3.71752232e-01
5.62882125e-01 5.60114086e-01 -6.47070587e-01 9.91728961e-01
-1.54211491e-01 1.08777225e+00 9.41790789e-02 1.97022840e-01
-4.75184321e-02 2.35072672e-01 6.77447200e-01 1.35990179e+00
4.75593448e-01 -2.13995744e-02 -7.15504885e-02 4.67372239e-01
5.48444539e-02 4.30494249e-02 -6.61585867e-01 -1.67668551e-01
9.67215002e-01 7.41337776e-01 -2.83640087e-01 -2.20431209e-01
-2.56501108e-01 1.36767840e+00 4.95750815e-01 5.74448884e-01
-5.20059109e-01 -1.90383434e-01 4.48416471e-01 2.99411893e-01
1.79437354e-01 -5.70807457e-01 1.65165171e-01 -1.29210722e+00
-4.37048338e-02 -1.10473752e+00 2.65352815e-01 -1.01392162e+00
-1.21435702e+00 8.12975109e-01 -1.20333321e-01 -1.04341793e+00
-3.31104368e-01 -3.35346669e-01 -2.64365107e-01 6.56808376e-01
-1.65900159e+00 -9.41054642e-01 1.69408135e-02 5.51188707e-01
1.51206326e+00 -3.89934808e-01 8.41727614e-01 3.82868052e-01
-4.54740524e-01 7.46691465e-01 1.95189249e-02 -4.95931804e-01
1.02331662e+00 -1.11087799e+00 4.94952440e-01 1.13300014e+00
4.69677359e-01 9.85614657e-01 8.74031961e-01 -7.28067577e-01
-1.42291725e+00 -1.12680030e+00 1.15489233e+00 -3.82286757e-01
4.24298406e-01 -6.07105553e-01 -1.41251028e+00 8.18556964e-01
3.88536125e-01 -3.43673408e-01 4.14817512e-01 2.94077933e-01
-3.08727294e-01 -1.99253112e-01 -7.96838045e-01 7.34089613e-01
1.36873603e+00 -6.88538074e-01 -9.92321134e-01 3.23213160e-01
1.23052347e+00 -3.72416705e-01 -4.86711860e-01 2.02783778e-01
1.43580258e-01 -8.79191160e-01 7.88475454e-01 -4.31260556e-01
-2.91563749e-01 -2.67547280e-01 -2.07177550e-01 -1.66810215e+00
-3.75737309e-01 -1.02878332e+00 -6.62312746e-01 1.39854336e+00
4.86651450e-01 -7.04176724e-01 2.50890374e-01 4.83465850e-01
-5.69602787e-01 -2.07265526e-01 -1.15112388e+00 -1.24825144e+00
-1.63331375e-01 -7.04517543e-01 4.96533543e-01 7.33666897e-01
-3.28528613e-01 3.49110752e-01 -6.60214961e-01 6.20843321e-02
2.15701237e-01 -3.21750224e-01 5.46538174e-01 -9.42066729e-01
-3.23262155e-01 -1.52263984e-01 8.98680761e-02 -1.25715554e+00
3.96460682e-01 -7.58055031e-01 2.15980768e-01 -1.37514091e+00
-3.16852219e-02 -3.76148343e-01 -6.06787682e-01 4.43187416e-01
-4.29983586e-02 -2.00056821e-01 3.78091663e-01 3.27453464e-01
-7.95387745e-01 7.52471030e-01 1.02196431e+00 -4.60914224e-02
-4.06671613e-01 1.43942863e-01 -4.27338809e-01 4.31391567e-01
7.76545823e-01 -3.71849239e-01 -6.39250219e-01 -4.48118597e-01
-8.11268017e-02 8.24449360e-02 9.31307301e-03 -1.12285364e+00
6.20510280e-01 -1.88677952e-01 -1.04831584e-01 -7.19874382e-01
6.12196147e-01 -6.63603306e-01 3.00274521e-01 1.22122280e-01
-4.97278303e-01 1.73724368e-02 2.80140042e-01 5.30476153e-01
-3.82683426e-01 -4.35188115e-01 7.35258996e-01 -2.32917935e-01
-1.04786730e+00 8.94557498e-03 -5.72043955e-01 5.62193543e-02
6.79607034e-01 -2.86901414e-01 -1.92024380e-01 -5.76671600e-01
-1.10996008e+00 -5.71866408e-02 2.56000072e-01 8.35739017e-01
1.00359750e+00 -1.13881779e+00 -6.26258016e-01 2.31538206e-01
1.44996583e-01 -2.43647024e-01 4.50515091e-01 7.17457473e-01
1.79007560e-01 5.13152301e-01 3.79616648e-01 -3.13284338e-01
-1.12157440e+00 7.52579510e-01 4.58765589e-02 -2.46733025e-01
-5.79524636e-01 7.73099482e-01 1.91505209e-01 -3.24503303e-01
5.54094553e-01 -4.58565205e-02 -2.11169198e-01 1.44309804e-01
7.55267024e-01 3.16345155e-01 5.79796612e-01 -4.29917127e-01
-2.65993029e-01 -8.30608755e-02 -5.80847859e-01 -4.29878205e-01
1.23974931e+00 -6.47721112e-01 2.22580954e-01 1.10584688e+00
5.06714344e-01 -5.42223789e-02 -1.19170642e+00 -4.89797145e-01
3.07889372e-01 -4.95200127e-01 2.29850486e-01 -9.79673982e-01
-6.04887903e-01 1.01365769e+00 4.54506457e-01 1.16407312e-01
1.22284257e+00 -2.06341803e-01 8.84341836e-01 5.20297170e-01
8.01112294e-01 -1.33872223e+00 2.19972223e-01 9.76802349e-01
1.33795369e+00 -1.04811144e+00 -3.81639600e-01 1.39508530e-01
-8.83355021e-01 9.06601727e-01 7.31877267e-01 1.48617208e-01
4.78335261e-01 1.40400782e-01 -8.08735266e-02 4.38270539e-01
-1.28895521e+00 -3.03751856e-01 2.02107020e-02 6.92488611e-01
3.65989447e-01 -1.19153030e-01 -2.91176319e-01 7.12148488e-01
-1.16906643e-01 1.10529423e-01 5.66125929e-01 9.90116060e-01
-5.44647992e-01 -1.15644848e+00 -2.86604762e-01 1.58150390e-01
-1.70443714e-01 -2.92587399e-01 -2.96135664e-01 4.67247337e-01
-3.23674709e-01 1.11720884e+00 -6.61832169e-02 -3.34540933e-01
5.98189354e-01 5.66534758e-01 3.41956913e-01 -9.57721174e-01
-6.62891388e-01 8.44475552e-02 1.24814041e-01 -4.46952581e-01
-1.96689084e-01 -7.47682333e-01 -8.93465281e-01 -1.04326885e-02
-6.34189427e-01 3.48189734e-02 5.22222519e-01 8.51727366e-01
4.51205403e-01 5.07624507e-01 5.46711624e-01 -6.44971311e-01
-8.13504159e-01 -1.26874232e+00 -5.46739697e-01 3.52089137e-01
4.36468184e-01 -7.88604796e-01 -5.52681804e-01 6.25628382e-02] | [14.429802894592285, 6.695429801940918] |
a12260bc-9485-4d1f-8480-73def9700a86 | learning-6-dof-grasping-interaction-via-deep | 1708.07303 | null | http://arxiv.org/abs/1708.07303v4 | http://arxiv.org/pdf/1708.07303v4.pdf | Learning 6-DOF Grasping Interaction via Deep Geometry-aware 3D Representations | This paper focuses on the problem of learning 6-DOF grasping with a parallel
jaw gripper in simulation. We propose the notion of a geometry-aware
representation in grasping based on the assumption that knowledge of 3D
geometry is at the heart of interaction. Our key idea is constraining and
regularizing grasping interaction learning through 3D geometry prediction.
Specifically, we formulate the learning of deep geometry-aware grasping model
in two steps: First, we learn to build mental geometry-aware representation by
reconstructing the scene (i.e., 3D occupancy grid) from RGBD input via
generative 3D shape modeling. Second, we learn to predict grasping outcome with
its internal geometry-aware representation. The learned outcome prediction
model is used to sequentially propose grasping solutions via
analysis-by-synthesis optimization. Our contributions are fourfold: (1) To best
of our knowledge, we are presenting for the first time a method to learn a
6-DOF grasping net from RGBD input; (2) We build a grasping dataset from
demonstrations in virtual reality with rich sensory and interaction
annotations. This dataset includes 101 everyday objects spread across 7
categories, additionally, we propose a data augmentation strategy for effective
learning; (3) We demonstrate that the learned geometry-aware representation
leads to about 10 percent relative performance improvement over the baseline
CNN on grasping objects from our dataset. (4) We further demonstrate that the
model generalizes to novel viewpoints and object instances. | ['James Davidson', 'Yunfei Bai', 'Xinchen Yan', 'Mohi Khansari', 'Honglak Lee', 'Abhinav Gupta', 'Jasmine Hsu', 'Arkanath Pathak'] | 2017-08-24 | null | null | null | null | ['3d-shape-modeling'] | ['computer-vision'] | [ 1.03907183e-01 3.72678041e-01 5.46809845e-02 -4.79744077e-01
-5.00052154e-01 -6.60371602e-01 3.23386699e-01 3.06817647e-02
1.02029018e-01 2.67337292e-01 3.89272809e-01 -5.26186042e-02
-3.20549816e-01 -7.98229754e-01 -1.55598855e+00 -5.46298862e-01
-3.53860766e-01 7.58552909e-01 -1.54432103e-01 -2.68592447e-01
1.84624523e-01 8.92352223e-01 -1.84001827e+00 4.72667366e-01
6.81442559e-01 1.20856988e+00 7.10780501e-01 6.35772467e-01
1.49803385e-01 6.33937538e-01 -2.50266165e-01 2.13013768e-01
6.66860819e-01 5.71639203e-02 -9.16152179e-01 3.52116585e-01
1.51886269e-01 -8.98156047e-01 -4.84177738e-01 4.88477737e-01
2.37446740e-01 2.21199587e-01 7.45743215e-01 -1.19592297e+00
-7.37918615e-01 6.87269449e-01 -1.41796693e-02 -5.26893139e-01
2.83653438e-01 4.16533977e-01 8.48484814e-01 -8.77756178e-01
7.97742069e-01 1.53338456e+00 7.07080737e-02 7.63316810e-01
-1.18595946e+00 -5.47107831e-02 4.18859392e-01 -5.36560081e-02
-9.14364219e-01 9.64360833e-02 9.23488736e-01 -5.41959763e-01
1.09365451e+00 1.19978309e-01 9.86424208e-01 1.37806416e+00
-3.11882724e-03 1.16157961e+00 8.29514921e-01 -3.34645927e-01
4.31786567e-01 -5.65058053e-01 -6.20360039e-02 7.58283675e-01
4.68521845e-03 2.03462131e-02 -4.46819127e-01 5.25619723e-02
1.32322288e+00 3.60388458e-01 -2.62273848e-02 -1.17062068e+00
-1.46939778e+00 4.98781919e-01 8.02178741e-01 -1.27290517e-01
-5.44850826e-01 6.83885574e-01 2.76133895e-01 2.48091035e-02
2.31158182e-01 4.83050644e-01 -8.15571308e-01 -4.76210900e-02
1.70623716e-02 7.04754829e-01 8.86755049e-01 1.45127153e+00
5.64765930e-01 -1.75926730e-01 -3.85766774e-02 5.26786864e-01
3.06978315e-01 5.80125868e-01 -4.80908938e-02 -1.45342445e+00
4.39501375e-01 5.89129210e-01 3.81840348e-01 -4.32279766e-01
-5.16959071e-01 -2.94859782e-02 -4.14037228e-01 6.14244282e-01
4.34963912e-01 2.52311945e-01 -1.13146436e+00 1.72655511e+00
2.51541615e-01 -1.82184100e-01 -5.62446052e-03 1.06415832e+00
7.95162857e-01 1.99914783e-01 1.80189349e-02 2.92147726e-01
9.94123638e-01 -8.42939734e-01 -3.92577380e-01 1.50282085e-01
2.64875352e-01 -2.73864806e-01 1.31725180e+00 5.18086255e-01
-1.10010767e+00 -5.85679710e-01 -9.10022438e-01 -3.95350039e-01
-2.48210847e-01 2.63715982e-01 1.09231162e+00 -7.95606747e-02
-7.72175491e-01 9.21021760e-01 -1.24115467e+00 -3.61777604e-01
4.39507216e-01 3.84987324e-01 -4.44077641e-01 -1.74769223e-01
-3.08066338e-01 9.05518234e-01 3.91166776e-01 -6.98456392e-02
-1.35758889e+00 -6.28650248e-01 -8.41642439e-01 -1.32300824e-01
5.67049921e-01 -9.38333631e-01 1.25392652e+00 -2.86657125e-01
-1.62407923e+00 8.55828881e-01 -5.15656779e-04 3.62791978e-02
4.75168854e-01 -6.03895783e-01 7.15886116e-01 8.58274624e-02
-5.93536161e-02 8.30125928e-01 6.72677517e-01 -2.04936075e+00
-7.27380533e-03 -6.64992094e-01 7.17388690e-01 1.97952300e-01
1.47564366e-01 -8.12346458e-01 -2.99563527e-01 -6.81925654e-01
7.74452031e-01 -9.19497669e-01 -1.44591764e-01 3.67099345e-01
-5.66538155e-01 -4.16755974e-01 7.04534590e-01 -7.17214763e-01
3.76302749e-04 -1.93275607e+00 1.03851593e+00 6.43092841e-02
1.89368889e-01 -1.91070423e-01 -2.03949749e-01 5.78008831e-01
1.56121269e-01 -1.26272827e-01 -9.26676244e-02 -7.21451879e-01
5.40391862e-01 6.66241884e-01 -8.35727215e-01 2.13721871e-01
2.83168137e-01 1.34603417e+00 -9.90513325e-01 3.83673087e-02
6.33451879e-01 6.17059469e-01 -9.88075256e-01 7.20029354e-01
-9.24226403e-01 9.39657092e-01 -6.22019112e-01 1.10887849e+00
5.55162549e-01 -1.35279879e-01 1.43414468e-01 -6.43342614e-01
3.91529202e-02 2.47106522e-01 -8.32808971e-01 2.46383190e+00
-4.73987699e-01 -1.14563487e-01 1.26066178e-01 -1.11616623e+00
9.18500125e-01 8.46677423e-02 7.09262192e-01 -1.82815716e-01
3.28364998e-01 1.01364516e-01 -2.58151352e-01 -9.03069973e-01
1.80262223e-01 2.50999451e-01 -1.31465942e-01 3.46315116e-01
3.62732321e-01 -7.35693395e-01 -4.56039310e-01 -1.83601305e-02
1.02043164e+00 1.17136121e+00 -1.15382873e-01 -7.89574757e-02
-3.19904923e-01 -2.29293201e-02 5.67594506e-02 6.47827804e-01
2.32738003e-01 6.19053662e-01 3.90103161e-01 -6.09776318e-01
-1.31913960e+00 -1.58525479e+00 -2.26976648e-02 1.01179147e+00
2.84805775e-01 -1.80663764e-01 -5.84506094e-01 -5.09405613e-01
6.01658463e-01 5.36901653e-01 -8.31790805e-01 8.03299248e-02
-8.25905442e-01 -1.45000502e-01 -8.36705714e-02 1.06483281e+00
3.97315711e-01 -1.27452922e+00 -1.01607811e+00 -1.87108282e-03
-1.26442224e-01 -1.08982539e+00 2.38524556e-01 4.25523788e-01
-1.14996922e+00 -1.16692221e+00 -5.25614500e-01 -5.82673907e-01
8.71094525e-01 3.32576483e-01 9.31179821e-01 1.39387935e-01
-5.11006117e-01 1.03514493e+00 -7.34102309e-01 -4.16774958e-01
-1.61471218e-01 -2.01822475e-01 1.45710140e-01 -6.29437625e-01
-4.27824408e-02 -9.00794089e-01 -6.19400203e-01 -4.37262990e-02
-6.58746898e-01 2.29910910e-01 6.64267838e-01 6.77900255e-01
8.66147995e-01 -5.18448591e-01 2.76865870e-01 -6.22858442e-02
1.94551826e-01 -2.85867393e-01 -3.62198293e-01 1.70800596e-01
2.68436313e-01 1.43425450e-01 3.32676739e-01 -3.43818337e-01
-8.20693731e-01 4.47688252e-01 -1.58165768e-01 -7.81292558e-01
-4.15704012e-01 1.04014829e-01 -5.07998049e-01 1.45796994e-02
3.36135447e-01 -1.85609367e-02 5.58195263e-02 -8.21371794e-01
7.25957274e-01 3.00696611e-01 6.01712525e-01 -1.23068011e+00
5.75581014e-01 6.92627668e-01 2.23122954e-01 -4.28078204e-01
-7.08450973e-01 -6.95974752e-02 -1.24213374e+00 -1.85328931e-01
1.08621085e+00 -7.99055755e-01 -1.62237775e+00 4.17814791e-01
-1.31993985e+00 -9.29921389e-01 -5.31553507e-01 4.97944087e-01
-1.34591818e+00 1.93924189e-01 -5.60951233e-01 -9.52566147e-01
-7.01394007e-02 -1.28914511e+00 1.62024093e+00 -2.63516217e-01
-1.24015100e-02 -4.11981523e-01 -4.60928112e-01 2.79607236e-01
-1.14558600e-02 8.96977901e-01 9.36515570e-01 -1.70147091e-01
-1.11650097e+00 9.61472765e-02 -1.72588661e-01 2.68481702e-01
3.33334446e-01 -3.66246372e-01 -9.47367787e-01 -3.74979407e-01
-7.76005909e-02 -7.54169524e-01 7.85265923e-01 3.63361746e-01
1.86351430e+00 -7.28716180e-02 -2.95676410e-01 7.18874216e-01
1.22763741e+00 6.48696050e-02 4.06321287e-01 6.94574043e-02
9.94190454e-01 7.44727910e-01 6.87467694e-01 6.67959690e-01
4.98082221e-01 7.58556485e-01 1.29925728e+00 3.62367600e-01
-1.55461133e-01 -5.69697440e-01 -5.47197014e-02 4.48391587e-01
-7.01639473e-01 -1.91241466e-02 -7.82263815e-01 3.58933032e-01
-2.10057330e+00 -5.78335464e-01 3.40750873e-01 1.98980272e+00
4.27984536e-01 -1.79727376e-01 8.12897086e-02 3.01246773e-02
3.39039043e-02 -2.69824326e-01 -9.97190893e-01 7.10614547e-02
2.21617073e-01 3.59538168e-01 1.90051377e-01 4.22993004e-01
-9.22385097e-01 1.00451469e+00 5.48670912e+00 5.61307743e-02
-7.39171684e-01 -3.92208956e-02 -1.82719082e-02 -2.28165910e-01
-2.85192281e-01 -6.79326430e-02 -3.48161459e-01 6.33500814e-02
-2.19526649e-01 4.12103295e-01 7.97659039e-01 1.16297984e+00
-1.52334541e-01 1.06728442e-01 -1.72826767e+00 9.58322525e-01
6.11699373e-02 -1.11684167e+00 1.82601482e-01 2.14981765e-01
4.31926191e-01 -2.92550176e-02 -1.48337692e-01 2.57182330e-01
5.88991165e-01 -1.07027984e+00 1.23200142e+00 7.47989118e-01
6.83097005e-01 -4.20051277e-01 2.11634740e-01 5.34849942e-01
-9.80345130e-01 -3.72608840e-01 -4.25965965e-01 -3.07845742e-01
2.53843546e-01 2.01020330e-01 -5.71614504e-01 6.18865132e-01
9.39862967e-01 6.66000366e-01 2.86383122e-01 6.14648521e-01
-4.37861770e-01 -9.37523544e-02 -1.73982620e-01 3.45269740e-02
-4.45363224e-02 8.62637255e-03 6.27341330e-01 5.96027732e-01
2.39588737e-01 5.85636020e-01 3.58226955e-01 1.23076558e+00
-1.71682835e-02 -4.31076705e-01 -6.73940957e-01 9.31190178e-02
3.54239732e-01 8.21092248e-01 -6.56816244e-01 -1.77621424e-01
6.25892952e-02 1.10174882e+00 5.63885450e-01 3.11120063e-01
-5.40580630e-01 1.32694952e-02 8.36909771e-01 -3.53657119e-02
4.67649996e-01 -7.89210856e-01 -5.17246842e-01 -1.18557751e+00
3.24170262e-01 -4.57208127e-01 -3.79748523e-01 -1.04081380e+00
-1.28527248e+00 3.32600504e-01 3.88966262e-01 -9.66565311e-01
-6.88166842e-02 -1.21388483e+00 -9.01824012e-02 7.49411523e-01
-1.19648743e+00 -1.53196073e+00 -8.48245025e-01 4.48508352e-01
6.90882027e-01 5.68839014e-02 1.12654471e+00 -4.18316931e-01
2.06241220e-01 3.46583575e-02 -2.81669706e-01 -1.55258588e-02
1.58783540e-01 -1.35579562e+00 4.27383959e-01 4.60513830e-02
-2.14871228e-01 8.37197661e-01 5.17871976e-01 -6.49820149e-01
-2.24793792e+00 -8.61765206e-01 1.21927321e-01 -9.29559350e-01
2.24774465e-01 -8.77364695e-01 -6.43487692e-01 1.04880500e+00
-2.65079886e-01 1.25291586e-01 1.71275377e-01 -4.25045229e-02
-4.98504966e-01 1.50655746e-01 -1.36409819e+00 4.75391448e-01
1.78567266e+00 -3.86302441e-01 -8.39779317e-01 6.07848883e-01
1.00616908e+00 -1.02924955e+00 -1.06873620e+00 8.17966521e-01
1.00130129e+00 -6.70675814e-01 1.33979678e+00 -8.24570239e-01
8.01739454e-01 -3.74216996e-02 -9.06117260e-01 -1.21404147e+00
-2.13166595e-01 -2.52473593e-01 -4.38322634e-01 6.48306727e-01
-3.02089363e-01 -2.77622193e-01 7.41459489e-01 5.66885829e-01
-5.77425063e-01 -1.03566086e+00 -7.69488096e-01 -7.30909050e-01
2.28522569e-01 -5.16020775e-01 7.26738691e-01 5.92330992e-01
6.78571314e-02 -3.92311603e-01 -1.39258921e-01 3.38105440e-01
8.37157965e-01 5.82309365e-01 1.09431541e+00 -1.17215574e+00
-6.35419607e-01 -1.11664459e-01 -2.67192394e-01 -1.66368353e+00
3.57134283e-01 -9.02893722e-01 4.25599605e-01 -1.90825224e+00
3.03771347e-01 -7.36974061e-01 1.28005430e-01 6.91585958e-01
2.36524075e-01 -9.06683803e-02 5.33300996e-01 2.35688403e-01
-2.08603695e-01 8.05715561e-01 1.74799609e+00 -7.86940679e-02
-1.31837979e-01 -1.86471522e-01 -3.17423582e-01 5.77127337e-01
7.43575752e-01 1.30126297e-01 -4.07180041e-01 -8.61530542e-01
-9.26160906e-03 1.74618244e-01 1.16730618e+00 -7.33859062e-01
-3.69154096e-01 -3.20315272e-01 4.76646185e-01 -7.27106869e-01
8.39818895e-01 -8.93296301e-01 -1.29448414e-01 5.02805591e-01
-3.41741443e-01 -2.71632731e-01 2.72746593e-01 6.12974346e-01
4.74183589e-01 5.44583462e-02 1.34487763e-01 -5.40293157e-01
-7.27190733e-01 3.94522578e-01 1.10966884e-01 -3.65511984e-01
9.21490133e-01 -7.00632250e-03 -1.82259575e-01 -1.37348846e-01
-1.13221300e+00 -7.30259158e-03 6.18050933e-01 6.46179616e-01
7.69346476e-01 -1.34058201e+00 -3.94363105e-01 1.43677294e-01
5.85263819e-02 6.01192892e-01 1.79768294e-01 2.38299966e-01
-5.01955986e-01 1.88132584e-01 -4.78536278e-01 -9.13182199e-01
-8.60901535e-01 6.54918432e-01 6.09805770e-02 3.97921652e-01
-1.01164830e+00 1.04801190e+00 2.84632534e-01 -8.43833923e-01
7.08537936e-01 -8.07481289e-01 3.14836115e-01 -6.28022194e-01
3.78786847e-02 2.24158511e-01 -6.37345612e-02 -2.77620614e-01
-1.84496149e-01 6.74820602e-01 2.89600581e-01 -3.03268433e-03
1.79869807e+00 2.31795579e-01 -2.47832388e-01 5.46266377e-01
1.10592115e+00 -4.83265191e-01 -1.84621572e+00 5.73600158e-02
-5.23243725e-01 -5.89886665e-01 -4.83824641e-01 -9.61566329e-01
-7.74442911e-01 1.05127835e+00 3.32148403e-01 -2.84881741e-01
7.90186167e-01 6.02932394e-01 4.99936134e-01 9.41834569e-01
9.67975080e-01 -8.13469231e-01 7.14998186e-01 6.86767340e-01
1.73711848e+00 -1.22779870e+00 -2.62721002e-01 -6.66097820e-01
-2.58948296e-01 1.20269132e+00 7.39579260e-01 -5.80295503e-01
6.73936129e-01 4.24692541e-01 -3.83469373e-01 -4.55475688e-01
-4.12344843e-01 -1.82414517e-01 1.71938106e-01 8.14075351e-01
5.33226952e-02 2.85547167e-01 2.04190761e-01 6.77396953e-01
-2.93984443e-01 -2.66135726e-02 3.07795461e-02 1.35585308e+00
-3.83176386e-01 -1.00047874e+00 -7.57637024e-02 2.03012139e-01
2.05046013e-01 3.44706267e-01 -3.64566326e-01 6.94105268e-01
3.29968154e-01 6.32663667e-01 8.47136974e-02 -5.67319572e-01
5.85695982e-01 -2.80556958e-02 1.43263435e+00 -7.89733648e-01
-9.73523483e-02 -1.80443183e-01 -4.28938776e-01 -1.00886369e+00
-4.50526386e-01 -6.05135560e-01 -1.57544577e+00 8.62113480e-03
4.76134233e-02 -4.93894696e-01 1.03033364e+00 9.45974648e-01
3.22098970e-01 7.90751815e-01 2.96199977e-01 -1.90207124e+00
-8.25239062e-01 -9.39503491e-01 -4.88740891e-01 6.25183642e-01
3.19308370e-01 -1.24441111e+00 -1.34322941e-01 8.00466016e-02] | [5.763444900512695, -0.8376744389533997] |
1661f468-4c88-4f87-b77a-035006949cab | sat-improving-semi-supervised-text | 2210.12653 | null | https://arxiv.org/abs/2210.12653v1 | https://arxiv.org/pdf/2210.12653v1.pdf | SAT: Improving Semi-Supervised Text Classification with Simple Instance-Adaptive Self-Training | Self-training methods have been explored in recent years and have exhibited great performance in improving semi-supervised learning. This work presents a Simple instance-Adaptive self-Training method (SAT) for semi-supervised text classification. SAT first generates two augmented views for each unlabeled data and then trains a meta-learner to automatically identify the relative strength of augmentations based on the similarity between the original view and the augmented views. The weakly-augmented view is fed to the model to produce a pseudo-label and the strongly-augmented view is used to train the model to predict the same pseudo-label. We conducted extensive experiments and analyses on three text classification datasets and found that with varying sizes of labeled training data, SAT consistently shows competitive performance compared to existing semi-supervised learning methods. Our code can be found at \url{https://github.com/declare-lab/SAT.git}. | ['Soujanya Poria', 'Wei Han', 'Hui Chen'] | 2022-10-23 | null | null | null | null | ['semi-supervised-text-classification-1'] | ['natural-language-processing'] | [ 4.36947405e-01 4.67475653e-01 -7.36803114e-01 -8.30836952e-01
-8.45892489e-01 -5.43421984e-01 7.04986334e-01 1.82948485e-01
-2.44158596e-01 7.16165304e-01 3.33539784e-01 -3.05509150e-01
4.68035042e-01 -2.56228715e-01 -4.14920926e-01 -4.59678829e-01
4.02305722e-01 9.71063077e-01 1.04039431e-01 1.23696744e-01
9.49210897e-02 -3.18374097e-01 -1.47161818e+00 6.60144925e-01
8.10356200e-01 6.47594273e-01 -9.10425782e-02 5.86469650e-01
-2.41999507e-01 8.45193863e-01 -2.64839202e-01 -3.52895170e-01
2.33732045e-01 -7.12951005e-01 -1.24444878e+00 4.31942195e-01
5.14800549e-01 -7.40876272e-02 -1.40768394e-01 8.44256520e-01
1.85565293e-01 6.98613971e-02 5.47428370e-01 -1.39756370e+00
-3.64133120e-01 9.00393724e-01 -6.53502166e-01 2.01171294e-01
3.16753179e-01 -2.32356191e-01 1.02468145e+00 -1.06665051e+00
7.58726001e-01 8.82529318e-01 3.78420889e-01 8.93098593e-01
-1.28467810e+00 -7.66697884e-01 2.26561293e-01 -8.00682828e-02
-9.04678822e-01 -5.75740635e-01 7.50478208e-01 -1.68221816e-01
6.18543208e-01 5.88045940e-02 3.73732120e-01 1.12670910e+00
-2.18925565e-01 1.25823760e+00 1.60631025e+00 -7.69622087e-01
2.10551411e-01 7.64880598e-01 4.92703140e-01 8.66241932e-01
-3.00185662e-03 -1.39294147e-01 -6.63782954e-01 -3.77210438e-01
2.94087201e-01 1.20527439e-01 -4.03526016e-02 -5.07086158e-01
-1.22621369e+00 7.49789894e-01 2.50334471e-01 3.62502396e-01
-9.51349065e-02 -2.95069665e-01 4.79677498e-01 4.40515697e-01
9.87485886e-01 2.81933099e-01 -9.10916567e-01 -1.60137177e-01
-1.06122577e+00 -1.53662890e-01 8.63906682e-01 8.14273477e-01
7.57656932e-01 -1.14995979e-01 1.55407161e-01 1.14288330e+00
3.12657744e-01 2.22141713e-01 7.66538620e-01 -7.96351373e-01
7.65369892e-01 1.05384803e+00 -1.55323580e-01 -1.14652693e-01
-3.83411437e-01 -4.70783532e-01 -6.64087951e-01 1.64329782e-01
5.27705550e-01 -4.44561869e-01 -9.37567949e-01 1.51955140e+00
5.13587773e-01 -1.07684443e-02 2.04729557e-01 5.56479275e-01
8.39231074e-01 4.63312954e-01 1.05058402e-01 -2.39227012e-01
1.05745256e+00 -1.36277413e+00 -6.04041338e-01 -6.09824002e-01
1.23167336e+00 -5.78004897e-01 1.03513598e+00 1.67366445e-01
-1.11359596e+00 -5.10193706e-01 -1.07310188e+00 2.38527149e-01
-3.70898247e-01 2.57646769e-01 2.68421799e-01 4.46573436e-01
-9.12532866e-01 5.48508823e-01 -8.71806741e-01 -4.65542197e-01
5.68055093e-01 2.55525321e-01 -4.88929093e-01 -6.28376454e-02
-9.04615998e-01 7.28563368e-01 6.05576277e-01 -4.99260604e-01
-6.42146230e-01 -4.02850986e-01 -7.68239558e-01 -1.25676826e-01
4.27902997e-01 -3.62255007e-01 1.44480848e+00 -1.51924181e+00
-1.20384073e+00 1.26720393e+00 -3.91109437e-01 -3.70687217e-01
5.57621181e-01 -1.02591954e-01 -3.22476506e-01 3.15808468e-02
3.00193697e-01 7.85128593e-01 8.13705206e-01 -1.58986700e+00
-7.58887529e-01 -6.99707866e-01 -1.85436845e-01 6.42573953e-01
-6.18070483e-01 -3.27245705e-02 -3.13386947e-01 -5.08857787e-01
4.09791768e-01 -1.25125909e+00 -3.86635140e-02 -2.92874664e-01
-4.44510430e-01 -3.26088369e-01 1.10993361e+00 -2.71888971e-01
1.00864470e+00 -1.98197901e+00 1.16440631e-01 -5.96282706e-02
1.69715196e-01 3.76514971e-01 -6.87401276e-03 3.29908103e-01
-5.92922807e-01 8.95124525e-02 -2.33374640e-01 -7.72763491e-01
-3.90872508e-01 -9.45124775e-02 -1.87446743e-01 3.16139519e-01
-3.71457599e-02 7.41383195e-01 -1.04863000e+00 -6.36411548e-01
4.55932245e-02 1.26189813e-02 -3.39970216e-02 4.10445303e-01
-3.85136515e-01 3.88974249e-01 -3.89830798e-01 4.35901016e-01
4.17846709e-01 -9.23906565e-01 4.03941661e-01 1.57492399e-01
1.90898404e-01 3.73126149e-01 -1.14948654e+00 1.35080755e+00
-2.37601459e-01 4.66328859e-01 -1.67586684e-01 -9.39437866e-01
9.35031712e-01 5.38949072e-01 4.45981473e-01 -4.20584410e-01
1.85400873e-01 5.93117848e-02 -3.79928350e-01 -2.27818340e-01
1.43134996e-01 -1.04185082e-01 2.17325687e-01 1.33884680e+00
3.22598219e-01 6.69923201e-02 2.27450028e-01 5.75931609e-01
8.05271268e-01 4.47830856e-01 4.02264923e-01 -2.77812909e-02
6.27151549e-01 3.56231660e-01 9.29628015e-02 4.39641207e-01
-2.47938141e-01 4.75865096e-01 2.51742154e-01 -6.28631532e-01
-1.01936567e+00 -7.72367716e-01 -1.15929879e-01 1.62622929e+00
-1.35373265e-01 -4.98803139e-01 -6.84661627e-01 -1.55652654e+00
-9.96848866e-02 8.82834315e-01 -8.71487260e-01 -8.75043944e-02
-9.19147432e-02 -4.97960329e-01 1.78157583e-01 8.13409567e-01
6.40192688e-01 -1.02636361e+00 -2.45567381e-01 -1.07170701e-01
-2.33535931e-01 -1.00166202e+00 -4.72906679e-01 7.60143876e-01
-1.23882675e+00 -9.59296763e-01 -5.22682309e-01 -1.06618822e+00
1.20519757e+00 5.03581047e-01 1.00829387e+00 2.80486047e-01
2.62163073e-01 3.04181874e-01 -5.50408661e-01 -4.67564642e-01
-9.57158744e-01 1.49154916e-01 5.37525602e-02 -8.76123644e-03
5.15839696e-01 -3.09914231e-01 -2.99478740e-01 5.30157328e-01
-7.80688643e-01 5.04800797e-01 2.22781196e-01 1.03842378e+00
6.23806596e-01 -1.69369966e-01 6.22558177e-01 -1.65755963e+00
2.12919384e-01 -6.29376709e-01 -3.78222972e-01 1.67325333e-01
-1.04292965e+00 1.98863968e-01 7.52721548e-01 -3.61296207e-01
-1.23709643e+00 4.11721170e-01 1.79906040e-01 -3.45510840e-01
-4.86303568e-01 5.71723461e-01 2.54360825e-01 4.19506431e-01
9.03258622e-01 3.50705534e-01 7.24632889e-02 -2.49679461e-01
2.90952981e-01 9.53491867e-01 1.70674503e-01 -2.84396440e-01
7.82958627e-01 7.15968132e-01 -4.89213645e-01 -3.82847369e-01
-1.58815432e+00 -6.84772015e-01 -1.09127319e+00 -1.75915048e-01
5.33949196e-01 -9.94586110e-01 1.41036063e-01 3.34773988e-01
-4.41982627e-01 -7.51088321e-01 -3.30332309e-01 3.34976554e-01
-4.75946337e-01 2.34755963e-01 -4.29947406e-01 -7.05307484e-01
-4.86531287e-01 -7.36758471e-01 9.17585909e-01 3.65991980e-01
-3.73402864e-01 -1.42278326e+00 3.27015817e-01 9.28567111e-01
3.15566175e-02 -2.59124547e-01 5.87382019e-01 -1.40804052e+00
9.99827832e-02 -3.81990463e-01 -5.80154136e-02 2.92201549e-01
3.20218116e-01 -2.18113288e-01 -1.24027717e+00 -5.26556790e-01
-1.18153200e-01 -1.11251521e+00 7.91491270e-01 1.44949257e-01
1.00167203e+00 -6.68815002e-02 -5.62388480e-01 4.43389982e-01
1.02970326e+00 -1.14624515e-01 1.59366801e-01 4.64178979e-01
7.09590137e-01 5.50405443e-01 8.12809169e-01 4.29844230e-01
4.16443706e-01 3.26061010e-01 1.82163388e-01 -2.98539639e-01
-6.27359152e-02 -4.14225221e-01 2.45222971e-01 6.51927710e-01
1.58958822e-01 -3.30886424e-01 -9.58955348e-01 2.88987190e-01
-1.92279100e+00 -9.35280979e-01 -5.60487732e-02 2.14302468e+00
1.09754956e+00 3.98018867e-01 3.05104941e-01 2.00931609e-01
6.98631227e-01 2.66705960e-01 -7.04185724e-01 -1.31865323e-01
2.17709765e-02 5.60953794e-03 1.79362178e-01 2.91852593e-01
-1.36370242e+00 1.02979481e+00 6.14040184e+00 3.50348085e-01
-9.31488276e-01 1.80672392e-01 9.67905521e-01 -1.35578692e-01
-1.03800200e-01 1.54098928e-01 -8.68380129e-01 2.73254097e-01
1.16475010e+00 -1.53420269e-01 5.35600223e-02 1.00062358e+00
-9.49570835e-02 -1.71739236e-01 -1.17617214e+00 5.26997805e-01
3.93691152e-01 -1.16947949e+00 -5.31895040e-03 -6.34698421e-02
1.22940934e+00 3.07989210e-01 6.83149248e-02 2.90984482e-01
6.57731712e-01 -5.98369420e-01 3.48136008e-01 1.65469702e-02
8.66707742e-01 -5.52527666e-01 7.03833938e-01 6.98617816e-01
-1.00360096e+00 1.53831346e-02 2.13351613e-03 3.76497656e-02
-2.75930107e-01 1.63318783e-01 -1.13011026e+00 3.01014274e-01
5.91219664e-01 9.12955582e-01 -8.93619061e-01 4.71377492e-01
-3.26343089e-01 1.05327904e+00 -8.68525952e-02 9.86214951e-02
1.20207712e-01 -9.04849246e-02 2.55360961e-01 1.07162011e+00
-3.31027299e-01 6.20001927e-02 4.81365412e-01 4.36653376e-01
-2.87919164e-01 2.21577182e-01 -5.14540792e-01 -1.19253159e-01
3.68343562e-01 1.42995203e+00 -9.78183031e-01 -8.73344064e-01
-7.14917898e-01 1.03927779e+00 6.44259930e-01 2.47941062e-01
-5.10450780e-01 1.56712651e-01 -9.86636281e-02 1.21613860e-01
1.44399136e-01 1.87562600e-01 -4.27857190e-01 -1.28805852e+00
-1.72880188e-01 -9.40186560e-01 9.96056616e-01 -8.52896273e-01
-1.17953050e+00 6.24999404e-01 -1.79427080e-02 -1.41993201e+00
-4.42599714e-01 -3.09945107e-01 -5.82293332e-01 6.15761697e-01
-1.12813795e+00 -1.25361860e+00 -4.51469839e-01 5.87847531e-01
9.64880109e-01 -4.49369520e-01 1.06579590e+00 -3.22789788e-01
-6.69937968e-01 7.23425269e-01 3.32839817e-01 2.70785689e-01
1.09578013e+00 -1.62019360e+00 5.18461764e-01 5.46860456e-01
4.75673705e-01 1.96757123e-01 5.31268597e-01 -9.12424624e-01
-9.81262684e-01 -1.07305026e+00 8.47852290e-01 -8.26085389e-01
5.66235363e-01 -1.85491785e-01 -1.07510114e+00 1.08578610e+00
4.34657186e-01 2.58702666e-01 1.13045013e+00 1.92767888e-01
-7.05981374e-01 3.00345600e-01 -1.06195188e+00 4.67302948e-01
7.98476815e-01 -4.85122561e-01 -6.06634140e-01 6.68938756e-01
3.72458756e-01 -4.95781630e-01 -5.41463196e-01 1.81611314e-01
4.01231587e-01 -9.14317966e-01 4.96247292e-01 -8.09715688e-01
6.18809521e-01 9.85655375e-03 2.45575786e-01 -1.40214241e+00
-3.25463414e-01 -2.34470621e-01 -2.97716767e-01 1.15857005e+00
7.93719053e-01 -7.17535019e-01 1.34267926e+00 4.11988199e-01
1.03887431e-01 -9.46808755e-01 -3.79083604e-01 -4.80861366e-01
6.11693077e-02 -7.17219561e-02 1.03455782e-01 1.41849315e+00
5.84655821e-01 8.22398663e-01 -1.21892385e-01 -9.44515541e-02
7.49008358e-01 3.65798444e-01 7.59505570e-01 -1.32988334e+00
-2.18373820e-01 -1.12873875e-01 7.77192116e-02 -9.26498890e-01
3.73422354e-01 -1.34245646e+00 -1.64684817e-01 -1.46448278e+00
7.05612004e-01 -3.78469229e-01 -3.15912306e-01 9.43435311e-01
-6.35378003e-01 3.77325326e-01 -9.59453136e-02 5.80687404e-01
-8.95926178e-01 2.18719155e-01 9.90410447e-01 -3.44571434e-02
-3.51400405e-01 3.01971108e-01 -7.10753381e-01 8.47384214e-01
1.09316027e+00 -6.52388871e-01 -5.59874356e-01 -1.45071849e-01
-7.75181726e-02 1.12180486e-01 -1.11038022e-01 -8.55498195e-01
1.84106827e-01 -5.33994811e-04 7.70745158e-01 -7.25753188e-01
1.64470881e-01 -7.22235799e-01 -3.52454484e-01 4.21494275e-01
-1.04645574e+00 -3.99152935e-03 8.70488361e-02 4.34271872e-01
-2.61718798e-02 -3.75801086e-01 9.52217102e-01 -1.57179192e-01
-2.73121834e-01 2.67981410e-01 -1.41701907e-01 3.43748063e-01
9.07841980e-01 -2.63727754e-01 -3.89735520e-01 -5.83645523e-01
-8.64348531e-01 4.88148749e-01 6.72994733e-01 4.10268068e-01
4.69953954e-01 -1.13110781e+00 -8.04829895e-01 1.95289522e-01
4.25399601e-01 -1.46627709e-01 7.28594735e-02 5.25463820e-01
5.57022728e-02 2.48903215e-01 -5.69935106e-02 -6.55839562e-01
-1.60478520e+00 6.18755519e-01 2.57580161e-01 -4.62149233e-01
-4.57235307e-01 8.37633014e-01 -1.47049064e-02 -7.08321214e-01
3.91653657e-01 2.98734725e-01 -2.53599018e-01 1.71728036e-03
5.76545238e-01 2.57635355e-01 -4.62186802e-03 -6.35185838e-01
-2.28010789e-01 1.59749508e-01 -6.00327790e-01 -3.02686989e-01
1.30706656e+00 -1.01697996e-01 3.06959510e-01 8.79534662e-01
1.21668041e+00 -2.48038158e-01 -1.26336634e+00 -8.81755352e-01
2.12161597e-02 -2.13036552e-01 2.15587560e-02 -9.98925507e-01
-1.02507186e+00 5.21950364e-01 4.77481067e-01 2.05470920e-01
7.58234143e-01 4.51293111e-01 3.14123392e-01 4.54679728e-01
9.44226906e-02 -1.24430549e+00 5.95469236e-01 5.24912417e-01
4.98966008e-01 -1.66906214e+00 2.29154006e-01 -2.52439290e-01
-1.23218548e+00 1.07205987e+00 1.06902337e+00 1.08134434e-01
6.83419347e-01 3.30400437e-01 5.62694907e-01 -3.12606186e-01
-1.15187514e+00 -1.58564001e-02 2.23392650e-01 4.04379964e-01
8.55067015e-01 -5.74816018e-02 1.54638901e-01 1.19105205e-01
-1.58139408e-01 -2.49748025e-02 3.55695903e-01 1.25312686e+00
-4.40336734e-01 -1.20833242e+00 -2.63868421e-01 8.21714938e-01
-1.34202838e-01 -1.54716356e-04 -8.11468303e-01 4.71210986e-01
-2.39426047e-01 8.89750659e-01 7.20413700e-02 -3.98390651e-01
1.09048389e-01 7.59601235e-01 3.23377341e-01 -1.16061127e+00
-6.33281231e-01 3.31539474e-02 1.86360538e-01 -2.35327408e-01
-5.61826050e-01 -9.28441703e-01 -1.47914124e+00 1.63715884e-01
-6.55257523e-01 3.63051862e-01 4.20636892e-01 1.05813479e+00
2.08344862e-01 1.43807411e-01 1.00329125e+00 -6.27584577e-01
-8.01299036e-01 -1.07327986e+00 -3.07613850e-01 6.44447505e-01
6.76543564e-02 -3.73951584e-01 -5.28756320e-01 4.36861098e-01] | [9.716093063354492, 4.002109527587891] |
3833bc64-55ca-401a-b9b4-f73769118f6c | classification-of-perceived-human-stress | 1905.06384 | null | https://arxiv.org/abs/1905.06384v1 | https://arxiv.org/pdf/1905.06384v1.pdf | Classification of Perceived Human Stress using Physiological Signals | In this paper, we present an experimental study for the classification of perceived human stress using non-invasive physiological signals. These include electroencephalography (EEG), galvanic skin response (GSR), and photoplethysmography (PPG). We conducted experiments consisting of steps including data acquisition, feature extraction, and perceived human stress classification. The physiological data of $28$ participants are acquired in an open eye condition for a duration of three minutes. Four different features are extracted in time domain from EEG, GSR and PPG signals and classification is performed using multiple classifiers including support vector machine, the Naive Bayes, and multi-layer perceptron (MLP). The best classification accuracy of 75% is achieved by using MLP classifier. Our experimental results have shown that our proposed scheme outperforms existing perceived stress classification methods, where no stress inducers are used. | ['Aamir Arsalan', 'Ulas Bagci', 'Syed Muhammad Anwar', 'Muhammad Majid'] | 2019-05-13 | null | null | null | null | ['photoplethysmography-ppg'] | ['medical'] | [ 2.80257612e-01 -3.83529484e-01 2.49208227e-01 -5.72043657e-01
5.63994646e-02 -1.61012277e-01 -5.94499670e-02 3.40598702e-01
-6.81160688e-01 1.04432023e+00 -5.34606678e-03 -4.05418724e-02
-4.52804007e-02 -1.42801896e-01 5.59685007e-02 -5.84085524e-01
-2.98181087e-01 -8.13666582e-01 -3.21482927e-01 1.95866581e-02
8.77747476e-01 4.61470097e-01 -1.49738240e+00 -1.35233045e-01
7.76533067e-01 1.48655748e+00 -2.02412426e-01 5.86386025e-01
5.38826764e-01 4.53936964e-01 -1.03924179e+00 1.25572979e-01
1.16449028e-01 -4.18362826e-01 -4.26582843e-01 4.16640006e-02
-2.53715783e-01 -3.81770059e-02 -3.86829227e-02 7.80833006e-01
1.03376722e+00 2.58873731e-01 4.06628579e-01 -1.60792160e+00
-4.63711858e-01 -3.06008626e-02 -6.08983159e-01 7.30495453e-01
1.01268530e+00 -1.12462789e-01 8.03399552e-03 -8.00342798e-01
-1.65432930e-01 7.86213279e-01 5.92700064e-01 5.58099389e-01
-1.20931160e+00 -1.05276525e+00 -5.46214640e-01 5.39266050e-01
-1.56255639e+00 -3.65582854e-01 1.12434125e+00 -4.67051685e-01
1.39150119e+00 2.44347095e-01 7.89466679e-01 1.24569845e+00
1.00569165e+00 1.73821047e-01 2.24797535e+00 -4.15474713e-01
7.08998919e-01 6.81536138e-01 7.32976735e-01 1.97980702e-01
1.40217431e-02 2.03395650e-01 -1.13569796e+00 -6.35529399e-01
3.25023860e-01 -1.19709186e-01 -6.57173157e-01 4.75822538e-01
-7.33104885e-01 1.82620615e-01 -6.19463474e-02 4.22149211e-01
-8.55747044e-01 -2.70429611e-01 5.96913993e-01 6.40750110e-01
4.55553323e-01 4.84841317e-01 -5.97243845e-01 -4.96892542e-01
-6.31754994e-01 -3.52394521e-01 1.00273848e+00 5.97759783e-01
3.28056008e-01 9.67308953e-02 1.50825754e-01 7.92002261e-01
1.50604174e-01 5.54349065e-01 1.00779223e+00 -4.66475934e-01
-1.99069634e-01 4.70720112e-01 3.04169655e-01 -1.27392757e+00
-6.65542305e-01 1.28538698e-01 -8.42259407e-01 1.30055457e-01
-2.16121376e-01 -8.32320273e-01 -5.09280622e-01 1.21898830e+00
-1.34447753e-01 8.17054212e-01 1.73998624e-01 7.23655224e-01
6.11522913e-01 6.42453134e-01 3.57060999e-01 -8.94789755e-01
1.48289073e+00 -1.63753077e-01 -1.20738912e+00 -2.86071777e-01
1.42822266e-01 -5.63154340e-01 9.96964216e-01 9.22142446e-01
-6.97942197e-01 -6.17690265e-01 -1.41743886e+00 4.80358809e-01
-4.71309215e-01 3.19719501e-02 5.22715807e-01 1.24365580e+00
-9.14149523e-01 5.85206807e-01 -6.54043436e-01 -5.43758154e-01
-4.17863578e-02 6.03436649e-01 -4.58488643e-01 5.17173588e-01
-1.19632351e+00 1.16846573e+00 1.38361910e-02 3.00124168e-01
-3.20907056e-01 -3.03226054e-01 -7.94446588e-01 -5.38808964e-02
-2.06518263e-01 -7.03377463e-03 6.83644831e-01 -8.75166655e-01
-2.00279450e+00 8.26110125e-01 -3.77453238e-01 -9.69501212e-02
-5.62614381e-01 -1.81352869e-01 -9.02662516e-01 2.32874095e-01
-5.19807220e-01 -4.73811999e-02 7.41791964e-01 -6.99874938e-01
8.93606469e-02 -6.97777808e-01 -4.91400987e-01 1.24510176e-01
-3.74228656e-01 6.66770220e-01 8.47118914e-01 -1.44959196e-01
1.43123627e-01 -7.60926068e-01 2.30314191e-02 -7.99522579e-01
-1.93322405e-01 -1.45076483e-01 5.79200387e-01 -8.36443841e-01
1.35088575e+00 -2.28816509e+00 -2.40558475e-01 3.84502858e-01
-1.96716800e-01 1.71196595e-01 3.02822024e-01 3.77634227e-01
-4.07804996e-01 -1.14200093e-01 -2.77216975e-02 -1.82372138e-01
7.34668178e-03 -6.38056919e-02 -2.18799844e-01 5.81722558e-01
-5.37374876e-02 5.35679102e-01 -4.95216012e-01 -6.71460107e-02
3.53643209e-01 4.77239102e-01 2.76306421e-01 5.07900059e-01
1.02972722e+00 3.71875167e-01 -9.79273301e-03 8.36188734e-01
6.79008722e-01 4.70360279e-01 -8.01085681e-02 -1.43488199e-02
-1.50371805e-01 8.70667398e-02 -1.18152201e+00 1.37071490e+00
-2.87700534e-01 6.08811617e-01 -1.12272002e-01 -9.70042825e-01
1.59388661e+00 7.37296522e-01 2.46940717e-01 -8.34017336e-01
5.00849307e-01 5.29504567e-02 -1.70269772e-01 -1.09588182e+00
-1.58486199e-02 -3.46003085e-01 -1.01123184e-01 4.80356038e-01
1.51092753e-01 1.21607929e-01 -3.02366287e-01 -2.30737939e-01
9.99234617e-01 -2.64335424e-01 7.97614872e-01 -7.14161396e-01
6.08202159e-01 -6.22076094e-01 7.75835395e-01 2.88654983e-01
-8.56483519e-01 -1.29905760e-01 6.84228599e-01 -1.49589971e-01
-2.61765212e-01 -6.31300628e-01 -3.05186659e-01 5.88322997e-01
1.60821259e-01 -3.19473669e-02 -8.22736025e-01 -8.68923403e-03
-3.35429944e-02 7.58948743e-01 -5.64894736e-01 -4.07027990e-01
9.89869311e-02 -1.04611957e+00 4.79661942e-01 5.47492802e-01
5.99060774e-01 -1.25337350e+00 -1.10787535e+00 1.88036352e-01
1.93408832e-01 -9.59690690e-01 8.76340792e-02 3.82064044e-01
-9.03527975e-01 -8.17206442e-01 -2.60407180e-01 -4.32523221e-01
3.78767282e-01 -1.58495873e-01 5.71188569e-01 -3.09759587e-01
-6.81436300e-01 5.23907840e-01 -2.51805127e-01 -9.26324666e-01
5.23005307e-01 -5.22411883e-01 6.82190001e-01 1.71605006e-01
1.38465726e+00 -1.19298053e+00 -6.51977956e-01 2.53870934e-01
-3.44858617e-01 -6.39477670e-01 5.04123330e-01 3.07248235e-01
4.66619357e-02 -9.10279229e-02 1.13387489e+00 -3.37974727e-01
1.33078206e+00 -4.51276422e-01 -1.31079644e-01 2.49445662e-02
-6.73177660e-01 -5.81021070e-01 2.86341280e-01 -4.84780580e-01
-1.02737510e+00 -3.79126936e-01 1.85208023e-01 1.26084939e-01
-9.04581249e-01 5.23118138e-01 -1.26582637e-01 -4.24647242e-01
1.18927240e+00 1.08224243e-01 -1.50337085e-01 -2.34349594e-01
-5.55135429e-01 1.47042453e+00 3.56370151e-01 -2.72895634e-01
-7.26963580e-02 -1.40067682e-01 -4.28076833e-02 -1.12578022e+00
-3.04980487e-01 -5.74084818e-01 -7.21636713e-01 -3.83658379e-01
8.03327382e-01 -7.98757374e-01 -1.09193540e+00 9.96805727e-01
-8.74202728e-01 2.50417572e-02 5.21668553e-01 9.45611954e-01
-1.74772918e-01 2.53725260e-01 -7.43069232e-01 -1.55861390e+00
-7.27062225e-01 -7.28681922e-01 4.70938176e-01 5.66312850e-01
-5.17319858e-01 -7.52674818e-01 3.27124074e-02 3.10510546e-01
4.59861308e-01 5.44635594e-01 4.76987332e-01 -5.48321009e-01
4.63871598e-01 -5.19678295e-01 1.77450716e-01 6.66153133e-01
2.43044183e-01 -2.37990618e-01 -1.47497666e+00 -2.16006607e-01
7.01176405e-01 -5.40050924e-01 8.51938203e-02 3.23406696e-01
1.14515102e+00 1.55105650e-01 -8.73667970e-02 2.19861120e-01
1.50679851e+00 1.04921234e+00 9.88965452e-01 -1.55615792e-01
-6.96297130e-03 4.53975111e-01 3.82550150e-01 5.40916622e-01
8.19244236e-02 -1.87508892e-02 -2.11720094e-01 1.41414896e-01
8.13649595e-01 4.19656664e-01 4.86603290e-01 9.88873243e-01
-2.11782634e-01 1.05012067e-01 -7.70182848e-01 1.27144247e-01
-1.38822889e+00 -6.73187256e-01 3.56854647e-02 2.32505894e+00
7.13032007e-01 -3.42598185e-02 -2.41377708e-02 8.26142907e-01
5.18835843e-01 -2.54996806e-01 -5.35855293e-01 -1.11757505e+00
1.01087220e-01 9.29700136e-01 2.59195030e-01 2.42116302e-01
-7.97646284e-01 1.85002267e-01 6.74083567e+00 -2.32190609e-01
-1.48994839e+00 -1.41392350e-01 4.26894218e-01 -5.10324687e-02
4.91600722e-01 -2.04737887e-01 -2.73678064e-01 8.16176176e-01
1.46608150e+00 -4.46590334e-01 5.78504860e-01 6.75005376e-01
3.36313516e-01 -9.34078217e-01 -9.41794157e-01 1.61047292e+00
4.83282000e-01 -3.08841437e-01 -8.50822449e-01 -2.43577734e-01
6.28311858e-02 -4.81184959e-01 -3.74701202e-01 3.26613784e-01
-8.61866951e-01 -9.84109819e-01 -2.72811323e-01 1.10210598e+00
4.08026516e-01 -9.02517080e-01 8.45185220e-01 3.37492257e-01
-6.14273787e-01 -2.89197326e-01 -3.82312596e-01 -9.51806843e-01
-1.34841010e-01 8.20242643e-01 -3.59839141e-01 2.83919305e-01
7.48821259e-01 3.11300516e-01 -3.49762619e-01 9.85114455e-01
-1.83959350e-01 6.48222029e-01 -2.00378329e-01 -4.39543724e-01
-3.97294641e-01 -2.22363234e-01 1.87280178e-01 1.16071236e+00
2.53847301e-01 9.94961500e-01 -2.74972141e-01 6.41562462e-01
4.13591266e-01 2.67552584e-01 -6.67192042e-01 5.41742891e-02
5.64708769e-01 1.45767367e+00 -5.62197089e-01 -1.89403191e-01
-3.40631455e-01 8.95998597e-01 -2.50046521e-01 4.84109432e-01
-5.10609865e-01 -1.41082489e+00 3.99462819e-01 -3.30551803e-01
-7.03566611e-01 -2.32301489e-01 -8.30493867e-01 -1.09354985e+00
1.22619845e-01 -5.15632212e-01 3.90135832e-02 -1.23530734e+00
-1.17618787e+00 5.72593927e-01 1.86606348e-01 -6.97603285e-01
4.42695245e-02 -6.63968265e-01 -8.97297680e-01 1.46507764e+00
-1.14882541e+00 -6.92827925e-02 -6.06785059e-01 6.37007654e-01
-1.41221583e-02 -6.03884123e-02 1.15065181e+00 3.20421427e-01
-8.20933342e-01 4.55160737e-01 -6.03904128e-01 -2.76597232e-01
8.93003285e-01 -1.19837296e+00 -1.69150785e-01 7.18624532e-01
-6.79328203e-01 7.26629496e-01 6.05557203e-01 -4.88943458e-01
-1.27596414e+00 -2.50707358e-01 1.05585158e+00 -1.51770890e-01
3.37547272e-01 -4.97801572e-01 -8.88303041e-01 4.13463295e-01
5.83073497e-01 -1.63769066e-01 1.44014180e+00 8.77572969e-03
2.09615842e-01 -2.67327815e-01 -1.58487046e+00 5.26689999e-02
3.70698094e-01 -7.69432604e-01 -9.64638770e-01 -1.75848067e-01
-1.96982697e-02 -2.05747280e-02 -1.30952787e+00 4.06346500e-01
5.88076651e-01 -9.45842564e-01 3.62458706e-01 -3.67271394e-01
-5.30695803e-02 7.63657540e-02 -5.64568602e-02 -1.69665527e+00
-1.77039400e-01 -7.84831285e-01 1.08378008e-01 9.70434964e-01
6.75565824e-02 -1.23535645e+00 1.63021699e-01 1.39329267e+00
-5.68199158e-02 -7.28686094e-01 -4.90326375e-01 -3.74017030e-01
-6.15953445e-01 -2.56016046e-01 2.24993527e-01 1.28944159e+00
1.39956176e+00 4.95541483e-01 -3.86844724e-01 1.56679094e-01
5.63215315e-01 -3.64589870e-01 2.70620435e-01 -1.20206439e+00
8.91666785e-02 2.60670424e-01 -9.68597829e-01 -3.29146594e-01
2.23827362e-01 -2.10782871e-01 -1.13101035e-01 -1.03522968e+00
4.18117307e-02 2.48317197e-01 -1.01768124e+00 5.48947990e-01
-2.04041183e-01 9.23851654e-02 -2.85491258e-01 -5.09102166e-01
1.86852753e-01 1.90435499e-01 5.75113535e-01 5.95193207e-01
-5.13344526e-01 -2.22156048e-01 -6.48466349e-01 5.72223246e-01
1.22519505e+00 -3.52989852e-01 -5.97000301e-01 1.62108898e-01
-8.35710168e-02 4.52747941e-01 2.24381626e-01 -1.29682136e+00
2.67856628e-01 -1.66055232e-01 7.17028201e-01 -1.08536981e-01
5.32299280e-01 -4.74673361e-01 5.18161757e-03 3.13380927e-01
-1.31881148e-01 1.77524924e-01 4.38757032e-01 1.34902149e-01
-6.70883283e-02 -8.48147199e-02 7.45512962e-01 3.73991467e-02
-6.09707892e-01 -1.84157506e-01 -7.80584693e-01 -6.29194021e-01
1.24561107e+00 -5.17050147e-01 -2.98661828e-01 -5.22541776e-02
-8.69896650e-01 3.95640591e-03 -9.40306857e-02 1.48830697e-01
9.17108536e-01 -1.12241185e+00 -1.13704368e-01 6.38295412e-01
1.25082731e-01 -1.00864494e+00 3.04719657e-01 1.28081548e+00
-1.14074806e-02 3.55926186e-01 -1.01979816e+00 -1.71195492e-01
-1.40311074e+00 4.09071147e-01 4.08493131e-01 7.53219604e-01
-1.50776744e-01 7.80177295e-01 -6.14766479e-01 2.07409799e-01
4.37169462e-01 -4.02211547e-01 -4.94785666e-01 7.09700510e-02
8.27429414e-01 7.69925356e-01 2.43619144e-01 -3.25961918e-01
-6.17871046e-01 4.46523458e-01 3.45549911e-01 -1.80142775e-01
9.63070631e-01 -6.87431544e-02 -4.01773721e-01 9.57779527e-01
1.08812630e+00 -3.69569093e-01 -5.91558933e-01 2.21795991e-01
2.69142613e-02 -6.87566102e-01 2.30118647e-01 -1.06694055e+00
-4.60904092e-01 9.96960044e-01 1.09237921e+00 3.54867309e-01
1.66614866e+00 -8.63215506e-01 6.74843729e-01 5.19422531e-01
6.26334131e-01 -1.49182057e+00 4.26670909e-02 -1.17175609e-01
7.43708074e-01 -8.12475026e-01 -1.53079003e-01 -1.98917568e-01
-9.45928752e-01 9.28492308e-01 7.55203843e-01 -5.15044749e-01
1.11775625e+00 4.74458426e-01 2.97035426e-01 -2.32612863e-01
-9.49913204e-01 3.06777984e-01 3.69220264e-02 6.92648292e-01
5.71292818e-01 1.46058023e-01 -7.84013391e-01 1.00841796e+00
-8.19149315e-02 6.28496587e-01 7.57208765e-01 1.25325155e+00
-6.23595297e-01 -5.51709533e-01 -4.48104173e-01 6.94676638e-01
-7.25219011e-01 1.46364689e-01 -4.84684944e-01 2.18147337e-01
2.09978204e-02 1.46677256e+00 -4.31462862e-02 -7.75885999e-01
6.74017727e-01 7.27377295e-01 5.76882601e-01 -3.79053891e-01
-6.20407045e-01 -1.67601988e-01 -5.06108887e-02 -7.29656458e-01
-4.97547507e-01 -3.76788437e-01 -1.01245284e+00 -7.88425878e-02
-2.34160334e-01 3.32574338e-01 1.13061917e+00 9.30459619e-01
4.72400635e-01 1.38349444e-01 9.69932914e-01 -8.26817513e-01
-1.85325682e-01 -1.48110390e+00 -1.23002732e+00 3.24946582e-01
2.36058190e-01 -7.76186526e-01 -8.05257976e-01 7.12302998e-02] | [13.506820678710938, 3.083127737045288] |
dafe45f1-2288-48ae-a072-2e6a6cc14b19 | deep-spatial-transformation-for-pose-guided | 2008.12606 | null | https://arxiv.org/abs/2008.12606v1 | https://arxiv.org/pdf/2008.12606v1.pdf | Deep Spatial Transformation for Pose-Guided Person Image Generation and Animation | Pose-guided person image generation and animation aim to transform a source person image to target poses. These tasks require spatial manipulation of source data. However, Convolutional Neural Networks are limited by the lack of ability to spatially transform the inputs. In this paper, we propose a differentiable global-flow local-attention framework to reassemble the inputs at the feature level. This framework first estimates global flow fields between sources and targets. Then, corresponding local source feature patches are sampled with content-aware local attention coefficients. We show that our framework can spatially transform the inputs in an efficient manner. Meanwhile, we further model the temporal consistency for the person image animation task to generate coherent videos. The experiment results of both image generation and animation tasks demonstrate the superiority of our model. Besides, additional results of novel view synthesis and face image animation show that our model is applicable to other tasks requiring spatial transformation. The source code of our project is available at https://github.com/RenYurui/Global-Flow-Local-Attention. | ['Thomas H. Li', 'Shan Liu', 'Ge Li', 'Yurui Ren'] | 2020-08-27 | null | null | null | null | ['image-animation'] | ['computer-vision'] | [ 1.58899084e-01 -3.90836261e-02 4.34361696e-02 -3.04332048e-01
-5.35511434e-01 -4.69128698e-01 6.70182586e-01 -7.39601672e-01
-3.61476503e-02 7.62875319e-01 4.14583594e-01 2.56584048e-01
1.24181472e-01 -7.71606743e-01 -9.44587588e-01 -5.75742841e-01
2.95895606e-01 -4.81638759e-02 -1.58117488e-01 -8.10559988e-02
1.18229464e-01 5.05361259e-01 -1.51789272e+00 1.34122193e-01
8.72189760e-01 6.10350966e-01 1.06961079e-01 8.67511988e-01
1.99937269e-01 7.39700317e-01 -4.93563741e-01 -2.12715313e-01
3.99358332e-01 -9.39736068e-01 -7.38635123e-01 1.60874426e-01
8.90573978e-01 -7.64491200e-01 -5.69357574e-01 1.00356412e+00
5.42389035e-01 3.83860558e-01 3.99618894e-01 -1.54441440e+00
-1.08116043e+00 2.42741972e-01 -6.17781997e-01 1.03406258e-01
6.15604222e-01 5.77023923e-01 5.97900093e-01 -9.49069560e-01
8.45891297e-01 1.50555909e+00 4.05905217e-01 8.90471518e-01
-1.03116286e+00 -8.08163881e-01 4.48274165e-01 1.76858142e-01
-1.18109822e+00 -5.25584459e-01 9.65434432e-01 -4.56762254e-01
6.34541810e-01 1.93365782e-01 9.55197811e-01 1.16837335e+00
1.23196185e-01 6.02632821e-01 8.72163236e-01 -2.10822061e-01
-2.71559447e-01 -3.54633063e-01 -2.95257181e-01 1.02509952e+00
4.22850884e-02 3.79786730e-01 -6.57072365e-01 3.06942433e-01
1.57296753e+00 1.46479502e-01 -5.78465402e-01 -2.19750166e-01
-1.53832603e+00 7.30043411e-01 7.08225489e-01 1.89287752e-01
-4.95103091e-01 6.53169274e-01 1.36849254e-01 -1.07401619e-02
4.05365586e-01 3.18271816e-01 -8.90474617e-02 3.13184271e-03
-6.85776174e-01 4.91402715e-01 2.86804020e-01 9.46814239e-01
6.06738806e-01 3.32430601e-01 -4.18740958e-01 4.58514452e-01
9.57696810e-02 5.85812688e-01 2.67311573e-01 -1.54851174e+00
3.85947883e-01 2.64067799e-01 2.38771096e-01 -1.26177645e+00
-1.22287035e-01 -2.34639466e-01 -9.60602403e-01 2.66247183e-01
5.90470433e-01 -3.23529333e-01 -7.23866224e-01 2.02404141e+00
5.36607563e-01 5.84907472e-01 -2.95994580e-01 1.27277541e+00
8.58049870e-01 8.32185268e-01 4.71349135e-02 -1.81413874e-01
1.12485790e+00 -1.21933246e+00 -9.52519059e-01 -2.01094169e-02
5.81393465e-02 -5.62857330e-01 1.23649192e+00 3.43917543e-03
-1.50208378e+00 -1.00588346e+00 -6.88677490e-01 -4.48973387e-01
7.27766976e-02 1.85442865e-01 5.29711127e-01 2.45476171e-01
-1.02805638e+00 6.39008284e-01 -8.25692534e-01 -2.35853031e-01
4.83387023e-01 2.55341113e-01 -3.40276510e-01 1.55077592e-01
-1.14772582e+00 4.19268280e-01 -2.95177214e-02 3.06614220e-01
-7.73748875e-01 -9.09778833e-01 -1.05275226e+00 2.83034649e-02
9.28387120e-02 -1.22889125e+00 1.19030011e+00 -1.34943736e+00
-1.72819650e+00 5.79155862e-01 -3.89584363e-01 -4.87086847e-02
7.76668012e-01 -3.12529176e-01 9.14062113e-02 3.33265692e-01
2.93069363e-01 1.08563340e+00 9.67635214e-01 -1.15278292e+00
-5.09190559e-01 -8.75932500e-02 8.00281689e-02 3.59641522e-01
-3.00790668e-01 -1.83228943e-02 -6.09079242e-01 -1.00004303e+00
-3.16035926e-01 -6.85238779e-01 -1.27770275e-01 4.71494257e-01
-4.27103311e-01 -7.42572397e-02 7.76685596e-01 -8.18107069e-01
9.37283337e-01 -2.00859928e+00 5.10978401e-01 -1.00265034e-01
2.37205088e-01 5.04119275e-03 -3.58013272e-01 1.56800032e-01
-2.34654054e-01 1.14716627e-01 -1.44157067e-01 -3.95054221e-01
-1.74420372e-01 -1.25229180e-01 -3.62371176e-01 4.25393969e-01
2.81612724e-01 1.26627541e+00 -9.86735880e-01 -5.36272347e-01
4.41547394e-01 9.98300076e-01 -7.04415023e-01 3.63687038e-01
4.85318340e-03 1.00969076e+00 -4.51110393e-01 3.90168190e-01
5.86528957e-01 -2.47731343e-01 -1.58190325e-01 -4.65571731e-01
-1.18099883e-01 -2.73000039e-02 -1.06064761e+00 1.88368309e+00
-4.30850953e-01 7.28521347e-01 6.36713952e-02 -6.42970145e-01
6.08529866e-01 1.94226488e-01 5.98004460e-01 -5.70654452e-01
2.18872368e-01 -1.73658311e-01 -1.83969319e-01 -4.55108464e-01
3.90066028e-01 2.06709132e-02 2.14410201e-02 4.93643016e-01
-1.71193749e-01 3.02830450e-02 7.97133520e-02 1.25730738e-01
5.65164387e-01 6.84641838e-01 1.43761113e-01 -3.53412367e-02
6.35848403e-01 -1.81088969e-01 5.62000453e-01 3.37215960e-01
-3.64189804e-01 8.84065807e-01 2.72617400e-01 -6.29780948e-01
-1.14599967e+00 -1.07290637e+00 3.31546962e-01 9.00151432e-01
3.86626840e-01 -3.25062841e-01 -9.11105275e-01 -5.50047040e-01
-1.41857564e-01 4.15945143e-01 -7.27436662e-01 -8.76512155e-02
-1.02224195e+00 -1.64059736e-02 2.98818558e-01 7.65657723e-01
7.51364470e-01 -1.31673002e+00 -7.59600461e-01 6.76124096e-02
-5.15000939e-01 -9.22669768e-01 -1.23630714e+00 -8.89877915e-01
-7.78998077e-01 -9.88407612e-01 -1.13558722e+00 -8.91987264e-01
9.52061832e-01 3.48621517e-01 8.08112204e-01 1.80139989e-01
-3.68751824e-01 5.18612623e-01 -3.88353579e-02 7.84976259e-02
-1.22882418e-01 -2.18683466e-01 -1.15613632e-01 1.11707866e-01
-1.39611766e-01 -5.57490349e-01 -1.02587914e+00 3.05771172e-01
-7.08811164e-01 5.00874460e-01 2.93578506e-01 8.21670115e-01
4.72093791e-01 -3.13001364e-01 4.72050101e-01 -5.02212286e-01
5.95053971e-01 -6.57174364e-02 -4.15034562e-01 2.80680545e-02
1.16028421e-01 -1.03555463e-01 6.25706792e-01 -5.95752656e-01
-1.26018822e+00 2.05236748e-01 4.19929139e-02 -7.07835615e-01
-2.35667452e-01 1.54081117e-02 -3.49743098e-01 1.55980155e-01
4.09476280e-01 2.00639337e-01 2.11325914e-01 -1.47129670e-01
6.39077783e-01 8.16675276e-02 7.66180933e-01 -6.73729181e-01
1.00362909e+00 6.55792356e-01 -1.17750756e-01 -6.49889290e-01
-4.87345368e-01 1.99980915e-01 -8.10433686e-01 -5.19339085e-01
1.10326958e+00 -8.47175717e-01 -9.74931419e-01 6.74211919e-01
-1.35561228e+00 -5.74574590e-01 -3.62653285e-01 3.22786808e-01
-8.20872307e-01 3.63093466e-01 -6.45196795e-01 -4.84814227e-01
-4.13862139e-01 -1.12184095e+00 1.19297183e+00 4.53959197e-01
-2.80538380e-01 -9.75372434e-01 -8.33017156e-02 4.00565147e-01
3.40081215e-01 5.80689907e-01 4.22450811e-01 2.67764926e-01
-9.41375017e-01 1.64364293e-01 -2.47298062e-01 2.01621056e-02
4.05509084e-01 1.76930383e-01 -6.97429240e-01 -4.13081139e-01
-4.15923059e-01 -1.74401715e-01 7.26534009e-01 7.06658065e-01
1.33290982e+00 -5.17019331e-01 -2.27449551e-01 9.67246771e-01
1.10677791e+00 7.84753859e-02 6.10060453e-01 3.01520806e-02
1.07771456e+00 7.75181532e-01 5.27801931e-01 3.76039386e-01
3.70826364e-01 8.39972198e-01 1.44518241e-01 -3.36626351e-01
-6.42349362e-01 -5.51098406e-01 4.85161662e-01 4.31164056e-01
-5.65004528e-01 -1.12527087e-01 -5.66983342e-01 5.43214202e-01
-1.85819054e+00 -1.35865891e+00 2.90940180e-02 1.97253060e+00
7.61668921e-01 -3.62526447e-01 3.49710375e-01 -2.59098500e-01
9.26862895e-01 2.11617857e-01 -5.81435621e-01 -1.26181737e-01
3.04573894e-01 7.80874789e-02 3.20569463e-02 8.71994734e-01
-1.07546854e+00 1.08297896e+00 5.54647398e+00 5.07530987e-01
-1.05266893e+00 5.16532212e-02 6.63948715e-01 -3.53621811e-01
-3.80323052e-01 -3.04504901e-01 -5.70689738e-01 5.98108172e-01
5.01082778e-01 -3.77841681e-01 5.11608243e-01 4.67192590e-01
5.92205107e-01 3.54841262e-01 -1.00038767e+00 1.06221926e+00
1.72799468e-01 -1.36976576e+00 2.31594488e-01 4.05421713e-03
8.50084305e-01 -7.86585867e-01 3.46328050e-01 -5.96110225e-02
1.45834342e-01 -1.10300982e+00 7.96122551e-01 8.38867128e-01
1.08298779e+00 -8.70897710e-01 2.56190091e-01 1.80532709e-02
-1.49209571e+00 6.37556091e-02 -1.74432278e-01 -1.12485290e-01
4.84423757e-01 -1.08662527e-02 -3.18100095e-01 4.81415093e-01
6.56004190e-01 9.80245411e-01 -3.14784229e-01 6.78095818e-01
-3.10002416e-01 3.69681641e-02 -4.57436256e-02 1.74385831e-01
-8.96347761e-02 -3.48744392e-01 4.61884499e-01 8.87602866e-01
4.83618975e-01 1.61974311e-01 3.94880027e-02 1.25736868e+00
-3.62462625e-02 6.20874949e-02 -7.15876997e-01 1.23572737e-01
4.35190409e-01 1.10462737e+00 -4.23763990e-01 -3.15173417e-01
-2.86015779e-01 1.35558832e+00 3.24538827e-01 6.36180937e-01
-1.28663242e+00 -4.79946256e-01 8.78894687e-01 2.77059078e-01
1.53435633e-01 -3.03118706e-01 -1.45828977e-01 -1.28901803e+00
-2.39297326e-04 -7.78861463e-01 7.46499151e-02 -1.05868673e+00
-1.15307367e+00 5.39677262e-01 1.72404990e-01 -1.36011612e+00
-4.16830271e-01 -2.82709181e-01 -8.58059824e-01 9.91957307e-01
-1.27746463e+00 -1.55329657e+00 -7.73123324e-01 9.32344973e-01
7.74914980e-01 3.96059677e-02 4.12252635e-01 2.21234426e-01
-4.97851014e-01 6.92636549e-01 -4.68546271e-01 3.78216416e-01
7.96696961e-01 -9.23352540e-01 6.27835929e-01 1.03923094e+00
-1.21444501e-01 6.66814983e-01 4.56032097e-01 -7.70815730e-01
-1.14841413e+00 -1.25953352e+00 6.57767713e-01 -3.80173415e-01
2.56061912e-01 -1.47697866e-01 -7.66003430e-01 8.75442803e-01
5.34833372e-01 1.27269447e-01 2.33810812e-01 -5.35057962e-01
-1.60351932e-01 -3.83951068e-02 -9.65372801e-01 8.92507672e-01
1.45320535e+00 -2.80111313e-01 -2.34921724e-01 2.48212323e-01
7.69529521e-01 -6.23043954e-01 -7.36587882e-01 1.15207851e-01
6.78757131e-01 -9.38047230e-01 1.29170883e+00 -5.95841050e-01
8.14725876e-01 -4.42517340e-01 2.25884825e-01 -1.20354903e+00
-5.75505197e-01 -8.27542841e-01 -8.25997144e-02 1.24530816e+00
-4.14335765e-02 -6.92234933e-01 7.15281963e-01 6.23510957e-01
-1.57987955e-03 -3.70109051e-01 -7.31042325e-01 -5.63296020e-01
2.67918527e-01 4.93311025e-02 5.85100353e-01 8.15012932e-01
-2.91739404e-01 1.02150865e-01 -6.88246071e-01 1.54550850e-01
8.18526804e-01 3.18957746e-01 1.07083035e+00 -7.65447199e-01
-3.52804929e-01 -5.81442595e-01 -1.45475000e-01 -1.23389876e+00
3.17990154e-01 -7.29140639e-01 -1.16761222e-01 -1.62583220e+00
1.45749405e-01 5.72064854e-02 2.43266225e-01 4.86832619e-01
-5.19023597e-01 4.28144991e-01 5.41326880e-01 2.18990296e-01
-1.55445173e-01 7.60283709e-01 1.92490959e+00 1.14785489e-02
-2.54420042e-01 -2.34255478e-01 -5.89750767e-01 5.14817715e-01
9.84175563e-01 -2.18213294e-02 -5.43373883e-01 -5.33469260e-01
-2.51621395e-01 9.17649046e-02 9.02113676e-01 -9.04067039e-01
9.86990407e-02 -4.95307863e-01 7.96824932e-01 -3.60056549e-01
5.60344279e-01 -5.34605324e-01 3.65436941e-01 7.55525589e-01
-4.73709434e-01 2.13858396e-01 1.61094591e-02 4.27603573e-01
1.33466525e-02 2.56215751e-01 9.06642854e-01 -1.57878399e-01
-6.21017873e-01 6.94812059e-01 -7.50664920e-02 -2.88640726e-02
1.19706082e+00 -1.98904023e-01 -3.75317633e-01 -7.80868948e-01
-7.33104408e-01 1.57119155e-01 5.61595023e-01 5.40265560e-01
9.55890596e-01 -1.73089683e+00 -8.18581581e-01 4.55853403e-01
-3.53254616e-01 5.75908180e-03 5.62910378e-01 6.89405620e-01
-6.73160374e-01 2.87336200e-01 -6.55782521e-01 -5.45222044e-01
-1.36922932e+00 6.28804207e-01 6.09181106e-01 1.77944079e-01
-7.72583604e-01 8.60231936e-01 7.37714052e-01 -2.28772178e-01
-1.84357706e-02 -2.66584277e-01 -2.20515616e-02 -3.33244830e-01
6.40488863e-01 4.30916935e-01 -7.32638717e-01 -8.50387633e-01
-2.13231355e-01 1.07774007e+00 1.02800868e-01 -2.05976099e-01
1.13123381e+00 -2.41529912e-01 8.41338653e-03 -5.70977889e-02
1.21195912e+00 -5.68828546e-02 -1.84658659e+00 8.12419131e-02
-8.25331450e-01 -9.70714152e-01 -2.38932729e-01 -3.87052327e-01
-1.46699202e+00 9.98991251e-01 3.90640587e-01 -2.59850323e-01
1.22867477e+00 -1.37131259e-01 8.91359210e-01 -2.28626981e-01
5.38700707e-02 -6.26499236e-01 5.22331834e-01 2.06492111e-01
1.38808417e+00 -8.72273743e-01 -1.70486465e-01 -6.19139373e-01
-6.21213198e-01 1.00279820e+00 1.11653018e+00 -3.62257093e-01
3.59398901e-01 1.21094897e-01 -1.28679618e-04 -3.14976424e-02
-6.01377189e-01 -1.05813384e-01 3.09664339e-01 9.50058281e-01
5.08788943e-01 -2.15622455e-01 -2.09441245e-01 3.25205863e-01
-3.24928075e-01 6.99928179e-02 4.99761015e-01 6.59029722e-01
-8.24524760e-02 -9.65871096e-01 -4.77067232e-01 -4.14821357e-02
-1.19626582e-01 7.54377246e-02 -2.62105793e-01 8.61749709e-01
1.16749130e-01 7.25359797e-01 2.77272463e-01 -1.17870688e-01
3.77087414e-01 -1.90362245e-01 7.25256801e-01 -4.09325242e-01
-4.72552478e-01 3.53687674e-01 -2.36015141e-01 -8.22779655e-01
-5.78746080e-01 -6.63639009e-01 -1.31361639e+00 -6.22034371e-01
2.44012415e-01 -1.81260750e-01 1.55062720e-01 3.96269947e-01
5.32762587e-01 7.67924428e-01 6.42855823e-01 -1.29988956e+00
-9.43778157e-02 -7.23038912e-01 -1.29770502e-01 8.02852213e-01
4.74822342e-01 -6.02540135e-01 -1.87909946e-01 6.15954757e-01] | [11.064483642578125, -0.8715901374816895] |
d81aca74-9fff-4f90-96c7-26e98b67183e | coarse-to-fine-video-retrieval-before-moment | 2110.07201 | null | https://arxiv.org/abs/2110.07201v1 | https://arxiv.org/pdf/2110.07201v1.pdf | Coarse to Fine: Video Retrieval before Moment Localization | The current state-of-the-art methods for video corpus moment retrieval (VCMR) often use similarity-based feature alignment approach for the sake of convenience and speed. However, late fusion methods like cosine similarity alignment are unable to make full use of the information from both query texts and videos. In this paper, we combine feature alignment with feature fusion to promote the performance on VCMR. | ['Jingyu Liu', 'Huanyu Liu', 'Zijian Gao'] | 2021-10-14 | null | null | null | null | ['moment-retrieval'] | ['computer-vision'] | [-8.50567371e-02 -9.85193908e-01 -3.55902523e-01 -2.09973797e-01
-9.72313583e-01 -2.36837387e-01 9.38883007e-01 1.55371815e-01
-4.95534062e-01 3.11687499e-01 2.75915742e-01 6.45958781e-02
-3.13723296e-01 -4.21355158e-01 3.19361617e-03 -5.54910541e-01
6.48597702e-02 -3.17963064e-02 4.83040750e-01 -3.96907240e-01
5.41243494e-01 3.15786541e-01 -1.60531461e+00 3.29248965e-01
7.16306686e-01 1.04692161e+00 4.13319260e-01 4.57151055e-01
-4.12822008e-01 4.56220746e-01 -4.92289662e-01 -3.16338003e-01
2.84629852e-01 -4.47441280e-01 -4.74917054e-01 -1.75294504e-01
2.63972253e-01 -2.74680853e-01 -1.06369269e+00 9.38313782e-01
7.81452239e-01 5.65816879e-01 5.82447112e-01 -1.29166663e+00
-4.74527568e-01 2.07302615e-01 -7.80002058e-01 7.70573795e-01
9.72633660e-01 -2.51057357e-01 1.02501798e+00 -9.16541219e-01
8.95768523e-01 1.02706075e+00 3.22448701e-01 1.72816828e-01
-4.14755315e-01 -5.57373106e-01 3.09019387e-02 9.46236193e-01
-1.75062370e+00 -5.58689654e-01 1.01190472e+00 -1.42324716e-01
9.96059835e-01 4.76139009e-01 6.66057706e-01 8.61710906e-01
3.77117768e-02 1.03913152e+00 6.59172416e-01 -5.50895989e-01
-2.56126642e-01 -2.01190263e-01 9.27666053e-02 3.23846638e-01
-1.23542950e-01 -1.79791063e-01 -7.14710236e-01 -2.77640641e-01
5.22996783e-01 3.27114820e-01 -4.72467601e-01 -6.53249919e-02
-1.26429415e+00 8.08767080e-01 1.20988965e-01 1.03438640e+00
-4.16548073e-01 -1.92353263e-01 6.15550101e-01 4.55659270e-01
2.87170231e-01 2.61410832e-01 6.85725883e-02 -4.39289898e-01
-1.32106149e+00 3.31911057e-01 4.45769131e-01 9.75499928e-01
4.61800933e-01 -2.86408305e-01 -1.85698196e-01 7.57541120e-01
5.19839525e-01 6.55847549e-01 1.06266987e+00 -8.47573936e-01
4.64486778e-01 4.35479671e-01 -2.70677924e-01 -1.44997430e+00
-8.36150814e-03 5.55165969e-02 -3.51258069e-01 -5.20192921e-01
-4.23922986e-02 3.58132392e-01 -7.02360809e-01 1.21972466e+00
2.99683779e-01 1.56645820e-01 2.32135072e-01 1.05146635e+00
1.11455131e+00 8.60935330e-01 -4.05916244e-01 -5.06007135e-01
1.29679358e+00 -8.78835320e-01 -1.15972674e+00 1.66055366e-01
5.31129360e-01 -1.29510033e+00 5.27082264e-01 2.73547590e-01
-1.09567487e+00 -5.63900769e-01 -1.18780196e+00 -2.32712477e-02
-3.30187708e-01 -1.18301779e-01 3.95403177e-01 2.95816392e-01
-7.68087685e-01 5.20455718e-01 -7.55816877e-01 -3.63016248e-01
-1.11456010e-02 2.17331350e-01 -5.94543397e-01 -3.64633888e-01
-1.38276601e+00 7.79636860e-01 3.96131396e-01 -7.36681977e-03
-3.04247409e-01 -1.94100738e-01 -6.15394294e-01 -1.32662104e-02
3.91952217e-01 -2.15839341e-01 1.15260696e+00 -6.69993222e-01
-1.25271940e+00 3.69483948e-01 -3.69908392e-01 -2.04271033e-01
2.73986638e-01 -4.44519132e-01 -8.31340432e-01 7.26290226e-01
-2.05127761e-01 3.45869899e-01 8.73346031e-01 -6.83034480e-01
-7.75200427e-01 -8.57609436e-02 -9.17436332e-02 5.24833679e-01
-3.84191275e-01 3.99523318e-01 -8.46562803e-01 -7.01979935e-01
3.93899977e-01 -7.30678499e-01 1.12603575e-01 -2.15299815e-01
2.08709016e-01 -4.67299759e-01 1.30437124e+00 -7.46544182e-01
1.75016618e+00 -2.22705173e+00 2.06128716e-01 2.65994608e-01
3.19066010e-02 5.45966685e-01 -1.96481735e-01 7.44432807e-01
2.66139477e-01 -2.52571434e-01 4.45361465e-01 -1.30271003e-01
-1.26361713e-01 1.01106547e-01 -1.85350135e-01 6.47190392e-01
-8.43667090e-02 5.92521548e-01 -9.17692959e-01 -1.11519742e+00
2.95371205e-01 5.98956406e-01 -3.28049213e-01 3.53117764e-01
2.60703713e-01 9.11418647e-02 -6.34454727e-01 7.42763758e-01
3.55053663e-01 1.09021425e-01 9.13098380e-02 -4.57740963e-01
-1.82430029e-01 3.50935943e-02 -1.17871964e+00 2.17125893e+00
5.17963199e-03 9.41085458e-01 -2.90425330e-01 -7.53652096e-01
8.94623280e-01 6.22388780e-01 9.58338439e-01 -9.71937001e-01
1.88946873e-01 3.57403100e-01 1.44375814e-02 -6.19048059e-01
8.38460386e-01 3.75527710e-01 1.49471208e-01 3.19308966e-01
1.20051958e-01 8.92135352e-02 5.84281385e-01 4.62556332e-01
8.85407269e-01 1.66744366e-01 5.17671525e-01 2.32633725e-01
8.18746507e-01 -9.56386104e-02 4.78418529e-01 3.87006819e-01
-3.54679316e-01 6.79454029e-01 -1.16054863e-01 -1.26292631e-01
-1.08950603e+00 -7.35964298e-01 -1.01629578e-01 8.97012949e-01
3.41122806e-01 -1.01881421e+00 -3.97908330e-01 -5.39685130e-01
-2.16918185e-01 2.31563359e-01 -1.62614748e-01 -1.15927614e-01
-7.54133701e-01 -2.15025112e-01 4.53076690e-01 1.16415940e-01
4.58383054e-01 -8.19916904e-01 -5.38422227e-01 2.39438474e-01
-5.71797669e-01 -1.04464757e+00 -7.73584545e-01 -6.00621641e-01
-6.57337308e-01 -1.01606369e+00 -8.94307256e-01 -5.89540124e-01
2.41834968e-01 1.02161527e+00 5.97868741e-01 3.59340250e-01
-2.24073440e-01 4.64670897e-01 -9.59068120e-01 -5.31831272e-02
-1.21244326e-01 4.66239033e-03 4.31053564e-02 -1.30082607e-01
5.25230050e-01 -4.82522756e-01 -5.37075162e-01 4.29462671e-01
-1.08248293e+00 -2.91831255e-01 3.97460759e-01 6.00312710e-01
4.71980542e-01 -2.15466227e-02 2.30802134e-01 -1.01359688e-01
7.82608747e-01 -4.57706779e-01 -2.93578625e-01 4.89818662e-01
-5.33139169e-01 -7.50564262e-02 1.22883551e-01 -8.17302644e-01
-7.82050490e-01 -4.05535847e-01 3.07720881e-02 -8.49104702e-01
2.14536101e-01 7.76778102e-01 5.57585396e-02 -2.67511398e-01
2.00977519e-01 4.21091050e-01 -9.23253689e-03 -5.21555126e-01
2.04549670e-01 1.02136338e+00 5.03125727e-01 -2.22241536e-01
4.74909544e-01 6.46081865e-02 -1.75540037e-02 -7.15301633e-01
-3.93440306e-01 -1.12343872e+00 -4.10716116e-01 -4.31563199e-01
6.39939845e-01 -9.38362777e-01 -3.84434849e-01 2.91077137e-01
-1.08104849e+00 6.12012804e-01 2.36142009e-01 1.04029942e+00
-4.16287661e-01 9.20913160e-01 -3.90824437e-01 -6.93392754e-01
-5.42023063e-01 -1.10954225e+00 9.70988035e-01 3.85532320e-01
8.57754797e-02 -5.29327035e-01 2.77959228e-01 2.22928792e-01
6.26645744e-01 -1.60905525e-01 1.78764537e-01 -9.73388314e-01
-1.75501406e-01 -6.42877936e-01 -4.37851176e-02 3.33381966e-02
1.67626739e-01 3.39142829e-01 -5.73521912e-01 -2.73348451e-01
-1.54538993e-02 6.30173534e-02 6.71423614e-01 2.03471661e-01
6.40618980e-01 -5.50584607e-02 -4.32062507e-01 2.09572315e-01
1.23691750e+00 4.17604506e-01 7.46810377e-01 4.06398773e-01
4.83118325e-01 3.00162852e-01 1.28261781e+00 5.33263385e-01
2.82133937e-01 1.01047242e+00 2.25351453e-02 3.31370115e-01
-4.09347266e-02 -2.05683149e-02 2.87490368e-01 1.37360787e+00
-1.34856135e-01 -3.94525349e-01 -8.48608255e-01 4.88242835e-01
-2.19104147e+00 -1.23847544e+00 9.71825272e-02 2.02104902e+00
4.91522104e-01 -5.63652031e-02 2.76960023e-02 4.09172118e-01
8.75892758e-01 4.13140148e-01 5.44087626e-02 -1.77147880e-01
-1.00929216e-01 -2.87168652e-01 2.06855491e-01 6.93627968e-02
-1.02339637e+00 6.81300879e-01 6.36048365e+00 1.40224934e+00
-1.00654447e+00 1.28989801e-01 -2.18804389e-01 -2.08369613e-01
-1.64781153e-01 1.20202146e-01 -6.43908381e-01 4.58093941e-01
8.86994660e-01 -3.26792091e-01 4.97170895e-01 6.39260828e-01
-1.25628769e-01 -2.46003896e-01 -8.08653772e-01 1.52280700e+00
5.33824980e-01 -1.05189836e+00 -6.02567615e-03 -6.06965683e-02
6.11504555e-01 1.83098996e-03 -8.86898711e-02 1.50804102e-01
-5.13780177e-01 -4.69453186e-01 5.34980953e-01 8.95058930e-01
4.90801036e-01 -6.42640054e-01 9.69507456e-01 1.37551039e-01
-1.49373353e+00 3.43252122e-02 -3.25054228e-01 2.57988691e-01
6.00303710e-01 4.24883395e-01 -4.55227047e-01 1.12822092e+00
5.32456875e-01 6.97428107e-01 -5.53214908e-01 1.30512619e+00
2.03745827e-01 1.45785272e-01 -4.64267641e-01 -2.14374922e-02
4.05751586e-01 -1.51967525e-01 6.98212802e-01 1.14904535e+00
6.46260202e-01 3.16068351e-01 4.69907224e-01 -1.04102805e-01
2.90561974e-01 5.76502442e-01 -6.34762585e-01 -4.60219204e-01
6.15875781e-01 1.09585047e+00 -4.70637649e-01 -5.33372581e-01
-6.77317142e-01 7.03357577e-01 -9.78757963e-02 6.41319947e-03
-7.22075284e-01 -6.17848039e-01 5.15953064e-01 -2.31507003e-01
4.48763907e-01 -5.14447927e-01 5.47260046e-01 -1.31043422e+00
-3.70436199e-02 -9.91507649e-01 4.47424650e-01 -9.57476139e-01
-1.17877758e+00 5.66662371e-01 3.44384313e-01 -1.68225098e+00
-6.04272544e-01 -1.83839515e-01 -3.93244058e-01 5.30946791e-01
-1.39889860e+00 -9.68680084e-01 -2.48038873e-01 8.05147707e-01
5.72297215e-01 -3.49907070e-01 6.55331612e-01 6.28653884e-01
-2.91898906e-01 3.42377305e-01 2.88208246e-01 5.69847040e-03
9.88720536e-01 -5.44356763e-01 5.74975312e-02 7.87786901e-01
4.84535396e-01 6.68064356e-01 7.57942379e-01 -6.18275702e-01
-1.84298992e+00 -3.63929033e-01 8.80189300e-01 3.27819027e-02
5.92561603e-01 2.83318549e-01 -1.04257047e+00 8.78312960e-02
2.72996306e-01 1.20458506e-01 7.37663388e-01 -1.64290279e-01
-4.06205356e-01 -2.02772617e-01 -1.01495028e+00 6.11484647e-01
8.53465915e-01 -7.42452443e-01 -8.60340059e-01 6.94293901e-02
7.19921827e-01 -3.24805588e-01 -1.20159602e+00 5.68784952e-01
8.97242606e-01 -6.06160104e-01 9.77616847e-01 -2.44681492e-01
-4.50520031e-02 -4.19203401e-01 -7.04599142e-01 -8.35801482e-01
-1.11005716e-01 -5.16959965e-01 -3.43507707e-01 1.29525411e+00
-6.51561022e-02 -3.01882178e-01 7.49745220e-02 1.55422702e-01
5.51756509e-02 -5.05818844e-01 -1.03153932e+00 -7.38318861e-01
-5.99194825e-01 -4.07536447e-01 7.66395628e-01 8.71114254e-01
4.28098619e-01 2.12628797e-01 -4.33933407e-01 -3.13695312e-01
2.26456895e-01 3.64503473e-01 5.99136591e-01 -1.03662348e+00
-1.01763524e-01 -5.87351203e-01 -9.48563397e-01 -7.54031956e-01
-1.66986473e-02 -4.34056312e-01 -5.51733188e-02 -1.31654382e+00
4.28005606e-01 2.50816047e-02 -5.48003614e-01 5.94545305e-02
-2.22641930e-01 2.34188408e-01 6.52069211e-01 6.37115479e-01
-1.04030585e+00 4.86686885e-01 1.13063955e+00 2.29534656e-02
-8.36265907e-02 -3.81256700e-01 -1.32306159e-01 3.01144123e-01
7.45347023e-01 -4.08569992e-01 -3.47752512e-01 -4.13991630e-01
6.77077286e-03 3.89375985e-01 -1.54878736e-01 -1.05961895e+00
5.01632571e-01 -2.07706138e-01 2.07561821e-01 -8.53161454e-01
5.49732447e-01 -9.06096637e-01 4.29346055e-01 1.48740977e-01
-1.45984039e-01 6.74281895e-01 -1.53578982e-01 5.27444839e-01
-7.91773379e-01 -2.93955535e-01 1.52123868e-01 -6.94113448e-02
-8.48221123e-01 3.21577817e-01 -2.42490366e-01 -3.38017642e-01
8.89664233e-01 -2.56044894e-01 -4.29052234e-01 -5.53814471e-01
-2.17845634e-01 1.94827721e-01 4.89779234e-01 6.41213715e-01
7.90301919e-01 -1.59874213e+00 -5.69658279e-01 3.74971926e-02
1.32650867e-01 -5.70132434e-01 2.95555115e-01 1.06966770e+00
-2.93603063e-01 6.93517208e-01 -2.90152609e-01 -5.74037433e-01
-1.58059943e+00 8.07847023e-01 -3.57736856e-01 -2.99566895e-01
-4.54764277e-01 2.50394225e-01 -3.91791582e-01 3.43888849e-01
8.65955800e-02 3.41665775e-01 -6.84364438e-01 2.82987267e-01
8.51409376e-01 3.93702626e-01 7.40094408e-02 -1.01224434e+00
-4.96114433e-01 8.12767684e-01 -1.49389923e-01 -4.74858940e-01
9.58722711e-01 -4.35164899e-01 1.13371136e-02 3.40576321e-01
1.40552950e+00 -9.02583599e-02 -6.02092445e-01 -4.49483603e-01
5.28731272e-02 -9.95316088e-01 2.50396192e-01 -1.86954051e-01
-1.04195035e+00 7.08132625e-01 7.38801658e-01 1.02174379e-01
1.26895177e+00 -2.25129664e-01 1.08333731e+00 5.37888348e-01
4.86288577e-01 -1.16368270e+00 -4.30894680e-02 2.91670918e-01
6.64812207e-01 -1.14620674e+00 5.06265998e-01 -1.82309285e-01
-6.43682122e-01 1.28208637e+00 1.55450255e-01 -1.06308393e-01
6.30766571e-01 -1.45926446e-01 4.60561588e-02 -2.26888843e-02
-9.39570665e-01 -4.20769155e-01 8.32962990e-01 4.31420356e-01
5.06774783e-01 -3.48372579e-01 -1.07593822e+00 2.96060503e-01
1.53618827e-01 -1.30700082e-01 1.50885776e-01 1.38488126e+00
-6.43329918e-01 -1.30286419e+00 -3.96134377e-01 3.86609435e-01
-8.15084279e-01 -1.07604496e-01 7.54716573e-03 7.29560554e-01
-2.24858463e-01 1.07508743e+00 1.63448770e-02 -5.13424635e-01
6.89654350e-02 3.46394293e-02 6.90161347e-01 -4.87243384e-02
-4.54944611e-01 6.36846423e-01 -2.55634892e-03 -6.97258711e-01
-1.11931360e+00 -8.22887063e-01 -1.03243101e+00 -4.61044937e-01
-8.55971336e-01 4.59632963e-01 9.93045747e-01 1.08129132e+00
2.43356586e-01 1.48553312e-01 7.66207278e-01 -9.18941379e-01
-4.90514725e-01 -1.18104768e+00 -4.54895198e-01 4.53048289e-01
1.35410234e-01 -8.05408418e-01 -2.70863414e-01 -5.24992645e-02] | [10.28172492980957, 0.7766464948654175] |
aed53665-9748-48e7-887e-85d63f1cb17a | a-multilingual-study-of-multi-sentence | 2004.04468 | null | https://arxiv.org/abs/2004.04468v1 | https://arxiv.org/pdf/2004.04468v1.pdf | A Multilingual Study of Multi-Sentence Compression using Word Vertex-Labeled Graphs and Integer Linear Programming | Multi-Sentence Compression (MSC) aims to generate a short sentence with the key information from a cluster of similar sentences. MSC enables summarization and question-answering systems to generate outputs combining fully formed sentences from one or several documents. This paper describes an Integer Linear Programming method for MSC using a vertex-labeled graph to select different keywords, with the goal of generating more informative sentences while maintaining their grammaticality. Our system is of good quality and outperforms the state of the art for evaluations led on news datasets in three languages: French, Portuguese and Spanish. We led both automatic and manual evaluations to determine the informativeness and the grammaticality of compressions for each dataset. In additional tests, which take advantage of the fact that the length of compressions can be modulated, we still improve ROUGE scores with shorter output sentences. | ['Andréa Carneiro Linhares', 'Juan-Manuel Torres-Moreno', 'Stéphane Huet', 'Elvys Linhares Pontes', 'Thiago G. da Silva'] | 2020-04-09 | null | null | null | null | ['sentence-compression'] | ['natural-language-processing'] | [ 5.04346073e-01 4.82537478e-01 -5.44407181e-02 -3.23788017e-01
-1.28117883e+00 -6.80251062e-01 5.81529438e-01 8.44850183e-01
-3.84375155e-01 1.13370335e+00 8.16264331e-01 -1.53012633e-01
-2.50726342e-01 -7.59370983e-01 -5.52707732e-01 -2.91932583e-01
-4.42312062e-02 7.66922355e-01 1.25125289e-01 -4.29239839e-01
6.48754895e-01 1.93252146e-01 -1.51812565e+00 6.62247181e-01
1.24276233e+00 2.15347037e-01 5.57356238e-01 1.13180196e+00
-4.40378815e-01 6.48038924e-01 -1.00867224e+00 -5.97583890e-01
-1.50973007e-01 -8.36094320e-01 -1.17121255e+00 8.28312635e-02
3.51985097e-01 1.87075824e-01 -1.79254189e-01 8.49887371e-01
5.71053207e-01 -3.08425147e-02 5.24797857e-01 -9.08279300e-01
-1.07148021e-01 1.19455254e+00 -3.11204076e-01 2.71928549e-01
1.04371250e+00 -1.91780776e-01 1.18648827e+00 -3.43712956e-01
9.54194784e-01 1.34391069e+00 2.26956055e-01 1.92438930e-01
-1.06962359e+00 1.28562883e-01 -2.39201367e-01 1.08651161e-01
-1.19166231e+00 -5.65328121e-01 4.77613300e-01 1.80418238e-01
1.44228983e+00 9.78186011e-01 5.67821980e-01 5.49179733e-01
4.97723669e-01 6.11880183e-01 5.79036415e-01 -8.23684156e-01
2.03709409e-01 2.94824690e-01 1.56636596e-01 6.58550501e-01
3.59428227e-01 -6.08981609e-01 -5.92748880e-01 -4.41484600e-01
-2.10009426e-01 -6.58412993e-01 -3.11858773e-01 2.83766270e-01
-1.25157642e+00 9.71721947e-01 -1.61343768e-01 5.83600283e-01
-5.83038986e-01 -6.06705584e-02 5.97745478e-01 2.80550212e-01
4.57664132e-01 8.35380077e-01 -1.76527917e-01 -2.77564436e-01
-1.34168780e+00 4.53635246e-01 1.28493297e+00 1.15466464e+00
4.75528479e-01 -1.30228013e-01 -6.41867697e-01 7.46410847e-01
-6.14700094e-02 4.02157992e-01 5.60282409e-01 -1.06610107e+00
9.49267864e-01 5.88042498e-01 -1.44684359e-01 -9.12661433e-01
-3.10961753e-01 -3.44859540e-01 -6.54795885e-01 -5.59326351e-01
-1.12699166e-01 -3.84118229e-01 -4.77918237e-01 1.33395445e+00
-6.72748610e-02 -4.73017305e-01 3.49236190e-01 2.73332208e-01
9.04675484e-01 1.20655322e+00 -4.42365080e-01 -8.13175321e-01
1.18341446e+00 -9.79589283e-01 -6.96201146e-01 -1.36270061e-01
6.46517634e-01 -9.26066756e-01 8.85151386e-01 3.18273544e-01
-1.52510536e+00 -3.72557282e-01 -9.88582194e-01 -1.88631471e-02
-2.82453112e-02 1.08041823e-01 2.00612009e-01 7.28194296e-01
-1.27391100e+00 7.26336896e-01 -4.05006766e-01 -3.06805462e-01
9.97600728e-04 2.30989680e-01 -2.66697168e-01 -1.30742475e-01
-1.00116229e+00 8.25695276e-01 8.33238363e-01 -5.75008631e-01
-3.39016706e-01 -4.46759105e-01 -7.52216816e-01 3.09695154e-01
2.65558034e-01 -9.01796639e-01 1.11100733e+00 -5.68183780e-01
-1.28788006e+00 5.70178509e-01 -4.48444456e-01 -8.02253067e-01
3.37877035e-01 1.63777635e-01 -1.66725114e-01 7.25418806e-01
2.43665308e-01 8.04527998e-01 4.73800600e-01 -8.37217569e-01
-6.27880156e-01 -1.43561259e-01 -4.16848175e-02 5.67068338e-01
-1.90170705e-01 1.00678384e-01 -5.99246264e-01 -5.05720913e-01
-2.17183053e-01 -6.92066312e-01 -3.66256624e-01 -8.99996459e-01
-6.87291384e-01 -3.05539101e-01 3.68996322e-01 -1.01352763e+00
1.50258541e+00 -1.66661370e+00 4.74551201e-01 1.41480818e-01
-1.23186402e-01 8.05670545e-02 -2.65218198e-01 9.54080760e-01
2.26211041e-01 3.64166349e-01 -3.71004999e-01 -3.70784402e-01
-1.61043569e-01 1.61916897e-01 -2.49591053e-01 -6.09562173e-03
1.18745297e-01 8.14795554e-01 -9.70665634e-01 -8.85065258e-01
-1.33963302e-01 2.22207420e-02 -5.89589238e-01 4.45614569e-02
-5.08789301e-01 -1.64047200e-02 -1.92344889e-01 2.15982690e-01
1.93530396e-01 1.61711261e-01 3.01244676e-01 3.86111811e-02
-2.27445383e-02 4.89836782e-01 -1.04582393e+00 1.56657720e+00
-3.63993376e-01 6.72441244e-01 -2.34010324e-01 -8.72484505e-01
1.02368796e+00 2.95360148e-01 2.78110266e-01 -6.60133898e-01
-1.05370671e-01 1.90131798e-01 -2.30274752e-01 -5.67089081e-01
1.27107143e+00 1.84100911e-01 -3.42697620e-01 6.57245517e-01
6.45287484e-02 -6.55513644e-01 1.18393648e+00 8.78246248e-01
1.03670478e+00 -5.41054964e-01 3.13248932e-01 -2.37671226e-01
6.57133639e-01 1.36541739e-01 3.81546915e-02 9.50982630e-01
4.29892987e-01 8.73522401e-01 9.23327923e-01 1.19906895e-01
-1.37048805e+00 -7.00396359e-01 2.07931891e-01 8.04314494e-01
-1.91245705e-01 -9.37072754e-01 -1.01703191e+00 -6.07969940e-01
-3.52107674e-01 1.41326642e+00 -9.07663181e-02 -1.30593970e-01
-7.74526954e-01 -6.75374627e-01 6.64665937e-01 -3.71664651e-02
1.72486886e-01 -1.18848443e+00 -5.17627597e-01 3.36465627e-01
-8.46379638e-01 -1.08713305e+00 -6.58121943e-01 -1.05986662e-01
-8.85267079e-01 -8.53699863e-01 -6.18866384e-01 -8.09447408e-01
6.15734458e-01 1.02214307e-01 1.37004817e+00 -1.27507653e-02
-1.72168948e-02 2.34546378e-01 -6.38037801e-01 -4.58131254e-01
-1.07763338e+00 5.16127884e-01 -3.03627074e-01 -4.68317986e-01
-1.28190875e-01 -3.18160176e-01 -6.96863160e-02 -2.58838803e-01
-1.18854499e+00 8.79493877e-02 5.23852050e-01 4.92060274e-01
5.55036783e-01 1.63301140e-01 7.27370977e-01 -9.59361970e-01
1.46092558e+00 -2.91315973e-01 -2.04068705e-01 6.35640323e-01
-5.58774769e-01 5.70759237e-01 8.79553020e-01 1.45415381e-01
-8.36097062e-01 -1.74735680e-01 -3.01515669e-01 4.02740479e-01
1.28695309e-01 7.13235438e-01 8.26075859e-03 4.22414333e-01
7.61732697e-01 5.79210579e-01 6.72402829e-02 -2.95948923e-01
5.32181203e-01 7.92147517e-01 5.43332636e-01 -1.72416687e-01
1.32314265e-01 -4.51661944e-02 -4.90590520e-02 -1.05419433e+00
-4.26674068e-01 -4.77934599e-01 -3.81663352e-01 -1.75234765e-01
4.60179925e-01 -5.93158662e-01 -4.06347886e-02 -7.56712332e-02
-1.42582297e+00 3.70613337e-01 -5.87990463e-01 1.84132025e-01
-6.08788013e-01 8.66551697e-01 -4.28021997e-01 -5.44925988e-01
-9.84674394e-01 -9.39806461e-01 1.04795849e+00 1.69452757e-01
-4.98690188e-01 -7.10028589e-01 1.63512081e-01 3.84719193e-01
1.24402188e-01 1.21635161e-01 1.09044552e+00 -8.11059415e-01
-1.40403122e-01 -4.53994662e-01 1.08450234e-01 2.59343356e-01
-1.01086080e-01 1.08330116e-01 -2.43778914e-01 -3.70888621e-01
-1.23687975e-01 -1.93207711e-01 1.01811349e+00 4.70927358e-01
7.48370409e-01 -7.99259067e-01 -1.58294052e-01 1.35491155e-02
1.33562589e+00 1.34002522e-01 8.27152848e-01 1.23913042e-01
1.01990409e-01 7.53747702e-01 5.66170514e-01 4.30098236e-01
3.44033211e-01 4.75991577e-01 1.52467042e-01 4.86654729e-01
-5.53848445e-02 -3.04433972e-01 4.24541414e-01 1.12852657e+00
2.62711436e-01 -7.99390495e-01 -5.81875861e-01 6.24126375e-01
-1.57392645e+00 -1.17790091e+00 -1.42280966e-01 2.08568645e+00
9.17826712e-01 3.23426157e-01 2.73831427e-01 2.90713102e-01
8.08360994e-01 3.46220255e-01 -3.44491587e-03 -1.02363169e+00
-3.61395687e-01 1.87504023e-01 4.02933866e-01 8.11352074e-01
-5.98256111e-01 7.81329811e-01 6.61582994e+00 9.52228308e-01
-6.74510479e-01 -3.05356264e-01 6.56167805e-01 -3.48385245e-01
-8.72694910e-01 -2.22596806e-02 -7.91823685e-01 5.62943637e-01
1.43694043e+00 -9.03665721e-01 3.96917909e-01 2.86986202e-01
4.39482629e-01 -4.66620475e-01 -6.98889494e-01 4.88985002e-01
4.60743785e-01 -1.79137397e+00 3.48465145e-01 -2.58627951e-01
8.72573674e-01 -1.02836043e-01 -4.88222867e-01 1.05055407e-01
5.59054352e-02 -7.36721158e-01 6.53440952e-01 6.57234907e-01
5.32443225e-01 -1.06836081e+00 8.12005997e-01 7.20454454e-01
-7.36183465e-01 8.65515172e-02 -5.41004300e-01 1.46815538e-01
4.49861646e-01 6.58000052e-01 -1.17467654e+00 1.04962134e+00
2.49730989e-01 3.18060517e-01 -8.56210530e-01 1.06794763e+00
-1.96099892e-01 6.25987172e-01 -3.76789838e-01 -6.64063334e-01
3.20951998e-01 -2.34563872e-01 9.07129884e-01 1.61126637e+00
4.29223031e-01 -6.67817220e-02 -4.89338674e-02 4.39538062e-01
-8.13795552e-02 5.62904418e-01 -6.34035110e-01 -2.32606053e-01
5.64788699e-01 1.02671993e+00 -7.54713655e-01 -4.88834202e-01
1.58938333e-01 8.56133521e-01 1.18539050e-01 -1.13117307e-01
-4.13771033e-01 -7.78327584e-01 -2.58379191e-01 -1.28159449e-01
2.84850717e-01 -9.92355198e-02 -3.96927536e-01 -8.66000712e-01
2.48043954e-01 -1.06396461e+00 3.88719022e-01 -6.91785336e-01
-4.71686453e-01 8.69162202e-01 2.75992036e-01 -9.71866667e-01
-9.23262000e-01 2.80330062e-01 -6.88916445e-01 7.50572383e-01
-9.06676590e-01 -5.44746518e-01 1.46161616e-01 -3.29464152e-02
8.47266853e-01 -3.48742753e-01 8.13141227e-01 2.37968247e-02
-4.18890476e-01 4.12366301e-01 3.54731947e-01 -4.01357532e-01
2.90210247e-01 -1.22270870e+00 4.94558901e-01 9.71549153e-01
3.69640440e-01 2.71603912e-01 1.06123316e+00 -6.34588540e-01
-1.22298658e+00 -9.65848267e-01 1.73715138e+00 7.91333243e-02
2.13516816e-01 -2.26000454e-02 -5.16508520e-01 7.47834891e-02
7.71099687e-01 -9.92437899e-01 4.28683370e-01 -3.02317530e-01
2.40518183e-01 -9.83920693e-03 -1.10017288e+00 5.20893216e-01
6.47869408e-01 -8.01278204e-02 -7.61241138e-01 6.90947771e-01
9.91902888e-01 -2.42739096e-01 -5.45685291e-01 7.31881559e-02
5.38794957e-02 -9.43690836e-01 6.77548409e-01 -5.05117893e-01
9.02330220e-01 3.67429070e-02 -1.14316829e-01 -1.55107021e+00
-1.35022759e-01 -5.93851209e-01 -7.08700866e-02 1.31096923e+00
7.36320019e-01 -1.60269231e-01 6.55907393e-01 7.99812451e-02
-2.36976191e-01 -7.52772689e-01 -8.89493287e-01 -6.47677720e-01
-2.99133454e-02 -2.02119201e-01 5.87862194e-01 1.60272464e-01
3.62254351e-01 9.05384362e-01 -2.88573772e-01 -3.30417484e-01
4.08389270e-01 3.56331050e-01 4.82779086e-01 -8.31042826e-01
-1.37429848e-01 -4.16452885e-01 -7.64372572e-02 -6.58633947e-01
9.07960236e-02 -1.08014119e+00 1.34060960e-02 -2.03331995e+00
3.38937789e-01 1.99399486e-01 5.14426291e-01 9.34005380e-02
-2.51748890e-01 7.53860734e-03 4.17368293e-01 -4.10974734e-02
-8.49411130e-01 4.44802165e-01 1.03843617e+00 -3.28289390e-01
-4.27193344e-01 1.65436596e-01 -9.61414635e-01 3.16376477e-01
1.02710426e+00 -5.57805419e-01 -4.89523411e-01 -3.26597840e-01
4.71957654e-01 5.15594184e-01 -2.83601880e-01 -9.19989347e-01
3.19998950e-01 1.26997575e-01 -1.52841389e-01 -1.03984046e+00
-1.44014647e-02 -2.56401807e-01 2.46148303e-01 6.63788736e-01
-7.92736471e-01 4.47274625e-01 1.21852636e-01 4.78402019e-01
-3.69674534e-01 -8.31034660e-01 5.21721363e-01 -3.45019013e-01
-2.39623904e-01 -2.20990881e-01 -6.18597865e-01 3.68684709e-01
7.97835410e-01 -1.00571483e-01 -2.00696424e-01 -8.42611194e-01
-2.63585120e-01 4.78784949e-01 2.50405788e-01 3.93578947e-01
8.12363982e-01 -8.74477983e-01 -1.37917554e+00 -1.56918183e-01
-8.58802125e-02 -2.04547197e-01 7.81296566e-03 5.30182481e-01
-1.08686781e+00 9.04445410e-01 -1.54067483e-02 -3.65096331e-01
-1.56352651e+00 2.98832208e-01 -1.39662102e-01 -7.56107628e-01
-4.03877348e-01 5.26979864e-01 -8.61541748e-01 -3.31960082e-01
2.23365158e-01 -6.45829961e-02 -4.68810022e-01 2.32389957e-01
6.43249869e-01 7.32610643e-01 4.34130460e-01 -4.90522146e-01
-7.53238648e-02 -2.92673800e-02 -1.21230952e-01 -3.99013579e-01
1.25094259e+00 -1.99121103e-01 -4.88314062e-01 4.46918197e-02
1.36198032e+00 2.92043477e-01 -3.78028661e-01 1.84043989e-01
1.48156345e-01 -1.78347677e-01 -1.76756546e-01 -6.18325055e-01
-5.57870150e-01 2.33353496e-01 -9.68587026e-02 6.68851256e-01
1.07815754e+00 1.21299282e-01 8.66601765e-01 5.43795705e-01
3.05408329e-01 -1.24929905e+00 7.53644435e-03 6.63140655e-01
1.09702730e+00 -6.98143661e-01 3.12395900e-01 -3.81167114e-01
-9.32852566e-01 1.21004844e+00 -4.47320379e-02 1.25550792e-01
4.98568080e-02 1.28782809e-01 -4.16174412e-01 -1.10822842e-02
-9.80288982e-01 6.35128021e-02 2.72752404e-01 3.38055462e-01
3.79165202e-01 6.65895715e-02 -1.24867475e+00 2.27252275e-01
-8.30919266e-01 -3.54489535e-01 1.01683879e+00 7.57519603e-01
-8.29601586e-01 -1.21127534e+00 -2.89896607e-01 9.34938371e-01
-5.55613399e-01 -2.66526490e-01 -8.03669274e-01 3.02771568e-01
-3.36786658e-01 1.37658834e+00 7.74752870e-02 -2.76490092e-01
3.54685962e-01 5.83479786e-03 5.38620055e-01 -7.89668620e-01
-8.24086726e-01 -3.52370664e-02 7.35095680e-01 -1.96138352e-01
-2.72005737e-01 -8.87466967e-01 -1.13096023e+00 -4.52354848e-01
-3.65922540e-01 7.75446892e-01 6.91544712e-01 8.82110775e-01
4.62154746e-01 5.29256701e-01 7.99185514e-01 -5.64248979e-01
-7.06743240e-01 -1.01932383e+00 -4.59117711e-01 1.63498983e-01
-4.54722717e-02 4.82956290e-01 -1.49295941e-01 9.01933177e-04] | [12.374893188476562, 9.518216133117676] |
93f37658-2376-4e9c-a179-de305e317599 | causal-discovery-from-subsampled-time-series-1 | 2305.05276 | null | https://arxiv.org/abs/2305.05276v2 | https://arxiv.org/pdf/2305.05276v2.pdf | Causal Discovery from Subsampled Time Series with Proxy Variables | Inferring causal structures from time series data is the central interest of many scientific inquiries. A major barrier to such inference is the problem of subsampling, i.e., the frequency of measurement is much lower than that of causal influence. To overcome this problem, numerous methods have been proposed, yet either was limited to the linear case or failed to achieve identifiability. In this paper, we propose a constraint-based algorithm that can identify the entire causal structure from subsampled time series, without any parametric constraint. Our observation is that the challenge of subsampling arises mainly from hidden variables at the unobserved time steps. Meanwhile, every hidden variable has an observed proxy, which is essentially itself at some observable time in the future, benefiting from the temporal structure. Based on these, we can leverage the proxies to remove the bias induced by the hidden variables and hence achieve identifiability. Following this intuition, we propose a proxy-based causal discovery algorithm. Our algorithm is nonparametric and can achieve full causal identification. Theoretical advantages are reflected in synthetic and real-world experiments. | ['Yizhou Wang', 'Lingjing Hu', 'Xinwei Sun', 'Mingzhou Liu'] | 2023-05-09 | null | null | null | null | ['causal-discovery', 'causal-identification'] | ['knowledge-base', 'reasoning'] | [ 2.36500368e-01 1.62125036e-01 -6.97557628e-01 -1.46136463e-01
-4.29324389e-01 -3.59409660e-01 4.97389704e-01 -2.26761356e-01
1.50586531e-01 1.21787608e+00 5.69877088e-01 -2.66804069e-01
-5.25848329e-01 -8.72526169e-01 -7.55758405e-01 -7.31474221e-01
-3.12638670e-01 1.31443307e-01 -1.88337728e-01 2.26697356e-01
6.23393245e-02 -4.30275165e-02 -1.23283255e+00 -2.33620197e-01
9.65714812e-01 5.36986887e-01 5.02353050e-02 1.30189866e-01
1.97805241e-01 5.84619343e-01 -4.32991236e-01 1.22325443e-01
-1.89456847e-02 -6.78196847e-01 -4.04005259e-01 2.05768645e-02
-1.83910251e-01 -4.87732291e-01 -5.31099319e-01 8.55398417e-01
2.13056982e-01 -1.31253824e-01 4.39236552e-01 -1.46292913e+00
-7.14777946e-01 1.09664166e+00 -6.76789641e-01 4.00577970e-02
3.70691210e-01 -1.52024657e-01 1.11463678e+00 -6.37852132e-01
3.38072628e-01 1.49117780e+00 4.32296485e-01 6.50703683e-02
-1.47987092e+00 -8.89529109e-01 3.94222200e-01 1.31924273e-02
-1.21825492e+00 -3.51176918e-01 9.00016546e-01 -4.87736613e-01
8.57571512e-02 2.68751830e-01 4.73930955e-01 1.50439715e+00
9.68261957e-02 6.78756058e-01 1.22854507e+00 -2.72433609e-01
4.59698796e-01 -1.37504354e-01 1.84362948e-01 2.48609006e-01
5.93421638e-01 5.92031240e-01 -6.92571521e-01 -5.20997167e-01
9.24747527e-01 3.62968028e-01 -5.46467364e-01 -5.09538613e-02
-1.39067900e+00 9.11015928e-01 1.26295742e-02 1.97821945e-01
-5.32318950e-01 1.51551425e-01 9.98449773e-02 3.45896572e-01
4.58939701e-01 2.48348534e-01 -6.14394903e-01 1.89146977e-02
-8.74677241e-01 1.41377509e-01 7.32881606e-01 7.81070888e-01
5.70833147e-01 5.84591627e-02 -1.81073770e-01 2.36569315e-01
2.96597004e-01 6.88129067e-01 1.70155004e-01 -8.77013445e-01
1.71612650e-01 4.72737432e-01 3.81922990e-01 -1.07537591e+00
-2.59068698e-01 -5.21379232e-01 -1.11910415e+00 -2.49071836e-01
5.68503261e-01 -4.10084605e-01 -5.87007642e-01 2.23435903e+00
4.36213106e-01 6.93094432e-01 -2.53070146e-01 9.05005276e-01
2.45546862e-01 5.17300069e-01 -8.56585577e-02 -8.57742369e-01
1.26345956e+00 -1.36834815e-01 -1.02394831e+00 2.15486482e-01
1.67849615e-01 -3.57348144e-01 7.98638463e-01 2.64206052e-01
-6.50264621e-01 -3.81157100e-01 -8.32192957e-01 4.31076974e-01
1.00738995e-01 -1.32255241e-01 9.53110576e-01 5.10057449e-01
-4.58719969e-01 4.70348656e-01 -8.66409779e-01 -1.86902300e-01
-7.22998334e-03 9.63493064e-02 2.60525104e-02 5.11363195e-03
-1.60508740e+00 2.04628289e-01 2.37435788e-01 2.89243795e-02
-1.03536117e+00 -1.07444286e+00 -3.02502900e-01 2.01127574e-01
7.60397732e-01 -7.74630070e-01 9.53063250e-01 -6.46985888e-01
-1.20643044e+00 8.00870452e-03 -5.66041529e-01 -3.50051522e-01
5.65029442e-01 -9.18213725e-02 -5.61848819e-01 -1.08035319e-01
4.61518675e-01 -2.71990240e-01 1.00903463e+00 -1.16805577e+00
-5.51773727e-01 -4.19488311e-01 -4.13904712e-02 -3.86810303e-01
-2.59019047e-01 -3.17269236e-01 -1.87427893e-01 -7.75121748e-01
3.84511054e-01 -1.02046812e+00 -2.53430486e-01 -4.30952728e-01
-6.93327546e-01 -1.60302445e-01 8.99027169e-01 -5.22111475e-01
1.51364851e+00 -2.15585542e+00 8.76374692e-02 1.30544960e-01
5.17716229e-01 -4.01221037e-01 2.12017179e-01 7.92675614e-01
-3.03073585e-01 3.05388391e-01 -1.74789533e-01 -3.46828140e-02
-1.64265350e-01 1.35089695e-01 -8.38935494e-01 6.76174879e-01
-3.02465279e-02 7.45715439e-01 -1.09048152e+00 -1.71076134e-01
1.04770608e-01 1.57749549e-01 -5.04101932e-01 1.86150506e-01
-1.62190050e-01 8.96673977e-01 -8.27098072e-01 5.07024169e-01
6.34197831e-01 -5.04662335e-01 4.89959508e-01 2.07815561e-02
-5.22143364e-01 2.18669206e-01 -1.23539376e+00 1.28034294e+00
-1.85468018e-01 4.04831737e-01 -6.56107292e-02 -1.20419919e+00
6.39884055e-01 7.31890917e-01 7.31242955e-01 -5.39005637e-01
-1.12887934e-01 1.33421719e-01 -4.74161766e-02 -4.71059769e-01
4.51583415e-02 -1.73685417e-01 -1.60874858e-01 6.20920837e-01
-3.91826719e-01 4.85526770e-01 -1.10018989e-02 1.49016738e-01
1.19403875e+00 -4.42222282e-02 4.78627861e-01 -3.01759630e-01
-4.25710492e-02 -5.86821400e-02 1.14026725e+00 9.88565445e-01
1.60695706e-02 2.60360181e-01 8.39675546e-01 -1.57835841e-01
-9.54309583e-01 -1.11364019e+00 -2.16011167e-01 6.19242251e-01
-3.78081501e-02 -1.60708487e-01 -3.07254732e-01 -3.65712881e-01
2.85902202e-01 7.22692311e-01 -1.06646502e+00 -2.59784967e-01
-4.87086564e-01 -9.04887795e-01 1.75141826e-01 3.40437919e-01
2.24093050e-01 -5.18999457e-01 -4.50931311e-01 4.63246137e-01
-4.29869980e-01 -7.89377868e-01 -3.08021426e-01 -8.74274895e-02
-1.03577602e+00 -1.17962325e+00 -4.02833223e-01 5.71503974e-02
6.08759999e-01 4.64260846e-01 9.18781340e-01 -2.14231506e-01
6.73223883e-02 2.42214240e-02 -2.91809797e-01 -4.77068365e-01
-9.15639400e-02 -2.17572317e-01 2.45554000e-01 3.18568438e-01
3.47563863e-01 -1.00884271e+00 -5.99530339e-01 3.07247251e-01
-7.20136940e-01 -6.47807270e-02 7.04238594e-01 9.60970700e-01
3.55628341e-01 5.44096708e-01 1.00118911e+00 -8.53876054e-01
4.15192485e-01 -9.71316338e-01 -7.75497377e-01 1.00993410e-01
-6.66812062e-01 1.86993897e-01 6.57229424e-01 -6.94451213e-01
-1.13744855e+00 -2.29756579e-01 5.94682992e-01 -3.61945778e-01
8.09249375e-03 9.15601015e-01 -3.81330222e-01 6.83330178e-01
1.84713870e-01 7.92866573e-02 2.76391115e-02 -4.80688632e-01
2.59792566e-01 4.43034947e-01 2.45567814e-01 -6.80403769e-01
8.40684474e-01 9.26000416e-01 2.57258266e-01 -7.92195380e-01
-1.03821874e+00 -2.80668855e-01 -3.86504591e-01 -1.01510569e-01
5.05106151e-01 -1.03305972e+00 -8.56970727e-01 4.11263406e-02
-9.62179840e-01 -2.31620502e-02 -1.19828358e-01 9.85257506e-01
-3.24679285e-01 1.77802779e-02 -3.53127927e-01 -1.13731611e+00
1.56385705e-01 -7.12229788e-01 7.43935466e-01 1.37832150e-01
-4.41666484e-01 -1.01499200e+00 2.42358863e-01 -3.08955107e-02
1.39816210e-01 5.66816211e-01 9.93667603e-01 -1.58060297e-01
-7.71001995e-01 -1.68058485e-01 -2.38812461e-01 -4.41990733e-01
4.87675190e-01 5.83026074e-02 -8.04517925e-01 -2.58356899e-01
2.57489502e-01 1.64333910e-01 7.49693930e-01 1.00068605e+00
9.94595885e-01 -3.99346620e-01 -5.76199830e-01 2.65223801e-01
1.19712925e+00 2.16014430e-01 4.21893775e-01 2.43489817e-02
5.48334062e-01 6.86977267e-01 6.23689950e-01 9.68733490e-01
4.06198174e-01 5.45832217e-01 3.19571704e-01 -1.46468967e-01
3.25930089e-01 -6.87138617e-01 1.26785710e-01 7.29389131e-01
-1.27554148e-01 -1.70900375e-01 -6.00242376e-01 7.15620875e-01
-2.11215711e+00 -1.15575075e+00 -6.66514516e-01 2.51993179e+00
8.51576090e-01 -1.26122862e-01 1.24797828e-01 1.37171954e-01
9.25941169e-01 3.78517737e-03 -7.25022495e-01 3.88166040e-01
-2.30916888e-01 -2.85506248e-01 6.36305273e-01 2.89259642e-01
-7.89452732e-01 3.55148107e-01 6.54755354e+00 3.19029272e-01
-8.93313050e-01 3.68952565e-02 4.19740260e-01 -9.84997377e-02
-4.69220847e-01 5.74149013e-01 -6.67160094e-01 6.70176983e-01
1.01065624e+00 -6.62069857e-01 3.86930555e-01 4.38696235e-01
1.07676435e+00 -3.15551162e-02 -1.17855513e+00 3.56733054e-01
-5.66271901e-01 -9.14707124e-01 -6.49274811e-02 5.36166191e-01
8.17625046e-01 -4.27096665e-01 2.33456157e-02 1.10365018e-01
6.53493881e-01 -8.86156023e-01 6.65113866e-01 6.32076502e-01
6.79565847e-01 -5.59731543e-01 3.68819147e-01 4.85000223e-01
-1.05986547e+00 -2.93313473e-01 -4.64316577e-01 -5.88134289e-01
3.25206906e-01 1.45969331e+00 -5.17726004e-01 7.39269078e-01
4.82243598e-01 7.96591401e-01 5.47580235e-02 7.48616695e-01
-4.46617275e-01 1.23088443e+00 -2.05235988e-01 1.16022848e-01
-1.72532946e-01 -3.66153955e-01 6.67207241e-01 6.56344533e-01
6.23998523e-01 3.34790289e-01 1.56580806e-01 1.08771193e+00
1.08139381e-01 -3.50090981e-01 -5.98634064e-01 -2.91839510e-01
9.50743079e-01 7.49893248e-01 -4.17819828e-01 -3.33918214e-01
-6.25768960e-01 4.22295004e-01 -1.18671663e-01 7.11164296e-01
-1.02512002e+00 3.15390304e-02 5.84810734e-01 2.06759945e-01
1.18048742e-01 -2.94287175e-01 -3.30746412e-01 -1.33246136e+00
-8.94585550e-02 -8.14561427e-01 5.09373128e-01 -3.58932346e-01
-1.26125467e+00 -2.82685637e-01 1.61055893e-01 -1.17604935e+00
-1.77351043e-01 4.24308628e-02 -5.15478790e-01 9.77529645e-01
-1.25408459e+00 -8.25457454e-01 -1.04949564e-01 5.19801915e-01
1.86806723e-01 3.26742351e-01 5.49673259e-01 2.66232878e-01
-7.99714208e-01 1.20685704e-01 1.96878091e-01 -1.57894213e-02
7.56260812e-01 -1.21006024e+00 2.19132118e-02 9.41059887e-01
-1.95653081e-01 1.11955631e+00 9.80300426e-01 -1.04430878e+00
-1.71173239e+00 -1.08352923e+00 9.13177967e-01 -3.00366938e-01
1.12360954e+00 -4.03991908e-01 -8.86448741e-01 8.16306412e-01
-6.70591891e-02 -3.10191214e-01 6.75536096e-01 6.38979554e-01
-2.35187307e-01 -6.56552538e-02 -7.06843317e-01 7.23637462e-01
1.11199272e+00 -4.03982073e-01 -5.65167069e-01 8.53725821e-02
9.71489191e-01 1.99055925e-01 -9.20678556e-01 4.60421711e-01
6.74606085e-01 -8.42213273e-01 8.41051698e-01 -5.92059374e-01
5.56754887e-01 -3.39074314e-01 -7.66323656e-02 -1.33257806e+00
-6.32725298e-01 -6.84688747e-01 -2.95700103e-01 1.45537531e+00
2.66017765e-01 -8.55066836e-01 5.19756615e-01 6.46277666e-01
3.00933331e-01 -8.47345889e-02 -8.63737941e-01 -9.06207025e-01
-9.83283222e-02 -3.02756667e-01 8.46286833e-01 1.35107219e+00
-4.48853932e-02 4.34571922e-01 -8.36429954e-01 5.10977566e-01
1.18490040e+00 6.67056441e-01 8.00494909e-01 -1.60496891e+00
-5.12131155e-01 -1.15093410e-01 1.50805771e-01 -9.20032680e-01
9.22366902e-02 -2.55801797e-01 -1.44605890e-01 -1.09984231e+00
6.05970681e-01 -4.47319835e-01 -3.48886132e-01 1.80734083e-01
-4.74477917e-01 -3.70108128e-01 -2.86551654e-01 4.31652993e-01
1.55575043e-02 6.85748458e-01 1.26826608e+00 9.91698913e-03
-4.02593374e-01 5.36922850e-02 -8.46668363e-01 5.52729070e-01
7.80989110e-01 -7.86703408e-01 -6.27117932e-01 -5.95855564e-02
1.84716776e-01 8.24316800e-01 6.53083265e-01 -3.75180125e-01
4.64998707e-02 -6.63857222e-01 7.79797658e-02 -6.88861966e-01
-6.16860613e-02 -7.38832057e-01 6.89639211e-01 5.52147806e-01
-2.71608233e-01 -2.05125928e-01 -2.81374782e-01 1.00900328e+00
-1.87053978e-01 1.97269633e-01 3.05481374e-01 6.33012876e-02
-1.79571524e-01 3.66162837e-01 -2.46771127e-01 3.61523405e-02
7.40201116e-01 3.28979701e-01 -3.29515815e-01 -4.81997579e-01
-5.35005569e-01 2.45195344e-01 2.34735414e-01 3.05981934e-01
2.62551844e-01 -1.38764656e+00 -9.97638106e-01 -6.66554123e-02
-6.35340959e-02 -3.81750137e-01 2.91101843e-01 1.31520367e+00
5.89224339e-01 7.68229246e-01 3.37765962e-01 -5.09477913e-01
-7.67235875e-01 8.39972436e-01 -2.18165964e-01 -1.57949969e-01
-6.08030379e-01 2.59817868e-01 6.38680041e-01 -7.95481354e-03
-1.16539918e-01 -2.93786585e-01 2.93956008e-02 2.13173583e-01
6.01284266e-01 5.32686651e-01 -5.55101931e-01 -1.31484181e-01
-1.89875305e-01 1.96586788e-01 3.04234445e-01 -2.27938890e-01
1.27418184e+00 -4.55782920e-01 -2.89145947e-01 8.94499600e-01
1.04816699e+00 3.08034599e-01 -1.26088142e+00 -3.20387244e-01
1.31723374e-01 -5.91425598e-01 7.62798190e-02 -4.63491172e-01
-8.59982550e-01 4.50779408e-01 9.76403952e-02 7.61884928e-01
9.66428459e-01 -3.75195853e-02 4.02555615e-01 -1.09299496e-01
5.14790058e-01 -7.90457189e-01 -2.47386947e-01 7.52190202e-02
8.14728916e-01 -1.13168013e+00 3.37741040e-02 -4.53131229e-01
-4.04830426e-02 7.67973006e-01 3.60704446e-03 -3.70766222e-02
6.74505115e-01 1.83309212e-01 -3.81382048e-01 -1.76074579e-01
-1.00658453e+00 -4.27667908e-02 -6.76779151e-02 2.32076719e-01
5.29438555e-01 4.65598404e-01 -6.04600966e-01 6.61139965e-01
1.02347480e-02 1.88490197e-01 6.26282096e-01 6.23473883e-01
-1.34006187e-01 -9.04672325e-01 -7.22112417e-01 5.12909174e-01
-5.89100838e-01 -2.74848193e-02 -1.65628701e-01 8.28303039e-01
-3.00393373e-01 1.39647877e+00 -1.36183217e-01 -1.31557286e-01
2.64113277e-01 -2.27417782e-01 5.11707796e-04 -3.99729401e-01
3.19877297e-01 4.46541667e-01 -3.36646917e-03 -6.31278098e-01
-4.75422949e-01 -1.10730946e+00 -1.06151247e+00 -5.46390772e-01
-5.35743415e-01 4.58949417e-01 3.33580405e-01 9.09283340e-01
3.12442750e-01 7.76474059e-01 1.04098582e+00 -3.73912126e-01
-6.15622103e-01 -8.90438855e-01 -8.91525030e-01 2.26753116e-01
5.74048758e-01 -9.58535910e-01 -8.06189001e-01 1.12574346e-01] | [7.803852558135986, 5.2190327644348145] |
c380bb17-cb30-4306-bab9-74e848a5b58d | anticipating-the-unseen-discrepancy-for | 2209.04725 | null | https://arxiv.org/abs/2209.04725v1 | https://arxiv.org/pdf/2209.04725v1.pdf | Anticipating the Unseen Discrepancy for Vision and Language Navigation | Vision-Language Navigation requires the agent to follow natural language instructions to reach a specific target. The large discrepancy between seen and unseen environments makes it challenging for the agent to generalize well. Previous studies propose data augmentation methods to mitigate the data bias explicitly or implicitly and provide improvements in generalization. However, they try to memorize augmented trajectories and ignore the distribution shifts under unseen environments at test time. In this paper, we propose an Unseen Discrepancy Anticipating Vision and Language Navigation (DAVIS) that learns to generalize to unseen environments via encouraging test-time visual consistency. Specifically, we devise: 1) a semi-supervised framework DAVIS that leverages visual consistency signals across similar semantic observations. 2) a two-stage learning procedure that encourages adaptation to test-time distribution. The framework enhances the basic mixture of imitation and reinforcement learning with Momentum Contrast to encourage stable decision-making on similar observations under a joint training stage and a test-time adaptation stage. Extensive experiments show that DAVIS achieves model-agnostic improvement over previous state-of-the-art VLN baselines on R2R and RxR benchmarks. Our source code and data are in supplemental materials. | ['William Yang Wang', 'Xin Eric Wang', 'Wenda Xu', 'Weixi Feng', 'Ping Nie', 'Huiliang Zhang', 'Yujie Lu'] | 2022-09-10 | null | null | null | null | ['vision-language-navigation'] | ['computer-vision'] | [-3.92812230e-02 -1.53561220e-01 -1.22837834e-01 -6.79353356e-01
-6.44927740e-01 -5.65119386e-01 8.24802518e-01 -2.88965344e-01
-7.60136306e-01 6.96113110e-01 1.14615910e-01 -4.60693359e-01
2.14560464e-01 -4.65562522e-01 -1.11957943e+00 -6.15557730e-01
3.89142595e-02 4.92169410e-01 2.05483750e-01 -2.63331324e-01
8.36412609e-02 3.41529608e-01 -1.29625034e+00 6.01761788e-02
1.13430560e+00 8.02422106e-01 6.53039157e-01 6.03199184e-01
3.96933109e-02 9.96203601e-01 -1.84982225e-01 7.22842887e-02
5.75124204e-01 -4.39111114e-01 -4.19043362e-01 1.93261638e-01
7.71462679e-01 -5.72046995e-01 -7.17861593e-01 1.23843026e+00
3.84948075e-01 7.52351940e-01 6.83428943e-01 -1.34019995e+00
-1.43711650e+00 1.87348679e-01 -6.54922426e-01 3.04850250e-01
1.23851329e-01 8.05361748e-01 6.62774444e-01 -1.14530051e+00
5.78144908e-01 1.26051784e+00 5.42110920e-01 1.03287125e+00
-1.28856003e+00 -5.64145625e-01 7.45179892e-01 2.76666701e-01
-9.25886571e-01 -4.00532603e-01 6.16204381e-01 -3.99363041e-01
1.06314456e+00 -3.29583138e-01 6.30168736e-01 1.66558194e+00
6.65018037e-02 8.99238765e-01 1.14972365e+00 -1.46919921e-01
5.02969742e-01 5.76390252e-02 -3.58740650e-02 7.83613622e-01
2.24065259e-01 6.54078126e-01 -3.72102916e-01 2.42721722e-01
7.51021981e-01 1.93781599e-01 -3.55196118e-01 -9.86351311e-01
-1.10163617e+00 8.47698212e-01 9.83608246e-01 -2.55658448e-01
-4.56925482e-01 2.70431638e-01 3.40149432e-01 2.95242757e-01
6.18445016e-02 4.68411863e-01 -4.34186846e-01 1.29065096e-01
-5.33863962e-01 2.47384399e-01 3.62670183e-01 1.23051810e+00
7.84212112e-01 4.25613880e-01 -3.00931334e-01 8.14903319e-01
4.66819733e-01 7.31399775e-01 7.53667593e-01 -1.10042942e+00
5.46540141e-01 3.37309062e-01 8.73433277e-02 -4.28231210e-01
-2.08274931e-01 -6.24183714e-01 -6.31021440e-01 6.63592696e-01
3.00193816e-01 -1.60141379e-01 -1.41359091e+00 2.25321937e+00
2.56190628e-01 3.77772838e-01 5.76956213e-01 1.08360839e+00
7.73049831e-01 4.60968345e-01 1.09953202e-01 1.96753636e-01
7.28654027e-01 -1.70869410e+00 -4.64533925e-01 -7.83921361e-01
4.64703709e-01 -1.81859523e-01 1.48863101e+00 9.36455056e-02
-1.02015758e+00 -8.22425008e-01 -1.02994370e+00 -8.08559358e-02
-3.58884543e-01 -2.38032341e-02 4.17629570e-01 1.05155356e-01
-1.24960208e+00 3.14634770e-01 -1.05068207e+00 -4.91475552e-01
5.12797654e-01 5.44471815e-02 -4.41338658e-01 -2.69098729e-01
-8.84250820e-01 1.02644753e+00 2.73505002e-01 2.04264909e-01
-1.54421723e+00 -5.69742203e-01 -1.27262449e+00 -4.12870228e-01
5.93110502e-01 -8.24708939e-01 1.45046079e+00 -9.89833891e-01
-1.52949023e+00 7.51036286e-01 -1.28642917e-01 -6.81801796e-01
7.96491563e-01 -4.97292846e-01 -9.36623886e-02 -2.09815204e-01
3.00072253e-01 1.14616406e+00 7.54079759e-01 -1.52690506e+00
-6.28725708e-01 -4.33986843e-01 1.43809123e-02 5.47632039e-01
6.80926368e-02 -8.03245604e-01 -6.86164975e-01 -6.04723036e-01
1.41247839e-01 -1.06573761e+00 -5.66598475e-01 2.02304348e-01
-1.97218910e-01 -3.57114412e-02 6.27935827e-01 -3.63717377e-01
4.22638088e-01 -1.87001288e+00 2.17083111e-01 -1.05487406e-02
4.69514057e-02 4.94301096e-02 -5.69077373e-01 -5.32284975e-02
1.90766096e-01 -4.19279277e-01 -2.48309657e-01 -4.97954041e-01
-3.94658856e-02 5.63407958e-01 -6.27585471e-01 4.85109150e-01
1.76239073e-01 1.19203615e+00 -1.21277750e+00 4.42659818e-02
2.65771687e-01 3.35587591e-01 -7.51622260e-01 3.99776578e-01
-5.07009566e-01 1.00328040e+00 -4.61250603e-01 5.20806313e-01
5.20751476e-01 -3.07829946e-01 -2.19330445e-01 5.49682975e-02
-7.11910501e-02 5.11758775e-02 -7.54972458e-01 2.20716739e+00
-5.06357133e-01 6.59555554e-01 -1.28574431e-01 -9.29464102e-01
8.82148445e-01 -2.01971874e-01 -7.39575326e-02 -1.05775011e+00
-4.73054610e-02 1.34375498e-01 -7.72382645e-03 -5.50130963e-01
5.69277883e-01 1.84648827e-01 2.07399100e-01 1.12850256e-01
6.00179285e-02 -2.04360172e-01 -7.33995512e-02 1.65724501e-01
9.85341728e-01 6.60908639e-01 1.05810352e-01 -5.36007062e-02
4.30468053e-01 1.68406367e-01 6.04225636e-01 1.24412572e+00
-6.67148888e-01 5.55578709e-01 -1.02667041e-01 -3.69036257e-01
-1.08216572e+00 -1.50027347e+00 1.76459134e-01 1.22246969e+00
4.85960960e-01 2.04424977e-01 -3.34259510e-01 -9.89711583e-01
1.88142389e-01 1.00839627e+00 -9.07332122e-01 -3.87047946e-01
-5.89778125e-01 -2.75637925e-01 1.75895661e-01 1.02951300e+00
7.12712348e-01 -1.27560723e+00 -5.98413408e-01 -3.01106572e-02
5.77145591e-02 -1.18742251e+00 -6.23648226e-01 4.23522621e-01
-7.25452006e-01 -8.35971713e-01 -7.99344540e-01 -1.05778062e+00
9.17927802e-01 5.97914815e-01 9.49528694e-01 -2.21366659e-01
-8.59789178e-02 8.05420458e-01 -4.21216220e-01 -3.01365465e-01
-3.07323545e-01 -2.81873941e-01 3.70833099e-01 -3.83148372e-01
3.61092448e-01 -3.86644185e-01 -8.13392878e-01 3.26106071e-01
-5.64350784e-01 4.50541526e-02 7.47810960e-01 1.08877695e+00
8.30183983e-01 -6.72989786e-01 5.13868153e-01 -4.87641007e-01
4.93330419e-01 -5.41025698e-01 -8.23644578e-01 3.52730989e-01
-7.89027095e-01 3.49475801e-01 7.16163754e-01 -7.87519634e-01
-1.09458876e+00 1.66427195e-01 2.71229260e-02 -7.76055455e-01
-1.93022713e-01 2.16262296e-01 6.04367591e-02 -4.36476506e-02
7.36775935e-01 5.85505605e-01 1.18002482e-01 -1.80456936e-01
7.44441092e-01 2.97010094e-01 1.02042973e+00 -7.20193088e-01
9.28622782e-01 6.73942089e-01 -3.46340895e-01 -5.67139208e-01
-9.57845807e-01 -3.75264108e-01 -4.70314503e-01 -2.06474349e-01
9.45300817e-01 -1.27369511e+00 -4.26907688e-01 2.20675409e-01
-8.08487833e-01 -1.12370205e+00 -4.21689183e-01 7.47811496e-01
-9.30838287e-01 2.07562700e-01 -2.57821620e-01 -6.19046986e-01
-1.10168926e-01 -1.25724053e+00 8.08380425e-01 4.77355629e-01
1.14441566e-01 -9.35980320e-01 3.36435854e-01 1.50951222e-01
5.29654682e-01 -1.80490513e-03 3.85550678e-01 -6.84179425e-01
-6.82376504e-01 2.54390955e-01 -2.49182135e-01 3.98479313e-01
1.30618483e-01 -4.90482807e-01 -8.64191592e-01 -7.78519273e-01
-3.63856070e-02 -8.99743617e-01 1.29232645e+00 5.04073143e-01
1.15568364e+00 -1.18958965e-01 -2.36455470e-01 8.97613406e-01
1.17642641e+00 2.58567601e-01 3.96840602e-01 7.25360990e-01
6.66522443e-01 4.99506623e-01 6.89333200e-01 1.28360510e-01
6.39526904e-01 4.71131265e-01 6.89673126e-01 -6.61576027e-03
-1.95217818e-01 -5.94931364e-01 5.36521971e-01 3.88139486e-01
2.41969898e-01 -1.10753186e-01 -7.86608934e-01 7.20715642e-01
-2.07269788e+00 -9.23726141e-01 3.79812896e-01 2.17149782e+00
6.87815070e-01 2.22733364e-01 -2.24372726e-02 -7.70121455e-01
4.16224271e-01 1.67025402e-01 -1.34810185e+00 1.23159373e-02
-1.74774960e-01 -2.76267201e-01 4.87064868e-01 7.11662233e-01
-8.89233708e-01 1.24077308e+00 5.60333204e+00 1.84576660e-01
-1.08239913e+00 -5.07422024e-03 4.21352088e-01 -2.23882839e-01
-2.79681206e-01 -1.41867310e-01 -7.06304312e-01 1.22412562e-01
4.04299587e-01 2.88186967e-02 6.06785715e-01 1.14223921e+00
1.55670032e-01 2.31892783e-02 -1.37230229e+00 9.12252665e-01
1.63014054e-01 -1.10531712e+00 1.45459235e-01 -1.16911799e-01
9.75580633e-01 7.84433424e-01 5.50240934e-01 8.56500566e-01
7.81398714e-01 -9.34760094e-01 7.70844996e-01 5.79335392e-01
5.05738735e-01 -2.71027356e-01 2.76579380e-01 3.02947670e-01
-9.87146199e-01 -3.14295322e-01 -4.92123574e-01 8.98089707e-02
9.54661146e-02 -2.94844747e-01 -6.75490439e-01 2.02144980e-01
7.87584722e-01 8.87204945e-01 -6.34522915e-01 1.02979064e+00
-5.19222200e-01 2.12472782e-01 -1.83152258e-02 -8.32337439e-02
7.69290566e-01 -3.73984575e-01 6.92613959e-01 9.34786797e-01
3.01814854e-01 -8.42176676e-02 4.78816330e-01 1.03454638e+00
-6.20515039e-03 -2.77761728e-01 -7.90732622e-01 3.66733849e-01
4.55141038e-01 8.59937429e-01 -3.37760508e-01 -2.93662161e-01
-6.21594846e-01 1.22295928e+00 8.01994264e-01 9.22856569e-01
-7.92596161e-01 4.41098288e-02 6.88072324e-01 -3.92049134e-01
5.11090457e-01 -4.87013012e-01 -1.72855914e-01 -1.30811620e+00
1.20866284e-01 -7.62142241e-01 2.84105331e-01 -8.96215141e-01
-1.53336799e+00 6.77086115e-01 -2.24738941e-01 -1.26865697e+00
-3.80918294e-01 -7.17510998e-01 -6.89923048e-01 7.90017962e-01
-1.98549557e+00 -1.00635052e+00 -6.90186024e-01 6.93936706e-01
1.11392534e+00 -5.38460016e-01 4.73644853e-01 -2.00270355e-01
-5.54476321e-01 6.78428769e-01 3.54246318e-01 1.46002367e-01
8.38954926e-01 -1.45224988e+00 5.83179474e-01 9.14572656e-01
2.45219588e-01 6.31127238e-01 7.84069479e-01 -7.48651326e-01
-1.25293911e+00 -1.30982208e+00 3.78716849e-02 -6.77849472e-01
6.71926439e-01 -2.86006987e-01 -1.14529479e+00 1.10366786e+00
2.05151096e-01 4.05159235e-01 2.54703552e-01 -8.84082317e-02
-6.82095051e-01 -5.63062392e-02 -8.21900845e-01 1.02477372e+00
1.25860012e+00 -5.57501435e-01 -8.71648073e-01 2.77306914e-01
7.49282658e-01 -7.08296895e-01 -1.45874098e-01 4.06666905e-01
4.68144029e-01 -7.86743522e-01 1.00573623e+00 -9.61905539e-01
2.15843678e-01 -4.44288731e-01 -4.10446256e-01 -1.55648792e+00
-3.12367052e-01 -5.36461234e-01 -2.36030385e-01 6.20253563e-01
5.10600567e-01 -5.70135772e-01 8.45949829e-01 5.57316005e-01
-3.94374788e-01 -7.31892526e-01 -6.62786603e-01 -1.17929673e+00
2.31559530e-01 -4.36837703e-01 2.09514648e-01 6.50106311e-01
-3.13670188e-01 3.00892621e-01 -3.06676865e-01 4.26468074e-01
8.03530574e-01 5.47939800e-02 1.00813818e+00 -7.60488451e-01
-3.59838247e-01 -4.05768365e-01 -1.49405420e-01 -1.62904418e+00
4.74656373e-01 -9.55049992e-01 5.39705515e-01 -1.68704772e+00
2.34293640e-01 -3.73919845e-01 -4.31424677e-01 4.56281304e-01
-2.29747817e-01 -7.83674195e-02 1.05072096e-01 3.56037617e-01
-1.04714930e+00 1.18601120e+00 1.47075939e+00 -1.91593349e-01
-5.62063158e-01 -5.85600249e-02 -6.26919150e-01 7.20866919e-01
6.81509793e-01 -2.11826488e-01 -9.10654485e-01 -8.94967973e-01
-1.82349980e-01 -3.45653981e-01 6.49827838e-01 -1.06796288e+00
4.77759361e-01 -2.24307671e-01 6.10112309e-01 -5.84210873e-01
3.52047563e-01 -6.88906133e-01 -5.41501641e-01 5.57319462e-01
-6.90089464e-01 3.14268947e-01 3.77085060e-01 1.18467176e+00
1.23364218e-01 -9.45936050e-03 8.64297211e-01 -1.21416032e-01
-1.24576199e+00 5.46913505e-01 -1.14596985e-01 4.06563252e-01
1.04540622e+00 -2.59714544e-01 -4.71624345e-01 -5.31077266e-01
-7.63585627e-01 9.09695506e-01 6.19402587e-01 8.26738179e-01
9.50436354e-01 -1.40868342e+00 -6.51035488e-01 1.96384177e-01
4.14457321e-01 1.69433862e-01 2.94529676e-01 6.37947321e-01
-2.05321550e-01 3.16233665e-01 -3.76424313e-01 -8.70016277e-01
-7.08113670e-01 7.65767753e-01 5.88873327e-01 8.42776075e-02
-8.69571805e-01 1.01296711e+00 6.86217546e-01 -7.64146507e-01
6.85155809e-01 -4.02261615e-01 -6.59876168e-02 -5.05926013e-01
5.27235925e-01 8.72140229e-02 -4.16099399e-01 -4.75702047e-01
-2.49945953e-01 5.02428412e-01 -4.97266710e-01 -3.59010577e-01
1.21102476e+00 -3.98565888e-01 4.10211921e-01 5.14030457e-01
1.04315495e+00 -3.81440014e-01 -2.28311610e+00 -5.95826328e-01
-1.07130490e-01 -3.77631456e-01 -7.84809738e-02 -1.00344622e+00
-8.03739965e-01 7.47636259e-01 7.85186052e-01 -3.48137259e-01
8.28339934e-01 7.38362893e-02 5.49100518e-01 9.10505354e-01
2.07043111e-01 -1.16625559e+00 6.74470782e-01 7.83629715e-01
1.16023922e+00 -1.84406602e+00 -3.35580766e-01 2.69328564e-01
-1.05211079e+00 7.80005574e-01 1.35145259e+00 -2.67856926e-01
3.60123217e-01 -2.40047975e-03 3.33390236e-01 2.58880053e-02
-7.85645664e-01 -3.95800620e-01 3.83255273e-01 1.04019129e+00
-7.45435655e-02 -2.36944467e-01 4.38428909e-01 3.50051224e-01
-1.05145611e-02 -1.53419524e-01 3.30356330e-01 8.73748958e-01
-5.58244288e-01 -5.23438096e-01 -1.00528516e-01 1.48423493e-01
2.63125211e-01 2.08772924e-02 -1.93382874e-01 9.79700804e-01
-1.99389741e-01 8.16983879e-01 1.77340031e-01 -2.14808434e-01
4.78200763e-01 -2.21185610e-01 5.69215119e-01 -6.11018956e-01
-4.24779318e-02 -5.07062413e-02 -4.24940228e-01 -8.09609175e-01
-2.08111927e-01 -6.05956495e-01 -1.58043718e+00 1.55786246e-01
-2.41375994e-02 -4.01358828e-02 5.05674899e-01 9.12725866e-01
3.85544389e-01 6.93768620e-01 4.33066666e-01 -9.17741358e-01
-1.04342508e+00 -8.09160411e-01 -1.87028900e-01 4.74948734e-01
8.26255381e-01 -7.78128147e-01 -4.00103599e-01 -1.43854588e-01] | [4.426268577575684, 0.6249600052833557] |
15be64bb-be2f-4756-a1d2-a67309862415 | discovering-governing-equations-from-partial | 2201.05136 | null | https://arxiv.org/abs/2201.05136v1 | https://arxiv.org/pdf/2201.05136v1.pdf | Discovering Governing Equations from Partial Measurements with Deep Delay Autoencoders | A central challenge in data-driven model discovery is the presence of hidden, or latent, variables that are not directly measured but are dynamically important. Takens' theorem provides conditions for when it is possible to augment these partial measurements with time delayed information, resulting in an attractor that is diffeomorphic to that of the original full-state system. However, the coordinate transformation back to the original attractor is typically unknown, and learning the dynamics in the embedding space has remained an open challenge for decades. Here, we design a custom deep autoencoder network to learn a coordinate transformation from the delay embedded space into a new space where it is possible to represent the dynamics in a sparse, closed form. We demonstrate this approach on the Lorenz, R\"ossler, and Lotka-Volterra systems, learning dynamics from a single measurement variable. As a challenging example, we learn a Lorenz analogue from a single scalar variable extracted from a video of a chaotic waterwheel experiment. The resulting modeling framework combines deep learning to uncover effective coordinates and the sparse identification of nonlinear dynamics (SINDy) for interpretable modeling. Thus, we show that it is possible to simultaneously learn a closed-form model and the associated coordinate system for partially observed dynamics. | ['Steven L. Brunton', 'J. Nathan Kutz', 'Kathleen Champion', 'Joseph Bakarji'] | 2022-01-13 | null | null | null | null | ['model-discovery'] | ['miscellaneous'] | [-9.53439549e-02 5.51769994e-02 8.98897350e-02 -6.82862625e-02
-1.58101141e-01 -8.44804049e-01 8.16899300e-01 -2.23088205e-01
-1.15306512e-01 7.11852551e-01 -2.94453725e-02 -1.24226071e-01
-3.24533463e-01 -4.53051716e-01 -8.03936362e-01 -1.10512686e+00
-3.31623495e-01 6.00428283e-01 -4.95346487e-01 -2.66299337e-01
-1.76238224e-01 8.55658114e-01 -1.09754908e+00 -3.51255864e-01
2.10908473e-01 6.91078305e-01 6.90000728e-02 1.02035248e+00
3.38657051e-01 8.21250796e-01 -5.18501759e-01 4.18735385e-01
4.85775203e-01 -4.70350862e-01 -4.18143392e-01 -3.97253260e-02
1.27917469e-01 -3.48265737e-01 -9.57558990e-01 1.02947915e+00
5.04850596e-02 6.56560510e-02 7.56987929e-01 -1.08915198e+00
-6.96313381e-01 4.89662498e-01 4.84649800e-02 2.76043415e-01
-2.24562064e-02 5.56716993e-02 8.96089494e-01 -4.49275613e-01
7.50495195e-01 1.01903069e+00 5.75797498e-01 3.52023184e-01
-1.84074938e+00 -2.86395341e-01 -1.42380506e-01 1.13330297e-01
-1.29455006e+00 -4.22207892e-01 1.10267150e+00 -7.92538166e-01
6.80646658e-01 1.88236609e-01 9.61554527e-01 1.37904859e+00
6.72498167e-01 2.10103333e-01 1.03533304e+00 -4.81939852e-01
4.61224884e-01 2.24752635e-01 2.41878033e-01 6.48453712e-01
-1.21850688e-02 5.81983924e-01 -4.30633761e-02 -2.16581315e-01
8.41963828e-01 3.36677700e-01 -3.99172485e-01 -5.62802494e-01
-1.37887704e+00 1.05382526e+00 3.69885415e-01 5.34525990e-01
-4.76604819e-01 3.08939993e-01 -1.72389060e-01 8.50606859e-01
2.96064883e-01 1.01992834e+00 -4.06273872e-01 -1.27482355e-01
-6.50686383e-01 3.38143736e-01 1.15986013e+00 5.26949704e-01
1.02298951e+00 5.52963793e-01 5.60173213e-01 -2.06778079e-01
-4.37432304e-02 7.56400824e-01 6.66916013e-01 -1.18744648e+00
-1.74597859e-01 4.22759086e-01 3.23331296e-01 -1.08653522e+00
-5.24043858e-01 -6.52656794e-01 -1.17887163e+00 2.46347517e-01
3.58403623e-01 -5.27990520e-01 -5.54563999e-01 2.01565146e+00
1.03869200e-01 4.88342345e-01 2.98164755e-01 8.31090033e-01
5.96096963e-02 1.11667120e+00 -8.05969119e-01 -2.56911337e-01
8.68917823e-01 -2.54162103e-01 -9.95892763e-01 -2.45210389e-03
6.57445788e-01 -2.02406287e-01 7.22920537e-01 1.85456604e-01
-7.86440015e-01 -4.57501024e-01 -1.30350161e+00 4.51241210e-02
-5.03840923e-01 2.42737606e-02 2.63439387e-01 -1.06994644e-01
-1.13159108e+00 9.84687030e-01 -1.26651299e+00 -2.47663006e-01
-5.14212012e-01 4.42549407e-01 -6.40776396e-01 4.14003700e-01
-1.35911441e+00 1.04320014e+00 1.92193210e-01 1.89485669e-01
-1.10900450e+00 -6.74823105e-01 -7.96833634e-01 1.70834303e-01
5.49242273e-02 -5.88677466e-01 9.99322593e-01 -7.33479738e-01
-1.64475894e+00 1.64181635e-01 -1.62936762e-01 -6.44111097e-01
9.75077823e-02 1.72645077e-01 -5.30978382e-01 2.02878177e-01
-1.13084286e-01 1.71841711e-01 1.26687932e+00 -9.38271582e-01
5.72299361e-02 -2.43245065e-01 2.23410115e-01 -9.49488282e-02
-2.94612586e-01 -6.43576503e-01 5.04093707e-01 -3.86111408e-01
1.73306406e-01 -1.31611061e+00 -2.21744284e-01 -1.04007147e-01
-2.64729917e-01 3.55335593e-01 1.28347087e+00 -6.21559083e-01
1.00867009e+00 -2.03709674e+00 8.90709817e-01 2.20737442e-01
6.61415935e-01 -3.42334434e-02 -3.71940508e-02 7.52966106e-01
-5.18495083e-01 -5.05337305e-02 -2.37463057e-01 -2.73694366e-01
-1.27186328e-01 3.71413648e-01 -7.23744273e-01 8.17401528e-01
2.84560561e-01 8.19384038e-01 -7.58280516e-01 3.32736522e-01
2.87201136e-01 5.71990967e-01 -4.97577846e-01 3.22248667e-01
-1.88602824e-02 1.19924843e+00 -3.68209600e-01 -3.87472683e-03
1.41324684e-01 -3.53454083e-01 -8.08403715e-02 -1.59949049e-01
-3.92058313e-01 -1.59431905e-01 -1.17099333e+00 1.44333112e+00
-6.63363397e-01 1.17341244e+00 1.34111091e-01 -1.59860051e+00
9.88829792e-01 5.02317250e-01 8.44221354e-01 -3.85428071e-01
3.26673180e-01 6.58044219e-02 1.82472020e-01 -6.68805242e-01
1.25793695e-01 -2.79654950e-01 -1.40112340e-01 4.89111751e-01
2.95940965e-01 -2.35947743e-01 -2.65050203e-01 1.64865524e-01
1.34556651e+00 -3.58641177e-01 3.43641818e-01 -3.27330410e-01
4.50702369e-01 -8.41558278e-02 3.20764244e-01 4.87855047e-01
5.01869284e-02 1.62792265e-01 6.93826497e-01 -7.58689165e-01
-1.59791696e+00 -9.90569234e-01 -2.09882602e-01 3.56177427e-02
-1.57734811e-01 -3.04677427e-01 -6.38566196e-01 1.16465740e-01
2.48248223e-02 4.91170198e-01 -1.04177129e+00 -7.13208735e-01
-7.54357278e-01 -4.74632710e-01 3.08671623e-01 -1.03883026e-03
8.38414505e-02 -6.34024262e-01 -5.51020086e-01 4.10270989e-01
-8.42147171e-02 -1.11829793e+00 -2.13106707e-01 3.98016185e-01
-6.86208367e-01 -8.79843295e-01 -5.68419933e-01 -4.39223886e-01
5.99876702e-01 -2.94935673e-01 5.24015069e-01 -5.35221517e-01
-3.81605059e-01 5.63020468e-01 8.55415165e-02 -1.81970313e-01
-7.36476958e-01 -1.29730627e-01 7.13536918e-01 4.13274705e-01
-4.52786162e-02 -9.88750577e-01 -3.06222945e-01 7.76118424e-04
-9.50357556e-01 -5.47197685e-02 2.07778305e-01 1.13811183e+00
4.80440646e-01 6.30965978e-02 4.47326243e-01 -2.93581754e-01
4.82246488e-01 -7.53871858e-01 -1.00323820e+00 -1.34881213e-01
-4.80355352e-01 6.19202256e-01 1.11705911e+00 -8.56264472e-01
-3.57356787e-01 3.22060049e-01 2.39114478e-01 -8.88575315e-01
9.51824989e-03 6.66460872e-01 1.72067329e-01 -2.20405877e-01
6.62467480e-01 5.38421035e-01 5.14786780e-01 -5.91948986e-01
3.93766284e-01 4.42051560e-01 6.95039749e-01 -3.15493286e-01
1.02819824e+00 6.16927624e-01 4.15043682e-01 -1.23171210e+00
-5.23877323e-01 -1.76332757e-01 -9.65193331e-01 4.14878689e-03
6.73403919e-01 -8.93854797e-01 -9.05067921e-01 3.30763757e-01
-1.15333796e+00 -3.33913624e-01 -8.73040080e-01 7.61509717e-01
-7.51707792e-01 7.19172657e-02 -6.20870411e-01 -5.88225842e-01
1.38242826e-01 -1.07940960e+00 8.25254679e-01 -1.16155334e-01
-2.94938713e-01 -1.30043447e+00 7.90313244e-01 -5.94405413e-01
4.54331964e-01 5.89179218e-01 8.67247939e-01 -4.25606549e-01
-5.09072006e-01 -7.33549237e-01 4.97544110e-01 4.57135648e-01
5.66583537e-02 6.89627156e-02 -6.84067190e-01 -6.64854288e-01
8.25410068e-01 2.07296014e-01 5.30354619e-01 5.69659770e-01
5.75443447e-01 -7.14660525e-01 -1.06189966e-01 9.95828331e-01
1.26478517e+00 2.97460616e-01 -7.23286346e-02 -9.55788419e-02
6.67009115e-01 4.26255047e-01 -3.46585900e-01 3.02750289e-01
3.17982286e-01 6.21035933e-01 3.64737302e-01 9.37842727e-02
4.35010403e-01 -9.86317173e-02 6.91343069e-01 1.41833949e+00
4.08309288e-02 1.88806295e-01 -8.30179811e-01 3.39859128e-01
-1.74719179e+00 -1.10210657e+00 2.73052514e-01 1.95465100e+00
3.85156900e-01 -3.61189038e-01 -1.41218334e-01 2.62952864e-01
4.98056769e-01 8.14388096e-02 -9.73842442e-01 -2.09528238e-01
-2.01682687e-01 5.92365190e-02 2.09202468e-01 9.26067710e-01
-1.01669323e+00 4.25110340e-01 6.23177433e+00 -1.33679390e-01
-1.72853959e+00 7.26895407e-02 1.95823818e-01 3.15026976e-02
-1.15098342e-01 2.81669110e-01 -5.77676654e-01 4.06351447e-01
1.53167892e+00 -7.65183687e-01 8.52388144e-01 5.80688119e-01
3.26073468e-01 5.01090288e-01 -1.32301438e+00 9.95144427e-01
-1.50100768e-01 -1.37280202e+00 -1.24216869e-01 3.46617311e-01
7.05033183e-01 3.08614057e-02 2.46296942e-01 2.20164701e-01
1.67551354e-01 -8.01832378e-01 5.74278951e-01 9.97229159e-01
7.38547683e-01 -3.13573062e-01 4.80195612e-01 7.12097228e-01
-9.42234993e-01 -4.43472177e-01 -4.29767042e-01 -5.38950443e-01
1.10467114e-01 4.59021300e-01 -6.66376531e-01 5.83487712e-02
2.57843852e-01 1.26614749e+00 -1.92211106e-01 5.71247339e-01
1.79189846e-01 6.36608362e-01 -5.02549648e-01 4.78597321e-02
3.77512753e-01 -6.26334786e-01 1.14658558e+00 5.25069237e-01
7.86126554e-01 3.77602041e-01 2.59531178e-02 1.23269176e+00
1.68574333e-01 -5.30254304e-01 -1.13590419e+00 -3.91207606e-01
1.74008191e-01 1.10799873e+00 -4.08966810e-01 -2.56238371e-01
-1.67356655e-01 6.48974240e-01 2.02319846e-01 9.09838557e-01
-5.49816728e-01 -2.80732840e-01 8.46733272e-01 7.45153651e-02
2.09332317e-01 -5.47676444e-01 4.00231719e-01 -1.90417147e+00
-8.95596966e-02 -6.74066603e-01 -1.64481685e-01 -5.88064015e-01
-9.61152494e-01 7.97018647e-01 4.83942106e-02 -1.50187230e+00
-9.52398121e-01 -3.62177223e-01 -5.15000105e-01 9.56114113e-01
-9.71634388e-01 -6.76969647e-01 -3.90717909e-02 7.82395184e-01
-3.00527159e-02 -4.40987736e-01 1.18651736e+00 -1.20334245e-01
-5.73174953e-01 7.13701472e-02 8.73001873e-01 5.21431537e-03
1.70156658e-01 -1.50010419e+00 4.16781813e-01 7.11806834e-01
3.71954083e-01 6.75881863e-01 1.09022737e+00 -3.51815701e-01
-1.94505918e+00 -1.01150322e+00 3.12699765e-01 -6.14869475e-01
1.16911387e+00 -6.37283266e-01 -9.29975927e-01 1.16374028e+00
-1.48318380e-01 2.95612067e-01 2.07004324e-01 -3.88312548e-01
-1.55633138e-02 -2.23589212e-01 -7.95830309e-01 5.13467133e-01
2.58466870e-01 -8.63472879e-01 -6.44708455e-01 2.94753999e-01
8.06559563e-01 -2.87540108e-01 -8.28708768e-01 -9.04661939e-02
5.43115318e-01 -4.68962252e-01 9.12875593e-01 -8.23306739e-01
1.84237391e-01 -2.32782722e-01 -1.45656496e-01 -1.83737290e+00
-4.06974584e-01 -1.08110297e+00 -7.87320137e-01 4.85869288e-01
1.23148456e-01 -9.18356419e-01 5.41318893e-01 3.21887702e-01
1.22853756e-01 -5.99701285e-01 -1.04000020e+00 -8.12597036e-01
3.63760114e-01 3.27900462e-02 5.30067563e-01 1.21578002e+00
1.35790467e-01 3.65466118e-01 -5.96561253e-01 6.46951914e-01
7.06062794e-01 8.03207532e-02 6.97724462e-01 -1.36033809e+00
-5.07542312e-01 -1.44797102e-01 -8.10904980e-01 -1.03163695e+00
5.69740355e-01 -8.77382219e-01 -2.19431728e-01 -7.88390994e-01
-2.64412582e-01 -4.81962524e-02 -2.08577543e-01 -7.11683929e-02
4.86637592e-01 -2.66715795e-01 2.76923507e-01 4.49900717e-01
2.05914959e-01 7.23595381e-01 9.84390676e-01 -1.50209084e-01
-3.41024697e-01 7.87806138e-02 -2.53309429e-01 5.86190224e-01
5.53768516e-01 -4.48636711e-01 -3.47707003e-01 -3.27064037e-01
2.21513137e-01 7.00676858e-01 6.22726023e-01 -1.16383028e+00
5.14664471e-01 6.55808523e-02 2.52949417e-01 -3.25722486e-01
6.88983679e-01 -1.07290661e+00 5.11751950e-01 6.37325048e-01
-4.62479174e-01 4.32927161e-01 3.33560854e-02 8.13259423e-01
-3.69337738e-01 6.03453815e-02 6.45086706e-01 1.10454649e-01
-2.67608106e-01 4.60545778e-01 -5.42542815e-01 -2.52271533e-01
7.82582283e-01 1.53524622e-01 -9.13464278e-02 -8.84146273e-01
-1.31635153e+00 -7.77578913e-03 3.13363045e-01 1.72737405e-01
3.15174162e-01 -1.35317552e+00 -6.25108421e-01 7.35946774e-01
-1.73412547e-01 -3.14277261e-01 2.97880322e-01 7.66432762e-01
-4.52795386e-01 6.52108252e-01 -3.80224586e-01 -8.06818545e-01
-6.44838572e-01 6.47133231e-01 6.78851962e-01 -1.16372645e-01
-9.63916540e-01 5.17125539e-02 9.16803703e-02 -5.47676682e-01
-2.69263476e-01 -6.67490184e-01 -2.92564202e-02 -2.10298840e-02
5.27352512e-01 1.83997184e-01 -2.70078868e-01 -8.76023829e-01
1.33522242e-01 6.81864023e-01 3.38787317e-01 -3.49161148e-01
1.50383198e+00 -2.72695780e-01 -2.48796210e-01 1.07105577e+00
1.77789843e+00 -2.95402914e-01 -1.42442274e+00 -4.42156762e-01
-2.12635353e-01 6.46230653e-02 1.85989439e-01 -2.14419588e-01
-9.04471576e-01 1.05988562e+00 5.42530477e-01 7.37934411e-01
7.70754278e-01 -1.04669280e-01 4.95637387e-01 1.11882746e+00
1.05168171e-01 -4.65097070e-01 -1.51107818e-01 7.43187606e-01
1.03998971e+00 -1.00646091e+00 -3.43312353e-01 5.10039806e-01
5.39686270e-02 1.55152166e+00 -1.38166279e-01 -6.85810208e-01
1.25075006e+00 4.26644742e-01 -7.34214264e-04 -2.15113223e-01
-1.03348923e+00 3.97447050e-01 1.46033853e-01 3.78807396e-01
-1.70710698e-01 1.17759541e-01 4.87061888e-01 3.65761131e-01
-5.82437575e-01 -2.63687789e-01 1.18662262e+00 5.70653200e-01
-4.86591943e-02 -6.08008325e-01 -3.31561536e-01 3.51594657e-01
-1.64114580e-01 4.09199715e-01 -1.42540336e-01 9.85307336e-01
-3.63371968e-01 4.62272674e-01 3.32204700e-01 -3.84204417e-01
1.90306231e-01 1.74163908e-01 1.76376969e-01 -4.57110673e-01
1.90080807e-01 -3.05338893e-02 -5.72759628e-01 -4.80658829e-01
-1.71651885e-01 -7.27354050e-01 -8.40284944e-01 -3.88287932e-01
-1.18113488e-01 4.41732138e-01 7.42527425e-01 1.08438194e+00
3.19709510e-01 5.20828903e-01 9.74921167e-01 -1.14945269e+00
-9.52756763e-01 -7.88422704e-01 -9.09710526e-01 1.81836784e-01
1.48387349e+00 -5.85942507e-01 -1.01440561e+00 1.96657300e-01] | [6.531064510345459, 3.510784387588501] |
6bf33bf0-e0ef-4752-9160-0565ed8ee68a | bilingunet-image-segmentation-by-modulating | 2003.12739 | null | https://arxiv.org/abs/2003.12739v3 | https://arxiv.org/pdf/2003.12739v3.pdf | Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters | How to best integrate linguistic and perceptual processing in multi-modal tasks that involve language and vision is an important open problem. In this work, we argue that the common practice of using language in a top-down manner, to direct visual attention over high-level visual features, may not be optimal. We hypothesize that the use of language to also condition the bottom-up processing from pixels to high-level features can provide benefits to the overall performance. To support our claim, we propose a U-Net-based model and perform experiments on two language-vision dense-prediction tasks: referring expression segmentation and language-guided image colorization. We compare results where either one or both of the top-down and bottom-up visual branches are conditioned on language. Our experiments reveal that using language to control the filters for bottom-up visual processing in addition to top-down attention leads to better results on both tasks and achieves competitive performance. Our linguistic analysis suggests that bottom-up conditioning improves segmentation of objects especially when input text refers to low-level visual concepts. Code is available at https://github.com/ilkerkesen/bvpr. | ['Deniz Yuret', 'Aykut Erdem', 'Erkut Erdem', 'İlker Kesen', 'Ozan Arkan Can'] | 2020-03-28 | null | null | null | null | ['referring-expression-segmentation'] | ['computer-vision'] | [ 1.49679527e-01 -1.31874248e-01 7.29878172e-02 -5.05531549e-01
-5.47128856e-01 -5.19354284e-01 6.82363451e-01 3.76569510e-01
-7.47320712e-01 8.74746889e-02 3.48721534e-01 -5.23814261e-01
4.30786520e-01 -7.75359988e-01 -9.30302918e-01 -3.58129412e-01
4.51620907e-01 1.19750807e-02 4.59667265e-01 -2.72227079e-01
4.41245496e-01 5.80955207e-01 -1.66550624e+00 9.56646204e-01
6.68650329e-01 7.59143412e-01 5.04463077e-01 6.97055817e-01
-3.35779488e-01 8.33281457e-01 -1.60223901e-01 -3.34253758e-01
3.07413518e-01 -4.08885062e-01 -8.44090343e-01 6.94226250e-02
7.26873755e-01 -2.15222761e-01 1.30957648e-01 1.27002287e+00
3.38614255e-01 1.80268213e-01 5.70789814e-01 -9.38131154e-01
-1.01822650e+00 4.94041234e-01 -9.10264015e-01 4.22386527e-01
2.26523563e-01 4.51951891e-01 1.27368188e+00 -8.61545086e-01
5.58367729e-01 1.59757245e+00 2.74529785e-01 4.11439151e-01
-1.57771826e+00 -2.75095373e-01 6.29521370e-01 1.98009685e-01
-1.20627272e+00 -5.19186616e-01 7.40592360e-01 -7.52892256e-01
1.09697092e+00 5.34708947e-02 6.27612233e-01 6.76771879e-01
2.07977191e-01 9.07852292e-01 1.56904185e+00 -6.66923106e-01
-6.49932772e-02 3.58320892e-01 3.44053894e-01 8.76149595e-01
2.22429067e-01 1.27437532e-01 -6.31337464e-01 2.09322006e-01
7.00708628e-01 -9.44323391e-02 -2.87253171e-01 -1.29186884e-01
-1.01632583e+00 7.61413038e-01 8.22335660e-01 4.55423325e-01
-5.08485556e-01 3.29102695e-01 2.42022052e-01 1.18554793e-01
3.07056099e-01 5.38187504e-01 -4.57112491e-01 2.49497309e-01
-9.86718059e-01 -2.20673606e-01 2.38996178e-01 5.64210236e-01
1.09325099e+00 -1.51383072e-01 -5.08477867e-01 8.94201517e-01
6.02529466e-01 4.23947610e-02 2.98733503e-01 -1.07333302e+00
3.56198579e-01 6.21215045e-01 -3.60160358e-02 -7.65685916e-01
-5.89733183e-01 -1.10708609e-01 -2.70842254e-01 6.80399120e-01
9.40056622e-01 -2.45018244e-01 -1.09481549e+00 1.79078877e+00
-2.37755980e-02 -4.30464000e-01 -2.25820377e-01 1.16311944e+00
5.55668354e-01 7.28971660e-01 5.79524934e-01 5.51103279e-02
1.77920735e+00 -9.93054509e-01 -5.42731345e-01 -6.94278121e-01
5.32626033e-01 -8.83245826e-01 1.74463010e+00 2.40135774e-01
-1.24145246e+00 -7.35705733e-01 -8.08616102e-01 -6.66951597e-01
-4.75373924e-01 3.75218719e-01 7.06844270e-01 3.54050398e-01
-1.37471366e+00 3.67349267e-01 -8.46152723e-01 -7.15206623e-01
5.65796673e-01 1.33529991e-01 -1.85728788e-01 -6.63648173e-02
-1.01846027e+00 9.47699606e-01 2.23307580e-01 8.56036022e-02
-5.85584998e-01 -3.11963558e-01 -7.74216175e-01 2.20085219e-01
3.79441351e-01 -9.63799298e-01 1.01386285e+00 -1.42063999e+00
-1.14411318e+00 1.17401922e+00 -4.33537066e-01 -2.43889853e-01
3.54275823e-01 -2.47674972e-01 2.23943263e-01 3.55671704e-01
9.81146917e-02 1.27139461e+00 8.05638194e-01 -1.51096177e+00
-5.86505473e-01 -6.06810868e-01 2.25852221e-01 3.21591914e-01
-2.06712037e-01 2.08491564e-01 -7.32260466e-01 -4.64451045e-01
1.48531750e-01 -7.43224502e-01 -7.45206773e-02 2.32771382e-01
-2.54070699e-01 -2.79184699e-01 2.82186002e-01 -7.14704037e-01
8.97395253e-01 -2.00423479e+00 7.49593675e-02 -2.57348008e-02
-9.09814984e-03 -7.58886263e-02 -1.91173911e-01 2.01625064e-01
-3.39049064e-02 3.15734804e-01 -1.41947977e-02 -3.28766584e-01
-1.36836126e-01 -2.67063286e-02 -8.40293467e-02 3.63211423e-01
3.86382699e-01 1.04645801e+00 -6.41685963e-01 -4.78574067e-01
2.93235540e-01 4.76150781e-01 -8.26589942e-01 -2.09829643e-01
-3.97487193e-01 3.59865546e-01 -1.22302085e-01 5.88940620e-01
4.20121312e-01 -3.58897179e-01 1.01194084e-01 -4.83683944e-01
-3.11541885e-01 2.20206141e-01 -9.28394616e-01 1.62908053e+00
-5.37527740e-01 9.78219151e-01 3.31119508e-01 -7.60189235e-01
4.22774076e-01 -6.51516244e-02 -9.93747860e-02 -1.03832686e+00
2.95618057e-01 -1.67053029e-01 5.18354535e-01 -4.26458061e-01
3.44654888e-01 -3.34914058e-01 1.57174736e-01 2.87417114e-01
4.87092920e-02 -6.66607618e-02 3.00020307e-01 3.44303340e-01
4.93645400e-01 3.68590057e-01 2.27355182e-01 -3.62845004e-01
5.47536671e-01 2.52989717e-02 3.55757266e-01 7.70350039e-01
-4.10163820e-01 4.57481265e-01 7.57213175e-01 2.40069926e-02
-7.15747356e-01 -8.02747071e-01 4.81973812e-02 1.87166011e+00
-2.45206691e-02 -3.18186998e-01 -6.85017228e-01 -2.68511266e-01
-7.19270483e-02 9.80545819e-01 -6.11094713e-01 3.08306981e-02
-2.94649869e-01 -6.16388261e-01 1.55602917e-01 6.15342498e-01
2.67312557e-01 -1.22840619e+00 -8.52933466e-01 -1.74377277e-01
1.84824824e-01 -1.06255400e+00 -4.44005132e-01 4.19162273e-01
-7.33965755e-01 -7.80762553e-01 -7.92648137e-01 -7.57837355e-01
9.14190888e-01 2.66593844e-01 1.03323340e+00 1.82076320e-01
-1.40200213e-01 5.79673529e-01 -2.06834078e-01 -2.44514957e-01
-2.61996567e-01 -1.62435904e-01 -3.80376905e-01 8.02148432e-02
4.11709517e-01 -2.30652541e-01 -5.97503543e-01 -6.08096905e-02
-8.06761861e-01 3.86027008e-01 5.67544281e-01 6.44047379e-01
6.81455731e-01 -4.08457726e-01 6.71113282e-02 -8.53277445e-01
5.39383650e-01 8.40734094e-02 -7.55892456e-01 2.74648964e-01
-3.55887830e-01 2.26314574e-01 4.33765143e-01 -1.99834436e-01
-9.88288760e-01 3.72761071e-01 -1.81927726e-01 -4.05303448e-01
-3.57934922e-01 3.72155130e-01 -1.90274552e-01 -1.61043946e-02
6.51472330e-01 1.55625179e-01 -8.07142779e-02 -2.53786385e-01
7.23561585e-01 2.57817239e-01 1.47628352e-01 -7.24019468e-01
2.96326190e-01 7.42549777e-01 -2.42733151e-01 -9.94631350e-01
-1.01359439e+00 -3.14544737e-01 -8.38936567e-01 -2.42576674e-01
1.48186696e+00 -1.01871312e+00 -7.48136342e-01 1.92410350e-01
-1.36862648e+00 -7.53584802e-01 -8.69126171e-02 2.81310201e-01
-5.95085740e-01 9.51694772e-02 -5.89433491e-01 -6.81127489e-01
-1.86272889e-01 -1.51736939e+00 9.20181453e-01 2.72721231e-01
-1.19210273e-01 -8.76152754e-01 -4.16264385e-01 5.22891283e-01
2.69399554e-01 -2.18395069e-01 1.00056732e+00 -4.60258216e-01
-5.98409832e-01 3.05789620e-01 -7.08573818e-01 2.39292949e-01
-2.10138023e-01 2.38801524e-01 -1.31931889e+00 1.53459907e-02
-2.36483067e-01 -4.23784286e-01 1.39788020e+00 6.75566196e-01
1.17538095e+00 3.30911614e-02 -2.35803291e-01 6.23203278e-01
1.58226585e+00 -3.22161056e-02 4.58168805e-01 2.77610064e-01
8.32692683e-01 9.30731177e-01 4.20939505e-01 1.56136528e-01
5.93689620e-01 6.15958631e-01 2.49613389e-01 -3.83758277e-01
-4.54760343e-01 -1.09372817e-01 4.72053945e-01 2.05779582e-01
2.02017143e-01 1.00713484e-01 -1.18144643e+00 6.50483847e-01
-1.66706979e+00 -8.78612995e-01 -2.57080615e-01 2.00050163e+00
9.52756584e-01 2.90180594e-01 1.33712962e-01 -3.60581249e-01
6.90629482e-01 1.68190785e-02 -3.81477475e-01 -7.10964978e-01
-1.06534809e-01 -1.11682303e-01 3.98602903e-01 8.02693486e-01
-9.57386494e-01 1.35661769e+00 5.73580742e+00 5.70716619e-01
-1.48272216e+00 2.87710458e-01 9.38811481e-01 -2.71055788e-01
-2.53844529e-01 9.99546200e-02 -8.16675901e-01 1.63043350e-01
6.34244382e-01 1.85768515e-01 4.70255435e-01 5.18537641e-01
4.46229577e-01 -5.55273533e-01 -1.14265990e+00 8.20396423e-01
9.97848511e-02 -1.21557641e+00 2.26953179e-01 -4.59556393e-02
4.72389519e-01 2.85118997e-01 9.66385677e-02 1.12281479e-01
2.29986295e-01 -8.92982006e-01 1.03768432e+00 5.08501887e-01
4.35806215e-01 -4.02949184e-01 1.98988378e-01 2.90517032e-01
-1.06733167e+00 -7.39178387e-04 -2.63499439e-01 -1.87891468e-01
2.33705685e-01 2.60687232e-01 -4.73182291e-01 -1.36483312e-01
7.79635847e-01 4.67417568e-01 -8.26621950e-01 7.78638184e-01
-5.16028583e-01 5.39748430e-01 -1.24454431e-01 1.37480155e-01
3.55575114e-01 -1.55648470e-01 2.21823573e-01 1.47971892e+00
-2.07441032e-01 8.93339738e-02 2.21277922e-01 1.14722073e+00
1.07201286e-01 3.86686802e-01 -4.89384025e-01 -1.49892092e-01
1.26204684e-01 1.34709787e+00 -1.07271302e+00 -3.83944213e-01
-7.94143796e-01 1.04438090e+00 5.86938143e-01 6.12308562e-01
-6.30731225e-01 -1.72907457e-01 4.28972483e-01 3.72233570e-01
3.21434855e-01 -3.59930843e-01 -7.59064376e-01 -1.04739022e+00
-2.88885951e-01 -6.12633228e-01 3.44293475e-01 -1.12892234e+00
-1.07364690e+00 4.50539738e-01 -3.00045937e-01 -6.28568769e-01
2.13509023e-01 -1.02452183e+00 -4.74742532e-01 1.26456499e+00
-1.66051245e+00 -1.23461211e+00 -9.90519598e-02 7.47616470e-01
5.45943439e-01 2.58365899e-01 4.63812411e-01 1.54397801e-01
-5.14218986e-01 2.71913618e-01 -4.88226175e-01 2.52173752e-01
7.35715747e-01 -1.25125444e+00 -4.47450653e-02 1.10306382e+00
5.20569146e-01 9.13633764e-01 6.93965197e-01 -4.69527096e-01
-1.22750914e+00 -7.20902264e-01 6.54257834e-01 -4.39343035e-01
7.67591596e-01 -4.28631663e-01 -9.58444655e-01 7.01179802e-01
6.12805188e-01 2.31740512e-02 6.39389813e-01 1.90592512e-01
-4.38719094e-01 3.11053416e-04 -8.65860999e-01 7.09660888e-01
5.43352544e-01 -7.62236655e-01 -7.28141785e-01 1.79526031e-01
4.53010023e-01 -3.14301662e-02 -5.42390764e-01 -1.01141416e-01
3.71181428e-01 -9.98633742e-01 8.86010885e-01 -5.75689256e-01
5.66458941e-01 -4.35122162e-01 -2.96671987e-01 -1.08885920e+00
-4.20151502e-01 -4.05799132e-03 3.49728853e-01 1.18869042e+00
6.57155335e-01 -4.28522021e-01 3.11796725e-01 5.23171067e-01
5.22403652e-03 -5.90598941e-01 -5.15387893e-01 -3.14367652e-01
3.02212834e-01 -6.24824464e-01 -3.39430243e-01 7.65566409e-01
-1.43819779e-01 8.21808934e-01 8.13523978e-02 1.55695960e-01
2.61448115e-01 2.19896957e-01 4.72280651e-01 -1.00884342e+00
-3.60331118e-01 -8.81400466e-01 6.87132939e-04 -1.07668519e+00
3.11349332e-01 -1.08752954e+00 7.37274960e-02 -2.14035130e+00
1.40699610e-01 -4.13401313e-02 -3.07565451e-01 8.53270769e-01
-3.20173711e-01 2.98207432e-01 6.87051535e-01 5.44633716e-02
-4.37598914e-01 2.10246384e-01 1.50325334e+00 -4.67947461e-02
-2.52146512e-01 -3.40564966e-01 -1.04253399e+00 9.19295728e-01
7.14317918e-01 -4.85874116e-02 -2.47530952e-01 -8.10436189e-01
2.76077807e-01 -1.27626091e-01 4.49391782e-01 -7.13251412e-01
2.10711807e-01 -2.26629838e-01 5.27520120e-01 -4.02286321e-01
4.83467311e-01 -6.88830495e-01 -7.69483507e-01 5.38689613e-01
-5.30161977e-01 9.51688737e-03 6.59301221e-01 3.12186748e-01
-1.57301113e-01 -8.76457244e-02 1.22056377e+00 -5.79674661e-01
-1.04922915e+00 -1.47165909e-01 -5.09024382e-01 -1.39242345e-02
8.68703246e-01 -2.22814664e-01 -4.13403928e-01 -2.10541978e-01
-1.02574360e+00 2.99219877e-01 6.00994945e-01 3.64809513e-01
5.23615479e-01 -8.39240789e-01 -5.88434279e-01 6.03833161e-02
7.78881982e-02 -5.26975334e-01 1.91512704e-01 1.12569714e+00
-5.37998438e-01 5.26110649e-01 -3.57731462e-01 -6.99043691e-01
-1.31159174e+00 8.12764823e-01 5.02022028e-01 1.44037843e-01
-4.42053109e-01 1.35724068e+00 6.31040215e-01 -3.01064998e-02
9.95655879e-02 -5.64651608e-01 -2.67739922e-01 5.27230263e-01
3.99129927e-01 -2.00996436e-02 -1.97008163e-01 -8.03506553e-01
-5.16219676e-01 6.85144484e-01 -8.55717137e-02 -4.42595273e-01
1.01436663e+00 -3.95266443e-01 -3.71331841e-01 7.91551828e-01
8.62152874e-01 2.04868630e-01 -1.33082759e+00 -1.97124388e-03
-3.51713374e-02 -3.51101696e-01 3.64061773e-01 -1.09273362e+00
-1.15979290e+00 1.48205543e+00 5.95823884e-01 1.16131417e-01
1.21882164e+00 2.24367067e-01 1.29852638e-01 1.60642385e-01
6.55209497e-02 -1.13639510e+00 1.29113376e-01 4.77289289e-01
9.22318697e-01 -1.53529823e+00 -3.47079672e-02 -2.37342730e-01
-9.69793975e-01 8.68071556e-01 1.03380919e+00 -1.86105922e-01
4.55926865e-01 1.11981668e-01 2.61140227e-01 -1.18118353e-01
-9.82426286e-01 -9.10951197e-01 5.57788670e-01 3.32518160e-01
1.09984457e+00 -4.34615798e-02 -2.37874791e-01 3.78798664e-01
1.48099512e-01 -2.91287184e-01 4.61040765e-01 6.46800041e-01
-7.67334521e-01 -9.30906773e-01 -6.63846552e-01 5.26346922e-01
-4.51135904e-01 -5.19673765e-01 -5.33343375e-01 6.80267870e-01
3.33368093e-01 8.19617927e-01 3.87532532e-01 1.48932308e-01
1.74122736e-01 3.81090552e-01 5.94201148e-01 -9.11675155e-01
-6.85706675e-01 5.24179637e-01 -7.40773454e-02 -5.79025328e-01
-4.19277072e-01 -7.73328364e-01 -1.55838633e+00 1.54138803e-01
3.52577679e-02 -3.93111706e-01 4.88941461e-01 7.06587017e-01
3.43142569e-01 6.69550300e-01 -1.37824640e-01 -7.78880358e-01
-6.06528670e-02 -8.24203372e-01 -3.69374305e-01 4.39406335e-01
2.92474657e-01 -5.53559721e-01 -1.41698048e-01 2.74291784e-01] | [10.4484224319458, 1.5655351877212524] |
788121cb-3abc-4420-a659-25fd42ff41c6 | demfi-deep-joint-deblurring-and-multi-frame | 2111.09985 | null | https://arxiv.org/abs/2111.09985v1 | https://arxiv.org/pdf/2111.09985v1.pdf | DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting | In this paper, we propose a novel joint deblurring and multi-frame interpolation (DeMFI) framework, called DeMFI-Net, which accurately converts blurry videos of lower-frame-rate to sharp videos at higher-frame-rate based on flow-guided attentive-correlation-based feature bolstering (FAC-FB) module and recursive boosting (RB), in terms of multi-frame interpolation (MFI). The DeMFI-Net jointly performs deblurring and MFI where its baseline version performs feature-flow-based warping with FAC-FB module to obtain a sharp-interpolated frame as well to deblur two center-input frames. Moreover, its extended version further improves the joint task performance based on pixel-flow-based warping with GRU-based RB. Our FAC-FB module effectively gathers the distributed blurry pixel information over blurry input frames in feature-domain to improve the overall joint performances, which is computationally efficient since its attentive correlation is only focused pointwise. As a result, our DeMFI-Net achieves state-of-the-art (SOTA) performances for diverse datasets with significant margins compared to the recent SOTA methods, for both deblurring and MFI. All source codes including pretrained DeMFI-Net are publicly available at https://github.com/JihyongOh/DeMFI. | ['Munchurl Kim', 'Jihyong Oh'] | 2021-11-19 | null | null | null | null | ['video-enhancement', 'video-restoration'] | ['computer-vision', 'computer-vision'] | [ 2.88141407e-02 -6.32878542e-01 -6.32689893e-02 -2.10224767e-04
-8.60397279e-01 -2.15547502e-01 5.44575572e-01 -7.02349126e-01
-2.28446513e-01 8.25823069e-01 6.21894002e-01 -1.88915715e-01
3.63625400e-02 -5.68898201e-01 -7.63350904e-01 -7.85565078e-01
6.57392293e-03 -3.98633778e-01 2.40581676e-01 -1.26737803e-01
1.44622311e-01 2.31519699e-01 -1.15173304e+00 3.34998071e-01
1.30679083e+00 9.23216224e-01 3.93926531e-01 9.64728117e-01
5.67108393e-01 1.12084925e+00 -1.82658851e-01 -9.59915817e-02
3.25480163e-01 -5.27358651e-01 -6.49670362e-01 -1.20390728e-01
8.26474369e-01 -1.16277039e+00 -8.91407013e-01 1.02325797e+00
4.50081795e-01 4.12000209e-01 4.22665656e-01 -8.54622364e-01
-1.06785417e+00 1.08255222e-01 -9.72122669e-01 5.87604582e-01
2.00610191e-01 4.88593131e-01 6.32538676e-01 -1.24034524e+00
4.38841999e-01 1.37861657e+00 6.95467353e-01 3.89334708e-01
-1.18140960e+00 -8.18003356e-01 -1.58396989e-01 6.61725700e-01
-1.30044353e+00 -4.79393810e-01 7.54831374e-01 -2.44937912e-01
5.63107908e-01 3.53163868e-01 4.50332582e-01 8.80697727e-01
3.47427517e-01 7.88923562e-01 1.10071909e+00 -1.81279451e-01
-3.64896618e-02 -7.64367998e-01 1.67816449e-02 5.21261036e-01
1.43458694e-01 5.63333988e-01 -4.88619715e-01 1.54630542e-01
1.33943641e+00 1.96117982e-01 -9.68203902e-01 3.13367814e-01
-1.43591785e+00 4.40517187e-01 7.18913734e-01 2.99665183e-01
-4.03572828e-01 4.06527638e-01 2.39641100e-01 1.96551368e-01
8.10826004e-01 1.98265851e-01 -2.34351382e-01 -9.05798823e-02
-1.34783721e+00 2.95488000e-01 2.25785494e-01 7.23059833e-01
9.06743586e-01 6.81307763e-02 -6.30047679e-01 1.06596375e+00
1.47430107e-01 5.16141593e-01 5.13181329e-01 -1.41475391e+00
4.42328393e-01 -1.39359385e-01 3.23179334e-01 -9.88875985e-01
-5.02781421e-02 -5.66363096e-01 -1.27112937e+00 7.06227049e-02
3.04592490e-01 -2.35661894e-01 -9.00760174e-01 1.51890707e+00
2.84050852e-01 9.27981615e-01 -1.53465688e-01 1.54731190e+00
6.11872494e-01 9.90986288e-01 -9.78554189e-02 -3.81338060e-01
1.31678307e+00 -1.39872909e+00 -8.05227637e-01 -2.49323606e-01
2.86506683e-01 -8.65123749e-01 8.24670434e-01 4.08394903e-01
-1.11773312e+00 -9.58617449e-01 -9.31072891e-01 -4.61969882e-01
4.05171722e-01 1.80715233e-01 3.02856714e-01 1.74394771e-01
-1.28727472e+00 6.68072522e-01 -8.62401307e-01 1.46185830e-01
6.90952659e-01 -8.48895982e-02 -1.95065916e-01 -6.45304084e-01
-1.34389162e+00 7.22111821e-01 1.59925316e-02 2.73474306e-01
-1.16529679e+00 -1.15488911e+00 -9.39202845e-01 5.34242019e-03
-7.42724398e-03 -1.01870847e+00 9.72250223e-01 -9.39862669e-01
-1.48832989e+00 2.83375829e-01 -4.88921970e-01 -4.31062341e-01
7.31372774e-01 -6.86338782e-01 -3.57782215e-01 3.57503533e-01
-3.00312811e-03 8.09261501e-01 1.33433926e+00 -1.15069222e+00
-5.88935852e-01 3.04082539e-02 -1.99174225e-01 1.69105396e-01
-1.30550593e-01 3.78537774e-02 -4.93558198e-01 -1.31861961e+00
-2.28068322e-01 -6.33907259e-01 5.65264523e-02 9.57471579e-02
-2.39243120e-01 1.94187418e-01 1.08823121e+00 -1.23120201e+00
1.66562390e+00 -2.22620344e+00 2.78587967e-01 -6.42099619e-01
5.27093649e-01 6.63453639e-01 -4.39168870e-01 8.99701789e-02
-2.78803378e-01 -1.60524696e-01 -4.00087953e-01 -4.27368373e-01
-5.50012112e-01 -8.83888453e-02 -4.29780632e-01 7.72461593e-01
1.66815519e-01 1.11927092e+00 -1.22468102e+00 -2.83721536e-01
7.25924015e-01 8.55354369e-01 -6.64399326e-01 3.96475881e-01
1.93525240e-01 7.02278972e-01 -1.49384484e-01 4.52829003e-01
1.25918174e+00 -1.86006024e-01 -3.64268541e-01 -6.51861131e-01
-3.83062482e-01 -2.05678597e-01 -7.22525954e-01 1.83832979e+00
-6.68325245e-01 9.88499582e-01 6.70670494e-02 -5.58205426e-01
5.71106374e-01 1.38366431e-01 4.70383525e-01 -4.30905700e-01
3.07017807e-02 3.51405323e-01 -2.64394492e-01 -4.73063082e-01
5.88491023e-01 5.72791435e-02 4.28663492e-01 7.91399926e-02
-4.35853787e-02 6.23142831e-02 4.47165072e-02 1.89875841e-01
1.07721984e+00 4.36745822e-01 3.88160683e-02 -3.34363669e-01
9.03715789e-01 -4.30085510e-01 5.79013884e-01 5.34522474e-01
-4.73765343e-01 1.17466736e+00 -1.49613887e-01 -3.21844339e-01
-1.13806677e+00 -1.04365575e+00 -1.75487369e-01 7.70146430e-01
6.58962011e-01 -1.26046866e-01 -8.51149619e-01 -4.77434427e-01
-1.43078461e-01 7.50534177e-01 -4.93283004e-01 -2.04734147e-01
-8.35520744e-01 -6.48198485e-01 1.97497606e-01 2.04073325e-01
1.12098956e+00 -5.23087144e-01 -2.51198471e-01 2.87736028e-01
-6.51485980e-01 -9.74126101e-01 -1.30501473e+00 -5.64807177e-01
-8.32828462e-01 -8.34504902e-01 -1.50942051e+00 -5.64019203e-01
5.81853330e-01 9.53429997e-01 7.79494882e-01 -2.65568774e-02
-1.76691964e-01 -6.97918385e-02 -5.35683513e-01 4.44271564e-01
-3.21920305e-01 -3.88740629e-01 -3.21789294e-01 2.72700280e-01
-1.44192666e-01 -6.98228896e-01 -1.42790246e+00 6.06210232e-01
-1.13016629e+00 5.01740932e-01 4.99662846e-01 1.22287035e+00
1.59834728e-01 -2.30566218e-01 4.66485977e-01 -2.21628189e-01
5.16318262e-01 -5.30812800e-01 -3.39081109e-01 7.80007541e-02
-4.68203604e-01 -1.65350750e-01 6.35485470e-01 -4.45787340e-01
-1.36915684e+00 -5.50884128e-01 -4.25459594e-02 -1.00492406e+00
-2.74269376e-02 9.20997411e-02 1.68471724e-01 -2.14339748e-01
6.28924191e-01 4.90636319e-01 1.17674069e-02 -4.45009500e-01
3.96433681e-01 6.96843922e-01 8.70018363e-01 -2.88912356e-01
6.89841092e-01 4.77451473e-01 -6.38823286e-02 -5.68300009e-01
-9.26817834e-01 -4.16471422e-01 -3.01485926e-01 -5.24607182e-01
7.74919629e-01 -1.35878897e+00 -4.18625355e-01 1.21013486e+00
-1.32611048e+00 -5.76008141e-01 8.51117969e-02 6.69443727e-01
-4.12513822e-01 8.79492044e-01 -1.06901217e+00 -3.66284102e-01
-7.01223195e-01 -1.23759282e+00 9.69775617e-01 3.50032151e-01
1.84280440e-01 -8.71460378e-01 -5.20269526e-03 5.79889834e-01
8.46872509e-01 4.63397279e-02 2.46617079e-01 2.98266023e-01
-8.33967328e-01 2.11313084e-01 -8.20299506e-01 6.85460806e-01
4.64432746e-01 -3.34722221e-01 -9.33211505e-01 -6.63284779e-01
-3.35636660e-02 -5.12952656e-02 1.25768101e+00 8.91503334e-01
1.17964733e+00 -3.39843243e-01 3.97585519e-03 1.08786583e+00
1.42803419e+00 4.12472524e-02 9.61331010e-01 3.45102161e-01
9.02651012e-01 1.70592160e-04 6.47158980e-01 4.01826501e-01
4.16384637e-01 8.70912492e-01 3.66199106e-01 -3.58160436e-01
-1.02919519e+00 -2.59232149e-02 5.67850590e-01 6.67433858e-01
-3.25224400e-01 -3.18580180e-01 -4.53959584e-01 6.30960405e-01
-1.97321618e+00 -1.05719960e+00 -2.17865959e-01 2.13702989e+00
1.13383400e+00 -4.96359766e-01 -1.14591785e-01 -2.16318816e-01
1.02431548e+00 5.55561483e-01 -7.20175266e-01 2.22248241e-01
-1.89697728e-01 9.38573852e-02 5.76161921e-01 1.04952133e+00
-1.20798159e+00 7.11621463e-01 4.47369385e+00 1.31470907e+00
-1.05153549e+00 6.09370530e-01 1.09500360e+00 -8.66918340e-02
-1.14748865e-01 -1.03642732e-01 -3.75120193e-01 8.93672824e-01
7.86730886e-01 -4.20911759e-02 9.13447559e-01 3.64918590e-01
8.17381799e-01 -3.11329037e-01 -5.80936551e-01 1.15221417e+00
-5.80662265e-02 -1.50808227e+00 -6.02323376e-02 -1.80115372e-01
9.96362686e-01 1.35932013e-01 9.87541899e-02 3.92119121e-03
2.25401133e-01 -7.57743418e-01 7.74583161e-01 6.45498216e-01
1.30787587e+00 -6.11196876e-01 6.53679967e-01 -5.52706197e-02
-1.13454914e+00 -8.21209103e-02 -9.73994806e-02 8.11133683e-02
4.57122087e-01 1.18146789e+00 5.54925017e-03 1.01027453e+00
6.67039692e-01 1.20316994e+00 -1.34046033e-01 1.19474947e+00
-2.87769526e-01 7.22176611e-01 6.02408797e-02 6.75228834e-01
1.43650725e-01 -3.26069027e-01 7.92221427e-01 1.32126546e+00
5.62778175e-01 2.67569691e-01 -2.38600567e-01 8.12838018e-01
-2.01099515e-02 -5.00685990e-01 1.72700152e-01 6.39524639e-01
5.46215713e-01 1.29628050e+00 -1.22297764e-01 -5.26147544e-01
-3.91066641e-01 1.33906209e+00 -2.86164298e-03 6.09592140e-01
-1.03646946e+00 -5.31145513e-01 1.08104110e+00 6.46447167e-02
4.26072806e-01 -1.93452820e-01 -8.62578601e-02 -1.68651307e+00
-1.19889140e-01 -7.14300394e-01 2.21580118e-01 -1.18219149e+00
-1.22482681e+00 5.83817303e-01 -1.25921145e-01 -1.47915244e+00
7.73926973e-02 -1.75247014e-01 -5.96380889e-01 1.20045280e+00
-2.05331445e+00 -1.20789802e+00 -7.84660876e-01 6.17605567e-01
9.88861501e-01 3.35050911e-01 -2.55833417e-02 6.32521272e-01
-7.86830664e-01 5.08337915e-01 3.31463337e-01 2.79650055e-02
1.20673358e+00 -7.56441176e-01 4.22849625e-01 1.39502072e+00
-5.74014187e-01 4.17259127e-01 6.60439670e-01 -8.07078063e-01
-1.27996266e+00 -1.67622721e+00 4.17845279e-01 8.33100751e-02
5.59955120e-01 2.46452689e-01 -1.08417523e+00 2.94501334e-01
4.66258436e-01 5.48996508e-01 -7.89912492e-02 -7.08718896e-01
-2.77910620e-01 -3.21909189e-01 -1.06157005e+00 3.77653003e-01
1.02276003e+00 -3.74231607e-01 -2.82816589e-01 6.58170581e-02
8.98158252e-01 -6.11864209e-01 -8.36252391e-01 4.40402031e-01
4.77531046e-01 -1.27241051e+00 1.28048110e+00 8.06197152e-02
1.09297597e+00 -7.17677176e-01 1.12248495e-01 -1.55564034e+00
-8.04979801e-01 -1.06419528e+00 -6.00283861e-01 1.03248847e+00
-2.05294818e-01 -7.86287069e-01 1.88384205e-01 2.17364669e-01
-4.11118895e-01 -7.03866601e-01 -9.19159234e-01 -7.79937327e-01
-5.86973839e-02 -2.16099441e-01 3.85576576e-01 8.91959012e-01
-3.65369111e-01 -1.01281017e-01 -9.08246338e-01 1.70828581e-01
9.51444566e-01 2.46091038e-02 4.48912531e-01 -4.23664242e-01
-3.37942243e-01 -3.39897335e-01 -1.00336693e-01 -1.69440281e+00
-1.77914992e-01 -5.84401131e-01 5.77526428e-02 -1.30210304e+00
3.12204301e-01 -1.20322920e-01 -2.03958094e-01 1.34844199e-01
-8.00417840e-01 4.74326491e-01 2.79839844e-01 6.64355993e-01
-2.92097479e-01 6.70009911e-01 1.77211559e+00 2.39663366e-02
-1.56400681e-01 -3.71975183e-01 -4.58245605e-01 2.80713022e-01
5.39397061e-01 -1.19364455e-01 -1.85561880e-01 -7.89709866e-01
-4.85859901e-01 3.32547486e-01 7.75684059e-01 -1.03659737e+00
2.17817366e-01 -1.97575018e-01 6.15065038e-01 -3.32357526e-01
2.30399385e-01 -3.09104264e-01 2.82887846e-01 5.14987528e-01
-2.55641490e-01 -3.07494700e-01 1.13466308e-01 6.21441007e-01
-3.39190304e-01 1.27427295e-01 1.17551112e+00 1.79833293e-01
-7.08554745e-01 5.00949383e-01 -1.74653262e-01 2.24027373e-02
8.76386106e-01 -1.25491291e-01 -8.30922484e-01 -4.80897605e-01
-2.79329747e-01 9.61739123e-02 5.86186230e-01 2.14979440e-01
7.00226843e-01 -1.29696226e+00 -1.05335736e+00 1.38118282e-01
-4.28378999e-01 1.07391439e-01 9.48890686e-01 1.33922076e+00
-7.04121470e-01 2.23670617e-01 -2.45912760e-01 -4.38511968e-01
-1.00158811e+00 5.08124590e-01 2.78108358e-01 -2.07310736e-01
-6.90085173e-01 1.01237094e+00 6.17726088e-01 3.67267668e-01
-2.77949005e-01 -3.37949693e-01 2.02627420e-01 -3.31543684e-01
9.16647017e-01 8.14298332e-01 -1.67150632e-01 -6.07358932e-01
-9.23372507e-02 5.27161479e-01 -1.00093804e-01 6.08392283e-02
1.22968400e+00 -6.00604057e-01 -2.16496438e-01 -2.85194784e-01
1.32348049e+00 -1.13468572e-01 -2.07290030e+00 -2.81280458e-01
-7.26925790e-01 -1.11158800e+00 7.70379722e-01 -7.85868287e-01
-1.38102043e+00 7.41059363e-01 6.54724956e-01 -4.08400655e-01
1.72592986e+00 -2.53136516e-01 1.34387922e+00 -4.94114578e-01
1.80980772e-01 -4.45947945e-01 1.34583116e-01 3.74675959e-01
1.05944538e+00 -1.02903211e+00 2.21560538e-01 -4.92466331e-01
-3.71529490e-01 1.24667299e+00 4.80697840e-01 -2.91185528e-01
4.08902317e-01 5.62587194e-02 -2.23839298e-01 4.73449856e-01
-6.02586031e-01 3.46024595e-02 4.34742808e-01 3.86161834e-01
2.67856598e-01 -1.52180463e-01 -3.97052497e-01 3.49441528e-01
3.90556931e-01 5.47998965e-01 5.34983277e-01 4.80189770e-01
-4.03481901e-01 -6.31877065e-01 -5.71084440e-01 3.21403384e-01
-2.38755941e-01 -5.05099893e-01 5.04550934e-01 1.96181685e-01
7.05652162e-02 1.04773414e+00 6.41610026e-02 -4.53313261e-01
-8.21878463e-02 -5.93029320e-01 4.01470661e-01 5.49846813e-02
-4.24412578e-01 2.88966298e-01 -3.22433300e-02 -7.84521759e-01
-4.42477435e-01 -6.42062008e-01 -7.86493599e-01 -5.92965901e-01
-3.19827706e-01 -2.28254870e-01 5.40546961e-02 7.52808988e-01
7.82846928e-01 5.01720428e-01 9.76433575e-01 -1.51755524e+00
-2.18511879e-01 -1.15714407e+00 -2.30645865e-01 2.77075052e-01
9.64329958e-01 -5.36600173e-01 -6.24937832e-01 3.72250676e-01] | [11.444059371948242, -2.4156103134155273] |
932ca3b9-c76f-4436-aea5-3764d4733782 | biasing-mcts-with-features-for-general-games | 1903.08942 | null | http://arxiv.org/abs/1903.08942v1 | http://arxiv.org/pdf/1903.08942v1.pdf | Biasing MCTS with Features for General Games | This paper proposes using a linear function approximator, rather than a deep
neural network (DNN), to bias a Monte Carlo tree search (MCTS) player for
general games. This is unlikely to match the potential raw playing strength of
DNNs, but has advantages in terms of generality, interpretability and resources
(time and hardware) required for training. Features describing local patterns
are used as inputs. The features are formulated in such a way that they are
easily interpretable and applicable to a wide range of general games, and might
encode simple local strategies. We gradually create new features during the
same self-play training process used to learn feature weights. We evaluate the
playing strength of an MCTS player biased by learnt features against a standard
upper confidence bounds for trees (UCT) player in multiple different board
games, and demonstrate significantly improved playing strength in the majority
of them after a small number of self-play training games. | ['Cameron Browne', 'Éric Piette', 'Dennis J. N. J. Soemers'] | 2019-03-21 | null | null | null | null | ['board-games'] | ['playing-games'] | [ 1.28573030e-01 9.28140283e-02 -2.15838358e-01 -3.54341388e-01
-7.49603331e-01 -6.09182596e-01 8.34396422e-01 -2.26133943e-01
-8.56857717e-01 1.02618015e+00 -8.31354316e-03 -4.45669174e-01
-4.39711630e-01 -1.30115533e+00 -7.36697257e-01 -7.90888011e-01
-4.10714373e-02 8.00391316e-01 7.50335515e-01 -3.87736320e-01
2.79594272e-01 5.55949152e-01 -1.74613154e+00 2.65230894e-01
5.33231378e-01 9.62578118e-01 3.56338292e-01 1.08638692e+00
9.58102271e-02 1.08285093e+00 -7.78927624e-01 -6.67224705e-01
4.25197691e-01 -4.77680683e-01 -8.20185483e-01 -2.47405559e-01
2.11734086e-01 -4.33600038e-01 -5.41720212e-01 8.59442890e-01
5.27828693e-01 2.74626523e-01 5.98025203e-01 -8.76178801e-01
-1.47355348e-02 9.03369427e-01 -2.34831840e-01 5.84198833e-01
-2.57505737e-02 5.52148461e-01 1.41219735e+00 -7.00357407e-02
3.46325189e-01 1.05853510e+00 7.78813303e-01 7.99039960e-01
-1.16700101e+00 -8.08005512e-01 -1.38609663e-01 5.95872365e-02
-8.67117763e-01 -2.69739956e-01 2.73472100e-01 -1.44714981e-01
1.00115275e+00 2.66100883e-01 1.31086421e+00 1.09680486e+00
2.91081816e-01 9.12835956e-01 8.48160744e-01 -4.53014731e-01
8.03868294e-01 -3.98090005e-01 -3.15330505e-01 8.12876046e-01
2.99044460e-01 8.66314113e-01 -6.57530546e-01 -1.97492495e-01
1.18420196e+00 -2.46889472e-01 3.65265787e-01 -4.11709428e-01
-5.90985000e-01 1.37574923e+00 4.69733298e-01 5.34565933e-02
-3.32822412e-01 8.96975875e-01 4.20459479e-01 3.56540829e-01
3.34003866e-01 8.54800582e-01 -7.18128681e-01 -8.49546552e-01
-9.91682649e-01 7.87077487e-01 7.17971563e-01 4.49498177e-01
6.53341353e-01 3.10277641e-01 -1.11386657e-01 6.06689274e-01
6.19562082e-02 1.89018518e-01 8.18858087e-01 -1.23641384e+00
2.84689635e-01 2.64285982e-01 -1.64934695e-01 -4.76766109e-01
-3.61130178e-01 -5.86842597e-01 -2.89699465e-01 7.68301964e-01
7.04969764e-01 -4.05391842e-01 -8.86138082e-01 1.70166981e+00
1.43681571e-01 2.82639526e-02 -1.68003127e-01 4.47834492e-01
3.40866685e-01 5.32865822e-01 -4.87653427e-02 2.84376144e-01
9.75405097e-01 -6.88887835e-01 9.63656902e-02 -7.86109626e-01
6.64307833e-01 -3.19599569e-01 9.18960154e-01 4.98070598e-01
-1.41907132e+00 -3.31887305e-01 -1.06209028e+00 2.89422184e-01
-1.38123319e-01 -2.83668369e-01 1.39113569e+00 1.07244086e+00
-9.65673149e-01 9.92174506e-01 -1.03921342e+00 -2.11493686e-01
7.17596471e-01 6.48101807e-01 6.59194887e-02 1.50745004e-01
-1.14920390e+00 9.44710732e-01 4.26506519e-01 -2.64411777e-01
-1.28434670e+00 -4.44395810e-01 -6.05537236e-01 2.63386607e-01
2.98323095e-01 -5.42814612e-01 1.86492562e+00 -8.23732913e-01
-1.85701418e+00 7.16854453e-01 2.75097966e-01 -8.71728778e-01
5.81556261e-01 1.52821643e-02 1.80066228e-02 -1.99878737e-01
1.50168136e-01 8.35061610e-01 6.99712992e-01 -6.70877635e-01
-1.16629446e+00 -1.96377188e-01 4.02121037e-01 4.38186496e-01
-4.19119261e-02 -1.69480756e-01 -1.22451298e-01 -6.08802974e-01
2.99127940e-02 -7.76289999e-01 -4.60635096e-01 -1.87790379e-01
4.40588687e-03 -2.14353323e-01 1.84371397e-01 4.63105366e-02
1.13892210e+00 -1.72210026e+00 -2.23478407e-01 4.22739863e-01
2.19888151e-01 2.26484939e-01 -2.56735384e-01 1.72367796e-01
1.49632365e-01 1.11177690e-01 1.42454758e-01 3.04700851e-01
8.21143165e-02 6.59454763e-01 3.20222303e-02 1.26718342e-01
1.39771461e-01 1.17067480e+00 -9.11817789e-01 -1.46264240e-01
1.83222637e-01 -3.64002377e-01 -1.04263818e+00 -1.28475368e-01
-5.28345764e-01 -1.94146574e-01 -6.88063025e-01 2.13814974e-01
1.30978778e-01 1.96448970e-03 4.12544645e-02 6.41840756e-01
1.34436071e-01 6.10112965e-01 -9.69628334e-01 1.19476604e+00
-5.78823149e-01 5.76359153e-01 -4.57010657e-01 -1.11885786e+00
8.00265908e-01 -9.35972333e-02 6.94197416e-02 -6.83002293e-01
2.95505792e-01 1.60457283e-01 6.47543490e-01 -1.76711883e-02
3.30920964e-01 -4.70894873e-01 -3.02151263e-01 4.56183255e-01
3.39597076e-01 -6.31588876e-01 5.02352357e-01 -3.60841267e-02
1.62137628e+00 -9.63433180e-03 3.36285502e-01 -2.76515871e-01
-8.36781338e-02 6.25765845e-02 4.58950073e-01 1.40950811e+00
-1.18417107e-01 4.04454321e-01 6.51701689e-01 -8.23950529e-01
-1.21914256e+00 -1.17231679e+00 3.13004293e-02 1.52312291e+00
-2.75850743e-01 -4.73330587e-01 -6.21038556e-01 -5.44534862e-01
-1.26537457e-01 7.28051722e-01 -7.88960516e-01 -5.16717970e-01
-3.82174700e-01 -7.69304216e-01 7.29413688e-01 7.76386261e-01
4.58354235e-01 -1.34292734e+00 -1.00494075e+00 5.84363163e-01
3.22774500e-01 -5.72491407e-01 -7.63257593e-02 9.25649822e-01
-1.09408104e+00 -8.79911125e-01 -2.78103262e-01 -5.48836589e-01
1.43049911e-01 -1.95661351e-01 1.34068835e+00 1.51803493e-02
-3.13572824e-01 -1.72069259e-02 -2.34976113e-01 -4.02200460e-01
-4.10015374e-01 2.81885296e-01 -2.78221872e-02 -8.80246341e-01
4.79049325e-01 -6.75743282e-01 -4.09158289e-01 2.32147783e-01
-5.86097598e-01 -6.72781691e-02 8.11234415e-01 1.33627927e+00
1.53998151e-01 5.49929678e-01 4.75220047e-02 -7.82853127e-01
8.33642602e-01 -2.30805829e-01 -7.07381308e-01 -1.13112815e-01
-3.30068082e-01 3.97851765e-01 6.94697857e-01 -6.20208681e-01
-8.60943317e-01 -5.77747710e-02 -2.72794276e-01 1.28587112e-01
-3.22360247e-02 3.03060532e-01 1.15861639e-01 -1.82190210e-01
1.22424197e+00 2.22513229e-01 -1.37753338e-01 -1.64274290e-01
2.80811161e-01 1.44479826e-01 2.80489683e-01 -9.85002637e-01
9.92770910e-01 9.09495801e-02 -3.39772627e-02 -2.62535334e-01
-7.74895430e-01 2.24321216e-01 -9.92728919e-02 -2.08039507e-01
4.37967598e-01 -7.83831537e-01 -1.00609612e+00 4.85091001e-01
-6.70675397e-01 -7.41843104e-01 -9.37203526e-01 4.99648720e-01
-1.02638555e+00 -2.50576466e-01 -5.22837579e-01 -7.11164832e-01
1.34091616e-01 -8.98220956e-01 6.53642833e-01 4.88398463e-01
-4.67330962e-01 -8.95119071e-01 1.63227975e-01 3.43160838e-01
2.72208720e-01 -1.41344234e-01 9.49129164e-01 -6.88023090e-01
-4.23012495e-01 -4.63136435e-01 1.97216094e-01 2.89688319e-01
-1.11494981e-01 9.56494883e-02 -8.21893573e-01 -4.03123014e-02
-2.38825649e-01 -7.35953987e-01 8.70020866e-01 8.53235662e-01
1.17490709e+00 -2.30548695e-01 -9.17436630e-02 4.55759853e-01
1.16316116e+00 3.28594297e-01 6.59832954e-01 6.91220403e-01
9.31046903e-02 1.15426585e-01 3.14561665e-01 7.20405221e-01
-3.32015194e-02 4.14696336e-01 5.04234910e-01 2.48664275e-01
1.77986875e-01 -6.50505900e-01 4.24502045e-01 2.21521899e-01
-4.02366519e-01 -1.53632894e-01 -8.30012262e-01 5.25692940e-01
-1.75134695e+00 -1.19391179e+00 3.64376158e-01 2.05776358e+00
8.70473385e-01 9.85019743e-01 4.83520865e-01 2.97815621e-01
5.92593253e-01 1.73465833e-01 -7.22297847e-01 -7.66390204e-01
1.82512533e-02 1.08748281e+00 8.07270825e-01 4.26289946e-01
-8.08406293e-01 1.32345963e+00 7.83309889e+00 1.55810952e+00
-7.58803785e-01 -1.55007362e-01 7.81497598e-01 -4.68948632e-01
-2.54253536e-01 1.92345846e-02 -6.37771189e-01 3.48480225e-01
1.08392930e+00 -2.09202886e-01 8.10419619e-01 1.10716486e+00
2.60985661e-02 -3.13845605e-01 -9.02275145e-01 6.06488466e-01
-5.83742797e-01 -1.67260659e+00 -2.44591683e-02 2.86668360e-01
6.64303243e-01 2.45808885e-01 3.62119555e-01 7.95935094e-01
1.56807911e+00 -1.42861569e+00 9.98851299e-01 8.08621272e-02
4.56108779e-01 -1.02807677e+00 6.74501538e-01 4.51189399e-01
-8.70242834e-01 -3.11123788e-01 -6.70713902e-01 -7.84364641e-01
-4.08019572e-01 3.08015674e-01 -7.27967620e-01 -1.45260409e-01
7.76464403e-01 -8.55946541e-03 -4.45825070e-01 1.07985139e+00
-3.97871554e-01 9.67105746e-01 -7.61574566e-01 -7.18994617e-01
8.74612451e-01 1.78530008e-01 7.27637932e-02 6.39675915e-01
1.94564134e-01 6.46101460e-02 -2.37380370e-01 7.19826937e-01
4.33343165e-02 -2.51974553e-01 -4.57336873e-01 -1.33009493e-01
4.95763272e-01 1.01255751e+00 -8.24489713e-01 -1.65997036e-02
-1.16131850e-01 6.78576767e-01 3.90881479e-01 6.30919263e-03
-7.13445365e-01 -3.07716846e-01 9.10353065e-01 8.09506774e-02
6.66658044e-01 9.88775790e-02 -4.75389540e-01 -8.65012765e-01
-3.12731117e-01 -9.44255292e-01 2.25227073e-01 -6.88112915e-01
-1.18052483e+00 3.59192044e-01 -1.02340780e-01 -9.40632224e-01
-8.41169000e-01 -8.91166866e-01 -9.95038390e-01 6.45610809e-01
-6.73743308e-01 -6.21852517e-01 3.18473786e-01 4.50494021e-01
5.40258110e-01 -4.97307241e-01 8.03532362e-01 -4.04578626e-01
-1.86782956e-01 7.88213670e-01 3.98642570e-01 1.95093140e-01
-2.49527737e-01 -1.34358823e+00 7.52287507e-01 5.12179554e-01
5.89539289e-01 3.13541144e-01 8.32272649e-01 -2.46130228e-01
-9.11061943e-01 -5.17186701e-01 3.24595332e-01 -3.51781011e-01
8.32994163e-01 -3.17412972e-01 -1.36133209e-01 5.81139207e-01
-3.01662654e-01 1.39276013e-01 5.24823010e-01 5.32365024e-01
-1.01793624e-01 -3.24673764e-02 -1.32529747e+00 9.41516936e-01
1.25849938e+00 -3.62121910e-01 -5.95680475e-01 -3.14783156e-02
7.13953227e-02 -4.71371651e-01 -4.58631843e-01 5.57558835e-02
6.07307017e-01 -1.15854645e+00 8.85545433e-01 -1.04440761e+00
5.98693192e-01 1.02538094e-01 -2.36992106e-01 -1.51356542e+00
-6.29819989e-01 -6.73250079e-01 4.57327925e-02 6.24531806e-01
5.43641210e-01 -4.64984536e-01 1.74798524e+00 3.89716268e-01
2.56253511e-01 -9.17274892e-01 -1.28249359e+00 -9.26042736e-01
5.37423491e-01 -7.68313885e-01 5.92546642e-01 3.58641088e-01
1.28577515e-01 2.57282227e-01 -1.40132785e-01 -2.23768324e-01
3.78445268e-01 -2.06027150e-01 7.03673840e-01 -1.33232903e+00
-8.82128537e-01 -7.32412040e-01 -1.02466738e+00 -1.27234387e+00
-1.27743809e-02 -7.66851127e-01 7.66319260e-02 -1.19760168e+00
1.92232504e-01 -4.93160337e-01 -1.75717890e-01 4.89201635e-01
-3.96090634e-02 9.65123326e-02 1.43643156e-01 -2.57905275e-01
-4.16700900e-01 4.96115059e-01 1.10695350e+00 -1.22065302e-02
2.18608499e-01 5.14725626e-01 -1.01819217e+00 1.07232988e+00
8.59699845e-01 -7.52089620e-01 -5.12532294e-01 -2.37921938e-01
4.09125566e-01 -5.98216802e-02 1.71268463e-01 -1.47461939e+00
1.08863264e-01 -4.08242404e-01 8.09872091e-01 -9.63076055e-02
3.35583091e-01 -4.79868889e-01 -8.80645365e-02 7.43860245e-01
-3.69354159e-01 -2.19224438e-01 2.27901578e-01 4.00715530e-01
1.83192343e-02 -8.51305127e-01 8.10613871e-01 -4.61579740e-01
-6.34368539e-01 2.34960452e-01 -9.76273000e-01 4.25233752e-01
9.56502259e-01 -8.35725307e-01 9.23254117e-02 -7.44666219e-01
-6.80241644e-01 -1.68824531e-02 3.59285295e-01 -1.38198242e-01
2.89035708e-01 -1.13764918e+00 -4.93665338e-01 1.74707934e-01
-1.28712565e-01 3.88171561e-02 -1.67612713e-02 -2.50354677e-01
-9.01364863e-01 8.02774057e-02 -3.90054941e-01 -2.25227937e-01
-8.19922626e-01 -1.24712706e-01 6.52101636e-01 -7.36692548e-01
-5.30664027e-01 1.40865850e+00 1.50564956e-02 -5.61639547e-01
7.54194483e-02 -3.42578709e-01 3.70633960e-01 -2.95704603e-01
2.66422212e-01 1.91960931e-01 -4.13067155e-02 9.00990143e-02
-9.63578373e-02 3.30594212e-01 -3.13107699e-01 -4.33768779e-01
1.41009855e+00 5.10261238e-01 6.34249508e-01 2.20335588e-01
5.85852504e-01 -2.94620544e-01 -1.77830744e+00 -1.21336989e-01
1.62201806e-03 -4.70841140e-01 2.73769021e-01 -9.05432880e-01
-1.22768772e+00 7.27387846e-01 6.29970193e-01 2.64803171e-01
7.31823802e-01 6.59174174e-02 5.68805039e-01 7.47760773e-01
5.91207981e-01 -1.25142694e+00 1.57894149e-01 8.08541417e-01
2.63369679e-01 -8.19828808e-01 -7.63684735e-02 1.87147632e-01
-6.49807453e-01 1.20736372e+00 6.78124905e-01 -6.18679821e-01
4.38955694e-01 6.07798576e-01 -1.78344548e-01 -1.53832778e-01
-1.06222475e+00 -4.80895013e-01 -4.02820647e-01 7.81179249e-01
4.68257926e-02 1.07023045e-01 -8.86500031e-02 5.17280996e-01
-9.39407825e-01 8.48274603e-02 4.71441597e-01 9.68440652e-01
-8.40842783e-01 -9.45247114e-01 -9.10509378e-02 8.84805977e-01
-5.08153617e-01 -2.96056300e-01 -1.76192284e-01 9.13029194e-01
2.81271189e-01 6.98403358e-01 4.24375176e-01 -6.35592580e-01
1.24931224e-01 -9.52660218e-02 8.61362338e-01 -5.89466691e-01
-7.20682144e-01 -2.90788323e-01 2.55460948e-01 -4.50956315e-01
5.47632687e-02 -6.17570043e-01 -1.03788435e+00 -9.70499337e-01
-4.56027389e-01 1.44560784e-01 3.19987357e-01 1.03488934e+00
-2.15397745e-01 5.05062461e-01 4.88936394e-01 -8.56236756e-01
-8.25409651e-01 -8.23976636e-01 -9.39904928e-01 -1.72036495e-02
-2.48382226e-01 -7.94623494e-01 -3.85320604e-01 -5.49050927e-01] | [3.523505210876465, 1.5096849203109741] |
6377d684-8c11-41d0-bfde-e801ada163a7 | a-review-of-deep-learning-techniques-for | 2201.02503 | null | https://arxiv.org/abs/2201.02503v1 | https://arxiv.org/pdf/2201.02503v1.pdf | A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets | Markerless motion capture has become an active field of research in computer vision in recent years. Its extensive applications are known in a great variety of fields, including computer animation, human motion analysis, biomedical research, virtual reality, and sports science. Estimating human posture has recently gained increasing attention in the computer vision community, but due to the depth of uncertainty and the lack of the synthetic datasets, it is a challenging task. Various approaches have recently been proposed to solve this problem, many of which are based on deep learning. They are primarily focused on improving the performance of existing benchmarks with significant advances, especially 2D images. Based on powerful deep learning techniques and recently collected real-world datasets, we explored a model that can predict the skeleton of an animation based solely on 2D images. Frames generated from different real-world datasets with synthesized poses using different body shapes from simple to complex. The implementation process uses DeepLabCut on its own dataset to perform many necessary steps, then use the input frames to train the model. The output is an animated skeleton for human movement. The composite dataset and other results are the "ground truth" of the deep model. | ['Russell Butler', 'Doan Duy Vo'] | 2022-01-07 | null | null | null | null | ['markerless-motion-capture'] | ['computer-vision'] | [ 7.45928064e-02 -2.52620876e-01 -2.49173880e-01 -6.69171140e-02
-3.07311296e-01 -1.86799884e-01 4.79436427e-01 -4.77691323e-01
-6.06269121e-01 5.36807716e-01 2.14271113e-01 1.00121677e-01
3.34910750e-01 -6.18264139e-01 -6.43949986e-01 -6.13783896e-01
-1.02001384e-01 5.16008079e-01 6.21964157e-01 -3.35095644e-01
1.82873145e-01 4.08597052e-01 -1.49634004e+00 -1.00288965e-01
5.53881407e-01 7.28490889e-01 4.24268143e-03 6.47307932e-01
3.97843905e-02 4.05891657e-01 -5.81627131e-01 -2.98465848e-01
3.56271893e-01 -5.79369545e-01 -5.56975126e-01 7.57469013e-02
2.72837728e-01 -2.23029807e-01 -4.58440483e-01 8.76746058e-01
8.29380572e-01 3.05223405e-01 3.54389220e-01 -1.33322966e+00
-8.67694020e-02 2.05208495e-01 -9.59496081e-01 1.98498309e-01
5.91201603e-01 4.18930918e-01 4.03571784e-01 -6.19975090e-01
9.13067460e-01 1.37401199e+00 7.70234048e-01 8.16525161e-01
-8.82047415e-01 -6.69372797e-01 -1.64047301e-01 4.34794277e-01
-9.75713730e-01 -1.57166183e-01 1.07636178e+00 -5.82044244e-01
5.80941439e-01 1.45123884e-01 1.22249389e+00 1.30260921e+00
3.81669670e-01 9.94279563e-01 9.32633102e-01 -3.53528440e-01
1.16052799e-01 -4.37136739e-01 -4.25399207e-02 7.77001619e-01
1.34731561e-01 1.39818177e-01 -2.14830220e-01 5.56942932e-02
1.04533684e+00 -1.15468279e-01 -4.79182631e-01 -7.49834597e-01
-1.37388718e+00 7.30114698e-01 2.12075531e-01 8.05475563e-02
-2.90154397e-01 2.52560377e-01 5.80381751e-01 -7.35543445e-02
4.31252599e-01 7.97216743e-02 -3.91676128e-01 -3.09977978e-01
-8.83698583e-01 6.94707930e-01 6.21044219e-01 4.18684006e-01
3.07308465e-01 1.93824008e-01 8.18622410e-02 7.21648753e-01
2.89021313e-01 4.42209065e-01 7.78314054e-01 -1.10665238e+00
4.29910779e-01 6.57440066e-01 -9.32603609e-03 -1.28757596e+00
-6.67173266e-01 -2.20070735e-01 -9.49324191e-01 5.91147125e-01
7.20300913e-01 -3.05544049e-01 -1.04130077e+00 1.60317981e+00
7.27554381e-01 5.87106705e-01 -3.53302538e-01 1.29483485e+00
9.11099434e-01 4.29417104e-01 5.61939143e-02 5.04151499e-03
1.01378465e+00 -9.82741117e-01 -5.69213092e-01 -2.09165379e-01
3.15445065e-01 -6.67025566e-01 9.09235358e-01 3.81588846e-01
-1.01692915e+00 -7.99825907e-01 -9.82854962e-01 -1.05791055e-02
-5.38012795e-02 -1.80179777e-03 5.51870465e-01 5.70223808e-01
-7.44266510e-01 7.90501416e-01 -1.13914216e+00 -3.39055806e-01
3.82455140e-01 3.11779171e-01 -5.48471034e-01 1.44330263e-01
-1.16187644e+00 9.53301430e-01 2.46155009e-01 2.80087113e-01
-6.92356646e-01 -3.12251866e-01 -1.03378224e+00 -3.67112190e-01
3.48633140e-01 -1.07751167e+00 1.00959289e+00 -8.77639234e-01
-1.73964822e+00 1.05507576e+00 2.95300275e-01 -3.59786570e-01
1.18771780e+00 -4.04287517e-01 -9.84484032e-02 -2.04815045e-02
-1.55242030e-02 7.00280428e-01 7.63671458e-01 -9.70188260e-01
-2.65933216e-01 -5.19702613e-01 -1.68107182e-01 1.85632646e-01
2.06570759e-01 3.77538204e-02 -8.55649889e-01 -7.65657008e-01
9.04514119e-02 -1.45679665e+00 -3.86622250e-01 3.31765115e-01
-3.98543775e-01 -1.00697756e-01 7.97824740e-01 -6.68250799e-01
9.35696125e-01 -1.84989572e+00 5.26297629e-01 -2.17167631e-01
3.36867124e-02 6.66573822e-01 1.45136833e-01 3.72475646e-02
-9.93363187e-02 -2.37481773e-01 -3.22653919e-01 -2.01371938e-01
-2.53853619e-01 6.67894930e-02 8.25469345e-02 6.90451801e-01
-1.37071803e-01 8.63469183e-01 -8.83583546e-01 -7.72742629e-01
6.16868675e-01 5.01229942e-01 -3.24905783e-01 2.22542256e-01
-2.34247223e-01 8.35473478e-01 -3.38634431e-01 4.07026947e-01
5.59634805e-01 -7.59620667e-02 -1.13924211e-02 -1.18635014e-01
3.73486765e-02 -3.84273618e-01 -1.37267971e+00 2.07398343e+00
6.79434240e-02 7.88292348e-01 -1.53783649e-01 -1.04116940e+00
7.46225536e-01 2.37971559e-01 7.26221681e-01 -4.64406103e-01
4.05986845e-01 4.21283916e-02 2.29932934e-01 -9.75859046e-01
2.64780819e-01 -5.81587665e-02 1.63645685e-01 2.99664557e-01
-2.81963378e-01 -5.68414479e-02 7.84664229e-02 -2.21726313e-01
8.60536158e-01 8.63453865e-01 1.48625255e-01 2.51165092e-01
5.69429517e-01 3.06121826e-01 7.02013135e-01 1.20395713e-01
-5.67597985e-01 9.63326633e-01 1.98170021e-01 -8.86604190e-01
-1.02957964e+00 -8.01614046e-01 1.66087538e-01 6.05319381e-01
3.74065876e-01 -7.66518861e-02 -8.04136097e-01 -3.35018069e-01
-5.63252829e-02 6.52720407e-02 -6.46195889e-01 -2.30586141e-01
-1.22667563e+00 -7.49788105e-01 5.62587202e-01 7.32747078e-01
7.67719328e-01 -1.42685580e+00 -1.19098830e+00 2.29443654e-01
-2.66100466e-01 -1.15210068e+00 -2.04035088e-01 -5.80466211e-01
-9.06988680e-01 -1.40769887e+00 -1.28892863e+00 -6.80652916e-01
2.86472172e-01 1.51039615e-01 9.52337801e-01 5.00439331e-02
-5.95715344e-01 1.31616279e-01 -6.21662140e-02 -4.83382046e-01
-3.26540440e-01 -1.50144294e-01 5.45904860e-02 2.36517452e-02
7.11643742e-03 -3.42331737e-01 -8.00575316e-01 3.32484066e-01
-6.27443910e-01 2.97116786e-01 5.03246725e-01 6.48069143e-01
6.38345361e-01 -4.47912693e-01 2.87926167e-01 -7.03233898e-01
4.48972315e-01 -3.47087950e-01 -3.95840228e-01 1.08579351e-02
-3.51621211e-02 -8.36845338e-02 3.59137863e-01 -6.62336469e-01
-8.41711819e-01 3.16910982e-01 -5.02678335e-01 -7.67685413e-01
-2.09376276e-01 3.71394485e-01 -1.32361233e-01 9.42825153e-02
5.19832253e-01 1.93255484e-01 3.80064309e-01 -4.33666199e-01
1.84342936e-01 2.43862435e-01 8.50963712e-01 -4.10233319e-01
4.92511272e-01 5.74898601e-01 2.60554999e-01 -8.43257546e-01
-4.79338944e-01 -3.00738692e-01 -7.28528619e-01 -6.18536294e-01
1.08884704e+00 -6.95243061e-01 -6.27572000e-01 9.61267292e-01
-1.10664511e+00 -4.21104312e-01 -1.69727427e-04 8.55678201e-01
-6.25559688e-01 6.49325013e-01 -4.58892107e-01 -5.59740603e-01
-4.15137231e-01 -1.30348694e+00 1.09241414e+00 3.50967765e-01
-3.45358461e-01 -9.65468109e-01 5.49962163e-01 3.31738144e-01
8.40068534e-02 1.03928459e+00 7.23257542e-01 -2.17849433e-01
-3.62051576e-01 -3.96984458e-01 1.73548952e-01 1.99938297e-01
-1.33325737e-02 2.74977386e-01 -6.20579541e-01 -1.70613721e-01
-1.20780468e-01 -2.91788280e-01 6.41946793e-01 8.49823833e-01
1.03837836e+00 2.27155879e-01 -5.02827466e-01 7.67293751e-01
1.12875021e+00 2.02003960e-02 6.61654115e-01 5.10167241e-01
9.45409775e-01 5.91648459e-01 6.48135006e-01 2.37950012e-01
2.84153104e-01 1.05520058e+00 5.36648571e-01 -1.79934889e-01
-2.91623086e-01 -1.32354498e-01 1.89316660e-01 7.26129115e-01
-5.84989488e-01 1.59339800e-01 -9.94306445e-01 3.61899734e-01
-1.98500669e+00 -1.22171676e+00 -3.69033396e-01 2.19362354e+00
5.98413646e-01 2.69257277e-01 5.08502722e-01 2.53918231e-01
8.00991476e-01 2.46766061e-01 -6.93509340e-01 -7.25810081e-02
3.52422856e-02 8.42793435e-02 1.11392863e-01 5.94232008e-02
-1.17740953e+00 8.32107842e-01 5.97449207e+00 3.91615063e-01
-1.47528493e+00 -2.31139675e-01 3.54586929e-01 1.86607495e-01
1.32740855e-01 -3.19595277e-01 -5.26555836e-01 6.88326716e-01
5.66326857e-01 -1.83925897e-01 -1.39646471e-01 8.61242056e-01
4.07227099e-01 -1.80004328e-01 -8.85752678e-01 1.20229936e+00
1.64686427e-01 -1.27394688e+00 -1.06498852e-01 -1.44374138e-02
7.09152877e-01 -4.02246118e-02 -8.46818089e-02 2.32657865e-01
-4.15361710e-02 -8.90363812e-01 5.29184997e-01 6.46243513e-01
6.67400777e-01 -5.62368453e-01 6.56154692e-01 7.79904842e-01
-1.09511805e+00 2.17687249e-01 -2.97716737e-01 -2.50698864e-01
3.33777964e-01 1.62746996e-01 -5.20949662e-01 4.07311678e-01
6.51218534e-01 7.19869733e-01 -4.36920285e-01 1.48901188e+00
-1.68814108e-01 4.36052352e-01 -2.88480937e-01 5.16083241e-02
-4.71168198e-02 -2.61295915e-01 5.58705211e-01 9.95371819e-01
1.17280230e-01 -3.87831330e-02 3.27173203e-01 5.29759586e-01
1.49575606e-01 1.72019098e-02 -6.47025585e-01 3.30151320e-01
6.92645535e-02 1.14504516e+00 -8.49157035e-01 -3.19556624e-01
-2.54915178e-01 8.13724279e-01 4.56124498e-03 2.34726146e-02
-1.18748450e+00 -1.88179865e-01 5.53388894e-01 1.96125269e-01
-2.25257259e-02 -4.76141334e-01 -1.10770427e-01 -1.22988462e+00
-5.86860590e-02 -8.87374401e-01 3.01298767e-01 -6.96948230e-01
-6.89243317e-01 4.50742990e-01 2.25995839e-01 -1.43968141e+00
-6.02147460e-01 -4.85313386e-01 -7.36342609e-01 7.19599009e-01
-1.00521970e+00 -8.80116105e-01 -7.17408180e-01 7.33708799e-01
7.83175290e-01 -1.77096538e-02 7.08552539e-01 4.92612720e-01
-8.29652786e-01 2.05116823e-01 -2.63264596e-01 5.43256760e-01
6.79131031e-01 -9.82237339e-01 7.38120317e-01 8.22272003e-01
2.51266629e-01 1.87149554e-01 7.73709774e-01 -6.41730666e-01
-1.40082490e+00 -8.67477655e-01 4.48682785e-01 -5.27189374e-01
2.27239072e-01 9.64912921e-02 -8.16593945e-01 5.82672715e-01
2.62719877e-02 3.93653631e-01 3.76882076e-01 -5.26190281e-01
3.03063005e-01 1.45962492e-01 -8.48821759e-01 6.96986139e-01
1.05083966e+00 1.56706363e-01 -6.56334162e-01 5.34085296e-02
3.03563595e-01 -1.11035967e+00 -5.04939258e-01 5.27216136e-01
8.49717975e-01 -9.87364113e-01 1.09747493e+00 -7.82783866e-01
5.95314205e-01 -3.82128030e-01 4.25019503e-01 -1.30310500e+00
-1.02088712e-01 -3.94498467e-01 -2.93109953e-01 6.87632859e-01
-1.88907549e-01 -7.73365349e-02 1.23707652e+00 6.23296261e-01
-5.78763969e-02 -9.62295711e-01 -8.58389080e-01 -4.56356943e-01
-8.82559344e-02 -4.17169452e-01 3.03291202e-01 8.48853648e-01
-4.32635576e-01 3.47269416e-01 -6.77178621e-01 -2.06142053e-01
7.04878449e-01 3.06763142e-01 1.43611717e+00 -1.36307478e+00
-2.94416368e-01 -3.59975934e-01 -8.84299755e-01 -1.11597371e+00
1.76641524e-01 -6.18295968e-01 -8.66860002e-02 -1.72241747e+00
1.80569310e-02 -1.16988070e-01 1.43825084e-01 2.67206103e-01
-3.32917124e-01 3.93766403e-01 3.17120641e-01 2.76072413e-01
-3.39632094e-01 4.72041607e-01 1.61586893e+00 -1.81557715e-01
-2.62478709e-01 4.49227601e-01 5.13012288e-04 1.20852447e+00
6.41697288e-01 -3.08924258e-01 -3.20649236e-01 -5.35431325e-01
-8.59582871e-02 3.94372672e-01 5.64753532e-01 -1.36082029e+00
1.01979561e-01 -1.75528035e-01 6.75654113e-01 -5.78596413e-01
5.75427055e-01 -6.78265035e-01 5.18936157e-01 8.82859409e-01
-1.56361818e-01 2.75518477e-01 3.06043997e-02 5.80896616e-01
-1.57010287e-01 4.11469936e-02 9.05030608e-01 -3.94985110e-01
-1.07632327e+00 5.65602422e-01 9.07846838e-02 3.40394586e-01
1.21361649e+00 -5.19008934e-01 4.72714566e-02 -3.20364565e-01
-9.44865584e-01 2.52610501e-02 5.42699635e-01 5.26578188e-01
7.30759621e-01 -1.27638853e+00 -7.03943431e-01 4.40980159e-02
-2.22649276e-01 1.42888173e-01 1.44400522e-01 7.61929929e-01
-9.87000644e-01 3.66433486e-02 -7.86198854e-01 -9.13311958e-01
-1.33363318e+00 4.42040592e-01 4.10863012e-01 -1.73010573e-01
-9.74424124e-01 5.54132044e-01 -1.13668740e-01 -1.31307796e-01
2.65987217e-01 -2.69609213e-01 -4.43117201e-01 -2.39780381e-01
3.17608088e-01 6.24764502e-01 -1.69504255e-01 -9.20777440e-01
-4.26477611e-01 9.82729256e-01 3.75813693e-01 -1.04293108e-01
1.33629143e+00 1.35219470e-01 3.65484148e-01 4.58396673e-01
1.05335772e+00 -9.73785967e-02 -1.46096385e+00 1.26604229e-01
-1.01493590e-01 -6.24402642e-01 -3.46888214e-01 -4.40853149e-01
-1.45485532e+00 1.21630907e+00 7.24277079e-01 -1.31316200e-01
7.83354282e-01 -3.66152138e-01 1.09633756e+00 3.44257466e-02
5.47765017e-01 -1.11702299e+00 1.88447878e-01 2.73791343e-01
7.39146113e-01 -1.36887491e+00 1.60282508e-01 -2.93989509e-01
-7.46288598e-01 1.17503667e+00 8.42679083e-01 -4.85737562e-01
5.56038141e-01 5.50946072e-02 3.15003872e-01 -1.82747860e-02
-2.89667845e-01 -1.19264022e-01 2.50001639e-01 7.03366339e-01
4.73576188e-01 -1.35910287e-01 -6.58102989e-01 4.05820400e-01
-8.79431441e-02 4.25176442e-01 3.61595899e-01 8.12895417e-01
-2.70260632e-01 -1.10687494e+00 -4.46835965e-01 1.65201306e-01
-5.35795331e-01 6.23781919e-01 -2.59096861e-01 1.15004385e+00
2.60705262e-01 3.90574902e-01 -1.26337647e-01 -3.12083602e-01
4.85439390e-01 -1.62163228e-01 6.80587709e-01 -3.87132466e-01
-3.74200195e-01 -5.38314916e-02 -7.24743903e-02 -5.65375209e-01
-7.45286167e-01 -6.16402686e-01 -1.34127665e+00 -2.51677006e-01
-7.92904273e-02 -1.60429120e-01 7.08318770e-01 9.04862344e-01
2.26236716e-01 3.56566846e-01 3.13634902e-01 -1.46280515e+00
-5.07898211e-01 -7.95239866e-01 -1.99277014e-01 7.77993381e-01
1.09417744e-01 -9.90202606e-01 4.83623855e-02 2.16172799e-01] | [7.220550537109375, -0.6902354955673218] |
08a12caa-b520-43d1-be3b-1ab78cf44770 | pp-yoloe-r-an-efficient-anchor-free-rotated | 2211.02386 | null | https://arxiv.org/abs/2211.02386v1 | https://arxiv.org/pdf/2211.02386v1.pdf | PP-YOLOE-R: An Efficient Anchor-Free Rotated Object Detector | Arbitrary-oriented object detection is a fundamental task in visual scenes involving aerial images and scene text. In this report, we present PP-YOLOE-R, an efficient anchor-free rotated object detector based on PP-YOLOE. We introduce a bag of useful tricks in PP-YOLOE-R to improve detection precision with marginal extra parameters and computational cost. As a result, PP-YOLOE-R-l and PP-YOLOE-R-x achieve 78.14 and 78.28 mAP respectively on DOTA 1.0 dataset with single-scale training and testing, which outperform almost all other rotated object detectors. With multi-scale training and testing, PP-YOLOE-R-l and PP-YOLOE-R-x further improve the detection precision to 80.02 and 80.73 mAP. In this case, PP-YOLOE-R-x surpasses all anchor-free methods and demonstrates competitive performance to state-of-the-art anchor-based two-stage models. Further, PP-YOLOE-R is deployment friendly and PP-YOLOE-R-s/m/l/x can reach 69.8/55.1/48.3/37.1 FPS respectively on RTX 2080 Ti with TensorRT and FP16-precision. Source code and pre-trained models are available at https://github.com/PaddlePaddle/PaddleDetection, which is powered by https://github.com/PaddlePaddle/Paddle. | ['dianhai yu', 'Xiaoguang Hu', 'Yi Liu', 'Qingqing Dang', 'Guanzhong Wang', 'Xinxin Wang'] | 2022-11-04 | null | null | null | null | ['object-detection-in-aerial-images'] | ['computer-vision'] | [-2.98446357e-01 -4.36789453e-01 -4.86617945e-02 1.70307279e-01
-9.60989594e-01 -5.69173694e-01 3.22384946e-02 -2.04365119e-01
-4.74185258e-01 1.22657962e-01 -5.62410474e-01 -4.44672823e-01
9.70626250e-02 -5.57176292e-01 -8.34175766e-01 -4.50407237e-01
-4.11003113e-01 -7.67755881e-02 8.72236967e-01 -2.98878700e-01
-1.43286567e-02 3.77706200e-01 -1.30172133e+00 1.74187362e-01
3.69339049e-01 1.13594615e+00 6.18310153e-01 1.20933187e+00
9.49578047e-01 3.13642293e-01 -4.76095915e-01 -1.59439281e-01
5.76464117e-01 1.42639488e-01 -1.01513207e-01 -1.66419849e-01
5.88982821e-01 -7.65496612e-01 -3.99162292e-01 8.35824788e-01
7.28060007e-01 -3.35866749e-01 5.10061502e-01 -1.35429358e+00
-7.69127309e-01 5.33180237e-02 -1.30729842e+00 5.29369771e-01
2.29580939e-01 4.30562407e-01 6.89721048e-01 -1.66000032e+00
2.26888493e-01 9.48217630e-01 9.55389380e-01 3.60242993e-01
-9.07434106e-01 -1.04442716e+00 6.61799312e-02 -1.91549733e-02
-1.75474036e+00 -2.34986827e-01 1.55024543e-01 -4.13041711e-01
8.98239493e-01 1.12545609e-01 4.26104993e-01 8.42837572e-01
4.03310567e-01 8.23468864e-01 8.40718627e-01 -3.41718733e-01
-1.07019812e-01 -1.97855141e-02 -3.78509605e-04 1.11236882e+00
7.54041851e-01 1.49062186e-01 -4.19117391e-01 1.47752523e-01
8.86037409e-01 1.98363572e-01 -2.74665058e-01 -3.03269476e-01
-1.18974519e+00 6.79456890e-01 7.62242258e-01 -1.08434148e-01
-1.51207790e-01 2.75628954e-01 2.71659344e-01 -2.21135661e-01
1.73559949e-01 4.02311891e-01 -4.18023825e-01 9.24770609e-02
-7.26718068e-01 8.29373524e-02 9.93420556e-02 1.49466860e+00
1.55550092e-01 2.33141974e-01 -1.46043494e-01 7.10212708e-01
4.62061316e-01 1.17187023e+00 7.74901658e-02 -6.27021015e-01
6.25388265e-01 4.01019871e-01 4.93847460e-01 -9.42712247e-01
-7.42286921e-01 -8.07237804e-01 -5.90215921e-01 3.59124064e-01
3.96614999e-01 -3.18450391e-01 -9.64530230e-01 1.26921272e+00
3.17971110e-01 -3.35074872e-01 -3.61354053e-02 1.12979102e+00
9.76548374e-01 9.37942982e-01 -7.91310072e-02 3.29833716e-01
1.94595814e+00 -1.12075114e+00 -1.17175087e-01 -6.41250134e-01
6.77979767e-01 -9.13781762e-01 1.16458356e+00 4.85532463e-01
-8.82017732e-01 -8.69419396e-01 -1.23339057e+00 1.29820764e-01
-2.15083942e-01 1.39585340e+00 5.85433662e-01 5.71336448e-01
-7.96202898e-01 9.40640122e-02 -9.61512566e-01 -5.77789545e-01
6.66008413e-01 3.18708479e-01 -3.68473709e-01 -2.84119874e-01
-6.47804260e-01 7.53218770e-01 3.16163570e-01 2.03968883e-01
-1.20426023e+00 -6.04846537e-01 -4.71798122e-01 -7.59529099e-02
7.28312612e-01 -3.90743494e-01 1.43261588e+00 -5.68435453e-02
-1.11398101e+00 7.85283625e-01 -3.55238648e-04 -4.31754500e-01
3.69606912e-01 -6.41222358e-01 -5.28605163e-01 3.79080683e-01
6.00586832e-01 9.49452162e-01 6.61158800e-01 -1.02273905e+00
-1.02222705e+00 -4.62885469e-01 -4.58927043e-02 1.82516336e-01
-2.22752243e-01 2.06598446e-01 -8.49212825e-01 -4.68525112e-01
1.29486337e-01 -9.73825455e-01 1.60918292e-02 3.44805539e-01
-5.80444634e-01 -1.21695712e-01 1.12775266e+00 -4.97372270e-01
1.07924056e+00 -2.14298773e+00 -6.19057894e-01 -4.63547409e-01
3.97069633e-01 9.24786210e-01 -1.80367753e-01 2.37381160e-01
3.02887186e-02 -6.33592755e-02 2.40371361e-01 -3.59368712e-01
-3.12104285e-01 -4.38120961e-01 -1.74586236e-01 7.42610633e-01
2.57081062e-01 7.57435977e-01 -8.80087435e-01 -2.34981537e-01
5.44709086e-01 3.06851774e-01 -2.29620442e-01 -5.69682345e-02
3.60065967e-01 8.36117193e-02 -5.55217862e-01 1.34638190e+00
8.37159932e-01 -4.44351554e-01 -3.80882770e-01 -4.15690631e-01
-3.98649782e-01 -7.05498159e-02 -1.07376850e+00 1.21782792e+00
-3.99703532e-02 9.62205350e-01 1.39531642e-02 -4.64416862e-01
9.39033389e-01 -8.03133026e-02 6.06240034e-02 -5.59696436e-01
3.27319771e-01 2.38186523e-01 -3.52941863e-02 -2.24352613e-01
8.78821671e-01 4.54829723e-01 -7.52258077e-02 -1.18346803e-01
-5.02833053e-02 2.10530505e-01 4.69840497e-01 3.47538054e-01
1.25592315e+00 1.82421193e-01 5.05362689e-01 -9.37149078e-02
2.49403164e-01 4.41723466e-02 5.10582745e-01 1.09881723e+00
-4.09165263e-01 6.95070922e-01 2.06281200e-01 -2.05976918e-01
-1.04953659e+00 -1.04664207e+00 -5.42271614e-01 1.06522191e+00
4.42161918e-01 -5.68414688e-01 -4.84727412e-01 -3.61964226e-01
-2.42564473e-02 4.67525244e-01 -5.03403187e-01 2.34414525e-02
-2.39171356e-01 -8.74186516e-01 7.26253629e-01 7.09458768e-01
7.18126178e-01 -4.78708833e-01 -1.18701911e+00 1.77289113e-01
1.44232437e-01 -1.31883705e+00 -4.71700817e-01 1.77552029e-01
-7.25798249e-01 -1.13018763e+00 -8.57350886e-01 -4.14480776e-01
6.83972895e-01 1.19947708e+00 7.90664673e-01 -1.16766848e-01
-8.67228329e-01 4.53521907e-01 -6.94372952e-01 -7.41271019e-01
2.92397588e-01 -2.17397995e-02 2.74632424e-01 -3.53618681e-01
4.68131661e-01 4.79005724e-02 -1.03123128e+00 1.01348853e+00
-4.12780762e-01 3.67849022e-02 8.52855086e-01 6.80226147e-01
4.71127808e-01 -3.75324816e-01 1.25299573e-01 -1.52317896e-01
-1.28882617e-01 -2.30579004e-01 -1.12890208e+00 5.61283343e-02
-5.80648243e-01 -4.73645300e-01 5.10836482e-01 -5.54494262e-01
-3.86004984e-01 1.82755932e-01 1.49421141e-01 -8.31952751e-01
1.76856279e-01 -1.73373178e-01 6.65804297e-02 -2.62879342e-01
9.80272293e-01 1.06457204e-01 -4.88080502e-01 -2.98636734e-01
2.20093161e-01 8.81862402e-01 7.96031475e-01 -1.37731940e-01
1.00245845e+00 6.06794298e-01 -7.65552074e-02 -9.10213411e-01
-8.84134293e-01 -7.18281150e-01 -1.81133345e-01 -3.84119838e-01
8.19628060e-01 -1.43156338e+00 -8.40812862e-01 6.91266418e-01
-9.54160094e-01 -2.48856723e-01 8.00537760e-04 7.13004947e-01
6.73735365e-02 1.35354355e-01 -3.74700457e-01 -8.57547641e-01
-4.81763184e-01 -1.24189258e+00 1.42625725e+00 5.97027540e-01
2.57031441e-01 -1.70407489e-01 -5.81722081e-01 3.20485383e-01
2.42205381e-01 1.55250907e-01 -2.98298925e-01 -2.50335544e-01
-7.58736193e-01 -6.13619924e-01 -7.24207938e-01 2.58473486e-01
-2.56915480e-01 2.38426670e-01 -6.97717845e-01 -7.15128481e-01
-4.46301460e-01 -2.47599974e-01 8.09893250e-01 6.41267598e-01
7.39557266e-01 7.20501095e-02 -7.40249753e-01 8.05707812e-01
1.40950930e+00 4.87256020e-01 4.92187172e-01 7.04089642e-01
6.52351260e-01 -2.86472619e-01 1.23601675e+00 6.40860200e-01
4.50143367e-01 1.05114329e+00 6.14138603e-01 -1.80248722e-01
-2.55402625e-01 -2.12026015e-01 5.52704334e-01 -1.81094129e-02
-2.09573358e-01 -4.39429134e-01 -1.00495017e+00 4.15033489e-01
-1.47795129e+00 -7.27035642e-01 -4.37079728e-01 2.17945814e+00
1.62639752e-01 3.92657816e-01 2.55560279e-01 -9.87604558e-02
8.91525745e-01 1.53850436e-01 -6.88466012e-01 1.60621479e-01
-5.13376947e-03 -2.40841046e-01 1.49496782e+00 -1.88888162e-02
-1.44487488e+00 9.81704593e-01 4.28654575e+00 8.81298780e-01
-9.71778572e-01 2.90768892e-01 3.34990799e-01 -1.92374691e-01
1.00012004e+00 -2.06509214e-02 -1.72645402e+00 4.05934423e-01
6.54925406e-01 1.77005887e-01 2.89944820e-02 1.50939763e+00
1.09109141e-01 -5.09453952e-01 -8.06273758e-01 1.17752361e+00
1.45812944e-01 -1.05436361e+00 -6.11159742e-01 3.13318968e-02
2.85646081e-01 3.58708590e-01 1.53754801e-01 3.76569360e-01
1.22668959e-01 -5.85460961e-01 9.38453794e-01 -2.74311211e-02
1.23706996e+00 -4.02106971e-01 7.19132185e-01 1.94548622e-01
-1.63755047e+00 -2.72180498e-01 -7.23518550e-01 1.22937456e-01
1.36772081e-01 3.74304682e-01 -7.60881364e-01 5.25746763e-01
1.25052965e+00 7.15650618e-01 -9.57599521e-01 1.21810651e+00
-5.26198506e-01 5.70035338e-01 -5.40216446e-01 1.44195072e-02
2.85582751e-01 3.28211457e-01 7.98519850e-01 1.28401446e+00
6.94892764e-01 3.70170504e-01 1.85446769e-01 4.72967029e-01
6.41425923e-02 -3.15545827e-01 -4.62605357e-01 2.94130534e-01
7.55775273e-01 1.73320723e+00 -9.54173982e-01 -3.32564741e-01
-3.80838871e-01 8.17800701e-01 -6.09676652e-02 3.84766683e-02
-1.33449805e+00 -6.77079320e-01 4.47140604e-01 3.71210456e-01
8.49213362e-01 -5.10818124e-01 3.42487007e-01 -1.10572958e+00
1.25666142e-01 -6.99120045e-01 2.22457543e-01 -1.29928493e+00
-7.61699557e-01 8.12140763e-01 7.09480345e-02 -1.81836605e+00
3.27962816e-01 -1.19527352e+00 -3.14133346e-01 4.88883883e-01
-1.33619285e+00 -1.23801231e+00 -8.11579227e-01 1.96098447e-01
6.84259713e-01 -3.82673621e-01 5.30904770e-01 3.68106693e-01
-8.66465092e-01 8.44509900e-01 2.84190476e-01 5.01410425e-01
7.08932757e-01 -8.45405102e-01 6.85940206e-01 1.42756581e+00
4.13925350e-02 4.10727590e-01 5.79079032e-01 -3.80458921e-01
-1.58170259e+00 -1.24155140e+00 8.41756389e-02 -6.24179542e-01
5.24213612e-01 -4.91020948e-01 -5.95216513e-01 6.77079141e-01
-3.08520585e-01 6.22756064e-01 2.13607237e-01 -3.90577108e-01
-3.33458930e-01 -4.56759840e-01 -8.50536823e-01 4.66193885e-01
9.61144865e-01 -1.75696194e-01 -2.65766382e-01 5.03048241e-01
5.66759706e-01 -9.63633537e-01 -7.18393624e-01 4.12385494e-01
6.43650293e-01 -1.15383410e+00 1.13598931e+00 1.17261909e-01
4.69044819e-02 -9.17321622e-01 -3.62404317e-01 -7.33214140e-01
-2.63982713e-01 -5.99888146e-01 1.75386705e-02 1.09513867e+00
1.39365464e-01 -8.94863605e-01 6.03655457e-01 4.11699433e-03
-3.38690102e-01 -6.98317885e-01 -9.38907862e-01 -1.20009220e+00
-5.28473496e-01 -3.69915068e-01 2.66410932e-02 2.64358014e-01
-6.12245381e-01 3.17244142e-01 -5.64005911e-01 7.92365849e-01
8.02883446e-01 -8.41008723e-02 1.11682272e+00 -6.68583035e-01
-4.06034708e-01 -1.07766921e-02 -4.37193662e-01 -1.47840714e+00
-8.26844752e-01 -3.97503585e-01 -9.67821479e-02 -1.46737373e+00
-2.37547737e-02 -3.87116075e-01 2.09428295e-02 6.62592173e-01
-2.47029498e-01 7.22339332e-01 4.62099284e-01 5.89536488e-01
-8.25143099e-01 3.37832212e-01 7.80819416e-01 1.92027166e-01
-9.19279158e-02 -1.05304427e-01 -6.16224110e-01 7.03044415e-01
9.85450745e-01 -8.16721380e-01 7.63467848e-02 -2.62309581e-01
-1.36170909e-01 1.04224253e-02 7.11936235e-01 -1.49933636e+00
3.14423442e-01 3.60887975e-01 8.57695997e-01 -8.97066236e-01
5.51431417e-01 -4.74199414e-01 -1.66430488e-01 8.55505407e-01
2.71102637e-01 3.62219512e-01 4.36458737e-01 4.95722860e-01
1.60601079e-01 -1.36967584e-01 9.41224992e-01 5.79307564e-02
-1.04170251e+00 1.40941799e-01 -2.76453167e-01 -7.84759074e-02
1.42150056e+00 -4.27152067e-01 -9.07060385e-01 1.93337929e-02
-3.00656021e-01 4.23260391e-01 2.31216267e-01 5.28817058e-01
7.42926657e-01 -1.13837695e+00 -6.27615511e-01 1.58578426e-01
5.54671705e-01 1.46604389e-01 3.24774742e-01 1.10887921e+00
-6.98549688e-01 8.56305599e-01 -2.36358926e-01 -8.22715282e-01
-1.64809763e+00 5.88880241e-01 1.64528072e-01 -8.61758068e-02
-6.48188651e-01 9.25905406e-01 3.08315337e-01 -4.18021902e-03
-4.09657834e-03 -4.47060972e-01 1.32363603e-01 -2.90399432e-01
6.36065364e-01 6.54607773e-01 -2.41059542e-01 -5.36425889e-01
-8.02010238e-01 8.54095280e-01 -2.39000902e-01 2.85919279e-01
1.06157684e+00 -9.94404256e-02 4.97102290e-01 2.56272331e-02
7.98318148e-01 -7.40550980e-02 -1.45978868e+00 1.33411512e-01
-3.90813589e-01 -7.59154797e-01 1.32764414e-01 -7.67716110e-01
-7.51498044e-01 7.74881363e-01 1.19058871e+00 -2.39153489e-01
1.19154131e+00 2.38431841e-01 3.81716549e-01 4.28686023e-01
5.18812716e-01 -7.41349936e-01 4.65405434e-01 2.26806760e-01
7.71312654e-01 -1.50657749e+00 5.60567856e-01 -4.20607835e-01
-6.39627457e-01 1.02679753e+00 1.00514567e+00 -2.64534950e-01
9.18227360e-02 2.43652672e-01 -1.32525936e-01 -3.20989043e-01
-4.17356730e-01 -3.43958110e-01 2.74194896e-01 4.42803770e-01
1.51955679e-01 1.67808354e-01 -3.08323707e-02 4.66899097e-01
8.18365067e-02 -1.17376566e-01 5.29145002e-01 1.04695868e+00
-5.47140479e-01 -6.70012057e-01 -7.64952898e-01 2.87138849e-01
-3.23373586e-01 -8.03085417e-02 1.22899756e-01 1.29447734e+00
1.19294347e-02 9.54113960e-01 -1.90772012e-01 -5.66944718e-01
5.46083450e-01 -5.58162212e-01 1.98491156e-01 -5.67694068e-01
-1.60942361e-01 2.92554975e-01 -8.02695230e-02 -6.60830498e-01
5.37501201e-02 -6.42641723e-01 -1.13234770e+00 -8.92432407e-02
-8.27721298e-01 -2.27929592e-01 7.86956787e-01 1.98927388e-01
6.65549099e-01 6.52896404e-01 3.91837299e-01 -1.05216312e+00
-6.59054697e-01 -8.81513298e-01 -7.11172402e-01 -5.10794401e-01
2.50570774e-01 -9.43533003e-01 -3.69211525e-01 -2.30725169e-01] | [8.703290939331055, -0.6552004218101501] |
bff3e118-6f95-4c27-ab83-06c42945e28c | pastiche-detection-based-on-stopword-rankings | null | null | https://aclanthology.org/W12-0411 | https://aclanthology.org/W12-0411.pdf | Pastiche Detection Based on Stopword Rankings. Exposing Impersonators of a Romanian Writer | null | ['Maria-Octavia Sulea', 'Vlad Niculae', 'Liviu P. Dinu'] | 2012-04-01 | null | null | null | ws-2012-4 | ['deception-detection'] | ['miscellaneous'] | [-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] | [-7.425676345825195, 3.56643009185791] |
2496b946-d881-43bc-aded-64e46e471285 | benchmarking-deep-reinforcement-learning-for | 1604.06778 | null | http://arxiv.org/abs/1604.06778v3 | http://arxiv.org/pdf/1604.06778v3.pdf | Benchmarking Deep Reinforcement Learning for Continuous Control | Recently, researchers have made significant progress combining the advances
in deep learning for learning feature representations with reinforcement
learning. Some notable examples include training agents to play Atari games
based on raw pixel data and to acquire advanced manipulation skills using raw
sensory inputs. However, it has been difficult to quantify progress in the
domain of continuous control due to the lack of a commonly adopted benchmark.
In this work, we present a benchmark suite of continuous control tasks,
including classic tasks like cart-pole swing-up, tasks with very high state and
action dimensionality such as 3D humanoid locomotion, tasks with partial
observations, and tasks with hierarchical structure. We report novel findings
based on the systematic evaluation of a range of implemented reinforcement
learning algorithms. Both the benchmark and reference implementations are
released at https://github.com/rllab/rllab in order to facilitate experimental
reproducibility and to encourage adoption by other researchers. | ['Pieter Abbeel', 'John Schulman', 'Yan Duan', 'Rein Houthooft', 'Xi Chen'] | 2016-04-22 | null | null | null | null | ['action-triplet-recognition'] | ['computer-vision'] | [ 2.17099171e-02 -2.41383076e-01 -1.51800647e-01 -5.17459102e-02
-3.81745875e-01 -5.49803674e-01 6.77369058e-01 4.63479199e-02
-6.77383363e-01 1.09823060e+00 -1.03734501e-01 -1.71900213e-01
-3.59498829e-01 -5.52957416e-01 -7.56599963e-01 -5.80025554e-01
-5.65096796e-01 4.14891481e-01 1.00310609e-01 -6.53646290e-01
3.86046499e-01 5.11970341e-01 -1.84524536e+00 1.20512269e-01
4.69818294e-01 8.38125288e-01 3.66345316e-01 7.64124036e-01
5.62446415e-01 8.37212384e-01 -5.20583451e-01 3.55193019e-01
5.44710815e-01 -3.70046824e-01 -6.91299379e-01 -9.04403329e-02
9.48223397e-02 -4.99266416e-01 -3.85702252e-01 5.98961353e-01
6.43794298e-01 5.33812642e-01 4.43299413e-01 -1.53013265e+00
-3.17616940e-01 5.00154495e-01 -2.96006799e-01 3.25169951e-01
5.02121031e-01 8.34593892e-01 9.08479631e-01 -1.85209364e-01
6.22262061e-01 1.20330358e+00 4.91829634e-01 6.06988430e-01
-1.10698342e+00 -7.48706281e-01 -4.61075231e-02 4.89158005e-01
-7.29727149e-01 -2.62023717e-01 3.81053656e-01 -3.18849325e-01
1.36430037e+00 -2.24173129e-01 8.85284245e-01 1.54288423e+00
3.75929773e-01 8.48881781e-01 1.44738400e+00 -2.06065074e-01
4.97580618e-01 -5.49036503e-01 -3.22503835e-01 6.43311858e-01
3.34457695e-01 7.59717524e-01 -5.21991313e-01 8.79132077e-02
1.01141870e+00 -1.80429637e-01 -6.08761944e-02 -8.83033693e-01
-1.32378662e+00 7.87694395e-01 5.51789224e-01 1.77740186e-01
-4.80485976e-01 5.48077106e-01 4.92963612e-01 8.32002878e-01
-2.72094697e-01 9.77518737e-01 -7.70674586e-01 -8.34308505e-01
-2.38011554e-01 9.04417932e-01 8.67306590e-01 8.27149928e-01
6.53196573e-01 3.13402802e-01 3.23068678e-01 5.44297159e-01
-3.15344781e-02 2.47526944e-01 6.25177741e-01 -1.55386639e+00
3.91420335e-01 4.79680508e-01 3.03053856e-01 -5.09520710e-01
-7.63806522e-01 -1.43067371e-02 -5.39255798e-01 1.12795603e+00
6.25411212e-01 -5.91048837e-01 -8.52113128e-01 1.65013826e+00
2.48067632e-01 -5.43612540e-02 1.50311306e-01 1.02168894e+00
3.23013127e-01 4.72864628e-01 -4.52479683e-02 1.58873826e-01
9.22961771e-01 -8.92875373e-01 -4.52675819e-01 -2.35107169e-01
6.28008306e-01 -3.50504130e-01 1.25891733e+00 6.96641266e-01
-1.13081288e+00 -6.60977125e-01 -1.18369222e+00 2.71590389e-02
-6.09140396e-01 -9.99279767e-02 8.61804724e-01 9.34423208e-02
-9.56354022e-01 1.08968270e+00 -1.33782697e+00 -5.00783026e-01
2.90196180e-01 6.10981345e-01 -4.50194716e-01 6.85561374e-02
-1.17343438e+00 1.27092934e+00 4.47650850e-01 -1.30904093e-01
-1.28261685e+00 -6.16571605e-01 -8.48375976e-01 -1.79801524e-01
5.49722493e-01 -6.66187227e-01 1.59941959e+00 -5.99572301e-01
-1.96041632e+00 4.78284001e-01 7.00114787e-01 -5.90479851e-01
6.98195815e-01 -5.37005663e-01 1.10061623e-01 -9.79762673e-02
7.10796267e-02 8.57708693e-01 7.40014017e-01 -9.23829317e-01
-6.91100597e-01 -3.10599178e-01 4.91573483e-01 3.84065270e-01
1.87906310e-01 -4.51244503e-01 2.98224270e-01 -3.23458225e-01
-3.29085082e-01 -1.17101133e+00 -3.72367889e-01 7.58107156e-02
4.97549437e-02 -2.92724371e-01 7.10289538e-01 -1.39247775e-01
4.63985503e-01 -1.89722586e+00 5.76883495e-01 -2.65414029e-01
-4.74101827e-02 1.01938240e-01 -7.45109469e-02 8.14989507e-01
-3.41819637e-02 -2.40898564e-01 -1.17472269e-01 7.20925704e-02
1.82207152e-01 4.10983741e-01 -5.83806261e-02 3.27082723e-01
3.15658808e-01 8.68530214e-01 -1.17053759e+00 -1.06119320e-01
4.70979869e-01 1.79738328e-01 -6.48790359e-01 1.94661230e-01
-5.04020333e-01 6.96309686e-01 -5.94323933e-01 4.62140650e-01
-1.20027471e-04 2.42431909e-02 9.91649553e-02 3.39182258e-01
-4.70551193e-01 2.77112246e-01 -1.11567461e+00 2.01462007e+00
-4.78861004e-01 5.41977525e-01 2.04680353e-01 -1.08994031e+00
6.27502561e-01 1.66382730e-01 7.73603261e-01 -7.07748234e-01
4.20336902e-01 1.20822638e-01 4.11375791e-01 -6.47078454e-01
4.25357014e-01 2.10612845e-02 -2.55530894e-01 3.76445413e-01
2.41699368e-01 -7.05791712e-01 6.03249907e-01 -3.29710901e-01
1.43297040e+00 7.92042732e-01 4.40600693e-01 -2.24614859e-01
1.33146271e-01 5.04593372e-01 1.11805096e-01 7.41351843e-01
-3.98550302e-01 2.46964708e-01 5.17765880e-01 -5.14824510e-01
-1.17374587e+00 -1.12979078e+00 5.35355955e-02 1.23070586e+00
-4.20268066e-02 -3.88109416e-01 -4.74898785e-01 -1.31000817e-01
2.86298335e-01 6.12958312e-01 -8.31439853e-01 -1.63024470e-01
-7.52945721e-01 -3.97846073e-01 3.92329037e-01 7.66467988e-01
5.18274009e-01 -1.67071831e+00 -1.45413721e+00 2.35737786e-01
3.71267170e-01 -8.01627636e-01 2.81136692e-01 6.68379128e-01
-8.39231670e-01 -1.38121486e+00 -4.27728295e-01 -7.34513998e-01
1.26719549e-01 -5.12900539e-02 8.36985290e-01 -1.42526310e-02
-4.88408059e-01 4.14000124e-01 -5.11365831e-01 -4.01691258e-01
-2.61754066e-01 1.47315085e-01 3.49790901e-01 -9.75651741e-01
-1.74236821e-03 -6.44878507e-01 -5.21083832e-01 2.08587438e-01
-7.76025295e-01 2.71808300e-02 5.85950077e-01 1.06901264e+00
3.18253487e-01 -6.47278279e-02 4.03654754e-01 -2.76042283e-01
8.63804877e-01 -4.40699607e-01 -8.21101606e-01 -2.92095155e-01
-2.59976387e-01 1.56771004e-01 6.71352088e-01 -4.72686172e-01
-6.65750086e-01 4.76121381e-02 -1.82395145e-01 -2.12115049e-01
-5.23231030e-01 4.80182260e-01 3.99637580e-01 3.46833579e-02
8.74615967e-01 1.81109115e-01 3.93652320e-01 -1.32294804e-01
3.81699950e-01 3.50301325e-01 2.47362316e-01 -8.64761174e-01
5.09284258e-01 1.55398652e-01 2.36970603e-01 -7.71402180e-01
-3.22479337e-01 -3.75192016e-02 -7.01628208e-01 -8.70682001e-02
7.70702600e-01 -7.75197864e-01 -1.10925531e+00 5.57628393e-01
-4.52430606e-01 -1.35488987e+00 -4.13361818e-01 5.97079277e-01
-1.51294625e+00 5.22816554e-02 -7.59784818e-01 -4.58097190e-01
1.71138510e-01 -1.28001618e+00 9.06005621e-01 3.56789857e-01
-3.07187706e-01 -7.28439808e-01 3.66172045e-01 2.65859514e-02
4.72043902e-01 5.44474185e-01 7.01275587e-01 -1.86229408e-01
-3.14253330e-01 2.63501238e-02 2.81276107e-01 8.69960338e-02
3.21367055e-01 5.50021883e-03 -6.23822629e-01 -6.52532578e-01
-3.21627766e-01 -1.10618579e+00 5.97403169e-01 3.30009252e-01
1.09242356e+00 1.71956196e-01 -8.35358426e-02 3.56971115e-01
1.14630616e+00 3.32350403e-01 4.34626758e-01 8.21129441e-01
2.24706903e-01 3.73239875e-01 8.64373565e-01 5.91586769e-01
2.10550606e-01 7.04037249e-01 7.37705112e-01 3.68022054e-01
-7.92558566e-02 -1.13830484e-01 3.58335435e-01 4.07239616e-01
-2.73838282e-01 -3.55136720e-03 -9.88370299e-01 2.96462506e-01
-1.87315631e+00 -9.78014171e-01 3.32889557e-01 1.91025269e+00
7.10999012e-01 3.07893813e-01 3.95634621e-01 2.94672012e-01
2.28296369e-01 -4.80390303e-02 -8.99922848e-01 -4.45099831e-01
4.27035093e-01 4.13436800e-01 2.70579636e-01 3.47699851e-01
-1.10610533e+00 9.93331671e-01 6.52383900e+00 3.81667435e-01
-1.23854280e+00 -2.59618193e-01 1.05463527e-01 -2.92511493e-01
5.52942097e-01 -2.77434468e-01 -5.10531008e-01 2.54896015e-01
8.84057879e-01 -2.46960104e-01 8.24493885e-01 9.35535848e-01
2.55849600e-01 -3.39374989e-01 -1.28596437e+00 7.57441878e-01
-5.00559330e-01 -9.39730287e-01 -4.77447927e-01 -7.62195811e-02
6.97130322e-01 4.24750239e-01 2.06669465e-01 8.79068315e-01
7.98794091e-01 -1.05850101e+00 5.49417078e-01 2.75329828e-01
5.63673735e-01 -6.17814124e-01 4.07029539e-01 4.42566007e-01
-9.90006983e-01 -5.07169366e-01 -3.80715281e-01 -9.00615752e-01
-5.14161997e-02 -3.10948223e-01 -7.21509159e-01 3.25668812e-01
7.56808102e-01 9.54765916e-01 -3.63440543e-01 1.08097100e+00
-2.83673227e-01 2.80155003e-01 -4.43536341e-01 -4.01091367e-01
6.87018752e-01 -1.27792284e-01 2.69042015e-01 6.14926338e-01
1.47255525e-01 8.23419094e-02 3.84503901e-01 6.67207718e-01
2.56196350e-01 -2.88800269e-01 -9.00462985e-01 -6.89997673e-02
1.78865552e-01 1.10221815e+00 -6.84378207e-01 -9.71117690e-02
-2.53500104e-01 6.18867218e-01 5.32834232e-01 2.18683630e-01
-8.31216514e-01 -3.74992758e-01 1.10716867e+00 -1.11616872e-01
3.64514083e-01 -8.91922235e-01 -7.29879066e-02 -8.78104389e-01
-1.79295465e-01 -1.01608992e+00 2.27186248e-01 -8.09808791e-01
-1.10093904e+00 1.90293491e-01 3.16433907e-01 -1.25977075e+00
-6.42854631e-01 -9.19893205e-01 -5.78010082e-01 3.87710243e-01
-1.22114635e+00 -5.37656426e-01 -3.86295021e-01 6.56329572e-01
7.22858846e-01 -1.61591843e-01 8.64874005e-01 -2.78726015e-02
-4.60855961e-01 6.92884028e-02 1.15073837e-01 -1.47493869e-01
4.65589434e-01 -1.44263768e+00 4.36299056e-01 1.38273790e-01
-1.72920540e-01 4.72066253e-01 7.94874847e-01 -4.67273444e-01
-1.66012621e+00 -6.20578110e-01 -1.11891754e-01 -4.29363698e-01
9.17520881e-01 -2.70022303e-01 -5.57789266e-01 6.95819616e-01
3.04826826e-01 1.82169620e-02 1.45600736e-01 -4.91643064e-02
1.61661342e-01 2.32473575e-02 -1.04546630e+00 8.43990803e-01
1.20113552e+00 -8.86689872e-02 -8.10106635e-01 2.54603803e-01
3.19244355e-01 -7.02400744e-01 -9.62029636e-01 4.10454452e-01
7.14020133e-01 -9.51374173e-01 8.81782889e-01 -8.99350524e-01
7.35007226e-01 -2.64363199e-01 -1.81967318e-02 -1.75726783e+00
-3.97018462e-01 -4.78125393e-01 -1.44200742e-01 2.98080385e-01
1.19796954e-01 -4.63190496e-01 7.83362567e-01 3.41534093e-02
-2.31687456e-01 -8.47544253e-01 -9.21770513e-01 -8.83687198e-01
5.10133147e-01 -2.33737722e-01 2.66761959e-01 7.09414959e-01
3.38980407e-01 8.52061510e-02 -3.03937435e-01 -1.20075166e-01
3.95362645e-01 1.65567070e-01 1.07880127e+00 -9.74744678e-01
-3.63856077e-01 -5.68378627e-01 -4.98071820e-01 -7.88827181e-01
2.15792030e-01 -6.16384089e-01 2.94489592e-01 -1.50624025e+00
-3.89954984e-01 -3.49209547e-01 -2.99133778e-01 7.42895067e-01
1.73496693e-01 1.32589743e-01 2.36581728e-01 -6.47888929e-02
-6.43830180e-01 7.46352375e-01 1.50615692e+00 8.73279646e-02
-2.99498647e-01 6.99964762e-02 -3.08123320e-01 5.18383563e-01
1.55324888e+00 -2.30438218e-01 -5.23233652e-01 -4.25912797e-01
1.02860220e-01 1.47099018e-01 3.77202094e-01 -1.59005165e+00
-2.87123118e-02 -3.93691361e-01 5.93794346e-01 -1.51305065e-01
5.46980202e-01 -6.80563509e-01 -1.21403135e-01 1.02276790e+00
-5.12942076e-01 5.00300646e-01 4.37166899e-01 5.00034451e-01
4.42323275e-02 9.44700614e-02 6.79189861e-01 -4.17743444e-01
-1.03300416e+00 1.16730489e-01 -7.23231435e-01 1.61891267e-01
1.22889948e+00 -1.09272555e-01 -2.82025725e-01 -3.59643698e-01
-8.84512842e-01 5.26236773e-01 5.11430681e-01 7.34829068e-01
4.27998513e-01 -1.11321151e+00 -4.35236871e-01 2.46725157e-01
-7.87870027e-03 -1.71483874e-01 -1.92621034e-02 7.54464567e-01
-7.25240767e-01 3.49548995e-01 -1.28973377e+00 -3.76110047e-01
-9.31662798e-01 5.29137373e-01 2.51676023e-01 -1.04499735e-01
-8.46596777e-01 3.66602093e-01 -2.03121871e-01 -5.77119291e-01
2.36321628e-01 -6.86136365e-01 -1.03127472e-01 -3.47806513e-01
2.21043363e-01 3.90674829e-01 -9.99524072e-02 -9.02496800e-02
-1.62123799e-01 3.29921752e-01 1.54232204e-01 -6.83784708e-02
1.60957849e+00 2.41134390e-01 3.59424621e-01 5.40781379e-01
6.64485335e-01 -7.23359346e-01 -1.97709668e+00 2.22770810e-01
-6.37104437e-02 -2.50125796e-01 -2.02081457e-01 -7.90873885e-01
-8.74232948e-01 8.89756501e-01 6.94992840e-01 2.13994429e-01
7.73785114e-01 -3.31065595e-01 3.60209972e-01 1.00700057e+00
8.53286266e-01 -1.22264922e+00 4.52335298e-01 9.74121571e-01
1.08012843e+00 -1.26064312e+00 1.25282779e-01 2.84598172e-01
-5.90757787e-01 1.20157039e+00 9.91589308e-01 -6.91842854e-01
5.36419988e-01 4.94957715e-01 5.59566543e-02 -1.26619831e-01
-1.07443106e+00 -4.55344766e-01 -2.76864022e-01 8.68426800e-01
3.19742680e-01 -5.32035865e-02 -1.44865707e-01 1.52919471e-01
-5.48942685e-01 2.98298985e-01 7.08540022e-01 1.52986634e+00
-5.09638369e-01 -1.10327864e+00 -3.62217389e-02 4.69842225e-01
-1.54175818e-01 3.96662682e-01 -2.24159256e-01 1.26324308e+00
-1.19099163e-01 6.95813477e-01 -5.29473610e-02 -3.01009297e-01
4.57348526e-01 -1.19779095e-01 1.06866395e+00 -6.65561557e-01
-5.31709373e-01 -5.40008903e-01 3.41410711e-02 -9.35247540e-01
-3.70467067e-01 -7.80863762e-01 -1.41282201e+00 -3.20317745e-01
1.53371766e-01 -1.21531047e-01 6.27799034e-01 7.10843265e-01
1.52252883e-01 7.41733849e-01 1.38395697e-01 -1.49181533e+00
-9.75926399e-01 -1.09534574e+00 -4.87976164e-01 4.70359594e-01
3.32888782e-01 -1.37475240e+00 -1.18053548e-01 -2.28727594e-01] | [4.324071407318115, 1.2546911239624023] |
2b4c90a8-bfab-4995-a523-5d7089135b80 | bidirectional-self-training-with-multiple | 2204.07730 | null | https://arxiv.org/abs/2204.07730v2 | https://arxiv.org/pdf/2204.07730v2.pdf | Bidirectional Self-Training with Multiple Anisotropic Prototypes for Domain Adaptive Semantic Segmentation | A thriving trend for domain adaptive segmentation endeavors to generate the high-quality pseudo labels for target domain and retrain the segmentor on them. Under this self-training paradigm, some competitive methods have sought to the latent-space information, which establishes the feature centroids (a.k.a prototypes) of the semantic classes and determines the pseudo label candidates by their distances from these centroids. In this paper, we argue that the latent space contains more information to be exploited thus taking one step further to capitalize on it. Firstly, instead of merely using the source-domain prototypes to determine the target pseudo labels as most of the traditional methods do, we bidirectionally produce the target-domain prototypes to degrade those source features which might be too hard or disturbed for the adaptation. Secondly, existing attempts simply model each category as a single and isotropic prototype while ignoring the variance of the feature distribution, which could lead to the confusion of similar categories. To cope with this issue, we propose to represent each category with multiple and anisotropic prototypes via Gaussian Mixture Model, in order to fit the de facto distribution of source domain and estimate the likelihood of target samples based on the probability density. We apply our method on GTA5->Cityscapes and Synthia->Cityscapes tasks and achieve 61.2 and 62.8 respectively in terms of mean IoU, substantially outperforming other competitive self-training methods. Noticeably, in some categories which severely suffer from the categorical confusion such as "truck" and "bus", our method achieves 56.4 and 68.8 respectively, which further demonstrates the effectiveness of our design. | ['Jun Xiao', 'Yi Yang', 'Zheyang Li', 'Li Zhang', 'Yawei Luo', 'Yulei Lu'] | 2022-04-16 | null | null | null | null | ['synthetic-to-real-translation'] | ['computer-vision'] | [ 1.00161590e-01 2.76621103e-01 -2.93605119e-01 -4.89248395e-01
-8.34923267e-01 -8.75999749e-01 6.28209770e-01 -3.32498431e-01
-3.74966502e-01 6.96079791e-01 4.04141657e-02 -2.39591494e-01
-1.13516062e-01 -5.95429778e-01 -4.67585951e-01 -1.00272918e+00
3.91788185e-01 8.58444512e-01 4.47855234e-01 4.87112962e-02
2.80884385e-01 2.76306480e-01 -1.57542360e+00 2.32776344e-01
1.44976199e+00 8.08195174e-01 1.13065809e-01 3.25855494e-01
-3.96766424e-01 1.12830885e-01 -6.82496190e-01 -3.71366024e-01
3.31810951e-01 -3.79720092e-01 -8.46274734e-01 5.12188554e-01
2.55500376e-01 -5.01073562e-02 -2.84082126e-02 1.21691096e+00
9.01787505e-02 2.50353426e-01 1.40158176e+00 -1.19717991e+00
-5.66864133e-01 5.43315470e-01 -8.04048717e-01 -8.85605961e-02
-5.56893535e-02 -9.07526612e-02 7.46552408e-01 -7.84260273e-01
5.14797151e-01 1.12036550e+00 5.96341670e-01 7.18311071e-01
-1.25570846e+00 -7.52822697e-01 2.75245577e-01 8.50460455e-02
-1.52448821e+00 -4.71976131e-01 7.79649198e-01 -4.83314931e-01
2.77512193e-01 2.92656541e-01 3.91109705e-01 1.24707484e+00
-3.43165010e-01 9.61018920e-01 1.12664926e+00 -4.03280884e-01
3.30424011e-01 5.30835092e-01 2.91102380e-01 2.51065224e-01
5.07488586e-02 -1.88678458e-01 1.00691989e-02 -8.34774449e-02
7.05468237e-01 -2.27818474e-01 -5.29041179e-02 -6.23240829e-01
-1.05772376e+00 8.10227454e-01 2.35021397e-01 4.00868595e-01
-2.12370753e-01 -4.16298836e-01 1.33159950e-01 1.39061622e-02
5.13347328e-01 2.68432111e-01 -5.13676763e-01 -1.56903658e-02
-1.17969441e+00 -2.42951047e-02 5.72005749e-01 1.21415687e+00
6.74351752e-01 -4.28057127e-02 1.11243576e-02 1.26050735e+00
5.06276965e-01 3.67754787e-01 7.52840936e-01 -9.95353043e-01
4.10764128e-01 6.74689591e-01 2.33395338e-01 -6.21696174e-01
-2.34246120e-01 -7.49871016e-01 -7.70284116e-01 7.39094839e-02
7.54382014e-01 -4.29198109e-02 -1.49941218e+00 1.67377973e+00
4.72497463e-01 1.53052852e-01 3.35884541e-01 8.29942822e-01
4.21166599e-01 5.77504873e-01 5.80166988e-02 -1.27701536e-01
1.21981871e+00 -1.07142246e+00 -3.29482824e-01 -2.53244966e-01
5.10891676e-01 -8.76730800e-01 1.13272452e+00 3.39427590e-01
-7.73468196e-01 -7.30534554e-01 -8.40046585e-01 4.50867325e-01
-4.70174015e-01 2.05275804e-01 4.39466774e-01 7.26103008e-01
-8.44705999e-01 4.59502906e-01 -7.59419799e-01 -3.74560326e-01
3.18010241e-01 3.11928660e-01 -8.59548673e-02 5.76545447e-02
-1.00061631e+00 5.78201115e-01 5.58849633e-01 -9.16259512e-02
-7.31095016e-01 -4.13933903e-01 -5.71062565e-01 -1.36729255e-01
2.42974788e-01 -4.01868522e-01 1.07815349e+00 -1.24321437e+00
-1.59743404e+00 8.05640280e-01 -1.91541478e-01 -1.25368744e-01
6.26756191e-01 1.59083739e-01 -5.76682568e-01 5.95104098e-02
5.34413755e-01 1.01925313e+00 9.43246067e-01 -1.63946021e+00
-1.03135455e+00 -2.60135442e-01 -2.86135018e-01 4.02051836e-01
-3.57191473e-01 -2.40738124e-01 -6.79861307e-01 -5.83895683e-01
7.37557769e-01 -1.12987614e+00 -2.59424061e-01 -5.00307322e-01
-5.30660093e-01 -4.62390691e-01 6.40385807e-01 -3.92525494e-01
1.05852151e+00 -2.33334374e+00 -2.28691418e-02 4.84040141e-01
2.04195991e-01 3.14877301e-01 6.73457310e-02 -1.31443933e-01
1.68925505e-02 7.50506893e-02 -4.18491334e-01 -2.58524448e-01
1.21401817e-01 3.35829735e-01 -2.88398415e-01 4.63166237e-01
-7.44243339e-02 5.58802187e-01 -8.02041948e-01 -6.99298680e-01
5.80460839e-02 2.96329439e-01 -4.56886142e-01 4.27795239e-02
-5.88183030e-02 5.88324070e-01 -5.42507410e-01 5.56538999e-01
8.88362706e-01 -1.02965921e-01 4.98492084e-02 1.03744278e-02
-4.93752658e-02 2.71980371e-02 -1.37630975e+00 1.36225867e+00
-7.71296024e-02 3.29565823e-01 6.98937476e-03 -1.15399170e+00
1.04877067e+00 2.07958683e-01 5.43610632e-01 -4.32153344e-01
-2.30963356e-04 5.59732974e-01 -6.92169275e-03 -2.91900903e-01
4.26085681e-01 -1.94791600e-01 -2.50004113e-01 8.67060050e-02
-1.90013722e-02 -8.40740353e-02 8.98518786e-02 -4.66983430e-02
6.21236265e-01 3.63631189e-01 -1.58801138e-01 -2.98646778e-01
3.71041030e-01 2.65965879e-01 6.02713406e-01 7.23871350e-01
-3.95120025e-01 9.06791925e-01 3.02289307e-01 -9.57943797e-02
-1.09432364e+00 -1.49820530e+00 -4.58073407e-01 9.66236770e-01
2.56827474e-01 2.07833409e-01 -9.91036773e-01 -1.01063645e+00
-1.94194674e-01 9.47597325e-01 -4.46110010e-01 -1.62392721e-01
-3.95053983e-01 -8.45233679e-01 5.69827676e-01 3.89501482e-01
5.58763862e-01 -8.49883020e-01 -2.69789547e-01 2.76855558e-01
-4.60815161e-01 -8.35014284e-01 -4.65745121e-01 3.64268124e-01
-1.00272334e+00 -7.28407919e-01 -1.16441059e+00 -9.92493689e-01
8.55755270e-01 1.52827948e-01 8.11460376e-01 -4.59895074e-01
2.74864793e-01 -2.71900706e-02 -4.68724281e-01 -8.93896073e-02
-5.45318246e-01 4.01203692e-01 1.38187602e-01 2.37807497e-01
5.31872749e-01 -5.92464805e-01 -5.46589494e-01 7.62533426e-01
-6.66458488e-01 7.73238018e-02 5.96718907e-01 7.12238133e-01
6.62173629e-01 3.46694499e-01 7.50795841e-01 -9.53682840e-01
4.50771868e-01 -8.18268836e-01 -3.53358984e-01 2.49118552e-01
-6.56096637e-01 -6.30601123e-02 6.58389986e-01 -7.82890439e-01
-1.23164618e+00 2.10776329e-01 -1.05661288e-01 -4.38481539e-01
-8.07332218e-01 1.76270410e-01 -2.73552805e-01 3.81685823e-01
8.10933709e-01 3.00755948e-01 -2.81709373e-01 -5.47295392e-01
4.38475639e-01 1.21356618e+00 5.70085526e-01 -6.27939820e-01
8.08379948e-01 3.72633874e-01 -4.98098582e-01 -6.12681031e-01
-8.65584314e-01 -8.38344932e-01 -9.03861046e-01 -3.87180038e-02
9.16856587e-01 -7.66294360e-01 2.00469829e-02 4.29369718e-01
-9.40599561e-01 -2.17613339e-01 -3.04929227e-01 6.01689756e-01
-5.98743498e-01 4.16832149e-01 -3.61995906e-01 -7.91761756e-01
3.97506729e-02 -1.29918671e+00 9.41807091e-01 4.27257150e-01
-2.41045013e-01 -9.67181563e-01 -2.31332287e-01 3.95107210e-01
2.86483705e-01 -3.83871272e-02 9.13552642e-01 -8.63599122e-01
-1.60014421e-01 -1.85784951e-01 -3.52673411e-01 3.57551813e-01
2.54638761e-01 -2.27522030e-02 -1.12006521e+00 -1.64853349e-01
6.99982122e-02 1.73179694e-02 5.68627000e-01 5.33405900e-01
9.48942840e-01 -2.24960949e-02 -6.29074752e-01 6.63457036e-01
1.12018180e+00 6.45746589e-01 5.05030215e-01 3.57061446e-01
6.64604783e-01 7.39474833e-01 6.78793907e-01 1.04443863e-01
4.50429261e-01 7.27409482e-01 7.84060359e-02 -2.53300190e-01
-1.91274360e-01 -2.28720814e-01 2.44548187e-01 8.89673471e-01
1.13124736e-01 -2.17714965e-01 -9.58044827e-01 7.72143900e-01
-1.76066840e+00 -6.14023387e-01 -2.34839574e-01 2.14026856e+00
9.16422129e-01 3.40164721e-01 2.45887637e-01 3.64170149e-02
9.74006951e-01 -2.69910574e-01 -7.01543331e-01 -1.87403634e-01
-3.55858244e-02 -8.92654583e-02 5.87515891e-01 3.98633301e-01
-1.19410169e+00 1.14066851e+00 6.38311148e+00 1.26604223e+00
-9.91494536e-01 3.64444591e-02 8.07693839e-01 3.36853743e-01
-2.91186571e-01 5.07904030e-02 -9.30896699e-01 6.88284159e-01
8.61063778e-01 1.62453219e-01 2.88556218e-01 9.60302114e-01
-4.14133482e-02 -1.26332834e-01 -7.72481680e-01 7.95144618e-01
-1.43803596e-01 -6.66756630e-01 -3.30630727e-02 2.23096058e-01
9.17399526e-01 -6.69515580e-02 2.67617404e-01 4.81437594e-01
4.52128977e-01 -7.86913455e-01 9.00180459e-01 2.54152834e-01
8.22014749e-01 -6.45300329e-01 6.13286614e-01 5.75478256e-01
-1.00141048e+00 1.17197796e-03 -6.12735331e-01 2.89355576e-01
3.52295414e-02 4.87484425e-01 -1.00977862e+00 4.65758532e-01
5.93133628e-01 2.59800613e-01 -5.61181366e-01 1.15073562e+00
-1.13061769e-02 8.97214055e-01 -6.10043347e-01 2.62389094e-01
5.38529932e-01 -3.99212509e-01 4.66476172e-01 1.11764276e+00
4.94497240e-01 -2.51255959e-01 2.45854497e-01 9.19901311e-01
2.34303176e-01 1.89410076e-01 -3.62449735e-01 2.30526537e-01
5.51105678e-01 1.04799378e+00 -1.32718694e+00 -5.61769426e-01
-2.04833075e-01 1.05236518e+00 1.29046127e-01 6.56726122e-01
-1.16251767e+00 -3.96689594e-01 3.70535374e-01 2.95744538e-02
2.42974743e-01 -1.36226356e-01 -5.79407096e-01 -1.16810977e+00
-6.55441359e-02 -7.83089340e-01 4.20875967e-01 -4.77308124e-01
-1.32862723e+00 8.53645742e-01 3.35231632e-01 -1.49049449e+00
-2.61365414e-01 -4.15706605e-01 -4.50101554e-01 8.47611725e-01
-1.31950879e+00 -1.10457444e+00 -6.93518147e-02 5.90002000e-01
7.70114183e-01 -2.25866720e-01 6.26568913e-01 4.10813421e-01
-4.96655524e-01 7.72175610e-01 5.65253913e-01 9.24294665e-02
7.52430439e-01 -1.30081928e+00 3.29019248e-01 6.90363109e-01
2.89037794e-01 5.54663301e-01 6.44571662e-01 -5.90086997e-01
-4.93655443e-01 -8.88019502e-01 7.15425670e-01 -4.53338206e-01
5.21628261e-01 -3.28409672e-01 -8.65903735e-01 4.49089676e-01
-1.83887854e-01 -2.50171512e-01 5.60517967e-01 6.79324940e-02
-1.88862264e-01 6.20177500e-02 -1.25361490e+00 7.33349025e-01
1.03030694e+00 -1.65315136e-01 -6.92682385e-01 2.70866871e-01
5.19373715e-01 -2.44198367e-01 -6.33754611e-01 4.14216131e-01
3.61654818e-01 -9.41616058e-01 8.87748599e-01 -2.92218238e-01
-3.23194661e-03 -4.46487606e-01 -1.30687147e-01 -1.42572153e+00
-4.24951166e-01 -1.41744331e-01 3.16109985e-01 1.62728608e+00
6.96464300e-01 -7.59428859e-01 1.17748857e+00 6.27913952e-01
-4.48488295e-01 -5.70159972e-01 -1.07618809e+00 -8.03274930e-01
3.85777265e-01 -4.44437623e-01 7.23078609e-01 1.07998610e+00
-2.59668738e-01 2.28038236e-01 -5.91972470e-02 2.21830294e-01
6.51670396e-01 2.06481129e-01 5.29654562e-01 -1.26657593e+00
-2.07083806e-01 -6.52612269e-01 7.17040151e-03 -1.37101948e+00
2.04744369e-01 -9.20652807e-01 2.76778728e-01 -1.40722311e+00
-2.01886594e-02 -1.11954486e+00 -3.27302635e-01 3.28362733e-01
-5.29485568e-02 3.64004135e-01 -1.73892990e-01 6.16370499e-01
-5.30322313e-01 3.39175850e-01 1.21463633e+00 -1.05662651e-01
-5.22985876e-01 3.85792911e-01 -7.56843865e-01 9.25482035e-01
9.01189387e-01 -5.23827255e-01 -5.77672601e-01 -3.65618438e-01
-4.22831744e-01 -2.15965956e-01 -4.22864268e-03 -1.09434700e+00
7.64621720e-02 -3.92630577e-01 4.49452460e-01 -5.58686852e-01
2.53570199e-01 -1.02089262e+00 2.11842909e-01 1.03492454e-01
-1.01615563e-01 -4.23249930e-01 -1.60019025e-01 3.76141608e-01
-3.00591826e-01 -5.26394248e-01 9.72252488e-01 -8.95429924e-02
-6.56144738e-01 6.74790591e-02 -5.31413674e-01 6.22621067e-02
1.10883570e+00 -7.35119700e-01 -6.57029497e-03 -2.08778158e-01
-8.69600952e-01 1.86791971e-01 6.19160652e-01 2.34677017e-01
3.01895201e-01 -1.22285247e+00 -4.94133621e-01 4.43812400e-01
9.47965160e-02 3.50007117e-01 1.39242157e-01 7.46002078e-01
-2.52446920e-01 2.66557485e-01 -1.52140766e-01 -7.84809589e-01
-7.76176393e-01 5.44996440e-01 3.61177355e-01 -1.49014041e-01
-4.47395086e-01 8.58003914e-01 4.64977890e-01 -5.49434543e-01
2.42298156e-01 -1.75845414e-01 -4.92064595e-01 2.39635244e-01
-6.52402341e-02 2.82042831e-01 -1.94075480e-01 -8.60356867e-01
-2.53622115e-01 7.19922185e-01 -1.09001637e-01 -2.30708078e-01
1.02073157e+00 -3.41701925e-01 2.90390015e-01 3.74447465e-01
1.10178220e+00 8.54908228e-02 -1.51162207e+00 -1.10136390e-01
3.46766442e-01 -3.02200079e-01 -3.13733310e-01 -8.14731061e-01
-9.43982124e-01 8.09949696e-01 7.34747410e-01 3.56400281e-01
9.26709950e-01 2.61603594e-01 6.57485008e-01 -1.87751234e-01
3.18654269e-01 -1.37987173e+00 -1.53023764e-01 4.87233043e-01
3.01976860e-01 -1.12081456e+00 -4.35660034e-01 -5.64691782e-01
-8.92053306e-01 9.32992458e-01 6.29692554e-01 -7.63339847e-02
4.74418133e-01 -6.94825053e-02 3.71489197e-01 6.41206875e-02
-1.21115722e-01 -3.00778061e-01 5.10137796e-01 8.03310275e-01
1.74508035e-01 3.17985088e-01 -1.72370881e-01 7.58047223e-01
-2.78126746e-01 -2.99377084e-01 2.95771301e-01 5.18959820e-01
-5.18293262e-01 -1.21125269e+00 -5.28080463e-01 4.40338820e-01
-2.95131624e-01 1.03399001e-01 -1.31065592e-01 5.69989145e-01
4.60680574e-01 1.03067195e+00 1.53815195e-01 -3.72435749e-01
3.13044101e-01 3.55795592e-01 9.95169058e-02 -6.22198105e-01
-1.20803356e-01 5.77291369e-01 -3.86468805e-02 8.85947272e-02
-2.79625237e-01 -6.33120418e-01 -1.37545633e+00 3.89084890e-02
-5.12736857e-01 4.01985943e-01 5.90740442e-01 8.84634614e-01
1.22735634e-01 2.23327070e-01 6.11391604e-01 -7.29935944e-01
-6.03572667e-01 -1.04148698e+00 -6.05650783e-01 6.37729645e-01
-4.18842733e-02 -9.58092034e-01 -5.38750172e-01 7.22581074e-02] | [9.629524230957031, 1.3837283849716187] |
24c4842e-e2e1-4f9e-844a-3945a8715569 | scalable-and-robust-self-learning-for-skill | 2204.07135 | null | https://arxiv.org/abs/2204.07135v1 | https://arxiv.org/pdf/2204.07135v1.pdf | Scalable and Robust Self-Learning for Skill Routing in Large-Scale Conversational AI Systems | Skill routing is an important component in large-scale conversational systems. In contrast to traditional rule-based skill routing, state-of-the-art systems use a model-based approach to enable natural conversations. To provide supervision signal required to train such models, ideas such as human annotation, replication of a rule-based system, relabeling based on user paraphrases, and bandit-based learning were suggested. However, these approaches: (a) do not scale in terms of the number of skills and skill on-boarding, (b) require a very costly expert annotation/rule-design, (c) introduce risks in the user experience with each model update. In this paper, we present a scalable self-learning approach to explore routing alternatives without causing abrupt policy changes that break the user experience, learn from the user interaction, and incrementally improve the routing via frequent model refreshes. To enable such robust frequent model updates, we suggest a simple and effective approach that ensures controlled policy updates for individual domains, followed by an off-policy evaluation for making deployment decisions without any need for lengthy A/B experimentation. We conduct various offline and online A/B experiments on a commercial large-scale conversational system to demonstrate the effectiveness of the proposed method in real-world production settings. | ['Sungjin Lee', 'Jin-Myung Won', 'Sarthak Ahuja', 'Jinseok Nam', 'Mohammad Kachuee'] | 2022-04-14 | null | https://aclanthology.org/2022.naacl-industry.1 | https://aclanthology.org/2022.naacl-industry.1.pdf | naacl-acl-2022-7 | ['self-learning'] | ['natural-language-processing'] | [ 1.79806367e-01 3.09858024e-01 -1.73562303e-01 -4.31208640e-01
-6.49059951e-01 -7.73791254e-01 5.15694201e-01 1.27153739e-01
-4.07633275e-01 1.07921612e+00 2.00440705e-01 -5.98240793e-01
-3.09678495e-01 -4.48354423e-01 -4.20720816e-01 -4.18881774e-01
1.15536377e-01 9.72387552e-01 6.54287636e-01 -5.35913110e-01
3.83425236e-01 2.01045603e-01 -1.46023822e+00 2.80239075e-01
1.10788655e+00 7.96072185e-01 3.83313119e-01 9.31071401e-01
-3.75178307e-01 1.04208505e+00 -7.11813271e-01 -1.06730632e-01
2.16807470e-01 -5.25144875e-01 -1.10081518e+00 2.13450313e-01
-6.52058795e-02 -4.88703132e-01 -8.75364393e-02 5.94430625e-01
5.47417939e-01 4.88310277e-01 2.17562631e-01 -1.34479356e+00
-8.99936855e-02 6.72655284e-01 -2.66185135e-01 1.61826968e-01
7.05832124e-01 4.34641451e-01 6.11531436e-01 -1.54674858e-01
3.11840266e-01 1.40317953e+00 5.86609423e-01 7.52681851e-01
-1.10366285e+00 -5.73458016e-01 6.34871483e-01 3.01649403e-02
-9.26003695e-01 -5.68822742e-01 7.24218488e-01 -2.37062752e-01
9.92293656e-01 4.04588252e-01 8.31789970e-01 1.14991653e+00
-1.77607268e-01 5.82152843e-01 1.35666430e+00 -5.25866747e-01
3.74224544e-01 5.11341572e-01 1.50286421e-01 8.14357221e-01
-1.86820999e-01 -1.91047028e-01 -5.59468448e-01 -6.17730916e-01
6.94579601e-01 2.39415411e-02 -8.94159749e-02 -8.26834589e-02
-7.81274557e-01 5.13976336e-01 -1.07760072e-01 1.39585733e-01
-4.42831427e-01 -7.60466903e-02 4.11576509e-01 7.45303392e-01
2.45456830e-01 6.32583320e-01 -8.38792980e-01 -9.08956110e-01
-6.24900222e-01 1.95871532e-01 1.31630993e+00 8.97583246e-01
6.54988825e-01 -2.90602952e-01 -2.20264792e-01 9.47858691e-01
1.02557138e-01 2.03541338e-01 6.76256299e-01 -1.34400523e+00
4.86547679e-01 6.60563946e-01 5.94366550e-01 -6.01793647e-01
-4.66836691e-01 1.33695453e-01 -4.61906284e-01 -1.04677461e-01
4.06656861e-01 -5.91381073e-01 -6.28923178e-01 1.63060749e+00
3.91295403e-01 3.59598219e-01 -6.34266138e-02 4.24214661e-01
2.68485516e-01 5.62776625e-01 -3.45181897e-02 -6.43473864e-01
1.03797841e+00 -1.11672866e+00 -7.21502841e-01 -2.51963884e-01
5.30224264e-01 -6.73875570e-01 1.56154215e+00 7.05441833e-01
-1.18987477e+00 -5.08463085e-01 -6.92959249e-01 5.22518456e-01
-9.13834274e-02 -4.75363642e-01 6.01847231e-01 6.87987685e-01
-9.19484019e-01 6.82635844e-01 -7.34465778e-01 -6.73557699e-01
-3.43412071e-01 4.76474047e-01 1.22730643e-01 1.74065068e-01
-1.21221256e+00 1.06166470e+00 2.76327282e-01 4.38451068e-03
-7.71693885e-01 -3.08362126e-01 -4.54728186e-01 1.19600251e-01
7.62259841e-01 -4.76375312e-01 1.94934809e+00 -1.09141767e+00
-2.32071900e+00 3.72545779e-01 -1.17886234e-02 -1.59519270e-01
5.34174204e-01 -2.98611522e-01 -3.06866258e-01 -5.16956262e-02
-3.84148657e-01 1.91539735e-01 6.97703600e-01 -1.32941067e+00
-9.84021008e-01 1.44105449e-01 5.93464255e-01 6.11806095e-01
-4.26389605e-01 3.66292521e-02 -3.61771733e-01 -1.15336142e-01
-3.40714067e-01 -1.24409425e+00 -2.84075439e-01 -6.03458345e-01
9.50613432e-03 -4.42364335e-01 6.55203462e-01 -5.96850216e-01
1.62309551e+00 -1.90542269e+00 -4.25362661e-02 3.37440401e-01
-2.44209379e-01 5.40088356e-01 -3.19303647e-02 7.17818499e-01
4.52055275e-01 1.78651780e-01 1.06007293e-01 -3.05799395e-01
-8.76547245e-04 3.97143066e-01 -2.84553375e-02 -3.07561476e-02
-3.14930201e-01 4.58211154e-01 -9.09575522e-01 -5.95483899e-01
2.47652546e-01 -2.14071587e-01 -8.73065472e-01 7.39926219e-01
-5.88358343e-01 6.41717911e-01 -4.32035595e-01 3.34393233e-01
7.11212829e-02 -3.07693303e-01 4.95116830e-01 4.07342196e-01
1.74190030e-02 5.19500971e-01 -1.17232990e+00 1.42664480e+00
-9.65195417e-01 4.55356762e-02 4.06567961e-01 -8.93860102e-01
7.28881061e-01 6.23905122e-01 3.95321518e-01 -4.45024341e-01
-2.35486235e-02 -2.11733431e-01 1.10515684e-01 -6.57963812e-01
2.66108304e-01 2.09104002e-01 -2.44584098e-01 8.36475372e-01
-1.82562158e-01 -1.48144633e-01 1.19974114e-01 1.46759972e-01
1.14711618e+00 7.31138587e-02 4.86844748e-01 3.20452005e-02
5.34373105e-01 -1.50647596e-01 7.01861680e-01 1.06004024e+00
-4.12539393e-01 -4.30284776e-02 4.79159236e-01 -3.71874511e-01
-6.07264996e-01 -4.20361847e-01 4.94960368e-01 1.69992828e+00
1.89488456e-01 -3.39028507e-01 -9.08410788e-01 -8.94369066e-01
-1.35403708e-01 7.21500397e-01 -1.63334250e-01 -2.02265903e-01
-6.76548898e-01 -3.82853180e-01 3.09459180e-01 2.25637808e-01
7.48907149e-01 -1.39037108e+00 -4.28666502e-01 5.57188511e-01
-3.75011772e-01 -9.58757579e-01 -6.82657421e-01 1.45981744e-01
-7.50158787e-01 -9.39411938e-01 -6.70164675e-02 -5.70265651e-01
5.55163622e-01 1.03568047e-01 1.04224515e+00 3.88357848e-01
3.09594393e-01 4.13894385e-01 -4.31516439e-01 -2.78561592e-01
-6.28749192e-01 2.75839597e-01 4.39967722e-01 -2.02080920e-01
1.38870940e-01 -7.56558776e-01 -6.64187312e-01 6.52251959e-01
-3.49211574e-01 -3.21913771e-02 5.52978158e-01 9.38206136e-01
5.32070696e-02 1.47345930e-01 9.17979419e-01 -1.30637121e+00
1.31474864e+00 -3.26560438e-01 -5.33112466e-01 6.33553863e-01
-1.04734635e+00 3.94908860e-02 7.27578402e-01 -6.94543779e-01
-1.41077137e+00 -1.11015260e-01 -8.15266967e-02 -1.27439387e-02
-3.74648124e-01 3.29812318e-01 1.01854473e-01 1.51072726e-01
7.99579263e-01 1.78660706e-01 5.39416224e-02 -4.18668240e-01
3.17740381e-01 1.29300117e+00 1.67811617e-01 -9.42927897e-01
5.11214793e-01 -1.63700685e-01 -8.02452505e-01 -5.78043342e-01
-8.71759415e-01 -5.35097182e-01 -2.60864556e-01 -2.68397421e-01
4.11170721e-01 -7.78080642e-01 -1.13600254e+00 3.31963807e-01
-8.15351725e-01 -9.49207723e-01 7.81178847e-02 6.25572503e-02
-6.73341990e-01 2.27160096e-01 -5.96709192e-01 -1.14283800e+00
-4.77477968e-01 -9.39573824e-01 4.76069927e-01 6.14049613e-01
-7.74801195e-01 -9.30396616e-01 5.51239029e-02 7.14734674e-01
7.11230576e-01 -3.92013758e-01 8.00762177e-01 -9.53317463e-01
-2.05687016e-01 -2.68971562e-01 2.19590172e-01 2.46442586e-01
3.23659092e-01 -8.83479565e-02 -7.87830353e-01 -5.40905893e-01
-2.90973306e-01 -7.32972026e-01 -1.57878324e-02 3.48574482e-02
1.13845861e+00 -7.14172006e-01 -1.70147762e-01 3.13172080e-02
6.52260661e-01 5.20345628e-01 1.26000345e-01 2.96443254e-01
3.19793552e-01 4.53943133e-01 9.17500854e-01 6.68877542e-01
4.20778930e-01 6.87925756e-01 -5.60476854e-02 5.90267368e-02
2.95911133e-01 -5.45282841e-01 4.84664977e-01 8.52987826e-01
-9.16812792e-02 -1.53514788e-01 -6.61099732e-01 3.62828821e-01
-2.21789336e+00 -7.94548154e-01 7.61914730e-01 2.21473265e+00
1.26478422e+00 7.60782421e-01 6.46725059e-01 -1.26603097e-01
6.08236432e-01 -1.60990328e-01 -5.60322702e-01 -6.91626012e-01
7.61064112e-01 -1.65288784e-02 2.42338032e-01 8.68047476e-01
-6.36157990e-01 1.18331933e+00 6.66448450e+00 5.08246064e-01
-1.02044797e+00 1.84244812e-01 5.12614369e-01 -1.71850219e-01
-5.94684184e-02 9.37431008e-02 -8.03185940e-01 6.62271440e-01
1.08231246e+00 -1.95610911e-01 9.05111253e-01 1.09771132e+00
5.50564885e-01 -3.43018740e-01 -9.92582083e-01 7.48777926e-01
-4.47116226e-01 -9.53127503e-01 -3.45909595e-01 -2.59702414e-01
6.50559783e-01 -2.61827707e-01 -4.94772702e-01 8.08499992e-01
9.30390298e-01 -5.85345507e-01 2.60029256e-01 4.79942650e-01
5.41162729e-01 -7.99847066e-01 7.05498636e-01 1.01074469e+00
-7.08550513e-01 -4.03789401e-01 -1.45313501e-01 -4.19946492e-01
1.96287110e-01 5.07842675e-02 -1.02512014e+00 1.25930272e-02
7.06434488e-01 -1.08315960e-01 -1.53040111e-01 6.36620104e-01
-2.05299169e-01 9.09761190e-01 -4.16304410e-01 -3.69324207e-01
1.23594195e-01 -4.78091426e-02 2.34535143e-01 1.12914026e+00
-2.51054186e-02 4.45290476e-01 8.08753431e-01 1.46393999e-01
1.01981662e-01 -1.28343599e-02 -4.92576003e-01 2.71581300e-02
1.11900330e+00 1.05455828e+00 -5.61960578e-01 -4.11583304e-01
-3.28659922e-01 8.78106058e-01 4.15910810e-01 4.08612102e-01
-6.47285461e-01 -2.35765696e-01 5.65071344e-01 3.20376277e-01
3.26746106e-02 -1.01244561e-01 7.72038326e-02 -7.72618234e-01
-1.23810157e-01 -1.33282268e+00 3.19411546e-01 -4.05304343e-01
-1.06921041e+00 5.69345415e-01 2.00328067e-01 -8.54088247e-01
-7.07601964e-01 3.25138308e-02 -7.93736875e-01 5.89700758e-01
-1.16136813e+00 -5.97434103e-01 -2.86263406e-01 6.77272379e-01
8.02700400e-01 -2.99567699e-01 1.06798232e+00 2.75448076e-02
-7.06653953e-01 6.48493409e-01 -2.10655153e-01 -3.09931368e-01
8.82025540e-01 -1.29515612e+00 2.72427678e-01 4.52461779e-01
-2.71341920e-01 8.20513189e-01 9.67419088e-01 -6.89916015e-01
-1.03736901e+00 -6.14662290e-01 6.93937123e-01 -3.47541779e-01
5.77354491e-01 -4.25822496e-01 -7.99893856e-01 7.67373204e-01
3.49262804e-01 -3.88929158e-01 6.43692732e-01 6.39898658e-01
2.49019444e-01 -3.49438161e-01 -1.25637412e+00 6.73266351e-01
1.05074930e+00 -3.74420613e-01 -6.03802860e-01 4.55293298e-01
8.35838377e-01 -3.77288520e-01 -6.99717522e-01 2.26681620e-01
4.62440282e-01 -8.40466976e-01 3.89645964e-01 -7.33889878e-01
-1.66120514e-01 6.27808273e-02 2.55884528e-01 -1.55710840e+00
-3.62613797e-01 -1.54036653e+00 -4.42841560e-01 1.22450185e+00
5.46460629e-01 -6.30048990e-01 6.99607253e-01 1.15850294e+00
9.28077623e-02 -9.21160758e-01 -5.46873987e-01 -5.50969660e-01
-4.43730831e-01 -5.87035306e-02 6.18958652e-01 8.26440096e-01
5.83828866e-01 4.30864513e-01 -8.37616086e-01 1.12762339e-02
6.73563108e-02 -1.23714264e-02 1.09645474e+00 -1.19304371e+00
-7.16648996e-01 -1.65850952e-01 4.36630666e-01 -1.37402296e+00
1.11980602e-01 -7.48830512e-02 3.46311063e-01 -1.41388667e+00
-8.31456929e-02 -6.79006934e-01 -4.30892885e-01 5.75497508e-01
-2.81157821e-01 -5.71547031e-01 1.94060262e-02 1.32588103e-01
-1.09892666e+00 2.25256100e-01 1.01973307e+00 2.69964188e-01
-8.19238663e-01 5.96023202e-01 -8.77146184e-01 8.90632570e-01
9.16838884e-01 -3.54771346e-01 -9.33336556e-01 8.32148045e-02
1.09292515e-01 5.53313613e-01 -3.88131410e-01 -7.69040287e-01
4.17219341e-01 -7.15436399e-01 -2.23558575e-01 3.03920787e-02
2.45405108e-01 -9.69541490e-01 -1.37453854e-01 3.31472903e-01
-4.38434154e-01 2.00596765e-01 2.03552600e-02 5.88352621e-01
-2.41400525e-02 -1.60131097e-01 7.48930037e-01 -4.36104834e-01
-6.05102479e-01 -1.79076884e-02 -6.53664887e-01 -5.46484664e-02
1.13902044e+00 -1.45286277e-01 -1.59191489e-01 -9.07833338e-01
-7.11467087e-01 7.44654238e-01 3.23179543e-01 4.69565064e-01
1.21519670e-01 -7.58040071e-01 -2.20659122e-01 7.87137076e-02
1.02396592e-01 -3.60632390e-02 1.01418480e-01 4.56549078e-01
-2.84679860e-01 3.11112136e-01 -8.01544636e-02 -3.34805042e-01
-1.42596209e+00 3.62185448e-01 3.71794850e-01 -6.93087816e-01
-4.20733213e-01 7.80403078e-01 -3.80515635e-01 -7.35676825e-01
8.50760758e-01 -1.69074103e-01 -1.55644447e-01 -9.93122458e-02
3.27828795e-01 2.60398060e-01 6.43154047e-03 2.62638807e-01
-1.51009768e-01 3.57790738e-02 -3.30975264e-01 -3.64038259e-01
1.00488186e+00 -4.40177500e-01 2.09846124e-01 5.92162848e-01
2.86702245e-01 -1.91358417e-01 -1.55871189e+00 -6.05495274e-01
1.67047784e-01 -3.78332257e-01 -2.03425944e-01 -1.15142906e+00
-3.69992942e-01 2.93585092e-01 4.66553420e-01 5.54638028e-01
1.09223890e+00 -2.42965445e-01 8.23821902e-01 9.31343079e-01
5.78683376e-01 -1.73614216e+00 2.04424620e-01 4.97033626e-01
7.09177077e-01 -1.35140312e+00 -1.03493042e-01 -9.62319672e-02
-1.14063787e+00 6.45818233e-01 1.11962271e+00 3.40582103e-01
6.29313469e-01 2.45644212e-01 3.62255722e-01 3.03304251e-02
-1.35111308e+00 3.46250869e-02 -2.99129188e-01 3.95127207e-01
3.74540418e-01 8.43395740e-02 -2.84106672e-01 5.55695176e-01
-1.45768240e-01 1.77396074e-01 3.42163712e-01 1.21384084e+00
-7.54340410e-01 -1.30274439e+00 -1.01974577e-01 5.57802916e-01
-1.85407221e-01 1.69211715e-01 -4.88875777e-01 4.99576867e-01
-1.23940229e-01 1.28083849e+00 -2.23535344e-01 -4.02780890e-01
6.97088838e-01 5.06018758e-01 3.51684302e-01 -8.00949931e-01
-8.50702763e-01 3.20998505e-02 6.61676586e-01 -5.20034730e-01
-1.69559121e-01 -6.24141634e-01 -1.13225198e+00 -6.14012659e-01
-4.28395748e-01 4.94990319e-01 2.50416487e-01 1.16354132e+00
4.09115821e-01 3.98561090e-01 9.50234950e-01 -5.96618295e-01
-9.58702505e-01 -1.59335208e+00 -3.94564509e-01 5.02493739e-01
9.84835103e-02 -6.51224017e-01 -2.59259164e-01 -9.10226628e-02] | [12.904173851013184, 7.9771013259887695] |
6f4ebd2b-9ac8-43a0-8490-3b886121a1d5 | amark-automated-marking-and-processing | 2005.14115 | null | https://arxiv.org/abs/2005.14115v2 | https://arxiv.org/pdf/2005.14115v2.pdf | Amark: Automated Marking and Processing Techniques for Ambulatory ECG Data | We describe techniques and specifications of MATLAB software to process ambulatory electrocardiogram (ECG) data. Through template-based beat identification and simple pattern recognition models on the intervals between regular heart beats, we filter noisy sections of waveform and ectopic beats. Our end-to-end process can be used towards analysis of ECG and calculation of heart rate variability metrics after beat adjustments, removals and interpolation. Classification and noise detection is assessed on the human-annotated MIT-BIH Arrythmia and Noise Stress Test Databases. | ['Richard P. Sloan', 'Sharath Koorathota'] | 2020-05-28 | null | null | null | null | ['heart-rate-variability'] | ['medical'] | [ 6.13340080e-01 -3.92903715e-01 3.23981076e-01 -4.83014971e-01
-4.90477622e-01 -6.69080317e-01 -2.97283351e-01 5.44076622e-01
-2.41759673e-01 8.79626989e-01 8.43266398e-02 -4.85786557e-01
-5.13584554e-01 -2.87205487e-01 3.52965683e-01 -3.43469560e-01
-6.35536134e-01 2.81238824e-01 -2.42758512e-01 3.31256352e-02
2.13617340e-01 6.72358215e-01 -7.88923144e-01 3.95762622e-01
6.50500834e-01 1.18215036e+00 -6.71548188e-01 1.40755796e+00
4.79197234e-01 2.27776721e-01 -9.62001085e-01 5.94771318e-02
2.77789116e-01 -1.06340861e+00 -3.81954610e-01 -3.08689862e-01
-1.96616799e-01 1.01152904e-01 -8.81845355e-02 5.56165576e-01
1.48016274e+00 -2.42158026e-01 4.96279657e-01 -8.12613487e-01
3.91490310e-01 5.08318365e-01 -1.13164075e-01 1.03516495e+00
6.53084815e-01 2.37582907e-01 6.47985470e-03 -7.33405650e-01
3.50390911e-01 4.59762543e-01 1.76536870e+00 1.04588762e-01
-1.71248591e+00 -3.03540289e-01 -1.13420737e+00 -2.29341134e-01
-1.81142151e+00 -5.33105969e-01 7.23752499e-01 -4.01973456e-01
9.41639602e-01 9.58364308e-01 1.04166389e+00 4.94500905e-01
7.23074973e-01 -6.94400072e-02 1.01968014e+00 -6.08558595e-01
1.38033703e-01 -3.30344379e-01 3.49992633e-01 1.40706658e-01
2.43881300e-01 1.91293105e-01 -4.04255331e-01 -8.13436627e-01
9.60055292e-01 -6.38516173e-02 -5.73116720e-01 2.18041778e-01
-1.36514449e+00 2.14622647e-01 -3.13996702e-01 1.94084004e-01
-6.79799795e-01 -9.83498618e-02 9.07120049e-01 6.64185166e-01
4.73843738e-02 6.35263860e-01 -4.58274543e-01 -6.13992691e-01
-1.29814374e+00 1.76006839e-01 7.76654124e-01 8.40058863e-01
2.33901456e-01 2.84788281e-01 -6.42737806e-01 6.69473767e-01
7.25030378e-02 4.62109208e-01 5.80975294e-01 -1.18457925e+00
-5.28175309e-02 2.96320200e-01 3.21818531e-01 -8.95943642e-01
-8.94528449e-01 -5.20095944e-01 -1.05068564e+00 -2.08256040e-02
3.66780400e-01 -3.65762144e-01 -7.44269967e-01 8.22963297e-01
1.37416452e-01 6.38971701e-02 -2.98598390e-02 5.45651376e-01
5.61765790e-01 -7.29364529e-02 1.68694988e-01 -9.59007323e-01
1.22481537e+00 1.91523224e-01 -1.21549726e+00 2.98652619e-01
5.88662446e-01 -6.93770647e-01 5.73373973e-01 7.31414199e-01
-1.40096211e+00 -7.41086423e-01 -9.20656800e-01 1.99288622e-01
1.49230227e-01 2.31914502e-02 2.61568666e-01 1.10451698e+00
-8.02910984e-01 1.22799063e+00 -8.50158393e-01 -1.32941589e-01
5.12275755e-01 3.58006090e-01 1.06868297e-01 5.96097648e-01
-1.20464611e+00 8.38009834e-01 9.30049494e-02 4.55014050e-01
-2.68039018e-01 -9.20057118e-01 -7.93365836e-01 -3.34324330e-01
-4.29183543e-01 -7.35954523e-01 8.62777650e-01 -3.95183891e-01
-1.24142230e+00 8.84011865e-01 -2.28493184e-01 -7.02694714e-01
6.80127263e-01 2.68206149e-02 -8.59813869e-01 1.73086926e-01
-2.05994874e-01 -3.76799643e-01 7.95248985e-01 -5.23442805e-01
-1.77876845e-01 -4.82176363e-01 -1.01872051e+00 6.00573868e-02
6.14558399e-01 1.77326143e-01 1.47520080e-01 -9.23671663e-01
5.90075910e-01 -4.72780764e-01 -3.27057630e-01 -4.08641219e-01
-3.63996118e-01 6.94334924e-01 2.72722363e-01 -1.18523455e+00
1.98737967e+00 -2.42427850e+00 -3.57883096e-01 8.78554404e-01
1.64937049e-01 3.12986851e-01 3.28444332e-01 3.77694875e-01
-2.35984206e-01 2.18791589e-01 -2.60387361e-01 2.03687772e-01
-3.05472523e-01 1.15992546e-01 -2.14982376e-01 7.72257626e-01
-1.15108490e-01 9.55400348e-01 -5.02723098e-01 -3.60048205e-01
5.25350928e-01 5.29209375e-01 8.86057392e-02 1.05079450e-01
6.43814445e-01 8.56384993e-01 7.57530630e-02 6.71949089e-01
3.80802453e-01 5.15628874e-01 2.83018738e-01 -5.72764516e-01
-1.42668923e-02 5.00966251e-01 -1.30163455e+00 1.65342653e+00
2.20225323e-02 4.63957220e-01 -2.06659257e-01 -5.57724953e-01
1.36097431e+00 7.88555682e-01 5.33071697e-01 -3.82759541e-01
2.78685331e-01 2.88277924e-01 4.30391788e-01 -7.01857805e-01
-3.86884063e-01 -1.87378973e-01 1.40194163e-01 4.13722843e-01
-2.12938592e-01 -2.63829231e-01 1.52456373e-01 -3.20451200e-01
1.20295036e+00 -2.54019420e-03 9.91652429e-01 -6.88813746e-01
5.98858953e-01 -3.11077744e-01 6.13956392e-01 9.43891525e-01
-5.25286615e-01 1.07937515e+00 4.19648468e-01 -1.17147183e+00
-8.49546254e-01 -1.15875518e+00 -6.82143748e-01 1.83793485e-01
-4.51847404e-01 -4.93718356e-01 -5.12697875e-01 -1.15217097e-01
3.51637863e-02 3.91251892e-01 -4.44877565e-01 -1.32352278e-01
-7.43527889e-01 -8.70201766e-01 1.31553090e+00 6.36546850e-01
-6.58244044e-02 -1.26685739e+00 -1.18304920e+00 8.27155650e-01
-1.40057504e-01 -5.79122245e-01 -2.25053504e-01 5.15544474e-01
-1.30556035e+00 -1.11162770e+00 -4.40755814e-01 -4.39115196e-01
1.55155540e-01 -7.72715569e-01 1.35190451e+00 2.24079356e-01
-1.27474117e+00 2.99826026e-01 2.17811037e-02 -8.46690476e-01
-5.11892378e-01 -4.58162546e-01 1.83235914e-01 -1.85731024e-01
3.74982774e-01 -1.00775158e+00 -8.92552495e-01 4.08359051e-01
-2.41248727e-01 -5.19203424e-01 -6.66491985e-02 5.81678271e-01
8.71150613e-01 -2.53222913e-01 7.85425425e-01 -5.65810263e-01
1.13394380e+00 4.27697785e-02 -1.90279618e-01 -3.44227254e-02
-8.99706185e-01 -6.96296751e-01 3.19184989e-01 -1.81558102e-01
-2.63724834e-01 2.71784455e-01 -2.16423929e-01 -5.20053059e-02
-3.55581552e-01 2.51931667e-01 7.80264810e-02 9.08285566e-03
1.25581193e+00 2.59812176e-01 3.26946318e-01 -6.84505925e-02
-3.20406646e-01 5.53592622e-01 1.20778334e+00 -2.45618761e-01
2.16412857e-01 1.31349400e-01 2.35012293e-01 -9.53840554e-01
-2.24765778e-01 -5.71335793e-01 -9.66446519e-01 -1.23727277e-01
6.75311089e-01 -6.08076215e-01 -7.09567904e-01 1.96892247e-01
-9.32066619e-01 -1.50407314e-01 -9.11337256e-01 5.25549293e-01
-6.10681951e-01 5.37618518e-01 -5.67469358e-01 -1.25190103e+00
-1.03803754e+00 -4.68369484e-01 4.76111203e-01 -1.77466311e-02
-1.15967810e+00 -7.86906540e-01 3.68768722e-01 -3.19224089e-01
3.90842170e-01 1.05004251e+00 5.41924596e-01 -5.95722556e-01
3.76480997e-01 -7.49090254e-01 5.76706350e-01 4.10074919e-01
4.43299085e-01 1.16938375e-01 -9.14055705e-01 -7.11970180e-02
3.21133137e-01 3.08531314e-01 2.19693080e-01 8.08221936e-01
1.08419657e+00 -1.89909060e-02 -1.74127281e-01 9.07604933e-01
1.17725110e+00 6.46335125e-01 1.38981080e+00 -1.83780298e-01
1.92092225e-01 1.11458510e-01 2.91593343e-01 7.06441045e-01
-3.37724864e-01 1.40907258e-01 -4.52735752e-01 -3.23392361e-01
1.95167467e-01 3.98269057e-01 -1.85336009e-01 4.62986112e-01
-7.14827359e-01 3.73220563e-01 -1.06634653e+00 4.13059354e-01
-1.43799639e+00 -1.01865590e+00 -7.61222899e-01 2.42043757e+00
9.87782955e-01 2.81897336e-01 3.32026362e-01 9.22381938e-01
6.82362854e-01 -4.48998004e-01 -4.71595019e-01 -7.60801375e-01
-1.23307683e-01 6.62008941e-01 2.57626683e-01 4.21420634e-01
-8.50731015e-01 -5.93973733e-02 8.27766228e+00 -9.43658128e-02
-9.05931354e-01 -1.73243791e-01 7.83793628e-01 1.88074484e-02
4.63880062e-01 -3.63620281e-01 -4.08514917e-01 3.82164359e-01
1.32846069e+00 -3.91263276e-01 4.09351826e-01 5.10342658e-01
6.84774876e-01 -9.68708016e-04 -1.21790099e+00 1.54475176e+00
-2.89717674e-01 -1.39941382e+00 -7.41894305e-01 -4.29425150e-01
1.95441529e-01 -2.17061907e-01 -6.44982338e-01 4.64278460e-02
-9.41120803e-01 -1.00189495e+00 2.92745173e-01 1.11458075e+00
1.12307978e+00 -6.98945582e-01 7.69252062e-01 -6.69654757e-02
-9.96678174e-01 2.02628672e-02 -1.42968699e-01 -2.10402325e-01
1.12726733e-01 1.00780618e+00 -6.51583850e-01 4.81824994e-01
5.22354901e-01 4.68907058e-01 -5.33564091e-01 1.57267416e+00
4.66695167e-02 9.87685144e-01 -5.66946447e-01 6.90414667e-01
-9.27881122e-01 -6.47723898e-02 6.73458159e-01 1.46080279e+00
2.20319599e-01 6.83899820e-01 6.85083643e-02 7.74183869e-01
6.16159916e-01 9.57476422e-02 -5.88756144e-01 3.83301586e-01
5.30816674e-01 1.06689382e+00 -7.11544871e-01 -4.79239374e-01
1.50976777e-01 5.25780618e-01 -6.96992397e-01 3.38358134e-01
-5.69184065e-01 -1.08931494e+00 2.75686115e-01 4.22270507e-01
-4.26653147e-01 2.55765039e-02 -1.38810873e+00 -5.23727953e-01
7.03999251e-02 -1.16821063e+00 6.30210519e-01 -5.26614666e-01
-8.86260390e-01 6.88422203e-01 -2.05717176e-01 -1.19736743e+00
-5.25296688e-01 -6.43276572e-02 -1.21372509e+00 1.45430410e+00
-5.29560328e-01 -1.97698753e-02 -1.87081665e-01 5.90663970e-01
-7.74286166e-02 1.65969953e-01 1.42984271e+00 4.18600291e-01
-1.46333249e-02 6.55632675e-01 -6.23868048e-01 1.71062946e-01
4.11273837e-01 -1.38343859e+00 5.37694633e-01 6.66380048e-01
-2.02163458e-01 8.61904562e-01 9.16849256e-01 -8.05593967e-01
-9.14546788e-01 -8.92625809e-01 1.09944832e+00 -6.63331985e-01
1.36842266e-01 -2.82530878e-02 -1.04820228e+00 1.91882104e-01
-1.34565219e-01 3.32650512e-01 9.46765423e-01 -1.42295018e-01
3.92272174e-01 -3.78260940e-01 -1.29436457e+00 1.50184378e-01
5.02245843e-01 -3.50793570e-01 -7.52261579e-01 2.98605282e-02
-2.65283972e-01 -5.46332121e-01 -1.49822617e+00 7.82226026e-01
1.07409048e+00 -8.12942386e-01 8.93486261e-01 -5.20074368e-01
-4.26092863e-01 -3.60589713e-01 4.08697605e-01 -1.03980541e+00
-3.16457957e-01 -1.90683484e+00 -1.71643533e-02 9.33085680e-01
4.88190413e-01 -5.29699445e-01 3.27922463e-01 5.68549812e-01
-1.73203140e-01 -5.37402332e-01 -8.74415517e-01 -5.16240001e-01
-7.32800782e-01 -5.51816940e-01 1.18599698e-01 6.80803716e-01
4.80076164e-01 2.14828588e-02 -3.55427444e-01 2.25452408e-02
7.56635725e-01 -2.47404888e-01 4.02173102e-01 -1.36607432e+00
-1.04293175e-01 -9.57951993e-02 -6.29124999e-01 3.22900295e-01
-9.64956641e-01 -4.45763916e-01 -1.36048617e-02 -1.30482686e+00
-5.80937862e-01 -2.76649594e-01 -7.70678937e-01 3.72089356e-01
-2.78007269e-01 8.08137894e-01 -2.15015665e-01 -6.03601299e-02
2.34340634e-02 -2.26350397e-01 6.82533801e-01 3.95274520e-01
-1.10573685e+00 4.86243546e-01 -1.29267141e-01 7.22767055e-01
9.53166783e-01 -7.61960387e-01 -3.37023348e-01 6.32973254e-01
2.06922591e-01 5.59123218e-01 3.59756321e-01 -1.49324870e+00
-2.82412708e-01 3.54197443e-01 1.02125812e+00 -8.84110808e-01
-1.79557297e-02 -4.61179763e-01 8.15521955e-01 9.09652829e-01
-3.76644164e-01 5.63970864e-01 3.17959458e-01 2.71101147e-01
3.03595793e-02 1.02682207e-02 8.82317543e-01 -2.45661899e-01
3.39768946e-01 1.55326203e-01 -9.19572055e-01 3.47015828e-01
7.37046242e-01 -6.89637482e-01 1.83061853e-01 -1.30874708e-01
-1.67555487e+00 -2.52834111e-02 -6.68429807e-02 -5.36404960e-02
7.50622272e-01 -1.30069506e+00 -9.26860869e-01 5.82308650e-01
-4.02654707e-03 -4.04177248e-01 2.43351430e-01 1.58548903e+00
-9.88277495e-01 8.02760944e-03 -6.07439995e-01 -8.08157444e-01
-1.47681689e+00 1.22976065e-01 8.28986585e-01 -1.50611447e-02
-1.03639781e+00 3.61317873e-01 -8.02540004e-01 5.08132637e-01
4.85186815e-01 -5.88141441e-01 -1.89343274e-01 2.16942336e-02
9.58806574e-01 7.78491139e-01 4.10968363e-01 5.86317629e-02
-6.02258861e-01 2.64985383e-01 5.30293167e-01 4.75430023e-03
7.48657942e-01 -4.77337509e-01 -1.83482945e-01 8.52433503e-01
5.87277710e-01 -1.13405965e-01 -5.69015563e-01 4.53001887e-01
2.00997159e-01 -1.69344112e-01 -2.40031570e-01 -1.14051819e+00
-5.08016467e-01 7.88694561e-01 1.18521941e+00 5.34437358e-01
1.43640912e+00 -1.01550400e+00 5.01739740e-01 1.96517974e-01
7.58746788e-02 -1.11796248e+00 -6.55050337e-01 -6.91084117e-02
9.22454417e-01 -4.34414029e-01 3.35797459e-01 -1.54737100e-01
-4.85432953e-01 1.37062919e+00 -2.04257831e-01 -3.24000865e-01
9.78760362e-01 5.40451944e-01 6.02010190e-01 -8.07031319e-02
-4.15807664e-01 2.32422918e-01 1.65268719e-01 1.19428146e+00
6.79664969e-01 5.17678224e-02 -9.14196789e-01 7.17465162e-01
-6.72374964e-02 5.62210977e-01 5.30957222e-01 1.01523721e+00
-3.24581921e-01 -8.46954226e-01 -5.40710747e-01 7.06675947e-01
-9.93458152e-01 -3.15578014e-01 -1.38197646e-01 4.17193264e-01
6.46008626e-02 9.78666782e-01 -2.40926594e-01 1.27654728e-02
4.94956851e-01 7.62053490e-01 5.81385553e-01 -4.92751867e-01
-1.30433583e+00 5.17648637e-01 3.50713342e-01 -5.41363895e-01
-1.31969169e-01 -7.58045435e-01 -1.39680040e+00 4.10279572e-01
-6.32757619e-02 1.69210136e-01 6.52266324e-01 5.99045038e-01
5.11146307e-01 7.27392912e-01 4.42129701e-01 -5.54075062e-01
-6.47412181e-01 -1.28151453e+00 -1.04838121e+00 3.76798570e-01
5.55979371e-01 6.09010197e-02 -2.72383869e-01 6.84161484e-01] | [14.215584754943848, 3.212907552719116] |
1adfcf79-c7e6-4898-bf08-39c164840537 | multistream-gaze-estimation-with-anatomical | 2206.09256 | null | https://arxiv.org/abs/2206.09256v1 | https://arxiv.org/pdf/2206.09256v1.pdf | Multistream Gaze Estimation with Anatomical Eye Region Isolation by Synthetic to Real Transfer Learning | We propose a novel neural pipeline, MSGazeNet, that learns gaze representations by taking advantage of the eye anatomy information through a multistream framework. Our proposed solution comprises two components, first a network for isolating anatomical eye regions, and a second network for multistream gaze estimation. The eye region isolation is performed with a U-Net style network which we train using a synthetic dataset that contains eye region masks for the visible eyeball and the iris region. The synthetic dataset used in this stage is a new dataset consisting of 60,000 eye images, which we create using an eye-gaze simulator, UnityEyes. Successive to training, the eye region isolation network is then transferred to the real domain for generating masks for the real-world eye images. In order to successfully make the transfer, we exploit domain randomization in the training process, which allows for the synthetic images to benefit from a larger variance with the help of augmentations that resemble artifacts. The generated eye region masks along with the raw eye images are then used together as a multistream input to our gaze estimation network. We evaluate our framework on three benchmark gaze estimation datasets, MPIIGaze, Eyediap, and UTMultiview, where we set a new state-of-the-art on Eyediap and UTMultiview datasets by obtaining a performance gain of 7.57% and 1.85% respectively, while achieving competitive performance on MPIIGaze. We also study the robustness of our method with respect to the noise in the data and demonstrate that our model is less sensitive to noisy data. Lastly, we perform a variety of experiments including ablation studies to evaluate the contribution of different components and design choices in our solution. | ['Ali Etemad', 'Paul Hungler', 'Zunayed Mahmud'] | 2022-06-18 | null | null | null | null | ['gaze-estimation'] | ['computer-vision'] | [ 2.46744737e-01 1.97953761e-01 1.25700638e-01 -3.41427892e-01
-2.52384424e-01 -4.48042989e-01 3.53400737e-01 -5.57922184e-01
-4.76021916e-01 5.25566339e-01 -7.05822334e-02 -1.78082988e-01
1.48246229e-01 -3.31069440e-01 -9.71799612e-01 -7.59083450e-01
2.66263515e-01 -7.88890868e-02 2.39890501e-01 -1.14084274e-01
3.11747342e-01 1.46424577e-01 -2.28579140e+00 1.36196867e-01
9.42646146e-01 1.24719453e+00 -1.76270846e-02 6.93444610e-01
2.07496136e-01 6.12429321e-01 -6.76021993e-01 -1.56251565e-01
4.93525118e-01 -5.35745561e-01 -5.58579683e-01 1.57912523e-01
9.66479182e-01 -3.97949487e-01 2.00955316e-01 8.29572201e-01
6.12091959e-01 1.32167503e-01 4.88033384e-01 -1.47005451e+00
-4.75481480e-01 -6.84836954e-02 -1.04934812e+00 1.43778414e-01
3.48242491e-01 6.16547763e-01 7.39911556e-01 -7.67542720e-01
5.98144889e-01 1.05846930e+00 2.89470226e-01 7.64626741e-01
-1.19130874e+00 -1.18391347e+00 9.49413851e-02 -2.01273151e-02
-1.31309962e+00 -9.30490494e-01 5.19984722e-01 -4.24049854e-01
6.03847742e-01 2.06038132e-01 3.52016032e-01 1.21520770e+00
-2.61610318e-02 7.99064994e-01 1.41272640e+00 -5.04859149e-01
-6.13956414e-02 3.45301867e-01 2.03577027e-01 6.36502206e-01
-1.01532958e-01 3.21803838e-01 -7.73613930e-01 2.61117876e-01
7.22358704e-01 -2.05895022e-01 -6.36722744e-01 -2.07021371e-01
-9.50412393e-01 4.26290661e-01 7.43276238e-01 -1.25352934e-01
-3.40404779e-01 -9.94443521e-02 -1.06965125e-01 3.69810998e-01
5.59879720e-01 3.44482958e-01 -2.65866220e-01 -1.79807805e-02
-9.94687438e-01 1.68542951e-01 5.42641759e-01 8.94683599e-01
8.29221666e-01 -2.08814710e-01 -3.70256215e-01 6.95492387e-01
5.86077809e-01 4.83330458e-01 4.89713579e-01 -7.98167944e-01
4.38001722e-01 7.05292642e-01 1.64261132e-01 -5.15965343e-01
-3.64499807e-01 -3.76481742e-01 -4.40950096e-01 7.27312863e-01
6.80269718e-01 -3.43923420e-01 -1.18338311e+00 1.91480601e+00
3.76936316e-01 4.93764818e-01 -8.97672698e-02 1.07143223e+00
9.04980540e-01 2.29465142e-01 -5.41285910e-02 6.37203828e-02
1.41292512e+00 -1.06288755e+00 -4.79274571e-01 -2.77914762e-01
4.74755555e-01 -6.93580270e-01 1.32958472e+00 3.61680627e-01
-1.13727057e+00 -6.16120934e-01 -9.51352954e-01 -1.72163054e-01
-3.00301284e-01 3.31110507e-01 3.29692841e-01 6.98978543e-01
-1.32944834e+00 2.74484068e-01 -6.24631584e-01 -1.62944421e-01
6.38953984e-01 6.71632111e-01 -3.61798286e-01 2.84106344e-01
-6.85112894e-01 5.65972447e-01 1.11571401e-01 7.48400241e-02
-7.36964107e-01 -8.45101953e-01 -9.96796787e-01 2.36160904e-01
2.64064550e-01 -7.03710556e-01 1.08467078e+00 -1.37321854e+00
-1.70953560e+00 1.01394200e+00 -7.02862620e-01 -1.87148958e-01
5.21857381e-01 -2.50827342e-01 -3.40023339e-01 3.91473360e-02
-1.17700234e-01 1.02669525e+00 1.34829116e+00 -1.04666638e+00
-7.90233910e-01 -3.89399767e-01 1.58845335e-01 8.09186772e-02
-1.22328989e-01 3.03783059e-01 -5.78030229e-01 -3.41078967e-01
-3.79754990e-01 -1.11182904e+00 5.58078706e-01 2.73399185e-02
-6.15008116e-01 -1.94534793e-01 5.52317977e-01 -4.94302541e-01
1.16433489e+00 -2.44437408e+00 1.85511008e-01 2.75526285e-01
6.54321969e-01 1.35056391e-01 -3.59129667e-01 -2.01966882e-01
-5.09236276e-01 -1.50103662e-02 -1.17032386e-01 -9.76402342e-01
-1.74206838e-01 -3.48406076e-01 -1.08229145e-01 3.50892425e-01
5.33917189e-01 8.21499944e-01 -6.56736076e-01 -2.78465360e-01
-9.21674296e-02 4.66933578e-01 -6.18530273e-01 3.23531836e-01
-1.44871175e-01 5.36860704e-01 -1.70280002e-02 5.22974491e-01
7.73753524e-01 -4.72362012e-01 -4.05585378e-01 5.20140752e-02
-2.59775996e-01 1.22628652e-01 -9.36647296e-01 1.46275961e+00
-4.25258100e-01 9.53417718e-01 -9.18298736e-02 2.89803557e-03
5.96254170e-01 1.19671449e-01 -2.72192024e-02 -7.99689531e-01
5.98010361e-01 -1.37635797e-01 3.15043002e-01 -4.24115419e-01
5.02030492e-01 3.10467958e-01 4.24443901e-01 8.02352965e-01
2.96055019e-01 4.96882051e-01 2.68062592e-01 8.94429833e-02
6.32290840e-01 3.19263488e-01 -2.01904476e-01 -1.86075181e-01
5.51804960e-01 -4.57077593e-01 2.31390640e-01 2.17389882e-01
-2.37527966e-01 8.43067288e-01 7.99808979e-01 -8.04800913e-02
-6.23630285e-01 -8.98782730e-01 -1.25264898e-01 1.26427543e+00
1.23348266e-01 -2.20949695e-01 -1.02077425e+00 -7.39409924e-01
-2.21407339e-01 5.69744349e-01 -1.13509345e+00 -2.21913278e-01
-1.40587211e-01 -6.85909390e-01 2.89421022e-01 2.35855460e-01
4.89641011e-01 -1.23663783e+00 -8.30847919e-01 -5.65230668e-01
1.72348142e-01 -9.56881940e-01 -6.15011334e-01 -2.25077823e-01
-3.96169990e-01 -1.36517525e+00 -8.43940020e-01 -5.14777005e-01
8.07214916e-01 2.06641838e-01 9.59142685e-01 1.33345351e-01
-8.10389314e-03 -8.71425793e-02 2.16770209e-02 -6.08289719e-01
-1.14502199e-01 3.40100527e-01 8.20209607e-02 6.83167517e-01
5.62136829e-01 -3.97182554e-01 -9.16556597e-01 3.36685330e-01
-7.77615845e-01 1.97840437e-01 4.83838946e-01 7.74142861e-01
2.35936955e-01 -5.33432662e-01 2.63641477e-01 -9.44292247e-01
6.82537019e-01 -6.35918975e-01 -8.54288280e-01 3.91885787e-02
-4.58233654e-01 1.29437834e-01 1.98687956e-01 -5.30653298e-01
-1.07368994e+00 -1.58103004e-01 1.26293898e-01 -7.17987955e-01
-2.02775210e-01 -4.07209899e-03 2.17696093e-02 -2.12424055e-01
1.01733685e+00 3.73878516e-02 4.43242997e-01 -4.71419990e-01
2.45739460e-01 8.73713255e-01 3.57602179e-01 -8.56614634e-02
6.38857305e-01 3.83999228e-01 -1.98913530e-01 -6.66911602e-01
-8.50588262e-01 -2.34844863e-01 -4.94663328e-01 -1.54338464e-01
8.02191913e-01 -9.22416866e-01 -1.13100135e+00 8.89354825e-01
-8.43062580e-01 -4.90735739e-01 8.87440816e-02 2.55290866e-01
-1.64533839e-01 -2.24348336e-01 -2.73784369e-01 -6.11588061e-01
-3.08835477e-01 -1.43186843e+00 1.11688113e+00 8.71722102e-01
-1.61566988e-01 -6.73325717e-01 3.16287987e-02 2.42224783e-01
2.82449394e-01 1.34092599e-01 4.91781741e-01 -4.80461806e-01
-6.93355799e-01 8.56161565e-02 -5.03760219e-01 3.84653330e-01
1.86151013e-01 3.02471876e-01 -1.57569742e+00 -3.35963756e-01
-3.84273291e-01 -4.28667426e-01 7.50529945e-01 3.38612497e-01
1.04879081e+00 1.38943046e-01 -3.87210220e-01 1.05603647e+00
1.08664286e+00 -2.14532658e-01 6.91496491e-01 3.77162427e-01
8.02039146e-01 8.03381741e-01 3.60356897e-01 1.19333081e-01
5.56656599e-01 4.09628123e-01 5.56915045e-01 -3.22924823e-01
-2.77357668e-01 3.85617837e-02 1.66159153e-01 1.45931989e-01
-1.18070841e-01 -2.91608095e-01 -8.37738812e-01 5.64518154e-01
-1.51675105e+00 -5.52762568e-01 3.39364856e-02 2.34713268e+00
9.42169428e-01 1.38513550e-01 4.32008713e-01 -5.38080977e-03
4.73098963e-01 -3.36962044e-02 -6.97508574e-01 -1.30698815e-01
1.33909911e-01 4.42713737e-01 3.96127403e-01 2.88211644e-01
-9.71725583e-01 9.02538061e-01 5.74875355e+00 2.94385195e-01
-1.74650049e+00 -1.06782727e-01 6.52185023e-01 -6.96803212e-01
5.26312999e-02 -3.99416655e-01 -8.72036874e-01 8.66470575e-01
1.08756876e+00 2.93835104e-01 5.39832830e-01 4.60501164e-01
9.26468596e-02 -3.43334973e-01 -1.15769899e+00 1.08285606e+00
2.13613078e-01 -9.40598547e-01 -4.18179512e-01 1.02815300e-01
5.74946284e-01 4.36523169e-01 4.73023444e-01 7.26613104e-02
2.83834003e-02 -1.14932370e+00 6.52728617e-01 6.22198880e-01
1.18788469e+00 -5.77922702e-01 5.51478148e-01 1.99056238e-01
-5.32404542e-01 -2.87028216e-02 9.85886455e-02 -5.17469682e-02
-2.45157912e-01 -3.01370062e-02 -8.52315903e-01 2.01235890e-01
9.47256923e-01 6.68297112e-01 -9.88162577e-01 1.30654991e+00
-3.43132496e-01 4.32610780e-01 -4.98083234e-01 1.65044874e-01
-8.38762149e-02 -5.26719354e-03 4.08027261e-01 5.62402010e-01
8.59256741e-03 -3.50105137e-01 -6.62935317e-01 1.15691233e+00
-4.17401195e-01 -1.89395562e-01 -3.44314307e-01 3.81441563e-01
4.96505469e-01 1.22905850e+00 -3.39028686e-01 -1.11202151e-01
-4.15048540e-01 8.42060387e-01 4.52314556e-01 8.14385176e-01
-7.65786290e-01 -4.90428418e-01 9.89138484e-01 1.58951223e-01
2.89756894e-01 2.98340201e-01 -2.06128687e-01 -1.10380960e+00
1.34540245e-01 -1.00013983e+00 -4.54015248e-02 -1.02268875e+00
-8.55998337e-01 9.36867952e-01 -1.39811309e-02 -1.20512927e+00
-4.67270166e-01 -6.07223809e-01 -7.10796177e-01 1.60544860e+00
-1.80314863e+00 -1.13699245e+00 -7.99323082e-01 7.87289083e-01
2.14404851e-01 -2.43827313e-01 5.71741939e-01 1.91222072e-01
-1.09400976e+00 1.02490234e+00 -2.07680926e-01 1.15971424e-01
1.15889442e+00 -1.19755805e+00 5.31188548e-01 8.87169421e-01
-1.37694865e-01 8.57926607e-01 3.69072825e-01 -1.90025181e-01
-9.01479900e-01 -8.60115767e-01 7.04973519e-01 -8.17264915e-01
4.04033214e-01 -6.77187979e-01 -8.81790638e-01 8.85730088e-01
4.19497818e-01 1.94068968e-01 6.48637176e-01 1.60848439e-01
-3.24339926e-01 -8.24788585e-02 -1.06439245e+00 7.41743267e-01
8.76623511e-01 -4.79424298e-01 -4.52893406e-01 -2.11138293e-01
5.27764618e-01 -7.01248050e-01 -4.88060772e-01 6.33035898e-02
7.54182220e-01 -1.19916141e+00 6.35610402e-01 -5.45845509e-01
5.33806384e-01 -3.75322759e-01 5.77865541e-01 -1.42890286e+00
5.05724810e-02 -7.89581895e-01 -1.26380682e-01 1.23929751e+00
4.76030886e-01 -9.94878590e-01 6.87040269e-01 6.13042116e-01
2.47815773e-01 -6.91824317e-01 -4.48892742e-01 -1.65603489e-01
-2.09453255e-01 -1.91275209e-01 8.01416755e-01 6.78573728e-01
-5.15404165e-01 5.03482759e-01 -1.84022084e-01 9.06134397e-02
6.20226800e-01 -2.91450415e-02 1.11845458e+00 -1.32110107e+00
-8.87510702e-02 -3.83284599e-01 -1.03908487e-01 -1.12845886e+00
2.09572241e-01 -3.36929619e-01 -2.18113177e-02 -7.16464579e-01
-1.63980067e-01 -2.88894117e-01 -3.46936226e-01 5.12041569e-01
-4.65881646e-01 6.50698721e-01 3.42502415e-01 2.47064397e-01
-2.46299982e-01 3.66747648e-01 1.34975779e+00 1.90258831e-01
-5.52617192e-01 1.32643014e-01 -8.89576912e-01 5.74759066e-01
4.88120556e-01 -2.74244487e-01 -6.34170413e-01 -6.09472871e-01
2.42866576e-01 -3.18602920e-01 4.84582007e-01 -8.11109185e-01
2.64439583e-01 3.83294553e-01 4.70118761e-01 -3.28171909e-01
2.39713892e-01 -7.12144136e-01 -3.75677228e-01 -1.59476578e-01
-8.65160078e-02 -1.72251776e-01 5.91203630e-01 2.66854256e-01
-1.22256286e-01 7.44848028e-02 8.03912222e-01 3.16813260e-01
-5.03625512e-01 2.48087719e-01 2.22027808e-01 7.16756582e-02
9.88202214e-01 -4.14713234e-01 -5.14940560e-01 -1.98480248e-01
-6.62975371e-01 4.51710790e-01 7.44591117e-01 6.84138715e-01
2.69452631e-01 -8.13954711e-01 -5.36439121e-01 9.48612750e-01
2.98787653e-01 1.81233719e-01 1.51751369e-01 1.10377431e+00
-4.21594381e-01 1.41710371e-01 -5.22297561e-01 -8.83594036e-01
-1.34282708e+00 3.96866411e-01 4.96989936e-01 3.47919345e-01
-2.51487583e-01 1.10246241e+00 6.66993856e-01 -3.28277349e-02
3.25747073e-01 -5.81532121e-01 -4.33533162e-01 1.07995227e-01
8.48143578e-01 1.43505648e-01 1.38967587e-02 -7.18309343e-01
-2.81775057e-01 5.51028669e-01 -1.76906869e-01 6.24308288e-02
1.19988537e+00 -3.74780715e-01 -1.58811416e-02 2.57547349e-01
1.08119416e+00 2.18478858e-01 -1.68949652e+00 -1.53626785e-01
-3.00398111e-01 -5.02155542e-01 1.56717643e-01 -9.69443798e-01
-1.26258290e+00 8.50330949e-01 9.02324259e-01 5.04468707e-03
1.54156542e+00 -1.39628634e-01 5.36269903e-01 -1.85856879e-01
-7.82956257e-02 -5.01018643e-01 -2.75236368e-01 3.16445619e-01
6.97430551e-01 -1.64016700e+00 -4.98302579e-01 -2.62856811e-01
-5.90943694e-01 7.25972235e-01 8.47566664e-01 -2.18301892e-01
7.04026997e-01 2.55990438e-02 4.35535580e-01 -2.90202081e-01
-6.89474463e-01 -4.43123877e-01 7.39685416e-01 5.06617248e-01
3.30880582e-01 -4.12723780e-01 3.04917336e-01 4.49516147e-01
-4.75967109e-01 3.29938084e-01 3.19997817e-01 5.26910543e-01
1.18384100e-01 -8.89456809e-01 -3.69029671e-01 3.98518294e-01
-5.58878362e-01 -3.72240931e-01 -4.17056173e-01 9.63380158e-01
2.00598314e-01 7.42809534e-01 4.86360967e-01 -3.20384383e-01
2.40412682e-01 1.91934794e-01 4.52471137e-01 -6.50362253e-01
-7.45416582e-01 -2.92121507e-02 -1.79141760e-01 -7.09344029e-01
-3.48859429e-01 -4.10063714e-01 -8.33429515e-01 -2.69353837e-01
-3.23720336e-01 -2.97230959e-01 5.15451252e-01 8.31993341e-01
7.47911096e-01 8.38000059e-01 5.26049316e-01 -1.03908551e+00
-3.97414677e-02 -1.33007193e+00 -3.95853817e-01 4.57448632e-01
9.24934208e-01 -9.65344489e-01 -4.33617741e-01 1.40512332e-01] | [14.134645462036133, 0.048441071063280106] |
d527cfab-e3b0-4914-88fa-70bfefe82760 | mian-xiang-fa-lu-wen-ben-de-shi-ti-guan-xi | null | null | https://aclanthology.org/2021.ccl-1.53 | https://aclanthology.org/2021.ccl-1.53.pdf | 面向法律文本的实体关系联合抽取算法(Joint Entity and Relation Extraction for Legal Texts) | “法律文本中包含的丰富信息可以通过结构化的实体关系三元组进行表示,便于法律知识的存储和查询。传统的流水线方法在自动抽取三元组时执行了大量冗余计算,造成了误差传播。而现有的联合学习方法无法适用于有大量重叠关系的法律文本,也并未关注语法结构信息对文本表示的增强,因此本文提出一种面向法律文本的实体关系联合抽取模型。该模型首先通过ON-LSTM注入语法信息,然后引入多头注意力机制分解重叠关系。相较于流水线和其他联合学习方法本文模型抽取效果最佳,在涉毒类法律文本数据集上抽取结果的F1值达到78.7%。” | ['Hongfei Lin', 'Liang Yang', 'Yuanyuan Sun', 'Ping Yang', 'Xiang Zhou', 'Wenhui Song'] | null | null | null | null | ccl-2021-8 | ['joint-entity-and-relation-extraction'] | ['natural-language-processing'] | [-8.54476511e-01 -7.03434706e-01 4.45536911e-01 3.20582211e-01
-1.85502898e-02 -5.75404227e-01 -6.64204210e-02 1.11477530e+00
-4.05275136e-01 4.21618193e-01 6.71756923e-01 -8.22299197e-02
-1.63218990e-01 -9.87018108e-01 -6.02135420e-01 -1.22195983e+00
-5.74167430e-01 1.47820282e+00 5.86456537e-01 -7.13670492e-01
3.27535778e-01 7.54631639e-01 -7.92475462e-01 5.58877528e-01
8.30460012e-01 1.05779684e+00 1.00352442e+00 4.16407138e-01
-1.52762756e-01 6.25053823e-01 -1.16832435e+00 4.63352442e-01
-7.22702444e-01 4.53986615e-01 -7.11167529e-02 6.19107842e-01
2.83079650e-02 -1.03403306e+00 -1.62446976e+00 9.50747907e-01
5.73060334e-01 1.92431524e-01 9.45699275e-01 -4.99034226e-01
-8.49695265e-01 6.69496477e-01 -3.92299518e-02 9.15004373e-01
-5.86285114e-01 1.65390939e-01 4.06129956e-01 -7.28619277e-01
4.30448074e-03 1.61085320e+00 1.71600413e+00 5.02303898e-01
-1.48190343e+00 -1.05440962e+00 7.92011559e-01 -1.99534982e-01
-1.48185658e+00 3.57499838e-01 5.90881705e-01 -2.56210327e-01
1.61005771e+00 3.46726358e-01 1.09166181e+00 2.03523183e+00
7.35198855e-01 1.49894238e+00 1.43617535e+00 6.08906448e-01
1.58785433e-01 1.55425155e+00 -4.37227994e-01 -1.44120455e-01
6.21497512e-01 3.97157818e-01 -3.79760973e-02 6.42046332e-01
2.80825585e-01 3.28036487e-01 2.32413650e-01 1.13135004e+00
-1.44341040e+00 1.52438736e+00 4.89614069e-01 1.79695904e+00
-2.10191712e-01 -1.19299388e+00 -5.48656821e-01 5.41338682e-01
3.54192495e-01 -2.76617169e-01 3.49866122e-01 6.02676868e-01
-1.01450503e-01 -2.94079930e-01 5.91507256e-01 1.20209420e+00
1.02725077e+00 8.30825150e-01 -6.17973030e-01 8.35805774e-01
1.45939279e+00 8.77771556e-01 1.48949409e+00 -5.75739741e-01
-1.08700001e+00 3.86061400e-01 -7.36731946e-01 -2.05961227e+00
-1.24986625e+00 -1.56072903e+00 -7.92485416e-01 -1.20985472e+00
-2.77597219e-01 -5.95216215e-01 -9.45032060e-01 1.26240313e+00
4.70995121e-02 -4.37945724e-01 3.42451960e-01 6.37827277e-01
8.52497935e-01 1.73739469e+00 2.69850846e-02 3.09738386e-02
9.58654940e-01 -4.82603431e-01 -4.19451565e-01 -5.82630992e-01
-8.62265468e-01 -1.50609934e+00 1.37223017e+00 1.42988749e-03
-5.69296837e-01 -3.65400732e-01 -1.69890320e+00 3.69488329e-01
-3.14740837e-01 -3.76042098e-01 6.25586629e-01 1.26907158e+00
-1.71125698e+00 4.74906772e-01 -1.20812297e+00 -1.51317215e+00
-9.89097208e-02 5.24708986e-01 3.77966583e-01 2.79302746e-01
-1.27988565e+00 1.27492881e+00 -1.60282701e-01 9.67700899e-01
-1.84226501e+00 -3.50466043e-01 -4.87975538e-01 -9.11790952e-02
6.95170343e-01 -6.01205230e-02 1.66103923e+00 -1.26320648e+00
-8.82595837e-01 6.11513078e-01 -7.70014942e-01 -4.53951061e-01
3.42742980e-01 4.44564611e-01 -2.95467854e-01 4.49609570e-02
-3.60645741e-01 5.11531234e-01 8.00925672e-01 -2.10054588e+00
-3.55702549e-01 -1.42003739e+00 1.63775429e-01 -2.10270554e-01
3.33668366e-02 7.42804050e-01 1.69290915e-01 -7.35307336e-01
-1.35985449e-01 -1.87762547e+00 -1.48348317e-01 -1.50022006e+00
-4.51080680e-01 3.88272882e-01 1.23646498e+00 2.67648008e-02
1.08695853e+00 -2.22266078e+00 -1.07484353e+00 8.29325914e-01
1.75393239e-01 1.13034964e+00 -1.77023798e-01 2.11376309e+00
4.08250779e-01 1.09022999e+00 -9.26421106e-01 4.75719184e-01
-2.73060292e-01 2.18088403e-01 8.62742126e-01 -2.21300840e-01
-2.81972855e-01 -3.35838675e-01 -1.43755674e-01 2.53974527e-01
6.72168136e-01 7.94220984e-01 7.66221285e-01 3.21822613e-01
4.89383668e-01 2.88161308e-01 1.38725102e-01 8.35735679e-01
1.11409199e+00 -4.57086653e-01 5.10174751e-01 2.93182842e-02
-5.88878334e-01 -2.69779772e-01 -2.09796071e+00 1.37881827e+00
-2.45087087e-01 1.01924503e+00 3.41089278e-01 -9.97717261e-01
1.35570228e+00 1.37911117e+00 8.34259033e-01 -2.39115104e-01
4.70354706e-01 8.22328627e-01 4.13500249e-01 -2.75131106e-01
1.09356141e+00 -1.05092502e+00 1.08958256e+00 3.03880751e-01
-4.70609158e-01 5.97568452e-01 2.24332348e-01 -9.54740942e-01
1.26700294e+00 -9.92257655e-01 -4.62651700e-01 -7.31136441e-01
6.59420848e-01 -4.52265054e-01 3.01601529e-01 8.19071084e-02
-6.34646595e-01 2.52413064e-01 -9.29171801e-01 5.71640611e-01
-1.24641895e-01 -1.55553257e+00 -3.12993705e-01 1.37889957e+00
-3.26869875e-01 -6.83412135e-01 -6.86563015e-01 -2.96032995e-01
-3.90847147e-01 1.00370085e+00 1.85268521e-01 -3.78253877e-01
-7.84254789e-01 -9.93941724e-01 -8.81142989e-02 2.84043830e-02
1.59863865e+00 -1.61179733e+00 -2.03300551e-01 -1.74613088e-01
-1.10600971e-01 -5.78490496e-01 -7.08266020e-01 -1.72793001e-01
-1.96331608e+00 -6.69252753e-01 9.19180363e-02 -1.65062535e+00
1.12221980e+00 2.19412580e-01 5.39553463e-01 2.28660226e-01
2.59862363e-01 5.85770905e-01 3.84736503e-03 -1.25272834e+00
-9.48584825e-02 6.68888927e-01 1.14235036e-01 1.35585392e+00
9.84454334e-01 -4.11576092e-01 -1.15505421e+00 3.35733652e-01
-1.21580470e+00 -4.48475257e-02 4.00245637e-01 5.18622361e-02
8.42649043e-01 2.62311637e-01 1.49748176e-02 -8.50776196e-01
1.17084527e+00 3.11800390e-01 -1.10888469e+00 4.34701145e-01
-1.46218240e+00 -7.53397644e-01 1.15649712e+00 -7.70834506e-01
-1.19003701e+00 -1.13096821e+00 -4.83391464e-01 -5.43495595e-01
2.75139332e-01 2.66868502e-01 -1.15621343e-01 6.42346561e-01
-4.60370690e-01 2.97141701e-01 3.94012272e-01 -9.26076829e-01
-4.05260712e-01 1.06945598e+00 2.42856875e-01 -8.61588657e-01
2.96264887e-01 1.88815832e-01 -4.08417344e-01 -6.16664767e-01
1.44659251e-01 -1.82475463e-01 -6.51213408e-01 8.49165976e-01
9.73791718e-01 -1.34888875e+00 -2.72444010e-01 8.96470785e-01
-8.39516759e-01 4.74324435e-01 -4.73216206e-01 1.70330358e+00
-4.47574072e-02 -6.36112452e-01 -8.68500888e-01 -9.01331842e-01
-3.47020388e-01 -2.44194627e+00 1.68830175e-02 2.04642487e+00
-8.08293819e-02 -1.29341233e+00 7.68252388e-02 2.74499059e-01
1.13498139e+00 -2.42338821e-01 9.51003969e-01 -8.67950559e-01
-6.18570447e-01 -4.32679892e-01 4.29386795e-01 1.57992208e+00
7.34513998e-01 5.27145624e-01 -7.36287534e-02 -3.77936721e-01
-4.57034782e-02 7.08569109e-01 7.55810738e-01 1.08451712e+00
1.99849889e-01 -4.98756409e-01 -2.37360655e-04 5.95279574e-01
2.12059140e+00 1.44600129e+00 8.08909297e-01 2.02638531e+00
-5.60328662e-01 -4.69159968e-02 -1.22012846e-01 4.02176291e-01
1.15951493e-01 8.42050254e-01 -1.32821247e-01 9.50633407e-01
-1.05831754e+00 -3.21772724e-01 9.99377370e-01 1.56427991e+00
4.32826549e-01 -5.71242198e-02 -9.63349417e-02 7.43116140e-01
-2.49639654e+00 -1.85637653e+00 5.05598545e-01 2.78161907e+00
1.67718068e-01 -3.52006167e-01 5.64526813e-03 6.77724779e-02
1.81235838e+00 2.16516107e-03 -2.55725205e-01 -5.36835730e-01
4.12330508e-01 1.20909476e+00 8.12297344e-01 4.86045003e-01
-7.93490887e-01 4.64384437e-01 6.35982811e-01 7.59953201e-01
-2.47767639e+00 -8.16752315e-02 4.19130832e-01 -1.35096836e+00
-7.37810254e-01 6.22520328e-01 -5.36966920e-01 2.06303072e+00
1.26674616e+00 -1.16888440e+00 9.35556516e-02 3.91871436e-03
1.17838705e+00 3.85413051e-01 -6.42909527e-01 1.48776400e+00
1.95918679e-01 -1.49915361e+00 7.62233213e-02 1.44565344e-01
7.33702719e-01 -4.75598313e-02 1.87625065e-01 3.91653955e-01
2.94502918e-02 -1.17395818e+00 9.38048959e-01 1.92956962e-02
-8.81207585e-02 -1.22194386e+00 1.58184326e+00 2.26844177e-02
-1.22567654e+00 -9.16108191e-01 1.51199475e-01 -3.86715114e-01
5.33674836e-01 2.02388316e-01 -1.93250522e-01 2.07680970e-01
-1.36514515e-01 6.82840943e-02 -7.10527539e-01 2.30441022e+00
-9.34405088e-01 -5.20138443e-02 -2.65133291e-01 -1.57553184e+00
1.00509870e+00 -8.28640610e-02 7.84062207e-01 1.61198568e+00
4.38607097e-01 6.55493855e-01 3.92045051e-01 6.44742429e-01
-5.19074678e-01 1.36887804e-01 -6.92120492e-02 4.75055426e-01
8.48516285e-01 1.15582728e+00 -1.37273490e+00 -7.13294327e-01
-7.71093741e-02 -9.33175623e-01 -2.49739349e-01 -3.76445860e-01
-3.17886472e-02 -7.54177690e-01 -2.07568347e-01 1.70056611e-01
-4.91029203e-01 -9.32256162e-01 5.83972394e-01 -2.55413860e-01
-4.33665961e-01 -1.09958363e+00 5.67678772e-02 -7.16893256e-01
-1.09776998e+00 3.89155239e-01 1.79254547e-01 -1.07601166e+00
6.17091596e-01 -1.42887449e+00 -1.84699640e-01 5.58762133e-01
7.98583403e-02 -8.85987580e-01 4.08135131e-02 -2.94348150e-02
1.35014784e+00 2.91211507e-03 8.07411611e-01 1.10779905e+00
-1.14495659e+00 6.09105885e-01 1.58981943e+00 6.10459924e-01
2.25092605e-01 -1.94515133e+00 -1.03877652e+00 4.91239160e-01
1.05564952e+00 1.68685421e-01 6.30459711e-02 -2.73929924e-01
-9.78961408e-01 -7.97988296e-01 7.28959441e-01 5.30403793e-01
3.77598256e-01 -2.90268540e-01 -3.88629675e-01 1.71834767e+00
5.86952984e-01 -9.55482498e-02 4.32462633e-01 -3.90684009e-01
6.99644685e-01 -1.34084129e+00 -1.74109268e+00 1.18342495e+00
3.62843692e-01 -1.25381649e-01 -7.05967903e-01 -4.01128605e-02
2.50811815e-01 -1.04825532e+00 -1.35991335e+00 4.34951067e-01
1.74302471e+00 -8.40703309e-01 -1.94233015e-01 -3.77982616e-01
-2.42647082e-01 3.82875279e-02 -5.19908309e-01 -1.39516091e+00
5.63010991e-01 -8.22247207e-01 1.27805018e+00 1.37107348e+00
5.23700953e-01 -1.10111201e+00 9.04298604e-01 1.59272993e+00
-8.27710211e-01 -6.35685503e-01 -2.03340077e+00 -1.35272789e+00
4.51323301e-01 -3.95221591e-01 6.23592809e-02 -2.38374904e-01
-5.98742664e-01 4.10906345e-01 3.90436500e-01 -2.45462090e-01
-5.65095097e-02 -9.42174971e-01 -3.47995758e-02 -1.08009422e+00
1.05896330e+00 -7.35032380e-01 -3.87904763e-01 -2.79300939e-02
-7.03683972e-01 -2.92491257e-01 -1.86623001e+00 -1.95739746e+00
4.45716977e-01 -4.84927557e-02 -7.07810760e-01 -2.87097573e-01
1.70745075e+00 -5.77361695e-02 1.11993122e+00 7.64661372e-01
4.04010862e-01 -1.79596663e-01 1.11527562e+00 -8.09514165e-01
-6.25988901e-01 1.43009052e-01 -3.87121439e-01 1.18800652e+00
3.80320638e-01 -2.12395847e-01 -2.93372363e-01 -9.45024431e-01
-2.03129575e-01 -1.20750690e+00 -1.26405013e+00 -1.29290557e+00
3.22301716e-01 3.54366779e-01 1.79919004e-01 5.64157903e-01
6.66824162e-01 -4.91314530e-01 4.33431387e-01 6.30738676e-01
-2.00120270e-01 9.94971097e-01 4.82433170e-01 -8.51103842e-01
-1.06890641e-01 -1.19347572e+00 9.21567857e-01 -3.34886044e-01
-5.72735250e-01 -3.59920979e-01 -5.47302246e-01 -7.01088309e-01
1.10215652e+00 -1.18061937e-01 -6.04682684e-01 2.45913148e-01
-1.15147662e+00 -2.84597456e-01 3.08424234e-01 1.08498216e+00
1.47255862e+00 -1.31549990e+00 -2.03133464e+00 1.93441778e-01
-8.63367140e-01 3.46837007e-02 6.20196164e-01 1.00941479e+00
-4.46297646e-01 6.80608094e-01 -6.16528749e-01 -6.16578043e-01
-2.40779543e+00 7.16795504e-01 -2.64430910e-01 -1.58005670e-01
-2.08855078e-01 6.70708537e-01 -6.20610058e-01 2.32593372e-01
4.47763115e-01 -5.83383918e-01 -5.39063394e-01 3.99780035e-01
3.30925643e-01 3.67734611e-01 9.40490514e-02 -1.27356994e+00
-7.89335668e-01 1.54217255e+00 -9.64995801e-01 -5.55129588e-01
4.02774185e-01 -1.58379436e-01 -3.00681233e-01 4.19546157e-01
1.20641816e+00 6.85899496e-01 -3.47598374e-01 5.34284651e-01
-6.52675807e-01 -6.47063628e-02 -4.87537265e-01 -1.89097083e+00
-9.31823015e-01 1.12195933e+00 8.64707649e-01 -8.99455488e-01
6.42312467e-01 -9.20810103e-01 1.56853473e+00 3.46107692e-01
1.61305857e+00 -2.14815855e+00 -9.96328056e-01 1.09444749e+00
1.02940559e+00 -1.75731659e+00 1.45054579e-01 8.87052044e-02
4.47319418e-01 1.62874663e+00 8.90192688e-01 -5.99057078e-01
1.06668520e+00 -1.06586805e-02 -3.51537645e-01 9.51217934e-02
-2.20508531e-01 -6.22103751e-01 -9.09845755e-02 8.33892465e-01
1.18357575e+00 -4.73577082e-02 -1.17655826e+00 2.91751593e-01
-9.94713306e-01 5.42375624e-01 1.10129499e+00 8.30502510e-01
-8.19861174e-01 -3.44009519e-01 -1.42316055e+00 2.64302373e-01
-1.03630781e+00 8.59065115e-01 3.16442072e-01 9.62298214e-01
4.96220767e-01 2.87635875e+00 -1.97269410e-01 -1.34590995e+00
1.87428117e+00 -3.06331664e-01 6.58436120e-01 -1.87210664e-01
-1.55296099e+00 -5.05057514e-01 1.55011928e-02 5.97730100e-01
-3.51568073e-01 5.49249761e-02 -8.44043791e-01 -1.25045371e+00
2.69544758e-02 1.93459451e+00 1.32174230e+00 7.77614057e-01
3.76854166e-02 1.01400650e+00 1.00499523e+00 -8.94872546e-01
-1.08167124e+00 -1.19793284e+00 -8.28077555e-01 -5.85428357e-01
3.44574153e-01 -7.72199988e-01 -1.41028118e+00 -1.04530513e+00] | [-3.316117763519287, 6.907679080963135] |
23f89d57-1c3c-4c4f-bc0b-eaa7aa0c0b46 | itkd-interchange-transfer-based-knowledge | 2205.15531 | null | https://arxiv.org/abs/2205.15531v2 | https://arxiv.org/pdf/2205.15531v2.pdf | itKD: Interchange Transfer-based Knowledge Distillation for 3D Object Detection | Point-cloud based 3D object detectors recently have achieved remarkable progress. However, most studies are limited to the development of network architectures for improving only their accuracy without consideration of the computational efficiency. In this paper, we first propose an autoencoder-style framework comprising channel-wise compression and decompression via interchange transfer-based knowledge distillation. To learn the map-view feature of a teacher network, the features from teacher and student networks are independently passed through the shared autoencoder; here, we use a compressed representation loss that binds the channel-wised compression knowledge from both student and teacher networks as a kind of regularization. The decompressed features are transferred in opposite directions to reduce the gap in the interchange reconstructions. Lastly, we present an head attention loss to match the 3D object detection information drawn by the multi-head self-attention mechanism. Through extensive experiments, we verify that our method can train the lightweight model that is well-aligned with the 3D point cloud detection task and we demonstrate its superiority using the well-known public datasets; e.g., Waymo and nuScenes. | ['Wonjun Hwang', 'Geonwoo Baek', 'Junyong Choi', 'Hyeon Cho'] | 2022-05-31 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Cho_itKD_Interchange_Transfer-Based_Knowledge_Distillation_for_3D_Object_Detection_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Cho_itKD_Interchange_Transfer-Based_Knowledge_Distillation_for_3D_Object_Detection_CVPR_2023_paper.pdf | cvpr-2023-1 | ['cloud-detection'] | ['computer-vision'] | [-1.86630577e-01 -3.91421467e-03 -1.78869385e-02 -4.32996154e-01
-6.50632739e-01 -2.13114068e-01 5.83761990e-01 -1.71098113e-01
-5.12356281e-01 8.47916156e-02 -1.45141870e-01 -2.23673999e-01
-4.72841449e-02 -9.01477754e-01 -1.33028555e+00 -7.12990761e-01
9.08409879e-02 4.41494703e-01 4.17762667e-01 1.29293770e-01
3.28211822e-02 7.79921651e-01 -1.93308091e+00 2.28086963e-01
7.69288182e-01 1.24561226e+00 4.98070717e-01 5.08191586e-01
-6.59570172e-02 9.49452341e-01 -5.29298842e-01 -4.73997056e-01
4.89960760e-01 4.28228378e-02 -6.23912454e-01 -3.98804583e-02
6.87416136e-01 -7.87500560e-01 -8.40364695e-01 9.99404967e-01
7.38335550e-01 2.13485673e-01 7.10887253e-01 -1.27617562e+00
-7.87616134e-01 2.91917652e-01 -6.52062058e-01 1.68666765e-01
7.55313202e-04 1.28104731e-01 8.53766680e-01 -1.11101878e+00
5.36893427e-01 1.28101420e+00 6.09655738e-01 4.84189183e-01
-8.56134713e-01 -8.98705959e-01 1.76534131e-01 7.03227222e-01
-1.61711204e+00 -1.77436829e-01 9.44157839e-01 -2.18449786e-01
1.38458765e+00 4.80179898e-02 9.82571483e-01 9.04635906e-01
-2.52730787e-01 1.14453113e+00 6.43430650e-01 -3.43971997e-01
1.01999626e-01 3.99167955e-01 -1.97045952e-01 6.88473701e-01
1.14050299e-01 2.18704060e-01 -6.75676465e-01 2.67673939e-01
7.02457130e-01 1.52131543e-01 -2.09377572e-01 -6.58519268e-01
-6.87578261e-01 9.59866822e-01 1.00734568e+00 1.11861847e-01
-2.48752296e-01 9.76749808e-02 1.60706803e-01 3.72218043e-01
6.48421824e-01 -1.08875602e-01 -4.84699756e-01 2.90157765e-01
-8.83628666e-01 1.67565197e-01 8.14375341e-01 1.50286758e+00
9.07118022e-01 -1.04021594e-01 9.09466948e-03 5.43319881e-01
4.39822704e-01 5.30078173e-01 3.45951259e-01 -7.47996330e-01
4.53010261e-01 7.43421435e-01 -3.36445063e-01 -9.21030164e-01
-7.54512008e-03 -6.24371946e-01 -7.77522981e-01 2.65180111e-01
-7.74766728e-02 2.40411982e-01 -8.63794029e-01 1.56976128e+00
6.76944017e-01 7.33030319e-01 5.37958145e-02 1.10164320e+00
1.13152659e+00 5.99059761e-01 -9.63006467e-02 2.91987717e-01
1.27786922e+00 -9.82097566e-01 -1.34055376e-01 -5.43555617e-02
5.70712388e-01 -5.74007332e-01 7.99372733e-01 7.96746388e-02
-1.29086208e+00 -6.91578567e-01 -1.10914087e+00 -5.83262324e-01
-4.85702068e-01 2.41749100e-02 5.34875214e-01 2.80707866e-01
-9.20340538e-01 6.64110720e-01 -9.96841729e-01 -1.81718305e-01
7.94503570e-01 3.97899926e-01 -4.00779784e-01 -2.08274946e-01
-8.07349980e-01 1.02720439e+00 4.90392864e-01 -1.75606892e-01
-1.05589426e+00 -8.91201735e-01 -6.17308557e-01 4.24693406e-01
1.46156013e-01 -9.53310847e-01 1.22739315e+00 -5.30436635e-01
-1.46505702e+00 1.08113706e+00 2.86736995e-01 -5.44054508e-01
4.74539489e-01 -3.99226815e-01 1.14345863e-01 3.30009460e-01
-4.52276990e-02 1.25454700e+00 1.01008916e+00 -9.83812869e-01
-8.75841081e-01 -5.14611483e-01 -1.04415908e-01 4.93120521e-01
-6.91740036e-01 -2.00122163e-01 -8.28924716e-01 -3.72288525e-01
2.79401541e-01 -7.77304471e-01 9.57724452e-02 3.15376133e-01
-2.31299564e-01 -6.57078862e-01 1.08340442e+00 -2.88494140e-01
6.62303567e-01 -2.38448310e+00 2.21749410e-01 -1.96399894e-02
3.48453164e-01 3.00611377e-01 -3.00096035e-01 7.01037422e-02
-5.13676926e-02 -2.04815269e-01 -7.69302398e-02 -6.24182105e-01
9.12612826e-02 3.82624745e-01 -4.39899474e-01 6.34256601e-01
4.43395913e-01 8.84181499e-01 -6.74287796e-01 -5.54217398e-01
3.32376271e-01 8.94265234e-01 -9.70170557e-01 5.65695345e-01
-9.17935446e-02 1.13668256e-01 -5.05272746e-01 5.46924293e-01
9.70508695e-01 -3.83010119e-01 -4.82598692e-01 -2.80476213e-01
-1.79167286e-01 4.20790195e-01 -9.02221859e-01 2.00699735e+00
-2.44816840e-01 5.30949056e-01 2.10324511e-01 -1.12721157e+00
7.78216660e-01 1.48622259e-01 2.97393590e-01 -6.24445140e-01
4.11396980e-01 1.27987796e-02 -3.26471657e-01 -3.86331409e-01
2.76710600e-01 1.09575503e-01 4.23343360e-01 3.66126090e-01
5.46620727e-01 -4.95881826e-01 -2.76535690e-01 2.23193899e-01
9.59205091e-01 4.05143313e-02 -1.81185022e-01 1.50697246e-01
4.16856796e-01 -1.15763895e-01 2.09745705e-01 8.97268057e-01
-2.03818232e-01 4.47865218e-01 -5.38053224e-03 -3.93661827e-01
-1.09513950e+00 -1.00364304e+00 -3.06857347e-01 1.23170650e+00
1.61017522e-01 -2.94804394e-01 -7.27083981e-01 -7.29268789e-01
3.76484364e-01 5.05410492e-01 -3.75941247e-01 -4.69016165e-01
-3.78352255e-01 -4.12693799e-01 6.29936576e-01 6.75357342e-01
7.04334021e-01 -7.54515946e-01 -8.25447142e-01 2.28465907e-02
2.17208862e-01 -1.26327193e+00 -1.22509133e-02 4.83927310e-01
-9.00801003e-01 -1.05924928e+00 -6.67186975e-01 -1.06125379e+00
6.13479495e-01 7.80279756e-01 9.84135568e-01 1.29063591e-01
-3.02416801e-01 4.87458885e-01 -3.12765509e-01 -8.00133765e-01
4.36821096e-02 2.62001336e-01 6.16968051e-02 -2.84763426e-01
8.43809128e-01 -7.70425975e-01 -6.22611284e-01 1.27484888e-01
-7.93485403e-01 6.84025511e-02 8.34171236e-01 6.81181788e-01
8.20053101e-01 -8.34333599e-02 6.45501092e-02 -3.11491132e-01
2.74852395e-01 -4.08544898e-01 -7.27695763e-01 -8.77943784e-02
-4.30288166e-01 4.71128188e-02 3.28072280e-01 -4.63885963e-01
-8.85941029e-01 2.75845826e-01 -3.70463550e-01 -1.24548364e+00
-2.70737827e-01 7.54771531e-02 -3.43459584e-02 -5.45497537e-01
4.22261238e-01 4.95690197e-01 -1.02817498e-01 -6.83013976e-01
6.02091849e-01 6.44561231e-01 6.67236209e-01 -4.42439795e-01
1.05898356e+00 6.04827225e-01 -1.03875093e-01 -7.36075521e-01
-8.81727219e-01 -3.58692348e-01 -6.37126625e-01 -1.83691382e-02
9.43411350e-01 -1.41865063e+00 -1.05560517e+00 5.32247841e-01
-1.46325791e+00 3.79348956e-02 -5.19115865e-01 7.20636666e-01
-6.26813471e-01 1.17534839e-01 -7.88464844e-01 -5.56828916e-01
-4.53095704e-01 -1.08157635e+00 1.09841490e+00 1.75736606e-01
6.62901998e-01 -4.35611814e-01 -9.88785028e-02 1.64638788e-01
3.38281184e-01 -3.26221436e-01 8.59225571e-01 -7.57262766e-01
-1.09933209e+00 -2.61793822e-01 -5.46624959e-01 5.06749749e-01
-5.80927968e-01 -3.74871910e-01 -1.27055991e+00 -3.86827588e-01
4.39574212e-01 -5.94496250e-01 1.18200707e+00 1.48847580e-01
1.54759502e+00 -2.67560124e-01 -3.00589830e-01 1.09262872e+00
1.22058225e+00 -3.18513960e-01 3.01851958e-01 1.25926688e-01
8.92809212e-01 3.99363369e-01 8.05327743e-02 4.00628418e-01
6.06928587e-01 3.89962941e-01 8.48173916e-01 7.71198645e-02
-3.19281816e-01 -6.06954396e-01 1.44016044e-02 1.26653051e+00
-1.50187582e-01 -1.70482337e-01 -7.13781118e-01 3.50125939e-01
-1.57960951e+00 -8.50589454e-01 2.53618002e-01 1.89265406e+00
6.42309666e-01 4.21256162e-02 -2.98459351e-01 -9.29098576e-02
5.07828832e-01 1.09802820e-01 -6.50562108e-01 8.32217559e-02
-8.13089311e-02 1.48827538e-01 5.12399912e-01 2.04828128e-01
-1.23298025e+00 1.03447497e+00 5.75201559e+00 9.25027072e-01
-1.07192135e+00 3.08755845e-01 2.70781040e-01 -4.30923283e-01
-8.51917360e-03 -1.61229029e-01 -9.93902802e-01 2.78773189e-01
6.60885096e-01 1.09805718e-01 3.68139952e-01 1.15881538e+00
-4.60406482e-01 3.18678260e-01 -1.33593512e+00 1.23999107e+00
2.45108381e-01 -1.29776478e+00 1.45448044e-01 -2.13852245e-03
6.46954954e-01 5.92603445e-01 2.51232386e-01 5.15968680e-01
9.80072916e-02 -7.12352633e-01 8.15242887e-01 3.46040249e-01
5.51185012e-01 -7.79787838e-01 5.72788358e-01 7.25329518e-01
-1.04228938e+00 -1.80298597e-01 -8.39033425e-01 -6.66884929e-02
-2.26947755e-01 5.13221800e-01 -9.12699997e-01 3.53169739e-01
1.15079308e+00 7.49576271e-01 -4.11114216e-01 1.06545711e+00
-4.58721757e-01 4.38299805e-01 -7.59802341e-01 -1.00034419e-02
3.45062971e-01 -1.44553352e-02 6.75329268e-01 1.00785565e+00
4.72234666e-01 2.98613280e-01 4.66908654e-03 1.10595202e+00
-4.91847754e-01 -1.02074362e-01 -8.03992152e-01 3.76525015e-01
6.64072096e-01 9.53679979e-01 -1.66168749e-01 -2.71534055e-01
-7.55509079e-01 9.40355301e-01 7.21651495e-01 1.34764940e-01
-6.78030908e-01 -2.79661268e-01 6.84134364e-01 -7.41675422e-02
8.48784447e-01 -4.85892557e-02 -8.04259852e-02 -1.20330215e+00
-6.44375905e-02 -3.96898389e-01 2.53810287e-01 -7.59285033e-01
-1.43892384e+00 3.45182180e-01 2.04852168e-02 -1.17717505e+00
4.37990129e-02 -6.72621608e-01 -7.00746119e-01 7.16004789e-01
-1.86930048e+00 -1.18515873e+00 -4.01719183e-01 8.11554432e-01
2.76133984e-01 -2.34785259e-01 6.20718062e-01 7.01831102e-01
-4.82326001e-01 8.07122350e-01 -5.41838221e-02 1.53710425e-01
5.86016238e-01 -9.60307777e-01 3.00771594e-01 5.24604499e-01
2.54925907e-01 2.48803228e-01 3.19179088e-01 -3.79408181e-01
-1.70894194e+00 -1.18971992e+00 7.41313517e-01 -3.95803064e-01
4.64829504e-01 -6.14826322e-01 -1.16099346e+00 7.43024826e-01
8.80548581e-02 3.10377866e-01 4.36504900e-01 -4.58565317e-02
-5.43832302e-01 -1.51441619e-01 -1.01193810e+00 1.29329517e-01
1.21253276e+00 -7.58864224e-01 -8.00229073e-01 4.38928902e-01
1.09686291e+00 -6.99900925e-01 -7.48772681e-01 4.69147652e-01
2.51293838e-01 -9.41496313e-01 1.22274363e+00 -6.08185887e-01
4.72535998e-01 -2.19864696e-01 -2.57962644e-01 -1.00829756e+00
-4.19137239e-01 4.53196466e-02 -5.80962598e-01 9.52345133e-01
2.10442021e-02 -2.32718140e-01 1.14888108e+00 2.52686769e-01
-4.91507679e-01 -8.54505002e-01 -1.26206267e+00 -7.11105525e-01
1.31737441e-01 -5.94330907e-01 8.79210353e-01 8.94825339e-01
-3.56531262e-01 4.14900392e-01 -2.44140208e-01 3.41833651e-01
7.74978936e-01 1.96663260e-01 8.33843291e-01 -1.28543210e+00
-3.14883769e-01 -4.41400975e-01 -6.25317216e-01 -1.59645307e+00
2.08082423e-01 -1.22379756e+00 -4.31273207e-02 -9.93569970e-01
3.87172997e-01 -3.69595557e-01 -3.22232813e-01 4.67663258e-01
4.72733118e-02 1.64638594e-01 5.24139583e-01 2.53719091e-01
-7.52246022e-01 1.01858771e+00 1.21338010e+00 -2.67631948e-01
-1.87533587e-01 -1.64526030e-01 -4.04731810e-01 7.98061132e-01
3.63487929e-01 -7.01986134e-01 -2.69125134e-01 -1.05006146e+00
3.60491942e-03 -1.78568542e-01 6.87971652e-01 -1.16691113e+00
9.15726662e-01 2.90749609e-01 7.42999434e-01 -1.11240518e+00
4.76320177e-01 -1.12921262e+00 -3.49691808e-01 3.66087705e-01
-2.02174366e-01 -3.12896997e-01 1.79750443e-01 6.68414652e-01
-1.41619638e-01 -1.03336252e-01 7.26419508e-01 -1.48438141e-01
-6.42182350e-01 7.16104567e-01 2.17440248e-01 -2.22564012e-01
1.04238153e+00 -1.24732777e-01 -3.08939785e-01 -1.36421859e-01
-4.91217047e-01 3.72278184e-01 2.30506659e-01 3.32268536e-01
8.65043461e-01 -1.33544075e+00 -7.19240189e-01 6.80377364e-01
6.07337393e-02 5.48257113e-01 3.57101858e-01 6.05148256e-01
-3.46376538e-01 4.05586928e-01 -2.31900707e-01 -8.93122196e-01
-9.30965841e-01 8.36950898e-01 2.26721674e-01 1.26147866e-01
-9.78016675e-01 1.24566376e+00 3.40693593e-01 -5.87244213e-01
8.22096765e-01 -1.69968039e-01 9.26104933e-02 -9.99091268e-02
5.32045543e-01 2.92356431e-01 1.73668891e-01 -3.75935704e-01
-3.92447412e-01 5.73380470e-01 -2.59831518e-01 3.27229887e-01
1.62609923e+00 6.50660098e-02 1.48631409e-01 -2.81960815e-02
1.54687500e+00 -5.12743175e-01 -1.52998376e+00 -4.08765674e-01
-4.51303571e-01 -4.61188972e-01 4.11780357e-01 -3.47620577e-01
-1.28081369e+00 1.25087774e+00 8.07763278e-01 -7.96607584e-02
1.18218923e+00 4.84465539e-01 7.60501683e-01 7.69334257e-01
1.56196132e-01 -9.24509823e-01 8.48289579e-03 7.70322382e-01
6.75730586e-01 -1.31825542e+00 -2.49798670e-02 -4.36859727e-01
-1.70233771e-01 7.21902370e-01 8.30438733e-01 -4.35305834e-01
7.10404396e-01 1.50115713e-01 -3.22954714e-01 -2.91323006e-01
-9.49000418e-01 -3.36954981e-01 2.56288558e-01 5.40455937e-01
-5.16090654e-02 -4.01512012e-02 2.88708836e-01 6.02491379e-01
-2.73750693e-01 -1.10390738e-01 -1.03280105e-01 9.29205775e-01
-7.41620421e-01 -6.96187973e-01 -2.34980896e-01 4.82301861e-01
-1.21379070e-01 6.25954987e-03 -3.12593162e-01 8.01155388e-01
2.64697194e-01 4.89004850e-01 3.82145107e-01 -5.82025290e-01
4.47619706e-01 1.57107655e-02 6.35377467e-01 -4.78684336e-01
-5.52489698e-01 -1.34423688e-01 -6.47630513e-01 -5.74933469e-01
-2.57563949e-01 -2.04131201e-01 -1.14209676e+00 -4.93157595e-01
-5.21631181e-01 -2.95664109e-02 8.29804122e-01 7.43460476e-01
6.42468214e-01 4.25841421e-01 5.63876092e-01 -1.12628758e+00
-8.68389547e-01 -8.11020315e-01 -4.47126746e-01 4.17268068e-01
3.21619660e-01 -7.00360298e-01 -5.30071437e-01 -2.25508630e-01] | [8.009734153747559, -3.312575340270996] |
3509e086-53bb-4208-a170-0f65238e4723 | hyperbolic-disentangled-representation-for | 2112.09215 | null | https://arxiv.org/abs/2112.09215v1 | https://arxiv.org/pdf/2112.09215v1.pdf | Hyperbolic Disentangled Representation for Fine-Grained Aspect Extraction | Automatic identification of salient aspects from user reviews is especially useful for opinion analysis. There has been significant progress in utilizing weakly supervised approaches, which require only a small set of seed words for training aspect classifiers. However, there is always room for improvement. First, no weakly supervised approaches fully utilize latent hierarchies between words. Second, each seed words representation should have different latent semantics and be distinct when it represents a different aspect. In this paper, we propose HDAE, a hyperbolic disentangled aspect extractor in which a hyperbolic aspect classifier captures words latent hierarchies, and aspect-disentangled representation models the distinct latent semantics of each seed word. Compared to previous baselines, HDAE achieves average F1 performance gains of 18.2% and 24.1% on Amazon product review and restaurant review datasets, respectively. In addition, the em-bedding visualization experience demonstrates that HDAE is a more effective approach to leveraging seed words. An ablation study and a case study further attest to the effectiveness of the proposed components | ['Lun-Wei Ku', 'Ming-Yao Li', 'Chang-You Tai'] | 2021-12-16 | null | null | null | null | ['aspect-extraction'] | ['natural-language-processing'] | [-8.03666413e-02 3.75374496e-01 -7.28440166e-01 -3.88580173e-01
-8.41249466e-01 -8.15743327e-01 7.73845792e-01 3.79612893e-01
-1.92441382e-02 2.51119494e-01 7.00087786e-01 -3.92409742e-01
2.48702675e-01 -6.35693610e-01 -2.68540476e-02 -5.95026791e-01
1.51473433e-01 3.46966147e-01 -1.88351005e-01 -2.83912241e-01
4.71720725e-01 -2.55682040e-03 -1.51159751e+00 3.52579713e-01
6.57614172e-01 5.72223246e-01 -2.36378446e-01 5.70825219e-01
-3.65104407e-01 2.90573269e-01 -7.01996684e-01 -6.66645169e-01
1.47532085e-02 -3.41905892e-01 -5.25209129e-01 2.62452632e-01
5.28705001e-01 -1.69708565e-01 2.01930121e-01 8.10102463e-01
2.86616832e-01 -1.34892404e-01 8.65832984e-01 -1.33956146e+00
-1.03721023e+00 9.26281393e-01 -1.06884086e+00 1.04308076e-01
2.64369756e-01 -1.01618931e-01 1.93106377e+00 -1.28827536e+00
2.82688290e-01 1.14949501e+00 5.12467742e-01 2.52166539e-01
-1.35880220e+00 -6.50856018e-01 6.19117439e-01 -2.34965354e-01
-9.76560295e-01 -2.16941968e-01 6.20198786e-01 -1.80668727e-01
1.13735378e+00 3.18217486e-01 1.09996581e+00 9.38593626e-01
7.87550211e-02 1.30430555e+00 1.38265491e+00 -3.09357941e-01
2.71308690e-01 6.82099581e-01 9.62851822e-01 6.46447480e-01
9.24423516e-01 -2.44930193e-01 -8.20637047e-01 -5.13802111e-01
1.86838448e-01 1.18303373e-01 1.06922090e-02 -6.04314029e-01
-9.16062772e-01 1.04630685e+00 8.22360963e-02 3.14123556e-02
-2.11924881e-01 -1.41582057e-01 3.56937230e-01 9.94880199e-02
9.70427573e-01 8.30946088e-01 -5.48407197e-01 -2.43279949e-01
-9.50263083e-01 1.96052626e-01 1.10225558e+00 1.12303877e+00
8.42805862e-01 -2.03228015e-02 -9.36523601e-02 5.89017272e-01
5.33256888e-01 7.20160723e-01 3.20493400e-01 -5.58899760e-01
1.01061814e-01 1.01036561e+00 -1.01493232e-01 -1.05386853e+00
-1.59394845e-01 -6.21068656e-01 -4.61184829e-01 1.74444124e-01
-1.90030396e-01 4.25183699e-02 -1.11077523e+00 1.36395442e+00
1.76736251e-01 -9.22958702e-02 1.95616022e-01 5.09419978e-01
8.85359466e-01 4.74361211e-01 1.50151223e-01 2.32568812e-02
1.86274016e+00 -1.20943236e+00 -9.82016027e-01 -5.03290474e-01
5.49727380e-01 -9.09061313e-01 1.63258767e+00 4.33183819e-01
-1.02462816e+00 -9.64944363e-02 -1.48119092e+00 -1.28962725e-01
-6.58915579e-01 2.93588817e-01 1.05467463e+00 8.09285998e-01
-7.89426923e-01 9.26007330e-03 -7.91443586e-01 -1.64820686e-01
3.44275534e-01 1.37783244e-01 -2.93489128e-01 4.67248820e-03
-9.20217812e-01 6.66594505e-01 -1.62141621e-01 -2.11895540e-01
-5.20604372e-01 -7.40602553e-01 -1.14107001e+00 2.66619116e-01
2.67648280e-01 -6.31225049e-01 1.29906595e+00 -6.76297724e-01
-9.75087106e-01 8.14806998e-01 -5.40476799e-01 -1.45261601e-01
-3.45079273e-01 -6.56716883e-01 -4.19272482e-01 1.95288256e-01
4.93276000e-01 4.37567055e-01 9.90726590e-01 -1.47702551e+00
-5.40212274e-01 -4.86097991e-01 2.66414255e-01 4.69138801e-01
-7.92568088e-01 -1.10776074e-01 -4.40521538e-01 -7.54422247e-01
6.42957687e-02 -1.00908303e+00 -2.16555342e-01 -2.73103982e-01
-4.63120610e-01 -2.10969627e-01 1.01363242e+00 -2.82834500e-01
1.49999213e+00 -2.27195811e+00 -1.59388378e-01 9.51515883e-02
7.04079986e-01 7.28904679e-02 -1.77972868e-01 3.58762741e-01
-3.86203974e-02 5.04728436e-01 -1.18568026e-01 -7.02470660e-01
1.03733972e-01 2.30766945e-02 -6.65385365e-01 1.14943415e-01
2.16979027e-01 9.58490074e-01 -9.48972464e-01 -1.84589133e-01
-2.69198895e-01 5.52588522e-01 -5.06548405e-01 -7.25083873e-02
-1.94456026e-01 -4.87819880e-01 -3.66394013e-01 6.51813865e-01
5.80909491e-01 -7.59508789e-01 1.51561499e-01 -2.97079712e-01
9.47992057e-02 6.20733798e-01 -9.00872469e-01 1.45548809e+00
-5.19594908e-01 8.87348473e-01 -3.30271125e-01 -1.81829080e-01
9.27126646e-01 2.55723476e-01 1.55049026e-01 -2.41769686e-01
-1.11285359e-01 7.91108422e-03 -3.22693467e-01 -2.20624596e-01
1.10931313e+00 -2.09252104e-01 -2.83055186e-01 1.12161946e+00
-5.14361635e-02 -3.88183266e-01 2.24179819e-01 7.63475835e-01
8.72873306e-01 -4.87614684e-02 6.70174479e-01 -4.04543221e-01
-2.08782195e-03 2.23432854e-01 2.07441658e-01 4.44749892e-01
-1.86771482e-01 7.86666572e-01 8.46877992e-01 -3.33159387e-01
-9.27790880e-01 -1.23048484e+00 3.89416404e-02 1.12338269e+00
2.89132118e-01 -1.05837071e+00 -3.15038472e-01 -8.84701192e-01
-3.00625581e-02 1.08686149e+00 -9.26042795e-01 -2.72314548e-01
-3.22856158e-01 -8.14617753e-01 1.82089821e-01 6.72889709e-01
2.42073089e-01 -6.15750074e-01 -4.17158335e-01 -2.30470359e-01
-9.57015082e-02 -1.13322616e+00 -6.71292961e-01 2.34030753e-01
-8.26411784e-01 -1.04206693e+00 -4.92238581e-01 -6.36036038e-01
8.14931750e-01 1.07037401e+00 1.70118797e+00 -1.39774263e-01
-1.05977207e-01 4.76569116e-01 -5.56224346e-01 -6.06041551e-01
-9.15823877e-02 5.00713706e-01 1.93454893e-04 -3.07387352e-01
1.28771842e+00 -4.52613473e-01 -9.23195541e-01 1.72772259e-01
-7.12987244e-01 4.12979499e-02 8.02095413e-01 6.89158797e-01
4.96421129e-01 -2.61812091e-01 3.29271823e-01 -1.33769166e+00
1.09073877e+00 -6.29526019e-01 -1.81055497e-02 1.46706328e-01
-1.30194068e+00 1.29950121e-01 1.96409956e-01 -3.71045619e-01
-1.04137337e+00 -3.94426286e-01 3.53074670e-01 7.81262740e-02
2.08274089e-02 6.57599568e-01 2.36458499e-02 9.01087880e-01
6.77466273e-01 2.33739931e-02 3.62552777e-02 -2.23697767e-01
7.58285105e-01 6.62379622e-01 -1.80942670e-01 -1.93887889e-01
6.39773905e-01 6.38043463e-01 -4.19332385e-01 -7.90837228e-01
-1.39525473e+00 -8.28063607e-01 -4.01023865e-01 3.17470998e-01
8.13827097e-01 -1.27407837e+00 -2.23550871e-01 3.35482098e-02
-8.75940621e-01 2.34295219e-01 -6.38502002e-01 2.67669648e-01
-4.05178517e-02 2.19151095e-01 -4.94636655e-01 -6.55500412e-01
-6.38831675e-01 -1.00397468e+00 1.36634386e+00 2.82277554e-01
-8.32422256e-01 -1.11422467e+00 2.98793286e-01 4.68753844e-01
3.94142896e-01 -1.22024842e-01 1.09323859e+00 -9.37054634e-01
-4.49642867e-01 -4.52935815e-01 -1.08070999e-01 2.76598275e-01
5.09450018e-01 5.01337983e-02 -1.10754979e+00 -2.43248135e-01
-1.79627519e-02 -3.93560559e-01 8.50014329e-01 1.17299490e-01
3.40268970e-01 -3.88729542e-01 -3.44529182e-01 1.52237684e-01
1.10308123e+00 -2.76996315e-01 2.69097060e-01 2.40045860e-01
7.29446709e-01 5.22446573e-01 5.95497370e-01 2.72361457e-01
6.49346292e-01 3.17980260e-01 2.27433126e-02 -3.20963264e-01
-1.30902186e-01 -4.14682448e-01 5.62379718e-01 1.29170215e+00
3.29944104e-01 -9.09026414e-02 -7.03316450e-01 6.91744566e-01
-1.47491205e+00 -7.36691415e-01 -1.84801191e-01 1.89016700e+00
7.39795089e-01 3.29619348e-01 1.43689230e-01 2.58610249e-02
2.93876857e-01 6.35307550e-01 -5.74263930e-01 -5.90336323e-01
-2.41443783e-01 1.87654242e-01 4.25031260e-02 5.49244165e-01
-9.04538214e-01 8.78562212e-01 6.60597515e+00 5.35131395e-01
-6.93146467e-01 -3.37359048e-02 5.86165488e-01 -2.40034878e-01
-1.07760739e+00 2.71847188e-01 -9.60319638e-01 -9.60510597e-02
6.84860349e-01 -4.55537498e-01 -2.90681064e-01 1.20976853e+00
-2.78956071e-02 -2.59174019e-01 -1.01413989e+00 7.11012602e-01
5.93192875e-01 -1.00864494e+00 5.13455451e-01 2.15402678e-01
9.31353569e-01 -2.70361960e-01 6.34271979e-01 4.03082788e-01
5.22150755e-01 -9.99433100e-01 1.73719019e-01 -6.21621609e-02
5.56053758e-01 -8.39363515e-01 5.86708963e-01 -4.62784228e-04
-1.30791795e+00 3.07762504e-01 -2.72816688e-01 -8.86555575e-03
1.10170089e-01 6.48868859e-01 -8.70676577e-01 9.95764881e-02
4.88376260e-01 9.15953100e-01 -7.60954738e-01 4.67288524e-01
-6.93274438e-01 8.48734319e-01 8.41040164e-02 -3.61816555e-01
2.84883827e-01 -1.65466413e-01 6.31155610e-01 1.19140780e+00
2.05436256e-02 -1.22172542e-01 9.46349092e-03 6.88543260e-01
7.36207664e-02 2.73519307e-01 -8.55813980e-01 -4.48422730e-01
2.29055911e-01 1.65136969e+00 -9.41519976e-01 -5.07290781e-01
-7.54461050e-01 1.02593553e+00 1.66429549e-01 5.61985433e-01
-4.30742562e-01 -2.89969981e-01 1.03883469e+00 5.89110442e-02
4.87415463e-01 -3.77030551e-01 -8.08878303e-01 -1.49381721e+00
-3.30974609e-02 -1.11962748e+00 2.69192815e-01 -7.11897790e-01
-1.37380397e+00 8.68939340e-01 8.23309422e-02 -1.28392410e+00
-2.45805338e-01 -4.94522542e-01 -5.80839396e-01 9.02133524e-01
-1.44021404e+00 -1.20319963e+00 -2.15154901e-01 1.76939256e-02
8.64259601e-01 -2.10441768e-01 1.21245205e+00 -2.90313601e-01
-2.75749028e-01 6.09681189e-01 -2.43098482e-01 -2.06601694e-01
6.87087357e-01 -1.73564577e+00 8.80558312e-01 7.43553400e-01
6.06830180e-01 1.16299617e+00 8.70244086e-01 -6.97325349e-01
-1.20912540e+00 -6.44952476e-01 1.01037705e+00 -8.85803342e-01
7.83688188e-01 -6.07456982e-01 -8.25061798e-01 6.76935196e-01
8.67510557e-01 -4.13954794e-01 1.65207112e+00 8.94853294e-01
-9.70304608e-01 1.95064321e-01 -6.27538562e-01 1.10029995e+00
5.90187788e-01 -7.99807489e-01 -8.65715742e-01 -3.89958285e-02
1.14098036e+00 1.16182849e-01 -4.99334276e-01 3.52260441e-01
6.98178530e-01 -8.24160457e-01 6.94908381e-01 -8.07285964e-01
7.23054290e-01 -1.76481545e-01 -1.05130211e-01 -1.52901256e+00
-2.86079049e-01 -4.78882283e-01 -6.54012263e-01 1.20937276e+00
9.84201849e-01 -3.96077514e-01 9.74968374e-01 7.44287610e-01
2.52114236e-01 -1.15337670e+00 -1.37073576e-01 -4.21477973e-01
-3.28199081e-02 -3.56564075e-01 4.94197965e-01 8.64601851e-01
3.07365149e-01 1.21246135e+00 -1.65364355e-01 3.61650549e-02
5.20900011e-01 6.14120781e-01 7.18369424e-01 -9.18035924e-01
-4.39264655e-01 -4.32019234e-01 -1.17394499e-01 -1.25385404e+00
6.66518733e-02 -7.88041711e-01 -1.93807676e-01 -1.69672120e+00
6.69383883e-01 -2.87283301e-01 -3.25650394e-01 3.42814296e-01
-8.48173738e-01 2.93063819e-01 3.78728807e-02 1.82908475e-01
-6.29864752e-01 7.53323317e-01 1.19381189e+00 -3.05958450e-01
-2.30198011e-01 1.64233506e-01 -1.53554702e+00 8.50747645e-01
1.02592134e+00 -4.13244992e-01 -9.74867880e-01 -3.09404641e-01
7.46976614e-01 -6.44218385e-01 -1.36306986e-01 -2.31149361e-01
3.79146673e-02 1.78253949e-01 1.72293901e-01 -8.06712389e-01
4.91081297e-01 -6.28675222e-01 -5.73577285e-01 1.05128452e-01
-4.18165982e-01 6.53667212e-01 2.07190752e-01 7.29968965e-01
-3.60293508e-01 -2.09299959e-02 2.54072845e-01 -1.47298664e-01
-4.15396333e-01 5.58763742e-02 -5.49170554e-01 3.02626431e-01
7.84239709e-01 -1.01368666e-01 -5.17073929e-01 -5.27889490e-01
-5.37210166e-01 1.53734952e-01 4.02500361e-01 6.29076004e-01
8.86751592e-01 -1.25158966e+00 -5.01460791e-01 2.53815860e-01
5.26269615e-01 -2.41366535e-01 -1.15961604e-01 4.52758849e-01
1.52738160e-02 2.61166990e-01 2.77372718e-01 -4.33348864e-01
-1.58334184e+00 5.90968549e-01 -2.80429989e-01 -4.47842002e-01
-5.90516388e-01 7.77337313e-01 3.61443460e-01 -3.13467234e-01
3.49398032e-02 -3.32478672e-01 -4.32624757e-01 5.62092185e-01
7.05309570e-01 2.75731206e-01 -1.30117789e-01 -5.18662333e-01
-1.30239651e-01 5.50669432e-01 -6.57788038e-01 -4.77961898e-01
1.20844460e+00 -2.24311829e-01 -1.16307773e-01 8.60354960e-01
1.22570252e+00 5.12941658e-01 -8.26930106e-01 -3.06094915e-01
1.71762094e-01 -3.52911890e-01 -6.01846538e-02 -7.41938829e-01
-8.77368093e-01 8.69099081e-01 2.04295978e-01 6.14065588e-01
8.86265397e-01 2.57974327e-01 6.37405932e-01 3.17176163e-01
5.24273701e-02 -7.30141521e-01 3.91612202e-01 4.35697407e-01
7.38319516e-01 -1.36164880e+00 4.45505917e-01 -6.21258676e-01
-1.09573913e+00 7.95107484e-01 7.61996210e-01 -9.44946632e-02
9.17288363e-01 4.41781372e-01 4.15845573e-01 -7.75715590e-01
-1.17063200e+00 -2.35252783e-01 5.76887667e-01 1.57123566e-01
8.50182533e-01 2.02962980e-01 -2.79299438e-01 6.29473150e-01
-4.69498843e-01 -6.79004967e-01 5.54127097e-01 9.08254027e-01
-4.03453827e-01 -1.07709527e+00 1.55155078e-01 5.69119751e-01
-5.05322039e-01 -6.63915098e-01 -5.32145202e-01 7.75702119e-01
-4.54254955e-01 1.03645277e+00 -9.88236591e-02 -2.67687619e-01
3.08543205e-01 9.16321278e-02 -6.39060419e-03 -1.13976717e+00
-5.71506739e-01 2.46433586e-01 1.22353896e-01 -3.95936817e-01
-2.99045742e-01 -5.72119594e-01 -1.18156159e+00 -4.24558930e-02
-5.39177597e-01 5.37083685e-01 6.59624219e-01 7.45882452e-01
6.20695233e-01 3.20550174e-01 5.99403143e-01 -2.21058667e-01
-4.32624459e-01 -8.63320410e-01 -6.44331276e-01 3.69461060e-01
3.80997866e-01 -3.98194849e-01 -6.65580630e-01 -3.77424099e-02] | [11.419685363769531, 6.708292484283447] |
94ae86d1-93e8-4e9c-b49e-ce6b87d1c38f | highlight-detection-with-pairwise-deep | null | null | http://openaccess.thecvf.com/content_cvpr_2016/html/Yao_Highlight_Detection_With_CVPR_2016_paper.html | http://openaccess.thecvf.com/content_cvpr_2016/papers/Yao_Highlight_Detection_With_CVPR_2016_paper.pdf | Highlight Detection With Pairwise Deep Ranking for First-Person Video Summarization | The emergence of wearable devices such as portable cameras and smart glasses makes it possible to record life logging first-person videos. Browsing such long unstructured videos is time-consuming and tedious. This paper studies the discovery of moments of user's major or special interest (i.e., highlights) in a video, for generating the summarization of first-person videos. Specifically, we propose a novel pairwise deep ranking model that employs deep learning techniques to learn the relationship between highlight and non-highlight video segments. A two-stream network structure by representing video segments from complementary information on appearance of video frames and temporal dynamics across frames is developed for video highlight detection. Given a long personal video, equipped with the highlight detection model, a highlight score is assigned to each segment. The obtained highlight segments are applied for summarization in two ways: video timelapse and video skimming. The former plays the highlight (non-highlight) segments at low (high) speed rates, while the latter assembles the sequence of segments with the highest scores. On 100 hours of first-person videos for 15 unique sports categories, our highlight detection achieves the improvement over the state-of-the-art RankSVM method by 10.5% in terms of accuracy. Moreover, our approaches produce video summary with better quality by a user study from 35 human subjects. | ['Ting Yao', 'Yong Rui', 'Tao Mei'] | 2016-06-01 | null | null | null | cvpr-2016-6 | ['highlight-detection'] | ['computer-vision'] | [ 4.29096580e-01 -3.81287813e-01 -2.61279911e-01 -1.81919619e-01
-9.78617072e-01 -5.40497601e-01 4.90259945e-01 3.44596088e-01
-3.56554896e-01 5.61126292e-01 5.07778168e-01 3.65072608e-01
5.31620719e-02 -3.00269872e-01 -8.58607054e-01 -6.78406656e-01
-5.33205450e-01 -3.07716250e-01 3.45435977e-01 8.62038061e-02
3.93481135e-01 1.37280136e-01 -1.97895050e+00 8.44186366e-01
6.18467927e-01 1.16417515e+00 2.92527199e-01 1.01391578e+00
2.08141789e-01 1.02215862e+00 -7.85438955e-01 -3.53330612e-01
1.90896139e-01 -5.05619466e-01 -2.78709799e-01 2.96078712e-01
1.07519305e+00 -7.81201780e-01 -8.41724277e-01 8.66527379e-01
6.77630126e-01 4.36216086e-01 2.83449769e-01 -1.26088881e+00
-2.19076514e-01 5.92124701e-01 -8.14288616e-01 7.37410069e-01
7.09304571e-01 8.15195814e-02 1.13919711e+00 -7.46967614e-01
8.61227691e-01 7.97574341e-01 4.55035746e-01 4.63545769e-01
-7.09244668e-01 -5.89092553e-01 2.51723349e-01 6.64102018e-01
-1.14663696e+00 -5.10919273e-01 9.37749922e-01 -5.28634369e-01
7.29768872e-01 5.24878561e-01 9.50136960e-01 1.31387246e+00
1.32288516e-01 1.12856030e+00 6.26447916e-01 1.05257683e-01
-6.57536313e-02 -1.64486602e-01 5.52774221e-02 7.07364023e-01
1.35888636e-01 -3.75289708e-01 -1.13418198e+00 3.08329705e-03
6.16703093e-01 3.02624345e-01 -3.20131958e-01 1.52593218e-02
-1.42370629e+00 4.31717783e-01 1.34915292e-01 -2.50859987e-02
-6.29863679e-01 1.41489521e-01 8.18242550e-01 1.06367007e-01
4.91259664e-01 1.85301095e-01 2.10499717e-03 -4.21211541e-01
-1.47864938e+00 4.88102585e-01 5.11190116e-01 8.46179366e-01
2.55045354e-01 -7.38554969e-02 -8.70686948e-01 7.79152572e-01
-1.71717763e-01 2.76434898e-01 3.56242537e-01 -1.00698340e+00
6.19254649e-01 5.30908763e-01 1.48754597e-01 -1.45165670e+00
-2.63693959e-01 -4.23155516e-01 -8.42192590e-01 -2.25543782e-01
1.94548190e-01 -1.92232043e-01 -5.63854694e-01 1.45527256e+00
1.44450083e-01 6.80897295e-01 -3.03516537e-01 1.15490830e+00
1.20584369e+00 1.00969326e+00 -1.85661577e-02 -4.99976844e-01
1.60621989e+00 -1.01997113e+00 -5.70682764e-01 1.58087090e-01
9.29087177e-02 -6.52517498e-01 8.34470212e-01 7.84699857e-01
-1.45111001e+00 -7.88624644e-01 -9.29112673e-01 -1.99353218e-01
1.62229970e-01 5.89889646e-01 4.10093725e-01 1.33739024e-01
-8.73381674e-01 7.77982950e-01 -4.69807416e-01 -2.97610372e-01
5.40848553e-01 1.56619012e-01 -3.72450203e-01 1.48018494e-01
-9.73298550e-01 1.02050781e-01 2.25643262e-01 -4.94500026e-02
-1.04768145e+00 -7.05500722e-01 -5.99853218e-01 1.39673993e-01
6.38150394e-01 -6.14371240e-01 1.02432609e+00 -1.14953864e+00
-1.26232243e+00 9.88763988e-01 -3.73242170e-01 -6.23945713e-01
7.77338922e-01 -8.22054923e-01 -2.84319580e-01 8.24398160e-01
1.37495369e-01 4.68472213e-01 1.24455953e+00 -1.00954354e+00
-1.08576393e+00 -8.01146924e-02 2.28890494e-01 4.74645793e-01
-5.15855014e-01 3.68129373e-01 -9.21902537e-01 -7.84129202e-01
-2.83717066e-01 -6.67602956e-01 2.71261692e-01 -8.93322155e-02
-7.02162206e-01 -2.29240954e-01 7.94034719e-01 -1.25144625e+00
1.62845230e+00 -2.16365528e+00 3.88711303e-01 -2.37573143e-02
5.77196240e-01 1.46703273e-01 6.25453293e-02 4.00893956e-01
1.22097962e-01 -1.91790402e-01 2.24567235e-01 -4.30384040e-01
-2.49740407e-01 -3.95850629e-01 -3.59287173e-01 3.60985518e-01
8.96606296e-02 5.50814509e-01 -1.19660127e+00 -6.22281373e-01
1.38350800e-01 4.81204182e-01 -4.59198356e-01 2.78968424e-01
2.14623846e-02 3.83785874e-01 -1.70415804e-01 7.13506401e-01
3.08309168e-01 -1.60615966e-01 1.12159133e-01 -5.27642787e-01
-2.18864232e-01 4.93954606e-02 -1.07839823e+00 1.70501542e+00
-1.08550931e-03 1.01036417e+00 -2.49697745e-01 -6.87148213e-01
5.50055683e-01 2.46888101e-01 7.51044154e-01 -4.91670161e-01
-4.46712598e-02 -1.36726096e-01 -3.12170923e-01 -9.13347363e-01
1.01843870e+00 5.27971625e-01 -1.31834522e-01 1.94557831e-01
-6.29389808e-02 5.31301260e-01 7.29855120e-01 5.88189006e-01
1.15407562e+00 2.89570957e-01 2.58485883e-01 2.27350026e-01
4.66425598e-01 -4.59393173e-01 4.82989341e-01 7.60360599e-01
-2.86243141e-01 8.96428823e-01 7.67849982e-01 -4.34947342e-01
-1.10171914e+00 -9.53579843e-01 5.94378591e-01 1.47951663e+00
2.08708256e-01 -8.03642631e-01 -8.09629381e-01 -3.74956131e-01
-1.50930628e-01 1.46594450e-01 -3.90289426e-01 -1.39058545e-01
-8.54869425e-01 -3.56716871e-01 3.81072879e-01 3.69139910e-01
5.37974179e-01 -1.21682668e+00 -8.97260666e-01 5.01869135e-02
-5.88462114e-01 -1.18856299e+00 -9.48369145e-01 -4.92341876e-01
-7.08557010e-01 -1.18698549e+00 -1.15813959e+00 -8.18583488e-01
5.44461966e-01 6.90150797e-01 9.63433564e-01 -6.36054110e-03
-4.18672562e-01 4.00509626e-01 -5.03467202e-01 4.91295978e-02
7.58729354e-02 -8.29549208e-02 1.96739614e-01 4.76644427e-01
3.33464183e-02 -4.67773557e-01 -9.81806159e-01 -2.50098575e-02
-7.90727317e-01 2.40445107e-01 5.27789474e-01 6.15310311e-01
6.69977367e-01 1.76478311e-01 2.53684968e-01 -5.49211979e-01
6.72268808e-01 -6.48261011e-01 -5.72347976e-02 4.17255498e-02
2.26272456e-02 -5.63226521e-01 5.65820634e-01 -5.99471033e-01
-7.65813887e-01 -7.95153379e-02 4.64992285e-01 -7.29369521e-01
5.35932370e-02 2.46076733e-01 2.82230973e-02 3.88581038e-01
4.09737259e-01 4.35655385e-01 -4.59116518e-01 -3.11243057e-01
1.69780806e-01 4.87059921e-01 9.10126984e-01 -3.50330770e-01
5.46942592e-01 5.64556301e-01 -1.34617507e-01 -1.16048765e+00
-6.86939657e-01 -8.13237429e-01 -4.36081648e-01 -8.59221160e-01
7.83067346e-01 -1.13844085e+00 -9.02010381e-01 7.21498907e-01
-1.12545443e+00 -5.45523316e-02 -1.65953264e-01 2.94527680e-01
-3.68553281e-01 8.31102014e-01 -7.17596710e-01 -7.64004886e-01
-6.30082011e-01 -8.46708655e-01 1.26765025e+00 4.77370650e-01
-3.80712390e-01 -2.55505800e-01 -3.01349372e-01 4.72851336e-01
-8.58618692e-02 6.06404722e-01 3.91606420e-01 -4.41468328e-01
-7.95884132e-01 -3.53676558e-01 -2.56547689e-01 2.77809530e-01
-7.47079775e-02 3.33586305e-01 -8.08020353e-01 -4.16851729e-01
-4.83676046e-01 6.72836381e-04 9.98249114e-01 7.04198301e-01
1.55512011e+00 -5.55629849e-01 -1.76550284e-01 5.94530523e-01
1.02116120e+00 1.99479952e-01 5.86859941e-01 3.07715714e-01
9.32150543e-01 5.41260779e-01 6.82728171e-01 8.96230340e-01
3.14436316e-01 6.93632782e-01 3.18713069e-01 1.01612613e-01
-6.14587069e-02 -2.39734977e-01 7.17531323e-01 7.33836353e-01
-6.80746377e-01 -3.83725166e-01 -3.40939820e-01 5.28091431e-01
-2.02232051e+00 -1.66304266e+00 -9.03499499e-02 2.51220965e+00
5.73095500e-01 4.10698414e-01 6.56673133e-01 1.08294353e-01
1.05837238e+00 5.78110635e-01 -6.62755013e-01 4.12172638e-02
-3.02424461e-01 -1.07201621e-01 2.24814087e-01 -1.04312167e-01
-1.37699378e+00 5.92477620e-01 5.06852198e+00 7.35148847e-01
-1.02753246e+00 5.71895801e-02 7.05528796e-01 -9.28039968e-01
1.24739081e-01 -4.76722538e-01 -5.93764842e-01 9.26643789e-01
8.13795924e-01 -1.49701223e-01 3.59788954e-01 7.30459452e-01
6.99149728e-01 -2.49223724e-01 -1.03491712e+00 1.45999277e+00
5.87016523e-01 -1.52187216e+00 2.18445763e-01 -1.39616057e-01
8.73320818e-01 -3.53315592e-01 1.65538162e-01 1.99383095e-01
-4.48315352e-01 -5.71166337e-01 9.81950521e-01 8.53037655e-01
7.43467450e-01 -9.60568488e-01 4.73725021e-01 -1.30276203e-01
-1.30936623e+00 -3.74241412e-01 -1.10016234e-01 4.06254120e-02
3.12246263e-01 6.53807461e-01 -3.88278812e-01 3.63765031e-01
9.23070908e-01 1.14561582e+00 -4.54580396e-01 1.35451519e+00
-1.13472305e-01 6.01513743e-01 1.11902192e-01 7.07743913e-02
6.22592717e-02 -7.89861456e-02 9.75948036e-01 1.59951901e+00
4.36734974e-01 7.90663287e-02 3.03316325e-01 3.19430560e-01
-4.22634274e-01 1.89146653e-01 -3.51752460e-01 -4.04445864e-02
3.45225155e-01 1.46886992e+00 -8.26991260e-01 -6.85160756e-01
-2.32915312e-01 1.39807796e+00 -5.56804426e-02 2.23939881e-01
-1.09196889e+00 -5.30472636e-01 5.88684082e-01 2.93103576e-01
2.99041748e-01 -1.26055419e-01 1.76987723e-01 -1.22912216e+00
4.03148323e-01 -9.58015382e-01 4.00382459e-01 -9.17201161e-01
-1.00315583e+00 5.00865936e-01 -4.02830467e-02 -1.50786436e+00
-1.81408122e-01 -1.26898453e-01 -9.23814118e-01 3.63122016e-01
-1.12246251e+00 -8.81356776e-01 -8.41831744e-01 6.20572448e-01
1.02728534e+00 -2.20691457e-01 9.83427837e-02 5.76854944e-01
-6.80468500e-01 6.22623742e-01 1.17028870e-01 1.12025321e-01
8.70746553e-01 -1.09254038e+00 3.11932385e-01 1.05427051e+00
7.70176947e-02 5.47080934e-01 7.98035324e-01 -9.07815397e-01
-1.38759089e+00 -9.70052898e-01 7.57083774e-01 -1.73803270e-01
5.32610714e-01 -1.07042640e-01 -5.83832920e-01 2.82861620e-01
1.67111397e-01 -4.00480062e-01 6.45820022e-01 -1.93052813e-01
-2.28247359e-01 -2.56018788e-01 -7.20090091e-01 7.09733248e-01
1.19189990e+00 -6.12501800e-01 -3.64983439e-01 4.43788290e-01
6.25706971e-01 -4.56180125e-01 -5.21726072e-01 6.92085177e-02
9.43494797e-01 -1.17628956e+00 1.06658924e+00 -6.34763181e-01
1.03817892e+00 -2.45342195e-01 6.32717237e-02 -8.79164398e-01
-2.71857500e-01 -1.07945001e+00 -5.94938636e-01 1.25803280e+00
-2.11915851e-01 2.79929936e-01 7.73038983e-01 2.92740762e-01
-2.61360943e-01 -7.44554281e-01 -6.79698288e-01 -3.35502446e-01
-1.02557707e+00 -2.58149266e-01 1.05709061e-01 6.58227265e-01
-3.77904065e-02 1.71099305e-01 -1.04804993e+00 7.30622420e-03
7.61064470e-01 1.74405155e-04 8.71527374e-01 -1.16816187e+00
-2.74899393e-01 -4.06236202e-01 -6.14595175e-01 -1.07564282e+00
-7.76446983e-02 -5.80746591e-01 -6.24702349e-02 -1.49550998e+00
7.91643679e-01 4.94833946e-01 -5.29951572e-01 5.42985834e-02
-2.85434365e-01 3.21925759e-01 4.06771362e-01 3.78972888e-01
-1.20211840e+00 7.37382248e-02 9.01929200e-01 -2.16517553e-01
-4.60701615e-01 1.75924420e-01 -5.51494241e-01 7.38202810e-01
4.63975668e-01 -7.84596875e-02 -3.80165577e-01 -1.44515291e-01
3.61880064e-01 2.20932424e-01 5.38985670e-01 -1.21984529e+00
2.43789583e-01 1.13320254e-01 6.10239625e-01 -9.11660194e-01
5.65651953e-01 -2.71263540e-01 -3.57614271e-02 3.25240880e-01
-7.03586280e-01 2.05383047e-01 1.79458782e-02 8.22366118e-01
-1.30008221e-01 -2.95228194e-02 4.23496753e-01 -2.32981041e-01
-1.01896191e+00 3.86125565e-01 -3.61382931e-01 -7.75405169e-02
9.80548739e-01 -4.17186975e-01 -4.32217151e-01 -6.72779381e-01
-7.67468333e-01 3.56522165e-02 1.52391419e-01 5.79020023e-01
9.11481202e-01 -1.25144851e+00 -7.76739120e-01 -1.05376251e-01
9.87313222e-03 -2.44656384e-01 8.71338546e-01 8.16581011e-01
-4.74742919e-01 4.18637842e-02 -4.76548910e-01 -5.14267862e-01
-1.73898876e+00 3.29058528e-01 -1.41100362e-01 -1.71203330e-01
-9.00483012e-01 1.00163817e+00 1.40522718e-01 7.04007864e-01
5.38366735e-01 -3.07898283e-01 -5.68193674e-01 7.72844434e-01
1.01760888e+00 8.42467010e-01 -3.27277005e-01 -8.90622973e-01
-1.84515789e-01 4.82359380e-01 -2.57727861e-01 1.33645102e-01
1.18986070e+00 -1.60260722e-01 8.62630457e-02 4.56007868e-01
1.23532534e+00 1.37257367e-01 -1.42392349e+00 -1.61950409e-01
-3.09706241e-01 -5.99494219e-01 -1.46929324e-01 -3.19795281e-01
-1.05643344e+00 6.73786700e-01 5.50767183e-01 1.07864544e-01
1.21487534e+00 -2.67038673e-01 1.28845930e+00 2.65707910e-01
1.00349993e-01 -1.22720981e+00 5.32728434e-01 5.16549572e-02
8.10825348e-01 -1.25493383e+00 2.54920959e-01 -1.80444539e-01
-8.84571135e-01 1.17301154e+00 4.35769647e-01 -2.79040843e-01
8.84170681e-02 -3.46546710e-01 -4.11900520e-01 -2.62034744e-01
-6.64306998e-01 -6.45646602e-02 7.28127718e-01 2.69224346e-01
3.07005823e-01 9.40712169e-02 -2.40415081e-01 5.08857250e-01
-8.66038948e-02 -1.36987446e-02 7.16117442e-01 5.50870717e-01
-4.87170368e-01 -2.99270749e-01 -2.32892141e-01 7.62517869e-01
-8.11884165e-01 -2.11900920e-02 -2.89122254e-01 3.83846700e-01
1.09918013e-01 9.06389892e-01 2.24993065e-01 -6.20686412e-01
2.50074834e-01 -1.29672855e-01 2.80843914e-01 -4.26864892e-01
-6.91957235e-01 2.01560736e-01 1.08946085e-01 -8.03345621e-01
-5.63601911e-01 -9.25657511e-01 -9.98221099e-01 -2.99104124e-01
2.58185565e-01 -1.12052016e-01 4.63988751e-01 5.67222893e-01
4.08842981e-01 7.73242891e-01 7.33817577e-01 -1.36786580e+00
-8.77463371e-02 -7.35904396e-01 -5.55764854e-01 7.62554407e-01
4.57724273e-01 -5.07222772e-01 -3.12719345e-01 4.89048630e-01] | [10.220973014831543, 0.43379276990890503] |
af4189eb-ce93-4424-b38e-5f5e94c37a9f | efficient-3-d-near-field-mimo-sar-imaging-for | 2305.02064 | null | https://arxiv.org/abs/2305.02064v1 | https://arxiv.org/pdf/2305.02064v1.pdf | Efficient 3-D Near-Field MIMO-SAR Imaging for Irregular Scanning Geometries | In this article, we introduce a novel algorithm for efficient near-field synthetic aperture radar (SAR) imaging for irregular scanning geometries. With the emergence of fifth-generation (5G) millimeter-wave (mmWave) devices, near-field SAR imaging is no longer confined to laboratory environments. Recent advances in positioning technology have attracted significant interest for a diverse set of new applications in mmWave imaging. However, many use cases, such as automotive-mounted SAR imaging, unmanned aerial vehicle (UAV) imaging, and freehand imaging with smartphones, are constrained to irregular scanning geometries. Whereas traditional near-field SAR imaging systems and quick personnel security (QPS) scanners employ highly precise motion controllers to create ideal synthetic arrays, emerging applications, mentioned previously, inherently cannot achieve such ideal positioning. In addition, many Internet of Things (IoT) and 5G applications impose strict size and computational complexity limitations that must be considered for edge mmWave imaging technology. In this study, we propose a novel algorithm to leverage the advantages of non-cooperative SAR scanning patterns, small form-factor multiple-input multiple-output (MIMO) radars, and efficient monostatic planar image reconstruction algorithms. We propose a framework to mathematically decompose arbitrary and irregular sampling geometries and a joint solution to mitigate multistatic array imaging artifacts. The proposed algorithm is validated through simulations and an empirical study of arbitrary scanning scenarios. Our algorithm achieves high-resolution and high-efficiency near-field MIMO-SAR imaging, and is an elegant solution to computationally constrained irregularly sampled imaging problems. | ['Murat Torlak', 'Josiah Smith'] | 2023-05-03 | null | null | null | null | ['image-reconstruction'] | ['computer-vision'] | [ 7.14907825e-01 -2.70463526e-01 2.95636952e-01 -4.32276547e-01
-6.67031169e-01 -6.86369121e-01 1.89445809e-01 -8.73760462e-01
1.11483589e-01 6.66238964e-01 1.99598186e-02 -6.02530420e-01
-9.86484110e-01 -8.05645764e-01 -2.24725470e-01 -7.41169214e-01
-2.41092518e-02 2.82528788e-01 -2.30475307e-01 -8.66356492e-02
-1.26559913e-01 7.84670055e-01 -1.05569851e+00 -2.36895591e-01
1.08653557e+00 1.16933739e+00 5.49924672e-01 4.30905968e-01
6.55101240e-01 3.05857360e-01 -5.06296098e-01 1.20563433e-01
7.33723819e-01 -3.51735055e-01 1.04465798e-01 2.72891611e-01
5.81395268e-01 -4.08060402e-01 -3.78877878e-01 9.90232050e-01
7.10098088e-01 -2.53810614e-01 3.28052402e-01 -6.13692045e-01
-5.49736619e-01 1.17535621e-01 -8.17010283e-01 1.70211300e-01
1.74842268e-01 2.45755821e-01 3.21467906e-01 -8.39835227e-01
3.05994153e-01 4.18807596e-01 6.51660681e-01 -1.23332655e-02
-6.85843229e-01 -6.78518593e-01 -5.43068588e-01 -1.36677250e-01
-1.36058736e+00 -5.59011579e-01 7.78215289e-01 -2.61606306e-01
3.14484656e-01 5.77913105e-01 5.93557835e-01 7.05782056e-01
4.18508649e-01 5.91206886e-02 1.24365520e+00 -3.65210325e-01
2.84118980e-01 -3.61558139e-01 -2.89216768e-02 5.30796945e-01
1.02859294e+00 2.50734597e-01 -2.19057515e-01 -3.18115443e-01
1.08823764e+00 2.89463341e-01 -8.35625112e-01 -4.62410301e-01
-1.48643470e+00 5.54322660e-01 4.13172811e-01 6.64726138e-01
-8.04164350e-01 -2.98311729e-02 -8.76260459e-01 2.54520208e-01
1.56398699e-01 1.03813624e+00 -1.79073304e-01 4.21672553e-01
-1.26963043e+00 -1.38786405e-01 4.50361609e-01 7.86941469e-01
6.65722489e-01 6.54840529e-01 -1.51585171e-03 4.59562182e-01
3.48137140e-01 1.39040792e+00 1.08572513e-01 -7.47292221e-01
3.80047321e-01 5.96942119e-02 3.44641834e-01 -9.60349619e-01
-5.12255847e-01 -1.65682268e+00 -1.37741494e+00 -1.73746005e-01
6.43568039e-02 -5.63103080e-01 -8.92497480e-01 1.25850868e+00
1.56341657e-01 3.98882091e-01 3.05530280e-01 1.18199420e+00
4.98313904e-01 5.71866870e-01 -5.20441532e-01 -6.90867543e-01
1.35835660e+00 -3.14051837e-01 -6.74682140e-01 -9.40242887e-01
1.60170257e-01 -8.87099564e-01 4.09277648e-01 3.53794426e-01
-9.56183970e-01 -2.86496073e-01 -1.36690032e+00 8.15748870e-01
5.61621249e-01 3.01901639e-01 6.59447849e-01 9.66471970e-01
-8.42716277e-01 -9.63546112e-02 -5.33110321e-01 -3.67278829e-02
4.03495312e-01 -3.22561967e-03 1.77253753e-01 -5.40560901e-01
-7.92646289e-01 4.58914846e-01 -6.66933000e-01 1.28837615e-01
-1.07610293e-01 -1.12219584e+00 -4.94038582e-01 -2.12117191e-02
2.13074222e-01 -1.15362573e+00 7.40824938e-01 -4.47223991e-01
-1.32912993e+00 4.69345689e-01 -7.75818527e-02 -6.14569604e-01
-1.95400760e-01 -1.47052139e-01 -8.59141469e-01 4.99094635e-01
1.65036216e-01 -3.91831473e-02 1.01747215e+00 -1.12381387e+00
-1.38601944e-01 -7.56180048e-01 -3.09062064e-01 1.28834814e-01
1.48602709e-01 -3.12873214e-01 3.93598855e-01 -6.72353923e-01
1.03241849e+00 -8.92506301e-01 -7.02694535e-01 -4.30280745e-01
-8.31089541e-02 9.28074956e-01 1.03398263e+00 -2.66615510e-01
9.66616511e-01 -2.02898479e+00 -2.38847792e-01 2.78998643e-01
1.08279042e-01 1.97651997e-01 -4.82670628e-02 1.68670997e-01
5.71974665e-02 -4.14365053e-01 -3.59150380e-01 4.42558348e-01
-5.02486765e-01 -3.11227977e-01 -5.42532682e-01 6.71033323e-01
-4.30607259e-01 1.03901958e+00 -3.69681448e-01 2.22754166e-01
1.37535021e-01 2.39038169e-01 -3.45537812e-01 -8.22856575e-02
1.34233579e-01 9.41015542e-01 -9.13312495e-01 1.10186708e+00
1.16445935e+00 -5.97046018e-01 9.67217833e-02 -6.30624294e-01
-4.01772678e-01 -6.22116208e-01 -1.07309079e+00 1.35126257e+00
-7.85818517e-01 3.96534503e-01 5.79437017e-01 -1.02886593e+00
1.04541552e+00 1.54118881e-01 6.90932274e-01 -1.02564204e+00
-2.49074008e-02 3.60035092e-01 -7.53889605e-02 -3.89710218e-01
1.93645045e-01 -2.91999906e-01 -1.83703154e-01 5.38953900e-01
-4.83074009e-01 -5.64832330e-01 -4.17183757e-01 -1.60153523e-01
1.36940885e+00 -4.29526746e-01 6.22321188e-01 -3.90275300e-01
4.47795421e-01 2.68949479e-01 4.67648298e-01 7.01491416e-01
2.28669599e-01 5.53440869e-01 -7.65830457e-01 -4.52549100e-01
-4.85737294e-01 -1.25201893e+00 -9.86389592e-02 4.36642691e-02
5.24741054e-01 1.92418367e-01 -3.61081958e-01 2.91403458e-02
-3.61162305e-01 6.49596035e-01 3.88121247e-01 3.01188916e-01
-8.63833368e-01 -1.07565427e+00 1.16250642e-01 -1.07695535e-01
9.98194575e-01 -1.71691656e-01 -1.34603572e+00 1.26001373e-01
-2.64995903e-01 -1.54692888e+00 -1.06096424e-01 -2.42020845e-01
-9.88336086e-01 -1.02073467e+00 -6.58914626e-01 -6.65817440e-01
6.08089209e-01 1.24248827e+00 9.34203804e-01 -4.20752853e-01
-5.43971479e-01 7.39378452e-01 -2.60254204e-01 -2.46641606e-01
2.34294355e-01 -4.84500468e-01 2.32744113e-01 3.81853074e-01
-1.96072698e-01 -1.02623689e+00 -1.03915620e+00 7.12914646e-01
-6.62076116e-01 1.04320813e-02 1.35447407e+00 7.24086404e-01
6.12205744e-01 1.03220508e-01 6.80185080e-01 -4.91110623e-01
1.82698771e-01 -2.50807792e-01 -9.71693099e-01 2.38926947e-01
-3.17411959e-01 -2.96347916e-01 7.20266819e-01 -1.60368919e-01
-1.19066203e+00 9.26617384e-02 1.57386318e-01 -2.88937330e-01
-8.04801658e-02 6.53444111e-01 -3.45512718e-01 -8.06137621e-01
8.34779859e-01 4.99196619e-01 -1.86200157e-01 -6.42421246e-02
-2.13754829e-03 6.75021052e-01 6.30127430e-01 9.84211341e-02
1.57044566e+00 7.45746672e-01 5.95476508e-01 -1.58530402e+00
-8.85837615e-01 -3.41675401e-01 2.59849825e-03 -9.30592790e-02
7.15090632e-01 -1.18375504e+00 -2.89710909e-01 8.40894505e-02
-7.52461135e-01 -1.31700948e-01 -9.33271497e-02 1.07406187e+00
-3.00077826e-01 4.59332019e-01 1.70496702e-01 -8.03190529e-01
-4.91066217e-01 -8.72536838e-01 1.01750481e+00 2.17529878e-01
-1.04724176e-01 -3.87960106e-01 -1.56627983e-01 8.34578812e-01
1.03012896e+00 2.54613221e-01 5.77750683e-01 3.38387936e-01
-1.44468927e+00 -1.18403636e-01 -7.33435079e-02 -3.84541869e-01
1.26201212e-01 -1.17455745e+00 -5.13913095e-01 -4.50168014e-01
7.20337629e-01 2.57873118e-01 3.80541027e-01 1.20215189e+00
7.22067595e-01 -2.65871584e-01 -6.66271925e-01 1.27663600e+00
1.71602809e+00 4.48147923e-01 7.73302138e-01 -1.37049779e-01
1.80360928e-01 1.59251317e-01 9.27103996e-01 4.87690419e-01
-2.00691819e-01 7.28256643e-01 4.60860610e-01 -2.90445127e-02
-1.12441741e-02 2.74946690e-01 -1.20678276e-01 4.51121420e-01
-3.00422013e-02 -4.99591112e-01 -5.46532571e-01 3.00793141e-01
-1.20245051e+00 -1.14949012e+00 -3.56170326e-01 2.15285683e+00
-1.04405031e-01 -6.15260899e-01 -8.69806945e-01 -1.91787124e-01
4.07623589e-01 3.95621002e-01 -4.73070085e-01 5.03400445e-01
-4.14811045e-01 6.09500766e-01 9.24046040e-01 4.37133491e-01
-8.81890535e-01 2.89115191e-01 5.18345594e+00 5.09855449e-01
-1.22010982e+00 3.55778396e-01 3.54513437e-01 1.13346152e-01
-6.19528890e-01 1.06603270e-02 -4.61748689e-01 1.88244693e-02
4.71131206e-01 1.63950603e-02 2.08682016e-01 4.38161582e-01
2.45691732e-01 -2.57653683e-01 -3.63855153e-01 1.61691082e+00
3.36544518e-03 -1.58852017e+00 -1.17601626e-01 1.81903884e-01
9.11598742e-01 -1.16919465e-01 3.67365986e-01 -3.13468486e-01
-1.48416996e-01 -8.65275562e-01 1.02611519e-01 4.68490303e-01
9.95595098e-01 -5.26653230e-01 4.08758998e-01 5.66321433e-01
-1.04791844e+00 -2.77714819e-01 -1.80935651e-01 -1.73478320e-01
5.64184129e-01 1.49701989e+00 -6.09594643e-01 1.03943694e+00
3.88637751e-01 1.61124304e-01 6.94328994e-02 8.63717258e-01
-1.87300015e-02 5.19176245e-01 -2.49955684e-01 1.11388080e-01
1.98757350e-01 -5.48051298e-01 1.02101839e+00 3.85261834e-01
1.36203229e+00 9.84637976e-01 1.09118246e-01 6.28679514e-01
4.60717559e-01 -3.85921806e-01 -9.46199059e-01 2.63504237e-01
5.82523584e-01 1.38935506e+00 -5.09068310e-01 1.78977206e-01
-4.18411940e-01 4.86331522e-01 -9.09138680e-01 6.14047587e-01
-7.47351885e-01 -2.75264174e-01 8.21751297e-01 6.52946353e-01
3.30384016e-01 -9.03377831e-01 -5.60853601e-01 -1.10108185e+00
1.30371284e-02 -7.84640968e-01 -2.72424836e-02 -9.16179121e-01
-8.23642790e-01 7.16059387e-01 -1.09784134e-01 -1.81613958e+00
-2.25347623e-01 -5.61442738e-03 -4.83840346e-01 6.84608102e-01
-1.61664033e+00 -1.14412832e+00 -6.76282346e-01 4.49335515e-01
3.80037725e-01 -5.24079263e-01 6.96672678e-01 1.60033733e-01
2.28032008e-01 2.37959344e-02 8.01219940e-02 -3.05570632e-01
4.03242230e-01 -1.99751228e-01 6.55874982e-02 1.37395287e+00
-2.61388924e-02 5.40305078e-01 8.20290923e-01 -8.30032527e-01
-2.20676756e+00 -1.40519309e+00 2.75977373e-01 1.54772177e-01
2.60646224e-01 -3.19017246e-02 -4.21500616e-02 7.10831165e-01
1.84670761e-01 2.23811060e-01 6.17790759e-01 -5.53441644e-01
1.46312907e-01 -4.20529604e-01 -1.28537703e+00 4.70794588e-01
1.44857955e+00 2.15344936e-01 -2.77304918e-01 5.59107423e-01
3.11952978e-01 -3.70594323e-01 -4.15334433e-01 1.07166326e+00
3.91472161e-01 -8.99348557e-01 1.46762741e+00 3.72662336e-01
-3.83190550e-02 -5.52488685e-01 -7.14375317e-01 -1.44455707e+00
-6.61527812e-01 -1.06153607e+00 6.63395375e-02 2.47824356e-01
1.03468709e-01 -1.13005435e+00 1.00688148e+00 -3.83347034e-01
-4.38108116e-01 -4.44861531e-01 -9.20344651e-01 -9.52407360e-01
-6.89847946e-01 -2.57992685e-01 4.84320760e-01 8.61883938e-01
-5.25433183e-01 4.45330918e-01 -5.15737355e-01 1.33754992e+00
1.45411706e+00 9.62572038e-01 6.87452853e-01 -1.42415416e+00
-7.12918818e-01 1.64510444e-01 -3.10347825e-01 -1.45677590e+00
-4.02790070e-01 -6.03188455e-01 -1.96571454e-01 -1.60161686e+00
-3.58178079e-01 -6.15963042e-01 6.01579428e-01 -2.81528264e-01
5.59476078e-01 8.12586308e-01 -2.01548025e-01 2.07366705e-01
-1.40797228e-01 3.16730559e-01 1.32611084e+00 -1.62599891e-01
-1.08378537e-01 6.06204391e-01 -6.51979089e-01 6.19315922e-01
7.25060165e-01 -5.05626574e-02 -6.53733075e-01 -8.35311413e-01
3.52385014e-01 8.32238853e-01 6.01895452e-01 -1.64422452e+00
7.31906831e-01 -3.10271025e-01 5.76067090e-01 -6.37697160e-01
6.11293793e-01 -1.06412828e+00 8.59108090e-01 6.82033658e-01
7.85256326e-01 -3.01637441e-01 -2.40158975e-01 5.07888913e-01
-2.08475053e-01 9.34885964e-02 1.00812316e+00 -1.56826153e-01
-4.78138238e-01 4.27181065e-01 -4.47805077e-01 -1.60498798e-01
1.28740156e+00 -5.59006631e-01 -4.77468312e-01 -7.88514078e-01
-4.05909389e-01 -1.00499131e-01 1.49690852e-01 -2.64790833e-01
9.17879641e-01 -1.00001347e+00 -8.03190351e-01 6.69328749e-01
-1.82048753e-01 -3.53424579e-01 9.03959930e-01 1.02023304e+00
-4.82986927e-01 7.79125214e-01 -1.47047535e-01 -6.92757487e-01
-1.20439005e+00 -7.38406107e-02 2.58196980e-01 -2.16242790e-01
-4.13912863e-01 4.23390567e-01 4.52535063e-01 -2.87394404e-01
-7.18264163e-01 -5.35265431e-02 1.46126807e-01 -3.80636007e-01
6.02576196e-01 1.19080000e-01 1.52525127e-01 -2.83948421e-01
-3.98324996e-01 1.24455583e+00 5.73797822e-01 -1.45872205e-01
1.52781546e+00 -3.16420525e-01 1.16402149e-01 -5.63391268e-01
4.85132247e-01 7.67769396e-01 -7.14146137e-01 -1.51658654e-01
-4.74596590e-01 -6.72930241e-01 3.22859555e-01 -7.22682118e-01
-9.81365919e-01 4.20370072e-01 4.83513266e-01 8.01046416e-02
1.48378682e+00 8.41589365e-03 8.94390106e-01 7.33437061e-01
1.20594549e+00 -2.56518900e-01 2.37300284e-02 4.05977935e-01
6.54360831e-01 -6.73251331e-01 5.04276752e-01 -8.02407205e-01
-1.32428631e-01 9.44933474e-01 1.45662159e-01 -3.93697359e-02
6.59131646e-01 5.77220082e-01 1.27317071e-01 -5.56780636e-01
-2.02877015e-01 2.29248628e-02 3.44859585e-02 8.11211824e-01
-4.97504398e-02 9.03370157e-02 -2.25102469e-01 6.94778740e-01
-2.44545132e-01 -1.37356654e-01 7.01811314e-01 8.39578927e-01
-8.00696135e-01 -6.41512573e-01 -8.21999907e-01 5.68800926e-01
-2.70398140e-01 4.21439111e-02 3.13701868e-01 6.55353665e-01
-1.96095705e-01 1.12510884e+00 -2.08612327e-02 -1.27621815e-01
3.20687890e-01 -4.26009148e-01 6.98454142e-01 -4.09478247e-01
-1.59105449e-03 3.97457369e-02 -9.95942671e-03 -5.13723969e-01
-3.50294650e-01 -4.38832283e-01 -6.65882945e-01 2.84411758e-01
-1.63259014e-01 3.14383537e-01 7.29130387e-01 7.56591856e-01
8.07571709e-01 3.77019495e-01 9.56976235e-01 -5.83343685e-01
-5.46233237e-01 -6.24492645e-01 -7.66089737e-01 -5.84875286e-01
1.14293046e-01 -4.76565182e-01 -3.57471883e-01 -3.51620972e-01] | [6.707255840301514, 0.9779950976371765] |
1e9fdf77-f0b9-45c2-9ded-81f500134908 | hypernym-discovery-via-a-recurrent-mapping | null | null | https://aclanthology.org/2021.findings-acl.257 | https://aclanthology.org/2021.findings-acl.257.pdf | Hypernym Discovery via a Recurrent Mapping Model | null | ['Yongyi Mao', 'Junfan Chen', 'Fanshuang Kong', 'Richong Zhang', 'Yuhang Bai'] | null | null | null | null | findings-acl-2021-8 | ['hypernym-discovery'] | ['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] | [-7.343100547790527, 3.7300987243652344] |
7de07004-b4e8-417d-81c3-902fee2060de | learning-semantics-aware-distance-map-with | 1905.12898 | null | https://arxiv.org/abs/1905.12898v2 | https://arxiv.org/pdf/1905.12898v2.pdf | Learning Semantics-aware Distance Map with Semantics Layering Network for Amodal Instance Segmentation | In this work, we demonstrate yet another approach to tackle the amodal segmentation problem. Specifically, we first introduce a new representation, namely a semantics-aware distance map (sem-dist map), to serve as our target for amodal segmentation instead of the commonly used masks and heatmaps. The sem-dist map is a kind of level-set representation, of which the different regions of an object are placed into different levels on the map according to their visibility. It is a natural extension of masks and heatmaps, where modal, amodal segmentation, as well as depth order information, are all well-described. Then we also introduce a novel convolutional neural network (CNN) architecture, which we refer to as semantic layering network, to estimate sem-dist maps layer by layer, from the global-level to the instance-level, for all objects in an image. Extensive experiments on the COCOA and D2SA datasets have demonstrated that our framework can predict amodal segmentation, occlusion and depth order with state-of-the-art performance. | ['Ziheng Zhang', 'Ling Xie', 'Shenghua Gao', 'Anpei Chen', 'Jingyi Yu'] | 2019-05-30 | null | null | null | null | ['amodal-instance-segmentation'] | ['computer-vision'] | [-3.62439901e-02 3.32650810e-01 -1.05264060e-01 -6.39182448e-01
-5.22680104e-01 -6.67714596e-01 5.27264953e-01 3.81391525e-01
-1.47869498e-01 2.20602557e-01 -7.53879696e-02 -2.01577768e-02
1.29365742e-01 -1.03280532e+00 -7.83458233e-01 -6.04626536e-01
3.61035764e-02 5.74052751e-01 5.67712724e-01 -9.73182023e-02
3.44535381e-01 4.80939984e-01 -1.68333721e+00 5.22545576e-01
1.22808039e+00 1.40494120e+00 2.91532278e-01 3.16669345e-01
-5.76699972e-01 4.27669227e-01 -5.65486670e-01 -3.31002653e-01
4.54032645e-02 -2.70281792e-01 -1.06597757e+00 2.57511705e-01
5.15078366e-01 -7.10050464e-02 -7.60869607e-02 1.25745487e+00
1.99284911e-01 -2.68694423e-02 9.48346794e-01 -1.14936185e+00
-7.29388654e-01 5.77888310e-01 -6.15112424e-01 -1.33671775e-01
3.30530614e-01 -7.90531095e-03 9.67030466e-01 -8.65435064e-01
6.27465308e-01 1.55091524e+00 2.93493479e-01 2.22100258e-01
-1.20321739e+00 -7.39461854e-02 5.49731791e-01 3.00887734e-01
-1.23513925e+00 2.72026598e-01 8.81206334e-01 -6.24453068e-01
3.61367047e-01 3.32667619e-01 7.14398503e-01 5.64891994e-01
-1.33633595e-02 1.34942770e+00 1.28420472e+00 -2.80202597e-01
4.37176645e-01 9.43976715e-02 4.05624241e-01 6.19420767e-01
4.69146408e-02 -3.87291878e-01 -3.07331830e-01 3.45857084e-01
7.61655271e-01 -1.45396367e-01 -1.88174024e-01 -7.37171113e-01
-1.19202054e+00 7.30795383e-01 1.08819866e+00 2.85390168e-01
-3.39922518e-01 -4.49931398e-02 2.76431590e-01 -1.67037938e-02
5.95589519e-01 4.01791900e-01 -3.67056757e-01 3.42339218e-01
-8.39233160e-01 2.41913721e-01 8.24741364e-01 8.81468713e-01
1.23827732e+00 -4.71770674e-01 -4.80433106e-01 9.61836457e-01
3.96130800e-01 1.53961077e-01 2.33488545e-01 -8.87065411e-01
3.55533570e-01 1.06933153e+00 -5.62178642e-02 -1.09919143e+00
-5.64488888e-01 -2.37340763e-01 -7.28918374e-01 1.94038212e-01
5.89236617e-01 2.34540343e-01 -1.39060104e+00 1.71715605e+00
4.63142574e-01 -4.21756966e-04 -1.85123667e-01 1.14946222e+00
1.07901061e+00 7.24244058e-01 -4.16436186e-03 3.09584796e-01
1.68070376e+00 -1.26123977e+00 -6.08549595e-01 -4.92899418e-01
4.52850312e-01 -4.75822628e-01 1.28057051e+00 3.88229102e-01
-1.26565659e+00 -6.98258519e-01 -1.02652526e+00 -3.35548371e-01
-1.04376733e+00 1.02834567e-01 5.25022209e-01 3.82920712e-01
-1.25396097e+00 4.47792828e-01 -7.32424676e-01 -3.60114336e-01
5.50699830e-01 -7.35125244e-02 -1.67360067e-01 -2.53826547e-02
-1.18366206e+00 9.18492377e-01 6.26438200e-01 2.46254057e-01
-9.05625105e-01 -4.90618020e-01 -1.18006408e+00 2.41709068e-01
3.23920876e-01 -5.16494691e-01 8.31007302e-01 -9.51493740e-01
-1.28932214e+00 1.36755061e+00 -8.24554339e-02 -2.62672096e-01
2.51403093e-01 -9.07954201e-02 -1.15429863e-01 3.59272063e-01
1.49577245e-01 1.24618304e+00 7.91208267e-01 -1.75251818e+00
-6.42411351e-01 -5.71423948e-01 3.37269157e-01 2.60329068e-01
-1.88598245e-01 -3.08962762e-01 -8.14806402e-01 -6.16018534e-01
4.78882551e-01 -6.85331821e-01 -2.11935684e-01 1.59090757e-01
-8.97896528e-01 -5.39314389e-01 6.65756464e-01 -7.11226344e-01
1.29625261e+00 -2.09677553e+00 6.28843009e-01 3.65436465e-01
2.86963135e-01 5.86101152e-02 -9.91667435e-02 1.30694032e-01
-1.73355322e-02 3.78001630e-02 -8.69066358e-01 -2.78810531e-01
2.92795718e-01 1.50714010e-01 1.35699669e-02 2.47632504e-01
4.28387135e-01 9.60360289e-01 -7.63615072e-01 -5.90941966e-01
4.04195219e-01 3.97456229e-01 -3.19164217e-01 3.54935616e-01
-6.52792871e-01 4.69429016e-01 -2.66183287e-01 8.77934873e-01
1.16636431e+00 -2.60510504e-01 -1.52071670e-01 -3.61450464e-01
-1.92271173e-01 7.26427138e-03 -1.09889674e+00 2.21844888e+00
-3.55621547e-01 3.29242647e-01 8.67049396e-02 -1.10262501e+00
1.03806889e+00 -1.69607386e-01 2.87015796e-01 -8.15228283e-01
2.14920923e-01 3.62136334e-01 -2.09406942e-01 -3.30396652e-01
5.18566370e-01 3.69273603e-01 -4.95615572e-01 1.47839904e-01
1.01453498e-01 -1.93703324e-01 4.69839901e-01 8.48429799e-02
3.45400125e-01 1.96055084e-01 -5.03293313e-02 -5.50900638e-01
8.26431513e-01 1.34580836e-01 2.54260570e-01 5.90761781e-01
-9.43809077e-02 1.02161074e+00 9.38591897e-01 -4.11484122e-01
-6.97097003e-01 -1.25779164e+00 -4.80224401e-01 1.04845119e+00
8.48142326e-01 -1.00935481e-01 -1.28536415e+00 -7.06613064e-01
1.55647442e-01 4.85720515e-01 -8.21837068e-01 4.14867466e-03
-5.03843486e-01 -5.83648384e-01 8.31942931e-02 6.66958272e-01
6.75269783e-01 -1.17366278e+00 -4.70277220e-01 -7.58172050e-02
-2.36984119e-01 -1.03842771e+00 -4.88535821e-01 2.31503010e-01
-6.58065319e-01 -9.10606682e-01 -1.12644446e+00 -1.10654080e+00
7.71224916e-01 -1.35025252e-02 1.41127765e+00 -2.47544885e-01
-1.80164441e-01 6.66923821e-02 -4.12514955e-01 -1.60684675e-01
-6.97822869e-02 2.34052375e-01 -7.07982361e-01 3.17388862e-01
2.69143790e-01 -3.40135545e-01 -9.91442025e-01 3.68056625e-01
-1.06771016e+00 2.01324150e-01 5.81063569e-01 4.41438466e-01
1.06422627e+00 -3.62180591e-01 3.20151180e-01 -9.07902241e-01
4.04663801e-01 -5.28817058e-01 -5.43123364e-01 3.95449668e-01
-2.90526360e-01 2.10061148e-02 3.24717790e-01 -1.47654787e-01
-8.42647910e-01 7.85487667e-02 -2.45151266e-01 -2.41188407e-01
-4.85169798e-01 6.30764961e-01 -5.31135798e-01 2.01961234e-01
3.77929479e-01 1.06775008e-01 -4.21464927e-02 -6.90923154e-01
8.16672206e-01 7.25030839e-01 7.79581368e-01 -6.46841288e-01
4.63662565e-01 6.80103481e-01 -9.34924483e-02 -5.07916927e-01
-9.93035436e-01 -4.98887092e-01 -1.07069027e+00 -1.25737920e-01
1.48067033e+00 -8.23149920e-01 -5.01506388e-01 7.31150806e-01
-1.23673403e+00 -4.24063474e-01 -2.67013878e-01 1.64985377e-02
-6.02987468e-01 8.55273902e-02 -5.69570780e-01 -4.47521955e-01
-1.41516298e-01 -1.31798148e+00 1.55080128e+00 5.88741183e-01
9.03436244e-02 -1.15879107e+00 -1.55886456e-01 2.94050336e-01
7.87955970e-02 5.13827682e-01 1.26148713e+00 -6.99128032e-01
-7.57052064e-01 -9.91704315e-03 -6.92430139e-01 3.56925637e-01
-3.56589258e-02 -2.22116709e-01 -1.08762515e+00 -1.30943567e-01
-3.46246630e-01 -2.40640610e-01 1.12334359e+00 6.83420002e-01
1.67101145e+00 2.39733923e-02 -4.71995115e-01 7.71028578e-01
1.43642032e+00 2.11428836e-01 9.12378430e-01 2.97245473e-01
1.00912392e+00 8.85355592e-01 7.07933486e-01 1.50490791e-01
7.27818489e-01 7.55993664e-01 8.29625010e-01 -5.96997499e-01
-2.36887634e-01 -5.04163839e-02 -8.57326761e-02 6.69901669e-01
3.39005888e-01 -4.81493473e-01 -7.92647004e-01 6.15109861e-01
-1.85141706e+00 -3.63910168e-01 -3.56564641e-01 2.03600359e+00
6.83135748e-01 5.62594272e-02 4.97235835e-01 3.19794635e-03
9.27244246e-01 3.86900812e-01 -5.39258182e-01 -7.32428372e-01
-1.71040848e-01 5.28545454e-02 1.19629048e-01 5.33762157e-01
-1.32932067e+00 9.81421590e-01 5.84243631e+00 8.59254181e-01
-1.05255127e+00 -1.56930253e-01 9.66560483e-01 6.28930807e-01
-4.09435362e-01 -1.63848385e-01 -5.97563148e-01 7.08875954e-01
4.16602433e-01 3.56077611e-01 1.95955113e-01 9.51107621e-01
-3.00105512e-01 -3.12055290e-01 -1.30661666e+00 9.30208385e-01
1.47051498e-01 -1.10237134e+00 8.08556378e-02 -2.14612126e-01
7.30790496e-01 -3.25219721e-01 2.10609570e-01 2.08542645e-01
7.88448080e-02 -1.13269079e+00 9.26097274e-01 5.31048357e-01
6.93649232e-01 -7.92903662e-01 6.26697600e-01 2.15958849e-01
-1.47970259e+00 1.10572338e-01 -3.74297768e-01 3.99706066e-01
1.65664926e-01 5.74188471e-01 -2.86411136e-01 7.15420067e-01
7.86530256e-01 9.50868249e-01 -7.35794783e-01 1.06071031e+00
-3.56750220e-01 3.14540155e-02 -6.81100562e-02 1.33239239e-01
5.15001833e-01 -2.88310558e-01 2.12662131e-01 1.39582109e+00
2.22634956e-01 -3.21028531e-01 2.79602170e-01 1.33583808e+00
-1.80564076e-02 2.76866704e-02 -3.09587955e-01 2.10463181e-01
3.16773266e-01 1.47168744e+00 -1.06751680e+00 -4.04497623e-01
-2.97377169e-01 1.14585257e+00 2.36085325e-01 3.85708123e-01
-8.63788664e-01 -6.93371058e-01 5.52258551e-01 6.20963611e-02
3.14502150e-01 9.42622498e-03 -5.74482083e-01 -1.00440776e+00
3.96943614e-02 -4.43513572e-01 6.08448505e-01 -8.81019413e-01
-1.45437968e+00 6.79787338e-01 1.68492183e-01 -1.24963999e+00
1.46461114e-01 -9.17984366e-01 -7.28749573e-01 1.01170993e+00
-1.65886843e+00 -1.07632494e+00 -6.87103808e-01 4.09506381e-01
5.52500248e-01 2.68158793e-01 4.74077791e-01 1.98648170e-01
-6.13718748e-01 2.83498853e-01 -1.80919036e-01 1.17027342e-01
3.07453126e-01 -1.71176839e+00 2.84192652e-01 6.17507100e-01
3.16043831e-02 2.32655048e-01 3.54044259e-01 -4.40091282e-01
-9.50708330e-01 -1.01062775e+00 6.37961805e-01 -4.13228303e-01
4.37590420e-01 -5.77787161e-01 -1.10349786e+00 4.25264359e-01
2.17089713e-01 -4.12394144e-02 9.00801495e-02 -6.46235943e-02
-2.49366656e-01 -1.97953969e-01 -1.12999582e+00 4.52437311e-01
9.61037695e-01 -4.70734179e-01 -6.33826911e-01 3.12926054e-01
9.90144789e-01 -5.88963985e-01 -9.93126214e-01 4.22929972e-01
2.58569509e-01 -1.11208475e+00 1.20130098e+00 -1.50095031e-01
6.51535928e-01 -4.50574994e-01 -9.70938206e-02 -1.40234447e+00
-2.35473141e-01 -1.01678543e-01 -1.80807382e-01 1.26862514e+00
4.03663367e-01 -3.70667338e-01 6.72224641e-01 2.30628088e-01
-4.83054310e-01 -8.88796270e-01 -7.07551181e-01 -5.53918481e-01
2.42011026e-01 -3.10769945e-01 9.04155612e-01 8.62550676e-01
-1.63321361e-01 1.82931378e-01 1.76903754e-01 1.69458658e-01
4.50932562e-01 5.02642095e-01 4.02130932e-01 -1.33217895e+00
1.72836781e-01 -7.26388276e-01 -5.29862642e-01 -1.42137122e+00
-2.36398168e-02 -1.17348707e+00 3.03129077e-01 -2.12969542e+00
1.14694059e-01 -3.80561560e-01 -4.36551422e-01 2.51504779e-01
-2.63895988e-01 4.00090814e-01 1.19905390e-01 1.55550137e-01
-7.61491477e-01 4.75757539e-01 1.67602468e+00 -3.69873911e-01
-3.59252483e-01 -2.85233200e-01 -5.88157713e-01 7.41559446e-01
4.60871369e-01 -7.56697431e-02 -3.48447174e-01 -5.92278659e-01
3.74170928e-03 -6.16019517e-02 4.93222326e-01 -8.47818255e-01
8.14518929e-02 -2.49240231e-02 3.93776387e-01 -1.12604749e+00
3.00380021e-01 -7.91447163e-01 -2.35306844e-01 2.68098116e-01
-3.90912533e-01 -1.31041586e-01 6.33639842e-02 3.57099622e-01
-5.72678626e-01 -3.07385139e-02 8.37418914e-01 -1.78477645e-01
-9.79687691e-01 4.11595881e-01 4.47160527e-02 9.19623375e-02
1.13670278e+00 -3.12979013e-01 -5.40954828e-01 -4.98386249e-02
-1.02424955e+00 4.89126235e-01 5.29907346e-01 3.03271115e-01
5.46203315e-01 -1.47037745e+00 -4.13960606e-01 1.38878331e-01
4.23776150e-01 6.40804708e-01 3.20172578e-01 9.17439282e-01
-7.05612123e-01 3.82048726e-01 -3.84018600e-01 -1.12999380e+00
-6.03845298e-01 6.18757963e-01 3.30158651e-01 -1.48374140e-01
-5.56390405e-01 1.02434206e+00 7.41381824e-01 -4.86149579e-01
3.40475112e-01 -6.45483196e-01 -5.25940001e-01 3.51206124e-01
2.84602016e-01 1.24028675e-01 -6.42169937e-02 -6.97192371e-01
-4.38647091e-01 8.61903965e-01 1.34307593e-01 6.79698512e-02
9.43779469e-01 -1.95438549e-01 -4.65994775e-01 5.56629837e-01
1.18912888e+00 -5.59227705e-01 -1.49035895e+00 -1.68286756e-01
1.08522743e-01 -3.71233672e-01 -1.51799992e-01 -8.17547619e-01
-1.18757105e+00 1.26762092e+00 7.06523657e-01 7.35179842e-01
1.16349506e+00 4.66689914e-01 8.54038775e-01 -5.64764403e-02
6.61743805e-02 -1.27262306e+00 3.29716802e-01 3.67823362e-01
8.84337664e-01 -1.14681113e+00 -4.09981519e-01 -6.27660930e-01
-7.14631557e-01 9.83649194e-01 8.18332076e-01 -9.62158069e-02
6.00842893e-01 1.61978118e-02 7.18933418e-02 -3.29775482e-01
-1.74692124e-01 -6.31652176e-01 7.03699112e-01 6.89633071e-01
2.60681093e-01 1.71707779e-01 -1.37337923e-01 6.03962064e-01
-2.67707035e-02 -3.60530227e-01 8.80342573e-02 6.13942385e-01
-7.03522921e-01 -7.87820756e-01 -3.28925967e-01 2.50316352e-01
4.39705439e-02 1.44706205e-01 -5.21111429e-01 8.29446375e-01
3.77466559e-01 7.33817816e-01 6.17575347e-01 -4.12003964e-01
3.71674985e-01 3.01396828e-02 4.20435965e-01 -6.74362063e-01
-3.62310797e-01 -2.46167951e-03 -1.95066988e-01 -5.54329753e-01
-4.52731967e-01 -2.84857869e-01 -1.46613753e+00 -4.11174521e-02
-3.37994881e-02 -1.08139925e-01 7.97425568e-01 8.70592952e-01
1.54983804e-01 6.49491072e-01 7.07306981e-01 -1.07764268e+00
9.85389203e-02 -8.57631207e-01 -6.04500890e-01 7.41030693e-01
1.72708079e-01 -6.26288831e-01 -2.57776588e-01 1.56063046e-02] | [9.69814395904541, 0.47055062651634216] |
defec607-5152-4ce0-ab82-37e882d46a04 | m3pt-a-multi-modal-model-for-poi-tagging | 2306.10079 | null | https://arxiv.org/abs/2306.10079v1 | https://arxiv.org/pdf/2306.10079v1.pdf | M3PT: A Multi-Modal Model for POI Tagging | POI tagging aims to annotate a point of interest (POI) with some informative tags, which facilitates many services related to POIs, including search, recommendation, and so on. Most of the existing solutions neglect the significance of POI images and seldom fuse the textual and visual features of POIs, resulting in suboptimal tagging performance. In this paper, we propose a novel Multi-Modal Model for POI Tagging, namely M3PT, which achieves enhanced POI tagging through fusing the target POI's textual and visual features, and the precise matching between the multi-modal representations. Specifically, we first devise a domain-adaptive image encoder (DIE) to obtain the image embeddings aligned to their gold tags' semantics. Then, in M3PT's text-image fusion module (TIF), the textual and visual representations are fully fused into the POIs' content embeddings for the subsequent matching. In addition, we adopt a contrastive learning strategy to further bridge the gap between the representations of different modalities. To evaluate the tagging models' performance, we have constructed two high-quality POI tagging datasets from the real-world business scenario of Ali Fliggy. Upon the datasets, we conducted the extensive experiments to demonstrate our model's advantage over the baselines of uni-modality and multi-modality, and verify the effectiveness of important components in M3PT, including DIE, TIF and the contrastive learning strategy. | ['Shenghua Ni', 'Baohua Wu', 'Xiang Xu', 'Yanghua Xiao', 'Jingping Liu', 'Deqing Yang', 'Guanzhou Han', 'Jingsong Yang'] | 2023-06-16 | null | null | null | null | ['contrastive-learning', 'contrastive-learning'] | ['computer-vision', 'methodology'] | [ 5.14898673e-02 -2.25011364e-01 -4.43811417e-01 -8.07253085e-03
-8.14746737e-01 -3.30502391e-01 8.13520074e-01 8.40453207e-02
-4.43611056e-01 4.33459401e-01 6.45896912e-01 1.92126513e-01
-1.45806074e-01 -7.91748464e-01 -4.70899075e-01 -6.41735494e-01
1.79250538e-01 1.21875994e-01 6.21509731e-01 4.35684510e-02
4.67170067e-02 4.51482907e-02 -1.51877403e+00 1.09757692e-01
6.83111846e-01 1.22776675e+00 3.92653048e-01 1.86809495e-01
-4.35033739e-01 7.19544232e-01 -3.23593050e-01 -6.17842436e-01
9.57153663e-02 -2.05156237e-01 -6.67821944e-01 8.37194249e-02
1.19775936e-01 -7.11890683e-02 -6.46600068e-01 1.13007462e+00
4.18165416e-01 2.46175513e-01 7.69423902e-01 -1.66753018e+00
-8.59822631e-01 3.34009171e-01 -7.11814463e-01 1.07023954e-01
1.61429301e-01 -2.50184476e-01 1.16897595e+00 -8.05637479e-01
4.44797605e-01 1.18439829e+00 8.40267181e-01 1.96444646e-01
-5.29702425e-01 -7.66648710e-01 -1.42494977e-01 3.23223025e-01
-1.88552856e+00 -2.57601261e-01 6.24637425e-01 -2.22674116e-01
4.19508308e-01 1.30991012e-01 5.57146370e-01 6.13055825e-01
1.15841301e-03 9.66940820e-01 8.45763981e-01 -3.84091407e-01
-3.52899402e-01 3.82994235e-01 -2.46029720e-01 7.91218638e-01
2.89772712e-02 5.69233820e-02 -5.41915238e-01 -8.59346166e-02
6.87488139e-01 5.04853547e-01 -8.33771452e-02 -1.26505136e-01
-1.43142104e+00 5.73161185e-01 4.88720655e-01 7.14355290e-01
-4.39431101e-01 1.45769686e-01 3.49563688e-01 -3.46784294e-01
3.60803694e-01 1.21479474e-01 -1.44163534e-01 -1.67463347e-01
-7.38910973e-01 -1.56712100e-01 3.99861366e-01 1.12133133e+00
1.02382588e+00 -5.97896576e-01 -5.38132548e-01 1.11768150e+00
8.53335500e-01 5.88541806e-01 6.46266758e-01 -8.75955403e-01
4.84248281e-01 6.50820017e-01 2.20015138e-01 -1.30135369e+00
-7.45696500e-02 -7.73381963e-02 -6.62198365e-01 -5.27563035e-01
-7.24137351e-02 -5.56575656e-02 -7.79653490e-01 1.59350085e+00
3.48622769e-01 7.16378391e-01 1.47917509e-01 7.90228486e-01
1.21170616e+00 9.10764515e-01 7.07678318e-01 6.61004931e-02
1.82917666e+00 -1.06129718e+00 -8.02545309e-01 -2.51363963e-01
6.70685112e-01 -9.30278659e-01 1.02217591e+00 -3.70055884e-01
-7.78400719e-01 -7.45806694e-01 -1.07702136e+00 -1.52599722e-01
-5.33858716e-01 4.58470434e-01 5.63354135e-01 3.04052502e-01
-7.18607843e-01 3.19943100e-01 -3.81321311e-01 -6.97865844e-01
6.29117131e-01 2.02135563e-01 -5.57575226e-01 -1.32997841e-01
-1.51051891e+00 6.40338302e-01 8.06106031e-01 -1.27017498e-01
-5.49379170e-01 -5.54059029e-01 -9.01389897e-01 3.12351704e-01
1.95667744e-01 -4.81532395e-01 9.38735127e-01 -9.27978098e-01
-9.68911529e-01 1.00330603e+00 -2.31570601e-01 -2.90498827e-02
4.30145767e-04 1.32250071e-01 -9.11265612e-01 2.82787442e-01
5.00057757e-01 1.15768468e+00 6.35361493e-01 -1.29850090e+00
-1.36781454e+00 -4.86831227e-03 1.28996700e-01 4.77171242e-01
-5.76942027e-01 2.49876559e-01 -1.05877113e+00 -3.90007228e-01
-1.20351445e-02 -7.09340692e-01 7.65883178e-02 -7.56073892e-02
-4.77115922e-02 -4.32328612e-01 8.29057097e-01 -6.69767201e-01
1.39545476e+00 -2.86924124e+00 -2.83439070e-01 6.15331493e-02
2.27682158e-01 3.75315040e-01 -3.37823600e-01 3.07493925e-01
1.78953409e-01 1.98802739e-01 1.47193670e-01 -4.70944375e-01
3.77176434e-01 6.38890982e-01 8.27096403e-03 1.03786767e-01
3.66812162e-02 1.12322545e+00 -9.41495299e-01 -1.28750300e+00
2.61609495e-01 3.57322574e-01 -3.48992139e-01 1.92118555e-01
1.98841304e-01 1.55040398e-01 -4.92792547e-01 7.58122802e-01
6.36530995e-01 -4.01316106e-01 -6.41014613e-03 -5.36899686e-01
-5.58370054e-02 1.28990486e-01 -1.10084057e+00 1.61983919e+00
-5.24488807e-01 2.75874197e-01 -2.02715978e-01 -9.63815331e-01
8.96733046e-01 5.17655969e-01 9.30646539e-01 -8.08487833e-01
6.34238124e-02 1.67717829e-01 -4.61253405e-01 -4.40465510e-01
5.88473141e-01 -2.60230362e-01 -4.41355526e-01 1.62324488e-01
2.61725932e-01 3.76172513e-01 1.19074523e-01 1.97939605e-01
9.32261884e-01 1.69025287e-01 3.54322731e-01 8.47683772e-02
7.90409267e-01 -1.22446353e-02 7.00612247e-01 5.25614679e-01
-4.74584788e-01 4.57330197e-01 2.06043303e-01 -7.14541525e-02
-8.27035785e-01 -9.70337093e-01 -5.85184470e-02 1.10474277e+00
7.45042503e-01 -5.33509195e-01 -3.58858734e-01 -1.10454261e+00
-1.16900600e-01 3.46410096e-01 -4.69387710e-01 -2.77299047e-01
-1.71969011e-01 -5.81561387e-01 5.00485718e-01 5.40511787e-01
1.06598580e+00 -1.13597751e+00 6.23319335e-02 6.80651888e-02
-5.82282603e-01 -1.12873960e+00 -8.34607720e-01 -2.13821486e-01
-3.00050259e-01 -8.56804609e-01 -5.24499714e-01 -1.19560182e+00
5.31366169e-01 8.54220212e-01 7.80336082e-01 2.02773064e-01
2.19884306e-01 5.17207682e-01 -6.51537895e-01 -2.18893230e-01
1.46531127e-02 8.10190737e-02 -3.08234334e-01 1.15527034e-01
7.37741172e-01 -5.10839701e-01 -5.23200274e-01 6.67899430e-01
-9.90910709e-01 7.73903355e-02 7.41200984e-01 7.37030864e-01
7.84680724e-01 4.58595186e-01 3.06786239e-01 -6.47413909e-01
2.91603297e-01 -7.91920424e-01 -3.42515744e-02 4.02611554e-01
-3.25876862e-01 -2.24869877e-01 1.56308696e-01 -5.19373834e-01
-1.32440376e+00 -3.28583643e-02 -2.49548212e-01 -4.22440767e-01
-1.08988352e-01 7.71872699e-01 -6.44332826e-01 -1.66182950e-01
1.15854867e-01 1.61098987e-01 -3.28768760e-01 -4.03784752e-01
3.18286628e-01 1.18802822e+00 6.41999960e-01 -3.51740032e-01
9.11728084e-01 4.75655019e-01 -1.44732952e-01 -4.43567991e-01
-1.22206831e+00 -8.82380486e-01 -5.41403472e-01 -1.29281998e-01
1.00764728e+00 -1.17250741e+00 -5.95147371e-01 2.23308235e-01
-8.70908678e-01 1.29885420e-01 -3.01131368e-01 7.16158450e-01
-4.85970020e-01 7.08087325e-01 -2.87968069e-01 -4.55014557e-01
-1.38663247e-01 -8.38567138e-01 1.31466484e+00 6.97352052e-01
3.68953310e-02 -1.10554147e+00 1.01937922e-02 5.98801196e-01
3.55960242e-02 -4.08255398e-01 6.49272740e-01 -7.19056845e-01
-3.48025411e-01 -3.16367835e-01 -9.83141720e-01 2.23997369e-01
1.82838202e-01 -3.80088300e-01 -9.39966977e-01 1.31926388e-01
-4.83737439e-01 -9.69823159e-04 6.30697072e-01 5.68300262e-02
9.49090362e-01 -2.12390721e-01 -6.88074172e-01 5.83863258e-01
1.50636101e+00 3.06985766e-01 9.28101301e-01 3.89402807e-01
9.23999488e-01 2.49226853e-01 1.20282102e+00 4.37191278e-01
8.57901931e-01 7.62604177e-01 2.49200568e-01 -1.00871071e-01
-3.55925530e-01 -9.59797204e-01 2.66331464e-01 8.46606672e-01
-6.66567460e-02 -3.10998052e-01 -5.77057958e-01 9.64600444e-01
-2.06066203e+00 -1.06356466e+00 1.76505044e-01 1.99023974e+00
4.61375058e-01 -1.60949200e-01 -3.11237387e-02 -6.63437173e-02
7.87392616e-01 2.80526638e-01 5.97402714e-02 2.64585793e-01
6.14955835e-03 -7.46032596e-02 8.37686479e-01 1.52443811e-01
-1.54821718e+00 1.03502285e+00 5.65633965e+00 1.45512962e+00
-7.82947361e-01 7.56144941e-01 8.14548209e-02 4.45251971e-01
-4.35580641e-01 2.08313838e-01 -9.77396250e-01 8.10910821e-01
7.91311860e-01 -1.43272743e-01 3.34687710e-01 6.98250353e-01
3.61526327e-04 4.54998016e-02 -4.83482778e-01 1.12750673e+00
2.37549573e-01 -1.27724326e+00 -2.02738419e-01 3.09992313e-01
5.89398861e-01 2.55234865e-03 -1.92820057e-01 6.91630363e-01
2.43208498e-01 -7.02711940e-01 7.06094384e-01 5.68409383e-01
8.26441526e-01 -5.86244762e-01 1.07601571e+00 1.83347136e-01
-1.73289800e+00 -2.32777461e-01 -3.73077303e-01 2.74617612e-01
1.86356217e-01 2.82233916e-02 -5.77317238e-01 8.38936090e-01
7.39210188e-01 1.21258891e+00 -5.57834029e-01 1.07470155e+00
-2.24996701e-01 4.98306274e-01 -4.05910879e-01 5.92480553e-03
4.20931697e-01 -2.46826485e-01 1.06372952e-01 1.13432407e+00
7.67296553e-01 4.21616994e-03 3.79970223e-01 5.56464732e-01
-2.49718428e-01 3.97738308e-01 -4.34753209e-01 -3.29856843e-01
9.13820744e-01 1.45743787e+00 -4.46495473e-01 -5.18184841e-01
-9.64896321e-01 1.03266943e+00 1.21947855e-01 2.46750981e-01
-1.17339790e+00 -3.41284603e-01 5.16417861e-01 1.12606846e-01
3.53576809e-01 -6.33063763e-02 -3.51656899e-02 -1.14866531e+00
-1.35097176e-01 -1.87337622e-01 7.70714223e-01 -1.02812934e+00
-1.32768953e+00 8.69675428e-02 6.98102266e-02 -1.59062088e+00
2.58377373e-01 -3.19833428e-01 -5.86557209e-01 6.90414846e-01
-1.91635382e+00 -1.91855788e+00 -4.39702153e-01 6.62782073e-01
5.65195009e-02 -1.00708909e-01 6.65337026e-01 1.05194521e+00
-4.79386300e-01 5.56904018e-01 3.34811546e-02 2.74340838e-01
7.68458486e-01 -8.35246086e-01 -1.25520557e-01 7.26428032e-01
3.90004277e-01 1.84101477e-01 1.01719573e-01 -5.62202692e-01
-8.96591604e-01 -1.24141657e+00 1.36851788e+00 -9.32987258e-02
6.90430343e-01 2.21038356e-01 -6.80387974e-01 7.70517170e-01
4.22993563e-02 2.05934793e-01 7.75836647e-01 -2.01328695e-02
-5.42901084e-02 -2.65474349e-01 -1.07442808e+00 4.90805537e-01
1.15828180e+00 -5.72709858e-01 -6.40762746e-01 2.89175808e-01
5.39562047e-01 -2.25386787e-02 -1.24474847e+00 2.34412730e-01
3.98061842e-01 -4.89851356e-01 1.28887761e+00 -1.40351012e-01
3.61517727e-01 -7.20671237e-01 -4.53061402e-01 -1.09212804e+00
-6.30441904e-01 -5.31246103e-02 2.29057208e-01 1.87773168e+00
6.94063082e-02 -5.23744226e-01 4.78022128e-01 2.50164330e-01
-2.15694502e-01 -2.27198571e-01 -1.09977925e+00 -5.31622410e-01
-5.03366649e-01 -3.67010385e-01 9.28397834e-01 9.44145620e-01
2.38982528e-01 3.92161936e-01 -6.22011542e-01 3.62823844e-01
1.75271943e-01 2.28422228e-02 7.48203278e-01 -1.25851047e+00
3.12841758e-02 -3.16424280e-01 -7.07368791e-01 -1.14227211e+00
2.82551080e-01 -8.86148810e-01 4.21507247e-02 -1.66549289e+00
6.48348033e-01 -7.73278952e-01 -6.06029391e-01 8.30538988e-01
-3.22882622e-01 6.38534367e-01 2.36989126e-01 6.20083451e-01
-1.11093986e+00 5.43811977e-01 1.35238981e+00 -3.29888254e-01
7.25993887e-02 -2.67796248e-01 -8.43081236e-01 7.73044407e-01
4.58433509e-01 -4.24518466e-01 -3.38129342e-01 -2.97192782e-01
-7.48104183e-03 -7.52458423e-02 4.71113920e-01 -1.14596784e+00
2.31758744e-01 -2.72555947e-01 2.34719515e-01 -5.34153640e-01
4.31310058e-01 -1.15850234e+00 2.56808728e-01 -2.09673699e-02
2.87774927e-03 -4.94024426e-01 1.01999016e-02 4.76021230e-01
-6.28201962e-01 -5.23903489e-01 6.20236456e-01 -4.93828431e-02
-1.38119030e+00 6.46411717e-01 -4.75450121e-02 -9.13364142e-02
1.08105350e+00 -2.15892419e-01 -2.37033799e-01 -2.68736243e-01
-5.07362962e-01 2.83948541e-01 5.23025036e-01 4.61003125e-01
4.08739656e-01 -1.97596622e+00 -3.28034163e-01 1.19622208e-01
6.24446571e-01 -3.57672244e-01 5.17744362e-01 9.95056272e-01
-2.36668736e-01 2.31682912e-01 -2.43135840e-01 -3.97379577e-01
-1.26588702e+00 6.29154742e-01 1.75578192e-01 -4.38998699e-01
-4.27681386e-01 4.73898292e-01 3.40383679e-01 -3.56341332e-01
-4.56979126e-02 1.30489022e-01 -6.42127573e-01 2.03790486e-01
4.27078724e-01 -6.08252771e-02 -4.46261108e-01 -1.21943212e+00
-3.25937241e-01 6.77512467e-01 3.64836872e-01 -1.13567263e-01
1.01568234e+00 -6.15970314e-01 3.38661075e-02 7.24896640e-02
1.27931273e+00 1.31380126e-01 -8.69689345e-01 -6.44466579e-01
-1.42964929e-01 -7.69147515e-01 1.99206457e-01 -5.44874549e-01
-1.08621049e+00 8.49394321e-01 5.67128539e-01 2.88725570e-02
1.14113808e+00 2.79109687e-01 1.30273890e+00 -1.16911396e-01
3.35701227e-01 -1.00582886e+00 -1.27124965e-01 2.02583864e-01
2.56846100e-01 -1.20692277e+00 -1.28493130e-01 -4.90080953e-01
-9.92522359e-01 5.67856848e-01 4.79110092e-01 1.88867897e-01
8.39526832e-01 -1.51013345e-01 9.60285887e-02 -2.56466955e-01
-2.81667769e-01 -7.73528755e-01 5.41457176e-01 7.95412660e-01
1.21295184e-01 1.62210360e-01 -4.28657979e-01 8.42722595e-01
1.85797825e-01 2.02158242e-01 -7.70632774e-02 7.97629476e-01
-4.61925924e-01 -1.15574586e+00 -2.18071729e-01 2.75607854e-01
-2.34089047e-01 1.15743242e-02 1.64554268e-01 7.19133198e-01
7.93017268e-01 8.46812129e-01 1.68573305e-01 -6.32144034e-01
2.14297697e-01 3.36576104e-02 7.53934830e-02 -4.69062805e-01
-2.67950416e-01 1.56473368e-01 1.96722865e-01 -2.66607165e-01
-9.44890201e-01 -7.64040828e-01 -1.28514349e+00 -1.84677616e-01
-2.82972783e-01 3.24469656e-01 4.39926147e-01 1.12951910e+00
4.28093016e-01 3.70296985e-01 6.75338686e-01 -6.81224704e-01
3.37963216e-02 -1.00582719e+00 -8.65538955e-01 8.36362183e-01
-3.55049431e-01 -1.04574418e+00 -2.03231484e-01 8.64986330e-02] | [10.66134262084961, 1.382787823677063] |
59b3d1bc-b16b-409f-b216-2f8d478e6ba4 | convolutional-relational-machine-for-group | 1904.03308 | null | http://arxiv.org/abs/1904.03308v1 | http://arxiv.org/pdf/1904.03308v1.pdf | Convolutional Relational Machine for Group Activity Recognition | We present an end-to-end deep Convolutional Neural Network called
Convolutional Relational Machine (CRM) for recognizing group activities that
utilizes the information in spatial relations between individual persons in
image or video. It learns to produce an intermediate spatial representation
(activity map) based on individual and group activities. A multi-stage
refinement component is responsible for decreasing the incorrect predictions in
the activity map. Finally, an aggregation component uses the refined
information to recognize group activities. Experimental results demonstrate the
constructive contribution of the information extracted and represented in the
form of the activity map. CRM shows advantages over state-of-the-art models on
Volleyball and Collective Activity datasets. | ['Mina Ghadimi Atigh', 'Ahmad Nickabadi', 'Sina Mokhtarzadeh Azar', 'Alexandre Alahi'] | 2019-04-05 | convolutional-relational-machine-for-group-1 | http://openaccess.thecvf.com/content_CVPR_2019/html/Azar_Convolutional_Relational_Machine_for_Group_Activity_Recognition_CVPR_2019_paper.html | http://openaccess.thecvf.com/content_CVPR_2019/papers/Azar_Convolutional_Relational_Machine_for_Group_Activity_Recognition_CVPR_2019_paper.pdf | cvpr-2019-6 | ['group-activity-recognition'] | ['computer-vision'] | [ 1.18587285e-01 2.73726016e-01 -3.79378796e-01 -4.58028436e-01
-1.26478836e-01 -9.11608785e-02 7.05694914e-01 6.54482916e-02
-5.47329426e-01 5.64017236e-01 7.06753135e-01 1.16665207e-01
-4.36042041e-01 -1.00973165e+00 -9.66370344e-01 -2.98630148e-01
-4.47941035e-01 2.48153836e-01 3.01665723e-01 -2.34131321e-01
1.42353758e-01 5.05984664e-01 -1.44392169e+00 8.33865821e-01
6.31788611e-01 1.13298142e+00 -4.16526478e-03 6.69129372e-01
9.29417461e-02 1.82240391e+00 -7.28034139e-01 -3.50630619e-02
2.42355883e-01 -6.36982977e-01 -9.01285887e-01 4.13129300e-01
3.55049759e-01 -2.78137028e-01 -7.67173231e-01 4.92928952e-01
1.05429525e-02 5.54956675e-01 4.86246228e-01 -1.08997202e+00
-8.76364172e-01 4.92623806e-01 -3.11035722e-01 4.49161351e-01
5.55289268e-01 -1.87538564e-02 6.34704709e-01 -8.46838653e-01
6.80209696e-01 8.70444894e-01 6.90598369e-01 2.37278178e-01
-7.35592365e-01 -3.83915246e-01 4.64428067e-01 4.60997224e-01
-1.52338362e+00 -2.13588029e-02 5.98126411e-01 -6.40364647e-01
1.36173892e+00 -2.96029244e-02 1.09938145e+00 9.86188829e-01
1.65327743e-01 1.01914775e+00 5.74111223e-01 -1.83473304e-01
-8.80362615e-02 -4.34482276e-01 6.09260313e-02 9.81622040e-01
1.23870514e-01 -8.78831521e-02 -1.18321502e+00 4.19114947e-01
1.20134020e+00 3.80951464e-01 5.99158593e-02 -3.48280400e-01
-1.39386046e+00 3.30330402e-01 9.34217989e-01 3.89444709e-01
-7.95648098e-01 3.93334836e-01 -6.69065639e-02 5.73006868e-02
6.47367060e-01 4.48027700e-01 -2.45800540e-01 -3.75804365e-01
-9.09855604e-01 3.11352700e-01 4.15907085e-01 7.35143960e-01
8.49731803e-01 -1.43613353e-01 -5.82866013e-01 5.88343441e-01
-8.79631191e-02 -3.77129838e-02 1.54614225e-01 -1.03112280e+00
7.21352220e-01 1.25005913e+00 2.61187017e-01 -1.02449703e+00
-5.85635126e-01 -6.50930583e-01 -9.32482064e-01 7.36439079e-02
3.72976869e-01 3.71082574e-02 -9.53387320e-01 1.36915910e+00
9.52135473e-02 5.77559769e-01 -1.61312204e-02 8.74162495e-01
9.02433038e-01 5.10311842e-01 2.23268420e-01 2.41054967e-01
1.04638493e+00 -1.57165194e+00 -7.27300704e-01 -2.93038905e-01
6.61121011e-01 6.38344139e-02 5.27413130e-01 2.48857215e-01
-1.13476491e+00 -1.11911559e+00 -1.07202864e+00 -1.92347586e-01
-5.80764174e-01 4.74408001e-01 7.95067966e-01 1.30428344e-01
-1.03216434e+00 8.15947354e-01 -1.14149714e+00 -4.19114828e-01
9.04164374e-01 4.52686280e-01 -7.89773524e-01 2.16639683e-01
-8.89920652e-01 8.22132051e-01 4.41712826e-01 2.67793775e-01
-8.37987840e-01 -6.54572785e-01 -1.13142252e+00 8.48670900e-02
4.85890239e-01 -6.22892916e-01 9.51856554e-01 -1.32440233e+00
-1.22009337e+00 6.88539803e-01 -4.38868403e-02 -7.73777604e-01
7.14687884e-01 -5.59996068e-01 -3.85600775e-01 2.07811505e-01
1.73782974e-01 6.51456594e-01 1.86689004e-01 -7.72847593e-01
-1.12657535e+00 -3.96940857e-01 1.46568820e-01 5.19740343e-01
-1.18107677e-01 -3.10888477e-02 -8.46058905e-01 -6.98023200e-01
2.25338429e-01 -8.73650193e-01 -2.60733902e-01 -2.98651665e-01
-1.35842264e-01 -5.20876288e-01 5.77302396e-01 -9.37917531e-01
1.22983170e+00 -1.84408772e+00 4.85283136e-01 3.22300166e-01
2.33672023e-01 -1.78457707e-01 -7.03089014e-02 3.52559894e-01
-2.62803659e-02 -1.92739833e-02 7.83188120e-02 -2.64379561e-01
-3.35811287e-01 1.95580408e-01 7.34664574e-02 4.52089369e-01
3.37558657e-01 1.12831736e+00 -9.68614697e-01 -4.19738293e-01
3.76164109e-01 4.88720804e-01 -5.08229196e-01 2.54672140e-01
7.29215816e-02 6.87823772e-01 -3.20380658e-01 6.48758471e-01
2.62480646e-01 -3.27154279e-01 2.48168483e-01 4.50960770e-02
-1.70257106e-01 1.86383277e-01 -1.04213202e+00 2.00935960e+00
-7.64163164e-03 7.17278659e-01 -5.11621475e-01 -8.89236748e-01
7.37853765e-01 -5.01481257e-02 8.85016024e-01 -7.59077966e-01
-1.07226558e-01 -3.92570198e-01 -2.25092530e-01 -3.56847525e-01
7.15967059e-01 5.05361855e-01 -4.08149868e-01 2.41198406e-01
5.26524246e-01 6.92236066e-01 4.18915153e-01 2.86783457e-01
1.25442970e+00 5.57363927e-01 4.18096930e-01 2.01146794e-03
5.59429288e-01 5.90104610e-02 6.73263848e-01 1.07074547e+00
-2.18900993e-01 5.70006728e-01 5.79066992e-01 -1.20465362e+00
-7.30527699e-01 -1.12934732e+00 6.13786519e-01 1.50262058e+00
4.55435306e-01 -5.55514753e-01 -6.44768357e-01 -9.17358279e-01
-3.26653898e-01 1.21770032e-01 -1.20859158e+00 -1.12660982e-01
-9.98925865e-01 -3.91644657e-01 4.87245560e-01 1.35502303e+00
1.10736740e+00 -1.28510952e+00 -4.97594357e-01 4.37510759e-03
-2.94271082e-01 -1.01915979e+00 -2.59416103e-01 9.27455798e-02
-7.80405581e-01 -1.30013478e+00 -4.15940553e-01 -7.89805651e-01
8.43564034e-01 2.31011197e-01 1.12013805e+00 1.98320389e-01
1.09303124e-01 2.15375811e-01 -4.63451862e-01 -3.84341002e-01
2.00096846e-01 2.51707822e-01 -9.45665315e-02 3.21363032e-01
4.87972140e-01 -3.94984841e-01 -7.23208427e-01 3.91063780e-01
-5.20193040e-01 4.24850076e-01 8.03910136e-01 5.37096798e-01
6.63186073e-01 8.34389329e-02 1.09381586e-01 -6.81347370e-01
4.40676510e-01 -3.58245730e-01 -2.98704445e-01 3.74004662e-01
-2.74682194e-01 2.13902798e-02 1.02295153e-01 -3.65156829e-01
-1.25305951e+00 3.71208191e-01 2.61936307e-01 -2.92280674e-01
-2.06836939e-01 5.21400154e-01 -2.60560401e-02 3.19719285e-01
7.72011459e-01 2.40948677e-01 -3.15078288e-01 -3.92967701e-01
2.28529990e-01 2.79905826e-01 8.94387245e-01 -2.85285115e-01
4.63778108e-01 5.31918049e-01 -1.85840875e-02 -4.96953607e-01
-1.20699799e+00 -5.20568490e-01 -1.27775037e+00 -6.98637426e-01
1.34240031e+00 -1.23888600e+00 -7.28214979e-01 6.85867667e-01
-9.40477490e-01 -5.68694115e-01 -4.65571105e-01 5.53663909e-01
-5.02536178e-01 -7.87866265e-02 -6.75731301e-01 -6.80399299e-01
4.91904132e-02 -5.77599525e-01 1.06496322e+00 4.83736306e-01
-2.57041365e-01 -7.02316046e-01 7.36511722e-02 7.75466442e-01
-8.54801107e-03 4.23436880e-01 2.06361249e-01 -5.51224470e-01
-1.03393531e+00 -3.76001000e-01 4.33543585e-02 2.34621733e-01
-1.21579028e-03 -2.16656521e-01 -5.31903327e-01 1.50928259e-01
-8.43602300e-01 -7.64496857e-03 1.10191274e+00 5.25840938e-01
1.54262805e+00 -2.65085846e-01 -3.57876778e-01 6.57437384e-01
8.21938813e-01 1.95586964e-01 1.02676570e+00 4.75235313e-01
9.58144367e-01 5.06165743e-01 7.88143396e-01 3.93984228e-01
5.44777215e-01 7.12012112e-01 2.72086322e-01 -2.52993554e-01
-1.97654843e-01 -6.38272405e-01 1.48726895e-01 2.98871309e-01
-1.10538971e+00 -6.93531558e-02 -1.09572029e+00 5.73217690e-01
-2.50632930e+00 -1.60713816e+00 7.43690059e-02 1.72112143e+00
3.03484082e-01 1.50912657e-01 3.57435733e-01 -9.88072306e-02
5.91858208e-01 4.68353242e-01 -2.35045001e-01 6.91205710e-02
-2.38188982e-01 6.53908849e-02 6.84877872e-01 2.08893344e-01
-1.46861875e+00 1.11887777e+00 6.83907986e+00 4.63551760e-01
-3.34484607e-01 9.55364928e-02 5.54123819e-01 -4.33605969e-01
4.16108608e-01 -3.60904634e-01 -5.36757290e-01 1.70324966e-01
6.19502962e-01 2.30720431e-01 4.26609427e-01 1.05497837e+00
1.05071358e-01 -3.05997223e-01 -1.05800819e+00 9.78536189e-01
2.49078542e-01 -1.76992667e+00 -5.09476475e-03 2.10736275e-01
8.92680883e-01 -6.26419554e-04 -1.45112157e-01 7.09071398e-01
5.86674571e-01 -1.12618053e+00 1.11449695e+00 1.24551129e+00
3.66498649e-01 -9.89228904e-01 9.42979395e-01 5.55386484e-01
-1.44054413e+00 -4.63504374e-01 -8.07105973e-02 -4.55625713e-01
4.82504293e-02 -9.35958177e-02 -6.99895203e-01 4.78242666e-01
1.09425104e+00 1.12227905e+00 -9.68555510e-01 6.02608860e-01
-4.29885179e-01 2.15587914e-01 1.08561821e-01 1.87319383e-01
3.46151441e-01 -2.49557704e-01 4.17721421e-02 1.22316301e+00
3.01597118e-01 1.40139699e-01 2.03870133e-01 6.32346213e-01
-2.53844678e-01 -4.08380747e-01 -6.19233906e-01 -5.54458164e-02
1.26908839e-01 9.76402879e-01 -6.85534716e-01 -4.95873302e-01
-4.13715750e-01 1.10443807e+00 7.63929188e-01 3.18612844e-01
-1.01117849e+00 -1.61651358e-01 7.95440197e-01 4.44647104e-01
3.23288769e-01 -2.90500164e-01 -2.56418914e-01 -1.01886034e+00
3.92833203e-02 -4.66963619e-01 7.07568109e-01 -1.10027528e+00
-7.07646549e-01 5.20638525e-01 9.53570455e-02 -1.29759371e+00
-4.07022953e-01 -4.58823353e-01 -5.59299529e-01 6.47069871e-01
-8.58790159e-01 -1.48978007e+00 -8.95404458e-01 6.68933749e-01
6.95038557e-01 -4.72915083e-01 4.83937025e-01 7.14125950e-03
-7.47260511e-01 2.85410017e-01 -6.03093326e-01 7.81359255e-01
1.28428161e-01 -1.23634279e+00 3.52637053e-01 1.07190096e+00
3.97749752e-01 6.04920924e-01 1.53044641e-01 -8.64177227e-01
-7.25426853e-01 -1.32867956e+00 1.00080967e+00 -8.26021850e-01
2.31673345e-01 -3.22189271e-01 -5.63150406e-01 1.18766832e+00
2.46238187e-01 3.70307475e-01 8.26253116e-01 4.25355792e-01
-2.10177526e-01 -2.12384939e-01 -7.44495034e-01 6.45461619e-01
1.73832691e+00 -5.84584892e-01 -7.16747582e-01 1.25206172e-01
5.51448524e-01 -5.67064643e-01 -9.07661259e-01 4.05264497e-01
5.92560410e-01 -1.04890728e+00 1.12561595e+00 -9.50911522e-01
5.47963202e-01 -5.03257632e-01 1.93039000e-01 -1.23591411e+00
-8.46595407e-01 -2.74129122e-01 -5.51031649e-01 6.44638598e-01
4.32390213e-01 1.58412233e-01 1.30140686e+00 4.91179854e-01
-3.13698143e-01 -6.43496692e-01 -6.80030227e-01 -5.81974685e-01
-7.08670974e-01 -3.85988712e-01 6.85495913e-01 9.01001096e-01
7.63000548e-02 1.27415046e-01 -6.37534559e-01 1.79107204e-01
2.59121120e-01 -1.96121156e-01 1.03602827e+00 -1.20932710e+00
-1.96908697e-01 -1.57654509e-01 -7.76039481e-01 -1.03871715e+00
2.68397648e-02 -5.00849009e-01 -1.73592865e-01 -2.04410768e+00
2.44348988e-01 2.81712055e-01 -7.13060200e-01 6.74024403e-01
-2.10889317e-02 3.88007641e-01 3.19472373e-01 2.96579480e-01
-1.51299143e+00 3.23297083e-01 1.11166573e+00 -2.06290707e-01
-5.30768335e-01 1.16011575e-01 -6.65525556e-01 9.58413720e-01
8.04266930e-01 -2.94969231e-01 -2.38623038e-01 -4.34324384e-01
3.33359331e-01 3.32582705e-02 5.99658370e-01 -1.61281657e+00
4.92064327e-01 -3.53646040e-01 1.06569314e+00 -1.01585555e+00
4.56112593e-01 -6.73076808e-01 3.03911895e-01 3.42912197e-01
-6.40400290e-01 -3.73453996e-03 -2.52027005e-01 8.66639137e-01
-5.06581485e-01 5.11952460e-01 3.79788607e-01 -3.07894170e-01
-1.13465309e+00 3.09947819e-01 -4.67857242e-01 -4.87780362e-01
1.24117601e+00 -6.15498960e-01 -3.88371527e-01 -4.58842307e-01
-1.18793106e+00 2.26805255e-01 -1.42602250e-02 7.91409373e-01
6.39322340e-01 -1.68152845e+00 -4.82820034e-01 2.57263750e-01
3.74397278e-01 8.03144276e-02 5.44951916e-01 9.98587072e-01
-8.40936184e-01 4.61247325e-01 -6.27173305e-01 -5.59651315e-01
-1.25611818e+00 2.66792774e-01 6.27230823e-01 -6.07666135e-01
-4.75439876e-01 9.01662350e-01 9.09240171e-02 -2.38803104e-01
3.72331738e-01 -5.37040949e-01 -5.54563820e-01 -2.39361916e-02
7.82462597e-01 6.56567216e-01 -2.74158716e-02 -8.69684458e-01
-4.27765548e-01 1.80920139e-01 1.92984819e-01 -7.42601380e-02
1.72706711e+00 1.15698837e-01 8.62610638e-02 9.72629413e-02
7.15047121e-01 -3.51842761e-01 -1.96314728e+00 -1.88212603e-01
1.75792977e-01 -5.20437717e-01 -1.14830583e-02 -8.32114697e-01
-1.11440718e+00 5.02105832e-01 4.76457119e-01 -7.83278495e-02
1.12577128e+00 2.13308051e-01 3.75747442e-01 7.46319413e-01
3.88259202e-01 -1.66833127e+00 5.78358710e-01 5.75061798e-01
9.61458206e-01 -1.10376871e+00 1.83014169e-01 -3.24129432e-01
-1.13067961e+00 7.82360256e-01 9.43357527e-01 -3.05538535e-01
5.48664212e-01 1.15969889e-01 -2.67319828e-01 -3.72165233e-01
-7.17643440e-01 -5.17399073e-01 6.77311420e-01 8.64595711e-01
1.90802962e-01 7.51224607e-02 3.13472338e-02 9.99205172e-01
7.20460042e-02 2.73854733e-01 1.40320867e-01 1.09103465e+00
-5.17755747e-01 -5.00511825e-01 -2.46763349e-01 4.55401689e-01
-4.21333045e-01 3.66892219e-01 -8.12929869e-01 9.69062209e-01
7.32752562e-01 8.42902601e-01 5.88001251e-01 -8.08166325e-01
6.00241244e-01 -6.51483610e-02 4.87827182e-01 -6.15823567e-01
-9.25368786e-01 -1.65599301e-01 3.12937409e-01 -1.15180373e+00
-7.90352106e-01 -5.42373002e-01 -1.16677928e+00 -2.54817933e-01
3.50841701e-01 -1.44852325e-01 2.92182505e-01 8.61708641e-01
4.33798075e-01 8.45342815e-01 1.04728147e-01 -9.97218490e-01
4.53961313e-01 -1.23521769e+00 -5.55458784e-01 6.99396670e-01
4.42038290e-02 -7.41825700e-01 3.12346905e-01 3.18455219e-01] | [8.096292495727539, 0.5572760105133057] |
76b0c9c6-9491-4118-8754-78dda0437780 | futuristic-methods-in-virus-genome-evolution | 1902.09148 | null | http://arxiv.org/abs/1902.09148v1 | http://arxiv.org/pdf/1902.09148v1.pdf | Futuristic methods in virus genome evolution using the Third-Generation DNA sequencing and artificial neural networks | The Third-Generation in DNA sequencing has emerged in the last few years
using new technologies that allow the production of long-read sequences.
Applications of the Third-Generation sequencing enable real-time and on-site
data production, changing the research paradigms in environmental and medical
sampling in virology. To take full advantage of large-scale data generated from
long-read sequencing, an innovation in the downstream data analysis is
necessary. Here, we discuss futuristic methods using machine learning
approaches to analyze big genetic data. Machine learning combines pattern
recognition and computational learning to perform predictive and exploratory
data analysis. In particular, deep learning is a field of machine learning that
is used to solve complex problems through artificial neural networks. Unlike
other methods, features can be learned using neural networks entirely from data
without manual specifications. We discuss the future of 21st-century virology
by presenting futuristic approaches for virus studies using real-time data
production and on-site data analysis with the Third-Generation Sequencing and
machine learning methods. We first introduce the basic concepts in conventional
statistical models and methods in virology, building gradually into the
necessity of innovating the downstream data analysis to meet the advances in
sequencing technologies. We argue that artificial neural networks can innovate
the downstream data analysis, as they can learn from big datasets without model
assumptions or feature specifications, as opposed to the current data analysis
in bioinformatics. Furthermore, we discuss how futuristic methods using
artificial neural networks combined with long-read sequences can revolutionize
virus studies, using specific examples in supervised and unsupervised settings. | [] | 2019-02-25 | null | null | null | null | ['virology'] | ['miscellaneous'] | [ 6.45378590e-01 -4.33076739e-01 1.95683241e-02 -3.58513504e-01
-1.81307063e-01 -6.76535785e-01 5.19905210e-01 9.55232456e-02
-5.84322095e-01 8.68047357e-01 -1.09766841e-01 -6.40871823e-01
-2.15011343e-01 -8.11277628e-01 -8.34014773e-01 -1.14149714e+00
-2.56866962e-01 8.20506155e-01 -4.82011974e-01 -3.15400809e-01
2.88512290e-01 7.78086424e-01 -1.61557066e+00 7.32331991e-01
8.49847615e-01 6.31394506e-01 7.07398534e-01 1.24448466e+00
-6.42485499e-01 9.49846283e-02 -5.73619366e-01 -2.07429137e-02
2.61630446e-01 -1.79992557e-01 -4.58600760e-01 -5.61930478e-01
-2.13343456e-01 -2.18522370e-01 3.29617977e-01 5.99939585e-01
6.76295996e-01 -6.17372870e-01 4.87006396e-01 -1.01784515e+00
-8.77983153e-01 9.37118307e-02 -1.44475877e-01 8.42115434e-04
1.13078222e-01 6.00692928e-01 5.41426241e-01 -6.56543911e-01
9.71859217e-01 1.23023582e+00 1.17080927e+00 6.03220761e-01
-1.20219374e+00 -1.12820745e-01 -4.42358464e-01 4.16733086e-01
-1.02116430e+00 -1.01560066e-02 2.68278688e-01 -9.79651928e-01
1.41355467e+00 4.98626024e-01 7.61963785e-01 1.48224914e+00
6.72386885e-01 6.01105750e-01 9.61204708e-01 -2.84802824e-01
2.54596442e-01 -1.72415793e-01 9.61413458e-02 5.83721220e-01
2.67302305e-01 6.02741599e-01 -7.66171366e-02 -4.21790779e-01
3.65816712e-01 5.87044418e-01 -6.30748868e-02 1.37431294e-01
-1.32903373e+00 1.10253131e+00 -9.96461883e-02 4.85247433e-01
-5.07136822e-01 -3.57166171e-01 7.04618275e-01 3.60522002e-01
4.06888604e-01 7.76648283e-01 -1.13889205e+00 -1.13985099e-01
-7.45715320e-01 -1.48950323e-01 7.32787013e-01 5.00876546e-01
7.41801620e-01 1.06643565e-01 -1.77213401e-01 7.83275008e-01
4.99290153e-02 7.92803168e-01 5.78252912e-01 -4.70132321e-01
-3.71243209e-01 4.39000458e-01 -4.30832580e-02 -6.30373061e-01
-1.08994532e+00 -3.68511379e-01 -1.21011817e+00 3.27697769e-02
4.28689301e-01 -3.71333331e-01 -1.09697545e+00 1.18052709e+00
3.02643061e-01 1.94683224e-01 9.53222252e-03 7.13578463e-01
6.11427784e-01 9.04289722e-01 -2.66244978e-01 -4.25847977e-01
1.40138793e+00 -4.85712051e-01 -8.14187050e-01 2.49510974e-01
8.11436415e-01 -5.05354166e-01 8.05520952e-01 6.16742313e-01
-1.90184966e-01 -4.93924469e-01 -8.27336311e-01 7.33664632e-02
-1.07354295e+00 -2.81525820e-01 6.05686426e-01 8.64299297e-01
-1.02724361e+00 6.78622305e-01 -7.41047502e-01 -8.17267239e-01
4.41794693e-01 3.57849926e-01 -3.40810299e-01 9.76567268e-02
-1.14794028e+00 7.92232335e-01 5.71401358e-01 4.81182933e-01
-1.03639793e+00 -1.03090072e+00 -4.18852299e-01 -1.55986905e-01
1.05353385e-01 -8.51156414e-01 5.37913024e-01 -7.48479426e-01
-1.63688898e+00 8.66941750e-01 -3.09446380e-02 -1.51984245e-01
4.95915264e-02 -9.36244130e-02 -4.29663867e-01 -2.44368613e-01
-4.82863635e-01 2.32664675e-01 4.04171467e-01 -8.37471366e-01
-5.86304188e-01 -6.68172598e-01 -6.15790725e-01 -9.32057381e-01
-1.03124641e-01 3.76647823e-02 1.59549609e-01 -3.58080655e-01
-6.27943575e-01 -8.82392049e-01 -3.36982816e-01 -3.15015227e-01
-2.76469082e-01 -1.13958567e-01 9.98512805e-01 -7.31224597e-01
5.08061767e-01 -1.63502586e+00 1.17643192e-01 2.58765202e-02
4.86502014e-02 8.64316642e-01 -7.34091759e-01 8.30066562e-01
5.03155813e-02 2.44814306e-01 -1.46210715e-01 3.70704144e-01
-3.62685293e-01 3.37551445e-01 -1.84256956e-01 3.37936163e-01
4.99419868e-01 1.25198686e+00 -1.09886503e+00 2.31835261e-01
2.70551443e-01 8.21918845e-01 -3.68013382e-01 4.54871625e-01
-5.26354015e-01 7.16075599e-01 -2.60798633e-01 7.02200353e-01
8.87219191e-01 -4.30229694e-01 5.95078528e-01 -4.25761901e-02
-2.44146585e-01 -3.30681652e-01 -4.43739712e-01 1.65387297e+00
-3.56624216e-01 6.20513439e-01 3.44418176e-02 -1.20777500e+00
9.47459579e-01 2.00849548e-01 3.33003670e-01 -6.13372266e-01
-9.17526633e-02 2.48091847e-01 1.26057163e-01 -1.18981338e+00
6.39029890e-02 -4.29849774e-01 4.91902232e-01 3.00214440e-01
-8.06246772e-02 2.41257012e-01 2.34956923e-03 -3.50627720e-01
1.07447147e+00 2.20558658e-01 2.65186697e-01 -3.52587223e-01
5.28850675e-01 2.48031721e-01 9.24057901e-01 9.53090310e-01
-8.72209743e-02 3.92192155e-01 4.14569318e-01 -1.19075704e+00
-1.52838039e+00 -6.34535372e-01 -2.56817847e-01 1.30388117e+00
-7.22035468e-01 -3.33799534e-02 -5.15273452e-01 -4.46853042e-01
2.83501416e-01 1.79749712e-01 -6.54410958e-01 2.47525811e-01
-5.75549066e-01 -1.48229456e+00 7.81962872e-01 1.34186968e-01
-3.69675487e-01 -1.19047856e+00 -4.25812960e-01 3.41363430e-01
1.80309303e-02 -7.65654504e-01 1.56320155e-01 4.44591790e-01
-6.94722295e-01 -1.04594028e+00 -4.54827458e-01 -5.71492732e-01
3.16665411e-01 9.22682043e-03 7.59997189e-01 1.44328892e-01
-1.01568961e+00 -2.58071959e-01 -4.27357495e-01 -8.53303790e-01
-8.18808854e-01 1.75271332e-01 3.71570051e-01 -2.00792626e-01
8.34454298e-01 -4.21733677e-01 -4.57445383e-01 -1.08078375e-01
-1.09183621e+00 7.57387727e-02 8.91664565e-01 1.38363945e+00
3.35920393e-01 -3.87218267e-01 1.07869911e+00 -1.06021297e+00
4.67933118e-01 -7.19171643e-01 -7.78544903e-01 5.44102669e-01
-4.63361859e-01 3.89356315e-01 1.17814028e+00 -3.95715460e-02
-7.72253096e-01 -3.28583360e-01 -5.92907608e-01 2.77648401e-02
-2.66353577e-01 7.30043173e-01 4.18976545e-02 2.42755622e-01
7.44490385e-01 5.57475030e-01 7.68623888e-01 -5.05778670e-01
2.30255097e-01 1.31173944e+00 -1.00601554e-01 -1.42040804e-01
2.34995276e-01 7.80511618e-01 2.16366991e-01 -1.09556961e+00
-3.08426738e-01 -4.48916972e-01 -7.45771825e-01 2.14698929e-02
9.95382786e-01 -3.89051616e-01 -1.36662567e+00 8.10526490e-01
-1.12906277e+00 -3.35805446e-01 1.21358089e-01 4.53220248e-01
-6.40177906e-01 3.52203548e-01 -8.59919548e-01 -8.93860638e-01
-6.71724796e-01 -1.13235199e+00 1.33972609e+00 -9.30309948e-03
3.06851193e-02 -1.03241193e+00 5.37061512e-01 2.09091321e-01
6.42783225e-01 3.36603165e-01 1.10450232e+00 -8.84235680e-01
-4.65173215e-01 -2.01804474e-01 -8.17816332e-02 2.43547484e-01
4.59948927e-01 3.12071353e-01 -1.14792573e+00 -3.94672632e-01
-2.45268103e-02 -2.06632823e-01 9.00663972e-01 5.29276550e-01
1.33606660e+00 -2.20336616e-01 -6.13747299e-01 8.99929285e-01
1.57853377e+00 5.34017801e-01 6.77169979e-01 3.30342174e-01
7.28351176e-01 9.62995052e-01 4.52065051e-01 5.17398179e-01
-1.80246681e-01 2.00015217e-01 2.42731035e-01 -9.12100598e-02
4.77689803e-01 9.90287885e-02 9.57213640e-02 8.21172774e-01
-2.53202975e-01 -2.33462662e-01 -1.20090020e+00 1.56991765e-01
-1.80703795e+00 -1.29029882e+00 -3.03902328e-01 2.25198483e+00
7.23948419e-01 -5.51687598e-01 8.70237127e-02 -3.30611825e-01
6.80633366e-01 -1.72122315e-01 -4.10168558e-01 -7.88367450e-01
-4.35710877e-01 5.22117466e-02 2.86615461e-01 3.52897197e-01
-8.64170432e-01 5.82753420e-01 7.46967936e+00 6.92539215e-01
-1.57922602e+00 1.82671528e-02 6.61579847e-01 -2.73273051e-01
-4.58857358e-01 -3.79793078e-01 -7.05647230e-01 6.80382907e-01
1.45505559e+00 3.62435520e-01 5.01069844e-01 5.38964331e-01
6.43930674e-01 3.05959523e-01 -1.10998869e+00 7.13722050e-01
-9.87624153e-02 -2.05194879e+00 1.22808218e-01 3.67860436e-01
5.55891871e-01 6.47657812e-01 -3.61761779e-01 4.42088917e-02
1.89014524e-01 -1.28884089e+00 -3.03191483e-01 8.91985714e-01
7.43630528e-01 -7.42109060e-01 1.25226235e+00 5.49689710e-01
-5.01498282e-01 -2.25513086e-01 -7.23893344e-01 -9.89502668e-02
1.32333994e-01 1.21530497e+00 -1.40825653e+00 6.88056350e-01
6.04562223e-01 5.11119545e-01 -3.28946523e-02 6.61883652e-01
3.37869078e-01 3.44618350e-01 -1.66475207e-01 -5.38666427e-01
4.31597717e-02 -4.56906796e-01 4.95915323e-01 1.72918379e+00
3.55652839e-01 -2.78572321e-01 4.26244363e-02 6.38092279e-01
4.99970943e-01 -9.96323153e-02 -7.73624718e-01 -6.75682425e-01
1.20890424e-01 1.35180128e+00 -5.43097496e-01 -4.71848518e-01
-3.31997663e-01 5.56484461e-01 2.65714347e-01 4.18695986e-01
-4.04098481e-01 -4.71855313e-01 1.00388885e+00 -1.55116124e-02
3.68634850e-01 -2.61506826e-01 -3.35810930e-01 -8.89798403e-01
-3.35738689e-01 -1.17214489e+00 5.51395953e-01 -5.15042007e-01
-1.64152610e+00 5.02085507e-01 -6.08531356e-01 -7.21935213e-01
-3.66886228e-01 -1.32918465e+00 -2.94433296e-01 8.65163565e-01
-1.42060041e+00 -1.08240080e+00 -2.26289928e-02 -1.68364003e-01
3.89913559e-01 -5.17448962e-01 1.16603017e+00 1.49310473e-02
-5.21506727e-01 1.28978625e-01 1.21692872e+00 -9.27500352e-02
5.77173948e-01 -9.24514592e-01 4.94305789e-01 3.49758416e-01
-5.00190556e-01 9.19346452e-01 5.86120188e-01 -1.02774501e+00
-2.18481874e+00 -1.01192749e+00 8.16071033e-01 -4.53627735e-01
5.63211799e-01 -8.39454889e-01 -9.60068464e-01 5.52047491e-01
7.52994195e-02 -3.23646307e-01 1.40110171e+00 4.68792528e-01
-4.87958878e-01 -2.22559467e-01 -1.31860399e+00 3.61202210e-01
9.78378713e-01 -6.07420683e-01 -3.54833573e-01 6.21156156e-01
6.03544116e-01 3.38577330e-01 -8.34717214e-01 5.86227775e-01
1.08384979e+00 -6.39362633e-01 9.07338679e-01 -1.33376491e+00
2.13483572e-01 -4.11805511e-01 3.15755643e-02 -1.48087645e+00
-5.55988193e-01 -5.95542610e-01 2.36618236e-01 5.29029071e-01
2.60331243e-01 -8.62320960e-01 6.37220621e-01 -1.92276165e-01
-2.18712300e-01 -6.79412961e-01 -7.45768845e-01 -9.80070114e-01
8.51907507e-02 -1.61793932e-01 7.94371665e-01 1.07246065e+00
2.35297754e-01 4.25492190e-02 -5.93180835e-01 -4.11114059e-02
4.30366307e-01 2.70762503e-01 6.88577592e-01 -1.42463815e+00
-3.55755717e-01 -3.59799057e-01 -6.64394319e-01 -4.39637423e-01
-9.63613577e-03 -9.21370864e-01 2.44485587e-01 -1.51277328e+00
4.38277394e-01 -2.30428159e-01 -2.45157883e-01 1.30476549e-01
-3.93308938e-01 4.01806682e-02 -2.36899078e-01 -1.12046622e-01
5.79674058e-02 1.11534268e-01 1.01052654e+00 -1.98175296e-01
-9.43064243e-02 -5.04430413e-01 -4.08985257e-01 2.73570925e-01
8.75555992e-01 -2.67298192e-01 -4.75772657e-02 -3.26521873e-01
6.07682645e-01 -4.14952040e-01 1.07043780e-01 -3.83934766e-01
-7.51560703e-02 -6.00042820e-01 6.88530207e-01 -7.14855492e-01
-1.60482172e-02 -6.93988800e-01 6.05104446e-01 1.06670141e+00
1.59380823e-01 -4.34170626e-02 2.98628122e-01 4.58624244e-01
2.61618346e-01 6.32249052e-03 6.25484705e-01 -2.27123439e-01
-5.00067055e-01 9.06111002e-02 -8.72859955e-01 -5.46925485e-01
1.05322480e+00 -3.30450833e-01 -8.50559533e-01 2.60242850e-01
-6.33467555e-01 1.87179536e-01 3.13686281e-01 5.77885330e-01
5.30065298e-01 -8.20671320e-01 -1.19981480e+00 7.45443583e-01
2.81727433e-01 -4.12013769e-01 7.08309710e-01 8.92187774e-01
-1.01573944e+00 1.05008364e+00 -6.48584306e-01 -1.15995026e+00
-1.14154553e+00 1.35434699e+00 1.58374012e-01 -1.34872928e-01
-2.45720506e-01 4.80774909e-01 2.88400501e-01 -1.08703470e+00
-3.17127258e-01 2.70500835e-02 -1.77478090e-01 3.28177400e-02
1.08734930e+00 2.88155437e-01 2.62241453e-01 1.19758591e-01
-5.42277694e-01 3.80954027e-01 -7.13794231e-02 4.54571038e-01
1.84773803e+00 1.60378605e-01 -6.12817347e-01 6.58506870e-01
1.27802408e+00 -3.22788477e-01 -6.52536154e-01 3.06871414e-01
1.29520789e-01 -3.90025973e-01 -4.65198338e-01 -1.02829683e+00
-6.28432155e-01 9.70787287e-01 7.11580276e-01 2.03996897e-01
9.35183465e-01 -3.14117521e-01 6.40255272e-01 7.63972938e-01
4.55902696e-01 -1.12590659e+00 -2.00992316e-01 7.38598585e-01
8.61059844e-01 -1.36615694e+00 -4.81148064e-01 -4.97253388e-02
-3.68382782e-02 1.33870971e+00 1.46955892e-01 4.59705323e-01
4.51293737e-01 6.63359582e-01 3.61903667e-01 -1.76345915e-01
-1.02429414e+00 2.59593800e-02 -2.35959768e-01 1.19201279e+00
6.52769566e-01 2.78843284e-01 -5.61859608e-01 2.33788982e-01
7.52877966e-02 5.33271074e-01 4.16840285e-01 1.01236641e+00
-5.86547077e-01 -1.39573550e+00 -5.76429069e-01 8.53607893e-01
-3.80590379e-01 -2.23532304e-01 -4.15618360e-01 2.53018290e-01
2.57833838e-01 9.50922370e-01 3.07185113e-01 -5.12177169e-01
-3.62849951e-01 5.45580029e-01 3.13400716e-01 -4.04704630e-01
-6.30191982e-01 -9.31484178e-02 1.01543970e-01 -3.20360482e-01
-9.72187445e-02 -4.02224064e-01 -1.16070557e+00 -7.03773320e-01
-1.51032269e-01 1.92827985e-01 1.30792332e+00 9.93764341e-01
1.10745740e+00 4.48677212e-01 5.26916683e-01 -5.50928175e-01
-2.71730274e-01 -1.12064338e+00 -3.97530496e-01 8.92052278e-02
5.21168351e-01 -1.31733576e-02 -8.90124068e-02 -1.20287631e-02] | [5.448887348175049, 5.468742847442627] |
0ae7446a-adc6-4c08-b828-14a80a9aa0d0 | ssncse-nlp-dravidianlangtech-eacl2021-meme | null | null | https://aclanthology.org/2021.dravidianlangtech-1.49 | https://aclanthology.org/2021.dravidianlangtech-1.49.pdf | SSNCSE_NLP@DravidianLangTech-EACL2021: Meme classification for Tamil using machine learning approach | Social media are interactive platforms that facilitate the creation or sharing of information, ideas or other forms of expression among people. This exchange is not free from offensive, trolling or malicious contents targeting users or communities. One way of trolling is by making memes. A meme is an image or video that represents the thoughts and feelings of a specific audience. The challenge of dealing with memes is that they are region-specific and their meaning is often obscured in humour or sarcasm. A meme is a form of media that spreads an idea or emotion across the internet. The multi modal nature of memes, postings of hateful memes or related events like trolling, cyberbullying are increasing day by day. Memes make it even more challenging since they express humour and sarcasm in an implicit way, because of which the meme may not be offensive if we only consider the text or the image. In this paper we proposed a approach for meme classification for Tamil language that considers only the text present in the meme. This work explains the submissions made by SSNCSE NLP in DravidanLangTechEACL2021 task for meme classification in Tamil language. We achieve F1 scores of 0.50 using the proposed approach using the test-set. | ['Agnusimmaculate Silvia A', 'Bharathi B'] | null | null | null | null | eacl-dravidianlangtech-2021-4 | ['meme-classification'] | ['natural-language-processing'] | [-3.22770357e-01 -2.60754582e-02 1.96995959e-01 2.59022921e-01
-1.14946395e-01 -9.24208105e-01 1.09147656e+00 6.46928549e-01
-4.16088879e-01 9.63280499e-01 4.85661626e-01 4.64405343e-02
4.46188986e-01 -8.42892230e-01 -4.01709259e-01 -5.11524677e-01
3.36359024e-01 -7.97879919e-02 2.79952884e-01 -5.90638399e-01
8.87857020e-01 2.00849026e-01 -1.26235855e+00 7.49188781e-01
3.50978941e-01 6.51706457e-01 8.65740255e-02 7.16096163e-01
-7.91750133e-01 1.61968207e+00 -1.17555571e+00 -5.43521404e-01
-1.23993725e-01 -6.33560002e-01 -6.38380706e-01 1.35191008e-01
5.67445636e-01 1.94704309e-02 -2.19183564e-01 1.14656186e+00
3.45029205e-01 2.93037966e-02 6.07253075e-01 -1.07861972e+00
-7.28198886e-01 4.63886112e-01 -8.64646018e-01 4.50679213e-01
5.32022119e-01 -2.78102696e-01 3.17573130e-01 -1.06337368e+00
9.81778204e-01 1.53700924e+00 5.52313566e-01 3.28296691e-01
-9.75458741e-01 -8.51454794e-01 -6.18631601e-01 -8.21100026e-02
-1.34652615e+00 8.89727697e-02 8.26356173e-01 -9.79600966e-01
4.76281792e-01 5.15603781e-01 7.51226783e-01 1.23397613e+00
9.21103060e-01 6.95600867e-01 1.31604993e+00 -2.15596318e-01
7.30706081e-02 7.53411233e-01 1.31096303e-01 5.36433101e-01
-1.98075145e-01 -6.33392215e-01 -8.08981121e-01 -4.85936224e-01
6.06954731e-02 2.12111726e-01 4.28756289e-02 5.35661817e-01
-1.12391925e+00 1.17605829e+00 4.16738898e-01 7.86491454e-01
-3.46084237e-01 -2.76109427e-02 8.55128646e-01 6.44492090e-01
9.68917668e-01 4.32490736e-01 4.67764556e-01 -2.56312937e-01
-1.05533350e+00 2.09141299e-01 8.45272005e-01 1.62185833e-01
6.36052430e-01 -4.67621863e-01 1.28364459e-01 1.04025972e+00
8.52268375e-03 6.96647406e-01 5.64094841e-01 -1.83354691e-01
2.49299765e-01 7.90421128e-01 1.49620116e-01 -2.25125122e+00
-3.33630800e-01 -1.91958755e-01 -6.39168561e-01 3.27396423e-01
7.87590668e-02 -2.58360773e-01 -3.76633257e-01 1.31858242e+00
3.46204191e-01 -2.97249854e-01 -3.39426875e-01 8.19531381e-01
1.11100245e+00 1.32594752e+00 9.33003351e-02 -3.14445943e-01
1.26184058e+00 -8.31489563e-01 -1.13088465e+00 -3.75235714e-02
4.81278628e-01 -1.58968997e+00 8.84747326e-01 4.58931327e-01
-9.58268166e-01 -2.29633644e-01 -9.24615145e-01 -7.82860536e-03
-8.64908993e-01 -2.83035219e-01 -1.71722353e-01 5.79499304e-01
-6.65859401e-01 4.41804320e-01 6.88553974e-02 -7.68707812e-01
3.08485091e-01 -1.97474614e-01 -4.65426803e-01 4.12952572e-01
-1.06405890e+00 1.02893066e+00 4.93773967e-01 -2.68243551e-01
-3.25301856e-01 -4.45916265e-01 -2.61174411e-01 -5.67755878e-01
3.43970865e-01 1.04992464e-01 4.81561273e-01 -1.57705677e+00
-9.83665526e-01 1.46385324e+00 1.80447474e-01 -2.92863816e-01
9.16454971e-01 -3.89851421e-01 -6.73207104e-01 2.14469537e-01
2.86631882e-01 4.72176671e-01 1.22050774e+00 -1.06517136e+00
-1.91252187e-01 -4.01076004e-02 -4.10532504e-02 -2.40552559e-01
-7.80617774e-01 6.40401185e-01 3.45662355e-01 -9.89597857e-01
-6.53635487e-02 -1.01846015e+00 4.52906370e-01 -3.10468584e-01
-8.01892519e-01 -5.39133325e-02 1.62409568e+00 -9.36604679e-01
1.41895485e+00 -2.32169127e+00 -4.54080068e-02 7.66011328e-02
7.75099337e-01 3.64289880e-01 2.44733274e-01 1.26631856e+00
2.39980742e-01 6.60825849e-01 7.13384449e-02 3.35114822e-02
-2.74578989e-01 -2.52741635e-01 -3.73392642e-01 7.48985887e-01
-2.63012052e-01 6.80509090e-01 -9.25136626e-01 -6.98411226e-01
-4.65171114e-02 4.71576363e-01 -2.36530155e-01 5.43845147e-02
1.25702083e-01 5.66944599e-01 -5.33250093e-01 1.72000602e-01
7.23581076e-01 -1.10052392e-01 -1.23723425e-01 -5.09774052e-02
-5.78105807e-01 -6.28345236e-02 -7.21404791e-01 8.36977005e-01
-3.27566206e-01 1.42951238e+00 -1.15241762e-02 -2.65589923e-01
1.10026562e+00 2.53897101e-01 3.33713144e-01 -3.95721495e-01
5.94624579e-01 1.34998500e-01 -3.91930908e-01 -6.32860303e-01
8.08192074e-01 -4.45494950e-01 -3.30337465e-01 1.07601857e+00
-3.68293554e-01 -2.05187779e-02 4.85354885e-02 5.38090408e-01
1.00243211e+00 -4.81319457e-01 6.49808764e-01 -4.83077049e-01
5.34773946e-01 2.26146262e-02 -1.07781291e-01 5.95300496e-01
-1.41607225e-01 2.77559876e-01 5.34613132e-01 -7.11764336e-01
-1.29097497e+00 -7.96345055e-01 -1.46317661e-01 1.22665012e+00
8.54598135e-02 -4.19627309e-01 -5.97849011e-01 -4.23354805e-01
-2.13901605e-02 4.61497307e-01 -8.70612144e-01 4.03675959e-02
-2.31487602e-01 -5.49700499e-01 4.93318319e-01 -4.18297559e-01
1.01344502e+00 -1.31217420e+00 -6.89140916e-01 4.15606737e-01
-4.14891750e-01 -9.17086720e-01 -4.78795052e-01 -5.00440538e-01
-4.24905688e-01 -8.66780162e-01 -7.67220736e-01 -5.39671898e-01
5.80895483e-01 3.36881340e-01 8.55942965e-01 4.61837232e-01
-5.32849059e-02 1.11581340e-01 -7.03622162e-01 -5.28452456e-01
-9.73185837e-01 -8.26755315e-02 3.67556289e-02 4.75415528e-01
3.35836411e-01 -3.84615749e-01 -1.53086096e-01 2.80412495e-01
-1.20721662e+00 3.51538956e-01 -3.04579258e-01 6.37235940e-01
-2.99512804e-01 7.81322420e-02 5.52820265e-01 -1.21187949e+00
9.98346031e-01 -1.05902326e+00 2.20543131e-01 -1.05536461e-01
1.93601787e-01 -5.95626414e-01 4.91147399e-01 -7.51098931e-01
-9.36224937e-01 -6.36798441e-01 3.39018047e-01 -5.81337921e-02
-9.71055031e-02 5.43527067e-01 5.34642816e-01 -2.17717573e-01
8.88194144e-01 -6.00454696e-02 3.66977006e-02 -4.34076041e-01
-1.83421478e-01 1.08379042e+00 -2.27816030e-02 -4.40591723e-02
9.17414904e-01 6.53660119e-01 -1.94315553e-01 -1.50019145e+00
-9.69658196e-01 -6.39279544e-01 -3.68438959e-01 -9.49274540e-01
1.02471113e+00 -4.34648931e-01 -7.18319893e-01 6.10421956e-01
-1.41472507e+00 2.44353190e-01 3.57453167e-01 -4.73090727e-03
3.78879495e-02 3.84554207e-01 -8.96692097e-01 -1.00405300e+00
-3.01476061e-01 -3.60368788e-01 1.54321298e-01 1.46343410e-01
-6.99550867e-01 -1.13719690e+00 2.20179155e-01 6.66338623e-01
5.57543695e-01 8.95260811e-01 5.67764580e-01 -8.22648108e-01
-1.56113608e-02 -3.74226242e-01 -3.32347542e-01 1.11960225e-01
2.26791993e-01 8.99598561e-03 -8.51670146e-01 -1.59921736e-01
3.20708841e-01 -7.03953087e-01 6.16941094e-01 -3.12468648e-01
4.47676212e-01 -9.00078773e-01 -2.87549058e-03 -3.66626590e-01
1.46737325e+00 8.91526937e-02 7.93463588e-01 6.51715815e-01
6.30253255e-01 9.00734365e-01 5.13819456e-01 8.02426636e-01
-2.08854780e-01 4.70952809e-01 3.40334415e-01 -1.84970926e-02
1.64514810e-01 -3.35275143e-01 5.35432935e-01 9.05478120e-01
-1.01411819e-01 -3.68320793e-01 -1.05309951e+00 4.34472769e-01
-1.71327209e+00 -1.45981598e+00 -6.48577631e-01 1.81954241e+00
6.17138922e-01 -7.95843750e-02 3.52507263e-01 7.24665225e-02
1.08857214e+00 4.73517120e-01 1.52626365e-01 -9.26551402e-01
-2.96227753e-01 -3.75731349e-01 2.93770522e-01 5.46293437e-01
-8.85432482e-01 9.48572874e-01 5.12819147e+00 9.88520265e-01
-1.47886741e+00 7.64794230e-01 5.56125283e-01 -2.24080801e-01
-6.31574616e-02 -5.24160802e-01 -3.91106457e-01 7.87590086e-01
7.39271522e-01 -8.55792537e-02 2.98671484e-01 4.53702390e-01
6.27387166e-01 -6.66000605e-01 -3.26238394e-01 9.43754971e-01
6.83179498e-01 -1.57734668e+00 -2.27759093e-01 -2.83722952e-02
9.91306365e-01 -1.18758045e-01 2.17886582e-01 -6.96748495e-02
-4.05321777e-01 -8.83110762e-01 9.91723537e-01 2.82677591e-01
2.26865157e-01 -7.84402311e-01 6.99299812e-01 4.75043386e-01
-6.02427840e-01 8.12525824e-02 -4.30131942e-01 -3.20316762e-01
3.54602486e-01 5.17630398e-01 -7.33798802e-01 -4.06205267e-01
5.22796214e-01 7.94866800e-01 -7.98477054e-01 8.43547165e-01
-5.53480238e-02 7.49307632e-01 -1.38825998e-01 -6.36151254e-01
5.59711933e-01 -7.97796622e-03 1.29138994e+00 1.77157450e+00
9.82047096e-02 -1.27484426e-02 4.75170799e-02 8.79501224e-01
3.70846279e-02 7.34896243e-01 -9.28208709e-01 -6.90804422e-01
1.35833964e-01 1.35131752e+00 -1.11742568e+00 -1.58452138e-01
-6.19083531e-02 1.23689783e+00 5.16123585e-02 -4.34636027e-02
-9.18528914e-01 -1.73652008e-01 -1.34605065e-01 6.29504263e-01
-3.35610032e-01 -1.67481944e-01 -2.61217449e-02 -9.26293790e-01
-2.22466111e-01 -7.47416914e-01 2.45922264e-02 -7.57060647e-01
-1.51176131e+00 7.41703272e-01 -1.99814707e-01 -1.00848293e+00
2.92325884e-01 -3.39655191e-01 -8.60495031e-01 4.78426278e-01
-6.16699934e-01 -1.24103141e+00 -2.92983890e-01 3.99528414e-01
6.18033230e-01 -4.02145058e-01 4.08730567e-01 3.32873702e-01
-9.18038487e-02 9.61672142e-02 -1.17828064e-01 9.10051167e-02
8.02963555e-01 -7.79609203e-01 -4.44600731e-01 4.86901313e-01
2.48306468e-02 5.41461289e-01 1.28205919e+00 -1.02040505e+00
-8.33306789e-01 -6.72844052e-01 1.21925044e+00 -6.15180075e-01
1.36013746e+00 -3.58788699e-01 -9.12877083e-01 3.45211178e-01
6.46576047e-01 -5.43622851e-01 9.66614664e-01 -2.68490128e-02
-3.34181309e-01 5.91193736e-01 -1.42366993e+00 6.19487107e-01
4.64216858e-01 -7.02235818e-01 -7.30321765e-01 6.35277271e-01
2.54073501e-01 1.04523800e-01 -3.89603227e-01 -7.18476832e-01
5.15360117e-01 -1.35344064e+00 4.54282552e-01 -7.86096752e-01
1.08681929e+00 -1.14167303e-01 -9.76524800e-02 -1.11839426e+00
3.59534170e-03 -7.57233024e-01 4.38259900e-01 1.37398171e+00
3.09373736e-01 -5.12133896e-01 4.68577266e-01 1.71054646e-01
1.99909717e-01 -9.38472599e-02 -6.96824491e-01 -3.96867007e-01
1.07463241e-01 -2.72022784e-01 -1.87423199e-01 1.63703144e+00
3.47627014e-01 5.11864662e-01 -1.00538480e+00 -4.39616770e-01
5.77483833e-01 -3.45547825e-01 8.65288854e-01 -1.11361241e+00
-8.15278571e-03 -2.77197480e-01 -7.33675420e-01 -1.64321676e-01
-2.60202922e-02 -6.91315234e-01 -3.63993466e-01 -1.08922803e+00
7.53644228e-01 4.14824747e-02 1.31324604e-01 2.68666685e-01
4.41310883e-01 1.04854989e+00 7.41351128e-01 5.86136460e-01
-5.37750125e-01 -2.15182155e-01 1.35498989e+00 -2.82696694e-01
-3.65243733e-01 -5.16608894e-01 -1.60531476e-01 8.79446030e-01
8.36327434e-01 -7.59567678e-01 -7.03737810e-02 4.13220108e-01
1.12802780e+00 -6.01790398e-02 5.43149412e-01 -8.14760089e-01
1.01237983e-01 -3.67026299e-01 -2.57098675e-02 -7.09706604e-01
3.01656932e-01 -6.17838800e-01 3.64940315e-01 6.69239283e-01
-3.48432899e-01 5.93759306e-02 1.76959276e-01 4.60748732e-01
-2.94395149e-01 -3.47957760e-01 1.14147878e+00 -1.50928587e-01
-3.73875052e-01 -3.76042604e-01 -1.13559484e+00 1.10473536e-01
1.22906899e+00 -3.39972287e-01 -6.44018531e-01 -9.30192888e-01
-8.26821268e-01 -4.05290753e-01 5.15423834e-01 6.77697361e-01
3.88155520e-01 -1.31765282e+00 -1.07499623e+00 -4.38200086e-01
9.53859463e-02 -1.05075240e+00 3.33521843e-01 9.52332079e-01
-7.86082566e-01 4.45758440e-02 -7.25166976e-01 -9.28840116e-02
-1.61806142e+00 3.49928528e-01 1.63764253e-01 1.34709239e-01
-7.35507488e-01 6.15498841e-01 3.87292206e-01 4.12307195e-02
-3.74829948e-01 8.21891904e-01 -4.91441935e-01 7.25318730e-01
1.12286460e+00 6.85572386e-01 -4.73159999e-01 -1.32355618e+00
-1.69432178e-01 2.82013506e-01 -1.65739521e-01 -6.45805299e-02
1.17353070e+00 -3.35476249e-01 -7.65257001e-01 1.12830853e+00
1.42226017e+00 6.69128776e-01 -3.03061277e-01 2.41610780e-01
-4.19046544e-02 -7.85823345e-01 2.07355008e-01 -8.60476494e-01
-7.91473269e-01 7.00955808e-01 3.72576952e-01 1.01484036e+00
4.11175817e-01 1.01363705e-02 1.10282493e+00 2.07815275e-01
2.91190684e-01 -1.46469283e+00 7.69803703e-01 5.49121678e-01
1.42511141e+00 -1.22493613e+00 -2.06324160e-02 -2.68107474e-01
-7.18963921e-01 1.26846862e+00 2.67110586e-01 -2.47731373e-01
6.90610290e-01 1.42034948e-01 2.51307219e-01 -4.95659083e-01
-4.06086415e-01 4.64287549e-01 3.61097306e-01 9.39495265e-02
7.48150647e-01 1.53404593e-01 -1.17582822e+00 2.67186821e-01
-2.22301632e-01 -2.48180896e-01 1.13576353e+00 8.97294402e-01
-8.91567826e-01 -5.70857346e-01 -9.69252944e-01 2.33416632e-01
-1.10263979e+00 2.05972135e-01 -1.14032197e+00 6.32470489e-01
3.60729337e-01 1.07464278e+00 9.04784277e-02 -6.85545444e-01
-5.44901192e-01 -7.23135397e-02 3.82141769e-02 -5.74847698e-01
-1.03337741e+00 -1.72327027e-01 3.83332402e-01 -2.05223516e-01
-4.81640399e-01 -4.20860350e-01 -1.06116271e+00 -1.18398678e+00
-1.64044172e-01 1.98115379e-01 8.82024050e-01 9.80150163e-01
-8.68224800e-02 -9.02307332e-02 6.29708767e-01 -6.47496164e-01
2.44824141e-01 -1.02021706e+00 -7.85447121e-01 7.13314116e-01
2.79409856e-01 -5.30028880e-01 -5.77606857e-01 5.79900295e-02] | [8.56498908996582, 10.651022911071777] |
73e5a700-cb52-4ecd-85b9-02a543b4a22e | ccpl-contrastive-coherence-preserving-loss | 2207.04808 | null | https://arxiv.org/abs/2207.04808v4 | https://arxiv.org/pdf/2207.04808v4.pdf | CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer | In this paper, we aim to devise a universally versatile style transfer method capable of performing artistic, photo-realistic, and video style transfer jointly, without seeing videos during training. Previous single-frame methods assume a strong constraint on the whole image to maintain temporal consistency, which could be violated in many cases. Instead, we make a mild and reasonable assumption that global inconsistency is dominated by local inconsistencies and devise a generic Contrastive Coherence Preserving Loss (CCPL) applied to local patches. CCPL can preserve the coherence of the content source during style transfer without degrading stylization. Moreover, it owns a neighbor-regulating mechanism, resulting in a vast reduction of local distortions and considerable visual quality improvement. Aside from its superior performance on versatile style transfer, it can be easily extended to other tasks, such as image-to-image translation. Besides, to better fuse content and style features, we propose Simple Covariance Transformation (SCT) to effectively align second-order statistics of the content feature with the style feature. Experiments demonstrate the effectiveness of the resulting model for versatile style transfer, when armed with CCPL. | ['Xiang Bai', 'Junping Du', 'Zhen Zhu', 'Zijie Wu'] | 2022-07-11 | null | null | null | null | ['video-style-transfer'] | ['computer-vision'] | [ 3.64836454e-01 -2.19783202e-01 1.63826682e-02 -2.22826228e-01
-5.25707126e-01 -6.64090037e-01 7.79891491e-01 -4.29498821e-01
-1.12815395e-01 8.40110302e-01 9.27234888e-02 2.13113260e-02
7.74923488e-02 -6.18368626e-01 -8.80514622e-01 -9.16997075e-01
6.15418017e-01 -1.34776086e-01 2.73684710e-01 -3.18496853e-01
1.76228464e-01 5.39522648e-01 -1.26907885e+00 -9.34281386e-03
1.11635530e+00 1.05857646e+00 4.22477663e-01 2.69371957e-01
4.51858342e-02 6.23854637e-01 -4.87987071e-01 -5.79850435e-01
3.22001219e-01 -8.29780996e-01 -6.47876143e-01 4.43198293e-01
5.97466111e-01 -3.37847620e-01 -2.36859143e-01 1.15437841e+00
3.84118497e-01 1.29970789e-01 6.92288697e-01 -1.21465313e+00
-7.87680209e-01 -7.13814273e-02 -7.70292878e-01 -1.66562170e-01
3.39750499e-01 2.23386273e-01 8.93054724e-01 -8.41942191e-01
8.09122086e-01 1.25699854e+00 4.56886798e-01 4.22416002e-01
-1.48232424e+00 -4.59945709e-01 2.13627979e-01 1.03451349e-01
-1.22815943e+00 -5.02411783e-01 1.14466488e+00 -2.65255183e-01
1.72388121e-01 4.25231218e-01 6.98789895e-01 1.22279692e+00
2.65733361e-01 7.90852904e-01 1.27365053e+00 -4.75818157e-01
1.30796775e-01 1.36452764e-01 -6.61499977e-01 5.82024097e-01
6.75655976e-02 -8.10849518e-02 -5.39157152e-01 1.39780551e-01
1.20180178e+00 -1.85712636e-01 -6.79727197e-01 -6.74771190e-01
-1.43425596e+00 5.68955541e-01 3.05021346e-01 4.00370210e-01
-2.29608998e-01 -3.30072828e-02 2.35092849e-01 5.25460780e-01
6.54312789e-01 4.15385872e-01 -6.22958764e-02 -9.38817337e-02
-9.18628275e-01 1.88089877e-01 3.67431492e-01 1.04662812e+00
7.70787060e-01 2.07216382e-01 -4.88274634e-01 7.42100000e-01
-6.29770532e-02 5.18232942e-01 2.48784050e-01 -1.16830683e+00
3.35800529e-01 1.52467370e-01 2.66569674e-01 -1.11060321e+00
5.78828864e-02 -4.65066701e-01 -1.01728344e+00 3.57417077e-01
4.22523558e-01 4.43245191e-03 -4.75310534e-01 2.06111932e+00
3.02500933e-01 1.14800967e-01 -3.20644289e-01 9.60873365e-01
2.26696104e-01 4.48014915e-01 -1.84868708e-01 -4.19296563e-01
1.09688520e+00 -7.47795999e-01 -8.78107607e-01 -2.26749154e-03
2.52345473e-01 -1.01160049e+00 1.36443818e+00 2.15119958e-01
-1.35598779e+00 -6.23275876e-01 -8.59874070e-01 -2.44789526e-01
2.16433734e-01 -4.06349823e-02 4.76483852e-01 3.86665344e-01
-1.14760256e+00 6.44115269e-01 -5.84152341e-01 -3.54897141e-01
2.79387414e-01 8.86297375e-02 -4.31171745e-01 -6.66461699e-03
-9.65666056e-01 8.38382483e-01 1.52873442e-01 2.24976195e-03
-4.03034925e-01 -7.66950607e-01 -7.98117280e-01 8.91873334e-03
3.75227183e-01 -1.16114128e+00 8.49276423e-01 -1.46398401e+00
-2.02646351e+00 8.01811039e-01 -3.67700696e-01 1.72103718e-01
9.14101362e-01 -2.53232569e-01 -1.42511278e-01 1.23440653e-01
6.26491681e-02 6.60776854e-01 1.15912807e+00 -1.39240682e+00
-4.66257274e-01 -9.13574174e-02 3.98388952e-02 4.32681054e-01
-6.94849670e-01 -1.07251987e-01 -6.30864859e-01 -1.17553425e+00
7.26640224e-02 -1.02591968e+00 1.40927419e-01 5.33893704e-01
-3.25410634e-01 9.17635709e-02 8.26985717e-01 -6.20037496e-01
1.00151730e+00 -2.39374042e+00 6.12427175e-01 1.15871327e-02
3.86463548e-03 2.56151527e-01 -3.94545525e-01 3.65885019e-01
1.14085399e-01 -1.99893475e-01 -3.30235988e-01 -4.06699985e-01
-2.73779511e-01 1.80167094e-01 -4.19492632e-01 4.47376907e-01
5.09474277e-01 1.09919667e+00 -8.86493921e-01 -4.44449008e-01
2.17192084e-01 5.49334049e-01 -7.83647120e-01 2.02889279e-01
-9.45754871e-02 9.58114803e-01 -5.55427909e-01 3.54841292e-01
8.12131464e-01 -2.00920701e-01 8.38821232e-02 -2.63390839e-01
-4.10036147e-02 -9.56146121e-02 -1.01358318e+00 1.98607135e+00
-5.81454515e-01 6.60691679e-01 2.12881073e-01 -8.12538624e-01
8.41511846e-01 1.35794923e-01 4.66912538e-01 -7.62119472e-01
5.47660738e-02 2.65799880e-01 -3.36722642e-01 -3.28604430e-01
3.61195982e-01 -2.63685435e-01 1.39998108e-01 1.66133046e-01
-7.42942989e-02 -3.77841145e-01 -1.03323996e-01 2.04433799e-02
6.87290668e-01 4.87351179e-01 6.56794086e-02 -4.28736329e-01
7.15450585e-01 -5.17294347e-01 5.57548285e-01 3.51107121e-01
-1.21789627e-01 1.01341987e+00 4.94531244e-01 -1.21312119e-01
-1.25391603e+00 -1.15270567e+00 -7.83283934e-02 7.79507875e-01
4.89828736e-01 -1.70123011e-01 -8.45601976e-01 -5.78158557e-01
-2.27816045e-01 5.42521775e-01 -3.77363265e-01 -2.98168391e-01
-6.44308567e-01 -2.88681507e-01 2.39410400e-01 3.13028723e-01
8.69650960e-01 -8.07658315e-01 -2.70509571e-01 2.07927212e-01
-5.70191085e-01 -1.14181232e+00 -1.06573272e+00 -3.54308069e-01
-6.92784548e-01 -6.35140061e-01 -1.12052846e+00 -7.91008890e-01
4.95077819e-01 6.12690449e-01 9.21095848e-01 3.54727618e-02
5.92170283e-02 2.04299122e-01 -2.80055940e-01 3.03884018e-02
-3.52212280e-01 -2.08887756e-01 -1.34661961e-02 4.06465173e-01
-3.21083337e-01 -9.56567943e-01 -7.05001950e-01 3.61907691e-01
-1.12541771e+00 2.99842268e-01 4.57159996e-01 1.12839341e+00
3.81304443e-01 -7.77477026e-02 3.81218910e-01 -5.37494361e-01
3.79247338e-01 3.08777159e-03 -3.53750855e-01 3.33489805e-01
-4.30314660e-01 -5.46015240e-03 7.50781834e-01 -6.38117850e-01
-1.34442341e+00 -8.80576298e-02 -7.16434717e-02 -7.26526439e-01
1.06073534e-02 7.94971511e-02 -4.48554933e-01 -3.09911638e-01
4.38375443e-01 5.12606919e-01 1.97314635e-01 -4.05076861e-01
5.31676173e-01 2.51810700e-01 6.00491166e-01 -7.52132475e-01
1.12042618e+00 5.67867756e-01 1.38874128e-01 -8.14086378e-01
-7.11944699e-01 -1.30064487e-01 -6.49108410e-01 -1.88054889e-01
7.11485445e-01 -1.02726424e+00 -5.42026818e-01 6.26779199e-01
-1.13818061e+00 -3.17852110e-01 -2.67310858e-01 3.59308720e-01
-8.07584345e-01 7.65083134e-01 -5.16595304e-01 -5.14646590e-01
-4.32700589e-02 -9.68654037e-01 1.22257555e+00 -3.36809456e-02
-2.13102385e-01 -1.07763922e+00 -5.64544313e-02 1.50681168e-01
4.80690598e-01 3.12147290e-01 8.59576106e-01 2.50275940e-01
-6.04181409e-01 2.13543847e-01 -3.39283168e-01 6.01950049e-01
3.91425103e-01 -6.60562962e-02 -9.14329827e-01 -5.35430789e-01
1.08594105e-01 -1.95926517e-01 8.16166282e-01 2.53773093e-01
1.18909121e+00 -3.79171520e-01 2.15940215e-02 8.55077982e-01
1.27090955e+00 -1.41615467e-02 8.97359669e-01 2.48121232e-01
1.01487970e+00 6.94877028e-01 5.66490591e-01 3.08078051e-01
7.26810992e-02 1.09805262e+00 2.58534461e-01 -2.93965459e-01
-4.97802258e-01 -2.31842443e-01 4.99494582e-01 7.61338770e-01
-3.94319683e-01 -3.39049071e-01 -2.14736462e-01 3.98422301e-01
-1.75892913e+00 -9.68998849e-01 4.08480205e-02 2.27742839e+00
9.95743811e-01 -1.26712695e-01 -1.89909935e-02 8.29131529e-02
6.49891019e-01 2.32040003e-01 -3.98280650e-01 -1.77630782e-01
-4.03804630e-01 1.45362709e-02 1.65791243e-01 3.67233336e-01
-8.94870102e-01 9.64039505e-01 5.87588549e+00 1.26072025e+00
-1.36434126e+00 5.34740426e-02 6.85275853e-01 -2.19472311e-02
-7.34187484e-01 -1.40577614e-01 -2.84490258e-01 6.39674962e-01
2.72665918e-01 -1.20684378e-01 5.93782842e-01 5.60005188e-01
4.15865809e-01 8.85658339e-02 -1.02429140e+00 1.03261435e+00
3.35210888e-03 -1.11965513e+00 3.10471773e-01 1.00747675e-01
1.04578185e+00 -7.22901702e-01 3.89925122e-01 -1.66860402e-01
-2.23126099e-01 -6.67938590e-01 1.03710413e+00 5.00897050e-01
1.19418216e+00 -7.83465624e-01 3.69066626e-01 1.95347205e-01
-9.90464926e-01 1.52929589e-01 -3.09130788e-01 1.17310040e-01
1.98730960e-01 7.06152737e-01 -6.23778366e-02 9.13998604e-01
4.75628257e-01 8.94362986e-01 -4.49260801e-01 7.72428513e-01
-2.74672478e-01 1.58004403e-01 -1.87188163e-02 3.76892179e-01
6.96622655e-02 -5.75984478e-01 8.23624194e-01 9.09394920e-01
6.46832407e-01 -7.69329593e-02 -9.72701907e-02 9.18948293e-01
-4.30440083e-02 3.05477649e-01 -6.25152528e-01 2.92774707e-01
2.27535650e-01 1.19578326e+00 -5.49021840e-01 -2.26796955e-01
-3.95868152e-01 1.63871634e+00 2.38397181e-01 5.66369057e-01
-8.50028396e-01 -1.99931890e-01 8.25899124e-01 1.64105371e-01
4.40801710e-01 -1.47987500e-01 -4.07384932e-01 -1.57470679e+00
4.02773231e-01 -9.06379104e-01 -1.55645385e-01 -8.03782761e-01
-1.32590675e+00 5.54637730e-01 -1.23570971e-01 -1.67939079e+00
-8.34112391e-02 -4.45094615e-01 -7.94000804e-01 7.94128835e-01
-1.58920264e+00 -1.41993654e+00 -2.78728217e-01 8.85097265e-01
5.21786332e-01 6.14853576e-02 4.90437001e-01 3.22098970e-01
-3.75555843e-01 7.06608474e-01 1.44929200e-01 -2.80486524e-01
1.23574615e+00 -1.09022748e+00 4.32469882e-02 9.88075435e-01
-8.39238614e-02 6.09478295e-01 8.35222781e-01 -4.48881716e-01
-1.28817344e+00 -1.28874874e+00 7.21214652e-01 -3.62698525e-01
4.78293687e-01 -3.26356411e-01 -9.78879809e-01 4.16793972e-01
3.42695713e-01 -9.26995557e-03 1.46035597e-01 -1.52069628e-01
-4.13883299e-01 -1.77837774e-01 -8.99093151e-01 8.53263378e-01
1.25767648e+00 -6.16699100e-01 -2.57133335e-01 1.73906058e-01
6.24909937e-01 -2.53404945e-01 -8.89273047e-01 3.89669657e-01
6.37180805e-01 -1.12570298e+00 9.27537858e-01 -2.54527539e-01
7.10449219e-01 -3.87190163e-01 -3.63967828e-02 -1.40935981e+00
-5.08794487e-01 -9.30445671e-01 1.24510571e-01 1.52481997e+00
3.85734625e-02 -5.23883104e-01 4.69649851e-01 4.27221388e-01
-1.71863899e-01 -4.16110158e-01 -8.57819676e-01 -1.03355753e+00
2.40090013e-01 -2.53205914e-02 4.02048439e-01 1.05091882e+00
-2.95354754e-01 2.20014319e-01 -8.75250220e-01 -8.69377255e-02
5.33711314e-01 1.77161187e-01 8.76283169e-01 -9.89799976e-01
-5.29559791e-01 -5.78698516e-01 -2.29234964e-01 -1.28869188e+00
1.62132114e-01 -4.95470196e-01 8.58791173e-02 -1.09720850e+00
2.24292085e-01 -2.75655776e-01 -2.36756891e-01 1.80264324e-01
-3.80853117e-01 5.98808885e-01 4.06489611e-01 3.63640606e-01
-3.97555023e-01 1.01839626e+00 2.08786178e+00 9.66267511e-02
-1.31585836e-01 -5.19437492e-02 -6.50381327e-01 5.53239107e-01
5.22758842e-01 -3.62165757e-02 -5.80127001e-01 -4.61937129e-01
-3.35748084e-02 1.25721812e-01 4.34316725e-01 -7.96274900e-01
-1.92906082e-01 -3.42031628e-01 4.19563085e-01 -5.39282933e-02
3.67806762e-01 -6.64596856e-01 3.70194227e-01 2.48146325e-01
-2.25040153e-01 -1.56860054e-01 -3.31022427e-03 6.55315280e-01
-4.50298309e-01 1.34560257e-01 1.07953322e+00 7.25062788e-02
-4.63533103e-01 3.59017223e-01 2.95819622e-02 -1.74382195e-01
1.00165021e+00 -2.49608263e-01 -1.23869188e-01 -5.52748322e-01
-3.46316248e-01 -1.58671647e-01 1.02953351e+00 5.66574097e-01
4.34303373e-01 -1.68629086e+00 -7.00841606e-01 3.19528341e-01
6.82310313e-02 -1.93509340e-01 4.01440382e-01 1.04668009e+00
-3.38452488e-01 2.11647645e-01 -4.57212090e-01 -6.55304134e-01
-1.12500525e+00 6.72895610e-01 3.83897498e-02 -7.31768161e-02
-8.22563827e-01 6.80650413e-01 9.22306001e-01 -4.81652319e-02
-9.93436668e-03 -7.77477771e-02 6.19226731e-02 -1.97614312e-01
4.98589426e-01 7.12720677e-02 -4.93227281e-02 -6.48803353e-01
-9.44875777e-02 9.22515333e-01 2.13663995e-01 -5.33090308e-02
1.17389083e+00 -5.94536424e-01 -1.24601573e-01 3.05026799e-01
1.22386801e+00 2.91273147e-01 -1.78816044e+00 -2.77321041e-01
-4.45477843e-01 -8.07827115e-01 -1.60226952e-02 -3.65634680e-01
-1.16915894e+00 7.94828713e-01 3.90772521e-01 3.86431701e-02
1.47399116e+00 -2.35954061e-01 8.74234974e-01 -4.50410098e-02
4.54907119e-01 -7.28819847e-01 3.48007441e-01 2.95613170e-01
1.22976696e+00 -1.16588438e+00 -1.80259809e-01 -6.53169692e-01
-6.93307698e-01 1.06382847e+00 4.41797078e-01 -1.05007403e-01
2.86705703e-01 -1.47384822e-01 -7.99731836e-02 3.29972833e-01
-4.59029973e-01 -1.14398852e-01 6.10892236e-01 6.08699143e-01
3.16368788e-01 -2.48630241e-01 -3.79550785e-01 -7.01491609e-02
-4.65561599e-02 -3.79623398e-02 3.75488758e-01 5.89378178e-01
-1.82362854e-01 -1.34270656e+00 -2.55490184e-01 -6.51097670e-02
-3.12636912e-01 5.34530124e-03 -1.23293325e-01 7.94484913e-01
1.11185290e-01 7.11664498e-01 -2.40555927e-02 -2.34874561e-01
3.34276438e-01 -1.32085547e-01 7.25630701e-01 -2.19908774e-01
-2.07706839e-01 6.04429245e-01 -1.55740902e-01 -7.33111143e-01
-5.30688167e-01 -6.62819982e-01 -5.75716257e-01 -6.07364476e-01
-1.43965200e-01 -2.48563915e-01 3.05731505e-01 8.48428786e-01
3.11146498e-01 4.28166628e-01 9.05735910e-01 -9.23921347e-01
-2.83461541e-01 -7.88027525e-01 -8.09829116e-01 8.74865234e-01
4.04867113e-01 -7.35232592e-01 -3.35606575e-01 3.40352356e-01] | [11.413702011108398, -0.7205803990364075] |
995ac14a-8500-49c0-93e0-8137c0688d0a | joint-task-and-data-oriented-semantic | 2302.13580 | null | https://arxiv.org/abs/2302.13580v1 | https://arxiv.org/pdf/2302.13580v1.pdf | Joint Task and Data Oriented Semantic Communications: A Deep Separate Source-channel Coding Scheme | Semantic communications are expected to accomplish various semantic tasks with relatively less spectrum resource by exploiting the semantic feature of source data. To simultaneously serve both the data transmission and semantic tasks, joint data compression and semantic analysis has become pivotal issue in semantic communications. This paper proposes a deep separate source-channel coding (DSSCC) framework for the joint task and data oriented semantic communications (JTD-SC) and utilizes the variational autoencoder approach to solve the rate-distortion problem with semantic distortion. First, by analyzing the Bayesian model of the DSSCC framework, we derive a novel rate-distortion optimization problem via the Bayesian inference approach for general data distributions and semantic tasks. Next, for a typical application of joint image transmission and classification, we combine the variational autoencoder approach with a forward adaption scheme to effectively extract image features and adaptively learn the density information of the obtained features. Finally, an iterative training algorithm is proposed to tackle the overfitting issue of deep learning models. Simulation results reveal that the proposed scheme achieves better coding gain as well as data recovery and classification performance in most scenarios, compared to the classical compression schemes and the emerging deep joint source-channel schemes. | ['Wei zhang', 'Xiaoqi Qin', 'Chuan Huang', 'Dongxu Li', 'Jianhao Huang'] | 2023-02-27 | null | null | null | null | ['data-compression'] | ['time-series'] | [ 4.66558456e-01 1.45876139e-01 -1.44085854e-01 -3.87188613e-01
-9.17798519e-01 3.13046873e-01 4.62431550e-01 -4.49852571e-02
-3.12964201e-01 6.66641057e-01 4.30221558e-01 4.42508608e-02
-5.50033748e-01 -8.16073239e-01 -5.86338639e-01 -1.09902918e+00
1.72071263e-01 3.18457246e-01 -9.61742103e-02 7.53934085e-02
7.09196553e-02 -1.06214751e-02 -1.51802826e+00 -3.83193344e-02
9.03002143e-01 1.58583045e+00 9.34051394e-01 7.07610369e-01
-2.45217949e-01 9.34104085e-01 -5.66388726e-01 -3.98460031e-01
-2.01298147e-01 -4.83405054e-01 -6.50633335e-01 3.47145021e-01
-5.65993428e-01 -4.19515401e-01 -7.64407337e-01 1.38203561e+00
5.28228283e-01 1.46643564e-01 7.99842238e-01 -1.17278671e+00
-7.54780114e-01 4.84748870e-01 -3.55117708e-01 1.43558895e-02
1.02320977e-01 -5.67566037e-01 8.30695748e-01 -5.75505018e-01
1.33074597e-01 1.35819077e+00 4.69446421e-01 4.23544109e-01
-7.22692251e-01 -6.12048745e-01 -2.72833377e-01 6.32940352e-01
-1.60157132e+00 -4.42965686e-01 1.05737340e+00 -1.04149856e-01
6.14441931e-01 -1.38321891e-01 4.58552390e-01 1.09848142e+00
-8.16472527e-03 1.09827697e+00 7.83472419e-01 -4.65878218e-01
5.13658524e-01 1.37323454e-01 -3.03008199e-01 6.03606939e-01
-1.35277603e-02 8.78609419e-02 -5.61779618e-01 -4.93806116e-02
5.40997922e-01 9.18932818e-03 -2.32620701e-01 -1.49441957e-01
-7.47037888e-01 1.10622454e+00 2.25632831e-01 2.87400067e-01
-5.14051974e-01 5.17852664e-01 3.01458687e-01 1.44407615e-01
5.15000522e-01 -5.44728398e-01 -3.63370776e-01 -2.14692011e-01
-9.65376139e-01 1.00969888e-01 8.55300903e-01 1.23235321e+00
4.39978629e-01 3.28207493e-01 1.65863018e-02 1.21618938e+00
6.26520693e-01 6.67466044e-01 4.95400608e-01 -1.05822766e+00
4.42164242e-01 -1.68715417e-01 -1.81059167e-01 -9.88301694e-01
-6.96511120e-02 -9.78612185e-01 -1.27533925e+00 -3.54507655e-01
-1.13742858e-01 1.11730639e-02 -6.56328976e-01 1.76506960e+00
1.07088730e-01 2.45799288e-01 5.51420033e-01 7.16230273e-01
6.96802020e-01 8.89590144e-01 1.45232916e-01 -5.11287272e-01
1.35382128e+00 -5.01376748e-01 -1.12467003e+00 1.26076654e-01
5.88828087e-01 -5.90849161e-01 3.43581825e-01 5.02843797e-01
-1.04434586e+00 -5.83006144e-01 -1.26344073e+00 -6.19134456e-02
-1.42193651e-02 1.97199091e-01 3.85577142e-01 6.87828600e-01
-7.76365876e-01 3.70959848e-01 -6.92850649e-01 -8.12552422e-02
8.47114980e-01 2.14893550e-01 7.86352232e-02 -3.34391326e-01
-1.33059204e+00 4.49626267e-01 7.20426559e-01 -1.72490001e-01
-1.02912402e+00 -5.52007675e-01 -8.53841722e-01 2.33448207e-01
2.78268307e-01 -6.70278370e-01 1.17349148e+00 -8.17310035e-01
-1.57164431e+00 2.97754705e-01 -1.60726398e-01 -7.82780170e-01
1.98749825e-01 -1.04529060e-01 -5.01579165e-01 5.12141585e-01
-2.00176582e-01 5.29284656e-01 1.06300104e+00 -1.09932637e+00
-7.53856242e-01 -3.65187556e-01 -3.44777465e-01 4.07530636e-01
-6.44804060e-01 -4.20121342e-01 -5.32372296e-01 -8.43667626e-01
2.41033897e-01 -4.44883317e-01 -1.29724955e-02 -3.63960378e-02
-1.40221968e-01 -1.74261883e-01 9.94843960e-01 -1.10889661e+00
1.04030073e+00 -2.35331416e+00 4.79938567e-01 1.95669517e-01
6.19680211e-02 -4.61553596e-02 1.85672939e-01 1.00257978e-01
4.27557319e-01 -4.32500064e-01 -5.97519100e-01 -5.82869768e-01
8.72708112e-02 4.75213140e-01 -7.11231977e-02 4.94208664e-01
-3.86505395e-01 6.01440668e-01 -7.07880020e-01 -6.41737640e-01
1.51193529e-01 8.55214894e-01 -7.73047388e-01 2.51832485e-01
-1.77467704e-01 4.58036721e-01 -6.82268322e-01 5.23783505e-01
9.55548644e-01 -3.16964686e-01 1.27545476e-01 -3.41103345e-01
3.89854014e-01 -2.00905889e-01 -9.21432376e-01 2.23558688e+00
-9.26213801e-01 5.20901442e-01 3.35898966e-01 -1.80246139e+00
9.20102537e-01 4.14102733e-01 6.68536901e-01 -1.03165805e+00
2.43744001e-01 4.07196820e-01 -4.73060757e-01 -5.45410812e-01
5.02527833e-01 -4.64417815e-01 -1.14765681e-01 1.15239225e-01
5.18617690e-01 -1.25180721e-01 -3.72374415e-01 2.63947606e-01
7.32246697e-01 -7.14065731e-02 1.94951296e-01 -1.25134751e-01
6.08754873e-01 -4.04115558e-01 4.98773813e-01 6.75064266e-01
9.69488453e-03 2.57980317e-01 4.89859842e-02 1.60520256e-01
-1.24655628e+00 -1.03628886e+00 -2.73588777e-01 6.36339188e-01
3.87469798e-01 -1.13819174e-01 -8.65048945e-01 -3.57460946e-01
-2.42293373e-01 1.02249980e+00 -8.93631056e-02 -5.91861665e-01
8.55111927e-02 -9.71707761e-01 4.50777262e-01 3.02722603e-01
1.10289645e+00 -5.15129685e-01 -4.95565295e-01 2.97205806e-01
-4.83876079e-01 -1.45220172e+00 -6.64865226e-03 1.60442501e-01
-6.20075524e-01 -6.32139444e-01 -9.23919439e-01 -8.24595451e-01
2.17167765e-01 2.66760439e-01 3.76922667e-01 -1.59789294e-01
-2.60730445e-01 6.80385828e-01 -7.10989773e-01 -3.08108449e-01
-6.65452182e-01 -2.05338791e-01 -2.32934192e-01 2.74824888e-01
2.49161705e-01 -8.09539616e-01 -6.38146102e-01 -6.13753088e-02
-1.11396873e+00 1.97006419e-01 7.19622791e-01 9.02451694e-01
4.46224898e-01 8.86076570e-01 8.01128149e-01 -3.44973445e-01
5.67708611e-01 -8.65393698e-01 -4.03204679e-01 7.65292495e-02
-6.07636631e-01 1.81926653e-01 4.93835181e-01 7.20508099e-02
-1.55006981e+00 -1.68306947e-01 -4.85844940e-01 -4.47678089e-01
-2.13984940e-02 6.18946075e-01 -4.08616275e-01 1.48642525e-01
1.68671533e-01 9.29572284e-01 2.24852279e-01 -6.53173506e-01
2.46504605e-01 1.15851426e+00 6.37390196e-01 -4.67067689e-01
5.85295677e-01 7.24898994e-01 6.77366480e-02 -1.06097031e+00
-8.95413458e-01 -3.94041538e-01 -2.91022539e-01 -1.65946528e-01
1.21361494e+00 -1.30169702e+00 -5.60356915e-01 6.58033252e-01
-1.18698370e+00 1.74249068e-01 -1.15587942e-01 9.26660717e-01
-9.47483480e-01 6.76554978e-01 -3.95027190e-01 -9.08104122e-01
-2.00961828e-01 -1.19334722e+00 1.11239243e+00 -8.98621138e-03
5.35168827e-01 -1.20888543e+00 -4.14873809e-01 4.76650089e-01
4.46894348e-01 -2.05372721e-01 1.08059990e+00 -5.77400744e-01
-4.82626736e-01 -1.51199952e-01 -4.27894443e-01 7.20011711e-01
-5.25548086e-02 -1.05530429e+00 -9.71174002e-01 -2.00483933e-01
5.36617756e-01 -3.86324704e-01 1.00645697e+00 5.18073678e-01
1.82717478e+00 -3.42840999e-01 -1.00703813e-01 8.29678178e-01
1.60156298e+00 3.20437759e-01 6.42744124e-01 -1.71964109e-01
5.87381423e-01 4.70311821e-01 2.92187661e-01 1.00877726e+00
6.46308839e-01 6.45441175e-01 6.15112305e-01 2.94955641e-01
-2.55567729e-01 -3.30851346e-01 1.43691689e-01 1.14577436e+00
2.44681746e-01 -4.69519228e-01 -2.78823018e-01 3.70358944e-01
-1.62793112e+00 -9.17563975e-01 8.22985247e-02 1.92966127e+00
5.95618963e-01 -1.41508549e-01 -3.68482620e-01 6.21808827e-01
7.82989383e-01 2.75277197e-01 -4.48298603e-01 -1.03336498e-01
-1.74659342e-01 2.25375012e-01 7.22442865e-01 3.13079089e-01
-9.83309984e-01 5.11802256e-01 5.61355114e+00 1.75596559e+00
-5.06557941e-01 6.12095237e-01 4.44893271e-01 2.15694666e-01
-6.16099000e-01 -1.48240430e-02 -4.63021994e-01 6.65829360e-01
1.09423125e+00 9.82198343e-02 6.30266786e-01 6.16732657e-01
1.17031932e-01 -2.36933097e-01 -6.52677059e-01 1.56411362e+00
1.77233577e-01 -1.30852854e+00 1.27577648e-01 2.61600703e-01
4.14521873e-01 -2.99762428e-01 1.02350652e-01 1.25701770e-01
1.44678593e-01 -8.18738580e-01 1.05450857e+00 7.00246692e-01
7.71629572e-01 -8.29125345e-01 5.31413674e-01 6.32569909e-01
-1.02984643e+00 -6.41122520e-01 -4.46697116e-01 1.69524193e-01
4.33562577e-01 1.02128828e+00 -2.20398977e-01 9.84938979e-01
6.00147367e-01 9.67736661e-01 9.27516744e-02 8.03610861e-01
2.45909020e-01 5.31267107e-01 -1.70199394e-01 6.92535788e-02
9.74603593e-02 -9.39181373e-02 6.26840293e-01 1.02806473e+00
8.53275597e-01 7.37030804e-02 -1.59354255e-01 8.13202679e-01
-7.49853924e-02 -1.06102780e-01 -2.58696377e-01 3.31896432e-02
5.78121245e-01 6.75594091e-01 -4.19625849e-01 -3.46912146e-01
-5.25866985e-01 1.26756489e+00 -5.76939955e-02 4.94484276e-01
-8.58647048e-01 -3.38519484e-01 2.43263796e-01 -3.90752316e-01
6.62415147e-01 -3.47320288e-01 -1.85960904e-01 -1.03521931e+00
-1.75625570e-02 -4.20217961e-01 3.22552741e-01 -6.98781252e-01
-8.17144752e-01 4.84804511e-02 2.49005198e-01 -1.15945840e+00
1.82086080e-02 -3.17678213e-01 -2.19108939e-01 5.47518849e-01
-1.88227129e+00 -1.08292890e+00 -2.25364625e-01 8.65865290e-01
8.83147717e-01 -5.50795794e-01 6.48795187e-01 6.33221149e-01
-3.03817123e-01 5.21278799e-01 6.30062282e-01 -1.83966815e-01
-1.89310446e-01 -7.46180117e-01 -4.84128118e-01 6.33645713e-01
-7.20935091e-02 -1.13025576e-01 7.47204840e-01 -3.77229393e-01
-1.47562623e+00 -1.15398967e+00 4.82075989e-01 6.40110373e-01
3.60678047e-01 -2.96293467e-01 -6.47869051e-01 1.57585919e-01
1.58863053e-01 -1.24547966e-01 7.05514908e-01 -4.68696952e-01
-7.63777718e-02 -1.50037244e-01 -1.33198035e+00 -2.12092753e-02
1.07541370e+00 -8.09458017e-01 -3.60605776e-01 4.00297672e-01
9.08890665e-01 -6.56295791e-02 -9.97907698e-01 2.69253790e-01
3.35436106e-01 -8.20021093e-01 1.01456678e+00 1.34135470e-01
4.91249532e-01 8.57254863e-02 -1.11067164e+00 -1.19600594e+00
-1.68851525e-01 -4.03686374e-01 -4.57436860e-01 1.27500236e+00
-1.67739522e-02 -3.29325050e-01 5.91218054e-01 -6.38183579e-02
-2.48460695e-01 -4.18067575e-01 -1.33522224e+00 -6.86661720e-01
-1.42140225e-01 -8.77945781e-01 5.71727514e-01 3.54130268e-01
-1.52851298e-01 -4.67157885e-02 -7.56051719e-01 1.95462123e-01
1.25832450e+00 -3.41888100e-01 2.19727963e-01 -1.06281328e+00
-6.20582104e-01 -1.96087211e-01 -5.54881215e-01 -1.53829038e+00
4.49464262e-01 -1.22326815e+00 6.08361997e-02 -1.58077812e+00
3.23424250e-01 -3.64894271e-01 -2.43413329e-01 -3.41793597e-01
3.34166676e-01 -1.58154234e-01 -1.29961586e-02 3.04871947e-01
-6.18031561e-01 1.38661718e+00 1.03752124e+00 -2.25082815e-01
2.61495233e-01 6.91357255e-02 -7.05863476e-01 4.66212571e-01
5.16982257e-01 -4.16695684e-01 -8.80265236e-01 -6.33395791e-01
6.38128966e-02 6.18566751e-01 7.12921798e-01 -1.15959358e+00
3.42569828e-01 7.86844939e-02 2.38302171e-01 -5.60418308e-01
6.62416399e-01 -1.03691196e+00 -5.20274788e-02 5.56012511e-01
-4.61107612e-01 -7.32493103e-01 -4.09699649e-01 1.33495677e+00
-4.12054181e-01 -2.86280334e-01 8.95026207e-01 -1.19192928e-01
-8.73837292e-01 3.34318012e-01 -5.41440964e-01 -2.71302521e-01
9.74367142e-01 -2.46336788e-01 2.09568396e-01 -6.87674820e-01
-9.20633674e-01 7.33195469e-02 -1.92753464e-01 2.51410723e-01
1.02750480e+00 -1.45890880e+00 -6.17198229e-01 2.39979193e-01
6.82837218e-02 3.31188478e-02 7.20115185e-01 7.96777904e-01
-2.09863186e-01 5.06458044e-01 1.60867885e-01 -7.26255238e-01
-6.04556322e-01 3.28595370e-01 1.81389809e-01 1.86142214e-02
-6.80395484e-01 8.60075414e-01 1.67505071e-01 -2.00756248e-02
4.08445925e-01 8.95348415e-02 -2.41243944e-01 -1.12680160e-01
3.25653404e-01 4.23655927e-01 1.45835346e-02 -7.50234902e-01
2.06523631e-02 2.86148816e-01 2.52979904e-01 -2.20818967e-01
1.29439676e+00 -7.13270724e-01 2.10749790e-01 2.45884806e-02
1.87253630e+00 -6.33224368e-01 -1.32264972e+00 -7.00773060e-01
-3.25728595e-01 -3.48931223e-01 7.09888279e-01 -4.66818899e-01
-1.26217043e+00 9.39821184e-01 8.17915142e-01 9.68308449e-02
1.36166179e+00 2.01560065e-01 1.14685917e+00 4.69728522e-02
4.44248110e-01 -1.50451064e+00 1.80476964e-01 2.42058724e-01
7.18775213e-01 -9.96036112e-01 -1.57641768e-01 -2.68842131e-01
-4.29434925e-01 1.01139772e+00 -1.36007518e-01 1.41000628e-01
1.25944042e+00 1.62500486e-01 -6.58455431e-01 -1.51120812e-01
-6.62542999e-01 -2.28792336e-02 -3.89646064e-03 8.85686100e-01
-7.27844536e-02 1.60997763e-01 -2.51450807e-01 7.58585036e-01
-1.12414457e-01 1.13230079e-01 3.13063741e-01 7.07117498e-01
-7.11743057e-01 -8.37231517e-01 -2.95253426e-01 4.95217741e-01
-5.21174967e-01 -6.98009655e-02 4.86290008e-01 1.62729397e-01
3.98225822e-02 1.21849084e+00 1.27030253e-01 -5.17697930e-01
-2.32963517e-01 -1.06756739e-01 4.63778675e-01 -3.87490317e-02
5.56962967e-01 3.35227042e-01 -9.63885337e-02 -3.41317564e-01
-7.41614461e-01 -6.34706676e-01 -1.33508480e+00 -1.22863010e-01
-2.54290909e-01 2.36366451e-01 1.20808804e+00 1.36160648e+00
2.17591107e-01 7.90650368e-01 8.22974205e-01 -6.04256094e-01
-7.76219010e-01 -7.16089189e-01 -9.87975359e-01 3.29111159e-01
4.28121090e-01 -7.65921712e-01 -3.88506204e-01 6.15073144e-02] | [11.29651165008545, -1.6621114015579224] |
f8281015-87ce-43ba-a182-bdd97bfafab2 | iapucp-at-semeval-2021-task-1-stacking-fine | null | null | https://aclanthology.org/2021.semeval-1.14 | https://aclanthology.org/2021.semeval-1.14.pdf | IAPUCP at SemEval-2021 Task 1: Stacking Fine-Tuned Transformers is Almost All You Need for Lexical Complexity Prediction | This paper describes our submission to SemEval-2021 Task 1: predicting the complexity score for single words. Our model leverages standard morphosyntactic and frequency-based features that proved helpful for Complex Word Identification (a related task), and combines them with predictions made by Transformer-based pre-trained models that were fine-tuned on the Shared Task data. Our submission system stacks all previous models with a LightGBM at the top. One novelty of our approach is the use of multi-task learning for fine-tuning a pre-trained model for both Lexical Complexity Prediction and Word Sense Disambiguation. Our analysis shows that all independent models achieve a good performance in the task, but that stacking them obtains a Pearson correlation of 0.7704, merely 0.018 points behind the winning submission. | ['Fernando Alva-Manchego', 'Kervy Rivas Rojas'] | 2021-08-01 | null | null | null | semeval-2021 | ['lexical-complexity-prediction', 'complex-word-identification'] | ['natural-language-processing', 'natural-language-processing'] | [-7.77217001e-02 6.33949637e-02 -3.08053851e-01 -2.50721723e-01
-1.08225536e+00 -6.82618141e-01 6.89535737e-01 5.26791632e-01
-8.38342488e-01 5.38040280e-01 5.66494524e-01 -4.99542505e-01
-1.38417512e-01 -5.57623684e-01 -3.21441174e-01 -1.00205310e-01
6.31125495e-02 7.29571164e-01 3.67217988e-01 -6.51517451e-01
5.75407624e-01 -8.06930587e-02 -1.39382136e+00 6.25732243e-01
7.55107403e-01 7.86091089e-01 4.59810108e-01 8.05082738e-01
-4.81441438e-01 6.28982365e-01 -5.11941791e-01 -6.75231874e-01
7.83431530e-02 9.65081677e-02 -1.18497968e+00 -7.08159864e-01
4.56070125e-01 3.00113857e-01 9.12105367e-02 7.18850970e-01
5.28887510e-01 1.18525483e-01 6.60833597e-01 -8.34410965e-01
-3.97177458e-01 1.11019158e+00 -2.39443406e-01 6.11756802e-01
5.21373034e-01 7.39174262e-02 1.91034341e+00 -1.07334173e+00
5.47799170e-01 1.12968433e+00 1.05683160e+00 2.67448157e-01
-1.28427482e+00 -7.76104093e-01 2.20032021e-01 4.68256533e-01
-1.41819859e+00 -5.05555034e-01 2.71620154e-01 -5.31313539e-01
2.18055153e+00 6.59401640e-02 6.35529697e-01 9.08098996e-01
2.20030546e-01 4.14692342e-01 1.16256940e+00 -7.35772669e-01
-2.17952449e-02 -1.26185447e-01 3.16400081e-01 6.59768522e-01
2.71214575e-01 -8.43744949e-02 -7.41278589e-01 -2.19959989e-01
2.87379533e-01 -5.77396274e-01 2.12543488e-01 2.14846328e-01
-1.19893765e+00 8.28679621e-01 -1.75927043e-01 7.65263081e-01
-6.62376657e-02 -1.77664682e-01 5.80453813e-01 5.85102677e-01
5.94192028e-01 1.10044825e+00 -1.23975122e+00 -4.70011801e-01
-1.04718626e+00 4.50851679e-01 9.17065799e-01 5.58436632e-01
6.66094184e-01 -2.21718892e-01 -2.91350901e-01 1.07205749e+00
6.97957203e-02 2.35274851e-01 1.01482046e+00 -4.24656332e-01
4.73284513e-01 5.13921082e-01 -2.28060022e-01 -6.29890263e-01
-8.49998951e-01 -4.50058132e-01 2.03615215e-04 -2.52337635e-01
2.87053198e-01 1.56832803e-02 -7.83989251e-01 1.72830200e+00
-2.44684845e-01 -5.90597056e-02 -2.55743980e-01 3.76776099e-01
6.14688993e-01 4.29394364e-01 5.98387003e-01 -1.59664452e-01
1.58838844e+00 -9.43699658e-01 -4.89276797e-01 -5.15857995e-01
1.19809127e+00 -1.14670241e+00 1.63530350e+00 5.37775755e-01
-1.06987178e+00 -6.08190954e-01 -9.85825896e-01 -2.45717406e-01
-6.51556015e-01 -2.19065055e-01 7.03563988e-01 6.44518375e-01
-1.09382951e+00 5.55844426e-01 -3.82496744e-01 -3.32167536e-01
-1.00322450e-02 1.92186907e-01 -2.22384825e-01 2.93986440e-01
-1.43616402e+00 1.52654600e+00 4.70946819e-01 -7.08707333e-01
-3.10576051e-01 -1.00579977e+00 -5.93521893e-01 1.25207469e-01
3.26646864e-01 -6.62535727e-01 1.40185106e+00 -5.28157413e-01
-1.40055096e+00 1.23188376e+00 -1.96233422e-01 -4.53569531e-01
-4.27583493e-02 -2.29463100e-01 -5.82025647e-01 -3.85871470e-01
3.34201068e-01 3.92469645e-01 6.37233675e-01 -5.64440250e-01
-9.51956332e-01 -6.77351803e-02 -2.61675450e-03 1.89309746e-01
-5.22270203e-01 3.16948086e-01 -2.03779250e-01 -8.57671142e-01
-2.67630160e-01 -6.19054019e-01 -8.29551369e-02 -9.02539194e-01
-2.69842148e-01 -7.24496841e-01 7.07071796e-02 -6.52140141e-01
1.81992197e+00 -1.61914563e+00 4.34796922e-02 2.72942156e-01
3.17818344e-01 2.37194151e-01 -5.68415821e-01 5.64018309e-01
-3.68657708e-01 4.03050631e-01 1.06861278e-01 -4.90214288e-01
1.91916510e-01 -2.10268900e-01 -1.00243099e-01 -7.28472546e-02
2.41069242e-01 1.27714670e+00 -8.98241162e-01 -4.21352476e-01
1.10619858e-01 -1.15191355e-01 -7.45368958e-01 5.40060438e-02
-4.16224569e-01 -1.85040414e-01 -1.84207615e-02 3.39064807e-01
3.15588892e-01 -1.81754127e-01 4.48948503e-01 -2.40516141e-01
-3.71273488e-01 1.11304080e+00 -8.73981357e-01 1.71083212e+00
-9.30380106e-01 4.14611906e-01 -3.97374362e-01 -8.95716667e-01
6.25068963e-01 8.58329609e-02 3.08903813e-01 -9.62264538e-01
2.06383821e-02 3.31969500e-01 4.31356132e-01 -4.39064860e-01
6.26480460e-01 -2.89747745e-01 -4.82988745e-01 5.16568959e-01
3.81702483e-01 -4.17934269e-01 3.13399225e-01 -1.67812202e-02
1.39103830e+00 -5.51650263e-02 7.97092497e-01 -7.63603091e-01
5.19594312e-01 -1.26338497e-01 4.08758402e-01 6.04734957e-01
5.12616821e-02 1.90965384e-01 2.18656465e-01 -5.87134778e-01
-1.26661658e+00 -9.47986305e-01 -2.19100729e-01 1.85935223e+00
-4.96527970e-01 -1.23360741e+00 -4.25281256e-01 -5.81916928e-01
4.60873991e-02 7.54873097e-01 -5.73297858e-01 -1.36176780e-01
-6.40734315e-01 -6.77135587e-01 7.60314465e-01 4.44248110e-01
-1.72068551e-01 -9.95944500e-01 -3.43307734e-01 3.82172793e-01
-4.24938351e-01 -1.26239955e+00 -4.28073972e-01 5.17036974e-01
-4.04758096e-01 -7.68210828e-01 -1.46215811e-01 -8.66624117e-01
-1.58037052e-01 -1.82806551e-02 1.73240721e+00 2.49405682e-01
-4.56799835e-01 8.50514770e-02 -4.11556482e-01 -4.92680550e-01
-3.22762817e-01 8.09561670e-01 3.13948661e-01 -6.18373752e-01
8.85480940e-01 -5.86313903e-01 -1.28095165e-01 -5.80476671e-02
-5.13693035e-01 -2.18522906e-01 4.63281482e-01 7.90124357e-01
3.01901758e-01 -2.00561613e-01 5.10036111e-01 -7.80816495e-01
8.37364495e-01 -2.76991576e-01 -4.44111437e-01 2.50227362e-01
-1.10591400e+00 2.63838053e-01 4.89271611e-01 -3.57747167e-01
-6.39282107e-01 3.57253514e-02 -4.17339772e-01 1.45243421e-01
7.01917186e-02 6.83548927e-01 7.84869399e-03 8.55036676e-02
7.12734222e-01 -1.47412181e-01 -4.15577710e-01 -6.84787631e-01
5.52952051e-01 3.73206586e-01 2.67819136e-01 -6.09276474e-01
9.19797242e-01 -2.49673918e-01 -2.90652782e-01 -7.18443453e-01
-1.33119714e+00 -6.46172047e-01 -7.82903373e-01 3.30724865e-01
8.45376790e-01 -1.03405619e+00 -7.30556130e-01 3.13730896e-01
-1.19975591e+00 -4.52329338e-01 -2.51842558e-01 3.04027110e-01
-4.73592907e-01 3.43400806e-01 -4.67027009e-01 -4.95213509e-01
-4.89399701e-01 -6.10114217e-01 9.74444091e-01 -3.37764293e-01
-9.43811595e-01 -1.31283641e+00 4.76008773e-01 3.72564077e-01
7.63267756e-01 -3.76853257e-01 1.41695523e+00 -1.15283155e+00
-4.04440761e-02 5.04363179e-02 -2.44923099e-03 9.25417617e-02
2.51436830e-02 -7.67021552e-02 -9.88797307e-01 5.62208481e-02
-1.84251159e-01 -5.34853101e-01 1.08599949e+00 3.17668229e-01
1.09271693e+00 -9.53108221e-02 -2.03528434e-01 4.41473156e-01
1.24115801e+00 -3.32140356e-01 3.36760521e-01 6.28689826e-01
6.56805277e-01 3.44259828e-01 3.97787452e-01 4.54155713e-01
8.68534148e-01 8.13856542e-01 -3.30622457e-02 1.11128472e-01
-1.73435584e-01 -1.87763736e-01 3.22093219e-01 1.21038938e+00
1.45287281e-02 -3.61223780e-02 -1.30159092e+00 5.79272389e-01
-1.53820622e+00 -9.24101293e-01 -1.59754783e-01 1.97671878e+00
1.24596918e+00 6.69839084e-01 3.94723177e-01 2.14407265e-01
4.15928751e-01 2.48616159e-01 -5.05922027e-02 -8.06543946e-01
-3.50754827e-01 9.52731490e-01 4.26870406e-01 9.66932535e-01
-9.90122974e-01 1.48876286e+00 7.50510263e+00 1.17939258e+00
-7.17408061e-01 2.94037282e-01 2.58492261e-01 -1.73755720e-01
-5.05153716e-01 8.56700465e-02 -1.00742209e+00 2.60080695e-01
1.33425319e+00 -6.48251712e-01 6.32385194e-01 6.09060466e-01
-9.39523280e-02 -4.52638939e-02 -1.19105148e+00 8.00997972e-01
9.98953655e-02 -1.11403060e+00 2.02888489e-01 -9.21711624e-02
5.58711112e-01 4.16450858e-01 -1.56424176e-02 7.25320399e-01
4.23062325e-01 -1.20175421e+00 6.35462463e-01 4.83201414e-01
7.89311051e-01 -6.25984073e-01 6.87921345e-01 2.55956799e-01
-1.37688696e+00 -9.02317837e-02 -2.03462124e-01 -5.74992061e-01
-1.77220721e-02 8.97871912e-01 -8.73280823e-01 1.07087605e-01
4.31575179e-01 4.24851835e-01 -8.13810050e-01 6.89420223e-01
-1.61162913e-01 6.87196672e-01 -2.51348823e-01 -1.41257480e-01
-1.46812303e-02 3.42447042e-01 3.74661118e-01 1.82882583e+00
8.05698782e-02 -1.38487190e-01 3.28323781e-01 5.18172383e-01
-5.57194799e-02 6.29520833e-01 -2.31591463e-01 -1.69176906e-01
6.76826656e-01 1.38400447e+00 -4.62280959e-01 -4.88351345e-01
-4.67320532e-01 7.05237627e-01 7.46051252e-01 -3.28690410e-01
-6.14962220e-01 -5.72740018e-01 8.51293445e-01 1.63468570e-02
3.92578483e-01 -4.33755904e-01 -8.43249202e-01 -1.26835608e+00
-9.74971801e-02 -8.39014828e-01 5.36270082e-01 -3.03226024e-01
-1.60049570e+00 6.47549093e-01 -9.84960720e-02 -6.56230748e-01
-4.44577515e-01 -9.56277847e-01 -6.18515730e-01 1.09678400e+00
-1.64850056e+00 -9.58284557e-01 4.73076217e-02 3.45948368e-01
6.51811600e-01 -4.05529380e-01 1.22374284e+00 1.93368822e-01
-2.06990778e-01 9.84185278e-01 -3.78564090e-01 -1.45813048e-01
9.68154073e-01 -1.53605413e+00 1.08291566e+00 5.30060410e-01
4.10871953e-01 6.92216516e-01 6.11366093e-01 -6.20133579e-01
-7.88239658e-01 -7.18480468e-01 1.87672591e+00 -9.38716829e-01
1.28779221e+00 -5.21884620e-01 -7.86360502e-01 4.56777632e-01
1.49817362e-01 -3.05712134e-01 1.03084099e+00 8.56128097e-01
-8.49290788e-01 1.86252847e-01 -6.03907824e-01 3.60008687e-01
1.29826701e+00 -9.63535011e-01 -1.16627002e+00 4.25570399e-01
9.47170854e-01 -2.32122391e-01 -1.04639983e+00 2.34885484e-01
6.67852819e-01 -8.10256600e-01 9.22956169e-01 -8.69643629e-01
5.08407891e-01 2.45204031e-01 -2.93386489e-01 -1.60891187e+00
-8.29236507e-01 -4.77465034e-01 1.35013014e-01 9.46449101e-01
9.34186280e-01 -4.88794625e-01 4.26561505e-01 2.34288037e-01
-2.20364764e-01 -6.57795966e-01 -8.35493803e-01 -8.84744048e-01
5.68097770e-01 -7.97722995e-01 5.49452960e-01 1.17695963e+00
5.37877500e-01 9.82758284e-01 8.12099725e-02 -3.56882572e-01
2.08031505e-01 -7.30762631e-02 3.13015729e-01 -1.54369533e+00
-5.18300176e-01 -8.39640141e-01 -3.17757845e-01 -7.59014010e-01
4.98797596e-01 -1.32345688e+00 -2.51388103e-01 -1.28625059e+00
3.26936096e-01 -4.35788453e-01 -5.43968201e-01 8.55019629e-01
-5.34929872e-01 1.61676824e-01 2.85391778e-01 7.73404585e-03
-6.45766854e-01 1.87581182e-01 7.17085600e-01 1.21020190e-01
-9.41118449e-02 -1.42529398e-01 -9.91936207e-01 7.10686445e-01
8.68315339e-01 -4.52947080e-01 -8.79157409e-02 -6.47321224e-01
7.15463281e-01 -5.30857801e-01 -3.03816050e-02 -8.86226237e-01
-1.93127024e-03 -1.43305451e-01 1.27461016e-01 -4.08116430e-01
2.19649374e-01 -2.65528917e-01 -4.65649486e-01 4.41114038e-01
-5.35604715e-01 5.89315116e-01 4.13369685e-01 -2.31575352e-04
1.11752875e-01 -2.50181764e-01 6.01296902e-01 -2.74636269e-01
-6.71685755e-01 -4.66136262e-02 -4.62104887e-01 5.72301388e-01
4.89558846e-01 7.26234093e-02 -2.98395842e-01 -1.28498878e-02
-7.48289287e-01 -7.07804635e-02 1.22462720e-01 7.40921497e-01
9.96836573e-02 -1.09447455e+00 -8.56834054e-01 3.53863835e-02
3.40542942e-01 -6.34304166e-01 -2.87452608e-01 4.38298136e-01
7.66946524e-02 8.47481251e-01 -1.60164058e-01 -2.01511890e-01
-1.11086321e+00 4.69476342e-01 1.34389147e-01 -6.66910768e-01
-2.81091154e-01 1.00732410e+00 -3.42460454e-01 -5.80479860e-01
-9.87369791e-02 -6.46572709e-01 -1.89284295e-01 3.15106690e-01
5.51681757e-01 2.54389554e-01 6.76941216e-01 -4.50421989e-01
-5.66614985e-01 7.14683473e-01 -2.93625623e-01 -2.55186379e-01
1.45046628e+00 -3.98014709e-02 -2.29344636e-01 7.92964339e-01
1.24775684e+00 3.76846164e-01 -3.05191725e-01 -6.07527137e-01
6.91539586e-01 -1.20028071e-01 1.91558108e-01 -1.14232171e+00
-3.65350157e-01 6.20187223e-01 2.79516190e-01 1.74352303e-01
7.93105900e-01 1.35372534e-01 8.99706185e-01 6.58864439e-01
2.39966020e-01 -1.51788163e+00 1.91032290e-01 1.31005883e+00
5.36758244e-01 -9.90821719e-01 -8.28532875e-02 -3.73377591e-01
-3.86753857e-01 1.12589669e+00 6.46619916e-01 -7.71701112e-02
6.56540573e-01 6.28336072e-01 -8.25349391e-02 -2.51782894e-01
-1.24147201e+00 -5.52277803e-01 4.80448902e-01 4.84462172e-01
9.04801130e-01 2.85783470e-01 -7.06039786e-01 1.03465545e+00
-9.08138037e-01 -3.58464807e-01 2.14286432e-01 6.29662275e-01
-7.93304324e-01 -1.39734900e+00 4.72064037e-03 7.92781711e-01
-4.95244682e-01 -9.54089522e-01 -4.10001457e-01 5.26357472e-01
1.99663028e-01 8.16070735e-01 1.84398279e-01 -7.20438182e-01
4.89659965e-01 6.73307240e-01 5.13675392e-01 -1.10984528e+00
-9.54433560e-01 -2.09319517e-01 4.39210355e-01 -7.13339031e-01
-6.47901073e-02 -7.16203272e-01 -1.02267456e+00 -1.41786784e-01
-1.94197252e-01 1.25236347e-01 6.21133626e-01 1.23830235e+00
1.77819625e-01 4.32693660e-01 5.77415347e-01 -7.31355131e-01
-6.47722185e-01 -1.18252468e+00 -2.91747153e-01 3.38595390e-01
1.36108771e-01 -5.64070165e-01 -3.36684167e-01 -1.60392642e-01] | [10.629138946533203, 10.318766593933105] |
4bb09040-eeaa-49ae-b081-23b249f81747 | fast-rule-based-decoding-revisiting-syntactic | 2212.08458 | null | https://arxiv.org/abs/2212.08458v1 | https://arxiv.org/pdf/2212.08458v1.pdf | Fast Rule-Based Decoding: Revisiting Syntactic Rules in Neural Constituency Parsing | Most recent studies on neural constituency parsing focus on encoder structures, while few developments are devoted to decoders. Previous research has demonstrated that probabilistic statistical methods based on syntactic rules are particularly effective in constituency parsing, whereas syntactic rules are not used during the training of neural models in prior work probably due to their enormous computation requirements. In this paper, we first implement a fast CKY decoding procedure harnessing GPU acceleration, based on which we further derive a syntactic rule-based (rule-constrained) CKY decoding. In the experiments, our method obtains 95.89 and 92.52 F1 on the datasets of PTB and CTB respectively, which shows significant improvements compared with previous approaches. Besides, our parser achieves strong and competitive cross-domain performance in zero-shot settings. | ['Cong Liu', 'Liyin Xiao', 'Zhicheng Wang', 'Tianyu Shi'] | 2022-12-16 | null | null | null | null | ['constituency-parsing'] | ['natural-language-processing'] | [ 3.52748126e-01 2.70033509e-01 -1.70719415e-01 -6.51249349e-01
-1.09101272e+00 -5.93308270e-01 4.79558319e-01 1.45802617e-01
-6.22665763e-01 8.34986448e-01 4.01313573e-01 -6.35411084e-01
3.51663589e-01 -8.47563088e-01 -8.19215953e-01 -5.53072393e-01
3.00647318e-01 2.11006477e-01 2.41449445e-01 -2.26793066e-01
1.43801779e-01 -1.59534052e-01 -1.32353103e+00 4.02936637e-01
5.16206443e-01 7.27306783e-01 4.11184818e-01 8.54303241e-01
-3.10106337e-01 7.74700880e-01 -5.10492504e-01 -7.52475441e-01
-7.02382550e-02 -3.39275777e-01 -7.44074225e-01 -5.17289579e-01
4.94812787e-01 -2.57608324e-01 -1.96609706e-01 9.19449508e-01
5.55136502e-01 7.26809725e-02 4.65321004e-01 -3.63736957e-01
-6.06494427e-01 1.12744808e+00 -3.06873590e-01 4.43958580e-01
9.73009467e-02 -3.45298082e-01 1.43548918e+00 -6.41072571e-01
4.97210562e-01 1.07067311e+00 6.66423619e-01 9.84563887e-01
-1.12355685e+00 -7.02106297e-01 3.45396578e-01 2.61051226e-02
-6.99004412e-01 -6.23615503e-01 6.28167689e-01 -1.92897916e-02
1.68972123e+00 9.09434408e-02 4.31201518e-01 1.35645497e+00
2.36464858e-01 9.60667670e-01 1.07198334e+00 -7.80052066e-01
3.15753847e-01 -2.06696272e-01 7.04917550e-01 7.23123312e-01
2.06000492e-01 2.21122831e-01 -7.11062253e-01 1.02827132e-01
5.51859140e-01 -8.09096336e-01 7.95059949e-02 4.21720922e-01
-8.75449419e-01 1.20516145e+00 3.21855955e-02 4.27865863e-01
-2.15509564e-01 2.99070209e-01 7.66784549e-01 5.84937893e-02
5.26932359e-01 1.31823540e-01 -6.72304273e-01 -5.62983751e-01
-7.58367777e-01 4.26438376e-02 8.63444567e-01 1.18704259e+00
2.31484905e-01 1.10241689e-01 -1.72390416e-01 1.02693820e+00
1.67295054e-01 2.21015349e-01 6.58389628e-01 -7.36972690e-01
8.97916794e-01 1.44013554e-01 -4.44932222e-01 -6.35254741e-01
-3.82515877e-01 -1.50488466e-01 -6.42105520e-01 -3.74978185e-01
3.61005247e-01 -3.37390214e-01 -1.05694199e+00 1.97262228e+00
2.57995903e-01 2.50074416e-01 5.76905668e-01 5.01060247e-01
1.15602875e+00 8.81642878e-01 6.80124283e-01 -1.55344144e-01
1.68144989e+00 -8.88360739e-01 -7.16135204e-01 -4.29522336e-01
8.59737098e-01 -6.78828239e-01 8.32607031e-01 3.47596616e-01
-1.27577627e+00 -3.95307571e-01 -1.07489705e+00 -3.67029458e-01
-1.90732747e-01 3.94257993e-01 1.08451962e+00 1.11248279e+00
-1.03657568e+00 5.46490550e-01 -1.01903486e+00 -3.15062374e-01
3.91819566e-01 3.51555020e-01 -3.16050440e-01 1.10425755e-01
-1.22931063e+00 8.82904232e-01 7.50846624e-01 -2.24983823e-02
-6.75871670e-01 -3.47061962e-01 -9.74267185e-01 1.21451721e-01
1.84295714e-01 -4.70982492e-01 1.52813244e+00 -4.94459420e-01
-1.93353891e+00 1.01253414e+00 -2.37500265e-01 -6.44385397e-01
-5.16236667e-03 -3.62319767e-01 -6.01860099e-02 -4.05982770e-02
-4.41587530e-02 8.50598872e-01 3.43521178e-01 -7.08785653e-01
-1.00990868e+00 -1.37429744e-01 1.97890550e-01 1.97501838e-01
-3.04400116e-01 3.74057591e-01 -6.02443099e-01 -5.62642574e-01
2.58298486e-01 -8.39190602e-01 -1.41611353e-01 -9.21457350e-01
-4.70442533e-01 -6.63278639e-01 2.25144699e-01 -7.29325950e-01
1.18477309e+00 -2.15854073e+00 -8.47598240e-02 -2.68669307e-01
-1.47336423e-01 3.96256477e-01 -9.80473589e-03 2.23618016e-01
8.79725348e-03 1.31993756e-01 -2.17906043e-01 -5.75615048e-01
5.64940721e-02 4.59970385e-01 -4.30953503e-01 2.08639279e-01
3.91953439e-01 8.85764182e-01 -5.74679613e-01 -6.67133808e-01
9.50849280e-02 3.82755309e-01 -7.70015299e-01 1.27763972e-01
-1.27423942e-01 8.70707631e-02 -4.37804699e-01 6.07286930e-01
5.18560469e-01 6.32301271e-02 6.95505500e-01 1.08663909e-01
-2.59445250e-01 9.51579750e-01 -5.98203599e-01 1.93227613e+00
-6.97569728e-01 5.26049912e-01 -4.97550741e-02 -1.30307579e+00
8.94993842e-01 4.97567147e-01 -1.60800681e-01 -5.64015150e-01
5.10195673e-01 1.14897028e-01 1.30488023e-01 -1.41621813e-01
7.29977667e-01 -2.89340615e-01 -4.81572509e-01 1.53366193e-01
3.90224725e-01 9.98073518e-02 2.69926786e-01 6.63050637e-02
1.18986273e+00 4.31684822e-01 4.16253388e-01 -3.37732464e-01
3.56999546e-01 2.83229083e-01 6.72030568e-01 8.28891575e-01
-2.89236426e-01 4.47054595e-01 5.44511855e-01 -2.49389246e-01
-9.39538836e-01 -9.20680225e-01 -4.47793931e-01 1.48876011e+00
-1.45401776e-01 -5.97996593e-01 -1.12152028e+00 -7.34178483e-01
-6.46788657e-01 8.55013549e-01 -5.06244063e-01 1.56678379e-01
-1.11038828e+00 -1.22168922e+00 8.56263578e-01 8.01180542e-01
5.22863090e-01 -1.29055393e+00 -7.31625319e-01 7.57200599e-01
-1.53572187e-01 -1.40313697e+00 -1.59819908e-02 7.55707145e-01
-1.17407739e+00 -8.30058634e-01 -4.14492041e-01 -1.28316689e+00
1.97059840e-01 -8.26640129e-02 1.20796037e+00 1.16868457e-02
-1.77177340e-02 -2.43783772e-01 -5.54844201e-01 -3.25328946e-01
-5.93285620e-01 4.47219074e-01 -1.94017962e-01 -6.57165527e-01
7.69518971e-01 -4.96814698e-01 -2.02633739e-01 -2.91465044e-01
-3.09511185e-01 3.66080582e-01 6.37609959e-01 1.04529691e+00
5.31781256e-01 -2.23932087e-01 5.15198052e-01 -1.20626211e+00
5.37740111e-01 -3.53351027e-01 -6.65023029e-01 2.42600620e-01
-3.73677820e-01 1.43622443e-01 5.57030082e-01 -1.68011114e-01
-1.42975986e+00 2.53435671e-01 -6.67818069e-01 3.02263618e-01
-4.57285792e-01 3.22669685e-01 -1.70743421e-01 4.64600295e-01
4.40256089e-01 2.15237871e-01 -7.17223644e-01 -5.36050677e-01
3.98586333e-01 6.49190903e-01 5.70196927e-01 -1.05030262e+00
1.39541000e-01 1.04180478e-01 -3.11618805e-01 -6.54418290e-01
-1.11374104e+00 -1.68282464e-01 -4.94088620e-01 2.84047693e-01
1.21266615e+00 -1.03594971e+00 -5.40454149e-01 1.93343535e-01
-1.46808791e+00 -1.58056006e-01 1.16116986e-01 5.76285183e-01
-5.80910563e-01 3.13272059e-01 -1.04157352e+00 -7.49546170e-01
-6.74365759e-01 -1.17578053e+00 1.12582803e+00 1.85294986e-01
-3.03588927e-01 -8.51085186e-01 2.30909482e-01 2.85365701e-01
6.25341460e-02 -6.72054887e-02 1.11238492e+00 -6.51678264e-01
-2.82056183e-01 -4.08940576e-02 -1.99130878e-01 2.96706706e-01
-3.11605215e-01 -1.99407175e-01 -1.22589457e+00 1.54596657e-01
-2.61408240e-02 -3.87150735e-01 9.19001520e-01 6.36250377e-01
7.63463557e-01 9.08206180e-02 -3.61249268e-01 6.99512720e-01
1.44149935e+00 2.62747943e-01 5.23847222e-01 4.03640419e-01
5.27267218e-01 6.93111777e-01 5.92277825e-01 1.61955655e-01
4.69312608e-01 5.68370819e-01 1.17183842e-01 2.86248803e-01
-1.12746738e-01 -3.47357601e-01 5.83717883e-01 1.21870792e+00
-1.65498868e-01 -3.08264852e-01 -7.06164479e-01 6.19259834e-01
-1.78899872e+00 -7.00620234e-01 -4.22177017e-01 1.72676110e+00
1.18488181e+00 3.77335459e-01 -3.04017603e-01 1.94623858e-01
8.55854511e-01 5.07284254e-02 -9.87181589e-02 -1.09281361e+00
-1.76032662e-01 7.86877513e-01 5.57685792e-01 3.39235663e-01
-1.51046348e+00 1.61006582e+00 6.69034195e+00 9.14716601e-01
-7.66141236e-01 4.97348040e-01 7.68423975e-01 -9.59921628e-02
4.76441607e-02 1.83672961e-02 -1.43580997e+00 3.04893613e-01
1.28646016e+00 2.84589887e-01 2.50374712e-02 1.09382331e+00
-2.41409391e-01 -1.96966141e-01 -9.35051024e-01 8.74199331e-01
-1.52372301e-01 -1.28052425e+00 -3.85292262e-01 -1.24245539e-01
5.33419430e-01 2.53024846e-01 -2.60724157e-01 7.84711540e-01
6.85239375e-01 -8.77321243e-01 8.21837783e-01 -2.54468679e-01
7.22896636e-01 -8.96604121e-01 8.21706533e-01 4.55569565e-01
-1.06319034e+00 3.02727193e-01 -7.41818011e-01 -2.36900091e-01
4.08975244e-01 5.06551087e-01 -7.98203647e-01 3.16613972e-01
6.88662827e-01 3.94763529e-01 -1.07334472e-01 2.99513727e-01
-7.56686449e-01 1.14241982e+00 -5.19822001e-01 -3.95295024e-01
5.17420530e-01 3.34344432e-02 1.65498182e-01 1.69235325e+00
2.56670088e-01 2.81760246e-01 -1.27427354e-01 4.42596376e-01
-7.57285208e-02 3.46964121e-01 -4.13855106e-01 1.49485931e-01
3.74615133e-01 1.17536438e+00 -8.15711915e-01 -5.56046784e-01
-5.00911772e-01 8.41655970e-01 8.24213207e-01 -1.97060436e-01
-1.04825628e+00 -1.37003630e-01 5.37173986e-01 -6.35467529e-01
6.72973514e-01 -3.68171215e-01 -6.43900335e-01 -1.16146827e+00
-1.38169885e-01 -6.68946683e-01 4.16469932e-01 -1.40052512e-01
-1.00878346e+00 9.64880407e-01 1.04265630e-01 -6.49099588e-01
-2.46093079e-01 -9.57155347e-01 -5.79042614e-01 7.84601271e-01
-1.63710928e+00 -1.04331219e+00 2.67128050e-01 1.92957401e-01
7.33262420e-01 -2.22186834e-01 1.17078805e+00 1.84836596e-01
-7.55423963e-01 6.72256827e-01 -8.89012218e-02 2.41451472e-01
2.22462684e-01 -1.35318637e+00 8.48993182e-01 1.16067386e+00
4.68371421e-01 6.77029908e-01 4.90796536e-01 -5.52970529e-01
-1.29919708e+00 -9.26928341e-01 1.34342229e+00 -4.98566359e-01
4.44299370e-01 -7.19119787e-01 -5.93271613e-01 5.92844069e-01
3.56730461e-01 -2.57506698e-01 8.23087513e-01 4.82949585e-01
-2.43423939e-01 5.29519975e-01 -8.97888184e-01 4.13586706e-01
1.20326996e+00 -2.18014672e-01 -9.75499749e-01 1.79157406e-01
7.97302842e-01 -6.50742412e-01 -7.19555378e-01 3.21710914e-01
5.41701019e-01 -9.52616870e-01 7.31840611e-01 -5.76656342e-01
5.86545944e-01 2.01557398e-01 -5.24311066e-01 -8.97036493e-01
-2.38992944e-01 -2.50714839e-01 3.42691178e-03 1.44219279e+00
6.57559633e-01 -4.05493975e-01 9.67249095e-01 4.42273885e-01
-3.22137475e-01 -6.23668432e-01 -1.14656591e+00 -6.30766511e-01
3.17243785e-01 -9.65961397e-01 3.68196130e-01 7.14168966e-01
-1.29355406e-02 6.42474413e-01 -3.63498390e-01 9.21994001e-02
3.18304569e-01 2.20474675e-01 4.30056006e-01 -8.26447189e-01
-6.33063197e-01 -3.52991462e-01 -1.16766311e-01 -1.20826805e+00
4.17435735e-01 -1.08812535e+00 4.85414714e-01 -1.27812421e+00
1.86738953e-01 -6.17658794e-01 -1.59516945e-01 6.53503597e-01
-3.07180196e-01 3.85452569e-01 6.42866492e-02 -1.20804265e-01
-2.44986281e-01 4.18320745e-01 7.83803523e-01 2.72312731e-01
-2.50825193e-02 -2.00812280e-01 -7.28519261e-01 7.67060637e-01
1.07576668e+00 -7.59092212e-01 -1.45020172e-01 -7.81540930e-01
1.85425356e-01 -4.46328893e-02 -2.49387249e-01 -8.42598379e-01
-9.79720354e-02 2.15699777e-01 5.55654094e-02 -5.65368652e-01
4.05755877e-01 -3.47925067e-01 -4.49512273e-01 3.23523372e-01
-2.38750771e-01 1.62175477e-01 4.07150358e-01 4.54988480e-01
-2.35066801e-01 -6.91260934e-01 6.12355828e-01 -3.02952826e-01
-8.15778613e-01 -3.37014114e-03 -5.56284726e-01 1.69346645e-01
7.16553688e-01 -3.59190144e-02 -2.36349240e-01 5.92885055e-02
-6.70266867e-01 -2.89523900e-01 -8.74238312e-02 2.58425146e-01
3.77189279e-01 -1.04663241e+00 -7.77886033e-01 1.16040617e-01
-1.35179358e-02 1.44280121e-01 7.64346197e-02 5.33267975e-01
-6.68104172e-01 7.74046600e-01 -8.68023094e-03 -4.70869690e-01
-1.28560328e+00 1.40404165e-01 -2.02596337e-01 -4.97003436e-01
-9.08633828e-01 1.35560882e+00 3.29239786e-01 -3.14824075e-01
2.15199336e-01 -5.85677445e-01 -3.78148884e-01 -1.32202342e-01
4.60720509e-01 -7.28757754e-02 2.68472314e-01 -5.80161452e-01
-4.50722665e-01 4.81607199e-01 -2.63927251e-01 -2.14002892e-01
1.45200741e+00 2.71448374e-01 2.56594330e-01 1.75474539e-01
1.00556362e+00 -4.66430187e-02 -1.04720032e+00 -3.50980163e-02
3.61311883e-01 6.79237768e-02 2.83992201e-01 -7.45730460e-01
-7.54506648e-01 1.16602671e+00 3.11279953e-01 -2.56673563e-02
1.13346100e+00 1.74334824e-01 1.16462505e+00 5.09251118e-01
3.25662822e-01 -1.14443851e+00 -7.13646054e-01 1.07817101e+00
2.72064388e-01 -1.20559847e+00 -3.20402294e-01 -6.15334928e-01
-5.74892223e-01 1.10200822e+00 4.62594420e-01 -4.30177033e-01
3.99642676e-01 6.36732221e-01 -6.44891635e-02 -4.05943170e-02
-1.12066042e+00 -1.88526422e-01 -8.09305385e-02 4.68667090e-01
8.58719170e-01 2.81908780e-01 -7.56654918e-01 1.10332239e+00
-6.22335553e-01 -3.09318602e-01 2.48495907e-01 1.07012284e+00
-5.58054328e-01 -1.53465700e+00 8.98344144e-02 9.45279896e-02
-9.63992715e-01 -8.00291836e-01 -1.02202646e-01 8.54079127e-01
5.81862368e-02 9.57548499e-01 2.94857677e-02 -2.55884200e-01
2.07199618e-01 2.30978310e-01 8.09198916e-01 -1.02631497e+00
-8.88377249e-01 1.21613331e-01 7.18942940e-01 -4.12111342e-01
-3.76144052e-01 -7.64688671e-01 -1.38068998e+00 -1.58983409e-01
-4.95562345e-01 6.50516376e-02 1.03587389e+00 1.07124972e+00
2.58151758e-02 4.45008129e-01 9.10953209e-02 -5.31114459e-01
-4.02149260e-01 -1.17617166e+00 -1.94452181e-01 2.60757916e-02
-2.82617778e-01 -5.26231945e-01 -5.24899215e-02 1.92904845e-02] | [10.413485527038574, 9.711186408996582] |
800b2a3d-b65b-4f21-8021-4f0dda164d3d | studying-very-low-resolution-recognition | 1601.04153 | null | http://arxiv.org/abs/1601.04153v2 | http://arxiv.org/pdf/1601.04153v2.pdf | Studying Very Low Resolution Recognition Using Deep Networks | Visual recognition research often assumes a sufficient resolution of the
region of interest (ROI). That is usually violated in practice, inspiring us to
explore the Very Low Resolution Recognition (VLRR) problem. Typically, the ROI
in a VLRR problem can be smaller than $16 \times 16$ pixels, and is challenging
to be recognized even by human experts. We attempt to solve the VLRR problem
using deep learning methods. Taking advantage of techniques primarily in super
resolution, domain adaptation and robust regression, we formulate a dedicated
deep learning method and demonstrate how these techniques are incorporated step
by step. Any extra complexity, when introduced, is fully justified by both
analysis and simulation results. The resulting \textit{Robust Partially Coupled
Networks} achieves feature enhancement and recognition simultaneously. It
allows for both the flexibility to combat the LR-HR domain mismatch, and the
robustness to outliers. Finally, the effectiveness of the proposed models is
evaluated on three different VLRR tasks, including face identification, digit
recognition and font recognition, all of which obtain very impressive
performances. | ['Shiyu Chang', 'Zhangyang Wang', 'Yingzhen Yang', 'Thomas S. Huang', 'Ding Liu'] | 2016-01-16 | studying-very-low-resolution-recognition-1 | http://openaccess.thecvf.com/content_cvpr_2016/html/Wang_Studying_Very_Low_CVPR_2016_paper.html | http://openaccess.thecvf.com/content_cvpr_2016/papers/Wang_Studying_Very_Low_CVPR_2016_paper.pdf | cvpr-2016-6 | ['font-recognition'] | ['computer-vision'] | [ 3.24191153e-01 -1.57573849e-01 -4.31362726e-02 -3.04754019e-01
-1.02394223e+00 -2.06585839e-01 4.26331282e-01 -4.93457258e-01
-2.67885476e-01 8.50743890e-01 -7.64007568e-02 5.97984232e-02
-3.40955615e-01 -3.35352898e-01 -6.06439412e-01 -1.03902340e+00
3.28644544e-01 -3.43181677e-02 -2.98975915e-01 -1.74862165e-02
3.13804239e-01 9.63087320e-01 -1.67818689e+00 1.92491323e-01
9.46962416e-01 1.28703928e+00 1.97581142e-01 3.90139550e-01
-4.79380339e-02 9.26532030e-01 -5.01571536e-01 -1.83019310e-01
3.08996469e-01 -2.38012642e-01 -3.74839306e-01 3.68933976e-01
5.83588719e-01 -3.33048046e-01 -3.17005187e-01 1.15494812e+00
7.55655646e-01 2.43573442e-01 6.13523662e-01 -7.68744588e-01
-9.51796889e-01 3.94092590e-01 -1.14537084e+00 3.58083427e-01
1.40569702e-01 -3.67757194e-02 7.06985235e-01 -1.37433624e+00
4.23854589e-01 1.14838493e+00 5.52391768e-01 4.48560297e-01
-1.20219684e+00 -6.79428875e-01 2.75559515e-01 2.18714789e-01
-1.82196200e+00 -8.33156049e-01 9.65832114e-01 -2.71638393e-01
5.94957411e-01 2.52138466e-01 -9.98639688e-02 1.26753724e+00
-1.19973153e-01 4.12300169e-01 1.44291902e+00 -4.66162890e-01
7.60555035e-03 3.60980242e-01 1.76343843e-01 3.30053985e-01
6.33856431e-02 1.04260042e-01 -4.60402757e-01 2.29315683e-01
1.09120774e+00 -9.46325343e-03 -4.50146079e-01 -2.13725165e-01
-8.72873664e-01 5.34447551e-01 3.59702319e-01 4.54699546e-01
-2.33756766e-01 -3.85777920e-01 5.60238911e-03 2.60436863e-01
5.33525169e-01 2.46557191e-01 -1.64565131e-01 3.54810804e-01
-1.11632419e+00 -2.44997144e-01 3.61300647e-01 8.00002158e-01
2.29494229e-01 4.98733461e-01 -7.07310289e-02 1.36029232e+00
1.86458096e-01 4.53592151e-01 4.29330170e-01 -7.17452765e-01
4.08728421e-01 3.29965085e-01 2.60935068e-01 -1.13346434e+00
-3.31068993e-01 -7.19749510e-01 -1.42401946e+00 2.24068388e-01
4.27699447e-01 1.52237471e-02 -8.16612363e-01 1.64768839e+00
2.22021595e-01 2.44254619e-01 2.49041378e-01 1.17236316e+00
1.09976327e+00 4.73754555e-01 -2.20357195e-01 -5.59460104e-01
1.24241459e+00 -6.44130349e-01 -7.78868496e-01 -1.95804685e-01
-1.52580842e-01 -7.73474813e-01 9.16613758e-01 5.17846286e-01
-1.04315102e+00 -1.02838087e+00 -1.17012084e+00 -3.14299203e-02
-9.63987708e-02 5.44846952e-01 2.58962780e-01 6.43867671e-01
-9.28863466e-01 4.83289152e-01 -3.58013570e-01 -9.03356075e-02
4.98465151e-01 5.04499674e-01 -4.13253069e-01 -2.81061679e-01
-9.56052065e-01 6.86502814e-01 2.44409274e-02 7.22385764e-01
-5.71578562e-01 -4.10962790e-01 -7.57587075e-01 -7.28061125e-02
3.69433135e-01 -6.03110082e-02 6.41048908e-01 -8.78023565e-01
-1.41568828e+00 8.70573342e-01 -2.70669699e-01 -2.46470928e-01
5.36760390e-01 -2.18355358e-01 -8.09817493e-01 1.99525476e-01
-3.26267272e-01 2.06783921e-01 1.48827744e+00 -1.23484850e+00
-2.56865561e-01 -7.10177839e-01 -2.86654115e-01 1.35942772e-01
-4.94477481e-01 3.83305490e-01 -4.21503574e-01 -7.10478008e-01
2.13768944e-01 -5.17647564e-01 -2.82489866e-01 -1.72394678e-01
-3.08115155e-01 5.83209284e-02 6.68945432e-01 -1.01706660e+00
9.88060415e-01 -2.41843581e+00 1.63004875e-01 9.08046663e-02
1.88280910e-01 3.82808805e-01 -1.57109752e-01 -2.21738935e-01
-5.18960536e-01 -7.36898556e-02 -1.48933917e-01 -1.77142978e-01
-2.33667254e-01 -3.02790463e-01 -4.66283321e-01 8.06454062e-01
3.03446561e-01 6.24889791e-01 -9.08076987e-02 -4.45484459e-01
2.35441357e-01 9.65015590e-01 -2.38093156e-02 2.58834392e-01
2.17591375e-01 6.87392533e-01 -4.33363557e-01 7.94470906e-01
1.09698272e+00 -3.60075593e-01 1.11172006e-01 -4.78998989e-01
-1.90577358e-01 -4.32219237e-01 -1.59843910e+00 1.20617414e+00
-2.50630289e-01 5.50801516e-01 4.10899520e-01 -1.17758238e+00
1.39641953e+00 2.78924614e-01 4.89863813e-01 -1.08049715e+00
6.13674223e-02 2.44142547e-01 -2.17736334e-01 -2.21333742e-01
3.81572694e-01 -1.76173300e-02 1.76878467e-01 1.81105122e-01
-1.54913172e-01 4.17355865e-01 -3.68517280e-01 -3.07814360e-01
5.32200396e-01 1.02065079e-01 3.01293045e-01 -3.83273587e-02
8.52796197e-01 -4.97520626e-01 6.54005945e-01 6.78231418e-01
-2.01222122e-01 8.30236197e-01 2.81571984e-01 -1.71049684e-01
-1.00343060e+00 -9.03222620e-01 -4.88502026e-01 7.98025906e-01
1.69238254e-01 3.81486654e-01 -6.54408813e-01 -3.94601673e-01
-2.37377837e-01 3.07010919e-01 -4.48095053e-01 -1.22210965e-01
-8.10482681e-01 -8.90136242e-01 3.89189363e-01 5.75322747e-01
7.60569394e-01 -9.90527630e-01 -2.94295669e-01 -5.80597296e-02
-3.43023688e-02 -1.47834635e+00 -2.85268873e-01 4.15287958e-03
-6.88204944e-01 -8.39582384e-01 -1.09479105e+00 -8.23948562e-01
6.56422377e-01 4.50642228e-01 7.77055740e-01 -1.40787989e-01
-5.68920553e-01 2.70604938e-01 -1.58445567e-01 1.71553031e-01
-8.80823433e-02 -1.66495010e-01 3.45252246e-01 4.05399084e-01
3.28403562e-01 -4.95404005e-01 -5.15182078e-01 5.19463003e-01
-6.33041143e-01 -2.86501676e-01 8.66445661e-01 1.08382034e+00
8.44712734e-01 3.69270653e-01 8.47349942e-01 -4.79041696e-01
4.72834617e-01 2.90450780e-03 -7.85242975e-01 3.49457681e-01
-4.83455628e-01 -1.29333079e-01 7.43902683e-01 -6.17297292e-01
-1.35544217e+00 4.80673276e-02 -1.14477739e-01 -6.77408636e-01
-3.31322461e-01 2.47862339e-01 -6.12191737e-01 -3.95468771e-01
5.44041991e-01 3.61671478e-01 -1.84982419e-02 -7.19681263e-01
3.20516646e-01 8.87339950e-01 6.78039968e-01 -3.51045042e-01
9.38921571e-01 3.11690420e-01 -1.08212911e-01 -1.25193822e+00
-7.46283650e-01 -1.65979102e-01 -7.42668867e-01 -1.86254099e-01
6.42243862e-01 -1.20080268e+00 -6.91182375e-01 5.28036952e-01
-8.65109563e-01 4.45348807e-02 -2.15282202e-01 4.22533005e-01
-3.98116767e-01 5.03309250e-01 -4.75495338e-01 -1.02337205e+00
-2.74899930e-01 -1.18081307e+00 7.29699910e-01 4.60335165e-01
3.79376948e-01 -6.76597536e-01 -4.40069348e-01 5.55063605e-01
4.96517122e-01 2.27838710e-01 6.42609954e-01 -5.14295697e-01
-5.36615908e-01 -1.98868021e-01 -7.78332770e-01 5.31611383e-01
1.61970332e-01 -2.22782508e-01 -1.34432352e+00 -6.14547968e-01
2.58928984e-01 -3.39262187e-01 9.66456711e-01 4.77968335e-01
1.43754923e+00 -9.70555991e-02 -4.66947258e-02 7.06412673e-01
1.49332142e+00 1.39594361e-01 7.59844720e-01 1.15187550e-02
7.98381448e-01 7.91593432e-01 7.98943758e-01 4.87558961e-01
7.28183761e-02 9.63312924e-01 2.62610346e-01 -4.59170669e-01
-2.05231547e-01 1.20255694e-01 3.54099989e-01 6.21481955e-01
-2.53741086e-01 7.99287260e-02 -5.94081223e-01 3.12638164e-01
-1.62220621e+00 -9.33213949e-01 1.90175951e-01 2.23032880e+00
6.34634018e-01 -1.71238184e-01 -1.46765664e-01 2.56156236e-01
1.01764798e+00 3.84571373e-01 -9.31306541e-01 -2.71886617e-01
-4.22786236e-01 2.48583630e-01 3.21622372e-01 2.56017238e-01
-1.12155962e+00 9.48840678e-01 5.98865938e+00 9.57963288e-01
-1.23498821e+00 -8.72305557e-02 9.13420498e-01 -1.90933060e-03
1.30329296e-01 -5.23028314e-01 -9.56309736e-01 7.85631761e-02
6.96817994e-01 2.53949255e-01 6.33983314e-01 7.12766230e-01
3.39190215e-01 1.40182301e-01 -9.89116490e-01 1.50797796e+00
3.83866996e-01 -9.05648887e-01 -1.16615221e-01 1.52585104e-01
4.95684087e-01 -4.66437727e-01 6.58797085e-01 3.82535487e-01
-1.23219773e-01 -1.68391025e+00 3.71016920e-01 7.18446553e-01
1.25596333e+00 -1.04366577e+00 4.88215923e-01 3.33038986e-01
-1.28353202e+00 -3.81639034e-01 -6.82425559e-01 4.13186759e-01
-2.46225327e-01 6.25822604e-01 -3.22517246e-01 6.41944706e-01
6.75979495e-01 6.31999493e-01 -5.99116921e-01 7.34911680e-01
9.83222052e-02 1.09772868e-01 -1.16036851e-02 4.65825588e-01
-3.25486630e-01 -2.94997483e-01 6.02869928e-01 1.02959871e+00
4.55919385e-01 1.29366904e-01 -8.13120604e-03 1.12780130e+00
-2.02232033e-01 1.54157788e-01 -4.86222714e-01 -5.48545867e-02
3.75515252e-01 1.32967412e+00 -5.33888340e-01 1.00786455e-01
-3.60860556e-01 9.32856977e-01 3.31726640e-01 5.89967251e-01
-9.23670590e-01 -4.19199854e-01 5.72784185e-01 -3.43206786e-02
6.62685275e-01 -2.73956120e-01 -3.47045094e-01 -1.31950748e+00
3.72392058e-01 -1.27383292e+00 2.43289709e-01 -6.17419302e-01
-1.23363829e+00 8.29722106e-01 -2.73424774e-01 -1.35256803e+00
-1.60085022e-01 -5.67519009e-01 -1.17415026e-01 1.03291440e+00
-1.81606233e+00 -1.02093208e+00 -4.34930354e-01 8.84664237e-01
5.82488596e-01 -4.16592628e-01 5.40996850e-01 5.54526985e-01
-1.17308187e+00 1.06448221e+00 1.30814210e-01 1.30700007e-01
7.63211071e-01 -7.90533900e-01 -5.94827421e-02 1.04911184e+00
4.67390269e-02 6.13215506e-01 6.35493875e-01 -2.56895036e-01
-1.52150607e+00 -1.12980437e+00 3.82358998e-01 -2.07736537e-01
2.56269693e-01 -3.14779431e-01 -1.19616616e+00 2.77388901e-01
-1.28275082e-01 4.07715648e-01 3.72132301e-01 -7.80268908e-02
-5.87797761e-01 -5.13901412e-01 -1.39811516e+00 3.93474847e-01
9.45052207e-01 -6.48803711e-01 -4.31712985e-01 1.44405141e-01
4.99447793e-01 -2.48207122e-01 -1.09147501e+00 6.57875121e-01
5.05306542e-01 -1.04107165e+00 1.42639482e+00 -3.54723662e-01
1.79914579e-01 -2.82017380e-01 -4.63075548e-01 -9.31953967e-01
-2.19831392e-01 -3.08228046e-01 -3.16605985e-01 1.57797050e+00
2.73265809e-01 -5.17168880e-01 5.78193605e-01 6.56599581e-01
3.86076242e-01 -3.85792077e-01 -1.03444135e+00 -7.79414535e-01
-6.93117455e-02 -2.77540475e-01 4.06448156e-01 1.04033995e+00
-4.27178562e-01 1.66394398e-01 -8.72743368e-01 5.13667464e-01
9.76005375e-01 3.42790365e-01 5.04731119e-01 -1.24873793e+00
-3.33399266e-01 -2.87694693e-01 -7.27703869e-02 -1.07674420e+00
1.89590782e-01 -3.41647565e-01 1.81836169e-02 -1.24009609e+00
1.84246123e-01 -3.03845733e-01 -6.21013939e-01 1.42762914e-01
-1.44552719e-02 4.66688931e-01 1.29932031e-01 2.87942201e-01
-4.98518407e-01 6.32499516e-01 1.20306337e+00 -8.58761743e-02
-3.44317108e-01 4.55174297e-02 -9.51813340e-01 6.60649180e-01
6.08649969e-01 2.27826531e-03 -1.47307739e-01 -2.16842055e-01
-2.77898610e-01 4.13083404e-01 4.24200565e-01 -9.18478131e-01
1.73593625e-01 -1.01930954e-01 9.51291502e-01 -4.77043390e-01
7.56296456e-01 -9.00835514e-01 -6.87853172e-02 -1.68117881e-01
-4.17388797e-01 -3.59913677e-01 8.87829959e-02 6.16013825e-01
-3.94616514e-01 8.63599181e-02 1.36925864e+00 -7.80425593e-02
-7.41082370e-01 2.91656911e-01 6.08711429e-02 -2.64889896e-01
8.86805117e-01 -4.47958499e-01 -2.21815258e-01 -2.48607010e-01
-8.22928667e-01 -1.62127957e-01 1.29298717e-01 4.36352640e-01
1.08297169e+00 -1.22050869e+00 -8.14776957e-01 4.49824244e-01
-2.19859444e-02 -1.88278988e-01 6.36314213e-01 1.06856942e+00
1.07153609e-01 4.44497168e-01 -1.44001037e-01 -5.47120512e-01
-1.54900765e+00 7.49317646e-01 4.44598496e-01 -1.34189442e-01
-8.12502027e-01 7.58961737e-01 1.66723475e-01 -2.35515535e-01
5.35056233e-01 8.76026750e-02 -8.31591129e-01 1.37600139e-01
8.66050780e-01 3.55899900e-01 -4.56717797e-02 -9.05213177e-01
-3.33315820e-01 9.80260551e-01 -3.85748446e-01 5.35181277e-02
1.40835297e+00 -4.65445995e-01 2.05107667e-02 7.99508840e-02
9.57556248e-01 1.16904147e-01 -1.46559536e+00 -5.27685285e-01
-3.70799489e-02 -6.34471953e-01 1.80769533e-01 -6.46623015e-01
-1.25983095e+00 9.68774319e-01 1.05091763e+00 -4.84468136e-03
1.32217395e+00 -3.01299244e-01 4.56242144e-01 2.42402494e-01
3.91207188e-01 -1.09249699e+00 1.62588164e-01 2.79801309e-01
1.12918818e+00 -1.35853291e+00 4.60249186e-02 -3.95015270e-01
-7.21361518e-01 1.07870471e+00 7.16430724e-01 -7.71200955e-02
4.64796752e-01 2.43368223e-01 -5.11476137e-02 2.28200048e-01
-4.60501581e-01 -1.65617600e-01 4.16138142e-01 6.60018265e-01
3.87983173e-01 -2.77094245e-01 1.92672946e-02 7.59336591e-01
2.20763937e-01 -2.36601651e-01 3.04597020e-01 4.29094255e-01
-4.74928081e-01 -8.10354054e-01 -7.48906434e-01 1.98223174e-01
-5.81625998e-01 3.46952002e-04 -3.05571198e-01 7.72134483e-01
-1.29277945e-01 1.09385574e+00 -1.18302919e-01 -2.94504851e-01
3.30053896e-01 -1.46178886e-01 4.75582212e-01 -7.38311186e-02
-2.08672002e-01 3.65244150e-01 -2.17322037e-01 -4.76736277e-01
-3.56265754e-01 -5.82497597e-01 -9.48757946e-01 -7.92509839e-02
-3.69727910e-01 -1.47111788e-01 5.84248066e-01 8.31370831e-01
2.61912465e-01 6.03505194e-01 1.02636123e+00 -6.01861954e-01
-7.49828398e-01 -9.06772852e-01 -8.66382599e-01 3.31285223e-02
5.52539349e-01 -6.42088711e-01 -4.31638747e-01 -2.37559751e-01] | [12.888928413391113, 0.11093834042549133] |
cd531114-c346-4721-a0a7-68f3865acbf8 | learning-correspondence-from-the-cycle | 1903.07593 | null | http://arxiv.org/abs/1903.07593v2 | http://arxiv.org/pdf/1903.07593v2.pdf | Learning Correspondence from the Cycle-Consistency of Time | We introduce a self-supervised method for learning visual correspondence from
unlabeled video. The main idea is to use cycle-consistency in time as free
supervisory signal for learning visual representations from scratch. At
training time, our model learns a feature map representation to be useful for
performing cycle-consistent tracking. At test time, we use the acquired
representation to find nearest neighbors across space and time. We demonstrate
the generalizability of the representation -- without finetuning -- across a
range of visual correspondence tasks, including video object segmentation,
keypoint tracking, and optical flow. Our approach outperforms previous
self-supervised methods and performs competitively with strongly supervised
methods. | ['Xiaolong Wang', 'Alexei A. Efros', 'Allan Jabri'] | 2019-03-18 | learning-correspondence-from-the-cycle-1 | http://openaccess.thecvf.com/content_CVPR_2019/html/Wang_Learning_Correspondence_From_the_Cycle-Consistency_of_Time_CVPR_2019_paper.html | http://openaccess.thecvf.com/content_CVPR_2019/papers/Wang_Learning_Correspondence_From_the_Cycle-Consistency_of_Time_CVPR_2019_paper.pdf | cvpr-2019-6 | ['unsupervised-video-object-segmentation'] | ['computer-vision'] | [-1.61432996e-01 -3.08454245e-01 -8.49438429e-01 -4.18356538e-01
-5.50071716e-01 -8.09476852e-01 5.71517050e-01 -6.28597960e-02
-2.85402298e-01 6.30063951e-01 1.83175638e-01 5.34206219e-02
8.27144533e-02 -4.07743365e-01 -9.55156922e-01 -3.55219841e-01
-2.66001880e-01 3.72739017e-01 4.56681460e-01 1.46484882e-01
3.42101991e-01 6.90162361e-01 -1.42770422e+00 8.38684291e-03
4.66484189e-01 6.22532547e-01 1.31147683e-01 8.08692098e-01
8.22097659e-02 9.45698678e-01 -2.17752263e-01 2.46136144e-01
5.82817316e-01 -6.04488850e-01 -9.80629802e-01 3.58754367e-01
1.01162624e+00 -4.18906152e-01 -8.71508002e-01 8.67784679e-01
-5.44292759e-03 4.81393695e-01 7.62954235e-01 -1.35606074e+00
-6.04756951e-01 1.30876496e-01 -3.26747686e-01 6.04909897e-01
4.30233777e-01 3.37030768e-01 1.03155041e+00 -7.75643051e-01
1.14961600e+00 1.06293738e+00 7.40614474e-01 7.93659866e-01
-1.33973038e+00 -3.62327248e-01 2.75967628e-01 1.25994340e-01
-1.10828400e+00 -5.78655839e-01 7.48979747e-01 -7.65428901e-01
8.40221345e-01 -1.82165071e-01 8.76978934e-01 7.60408640e-01
1.31362200e-01 8.43574584e-01 9.57857907e-01 -3.38386834e-01
2.50555694e-01 -1.75223589e-01 1.12711504e-01 1.22904980e+00
1.23638012e-01 7.39388287e-01 -6.67244017e-01 9.38724820e-03
1.44518244e+00 1.31508440e-01 -3.00747722e-01 -8.55195284e-01
-1.56234968e+00 6.15645468e-01 6.08090520e-01 2.27985188e-01
-7.29866931e-03 6.69685185e-01 3.19413930e-01 5.91572940e-01
2.67315924e-01 4.89063352e-01 -4.00434017e-01 -1.47249460e-01
-1.08664441e+00 -6.87684715e-02 6.91848516e-01 1.23974168e+00
1.05604637e+00 2.89843231e-01 -3.16581100e-01 2.44688079e-01
2.95382410e-01 3.95885438e-01 6.39074445e-01 -1.53004110e+00
6.96182996e-02 2.57666796e-01 1.16052181e-01 -7.39500821e-01
-1.69470355e-01 -2.09586918e-01 -4.23231721e-01 5.06182194e-01
5.85080564e-01 7.88905472e-02 -1.03059185e+00 1.77351236e+00
2.47543111e-01 8.36490095e-01 1.59815827e-03 1.00045931e+00
6.60013616e-01 4.90272164e-01 -8.30697492e-02 -3.41356248e-01
5.73402405e-01 -1.24889827e+00 -4.80165482e-01 -1.27033055e-01
5.65964758e-01 -5.67381442e-01 8.16226959e-01 5.98081388e-02
-1.08568299e+00 -9.61502671e-01 -8.81391346e-01 6.00257935e-03
-5.12097664e-02 -6.23953529e-02 7.35786200e-01 2.49270394e-01
-1.33449340e+00 1.08367789e+00 -1.03960776e+00 -5.28712332e-01
5.28726459e-01 3.91853124e-01 -5.22766054e-01 9.56663713e-02
-6.84639513e-01 7.15256333e-01 2.42014065e-01 -1.87151909e-01
-1.17282867e+00 -8.35225642e-01 -1.06770170e+00 -3.31633747e-01
1.05636284e-01 -8.34318340e-01 1.19108593e+00 -9.03268218e-01
-1.54757488e+00 1.07082498e+00 -5.19569933e-01 -5.73324084e-01
6.39967859e-01 -2.60802597e-01 3.38521935e-02 5.37748754e-01
4.16653156e-01 1.09648776e+00 1.27372932e+00 -1.24496913e+00
-5.98029613e-01 -4.58441637e-02 -7.19085038e-02 1.82093516e-01
-3.90657373e-02 -3.06115776e-01 -5.97939372e-01 -7.44998693e-01
2.44916648e-01 -1.10713685e+00 -3.08224231e-01 5.39507866e-01
-1.30580068e-01 -8.28251690e-02 1.02963102e+00 -2.27624252e-01
6.22785211e-01 -2.08606458e+00 1.54006809e-01 1.95431098e-01
4.17952448e-01 2.04842947e-02 -1.81284145e-01 -2.59485524e-02
-1.50974393e-01 -2.76672214e-01 9.38116387e-02 -3.59519899e-01
-3.79947811e-01 3.96176964e-01 -3.77174139e-01 9.18380380e-01
1.65603489e-01 1.41006970e+00 -1.39434373e+00 -7.70103276e-01
5.39921761e-01 1.46171734e-01 -5.90274274e-01 5.58892369e-01
-4.49389994e-01 9.84346569e-01 -4.25114810e-01 6.62810326e-01
1.33661628e-01 -5.89664519e-01 -1.55661672e-01 -2.36564398e-01
2.78093852e-02 -5.80654573e-03 -1.04620790e+00 2.15639019e+00
-1.91407427e-01 1.05386817e+00 -3.71860355e-01 -1.02068102e+00
8.06730330e-01 -5.17016612e-02 8.02180409e-01 -4.93940085e-01
-5.92038222e-02 -8.76673013e-02 -3.38478118e-01 -3.69913191e-01
1.30908221e-01 2.28012517e-01 2.86637038e-01 6.52037263e-01
4.22724277e-01 -2.00842381e-01 1.82861641e-01 1.86526224e-01
9.07802761e-01 7.07426965e-01 2.85603940e-01 -2.62960792e-01
4.42068100e-01 3.38837057e-01 5.52053273e-01 7.49386370e-01
-6.22011602e-01 6.77572250e-01 3.42740566e-02 -6.56455040e-01
-8.94922495e-01 -1.20759451e+00 9.44889858e-02 1.12551975e+00
5.56768775e-01 -3.09569150e-01 -3.73215765e-01 -9.18073952e-01
1.70847952e-01 -9.09311622e-02 -6.62124574e-01 -3.58841680e-02
-7.04348624e-01 3.58100921e-01 2.17713505e-01 9.17551816e-01
3.98513228e-01 -9.47326005e-01 -7.72392929e-01 1.31559610e-01
1.35594502e-01 -1.35137093e+00 -1.01568699e+00 2.60363817e-01
-1.30851805e+00 -1.27566946e+00 -6.49994910e-01 -1.08003926e+00
9.33159411e-01 6.28208220e-01 1.08102512e+00 2.69178033e-01
-4.12922829e-01 1.10753012e+00 -3.71961296e-02 3.48856747e-01
-3.87188971e-01 -2.99869806e-01 2.08727390e-01 -2.33528540e-01
-1.92387793e-02 -3.51406395e-01 -6.14414155e-01 4.96073335e-01
-4.16781217e-01 -3.53284925e-01 1.36689380e-01 8.49324286e-01
9.38647866e-01 -5.32825291e-01 1.30623013e-01 -7.32851982e-01
7.35522509e-02 -9.81819481e-02 -8.05892587e-01 1.90593809e-01
-5.33505321e-01 2.39658475e-01 5.64182281e-01 -5.66097081e-01
-5.69730699e-01 5.54596901e-01 5.03228009e-01 -1.24671054e+00
-2.11525410e-01 -1.46364972e-01 3.57566297e-01 -5.33667684e-01
7.30876505e-01 3.71409953e-01 3.24749380e-01 6.00583560e-04
7.90794909e-01 -2.14745440e-02 9.43245471e-01 -6.77936554e-01
1.17216980e+00 8.15987766e-01 1.06194064e-01 -6.43169343e-01
-8.92994225e-01 -9.08723176e-01 -1.18465817e+00 -4.07488704e-01
8.08785439e-01 -1.03079152e+00 -5.85954130e-01 1.92826018e-01
-1.09007192e+00 -6.83721125e-01 -6.94873691e-01 8.37223351e-01
-1.08573329e+00 4.68403459e-01 -5.93349457e-01 -2.58204788e-01
1.69057418e-02 -9.25408959e-01 9.34135318e-01 3.14845443e-01
-3.75793844e-01 -1.59372401e+00 4.56681222e-01 6.60994649e-03
1.69873625e-01 2.44828478e-01 1.05582289e-01 -4.82808739e-01
-9.61817443e-01 6.31786659e-02 -1.82723433e-01 2.13516116e-01
4.21407759e-01 5.47983423e-02 -9.20781314e-01 -5.57485282e-01
-3.57196450e-01 -5.03423333e-01 8.83557439e-01 6.59436584e-01
1.06241906e+00 -8.05381089e-02 -5.90896368e-01 9.38517988e-01
1.26931071e+00 -1.64703369e-01 2.83888161e-01 2.34630644e-01
8.45415235e-01 3.92110854e-01 7.19454169e-01 1.55825406e-01
2.06562594e-01 6.02454245e-01 2.80440181e-01 -1.38671920e-01
-4.25407976e-01 -4.34881210e-01 3.68952453e-01 6.63947105e-01
-1.39665648e-01 4.35751975e-01 -6.23676062e-01 6.13330483e-01
-1.98732698e+00 -1.19001639e+00 2.78199881e-01 2.12754107e+00
7.41024673e-01 2.26792186e-01 3.57001454e-01 -2.16244578e-01
6.97328031e-01 2.34407350e-01 -6.40381038e-01 -5.47676086e-02
1.42563045e-01 8.58672932e-02 5.89276433e-01 6.36032879e-01
-1.34643865e+00 1.29343593e+00 7.77374220e+00 6.65104911e-02
-1.21112657e+00 -2.75460687e-02 4.57292080e-01 1.13652393e-01
-1.50608458e-02 2.52346545e-01 -7.32235312e-01 1.81572244e-01
4.68934000e-01 -2.32925758e-01 3.98787320e-01 9.39739585e-01
1.42980248e-01 1.55055612e-01 -1.85694456e+00 1.10661352e+00
2.43258536e-01 -1.81568158e+00 -5.19017242e-02 -2.88289249e-01
1.08006334e+00 1.21862710e-01 -5.21846339e-02 2.86878496e-02
4.43717659e-01 -8.77559900e-01 4.57991868e-01 4.81967896e-01
8.77202332e-01 -1.33378133e-01 4.54056188e-02 3.97623256e-02
-1.48123693e+00 1.15065292e-01 -3.19519609e-01 4.98886332e-02
2.45686155e-02 1.20720997e-01 -5.97058177e-01 1.07179992e-01
5.46140075e-01 1.42705929e+00 -4.65855718e-01 1.27248394e+00
-1.83125883e-01 3.75972092e-01 -2.11282894e-01 2.98668653e-01
3.49708050e-01 -1.34457514e-01 5.30492604e-01 1.36422038e+00
-1.35913834e-01 -5.48750497e-02 6.61580741e-01 8.68477225e-01
-4.00643758e-02 -1.90099478e-01 -9.29949760e-01 1.43163115e-01
5.64270914e-01 9.66956437e-01 -8.76845300e-01 -4.40026700e-01
-3.51794213e-01 1.19043720e+00 3.21602613e-01 5.52269459e-01
-6.51132941e-01 -5.36725782e-02 4.81312692e-01 3.09154540e-02
6.04496419e-01 -5.88548958e-01 -4.52281907e-02 -1.30993128e+00
-2.04521328e-01 -3.98367971e-01 4.23039794e-01 -6.87543869e-01
-1.16155207e+00 2.76105881e-01 6.26693293e-02 -1.81169379e+00
-7.34642982e-01 -4.47392046e-01 -9.21269238e-01 4.11990702e-01
-1.71321261e+00 -1.05668652e+00 -5.36363065e-01 1.06035006e+00
7.69330502e-01 -3.63104612e-01 5.54917097e-01 -1.59015909e-01
-1.33871228e-01 5.01296401e-01 2.30862679e-05 5.01456380e-01
8.83200586e-01 -1.33358836e+00 3.71650815e-01 8.57773364e-01
7.98505962e-01 7.29891658e-01 4.07622278e-01 -5.99514127e-01
-1.52546728e+00 -1.32501364e+00 4.57566559e-01 -6.04827285e-01
7.38896787e-01 2.33521201e-02 -8.63366246e-01 9.40576375e-01
8.94344300e-02 1.00851536e+00 3.46028268e-01 -2.27480710e-01
-6.72480404e-01 -1.52603909e-01 -9.40196216e-01 3.77715141e-01
1.36475909e+00 -7.74525702e-01 -8.36941123e-01 4.49899316e-01
7.05889106e-01 -6.75273895e-01 -8.22876215e-01 8.95311311e-02
4.02293622e-01 -7.46455371e-01 1.16010845e+00 -8.70767236e-01
1.17946036e-01 -3.98928732e-01 8.15674886e-02 -1.23733103e+00
-4.05538738e-01 -1.16712844e+00 -5.35772681e-01 6.64947510e-01
6.50305301e-02 -3.35415304e-01 1.12993002e+00 2.39034355e-01
9.61849466e-02 -2.82311589e-01 -7.50865102e-01 -1.09408510e+00
-1.12525068e-01 -1.37218431e-01 -6.73983991e-02 1.02934790e+00
-8.76077786e-02 1.11823201e-01 -1.45922840e-01 1.02636620e-01
1.13358712e+00 5.37556231e-01 9.47659850e-01 -1.22235525e+00
-4.14873153e-01 -2.84425676e-01 -8.31564546e-01 -1.67605865e+00
5.81238568e-01 -8.91563535e-01 8.69114846e-02 -1.25166082e+00
3.33776847e-02 -3.00493628e-01 -2.96515167e-01 5.50447524e-01
5.46853133e-02 3.64841908e-01 1.75272077e-01 7.55634487e-01
-1.04836118e+00 2.19449461e-01 1.52842665e+00 -1.59781113e-01
-4.39332217e-01 3.46947275e-02 -1.62134811e-01 6.41835153e-01
6.83038712e-01 -4.23536271e-01 -5.58774769e-01 -3.66068900e-01
-4.99592483e-01 1.69051945e-01 6.44000769e-01 -1.00938332e+00
5.29235959e-01 -3.62525523e-01 5.48522830e-01 -4.07967418e-01
6.53024539e-02 -6.83183670e-01 -3.84789199e-01 6.10760689e-01
-5.46519220e-01 1.59560814e-01 1.01391755e-01 9.30330038e-01
-2.33826548e-01 -4.34497744e-02 8.28507185e-01 -1.88273609e-01
-1.30066359e+00 6.35893047e-01 -1.01984039e-01 5.13251960e-01
1.14826870e+00 -6.73830986e-01 -1.62521794e-01 -4.41441119e-01
-9.77388978e-01 2.85401851e-01 6.73784137e-01 4.54509646e-01
8.65083277e-01 -1.40277171e+00 -4.59682494e-01 3.29529434e-01
2.45237425e-01 -6.37199283e-02 -3.43294621e-01 5.20741642e-01
-5.89445293e-01 3.89404416e-01 -5.59804916e-01 -1.29860461e+00
-9.86957431e-01 5.43865323e-01 4.68296707e-01 2.19395354e-01
-9.89375293e-01 6.73949420e-01 4.25647385e-02 -1.02271013e-01
5.32213688e-01 -3.91300946e-01 8.95999651e-03 -3.93540442e-01
3.72737050e-01 2.03396857e-01 -3.52565557e-01 -5.47981560e-01
-2.66118675e-01 1.14639747e+00 5.44584133e-02 -3.27429958e-02
1.03638387e+00 -2.41909981e-01 8.24021772e-02 6.51674330e-01
1.51020658e+00 -2.72656053e-01 -1.97508347e+00 -4.83355939e-01
3.49640474e-02 -6.78495526e-01 -4.13849391e-02 -7.47402012e-02
-1.22712731e+00 6.20035172e-01 6.18318796e-01 -2.69402415e-01
5.94050229e-01 2.49877676e-01 4.33486640e-01 7.18822658e-01
4.11659002e-01 -9.48629141e-01 5.93280435e-01 4.84553963e-01
4.82532829e-01 -1.49370933e+00 8.26915801e-02 -2.30984107e-01
-5.73476911e-01 1.30170500e+00 7.91314602e-01 -6.87195301e-01
8.51881444e-01 1.98809162e-01 1.76702157e-01 -1.68036520e-01
-6.41761661e-01 -3.98988724e-01 5.26055872e-01 1.07255793e+00
2.34879509e-01 -4.48303014e-01 3.67416501e-01 -4.08134341e-01
2.57795751e-01 1.73378736e-01 3.72077882e-01 1.04266202e+00
-3.75482291e-01 -9.69170034e-01 -8.94902274e-02 2.53137738e-01
8.52851346e-02 3.29780549e-01 -1.80675313e-01 8.52369845e-01
-2.23977804e-01 5.46712458e-01 3.02537590e-01 -1.78998068e-01
8.28612447e-02 -2.27505222e-01 9.44691360e-01 -7.80951679e-01
-3.26094776e-01 7.05378130e-02 -3.04710358e-01 -1.04040682e+00
-1.01375067e+00 -6.27085507e-01 -1.55275798e+00 -1.09592505e-01
-1.43582940e-01 7.69642293e-02 1.54603913e-01 9.00950253e-01
2.24536642e-01 1.67251959e-01 9.18759823e-01 -1.07683301e+00
-4.93719339e-01 -2.68424928e-01 -2.07704410e-01 7.29541540e-01
7.54710138e-01 -7.95287848e-01 -3.24452847e-01 6.03000462e-01] | [8.951781272888184, -0.21573621034622192] |
143cad07-63a2-4b62-ab93-cfb3cf891d35 | deep-monocular-3d-human-pose-estimation-via | 2104.03520 | null | https://arxiv.org/abs/2104.03520v1 | https://arxiv.org/pdf/2104.03520v1.pdf | Deep Monocular 3D Human Pose Estimation via Cascaded Dimension-Lifting | The 3D pose estimation from a single image is a challenging problem due to depth ambiguity. One type of the previous methods lifts 2D joints, obtained by resorting to external 2D pose detectors, to the 3D space. However, this type of approaches discards the contextual information of images which are strong cues for 3D pose estimation. Meanwhile, some other methods predict the joints directly from monocular images but adopt a 2.5D output representation $P^{2.5D} = (u,v,z^{r}) $ where both $u$ and $v$ are in the image space but $z^{r}$ in root-relative 3D space. Thus, the ground-truth information (e.g., the depth of root joint from the camera) is normally utilized to transform the 2.5D output to the 3D space, which limits the applicability in practice. In this work, we propose a novel end-to-end framework that not only exploits the contextual information but also produces the output directly in the 3D space via cascaded dimension-lifting. Specifically, we decompose the task of lifting pose from 2D image space to 3D spatial space into several sequential sub-tasks, 1) kinematic skeletons \& individual joints estimation in 2D space, 2) root-relative depth estimation, and 3) lifting to the 3D space, each of which employs direct supervisions and contextual image features to guide the learning process. Extensive experiments show that the proposed framework achieves state-of-the-art performance on two widely used 3D human pose datasets (Human3.6M, MuPoTS-3D). | ['Yuan Chang', 'Fangneng Zhan', 'Changgong Zhang'] | 2021-04-08 | null | null | null | null | ['3d-pose-estimation', '3d-multi-person-pose-estimation-absolute', '3d-multi-person-pose-estimation-root-relative', 'monocular-3d-human-pose-estimation'] | ['computer-vision', 'computer-vision', 'computer-vision', 'computer-vision'] | [-7.99043626e-02 -4.12305519e-02 -2.40212828e-01 -2.47869581e-01
-6.18537486e-01 -2.98160821e-01 1.99514642e-01 -4.39432383e-01
-6.40124738e-01 4.46586639e-01 1.01728149e-01 -9.62819234e-02
1.15241699e-01 -6.05266631e-01 -7.49396324e-01 -5.79947352e-01
1.43652380e-01 4.42187309e-01 2.86982089e-01 -2.80411810e-01
1.88697912e-02 5.34192324e-01 -1.38662255e+00 -1.85106441e-01
3.81163657e-01 1.19400263e+00 1.91043884e-01 5.10985255e-01
1.64586809e-02 1.59915641e-01 -4.44758922e-01 -1.23555921e-01
5.10500431e-01 -2.34810024e-01 -4.39738870e-01 4.70013171e-01
3.61567289e-01 -4.74111289e-01 -3.73427689e-01 1.05168724e+00
5.23604453e-01 1.03318989e-02 5.42468309e-01 -1.14041495e+00
-3.36166799e-01 -2.92569160e-01 -1.08896518e+00 -1.13099664e-01
6.37098908e-01 2.41734400e-01 7.04657614e-01 -1.05207527e+00
7.86702514e-01 1.59170997e+00 4.47569132e-01 3.90807569e-01
-8.42702746e-01 -6.86556578e-01 4.38722670e-01 -2.21680656e-01
-1.53302968e+00 4.37368974e-02 1.03598058e+00 -6.07662499e-01
8.07671010e-01 -8.46526697e-02 7.71413922e-01 1.05739236e+00
2.95853376e-01 8.60055387e-01 1.15706408e+00 -3.48350316e-01
-1.45130008e-01 -3.72394323e-01 -7.02416897e-02 9.97645915e-01
-2.46225228e-03 1.56619325e-01 -6.19627655e-01 1.76742896e-01
1.24804020e+00 2.10914209e-01 -1.96787283e-01 -7.85659313e-01
-1.21349132e+00 5.69453061e-01 6.05459630e-01 -2.40419939e-01
-2.72563189e-01 1.70651168e-01 1.54008061e-01 -5.02642207e-02
5.17508030e-01 -9.39311683e-02 -6.39454842e-01 1.63476989e-02
-4.27646250e-01 5.15387595e-01 1.85305223e-01 1.25583804e+00
8.10648203e-01 -1.72216773e-01 1.02671444e-01 5.65580606e-01
6.78992748e-01 7.30558276e-01 2.54716724e-01 -1.00882208e+00
1.01360893e+00 8.69302988e-01 3.04032594e-01 -9.48388338e-01
-6.85774326e-01 -4.29989606e-01 -6.43295348e-01 3.13789338e-01
4.89470541e-01 -2.48966470e-01 -1.10251749e+00 1.80891657e+00
7.42653072e-01 -1.76164463e-01 -1.99829206e-01 1.38159359e+00
5.86505830e-01 4.51192796e-01 -1.77425191e-01 3.76652032e-02
1.46402359e+00 -9.18893516e-01 -4.00589198e-01 -5.66487312e-01
3.35254192e-01 -7.78407574e-01 1.08494401e+00 2.93616116e-01
-1.01306605e+00 -8.80436897e-01 -1.05735910e+00 -3.07639837e-01
-1.45105854e-01 4.29480642e-01 3.42228085e-01 2.62381703e-01
-4.89059448e-01 3.03310096e-01 -1.06389213e+00 -2.86114007e-01
1.53958902e-01 3.81207556e-01 -7.13528693e-01 -1.42776847e-01
-1.23745894e+00 9.06045675e-01 3.46151114e-01 3.85268778e-01
-6.62026465e-01 8.14512372e-03 -1.11668265e+00 -4.56084073e-01
8.48411918e-01 -9.54870939e-01 9.68657851e-01 -1.12417653e-01
-1.49853480e+00 1.11422372e+00 -8.50378722e-02 2.18130685e-02
8.67181778e-01 -7.64479160e-01 1.74640000e-01 1.89065844e-01
2.71595031e-01 6.43701553e-01 9.63980973e-01 -1.18085420e+00
-6.40621543e-01 -1.12642705e+00 1.59818992e-01 6.51936054e-01
7.86949098e-02 -4.01462913e-01 -1.08375740e+00 -7.30634630e-01
7.66423821e-01 -1.12554884e+00 -2.49210760e-01 3.04470479e-01
-6.52630091e-01 -1.64047748e-01 6.47518992e-01 -6.70458317e-01
9.53537464e-01 -1.91698802e+00 6.39645338e-01 2.04011530e-01
1.03142947e-01 1.27165904e-02 2.44349629e-01 1.40206769e-01
1.39439866e-01 -2.31021494e-01 -1.73467919e-01 -4.49096560e-01
-1.70824304e-02 2.58560181e-01 1.82370842e-01 6.91347241e-01
2.27471828e-01 7.09622383e-01 -8.34413111e-01 -7.14321792e-01
3.49837363e-01 5.46026170e-01 -5.25997102e-01 3.49155307e-01
2.23892778e-02 7.37669051e-01 -8.09183180e-01 7.33587682e-01
6.35408342e-01 -2.76676938e-02 -1.98533997e-01 -3.32438499e-01
-9.43741351e-02 1.71914119e-02 -1.49789047e+00 2.19668055e+00
-2.93256611e-01 -8.92435759e-02 1.40640110e-01 -7.68936038e-01
1.02741230e+00 2.47118875e-01 5.46265364e-01 -3.71129632e-01
2.37371445e-01 1.54400527e-01 -3.15267831e-01 -4.85955000e-01
1.71435297e-01 -1.19183652e-01 -4.96427119e-01 2.00204223e-01
8.17965716e-02 -3.26922923e-01 -1.05668463e-01 -2.87605494e-01
6.85895085e-01 8.37748528e-01 2.55232126e-01 1.58748940e-01
5.60767770e-01 -1.69003844e-01 7.65804052e-01 3.70404422e-01
-3.44609827e-01 7.25684285e-01 5.66406131e-01 -2.77674377e-01
-9.85986471e-01 -1.43517363e+00 1.77900538e-01 6.07454300e-01
4.35972810e-01 -3.58398467e-01 -7.78006494e-01 -8.75268936e-01
2.05527514e-01 1.62168741e-02 -5.23878574e-01 -3.51242930e-01
-9.01353896e-01 -3.28379691e-01 2.15142965e-01 7.33211756e-01
7.16663182e-01 -7.00452209e-01 -1.01051104e+00 2.73579583e-02
-3.48146081e-01 -1.27852571e+00 -7.55721033e-01 4.92092110e-02
-1.03664184e+00 -1.14150047e+00 -9.35632169e-01 -6.51308954e-01
6.99694991e-01 2.69229710e-01 6.60928667e-01 -1.54236123e-01
-3.95427525e-01 2.26337969e-01 -2.60603756e-01 -1.89948931e-01
3.83228928e-01 -1.75116863e-02 3.24407071e-01 -3.35134380e-02
2.27279052e-01 -3.30531150e-01 -8.23907971e-01 6.29964173e-01
-4.08931047e-01 1.71803594e-01 8.50357473e-01 8.01143587e-01
9.61835027e-01 -6.69592898e-03 1.31476521e-01 -5.12995601e-01
1.31218404e-01 6.83241934e-02 -4.76567239e-01 -5.81664592e-02
-1.62286565e-01 5.66590168e-02 3.16681027e-01 -3.05372089e-01
-1.03506351e+00 5.98992109e-01 -3.02993506e-01 -7.21931517e-01
-1.86231360e-01 3.54968458e-01 -4.86107022e-01 4.11988705e-01
5.74487448e-01 8.33201557e-02 2.74702251e-01 -7.83253491e-01
2.68350333e-01 4.74775851e-01 8.05525482e-01 -6.71664655e-01
9.72547710e-01 5.67766011e-01 3.13961655e-01 -5.58092594e-01
-9.70080376e-01 -5.72979391e-01 -1.19923568e+00 -1.80184558e-01
1.13505685e+00 -1.18817019e+00 -6.26510978e-01 5.19099951e-01
-1.07863998e+00 1.11914553e-01 6.22653477e-02 8.39073837e-01
-8.13503802e-01 4.85161245e-01 -5.94594181e-01 -7.41818488e-01
-2.90544540e-01 -1.43877125e+00 1.53936911e+00 8.95221811e-03
-1.70417279e-01 -2.89378911e-01 -2.36586601e-01 5.51652253e-01
-4.55251545e-01 6.09247208e-01 7.78040290e-01 1.93791971e-01
-3.73410374e-01 -4.86748815e-01 -1.59120366e-01 3.17068815e-01
5.22448355e-03 -3.74287635e-01 -6.71046913e-01 -2.41672486e-01
-7.33589381e-03 -3.18708599e-01 6.49216235e-01 4.00973886e-01
8.30870807e-01 1.64107963e-01 -2.94094831e-01 6.58338547e-01
1.11746335e+00 -8.42690840e-03 3.77229363e-01 2.59778291e-01
8.93825769e-01 6.81346238e-01 1.13711059e+00 5.30288577e-01
4.12051052e-01 9.79651749e-01 6.20570898e-01 -8.21175575e-02
-5.73070757e-02 -6.69782221e-01 3.38093728e-01 4.93468791e-01
-3.71909708e-01 2.69941390e-01 -7.83358097e-01 1.31264508e-01
-1.93944609e+00 -3.69777620e-01 1.83866397e-01 2.13758969e+00
7.55958378e-01 6.25658691e-01 2.55998194e-01 9.15656686e-02
7.17387855e-01 1.36426464e-01 -8.03485453e-01 1.95636541e-01
2.24834651e-01 1.84296072e-02 4.37032700e-01 4.67923135e-01
-1.09618104e+00 9.18362141e-01 4.53682709e+00 5.03014743e-01
-9.00216639e-01 -1.86574355e-01 2.40813687e-01 -1.38591856e-01
1.61253646e-01 -1.17876016e-01 -1.10204172e+00 3.42780679e-01
7.77949542e-02 5.56612730e-01 -1.31283417e-01 8.79378676e-01
1.42421022e-01 -1.88772351e-01 -1.15971768e+00 1.32391059e+00
-6.17413260e-02 -6.27657771e-01 -2.74069067e-02 9.03789699e-02
3.89539301e-01 -4.45002168e-01 6.32904470e-02 3.26554537e-01
-1.15524217e-01 -8.03062439e-01 1.04362893e+00 4.17532444e-01
9.75199044e-01 -8.80971789e-01 6.57002747e-01 8.90901148e-01
-1.52717578e+00 5.64451478e-02 -2.61665046e-01 -2.04229400e-01
3.55667919e-01 4.58711028e-01 -5.03727615e-01 6.34300709e-01
9.16557670e-01 6.40247703e-01 -3.46701860e-01 5.91894209e-01
-6.16287649e-01 -1.60325438e-01 -4.19926286e-01 2.45176464e-01
2.75625497e-01 -9.56554264e-02 4.74558622e-01 7.98079550e-01
4.45061862e-01 3.28748554e-01 4.91977662e-01 5.85831761e-01
4.05647494e-02 -1.91242427e-01 -5.50997853e-01 4.20952350e-01
1.85232043e-01 9.40109909e-01 -6.21112764e-01 -5.72108105e-02
-2.23216146e-01 1.12238002e+00 2.64232546e-01 2.48754650e-01
-8.93205643e-01 -3.53801221e-01 6.54420733e-01 2.61511952e-01
3.39355022e-01 -6.33301675e-01 -1.05994277e-01 -1.27022600e+00
4.26966101e-01 -6.14340007e-01 3.89702350e-01 -8.23267341e-01
-9.40121055e-01 3.41461539e-01 3.09046179e-01 -1.49737597e+00
-3.30910623e-01 -8.83719027e-01 -9.98787135e-02 1.06605530e+00
-1.24556410e+00 -1.07715642e+00 -3.99945080e-01 7.76008368e-01
5.37152052e-01 1.20985799e-01 5.07305741e-01 7.42160678e-02
-4.32506204e-01 5.45796931e-01 -4.49901998e-01 4.37881082e-01
7.71062434e-01 -1.10864663e+00 3.76971245e-01 6.18615806e-01
-4.20804396e-02 4.90802258e-01 4.56805944e-01 -6.79084897e-01
-1.56091785e+00 -8.62922192e-01 7.62874365e-01 -5.90069175e-01
1.37784451e-01 -5.30278444e-01 -3.44805360e-01 6.92851067e-01
-4.44034994e-01 3.13144892e-01 1.88339189e-01 -8.32110345e-02
-3.14179778e-01 -1.55378357e-01 -1.10026765e+00 6.74681127e-01
1.48010468e+00 -4.36381489e-01 -6.82519853e-01 8.34675804e-02
6.83782816e-01 -1.02928460e+00 -9.17852283e-01 5.23994505e-01
7.78793573e-01 -7.81757534e-01 1.35689557e+00 -4.47437644e-01
4.31678087e-01 -6.52858973e-01 -3.02672416e-01 -1.01536191e+00
-4.03523482e-02 -3.24226618e-01 -2.50891864e-01 6.42499566e-01
-3.87425162e-02 -1.93256944e-01 1.09028375e+00 1.94602951e-01
-1.90774858e-01 -1.11343038e+00 -1.18240178e+00 -5.61489344e-01
-1.10866700e-03 -4.59335983e-01 3.48947853e-01 3.38504583e-01
-2.18317568e-01 5.59921205e-01 -4.30570751e-01 2.50676543e-01
7.72310257e-01 3.55490893e-01 1.05085313e+00 -1.14779878e+00
-2.96490729e-01 -1.07098386e-01 -6.46629155e-01 -1.71504605e+00
-6.11258410e-02 -5.31046927e-01 1.21986873e-01 -1.37341642e+00
-8.02691877e-02 -1.77664146e-01 -6.95470795e-02 3.45005840e-01
-2.78323025e-01 2.44222224e-01 2.72979528e-01 1.86718196e-01
-3.64695400e-01 4.85369802e-01 1.78590024e+00 3.83168459e-02
-4.88171428e-02 3.15901935e-02 -3.78065646e-01 1.02313983e+00
4.37311441e-01 -1.21819451e-01 -4.69169080e-01 -6.16817832e-01
-6.31314218e-02 4.82743800e-01 5.49861670e-01 -1.01154459e+00
-3.57282013e-02 -2.21999720e-01 8.91458213e-01 -1.16673136e+00
7.99172878e-01 -8.04438353e-01 -1.58988357e-01 6.24740422e-01
2.12902073e-02 1.56871170e-01 -2.37942472e-01 6.86182559e-01
-1.35234937e-01 1.06410950e-01 7.59639442e-01 -6.14326358e-01
-7.73218870e-01 7.03169167e-01 2.14601129e-01 1.48593977e-01
1.08493257e+00 -3.68027508e-01 2.01336756e-01 -1.67762071e-01
-9.94851410e-01 3.44233453e-01 4.53044534e-01 4.40520674e-01
9.39884782e-01 -1.44827521e+00 -4.51292545e-01 3.35062265e-01
2.11224869e-01 7.53580928e-01 3.06557417e-01 7.63697267e-01
-5.07597446e-01 4.39902753e-01 -2.59665191e-01 -1.12819123e+00
-1.09476590e+00 5.35684824e-01 3.52241904e-01 -3.39759678e-01
-7.37165749e-01 9.56751645e-01 3.41345370e-01 -5.59810579e-01
3.88864338e-01 -3.97425056e-01 -1.57607701e-02 -4.52405177e-02
1.51739910e-01 2.03794718e-01 -4.97686714e-02 -9.69954967e-01
-5.17214179e-01 1.27926028e+00 -1.15841394e-02 -2.57529080e-01
1.12813151e+00 -3.67386997e-01 2.86716819e-01 3.70168328e-01
1.52725756e+00 -3.41882616e-01 -1.80745673e+00 -4.97383922e-01
-2.58914351e-01 -6.79074228e-01 -3.57098550e-01 -4.76076424e-01
-1.06906986e+00 1.16987324e+00 5.71438849e-01 -5.78807652e-01
9.48190272e-01 1.20831490e-01 9.17781949e-01 2.69163191e-01
6.84694648e-01 -1.42565835e+00 4.77633268e-01 4.73265946e-01
8.77855301e-01 -1.24643600e+00 1.90182462e-01 -5.37621856e-01
-5.54432690e-01 1.08810508e+00 8.65030050e-01 -2.50002801e-01
7.65279174e-01 -9.32102501e-02 9.65358689e-02 -1.98748812e-01
-2.48021021e-01 -2.24095345e-01 3.68802309e-01 5.33144712e-01
2.94315875e-01 2.92662010e-02 -2.28537962e-01 6.80302799e-01
-1.65239587e-01 -1.75070852e-01 -4.67518307e-02 1.30057466e+00
-5.02997458e-01 -1.01222503e+00 -7.58809030e-01 5.16249752e-03
-2.03970060e-01 5.29185355e-01 -2.86033958e-01 1.12828803e+00
5.47219336e-01 7.73984790e-01 -1.77737147e-01 -5.12912691e-01
8.99669826e-01 8.03706273e-02 7.38587320e-01 -7.57059872e-01
-1.09049156e-01 6.40598536e-01 -1.89657301e-01 -6.32914960e-01
-2.71523029e-01 -6.09901726e-01 -1.62927103e+00 7.73056224e-02
-2.05000132e-01 -1.95160091e-01 5.14741063e-01 9.27508354e-01
5.27484901e-02 2.67673165e-01 5.01832664e-01 -1.18346512e+00
-7.01226771e-01 -8.11046243e-01 -6.82516098e-01 5.43174207e-01
3.47249836e-01 -1.29566395e+00 -3.34094581e-03 -4.73041534e-02] | [6.99766731262207, -1.0312323570251465] |
f6307c28-0761-4b32-92a4-bc56d860708b | faxplainac-a-fact-checking-tool-based-on | 2110.10144 | null | https://arxiv.org/abs/2110.10144v1 | https://arxiv.org/pdf/2110.10144v1.pdf | FaxPlainAC: A Fact-Checking Tool Based on EXPLAINable Models with HumAn Correction in the Loop | Fact-checking on the Web has become the main mechanism through which we detect the credibility of the news or information. Existing fact-checkers verify the authenticity of the information (support or refute the claim) based on secondary sources of information. However, existing approaches do not consider the problem of model updates due to constantly increasing training data due to user feedback. It is therefore important to conduct user studies to correct models' inference biases and improve the model in a life-long learning manner in the future according to the user feedback. In this paper, we present FaxPlainAC, a tool that gathers user feedback on the output of explainable fact-checking models. FaxPlainAC outputs both the model decision, i.e., whether the input fact is true or not, along with the supporting/refuting evidence considered by the model. Additionally, FaxPlainAC allows for accepting user feedback both on the prediction and explanation. Developed in Python, FaxPlainAC is designed as a modular and easily deployable tool. It can be integrated with other downstream tasks and allowing for fact-checking human annotation gathering and life-long learning. | ['Avishek Anand', 'Koustav Rudra', 'Zijian Zhang'] | 2021-09-12 | null | null | null | null | ['explainable-models'] | ['computer-vision'] | [-1.53434217e-01 5.91294050e-01 -3.58101517e-01 -3.68028194e-01
-7.38303840e-01 -8.89528334e-01 6.82984293e-01 1.03297341e+00
-5.20207547e-02 8.98189306e-01 8.99105966e-02 -8.19447517e-01
5.35616688e-02 -8.14940393e-01 -1.01712000e+00 -1.40090525e-01
4.16167557e-01 6.16150796e-01 6.41341209e-01 1.44097030e-01
4.29452240e-01 -7.40720555e-02 -1.63149440e+00 8.04335117e-01
9.22695458e-01 8.52553129e-01 -8.24119225e-02 7.21362710e-01
-1.22620910e-01 1.16914558e+00 -5.11723697e-01 -9.55698550e-01
-1.92928463e-01 -5.74852467e-01 -8.46630335e-01 -2.88767070e-01
2.35455886e-01 -1.53228641e-01 4.27158445e-01 1.20648038e+00
1.34504944e-01 -4.88928765e-01 2.06670985e-01 -1.42066753e+00
-4.47295934e-01 1.16445577e+00 -1.21037988e-02 1.67144746e-01
7.32609510e-01 7.11439177e-02 9.76985693e-01 -7.37291873e-01
8.65937591e-01 8.81411731e-01 6.54783666e-01 4.22997475e-01
-8.00664008e-01 -5.55891693e-01 3.55686173e-02 6.84215724e-01
-8.75864863e-01 -2.73974329e-01 4.91043031e-01 -7.98402250e-01
6.65199041e-01 5.69426596e-01 5.49518466e-01 9.45414424e-01
1.33460745e-01 6.31204545e-01 1.42950618e+00 -6.49377167e-01
5.86877823e-01 9.30407584e-01 4.71988648e-01 9.38606024e-01
6.47214651e-01 -7.91187435e-02 -7.93674171e-01 -4.27617103e-01
1.17714688e-01 -4.81088102e-01 -1.95546970e-01 5.31238802e-02
-7.87467539e-01 5.92483938e-01 1.21145815e-01 2.97295064e-01
-6.62504613e-01 -1.59838304e-01 3.39900762e-01 1.69941515e-01
4.65608299e-01 2.92897284e-01 -8.59134674e-01 -2.94220418e-01
-1.04723191e+00 3.93096864e-01 1.14446056e+00 5.35320282e-01
4.65815097e-01 -4.32063609e-01 -6.19650409e-02 2.15260595e-01
5.67198157e-01 1.19556852e-01 3.13027948e-01 -7.43202448e-01
3.24688643e-01 9.44156051e-01 4.23675865e-01 -1.01528347e+00
-3.76698583e-01 -5.87275267e-01 -3.73203367e-01 3.72818917e-01
6.26425564e-01 -1.80579290e-01 -2.96076238e-01 1.30268347e+00
7.17879534e-01 1.30105689e-01 -4.90330867e-02 7.64396787e-01
8.64601374e-01 3.84688765e-01 3.24389994e-01 -2.93228358e-01
1.48754287e+00 -6.02547228e-01 -1.02442002e+00 -7.11366534e-02
7.15574265e-01 -7.23185718e-01 8.45404029e-01 6.52411401e-01
-9.46670473e-01 -2.26659283e-01 -9.14684534e-01 8.41866508e-02
-4.48710054e-01 9.19747651e-02 5.28427720e-01 6.65918887e-01
-7.02403605e-01 7.58934379e-01 -6.59008145e-01 -7.18510598e-02
3.48568738e-01 -1.70962423e-01 -2.02296481e-01 1.42883986e-01
-1.43122089e+00 1.05306196e+00 7.97058821e-01 -2.69709021e-01
-5.09891570e-01 -6.92033708e-01 -6.26202345e-01 2.11171538e-01
7.25621521e-01 -3.77373576e-01 1.53570247e+00 -8.63962829e-01
-1.14624417e+00 8.95882189e-01 -1.13032058e-01 -6.44486248e-01
1.09755576e+00 5.48788644e-02 -5.77061534e-01 -1.31148249e-01
1.47056162e-01 1.29562855e-01 5.01416087e-01 -1.35464418e+00
-1.01030123e+00 -2.21629813e-01 9.35404003e-02 -4.38080788e-01
1.02095895e-01 1.22602955e-01 -2.40388632e-01 -2.66676903e-01
-1.23171136e-01 -6.76213562e-01 1.62904456e-01 9.88648832e-02
-3.25058252e-01 -3.94318849e-01 8.46241832e-01 -1.09909177e+00
1.64903688e+00 -1.57830215e+00 -6.77291930e-01 3.35500956e-01
1.20866023e-01 5.48454583e-01 4.18957382e-01 5.40624917e-01
-1.24774568e-01 4.31990027e-01 -4.42557931e-02 -4.20172028e-02
1.77819803e-02 2.94783860e-02 -2.41982549e-01 9.65729877e-02
1.44806877e-01 6.38005674e-01 -1.06964350e+00 -6.92646325e-01
-3.99098173e-02 1.68507844e-01 -5.15942931e-01 4.21650056e-03
-7.10235775e-01 4.97061312e-01 -2.70099044e-01 3.73440087e-01
6.16025627e-01 -6.55350685e-01 4.30668473e-01 5.76157756e-02
-1.56103387e-01 7.59804606e-01 -1.25962615e+00 9.82270837e-01
-3.42652351e-01 5.05979300e-01 -9.29281190e-02 -6.10823989e-01
7.00009584e-01 6.50968373e-01 -6.94908872e-02 -5.44935107e-01
1.33980006e-01 4.35512871e-01 -3.24572235e-01 -7.82602131e-01
2.85942942e-01 -3.96540463e-02 2.51148015e-01 9.97000635e-01
-1.07574314e-01 2.86168396e-01 3.42406452e-01 5.27335703e-01
9.23279345e-01 2.77572036e-01 7.47005641e-01 1.58155307e-01
7.11140633e-01 3.81542981e-01 5.79145253e-01 7.15586662e-01
1.03098176e-01 3.62729095e-02 8.65054786e-01 -5.28015971e-01
-8.97645891e-01 -4.19786453e-01 -1.12789460e-01 7.72659898e-01
-2.22925127e-01 -6.16705120e-01 -7.17203975e-01 -1.20906901e+00
-1.13728389e-01 1.49284470e+00 -6.20525777e-01 8.12118873e-02
6.76634610e-02 -1.81094706e-01 2.29845151e-01 2.44065106e-01
5.11724532e-01 -1.13474131e+00 -8.31129491e-01 2.28464454e-01
-4.97691482e-01 -8.33859861e-01 8.18877816e-02 3.61397937e-02
-7.04087555e-01 -1.62199831e+00 2.61863053e-01 -3.00450891e-01
5.45645654e-01 -1.79273725e-01 1.06264114e+00 6.79108322e-01
3.88892770e-01 9.26471129e-02 -3.38531882e-01 -6.76186681e-01
-1.15397537e+00 -1.80686146e-01 -2.50807852e-01 -3.45979668e-02
3.09634894e-01 -3.35660368e-01 -1.82741135e-01 3.67603391e-01
-1.02997458e+00 4.02253985e-01 7.42127001e-02 4.62655574e-01
3.75359267e-01 5.34945726e-01 6.38790131e-01 -1.57073331e+00
7.52746344e-01 -7.00428426e-01 -8.49614382e-01 6.78805709e-01
-1.12609279e+00 1.04257934e-01 4.48288888e-01 -1.28283396e-01
-1.18531334e+00 -1.22539811e-02 -2.66125739e-01 1.84393123e-01
-4.60586138e-03 1.09851468e+00 -1.87965229e-01 5.65627933e-01
9.11652327e-01 -1.86931491e-01 -3.86578888e-01 -4.39744800e-01
1.02933399e-01 7.53383934e-01 4.62964684e-01 -2.44585842e-01
7.52563238e-01 8.41037855e-02 -3.88415396e-01 9.27036181e-02
-1.29306757e+00 -3.40678185e-01 -6.59914851e-01 -5.68980634e-01
3.91814202e-01 -6.88000619e-01 -1.12915146e+00 2.37262681e-01
-1.35167527e+00 -3.51895213e-01 9.40356255e-02 3.12833846e-01
-8.85732621e-02 9.23898220e-02 -2.41062671e-01 -1.25472677e+00
-3.42265993e-01 -6.10710025e-01 4.58866745e-01 1.04735874e-01
-7.11376667e-01 -1.04923415e+00 1.27370860e-02 6.51556015e-01
1.01166405e-01 1.86333776e-01 1.02821589e+00 -1.04317451e+00
-4.46410090e-01 -8.13099027e-01 5.49211800e-02 1.04884095e-01
-3.55559796e-01 2.71013081e-01 -1.17388046e+00 3.22029352e-01
-1.37566388e-01 -2.56434619e-01 3.76255572e-01 -1.37356997e-01
8.99305820e-01 -1.01327336e+00 -2.04296321e-01 -3.50489527e-01
1.09629250e+00 -1.94515079e-01 5.89154005e-01 5.41476011e-01
7.25732371e-02 7.96355546e-01 8.02093625e-01 3.98198545e-01
5.21252275e-01 4.99031037e-01 5.64507008e-01 2.89098114e-01
1.30031005e-01 -7.34821320e-01 2.33606994e-01 2.47523233e-01
5.56130633e-02 -3.14505547e-01 -9.44872797e-01 2.61601686e-01
-2.06392646e+00 -1.34087276e+00 -7.74405241e-01 2.31202412e+00
1.20964718e+00 6.60603702e-01 -2.41407007e-02 5.74460268e-01
7.07633793e-01 -3.45780969e-01 -3.28654379e-01 -3.71487349e-01
6.70934469e-02 -2.66399354e-01 1.65400952e-01 8.73837113e-01
-8.35473955e-01 5.64992487e-01 5.46870613e+00 5.69090068e-01
-9.98296857e-01 4.85846668e-01 5.50208151e-01 2.87174553e-01
-6.52408481e-01 3.81766886e-01 -6.81410909e-01 5.85036099e-01
1.10594296e+00 -2.64100909e-01 1.46347091e-01 1.09283495e+00
5.49522996e-01 -5.80113530e-01 -9.89034951e-01 3.61581117e-01
-1.29947320e-01 -1.70532775e+00 -1.25590354e-01 -1.37759566e-01
6.19744718e-01 -2.83352941e-01 -4.85468090e-01 2.45982006e-01
4.65617269e-01 -5.47446549e-01 1.29431868e+00 7.24863529e-01
6.16723001e-01 -3.29319268e-01 1.09461057e+00 1.02242911e+00
-3.81326169e-01 -1.80463716e-02 1.98447198e-01 -2.31516480e-01
2.16985673e-01 1.01645577e+00 -1.33358741e+00 3.35672259e-01
5.33875883e-01 4.68426019e-01 -9.91343021e-01 1.09709477e+00
-9.31519568e-01 1.05212450e+00 -2.11959183e-02 -1.53263628e-01
-3.77527416e-01 3.92941087e-01 3.79690409e-01 1.15552354e+00
1.21137142e-01 4.11394462e-02 1.62505526e-02 8.06202054e-01
2.85661537e-02 -4.16417867e-02 -6.95729405e-02 -9.30234268e-02
5.20661771e-01 1.26767230e+00 -7.27875054e-01 -7.48619616e-01
1.35424836e-02 4.89088476e-01 2.15220287e-01 -1.08190432e-01
-7.89962828e-01 9.57779437e-02 -6.90317675e-02 6.58855557e-01
1.69151336e-01 2.00654447e-01 -5.80221772e-01 -1.08953297e+00
2.54107088e-01 -1.10617328e+00 7.00050771e-01 -1.22941327e+00
-9.49791968e-01 4.55531955e-01 -2.92781174e-01 -8.37072909e-01
-3.07039440e-01 -3.27260315e-01 -6.34089768e-01 8.01975191e-01
-1.57613266e+00 -9.75993037e-01 -3.48816574e-01 3.03604543e-01
1.97750270e-01 3.07272285e-01 8.47885072e-01 1.51054516e-01
-4.31389600e-01 2.18141168e-01 -5.81519306e-01 3.00581101e-03
6.57972336e-01 -1.25831676e+00 1.67185843e-01 9.62123752e-01
1.68194547e-01 7.20701516e-01 1.20560789e+00 -1.23402417e+00
-7.96780229e-01 -9.37977493e-01 1.73400140e+00 -7.47825086e-01
9.65855241e-01 -1.47897303e-01 -1.33635569e+00 6.14792764e-01
7.74931535e-02 -1.48797616e-01 8.28588605e-01 2.52096355e-01
-7.48593867e-01 6.49816543e-02 -1.31886208e+00 1.95688024e-01
5.23989260e-01 -5.06976008e-01 -6.68017685e-01 4.43114370e-01
4.48821604e-01 -4.64202106e-01 -3.76634866e-01 -8.96837935e-02
5.47454596e-01 -1.01508605e+00 7.61671662e-02 -8.63061547e-01
5.79667270e-01 -4.80928838e-01 2.86323398e-01 -9.34308946e-01
-1.12385340e-01 -5.76477468e-01 -4.39281851e-01 1.37673533e+00
1.05810308e+00 -5.07203400e-01 5.54086626e-01 9.03967917e-01
2.39708170e-01 -2.55262017e-01 -8.16336632e-01 -2.00874850e-01
-5.44982135e-01 -8.41338456e-01 5.88174045e-01 1.09088993e+00
4.86862332e-01 2.72810340e-01 -1.99322894e-01 6.41049385e-01
3.33118528e-01 -5.98172508e-02 6.76256120e-01 -1.58037329e+00
-3.75690222e-01 -7.67486170e-02 4.44459729e-02 -3.91913176e-01
-1.55470341e-01 -9.27607000e-01 -1.53334299e-02 -1.77551031e+00
2.37485975e-01 -4.47490633e-01 -2.75708269e-03 9.21228528e-01
-3.59446645e-01 -2.73002144e-02 5.48276398e-03 3.20586681e-01
-7.37613440e-01 -1.13861248e-01 7.76395261e-01 1.86619237e-01
-7.41180554e-02 4.70487058e-01 -6.90334737e-01 9.70099807e-01
8.27666521e-01 -9.18763876e-01 -7.72815496e-02 1.75327267e-02
1.10333931e+00 1.93324685e-01 9.21138823e-01 -9.65304255e-01
5.03689528e-01 -1.32275283e-01 2.69555092e-01 -7.32493043e-01
-3.07517201e-01 -1.02161646e+00 3.96930844e-01 6.74964786e-01
-6.81969166e-01 1.91113986e-02 5.38391583e-02 6.84352279e-01
1.30485252e-01 -5.93332469e-01 3.84638101e-01 -1.79173559e-01
-2.89065063e-01 -2.34147877e-01 -6.00461662e-01 -2.72126049e-01
9.11390245e-01 1.85314100e-02 -6.18114591e-01 -5.44932246e-01
-8.55575025e-01 1.94277659e-01 1.78039327e-01 3.28335434e-01
2.59796023e-01 -8.51916850e-01 -7.87651181e-01 -2.12391820e-02
2.04190493e-01 -4.49164212e-01 7.22590089e-02 8.39629471e-01
-3.89420778e-01 3.86068285e-01 1.53786287e-01 -1.60029218e-01
-1.44377625e+00 8.12847137e-01 1.14121296e-01 -5.78070223e-01
-3.69167894e-01 3.38075340e-01 -8.55523705e-01 -4.25607026e-01
2.45297328e-01 -1.52019396e-01 -3.58749002e-01 2.52357334e-01
9.33070362e-01 2.66448200e-01 5.85422873e-01 -1.12174369e-01
-2.94409722e-01 -3.68281275e-01 3.67357582e-02 -2.37394065e-01
1.53699207e+00 -1.11705765e-01 -2.27613181e-01 5.77026784e-01
2.69911349e-01 4.79732484e-01 -1.15864670e+00 -3.18856001e-01
4.22031194e-01 -4.56743628e-01 -2.38031559e-02 -1.66190076e+00
-7.97956765e-01 5.16170502e-01 1.88478053e-01 6.30582392e-01
6.14837050e-01 1.32550701e-01 2.11243615e-01 2.06038162e-01
4.71040756e-01 -1.10551679e+00 -2.42235318e-01 2.44056717e-01
1.05607140e+00 -1.32412338e+00 2.53923684e-01 -4.19805378e-01
-7.63495147e-01 1.01349270e+00 4.38456893e-01 6.03063941e-01
6.67166710e-01 4.64325361e-02 3.08887303e-01 -4.52883691e-01
-1.14009261e+00 8.22154135e-02 2.45591179e-01 4.44295347e-01
4.97584641e-01 1.85934838e-03 -6.56144142e-01 9.87399399e-01
-4.30980921e-01 3.88535649e-01 6.80389345e-01 6.59344673e-01
-5.14198899e-01 -9.87979293e-01 -6.01728618e-01 3.59719485e-01
-5.82803071e-01 1.07658831e-02 -6.00216866e-01 4.55419987e-01
4.27243710e-01 1.37669063e+00 -3.76635432e-01 -2.19417393e-01
2.35125780e-01 2.16732368e-01 -1.27735347e-01 -6.53144777e-01
-8.92158091e-01 -3.27386260e-01 6.85804605e-01 -3.83052766e-01
-3.39351058e-01 -7.95843840e-01 -1.26809943e+00 -4.44833159e-01
-6.67680323e-01 6.37873232e-01 9.29083645e-01 1.20395124e+00
3.45519662e-01 2.89258927e-01 2.59045124e-01 -5.56913130e-02
-3.05381179e-01 -8.71215045e-01 -5.32518364e-02 2.74027705e-01
2.43253578e-02 -2.64605492e-01 -2.14348912e-01 3.53052199e-01] | [9.010374069213867, 9.423772811889648] |
be007b95-8049-46fb-8c57-35d881edc8b0 | analysis-of-hand-segmentation-in-the-wild | 1803.03317 | null | http://arxiv.org/abs/1803.03317v2 | http://arxiv.org/pdf/1803.03317v2.pdf | Analysis of Hand Segmentation in the Wild | A large number of works in egocentric vision have concentrated on action and
object recognition. Detection and segmentation of hands in first-person videos,
however, has less been explored. For many applications in this domain, it is
necessary to accurately segment not only hands of the camera wearer but also
the hands of others with whom he is interacting. Here, we take an in-depth look
at the hand segmentation problem. In the quest for robust hand segmentation
methods, we evaluated the performance of the state of the art semantic
segmentation methods, off the shelf and fine-tuned, on existing datasets. We
fine-tune RefineNet, a leading semantic segmentation method, for hand
segmentation and find that it does much better than the best contenders.
Existing hand segmentation datasets are collected in the laboratory settings.
To overcome this limitation, we contribute by collecting two new datasets: a)
EgoYouTubeHands including egocentric videos containing hands in the wild, and
b) HandOverFace to analyze the performance of our models in presence of similar
appearance occlusions. We further explore whether conditional random fields can
help refine generated hand segmentations. To demonstrate the benefit of
accurate hand maps, we train a CNN for hand-based activity recognition and
achieve higher accuracy when a CNN was trained using hand maps produced by the
fine-tuned RefineNet. Finally, we annotate a subset of the EgoHands dataset for
fine-grained action recognition and show that an accuracy of 58.6% can be
achieved by just looking at a single hand pose which is much better than the
chance level (12.5%). | ['Ali Borji', 'Aisha Urooj Khan'] | 2018-03-08 | analysis-of-hand-segmentation-in-the-wild-1 | http://openaccess.thecvf.com/content_cvpr_2018/html/Urooj_Analysis_of_Hand_CVPR_2018_paper.html | http://openaccess.thecvf.com/content_cvpr_2018/papers/Urooj_Analysis_of_Hand_CVPR_2018_paper.pdf | cvpr-2018-6 | ['hand-segmentation', 'fine-grained-action-recognition'] | ['computer-vision', 'computer-vision'] | [ 2.25549072e-01 1.33259073e-01 -4.48011085e-02 -2.59888470e-01
-4.95989203e-01 -7.78285146e-01 2.28747606e-01 -6.19036078e-01
-5.44631004e-01 7.06073761e-01 6.53649122e-02 2.75793314e-01
-5.68762422e-02 -3.13246936e-01 -7.56806910e-01 -7.54791439e-01
2.47647017e-01 9.17926848e-01 6.19014978e-01 1.24585852e-02
3.01493406e-02 7.09087610e-01 -1.60312378e+00 4.48439807e-01
3.81287903e-01 7.28420556e-01 1.76387474e-01 8.66273701e-01
3.12640160e-01 3.20854694e-01 -7.02926099e-01 -4.40998852e-01
4.13550913e-01 -3.36958766e-01 -1.15879357e+00 3.14879835e-01
7.67916679e-01 -8.44269156e-01 -2.79231519e-01 6.64417267e-01
7.83720076e-01 5.71662374e-02 4.60933715e-01 -1.17811882e+00
9.52110440e-02 4.76873040e-01 -4.94086713e-01 3.71545553e-01
4.55186456e-01 5.81028581e-01 5.51652789e-01 -4.29767966e-01
1.12898767e+00 1.22921681e+00 4.69679981e-01 7.04799771e-01
-1.14873397e+00 -6.43968344e-01 3.12051296e-01 8.57063681e-02
-1.26105070e+00 -4.38922018e-01 5.37923276e-01 -6.03055418e-01
1.07287109e+00 4.39062193e-02 9.27660525e-01 1.73588383e+00
-8.63540918e-02 9.67410624e-01 1.18163240e+00 -4.11063045e-01
2.16637388e-01 5.78989349e-02 5.82462922e-02 7.87734449e-01
6.61316961e-02 -1.63002908e-01 -5.67826807e-01 2.29304016e-01
1.25988698e+00 -4.82967086e-02 -3.34279120e-01 -5.54019451e-01
-1.46218514e+00 4.61189657e-01 2.94616699e-01 6.58407748e-01
-3.99802744e-01 3.54943514e-01 1.67707801e-01 -1.75857395e-01
1.95909515e-01 3.56349409e-01 -6.70877278e-01 -4.24587041e-01
-1.23153853e+00 4.38182533e-01 8.21366191e-01 9.54880774e-01
2.56301641e-01 -2.76378572e-01 -5.05710602e-01 4.60862905e-01
2.77951598e-01 3.05906236e-01 2.96067148e-01 -1.17459023e+00
3.53496909e-01 3.80641639e-01 3.17609340e-01 -5.12515962e-01
-6.02841377e-01 -2.56447345e-01 -3.85010205e-02 4.49661106e-01
1.36878848e+00 -2.67325342e-01 -1.23461854e+00 1.61020899e+00
3.62852097e-01 -1.72143519e-01 -4.57706898e-01 1.34309733e+00
5.73643744e-01 -7.89239332e-02 2.49474093e-01 1.31206468e-01
1.54576695e+00 -9.93256748e-01 -6.15921795e-01 -1.17663488e-01
4.15908635e-01 -7.06833899e-01 1.10283780e+00 6.47288680e-01
-1.04421532e+00 -5.01860976e-01 -8.88551116e-01 1.54106468e-01
-3.49580765e-01 4.33145374e-01 8.09086800e-01 9.87719238e-01
-9.32282150e-01 9.07295942e-01 -1.02089870e+00 -9.63413477e-01
6.75887883e-01 5.65205812e-01 -6.35276735e-01 1.90949038e-01
-8.24175656e-01 7.80289590e-01 2.56474316e-01 5.64100258e-02
-1.01631451e+00 -3.94487888e-01 -4.74350601e-01 -8.67057070e-02
7.01909363e-01 -7.00068295e-01 1.17572212e+00 -8.61152053e-01
-1.33611071e+00 1.16690361e+00 -9.96221229e-02 -9.40257981e-02
1.02901793e+00 -3.41932893e-01 9.52835232e-02 4.17653948e-01
4.10546549e-02 9.04785335e-01 9.07418370e-01 -8.87447596e-01
-5.17738461e-01 -9.03341830e-01 4.54829246e-01 1.00203410e-01
3.18373814e-02 2.50474978e-02 -8.11049938e-01 -6.29113793e-01
-1.66716456e-01 -1.20815003e+00 1.84858069e-01 1.13913722e-01
-4.21341181e-01 -4.22324806e-01 7.58429468e-01 -9.77295876e-01
6.96974218e-01 -1.80387926e+00 3.60196948e-01 2.39074335e-01
1.47995710e-01 3.98477882e-01 -2.92387772e-02 5.65126203e-02
-3.35942619e-02 -5.04102781e-02 -5.37727885e-02 -3.74903023e-01
4.44331057e-02 6.37396723e-02 8.10857639e-02 4.89389837e-01
-1.89688392e-02 1.02505422e+00 -7.67403841e-01 -5.92094421e-01
3.85606319e-01 5.99456906e-01 -5.62808573e-01 2.02410012e-01
-2.14743927e-01 7.63534248e-01 -4.17510241e-01 8.21941316e-01
2.74059176e-01 -1.35565847e-01 2.53445357e-01 -4.61916894e-01
2.40905389e-01 -3.10485274e-01 -1.37518370e+00 2.13361192e+00
-1.60266280e-01 5.38313985e-01 1.21436127e-01 -5.61016500e-01
1.82782918e-01 4.57892507e-01 6.37763798e-01 -4.60855573e-01
5.28309107e-01 4.41474132e-02 3.17019932e-02 -6.05428159e-01
5.28899357e-02 1.21375389e-01 3.73512268e-01 5.71363211e-01
4.75707620e-01 8.42474923e-02 3.17615718e-01 4.32541817e-02
9.57641602e-01 8.77548218e-01 -1.94958270e-01 -1.89013883e-01
2.56095797e-01 3.24428789e-02 1.81770548e-02 8.19971025e-01
-6.04345202e-01 9.71579790e-01 4.85771984e-01 -2.83565640e-01
-9.37090099e-01 -9.39445078e-01 -1.32383350e-02 1.37405884e+00
-3.15903057e-03 -3.12625438e-01 -1.60999143e+00 -1.05137014e+00
-1.09112263e-01 2.75841981e-01 -7.11443603e-01 3.48747581e-01
-5.68463147e-01 -5.39660037e-01 6.86211705e-01 1.06458104e+00
7.10454285e-01 -1.32233989e+00 -9.33780909e-01 9.53073055e-02
-2.75040239e-01 -1.24036443e+00 -3.82861286e-01 -1.94909461e-02
-5.64757049e-01 -1.55249667e+00 -1.24122298e+00 -4.25642490e-01
4.31401461e-01 -1.87271878e-01 9.39427078e-01 -1.90708876e-01
-6.96465254e-01 9.14710760e-01 -1.22577243e-01 -2.71502465e-01
1.88407749e-01 2.82767266e-01 1.13734029e-01 -2.26012114e-02
4.01676923e-01 -4.99249905e-01 -7.48025954e-01 6.48424029e-01
-3.80938947e-01 -3.01350534e-01 5.46194673e-01 4.90245610e-01
4.90393370e-01 -3.39840233e-01 1.51277989e-01 -8.13116014e-01
3.58808875e-01 1.56264305e-01 -4.30675864e-01 2.58498520e-01
-2.66052634e-01 1.79984607e-02 3.19747217e-02 -4.01851207e-01
-1.12651598e+00 5.71313500e-01 -2.80272692e-01 -5.64333797e-01
-6.34800971e-01 -3.83082986e-01 -2.82527089e-01 -2.01389626e-01
7.77094126e-01 -1.04240462e-01 -6.54573366e-02 -5.30657351e-01
4.23776746e-01 7.22940683e-01 5.50406337e-01 -6.54512465e-01
2.47217268e-01 8.23473811e-01 -1.65638894e-01 -8.33998024e-01
-6.81439579e-01 -5.50770044e-01 -1.18243110e+00 -5.80624223e-01
1.36102712e+00 -6.17469668e-01 -9.87824261e-01 6.23755395e-01
-1.12709999e+00 -7.59971201e-01 -1.82836875e-01 4.53538507e-01
-1.01575732e+00 3.20759892e-01 -3.28011900e-01 -8.38159144e-01
-1.30901799e-01 -1.39907897e+00 1.45749378e+00 2.36042514e-02
-6.31459236e-01 -7.86181927e-01 -1.95871323e-01 8.91113877e-01
1.55714244e-01 3.80200058e-01 3.34851563e-01 -6.93979263e-01
-6.86646938e-01 -1.27416447e-01 -1.19285546e-01 1.18392788e-01
-6.64891079e-02 -2.25009203e-01 -1.44677150e+00 -2.71709353e-01
-2.53469855e-01 -3.93830895e-01 7.57157207e-01 4.81380582e-01
1.14852238e+00 1.81824371e-01 -4.91358876e-01 4.18007791e-01
8.02165031e-01 7.31324703e-02 6.59402728e-01 1.48588479e-01
8.93226743e-01 8.82111371e-01 5.90098143e-01 3.02607983e-01
2.91104522e-02 9.11461473e-01 1.84444189e-01 7.37581551e-02
-5.48507214e-01 7.90222269e-03 -7.18959644e-02 -2.56100446e-01
-9.41703200e-01 -1.51922852e-01 -7.65217125e-01 4.61153537e-01
-1.77264845e+00 -8.54193807e-01 1.41234305e-02 1.93510604e+00
5.03221035e-01 1.73865572e-01 7.49136925e-01 3.40810299e-01
6.83563352e-01 -1.22553408e-01 -5.97744823e-01 1.99160185e-02
2.59127706e-01 4.33440983e-01 5.09834826e-01 2.64400840e-01
-1.42191875e+00 1.15669143e+00 6.56253624e+00 5.36905408e-01
-9.98814344e-01 1.81129783e-01 3.55498284e-01 -3.52120787e-01
4.94611084e-01 -3.16685259e-01 -8.38596702e-01 3.48858476e-01
5.56298137e-01 7.73874998e-01 7.63569117e-01 1.07962930e+00
1.25690684e-01 -3.52045059e-01 -1.40728366e+00 1.35616112e+00
2.54952103e-01 -9.48234499e-01 -3.67472649e-01 9.52633768e-02
5.90537429e-01 -1.78457141e-01 -1.87085584e-01 5.43079600e-02
4.11252193e-02 -1.14392960e+00 7.48041272e-01 5.59220850e-01
6.01454198e-01 -4.79171693e-01 7.79226542e-01 2.11729348e-01
-1.03235960e+00 9.19864327e-03 1.45509630e-01 1.36152148e-01
2.03425586e-01 3.25419158e-02 -8.78320158e-01 -2.02370193e-02
1.04740024e+00 4.48406905e-01 -6.25025749e-01 8.01161289e-01
-3.87928426e-01 3.76315296e-01 -4.44286287e-01 1.43695623e-01
1.12247467e-01 1.05934247e-01 5.15479088e-01 1.20078480e+00
-1.62340596e-01 5.58854826e-02 -1.68492924e-03 9.79480445e-01
1.27581462e-01 -1.78044006e-01 -2.88482845e-01 -2.79786766e-01
-1.52262568e-01 1.24746215e+00 -1.17579186e+00 -3.00333917e-01
-1.25302330e-01 1.48226070e+00 1.78786501e-01 4.88492459e-01
-7.67543316e-01 -4.28520381e-01 5.91091096e-01 3.76719117e-01
4.78274763e-01 -1.98856041e-01 -1.29014641e-01 -9.98365343e-01
2.71676600e-01 -8.32560301e-01 2.96138257e-01 -9.96905386e-01
-8.88792634e-01 3.79889399e-01 1.67356864e-01 -5.96004605e-01
-5.56911230e-01 -1.03571594e+00 -1.82305604e-01 8.41969192e-01
-8.55707467e-01 -1.40924966e+00 -8.20197821e-01 7.97098875e-01
7.53387332e-01 1.68817386e-03 5.98326027e-01 2.59490192e-01
-4.15263355e-01 5.72242856e-01 -5.73035955e-01 3.35537612e-01
7.95362771e-01 -1.26701069e+00 3.09741139e-01 6.19112790e-01
2.10440874e-01 7.18908668e-01 5.99565923e-01 -6.90338612e-01
-1.16473019e+00 -7.54060626e-01 3.99481624e-01 -1.23747480e+00
2.76255369e-01 -5.21458387e-01 -4.85490441e-01 8.97604227e-01
-1.15885869e-01 -6.84943646e-02 2.67048806e-01 1.59458648e-02
-7.03208670e-02 1.62944034e-01 -1.38450217e+00 4.19606566e-01
1.61770535e+00 -5.43345749e-01 -5.88671505e-01 6.79659426e-01
1.06684677e-02 -5.70910692e-01 -8.45829189e-01 2.50303417e-01
1.15897691e+00 -1.27318895e+00 9.25270498e-01 -7.93743134e-01
7.72971660e-02 -2.22356930e-01 4.29085121e-02 -9.32779074e-01
3.61444652e-02 -3.67422819e-01 -1.59736544e-01 1.14201558e+00
-9.98602584e-02 -4.38796997e-01 1.35996199e+00 7.40503728e-01
1.93258494e-01 -6.17443323e-01 -7.42613852e-01 -8.73266101e-01
-1.73796237e-01 -4.80989248e-01 2.78148592e-01 3.98457676e-01
-5.22029176e-02 1.06311038e-01 -4.51972373e-02 -1.80734456e-01
6.91355586e-01 -2.00185671e-01 9.56024349e-01 -1.13886046e+00
-3.61313969e-01 -2.73238897e-01 -6.09016776e-01 -8.65230322e-01
2.16415048e-01 -5.77319205e-01 3.06410473e-02 -1.62087047e+00
2.94971257e-01 -1.66081280e-01 5.57621680e-02 6.09641552e-01
1.45948425e-01 7.23410308e-01 2.79312849e-01 1.39236376e-01
-5.36932409e-01 -1.91071659e-01 1.43680763e+00 -1.18518151e-01
-2.27202043e-01 7.92279840e-02 -2.67301202e-01 8.37849319e-01
5.96061647e-01 -1.60421059e-01 -3.85369658e-01 -9.06434059e-02
-2.32608110e-01 -2.17511430e-01 7.33828187e-01 -1.24341309e+00
7.60500645e-03 1.70741752e-01 7.35820532e-01 -5.61142564e-01
5.70755839e-01 -8.00051749e-01 1.25380531e-01 4.31788772e-01
-7.39793330e-02 -5.02285838e-01 1.09050525e-02 4.06768620e-01
2.82604814e-01 -1.35509118e-01 7.12126434e-01 -5.54721355e-01
-8.55344296e-01 1.84736162e-01 -3.87086391e-01 7.40918219e-02
1.09149718e+00 -5.67677498e-01 -1.70404419e-01 -1.75866991e-01
-1.31287110e+00 -4.51072864e-02 4.68141645e-01 4.57687765e-01
1.71231657e-01 -7.57859290e-01 -2.20840126e-01 2.53180712e-01
1.18120499e-02 -1.63098052e-01 2.41149426e-01 1.14265382e+00
-5.17771721e-01 7.53914595e-01 -5.33100128e-01 -7.98147440e-01
-1.38859665e+00 4.53365833e-01 5.92251301e-01 1.41225439e-02
-5.31458259e-01 8.28454316e-01 1.69766366e-01 -1.23839810e-01
4.73064929e-01 -4.72064763e-01 -2.24265337e-01 2.17439741e-01
4.52348143e-01 7.68244028e-01 1.48706809e-01 -7.10183740e-01
-5.99132538e-01 8.58239710e-01 1.77263424e-01 -2.34650418e-01
9.73869920e-01 2.38053292e-01 2.41204828e-01 1.14185095e-01
8.11954677e-01 -1.47892311e-01 -1.70761585e+00 4.52850670e-01
-3.62005919e-01 -5.92162728e-01 -7.84528926e-02 -1.13081765e+00
-1.13970268e+00 9.69612241e-01 1.06780410e+00 -2.24378169e-01
7.23300040e-01 4.23607439e-01 6.16025269e-01 4.50571388e-01
7.31528223e-01 -1.34003556e+00 4.06540811e-01 1.52100936e-01
8.57786179e-01 -1.20678973e+00 -1.31995082e-01 -6.54121697e-01
-6.20391011e-01 1.00328457e+00 7.47941077e-01 -1.22245573e-01
3.07997108e-01 4.61699292e-02 8.39010701e-02 -3.82822216e-01
2.21369490e-01 -5.98198056e-01 3.50046098e-01 9.57706809e-01
2.04792798e-01 -7.26638734e-02 -5.92531636e-02 7.16207087e-01
-1.97528258e-01 4.05418247e-01 1.12124309e-01 9.84977365e-01
-9.90193561e-02 -9.22721922e-01 -4.97009754e-01 4.70474988e-01
-5.10650277e-01 4.54264969e-01 -7.40055442e-01 1.01556146e+00
4.26319480e-01 8.41446042e-01 -1.75533593e-02 -2.58120179e-01
5.65532565e-01 3.71637464e-01 1.17048490e+00 -5.49556017e-01
-6.10412002e-01 3.19801830e-02 4.17978019e-02 -1.12566781e+00
-6.37211859e-01 -6.17706656e-01 -1.14766598e+00 5.37657586e-04
-2.59661287e-01 -4.05612260e-01 7.86287189e-01 1.24772978e+00
2.56791525e-02 6.66494310e-01 -2.75438309e-01 -1.48076177e+00
-3.27918053e-01 -1.02435291e+00 -8.82579744e-01 5.59128881e-01
-4.72108163e-02 -1.16888845e+00 -2.59373486e-01 2.28988841e-01] | [6.648462772369385, -0.6505990028381348] |
cb83ede5-8a1b-46c8-8ef8-aac3c1383f55 | datasets-for-data-driven-reinforcement | 2004.07219 | null | https://arxiv.org/abs/2004.07219v4 | https://arxiv.org/pdf/2004.07219v4.pdf | D4RL: Datasets for Deep Data-Driven Reinforcement Learning | The offline reinforcement learning (RL) setting (also known as full batch RL), where a policy is learned from a static dataset, is compelling as progress enables RL methods to take advantage of large, previously-collected datasets, much like how the rise of large datasets has fueled results in supervised learning. However, existing online RL benchmarks are not tailored towards the offline setting and existing offline RL benchmarks are restricted to data generated by partially-trained agents, making progress in offline RL difficult to measure. In this work, we introduce benchmarks specifically designed for the offline setting, guided by key properties of datasets relevant to real-world applications of offline RL. With a focus on dataset collection, examples of such properties include: datasets generated via hand-designed controllers and human demonstrators, multitask datasets where an agent performs different tasks in the same environment, and datasets collected with mixtures of policies. By moving beyond simple benchmark tasks and data collected by partially-trained RL agents, we reveal important and unappreciated deficiencies of existing algorithms. To facilitate research, we have released our benchmark tasks and datasets with a comprehensive evaluation of existing algorithms, an evaluation protocol, and open-source examples. This serves as a common starting point for the community to identify shortcomings in existing offline RL methods and a collaborative route for progress in this emerging area. | ['Sergey Levine', 'George Tucker', 'Ofir Nachum', 'Aviral Kumar', 'Justin Fu'] | 2020-04-15 | null | https://openreview.net/forum?id=px0-N3_KjA | https://openreview.net/pdf?id=px0-N3_KjA | null | ['d4rl'] | ['robots'] | [ 4.85788435e-02 -1.47801870e-02 -5.23871183e-01 -1.10753149e-01
-9.00200963e-01 -1.04944658e+00 8.32140923e-01 -7.50792250e-02
-7.14933932e-01 1.15371454e+00 2.87481964e-01 -2.51147985e-01
-1.68396056e-01 -1.68213546e-01 -8.17295730e-01 -6.25750065e-01
-5.54696679e-01 5.87210953e-01 -1.65865928e-01 -3.12936872e-01
4.66393158e-02 3.98353189e-01 -1.68196833e+00 6.57009184e-02
3.14400703e-01 5.83601117e-01 3.91566336e-01 6.59102380e-01
3.14451545e-01 1.11400962e+00 -8.65059435e-01 1.89050779e-01
6.07517004e-01 -5.90350628e-01 -7.51486599e-01 6.16565794e-02
1.79981485e-01 -6.68316364e-01 -2.65236765e-01 6.17284775e-01
6.57432675e-01 5.12617528e-01 1.14993133e-01 -1.57213306e+00
-4.38848853e-01 7.88175464e-01 -7.96161741e-02 -4.17223573e-02
5.70551097e-01 7.95589089e-01 1.22004294e+00 -1.04688056e-01
7.54968524e-01 1.28139806e+00 5.64185441e-01 8.85931551e-01
-1.33662999e+00 -5.61414540e-01 4.93802518e-01 -4.92340475e-02
-5.29865205e-01 -5.94876885e-01 5.98536432e-01 -3.44266951e-01
1.07712913e+00 -4.70126048e-02 7.55446911e-01 1.77094841e+00
-1.20281562e-01 1.31194305e+00 1.41552961e+00 -1.69035569e-01
5.19267857e-01 -1.23901084e-01 -3.87626857e-01 4.75923002e-01
2.10001558e-01 7.55214632e-01 -4.61541593e-01 -1.21045321e-01
8.32940936e-01 -9.40595493e-02 -1.61261350e-01 -6.61125958e-01
-1.62710547e+00 7.10905194e-01 1.36188477e-01 1.25801831e-01
-3.47635359e-01 4.18972790e-01 6.46642029e-01 7.73409486e-01
-4.69417237e-02 9.18772638e-01 -7.97722876e-01 -6.78584278e-01
-3.21879745e-01 7.19770253e-01 1.04656076e+00 1.14319313e+00
7.82582879e-01 2.54028559e-01 -1.24980338e-01 5.79001784e-01
4.90953177e-02 4.06042278e-01 7.61866510e-01 -1.50753701e+00
4.72523868e-01 3.09151888e-01 6.81485832e-01 -4.27032799e-01
-5.31971872e-01 -1.77612185e-01 -8.76586586e-02 5.41044533e-01
7.68653810e-01 -5.65169513e-01 -4.09253299e-01 2.04681635e+00
2.95266122e-01 -7.17725083e-02 3.77447248e-01 9.48975682e-01
3.42288405e-01 3.60226214e-01 -5.74189238e-02 -3.20967644e-01
7.35082030e-01 -1.35358608e+00 -5.47851324e-01 -2.96459258e-01
7.52143741e-01 -2.89947718e-01 1.51576042e+00 5.84198415e-01
-9.00864720e-01 -3.53298157e-01 -8.60384881e-01 2.06553653e-01
-3.99107575e-01 2.85040885e-02 9.41817462e-01 2.87330925e-01
-9.79332745e-01 7.43605793e-01 -8.38188469e-01 -5.25836825e-01
3.42872232e-01 4.25777525e-01 -2.34224677e-01 5.80077730e-02
-7.45253503e-01 8.62932563e-01 2.92775840e-01 -2.87322756e-02
-1.72666335e+00 -6.14447594e-01 -6.76512063e-01 -4.22460347e-01
9.55753505e-01 -2.96409994e-01 1.98964655e+00 -1.16477561e+00
-2.03676391e+00 4.88624066e-01 3.96510035e-01 -5.41359723e-01
7.65066445e-01 -3.48171800e-01 -1.36205882e-01 -1.51801229e-01
5.81507422e-02 5.29984891e-01 6.83194995e-01 -1.43196213e+00
-7.38115251e-01 -1.79118544e-01 6.37419283e-01 3.11206818e-01
6.78829923e-02 3.80707718e-02 9.02044699e-02 -4.22524452e-01
-8.03945780e-01 -9.72144246e-01 -3.03002656e-01 -2.88676828e-01
-6.07221946e-02 -3.88886809e-01 9.17738974e-01 -2.15231881e-01
6.72564685e-01 -1.99441504e+00 1.44028574e-01 -4.00894910e-01
1.52263403e-01 6.45229965e-02 -4.69300300e-01 8.43214393e-01
1.94910988e-01 -1.90155745e-01 2.74104998e-02 -3.67960870e-01
4.78428006e-01 4.56958979e-01 -5.14355779e-01 4.08880442e-01
-3.15781645e-02 9.63988125e-01 -1.50858212e+00 -1.98675945e-01
1.64760485e-01 -2.04439223e-01 -5.82689941e-01 5.12590885e-01
-7.66653061e-01 8.68310690e-01 -6.03544354e-01 6.52986109e-01
-1.31848305e-01 -5.65598980e-02 3.17182451e-01 2.53077447e-01
-2.70161927e-01 3.03610504e-01 -8.46654356e-01 2.00075817e+00
-4.42801446e-01 5.47595322e-01 3.54440004e-01 -8.73805463e-01
6.02416098e-01 3.51877093e-01 9.29488003e-01 -8.09431791e-01
1.16757102e-01 4.54857238e-02 1.59158036e-01 -6.10996246e-01
4.23187733e-01 9.59997252e-02 -2.98433244e-01 8.84881973e-01
1.88739106e-01 -3.24978024e-01 4.95635927e-01 -7.10934447e-03
1.52121544e+00 6.59212947e-01 3.42552513e-01 3.11876601e-03
-8.31916630e-02 4.61324573e-01 5.17834306e-01 1.16228199e+00
-6.61572218e-01 -1.73002928e-02 4.09339964e-01 -5.51687479e-01
-1.00159669e+00 -9.64815974e-01 3.76189381e-01 1.55737805e+00
-6.71821535e-02 -5.05096018e-01 -4.89293605e-01 -9.44706023e-01
2.46544108e-01 5.40664494e-01 -7.21105933e-01 2.52149478e-02
-7.26373494e-01 -3.85569960e-01 5.84933400e-01 4.57919955e-01
3.84868890e-01 -1.58577573e+00 -1.18725336e+00 3.05506736e-01
1.42226396e-02 -1.10224152e+00 -1.73574522e-01 3.06820124e-01
-8.18659604e-01 -1.39037097e+00 -4.02726203e-01 -6.03854299e-01
3.47199082e-01 2.87632585e-01 1.27746701e+00 -8.10857341e-02
-2.10618153e-01 1.08592141e+00 -4.32146162e-01 -5.39445341e-01
-4.70522285e-01 -1.56201318e-01 3.85281384e-01 -3.43183011e-01
-1.28411338e-01 -4.89403009e-01 -4.38405752e-01 3.49299669e-01
-6.51803970e-01 -1.27851814e-01 6.61974013e-01 9.19745922e-01
2.81363994e-01 -2.01703459e-01 7.21065998e-01 -6.89365327e-01
1.02525365e+00 -5.98390043e-01 -8.50859344e-01 1.28462255e-01
-5.62868714e-01 9.01442096e-02 1.03372228e+00 -8.57892990e-01
-8.01497400e-01 3.23991291e-02 4.07987446e-01 -4.26774263e-01
-3.15331310e-01 1.97808549e-01 4.96009365e-02 6.34801686e-02
6.78794920e-01 1.84742749e-01 3.73474866e-01 -4.65579093e-01
5.64746201e-01 3.11299443e-01 2.68763453e-01 -1.24682271e+00
5.40036917e-01 3.38982612e-01 -3.35402846e-01 -4.81349289e-01
-6.91543758e-01 -1.19464360e-01 -3.56408477e-01 -3.63499165e-01
4.11636114e-01 -7.42233634e-01 -1.21375573e+00 2.94931620e-01
-5.86872935e-01 -1.66540599e+00 -8.36909950e-01 5.51666200e-01
-1.35636616e+00 -1.75797284e-01 -5.81285834e-01 -7.79806614e-01
1.73187658e-01 -1.40009880e+00 9.88659859e-01 1.81190133e-01
-1.44355878e-01 -1.14232814e+00 5.02839506e-01 1.66377336e-01
5.17371595e-01 2.31457129e-01 6.87025845e-01 -7.25615323e-01
-4.40375268e-01 2.04975650e-01 2.72415221e-01 2.60531664e-01
2.08275497e-01 -2.10583836e-01 -8.59254837e-01 -6.63566291e-01
-1.73912734e-01 -1.34698415e+00 3.64786148e-01 -3.13614197e-02
1.07753301e+00 -4.74425972e-01 -1.07306369e-01 2.26458609e-01
1.20623374e+00 3.25383484e-01 2.58441418e-02 6.46173477e-01
3.44786376e-01 4.85976607e-01 8.30913007e-01 6.92342997e-01
5.45637846e-01 4.90109622e-01 5.38367331e-01 2.01264352e-01
7.98683763e-02 -6.20472670e-01 7.94413030e-01 5.63477695e-01
-1.15273617e-01 -1.63264647e-01 -5.90083539e-01 3.65471750e-01
-2.10877180e+00 -1.07415950e+00 6.42279625e-01 2.16820288e+00
9.97089922e-01 -1.97589561e-01 7.11705148e-01 -2.39888236e-01
2.41648853e-01 1.97347596e-01 -1.15165484e+00 -2.25709036e-01
7.19816759e-02 3.25237215e-02 3.36690724e-01 3.00757766e-01
-9.69673932e-01 1.08168781e+00 7.43769789e+00 5.86611807e-01
-1.03905535e+00 5.01711965e-02 2.24559933e-01 -5.03937364e-01
7.36142993e-02 2.90741622e-02 -5.90333641e-01 2.83324331e-01
8.39042366e-01 -1.45534858e-01 1.25166297e+00 1.01251364e+00
4.37146187e-01 -2.50908881e-01 -1.62370908e+00 8.55682552e-01
-1.18621394e-01 -9.31069851e-01 -4.92338181e-01 1.71185270e-01
7.84471750e-01 3.97482365e-01 1.17194615e-01 1.08468080e+00
1.24007463e+00 -9.62489903e-01 8.04963052e-01 2.61280596e-01
4.94579166e-01 -2.73826212e-01 1.51785001e-01 6.39622271e-01
-8.15406621e-01 -6.58137262e-01 -2.00885221e-01 -3.95340949e-01
-1.96344361e-01 -2.43375674e-01 -8.87648523e-01 1.22208528e-01
6.88590586e-01 9.35839713e-01 -2.12277949e-01 7.71557927e-01
-3.09491336e-01 6.12334073e-01 -2.23712951e-01 -3.55175018e-01
5.66989183e-01 -1.94346324e-01 4.59164858e-01 7.91237712e-01
-2.03102738e-01 -8.63169283e-02 6.88013852e-01 7.85422206e-01
-1.26179056e-02 -9.71100777e-02 -1.11813450e+00 -4.48410392e-01
4.11794841e-01 1.38533652e+00 -3.71834040e-01 -8.67089778e-02
-3.80138785e-01 5.18840790e-01 7.43219018e-01 5.41276157e-01
-8.76821876e-01 5.05076088e-02 9.10784960e-01 -3.46841812e-01
-2.04784498e-02 -7.17992783e-01 3.00334096e-01 -1.01948845e+00
-2.21347585e-01 -1.53332007e+00 2.96809375e-01 -5.78444719e-01
-1.18741155e+00 6.59184307e-02 1.45982057e-01 -1.26526558e+00
-6.06093049e-01 -5.48346698e-01 -3.94564003e-01 8.91686156e-02
-1.42114758e+00 -7.07569182e-01 -2.15685561e-01 6.49890304e-01
8.80214810e-01 -3.63477409e-01 8.38004410e-01 -5.09652644e-02
-7.38188565e-01 4.39839631e-01 3.86298358e-01 -4.02491167e-02
8.86314869e-01 -1.27549076e+00 7.45278001e-02 2.50579387e-01
1.84752777e-01 5.57115853e-01 6.73241019e-01 -4.58642215e-01
-2.23288822e+00 -9.73708093e-01 -2.47607723e-01 -6.99920297e-01
1.04756784e+00 -5.58328748e-01 -2.64913291e-01 1.08335185e+00
2.28752166e-01 -2.51210723e-02 3.77490938e-01 1.77027717e-01
-1.46264270e-01 -1.17366850e-01 -1.07388318e+00 8.19467485e-01
1.30301046e+00 -3.47275227e-01 -3.88859957e-01 6.42744899e-01
7.69788861e-01 -4.51887250e-01 -8.99297178e-01 1.55112252e-01
6.54093921e-01 -8.47837985e-01 7.59207428e-01 -1.13360751e+00
2.45948330e-01 -8.71138275e-02 -1.48926347e-01 -1.66927433e+00
3.08905859e-02 -1.22495472e+00 -1.89848959e-01 8.60466778e-01
2.57886678e-01 -8.10136616e-01 6.24114156e-01 5.26005983e-01
-2.16215029e-01 -6.42534435e-01 -5.06028712e-01 -1.16145432e+00
7.36614913e-02 -3.95088285e-01 5.26721239e-01 8.97013605e-01
2.39652738e-01 1.68111891e-01 -3.38424414e-01 -2.87798941e-01
6.18960977e-01 2.31114551e-01 1.39304435e+00 -8.85442853e-01
-6.33022666e-01 -5.65764010e-01 1.71698600e-01 -1.26529968e+00
6.19825900e-01 -7.32717097e-01 3.79030168e-01 -1.17818117e+00
1.32365152e-02 -8.88844073e-01 -1.09495990e-01 7.67709374e-01
2.63403416e-01 -2.39964262e-01 3.41328144e-01 3.32555026e-01
-1.13940454e+00 7.64489651e-01 1.45150912e+00 3.27328257e-02
-3.33087444e-01 -5.39905252e-03 -5.34075320e-01 6.70850694e-01
1.19443274e+00 -2.78026104e-01 -7.55127788e-01 -5.36343932e-01
1.24360181e-01 9.71150622e-02 3.55138719e-01 -1.05827129e+00
2.06385151e-01 -6.19720101e-01 -4.29187494e-04 -5.78459315e-02
3.92988920e-01 -8.24809849e-01 -3.17956120e-01 3.31363082e-01
-6.70237362e-01 3.30129117e-01 2.73592561e-01 7.12812901e-01
1.73481166e-01 -2.10353080e-02 3.51887226e-01 -4.82464790e-01
-8.73182118e-01 1.34507433e-01 -3.92481744e-01 5.21309018e-01
1.28054726e+00 -6.27203137e-02 -6.15482390e-01 -5.29822469e-01
-5.54448187e-01 7.27456272e-01 5.70738733e-01 5.57240367e-01
3.59935641e-01 -1.01176369e+00 -4.59550083e-01 9.21550989e-02
8.23044404e-02 -4.46174815e-02 -2.29669705e-01 7.79457033e-01
-4.69414480e-02 2.67981440e-01 -4.76200640e-01 -3.07095736e-01
-8.00254047e-01 6.92687213e-01 3.32852125e-01 -2.94401765e-01
-7.40038872e-01 4.09656495e-01 -4.73140879e-03 -9.20782089e-01
6.33132637e-01 -6.20444417e-01 -5.99259743e-04 -2.05472216e-01
4.00883436e-01 4.56686974e-01 -2.48349503e-01 -4.56420379e-03
1.02965371e-03 -2.37172171e-02 1.27861455e-01 -3.94588619e-01
1.48346198e+00 1.44766688e-01 2.48525202e-01 9.40878510e-01
7.58916497e-01 -5.57569489e-02 -1.96255398e+00 -1.33284122e-01
-4.29045670e-02 -1.88342273e-01 -2.87257880e-01 -1.11523545e+00
-7.82302082e-01 4.39705491e-01 2.04505205e-01 1.89397022e-01
8.01320374e-01 2.16199849e-02 4.46904451e-01 9.32967484e-01
1.08478880e+00 -1.46280241e+00 5.77573955e-01 7.10226059e-01
9.19543445e-01 -1.43057954e+00 -1.03100859e-01 5.37070453e-01
-8.56981099e-01 1.00628865e+00 8.18055987e-01 -3.32969666e-01
2.05027357e-01 4.43320811e-01 -8.60505104e-02 5.76157216e-03
-1.28350508e+00 -4.45550829e-01 -4.77158397e-01 7.70912230e-01
7.91808739e-02 1.68451786e-01 1.71094328e-01 5.20447552e-01
-2.85698920e-01 1.17215037e-01 5.45995295e-01 1.30056190e+00
-3.64668697e-01 -1.22045314e+00 -1.49055526e-01 3.13816726e-01
-8.58560428e-02 4.30597007e-01 -6.05402946e-01 1.19524944e+00
-2.23778591e-01 1.07013512e+00 -7.91212693e-02 -3.37786108e-01
3.26355636e-01 -1.40394509e-01 9.65244830e-01 -5.26862264e-01
-7.89402127e-01 -2.92485982e-01 3.11382353e-01 -1.09632874e+00
-4.61544275e-01 -8.80388439e-01 -1.21473753e+00 -1.96509048e-01
1.03579655e-01 1.01662487e-01 6.93120956e-01 9.53890443e-01
3.17172945e-01 3.59653980e-01 6.41143084e-01 -1.25988698e+00
-1.04413915e+00 -8.95565987e-01 -4.08818305e-01 3.73313278e-01
5.50628364e-01 -8.98066521e-01 -4.51353759e-01 -2.19851047e-01] | [4.0568671226501465, 1.6971025466918945] |
f04fcda6-2b38-4437-a97e-8ff406105a6a | harmonizing-base-and-novel-classes-a-class | 2303.13724 | null | https://arxiv.org/abs/2303.13724v1 | https://arxiv.org/pdf/2303.13724v1.pdf | Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation | Current methods for few-shot segmentation (FSSeg) have mainly focused on improving the performance of novel classes while neglecting the performance of base classes. To overcome this limitation, the task of generalized few-shot semantic segmentation (GFSSeg) has been introduced, aiming to predict segmentation masks for both base and novel classes. However, the current prototype-based methods do not explicitly consider the relationship between base and novel classes when updating prototypes, leading to a limited performance in identifying true categories. To address this challenge, we propose a class contrastive loss and a class relationship loss to regulate prototype updates and encourage a large distance between prototypes from different classes, thus distinguishing the classes from each other while maintaining the performance of the base classes. Our proposed approach achieves new state-of-the-art performance for the generalized few-shot segmentation task on PASCAL VOC and MS COCO datasets. | ['Guosheng Lin', 'Jun Cheng', 'Chuan-Sheng Foo', 'Yuming Fang', 'Yang Zhao', 'Zhonghua Wu', 'Weide Liu'] | 2023-03-24 | null | null | null | null | ['generalized-few-shot-semantic-segmentation'] | ['computer-vision'] | [ 2.78674662e-01 2.30366737e-02 -2.48439431e-01 -5.19172370e-01
-6.48228586e-01 -1.23976439e-01 4.87222314e-01 4.61267710e-01
-4.99231905e-01 5.75099230e-01 -3.88452083e-01 3.63578975e-01
9.65207666e-02 -7.45415866e-01 -5.66071093e-01 -7.42244422e-01
3.63628209e-01 5.67158759e-01 1.21631825e+00 -5.00699468e-02
3.92172605e-01 2.14024559e-01 -1.95853567e+00 3.09791148e-01
1.22797215e+00 9.55023110e-01 3.67694765e-01 4.65728730e-01
-4.21781957e-01 3.48314315e-01 -7.55745173e-01 -2.78903306e-01
1.49118170e-01 -6.80537820e-01 -6.93637550e-01 2.30408147e-01
6.46661162e-01 -1.01055562e-01 3.87395695e-02 1.29266942e+00
4.94010240e-01 6.83664680e-01 8.28021109e-01 -1.14535177e+00
-2.51696587e-01 4.95077312e-01 -6.62421227e-01 3.33835095e-01
-1.11820735e-02 7.71232843e-02 9.54753220e-01 -7.03859329e-01
7.25538075e-01 1.06351602e+00 7.12555110e-01 8.29905748e-01
-1.03817594e+00 -4.70348150e-01 5.71388006e-01 5.13043523e-01
-1.49758124e+00 -3.29883277e-01 7.19463587e-01 -5.23553669e-01
7.12383091e-01 1.83998898e-01 6.48167193e-01 6.99611127e-01
-3.69078130e-01 1.18330860e+00 8.39635253e-01 -3.50036919e-01
4.91823703e-01 4.15182054e-01 7.17244267e-01 3.86588961e-01
4.47095633e-02 -3.30857158e-01 -2.52116203e-01 2.09546417e-01
1.26662165e-01 -9.25062820e-02 -2.62699515e-01 -6.76879942e-01
-5.44435441e-01 8.23756814e-01 4.41052377e-01 5.35736322e-01
-1.67080209e-01 -1.30632833e-01 5.36451340e-01 -3.58377695e-01
4.88950759e-01 2.85343230e-01 -2.51578033e-01 -1.12437688e-01
-1.36352551e+00 3.31407040e-01 6.16281092e-01 1.03358424e+00
9.18062449e-01 -1.04247727e-01 -6.64171517e-01 1.15454054e+00
-3.86006646e-02 -7.79254436e-02 5.99859059e-01 -7.21521676e-01
2.48079166e-01 8.27762067e-01 -2.67302431e-02 -7.58088887e-01
-2.54027218e-01 -5.46792984e-01 -2.00992331e-01 4.27034497e-02
3.66553307e-01 1.74404085e-01 -1.50686836e+00 1.54152787e+00
7.18964219e-01 4.44901973e-01 1.44601325e-02 9.26641226e-01
1.03807116e+00 7.60812283e-01 3.23479503e-01 -2.72939712e-01
1.12457871e+00 -1.21737552e+00 -5.72809994e-01 -3.30764711e-01
6.32918596e-01 -5.04948378e-01 1.24190509e+00 1.18839748e-01
-9.32424247e-01 -8.60178173e-01 -1.21102941e+00 5.67420349e-02
-6.44704521e-01 -1.08271569e-01 5.17730772e-01 6.96726739e-01
-5.15009940e-01 6.76653981e-01 -9.40390408e-01 -3.82647663e-01
7.00244546e-01 -6.25007134e-03 2.64892876e-01 -1.99222624e-01
-1.06416881e+00 5.36417186e-01 9.02263343e-01 -6.55640289e-02
-7.67561316e-01 -8.22637141e-01 -8.62714469e-01 1.70528650e-01
7.12061226e-01 -2.98724741e-01 1.14766085e+00 -1.11546171e+00
-1.17661142e+00 8.26225877e-01 1.51313797e-01 -6.67649150e-01
7.60330379e-01 -1.07437015e-01 -3.37623864e-01 1.51187345e-01
1.48750588e-01 1.03258574e+00 7.94727683e-01 -1.34979248e+00
-1.05411553e+00 -2.58265734e-01 -6.80920249e-03 3.21377397e-01
-2.90495157e-01 -2.95414627e-01 -8.08629394e-01 -5.95363855e-01
2.03029305e-01 -6.88330054e-01 -9.98192579e-02 -1.28153682e-01
-4.64465290e-01 -4.19821709e-01 1.22062910e+00 -2.54204959e-01
1.30609870e+00 -2.15922785e+00 -1.87560245e-02 -2.30700463e-01
-8.95429328e-02 8.74979019e-01 -2.71375477e-02 -2.44912907e-01
3.62307221e-01 -2.53568172e-01 -6.26668215e-01 -4.77593154e-01
-1.02191761e-01 4.21473473e-01 -2.24635433e-02 2.61579841e-01
2.47061908e-01 5.88801563e-01 -9.91689622e-01 -7.02780843e-01
3.51038337e-01 3.31458688e-01 -5.18359959e-01 2.17944056e-01
-5.16399145e-01 2.48435885e-01 -2.93493927e-01 5.07878006e-01
7.94889212e-01 4.53672148e-02 -2.16859803e-01 3.75139946e-03
-4.84082513e-02 -6.51958659e-02 -1.28619754e+00 1.54683387e+00
-3.96057451e-03 3.34303737e-01 -1.80735514e-01 -1.14486885e+00
8.86940598e-01 -5.57387546e-02 4.12140250e-01 -5.24721503e-01
1.98317602e-01 2.57298976e-01 3.35785188e-02 -3.54083508e-01
7.10528195e-01 -1.82325691e-01 9.83557403e-02 -1.28031164e-01
1.29146859e-01 -3.14602256e-01 7.16773272e-01 2.46177558e-02
5.93735754e-01 3.72224092e-01 5.52260168e-02 -1.35126591e-01
3.97763968e-01 1.85620636e-01 9.83595371e-01 8.55437279e-01
-7.41809487e-01 1.00735867e+00 4.24258024e-01 -1.71553101e-02
-7.38838911e-01 -1.03358889e+00 -2.81082273e-01 1.06977582e+00
6.44047081e-01 -1.22680254e-01 -1.12363112e+00 -9.63180780e-01
-1.16461121e-01 1.18674755e+00 -6.38674915e-01 -3.60246330e-01
-4.86764550e-01 -8.02986205e-01 3.00675780e-01 4.93236065e-01
6.18764877e-01 -9.63891804e-01 -8.29756975e-01 3.22030842e-01
-1.45902157e-01 -1.15435481e+00 -5.49853742e-01 1.46985367e-01
-7.78529108e-01 -1.27791572e+00 -1.10797834e+00 -8.32966745e-01
7.10402489e-01 1.78526804e-01 7.54233003e-01 -1.27015278e-01
-6.25472009e-01 1.38239682e-01 -4.99113798e-01 -3.29319954e-01
-3.74296546e-01 1.78310052e-01 -4.01292264e-01 2.65381038e-01
4.37215179e-01 -1.07419699e-01 -5.97977400e-01 4.41427499e-01
-8.82331073e-01 -1.96202677e-02 1.45518661e-01 6.04422390e-01
8.52247775e-01 3.34529430e-02 6.56508029e-01 -1.19304049e+00
1.33080199e-01 -3.60346645e-01 -4.81704891e-01 3.15297276e-01
-5.95227361e-01 -2.90321231e-01 5.19180238e-01 -6.42370582e-01
-1.21010959e+00 5.07073440e-02 -1.11077189e-01 -5.18964767e-01
-3.20496023e-01 1.91638350e-01 -7.43495226e-02 1.48003906e-01
5.81066370e-01 1.86736763e-01 -3.59795094e-01 -4.90243763e-01
4.25229698e-01 7.11431623e-01 5.71909249e-01 -3.58690977e-01
2.55590111e-01 3.71037036e-01 -3.87489885e-01 -1.03934610e+00
-1.00703871e+00 -1.05379581e+00 -7.75138617e-01 -2.81708449e-01
9.50299919e-01 -6.52512372e-01 1.58183187e-01 6.99361324e-01
-9.19533312e-01 -3.15908670e-01 -7.78435290e-01 3.27144146e-01
-6.14578903e-01 5.08330941e-01 -4.11274046e-01 -7.76619732e-01
-2.42035046e-01 -1.26611245e+00 9.49733615e-01 6.85228765e-01
-9.17381421e-02 -7.05239594e-01 -4.82323803e-02 3.91087979e-01
1.77310780e-01 2.78905988e-01 8.69801581e-01 -8.25762570e-01
-4.18734729e-01 -4.78535682e-01 -2.36166626e-01 5.31735837e-01
5.74912690e-02 1.26496002e-01 -9.82178271e-01 -3.45907748e-01
-1.51623279e-01 -3.13793182e-01 1.24387038e+00 5.04298806e-01
9.68169212e-01 2.08652198e-01 -5.32276452e-01 5.43709636e-01
1.28778994e+00 4.30340379e-01 6.57949388e-01 -8.69229250e-03
7.03567147e-01 6.66878581e-01 1.12945187e+00 3.26661736e-01
9.39598754e-02 7.10091174e-01 1.53022677e-01 1.47632763e-01
-4.36585635e-01 -3.08113527e-02 -9.83449519e-02 4.40696120e-01
2.79868692e-01 -3.34315389e-01 -8.92888725e-01 9.58417416e-01
-1.89568377e+00 -6.37382150e-01 -1.50905624e-02 2.24429774e+00
6.98176801e-01 5.95947862e-01 2.20953971e-01 1.19524963e-01
1.25210309e+00 3.30108076e-01 -7.91220009e-01 -3.95638019e-01
1.99548658e-02 3.90784219e-02 2.19382659e-01 1.64569914e-01
-1.32452595e+00 1.35345566e+00 5.61880684e+00 1.30104077e+00
-1.06924260e+00 1.81271151e-01 5.78633249e-01 -9.45148468e-02
8.99063945e-02 4.50136103e-02 -1.20239389e+00 4.04265702e-01
5.36861181e-01 -3.73882018e-02 -1.00807294e-01 1.08231211e+00
-2.22902726e-02 -3.82567078e-01 -9.30125356e-01 7.76930571e-01
2.29776189e-01 -9.53744113e-01 1.25898764e-01 -5.70239663e-01
1.09551930e+00 -1.98794335e-01 -1.54036850e-01 6.02108717e-01
-2.87774861e-01 -5.03413975e-01 6.94996417e-01 3.48459750e-01
4.63965774e-01 -8.04870963e-01 4.89942193e-01 4.01723683e-01
-1.18799090e+00 -6.66282326e-02 -5.53618610e-01 2.31917948e-01
9.88561735e-02 6.30367577e-01 -8.62033606e-01 3.94956559e-01
5.41384339e-01 6.73729956e-01 -7.01697469e-01 1.55175543e+00
4.14591981e-03 5.16570449e-01 -1.50062203e-01 -6.14258610e-02
6.02344036e-01 -4.78761755e-02 7.33930528e-01 1.16688466e+00
-5.27504496e-02 -4.00579944e-02 4.47365671e-01 9.80365396e-01
1.91425756e-01 2.25264296e-01 8.51893681e-04 -1.27326116e-01
3.61873239e-01 9.92519617e-01 -1.43751204e+00 -6.85543001e-01
-2.26554960e-01 1.02272785e+00 2.25028515e-01 1.95403844e-01
-9.56992865e-01 -8.06723416e-01 5.37844121e-01 1.81551725e-01
5.93069077e-01 5.13242371e-02 -3.20542961e-01 -9.79660571e-01
-3.07685025e-02 -4.17568594e-01 6.82877243e-01 -3.77883404e-01
-1.06708634e+00 3.61006707e-01 2.19654173e-01 -1.22577739e+00
8.74120221e-02 -2.08669662e-01 -6.65843427e-01 3.87470335e-01
-1.39191365e+00 -1.15973914e+00 -3.82281691e-01 1.75463274e-01
1.08054125e+00 1.81687370e-01 3.05832505e-01 4.37008202e-01
-7.05940545e-01 6.59660339e-01 1.77881613e-01 -6.12077564e-02
6.15505397e-01 -1.29678929e+00 3.05756867e-01 9.99559402e-01
-1.02084577e-01 2.19885230e-01 8.14282179e-01 -7.84173667e-01
-4.73183632e-01 -1.28045118e+00 4.99646574e-01 -4.67527192e-03
1.57451034e-01 -2.40253314e-01 -1.25418508e+00 1.93955705e-01
-4.07648116e-01 1.61604017e-01 3.18545491e-01 -1.74474299e-01
-2.05348387e-01 2.03931201e-02 -1.25974250e+00 6.61365867e-01
9.88413751e-01 -2.26141214e-01 -6.56454802e-01 3.08959872e-01
7.57287979e-01 -3.73932749e-01 -4.20684040e-01 6.55842125e-01
2.37360626e-01 -9.40225005e-01 8.16772640e-01 -4.15985703e-01
2.92551219e-01 -4.19096828e-01 5.87727390e-02 -1.21084440e+00
-6.54007355e-03 -8.17052647e-02 -1.51945964e-01 1.49405074e+00
1.55812770e-01 -3.56880128e-01 1.06892824e+00 5.38196802e-01
-5.43326914e-01 -7.46142507e-01 -9.76064801e-01 -9.42251980e-01
-1.82682741e-02 -3.16572368e-01 2.77797043e-01 9.75866497e-01
-4.11426127e-01 3.10948566e-02 -4.00360040e-02 -4.72062342e-02
5.71174383e-01 2.77099341e-01 5.45509100e-01 -1.12872696e+00
-2.40053758e-01 -5.65412045e-01 -6.49933577e-01 -9.06704664e-01
5.46807609e-02 -8.09406638e-01 6.28156006e-01 -1.64048731e+00
3.95853758e-01 -6.21432781e-01 -4.23202485e-01 3.41104358e-01
-5.66551149e-01 4.04343069e-01 1.85892969e-01 5.68360649e-02
-9.59286392e-01 6.49547517e-01 1.25470781e+00 -2.86284328e-01
-5.62574387e-01 1.87683925e-01 -3.07018548e-01 7.76649714e-01
5.20356953e-01 -5.67366540e-01 -5.83411276e-01 3.28223556e-02
-4.80478346e-01 -3.61221671e-01 9.46620256e-02 -1.48880434e+00
2.79102415e-01 -1.62125036e-01 2.64766999e-02 -8.57891321e-01
2.98396856e-01 -4.60747719e-01 -1.28967732e-01 5.22353351e-01
-3.84259164e-01 -8.72620463e-01 1.65842831e-01 7.83041000e-01
-2.18543574e-01 -7.01863587e-01 1.42729592e+00 -8.28194544e-02
-1.37620401e+00 2.95145482e-01 -4.18096222e-02 5.16901076e-01
1.38882172e+00 -7.41656363e-01 -1.32258683e-01 3.35637540e-01
-8.70104671e-01 4.09261674e-01 5.05642354e-01 6.26539171e-01
5.03553152e-01 -8.62676024e-01 -3.82888824e-01 1.47716239e-01
4.90782917e-01 2.87794620e-01 6.33587420e-01 7.51754701e-01
-5.72201550e-01 8.99414197e-02 -1.65162101e-01 -7.47360051e-01
-1.25559223e+00 5.77989757e-01 5.47288120e-01 -4.79315333e-02
-6.94376171e-01 1.07754135e+00 3.59466970e-01 -3.57487231e-01
4.19739932e-01 -1.75684422e-01 -5.84512234e-01 4.70643729e-01
4.78267103e-01 6.27153099e-01 -1.40074836e-02 -6.78793848e-01
-2.16843471e-01 5.79999924e-01 -3.68745357e-01 3.56997281e-01
9.26149786e-01 -1.73471004e-01 3.35686624e-01 8.13936412e-01
1.19922006e+00 -4.82626826e-01 -1.49671793e+00 -1.24145702e-01
1.81285471e-01 -5.01193464e-01 4.43977341e-02 -6.90895021e-01
-9.61675763e-01 1.00456190e+00 8.61472726e-01 -1.91255733e-02
9.60109770e-01 -1.05158955e-01 1.12254226e+00 1.73486881e-02
4.06496972e-01 -1.72146726e+00 7.24359676e-02 4.69124943e-01
2.31039032e-01 -1.25461674e+00 -1.06731139e-01 -7.46711969e-01
-6.84980392e-01 8.69786322e-01 8.38012516e-01 -3.67401950e-02
4.38586116e-01 -2.59983748e-01 -1.03980891e-01 -7.17991889e-02
-1.50244877e-01 -5.39461017e-01 4.11263704e-01 6.09445989e-01
7.86755085e-02 5.41439690e-02 -7.21234798e-01 5.89600325e-01
3.80644470e-01 -5.77109382e-02 4.45396632e-01 1.04147482e+00
-8.52574468e-01 -7.14219511e-01 -8.69166851e-02 6.60079896e-01
-3.65620047e-01 7.30492100e-02 -2.47312248e-01 6.74485385e-01
4.32540864e-01 8.25652897e-01 2.67603278e-01 -1.28343821e-01
4.78195786e-01 3.22558939e-01 4.30640489e-01 -9.63213980e-01
-4.54770416e-01 1.16072141e-01 -1.50642861e-02 -2.37024322e-01
-4.25581783e-01 -5.42944729e-01 -1.45436442e+00 2.03578815e-01
-7.71655202e-01 3.42455715e-01 5.43085158e-01 9.24659789e-01
8.04494768e-02 6.82762444e-01 3.53159159e-01 -7.62465656e-01
-5.66413879e-01 -7.69302607e-01 -8.55030000e-01 6.31936193e-01
-1.27916336e-01 -9.19485688e-01 -4.13492918e-01 -1.98607236e-01] | [9.522047996520996, 1.5550899505615234] |
bd6549b0-d9cf-44fd-86b7-2b62a2b6256e | layoutdiffuse-adapting-foundational-diffusion | 2302.08908 | null | https://arxiv.org/abs/2302.08908v1 | https://arxiv.org/pdf/2302.08908v1.pdf | LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation | Layout-to-image generation refers to the task of synthesizing photo-realistic images based on semantic layouts. In this paper, we propose LayoutDiffuse that adapts a foundational diffusion model pretrained on large-scale image or text-image datasets for layout-to-image generation. By adopting a novel neural adaptor based on layout attention and task-aware prompts, our method trains efficiently, generates images with both high perceptual quality and layout alignment, and needs less data. Experiments on three datasets show that our method significantly outperforms other 10 generative models based on GANs, VQ-VAE, and diffusion models. | ['Mu Li', 'Tianjun Xiao', 'Tong He', 'Xingjian Shi', 'Xiao Liang', 'Jiaxin Cheng'] | 2023-02-16 | null | null | null | null | ['layout-to-image-generation'] | ['computer-vision'] | [ 3.79134357e-01 2.45087624e-01 2.65476257e-01 -2.48783290e-01
-6.83943391e-01 -5.97546935e-01 7.12421358e-01 -5.12755275e-01
1.16937652e-01 6.62120163e-01 4.25685912e-01 -3.95377070e-01
2.02096984e-01 -1.00973654e+00 -1.10065746e+00 -3.99507225e-01
5.22690773e-01 3.78303856e-01 -6.11689687e-02 -4.47182357e-02
3.41095805e-01 2.48397887e-01 -1.05064452e+00 3.97897661e-01
1.05416918e+00 8.86795938e-01 5.65318882e-01 8.14520180e-01
-4.17295694e-01 8.86329710e-01 -1.03218853e+00 -5.24420083e-01
1.57575786e-01 -8.50119054e-01 -6.61206603e-01 3.14115673e-01
7.60854542e-01 -5.43314159e-01 -3.32719892e-01 7.06993043e-01
7.29190707e-01 -5.76505624e-02 8.47750425e-01 -1.35335982e+00
-1.88088691e+00 5.47375560e-01 -5.95573127e-01 -2.43523210e-01
3.23235750e-01 7.18800485e-01 6.32221580e-01 -8.61074865e-01
9.07686710e-01 1.34992564e+00 3.62025291e-01 8.21877658e-01
-1.50607395e+00 -5.01882195e-01 1.20336741e-01 -2.09666286e-02
-1.36078227e+00 -2.99669802e-01 1.04496610e+00 -4.04210895e-01
8.87468398e-01 2.65942346e-02 8.13298702e-01 1.81870174e+00
2.26495788e-01 7.81081796e-01 1.08358681e+00 -3.25050086e-01
3.97331417e-01 -1.68047905e-01 -8.21527123e-01 5.31132936e-01
1.49316788e-01 7.82528222e-02 -4.20875758e-01 3.31173390e-01
1.21290100e+00 -2.75877506e-01 -1.69297457e-01 -2.92922974e-01
-1.24645782e+00 6.90948904e-01 7.18497097e-01 -6.37729019e-02
-5.09325325e-01 5.27768373e-01 2.81945802e-02 -8.91712531e-02
5.43359101e-01 7.78952479e-01 5.97769096e-02 4.87768382e-04
-8.71636331e-01 3.17646831e-01 3.96590054e-01 1.45275593e+00
6.22988164e-01 6.05179608e-01 -8.14152241e-01 7.45328903e-01
1.18759438e-01 1.01955247e+00 2.39937887e-01 -1.10114360e+00
5.79839289e-01 4.60171938e-01 2.08644524e-01 -8.33091795e-01
1.10628344e-02 -1.94905624e-01 -1.16985738e+00 5.25790490e-02
-3.34885061e-01 -3.44377369e-01 -1.28203118e+00 1.61485040e+00
-1.34444535e-01 1.11446634e-01 -1.53020453e-02 7.54515886e-01
9.44070756e-01 8.77868772e-01 9.06107202e-02 1.67033702e-01
7.79284120e-01 -1.50710535e+00 -1.01384687e+00 -3.56959671e-01
1.88956916e-01 -7.65035927e-01 1.44624841e+00 2.67027527e-01
-1.28014445e+00 -8.93121004e-01 -9.94609952e-01 -2.01285139e-01
-3.71198356e-01 2.83582479e-01 5.06633103e-01 5.86886883e-01
-1.66246831e+00 1.29111528e-01 -1.95452809e-01 -2.69595057e-01
7.56789684e-01 -2.83619970e-01 -8.37849155e-02 -2.49787822e-01
-7.21805274e-01 5.20021856e-01 4.18195486e-01 9.14470777e-02
-1.18181574e+00 -6.34171069e-01 -9.92137015e-01 -2.61050779e-02
1.51010409e-01 -1.35323012e+00 1.10708547e+00 -1.06206965e+00
-1.82661092e+00 4.64803159e-01 -8.17072690e-02 -3.06773692e-01
6.12123609e-01 -9.90402177e-02 -2.34973043e-01 5.58330864e-03
1.35665938e-01 1.53599000e+00 1.02213120e+00 -1.73279524e+00
-9.14185271e-02 2.74073452e-01 6.56803772e-02 1.77410990e-01
-2.61243463e-01 -5.21869302e-01 -6.03162289e-01 -7.79617727e-01
-5.55392921e-01 -6.89501882e-01 -3.78761500e-01 -6.31281808e-02
-9.18847382e-01 -9.97336954e-03 9.03815687e-01 -6.55951679e-01
1.05404985e+00 -2.10347366e+00 2.56970972e-01 4.12269942e-02
2.45673224e-01 2.15934873e-01 -8.51170838e-01 7.01690495e-01
1.23447530e-01 5.61818004e-01 -8.98288339e-02 -5.61819196e-01
3.60902958e-02 2.09293008e-01 -4.85307693e-01 -2.71651059e-01
4.29860085e-01 1.73051059e+00 -9.60566580e-01 -4.95784134e-01
4.48374867e-01 5.04543006e-01 -6.94530427e-01 6.44786179e-01
-5.84696829e-01 6.17373049e-01 -1.50252774e-01 4.22510266e-01
7.44803131e-01 -3.65834504e-01 5.99297099e-02 -2.96969444e-01
1.81232661e-01 -1.41686633e-01 -5.03178179e-01 2.29341340e+00
-7.40948319e-01 8.09741318e-01 -5.40139616e-01 -4.25860077e-01
1.07983732e+00 -4.80433777e-02 -2.85193212e-02 -1.22477472e+00
3.76071110e-02 -1.42207131e-01 -3.68485242e-01 -3.71513247e-01
7.53784895e-01 5.25057435e-01 1.28572136e-02 4.68875736e-01
5.19596972e-03 -6.16059542e-01 2.62037873e-01 4.82518762e-01
9.56718862e-01 4.42620695e-01 -1.89983040e-01 -1.07936360e-01
-2.00613607e-02 -2.99594671e-01 -4.45876271e-02 8.70520413e-01
4.08456892e-01 1.13087761e+00 5.28010666e-01 -2.94566572e-01
-1.64216959e+00 -1.39127576e+00 5.67226708e-01 4.82750028e-01
1.60034329e-01 -5.39121330e-01 -1.20327091e+00 -6.88473582e-01
-3.63716960e-01 1.01442266e+00 -8.97318006e-01 -1.30870789e-01
-3.34767848e-01 -2.44622022e-01 4.05786604e-01 7.27260232e-01
7.58343816e-01 -1.42013681e+00 -3.37717742e-01 4.94152233e-02
-2.57285267e-01 -1.21267807e+00 -7.57477164e-01 -4.69804972e-01
-6.13024116e-01 -6.13253355e-01 -1.08485758e+00 -8.30763698e-01
1.11648965e+00 4.07091171e-01 1.48848116e+00 -2.93975025e-02
-3.33637506e-01 3.08445543e-01 -4.48806822e-01 -3.16314906e-01
-4.92183685e-01 1.46882102e-01 -5.39904773e-01 3.94294597e-03
-4.35775489e-01 -5.08864999e-01 -9.16097820e-01 6.81230277e-02
-1.28470516e+00 7.41714001e-01 9.45111632e-01 9.11956429e-01
6.87998950e-01 -1.30096421e-01 4.96867806e-01 -9.20385599e-01
9.77983773e-01 -2.79154867e-01 -4.39535618e-01 3.74151379e-01
-6.31763697e-01 1.78080171e-01 6.99349523e-01 -5.48432946e-01
-1.24873054e+00 -1.33463860e-01 -1.75653175e-01 -7.54420102e-01
-2.01420724e-01 1.09057568e-01 -5.25170386e-01 1.19940959e-01
7.30260611e-01 5.63013732e-01 -3.63469332e-01 -2.48541310e-01
1.14385557e+00 4.32882994e-01 6.40564978e-01 -6.44878983e-01
1.01256871e+00 3.37829441e-01 -2.01133206e-01 -5.59521496e-01
-5.06890535e-01 4.44579214e-01 -4.96523112e-01 -2.64444113e-01
1.10702300e+00 -7.94920921e-01 -2.31103137e-01 7.09318876e-01
-1.53029728e+00 -9.94799256e-01 -5.48233747e-01 -2.88651288e-01
-6.40488863e-01 1.43273041e-01 -4.12765324e-01 -5.17851591e-01
-4.73917812e-01 -1.22038126e+00 1.38890493e+00 2.43004248e-01
-1.02957487e-01 -9.17108238e-01 1.48567674e-03 1.67438626e-01
7.69601405e-01 3.69646281e-01 8.56018782e-01 2.70506054e-01
-1.08821213e+00 2.92987198e-01 -6.05661094e-01 4.82646137e-01
2.66013086e-01 2.20008671e-01 -7.17232108e-01 -1.19308814e-01
-7.40501761e-01 -4.81359482e-01 7.85700381e-01 5.25288045e-01
1.71134686e+00 -6.16144121e-01 -1.98814720e-01 9.91464794e-01
1.49058235e+00 3.09231669e-01 1.22356510e+00 5.75394891e-02
1.18665493e+00 3.58755797e-01 1.59641713e-01 3.42762560e-01
6.38989925e-01 5.23011923e-01 4.46297944e-01 -7.36422181e-01
-8.19332600e-01 -1.01634634e+00 1.38005197e-01 7.44643986e-01
2.72269160e-01 -8.71427596e-01 -5.78299701e-01 7.14895546e-01
-1.77751124e+00 -8.75327885e-01 -5.55502139e-02 1.58527529e+00
7.22369611e-01 -1.51080284e-02 -1.02959290e-01 -5.42700469e-01
5.14721572e-01 3.42712760e-01 -6.80623412e-01 -6.20778143e-01
-3.83718848e-01 2.93272078e-01 4.17383522e-01 2.55693406e-01
-6.90484703e-01 1.34386265e+00 7.04105759e+00 9.65087235e-01
-9.65954661e-01 8.43016580e-02 1.12440431e+00 -3.80887538e-02
-9.72913206e-01 -1.10109664e-01 -3.73689622e-01 5.80290914e-01
6.95900500e-01 -4.87642027e-02 7.29656935e-01 7.97545314e-01
3.29723775e-01 1.28718782e-02 -9.09603417e-01 1.20802748e+00
3.59347790e-01 -1.79082811e+00 6.76386237e-01 2.43978783e-01
1.49260008e+00 -4.99873906e-01 6.42222822e-01 8.85351449e-02
7.13244438e-01 -1.34403491e+00 1.06476009e+00 6.41240895e-01
1.28496695e+00 -6.31811678e-01 3.73151720e-01 -8.12150072e-03
-1.04198146e+00 1.56407371e-01 -3.16912621e-01 2.84488112e-01
4.57486957e-01 4.57169861e-01 -7.50238001e-01 6.30005717e-01
4.56475407e-01 7.21026778e-01 -8.79856706e-01 8.52748454e-01
-7.18081117e-01 4.79130119e-01 2.99267322e-01 -1.72337447e-03
3.00259203e-01 -1.20279044e-01 -7.39681646e-02 1.18631744e+00
6.36918426e-01 -2.97516376e-01 -6.57542869e-02 1.57523739e+00
-2.41279960e-01 -1.28927249e-02 -9.99331951e-01 -2.29274243e-01
6.44858420e-01 1.30523252e+00 -6.44672215e-01 -3.67406934e-01
-9.11094621e-03 1.55453050e+00 3.28783900e-01 7.54079521e-01
-1.09689713e+00 -3.98530573e-01 3.90583903e-01 3.03835720e-02
4.64491397e-01 -3.63114685e-01 -4.33268696e-01 -9.02426779e-01
-9.43856835e-02 -8.73049855e-01 -3.21695715e-01 -1.58935964e+00
-1.26795232e+00 9.64873552e-01 -9.69131812e-02 -9.46628451e-01
-4.01910007e-01 -2.59042680e-01 -7.89756954e-01 9.30528283e-01
-1.38209605e+00 -1.78144681e+00 -7.00615585e-01 4.19913888e-01
7.28074431e-01 -1.12429082e-01 6.12329066e-01 2.03612465e-02
-5.06784976e-01 6.61271691e-01 -2.56787390e-01 9.27165225e-02
6.84226096e-01 -1.37821627e+00 1.45168006e+00 8.81298661e-01
2.38919601e-01 3.90446007e-01 3.33972782e-01 -7.32614338e-01
-1.28656411e+00 -1.57184553e+00 4.82897729e-01 -5.93828440e-01
2.17266858e-01 -6.24591291e-01 -4.97714072e-01 5.25470138e-01
1.05189383e+00 -4.15808946e-01 4.02208775e-01 -3.61939579e-01
-4.03016329e-01 -2.89553553e-02 -9.10749793e-01 9.00032699e-01
1.63410187e+00 -4.61684287e-01 -2.18573380e-02 2.67627835e-01
1.15410304e+00 -5.41904330e-01 -5.61445653e-01 3.27340961e-02
2.65451521e-01 -9.72725332e-01 1.09605205e+00 -2.99175620e-01
9.24619198e-01 -2.94231087e-01 1.32786721e-01 -1.80986786e+00
-5.75096071e-01 -8.94423008e-01 1.37947261e-01 1.49264717e+00
3.87459457e-01 -2.68804163e-01 4.69688147e-01 1.51027292e-01
-2.68923968e-01 -5.36749303e-01 -3.25853378e-01 -8.68789554e-01
-8.68345145e-03 -1.52174428e-01 1.15425086e+00 5.96542716e-01
-8.51045370e-01 5.96671939e-01 -6.90361321e-01 -1.93025365e-01
6.24327064e-01 -4.74206135e-02 1.25004089e+00 -5.92464149e-01
-3.07407886e-01 -6.11497760e-01 -1.38674947e-02 -1.34727430e+00
2.60204852e-01 -5.25635004e-01 1.88619897e-01 -2.23951697e+00
1.52728468e-01 -2.68028736e-01 1.34968206e-01 4.06927258e-01
-1.69969976e-01 4.41670656e-01 2.15830952e-01 -6.66844770e-02
-6.95523024e-01 9.04886305e-01 1.82166338e+00 -4.40443099e-01
-1.52620804e-02 -6.69383943e-01 -9.59699750e-01 1.97258919e-01
6.41663730e-01 2.28674337e-02 -1.00112224e+00 -9.47240770e-01
4.52352643e-01 -1.76362433e-02 3.56445581e-01 -9.59619105e-01
-7.82403499e-02 -3.25087011e-01 7.30186284e-01 -5.92354238e-01
3.51749659e-01 -3.65186423e-01 5.12487590e-01 1.91004649e-01
-5.86223543e-01 3.84221137e-01 1.76637813e-01 6.40361726e-01
3.12069375e-02 1.80089071e-01 4.86983716e-01 -1.53698087e-01
-8.02841961e-01 3.88868541e-01 -7.90066719e-02 1.93914130e-01
1.00441980e+00 -1.79461136e-01 -7.88399458e-01 -6.72899485e-01
-1.48342103e-01 -1.01274364e-02 8.44920099e-01 7.79109776e-01
1.05676270e+00 -1.78029060e+00 -8.09854925e-01 3.52570474e-01
3.35567474e-01 1.21030524e-01 5.75522840e-01 1.42835528e-01
-6.81872547e-01 4.54424530e-01 -3.67197037e-01 -5.28841197e-01
-6.53640866e-01 7.32693672e-01 1.12834461e-02 -1.03433065e-01
-4.56488192e-01 9.99498725e-01 7.26637959e-01 -2.24295616e-01
-1.10604972e-01 -3.98008078e-01 2.95389026e-01 -4.16176915e-01
4.60308373e-01 -7.88915306e-02 -2.74521708e-01 -3.46124351e-01
1.02560431e-01 3.77261907e-01 1.08447224e-01 -3.66688341e-01
9.14814413e-01 -9.42517072e-02 1.04354106e-01 2.53821258e-03
1.01583648e+00 -1.33801296e-01 -1.80339229e+00 5.77824451e-02
-5.84482968e-01 -6.86229646e-01 -8.37038159e-02 -1.14169014e+00
-1.29446793e+00 9.65018928e-01 4.09254134e-01 -4.04222757e-02
1.28687334e+00 -1.04111917e-01 1.02649832e+00 -7.49551952e-02
3.62378567e-01 -9.55701828e-01 9.06792343e-01 2.05624685e-01
1.27905035e+00 -9.22732711e-01 -4.69569355e-01 -1.53620377e-01
-1.02789032e+00 7.42558002e-01 1.08914518e+00 -1.01333618e-01
1.02613024e-01 2.66556710e-01 1.65364310e-01 8.52437392e-02
-9.23761010e-01 -1.36808708e-01 4.25222844e-01 1.28154361e+00
1.35354504e-01 1.55515805e-01 1.46062374e-01 1.60626963e-01
-2.28116870e-01 4.31616651e-03 5.81214190e-01 4.97606903e-01
-2.77493037e-02 -1.23239326e+00 -1.64475050e-02 1.89573273e-01
2.33938411e-01 -4.54225302e-01 -6.68596506e-01 5.24722219e-01
1.96336612e-01 8.30970228e-01 2.44971111e-01 -5.95851541e-01
2.47112468e-01 -3.59871984e-01 6.65278852e-01 -4.59851474e-01
-2.23541260e-01 3.81646901e-02 -2.28145737e-02 -7.39581704e-01
-2.70388037e-01 -1.59186229e-01 -6.48711920e-01 -3.71862769e-01
4.09520417e-02 -3.14621210e-01 8.37934673e-01 5.80506146e-01
9.61772203e-01 1.06437540e+00 6.30342603e-01 -9.62557197e-01
-1.29395157e-01 -1.00673914e+00 -3.32286000e-01 5.44643104e-01
-1.04432575e-01 -3.49111289e-01 1.85073674e-01 3.10354561e-01] | [11.471221923828125, -0.30291691422462463] |
c7d2b3ca-49f7-4990-8bcb-1a7384a99653 | diffg-rl-leveraging-difference-between-state | 2211.16002 | null | https://arxiv.org/abs/2211.16002v1 | https://arxiv.org/pdf/2211.16002v1.pdf | DiffG-RL: Leveraging Difference between State and Common Sense | Taking into account background knowledge as the context has always been an important part of solving tasks that involve natural language. One representative example of such tasks is text-based games, where players need to make decisions based on both description text previously shown in the game, and their own background knowledge about the language and common sense. In this work, we investigate not simply giving common sense, as can be seen in prior research, but also its effective usage. We assume that a part of the environment states different from common sense should constitute one of the grounds for action selection. We propose a novel agent, DiffG-RL, which constructs a Difference Graph that organizes the environment states and common sense by means of interactive objects with a dedicated graph encoder. DiffG-RL also contains a framework for extracting the appropriate amount and representation of common sense from the source to support the construction of the graph. We validate DiffG-RL in experiments with text-based games that require common sense and show that it outperforms baselines by 17% of scores. The code is available at https://github.com/ibm/diffg-rl | ['Michiaki Tatsubori', 'Daiki Kimura', 'Tsunehiko Tanaka'] | 2022-11-29 | null | null | null | null | ['text-based-games', 'common-sense-reasoning'] | ['playing-games', 'reasoning'] | [ 2.40224168e-01 2.95125157e-01 -9.18178260e-02 -2.07191601e-01
-5.99334061e-01 -8.43469799e-01 7.73716509e-01 5.66058636e-01
-6.43928170e-01 4.57247317e-01 6.61126852e-01 -4.31133598e-01
7.47196898e-02 -1.12232685e+00 -5.69675088e-01 -1.82922661e-01
2.48279467e-01 4.08050060e-01 6.40977919e-01 -7.10900486e-01
3.06502044e-01 -2.89001405e-01 -1.34007013e+00 5.83232641e-01
7.26617038e-01 4.33718085e-01 6.41273677e-01 6.42904103e-01
-3.22308630e-01 1.13739741e+00 -7.35474825e-01 -7.43041217e-01
1.89462274e-01 -8.38720441e-01 -1.16733265e+00 2.73304693e-02
-4.85607907e-02 -1.54738845e-02 -2.64568508e-01 1.15394807e+00
4.12265569e-01 5.51892221e-01 3.79669458e-01 -1.10964620e+00
-3.11488748e-01 1.30632913e+00 -1.65969640e-01 2.62977302e-01
8.39074194e-01 4.80724871e-01 1.47774851e+00 -4.31873679e-01
9.48046505e-01 1.27519059e+00 2.76524574e-01 6.31843686e-01
-1.02825129e+00 -2.46075839e-01 5.32810688e-01 3.07851642e-01
-1.23445415e+00 -3.10206145e-01 7.41577566e-01 -3.86759549e-01
1.22801208e+00 2.58386463e-01 9.32420790e-01 9.87945795e-01
1.18988864e-01 8.61917555e-01 1.00181031e+00 -7.08952546e-01
4.28569376e-01 -6.52853027e-02 2.46275395e-01 8.33850920e-01
2.23350793e-01 -1.88413665e-01 -8.30754161e-01 -2.05412861e-02
4.89707321e-01 -3.10775548e-01 -1.85564294e-01 -3.48433793e-01
-8.57548594e-01 6.95373297e-01 1.69435769e-01 5.51910281e-01
-2.76267201e-01 2.76257485e-01 3.36544722e-01 2.92008966e-01
2.94696450e-01 7.58902490e-01 -2.56343961e-01 -4.72203761e-01
-4.62245464e-01 3.84569257e-01 9.94201720e-01 9.85229671e-01
7.01833963e-01 -5.53053856e-01 -3.76755357e-01 5.92622161e-01
3.32453638e-01 1.67300418e-01 6.00708127e-01 -8.48713219e-01
6.36171937e-01 9.99452412e-01 1.08999602e-01 -1.02617121e+00
-3.24625432e-01 -4.59992915e-01 -3.14172834e-01 4.01021726e-03
6.13294005e-01 -1.92683443e-01 -4.79929537e-01 2.07365465e+00
2.88897902e-01 3.27131838e-01 2.75089204e-01 5.99238932e-01
8.89547050e-01 4.65719551e-01 1.43812224e-01 8.57510492e-02
1.32153523e+00 -6.96218193e-01 -6.53769314e-01 -8.96606445e-01
1.06853855e+00 -2.24880785e-01 1.42690969e+00 2.92422116e-01
-8.90381515e-01 -9.10649821e-02 -1.03105199e+00 -1.84488043e-01
-4.41231698e-01 -9.59079489e-02 5.23577869e-01 3.46599340e-01
-1.08801937e+00 5.79242229e-01 -4.35347855e-01 -6.28185213e-01
-1.55332629e-02 -2.77421977e-02 -2.68719077e-01 3.10265608e-02
-1.58510447e+00 9.22295749e-01 8.59660268e-01 -1.16373941e-01
-5.31189561e-01 -2.44546145e-01 -1.27885401e+00 1.01308644e-01
1.25146115e+00 -7.54495084e-01 1.59230113e+00 -8.01317990e-01
-1.48077583e+00 9.18834031e-01 -7.15994984e-02 -4.55269665e-01
3.14171374e-01 -2.41341025e-01 -6.98918551e-02 -1.27679601e-01
3.08767229e-01 1.56682253e-01 3.83278519e-01 -8.16858053e-01
-7.68998921e-01 -3.43263656e-01 7.95433879e-01 5.74512303e-01
1.96261093e-01 2.58649532e-02 -7.57763863e-01 -4.58888590e-01
-1.39355734e-01 -9.94144201e-01 -5.16603231e-01 -4.59873289e-01
-6.41868174e-01 -2.75019765e-01 1.48393795e-01 -5.28727114e-01
1.69158614e+00 -1.92920411e+00 2.36406043e-01 2.40328833e-01
3.75999808e-01 1.01644002e-01 -1.33579761e-01 8.51141453e-01
7.68846497e-02 3.81604105e-01 -5.02964854e-02 -1.65668979e-01
2.82516152e-01 1.98364526e-01 -1.61700204e-01 1.79610364e-02
-7.85242170e-02 8.50426078e-01 -1.26147306e+00 -2.26573616e-01
6.88921064e-02 -3.05715576e-02 -8.29317331e-01 8.31325501e-02
-6.67938650e-01 2.49234393e-01 -5.23294151e-01 -1.46828890e-01
-6.25725975e-03 -4.05862957e-01 6.05865717e-01 1.39353916e-01
5.15575819e-02 9.73181546e-01 -1.48875999e+00 2.05954456e+00
-5.50818443e-01 4.33169752e-01 -3.34101349e-01 -7.17683733e-01
5.58187246e-01 4.14029956e-02 -1.27645989e-03 -6.75948441e-01
3.08727175e-02 -4.87844348e-02 3.51458341e-01 -5.19968092e-01
6.61851287e-01 -3.13687418e-03 -5.06945312e-01 6.89519584e-01
6.10308759e-02 -3.12455505e-01 5.80868244e-01 8.03172648e-01
1.38782239e+00 1.65637046e-01 7.70020187e-01 -1.71716437e-01
4.75603849e-01 -2.68289931e-02 6.20421946e-01 1.02220774e+00
1.49731562e-01 2.22040594e-01 9.54672217e-01 -2.64125735e-01
-4.54109401e-01 -4.79791909e-01 8.15671325e-01 1.18971348e+00
3.81950498e-01 -1.46393526e+00 -6.42065108e-01 -7.22181499e-01
-4.92579043e-01 1.18512201e+00 -6.56034410e-01 -4.11112964e-01
-3.60561073e-01 -7.98767284e-02 4.20789957e-01 4.26271945e-01
5.98341167e-01 -1.28943002e+00 -8.94241095e-01 2.06319958e-01
-5.26696920e-01 -1.15565836e+00 -5.38073719e-01 1.86778098e-01
-2.95158178e-01 -1.17930710e+00 1.38159171e-01 -3.17531079e-01
2.16551766e-01 1.33233994e-01 1.49984050e+00 3.88489753e-01
7.94858336e-02 5.50126493e-01 -6.89521611e-01 -5.01442790e-01
-5.22916257e-01 1.86934933e-01 -3.68259698e-01 -1.50808871e-01
3.92128348e-01 -4.98675406e-01 -1.94214761e-01 -2.51991749e-02
-9.36263323e-01 4.89028007e-01 3.00177932e-01 5.06399810e-01
4.73167539e-01 3.08804184e-01 -8.30766708e-02 -1.41232407e+00
9.97920692e-01 -4.44064498e-01 -4.89392489e-01 2.54497319e-01
-2.32158497e-01 3.66940945e-01 3.65212023e-01 -5.31890709e-03
-9.80502069e-01 -3.79241183e-02 -1.67315006e-01 1.45351276e-01
-1.52206436e-01 9.27205086e-01 -4.82707173e-01 6.87635958e-01
7.82774746e-01 3.88249010e-01 -2.71434277e-01 -2.35655606e-01
6.44956589e-01 3.55781466e-01 1.96299687e-01 -9.32170153e-01
5.89481294e-01 7.02786073e-02 -2.57748991e-01 -6.50523722e-01
-1.05067110e+00 -5.84531188e-01 -4.82321501e-01 -1.69462591e-01
8.53447020e-01 -6.34841502e-01 -5.98874509e-01 3.12294215e-01
-1.21759140e+00 -9.61974442e-01 -4.22481894e-01 8.00820962e-02
-6.74034655e-01 1.76191136e-01 -3.05425793e-01 -8.36108625e-01
-2.13016220e-03 -1.22599196e+00 7.78273880e-01 2.09355697e-01
-4.95801508e-01 -1.02015364e+00 -4.60429601e-02 8.02551955e-02
8.50066990e-02 5.29284813e-02 8.99486005e-01 -1.11534452e+00
-3.73863697e-01 8.98673087e-02 3.80370289e-01 -1.84465304e-01
2.72709489e-01 -2.71712035e-01 -6.74867570e-01 4.83775437e-02
-2.48267040e-01 -2.17729479e-01 8.00048411e-01 1.10389955e-01
8.96788538e-01 -5.19164324e-01 -3.61422271e-01 1.42151669e-01
1.35857940e+00 2.93105453e-01 6.99646592e-01 4.32023287e-01
4.95434374e-01 6.22041583e-01 5.84075928e-01 5.35008073e-01
7.78094351e-01 9.25085187e-01 3.65860581e-01 2.88336247e-01
-2.08985612e-01 -6.48243308e-01 4.68171895e-01 4.36535835e-01
1.41870361e-02 -6.02979362e-01 -1.00378120e+00 6.22193813e-01
-1.95598674e+00 -1.30232358e+00 1.10710591e-01 2.06864595e+00
9.79490340e-01 3.95479292e-01 2.92875111e-01 1.60190538e-02
7.26281762e-01 3.50129992e-01 -4.11630303e-01 -3.84032547e-01
4.97134253e-02 1.70342505e-01 1.75216705e-01 9.00826097e-01
-9.48964596e-01 1.37903619e+00 4.75683975e+00 8.15854132e-01
-7.27759004e-01 4.13851067e-02 2.46147320e-01 1.31569147e-01
-4.72111106e-01 3.02892745e-01 -6.50739372e-01 3.25333893e-01
5.40706277e-01 -5.07490695e-01 4.30875242e-01 5.40591419e-01
1.06104247e-01 -3.69602382e-01 -1.11359549e+00 7.88586020e-01
-5.67990020e-02 -1.21238625e+00 -3.78060453e-02 -7.33725820e-03
2.21372128e-01 -7.35620782e-02 -2.69008309e-01 4.93704110e-01
1.03516173e+00 -7.07205117e-01 1.11074412e+00 3.00071985e-01
5.47616363e-01 -5.19895077e-01 5.32706678e-01 6.20409787e-01
-1.35840333e+00 1.06621045e-03 -1.72860697e-01 -4.47162062e-01
-1.92970470e-01 3.10106754e-01 -8.32173407e-01 7.11060941e-01
4.29850698e-01 9.53757405e-01 -5.71138918e-01 8.42791378e-01
-1.03968692e+00 7.09423423e-01 -2.62116492e-01 -3.32846135e-01
2.68063515e-01 -4.68566082e-02 8.80856574e-01 1.11784089e+00
1.81994095e-01 4.92090404e-01 6.38903737e-01 9.49360430e-01
-9.49252397e-02 2.52817541e-01 -9.11110044e-01 -2.74507314e-01
6.05941772e-01 8.99836540e-01 -6.87892079e-01 -4.48531717e-01
-4.42077935e-01 9.29528952e-01 3.40754628e-01 2.36314610e-01
-4.47500616e-01 -4.10845548e-01 7.84927189e-01 1.60215691e-01
1.75044075e-01 -1.74010113e-01 9.58982557e-02 -1.39384663e+00
7.72685036e-02 -9.16352332e-01 8.71774554e-01 -8.35969269e-01
-8.95308673e-01 6.31677508e-01 9.41005349e-02 -1.03908360e+00
-4.93312746e-01 -5.03936708e-01 -7.25139439e-01 8.02162528e-01
-1.15368676e+00 -8.91416669e-01 -9.76301432e-02 5.90074062e-01
7.62117326e-01 3.38240038e-03 6.68246567e-01 -3.20461333e-01
-5.36183000e-01 2.57392168e-01 -8.21476519e-01 4.38803822e-01
4.15024996e-01 -1.52872097e+00 7.44369149e-01 1.30720711e+00
6.17998898e-01 7.57042170e-01 9.60250735e-01 -9.15190458e-01
-1.26521969e+00 -9.29440856e-01 8.70370746e-01 -4.64431167e-01
7.37045705e-01 -3.68653804e-01 -7.21594214e-01 9.38135445e-01
4.08187807e-01 -2.77746677e-01 9.04955208e-01 2.22163722e-01
-4.36449409e-01 2.22526520e-01 -7.75487602e-01 1.00213659e+00
1.53645837e+00 -5.42201221e-01 -9.04972792e-01 1.49471015e-01
7.01957524e-01 -8.55682790e-01 -1.99130982e-01 -3.61388892e-01
8.97069648e-02 -9.02390003e-01 4.41167384e-01 -8.18945765e-01
5.24661064e-01 -5.60972571e-01 -2.45547757e-01 -1.87808371e+00
-3.72432470e-01 -8.34384561e-01 1.19432382e-01 1.09039557e+00
6.10903323e-01 -4.77325708e-01 5.22524655e-01 7.81668365e-01
-4.61301506e-02 -4.25829470e-01 -5.21562397e-01 -6.48912489e-01
-6.29068464e-02 -9.68597472e-01 6.95084453e-01 7.66811669e-01
5.68586588e-01 7.29324758e-01 -1.11719199e-01 2.32894331e-01
1.89426854e-01 1.68123782e-01 8.41007531e-01 -1.22183478e+00
-6.93922877e-01 -4.72041696e-01 -3.78740251e-01 -1.15006220e+00
3.86145145e-01 -1.29310775e+00 1.95840076e-01 -2.09460974e+00
1.73911512e-01 -2.65582263e-01 -1.81664586e-01 9.87863779e-01
-3.29265177e-01 -1.35915220e-01 5.45947909e-01 -2.69713312e-01
-1.09984326e+00 2.14944661e-01 1.15454078e+00 -2.34215841e-01
-3.71478170e-01 -1.76349074e-01 -1.27182782e+00 8.78852129e-01
8.53291094e-01 -4.00912672e-01 -7.42044210e-01 -4.94071543e-01
9.11671937e-01 -2.78215427e-02 1.35363489e-01 -9.03050125e-01
4.58333641e-01 -6.23585701e-01 -2.73976117e-01 8.16140771e-02
2.70079911e-01 -6.87144160e-01 -6.94338558e-03 3.79018068e-01
-8.35726023e-01 4.66544665e-02 1.99855238e-01 4.16958094e-01
-3.09592132e-02 -3.44598860e-01 1.96333393e-01 -6.02354765e-01
-1.35963166e+00 2.10063010e-02 -4.66671526e-01 5.63867569e-01
8.18346262e-01 -1.19587436e-01 -1.80640340e-01 -8.34951639e-01
-7.77906179e-01 1.50425598e-01 5.00184000e-01 3.86432230e-01
5.56904256e-01 -1.06190073e+00 -7.06909418e-01 -2.00817361e-01
4.22676444e-01 -8.91821086e-02 -6.70688748e-02 4.36008573e-01
-1.74957260e-01 7.05235675e-02 7.97186121e-02 -5.31938411e-02
-1.28033590e+00 4.70228612e-01 4.95921880e-01 -4.84074622e-01
-7.56787300e-01 8.67745042e-01 3.08058530e-01 -2.25838333e-01
-8.63114670e-02 -6.34806573e-01 -4.63927329e-01 -1.44732192e-01
8.49188745e-01 -6.79680556e-02 1.72944546e-01 -6.57676160e-01
-4.64387506e-01 2.83464640e-01 3.45434286e-02 -3.97371531e-01
1.25262082e+00 -2.05645174e-01 -1.10331811e-01 5.96414983e-01
4.76479441e-01 4.12488550e-01 -8.88570845e-01 -6.17696881e-01
2.62040913e-01 -4.35494959e-01 -7.85763711e-02 -1.13145113e+00
-9.11699951e-01 6.43704236e-01 -1.93100035e-01 4.12689537e-01
9.92059052e-01 3.32667112e-01 3.07915449e-01 6.15647376e-01
8.12820971e-01 -8.82299960e-01 9.43554118e-02 9.39172506e-01
1.04133224e+00 -9.62378919e-01 -2.80285180e-01 -6.57654345e-01
-1.00678563e+00 9.18804348e-01 7.75586843e-01 1.84063669e-02
3.72917980e-01 2.18205720e-01 -5.40376082e-02 -3.68832469e-01
-1.13490534e+00 -7.94571161e-01 2.06216529e-01 6.43935382e-01
5.25667489e-01 1.13554105e-01 -3.60968292e-01 1.16736817e+00
-5.18394351e-01 -8.18633214e-02 8.50549996e-01 1.10150075e+00
-3.88376862e-01 -1.41358924e+00 1.42216146e-01 3.66254121e-01
-4.92981285e-01 -2.82537133e-01 -8.85120928e-01 5.28134823e-01
1.34484336e-01 1.29227221e+00 -1.50627896e-01 -5.63034713e-01
4.92794037e-01 1.58239916e-01 5.16009152e-01 -1.33528483e+00
-7.58943498e-01 -2.42861420e-01 5.10512650e-01 -8.44398618e-01
-3.12475979e-01 -5.20021975e-01 -1.47599089e+00 6.74739899e-03
-9.91553739e-02 3.42966706e-01 1.59211963e-01 1.24568427e+00
2.98911959e-01 4.76417929e-01 -3.57859321e-02 -3.09788704e-01
-1.72947526e-01 -8.38018119e-01 -5.28038442e-01 6.28545761e-01
-3.84115428e-02 -6.53964341e-01 6.21969216e-02 3.24856415e-02] | [3.8051981925964355, 1.322052240371704] |
b7be3329-9443-4c0a-a596-f44f3b192d07 | sensor-fusion-using-backward-shortcut | 1912.06879 | null | https://arxiv.org/abs/1912.06879v2 | https://arxiv.org/pdf/1912.06879v2.pdf | Sensor Fusion using Backward Shortcut Connections for Sleep Apnea Detection in Multi-Modal Data | Sleep apnea is a common respiratory disorder characterized by breathing pauses during the night. Consequences of untreated sleep apnea can be severe. Still, many people remain undiagnosed due to shortages of hospital beds and trained sleep technicians. To assist in the diagnosis process, automated detection methods are being developed. Recent works have demonstrated that deep learning models can extract useful information from raw respiratory data and that such models can be used as a robust sleep apnea detector. However, trained sleep technicians take into account multiple sensor signals when annotating sleep recordings instead of relying on a single respiratory estimate. To improve the predictive performance and reliability of the models, early and late sensor fusion methods are explored in this work. In addition, a novel late sensor fusion method is proposed which uses backward shortcut connections to improve the learning of the first stages of the models. The performance of these fusion methods is analyzed using CNN as well as LSTM deep learning base-models. The results demonstrate a significant and consistent improvement in predictive performance over the single sensor methods and over the other explored sensor fusion methods, by using the proposed sensor fusion method with backward shortcut connections. | ['Tom Dhaene', 'Tom Van Steenkiste', 'Dirk Deschrijver'] | 2019-12-14 | null | null | null | null | ['sleep-apnea-detection'] | ['medical'] | [ 2.65835106e-01 1.05355911e-01 -1.13377152e-02 -6.39546752e-01
-5.19110620e-01 2.61177551e-02 6.67474279e-03 2.10977510e-01
-6.56421244e-01 7.43109226e-01 2.15851828e-01 2.47669592e-02
-1.48123115e-01 -5.76727629e-01 -1.54613748e-01 -7.91611969e-01
2.20703751e-01 2.80771911e-01 2.83037931e-01 -7.42242336e-02
-2.65593886e-01 3.27665716e-01 -1.47143209e+00 2.69080937e-01
8.37344229e-01 1.17169774e+00 3.87658834e-01 7.01325417e-01
-9.70486328e-02 7.31469989e-01 -7.33836651e-01 1.29157603e-01
1.70268461e-01 -5.68093002e-01 -3.34752768e-01 -1.77324474e-01
-1.34020047e-02 -2.60565907e-01 -1.26338944e-01 8.20145130e-01
7.81356752e-01 1.89439997e-01 7.34768733e-02 -9.81759906e-01
-8.55399221e-02 6.12957656e-01 1.04539851e-02 6.62909448e-01
4.38164979e-01 4.07897793e-02 7.16119230e-01 -6.80390418e-01
-3.92186999e-01 6.17777169e-01 8.61232519e-01 7.67773688e-01
-8.70180249e-01 -9.09923911e-01 -1.80667877e-01 4.49157774e-01
-1.27348983e+00 -6.35086954e-01 5.91227055e-01 -2.13229954e-01
1.15401411e+00 1.72156245e-01 1.12998915e+00 1.02117944e+00
3.59267384e-01 3.91806543e-01 7.96571195e-01 -1.63677603e-01
2.39807859e-01 1.72598317e-01 2.58596122e-01 7.59942353e-01
4.92273420e-01 3.67540121e-02 -4.33382124e-01 1.46743491e-01
2.48186588e-01 1.01929200e+00 -2.87289172e-01 2.99242556e-01
-9.22962785e-01 6.80462420e-01 7.92623997e-01 6.40005827e-01
-6.26046002e-01 6.95876256e-02 2.24817604e-01 -1.51320649e-02
2.64339715e-01 4.19576198e-01 -2.82252848e-01 -1.50956362e-01
-1.50531387e+00 -1.98731095e-01 8.43239188e-01 5.16102672e-01
7.31227040e-01 1.20296627e-01 -3.28369468e-01 8.10598552e-01
4.49381441e-01 5.05873561e-01 8.94307077e-01 -9.05104995e-01
3.31147373e-01 1.02319646e+00 -1.77885458e-01 -6.71607554e-01
-9.59911764e-01 -3.97835076e-01 -1.11475194e+00 -5.57608120e-02
-3.11420292e-01 -2.25949943e-01 -1.14670980e+00 1.33258462e+00
-1.05051115e-01 3.55814576e-01 1.16048545e-01 6.31761014e-01
1.03067362e+00 3.80948186e-01 6.34213835e-02 -3.32881063e-01
1.21899199e+00 -1.12943339e+00 -1.08439875e+00 -5.51185668e-01
1.75871074e-01 -3.28602076e-01 5.54426372e-01 3.97490442e-01
-1.09392595e+00 -7.89504588e-01 -1.27790177e+00 5.78866601e-02
-4.70919073e-01 3.63871343e-02 7.65902251e-02 5.25490761e-01
-1.23931777e+00 7.61597872e-01 -1.49063694e+00 -4.73432183e-01
6.88295245e-01 8.67190957e-01 -6.98339269e-02 -2.56441645e-02
-1.06444395e+00 9.67547417e-01 4.33975548e-01 4.95182812e-01
-6.50097191e-01 -3.73637289e-01 -8.64410341e-01 2.90851176e-01
5.98683441e-03 -1.11769736e+00 1.24209034e+00 -4.89636749e-01
-1.20659745e+00 4.37371731e-01 -2.52953738e-01 -9.71336961e-01
1.79903254e-01 -5.29161990e-01 -5.55588663e-01 3.00036043e-01
-1.48266226e-01 4.52851504e-01 7.81786919e-01 -6.59730613e-01
-8.60134661e-01 -4.73359078e-01 -3.18461984e-01 3.95369856e-03
-4.07797128e-01 -2.44564876e-01 -2.39841100e-02 -2.30547428e-01
-4.26310338e-02 -9.33494091e-01 -5.80355227e-01 -9.18716118e-02
-3.08982223e-01 -2.28475869e-01 9.08814371e-01 -6.82970583e-01
1.46550715e+00 -2.10537982e+00 -1.93820998e-01 -1.01405587e-02
6.61393464e-01 7.63520479e-01 4.53917772e-01 2.03637302e-01
1.53816178e-01 1.04325876e-01 -4.87426013e-01 -8.38946462e-01
-3.22279781e-01 8.77645850e-01 2.32888833e-01 3.13346177e-01
3.52431089e-02 7.59137571e-01 -6.78743720e-01 -5.69441199e-01
8.13753068e-01 8.70320797e-01 -2.51368463e-01 7.46962905e-01
2.56758183e-01 4.76274937e-01 -3.19792449e-01 4.74977970e-01
1.62824899e-01 -4.69443232e-01 -3.24846238e-01 -1.61834389e-01
-8.00132453e-02 6.74518406e-01 -6.21084213e-01 1.92545509e+00
-6.32218421e-01 3.48321676e-01 -1.22021750e-01 -9.42053378e-01
7.80391753e-01 7.57603288e-01 7.23450243e-01 -5.91150820e-01
3.38191509e-01 2.65929610e-01 1.56013459e-01 -9.48110998e-01
3.47805861e-03 -4.09436911e-01 3.33874047e-01 8.77716690e-02
-4.28729840e-02 9.58100557e-02 1.16811655e-01 -3.26277107e-01
1.31811023e+00 -3.25401425e-01 5.13763607e-01 1.33196816e-01
6.40569270e-01 -3.59575719e-01 7.50592709e-01 5.79593301e-01
-3.45014691e-01 7.48536885e-01 -4.35362428e-01 -4.65760797e-01
-5.58326781e-01 -8.43788266e-01 3.91189046e-02 5.96203446e-01
-4.14856337e-02 -4.38154459e-01 -5.54276407e-01 -4.80408788e-01
-1.59976557e-01 6.19352520e-01 -5.54217935e-01 -6.22994244e-01
-5.91490448e-01 -8.65040600e-01 6.17321312e-01 1.07726252e+00
7.91519344e-01 -1.35752428e+00 -1.27928424e+00 4.15778518e-01
-2.09450871e-01 -1.14567089e+00 -4.72047962e-02 6.35061443e-01
-9.70710933e-01 -1.15472078e+00 -5.56137145e-01 -4.79063421e-01
2.92156398e-01 1.98965371e-01 7.55704522e-01 4.05686915e-01
-4.66765523e-01 1.83443755e-01 -3.19282591e-01 -6.08968019e-01
-3.21978539e-01 2.41966546e-01 2.01436266e-01 -1.16718829e-01
6.39554620e-01 -8.29939663e-01 -1.16272902e+00 -6.55736551e-02
-7.45866060e-01 -9.92197767e-02 8.64219785e-01 5.63301802e-01
5.81998944e-01 -6.58096895e-02 7.21116304e-01 -6.69555902e-01
5.49426436e-01 -6.20864272e-01 -1.40995830e-01 2.53639799e-02
-1.14180565e+00 -6.64436771e-03 6.96295083e-01 1.90218184e-02
-7.18687117e-01 9.63416100e-02 -7.41970956e-01 -7.56431103e-01
-3.36218476e-01 2.00694323e-01 2.57408261e-01 2.36567974e-01
4.72679317e-01 2.38614082e-01 8.58160406e-02 -6.92645848e-01
-3.27892244e-01 8.49239588e-01 4.38360333e-01 3.43015254e-01
4.63410467e-01 4.05738384e-01 3.49942991e-03 -9.08916175e-01
-1.32309103e+00 -1.00439608e+00 -6.51783526e-01 2.00254675e-02
1.41990268e+00 -9.15182412e-01 -5.85776865e-01 2.22907484e-01
-7.68803775e-01 -2.30355382e-01 -5.10857821e-01 6.58713400e-01
-2.61255831e-01 1.19167328e-01 -3.79113704e-01 -8.35238934e-01
-8.58570993e-01 -1.12178123e+00 9.08058822e-01 5.21223724e-01
-4.95137036e-01 -1.17760468e+00 2.60118216e-01 5.18254459e-01
6.91370070e-01 2.32827663e-01 4.11572665e-01 -1.19752991e+00
-1.83405980e-01 -3.52945656e-01 1.29636945e-02 8.91315639e-01
7.09725201e-01 -2.08769605e-01 -1.23750293e+00 -3.77439350e-01
6.16602123e-01 5.44838235e-02 1.09946024e+00 4.08732265e-01
9.97844577e-01 -3.61212105e-01 -5.14747322e-01 6.91784978e-01
1.30233240e+00 4.60306287e-01 3.15079927e-01 7.24361166e-02
7.53515422e-01 1.41638234e-01 1.94035866e-03 2.61876911e-01
4.33323622e-01 1.91088453e-01 5.63486040e-01 -3.60516608e-01
-2.67954946e-01 1.36770904e-01 3.30822766e-01 1.08576119e+00
-1.17544666e-01 -1.36152178e-01 -8.11161876e-01 4.74897712e-01
-1.82678151e+00 -9.01108980e-01 2.64235791e-02 2.12028646e+00
5.97082973e-01 2.57500470e-01 1.44507602e-01 6.68727398e-01
4.55979794e-01 2.91936006e-03 -5.79096675e-01 -2.83335268e-01
2.67872185e-01 6.86591744e-01 3.73629242e-01 1.38620213e-01
-9.40980017e-01 2.33561993e-01 6.62308502e+00 -6.17004111e-02
-1.17763352e+00 3.74794304e-01 5.89871295e-02 -3.38450581e-01
3.08573365e-01 -4.73157912e-01 -9.12045896e-01 7.67041981e-01
1.52809298e+00 2.45046258e-01 3.70878607e-01 8.44208658e-01
5.40724277e-01 2.56497469e-02 -1.07437825e+00 1.04380441e+00
1.72604129e-01 -1.09546196e+00 -4.54805613e-01 -6.94458410e-02
4.59814847e-01 6.09105647e-01 -3.49200517e-01 2.26347074e-01
-7.92321786e-02 -1.11943710e+00 7.93826506e-02 8.07544053e-01
5.18030286e-01 -5.48979104e-01 1.22224724e+00 2.23390311e-01
-1.33128715e+00 -5.88369548e-01 -1.84090063e-01 -1.06827095e-01
1.85075551e-01 5.99396110e-01 -1.17015254e+00 3.07039022e-01
1.02969563e+00 1.12786615e+00 -8.90505731e-01 1.34550941e+00
-3.75011206e-01 8.31707776e-01 -5.93246639e-01 9.21426564e-02
-3.80394161e-02 1.28615843e-02 3.01129401e-01 1.19216001e+00
5.08264363e-01 -9.59985889e-03 3.36901635e-01 1.01507187e+00
6.88903779e-02 -3.43342602e-01 -6.84598804e-01 -4.49263044e-02
1.54096410e-01 1.33079827e+00 -5.13614595e-01 -2.72022754e-01
-6.62066340e-01 7.44982541e-01 -4.49594222e-02 1.52965501e-01
-7.42663383e-01 -1.93243772e-01 4.67778713e-01 3.46848696e-01
2.99615920e-01 5.54375388e-02 -2.86811590e-01 -8.73834312e-01
-1.86938301e-01 -3.12723160e-01 5.24113715e-01 -6.16444111e-01
-1.06272042e+00 7.60359108e-01 -1.11386843e-01 -1.04464698e+00
-3.77996683e-01 -2.71381527e-01 -9.09212530e-01 5.75094819e-01
-1.66642892e+00 -8.59170437e-01 -7.53319025e-01 8.42525780e-01
7.32433498e-01 -1.97954215e-02 8.77249241e-01 6.37044311e-01
-9.73552763e-01 2.79093087e-01 -3.49137485e-01 1.13659054e-02
4.71492440e-01 -1.38271713e+00 -7.82977939e-02 8.80561531e-01
-1.60627946e-01 6.90428913e-01 4.97716904e-01 -4.20841336e-01
-9.11264360e-01 -1.43778169e+00 9.18218911e-01 -2.46235937e-01
1.55606166e-01 6.56871945e-02 -1.03030431e+00 6.44927204e-01
3.48759651e-01 9.94568169e-02 1.02851164e+00 -2.86100298e-01
3.58142138e-01 -5.75678408e-01 -1.22014666e+00 4.53194370e-03
5.67647994e-01 -2.60151982e-01 -1.04011345e+00 1.28879786e-01
7.33783841e-01 -1.19209431e-01 -7.77388811e-01 6.58193529e-01
4.03625101e-01 -1.18481338e+00 7.52806842e-01 2.06784178e-02
2.84764972e-02 -1.98931217e-01 -7.78084947e-03 -1.07862794e+00
-1.07814491e-01 -4.89628702e-01 -5.77774405e-01 8.75707924e-01
2.68579930e-01 -5.48860431e-01 7.20410347e-01 5.78467369e-01
-6.09954238e-01 -8.58345389e-01 -9.08672333e-01 -4.36392248e-01
-5.50916195e-01 -2.72153825e-01 4.30586010e-01 3.24159712e-01
-2.83788234e-01 6.56308115e-01 -1.17741570e-01 5.18947840e-02
2.27212831e-01 -2.39696130e-01 1.96107030e-01 -1.54953146e+00
7.08666584e-03 -2.76766092e-01 -3.33376586e-01 -4.41406459e-01
-1.99456841e-01 -9.02948320e-01 3.00906718e-01 -2.33293271e+00
-1.44977763e-01 -8.17674920e-02 -1.06056106e+00 8.28300238e-01
-1.92556530e-01 4.13476259e-01 -7.19545633e-02 8.49058330e-02
-5.90597570e-01 4.35383230e-01 9.26059783e-01 3.17377374e-02
-4.18016404e-01 7.43265212e-01 -6.01221502e-01 9.16344106e-01
1.19897890e+00 -7.16674447e-01 -6.12517357e-01 -1.54251784e-01
2.53474653e-01 8.04746300e-02 4.79319245e-01 -1.68669641e+00
4.95869130e-01 3.78159761e-01 5.46672702e-01 -6.79991364e-01
7.66157448e-01 -1.21801913e+00 7.92362913e-02 9.17843163e-01
-1.83292702e-01 2.62513161e-01 1.60661191e-01 5.92032313e-01
-2.38956138e-01 -4.73746434e-02 9.54120636e-01 -3.86221617e-01
-2.91939974e-01 1.82532847e-01 -6.32198215e-01 -1.09467134e-01
7.86134481e-01 -4.23403025e-01 7.59069175e-02 -8.92238468e-02
-1.05431294e+00 3.16989094e-01 -3.47179994e-02 2.91451335e-01
1.00667071e+00 -9.96237338e-01 -3.08787376e-01 5.57186663e-01
-5.16153201e-02 3.91777396e-01 1.67424321e-01 1.30183458e+00
-3.57571602e-01 5.18239379e-01 -2.07443774e-01 -7.16666818e-01
-1.16768551e+00 6.16016507e-01 6.05301797e-01 -1.78334802e-01
-8.50912452e-01 7.57597148e-01 -2.91671693e-01 -3.23803946e-02
4.80928779e-01 -9.37253952e-01 -5.10578513e-01 -2.62696878e-03
6.06564879e-01 5.63680828e-01 3.84095371e-01 -3.15299362e-01
-5.39927363e-01 3.96233052e-01 1.35797679e-01 3.90820205e-01
1.48942733e+00 -3.18217516e-01 -1.28965765e-01 6.87347412e-01
1.10182011e+00 -2.74906099e-01 -8.60286534e-01 2.20813006e-02
1.54542467e-02 1.37172326e-01 4.08702642e-02 -8.42000186e-01
-1.41734707e+00 1.26346636e+00 1.10226202e+00 3.97510320e-01
1.43130505e+00 -2.01826274e-01 1.33768249e+00 5.92747331e-01
-1.60377905e-01 -8.02214384e-01 -4.58017737e-02 -7.54256966e-03
4.45915341e-01 -1.38355374e+00 -9.53298435e-02 1.71317860e-01
-2.73236513e-01 1.15867782e+00 5.07637680e-01 -2.94717282e-01
9.04992044e-01 2.01116398e-01 1.63631976e-01 -3.02422136e-01
-7.53611863e-01 -3.60344231e-01 4.49614137e-01 4.58015800e-01
3.98504078e-01 -1.79035142e-01 -1.28914893e-01 7.26107121e-01
-3.35480601e-01 3.16025168e-01 3.30216318e-01 8.73667896e-01
-6.43864512e-01 -9.39312816e-01 7.95244053e-03 8.00109744e-01
-7.41067171e-01 -1.94892123e-01 -1.32095024e-01 5.73487282e-01
5.61751604e-01 1.35641038e+00 4.31857221e-02 -6.32225990e-01
3.52462292e-01 4.48075950e-01 7.34204054e-02 -1.01844418e+00
-9.96737421e-01 -5.65114915e-02 -1.57522246e-01 -6.28349066e-01
-8.49624455e-01 -3.03826153e-01 -1.52584398e+00 2.86293864e-01
-2.28987247e-01 2.28974938e-01 6.29842162e-01 1.28230655e+00
2.93964177e-01 1.18802905e+00 4.29974943e-01 -6.49146199e-01
-3.38568777e-01 -1.08427155e+00 -2.24644035e-01 1.41905576e-01
1.05992818e+00 -5.71908772e-01 -4.06780005e-01 3.20979506e-02] | [13.643396377563477, 3.4449214935302734] |
86d7c9b8-e5f1-42aa-978d-e94518073391 | prompt-tuning-pushes-farther-contrastive | 2307.01595 | null | https://arxiv.org/abs/2307.01595v1 | https://arxiv.org/pdf/2307.01595v1.pdf | Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases | As the representation capability of Pre-trained Language Models (PLMs) improve, there is growing concern that they will inherit social biases from unprocessed corpora. Most previous debiasing techniques used Counterfactual Data Augmentation (CDA) to balance the training corpus. However, CDA slightly modifies the original corpus, limiting the representation distance between different demographic groups to a narrow range. As a result, the debiasing model easily fits the differences between counterfactual pairs, which affects its debiasing performance with limited text resources. In this paper, we propose an adversarial training-inspired two-stage debiasing model using Contrastive learning with Continuous Prompt Augmentation (named CCPA) to mitigate social biases in PLMs' encoding. In the first stage, we propose a data augmentation method based on continuous prompt tuning to push farther the representation distance between sample pairs along different demographic groups. In the second stage, we utilize contrastive learning to pull closer the representation distance between the augmented sample pairs and then fine-tune PLMs' parameters to get debiased encoding. Our approach guides the model to achieve stronger debiasing performance by adding difficulty to the training process. Extensive experiments show that CCPA outperforms baselines in terms of debiasing performance. Meanwhile, experimental results on the GLUE benchmark show that CCPA retains the language modeling capability of PLMs. | ['Ying Wang', 'Xin Wang', 'Mengnan Du', 'Yingji Li'] | 2023-07-04 | null | null | null | null | ['contrastive-learning', 'contrastive-learning'] | ['computer-vision', 'methodology'] | [ 6.25243336e-02 2.11580843e-01 -6.74301088e-01 -3.30053866e-01
-5.21567583e-01 -4.20111626e-01 9.38419938e-01 4.01062332e-02
-4.94635850e-01 1.01609254e+00 7.34772265e-01 -5.26827812e-01
2.97246128e-01 -9.51942861e-01 -8.06477010e-01 -5.41463137e-01
2.60117561e-01 3.69467765e-01 -2.19755933e-01 -4.49589193e-01
1.98082522e-01 7.14027882e-02 -9.75977957e-01 2.99238473e-01
1.48590350e+00 6.23137355e-01 -1.11133799e-01 1.17122941e-01
-3.59339237e-01 7.88073599e-01 -8.26369405e-01 -8.40881705e-01
3.40015769e-01 -3.33126843e-01 -6.15886390e-01 -4.30410028e-01
3.93261582e-01 -5.78804553e-01 -5.06363034e-01 1.09368527e+00
7.05203593e-01 2.64019728e-01 6.31390274e-01 -1.40250528e+00
-1.28383780e+00 1.46392918e+00 -9.15049016e-01 2.40317136e-01
4.56950404e-02 1.37811422e-01 8.07770550e-01 -6.57819092e-01
1.61492720e-01 1.67559218e+00 8.40758920e-01 8.97726655e-01
-1.41839778e+00 -1.44768608e+00 5.28119862e-01 -5.57993352e-02
-1.07892060e+00 -3.45595479e-01 1.22143567e+00 -2.49384418e-01
5.03857553e-01 2.74703652e-01 4.41883504e-01 1.52998769e+00
-9.67028067e-02 1.03369403e+00 1.14213872e+00 -2.76763439e-01
2.47056708e-01 1.89983010e-01 2.15669870e-01 1.59606025e-01
5.83391845e-01 2.13128135e-01 -4.44556713e-01 -6.19951367e-01
5.52505255e-01 -1.15458868e-01 -1.75411984e-01 -3.96225899e-01
-9.58538413e-01 1.12047017e+00 4.68638718e-01 2.68881559e-01
-2.03370750e-01 8.80600289e-02 6.63692057e-01 3.52386653e-01
9.12186801e-01 7.92709410e-01 -4.34458375e-01 8.82735252e-02
-9.35154200e-01 5.17652750e-01 3.38609189e-01 6.23006642e-01
4.15135682e-01 8.83699954e-02 -4.79922950e-01 1.06366360e+00
1.32234916e-01 6.50127113e-01 1.15106404e+00 -7.99733162e-01
9.74679530e-01 6.23542011e-01 3.41375396e-02 -1.19957638e+00
-4.06318950e-03 -5.00452876e-01 -1.24336708e+00 -2.08965972e-01
5.59583902e-01 -3.21322232e-01 -5.58937311e-01 2.27543855e+00
2.54594535e-01 2.07875878e-01 9.83323604e-02 7.45931447e-01
3.39495808e-01 7.11178124e-01 4.09594387e-01 -2.03966871e-01
9.63665247e-01 -7.20452845e-01 -8.27936172e-01 -6.51204467e-01
9.65537846e-01 -4.80006844e-01 1.53569829e+00 9.02399570e-02
-1.04206622e+00 -4.41898823e-01 -1.12519467e+00 5.64543605e-02
-1.79202661e-01 -1.29489467e-01 7.64287949e-01 9.76709008e-01
-5.29515862e-01 6.80612862e-01 -4.49792713e-01 2.40388945e-01
7.41990268e-01 2.47112900e-01 -9.35790166e-02 -4.68984656e-02
-1.89661813e+00 6.43403232e-01 4.34083492e-01 -3.47687662e-01
-5.21921277e-01 -1.19225514e+00 -1.04699922e+00 6.98036999e-02
2.70634860e-01 -6.09844983e-01 9.45271313e-01 -1.20998657e+00
-1.38786149e+00 6.88178837e-01 9.18537229e-02 -7.48857558e-01
8.82081509e-01 -4.41788167e-01 -3.55918974e-01 -3.24830949e-01
1.84984565e-01 8.08080375e-01 1.04808462e+00 -1.43945897e+00
-1.76285058e-01 -2.29631200e-01 -8.05388838e-02 2.46075317e-01
-7.56592155e-01 -1.39454916e-01 1.93240911e-01 -1.43291569e+00
-2.82710046e-01 -6.99552596e-01 -2.45825261e-01 -3.34970355e-01
-4.01218653e-01 -2.35641062e-01 6.64048851e-01 -6.96946323e-01
1.64146924e+00 -2.22095656e+00 -7.02898875e-02 8.12514275e-02
1.66137442e-01 6.26517296e-01 -4.39875811e-01 -4.99546267e-02
-4.77405548e-01 4.86534476e-01 -2.61778086e-01 -7.07519472e-01
1.47408202e-01 9.96694043e-02 -9.87375617e-01 3.50706309e-01
6.95619285e-02 8.54174316e-01 -1.12427628e+00 -4.01351154e-01
-2.12559812e-02 -1.67138856e-02 -1.02901626e+00 3.73664826e-01
-2.03450531e-01 1.58930987e-01 -2.11848348e-01 1.31874084e-01
1.21777010e+00 2.11740538e-01 1.68309271e-01 6.60840282e-03
1.73728198e-01 5.58572412e-01 -9.00749028e-01 1.43250155e+00
-4.64292020e-01 2.46102676e-01 -1.81163996e-01 -1.04315472e+00
1.09408104e+00 -1.08339220e-01 1.52797654e-01 -7.20722735e-01
2.26246879e-01 9.81772542e-02 5.92790730e-02 -7.95519873e-02
8.88746262e-01 -6.75900102e-01 -4.43331003e-01 8.95509601e-01
-4.12920207e-01 -1.00414224e-01 -3.13769132e-01 4.47422713e-01
4.99579519e-01 -1.42826229e-01 2.02827156e-01 -3.26193213e-01
4.97368664e-01 -3.90321106e-01 7.87567377e-01 8.93902898e-01
-3.80031735e-01 4.08472955e-01 6.41900718e-01 -1.89715967e-01
-1.07595074e+00 -8.76996875e-01 1.72668949e-01 1.34483469e+00
1.34904861e-01 -1.43632442e-01 -7.39142835e-01 -1.19642437e+00
2.92933315e-01 1.29810417e+00 -9.67861593e-01 -9.12277460e-01
-7.31821477e-01 -1.15554678e+00 8.15225899e-01 4.96425688e-01
7.86744416e-01 -8.24059010e-01 1.69208810e-01 -6.23045564e-02
-3.90979767e-01 -3.53716642e-01 -8.98221314e-01 -2.60139883e-01
-8.50214124e-01 -5.07287443e-01 -8.57820392e-01 -5.27953506e-01
5.60472429e-01 2.65466779e-01 8.20003808e-01 -7.87011087e-02
5.68156898e-01 -2.51686245e-01 -2.15018228e-01 -4.01753455e-01
-7.47688770e-01 2.72542357e-01 3.14507544e-01 -1.22702755e-01
3.05928856e-01 -6.22703254e-01 -5.71298957e-01 2.30640426e-01
-9.45676088e-01 8.73681856e-04 3.17524999e-01 1.14442551e+00
-5.79361618e-02 -2.07264230e-01 1.07342923e+00 -1.01774180e+00
1.01038611e+00 -8.09122384e-01 -1.03076302e-01 1.14609189e-01
-7.39146411e-01 1.95191234e-01 8.60970497e-01 -1.16942191e+00
-1.45176411e+00 -6.93564951e-01 4.90546525e-02 -3.47117633e-01
2.65748739e-01 4.24441963e-01 -5.45271873e-01 5.58622718e-01
7.73370326e-01 7.82625228e-02 2.23665729e-01 -4.68249589e-01
6.31672263e-01 8.48864436e-01 5.22799492e-01 -7.68821478e-01
7.69719243e-01 4.11234707e-01 -6.83119059e-01 -1.46878824e-01
-1.15083838e+00 1.55361295e-01 -2.63284355e-01 2.36061975e-01
1.85618937e-01 -8.81041348e-01 -3.39112192e-01 6.70066893e-01
-9.51189697e-01 -6.59783661e-01 -4.11876291e-01 3.71552587e-01
-2.52559662e-01 5.98671496e-01 -4.52630967e-01 -7.30322897e-01
-3.71529937e-01 -6.01360798e-01 5.71008742e-01 -4.60141711e-02
-6.02408588e-01 -1.02989888e+00 1.94060728e-01 6.93728685e-01
3.64367485e-01 -1.58373550e-01 1.10578775e+00 -9.38070476e-01
1.39242172e-01 -1.82256475e-01 -1.98276728e-01 5.37892699e-01
2.28031427e-01 -4.82471406e-01 -8.48131955e-01 -5.22591233e-01
1.86718199e-02 -4.61312145e-01 9.97259021e-01 2.96352208e-01
1.46573639e+00 -7.74222672e-01 -2.78610915e-01 4.52171117e-01
7.04103649e-01 -2.61704065e-02 7.91988432e-01 4.75032330e-01
6.81855679e-01 6.19902134e-01 7.29481101e-01 4.94901627e-01
5.14214575e-01 2.40092307e-01 3.26391101e-01 -1.29714698e-01
-4.21150327e-02 -9.01711762e-01 6.49454415e-01 5.83470643e-01
4.93630916e-01 -2.17439801e-01 -6.80897534e-01 7.25928366e-01
-1.70983005e+00 -1.01509130e+00 3.14100713e-01 2.31522059e+00
1.40892971e+00 2.87686735e-01 3.83149572e-02 2.06226245e-01
8.91358972e-01 4.95307684e-01 -7.90214479e-01 -4.49355513e-01
-2.82958001e-01 -1.68077737e-01 4.63189185e-01 4.84568119e-01
-9.97890532e-01 1.06441784e+00 5.72306919e+00 1.16834283e+00
-1.15790009e+00 1.70085505e-01 1.08071077e+00 -2.85312206e-01
-8.12083542e-01 -1.30885959e-01 -5.90149581e-01 8.44462693e-01
7.03379333e-01 -4.56835479e-01 3.97394121e-01 7.04780936e-01
2.10819691e-01 1.75066620e-01 -8.96743238e-01 7.42538810e-01
1.47002310e-01 -1.29863048e+00 5.83498776e-01 -5.52317351e-02
8.55084300e-01 -2.69900262e-01 5.32112479e-01 8.35469425e-01
7.21274495e-01 -9.30483937e-01 9.33057308e-01 1.93244845e-01
8.09535086e-01 -9.92402971e-01 7.83049166e-01 6.96705997e-01
-3.66895258e-01 -3.51092070e-01 -5.29849172e-01 -3.80935669e-01
-7.70942569e-02 4.91893679e-01 -7.52750456e-01 2.08600998e-01
3.85297596e-01 4.35002357e-01 -6.49661899e-01 2.96446979e-01
-1.18045710e-01 9.41418827e-01 7.33763948e-02 -4.05261591e-02
2.57992055e-02 -3.02273277e-02 4.33548868e-01 9.69701469e-01
2.40524933e-01 8.70617330e-02 -1.27559975e-01 1.01006353e+00
-5.70566595e-01 1.69497296e-01 -5.39069831e-01 -8.58791023e-02
9.37691152e-01 6.65909529e-01 5.97652420e-02 -5.58416009e-01
-3.97814214e-02 8.22763920e-01 6.40239537e-01 1.25930130e-01
-9.05812144e-01 -3.35876107e-01 7.93646872e-01 2.92680919e-01
-1.55445218e-01 1.15192622e-01 -6.09209836e-01 -1.40017688e+00
-3.84846985e-01 -1.13729227e+00 5.50391853e-01 -5.34813523e-01
-1.68053353e+00 8.07424784e-02 7.08325133e-02 -8.25003862e-01
-1.04299180e-01 -1.01300634e-01 -7.40125179e-01 9.41777766e-01
-1.39719987e+00 -1.23381579e+00 2.07431167e-01 2.96099275e-01
3.44512403e-01 -2.54871905e-01 4.59814399e-01 2.19813511e-01
-8.15959811e-01 1.29255068e+00 4.55074236e-02 2.71923751e-01
1.20587409e+00 -9.93790925e-01 4.61378366e-01 7.81197250e-01
-5.08173645e-01 1.10633004e+00 7.81104982e-01 -9.84559774e-01
-5.99521101e-01 -1.24618471e+00 9.22674060e-01 -3.40328515e-01
7.84662008e-01 -3.84481579e-01 -1.33069992e+00 7.46941686e-01
1.66511759e-01 -3.46196413e-01 1.00334001e+00 2.00959638e-01
-6.93700016e-01 -1.57729551e-01 -1.31800175e+00 9.76616681e-01
9.42709386e-01 -3.87598425e-01 -1.10285258e+00 -9.11651254e-02
1.03673017e+00 -8.72295499e-02 -5.09229422e-01 3.26063275e-01
3.04933280e-01 -5.62500656e-01 1.02803659e+00 -9.97424722e-01
6.34687543e-01 -1.76204238e-02 -6.39567524e-02 -1.65260649e+00
-2.86081761e-01 -7.61526048e-01 -7.13965818e-02 1.71577370e+00
3.07862610e-01 -8.03917468e-01 7.22019792e-01 7.59376943e-01
1.80419728e-01 -4.54066128e-01 -8.79030406e-01 -6.79670691e-01
9.36146319e-01 -3.94711435e-01 1.20564485e+00 1.60454571e+00
2.33148187e-01 3.07677418e-01 -7.00963199e-01 -8.38523582e-02
5.66429734e-01 9.46272984e-02 8.34113181e-01 -8.75270784e-01
-2.45554298e-01 -3.91592920e-01 3.70940626e-01 -1.21178067e+00
6.90912187e-01 -1.03780508e+00 -3.02017272e-01 -8.93115103e-01
4.89648491e-01 -8.49585772e-01 -2.94219434e-01 3.81612182e-01
-7.36170292e-01 4.42292318e-02 2.17321172e-01 1.32642612e-01
-2.31029794e-01 1.06307971e+00 1.24275911e+00 -2.59904444e-01
-4.12253082e-01 -1.73949555e-01 -1.38537753e+00 8.32834184e-01
1.03872931e+00 -4.84569609e-01 -4.45145547e-01 -4.61575717e-01
3.01292509e-01 -3.86868894e-01 2.81802773e-01 -3.89163792e-01
-1.11680023e-01 -4.07256901e-01 3.28072399e-01 -4.08064753e-01
9.49383611e-05 -3.39912295e-01 -2.83144176e-01 6.54688299e-01
-9.23256636e-01 -1.64337218e-01 2.93808699e-01 4.60688353e-01
9.36133265e-02 -2.28142723e-01 8.44305217e-01 1.17074825e-01
-2.68956032e-02 4.23049964e-02 -2.72013843e-01 3.08254451e-01
7.68601656e-01 1.83935121e-01 -5.49859464e-01 -3.97862226e-01
-3.36985797e-01 4.10140514e-01 4.95316654e-01 5.06034911e-01
2.96528935e-01 -1.57888103e+00 -8.10541987e-01 3.09346348e-01
-9.18492377e-02 -6.54636230e-03 4.32848394e-01 4.55024302e-01
2.98391823e-02 5.63415103e-02 -9.47851911e-02 7.09972084e-02
-1.10931981e+00 8.56458426e-01 3.21519792e-01 -5.23245454e-01
-6.11930043e-02 9.16249871e-01 5.15162349e-01 -7.67257929e-01
1.01050638e-01 -2.77714878e-01 -1.59343734e-01 3.43161792e-01
5.54447174e-01 4.82382983e-01 -4.26322967e-01 -2.62125224e-01
2.68254057e-02 -2.39535257e-01 -4.66619551e-01 -6.37688488e-02
1.18154395e+00 -3.06391418e-01 -1.68225288e-01 2.06561312e-01
9.57144260e-01 4.39143807e-01 -1.28199768e+00 -5.03218234e-01
-1.25057206e-01 -6.90249860e-01 4.52187769e-02 -7.91803956e-01
-7.96685636e-01 8.22946608e-01 2.20563114e-01 5.52793369e-02
9.72138643e-01 -1.39516979e-01 9.97042775e-01 -6.40925616e-02
-2.64178719e-02 -1.09931505e+00 3.63151908e-01 4.32551920e-01
1.02420759e+00 -1.08462226e+00 3.49702612e-02 -3.59339118e-01
-9.26498115e-01 4.07099396e-01 8.54005098e-01 -1.86747804e-01
3.93018544e-01 1.18858382e-01 -2.62931809e-02 5.25881886e-01
-7.05778360e-01 5.63074112e-01 4.25848737e-02 5.90169609e-01
3.22951257e-01 1.99564308e-01 -5.41013658e-01 1.38812995e+00
-6.17665350e-01 -3.14920545e-01 4.77489471e-01 3.86095524e-01
-1.70799345e-01 -1.15279531e+00 -6.20489120e-01 4.30774003e-01
-5.11941433e-01 -3.82663101e-01 -5.87880731e-01 6.62348270e-01
3.31456661e-01 7.50255704e-01 2.51200408e-01 -4.33185965e-01
2.84660101e-01 7.83015341e-02 2.00014070e-01 -4.06314105e-01
-6.68676615e-01 -2.11286142e-01 7.81875253e-02 -1.68339148e-01
-9.49533582e-02 -8.86798739e-01 -1.05222631e+00 -7.84941852e-01
-4.19366926e-01 2.83594817e-01 3.73955183e-02 7.79507101e-01
3.97099197e-01 3.11200529e-01 7.52530277e-01 -5.14730990e-01
-1.15567291e+00 -1.29206026e+00 -4.23214883e-01 6.31324828e-01
3.68380278e-01 -5.92006981e-01 -4.48463917e-01 -3.10023278e-01] | [10.289628982543945, 7.693171977996826] |
40444cad-9774-4e06-b2d9-134324fe1935 | large-language-models-in-the-workplace-a-case | 2303.07142 | null | https://arxiv.org/abs/2303.07142v3 | https://arxiv.org/pdf/2303.07142v3.pdf | Large Language Models in the Workplace: A Case Study on Prompt Engineering for Job Type Classification | This case study investigates the task of job classification in a real-world setting, where the goal is to determine whether an English-language job posting is appropriate for a graduate or entry-level position. We explore multiple approaches to text classification, including supervised approaches such as traditional models like Support Vector Machines (SVMs) and state-of-the-art deep learning methods such as DeBERTa. We compare them with Large Language Models (LLMs) used in both few-shot and zero-shot classification settings. To accomplish this task, we employ prompt engineering, a technique that involves designing prompts to guide the LLMs towards the desired output. Specifically, we evaluate the performance of two commercially available state-of-the-art GPT-3.5-based language models, text-davinci-003 and gpt-3.5-turbo. We also conduct a detailed analysis of the impact of different aspects of prompt engineering on the model's performance. Our results show that, with a well-designed prompt, a zero-shot gpt-3.5-turbo classifier outperforms all other models, achieving a 6% increase in Precision@95% Recall compared to the best supervised approach. Furthermore, we observe that the wording of the prompt is a critical factor in eliciting the appropriate "reasoning" in the model, and that seemingly minor aspects of the prompt significantly affect the model's performance. | ['Thomas Brightwell', 'Guillaume Soulié', 'Frederick Naylor', 'Alexandru Ciceu', 'Benjamin Clavié'] | 2023-03-13 | null | null | null | null | ['job-classification'] | ['natural-language-processing'] | [ 7.37294555e-02 1.47744664e-04 -5.49352884e-01 -3.62909436e-01
-7.18004704e-01 -3.61541986e-01 7.39453077e-01 6.96821392e-01
-5.75758457e-01 2.79022217e-01 1.72729939e-01 -1.23890007e+00
-2.43302122e-01 -7.28642583e-01 -2.79718906e-01 -1.64906666e-01
5.69901109e-01 5.57832181e-01 -1.68788563e-02 -4.87154603e-01
4.75091457e-01 3.60975236e-01 -1.42561889e+00 2.81555295e-01
7.22461879e-01 7.90637136e-01 2.41399389e-02 1.00441575e+00
-4.42301780e-01 9.78500426e-01 -8.10124755e-01 -4.97930855e-01
-1.69114187e-01 -1.64917856e-01 -1.03104782e+00 -2.05438524e-01
4.61022168e-01 2.21995208e-02 -4.55821693e-01 5.82046747e-01
6.16130948e-01 4.68685210e-01 8.00210893e-01 -1.05202913e+00
-4.69266981e-01 4.60678577e-01 7.09261920e-04 4.93389457e-01
4.70994353e-01 3.85369271e-01 9.63588655e-01 -8.27047706e-01
4.01082873e-01 1.18129873e+00 8.79048228e-01 3.77317488e-01
-1.23304904e+00 -5.95292389e-01 -8.34742263e-02 -2.73930617e-02
-1.19359326e+00 -4.90689218e-01 5.84270775e-01 -8.92008781e-01
1.14499378e+00 1.24940477e-01 2.91914970e-01 1.34992647e+00
7.75777996e-01 6.47871733e-01 1.23260581e+00 -8.19293439e-01
4.00471717e-01 4.31240290e-01 9.54550445e-01 8.09646666e-01
2.37819478e-02 5.81145883e-02 -6.59673572e-01 -5.11910200e-01
2.64919549e-01 -1.56194091e-01 3.28703165e-01 7.83999562e-02
-9.14200604e-01 9.55680788e-01 -4.16022167e-02 4.84774709e-01
-2.15897962e-01 -2.18468100e-01 3.88978451e-01 2.65767515e-01
4.55904484e-01 7.67322779e-01 -3.45028877e-01 -5.57323694e-01
-1.02788103e+00 4.23061013e-01 1.08748114e+00 8.12845409e-01
2.62177140e-01 -4.56468649e-02 -9.73802984e-01 7.26989567e-01
1.28569514e-01 1.18118845e-01 7.54157662e-01 -4.71088201e-01
4.88330930e-01 6.71302378e-01 1.26635373e-01 -6.93966508e-01
-4.46653396e-01 -6.64517760e-01 -3.59531432e-01 -2.06885561e-02
6.64700508e-01 -3.69646013e-01 -1.08360004e+00 1.19880795e+00
-1.87099472e-01 -2.18221340e-02 2.28390276e-01 4.04270798e-01
1.00738859e+00 6.03144825e-01 6.64306939e-01 1.08920142e-01
1.66435683e+00 -9.55520689e-01 -6.50400102e-01 -8.08736503e-01
1.28855729e+00 -7.75880337e-01 1.37447131e+00 1.54204756e-01
-7.84886897e-01 -9.33094621e-01 -1.00836384e+00 -2.11382136e-01
-5.72768807e-01 3.39239687e-01 4.43182051e-01 9.52069283e-01
-6.74755812e-01 6.55170083e-01 -3.45252186e-01 -3.98581803e-01
1.17841117e-01 1.87885210e-01 -1.16340376e-01 -1.81038845e-02
-1.36198843e+00 1.11430490e+00 1.25346079e-01 -4.88978058e-01
-5.85130632e-01 -8.10136914e-01 -8.85125399e-01 5.00495851e-01
2.72372842e-01 -4.41058069e-01 1.98469388e+00 -4.65157688e-01
-1.30834568e+00 9.01093960e-01 -3.31562668e-01 -4.21366364e-01
3.71596783e-01 -7.26295784e-02 -4.55530524e-01 -1.59264341e-01
1.19531363e-01 1.24453135e-01 4.68699783e-01 -7.44019151e-01
-5.79446018e-01 -2.31878281e-01 -7.11867660e-02 1.85921371e-01
-6.00709379e-01 3.07895273e-01 -2.06134900e-01 -3.86632979e-01
-4.63924617e-01 -8.15695167e-01 -4.00157064e-01 -5.93510926e-01
-3.47392887e-01 -6.67799175e-01 4.87261683e-01 -5.68194628e-01
1.64293993e+00 -2.05206275e+00 -4.20701414e-01 1.11009866e-01
-6.60655499e-02 4.69042212e-01 1.29016444e-01 3.70942026e-01
-7.29741007e-02 3.21481824e-01 3.52869391e-01 -4.99433070e-01
8.17220360e-02 -7.99216107e-02 -2.30914667e-01 4.00118008e-02
-1.05567891e-02 9.43165243e-01 -9.23723996e-01 -4.58622485e-01
2.44103342e-01 8.04947391e-02 -2.72714615e-01 2.27435172e-01
9.91415698e-03 -5.67035414e-02 -3.83989573e-01 4.78207111e-01
-1.67970613e-01 -3.73386592e-01 1.30783483e-01 4.82129306e-01
-3.74690592e-02 7.16071129e-01 -6.81929171e-01 1.23368609e+00
-5.53658843e-01 6.98981285e-01 -2.31941372e-01 -8.66229236e-01
1.14671111e+00 4.93030965e-01 1.20738037e-02 -6.22105181e-01
3.56822968e-01 3.25607173e-02 1.14900269e-01 -3.49095076e-01
1.03224826e+00 -3.18533987e-01 -3.86364341e-01 3.82253855e-01
1.72534168e-01 8.93883556e-02 1.77411169e-01 3.43155414e-01
1.13252330e+00 -3.15656334e-01 4.48684841e-01 -4.54328716e-01
1.39438674e-01 2.78429210e-01 1.06563486e-01 1.41886806e+00
-2.33918667e-01 2.42687941e-01 5.62094152e-01 -2.15699285e-01
-8.49837184e-01 -4.34322536e-01 -1.10851064e-01 1.59518635e+00
-4.02934194e-01 -6.74839020e-01 -7.45966554e-01 -7.78755605e-01
2.06887856e-01 1.44466293e+00 -4.04918104e-01 -5.83194017e-01
-1.16702072e-01 -4.55165088e-01 6.28415704e-01 5.73548436e-01
1.28282145e-01 -8.46048057e-01 -5.62216818e-01 1.34986967e-01
-2.15890929e-02 -1.13629353e+00 -3.91684771e-01 5.77582061e-01
-7.44601309e-01 -6.52329147e-01 -4.83352393e-01 -7.57362366e-01
5.88291943e-01 1.93716154e-01 1.15593863e+00 4.48740609e-02
-9.21494514e-02 5.54829776e-01 -2.20350847e-01 -4.98840749e-01
-7.62456715e-01 5.63782275e-01 8.36503133e-02 -2.90677160e-01
9.79519248e-01 1.67085573e-01 -2.53467262e-03 9.96124446e-02
-4.39366639e-01 7.16792196e-02 5.72365344e-01 9.04377103e-01
-4.72848341e-02 1.97775051e-01 3.84670407e-01 -1.26602101e+00
1.42927063e+00 -5.41367769e-01 -1.12877205e-01 3.29055697e-01
-1.07724762e+00 3.10050398e-02 6.67418838e-01 -6.52329624e-01
-9.06725049e-01 -1.70342147e-01 -2.72127301e-01 -2.27440059e-01
-3.71369153e-01 8.34395528e-01 3.00853729e-01 -7.08567649e-02
1.14515579e+00 3.18702877e-01 -9.57583264e-02 -3.78214747e-01
-3.35005373e-02 1.19804955e+00 4.18608516e-01 -7.58915484e-01
4.77037877e-01 -3.74803782e-01 -1.80762962e-01 -8.49151552e-01
-1.19158685e+00 -8.13152492e-01 -5.70188165e-01 -1.94459617e-01
5.18393159e-01 -8.12300563e-01 -7.35381246e-01 3.30485195e-01
-8.90004933e-01 -7.38703430e-01 2.68332055e-03 3.44759762e-01
-3.65789890e-01 3.96164842e-02 -8.03683341e-01 -9.91569638e-01
-3.60063314e-01 -1.23037970e+00 1.00181162e+00 4.65819478e-01
-8.43072474e-01 -1.07258105e+00 -3.15552980e-01 7.35934317e-01
4.10213321e-01 -5.52690089e-01 1.22772133e+00 -1.37523580e+00
3.39576185e-01 -5.63833475e-01 1.69413313e-01 1.28110528e-01
-2.27867410e-01 -2.84217060e-01 -1.06825256e+00 -1.49679288e-01
-1.06702656e-01 -3.94345403e-01 5.76400816e-01 1.99926332e-01
1.13511407e+00 -1.28442481e-01 -4.27062422e-01 1.65900722e-01
8.66232932e-01 2.23963529e-01 2.94845194e-01 4.63964999e-01
5.34168541e-01 5.72395682e-01 8.23514998e-01 2.28048563e-01
2.59069860e-01 6.47542655e-01 -3.93989027e-01 7.06252679e-02
2.00211316e-01 -5.63641727e-01 3.85570228e-01 4.74719048e-01
4.08511847e-01 -2.51369536e-01 -1.48680437e+00 2.40754873e-01
-1.69946337e+00 -7.48818219e-01 -8.94596055e-02 2.24282575e+00
9.94302392e-01 8.17836642e-01 1.78794973e-02 2.01265246e-01
2.71078318e-01 8.40200111e-02 -2.04139739e-01 -8.38541985e-01
4.67112422e-01 2.45558158e-01 5.41715443e-01 6.02800906e-01
-1.04979694e+00 9.87838686e-01 7.13005114e+00 9.91984010e-01
-1.06487393e+00 3.22269369e-03 8.99023473e-01 6.42003417e-02
8.22611600e-02 -4.43612970e-02 -1.49856448e+00 5.23019016e-01
1.76188827e+00 -6.11355126e-01 6.79834262e-02 1.16780353e+00
2.95173347e-01 -1.85398355e-01 -1.09853804e+00 7.08599627e-01
9.28636491e-02 -1.31840587e+00 -7.41407946e-02 1.03382170e-01
4.14114684e-01 -4.92527038e-01 -4.70399894e-02 1.19952345e+00
4.94032621e-01 -1.12679648e+00 6.85836017e-01 3.81692052e-01
6.70888007e-01 -6.37924016e-01 7.01394379e-01 7.75928259e-01
-6.66330695e-01 -4.06496137e-01 -1.50784388e-01 -4.48630989e-01
-2.41361886e-01 5.38383484e-01 -1.24925816e+00 2.36651093e-01
2.32780278e-01 2.05191106e-01 -8.23337913e-01 6.60365224e-01
-1.88109890e-01 1.11718130e+00 1.59761012e-01 -3.49846363e-01
3.15947860e-01 3.90182436e-01 2.75489718e-01 1.55069256e+00
2.17569172e-01 1.66819990e-01 6.03981853e-01 6.20320559e-01
-1.15238326e-02 1.98770359e-01 -6.95422649e-01 -4.46614444e-01
6.52053654e-01 1.20210850e+00 -6.44388080e-01 -8.14686179e-01
-4.35551822e-01 7.01429665e-01 1.75725833e-01 3.41867924e-01
-2.81810373e-01 -5.31572402e-01 4.89279479e-01 3.62793475e-01
-1.50009200e-01 -3.10964108e-01 -6.70402527e-01 -7.19039977e-01
-3.07888925e-01 -1.05731070e+00 3.56294453e-01 -8.69055510e-01
-1.14339495e+00 3.45130116e-01 -1.59989521e-02 -7.89612830e-01
-3.20186824e-01 -8.60908270e-01 -8.84470224e-01 1.18532085e+00
-1.15944552e+00 -6.74891055e-01 -1.55321375e-01 7.11988881e-02
8.15914214e-01 -3.75245035e-01 9.85648215e-01 5.57597121e-03
-7.64418960e-01 7.38124788e-01 -2.82964902e-03 3.81119221e-01
8.57803822e-01 -1.25310826e+00 6.70887172e-01 7.11529493e-01
-1.29337564e-01 9.97682333e-01 8.78742099e-01 -8.11822176e-01
-1.44594526e+00 -9.94139791e-01 1.55126667e+00 -6.73569024e-01
7.03538358e-01 -3.86232018e-01 -7.79232383e-01 6.84762657e-01
-1.03585087e-01 -2.31220856e-01 9.71192658e-01 6.53867006e-01
-7.67508596e-02 2.66813308e-01 -9.05203938e-01 6.60762250e-01
5.32466352e-01 -7.71995544e-01 -9.02846396e-01 4.07933265e-01
6.37938142e-01 -5.96606255e-01 -9.21336114e-01 2.10084748e-02
4.96091604e-01 -6.11653149e-01 8.72982085e-01 -1.10092735e+00
6.55639052e-01 5.40041804e-01 2.88056582e-01 -1.45993841e+00
-6.87257111e-01 -4.41027999e-01 -1.41275108e-01 9.36264932e-01
5.14625132e-01 -4.38875794e-01 7.71160305e-01 1.03665900e+00
-2.27483392e-01 -8.81713748e-01 -4.84140664e-01 -8.45472217e-01
2.34203428e-01 -4.92218733e-01 2.15131178e-01 1.02121699e+00
4.21296418e-01 9.00484145e-01 -1.53866097e-01 -2.50461161e-01
2.58916706e-01 -1.28979519e-01 7.80849397e-01 -1.63251436e+00
-2.90543079e-01 -6.14280641e-01 -1.65765837e-01 -1.00507677e+00
3.32429856e-01 -9.58202362e-01 8.65863860e-02 -1.42666006e+00
1.66623011e-01 -4.64872867e-01 -3.29000801e-01 7.32759118e-01
-4.58612025e-01 -4.67095584e-01 1.04769945e-01 -1.04131810e-01
-2.75706500e-01 1.32262632e-01 8.84329200e-01 -1.61577776e-01
-3.29098761e-01 2.98940569e-01 -1.04880977e+00 4.86168236e-01
8.38392556e-01 -4.18522328e-01 -3.12439471e-01 7.48459250e-02
-2.51590740e-02 2.30821297e-01 3.00686777e-01 -1.04106772e+00
6.21335626e-01 -2.81450927e-01 4.60679561e-01 -1.41624331e-01
2.80307800e-01 -2.47314095e-01 -4.91695940e-01 4.55734193e-01
-1.02438295e+00 6.77161068e-02 4.56026345e-01 4.02658939e-01
8.91063958e-02 -7.52607942e-01 6.25671029e-01 -1.38615742e-01
-6.92187250e-01 -3.04465145e-02 -9.11553204e-01 -8.89875647e-03
8.56280744e-01 -1.03578180e-01 -4.78233159e-01 -3.45799655e-01
-5.97179413e-01 1.76788896e-01 2.22826883e-01 7.61174977e-01
2.42040977e-01 -1.04088652e+00 -4.33704495e-01 2.46017560e-01
3.64930302e-01 -5.15964329e-01 -1.29573554e-01 7.74804354e-01
-2.71031503e-02 9.95764434e-01 6.87757134e-02 -3.49018782e-01
-1.51804340e+00 3.65911961e-01 1.92374572e-01 -5.43327212e-01
-5.67033529e-01 6.06229722e-01 -3.38892698e-01 -6.78778410e-01
5.01963973e-01 -2.10069135e-01 -3.50838840e-01 -1.43707097e-02
5.41162670e-01 1.91732928e-01 3.62976134e-01 -3.47437650e-01
-6.89834133e-02 -2.29527265e-01 -2.77874053e-01 -1.78430870e-01
7.29215145e-01 3.99901837e-01 4.65021431e-01 8.52048576e-01
7.75103331e-01 -2.83486426e-01 -5.03539145e-01 -4.13220882e-01
3.60551864e-01 -2.73846895e-01 5.06428301e-01 -9.91473734e-01
-9.47825313e-02 9.26222742e-01 4.47571844e-01 1.85769424e-01
3.61407697e-01 -3.77573907e-01 5.04687428e-01 5.72244406e-01
1.77950755e-01 -1.26594329e+00 1.16246633e-01 9.91366744e-01
1.30334035e-01 -1.39853156e+00 -1.92790657e-01 -1.12984188e-01
-6.80674493e-01 1.10487247e+00 8.10363233e-01 5.10889769e-01
4.45787251e-01 2.41135895e-01 4.52244170e-02 -2.99688041e-01
-1.05805314e+00 1.49126025e-03 4.23578680e-01 1.25581026e-02
9.37193155e-01 2.46668845e-01 -2.74978071e-01 9.38982368e-01
-4.38963801e-01 2.13266805e-01 4.75319922e-01 1.27212727e+00
-7.34900773e-01 -9.81890500e-01 -4.84540403e-01 8.78508925e-01
-5.08050084e-01 -2.29082122e-01 -4.95806128e-01 4.23216194e-01
-3.91989738e-01 1.22942185e+00 3.19100614e-03 -6.96246803e-01
3.84062409e-01 8.92042339e-01 4.79193479e-02 -1.25741088e+00
-9.41850066e-01 -3.57626289e-01 4.70753372e-01 9.68413707e-03
4.34079081e-01 -5.05193591e-01 -1.13294816e+00 -4.13080633e-01
-1.94316939e-01 4.34683412e-01 6.48170531e-01 1.24993372e+00
3.99568051e-01 7.41761446e-01 2.39903271e-01 -5.46402633e-01
-1.08484948e+00 -1.23913574e+00 -4.05813366e-01 2.04259783e-01
-1.91097576e-02 -6.50817037e-01 -2.14208081e-01 -1.89757109e-01] | [10.939555168151855, 8.516921043395996] |
1d5d7cb5-c95b-4dd5-bc19-964585829ad4 | cartoonrenderer-an-instance-based-multi-style | 1911.06102 | null | https://arxiv.org/abs/1911.06102v1 | https://arxiv.org/pdf/1911.06102v1.pdf | CartoonRenderer: An Instance-based Multi-Style Cartoon Image Translator | Instance based photo cartoonization is one of the challenging image stylization tasks which aim at transforming realistic photos into cartoon style images while preserving the semantic contents of the photos. State-of-the-art Deep Neural Networks (DNNs) methods still fail to produce satisfactory results with input photos in the wild, especially for photos which have high contrast and full of rich textures. This is due to that: cartoon style images tend to have smooth color regions and emphasized edges which are contradict to realistic photos which require clear semantic contents, i.e., textures, shapes etc. Previous methods have difficulty in satisfying cartoon style textures and preserving semantic contents at the same time. In this work, we propose a novel "CartoonRenderer" framework which utilizing a single trained model to generate multiple cartoon styles. In a nutshell, our method maps photo into a feature model and renders the feature model back into image space. In particular, cartoonization is achieved by conducting some transformation manipulation in the feature space with our proposed Soft-AdaIN. Extensive experimental results show our method produces higher quality cartoon style images than prior arts, with accurate semantic content preservation. In addition, due to the decoupling of whole generating process into "Modeling-Coordinating-Rendering" parts, our method could easily process higher resolution photos, which is intractable for existing methods. | ['Bingbing Ni', 'Muchun Chen', 'Chaoyue Song', 'Yugang Chen'] | 2019-11-14 | null | null | null | null | ['image-stylization'] | ['computer-vision'] | [ 4.74159300e-01 -3.85489245e-03 2.04845294e-01 -2.22663030e-01
-2.33751178e-01 -5.40823936e-01 7.07702756e-01 -6.14326000e-01
-2.41283420e-02 8.33209276e-01 2.10462749e-01 1.61991507e-01
3.21029276e-01 -1.10655665e+00 -9.86428380e-01 -6.33610368e-01
7.85811484e-01 2.10710704e-01 -1.15027212e-01 -4.68274295e-01
2.00733110e-01 6.95901692e-01 -1.44404387e+00 4.76909995e-01
8.60086918e-01 7.15534627e-01 2.45596588e-01 5.07356882e-01
-3.79631668e-01 7.73873210e-01 -4.27997917e-01 -8.12106669e-01
4.73859370e-01 -5.54669261e-01 -5.45055330e-01 4.91415441e-01
8.57050419e-01 -6.79766476e-01 -4.39439714e-01 1.51093841e+00
2.66436845e-01 6.04179278e-02 5.68615019e-01 -1.44696248e+00
-1.45155299e+00 4.24788028e-01 -9.50212240e-01 -6.77312255e-01
2.04553559e-01 4.39210497e-02 7.01471627e-01 -8.80599082e-01
8.90179694e-01 1.74096942e+00 6.61302388e-01 7.10307777e-01
-1.41210282e+00 -7.34991729e-01 1.54544398e-01 5.61771989e-02
-9.93498206e-01 -2.39594147e-01 1.00422311e+00 -2.06872404e-01
2.97649980e-01 3.17706525e-01 8.39550138e-01 1.08470500e+00
2.97913969e-01 8.48625004e-01 1.28819644e+00 -2.32349426e-01
5.03117219e-02 3.08417886e-01 -6.05614960e-01 6.22180462e-01
3.10954154e-01 -4.15127054e-02 -3.35057586e-01 2.86981225e-01
1.27467084e+00 3.71769041e-01 -3.08617830e-01 -5.44053435e-01
-1.23315454e+00 5.90078413e-01 4.96447980e-01 2.06377849e-01
-3.26346666e-01 2.35938355e-01 1.14852332e-01 1.74779356e-01
3.24679464e-01 4.22450930e-01 -1.29358312e-02 1.27679199e-01
-9.79652584e-01 2.98195779e-01 5.39128840e-01 1.24865770e+00
9.08750296e-01 5.27385354e-01 -5.54066338e-02 9.84276533e-01
-9.73325148e-02 5.99518657e-01 3.90940726e-01 -1.03810763e+00
2.70707995e-01 6.13069713e-01 1.87924594e-01 -1.25115907e+00
-3.96259725e-02 -2.44413674e-01 -1.42793190e+00 6.06800973e-01
2.79275060e-01 -1.07228875e-01 -1.03250635e+00 1.50617349e+00
9.84598622e-02 -1.54571116e-01 1.45238787e-01 9.25165236e-01
7.50921547e-01 9.38172936e-01 -4.24117260e-02 1.13982260e-01
1.50414371e+00 -1.06223071e+00 -9.19651031e-01 -1.62693530e-01
1.97416022e-02 -1.09202719e+00 1.43863368e+00 4.16789442e-01
-1.26833332e+00 -7.61036754e-01 -1.00790226e+00 -4.51806217e-01
-4.11243051e-01 4.28102911e-01 4.11961973e-01 5.93329847e-01
-1.16128111e+00 7.23157644e-01 -2.26090536e-01 -3.71622860e-01
5.39449632e-01 -1.05288602e-01 -4.96650368e-01 -1.44273713e-01
-8.82197499e-01 7.31371164e-01 4.47221249e-01 1.44705117e-01
-6.73486173e-01 -7.06118524e-01 -8.30138266e-01 1.30431190e-01
2.64608800e-01 -8.69186938e-01 1.00818765e+00 -1.62955880e+00
-1.74791145e+00 7.97164083e-01 -3.89487706e-02 -1.71728984e-01
9.69985843e-01 -3.23729128e-01 -3.67555767e-01 9.66648832e-02
1.05947047e-01 1.08820510e+00 1.24052596e+00 -1.70604467e+00
-6.33885324e-01 -2.85079293e-02 1.62598044e-01 2.71648049e-01
-3.50316614e-01 -1.46044225e-01 -5.54139912e-01 -1.07910073e+00
-2.09995490e-02 -8.34691703e-01 -1.22855805e-01 3.81534368e-01
-6.89413905e-01 2.50163406e-01 1.10901344e+00 -7.97369540e-01
7.12231815e-01 -2.06602359e+00 2.64621223e-03 5.57664186e-02
2.47674540e-01 2.46650055e-01 -3.51219237e-01 5.81090450e-01
-2.37380758e-01 1.20070964e-01 -2.40513459e-01 -3.97247910e-01
2.16970906e-01 9.34264064e-02 -5.42978823e-01 1.49265260e-01
3.22020739e-01 9.95058477e-01 -7.56018400e-01 -4.68304485e-01
3.63152236e-01 6.26932383e-01 -5.83769321e-01 1.02380425e-01
-2.90703028e-01 3.81337523e-01 -1.37803510e-01 6.39420450e-01
1.10089684e+00 4.68325354e-02 1.86936617e-01 -5.72255611e-01
-9.04026926e-02 -4.12392288e-01 -1.25605762e+00 1.64641690e+00
-6.22102082e-01 7.97265172e-01 9.03716777e-03 -6.74265623e-01
1.06140089e+00 -5.18673006e-03 2.83569515e-01 -6.95778191e-01
2.53891706e-01 9.43934470e-02 -3.51073205e-01 -3.75787795e-01
9.13585365e-01 -3.29808056e-01 1.41520232e-01 3.53214890e-01
-3.55965823e-01 -5.29763520e-01 2.02011108e-01 1.51249230e-01
3.55837584e-01 4.87111896e-01 4.86568809e-02 -1.30460039e-01
3.45155478e-01 -1.58640310e-01 5.59625983e-01 4.99011308e-01
2.72351295e-01 1.07243800e+00 5.50589979e-01 -6.87922359e-01
-1.59731102e+00 -9.45106924e-01 1.66408271e-01 6.59141123e-01
2.99202055e-01 1.53389643e-03 -1.13254380e+00 -3.20756882e-01
-1.79892674e-01 7.28544831e-01 -7.40589559e-01 -6.56208843e-02
-6.83970213e-01 -5.06440938e-01 3.35017920e-01 4.56412554e-01
9.92024422e-01 -1.33526599e+00 -2.74632245e-01 1.83359817e-01
-2.12137908e-01 -1.34847653e+00 -7.80975878e-01 -5.21649063e-01
-6.44184172e-01 -8.69145870e-01 -1.17962694e+00 -1.11114335e+00
9.18158233e-01 5.11434197e-01 9.91092861e-01 5.64220920e-02
-2.02669874e-01 -9.06669348e-02 -2.43409202e-01 -2.74643868e-01
-5.51735401e-01 -3.73203933e-01 -1.59991875e-01 5.90161622e-01
-1.68741778e-01 -7.14717448e-01 -6.99832618e-01 8.91859382e-02
-1.51850891e+00 8.82260859e-01 8.49177539e-01 9.00595427e-01
5.17279506e-01 1.60231814e-01 3.28483164e-01 -1.11688721e+00
6.05571032e-01 3.88822816e-02 -5.65465093e-01 3.88153732e-01
-2.80774385e-01 -4.61953804e-02 1.20408225e+00 -5.56710005e-01
-1.31444037e+00 1.04109295e-01 -2.14517117e-03 -6.53918982e-01
-1.73835933e-01 -1.62556827e-01 -3.98677200e-01 -8.06943253e-02
3.08144957e-01 5.83743691e-01 1.36667192e-01 -4.39059138e-01
6.93188012e-01 3.45379800e-01 7.27109134e-01 -4.95443076e-01
1.23075342e+00 9.08793509e-01 -2.04705750e-03 -7.79883623e-01
-5.91872275e-01 3.45316052e-01 -6.21923029e-01 -2.44669452e-01
9.30534840e-01 -7.40200281e-01 -5.02605379e-01 8.36534739e-01
-1.19281375e+00 -2.56939381e-01 -3.45923990e-01 1.97783876e-02
-7.23927498e-01 5.98387003e-01 -5.60629189e-01 -4.37106311e-01
-4.08510417e-01 -1.10217535e+00 1.15069604e+00 4.91568506e-01
1.07068233e-01 -7.01282501e-01 -2.62028486e-01 1.81564376e-01
4.16238934e-01 4.92771566e-01 1.09139705e+00 2.72757709e-01
-7.00350881e-01 -1.12340093e-01 -9.15399253e-01 4.99036252e-01
1.97179213e-01 2.36198321e-01 -8.98284018e-01 -1.54427633e-01
-3.21028650e-01 -1.35851398e-01 6.24881148e-01 3.06942612e-01
1.35053408e+00 -4.80889916e-01 -3.65308300e-02 8.81885588e-01
1.69807088e+00 3.42046261e-01 1.05013573e+00 3.77629846e-01
1.02946556e+00 6.86567366e-01 4.09681678e-01 2.87748069e-01
1.79310083e-01 5.65424323e-01 3.49787086e-01 -7.55151510e-01
-5.07819057e-01 -6.44771993e-01 3.42099816e-01 3.29650402e-01
1.89128127e-02 -2.79876620e-01 -3.18664551e-01 4.32987422e-01
-1.67745173e+00 -9.98641610e-01 -5.85701391e-02 1.76083720e+00
7.93051839e-01 -9.56582129e-02 -2.71857586e-02 -1.28312886e-01
9.00815129e-01 9.35312361e-02 -5.52206874e-01 -4.82732832e-01
-3.53204340e-01 6.71066437e-03 4.17916834e-01 2.77691960e-01
-7.92301953e-01 1.15219760e+00 5.13791609e+00 1.00150383e+00
-1.27989137e+00 -1.56052306e-01 7.16175437e-01 8.10091719e-02
-5.04793942e-01 -7.03194179e-03 -4.57162559e-01 5.03750563e-01
-4.59903292e-02 -4.61005606e-02 6.63704991e-01 7.21742630e-01
4.05208379e-01 1.02252975e-01 -8.59646559e-01 1.30644846e+00
1.76349804e-01 -1.58878756e+00 7.05475390e-01 -1.25024438e-01
1.16450024e+00 -6.72144353e-01 2.43187785e-01 -4.17463072e-02
5.37935019e-01 -9.22834694e-01 1.13743651e+00 6.99401915e-01
1.16170096e+00 -7.77154267e-01 3.72959524e-01 -2.59598233e-02
-1.00052607e+00 8.59284252e-02 -6.26696408e-01 2.99368799e-01
3.12490195e-01 5.76023042e-01 -3.76565129e-01 5.79100490e-01
8.30040157e-01 8.20719004e-01 -4.65698451e-01 9.13070560e-01
-6.01388551e-02 2.73785624e-03 -4.54409011e-02 2.52201594e-02
4.18705434e-01 -6.70645118e-01 4.03306097e-01 1.10760057e+00
5.70358098e-01 3.55896577e-02 2.06078961e-03 1.30873787e+00
-3.72087121e-01 1.26117811e-01 -8.04173589e-01 -9.03453976e-02
2.15450123e-01 1.35801280e+00 -8.25930715e-01 -6.14175498e-01
-2.48343751e-01 1.13034654e+00 1.19057801e-02 5.53891897e-01
-8.28510344e-01 -5.92359126e-01 4.41045970e-01 1.45182282e-01
5.05399853e-02 -3.89445163e-02 -4.36150730e-01 -1.41013849e+00
9.51298252e-02 -1.11108017e+00 -3.58058274e-01 -1.35595775e+00
-1.27911985e+00 8.46707225e-01 -3.21308464e-01 -1.55201817e+00
1.35616392e-01 -5.41731000e-01 -7.36747026e-01 7.58754730e-01
-1.44349408e+00 -1.56581438e+00 -6.43268108e-01 6.63444877e-01
7.70336032e-01 -1.73246652e-01 4.43088382e-01 3.01643372e-01
-5.25128663e-01 4.57292378e-01 3.52361321e-01 2.50298023e-01
7.96846628e-01 -1.18167663e+00 5.40463388e-01 9.18893278e-01
2.26691421e-02 3.21902603e-01 7.42246330e-01 -6.52020514e-01
-1.37335563e+00 -1.26912940e+00 4.46758687e-01 -3.56161222e-02
3.69715303e-01 -4.69256163e-01 -7.49114215e-01 4.82363850e-01
6.15876079e-01 -4.34091687e-01 1.83928944e-02 -5.69058895e-01
-2.67493993e-01 -1.57310098e-01 -1.08730769e+00 1.11457336e+00
1.00925684e+00 -2.99924254e-01 -2.21702889e-01 2.80308902e-01
5.65290153e-01 -3.57689708e-01 -4.85857666e-01 1.18707016e-01
8.54881585e-01 -1.06270540e+00 9.83369350e-01 -4.03873861e-01
8.51054132e-01 -4.23382998e-01 -3.18004824e-02 -1.40565526e+00
-3.20598364e-01 -7.28284955e-01 5.60405970e-01 1.35131955e+00
1.11507572e-01 -5.83262086e-01 7.12170005e-01 3.97220105e-01
-6.31127805e-02 -3.83879662e-01 -3.18024904e-01 -5.93164504e-01
-9.37266555e-03 -7.56637892e-03 9.67301428e-01 1.04602718e+00
-6.68581545e-01 -2.18175282e-03 -8.47588062e-01 -1.29161239e-01
6.58145845e-01 4.50811595e-01 1.02978408e+00 -9.05111790e-01
-1.81382969e-02 -6.11986220e-01 -1.18677974e-01 -6.09382331e-01
9.34990775e-03 -5.69484651e-01 9.50077549e-03 -1.64646995e+00
2.29590848e-01 -3.22220236e-01 2.05858663e-01 4.06845272e-01
3.11813634e-02 7.68852830e-01 6.29185915e-01 1.23383820e-01
-1.35065436e-01 7.04117000e-01 1.93209589e+00 -1.45978212e-01
1.97239574e-02 -3.56835186e-01 -8.37111771e-01 9.21276152e-01
8.39804053e-01 -1.90148950e-01 -3.60732406e-01 -5.63320637e-01
1.37791097e-01 -3.45488824e-02 5.11217535e-01 -9.87611771e-01
-1.92231387e-01 -3.65095586e-01 7.66804039e-01 -5.87173223e-01
5.21126151e-01 -9.04494703e-01 4.57335562e-01 3.72059613e-01
-2.91095048e-01 3.09368044e-01 1.64986715e-01 5.34604311e-01
-2.35423237e-01 -8.01211894e-02 1.18933058e+00 -2.68628150e-01
-8.04762244e-01 3.37387443e-01 -1.75172701e-01 -7.92238116e-02
9.36885834e-01 -3.93419951e-01 -3.15485865e-01 -7.00002849e-01
-5.37677407e-01 -2.61121720e-01 9.28826928e-01 6.61937416e-01
7.06041217e-01 -1.63637173e+00 -7.87288964e-01 3.37313414e-01
-2.15570137e-01 -4.37862240e-02 5.56221485e-01 4.66480851e-01
-1.04601550e+00 1.82866782e-01 -8.94840479e-01 -2.40648314e-01
-1.15002203e+00 6.09519899e-01 2.92642742e-01 -1.30449422e-03
-9.70527351e-01 4.07008410e-01 8.98731768e-01 -3.10507059e-01
1.12274964e-03 -3.28744709e-01 -3.14584412e-02 6.88996390e-02
4.68572229e-01 1.68617249e-01 -2.61740059e-01 -5.60638547e-01
2.10148215e-01 9.23535228e-01 -1.93143994e-01 -5.51772118e-02
1.26833212e+00 -1.32091686e-01 -2.78761357e-01 -1.13568097e-01
1.09055328e+00 1.60220370e-01 -1.46781409e+00 -2.20722347e-01
-5.80333292e-01 -7.92070985e-01 -1.30063295e-01 -7.43870914e-01
-1.47083652e+00 9.83087242e-01 3.98420185e-01 1.29887700e-01
1.30951858e+00 -6.29772365e-01 1.15260482e+00 1.57723621e-01
1.66845366e-01 -1.18419003e+00 2.07813084e-01 8.52344781e-02
1.30691862e+00 -1.06771028e+00 -6.44719601e-02 -4.30738181e-01
-9.22371745e-01 1.30554938e+00 7.59553730e-01 -4.37386304e-01
1.12540074e-01 2.18225792e-02 1.94345132e-01 1.40639776e-02
-3.78591746e-01 -2.44840905e-02 3.35493267e-01 5.92091501e-01
5.01822978e-02 1.22025564e-01 1.14464378e-02 2.08759338e-01
-4.42178607e-01 1.02246245e-02 9.11183059e-01 4.74493980e-01
-2.62465537e-01 -1.00652313e+00 -6.19743645e-01 2.35629335e-01
-2.57720351e-01 -2.24560529e-01 -4.29744184e-01 9.79099154e-01
1.51680440e-01 6.42828286e-01 1.37552842e-02 -2.23395005e-01
3.86512816e-01 -2.81482846e-01 3.80398363e-01 -2.43078917e-01
-3.06234449e-01 2.82746255e-01 -1.25172824e-01 -5.41784585e-01
-2.86151260e-01 -4.51802313e-01 -9.30775642e-01 -7.20183909e-01
1.74793318e-01 -3.13722253e-01 5.86769044e-01 6.50975049e-01
1.92554981e-01 5.90993941e-01 5.50754547e-01 -1.11744905e+00
-2.35977650e-01 -6.85423255e-01 -7.85689533e-01 8.16952169e-01
2.50270605e-01 -4.62018281e-01 7.99301863e-02 3.70413870e-01] | [11.623879432678223, -0.7245042324066162] |
d65d64be-33d1-4433-9b4b-bcd439df8d78 | multi-predict-few-shot-predictors-for | 2306.02459 | null | https://arxiv.org/abs/2306.02459v1 | https://arxiv.org/pdf/2306.02459v1.pdf | Multi-Predict: Few Shot Predictors For Efficient Neural Architecture Search | Many hardware-aware neural architecture search (NAS) methods have been developed to optimize the topology of neural networks (NN) with the joint objectives of higher accuracy and lower latency. Recently, both accuracy and latency predictors have been used in NAS with great success, achieving high sample efficiency and accurate modeling of hardware (HW) device latency respectively. However, a new accuracy predictor needs to be trained for every new NAS search space or NN task, and a new latency predictor needs to be additionally trained for every new HW device. In this paper, we explore methods to enable multi-task, multi-search-space, and multi-HW adaptation of accuracy and latency predictors to reduce the cost of NAS. We introduce a novel search-space independent NN encoding based on zero-cost proxies that achieves sample-efficient prediction on multiple tasks and NAS search spaces, improving the end-to-end sample efficiency of latency and accuracy predictors by over an order of magnitude in multiple scenarios. For example, our NN encoding enables multi-search-space transfer of latency predictors from NASBench-201 to FBNet (and vice-versa) in under 85 HW measurements, a 400$\times$ improvement in sample efficiency compared to a recent meta-learning approach. Our method also improves the total sample efficiency of accuracy predictors by over an order of magnitude. Finally, we demonstrate the effectiveness of our method for multi-search-space and multi-task accuracy prediction on 28 NAS search spaces and tasks. | ['Mohamed S. Abdelfattah', 'Yash Akhauri'] | 2023-06-04 | null | null | null | null | ['architecture-search'] | ['methodology'] | [-1.05351441e-01 -5.77908218e-01 -4.31920469e-01 -6.44154072e-01
-9.94056582e-01 -3.38431418e-01 4.42743972e-02 -2.34824624e-02
-7.20449507e-01 5.61468422e-01 -3.37326348e-01 -5.35049558e-01
-3.00733209e-01 -6.03175163e-01 -9.81457829e-01 -3.90798092e-01
-5.65037914e-02 4.80834812e-01 5.93732953e-01 6.81065097e-02
4.46586721e-02 5.06514132e-01 -1.59485567e+00 3.12112302e-01
4.80910271e-01 1.65374875e+00 2.76838094e-01 6.94812715e-01
-7.83120245e-02 6.81459963e-01 -7.98936725e-01 -2.69084632e-01
3.40763330e-01 1.71536013e-01 -6.40078664e-01 -9.29704130e-01
7.19898701e-01 -4.51237172e-01 -4.41400081e-01 6.24315083e-01
7.72996068e-01 -1.60014089e-02 9.23960134e-02 -1.34151804e+00
-6.50854260e-02 8.75400841e-01 -4.90489244e-01 5.52146673e-01
-5.14372230e-01 1.16866425e-01 9.04662490e-01 -6.85105443e-01
1.03483602e-01 8.64878953e-01 7.26666272e-01 4.96187061e-01
-1.16554332e+00 -1.27805090e+00 1.47180170e-01 4.64869946e-01
-1.60238552e+00 -7.35893309e-01 5.62749565e-01 1.03674799e-01
1.79621410e+00 3.75467807e-01 6.08250439e-01 1.18503797e+00
4.62857127e-01 4.94705349e-01 5.40697813e-01 -3.52878749e-01
6.39215469e-01 -1.94174349e-01 3.39321882e-01 6.27890110e-01
2.71573961e-01 2.11598665e-01 -7.50132680e-01 -1.52427778e-01
7.13489771e-01 -5.73046831e-03 1.18546277e-01 6.33995011e-02
-1.00741887e+00 4.51450437e-01 6.17942750e-01 1.58658296e-01
-3.42946649e-01 8.65424275e-01 8.94290805e-01 2.60974616e-01
3.09085995e-01 6.99697554e-01 -1.03206253e+00 -5.17140090e-01
-1.33374512e+00 1.17717706e-01 7.89060652e-01 1.14050376e+00
4.89990860e-01 6.71497107e-01 -2.85066456e-01 7.99389899e-01
-8.55292454e-02 6.10684633e-01 7.39371061e-01 -8.90678227e-01
5.08275270e-01 5.95338225e-01 -4.14493144e-01 -3.17280918e-01
-7.68416822e-01 -9.31005836e-01 -8.45818043e-01 9.24139023e-02
-1.33221820e-01 -1.44485936e-01 -9.53727663e-01 1.99102437e+00
1.63760930e-01 4.67333823e-01 -1.98206976e-01 6.38119042e-01
3.39001566e-01 7.25278080e-01 6.45352602e-02 -1.79499716e-01
1.45268393e+00 -1.23048282e+00 -3.30576628e-01 -2.96359390e-01
7.56044030e-01 -6.55532300e-01 1.04909718e+00 3.67674351e-01
-1.32370913e+00 -6.55973017e-01 -1.29949701e+00 -2.67218389e-02
-1.62988842e-01 2.31200919e-01 5.17973781e-01 7.86941707e-01
-1.21922171e+00 4.86860603e-01 -1.15871263e+00 -5.28025404e-02
2.30865195e-01 1.14412558e+00 3.33247185e-01 3.03940177e-01
-7.63059437e-01 5.68324327e-01 3.00528735e-01 -2.54739821e-01
-9.63123679e-01 -1.24893367e+00 -2.24680141e-01 5.07528067e-01
4.26176131e-01 -8.09069991e-01 1.37105596e+00 -7.69506514e-01
-1.62278092e+00 8.11804831e-02 -1.03097200e-01 -8.93543720e-01
-2.37383604e-01 -3.34234387e-01 -6.77095413e-01 -4.45474446e-01
-3.29071105e-01 6.93727672e-01 5.75917661e-01 -5.55409014e-01
-7.30969131e-01 -3.66606176e-01 -1.13351658e-01 -1.21049307e-01
-9.72313881e-01 -1.39716119e-01 -4.47191179e-01 -6.64108574e-01
-2.67019510e-01 -9.44567740e-01 1.56276803e-02 -1.58714592e-01
-1.16355933e-01 -4.41072956e-02 8.30029786e-01 -4.93151367e-01
1.59023666e+00 -2.11709833e+00 -4.39216346e-02 1.51022986e-01
3.95865351e-01 3.00297379e-01 -2.97511339e-01 -2.94647187e-01
2.21447214e-01 -1.01934532e-02 2.84221143e-01 -3.85051727e-01
-9.16685238e-02 9.08719897e-02 -1.68772489e-01 6.24704063e-02
-3.74706183e-03 7.50805497e-01 -2.26450250e-01 -2.13943481e-01
-1.33788124e-01 4.19009894e-01 -7.61760175e-01 8.94718245e-02
-9.03600082e-02 -2.40367904e-01 -3.20199668e-01 8.82254064e-01
3.62425178e-01 -4.96823907e-01 2.31779054e-01 -5.38428307e-01
-2.21761987e-01 4.97328639e-01 -8.27536047e-01 1.70391750e+00
-1.09962332e+00 7.32952416e-01 1.76510159e-02 -6.48606300e-01
1.02165377e+00 2.23162666e-01 3.07370275e-01 -1.17213631e+00
2.66132772e-01 7.23009408e-01 1.25967696e-01 1.67475462e-01
4.68398333e-01 4.34014380e-01 1.07399160e-02 3.51235151e-01
6.74219476e-03 3.90578657e-01 -1.79807276e-01 -4.16459173e-01
1.52579343e+00 -3.15774828e-01 -1.19459085e-01 -5.37639081e-01
3.53600293e-01 6.03025034e-02 6.19232118e-01 5.45607090e-01
-1.41111046e-01 -1.51625901e-01 2.47856621e-02 -7.86865950e-01
-1.30296659e+00 -8.16009939e-01 -1.02208145e-01 1.52333856e+00
-1.73746049e-01 -3.90359849e-01 -8.17065001e-01 -4.27104264e-01
-8.00800547e-02 8.59536707e-01 -2.62861371e-01 -4.04945761e-01
-1.05843413e+00 -5.09894967e-01 1.08280051e+00 9.37142849e-01
5.87089479e-01 -5.55437803e-01 -1.28000951e+00 4.43996429e-01
3.73871565e-01 -1.15051794e+00 -6.37657166e-01 8.67014468e-01
-1.28118777e+00 -4.61171359e-01 -2.61977762e-01 -8.13830018e-01
2.71795899e-01 -6.67702928e-02 1.10355914e+00 1.12079129e-01
-3.66862506e-01 -1.63632572e-01 2.65278816e-01 -1.71733528e-01
-6.20152242e-02 6.79836988e-01 3.82943571e-01 -4.66323912e-01
2.29311138e-01 -7.42181599e-01 -6.37635827e-01 3.37545305e-01
-5.45324981e-01 8.40588808e-02 9.14632380e-01 9.58635211e-01
6.68760717e-01 -1.22719109e-01 5.36848366e-01 -4.89786953e-01
2.43627325e-01 -4.01478201e-01 -9.57047880e-01 3.74636054e-01
-1.34069204e+00 5.52162349e-01 9.56383884e-01 -8.99197459e-01
-6.84274793e-01 2.91985404e-02 -1.97126091e-01 -9.67156947e-01
2.32225999e-01 2.15793386e-01 2.53451556e-01 -3.93603295e-01
7.73629665e-01 1.28141671e-01 -1.29777491e-01 -4.97109264e-01
-1.45771243e-02 4.65581417e-01 3.84395540e-01 -7.09056854e-01
3.79714608e-01 -1.04691550e-01 3.08095515e-01 -4.00089353e-01
-1.81976646e-01 -9.84378904e-02 -1.61793739e-01 8.71487856e-02
3.58669668e-01 -1.11806619e+00 -9.75322902e-01 2.21214160e-01
-1.03298426e+00 -7.37916589e-01 -1.26499057e-01 3.96724105e-01
-1.65134162e-01 -3.07077795e-01 -7.22036123e-01 -5.72637081e-01
-1.11093032e+00 -1.70912063e+00 9.16594863e-01 2.56660938e-01
-2.92555988e-01 -6.35400891e-01 -3.77924860e-01 -6.17262386e-02
1.06153727e+00 -4.52756107e-01 1.33800197e+00 -8.34557414e-01
-8.00090373e-01 -7.78447017e-02 -4.83848810e-01 8.03734884e-02
-3.62104177e-01 -1.56417519e-01 -8.21629405e-01 -4.78922844e-01
2.34565102e-02 -2.31514290e-01 5.82596362e-01 6.23493850e-01
1.50038874e+00 -3.11676770e-01 -4.70325768e-01 9.97606695e-01
1.55478990e+00 5.75309217e-01 1.00063950e-01 3.93737048e-01
5.40535688e-01 -6.20936379e-02 1.93457097e-01 4.23735023e-01
2.22994328e-01 1.25857675e+00 4.73289043e-01 1.25169009e-01
-2.61726558e-01 1.58691123e-01 4.80113328e-01 1.03349924e+00
1.95151284e-01 -2.30557501e-01 -1.04300880e+00 3.54706466e-01
-1.45354831e+00 -2.30404913e-01 3.08337986e-01 2.42466259e+00
8.56746614e-01 4.09067422e-01 5.92998303e-02 -4.28401306e-02
2.33399421e-01 -1.23588137e-01 -1.02164936e+00 -6.66206241e-01
2.98624188e-01 6.50361121e-01 9.24500942e-01 1.98669687e-01
-5.54460526e-01 7.32426107e-01 5.78484821e+00 1.32184398e+00
-1.58369017e+00 4.69705641e-01 9.12771821e-01 -8.32405388e-01
-2.07661353e-02 -1.78718135e-01 -1.33607721e+00 4.12570029e-01
1.87383699e+00 2.57937592e-02 6.02134645e-01 1.44412398e+00
-2.22491845e-01 2.33062953e-01 -1.28931260e+00 1.13800836e+00
-1.66044027e-01 -1.68021417e+00 -2.34216243e-01 9.34033543e-02
5.84321618e-01 2.46734083e-01 1.09608054e-01 5.88645160e-01
-1.63350493e-01 -6.92153692e-01 9.21313226e-01 1.03769332e-01
1.36351466e+00 -1.02718365e+00 7.89238870e-01 2.23686650e-01
-1.53826046e+00 -5.20087779e-01 -2.07998365e-01 6.29545376e-02
-1.82099491e-02 5.55375814e-01 -7.04119265e-01 5.55686317e-02
9.30671990e-01 -6.02552891e-02 -5.73983610e-01 9.02339935e-01
5.31889319e-01 6.29121959e-01 -5.55497885e-01 -5.43637872e-01
7.92063996e-02 4.37022209e-01 1.41307995e-01 1.11182570e+00
5.96735716e-01 -7.89690763e-02 -1.05781786e-01 7.61710823e-01
-2.67231286e-01 -1.29140794e-01 7.90693089e-02 2.28752732e-01
1.08202565e+00 1.06809473e+00 -5.61416686e-01 -2.40006030e-01
-1.57580301e-01 7.51171410e-01 4.17294651e-01 1.07671022e-01
-1.22283888e+00 -3.05028737e-01 9.45768714e-01 8.78255256e-03
3.34689468e-02 -2.62311131e-01 -8.67621541e-01 -4.43732172e-01
-1.40339695e-02 -7.45805740e-01 6.09701909e-02 -2.81830698e-01
-7.05459774e-01 1.00532210e+00 -1.71835393e-01 -6.87767863e-01
-3.26007366e-01 -5.18873513e-01 -3.57622266e-01 7.80704439e-01
-1.19832015e+00 -8.95694196e-01 -3.07344019e-01 2.41677225e-01
9.93008316e-01 -6.81710422e-01 7.84758568e-01 6.53466821e-01
-8.50483418e-01 1.32295370e+00 1.32488489e-01 -4.82283056e-01
5.97908854e-01 -7.42069244e-01 7.69648492e-01 6.04802072e-01
-5.70587404e-02 5.83992481e-01 3.34507555e-01 -5.37503123e-01
-1.94555008e+00 -1.07595706e+00 6.24414384e-01 -4.32288498e-02
5.14782608e-01 -4.59344059e-01 -8.34200680e-01 4.81274545e-01
-1.38286427e-01 4.58330251e-02 4.52185929e-01 3.08633208e-01
-4.25431460e-01 -8.54214013e-01 -8.13682795e-01 5.21918297e-01
1.04192412e+00 -3.11996669e-01 4.32180166e-01 2.39696205e-01
1.20329428e+00 -7.10115969e-01 -9.01424706e-01 6.79098547e-01
7.80447006e-01 -7.25242555e-01 1.10375011e+00 -2.20940888e-01
9.82775092e-02 1.30957857e-01 -4.52184707e-01 -6.93603933e-01
-4.05630052e-01 -3.05977672e-01 -7.10622370e-01 7.76996315e-01
5.73612094e-01 -5.29036939e-01 1.04617012e+00 5.29903948e-01
-6.18329048e-01 -1.45310426e+00 -1.35726595e+00 -9.99256968e-01
-2.53654689e-01 -5.64972043e-01 9.43666577e-01 4.19836462e-01
-5.42725265e-01 4.04009968e-01 -2.22181693e-01 1.22821845e-01
4.22416747e-01 -2.26063013e-01 3.88922632e-01 -9.98758972e-01
-6.45654559e-01 -8.72596800e-01 -7.88837448e-02 -1.10898530e+00
7.36675411e-02 -5.71531355e-01 -1.10969849e-01 -7.22199678e-01
-1.40191717e-02 -9.90493536e-01 -4.62489933e-01 6.66372359e-01
2.90040344e-01 2.25203158e-03 8.39557275e-02 3.64605039e-01
-5.05368233e-01 4.41484869e-01 4.62486237e-01 2.26879790e-02
-3.33373219e-01 -5.61465435e-02 -1.16694055e-01 2.17106193e-01
6.19986773e-01 -4.55149114e-01 -5.12376726e-01 -9.85875368e-01
2.06308633e-01 1.89956352e-01 1.46155208e-01 -1.63632333e+00
6.75535440e-01 3.09244115e-02 4.48105365e-01 -4.79391247e-01
6.61041081e-01 -9.57795322e-01 5.18646955e-01 9.09379423e-01
-2.44962513e-01 7.75635242e-01 7.76586235e-01 3.62223655e-01
1.62139535e-01 -2.34709308e-02 7.37171412e-01 4.31792587e-01
-9.12085414e-01 3.21281672e-01 8.42425004e-02 -3.43725622e-01
9.40517843e-01 -1.21956401e-01 -6.29019558e-01 1.75521940e-01
-2.94646263e-01 1.39132608e-02 1.12838075e-01 2.23847613e-01
7.06185520e-01 -1.27618110e+00 -2.39853576e-01 4.50147748e-01
-2.06602111e-01 -1.40552908e-01 4.09623206e-01 9.24756110e-01
-6.66863143e-01 8.54623556e-01 -3.14097911e-01 -6.49068892e-01
-1.32935727e+00 3.36997747e-01 2.11760715e-01 -4.84948456e-01
-1.67478129e-01 1.23202837e+00 -1.72241077e-01 -6.68626651e-02
5.42066813e-01 -4.11593705e-01 3.87384385e-01 -4.99131441e-01
4.68136102e-01 7.92342663e-01 5.36817372e-01 8.67159888e-02
-5.73082983e-01 4.01852280e-01 -1.87519431e-01 1.49058178e-01
1.26029706e+00 1.17897496e-01 -3.98860760e-02 4.02815551e-01
1.26948404e+00 -3.47125202e-01 -1.11396062e+00 -3.42599362e-01
4.58224528e-02 1.15777016e-01 6.96124852e-01 -9.95278537e-01
-1.29417074e+00 7.41542637e-01 1.13230288e+00 -1.78868458e-01
1.78029537e+00 -2.61438757e-01 1.21607196e+00 3.58266294e-01
6.50167167e-01 -9.91858065e-01 1.35298356e-01 5.62699139e-01
3.86760384e-01 -8.34181845e-01 -1.39106020e-01 -9.60261822e-02
-1.76592037e-01 1.31525612e+00 1.12402654e+00 1.39428958e-01
6.58305049e-01 9.43419278e-01 -5.06509304e-01 -7.89521709e-02
-1.26569128e+00 5.64491868e-01 4.39959079e-01 1.56099051e-01
2.59978324e-01 2.23427713e-01 1.62791684e-01 8.25083315e-01
-4.38116305e-02 6.25863746e-02 -3.83133180e-02 8.44160914e-01
-3.76745224e-01 -1.19217992e+00 -4.37875278e-02 7.94802964e-01
-1.64282337e-01 -3.66845399e-01 2.79449642e-01 6.09329164e-01
-4.76217121e-02 4.63381946e-01 4.54764217e-01 -1.12305653e+00
1.63189277e-01 3.00991982e-01 2.77543604e-01 -3.59785229e-01
-1.02023864e+00 7.85646513e-02 1.52559370e-01 -9.16641712e-01
4.75264937e-01 -1.80514127e-01 -1.30919850e+00 -8.12292039e-01
-4.34528291e-01 -2.94378877e-01 1.30449724e+00 7.83814669e-01
9.04420078e-01 1.04419541e+00 4.07888710e-01 -6.91946507e-01
-8.72008443e-01 -6.19312286e-01 -1.89426541e-01 -5.81631184e-01
1.18691303e-01 -5.62824070e-01 -6.02368303e-02 -4.64172661e-01] | [8.508374214172363, 2.994194984436035] |
8ba294d2-49e0-43ad-987f-b48c8d2e6a88 | edge-aware-guidance-fusion-network-for-rgb | 2112.05144 | null | https://arxiv.org/abs/2112.05144v1 | https://arxiv.org/pdf/2112.05144v1.pdf | Edge-aware Guidance Fusion Network for RGB Thermal Scene Parsing | RGB thermal scene parsing has recently attracted increasing research interest in the field of computer vision. However, most existing methods fail to perform good boundary extraction for prediction maps and cannot fully use high level features. In addition, these methods simply fuse the features from RGB and thermal modalities but are unable to obtain comprehensive fused features. To address these problems, we propose an edge-aware guidance fusion network (EGFNet) for RGB thermal scene parsing. First, we introduce a prior edge map generated using the RGB and thermal images to capture detailed information in the prediction map and then embed the prior edge information in the feature maps. To effectively fuse the RGB and thermal information, we propose a multimodal fusion module that guarantees adequate cross-modal fusion. Considering the importance of high level semantic information, we propose a global information module and a semantic information module to extract rich semantic information from the high-level features. For decoding, we use simple elementwise addition for cascaded feature fusion. Finally, to improve the parsing accuracy, we apply multitask deep supervision to the semantic and boundary maps. Extensive experiments were performed on benchmark datasets to demonstrate the effectiveness of the proposed EGFNet and its superior performance compared with state of the art methods. The code and results can be found at https://github.com/ShaohuaDong2021/EGFNet. | ['Yaguan Qian', 'Caie Xu', 'Shaohua Dong', 'WuJie Zhou'] | 2021-12-09 | null | null | null | null | ['scene-parsing', 'thermal-image-segmentation'] | ['computer-vision', 'computer-vision'] | [ 3.57436925e-01 -2.06360593e-02 5.85694760e-02 -7.72847295e-01
-9.25307333e-01 -2.84146369e-01 3.17353398e-01 4.63547534e-04
-4.09463197e-01 2.35321954e-01 1.06522210e-01 -1.14992835e-01
-7.02693090e-02 -8.79155934e-01 -7.59752870e-01 -7.74488747e-01
4.96665061e-01 -1.30421817e-01 3.48737866e-01 -1.46419778e-01
7.40405023e-02 -6.80422485e-02 -1.55132473e+00 4.16302830e-01
1.24108565e+00 1.46646678e+00 6.27349615e-01 3.73612881e-01
-4.37110811e-01 3.71160090e-01 -1.18694715e-01 -2.57895112e-01
1.46077558e-01 -2.85505623e-01 -6.02850974e-01 9.53821372e-03
1.48034215e-01 -3.65237027e-01 -1.62606239e-01 1.22480011e+00
4.49460685e-01 1.08075716e-01 1.60276473e-01 -1.18524444e+00
-3.61515462e-01 3.63658011e-01 -7.05783546e-01 -1.67098925e-01
3.31874251e-01 7.89677203e-02 9.06061471e-01 -8.10513079e-01
3.51133287e-01 1.00921714e+00 5.29375017e-01 3.12925667e-01
-6.46755040e-01 -6.63897872e-01 3.72305989e-01 4.34501320e-01
-1.00243735e+00 -2.45136663e-01 1.20790827e+00 2.11849492e-02
5.92233360e-01 1.47493824e-01 5.96744001e-01 8.59552920e-01
4.07345705e-02 1.01574659e+00 1.12989211e+00 -2.58022100e-01
-1.55961318e-02 -1.36701792e-01 1.65312454e-01 1.09636283e+00
-7.80489892e-02 -4.52284291e-02 -6.85182095e-01 2.59890139e-01
4.65678364e-01 1.74208909e-01 -2.61520833e-01 -9.42694098e-02
-1.02476943e+00 6.08363628e-01 9.77740049e-01 3.75567317e-01
-4.42760319e-01 1.87871158e-01 2.27610454e-01 -2.00406000e-01
6.06624663e-01 -2.28214785e-01 -4.64769423e-01 -4.36183810e-03
-6.93155289e-01 -3.03950787e-01 1.21127464e-01 7.47718036e-01
1.26851201e+00 -2.95237064e-01 8.29976576e-04 8.48753989e-01
6.59542322e-01 5.41003346e-01 2.78940618e-01 -9.73657906e-01
7.95707643e-01 9.16597366e-01 -1.64037347e-01 -1.11671591e+00
-6.13550246e-01 -2.05165863e-01 -8.19983900e-01 -1.40382543e-01
1.25698686e-01 -1.15160488e-01 -1.24718893e+00 1.53388083e+00
5.87643743e-01 3.96008700e-01 1.24063820e-01 1.14340281e+00
1.18571234e+00 6.51353538e-01 7.50964507e-02 1.04797296e-01
1.53864133e+00 -1.03430557e+00 -6.38562500e-01 -4.87674505e-01
6.13621950e-01 -6.92007422e-01 1.01916051e+00 1.09153464e-01
-7.11304247e-01 -5.55058241e-01 -1.13452697e+00 -3.68056804e-01
-4.00110245e-01 4.63969707e-01 8.99379253e-01 5.13880849e-01
-8.29721689e-01 4.40001637e-01 -1.20471168e+00 -1.61811426e-01
4.53280896e-01 4.26698685e-01 -4.51802015e-01 -5.16068041e-01
-1.25589120e+00 4.89358127e-01 6.30826592e-01 7.11048424e-01
-3.85496080e-01 -3.86414468e-01 -1.16498005e+00 -1.80510223e-01
4.14296061e-01 -6.65833294e-01 8.77630055e-01 -7.75808275e-01
-1.45355415e+00 4.21837032e-01 -2.64279008e-01 1.91602662e-01
2.00512409e-01 -3.45931500e-01 -5.79035953e-02 4.42199886e-01
1.59388766e-01 7.63465166e-01 5.35397887e-01 -1.32194149e+00
-8.40995669e-01 -6.46216393e-01 1.40903488e-01 4.67910081e-01
-7.14148939e-01 -2.34076038e-01 -9.16764915e-01 -3.33661735e-01
6.98116422e-01 -6.72381282e-01 -3.05084467e-01 -3.22821736e-01
-5.60018837e-01 -8.14282745e-02 8.09421897e-01 -8.87422264e-01
9.36691821e-01 -2.24651027e+00 1.61139205e-01 1.19860992e-01
6.76579997e-02 7.42536634e-02 -8.65885168e-02 2.76785600e-03
3.04461181e-01 -4.17114282e-03 -5.82615376e-01 -6.91597164e-01
4.46453318e-02 2.53854811e-01 1.12530053e-01 3.31140429e-01
1.82022318e-01 1.04829323e+00 -7.97763586e-01 -6.04003549e-01
5.74879706e-01 7.73084939e-01 -3.84799510e-01 1.98822871e-01
-1.44587889e-01 5.94979942e-01 -1.00281167e+00 7.54482806e-01
9.56983864e-01 -1.67090073e-01 -1.63531572e-01 -6.74144089e-01
-2.52572056e-02 1.29332334e-01 -9.64443266e-01 2.34458542e+00
-5.26361465e-01 1.17183164e-01 2.66580820e-01 -1.04351580e+00
8.92020047e-01 9.55244303e-02 6.63215816e-01 -9.58414257e-01
4.72589284e-01 2.84509182e-01 -4.26458269e-01 -3.72102469e-01
5.96006691e-01 -4.46726754e-02 -3.12088996e-01 2.46146277e-01
-5.64728193e-02 -1.70201346e-01 -1.32730067e-01 1.73146680e-01
9.46173966e-01 4.70008790e-01 -3.08843553e-01 2.29378358e-01
6.30700231e-01 1.75087731e-02 9.21461880e-01 2.31923029e-01
-1.76240966e-01 7.59281874e-01 2.37561911e-01 -2.23935232e-01
-5.94927371e-01 -7.89565682e-01 1.34915486e-01 9.63055670e-01
7.58225858e-01 -5.40503740e-01 -8.95405412e-01 -7.87373066e-01
-2.59822011e-01 3.46680403e-01 -6.29432678e-01 -2.89110929e-01
-5.73631763e-01 -1.00773990e+00 2.65496343e-01 7.14369893e-01
1.19452369e+00 -8.30842555e-01 -6.05516136e-01 8.75178054e-02
-6.71480715e-01 -1.45503294e+00 -2.48803422e-01 2.10786402e-01
-7.88968921e-01 -9.68723416e-01 -3.45218658e-01 -6.56325758e-01
7.25277662e-01 3.69330227e-01 5.77327371e-01 2.16081187e-01
-2.27030396e-01 3.33010405e-01 -6.99984729e-01 -4.77525517e-02
1.88042279e-02 2.58472592e-01 -4.65255141e-01 7.72935078e-02
2.25707248e-01 -3.69662583e-01 -7.56752968e-01 1.91324130e-01
-9.43858981e-01 5.72428584e-01 6.96073949e-01 7.03727543e-01
5.77475786e-01 1.06064349e-01 1.99239045e-01 -5.76156735e-01
1.36165902e-01 -3.31076950e-01 -4.37630713e-01 3.64937782e-01
-2.86388308e-01 1.52668223e-01 4.56784964e-01 2.06276596e-01
-1.49845219e+00 4.62307185e-01 -3.90152305e-01 -3.03453803e-01
-2.54971832e-01 5.57527661e-01 -5.69710016e-01 1.75672434e-02
-5.13101630e-02 2.19164997e-01 -2.95939773e-01 -6.16092980e-01
4.65643257e-01 6.95970416e-01 6.28763616e-01 -6.83565378e-01
5.85990846e-01 5.45041502e-01 -5.59310205e-02 -4.15165305e-01
-9.59117770e-01 -3.79878461e-01 -6.63699269e-01 -3.38212937e-01
1.25831723e+00 -9.54526782e-01 -5.78226268e-01 7.13678539e-01
-1.03158796e+00 -1.53593078e-01 3.26561779e-01 4.72679466e-01
-3.84845525e-01 5.45717001e-01 -6.58287585e-01 -7.06023633e-01
-4.28087831e-01 -1.33748579e+00 1.49730790e+00 6.18864715e-01
6.50589406e-01 -8.02986264e-01 -3.79780710e-01 8.21025610e-01
2.21985370e-01 3.46229732e-01 5.83419502e-01 -6.31984398e-02
-7.18039870e-01 -1.18176222e-01 -6.49843395e-01 2.39108667e-01
3.05320799e-01 -1.33282870e-01 -1.09666836e+00 1.03181861e-01
-2.87867002e-02 -2.21330434e-01 1.37873256e+00 3.11368644e-01
1.05759072e+00 2.68552840e-01 -4.35820103e-01 9.15964663e-01
1.51808929e+00 5.96659891e-02 3.95062298e-01 3.74195248e-01
1.27908707e+00 6.37728989e-01 8.51258397e-01 4.81535673e-01
9.04464304e-01 4.73497182e-01 7.20432162e-01 -2.97566831e-01
-1.49219902e-02 -2.07099348e-01 2.98825502e-01 9.43902612e-01
-7.58047625e-02 -1.30174309e-01 -9.67859685e-01 3.42765689e-01
-2.08450437e+00 -2.99100339e-01 -1.46819368e-01 1.74161601e+00
4.66503173e-01 1.19584329e-01 -3.03359926e-01 9.45980921e-02
8.46018612e-01 1.57567084e-01 -5.27961195e-01 -2.04883814e-02
-1.56603068e-01 2.30149459e-02 5.76580048e-01 3.14515531e-01
-1.25534213e+00 1.18041039e+00 4.24264526e+00 8.34541082e-01
-1.08433211e+00 2.76819378e-01 7.79613614e-01 1.47909850e-01
-5.64372540e-01 1.41647220e-01 -5.86236596e-01 4.51544285e-01
5.66036820e-01 4.33462352e-01 2.33999297e-01 4.98429239e-01
6.15693554e-02 -3.78982127e-01 -6.04628980e-01 8.58977020e-01
-3.01907286e-02 -8.64313960e-01 -3.67617935e-01 -6.37406185e-02
5.33706427e-01 1.39725626e-01 1.23301186e-02 8.35409015e-02
3.22079509e-01 -7.07942188e-01 6.34546757e-01 7.18211234e-01
4.92767662e-01 -8.13657939e-01 8.71405303e-01 2.27785796e-01
-1.64397013e+00 -2.05056369e-01 -2.76800364e-01 1.72740236e-01
2.99763441e-01 8.06914926e-01 -2.52450973e-01 1.27646196e+00
8.76487672e-01 9.01017725e-01 -6.06600106e-01 6.90402508e-01
-4.70289677e-01 3.80351722e-01 -6.41365647e-01 2.90775478e-01
4.33634460e-01 -2.16850445e-01 6.82642385e-02 8.75883758e-01
5.04787445e-01 3.43268543e-01 2.58769274e-01 6.62109494e-01
5.93585186e-02 1.91550732e-01 -2.16311991e-01 1.09853983e-01
3.30059201e-01 1.60635424e+00 -1.06888318e+00 -2.37292260e-01
-5.62787652e-01 1.13662219e+00 3.29654902e-01 2.90424228e-01
-9.32851613e-01 -2.94949442e-01 4.23156947e-01 -4.96332169e-01
3.62338424e-01 -3.84159178e-01 -5.69546998e-01 -1.35143864e+00
2.70648599e-01 -2.19392940e-01 3.72904897e-01 -8.51758122e-01
-9.48537171e-01 6.80396855e-01 -9.50830728e-02 -1.04891515e+00
9.35992524e-02 -5.41261792e-01 -5.56494057e-01 6.55793369e-01
-1.69202816e+00 -1.59147477e+00 -7.58242190e-01 5.93903482e-01
2.91038334e-01 2.62979120e-01 4.01859790e-01 3.35118145e-01
-9.13052142e-01 3.86771500e-01 -1.52839407e-01 1.26695767e-01
5.05724728e-01 -1.19905329e+00 2.62897521e-01 1.03064847e+00
-6.48722649e-02 2.92260706e-01 2.96024352e-01 -6.25633597e-01
-1.63450229e+00 -1.10343289e+00 3.69312346e-01 -6.86508343e-02
2.41766721e-01 -3.83610785e-01 -8.06751668e-01 3.95156980e-01
8.15598890e-02 2.62097776e-01 3.39486063e-01 -1.32420331e-01
-1.65936381e-01 -2.37778813e-01 -9.58362937e-01 1.82027578e-01
1.07000649e+00 -4.56463873e-01 -2.39678591e-01 5.77813685e-02
9.58858252e-01 -4.66094077e-01 -8.60620856e-01 8.26729119e-01
4.59912688e-01 -1.17095697e+00 8.23650301e-01 2.13781431e-01
5.35419464e-01 -4.34101582e-01 -5.00553966e-01 -1.13770461e+00
-2.60489956e-02 3.98561284e-02 2.78970182e-01 1.39684129e+00
2.81782746e-01 -5.95996678e-01 9.30882454e-01 7.82965899e-01
-5.49273431e-01 -7.89177895e-01 -9.81231451e-01 -2.17673331e-01
-1.69299006e-01 -8.75158012e-01 6.80005193e-01 6.50329113e-01
-9.65475440e-02 2.59161830e-01 -3.25757742e-01 3.39964390e-01
6.75960779e-01 4.36482012e-01 4.88138258e-01 -1.01954687e+00
1.14591885e-02 -3.91422659e-01 -3.34551960e-01 -9.66444910e-01
2.11755693e-01 -8.76254082e-01 3.53053540e-01 -2.03191042e+00
2.20596179e-01 -5.84563136e-01 -5.28009534e-01 8.19404483e-01
-6.29210889e-01 4.45644230e-01 3.50028932e-01 -1.41190425e-01
-7.72780597e-01 9.94530022e-01 1.37882507e+00 -3.13218571e-02
-2.93173585e-02 -4.59699363e-01 -7.79477894e-01 7.39611566e-01
8.95671487e-01 -2.97844738e-01 -3.48479986e-01 -7.55241632e-01
1.66757017e-01 1.25933364e-01 4.54205424e-01 -9.89438176e-01
4.10409987e-01 -2.72448678e-02 4.66040045e-01 -7.29002595e-01
5.27098536e-01 -8.67698550e-01 -1.56021088e-01 1.34049878e-01
1.48390561e-01 -2.43149593e-01 1.73061460e-01 5.11681139e-01
-3.83496046e-01 1.44433035e-02 3.98509949e-01 -8.43578354e-02
-1.13346982e+00 4.00819242e-01 1.49909601e-01 -3.74624282e-01
8.74493957e-01 -1.91725239e-01 -3.11939031e-01 -3.49311419e-02
-5.99587560e-01 5.38272798e-01 5.13481319e-01 4.66630220e-01
8.67663562e-01 -1.29429531e+00 -4.04248267e-01 2.99485952e-01
1.61906794e-01 3.70474637e-01 7.33423471e-01 1.03978503e+00
-3.45340937e-01 2.21717492e-01 -1.90468684e-01 -7.37787545e-01
-1.14906120e+00 1.77733794e-01 2.03036577e-01 -6.65949956e-02
-5.12602687e-01 8.98387969e-01 3.04707110e-01 -6.01397038e-01
-1.16165996e-01 -5.09319305e-01 -2.26428464e-01 -2.18657916e-03
1.21009402e-01 2.90435608e-02 1.83683127e-01 -8.72871399e-01
-6.79816723e-01 9.00016129e-01 1.31127536e-01 -1.36506259e-01
1.39309359e+00 -4.20096189e-01 -1.54507428e-01 1.43162683e-01
1.30186188e+00 -3.59285355e-01 -1.38900638e+00 -3.24661642e-01
-1.30738989e-01 -4.14947599e-01 4.23085332e-01 -5.98389030e-01
-1.57265699e+00 1.09612131e+00 5.95435560e-01 -1.43414840e-01
1.75990152e+00 3.02201905e-03 1.16390777e+00 2.03501061e-02
2.64692307e-01 -1.07356322e+00 -6.08226983e-04 3.35863709e-01
3.98429483e-01 -1.49500418e+00 -7.84538593e-03 -8.00641239e-01
-5.75235724e-01 1.11359954e+00 8.25615466e-01 2.67543625e-02
6.10489607e-01 2.68616050e-01 1.41250238e-01 -1.66923150e-01
-5.94147444e-01 -5.18852890e-01 3.79490167e-01 2.80368000e-01
2.81568795e-01 2.86696665e-02 -1.76344723e-01 9.27620351e-01
-7.53999054e-02 -7.74506480e-02 1.17548764e-01 1.01299739e+00
-5.56087911e-01 -1.13410580e+00 -3.25093329e-01 2.73942053e-01
-2.64699697e-01 -1.36425018e-01 -1.45759702e-01 3.58613551e-01
4.32065368e-01 1.14944184e+00 -7.88066760e-02 -9.42079782e-01
1.55267894e-01 -6.68806583e-02 4.44744647e-01 -3.20165217e-01
-3.85779321e-01 2.85625994e-01 -1.10722054e-02 -7.71348119e-01
-6.78223491e-01 -5.50423384e-01 -1.64349020e+00 -2.63466593e-02
-4.05233890e-01 4.60224673e-02 1.01648104e+00 1.18855536e+00
3.86427760e-01 7.98090398e-01 6.18763089e-01 -9.79707837e-01
1.99097723e-01 -1.00937796e+00 -2.70131081e-01 2.02270836e-01
1.18644036e-01 -8.20742130e-01 -1.85515851e-01 -9.61753801e-02] | [9.463968276977539, -1.0915910005569458] |
31bfafca-f245-44ef-8fd3-e59d98686e8b | ground-plane-matters-picking-up-ground-plane | 2211.01556 | null | https://arxiv.org/abs/2211.01556v1 | https://arxiv.org/pdf/2211.01556v1.pdf | Ground Plane Matters: Picking Up Ground Plane Prior in Monocular 3D Object Detection | The ground plane prior is a very informative geometry clue in monocular 3D object detection (M3OD). However, it has been neglected by most mainstream methods. In this paper, we identify two key factors that limit the applicability of ground plane prior: the projection point localization issue and the ground plane tilt issue. To pick up the ground plane prior for M3OD, we propose a Ground Plane Enhanced Network (GPENet) which resolves both issues at one go. For the projection point localization issue, instead of using the bottom vertices or bottom center of the 3D bounding box (BBox), we leverage the object's ground contact points, which are explicit pixels in the image and easy for the neural network to detect. For the ground plane tilt problem, our GPENet estimates the horizon line in the image and derives a novel mathematical expression to accurately estimate the ground plane equation. An unsupervised vertical edge mining algorithm is also proposed to address the occlusion of the horizon line. Furthermore, we design a novel 3D bounding box deduction method based on a dynamic back projection algorithm, which could take advantage of the accurate contact points and the ground plane equation. Additionally, using only M3OD labels, contact point and horizon line pseudo labels can be easily generated with NO extra data collection and label annotation cost. Extensive experiments on the popular KITTI benchmark show that our GPENet can outperform other methods and achieve state-of-the-art performance, well demonstrating the effectiveness and the superiority of the proposed approach. Moreover, our GPENet works better than other methods in cross-dataset evaluation on the nuScenes dataset. Our code and models will be published. | ['Guiguang Ding', 'Kai Ni', 'Jungong Han', 'Yuchen Guo', 'Hui Chen', 'Xinhao Xu', 'Fan Yang'] | 2022-11-03 | null | null | null | null | ['monocular-3d-object-detection'] | ['computer-vision'] | [-8.63306075e-02 6.75324127e-02 -3.32106054e-01 -9.14843157e-02
-4.20849741e-01 -3.39935750e-01 2.19838411e-01 -1.22790448e-01
-1.19027101e-01 1.98549822e-01 -2.73412883e-01 -2.67973185e-01
-4.69255522e-02 -8.36808741e-01 -8.67081642e-01 -6.82373703e-01
3.00530523e-01 4.10456449e-01 6.44029319e-01 1.48712676e-02
3.39362174e-01 6.92263424e-01 -1.60313475e+00 -3.37548479e-02
7.37721443e-01 1.43186629e+00 1.75893307e-01 1.50324181e-01
-1.12927504e-01 2.52808034e-01 -3.82853121e-01 -2.10989222e-01
6.75040305e-01 1.26247808e-01 -2.45281637e-01 3.00980419e-01
6.56231523e-01 -6.11498237e-01 -1.30661979e-01 1.01953280e+00
5.27278423e-01 -2.24153265e-01 7.77709961e-01 -1.30437291e+00
-2.66607940e-01 5.37885912e-02 -1.20922399e+00 -1.18558273e-01
2.05284551e-01 -1.70512199e-01 8.91713619e-01 -1.29090071e+00
6.04693532e-01 9.84512925e-01 9.30416703e-01 -6.51384238e-03
-7.07562089e-01 -8.56068790e-01 3.58111233e-01 1.92421630e-01
-1.86075914e+00 -1.65106393e-02 1.06674981e+00 -5.69972038e-01
7.15302169e-01 1.13501184e-01 6.18048429e-01 6.64101541e-01
-8.59154314e-02 8.92213106e-01 1.00057018e+00 -6.35739446e-01
-7.48345107e-02 1.63022950e-01 2.41793796e-01 9.87502813e-01
3.65783185e-01 1.18370861e-01 -4.04202849e-01 1.10059366e-01
8.73499870e-01 8.19187239e-02 -4.35279548e-01 -8.73952985e-01
-8.53906274e-01 5.86713314e-01 6.01976931e-01 -2.66851574e-01
4.69627380e-02 -7.97654241e-02 4.15971130e-02 -2.32217297e-01
4.55384284e-01 8.26920569e-02 -2.71922082e-01 3.49010885e-01
-7.17582881e-01 1.97531909e-01 5.63864887e-01 1.34536767e+00
8.78032267e-01 -3.12581182e-01 -7.94789493e-02 5.74885309e-01
4.03369993e-01 5.11847198e-01 -1.48294389e-01 -7.10592330e-01
6.26568317e-01 1.15313399e+00 2.64515489e-01 -1.30865717e+00
-6.35946393e-01 -5.39556801e-01 -7.21707404e-01 2.50904828e-01
5.59319794e-01 1.53351361e-02 -8.63506079e-01 1.34343529e+00
7.94266343e-01 3.61156240e-02 -3.43149662e-01 1.13359523e+00
1.10288143e+00 4.50434625e-01 -6.51162803e-01 7.11525828e-02
1.55684221e+00 -1.02691507e+00 -3.10932755e-01 -3.06990623e-01
7.07957447e-01 -6.97799444e-01 8.78000915e-01 3.97101879e-01
-6.22681499e-01 -4.60258722e-01 -1.21622789e+00 -2.20257133e-01
-2.72913098e-01 6.99377894e-01 7.18386054e-01 7.02882767e-01
-5.62760770e-01 7.99933970e-02 -5.68704903e-01 -1.29947647e-01
4.22799617e-01 2.98839360e-01 -1.31543607e-01 -9.39938277e-02
-7.52420127e-01 5.50328493e-01 4.84349281e-01 2.71618545e-01
-3.26760530e-01 -5.81703007e-01 -7.53987670e-01 -5.86796328e-02
9.45682764e-01 -7.29614854e-01 9.72149193e-01 -3.52013528e-01
-1.26438999e+00 1.09194887e+00 -7.04910383e-02 -1.28409892e-01
7.34889746e-01 -2.88887352e-01 -7.10549653e-02 2.51312613e-01
9.18479860e-02 5.59553325e-01 7.68189371e-01 -1.33147740e+00
-9.04254198e-01 -6.29781246e-01 9.48152766e-02 4.10053611e-01
-8.92039910e-02 -2.63571650e-01 -8.49771202e-01 -3.06699902e-01
7.72438586e-01 -9.56886292e-01 7.30263740e-02 3.00257444e-01
-6.73297405e-01 -3.72586489e-01 8.78292501e-01 -4.34957743e-01
1.09959364e+00 -2.25094843e+00 -3.31251383e-01 3.29377055e-01
3.57350826e-01 1.27381518e-01 4.54299241e-01 8.83442461e-02
1.10901453e-01 8.43479559e-02 3.68802175e-02 -2.30910808e-01
8.79309177e-02 -1.50564179e-01 -2.51996040e-01 5.76255202e-01
1.27703249e-01 7.67056525e-01 -5.93131959e-01 -4.76929516e-01
2.27793053e-01 3.89140069e-01 -4.83439833e-01 -2.87675913e-02
-9.07772556e-02 3.51460576e-02 -5.43721855e-01 8.02776635e-01
1.18303621e+00 -3.68615627e-01 -2.16760412e-01 -5.62236547e-01
-3.28556597e-01 -1.24101937e-02 -1.71506393e+00 1.24154091e+00
6.79279193e-02 4.08616275e-01 -1.75167114e-01 -4.86853898e-01
1.28453624e+00 -2.58658826e-02 3.62445921e-01 -4.00061637e-01
4.30532426e-01 3.35754514e-01 -2.52160788e-01 -3.86319071e-01
4.47033018e-01 2.38056034e-01 1.57376409e-01 1.79642543e-01
-3.67844164e-01 -2.03055680e-01 -1.38710320e-01 -1.76203445e-01
4.89225447e-01 4.42806572e-01 5.03477156e-01 -2.09219158e-01
4.90575969e-01 5.78893013e-02 8.09610426e-01 6.24982059e-01
-1.61194906e-01 9.91220772e-01 4.73666012e-01 -5.66693008e-01
-7.93467402e-01 -7.66290724e-01 -3.41627121e-01 5.70355892e-01
8.62259388e-01 -4.55118001e-01 -7.01481760e-01 -6.04805946e-01
-7.38868564e-02 2.97808826e-01 -3.98629814e-01 1.53364494e-01
-5.66952229e-01 -7.58714616e-01 1.66998088e-01 6.24544680e-01
9.04808402e-01 -3.81052196e-01 -8.37663472e-01 -1.54450744e-01
-3.53102148e-01 -1.44584024e+00 -5.13217986e-01 1.16200387e-01
-6.85352683e-01 -1.16466272e+00 -5.87032795e-01 -7.85469651e-01
7.84035265e-01 6.86152935e-01 7.84122050e-01 3.88682224e-02
-1.60483822e-01 -1.84691008e-02 -3.17170531e-01 -7.03538537e-01
3.61116469e-01 3.18315215e-02 -7.74046332e-02 4.56707813e-02
4.81470942e-01 -2.55141079e-01 -8.34272385e-01 9.19797122e-01
-2.68486381e-01 5.52403092e-01 5.00852168e-01 5.67371905e-01
9.51969802e-01 3.87644261e-01 1.32926196e-01 -7.40050554e-01
-2.34100908e-01 -2.09743574e-01 -1.14372826e+00 -1.75991822e-02
-6.74984097e-01 -3.27304572e-01 1.09647073e-01 -2.16248050e-01
-9.62062597e-01 3.16672683e-01 9.15854201e-02 -7.10182011e-01
-1.09441787e-01 1.01691842e-01 -4.96298432e-01 -3.20759356e-01
4.89867181e-01 1.28921242e-02 -2.78726459e-01 -5.87523282e-01
8.03717375e-02 6.72980368e-01 4.33481961e-01 -4.43921179e-01
8.75301957e-01 9.03669357e-01 3.45896751e-01 -8.61884594e-01
-1.15717041e+00 -6.80824876e-01 -7.23861873e-01 -2.27551773e-01
8.10857058e-01 -1.07886314e+00 -7.76326299e-01 5.29453456e-01
-1.31370115e+00 1.55256897e-01 7.54380226e-02 4.30285782e-01
-2.86293358e-01 4.01553869e-01 -3.22972596e-01 -9.02654231e-01
-2.99932986e-01 -1.13687229e+00 1.41135097e+00 3.63386214e-01
2.71944612e-01 -4.74616885e-01 -4.47383076e-01 5.52800357e-01
-3.11992556e-01 4.65867311e-01 8.60870659e-01 -2.20218822e-01
-1.21955264e+00 -3.30566823e-01 -6.82789087e-01 -3.01205833e-02
-1.99516267e-01 -1.51942549e-02 -1.18875611e+00 -1.89116392e-02
1.07348949e-01 1.54205859e-01 6.20228529e-01 4.83150393e-01
1.13859558e+00 1.19742714e-02 -7.05158651e-01 1.12182558e+00
1.34954202e+00 7.83493370e-02 4.54193383e-01 6.05620742e-01
9.84730899e-01 7.07913220e-01 9.32702363e-01 4.54951227e-01
5.37785888e-01 9.22024965e-01 6.27238333e-01 -2.09563226e-01
-2.09786832e-01 -4.71323311e-01 8.46362263e-02 4.50894296e-01
-1.24678008e-01 -3.50752711e-01 -8.98226857e-01 3.38988751e-01
-1.73209536e+00 -3.51183057e-01 -6.66301727e-01 2.12041688e+00
2.47461006e-01 2.94070750e-01 1.55062294e-02 2.69655704e-01
8.03973317e-01 -1.13856934e-01 -5.58654308e-01 6.86918721e-02
-3.22989643e-01 -3.56451720e-01 7.30629206e-01 2.44519413e-01
-1.26946795e+00 8.03662419e-01 5.14650917e+00 9.77622211e-01
-1.03731537e+00 -1.43215686e-01 4.86997187e-01 2.12142333e-01
1.29426613e-01 7.53247738e-02 -1.60497546e+00 3.22167128e-01
-1.28012165e-01 2.24339217e-01 -2.52487380e-02 1.06466186e+00
2.30726469e-02 -2.98219264e-01 -1.11673045e+00 1.40660357e+00
2.42227212e-01 -1.05053508e+00 -1.55454546e-01 2.28210792e-01
8.16061139e-01 3.31723392e-02 -8.34167078e-02 -1.11606950e-03
-2.95994788e-01 -6.62509322e-01 9.14646208e-01 1.32345155e-01
7.84744561e-01 -6.03477657e-01 8.04978609e-01 7.09386468e-01
-1.48844457e+00 5.53759895e-02 -3.85944009e-01 -7.60049298e-02
1.03374422e-01 7.30432391e-01 -1.04183471e+00 8.20324481e-01
8.92477155e-01 4.29540992e-01 -6.48666799e-01 1.23904228e+00
-5.26258886e-01 1.82035029e-01 -7.95720696e-01 7.16639981e-02
1.16193734e-01 -3.89714748e-01 7.31752992e-01 8.56784582e-01
4.14030820e-01 5.10468930e-02 2.62604982e-01 1.00979269e+00
1.66048016e-02 2.59368151e-01 -6.14107788e-01 4.07718062e-01
4.83645886e-01 1.26607537e+00 -1.10572600e+00 5.63117955e-03
-4.48172599e-01 6.17491126e-01 2.59061188e-01 2.89494991e-01
-8.61977696e-01 -3.27293456e-01 1.46063253e-01 5.00691414e-01
6.23692751e-01 -1.53151929e-01 -5.44192076e-01 -1.11655426e+00
5.44950545e-01 -5.39719105e-01 3.51574779e-01 -9.61449504e-01
-1.01921749e+00 5.02509534e-01 1.22990429e-01 -1.47788250e+00
1.62760884e-01 -9.60304976e-01 -3.76238525e-01 7.04011083e-01
-1.61102057e+00 -1.30584121e+00 -7.87136555e-01 2.99199671e-01
1.69515148e-01 2.02739954e-01 4.24470514e-01 3.61336052e-01
-6.02382362e-01 5.79516351e-01 -2.30597511e-01 2.01110616e-01
3.95157367e-01 -9.58718419e-01 2.05754206e-01 8.48963737e-01
7.69981518e-02 4.46139336e-01 2.64239013e-01 -6.97857618e-01
-1.28142679e+00 -1.06421459e+00 5.65546453e-01 -5.96913517e-01
2.38513529e-01 -7.28298128e-01 -7.52318263e-01 6.07747316e-01
-4.73014981e-01 5.05820513e-02 2.64997095e-01 1.82086986e-03
-3.61561865e-01 -9.06839818e-02 -8.89684439e-01 5.73887110e-01
1.35978806e+00 -2.47705117e-01 -4.38156188e-01 2.92345494e-01
7.00723886e-01 -9.23727334e-01 -5.34279466e-01 8.91958833e-01
5.60332894e-01 -1.11783886e+00 1.11262834e+00 2.25187480e-01
1.88284531e-01 -8.25989068e-01 -1.59368783e-01 -6.80852771e-01
-1.20108977e-01 -4.78966862e-01 -2.61955678e-01 1.20034623e+00
1.93139687e-01 -6.11720383e-01 1.24581444e+00 2.99978346e-01
-3.25946689e-01 -1.06777978e+00 -8.98161292e-01 -8.24692965e-01
-3.84160966e-01 -5.31037211e-01 7.33274817e-01 7.21921504e-01
-5.39381981e-01 4.61225837e-01 -2.46059582e-01 5.87355614e-01
6.48205280e-01 6.36328042e-01 1.16744018e+00 -1.39870107e+00
-2.40392849e-01 -3.51724416e-01 -3.96845490e-01 -1.81493580e+00
-3.50717336e-01 -8.03746462e-01 -7.03534484e-03 -1.40560615e+00
1.58311680e-01 -6.16838455e-01 5.32172211e-02 2.66419619e-01
-6.47825301e-02 3.82898360e-01 -9.50289704e-03 2.51158267e-01
-3.76353323e-01 6.04881942e-01 1.43785298e+00 9.06620696e-02
-2.53213733e-01 2.80612260e-02 -5.59333980e-01 1.24498916e+00
5.14687836e-01 -4.47312742e-01 -3.13905835e-01 -4.68089700e-01
2.88849950e-01 -2.34312847e-01 4.79559213e-01 -8.59552383e-01
3.30524355e-01 -4.42356914e-02 4.45134372e-01 -1.39608431e+00
5.62276006e-01 -9.55673099e-01 1.87060591e-02 1.99660271e-01
5.39474666e-01 -2.96408087e-01 7.20419437e-02 6.17116511e-01
1.03572085e-01 -3.94480944e-01 6.85932219e-01 7.69592151e-02
-8.05210412e-01 4.52835232e-01 2.80727476e-01 -9.63033438e-02
1.24593282e+00 -8.00256371e-01 -3.48537087e-01 -4.02543582e-02
-2.07006097e-01 4.12390202e-01 6.41810119e-01 2.36589178e-01
6.78611696e-01 -1.22907519e+00 -4.22443569e-01 5.35028994e-01
4.90356445e-01 6.35823190e-01 9.47541296e-02 9.94985998e-01
-7.59601951e-01 4.16032284e-01 3.14363778e-01 -1.07628226e+00
-1.18727899e+00 5.53994298e-01 4.36404496e-01 1.11649744e-01
-1.05845368e+00 8.05315912e-01 7.46381581e-01 -3.62932324e-01
3.46249968e-01 -6.21356487e-01 -1.78801835e-01 6.27280027e-02
2.90161341e-01 3.62711489e-01 9.87239629e-02 -5.66973209e-01
-3.17556113e-01 1.24414682e+00 3.77135724e-02 3.97119910e-01
1.02838349e+00 -2.76160032e-01 1.92185730e-01 2.59006530e-01
8.87328565e-01 1.06959075e-01 -1.33366275e+00 -2.35910729e-01
-1.77263007e-01 -7.14043915e-01 2.34278083e-01 -4.94451672e-01
-8.11338961e-01 9.25638974e-01 7.14171469e-01 -3.40349823e-02
9.34107780e-01 -7.32797831e-02 6.92809582e-01 3.96134764e-01
4.85123307e-01 -1.05384910e+00 -6.59739152e-02 4.23120409e-01
6.90597117e-01 -1.35318100e+00 2.41997927e-01 -1.30121219e+00
-2.26403385e-01 1.14441884e+00 9.25803602e-01 -9.25212726e-03
5.88465095e-01 1.37510613e-01 -7.50180483e-02 -4.35153902e-01
3.46148200e-03 -1.80959433e-01 5.72646439e-01 5.06361008e-01
-1.22524217e-01 1.16430211e-03 -1.55677050e-01 6.55601859e-01
-3.79566371e-01 -1.70578927e-01 3.25712711e-01 7.11475551e-01
-5.54144204e-01 -6.77591026e-01 -5.74092984e-01 2.25494921e-01
-2.10048243e-01 7.98787698e-02 -3.94196063e-01 1.10158145e+00
5.94942272e-01 6.85290813e-01 1.18932158e-01 -2.56837964e-01
3.86744082e-01 -2.20485613e-01 5.32140851e-01 -6.50706232e-01
7.47143105e-02 3.68573129e-01 3.80611867e-02 -3.95973861e-01
-2.41742954e-01 -3.70175540e-01 -1.30101538e+00 -1.07728876e-01
-9.65063393e-01 -1.54180884e-01 7.32141554e-01 7.71105647e-01
3.51978332e-01 2.58191675e-01 5.85148871e-01 -8.40086639e-01
-2.69586593e-01 -6.53013170e-01 -5.93499839e-01 1.97015449e-01
3.48784737e-02 -1.18567061e+00 -4.99510825e-01 -2.56128043e-01] | [7.916460990905762, -2.481415033340454] |
188ebfe2-d007-4956-a862-715f5098a544 | dense-hybrid-proposal-modulation-for-lane | 2304.14874 | null | https://arxiv.org/abs/2304.14874v1 | https://arxiv.org/pdf/2304.14874v1.pdf | Dense Hybrid Proposal Modulation for Lane Detection | In this paper, we present a dense hybrid proposal modulation (DHPM) method for lane detection. Most existing methods perform sparse supervision on a subset of high-scoring proposals, while other proposals fail to obtain effective shape and location guidance, resulting in poor overall quality. To address this, we densely modulate all proposals to generate topologically and spatially high-quality lane predictions with discriminative representations. Specifically, we first ensure that lane proposals are physically meaningful by applying single-lane shape and location constraints. Benefitting from the proposed proposal-to-label matching algorithm, we assign each proposal a target ground truth lane to efficiently learn from spatial layout priors. To enhance the generalization and model the inter-proposal relations, we diversify the shape difference of proposals matching the same ground-truth lane. In addition to the shape and location constraints, we design a quality-aware classification loss to adaptively supervise each positive proposal so that the discriminative power can be further boosted. Our DHPM achieves very competitive performances on four popular benchmark datasets. Moreover, we consistently outperform the baseline model on most metrics without introducing new parameters and reducing inference speed. | ['Haibin Yan', 'Jiwen Lu', 'Linqing Zhao', 'Yuejian Wu'] | 2023-04-28 | null | null | null | null | ['lane-detection'] | ['computer-vision'] | [ 1.28193334e-01 1.32443190e-01 -5.66192925e-01 -6.61262870e-01
-9.48456526e-01 -4.61293280e-01 6.24081790e-01 1.97778672e-01
-1.90124691e-01 4.89747167e-01 2.93656349e-01 -1.72091588e-01
-3.60422060e-02 -8.01967502e-01 -7.18725383e-01 -6.55473888e-01
2.06440836e-01 4.55982506e-01 7.37839758e-01 -2.32937075e-02
5.77244878e-01 6.96172655e-01 -1.49167860e+00 4.78100404e-02
1.24832368e+00 9.03034687e-01 4.53113288e-01 8.19211453e-02
3.98962088e-02 2.84852684e-01 -1.42098650e-01 -1.71951637e-01
4.00258362e-01 -8.92476365e-02 -3.12483191e-01 3.16440344e-01
9.03452933e-01 -3.01787853e-01 -4.14435804e-01 8.78659785e-01
3.65584284e-01 2.75733203e-01 8.44107389e-01 -1.11757171e+00
-2.40605697e-01 9.51546878e-02 -8.76859903e-01 2.50813477e-02
3.51128504e-02 3.86865437e-01 1.37070179e+00 -1.14047456e+00
6.37333393e-01 1.27381408e+00 3.25338453e-01 -1.92168560e-02
-1.37262094e+00 -7.89176047e-01 7.87289441e-01 1.22691266e-01
-1.54707861e+00 -5.27451813e-01 1.26041496e+00 -2.07240343e-01
4.23596382e-01 1.31019473e-01 3.22023422e-01 8.01078975e-01
1.00518472e-01 8.69150877e-01 7.35002756e-01 -1.36355206e-01
1.60733819e-01 -1.40135558e-02 1.16533665e-02 1.03434622e+00
2.39536956e-01 -1.69710349e-03 -5.56972623e-01 -4.92526442e-02
9.01000261e-01 -6.00492768e-02 -1.78892732e-01 -9.59635556e-01
-1.30331409e+00 8.42566133e-01 8.07448268e-01 -7.66156614e-02
-1.65388867e-01 6.38738051e-02 2.38270447e-01 -3.41576576e-01
1.20314397e-01 4.04302686e-01 5.36955595e-02 3.10819924e-01
-9.23037410e-01 4.34827715e-01 -5.39504029e-02 1.03010726e+00
1.15303648e+00 -1.09376796e-01 -4.56825286e-01 8.28448653e-01
4.92132336e-01 5.45230925e-01 -1.36614650e-01 -1.20562279e+00
7.86990941e-01 6.15098774e-01 2.84197778e-01 -1.37095845e+00
-3.88514370e-01 -8.28132033e-01 -7.24584281e-01 2.85884589e-02
3.87215465e-01 3.90229493e-01 -1.11126959e+00 1.54360318e+00
2.89395899e-01 1.70362353e-01 -4.27289218e-01 1.27820444e+00
3.53644013e-01 7.69395947e-01 2.23984346e-01 1.28697962e-01
1.06715131e+00 -1.21729755e+00 -3.07111979e-01 -6.80872798e-01
7.04665184e-01 -7.91159868e-01 1.22572935e+00 2.08501294e-01
-8.64799201e-01 -5.80469966e-01 -1.14593506e+00 -1.36799380e-01
1.21483617e-01 5.90499222e-01 5.52883208e-01 2.93134034e-01
-6.27172768e-01 2.10770264e-01 -5.08870840e-01 1.58853799e-01
5.80609202e-01 2.64440745e-01 -2.15988055e-01 -5.10509789e-01
-8.81376684e-01 6.54667020e-01 3.04813057e-01 7.78642446e-02
-7.65944064e-01 -6.14837110e-01 -1.05497921e+00 -4.02651019e-02
5.14027059e-01 -5.37008345e-01 6.86773121e-01 -5.26275694e-01
-1.16509426e+00 7.20609546e-01 -3.21209311e-01 -2.78912544e-01
4.96157557e-01 9.75250974e-02 -1.54166371e-01 8.93151388e-02
4.11035717e-01 1.36920714e+00 7.60614157e-01 -1.64781046e+00
-8.32943261e-01 -1.39305085e-01 -1.29550576e-01 1.90250665e-01
3.60317938e-02 -5.59897721e-01 -7.38541186e-01 -7.04128623e-01
6.28450572e-01 -9.58269358e-01 -4.03997183e-01 3.34173381e-01
-5.06897032e-01 -1.80345207e-01 8.02807331e-01 -4.69353139e-01
1.08593738e+00 -2.34045672e+00 2.85369139e-02 4.96677309e-01
7.79573023e-02 -8.55618045e-02 -4.15210873e-01 -1.78337861e-02
4.96043473e-01 -1.69307321e-01 -3.02760422e-01 -4.53513950e-01
1.47440478e-01 4.40640062e-01 -6.24591231e-01 5.40209770e-01
5.16058981e-01 9.31685030e-01 -8.88441920e-01 -5.79629123e-01
4.05016869e-01 2.56165713e-01 -8.13182533e-01 1.56045780e-01
-2.44041443e-01 4.20239478e-01 -6.01658285e-01 6.61011040e-01
9.04990852e-01 -3.05443972e-01 1.45679608e-01 -4.39937383e-01
-3.66669632e-02 5.27854204e-01 -1.15179431e+00 1.71043217e+00
-5.32465041e-01 4.45837110e-01 -2.29054014e-03 -8.22899699e-01
1.21761978e+00 -3.85392517e-01 1.37737185e-01 -1.01828885e+00
-2.05073684e-01 2.75884718e-01 -8.54935274e-02 1.64299890e-01
6.82261348e-01 1.75209150e-01 -3.58060092e-01 9.77397859e-02
-5.34019887e-01 -1.04666650e-01 -1.70699641e-01 2.57321179e-01
8.27304780e-01 1.31137729e-01 1.42642617e-01 -1.44813880e-01
4.15044188e-01 -1.03003211e-01 1.03966391e+00 6.43164873e-01
-3.49137902e-01 7.73127854e-01 4.87836242e-01 -2.79257983e-01
-1.20139492e+00 -1.39211595e+00 -9.16619673e-02 1.10849953e+00
7.35125661e-01 -8.29389766e-02 -3.69091481e-01 -8.96147132e-01
1.88036546e-01 6.89162135e-01 -3.54797959e-01 -1.55831873e-01
-8.63639355e-01 -3.28909248e-01 1.20127872e-01 6.55474901e-01
4.84905243e-01 -7.40129530e-01 -4.62249696e-01 2.60283589e-01
-5.61785661e-02 -9.74507451e-01 -8.37896883e-01 1.72727089e-03
-7.22750306e-01 -7.77250290e-01 -5.21297038e-01 -7.42349327e-01
9.25409913e-01 6.54258370e-01 8.59474719e-01 7.59651139e-02
-2.36454662e-02 -1.84928492e-01 -1.92753375e-01 2.62479067e-01
4.26438218e-03 2.92340547e-01 -2.17228830e-01 4.57127206e-02
-1.28174260e-01 -3.71360302e-01 -7.71315813e-01 7.04894602e-01
-4.19050932e-01 3.26293617e-01 1.03824914e+00 8.49315703e-01
7.82403350e-01 -1.22382917e-01 5.67765117e-01 -5.04460812e-01
-4.87824418e-02 -3.48487198e-01 -8.53288651e-01 -5.06615117e-02
-5.35848916e-01 2.49126479e-01 4.50154185e-01 -1.70815021e-01
-9.37320530e-01 3.79345864e-01 1.31725939e-02 -5.42173982e-01
-1.58533424e-01 2.27420777e-01 -7.24709928e-01 -4.92040850e-02
2.20628694e-01 1.77437976e-01 -1.42153144e-01 -3.68275732e-01
4.92762536e-01 1.87562764e-01 5.21397948e-01 -6.26293659e-01
9.23760593e-01 6.81782961e-01 1.78701758e-01 -4.36280340e-01
-9.69270706e-01 -5.42950511e-01 -6.56197667e-01 -1.50105059e-01
5.10392964e-01 -8.74154687e-01 -4.02781785e-01 4.12334949e-02
-1.00400782e+00 -2.98033416e-01 1.21350072e-01 3.00002247e-01
-4.31216627e-01 5.15828669e-01 -2.54056513e-01 -7.33556926e-01
1.61405340e-01 -1.27026427e+00 1.52071941e+00 -2.14517694e-02
6.65783882e-02 -5.97082198e-01 -2.83378899e-01 3.92880738e-01
1.91494420e-01 -1.31595880e-01 9.88475323e-01 -1.29276395e-01
-1.29689705e+00 -1.67261243e-01 -7.26602614e-01 -4.64963168e-02
-1.03675894e-01 -2.04685852e-01 -7.80986309e-01 -2.41161108e-01
-7.00931787e-01 -1.08705692e-01 1.26105964e+00 2.94982463e-01
1.43370497e+00 -4.71068472e-02 -6.10362768e-01 5.16443729e-01
1.00469863e+00 -1.29672900e-01 5.61741531e-01 3.35283250e-01
9.07915652e-01 8.64144385e-01 1.12223876e+00 3.10020715e-01
4.75906193e-01 1.04540443e+00 6.07943654e-01 -1.37105539e-01
9.18187480e-03 -6.70138419e-01 2.89863914e-01 3.45261127e-01
4.43223268e-01 -3.51622045e-01 -7.06052125e-01 5.45932412e-01
-1.93607152e+00 -7.34032750e-01 -9.71716195e-02 2.40029216e+00
4.31689918e-01 6.20532393e-01 1.85107037e-01 -7.34473541e-02
6.04499996e-01 4.53981727e-01 -4.48698014e-01 1.91911846e-01
-1.71046987e-01 -4.11934197e-01 7.07342088e-01 6.69632971e-01
-1.23649740e+00 1.08525157e+00 5.06754208e+00 1.07116938e+00
-1.18807817e+00 -9.70141366e-02 8.25553298e-01 2.57063545e-02
-8.24266255e-01 1.47293225e-01 -1.19458711e+00 5.39802730e-01
3.55088830e-01 4.01657850e-01 5.72907440e-02 8.73803616e-01
5.43426633e-01 -2.59003490e-01 -7.77661502e-01 7.15850472e-01
-1.01139717e-01 -1.46378267e+00 2.23489106e-01 4.18834180e-01
7.60297954e-01 -1.36117786e-01 3.15132141e-01 2.74277300e-01
-1.15039438e-01 -8.15375984e-01 9.91657913e-01 5.14369905e-01
6.15161240e-01 -9.29906309e-01 5.25801957e-01 3.84997606e-01
-1.41553795e+00 -1.80728897e-01 -5.43142855e-01 2.46795759e-01
3.73119801e-01 7.13816345e-01 -7.90208936e-01 4.47933704e-01
4.90411781e-02 7.52500951e-01 -6.19411945e-01 1.23070371e+00
-3.63747597e-01 5.05777776e-01 -3.92596930e-01 2.78887510e-01
5.35249650e-01 -1.76485330e-01 5.11066496e-01 1.02890146e+00
2.01428726e-01 -2.11179912e-01 7.81872213e-01 1.04640877e+00
3.30971852e-02 8.74568298e-02 -4.79578346e-01 5.34798622e-01
9.39877331e-01 1.14858949e+00 -7.49923766e-01 -1.74723282e-01
-3.41640294e-01 8.33702564e-01 5.49199462e-01 2.81659931e-01
-9.07524824e-01 -1.42764628e-01 5.64318776e-01 5.44578969e-01
4.82150525e-01 -3.46963525e-01 -4.59641725e-01 -8.35726202e-01
2.57697374e-01 -3.43398094e-01 1.52718768e-01 -5.84990919e-01
-1.22547698e+00 1.42208129e-01 -3.92485559e-02 -1.44342780e+00
5.19056506e-02 -3.96827191e-01 -7.23649681e-01 7.69950986e-01
-1.73308241e+00 -1.48229492e+00 -2.99405932e-01 -1.25984162e-01
5.24987280e-01 2.03737810e-01 9.80360135e-02 3.70532751e-01
-5.70052683e-01 7.39048481e-01 -2.60246813e-01 -9.73837897e-02
9.82999802e-01 -9.79383469e-01 2.86399990e-01 7.15528309e-01
-6.99642897e-02 5.15200436e-01 4.57060754e-01 -7.85903633e-01
-1.07241535e+00 -1.63341486e+00 7.79508471e-01 -3.34400415e-01
2.91399866e-01 -4.88305748e-01 -1.19343746e+00 3.44616890e-01
-3.72732997e-01 2.22335458e-01 1.86669335e-01 -2.78103705e-02
-4.36904103e-01 -3.35817516e-01 -9.45252061e-01 7.00955808e-01
1.25846314e+00 -3.15903455e-01 -3.10633004e-01 1.30458981e-01
4.96963441e-01 -1.59559503e-01 -4.41316575e-01 5.85237563e-01
3.64457875e-01 -9.16771293e-01 1.10514796e+00 -9.47685093e-02
2.27886245e-01 -7.96629906e-01 -1.44474000e-01 -9.57685649e-01
-6.13318920e-01 -1.88439861e-01 7.51690939e-02 1.09739673e+00
4.07238334e-01 -3.82565081e-01 1.11320484e+00 2.31742591e-01
-6.68180704e-01 -9.83756185e-01 -1.00143111e+00 -7.24847972e-01
-8.18216950e-02 -4.39303786e-01 5.67522764e-01 6.66056216e-01
-2.91386843e-01 2.64407963e-01 -4.37383860e-01 5.73200703e-01
8.37737083e-01 3.46278101e-01 8.83883357e-01 -1.06368935e+00
-1.43144742e-01 -6.23974800e-01 -4.94262010e-01 -1.76239741e+00
4.17765051e-01 -8.98080289e-01 3.45285118e-01 -1.37118447e+00
1.92259178e-01 -9.82268691e-01 -2.41749719e-01 3.45885903e-01
-2.81475902e-01 3.71502250e-01 1.04635470e-01 3.44961464e-01
-9.86063182e-01 8.81376028e-01 1.33787167e+00 -1.83475927e-01
-1.68015540e-01 -1.56932801e-01 -4.88105446e-01 5.29615819e-01
6.35010958e-01 -1.45003200e-01 -4.73061293e-01 -3.40205401e-01
1.57030597e-02 -1.24463394e-01 5.98883569e-01 -9.48098779e-01
4.35415767e-02 -4.22129273e-01 4.37914968e-01 -1.12115753e+00
4.80609715e-01 -4.99860734e-01 -2.23252133e-01 2.72184163e-01
-3.43500227e-01 -3.59306008e-01 -4.39696386e-03 9.49428380e-01
6.23825043e-02 -1.29859857e-02 1.09918439e+00 4.16828334e-01
-9.03975010e-01 3.09241146e-01 -2.05766529e-01 -1.67033881e-01
1.06980300e+00 -3.11097264e-01 -2.80124307e-01 -2.06593707e-01
-2.17337847e-01 5.17565429e-01 9.49106276e-01 4.17791992e-01
7.40360379e-01 -1.41623747e+00 -3.76276672e-01 4.03767049e-01
5.02134323e-01 3.39113146e-01 2.34777406e-01 8.76944184e-01
-2.05467850e-01 6.87245190e-01 -1.18303470e-01 -7.37121105e-01
-8.45194995e-01 5.82289815e-01 2.01242179e-01 -6.72779828e-02
-7.20094442e-01 6.47320092e-01 7.23533452e-01 -4.34713215e-01
1.99109271e-01 -3.01899612e-01 -3.44811901e-02 -3.56981367e-01
2.03184247e-01 2.38108009e-01 -1.23038366e-01 -7.89656162e-01
-3.96503627e-01 7.89640605e-01 -2.74715155e-01 2.61617675e-02
8.66883397e-01 -2.23274902e-01 3.84013295e-01 1.15951553e-01
9.51681674e-01 3.27630103e-01 -1.82912350e+00 -1.31934673e-01
6.28745416e-03 -8.84305000e-01 3.39866847e-01 -5.19555986e-01
-9.66958106e-01 8.42392862e-01 4.12630677e-01 -4.50922340e-01
7.29289770e-01 7.63887838e-02 8.06819081e-01 2.30600983e-01
5.02263069e-01 -1.02611756e+00 2.75255769e-01 4.22066480e-01
7.19295084e-01 -1.32442558e+00 -1.60992909e-02 -9.47849631e-01
-6.72974586e-01 8.16302538e-01 8.27807546e-01 -2.22223371e-01
2.10738927e-01 -4.12523635e-02 -2.78749526e-01 -7.60805979e-02
-5.76738179e-01 -1.05039999e-01 7.06640840e-01 5.35712421e-01
2.53832221e-01 6.92808032e-02 -1.10590018e-01 3.06278318e-01
1.55404449e-01 -4.47037786e-01 1.56131715e-01 6.81699753e-01
-9.88507032e-01 -1.09193969e+00 -4.19945359e-01 6.40859663e-01
3.65540981e-01 2.18203232e-01 -1.40905961e-01 5.95913410e-01
1.26497865e-01 5.37700653e-01 3.84563625e-01 -2.95708865e-01
3.28148633e-01 -3.14183742e-01 2.10638061e-01 -6.44564092e-01
2.36141428e-01 3.40158701e-01 1.75713733e-01 -5.80609202e-01
1.48951352e-01 -6.84280992e-01 -1.44664109e+00 -2.97607481e-01
-2.94826865e-01 1.57421324e-02 2.70531446e-01 8.86243582e-01
6.39977634e-01 2.51974046e-01 8.18270147e-01 -1.10427427e+00
-4.53079760e-01 -6.03174508e-01 -4.77754116e-01 1.97397888e-01
7.22841918e-02 -1.25309741e+00 -2.68971086e-01 -4.47847307e-01] | [7.957812309265137, -1.6384923458099365] |
5bf25565-d15c-45d1-9c66-522ba3588e18 | computer-vision-application-for-improved | 2207.01323 | null | https://arxiv.org/abs/2207.01323v1 | https://arxiv.org/pdf/2207.01323v1.pdf | Computer vision application for improved product traceability in the granite manufacturing industry | The traceability of granite blocks consists in identifying each block with a finite number of color bands which represent a numerical code. This code has to be read several times throughout the manufacturing process, but its accuracy is subject to human errors, leading to cause faults in the traceability system. A computer vision system is presented to address this problem through color detection and the decryption of the associated code. The system developed makes use of color space transformations, and several thresholds for the isolation of the colors. Computer vision methods are implemented, along with contour detection procedures for color identification. Lastly, the analysis of geometrical features is used to decrypt the color code captured. The proposed algorithm is trained on a set of 109 pictures taken in different environmental conditions and validated on a set of 21 images. The outcome shows promising results with an accuracy rate of 75.00% in the validation process. Therefore, the application presented can help employees reduce the number of mistakes on product tracking. | ['Antonio Recaman', 'Maria Araujo', 'Javier Martinez', 'Xurxo Rigueira'] | 2022-07-04 | null | null | null | null | ['contour-detection'] | ['computer-vision'] | [ 3.61055493e-01 -2.66256094e-01 3.79075587e-01 -4.88947555e-02
-6.34394065e-02 -6.46603644e-01 3.86330992e-01 4.15132701e-01
-2.86158204e-01 3.49302769e-01 -8.46136510e-01 -4.74322647e-01
-3.49431396e-01 -1.07832420e+00 -2.25634381e-01 -7.08587825e-01
3.78958315e-01 4.25508440e-01 1.50103301e-01 -3.05282623e-01
7.23591089e-01 1.06245935e+00 -1.65256453e+00 1.98586941e-01
7.93066025e-01 1.03963757e+00 3.94195169e-01 6.94346070e-01
-8.90576690e-02 6.15545571e-01 -7.02493072e-01 -4.73722458e-01
1.85070276e-01 -4.03568089e-01 -5.08075416e-01 4.21493679e-01
-4.03644294e-02 -1.81639656e-01 3.06696653e-01 1.34948981e+00
-1.52142048e-01 -4.62819338e-02 8.52350235e-01 -1.10320663e+00
-7.45294273e-01 6.98689977e-03 -3.82344246e-01 -4.06805754e-01
3.21005076e-01 -2.08507597e-01 6.03404164e-01 -1.05784976e+00
4.77669775e-01 8.54880869e-01 3.83430928e-01 1.84580069e-02
-1.12627208e+00 -5.25274694e-01 -6.54071689e-01 3.65310669e-01
-1.49730027e+00 1.42419770e-01 7.54936278e-01 -7.59547114e-01
4.21000421e-01 4.59863305e-01 1.00342274e+00 1.63356766e-01
5.65237403e-01 -2.68199407e-02 1.60110271e+00 -1.02309370e+00
2.42854446e-01 5.26847422e-01 4.81757522e-01 1.07437384e+00
7.11185277e-01 4.13618274e-02 2.87352324e-01 1.18299201e-01
6.77916050e-01 1.31788015e-01 5.55993430e-03 -3.81629318e-01
-5.95568597e-01 7.65298307e-01 3.52558076e-01 6.01401269e-01
-2.98240423e-01 -2.21687153e-01 2.92576104e-02 1.01623632e-01
7.11232424e-02 3.97826135e-01 -1.27607433e-03 -9.11241248e-02
-7.94941187e-01 -2.26410538e-01 8.59794199e-01 7.95529068e-01
8.52730691e-01 -9.10223499e-02 3.28907520e-01 7.04161823e-01
3.57060224e-01 8.73829663e-01 -2.31413376e-02 -5.18235028e-01
3.52399610e-02 9.12656188e-01 2.19658062e-01 -1.51570940e+00
-2.89625943e-01 -2.45403238e-02 -6.18568301e-01 1.06685138e+00
5.81999600e-01 1.27443150e-01 -9.94199753e-01 6.14078403e-01
1.74453229e-01 -6.15655959e-01 -1.78345233e-01 5.69539428e-01
2.84981966e-01 7.47494221e-01 -1.86114341e-01 1.27302289e-01
1.55762541e+00 -5.93909442e-01 -9.81233597e-01 4.90045659e-02
4.40419316e-01 -1.25924551e+00 8.14815223e-01 1.08431232e+00
-8.66135597e-01 -8.05168986e-01 -1.22530901e+00 2.93312639e-01
-6.52765632e-01 1.04246020e+00 2.49865279e-01 1.08611178e+00
-6.71366811e-01 3.89945000e-01 -5.38488925e-01 -4.19481993e-01
-1.69288158e-01 4.29890364e-01 -3.47549051e-01 -8.15978274e-02
-7.15286672e-01 1.08547115e+00 4.95296687e-01 8.97921383e-01
-8.04886371e-02 -3.12159583e-03 -5.82320571e-01 -2.80775856e-02
-3.54167819e-02 -2.28313785e-02 6.21364295e-01 -1.11995518e+00
-1.23393059e+00 1.01882172e+00 4.49987829e-01 4.57509048e-02
7.73271263e-01 -3.31257135e-01 -8.01902354e-01 3.74045819e-01
5.31312898e-02 7.76699111e-02 8.42950046e-01 -1.54484153e+00
-9.44838941e-01 -1.36985376e-01 -2.86995769e-01 -4.59563017e-01
-2.74608195e-01 -1.09890290e-02 -5.85731566e-01 -3.94463807e-01
3.10282797e-01 -1.22117484e+00 2.15437576e-01 -8.56279731e-02
-4.06379223e-01 2.31713921e-01 6.89128637e-01 -1.19706857e+00
1.10549140e+00 -2.29113460e+00 -3.85627300e-01 1.16355419e+00
-3.29682946e-01 2.39973217e-01 3.59554440e-01 4.54209089e-01
-2.13922575e-01 -2.47099489e-01 -2.82003611e-01 5.31643152e-01
-2.52180696e-01 -1.23866878e-01 4.77544405e-02 4.53919709e-01
8.30238685e-02 8.53314474e-02 -4.50627178e-01 -4.25143689e-01
4.38671023e-01 2.58790880e-01 -2.77368389e-02 -8.37353691e-02
3.55586678e-01 -1.62919208e-01 -5.70182800e-01 8.23183358e-01
1.03991938e+00 8.33556429e-02 2.91430056e-01 -2.73619384e-01
-1.65891677e-01 -6.04806900e-01 -1.40121114e+00 9.14544940e-01
-4.95010257e-01 4.16462958e-01 1.25750065e-01 -6.59903347e-01
1.56154025e+00 1.57963887e-01 4.23104435e-01 -6.54640853e-01
3.71211946e-01 4.80580002e-01 -3.44663002e-02 -8.19654226e-01
6.38445318e-01 1.65440455e-01 1.30547788e-02 1.94080472e-01
-6.46744788e-01 -4.39745486e-01 4.52779353e-01 -6.36707172e-02
6.41468942e-01 1.32544428e-01 9.34027806e-02 -2.90541202e-01
9.23409760e-01 4.19509411e-01 -1.03557818e-02 1.60473555e-01
9.97058675e-02 2.10889906e-01 2.93926150e-01 -2.96245486e-01
-1.07595158e+00 -9.08835113e-01 -9.30972025e-02 4.30855632e-01
3.58009934e-01 2.66903669e-01 -9.52846646e-01 -1.84566393e-01
1.18099749e-01 6.92753792e-01 -4.74828929e-01 -2.76025385e-01
-4.20973897e-01 -3.19823951e-01 3.18093821e-02 4.77518924e-02
6.46402717e-01 -1.20582736e+00 -8.48822892e-01 2.79617339e-01
1.22701816e-01 -7.78300881e-01 2.69585341e-01 9.63573977e-02
-8.05844486e-01 -1.62467432e+00 -5.10046899e-01 -1.18173230e+00
1.12649167e+00 4.17227089e-01 6.70343757e-01 6.87994599e-01
-6.36024296e-01 3.84871095e-01 -5.82133532e-01 -4.62829828e-01
-9.40791488e-01 -2.32901841e-01 -5.20597696e-01 2.06863806e-01
5.01002312e-01 1.98986828e-01 -3.46933872e-01 2.30807960e-01
-8.10573459e-01 -1.28695160e-01 7.12628007e-01 6.22353017e-01
2.99154401e-01 4.42802310e-01 1.05862051e-01 -9.72901762e-01
7.72877574e-01 1.49906173e-01 -1.01286435e+00 5.62452376e-01
-8.79642725e-01 -2.18175843e-01 4.91946489e-01 1.10150151e-01
-1.11588621e+00 6.98750466e-02 7.09333941e-02 3.82701963e-01
-2.44105801e-01 3.03006351e-01 -1.31472364e-01 -3.47665548e-01
4.63868916e-01 1.00002527e-01 4.20413882e-01 -3.31780076e-01
1.49697825e-01 7.87012577e-01 6.10024631e-01 -1.92804053e-01
1.11607099e+00 3.07039976e-01 2.44570091e-01 -8.92306924e-01
-1.46654561e-01 -4.10750777e-01 -7.58452117e-01 -8.21202099e-01
1.08980834e+00 -4.15456265e-01 -7.78524220e-01 6.87486172e-01
-1.02607977e+00 1.94471091e-01 2.63936162e-01 7.20550358e-01
-2.59533674e-01 3.92076254e-01 -6.54373705e-01 -8.86438251e-01
-2.30973393e-01 -9.23064053e-01 3.52657408e-01 1.79805025e-01
-2.12120041e-01 -6.36574447e-01 -2.55987167e-01 4.01407659e-01
-1.05515338e-01 3.15686077e-01 1.17923403e+00 -2.30827585e-01
-5.38294792e-01 -7.89184332e-01 -2.31383801e-01 4.91662771e-01
4.26449090e-01 7.73896873e-01 -7.37567961e-01 -2.36451030e-01
1.54699963e-02 1.38144046e-01 5.72100699e-01 1.22044660e-01
8.87066126e-01 3.22706968e-01 -2.58509725e-01 3.32813412e-02
1.66806936e+00 1.00062811e+00 8.92259836e-01 8.84896219e-01
6.57893062e-01 8.68567348e-01 1.26742613e+00 2.52059311e-01
-4.45985198e-01 3.65821868e-01 6.80452049e-01 -3.76084238e-01
2.40295917e-01 4.31842059e-01 9.51341614e-02 5.22535324e-01
-5.22181273e-01 2.49244515e-02 -7.59570003e-01 2.74116307e-01
-1.29063737e+00 -9.28552866e-01 -8.64334166e-01 2.03530025e+00
2.37148508e-01 3.11630934e-01 -1.00667901e-01 8.58012617e-01
1.09832084e+00 -5.92512369e-01 1.90312803e-01 -8.42542410e-01
2.44844541e-01 3.42781425e-01 7.09220052e-01 4.11563456e-01
-9.88031983e-01 4.25674677e-01 5.65164471e+00 5.63283563e-01
-1.16907692e+00 -3.69799912e-01 3.56256157e-01 6.94923222e-01
-3.84126715e-02 -1.31960288e-01 -3.04827124e-01 4.17385995e-01
4.72437292e-01 2.66622066e-01 3.02812546e-01 9.20509696e-01
1.39370650e-01 -6.25394046e-01 -5.26335657e-01 8.88786852e-01
6.16594516e-02 -1.03710556e+00 -1.47538275e-01 1.35896742e-01
6.99603379e-01 -9.41928387e-01 1.41192958e-01 -4.07200903e-01
6.39625490e-02 -5.77128768e-01 1.19724274e+00 7.14212358e-01
5.15064061e-01 -1.18164122e+00 8.19535553e-01 -1.71329990e-01
-1.05446291e+00 -2.86735922e-01 -3.64298463e-01 8.62818882e-02
-1.26334295e-01 5.86182773e-01 -9.61237431e-01 6.16938591e-01
4.63123530e-01 8.88571665e-02 -9.00134325e-01 1.23622477e+00
-3.95406216e-01 2.22909003e-01 -1.02212578e-01 -2.90822744e-01
1.61367521e-01 -9.98357892e-01 -9.30649489e-02 1.13949013e+00
8.96008193e-01 -2.59456217e-01 -2.41883278e-01 9.11707878e-01
4.22444195e-01 3.50020796e-01 -4.98779446e-01 -1.88740052e-03
4.97648090e-01 1.37388861e+00 -1.44136834e+00 -1.95663810e-01
-4.61324185e-01 1.06697178e+00 -3.89288068e-01 3.10430855e-01
-7.55621850e-01 -8.63917708e-01 4.06592190e-02 1.35963276e-01
3.97184372e-01 -2.96505868e-01 -4.96630728e-01 3.48223373e-02
7.91478232e-02 -5.71710348e-01 1.59762412e-01 -9.89417017e-01
-7.05729127e-01 3.99964303e-01 -2.06381172e-01 -1.55087423e+00
5.81210619e-03 -1.19998109e+00 -3.99614573e-01 7.60851741e-01
-1.02501047e+00 -1.18599343e+00 -4.87429291e-01 4.54468042e-01
3.13908532e-02 -3.92713249e-01 8.05270731e-01 3.81154835e-01
-4.24500197e-01 2.05352828e-01 5.67865968e-01 2.26854637e-01
5.33409894e-01 -1.13861096e+00 -1.40676722e-01 1.06597114e+00
-1.63905591e-01 4.33134735e-01 6.27033234e-01 -7.88822293e-01
-9.85984743e-01 -6.96638525e-01 8.79917979e-01 1.25692517e-01
4.92153734e-01 -1.96441218e-01 -7.30839074e-01 2.31789500e-01
-2.90070195e-02 -3.77962589e-01 5.06079853e-01 -4.86784548e-01
1.45811707e-01 -2.79050261e-01 -1.17478573e+00 2.11311936e-01
1.30210578e-01 -5.35300016e-01 -4.02263969e-01 6.38575852e-02
-1.30029574e-01 -6.04430400e-02 -8.92875075e-01 -1.72936693e-01
7.79622436e-01 -1.16609836e+00 8.97940457e-01 2.15412036e-01
3.65180343e-01 -5.92812181e-01 3.03599298e-01 -7.78137028e-01
-5.47921538e-01 -2.20070574e-02 9.18275774e-01 1.35988545e+00
4.60488111e-01 -6.19600773e-01 7.24536657e-01 7.00475693e-01
-1.13325030e-01 6.36200383e-02 -4.73866373e-01 -6.43619180e-01
-5.03856122e-01 1.79123674e-02 3.30033004e-01 7.32328832e-01
-2.96072662e-01 -2.76540965e-01 -1.03237398e-01 3.20779145e-01
5.44399023e-01 2.82415658e-01 6.51821077e-01 -1.67505133e+00
1.14434406e-01 -3.45826566e-01 -6.02840543e-01 4.65641730e-02
-2.49844566e-01 -6.85224593e-01 4.09500636e-02 -1.49463856e+00
-1.48171008e-01 -3.45650584e-01 -8.02619159e-02 3.14798057e-01
1.17168285e-01 4.38244611e-01 3.79767507e-01 1.84790224e-01
2.94304848e-01 -3.45028676e-02 1.17424703e+00 -3.24783295e-01
-4.34762724e-02 1.25857800e-01 -1.67089030e-01 6.46996319e-01
7.75891960e-01 -3.59471112e-01 -2.45883659e-01 6.23685941e-02
3.98412645e-01 -2.46659726e-01 5.35981953e-01 -1.32193708e+00
-3.45924571e-02 -1.73740566e-01 6.75938427e-01 -8.24011683e-01
1.60683870e-01 -1.73196507e+00 6.76747084e-01 1.25900185e+00
2.92415112e-01 3.19082946e-01 5.13734706e-02 3.97548407e-01
-1.13031626e-01 -8.06320488e-01 8.55341613e-01 4.55877110e-02
-1.14174771e+00 -5.59952438e-01 -6.54903531e-01 -8.96110415e-01
1.49643576e+00 -1.01030028e+00 -7.31735229e-02 3.79474275e-02
-8.11045527e-01 -3.89377266e-01 6.32984579e-01 -4.82393876e-02
6.55445576e-01 -1.50152385e+00 -1.98688909e-01 5.95036805e-01
3.32398951e-01 -6.30628943e-01 2.96873003e-01 5.37957430e-01
-1.74761319e+00 1.76527604e-01 -9.43243802e-01 -2.63509393e-01
-1.63904440e+00 6.40451133e-01 3.59583236e-02 4.86806966e-02
-3.77763540e-01 3.78293216e-01 -4.41889316e-01 1.46938041e-01
-2.23480105e-01 -5.36207199e-01 -6.19535565e-01 1.98503152e-01
3.19885284e-01 8.38733494e-01 4.12538290e-01 -6.30518138e-01
-2.07966581e-01 1.10540736e+00 1.45900130e-01 -1.39941394e-01
1.06422865e+00 -3.79827283e-02 -4.69272822e-01 2.77709991e-01
8.76507401e-01 4.22012120e-01 -8.51247191e-01 3.19222927e-01
1.95155486e-01 -5.86952090e-01 -2.40983635e-01 -8.39848876e-01
-1.02345455e+00 6.20247185e-01 9.60637391e-01 6.84290051e-01
1.21578395e+00 -6.89409018e-01 3.95537853e-01 3.57597828e-01
3.89808863e-01 -1.62560272e+00 -5.32693118e-02 9.43568945e-02
6.75016165e-01 -9.18818831e-01 1.24429278e-01 -7.99283504e-01
-5.33539951e-01 1.86953306e+00 1.88512415e-01 -1.57519400e-01
5.53841650e-01 8.21439400e-02 2.24490628e-01 -4.32914376e-01
3.32795501e-01 -8.16686228e-02 7.82179534e-02 6.48506761e-01
3.17100406e-01 2.70135194e-01 -7.95098841e-01 1.03745475e-01
-2.13102326e-01 6.07433319e-02 7.55373240e-01 1.29541802e+00
-8.22102070e-01 -1.09895468e+00 -1.28306234e+00 1.13354295e-01
-3.48270386e-01 3.39376777e-01 -5.17310500e-01 1.34187520e+00
2.42563948e-01 1.22238290e+00 1.77448645e-01 -3.46754730e-01
4.67991531e-01 3.12565491e-02 4.79654670e-01 -1.61426514e-01
-5.86891532e-01 9.51192379e-02 3.98633555e-02 -1.05878145e-01
-3.95975053e-01 -5.81774235e-01 -1.55902243e+00 -3.33740622e-01
-2.78048664e-01 2.93353558e-01 1.03531218e+00 6.70754552e-01
-4.39788848e-01 5.28741241e-01 8.27997088e-01 -2.26606339e-01
-2.80226946e-01 -5.97644031e-01 -1.25635552e+00 7.32631207e-01
-5.22882827e-02 -6.88188255e-01 -1.23403579e-01 4.27792490e-01] | [9.433064460754395, -1.597640037536621] |
20bb5cdb-bdb2-4bfa-a360-d14c420e44d3 | glt-t-global-local-transformer-voting-for-3d | 2211.10927 | null | https://arxiv.org/abs/2211.10927v1 | https://arxiv.org/pdf/2211.10927v1.pdf | GLT-T: Global-Local Transformer Voting for 3D Single Object Tracking in Point Clouds | Current 3D single object tracking methods are typically based on VoteNet, a 3D region proposal network. Despite the success, using a single seed point feature as the cue for offset learning in VoteNet prevents high-quality 3D proposals from being generated. Moreover, seed points with different importance are treated equally in the voting process, aggravating this defect. To address these issues, we propose a novel global-local transformer voting scheme to provide more informative cues and guide the model pay more attention on potential seed points, promoting the generation of high-quality 3D proposals. Technically, a global-local transformer (GLT) module is employed to integrate object- and patch-aware prior into seed point features to effectively form strong feature representation for geometric positions of the seed points, thus providing more robust and accurate cues for offset learning. Subsequently, a simple yet effective training strategy is designed to train the GLT module. We develop an importance prediction branch to learn the potential importance of the seed points and treat the output weights vector as a training constraint term. By incorporating the above components together, we exhibit a superior tracking method GLT-T. Extensive experiments on challenging KITTI and NuScenes benchmarks demonstrate that GLT-T achieves state-of-the-art performance in the 3D single object tracking task. Besides, further ablation studies show the advantages of the proposed global-local transformer voting scheme over the original VoteNet. Code and models will be available at https://github.com/haooozi/GLT-T. | ['Jing Zhang', 'Mingyu Gao', 'Yuxiang Yang', 'Zhiwei He', 'Jiahao Nie'] | 2022-11-20 | null | null | null | null | ['3d-single-object-tracking'] | ['computer-vision'] | [-3.19197059e-01 -2.38693818e-01 -5.62344193e-01 -3.64372700e-01
-7.09885597e-01 -3.94063860e-01 6.57356024e-01 -1.07522354e-01
-2.88644493e-01 3.49528223e-01 -1.05909025e-02 -1.56526402e-01
1.22618735e-01 -7.27453709e-01 -6.03476584e-01 -8.31609607e-01
4.07961786e-01 4.90036070e-01 7.24759340e-01 -6.34534657e-02
2.14392722e-01 6.19980276e-01 -1.34818017e+00 -2.42337614e-01
8.73607934e-01 1.20972276e+00 3.80275756e-01 6.73569366e-02
-1.31043985e-01 3.13701242e-01 -4.27644074e-01 -1.60335988e-01
6.55473113e-01 -8.02816227e-02 -9.67129022e-02 -6.80256709e-02
9.37826216e-01 -4.21035528e-01 -3.20474595e-01 1.06977153e+00
6.86818123e-01 -3.30110714e-02 7.20226943e-01 -1.15272987e+00
-4.81533855e-01 3.65615100e-01 -8.94558966e-01 6.09343760e-02
3.92897278e-02 4.13586527e-01 1.07304299e+00 -1.33570039e+00
5.83655298e-01 1.05578899e+00 8.30170333e-01 5.20231485e-01
-1.01574540e+00 -1.04569733e+00 4.49360013e-01 -9.45199430e-02
-1.36927164e+00 -2.56378382e-01 1.06019938e+00 -2.95931995e-01
5.90157092e-01 1.51702166e-01 8.74327838e-01 7.11679637e-01
2.30659798e-01 9.71628547e-01 8.58729839e-01 -1.71366185e-01
-1.51359424e-01 3.65922712e-02 1.54922828e-01 9.28631127e-01
4.77065355e-01 5.33671141e-01 -4.67101663e-01 -2.65056521e-01
1.09530663e+00 3.22538823e-01 -2.51252383e-01 -8.67055058e-01
-1.05240381e+00 7.52987444e-01 1.14422357e+00 2.33497739e-01
-3.75842214e-01 3.60779881e-01 2.31956393e-02 -1.17026351e-01
5.08614004e-01 1.56319156e-01 -2.69515365e-01 4.02356863e-01
-9.62170005e-01 4.62070614e-01 1.79752350e-01 1.08435726e+00
7.41298974e-01 7.08287284e-02 -7.80863225e-01 5.83995104e-01
7.29925096e-01 7.99237132e-01 -1.20436892e-01 -9.01000381e-01
3.71206045e-01 9.67408121e-01 1.27707794e-01 -9.06067312e-01
-2.58056790e-01 -8.90786290e-01 -5.55842400e-01 5.04072130e-01
4.29100871e-01 1.53244048e-01 -1.29640913e+00 1.64936876e+00
7.81469345e-01 3.24974149e-01 -5.15560091e-01 1.30977535e+00
1.03021455e+00 4.71398115e-01 7.16488957e-02 1.09063797e-01
1.32433522e+00 -9.52360213e-01 -1.84226632e-01 -1.57508239e-01
3.63152653e-01 -8.59424591e-01 6.26650155e-01 -7.84189180e-02
-1.07534206e+00 -6.74008608e-01 -8.37290823e-01 2.64073871e-02
4.18914631e-02 3.73087794e-01 7.27672279e-01 3.77226800e-01
-7.19492018e-01 3.14295560e-01 -7.23786354e-01 1.18023017e-02
8.74125361e-01 4.21712041e-01 -2.88339462e-02 -1.15788780e-01
-9.03183818e-01 9.29358602e-01 1.91294387e-01 2.43213952e-01
-1.01649034e+00 -9.45971072e-01 -8.04933012e-01 -1.34648398e-01
3.89949054e-01 -9.38749194e-01 1.17229879e+00 -3.81494105e-01
-1.25613344e+00 8.88453484e-01 -2.37754017e-01 -1.60455227e-01
5.54106772e-01 -9.96172503e-02 4.11049314e-02 -1.17511556e-01
2.97502607e-01 9.99192297e-01 1.02156210e+00 -1.42207170e+00
-8.64501297e-01 -3.43093783e-01 -5.05585074e-02 1.54608190e-01
-1.46761332e-02 -2.51601070e-01 -8.71359229e-01 -8.29700172e-01
3.15599144e-01 -9.43236709e-01 -3.44144583e-01 5.70023298e-01
-2.75628507e-01 -5.85231066e-01 9.30189729e-01 -1.10696994e-01
1.02104628e+00 -1.93816078e+00 2.10910826e-03 2.79154986e-01
4.90877122e-01 4.32034016e-01 -1.34740680e-01 -1.93221688e-01
3.22357893e-01 -2.70577580e-01 -8.33406020e-03 -2.71555871e-01
3.82980220e-02 3.17172334e-02 -1.71248332e-01 4.69399065e-01
4.24884707e-01 1.29517317e+00 -9.42117751e-01 -4.98118311e-01
5.39921582e-01 6.31123722e-01 -6.65766656e-01 -2.14309786e-02
-3.62461776e-01 4.73211855e-01 -1.02861273e+00 1.00921071e+00
9.23705935e-01 -3.50214750e-01 -2.55527884e-01 -4.87709403e-01
-3.30736518e-01 1.32873878e-01 -9.39301789e-01 1.64840770e+00
-1.16889201e-01 2.92548478e-01 -1.85894892e-02 -4.44551885e-01
1.14837301e+00 -3.23002785e-02 5.32057583e-01 -7.11881518e-01
4.31465596e-01 3.18381041e-01 -1.03904434e-01 9.97181982e-02
5.10206401e-01 -6.18942454e-02 -1.37132272e-01 1.50374487e-01
-7.85063654e-02 -1.55403703e-01 -2.57773608e-01 1.02269284e-01
7.57793248e-01 3.92041296e-01 1.00186475e-01 -2.66530901e-01
5.09233832e-01 1.95633799e-01 9.61227655e-01 7.54057169e-01
-4.62100863e-01 6.61862433e-01 -4.82989401e-02 -4.83491212e-01
-9.69844282e-01 -9.14376795e-01 -3.65609348e-01 7.11149395e-01
7.34295964e-01 -2.75383353e-01 -2.74960190e-01 -8.17526221e-01
4.25223589e-01 4.41277385e-01 -6.12928748e-01 -1.12813480e-01
-8.32417607e-01 -3.63484204e-01 2.18890339e-01 7.43469059e-01
4.84489173e-01 -7.97075868e-01 -5.65157413e-01 2.80112803e-01
1.15414813e-01 -8.39078009e-01 -8.39579046e-01 1.43173352e-01
-1.03520679e+00 -9.76512730e-01 -9.12462771e-01 -6.79791749e-01
9.07521248e-01 7.94406533e-01 9.77130055e-01 4.10729796e-01
-2.04550117e-01 8.72434825e-02 -1.40814021e-01 -3.53627205e-01
9.53630880e-02 4.02503163e-02 -1.35953158e-01 -3.15468162e-01
3.41207802e-01 -2.59374648e-01 -9.15766060e-01 7.01255500e-01
-4.31293309e-01 1.03824750e-01 6.98932946e-01 8.73934090e-01
7.89746404e-01 -3.20534170e-01 2.07274228e-01 -5.18694222e-01
3.55601422e-02 -1.96509540e-01 -9.52946544e-01 8.73834789e-02
-4.64755356e-01 9.23457891e-02 2.67159224e-01 -5.62486947e-01
-9.27161157e-01 2.48377502e-01 -1.43725842e-01 -8.37630332e-01
2.07626104e-01 1.40997708e-01 -1.10357136e-01 -5.45050025e-01
4.01187778e-01 1.16182603e-01 -1.22581542e-01 -4.67826098e-01
2.78050065e-01 1.42452657e-01 2.32755944e-01 -6.01638854e-01
1.33349431e+00 5.58023334e-01 3.40635628e-02 -2.93505669e-01
-1.03413534e+00 -5.15259802e-01 -4.95877981e-01 -3.68300170e-01
6.96801066e-01 -1.17057264e+00 -5.94011307e-01 5.03510773e-01
-9.87353921e-01 -2.09334597e-01 -2.28114173e-01 4.94812697e-01
-1.38322636e-01 8.02692845e-02 -2.88506567e-01 -6.24674201e-01
-5.10588408e-01 -1.20060003e+00 1.43797100e+00 6.70133173e-01
8.21130127e-02 -8.02656651e-01 -5.58937937e-02 2.92749166e-01
4.28430855e-01 1.12688534e-01 5.51367819e-01 -2.82216161e-01
-1.24702287e+00 -3.45835418e-01 -4.79030222e-01 -1.21960580e-01
-1.25420960e-02 9.13982280e-03 -8.33174467e-01 -4.46520269e-01
-2.00579152e-01 -1.30556583e-01 1.12263238e+00 7.08451450e-01
9.01746213e-01 2.76518881e-01 -7.15132773e-01 7.47993827e-01
1.43991005e+00 -8.99698511e-02 2.05398992e-01 1.44097060e-01
8.71851563e-01 -4.01802622e-02 1.00929654e+00 3.21280777e-01
4.69265223e-01 1.02259481e+00 5.53967774e-01 -2.27393880e-01
-4.24862325e-01 -5.59890389e-01 1.80239752e-01 5.51041901e-01
-2.14641795e-01 2.34466698e-02 -6.36907578e-01 3.95962298e-01
-1.85869217e+00 -8.04177046e-01 -2.50013620e-01 2.15373611e+00
6.53314471e-01 4.63865250e-01 9.15142447e-02 -2.90682107e-01
7.85331726e-01 3.09835285e-01 -6.55798614e-01 4.64516401e-01
5.27686393e-03 1.20835684e-01 6.34751976e-01 4.28634495e-01
-1.16899657e+00 1.08572388e+00 5.01446342e+00 1.09532368e+00
-1.30909896e+00 9.23097730e-02 2.19846457e-01 -1.19701810e-01
-4.99007553e-01 1.65236071e-01 -1.50957704e+00 3.90805632e-01
-5.06282188e-02 1.34618238e-01 -1.46899924e-01 8.83588493e-01
2.07981214e-01 3.79705988e-02 -5.97755194e-01 8.27569842e-01
-1.58079624e-01 -1.35078728e+00 3.26599088e-03 1.27211332e-01
7.75218487e-01 2.36599460e-01 9.33879912e-02 3.48492146e-01
2.71011293e-01 -5.27941287e-01 1.02540028e+00 3.96421313e-01
5.72957456e-01 -4.82662976e-01 5.11067450e-01 2.94919223e-01
-1.69144309e+00 -2.30541751e-02 -6.83294952e-01 2.97085196e-01
2.27979779e-01 6.40116096e-01 -6.73868477e-01 6.68533087e-01
6.35375082e-01 9.43261504e-01 -5.43099046e-01 1.51243722e+00
-5.46909451e-01 4.29684103e-01 -4.95017052e-01 -2.70076375e-03
3.62579554e-01 1.27544031e-01 8.81790042e-01 7.75026858e-01
4.15100485e-01 1.03559487e-01 4.30092186e-01 1.10185182e+00
-7.15354905e-02 -2.50946909e-01 -3.75600964e-01 5.28117359e-01
7.21164644e-01 1.44504321e+00 -8.07726920e-01 -2.33645722e-01
-3.22363198e-01 4.01388496e-01 3.73561412e-01 1.08557224e-01
-1.12301207e+00 1.22041367e-01 6.26444519e-01 3.20713371e-01
8.05967331e-01 -2.18644783e-01 -2.67795354e-01 -1.08499122e+00
1.01872431e-02 -5.89911640e-01 2.78052837e-01 -6.88267291e-01
-1.35476232e+00 4.93270040e-01 -3.82401608e-02 -1.68625569e+00
2.54146457e-01 -6.50407195e-01 -8.00010443e-01 8.93837273e-01
-1.84682310e+00 -1.44289720e+00 -5.88432550e-01 4.94725943e-01
4.88770515e-01 -3.90688479e-02 2.61203647e-01 3.26325357e-01
-4.42520380e-01 5.85763633e-01 -3.59975308e-01 1.19115204e-01
7.36583173e-01 -9.69175279e-01 3.29083413e-01 6.60034060e-01
3.65067832e-02 6.65538669e-01 3.71214986e-01 -8.59766603e-01
-1.41598785e+00 -1.21812201e+00 6.52737260e-01 -7.09147096e-01
3.58490735e-01 -1.74762964e-01 -8.07099700e-01 3.95233095e-01
-1.23922028e-01 3.36370111e-01 2.16666624e-01 -4.64412533e-02
-2.98737586e-01 -1.96339071e-01 -9.02839422e-01 4.25989360e-01
1.23253644e+00 -1.34456128e-01 -6.36973381e-01 -5.41304685e-02
5.59430778e-01 -6.62591040e-01 -7.26144075e-01 7.58309722e-01
5.97768843e-01 -7.40832686e-01 1.19806802e+00 -4.23563756e-02
7.39301443e-02 -9.13945854e-01 1.74059421e-01 -9.99840140e-01
-5.88637888e-01 -4.43327844e-01 -3.18460852e-01 1.08176613e+00
2.35971168e-01 -4.83908325e-01 1.01154184e+00 4.41894144e-01
-4.68147635e-01 -9.10264194e-01 -1.11986649e+00 -6.52660489e-01
1.98661573e-02 -3.19008738e-01 5.75713336e-01 7.03875899e-01
-6.41352057e-01 3.13872188e-01 -4.25873280e-01 2.14681819e-01
1.06542814e+00 5.04463971e-01 9.81315315e-01 -1.47342527e+00
1.94389075e-02 -7.31273711e-01 -3.47017139e-01 -1.71930492e+00
-1.45535827e-01 -1.07076430e+00 2.15036452e-01 -1.38981676e+00
3.07343513e-01 -1.16640484e+00 -3.43639851e-01 6.48391485e-01
-5.64383090e-01 4.32886094e-01 4.34486806e-01 5.25781035e-01
-6.07409656e-01 8.40699017e-01 1.83054960e+00 -2.07991540e-01
-1.36867076e-01 3.68904591e-01 -6.57375634e-01 6.17524087e-01
4.35754091e-01 -7.03161538e-01 -9.30629522e-02 -5.04374564e-01
-1.64507285e-01 -1.78216070e-01 7.65082777e-01 -8.47041845e-01
5.15647113e-01 -8.18816796e-02 7.23234117e-01 -1.21793294e+00
4.19036567e-01 -1.06438744e+00 1.15921021e-01 5.37856638e-01
1.24204218e-01 -3.75418723e-01 1.93504363e-01 5.48600793e-01
-7.31484517e-02 -1.34788230e-01 8.18810761e-01 1.19273169e-02
-7.78469384e-01 9.30479228e-01 3.51043522e-01 -2.00957701e-01
1.05086648e+00 -5.13247848e-01 -2.88279712e-01 1.68427870e-01
-3.55315238e-01 6.96865797e-01 6.89392865e-01 4.71036941e-01
6.11257613e-01 -1.76154709e+00 -6.40274286e-01 2.99992651e-01
2.01867282e-01 3.52437586e-01 1.87658191e-01 9.83604908e-01
-2.06932813e-01 4.75946814e-01 -1.04657248e-01 -9.91284370e-01
-1.24210870e+00 2.57951736e-01 4.26286012e-01 -2.41882220e-01
-7.62737751e-01 9.71771896e-01 3.57335627e-01 -5.18724501e-01
2.66348064e-01 -4.74730760e-01 9.54920799e-03 -8.16578120e-02
2.44158447e-01 -4.58726520e-03 -2.16548428e-01 -6.06882870e-01
-5.66050053e-01 1.11316931e+00 -7.15562999e-02 4.06565338e-01
1.38629353e+00 8.18105713e-02 3.27398658e-01 -1.07607402e-01
6.98719323e-01 1.47297561e-01 -1.79674149e+00 -5.71153402e-01
-2.42565677e-01 -6.91584051e-01 2.47983947e-01 -5.63395560e-01
-1.40272915e+00 7.56783724e-01 6.06149197e-01 -1.69056773e-01
8.35875273e-01 1.19105212e-01 7.99786210e-01 -1.20102791e-02
5.16889155e-01 -6.14613771e-01 6.09757453e-02 5.34203470e-01
6.28051639e-01 -1.41476798e+00 2.26531789e-01 -5.57987332e-01
-3.43160003e-01 9.66855407e-01 9.66115117e-01 -2.75955945e-01
6.79678559e-01 1.23310201e-01 1.38805389e-01 -4.75388944e-01
-5.48740566e-01 -3.33698452e-01 7.59761095e-01 3.87546748e-01
2.91099221e-01 -1.54292971e-01 -2.06412032e-01 4.43082929e-01
2.77428359e-01 9.51064005e-03 -3.12820762e-01 1.01211846e+00
-6.77323401e-01 -1.20570564e+00 -5.65677583e-01 2.89024532e-01
-3.89738157e-02 7.99732134e-02 -2.12169975e-01 8.33969235e-01
2.48771399e-01 3.28684181e-01 -9.04329196e-02 -2.92445451e-01
5.10649681e-01 -3.69095057e-01 6.43698931e-01 -4.90515441e-01
-6.91431701e-01 4.22766268e-01 -3.06662798e-01 -4.46351796e-01
-5.75809538e-01 -5.95107257e-01 -1.24464154e+00 -2.13723555e-01
-8.45248580e-01 -1.75903626e-02 3.06999594e-01 6.94268286e-01
4.21529025e-01 4.08531606e-01 6.60702467e-01 -1.27745092e+00
-6.07864499e-01 -7.15938210e-01 -1.37606308e-01 1.75383195e-01
1.67891860e-01 -1.15939176e+00 -1.70581788e-01 -5.24099171e-01] | [6.561954498291016, -2.3013381958007812] |
bab38a03-173b-47f9-9eaf-194d2816d7b6 | osp2b-one-stage-point-to-box-network-for-3d | 2304.11584 | null | https://arxiv.org/abs/2304.11584v2 | https://arxiv.org/pdf/2304.11584v2.pdf | OSP2B: One-Stage Point-to-Box Network for 3D Siamese Tracking | Two-stage point-to-box network acts as a critical role in the recent popular 3D Siamese tracking paradigm, which first generates proposals and then predicts corresponding proposal-wise scores. However, such a network suffers from tedious hyper-parameter tuning and task misalignment, limiting the tracking performance. Towards these concerns, we propose a simple yet effective one-stage point-to-box network for point cloud-based 3D single object tracking. It synchronizes 3D proposal generation and center-ness score prediction by a parallel predictor without tedious hyper-parameters. To guide a task-aligned score ranking of proposals, a center-aware focal loss is proposed to supervise the training of the center-ness branch, which enhances the network's discriminative ability to distinguish proposals of different quality. Besides, we design a binary target classifier to identify target-relevant points. By integrating the derived classification scores with the center-ness scores, the resulting network can effectively suppress interference proposals and further mitigate task misalignment. Finally, we present a novel one-stage Siamese tracker OSP2B equipped with the designed network. Extensive experiments on challenging benchmarks including KITTI and Waymo SOT Dataset show that our OSP2B achieves leading performance with a considerable real-time speed.Code will be available at https://github.com/haooozi/OSP2B. | ['Jing Zhang', 'Mingyu Gao', 'Zhengyi Bao', 'Yuxiang Yang', 'Zhiwei He', 'Jiahao Nie'] | 2023-04-23 | null | null | null | null | ['3d-single-object-tracking'] | ['computer-vision'] | [-3.74136776e-01 -3.05513412e-01 -4.78809029e-01 -3.13562304e-01
-7.95417130e-01 -4.44556475e-01 3.50004673e-01 -1.70006201e-01
-3.71621490e-01 2.75991470e-01 -1.02319047e-01 4.79896627e-02
-8.04997981e-02 -3.99137974e-01 -6.05732262e-01 -7.59368062e-01
-2.36047313e-01 5.71267784e-01 8.30168188e-01 -1.21702708e-01
9.40520912e-02 7.34978139e-01 -1.29561973e+00 -2.57230550e-01
6.87962115e-01 1.32661474e+00 1.85160458e-01 3.07751268e-01
1.96986213e-01 1.38619170e-01 -7.50830889e-01 -2.64910936e-01
7.24184036e-01 2.12376058e-01 1.80719927e-01 -2.07761019e-01
8.50101054e-01 -1.07800744e-01 -4.28496391e-01 1.20024443e+00
8.00274253e-01 -6.43505156e-02 3.87427568e-01 -1.45396531e+00
-2.72950884e-02 4.17253435e-01 -8.26173186e-01 3.65784645e-01
-1.87864840e-01 5.65483212e-01 9.64256942e-01 -1.08737385e+00
4.07764494e-01 1.21897304e+00 8.39012265e-01 5.15016675e-01
-1.15840554e+00 -1.25954330e+00 2.73376286e-01 4.60582748e-02
-1.49080944e+00 -3.85176748e-01 9.93371785e-01 -3.25367928e-01
4.10179168e-01 1.11287475e-01 7.07480133e-01 1.08815849e+00
1.96659505e-01 7.95188844e-01 5.07376909e-01 2.45353803e-01
3.80322300e-02 -1.30542547e-01 1.21169724e-01 6.61397815e-01
5.20155072e-01 5.29500127e-01 -7.73208857e-01 -1.42768592e-01
7.03725100e-01 -2.25780141e-02 -1.24492258e-01 -8.87697875e-01
-1.46319771e+00 5.62004268e-01 9.63536859e-01 7.69166788e-03
-2.67273545e-01 2.67720968e-01 4.15577888e-01 5.53278252e-02
2.98897833e-01 6.88386858e-02 -2.48664990e-01 2.66233563e-01
-1.05170059e+00 3.94825518e-01 3.61521453e-01 1.23404193e+00
4.52855587e-01 1.48967296e-01 -7.31879652e-01 6.64929450e-01
7.37794518e-01 9.83256757e-01 -7.23755807e-02 -9.09798503e-01
6.50868833e-01 6.16375387e-01 2.17456415e-01 -1.07457781e+00
-5.40964007e-01 -1.12908614e+00 -6.56051934e-01 5.13054132e-01
5.16332984e-01 -3.07478625e-02 -7.61916339e-01 1.79434562e+00
8.83357704e-01 2.05353126e-01 -4.20931160e-01 1.53250051e+00
5.73945403e-01 3.70580167e-01 1.25526458e-01 7.48559013e-02
1.56079602e+00 -8.76612425e-01 -2.29274705e-01 -2.28620589e-01
4.11803454e-01 -8.04517508e-01 5.96936524e-01 1.92116126e-01
-9.48209226e-01 -7.23715127e-01 -1.19263077e+00 2.89505005e-01
9.60736126e-02 5.42685926e-01 3.99197817e-01 5.57373822e-01
-7.73855448e-01 3.77848208e-01 -8.11414540e-01 -7.25870356e-02
7.28713810e-01 6.37491584e-01 -3.93638462e-02 3.03741336e-01
-9.03764904e-01 6.68029904e-01 4.06897485e-01 3.24385732e-01
-1.05933022e+00 -9.58346426e-01 -4.82402265e-01 8.71443450e-02
6.73491120e-01 -7.31414497e-01 1.06735647e+00 -2.65065074e-01
-1.37802029e+00 5.89130044e-01 6.00867756e-02 -5.82032800e-01
5.97741127e-01 -2.50502169e-01 -4.15407628e-01 -5.29151559e-02
2.90822625e-01 1.07003415e+00 9.47156191e-01 -1.11227775e+00
-9.54744458e-01 -6.63534939e-01 -3.19654614e-01 2.21894726e-01
-7.17254430e-02 -2.07787491e-02 -8.12804520e-01 -7.92420566e-01
4.43545312e-01 -1.08847594e+00 -1.73694730e-01 6.11747205e-01
-4.36726004e-01 -5.73968530e-01 7.45178103e-01 -1.01226054e-01
9.36888993e-01 -2.23057771e+00 -1.60246789e-01 3.33394438e-01
6.90319419e-01 3.82401973e-01 -1.66098595e-01 -1.49476036e-01
2.16017559e-01 -5.49771905e-01 2.80384898e-01 -5.17221332e-01
1.95708454e-01 -3.06738198e-01 -1.70102194e-01 7.45673001e-01
2.64908761e-01 8.30174804e-01 -8.57163370e-01 -7.27642417e-01
2.06608489e-01 4.80870187e-01 -6.32184446e-01 6.59727976e-02
-1.84407070e-01 3.86203468e-01 -8.08757842e-01 9.44011927e-01
8.50282133e-01 -3.02437216e-01 -1.26740918e-01 -6.33516431e-01
-3.42209786e-01 2.83589780e-01 -1.14339054e+00 1.77283907e+00
-1.35413064e-02 4.45801526e-01 2.10987940e-01 -6.60441279e-01
1.21401882e+00 -4.75575291e-02 6.65895700e-01 -6.62022650e-01
4.00766343e-01 3.65722418e-01 1.12610184e-01 1.80657700e-01
4.82933402e-01 2.46122479e-01 -3.31480324e-01 -5.88141521e-03
-1.17089815e-01 2.34894469e-01 -4.79163276e-03 2.53522545e-01
1.05134809e+00 3.90987664e-01 -1.51380792e-01 -2.01825887e-01
7.19386280e-01 3.08758318e-01 1.03383744e+00 7.57946968e-01
-8.34431887e-01 3.89467776e-01 1.67205587e-01 -3.71527463e-01
-9.08140481e-01 -1.25033236e+00 -1.21278033e-01 9.34865236e-01
6.52403474e-01 -2.26988107e-01 -2.74771392e-01 -9.02269661e-01
4.07862455e-01 2.94969201e-01 -3.63408089e-01 -2.69555300e-01
-8.17751825e-01 -3.75755161e-01 5.47359109e-01 4.19175535e-01
2.73021609e-01 -7.01537073e-01 -5.26398540e-01 2.74893731e-01
7.29597360e-02 -9.17191029e-01 -9.55307782e-01 1.11206695e-01
-9.92706001e-01 -9.96701717e-01 -7.14410841e-01 -5.68496704e-01
4.34391648e-01 7.65987813e-01 9.30385649e-01 -1.04395598e-01
1.20358244e-02 2.46978272e-02 -2.35500690e-02 -3.37332487e-01
5.58787771e-02 1.82893753e-01 3.86558980e-01 -3.08633130e-02
5.57836175e-01 -4.29863364e-01 -9.86375213e-01 8.18812191e-01
-2.24113032e-01 -2.44953915e-01 8.58668745e-01 5.90028167e-01
7.48435199e-01 -5.40860295e-01 4.82646942e-01 -1.67008564e-01
7.32290968e-02 -2.76270956e-01 -1.25911903e+00 -1.81681514e-02
-5.05611837e-01 -8.29001796e-03 4.45307106e-01 -6.24397516e-01
-6.91797853e-01 3.43389124e-01 1.19017862e-01 -1.03855813e+00
1.94462150e-01 -1.98577896e-01 -1.60941824e-01 -5.00538230e-01
6.42655790e-01 4.76927236e-02 1.56269655e-01 -4.39284056e-01
2.36475497e-01 3.75249505e-01 6.65133655e-01 -4.75698799e-01
1.44839013e+00 5.68320870e-01 2.00502440e-01 -3.26529145e-01
-9.63867843e-01 -6.96349859e-01 -3.26692551e-01 -6.57261670e-01
6.96629167e-01 -1.31583786e+00 -1.14944613e+00 1.85724795e-01
-1.16906583e+00 7.78465867e-02 -2.44643152e-01 7.25674689e-01
-2.30716154e-01 1.54720962e-01 -2.53493667e-01 -5.99736989e-01
-5.69515049e-01 -1.14648819e+00 1.32158840e+00 4.01100397e-01
9.00558978e-02 -4.78642136e-01 1.02205999e-01 4.06875074e-01
3.26633543e-01 9.34633613e-03 1.12775892e-01 -6.85029268e-01
-1.11284256e+00 -2.92711824e-01 -4.61609960e-01 -8.58391896e-02
-4.07505810e-01 -2.67281890e-01 -7.07986414e-01 -5.23302555e-01
-2.88425572e-02 -1.39073536e-01 7.92276263e-01 4.89978552e-01
8.68352413e-01 1.95893481e-01 -6.39860690e-01 7.43578970e-01
1.22896683e+00 -8.95643160e-02 -6.46212371e-03 2.57395059e-01
7.52484858e-01 2.57585585e-01 1.04849517e+00 3.94675523e-01
3.68839830e-01 1.17690074e+00 6.79045558e-01 1.82710215e-01
-4.56936270e-01 -2.75319844e-01 4.51166958e-01 6.37403727e-01
9.98217165e-02 3.30860354e-02 -6.25311732e-01 3.97867799e-01
-1.82963955e+00 -7.73720860e-01 -3.63233715e-01 2.31137967e+00
5.52423656e-01 6.04105353e-01 4.26111609e-01 -3.71245921e-01
9.95116651e-01 3.68022740e-01 -8.11513841e-01 7.24408925e-01
1.04565322e-01 -2.05313146e-01 8.61377776e-01 7.94284046e-02
-1.23785126e+00 9.79670465e-01 4.64155531e+00 1.22482979e+00
-1.11777842e+00 2.66967833e-01 3.79041699e-03 -5.76208889e-01
2.46261060e-01 -5.45379370e-02 -1.51929045e+00 6.21593595e-01
6.04604185e-01 -1.05804075e-02 -9.61285681e-02 1.08578098e+00
3.67105156e-01 1.71745151e-01 -8.95471931e-01 9.53279436e-01
-1.87967956e-01 -1.35089016e+00 -2.44122609e-01 1.05646141e-01
2.97790647e-01 4.93525147e-01 7.42020160e-02 3.53501409e-01
2.61194348e-01 -1.67564139e-01 1.09796631e+00 2.20131904e-01
4.43407506e-01 -5.95663130e-01 3.96361738e-01 2.40296483e-01
-1.58529747e+00 -1.20189279e-01 -6.16329849e-01 5.00075400e-01
3.01016301e-01 7.00722039e-01 -6.85207009e-01 5.70999801e-01
8.10198307e-01 7.73884833e-01 -4.53890234e-01 1.62298107e+00
-1.26356542e-01 3.39798510e-01 -5.71041584e-01 -5.18084913e-02
2.75960237e-01 5.51764853e-02 1.29739416e+00 8.42763603e-01
4.16849256e-01 -1.50131822e-01 4.26321834e-01 9.60176170e-01
-5.41992784e-02 -1.81940079e-01 -2.53675550e-01 5.38893223e-01
8.56504023e-01 1.50415313e+00 -7.49845564e-01 -2.59632468e-01
-1.78088546e-01 2.97864258e-01 2.65166730e-01 2.81276032e-02
-1.26748300e+00 -2.24753052e-01 9.26752448e-01 1.44970790e-01
5.46591163e-01 -3.01118076e-01 -3.04988772e-01 -1.08681858e+00
1.48307756e-01 -5.72223783e-01 2.94499904e-01 -5.82738101e-01
-1.35962856e+00 5.19104242e-01 -2.17130303e-01 -1.99179471e+00
4.15039301e-01 -4.62684602e-01 -6.05040550e-01 7.01298535e-01
-1.60052836e+00 -1.02956152e+00 -4.84680593e-01 5.72022021e-01
4.92095619e-01 -2.72385806e-01 -9.72600430e-02 6.82112932e-01
-7.01064706e-01 7.30855525e-01 -2.90551335e-01 9.76947621e-02
1.09420812e+00 -8.62712741e-01 4.82786387e-01 7.93114603e-01
-2.26634238e-02 5.01578331e-01 5.74656487e-01 -9.97208416e-01
-1.40512788e+00 -1.30903149e+00 6.65800154e-01 -3.79670352e-01
8.07335317e-01 -4.21432734e-01 -7.22908556e-01 2.95721203e-01
-2.71500051e-01 2.51930416e-01 1.23728544e-01 -4.06069793e-02
-4.22474951e-01 -5.83827078e-01 -8.05007458e-01 6.49011552e-01
1.44649017e+00 1.92744937e-02 -4.89813447e-01 4.83779311e-01
8.93768072e-01 -6.18382931e-01 -8.14884424e-01 5.10623753e-01
5.82433045e-01 -8.45039964e-01 1.35488737e+00 -1.57551736e-01
-2.61186898e-01 -9.09376204e-01 2.27565318e-01 -8.79376709e-01
-6.52630031e-01 -6.31522536e-01 -3.79521221e-01 9.49796557e-01
2.70677894e-01 -5.59524238e-01 1.28583276e+00 1.33019611e-01
-5.13559461e-01 -6.49055481e-01 -1.22067189e+00 -1.17372453e+00
-3.48941833e-01 -3.02636504e-01 5.36455333e-01 4.61367309e-01
-5.70511818e-01 2.95144469e-01 -3.50328743e-01 5.81378281e-01
1.38570595e+00 1.06401227e-01 1.07993519e+00 -1.56810641e+00
-8.78444985e-02 -6.30766749e-01 -4.69049454e-01 -1.62233675e+00
-9.29185823e-02 -9.64298069e-01 2.90003151e-01 -8.73706043e-01
-6.73162714e-02 -1.06247389e+00 -3.97945523e-01 2.60886788e-01
-8.01334977e-02 3.20286691e-01 4.88503963e-01 7.12748647e-01
-1.07739043e+00 7.85956264e-01 1.34970188e+00 -1.92759037e-01
-2.34999001e-01 3.90313864e-01 -3.98035675e-01 4.11642730e-01
7.07129598e-01 -9.83540297e-01 -1.39751136e-01 -2.70935625e-01
-2.98944749e-02 4.12090681e-02 6.79511547e-01 -1.48122084e+00
7.08898485e-01 4.62238193e-02 4.99988586e-01 -1.30718410e+00
5.49948275e-01 -9.55067098e-01 1.39187172e-01 6.28836274e-01
-1.41196758e-01 -1.18550591e-01 1.83031727e-02 7.60083854e-01
-1.90384518e-02 1.43307373e-01 8.57696533e-01 3.27450067e-01
-5.71570694e-01 8.05852771e-01 2.65126735e-01 -2.51521319e-02
1.20325506e+00 -3.63305330e-01 -4.97281194e-01 2.90651172e-01
-4.23797488e-01 7.49120116e-01 3.78722817e-01 5.98878622e-01
4.08430308e-01 -1.69522703e+00 -5.97301781e-01 1.29483730e-01
2.34381050e-01 8.18927586e-02 3.08907717e-01 1.25705147e+00
-1.22181647e-01 5.60751915e-01 -1.34122476e-01 -1.20740843e+00
-1.15258229e+00 3.69437605e-01 2.99890757e-01 -2.38288149e-01
-8.00797462e-01 8.10906112e-01 2.34939203e-01 -3.82843018e-01
5.24145961e-01 -1.76089957e-01 -7.77526200e-02 -7.32242912e-02
3.35472763e-01 3.10951054e-01 -1.37515828e-01 -6.68767631e-01
-6.80527568e-01 7.21684754e-01 -9.38365161e-02 1.24653816e-01
1.13203871e+00 -1.25198076e-02 4.16042328e-01 -7.71164224e-02
8.07772160e-01 -7.76473433e-02 -1.79753637e+00 -4.87178117e-01
8.61547738e-02 -5.34536362e-01 1.78251311e-01 -3.96615595e-01
-1.35824621e+00 6.27652645e-01 7.82283425e-01 -1.04624555e-01
7.89489925e-01 6.83777258e-02 9.90802109e-01 3.09792250e-01
6.15586936e-01 -9.60318148e-01 1.85333490e-01 4.38485563e-01
5.72778940e-01 -1.28009713e+00 1.74422208e-02 -5.35339653e-01
-3.56010199e-01 8.06221426e-01 9.44547713e-01 -3.50389779e-01
4.89677668e-01 7.32964128e-02 1.15790113e-03 -4.41473335e-01
-6.96098387e-01 -2.51661003e-01 5.31596065e-01 5.38168252e-01
-1.31989434e-01 -4.06714827e-02 -1.80445924e-01 3.83008868e-01
-2.07144916e-02 -9.39868838e-02 -9.95015576e-02 6.43641829e-01
-6.83765531e-01 -8.71444643e-01 -7.05653667e-01 3.29059899e-01
-1.36301965e-01 1.65166214e-01 1.73843873e-03 7.58721292e-01
6.57443255e-02 5.08828104e-01 4.06267643e-02 -5.23585916e-01
5.71121454e-01 -3.32405090e-01 2.10425496e-01 -3.10080975e-01
-8.69467318e-01 3.08288634e-01 -4.05232161e-02 -1.02889490e+00
-2.80840248e-01 -7.13469148e-01 -1.10161996e+00 -2.07696423e-01
-5.17651379e-01 1.03010572e-01 7.41869748e-01 4.92513925e-01
8.05766761e-01 4.67216730e-01 5.90288639e-01 -1.21378708e+00
-1.00932086e+00 -6.45794749e-01 -2.24810302e-01 4.44791950e-02
2.59010762e-01 -1.16834867e+00 -3.28357249e-01 -5.73599637e-01] | [6.43184232711792, -2.237067937850952] |
d712b037-9812-48b9-8700-7650f385aa55 | nnembs-at-semeval-2017-task-4-neural-twitter | null | null | https://aclanthology.org/S17-2102 | https://aclanthology.org/S17-2102.pdf | NNEMBs at SemEval-2017 Task 4: Neural Twitter Sentiment Classification: a Simple Ensemble Method with Different Embeddings | Recently, neural twitter sentiment classification has become one of state-of-thearts, which relies less feature engineering work compared with traditional methods. In this paper, we propose a simple and effective ensemble method to further boost the performances of neural models. We collect several word embedding sets which are publicly released (often are learned on different corpus) or constructed by running Skip-gram on released large-scale corpus. We make an assumption that different word embeddings cover different words and encode different semantic knowledge, thus using them together can improve the generalizations and performances of neural models. In the SemEval 2017, our method ranks 1st in Accuracy, 5th in AverageR. Meanwhile, the additional comparisons demonstrate the superiority of our model over these ones based on only one word embedding set. We release our code for the method duplicability. | ['Ming Zhang', 'Yangqiu Song', 'Yichun Yin'] | 2017-08-01 | null | null | null | semeval-2017-8 | ['learning-word-embeddings'] | ['methodology'] | [-2.18405500e-01 -3.09609741e-01 -2.42049247e-01 -4.16510403e-01
-4.60356295e-01 -5.04600883e-01 6.65308535e-01 1.19343303e-01
-9.39570308e-01 6.62963569e-01 5.49857378e-01 -1.85412839e-01
2.72192024e-02 -8.37695062e-01 -5.70291817e-01 -6.85596764e-01
1.37423247e-01 1.92525722e-02 3.92474048e-02 -5.74482024e-01
1.41416207e-01 -1.66477203e-01 -1.61031926e+00 1.23962775e-01
7.87401080e-01 1.12566864e+00 -4.12170961e-03 3.25656831e-01
-5.21713972e-01 1.79953158e-01 -5.01776457e-01 -9.62222397e-01
2.84152348e-02 8.78136780e-04 -4.72194314e-01 -4.65325534e-01
1.31728336e-01 -9.66644511e-02 -4.09660012e-01 1.06082404e+00
6.70518160e-01 1.31383108e-03 6.68110609e-01 -1.19973135e+00
-1.13157725e+00 9.03396606e-01 -3.97428334e-01 9.83107463e-02
-1.10788211e-01 -2.18563035e-01 1.30335379e+00 -1.18270051e+00
2.93439329e-01 8.78985345e-01 8.11117291e-01 6.04145646e-01
-7.89606392e-01 -1.14628577e+00 4.52100575e-01 3.86182517e-01
-1.22684169e+00 -2.87879109e-01 8.24032485e-01 -2.40691260e-01
9.06836212e-01 9.37489420e-02 6.06232822e-01 1.53248382e+00
-1.82415228e-02 8.38569283e-01 9.78482306e-01 -2.78394103e-01
9.45758671e-02 4.60751474e-01 7.44255722e-01 5.15256584e-01
7.38900721e-01 -1.63450539e-01 -5.92214704e-01 -1.71077356e-01
1.22357346e-01 3.34226668e-01 -2.16747880e-01 7.61234760e-02
-1.06838393e+00 1.07581842e+00 3.58392894e-01 3.07980984e-01
-1.13411084e-01 2.06408501e-01 5.71788073e-01 3.72947454e-01
9.56591129e-01 3.96662116e-01 -7.32377172e-01 -2.95261323e-01
-4.27345902e-01 1.96545854e-01 6.00531101e-01 6.64690673e-01
8.30680728e-01 -7.69394487e-02 2.64732204e-02 1.05116963e+00
3.65427494e-01 4.04177219e-01 1.16074061e+00 -2.64109313e-01
3.61471921e-01 6.97472274e-01 -1.78468868e-01 -1.24446452e+00
-3.82728130e-01 -5.37547469e-01 -7.55252242e-01 -2.53336489e-01
7.57129416e-02 -5.44095218e-01 -7.48913467e-01 1.60658824e+00
2.03662828e-01 4.41061467e-01 1.79067776e-01 4.50253159e-01
1.05803013e+00 6.99761093e-01 8.00682791e-03 1.68237358e-01
1.42447972e+00 -1.30697191e+00 -8.04625034e-01 -2.79500723e-01
9.24122155e-01 -4.65809882e-01 1.05804133e+00 3.79675239e-01
-3.57286036e-01 -4.81131792e-01 -1.38287330e+00 6.47793636e-02
-9.63431954e-01 2.16681510e-02 8.74847949e-01 7.99235225e-01
-7.79269457e-01 6.45520508e-01 -5.86780429e-01 -1.88611209e-01
5.49055934e-01 1.03137210e-01 -5.31922221e-01 -8.15246403e-02
-1.61977518e+00 9.76199567e-01 4.87286627e-01 -4.78825904e-02
-3.97942692e-01 -6.47012413e-01 -8.78415585e-01 -3.20729166e-02
2.04272091e-01 -4.66774404e-01 1.08950257e+00 -8.75825763e-01
-1.45033324e+00 5.84172845e-01 -1.89927533e-01 -2.17546418e-01
2.23486111e-01 -4.93298948e-01 -6.41463280e-01 -3.65046263e-01
-1.55072555e-01 3.03948760e-01 7.20269799e-01 -1.06040204e+00
-5.10304332e-01 -4.09169972e-01 2.01568946e-01 -8.21416527e-02
-1.35138810e+00 -3.54738384e-02 -4.17671800e-01 -7.02286243e-01
-1.63383782e-01 -7.76673079e-01 -3.32653135e-01 -1.72430173e-01
-3.07981074e-01 -6.16964221e-01 5.95590234e-01 -2.33679697e-01
1.57904530e+00 -2.18759656e+00 6.13645976e-03 -7.05106109e-02
1.96599364e-01 2.61479318e-01 -3.29912692e-01 6.71453238e-01
-3.42644900e-02 4.12848979e-01 -1.34856194e-01 -7.72281647e-01
2.41303802e-01 1.97241187e-01 -3.75909299e-01 3.38066787e-01
2.66249627e-01 9.77770865e-01 -8.39817405e-01 -2.94361025e-01
-1.46345273e-01 6.13572717e-01 -4.04313803e-01 -4.12895791e-02
1.18669689e-01 -8.03452581e-02 -7.58378208e-01 3.98763061e-01
5.78968167e-01 -1.90549627e-01 8.95220339e-02 -2.79326975e-01
1.88715775e-02 2.58385509e-01 -1.00097620e+00 1.67320383e+00
-7.37491965e-01 3.88717741e-01 -6.43900275e-01 -9.28279042e-01
9.45308685e-01 9.42699015e-02 1.34104431e-01 -4.31676149e-01
4.93745178e-01 1.62379712e-01 9.51695908e-03 -5.44542611e-01
5.61334312e-01 8.67641643e-02 -1.75292134e-01 6.32147312e-01
3.25137198e-01 2.70083576e-01 1.10987686e-01 -1.01476451e-02
7.75910795e-01 -1.32548943e-01 2.30378360e-01 -3.33964348e-01
4.61624503e-01 -3.06617886e-01 3.07347596e-01 4.88248646e-01
-1.99986145e-01 6.79600835e-01 5.50976813e-01 -4.49924827e-01
-8.04477513e-01 -6.79071605e-01 -4.92778778e-01 1.44403589e+00
7.90814459e-02 -7.59198010e-01 -5.56301415e-01 -9.61006165e-01
1.49117485e-01 7.29792178e-01 -1.09271860e+00 -1.88415051e-01
-3.52174222e-01 -1.22400784e+00 6.23933136e-01 7.05845237e-01
3.71871620e-01 -8.38401973e-01 -1.05533235e-01 1.82752654e-01
1.23876967e-01 -9.52627659e-01 -2.90440828e-01 1.48162767e-01
-6.74245954e-01 -8.20594788e-01 -6.59077764e-01 -7.23824799e-01
4.66681421e-01 3.46536845e-01 9.27384973e-01 2.08458081e-01
1.65734589e-01 -4.88336757e-02 -8.82237911e-01 -9.26319778e-01
2.36525133e-01 4.72962230e-01 2.46721670e-01 2.64339685e-01
7.81041086e-01 -4.94273037e-01 -5.72412193e-01 -3.30313966e-02
-9.85873461e-01 -8.31014216e-02 2.17494965e-01 8.90592039e-01
2.92039812e-01 -7.19875023e-02 8.40156555e-01 -1.08616388e+00
9.80175734e-01 -8.69646966e-01 -1.34812653e-01 3.37837748e-02
-9.21901524e-01 1.26167700e-01 8.41398954e-01 -3.95473242e-01
-6.45770371e-01 -3.93580109e-01 -4.26545829e-01 -1.99670196e-01
9.04223099e-02 6.88514590e-01 4.91532944e-02 1.95639744e-01
4.43374455e-01 3.60605389e-01 -1.75269302e-02 -5.99418581e-01
4.49566752e-01 8.88452232e-01 -4.62907143e-02 -4.68098491e-01
6.64410353e-01 3.37595612e-01 -5.78283846e-01 -5.19814014e-01
-1.08462274e+00 -3.13964099e-01 -3.13075483e-01 1.95045978e-01
7.31897593e-01 -1.10060203e+00 -4.45221543e-01 6.39167070e-01
-1.26374567e+00 1.71519741e-01 1.24336131e-01 5.00659585e-01
3.09778631e-01 1.50716871e-01 -4.03714359e-01 -6.86132967e-01
-5.07413149e-01 -1.12324977e+00 8.04790378e-01 2.16029868e-01
-1.35580063e-01 -1.17802465e+00 4.92574871e-01 -4.91583459e-02
8.79870832e-01 3.86132337e-02 7.23838270e-01 -1.17277658e+00
2.83162653e-01 -4.77433622e-01 -1.84353322e-01 6.11376762e-01
1.26648337e-01 1.29379153e-01 -1.43893838e+00 -1.64112255e-01
-1.88639179e-01 -3.47525954e-01 1.44911432e+00 5.50641343e-02
1.62758279e+00 -2.01291606e-01 -3.90032828e-01 5.44221222e-01
1.43988585e+00 -1.90477118e-01 4.58158582e-01 6.62607312e-01
7.46031702e-01 6.74478412e-01 2.51669824e-01 3.88237625e-01
7.38814473e-01 2.79899240e-01 4.87080157e-01 1.22438692e-01
3.16775501e-01 -2.86713630e-01 5.45624912e-01 1.40727675e+00
-2.91829914e-01 -2.89689749e-01 -7.07124352e-01 6.78223312e-01
-1.79367733e+00 -7.96838045e-01 -1.78782001e-01 1.88471675e+00
8.17171991e-01 2.06090748e-01 -3.55659388e-02 4.75056581e-02
4.93984938e-01 5.52997172e-01 -4.70144093e-01 -4.73511934e-01
-1.41501114e-01 6.07870400e-01 5.70327878e-01 3.42955589e-01
-1.12614417e+00 9.20474887e-01 6.08582687e+00 8.40494037e-01
-1.10997748e+00 3.97927046e-01 5.38426518e-01 -1.81838393e-01
-6.56515598e-01 -4.26839232e-01 -1.13927209e+00 7.33751774e-01
1.03031099e+00 -3.24530661e-01 -2.24779937e-02 9.82065499e-01
-3.18162113e-01 3.63314718e-01 -8.20626497e-01 9.83494699e-01
4.65684265e-01 -1.31612849e+00 8.47841203e-02 -8.99083242e-02
8.60373914e-01 3.93133938e-01 2.73542315e-01 7.29604840e-01
2.54622489e-01 -1.14583993e+00 3.70120555e-01 2.97053486e-01
5.78237891e-01 -9.40221667e-01 1.17409778e+00 1.62658691e-01
-9.44630027e-01 -3.43356803e-02 -5.80288947e-01 -1.31924286e-01
3.76117118e-02 7.72593260e-01 -1.06578156e-01 6.36713326e-01
8.09250593e-01 1.03817296e+00 -8.10606658e-01 6.31014228e-01
-3.63831460e-01 7.88024545e-01 -9.93885547e-02 -7.53107607e-01
3.66942197e-01 -2.18503997e-01 2.28358302e-02 1.35102177e+00
3.19438875e-01 -2.24081337e-01 -1.12525985e-01 3.88502628e-01
-4.03537899e-01 4.64142740e-01 -7.15912223e-01 -2.13702410e-01
3.96470129e-01 1.47464585e+00 -1.51267663e-01 -4.40623790e-01
-6.91761851e-01 7.79838920e-01 5.12826920e-01 2.39995271e-01
-1.08159912e+00 -7.53863215e-01 1.03097486e+00 -4.11047399e-01
4.39396054e-01 -1.47804931e-01 -3.73185217e-01 -1.42471755e+00
7.59277940e-02 -6.06322169e-01 1.02303229e-01 -3.38386804e-01
-1.74771810e+00 1.08656931e+00 -1.58552393e-01 -1.04462433e+00
1.34985909e-01 -1.10973716e+00 -7.69668758e-01 7.31661320e-01
-1.93298233e+00 -8.91147077e-01 -1.87515736e-01 3.36470276e-01
4.82948720e-01 -4.44026053e-01 1.14149535e+00 3.67139965e-01
-1.02662098e+00 9.22834694e-01 5.24062932e-01 3.51175308e-01
8.47015917e-01 -1.06004918e+00 4.04764533e-01 4.07461226e-01
1.51748642e-01 8.69919538e-01 5.63476026e-01 -1.43477008e-01
-1.19980347e+00 -1.07296419e+00 1.02160621e+00 -5.37214637e-01
1.13047695e+00 -6.03825629e-01 -9.09340382e-01 5.55891871e-01
5.40753841e-01 7.03222700e-04 1.22594309e+00 5.54023266e-01
-7.07848012e-01 -2.83859074e-01 -6.51809394e-01 6.18144572e-01
9.39911067e-01 -3.58802646e-01 -8.04075122e-01 3.04509163e-01
1.10622609e+00 9.11945552e-02 -6.90739155e-01 2.96130240e-01
8.85992706e-01 -7.95831144e-01 6.85432136e-01 -9.98001575e-01
9.26012695e-01 -1.43603459e-01 -4.21819329e-01 -1.73164093e+00
-2.03835785e-01 1.58503857e-02 -6.30087703e-02 1.31275618e+00
7.94201553e-01 -1.16134238e+00 6.06438577e-01 2.90296316e-01
-1.09589659e-01 -1.19128263e+00 -6.76702619e-01 -6.29906058e-01
4.38041270e-01 -8.31745863e-01 9.08824444e-01 1.12619042e+00
5.60350977e-02 5.22628665e-01 -2.72000641e-01 -1.88288689e-01
2.80863702e-01 -1.03331998e-01 6.12593353e-01 -1.27632809e+00
-2.24068090e-01 -5.69862127e-01 -4.26600873e-01 -7.95180261e-01
5.54152727e-01 -1.08025205e+00 -2.91932374e-01 -1.33950102e+00
2.17803121e-01 -2.66640604e-01 -1.06464255e+00 6.78991079e-01
-5.12546599e-01 3.82847935e-01 2.98608541e-02 -5.78160696e-02
-5.42224050e-01 9.55615878e-01 9.60074902e-01 -2.02536181e-01
2.69110054e-01 -3.04587215e-01 -1.32990587e+00 7.24982560e-01
9.44506705e-01 -6.74773455e-01 -3.61059010e-01 -8.51976395e-01
5.52775085e-01 -8.91112447e-01 -1.61042474e-02 -7.81885266e-01
1.10780537e-01 1.32268220e-01 2.70988613e-01 -1.63931116e-01
2.11347446e-01 -7.19838440e-01 -3.36836398e-01 2.62581944e-01
-3.38932097e-01 3.62582654e-01 2.81708986e-01 7.08335280e-01
-3.77576977e-01 -3.84054899e-01 3.29671592e-01 1.07175305e-01
-8.07482421e-01 6.07151151e-01 8.83917734e-02 4.69770655e-03
8.86680484e-01 6.89624622e-02 -3.88262242e-01 -1.55754730e-01
-2.05860183e-01 2.33462155e-01 1.24927483e-01 8.11938524e-01
5.12810469e-01 -1.54285979e+00 -9.15653884e-01 1.72157720e-01
5.30918837e-01 -2.05777913e-01 2.22033948e-01 7.06729352e-01
-2.58937895e-01 1.49201900e-01 6.44799322e-02 -2.37491563e-01
-9.14531231e-01 2.71235138e-01 3.21665220e-02 -2.70848632e-01
-2.66453058e-01 1.07368505e+00 1.08545758e-01 -7.17055321e-01
2.18260381e-02 -1.13877185e-01 -7.22280145e-01 4.66502279e-01
9.75642443e-01 1.88072562e-01 1.16000392e-01 -4.56450611e-01
-4.68630522e-01 6.81401670e-01 -3.65377963e-01 9.75451246e-02
1.60277665e+00 1.59942418e-01 -7.71898106e-02 7.97118247e-01
1.80316746e+00 7.85771981e-02 -7.49926090e-01 -2.54170746e-01
-2.67332643e-01 -2.84184396e-01 2.00512975e-01 -4.56994742e-01
-1.21777499e+00 9.32495952e-01 5.17811477e-01 3.44274312e-01
8.81591082e-01 -1.82214767e-01 9.65838313e-01 4.74526078e-01
1.93770245e-01 -1.03099120e+00 -2.76135772e-01 8.39345813e-01
6.08137369e-01 -1.53442383e+00 -1.86601141e-03 1.11962728e-01
-7.84515679e-01 1.15481806e+00 6.56420350e-01 -5.47526121e-01
1.06860852e+00 6.62957206e-02 2.13086814e-01 -1.18339853e-02
-9.69171047e-01 -2.52433360e-01 2.22989127e-01 3.40825528e-01
6.86547220e-01 5.91365770e-02 -6.69740200e-01 1.17089319e+00
-3.53025168e-01 -2.70435244e-01 3.23775709e-01 5.06730437e-01
-4.55366045e-01 -1.31253314e+00 1.97731048e-01 6.58625126e-01
-5.93555987e-01 -4.82475996e-01 -2.20314458e-01 7.75491059e-01
1.30043119e-01 9.03457940e-01 7.21925423e-02 -8.31838131e-01
4.98978853e-01 2.75205255e-01 2.78347190e-02 -5.63190937e-01
-5.54761231e-01 -5.71104646e-01 1.26251474e-01 -3.52968842e-01
-3.81540984e-01 -3.68746340e-01 -9.74179745e-01 -3.66402775e-01
-4.30986822e-01 1.32634506e-01 8.73611987e-01 1.04353023e+00
5.53038061e-01 4.97800767e-01 8.04660499e-01 -6.11960590e-01
-6.91383541e-01 -1.18438029e+00 -5.32442451e-01 4.67588335e-01
1.94233581e-01 -7.64289141e-01 -5.59246421e-01 -3.15731466e-01] | [10.540263175964355, 8.331510543823242] |
4222b83d-ba58-4fb3-b05c-cafe75484386 | scalable-k-means-clustering-via-lightweight | 1702.08248 | null | http://arxiv.org/abs/1702.08248v2 | http://arxiv.org/pdf/1702.08248v2.pdf | Scalable k-Means Clustering via Lightweight Coresets | Coresets are compact representations of data sets such that models trained on
a coreset are provably competitive with models trained on the full data set. As
such, they have been successfully used to scale up clustering models to massive
data sets. While existing approaches generally only allow for multiplicative
approximation errors, we propose a novel notion of lightweight coresets that
allows for both multiplicative and additive errors. We provide a single
algorithm to construct lightweight coresets for k-means clustering as well as
soft and hard Bregman clustering. The algorithm is substantially faster than
existing constructions, embarrassingly parallel, and the resulting coresets are
smaller. We further show that the proposed approach naturally generalizes to
statistical k-means clustering and that, compared to existing results, it can
be used to compute smaller summaries for empirical risk minimization. In
extensive experiments, we demonstrate that the proposed algorithm outperforms
existing data summarization strategies in practice. | ['Andreas Krause', 'Olivier Bachem', 'Mario Lucic'] | 2017-02-27 | null | null | null | null | ['data-summarization'] | ['miscellaneous'] | [ 3.14869165e-01 3.02151352e-01 -4.44742948e-01 -4.15840894e-01
-1.12352598e+00 -5.04706323e-01 5.60956776e-01 7.21398890e-01
-2.46657684e-01 2.89345235e-01 4.56780970e-01 3.25108357e-02
-5.00078321e-01 -6.46364033e-01 -7.89746106e-01 -7.93241262e-01
-2.16746330e-01 1.01237845e+00 6.68802261e-02 3.10356617e-01
5.68076611e-01 1.21434852e-01 -1.83649445e+00 7.81014264e-02
9.82447267e-01 8.41745317e-01 1.19590573e-01 5.99865973e-01
5.48124090e-02 5.28872132e-01 -4.98573720e-01 -2.67994106e-01
3.22081089e-01 -9.10631344e-02 -1.12969005e+00 3.89588982e-01
5.68255126e-01 -2.49153182e-01 -1.85175434e-01 7.99407780e-01
4.13704753e-01 2.95006216e-01 8.62405002e-01 -1.25531650e+00
-5.16320825e-01 1.16232610e+00 -7.61822820e-01 -1.73176408e-01
8.29356238e-02 -5.24593890e-01 1.23805964e+00 -7.05604076e-01
2.12145343e-01 1.26433229e+00 6.58299804e-01 4.85385150e-01
-1.31545734e+00 -3.50842446e-01 2.55882502e-01 1.59021229e-01
-1.40078235e+00 -4.14645314e-01 3.69098961e-01 -3.45262177e-02
9.40514088e-01 6.17411613e-01 3.47838163e-01 5.98696232e-01
-3.27312768e-01 1.14398408e+00 7.32573807e-01 -5.37785828e-01
6.95539773e-01 -4.13202271e-02 7.78290808e-01 4.77053851e-01
9.22932148e-01 -4.26023185e-01 -2.97879636e-01 -8.38256478e-01
-6.28542975e-02 3.72248530e-01 -3.37680951e-02 -5.39949358e-01
-1.09678662e+00 1.02523541e+00 1.65677086e-01 1.43876180e-01
-1.61720410e-01 4.81082708e-01 5.39771378e-01 -2.42037158e-02
6.06127620e-01 2.66413122e-01 -2.45235935e-01 -6.13840260e-02
-1.39595068e+00 4.73462522e-01 9.09084737e-01 1.46127617e+00
8.08752954e-01 -2.71699876e-01 2.75148340e-02 9.58507180e-01
-4.28573675e-02 4.05822724e-01 3.92118961e-01 -1.27954066e+00
2.19968796e-01 5.45699179e-01 -3.47441733e-02 -9.07541871e-01
-3.51594925e-01 -2.46103957e-01 -1.17292178e+00 -6.43185794e-01
-6.57412261e-02 2.00837299e-01 -5.27537525e-01 1.75270891e+00
3.08124572e-01 2.77914762e-01 6.60663769e-02 2.33368978e-01
3.08759034e-01 7.28007197e-01 -1.92252442e-01 -6.72051132e-01
1.11167920e+00 -8.20936024e-01 -5.29247642e-01 7.68915340e-02
9.26654160e-01 -4.91018534e-01 8.08568537e-01 6.51338398e-01
-1.42122912e+00 -8.67357478e-02 -9.42759454e-01 -1.57459468e-01
-8.69005024e-02 -7.28102848e-02 9.39379811e-01 7.37905920e-01
-1.23477352e+00 7.50922918e-01 -9.63707149e-01 -6.26683772e-01
6.75130904e-01 3.60535741e-01 4.23958711e-02 -1.84240609e-01
-5.56987166e-01 5.37812591e-01 7.88270891e-01 -1.99192137e-01
-6.89699531e-01 -8.32232177e-01 -7.21538901e-01 2.96728373e-01
5.26429296e-01 -8.87905478e-01 1.26229835e+00 -4.83538300e-01
-1.04813111e+00 7.09252834e-01 -3.66461545e-01 -8.20287108e-01
1.98040500e-01 -3.54151338e-01 2.87513494e-01 3.90178174e-01
-1.19158747e-02 3.49059224e-01 6.34968221e-01 -1.27829325e+00
-7.81276762e-01 -3.96105558e-01 -2.08742097e-01 1.06811546e-01
-9.76982594e-01 1.77049324e-01 -4.67877686e-01 -6.22678816e-01
-1.76705308e-02 -9.04914200e-01 -6.83399141e-01 -3.20702583e-01
-6.39228582e-01 -6.14335120e-01 6.15158319e-01 -1.08805105e-01
1.60915709e+00 -1.95895374e+00 2.44240090e-01 4.81214434e-01
5.79154015e-01 6.10593185e-02 2.04536423e-01 5.45392752e-01
3.05230945e-01 2.21119091e-01 -5.60752273e-01 -7.41281033e-01
3.91489685e-01 5.29702902e-01 -3.57198954e-01 6.46311164e-01
-4.16047484e-01 5.51547229e-01 -8.39802265e-01 -5.91912329e-01
5.19240387e-02 -1.03440650e-01 -9.46818173e-01 5.59683926e-02
-2.46854469e-01 -5.83310306e-01 -3.00350159e-01 2.12783322e-01
8.66636693e-01 -5.45211017e-01 4.06916082e-01 1.52257532e-01
2.62605548e-01 5.53771257e-02 -1.37242126e+00 1.57957423e+00
-2.31912181e-01 5.81519715e-02 2.35044494e-01 -1.54237187e+00
6.18220925e-01 2.02124313e-01 6.27463520e-01 1.85942382e-01
1.45050615e-01 2.46094584e-01 -5.59431076e-01 -2.50723958e-03
8.70201766e-01 -1.04058823e-02 -5.24456024e-01 9.71132934e-01
-1.46121621e-01 -1.20611824e-01 5.21956265e-01 8.70801508e-01
1.27042401e+00 -5.71913779e-01 4.82211083e-01 -5.08121848e-01
2.00950667e-01 1.44169644e-01 5.41966379e-01 1.08393681e+00
2.49120668e-01 6.22974575e-01 2.97877103e-01 -2.97076225e-01
-1.15317249e+00 -1.03981090e+00 -1.60942331e-01 1.21701992e+00
2.21739024e-01 -1.19721341e+00 -1.10091960e+00 -5.14209151e-01
4.51032491e-03 6.51468515e-01 -4.91702616e-01 -1.71093076e-01
-3.86983961e-01 -9.65979695e-01 5.51066101e-01 7.30123103e-01
8.36166367e-02 -3.93426329e-01 -3.99281919e-01 2.31681079e-01
-2.03296661e-01 -9.69320238e-01 -6.77944660e-01 1.59773275e-01
-1.27806842e+00 -1.15047324e+00 -4.49643135e-01 -7.69723952e-01
8.21591735e-01 6.79747701e-01 1.00277615e+00 3.49409103e-01
-2.25268990e-01 6.29174113e-01 -5.18280923e-01 -5.35498738e-01
-6.18274808e-01 1.53320208e-01 4.51024711e-01 -1.98187292e-01
7.64669180e-01 -5.67773044e-01 -5.23410201e-01 3.55234258e-02
-1.12659633e+00 -4.43164632e-02 3.77211541e-01 7.10439920e-01
7.43975937e-01 2.67768085e-01 6.45406902e-01 -1.20653963e+00
5.90619802e-01 -4.79723066e-01 -4.21287566e-01 3.70365351e-01
-9.37417209e-01 2.11888880e-01 8.41092646e-01 -1.64400667e-01
-8.05446982e-01 3.78892981e-02 1.07455224e-01 -4.12525356e-01
-2.19180465e-01 2.33892396e-01 3.42343673e-02 4.21423078e-01
5.19837320e-01 2.22021267e-01 -6.78779334e-02 -6.50882304e-01
7.11454809e-01 9.70492244e-01 6.33003831e-01 -8.51028204e-01
7.90720582e-01 6.91917479e-01 -1.45255804e-01 -8.33948970e-01
-8.40780854e-01 -9.29240763e-01 -5.67710519e-01 2.87794203e-01
3.98663640e-01 -8.94279838e-01 -6.20208979e-01 1.79347083e-01
-8.23447585e-01 9.37910900e-02 -2.75406629e-01 2.14563534e-01
-9.22329605e-01 9.74765182e-01 -6.05466485e-01 -7.86959767e-01
-7.58327842e-01 -6.13010049e-01 1.16208005e+00 -1.73274145e-01
-4.49057877e-01 -9.89336252e-01 8.43670294e-02 3.79010290e-01
7.18184039e-02 1.10743523e-01 1.06195521e+00 -1.07386518e+00
-3.97843659e-01 -3.94844055e-01 1.65862683e-02 4.63171750e-01
-1.08758137e-01 4.44292240e-02 -8.50507319e-01 -5.72030365e-01
3.66960242e-02 -4.75110918e-01 1.21948946e+00 5.13596356e-01
1.72433174e+00 -8.59382868e-01 -6.73604667e-01 3.80774200e-01
1.44319570e+00 -5.16313076e-01 4.70569849e-01 -9.45917051e-03
5.93836308e-01 4.64722395e-01 5.15266657e-01 9.60082233e-01
5.05304158e-01 3.45974356e-01 1.57168135e-01 1.58047363e-01
3.26285750e-01 -1.53778389e-01 3.04980159e-01 1.34846914e+00
3.18690464e-02 -1.45409703e-01 -5.70671439e-01 9.65636790e-01
-2.15480638e+00 -1.05107570e+00 -2.24425539e-01 2.42044759e+00
1.01796901e+00 -9.10313874e-02 3.33481789e-01 4.74714279e-01
7.81704128e-01 -5.76475039e-02 -2.99468488e-01 -5.76258600e-01
-7.83827230e-02 3.34717959e-01 6.29491270e-01 2.91883409e-01
-1.05207753e+00 7.27858841e-01 7.38889360e+00 1.39206111e+00
-1.60439298e-01 1.31629258e-01 5.26725352e-01 -5.59804916e-01
-6.21656060e-01 2.03248009e-01 -7.00753331e-01 3.59027982e-01
1.08940256e+00 -5.68899632e-01 2.53663391e-01 1.11605799e+00
1.50788158e-01 -1.94391564e-01 -1.58742809e+00 9.64323103e-01
2.17568129e-01 -1.61289513e+00 1.94038391e-01 1.81463912e-01
9.48399425e-01 -1.48602203e-01 -2.29126871e-01 5.35854585e-02
8.50635171e-01 -7.63595223e-01 4.70085710e-01 -6.50951937e-02
3.94599408e-01 -9.85951483e-01 4.99149740e-01 7.41700768e-01
-1.04055178e+00 -3.03010970e-01 -8.59730184e-01 -2.85357423e-02
6.13129549e-02 7.73149073e-01 -6.16871357e-01 7.07954228e-01
7.12288380e-01 6.45451188e-01 -5.20241439e-01 1.01783788e+00
3.81148040e-01 7.86129653e-01 -7.80563831e-01 -1.28269210e-01
1.71093404e-01 -1.06748737e-01 3.05144519e-01 1.34692812e+00
4.04479206e-01 4.61883172e-02 4.09213096e-01 4.91840690e-01
-2.91516304e-01 1.56891242e-01 -5.15434206e-01 1.10962160e-01
9.02929664e-01 1.21151769e+00 -6.86115205e-01 -8.07838917e-01
-2.76240110e-01 7.72437036e-01 5.84423244e-01 6.64913654e-02
-6.03614330e-01 -4.73799914e-01 5.55635691e-01 1.14083163e-01
3.97122145e-01 -2.81442348e-02 -4.13922936e-01 -1.10340106e+00
-6.44086003e-02 -6.85522974e-01 9.96168554e-01 -2.58671343e-01
-1.56695521e+00 1.38343915e-01 4.20230865e-01 -9.86495972e-01
-2.43637830e-01 -2.82071084e-01 -5.65600455e-01 9.97910798e-02
-1.05189228e+00 -7.97303677e-01 -3.32086310e-02 5.76934159e-01
4.02050942e-01 1.45405665e-01 9.90774572e-01 -7.44021237e-02
-5.87547243e-01 7.66503036e-01 7.91197598e-01 -2.61695713e-01
5.55763662e-01 -1.50929046e+00 1.62756383e-01 9.06633794e-01
1.49681047e-01 8.57912421e-01 7.88888037e-01 -2.92707115e-01
-1.42199314e+00 -1.28428340e+00 6.36633933e-01 -4.13975090e-01
4.65200663e-01 -4.67953354e-01 -7.35820413e-01 7.36967146e-01
2.07861811e-01 -4.05522645e-01 1.14589012e+00 3.28676879e-01
-4.93625879e-01 -2.34423116e-01 -1.09105265e+00 3.90106440e-01
1.14361608e+00 -3.15138102e-02 -8.78983200e-01 7.18065739e-01
6.53799593e-01 3.08022965e-02 -9.91344690e-01 1.78518146e-01
9.91138369e-02 -8.25213253e-01 8.82942557e-01 -4.80137706e-01
2.09806070e-01 -5.39217144e-02 -3.19401205e-01 -1.09018540e+00
-4.45390195e-01 -1.04667103e+00 -6.49116933e-01 1.19601619e+00
1.43615201e-01 -3.01109701e-01 7.31722295e-01 6.88810766e-01
-2.11720213e-01 -6.26859605e-01 -7.42762864e-01 -8.97585809e-01
4.02416646e-01 -4.96378601e-01 5.90258777e-01 7.41943002e-01
5.86818635e-01 1.48260236e-01 -5.01345992e-01 7.34370351e-02
1.32274699e+00 4.20879871e-01 9.03780222e-01 -1.59265172e+00
-3.17245781e-01 -6.61361694e-01 -1.91949382e-01 -1.31417155e+00
2.47880816e-01 -1.23358119e+00 -1.65793654e-02 -1.69699788e+00
9.71859336e-01 -7.04688847e-01 -7.62862191e-02 3.50136727e-01
-3.40321153e-01 7.08643571e-02 -1.93368606e-02 3.22307348e-01
-1.22392082e+00 4.24654216e-01 4.86600041e-01 6.29758136e-03
7.02516036e-03 3.71125271e-03 -1.24289775e+00 6.97231948e-01
7.69091249e-01 -5.08987248e-01 -4.44495827e-01 -2.07021460e-01
1.82826027e-01 -5.49604058e-01 -4.28277738e-02 -7.04069912e-01
4.71999407e-01 -9.31886360e-02 -1.30590769e-02 -9.33100224e-01
-1.41249731e-01 -6.75124228e-01 -9.08945724e-02 3.10421288e-01
-6.50776267e-01 -2.64919132e-01 -3.11835594e-02 1.03622866e+00
-1.37143093e-03 -2.96160161e-01 7.69223511e-01 -1.20453008e-01
-2.20931143e-01 5.56153119e-01 -4.90944952e-01 3.84426951e-01
1.18661678e+00 -3.72887999e-01 -2.65131563e-01 -3.41427565e-01
-4.84796703e-01 7.02120960e-01 5.99881530e-01 7.84690902e-02
6.50357425e-01 -1.32575011e+00 -8.14942241e-01 -1.57055900e-01
2.61738747e-01 4.84396160e-01 2.64807045e-01 8.37689102e-01
-4.25379217e-01 4.39932704e-01 4.88430232e-01 -6.63944721e-01
-1.36603284e+00 1.05610752e+00 -2.48293757e-01 -1.86947137e-01
-8.52856338e-01 6.65242374e-01 2.57183373e-01 -2.76309043e-01
5.81840038e-01 -4.17417645e-01 3.19486111e-01 -1.23734497e-01
9.02793705e-01 7.17391789e-01 1.30858449e-02 -2.60156810e-01
-2.62637019e-01 4.21762764e-01 -4.31047827e-01 3.32821935e-01
1.71795225e+00 -3.82592231e-01 -3.95298302e-01 2.83254504e-01
1.19234347e+00 -6.91714212e-02 -7.94961035e-01 -6.72124803e-01
1.68817252e-01 -3.27507377e-01 -1.74556360e-01 -5.95875606e-02
-6.61768734e-01 6.64875329e-01 -1.50420144e-02 4.59918469e-01
1.31389320e+00 4.78111088e-01 9.08854783e-01 7.56773412e-01
4.25065547e-01 -1.54470265e+00 8.34430195e-03 1.99177951e-01
4.08530414e-01 -8.57568681e-01 3.28840971e-01 -4.52377707e-01
-4.13842440e-01 1.00698543e+00 1.25669524e-01 -3.18396866e-01
6.62114143e-01 5.03950655e-01 -6.18690968e-01 -1.42950058e-01
-1.19185519e+00 2.94693857e-02 -6.54687062e-02 6.29762471e-01
5.86180389e-02 2.67219782e-01 -3.98618162e-01 7.98815846e-01
-3.26876670e-01 -1.42828375e-01 8.83103013e-01 9.50346589e-01
-8.65275919e-01 -1.03457546e+00 -4.89794403e-01 9.43647444e-01
-4.97286409e-01 -1.12760022e-01 -4.42903608e-01 4.12434697e-01
-3.42752337e-01 1.19758213e+00 2.76256591e-01 -2.37290174e-01
-3.61174308e-02 -7.21084028e-02 4.83017832e-01 -7.94115901e-01
-3.55243504e-01 2.13226482e-01 -1.98074561e-02 -5.29410660e-01
-5.68724334e-01 -7.23851323e-01 -1.34435451e+00 -9.46235716e-01
-5.07643700e-01 3.43629718e-01 2.15454966e-01 9.06913340e-01
4.98322994e-01 3.24017294e-02 8.66955817e-01 -7.79762745e-01
-1.03002405e+00 -9.36360538e-01 -8.52386653e-01 5.13255477e-01
6.47375137e-02 -3.92429888e-01 -5.28225183e-01 1.08525939e-01] | [6.810621738433838, 5.068139553070068] |
5f009c08-8561-4386-97d0-fe92bc9b2a8b | flexible-channel-dimensions-for | 2306.08021 | null | https://arxiv.org/abs/2306.08021v1 | https://arxiv.org/pdf/2306.08021v1.pdf | Flexible Channel Dimensions for Differentiable Architecture Search | Finding optimal channel dimensions (i.e., the number of filters in DNN layers) is essential to design DNNs that perform well under computational resource constraints. Recent work in neural architecture search aims at automating the optimization of the DNN model implementation. However, existing neural architecture search methods for channel dimensions rely on fixed search spaces, which prevents achieving an efficient and fully automated solution. In this work, we propose a novel differentiable neural architecture search method with an efficient dynamic channel allocation algorithm to enable a flexible search space for channel dimensions. We show that the proposed framework is able to find DNN architectures that are equivalent to previous methods in task accuracy and inference latency for the CIFAR-10 dataset with an improvement of $1.3-1.7\times$ in GPU-hours and $1.5-1.7\times$ in the memory requirements during the architecture search stage. Moreover, the proposed frameworks do not require a well-engineered search space a priori, which is an important step towards fully automated design of DNN architectures. | ['Pascal Frossard', 'Nikolaos Dimitriadis', 'Ahmet Caner Yüzügüler'] | 2023-06-13 | null | null | null | null | ['architecture-search'] | ['methodology'] | [ 5.57452887e-02 -1.59167245e-01 4.00923267e-02 -3.44225496e-01
-4.40448970e-01 -6.46720111e-01 1.80430725e-01 -1.16493538e-01
-7.13597178e-01 5.51833868e-01 -2.76700139e-01 -6.23617887e-01
-3.01021218e-01 -8.20544362e-01 -6.23802543e-01 -5.77512145e-01
2.68598318e-01 5.56100190e-01 -7.79897021e-03 5.53825274e-02
3.89283836e-01 6.76866412e-01 -1.72848344e+00 -1.84530377e-01
5.95059097e-01 1.46711457e+00 4.50436503e-01 7.11256206e-01
-3.92641008e-01 1.01845451e-01 -5.01169443e-01 -2.22693160e-01
4.53435391e-01 -4.75619912e-01 -5.70736647e-01 -2.64907718e-01
5.80799758e-01 -1.32201448e-01 -1.14242606e-01 1.27820921e+00
6.64209664e-01 -8.76022950e-02 4.38778043e-01 -8.72320175e-01
6.00325093e-02 7.45380700e-01 7.48329014e-02 3.08515459e-01
-5.59508681e-01 2.86711147e-03 1.20975363e+00 -4.71400172e-01
3.62788409e-01 1.02829266e+00 2.45208114e-01 8.79436612e-01
-1.28861403e+00 -7.86169946e-01 2.55160123e-01 2.84552306e-01
-1.39594674e+00 -5.60940087e-01 6.24391019e-01 -4.19050425e-01
1.20225918e+00 1.03355229e-01 9.09204066e-01 7.16784656e-01
-1.52550027e-01 4.87656623e-01 6.18886769e-01 -5.48347592e-01
6.21291161e-01 -4.66719754e-02 2.07900360e-01 5.51424801e-01
5.21619856e-01 2.15940941e-02 -4.11899030e-01 1.01750856e-02
9.48913991e-01 -2.81491458e-01 1.79021079e-02 -2.92871535e-01
-8.30886245e-01 8.45984101e-01 3.92438948e-01 3.59730095e-01
-3.08046043e-01 5.90248764e-01 4.51966614e-01 2.74934024e-01
-2.24730983e-01 6.75670743e-01 -4.89232957e-01 -4.49668139e-01
-9.34008360e-01 3.58205646e-01 5.86373389e-01 8.67759347e-01
7.26819217e-01 4.05580044e-01 1.07580930e-01 6.42488241e-01
4.17678177e-01 4.82594699e-01 2.62474865e-01 -1.01101887e+00
6.38659298e-01 7.07628012e-01 -3.31966467e-02 -6.95270598e-01
-7.68518269e-01 -9.43482220e-01 -8.83585036e-01 1.71361998e-01
5.21684408e-01 -3.35210294e-01 -8.19434464e-01 1.73206675e+00
1.83835447e-01 -1.50092810e-01 1.82241410e-01 9.11704957e-01
2.96247184e-01 4.78402346e-01 -6.86130673e-02 -5.36081977e-02
1.46858478e+00 -7.76864529e-01 -5.13689458e-01 -3.95610690e-01
7.38853931e-01 -7.19459414e-01 1.02781773e+00 5.26947200e-01
-1.12319458e+00 -4.32524353e-01 -1.24855113e+00 7.23130032e-02
-7.66973644e-02 5.14367342e-01 7.68602312e-01 1.05856693e+00
-1.11863422e+00 3.42380285e-01 -7.40964830e-01 1.03348203e-01
4.71225888e-01 7.76170671e-01 2.20131949e-01 1.98242456e-01
-9.27172065e-01 5.42412460e-01 6.33232057e-01 2.82018691e-01
-8.67029071e-01 -6.99292600e-01 -3.03307325e-01 4.95416373e-01
1.81851536e-01 -5.11810243e-01 1.10828865e+00 -8.34511757e-01
-1.60765970e+00 2.38769799e-01 -1.27616450e-01 -9.64553535e-01
2.63893366e-01 -3.05576101e-02 -2.74855882e-01 -5.02752028e-02
-5.68034649e-01 9.06506956e-01 8.68028998e-01 -6.27004385e-01
-7.63111413e-01 -4.48347569e-01 1.70420885e-01 8.01272988e-02
-7.62958705e-01 -3.20258945e-01 -5.32978654e-01 -5.28783858e-01
1.29306361e-01 -1.23980594e+00 -5.79582334e-01 -9.30945501e-02
-2.29877368e-01 1.21780612e-01 3.81851166e-01 -2.59334177e-01
1.59221148e+00 -2.00936723e+00 1.48875386e-01 6.79210603e-01
1.75969884e-01 4.20231700e-01 -6.74447268e-02 -1.33683100e-01
2.92108476e-01 -2.23314995e-03 1.16798081e-01 -1.98037371e-01
2.11262748e-01 1.16216175e-01 -6.88043907e-02 1.07527472e-01
-2.67019778e-01 6.57035410e-01 -2.30684936e-01 -1.42359897e-01
4.20950688e-02 5.30026019e-01 -9.00204599e-01 -1.09701380e-01
-4.57971364e-01 2.85546422e-01 -4.23257768e-01 4.25869584e-01
5.10792673e-01 -2.75179356e-01 3.44322532e-01 -2.18937173e-01
-3.05339992e-01 3.56094390e-01 -1.13445735e+00 1.68756759e+00
-6.81056678e-01 7.63319194e-01 2.19561562e-01 -9.35811460e-01
1.24461854e+00 2.44649306e-01 3.07050914e-01 -1.00577378e+00
2.70825773e-01 7.06525862e-01 4.27602738e-01 1.49873361e-01
2.43088648e-01 2.22186074e-01 4.50950712e-02 2.41899252e-01
-2.29871254e-02 4.46430534e-01 3.94069254e-01 -5.27912080e-01
1.03188121e+00 -5.41732311e-01 -1.21269062e-01 -5.29955804e-01
7.35855222e-01 -7.48364478e-02 5.70435524e-01 6.60618007e-01
1.10632390e-01 5.86210154e-02 6.53357804e-01 -8.31156552e-01
-1.16799557e+00 -6.00213945e-01 -9.97132659e-02 8.41771126e-01
-1.38870731e-01 -2.75932252e-01 -1.20035815e+00 -1.83490604e-01
-4.48177874e-01 6.06708050e-01 -2.05300301e-01 1.64309442e-01
-8.19571376e-01 -6.34516180e-01 6.85753167e-01 4.94103253e-01
5.41067779e-01 -7.90263712e-01 -1.37609518e+00 4.57231194e-01
2.39290580e-01 -1.09006834e+00 -1.58006221e-01 4.42338109e-01
-1.20053458e+00 -7.21762121e-01 -7.56582975e-01 -7.17703462e-01
7.17145205e-01 -3.24606985e-01 9.08751845e-01 4.13055569e-02
-4.56170052e-01 -2.13685319e-01 2.38829688e-03 -3.59579146e-01
-2.26566643e-01 7.04491854e-01 -8.50814488e-03 -1.36561632e-01
2.86408305e-01 -5.96401751e-01 -8.89763653e-01 2.71474540e-01
-5.86644053e-01 9.72938910e-02 8.47471416e-01 7.25360453e-01
9.06529427e-01 2.13844240e-01 5.36907971e-01 -6.71090961e-01
5.61594427e-01 1.61955524e-02 -1.50819528e+00 2.61892706e-01
-1.05567586e+00 6.74897254e-01 8.31461847e-01 -2.43588880e-01
-6.12706780e-01 6.02809429e-01 -4.38044965e-01 -3.50610256e-01
-1.29696876e-01 2.24493027e-01 -2.01993957e-01 -2.37428114e-01
5.58334053e-01 1.78324327e-01 -2.93652028e-01 -6.43317103e-01
1.77567586e-01 2.22994506e-01 1.91078529e-01 -4.13890302e-01
4.19809073e-01 1.66423261e-01 3.50819230e-01 -7.66731501e-01
-3.08864206e-01 -1.69349045e-01 -3.96203011e-01 4.57463004e-02
8.72649372e-01 -7.30432928e-01 -9.47013021e-01 1.64498031e-01
-1.10235238e+00 -2.51372278e-01 5.76028898e-02 6.28550828e-01
-4.93393093e-01 -5.11861704e-02 -2.12936193e-01 -7.66547501e-01
-8.62869561e-01 -1.64321041e+00 7.00007141e-01 2.46826142e-01
-1.65705428e-01 -7.27342010e-01 -2.24083886e-01 1.32908762e-01
7.42646992e-01 -2.84897625e-01 1.30263638e+00 -5.01502156e-01
-9.22446489e-01 1.27302095e-01 -2.62146413e-01 2.08903447e-01
-5.20933211e-01 -4.45554107e-01 -6.79678082e-01 -2.18028873e-01
-2.60761112e-01 5.72619475e-02 7.08703279e-01 6.74243987e-01
1.30020022e+00 -4.22813565e-01 -1.80605754e-01 7.63425887e-01
1.74051988e+00 7.41893530e-01 5.85707903e-01 3.83261800e-01
4.73043203e-01 2.78966486e-01 3.95762324e-01 6.79355383e-01
-1.25935739e-02 8.72936189e-01 6.44822299e-01 1.21736832e-01
1.21434972e-01 1.01887211e-01 2.92305406e-02 5.30553997e-01
-5.00159618e-03 -3.02307993e-01 -1.00949609e+00 5.83423436e-01
-1.69304311e+00 -4.94487524e-01 1.43065736e-01 2.18526649e+00
5.14969349e-01 4.17720854e-01 6.97026178e-02 2.88379818e-01
5.34939647e-01 -1.42309904e-01 -8.48027945e-01 -7.54012346e-01
1.78180695e-01 4.43876207e-01 8.13572228e-01 4.13468897e-01
-8.66442978e-01 8.83421838e-01 5.65595341e+00 8.00469041e-01
-1.18019915e+00 -1.95629299e-01 4.96716857e-01 -4.83971417e-01
-3.03074539e-01 -3.57731543e-02 -1.35638094e+00 3.57264996e-01
1.20803463e+00 2.01882645e-01 6.84776247e-01 1.13761032e+00
-1.97723322e-03 3.72855633e-01 -1.09670377e+00 1.62635434e+00
-3.91587168e-01 -1.83277559e+00 2.20447616e-03 3.84431779e-01
5.34840465e-01 1.01521090e-02 1.33498386e-01 -9.01625603e-02
-3.23241830e-01 -1.07730353e+00 8.87763739e-01 2.46423244e-01
5.62907398e-01 -1.13517296e+00 6.47823155e-01 2.21096784e-01
-1.22426224e+00 -4.79250759e-01 -3.94435644e-01 9.58961770e-02
2.11965501e-01 5.11188209e-01 -8.33774447e-01 -2.06266955e-01
7.41362691e-01 4.95617315e-02 -4.15539026e-01 1.14953160e+00
1.22897357e-01 3.47084194e-01 -4.30081457e-01 -5.78316092e-01
5.09508312e-01 -1.63721174e-01 3.33318114e-01 1.01893628e+00
6.53749108e-01 -8.73225927e-02 -2.56378859e-01 8.96702468e-01
-1.36942342e-01 1.24121577e-01 -1.81635454e-01 -3.39980513e-01
6.77802622e-01 9.97080922e-01 -9.03694868e-01 5.53097241e-02
-2.11600170e-01 6.53542161e-01 1.93818212e-01 1.92058459e-01
-9.21207309e-01 -3.73370886e-01 8.24048042e-01 9.25777406e-02
6.67175710e-01 -3.41701508e-01 -6.01689398e-01 -5.86364686e-01
8.46479386e-02 -7.13776648e-01 9.11410302e-02 -7.13622570e-02
-6.28195703e-01 1.01428211e+00 -3.81805837e-01 -9.98055458e-01
-3.76726300e-01 -8.02125573e-01 -6.59959465e-02 6.15567803e-01
-1.38721287e+00 -5.94858706e-01 7.55356252e-03 4.94505018e-01
5.57909787e-01 -4.87639874e-01 7.99823225e-01 6.74414396e-01
-6.34896874e-01 9.69260097e-01 3.14185955e-02 -1.80956617e-01
1.66100357e-02 -9.31670308e-01 5.22199214e-01 8.44256938e-01
2.81309068e-01 6.39011681e-01 6.01537526e-01 -1.17995456e-01
-1.63869095e+00 -8.56113613e-01 7.06481874e-01 3.14642698e-01
3.45429450e-01 -5.67374587e-01 -4.36109066e-01 1.46606624e-01
-5.31008393e-02 -2.99292475e-01 5.69022596e-01 1.20846026e-01
-9.36772898e-02 -4.49845284e-01 -7.72190690e-01 7.14210570e-01
1.14135039e+00 -5.60745709e-02 2.03808933e-01 -9.53529496e-03
5.59138656e-01 -4.10722822e-01 -7.17376828e-01 2.55885571e-01
7.06624091e-01 -7.85263062e-01 9.49664176e-01 -1.41576171e-01
-1.29316762e-01 -2.41433099e-01 -4.20973212e-01 -7.18987882e-01
-9.96575207e-02 -7.31330931e-01 -2.24816546e-01 8.82221043e-01
9.15748954e-01 -6.59985542e-01 1.14467990e+00 7.16752112e-01
-1.67546526e-01 -9.44023907e-01 -1.27332318e+00 -6.73387170e-01
-1.58488214e-01 -6.29550397e-01 7.27277458e-01 1.83268234e-01
-6.86964810e-01 4.22784746e-01 -1.27169237e-01 1.35293782e-01
6.90252244e-01 1.49433032e-01 4.49201018e-01 -1.37536025e+00
-4.59425658e-01 -9.84133005e-01 -4.93565261e-01 -1.29528785e+00
1.13020532e-01 -4.96127009e-01 -2.70316422e-01 -1.27662122e+00
-2.92739630e-01 -9.59814250e-01 -2.97079861e-01 3.19875211e-01
5.66050768e-01 -1.58112675e-01 1.87955275e-01 2.26929113e-02
-3.03874403e-01 3.22872102e-01 7.30217755e-01 5.18727601e-02
-3.39256138e-01 1.44921541e-01 -5.09841681e-01 6.05727851e-01
1.10496581e+00 -3.11151564e-01 -8.05779219e-01 -9.07386541e-01
5.53500414e-01 -5.69010042e-02 1.77014023e-01 -1.28812897e+00
4.09539253e-01 1.68844521e-01 2.23821476e-01 -7.63447583e-01
4.29506987e-01 -1.04187441e+00 3.51475507e-01 6.83553517e-01
-4.77286726e-01 2.22772077e-01 2.74504781e-01 4.78823841e-01
-1.07157357e-01 -6.26080096e-01 7.16614962e-01 -8.25400949e-02
-9.29196596e-01 2.44945496e-01 -2.94682473e-01 -1.50701851e-01
8.19047093e-01 -2.99918622e-01 -5.44647686e-02 6.96689337e-02
-6.10430658e-01 1.40907392e-01 2.00299487e-01 2.65029848e-01
5.20921826e-01 -1.09336150e+00 -1.92487508e-01 2.72583932e-01
-3.17483664e-01 -9.54766851e-03 3.17679971e-01 5.16813755e-01
-9.71270740e-01 1.06675231e+00 -3.73666167e-01 -5.67119360e-01
-1.23435116e+00 3.43052089e-01 4.44737405e-01 -3.89106601e-01
-3.84524971e-01 1.03506899e+00 -1.33096837e-02 1.59054585e-02
5.45839548e-01 -5.18186867e-01 -9.06371698e-02 -5.36570325e-02
5.28890789e-01 5.35974562e-01 3.63930970e-01 -2.09403664e-01
-4.51632529e-01 7.14933991e-01 -2.22182684e-02 -2.27439344e-01
1.16660202e+00 -6.78213388e-02 -3.36907804e-02 -1.21431261e-01
1.11502087e+00 -3.77328813e-01 -1.25684166e+00 3.56555693e-02
2.15671644e-01 -5.60538732e-02 6.04537368e-01 -6.33071959e-01
-1.39378345e+00 1.09342837e+00 1.10383260e+00 -1.48812801e-01
1.49030566e+00 -1.69801682e-01 1.00327325e+00 6.76640570e-01
4.83415574e-01 -1.34051287e+00 -2.28939384e-01 5.65395236e-01
5.19032776e-01 -7.03277886e-01 -2.21664488e-01 -1.09808557e-01
-3.30342501e-01 1.28336287e+00 6.89877510e-01 1.80774972e-01
6.01433039e-01 4.02586073e-01 -1.34523094e-01 -2.49069110e-01
-7.69105911e-01 -1.46038383e-01 1.72691777e-01 1.58314183e-01
2.33690277e-01 9.52162892e-02 -4.01854962e-01 5.26481330e-01
-3.00339311e-01 -3.67568463e-01 -5.55221513e-02 5.02071083e-01
-6.20678484e-01 -1.40728462e+00 -1.14835516e-01 2.93899864e-01
-3.50079447e-01 -2.73617685e-01 -1.83895648e-01 4.88612026e-01
1.66864231e-01 5.88345230e-01 2.08157286e-01 -3.66413862e-01
2.63858527e-01 2.82508098e-02 4.93370533e-01 -2.72065967e-01
-4.78915215e-01 3.49397242e-01 7.27383569e-02 -5.72591841e-01
-8.41749310e-02 -3.54422390e-01 -1.53686941e+00 6.75596436e-03
-3.75045419e-01 6.78029135e-02 1.14800537e+00 7.21431434e-01
6.66872263e-01 4.78731304e-01 2.11803719e-01 -5.13613582e-01
-4.62530941e-01 -4.08497602e-01 -3.21001679e-01 -4.51497585e-01
8.14574212e-02 -5.63608050e-01 5.62458634e-02 -2.37098962e-01] | [8.462272644042969, 3.104220390319824] |
10be9c2b-19e6-4c36-8cb5-031091227740 | a-cnn-transformer-deep-learning-model-for | 2211.13005 | null | https://arxiv.org/abs/2211.13005v1 | https://arxiv.org/pdf/2211.13005v1.pdf | A CNN-Transformer Deep Learning Model for Real-time Sleep Stage Classification in an Energy-Constrained Wireless Device | This paper proposes a deep learning (DL) model for automatic sleep stage classification based on single-channel EEG data. The DL model features a convolutional neural network (CNN) and transformers. The model was designed to run on energy and memory-constrained devices for real-time operation with local processing. The Fpz-Cz EEG signals from a publicly available Sleep-EDF dataset are used to train and test the model. Four convolutional filter layers were used to extract features and reduce the data dimension. Then, transformers were utilized to learn the time-variant features of the data. To improve performance, we also implemented a subject specific training before the inference (i.e., prediction) stage. With the subject specific training, the F1 score was 0.91, 0.37, 0.84, 0.877, and 0.73 for wake, N1-N3, and rapid eye movement (REM) stages, respectively. The performance of the model was comparable to the state-of-the-art works with significantly greater computational costs. We tested a reduced-sized version of the proposed model on a low-cost Arduino Nano 33 BLE board and it was fully functional and accurate. In the future, a fully integrated wireless EEG sensor with edge DL will be developed for sleep research in pre-clinical and clinical experiments, such as real-time sleep modulation. | ['Xilin Liu', 'Zongyan Yao'] | 2022-11-20 | null | null | null | null | ['automatic-sleep-stage-classification'] | ['medical'] | [-2.55871832e-01 -3.38227659e-01 1.09086268e-01 -5.24475873e-01
-1.22739293e-01 -8.74751732e-02 -2.92306572e-01 -1.31308630e-01
-7.32626319e-01 9.15023565e-01 -2.43586704e-01 -2.51565963e-01
-3.56522501e-02 -6.03009760e-01 -3.54148477e-01 -6.47739887e-01
-3.52042615e-01 -1.60375997e-01 1.85283899e-01 1.37227625e-02
-2.76643168e-02 3.13572973e-01 -1.52040505e+00 2.03371421e-01
8.34690154e-01 1.47841883e+00 4.81830776e-01 3.77765357e-01
5.54134846e-01 4.48361456e-01 -7.61328638e-01 1.50773823e-01
1.61589589e-02 -3.39416713e-01 -2.54558533e-01 -4.19512898e-01
-3.58419657e-01 -2.61851907e-01 -3.86550099e-01 9.99593198e-01
1.01637340e+00 -5.13899028e-02 7.21561909e-02 -1.06066751e+00
-1.75343186e-01 3.28399509e-01 -1.96057752e-01 8.98465872e-01
1.79636985e-01 2.71624792e-03 2.71184891e-01 -7.77560115e-01
-8.46007019e-02 2.97428161e-01 7.78956473e-01 5.57540357e-01
-8.92980993e-01 -1.43139803e+00 -4.41394657e-01 5.84305704e-01
-1.67558014e+00 -5.60772061e-01 7.34063268e-01 -1.15783177e-01
1.48286223e+00 1.60256684e-01 1.34317040e+00 1.05718017e+00
1.11704767e+00 3.22283357e-01 1.39249730e+00 -3.27560939e-02
5.09090006e-01 1.08781114e-01 3.49681884e-01 6.12162590e-01
2.36475840e-01 -4.92580459e-02 -8.13639760e-01 1.76125273e-01
5.72605968e-01 2.57193327e-01 -4.01626438e-01 5.52418351e-01
-7.81553984e-01 4.92269307e-01 5.28550029e-01 4.11862046e-01
-5.91757476e-01 -1.11542918e-01 3.82416904e-01 1.72269568e-01
5.64981043e-01 3.12809736e-01 -7.35527277e-01 -5.31285286e-01
-1.39533854e+00 -3.02675575e-01 6.64864302e-01 7.96209455e-01
5.25992095e-01 1.85991839e-01 -1.72020346e-01 6.98203206e-01
3.21702987e-01 4.25164163e-01 1.13589597e+00 -3.57800037e-01
6.59526438e-02 6.27801001e-01 -1.71956494e-01 -4.42640305e-01
-1.21969306e+00 -5.57451487e-01 -1.08356166e+00 -1.31703183e-01
-2.62853861e-01 -2.74470717e-01 -8.60422552e-01 1.48621845e+00
-3.69129956e-01 5.33346534e-01 -1.09961405e-01 8.89725149e-01
1.05051959e+00 4.09656823e-01 -1.60449550e-01 -3.96087557e-01
1.65428913e+00 -5.96824348e-01 -1.11776352e+00 -3.96072656e-01
1.33368611e-01 -3.54178160e-01 1.02489614e+00 6.58356249e-01
-1.08697581e+00 -6.89548612e-01 -1.47156549e+00 -3.72764911e-03
-2.27515608e-01 5.85542262e-01 7.11380184e-01 8.29710901e-01
-1.28838527e+00 5.18770337e-01 -1.45616329e+00 -1.57016993e-01
6.63436472e-01 1.08496737e+00 -2.13963971e-01 5.09667337e-01
-1.19265759e+00 8.27447534e-01 1.49286091e-01 3.91852468e-01
-9.16895449e-01 -4.48682815e-01 -4.31115389e-01 3.03503752e-01
-4.24729437e-01 -5.47475398e-01 1.00260830e+00 -7.93374479e-01
-1.75339043e+00 7.63215542e-01 -3.96929979e-01 -6.00361049e-01
-3.01265895e-01 -1.65510923e-01 -9.80751514e-01 6.36225715e-02
-1.40342638e-01 2.97177583e-01 6.76809788e-01 -1.58461303e-01
-3.60481471e-01 -6.21787190e-01 -3.71109061e-02 -2.06039369e-01
-4.17461962e-01 1.26406968e-01 -1.28055528e-01 -4.32422847e-01
-7.59176165e-02 -8.54997873e-01 2.75167465e-01 -2.97979355e-01
-9.89716426e-02 -1.56738147e-01 4.92182583e-01 -6.41833305e-01
1.34277499e+00 -2.33136725e+00 -2.55920678e-01 -2.85186153e-02
3.66151959e-01 3.43889773e-01 3.47375661e-01 -5.35784364e-02
-2.43613437e-01 -2.78396070e-01 1.74766928e-01 -3.88947994e-01
-3.23430270e-01 -6.80882931e-02 2.43458450e-01 7.41956532e-01
-1.10967070e-01 8.73941839e-01 -4.07935560e-01 1.03645986e-02
2.40501761e-01 5.02999246e-01 -4.97123003e-01 4.28800881e-01
6.36574924e-01 2.71987051e-01 -1.22134127e-02 6.19189978e-01
6.24239445e-01 -1.85215950e-01 -2.29162127e-01 -5.00414371e-01
-2.99185336e-01 6.14804327e-01 -7.90425718e-01 1.90872431e+00
-7.05998838e-01 1.05491602e+00 -2.03572516e-03 -9.25074279e-01
8.02656591e-01 4.91681784e-01 4.05137628e-01 -1.09186697e+00
7.29429722e-01 1.65588781e-01 3.78091991e-01 -8.16229284e-01
2.16872357e-02 -1.90824881e-01 3.38273942e-01 2.79799968e-01
3.97238761e-01 3.47743511e-01 -2.32197404e-01 -3.21479946e-01
1.22765183e+00 -3.15594405e-01 2.95978189e-01 -7.69446671e-01
3.04600269e-01 -5.02737701e-01 6.68245792e-01 2.25870326e-01
-2.49232516e-01 2.75457680e-01 8.00699443e-02 -4.49045002e-01
-3.50582778e-01 -9.44791555e-01 -5.82593441e-01 5.18238485e-01
2.62873411e-01 -7.91771293e-01 -9.03050184e-01 -8.82970691e-02
-5.60787916e-01 5.82712710e-01 -3.70084614e-01 -6.82354808e-01
-1.82954207e-01 -1.13619781e+00 4.28774416e-01 6.84071004e-01
9.06643510e-01 -1.20272326e+00 -1.23811829e+00 4.06914890e-01
1.10802427e-02 -1.06217957e+00 -1.21086866e-01 8.95807445e-01
-1.00734091e+00 -9.00174201e-01 -1.92252547e-01 -7.94798017e-01
4.75671440e-01 -1.61285028e-01 7.07171619e-01 -9.86700952e-02
-3.58425111e-01 -2.17131808e-01 -2.07939073e-01 -7.62015343e-01
6.20283961e-01 -4.96040732e-02 5.48380017e-01 -7.32090101e-02
8.28930736e-01 -9.94869709e-01 -1.14479756e+00 1.46137238e-01
-3.92957181e-01 3.91171388e-02 6.76389813e-01 7.36096978e-01
6.30236447e-01 3.95667076e-01 6.68953240e-01 -3.14110875e-01
8.20634305e-01 -3.95684540e-01 -4.63046074e-01 -1.17500685e-01
-8.28750432e-01 -1.33345038e-01 8.51705253e-01 -4.69007492e-01
-6.56611741e-01 -8.11696127e-02 -5.00791073e-01 -2.15163246e-01
4.40948308e-02 2.66893655e-01 -1.98785573e-01 -6.22954257e-02
4.13925976e-01 3.47939759e-01 -3.51500154e-01 -3.99833083e-01
-6.40109718e-01 1.21110594e+00 4.92610246e-01 1.13037959e-01
1.07475080e-01 1.24434233e-01 -2.39458457e-01 -9.58715796e-01
-5.51616728e-01 -2.67786652e-01 -2.81550318e-01 -1.39024919e-02
1.02909040e+00 -1.48064911e+00 -8.90023410e-01 7.32309163e-01
-8.44126940e-01 -5.97395122e-01 3.84049453e-02 9.70279455e-01
-2.34909222e-01 -2.19092205e-01 -6.46503270e-01 -6.10007942e-01
-1.21965647e+00 -1.20330405e+00 7.69368470e-01 6.71014309e-01
-2.45561808e-01 -6.19522214e-01 -3.66533957e-02 -3.25173400e-02
6.29300177e-01 -2.90856808e-01 5.14230907e-01 -5.12050748e-01
-2.54136343e-02 -2.03236163e-01 1.36831447e-01 5.29796720e-01
2.08067447e-01 -4.63423550e-01 -1.35191870e+00 -4.57426459e-01
7.57871449e-01 -1.42228171e-01 3.59497190e-01 7.01189101e-01
1.68334925e+00 -3.69600318e-02 -3.58795434e-01 1.11257994e+00
1.32647896e+00 5.86865902e-01 1.00433540e+00 1.55166388e-01
1.75211102e-01 -3.37994903e-01 9.11468863e-02 5.38595498e-01
5.02355993e-01 4.64535326e-01 2.47154966e-01 -1.29677773e-01
3.98644060e-02 2.72015452e-01 5.22174597e-01 9.95840490e-01
-9.56314132e-02 -8.74930546e-02 -6.90544426e-01 3.17666769e-01
-1.22729492e+00 -5.47121942e-01 -1.54769242e-01 1.98316538e+00
7.26014078e-01 3.96300077e-01 -1.05890371e-01 3.57269466e-01
2.68772960e-01 -4.57835734e-01 -6.50310874e-01 -3.76214325e-01
1.72303289e-01 1.26032364e+00 3.43198419e-01 -1.43615589e-01
-7.58416593e-01 4.96485710e-01 5.73332930e+00 4.54087168e-01
-1.58609104e+00 5.82707524e-01 2.12671235e-01 -5.58718562e-01
4.93900061e-01 -4.57851827e-01 -7.22880423e-01 1.16174686e+00
1.75111461e+00 -6.89034462e-02 8.02543342e-01 6.87237978e-01
5.75111330e-01 -3.89131606e-01 -9.60880041e-01 1.58504093e+00
-7.96370059e-02 -1.05763829e+00 -8.89794052e-01 -1.14358351e-01
2.42388219e-01 4.55705315e-01 -2.89645702e-01 3.78072798e-01
-6.84361398e-01 -1.12343955e+00 6.00236833e-01 6.42123282e-01
1.14374077e+00 -8.87686312e-01 1.17067599e+00 5.14064252e-01
-1.20328951e+00 -3.29146951e-01 -5.16544342e-01 -5.53969920e-01
-2.24936575e-01 8.40211809e-01 -2.42586389e-01 1.65172473e-01
1.28861094e+00 8.90366435e-01 -8.62472653e-01 1.08890772e+00
-3.30008000e-01 9.04235303e-01 -4.35663462e-01 -2.45967895e-01
-2.94157684e-01 1.63474921e-02 -1.66608095e-01 9.70153570e-01
5.73849976e-01 4.68051612e-01 -4.81547892e-01 7.81837285e-01
-1.06915735e-01 -4.37227786e-01 -8.56456682e-02 1.56132847e-01
4.19993609e-01 1.60597491e+00 -7.51400650e-01 -3.26664187e-02
-3.14804882e-01 1.00144553e+00 1.06598653e-01 1.09476790e-01
-9.87974465e-01 -7.66218662e-01 5.90267420e-01 7.59623349e-02
-1.47699460e-01 -2.04848051e-01 -6.01263165e-01 -1.40658116e+00
1.31852001e-01 -3.98222059e-01 -1.65048286e-01 -1.03466475e+00
-9.74647701e-01 1.08561802e+00 -2.17150211e-01 -1.03565681e+00
1.57812893e-01 -6.65304065e-01 -9.36311424e-01 9.84784484e-01
-1.34627068e+00 -4.17631805e-01 -6.82040751e-01 1.00233710e+00
3.98540199e-01 -2.49272317e-01 1.11860168e+00 6.37301445e-01
-9.72130120e-01 7.27654397e-01 -8.18767026e-02 -8.06120634e-02
4.97892112e-01 -8.69455695e-01 1.12240389e-01 8.57278705e-01
-2.33101055e-01 8.82410824e-01 1.83082655e-01 -2.30889022e-01
-1.41480339e+00 -1.07334006e+00 7.47435570e-01 1.68195590e-02
3.19254369e-01 -9.11011159e-01 -6.10147893e-01 5.41187823e-01
4.58212346e-01 1.62277997e-01 9.31979001e-01 -1.79065213e-01
6.24098063e-01 -6.74320519e-01 -1.27190173e+00 1.45148873e-01
8.63547921e-01 -5.19036055e-01 -6.06217623e-01 1.44986883e-01
1.22100048e-01 -4.81205612e-01 -9.02808011e-01 2.17568129e-01
7.04983354e-01 -1.01957846e+00 4.88202780e-01 9.81964171e-02
-8.65019783e-02 -9.96849239e-02 7.20141903e-02 -1.46319520e+00
-4.77119327e-01 -6.05193317e-01 -4.05264229e-01 8.89679790e-01
1.53747544e-01 -7.70893335e-01 5.04551172e-01 3.32545906e-01
-6.65980875e-01 -1.16675842e+00 -1.14271247e+00 -6.21782422e-01
-4.83233303e-01 -4.63481605e-01 6.68413639e-01 1.16107874e-01
3.39951277e-01 5.88892460e-01 -5.94288632e-02 2.28198141e-01
6.69882745e-02 -1.76985040e-01 -1.71961784e-02 -1.20896971e+00
1.24769956e-01 4.15794291e-02 -6.28889859e-01 -7.41010964e-01
1.33964643e-01 -9.40863729e-01 -4.61784862e-02 -1.49101090e+00
1.85492039e-01 -2.43444696e-01 -8.45682800e-01 6.32800877e-01
-6.35986682e-03 5.42143583e-01 -4.16269213e-01 -1.06641918e-01
-3.62575412e-01 5.85582972e-01 6.34593785e-01 9.28910449e-02
-2.94262171e-01 2.36208871e-01 -5.19875467e-01 6.24943733e-01
1.29236293e+00 -6.74230158e-01 -6.82289064e-01 -3.29318255e-01
7.67127946e-02 -8.72025713e-02 2.96476215e-01 -1.79090631e+00
4.87521440e-01 5.56331336e-01 1.00118089e+00 -5.06834805e-01
5.00134706e-01 -9.55698311e-01 3.16278219e-01 6.46926582e-01
1.71685591e-01 3.33379477e-01 4.51662213e-01 1.30248424e-02
7.80797452e-02 1.56060383e-01 8.50597382e-01 2.16414690e-01
-5.01196265e-01 3.93956006e-01 -6.24033511e-01 -2.08541453e-01
1.08981073e+00 -2.96453983e-01 -2.79281467e-01 9.95173827e-02
-6.13705277e-01 2.49064229e-02 8.61201212e-02 2.28789747e-01
8.95656765e-01 -1.20199847e+00 -1.71140715e-01 1.06198645e+00
-6.87609762e-02 -2.24224880e-01 3.97031784e-01 1.28720498e+00
-3.44689608e-01 5.33386409e-01 -7.75322855e-01 -5.55434585e-01
-1.02904773e+00 1.65361121e-01 6.92624211e-01 1.36372879e-01
-7.25346684e-01 8.36652875e-01 -3.87139559e-01 2.58433670e-01
2.08606869e-01 -7.58402050e-01 -2.07891256e-01 -3.04029807e-02
7.50543773e-01 3.39188069e-01 8.79524529e-01 -1.48446575e-01
-1.02422428e+00 3.67043257e-01 2.83073097e-01 2.22979799e-01
1.65482259e+00 3.04804295e-02 -2.68495053e-01 5.10936439e-01
1.14068127e+00 -3.07851195e-01 -9.94509459e-01 4.30671811e-01
-4.64972973e-01 1.55853808e-01 5.70308506e-01 -9.40579057e-01
-1.49942076e+00 1.07035124e+00 1.47663820e+00 -7.98696056e-02
1.85170078e+00 -3.19087565e-01 9.81644332e-01 3.10358733e-01
6.33587122e-01 -1.02756119e+00 -2.37774730e-01 2.64164120e-01
5.18015325e-01 -8.86646271e-01 6.88354522e-02 3.63820702e-01
-2.76708931e-01 1.30775046e+00 7.35290587e-01 -4.27253813e-01
1.18450797e+00 8.08723032e-01 -2.39654705e-01 -4.77528840e-01
-7.38606155e-01 1.67101324e-01 3.50622505e-01 4.59856719e-01
4.81565863e-01 2.28342697e-01 -5.00592470e-01 1.55514538e+00
-5.97287536e-01 7.13428497e-01 4.59645808e-01 7.58326292e-01
-1.57617882e-01 -5.57973623e-01 1.22629501e-01 9.81667817e-01
-8.06614101e-01 -2.35736772e-01 1.59090161e-01 4.94078398e-01
5.30644715e-01 1.28599453e+00 2.85548359e-01 -1.03211570e+00
3.52902234e-01 1.01708040e-01 5.26279390e-01 -6.81885302e-01
-8.80790472e-01 -5.47534823e-02 -2.75483429e-01 -8.92637372e-01
-3.72907251e-01 -2.30897084e-01 -1.47530234e+00 -1.58193141e-01
-4.00519252e-01 1.20047048e-01 8.29410970e-01 9.07963395e-01
7.07478583e-01 1.02916062e+00 4.64650840e-01 -8.19811642e-01
1.08477972e-01 -1.30420828e+00 -9.51758862e-01 -3.13771397e-01
4.14920390e-01 -7.99339592e-01 -2.48133615e-01 -1.75902784e-01] | [13.475996017456055, 3.5056540966033936] |
b92fdb20-1391-431d-9147-d9844aa39e81 | make-your-video-customized-video-generation | 2306.00943 | null | https://arxiv.org/abs/2306.00943v1 | https://arxiv.org/pdf/2306.00943v1.pdf | Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance | Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While text is convenient in conveying the overall scene context, it may be insufficient to control precisely. In this paper, we explore customized video generation by utilizing text as context description and motion structure (e.g. frame-wise depth) as concrete guidance. Our method, dubbed Make-Your-Video, involves joint-conditional video generation using a Latent Diffusion Model that is pre-trained for still image synthesis and then promoted for video generation with the introduction of temporal modules. This two-stage learning scheme not only reduces the computing resources required, but also improves the performance by transferring the rich concepts available in image datasets solely into video generation. Moreover, we use a simple yet effective causal attention mask strategy to enable longer video synthesis, which mitigates the potential quality degradation effectively. Experimental results show the superiority of our method over existing baselines, particularly in terms of temporal coherence and fidelity to users' guidance. In addition, our model enables several intriguing applications that demonstrate potential for practical usage. | ['Tien-Tsin Wong', 'Ying Shan', 'Xintao Wang', 'Xiaodong Cun', 'Haoxin Chen', 'Hanyuan Liu', 'Yingqing He', 'Yong Zhang', 'Yuechen Zhang', 'Yuxin Liu', 'Menghan Xia', 'Jinbo Xing'] | 2023-06-01 | null | null | null | null | ['video-generation'] | ['computer-vision'] | [ 4.66443181e-01 -9.84533429e-02 -1.53616369e-01 -2.79520243e-01
-7.79830039e-01 -4.09400553e-01 9.18876946e-01 -2.93912262e-01
-7.07165748e-02 7.48296797e-01 6.94162190e-01 -1.48355499e-01
3.25550050e-01 -6.15117788e-01 -6.34073734e-01 -7.30918765e-01
3.13178688e-01 -1.64499655e-01 1.46040931e-01 -1.79826230e-01
3.86237830e-01 1.60482600e-01 -1.54509985e+00 5.37818849e-01
9.45815384e-01 8.51444900e-01 6.98400021e-01 7.21373200e-01
-6.67258427e-02 1.25817382e+00 -5.47305882e-01 -3.80394787e-01
7.07867071e-02 -7.00817645e-01 -5.16391098e-01 4.76240158e-01
5.53202093e-01 -9.42348301e-01 -5.28256059e-01 5.81163049e-01
5.02614677e-01 2.42570564e-01 3.35965723e-01 -1.03570652e+00
-7.18970358e-01 3.55488002e-01 -6.40230596e-01 1.52883336e-01
6.72006607e-01 5.80123365e-01 8.97690475e-01 -8.47619891e-01
7.55338609e-01 1.27064383e+00 1.39217347e-01 7.44399130e-01
-1.18637395e+00 -6.67042315e-01 4.43856180e-01 2.82608837e-01
-1.09464538e+00 -7.94840276e-01 7.74884701e-01 -4.73239571e-01
8.73425663e-01 2.15652809e-01 7.08947659e-01 1.45630908e+00
2.04591155e-01 8.80423784e-01 7.59945214e-01 -2.55015999e-01
6.61328360e-02 -1.43180907e-01 -6.29978538e-01 5.91561258e-01
-1.66507110e-01 1.05580732e-01 -9.06416059e-01 2.29819134e-01
1.22822940e+00 -1.77644882e-02 -6.01373792e-01 -1.61455140e-01
-1.49339676e+00 6.78407133e-01 1.26856908e-01 -3.56849749e-03
-5.46273768e-01 4.89528447e-01 2.28601173e-01 6.76917955e-02
6.33532465e-01 3.58430713e-01 5.72489202e-02 -3.92129332e-01
-1.28906274e+00 3.72848272e-01 3.84075910e-01 1.09449387e+00
4.15356219e-01 4.19814318e-01 -6.04307413e-01 6.56896651e-01
1.04757100e-01 3.06819409e-01 3.49497825e-01 -1.40097535e+00
6.02940261e-01 1.39482796e-01 5.08396506e-01 -1.06377101e+00
8.05473477e-02 -1.20387517e-01 -5.70509493e-01 8.84358957e-02
1.55152887e-01 -2.46324435e-01 -9.19807732e-01 1.88728678e+00
7.18015432e-02 5.38897932e-01 -2.28627935e-01 1.05391788e+00
6.70856833e-01 1.02636087e+00 2.10113987e-01 -4.40902025e-01
1.14437401e+00 -1.26839375e+00 -1.05617118e+00 -2.83492565e-01
3.19634169e-01 -8.48356605e-01 1.17711198e+00 3.38177323e-01
-1.40829003e+00 -5.77043831e-01 -9.63293076e-01 -3.16986263e-01
2.39893481e-01 -2.17066053e-02 7.61501491e-01 3.24617147e-01
-1.31088793e+00 5.46004117e-01 -8.28235090e-01 -2.11484879e-01
4.00014728e-01 4.45355587e-02 -2.16194615e-01 -3.01363289e-01
-1.09676540e+00 5.17341137e-01 1.89573169e-01 1.40431244e-02
-1.00898004e+00 -6.37686491e-01 -9.27181900e-01 5.10867387e-02
5.06410420e-01 -1.06556618e+00 1.39675975e+00 -1.04114306e+00
-1.80596328e+00 3.10451746e-01 -3.98168147e-01 -2.42114261e-01
7.13031888e-01 -3.82134408e-01 -2.10061952e-01 5.93306839e-01
2.15126663e-01 1.40893006e+00 1.25213122e+00 -1.26156116e+00
-6.66099727e-01 3.46202970e-01 2.89077461e-01 5.06582022e-01
-4.16742682e-01 -5.58209680e-02 -8.80501091e-01 -1.05815554e+00
-8.97084475e-02 -7.18002319e-01 -3.33863854e-01 2.54134864e-01
-9.91638526e-02 5.82691804e-02 7.91458309e-01 -8.00065160e-01
1.49608433e+00 -2.12729168e+00 2.11927682e-01 -3.40564340e-01
2.55825937e-01 -2.08974406e-02 -2.77848959e-01 5.99741042e-01
1.47326672e-02 1.51057303e-01 -1.76828891e-01 -5.44236839e-01
-2.70732284e-01 3.72495763e-02 -5.36044121e-01 1.06496647e-01
4.10926074e-01 1.08581913e+00 -1.17201364e+00 -5.72412133e-01
4.19060439e-01 7.04379499e-01 -8.28612506e-01 3.98047566e-01
-5.19746542e-01 7.86860347e-01 -3.20993304e-01 3.82907212e-01
3.94565314e-01 -4.85450745e-01 1.43612698e-01 -2.80155838e-01
-1.93578079e-01 4.56970096e-01 -7.71178961e-01 2.05435562e+00
-6.00104570e-01 8.30470383e-01 -1.17865458e-01 -5.70318699e-01
4.87473190e-01 5.57636082e-01 4.37385142e-01 -7.64124453e-01
-2.63998687e-01 -1.89506173e-01 -2.94446498e-01 -7.15078950e-01
8.87826741e-01 -7.52817765e-02 1.99488789e-01 4.81240094e-01
-1.48663893e-01 -2.89700300e-01 3.16043109e-01 5.94184637e-01
8.53978634e-01 7.63658643e-01 1.05034851e-01 1.47424400e-01
2.01604757e-02 -1.75193980e-01 4.54163164e-01 5.87071896e-01
-3.70317288e-02 9.33882415e-01 4.31909204e-01 -9.13382992e-02
-1.17333901e+00 -1.01705599e+00 3.32330495e-01 8.97467792e-01
2.16495439e-01 -6.43910289e-01 -6.27668977e-01 -3.65700454e-01
-4.87785429e-01 8.99991035e-01 -4.44115877e-01 -1.76025108e-02
-6.88224435e-01 -3.11537445e-01 4.70604114e-02 5.03028095e-01
5.18142998e-01 -1.06414568e+00 -6.16567194e-01 3.70884299e-01
-8.33940446e-01 -1.38484859e+00 -9.15723920e-01 -4.77481723e-01
-9.81475532e-01 -5.10836482e-01 -9.56450403e-01 -4.97442842e-01
6.45279348e-01 8.39730024e-01 1.07798469e+00 1.18570840e-02
-1.46169700e-02 4.79868233e-01 -4.56834823e-01 1.23857982e-01
-2.22884908e-01 -3.45983505e-01 -2.96016216e-01 1.31640956e-01
-2.03772008e-01 -6.78307891e-01 -1.04900861e+00 2.27865323e-01
-1.08807254e+00 8.72100949e-01 4.93382990e-01 8.23676765e-01
3.56358171e-01 -1.65872276e-01 5.58468044e-01 -7.01107502e-01
4.94850665e-01 -5.78336358e-01 -2.27250785e-01 -3.47294845e-02
-4.36009496e-01 -1.15250133e-01 4.49039608e-01 -4.52570140e-01
-1.56917977e+00 -1.70747995e-01 9.17712450e-02 -5.12435436e-01
7.32220039e-02 3.77826869e-01 -7.21738413e-02 2.90752113e-01
3.79219890e-01 2.82186598e-01 -1.77291647e-01 -1.41691789e-01
6.50357485e-01 3.53581280e-01 5.81034124e-01 -5.40783703e-01
6.38049960e-01 6.11667514e-01 -2.20336542e-01 -7.63484716e-01
-6.72543108e-01 -1.64935172e-01 -3.19952637e-01 -4.95105922e-01
9.01605010e-01 -1.31872678e+00 -3.85628402e-01 2.98805892e-01
-1.23793626e+00 -6.04967773e-01 -1.27566338e-01 3.27663630e-01
-7.21201122e-01 6.06655300e-01 -9.00425732e-01 -6.81688607e-01
-1.48666456e-01 -1.17201996e+00 1.16183758e+00 1.41749606e-01
-3.37447226e-01 -9.43042755e-01 -4.23485696e-01 4.92808759e-01
5.07526219e-01 2.71077484e-01 5.20025492e-01 3.07728678e-01
-1.26013339e+00 1.42869636e-01 -3.88488263e-01 9.59809273e-02
2.10823059e-01 7.34831840e-02 -9.41008329e-01 -1.77078128e-01
-7.45235384e-02 -2.10009277e-01 8.96366119e-01 4.41386610e-01
1.31453395e+00 -4.54622418e-01 -2.16203585e-01 6.22247815e-01
1.23589587e+00 2.79184699e-01 8.66258085e-01 6.18271157e-02
9.76245224e-01 6.50663495e-01 7.66490817e-01 6.63039863e-01
5.34012914e-01 8.39282274e-01 2.58321226e-01 -1.53214499e-01
-5.13875902e-01 -5.03582358e-01 6.11878693e-01 8.53825688e-01
-1.63352966e-01 -6.21011138e-01 -5.20489872e-01 5.62825501e-01
-1.87117100e+00 -1.28572023e+00 1.14479735e-01 1.96831656e+00
9.07477438e-01 8.42639655e-02 -1.21998966e-01 -1.47361055e-01
6.11482322e-01 5.60773969e-01 -3.63730788e-01 -2.27438852e-01
-1.58529475e-01 1.71890296e-02 8.34751651e-02 5.79836130e-01
-7.76779532e-01 1.13517916e+00 6.21716499e+00 9.28926468e-01
-1.22333753e+00 6.97223172e-02 8.40317607e-01 -4.88178283e-01
-6.54474378e-01 7.11466894e-02 -4.42738116e-01 6.45174086e-01
9.34540927e-01 4.91580088e-03 5.13055205e-01 4.24168915e-01
9.56874669e-01 -2.86382884e-01 -1.09960496e+00 1.09083056e+00
2.30476931e-01 -1.61834896e+00 4.71559256e-01 -1.63704485e-01
8.42335463e-01 -5.21780670e-01 2.87913620e-01 2.37783846e-02
-8.65981169e-03 -8.34293664e-01 1.06278753e+00 4.28796321e-01
1.21685290e+00 -5.61107278e-01 1.39103919e-01 7.90028870e-02
-1.18538666e+00 2.41195671e-02 2.79066600e-02 -2.06966087e-01
7.03431010e-01 4.38233018e-01 -5.86791933e-01 4.08226967e-01
4.34175193e-01 9.16533828e-01 -3.18240345e-01 7.39532948e-01
-4.27113384e-01 6.37939155e-01 6.80332407e-02 2.69803047e-01
3.05362135e-01 -9.29829031e-02 4.77749735e-01 1.34787428e+00
5.05095840e-01 4.04101342e-01 9.59882960e-02 8.06275010e-01
4.22857404e-02 -2.45789848e-02 -6.21551871e-01 -2.96648800e-01
3.99553567e-01 1.20778465e+00 -6.64939463e-01 -4.77505505e-01
-4.91951406e-01 1.51356864e+00 9.04175118e-02 6.29484832e-01
-9.32218254e-01 -1.12401254e-01 5.60585618e-01 3.01789999e-01
4.32774305e-01 -3.91357243e-01 -2.15162590e-01 -1.36941922e+00
1.93160586e-02 -8.21525633e-01 -1.14122070e-01 -1.26805568e+00
-9.04896915e-01 5.68583548e-01 1.42028660e-01 -1.36917126e+00
-5.48663557e-01 -1.45330638e-01 -5.86126804e-01 7.70947337e-01
-1.48224485e+00 -1.19271266e+00 -4.91868496e-01 5.17906785e-01
1.06493092e+00 2.93569148e-01 4.21293586e-01 4.00703996e-01
-4.94677603e-01 4.94151860e-01 -3.44666660e-01 -3.55217308e-01
1.03864706e+00 -8.59556854e-01 6.19701385e-01 1.10846412e+00
-5.23902662e-02 5.65525115e-01 8.34364772e-01 -7.67839968e-01
-1.23361075e+00 -1.05660427e+00 7.97192037e-01 -3.85154128e-01
4.32859689e-01 -2.65766770e-01 -6.81371093e-01 5.70721149e-01
5.08604407e-01 -3.48727018e-01 5.36699355e-01 -3.85517031e-01
-2.27528363e-01 1.23555295e-01 -7.07265317e-01 1.25986373e+00
1.26486766e+00 -5.65047383e-01 -1.86680377e-01 2.25996524e-01
1.13836312e+00 -4.16117877e-01 -5.30601025e-01 1.97117403e-01
4.54702139e-01 -1.14632344e+00 9.43422675e-01 -1.74262464e-01
1.12459552e+00 -3.83318335e-01 -5.32848909e-02 -1.13446045e+00
-4.15224165e-01 -1.19843149e+00 -3.31035435e-01 1.27155626e+00
1.78976670e-01 -1.15242831e-01 6.76259041e-01 7.36300945e-01
-2.45200738e-01 -7.16756999e-01 -4.58116382e-01 -3.26699823e-01
-4.23057675e-01 -5.40663600e-01 3.16142112e-01 9.11201417e-01
-3.13992426e-02 4.30729657e-01 -9.03645813e-01 -1.43744618e-01
4.69980955e-01 9.33624730e-02 7.14397252e-01 -4.68933254e-01
-3.90566200e-01 -3.79134685e-01 -9.39440355e-02 -1.73348820e+00
-1.29030764e-01 -4.71544117e-01 6.60336763e-02 -1.67379773e+00
1.70416966e-01 -1.39399007e-01 -7.76426643e-02 1.97488338e-01
-5.29191852e-01 3.49103332e-01 3.77939850e-01 2.39830762e-01
-6.49233460e-01 6.68119729e-01 1.73132288e+00 2.12419242e-01
-2.08709374e-01 -3.45616311e-01 -7.88907349e-01 5.07342577e-01
5.61568379e-01 -1.06421281e-02 -7.97946990e-01 -6.83991849e-01
1.33688062e-01 5.07464647e-01 4.45320338e-01 -8.77273858e-01
9.82428268e-02 -4.55894887e-01 3.57884645e-01 -4.98304188e-01
6.47843599e-01 -3.17963839e-01 2.13017106e-01 1.02465160e-01
-4.04443622e-01 8.02939758e-02 1.50998339e-01 8.14386487e-01
-2.31976449e-01 1.15766056e-01 5.86600423e-01 -8.67558494e-02
-8.64180207e-01 4.75296885e-01 -4.60914701e-01 -1.55036896e-01
8.87022793e-01 -4.42020714e-01 -2.42551222e-01 -1.11592543e+00
-3.69584054e-01 1.82274461e-01 6.10129833e-01 5.37088037e-01
7.97416568e-01 -1.38974524e+00 -6.88302279e-01 6.29663141e-03
7.63923824e-02 -1.45099714e-01 5.79150617e-01 6.81799173e-01
-5.46379268e-01 4.69551355e-01 -1.07477926e-01 -5.80128074e-01
-9.16850269e-01 6.19392037e-01 -1.25911653e-01 -3.46892700e-02
-8.40046644e-01 9.17661250e-01 7.51557648e-01 4.94244069e-01
1.26045287e-01 -1.39022574e-01 -1.37604386e-01 1.53539423e-03
7.23274887e-01 1.53225929e-01 -4.95566487e-01 -5.19512832e-01
1.48032427e-01 3.51444423e-01 -2.64317989e-01 -5.89403152e-01
1.15886605e+00 -7.00508714e-01 1.73474938e-01 2.42762253e-01
8.29185903e-01 1.04954094e-01 -2.08703113e+00 -7.27842897e-02
-3.56438965e-01 -8.36970627e-01 9.01712179e-02 -7.87916422e-01
-1.07065392e+00 9.39736664e-01 2.07823530e-01 -1.28460780e-01
1.34991908e+00 -3.58788818e-01 1.11961889e+00 -7.67511353e-02
2.69866884e-01 -8.75596702e-01 5.83719492e-01 1.66991726e-01
9.91007626e-01 -1.20473182e+00 -2.03970820e-02 -4.68639404e-01
-9.10243452e-01 9.70343649e-01 6.91131115e-01 4.51889560e-02
1.86974227e-01 1.50815457e-01 1.85333248e-02 1.33292422e-01
-1.27809656e+00 3.19494270e-02 2.40075588e-01 5.70704460e-01
6.13654733e-01 -1.59457535e-01 -2.84257621e-01 1.98554680e-01
2.69977450e-02 1.77698374e-01 7.01351643e-01 7.50552654e-01
-3.82429421e-01 -1.05459929e+00 -1.47426844e-01 2.58780241e-01
-5.05286932e-01 -3.99825275e-01 6.74330443e-02 4.66910154e-01
-5.42783225e-03 1.15132618e+00 5.59592946e-03 -3.35797131e-01
-1.24307662e-01 -1.80025935e-01 6.53202236e-01 -6.24809206e-01
-2.07538918e-01 4.02850777e-01 1.55626714e-01 -9.10957813e-01
-5.45603275e-01 -5.17009020e-01 -1.02339554e+00 -3.79600793e-01
-1.47420198e-01 -1.28347144e-01 5.39533198e-01 8.50211501e-01
5.42044282e-01 7.46536314e-01 5.93395889e-01 -1.29359448e+00
-3.60071287e-02 -8.05652618e-01 -5.79509176e-02 3.63242120e-01
3.63577306e-01 -5.92736840e-01 -2.19434991e-01 6.16204441e-01] | [10.867264747619629, -0.5807967782020569] |
e7448fd6-6b70-46e4-a4b0-63f15cd6f936 | deeprecon-joint-2d-cardiac-segmentation-and | 2206.07163 | null | https://arxiv.org/abs/2206.07163v1 | https://arxiv.org/pdf/2206.07163v1.pdf | DeepRecon: Joint 2D Cardiac Segmentation and 3D Volume Reconstruction via A Structure-Specific Generative Method | Joint 2D cardiac segmentation and 3D volume reconstruction are fundamental to building statistical cardiac anatomy models and understanding functional mechanisms from motion patterns. However, due to the low through-plane resolution of cine MR and high inter-subject variance, accurately segmenting cardiac images and reconstructing the 3D volume are challenging. In this study, we propose an end-to-end latent-space-based framework, DeepRecon, that generates multiple clinically essential outcomes, including accurate image segmentation, synthetic high-resolution 3D image, and 3D reconstructed volume. Our method identifies the optimal latent representation of the cine image that contains accurate semantic information for cardiac structures. In particular, our model jointly generates synthetic images with accurate semantic information and segmentation of the cardiac structures using the optimal latent representation. We further explore downstream applications of 3D shape reconstruction and 4D motion pattern adaptation by the different latent-space manipulation strategies.The simultaneously generated high-resolution images present a high interpretable value to assess the cardiac shape and motion.Experimental results demonstrate the effectiveness of our approach on multiple fronts including 2D segmentation, 3D reconstruction, downstream 4D motion pattern adaption performance. | ['Dimitris Metaxas', 'Leon Axel', 'Subhi Al Aref', 'Mikael Kanski', 'Qilong Zhangli', 'Meng Ye', 'Khalid Sawalha', 'Di Liu', 'Mu Zhou', 'Zhennan Yan', 'Qi Chang'] | 2022-06-14 | null | null | null | null | ['cardiac-segmentation'] | ['medical'] | [ 2.39222541e-01 1.61088705e-01 -5.08508720e-02 -4.78184015e-01
-1.03073478e+00 -9.12490666e-01 1.86363190e-01 -1.20407425e-01
-2.45936438e-02 4.55389172e-01 4.26870346e-01 -4.23647836e-02
-2.58435130e-01 -5.18413544e-01 -4.29740220e-01 -7.18796909e-01
-3.05666506e-01 8.40075910e-01 1.47759646e-01 4.04940248e-01
1.19597800e-01 5.90676308e-01 -7.27269828e-01 1.93001255e-01
8.79905164e-01 5.69401026e-01 4.11247939e-01 1.00239229e+00
-1.53352961e-01 3.67717952e-01 -1.86437070e-01 1.77270845e-01
2.37730265e-01 -7.68134177e-01 -9.30553794e-01 3.52553278e-01
2.72986919e-01 -5.41426539e-01 6.11534640e-02 8.45579088e-01
7.92187333e-01 -8.91983137e-02 6.68060541e-01 -5.68957686e-01
-3.36592615e-01 5.35556972e-01 -3.98015112e-01 5.61994314e-01
2.41244081e-02 4.28718299e-01 3.55467379e-01 -7.80833960e-01
9.35321033e-01 1.03975356e+00 5.72259843e-01 5.99791825e-01
-1.76566243e+00 -1.96565568e-01 -2.02828959e-01 -4.54883367e-01
-9.33215320e-01 -2.65786141e-01 1.14189601e+00 -8.91290486e-01
2.50473827e-01 4.08155054e-01 7.09832132e-01 7.99566448e-01
3.04856777e-01 5.43332100e-01 1.24453020e+00 -1.19876824e-01
-2.51888670e-03 -3.35809529e-01 -7.26200491e-02 7.98529685e-01
1.14539839e-01 5.40087372e-02 -2.86998063e-01 -2.92111188e-01
1.48846793e+00 -7.57516846e-02 -4.51947659e-01 -7.05922544e-01
-1.86438835e+00 5.69437206e-01 1.75075263e-01 2.98815548e-01
-6.32296979e-01 2.76359230e-01 4.15354520e-01 -2.27333739e-01
5.23307920e-01 4.98135060e-01 -2.06590712e-01 -4.90007289e-02
-1.25424683e+00 4.06027228e-01 3.39114398e-01 6.18034244e-01
1.28011316e-01 2.53696769e-01 -5.62453389e-01 8.05089474e-01
5.46547472e-01 5.37186503e-01 5.41523814e-01 -1.64955032e+00
2.60746121e-01 3.56729209e-01 -2.42340386e-01 -9.18778002e-01
-5.63233137e-01 -5.03526866e-01 -1.06976867e+00 -4.10672203e-02
4.19518322e-01 1.77887566e-02 -1.06405580e+00 1.62930441e+00
7.17553675e-01 3.78368139e-01 -1.57955736e-01 1.36390603e+00
8.41519058e-01 3.75381202e-01 2.30634704e-01 -6.04580343e-01
1.22964096e+00 -6.85897708e-01 -7.41099715e-01 -1.13978148e-01
5.91641128e-01 -7.04542458e-01 9.84065652e-01 -2.36935139e-01
-1.55033624e+00 -5.07616997e-01 -7.47106194e-01 1.20886661e-01
7.52386630e-01 -1.75510973e-01 4.52933282e-01 4.30448920e-01
-8.85131598e-01 9.76611316e-01 -1.34726560e+00 3.02685201e-01
6.98742390e-01 1.52612939e-01 -3.20930034e-01 1.44553594e-02
-8.45561326e-01 5.05633235e-01 2.37090468e-01 1.87530026e-01
-1.02401519e+00 -1.28271246e+00 -7.93053865e-01 -3.86124521e-01
5.97259030e-02 -1.25991571e+00 1.00049436e+00 -4.68811899e-01
-1.37394416e+00 1.33763695e+00 -9.43393037e-02 -2.09475368e-01
8.64163220e-01 2.51101017e-01 1.95905298e-01 7.06327915e-01
4.70682621e-01 6.33485079e-01 8.06852281e-01 -1.11254501e+00
3.65382195e-01 -5.92309237e-01 -6.93862975e-01 3.04253757e-01
4.79111850e-01 -2.30152994e-01 -2.48031884e-01 -1.11904585e+00
9.46674407e-01 -9.38307822e-01 -7.11525977e-01 2.90100306e-01
-2.91337669e-01 6.39248550e-01 4.34101492e-01 -9.56341267e-01
1.10488951e+00 -1.90510488e+00 4.73799318e-01 1.65059492e-01
7.45766282e-01 -2.58537428e-03 1.05124034e-01 -4.15805608e-01
-1.84831381e-01 3.87946486e-01 -8.35578203e-01 -1.21907078e-01
-5.18298984e-01 1.50699601e-01 -7.29164779e-02 5.38435638e-01
-1.21246919e-01 1.42519057e+00 -1.06749129e+00 -1.02709126e+00
4.27985072e-01 3.95044297e-01 -8.21194649e-01 5.73714256e-01
1.05598621e-01 1.55330729e+00 -8.50157619e-01 4.01773810e-01
5.84873915e-01 -4.99833882e-01 4.75890666e-01 -4.45153058e-01
8.73529166e-02 -5.49557135e-02 -7.97070622e-01 2.23851323e+00
-1.99757591e-01 1.98591530e-01 9.17818323e-02 -8.12528670e-01
7.94507086e-01 5.80285192e-01 1.18941593e+00 -5.88195384e-01
-4.68602479e-02 2.65045822e-01 -1.17678240e-01 -6.93733752e-01
-1.52656600e-01 -6.38496041e-01 -3.11575383e-02 6.52141392e-01
-9.58844200e-02 -6.21938527e-01 -2.89897859e-01 1.31664738e-01
6.59701407e-01 3.64786267e-01 -1.79534107e-02 -4.69227463e-01
3.59560668e-01 4.80877794e-02 6.15361154e-01 5.15877366e-01
-5.19503891e-01 1.16748083e+00 5.49113035e-01 -6.43195510e-01
-1.51350236e+00 -1.43441319e+00 -3.76256108e-01 9.68258381e-02
5.46829700e-02 8.89186785e-02 -9.21332598e-01 -5.92497230e-01
-2.04816073e-01 5.08504689e-01 -4.61222410e-01 -7.57537633e-02
-1.17313182e+00 -9.47089434e-01 5.77678382e-01 4.70804662e-01
2.18418241e-01 -9.95772600e-01 -9.45095360e-01 5.20368457e-01
-8.01179290e-01 -1.13745832e+00 -6.90890849e-01 -4.12233084e-01
-1.78027427e+00 -9.89789605e-01 -9.57669258e-01 -5.54824591e-01
7.85702825e-01 -6.11422285e-02 1.27270424e+00 8.95999968e-02
-6.88027859e-01 2.20420837e-01 -3.75354802e-03 2.38565758e-01
-8.28674316e-01 -2.98078328e-01 -2.12249890e-01 -1.85434282e-01
-6.90771639e-01 -8.35460603e-01 -1.04970610e+00 2.25752249e-01
-7.45603263e-01 5.51977336e-01 2.93447852e-01 7.27810681e-01
1.22501767e+00 -5.21439791e-01 3.01805884e-01 -1.18405235e+00
3.29304874e-01 -3.23315859e-01 -3.39985758e-01 2.46300906e-01
-4.94841933e-01 3.03492129e-01 1.89403981e-01 -2.46764347e-01
-1.12969971e+00 8.85536000e-02 -1.02984868e-01 -6.13568544e-01
-1.72566459e-01 2.60322511e-01 2.80028075e-01 2.71735430e-01
7.47288287e-01 4.13767070e-01 3.73175859e-01 -4.01038468e-01
4.20513242e-01 7.37911742e-03 7.08417118e-01 -6.88390315e-01
5.80508828e-01 7.62694657e-01 4.73288864e-01 -4.33495700e-01
-7.66609788e-01 -1.78889170e-01 -1.40042806e+00 -3.59765023e-01
1.34038293e+00 -7.28234112e-01 -4.60710138e-01 3.35114509e-01
-1.11773241e+00 -3.32932711e-01 -6.31092668e-01 6.40456498e-01
-8.89121532e-01 7.21481919e-01 -7.88989782e-01 -4.52617913e-01
-7.51807034e-01 -1.75579286e+00 1.28564346e+00 -2.52695233e-01
-5.39404035e-01 -1.29601252e+00 1.43998593e-01 6.14788651e-01
3.11718851e-01 1.07588804e+00 1.23205256e+00 8.95774588e-02
-8.93120527e-01 2.38430366e-01 7.98319727e-02 1.64497733e-01
5.97547702e-02 -3.41868788e-01 -6.73959851e-01 -1.78987280e-01
2.29794681e-01 -8.07483196e-02 5.50961018e-01 1.35107636e+00
1.27300107e+00 -6.09874204e-02 -5.47955707e-02 1.12261200e+00
1.10450792e+00 7.78188417e-03 2.85554022e-01 -2.88612992e-01
9.66345131e-01 6.72241211e-01 4.99449641e-01 3.00461680e-01
2.47357115e-01 6.85858667e-01 8.41010809e-02 -3.21523637e-01
-4.56400752e-01 -2.90179580e-01 -1.50904626e-01 1.29842257e+00
-1.63976774e-01 4.38136965e-01 -1.22907364e+00 4.60311592e-01
-1.53803492e+00 -7.47449040e-01 -3.63840312e-01 1.99745142e+00
8.93763304e-01 -5.86513579e-02 -7.43123442e-02 -2.51733482e-01
5.58070242e-01 3.14270318e-01 -6.15000844e-01 1.21904567e-01
1.06689930e-01 7.05430284e-02 3.41486484e-01 7.89108038e-01
-8.96486104e-01 7.34750748e-01 6.78258324e+00 3.85508865e-01
-9.90741730e-01 3.75197709e-01 1.07339549e+00 -4.12912853e-02
-8.13497245e-01 1.63365871e-01 -3.07716459e-01 3.24775308e-01
7.30750144e-01 -1.82043150e-01 2.76150882e-01 4.37717289e-01
7.08493710e-01 9.04373601e-02 -9.63074923e-01 1.10178149e+00
-1.37358889e-01 -1.84309006e+00 2.62493521e-01 -4.20476198e-02
7.67718017e-01 -2.98754066e-01 -1.23061001e-01 -2.35993654e-01
-2.30669498e-01 -1.06760263e+00 7.93078780e-01 8.69329214e-01
1.40994275e+00 -3.48556966e-01 2.51644820e-01 4.65771466e-01
-1.04521799e+00 4.92862403e-01 8.12085718e-02 5.63156962e-01
5.63796759e-01 6.70625210e-01 -8.23148608e-01 4.16357666e-01
3.53803307e-01 6.69518530e-01 -2.77007490e-01 6.33694112e-01
5.20137884e-02 6.27164006e-01 -7.56646041e-03 7.47323096e-01
-1.04101710e-01 -3.55803490e-01 1.09108162e+00 8.57346952e-01
5.55025600e-02 4.79356110e-01 4.05813366e-01 1.47307348e+00
2.11324617e-01 8.19704533e-02 -5.31114697e-01 2.62892768e-02
3.64501953e-01 1.07340646e+00 -1.17364120e+00 -4.66876775e-01
2.87458718e-01 8.02912593e-01 1.59268398e-02 3.77865255e-01
-7.96312928e-01 4.58076239e-01 1.66303933e-01 5.15947700e-01
-3.18246275e-01 -4.97421384e-01 -7.51483798e-01 -1.24607933e+00
2.13559363e-02 -4.84455734e-01 3.71010631e-01 -6.86815798e-01
-1.04379451e+00 4.32603806e-01 3.19151789e-01 -1.02913713e+00
-4.22787994e-01 3.53220515e-02 -4.47497636e-01 1.10646224e+00
-1.03353918e+00 -9.36684787e-01 -3.02620679e-01 2.76305169e-01
7.21501291e-01 1.55584410e-01 7.97675073e-01 2.80594856e-01
-1.76949248e-01 1.43415049e-01 -2.88123846e-01 2.69780785e-01
3.85348678e-01 -1.22778809e+00 4.16338384e-01 6.89916670e-01
-1.86148256e-01 5.52727759e-01 3.95540446e-01 -9.88722920e-01
-1.15718985e+00 -1.09968281e+00 3.95400643e-01 -7.48190582e-01
-3.57292481e-02 -6.93728328e-02 -9.26739216e-01 5.56813776e-01
-5.02274513e-01 4.85951155e-01 6.28803849e-01 -4.74377543e-01
3.64721358e-01 2.82883704e-01 -1.32688284e+00 5.25656819e-01
1.15810835e+00 -3.12309891e-01 -5.27565181e-01 3.11096996e-01
9.26490426e-01 -8.82260680e-01 -1.41640913e+00 6.13022089e-01
4.49768960e-01 -7.58493781e-01 1.40512824e+00 -5.20190537e-01
7.02518702e-01 -3.02185476e-01 1.03931971e-01 -9.47878599e-01
-3.94412905e-01 -5.56707561e-01 -6.60931617e-02 6.75222754e-01
1.66276857e-01 -2.24164486e-01 8.75572503e-01 8.04509521e-01
-3.36159408e-01 -7.39827812e-01 -1.03336477e+00 -1.05337858e-01
2.53447026e-01 -5.61170340e-01 2.76628584e-01 1.32114184e+00
-5.61388791e-01 9.94195864e-02 -1.40973687e-01 6.84769824e-02
1.19360065e+00 6.47111535e-01 4.34939414e-01 -9.39789355e-01
-4.31251675e-01 -3.35095078e-01 -2.08365217e-01 -9.62081969e-01
4.13288400e-02 -1.40593410e+00 -2.28579760e-01 -1.44784403e+00
3.64135891e-01 -5.70274651e-01 2.86777392e-02 1.87084582e-02
-2.45813683e-01 1.70539796e-01 1.90788954e-01 6.56847656e-01
-1.59672961e-01 4.05651629e-01 2.36456227e+00 2.22013414e-01
-3.42381239e-01 -1.46960199e-01 -3.05414200e-01 7.44602263e-01
4.15595442e-01 -6.53472006e-01 -5.65726638e-01 -5.68430185e-01
-1.78337649e-01 1.13620484e+00 7.41821289e-01 -5.64729989e-01
-2.50537902e-01 -1.27363652e-01 7.18123794e-01 -6.30179346e-01
7.52860233e-02 -5.09879529e-01 3.49097759e-01 6.59522831e-01
-5.84744632e-01 -1.29437476e-01 -9.55824926e-03 4.05078471e-01
-5.83410375e-02 4.46584597e-02 1.24508572e+00 -7.04104841e-01
-1.60907149e-01 6.68617070e-01 -1.61349803e-01 6.48542404e-01
9.26809132e-01 -4.57961142e-01 5.01316309e-01 -9.63753536e-02
-1.43882954e+00 1.63474515e-01 2.05778390e-01 1.42434090e-01
9.38516259e-01 -1.36582243e+00 -1.11675656e+00 3.56573135e-01
-3.27130854e-01 5.55866539e-01 8.41090322e-01 1.18718076e+00
-1.06665337e+00 2.20530003e-01 -2.91637629e-01 -1.36311364e+00
-1.03303552e+00 1.61973521e-01 8.04069042e-01 -4.75028694e-01
-1.16680074e+00 5.99989355e-01 5.16025245e-01 -5.88408351e-01
-3.78526688e-01 -4.61197942e-01 2.69392058e-02 -3.15502703e-01
7.28253126e-02 1.61720425e-01 -3.08744818e-01 -7.63555408e-01
-2.82832891e-01 1.01274991e+00 3.40991735e-01 -1.84190318e-01
1.32198322e+00 -4.29775208e-01 -1.07347732e-02 5.07326305e-01
1.11519074e+00 -2.90143788e-01 -1.54795289e+00 -9.19613242e-03
-1.89748257e-01 -6.96570575e-01 1.76954865e-01 -5.22205114e-01
-1.26842225e+00 1.08220136e+00 8.23329806e-01 -4.88425732e-01
8.94575477e-01 -8.50039572e-02 9.74198818e-01 -5.98105907e-01
2.30196446e-01 -5.90522051e-01 1.30744174e-01 -1.23919085e-01
9.17015135e-01 -1.13143337e+00 2.04189807e-01 -6.08884037e-01
-8.36515903e-01 9.37806904e-01 3.47002476e-01 -3.92511301e-02
5.78713357e-01 1.55236855e-01 2.40606517e-01 -4.40866292e-01
-4.82608378e-01 5.04921556e-01 5.78815520e-01 3.93999517e-01
6.26941621e-01 2.12380052e-01 -2.41240367e-01 1.94196001e-01
1.51518090e-02 -1.33561060e-01 3.15130293e-01 6.33021712e-01
-5.72119765e-02 -1.00204039e+00 -4.71535623e-01 1.96577206e-01
-6.63484812e-01 9.82774887e-03 2.37574607e-01 2.67419964e-01
-6.66466132e-02 1.57623917e-01 -1.19682051e-01 3.43759358e-01
3.30462813e-01 1.04529984e-01 7.79645681e-01 -7.86631465e-01
-3.91776621e-01 5.37054658e-01 -3.13756347e-01 -6.81379437e-01
-3.07597548e-01 -7.32768059e-01 -1.72334242e+00 1.47850867e-02
2.16014087e-01 -1.41027004e-01 6.22480810e-01 7.40661383e-01
3.10873598e-01 7.54257619e-01 6.58811033e-01 -8.81032288e-01
-4.32018369e-01 -6.13019407e-01 -4.17307556e-01 9.22160387e-01
2.80427605e-01 -4.30342764e-01 -3.49095650e-02 5.05038679e-01] | [13.979771614074707, -2.389449119567871] |
29e09ea3-7594-442f-bdc8-f1a3461edc9c | region-prediction-for-efficient-robot | 2303.00295 | null | https://arxiv.org/abs/2303.00295v1 | https://arxiv.org/pdf/2303.00295v1.pdf | Region Prediction for Efficient Robot Localization on Large Maps | Recognizing already explored places (a.k.a. place recognition) is a fundamental task in Simultaneous Localization and Mapping (SLAM) to enable robot relocalization and loop closure detection. In topological SLAM the recognition takes place by comparing a signature (or feature vector) associated to the current node with the signatures of the nodes in the known map. However, as the number of nodes increases, matching the current node signature against all the existing ones becomes inefficient and thwarts real-time navigation. In this paper we propose a novel approach to pre-select a subset of map nodes for place recognition. The map nodes are clustered during exploration and each cluster is associated with a region. The region labels become the prediction targets of a deep neural network and, during navigation, only the nodes associated with the regions predicted with high probability are considered for matching. While the proposed technique can be integrated in different SLAM approaches, in this work we describe an effective integration with RTAB-Map (a popular framework for real-time topological SLAM) which allowed us to design and run several experiments to demonstrate its effectiveness. All the code and material from the experiments will be available online at https://github.com/MI-BioLab/region-learner. | ['Davide Maltoni', 'Matteo Scucchia'] | 2023-03-01 | null | null | null | null | ['simultaneous-localization-and-mapping', 'loop-closure-detection'] | ['computer-vision', 'computer-vision'] | [ 1.55546933e-01 2.05937531e-02 -1.62566245e-01 -4.81575310e-01
-5.17872870e-01 -5.77831864e-01 6.87512338e-01 5.82891822e-01
-7.09897041e-01 8.17330420e-01 -3.02716315e-01 -2.19483107e-01
-3.51904958e-01 -7.95927048e-01 -9.27304089e-01 -6.00456595e-01
-6.35556698e-01 8.89821827e-01 6.11357570e-01 -1.66183114e-01
6.19992614e-01 8.87917817e-01 -1.72775245e+00 -1.79716617e-01
8.34145010e-01 7.97971308e-01 7.23525107e-01 3.86143953e-01
-1.44673660e-01 3.78859818e-01 -2.44571194e-01 5.31035662e-01
3.24441075e-01 -2.76639342e-01 -8.02020729e-01 -5.17500103e-01
4.46174413e-01 1.98711723e-01 -2.71146417e-01 1.01668990e+00
3.07397813e-01 6.36627555e-01 3.71779621e-01 -1.35478127e+00
3.03386360e-01 3.91573787e-01 -2.77725399e-01 1.47808254e-01
4.48826462e-01 -2.98586845e-01 6.74432933e-01 -7.79433608e-01
8.24540317e-01 9.14256036e-01 6.31642163e-01 1.11790203e-01
-9.26395297e-01 -6.08360231e-01 8.15990940e-02 3.61711681e-01
-1.77505863e+00 -5.34128428e-01 6.87862575e-01 -2.65758753e-01
6.96241081e-01 1.62761912e-01 7.26860046e-01 6.91452086e-01
4.37999308e-01 6.05348170e-01 9.47138906e-01 -3.13901842e-01
4.97154504e-01 1.63526893e-01 -4.64868881e-02 1.07943904e+00
-2.58660968e-02 2.88091213e-01 -7.48105884e-01 -1.58916071e-01
5.72282612e-01 -5.18728606e-02 -1.23556092e-01 -1.10272515e+00
-1.38249660e+00 6.04372501e-01 1.15584528e+00 5.19690394e-01
-4.38645363e-01 2.78484404e-01 2.42664963e-01 5.86978607e-02
-1.05834641e-01 4.74740565e-01 -1.27616212e-01 -4.70840856e-02
-9.99522865e-01 1.56597242e-01 6.46324992e-01 8.15921307e-01
1.44599330e+00 -3.85342658e-01 3.58341604e-01 6.15079761e-01
3.04881215e-01 3.90461922e-01 4.92978305e-01 -7.09760010e-01
1.71178296e-01 7.27925360e-01 3.08200717e-01 -1.40477276e+00
-9.04089689e-01 -3.45557302e-01 -5.54848969e-01 3.04852486e-01
2.89542407e-01 2.82888979e-01 -9.91224110e-01 1.61872458e+00
4.79062587e-01 3.93685400e-01 1.96284279e-02 9.42889571e-01
4.62810576e-01 6.44864678e-01 -7.12006539e-02 3.07379097e-01
1.10238075e+00 -8.43380332e-01 -2.51635313e-01 -6.59778476e-01
7.77237952e-01 -4.56502229e-01 3.96682650e-01 5.65339923e-02
-3.26135784e-01 -5.28098583e-01 -1.17569184e+00 7.75883570e-02
-6.91500545e-01 8.97461101e-02 6.21060669e-01 1.98325235e-02
-1.35788953e+00 5.81029058e-01 -1.01089013e+00 -8.97227228e-01
5.60378246e-02 5.39746881e-01 -8.01518381e-01 -7.75484717e-04
-1.07364070e+00 1.20824158e+00 7.92791426e-01 2.78623760e-01
-1.10316777e+00 7.24324211e-02 -1.03926754e+00 -2.82080829e-01
7.05644190e-02 -1.88460350e-01 8.31431091e-01 -6.45867825e-01
-1.02039742e+00 9.31328773e-01 -5.69280624e-01 -5.54762304e-01
3.80034924e-01 -1.23031937e-01 -1.44497752e-01 -1.29769102e-01
4.73192453e-01 1.05317008e+00 3.07548136e-01 -1.40445948e+00
-9.84695375e-01 -4.06560630e-01 -1.76472321e-01 3.92760634e-01
3.97021264e-01 -4.16278303e-01 -4.86728936e-01 6.22008331e-02
9.85941350e-01 -1.18000805e+00 -4.15715486e-01 3.32245044e-02
-2.24145487e-01 -1.95626672e-02 5.98841548e-01 -3.66771013e-01
5.51017702e-01 -2.20042634e+00 2.17897698e-01 5.81813097e-01
-1.42276928e-01 -2.33597517e-01 -4.36772928e-02 6.02714121e-01
1.38253242e-01 -3.90247673e-01 -3.25925708e-01 -3.17317873e-01
-1.19675085e-01 3.18584561e-01 -1.50390476e-01 1.01056981e+00
-3.17303717e-01 6.07534945e-01 -1.15710664e+00 -4.08788651e-01
6.05202675e-01 3.27445298e-01 -4.98623662e-02 -8.17270800e-02
6.14831746e-02 7.97527730e-01 -3.97998005e-01 6.39578938e-01
7.51009345e-01 1.28539637e-01 1.70677662e-01 1.04633696e-01
-5.19448817e-01 4.60049629e-01 -1.36324942e+00 1.89072239e+00
-4.87712532e-01 7.22374558e-01 1.44043937e-02 -9.50091302e-01
1.42519414e+00 -9.53405499e-02 3.68713737e-01 -8.90365899e-01
-9.81836841e-02 6.53852642e-01 -1.57453179e-01 -8.38021636e-02
9.20732915e-01 2.23338336e-01 -2.46034175e-01 2.06855416e-01
8.15217644e-02 1.57933965e-01 -3.07433121e-02 2.37990133e-02
1.06970429e+00 2.08867267e-01 4.93423641e-01 -4.20521885e-01
6.14402950e-01 4.72051322e-01 5.02916992e-01 8.33346546e-01
-3.44071627e-01 4.97981086e-02 -1.75318420e-02 -7.74181128e-01
-7.57979631e-01 -1.01289392e+00 -2.24895343e-01 8.74405444e-01
8.88340831e-01 -1.97113335e-01 -1.41682670e-01 -4.85472172e-01
1.48179680e-01 6.06089175e-01 -6.27363801e-01 -9.66250375e-02
-5.42505920e-01 -1.98197544e-01 3.26913148e-01 1.14634387e-01
4.56755280e-01 -1.32807040e+00 -1.06446075e+00 3.02505553e-01
-1.51470810e-01 -6.41358614e-01 3.05319279e-01 7.11341739e-01
-6.95555568e-01 -1.04524660e+00 -2.73106903e-01 -9.58570182e-01
9.23161924e-01 3.71281117e-01 6.03747308e-01 1.23753689e-01
-4.53077555e-02 -2.54497305e-02 -4.37152952e-01 -7.81347677e-02
-2.99734890e-01 3.56840223e-01 3.40157539e-01 -1.74149662e-01
9.73749384e-02 -5.77118397e-01 -4.13764238e-01 5.84685266e-01
-3.27770650e-01 1.25760630e-01 6.38199151e-01 5.56332409e-01
8.36277068e-01 7.30936378e-02 8.33920985e-02 -4.92311954e-01
-2.02421937e-02 -5.62802792e-01 -9.58987951e-01 1.10857099e-01
-3.02474946e-01 5.02219349e-02 2.21121714e-01 -5.08778654e-02
-3.79441142e-01 5.66691041e-01 -6.06106929e-02 -2.43186429e-02
-3.70078206e-01 6.94720149e-01 3.03462520e-02 -6.23891056e-01
5.55338979e-01 5.57980955e-01 -2.00968370e-01 -3.89182746e-01
1.57441571e-01 3.59539509e-01 6.51481092e-01 -2.85206944e-01
7.76050866e-01 4.82325226e-01 2.38435388e-01 -5.18741906e-01
-2.94181675e-01 -7.53413200e-01 -9.09660757e-01 -4.04628545e-01
3.01701814e-01 -8.91774595e-01 -5.30403912e-01 1.08057283e-01
-9.71980155e-01 -2.87261903e-01 1.50876865e-01 6.24830842e-01
-5.42810738e-01 1.06407404e-01 -3.12156267e-02 -9.72300291e-01
6.61950409e-02 -1.08057022e+00 9.06059980e-01 4.52496409e-01
-2.81242758e-01 -7.94915855e-01 3.89652610e-01 -1.59472391e-01
2.97802806e-01 2.68683165e-01 3.18717569e-01 -8.05485308e-01
-8.75919104e-01 -5.28765142e-01 2.62046922e-02 -5.75889945e-01
7.48094022e-02 -3.86317998e-01 -9.09501612e-01 -4.58751291e-01
-2.34689876e-01 -7.23760873e-02 9.61681783e-01 1.39507607e-01
5.65113723e-01 6.27300814e-02 -1.05184889e+00 6.24504864e-01
1.45281744e+00 2.97746688e-01 4.58772659e-01 8.75223458e-01
4.41854268e-01 6.87814116e-01 1.12988317e+00 3.58926892e-01
3.39224279e-01 8.06575298e-01 7.82264590e-01 7.06317499e-02
4.70800281e-01 -5.22436619e-01 3.19811404e-01 3.27619433e-01
3.53253603e-01 -2.23783761e-01 -1.32628441e+00 8.38069201e-01
-2.06940103e+00 -6.46251976e-01 5.15673235e-02 2.45937443e+00
2.16669038e-01 1.12409331e-01 -2.41979122e-01 -1.09357014e-01
8.15874815e-01 1.91717267e-01 -4.24812287e-01 -8.15702677e-02
-4.79945876e-02 -1.50535613e-01 8.02654803e-01 1.01164436e+00
-1.37656307e+00 1.20159745e+00 4.96854496e+00 5.15536547e-01
-1.20265210e+00 -1.01762652e-01 5.32806404e-02 2.99657375e-01
3.93230617e-02 3.00184727e-01 -8.08102489e-01 2.23732352e-01
8.70009243e-01 1.50183499e-01 3.63164961e-01 1.13738990e+00
3.03031523e-02 -8.89703929e-01 -1.02559674e+00 7.30965495e-01
-1.38928637e-01 -1.23740220e+00 -3.97735298e-01 8.07662234e-02
4.32759017e-01 6.52593255e-01 -2.88807005e-01 2.82259375e-01
8.00384805e-02 -8.80405784e-01 8.37534308e-01 4.01228875e-01
4.73137051e-01 -7.93624580e-01 9.48237002e-01 6.54762328e-01
-1.39674878e+00 -7.41521418e-02 -5.04090369e-01 1.13024646e-02
1.43047884e-01 4.31311399e-01 -1.52693033e+00 8.43931556e-01
6.65155053e-01 5.90726495e-01 -7.18703330e-01 1.48178923e+00
-3.93580943e-01 -3.86583023e-02 -7.22589791e-01 -1.58978462e-01
4.89657521e-01 -9.59517360e-02 6.75670207e-01 1.01683736e+00
6.17276609e-01 -5.72879314e-01 4.93294358e-01 7.18339384e-01
3.85590255e-01 7.31564388e-02 -8.84722173e-01 3.99037123e-01
8.54943573e-01 1.30121171e+00 -1.25027215e+00 -2.39675671e-01
2.20906302e-01 1.02035558e+00 5.65347373e-01 5.55865914e-02
-6.37077093e-01 -3.77363622e-01 4.03550744e-01 1.27531290e-02
4.42230925e-02 -4.77863461e-01 -5.67820147e-02 -6.38680577e-01
-1.39142916e-01 -1.95093796e-01 1.75655589e-01 -7.04011559e-01
-5.51590502e-01 6.10896587e-01 -1.22543871e-01 -1.36721218e+00
-1.86532319e-01 -3.54783118e-01 -4.58189279e-01 8.93280029e-01
-1.43909717e+00 -9.22698379e-01 -5.89885533e-01 2.84316957e-01
8.25196803e-02 1.67442515e-01 1.02806318e+00 2.02839181e-01
-8.42140019e-02 1.71995729e-01 2.70074219e-01 5.55124916e-02
6.60025299e-01 -1.07227075e+00 5.67410529e-01 8.07868659e-01
4.58889544e-01 6.24351740e-01 8.30202818e-01 -9.29844737e-01
-1.24794412e+00 -9.40819025e-01 1.15785336e+00 -1.53166518e-01
3.97591621e-01 -5.05796432e-01 -8.87777746e-01 7.59586692e-01
-2.44541213e-01 -3.12361810e-02 1.81016743e-01 1.03681959e-01
1.00377806e-01 -1.04098774e-01 -1.08277631e+00 4.35591936e-01
8.80859494e-01 -5.16723394e-01 -3.01200062e-01 2.52756149e-01
2.39306465e-01 -5.98668575e-01 -4.42508280e-01 5.91756344e-01
3.65674973e-01 -1.04580176e+00 6.60504401e-01 1.27417326e-01
-4.90186691e-01 -9.63751912e-01 -2.92162538e-01 -1.31108510e+00
-3.05379480e-01 -2.20212236e-01 2.51768112e-01 8.90534282e-01
3.00967038e-01 -6.94679856e-01 9.66395080e-01 5.85177506e-04
-2.25113273e-01 -3.15951407e-01 -1.56392348e+00 -8.02004278e-01
-6.72717869e-01 -2.37180069e-01 3.46998602e-01 8.23234379e-01
1.40822113e-01 -5.88203035e-02 -1.71914637e-01 7.05858648e-01
5.78277826e-01 3.37285727e-01 9.12809849e-01 -1.28934777e+00
3.85016590e-01 -1.53731853e-01 -9.55695808e-01 -1.01449788e+00
2.10879982e-01 -1.21406412e+00 6.83741093e-01 -1.68433022e+00
-2.35422924e-01 -1.04489410e+00 -5.55968940e-01 5.76796830e-01
3.31763357e-01 4.28304486e-02 -1.90871470e-02 4.21561956e-01
-8.48094344e-01 5.43002129e-01 5.43596089e-01 4.79596928e-02
-4.24283355e-01 1.27412632e-01 9.72972661e-02 4.57287610e-01
1.04108739e+00 -7.64464974e-01 -5.46133295e-02 -7.98512027e-02
1.67513967e-01 1.11965299e-01 5.71068764e-01 -1.76273906e+00
7.48690248e-01 2.09335773e-03 4.37090486e-01 -1.02647626e+00
5.09855449e-01 -9.66861606e-01 4.99013036e-01 9.57744122e-01
-1.93108559e-01 8.37059990e-02 2.81116992e-01 6.45969868e-01
-1.82881713e-01 -4.32132602e-01 6.82088017e-01 -1.82822913e-01
-1.55974746e+00 3.45880128e-02 -4.26918685e-01 -6.64374650e-01
9.99809384e-01 -2.48666331e-01 -8.45517293e-02 -3.07388604e-01
-5.57394683e-01 4.39330995e-01 9.67203677e-01 4.22633290e-01
8.20297658e-01 -1.13110375e+00 -3.14068258e-01 4.01104271e-01
4.71717209e-01 2.08191365e-01 1.48482576e-01 9.42300498e-01
-8.81745756e-01 4.90512103e-01 -5.43414712e-01 -8.16409469e-01
-1.02150333e+00 4.58262324e-01 4.56080109e-01 1.11983940e-01
-6.10008359e-01 9.10417616e-01 1.21684987e-02 -8.13384652e-01
3.38503778e-01 -3.78834419e-02 -2.00508773e-01 -1.09235093e-01
3.12384695e-01 1.67541444e-01 2.96806451e-03 -9.76289153e-01
-9.37843323e-01 5.52578151e-01 2.44053140e-01 -2.38040447e-01
1.25708055e+00 -3.03046674e-01 -4.44449186e-01 7.36995459e-01
9.55517828e-01 -1.23352176e-02 -9.74045038e-01 -1.99099228e-01
5.37630439e-01 -3.48607808e-01 -8.92427340e-02 -5.85393667e-01
-5.77167451e-01 4.99366909e-01 9.20748353e-01 -3.66364002e-01
5.97203970e-01 1.71764553e-01 2.81117350e-01 7.60877669e-01
1.20889771e+00 -7.98316121e-01 -4.31474447e-01 7.99518764e-01
6.16237998e-01 -1.22399056e+00 3.13655846e-02 -3.65909971e-02
-4.11766857e-01 1.00565100e+00 7.09124982e-01 -2.88932174e-01
4.74173576e-01 7.80624375e-02 1.47111773e-01 -2.80379117e-01
-2.31236503e-01 -2.26451620e-01 5.89085333e-02 5.49061596e-01
-2.67435964e-02 1.44634828e-01 1.23221735e-02 -2.16006130e-01
-2.89004624e-01 -2.82927424e-01 2.85201043e-01 1.09138680e+00
-1.12893760e+00 -9.38065469e-01 -6.65897965e-01 3.26194502e-02
3.01188618e-01 2.20005929e-01 -3.96222502e-01 7.73635685e-01
3.10133696e-01 5.98372877e-01 3.20951283e-01 -5.98561287e-01
-3.87359336e-02 1.28688335e-01 2.99982399e-01 -4.25254613e-01
-1.36938229e-01 -2.12486506e-01 -1.08587341e-02 -7.39242554e-01
-3.37555021e-01 -6.83088005e-01 -1.72820449e+00 -2.60154873e-01
-1.79449692e-01 5.03933787e-01 1.09986186e+00 6.41702235e-01
3.68160158e-01 1.29145160e-01 5.09158015e-01 -1.27797544e+00
2.11423472e-01 -8.49281073e-01 -5.25317132e-01 -1.17559865e-01
3.42961878e-01 -1.03195465e+00 -1.27175599e-01 -5.04977345e-01] | [7.356849193572998, -2.0206503868103027] |
55b5a8c5-8daf-4f16-8224-339e7527c6d0 | gait-recognition-using-3-d-human-body-shape | 2212.09042 | null | https://arxiv.org/abs/2212.09042v1 | https://arxiv.org/pdf/2212.09042v1.pdf | Gait Recognition Using 3-D Human Body Shape Inference | Gait recognition, which identifies individuals based on their walking patterns, is an important biometric technique since it can be observed from a distance and does not require the subject's cooperation. Recognizing a person's gait is difficult because of the appearance variants in human silhouette sequences produced by varying viewing angles, carrying objects, and clothing. Recent research has produced a number of ways for coping with these variants. In this paper, we present the usage of inferring 3-D body shapes distilled from limited images, which are, in principle, invariant to the specified variants. Inference of 3-D shape is a difficult task, especially when only silhouettes are provided in a dataset. We provide a method for learning 3-D body inference from silhouettes by transferring knowledge from 3-D shape prior from RGB photos. We use our method on multiple existing state-of-the-art gait baselines and obtain consistent improvements for gait identification on two public datasets, CASIA-B and OUMVLP, on several variants and settings, including a new setting of novel views not seen during training. | ['Ram Nevatia', 'Zhaoheng Zheng', 'Haidong Zhu'] | 2022-12-18 | null | null | null | null | ['gait-recognition', 'gait-identification'] | ['computer-vision', 'computer-vision'] | [ 1.10138267e-01 -4.32144135e-01 -3.57635058e-02 -3.84974360e-01
-2.89700598e-01 -6.12971008e-01 3.37280899e-01 -3.88784796e-01
-3.13806385e-01 6.25868738e-01 1.70578286e-01 4.06867057e-01
2.60492086e-01 -5.75779676e-01 -4.63048190e-01 -6.43401563e-01
-3.27449322e-01 7.22303987e-01 2.45610595e-01 -2.72079319e-01
7.84643665e-02 5.33051670e-01 -1.69997013e+00 -1.44324452e-01
3.62084717e-01 7.10676908e-01 -5.30463696e-01 9.21555877e-01
4.45616096e-01 -3.58977020e-02 -5.25507867e-01 -9.90666687e-01
4.70682502e-01 -4.00337249e-01 -5.19281209e-01 6.13065958e-01
9.59563792e-01 -4.60528642e-01 -3.06607753e-01 7.16826200e-01
7.34748781e-01 5.07081635e-02 8.97073746e-01 -1.30968404e+00
-5.58500826e-01 -2.60523617e-01 -8.19400966e-01 7.52786472e-02
9.54237938e-01 5.10138690e-01 6.38357282e-01 -5.46800435e-01
5.98641396e-01 1.56796086e+00 1.11469150e+00 9.33837473e-01
-1.48265219e+00 -3.77837837e-01 -9.71485004e-02 3.67609501e-01
-1.49287462e+00 -5.26757419e-01 8.79244447e-01 -4.19941515e-01
7.64582455e-01 2.80120611e-01 1.00674248e+00 1.46755278e+00
-3.34593393e-02 7.28962481e-01 1.05329955e+00 -4.81446058e-01
1.88704450e-02 -2.55478233e-01 1.75983235e-02 8.63397956e-01
7.33452797e-01 1.22288316e-02 -6.95378482e-01 -1.75714642e-01
8.65958095e-01 -2.64259368e-01 -3.14073652e-01 -8.38124454e-01
-1.18440831e+00 2.81828791e-01 -1.78895414e-01 -2.37721935e-01
-6.49023280e-02 9.36191231e-02 3.95243824e-01 2.04621032e-01
3.28953832e-01 -1.67699546e-01 -1.44573420e-01 -4.68886822e-01
-9.01953816e-01 3.92489195e-01 9.53843474e-01 7.74362087e-01
4.65772361e-01 3.71769853e-02 1.14517614e-01 7.50559926e-01
3.97526830e-01 1.13970387e+00 3.60594749e-01 -7.62654722e-01
5.53654432e-01 3.76340151e-01 2.35529080e-01 -1.24208283e+00
-3.23711038e-01 1.38429865e-01 -8.22251678e-01 7.49553666e-02
8.34539890e-01 -2.73594055e-02 -9.48904991e-01 1.69152164e+00
5.58020592e-01 3.35828245e-01 -1.68764621e-01 9.65645671e-01
6.05006754e-01 -1.31078571e-01 -1.58496499e-01 1.44582018e-01
1.36774027e+00 -4.53710467e-01 -4.03792977e-01 -3.15476775e-01
2.23529994e-01 -4.51239318e-01 9.48563516e-01 4.24595416e-01
-9.20529187e-01 -6.43872678e-01 -1.02153921e+00 1.51061878e-01
-3.68334532e-01 1.60307765e-01 2.96537727e-01 1.42644680e+00
-9.05013263e-01 7.53451943e-01 -1.19316995e+00 -8.96896243e-01
1.64874181e-01 5.29538572e-01 -7.21501410e-01 1.13480434e-01
-9.81370449e-01 8.95564437e-01 2.05009663e-03 1.49244770e-01
-2.43959680e-01 -1.75521776e-01 -1.11809158e+00 -3.93103957e-01
2.19575718e-01 -9.15844202e-01 6.92273557e-01 -4.10914451e-01
-1.43768942e+00 1.39103568e+00 -2.75994658e-01 -2.30693936e-01
9.12988603e-01 -2.56971866e-01 -4.99614805e-01 2.49779165e-01
-7.76633173e-02 3.92440796e-01 1.33221328e+00 -9.17938828e-01
-6.92358464e-02 -8.18241477e-01 -3.47392410e-01 2.19469666e-01
-1.08168103e-01 -3.52708995e-01 -6.75715327e-01 -7.00938225e-01
3.51446941e-02 -1.24754715e+00 1.51605636e-01 3.00884187e-01
-4.24565703e-01 1.04509071e-01 8.47718239e-01 -9.83797848e-01
7.82077968e-01 -1.82088280e+00 2.90090233e-01 3.60448718e-01
-1.41724214e-01 2.00442687e-01 2.38033518e-01 2.81473845e-01
2.36375660e-01 6.16199598e-02 -2.40267381e-01 -7.43484020e-01
3.20758522e-01 4.63797122e-01 1.19883694e-01 8.54117393e-01
6.34875894e-02 6.37097776e-01 -7.70768046e-01 -7.71219134e-01
4.27609771e-01 4.83199060e-01 -4.70110893e-01 6.71627149e-02
4.79355812e-01 6.40803635e-01 -1.09811097e-01 1.06311691e+00
7.20354676e-01 -7.62846470e-02 2.28858426e-01 -4.02921021e-01
4.82198179e-01 -2.74763763e-01 -1.46060288e+00 1.67066061e+00
5.29639311e-02 3.58763754e-01 -1.40910447e-01 -1.14846814e+00
8.86170268e-01 3.36177021e-01 6.30406082e-01 -2.43842319e-01
-3.03819496e-02 2.89986059e-02 -1.29041582e-01 -6.89452589e-01
1.84389964e-01 -1.22848395e-02 -2.33894065e-01 4.25311208e-01
2.14774743e-01 6.24334402e-02 5.16860008e-01 -3.27814996e-01
8.77904654e-01 5.25651813e-01 3.87649268e-01 -9.03159231e-02
5.33787251e-01 -4.63225871e-01 6.94223642e-01 6.97929442e-01
-6.68774486e-01 8.99716735e-01 -6.40318692e-02 -6.24930978e-01
-1.08525574e+00 -1.61436772e+00 -1.86011061e-01 4.21007723e-01
2.21737057e-01 -2.94340879e-01 -6.08193159e-01 -6.24551356e-01
4.61005002e-01 -1.21520512e-01 -7.42823482e-01 -2.12869018e-01
-8.03941905e-01 -8.74847770e-01 8.78871977e-01 8.83127749e-01
9.32726979e-01 -5.19492269e-01 -1.02482581e+00 3.88453132e-03
-4.68285173e-01 -1.35132384e+00 -8.15778792e-01 -5.16147375e-01
-7.67799020e-01 -1.27691567e+00 -9.56310332e-01 -3.16070348e-01
8.16511869e-01 5.84986173e-02 1.36728585e+00 1.56694606e-01
-6.46781564e-01 9.87356484e-01 -2.53102720e-01 -1.89461440e-01
4.98305494e-03 -2.60901511e-01 7.51266956e-01 2.38114581e-01
6.22005522e-01 -6.50925577e-01 -7.26280689e-01 5.71334064e-01
-2.15518624e-01 -6.37908727e-02 1.67324826e-01 9.40951228e-01
3.19957703e-01 -9.05621573e-02 1.09026447e-01 -5.47859371e-01
2.00317755e-01 -1.66226085e-02 -6.32420182e-02 3.44275713e-01
-9.91836861e-02 1.97736081e-02 2.10934535e-01 -5.99491060e-01
-9.23266649e-01 1.66208774e-01 -6.75187856e-02 -4.44803566e-01
-4.66935217e-01 -3.57882194e-02 -3.26236457e-01 -3.27531189e-01
5.53321481e-01 2.75381237e-01 2.86323994e-01 -4.99983609e-01
2.31404722e-01 4.29343522e-01 9.46469009e-01 -9.46446419e-01
1.04438269e+00 8.21871638e-01 3.38890135e-01 -1.03431392e+00
-1.21871307e-01 -5.92170894e-01 -1.40725780e+00 -5.68425477e-01
7.21756935e-01 -6.96908295e-01 -9.73765254e-01 9.17555332e-01
-6.21414959e-01 -2.13936809e-02 -8.99458528e-02 3.74964595e-01
-7.53362894e-01 1.05364621e+00 -4.62372869e-01 -8.93930852e-01
-3.29565734e-01 -8.60775173e-01 1.32445967e+00 2.00323150e-01
-6.70670748e-01 -1.12240279e+00 1.59148499e-01 4.76970762e-01
-2.76069380e-02 7.02230334e-01 4.39786464e-01 -1.07078165e-01
-6.03421358e-03 -2.57996112e-01 2.09658176e-01 3.84789445e-02
6.27965868e-01 4.96244542e-02 -8.68180096e-01 -6.11426175e-01
-4.78334427e-01 -3.58278930e-01 6.39148295e-01 3.98036212e-01
7.07281470e-01 -2.09676430e-01 -3.77767652e-01 6.97947443e-01
1.06183887e+00 -8.05184022e-02 5.53599954e-01 1.56186715e-01
7.83106029e-01 6.41896009e-01 3.63717735e-01 4.86694515e-01
5.35844088e-01 1.06073928e+00 1.17142526e-02 3.59941199e-02
-2.42733181e-01 -2.18243450e-01 4.30032045e-01 4.54889417e-01
-7.36083567e-01 6.66212291e-02 -9.35348392e-01 4.51209873e-01
-1.77991164e+00 -1.11624610e+00 2.13122442e-01 2.51763082e+00
5.92095912e-01 -2.95721609e-02 8.68130744e-01 4.75272894e-01
7.78410673e-01 -1.17598854e-01 -7.41420507e-01 7.54228681e-02
-3.53545398e-02 2.27910757e-01 6.86031282e-01 1.52149931e-01
-1.30513096e+00 5.73310196e-01 6.71420193e+00 1.62826434e-01
-1.00411499e+00 -2.95487553e-01 1.61571190e-01 -6.99543208e-02
4.31301683e-01 -5.23343801e-01 -8.60903084e-01 5.96439958e-01
5.27876318e-01 3.58608402e-02 8.35067555e-02 5.25870442e-01
1.59288906e-02 -7.81526789e-02 -1.33136928e+00 1.47303629e+00
4.70643967e-01 -7.11538196e-01 -8.40624794e-02 9.27099138e-02
2.99437016e-01 -6.82321548e-01 2.44296819e-01 -2.97712013e-02
1.98090792e-01 -6.48738682e-01 4.95724469e-01 4.07520354e-01
9.87414300e-01 -5.17998755e-01 5.79195559e-01 2.60889046e-02
-1.65837324e+00 2.78827101e-01 -2.64259756e-01 9.55109112e-03
2.79248834e-01 1.57224834e-01 -6.49554908e-01 6.63304806e-01
1.03552747e+00 1.04088140e+00 -7.37951577e-01 1.01719713e+00
-2.01244261e-02 5.35402417e-01 -5.70644200e-01 2.89922595e-01
-5.21004975e-01 -2.50305682e-01 6.44755661e-01 1.19696581e+00
4.43972498e-01 -8.14995542e-02 2.44428262e-01 5.29059708e-01
1.33489996e-01 -2.15522245e-01 -7.99150765e-01 1.46163836e-01
3.85718584e-01 8.14936936e-01 -8.08716714e-01 -2.04298824e-01
-3.99297386e-01 1.20009744e+00 -9.07198638e-02 2.30337918e-01
-6.89672232e-01 -2.68600471e-02 8.88310075e-01 2.58543342e-01
3.85185897e-01 -5.61878562e-01 -9.17376578e-02 -1.61030281e+00
2.27216795e-01 -8.73505652e-01 6.23859942e-01 -4.47103024e-01
-1.57791972e+00 -7.60060642e-03 3.22880298e-01 -1.43751550e+00
-5.07233858e-01 -8.10628235e-01 -5.17181396e-01 7.26544499e-01
-8.46457243e-01 -1.47804976e+00 -4.20896858e-01 8.32516134e-01
3.56340647e-01 -2.31901612e-02 9.70381260e-01 3.34733158e-01
-4.45447475e-01 9.61103618e-01 -3.01628947e-01 4.81348574e-01
1.07778811e+00 -1.40453851e+00 9.49745953e-01 9.31914449e-01
2.42330626e-01 5.32269776e-01 9.11760211e-01 -8.13443482e-01
-1.72686172e+00 -7.19486833e-01 4.43498433e-01 -9.06349659e-01
2.56773800e-01 -4.64525998e-01 -7.08044350e-01 7.83173740e-01
-2.66069800e-01 4.42120731e-02 8.44009578e-01 2.26744696e-01
-3.30640137e-01 -6.78718463e-02 -1.45727682e+00 6.06750190e-01
1.51275802e+00 -3.81440580e-01 -7.76476502e-01 -2.08682433e-01
-3.13695490e-01 -6.05734110e-01 -9.52728808e-01 5.08194029e-01
1.20698595e+00 -8.09394956e-01 1.58897424e+00 -4.93841052e-01
-2.67487943e-01 -3.63720775e-01 -1.03871375e-01 -1.29178703e+00
-1.30880117e-01 -3.90798032e-01 -4.30407137e-01 1.05368233e+00
-2.97762930e-01 -5.25238514e-01 1.19737637e+00 8.27695131e-01
4.44663614e-01 -1.62705794e-01 -9.75753009e-01 -1.13043559e+00
-2.33807459e-01 -1.24841049e-01 5.52729547e-01 7.55994499e-01
4.25236002e-02 -9.20907110e-02 -9.42219734e-01 2.12219581e-01
1.30641901e+00 2.94479318e-02 1.32085812e+00 -1.44032657e+00
-5.10302365e-01 -2.08656061e-02 -1.22021210e+00 -9.96822953e-01
9.77940634e-02 -4.23646271e-01 -1.79484531e-01 -1.04717422e+00
1.01005919e-01 -2.15828493e-02 7.04179034e-02 5.65196097e-01
-1.63183570e-01 7.11251736e-01 2.36452684e-01 2.45857447e-01
-2.33391643e-01 2.52219081e-01 1.11735761e+00 -3.45067948e-01
2.13078111e-02 7.35119432e-02 -1.19791508e-01 8.75468075e-01
5.59439659e-01 5.72340004e-02 -3.54673117e-01 -1.32054493e-01
-1.88416302e-01 -8.19054917e-02 6.45446241e-01 -1.28692222e+00
5.60324453e-03 -2.56774314e-02 9.10747588e-01 -7.35848248e-01
8.04094970e-01 -6.76024377e-01 4.07914042e-01 6.89566791e-01
2.51646429e-01 2.59457618e-01 1.48747921e-01 5.83060265e-01
2.34195516e-01 1.93984419e-01 7.37378657e-01 -3.07119370e-01
-9.07818913e-01 3.99664700e-01 -2.42395461e-01 1.72185153e-01
6.84011221e-01 -9.23530936e-01 -1.08978972e-01 -4.24525619e-01
-1.00598311e+00 4.83382195e-02 8.27788532e-01 4.12417859e-01
7.09818542e-01 -1.51139283e+00 -6.82052195e-01 5.83107948e-01
7.51210451e-02 -5.23143351e-01 2.59235799e-01 7.42690444e-01
-5.22757351e-01 7.68449903e-02 -7.22137153e-01 -9.98173296e-01
-1.82433331e+00 2.82053471e-01 4.21046257e-01 -1.88327461e-01
-8.50797117e-01 4.13730592e-01 -1.68382153e-01 -3.43471766e-01
-5.95998950e-02 -1.27997980e-01 -5.05204797e-02 -1.17006645e-01
4.02078062e-01 5.58782458e-01 -3.23090679e-03 -1.14296377e+00
-6.51736438e-01 1.24013078e+00 2.32638434e-01 -1.17389686e-01
8.38480413e-01 -4.41131860e-01 4.76498038e-01 4.91269976e-01
8.99770141e-01 -1.62746832e-01 -1.31728292e+00 -8.75116736e-02
-1.38782844e-01 -9.73421693e-01 -7.34099865e-01 -5.07394910e-01
-9.58521366e-01 8.72360289e-01 8.89401257e-01 -1.04354806e-01
9.19331849e-01 -3.28119814e-01 8.31977963e-01 3.94902885e-01
8.15391421e-01 -1.20303357e+00 2.17104301e-01 2.16334566e-01
5.92250884e-01 -1.28342295e+00 1.24378137e-01 -5.32089710e-01
-4.25928116e-01 1.02768242e+00 5.07840872e-01 -6.68936819e-02
4.57027048e-01 9.84840915e-02 3.14070508e-02 2.34535951e-02
-2.21162096e-01 -3.00508082e-01 5.77783346e-01 1.26026440e+00
2.63462484e-01 1.23262383e-01 -9.18685570e-02 1.39140710e-01
-3.68872076e-01 -1.06415316e-01 2.88779467e-01 1.05859554e+00
4.99197505e-02 -1.33907735e+00 -8.09893548e-01 3.13124120e-01
-3.58670056e-01 5.55342197e-01 -4.70100820e-01 9.22986090e-01
1.45871624e-01 7.52678037e-01 -8.37836042e-03 -5.15371323e-01
4.28591400e-01 2.76720166e-01 1.18445110e+00 -4.44611669e-01
7.12274313e-02 -2.67006487e-01 2.61607081e-01 -4.85350668e-01
-8.74280393e-01 -1.12243927e+00 -7.62466311e-01 -5.69953978e-01
6.11263625e-02 -1.66238368e-01 1.16448209e-01 9.51150775e-01
8.64631161e-02 -1.15135461e-02 2.88533002e-01 -1.36742461e+00
-5.05949020e-01 -6.47271633e-01 -8.31155241e-01 1.13407230e+00
2.78319955e-01 -1.29563951e+00 -1.79690987e-01 7.24287212e-01] | [14.279719352722168, 1.382308006286621] |
0baa8371-ba8d-4f42-ad85-482e3f1e46e5 | boningknife-joint-entity-mention-detection | 2107.09429 | null | https://arxiv.org/abs/2107.09429v1 | https://arxiv.org/pdf/2107.09429v1.pdf | BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge | While named entity recognition (NER) is a key task in natural language processing, most approaches only target flat entities, ignoring nested structures which are common in many scenarios. Most existing nested NER methods traverse all sub-sequences which is both expensive and inefficient, and also don't well consider boundary knowledge which is significant for nested entities. In this paper, we propose a joint entity mention detection and typing model via prior boundary knowledge (BoningKnife) to better handle nested NER extraction and recognition tasks. BoningKnife consists of two modules, MentionTagger and TypeClassifier. MentionTagger better leverages boundary knowledge beyond just entity start/end to improve the handling of nesting levels and longer spans, while generating high quality mention candidates. TypeClassifier utilizes a two-level attention mechanism to decouple different nested level representations and better distinguish entity types. We jointly train both modules sharing a common representation and a new dual-info attention layer, which leads to improved representation focus on entity-related information. Experiments over different datasets show that our approach outperforms previous state of the art methods and achieves 86.41, 85.46, and 94.2 F1 scores on ACE2004, ACE2005, and NNE, respectively. | ['Börje F. Karlsson', 'Chengxi Zhang', 'WEILE CHEN', 'Guoxin Wang', 'Huiqiang Jiang'] | 2021-07-20 | null | null | null | null | ['nested-named-entity-recognition', 'nested-mention-recognition'] | ['natural-language-processing', 'natural-language-processing'] | [-3.92607480e-01 2.43243590e-01 -2.79897362e-01 -4.57790256e-01
-8.08445513e-01 -7.59990811e-01 3.35344225e-01 5.44590592e-01
-8.32306385e-01 7.76759267e-01 5.84978282e-01 -3.49761158e-01
2.72951901e-01 -1.04398489e+00 -7.53164589e-01 -2.37219393e-01
-6.98041767e-02 3.07632983e-01 3.20712835e-01 -9.77445990e-02
-1.70974266e-02 2.34737918e-01 -9.09357905e-01 3.86738211e-01
1.27976608e+00 7.41840839e-01 1.61880434e-01 4.13915128e-01
-6.42264783e-01 6.79614365e-01 -7.12595284e-01 -8.39425266e-01
5.23814410e-02 1.90963551e-01 -1.00116229e+00 -4.65420932e-01
3.10452610e-01 -1.23305671e-01 -3.67075771e-01 9.70720232e-01
4.78714377e-01 2.77254194e-01 5.62735319e-01 -8.34585130e-01
-1.02420890e+00 1.13835669e+00 -6.13272369e-01 3.09370250e-01
2.01161057e-01 -6.86819032e-02 1.33303833e+00 -1.04894173e+00
4.68627721e-01 1.07579672e+00 9.02228355e-01 6.10879123e-01
-8.54245365e-01 -7.54721999e-01 4.57449853e-01 5.77712283e-02
-1.36865604e+00 -3.33164245e-01 2.13072449e-01 -3.05105895e-01
1.23572397e+00 6.27289265e-02 -4.04048711e-02 7.39992976e-01
-1.18799374e-01 9.90463853e-01 5.27312398e-01 -1.77844584e-01
-5.12784161e-02 -2.96841841e-02 6.94461167e-01 5.04322112e-01
6.31907403e-01 -2.61377186e-01 1.26093969e-01 -3.92908491e-02
6.58795476e-01 1.69129577e-02 -2.30217442e-01 6.87874556e-02
-1.28746295e+00 7.29153693e-01 7.61750698e-01 5.91368616e-01
-5.63544512e-01 -6.67821020e-02 4.80097294e-01 -1.92779616e-01
2.32717961e-01 5.31099975e-01 -8.13228548e-01 9.80309099e-02
-8.12415063e-01 2.89870705e-02 9.31033432e-01 1.26649666e+00
7.82557487e-01 -6.73007965e-02 -5.14563084e-01 9.95151043e-01
4.02672142e-01 3.59963775e-01 4.17210966e-01 -2.49561563e-01
8.68359923e-01 1.10457683e+00 1.83425561e-01 -7.41473317e-01
-6.98324740e-01 -5.67159057e-01 -9.41382885e-01 -5.32656968e-01
1.21243551e-01 -6.02984428e-01 -1.14652848e+00 1.75972474e+00
4.19776887e-01 3.22669595e-01 1.11983433e-01 8.08234155e-01
1.36555123e+00 7.41868675e-01 5.43870151e-01 1.29631102e-01
1.70573246e+00 -1.08307290e+00 -7.20112562e-01 -4.71576214e-01
9.44233656e-01 -5.56820095e-01 5.96976101e-01 -3.15713167e-01
-8.54310393e-01 -4.11764860e-01 -8.65521014e-01 -5.18458068e-01
-7.14120686e-01 5.59353411e-01 7.57457674e-01 5.13721228e-01
-5.93213022e-01 3.55817378e-01 -7.40423739e-01 -1.55214205e-01
2.96914846e-01 4.08383727e-01 -4.89608943e-01 2.11428236e-02
-1.70582807e+00 8.76008809e-01 7.56577253e-01 4.73600775e-01
-4.26866412e-01 -9.01188314e-01 -1.29656363e+00 3.25101346e-01
4.46500123e-01 -6.24450684e-01 1.26579130e+00 -2.71590024e-01
-9.07746434e-01 7.06975400e-01 -3.49023312e-01 -5.43398023e-01
1.96296498e-01 -5.55452764e-01 -6.83594584e-01 -3.32714617e-01
3.50786477e-01 5.04204392e-01 2.44090380e-03 -1.13229036e+00
-7.17710614e-01 -1.56387672e-01 2.63978750e-01 1.31263301e-01
-2.48598799e-01 6.95704743e-02 -4.75792587e-01 -6.13242686e-01
-1.28059089e-01 -5.10609150e-01 -5.31463683e-01 -7.92336881e-01
-7.46651232e-01 -5.90119898e-01 3.50194812e-01 -8.28608632e-01
1.79293680e+00 -1.92254448e+00 -1.56642452e-01 -6.28166869e-02
3.26183498e-01 6.40565157e-01 -1.17598310e-01 4.75622535e-01
-2.29553148e-01 6.36252642e-01 -2.09197536e-01 -3.12532902e-01
2.51282275e-01 5.61428517e-02 -1.97460413e-01 6.47210702e-02
5.09197891e-01 1.03995895e+00 -1.00697505e+00 -4.56166863e-01
-1.88900828e-01 5.12822628e-01 -5.30397952e-01 2.81749517e-01
-5.20750247e-02 -1.19676404e-01 -5.38944781e-01 5.51114202e-01
8.49158168e-01 -3.00493389e-01 2.35965893e-01 -2.84185410e-01
-3.88161898e-01 8.15751314e-01 -1.46743107e+00 1.31697285e+00
-6.00989044e-01 1.28870592e-01 -4.43400666e-02 -6.72002733e-01
9.78361368e-01 4.81562674e-01 9.81709510e-02 -3.60785365e-01
3.38825732e-02 2.33418435e-01 -5.98036982e-02 -4.32441682e-01
8.33526194e-01 6.41300753e-02 -4.86408263e-01 4.92392071e-02
2.22731993e-01 7.26988137e-01 4.91497248e-01 3.76615107e-01
1.24845219e+00 -6.68169707e-02 5.72829902e-01 -1.45409822e-01
5.26110172e-01 -1.57374293e-01 1.27895987e+00 6.85144246e-01
-7.90388063e-02 4.65738535e-01 4.50919539e-01 -4.00249720e-01
-7.66966701e-01 -9.35751319e-01 1.24225281e-02 1.19800007e+00
2.20754400e-01 -5.60779870e-01 -6.95538938e-01 -1.12855482e+00
-7.49344975e-02 7.31912076e-01 -7.33472168e-01 2.51471642e-02
-9.00545537e-01 -8.63466084e-01 8.27830017e-01 9.34621990e-01
7.07191288e-01 -1.26306808e+00 -7.92111084e-02 4.41977024e-01
-4.74651128e-01 -1.22140777e+00 -7.93701649e-01 2.88773566e-01
-5.74338377e-01 -9.40299034e-01 -7.16676414e-01 -9.56019938e-01
5.01183212e-01 4.68905009e-02 1.26290858e+00 1.63068473e-01
9.61839780e-03 -2.96266228e-01 -5.72707236e-01 -3.04135501e-01
1.02258205e-01 7.62219429e-01 -1.18256517e-01 -1.04843706e-01
6.25976682e-01 -2.50234634e-01 -4.18530822e-01 1.41285151e-01
-7.63194442e-01 -2.19214022e-01 1.10882390e+00 9.85162854e-01
3.51152390e-01 -2.67463446e-01 6.51359677e-01 -1.29160094e+00
2.36241251e-01 -8.71859491e-01 -2.92012930e-01 3.78491372e-01
-2.81373709e-01 1.37356788e-01 7.83953249e-01 -2.74380594e-01
-1.38466907e+00 -1.07279137e-01 -5.57989359e-01 -1.36518776e-01
-4.69917983e-01 7.49558628e-01 -8.11153650e-01 5.99041343e-01
3.77294064e-01 9.16424766e-02 -9.55406964e-01 -7.84946620e-01
1.89875394e-01 7.09674239e-01 6.31004453e-01 -5.87235272e-01
7.19722211e-01 -4.31721844e-02 -6.15154207e-01 -7.16203451e-01
-1.14858902e+00 -7.97858357e-01 -7.78732002e-01 3.90473217e-01
9.01682675e-01 -1.14026833e+00 -5.57808101e-01 3.37516516e-01
-1.45371878e+00 -4.63595130e-02 -1.09821158e-02 4.17952627e-01
3.06157649e-01 3.17022204e-01 -9.15121019e-01 -6.77088499e-01
-6.15602195e-01 -7.48374522e-01 1.05015504e+00 7.50358641e-01
8.55296180e-02 -8.90364468e-01 5.75989969e-02 2.88873076e-01
1.55762941e-01 1.01016872e-01 8.32587004e-01 -1.33718145e+00
-5.42397797e-01 -1.76889971e-01 -4.92429823e-01 -5.35715558e-02
-1.09724738e-01 -1.59347057e-01 -7.85626709e-01 -1.63167510e-02
-6.64186180e-01 2.18254812e-02 1.12728286e+00 -1.12134852e-01
6.31480277e-01 -5.50478935e-01 -6.64171755e-01 6.54550850e-01
1.41149771e+00 1.55574024e-01 8.58309031e-01 4.80026245e-01
1.00379133e+00 5.03781736e-01 5.44875920e-01 3.11106920e-01
9.69957054e-01 3.57009172e-01 2.35255823e-01 -2.40557268e-01
1.10904135e-01 -3.86416942e-01 2.67750949e-01 9.12754714e-01
7.93191344e-02 -3.62946868e-01 -1.14964283e+00 9.66304958e-01
-1.72820604e+00 -1.02588272e+00 -3.23857963e-01 1.87105215e+00
1.11765194e+00 6.16697893e-02 4.85213548e-02 -2.39795312e-01
1.09824538e+00 9.55456644e-02 -5.56108594e-01 -3.00732166e-01
-1.27786994e-02 1.85516790e-01 6.82949841e-01 2.31464162e-01
-1.54138994e+00 1.07546437e+00 4.79006958e+00 6.52359247e-01
-5.96920192e-01 -4.20448603e-03 3.45858097e-01 5.65957129e-01
-3.68565500e-01 4.82137837e-02 -1.48212755e+00 4.67217803e-01
8.54041457e-01 -2.30209470e-01 -2.39204586e-01 9.81914699e-01
-2.62116432e-01 3.61947119e-01 -9.51667190e-01 5.12739956e-01
-2.79891729e-01 -1.16830873e+00 -5.25293946e-02 1.04722120e-02
6.51116729e-01 1.68038383e-01 -5.05042195e-01 9.52287138e-01
7.35616982e-01 -9.30449009e-01 4.50428694e-01 4.65580434e-01
5.07279694e-01 -8.90765488e-01 1.31503654e+00 3.26032579e-01
-1.78974366e+00 -7.04155713e-02 -3.69839787e-01 3.23069900e-01
2.70063668e-01 8.10411036e-01 -7.05904543e-01 1.00029051e+00
6.30514085e-01 5.29629171e-01 -4.19516832e-01 1.40458310e+00
-4.74697232e-01 6.43999577e-01 -3.53200287e-01 -1.72275528e-01
3.39324564e-01 1.50359049e-01 4.58057225e-01 1.84249985e+00
6.70832396e-02 3.58414859e-01 3.46847057e-01 7.48338997e-01
-5.55480421e-01 2.06530347e-01 -1.07845671e-01 -8.14110860e-02
8.78716350e-01 1.56357455e+00 -6.06378317e-01 -4.12189722e-01
-6.62078857e-01 7.96770096e-01 7.41032958e-01 1.32314071e-01
-1.04233932e+00 -1.04050696e+00 7.83584893e-01 -1.86459094e-01
6.68226004e-01 -2.10046694e-01 -2.82635510e-01 -1.60326302e+00
-5.39642833e-02 -6.31278217e-01 8.01110268e-01 -2.26263732e-01
-1.38711810e+00 7.51846373e-01 -2.91115642e-01 -7.92214334e-01
3.79741229e-02 -5.01694858e-01 -8.07088077e-01 9.24298048e-01
-1.61686885e+00 -1.35099709e+00 -1.50655761e-01 2.24450201e-01
4.69036728e-01 3.16094011e-01 7.35213339e-01 7.11641014e-01
-1.07694364e+00 1.10097694e+00 -8.15262720e-02 1.14180970e+00
6.99042976e-01 -1.60741985e+00 9.45940673e-01 1.09754908e+00
2.81500109e-02 1.22133565e+00 2.13932872e-01 -7.60289967e-01
-1.10325301e+00 -1.43655026e+00 1.41420674e+00 -2.61019856e-01
4.97313946e-01 -4.22499448e-01 -1.18241215e+00 8.24317396e-01
1.61386609e-01 -4.32204902e-02 7.15702474e-01 6.03329241e-01
-6.99781299e-01 2.33533889e-01 -9.18102860e-01 5.27056098e-01
1.03962326e+00 -3.47084761e-01 -1.04439795e+00 -8.72052163e-02
9.89873648e-01 -4.04523343e-01 -1.06975901e+00 4.85893965e-01
2.83950001e-01 -5.65647840e-01 8.39877546e-01 -6.72833920e-01
2.07657441e-01 -3.99544090e-01 3.49990209e-03 -1.21954203e+00
-4.88861918e-01 -3.62593651e-01 -3.32226038e-01 1.94533682e+00
8.97434831e-01 -4.84943837e-01 6.34167671e-01 6.78943038e-01
-3.65107536e-01 -7.94701934e-01 -5.10534823e-01 -7.98242569e-01
2.34945834e-01 -7.00360537e-02 8.95539701e-01 1.17766976e+00
5.81353977e-02 7.71227419e-01 -8.92366990e-02 6.54698312e-01
3.63151282e-01 1.71786427e-01 5.04669368e-01 -1.20447671e+00
3.80934067e-02 -3.04765493e-01 -2.84102917e-01 -1.30727112e+00
2.38284379e-01 -9.41727340e-01 2.25849181e-01 -1.89832306e+00
2.14176282e-01 -6.08982623e-01 -4.02944893e-01 9.49021518e-01
-6.17205024e-01 -1.34800240e-01 1.23889215e-01 9.95548256e-03
-7.48307943e-01 3.94895464e-01 7.55563080e-01 -1.15007237e-01
-1.40025720e-01 -2.56465048e-01 -9.11123931e-01 6.96921527e-01
6.49441063e-01 -5.23257434e-01 2.53587782e-01 -7.34824121e-01
2.56281018e-01 -1.07928202e-01 1.80845242e-02 -8.71161044e-01
4.80663806e-01 1.78162623e-02 4.16023642e-01 -6.96196198e-01
-1.67980000e-01 -4.53515559e-01 -2.29095131e-01 3.70083041e-02
-2.50902712e-01 1.06597349e-01 1.47417590e-01 5.47295451e-01
-2.32820109e-01 -3.75722468e-01 5.54220319e-01 -2.23000184e-01
-1.09043360e+00 5.94096422e-01 1.15240713e-04 5.20460606e-01
8.26549172e-01 6.17268234e-02 -5.10271847e-01 1.74872860e-01
-6.38809860e-01 7.13987350e-01 9.67324972e-02 5.94830394e-01
3.76007378e-01 -1.32264352e+00 -8.03108513e-01 1.66209359e-02
6.66342601e-02 3.44616115e-01 4.41289216e-01 5.91233969e-01
-3.19491774e-01 4.24052298e-01 1.59353614e-01 -9.82102752e-02
-8.98238182e-01 6.17559075e-01 2.59204060e-01 -8.22904646e-01
-4.74907249e-01 1.06833684e+00 3.98749441e-01 -9.42820549e-01
1.61365762e-01 -3.49645466e-01 -6.47136450e-01 2.68644899e-01
7.02807426e-01 2.59031832e-01 1.70832932e-01 -8.23678851e-01
-5.97155988e-01 2.52418935e-01 -5.48939347e-01 3.39644969e-01
1.34168613e+00 -6.20289557e-02 -3.94964814e-02 2.23621503e-01
1.08780718e+00 2.60694176e-01 -8.15087080e-01 -2.54850566e-01
6.14047706e-01 4.32831272e-02 -2.05981046e-01 -8.51709068e-01
-1.06555140e+00 8.44220400e-01 -5.93690388e-03 1.91424146e-01
7.98649907e-01 -1.35314882e-01 1.24443722e+00 5.07530093e-01
2.71027416e-01 -7.91372895e-01 -5.26680052e-01 1.07611763e+00
4.70333487e-01 -1.17622793e+00 -2.58458853e-01 -6.16598368e-01
-6.48502886e-01 7.89692521e-01 1.03644168e+00 -8.45989957e-02
4.63836044e-01 5.12934804e-01 -2.34156754e-02 1.27308637e-01
-8.17534447e-01 -5.54876208e-01 4.34061110e-01 3.70643228e-01
8.42830002e-01 8.10157061e-02 -3.85714471e-01 1.44521666e+00
8.75731930e-02 -2.34757960e-01 3.88914734e-01 8.09245110e-01
-4.45831478e-01 -1.05809867e+00 -1.18472919e-01 4.40459967e-01
-9.78125811e-01 -5.89675128e-01 -2.58007407e-01 8.88948858e-01
3.35164607e-01 9.18921292e-01 -2.48830933e-02 -3.71166646e-01
6.19968772e-01 7.48600662e-02 -1.16587840e-01 -9.14099872e-01
-1.12228596e+00 -2.39774391e-01 4.20726269e-01 -3.11589360e-01
-4.98652980e-02 -5.58414161e-01 -1.65579998e+00 -2.42948085e-01
-9.13355231e-01 6.13500059e-01 3.17212969e-01 9.59586680e-01
6.54020190e-01 6.39064133e-01 4.61032391e-01 -3.50587040e-01
-3.90583187e-01 -1.03652453e+00 -4.11876053e-01 3.32847387e-01
1.62013680e-01 -7.18670487e-01 -1.21677600e-01 -1.18330777e-01] | [9.570478439331055, 9.440321922302246] |
693f1dd6-41ad-4fb7-9b21-e9defce1e75e | graph-collaborative-reasoning | 2112.13705 | null | https://arxiv.org/abs/2112.13705v2 | https://arxiv.org/pdf/2112.13705v2.pdf | Graph Collaborative Reasoning | Graphs can represent relational information among entities and graph structures are widely used in many intelligent tasks such as search, recommendation, and question answering. However, most of the graph-structured data in practice suffers from incompleteness, and thus link prediction becomes an important research problem. Though many models are proposed for link prediction, the following two problems are still less explored: (1) Most methods model each link independently without making use of the rich information from relevant links, and (2) existing models are mostly designed based on associative learning and do not take reasoning into consideration. With these concerns, in this paper, we propose Graph Collaborative Reasoning (GCR), which can use the neighbor link information for relational reasoning on graphs from logical reasoning perspectives. We provide a simple approach to translate a graph structure into logical expressions, so that the link prediction task can be converted into a neural logic reasoning problem. We apply logical constrained neural modules to build the network architecture according to the logical expression and use back propagation to efficiently learn the model parameters, which bridges differentiable learning and symbolic reasoning in a unified architecture. To show the effectiveness of our work, we conduct experiments on graph-related tasks such as link prediction and recommendation based on commonly used benchmark datasets, and our graph collaborative reasoning approach achieves state-of-the-art performance. | ['Yongfeng Zhang', 'He Zhu', 'Shuchang Liu', 'Shaoyun Shi', 'Yunqi Li', 'Hanxiong Chen'] | 2021-12-27 | null | null | null | null | ['relational-reasoning'] | ['natural-language-processing'] | [-2.23453179e-01 4.18215513e-01 -6.64073288e-01 -3.90679538e-01
2.39566699e-01 -2.56392926e-01 3.93051356e-01 4.84341115e-01
3.72580513e-02 4.14659679e-01 7.75545761e-02 -7.52285123e-01
-5.50758958e-01 -1.53988266e+00 -7.22193480e-01 -1.49075314e-03
-1.19126312e-01 4.81598884e-01 5.97486258e-01 -4.30709213e-01
-9.30222794e-02 2.90333629e-01 -1.10786724e+00 2.98759252e-01
1.23690808e+00 1.05319166e+00 -1.82374522e-01 3.55619416e-02
-6.81127489e-01 1.61257184e+00 -2.46764831e-02 -9.78042305e-01
-2.63635758e-02 -4.20664757e-01 -1.04427910e+00 -4.18713152e-01
-8.84829909e-02 -9.21823308e-02 -6.90991700e-01 1.17706168e+00
3.14159244e-02 1.34956986e-01 3.15241635e-01 -1.39596224e+00
-1.08812666e+00 1.21844459e+00 -1.93284243e-01 -1.44222304e-01
5.34669042e-01 -3.70905727e-01 1.47441745e+00 -6.04367435e-01
6.06495857e-01 1.40501797e+00 6.61817908e-01 1.99857816e-01
-9.81302500e-01 -6.15771055e-01 6.55402601e-01 6.97031021e-01
-1.40148115e+00 -2.69801859e-02 1.05560565e+00 -2.88202435e-01
9.18639779e-01 1.34148568e-01 8.57907832e-01 4.06544834e-01
-3.67756151e-02 8.48855376e-01 5.68692088e-01 -1.68992653e-01
-5.16297668e-02 1.20323546e-01 3.46700877e-01 1.15149164e+00
2.74254918e-01 -2.66253769e-01 -3.30726415e-01 5.29253967e-02
5.93303025e-01 2.47842014e-01 -3.54550123e-01 -4.16696131e-01
-9.93791342e-01 8.32638562e-01 1.20369172e+00 2.87318587e-01
-1.25265479e-01 1.37695581e-01 3.51060599e-01 5.81581354e-01
3.02079976e-01 3.05155039e-01 -2.08806723e-01 5.80875039e-01
-2.14449480e-01 4.07556817e-02 1.04300189e+00 9.51322258e-01
8.29174638e-01 -2.44690001e-01 1.54114515e-02 8.34675014e-01
8.30224812e-01 2.28807509e-01 2.21984521e-01 -5.64497113e-01
6.36557341e-01 1.34866226e+00 -3.75535607e-01 -1.58956671e+00
-3.44224662e-01 -3.18528295e-01 -8.36925328e-01 -3.42744946e-01
8.14257041e-02 8.81606713e-02 -4.26338553e-01 1.64420485e+00
3.22027683e-01 3.32181245e-01 1.25595659e-01 7.55907297e-01
1.37573361e+00 5.80451548e-01 5.13586551e-02 -1.44458473e-01
1.02940965e+00 -1.11613488e+00 -7.47276604e-01 -2.35559288e-02
7.86747456e-01 -2.20792621e-01 7.60151207e-01 1.55506492e-01
-8.87987971e-01 -4.74128813e-01 -1.06574070e+00 -1.93669498e-01
-6.74088418e-01 -2.45671645e-01 1.02713656e+00 2.52151340e-01
-8.93680215e-01 6.54302239e-01 -5.25938690e-01 -4.04174060e-01
4.12346423e-01 4.07236069e-01 -3.26697111e-01 -2.37541929e-01
-1.67746377e+00 8.49196970e-01 7.93828785e-01 4.32178915e-01
-9.36703831e-02 -3.30271333e-01 -9.26059544e-01 2.84868002e-01
9.45857882e-01 -7.69063413e-01 6.70387626e-01 -6.07976437e-01
-1.37642634e+00 3.83234650e-01 1.49114072e-01 -4.43653077e-01
3.06890339e-01 4.56788279e-02 -8.47706199e-01 -1.32042155e-01
-2.31087089e-01 2.49916688e-01 1.82309449e-01 -1.02930009e+00
-5.13175726e-01 -2.73118526e-01 6.52578473e-01 1.54344559e-01
-5.57337403e-01 -2.51594424e-01 -8.13952386e-01 -4.24357653e-01
4.08383727e-01 -6.54190123e-01 1.96737032e-02 -6.49923906e-02
-5.63260376e-01 -6.72429860e-01 5.85423768e-01 -4.94026095e-01
1.59037423e+00 -1.69000709e+00 3.12038004e-01 5.14979720e-01
4.65752631e-01 3.31075817e-01 4.80667548e-03 5.26333869e-01
-4.62279730e-02 2.39933833e-01 2.09559500e-01 2.49876648e-01
1.08383723e-01 3.31662804e-01 -5.88122368e-01 -1.23979405e-01
-6.46102950e-02 1.31201243e+00 -1.00397468e+00 -7.13680267e-01
3.73719595e-02 9.29548591e-02 -6.06875837e-01 2.81002074e-01
-6.92854404e-01 4.87202071e-02 -8.39815319e-01 6.88048363e-01
3.45494658e-01 -5.68702698e-01 6.23888552e-01 -6.93881512e-01
3.48675698e-01 3.48635256e-01 -1.19158471e+00 1.55302382e+00
-2.96967953e-01 1.52494028e-01 -3.95184875e-01 -1.12621236e+00
1.10613549e+00 6.91378787e-02 2.99472541e-01 -7.19690323e-01
-9.03622136e-02 1.80209547e-01 2.29675561e-01 -6.52531385e-01
8.08459520e-02 -1.69118363e-02 2.72518605e-01 2.90581465e-01
-8.63167569e-02 1.88672066e-01 2.64398307e-01 4.39498037e-01
1.21331942e+00 2.52932131e-01 1.79247931e-01 1.66926891e-01
8.52201402e-01 1.07748108e-02 5.55381417e-01 3.61875415e-01
2.66552716e-01 -2.00723305e-01 8.31862271e-01 -5.67481935e-01
-2.83106476e-01 -9.27086353e-01 2.79887378e-01 8.79651546e-01
5.25001645e-01 -8.64370823e-01 -2.83810407e-01 -9.03955042e-01
1.25988021e-01 5.42560756e-01 -3.90127093e-01 -4.01197642e-01
-5.33893466e-01 -4.28242683e-01 4.53422874e-01 6.82351351e-01
6.51205659e-01 -1.17873430e+00 2.91972071e-01 1.79841056e-01
-1.17600299e-01 -1.10595810e+00 -7.36395642e-02 -2.20745876e-01
-8.80267799e-01 -1.32726073e+00 4.08164486e-02 -7.97201037e-01
6.70630515e-01 2.43574485e-01 1.19915116e+00 7.99465537e-01
3.15641403e-01 2.08251610e-01 -3.68149549e-01 -2.47847307e-02
-2.74881124e-01 1.66714951e-01 -2.24699199e-01 3.88949662e-02
3.08675677e-01 -7.38022029e-01 -2.83650726e-01 3.76043051e-01
-7.81622589e-01 2.50213057e-01 6.60108447e-01 7.66611397e-01
5.41414797e-01 5.15228510e-01 7.13814497e-01 -1.40118623e+00
9.14018154e-01 -5.50515413e-01 -6.50856853e-01 8.77360940e-01
-9.95619833e-01 3.14744562e-01 8.94989252e-01 -1.06120385e-01
-1.01179397e+00 -3.66441220e-01 1.58764683e-02 -4.91119504e-01
3.75885516e-01 1.42937124e+00 -5.59096992e-01 -1.54947922e-01
2.54182696e-01 -8.71239007e-02 -9.76322144e-02 -3.18378001e-01
5.33432186e-01 3.56114060e-01 3.12171608e-01 -7.25399375e-01
9.51333165e-01 1.74055114e-01 3.00825626e-01 -2.24657819e-01
-9.57581043e-01 -9.30220708e-02 -4.92776841e-01 -1.03823565e-01
6.99229777e-01 -7.15776205e-01 -1.11075079e+00 -6.05305843e-02
-1.09921300e+00 -3.19560289e-01 1.96059346e-01 4.44627374e-01
-1.45620525e-01 3.98872733e-01 -6.81127608e-01 -5.98412097e-01
-2.55806834e-01 -9.53672707e-01 2.42013931e-01 2.09730282e-01
9.37485173e-02 -1.24498069e+00 -9.25242454e-02 4.63724583e-01
1.66559458e-01 -5.72217023e-03 1.57520711e+00 -7.84755826e-01
-1.00143468e+00 -2.15377837e-01 -5.78313589e-01 -2.85593187e-03
2.00878121e-02 -4.51676622e-02 -3.63688052e-01 1.01960458e-01
-5.65062225e-01 -3.59695435e-01 7.10287929e-01 -2.42382646e-01
1.31685221e+00 -3.43897581e-01 -5.49390554e-01 4.55158770e-01
1.32364416e+00 1.59735009e-01 6.16453886e-01 1.14299789e-01
1.14633918e+00 6.52767062e-01 5.60745776e-01 -8.48321617e-02
9.25834835e-01 5.43677032e-01 5.50075650e-01 1.87155917e-01
3.96692194e-03 -8.88985991e-01 1.51188327e-02 1.08359265e+00
-3.46027374e-01 -2.89213240e-01 -9.19434011e-01 8.66314024e-02
-2.47974467e+00 -8.89520109e-01 -2.51491874e-01 1.91790676e+00
7.58240521e-01 3.76236379e-01 -6.52791411e-02 -1.08748592e-01
7.12336361e-01 1.06732361e-01 -6.65812790e-01 1.96096208e-02
1.60501987e-01 -1.53374746e-01 1.73143193e-01 4.71946746e-01
-8.44048917e-01 1.09460723e+00 5.17891693e+00 6.73624337e-01
-9.54733491e-01 -2.10054487e-01 2.51543939e-01 3.93307537e-01
-6.54249787e-01 2.94614911e-01 -4.24618751e-01 2.96472102e-01
5.58577418e-01 -2.24410206e-01 8.36104155e-01 7.77204990e-01
-2.17319041e-01 3.57813060e-01 -1.28505158e+00 9.86782968e-01
-4.15831357e-02 -1.41851330e+00 3.61366242e-01 -9.56525877e-02
4.48177040e-01 -2.31982991e-01 -3.47352654e-01 7.97642231e-01
5.08272350e-01 -1.15348637e+00 4.09384608e-01 9.32117403e-01
2.18436256e-01 -6.15267634e-01 7.77646601e-01 3.40656459e-01
-1.58360302e+00 -1.48132443e-01 -4.61000502e-01 -6.74196258e-02
-3.40000279e-02 5.68335354e-01 -6.04154944e-01 1.29034746e+00
4.84378666e-01 1.11346471e+00 -7.73066044e-01 8.51472735e-01
-7.13249862e-01 4.57145333e-01 -8.31054151e-02 -3.36623460e-01
-1.52697444e-01 -4.45688933e-01 4.39393148e-02 5.87880492e-01
1.22292057e-01 2.54101604e-01 4.27482933e-01 1.10413647e+00
-4.93115216e-01 2.94919312e-01 -5.99760115e-01 -2.40566999e-01
6.16495967e-01 1.18525887e+00 -8.50480855e-01 -1.88094974e-01
-7.75937855e-01 5.03970563e-01 8.46323669e-01 4.28884238e-01
-8.72138023e-01 -4.01193470e-01 4.52398434e-02 1.15795627e-01
1.98481277e-01 -3.35410312e-02 -3.65203507e-02 -1.43404984e+00
2.09823936e-01 -7.29481637e-01 7.71251678e-01 -9.26091850e-01
-1.44334555e+00 4.62471604e-01 4.75043021e-02 -9.59812045e-01
-1.23591669e-01 -6.22725189e-01 -7.46162891e-01 6.95372820e-01
-1.53454816e+00 -1.32698107e+00 -5.16432285e-01 5.92441320e-01
-2.23140568e-01 -2.74184614e-01 6.71500027e-01 4.54171389e-01
-6.86124384e-01 4.13378060e-01 -4.28190500e-01 5.18030882e-01
4.00589764e-01 -1.11843789e+00 1.59777507e-01 5.55161655e-01
3.56865078e-01 9.45389092e-01 1.73138961e-01 -8.15186799e-01
-1.81695521e+00 -1.16610515e+00 9.01698828e-01 -1.41610041e-01
1.08763063e+00 -1.10885084e-01 -1.16690779e+00 9.60298002e-01
-1.12377435e-01 3.94059509e-01 6.47366226e-01 5.88379920e-01
-5.23516178e-01 -3.57987136e-01 -6.90560639e-01 8.04705977e-01
1.52490020e+00 -6.35711491e-01 -6.51128948e-01 3.12420011e-01
9.29497540e-01 -2.66245186e-01 -1.14066184e+00 5.20995915e-01
3.75628382e-01 -8.94145072e-01 9.78311956e-01 -8.34568322e-01
4.94402975e-01 -6.47969067e-01 -2.44318303e-02 -1.12291300e+00
-4.06883538e-01 -1.85225889e-01 -6.25465751e-01 1.44765782e+00
4.86871511e-01 -8.93704176e-01 7.64334083e-01 6.67495728e-01
-5.78597840e-03 -1.12732720e+00 -3.65737230e-01 -4.69412267e-01
-3.94786865e-01 -2.91599393e-01 8.57371509e-01 1.26753342e+00
3.52453470e-01 8.22366238e-01 -1.41707629e-01 2.51288831e-01
2.67856210e-01 7.07306206e-01 6.78284526e-01 -1.52064800e+00
-4.43911403e-01 -5.90773225e-01 -5.08613169e-01 -1.03546083e+00
5.78427970e-01 -1.39433575e+00 -4.21206295e-01 -2.13092041e+00
-2.16827472e-03 -6.31965280e-01 -4.26694453e-01 8.08972836e-01
-2.10464790e-01 -2.70673186e-01 5.04692420e-02 3.31346482e-01
-9.43227351e-01 6.21385694e-01 1.30266166e+00 -4.64841872e-01
-3.07781082e-02 -7.39512444e-02 -8.43716562e-01 7.96596766e-01
3.62020284e-01 -9.61338133e-02 -1.08204913e+00 -5.70472062e-01
9.17872131e-01 3.58888358e-01 3.11567932e-01 -8.01958084e-01
6.87516212e-01 -3.34621102e-01 1.38858721e-01 -4.23808992e-01
-3.98029275e-02 -1.04638720e+00 3.32736939e-01 4.04371887e-01
-3.63708913e-01 -1.44324094e-01 -2.14113325e-01 7.69260168e-01
-3.78615320e-01 -1.39083102e-01 9.97089669e-02 -9.51190013e-03
-9.74651754e-01 5.94580054e-01 4.60026026e-01 -5.21738566e-02
7.88866401e-01 1.65779084e-01 -4.49145406e-01 -3.66723478e-01
-6.75518572e-01 6.67007148e-01 2.07704008e-01 4.37698126e-01
5.55247307e-01 -1.65511584e+00 -3.01021576e-01 -8.09745193e-02
1.98941559e-01 1.69048399e-01 1.12426072e-01 8.53083849e-01
-5.45652092e-01 3.53812963e-01 1.04825549e-01 -1.79825515e-01
-8.46108675e-01 8.73197556e-01 4.65043485e-01 -4.88925785e-01
-5.83402932e-01 5.69699764e-01 -2.01021507e-02 -6.97846115e-01
2.67632544e-01 -2.43177205e-01 -6.04777515e-01 -1.00211322e-01
1.75741240e-01 1.61222473e-01 2.59871818e-02 -2.71883756e-01
-3.07467192e-01 4.23507750e-01 -9.63631738e-03 5.10393500e-01
1.14801383e+00 7.68521950e-02 -5.60424030e-01 3.99159759e-01
9.15923953e-01 7.25408923e-03 -5.51839888e-01 -6.57916665e-01
2.07320735e-01 -1.69963762e-01 5.56193199e-03 -6.88218296e-01
-1.29387057e+00 7.57421434e-01 -1.23608083e-01 6.40089273e-01
8.84010315e-01 1.18703432e-01 7.03587413e-01 1.01052380e+00
4.44770366e-01 -7.80889392e-01 -2.32135244e-02 5.34755170e-01
6.70140386e-01 -1.07711422e+00 2.34502673e-01 -9.28123474e-01
-3.80024731e-01 1.29197776e+00 8.58105004e-01 -5.08949794e-02
8.49287629e-01 -1.60446510e-01 -2.98905641e-01 -3.66993964e-01
-7.71772265e-01 -2.87177294e-01 5.72482109e-01 3.56540114e-01
5.49536526e-01 -2.02014484e-02 -3.47866535e-01 9.23659682e-01
3.16010639e-02 2.68208295e-01 -7.55804554e-02 6.06243432e-01
-2.51904637e-01 -1.27706647e+00 1.20646462e-01 6.11664653e-01
2.90905330e-02 -6.35106638e-02 -4.29387033e-01 6.41026616e-01
1.29879683e-01 8.36182714e-01 -2.22757205e-01 -7.08513558e-01
3.92378598e-01 -1.35824950e-02 3.73491228e-01 -5.84545493e-01
-2.21966788e-01 -4.46047872e-01 3.26144725e-01 -5.15735328e-01
-4.82951790e-01 -1.03922263e-01 -1.67302728e+00 -5.11512518e-01
-4.15473223e-01 3.10579449e-01 1.65493920e-01 1.12136149e+00
2.81322509e-01 8.75695050e-01 3.10918599e-01 -2.96646580e-02
-3.03433895e-01 -6.12902284e-01 -5.97558916e-01 4.71760273e-01
-3.77817899e-01 -8.54045093e-01 7.10936561e-02 -2.65130132e-01] | [8.957550048828125, 7.779364109039307] |
8f052b9e-a5a5-4164-9ece-918548d5debb | 3d-human-pose-estimation-with-spatial-and | 2103.10455 | null | https://arxiv.org/abs/2103.10455v3 | https://arxiv.org/pdf/2103.10455v3.pdf | 3D Human Pose Estimation with Spatial and Temporal Transformers | Transformer architectures have become the model of choice in natural language processing and are now being introduced into computer vision tasks such as image classification, object detection, and semantic segmentation. However, in the field of human pose estimation, convolutional architectures still remain dominant. In this work, we present PoseFormer, a purely transformer-based approach for 3D human pose estimation in videos without convolutional architectures involved. Inspired by recent developments in vision transformers, we design a spatial-temporal transformer structure to comprehensively model the human joint relations within each frame as well as the temporal correlations across frames, then output an accurate 3D human pose of the center frame. We quantitatively and qualitatively evaluate our method on two popular and standard benchmark datasets: Human3.6M and MPI-INF-3DHP. Extensive experiments show that PoseFormer achieves state-of-the-art performance on both datasets. Code is available at \url{https://github.com/zczcwh/PoseFormer} | ['Zhengming Ding', 'Chen Chen', 'Taojiannan Yang', 'Matias Mendieta', 'Sijie Zhu', 'Ce Zheng'] | 2021-03-18 | 3d-human-pose-estimation-with-spatial-and-1 | http://openaccess.thecvf.com//content/ICCV2021/html/Zheng_3D_Human_Pose_Estimation_With_Spatial_and_Temporal_Transformers_ICCV_2021_paper.html | http://openaccess.thecvf.com//content/ICCV2021/papers/Zheng_3D_Human_Pose_Estimation_With_Spatial_and_Temporal_Transformers_ICCV_2021_paper.pdf | iccv-2021-1 | ['monocular-3d-human-pose-estimation'] | ['computer-vision'] | [-3.25878322e-01 -1.66204885e-01 1.87302724e-01 -4.05345708e-01
-5.93786538e-01 -4.13006157e-01 4.33488846e-01 -1.41764477e-01
-7.01386511e-01 1.43382221e-01 1.79914951e-01 8.29595476e-02
1.56668007e-01 -3.61040384e-01 -6.98368728e-01 -2.94036478e-01
-1.32992074e-01 6.88031554e-01 4.28366542e-01 -1.99676886e-01
-1.25907049e-01 3.07661951e-01 -1.22355032e+00 8.59059393e-02
3.80111694e-01 1.22658038e+00 1.26575246e-01 6.80058241e-01
4.12990361e-01 7.26432204e-01 -3.94132704e-01 -6.29952490e-01
2.74826884e-01 -2.51940310e-01 -1.05651927e+00 3.70121628e-01
5.45400262e-01 -4.56803352e-01 -7.23199189e-01 8.41170609e-01
6.79051161e-01 1.36541441e-01 3.85905027e-01 -1.15927315e+00
-9.18739438e-02 2.09953442e-01 -7.98776627e-01 3.32002252e-01
6.02609336e-01 2.67923981e-01 7.67507315e-01 -1.07992792e+00
7.14044690e-01 1.44451737e+00 7.75204659e-01 3.70488256e-01
-8.73847008e-01 -5.46772718e-01 1.55738711e-01 4.43710744e-01
-1.45583785e+00 -2.88616359e-01 7.01257944e-01 -5.44308662e-01
8.85986030e-01 1.85926676e-01 1.02381766e+00 1.24090981e+00
2.62817591e-01 1.34169209e+00 8.54015231e-01 -2.28427172e-01
-1.72756895e-01 -5.04634857e-01 -1.07738316e-01 1.08245254e+00
-6.93296492e-02 6.41840100e-02 -8.75329375e-01 1.91372961e-01
1.03309679e+00 -2.01953262e-01 -2.87134767e-01 -5.90299129e-01
-1.55554712e+00 5.72068870e-01 6.77541018e-01 1.26021385e-01
-3.98648769e-01 6.21951163e-01 4.44143534e-01 -1.99330121e-01
5.14280736e-01 9.91606042e-02 -4.20032442e-01 -1.82605520e-01
-8.35690200e-01 6.38554513e-01 3.84994626e-01 9.98241723e-01
2.06038132e-01 -2.59014726e-01 -3.26739728e-01 6.15217686e-01
4.27813888e-01 6.19129181e-01 1.59493625e-01 -1.27378464e+00
3.34822178e-01 4.28505808e-01 2.32744738e-01 -9.63583708e-01
-6.10589862e-01 -5.48490822e-01 -7.21391976e-01 -1.21067502e-01
7.26885796e-01 8.23739246e-02 -9.84835029e-01 1.49593854e+00
6.04484916e-01 6.34579733e-02 -6.30438030e-01 1.35946810e+00
9.40317333e-01 3.52960438e-01 2.39477772e-02 2.34518141e-01
1.60509861e+00 -1.12966049e+00 -4.85909998e-01 -3.16431791e-01
2.12519467e-01 -7.78228581e-01 7.44456291e-01 4.90552843e-01
-1.25340748e+00 -6.93885922e-01 -6.82911873e-01 -4.51088667e-01
-9.32862088e-02 3.36398154e-01 6.15275204e-01 3.01826239e-01
-9.25927758e-01 4.07435656e-01 -1.27005672e+00 -4.72446322e-01
5.77295005e-01 2.57732719e-01 -4.12920117e-01 9.75781232e-02
-1.05676723e+00 8.44525933e-01 1.40061095e-01 4.47797865e-01
-9.33448076e-01 -3.86255682e-01 -8.78314793e-01 -3.29884887e-01
4.83993769e-01 -1.02231908e+00 1.69474924e+00 -4.26816732e-01
-1.30981874e+00 1.16545570e+00 -8.92340243e-02 -4.93041545e-01
9.81439829e-01 -8.21744502e-01 1.41271994e-01 2.61725694e-01
3.20154369e-01 1.02366483e+00 6.82689369e-01 -9.05534148e-01
-6.20934188e-01 -5.72453260e-01 4.01476249e-02 2.86821544e-01
-2.74070539e-02 1.80213675e-01 -1.24152327e+00 -6.27443314e-01
2.31038645e-01 -1.18004262e+00 -3.39806408e-01 4.04219061e-01
-5.92014432e-01 -4.58316594e-01 5.88594496e-01 -6.97754741e-01
9.62321162e-01 -1.80088282e+00 5.88896096e-01 1.00162867e-02
4.07087862e-01 2.53418565e-01 1.09297425e-01 5.55907898e-02
1.62675172e-01 -4.36339885e-01 -6.17670193e-02 -8.86486590e-01
1.17297359e-01 -6.38352334e-02 6.95291013e-02 8.13807845e-01
-4.69306037e-02 1.29387856e+00 -8.56856108e-01 -6.87671006e-01
6.70859694e-01 7.73831427e-01 -4.14488077e-01 2.33249366e-01
-1.56896368e-01 7.70890474e-01 -4.82157916e-01 7.53292203e-01
3.54973435e-01 -4.76907074e-01 -1.79722541e-04 -4.75411892e-01
4.58920887e-03 -2.65824515e-02 -1.01854324e+00 2.19282508e+00
-3.12727015e-03 6.27281129e-01 4.99354210e-03 -7.87276208e-01
3.74669760e-01 3.29497904e-01 7.68157780e-01 -6.19459450e-01
6.13005579e-01 1.09449282e-01 -2.37739712e-01 -4.45520520e-01
4.52880472e-01 3.07536662e-01 -1.38610587e-01 -2.38602720e-02
2.45490655e-01 -8.64006281e-02 3.01507115e-01 7.02643618e-02
8.73945236e-01 4.80954379e-01 2.95038819e-01 -1.88789561e-01
3.38092029e-01 -2.92852242e-02 3.61142427e-01 3.36507618e-01
-4.87515420e-01 9.75508153e-01 2.54000843e-01 -7.37320006e-01
-8.67956817e-01 -1.31285727e+00 2.97564752e-02 9.45543110e-01
2.92026073e-01 -6.06824398e-01 -8.70354772e-01 -5.28807580e-01
-1.09520964e-01 -1.51774185e-02 -6.54645026e-01 1.93916127e-01
-7.77312040e-01 -4.38847661e-01 6.70978367e-01 7.43416250e-01
7.22262800e-01 -1.03411162e+00 -1.22676349e+00 8.30467790e-02
-8.19619477e-01 -1.36357129e+00 -7.06511974e-01 -2.01881044e-02
-5.34409702e-01 -1.27095175e+00 -1.13703930e+00 -6.24032557e-01
3.47972095e-01 1.09518595e-01 1.21348548e+00 -1.34715989e-01
-7.40114868e-01 5.69929898e-01 -2.15345904e-01 -2.76803136e-01
3.57726961e-01 2.34009102e-02 6.83081597e-02 -1.04155794e-01
1.76196620e-01 -2.64898002e-01 -9.63920355e-01 4.45533484e-01
-4.86163706e-01 2.04067782e-01 2.99685150e-01 5.79478681e-01
5.83061099e-01 -2.11412489e-01 -1.82062835e-01 -5.15033305e-01
1.80970147e-01 6.38882071e-02 -5.65629482e-01 4.77966592e-02
7.51006305e-02 -2.02768579e-01 3.00453473e-02 -1.99830845e-01
-8.56228113e-01 4.27643925e-01 -3.27145249e-01 -7.74326205e-01
-2.63181895e-01 2.76579171e-01 -8.78893398e-03 1.23226397e-01
5.82470894e-01 5.73336668e-02 -7.27335662e-02 -4.91799355e-01
2.84956902e-01 2.12549120e-01 8.90282452e-01 -4.93027270e-01
6.21200740e-01 7.20137179e-01 4.65317704e-02 -7.10971832e-01
-1.03521156e+00 -7.85796046e-01 -8.62525463e-01 -5.99123120e-01
1.31632543e+00 -1.11277223e+00 -9.35306847e-01 8.85012269e-01
-1.43436337e+00 -3.38938773e-01 3.27232741e-02 5.00226200e-01
-7.87811279e-01 2.17170343e-01 -8.03254247e-01 -5.59487402e-01
-4.33578938e-01 -1.33881593e+00 1.71171880e+00 1.33145884e-01
-5.16763926e-01 -7.98246443e-01 -9.61738527e-02 6.96143448e-01
-1.88038945e-02 4.93187666e-01 2.35943735e-01 2.46705338e-02
-5.64345658e-01 -2.69567162e-01 -2.90691741e-02 1.30102396e-01
-1.65496290e-01 -3.20100635e-01 -8.71057391e-01 -3.50425750e-01
-3.55007827e-01 -3.67471695e-01 8.67213309e-01 7.86092103e-01
1.18505538e+00 1.74777791e-01 -5.14143169e-01 7.05191851e-01
8.48597288e-01 -2.24726126e-01 6.42642200e-01 2.07624465e-01
1.02322507e+00 6.60699368e-01 6.41075015e-01 5.15732586e-01
5.21270037e-01 1.05421937e+00 4.14844483e-01 -1.01589471e-01
-2.02961862e-01 -2.98959672e-01 1.94397956e-01 4.85581815e-01
-4.84542400e-01 -2.50451148e-01 -1.13348556e+00 3.89578789e-01
-1.98581970e+00 -8.09110582e-01 -2.32418120e-01 1.91731167e+00
4.73142862e-01 2.09811240e-01 4.25536424e-01 3.29414904e-02
4.73498434e-01 1.62943080e-01 -3.59208673e-01 4.27802742e-01
1.30423710e-01 2.60800004e-01 4.31372792e-01 3.54476690e-01
-1.60122752e+00 1.04453552e+00 5.36037111e+00 6.31533623e-01
-9.32465374e-01 1.78556621e-01 6.51022673e-01 -2.71041155e-01
4.60991621e-01 -4.63227242e-01 -6.94981158e-01 2.10346714e-01
2.33149037e-01 1.97457179e-01 8.93498957e-02 6.27553523e-01
2.52322853e-01 -2.01248318e-01 -1.21218622e+00 1.40529001e+00
-2.41103023e-02 -9.98464704e-01 -2.08502829e-01 -3.45330723e-02
4.76634532e-01 7.60738701e-02 2.18897343e-01 4.01090756e-02
-1.26785472e-01 -1.08796680e+00 1.23733282e+00 4.81617630e-01
6.17221177e-01 -6.91589177e-01 6.49156511e-01 3.25041622e-01
-1.59079087e+00 2.46286854e-01 1.44771533e-02 2.50426605e-02
3.97874206e-01 4.48109031e-01 -5.31480372e-01 4.56905484e-01
1.41189635e+00 9.17685568e-01 -7.46453345e-01 1.14127493e+00
-3.34988654e-01 2.29696780e-01 -3.10759515e-01 2.21715480e-01
9.45914984e-02 1.64265141e-01 5.55413485e-01 1.14492595e+00
1.47177398e-01 2.06008837e-01 4.58905458e-01 6.04310811e-01
2.53466256e-02 -3.24018210e-01 -2.54451662e-01 1.26046002e-01
1.52964219e-01 1.22721994e+00 -1.02331984e+00 -1.33611083e-01
-1.64618984e-01 1.29411912e+00 2.20373198e-01 2.45165199e-01
-1.11705530e+00 -4.47103381e-03 6.48930788e-01 3.47958922e-01
2.66442090e-01 -5.99925697e-01 1.59164164e-02 -1.04016864e+00
2.62355387e-01 -8.09659719e-01 3.39740425e-01 -8.57468784e-01
-9.52118576e-01 5.58122098e-01 3.35113376e-01 -1.26114798e+00
-3.67631018e-01 -8.20788026e-01 -1.40777782e-01 5.08644998e-01
-8.72752190e-01 -1.29710579e+00 -5.26484728e-01 8.11128676e-01
7.08804131e-01 1.53306901e-01 5.60154080e-01 3.92721295e-01
-3.35073441e-01 4.92517054e-01 -5.04306853e-01 5.97185552e-01
5.69578409e-01 -1.13939762e+00 6.73367321e-01 8.10336769e-01
3.11097264e-01 4.64446634e-01 8.01620245e-01 -4.45588261e-01
-1.39735866e+00 -9.70360994e-01 7.77867258e-01 -7.50181735e-01
3.56091619e-01 -5.54714322e-01 -3.25590909e-01 7.06774056e-01
1.82972565e-01 2.74016678e-01 1.42741084e-01 -1.12565383e-01
-2.21147701e-01 8.21917877e-02 -8.08864832e-01 6.31309092e-01
1.37642205e+00 -3.39130640e-01 -3.08353513e-01 4.25688773e-01
5.25936067e-01 -1.05238855e+00 -5.96754074e-01 5.01520276e-01
7.62453020e-01 -1.10614657e+00 1.27309704e+00 -1.71182722e-01
3.47598702e-01 -4.07999367e-01 -1.49298370e-01 -1.03037620e+00
-3.51847440e-01 -5.05141914e-01 -1.88098550e-01 5.38946986e-01
-1.04660176e-01 -1.50724530e-01 1.03720355e+00 1.89983770e-01
-2.04755925e-02 -9.98518467e-01 -1.06599653e+00 -6.18737459e-01
-1.10198952e-01 -5.41781545e-01 -1.89789498e-04 3.97321701e-01
-2.55841166e-01 3.38462383e-01 -5.41893899e-01 1.73381060e-01
9.92395282e-01 -9.91407856e-02 8.94015014e-01 -1.03267109e+00
-3.80681813e-01 -4.84375566e-01 -6.95108354e-01 -1.46385777e+00
-6.61156103e-02 -5.02290249e-01 2.74199873e-01 -1.56578803e+00
2.22245604e-01 1.00120924e-01 8.86649862e-02 3.83816481e-01
-4.33398485e-02 6.00810766e-01 3.50953072e-01 1.10364994e-02
-9.87592697e-01 5.86677313e-01 1.39020109e+00 -1.75820872e-01
2.01142609e-01 1.89375505e-02 -8.15558955e-02 8.91414881e-01
7.23543823e-01 -1.35973319e-01 -3.77637804e-01 -6.34192348e-01
-4.08073142e-02 1.50164753e-01 9.08974767e-01 -1.34386027e+00
2.75771469e-01 6.24705739e-02 7.57719576e-01 -8.61476183e-01
7.28759944e-01 -6.23347640e-01 2.49183655e-01 7.11627841e-01
-1.41736299e-01 3.39017719e-01 9.43869725e-02 3.28956574e-01
-1.23849839e-01 4.20386106e-01 8.64883959e-01 -3.84003699e-01
-9.54785705e-01 6.55317903e-01 -6.81793317e-02 2.14885458e-01
9.35629547e-01 1.71377172e-03 -1.21158604e-02 -4.04711455e-01
-7.61631310e-01 4.46515292e-01 2.04950437e-01 7.35913932e-01
8.52175713e-01 -1.30080557e+00 -7.18678057e-01 -9.57604572e-02
1.50474355e-01 3.19443971e-01 2.58759499e-01 1.13967848e+00
-8.05636883e-01 6.48163617e-01 -1.90962434e-01 -1.01455867e+00
-1.38068688e+00 1.99887514e-01 6.56033933e-01 -2.05673411e-01
-6.67577624e-01 1.26806748e+00 4.49722201e-01 -3.67079318e-01
5.04511356e-01 -4.23362613e-01 2.61432361e-02 -1.72838360e-01
3.99127573e-01 4.08323377e-01 -1.53098600e-02 -1.03012073e+00
-6.96221650e-01 7.44437575e-01 1.31235942e-01 -2.18313903e-01
1.04261613e+00 -1.28514975e-01 2.44805850e-02 3.22396338e-01
1.19251895e+00 -4.31755245e-01 -1.36096072e+00 -2.56678611e-01
-2.06417978e-01 -4.15483534e-01 -1.73058167e-01 -4.92919087e-01
-1.30009472e+00 9.72319543e-01 7.19154298e-01 -2.76562929e-01
9.87766564e-01 3.95650178e-01 8.47143233e-01 2.23203257e-01
7.91268289e-01 -1.02735925e+00 5.65741599e-01 6.20490909e-01
9.85609889e-01 -1.18839741e+00 5.57446070e-02 -6.20181382e-01
-4.68815982e-01 7.83749461e-01 8.21353376e-01 -1.45253822e-01
7.16926098e-01 1.19307823e-01 1.26797795e-01 -3.98649722e-01
-3.70180875e-01 -4.33223516e-01 6.32935882e-01 4.55646396e-01
7.49286234e-01 1.22903578e-01 -9.24151242e-02 3.13098967e-01
-3.34062010e-01 3.67652066e-02 -4.19588126e-02 1.00844479e+00
-2.25655511e-01 -9.23668265e-01 -4.99180138e-01 9.67910439e-02
-4.51211452e-01 2.18473822e-01 -3.33787829e-01 7.32460201e-01
3.21101516e-01 7.66159117e-01 -1.53778940e-02 -4.71081644e-01
5.30763149e-01 -3.04476529e-01 9.53932106e-01 -4.18177426e-01
-3.90940070e-01 3.05395752e-01 -2.61180513e-02 -1.00076699e+00
-6.16067052e-01 -7.22195148e-01 -1.37317836e+00 -3.19917202e-01
3.00254561e-02 -2.14254156e-01 3.33953977e-01 9.46372569e-01
2.49700118e-02 5.96888065e-01 -4.91205379e-02 -1.36123705e+00
-2.81640261e-01 -8.97461236e-01 -3.50531667e-01 4.41980124e-01
1.93096802e-01 -1.04805410e+00 1.69802532e-01 2.04724252e-01] | [7.1348185539245605, -0.7319750189781189] |
1b1441ba-86e3-4ed1-9f9f-983b0dc7b80a | premise-based-multimodal-reasoning-a-human | 2105.07122 | null | https://arxiv.org/abs/2105.07122v3 | https://arxiv.org/pdf/2105.07122v3.pdf | Premise-based Multimodal Reasoning: Conditional Inference on Joint Textual and Visual Clues | It is a common practice for recent works in vision language cross-modal reasoning to adopt a binary or multi-choice classification formulation taking as input a set of source image(s) and textual query. In this work, we take a sober look at such an unconditional formulation in the sense that no prior knowledge is specified with respect to the source image(s). Inspired by the designs of both visual commonsense reasoning and natural language inference tasks, we propose a new task termed Premise-based Multi-modal Reasoning(PMR) where a textual premise is the background presumption on each source image. The PMR dataset contains 15,360 manually annotated samples which are created by a multi-phase crowd-sourcing process. With selected high-quality movie screenshots and human-curated premise templates from 6 pre-defined categories, we ask crowd-source workers to write one true hypothesis and three distractors (4 choices) given the premise and image through a cross-check procedure. Besides, we generate adversarial samples to alleviate the annotation artifacts and double the size of PMR. We benchmark various state-of-the-art (pretrained) multi-modal inference models on PMR and conduct comprehensive experimental analyses to showcase the utility of our dataset. | ['Zhongyu Wei', 'Sujian Li', 'Weidong Zhan', 'Zuifang Sui', 'Tianyu Liu', 'Lin Xu', 'Haoran Meng', 'Shoujie Tong', 'Tian Feng', 'Heming Xia', 'Ziwei Qin', 'Qingxiu Dong'] | 2021-05-15 | null | https://aclanthology.org/2022.acl-long.66 | https://aclanthology.org/2022.acl-long.66.pdf | acl-2022-5 | ['visual-commonsense-reasoning'] | ['reasoning'] | [ 5.44256151e-01 4.22991812e-02 6.91659749e-02 -4.03704971e-01
-1.02579594e+00 -7.45489478e-01 8.93717349e-01 -2.68599272e-01
-5.46224654e-01 6.48051679e-01 5.56188934e-02 -5.03335655e-01
2.06049979e-01 -6.01035774e-01 -9.39681232e-01 -4.67974752e-01
7.98557401e-01 4.66913491e-01 3.13830823e-01 -3.26907903e-01
2.75784791e-01 1.20491534e-01 -1.57616901e+00 8.23019326e-01
7.18988597e-01 9.90219355e-01 2.69041955e-01 7.85058320e-01
1.87147319e-01 1.33342719e+00 -9.44788039e-01 -1.41620672e+00
3.50525081e-01 -5.29709756e-01 -9.53717232e-01 3.97871286e-01
8.20017874e-01 -2.88106054e-01 -2.93477803e-01 1.29525220e+00
5.68738997e-01 1.77581161e-01 7.50497282e-01 -1.47381508e+00
-1.42613578e+00 4.82681185e-01 -7.82544494e-01 3.26731712e-01
7.21738219e-01 7.20585763e-01 9.60426211e-01 -1.08560181e+00
7.31135309e-01 1.38571048e+00 4.01796490e-01 6.88125134e-01
-1.15444446e+00 -4.72307831e-01 1.36362061e-01 2.62102008e-01
-1.49077761e+00 -5.86756289e-01 8.37000906e-01 -6.01642251e-01
4.90024626e-01 4.02337492e-01 4.13833886e-01 1.58692944e+00
6.86564390e-03 8.01701725e-01 1.50772476e+00 -4.49185431e-01
2.65764445e-01 5.03076851e-01 -1.68405801e-01 7.35645056e-01
8.62680667e-04 -1.13959059e-01 -5.20244718e-01 -1.74473956e-01
6.37300253e-01 -1.56973258e-01 -4.76241350e-01 -9.54040606e-03
-1.41189110e+00 7.18123496e-01 4.57352340e-01 -3.28019895e-02
-3.24615330e-01 -1.03848912e-01 1.55420229e-01 2.62633804e-02
1.32281706e-02 1.47856802e-01 3.26458849e-02 4.14965421e-01
-8.18310022e-01 3.83169770e-01 5.47828972e-01 1.04033482e+00
7.28563905e-01 -2.46482655e-01 -6.93666816e-01 7.32690215e-01
2.77196854e-01 7.62708306e-01 2.90764809e-01 -1.20789266e+00
6.22785449e-01 5.26318312e-01 3.15033734e-01 -1.21433628e+00
3.64806831e-01 8.96276254e-03 -8.65009487e-01 2.32692182e-01
6.56582355e-01 -3.15508954e-02 -7.47566164e-01 1.54201591e+00
2.90117264e-01 -5.93175925e-03 3.56349200e-01 1.21154416e+00
1.00746298e+00 3.54462624e-01 4.81393933e-03 -7.94513598e-02
1.52656043e+00 -1.01132810e+00 -5.88245809e-01 -3.11454564e-01
-1.05959088e-01 -7.80249178e-01 1.59399438e+00 3.91975939e-01
-1.03989506e+00 -6.70545578e-01 -8.35282326e-01 -3.90435636e-01
-3.97977799e-01 3.35927546e-01 1.95560485e-01 5.21222472e-01
-8.80135000e-01 -1.09981500e-01 -1.36575952e-01 9.11138281e-02
6.15534127e-01 -3.81278843e-01 -3.02500755e-01 -5.24749577e-01
-1.25163209e+00 9.17556584e-01 2.67326057e-01 1.66997358e-01
-1.40144670e+00 -5.91417134e-01 -8.40313077e-01 -4.35812652e-01
7.38541007e-01 -8.90416801e-01 1.22082424e+00 -1.24232233e+00
-1.20416200e+00 1.68213272e+00 -3.19089323e-01 -3.62510741e-01
9.34107065e-01 -1.34939954e-01 -3.88406515e-01 3.97049665e-01
4.11854714e-01 7.15356827e-01 1.24894440e+00 -1.75876093e+00
-4.77429211e-01 -3.07305038e-01 7.55407512e-01 1.39551491e-01
2.90265471e-01 1.20801523e-01 -6.06146455e-01 -6.88240409e-01
-4.13490444e-01 -8.92970741e-01 3.08573898e-02 1.94659323e-01
-8.53271842e-01 -1.34100392e-01 4.00498271e-01 -5.88717341e-01
8.44617069e-01 -2.16948080e+00 1.71495065e-01 -2.62359023e-01
3.28361273e-01 1.13485172e-01 -5.29744942e-03 6.67503327e-02
8.20880234e-02 3.19544263e-02 -2.88598567e-01 -4.75336492e-01
1.19549647e-01 2.55513430e-01 -8.55669141e-01 4.39826280e-01
4.21664387e-01 1.04477727e+00 -1.03427768e+00 -9.84008908e-01
1.72360092e-01 4.00368333e-01 -2.03902081e-01 3.42748165e-01
-5.35280466e-01 3.11699688e-01 -1.21956378e-01 8.26280653e-01
5.39946020e-01 -4.74711746e-01 -2.97212809e-01 -4.37996149e-01
2.55616546e-01 -1.75574660e-01 -9.63046253e-01 1.60745382e+00
-2.35338315e-01 7.35501230e-01 -1.03323385e-01 -5.08761525e-01
6.50387824e-01 2.28857741e-01 -2.41113067e-01 -5.64321816e-01
1.41046658e-01 -1.03286751e-01 -1.54999167e-01 -7.92429745e-01
4.39515829e-01 -3.07987928e-01 -1.28131270e-01 2.70962447e-01
2.53718700e-02 -2.18472570e-01 2.76906341e-01 5.43939412e-01
8.20084631e-01 5.15686627e-03 2.25097090e-01 1.31104216e-01
7.99584389e-01 2.29292318e-01 4.34506267e-01 9.70244408e-01
-5.77006280e-01 8.40196431e-01 5.39888382e-01 -1.77571997e-01
-8.15082192e-01 -1.19351816e+00 1.43207669e-01 1.24721730e+00
2.43514210e-01 -1.56364098e-01 -6.20222092e-01 -6.35413826e-01
-1.57659680e-01 9.69143093e-01 -9.87202346e-01 2.27185577e-01
-1.23429127e-01 -4.18873817e-01 8.63124073e-01 3.17474812e-01
9.68527913e-01 -1.22178912e+00 -8.60327661e-01 -5.62882066e-01
-6.40634477e-01 -1.42271221e+00 -4.90200698e-01 -3.72088820e-01
1.05110608e-01 -1.30636239e+00 -7.43124962e-01 -5.66375971e-01
7.06048071e-01 4.12277013e-01 1.44971478e+00 -3.48026194e-02
-2.14157999e-01 7.02746451e-01 -4.07903731e-01 -4.38775718e-01
-5.38716555e-01 -7.23395646e-01 -1.73223585e-01 5.21165967e-01
3.43712509e-01 -7.10804462e-02 -4.63769585e-01 2.73306221e-01
-1.01270044e+00 2.96072155e-01 6.07470095e-01 6.59868836e-01
6.91808403e-01 8.27187523e-02 2.62267977e-01 -7.60788620e-01
7.50371754e-01 -3.96708459e-01 -4.57078725e-01 7.14936554e-01
-8.23951960e-02 -2.27556601e-01 5.63722193e-01 -7.07797706e-01
-1.31633437e+00 -1.08477399e-01 3.11566263e-01 -1.07576215e+00
-3.41723561e-01 1.97905108e-01 -4.52934861e-01 2.30489731e-01
8.85947406e-01 4.75435138e-01 -2.00014204e-01 1.26572311e-01
8.10217619e-01 5.25957286e-01 1.09213424e+00 -7.83767283e-01
8.57614517e-01 7.06124365e-01 -2.70116717e-01 -5.90452492e-01
-1.32035935e+00 -2.13492721e-01 -5.30272603e-01 -4.88667518e-01
1.34547246e+00 -1.09256828e+00 -9.13199425e-01 3.98128301e-01
-1.48114669e+00 -3.49374533e-01 -3.82947586e-02 -1.66543052e-01
-5.64350843e-01 1.06477000e-01 -2.47516543e-01 -1.12481904e+00
-1.11983836e-01 -1.22102332e+00 1.23543549e+00 1.88322350e-01
3.26709300e-02 -7.63162613e-01 -3.20055753e-01 1.09329295e+00
1.09639473e-01 2.94418305e-01 6.94862008e-01 -4.35745746e-01
-7.16941416e-01 1.10752262e-01 -4.80834842e-01 3.57016146e-01
-7.38773048e-02 5.16471043e-02 -1.20767725e+00 4.74065468e-02
1.26259789e-01 -8.09183776e-01 7.75933683e-01 -8.03794414e-02
1.10455251e+00 -3.23447555e-01 5.45760766e-02 2.30785847e-01
1.49000108e+00 -2.61161961e-02 6.80691957e-01 1.87290162e-01
8.14151168e-01 6.30758703e-01 6.65822327e-01 2.43900776e-01
7.50776410e-01 3.57376009e-01 4.27317083e-01 7.74074122e-02
-2.01436579e-01 -3.29955637e-01 3.04615915e-01 3.47429402e-02
-5.30757234e-02 -4.33829963e-01 -1.07149684e+00 5.81125796e-01
-1.73094237e+00 -1.38791299e+00 -6.54058717e-03 1.97278941e+00
1.19413078e+00 1.76380605e-01 5.58027066e-02 -2.87153642e-03
8.19626629e-01 2.34284058e-01 -6.93795621e-01 1.67945683e-01
-5.61337590e-01 -3.48030150e-01 1.45591363e-01 4.64430660e-01
-1.08633435e+00 7.93737411e-01 5.54656935e+00 8.18667531e-01
-9.29937422e-01 1.96899220e-01 7.95184076e-01 -1.41690046e-01
-4.03827280e-01 -1.55289978e-01 -7.20985234e-01 4.04797554e-01
3.66852164e-01 3.93461660e-02 6.28504157e-01 6.88064456e-01
-7.53594190e-02 -5.20247698e-01 -1.13729095e+00 1.38793230e+00
6.14454687e-01 -1.38424015e+00 3.14731032e-01 -2.75096595e-01
7.94121444e-01 -2.04846904e-01 3.48074317e-01 3.29674482e-01
4.40113693e-01 -1.14704216e+00 1.07433283e+00 8.16567719e-01
9.56044376e-01 -3.28705490e-01 5.13328016e-01 5.61929405e-01
-8.56604815e-01 -7.23438710e-03 -1.21818483e-01 -3.80133055e-02
1.52563661e-01 3.80064189e-01 -6.16549909e-01 5.05669773e-01
8.26258600e-01 3.43043476e-01 -9.70825791e-01 4.47955728e-01
-5.18587232e-01 2.45932341e-01 1.01249166e-01 5.98076507e-02
1.35246618e-02 -4.82625961e-02 5.06891787e-01 1.03062069e+00
-4.14880872e-01 1.41750723e-01 -3.42645124e-02 1.40844131e+00
-2.18085542e-01 -3.61011833e-01 -6.29392147e-01 1.72469065e-01
4.81318682e-01 1.20621884e+00 -5.18746555e-01 -5.49584448e-01
-4.73058760e-01 1.28826058e+00 3.63903999e-01 6.80319846e-01
-1.19739950e+00 -1.22212313e-01 3.55467111e-01 -1.11273244e-01
3.25555325e-01 1.04872286e-01 -2.28916705e-01 -1.25518191e+00
2.69802362e-01 -1.19748747e+00 4.28626180e-01 -1.54131413e+00
-1.79885769e+00 6.06904268e-01 1.23209089e-01 -9.74245906e-01
-6.05516396e-02 -7.03827977e-01 -5.09553671e-01 1.04198933e+00
-1.51313877e+00 -1.38724196e+00 -5.33945680e-01 9.77145433e-01
6.79191291e-01 -1.27261028e-01 5.58404565e-01 1.28756449e-01
-4.97966200e-01 4.48204756e-01 -7.43271530e-01 4.53703254e-01
7.89040148e-01 -1.26141202e+00 2.48030033e-02 1.09300005e+00
3.56970608e-01 8.20742011e-01 8.28925550e-01 -6.30586982e-01
-1.38894367e+00 -1.25808501e+00 5.51445782e-01 -1.12491167e+00
7.54406035e-01 -2.62647927e-01 -8.52810740e-01 7.82289982e-01
5.41056633e-01 3.13243598e-01 6.74406886e-01 -3.47716153e-01
-7.20002294e-01 1.23693138e-01 -1.06610179e+00 8.67048144e-01
9.53326225e-01 -9.93068933e-01 -1.05446446e+00 3.59735817e-01
8.36991668e-01 -5.98841369e-01 -4.85439360e-01 9.41178799e-02
2.48780772e-01 -1.24447346e+00 1.07029021e+00 -6.23074889e-01
9.45899487e-01 -5.97515225e-01 -6.09506786e-01 -8.98326337e-01
1.06854789e-01 -4.03216809e-01 -3.10950121e-03 1.36676347e+00
3.42962384e-01 -2.62120396e-01 2.15860426e-01 8.31947029e-01
2.40248606e-01 -6.67466283e-01 -6.75727308e-01 -4.53597546e-01
-1.55061319e-01 -5.40609002e-01 2.87463516e-01 9.00042772e-01
-4.51743215e-01 6.98664606e-01 -3.80162746e-01 3.58110636e-01
7.76793003e-01 3.69020462e-01 9.71702278e-01 -7.56802797e-01
-4.49420124e-01 -2.67680138e-01 2.36573238e-02 -9.74369824e-01
4.12061006e-01 -5.80405772e-01 8.41991752e-02 -1.36260784e+00
4.43293005e-01 -6.41878620e-02 -2.37080939e-02 4.42115307e-01
-4.42904770e-01 4.73436445e-01 3.58141541e-01 2.54824787e-01
-1.00901473e+00 5.05565822e-01 1.41302109e+00 -3.87363225e-01
1.46666601e-01 -1.82424575e-01 -8.31804276e-01 7.46116400e-01
4.53523993e-01 -6.49119169e-02 -6.56691551e-01 -6.31122172e-01
4.90862072e-01 2.11692154e-01 1.25645268e+00 -6.75550938e-01
3.19140762e-01 -4.11153942e-01 4.18343484e-01 -6.79933488e-01
5.28567910e-01 -6.86895490e-01 2.69082915e-02 -8.44892040e-02
-5.87911665e-01 2.22252607e-02 -6.06797561e-02 7.98743904e-01
-9.88667756e-02 -1.32843971e-01 6.68162107e-01 -4.07050908e-01
-8.28842461e-01 1.37605760e-02 7.33443871e-02 5.19890606e-01
1.08296323e+00 -1.43654957e-01 -7.88463831e-01 -2.99006343e-01
-5.06374419e-01 1.53580159e-01 6.04942560e-01 4.15043622e-01
9.35032785e-01 -1.21502829e+00 -7.35702991e-01 -1.69157550e-01
4.01606619e-01 1.62056565e-01 3.63320887e-01 7.77362943e-01
-2.48298228e-01 1.72065675e-01 -1.63553908e-01 -5.78341484e-01
-1.03232157e+00 9.99221683e-01 4.60861593e-01 3.54049206e-01
-4.04901564e-01 1.04833210e+00 1.58429518e-01 -1.33161336e-01
1.83110580e-01 -9.23956782e-02 1.16040735e-02 -8.57360382e-03
8.77724290e-01 1.50246620e-01 -4.05997396e-01 -9.73997116e-01
-4.03013408e-01 1.87675491e-01 2.06213534e-01 -4.53010440e-01
6.85521305e-01 -2.14418277e-01 -2.22454533e-01 9.37817097e-01
8.55733454e-01 1.74784139e-01 -1.32070947e+00 -4.53904867e-01
-4.71693009e-01 -6.61202371e-01 -2.42885694e-01 -1.05817330e+00
-8.50878954e-01 8.05780292e-01 1.13531612e-01 8.77221003e-02
1.10766244e+00 3.45100582e-01 3.93905878e-01 3.52665395e-01
3.04120690e-01 -8.38739753e-01 4.84478503e-01 1.67865068e-01
1.23504913e+00 -1.86182702e+00 -2.81683654e-01 -1.85364857e-01
-1.28717065e+00 6.20966613e-01 8.22256267e-01 5.64191714e-02
2.47622892e-01 -1.17417462e-02 3.06933403e-01 -2.70308256e-01
-7.69150019e-01 -4.58796591e-01 3.80027533e-01 8.04711342e-01
3.52754481e-02 2.94890106e-02 3.71984094e-01 7.60134220e-01
-2.03460351e-01 -6.76562488e-02 3.73259932e-01 5.54419935e-01
-6.34251088e-02 -3.44659418e-01 -6.79471254e-01 1.55478954e-01
-3.60890925e-01 -1.96729586e-01 -6.79375112e-01 6.01731956e-01
3.61535072e-01 1.33328164e+00 -1.61757633e-01 -2.21237063e-01
1.67795643e-01 3.52396513e-04 5.83822548e-01 -4.26309049e-01
-3.91857177e-01 -4.12402421e-01 -3.58963795e-02 -4.40479189e-01
-7.56330490e-01 -5.40929198e-01 -9.83335257e-01 -1.08359449e-01
-1.90897696e-02 -3.74160290e-01 2.04225600e-01 1.24850941e+00
1.52311713e-01 5.22521913e-01 1.15526415e-01 -6.62936807e-01
-5.26907980e-01 -8.78848970e-01 -9.94184315e-02 9.30881977e-01
5.04828393e-01 -7.03211248e-01 -3.46518338e-01 6.96575820e-01] | [10.750039100646973, 1.6436680555343628] |
edff9c71-0f1b-40e8-985d-998497fcec01 | 2d-3d-facial-expression-recognition-via-1 | 2201.12506 | null | https://arxiv.org/abs/2201.12506v1 | https://arxiv.org/pdf/2201.12506v1.pdf | 2D+3D facial expression recognition via embedded tensor manifold regularization | In this paper, a novel approach via embedded tensor manifold regularization for 2D+3D facial expression recognition (FERETMR) is proposed. Firstly, 3D tensors are constructed from 2D face images and 3D face shape models to keep the structural information and correlations. To maintain the local structure (geometric information) of 3D tensor samples in the low-dimensional tensors space during the dimensionality reduction, the $\ell_0$-norm of the core tensors and a tensor manifold regularization scheme embedded on core tensors are adopted via a low-rank truncated Tucker decomposition on the generated tensors. As a result, the obtained factor matrices will be used for facial expression classification prediction. To make the resulting tensor optimization more tractable, $\ell_1$-norm surrogate is employed to relax $\ell_0$-norm and hence the resulting tensor optimization problem has a nonsmooth objective function due to the $\ell_1$-norm and orthogonal constraints from the orthogonal Tucker decomposition. To efficiently tackle this tensor optimization problem, we establish the first-order optimality condition in terms of stationary points, and then design a block coordinate descent (BCD) algorithm with convergence analysis and the computational complexity. Numerical results on BU-3DFE database and Bosphorus databases demonstrate the effectiveness of our proposed approach. | ['Jun Wan', 'Yi Jin', 'Gaoyun An', 'Ziyan Luo', 'Qiuqi Ruan', 'Yunfang Fu'] | 2022-01-29 | null | null | null | null | ['3d-facial-expression-recognition', 'facial-expression-recognition'] | ['computer-vision', 'computer-vision'] | [-3.00211996e-01 -1.11098453e-01 -2.11206526e-01 -2.88833499e-01
-3.28231990e-01 -7.42057115e-02 5.40493522e-03 -5.40393829e-01
-9.20836441e-03 3.21836233e-01 1.64590001e-01 -1.04621053e-01
-6.02362871e-01 -1.64484382e-01 -3.99673402e-01 -1.06411505e+00
-3.98963124e-01 1.77999567e-02 -6.59761369e-01 -3.07362020e-01
1.63177967e-01 6.98099494e-01 -1.44141603e+00 -1.45398006e-01
7.34134495e-01 1.40492964e+00 -3.47447991e-01 8.42240825e-02
-2.25033432e-01 6.89549208e-01 -8.14403147e-02 -3.93097043e-01
3.66094798e-01 -1.03945665e-01 -6.72165573e-01 7.99968660e-01
5.52666426e-01 -2.96325415e-01 -3.36481005e-01 1.23352599e+00
3.27719808e-01 3.40846092e-01 6.08405590e-01 -1.29683983e+00
-5.82827330e-01 -1.30022198e-01 -1.03868496e+00 7.05151632e-02
1.94320410e-01 -1.77254379e-01 1.02938700e+00 -1.37591875e+00
5.50306082e-01 1.36522257e+00 3.40407550e-01 2.66879827e-01
-1.18028200e+00 -5.65464497e-01 2.58492172e-01 2.24166960e-01
-1.58998001e+00 -5.77965438e-01 1.38373864e+00 -6.35448337e-01
5.27258813e-01 3.96165460e-01 5.63392878e-01 6.44361198e-01
-1.70377374e-01 7.81197906e-01 9.38056350e-01 -1.88574240e-01
-9.00946110e-02 -1.21650554e-01 2.38581851e-01 1.10773325e+00
-1.07538819e-01 -3.10732871e-01 -5.15900195e-01 -4.13306952e-01
7.88217068e-01 -4.22363281e-02 -2.74867147e-01 -4.41712111e-01
-9.20578480e-01 8.36896241e-01 2.19819590e-01 3.78633350e-01
-6.34045720e-01 -1.07889146e-01 4.40931350e-01 9.27913785e-02
7.33708501e-01 -2.40435258e-01 -7.82426149e-02 -2.13625412e-02
-7.19827950e-01 1.55504644e-01 2.96044230e-01 9.36321974e-01
9.02726471e-01 4.75104898e-01 1.25060558e-01 1.21784246e+00
7.04840600e-01 6.12946689e-01 1.57752827e-01 -1.07163334e+00
6.46126986e-01 8.58051836e-01 -1.40605763e-01 -1.74755800e+00
-3.50102872e-01 -3.43502909e-01 -1.10220814e+00 -1.18502587e-01
3.51002902e-01 1.10267945e-01 -4.72536474e-01 1.56964278e+00
7.51556635e-01 1.80962756e-01 -1.62051767e-01 1.40344560e+00
4.22390670e-01 5.72138667e-01 -3.12015444e-01 -6.62497103e-01
1.38727260e+00 -4.59950715e-01 -1.01140547e+00 3.68898809e-01
8.32431614e-01 -9.49859083e-01 8.00988257e-01 2.93163538e-01
-9.78841603e-01 -4.33118075e-01 -8.66731763e-01 -1.13127068e-01
2.91818768e-01 4.97050524e-01 7.04966843e-01 4.67837572e-01
-5.54176509e-01 2.19254419e-01 -7.94182420e-01 1.49465665e-01
3.55099767e-01 4.63966340e-01 -7.57709622e-01 -2.47322142e-01
-7.48456717e-01 3.89466017e-01 -6.85372353e-02 8.54933143e-01
-5.25677800e-01 -6.70104682e-01 -7.27287948e-01 -2.91001290e-01
3.46224457e-01 -2.46976867e-01 4.86650378e-01 -6.72911465e-01
-1.61418498e+00 8.29223096e-01 -3.91349167e-01 4.40389633e-01
6.96169809e-02 -1.59962941e-02 -2.92066574e-01 3.34635526e-01
-9.69063397e-03 -1.32486448e-01 1.22795343e+00 -1.08396745e+00
-5.08039407e-02 -9.79399025e-01 -1.33602768e-01 2.89130598e-01
-5.85003436e-01 1.48362905e-01 -3.21983457e-01 -7.51435101e-01
7.73343623e-01 -1.13731897e+00 -9.16031525e-02 6.93636686e-02
-2.98949629e-01 -1.19579256e-01 1.02158785e+00 -9.46462810e-01
1.23663521e+00 -2.35740614e+00 7.54704356e-01 6.26049936e-01
4.69094694e-01 1.77883744e-01 -2.79324293e-01 -2.61543598e-03
-4.01740521e-01 -2.13179156e-01 -1.21756501e-01 -3.98326069e-01
-1.47092104e-01 2.34748155e-01 1.97203029e-02 7.78326333e-01
1.79744914e-01 2.60194987e-01 -6.41469657e-01 -5.06304145e-01
7.32880235e-02 6.48540378e-01 -7.50035703e-01 2.29967520e-01
1.20996110e-01 5.98343551e-01 -9.78698969e-01 7.97135711e-01
1.13085282e+00 7.90076777e-02 8.13306868e-02 -8.18966746e-01
-1.35249108e-01 -2.62381881e-01 -1.56371975e+00 1.62586641e+00
-2.89713711e-01 5.70335761e-02 8.79784822e-01 -1.47778702e+00
1.18079174e+00 3.14574152e-01 1.17197156e+00 -4.53120083e-01
4.16315883e-01 2.38603011e-01 -6.03776984e-02 -6.84710264e-01
8.18229094e-02 -1.79912373e-01 3.53339612e-01 3.53228271e-01
5.23356833e-02 1.73061967e-01 8.63394588e-02 -2.59351172e-02
5.92812121e-01 9.90499258e-02 -3.09970766e-01 -5.52820206e-01
1.10772550e+00 -2.18846381e-01 7.95989990e-01 -3.49204183e-01
-8.54857415e-02 1.06426872e-01 7.22298503e-01 -6.68890834e-01
-8.82553458e-01 -5.34229517e-01 -4.22668219e-01 8.52240682e-01
-2.28471801e-01 -4.28955197e-01 -7.71830261e-01 -5.42588472e-01
-8.15116018e-02 2.20277324e-01 -6.04841650e-01 -1.62037805e-01
-6.46785796e-01 -9.30451989e-01 2.56391317e-01 5.44003807e-02
5.81517339e-01 -2.23780006e-01 1.47059828e-01 -2.27125231e-02
-2.28667185e-01 -1.03231168e+00 -7.13066399e-01 -3.89863133e-01
-1.03969765e+00 -9.28957224e-01 -7.32999802e-01 -5.27897656e-01
1.03910553e+00 3.95245224e-01 2.61078775e-01 1.43413410e-01
-2.54983455e-01 3.73224229e-01 -2.16829434e-01 1.78623572e-01
5.51207885e-02 -5.28346658e-01 5.14419317e-01 9.79177773e-01
2.91948557e-01 -6.96619093e-01 -4.69376892e-01 5.28176904e-01
-9.29997861e-01 -1.64936304e-01 2.80178845e-01 1.10266876e+00
7.25274265e-01 1.11069210e-01 4.14930098e-02 -1.85733959e-01
6.37248635e-01 -2.55406082e-01 -8.43112588e-01 1.09870927e-02
-2.67809838e-01 5.74132428e-02 4.72659707e-01 -4.23460454e-01
-9.41518009e-01 2.93452907e-02 8.81883726e-02 -1.24715054e+00
4.74855483e-01 7.18156636e-01 -4.79734957e-01 -3.54540050e-01
2.41046652e-01 4.85137045e-01 4.55262065e-01 -7.36098111e-01
3.38210434e-01 4.99976307e-01 2.16578096e-02 -8.68951201e-01
8.50842595e-01 5.79066992e-01 5.03793359e-01 -1.24247682e+00
-8.31632197e-01 -3.53342503e-01 -8.54158401e-01 -3.35938066e-01
7.14337647e-01 -7.74662733e-01 -1.14222848e+00 4.60695237e-01
-9.39154506e-01 4.57982063e-01 1.75399512e-01 7.99976349e-01
-4.11413193e-01 8.18235815e-01 -5.28319418e-01 -9.96886551e-01
-2.69145548e-01 -1.38177586e+00 9.71219897e-01 -2.21974790e-01
1.14985280e-01 -8.09242189e-01 -1.04910322e-01 8.06755841e-01
8.22161064e-02 4.17353779e-01 9.63154554e-01 1.32608280e-01
-4.52920377e-01 -2.41077557e-01 -2.81106293e-01 7.40312338e-01
1.81667432e-01 1.99187547e-01 -6.08311057e-01 -2.61215389e-01
4.57004279e-01 -3.96679640e-02 3.65121156e-01 1.49882793e-01
1.07366288e+00 -6.39499307e-01 7.97626600e-02 7.99544752e-01
9.38870132e-01 -2.88261268e-02 3.07126462e-01 -4.67649661e-02
1.18053877e+00 9.68514681e-01 6.03008270e-01 7.74808407e-01
2.34078139e-01 8.04496169e-01 2.83259690e-01 1.44729167e-01
2.60662228e-01 -5.87623566e-02 3.13311428e-01 1.47527039e+00
-5.87442100e-01 6.39411628e-01 -6.76173449e-01 2.09645331e-01
-1.72514486e+00 -7.40951777e-01 -2.78956622e-01 2.28289795e+00
5.44368923e-01 -4.04069901e-01 6.00737408e-02 3.57013077e-01
5.63880622e-01 2.99047440e-01 -4.94223088e-01 -3.35121274e-01
-2.24177808e-01 -2.38774717e-02 5.01659513e-02 4.77757663e-01
-7.93678105e-01 7.67623246e-01 4.88928318e+00 9.56152141e-01
-1.28734827e+00 -5.74850030e-02 3.94922048e-01 2.44383346e-02
-1.89070582e-01 -6.07442867e-04 -5.87311566e-01 3.74964565e-01
4.06558573e-01 -3.81637290e-02 5.31084061e-01 8.74308407e-01
5.46630681e-01 2.61537760e-01 -6.26353502e-01 1.46830785e+00
3.93372811e-02 -1.07516658e+00 5.81780970e-02 4.53116000e-01
5.22635877e-01 -4.89002436e-01 3.32455903e-01 -7.34385848e-02
-4.08709496e-01 -7.70071685e-01 5.02576113e-01 6.12640262e-01
8.19579720e-01 -8.85391712e-01 3.04334491e-01 7.78088719e-02
-1.28828597e+00 -9.86345857e-02 -6.78294301e-01 7.05091059e-02
5.18455990e-02 8.71351779e-01 -3.15538079e-01 7.26914108e-01
5.95909476e-01 9.81183529e-01 -8.36152807e-02 4.07861739e-01
1.29299030e-01 4.00654703e-01 -4.63605106e-01 2.50600427e-01
3.22606057e-01 -1.12609458e+00 9.49268579e-01 6.13149345e-01
3.76324892e-01 5.29042006e-01 1.94892228e-01 7.22332001e-01
2.42518745e-02 6.48807645e-01 -4.23227161e-01 -2.31450796e-01
5.35713835e-03 1.48546791e+00 -1.84789717e-01 7.03297928e-02
-4.21271086e-01 8.21388423e-01 2.82548368e-01 4.95822817e-01
-5.55810869e-01 -1.46861792e-01 1.24737680e+00 5.84108979e-02
1.64465874e-01 -5.88456810e-01 6.39918214e-03 -1.53642988e+00
5.07797360e-01 -1.02432036e+00 2.59360462e-01 -4.87483829e-01
-1.21204591e+00 7.33536899e-01 -1.07581571e-01 -1.36125326e+00
7.81111047e-02 -8.05545032e-01 -2.69366294e-01 8.15565109e-01
-1.27292264e+00 -1.25566995e+00 -1.59416541e-01 9.68973219e-01
-1.34113148e-01 -2.33717561e-01 7.47453749e-01 6.04160786e-01
-1.16159356e+00 6.00821972e-01 1.46120816e-01 2.84672201e-01
1.48975924e-01 -5.94922662e-01 -6.16743088e-01 4.65478331e-01
-2.35691965e-01 8.56921375e-01 3.94944042e-01 -3.33539248e-01
-2.17910409e+00 -9.19056952e-01 4.51241940e-01 -2.25155451e-03
8.17660987e-01 -3.22946459e-01 -9.97003198e-01 6.20086014e-01
-4.19324517e-01 3.27621281e-01 8.64182293e-01 2.84991682e-01
-5.75962067e-01 -4.35591429e-01 -1.09422052e+00 5.99128306e-01
1.03292418e+00 -5.51880062e-01 -1.99902117e-01 5.66737354e-01
2.74779886e-01 -2.80020118e-01 -1.55031264e+00 5.45692563e-01
5.16696036e-01 -6.27009213e-01 8.23762715e-01 -9.86575305e-01
1.29866391e-01 -4.84601408e-01 -4.78747398e-01 -9.29450452e-01
-3.73135090e-01 -1.01073945e+00 -1.90437451e-01 1.07047343e+00
8.74850303e-02 -4.32915479e-01 8.80697370e-01 7.63541877e-01
-1.51496872e-01 -1.00164998e+00 -1.38611174e+00 -7.05124795e-01
-1.01713732e-01 -3.21179718e-01 3.63558948e-01 1.21285868e+00
1.07918270e-01 3.90966952e-01 -5.74020624e-01 2.20445395e-01
9.75438118e-01 -2.89757047e-02 8.24853778e-01 -9.62121665e-01
1.20569639e-01 -3.74884278e-01 -6.66005790e-01 -1.06890929e+00
6.03603005e-01 -8.67664993e-01 -5.73259413e-01 -7.83086836e-01
1.72576902e-03 -5.77111661e-01 -1.53870493e-01 3.09446871e-01
1.21150419e-01 2.46540643e-02 1.33223578e-01 4.44794267e-01
-1.40818030e-01 1.21876419e+00 1.55667233e+00 -1.43271700e-01
-1.64071739e-01 -3.22679311e-01 -2.84411401e-01 6.77329063e-01
2.47603431e-01 -1.75703600e-01 -3.57231259e-01 -4.96445596e-01
2.60460172e-02 3.14523429e-01 1.03482082e-01 -4.81603384e-01
-7.69390836e-02 -3.06081772e-01 2.08544612e-01 -4.91215110e-01
8.53520572e-01 -8.33679736e-01 9.12110358e-02 1.37355160e-02
9.44484845e-02 -8.97884667e-02 4.68729995e-02 2.65033126e-01
-3.98319334e-01 5.51509187e-02 8.48880947e-01 3.40825289e-01
-2.33312279e-01 7.05907941e-01 -1.37635320e-01 -2.19784737e-01
8.77722263e-01 -3.79402727e-01 2.50444412e-01 -9.53177437e-02
-8.39374483e-01 1.29281074e-01 1.10217184e-01 2.64895350e-01
8.29642177e-01 -1.83450174e+00 -9.28271949e-01 4.84466672e-01
1.53373048e-01 -1.06335431e-01 6.75891280e-01 1.35197544e+00
-3.79988223e-01 3.36851954e-01 -2.98286796e-01 -8.35166991e-01
-1.25847769e+00 5.10657191e-01 4.79677886e-01 -3.44585888e-02
-3.62720937e-01 9.11210895e-01 1.45477742e-01 -5.27056813e-01
-2.03125775e-02 6.88326657e-02 -2.41777971e-01 2.15478048e-01
5.05221546e-01 5.55541754e-01 6.32903799e-02 -1.46105731e+00
-4.13804114e-01 1.10020685e+00 -6.46035746e-02 5.42326309e-02
1.40291154e+00 -1.92068428e-01 -7.58585870e-01 1.90554991e-01
1.93165779e+00 -3.41201276e-02 -9.92550433e-01 -3.66177946e-01
-1.28700361e-01 -8.81267369e-01 4.00219262e-01 2.27489948e-01
-1.48716819e+00 8.69837821e-01 3.74501795e-01 -2.92543828e-01
1.22780192e+00 -2.68823773e-01 6.01504207e-01 3.27403873e-01
1.61622539e-01 -1.12271297e+00 1.98922679e-01 4.42608595e-01
1.25325859e+00 -7.90946901e-01 1.02006987e-01 -6.93478525e-01
-4.71940756e-01 1.27642298e+00 4.65690106e-01 -2.68785775e-01
9.58714664e-01 -3.54930103e-01 1.99996401e-02 -4.99947339e-01
-3.84155065e-01 6.25830367e-02 5.24661362e-01 1.22981712e-01
4.77086544e-01 -1.46541029e-01 -4.20214266e-01 3.93984377e-01
-1.46985844e-01 -1.91347808e-01 4.42861505e-02 6.57819271e-01
2.78014084e-03 -9.25528944e-01 -7.09504902e-01 1.92215085e-01
-4.10437405e-01 3.56525630e-01 -3.06850784e-02 4.70775872e-01
3.27346511e-02 8.87869477e-01 -1.73825473e-01 -4.09906447e-01
5.46919286e-01 8.79081115e-02 6.38867259e-01 -1.73049435e-01
4.65899296e-02 5.67343831e-01 1.25687886e-02 -7.00024128e-01
-4.28599715e-01 -8.29300046e-01 -1.10252917e+00 -3.33257079e-01
-3.86878133e-01 4.05799657e-01 8.45538795e-01 7.18098760e-01
5.51225483e-01 -8.83188471e-02 1.32735050e+00 -6.95963442e-01
-6.87207639e-01 -9.87657905e-01 -9.94693577e-01 6.24512076e-01
1.69131145e-01 -1.03862357e+00 -4.75420803e-01 -2.08535828e-02] | [7.610286235809326, 4.405937194824219] |
d2e8025b-d5e2-466c-b924-d4b5889730d1 | vtcc-nlp-at-nl4opt-competition-subtask-1-an | 2212.07219 | null | https://arxiv.org/abs/2212.07219v1 | https://arxiv.org/pdf/2212.07219v1.pdf | VTCC-NLP at NL4Opt competition subtask 1: An Ensemble Pre-trained language models for Named Entity Recognition | We propose a combined three pre-trained language models (XLM-R, BART, and DeBERTa-V3) as an empower of contextualized embedding for named entity recognition. Our model achieves a 92.9% F1 score on the test set and ranks 5th on the leaderboard at NL4Opt competition subtask 1. | ['Xuan-Dung Doan'] | 2022-12-14 | null | null | null | null | ['xlm-r'] | ['natural-language-processing'] | [-2.65009612e-01 5.07100642e-01 -4.26444054e-01 -4.56375003e-01
-9.98416245e-01 -6.14465952e-01 7.14687884e-01 1.53072670e-01
-9.69648778e-01 7.41438746e-01 8.29951167e-01 -5.58253169e-01
1.48819372e-01 -2.25595847e-01 -5.20066977e-01 5.28447218e-02
-1.72196835e-01 4.74363387e-01 -3.02834392e-01 -1.32555634e-01
-1.81691517e-04 3.80051732e-01 -3.47440481e-01 3.77015769e-01
8.38602126e-01 7.43690252e-01 -1.67033762e-01 7.01119661e-01
-4.70664769e-01 8.98687601e-01 -7.31956184e-01 -8.31520379e-01
3.77214514e-02 6.35918453e-02 -1.20860374e+00 -5.96213102e-01
4.63554233e-01 -2.39001848e-02 -3.89119685e-01 6.20199680e-01
5.98710358e-01 3.24959755e-01 6.01855218e-01 -8.65452349e-01
-1.21111155e+00 1.02996588e+00 -5.50141782e-02 4.22185034e-01
2.47992620e-01 4.63861078e-02 1.49988770e+00 -1.63816452e+00
1.10911024e+00 1.00023818e+00 6.47060096e-01 8.58100355e-01
-1.19086897e+00 -5.62454462e-01 5.24598658e-01 6.07588887e-02
-1.49713433e+00 -6.20579958e-01 1.24500714e-01 2.89597847e-02
1.86361182e+00 2.73594894e-02 3.11431259e-01 1.47362876e+00
3.46793801e-01 1.28490150e+00 8.13561976e-01 -1.88651010e-01
2.18279392e-01 2.61596590e-03 3.99978220e-01 5.10204852e-01
4.25989449e-01 -1.35600404e-03 -7.62224913e-01 -2.52523571e-01
1.84592798e-01 -4.32900280e-01 -3.47907215e-01 4.11924198e-02
-1.37888575e+00 7.51178443e-01 6.80470645e-01 3.61013532e-01
-6.81746185e-01 3.51927690e-02 3.45855862e-01 2.17348009e-01
7.72035360e-01 1.05984712e+00 -1.22789145e+00 -1.56434536e-01
-8.26891840e-01 -6.55715540e-02 1.12869585e+00 1.21428764e+00
1.78231969e-01 2.69117773e-01 -3.97746384e-01 6.71977818e-01
4.37170088e-01 5.38256109e-01 5.71347296e-01 -4.24726576e-01
8.46167862e-01 6.16288424e-01 2.09033892e-01 -4.79815632e-01
-5.69297969e-01 -6.61220551e-01 -5.62977076e-01 -5.04069269e-01
-2.08714858e-01 -4.27842259e-01 -1.16719210e+00 1.68340933e+00
1.05959520e-01 1.84191093e-01 5.43215096e-01 5.49064398e-01
1.15744472e+00 8.75072241e-01 7.17433572e-01 3.70760441e-01
1.21050394e+00 -1.31227088e+00 -6.76758111e-01 -6.70990646e-01
9.59495246e-01 -5.42130172e-01 7.35533595e-01 -1.18621420e-02
-8.50728750e-01 -4.49325830e-01 -7.94059336e-01 -4.59729522e-01
-8.45385134e-01 5.93614697e-01 5.38802981e-01 3.07376802e-01
-1.29824293e+00 2.55289882e-01 -8.60066712e-01 -2.70019114e-01
2.75917470e-01 2.39911214e-01 -7.93001115e-01 1.88618004e-02
-1.36925793e+00 1.06996560e+00 6.57273889e-01 2.78952181e-01
-1.00771344e+00 -1.12293935e+00 -1.17210734e+00 1.03085198e-01
3.31574847e-04 -6.96310461e-01 1.13682866e+00 -1.90327561e-03
-1.48442602e+00 1.25006723e+00 -3.83548737e-01 -7.01637447e-01
2.62072414e-01 -7.99416900e-01 -6.83521986e-01 -3.29472236e-02
2.07588032e-01 7.43053138e-01 1.98270813e-01 -7.79656708e-01
-4.36488152e-01 -2.01299429e-01 -1.24775738e-01 6.15258738e-02
-1.61128893e-01 1.36751488e-01 -2.28840515e-01 -6.09959662e-01
-1.70483455e-01 -7.40107536e-01 -5.72147787e-01 -4.10170615e-01
-9.46015120e-01 -6.31812811e-01 4.39109594e-01 -1.00144827e+00
1.20495284e+00 -2.14513302e+00 2.22296819e-01 -1.04584724e-01
3.46967101e-01 7.42975473e-01 -6.06098711e-01 7.49696434e-01
-4.09660697e-01 7.71985888e-01 -1.18908964e-01 -6.35880888e-01
2.79059380e-01 -2.14357615e-01 -7.12781787e-01 2.48846710e-01
6.48915410e-01 1.39584923e+00 -1.13372540e+00 -1.24383479e-01
-6.61240965e-02 6.52727127e-01 -4.63797152e-01 4.92026389e-01
-2.01655924e-03 2.35870048e-01 -3.51769984e-01 6.11548960e-01
4.50166285e-01 -4.01140630e-01 1.43537879e-01 -6.02025464e-02
-7.50219151e-02 9.68504369e-01 -8.94292712e-01 1.88906646e+00
-7.11489260e-01 6.08638108e-01 2.47602724e-02 -3.31655651e-01
8.84317636e-01 6.00995064e-01 2.45919097e-02 -4.85213906e-01
-1.71232864e-01 2.14996234e-01 -3.63312989e-01 -1.13237992e-01
6.74518883e-01 2.27068976e-01 -4.51943398e-01 1.99949294e-01
6.18546367e-01 2.98907191e-01 -9.20098573e-02 5.33585429e-01
1.54859734e+00 4.74183336e-02 6.79636478e-01 -2.80751228e-01
4.05312657e-01 -8.49456340e-02 8.10766876e-01 7.76797175e-01
-5.93884170e-01 4.12967086e-01 3.80281508e-01 -4.97273237e-01
-6.67657435e-01 -1.27980471e+00 -5.63339852e-02 1.29887938e+00
-2.09162772e-01 -7.34975517e-01 -1.78766757e-01 -1.27669549e+00
1.33735120e-01 1.37250042e+00 -6.73026621e-01 -1.43938720e-01
-5.39190054e-01 -3.12280238e-01 9.75461960e-01 7.93626368e-01
1.91338137e-01 -1.42713380e+00 1.08915299e-01 3.87389123e-01
6.01299945e-03 -1.50455320e+00 -7.62822807e-01 4.79561210e-01
-8.74291718e-01 -8.65147293e-01 -5.90565920e-01 -1.11509728e+00
4.34879720e-01 -3.49442840e-01 1.48854601e+00 -3.26469809e-01
-6.71110675e-02 2.97438681e-01 -4.87412035e-01 -2.58513033e-01
2.52919197e-02 5.41048229e-01 -8.40960294e-02 -2.45536119e-01
4.34061557e-01 -2.76870728e-01 -5.70554972e-01 -1.60393521e-01
-5.23957849e-01 -2.57537097e-01 8.69370282e-01 9.98586893e-01
5.73595762e-01 -9.81627047e-01 7.00520515e-01 -1.04783273e+00
4.34626430e-01 -4.69073653e-01 -3.59594762e-01 4.46403235e-01
-7.09246635e-01 2.11277753e-01 6.25846505e-01 -9.86278579e-02
-1.02685952e+00 -1.92795098e-01 -4.38687831e-01 -1.59066677e-01
6.43570302e-03 5.47645330e-01 -3.67139220e-01 2.97789723e-01
4.30871278e-01 2.51270980e-01 -8.40751529e-01 -7.83056498e-01
9.80538070e-01 7.12439179e-01 4.87221360e-01 -3.37086886e-01
6.16997123e-01 1.80455983e-01 -5.83587289e-01 -9.45365071e-01
-1.13308191e+00 -6.85002089e-01 -5.68180621e-01 4.92508888e-01
1.19801116e+00 -1.26919889e+00 -2.60099471e-01 4.15146016e-02
-1.69331217e+00 -2.53841132e-01 -2.64544636e-01 6.80784523e-01
6.35174885e-02 -1.72709867e-01 -8.92482519e-01 -5.67087591e-01
-1.04010177e+00 -6.67057693e-01 1.13772643e+00 3.77734751e-02
-2.65925884e-01 -1.23833418e+00 4.14707661e-01 3.00965011e-01
5.25618434e-01 1.69706255e-01 7.32585549e-01 -1.58655775e+00
-4.16990131e-01 -1.34530202e-01 -2.63231486e-01 4.89374846e-01
-2.19731808e-01 -3.41909409e-01 -9.89626229e-01 -2.20278889e-01
-5.93628883e-01 -4.61369783e-01 1.11180007e+00 1.31285908e-02
7.99560189e-01 -3.03282470e-01 -6.01454973e-01 7.85222590e-01
1.25776207e+00 1.18181277e-02 3.49954575e-01 3.31226528e-01
8.00278783e-01 1.59346819e-01 1.44792870e-01 2.53646106e-01
4.58958417e-01 3.62143427e-01 1.55662909e-01 1.73183873e-01
-2.88021713e-01 -7.67902851e-01 4.94651049e-01 1.31766844e+00
4.58345294e-01 -6.76821768e-01 -1.16813207e+00 1.09658325e+00
-1.46067941e+00 -6.11073196e-01 5.80283999e-02 1.60210705e+00
9.06400681e-01 2.46268474e-02 -5.42818606e-01 -9.50593650e-01
6.12336516e-01 7.87790477e-01 -5.79016030e-01 -5.02787471e-01
-3.56119365e-01 7.20732450e-01 4.81516778e-01 5.57681143e-01
-1.31569040e+00 1.56849694e+00 6.95828342e+00 5.22774220e-01
-8.46469998e-01 3.65764737e-01 3.07372212e-01 1.63935870e-01
-3.70283931e-01 2.71379173e-01 -1.38810241e+00 2.41218299e-01
1.61760175e+00 -4.55135614e-01 -7.73600638e-02 9.70862925e-01
-2.76819289e-01 6.60167873e-01 -1.10415804e+00 5.52878976e-01
5.28291315e-02 -1.33643317e+00 2.76883453e-01 1.11294109e-02
9.00312006e-01 9.82890248e-01 -1.32454559e-02 1.09550238e+00
6.44124687e-01 -1.24612975e+00 3.47615004e-01 4.18216497e-01
7.47597158e-01 -4.23281193e-01 9.49899256e-01 1.68187678e-01
-1.15592527e+00 3.01173419e-01 -3.80425662e-01 4.91807938e-01
6.24276161e-01 4.61287707e-01 -9.66510773e-01 6.21517420e-01
2.74699211e-01 7.12369919e-01 -5.67597091e-01 9.14268494e-01
-9.35263753e-01 1.18983638e+00 -1.76082134e-01 -1.64246485e-01
4.71267700e-01 4.35171187e-01 8.18521202e-01 1.61554670e+00
-2.12935731e-01 -7.60852247e-02 -2.18726918e-02 6.79021060e-01
-1.07358813e+00 3.89135778e-01 -6.27645254e-01 -6.54833794e-01
6.24067426e-01 1.12063253e+00 -1.66776687e-01 -4.15126711e-01
-5.00900745e-01 1.32497048e+00 9.43883181e-01 4.92641658e-01
-5.73437154e-01 -8.48861098e-01 8.90486181e-01 -4.61504579e-01
6.91080749e-01 -3.46520752e-01 -9.70140025e-02 -1.61876559e+00
-1.07200831e-01 -6.89218402e-01 5.23068249e-01 -6.94052041e-01
-1.67404366e+00 1.04679251e+00 -3.76166224e-01 -7.66188383e-01
-3.80901583e-02 -9.61857796e-01 -5.94103158e-01 9.41193461e-01
-1.77761543e+00 -1.24405932e+00 1.67040586e-01 1.10754728e-01
4.50484276e-01 -5.39969087e-01 1.25158095e+00 2.26121485e-01
-5.91975689e-01 9.25055623e-01 3.93470466e-01 9.23529506e-01
8.10461879e-01 -1.47577882e+00 1.31558526e+00 6.99030280e-01
6.66677356e-01 1.17762530e+00 3.40797976e-02 -6.66060328e-01
-1.31115210e+00 -1.47982776e+00 1.89861846e+00 -1.09820449e+00
8.41034889e-01 -4.45088863e-01 -8.26869130e-01 1.31053901e+00
4.65443194e-01 3.04541171e-01 9.67856944e-01 5.38809121e-01
-7.60504603e-01 1.95351526e-01 -9.19468462e-01 5.04111707e-01
1.08777416e+00 -8.40749502e-01 -1.30082822e+00 3.59930605e-01
1.43462670e+00 -2.67188668e-01 -1.18810546e+00 4.08803105e-01
3.06417108e-01 -1.97280869e-01 9.44150925e-01 -1.42638338e+00
1.74677715e-01 7.90683329e-02 -2.40972683e-01 -1.47838104e+00
-2.88871020e-01 -6.69174552e-01 -2.50844210e-01 1.13776255e+00
1.12138426e+00 -6.13322496e-01 6.57120466e-01 3.10245246e-01
-1.27857268e-01 -9.02540326e-01 -1.10326827e+00 -1.06620991e+00
3.13324094e-01 -5.07290602e-01 2.74824739e-01 1.07927132e+00
-1.74775913e-01 7.84976900e-01 4.87425998e-02 3.08936656e-01
4.02676940e-01 -8.52584019e-02 5.29057682e-01 -8.75327408e-01
-2.54138019e-02 -3.44387591e-01 -4.97662127e-01 -1.18973410e+00
7.31812775e-01 -1.54297018e+00 -2.63136536e-01 -1.87090898e+00
1.01917058e-01 -3.01935375e-02 -9.09056544e-01 6.92091703e-01
-3.56805831e-01 -1.10055603e-01 3.32433790e-01 7.15395659e-02
-1.13033843e+00 1.01184976e+00 4.75647509e-01 -2.39065334e-01
-2.31223688e-01 -2.96823710e-01 -6.56039476e-01 2.92050183e-01
5.17703831e-01 -7.45874286e-01 1.52439743e-01 -8.42849493e-01
1.49628878e-01 -2.62714624e-01 -6.52348995e-02 -6.63199127e-01
1.44659698e-01 -5.08103520e-03 3.17715317e-01 -5.98049343e-01
5.44843860e-02 -2.22077534e-01 -4.76393223e-01 4.29455280e-01
-8.64892662e-01 3.84079218e-01 3.49753141e-01 6.30051851e-01
-3.75839382e-01 -1.13268718e-01 2.61355400e-01 5.35146259e-02
-9.57141757e-01 4.34593201e-01 -6.74314871e-02 9.10912275e-01
4.98910487e-01 6.14832461e-01 -4.16391879e-01 -1.51719064e-01
-8.42697561e-01 6.67985439e-01 -9.61380154e-02 7.66968846e-01
5.77581584e-01 -1.29228878e+00 -1.06258059e+00 -5.82552962e-02
4.89822507e-01 -3.20641160e-01 1.05265211e-02 4.15004134e-01
-5.37936151e-01 8.99039686e-01 3.33495289e-01 -1.82717275e-02
-6.38700843e-01 9.76560712e-02 1.39884815e-01 -9.33627009e-01
-4.35801864e-01 1.46639872e+00 7.07755461e-02 -1.09487474e+00
2.57231519e-02 -4.95889932e-01 -4.38496135e-02 -1.14479341e-01
7.00230837e-01 4.36250836e-01 5.41761369e-02 -6.89705968e-01
-1.05130446e+00 1.20188631e-01 -4.79501784e-01 -3.52072120e-01
1.58581018e+00 2.63487488e-01 8.17888305e-02 4.27193135e-01
1.75104940e+00 3.63637328e-01 -5.69286048e-01 -4.46207881e-01
7.24555910e-01 2.38928631e-01 5.15252985e-02 -1.34895182e+00
-6.33160293e-01 7.71579623e-01 1.04479924e-01 -2.91655540e-01
5.04546881e-01 1.62671193e-01 1.11106098e+00 1.00175762e+00
2.63114244e-01 -9.21821713e-01 -2.51106143e-01 1.06742239e+00
9.96116519e-01 -1.22827971e+00 -4.30163816e-02 9.37135071e-02
-8.45657468e-01 8.86098146e-01 5.32579422e-01 -3.03899705e-01
7.98870742e-01 2.33904216e-02 4.16979671e-01 -1.32285222e-01
-1.16458559e+00 -2.82672495e-01 6.91594779e-01 4.06311780e-01
6.75472438e-01 1.59731656e-01 -4.50534701e-01 1.07191598e+00
-1.69750422e-01 -3.65180910e-01 -2.83551384e-02 9.87451792e-01
-1.71278909e-01 -8.23325396e-01 3.61702353e-01 1.69574156e-01
-7.74890780e-01 -5.22942841e-01 -7.85022497e-01 9.66201663e-01
-2.34249040e-01 8.99372518e-01 -2.94183522e-01 -4.17879730e-01
6.80842698e-01 6.60286427e-01 -2.15424702e-01 -9.43448901e-01
-9.82703745e-01 -6.62561595e-01 3.12400132e-01 -1.01439703e+00
1.69624537e-01 -3.13145429e-01 -1.32312715e+00 1.20114803e-01
-2.52121031e-01 4.38336194e-01 8.12378347e-01 6.56232595e-01
1.10123503e+00 3.29718441e-01 3.05740237e-01 -2.41276741e-01
-7.17438936e-01 -1.24735785e+00 -2.48614579e-01 1.62218556e-01
3.57244343e-01 -1.94362953e-01 -5.54917634e-01 -2.96999931e-01] | [9.78378963470459, 9.621247291564941] |
183ebc6d-fa0a-4f23-b2e8-6063b2d48e86 | multivariate-probabilistic-forecasting-of | 2205.13826 | null | https://arxiv.org/abs/2205.13826v4 | https://arxiv.org/pdf/2205.13826v4.pdf | Multivariate Probabilistic Forecasting of Intraday Electricity Prices using Normalizing Flows | Electricity is traded on various markets with different time horizons and regulations. Short-term intraday trading becomes increasingly important due to the higher penetration of renewables. In Germany, the intraday electricity price typically fluctuates around the day-ahead price of the European Power EXchange (EPEX) spot markets in a distinct hourly pattern. This work proposes a probabilistic modeling approach that models the intraday price difference to the day-ahead contracts. The model captures the emerging hourly pattern by considering the four 15 min intervals in each day-ahead price interval as a four-dimensional joint probability distribution. The resulting nontrivial, multivariate price difference distribution is learned using a normalizing flow, i.e., a deep generative model that combines conditional multivariate density estimation and probabilistic regression. Furthermore, this work discusses the influence of different external impact factors based on literature insights and impact analysis using explainable artificial intelligence (XAI). The normalizing flow is compared to an informed selection of historical data and probabilistic forecasts using a Gaussian copula and a Gaussian regression model. Among the different models, the normalizing flow identifies the trends with the highest accuracy and has the narrowest prediction intervals. Both the XAI analysis and the empirical experiments highlight that the immediate history of the price difference realization and the increments of the day-ahead price have the most substantial impact on the price difference. | ['Manuel Dahmen', 'Alexander Mitsos', 'Dirk Witthaut', 'Eike Cramer'] | 2022-05-27 | null | null | null | null | ['prediction-intervals'] | ['miscellaneous'] | [-4.79770064e-01 -2.71649331e-01 -7.33881593e-02 -1.22529380e-01
-5.41094482e-01 -7.06620455e-01 8.05616260e-01 -1.44114261e-02
5.94251975e-02 1.08491015e+00 1.01861067e-01 -4.50624228e-01
-6.27400279e-01 -1.07312107e+00 -4.98400718e-01 -8.82381737e-01
-1.57799631e-01 7.33153880e-01 -3.65120918e-01 2.41847727e-02
1.41682670e-01 4.45774734e-01 -1.25261879e+00 -3.77115518e-01
9.86927927e-01 1.24213374e+00 1.44410878e-01 1.66894525e-01
2.57403683e-02 1.39125004e-01 -8.68930519e-01 -2.83396095e-01
3.74867946e-01 -2.81029463e-01 6.66689426e-02 -2.44541153e-01
-8.31487060e-01 -2.43586630e-01 -4.39543985e-02 9.13941026e-01
2.50342280e-01 1.01569906e-01 8.73303473e-01 -1.51526856e+00
-6.81747794e-01 9.75242436e-01 -6.63711369e-01 3.46264333e-01
-1.63384795e-01 -1.37516409e-01 9.28175449e-01 -7.57553160e-01
7.25851441e-03 7.92960823e-01 4.33101654e-01 -4.59999770e-01
-1.35888469e+00 -4.76114273e-01 -4.27802317e-02 2.24181503e-01
-1.42998612e+00 4.86138314e-01 1.04189944e+00 -5.12885451e-01
1.09238303e+00 9.59617049e-02 7.35018253e-01 8.92922461e-01
9.05013978e-01 4.61645067e-01 1.20964718e+00 -2.03774124e-01
3.94442916e-01 7.32451603e-02 -2.25078523e-01 -6.31306589e-01
3.30182731e-01 6.11218929e-01 -1.68858871e-01 -3.47497523e-01
3.11934233e-01 1.77455574e-01 -7.63142928e-02 -6.93289712e-02
-7.79235482e-01 8.89543414e-01 -4.38222960e-02 6.52255952e-01
-9.67443526e-01 -2.25953087e-01 1.28477132e-02 3.23711932e-02
6.58409119e-01 6.98462799e-02 -9.16597486e-01 -4.79029953e-01
-1.37147737e+00 3.75038683e-01 1.24665165e+00 6.13993227e-01
3.91965955e-01 5.00806868e-01 -2.01452211e-01 3.18889737e-01
4.67202634e-01 9.87249076e-01 3.46953899e-01 -3.42421144e-01
7.44748488e-02 1.01417759e-02 5.48268914e-01 -7.12538719e-01
-3.91789943e-01 -9.15303767e-01 -6.77187562e-01 3.45721662e-01
4.68068600e-01 -6.19529724e-01 -3.48851830e-01 1.41913831e+00
-8.15240219e-02 1.31389618e-01 -6.86233416e-02 2.66446233e-01
-1.90911278e-01 9.90886927e-01 -1.81063060e-02 -5.17234743e-01
1.24370337e+00 -4.35170621e-01 -8.56638014e-01 4.70900387e-01
-1.36687728e-02 -8.04558933e-01 1.26640409e-01 5.42165875e-01
-9.60052133e-01 -4.53298301e-01 -9.96422529e-01 7.73123503e-01
-6.19881868e-01 -2.97903884e-02 7.68150836e-02 6.06526136e-01
-6.55039072e-01 8.53235304e-01 -7.75758445e-01 3.85423034e-01
-2.15164974e-01 -1.13983832e-01 4.11324650e-01 5.97527921e-01
-1.54969597e+00 1.18657243e+00 5.68876803e-01 3.35403830e-01
-4.55098867e-01 -1.06332481e+00 -6.54902101e-01 5.84683359e-01
5.23735546e-02 -4.14821625e-01 9.45917726e-01 -3.53702068e-01
-1.46660590e+00 -1.83499962e-01 -1.81388669e-02 -1.06182063e+00
6.07085049e-01 3.17609943e-02 -9.21663344e-01 -3.07416439e-01
-5.55731617e-02 -1.61718071e-01 7.46408165e-01 -8.13734889e-01
-7.74359465e-01 -3.07784408e-01 -4.17530596e-01 1.10446233e-02
3.13942552e-01 -2.06942782e-01 2.80684441e-01 -1.01596308e+00
-2.99825400e-01 -7.93366134e-01 -3.35887074e-02 -1.13350141e+00
-2.85529196e-01 -3.58083040e-01 7.71546483e-01 -8.45352054e-01
1.51578963e+00 -2.07589912e+00 -1.43289819e-01 5.71506560e-01
-3.92758191e-01 -4.48339194e-01 6.93996429e-01 8.37663174e-01
-4.12789285e-01 2.19512302e-02 -1.95222303e-01 -5.04266135e-02
7.62902200e-01 4.13435072e-01 -7.60445952e-01 2.60973275e-01
2.00120240e-01 9.19955850e-01 -5.81170619e-01 4.74809617e-01
4.83698338e-01 5.58683813e-01 2.93785393e-01 -1.48005113e-01
-3.00278366e-01 3.29053074e-01 -9.91765112e-02 4.24093425e-01
1.07725847e+00 -1.44513950e-01 1.23379305e-01 -7.25191534e-02
-5.54039776e-01 8.73043090e-02 -1.17109716e+00 1.01964581e+00
-2.89957076e-01 2.56403804e-01 -2.36806452e-01 -8.31032932e-01
1.13413918e+00 4.22555953e-01 5.11954725e-01 -7.91430771e-01
1.54524576e-03 3.98810029e-01 1.14814423e-01 2.49940887e-01
4.83601630e-01 -4.41251814e-01 -2.32081801e-01 6.70814514e-01
-9.95036587e-02 -1.21625185e-01 3.55707139e-01 -4.89324927e-01
2.98113972e-01 2.57511228e-01 3.61157835e-01 -5.03529370e-01
1.48551077e-01 -4.18637335e-01 7.78921843e-01 3.25911164e-01
1.48630232e-01 3.93369764e-01 7.56294250e-01 -3.89314413e-01
-8.28909457e-01 -1.31634843e+00 -8.49583745e-01 3.50855261e-01
-1.68487906e-01 6.20168038e-02 -4.64526534e-01 -1.71564400e-01
5.70780337e-01 1.73412025e+00 -6.61719680e-01 3.92066091e-02
2.38237604e-01 -1.36863542e+00 -7.42096603e-02 5.62589169e-01
2.69336551e-01 -9.13426876e-01 -6.33196414e-01 5.40937662e-01
2.33564526e-01 -5.95777869e-01 2.27239467e-02 5.34156084e-01
-4.30901408e-01 -6.20139718e-01 -8.20399940e-01 9.55491289e-02
1.96449324e-01 -5.62371850e-01 1.11073029e+00 -9.18026030e-01
4.84047197e-02 4.21155453e-01 -1.03035897e-01 -1.02203488e+00
-1.67024314e-01 -3.03749174e-01 -6.07515983e-02 3.40098925e-02
5.81656158e-01 -9.00731146e-01 -6.10779405e-01 2.15932712e-01
-7.73596704e-01 -4.14168298e-01 3.85488689e-01 7.88607657e-01
7.92139471e-01 9.80767906e-01 9.01086509e-01 -3.45718563e-01
7.48140156e-01 -9.84589994e-01 -1.19529271e+00 2.12787092e-01
-1.17072594e+00 3.33046378e-03 3.89785826e-01 2.68085618e-02
-1.20473850e+00 -5.08031189e-01 3.13129008e-01 -2.55130142e-01
-2.21460119e-01 9.88525629e-01 -8.84910375e-02 7.30357409e-01
-2.38674521e-01 5.29054642e-01 -2.34445900e-01 -6.99763417e-01
1.88921034e-01 9.67517719e-02 3.77655655e-01 -4.57975835e-01
9.57132697e-01 1.44698337e-01 3.38975992e-03 -4.78989035e-01
-3.68575692e-01 2.60955431e-02 -5.69706142e-01 -5.66302352e-02
7.76464522e-01 -7.92143583e-01 -6.12820864e-01 8.12236428e-01
-9.33963776e-01 -2.34039929e-02 -5.73077023e-01 8.31229985e-01
-5.46859145e-01 8.08893815e-02 -4.24843997e-01 -1.27841353e+00
-1.98876157e-01 -1.04954302e+00 5.85742354e-01 3.91764760e-01
-3.53871435e-01 -1.25817990e+00 3.82039070e-01 -2.76066422e-01
6.07244074e-01 6.99287713e-01 1.25946975e+00 -1.06851566e+00
-2.68599719e-01 -2.36888364e-01 4.47862558e-02 5.54520190e-01
3.78160119e-01 3.25611204e-01 -7.36252367e-01 -5.00813825e-03
4.08719093e-01 6.52437449e-01 2.36394957e-01 1.02298558e+00
5.85410774e-01 -5.86614758e-02 -1.93152633e-02 2.23732024e-01
1.52050102e+00 9.69265521e-01 4.48786229e-01 4.71527547e-01
7.54078701e-02 3.89251888e-01 4.89440054e-01 1.02341163e+00
5.34972131e-01 3.16646487e-01 4.86198902e-01 3.74492586e-01
8.08159709e-01 -2.47524440e-01 1.75641403e-01 5.19468486e-01
-4.39400636e-02 -1.23200484e-01 -8.71741116e-01 5.33201873e-01
-1.68783212e+00 -1.18353856e+00 6.51328638e-02 2.37800050e+00
3.96886081e-01 4.27678853e-01 4.01029177e-02 1.36322111e-01
7.15753496e-01 2.05980778e-01 -6.02829158e-01 -4.82454091e-01
-5.03557086e-01 3.96787614e-01 5.49964905e-01 3.66393924e-01
-8.83618176e-01 -3.01875081e-02 5.93537521e+00 7.64776945e-01
-8.79388034e-01 -2.53018677e-01 9.90551114e-01 9.97477844e-02
-5.73357761e-01 -6.37461394e-02 -8.37189317e-01 1.15106356e+00
1.46582735e+00 -1.22807157e+00 3.88382763e-01 7.77374685e-01
6.41977847e-01 -3.79300803e-01 -8.48823786e-01 7.43518114e-01
-2.93100029e-01 -1.08895850e+00 -9.47725549e-02 6.14577770e-01
9.14899528e-01 1.53721884e-01 3.23109537e-01 3.23753864e-01
1.84697732e-01 -9.51860964e-01 8.97943556e-01 1.14303386e+00
-5.72182275e-02 -1.48681009e+00 1.19863820e+00 3.63325596e-01
-1.16395330e+00 -1.86207011e-01 -1.02902822e-01 -6.33470267e-02
5.97975731e-01 1.14549124e+00 -4.57180202e-01 1.18010521e+00
8.28764915e-01 5.63121617e-01 3.79212573e-02 9.59599853e-01
-2.82995462e-01 7.13295400e-01 -5.76332033e-01 1.44639507e-01
1.58169597e-01 -8.99702609e-01 6.16099715e-01 6.61052167e-01
9.43479002e-01 -1.56268090e-01 -2.24234238e-01 1.27740788e+00
2.68006951e-01 -2.26596192e-01 -6.10598564e-01 -8.57098401e-02
6.41227961e-01 9.74283636e-01 -5.73327184e-01 -8.92211869e-02
-5.91046214e-01 4.40452784e-01 -6.33984625e-01 6.54261947e-01
-1.00216055e+00 -1.96302310e-01 5.80811560e-01 -1.35188088e-01
8.77931595e-01 -2.39903733e-01 -5.20402789e-01 -6.98959470e-01
1.79803714e-01 -3.00406754e-01 3.59668672e-01 -7.57354140e-01
-1.65559292e+00 3.82607967e-01 4.03109193e-01 -1.29241014e+00
-7.87995994e-01 -3.51322830e-01 -1.13621342e+00 1.62984300e+00
-1.80270875e+00 -4.45427626e-01 5.81137955e-01 2.95736045e-01
9.09848586e-02 -1.16852105e-01 9.66879010e-01 -1.11998051e-01
-5.01245916e-01 1.03272177e-01 9.47559774e-01 -8.34157318e-02
1.30262494e-01 -1.66193080e+00 3.62054378e-01 6.35861397e-01
7.38834068e-02 3.86515975e-01 7.75727093e-01 -6.94036663e-01
-9.04062271e-01 -7.30423152e-01 9.34710085e-01 -2.45478094e-01
1.22699499e+00 1.18024066e-01 -8.66770208e-01 4.31288928e-01
7.64024138e-01 -5.93980610e-01 9.95467305e-01 -2.93623030e-01
8.99406001e-02 -2.15587944e-01 -1.16844058e+00 -2.44184770e-03
-2.91132748e-01 -3.61129314e-01 -9.39722419e-01 -7.89957270e-02
3.35850328e-01 -3.51252221e-02 -1.40091336e+00 4.03021067e-01
6.35571539e-01 -9.63315368e-01 4.68151510e-01 8.43414366e-02
-4.22527231e-02 -4.67379183e-01 -3.04437399e-01 -1.77130854e+00
-2.95596391e-01 -8.03843498e-01 -3.38924319e-01 1.36149049e+00
7.82093346e-01 -1.20238459e+00 2.53996044e-01 1.11040914e+00
4.83151585e-01 -7.19417632e-01 -1.35726452e+00 -9.27789152e-01
1.56840831e-01 -5.33576846e-01 1.35928559e+00 7.74231553e-01
-6.20452277e-02 -1.70000717e-01 -1.92571357e-01 3.52688730e-01
8.24824810e-01 7.72151530e-01 2.13081971e-01 -1.37701154e+00
-4.69906956e-01 -6.76332355e-01 -1.60387620e-01 -4.63326842e-01
-1.77885797e-02 -4.74229485e-01 -4.36718047e-01 -1.19511151e+00
-1.56881019e-01 2.61982620e-01 -8.42029870e-01 -5.90197966e-02
1.40060276e-01 -4.64764565e-01 1.82388902e-01 -7.69770145e-02
3.21341336e-01 9.64019120e-01 5.87125421e-01 -1.45719135e-02
-4.15849648e-02 5.20903528e-01 -3.20442170e-01 5.95283747e-01
9.60662484e-01 -2.04384416e-01 -4.01104182e-01 1.61024213e-01
3.93455535e-01 3.20760608e-01 1.17539376e-01 -7.32963622e-01
8.02244321e-02 -1.32470792e-02 6.50656879e-01 -1.48558497e+00
1.66570651e-03 -1.04384434e+00 8.78399134e-01 3.03532004e-01
3.57525289e-01 5.63804567e-01 3.98494840e-01 7.47860849e-01
-6.05510592e-01 -9.00474787e-02 3.18932474e-01 1.62185892e-01
-3.33726883e-01 6.32193536e-02 -5.81888914e-01 -3.18287551e-01
1.18429160e+00 -2.78495818e-01 2.61536930e-02 -5.43970704e-01
-1.16846263e+00 4.22843218e-01 5.52731678e-02 4.19693708e-01
1.19330168e-01 -1.17355204e+00 -8.52349401e-01 1.20567493e-01
-5.02258718e-01 -3.59766632e-01 5.05162954e-01 8.49106431e-01
2.53596324e-02 6.70433998e-01 -1.53382383e-02 -4.39330667e-01
-1.73739642e-01 3.75800788e-01 3.51388156e-01 -6.54020369e-01
-3.37691635e-01 1.85961768e-01 6.70036525e-02 8.20472650e-03
-9.21049118e-02 -6.00889087e-01 -3.04805934e-01 8.61231565e-01
4.99164850e-01 6.36575401e-01 1.15494676e-01 -6.15471780e-01
1.86955687e-02 3.06534857e-01 3.27477872e-01 -1.47866890e-01
1.62050056e+00 -2.26878881e-01 -2.92896986e-01 9.67059970e-01
7.79058695e-01 -1.58376053e-01 -1.45604789e+00 1.01813816e-01
4.10656035e-01 1.50264315e-02 6.45807432e-03 -1.16727448e+00
-9.97402608e-01 4.01534438e-01 2.76335448e-01 8.38021576e-01
9.76400495e-01 -4.04406637e-01 5.71455836e-01 -3.06134313e-01
5.56910157e-01 -1.23427606e+00 -1.13648582e+00 4.29693669e-01
8.61355364e-01 -6.18517458e-01 -2.33792275e-01 3.23798120e-01
-5.64524949e-01 1.16578364e+00 -4.06839192e-01 -6.49673715e-02
1.57144833e+00 5.46998024e-01 -2.36727461e-01 1.48872465e-01
-6.96788669e-01 2.03229681e-01 3.23015362e-01 3.15909564e-01
1.61178425e-01 6.78706288e-01 -5.68988800e-01 1.23923218e+00
-6.16500378e-01 -9.98899639e-02 3.70852530e-01 6.22718692e-01
2.34522387e-01 -1.04454112e+00 -3.73235643e-01 3.14628214e-01
-6.14532471e-01 -2.09531158e-01 1.93656772e-01 8.97802889e-01
-5.62595241e-02 9.26170170e-01 4.72264677e-01 8.27145502e-02
3.43259901e-01 5.29294372e-01 -1.61445335e-01 -2.01584980e-01
-3.77269745e-01 5.06969512e-01 -2.88347900e-01 -2.17381582e-01
-1.41681343e-01 -1.04648316e+00 -1.21194828e+00 -3.72129351e-01
-2.27205962e-01 6.12781644e-01 7.98508108e-01 1.04572105e+00
2.82055795e-01 4.73581553e-01 1.07801580e+00 -9.08581913e-01
-8.58231902e-01 -1.04378819e+00 -1.41256475e+00 -1.85923621e-01
-2.47874297e-02 -6.39026284e-01 -9.06411946e-01 -3.58955801e-01] | [6.062414646148682, 3.0027811527252197] |
4aea09bd-be47-43af-9d66-bb125467aa39 | pmal-open-set-recognition-via-robust | 2203.08569 | null | https://arxiv.org/abs/2203.08569v1 | https://arxiv.org/pdf/2203.08569v1.pdf | PMAL: Open Set Recognition via Robust Prototype Mining | Open Set Recognition (OSR) has been an emerging topic. Besides recognizing predefined classes, the system needs to reject the unknowns. Prototype learning is a potential manner to handle the problem, as its ability to improve intra-class compactness of representations is much needed in discrimination between the known and the unknowns. In this work, we propose a novel Prototype Mining And Learning (PMAL) framework. It has a prototype mining mechanism before the phase of optimizing embedding space, explicitly considering two crucial properties, namely high-quality and diversity of the prototype set. Concretely, a set of high-quality candidates are firstly extracted from training samples based on data uncertainty learning, avoiding the interference from unexpected noise. Considering the multifarious appearance of objects even in a single category, a diversity-based strategy for prototype set filtering is proposed. Accordingly, the embedding space can be better optimized to discriminate therein the predefined classes and between known and unknowns. Extensive experiments verify the two good characteristics (i.e., high-quality and diversity) embraced in prototype mining, and show the remarkable performance of the proposed framework compared to state-of-the-arts. | ['Yi Niu', 'Zhanzhan Cheng', 'Hao Li', 'Yunxu Xu', 'Jing Lu'] | 2022-03-16 | null | null | null | null | ['open-set-learning'] | ['miscellaneous'] | [ 1.51278049e-01 -8.21464520e-04 -2.66177684e-01 -4.24548715e-01
-4.81578082e-01 -1.82999447e-01 3.23492616e-01 1.66636452e-01
-1.90159515e-01 5.87071300e-01 -1.81919962e-01 -6.76622540e-02
-8.19975615e-01 -7.28352606e-01 -3.64377946e-01 -8.70568037e-01
2.63953526e-02 4.67823058e-01 8.52680132e-02 -9.51861590e-02
2.94090092e-01 5.14178395e-01 -2.22106194e+00 1.07073195e-01
1.30520380e+00 1.43135917e+00 2.50312060e-01 -1.79721385e-01
-3.05630863e-01 1.44043893e-01 -3.46929878e-01 -7.87259564e-02
3.25351924e-01 -1.42801672e-01 -1.24558516e-01 3.51707876e-01
3.01376283e-01 1.46503568e-01 -2.02125311e-01 1.09124887e+00
4.07740265e-01 1.18006334e-01 8.23634088e-01 -1.06831491e+00
-5.24301052e-01 4.90081996e-01 -3.59307468e-01 1.27829269e-01
5.31568639e-02 -7.49653801e-02 1.04357409e+00 -1.20749676e+00
3.02662373e-01 1.05960131e+00 2.19209880e-01 3.17063272e-01
-1.02286005e+00 -7.44699001e-01 4.25304502e-01 5.23208857e-01
-2.01066303e+00 -4.85536575e-01 1.02613235e+00 -4.08872724e-01
2.96212196e-01 5.27697980e-01 5.08598208e-01 8.14322472e-01
-3.16544622e-02 7.03563988e-01 9.05029714e-01 -4.02367234e-01
4.68852192e-01 8.35366309e-01 5.39230227e-01 5.45579553e-01
5.77010751e-01 9.68972445e-02 -2.78422683e-01 -1.08546212e-01
3.10250521e-01 6.42216355e-02 -5.13837457e-01 -6.05158448e-01
-9.74001884e-01 6.17571831e-01 2.85484284e-01 4.31126058e-01
-2.17687368e-01 -7.00482905e-01 2.77399242e-01 9.66326892e-02
7.36209527e-02 3.56181026e-01 -3.26424628e-01 4.01778460e-01
-9.49696660e-01 -2.97113061e-01 4.89327103e-01 8.80742431e-01
7.76864469e-01 1.22448891e-01 -1.74647808e-01 8.07121515e-01
5.11248469e-01 2.70279258e-01 7.95259655e-01 -1.12854071e-01
4.28645998e-01 1.07379675e+00 -1.13040365e-01 -1.33807564e+00
-2.67672509e-01 -9.06957746e-01 -1.03024101e+00 8.52338225e-02
1.62419528e-01 2.27406710e-01 -6.77838743e-01 1.32037723e+00
6.28922999e-01 3.80329996e-01 1.76750004e-01 8.15048039e-01
7.98414052e-01 6.25322878e-01 -1.49512172e-01 -7.10139692e-01
1.33304763e+00 -4.54289049e-01 -6.27989650e-01 -3.92922424e-02
4.35267776e-01 -4.20421034e-01 8.78603578e-01 5.90111136e-01
-4.24283236e-01 -8.72271538e-01 -1.30602157e+00 5.28017759e-01
-3.35696995e-01 6.72312677e-01 5.64378858e-01 8.52174222e-01
-3.66898298e-01 4.24284428e-01 -3.27249259e-01 4.95536020e-03
4.26709086e-01 3.31102550e-01 -3.88405442e-01 -4.70781550e-02
-1.06134570e+00 5.95568895e-01 9.29501712e-01 4.21548158e-01
-4.84224528e-01 -5.56577981e-01 -7.20083356e-01 2.59470612e-01
6.83204532e-01 -3.67988348e-01 6.34752214e-01 -8.78174782e-01
-1.21134269e+00 4.37494516e-01 2.02693895e-01 -2.75915980e-01
5.14419377e-01 8.27397406e-03 -8.96573305e-01 5.38760312e-02
-2.75542200e-01 -5.49644977e-03 1.19437182e+00 -1.32876384e+00
-8.05550754e-01 -6.12769604e-01 -3.61215889e-01 2.47032598e-01
-8.72739971e-01 -3.88542473e-01 -2.47774869e-01 -5.29763758e-01
7.37550259e-01 -5.63228309e-01 -8.25546756e-02 -1.89660601e-02
-3.20092380e-01 -4.77332652e-01 9.07506764e-01 -2.63388932e-01
1.65271068e+00 -2.15503025e+00 -3.13284621e-02 7.25655973e-01
1.98179379e-01 4.74055141e-01 8.58093575e-02 5.37968706e-03
-2.12886199e-01 -8.59596282e-02 -1.96937263e-01 3.33882049e-02
-2.76726461e-03 1.53185949e-01 -3.19147229e-01 5.68758368e-01
2.72268802e-01 3.76099527e-01 -6.05771363e-01 -6.10137463e-01
3.28320086e-01 2.36460209e-01 -2.73211509e-01 9.67451781e-02
-1.89471126e-01 2.46607959e-01 -7.44559944e-01 8.02180052e-01
7.17905343e-01 -1.34166732e-01 2.45085940e-01 -4.62645501e-01
-1.09508052e-01 -2.95134187e-01 -1.97067249e+00 1.08766699e+00
-3.55335712e-01 2.86635272e-02 2.04023700e-02 -1.26693225e+00
1.51008451e+00 1.23463653e-01 3.66945267e-01 -5.63593209e-01
2.77942210e-01 6.01875842e-01 9.87999290e-02 -5.40594935e-01
4.14806694e-01 2.27635615e-02 1.07464202e-01 7.76674077e-02
-9.64943841e-02 3.23616654e-01 1.99068144e-01 -1.40558556e-01
4.45188046e-01 -1.94454342e-01 3.85247618e-01 -4.31934506e-01
1.02156365e+00 -3.34552526e-01 8.08329940e-01 4.94931072e-01
-4.72995974e-02 2.36584455e-01 2.24222578e-02 -4.17362988e-01
-6.85763657e-01 -8.48226070e-01 -5.33908725e-01 5.05144417e-01
5.09487152e-01 -1.18289769e-01 -2.69561470e-01 -6.66040421e-01
1.57413468e-01 7.12827682e-01 -5.22988379e-01 -4.31076169e-01
-4.42087680e-01 -6.61737859e-01 2.15523943e-01 1.63166940e-01
1.53775960e-01 -7.12851107e-01 -5.56957245e-01 1.55251801e-01
1.23097412e-02 -6.59783781e-01 -2.30937794e-01 1.18240885e-01
-9.04704392e-01 -1.27306890e+00 -4.24314648e-01 -8.92331958e-01
8.00921023e-01 3.31997126e-01 7.06739306e-01 1.90319583e-01
-3.79601091e-01 7.23700076e-02 -5.79895020e-01 -2.38628060e-01
-2.37071887e-01 -2.27359906e-01 4.04178232e-01 7.09645629e-01
3.27938199e-01 -5.68029881e-01 -4.17890191e-01 5.00082433e-01
-9.05518234e-01 -3.01233947e-01 1.02914047e+00 1.07722187e+00
1.03646064e+00 6.48298383e-01 8.47279072e-01 -7.04568982e-01
5.27858198e-01 -5.79505682e-01 -7.46679425e-01 6.75727606e-01
-8.68485808e-01 5.32150418e-02 8.13499153e-01 -7.08127499e-01
-1.04496169e+00 2.23560065e-01 1.31226033e-01 -6.09119475e-01
-2.67971784e-01 4.58258897e-01 -6.94635212e-01 4.50726748e-02
4.26062524e-01 5.07175803e-01 -1.22266691e-02 -4.62260365e-01
3.48824739e-01 9.43737745e-01 4.30503815e-01 -5.22722244e-01
9.73336995e-01 3.63465577e-01 -6.94579855e-02 -9.95227754e-01
-5.89161754e-01 -7.01107800e-01 -6.14777446e-01 -1.66027650e-01
2.57411540e-01 -7.70867348e-01 -5.68550766e-01 1.32261977e-01
-6.69452727e-01 6.36917293e-01 -3.99443597e-01 6.97064817e-01
-2.40655839e-01 6.54865026e-01 1.32724404e-01 -1.13163888e+00
-5.03877819e-01 -1.04752123e+00 6.41130924e-01 5.14288366e-01
2.32470959e-01 -5.65672338e-01 -2.86674410e-01 5.86469956e-02
-2.52168509e-03 -4.06065863e-03 8.67704988e-01 -1.19913948e+00
-5.56032002e-01 -3.07387978e-01 -1.39627352e-01 3.77158135e-01
1.09745055e-01 5.81956469e-02 -7.88825512e-01 -3.82817507e-01
3.01372081e-01 -1.72364593e-01 9.48003531e-01 1.46478573e-02
1.27666020e+00 -3.54094625e-01 -4.80618834e-01 5.09992599e-01
1.37936938e+00 3.15968305e-01 5.55423677e-01 2.31348768e-01
4.02141541e-01 5.24634898e-01 1.23397231e+00 8.19930971e-01
2.12531723e-02 6.17617369e-01 4.76741582e-01 1.80780604e-01
2.13748217e-01 -8.07923228e-02 1.18339509e-01 9.24764812e-01
3.88156533e-01 -1.01674147e-01 -5.59869230e-01 3.50910991e-01
-1.77819932e+00 -9.12849724e-01 -5.70816286e-02 2.44219470e+00
6.80784941e-01 4.19707924e-01 -9.84955803e-02 6.73018038e-01
9.10482168e-01 -3.87033112e-02 -6.38387978e-01 -8.95279925e-03
-2.40427598e-01 3.89627069e-02 3.36402766e-02 -3.00597623e-02
-1.12293983e+00 4.00398344e-01 4.16995192e+00 1.29266810e+00
-1.10662210e+00 -3.45292598e-01 4.85887080e-01 2.30942741e-01
-4.50502217e-01 -1.47797853e-01 -1.20565581e+00 5.50134480e-01
4.98300791e-01 -1.86487898e-01 5.31396316e-03 1.05668259e+00
5.87744415e-02 -1.59973819e-02 -1.14694071e+00 1.22656357e+00
1.99604839e-01 -1.16747630e+00 1.73375145e-01 -3.16559263e-02
5.07562399e-01 -5.93306780e-01 1.26923665e-01 5.04501760e-01
-5.61288059e-01 -7.01045036e-01 8.14764559e-01 6.73253000e-01
7.39459157e-01 -9.93252099e-01 7.30593622e-01 7.44986117e-01
-1.32085395e+00 -5.32763779e-01 -7.41423249e-01 3.17510754e-01
-1.41548812e-01 1.00080788e+00 -5.75039804e-01 1.00014174e+00
5.47021031e-01 7.09231913e-01 -7.04406559e-01 1.31316888e+00
2.14301310e-02 3.19871873e-01 -4.16276366e-01 -9.68481153e-02
-1.90914303e-01 -5.43272316e-01 5.38033724e-01 8.73499990e-01
4.40340191e-01 2.45659590e-01 4.06882674e-01 7.41032600e-01
1.77097663e-01 5.05747020e-01 -4.82698917e-01 6.72841594e-02
8.30764711e-01 1.24515212e+00 -6.95227504e-01 -3.41101050e-01
-1.96922138e-01 5.37358344e-01 1.34053409e-01 -1.21618249e-01
-8.13737929e-01 -6.09481335e-01 4.69929129e-01 -6.23717606e-02
6.58787489e-01 1.10031823e-02 -2.89994806e-01 -1.24669170e+00
3.81631285e-01 -9.19628203e-01 6.77858055e-01 -7.09254667e-02
-1.42167890e+00 6.24060929e-01 -2.22728580e-01 -1.79760349e+00
3.10260057e-01 -5.78648210e-01 -5.36715806e-01 5.23353934e-01
-1.63260722e+00 -1.01235402e+00 -2.80687869e-01 5.98120868e-01
5.48230708e-01 -2.77635396e-01 7.19743431e-01 4.81564999e-01
-8.37576449e-01 9.60883081e-01 4.75845605e-01 -2.00565159e-01
4.16724145e-01 -7.80212164e-01 -4.42383736e-01 7.60350227e-01
3.72031122e-01 7.29217589e-01 3.85007977e-01 -5.88893831e-01
-1.52294695e+00 -1.08184707e+00 4.01333302e-01 1.34571958e-02
5.19076407e-01 -1.69075221e-01 -1.11379194e+00 4.35331501e-02
-5.58083296e-01 1.29904121e-01 7.48660147e-01 1.24491930e-01
-4.21596706e-01 -4.79717791e-01 -1.02289355e+00 4.08638865e-01
7.36783564e-01 -2.03370094e-01 -8.03379655e-01 1.01521082e-01
5.26433349e-01 -7.82271549e-02 -8.77417862e-01 8.01450789e-01
6.66834474e-01 -9.03485298e-01 9.75538790e-01 -3.67722809e-01
-1.97942376e-01 -6.75322711e-01 -2.02723846e-01 -1.04514301e+00
-2.24422559e-01 -1.64507464e-01 -4.68440920e-01 1.43623364e+00
2.83260167e-01 -7.01368868e-01 7.75803387e-01 2.76165366e-01
-2.32215375e-01 -9.48540032e-01 -1.04849577e+00 -1.12520802e+00
-4.08164620e-01 -2.64965951e-01 5.07435799e-01 8.90208542e-01
8.74530431e-03 3.23711365e-01 -3.09212238e-01 5.15963256e-01
6.57328308e-01 5.61764479e-01 5.54384947e-01 -1.68815041e+00
-3.87652725e-01 -3.97314399e-01 -6.46497071e-01 -9.94293213e-01
-2.08060890e-02 -9.10802722e-01 -2.31148563e-02 -1.15654325e+00
-4.27527986e-02 -9.99694347e-01 -6.76047266e-01 1.34807706e-01
-1.63244605e-01 -7.46347532e-02 -1.09437080e-02 4.80578303e-01
-7.37035394e-01 9.52979803e-01 1.04035902e+00 -2.40214095e-01
-4.77734476e-01 3.96074176e-01 -8.08332443e-01 6.06021106e-01
8.44544470e-01 -2.73095220e-01 -5.40966451e-01 3.01221032e-02
-1.39819980e-01 -1.32795230e-01 -2.18309909e-02 -1.14901936e+00
2.19608486e-01 -2.63678402e-01 3.67099702e-01 -7.00935423e-01
2.64451951e-01 -1.22964442e+00 2.40574494e-01 5.22147894e-01
-5.79739101e-02 -4.81733322e-01 2.77875345e-02 1.04828537e+00
-2.27919146e-01 -3.11754078e-01 8.78202736e-01 1.71412602e-01
-1.09795761e+00 3.87069434e-01 1.37940288e-01 -1.83506921e-01
1.37232745e+00 -5.96830428e-01 -1.01008818e-01 2.65022665e-01
-6.15992665e-01 3.21747243e-01 9.59661081e-02 5.73015690e-01
9.39194083e-01 -1.19570065e+00 -6.49767220e-01 4.86676455e-01
6.11803174e-01 8.41119289e-02 3.75756055e-01 7.87939250e-01
3.51207219e-02 2.49292195e-01 1.35230999e-02 -6.10312045e-01
-1.20145929e+00 8.66647959e-01 1.23498462e-01 -1.28052801e-01
-5.67546785e-01 6.52713895e-01 9.17621925e-02 -3.41216236e-01
5.14698446e-01 -1.33199170e-01 -6.68579757e-01 3.32593322e-01
7.58402348e-01 4.64114398e-01 3.17074269e-01 -6.69948757e-01
-3.74398023e-01 4.79664028e-01 -1.19657822e-01 6.75310671e-01
1.32550442e+00 -1.72719076e-01 -3.57830711e-02 3.06726962e-01
9.67121601e-01 5.47402315e-02 -9.40576613e-01 -4.17008579e-01
2.99111158e-01 -6.22618377e-01 -7.40897804e-02 -4.44378287e-01
-7.26622224e-01 7.20415413e-01 8.26248109e-01 2.80508727e-01
1.14159870e+00 -1.04000352e-01 4.17442501e-01 4.23295498e-01
5.30858815e-01 -1.27044535e+00 8.13324302e-02 2.05579698e-01
8.00368190e-01 -1.23164773e+00 1.32098183e-01 -6.26008034e-01
-4.01167035e-01 1.22271466e+00 7.15546846e-01 8.33850130e-02
8.30180705e-01 -2.75779992e-01 -2.48497620e-01 -3.70973833e-02
-5.55691540e-01 -2.02856317e-01 6.87964916e-01 4.92706567e-01
-9.16549191e-02 1.84801638e-01 -5.02564192e-01 1.00049543e+00
2.24324375e-01 -3.97761196e-01 2.17293948e-01 6.23012960e-01
-8.21728885e-01 -8.60865116e-01 -5.32223701e-01 7.36599863e-01
1.43464252e-01 1.75205335e-01 -6.65671602e-02 5.85668147e-01
4.92287904e-01 9.90842402e-01 -1.74614474e-01 -6.51932776e-01
4.80254620e-01 -8.44399929e-02 1.93821728e-01 -6.82204843e-01
-9.32150707e-02 -9.66600925e-02 -2.26449117e-01 -3.17039251e-01
-1.27776161e-01 -4.25424993e-01 -1.09214735e+00 3.74616563e-01
-1.14776874e+00 4.32212174e-01 6.19441509e-01 8.34330499e-01
3.38312984e-01 3.62497807e-01 1.14688933e+00 -5.27574360e-01
-1.13606405e+00 -6.04044676e-01 -8.71601164e-01 2.52826214e-01
3.34308445e-02 -8.95477057e-01 -5.84230900e-01 -2.65715450e-01] | [9.654389381408691, 3.035294771194458] |
b2a3eb66-a5aa-475e-9123-db6f3f41a3b0 | se-ssd-self-ensembling-single-stage-object | 2104.09804 | null | https://arxiv.org/abs/2104.09804v1 | https://arxiv.org/pdf/2104.09804v1.pdf | SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud | We present Self-Ensembling Single-Stage object Detector (SE-SSD) for accurate and efficient 3D object detection in outdoor point clouds. Our key focus is on exploiting both soft and hard targets with our formulated constraints to jointly optimize the model, without introducing extra computation in the inference. Specifically, SE-SSD contains a pair of teacher and student SSDs, in which we design an effective IoU-based matching strategy to filter soft targets from the teacher and formulate a consistency loss to align student predictions with them. Also, to maximize the distilled knowledge for ensembling the teacher, we design a new augmentation scheme to produce shape-aware augmented samples to train the student, aiming to encourage it to infer complete object shapes. Lastly, to better exploit hard targets, we design an ODIoU loss to supervise the student with constraints on the predicted box centers and orientations. Our SE-SSD attains top performance compared with all prior published works. Also, it attains top precisions for car detection in the KITTI benchmark (ranked 1st and 2nd on the BEV and 3D leaderboards, respectively) with an ultra-high inference speed. The code is available at https://github.com/Vegeta2020/SE-SSD. | ['Chi-Wing Fu', 'Li Jiang', 'Weiliang Tang', 'Wu Zheng'] | 2021-04-20 | null | http://openaccess.thecvf.com//content/CVPR2021/html/Zheng_SE-SSD_Self-Ensembling_Single-Stage_Object_Detector_From_Point_Cloud_CVPR_2021_paper.html | http://openaccess.thecvf.com//content/CVPR2021/papers/Zheng_SE-SSD_Self-Ensembling_Single-Stage_Object_Detector_From_Point_Cloud_CVPR_2021_paper.pdf | cvpr-2021-1 | ['birds-eye-view-object-detection'] | ['computer-vision'] | [-1.37571439e-01 1.93166226e-01 5.95895462e-02 -5.30160904e-01
-8.62958252e-01 -4.80898768e-01 4.71183032e-01 -7.37078935e-02
-2.66606331e-01 2.02446785e-02 -5.85790396e-01 -3.37373286e-01
2.37878859e-01 -5.59777677e-01 -1.11361527e+00 -7.33158410e-01
2.94516832e-01 6.88445330e-01 8.80984247e-01 -3.67601030e-02
-7.57416859e-02 6.40483737e-01 -1.60992992e+00 -1.97835505e-01
1.09220386e+00 1.29266334e+00 7.95030236e-01 5.45691311e-01
2.44579762e-01 5.55569172e-01 -2.95702517e-01 -4.83700216e-01
4.36710477e-01 1.50218830e-01 -4.15791310e-02 8.30745324e-02
8.56385350e-01 -5.08563638e-01 -3.26361746e-01 1.08355784e+00
5.11282325e-01 7.16026202e-02 8.69257987e-01 -1.24578118e+00
-3.78722370e-01 8.06690902e-02 -7.36708224e-01 8.13904032e-02
-7.79321715e-02 4.57378387e-01 8.84468555e-01 -1.23199499e+00
7.80990347e-02 1.23396361e+00 7.21125066e-01 3.94036144e-01
-9.68321860e-01 -8.65316033e-01 5.33314705e-01 2.21529573e-01
-1.41160250e+00 -2.72464961e-01 6.74358368e-01 -5.03473580e-01
7.19542384e-01 2.87767798e-01 8.12775254e-01 8.26221466e-01
-1.91644877e-01 1.21722710e+00 6.75481260e-01 -1.45588443e-01
1.51737168e-01 4.65239018e-01 1.64215550e-01 9.41058755e-01
2.71608084e-01 3.23119342e-01 -2.01002061e-01 1.01795182e-01
6.03852689e-01 -3.27215604e-02 5.07030729e-03 -6.57643020e-01
-8.38464379e-01 6.18667305e-01 7.66495287e-01 -4.58324611e-01
-2.73209035e-01 -4.90868241e-02 -1.03538081e-01 -2.50388265e-01
5.45891285e-01 8.35815072e-02 -4.59069848e-01 3.24574023e-01
-6.54031575e-01 3.73072565e-01 3.89592886e-01 1.34501505e+00
6.88430488e-01 -1.04901791e-01 -4.76258039e-01 7.71146655e-01
8.94042671e-01 1.03049767e+00 -2.34095618e-01 -6.86884940e-01
4.86220032e-01 7.31328309e-01 2.63845205e-01 -8.22027326e-01
-1.72410890e-01 -7.94279337e-01 -4.53196883e-01 4.48247582e-01
2.31447682e-01 1.91568330e-01 -1.24816394e+00 1.39924049e+00
9.91115510e-01 6.21267617e-01 -1.98764518e-01 1.23707795e+00
1.06595337e+00 6.94095731e-01 -8.07381868e-02 2.59316444e-01
1.50472724e+00 -1.15244222e+00 -1.06826164e-01 -6.54345751e-01
4.52107221e-01 -6.97597980e-01 9.78166640e-01 2.53022671e-01
-1.00314200e+00 -7.52618253e-01 -1.05754232e+00 -1.14158705e-01
1.33876910e-03 7.17665493e-01 4.09340352e-01 3.89366955e-01
-5.11990130e-01 2.02952385e-01 -1.09571886e+00 3.71788330e-02
7.02102125e-01 2.74131656e-01 1.14187106e-01 4.35951911e-02
-6.18514299e-01 8.74960005e-01 3.62084478e-01 3.21246296e-01
-1.22329581e+00 -1.03525496e+00 -9.24546182e-01 -4.31806855e-02
6.99741066e-01 -6.54507339e-01 1.47379994e+00 -3.80931914e-01
-1.67895365e+00 9.94926989e-01 -1.40469931e-02 -3.94487232e-01
6.61629677e-01 -3.77164871e-01 1.41297415e-01 -1.25758484e-01
-1.41870277e-02 9.90173340e-01 9.30858254e-01 -1.29275167e+00
-9.61298406e-01 -6.00320101e-01 -1.25734165e-01 2.73860514e-01
-1.52595684e-01 -2.14962646e-01 -1.01934659e+00 -4.55270022e-01
3.84194314e-01 -9.95889902e-01 -3.21353048e-01 3.62552375e-01
-4.71758932e-01 -5.31315327e-01 1.01873267e+00 -4.33241725e-01
7.17496574e-01 -2.24805641e+00 2.96227541e-02 1.96627285e-02
2.98966587e-01 5.01679897e-01 -5.24967052e-02 -2.24148691e-01
4.06669468e-01 -5.06614149e-01 -2.29849592e-01 -9.04437959e-01
1.81580290e-01 2.09250078e-01 -4.79299128e-01 5.45527518e-01
4.98887986e-01 9.52099919e-01 -7.14797199e-01 -4.91450965e-01
6.15626991e-01 5.31495690e-01 -5.92156231e-01 5.58102071e-01
-5.73562205e-01 3.17597330e-01 -7.53826618e-01 7.05654383e-01
1.17961967e+00 -3.24812204e-01 -3.76902342e-01 -1.07221559e-01
-2.80712694e-01 3.26411963e-01 -1.27789116e+00 1.23957467e+00
-3.26343179e-01 3.11117321e-01 2.59819925e-01 -7.88996398e-01
1.15609229e+00 -2.17920810e-01 4.25814390e-02 -3.65744472e-01
2.69268632e-01 1.28133476e-01 -3.89799148e-01 -1.76047072e-01
2.09424093e-01 3.73249114e-01 2.23292559e-01 -1.94647908e-01
-2.72360221e-02 -6.06153309e-01 -1.12745717e-01 1.48652181e-01
6.07149780e-01 3.36584300e-01 -1.71816885e-01 -1.94892466e-01
7.15544760e-01 1.15681395e-01 6.00021660e-01 7.24492610e-01
-1.69518948e-01 5.71956098e-01 1.30077422e-01 -1.66805670e-01
-8.89956653e-01 -1.23455977e+00 -3.32247168e-01 8.83447051e-01
5.60683787e-01 -5.78225218e-02 -5.89752734e-01 -8.81778061e-01
3.72473001e-01 7.61285484e-01 -3.03302199e-01 -1.94593921e-01
-3.83569628e-01 -5.32150090e-01 1.65714294e-01 7.77972221e-01
3.88449311e-01 -6.21727526e-01 -6.67573929e-01 -7.68009350e-02
2.22656891e-01 -1.28030539e+00 -4.96264845e-01 2.48643145e-01
-7.31663287e-01 -9.75316584e-01 -5.78336775e-01 -8.55285943e-01
8.16669583e-01 4.43886340e-01 9.46562588e-01 -3.92287523e-02
-3.40097845e-01 9.57688615e-02 -1.96262345e-01 -8.56724203e-01
-1.77526608e-01 -3.09954281e-04 -6.14499580e-03 -1.83560282e-01
4.66370523e-01 -2.37242267e-01 -5.75919151e-01 5.74852407e-01
-3.31467330e-01 3.44053298e-01 7.38106668e-01 6.35999262e-01
8.89521241e-01 -3.58399034e-01 6.10799529e-02 -3.39069068e-01
-2.88025141e-01 -2.98408955e-01 -1.49257421e+00 4.34510037e-02
-4.55978960e-01 -6.21844977e-02 3.60859215e-01 -5.08877218e-01
-1.04802668e+00 5.94380975e-01 -3.32808733e-01 -9.60070252e-01
-1.35491386e-01 -1.98702991e-01 -3.66955847e-01 -2.92194307e-01
4.19749618e-01 2.60612160e-01 -5.66330962e-02 -6.90564036e-01
1.55599669e-01 7.07209706e-01 6.34220600e-01 -5.40821075e-01
1.16516542e+00 4.90765601e-01 -1.66195515e-03 -8.65664601e-01
-1.24614227e+00 -7.02850163e-01 -4.46540207e-01 -2.96343356e-01
8.22091103e-01 -1.29136348e+00 -1.01329410e+00 7.30790913e-01
-1.13053775e+00 -4.31456506e-01 -1.49884790e-01 5.50219178e-01
-3.15160960e-01 1.53133422e-01 -3.14706177e-01 -1.04315817e+00
-3.19168419e-01 -1.18387961e+00 1.55405295e+00 4.56918299e-01
3.74305815e-01 -4.16708708e-01 -1.09036341e-01 5.29950798e-01
-4.09269035e-02 -6.57257512e-02 2.91944027e-01 -5.58359027e-01
-1.04960370e+00 -1.70352027e-01 -5.09398699e-01 4.96780932e-01
-2.48213187e-01 7.08503053e-02 -1.01471746e+00 -2.56892860e-01
-1.63181409e-01 -2.46984392e-01 1.04433954e+00 4.81815547e-01
1.26915956e+00 9.91378278e-02 -7.01321840e-01 8.40525508e-01
1.02105188e+00 -1.33651001e-02 1.00780241e-01 7.58406222e-02
7.86791027e-01 4.66522247e-01 9.11031127e-01 4.43708926e-01
6.59391284e-01 8.70762408e-01 8.10655355e-01 -1.00077987e-02
-8.71498361e-02 -4.59243238e-01 2.75569499e-01 4.21748847e-01
1.53202504e-01 -2.25949511e-01 -8.39225888e-01 4.51730788e-01
-1.79330266e+00 -4.69688445e-01 -4.23717976e-01 2.22076535e+00
5.72917461e-01 4.38889146e-01 2.06394553e-01 -3.38868648e-01
5.57643890e-01 -6.41001090e-02 -8.23491037e-01 3.88558179e-01
2.08256409e-01 -1.00706212e-01 5.78050077e-01 6.03689849e-01
-1.38142443e+00 1.13001060e+00 4.77416468e+00 8.67699683e-01
-8.98213506e-01 4.81323935e-02 4.65509951e-01 -1.93153828e-01
-2.22794618e-03 -8.32431093e-02 -1.62381911e+00 4.85054106e-01
4.29712743e-01 2.97843665e-01 2.60140630e-03 1.28520274e+00
2.11272493e-01 2.75946129e-02 -9.59515870e-01 7.72078812e-01
-2.04801500e-01 -1.07170606e+00 -3.17532867e-01 -2.31222939e-02
5.17362654e-01 4.11707342e-01 4.04468738e-02 4.73282754e-01
4.05530065e-01 -6.23573542e-01 1.11434317e+00 4.31205630e-01
4.04252321e-01 -7.78218627e-01 6.13186240e-01 7.95767784e-01
-1.35094154e+00 1.13582057e-04 -5.76194227e-01 1.75481126e-01
-5.57248853e-03 6.18667543e-01 -9.80854809e-01 3.93803507e-01
8.82098675e-01 6.33494079e-01 -6.40352845e-01 1.24539554e+00
-6.09662592e-01 5.95874906e-01 -8.86628807e-01 -2.80395389e-01
1.78748623e-01 -2.06573948e-01 9.47566569e-01 1.05050492e+00
3.10023129e-01 2.21844301e-01 5.93376935e-01 1.12658715e+00
1.46965638e-01 -2.64805764e-01 -1.00910813e-01 3.89932871e-01
6.90110564e-01 1.37054515e+00 -4.68639702e-01 -3.47799927e-01
-1.75399959e-01 7.47532606e-01 3.57101977e-01 -2.99843606e-02
-1.17202127e+00 -1.19416669e-01 9.12564576e-01 2.47925431e-01
7.03463733e-01 -1.43819258e-01 -2.28046581e-01 -9.25236046e-01
2.43544906e-01 -4.15913671e-01 2.15686023e-01 -7.77009189e-01
-1.23863459e+00 4.95725602e-01 8.94548297e-02 -1.18418443e+00
7.34105781e-02 -8.67867708e-01 -6.50438607e-01 7.80823231e-01
-1.68555701e+00 -1.34391868e+00 -6.40734553e-01 2.78642863e-01
4.91850853e-01 1.18498474e-01 1.40463635e-01 3.50326508e-01
-8.61016393e-01 6.58139944e-01 -1.86337277e-01 -8.57901108e-03
5.38075924e-01 -1.37668073e+00 6.17008626e-01 8.36374044e-01
1.45154670e-01 1.72744200e-01 6.45560205e-01 -6.36958778e-01
-1.44718909e+00 -1.27541888e+00 3.93734366e-01 -6.57751679e-01
3.45434040e-01 -7.56419778e-01 -9.43636179e-01 5.80450714e-01
-4.05586511e-01 3.26784879e-01 -1.52060548e-02 -1.12141214e-01
-2.51249403e-01 -2.97749281e-01 -9.81184185e-01 4.54584539e-01
1.12127733e+00 -3.60091738e-02 -5.53791642e-01 5.32896996e-01
9.81717229e-01 -1.05297518e+00 -3.55037451e-01 6.82775080e-01
3.75825793e-01 -7.12429523e-01 1.16314185e+00 -2.28315532e-01
1.13876410e-01 -7.63293266e-01 3.66548151e-02 -9.67179596e-01
-2.87762254e-01 -2.72468358e-01 -4.91901845e-01 1.05390680e+00
2.92767525e-01 -5.65486133e-01 1.17915690e+00 3.14441115e-01
-6.49861217e-01 -1.01468861e+00 -7.98185050e-01 -8.68912280e-01
-2.58048207e-01 -5.10813236e-01 5.88683367e-01 3.56414318e-01
-8.41345012e-01 1.62065834e-01 -1.33399814e-01 1.00284791e+00
1.02866721e+00 1.84129909e-01 1.18034065e+00 -1.29461479e+00
-4.47191387e-01 -3.30712110e-01 -2.38979235e-01 -1.77500844e+00
-4.52608103e-03 -8.50638866e-01 3.99678469e-01 -1.26757777e+00
3.95039804e-02 -6.65318429e-01 -4.49087424e-03 4.67667192e-01
-4.23613966e-01 2.15957999e-01 3.49366665e-01 -8.87664035e-03
-6.46364629e-01 9.16084290e-01 1.18022037e+00 -6.33013770e-02
-2.49585360e-01 6.57885551e-01 -3.91059190e-01 8.43114316e-01
4.56077605e-01 -5.82983494e-01 -1.85455948e-01 -3.88044268e-01
-9.74060521e-02 -2.86388338e-01 9.42716002e-01 -1.09801877e+00
3.46650541e-01 -6.88753724e-02 4.38234746e-01 -1.29140210e+00
5.07331014e-01 -8.44499052e-01 -1.87192246e-01 5.15970469e-01
6.53616711e-02 -4.99739587e-01 4.41564560e-01 5.37029028e-01
8.19717050e-02 -2.96627522e-01 1.13847649e+00 2.72520691e-01
-7.43319213e-01 6.39267206e-01 1.57812744e-01 -4.35681157e-02
1.23091769e+00 -1.70246959e-01 -1.50184184e-02 1.41487569e-01
-3.21140617e-01 9.49653864e-01 3.51134926e-01 5.28929353e-01
6.18031979e-01 -1.07804585e+00 -7.78819442e-01 4.26358730e-01
2.30806395e-01 8.22893977e-01 3.05778325e-01 7.38254726e-01
-4.17825460e-01 3.12529802e-01 3.14009756e-01 -1.22486460e+00
-1.34713018e+00 3.81233543e-01 3.94828469e-01 -7.88282603e-02
-7.58047462e-01 1.36245596e+00 4.19428945e-01 -7.75498509e-01
6.72648251e-01 -5.13258100e-01 8.45150724e-02 -1.99451342e-01
4.65599686e-01 2.27058887e-01 7.43065849e-02 -2.22388044e-01
-5.84617138e-01 5.10294557e-01 -1.51836216e-01 4.30340499e-01
1.30737185e+00 1.13679044e-01 3.35559160e-01 6.99863061e-02
8.11407864e-01 -7.18367696e-02 -1.97079813e+00 -2.75638223e-01
-3.21201921e-01 -5.25720000e-01 3.58817309e-01 -6.13357544e-01
-9.05246973e-01 8.01639855e-01 7.25226104e-01 -1.94324777e-01
8.38485181e-01 4.24902380e-01 6.89099967e-01 4.35700923e-01
1.61004081e-01 -6.68394148e-01 7.90248513e-02 6.45661831e-01
7.63835073e-01 -1.52406347e+00 -3.40432934e-02 -6.93027198e-01
-4.69499260e-01 7.68338978e-01 1.13721836e+00 -2.10060745e-01
4.90031362e-01 4.84332114e-01 -9.65088382e-02 -1.95058972e-01
-6.15719318e-01 -3.21968675e-01 7.54986405e-01 3.94589812e-01
-2.21582711e-01 4.19404311e-03 3.40885639e-01 6.43018782e-01
-1.43508911e-01 -3.81701887e-01 -1.32808521e-01 5.03416836e-01
-7.81796634e-01 -6.45947754e-01 -5.28259695e-01 3.82855862e-01
8.90862122e-02 1.01433218e-01 -2.56123722e-01 6.55665696e-01
1.79485396e-01 6.24344230e-01 2.13425830e-01 -3.45313638e-01
6.58347964e-01 -3.40447992e-01 4.28378761e-01 -7.47701406e-01
-3.49149436e-01 3.88211757e-02 -2.66098827e-01 -6.11819565e-01
7.43994787e-02 -6.95099831e-01 -1.15155494e+00 1.05036404e-02
-8.02007198e-01 -1.32507354e-01 6.89872265e-01 8.13643515e-01
4.66658413e-01 4.75351214e-01 6.49800956e-01 -1.12073028e+00
-9.72719312e-01 -8.69212151e-01 -2.14971915e-01 -1.45912632e-01
3.53613704e-01 -8.74611199e-01 -4.94684219e-01 -3.64506423e-01] | [7.832198619842529, -2.432886838912964] |
313abe1e-c5b8-4096-9c80-6218808a65b4 | achieving-real-time-object-detection-on | 2106.14943 | null | https://arxiv.org/abs/2106.14943v1 | https://arxiv.org/pdf/2106.14943v1.pdf | Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search | Object detection plays an important role in self-driving cars for security development. However, mobile systems on self-driving cars with limited computation resources lead to difficulties for object detection. To facilitate this, we propose a compiler-aware neural pruning search framework to achieve high-speed inference on autonomous vehicles for 2D and 3D object detection. The framework automatically searches the pruning scheme and rate for each layer to find a best-suited pruning for optimizing detection accuracy and speed performance under compiler optimization. Our experiments demonstrate that for the first time, the proposed method achieves (close-to) real-time, 55ms and 99ms inference times for YOLOv4 based 2D object detection and PointPillars based 3D detection, respectively, on an off-the-shelf mobile phone with minor (or no) accuracy loss. | ['Xue Lin', 'Yanzhi Wang', 'Bin Ren', 'Yuxuan Cai', 'Geng Yuan', 'Wei Niu', 'Pu Zhao'] | 2021-06-28 | null | null | null | null | ['compiler-optimization', 'real-time-object-detection'] | ['computer-code', 'computer-vision'] | [-2.59100169e-01 -1.30667239e-01 -7.16383755e-01 -4.42591310e-01
-5.45805991e-01 -3.66946697e-01 5.04659712e-01 1.25605181e-01
-5.07789850e-01 1.74879320e-02 -9.29932833e-01 -1.17461407e+00
3.80775422e-01 -9.28141594e-01 -8.36281598e-01 -2.64967054e-01
5.62259182e-02 5.67999005e-01 1.02152216e+00 -1.81198031e-01
2.76747704e-01 8.77643347e-01 -2.13152814e+00 -1.11454122e-01
6.90661430e-01 1.30998659e+00 5.27338266e-01 9.56303954e-01
-3.82598154e-02 1.96780384e-01 -4.89422381e-01 -4.85126168e-01
4.00162667e-01 5.20274520e-01 -1.82840049e-01 -2.00945869e-01
6.48727059e-01 -5.28198063e-01 -3.62304419e-01 1.23722959e+00
2.82509595e-01 -2.75486708e-01 5.67224681e-01 -1.53005373e+00
1.57954141e-01 2.78819233e-01 -7.41829038e-01 4.44460124e-01
-2.25534543e-01 3.53030682e-01 5.76771736e-01 -9.06475604e-01
1.07291274e-01 1.30350733e+00 6.06548071e-01 4.84899014e-01
-7.30648100e-01 -1.09918559e+00 -1.03847392e-01 2.62953877e-01
-1.65443432e+00 -8.93231034e-01 4.88535166e-01 -3.11488714e-02
1.72069907e+00 2.42538080e-01 5.11922419e-01 4.66790766e-01
3.19135725e-01 7.82797992e-01 4.08662885e-01 -3.41051757e-01
3.00067902e-01 5.09175956e-01 2.28182003e-01 1.26763237e+00
6.94297910e-01 4.36496943e-01 -3.73920470e-01 8.24188888e-02
1.88963264e-01 -3.83542180e-01 6.49328768e-01 -2.19953209e-01
-5.76195180e-01 7.84420729e-01 2.02868611e-01 -2.44660571e-01
6.53483048e-02 5.61354697e-01 4.22713280e-01 1.99121032e-02
1.88412279e-01 -3.63115780e-02 -4.54247028e-01 -3.72672975e-01
-1.00168836e+00 3.59620571e-01 6.86789215e-01 1.61943555e+00
7.93859422e-01 2.36007988e-01 2.18407571e-01 5.40357769e-01
5.78404784e-01 1.04355097e+00 2.23042473e-01 -8.66069674e-01
6.08630955e-01 5.56171894e-01 -1.50514707e-01 -9.95244265e-01
-4.26856577e-01 -2.47817561e-01 -5.18202841e-01 5.55099785e-01
-4.88541424e-02 1.79535553e-01 -7.85100341e-01 1.17097938e+00
7.48042941e-01 2.99131334e-01 7.21408948e-02 6.38929129e-01
8.81305873e-01 4.84242499e-01 2.89257038e-02 -7.24667497e-03
1.79286563e+00 -9.22891855e-01 -2.18347058e-01 -3.85028124e-01
8.38430643e-01 -5.95402360e-01 8.44877422e-01 3.06209803e-01
-1.03903079e+00 -6.85323060e-01 -1.66185880e+00 -1.27988026e-01
-4.73623186e-01 3.13449651e-01 7.89205134e-01 1.30404019e+00
-6.08058155e-01 1.05142742e-01 -1.14703047e+00 -1.61732078e-01
5.62210798e-01 7.60208607e-01 1.90273374e-01 3.27418119e-01
-8.11292112e-01 9.65242505e-01 3.79769981e-01 -2.51290470e-01
-9.92764056e-01 -6.62125885e-01 -7.31883943e-01 -4.35904674e-02
7.09956706e-01 -3.66904467e-01 1.38678467e+00 -2.51403034e-01
-1.62913144e+00 9.48955774e-01 -3.50749344e-01 -1.10404146e+00
2.74018347e-01 -8.61706510e-02 -4.25331563e-01 7.77323246e-02
2.49880571e-02 1.09141409e+00 9.13922131e-01 -8.89685333e-01
-1.26696086e+00 -4.29494530e-01 3.39036174e-02 7.18909130e-02
-2.90791363e-01 -8.85785520e-02 -9.89390492e-01 9.82760545e-03
-4.90950234e-02 -1.02905250e+00 -1.35396868e-01 2.75791250e-02
-2.18693212e-01 -4.47222441e-01 1.39092171e+00 -8.55717361e-02
1.04449058e+00 -2.24668479e+00 -8.75352979e-01 1.31172404e-01
1.16395220e-01 6.20415688e-01 7.50152245e-02 -5.87035060e-01
5.20273149e-01 8.15955624e-02 2.07199350e-01 -4.39794630e-01
-1.24756014e-03 2.93768495e-01 -1.66156545e-01 4.58714664e-01
2.26978421e-01 8.57399583e-01 -6.70555353e-01 -8.92731428e-01
5.55645406e-01 1.75797611e-01 -7.37384379e-01 -1.68580383e-01
-1.47893324e-01 -5.90539157e-01 -4.72058773e-01 1.00633419e+00
9.43144500e-01 2.31891587e-01 -5.89294098e-02 -1.35789245e-01
-2.68654943e-01 4.55171585e-01 -1.12039769e+00 1.21026695e+00
-5.44471264e-01 8.70763004e-01 2.08769292e-01 -6.36742711e-01
9.57495511e-01 -2.42241278e-01 -5.75283775e-03 -9.49031353e-01
3.15596014e-01 2.25659415e-01 -1.13811105e-01 -1.78168982e-01
1.14560556e+00 3.40061575e-01 -9.83742848e-02 7.32424250e-03
-2.16933832e-01 -5.40106893e-01 2.60538727e-01 6.13858290e-02
8.23394299e-01 -2.69513428e-01 1.78244784e-01 -2.97440529e-01
4.93617982e-01 2.49354243e-01 2.91326016e-01 1.02672768e+00
-4.51204509e-01 -6.74452782e-02 2.95218229e-01 -2.28773341e-01
-1.01840556e+00 -6.79093361e-01 -4.18174237e-01 1.01591575e+00
5.75346529e-01 -4.09756601e-01 -9.03676212e-01 -6.66405797e-01
3.10132891e-01 8.86852980e-01 8.12018812e-02 -1.13859624e-01
-6.44288599e-01 -5.77407718e-01 8.83041859e-01 5.79276562e-01
6.54220939e-01 -4.86456782e-01 -1.20795310e+00 1.02827862e-01
5.32802701e-01 -1.51154029e+00 -9.61124077e-02 4.72040743e-01
-9.44769740e-01 -9.00171876e-01 1.45094618e-01 -9.28114653e-01
4.78564829e-01 7.87700713e-01 9.86180842e-01 3.47200394e-01
-3.39063376e-01 -1.39090687e-01 1.43284306e-01 -7.89790690e-01
-6.90107226e-01 3.64977270e-01 3.70901525e-01 -6.94246411e-01
5.90811610e-01 -6.97144046e-02 -2.84666747e-01 5.79663336e-01
-2.90820390e-01 -3.21990787e-03 4.70464557e-01 4.31932092e-01
6.68549836e-01 5.27195930e-01 1.79373696e-01 -4.71891016e-01
2.35100910e-01 -1.39055073e-01 -1.59230995e+00 -1.28526852e-01
-9.70801651e-01 3.12002487e-02 3.85365874e-01 -3.71011525e-01
-6.15473151e-01 3.27434778e-01 -2.56406575e-01 -5.13809502e-01
-2.03514695e-01 -1.34288669e-01 -2.21953750e-01 -3.93496484e-01
6.07326508e-01 -7.91066885e-02 3.64109315e-02 1.38296059e-03
3.56304109e-01 8.69937122e-01 6.57037914e-01 -3.85267526e-01
7.23747611e-01 4.62683707e-01 3.56751919e-01 -1.16225004e+00
-2.69263029e-01 -4.64848131e-01 -4.18741316e-01 -4.79960293e-02
5.86450458e-01 -1.14139044e+00 -1.17534208e+00 3.00341219e-01
-9.48210180e-01 -2.30232671e-01 3.39642130e-02 1.81386873e-01
-4.18834984e-01 2.80230731e-01 -1.08178750e-01 -1.09478855e+00
-5.11195123e-01 -1.58572078e+00 1.28158009e+00 1.63113356e-01
-1.92236491e-02 -1.75966009e-01 -6.43585026e-01 2.14252740e-01
1.42773360e-01 -5.41641533e-01 8.45611572e-01 -4.82857347e-01
-1.02013648e+00 -4.95958716e-01 -4.77081925e-01 -3.93099524e-02
-4.31243986e-01 1.80316225e-01 -9.11054313e-01 -1.77801494e-02
-2.41305932e-01 1.10798433e-01 7.12656736e-01 3.12321782e-01
1.24917662e+00 -1.27401754e-01 -7.04843879e-01 7.41377473e-01
1.18733263e+00 4.34289902e-01 3.89648169e-01 2.74756938e-01
4.82255936e-01 9.84379649e-02 1.10720146e+00 2.98264593e-01
3.77292246e-01 1.01027167e+00 7.37209916e-01 2.59611160e-01
-2.48780891e-01 -2.01571658e-01 2.72073716e-01 3.99383008e-01
4.53280509e-01 -2.20519364e-01 -8.39030743e-01 4.38389957e-01
-1.48875237e+00 -6.85281515e-01 -2.41760090e-01 2.19742274e+00
5.80832958e-01 1.10942400e+00 3.23101431e-01 2.05509946e-01
6.06607974e-01 -1.02720514e-01 -6.41188681e-01 -6.17803335e-01
1.55523822e-01 -7.78273214e-03 1.25952828e+00 6.37421191e-01
-1.24112809e+00 1.38987863e+00 6.37448120e+00 1.37099922e+00
-1.09904051e+00 1.34124309e-01 6.17640316e-01 -2.71216750e-01
1.13893352e-01 -1.39575183e-01 -1.88474393e+00 3.48258555e-01
1.28460991e+00 7.15248734e-02 2.65841305e-01 1.53063047e+00
1.30938932e-01 -2.49545842e-01 -8.85044038e-01 1.01466525e+00
-1.01871386e-01 -1.52579308e+00 -1.74465105e-01 6.02149963e-02
2.92664528e-01 2.63035595e-01 7.46432021e-02 4.63455379e-01
8.03768709e-02 -6.78661525e-01 1.08572602e+00 -1.60991371e-01
1.03873742e+00 -1.29467368e+00 6.03145838e-01 5.99763989e-01
-1.34326470e+00 -7.39680529e-02 -6.21050179e-01 1.88319445e-01
-4.33403719e-03 4.31167275e-01 -1.51152599e+00 -2.84875095e-01
8.50516677e-01 1.41953021e-01 -6.14255965e-01 6.90208137e-01
7.65020847e-02 5.77322483e-01 -8.78797174e-01 -6.86740458e-01
1.79571792e-01 3.71625215e-01 7.26450026e-01 1.37227738e+00
3.87312979e-01 7.82432780e-02 -4.56530116e-02 5.93883157e-01
-5.93325719e-02 -4.01278555e-01 -6.28886521e-01 1.63270414e-01
8.69551122e-01 1.26232946e+00 -1.07562315e+00 -4.84857947e-01
-1.73028320e-01 4.09419894e-01 -1.18482865e-01 -1.10998094e-01
-1.41273916e+00 -5.22006392e-01 9.66794670e-01 3.55544090e-01
7.46286154e-01 -6.06958926e-01 -6.77275121e-01 -4.22504038e-01
-2.00545758e-01 -7.02518404e-01 -1.63610056e-01 -3.24690312e-01
-2.69009203e-01 3.66417170e-01 1.27860337e-01 -9.36497509e-01
-1.96494877e-01 -9.99643266e-01 -1.95599943e-01 2.08384871e-01
-1.51110232e+00 -8.50699961e-01 -1.57359466e-01 1.53118640e-01
7.38727093e-01 -6.79486513e-01 2.81739295e-01 3.54158282e-01
-6.01508439e-01 1.10130632e+00 -2.09125310e-01 -3.02934438e-01
6.42592981e-02 -8.32389712e-01 9.76632476e-01 8.77009213e-01
1.54726654e-01 3.84712160e-01 6.30814791e-01 -6.38088822e-01
-1.86788571e+00 -1.17560434e+00 7.08418906e-01 -3.50912005e-01
2.59418547e-01 -5.30602336e-01 -4.38362122e-01 1.04637250e-01
-2.64283448e-01 -5.13207838e-02 1.05308078e-01 1.51617885e-01
-2.22418830e-01 -5.33074200e-01 -1.25457680e+00 8.58282745e-01
1.09165716e+00 -3.35823476e-01 -3.50863338e-02 2.70228535e-01
9.37783360e-01 -8.99836004e-01 -2.44657591e-01 4.90751624e-01
7.54351616e-01 -8.16531956e-01 1.21546447e+00 -9.24107805e-02
-2.45829284e-01 -5.62446356e-01 -2.93064386e-01 -6.60901219e-02
-6.08638152e-02 -6.89381838e-01 -5.54634333e-01 9.22764957e-01
4.93129879e-01 -4.44018066e-01 1.30870461e+00 2.65173972e-01
-4.64056790e-01 -8.43145311e-01 -1.25091863e+00 -7.89908767e-01
-4.14481759e-01 -1.25438106e+00 8.78078282e-01 1.03540264e-01
-6.30244911e-01 3.78610611e-01 1.27453670e-01 7.24424779e-01
6.28916740e-01 -8.46595317e-02 1.18649316e+00 -9.95727360e-01
2.90453713e-02 -7.69663393e-01 -7.62237608e-01 -1.50033784e+00
1.97086766e-01 -6.91164553e-01 2.14468271e-01 -6.62163854e-01
-4.57445271e-02 -8.12388182e-01 1.43257111e-01 3.54093075e-01
2.04518080e-01 3.00955117e-01 4.94828506e-04 -1.74689218e-01
-9.03365970e-01 5.18083051e-02 4.51268166e-01 -2.73819387e-01
-2.13024393e-01 2.97329485e-01 -4.67606962e-01 8.77612710e-01
5.71872115e-01 -5.78490376e-01 -3.47805470e-01 -3.81165475e-01
1.86143562e-01 -9.66691822e-02 4.16711122e-01 -1.32017052e+00
3.42295468e-01 -6.75325617e-02 1.62766263e-01 -1.45609510e+00
4.33725059e-01 -8.00196290e-01 -2.19586924e-01 7.86217988e-01
6.06817640e-02 4.16506976e-02 6.96049333e-01 4.33527321e-01
2.91551501e-01 -4.82373685e-01 9.40813184e-01 2.54295111e-01
-1.10398400e+00 2.33091757e-01 -6.73488319e-01 -3.04670811e-01
1.08145654e+00 -5.85203826e-01 -1.88469201e-01 1.85096357e-02
1.86041035e-02 3.99997383e-01 3.65594655e-01 5.45537412e-01
7.36005783e-01 -1.04849041e+00 -2.39325568e-01 6.42942488e-01
-1.16789714e-02 1.97475001e-01 -9.55501273e-02 4.24795926e-01
-8.15887094e-01 9.52119470e-01 1.85369462e-01 -1.13771713e+00
-1.60862792e+00 5.68149149e-01 2.69428998e-01 1.97322965e-02
-3.44623417e-01 9.91738439e-01 -1.07969351e-01 -1.96106553e-01
4.50055569e-01 -6.54506207e-01 1.95456728e-01 -3.04955304e-01
3.98124009e-01 6.18582010e-01 4.82730418e-01 -5.85270464e-01
-6.46604896e-01 4.34447408e-01 -4.43796553e-02 -2.34147739e-02
5.35290599e-01 -5.30224890e-02 4.37403470e-01 2.24128515e-02
1.11144805e+00 5.62433302e-02 -1.11426091e+00 1.62079886e-01
-1.53923973e-01 -3.81677300e-01 5.49699068e-01 -2.95115292e-01
-8.78159404e-01 9.04039025e-01 9.90188479e-01 1.35097042e-01
8.42792630e-01 -5.09112403e-02 1.08304322e+00 9.39346790e-01
5.62218368e-01 -1.21692753e+00 -2.81730205e-01 6.77515626e-01
1.75588042e-01 -1.39682865e+00 3.78659964e-01 -5.32782853e-01
-2.91301847e-01 9.49555337e-01 8.98516178e-01 6.77169412e-02
7.17338741e-01 7.03921437e-01 -3.70740980e-01 -1.40664652e-01
-8.59309196e-01 -2.53450334e-01 2.26750821e-01 6.17738843e-01
-2.46126682e-01 1.84438601e-01 2.31989577e-01 2.57379174e-01
-3.62894624e-01 -3.40526521e-01 -4.54835594e-02 7.53045201e-01
-8.41329038e-01 -7.10001647e-01 -2.91081309e-01 3.63648683e-01
-1.93588182e-01 -1.90212633e-02 1.44917056e-01 9.94168222e-01
3.41928184e-01 1.02777517e+00 4.14019555e-01 -6.71904862e-01
3.71181339e-01 -2.70364910e-01 3.88909817e-01 -3.70268255e-01
-3.01047593e-01 1.24934390e-02 2.66091943e-01 -6.26705050e-01
1.15554295e-01 -5.18041730e-01 -1.48977602e+00 -4.71552312e-01
-8.27367723e-01 -2.30247721e-01 1.25803351e+00 7.05642343e-01
6.93237603e-01 1.91960230e-01 5.03803074e-01 -8.85421395e-01
-4.75867450e-01 -4.18252558e-01 -1.92669481e-01 -5.09186685e-01
2.71943748e-01 -7.45040059e-01 -1.37130335e-01 -3.28713477e-01] | [8.22231388092041, -1.1965583562850952] |
e5ecdb79-4569-479b-9252-632b09bfeaf3 | lasso-based-feature-selection-for-malaria | 1511.01284 | null | http://arxiv.org/abs/1511.01284v1 | http://arxiv.org/pdf/1511.01284v1.pdf | Lasso based feature selection for malaria risk exposure prediction | In life sciences, the experts generally use empirical knowledge to recode
variables, choose interactions and perform selection by classical approach. The
aim of this work is to perform automatic learning algorithm for variables
selection which can lead to know if experts can be help in they decision or
simply replaced by the machine and improve they knowledge and results. The
Lasso method can detect the optimal subset of variables for estimation and
prediction under some conditions. In this paper, we propose a novel approach
which uses automatically all variables available and all interactions. By a
double cross-validation combine with Lasso, we select a best subset of
variables and with GLM through a simple cross-validation perform predictions.
The algorithm assures the stability and the the consistency of estimators. | ['Noël Fonton', 'Bienvenue Kouwayè', 'Fabrice Rossi'] | 2015-11-04 | null | null | null | null | ['malaria-risk-exposure-prediction'] | ['medical'] | [ 1.39619395e-01 1.02420291e-02 -4.55173552e-01 -4.05100286e-01
-2.01773003e-01 -3.54090750e-01 3.64632308e-01 2.30846450e-01
-3.42365116e-01 1.51737833e+00 -1.61706492e-01 -2.51502752e-01
-5.63676357e-01 -7.12625384e-01 -4.66941565e-01 -7.38060772e-01
-1.01431780e-01 8.68582368e-01 -2.10019141e-01 -4.84367646e-02
4.03432339e-01 5.20832062e-01 -1.66523862e+00 -1.06178105e-01
1.31165385e+00 5.12384057e-01 1.32312208e-01 3.29826921e-01
-1.90569207e-01 4.48643863e-01 -2.35017285e-01 -1.59187257e-01
2.88778007e-01 -7.08965302e-01 -5.60878456e-01 -7.02993646e-02
-1.32342145e-01 2.05200166e-01 6.57209754e-01 8.71992171e-01
5.05277872e-01 2.91607976e-01 9.26777840e-01 -1.10844028e+00
-1.04531124e-01 8.87075782e-01 -3.80520225e-01 -1.18373230e-01
4.41708028e-01 3.33803855e-02 8.53289604e-01 -8.85919750e-01
7.09294438e-01 1.44539201e+00 6.75926387e-01 3.20402622e-01
-1.60118723e+00 -7.01485395e-01 4.54135127e-02 2.14691758e-01
-1.52781332e+00 -3.59888345e-01 7.36954510e-01 -7.57295132e-01
4.91157442e-01 5.05159199e-01 6.88520133e-01 8.65498185e-01
1.25818819e-01 3.87686849e-01 1.54991114e+00 -7.19639540e-01
3.01988691e-01 7.55439520e-01 4.40040499e-01 6.43127680e-01
4.44531202e-01 2.98535138e-01 -5.19577205e-01 -2.76255906e-01
3.46163362e-01 -8.55959058e-02 -2.56625116e-01 -1.37877896e-01
-8.84487689e-01 9.88193214e-01 -6.94451332e-02 4.96483564e-01
-6.57130063e-01 -2.90114641e-01 1.60676092e-01 3.24007273e-01
2.84086704e-01 7.48967052e-01 -7.57398844e-01 4.25985098e-01
-1.06482387e+00 2.03176454e-01 9.95667756e-01 3.56603563e-01
6.77298069e-01 -2.83541456e-02 -5.84452599e-02 7.22268403e-01
3.56968850e-01 4.30044681e-01 5.93093038e-01 -5.87034643e-01
1.03517221e-02 8.32746267e-01 4.53938032e-03 -1.15599203e+00
-6.97040439e-01 -7.85714567e-01 -8.37365746e-01 7.04199910e-01
1.98106408e-01 -4.11126971e-01 -7.31391668e-01 1.53297687e+00
5.42734325e-01 9.25052539e-02 -2.30183467e-01 7.40667582e-01
5.26563168e-01 2.90042460e-01 2.41661221e-01 -9.68098402e-01
8.15836370e-01 -4.75592524e-01 -9.41440701e-01 3.10718715e-01
6.88230932e-01 -5.16074836e-01 4.74578947e-01 9.86216962e-01
-6.21324062e-01 -6.00916386e-01 -9.57137465e-01 4.07214731e-01
-5.07343471e-01 5.25074422e-01 7.77635217e-01 4.23373699e-01
-5.48957825e-01 1.04307520e+00 -4.56767112e-01 -2.53353029e-01
6.80952296e-02 8.49074423e-01 -5.88374913e-01 4.70205039e-01
-1.10960662e+00 1.03916383e+00 7.48850644e-01 1.92313015e-01
-5.88211477e-01 -3.46449375e-01 -3.77607554e-01 -9.39066336e-02
3.47935766e-01 -8.44673753e-01 2.28645816e-01 -1.64771712e+00
-1.32238817e+00 7.29782879e-01 -2.39347503e-01 -6.13660455e-01
8.60615432e-01 -1.34772047e-01 -1.83151662e-01 -2.85905540e-01
1.59085795e-01 -2.15077214e-02 7.59526014e-01 -1.18286026e+00
-5.01122057e-01 -5.99432886e-01 -4.94780004e-01 2.20345352e-02
-7.38074556e-02 -7.27746412e-02 1.34038970e-01 -4.79541481e-01
3.33885133e-01 -8.37028325e-01 -4.73112255e-01 -3.67097706e-01
-4.86058414e-01 -3.05063456e-01 2.92542398e-01 -7.92108476e-01
1.48734772e+00 -1.88872778e+00 5.02269149e-01 7.31331348e-01
1.37553677e-01 9.71682370e-02 3.34013343e-01 4.17272210e-01
-3.72111022e-01 5.41771233e-01 -2.59659380e-01 -1.50579318e-01
-3.79213601e-01 1.76541619e-02 -4.52262396e-03 5.62335134e-01
2.84267752e-03 1.67809531e-01 -4.52505976e-01 -9.53079045e-01
3.16434920e-01 1.79603606e-01 -2.81812727e-01 3.38334560e-01
-1.30734637e-01 8.63496542e-01 -8.83500814e-01 5.65966308e-01
6.44573510e-01 4.81656007e-02 3.48512024e-01 -1.37980923e-01
-1.80763006e-01 -1.61749080e-01 -1.66459000e+00 9.12553132e-01
-1.80904523e-01 2.99467921e-01 3.77259380e-03 -1.36145234e+00
1.38078773e+00 2.68313229e-01 4.38086390e-01 -8.37558061e-02
2.77879924e-01 5.56940258e-01 -7.55614936e-02 -7.91950762e-01
-5.33085883e-01 -2.21259072e-01 4.69278634e-01 2.18312163e-02
-2.56763399e-02 2.12237865e-01 1.94098294e-01 -3.44265401e-01
5.94058633e-01 3.10871691e-01 9.74000454e-01 -4.64980364e-01
1.03835571e+00 3.86176370e-02 8.39528680e-01 8.89325142e-01
3.09166223e-01 6.02042079e-02 5.94413877e-01 -4.19529438e-01
-7.60007203e-01 -5.64885914e-01 -5.86420536e-01 8.61099541e-01
-4.51362520e-01 1.86768800e-01 -2.64878452e-01 -8.07522297e-01
3.40107858e-01 8.44059765e-01 -8.39317441e-01 9.93535817e-02
-3.70758504e-01 -8.86056006e-01 6.62881583e-02 -8.52962211e-02
2.50776350e-01 -8.54721487e-01 -1.67398095e-01 2.81578422e-01
3.51047188e-01 -2.20943764e-01 5.03113329e-01 5.83805621e-01
-1.09519577e+00 -1.20814931e+00 -3.42373401e-01 -4.13755715e-01
6.64737761e-01 -4.95743066e-01 8.27825367e-01 3.15375775e-01
-1.68700427e-01 -5.58782637e-01 -6.43165171e-01 -4.26917344e-01
-3.55971545e-01 1.38709635e-01 1.26867712e-01 1.59174025e-01
2.09001392e-01 -8.50894630e-01 -1.62938252e-01 2.03030810e-01
-2.77911365e-01 -9.65131745e-02 7.28868663e-01 1.06194234e+00
6.07521713e-01 4.41735126e-02 7.26998031e-01 -1.38619018e+00
4.98355031e-01 -7.01972783e-01 -8.01966786e-01 3.38354409e-01
-1.16215408e+00 4.30786908e-01 7.89389014e-01 -2.34591812e-01
-8.59047115e-01 2.91302234e-01 1.21298574e-01 -2.14148283e-01
-6.53454810e-02 8.66662204e-01 -3.09288502e-01 -2.35613540e-01
8.28369439e-01 -2.70124804e-02 -2.19167754e-01 -6.78806007e-01
-6.86554685e-02 5.87931395e-01 -1.17194138e-01 -2.66998649e-01
5.29782653e-01 3.68512012e-02 6.37317181e-01 -5.16526997e-01
-5.63143253e-01 -2.28652671e-01 -9.24531043e-01 -1.54844567e-01
7.59487867e-01 -4.59796995e-01 -8.01228583e-01 -1.32123038e-01
-9.02604461e-01 6.98048472e-02 2.05856338e-01 9.71039832e-01
-3.91374230e-01 1.30174324e-01 2.31695130e-01 -1.42230701e+00
-3.09009403e-01 -8.74159336e-01 4.09258902e-01 1.58856317e-01
-3.03908646e-01 -1.06837964e+00 1.96064450e-02 1.68121129e-01
-8.48513395e-02 5.22858918e-01 6.97491169e-01 -1.30328178e+00
-3.01971644e-01 -2.82210082e-01 3.14862251e-01 2.65052140e-01
-1.31768407e-02 3.08698744e-01 -6.87213659e-01 -7.92126432e-02
-9.43280831e-02 -5.69389313e-02 9.61316466e-01 6.81444407e-01
1.05709898e+00 -7.37240165e-02 -7.20170319e-01 8.76884580e-01
1.48893881e+00 4.17801827e-01 2.89376140e-01 4.17497396e-01
3.97068679e-01 6.89238727e-01 9.51266944e-01 6.79876506e-01
-3.09036314e-01 5.78534126e-01 6.18573800e-02 -1.17062621e-01
3.39956522e-01 -6.20844439e-02 -2.53580883e-02 4.35862064e-01
-2.52411187e-01 -2.14190289e-01 -9.37980473e-01 1.84607536e-01
-2.08246183e+00 -7.93673098e-01 -5.20584702e-01 2.52050447e+00
1.00154495e+00 1.72711223e-01 1.20138526e-01 2.72020191e-01
7.72352576e-01 -5.19658327e-01 -3.16713244e-01 -3.62119883e-01
-4.34102237e-01 7.06159696e-02 8.18321645e-01 9.57024336e-01
-9.87747312e-01 8.35574269e-01 6.98900223e+00 8.18422079e-01
-1.00481391e+00 -1.63862273e-01 7.11271524e-01 1.45262197e-01
-2.77364910e-01 3.89985770e-01 -1.00839126e+00 4.07303005e-01
6.87232137e-01 -1.91104412e-01 4.58638728e-01 6.38142884e-01
7.18536794e-01 -3.73538673e-01 -1.04359436e+00 7.98946559e-01
3.74159887e-02 -7.25234389e-01 -3.43028307e-02 -1.20274723e-01
6.95219398e-01 -6.65872097e-01 -3.76508802e-01 1.12455729e-02
3.21948320e-01 -1.34158945e+00 1.20581344e-01 1.26515412e+00
2.43227884e-01 -5.69120646e-01 9.93112922e-01 5.61285257e-01
-7.01842964e-01 -2.33913675e-01 -2.73277372e-01 -2.99868226e-01
-6.59809858e-02 9.34695601e-01 -1.07517517e+00 7.07203090e-01
2.70578325e-01 6.40436769e-01 -6.83849871e-01 1.28595316e+00
-1.68061003e-01 8.39823246e-01 -4.42931563e-01 -4.12637740e-01
-2.48805329e-01 -5.59142232e-01 8.30540121e-01 1.02017617e+00
2.95285165e-01 1.17038988e-01 2.93037325e-01 9.36970472e-01
5.58516979e-01 9.01012540e-01 -5.24844289e-01 2.67520342e-02
6.91164494e-01 8.00277889e-01 -6.45408750e-01 -4.05297160e-01
4.88420576e-02 6.62518084e-01 2.85593331e-01 4.39677119e-01
-4.89212662e-01 -2.33402565e-01 -1.95355434e-02 1.69785544e-01
-5.18752895e-02 4.03290577e-02 -6.70787632e-01 -9.38920319e-01
-2.48687029e-01 -9.78716373e-01 6.30366862e-01 -4.85306293e-01
-1.11735797e+00 3.21153164e-01 1.44851327e-01 -1.04805422e+00
-1.43405601e-01 -6.82370543e-01 -4.98189360e-01 1.10851705e+00
-8.93817186e-01 -9.69616473e-01 -2.99340170e-02 3.46290171e-01
2.93303490e-01 -4.28526372e-01 6.64537251e-01 5.08250371e-02
-7.68096328e-01 2.90008247e-01 4.68149662e-01 -2.09341884e-01
8.18080723e-01 -1.24844778e+00 -8.13426018e-01 5.23889780e-01
-3.73900920e-01 8.15174043e-01 1.30748713e+00 -1.08724821e+00
-9.73717153e-01 -5.20678461e-01 1.01790106e+00 -2.74551362e-02
3.42697889e-01 5.90761937e-02 -7.03462660e-01 6.04995131e-01
-2.43877873e-01 -4.24405843e-01 8.16727161e-01 5.38253486e-01
3.32988888e-01 -3.16199988e-01 -1.18279135e+00 3.32974374e-01
5.60225189e-01 7.73595124e-02 -5.38136303e-01 4.18247342e-01
2.15747222e-01 1.87095687e-01 -8.11118722e-01 4.55848545e-01
6.76355004e-01 -9.06250715e-01 7.48524010e-01 -1.02463901e+00
5.88494763e-02 -3.93302292e-01 2.60625649e-02 -1.16819847e+00
-4.28842634e-01 -4.75675315e-01 3.63594532e-01 1.48441684e+00
7.79499173e-01 -7.43344307e-01 5.40535152e-01 5.17016590e-01
5.21879137e-01 -6.49968922e-01 -8.60170186e-01 -4.81825709e-01
-1.17975891e-01 1.36087229e-03 3.24421287e-01 1.21589625e+00
-8.79260525e-02 4.10827816e-01 -6.91763401e-01 2.10135859e-02
7.62237668e-01 1.44099563e-01 7.86734402e-01 -1.81250203e+00
-4.49878395e-01 -4.35879260e-01 -5.12499690e-01 -1.43610045e-01
3.31150353e-01 -7.85152256e-01 -2.35830233e-01 -1.23976731e+00
1.16189003e-01 -4.51908052e-01 -3.44554991e-01 4.18642461e-01
-4.22940642e-01 -4.03122246e-01 -1.96487889e-01 1.20461412e-01
-1.98153809e-01 4.00956333e-01 9.44638014e-01 2.08169982e-01
-6.82124913e-01 2.75604844e-01 -3.80580962e-01 7.34737933e-01
7.90592194e-01 -7.30613530e-01 -2.77570069e-01 3.06862295e-01
4.05831784e-01 2.45646045e-01 2.02559754e-01 -8.30064535e-01
-1.22571491e-01 -7.32303798e-01 7.81823158e-01 -3.16038966e-01
-1.47821411e-01 -9.77906525e-01 7.82407939e-01 5.79583406e-01
-5.86943865e-01 -3.19343269e-01 -2.37492695e-01 3.43603343e-01
9.09541734e-03 -8.63103449e-01 6.74356401e-01 -2.31371343e-01
-2.95176953e-01 -7.82749951e-02 -2.14552417e-01 -3.47676605e-01
1.13694501e+00 -2.13342384e-01 4.31959867e-01 -2.69480199e-01
-1.34235406e+00 4.52277571e-01 1.36740506e-01 -2.36378536e-01
1.62916005e-01 -9.21197832e-01 -9.53065515e-01 2.14276966e-02
-4.33101237e-01 -6.11084938e-01 -1.49452835e-01 1.06044352e+00
-4.96523768e-01 2.29882345e-01 -3.71652871e-01 -2.24890217e-01
-1.59891176e+00 7.30328619e-01 5.23469448e-01 -2.49172524e-01
1.93925807e-03 7.50634551e-01 -1.70652419e-01 -2.10390925e-01
-2.63681673e-02 3.08279842e-01 -9.67596233e-01 3.50223273e-01
2.76580393e-01 6.30153716e-01 -3.72281969e-01 -4.22038376e-01
-4.54538405e-01 6.94732845e-01 3.78132135e-01 -1.17996499e-01
1.32253432e+00 -2.32376635e-01 -4.84573990e-01 9.04002845e-01
9.98914897e-01 3.22167635e-01 -6.23155534e-01 1.01815529e-01
4.70299274e-02 -5.90207458e-01 2.12588117e-01 -1.04320025e+00
-7.03054070e-01 5.52342176e-01 7.45661259e-01 2.34979302e-01
1.17201722e+00 -2.67468631e-01 -2.65966713e-01 4.62172031e-01
6.73681498e-02 -1.20149350e+00 -7.20674574e-01 -1.24616111e-02
1.08811760e+00 -1.45005655e+00 5.13098896e-01 -6.71144009e-01
-5.67425489e-01 1.40395617e+00 4.26293641e-01 -1.91402197e-01
8.16624582e-01 -1.87252257e-02 -1.97341263e-01 5.08616418e-02
-7.69547105e-01 -4.26372349e-01 3.41238439e-01 4.79210109e-01
7.50501692e-01 2.58037239e-01 -1.58972049e+00 9.46749330e-01
-1.46537974e-01 2.84014344e-01 -1.44904060e-02 4.22117859e-01
-7.63238430e-01 -1.30595231e+00 -6.51917815e-01 7.19115198e-01
-4.26506668e-01 -4.96789925e-02 -6.13590479e-01 7.28305817e-01
6.54292226e-01 1.05187571e+00 -5.37493527e-01 -3.44886333e-01
1.79566011e-01 3.96995813e-01 1.61758766e-01 -2.82122701e-01
-6.50318205e-01 2.49242157e-01 4.14157987e-01 -3.09030771e-01
-3.78785223e-01 -8.93200040e-01 -1.09511471e+00 -1.27605619e-02
-7.76261687e-01 6.39503181e-01 5.81870496e-01 1.07780230e+00
5.49032800e-02 3.69038880e-01 9.56537068e-01 -2.70099819e-01
-6.60623968e-01 -1.15294313e+00 -6.09129190e-01 3.86966079e-01
1.86239153e-01 -1.06957388e+00 -7.03774691e-01 9.68975201e-02] | [7.817060947418213, 4.8235955238342285] |
e7c0e292-82d5-4a5f-9309-d76a8f330b6f | multi-modal-entity-alignment-in-hyperbolic | 2106.03619 | null | https://arxiv.org/abs/2106.03619v1 | https://arxiv.org/pdf/2106.03619v1.pdf | Multi-modal Entity Alignment in Hyperbolic Space | Many AI-related tasks involve the interactions of data in multiple modalities. It has been a new trend to merge multi-modal information into knowledge graph(KG), resulting in multi-modal knowledge graphs (MMKG). However, MMKGs usually suffer from low coverage and incompleteness. To mitigate this problem, a viable approach is to integrate complementary knowledge from other MMKGs. To this end, although existing entity alignment approaches could be adopted, they operate in the Euclidean space, and the resulting Euclidean entity representations can lead to large distortion of KG's hierarchical structure. Besides, the visual information has yet not been well exploited. In response to these issues, in this work, we propose a novel multi-modal entity alignment approach, Hyperbolic multi-modal entity alignment(HMEA), which extends the Euclidean representation to hyperboloid manifold. We first adopt the Hyperbolic Graph Convolutional Networks (HGCNs) to learn structural representations of entities. Regarding the visual information, we generate image embeddings using the densenet model, which are also projected into the hyperbolic space using HGCNs. Finally, we combine the structure and visual representations in the hyperbolic space and use the aggregated embeddings to predict potential alignment results. Extensive experiments and ablation studies demonstrate the effectiveness of our proposed model and its components. | ['Li Liu', 'Xiang Zhao', 'Weixin Zeng', 'Jiuyang Tang', 'Hao Guo'] | 2021-06-07 | null | null | null | null | ['multi-modal-entity-alignment'] | ['knowledge-base'] | [-2.53468335e-01 4.43657845e-01 -2.34022979e-02 -9.66374725e-02
-3.83660406e-01 -4.07031536e-01 4.97786343e-01 2.81308472e-01
-1.44615084e-01 3.90712053e-01 5.10640323e-01 1.64374575e-01
-4.13309038e-01 -1.09049547e+00 -6.31059408e-01 -6.28261626e-01
2.59453446e-01 2.06913605e-01 1.35073319e-01 -2.01650977e-01
6.43980205e-02 3.52406263e-01 -1.24819422e+00 1.46590620e-02
1.10977721e+00 7.82042086e-01 2.88036698e-03 1.47436932e-01
-2.16747418e-01 7.57223248e-01 -3.39539856e-01 -6.86355889e-01
5.04478551e-02 -1.93524882e-01 -8.96820784e-01 -1.35891885e-02
2.84816355e-01 -1.91151515e-01 -6.86942458e-01 1.14962447e+00
5.21650732e-01 1.11289091e-01 6.24067843e-01 -1.56235600e+00
-1.27323198e+00 7.04710841e-01 -6.79592192e-01 -5.63045777e-02
3.77988666e-01 -1.91161484e-01 1.19971526e+00 -1.13844395e+00
6.84778512e-01 1.30388105e+00 6.06442988e-01 4.78002019e-02
-1.05838144e+00 -4.19953614e-01 1.54984400e-01 6.30733311e-01
-1.83370268e+00 -4.61132750e-02 1.02580261e+00 -3.37575674e-01
6.86141789e-01 1.75761636e-02 9.99629200e-01 9.30470467e-01
-1.01691568e-02 8.64107490e-01 7.22711980e-01 -3.09516877e-01
-1.34704351e-01 -3.09845470e-02 -3.26430276e-02 8.26255143e-01
4.07251298e-01 -2.80370146e-01 -4.70647454e-01 2.12447718e-02
6.27815306e-01 1.72450960e-01 -3.88808995e-01 -8.58016610e-01
-1.50953662e+00 7.29270279e-01 1.07773471e+00 4.41451252e-01
-4.19063091e-01 5.06088277e-03 2.36982584e-01 3.71058146e-03
1.47031695e-01 5.73211133e-01 1.37833938e-01 3.11171353e-01
-5.84817410e-01 1.28079504e-01 4.95545775e-01 1.07825983e+00
9.56621289e-01 -4.39886451e-02 -7.50848502e-02 8.13928783e-01
4.65173841e-01 3.18564266e-01 3.67822498e-01 -5.29364288e-01
5.57564437e-01 1.30205655e+00 -2.78713822e-01 -1.78097367e+00
-7.31667399e-01 -4.37159717e-01 -1.08103514e+00 -1.96229905e-01
1.30996987e-01 2.28363603e-01 -7.99616635e-01 1.68928576e+00
4.78025556e-01 2.94713646e-01 3.66294771e-01 1.07253516e+00
1.17459166e+00 5.85427403e-01 6.58296943e-02 1.38529241e-01
1.22845745e+00 -1.01096511e+00 -7.07131743e-01 5.60854375e-02
7.17308939e-01 -4.57051456e-01 8.59672189e-01 -9.55138505e-02
-8.81050229e-01 -4.42719191e-01 -1.23178065e+00 -1.68466926e-01
-8.05164695e-01 1.11920878e-01 3.42325926e-01 2.08299220e-01
-9.79875326e-01 3.52445275e-01 -6.13879085e-01 -4.35236514e-01
3.05683792e-01 2.42966115e-01 -5.58397830e-01 -3.95730734e-01
-1.44864142e+00 9.88476276e-01 9.42487299e-01 4.27318603e-01
-3.78502548e-01 -5.16509950e-01 -1.16314244e+00 9.62183699e-02
4.72858161e-01 -8.05239499e-01 5.80932677e-01 -5.48752844e-01
-1.02303433e+00 4.38000172e-01 3.20290536e-01 -3.07741538e-02
2.68872947e-01 -6.87222853e-02 -5.57459354e-01 1.84431240e-01
6.01285622e-02 7.93707013e-01 5.88370919e-01 -1.50150561e+00
-4.51945126e-01 -5.00458002e-01 4.59716678e-01 7.93644130e-01
-8.08959007e-01 -4.95039821e-01 -6.66934133e-01 -6.06842875e-01
4.31392133e-01 -9.30595517e-01 -3.47188972e-02 -3.13509554e-01
-6.26588941e-01 -2.35369995e-01 7.56928921e-01 -7.38733709e-01
1.50907743e+00 -2.09641576e+00 8.41648757e-01 3.68276983e-01
5.24065375e-01 2.12115142e-02 -1.58931360e-01 5.07578611e-01
9.94334444e-02 1.16403207e-01 -1.02176197e-01 -1.35615826e-01
1.24900050e-01 2.72741646e-01 1.00341082e-01 3.34297210e-01
1.12799868e-01 1.26355076e+00 -9.47986126e-01 -7.54064918e-01
2.16419041e-01 5.51407158e-01 -4.60047722e-01 5.51980585e-02
1.11690097e-01 1.64387435e-01 -4.77509409e-01 9.01528299e-01
7.28751361e-01 -4.21362847e-01 3.21467370e-01 -9.61170316e-01
4.98217940e-02 -3.14043313e-01 -1.18540072e+00 1.92884338e+00
-1.18898846e-01 2.86298245e-01 -3.24068636e-01 -1.21321678e+00
8.12667727e-01 1.64313719e-01 6.70640409e-01 -6.10787272e-01
9.45927948e-02 1.63846686e-01 3.45173068e-02 -4.07251656e-01
7.52413273e-01 5.45722507e-02 -1.69291094e-01 7.40457475e-02
2.71618396e-01 2.65604496e-01 -1.73244327e-02 4.23595607e-01
9.00046647e-01 1.33157760e-01 3.88135880e-01 1.07816488e-01
5.68537712e-01 8.88693333e-02 4.84357893e-01 2.16275513e-01
-4.62419391e-02 5.79862952e-01 4.28405762e-01 -3.82787526e-01
-9.63400185e-01 -1.15616560e+00 5.34103215e-02 7.31738210e-01
7.77309656e-01 -7.63459682e-01 -5.35865486e-01 -7.12395370e-01
6.26352802e-02 2.93531388e-01 -7.38418758e-01 -5.65529227e-01
-5.46104968e-01 -6.70533299e-01 6.39369667e-01 6.36892974e-01
7.43789852e-01 -9.68741417e-01 -1.75052971e-01 2.06095904e-01
-3.34928662e-01 -1.13993573e+00 -2.71342933e-01 -3.19514900e-01
-4.23024535e-01 -1.29503953e+00 -7.63584733e-01 -8.58849406e-01
7.67327130e-01 4.48843271e-01 7.94157505e-01 -4.11045030e-02
-2.56853282e-01 7.56222308e-01 -6.15504384e-01 -1.15326166e-01
-5.78099638e-02 2.29297772e-01 9.21437889e-02 2.55811185e-01
3.56207520e-01 -5.87068379e-01 -7.45656013e-01 2.19874784e-01
-9.81740177e-01 3.09565365e-01 8.73515606e-01 8.46249044e-01
6.58911407e-01 8.23673606e-02 6.94488764e-01 -6.05105579e-01
6.09576523e-01 -7.14800119e-01 -2.67816782e-01 6.96622968e-01
-5.61208248e-01 -5.51116876e-02 6.77158117e-01 -3.69230241e-01
-8.44995320e-01 -7.81741962e-02 2.12402001e-01 -9.78584468e-01
1.52720809e-01 1.16346753e+00 -4.05055076e-01 -1.85224891e-01
5.09267986e-01 1.87979594e-01 -1.17307819e-01 -1.91375464e-01
8.15955937e-01 4.47159290e-01 5.28558671e-01 -4.63208109e-01
9.27757680e-01 2.78345853e-01 4.62080725e-02 -7.20465481e-01
-8.16781044e-01 -3.51673901e-01 -8.17065060e-01 -3.10198307e-01
1.10283172e+00 -9.04542208e-01 -4.45059568e-01 3.13678741e-01
-1.04513180e+00 3.30177426e-01 -3.23311798e-02 5.83631575e-01
-3.36969286e-01 6.13446534e-01 -2.84259796e-01 -4.16369766e-01
-2.63833195e-01 -9.73084807e-01 9.76294219e-01 4.31990385e-01
5.49597777e-02 -9.61289465e-01 -3.79664972e-02 3.90322506e-01
1.46463782e-01 4.37165111e-01 1.14208055e+00 -6.34748876e-01
-8.36319864e-01 -1.80246398e-01 -4.79050428e-01 -1.11302536e-03
1.57936111e-01 -7.23102689e-02 -5.26283503e-01 -3.62022191e-01
-4.78003383e-01 -3.22764963e-01 6.41134024e-01 1.57086313e-01
1.02000773e+00 -2.33228654e-01 -4.40784246e-01 6.12943888e-01
1.47273326e+00 1.23670502e-02 5.61197042e-01 4.94422108e-01
1.41277695e+00 5.95502913e-01 6.39496803e-01 3.93230081e-01
9.48053062e-01 6.84570372e-01 6.30846083e-01 -1.33481458e-01
9.73803224e-04 -4.25582528e-01 1.63712248e-01 1.35855663e+00
-1.46555841e-01 -2.32657790e-01 -1.12882900e+00 6.85283899e-01
-2.05422926e+00 -7.92429328e-01 -1.76935792e-02 1.80144811e+00
3.93922836e-01 -2.78790265e-01 4.98432256e-02 -7.47592151e-02
9.28902328e-01 1.60154834e-01 -5.44181585e-01 7.19737038e-02
-3.34820658e-01 -3.66886407e-01 3.15812916e-01 9.03657079e-02
-1.08702004e+00 8.72109711e-01 4.98227262e+00 6.16903424e-01
-8.02374780e-01 -7.41807465e-03 4.87028733e-02 1.90775692e-01
-6.02841318e-01 8.57372805e-02 -5.53036988e-01 2.58180618e-01
4.28693354e-01 -5.01320064e-01 3.93231541e-01 6.94867611e-01
-4.19537127e-01 2.54599839e-01 -9.42257702e-01 1.26861119e+00
4.19733077e-01 -1.28753901e+00 4.00839865e-01 1.53530374e-01
6.92824662e-01 -2.63126045e-01 -9.57785621e-02 5.95639765e-01
1.29385188e-01 -9.29429889e-01 4.79216874e-01 6.90168202e-01
6.10126495e-01 -9.51667547e-01 7.50132024e-01 1.99479803e-01
-1.73851717e+00 -1.19774930e-01 -6.48768842e-01 5.57943225e-01
1.31511897e-01 1.89677000e-01 -8.06571066e-01 1.35254121e+00
7.20510483e-01 9.58339989e-01 -8.47353041e-01 1.04265940e+00
-4.74543609e-02 -9.82795432e-02 -1.86330765e-01 2.63235778e-01
2.38928840e-01 -3.86680633e-01 5.56190968e-01 8.01729977e-01
5.92428982e-01 2.29591966e-01 3.88708860e-01 8.99375796e-01
-2.47225910e-01 4.04247731e-01 -9.65213597e-01 -2.49575645e-01
6.23140931e-01 1.46745813e+00 -5.10251522e-01 -2.07157284e-01
-8.38814497e-01 9.77358341e-01 6.98178649e-01 3.94515634e-01
-9.43809867e-01 -3.44443172e-01 3.79620671e-01 -1.84154212e-01
9.37894434e-02 -1.45129934e-01 8.88936222e-02 -1.38014913e+00
1.72860444e-01 -6.58672929e-01 7.58449852e-01 -8.34314644e-01
-1.33624685e+00 4.65798974e-01 1.76907197e-01 -1.40264714e+00
1.07380003e-01 -4.10019368e-01 -3.11883450e-01 5.92408180e-01
-1.37371910e+00 -1.63461924e+00 -6.81604385e-01 8.50840807e-01
7.20350668e-02 -1.59972414e-01 6.60751939e-01 4.15545940e-01
-6.53808713e-01 7.30460882e-01 -8.43463466e-03 2.73785740e-01
5.32887101e-01 -1.32618856e+00 -5.53841293e-02 6.61620080e-01
2.29607940e-01 5.28809249e-01 1.75154805e-01 -6.75225258e-01
-1.65842247e+00 -1.28182316e+00 4.68534499e-01 -2.45663121e-01
8.14101696e-01 -3.45471054e-02 -1.20717525e+00 7.88219213e-01
1.84286505e-01 9.38424841e-02 8.68472517e-01 2.24326029e-01
-4.35798079e-01 -9.27155837e-03 -8.15565169e-01 8.40294361e-01
1.20823693e+00 -5.70682347e-01 -8.18274200e-01 6.30753264e-02
8.24042559e-01 -4.47739661e-01 -1.44976747e+00 7.64937222e-01
4.61309642e-01 -6.35710776e-01 1.04285204e+00 -5.61782360e-01
5.24223864e-01 -5.91203630e-01 -3.55513394e-01 -1.60367692e+00
-5.39134204e-01 6.12005405e-02 -4.03821796e-01 1.35740685e+00
2.17951208e-01 -4.30255741e-01 5.95829606e-01 4.24722821e-01
-3.06158572e-01 -9.03283954e-01 -9.32960987e-01 -6.17713273e-01
-4.44462104e-03 1.01532163e-02 6.96318567e-01 1.37732875e+00
3.01592737e-01 5.11666059e-01 -4.70993310e-01 5.64404964e-01
4.97446179e-01 4.33722287e-01 7.20247924e-01 -1.29302907e+00
1.03145421e-01 -3.08560282e-01 -8.94136846e-01 -7.62800276e-01
1.55802339e-01 -1.26779783e+00 -2.42854998e-01 -2.00067115e+00
2.48203292e-01 -3.26732457e-01 -5.87558329e-01 5.18885672e-01
-2.29885072e-01 1.15960747e-01 3.01219404e-01 3.46065670e-01
-8.56069565e-01 1.03929269e+00 1.31790149e+00 -3.54245603e-01
-1.68953612e-01 -7.88870692e-01 -6.76075101e-01 5.76931775e-01
6.32590234e-01 -4.51869033e-02 -5.70141673e-01 -5.13487637e-01
4.22033012e-01 -2.03178730e-02 3.85589719e-01 -1.02399170e+00
5.94661176e-01 -1.65415760e-02 4.51896966e-01 -7.47267663e-01
3.67348582e-01 -1.00625861e+00 3.99819911e-01 -2.77282633e-02
2.06655879e-02 1.90370560e-01 5.21686636e-02 8.72596562e-01
-6.30745530e-01 1.13900356e-01 4.48510915e-01 3.72118205e-02
-9.37388241e-01 5.18385708e-01 1.12248100e-01 -1.37329757e-01
1.33913255e+00 -4.37568218e-01 -6.22858346e-01 -1.55109957e-01
-8.74659479e-01 5.97553611e-01 4.78338122e-01 6.39889896e-01
8.69310081e-01 -2.03735113e+00 -4.28709745e-01 -5.69683500e-02
5.75886667e-01 2.25276411e-01 5.52507460e-01 1.10656857e+00
-3.60626996e-01 2.65131682e-01 -3.36865276e-01 -5.85869670e-01
-1.04579031e+00 8.20326149e-01 2.05652595e-01 -1.92512423e-01
-7.68211663e-01 4.41372722e-01 3.36891860e-01 -6.41267180e-01
3.88713591e-02 1.58498734e-01 -6.78707659e-01 4.96589571e-01
1.17016785e-01 2.92986721e-01 -1.10701345e-01 -1.01411939e+00
-4.14777368e-01 6.99082971e-01 -1.03736900e-01 1.56794950e-01
1.21657038e+00 -2.33405560e-01 -1.90006524e-01 3.35297108e-01
1.20145774e+00 -1.34642065e-01 -6.83345735e-01 -5.10440588e-01
5.87002560e-03 -3.60047102e-01 -1.07308462e-01 -2.53644824e-01
-1.19273937e+00 7.07551658e-01 3.74578863e-01 2.79999197e-01
1.09757638e+00 6.72093853e-02 6.44707143e-01 4.24901038e-01
2.67595649e-01 -1.03941000e+00 3.04256856e-01 2.35413954e-01
9.70720232e-01 -1.12702394e+00 1.13287345e-01 -5.78710973e-01
-7.66013503e-01 1.18183434e+00 1.07005155e+00 6.68934584e-02
6.18829727e-01 -4.34358567e-01 -1.02663562e-01 -6.57780528e-01
-3.21758360e-01 -3.70765805e-01 5.76458454e-01 4.40266013e-01
3.03985626e-02 4.70668897e-02 -1.84778139e-01 6.25250161e-01
-1.27648339e-01 -3.34533155e-01 3.98613870e-01 8.34289253e-01
-2.27807716e-01 -8.61216843e-01 -3.23894501e-01 4.04906482e-01
-3.23626883e-02 3.84455337e-03 -5.78402638e-01 9.39181209e-01
1.81836978e-01 7.29377627e-01 -1.66989565e-01 -7.43885159e-01
6.56750858e-01 7.37395696e-03 3.07611167e-01 -4.02977705e-01
-1.30996227e-01 -2.27817390e-02 -8.70603323e-02 -4.35724556e-01
-6.68708920e-01 -3.11385512e-01 -1.20146775e+00 -3.59883189e-01
-4.67514575e-01 4.66568023e-02 2.10748449e-01 8.60336363e-01
4.80316937e-01 6.40946329e-01 4.37537819e-01 -7.26899981e-01
-1.88208520e-01 -7.95087397e-01 -7.24147856e-01 5.88177502e-01
-1.37761354e-01 -1.09001172e+00 -1.18720345e-01 -2.95071036e-01] | [8.687518119812012, 7.731289386749268] |
25a6f550-eae7-47f1-9ded-ccedf60cbe9c | complementary-pseudo-multimodal-feature-for | 2303.13194 | null | https://arxiv.org/abs/2303.13194v1 | https://arxiv.org/pdf/2303.13194v1.pdf | Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detection | Point cloud (PCD) anomaly detection steadily emerges as a promising research area. This study aims to improve PCD anomaly detection performance by combining handcrafted PCD descriptions with powerful pre-trained 2D neural networks. To this end, this study proposes Complementary Pseudo Multimodal Feature (CPMF) that incorporates local geometrical information in 3D modality using handcrafted PCD descriptors and global semantic information in the generated pseudo 2D modality using pre-trained 2D neural networks. For global semantics extraction, CPMF projects the origin PCD into a pseudo 2D modality containing multi-view images. These images are delivered to pre-trained 2D neural networks for informative 2D modality feature extraction. The 3D and 2D modality features are aggregated to obtain the CPMF for PCD anomaly detection. Extensive experiments demonstrate the complementary capacity between 2D and 3D modality features and the effectiveness of CPMF, with 95.15% image-level AU-ROC and 92.93% pixel-level PRO on the MVTec3D benchmark. Code is available on https://github.com/caoyunkang/CPMF. | ['Weiming Shen', 'Xiaohao Xu', 'Yunkang Cao'] | 2023-03-23 | null | null | null | null | ['3d-anomaly-detection-and-segmentation', 'depth-anomaly-detection-and-segmentation'] | ['methodology', 'methodology'] | [-8.19336921e-02 -1.93229243e-01 4.58343811e-02 -1.49862692e-01
-9.14686680e-01 -4.09003764e-01 9.02625024e-01 3.04301471e-01
-1.61634728e-01 2.38244548e-01 1.42458647e-01 9.71901566e-02
9.77319255e-02 -8.37511897e-01 -7.10409343e-01 -7.63464272e-01
-5.21000549e-02 3.02812755e-01 3.53671163e-01 -2.13312060e-01
4.14223224e-01 1.14720297e+00 -1.73648989e+00 2.16712445e-01
7.02565670e-01 1.58979118e+00 -1.85798109e-01 5.94844520e-01
-2.16835067e-01 4.22905535e-01 -2.16096178e-01 -2.50592172e-01
4.65588868e-01 -1.41958809e-02 -4.27758157e-01 1.01205416e-01
6.37597561e-01 -4.43006545e-01 -4.92467642e-01 1.07434332e+00
4.71311659e-01 -8.14393815e-03 1.13161480e+00 -1.55291831e+00
-5.47021925e-01 -2.31440559e-01 -8.50176692e-01 4.91137326e-01
3.59360099e-01 2.47468621e-01 9.60199952e-01 -1.37219775e+00
5.33640862e-01 1.11002588e+00 6.16183519e-01 2.23663762e-01
-8.27478349e-01 -3.31527084e-01 -2.70985737e-02 3.70910108e-01
-1.33471227e+00 9.61615443e-02 1.35839617e+00 -5.36870837e-01
1.07730448e+00 1.13711558e-01 6.21100187e-01 1.05036330e+00
3.81534427e-01 8.95442367e-01 6.73600674e-01 -2.44878396e-01
-9.73561630e-02 -3.03727865e-01 1.11057293e-02 7.27093816e-01
3.77660602e-01 1.34905815e-01 -6.20859265e-01 -2.54058212e-01
8.05533469e-01 3.07628155e-01 -6.66672513e-02 -6.55377209e-01
-1.02343869e+00 8.02570105e-01 4.64686960e-01 1.72168314e-01
-5.73554099e-01 -1.84117053e-02 5.55602431e-01 1.53812543e-01
6.73931301e-01 3.19042921e-01 -3.10028225e-01 -1.23252302e-01
-4.03585345e-01 2.20366418e-01 1.77395731e-01 8.53769183e-01
6.65714502e-01 2.58256674e-01 -2.16487706e-01 1.01286495e+00
3.75662208e-01 8.44285727e-01 3.71594280e-01 -1.02139306e+00
4.03909206e-01 9.75671291e-01 -2.17055038e-01 -1.37111306e+00
-3.66473049e-01 -3.03805441e-01 -8.44737649e-01 2.49685824e-01
1.75114378e-01 3.96300405e-01 -7.89380670e-01 1.20553339e+00
5.35502076e-01 -1.24075346e-01 -6.74005002e-02 9.03032601e-01
8.82903457e-01 5.32119811e-01 -2.36842588e-01 1.95973352e-01
1.03989768e+00 -7.76232958e-01 -3.42654228e-01 1.35452852e-01
7.77975082e-01 -6.01902962e-01 8.65510464e-01 3.48331481e-01
-1.00359607e+00 -4.69932616e-01 -9.19821382e-01 9.81892347e-02
-4.17896479e-01 1.36115953e-01 1.36806473e-01 1.03857018e-01
-7.26299942e-01 3.29144984e-01 -8.91916573e-01 -3.52939218e-01
8.84458005e-01 2.55843133e-01 -6.86619937e-01 -2.62322366e-01
-8.54879856e-01 6.77237451e-01 5.69957316e-01 -2.91155670e-02
-8.10584545e-01 -6.40684009e-01 -1.08128345e+00 -3.02154481e-01
1.24714047e-01 -5.29581487e-01 9.79981184e-01 -4.84118998e-01
-1.09180784e+00 1.00916862e+00 1.31028995e-01 -1.18576117e-01
2.22191557e-01 -3.63419622e-01 -5.15184164e-01 6.15201056e-01
2.66784906e-01 5.91603696e-01 1.10249031e+00 -1.41771257e+00
-9.96721864e-01 -7.76087701e-01 -3.91849041e-01 3.54326636e-01
-2.31866747e-01 -3.09602708e-01 -4.57112193e-01 -8.32716346e-01
5.90354621e-01 -6.77026153e-01 1.82532087e-01 1.55155107e-01
-4.83568937e-01 -4.52309757e-01 1.34858680e+00 -6.34084225e-01
7.14002848e-01 -2.11757898e+00 -9.46914777e-02 4.75345969e-01
4.02677953e-01 1.89765632e-01 -3.38714302e-01 2.71983296e-01
-1.70093805e-01 -3.53063643e-01 -4.07354891e-01 -1.69351384e-01
-1.28168538e-01 1.68266207e-01 -1.29173115e-01 8.40536535e-01
7.20066130e-01 8.68586719e-01 -8.04201782e-01 -4.52034533e-01
5.97828805e-01 2.26556331e-01 -5.12038708e-01 2.19633639e-01
-5.33168353e-02 6.96601927e-01 -7.86249936e-01 1.25255680e+00
9.81783152e-01 1.32319435e-01 -8.15705299e-01 -3.06313723e-01
-1.15732076e-02 -2.20713466e-01 -9.20848846e-01 1.71844757e+00
-1.69896379e-01 4.38603014e-01 -3.60645175e-01 -1.23392701e+00
1.20606899e+00 1.29806413e-03 9.15219724e-01 -9.05004144e-01
2.31496051e-01 5.32148898e-01 -5.27559876e-01 -6.70236468e-01
3.93218309e-01 2.28885889e-01 -1.22885011e-01 8.38073418e-02
3.50221276e-01 -4.01820749e-01 -2.01558888e-01 1.29360154e-01
1.09409535e+00 2.04926684e-01 2.82068729e-01 1.61206853e-02
1.03537858e+00 9.04807374e-02 3.12495559e-01 5.91719031e-01
-3.43424648e-01 9.21407282e-01 4.04269248e-01 -5.77947259e-01
-1.21179605e+00 -1.47740197e+00 -2.01691210e-01 4.99322087e-01
3.18810672e-01 -1.32122606e-01 -3.00997347e-01 -1.07945716e+00
1.50513396e-01 7.19096601e-01 -4.03177619e-01 -4.30599689e-01
-6.06281757e-01 -3.78679574e-01 6.86332762e-01 6.91035330e-01
7.02563643e-01 -6.27793908e-01 -4.69877332e-01 -1.44113421e-01
-1.34014308e-01 -1.10624349e+00 -1.89289957e-01 -1.65349722e-01
-1.06899536e+00 -9.36440468e-01 -7.59509385e-01 -6.39444590e-01
6.19655669e-01 2.74313658e-01 9.37169790e-01 -1.22122280e-01
-3.57903421e-01 9.36009169e-01 -4.40168411e-01 -3.57045859e-01
-1.80643663e-01 -2.10990295e-01 2.29861349e-01 6.59231246e-02
4.84655142e-01 -8.41318250e-01 -6.02754116e-01 1.79830715e-01
-8.75288188e-01 -2.74020463e-01 6.57899678e-01 8.99585068e-01
9.91670847e-01 -1.08057700e-01 2.60047108e-01 -1.31037384e-01
2.59757012e-01 -5.44316649e-01 -5.03343225e-01 -3.06409448e-01
-2.87385672e-01 -5.22176810e-02 4.94720191e-01 -9.35230628e-02
-9.84738529e-01 8.58168602e-02 -4.24959868e-01 -1.09828663e+00
-8.09752941e-01 1.51722044e-01 -3.12367171e-01 -5.77079579e-02
6.36265934e-01 4.05399412e-01 1.01878248e-01 -5.22942722e-01
4.41084057e-01 6.30316079e-01 8.47578287e-01 -6.59759521e-01
1.03101599e+00 7.15969443e-01 2.25112572e-01 -9.65781987e-01
-7.40639508e-01 -7.16685355e-01 -9.57557559e-01 -3.71574312e-01
9.08889830e-01 -9.38601434e-01 -2.09062740e-01 7.71047473e-01
-1.12620962e+00 3.51069123e-01 -5.41232407e-01 4.69282568e-01
-7.39474177e-01 7.03760386e-01 -3.83591115e-01 -5.78980565e-01
-4.00133312e-01 -1.00661254e+00 1.58145642e+00 3.43899280e-02
-1.22118769e-02 -8.05957675e-01 2.53163338e-01 2.19082400e-01
7.58908093e-02 6.55144632e-01 8.64613175e-01 -9.39445615e-01
-4.49267238e-01 -5.50750911e-01 -4.46705878e-01 6.08349025e-01
6.20664060e-02 -6.62860125e-02 -1.00061309e+00 -1.15445048e-01
4.03297246e-02 -1.29285723e-01 8.25815499e-01 3.94365281e-01
1.29334629e+00 -1.44271225e-01 -3.03443909e-01 6.76580369e-01
1.48287868e+00 7.48164058e-02 3.27355713e-01 5.45449674e-01
1.13549936e+00 3.09526414e-01 7.05081463e-01 5.84198654e-01
3.71774137e-01 6.31010830e-01 9.14918482e-01 2.47490466e-01
-4.88311611e-02 -2.66466856e-01 2.71859854e-01 7.78583765e-01
-2.94472635e-01 -4.74676564e-02 -1.35513270e+00 6.58736050e-01
-1.73919916e+00 -7.47794509e-01 -3.62929940e-01 1.95781422e+00
1.28221318e-01 1.19086273e-01 1.26823768e-01 1.35624215e-01
6.52778387e-01 7.22123757e-02 -5.04206777e-01 -2.58252561e-01
-4.35129374e-01 4.45024185e-02 2.68488824e-01 -6.56459201e-03
-1.49088180e+00 6.18874967e-01 3.83700728e+00 1.13791335e+00
-1.02246177e+00 1.14320824e-02 2.96715021e-01 1.51587473e-02
-1.76948577e-01 -4.00120199e-01 -5.33260286e-01 3.73492688e-01
6.55358136e-01 1.43255219e-01 -3.25786978e-01 9.34393048e-01
-3.03951427e-02 -1.71607174e-02 -8.89391601e-01 1.28628123e+00
2.79530615e-01 -1.09292114e+00 5.31981409e-01 1.82723358e-01
6.74833298e-01 3.74581516e-01 1.60659388e-01 1.90278977e-01
-2.86196947e-01 -7.55460083e-01 5.92455328e-01 7.00169384e-01
7.60267377e-01 -1.04374945e+00 9.40850198e-01 1.70612380e-01
-1.24505055e+00 -1.44316450e-01 -2.76754022e-01 3.26242536e-01
1.54377352e-02 5.30612350e-01 -5.82157314e-01 1.10937357e+00
1.00373924e+00 1.22814858e+00 -8.69993091e-01 1.06793249e+00
-8.43681842e-02 3.42317343e-01 -6.81694806e-01 4.33598965e-01
4.85819757e-01 -1.77992031e-01 1.25017738e+00 1.03750718e+00
6.18277669e-01 -5.68944542e-03 -1.07722752e-01 8.08277667e-01
1.12233736e-01 1.31089717e-01 -1.22135353e+00 7.53333569e-02
1.44330889e-01 1.28781760e+00 -4.64042157e-01 -3.28295380e-02
-5.04977822e-01 1.04201293e+00 7.28277266e-02 1.89979210e-01
-7.20034719e-01 -2.13546440e-01 6.59913182e-01 -7.40803108e-02
3.80707055e-01 -1.95625305e-01 -3.17237616e-01 -1.15988326e+00
1.25320882e-01 -5.26198447e-01 6.61481977e-01 -8.02484751e-01
-1.85533273e+00 4.65105027e-01 1.45432130e-01 -1.79675829e+00
-1.37239054e-01 -8.37559760e-01 -8.12507212e-01 6.25429511e-01
-1.26003313e+00 -1.41898668e+00 -6.37817264e-01 8.32342684e-01
5.70642948e-01 -5.36228418e-01 5.93570113e-01 1.10934876e-01
-6.15626991e-01 5.43171883e-01 1.86064377e-01 2.02649191e-01
5.64475954e-01 -1.22023463e+00 3.12858492e-01 8.83398950e-01
9.79237556e-02 -1.17483102e-01 3.39476049e-01 -6.82016671e-01
-1.18933344e+00 -1.38455725e+00 3.90408009e-01 -7.36829579e-01
3.47850680e-01 9.20308009e-02 -1.05099344e+00 2.63409525e-01
-1.06097251e-01 3.84444624e-01 3.84466976e-01 -5.31625092e-01
-3.11650574e-01 -1.48982625e-03 -1.26047218e+00 4.96441066e-01
1.06242013e+00 -5.16279995e-01 -6.77143335e-01 1.24501221e-01
5.38813353e-01 -6.18035614e-01 -1.09726191e+00 8.93698931e-01
1.78573251e-01 -8.62265050e-01 1.23625517e+00 -4.57198530e-01
6.01719856e-01 -3.97713482e-01 -6.98179066e-01 -1.05252147e+00
1.42667014e-02 1.40536174e-01 -4.78550524e-01 9.89772856e-01
4.69388664e-02 -6.66674912e-01 7.00817943e-01 7.87375346e-02
-5.99157512e-01 -1.07416022e+00 -1.15437305e+00 -9.00027752e-01
2.08852425e-01 -8.66381586e-01 4.61327344e-01 7.97921240e-01
-3.91996264e-01 6.83216155e-02 1.20279521e-01 5.73534191e-01
8.24455857e-01 4.36393470e-02 7.09379196e-01 -1.38129437e+00
3.69616061e-01 -5.14030159e-01 -1.07772171e+00 -7.44975865e-01
1.77703038e-01 -1.13617003e+00 -3.20029914e-01 -1.22181690e+00
-5.56277931e-02 -1.01123437e-01 -4.21749264e-01 2.33034208e-01
7.55930468e-02 3.33917648e-01 1.26168216e-02 3.72308731e-01
-4.87259388e-01 1.10445189e+00 1.18182826e+00 -1.66887790e-01
-1.36611521e-01 -2.60167918e-03 -2.26460978e-01 9.74160910e-01
1.04876518e+00 -3.65141451e-01 -1.36568487e-01 -1.39001682e-01
-2.18213722e-01 -2.44002327e-01 7.72969663e-01 -1.33332658e+00
5.41011840e-02 5.76303303e-02 6.97769642e-01 -1.32708454e+00
5.62266052e-01 -9.01375711e-01 -3.22734535e-01 1.83011055e-01
6.23306334e-02 2.09831402e-01 4.00657624e-01 8.38333011e-01
-5.05655408e-01 3.28999534e-02 7.47740328e-01 -7.60994330e-02
-1.05813301e+00 6.43498063e-01 -2.26674795e-01 1.29368469e-01
1.16153479e+00 -6.11279666e-01 -1.76837772e-01 -3.52884918e-01
-6.41281307e-01 1.89677805e-01 4.86318171e-01 6.12807512e-01
1.09648478e+00 -1.75877452e+00 -5.44775069e-01 5.81111729e-01
5.85896611e-01 3.13418657e-01 5.94063818e-01 1.00863624e+00
-7.19513834e-01 5.08482873e-01 -6.02731586e-01 -1.36118567e+00
-1.00015664e+00 3.49580616e-01 4.06610161e-01 9.88593549e-02
-9.24505413e-01 7.45904446e-01 6.44231513e-02 -5.84538817e-01
6.94067925e-02 -2.13189781e-01 -2.22732335e-01 -2.40223538e-02
1.15682587e-01 4.63272393e-01 1.60545379e-01 -9.93753314e-01
-5.13465703e-01 8.02627921e-01 -1.15464563e-02 -3.95325273e-02
1.38848877e+00 -1.10513516e-01 -5.19742854e-02 2.55873322e-01
1.50548196e+00 -1.69380024e-01 -1.14276481e+00 -4.66420650e-01
6.51172027e-02 -6.40998721e-01 8.86836722e-02 -3.80799413e-01
-1.20512044e+00 9.87714350e-01 8.75621617e-01 -1.84279948e-01
1.35285926e+00 2.94653237e-01 9.42077577e-01 4.73417521e-01
9.07034203e-02 -9.61873889e-01 4.69973683e-01 5.69143951e-01
1.08810484e+00 -1.31091309e+00 -1.26393899e-01 -1.94647729e-01
-7.59010136e-01 1.31680417e+00 9.43162382e-01 -3.64559472e-01
7.29984224e-01 -2.53058374e-01 -8.44487175e-02 -5.85044146e-01
-3.10287416e-01 -6.18870296e-02 6.60550773e-01 8.52859855e-01
-2.15268001e-01 -1.69429109e-01 2.40599543e-01 5.65877914e-01
-2.60008872e-02 -4.49106187e-01 3.92215639e-01 9.47043419e-01
-3.43211621e-01 -7.75472343e-01 -4.73860562e-01 6.40339434e-01
-3.11572075e-01 2.45483801e-01 -2.96615422e-01 8.98368180e-01
3.62647295e-01 4.16381240e-01 3.64199966e-01 -4.46042478e-01
5.62073946e-01 1.32890955e-01 3.02082747e-01 -3.09544563e-01
2.08921209e-02 5.58702461e-02 -3.91024314e-02 -8.58571351e-01
-3.55196893e-01 -7.90525794e-01 -1.15259171e+00 3.60907950e-02
-1.51289687e-01 -2.01214418e-01 4.74384725e-01 9.00594771e-01
4.84553128e-01 1.58899635e-01 6.97699010e-01 -9.80582476e-01
-2.45044217e-01 -7.46431172e-01 -4.70272362e-01 5.29237092e-01
5.69325209e-01 -9.95781720e-01 -3.18523079e-01 -1.75901040e-01] | [7.656673908233643, 1.9371974468231201] |
23190c6b-7e9f-466c-b9a5-7082f862c7c4 | evidence-of-task-independent-person-specific | 2007.13517 | null | https://arxiv.org/abs/2007.13517v4 | https://arxiv.org/pdf/2007.13517v4.pdf | Evidence of Task-Independent Person-Specific Signatures in EEG using Subspace Techniques | Electroencephalography (EEG) signals are promising as alternatives to other biometrics owing to their protection against spoofing. Previous studies have focused on capturing individual variability by analyzing task/condition-specific EEG. This work attempts to model biometric signatures independent of task/condition by normalizing the associated variance. Toward this goal, the paper extends ideas from subspace-based text-independent speaker recognition and proposes novel modifications for modeling multi-channel EEG data. The proposed techniques assume that biometric information is present in the entire EEG signal and accumulate statistics across time in a high dimensional space. These high dimensional statistics are then projected to a lower dimensional space where the biometric information is preserved. The lower dimensional embeddings obtained using the proposed approach are shown to be task-independent. The best subspace system identifies individuals with accuracies of 86.4% and 35.9% on datasets with 30 and 920 subjects, respectively, using just nine EEG channels. The paper also provides insights into the subspace model's scalability to unseen tasks and individuals during training and the number of channels needed for subspace modeling. | ['Hema A. Murthy', 'Shrikanth Narayanan', 'Mriganka Sur', 'Mari Ganesh Kumar'] | 2020-07-27 | null | null | null | null | ['text-independent-speaker-recognition'] | ['speech'] | [ 2.65855521e-01 -4.16864723e-01 2.21703917e-01 -4.60713804e-01
-5.44470191e-01 -5.31144679e-01 4.02054757e-01 -1.22099958e-01
-5.94028831e-01 7.05528736e-01 4.43762124e-01 1.79537624e-01
-2.88290232e-01 -5.45348860e-02 -3.22951883e-01 -9.30677354e-01
-2.34868884e-01 4.73245904e-02 -5.36568344e-01 2.03597203e-01
4.17150587e-01 5.56377649e-01 -1.36242950e+00 1.03874706e-01
7.44514942e-01 7.25889564e-01 -4.76390243e-01 7.16297925e-01
3.55821192e-01 -2.17014998e-01 -1.03758395e+00 -3.60473067e-01
1.88470393e-01 -2.44211614e-01 -1.64592847e-01 -9.35747940e-03
3.80512446e-01 -1.14538923e-01 -4.30115461e-01 1.04273880e+00
9.39695835e-01 -4.64336127e-02 9.34272230e-01 -1.47175515e+00
-7.50966549e-01 4.59636450e-01 -5.43459296e-01 3.36426854e-01
4.67971206e-01 -3.53707641e-01 2.96391279e-01 -8.67101908e-01
9.10073295e-02 8.95656288e-01 8.02418470e-01 8.36897969e-01
-1.54265320e+00 -1.02864718e+00 -2.44932041e-01 5.14398038e-01
-1.92196643e+00 -8.19130838e-01 1.04026544e+00 -5.45511842e-01
1.02105308e+00 4.90756094e-01 6.25400126e-01 1.62154090e+00
4.64182943e-01 3.51371765e-01 1.38275015e+00 -2.40561962e-01
3.76126885e-01 5.50195158e-01 7.79558420e-01 2.50461437e-02
5.37495792e-01 -4.85155843e-02 -1.37280178e+00 -5.13083577e-01
2.87158817e-01 -7.54072666e-02 -3.63599986e-01 -3.98366779e-01
-1.30151582e+00 3.18285137e-01 -2.84941673e-01 4.72225428e-01
-6.37667060e-01 -2.78809488e-01 3.75315815e-01 2.13078782e-01
4.99444723e-01 2.26343319e-01 -3.36095810e-01 -4.44143265e-01
-1.27716291e+00 6.68782219e-02 9.63555455e-01 9.23697472e-01
1.93935513e-01 2.34556764e-01 4.54821019e-03 7.47060180e-01
4.83204378e-03 8.40486050e-01 8.49388778e-01 -4.08483326e-01
4.32435989e-01 2.73109108e-01 5.03011718e-02 -9.96784151e-01
-6.05033219e-01 -4.67901647e-01 -1.00087583e+00 -3.49016339e-01
2.87150949e-01 -3.45164597e-01 -6.21792674e-01 1.78684199e+00
-1.95461676e-01 4.68256742e-01 2.57158607e-01 5.67825198e-01
4.16199237e-01 2.53736287e-01 -5.83790950e-02 -2.78277844e-01
1.33936024e+00 -2.44102120e-01 -9.71936047e-01 2.80643124e-02
1.25990391e-01 -3.86310071e-01 6.74585521e-01 6.68717802e-01
-7.43522406e-01 -4.49496090e-01 -1.24941766e+00 3.82221937e-01
-5.28398037e-01 2.83937484e-01 3.53181630e-01 1.72310293e+00
-1.18521512e+00 2.93537021e-01 -8.11923027e-01 -5.00630498e-01
3.76693428e-01 8.32834482e-01 -5.99709451e-01 3.35664034e-01
-1.10525465e+00 8.39016676e-01 1.41038671e-01 1.92845855e-02
-5.84432483e-01 -4.27964687e-01 -5.71689069e-01 1.59412161e-01
-4.70119983e-01 -2.95833915e-01 4.59531099e-01 -4.40632939e-01
-1.46051192e+00 3.27129602e-01 -6.91998422e-01 -4.51470315e-01
1.51672378e-01 -2.03979984e-01 -9.27450001e-01 7.07324073e-02
-2.10125238e-01 1.23329662e-01 1.16615307e+00 -8.73072922e-01
2.27300823e-02 -1.11620975e+00 -8.64402711e-01 1.44310579e-01
-1.39960301e+00 1.85016736e-01 1.53477304e-02 -6.02329552e-01
2.69484907e-01 -9.93666708e-01 4.22866881e-01 -6.76335514e-01
-4.69627202e-01 1.23166695e-01 7.16784298e-01 -1.07759905e+00
1.26373458e+00 -2.25274992e+00 3.07928264e-01 5.08785844e-01
1.80488795e-01 1.76931843e-02 -1.32841498e-01 3.67363125e-01
-3.54076654e-01 -1.36318192e-01 -1.67513341e-01 -4.97473001e-01
9.54973772e-02 -2.22003043e-01 -1.48248896e-01 1.05141699e+00
-2.19426990e-01 6.87228024e-01 -3.32785696e-01 -7.22016245e-02
1.68660998e-01 9.48068023e-01 -2.24441886e-01 -2.12748647e-01
1.14809263e+00 5.77561080e-01 -1.91564977e-01 6.05754316e-01
8.44621539e-01 4.02296126e-01 -5.91441989e-03 -2.55177319e-01
1.74405932e-01 -3.06728967e-02 -1.27651846e+00 1.60262287e+00
-1.39106080e-01 9.44155097e-01 2.84116827e-02 -9.93153274e-01
1.00631464e+00 7.32201636e-01 7.07347333e-01 -2.93707818e-01
2.37777039e-01 3.27034444e-02 6.94822147e-02 -3.01483363e-01
3.76887619e-01 2.65802518e-02 -1.32354215e-01 4.80265796e-01
3.43208134e-01 3.83079350e-01 -3.15312028e-01 -1.54087082e-01
1.04074156e+00 -3.08647901e-01 1.62248626e-01 -5.82297206e-01
7.11966991e-01 -6.61728799e-01 3.26095939e-01 6.67241991e-01
-5.14021039e-01 1.98923588e-01 8.94819014e-03 -8.15682337e-02
-8.04875970e-01 -1.00797975e+00 -7.83932984e-01 6.41166806e-01
8.28668941e-03 -5.03959417e-01 -1.19835949e+00 -2.54408181e-01
1.25976473e-01 8.58111441e-01 -8.95013690e-01 -4.22175556e-01
-1.39065683e-01 -1.13167918e+00 1.01635063e+00 5.55175304e-01
4.66823488e-01 -3.54105145e-01 -4.91419017e-01 1.15903400e-01
-8.62338245e-02 -9.60060894e-01 -3.20151746e-01 9.49867666e-02
-1.02357209e+00 -7.72699952e-01 -1.02856135e+00 -2.74844319e-01
6.69104576e-01 2.26695418e-01 2.39791110e-01 -6.81037664e-01
-2.30077177e-01 9.99361873e-01 -1.79801993e-02 -7.73524523e-01
9.98975709e-02 -9.91877764e-02 1.08431256e+00 6.03460252e-01
1.18631101e+00 -8.05806756e-01 -3.21268201e-01 2.77620703e-01
-4.71952677e-01 -3.96390140e-01 2.79231995e-01 9.06718254e-01
4.29202132e-02 1.23844430e-01 5.56033969e-01 -2.56225705e-01
1.04372537e+00 -3.03157091e-01 -4.39378060e-02 2.81207263e-01
-7.47383595e-01 -7.47809038e-02 3.86693835e-01 -7.84426868e-01
-8.83388758e-01 1.16189808e-01 3.41359347e-01 -2.45104983e-01
-4.57158387e-01 3.22541669e-02 -2.97699273e-01 -3.57246786e-01
6.92776620e-01 8.07973325e-01 -2.09877953e-01 -5.77868283e-01
4.97676292e-03 1.35368955e+00 5.28491497e-01 -2.87170857e-01
6.89207137e-01 4.02043760e-01 -2.34309688e-01 -1.41455102e+00
1.61346078e-01 -7.37473130e-01 -1.12379479e+00 -8.04924890e-02
6.25719666e-01 -8.63072991e-01 -7.29849458e-01 7.36941755e-01
-1.08974242e+00 4.99405533e-01 7.53452778e-02 9.20883238e-01
-4.14347380e-01 5.13029516e-01 -3.10718477e-01 -1.30172646e+00
-5.23123384e-01 -8.74219716e-01 9.92388368e-01 1.36510491e-01
-5.42467475e-01 -7.43997812e-01 7.12287501e-02 2.17571378e-01
4.70086604e-01 -1.98753238e-01 3.94521534e-01 -1.09208965e+00
2.55280226e-01 -7.94210017e-01 2.25142971e-01 4.15302187e-01
3.90754074e-01 -5.62407255e-01 -1.49372876e+00 -6.42900050e-01
5.99842310e-01 3.03905338e-01 5.32119811e-01 4.37003970e-01
9.84640062e-01 -1.79103449e-01 -3.69103670e-01 7.17186153e-01
9.26555574e-01 4.30489361e-01 4.50795740e-01 7.09292442e-02
6.60672367e-01 6.53958797e-01 -2.54925281e-01 5.27508020e-01
1.77295595e-01 6.51710749e-01 -3.42149287e-01 3.78043711e-01
2.50438988e-01 7.02723712e-02 6.95495903e-01 9.94410574e-01
-1.74526811e-01 -4.29994613e-02 -9.12346065e-01 4.60956037e-01
-1.34728718e+00 -1.03741765e+00 8.13458208e-03 2.44117069e+00
3.23134422e-01 -4.05189633e-01 2.90003151e-01 6.61754072e-01
8.18378687e-01 -2.54842490e-01 -7.27011681e-01 -1.73132285e-01
-3.92487139e-01 2.24145547e-01 7.08624065e-01 1.65191755e-01
-1.12229609e+00 3.81485760e-01 6.46388292e+00 2.35097349e-01
-1.05590439e+00 2.31960759e-01 1.05441533e-01 -3.45155150e-01
1.99980348e-01 -4.66110438e-01 -7.76853323e-01 5.98816633e-01
1.54366028e+00 -5.64081013e-01 5.34672141e-01 3.15613657e-01
2.03432664e-01 3.64900976e-02 -1.21225202e+00 1.78343141e+00
8.39320004e-01 -6.19117498e-01 -1.26164332e-01 4.53430384e-01
4.29641604e-01 -2.86500633e-01 4.28558975e-01 -1.54199466e-01
-5.33517122e-01 -1.01466811e+00 4.74986434e-01 7.55599916e-01
8.33232522e-01 -7.12781668e-01 7.38816202e-01 2.91688621e-01
-9.21385705e-01 -2.82756954e-01 -4.54202294e-01 6.59732074e-02
-8.14440176e-02 1.94072813e-01 -7.55209684e-01 4.58907843e-01
6.51129425e-01 7.45497286e-01 -8.89045775e-01 1.01682961e+00
2.47652695e-01 6.77583635e-01 -3.62469107e-01 -1.34473085e-01
-4.27132964e-01 -1.32504642e-01 9.07281399e-01 1.40943205e+00
7.05880046e-01 5.11815697e-02 -5.10175049e-01 6.68282330e-01
2.42645010e-01 2.37029135e-01 -7.99902678e-01 -1.10287465e-01
6.76130593e-01 9.47510600e-01 -5.33879459e-01 -1.98522121e-01
-2.14805424e-01 1.47121000e+00 -1.96716160e-01 6.56300604e-01
-5.20486832e-01 -6.35986924e-01 6.92875087e-01 -3.40359867e-01
-1.72673494e-01 -4.53415126e-01 -8.00539970e-01 -1.51611781e+00
1.75260201e-01 -7.17054367e-01 6.64504841e-02 -3.05222273e-01
-1.25869083e+00 6.11523867e-01 5.47883660e-02 -1.20577633e+00
-2.13910207e-01 -6.49566591e-01 -2.84208238e-01 1.32554042e+00
-9.19537067e-01 -1.04194343e+00 -1.55019790e-01 9.65648592e-01
2.10609213e-01 -7.75121331e-01 1.44026792e+00 2.47813612e-01
-7.93402791e-01 1.11836076e+00 5.39537072e-01 6.73576072e-02
8.63411486e-01 -1.05497265e+00 3.16789210e-01 8.71668041e-01
4.34890509e-01 1.20137179e+00 6.55991793e-01 -6.10455453e-01
-1.72474933e+00 -6.04305029e-01 9.28894460e-01 -8.11210454e-01
3.89007717e-01 -8.40542376e-01 -9.04898763e-01 3.36808711e-01
1.74833894e-01 -4.67546046e-01 1.44352436e+00 2.50276953e-01
-4.48317915e-01 -1.99558526e-01 -1.29008985e+00 2.88103044e-01
7.26589620e-01 -1.02815425e+00 -7.82946408e-01 7.51258209e-02
-2.22550958e-01 8.12107548e-02 -1.02401173e+00 -1.02521442e-01
1.04144537e+00 -7.07402945e-01 8.36647570e-01 -6.27774537e-01
-6.16735220e-01 -9.05392766e-02 -4.39908862e-01 -1.37512553e+00
-4.13860232e-01 -6.36995554e-01 -2.37347871e-01 1.24685121e+00
1.95156291e-01 -9.20578420e-01 8.57544243e-01 1.15881073e+00
3.94849479e-01 -4.72356789e-02 -1.23106122e+00 -1.08552289e+00
-5.72741441e-02 -5.40528715e-01 7.30411828e-01 8.63644242e-01
5.25520146e-01 1.42715171e-01 -6.00351453e-01 4.65116054e-01
1.06304181e+00 -4.73714292e-01 6.72461212e-01 -1.51712954e+00
-6.90210098e-03 -9.60042477e-02 -1.03398299e+00 -5.35681129e-01
4.15986240e-01 -8.30577195e-01 -3.27410609e-01 -7.68714070e-01
5.20940125e-01 1.81616932e-01 -7.49818265e-01 2.54993051e-01
2.26403307e-02 3.43508959e-01 8.69306326e-02 2.23896801e-01
-2.97114290e-02 5.09130657e-01 2.37872869e-01 -2.31693208e-01
-4.31816727e-01 -4.56804037e-02 -7.30092227e-01 4.51333761e-01
9.35544193e-01 -2.64777541e-01 -4.52650189e-01 -1.75922588e-01
-5.88398755e-01 -1.00555800e-01 3.97538751e-01 -1.36729825e+00
4.92811561e-01 4.18281227e-01 1.14382017e+00 -3.18865478e-01
7.98876941e-01 -9.05583024e-01 3.21136534e-01 2.88444877e-01
-3.37809652e-01 1.69485480e-01 4.29662794e-01 7.18367875e-01
-3.80994962e-03 1.12431921e-01 5.08039355e-01 5.20935416e-01
-3.06189030e-01 2.42572390e-02 -5.18840075e-01 -5.57080925e-01
1.02519846e+00 -7.48720407e-01 6.29640277e-03 -5.17787695e-01
-9.49551463e-01 -3.34048569e-01 3.31814587e-01 5.00169218e-01
8.56468379e-01 -1.15854275e+00 -6.46840990e-01 8.17841709e-01
1.59188598e-01 -1.24232614e+00 4.51444536e-01 9.11984086e-01
3.98237020e-01 8.54511082e-01 -6.30193830e-01 -5.70409954e-01
-1.70397174e+00 3.61145139e-01 1.45767137e-01 6.33200169e-01
-4.76701856e-01 7.96703815e-01 -1.64119467e-01 -4.85145040e-02
4.11503643e-01 1.95216373e-01 -4.31501955e-01 3.04842740e-01
8.50266397e-01 7.32396305e-01 2.65905112e-01 -1.19147778e+00
-7.19194591e-01 6.80389822e-01 8.14995766e-02 -5.55418849e-01
1.44194591e+00 -2.71404624e-01 -9.70038846e-02 6.53349996e-01
1.32931733e+00 8.50539953e-02 -7.42596745e-01 -5.87705038e-02
1.66493401e-01 -4.41960752e-01 2.03208029e-01 -7.38378763e-01
-6.33425832e-01 1.11561799e+00 1.21431506e+00 -7.53506273e-03
1.14072418e+00 -4.67195988e-01 2.79086560e-01 3.85799795e-01
7.12848485e-01 -1.03663313e+00 -5.47432363e-01 7.15811849e-02
7.28864014e-01 -6.41984582e-01 4.08349140e-03 -3.97056118e-02
-5.14803708e-01 1.18468070e+00 6.35371730e-02 5.26463017e-02
7.92233407e-01 1.33783236e-01 -1.56291381e-01 4.68313359e-02
-2.47292146e-01 4.29612994e-01 6.22121572e-01 1.18394899e+00
3.76685649e-01 3.23936284e-01 -3.59643340e-01 1.13356578e+00
-4.67553228e-01 -1.61887407e-01 5.55277944e-01 6.05680823e-01
5.15779816e-02 -1.12693930e+00 -8.03596735e-01 7.04304099e-01
-5.35795212e-01 -3.93721499e-02 -6.27220333e-01 3.29534799e-01
-1.78214282e-01 1.23863614e+00 -2.09858909e-01 -8.18013191e-01
3.40770990e-01 7.80446947e-01 5.44703007e-01 -2.66218096e-01
-3.57596010e-01 8.37972686e-02 -2.22471833e-01 -4.64924097e-01
-3.48758280e-01 -1.15990674e+00 -5.93050241e-01 -7.71500990e-02
-2.53642201e-01 3.34572703e-01 1.09979331e+00 5.75286329e-01
6.82297349e-01 2.77812272e-01 5.01810133e-01 -9.68563080e-01
-6.68575466e-01 -1.09713924e+00 -1.15422821e+00 3.14289510e-01
4.11792815e-01 -7.42747486e-01 -3.73544663e-01 1.32457823e-01] | [13.210680961608887, 3.2646782398223877] |
81ee57d5-4027-4577-b5e3-f6c96fb1dd17 | diverse-plausible-360-degree-image | 2203.14668 | null | https://arxiv.org/abs/2203.14668v1 | https://arxiv.org/pdf/2203.14668v1.pdf | Diverse Plausible 360-Degree Image Outpainting for Efficient 3DCG Background Creation | We address the problem of generating a 360-degree image from a single image with a narrow field of view by estimating its surroundings. Previous methods suffered from overfitting to the training resolution and deterministic generation. This paper proposes a completion method using a transformer for scene modeling and novel methods to improve the properties of a 360-degree image on the output image. Specifically, we use CompletionNets with a transformer to perform diverse completions and AdjustmentNet to match color, stitching, and resolution with an input image, enabling inference at any resolution. To improve the properties of a 360-degree image on an output image, we also propose WS-perceptual loss and circular inference. Thorough experiments show that our method outperforms state-of-the-art (SOTA) methods both qualitatively and quantitatively. For example, compared to SOTA methods, our method completes images 16 times larger in resolution and achieves 1.7 times lower Frechet inception distance (FID). Furthermore, we propose a pipeline that uses the completion results for lighting and background of 3DCG scenes. Our plausible background completion enables perceptually natural results in the application of inserting virtual objects with specular surfaces. | ['Yoshimitsu Aoki', 'Yuhi Matsuo', 'Naofumi Akimoto'] | 2022-03-28 | null | http://openaccess.thecvf.com//content/CVPR2022/html/Akimoto_Diverse_Plausible_360-Degree_Image_Outpainting_for_Efficient_3DCG_Background_Creation_CVPR_2022_paper.html | http://openaccess.thecvf.com//content/CVPR2022/papers/Akimoto_Diverse_Plausible_360-Degree_Image_Outpainting_for_Efficient_3DCG_Background_Creation_CVPR_2022_paper.pdf | cvpr-2022-1 | ['image-outpainting'] | ['computer-vision'] | [ 3.88927490e-01 1.13671519e-01 5.80155015e-01 -2.56335348e-01
-5.64392865e-01 -5.68997979e-01 5.33184707e-01 -6.34011328e-01
-4.55004089e-02 5.54576099e-01 -7.80447014e-03 -2.34059975e-01
3.50951254e-01 -8.94634724e-01 -1.04302859e+00 -5.01757443e-01
3.48478734e-01 1.08472683e-01 3.64398241e-01 -1.67796940e-01
1.26360923e-01 7.12331891e-01 -1.67863548e+00 4.33683634e-01
8.78469646e-01 1.12097466e+00 6.33562565e-01 9.84761536e-01
-1.14614449e-01 7.78714359e-01 -6.98603451e-01 -5.51386833e-01
5.87958336e-01 -8.19345340e-02 -3.58423918e-01 5.47763407e-01
1.29759753e+00 -7.91850388e-01 -2.12755039e-01 1.07399678e+00
4.02459770e-01 6.54848963e-02 3.67404997e-01 -1.01594996e+00
-7.02801168e-01 1.42151654e-01 -7.44952083e-01 -2.28538230e-01
4.72386539e-01 2.72166342e-01 6.03492975e-01 -1.05007851e+00
5.84133208e-01 1.45619917e+00 5.61714351e-01 3.98982704e-01
-1.38306773e+00 -6.52714908e-01 3.04858834e-01 -2.13569641e-01
-1.51691890e+00 -4.80358213e-01 7.95110106e-01 -3.21937799e-01
7.72657156e-01 2.95093805e-01 7.54926205e-01 8.87113750e-01
3.82751137e-01 3.84547442e-01 1.24331856e+00 -4.17833537e-01
1.39287651e-01 1.05398409e-01 -6.40292525e-01 8.84007812e-01
6.07787333e-02 2.66362607e-01 -3.82262349e-01 2.40898803e-01
1.51300049e+00 -1.11445069e-01 -3.51933181e-01 -2.96645164e-01
-1.19026625e+00 3.29876125e-01 4.37138617e-01 -3.85633767e-01
-2.71439012e-02 2.54400194e-01 -2.97456980e-01 -1.82927176e-01
6.36003077e-01 4.46511239e-01 -1.73139930e-01 4.40834552e-01
-9.60181773e-01 2.38375247e-01 3.31162751e-01 1.27256656e+00
9.05384839e-01 3.42255026e-01 -1.76324680e-01 6.32311702e-01
8.34127539e-04 8.28467309e-01 -2.58383811e-01 -1.61815584e+00
3.16709101e-01 1.90475687e-01 4.83964950e-01 -9.45180893e-01
-2.45614231e-01 -5.81198573e-01 -8.12599540e-01 7.50879347e-01
3.06606382e-01 -5.16490638e-02 -1.07101262e+00 1.45887804e+00
4.37901169e-01 2.72348672e-01 -1.34341210e-01 1.03718245e+00
7.01505721e-01 6.62924588e-01 -5.93009651e-01 -1.03416547e-01
1.23633802e+00 -1.06175065e+00 -6.04113460e-01 -1.93849474e-01
-2.60276526e-01 -1.05294096e+00 1.34591019e+00 9.38465118e-01
-1.42424309e+00 -1.03700519e+00 -1.03905272e+00 -4.40394610e-01
1.06537975e-01 2.47619301e-01 6.21917844e-01 5.48163712e-01
-1.39158940e+00 5.11126518e-01 -4.72383618e-01 8.48123208e-02
1.28967911e-01 -1.78805545e-01 -8.85415301e-02 -3.29500705e-01
-8.23478878e-01 6.70646071e-01 5.66238016e-02 -2.22134009e-01
-1.06021655e+00 -9.75455880e-01 -8.37627709e-01 -5.48720732e-02
2.80315310e-01 -1.05660689e+00 8.44585896e-01 -6.87382162e-01
-1.83672762e+00 8.05342019e-01 -1.00617535e-01 -2.51334578e-01
7.12577105e-01 -3.37728351e-01 -3.75089616e-01 1.63714632e-01
6.31625354e-02 1.02474153e+00 1.21918952e+00 -1.66158056e+00
-7.97094762e-01 -3.24751198e-01 2.70056129e-01 4.24287319e-01
6.73081055e-02 -3.84476990e-01 -7.74383664e-01 -6.02621198e-01
3.10983241e-01 -5.69953084e-01 -2.80079544e-01 2.97000229e-01
-6.49380267e-01 4.20076251e-01 7.17586339e-01 -5.63659668e-01
9.17478681e-01 -2.22321224e+00 -2.61424184e-01 -2.17677310e-01
2.96849221e-01 -1.17514066e-01 -1.84540212e-01 -8.76436308e-02
1.62598222e-01 -3.77184227e-02 5.25416620e-02 -8.16851377e-01
-2.22045854e-01 8.87110084e-02 -6.93779826e-01 3.88387740e-01
1.44237846e-01 5.57155669e-01 -7.78366387e-01 -4.17254925e-01
7.01193869e-01 8.17855537e-01 -7.71655381e-01 4.43861425e-01
-3.55136544e-01 6.25253320e-01 9.09106806e-02 5.28762817e-01
1.25624478e+00 -2.61706024e-01 -9.80823040e-02 -6.12908423e-01
-3.79554391e-01 1.99660715e-02 -1.32572734e+00 2.00050092e+00
-7.13681936e-01 6.46294355e-01 1.68993533e-01 -1.04494691e-01
1.09275091e+00 -2.54566967e-01 8.21224377e-02 -6.30737364e-01
-2.25109920e-01 -1.29768133e-01 -5.65475166e-01 -1.20229244e-01
8.17897737e-01 1.32902488e-01 2.07102865e-01 1.85551587e-02
-1.94403380e-01 -8.47970068e-01 2.30727819e-04 1.92222655e-01
7.41397262e-01 4.15145189e-01 -1.37856975e-01 -7.63748661e-02
3.10283452e-01 -2.80905306e-01 5.64437151e-01 7.00649083e-01
2.62488127e-01 1.38797534e+00 1.78663284e-01 -6.11462474e-01
-1.45505846e+00 -1.61696267e+00 -2.16485769e-01 6.22109592e-01
4.15179610e-01 -2.21543610e-01 -9.04511154e-01 -1.17744647e-01
-2.24474445e-01 9.42773998e-01 -4.53463167e-01 4.58473504e-01
-5.24928391e-01 -2.05357417e-01 3.81338298e-01 3.78992200e-01
9.16151285e-01 -4.57633942e-01 -7.57784963e-01 -1.46756833e-02
-4.01008934e-01 -1.61507177e+00 -6.57845736e-01 -1.47528917e-01
-6.67904258e-01 -7.98337936e-01 -6.91134036e-01 -4.50417727e-01
7.76362062e-01 6.94667041e-01 1.48912978e+00 -2.17154428e-01
-4.30035949e-01 1.71396479e-01 1.47473618e-01 -2.49299914e-01
-3.47734272e-01 -5.28143942e-01 3.90566252e-02 1.55935995e-02
-3.65808368e-01 -7.81703651e-01 -9.52315152e-01 4.01780486e-01
-9.73325849e-01 9.07487333e-01 4.36454803e-01 5.99951148e-01
7.58053958e-01 1.91313282e-01 -1.17940217e-01 -5.55142820e-01
1.42847851e-01 1.60023704e-01 -1.17125201e+00 1.05678648e-01
-4.90895450e-01 8.91849305e-03 7.82932222e-01 -4.58026409e-01
-1.59196579e+00 1.50593922e-01 1.76568657e-01 -8.88942719e-01
-1.93142697e-01 -4.80657846e-01 -2.91601628e-01 1.03013113e-01
9.15389240e-01 1.20499618e-01 -1.88354746e-01 -2.52934009e-01
6.36910856e-01 2.00249970e-01 9.10530448e-01 -5.16436696e-01
8.62448215e-01 1.06694555e+00 1.61985382e-01 -7.12729812e-01
-1.05474901e+00 -1.50906980e-01 -4.74966228e-01 -2.77381659e-01
9.63221133e-01 -1.25607991e+00 -6.32760465e-01 4.97224808e-01
-1.45032287e+00 -6.18257761e-01 -3.39210361e-01 1.90621004e-01
-6.26448870e-01 3.55064809e-01 -5.88928282e-01 -7.74134636e-01
-1.30430833e-01 -1.06740654e+00 1.38615453e+00 2.26196751e-01
3.64568323e-01 -7.14218855e-01 -3.59030247e-01 4.06308383e-01
4.95867670e-01 3.03271800e-01 5.19037426e-01 7.00936437e-01
-1.14151788e+00 4.57441986e-01 -5.43235898e-01 4.42282945e-01
5.05404100e-02 2.36324579e-01 -1.38537490e+00 -1.28815889e-01
-1.01508722e-02 2.23381463e-02 7.80924022e-01 8.08538139e-01
1.29755020e+00 -2.71824330e-01 -6.52035028e-02 1.25657785e+00
1.56666338e+00 -5.18654548e-02 1.01754975e+00 1.32557079e-01
7.89442658e-01 6.26086414e-01 6.30509794e-01 5.52418411e-01
3.27154994e-01 8.11047912e-01 6.75781906e-01 -6.30387187e-01
-7.94132292e-01 -4.73832130e-01 4.40512151e-01 1.67660743e-01
-4.68343161e-02 -2.69926578e-01 -4.05797571e-01 3.10808927e-01
-1.35825443e+00 -9.23590541e-01 -1.42921910e-01 2.30464339e+00
8.04150820e-01 6.84448332e-02 -2.11057827e-01 -3.14621300e-01
7.05027282e-01 2.27897614e-01 -6.51396453e-01 -2.05415368e-01
-5.11674702e-01 4.78036292e-02 6.96214437e-01 9.17329013e-01
-7.28132904e-01 1.06899774e+00 6.78536558e+00 8.82364929e-01
-1.16873479e+00 -4.25513424e-02 1.00807798e+00 -7.54312128e-02
-7.28868127e-01 -5.23523241e-02 -1.10011351e+00 2.42446929e-01
2.54872262e-01 2.51932561e-01 8.76245916e-01 6.77786827e-01
3.32737654e-01 -2.31763795e-01 -9.97031808e-01 1.12663019e+00
3.10167462e-01 -1.43660581e+00 3.47213477e-01 -4.31115441e-02
1.16575277e+00 -9.98110548e-02 4.96011317e-01 -1.58656865e-01
4.78483468e-01 -1.15058959e+00 9.31290507e-01 6.69947863e-01
1.45207429e+00 -6.27158284e-01 8.63327459e-02 3.52336437e-01
-1.06012166e+00 8.07489008e-02 -6.30284429e-01 6.19475208e-02
3.41630638e-01 1.00049460e+00 -9.53103006e-01 3.49039704e-01
8.84938002e-01 3.23481560e-01 -5.97585440e-01 6.27845943e-01
-4.02953386e-01 -7.18109086e-02 -2.84601450e-01 5.26375055e-01
-1.45588696e-01 -4.00507182e-01 4.97685313e-01 1.09046376e+00
5.78207135e-01 9.07457694e-02 1.45286113e-01 1.42757058e+00
2.38464251e-02 -3.74690473e-01 -6.93005145e-01 7.07937241e-01
5.43550849e-01 1.36652398e+00 -4.85117793e-01 -3.91370296e-01
-1.76716670e-01 1.24246430e+00 1.90862194e-01 7.42135525e-01
-1.01187336e+00 -1.71302184e-01 6.21089518e-01 5.70893466e-01
2.41055772e-01 -1.98342443e-01 -4.39938515e-01 -1.27894616e+00
1.04575597e-01 -4.82903719e-01 -1.79504260e-01 -1.61616385e+00
-9.86909568e-01 7.42986381e-01 1.60973035e-02 -1.34926343e+00
-4.24307697e-02 -5.90982795e-01 -3.91836524e-01 1.05037308e+00
-1.61487067e+00 -1.34149170e+00 -8.43008578e-01 7.09141672e-01
7.33403623e-01 7.65575543e-02 5.93973041e-01 6.86169565e-02
3.26281972e-02 2.29119301e-01 -1.14123560e-01 -1.38989791e-01
8.44902873e-01 -1.28552318e+00 7.38881528e-01 1.18087971e+00
-1.35957778e-01 4.74315226e-01 7.51113892e-01 -4.72338974e-01
-1.24479496e+00 -1.20796037e+00 1.88721836e-01 -5.25192857e-01
9.80559587e-02 -5.17220497e-01 -5.70229709e-01 5.43848634e-01
1.74953535e-01 2.93811381e-01 4.18335013e-03 -2.85090774e-01
-5.24872065e-01 -4.24129993e-01 -1.21656048e+00 8.82444859e-01
1.22205079e+00 -3.27678442e-01 3.17392647e-02 3.47239673e-02
1.10952115e+00 -9.15306926e-01 -6.26245141e-01 4.27753955e-01
6.44952834e-01 -1.64987612e+00 1.35192096e+00 1.65857971e-01
6.46620750e-01 -8.78942728e-01 -3.18945497e-01 -1.36926806e+00
-4.00213957e-01 -8.16271186e-01 4.12300862e-02 9.15562153e-01
1.65187046e-01 -4.18087095e-01 6.00474775e-01 4.52952832e-01
-3.09959948e-01 -3.43534470e-01 -5.78781247e-01 -5.51375031e-01
-1.24297664e-01 -4.30106461e-01 6.80606961e-01 8.45171571e-01
-6.27805293e-01 3.10700029e-01 -5.24420142e-01 5.22972703e-01
1.21036708e+00 1.87154099e-01 1.24182749e+00 -9.14891422e-01
-4.22644198e-01 -1.83305606e-01 -9.05778334e-02 -1.56293237e+00
-3.30128819e-01 -3.03433388e-01 1.34853553e-02 -1.54562569e+00
7.28067979e-02 -4.36030924e-01 2.75766373e-01 -1.68769568e-01
-1.55532390e-01 4.15511727e-01 2.37074554e-01 -2.75805052e-02
-4.23168123e-01 2.09633395e-01 1.78313220e+00 9.88396932e-04
-1.52475223e-01 -1.98988199e-01 -6.51014090e-01 8.63771617e-01
5.70764184e-01 5.56038097e-02 -6.25002384e-01 -8.63763690e-01
3.78272116e-01 2.30758622e-01 5.36433220e-01 -1.10279632e+00
4.44400012e-02 -2.35757142e-01 9.84461010e-01 -8.52739573e-01
7.45187342e-01 -4.65340734e-01 5.72268784e-01 3.87982070e-03
-1.68298870e-01 -7.12927133e-02 1.76775813e-01 4.31220204e-01
1.39379531e-01 2.63492167e-01 9.62636292e-01 -2.44130760e-01
-5.35867929e-01 2.80181348e-01 7.09504932e-02 -1.22883260e-01
6.49962366e-01 -4.53492820e-01 -6.37016475e-01 -5.02713025e-01
-6.28348947e-01 7.98146520e-03 1.03683269e+00 1.32276446e-01
1.02833819e+00 -1.29800379e+00 -8.56833220e-01 5.10215640e-01
-1.15391776e-01 5.90279341e-01 3.91569674e-01 3.95852119e-01
-9.21832919e-01 1.15210027e-01 -1.99890077e-01 -9.04739439e-01
-1.03474379e+00 5.60821056e-01 3.98928910e-01 -1.25769615e-01
-8.43931377e-01 8.51206839e-01 1.00078332e+00 -2.84033448e-01
2.85305381e-01 -5.46885192e-01 2.32734546e-01 -6.28606558e-01
7.62176692e-01 3.02784324e-01 -6.47425205e-02 -2.34689862e-01
1.31412730e-01 6.92415833e-01 1.23085104e-01 -4.60629225e-01
1.08037710e+00 -4.80936259e-01 1.05833232e-01 1.45449072e-01
9.06610906e-01 5.28348744e-01 -2.05270839e+00 -2.09322438e-01
-1.03780746e+00 -9.29189920e-01 1.90059006e-01 -8.57531726e-01
-1.07090640e+00 9.87711966e-01 5.59858263e-01 -5.43058589e-02
1.28159010e+00 -2.57158458e-01 5.86846471e-01 2.71579400e-02
4.06495571e-01 -9.84503865e-01 3.59004796e-01 4.25382406e-01
1.09077048e+00 -1.06630623e+00 1.14358865e-01 -7.35954762e-01
-5.86873889e-01 1.20112574e+00 8.45648885e-01 -1.95110291e-02
2.69940674e-01 6.12403452e-01 1.90245748e-01 -8.77046771e-03
-6.67806864e-01 -7.03081116e-02 2.50412881e-01 9.01729405e-01
1.46323293e-01 7.08899572e-02 5.38383245e-01 5.13889454e-03
-4.72730309e-01 -2.91697711e-01 8.00578773e-01 1.49241596e-01
-3.51622969e-01 -5.30803919e-01 -7.16884434e-01 -2.17569187e-01
-3.16074103e-01 -3.86290401e-01 2.51983609e-02 5.09811938e-01
2.02258602e-01 1.03228080e+00 3.68259490e-01 -2.31230721e-01
2.17251748e-01 -6.36268854e-01 7.99883604e-01 -5.58554471e-01
4.34076898e-02 3.87880862e-01 4.32006903e-02 -8.15422893e-01
-3.16235572e-01 -1.65837318e-01 -1.01267076e+00 -4.14485842e-01
-3.17923278e-01 -3.89143288e-01 7.52827048e-01 2.19322652e-01
4.44122285e-01 5.80222845e-01 8.49972069e-01 -1.20693791e+00
-1.48411945e-01 -6.61954343e-01 -5.89507818e-01 3.28069419e-01
4.46532220e-01 -4.36110675e-01 -4.85662848e-01 2.84397274e-01] | [9.388742446899414, -3.0922200679779053] |
c966d7e3-90f7-43a4-bdd9-f0fc3f54d49b | data-splits-and-metrics-for-method | 2204.05235 | null | https://arxiv.org/abs/2204.05235v2 | https://arxiv.org/pdf/2204.05235v2.pdf | Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets | In addition to generating data and annotations, devising sensible data splitting strategies and evaluation metrics is essential for the creation of a benchmark dataset. This practice ensures consensus on the usage of the data, homogeneous assessment, and uniform comparison of research methods on the dataset. This study focuses on CholecT50, which is a 50 video surgical dataset that formalizes surgical activities as triplets of <instrument, verb, target>. In this paper, we introduce the standard splits for the CholecT50 and CholecT45 datasets and show how they compare with existing use of the dataset. CholecT45 is the first public release of 45 videos of CholecT50 dataset. We also develop a metrics library, ivtmetrics, for model evaluation on surgical triplets. Furthermore, we conduct a benchmark study by reproducing baseline methods in the most predominantly used deep learning frameworks (PyTorch and TensorFlow) to evaluate them using the proposed data splits and metrics and release them publicly to support future research. The proposed data splits and evaluation metrics will enable global tracking of research progress on the dataset and facilitate optimal model selection for further deployment. | ['Nicolas Padoy', 'Chinedu Innocent Nwoye'] | 2022-04-11 | null | null | null | null | ['action-triplet-recognition'] | ['computer-vision'] | [ 8.23865924e-03 3.45175317e-03 -7.29469180e-01 -3.97450298e-01
-7.52073288e-01 -5.80577791e-01 5.83460093e-01 1.85738072e-01
-6.38400316e-01 4.63827014e-01 6.74090087e-01 -3.58024389e-01
-4.80507731e-01 -4.56497997e-01 -3.54733676e-01 -4.67393786e-01
-2.50891060e-01 3.99465501e-01 -1.25930784e-02 2.60213345e-01
2.40833536e-01 4.06555861e-01 -1.46729684e+00 6.87044561e-01
2.21174896e-01 1.19005048e+00 1.05064869e-01 6.02574289e-01
3.30257624e-01 1.05601346e+00 -5.81490755e-01 -4.21087772e-01
5.18689454e-01 -2.52873361e-01 -1.21234858e+00 -2.40173817e-01
6.78662777e-01 -4.51686889e-01 -2.89782375e-01 4.86346900e-01
7.82668650e-01 -3.13784659e-01 6.15731359e-01 -1.32600772e+00
-2.03173831e-01 7.46888578e-01 -1.47786632e-01 3.87858331e-01
2.16244027e-01 3.24423432e-01 6.64399683e-01 -4.66039807e-01
1.24443507e+00 7.81415880e-01 8.57329369e-01 6.61249399e-01
-8.18204165e-01 -7.72732973e-01 -3.20704281e-01 1.64618969e-01
-1.06011391e+00 -2.93779522e-01 3.77765626e-01 -8.54229629e-01
5.90922892e-01 5.28812706e-01 9.24213588e-01 1.72356558e+00
4.79976624e-01 8.59545171e-01 1.17080772e+00 -1.76578805e-01
2.12126568e-01 -1.22385040e-01 2.12667003e-01 8.62195551e-01
2.76161373e-01 1.67496070e-01 -4.85841393e-01 1.11423723e-01
6.54914975e-01 -9.32419002e-02 -3.30453604e-01 -6.84327066e-01
-1.82914948e+00 5.74431002e-01 4.07302350e-01 3.79120618e-01
-4.68131334e-01 2.00362563e-01 1.03587759e+00 1.47996604e-01
1.19017642e-02 5.38389266e-01 -3.21138889e-01 -5.50335050e-01
-1.02487516e+00 2.90701985e-01 7.26402700e-01 1.20119417e+00
8.24766383e-02 -3.99229884e-01 -6.80265188e-01 5.92381477e-01
1.83402896e-01 -2.39027008e-01 9.81743276e-01 -1.33584988e+00
2.01377869e-01 6.24190807e-01 -1.46834254e-01 -6.21948242e-01
-5.74027121e-01 -6.17241144e-01 -6.60527766e-01 2.09845215e-01
2.23668590e-01 -1.53364494e-01 -1.01853597e+00 1.46042347e+00
1.16042152e-01 8.03636611e-02 -1.18786814e-02 6.80422664e-01
1.53101265e+00 -1.93769395e-01 9.32337791e-02 -3.54161598e-02
1.26753259e+00 -1.05094540e+00 -7.40285099e-01 2.58477330e-01
1.42797756e+00 -8.48558903e-01 1.07015371e+00 6.87115490e-01
-9.09771025e-01 -4.50132996e-01 -1.00440419e+00 -1.68645874e-01
-3.86076897e-01 6.23502612e-01 7.60932744e-01 5.29617786e-01
-1.07396376e+00 4.79091525e-01 -1.08547723e+00 -4.39916253e-01
6.01906359e-01 4.04200703e-01 -7.11882055e-01 -4.53907773e-02
-8.01693678e-01 1.08303320e+00 3.91037792e-01 1.04023859e-01
-1.60942757e+00 -9.81447101e-01 -6.79161489e-01 -5.70349514e-01
7.92333111e-02 -8.35163593e-01 1.43681669e+00 -6.66455865e-01
-1.10748291e+00 1.50990117e+00 5.23190677e-01 -6.23430908e-01
9.47173595e-01 -1.29899919e-01 -1.38524979e-01 -7.21803829e-02
6.61405772e-02 7.88114846e-01 2.13836566e-01 -1.02545953e+00
-5.74840605e-01 -2.64907449e-01 3.02861333e-01 1.89861670e-01
-2.56232917e-01 1.42548550e-02 -7.44679987e-01 -6.18861496e-01
-4.82601196e-01 -1.21199143e+00 -2.12198243e-01 9.36752707e-02
-6.42193675e-01 7.99657255e-02 5.17080963e-01 -6.37029231e-01
1.49499345e+00 -2.20389056e+00 2.35508531e-01 -1.15072884e-01
4.94414091e-01 1.83781609e-01 -1.33035526e-01 5.09790123e-01
-3.61701578e-01 1.38697878e-01 7.45623112e-02 -5.32779455e-01
-3.20097566e-01 4.03955549e-01 3.14362645e-01 6.65326357e-01
-4.34800833e-01 5.09430826e-01 -7.81335056e-01 -7.46461570e-01
3.08253407e-01 3.29749763e-01 -8.30003440e-01 1.83619499e-01
2.96266884e-01 4.13187325e-01 -1.71886489e-01 8.48604202e-01
3.25342000e-01 1.72938183e-02 3.53048220e-02 -6.71976447e-01
-1.09772675e-01 -8.61554313e-03 -8.41663361e-01 2.34677792e+00
-5.48122585e-01 6.07251406e-01 1.84561796e-02 -7.51711369e-01
5.43493867e-01 2.80729443e-01 1.06837380e+00 -3.53442818e-01
6.11484110e-01 1.67530283e-01 1.79951236e-01 -7.88979650e-01
3.90776306e-01 3.04459751e-01 -1.22026093e-01 1.13076791e-01
4.79400158e-01 -3.11673284e-02 5.67351103e-01 2.32195228e-01
1.43655896e+00 2.24375233e-01 4.12634969e-01 -4.90636379e-01
2.02655181e-01 2.70617515e-01 4.32065576e-01 6.64929211e-01
-5.96882999e-01 7.94776261e-01 7.29818404e-01 -6.84772074e-01
-8.27131867e-01 -8.62657905e-01 -4.70639706e-01 6.28087580e-01
-4.65718023e-02 -7.63631403e-01 -9.03252840e-01 -1.04570091e+00
3.25213671e-02 4.16283101e-01 -1.40832460e+00 -1.89601302e-01
-3.00778061e-01 -8.39747965e-01 5.30085862e-01 5.51664710e-01
1.60401866e-01 -1.08855319e+00 -1.01208913e+00 -1.61946833e-01
-1.53666019e-01 -1.11767030e+00 -2.70556092e-01 2.71287233e-01
-8.17630291e-01 -1.59585071e+00 -4.95894879e-01 -6.77511930e-01
4.43179816e-01 -2.22564545e-02 1.20934153e+00 2.18360648e-02
-5.29311478e-01 5.95699608e-01 -6.24597967e-01 -4.35102940e-01
-5.80049574e-01 3.77188057e-01 -2.59922951e-01 -3.82562965e-01
1.94652647e-01 -6.02879301e-02 -9.03957188e-01 4.14859354e-01
-1.20234525e+00 5.28673649e-01 7.58714676e-01 5.79722822e-01
5.94917417e-01 -5.29817700e-01 3.74797694e-02 -8.53603125e-01
7.42524385e-01 -7.56942272e-01 -2.16085106e-01 1.47862613e-01
-6.33322895e-01 -2.11045876e-01 1.10205621e-01 -3.08896393e-01
-5.64388692e-01 -1.32603839e-01 -4.14281711e-02 -6.04875803e-01
-1.39406726e-01 7.81661510e-01 2.76987433e-01 -4.34281044e-02
8.84777248e-01 -2.10858524e-01 3.11154693e-01 -4.56761360e-01
1.02310486e-01 6.19216979e-01 5.84185600e-01 -4.43250507e-01
2.41692942e-02 4.75102872e-01 -1.01767041e-01 -4.48739558e-01
-6.27192378e-01 -5.72721362e-01 -6.36216581e-01 -4.05271739e-01
8.61660004e-01 -9.66774523e-01 -5.22314012e-01 4.43836093e-01
-7.67337620e-01 -4.18548197e-01 -2.67524004e-01 7.92820215e-01
-7.36289740e-01 3.52686122e-02 -5.43666780e-01 -1.08973138e-01
-4.83112514e-01 -1.83980155e+00 1.21440709e+00 -2.58086383e-01
-5.20898819e-01 -1.03167951e+00 4.18341190e-01 6.80554986e-01
4.01400805e-01 7.84958780e-01 5.28054953e-01 -6.54780447e-01
-2.30313942e-01 -4.77757365e-01 -7.21024945e-02 6.12400055e-01
2.04890922e-01 3.16450745e-01 -6.60059571e-01 -4.19289201e-01
-3.07794213e-01 -4.35449004e-01 6.96476698e-01 4.94103014e-01
1.65534806e+00 8.06019828e-02 -5.29410005e-01 9.01800811e-01
1.37954223e+00 2.11398602e-01 6.53458655e-01 7.27402091e-01
5.91934979e-01 4.64776814e-01 6.99785709e-01 3.66859972e-01
4.31865156e-01 6.60209835e-01 8.93762887e-01 -1.34107679e-01
-5.41877329e-01 1.68063417e-01 6.73604682e-02 8.08791101e-01
-3.98109049e-01 -3.05196904e-02 -1.26326787e+00 6.77254677e-01
-1.49967992e+00 -6.97541773e-01 -9.91035774e-02 2.10630083e+00
9.22294736e-01 -8.20165873e-02 2.29436923e-02 8.94875899e-02
1.29926786e-01 2.74560079e-02 -8.30271095e-02 -2.26893112e-01
2.68231809e-01 1.03434488e-01 6.10366285e-01 -7.76454480e-03
-1.27467465e+00 5.48354626e-01 6.95967007e+00 7.34464765e-01
-1.28118539e+00 2.74628609e-01 4.25678790e-01 -5.20039737e-01
1.77398205e-01 -2.66082615e-01 -6.55007064e-01 5.18434405e-01
1.10504520e+00 -1.79694831e-01 1.89008676e-02 8.20866525e-01
4.03273135e-01 -7.98278973e-02 -1.40556669e+00 9.81271446e-01
1.35686874e-01 -1.60194850e+00 -9.61439535e-02 2.03725889e-01
5.21014631e-01 4.66732323e-01 1.56894065e-02 3.56332123e-01
3.46062958e-01 -1.02133381e+00 7.24054933e-01 5.13246894e-01
8.40163827e-01 -2.68160731e-01 1.15393984e+00 -2.41601229e-01
-6.80718720e-01 -1.60546690e-01 8.69876891e-02 3.23311090e-01
-2.17413798e-01 1.90976694e-01 -1.17166758e+00 9.06630993e-01
9.93677974e-01 1.13020599e+00 -7.93340683e-01 1.47491455e+00
2.06015214e-01 5.44955969e-01 -3.76487374e-02 3.72599185e-01
2.36356452e-01 2.89047778e-01 3.17333370e-01 1.41246188e+00
3.17948669e-01 -6.16108000e-01 1.29001558e-01 2.06685364e-01
-2.17457145e-01 3.07093889e-01 -6.05294466e-01 2.69718170e-02
2.77662814e-01 1.45866513e+00 -6.25018418e-01 -2.47327268e-01
-4.76417929e-01 3.28900814e-01 1.00634776e-01 -3.94980758e-02
-1.01256323e+00 1.24673769e-01 7.73630500e-01 3.24175149e-01
-2.91471273e-01 1.06267463e-02 -2.29055867e-01 -9.92868543e-01
-1.48138151e-01 -1.18007708e+00 7.23562002e-01 -7.33866632e-01
-8.73638928e-01 8.27681720e-01 4.52062458e-01 -1.86416435e+00
3.89207713e-02 -7.92024672e-01 -2.54701495e-01 3.01818162e-01
-1.15785801e+00 -1.36469841e+00 -9.79838669e-01 5.98209202e-01
4.47227925e-01 -1.55352101e-01 9.59707260e-01 4.33298886e-01
-8.48507464e-01 5.21295071e-01 -1.28580719e-01 3.94893587e-01
9.29311037e-01 -1.19295800e+00 -1.24458194e-01 4.12656784e-01
-2.21425474e-01 6.21387005e-01 7.08390713e-01 -5.31561375e-01
-1.27996337e+00 -1.02819848e+00 7.63469711e-02 -7.55434752e-01
8.38522017e-01 -1.73402578e-01 -3.39212894e-01 9.56308365e-01
5.62834799e-01 6.36566505e-02 1.08324182e+00 -5.93115240e-02
2.51653325e-02 -2.08052382e-01 -1.05847263e+00 3.85016948e-01
1.19612670e+00 1.00110192e-02 -5.49982846e-01 3.78006816e-01
3.82544160e-01 -8.56117606e-01 -1.43559432e+00 7.60770679e-01
8.31762373e-01 -1.18671572e+00 7.24825859e-01 -6.82919502e-01
8.00719321e-01 3.10930647e-02 -2.04362020e-01 -1.22235656e+00
4.70448211e-02 -3.61459404e-01 1.22957863e-01 8.08165073e-01
4.15416449e-01 -1.48235202e-01 8.52367103e-01 2.76858330e-01
-6.99905217e-01 -1.20822966e+00 -9.55590665e-01 -6.17610157e-01
1.94120273e-01 -5.73191166e-01 3.59180093e-01 1.17503071e+00
-2.37556458e-01 -3.84331435e-01 -2.86012113e-01 -3.62646759e-01
4.22192216e-01 -1.71926484e-01 1.07905304e+00 -1.04360807e+00
4.45803776e-02 -6.22388661e-01 -8.41995180e-01 -1.18375540e-01
-2.84538537e-01 -1.03245294e+00 -2.85840392e-01 -1.89026272e+00
4.09653366e-01 -4.44682360e-01 -4.61251616e-01 7.34137714e-01
4.27841127e-01 3.39772940e-01 -1.29973758e-02 4.14046645e-01
-5.63064098e-01 2.70227224e-01 1.40007973e+00 -1.25123383e-02
8.59897882e-02 -2.34777495e-01 -5.27555585e-01 5.37323833e-01
6.17601752e-01 -5.22303104e-01 -4.97646272e-01 -6.62191987e-01
-9.11280327e-03 -2.15463936e-01 3.10180366e-01 -1.27565384e+00
3.08895521e-02 -8.52430984e-02 6.20855838e-02 -5.07638395e-01
1.25243142e-01 -8.14156353e-01 5.25436759e-01 6.33768499e-01
-5.89477897e-01 2.62085497e-01 2.25573227e-01 6.89728931e-02
-4.56899792e-01 -1.65829420e-01 7.59397924e-01 -1.89651325e-01
-6.78055704e-01 5.69105506e-01 -1.39011860e-01 1.45936742e-01
1.47278512e+00 -3.07892263e-01 -3.74341965e-01 1.19992591e-01
-9.29153502e-01 2.71898687e-01 6.27904773e-01 8.74134123e-01
3.66306454e-01 -1.45874488e+00 -7.72848904e-01 -9.04945210e-02
4.45043594e-01 -2.30158623e-02 4.45676237e-01 1.43144941e+00
-1.02645171e+00 3.74621689e-01 -6.03590071e-01 -6.69035971e-01
-1.48501790e+00 4.73998874e-01 5.81240237e-01 -5.49966514e-01
-6.43318295e-01 6.31482601e-01 1.64547384e-01 -4.14386630e-01
5.13065338e-01 -7.31496930e-01 -5.53057849e-01 2.68225729e-01
3.15445125e-01 1.59017429e-01 4.02111828e-01 -4.58887190e-01
-5.09424150e-01 1.13112837e-01 -1.56978592e-01 2.35338658e-01
1.34970903e+00 3.54439467e-01 5.57860434e-02 2.29777142e-01
1.32927787e+00 -1.72901675e-01 -8.36379349e-01 2.17980787e-01
-7.87749738e-02 -4.58258182e-01 3.91057163e-01 -1.12669659e+00
-1.37882876e+00 4.94707763e-01 9.56701279e-01 7.26671368e-02
1.16612303e+00 -4.76717129e-02 2.96943367e-01 -2.31807142e-01
3.98506343e-01 -8.17644596e-01 9.02687162e-02 5.48229963e-02
1.17078686e+00 -1.12750185e+00 7.04151988e-02 -2.04699978e-01
-6.70769930e-01 1.01780462e+00 7.51705408e-01 3.38802151e-02
7.10659504e-01 4.81570035e-01 3.81996542e-01 -5.07228792e-01
-7.70059109e-01 2.11916819e-01 3.80218178e-01 4.65013623e-01
8.43878865e-01 6.75778314e-02 -7.04370737e-01 4.96582508e-01
-5.41007876e-01 6.40399694e-01 7.86537766e-01 1.19869566e+00
3.91659141e-01 -1.05445802e+00 -1.05591202e-02 6.94589019e-01
-7.91394651e-01 1.11177586e-01 -2.51185894e-01 1.35098791e+00
3.57806206e-01 4.56072837e-01 -2.46937498e-01 -4.46907282e-01
5.75256348e-01 -4.60196674e-01 5.44962347e-01 -6.45805538e-01
-8.41513693e-01 -2.43012950e-01 4.25718963e-01 -8.64710152e-01
-7.26861656e-01 -6.80673003e-01 -7.73446739e-01 -8.91628489e-02
9.71075073e-02 8.50122273e-02 9.86708522e-01 6.53090954e-01
4.33408350e-01 9.49370265e-01 1.69950202e-01 -7.29662299e-01
-3.17028940e-01 -1.22124910e+00 -2.36895308e-01 5.22657037e-01
7.78041407e-02 -1.08092093e+00 -2.85438448e-01 5.56344120e-03] | [14.08061408996582, -3.3648154735565186] |
c32246ad-fa70-412e-85b7-17a10d154251 | an-advanced-yolov3-method-for-small-object | 2212.02809 | null | https://arxiv.org/abs/2212.02809v3 | https://arxiv.org/pdf/2212.02809v3.pdf | An advanced YOLOv3 method for small object detection | Small object detection has important application value in the fields of autonomous driving and drone scene analysis. As one of the most advanced object detection algorithms, YOLOv3 suffers some challenges when detecting small objects, such as the problem of detection failure of small objects and occluded objects. To solve these problems, an improved YOLOv3 algorithm for small object detection is proposed. In the proposed method, the dilated convolutions mish (DCM) module is introduced into the backbone network of YOLOv3 to improve the feature expression ability by fusing the feature maps of different receptive fields. In the neck network of YOLOv3, the convolutional block attention module (CBAM) and multi-level fusion module are introduced to select the important information for small object detection in the shallow network, suppress the uncritical information, and use the fusion module to fuse the feature maps of different scales, so as to improve the detection accuracy of the algorithm. In addition, the Soft-NMS and Complete-IoU (CloU) strategies are applied to candidate frame screening, which improves the accuracy of the algorithm for the detection of occluded objects. The ablation experiment of the MS COCO2017 object detection task proves the effectiveness of several modules introduced in this paper for small object detection. The experimental results on the MS COCO2017, VOC2007, and VOC2012 datasets show that the Average Precision (AP) of this method is 16.5%, 8.71%, and 9.68% higher than that of YOLOv3, respectively. | ['Wenjie Liu', 'Jiacheng Li', 'Shiqiang Du', 'Fengjie He', 'Baokai Liu'] | 2022-12-06 | null | null | null | null | ['small-object-detection'] | ['computer-vision'] | [-2.27562517e-01 -2.25376531e-01 1.46347851e-01 1.80772871e-01
-1.34589016e-01 -3.29971202e-02 2.04862759e-01 -1.34508342e-01
-7.41231084e-01 2.94905156e-01 -3.07189643e-01 5.62679395e-02
3.20014328e-01 -7.51062691e-01 -5.17757893e-01 -9.88994837e-01
3.34062397e-01 -2.04710141e-01 1.10902250e+00 -2.45247304e-01
9.36124250e-02 4.58303183e-01 -1.74964654e+00 3.74273121e-01
7.89816618e-01 1.41760612e+00 5.72809517e-01 2.72873133e-01
4.21875529e-02 8.12032402e-01 -7.43420660e-01 1.06594050e-02
2.31026337e-01 -1.76793724e-01 -4.03496474e-02 -8.94584656e-02
3.25828582e-01 -4.72098112e-01 -4.39052671e-01 1.31911910e+00
8.05297434e-01 7.10980296e-02 3.14420879e-01 -1.23962212e+00
-6.84090182e-02 2.35859305e-01 -8.30512047e-01 7.76618659e-01
-1.17373057e-01 4.10629421e-01 3.47902209e-01 -1.18867815e+00
1.89944491e-01 1.35473943e+00 4.32135642e-01 3.95419985e-01
-7.15309560e-01 -1.14784384e+00 2.47265339e-01 6.52239263e-01
-1.60153973e+00 -4.01031882e-01 4.45019692e-01 -4.11801845e-01
7.56546974e-01 9.41117480e-02 6.63813949e-01 5.18679082e-01
2.49136254e-01 1.15886962e+00 7.33505011e-01 -1.61496311e-01
-8.85641575e-02 3.45940441e-01 1.41327545e-01 7.78941453e-01
4.57676828e-01 1.56705514e-01 -1.94383487e-01 3.61486077e-01
6.27961874e-01 2.56175011e-01 -1.34251490e-01 -9.50882658e-02
-1.07173550e+00 6.20477438e-01 9.55376625e-01 2.55915910e-01
-1.46124914e-01 -1.03375085e-01 3.30834687e-01 -8.36978853e-02
2.80270040e-01 6.68826923e-02 -2.99336463e-01 3.76671255e-01
-6.41361475e-01 1.77514687e-01 6.41042963e-02 1.04267895e+00
6.89166188e-01 2.19476342e-01 -5.97986281e-01 6.28663957e-01
3.37623239e-01 6.21288776e-01 5.95033824e-01 -6.06554806e-01
5.95356464e-01 1.00483584e+00 1.75904036e-01 -1.01503766e+00
-4.38646406e-01 -5.95012724e-01 -6.99529350e-01 3.70954275e-01
1.06970511e-01 1.34494342e-02 -1.16518259e+00 1.39549541e+00
5.01365364e-01 1.56275362e-01 1.49270490e-01 1.15966606e+00
1.50663733e+00 7.69366860e-01 1.77090287e-01 -1.71239212e-01
1.38583958e+00 -1.04736900e+00 -6.17815197e-01 -4.25093770e-01
5.57875216e-01 -7.60044932e-01 6.27065599e-01 -2.59439647e-02
-8.50790620e-01 -1.12778854e+00 -1.15987957e+00 8.37160181e-03
-4.06792581e-01 7.11971641e-01 3.72654319e-01 2.63428539e-01
-5.53293824e-01 -2.78365146e-02 -6.18433893e-01 -3.27234238e-01
7.28921473e-01 3.95148426e-01 -2.08177068e-03 -1.84593186e-01
-1.06443548e+00 9.28871691e-01 8.44775438e-01 5.78023255e-01
-1.05768526e+00 -2.71167010e-01 -7.41807044e-01 2.68757552e-01
4.95885462e-01 -3.86530071e-01 8.17047119e-01 -8.61731529e-01
-8.21309984e-01 6.30823255e-01 1.28121078e-02 -5.36230087e-01
4.37539101e-01 -6.44321516e-02 -4.38063055e-01 2.06586286e-01
2.21544415e-01 9.54083920e-01 7.79852748e-01 -7.44198203e-01
-1.20846045e+00 -2.80781627e-01 5.99797666e-02 3.10015947e-01
-1.03086293e-01 1.50672421e-01 -5.63688993e-01 -4.78898317e-01
1.96363956e-01 -7.19391763e-01 -1.82888091e-01 -1.73015043e-01
-8.35301355e-02 -6.23228371e-01 1.21173358e+00 -3.87332350e-01
1.31273890e+00 -2.70070291e+00 1.10038981e-01 -1.30076155e-01
3.58637393e-01 7.26507843e-01 -7.11969361e-02 -2.22192913e-01
1.63199142e-01 -1.84002340e-01 -3.26691568e-03 3.99461947e-02
-5.33540547e-01 -5.37449196e-02 -6.90600500e-02 5.52099168e-01
3.68493736e-01 8.20108116e-01 -7.60626376e-01 -8.58827055e-01
6.88179195e-01 1.27618790e-01 -3.49819601e-01 2.15933010e-01
1.17045470e-01 3.13409567e-01 -7.02762783e-01 9.01544392e-01
8.73824239e-01 1.28837317e-01 -6.26459002e-01 -4.41979110e-01
-3.73621762e-01 -9.86695215e-02 -1.32512355e+00 1.11458993e+00
-8.77719149e-02 6.11449778e-01 1.44750208e-01 -7.57004201e-01
8.32382619e-01 1.16304591e-01 1.68688059e-01 -7.68962026e-01
6.29935801e-01 2.37711102e-01 3.74831527e-01 -7.53617048e-01
2.39861667e-01 2.95020342e-01 1.15827970e-01 -4.41224605e-01
1.13595270e-01 4.31843773e-02 4.12040293e-01 2.16864392e-01
7.71214306e-01 -1.25402242e-01 1.87114343e-01 -1.79751843e-01
8.74532402e-01 2.73819058e-03 8.75752807e-01 7.13513136e-01
-4.91475195e-01 4.98148233e-01 1.24243021e-01 -4.65995967e-01
-5.68475664e-01 -6.63785338e-01 -3.33307832e-01 7.22721696e-01
8.69671106e-01 -3.61128002e-01 -7.00825751e-01 -5.15394807e-01
-1.17727451e-03 4.43929017e-01 -6.14365578e-01 -5.28475881e-01
-5.90825617e-01 -9.85884607e-01 2.31296256e-01 6.90140188e-01
1.02874875e+00 -1.46402180e+00 -9.00265038e-01 1.46549046e-01
-1.66307583e-01 -1.36374676e+00 -1.42473608e-01 9.99641269e-02
-6.45373285e-01 -1.14762068e+00 -5.28454363e-01 -1.02538371e+00
7.56280124e-01 7.56411791e-01 3.53065670e-01 3.23579699e-01
-5.04864335e-01 -1.57057017e-01 -3.28142762e-01 -6.03921115e-01
-3.63451354e-02 -2.01604560e-01 1.71543986e-01 1.75049827e-01
4.64611977e-01 5.46335131e-02 -7.10333407e-01 6.36955202e-01
-7.21694052e-01 4.40019928e-02 8.63731861e-01 8.31133962e-01
3.63249540e-01 1.22983240e-01 4.55093443e-01 -3.24692905e-01
7.55648240e-02 -1.91150904e-01 -9.05669868e-01 -1.17356889e-01
-4.83912826e-01 -4.93314207e-01 5.74379086e-01 -5.83066463e-01
-8.58725011e-01 1.87670574e-01 -5.33882827e-02 -7.06194222e-01
-2.36488394e-02 -1.00924514e-01 -3.27621549e-01 -2.88922012e-01
3.81016135e-01 3.64311844e-01 -2.61256874e-01 -3.30552280e-01
-5.17689548e-02 7.66350150e-01 4.56749827e-01 2.41184145e-01
7.56267011e-01 3.33611429e-01 -1.49753094e-01 -7.11714804e-01
-8.71582031e-01 -6.39613092e-01 -4.10195857e-01 -4.47161764e-01
1.12979269e+00 -1.31617677e+00 -8.11602235e-01 5.95359504e-01
-1.06444001e+00 1.95786655e-01 -7.47164190e-02 6.34440899e-01
4.35284749e-02 1.32763237e-01 -3.93076360e-01 -7.51007974e-01
-4.16849703e-01 -1.44509208e+00 1.06728590e+00 9.72188771e-01
4.15304154e-01 -1.15632646e-01 -7.88032532e-01 3.54287267e-01
2.59403080e-01 -1.22874811e-01 4.71422583e-01 -3.53227764e-01
-7.96936870e-01 -4.64722574e-01 -6.47916138e-01 4.20530170e-01
-2.61004508e-01 -1.00562826e-01 -1.14077950e+00 -4.64634538e-01
-3.98311429e-02 -2.28120536e-01 1.38176513e+00 5.58355391e-01
1.09078908e+00 1.26978934e-01 -6.35188043e-01 7.23445415e-01
1.14431787e+00 5.51840007e-01 5.65475047e-01 4.64327008e-01
7.09819496e-01 3.65207672e-01 9.92864549e-01 2.18398750e-01
7.09926412e-02 4.85598505e-01 7.26116121e-01 -1.83825478e-01
-4.16745901e-01 -2.71543209e-02 5.92662275e-01 3.88551474e-01
-2.23974250e-02 -2.11274680e-02 -5.22611797e-01 5.49138725e-01
-1.89239109e+00 -1.01103103e+00 -3.04692149e-01 1.94462144e+00
2.90922552e-01 6.15686715e-01 -9.02077854e-02 -3.27268131e-02
8.92643690e-01 1.66604504e-01 -6.27879322e-01 9.85921547e-02
-3.84535819e-01 -3.08636338e-01 6.63112998e-01 2.23947782e-02
-1.38775969e+00 1.13035071e+00 4.98484039e+00 1.24715996e+00
-9.69978631e-01 1.66824564e-01 5.13002336e-01 -1.85370728e-01
5.99497139e-01 -1.40064046e-01 -1.51505232e+00 6.77007377e-01
1.72360674e-01 1.49574235e-01 1.36346191e-01 1.07602513e+00
2.59138137e-01 -5.20065725e-01 -5.36344290e-01 1.18806398e+00
1.56619594e-01 -1.12257898e+00 -1.02730297e-01 -4.09818947e-01
6.10481799e-01 2.68952280e-01 -4.37152758e-02 5.37482142e-01
-1.26090899e-01 -7.65933216e-01 8.85273159e-01 1.64856896e-01
5.12713075e-01 -8.01270902e-01 1.20872784e+00 5.75012326e-01
-1.46905851e+00 -5.39899826e-01 -8.45668197e-01 2.24348810e-02
-1.05823040e-01 3.73539269e-01 -6.47476375e-01 2.43646130e-01
1.23499513e+00 8.82285357e-01 -1.03545392e+00 1.39663517e+00
-4.15312052e-01 3.83877099e-01 -4.94917691e-01 -2.01237112e-01
4.13325816e-01 -2.44046301e-02 7.45057642e-01 1.09512866e+00
1.11818209e-01 2.14348570e-01 3.11941445e-01 7.27705657e-01
1.07455730e-01 -5.72728105e-02 -4.04133171e-01 3.53375763e-01
3.25342953e-01 1.61508799e+00 -8.67267191e-01 -5.57284951e-01
-4.15330708e-01 5.61939895e-01 6.65260851e-02 3.53515059e-01
-9.45923030e-01 -6.21688187e-01 2.93635339e-01 4.13250104e-02
7.06041038e-01 2.01815385e-02 -5.99690042e-02 -1.10841632e+00
-9.87160252e-04 -5.64946234e-01 3.68839264e-01 -9.09302950e-01
-5.79624712e-01 6.66530550e-01 -1.18824728e-01 -1.43879354e+00
3.51814002e-01 -6.06409967e-01 -7.82100260e-01 7.88290441e-01
-1.48202229e+00 -9.46727395e-01 -6.22139812e-01 4.36478198e-01
7.98374653e-01 -3.27400625e-01 8.82133842e-02 5.19436240e-01
-1.08322239e+00 3.83814871e-01 -1.09704509e-01 2.54111439e-01
4.95229155e-01 -6.19113505e-01 -1.04835415e-02 1.21420932e+00
-3.13546836e-01 2.19757810e-01 3.85028452e-01 -5.87144256e-01
-1.04987872e+00 -1.38419390e+00 4.51941192e-01 -2.15118259e-01
2.68808603e-01 -3.55288357e-01 -7.72918820e-01 3.94333392e-01
-1.03933416e-01 4.15237576e-01 -5.99158444e-02 -5.75475454e-01
1.79571047e-01 -3.91330004e-01 -8.44776928e-01 4.65416908e-01
7.45794952e-01 6.41696230e-02 -5.25478721e-01 2.43824661e-01
8.22942138e-01 -4.99846369e-01 -3.49917084e-01 7.77060866e-01
4.72746432e-01 -9.22453046e-01 1.04813337e+00 -2.20737711e-01
-1.48551380e-02 -9.94436204e-01 -7.15163574e-02 -8.38653266e-01
-3.33890706e-01 -3.75749730e-02 1.07635930e-02 1.19927657e+00
7.52754882e-02 -4.13399458e-01 4.72297490e-01 -1.60923619e-02
-3.47093999e-01 -7.09910810e-01 -1.06761050e+00 -4.81966913e-01
-5.74226320e-01 -2.39463627e-01 2.77216464e-01 3.46022040e-01
-5.85416317e-01 5.11868775e-01 -1.84670821e-01 3.75745714e-01
4.16452795e-01 2.72694945e-01 7.80605555e-01 -1.10691667e+00
1.69093430e-01 -5.41490376e-01 -6.57392561e-01 -1.21652436e+00
-3.09452862e-01 -7.28273392e-01 1.68566957e-01 -1.47370100e+00
2.41395369e-01 -3.35480809e-01 -5.66286922e-01 3.15596163e-01
-5.59586585e-01 4.60754186e-01 3.67735475e-01 2.10040033e-01
-9.88501847e-01 7.31456339e-01 1.39183056e+00 -2.58610576e-01
-2.60623574e-01 3.36771935e-01 -2.83361703e-01 9.48604107e-01
5.97398639e-01 -5.80714941e-01 -6.68034703e-02 -2.85710216e-01
-2.15793818e-01 -2.91232377e-01 5.61169267e-01 -1.36395502e+00
3.78160417e-01 1.51770189e-01 9.56946552e-01 -1.06336415e+00
3.44217330e-01 -7.70167291e-01 -4.11904871e-01 9.84303772e-01
1.57373801e-01 -1.60097092e-01 5.66387117e-01 5.30020773e-01
-2.91346908e-01 -1.40734270e-01 1.16250825e+00 -1.10278092e-01
-1.27596688e+00 3.28396082e-01 -4.64504182e-01 -8.43651965e-02
1.30335152e+00 -2.74119526e-01 -2.85633296e-01 1.75111756e-01
-4.63035554e-01 8.31923902e-01 7.20156580e-02 5.54113209e-01
9.68906343e-01 -1.21611822e+00 -6.25251472e-01 5.90736389e-01
3.31856370e-01 4.24504727e-01 2.78578401e-01 1.18118799e+00
-4.71493036e-01 3.47069561e-01 -2.37473413e-01 -7.88941681e-01
-1.41624427e+00 6.60293996e-01 4.76816654e-01 2.00733095e-01
-6.42420113e-01 1.05303776e+00 7.82141566e-01 9.21691060e-02
3.49852741e-01 -4.61725056e-01 -8.00375700e-01 1.05089992e-01
6.66006327e-01 3.90165776e-01 -7.38497302e-02 -8.58883560e-01
-6.06062770e-01 7.19101787e-01 -1.56301364e-01 5.63100338e-01
9.43560839e-01 -2.31760994e-01 -4.65489589e-02 9.82694179e-02
7.81324685e-01 -1.34043142e-01 -1.21633434e+00 -2.27777138e-01
-4.59122062e-01 -2.39836365e-01 2.71088094e-01 -5.86036503e-01
-1.17719543e+00 1.08795309e+00 9.91602480e-01 9.17537604e-03
1.15647900e+00 1.46442011e-01 6.74749434e-01 1.91204026e-01
6.49795309e-02 -8.59043121e-01 -1.46376356e-01 4.17225480e-01
6.44429922e-01 -1.49228799e+00 1.00214370e-01 -3.09070259e-01
-5.36487401e-01 1.02515960e+00 1.30927646e+00 -2.36528382e-01
3.85982275e-01 1.65077597e-01 -6.97959214e-02 -8.37649405e-02
-4.27525848e-01 -6.03282988e-01 3.37764412e-01 2.52961904e-01
-2.14012191e-01 -1.26543760e-01 -3.98848623e-01 7.35995054e-01
2.41307154e-01 -2.64080286e-01 3.40336531e-01 6.95729852e-01
-9.11931157e-01 -2.55375534e-01 -4.92352933e-01 4.44614470e-01
-4.07966971e-01 -2.04296470e-01 -2.07551405e-01 8.60800982e-01
8.19399059e-01 1.09878623e+00 1.09627135e-01 -7.15340912e-01
3.89099717e-01 -3.90048414e-01 1.29164785e-01 -4.79138255e-01
-4.69635785e-01 4.54480916e-01 -3.07644755e-01 -4.64997917e-01
-4.73422468e-01 -3.84731233e-01 -1.41495335e+00 1.13215603e-01
-8.23962271e-01 1.19105548e-01 2.69462138e-01 9.19463158e-01
2.48398289e-01 8.60385120e-01 4.84963715e-01 -8.31319034e-01
-1.95440531e-01 -1.14530253e+00 -4.38668191e-01 9.84132439e-02
4.62730885e-01 -1.11224818e+00 -3.77766818e-01 -2.56951809e-01] | [8.674844741821289, -0.6441714763641357] |
824cc224-183a-409b-beab-3dda5769978a | repeatability-is-not-enough-learning-affine | 1711.06704 | null | http://arxiv.org/abs/1711.06704v4 | http://arxiv.org/pdf/1711.06704v4.pdf | Repeatability Is Not Enough: Learning Affine Regions via Discriminability | A method for learning local affine-covariant regions is presented. We show
that maximizing geometric repeatability does not lead to local regions, a.k.a
features,that are reliably matched and this necessitates descriptor-based
learning. We explore factors that influence such learning and registration: the
loss function, descriptor type, geometric parametrization and the trade-off
between matchability and geometric accuracy and propose a novel hard
negative-constant loss function for learning of affine regions. The affine
shape estimator -- AffNet -- trained with the hard negative-constant loss
outperforms the state-of-the-art in bag-of-words image retrieval and wide
baseline stereo. The proposed training process does not require precisely
geometrically aligned patches.The source codes and trained weights are
available at https://github.com/ducha-aiki/affnet | ['Jiri Matas', 'Dmytro Mishkin', 'Filip Radenovic'] | 2017-11-17 | repeatability-is-not-enough-learning-affine-1 | http://openaccess.thecvf.com/content_ECCV_2018/html/Dmytro_Mishkin_Repeatability_Is_Not_ECCV_2018_paper.html | http://openaccess.thecvf.com/content_ECCV_2018/papers/Dmytro_Mishkin_Repeatability_Is_Not_ECCV_2018_paper.pdf | eccv-2018-9 | ['image-matching'] | ['computer-vision'] | [-1.59470096e-01 -2.72085965e-01 -1.98514789e-01 -7.93302238e-01
-1.50548363e+00 -7.97598600e-01 7.54253924e-01 2.47068748e-01
-6.34662986e-01 2.82544851e-01 2.80383706e-01 2.30360091e-01
-3.58487815e-01 -7.22243845e-01 -9.35981691e-01 -8.27876270e-01
-4.45755161e-02 4.40654159e-01 2.25394413e-01 -3.82828936e-02
4.19320256e-01 9.36854899e-01 -1.26447022e+00 1.63351685e-01
4.79784310e-01 1.18358171e+00 5.25974063e-03 4.64966804e-01
3.72520804e-01 8.14858153e-02 1.32905757e-02 -5.58408916e-01
7.69185841e-01 -8.66139606e-02 -5.23817897e-01 -2.06737369e-01
1.41429198e+00 -4.48171526e-01 -4.46736157e-01 9.25458074e-01
7.67597973e-01 1.22766018e-01 1.19366741e+00 -8.53690088e-01
-7.40921199e-01 1.29377907e-02 -4.97716159e-01 7.13799819e-02
9.38286334e-02 8.81338865e-02 1.33414495e+00 -1.23083615e+00
9.22714293e-01 1.16513586e+00 9.17984724e-01 2.70834118e-01
-1.19787192e+00 -5.48412502e-01 -7.39680529e-02 1.68487951e-01
-1.94738209e+00 -5.05034983e-01 7.84239650e-01 -5.72274625e-01
9.66150343e-01 2.42782906e-01 4.03112024e-01 8.45936418e-01
4.87923503e-01 3.80927742e-01 9.80204046e-01 -4.31186467e-01
-2.72982381e-03 -1.69719741e-01 -9.65082571e-02 8.46921027e-01
2.75911748e-01 3.81084681e-01 -4.20133471e-01 -2.25887716e-01
1.17145574e+00 8.85333493e-03 -6.00256734e-02 -1.05229282e+00
-1.09955597e+00 9.85439837e-01 8.10788631e-01 2.70264983e-01
-2.99798936e-01 4.03236926e-01 3.84487867e-01 3.80911678e-01
5.66061676e-01 6.22765958e-01 -3.75095576e-01 2.88451433e-01
-1.00344956e+00 4.07109261e-01 3.72692496e-01 1.14668691e+00
9.16280866e-01 -1.99184969e-01 -1.38994604e-02 9.82900798e-01
1.53306529e-01 7.28447378e-01 9.85098705e-02 -8.94172013e-01
2.92443454e-01 3.57124507e-01 -4.08748575e-02 -1.04689419e+00
-2.74145812e-01 -4.04976249e-01 -6.04614496e-01 2.47997046e-01
6.45554900e-01 3.03362489e-01 -8.64330471e-01 1.59365654e+00
3.07502270e-01 -2.62973011e-01 -3.27211380e-01 1.22123671e+00
5.63446462e-01 3.06140214e-01 -2.47783676e-01 2.60970980e-01
1.32016861e+00 -8.57381999e-01 -2.63582736e-01 -1.18312128e-01
5.12510538e-01 -1.31028426e+00 8.70326579e-01 -9.37971659e-03
-1.20841503e+00 -4.46453303e-01 -1.12153137e+00 -3.59109163e-01
-5.37030041e-01 2.41752625e-01 3.12823445e-01 1.48144007e-01
-1.04812074e+00 5.93598485e-01 -6.75133586e-01 -5.47564030e-01
3.05946141e-01 4.80343401e-01 -6.95662558e-01 -4.59049046e-02
-8.01030934e-01 1.04995072e+00 -5.82538247e-02 -8.26504081e-02
-9.37303841e-01 -6.29855454e-01 -9.31362629e-01 -1.57189116e-01
3.46357487e-02 -7.73975730e-01 9.76630390e-01 -8.99064422e-01
-1.01899219e+00 1.39312971e+00 -8.01136941e-02 -3.02061856e-01
6.66855633e-01 -3.87899399e-01 -6.50727376e-02 2.18157530e-01
-3.49592268e-02 1.01219606e+00 1.06337023e+00 -1.33533645e+00
-1.96263418e-01 -5.34381032e-01 -9.33574736e-02 2.50151038e-01
1.57522736e-03 8.85306895e-02 -2.88029253e-01 -7.27787733e-01
1.80836841e-01 -1.04500270e+00 -1.26146376e-01 5.62014401e-01
-2.61364393e-02 -1.44163117e-01 3.49548548e-01 -6.89027667e-01
7.95687735e-01 -2.15117431e+00 -2.59926021e-02 6.04217350e-01
1.45136854e-02 1.18452674e-02 -3.65717232e-01 4.20520663e-01
-1.68700367e-02 -1.55132830e-01 -6.30556345e-02 -2.10710123e-01
1.93511192e-02 -4.96347472e-02 -2.91704774e-01 1.07332015e+00
2.36738771e-01 9.02074039e-01 -6.32891715e-01 -5.36903620e-01
4.54306453e-01 7.99873769e-01 -5.57791114e-01 2.76576400e-01
9.83688608e-02 2.03175634e-01 -4.78313923e-01 6.31026924e-01
9.34781671e-01 -3.57107744e-02 -3.43351126e-01 -6.61125064e-01
-2.90726930e-01 1.02591082e-01 -1.09858680e+00 1.89772975e+00
-4.37231123e-01 6.58429086e-01 -7.02821761e-02 -8.75817895e-01
1.16374898e+00 -3.80247608e-02 3.75084132e-01 -8.84904027e-01
8.38712454e-02 6.01338029e-01 -1.94035679e-01 -2.44414717e-01
3.34818095e-01 2.05968563e-02 -4.92889211e-02 -6.22717254e-02
2.93731868e-01 -4.55673128e-01 -3.01577538e-01 -1.45899594e-01
7.95566440e-01 3.22442234e-01 4.85632300e-01 -6.97103977e-01
5.34281492e-01 -5.57820760e-02 3.87897551e-01 5.75584650e-01
-3.53843011e-02 1.11965132e+00 1.05877928e-01 -6.60733342e-01
-1.71184635e+00 -1.29101968e+00 -5.88617563e-01 9.10383880e-01
3.44647944e-01 -2.08163530e-01 -6.06446505e-01 -3.49485666e-01
3.29758883e-01 3.40344369e-01 -5.82613111e-01 -8.15984681e-02
-6.64508641e-01 -7.54231401e-03 4.47690934e-01 4.82269734e-01
1.89259261e-01 -7.91309714e-01 -3.30778182e-01 -1.27389029e-01
1.76217735e-01 -9.24384296e-01 -1.07841432e+00 3.86468917e-02
-8.33443940e-01 -9.06369090e-01 -9.21861589e-01 -9.74317968e-01
1.13117850e+00 1.40758753e-01 1.23712587e+00 -1.54570073e-01
-5.69601417e-01 6.66733682e-01 -1.31691590e-01 -1.10542178e-01
-4.24614884e-02 2.11231589e-01 -4.97271642e-02 -9.95561481e-02
2.15129107e-01 -4.32668090e-01 -1.08498311e+00 4.78816569e-01
-7.17317283e-01 -2.79088080e-01 8.03402960e-01 8.54966700e-01
1.11295199e+00 -6.32196784e-01 4.14278768e-02 -4.14359659e-01
2.08643526e-01 9.70535204e-02 -8.96924138e-01 4.21542585e-01
-6.40316188e-01 2.52576977e-01 3.50813150e-01 -3.70439619e-01
-6.32483959e-01 2.84364492e-01 -1.00581504e-01 -6.37350202e-01
-8.35847333e-02 4.57881950e-02 1.73897296e-02 -7.06595182e-01
7.95827508e-01 4.06542309e-02 5.44444546e-02 -3.39242756e-01
5.65091729e-01 3.82131934e-01 4.59584415e-01 -7.27290809e-01
9.08598423e-01 7.17129052e-01 1.81136057e-01 -6.08318448e-01
-6.81697249e-01 -9.41801727e-01 -9.22011733e-01 -1.55982137e-01
9.26481485e-01 -1.16048419e+00 -2.16748893e-01 3.91873896e-01
-1.19703960e+00 -1.83085069e-01 -2.57646263e-01 5.34903109e-01
-9.01542366e-01 1.36422068e-01 -4.04812992e-01 -4.47148681e-01
-6.64612889e-01 -1.07094300e+00 1.57718587e+00 -4.91157640e-03
-1.98506653e-01 -9.73084927e-01 2.43766278e-01 1.37803733e-01
6.13054395e-01 2.38191858e-01 5.83101094e-01 -5.52472711e-01
-8.36592376e-01 -2.43410081e-01 -4.60035652e-01 3.60888541e-01
-1.27474770e-01 -4.48663011e-02 -1.04141963e+00 -6.02415323e-01
-2.31998682e-01 -3.48983049e-01 8.52244496e-01 6.19054973e-01
1.05361092e+00 -4.04672742e-01 -7.38574490e-02 1.10877299e+00
1.77872157e+00 -2.13717118e-01 6.29589617e-01 3.91990036e-01
6.80831552e-01 5.31885922e-01 6.79617822e-01 2.30326831e-01
2.01617911e-01 1.11121166e+00 3.51132751e-01 -3.42440039e-01
-3.16683084e-01 -2.25292265e-01 2.77829558e-01 8.20712388e-01
-7.09452182e-02 8.44124407e-02 -8.95144403e-01 7.01761663e-01
-1.80154192e+00 -8.31751108e-01 1.09682269e-01 2.52463031e+00
9.17792022e-01 -1.53671071e-01 4.84682359e-02 -5.83864748e-01
5.12475967e-01 3.07494819e-01 -3.61157775e-01 -3.63879412e-01
-3.66559803e-01 2.83539474e-01 1.08028746e+00 1.02086210e+00
-1.20869839e+00 1.06176102e+00 5.43816376e+00 1.14326286e+00
-1.27190053e+00 2.00866282e-01 5.26583016e-01 1.13076016e-01
-3.73006135e-01 9.78781879e-02 -9.00178969e-01 6.14047647e-02
5.39310098e-01 -1.48886228e-02 2.63195813e-01 8.05959344e-01
1.37187779e-01 1.29816115e-01 -1.08552051e+00 9.95293498e-01
3.21519405e-01 -1.25205600e+00 6.71122223e-02 1.57821089e-01
7.47072875e-01 3.74529183e-01 1.86689690e-01 -2.89209396e-01
-2.46575363e-02 -8.77837062e-01 8.92841697e-01 7.52924025e-01
1.05789065e+00 -5.56199193e-01 7.30914712e-01 -2.79629469e-01
-1.24208224e+00 2.75213063e-01 -6.16890907e-01 5.58527708e-01
-7.99600929e-02 4.12451327e-01 -4.47018921e-01 3.79684269e-01
6.53296769e-01 5.32506227e-01 -7.75510132e-01 1.41639233e+00
4.70076054e-02 1.37705982e-01 -4.76124883e-01 1.75848261e-01
3.00492913e-01 -4.04197484e-01 5.41135073e-01 1.50604284e+00
4.99272346e-01 -8.81085396e-02 9.08685103e-02 7.93938935e-01
6.44572899e-02 3.25315237e-01 -8.35944712e-01 3.61301631e-01
4.62286413e-01 1.24659443e+00 -5.09236038e-01 5.75094707e-02
-3.47420752e-01 9.03167009e-01 4.37904656e-01 2.62119174e-01
-5.04422009e-01 -2.78492689e-01 6.80362999e-01 5.19560218e-01
3.88229489e-01 -5.56546688e-01 -3.79452378e-01 -1.01092207e+00
1.82090774e-01 -7.72515595e-01 3.13185304e-01 -7.67401099e-01
-1.64838886e+00 4.18678015e-01 2.83947289e-01 -1.40195096e+00
-1.20155267e-01 -8.38240445e-01 -4.49183285e-01 8.73237729e-01
-1.45065045e+00 -1.57504535e+00 -3.04995894e-01 5.45103908e-01
3.40642333e-01 -2.25120604e-01 7.85320938e-01 3.10235739e-01
9.53363553e-02 9.00518775e-01 3.78884286e-01 1.55054212e-01
1.34488714e+00 -1.12435019e+00 4.11018252e-01 5.55191994e-01
2.48060018e-01 6.78985238e-01 6.41077101e-01 -2.31390446e-01
-1.29755080e+00 -9.50806797e-01 9.83360529e-01 -5.64680755e-01
7.65581071e-01 -6.28168285e-01 -7.96893954e-01 3.94759774e-01
2.13982955e-01 3.48932832e-01 3.57854813e-01 -1.28341764e-01
-8.45577359e-01 -5.13444722e-01 -1.26078236e+00 3.97569954e-01
1.11841738e+00 -8.64673495e-01 -2.97107309e-01 4.00601208e-01
3.81655335e-01 -5.55789590e-01 -1.18583691e+00 4.38457608e-01
8.92713487e-01 -7.06005752e-01 1.42760646e+00 -3.36970329e-01
1.05610691e-01 -1.98350653e-01 -4.78711069e-01 -1.03643358e+00
-4.93529558e-01 -3.19891393e-01 3.76247436e-01 1.00331330e+00
4.08391923e-01 -7.74282277e-01 4.73826826e-01 4.48364466e-01
-5.33247553e-02 -8.62850308e-01 -1.12119102e+00 -1.11604047e+00
5.27826190e-01 -1.26519576e-01 3.35349381e-01 8.77144516e-01
-4.85915869e-01 2.93596406e-02 -1.54316396e-01 1.47233531e-01
8.04461241e-01 9.76578072e-02 6.47989452e-01 -1.02213693e+00
7.54153505e-02 -5.57798326e-01 -8.48226011e-01 -9.22349095e-01
1.32702485e-01 -9.11658823e-01 -3.58489193e-02 -1.18240166e+00
2.57626742e-01 -6.19754910e-01 -2.85295904e-01 4.43148434e-01
2.17885450e-01 3.08402538e-01 1.22531250e-01 3.83488685e-01
-6.69796586e-01 4.63238895e-01 1.25036740e+00 -1.60231476e-03
1.49623334e-01 -2.97364861e-01 -1.95362970e-01 4.48444515e-01
7.78788030e-01 -5.26170790e-01 -6.61255196e-02 -5.15450478e-01
1.53364718e-01 -3.34691733e-01 6.24167740e-01 -7.71736979e-01
3.65872204e-01 -1.16490208e-01 4.69331205e-01 -4.45917994e-01
4.29304123e-01 -1.00954306e+00 6.92195967e-02 1.33488894e-01
-5.49860954e-01 5.30241787e-01 9.05064940e-02 2.79707640e-01
-1.98702812e-01 -2.33392283e-01 1.00918579e+00 1.67175353e-01
-5.28986871e-01 4.42129374e-01 2.33974829e-01 2.07508549e-01
7.71920085e-01 -2.12457255e-01 -3.53838861e-01 -3.63885343e-01
-5.09606004e-01 -7.44682178e-02 9.36002195e-01 4.69893873e-01
6.25546455e-01 -1.62910986e+00 -8.95201027e-01 2.99840927e-01
4.88505721e-01 -8.00828189e-02 2.72867605e-02 7.89934397e-01
-8.99151742e-01 4.07537282e-01 -1.64899901e-01 -6.69589639e-01
-1.43304420e+00 1.99389845e-01 6.69701517e-01 -1.22266129e-01
-4.82048333e-01 9.07284677e-01 3.93348694e-01 -6.84228599e-01
2.25876510e-01 -2.23412111e-01 3.70048523e-01 -3.59526537e-02
-2.35974658e-02 4.92822379e-02 2.01586723e-01 -9.63396430e-01
-4.20846224e-01 1.27218294e+00 -9.40658152e-02 -1.25078410e-01
1.36807251e+00 -4.77930084e-02 -9.95233580e-02 2.01158375e-01
1.66359341e+00 -7.25895911e-02 -1.30719626e+00 -5.05131364e-01
-1.49664879e-01 -8.07525992e-01 2.19838887e-01 -5.53519785e-01
-9.18094695e-01 8.84960115e-01 1.16832602e+00 -3.04608345e-01
7.53123403e-01 1.78960383e-01 5.63322008e-01 3.11983943e-01
3.88658732e-01 -1.15301144e+00 -3.95635702e-02 4.38038647e-01
1.40888429e+00 -1.47971594e+00 3.36328924e-01 -2.26317853e-01
-4.60831881e-01 1.14033711e+00 4.92395043e-01 -6.66605234e-01
9.36495543e-01 1.55669704e-01 2.20715523e-01 -3.35896969e-01
-4.09762830e-01 -2.36334249e-01 1.04391813e+00 4.74286288e-01
5.77818871e-01 1.53281614e-01 -3.82946551e-01 -5.91195822e-02
-3.23371440e-01 -4.39399928e-01 -2.08426565e-01 5.38522243e-01
-1.97426453e-01 -1.09490132e+00 -5.02673030e-01 4.64462191e-01
-2.65769154e-01 -1.11554526e-01 -5.34682572e-01 8.07955146e-01
8.35211575e-02 3.16361755e-01 3.31963092e-01 -1.54125720e-01
5.14450908e-01 -1.30402267e-01 9.08742189e-01 -2.85135210e-01
-5.62472761e-01 2.98953533e-01 2.52667256e-03 -6.50821328e-01
-3.89958769e-01 -9.18614745e-01 -9.31378067e-01 -3.63314390e-01
-4.53209847e-01 -1.95066765e-01 6.34881735e-01 5.74180126e-01
4.12769288e-01 -1.90814972e-01 5.87383628e-01 -1.02751184e+00
-7.61191130e-01 -8.29766929e-01 -3.95147562e-01 5.23080170e-01
4.61798489e-01 -6.06549382e-01 -5.96601963e-01 -5.54494374e-02] | [8.175150871276855, -2.042151689529419] |
a43f270b-68d2-43ba-b3a4-cc9798507807 | tinydefectnet-highly-compact-deep-neural | 2111.14319 | null | https://arxiv.org/abs/2111.14319v1 | https://arxiv.org/pdf/2111.14319v1.pdf | TinyDefectNet: Highly Compact Deep Neural Network Architecture for High-Throughput Manufacturing Visual Quality Inspection | A critical aspect in the manufacturing process is the visual quality inspection of manufactured components for defects and flaws. Human-only visual inspection can be very time-consuming and laborious, and is a significant bottleneck especially for high-throughput manufacturing scenarios. Given significant advances in the field of deep learning, automated visual quality inspection can lead to highly efficient and reliable detection of defects and flaws during the manufacturing process. However, deep learning-driven visual inspection methods often necessitate significant computational resources, thus limiting throughput and act as a bottleneck to widespread adoption for enabling smart factories. In this study, we investigated the utilization of a machine-driven design exploration approach to create TinyDefectNet, a highly compact deep convolutional network architecture tailored for high-throughput manufacturing visual quality inspection. TinyDefectNet comprises of just ~427K parameters and has a computational complexity of ~97M FLOPs, yet achieving a detection accuracy of a state-of-the-art architecture for the task of surface defect detection on the NEU defect benchmark dataset. As such, TinyDefectNet can achieve the same level of detection performance at 52$\times$ lower architectural complexity and 11x lower computational complexity. Furthermore, TinyDefectNet was deployed on an AMD EPYC 7R32, and achieved 7.6x faster throughput using the native Tensorflow environment and 9x faster throughput using AMD ZenDNN accelerator library. Finally, explainability-driven performance validation strategy was conducted to ensure correct decision-making behaviour was exhibited by TinyDefectNet to improve trust in its usage by operators and inspectors. | ['Alexander Wong', 'Francis Li', 'Gautam Bathla', 'Mahmoud Famouri', 'Mohammad Javad Shafiee'] | 2021-11-29 | null | null | null | null | ['defect-detection'] | ['computer-vision'] | [-1.54328883e-01 9.54231340e-03 1.22983918e-01 -1.02502555e-01
-2.07099035e-01 -1.45463914e-01 -2.47225732e-01 4.22431499e-01
5.95121048e-02 -2.87461951e-02 -7.11150169e-01 -8.17414582e-01
-1.02366768e-01 -8.48028660e-01 -5.31820297e-01 -2.51973152e-01
-2.52016068e-01 2.63447136e-01 1.23394378e-01 -1.03642590e-01
3.42054188e-01 6.07773244e-01 -1.63198268e+00 5.24772644e-01
5.73523939e-01 1.57421196e+00 5.46164699e-02 8.18595707e-01
2.45929569e-01 6.84815288e-01 -8.80158424e-01 -1.48094893e-01
3.75650197e-01 8.51793587e-02 -7.15089440e-01 2.07129166e-01
2.21314877e-01 -4.94322956e-01 -1.67448204e-02 9.38611925e-01
5.62182724e-01 -5.29607952e-01 3.03245068e-01 -1.06124043e+00
-6.22837365e-01 1.66779459e-01 -5.20661950e-01 2.54977703e-01
1.97241530e-01 7.28719711e-01 8.48538518e-01 -8.35107923e-01
2.08057389e-01 9.73209560e-01 5.46459436e-01 1.55252159e-01
-9.25823390e-01 -6.20520890e-01 -3.04376036e-01 -4.87139970e-02
-9.55235481e-01 -1.83907717e-01 6.01286411e-01 -5.71561694e-01
1.54570222e+00 -3.93695310e-02 8.11841846e-01 7.15125382e-01
9.35857773e-01 3.45714808e-01 8.68068516e-01 -3.08574796e-01
5.08047640e-01 -2.54653841e-01 5.31418389e-03 1.26801503e+00
5.36905468e-01 3.10146332e-01 -2.34466344e-01 1.57760605e-01
1.18804681e+00 5.64906038e-02 1.16991177e-01 -1.34718329e-01
-9.52616394e-01 9.12579596e-01 5.59301853e-01 9.89976451e-02
-3.10884804e-01 5.71899295e-01 8.17792356e-01 6.30869210e-01
1.69963464e-01 9.54391539e-01 -6.56616867e-01 -3.49470049e-01
-5.67176819e-01 -1.62049547e-01 5.04735470e-01 7.85417199e-01
6.02470517e-01 6.54636979e-01 8.49748924e-02 5.08477688e-01
3.18731487e-01 4.76033300e-01 -8.21294542e-03 -7.79103458e-01
7.04572648e-02 1.09451115e+00 -1.97048813e-01 -1.00167036e+00
-5.92068732e-01 -6.11256123e-01 -8.50356996e-01 1.10012579e+00
3.14445719e-02 -1.76123261e-01 -1.26989305e+00 6.65566146e-01
1.93267345e-01 -7.11831570e-01 -3.67094427e-01 7.71971345e-01
5.18533945e-01 3.62906814e-01 -1.63369298e-01 4.12777334e-01
1.37476349e+00 -6.76701367e-01 -2.66147017e-01 -2.31842518e-01
7.49288857e-01 -8.83267701e-01 1.16445398e+00 9.83268976e-01
-8.88956487e-01 -8.31235528e-01 -1.90270901e+00 1.17155220e-02
-2.27434158e-01 7.15483665e-01 1.01842844e+00 7.48865783e-01
-7.40612149e-01 8.89533043e-01 -1.18967032e+00 -8.57280865e-02
7.06755757e-01 7.28354275e-01 -2.67816782e-01 -2.97399998e-01
-3.65537614e-01 5.01267195e-01 7.11502284e-02 2.17471063e-01
-1.35082150e+00 -1.07441020e+00 -8.64505351e-01 1.58751562e-01
3.04300696e-01 -3.58344585e-01 1.17575562e+00 -5.55810869e-01
-1.34812224e+00 4.76312310e-01 5.75987041e-01 -3.26521128e-01
1.88299358e-01 -3.57364655e-01 -7.00942099e-01 1.02490515e-01
3.21505442e-02 2.72214711e-01 9.74015594e-01 -8.95813942e-01
-6.26375735e-01 -2.24884242e-01 2.76116192e-01 -6.57871723e-01
-1.39649734e-01 -6.93330308e-03 -1.47816613e-01 -3.15215886e-01
8.62209275e-02 -6.30013227e-01 -1.53503135e-01 2.24438965e-01
-4.62916166e-01 -1.81318354e-02 9.18762803e-01 -5.84685802e-01
9.83913124e-01 -2.15052438e+00 -5.78181565e-01 2.30800167e-01
5.60573637e-01 5.81194580e-01 8.87113214e-02 2.58798450e-01
-2.38389909e-01 -2.25753020e-02 1.56602904e-01 -2.27345489e-02
-1.06881730e-01 -1.33033276e-01 4.45262969e-01 6.49913549e-01
6.70033753e-01 7.77412415e-01 -6.20834768e-01 6.51691183e-02
6.33609593e-01 3.62575203e-01 -6.39565110e-01 1.66580245e-01
-1.79481596e-01 8.31235107e-03 -3.20742488e-01 1.42867076e+00
4.20106322e-01 -4.82535571e-01 -1.55029669e-01 -6.28425300e-01
-1.17170319e-01 9.77201387e-03 -1.00245154e+00 1.52114344e+00
-8.65843594e-01 7.65757263e-01 3.42051566e-01 -1.01647890e+00
1.27589691e+00 1.27604857e-01 3.63455176e-01 -1.01322830e+00
6.45935178e-01 2.50436515e-01 2.41661027e-01 -4.73136157e-01
2.78597772e-01 4.22335826e-02 -2.26335421e-01 2.81625390e-01
4.04524505e-02 -5.78516126e-02 1.24139756e-01 -2.22365648e-01
1.80326521e+00 -2.50279516e-01 -1.00766063e-01 -3.70394886e-01
1.28848329e-01 2.10723042e-01 4.23918903e-01 2.96606928e-01
-4.69930284e-02 3.86546314e-01 5.86109936e-01 -9.17024255e-01
-1.28683758e+00 -9.84900355e-01 -4.09511626e-02 4.63548332e-01
-1.33252561e-01 -3.83456945e-01 -5.02451837e-01 -6.55391395e-01
2.47890681e-01 3.61955971e-01 -5.14380515e-01 -5.12424469e-01
-3.49952817e-01 -5.37298024e-01 2.54498869e-01 7.63230145e-01
5.59323072e-01 -9.75313723e-01 -1.34190607e+00 4.22330379e-01
1.00466001e+00 -9.44053173e-01 1.94183916e-01 5.58344841e-01
-6.71029747e-01 -1.40145802e+00 -1.10035427e-01 -7.56701469e-01
7.97811508e-01 -9.81254727e-02 1.29162407e+00 5.11481166e-01
-1.34112942e+00 7.25976303e-02 -3.41845423e-01 -4.58157033e-01
-5.42206168e-01 -1.51034266e-01 -8.72208551e-02 -5.06397843e-01
2.40879670e-01 -3.75423729e-01 -9.35650766e-01 3.05124670e-01
-5.08747339e-01 -1.62066519e-01 1.07527912e+00 1.00883865e+00
3.06258619e-01 5.75041473e-01 5.99511683e-01 -6.05499506e-01
5.69730580e-01 -5.74917421e-02 -8.98504257e-01 -1.84666932e-01
-9.67432022e-01 -1.05157562e-01 8.52013886e-01 -1.33621410e-01
-7.13760793e-01 -6.99068457e-02 -3.20114315e-01 -5.09099305e-01
-1.22223444e-01 5.10011137e-01 -4.71308492e-02 -4.19954956e-01
5.64751744e-01 -5.57205617e-01 2.23325729e-01 -4.51859325e-01
-1.32136717e-01 6.61831319e-01 3.49290878e-01 -3.87122661e-01
5.34999311e-01 2.52466410e-01 1.85535043e-01 -9.35793757e-01
-2.82126218e-01 -1.85208693e-01 -3.21444631e-01 -4.53237891e-01
7.96659172e-01 -7.88662434e-01 -1.28004456e+00 5.36186934e-01
-1.02846706e+00 -2.27099046e-01 -1.56137794e-01 1.24524601e-01
-1.98765714e-02 2.14911059e-01 -8.88154805e-01 -5.16710579e-01
-7.11534381e-01 -1.45150542e+00 1.07905138e+00 -9.69674625e-03
-3.59017760e-01 -6.09183133e-01 -7.04643726e-01 4.88959849e-01
5.82692266e-01 5.42265117e-01 1.33125722e+00 -2.10912928e-01
-6.84341550e-01 -6.61794662e-01 -5.08850396e-01 8.32162261e-01
3.61657679e-01 1.59507304e-01 -7.62940407e-01 -6.06641650e-01
-8.41292366e-02 -4.07644957e-01 2.95765102e-01 1.89899236e-01
1.13069415e+00 3.63455892e-01 -1.38561159e-01 4.11199450e-01
1.71308339e+00 4.78508443e-01 4.81866568e-01 2.14709938e-01
8.59074950e-01 1.86519966e-01 8.90132904e-01 6.15864992e-01
-3.04646522e-01 2.93445349e-01 1.06500781e+00 -4.69246328e-01
-2.04913124e-01 1.40138477e-01 1.62954286e-01 7.84566462e-01
1.55321777e-01 -3.17825489e-02 -1.05206692e+00 6.17218316e-01
-1.08932626e+00 -1.37382343e-01 -1.69355586e-01 2.00541306e+00
2.91486949e-01 8.12842369e-01 -2.93420643e-01 5.40616453e-01
2.41328180e-01 -3.03391218e-01 -7.58245349e-01 -8.36153328e-01
5.17541885e-01 7.29533911e-01 6.11764431e-01 -1.85259745e-01
-7.93489158e-01 5.29194951e-01 5.79118681e+00 6.60941124e-01
-1.36737275e+00 -4.28767828e-03 5.75973511e-01 -1.73596755e-01
3.56913507e-01 -2.37225831e-01 -5.90016425e-01 2.86617666e-01
1.01125312e+00 4.33161944e-01 4.98591103e-02 1.27510011e+00
3.22211832e-02 -3.46484691e-01 -1.32111514e+00 9.41859841e-01
-2.81264395e-01 -1.62354696e+00 -4.42037791e-01 3.03435624e-01
4.70879674e-01 -2.66722199e-02 9.59837288e-02 1.48715764e-01
3.75753254e-01 -1.17074370e+00 5.96090078e-01 -1.92251921e-01
1.06829190e+00 -1.15977812e+00 9.89948988e-01 -2.57991552e-01
-1.08237934e+00 -5.15964329e-01 -5.00704765e-01 -2.96410441e-01
8.90484527e-02 1.06369936e+00 -9.75824475e-01 4.18867826e-01
1.10184443e+00 3.41881454e-01 -5.01089990e-01 8.22296500e-01
-8.68809223e-02 6.03563249e-01 -5.52146100e-02 -6.59121759e-03
1.39601827e-01 3.44010949e-01 3.26308161e-02 8.59642923e-01
4.08758581e-01 -6.15286827e-01 1.95063680e-01 9.03081894e-01
1.28097653e-01 -4.46019173e-01 -2.39689603e-01 -2.96536744e-01
1.69111833e-01 1.37392175e+00 -1.12282288e+00 7.54171759e-02
-4.49048370e-01 9.30805743e-01 2.93511339e-02 -2.17423871e-01
-8.35301220e-01 -6.43793583e-01 1.09155953e+00 3.88315797e-01
5.86354494e-01 -4.17862415e-01 -5.52418053e-01 -2.28136316e-01
5.40430769e-02 -1.00838995e+00 -1.47151425e-01 -5.37970901e-01
-1.04356301e+00 5.29297233e-01 -5.55203080e-01 -1.09070277e+00
2.49140084e-01 -1.43769372e+00 -6.26053274e-01 6.22190595e-01
-1.06528151e+00 -1.01494825e+00 -4.74872589e-01 9.95706916e-02
7.53354669e-01 -3.20852578e-01 6.61341131e-01 4.93097693e-01
-8.46026242e-01 6.74989879e-01 -2.42919445e-01 1.26249343e-01
1.58655584e-01 -1.18999708e+00 8.03651810e-01 8.28753769e-01
-5.40149212e-01 3.99591267e-01 6.83012605e-01 -9.45252240e-01
-1.98265386e+00 -1.30035567e+00 -9.68486145e-02 -4.86850925e-02
6.34472907e-01 -5.39971828e-01 -6.69425964e-01 3.34571421e-01
7.47243613e-02 2.37564206e-01 3.78863901e-01 -5.47279650e-03
1.66566223e-02 -1.70191690e-01 -1.29856014e+00 3.22623372e-01
7.08609700e-01 -3.92783850e-01 1.21495068e-01 3.03237736e-01
7.57397234e-01 -4.36461866e-01 -1.32003880e+00 5.10804355e-01
3.02681416e-01 -1.05879319e+00 7.95235872e-01 -4.68999930e-02
7.02670038e-01 -2.97930479e-01 6.28327858e-03 -1.07547045e+00
-3.60834628e-01 -3.44160229e-01 -1.01299249e-01 1.06750858e+00
3.97470474e-01 -3.85986596e-01 1.05382335e+00 2.83385754e-01
-7.55064547e-01 -1.16425490e+00 -8.61205697e-01 -8.34503651e-01
-2.63665140e-01 -7.04346478e-01 5.67744911e-01 3.20539564e-01
-1.92946240e-01 2.09366232e-01 -6.30990043e-02 3.91637504e-01
3.32930326e-01 -2.77137548e-01 4.45560247e-01 -1.17662621e+00
-3.58325362e-01 -1.03882998e-01 -9.79406416e-01 -5.20700634e-01
-4.07907635e-01 -4.63533401e-01 -2.92873997e-02 -1.40485108e+00
-4.15321171e-01 -4.59264010e-01 -1.45119101e-01 5.51144540e-01
4.22144890e-01 3.16549689e-01 -2.57025570e-01 -4.15969044e-01
-3.77888888e-01 3.14460218e-01 1.19700897e+00 -4.46977854e-01
1.68708444e-01 -1.78009346e-01 -4.24942732e-01 5.19111514e-01
6.84576213e-01 -9.11724344e-02 -4.62993681e-01 -5.18106997e-01
5.52502096e-01 -9.57057774e-02 4.99692917e-01 -1.66475999e+00
3.27415541e-02 4.99559820e-01 6.97283864e-01 -5.82087696e-01
2.62610376e-01 -8.80126774e-01 1.06722347e-01 8.65682185e-01
3.80875200e-01 3.61958355e-01 5.10719538e-01 2.86017954e-01
-7.15005547e-02 -6.60158768e-02 7.39982486e-01 -1.83612213e-01
-8.78213882e-01 1.46698207e-01 -4.80108529e-01 -4.77763712e-01
1.12638712e+00 -4.30442631e-01 -2.81976968e-01 3.68932277e-01
-3.93211156e-01 2.53059026e-02 5.89839399e-01 3.70062679e-01
9.95647669e-01 -1.11252093e+00 -2.19905034e-01 6.44603968e-01
1.52079910e-01 7.53979757e-02 5.45089960e-01 4.33391154e-01
-1.17501438e+00 2.25052834e-01 -4.45096254e-01 -7.67710924e-01
-1.16560590e+00 6.87367916e-01 2.84412593e-01 -4.87285554e-02
-7.52792239e-01 9.15751696e-01 -1.18857376e-01 -1.97545126e-01
-5.49958237e-02 -7.27354705e-01 2.30895802e-01 -3.89853507e-01
4.87718135e-01 8.07076156e-01 9.05566454e-01 6.32012710e-02
-3.88310969e-01 3.39097053e-01 -3.12177092e-01 6.00386858e-01
1.30344176e+00 2.40236089e-01 -8.81910026e-02 1.15346842e-01
1.28275335e+00 -5.03760815e-01 -1.25731075e+00 4.13311929e-01
9.32627171e-02 -2.93779701e-01 6.83973849e-01 -1.02061212e+00
-1.61024129e+00 9.00735617e-01 1.22324848e+00 2.50691861e-01
1.10246575e+00 -7.76883066e-02 8.67556393e-01 1.59657419e-01
6.39913976e-01 -1.19655550e+00 4.67406601e-01 1.26721546e-01
7.99378574e-01 -1.38277757e+00 2.46597320e-01 -6.01115584e-01
-4.05428447e-02 1.29220366e+00 9.94850814e-01 -2.16343626e-01
6.68051302e-01 7.15223670e-01 6.99218065e-02 -1.09407949e+00
-6.56482995e-01 3.59815329e-01 1.74664501e-02 7.03796685e-01
3.79391700e-01 1.26441404e-01 3.27983320e-01 2.99589455e-01
-4.07802798e-02 5.43249622e-02 4.51924443e-01 1.49251115e+00
-3.46522629e-01 -7.66218543e-01 -1.97461486e-01 8.37431133e-01
-5.38156629e-01 1.34705976e-01 1.75065637e-01 9.24599886e-01
3.01627040e-01 1.19343519e+00 1.81853414e-01 -7.55963326e-01
5.26487648e-01 -5.77037275e-01 3.03466260e-01 -8.06842387e-01
-7.90165424e-01 -3.06476593e-01 2.42997259e-01 -1.07560587e+00
3.27160835e-01 -3.37131768e-01 -1.21078098e+00 -4.25750256e-01
-2.97803611e-01 -4.28590059e-01 1.02411461e+00 7.90233493e-01
5.39067268e-01 1.40274739e+00 5.80206633e-01 -7.54756451e-01
-4.64320630e-01 -8.77003908e-01 -7.08311141e-01 -7.73293674e-02
2.16447473e-01 -8.00489187e-01 -1.63901195e-01 -2.92182207e-01] | [7.392809867858887, 1.9408339262008667] |
21fc37c5-f865-42a7-ad8c-08f4b85e64af | a-neural-prosody-encoder-for-end-ro-end | 2205.05590 | null | https://arxiv.org/abs/2205.05590v1 | https://arxiv.org/pdf/2205.05590v1.pdf | A neural prosody encoder for end-ro-end dialogue act classification | Dialogue act classification (DAC) is a critical task for spoken language understanding in dialogue systems. Prosodic features such as energy and pitch have been shown to be useful for DAC. Despite their importance, little research has explored neural approaches to integrate prosodic features into end-to-end (E2E) DAC models which infer dialogue acts directly from audio signals. In this work, we propose an E2E neural architecture that takes into account the need for characterizing prosodic phenomena co-occurring at different levels inside an utterance. A novel part of this architecture is a learnable gating mechanism that assesses the importance of prosodic features and selectively retains core information necessary for E2E DAC. Our proposed model improves DAC accuracy by 1.07% absolute across three publicly available benchmark datasets. | ['Maurizio Omologo', 'Athanasios Mouchtaris', 'Nathan Susanj', 'Grant P. Strimel', 'Markus Muller', 'Thanh Tran', 'Martin Radfar', 'Dillon Knox', 'Kai Wei'] | 2022-05-11 | null | null | null | null | ['dialogue-act-classification'] | ['natural-language-processing'] | [ 2.18809824e-02 4.44809109e-01 -3.29863355e-02 -9.36541498e-01
-6.38641357e-01 -6.25288248e-01 6.66409969e-01 1.97255820e-01
-5.11602879e-01 7.15622663e-01 8.48949075e-01 1.29880413e-01
2.79602140e-01 -5.99708498e-01 -5.30571640e-02 -4.88281161e-01
-3.23713645e-02 3.86970580e-01 8.55692849e-02 -6.09218240e-01
2.11318567e-01 1.16550058e-01 -1.07386982e+00 6.32953465e-01
6.77835822e-01 1.05177891e+00 -4.79087830e-02 9.20133293e-01
-5.91019951e-02 5.76907158e-01 -8.89025211e-01 -7.16084912e-02
-1.80046871e-01 -8.22256267e-01 -1.02713740e+00 -2.00556502e-01
-7.66138509e-02 -3.26226771e-01 -9.88926291e-02 7.05157518e-01
7.60596335e-01 3.82208854e-01 6.66195333e-01 -6.91818416e-01
-1.78674519e-01 9.48722959e-01 -7.16025233e-02 3.25029433e-01
4.93015796e-01 2.53732204e-01 1.51068377e+00 -7.48289049e-01
2.60560185e-01 1.36304784e+00 4.27677900e-01 8.46698344e-01
-1.37663722e+00 -2.30351761e-01 8.32979158e-02 1.12909153e-01
-6.23199463e-01 -7.33085513e-01 1.00067759e+00 -2.51117706e-01
1.41122341e+00 3.30002964e-01 6.31961405e-01 1.14744771e+00
2.30944663e-01 1.03141665e+00 1.04868460e+00 -2.40405053e-01
4.32693988e-01 -4.92484309e-02 6.08650029e-01 4.29935098e-01
-7.66241372e-01 2.10569445e-02 -1.05018771e+00 -1.42112389e-01
3.51842165e-01 -7.68067479e-01 -3.14517289e-01 5.18746793e-01
-7.73078024e-01 1.17264819e+00 4.23795223e-01 2.69533128e-01
-4.91636902e-01 -1.24807321e-02 9.34263647e-01 3.04586917e-01
3.77960742e-01 7.59856701e-01 -6.07867599e-01 -7.39340127e-01
-4.69915807e-01 4.01681475e-02 9.03289616e-01 2.70899683e-01
2.50109524e-01 1.67166814e-01 -5.14180779e-01 1.18151391e+00
3.38562012e-01 -8.52834284e-02 6.71993375e-01 -9.88105893e-01
2.09848776e-01 4.99536157e-01 -2.39131734e-01 -5.37578404e-01
-7.83488512e-01 9.93569642e-02 -6.95636332e-01 -9.67221186e-02
2.51836717e-01 -4.61430430e-01 -3.24193299e-01 2.03986335e+00
1.98494434e-01 -1.99078426e-01 1.72292098e-01 1.03808320e+00
1.05468190e+00 8.53391469e-01 3.22684050e-01 -2.14451969e-01
1.52369940e+00 -8.58246624e-01 -9.42382634e-01 -2.13075861e-01
2.40993842e-01 -4.32252318e-01 1.16658866e+00 5.52125990e-01
-1.14281785e+00 -5.36140740e-01 -8.51357102e-01 -2.61338919e-01
-1.91029102e-01 -1.95556483e-03 6.04072273e-01 7.15598166e-01
-8.86953056e-01 2.74530232e-01 -6.13511205e-01 -5.93143813e-02
5.27756661e-02 5.01816928e-01 -2.20242634e-01 7.83604801e-01
-1.59734452e+00 9.13203061e-01 5.54072678e-01 2.52785027e-01
-5.12827158e-01 -5.31436205e-01 -8.32794607e-01 4.02432412e-01
6.21126480e-02 -2.92856574e-01 1.65004742e+00 -7.12616086e-01
-2.43692923e+00 5.40384293e-01 -2.52970397e-01 -7.21061587e-01
5.65299727e-02 -3.51689339e-01 -2.77961046e-02 3.56186569e-01
-5.07308900e-01 1.02956367e+00 5.30062020e-01 -8.61407816e-01
-3.92660141e-01 -1.97354436e-01 -4.34888080e-02 4.59809154e-01
-2.81122565e-01 1.70672968e-01 -4.58796173e-02 -5.17474294e-01
-2.22565711e-01 -6.38228416e-01 7.43717626e-02 -2.91339874e-01
-4.05000895e-01 -6.13903403e-01 6.13680899e-01 -9.41711426e-01
1.26986110e+00 -1.89799166e+00 4.00486320e-01 -1.07838295e-01
1.02146201e-01 3.35691571e-01 2.39004232e-02 4.27031219e-01
4.04139131e-01 3.28599103e-02 -3.08103234e-01 -4.04941887e-01
3.47006500e-01 1.19643100e-01 -4.24894452e-01 4.78149801e-02
6.18190110e-01 9.16214287e-01 -6.46920264e-01 -1.49125576e-01
4.43301558e-01 5.11583686e-01 -8.11072409e-01 5.72596848e-01
-5.11611819e-01 7.67757475e-01 -1.62440956e-01 2.59836257e-01
2.17567146e-01 3.52323174e-01 3.09365302e-01 -1.14458889e-01
-9.11291465e-02 1.09588146e+00 -5.41515589e-01 1.55139077e+00
-5.67821920e-01 7.77597010e-01 4.78670537e-01 -9.67652380e-01
1.04293108e+00 6.03252172e-01 2.96880841e-01 -7.06170917e-01
4.87385303e-01 -3.97569872e-02 3.14804137e-01 -2.85736740e-01
5.91516793e-01 -2.35078841e-01 -6.01885200e-01 4.15100187e-01
4.00828630e-01 -4.05067891e-01 -7.35565126e-02 -2.93455780e-01
9.28788841e-01 -1.64735481e-01 6.55358016e-01 -1.75374404e-01
7.65032113e-01 -4.02624398e-01 6.55839682e-01 3.96907598e-01
-5.34611166e-01 4.72864419e-01 6.68889344e-01 -3.22804928e-01
-5.69246590e-01 -8.09746623e-01 -1.42429233e-01 1.51915991e+00
-3.29723209e-01 -3.38103890e-01 -8.04158449e-01 -5.47728777e-01
-2.99690604e-01 9.90443468e-01 -5.79455733e-01 -4.28297371e-01
-8.27552378e-01 -6.51008844e-01 9.20870900e-01 5.38787365e-01
6.95636809e-01 -1.53796530e+00 -8.12136650e-01 6.17117822e-01
-3.94166231e-01 -1.00698829e+00 -5.25687099e-01 7.34348714e-01
-5.42834997e-01 -6.89828575e-01 -1.99079216e-01 -6.39329910e-01
-1.10437032e-02 -3.52025956e-01 1.04525542e+00 -4.48947757e-01
-1.49092689e-01 1.34561822e-01 -4.11999762e-01 -2.95585245e-01
-7.70796418e-01 2.20857695e-01 -8.32764283e-02 -1.09620253e-02
4.92177635e-01 -4.34345692e-01 -4.03083861e-01 3.15507442e-01
-5.29506743e-01 -6.52646646e-02 1.76873341e-01 1.16248012e+00
2.16290981e-01 -3.80217612e-01 1.06738555e+00 -8.04160297e-01
1.22994494e+00 -4.31682348e-01 -2.80599564e-01 -7.50054047e-02
-1.65156573e-01 2.53041655e-01 7.96004534e-01 -1.40319079e-01
-1.41833150e+00 3.49822678e-02 -8.01274836e-01 1.82669237e-01
-5.07742047e-01 7.05163479e-01 -3.17766577e-01 4.08046067e-01
3.72383505e-01 8.11446309e-02 8.92193317e-02 -3.67349207e-01
3.47542018e-01 1.02501369e+00 5.37338376e-01 -5.59828639e-01
-1.70731232e-01 -7.44111165e-02 -3.89787167e-01 -1.17039454e+00
-8.46117973e-01 -5.41121721e-01 -8.18184018e-01 -2.03266174e-01
1.16658902e+00 -5.98106802e-01 -1.11032355e+00 5.29143870e-01
-1.20534313e+00 -5.04091501e-01 -9.40951034e-02 2.78987437e-01
-7.45884180e-01 2.60358393e-01 -9.87230778e-01 -1.02985239e+00
-7.25664616e-01 -9.06756103e-01 9.54652667e-01 4.07579869e-01
-8.29475522e-01 -1.04650557e+00 2.23658532e-01 5.57520926e-01
3.84279460e-01 6.69444501e-02 9.10438418e-01 -9.84925687e-01
1.13573864e-01 8.53991583e-02 2.36769572e-01 4.97457325e-01
1.88638136e-01 -7.72262439e-02 -1.54896712e+00 6.46828711e-02
3.54479045e-01 -7.86059380e-01 9.83481050e-01 5.31513095e-01
9.10831392e-01 -3.52452874e-01 3.32190663e-01 8.93187746e-02
6.40412211e-01 4.21889871e-01 4.23363179e-01 -2.24271879e-01
1.64698303e-01 8.47020507e-01 6.31366670e-01 6.29013598e-01
3.49400342e-01 8.64429832e-01 2.64734060e-01 2.25932851e-01
-2.86056492e-02 -4.29505669e-02 7.02926755e-01 1.20466828e+00
3.93149048e-01 -2.28264838e-01 -9.16051686e-01 4.55320328e-01
-1.75008833e+00 -9.29678082e-01 1.04186416e-01 1.74926066e+00
1.35710287e+00 4.61955577e-01 2.51363397e-01 1.64753646e-01
4.44971502e-01 3.36418778e-01 -5.37865818e-01 -1.16267228e+00
-1.09354936e-01 4.87417102e-01 -3.22485030e-01 7.32980013e-01
-1.26593566e+00 8.92747939e-01 6.10283136e+00 4.70928937e-01
-1.09512353e+00 -5.52377775e-02 6.68692529e-01 1.17673010e-01
-1.08133759e-02 -4.58683848e-01 -8.03163469e-01 3.05630594e-01
1.34489810e+00 5.22738788e-03 2.67003775e-01 5.48899114e-01
5.25607526e-01 -2.18598127e-01 -1.27996588e+00 4.92204309e-01
-9.32734981e-02 -1.01048923e+00 -2.11895406e-01 -2.08421603e-01
2.93904364e-01 -1.45627126e-01 6.44065216e-02 5.16446710e-01
2.52879113e-01 -1.18829274e+00 4.50009823e-01 3.80759209e-01
4.14575249e-01 -6.64337039e-01 8.29331458e-01 3.98886561e-01
-1.04832613e+00 -8.45095664e-02 -1.13896534e-01 -1.86302766e-01
4.26768810e-01 1.72741309e-01 -1.37783885e+00 1.12716325e-01
2.04317376e-01 5.22906244e-01 -1.61331072e-01 7.63508677e-01
-4.85693336e-01 1.13340318e+00 -3.41462821e-01 -2.86488712e-01
3.28522712e-01 -1.18364543e-01 6.37885332e-01 1.51026297e+00
-1.86503723e-01 2.89294958e-01 -4.51199003e-02 8.85273099e-01
-1.22587539e-01 -3.47754620e-02 -2.43026629e-01 -1.91100195e-01
5.38233876e-01 9.35281634e-01 -4.95807886e-01 1.54999107e-01
-2.36110643e-01 9.04808521e-01 3.15078527e-01 -1.25498638e-01
-6.22869611e-01 -1.74310282e-01 9.26714838e-01 -6.20693326e-01
2.87298977e-01 -2.23886594e-01 -3.86846393e-01 -7.09893167e-01
-1.70146376e-01 -7.88460493e-01 3.45087260e-01 -3.68086278e-01
-1.28016901e+00 6.54809237e-01 -2.16915384e-01 -6.44982457e-01
-6.73160315e-01 -6.44121468e-01 -9.22481477e-01 8.78293931e-01
-1.26649094e+00 -9.69205797e-01 -9.29069817e-02 1.97623566e-01
1.28559673e+00 -1.09997034e-01 1.31784260e+00 -8.33447576e-02
-5.70349157e-01 5.08460939e-01 -1.14609435e-01 3.47243279e-01
5.86555839e-01 -1.59347677e+00 4.83465016e-01 3.27647746e-01
9.75837559e-02 3.60109806e-01 6.48528337e-01 -2.19064742e-01
-8.06744337e-01 -7.87093937e-01 9.11978066e-01 -1.82689279e-01
4.06598747e-01 -5.47156572e-01 -1.04547095e+00 2.56099045e-01
5.99271059e-01 -4.99125898e-01 1.01673615e+00 3.18201184e-01
-2.48022631e-01 1.17554180e-01 -1.04947472e+00 3.73787761e-01
4.43368793e-01 -8.62705648e-01 -1.01283681e+00 -3.10599178e-01
6.90606654e-01 -2.77732909e-01 -9.27137494e-01 2.33966976e-01
3.75275195e-01 -1.09422290e+00 6.40552759e-01 -5.08319974e-01
3.22509348e-01 2.16488674e-01 -4.20578718e-02 -1.59546471e+00
1.20991647e-01 -7.94945300e-01 -1.75167650e-01 1.15891278e+00
3.57877553e-01 -3.59948665e-01 4.60681260e-01 7.28634000e-01
-4.45715457e-01 -6.96982324e-01 -1.24629998e+00 -1.95129722e-01
3.12369645e-01 -2.47620106e-01 1.88465133e-01 7.99402595e-01
6.50245249e-01 9.52819109e-01 -3.87554258e-01 -2.43359163e-01
-5.12451530e-02 -1.04100361e-01 3.56011361e-01 -1.36654532e+00
-3.16737115e-01 -8.90433788e-01 -8.33132565e-02 -1.38217282e+00
4.64915872e-01 -7.29230523e-01 4.14037943e-01 -1.30844831e+00
-1.42028213e-01 -1.30356014e-01 -1.94069177e-01 5.34621596e-01
-3.08145255e-01 -1.65613189e-01 1.15956791e-01 -1.66408911e-01
-3.52699429e-01 1.15655124e+00 7.03033805e-01 -1.10765658e-01
-5.25923669e-01 1.83298439e-01 -3.59595001e-01 6.66013420e-01
1.20443404e+00 2.94250268e-02 -2.75563538e-01 -1.30935997e-01
-2.19052300e-01 5.09449363e-01 6.79871486e-03 -6.96006715e-01
1.77053273e-01 6.87933564e-02 -4.31972556e-02 -5.02531528e-01
9.23001766e-01 -3.51778001e-01 -5.29877484e-01 3.43106538e-01
-9.71301019e-01 -3.66202801e-01 3.34381461e-01 4.45164084e-01
-6.64264500e-01 -3.16628844e-01 8.16223264e-01 6.77112639e-02
-6.22251749e-01 -4.45658892e-01 -7.75681257e-01 3.97312120e-02
6.73439205e-01 1.02942176e-01 -2.08164960e-01 -5.97931683e-01
-9.07266974e-01 3.08998942e-01 -3.79186332e-01 4.96089190e-01
5.41226149e-01 -9.62982595e-01 -7.65929461e-01 1.21448874e-01
-1.97344571e-01 -8.10962021e-02 3.30947787e-02 6.18239701e-01
-1.64321929e-01 8.33732903e-01 -3.79023850e-01 -4.79825020e-01
-1.51838708e+00 -2.08550096e-01 4.91937816e-01 -2.98535287e-01
-3.80203426e-01 1.12021291e+00 2.62768045e-02 -6.82395756e-01
4.72628295e-01 -4.31792319e-01 -6.14534199e-01 4.68898833e-01
3.10186058e-01 2.16044828e-01 2.20916905e-02 -6.52172446e-01
-1.89329267e-01 -1.05287984e-01 -9.62080806e-02 -3.73271942e-01
1.46753693e+00 -1.82822764e-01 3.04892492e-02 8.89198601e-01
9.38725054e-01 -1.02061361e-01 -1.40100169e+00 -1.95355088e-01
2.56567657e-01 1.43319532e-01 2.03219652e-01 -1.11250222e+00
-6.05012953e-01 1.17995346e+00 2.01582626e-01 3.91842037e-01
1.17913437e+00 -1.61325619e-01 8.92929077e-01 5.81157804e-01
1.46510020e-01 -1.39776886e+00 2.63114244e-01 1.06218469e+00
1.04243982e+00 -1.29981470e+00 -4.80254978e-01 -2.76670456e-01
-1.16965258e+00 1.32933211e+00 7.90318191e-01 -7.99124241e-02
5.90080261e-01 1.68183804e-01 -3.02878022e-03 -1.67509869e-01
-1.12125313e+00 -6.94493875e-02 3.27533036e-01 3.02581578e-01
8.35746288e-01 1.34455219e-01 -4.88800108e-01 1.02029943e+00
-4.28274781e-01 -4.17217702e-01 3.79569620e-01 7.45659173e-01
-5.64624548e-01 -1.09510934e+00 8.02659839e-02 2.81329840e-01
-3.39614511e-01 -7.43725002e-02 -8.98886561e-01 3.95157963e-01
-3.33095789e-01 1.10621738e+00 1.34014353e-01 -3.19518268e-01
2.19711602e-01 6.60264730e-01 4.87810746e-02 -8.66313815e-01
-1.41440499e+00 1.71350583e-01 6.02314532e-01 -3.76045018e-01
-4.44659829e-01 -5.60895860e-01 -1.63399374e+00 7.98298717e-02
-2.20763594e-01 2.57415086e-01 4.85362649e-01 8.78814280e-01
3.26963753e-01 6.79535091e-01 7.53444076e-01 -6.96563721e-01
-7.51403272e-01 -1.26757038e+00 -3.77350897e-01 2.94554532e-01
4.29801792e-01 -4.92515475e-01 -2.34131575e-01 -5.42132743e-03] | [12.94299030303955, 7.681529998779297] |
982a1433-1b94-49f8-8b4c-e2e49ec09216 | local-global-context-aware-transformer-for | 2203.09773 | null | https://arxiv.org/abs/2203.09773v1 | https://arxiv.org/pdf/2203.09773v1.pdf | Local-Global Context Aware Transformer for Language-Guided Video Segmentation | We explore the task of language-guided video segmentation (LVS). Previous algorithms mostly adopt 3D CNNs to learn video representation, struggling to capture long-term context and easily suffering from visual-linguistic misalignment. In light of this, we present Locater (local-global context aware Transformer), which augments the Transformer architecture with a finite memory so as to query the entire video with the language expression in an efficient manner. The memory is designed to involve two components -- one for persistently preserving global video content, and one for dynamically gathering local temporal context and segmentation history. Based on the memorized local-global context and the particular content of each frame, Locater holistically and flexibly comprehends the expression as an adaptive query vector for each frame. The vector is used to query the corresponding frame for mask generation. The memory also allows Locater to process videos with linear time complexity and constant size memory, while Transformer-style self-attention computation scales quadratically with sequence length. To thoroughly examine the visual grounding capability of LVS models, we contribute a new LVS dataset, A2D-S+, which is built upon A2D-S dataset but poses increased challenges in disambiguating among similar objects. Experiments on three LVS datasets and our A2D-S+ show that Locater outperforms previous state-of-the-arts. Further, our Locater based solution achieved the 1st place in the Referring Video Object Segmentation Track of the 3rd Large-scale Video Object Segmentation Challenge. Our code and dataset are available at: https://github.com/leonnnop/Locater | ['Yi Yang', 'Yawei Luo', 'Jiaxu Miao', 'Tianfei Zhou', 'Wenguan Wang', 'Chen Liang'] | 2022-03-18 | null | null | null | null | ['referring-expression-segmentation', 'referring-video-object-segmentation'] | ['computer-vision', 'computer-vision'] | [ 2.40810364e-01 -1.89634785e-01 -5.19239724e-01 -2.34576076e-01
-9.59350705e-01 -8.14896286e-01 1.87752202e-01 -7.58527145e-02
-3.60565335e-01 1.57107204e-01 1.56336784e-01 -3.19833487e-01
4.12894785e-01 -4.06728089e-01 -9.08671737e-01 -4.57910836e-01
7.59482682e-02 2.92590767e-01 4.31177080e-01 2.62219068e-02
2.64760107e-01 3.47812176e-01 -1.51376891e+00 4.59544063e-01
3.84034097e-01 1.22431850e+00 7.49896705e-01 7.48160541e-01
-3.15851390e-01 8.59003544e-01 -4.47714806e-01 -9.99562517e-02
3.82354409e-01 -4.62749690e-01 -1.09431779e+00 3.94294411e-01
9.29396510e-01 -5.25454938e-01 -5.36747873e-01 8.81126642e-01
3.97469819e-01 3.67355406e-01 1.72680110e-01 -1.28886056e+00
-8.56813610e-01 5.68163753e-01 -5.44671297e-01 7.33166456e-01
3.74493659e-01 6.01325095e-01 1.04354465e+00 -1.02038205e+00
9.86378670e-01 1.18750203e+00 3.71685445e-01 6.84839666e-01
-1.01723790e+00 -5.14896274e-01 7.99189627e-01 2.02949926e-01
-1.51958942e+00 -4.70576823e-01 7.37365723e-01 -4.63076860e-01
1.19008672e+00 1.93047181e-01 9.35696959e-01 1.06219625e+00
-1.66928202e-01 1.26024997e+00 6.88434243e-01 -1.18641287e-01
1.84684336e-01 -4.32010174e-01 1.65299088e-01 9.19207871e-01
-2.45716974e-01 -1.70760557e-01 -7.85095870e-01 2.68812180e-01
9.03326273e-01 -1.16965793e-01 -4.41147447e-01 -2.54708409e-01
-1.26312995e+00 5.35687208e-01 3.28498363e-01 3.46298456e-01
-1.74918920e-01 5.42208254e-01 4.70001400e-01 1.92098156e-01
4.65018451e-01 2.34709904e-01 -6.63295150e-01 -2.34359428e-01
-1.28783739e+00 2.82324255e-01 4.42063421e-01 1.31786406e+00
7.84480095e-01 1.84601530e-01 -6.05214655e-01 5.20541966e-01
1.54740244e-01 4.53106344e-01 4.17194158e-01 -1.42641079e+00
4.42109406e-01 4.70964789e-01 -1.49882659e-01 -9.19568419e-01
-9.85316187e-02 -1.96921110e-01 -5.20556390e-01 -1.87814966e-01
1.57521427e-01 5.60282543e-02 -1.19442105e+00 2.03529215e+00
3.00082594e-01 6.27374530e-01 -1.86793193e-01 1.08747852e+00
9.57724869e-01 7.89994657e-01 2.84334749e-01 -1.60794750e-01
1.47996724e+00 -1.30023789e+00 -6.32116497e-01 -4.49963897e-01
5.05042374e-01 -5.33812106e-01 1.22931838e+00 9.42087825e-03
-1.38012075e+00 -7.63318121e-01 -8.94526482e-01 -5.32463849e-01
-1.63717583e-01 1.31495828e-02 3.91058743e-01 1.32939875e-01
-1.58495116e+00 3.35142314e-01 -8.65867674e-01 -2.56641775e-01
7.00552940e-01 1.35389283e-01 -2.53326148e-01 2.15495192e-03
-9.73223627e-01 4.07582581e-01 4.34935093e-01 1.39099002e-01
-1.18116927e+00 -8.80978465e-01 -1.04788899e+00 -2.02942733e-02
8.33152652e-01 -8.05149257e-01 1.28834772e+00 -1.17627525e+00
-1.21321154e+00 1.18590569e+00 -4.92705852e-01 -5.05546689e-01
3.74509901e-01 -2.42760658e-01 -1.01179764e-01 5.72802126e-01
3.71282667e-01 1.22586393e+00 1.03009534e+00 -1.09642446e+00
-6.14292204e-01 -2.01477617e-01 1.42398492e-01 3.65045726e-01
7.31104910e-02 5.29427500e-03 -1.40512967e+00 -1.03931427e+00
4.18703258e-02 -8.39298069e-01 -1.29919469e-01 1.47533715e-01
-3.15564007e-01 -2.51974374e-01 1.05643165e+00 -6.35374904e-01
1.31838369e+00 -2.30494547e+00 3.83617699e-01 -1.94551982e-02
4.16295350e-01 2.61453331e-01 -3.71901244e-01 1.50198657e-02
-8.49860385e-02 4.20065433e-01 -2.91834146e-01 -6.59054637e-01
-1.45961091e-01 2.87008375e-01 -4.53799993e-01 2.27662191e-01
4.54670370e-01 1.41564548e+00 -9.96382654e-01 -8.13264728e-01
5.13081625e-02 3.22393924e-01 -6.16121829e-01 4.04782265e-01
-6.45511329e-01 2.90702134e-01 -3.82199019e-01 9.17674243e-01
3.48354876e-01 -6.11495852e-01 1.91173673e-01 -5.01260757e-01
3.10277380e-02 9.73294824e-02 -8.79007578e-01 2.20805168e+00
-6.48274571e-02 9.45949197e-01 1.26825571e-01 -9.04414892e-01
5.68358541e-01 1.65815517e-01 5.74136317e-01 -8.21882606e-01
9.37673673e-02 3.63486409e-02 -6.52110696e-01 -6.66286826e-01
6.42280817e-01 4.23035651e-01 -3.03894952e-02 3.51301551e-01
2.64960259e-01 5.01595773e-02 4.01017785e-01 5.80978394e-01
8.31954479e-01 4.71067905e-01 -3.24870609e-02 -2.13765383e-01
4.90616292e-01 -4.57333736e-02 7.17961788e-01 7.09906697e-01
-4.90351558e-01 6.25969529e-01 5.12557268e-01 -5.65163851e-01
-8.25656176e-01 -1.03763723e+00 4.06302720e-01 1.29326248e+00
5.74530602e-01 -6.74294770e-01 -8.72996509e-01 -6.93156123e-01
-1.77999318e-01 6.02597415e-01 -6.99047267e-01 -2.33602943e-03
-9.23722684e-01 -9.41002741e-02 5.36522031e-01 8.42098713e-01
5.85632324e-01 -1.22192478e+00 -8.97833407e-01 8.26223269e-02
-5.56532621e-01 -1.32134950e+00 -1.18554485e+00 3.39377858e-02
-6.60861194e-01 -1.04874492e+00 -5.51032186e-01 -1.05821598e+00
5.20686746e-01 5.00041902e-01 1.49644172e+00 4.26093370e-01
-3.40113044e-01 8.32339704e-01 -3.50884080e-01 1.66158557e-01
-2.30798259e-01 -1.38990805e-02 -2.97344863e-01 -6.24974705e-02
2.29550034e-01 -4.05440569e-01 -8.01931798e-01 2.08761409e-01
-9.65830624e-01 2.89058089e-01 3.40004086e-01 5.66542923e-01
1.17625868e+00 -3.47236246e-01 2.44275555e-01 -6.06936276e-01
1.76557571e-01 -5.03596425e-01 -6.73476636e-01 3.45688254e-01
-2.94877648e-01 -2.45921239e-02 1.20335989e-01 -5.16602278e-01
-7.02762067e-01 1.45246714e-01 1.67452283e-02 -1.08000612e+00
-1.62125379e-01 2.91740209e-01 -1.74284279e-01 1.45757943e-01
9.50269550e-02 4.27194446e-01 -1.07253738e-01 -3.99174154e-01
6.58383787e-01 1.90888807e-01 9.31313753e-01 -8.02829742e-01
4.99536812e-01 3.22137296e-01 -2.59203762e-01 -5.81804514e-01
-8.26796293e-01 -4.53087896e-01 -6.38025045e-01 -3.90036047e-01
1.30867934e+00 -1.06281829e+00 -6.42185926e-01 4.91428316e-01
-1.26566803e+00 -8.71869504e-01 -4.65785652e-01 -1.23669393e-01
-7.71009922e-01 3.25526595e-01 -6.82329237e-01 -5.37304223e-01
-3.33277375e-01 -1.40232718e+00 1.38482308e+00 1.05501816e-01
-2.16932088e-01 -8.67140293e-01 -3.07946295e-01 5.04523098e-01
2.80227751e-01 2.94380546e-01 8.31253171e-01 -4.07106936e-01
-1.10868704e+00 4.44564372e-01 -2.63689548e-01 1.39137983e-01
-9.95731950e-02 -8.79947394e-02 -7.48156071e-01 -3.59763920e-01
-1.24627016e-01 -3.79385233e-01 9.73057508e-01 3.52569252e-01
1.50867867e+00 -3.51843715e-01 -2.66516238e-01 9.15028870e-01
1.36277997e+00 2.03924581e-01 5.23066282e-01 2.03863382e-01
9.28556740e-01 2.79396415e-01 7.22196877e-01 1.28108189e-01
5.87325513e-01 7.30082333e-01 4.30870503e-01 -1.03925683e-01
-5.80925763e-01 -4.11900997e-01 4.55046713e-01 7.59397984e-01
1.76511079e-01 -4.83158171e-01 -8.56033862e-01 8.13959420e-01
-1.95948386e+00 -1.04338348e+00 2.96324402e-01 1.76763153e+00
8.60529363e-01 -4.16607186e-02 1.13104217e-01 -3.49043578e-01
6.35821223e-01 5.77059567e-01 -7.89059818e-01 -6.61931485e-02
-3.28330189e-01 -1.45044811e-02 3.93215030e-01 6.01677775e-01
-1.17663538e+00 1.39170814e+00 5.85288048e+00 9.96769845e-01
-1.31993866e+00 2.31120989e-01 9.50626016e-01 -3.91367793e-01
-3.56163651e-01 2.95183919e-02 -6.90569997e-01 4.62666363e-01
6.50848150e-01 9.80860218e-02 4.95219797e-01 6.40166283e-01
1.27272427e-01 -1.14827491e-01 -1.23881257e+00 1.29034626e+00
2.77077526e-01 -1.71839964e+00 3.41621220e-01 -3.01479191e-01
6.84342086e-01 1.81206614e-01 2.52390563e-01 1.10629641e-01
-2.14171916e-01 -9.23564851e-01 1.27381098e+00 3.79322737e-01
9.94302809e-01 -4.68420535e-01 2.40525380e-01 -9.77139920e-02
-1.57947099e+00 1.92302521e-02 9.21235532e-02 3.06099743e-01
4.69103247e-01 5.35248071e-02 -5.31812966e-01 3.07243347e-01
1.04791236e+00 9.31543052e-01 -7.29674101e-01 4.59032774e-01
2.89686900e-02 5.74696124e-01 -2.50031143e-01 3.01981270e-01
5.28496027e-01 -3.05151492e-02 6.64070249e-01 1.40040183e+00
1.90425083e-01 2.68156171e-01 4.90378827e-01 1.03518176e+00
-2.64619589e-01 -9.62419659e-02 -3.89345258e-01 -2.45362282e-01
6.23151362e-01 1.00717449e+00 -1.02423930e+00 -7.40947545e-01
-3.68897468e-01 1.30185187e+00 2.80692250e-01 6.92153811e-01
-9.89714682e-01 4.83906046e-02 8.23973000e-01 1.81192651e-01
8.19045186e-01 -4.41701710e-01 -9.00729671e-02 -1.20081556e+00
1.45118490e-01 -9.89274859e-01 4.07054305e-01 -1.05789995e+00
-9.33895230e-01 7.00421572e-01 1.90330483e-02 -9.39556956e-01
-1.88833103e-01 -4.12647843e-01 -2.57748336e-01 5.19801736e-01
-1.38154960e+00 -1.34165740e+00 -3.18244368e-01 9.06885922e-01
1.03640079e+00 -4.50827628e-02 4.42542315e-01 2.88260072e-01
-5.77567160e-01 5.72037041e-01 -6.22089148e-01 2.92451352e-01
4.96278286e-01 -1.08576310e+00 7.04385161e-01 1.10500467e+00
4.51429099e-01 5.52926898e-01 4.88774896e-01 -7.38145530e-01
-1.53811812e+00 -1.31901765e+00 7.11742401e-01 -5.30920625e-01
5.74163854e-01 -4.49780434e-01 -9.41452920e-01 8.92523110e-01
3.57241809e-01 3.20494443e-01 4.12835836e-01 -5.02578497e-01
-4.83082503e-01 1.00285478e-01 -8.22155952e-01 7.77277231e-01
1.57984459e+00 -8.76841724e-01 -3.73452067e-01 2.39821285e-01
1.35531008e+00 -8.07169437e-01 -6.62217498e-01 1.62559062e-01
2.83267856e-01 -8.15944314e-01 1.06012952e+00 -5.49264073e-01
3.55021626e-01 -6.11676574e-01 -4.55291659e-01 -5.16519964e-01
-1.86733246e-01 -8.73426795e-01 -4.35616046e-01 1.26374102e+00
1.68365583e-01 -1.45890549e-01 6.91988885e-01 7.13913620e-01
-1.81750447e-01 -1.07585549e+00 -8.86866212e-01 -5.98234832e-01
-3.22526902e-01 -7.36852705e-01 5.31787455e-01 7.93540835e-01
-5.86174607e-01 2.16421381e-01 -2.79654115e-01 2.13166550e-01
4.46496040e-01 4.28175539e-01 5.73912680e-01 -4.94357318e-01
-3.76471043e-01 -4.84022915e-01 -4.59184766e-01 -1.72179234e+00
3.61102760e-01 -9.33277905e-01 8.56368393e-02 -1.23454893e+00
1.58495247e-01 -2.00269714e-01 -3.18181574e-01 7.74479985e-01
-3.01266968e-01 4.61297125e-01 6.46433651e-01 2.00122610e-01
-1.16392851e+00 3.40143651e-01 1.16100538e+00 -3.33242536e-01
-3.12161148e-01 -5.20215213e-01 -7.68144131e-01 5.86280704e-01
5.92762172e-01 -2.63658643e-01 -6.73054457e-01 -8.64781141e-01
2.89174821e-02 6.89167827e-02 6.30764484e-01 -6.78122282e-01
3.79683137e-01 -2.20612630e-01 2.45345622e-01 -8.17986488e-01
3.71287912e-01 -5.94831288e-01 7.31104091e-02 1.56251490e-01
-4.45444375e-01 4.76859272e-01 3.37705791e-01 6.62429154e-01
-2.78910786e-01 1.22359395e-01 5.38003981e-01 -2.02818200e-01
-1.45817411e+00 7.49586225e-01 -3.52911770e-01 4.41669077e-01
1.01072109e+00 -2.60875642e-01 -2.23588392e-01 -3.36752146e-01
-6.80836141e-01 5.57363451e-01 6.74916267e-01 6.89990520e-01
8.77703488e-01 -1.27110898e+00 -4.15785253e-01 2.08280027e-01
-9.85385012e-03 3.69914740e-01 5.68107486e-01 6.98077679e-01
-5.47697365e-01 2.85685599e-01 -1.56938359e-02 -8.50212514e-01
-1.12565148e+00 8.33282292e-01 3.32884133e-01 -8.65978003e-03
-7.26522744e-01 1.22749913e+00 4.30740982e-01 2.32586652e-01
2.83129871e-01 -5.28792322e-01 8.78214091e-02 -2.37344820e-02
5.94760358e-01 -2.97940988e-03 -3.58451843e-01 -8.71765316e-01
-4.41595584e-01 8.95351231e-01 -7.01467767e-02 -1.57242656e-01
1.09387624e+00 -5.60784876e-01 -1.54816777e-01 4.23877835e-01
1.39233828e+00 -1.52439654e-01 -1.69982851e+00 -3.07036847e-01
1.39857382e-02 -4.94832635e-01 6.88717440e-02 -6.46210611e-01
-1.52406120e+00 6.49908602e-01 4.84040350e-01 -1.37771472e-01
1.42408061e+00 2.77160883e-01 1.07894266e+00 9.61381719e-02
2.01441661e-01 -1.08149695e+00 4.00005847e-01 4.44875151e-01
8.97699118e-01 -1.06616557e+00 -2.72312254e-01 -2.88833410e-01
-8.44305992e-01 9.66131985e-01 8.48131061e-01 3.22576314e-02
4.40942943e-01 3.42835635e-01 1.92095041e-01 -2.39143893e-01
-8.50388587e-01 -2.04884768e-01 3.95431012e-01 5.83960474e-01
1.53921232e-01 -2.31091112e-01 3.02100807e-01 5.86359501e-01
8.17016065e-02 -3.89582217e-02 8.65076631e-02 9.24896061e-01
-1.76873103e-01 -9.34830248e-01 1.70884915e-02 3.79857384e-02
-3.71427238e-01 -2.23762378e-01 -2.39575759e-01 5.62685192e-01
2.35822096e-01 7.61001587e-01 3.78670275e-01 -2.60517538e-01
5.65527193e-02 1.33357346e-01 3.42687130e-01 -3.48453283e-01
-4.42387134e-01 2.10945398e-01 -2.01189727e-01 -1.30658197e+00
-6.76283777e-01 -6.02193832e-01 -1.50447440e+00 -1.19703822e-01
1.33002624e-01 -2.31357411e-01 3.21470499e-01 8.86917770e-01
6.86583459e-01 5.20713329e-01 1.72644064e-01 -1.08024323e+00
-3.54232565e-02 -2.82102942e-01 -2.13248715e-01 5.71085632e-01
5.62484622e-01 -4.41227347e-01 1.41548431e-02 5.06349206e-01] | [9.531639099121094, 0.4532826542854309] |
757cc530-7f27-487d-93bb-6d6eade4a98d | vulaste-long-sequence-model-with-abstract | 2302.02345 | null | https://arxiv.org/abs/2302.02345v1 | https://arxiv.org/pdf/2302.02345v1.pdf | VuLASTE: Long Sequence Model with Abstract Syntax Tree Embedding for vulnerability Detection | In this paper, we build a model named VuLASTE, which regards vulnerability detection as a special text classification task. To solve the vocabulary explosion problem, VuLASTE uses a byte level BPE algorithm from natural language processing. In VuLASTE, a new AST path embedding is added to represent source code nesting information. We also use a combination of global and dilated window attention from Longformer to extract long sequence semantic from source code. To solve the data imbalance problem, which is a common problem in vulnerability detection datasets, focal loss is used as loss function to make model focus on poorly classified cases during training. To test our model performance on real-world source code, we build a cross-language and multi-repository vulnerability dataset from Github Security Advisory Database. On this dataset, VuLASTE achieved top 50, top 100, top 200, top 500 hits of 29, 51, 86, 228, which are higher than state-of-art researches. | ['Huobin Tan', 'Botong Zhu'] | 2023-02-05 | null | null | null | null | ['vulnerability-detection'] | ['miscellaneous'] | [-4.12772864e-01 -4.81646925e-01 -2.48573929e-01 -1.24840297e-01
-6.53110504e-01 -6.18995249e-01 5.92637844e-02 8.47006798e-01
-3.55012149e-01 2.59258747e-01 4.27260727e-01 -4.95103866e-01
2.24148855e-01 -9.51587439e-01 -5.61904013e-01 -1.60026819e-01
-2.80139707e-02 -1.41088590e-01 5.76040208e-01 -3.99871975e-01
8.71018589e-01 1.04239834e-02 -1.07671618e+00 6.24145746e-01
9.00299788e-01 5.35274267e-01 -1.89600870e-01 4.84554380e-01
-6.37021542e-01 8.09834719e-01 -7.37423480e-01 -7.66920745e-01
2.11702749e-01 1.44825488e-01 -9.07919347e-01 -8.42899978e-01
-2.32112911e-02 -1.15314415e-02 -2.95880139e-01 1.33828700e+00
5.83416402e-01 -3.91067117e-01 5.63444018e-01 -1.36360705e+00
-6.62439823e-01 1.13991582e+00 -1.00160754e+00 6.24207318e-01
4.21342671e-01 -3.74844968e-02 1.11321616e+00 -7.64514744e-01
4.78089809e-01 1.27653003e+00 9.56153810e-01 3.93434584e-01
-7.89336383e-01 -8.48694801e-01 2.23611176e-01 3.34836781e-01
-1.26869607e+00 -1.27525315e-01 7.75732696e-01 -6.49373233e-01
1.39684737e+00 2.87406325e-01 5.68621978e-02 1.10619307e+00
6.31196797e-01 5.03804684e-01 5.85063279e-01 -3.15211922e-01
4.96697165e-02 2.65162736e-01 9.33009744e-01 5.04839897e-01
2.15326846e-01 -1.99763477e-01 -1.12010926e-01 -6.36750817e-01
-1.56102866e-01 7.16809928e-02 -2.77354300e-01 3.74452084e-01
-1.04233968e+00 9.92041469e-01 2.88561672e-01 2.42959619e-01
-1.14564985e-01 -2.10140407e-01 1.21871650e+00 6.06165648e-01
4.81689692e-01 3.65405738e-01 -7.23555744e-01 -3.26441318e-01
-6.28032684e-01 2.32641339e-01 7.35197425e-01 6.41401887e-01
3.69347543e-01 -1.20033391e-01 -3.36719215e-01 8.24900508e-01
5.35696805e-01 3.07233095e-01 7.61001408e-01 1.00564949e-01
1.04002392e+00 1.04556262e+00 -5.02633035e-01 -1.27097023e+00
-3.16337615e-01 -3.17074150e-01 -8.09160888e-01 3.64290662e-02
-1.10431574e-01 -1.75144479e-01 -9.10588980e-01 1.43023694e+00
2.93359190e-01 9.99145955e-02 2.15102717e-01 4.37083274e-01
1.11687458e+00 9.71046150e-01 2.22017825e-01 -1.84926569e-01
1.43428421e+00 -8.07918310e-01 -3.47324342e-01 -1.63367957e-01
9.14610863e-01 -7.99936354e-01 1.28997493e+00 6.43165886e-01
-4.17722583e-01 -2.11067975e-01 -9.64539826e-01 6.43337071e-02
-7.14753509e-01 -2.15769738e-01 3.40629846e-01 7.91743696e-01
-5.67580163e-01 2.68258095e-01 -4.38634932e-01 -2.90462017e-01
3.51113528e-01 -3.15519571e-01 -4.31736141e-01 1.08878285e-01
-1.43283594e+00 6.41441822e-01 8.60274255e-01 -3.79548907e-01
-9.18046594e-01 -1.11217523e+00 -6.28807724e-01 1.30630195e-01
4.96917427e-01 1.36839777e-01 7.23150730e-01 -3.27786595e-01
-9.96830821e-01 6.80485904e-01 6.40640259e-02 -2.18207151e-01
4.68296595e-02 -2.85123527e-01 -6.48074567e-01 -2.21071616e-01
-6.07229024e-02 -1.09818377e-01 5.37038028e-01 -7.39450693e-01
-3.31413001e-01 -2.77638286e-01 1.10928416e-02 -2.16213629e-01
-8.85760307e-01 6.57869697e-01 -2.13994682e-01 -9.18800771e-01
-2.79774249e-01 -5.36491871e-01 -1.30208954e-01 -6.51090264e-01
-7.10042417e-01 -4.84283447e-01 8.56534302e-01 -1.29428184e+00
1.99050331e+00 -2.27995467e+00 5.09025343e-02 3.30688834e-01
3.77273411e-01 4.23656553e-01 -3.91737103e-01 6.79639101e-01
-4.31332469e-01 7.45324910e-01 -4.43885446e-01 8.71478021e-02
-6.40034825e-02 -4.09926504e-01 -8.33709240e-01 1.28171965e-01
7.82579556e-03 5.39100766e-01 -5.78588486e-01 -5.74409544e-01
-4.62064713e-01 6.14757203e-02 -6.04572177e-01 2.98998475e-01
-2.95426905e-01 -2.00017959e-01 -6.26051009e-01 6.87660515e-01
7.98746169e-01 1.08672224e-01 -5.96852720e-01 1.40744865e-01
-1.21809825e-01 2.94065177e-01 -1.02463186e+00 1.70123696e+00
-4.37827319e-01 2.79445589e-01 -3.22094053e-01 -7.80977368e-01
1.11080325e+00 2.57573426e-01 7.99518377e-02 -6.02161944e-01
1.61690205e-01 9.89355743e-02 -1.33846626e-01 -9.23952043e-01
4.02912170e-01 2.98335016e-01 -4.36258465e-01 4.83871937e-01
-2.64617354e-01 2.49249414e-01 1.99995250e-01 5.54164469e-01
1.58041000e+00 -2.59770364e-01 -2.31996011e-02 -4.59053159e-01
8.24278831e-01 1.18260920e-01 8.81133795e-01 4.28081751e-01
-6.73375232e-03 4.60246325e-01 1.19231462e+00 -4.63695765e-01
-1.02834368e+00 -6.37902856e-01 -1.58950850e-01 9.92035508e-01
-5.20618707e-02 -9.80896175e-01 -8.09081733e-01 -1.14269173e+00
-1.33826971e-01 6.41623020e-01 -6.81265712e-01 -4.21366930e-01
-5.66188872e-01 -1.35771966e+00 8.63408267e-01 3.68335009e-01
5.28069437e-01 -1.15025258e+00 -3.87666106e-01 2.36120388e-01
-2.86449134e-01 -7.24122941e-01 -5.37569702e-01 -8.62793475e-02
-5.85694730e-01 -1.10031486e+00 -4.00081813e-01 -5.12880325e-01
2.84068525e-01 -8.92062709e-02 1.07820868e+00 3.79579574e-01
-5.86332738e-01 -3.43316376e-01 -8.91698062e-01 -4.96548027e-01
-4.18432415e-01 4.18404639e-01 -3.61660242e-01 -4.20615375e-01
4.56307411e-01 -3.94781202e-01 -1.82789832e-01 2.87699718e-02
-9.97337401e-01 -3.95701051e-01 3.98513496e-01 7.87713706e-01
2.02174887e-01 2.88883835e-01 6.55572474e-01 -7.62206078e-01
9.10975277e-01 -1.12771153e+00 -6.74671054e-01 5.24760127e-01
-7.54727602e-01 4.39377129e-02 9.64402556e-01 -3.11695069e-01
-1.04333568e+00 -4.86642510e-01 -4.28888530e-01 -1.42023697e-01
1.10511258e-01 1.01692736e+00 -3.78860593e-01 1.34798646e-01
8.16005707e-01 3.59217763e-01 -3.70987177e-01 -7.79238462e-01
9.50476006e-02 1.06886065e+00 2.02789620e-01 -6.03662491e-01
7.90105581e-01 -2.48547077e-01 -3.98647636e-01 -4.83626932e-01
-3.77631873e-01 -3.46144170e-01 -1.49218112e-01 4.59601939e-01
7.94672787e-01 -5.79912901e-01 -4.91047502e-01 7.39925921e-01
-1.34729719e+00 -2.48084627e-02 4.65445966e-01 -1.13232508e-02
3.91255945e-01 7.35096514e-01 -6.80342317e-01 -6.14953935e-01
-9.29701447e-01 -1.25374532e+00 6.99373364e-01 8.42690840e-02
4.89282422e-02 -6.24951839e-01 4.44569767e-01 -1.04505204e-01
3.92680168e-01 3.87934178e-01 1.47480059e+00 -9.29243684e-01
-3.93118747e-02 -3.05427343e-01 -3.21532458e-01 2.33784676e-01
-2.45155141e-01 4.31766033e-01 -8.15790892e-01 -3.98344547e-01
-4.25089709e-02 -3.00522268e-01 9.43306863e-01 -3.20227623e-01
1.50683796e+00 -4.32502329e-01 -4.85844642e-01 7.19338536e-01
1.71989322e+00 3.41797799e-01 9.61262882e-01 6.30824268e-01
8.43512297e-01 5.70226192e-01 4.90009338e-01 4.43168670e-01
3.79504353e-01 4.26930547e-01 6.18485034e-01 4.95765805e-01
2.46569335e-01 -1.93819478e-01 5.19272685e-01 8.08658659e-01
4.40093458e-01 -3.45361441e-01 -1.44877076e+00 5.02670228e-01
-1.47131360e+00 -9.24919486e-01 -5.06181359e-01 2.17662406e+00
1.03357875e+00 4.58310246e-01 1.08288564e-01 2.94557899e-01
6.67175889e-01 1.09174751e-01 -3.29154611e-01 -6.77859783e-01
6.99483207e-04 -9.93611887e-02 3.96284550e-01 1.14213534e-01
-1.17666578e+00 9.75596607e-01 5.25203848e+00 1.26655841e+00
-1.28136826e+00 3.19659531e-01 6.90876007e-01 7.24386722e-02
-4.90657508e-01 1.50606230e-01 -9.14530814e-01 9.38750923e-01
1.18172884e+00 -4.15030688e-01 8.31708834e-02 8.09110403e-01
-2.74717301e-01 7.41258562e-02 -7.12080300e-01 7.80062318e-01
1.66890368e-01 -9.91254449e-01 -1.21459313e-01 -1.83545128e-01
3.38088840e-01 1.41710818e-01 -1.68293454e-02 7.32011735e-01
2.80909747e-01 -1.20091486e+00 5.10663092e-01 2.14910239e-01
4.72229302e-01 -1.00284898e+00 1.12081552e+00 3.49633604e-01
-1.29304445e+00 -5.20100951e-01 -5.88646770e-01 3.99297118e-01
-1.49600714e-01 8.85445237e-01 -3.85053903e-01 9.05725241e-01
9.79465842e-01 6.47853315e-01 -1.04598498e+00 1.28810644e+00
-1.46000832e-01 7.98821330e-01 -2.41633341e-01 -1.08203568e-01
1.48327425e-01 3.63967925e-01 6.64659321e-01 1.47671092e+00
2.09871858e-01 -7.77324811e-02 1.05017781e-01 7.50977039e-01
-7.84224272e-02 5.47905564e-01 -4.66173351e-01 -2.51535536e-03
7.14208543e-01 1.33682787e+00 -5.39371848e-01 -2.69406855e-01
-3.41788828e-01 5.84193051e-01 3.23028088e-01 1.40365558e-02
-1.08346808e+00 -1.25006366e+00 4.24245775e-01 -3.27301651e-01
-1.08840140e-02 2.06385419e-01 -3.25038612e-01 -1.48226416e+00
3.92668217e-01 -1.05061388e+00 6.59747064e-01 -3.97129804e-01
-1.30447388e+00 9.52482581e-01 1.49088219e-01 -1.12214255e+00
3.68430436e-01 -4.04368758e-01 -1.21176493e+00 9.87492979e-01
-1.31124556e+00 -9.99644816e-01 -1.69428885e-01 3.56636196e-01
5.82877219e-01 -6.25336766e-01 6.44002855e-01 6.05799437e-01
-1.15012741e+00 1.19212198e+00 -3.38101536e-02 4.59537655e-01
7.68704712e-01 -1.05361271e+00 8.53922129e-01 1.25388515e+00
-2.83253193e-01 9.12606955e-01 5.16406357e-01 -1.09171104e+00
-1.18302727e+00 -1.22365522e+00 8.02634299e-01 -7.04304814e-01
8.04240108e-01 -4.48154777e-01 -1.53418493e+00 4.87903565e-01
1.97996885e-01 -7.54604489e-02 5.51325679e-01 9.04788077e-02
-9.05300617e-01 -6.81623304e-03 -1.23043966e+00 3.82103324e-01
7.48128653e-01 -2.96358824e-01 -9.09434974e-01 8.04313123e-02
1.14792347e+00 -2.82438010e-01 -9.72011983e-01 2.35277131e-01
1.64759487e-01 -7.26881206e-01 9.12649155e-01 -6.46928966e-01
8.37784052e-01 -7.25172907e-02 6.07147031e-02 -1.30791867e+00
-2.39113897e-01 -2.17331201e-01 1.66658126e-02 1.83378422e+00
6.32746458e-01 -7.74258852e-01 4.80151892e-01 1.94344923e-01
-2.01488033e-01 -7.79171407e-01 -7.49156058e-01 -6.77327514e-01
6.41656578e-01 -2.57637501e-01 1.06404257e+00 1.20022988e+00
2.30374530e-01 8.08385536e-02 -1.44368738e-01 1.49753973e-01
6.62465215e-01 -1.44106463e-01 4.62933153e-01 -1.28976655e+00
-1.70127600e-01 -5.92828572e-01 -3.32098365e-01 -2.09341526e-01
3.88404965e-01 -1.05006564e+00 -1.93712980e-01 -1.10215986e+00
5.57338059e-01 -3.85185122e-01 -4.47147608e-01 8.14656377e-01
-5.70193529e-01 -8.99301320e-02 -7.73521289e-02 1.32571310e-01
-2.76146114e-01 5.01716733e-01 4.18375671e-01 -3.94557655e-01
-1.36330053e-02 -3.41805428e-01 -8.47755075e-01 5.59114337e-01
9.42301035e-01 -8.87203455e-01 -3.03651571e-01 -5.68853021e-01
6.68216169e-01 -3.51076312e-02 1.65168449e-01 -8.39253843e-01
1.71629652e-01 -3.17164391e-01 -4.96344045e-02 -5.84081709e-01
-4.10241216e-01 -3.90243053e-01 -1.77027702e-01 6.66770041e-01
-4.85598564e-01 6.04611278e-01 5.11289179e-01 3.12383056e-01
-1.48582414e-01 -7.15242326e-01 4.86788750e-01 -1.33418992e-01
-8.87765467e-01 4.69537735e-01 -1.01345062e-01 3.95679057e-01
1.06237960e+00 1.25338987e-01 -8.60548794e-01 5.50810635e-01
-6.77762479e-02 4.17876512e-01 2.91377008e-01 8.84365201e-01
7.81125307e-01 -1.14549267e+00 -1.01033819e+00 2.42894083e-01
6.51831210e-01 -1.90049961e-01 4.47012901e-01 5.20069957e-01
-6.32613420e-01 1.78909063e-01 -2.34306619e-01 8.92793108e-03
-1.41569817e+00 7.75624096e-01 -5.82455248e-02 -4.71330523e-01
-8.26326311e-01 9.83194470e-01 -1.11868419e-01 -5.56222498e-01
1.32494196e-01 -7.69024640e-02 -6.35240436e-01 -7.23258927e-02
9.49914634e-01 3.61308128e-01 3.00424457e-01 -2.92013884e-01
-6.17323995e-01 5.91413021e-01 -4.30867463e-01 7.42473602e-02
1.18397021e+00 2.04079017e-01 -6.85642064e-01 1.79202110e-01
1.40351081e+00 2.44348869e-01 -4.98431712e-01 -5.41746058e-02
3.34769934e-01 -4.60974216e-01 1.25176907e-01 -9.02933359e-01
-1.13428915e+00 1.07238102e+00 5.88276565e-01 1.60937145e-01
1.01041961e+00 -3.44994515e-01 1.01396155e+00 2.44431898e-01
3.23305249e-01 -7.42505670e-01 1.01584747e-01 9.43131804e-01
9.47297692e-01 -1.27562273e+00 -2.31152877e-01 -1.50228813e-01
-4.05619264e-01 1.12810469e+00 1.11754680e+00 -2.54290085e-02
7.61908531e-01 4.43213284e-01 -1.46013930e-01 -9.49086025e-02
-9.22832668e-01 5.30353546e-01 4.54086177e-02 2.82243490e-01
4.28154945e-01 -3.43119353e-01 -5.96116066e-01 8.90748799e-01
-1.94525912e-01 -3.30973268e-01 8.03561151e-01 8.69320273e-01
-4.90434855e-01 -1.30300522e+00 -4.20944303e-01 6.47528410e-01
-1.00965416e+00 -6.34622514e-01 -1.38005361e-01 4.04579192e-01
-5.63472435e-02 1.05179548e+00 -2.73589462e-01 -9.11237538e-01
3.44696522e-01 3.18783298e-02 -2.26255506e-01 -6.75160348e-01
-1.02728343e+00 -4.54448789e-01 -1.52575359e-01 -4.32283610e-01
5.72836697e-01 -4.05503720e-01 -1.28996587e+00 -3.95922095e-01
-1.54724792e-01 5.72731316e-01 5.61139107e-01 6.44752622e-01
4.22510326e-01 7.72140801e-01 6.65666223e-01 -6.28732592e-02
-7.40453660e-01 -1.13531351e+00 -2.48073667e-01 3.65543693e-01
1.19957358e-01 -4.48265374e-01 -5.00494659e-01 -1.95148408e-01] | [7.060922145843506, 7.771525859832764] |
278427b3-fe13-40e1-9706-12f0ac1dd135 | pointnu-net-simultaneous-multi-tissue | 2111.01557 | null | https://arxiv.org/abs/2111.01557v2 | https://arxiv.org/pdf/2111.01557v2.pdf | PointNu-Net: Keypoint-assisted Convolutional Neural Network for Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification | Automatic nuclei segmentation and classification play a vital role in digital pathology. However, previous works are mostly built on data with limited diversity and small sizes, making the results questionable or misleading in actual downstream tasks. In this paper, we aim to build a reliable and robust method capable of dealing with data from the 'the clinical wild'. Specifically, we study and design a new method to simultaneously detect, segment, and classify nuclei from Haematoxylin and Eosin (H&E) stained histopathology data, and evaluate our approach using the recent largest dataset: PanNuke. We address the detection and classification of each nuclei as a novel semantic keypoint estimation problem to determine the center point of each nuclei. Next, the corresponding class-agnostic masks for nuclei center points are obtained using dynamic instance segmentation. Meanwhile, we proposed a novel Joint Pyramid Fusion Module (JPFM) to model the cross-scale dependencies, thus enhancing the local feature for better nuclei detection and classification. By decoupling two simultaneous challenging tasks and taking advantage of JPFM, our method can benefit from class-aware detection and class-agnostic segmentation, thus leading to a significant performance boost. We demonstrate the superior performance of our proposed approach for nuclei segmentation and classification across 19 different tissue types, delivering new benchmark results. | ['Amir Hussain', 'Jie Sun', 'Kaizhu Huang', 'Kai Yao'] | 2021-11-01 | null | null | null | null | ['multi-tissue-nucleus-segmentation'] | ['medical'] | [ 4.22892004e-01 -4.19176668e-02 -1.05529264e-01 -1.84647366e-01
-1.14274311e+00 -6.61715209e-01 4.10514563e-01 6.71158552e-01
-7.28094816e-01 5.17525792e-01 -2.12742105e-01 3.34922224e-02
-1.11788407e-01 -7.29384184e-01 -2.15264246e-01 -1.41567373e+00
1.84944883e-01 4.51100081e-01 6.51397109e-01 -3.86588089e-03
3.29403102e-01 7.86779642e-01 -1.32040358e+00 2.65916765e-01
7.57083297e-01 1.02670944e+00 5.27876139e-01 6.48658633e-01
1.65206231e-02 4.98171002e-01 -3.91367018e-01 -1.87133729e-01
-2.96878926e-02 -2.05560982e-01 -8.80086064e-01 2.58004874e-01
1.37375921e-01 4.78900820e-02 7.09486231e-02 1.24880660e+00
6.84280157e-01 -1.96586430e-01 7.46908724e-01 -8.83807182e-01
1.62079558e-02 3.80372792e-01 -8.41541708e-01 4.99178290e-01
-3.01814497e-01 2.68412858e-01 1.03681469e+00 -6.05539203e-01
7.82202244e-01 6.15464926e-01 7.20899224e-01 4.80576158e-01
-1.24704552e+00 -6.18647516e-01 -1.38435513e-01 4.19115722e-01
-1.73644733e+00 -3.35447311e-01 6.14310265e-01 -5.13183951e-01
4.48820978e-01 4.46069837e-01 7.38782763e-01 5.15265167e-01
2.90829577e-02 9.48003054e-01 1.28082669e+00 -1.22428142e-01
2.11629599e-01 4.56859395e-02 1.06949061e-01 5.35322189e-01
7.41740689e-03 -5.90008616e-01 1.94202941e-02 -6.59794174e-03
6.21666133e-01 1.78044051e-01 -4.33322728e-01 -1.89879864e-01
-1.46635854e+00 4.85486031e-01 6.46694958e-01 6.79937005e-01
-3.34763825e-01 -8.32145363e-02 5.16664028e-01 -2.61390030e-01
3.88204813e-01 1.22466706e-01 -2.42927432e-01 1.26033515e-01
-1.07182717e+00 9.45648644e-03 4.75036472e-01 3.90518516e-01
5.79917610e-01 -6.92113876e-01 -4.46384013e-01 7.58338213e-01
1.55340150e-01 2.98566818e-01 6.23407841e-01 -6.25462532e-01
6.33027181e-02 9.11581874e-01 -2.15538904e-01 -1.09595764e+00
-9.96424317e-01 -7.36202121e-01 -1.14234662e+00 -1.58721991e-02
7.06108332e-01 2.79351950e-01 -9.45268393e-01 1.46361303e+00
7.76482224e-01 2.06670389e-01 -1.15624145e-01 9.35429573e-01
7.28409410e-01 4.24112439e-01 1.95862949e-01 -3.06046039e-01
1.71736324e+00 -7.42278337e-01 -5.82921147e-01 1.14344135e-01
1.07957423e+00 -6.02010310e-01 7.38489985e-01 3.70413065e-01
-7.55974889e-01 -2.29731724e-01 -8.70396137e-01 -7.35209286e-02
-4.30808067e-01 4.50042248e-01 5.91144562e-01 2.95609742e-01
-1.03121662e+00 4.13910627e-01 -1.06806910e+00 -2.71986872e-01
7.31997132e-01 5.93926787e-01 -5.83604753e-01 5.97854517e-03
-7.95014083e-01 6.72848761e-01 6.40132010e-01 5.21050274e-01
-3.60664248e-01 -8.44008565e-01 -5.56019068e-01 -1.05347142e-01
3.49081337e-01 -5.26529610e-01 9.91076112e-01 -5.51199377e-01
-1.00660622e+00 1.11806071e+00 -1.36040837e-01 -2.21027896e-01
3.78184229e-01 6.10265374e-01 -3.73952314e-02 5.32245100e-01
1.34418547e-01 8.12931538e-01 4.19266164e-01 -1.06686068e+00
-1.00977540e+00 -6.53980136e-01 -2.44864583e-01 1.69371679e-01
-3.97604823e-01 -3.30977976e-01 -6.44580960e-01 -6.28562272e-01
2.02700406e-01 -7.75925338e-01 -3.92369032e-01 4.44741175e-02
-4.87485856e-01 -1.72603995e-01 7.40142763e-01 -9.05851185e-01
1.14816463e+00 -2.42504525e+00 3.26060355e-01 3.60833734e-01
6.08971119e-01 2.67703593e-01 2.50483990e-01 -1.58655167e-01
2.02584833e-01 9.52283591e-02 -2.39105567e-01 -2.91251898e-01
-6.29893392e-02 9.07591656e-02 3.89706701e-01 8.35986972e-01
2.12160408e-01 9.39924479e-01 -8.61762345e-01 -1.06262708e+00
9.13604051e-02 4.98801082e-01 -5.59749722e-01 -4.75399084e-02
1.12222172e-01 5.28317571e-01 -4.04178143e-01 1.06803823e+00
7.37518847e-01 -5.05117714e-01 3.72691721e-01 -5.57423949e-01
8.08250904e-02 -5.48453808e-01 -1.12023425e+00 1.34642363e+00
-2.04535648e-01 2.95057595e-01 4.49201465e-01 -9.31024551e-01
6.59572363e-01 2.12590039e-01 6.55058980e-01 -6.53337300e-01
3.51219624e-01 5.41272402e-01 1.39408708e-01 -5.59090734e-01
1.65447578e-01 -3.91334534e-01 2.69803796e-02 -4.77139279e-02
-5.21799251e-02 -1.84944928e-01 5.44949412e-01 3.45967598e-02
1.22843778e+00 -3.14937085e-01 4.31251258e-01 -2.07273260e-01
8.16555798e-01 -5.86351492e-02 6.99212432e-01 3.11926126e-01
-5.16275764e-01 7.62901425e-01 7.05013394e-01 -4.67814729e-02
-7.16413319e-01 -7.41282582e-01 -3.26504290e-01 7.04655349e-01
2.48843700e-01 -1.19749345e-01 -8.56783450e-01 -8.99048269e-01
-1.00629047e-01 7.57405683e-02 -8.90184522e-01 8.41147974e-02
-4.17496204e-01 -1.34145260e+00 5.05232453e-01 4.53451425e-01
3.38580251e-01 -8.47672224e-01 -4.29633260e-01 2.32095808e-01
-4.47053105e-01 -1.13089156e+00 -4.25034910e-01 3.21977377e-01
-7.90421069e-01 -1.19425917e+00 -9.93882537e-01 -8.70686293e-01
9.17821169e-01 1.43680021e-01 6.71463490e-01 2.50163317e-01
-6.35174274e-01 -8.07270408e-02 -2.45729148e-01 -9.31100622e-02
-2.48680651e-01 3.24195832e-01 -4.11224842e-01 2.94503570e-01
5.19466102e-02 -4.39188540e-01 -1.00564134e+00 2.93763459e-01
-1.13699341e+00 1.57685548e-01 1.08113050e+00 8.62629950e-01
1.02440608e+00 2.01774418e-01 4.79734689e-01 -1.06362557e+00
1.23814002e-01 -4.30328846e-01 -4.33102489e-01 1.63663268e-01
-2.69913316e-01 -3.30746531e-01 6.40630364e-01 -1.49665207e-01
-7.40731597e-01 2.15588823e-01 -3.77159119e-01 -9.98659655e-02
-9.80857238e-02 4.67505842e-01 -1.53948963e-01 -3.31142545e-01
3.38757217e-01 2.99958676e-01 1.64636314e-01 -2.33084470e-01
-1.53298490e-02 6.15257204e-01 6.08456850e-01 -5.80390096e-02
5.63010097e-01 9.51426744e-01 3.65778983e-01 -6.31106257e-01
-6.93276882e-01 -1.07521677e+00 -7.22046375e-01 -1.60626203e-01
9.21510458e-01 -7.14809299e-01 -8.15729082e-01 7.13193059e-01
-8.06361735e-01 -1.82208717e-01 -2.27926880e-01 2.79774845e-01
-3.80475193e-01 4.98976022e-01 -8.10740888e-01 -3.08885485e-01
-4.37606364e-01 -1.31770515e+00 1.29433978e+00 4.38430965e-01
-8.87523964e-03 -9.90590632e-01 1.31685108e-01 5.90412199e-01
3.17325085e-01 3.80903989e-01 1.03147602e+00 -8.49976182e-01
-4.58855391e-01 -4.27905619e-01 -5.22951245e-01 2.28954747e-01
1.25541419e-01 1.36160403e-01 -9.09398913e-01 -3.16352010e-01
-2.48659462e-01 -3.47809717e-02 9.60917950e-01 3.42133313e-01
1.33487439e+00 3.78234647e-02 -8.05606663e-01 7.59798348e-01
1.50026655e+00 -1.36651933e-01 4.83727276e-01 3.42653513e-01
7.07035005e-01 6.76052213e-01 7.61711299e-01 2.85986006e-01
4.50225830e-01 5.70175350e-01 5.32894135e-01 -5.12993395e-01
-2.55705237e-01 2.54904836e-01 -1.70649737e-01 8.06081831e-01
-1.92586124e-01 -1.70356244e-01 -1.07888103e+00 9.07154918e-01
-1.71419263e+00 -6.05435133e-01 -1.31744966e-01 1.62171793e+00
9.68907237e-01 4.17058207e-02 4.31807712e-05 4.66640592e-01
7.90050328e-01 -1.91718072e-01 -4.03748274e-01 3.25851440e-01
-4.80153896e-02 2.26926923e-01 4.64679748e-01 1.60782814e-01
-1.31017649e+00 5.78490138e-01 5.22697258e+00 1.46648002e+00
-1.24661326e+00 1.41551182e-01 9.16188598e-01 -3.52158807e-02
4.49298993e-02 -3.43263954e-01 -8.57886076e-01 5.22099078e-01
4.72315341e-01 1.43828452e-01 -1.10902488e-01 3.89447004e-01
2.43585289e-01 -2.24019319e-01 -7.79968262e-01 8.57812941e-01
-1.51273087e-01 -1.36184454e+00 -5.79089075e-02 2.29761899e-01
5.49584031e-01 -1.97242811e-01 1.86485797e-02 1.03809208e-01
-3.07369590e-01 -8.56730640e-01 3.38262469e-01 6.20531559e-01
6.37949228e-01 -8.46166134e-01 1.29174733e+00 3.39144170e-01
-1.07139575e+00 -7.35361576e-02 -1.17809691e-01 5.55396259e-01
-2.55068809e-01 7.43016064e-01 -1.07895505e+00 6.72184467e-01
4.40201461e-01 7.43496895e-01 -8.45236242e-01 1.36224186e+00
1.83013320e-01 4.76633042e-01 -3.51147115e-01 -2.37138616e-03
2.81917423e-01 -1.42641487e-02 2.72955954e-01 1.43318474e+00
3.26259196e-01 2.07713813e-01 1.02892540e-01 4.87746269e-01
-1.61073692e-02 4.28395152e-01 1.75016493e-01 -3.97326350e-02
1.41024679e-01 2.07880640e+00 -1.71614730e+00 -1.91528842e-01
-1.55068770e-01 6.72824502e-01 2.85796404e-01 1.10238090e-01
-8.56642425e-01 -4.63501692e-01 2.71699786e-01 2.77875394e-01
3.89283299e-01 8.98192152e-02 -2.26211563e-01 -8.97440553e-01
-1.35243908e-01 -6.68808818e-01 5.43363571e-01 -1.94339514e-01
-1.28816867e+00 3.21633935e-01 -2.78373301e-01 -1.21469259e+00
1.68850943e-01 -6.24063730e-01 -4.91230756e-01 4.99776125e-01
-1.68410361e+00 -1.40994799e+00 -4.05536383e-01 2.83508241e-01
1.70570582e-01 3.20649207e-01 5.41966319e-01 5.12610674e-01
-7.21373439e-01 6.59170270e-01 2.31684819e-01 1.24104530e-01
6.73752189e-01 -1.50035441e+00 -3.19524258e-01 5.70604622e-01
-4.67667639e-01 3.28092635e-01 3.74408603e-01 -4.07401443e-01
-1.19187236e+00 -1.14824462e+00 5.64622343e-01 -2.20634699e-01
6.60006642e-01 -2.65953124e-01 -9.59468603e-01 2.54701674e-01
-2.83497870e-01 3.88663173e-01 8.88287902e-01 -3.55747640e-01
1.99340850e-01 -1.48515016e-01 -1.48076463e+00 5.36443532e-01
6.31878614e-01 -2.54146546e-01 -1.03837878e-01 3.49223167e-01
4.16756511e-01 -4.94630456e-01 -1.11095285e+00 6.07279122e-01
3.62747490e-01 -8.40460837e-01 8.62237215e-01 8.72364640e-02
2.07153916e-01 -5.93025565e-01 9.23294127e-02 -9.19052303e-01
-3.40425849e-01 -4.09283563e-02 1.18256763e-01 1.25183213e+00
2.21785665e-01 -5.17734170e-01 9.87491131e-01 -3.86630222e-02
-3.08247149e-01 -1.15222895e+00 -1.16336870e+00 -1.27935290e-01
-7.76834488e-02 -2.02253118e-01 4.08232629e-01 7.40514696e-01
-9.04154964e-03 -2.80621368e-03 2.24757254e-01 1.87869400e-01
6.09325051e-01 1.30429119e-01 3.89818251e-01 -1.01296329e+00
-2.59078115e-01 -7.33419597e-01 -9.65007424e-01 -5.13791203e-01
-1.37961693e-02 -1.30580747e+00 5.88905662e-02 -1.44349217e+00
6.00195646e-01 -4.73101139e-01 -5.43669164e-01 5.59632182e-01
-4.06813979e-01 9.52128530e-01 6.42262399e-02 2.66569257e-01
-8.25522542e-01 2.47823074e-01 1.56219757e+00 -3.89750302e-01
2.00567365e-01 -5.52331284e-03 -7.94667363e-01 7.70973325e-01
5.52108645e-01 -3.04498851e-01 -1.44674242e-01 1.99774444e-01
1.23045810e-01 -1.30210027e-01 6.66597486e-01 -1.15137935e+00
4.11854178e-01 1.21775046e-02 6.24749780e-01 -6.95348024e-01
1.57076269e-01 -7.00741351e-01 -6.07817173e-02 5.11850238e-01
-1.50868241e-02 -5.82637072e-01 1.92571521e-01 6.67942882e-01
-3.76124382e-01 -1.37229800e-01 9.53144670e-01 -6.29857033e-02
-6.50137603e-01 3.43748122e-01 -3.50660920e-01 -1.78938806e-01
1.37895584e+00 -3.77462268e-01 -3.34681302e-01 3.32210422e-01
-9.86148715e-01 4.78669286e-01 5.22195578e-01 -2.14645132e-01
4.87866759e-01 -1.12861490e+00 -6.25764608e-01 7.34519288e-02
2.56940901e-01 3.80447924e-01 7.73075044e-01 1.47742510e+00
-7.26075411e-01 2.90904045e-01 -5.70437498e-02 -9.80318666e-01
-1.34442484e+00 3.48162413e-01 4.71969366e-01 -7.38701224e-01
-4.49168563e-01 9.46310043e-01 4.07496780e-01 -4.80358601e-01
6.24932088e-02 -5.19507885e-01 -6.15666330e-01 3.90975416e-01
4.76090252e-01 2.36507624e-01 3.82585168e-01 -6.75886750e-01
-4.75587755e-01 6.31226301e-01 -2.73854613e-01 2.98596919e-01
1.21429336e+00 -1.02495342e-01 -3.97274613e-01 3.37356716e-01
1.24550414e+00 -6.20886162e-02 -1.05124629e+00 -1.92159459e-01
7.19136596e-02 -2.63156325e-01 1.65441886e-01 -6.25996828e-01
-1.30285358e+00 7.94629157e-01 7.79490292e-01 1.25136927e-01
1.34524071e+00 1.04832537e-01 9.17069614e-01 -1.28695935e-01
1.28220364e-01 -9.77297664e-01 -2.40355060e-01 1.44507781e-01
2.89408147e-01 -1.19123590e+00 -3.27798724e-03 -6.66164756e-01
-3.68635207e-01 1.12250245e+00 3.43894124e-01 2.84067512e-01
4.98735428e-01 3.90095741e-01 6.58997670e-02 -3.34922194e-01
-6.19576335e-01 -2.69026905e-01 2.26997197e-01 4.52834904e-01
3.14698040e-01 1.52002454e-01 -2.61405885e-01 8.29625607e-01
1.36580557e-01 9.65416133e-02 2.82522917e-01 8.70454192e-01
-4.24832880e-01 -9.42217231e-01 -3.65203679e-01 6.31738245e-01
-6.87986374e-01 1.21583335e-01 -2.35733032e-01 9.03793693e-01
4.29248691e-01 3.45847189e-01 5.48168868e-02 -2.29230106e-01
1.97052404e-01 -2.89791942e-01 4.28504497e-01 -5.02014101e-01
-6.78975284e-01 3.42289329e-01 -3.75238180e-01 -2.30486155e-01
-4.67115223e-01 -6.45085156e-01 -1.67346656e+00 -8.46728235e-02
-3.70136499e-01 9.91813764e-02 4.13838685e-01 9.74254251e-01
8.77717882e-02 7.49121249e-01 6.39490366e-01 -8.24951887e-01
-3.88358295e-01 -7.09765851e-01 -8.67557883e-01 3.81572068e-01
3.18018347e-01 -5.52862406e-01 -4.06091630e-01 1.11452416e-01] | [14.968878746032715, -3.052016258239746] |
e34c359a-bf62-4a46-a5da-cb4adcd54d3f | reproducing-kernel-hilbert-space-mercer-s | 2106.08443 | null | https://arxiv.org/abs/2106.08443v1 | https://arxiv.org/pdf/2106.08443v1.pdf | Reproducing Kernel Hilbert Space, Mercer's Theorem, Eigenfunctions, Nyström Method, and Use of Kernels in Machine Learning: Tutorial and Survey | This is a tutorial and survey paper on kernels, kernel methods, and related fields. We start with reviewing the history of kernels in functional analysis and machine learning. Then, Mercer kernel, Hilbert and Banach spaces, Reproducing Kernel Hilbert Space (RKHS), Mercer's theorem and its proof, frequently used kernels, kernel construction from distance metric, important classes of kernels (including bounded, integrally positive definite, universal, stationary, and characteristic kernels), kernel centering and normalization, and eigenfunctions are explained in detail. Then, we introduce types of use of kernels in machine learning including kernel methods (such as kernel support vector machines), kernel learning by semi-definite programming, Hilbert-Schmidt independence criterion, maximum mean discrepancy, kernel mean embedding, and kernel dimensionality reduction. We also cover rank and factorization of kernel matrix as well as the approximation of eigenfunctions and kernels using the Nystr{\"o}m method. This paper can be useful for various fields of science including machine learning, dimensionality reduction, functional analysis in mathematics, and mathematical physics in quantum mechanics. | ['Mark Crowley', 'Fakhri Karray', 'Ali Ghodsi', 'Benyamin Ghojogh'] | 2021-06-15 | null | null | null | null | ['low-rank-matrix-completion'] | ['methodology'] | [-3.43953788e-01 -3.32318634e-01 -5.23065366e-02 -2.86113620e-01
-2.80307323e-01 -6.48216724e-01 4.11731824e-02 4.32248414e-02
-5.18381000e-01 6.10876203e-01 8.08933452e-02 -3.32237244e-01
-6.87619686e-01 -3.82246524e-01 -7.82746747e-02 -9.81214046e-01
-1.01845407e+00 -2.07818180e-01 1.25134643e-02 -1.42632559e-01
4.62642401e-01 8.85868073e-01 -1.26161265e+00 -2.53984660e-01
1.09992337e+00 9.31312442e-01 -3.32178682e-01 8.34668934e-01
3.17645609e-01 7.53149271e-01 -1.38749227e-01 -1.14666745e-01
8.71162415e-02 -2.01971412e-01 -8.01726520e-01 -2.77867854e-01
-4.73409861e-01 -4.12975699e-02 -8.20230663e-01 1.28876805e+00
3.16138029e-01 7.03078926e-01 1.65885758e+00 -1.35402393e+00
-1.49766350e+00 2.63390034e-01 -3.47528070e-01 1.85535178e-01
1.55035406e-01 -4.88400400e-01 4.39647615e-01 -1.27754092e+00
4.22255788e-03 8.61178339e-01 8.54839265e-01 4.80562031e-01
-1.30339801e+00 -1.19710073e-01 -8.06934536e-01 5.17151594e-01
-1.61760890e+00 -1.35752827e-01 5.45028210e-01 -8.43990684e-01
8.32657874e-01 4.85346407e-01 3.71459812e-01 4.66137916e-01
5.52532494e-01 8.31154287e-01 1.14225209e+00 -6.59935832e-01
4.50497776e-01 5.64675510e-01 7.17438459e-01 9.22403395e-01
1.57624677e-01 2.01507792e-01 6.16008230e-02 -7.22000301e-01
1.00293720e+00 1.24897443e-01 -5.80100000e-01 -8.46881509e-01
-1.55692577e+00 1.24787545e+00 -1.27600163e-01 2.20895380e-01
-2.84080535e-01 -1.38341591e-01 7.52737701e-01 5.27556539e-01
4.72377360e-01 5.76707423e-02 -3.35180759e-01 -3.45998704e-02
-3.45669031e-01 3.35187912e-02 1.16439366e+00 8.38055432e-01
7.74956286e-01 1.97189555e-01 -2.17436016e-01 9.98746812e-01
1.66985169e-01 9.07120168e-01 5.25934756e-01 -7.39079475e-01
-2.16193944e-01 2.35928029e-01 4.09601599e-01 -4.82147008e-01
-6.70741975e-01 3.98101985e-01 -1.04754376e+00 2.83558130e-01
2.24223644e-01 -1.16374873e-01 -2.61203766e-01 1.15099168e+00
2.59015650e-01 2.86110282e-01 4.55480754e-01 9.78612423e-01
4.03033733e-01 6.27970874e-01 -3.93261790e-01 -2.06797451e-01
1.19856250e+00 -8.16915870e-01 -8.76116812e-01 6.43265188e-01
1.20519626e+00 -9.10834312e-01 7.81173825e-01 2.34443694e-01
-5.88010907e-01 -6.86702430e-02 -8.54688704e-01 7.80920088e-02
-7.96611428e-01 5.82521796e-01 1.25873446e+00 9.97941494e-01
-9.49094534e-01 8.90870929e-01 -8.32005441e-01 -4.36304331e-01
-9.60129127e-02 4.19846058e-01 -9.47518766e-01 8.36944655e-02
-1.30367935e+00 1.17606270e+00 5.97076952e-01 -1.08514979e-01
-2.82792360e-01 -7.76170135e-01 -1.38996029e+00 -1.45315051e-01
-5.27550220e-01 -9.81527120e-02 8.02097917e-01 -3.15882325e-01
-1.64506006e+00 7.63508558e-01 -3.05565484e-02 -3.07249159e-01
-3.47665131e-01 -9.82973278e-02 -9.40980971e-01 7.69298673e-02
-7.60988100e-03 -3.42501134e-01 8.38283360e-01 -5.43782003e-02
-1.80006623e-01 -3.82207006e-01 -4.35429126e-01 -1.75038412e-01
-4.05866385e-01 2.06724972e-01 5.86655617e-01 -4.90160137e-01
-2.17998549e-02 -8.52578998e-01 -1.69841900e-01 -3.85467172e-01
-2.13068962e-01 -5.96708417e-01 8.11747909e-01 -7.63505161e-01
1.18538523e+00 -2.67610145e+00 1.18352145e-01 4.79689866e-01
1.43345091e-02 -7.39635015e-03 -6.17481060e-02 8.97064209e-01
-8.27754796e-01 -3.56502146e-01 -1.70498312e-01 3.72834504e-01
2.22467631e-01 -6.24886602e-02 -2.96398789e-01 1.37943804e+00
2.19657589e-02 8.53661776e-01 -8.78064811e-01 -1.77223697e-01
4.58047897e-01 5.58478117e-01 -8.32543522e-03 -3.16375196e-02
9.97217238e-01 -7.64731243e-02 -1.99677765e-01 7.46524632e-01
7.08952606e-01 -2.27864727e-01 -6.23287737e-01 -4.51232105e-01
-4.43827748e-01 -3.27112466e-01 -1.34130466e+00 1.44090009e+00
-2.19204336e-01 7.70269930e-01 -9.88207236e-02 -1.40324605e+00
7.33478725e-01 4.95461553e-01 4.80160117e-01 -1.20571621e-01
-3.77311632e-02 3.87909293e-01 -2.76302785e-01 -6.87316477e-01
2.07242832e-01 1.54971646e-03 1.98040649e-01 7.44903684e-01
2.44309962e-01 3.78610104e-01 2.50817657e-01 1.73300818e-01
1.05589235e+00 -3.99864763e-01 6.43899381e-01 -8.80318582e-01
9.21281040e-01 4.38107149e-04 -1.26027510e-01 2.38789842e-01
-4.58380133e-01 1.38820022e-01 5.14217913e-01 -5.20636797e-01
-1.06953156e+00 -1.45782673e+00 -7.25132763e-01 1.08116460e+00
2.63065677e-02 -1.13845736e-01 -5.38552880e-01 -2.46841967e-01
3.85685563e-01 5.77269614e-01 -1.04540277e+00 -9.03331757e-01
-4.04370390e-02 -1.03108799e+00 7.81436443e-01 6.15093708e-01
2.20829457e-01 -7.53921390e-01 1.98975094e-02 -1.05305925e-01
3.32074463e-01 -5.19821703e-01 -6.95875704e-01 4.69224006e-01
-1.06159949e+00 -1.33243656e+00 -1.01872146e+00 -8.10922742e-01
6.38139188e-01 2.19174683e-01 2.99827307e-01 -8.66131604e-01
-8.96537781e-01 7.85741270e-01 -2.22853974e-01 -8.83507505e-02
-1.97256610e-01 -6.32358015e-01 9.00039852e-01 1.21056311e-01
6.11683667e-01 -3.34174007e-01 -5.90984166e-01 4.12502468e-01
-1.00819314e+00 -8.62001717e-01 6.59687221e-01 1.05407822e+00
2.02650294e-01 2.16484696e-01 3.33818823e-01 -5.62061369e-01
1.13382483e+00 -4.40224588e-01 -4.55342144e-01 4.61969435e-01
-6.90045595e-01 4.14733887e-01 3.74629915e-01 -7.19925344e-01
-6.50298953e-01 -8.66980627e-02 5.98230243e-01 -5.46219409e-01
6.61510602e-02 2.75390834e-01 1.84261009e-01 -6.29664898e-01
1.40908122e+00 7.21569955e-01 5.33321559e-01 -3.63235772e-01
8.34812105e-01 8.04084957e-01 3.58159989e-01 -5.52621067e-01
7.10418761e-01 7.64334381e-01 1.28435001e-01 -1.08345473e+00
-6.17084980e-01 -1.30129004e+00 -9.94542181e-01 2.37195581e-01
8.85022759e-01 -5.92334926e-01 -8.38411212e-01 4.44919765e-01
-8.58636916e-01 -5.24845421e-02 -4.74170297e-01 1.29546618e+00
-1.00514495e+00 7.16215372e-01 -1.06447256e+00 -1.24378324e+00
-3.94463271e-01 -5.77942908e-01 6.46086693e-01 2.42525131e-01
7.82833248e-02 -1.78156972e+00 5.88392973e-01 -2.27381691e-01
4.70341027e-01 3.55292037e-02 1.09959888e+00 -8.82832468e-01
5.35710692e-01 -7.45013833e-01 -5.24019718e-01 9.84514534e-01
3.92876714e-01 -7.52976313e-02 -6.15533233e-01 -2.39943907e-01
7.49444440e-02 -2.42148295e-01 6.27432466e-01 5.00144482e-01
6.11160994e-01 -2.11511374e-01 -2.41276592e-01 6.58764064e-01
1.19645667e+00 8.87474511e-03 6.18803084e-01 4.05987054e-02
4.58923787e-01 5.13934910e-01 3.73211145e-01 4.95453060e-01
4.70985379e-03 -1.00909039e-01 -1.62275448e-01 1.29859403e-01
9.01449680e-01 5.52529991e-01 6.30096376e-01 9.26209867e-01
-4.18594271e-01 9.27289605e-01 -3.88897449e-01 2.60198981e-01
-2.16525126e+00 -1.17011964e+00 -3.44029725e-01 2.82319832e+00
4.40705419e-01 -6.49405062e-01 4.11882162e-01 2.29786515e-01
1.04259992e+00 -4.95948166e-01 -4.03857678e-01 -5.92950642e-01
-2.51512468e-01 2.83725798e-01 1.03534460e+00 3.35156918e-01
-1.56010449e+00 6.80905581e-01 7.46737671e+00 8.86756897e-01
-8.71945262e-01 2.16544166e-01 -1.46646410e-01 4.81249750e-01
2.17807010e-01 7.69199282e-02 -2.58512437e-01 1.70641854e-01
9.53559399e-01 -2.40592256e-01 7.32334137e-01 1.49459898e+00
-3.92921083e-02 -9.24196616e-02 -1.13983846e+00 1.72127855e+00
1.34166693e-02 -1.03320742e+00 -5.36807656e-01 3.75809550e-01
5.54780006e-01 -1.84112899e-02 5.51382937e-02 6.33232653e-01
-5.16027771e-02 -9.78724420e-01 4.50201221e-02 6.93797171e-01
7.18163729e-01 -1.07949793e+00 7.28576779e-01 8.56866241e-02
-1.23508608e+00 8.77090096e-02 -1.13040328e+00 -1.00978449e-01
-3.02065343e-01 1.16050065e+00 -3.68555725e-01 3.47085297e-01
3.14303160e-01 7.59610415e-01 -3.42508823e-01 1.17750776e+00
4.07392740e-01 4.15905148e-01 -2.30701685e-01 -2.71969348e-01
1.05392128e-01 -8.29010427e-01 3.48772287e-01 1.30982709e+00
1.24951050e-01 2.08787993e-01 -9.18477774e-02 8.31603050e-01
8.42573941e-01 6.10975862e-01 -7.39836395e-01 -5.27756393e-01
4.04413752e-02 1.52605271e+00 -6.42237842e-01 -3.20222676e-01
-7.03364968e-01 1.64489102e+00 2.26094902e-01 6.76445007e-01
-8.64790976e-01 -1.28074670e+00 1.04084194e+00 -2.34916508e-01
-2.38851652e-01 -3.79836828e-01 4.46872637e-02 -1.60548282e+00
-2.05233768e-01 2.34716550e-01 4.77904618e-01 -2.46022344e-01
-1.63841891e+00 2.15457231e-02 2.21827000e-01 -1.11092818e+00
-5.87996989e-02 -1.49382985e+00 -8.27345669e-01 1.14764988e+00
-9.21974897e-01 -5.69691718e-01 3.80551696e-01 1.18925059e+00
-3.31386626e-01 -3.39437693e-01 1.09982443e+00 2.39336252e-01
-3.91622245e-01 2.95166165e-01 9.26416159e-01 4.08982158e-01
8.31371129e-01 -1.72532177e+00 1.22099973e-01 1.81197807e-01
-2.11160004e-01 8.22279334e-01 4.03114110e-01 -3.17799419e-01
-1.75908685e+00 -7.51327813e-01 3.95223886e-01 -1.66786119e-01
1.24510801e+00 -1.20953150e-01 -7.35596597e-01 3.72965366e-01
-4.10093695e-01 6.13408566e-01 1.36078739e+00 9.19565409e-02
-7.04412401e-01 2.40879133e-01 -1.18863285e+00 4.69270885e-01
4.32898372e-01 -9.87365663e-01 -2.48448521e-01 9.53220785e-01
2.59795576e-01 1.42136589e-01 -1.31137311e+00 2.25841373e-01
7.66850233e-01 -1.08318603e+00 1.13037419e+00 -1.16627026e+00
-6.81091428e-01 -2.11221173e-01 -2.55025893e-01 -1.18538249e+00
-9.22168016e-01 -5.63655734e-01 -2.85783887e-01 3.84879082e-01
1.98032692e-01 -1.13265634e+00 2.94998258e-01 7.30143249e-01
-9.85116288e-02 -8.52509677e-01 -1.06069970e+00 -1.29241502e+00
1.14125907e-01 -2.33780578e-01 -1.06300406e-01 1.25133169e+00
1.03438592e+00 3.95221375e-02 -3.51068884e-01 1.27928615e-01
9.10093546e-01 1.05474340e-02 4.08680588e-01 -1.36675000e+00
-1.46996543e-01 -4.38175768e-01 -1.21519971e+00 -5.25150776e-01
3.07547271e-01 -9.72218156e-01 -4.07718807e-01 -1.20448697e+00
4.36591767e-02 -9.57534388e-02 -5.36355197e-01 2.52495617e-01
7.84407556e-02 -8.27018544e-02 -6.10537350e-01 2.65306890e-01
-4.12199736e-01 4.36755151e-01 8.72485220e-01 5.78116402e-02
-3.56245637e-01 1.91049829e-01 -5.62379472e-02 7.36308455e-01
7.78623819e-01 -1.69745758e-01 -4.33674008e-01 6.16934776e-01
6.38942048e-02 -1.48518264e-01 3.12250644e-01 -8.50082457e-01
1.20683499e-01 -2.19811246e-01 6.23288095e-01 -1.03009298e-01
2.65500218e-01 -4.65304762e-01 -2.09897116e-01 5.25193453e-01
3.71267684e-02 -1.20734591e-02 -1.89847529e-01 6.45800531e-01
-3.74799431e-03 -6.40165150e-01 1.00383317e+00 9.68114734e-02
-9.15766239e-01 3.44120294e-01 -7.56834567e-01 -3.02840658e-02
1.33643460e+00 -3.83514881e-01 -1.40902922e-01 -7.61362910e-02
-1.19919741e+00 -2.09382027e-01 2.36576334e-01 1.65868431e-01
8.50764513e-01 -1.80511069e+00 -5.32874048e-01 2.33362168e-01
4.88104999e-01 -8.56198251e-01 4.48814005e-01 1.50161040e+00
-5.68342149e-01 6.26489401e-01 1.27827683e-02 -2.18430087e-01
-6.97598696e-01 8.88509393e-01 2.17362225e-01 2.30227247e-01
-4.84256268e-01 6.56881213e-01 4.93801028e-01 -4.98500139e-01
2.24173982e-02 -3.97001028e-01 2.59067193e-02 -3.04013282e-01
9.42536533e-01 1.06006622e+00 -1.78077072e-01 -6.08051240e-01
-5.25273800e-01 4.37471807e-01 1.72047228e-01 -1.52356103e-01
5.89179158e-01 9.70731378e-02 -8.13497663e-01 9.84171629e-01
1.78084648e+00 -1.04181185e-01 -4.17384326e-01 -7.59956166e-02
3.98521125e-02 -5.82201174e-03 -2.85604388e-01 -9.74831358e-02
-3.19758862e-01 6.30883396e-01 6.93797588e-01 4.70633775e-01
7.56450772e-01 1.06295936e-01 6.06176496e-01 7.86542118e-01
1.41604781e-01 -1.26549721e+00 -2.95815200e-01 6.39686644e-01
6.17957771e-01 -1.18461883e+00 -1.70547619e-01 -4.47854072e-01
-5.43716550e-01 1.56543231e+00 8.63084272e-02 -5.23688138e-01
1.68875957e+00 -1.49666285e-02 -9.40050706e-02 -3.98547575e-02
-2.84392804e-01 -3.90426904e-01 7.59743571e-01 9.62022305e-01
6.32980406e-01 4.44976777e-01 -2.21834689e-01 4.28601205e-01
9.56506580e-02 -3.68502170e-01 3.14428508e-01 8.88778985e-01
-7.29697466e-01 -6.84018552e-01 -5.76636851e-01 6.00421369e-01
-2.13974625e-01 -2.61284411e-01 1.90678071e-02 5.46957076e-01
-4.92707193e-01 4.98727351e-01 -2.81462580e-01 -3.14156592e-01
1.41653925e-01 5.45477152e-01 7.33619750e-01 -5.27462304e-01
3.79517734e-01 -2.42387906e-01 -4.29875731e-01 -4.98935848e-01
-1.20828770e-01 -3.51516724e-01 -1.43909109e+00 -3.00342709e-01
-8.35369408e-01 8.37976933e-01 1.01311707e+00 8.11511576e-01
9.89213064e-02 -3.44091713e-01 7.09501922e-01 -6.21045053e-01
-9.92052257e-01 -1.03159392e+00 -1.79069185e+00 1.51025966e-01
1.64854929e-01 -7.53802240e-01 -8.88265967e-01 1.54224634e-01] | [7.5272626876831055, 4.044815540313721] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.