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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ed50646e-6b11-46be-9a0e-59437d846299 | iifl-implicit-interactive-fleet-learning-from | 2306.15228 | null | https://arxiv.org/abs/2306.15228v1 | https://arxiv.org/pdf/2306.15228v1.pdf | IIFL: Implicit Interactive Fleet Learning from Heterogeneous Human Supervisors | Imitation learning has been applied to a range of robotic tasks, but can struggle when (1) robots encounter edge cases that are not represented in the training data (distribution shift) or (2) the human demonstrations are heterogeneous: taking different paths around an obstacle, for instance (multimodality). Interactive fleet learning (IFL) mitigates distribution shift by allowing robots to access remote human teleoperators during task execution and learn from them over time, but is not equipped to handle multimodality. Recent work proposes Implicit Behavior Cloning (IBC), which is able to represent multimodal demonstrations using energy-based models (EBMs). In this work, we propose addressing both multimodality and distribution shift with Implicit Interactive Fleet Learning (IIFL), the first extension of implicit policies to interactive imitation learning (including the single-robot, single-human setting). IIFL quantifies uncertainty using a novel application of Jeffreys divergence to EBMs. While IIFL is more computationally expensive than explicit methods, results suggest that IIFL achieves 4.5x higher return on human effort in simulation experiments and an 80% higher success rate in a physical block pushing task over (Explicit) IFL, IBC, and other baselines when human supervision is heterogeneous. | ['Ken Goldberg', 'Eugen Solowjow', 'Anrui Gu', 'Ryan Hoque', 'Gaurav Datta'] | 2023-06-27 | null | null | null | null | ['imitation-learning'] | ['methodology'] | [ 8.71636420e-02 3.21564257e-01 -2.83716351e-01 2.04880908e-02
-6.20281696e-01 -5.78784585e-01 7.42920220e-01 -1.04900993e-01
-9.22764719e-01 1.08508837e+00 -3.05869879e-04 -3.37724060e-01
-5.15908301e-01 -5.09787165e-02 -1.10117841e+00 -6.09598935e-01
-6.66004062e-01 7.43165433e-01 1.18841209e-01 -3.39396596e-01
1.26361221e-01 4.94341046e-01 -1.40683091e+00 -9.09826830e-02
8.35993290e-01 6.26489758e-01 6.12496972e-01 6.58274174e-01
4.16478187e-01 9.57508028e-01 -6.14958227e-01 1.78112760e-01
6.19170189e-01 -9.13615152e-02 -8.71756017e-01 -1.35506943e-01
1.10742487e-01 -5.56980252e-01 -4.41943377e-01 7.36946344e-01
3.97122175e-01 5.03993094e-01 1.07206845e+00 -2.19450235e+00
-2.37692982e-01 3.18726987e-01 -5.48080862e-01 -2.43526146e-01
4.34272081e-01 7.78333008e-01 5.50258934e-01 -3.53929371e-01
5.96759319e-01 1.83324933e+00 7.85481334e-01 5.84890366e-01
-1.43318796e+00 -3.90763015e-01 1.60641253e-01 6.84215873e-02
-8.68142724e-01 5.15315533e-02 1.13425381e-01 -5.90560377e-01
1.29153252e+00 -2.53803164e-01 3.78787696e-01 1.53882265e+00
5.64900756e-01 9.47426081e-01 1.27461290e+00 -8.91005024e-02
3.57588530e-01 -1.15486853e-01 -2.10026637e-01 6.69145882e-01
1.68152139e-01 5.81728578e-01 -3.07451576e-01 -3.03304791e-01
7.36718476e-01 6.15274720e-02 -2.14915097e-01 -8.97589386e-01
-1.46804416e+00 6.62913203e-01 4.74394500e-01 -1.55606106e-01
-6.28396869e-01 7.08265483e-01 5.88022232e-01 6.84371948e-01
-3.99181694e-01 6.96998000e-01 -4.61630493e-01 -5.05770087e-01
-2.75159925e-01 5.82817733e-01 1.12045836e+00 1.29978251e+00
8.78798425e-01 -4.33358885e-02 -1.62298962e-01 4.40673947e-01
-7.45679671e-03 5.75524211e-01 3.40723991e-01 -1.66334939e+00
6.94872856e-01 2.43034393e-01 6.36411726e-01 -5.03263354e-01
-8.15583587e-01 2.42218092e-01 -4.24921840e-01 9.18118954e-01
4.65015173e-01 -4.10886735e-01 -9.20990229e-01 1.92006791e+00
9.48597267e-02 -1.70352548e-01 2.83223093e-01 1.06917918e+00
2.30459440e-02 5.24087787e-01 2.92737246e-01 2.48419300e-01
9.01972950e-01 -1.19331694e+00 -4.56632942e-01 -2.73331046e-01
8.95848095e-01 -8.79741311e-02 1.26386416e+00 5.10758400e-01
-7.11325467e-01 -4.28938568e-01 -1.10096562e+00 1.12596884e-01
-2.88370132e-01 -8.75730217e-02 2.58685023e-01 2.00261757e-01
-1.08109069e+00 8.12007427e-01 -1.01946843e+00 -5.58571100e-01
1.84709802e-01 6.92439497e-01 -6.08574688e-01 -1.43848732e-01
-9.83591735e-01 1.46332073e+00 4.33642536e-01 -2.78470546e-01
-1.56650126e+00 -5.87512434e-01 -1.08446717e+00 -2.28984892e-01
6.63753927e-01 -7.07667112e-01 1.41475487e+00 -8.29422653e-01
-1.68798566e+00 1.80466563e-01 4.61365581e-01 -7.09556341e-01
9.47975755e-01 -4.57340956e-01 3.19146901e-01 8.91667530e-02
2.75511265e-01 1.17328608e+00 9.21055973e-01 -1.52758479e+00
-4.15204406e-01 2.51812898e-02 3.80223036e-01 5.70662320e-01
2.02271283e-01 -5.93627930e-01 1.93941265e-01 -1.82440266e-01
-5.40729761e-01 -1.56816030e+00 -1.78570986e-01 8.81737396e-02
-1.12896621e-01 -4.49571759e-01 1.08250940e+00 -4.85499293e-01
2.27892995e-01 -2.08663034e+00 7.90351152e-01 -6.84500858e-02
-2.04191819e-01 2.57472601e-02 -4.00101483e-01 7.52050996e-01
4.72474128e-01 -1.30100727e-01 -5.63686311e-01 -6.05230391e-01
7.49505043e-01 9.14340436e-01 -2.09493250e-01 5.19183397e-01
6.84146583e-02 7.97218263e-01 -1.15083730e+00 -5.40036917e-01
1.80517256e-01 2.48166770e-01 -5.22726297e-01 1.08552657e-01
-3.17451507e-01 7.08836615e-01 -2.45967492e-01 4.40069079e-01
3.86540025e-01 1.78822920e-01 3.03020358e-01 2.50154823e-01
-9.65225026e-02 -9.58999395e-02 -9.19729233e-01 1.95940888e+00
-6.81137860e-01 6.06604040e-01 4.70348418e-01 -8.52501988e-01
3.95284295e-01 1.34346396e-01 4.58149940e-01 -5.78184724e-01
1.39976488e-02 3.22462976e-01 8.40025842e-02 -7.28385329e-01
5.79955995e-01 -4.02783081e-02 -4.88586485e-01 3.43559742e-01
2.12284446e-01 -4.38883066e-01 1.03879347e-01 1.59175768e-01
1.52545166e+00 8.14848423e-01 -4.54208180e-02 -3.04720938e-01
-6.79642707e-02 3.81426424e-01 5.22234917e-01 1.03260171e+00
-7.24112511e-01 8.57930407e-02 5.65156221e-01 -1.28440242e-02
-1.14807951e+00 -1.28058219e+00 2.97869891e-01 1.12159944e+00
7.04264283e-01 9.34686363e-02 -5.55784762e-01 -8.59590054e-01
6.25725925e-01 9.51230705e-01 -5.10723591e-01 -3.18732351e-01
-6.79228842e-01 -1.02676645e-01 7.83702016e-01 5.87987781e-01
5.02336681e-01 -1.25832129e+00 -1.34684384e+00 1.51173491e-02
-2.74188966e-01 -1.05037713e+00 -4.18206185e-01 4.93021071e-01
-6.38560891e-01 -1.06599009e+00 -8.08585167e-01 -6.52507901e-01
5.26336789e-01 8.49256366e-02 6.70510292e-01 -3.38535547e-01
-4.73506331e-01 1.27084816e+00 -4.28534359e-01 -1.82038650e-01
-4.62040216e-01 -1.36252210e-01 5.64307153e-01 -6.42589569e-01
-1.00852095e-01 -3.72299105e-01 -5.19420624e-01 4.68226314e-01
-6.81700706e-01 -2.08656341e-01 1.02773225e+00 1.13946557e+00
3.12406570e-01 -4.05277871e-03 5.67010999e-01 -1.56055763e-01
8.18370342e-01 -6.77953064e-01 -4.61235195e-01 3.51465940e-02
-4.05304044e-01 3.97333205e-01 4.10977632e-01 -8.89618874e-01
-1.13164544e+00 7.18261972e-02 5.21768451e-01 -8.55090201e-01
-1.23303741e-01 3.15862924e-01 2.48282537e-01 -4.94461730e-02
5.52790821e-01 5.85060334e-03 4.97247070e-01 -2.59096563e-01
2.48370439e-01 4.85300601e-01 4.23437297e-01 -1.02247930e+00
5.63638210e-01 2.76505649e-01 1.68713778e-01 -6.54472947e-01
4.24560644e-02 -2.70152777e-01 -6.67003393e-01 -2.49591812e-01
9.79478180e-01 -8.14755797e-01 -1.17370927e+00 2.85397738e-01
-1.00842476e+00 -1.40385985e+00 -3.25974256e-01 8.73418450e-01
-1.29047215e+00 4.40943360e-01 -6.55703843e-01 -1.06609738e+00
2.51073569e-01 -1.34888160e+00 1.22077084e+00 1.60659698e-03
-2.98573941e-01 -7.92173922e-01 4.28975746e-02 1.92162059e-02
3.52523059e-01 4.16728973e-01 9.25668240e-01 -4.30414319e-01
-4.29746240e-01 1.61419168e-01 -4.43335436e-02 2.43729144e-01
-1.38443857e-02 -6.06267214e-01 -5.11334062e-01 -7.22794175e-01
-3.05423588e-01 -1.07788408e+00 5.04049540e-01 1.51529193e-01
5.77865183e-01 -2.28078902e-01 -5.24385095e-01 -2.27703229e-02
1.03328907e+00 3.38275760e-01 4.84996498e-01 6.68543994e-01
4.33767289e-01 9.22871590e-01 1.10472178e+00 4.70414400e-01
6.80390894e-01 6.99136078e-01 8.19054484e-01 1.35846883e-01
1.75745696e-01 -3.03119034e-01 1.09724498e+00 1.40712053e-01
4.39333394e-02 -1.38326148e-02 -8.04010928e-01 4.89604235e-01
-2.28427649e+00 -8.68033051e-01 1.53156012e-01 2.19563580e+00
5.36002457e-01 -2.47588754e-02 3.96181673e-01 -3.14666629e-01
4.55417633e-01 -3.30181271e-01 -1.08468664e+00 -5.16371548e-01
2.01437965e-01 -3.48330826e-01 8.38361382e-01 5.26046097e-01
-9.49966133e-01 6.52798533e-01 5.72861671e+00 6.24310970e-01
-6.57404006e-01 1.13862157e-01 -1.03855738e-02 -1.90988645e-01
3.23757797e-01 3.24266553e-02 -3.63806576e-01 3.88394237e-01
7.08048224e-01 1.64976224e-01 7.44176984e-01 1.01107144e+00
8.92742276e-02 -4.46710825e-01 -1.58055139e+00 8.80248547e-01
-1.83194369e-01 -4.59421009e-01 -4.39103901e-01 3.15553129e-01
5.91608822e-01 4.27377164e-01 1.91058621e-01 1.07582116e+00
6.77247405e-01 -1.06986523e+00 9.29211080e-01 5.21813691e-01
5.70000470e-01 -4.82751131e-01 6.96155608e-01 9.21075344e-01
-9.55237269e-01 -4.69976723e-01 -3.12805474e-01 -1.00669868e-01
2.32133567e-01 -5.16026616e-01 -9.33007658e-01 5.77654064e-01
8.97513032e-01 4.09917146e-01 -4.22617309e-02 8.23393524e-01
-2.03527715e-02 -3.12490873e-02 -5.19399405e-01 -1.84567899e-01
7.68246472e-01 -1.16526440e-01 9.22865689e-01 1.18507123e+00
2.73387671e-01 -2.50598013e-01 6.76759005e-01 9.61211920e-01
2.57630587e-01 -5.46177804e-01 -8.77920747e-01 -2.45711729e-02
3.74143571e-01 8.78340542e-01 -2.99393535e-01 -9.67586637e-02
4.60839011e-02 1.35090411e+00 4.19989228e-01 5.35282314e-01
-1.00261271e+00 -5.96534908e-01 6.37230992e-01 -2.17327431e-01
1.62471548e-01 -7.04312384e-01 4.09979701e-01 -7.21108437e-01
3.93648632e-02 -8.28316510e-01 1.35706037e-01 -8.43652189e-01
-1.26981103e+00 1.63062230e-01 5.45904219e-01 -1.37186015e+00
-4.61418271e-01 -9.78920102e-01 -3.31343442e-01 5.95638633e-01
-1.48569512e+00 -7.77709961e-01 -2.20471263e-01 5.96616089e-01
7.29090273e-01 -2.06051301e-02 6.10034347e-01 3.96410748e-03
-1.74982369e-01 3.76502991e-01 8.12184662e-02 -3.41116101e-01
7.35440612e-01 -1.52844274e+00 -1.34850275e-02 1.07243761e-01
-5.38846195e-01 5.11527538e-01 7.82389283e-01 -7.57578671e-01
-1.88126898e+00 -9.18043554e-01 -4.03913334e-02 -4.25264984e-01
6.07328057e-01 -2.65831292e-01 -6.12920105e-01 1.00410140e+00
3.48034263e-01 -2.97713041e-01 6.54944219e-03 -2.83068448e-01
-1.82169214e-01 5.49957037e-01 -1.49375415e+00 7.89539039e-01
1.22493780e+00 -3.92696589e-01 -7.98655331e-01 2.87241042e-01
7.78261304e-01 -3.56364489e-01 -9.41220880e-01 5.72023153e-01
5.80580056e-01 -6.83802843e-01 7.50221670e-01 -4.52788115e-01
7.39498958e-02 -3.58856201e-01 -2.45113954e-01 -1.70272958e+00
-6.87228441e-02 -7.73589849e-01 -9.21599641e-02 5.66708148e-01
2.32584998e-01 -9.14248586e-01 3.28273684e-01 4.92167741e-01
-4.58427995e-01 -6.60351872e-01 -1.14061844e+00 -1.60860133e+00
3.57102066e-01 -2.07759235e-02 2.08189383e-01 6.07064486e-01
4.79513437e-01 -4.56013829e-02 -5.20752788e-01 9.71516967e-02
6.56883776e-01 -3.32463235e-01 1.11996830e+00 -9.28310633e-01
-4.40478325e-01 -3.94839436e-01 -3.59852493e-01 -1.22481239e+00
6.25149190e-01 -8.00617099e-01 6.42592907e-01 -1.70387185e+00
-9.50181298e-03 -7.71073997e-01 -6.49064826e-03 6.37296081e-01
3.83664191e-01 -3.75512302e-01 4.92453486e-01 3.38979602e-01
-7.43879855e-01 1.00754046e+00 1.13572848e+00 -3.20147097e-01
-2.34938025e-01 -3.01480860e-01 8.89050290e-02 6.90338373e-01
8.27461302e-01 -3.57663423e-01 -5.90282261e-01 -3.64396363e-01
-2.33850613e-01 2.90260851e-01 7.50154853e-01 -1.18623900e+00
2.73951769e-01 -2.57841885e-01 3.23996064e-03 -1.45830080e-01
7.39277601e-01 -9.99638498e-01 5.84926270e-02 9.31688249e-01
-4.12006855e-01 2.26242945e-01 5.34841120e-01 1.14024150e+00
2.46871188e-01 -3.41392159e-01 3.99475366e-01 -8.55034366e-02
-8.52309883e-01 -8.31833575e-03 -8.79624903e-01 9.23842490e-02
1.28078365e+00 -1.59673244e-01 -4.97399539e-01 -4.53689516e-01
-6.17391288e-01 8.35185289e-01 7.15187430e-01 5.23138225e-01
4.67936993e-01 -9.93901432e-01 -3.64261180e-01 -3.35309088e-01
6.90666139e-02 -1.25505909e-01 9.92708132e-02 1.24394119e+00
-4.53922451e-01 1.86139226e-01 -4.73095655e-01 -6.79320216e-01
-9.08076286e-01 5.71266949e-01 4.59155500e-01 -2.67921239e-01
-9.40221012e-01 4.82353538e-01 2.64634073e-01 -1.05751371e+00
6.01489067e-01 -3.92997831e-01 2.28326872e-01 -3.70383292e-01
-3.28204721e-01 7.73429751e-01 -5.37895858e-01 -5.64534962e-01
-2.45503396e-01 4.31198180e-01 1.79597273e-01 -4.33055520e-01
9.87743437e-01 -6.33559972e-02 2.51331180e-01 6.52234197e-01
9.71715987e-01 -6.08016908e-01 -2.04149413e+00 7.38687143e-02
2.23710552e-01 -9.79137719e-02 -4.21703517e-01 -1.07309067e+00
-1.67629734e-01 7.42422879e-01 7.48298526e-01 -1.34817734e-01
5.47464371e-01 -1.82815865e-01 7.61243165e-01 1.07293010e+00
1.10110474e+00 -1.48676050e+00 5.75454295e-01 6.53835833e-01
1.08436882e+00 -1.49676895e+00 -8.40177536e-02 2.10567608e-01
-1.24291146e+00 8.22701693e-01 8.66269648e-01 -2.72299975e-01
2.80269265e-01 3.02898914e-01 -2.52738684e-01 -2.76559684e-02
-7.90542901e-01 -1.60428047e-01 -2.62640476e-01 8.06830823e-01
-3.81414533e-01 1.86851218e-01 1.86142158e-02 2.18404263e-01
1.30872190e-01 -2.28322238e-01 4.38242227e-01 1.65226889e+00
-3.93220007e-01 -7.78515041e-01 -2.55046606e-01 1.29668862e-01
1.61155596e-01 5.38308918e-01 -2.98995733e-01 1.29487944e+00
6.90592155e-02 9.21673894e-01 5.49094863e-02 -4.31589574e-01
4.48697299e-01 3.89948324e-03 7.80502856e-01 -4.15476590e-01
-4.66215909e-01 -3.61273229e-01 1.09399863e-01 -9.05300438e-01
-3.28006983e-01 -7.13189304e-01 -1.76802945e+00 3.33443619e-02
-1.03398874e-01 2.37504747e-02 7.49657691e-01 8.90460014e-01
5.40482819e-01 5.01490772e-01 2.47459680e-01 -1.75128531e+00
-1.10986471e+00 -1.02433085e+00 -4.94914711e-01 4.02294546e-01
6.06270015e-01 -1.43049896e+00 -7.08540261e-01 -2.00366288e-01] | [4.494185447692871, 1.0423370599746704] |
64a3f49a-c545-40e0-a3ce-1902c8ee7a67 | phonocardiogram-classification-using-1 | null | null | https://www.researchgate.net/publication/363503972_Phonocardiogram_Classification_Using_1-Dimensional_Inception_Time_Convolutional_Neural_Networks?channel=doi&linkId=63202e0c0a70852150eda8fc&showFulltext=true | https://cinc.org/2022/Program/accepted/108_Preprint.pdf | Phonocardiogram Classification Using 1-Dimensional Inception Time Convolutional Neural Networks | Murmurs are sounds caused by turbulent blood flow that are often the first sign of structural heart disease. These sounds are detected by auscultating the heart using a stethoscope, or more recently by a phonocardiogram (PCG). We aim to identify the presence, absence, or unclear cases of murmurs, as well as predict normal or abnormal clinical outcome from PCG recordings using machine learning.
We trained and tested two 1-dimensional convolutional neural networks (CNN) on a PCG data set from a pediatric population of 1568 individuals. One model predicted murmurs, while the other model predicted clinical outcomes. Both models were trained to give recording-wise predictions, while the final predictions were given for every patient (patient-wise predictions).
This paper describes our participation in the George B. Moody PhysioNet Challenge 2022 whose objective was to identify heart murmurs and clinical outcome from PCGs. Our team, Simulab, trained a clinical outcome classifier that achieved a challenge cost score of 12419 (ranked 14th out of 39 teams) and the murmur classifier achieved a weighted accuracy of 0.593 (ranked 30th out of 40 teams) on the test set. | ['Henrik Schirmer', 'Lars Ailo Bongo', 'Johan Ravn', 'Markus Kreutzer Johnsen', 'Antony M. Gitau', 'Bjørn-Jostein Singstad'] | 2022-09-07 | null | null | null | computing-in-cardiology-2022-9 | ['predict-clinical-outcome', 'classify-murmurs', 'phonocardiogram-classification'] | ['time-series', 'time-series', 'time-series'] | [ 2.54122883e-01 4.13652241e-01 3.49058270e-01 -2.00953260e-01
-7.30891824e-01 -3.12080920e-01 -1.79258838e-01 3.46544236e-01
-1.57622248e-01 7.72821844e-01 3.68161172e-01 -6.14703298e-01
-2.69549906e-01 -5.24302602e-01 -2.74231374e-01 -3.77811372e-01
-7.62892663e-01 8.11179519e-01 -3.32631245e-02 4.59602982e-01
-1.24233633e-01 2.83964574e-01 -1.04584014e+00 3.47426414e-01
7.17422426e-01 1.11958456e+00 -1.45170048e-01 1.85384226e+00
4.04060364e-01 1.31320941e+00 -8.16659451e-01 -9.29607749e-02
-5.13669997e-02 -8.16578984e-01 -8.43557119e-01 -3.68133962e-01
7.70135164e-01 -5.87234855e-01 -6.12922348e-02 9.84869450e-02
1.28667295e+00 -3.80709618e-01 4.24721062e-01 -8.98470819e-01
-1.45828739e-01 6.86337292e-01 1.46130592e-01 7.47643352e-01
1.43945187e-01 1.91225424e-01 9.73730147e-01 -4.73458022e-01
3.60549778e-01 6.37469947e-01 1.44099152e+00 7.08935857e-01
-1.05206621e+00 -2.98122853e-01 -8.03679705e-01 -5.34965619e-02
-6.73563063e-01 -2.89181113e-01 2.64336377e-01 -8.07805002e-01
9.45897698e-01 4.27204460e-01 1.05937910e+00 6.19904399e-01
2.53246486e-01 3.63370150e-01 6.52648687e-01 -2.28790745e-01
-1.47779556e-02 -3.04747730e-01 5.94305173e-02 6.73748493e-01
2.30279550e-01 1.64073184e-01 -2.59859204e-01 -6.65249467e-01
6.29176617e-01 -1.28519684e-01 -6.05868161e-01 1.72008872e-01
-1.24246383e+00 5.99177837e-01 -5.32767028e-02 1.17317371e-01
-5.39781153e-01 3.16631705e-01 5.51703691e-01 4.24610645e-01
1.43486977e-01 8.52493048e-01 -7.32280135e-01 -7.26142645e-01
-8.59748483e-01 3.02512199e-01 1.04373026e+00 3.61908488e-02
-2.62576938e-01 1.21990424e-02 -3.51859778e-01 1.02127910e+00
1.82611607e-02 4.22044784e-01 6.92859232e-01 -1.07276475e+00
3.05331945e-01 1.72517285e-01 -3.82882319e-02 -7.36834466e-01
-1.13717008e+00 -5.90542614e-01 -8.60127747e-01 -7.04218745e-02
6.05054259e-01 -8.01793516e-01 -7.67522633e-01 1.39167690e+00
6.13243394e-02 3.93108249e-01 3.14962156e-02 9.33747351e-01
1.37896931e+00 2.27339864e-01 -7.87403211e-02 -1.02621183e-01
1.08503735e+00 -6.01280034e-01 -3.50920588e-01 5.17232828e-02
1.11571133e+00 -5.44681370e-01 4.14890856e-01 5.98062992e-01
-1.23984039e+00 -3.65465790e-01 -9.04462576e-01 3.53546768e-01
2.59466916e-01 2.66454101e-01 2.26800278e-01 8.39872539e-01
-9.91130590e-01 1.27159870e+00 -8.85653973e-01 -1.45644397e-01
4.90199000e-01 2.19419226e-01 -2.24434823e-01 2.15588778e-01
-1.31699264e+00 8.70953679e-01 3.56056280e-02 2.22969241e-03
-7.22003937e-01 -1.20100915e+00 -7.15707362e-01 1.60397962e-01
-3.34368408e-01 -7.14085460e-01 1.31750810e+00 -1.92548081e-01
-9.55298364e-01 1.05174327e+00 4.41380888e-01 -8.17960203e-01
7.65361607e-01 -1.79040700e-01 -5.69495261e-01 4.34133202e-01
-2.43085735e-02 3.15390259e-01 6.12618744e-01 -3.20603877e-01
-6.76138222e-01 -5.55324778e-02 -5.37069619e-01 -4.14266586e-02
8.99178237e-02 -7.77556524e-02 3.80628526e-01 -4.85147178e-01
2.01078922e-01 -8.10294867e-01 -7.34958798e-02 -1.86564520e-01
-5.32209158e-01 5.87979564e-03 5.07009506e-01 -1.29838729e+00
1.13137257e+00 -2.06278729e+00 -3.39037925e-01 -5.58108725e-02
9.82596874e-01 5.53285241e-01 1.19405955e-01 3.33412319e-01
-5.66372752e-01 2.26384506e-01 -2.14949757e-01 -1.46494225e-01
-3.58674586e-01 -1.07116900e-01 -9.53025557e-03 3.80148709e-01
3.57003182e-01 7.66800046e-01 -8.01680923e-01 -2.71175623e-01
3.12221199e-01 4.57590550e-01 -5.75948894e-01 5.35734236e-01
2.48948768e-01 6.97381198e-01 4.93793488e-02 4.46769089e-01
2.49931157e-01 -6.29839480e-01 1.16489306e-01 2.76340134e-02
1.37385428e-01 5.42895555e-01 -7.48128295e-01 1.02923572e+00
-2.19089851e-01 8.56758893e-01 -2.89235562e-01 -9.03401852e-01
1.06591904e+00 9.44063962e-01 8.18632543e-01 -1.18510410e-01
1.06444143e-01 5.96016407e-01 8.47296655e-01 -9.27184701e-01
-3.76348168e-01 -4.86322612e-01 1.36184841e-01 7.98814476e-01
-1.52503505e-01 -1.67831451e-01 8.66595879e-02 -7.33408779e-02
1.76821411e+00 -3.69413108e-01 3.40338379e-01 -8.85335654e-02
2.14947909e-01 -2.84488857e-01 7.25302160e-01 1.14687276e+00
-5.77482283e-01 1.41955829e+00 8.47661078e-01 -1.24413300e+00
-9.19396043e-01 -9.14423525e-01 -4.45821851e-01 4.95575458e-01
-6.74466789e-01 -2.24593073e-01 -4.97327358e-01 -5.10388911e-01
2.57739842e-01 2.09534496e-01 -6.08270884e-01 -2.43174970e-01
-7.57157207e-01 -7.11471796e-01 1.12380862e+00 7.59536386e-01
2.00388536e-01 -1.42413723e+00 -1.32337308e+00 6.17439270e-01
-2.02253953e-01 -6.80007458e-01 -1.75416976e-01 1.60112649e-01
-7.50365555e-01 -1.44584727e+00 -1.10234857e+00 -6.73789442e-01
-1.51668638e-01 -8.11282814e-01 1.27830327e+00 3.79945189e-01
-1.11058927e+00 1.86423555e-01 -2.46868998e-01 -6.36487305e-01
-6.51398182e-01 8.57484937e-02 1.58619463e-01 -1.89661235e-01
8.83247796e-03 -7.76583731e-01 -8.69792879e-01 -1.34452373e-01
-2.03676209e-01 -3.95451263e-02 2.46725693e-01 8.09567690e-01
2.00241208e-01 -5.79229116e-01 1.07112420e+00 -7.99483538e-01
7.70373285e-01 -3.92545164e-01 -1.57948121e-01 -1.58652022e-01
-5.57383060e-01 -5.31999290e-01 6.83916986e-01 -1.96820289e-01
-2.26437494e-01 -2.06617922e-01 -4.28435624e-01 -5.27930737e-01
-3.45434427e-01 2.91967094e-01 7.64675140e-01 3.82806897e-01
9.01642919e-01 5.76603785e-02 1.96039692e-01 -6.39451683e-01
-3.89855117e-01 7.62259722e-01 8.48966599e-01 -3.00131947e-01
2.17524886e-01 9.46024135e-02 3.07433128e-01 -7.53443658e-01
-9.48561549e-01 -2.79435068e-01 -4.29481328e-01 -2.24638805e-01
1.10624719e+00 -5.75467765e-01 -7.09496677e-01 7.58223116e-01
-1.10835648e+00 -3.92862231e-01 -5.73885024e-01 8.00532818e-01
-4.58972901e-01 1.37834638e-01 -8.21800590e-01 -8.10705125e-01
-8.76041889e-01 -6.88959181e-01 7.00216055e-01 8.90830681e-02
-7.55907714e-01 -1.20119500e+00 5.30753732e-01 4.25125450e-01
7.06897616e-01 8.99044454e-01 1.02247488e+00 -1.09486043e+00
2.18824074e-01 -5.21399975e-01 -9.78740826e-02 4.87651259e-01
1.82277977e-01 -1.38378814e-01 -1.02834487e+00 -2.35240877e-01
-2.48145163e-01 -4.05834973e-01 8.05438340e-01 8.45991790e-01
1.26695406e+00 1.51821226e-01 5.44330850e-02 6.69129610e-01
8.45261514e-01 5.10054350e-01 3.78072977e-01 -7.26532638e-02
6.31504178e-01 4.16969270e-01 -4.68223877e-02 5.97314835e-01
1.73241556e-01 1.12899169e-01 2.58760244e-01 -2.67819256e-01
-3.35158139e-01 -1.50986031e-01 -3.82761359e-01 6.74940288e-01
-2.81429589e-01 1.07208863e-01 -1.43109989e+00 6.69358015e-01
-1.37528932e+00 -6.40047610e-01 -5.50465047e-01 2.10105014e+00
6.34519875e-01 9.49913859e-02 3.20428163e-01 5.21469533e-01
8.73833299e-01 -2.54943203e-02 -5.23402154e-01 -6.06616497e-01
1.82079375e-01 5.60072303e-01 3.46298516e-02 2.02953845e-01
-1.21449840e+00 -5.05000316e-02 7.04164648e+00 -2.36527279e-01
-1.36142325e+00 -2.54266290e-03 8.97867262e-01 -2.30990902e-01
3.69749635e-01 -4.34416860e-01 -3.40193182e-01 6.20458007e-01
1.12000942e+00 5.33577092e-02 -9.74469334e-02 5.09052515e-01
1.39990345e-01 2.40888581e-01 -1.18514371e+00 9.36568499e-01
1.51736857e-02 -1.54778063e+00 -7.83631980e-01 -1.62234887e-01
4.47155148e-01 3.32057655e-01 -2.53875464e-01 1.42598093e-01
-1.76299646e-01 -1.36405921e+00 1.36080176e-01 6.86907649e-01
1.25705075e+00 -2.05709279e-01 1.02653170e+00 2.36035451e-01
-7.61823952e-01 -2.01440141e-01 6.79252818e-02 -3.88026506e-01
2.10932449e-01 7.16205001e-01 -1.35036099e+00 -1.05656534e-01
8.95444334e-01 7.33273149e-01 -1.96801960e-01 1.53002417e+00
-7.49431551e-02 1.24196506e+00 -4.03256178e-01 1.20054722e-01
-2.55017400e-01 5.38579226e-01 6.98134542e-01 1.10868073e+00
4.21911001e-01 2.80744791e-01 -1.37503192e-01 7.78658688e-01
8.83316547e-02 5.36295734e-02 -4.33604747e-01 1.57675613e-02
2.95974046e-01 1.12362540e+00 -3.35253179e-01 -5.02656817e-01
-3.36386338e-02 2.12708563e-01 -1.28824532e-01 -4.83477786e-02
-5.36670804e-01 -8.02842915e-01 1.47922546e-01 4.98532563e-01
9.62868407e-02 8.15910637e-01 -6.13403559e-01 -9.20587361e-01
-1.50923893e-01 -7.14452446e-01 6.96689546e-01 -8.43121052e-01
-1.22756636e+00 5.63394606e-01 -6.00498140e-01 -1.13408101e+00
-5.54482222e-01 -5.65294623e-01 -1.26603544e+00 1.17263496e+00
-1.09778392e+00 -3.26104939e-01 -4.49820668e-01 -8.06300566e-02
4.26737219e-02 -2.77024329e-01 1.08393073e+00 4.22263175e-01
-4.83335286e-01 3.93194228e-01 -3.75826299e-01 5.11722147e-01
6.25796974e-01 -1.66878712e+00 3.74984682e-01 3.03189784e-01
-5.95697224e-01 2.46039718e-01 5.03422022e-01 -5.72849989e-01
-5.40161610e-01 -1.13201559e+00 1.46792769e+00 -4.07301635e-01
3.29670817e-01 4.98061389e-01 -8.85064960e-01 4.48061615e-01
-3.76524627e-01 4.63733107e-01 8.20819378e-01 -9.77350101e-02
5.00920974e-02 1.21248156e-01 -1.21585882e+00 -1.47162288e-01
5.74858606e-01 -2.37635359e-01 -8.03697109e-01 3.65658730e-01
4.87629771e-01 -7.56206334e-01 -1.52994883e+00 7.97179103e-01
9.14464831e-01 -1.07765448e+00 6.65860236e-01 -8.60734284e-01
9.60662127e-01 1.92122981e-01 3.54214519e-01 -1.42344868e+00
-1.93301007e-01 -7.62821674e-01 -3.08244526e-01 5.09013116e-01
4.83338147e-01 -8.42566729e-01 7.72629917e-01 5.53585291e-01
-3.11279565e-01 -1.14426875e+00 -7.89296031e-01 -3.38021487e-01
2.23922238e-01 -2.99686432e-01 4.77294981e-01 1.03525698e+00
1.80605948e-01 1.75040305e-01 -3.86349291e-01 -1.35438278e-01
3.63534570e-01 9.44256634e-02 2.21329257e-01 -1.55149055e+00
-7.26902604e-01 -4.23473179e-01 -7.10983694e-01 -1.55867144e-01
-7.15990961e-01 -7.63010204e-01 -7.63549656e-02 -1.69888711e+00
8.04972798e-02 -6.15413368e-01 -4.82680142e-01 5.76058149e-01
-2.82569647e-01 5.07635593e-01 7.62821957e-02 1.85491238e-02
-7.15832338e-02 -2.72176474e-01 1.15690958e+00 2.57421792e-01
-2.95851380e-01 5.01507640e-01 -3.54409248e-01 7.74661720e-01
1.02950895e+00 -4.90534663e-01 -1.95284471e-01 -1.23765051e-01
1.97571084e-01 9.42089379e-01 5.64528286e-01 -1.24679744e+00
-3.31322134e-01 3.84526163e-01 6.53038263e-01 -5.46455741e-01
2.58767784e-01 -2.23908070e-02 1.39931189e-02 1.17373204e+00
-6.03287339e-01 -9.08644721e-02 -1.17727265e-01 3.42302024e-02
-8.88580009e-02 -2.16982618e-01 9.30186391e-01 -2.77700931e-01
2.09923342e-01 4.40538108e-01 -5.05586863e-01 6.48680031e-01
6.40371501e-01 1.02852779e-02 -5.01318812e-01 -5.80739200e-01
-1.42841899e+00 2.74989754e-02 -2.50431925e-01 2.40414828e-01
6.99008882e-01 -1.03978455e+00 -1.27280784e+00 3.06432933e-01
-1.21321246e-01 -1.47989439e-02 3.07309568e-01 1.33109033e+00
-1.18187129e+00 4.01895106e-01 -1.12786286e-01 -7.51546323e-01
-1.32972383e+00 -3.16477478e-01 1.12566924e+00 -2.98652232e-01
-1.14188159e+00 1.12698829e+00 -2.75969356e-01 -5.80835044e-01
2.87406355e-01 -3.69652897e-01 -4.22088683e-01 -1.21527888e-01
6.69432461e-01 6.00246608e-01 1.12114400e-01 -7.32918680e-02
-2.94260800e-01 3.90124470e-01 2.02318802e-01 1.63202420e-01
1.37119389e+00 4.55239505e-01 -6.65999278e-02 4.33345735e-01
1.08172679e+00 -4.15772468e-01 -7.52067745e-01 6.54592514e-02
-2.14776471e-01 -2.16299400e-01 -1.07520685e-01 -1.11195803e+00
-1.15543544e+00 1.25098622e+00 9.33149517e-01 7.68886685e-01
9.21863735e-01 -9.54303741e-02 1.07770813e+00 2.52622038e-01
-3.15623432e-01 -7.20058918e-01 -4.02814411e-02 1.35667130e-01
6.65796638e-01 -1.00426066e+00 -2.86498755e-01 -3.99541296e-02
-6.75848305e-01 1.20855272e+00 4.93577749e-01 -2.22857416e-01
6.82534277e-01 3.09605062e-01 3.64591032e-01 -3.26102704e-01
-1.07281816e+00 3.10269296e-01 1.42100394e-01 7.74590373e-01
7.93167830e-01 5.40109158e-01 -2.89858520e-01 7.07774520e-01
-4.28449661e-01 3.05776030e-01 8.49801481e-01 7.61671841e-01
-5.13504446e-01 -5.12671649e-01 -1.74056470e-01 1.41598880e+00
-1.07295358e+00 -2.25504294e-01 -1.88413098e-01 1.87816620e-01
3.98892373e-01 8.92644823e-01 1.41699865e-01 -2.66963273e-01
3.63571912e-01 4.59407359e-01 2.36194700e-01 -6.52849615e-01
-8.18100572e-01 -5.87226823e-02 5.60105503e-01 -1.95962951e-01
1.62667334e-01 -8.74636233e-01 -1.13069630e+00 1.24767907e-01
4.15130593e-02 2.03957528e-01 3.72056156e-01 7.56239235e-01
2.57998437e-01 9.19920743e-01 5.67215562e-01 -2.39585787e-01
-7.50192642e-01 -1.30294943e+00 -7.93447375e-01 3.32465082e-01
8.19522262e-01 -1.58981159e-01 -6.21890843e-01 9.91470441e-02] | [14.352355003356934, 3.286165714263916] |
8075dff4-4dd9-4552-8dbc-e67704ecd8e3 | neural-improvement-heuristics-for-preference | 2206.00383 | null | https://arxiv.org/abs/2206.00383v2 | https://arxiv.org/pdf/2206.00383v2.pdf | Neural Improvement Heuristics for Graph Combinatorial Optimization Problems | In recent years, methods based on deep neural networks, and especially Neural Improvement (NI) models, have led to a revolution in the field of combinatorial optimization. Given an instance of a graph-based problem and a candidate solution, they are able to propose a modification rule that improves its quality. However, existing NI approaches only consider node features and node-wise positional encodings to extract the instance and solution information, respectively. Thus, they are not suitable for problems where the essential information is encoded in the edges. In this paper, we present a NI model to solve graph-based problems where the information is stored either in the nodes, in the edges, or in both of them. We incorporate the NI model as a building block of hill-climbing-based algorithms to efficiently guide the election of neighborhood operations considering the solution at that iteration. Conducted experiments show that the model is able to recommend neighborhood operations that are in the $99^{th}$ percentile for the Preference Ranking Problem. Moreover, when incorporated to hill-climbing algorithms, such as Iterated or Multi-start Local Search, the NI model systematically outperforms the conventional versions. Finally, we demonstrate the flexibility of the model by extending the application to two well-known problems: the Traveling Salesman Problem and the Graph Partitioning Problem. | ['Alexander Mendiburu', 'Josu Ceberio', 'Andoni I. Garmendia'] | 2022-06-01 | null | null | null | null | ['graph-partitioning'] | ['graphs'] | [ 2.52487898e-01 3.15577835e-02 -6.28657222e-01 -2.67802685e-01
-2.30961516e-01 -2.36433774e-01 -3.55033875e-02 7.42187023e-01
-5.52604735e-01 8.65805805e-01 -1.17181316e-01 -4.63850051e-01
-1.06458938e+00 -1.32773769e+00 -7.64072955e-01 -6.96855903e-01
-3.45024943e-01 7.33921230e-01 5.04792966e-02 -5.51685035e-01
5.62520206e-01 5.39956689e-01 -1.79632211e+00 1.75581500e-01
1.21988833e+00 1.00163746e+00 3.90357584e-01 1.72740832e-01
-2.62875199e-01 2.85697073e-01 -3.36572707e-01 -2.94163734e-01
4.13972944e-01 -2.87074238e-01 -1.01790535e+00 -1.18366487e-01
3.94894853e-02 -3.65930833e-02 -2.53384616e-02 1.03366661e+00
3.96611482e-01 4.55556631e-01 2.35053897e-01 -1.24125302e+00
-5.24519563e-01 1.00436628e+00 -4.98870611e-01 9.58700553e-02
1.50975913e-01 -2.98965931e-01 1.38386345e+00 -3.99258107e-01
8.80097985e-01 8.81840289e-01 5.04712939e-01 1.82470307e-01
-9.45504844e-01 -1.94221526e-01 5.85975885e-01 8.72633040e-01
-1.34697640e+00 8.74441639e-02 1.10549283e+00 2.31190637e-01
1.00162673e+00 5.34937918e-01 9.03816581e-01 3.46686125e-01
4.03526351e-02 7.86666155e-01 8.01072538e-01 -5.31425774e-01
4.37308371e-01 -7.68820643e-02 2.96346664e-01 6.97045088e-01
3.95921558e-01 1.67951450e-01 -4.27533120e-01 4.31654416e-02
2.74320662e-01 -2.86478177e-02 -2.86594987e-01 -6.35911107e-01
-8.17341864e-01 1.07028437e+00 1.10011613e+00 4.87438738e-01
-6.15068674e-01 8.80398527e-02 2.12551370e-01 3.38630497e-01
1.73679695e-01 1.01950538e+00 -4.66798782e-01 6.56306744e-02
-9.47237253e-01 2.44340077e-01 7.94954121e-01 6.80821478e-01
1.07437360e+00 -3.13194484e-01 -2.83343792e-01 6.03176415e-01
-1.11965928e-02 -2.44086966e-01 3.43161583e-01 -6.79528117e-01
6.17839456e-01 1.14221704e+00 1.19271778e-01 -1.44103646e+00
-7.93863535e-01 -9.33049560e-01 -7.53043234e-01 -1.01170808e-01
6.85250759e-02 7.11665377e-02 -9.56343830e-01 1.74220729e+00
4.55153644e-01 8.49577785e-02 -1.72048286e-01 8.75645280e-01
7.17205048e-01 5.58006167e-01 -4.22053128e-01 -5.21037459e-01
7.49604762e-01 -1.26741648e+00 -5.17080963e-01 -1.83008179e-01
7.91945457e-01 -2.11329535e-01 6.99720383e-01 4.96163428e-01
-1.18676400e+00 -5.15716910e-01 -1.15971851e+00 1.87055588e-01
-7.01318026e-01 -7.52506480e-02 7.70100117e-01 6.56444013e-01
-1.31492162e+00 9.93597269e-01 -4.26100850e-01 -3.96353424e-01
1.45230904e-01 8.54879022e-01 -4.90113050e-02 -4.46058959e-01
-1.34516585e+00 9.08833563e-01 5.91902792e-01 5.08749664e-01
-5.15787601e-01 -1.24767058e-01 -7.52768338e-01 4.99136031e-01
7.97500670e-01 -6.13876522e-01 6.52568936e-01 -8.77758265e-01
-1.21826077e+00 3.56071532e-01 -1.74307987e-01 -5.04133344e-01
2.40733027e-01 2.75591671e-01 -3.54225010e-01 -8.30655918e-02
-1.80031732e-01 6.05145335e-01 3.92625749e-01 -1.24165881e+00
-9.61715400e-01 -4.92080808e-01 6.42957032e-01 5.32555223e-01
-5.97437680e-01 -4.34459001e-01 -6.78662539e-01 -1.94443345e-01
3.14952582e-01 -8.29828978e-01 -7.63787985e-01 -5.51005840e-01
-5.50331116e-01 -3.69480461e-01 3.28428596e-01 -2.99102902e-01
1.76085138e+00 -1.73784184e+00 4.57247257e-01 9.14785564e-01
2.02067062e-01 3.38850021e-01 -4.54859078e-01 6.46215558e-01
3.36468220e-02 4.21830326e-01 -1.40859619e-01 -1.12469964e-01
1.62010580e-01 3.95699531e-01 3.89189392e-01 2.80019104e-01
-6.11627363e-02 9.66251373e-01 -9.32571352e-01 -1.29101187e-01
2.25888356e-03 -7.29629248e-02 -8.15204263e-01 -2.23157451e-01
-1.48284391e-01 2.17708632e-01 -4.17735994e-01 4.17592674e-01
7.82116652e-01 -1.84829131e-01 4.44879383e-01 -8.12416524e-02
-2.12313205e-01 3.07143748e-01 -1.45689547e+00 1.68048143e+00
-3.91426921e-01 1.98715448e-01 1.22503713e-01 -1.43519628e+00
9.65339541e-01 -2.39376828e-01 5.40485620e-01 -1.03160620e+00
1.78509429e-01 2.47720152e-01 2.60984242e-01 -2.74165422e-01
8.59232605e-01 4.31735367e-01 6.26375824e-02 3.08717966e-01
-3.12986851e-01 1.34314805e-01 9.58878219e-01 -5.88461645e-02
9.96840894e-01 -1.43062904e-01 2.29389429e-01 -2.06193939e-01
7.54025996e-01 8.59986618e-02 6.52243018e-01 9.65794504e-01
2.03088760e-01 3.10333431e-01 4.08499330e-01 -7.38823533e-01
-6.65156484e-01 -5.18850744e-01 1.19654305e-01 1.14229095e+00
5.95327854e-01 -5.07203460e-01 -5.71884334e-01 -6.38676107e-01
-9.28364918e-02 6.52165473e-01 -7.59618819e-01 -5.43018639e-01
-7.95410454e-01 -9.65981066e-01 -1.21099152e-01 3.41836035e-01
3.71638685e-01 -1.04924583e+00 -5.93802989e-01 4.73535746e-01
-2.26136938e-01 -5.61678112e-01 -2.05559805e-01 5.77220857e-01
-9.51460004e-01 -9.87567425e-01 -3.38774651e-01 -1.01181793e+00
8.50323200e-01 1.98800653e-01 1.14608610e+00 6.88650846e-01
-6.95028380e-02 -7.57696107e-02 -7.07262039e-01 -7.28073716e-02
3.47306170e-02 6.03707790e-01 -2.07620203e-01 -2.32613292e-02
2.84207076e-01 -4.67700094e-01 -5.22919595e-01 4.70146000e-01
-8.37835789e-01 -1.29035890e-01 6.53536201e-01 9.16075945e-01
5.87980688e-01 6.32472932e-01 5.97050905e-01 -9.43154991e-01
9.69803035e-01 -4.05312836e-01 -6.88002348e-01 6.40390575e-01
-1.12397444e+00 3.12199444e-01 7.66854048e-01 -4.75672930e-02
-6.10776544e-01 9.68695432e-02 -1.74939245e-01 -7.71419331e-02
7.90142715e-02 1.26535690e+00 -1.13031358e-01 -1.14547335e-01
4.43475395e-01 1.41429633e-01 -3.84366393e-01 -2.73817837e-01
2.53439307e-01 1.94984347e-01 2.18466148e-01 -5.54788351e-01
5.50628245e-01 9.51636136e-02 2.26742133e-01 -3.25073183e-01
-4.35331583e-01 -4.33782637e-01 -6.07892513e-01 4.48782556e-02
4.61712778e-01 -1.21492699e-01 -7.88430512e-01 9.10177231e-02
-1.02893913e+00 6.73374999e-03 -3.43459666e-01 2.86642194e-01
-3.37739021e-01 2.79979825e-01 -3.08158427e-01 -7.84106433e-01
-1.60734862e-01 -1.51702905e+00 5.46810985e-01 4.56052482e-01
1.28191680e-01 -8.84373009e-01 -1.44385293e-01 1.96739733e-01
4.46123570e-01 1.04937226e-01 1.32380438e+00 -6.62825584e-01
-5.97717285e-01 -2.71106809e-01 -6.12962916e-02 -1.05219014e-01
7.89979752e-03 -7.67241791e-02 -3.09586614e-01 -3.14500064e-01
-3.02439779e-01 -1.08129485e-02 1.02814102e+00 7.44417310e-01
1.28589833e+00 -4.21290904e-01 -5.17341137e-01 6.58021092e-01
1.49914670e+00 6.10887647e-01 6.06790960e-01 6.87913239e-01
3.93985212e-01 6.45326674e-01 6.34062529e-01 4.73556757e-01
5.84513843e-01 7.16613412e-01 1.04750133e+00 -2.21161947e-01
3.14733922e-01 -8.64450559e-02 -1.35654882e-01 6.00481153e-01
-3.15297306e-01 -7.81301796e-01 -7.50299454e-01 6.06577635e-01
-2.02313733e+00 -6.48312628e-01 -1.18536398e-01 2.30149508e+00
5.03752947e-01 1.52979061e-01 5.04991747e-02 4.62952375e-01
1.01461112e+00 1.07330732e-01 -5.21584213e-01 -9.19413507e-01
-2.72206403e-02 3.50679249e-01 5.13309121e-01 5.28027534e-01
-1.07713950e+00 8.98525655e-01 5.78943300e+00 7.20369220e-01
-9.67688203e-01 -3.04187626e-01 6.30975485e-01 -1.48414867e-02
-4.70592886e-01 -1.09349713e-01 -7.35275447e-01 1.75466865e-01
6.10595465e-01 -1.51561469e-01 9.87654746e-01 7.11005092e-01
-2.46538687e-02 -2.16148585e-01 -1.25372851e+00 6.93397343e-01
1.21276639e-01 -1.46241152e+00 1.38942733e-01 1.30213127e-01
9.52518404e-01 -3.11285675e-01 3.30277443e-01 2.73417681e-01
2.15780601e-01 -1.13478386e+00 3.36286813e-01 9.53644514e-02
2.25571588e-01 -1.31965423e+00 1.14836931e+00 4.39024121e-01
-1.25053108e+00 -6.40743911e-01 -4.01081264e-01 -1.51122302e-01
6.67908713e-02 3.66865069e-01 -8.07890236e-01 1.23639309e+00
8.17699492e-01 5.68171382e-01 -5.21929145e-01 1.45210242e+00
-2.41411433e-01 1.29432142e-01 -4.11510825e-01 -3.22452307e-01
8.03312361e-01 -3.28757584e-01 3.96850079e-01 5.44005990e-01
4.51500297e-01 -2.14369185e-02 2.59588182e-01 6.23190761e-01
-9.51211676e-02 3.06077182e-01 -3.53418916e-01 4.73306812e-02
3.72679889e-01 1.16916561e+00 -1.10567605e+00 5.96504062e-02
2.80832052e-02 5.58417082e-01 5.33868909e-01 3.57594699e-01
-7.68679023e-01 -4.90445882e-01 1.84499517e-01 -1.89312056e-01
5.14105678e-01 2.08794456e-02 -4.04097170e-01 -5.63024461e-01
3.00384755e-03 -7.51427054e-01 6.15122855e-01 -4.17712033e-01
-8.78564656e-01 9.24749732e-01 -1.53627489e-02 -9.46809053e-01
-3.00328285e-01 -5.10707080e-01 -5.92071891e-01 5.59896648e-01
-1.65573955e+00 -8.10168386e-01 -4.11811054e-01 4.44399476e-01
2.15726122e-01 4.94808368e-02 5.96631765e-01 5.22369385e-01
-6.18174911e-01 6.04036450e-01 2.78634578e-01 -2.34672725e-01
5.50292619e-02 -1.08061445e+00 2.67788093e-03 8.97849143e-01
2.97573894e-01 6.14883840e-01 6.24531388e-01 -3.62646341e-01
-1.34037817e+00 -6.62746906e-01 9.07792389e-01 3.01698655e-01
2.06139401e-01 -1.13808319e-01 -5.31845927e-01 3.40405852e-01
9.08868834e-02 -2.25711018e-01 3.96724880e-01 4.96711940e-01
3.72464716e-01 -4.57356662e-01 -1.11960900e+00 5.36514342e-01
1.27978003e+00 1.85115218e-01 -3.09588730e-01 3.03612500e-01
5.40416539e-01 -4.49268281e-01 -6.28008127e-01 6.82047069e-01
3.76866251e-01 -9.80055213e-01 1.01099408e+00 -8.22395980e-01
4.02848512e-01 -2.83362955e-01 -3.79856699e-03 -1.67948103e+00
-6.98024750e-01 -2.61319607e-01 -6.17249161e-02 8.61098945e-01
8.62169266e-01 -5.39716721e-01 9.97842491e-01 5.03933728e-01
-3.09620440e-01 -1.18833625e+00 -1.11571956e+00 -5.22874117e-01
-2.46357068e-01 -1.02566101e-01 1.06225049e+00 8.25433969e-01
-9.60525125e-02 1.22959271e-01 -4.57906812e-01 1.46648929e-01
9.63964239e-02 7.36756206e-01 3.57630998e-01 -1.53595316e+00
-1.65518641e-01 -7.80780077e-01 -2.82460779e-01 -1.04461789e+00
-2.16127522e-02 -1.05176067e+00 1.20253779e-01 -2.13341761e+00
-8.15545171e-02 -8.12822938e-01 -8.49196970e-01 5.25026858e-01
-1.38217151e-01 3.39733250e-02 1.96602687e-01 -2.82158852e-01
-7.23954856e-01 5.00371277e-01 1.21960211e+00 -3.67234349e-01
-6.10665262e-01 1.81352034e-01 -8.66403401e-01 4.29531455e-01
8.71079326e-01 -5.16356707e-01 -5.21208584e-01 -5.76264918e-01
8.11954379e-01 -4.83838608e-03 -1.27493203e-01 -9.92531002e-01
6.00473523e-01 -3.29700619e-01 1.05547488e-01 -7.47093499e-01
2.80083418e-01 -1.17346060e+00 5.08489721e-02 6.17040932e-01
-5.00084639e-01 4.69131470e-01 6.19497560e-02 4.74534065e-01
-2.81175524e-01 -5.93453705e-01 3.72817278e-01 -1.24878690e-01
-8.80794287e-01 3.67861629e-01 -5.54557033e-02 -3.37109715e-01
1.03856838e+00 -4.65413094e-01 -2.86516309e-01 -2.80922443e-01
-7.56461322e-01 5.99714339e-01 3.57452631e-01 2.45100841e-01
6.34370923e-01 -1.10864544e+00 -5.48815846e-01 6.66085631e-02
3.17228101e-02 1.41451418e-01 2.33961433e-01 1.00512230e+00
-5.41663587e-01 4.68626589e-01 -3.73673707e-01 -3.41162622e-01
-1.06058383e+00 9.43353474e-01 1.47186950e-01 -8.04491878e-01
-1.03191525e-01 8.75233412e-01 -2.44987488e-01 -6.46107972e-01
3.43784422e-01 -5.49477637e-01 -6.70269847e-01 1.55284017e-01
1.65962890e-01 5.98542988e-01 4.52516347e-01 -3.19121778e-01
-4.65720624e-01 4.40349549e-01 -2.71633267e-02 3.15922678e-01
1.64684987e+00 -1.46784201e-01 -3.86550248e-01 -7.11119696e-02
8.69450450e-01 -9.44989175e-02 -5.36333323e-01 -1.13586798e-01
1.90423593e-01 -4.69129890e-01 1.66130975e-01 -8.58365476e-01
-1.55291533e+00 5.44759274e-01 3.46750498e-01 5.07653236e-01
1.53481603e+00 -2.61639237e-01 6.56477511e-01 7.32243121e-01
5.85136533e-01 -1.34965658e+00 -4.23771590e-01 5.45483351e-01
6.66135430e-01 -8.86856318e-01 8.89896825e-02 -3.09323311e-01
-3.88961971e-01 1.16159058e+00 6.99508250e-01 -3.41331698e-02
4.26699847e-01 -8.85370523e-02 -4.21738893e-01 -2.62014363e-02
-7.17892230e-01 -4.06495541e-01 4.51735526e-01 3.87431055e-01
3.08861379e-02 1.94297023e-02 -9.27329540e-01 5.75010777e-01
-1.15421876e-01 -5.31614162e-02 2.88618296e-01 8.51972342e-01
-4.80958104e-01 -1.23408520e+00 -1.52893558e-01 6.69996500e-01
3.95169742e-02 -2.46779755e-01 -5.08079171e-01 7.57103682e-01
4.64708775e-01 1.20589983e+00 5.06420285e-02 -5.80271900e-01
3.60524088e-01 -2.39763871e-01 2.66623795e-01 -3.75674605e-01
-9.15820241e-01 -2.13522762e-01 2.64106274e-01 -6.59721196e-01
-5.39270282e-01 -3.70894969e-01 -1.25772250e+00 -3.90413254e-01
-5.80864310e-01 5.80499291e-01 5.89472890e-01 8.88492405e-01
4.98953462e-01 6.70850873e-01 7.10575163e-01 -8.61687183e-01
-2.49916986e-01 -5.83683074e-01 -5.84467709e-01 7.05451369e-02
1.09242939e-03 -8.20815265e-01 -1.41003579e-01 -7.71152198e-01] | [5.3391523361206055, 3.174720048904419] |
b4aa3c8c-e9da-45c7-a888-e91ceb768253 | deep-joint-transmission-recognition-for-power | 2003.02027 | null | https://arxiv.org/abs/2003.02027v2 | https://arxiv.org/pdf/2003.02027v2.pdf | Joint Device-Edge Inference over Wireless Links with Pruning | We propose a joint feature compression and transmission scheme for efficient inference at the wireless network edge. Our goal is to enable efficient and reliable inference at the edge server assuming limited computational resources at the edge device. Previous work focused mainly on feature compression, ignoring the computational cost of channel coding. We incorporate the recently proposed deep joint source-channel coding (DeepJSCC) scheme, and combine it with novel filter pruning strategies aimed at reducing the redundant complexity from neural networks. We evaluate our approach on a classification task, and show improved results in both end-to-end reliability and workload reduction at the edge device. This is the first work that combines DeepJSCC with network pruning, and applies it to image classification over the wireless edge. | ['Krystian Mikolajczyk', 'Mikolaj Jankowski', 'Deniz Gunduz'] | 2020-03-04 | null | null | null | null | ['feature-compression'] | ['computer-vision'] | [ 5.47468364e-01 1.25581697e-01 -2.92470366e-01 -1.52967304e-01
-4.34058845e-01 -3.38398144e-02 3.20667326e-02 -3.58948600e-03
-4.25022691e-01 5.51187336e-01 1.59269087e-02 -4.79790390e-01
-3.47255141e-01 -8.27402711e-01 -7.76007295e-01 -4.43722069e-01
-5.87000430e-01 1.12895720e-01 1.50983602e-01 3.51285100e-01
-7.51523226e-02 2.89927334e-01 -1.41005874e+00 1.43089727e-01
5.12766957e-01 1.68602324e+00 4.42433834e-01 1.30809844e+00
3.84918123e-01 8.43437314e-01 -5.41937053e-01 -6.62744582e-01
2.49460891e-01 -2.40197316e-01 -5.90884626e-01 -4.95858416e-02
7.55911544e-02 -6.28185868e-01 -7.46423900e-01 8.14352632e-01
9.95915413e-01 -2.05223694e-01 1.86939970e-01 -1.22692621e+00
-5.04481699e-03 8.34395289e-01 -2.16942742e-01 1.40204221e-01
1.11402720e-01 -4.68380451e-01 8.58235657e-01 -3.70041460e-01
5.43784082e-01 7.95200706e-01 1.08111131e+00 3.50104004e-01
-9.84965146e-01 -6.55051649e-01 -1.13968723e-01 5.47741354e-01
-1.58409584e+00 -1.08048534e+00 7.33583748e-01 4.66449827e-01
1.32490683e+00 2.10083351e-01 6.25634372e-01 6.16592228e-01
2.24523962e-01 1.03706205e+00 5.56583285e-01 -6.41822815e-01
6.16671264e-01 -1.50729552e-01 -2.86373168e-01 8.98121178e-01
3.70941460e-01 5.11388332e-02 -9.59309578e-01 -3.42316091e-01
5.12989759e-01 2.96193478e-03 -3.24509859e-01 7.37374648e-02
-4.57095325e-01 5.30396819e-01 4.90467884e-02 -4.50270949e-03
-6.85750186e-01 1.03014183e+00 5.96883297e-01 6.30267918e-01
6.98921204e-01 -5.44161201e-01 -8.87525380e-01 -6.22936845e-01
-1.38675463e+00 -1.43746480e-01 1.45451427e+00 1.35499895e+00
2.64238834e-01 -1.72195837e-01 -3.78269076e-01 6.42553091e-01
4.12022293e-01 5.21251976e-01 1.47974089e-01 -1.40614545e+00
3.79836887e-01 -2.03904301e-01 -4.28361416e-01 -8.27673018e-01
-2.47875288e-01 -9.15750563e-01 -1.03668547e+00 -4.54743393e-02
-3.27615231e-01 -5.91526330e-01 -6.07221127e-01 1.73169565e+00
-2.85743866e-02 6.91893280e-01 2.45949119e-01 4.67723131e-01
7.77224481e-01 4.12327707e-01 -1.35799110e-01 -4.27150160e-01
1.21817124e+00 -9.57125306e-01 -7.67804027e-01 1.60316661e-01
7.74352670e-01 -6.97205305e-01 7.35046640e-02 6.57278657e-01
-1.63456857e+00 -1.85127020e-01 -1.03994489e+00 -7.15092719e-02
-7.41491467e-02 5.23752809e-01 9.72396851e-01 1.07498062e+00
-1.38690555e+00 7.60780215e-01 -1.01273060e+00 -1.13171227e-01
7.73166656e-01 7.99591601e-01 -1.35374039e-01 -1.90830931e-01
-9.26086605e-01 3.55890542e-01 7.57970512e-02 -2.13076919e-01
-4.49349165e-01 -5.13506651e-01 -6.92071974e-01 6.93138778e-01
4.46099669e-01 -1.14393306e+00 1.30326080e+00 -5.14088273e-01
-1.68636286e+00 4.43670414e-02 -4.65650856e-01 -1.08356643e+00
1.32492185e-01 -8.35878253e-02 -2.34409541e-01 4.43892807e-01
-4.93397683e-01 6.23767674e-01 8.06744695e-01 -6.32284105e-01
-7.79515028e-01 -2.56878197e-01 -1.55932665e-01 -2.89283507e-02
-5.47567010e-01 -3.36042911e-01 -8.58799338e-01 -7.45896816e-01
3.20418447e-04 -7.79908895e-01 -2.87035197e-01 3.87738913e-01
-1.86414286e-01 -1.59534603e-01 9.68717754e-01 -7.24467874e-01
1.41982436e+00 -2.14435959e+00 -4.66118976e-02 4.49051410e-01
2.65282035e-01 3.10344428e-01 5.18018566e-02 2.14683414e-01
5.79966903e-01 -2.47352812e-02 -3.60681564e-02 -1.05053604e+00
-2.49668762e-01 4.26081955e-01 9.62892249e-02 2.81750351e-01
-3.78709167e-01 7.76910067e-01 -4.98000383e-01 -5.83928347e-01
-1.40773326e-01 7.61843145e-01 -1.09590268e+00 -6.48302957e-02
-3.51880444e-03 -3.32960874e-01 -2.93187410e-01 6.29462540e-01
8.49158764e-01 -2.38227382e-01 3.82090032e-01 -2.53865898e-01
3.57340783e-01 4.16299701e-01 -1.10086608e+00 1.93290818e+00
-1.00054979e+00 7.67476201e-01 5.56392848e-01 -1.10636902e+00
3.74904782e-01 6.22368157e-01 5.31614244e-01 -6.19420230e-01
2.20703945e-01 2.48374864e-01 -3.86405885e-01 -2.77344882e-01
4.92162138e-01 3.64389300e-01 1.13383502e-01 2.39533246e-01
1.87152013e-01 1.25570416e-01 2.18526348e-02 4.28623587e-01
1.51725602e+00 -7.88397491e-02 9.89985391e-02 -1.68320730e-01
1.60609603e-01 -5.69178879e-01 4.50023860e-01 1.07215118e+00
1.29150182e-01 2.20121279e-01 3.08034420e-01 -6.27099499e-02
-8.01065147e-01 -7.97919452e-01 -3.03624384e-02 8.92351329e-01
3.59588601e-02 -1.06672251e+00 -6.09102428e-01 -4.99635756e-01
1.57142412e-02 3.65801424e-01 -8.57707262e-02 -2.98404157e-01
8.78189951e-02 -6.05477691e-01 8.45818996e-01 6.21233046e-01
9.22825575e-01 -2.63165027e-01 -1.01140571e+00 3.66293430e-01
-1.60510205e-02 -1.52085590e+00 -1.59286171e-01 5.17579973e-01
-1.05791306e+00 -6.71845078e-01 -3.82304132e-01 -5.29828668e-01
3.00280809e-01 1.74090788e-01 1.03856242e+00 2.91102946e-01
-4.07867730e-01 5.82310438e-01 -4.22050178e-01 -3.40721190e-01
-6.02329671e-02 1.41308293e-01 -2.12935194e-01 -2.57639408e-01
2.58593615e-02 -8.91196609e-01 -7.48942435e-01 -1.97885484e-01
-6.08460605e-01 7.20677301e-02 8.67345035e-01 8.19827139e-01
4.93380457e-01 6.89911723e-01 3.05528522e-01 -8.87698412e-01
5.41003525e-01 -4.23516721e-01 -2.78425455e-01 1.76790833e-01
-8.37062955e-01 1.69391140e-01 6.96084082e-01 1.01927808e-02
-8.72913480e-01 3.74206573e-01 -5.19871593e-01 -2.97861964e-01
2.57933319e-01 5.41203439e-01 -3.56271788e-02 -5.04488587e-01
4.29021716e-02 1.52540088e-01 -1.51314840e-01 -5.17642319e-01
1.95160672e-01 1.02802396e+00 5.36016285e-01 -3.15000683e-01
7.89141804e-02 6.08312786e-01 7.07370818e-01 -9.35359836e-01
-2.98204899e-01 -2.53978908e-01 -2.99409758e-02 6.72855228e-03
9.34458971e-02 -1.31909359e+00 -1.09805846e+00 2.31342241e-01
-1.22060406e+00 -2.94079751e-01 -2.76978612e-01 7.25588322e-01
-5.97211659e-01 5.49185395e-01 -7.57650971e-01 -9.33873534e-01
-8.05636466e-01 -7.66467571e-01 1.34501076e+00 -4.26878296e-02
1.97857440e-01 -8.05808425e-01 -5.18966854e-01 -2.20807254e-01
7.62743950e-01 -3.04516315e-01 4.55122501e-01 -2.56123781e-01
-7.19539404e-01 -4.89824355e-01 -3.99275959e-01 2.63661861e-01
-3.44622642e-01 -3.78060758e-01 -1.06395113e+00 -3.03946942e-01
-1.42178714e-01 -1.15595587e-01 1.33326149e+00 6.81010187e-01
1.85982394e+00 -3.59729767e-01 -5.92152357e-01 1.03110385e+00
1.50052178e+00 -2.66162366e-01 6.89091504e-01 -5.61086178e-01
2.05408663e-01 -1.84905961e-01 1.39961571e-01 9.68920112e-01
3.33554775e-01 7.25411475e-01 3.44823539e-01 -3.96917649e-02
-5.41768134e-01 1.15933701e-01 3.15585047e-01 7.69173265e-01
-2.48326138e-02 -7.44061232e-01 -1.83265265e-02 4.91965532e-01
-1.93136704e+00 -6.93659961e-01 1.47245731e-02 1.99854112e+00
5.41881442e-01 3.25515121e-01 -2.70109326e-01 6.65637612e-01
3.77395779e-01 -1.54238880e-01 -3.77488822e-01 -6.18776917e-01
1.48997560e-01 7.46101499e-01 1.08796382e+00 3.67367864e-01
-9.50062931e-01 4.45577353e-01 6.65497589e+00 1.21440041e+00
-7.94583380e-01 5.65016687e-01 6.03743732e-01 -3.77909541e-01
-7.04029426e-02 -1.08845465e-01 -6.84284031e-01 3.94418180e-01
1.35452390e+00 3.22663635e-01 6.81405604e-01 1.02891421e+00
-5.79043254e-02 -3.30579460e-01 -7.82596886e-01 1.29340422e+00
4.56531011e-02 -1.37300277e+00 -4.80684370e-01 1.32143095e-01
4.49226469e-01 1.72200561e-01 -2.49713123e-01 -8.19269419e-02
1.29247606e-01 -5.55516958e-01 4.57059503e-01 6.05651855e-01
1.06708813e+00 -9.45170820e-01 9.06494558e-01 2.37224728e-01
-1.44199383e+00 -2.04701111e-01 -2.78369248e-01 -2.62971818e-01
2.95282930e-01 1.19581103e+00 -6.34841383e-01 5.12291610e-01
7.82456696e-01 5.94674170e-01 -3.41444075e-01 1.16095114e+00
1.75806329e-01 7.49103546e-01 -9.50226009e-01 -1.39790043e-01
-3.56351823e-01 5.34392893e-01 4.45191562e-01 1.42113435e+00
6.13461733e-01 -1.37786165e-01 3.52075174e-02 2.38566369e-01
-5.04437506e-01 -3.20172220e-01 -5.12167811e-01 2.22108424e-01
7.12867916e-01 1.02212381e+00 -7.78107285e-01 -5.06274879e-01
-5.51459134e-01 1.38166606e+00 1.38751984e-01 1.48950085e-01
-6.45670176e-01 -7.34931767e-01 4.19126540e-01 -3.38360399e-01
7.93748438e-01 -3.78276974e-01 -5.76230645e-01 -8.06117833e-01
2.45474845e-01 -9.65110138e-02 3.05790097e-01 -4.45019752e-01
-6.79224491e-01 2.69839108e-01 -1.92989036e-01 -7.17111528e-01
-1.66215882e-01 -2.56240934e-01 -3.55924338e-01 4.97367710e-01
-1.71188927e+00 -9.66135919e-01 -1.72949582e-01 6.32979751e-01
2.58743972e-01 -1.03978932e-01 9.33552325e-01 8.29741061e-01
-2.92006910e-01 1.19955552e+00 2.78171450e-01 -3.23914856e-01
-1.01385266e-02 -8.25007439e-01 3.40493381e-01 8.99899483e-01
-1.52469769e-01 2.64389127e-01 5.94016314e-01 -5.48150420e-01
-1.96985400e+00 -1.04766166e+00 1.05178750e+00 4.44983095e-01
-4.00693044e-02 -4.75537390e-01 -2.10988462e-01 1.12171173e-01
1.89766943e-01 4.19187695e-01 6.89934790e-01 1.70413163e-02
7.80996606e-02 -2.67620504e-01 -1.32822096e+00 3.86989772e-01
1.45514512e+00 -6.93305731e-01 4.47649717e-01 3.50940645e-01
7.82017291e-01 -3.12391400e-01 -9.00266290e-01 4.91694272e-01
8.33877683e-01 -6.53979301e-01 9.12166178e-01 -7.52678439e-02
3.75934243e-02 1.27882799e-02 -3.88262421e-01 -8.67785096e-01
-1.40428916e-01 -9.50601399e-01 -9.77605999e-01 1.03631854e+00
3.72166663e-01 -2.45417029e-01 1.26363564e+00 3.35946381e-01
-1.96669847e-01 -8.79538476e-01 -1.22435272e+00 -7.18776286e-01
-9.82947707e-01 -1.00527489e+00 3.70894253e-01 -1.01015624e-02
-9.53713655e-02 1.73149824e-01 -6.43174887e-01 2.12168112e-01
5.58776498e-01 -1.15332916e-01 4.92285401e-01 -1.22982597e+00
-9.55337524e-01 -1.39015123e-01 -5.68179011e-01 -1.48421788e+00
-1.13662489e-01 -8.95800292e-01 -4.22387529e-06 -1.35562670e+00
-2.48742593e-03 -4.71484214e-01 3.30473520e-02 4.66636568e-01
2.62187451e-01 5.44200420e-01 1.60512358e-01 -2.20031455e-01
-9.99327660e-01 4.63973582e-01 6.13308012e-01 2.19200179e-01
-5.28937988e-02 3.42709005e-01 -5.81871092e-01 3.73031139e-01
8.13518167e-01 -5.31623244e-01 -4.70956743e-01 -5.01561880e-01
5.48300147e-01 2.45127469e-01 3.64018142e-01 -1.36422408e+00
7.75967300e-01 7.29187787e-01 3.10814708e-01 -3.87463868e-01
6.44509733e-01 -1.35450089e+00 6.52660429e-02 8.72675419e-01
-9.29621607e-02 -1.17388956e-01 6.86134398e-02 8.97881866e-01
1.97510764e-01 -2.01007947e-01 3.09817404e-01 2.13226527e-01
-6.16937518e-01 2.14593664e-01 -4.76992726e-01 -5.78089654e-01
7.64571846e-01 -2.04391181e-02 -9.85816717e-02 -6.81121647e-01
-9.62606788e-01 2.64714718e-01 -3.74704562e-02 -2.71518230e-01
7.55168438e-01 -8.58208537e-01 -5.24677694e-01 5.53502798e-01
-4.35697407e-01 -1.71584547e-01 1.68589622e-01 9.13633943e-01
-3.96363765e-01 4.93723422e-01 1.39755711e-01 -3.80644917e-01
-1.51522112e+00 2.09018290e-01 1.24470361e-01 -2.40933850e-01
-4.84890252e-01 9.92229760e-01 -8.23820472e-01 4.32971388e-01
7.32297719e-01 -2.33929887e-01 3.45838457e-01 -4.21555281e-01
4.34735328e-01 7.25137651e-01 4.50726032e-01 6.49341643e-02
-8.21394771e-02 3.82538289e-01 2.58190215e-01 2.57100370e-02
1.23219109e+00 -5.38316071e-01 -1.38479117e-02 -3.86223048e-01
1.41690099e+00 -4.03542854e-02 -1.06674814e+00 -2.01515019e-01
-4.88288313e-01 -3.67206573e-01 9.48510468e-01 -6.85080111e-01
-1.42632365e+00 6.25502586e-01 1.00830781e+00 9.04655457e-02
1.76376712e+00 -1.23571783e-01 1.30143130e+00 6.67106211e-01
5.83197534e-01 -1.12103772e+00 -4.96624470e-01 3.44960123e-01
8.90490264e-02 -7.10658312e-01 2.80664921e-01 -7.73374379e-01
-2.93166339e-02 1.13768208e+00 -2.05567345e-01 2.52804179e-02
1.42240524e+00 8.61315429e-01 -8.92219365e-01 -1.79724365e-01
-1.15024853e+00 -5.33706486e-01 -1.93672597e-01 4.97828811e-01
2.23147750e-01 1.14725448e-01 -6.43067479e-01 6.88352704e-01
9.68482047e-02 6.91893578e-01 1.86836198e-01 1.24114406e+00
-3.46857548e-01 -1.26155519e+00 1.12228572e-01 9.35731232e-01
-9.70889211e-01 -4.14239764e-01 4.06759158e-02 2.17758003e-03
3.38047683e-01 1.16799974e+00 2.85941750e-01 -7.24298239e-01
-9.07194912e-02 -1.51782408e-01 5.19886732e-01 -2.14144856e-01
-3.72059137e-01 1.72864884e-01 4.89134192e-01 -6.94420934e-01
-4.94690359e-01 -3.25096071e-01 -1.17743838e+00 -5.48585296e-01
-5.65693617e-01 1.82429075e-01 1.34522116e+00 7.52618611e-01
1.11486924e+00 7.68108547e-01 6.23881996e-01 -7.61803746e-01
-8.79747123e-02 -6.35487318e-01 -6.67385519e-01 -3.13698292e-01
4.18933898e-01 -2.37385213e-01 -8.52381869e-04 -1.22980610e-01] | [8.4058256149292, 2.8675856590270996] |
79600d25-8974-4827-9ee8-dc0675061549 | a-collection-of-scholarly-book-reviews-from | null | null | https://aclanthology.org/L14-1660 | https://aclanthology.org/L14-1660.pdf | A Collection of Scholarly Book Reviews from the Platforms of electronic sources in Humanities and Social Sciences OpenEdition.org | In this paper, we present our contribution for the automatic construction of the Scholarly Book Reviews corpora from two different sources, the OpenEdition platform which is dedicated to electronic resources in the humanities and social sciences, and the Web. The main target is the collect of reviews in order to provide automatic links between each review and its potential book in the future. For these purposes, we propose different document representations and we apply some supervised approaches for binary genre classification before evaluating their impact. | ["Fr{\\'e}d{\\'e}ric B{\\'e}chet", 'Patrice Bellot', 'Elodie Faath', 'Chahinez Benkoussas', 'Hussam Hamdan'] | 2014-05-01 | null | null | null | lrec-2014-5 | ['genre-classification'] | ['computer-vision'] | [-2.82950133e-01 8.02880153e-02 -8.48599732e-01 4.98713963e-02
-7.08498418e-01 -7.67603099e-01 1.24469960e+00 7.35505998e-01
-4.47162151e-01 8.79467547e-01 5.17955124e-01 -3.80077958e-01
-2.57214934e-01 -8.74018192e-01 -1.63283333e-01 -1.80395946e-01
3.99928957e-01 6.34487212e-01 1.14347599e-01 -3.84277254e-01
1.22247410e+00 3.51545960e-01 -1.70864010e+00 2.46491715e-01
9.98466015e-01 7.87053823e-01 2.54231364e-01 5.82795203e-01
-7.44427204e-01 5.62044799e-01 -9.18323815e-01 -1.06266057e+00
-2.57898867e-01 -3.78143996e-01 -8.89887869e-01 -2.33059362e-01
1.51978210e-01 2.79311359e-01 -8.29034150e-02 1.01509440e+00
3.23753059e-02 6.17550574e-02 1.52566338e+00 -7.89120495e-01
-8.90418530e-01 1.18340743e+00 -4.21971709e-01 5.93032002e-01
6.60792887e-01 -6.87776804e-01 1.36400163e+00 -6.19971693e-01
1.13726699e+00 1.15027952e+00 1.74424693e-01 2.00087711e-01
-4.26367611e-01 -4.20435190e-01 -1.44502848e-01 6.46198809e-01
-1.03195357e+00 -3.61090422e-01 1.11051929e+00 -7.07804024e-01
7.52984583e-01 1.10140331e-01 6.33377314e-01 1.38989198e+00
3.30612570e-01 4.31877732e-01 1.00366497e+00 -1.05582476e+00
1.50336042e-01 7.28304207e-01 7.08307564e-01 3.20440620e-01
5.23511469e-01 -5.59239388e-01 -6.74946368e-01 -9.75260511e-02
3.28984290e-01 -2.36006901e-01 -1.80804491e-01 1.86752632e-01
-8.12630713e-01 8.58013570e-01 -5.69215305e-02 1.06817687e+00
-3.18458825e-01 -3.45572323e-01 6.51109040e-01 1.11085974e-01
8.09841573e-01 7.18840778e-01 -2.08419248e-01 -3.14117938e-01
-9.87244189e-01 8.01305100e-02 1.33272564e+00 1.05103672e+00
1.85082838e-01 -6.34543240e-01 8.56439695e-02 9.91104126e-01
6.30784512e-01 9.58327651e-02 8.59554350e-01 -4.56799120e-01
6.07280493e-01 8.85636628e-01 -1.98082611e-01 -1.19015503e+00
-1.16054393e-01 -3.76107007e-01 -4.32042599e-01 -5.27374208e-01
-3.51984948e-02 1.71970055e-01 -2.48553157e-01 5.21983147e-01
-1.76638961e-01 -3.10060650e-01 1.64797232e-01 1.67775109e-01
1.82168615e+00 8.36377442e-01 1.50534675e-01 -6.22590601e-01
1.38152277e+00 -9.02888954e-01 -1.29637289e+00 2.60059565e-01
7.00187147e-01 -1.16835821e+00 7.93622673e-01 5.27993739e-01
-1.18559766e+00 -4.16052192e-01 -1.42837584e+00 -2.25407824e-01
-1.13256884e+00 6.57744467e-01 3.94411474e-01 3.83307546e-01
-7.02939212e-01 7.15137482e-01 -4.15382713e-01 -5.61284840e-01
3.65542084e-01 -2.35258743e-01 -1.36637092e-01 1.20029740e-01
-1.17586207e+00 1.32730949e+00 5.83677143e-02 -3.81735951e-01
-5.25793284e-02 -4.19747829e-01 -7.71563053e-01 6.92382678e-02
1.42483160e-01 -9.25498605e-02 8.03782284e-01 -7.47800648e-01
-1.21607316e+00 1.44970810e+00 -1.55726016e-01 -3.41005772e-01
1.48452848e-01 -2.56433934e-01 -7.06702471e-01 2.30814651e-01
3.65734249e-01 -1.09712817e-01 4.02537435e-01 -1.05913222e+00
-6.43258393e-01 -4.16875988e-01 -9.16677937e-02 5.65843172e-02
-9.70211327e-01 4.20067638e-01 -8.20568562e-01 -6.89208984e-01
-3.99436563e-01 -4.63794142e-01 1.28908828e-01 -7.94444799e-01
-2.08541572e-01 -8.81348431e-01 3.47103119e-01 -7.98328400e-01
1.55526507e+00 -1.94068587e+00 3.08074802e-01 1.06314182e-01
3.09056282e-01 -7.81401768e-02 2.27223933e-01 6.84922457e-01
4.36813623e-01 7.12654173e-01 2.24915579e-01 -5.23443758e-01
-1.15972675e-01 1.82746530e-01 -4.11393791e-01 3.50346476e-01
-1.62899479e-01 7.67756462e-01 -8.24002028e-01 -8.61682594e-01
-3.59035842e-02 3.87883216e-01 2.56373048e-01 6.67679161e-02
9.55659747e-02 -2.69730896e-01 -5.61059177e-01 7.22486198e-01
2.77608007e-01 6.06059246e-02 4.44260277e-02 -2.62315944e-02
-4.62467760e-01 1.09925520e+00 -7.44806767e-01 1.17333794e+00
-5.62810302e-01 1.02452242e+00 -2.93247342e-01 -9.25100505e-01
1.29654348e+00 1.51516259e-01 2.78177172e-01 -6.40259206e-01
5.66963255e-01 3.38944107e-01 -1.81194976e-01 -2.41457477e-01
9.72002327e-01 3.17717522e-01 -1.67220280e-01 3.67913246e-01
5.13448656e-01 -3.02227139e-01 9.82342482e-01 5.61483920e-01
5.86683393e-01 1.71167895e-01 6.72260582e-01 -5.72256327e-01
1.08409417e+00 1.26440227e-01 -1.61361450e-03 3.46263558e-01
2.22645402e-01 3.00457686e-01 8.58426869e-01 -2.90793061e-01
-9.85339403e-01 -5.33682644e-01 -7.65672147e-01 9.27055597e-01
3.52559686e-02 -7.79558718e-01 -6.48369372e-01 -8.52285683e-01
-5.95089234e-02 7.98811257e-01 -7.36930847e-01 1.15958869e-01
-2.65113354e-01 -4.53095704e-01 1.18806399e-01 1.57840729e-01
6.49140552e-02 -1.27976024e+00 -8.09131637e-02 8.22583493e-03
-4.43127751e-03 -8.82618010e-01 -7.38912076e-02 4.01286989e-01
-6.56402707e-01 -1.35304844e+00 -7.70347655e-01 -8.33268166e-01
4.18807983e-01 -1.38536230e-01 1.47806489e+00 1.60791740e-01
-1.67199358e-01 4.28986400e-01 -9.22570407e-01 -6.78594172e-01
-6.86585128e-01 8.07376862e-01 -1.84831217e-01 -6.32377684e-01
7.63754129e-01 -2.13037804e-01 1.54612079e-01 -5.46297133e-02
-6.48003101e-01 -5.43762147e-01 2.40132824e-01 5.18237889e-01
4.63107198e-01 -3.96118052e-02 9.04826105e-01 -1.30670786e+00
1.24170315e+00 -9.37623203e-01 -5.08661211e-01 2.68095940e-01
-1.03574431e+00 -1.30391657e-01 4.98355836e-01 -2.53657937e-01
-9.61600482e-01 -5.31351745e-01 -2.10973248e-01 1.91768810e-01
7.14114383e-02 8.13214600e-01 2.12284434e-03 8.02820548e-02
7.64854193e-01 3.19358483e-02 -4.07137752e-01 -7.58682549e-01
3.08474332e-01 1.15584135e+00 3.10153335e-01 -5.22346556e-01
4.80002552e-01 -1.56941503e-01 -1.19916148e-01 -8.22880924e-01
-9.36329067e-01 -8.50807965e-01 -1.02359021e+00 -6.48325145e-01
5.62955141e-01 -6.15315616e-01 -2.49198541e-01 -2.92410403e-01
-1.22311521e+00 5.77710569e-01 -2.82685041e-01 2.58659065e-01
-1.77656040e-01 2.51378268e-01 -4.97622341e-01 -6.87280118e-01
-6.69256210e-01 -9.03511226e-01 6.99153721e-01 5.43970942e-01
-3.25575024e-01 -1.30679429e+00 4.06687737e-01 5.18303931e-01
1.17663570e-01 -1.17022574e-01 9.21399415e-01 -1.04501009e+00
2.24485233e-01 -3.87414813e-01 1.50809996e-03 3.57271343e-01
-1.45576462e-01 6.71749353e-01 -5.78787804e-01 1.74402311e-01
-1.43128023e-01 -1.57771453e-01 1.04518020e+00 1.04755759e-01
1.04160035e+00 -2.89070070e-01 -4.96560663e-01 1.28260955e-01
1.30493104e+00 4.08744067e-01 6.78593576e-01 7.88226783e-01
4.99389887e-01 7.61548519e-01 6.11411750e-01 6.89113081e-01
5.24848998e-01 3.82152110e-01 5.71540408e-02 4.02163833e-01
2.88974922e-02 -6.03390150e-02 1.23799227e-01 1.70857298e+00
-4.94003534e-01 -4.10726517e-01 -9.33318794e-01 8.10631692e-01
-1.56257308e+00 -7.63291836e-01 -4.52733427e-01 1.89031875e+00
8.20796013e-01 3.65975976e-01 -2.66833100e-02 2.81902581e-01
5.05008399e-01 1.13406934e-01 2.30923414e-01 -9.46037471e-01
-1.54729202e-01 5.17794192e-01 4.89876956e-01 2.51162022e-01
-8.61699402e-01 7.82527208e-01 6.93013239e+00 9.13586676e-01
-5.21716535e-01 1.72173306e-01 6.37548029e-01 6.17083460e-02
-4.01535362e-01 -1.42376587e-01 -1.36487722e+00 5.44093072e-01
1.18254006e+00 -7.25633919e-01 2.17363145e-02 1.02896607e+00
-3.65126699e-01 -2.16509864e-01 -7.77901888e-01 5.83155096e-01
6.44141316e-01 -1.66794968e+00 2.20785663e-01 1.68923855e-01
7.60542870e-01 -1.50446057e-01 -2.40190789e-01 4.61226702e-01
7.45647177e-02 -8.06159675e-01 5.39368153e-01 6.53139889e-01
5.47087312e-01 -9.97540295e-01 1.13685238e+00 2.78554678e-01
-8.87194455e-01 3.95691395e-01 -5.61140954e-01 -1.38339698e-01
-1.64957091e-01 6.37131870e-01 -3.60987186e-01 5.09124219e-01
7.54270256e-01 1.40232074e+00 -1.04925025e+00 8.21455419e-01
-5.14733315e-01 7.32295811e-01 2.83369005e-01 -8.55668068e-01
-7.91798159e-02 -3.98186058e-01 5.67719340e-01 1.42639244e+00
1.82828113e-01 -2.41096452e-01 -1.07307948e-01 7.93542385e-01
-4.47868437e-01 7.07919300e-01 -7.05063641e-01 -4.08845663e-01
5.38391948e-01 1.78380346e+00 -8.46793115e-01 -3.02967757e-01
-4.34459358e-01 6.05241656e-01 3.31410795e-01 -9.16544721e-02
-3.11221540e-01 -8.54318440e-01 -1.24808960e-01 1.85714051e-01
-7.16742650e-02 1.21249914e-01 -5.66170812e-01 -1.30673218e+00
-1.19307660e-01 -5.44521987e-01 3.83690119e-01 -5.07375419e-01
-1.64892340e+00 7.62131989e-01 5.87676466e-03 -1.13986921e+00
-2.42240235e-01 -7.76848316e-01 -7.17194021e-01 8.66626978e-01
-1.51316082e+00 -9.65373218e-01 2.05423951e-01 1.29203573e-01
5.60240269e-01 -6.50735795e-01 7.73569345e-01 2.82366008e-01
-5.14805079e-01 4.35287327e-01 3.19337279e-01 -3.03600933e-02
8.72983277e-01 -1.35879040e+00 1.03813708e-02 3.74707669e-01
2.18357399e-01 5.20251274e-01 4.51243162e-01 -8.64714921e-01
-1.03005469e+00 -4.03305769e-01 1.61184454e+00 -5.53615153e-01
1.16552603e+00 -1.49306551e-01 -8.41744125e-01 3.36790711e-01
6.87729359e-01 -6.55603945e-01 1.07167399e+00 4.43664104e-01
-8.07769224e-02 1.30273044e-01 -9.29138362e-01 4.11131293e-01
5.29790342e-01 -3.07395577e-01 -1.08116782e+00 4.14861679e-01
4.09156561e-01 -1.20378463e-02 -1.37688887e+00 7.43310228e-02
3.59976679e-01 -3.24925929e-01 6.51913702e-01 -1.85655594e-01
1.46993959e+00 2.33417988e-01 1.56652927e-01 -1.21862996e+00
-3.00076485e-01 -6.94318488e-02 -3.07417840e-01 1.88032341e+00
6.89207554e-01 -3.37493420e-01 4.70037907e-01 3.27364355e-01
-7.90081546e-02 -9.19597149e-01 -9.39396560e-01 -3.04603845e-01
4.37487811e-01 -2.34153166e-01 2.64651626e-01 8.94675791e-01
7.29338169e-01 8.09111774e-01 8.83887187e-02 -7.36005604e-01
2.89248943e-01 9.37788859e-02 4.39550549e-01 -1.67409945e+00
1.69385150e-01 -1.12978280e+00 -3.76939803e-01 -5.97913563e-01
4.12765265e-01 -8.95538807e-01 -2.16818556e-01 -1.70281887e+00
4.30411339e-01 -3.43310162e-02 -2.21283272e-01 -1.37821913e-01
-7.35648796e-02 1.74422804e-02 8.22740719e-02 5.82146168e-01
-7.05379546e-01 3.84806544e-01 1.12640417e+00 -1.41076520e-01
-1.23450600e-01 -9.39390361e-02 -1.13635242e+00 7.79312193e-01
6.56002700e-01 -5.34636259e-01 4.49182689e-02 2.51560420e-01
6.64679706e-01 -3.24939728e-01 -3.91554981e-01 -6.82789266e-01
-2.70223171e-02 -3.16694714e-02 4.44314092e-01 -9.05849695e-01
-1.77206635e-01 -5.43977976e-01 -4.79410738e-01 8.00981447e-02
-6.46890223e-01 1.53930292e-01 1.54562807e-02 2.34679863e-01
-5.07223487e-01 -1.21880996e+00 4.40520316e-01 -3.66687685e-01
-1.30711287e-01 -2.72418886e-01 -7.24508822e-01 1.00098044e-01
8.69294167e-01 3.77498776e-01 -6.36984766e-01 -2.48863980e-01
-2.40822732e-01 1.00045122e-01 4.08663988e-01 6.88198388e-01
4.02550697e-01 -1.03959262e+00 -6.17743134e-01 -3.69348615e-01
3.32876891e-01 -6.29074037e-01 -4.22648907e-01 3.13505620e-01
-5.66366613e-01 6.10415041e-01 -3.26647282e-01 1.83134362e-01
-1.35232580e+00 5.37579238e-01 -2.66841382e-01 -7.40068018e-01
-3.84772450e-01 3.73559803e-01 -4.94679928e-01 -1.73014387e-01
4.51341003e-01 -1.05757890e-02 -1.94432962e+00 8.38801384e-01
7.71528065e-01 7.21023858e-01 1.73842728e-01 -8.82287204e-01
-1.90712035e-01 4.16558594e-01 -2.51899213e-01 -1.91242293e-01
1.55336344e+00 -1.60260215e-01 -5.25215387e-01 1.05471194e+00
1.16899931e+00 4.02312428e-01 1.94541458e-02 2.33517215e-02
3.15501332e-01 -1.99774101e-01 3.96226764e-01 -8.88992488e-01
-9.09487426e-01 6.69634759e-01 5.96096814e-02 7.51976311e-01
9.00485456e-01 2.93643087e-01 3.12474281e-01 4.45885569e-01
3.43341306e-02 -1.52859831e+00 -4.92450327e-01 6.00449681e-01
1.05875444e+00 -1.05907381e+00 7.74237633e-01 -4.78517264e-01
-6.66472912e-01 1.53442955e+00 3.56779903e-01 -2.60946840e-01
8.67055595e-01 2.48094484e-01 -6.23940527e-02 -4.43948358e-01
-7.14226544e-01 -2.62138277e-01 8.47129166e-01 4.96967196e-01
1.01387691e+00 -1.52536377e-01 -1.54073799e+00 1.25591493e+00
-3.18597108e-01 -2.12485388e-01 9.77607787e-01 5.93753815e-01
-2.84362286e-01 -1.44689047e+00 -2.67919213e-01 8.30329359e-01
-1.16697133e+00 -1.03398763e-01 -1.00278139e+00 6.99976742e-01
2.49699205e-02 8.67497206e-01 1.00566864e-01 -1.72065213e-01
2.74424970e-01 -5.76747693e-02 2.84570128e-01 -7.68516302e-01
-9.77149487e-01 1.73064634e-01 3.83987516e-01 2.34066382e-01
-7.98711717e-01 -8.80412281e-01 -8.78727257e-01 -1.59500197e-01
-4.90850359e-01 4.56200868e-01 1.13812053e+00 8.97578776e-01
1.12690158e-01 9.84687328e-01 4.59034652e-01 -7.31852353e-01
1.62044987e-01 -1.34125841e+00 -7.11054981e-01 2.05763415e-01
-3.55419725e-01 -8.98489773e-01 -5.41421831e-01 3.17408115e-01] | [12.064170837402344, 9.520589828491211] |
75f17e0b-de09-46da-9465-fc806f14a6d6 | learning-to-race-through-coordinate-descent | 1802.06179 | null | http://arxiv.org/abs/1802.06179v1 | http://arxiv.org/pdf/1802.06179v1.pdf | Learning to Race through Coordinate Descent Bayesian Optimisation | In the automation of many kinds of processes, the observable outcome can
often be described as the combined effect of an entire sequence of actions, or
controls, applied throughout its execution. In these cases, strategies to
optimise control policies for individual stages of the process might not be
applicable, and instead the whole policy might have to be optimised at once. On
the other hand, the cost to evaluate the policy's performance might also be
high, being desirable that a solution can be found with as few interactions as
possible with the real system. We consider the problem of optimising control
policies to allow a robot to complete a given race track within a minimum
amount of time. We assume that the robot has no prior information about the
track or its own dynamical model, just an initial valid driving example.
Localisation is only applied to monitor the robot and to provide an indication
of its position along the track's centre axis. We propose a method for finding
a policy that minimises the time per lap while keeping the vehicle on the track
using a Bayesian optimisation (BO) approach over a reproducing kernel Hilbert
space. We apply an algorithm to search more efficiently over high-dimensional
policy-parameter spaces with BO, by iterating over each dimension individually,
in a sequential coordinate descent-like scheme. Experiments demonstrate the
performance of the algorithm against other methods in a simulated car racing
environment. | ['Vitor Guizilini', 'Valdir Grassi Jr', 'Rafael Oliveira', 'Lionel Ott', 'Fernando H. M. Rocha', 'Fabio Ramos'] | 2018-02-17 | null | null | null | null | ['carracing-v0'] | ['playing-games'] | [ 2.73065746e-01 2.43701547e-01 7.61650354e-02 -1.67725325e-01
-2.30486006e-01 -4.25185174e-01 7.64470875e-01 3.07088494e-01
-8.55614603e-01 7.70108104e-01 -4.30104077e-01 -5.34658492e-01
-5.84271193e-01 -7.08089471e-01 -6.29273057e-01 -1.02685595e+00
-1.70670807e-01 7.91464090e-01 4.20914143e-01 -2.66966015e-01
4.77591962e-01 9.57366049e-01 -1.49390340e+00 -5.93637109e-01
5.56191921e-01 8.24696720e-01 5.70428610e-01 9.96317089e-01
1.79949164e-01 6.60417438e-01 -5.84959984e-01 7.80714750e-02
3.35297406e-01 -4.03838843e-01 -7.29354680e-01 5.29243946e-01
-6.04838729e-01 2.45007470e-01 -8.91992226e-02 1.04554534e+00
2.24117592e-01 6.68116927e-01 8.51814032e-01 -1.21037233e+00
5.17879128e-01 -4.96225357e-02 -2.14811623e-01 -5.78938983e-02
1.56594038e-01 3.51172894e-01 4.34344083e-01 -1.57570630e-01
3.86690617e-01 1.04599798e+00 2.64213443e-01 1.79857090e-01
-1.44293022e+00 -7.77949467e-02 6.04226477e-02 5.02852276e-02
-1.33427298e+00 -3.89041185e-01 4.57932532e-01 -4.47783291e-01
6.67351961e-01 1.62711248e-01 7.08734810e-01 4.50306654e-01
6.97952271e-01 3.83340031e-01 1.00903916e+00 -4.72923398e-01
6.38922274e-01 1.08556718e-01 -5.08773923e-01 5.37132800e-01
9.45510194e-02 3.13279361e-01 1.26486778e-01 -2.16874450e-01
6.02914035e-01 -1.05501011e-01 -1.05896667e-01 -8.75251532e-01
-1.19565594e+00 8.88483703e-01 5.40784560e-03 2.57600993e-01
-8.25113714e-01 9.97867584e-02 3.55941415e-01 5.21491110e-01
-5.15941605e-02 7.44659185e-01 -3.66233647e-01 -4.74788785e-01
-5.53579688e-01 6.54929459e-01 1.11553872e+00 7.63500273e-01
6.04134679e-01 -2.45526627e-01 3.12225930e-02 5.37555397e-01
2.26952568e-01 3.72240275e-01 4.18211222e-02 -1.16325629e+00
2.66733527e-01 2.06457421e-01 7.27344513e-01 -7.79468596e-01
-3.94316256e-01 -5.48802270e-03 -6.29369318e-01 7.86628902e-01
6.54929578e-01 -3.86803061e-01 -6.31631613e-01 1.53177965e+00
6.44902229e-01 -8.83068815e-02 2.09300533e-01 8.95790756e-01
-6.03769958e-01 8.95971537e-01 -1.54513538e-01 -5.12949944e-01
1.21474576e+00 -3.88249934e-01 -7.10209966e-01 -3.07096392e-01
7.69392788e-01 -8.17909479e-01 4.20221359e-01 6.54094040e-01
-9.65372264e-01 -4.27182704e-01 -1.04259872e+00 6.85942471e-01
-2.14994565e-01 1.25602424e-01 1.04176953e-01 4.01510924e-01
-6.69690788e-01 8.28345895e-01 -9.87416685e-01 -2.87858039e-01
-1.97140440e-01 4.59645838e-01 -2.34863997e-01 -2.88173016e-02
-1.01238692e+00 1.42060208e+00 6.13841832e-01 5.43520868e-01
-1.04599941e+00 1.49011686e-01 -8.36129844e-01 -1.44645572e-01
7.85195887e-01 -3.39013666e-01 1.58579636e+00 -6.31704271e-01
-1.77392054e+00 1.62157252e-01 -1.19296955e-02 -3.42776179e-01
6.91249609e-01 1.71551984e-02 -2.16859519e-01 -1.70989439e-01
6.40185848e-02 2.31064394e-01 8.36741924e-01 -1.00620985e+00
-8.64632010e-01 -1.88112289e-01 1.39183238e-01 4.19902027e-01
4.21138644e-01 -8.95182602e-03 -3.05775255e-01 1.16814516e-01
6.76863641e-02 -1.50036979e+00 -7.64029086e-01 -3.83171082e-01
-1.94282159e-01 -3.74056935e-01 7.15605021e-01 -2.45314285e-01
1.00893617e+00 -1.97981858e+00 4.65256304e-01 5.77967644e-01
-4.87090558e-01 2.19686612e-01 3.37557644e-01 5.71233392e-01
-1.98006481e-02 -3.43311489e-01 -4.49081570e-01 3.78900617e-02
-1.75983142e-02 5.82648814e-01 -9.05367881e-02 8.97517085e-01
1.40690133e-01 2.85430640e-01 -1.01523769e+00 -4.56251025e-01
3.56216162e-01 1.43466890e-01 -1.27562568e-01 2.63972789e-01
-1.78056970e-01 5.65188289e-01 -8.51992488e-01 -2.41009697e-01
1.99139267e-01 3.03646445e-01 2.51813352e-01 4.26299214e-01
-5.41733742e-01 5.13955988e-02 -1.79060113e+00 1.22772121e+00
-5.12269616e-01 5.12478471e-01 3.95477623e-01 -1.37469399e+00
1.08784342e+00 5.63716769e-01 6.73667967e-01 -4.99271214e-01
2.78775841e-01 1.57696739e-01 1.80654556e-01 -4.98039246e-01
3.65519911e-01 -3.45240057e-01 -2.02652901e-01 4.69665974e-01
-5.07147431e-01 -5.80162942e-01 2.59078801e-01 -1.02305107e-01
1.23655403e+00 5.63737154e-02 3.32866669e-01 -1.20369010e-01
6.35260880e-01 1.99510381e-01 3.01367134e-01 6.71811640e-01
-1.95743859e-01 -5.94913103e-02 6.58427119e-01 -2.08910719e-01
-1.15543902e+00 -4.52954948e-01 -1.17929764e-01 6.01622403e-01
2.95318812e-01 1.97821315e-02 -5.72714210e-01 -5.08810282e-01
-1.90346539e-01 9.34814215e-01 -5.21500707e-01 -2.28688627e-01
-6.81427717e-01 -5.21694183e-01 -9.10275709e-03 -1.31406635e-02
3.09686035e-01 -1.12853193e+00 -1.39074135e+00 7.13250220e-01
2.74909675e-01 -7.38064945e-01 -1.99393973e-01 6.36364341e-01
-7.51025200e-01 -1.12274122e+00 -4.54765230e-01 -5.20762444e-01
8.40769351e-01 -1.03160359e-01 5.39024770e-01 -2.96969235e-01
1.31124100e-02 2.32768521e-01 -1.30896151e-01 -4.67887104e-01
-7.35755086e-01 -1.43607676e-01 8.66386890e-02 1.11530721e-02
-3.53781395e-02 8.10466558e-02 -2.62549102e-01 6.61520481e-01
-7.38367856e-01 -1.68999329e-01 6.36301041e-01 6.63764298e-01
4.61414099e-01 9.49990749e-01 2.53186226e-01 -4.05016571e-01
8.59892070e-01 -2.98998952e-01 -9.79660571e-01 -4.39752564e-02
-4.30976629e-01 3.88705611e-01 5.34610212e-01 -6.82754397e-01
-9.31198478e-01 5.30874372e-01 8.35840702e-02 -4.52325851e-01
-4.00016069e-01 4.67522115e-01 -2.71226406e-01 1.50049388e-01
4.26391870e-01 3.00562263e-01 4.86214250e-01 -2.67558336e-01
2.06672221e-01 5.90032578e-01 3.99005383e-01 -6.58322096e-01
5.50013900e-01 1.35016099e-01 4.52301055e-01 -8.37979972e-01
-2.49108583e-01 -5.95830917e-01 -7.69167900e-01 -5.70982695e-01
7.89092481e-01 -3.03985417e-01 -1.03481352e+00 1.88672081e-01
-1.09937072e+00 -4.34124440e-01 -2.60867566e-01 7.07745135e-01
-1.02155077e+00 6.45939843e-04 1.20301150e-01 -1.34420812e+00
4.74391818e-01 -1.30746484e+00 8.51142645e-01 3.56335007e-02
-3.16869497e-01 -7.94764996e-01 2.56691933e-01 -2.17646256e-01
1.73259720e-01 3.46682787e-01 5.23116291e-01 -5.48251271e-01
-2.54060566e-01 -6.24352634e-01 3.70086491e-01 2.52234250e-01
3.80480736e-02 -1.60907149e-01 -3.56677055e-01 -3.95530134e-01
3.83346081e-01 7.77467936e-02 1.97940111e-01 3.49630326e-01
7.48623908e-01 -3.24027538e-01 -5.07382691e-01 -9.75638106e-02
1.16952360e+00 7.90434241e-01 4.99433935e-01 6.85245037e-01
2.79876858e-01 1.10632420e+00 1.23979473e+00 3.13008457e-01
5.21326400e-02 9.89523947e-01 5.41226268e-01 2.27277175e-01
7.96002567e-01 2.18167350e-01 3.94989133e-01 2.41489083e-01
-1.40162455e-02 -2.29199398e-02 -8.15799356e-01 5.54747283e-01
-2.05283952e+00 -1.01441419e+00 -2.14097321e-01 2.62011385e+00
4.17327404e-01 4.21114624e-01 2.02662960e-01 3.13275754e-01
8.55454862e-01 -2.97396153e-01 -5.73699832e-01 -9.33210492e-01
6.01447642e-01 -3.41789067e-01 9.71070647e-01 5.13667703e-01
-1.06561351e+00 3.97861689e-01 5.90221071e+00 6.43331051e-01
-9.33634877e-01 -1.50246978e-01 3.58362585e-01 -5.41134663e-02
3.82941365e-01 3.79806101e-01 -6.84168696e-01 4.85870928e-01
1.29999292e+00 -5.87408356e-02 5.67336380e-01 7.64660597e-01
5.99852443e-01 -6.96835220e-01 -9.88523841e-01 4.42264855e-01
-5.43014109e-01 -7.17996895e-01 -9.45917904e-01 5.56760907e-01
4.84634846e-01 -1.26109526e-01 -4.61432904e-01 2.32099235e-01
5.02522826e-01 -7.78173923e-01 9.19933796e-01 7.20576763e-01
3.24186236e-01 -1.24318290e+00 6.82590008e-01 1.11303198e+00
-1.00372696e+00 -3.62255991e-01 -2.77100772e-01 -1.58010453e-01
3.69064510e-01 2.75911719e-01 -1.08242953e+00 5.06831586e-01
2.76573509e-01 5.33696450e-02 4.92580496e-02 1.23087287e+00
-1.00393459e-01 2.71505415e-01 -6.68576658e-01 -4.58621413e-01
6.24433756e-01 -5.14350355e-01 7.26286232e-01 1.00645912e+00
4.02166188e-01 1.62144840e-01 3.88803303e-01 5.45322239e-01
8.80448163e-01 -9.54946056e-02 -9.15273011e-01 1.49396315e-01
2.53596246e-01 9.92355108e-01 -9.88332093e-01 -2.38689944e-01
-1.26304820e-01 6.79290771e-01 1.40136490e-02 2.33402967e-01
-6.43984497e-01 -7.60482132e-01 6.45513833e-01 3.57510298e-02
5.10134697e-01 -5.58986127e-01 1.71708778e-01 -3.52675170e-01
-1.00006172e-02 -6.58097804e-01 1.06963128e-01 -5.64565778e-01
-4.95645165e-01 2.42556840e-01 3.89099151e-01 -1.22059333e+00
-8.68914723e-01 -3.85718822e-01 -4.38597023e-01 1.07732487e+00
-1.04613113e+00 -2.05080420e-01 4.53148067e-01 3.93176347e-01
4.38434422e-01 -7.53592933e-03 5.85909724e-01 -2.47518569e-01
-4.37661856e-01 -3.70075852e-01 3.49967837e-01 -2.88524181e-01
2.84192353e-01 -1.29776108e+00 -3.17012258e-02 7.18098521e-01
-3.51789773e-01 4.34942484e-01 1.34639025e+00 -7.04785645e-01
-1.54635072e+00 -9.00265455e-01 7.77650476e-01 -3.11107278e-01
8.09851825e-01 -2.16033384e-01 -9.04379129e-01 4.90173131e-01
-1.42614335e-01 -2.60411024e-01 -1.52445093e-01 -7.79994354e-02
7.59992599e-01 -2.02626772e-02 -9.79069829e-01 6.38315618e-01
3.66476476e-01 -1.03718467e-01 -5.80599368e-01 2.43370116e-01
1.78203404e-01 -4.08191919e-01 -7.92808294e-01 2.88780093e-01
3.25759679e-01 -6.45744324e-01 6.14974558e-01 -2.89802104e-01
-3.83717954e-01 -6.23562515e-01 2.69167513e-01 -1.57732630e+00
-3.77419561e-01 -9.27139163e-01 1.18099377e-01 8.20823193e-01
1.30656168e-01 -6.33934498e-01 5.66207230e-01 6.27486527e-01
-1.39025412e-03 -8.97189736e-01 -1.33986104e+00 -7.70298958e-01
-2.63590574e-01 -6.39816761e-01 5.00623703e-01 4.00305033e-01
-2.90328376e-02 2.71024078e-01 -2.59410828e-01 4.87147123e-01
4.49931890e-01 -1.12707414e-01 9.73554552e-01 -1.15143728e+00
-3.11555177e-01 -3.85351658e-01 -4.81993288e-01 -8.66077840e-01
2.22784847e-01 -3.68085682e-01 6.69839144e-01 -1.41821730e+00
-4.33374226e-01 -6.70558214e-01 5.56168705e-03 1.35961488e-01
2.33732522e-01 -6.56806946e-01 1.27913192e-01 2.28946060e-01
-4.04642314e-01 2.83634782e-01 1.32441115e+00 1.13027811e-01
-3.61814201e-01 6.30743563e-01 -1.61255404e-01 5.72639227e-01
7.41548777e-01 -6.17206156e-01 -6.08646989e-01 1.39844641e-01
1.58610716e-01 6.29213870e-01 1.72370464e-01 -9.99140561e-01
5.13262987e-01 -5.87519765e-01 1.51647627e-01 -3.95369053e-01
4.63896722e-01 -1.25968337e+00 5.57430148e-01 6.96542561e-01
-3.39604974e-01 2.00580731e-01 1.02800906e-01 7.87914336e-01
4.49696742e-03 -7.31341600e-01 7.86922157e-01 -3.49050127e-02
-5.64343750e-01 1.72817800e-02 -8.88991773e-01 -6.67760313e-01
1.41725838e+00 -3.61695409e-01 4.84975398e-01 -2.95719922e-01
-9.23355997e-01 6.06140673e-01 5.17289042e-01 2.40099624e-01
2.52195716e-01 -9.85833347e-01 -4.16970193e-01 2.73467600e-01
-3.38573083e-02 1.46077856e-01 -1.32242426e-01 8.63285303e-01
-3.56474936e-01 6.80084407e-01 -8.90620239e-03 -6.68223262e-01
-1.02716970e+00 8.36172819e-01 5.09705782e-01 -3.13753873e-01
-6.64312541e-01 2.68694878e-01 -9.86626968e-02 -3.22188437e-01
3.24289761e-02 -2.41205469e-01 -4.27511752e-01 -5.36154807e-02
4.12304372e-01 3.79932374e-01 1.26984745e-01 -7.78626680e-01
-1.35292247e-01 4.15964752e-01 1.95466816e-01 -5.31625032e-01
1.16908371e+00 -2.88317651e-01 6.36005551e-02 6.45609081e-01
9.84495759e-01 -3.76691580e-01 -1.63140893e+00 -6.03906177e-02
2.74573475e-01 -4.57346767e-01 2.30798796e-01 -4.65096802e-01
-6.01117909e-01 3.65044445e-01 5.02131045e-01 6.30458772e-01
9.25471783e-01 -1.91712543e-01 1.31349012e-01 5.25713384e-01
5.67998469e-01 -1.31754863e+00 -4.10835117e-01 5.93715489e-01
7.20008910e-01 -8.76206875e-01 -1.82535052e-02 1.68843456e-02
-8.24176610e-01 1.18465781e+00 1.26318872e-01 -1.26349166e-01
4.76128519e-01 2.29573384e-01 -2.01454639e-01 -1.81790173e-01
-9.00711477e-01 -2.29196027e-01 6.65906966e-02 2.76930600e-01
-8.53828862e-02 1.59662992e-01 -3.07864875e-01 -4.32795107e-01
-3.99510153e-02 -9.17809084e-02 4.27410603e-01 1.35620904e+00
-7.97752440e-01 -1.08460712e+00 -8.61846089e-01 2.90049672e-01
-3.02751899e-01 7.88333595e-01 -1.82996374e-02 8.47792387e-01
3.48959640e-02 1.10602725e+00 1.83138207e-01 1.67908728e-01
7.37603605e-01 2.04643399e-01 2.97558695e-01 -5.37915468e-01
-1.40970707e-01 3.16855222e-01 3.42903048e-01 -6.26865566e-01
-1.88660756e-01 -1.17568278e+00 -1.30373752e+00 -1.16964258e-01
-4.20713246e-01 6.09075904e-01 1.18835890e+00 1.16196167e+00
-4.48269844e-02 5.56479633e-01 8.57398093e-01 -1.10530579e+00
-7.20500648e-01 -7.99347520e-01 -6.88764155e-01 -3.67676243e-02
4.29321468e-01 -9.16522682e-01 -2.51894325e-01 -1.58383697e-01] | [4.8166823387146, 1.826172947883606] |
c1bbc701-93d5-4961-8b32-5967031acb52 | video-language-co-attention-with-multimodal | null | null | https://aclanthology.org/2022.repl4nlp-1.15 | https://aclanthology.org/2022.repl4nlp-1.15.pdf | Video Language Co-Attention with Multimodal Fast-Learning Feature Fusion for VideoQA | We propose the Video Language Co-Attention Network (VLCN) – a novel memory-enhanced model for Video Question Answering (VideoQA). Our model combines two original contributions”:" A multi-modal fast-learning feature fusion (FLF) block and a mechanism that uses self-attended language features to separately guide neural attention on both static and dynamic visual features extracted from individual video frames and short video clips. When trained from scratch, VLCN achieves competitive results with the state of the art on both MSVD-QA and MSRVTT-QA with 38.06% and 36.01% test accuracies, respectively. Through an ablation study, we further show that FLF improves generalization across different VideoQA datasets and performance for question types that are notoriously challenging in current datasets, such as long questions that require deeper reasoning as well as questions with rare answers. | ['Andreas Bulling', 'Ekta Sood', 'Adnen Abdessaied'] | null | null | null | null | repl4nlp-acl-2022-5 | ['video-question-answering'] | ['computer-vision'] | [-1.20867290e-01 -3.50990444e-01 -3.24681103e-02 -2.83056468e-01
-1.28823924e+00 -6.68342173e-01 4.46974069e-01 -1.83711186e-01
-6.88965082e-01 4.15982187e-01 5.10268152e-01 -2.64948308e-01
3.87565419e-02 -4.18162584e-01 -9.35902655e-01 -2.76210308e-01
1.50854036e-01 1.82113707e-01 2.63478309e-01 -2.96171218e-01
-1.96872447e-02 2.47287322e-02 -1.67604733e+00 1.10222912e+00
6.43345177e-01 1.14332294e+00 1.53561860e-01 1.13870788e+00
-3.73550713e-01 1.74021101e+00 -6.32614732e-01 -6.12276375e-01
-1.11078531e-01 -4.45440024e-01 -1.29780781e+00 -3.19462195e-02
1.19763875e+00 -8.73677552e-01 -1.05382955e+00 6.08777702e-01
4.11133230e-01 5.65899432e-01 3.79927397e-01 -1.11907482e+00
-1.20233655e+00 1.22954443e-01 -2.54805833e-01 8.78594875e-01
9.04280841e-01 5.08074224e-01 1.11135089e+00 -1.15830755e+00
8.17458272e-01 1.56194723e+00 4.50325727e-01 7.11154580e-01
-7.95830727e-01 -3.81574214e-01 4.79092985e-01 1.06523180e+00
-9.90696251e-01 -4.13528472e-01 5.39828241e-01 -3.73036414e-01
1.41332102e+00 2.26960003e-01 4.13903773e-01 1.42832458e+00
2.75181234e-01 1.41470790e+00 5.95657706e-01 -4.85449545e-02
2.71494593e-03 -2.71305382e-01 3.00331503e-01 8.95767570e-01
-4.35745358e-01 -3.59439224e-01 -7.82668114e-01 2.22781533e-03
4.29606706e-01 1.23174135e-02 -4.64806587e-01 -4.06057462e-02
-1.24563754e+00 1.01991558e+00 4.06084120e-01 2.86766052e-01
-4.01067764e-01 2.64521688e-01 4.78671223e-01 6.60351634e-01
2.29673982e-01 3.40844125e-01 -5.29799700e-01 -3.62495691e-01
-8.04782629e-01 3.93435538e-01 5.34953356e-01 8.57440233e-01
5.24123430e-01 1.28400549e-01 -7.39988804e-01 6.61087155e-01
9.92785692e-02 7.38995492e-01 5.26065111e-01 -1.41794097e+00
6.05471969e-01 6.25275195e-01 -2.76468825e-02 -9.53812659e-01
-3.34201008e-01 -5.93979917e-02 -5.08506596e-01 -3.72545123e-01
5.16278625e-01 -9.30965096e-02 -1.12307513e+00 1.79526663e+00
-2.62644514e-02 1.60479680e-01 1.28025338e-01 1.05556989e+00
1.72581196e+00 1.02551556e+00 3.88847262e-01 -4.01163734e-02
1.45551872e+00 -1.45305932e+00 -8.64072978e-01 -2.16043189e-01
5.11066735e-01 -4.20561165e-01 1.56272054e+00 3.03148597e-01
-1.38831544e+00 -8.12116146e-01 -6.00327730e-01 -6.89447343e-01
-3.63711506e-01 -3.79183330e-02 5.41446984e-01 1.92088902e-01
-1.41332138e+00 -8.31188560e-02 -4.62033898e-01 -3.15555274e-01
6.05581820e-01 2.28414893e-01 -4.20279980e-01 -6.67302608e-01
-1.24438715e+00 7.21934557e-01 -1.44754276e-01 -5.80086000e-02
-1.42571425e+00 -8.37592304e-01 -9.05115187e-01 2.20457427e-02
7.22516179e-01 -9.59390461e-01 1.47457385e+00 -1.38976610e+00
-1.26590848e+00 7.97984242e-01 -5.83148718e-01 -5.17666698e-01
2.11217701e-01 -7.23007917e-01 -6.01906538e-01 1.01905775e+00
2.83451676e-02 1.03674209e+00 1.06582212e+00 -7.10993290e-01
-3.94164383e-01 -1.46390274e-01 7.37359226e-01 1.71919078e-01
-3.15226972e-01 1.30863443e-01 -7.58401513e-01 -5.87441444e-01
-4.44872320e-01 -5.51113605e-01 9.65881124e-02 1.34442197e-02
2.68198967e-01 -5.69256365e-01 1.25597668e+00 -1.18680692e+00
1.07556498e+00 -2.12158680e+00 4.63726759e-01 -3.83526921e-01
3.42030346e-01 4.13515329e-01 -7.38185763e-01 1.55527100e-01
1.63937435e-02 -9.19626206e-02 1.04098782e-01 -9.48605090e-02
-2.78717637e-01 1.49495751e-01 -3.40565026e-01 1.63017794e-01
6.15335464e-01 1.53537810e+00 -9.28786814e-01 -5.26653647e-01
-4.02822271e-02 5.66324294e-01 -8.43886495e-01 5.13528645e-01
-6.76247180e-01 2.47351483e-01 -2.57854491e-01 8.93700957e-01
3.53606641e-01 -6.73761189e-01 -1.96710885e-01 -4.19319957e-01
3.73323500e-01 -1.03796981e-01 -6.41655743e-01 2.18753242e+00
-2.68463135e-01 9.08019781e-01 1.19648084e-01 -8.12978923e-01
4.79100376e-01 4.52263296e-01 3.29381019e-01 -1.07853770e+00
1.23715915e-01 -4.18960661e-01 -3.37089807e-01 -1.17232609e+00
5.25002122e-01 4.18090731e-01 1.14536166e-01 2.79668808e-01
7.77320445e-01 2.59676993e-01 4.13984150e-01 7.41949558e-01
1.41419935e+00 1.99846327e-01 -3.18969823e-02 -2.19894145e-02
9.42788601e-01 -2.68821288e-02 1.85037017e-01 8.12626004e-01
-5.77273309e-01 5.28206766e-01 5.54030836e-01 -4.97193247e-01
-6.06476665e-01 -1.15623403e+00 5.12352049e-01 1.71121204e+00
-4.06789891e-02 -5.81324220e-01 -5.86019337e-01 -1.10541439e+00
-1.04153212e-02 5.66918552e-01 -7.61487186e-01 -4.06709522e-01
-4.96707201e-01 -6.44045770e-02 3.76846343e-01 6.95551157e-01
6.21261418e-01 -1.25303876e+00 -5.38828969e-01 -4.39403877e-02
-6.41967833e-01 -1.44873631e+00 -4.95943040e-01 -3.69674772e-01
-5.19730389e-01 -1.15941572e+00 -9.40875947e-01 -9.01222289e-01
2.67340779e-01 5.35764635e-01 1.58339047e+00 2.41612703e-01
-1.21658936e-01 1.34579325e+00 -6.46571040e-01 5.54983132e-03
9.48606133e-02 -1.64163679e-01 -3.43497664e-01 2.01012865e-01
5.61681032e-01 -1.50439620e-01 -5.70905626e-01 1.96931168e-01
-8.62626135e-01 -2.14569151e-01 4.68639672e-01 8.61313045e-01
5.20842791e-01 -6.48269892e-01 6.90099359e-01 -4.19064343e-01
6.14268363e-01 -7.42910326e-01 -2.35673502e-01 5.63300371e-01
6.99855611e-02 -1.48925409e-01 5.11516511e-01 -5.63542545e-01
-1.21021867e+00 -4.08940434e-01 -1.67185917e-01 -1.02680647e+00
-2.92944878e-01 4.17905986e-01 -1.14256464e-01 -6.14897581e-03
4.24539626e-01 2.63949275e-01 2.61713304e-02 -2.53125727e-01
5.61986506e-01 2.68437147e-01 8.71439576e-01 -3.72811615e-01
3.92586261e-01 4.73936617e-01 -4.64763761e-01 -8.01135778e-01
-9.78008330e-01 -5.51901937e-01 -4.01727021e-01 -4.88537043e-01
1.37813938e+00 -1.23296881e+00 -1.02076411e+00 2.63677448e-01
-1.21495986e+00 -4.36421782e-01 -1.22077852e-01 3.00469697e-01
-5.95069289e-01 4.26951319e-01 -9.26908195e-01 -6.44760609e-01
-4.33098197e-01 -1.12756789e+00 1.02723408e+00 3.23723227e-01
-2.90025584e-02 -8.40353787e-01 -1.67837813e-01 1.02773762e+00
4.85440761e-01 -4.06601727e-02 8.37811768e-01 -6.15253031e-01
-8.38247478e-01 1.50547475e-01 -4.17185545e-01 3.30278039e-01
-4.06045556e-01 -5.33646345e-02 -9.86873984e-01 -4.31213856e-01
-4.18445580e-02 -1.08176625e+00 1.25833476e+00 3.37820023e-01
1.51599383e+00 -1.45881325e-01 1.76780716e-01 4.76123214e-01
1.15001392e+00 2.49395728e-01 6.76644742e-01 1.02485798e-01
7.64718115e-01 4.38610196e-01 5.39312363e-01 1.24392003e-01
7.76060998e-01 3.94757569e-01 5.14526725e-01 1.27601221e-01
-4.27137315e-01 -3.15982103e-02 7.32529640e-01 8.56987596e-01
1.20827548e-01 -4.57508117e-01 -9.52120006e-01 8.15067053e-01
-1.85232341e+00 -1.28647256e+00 -6.39605820e-02 1.52298665e+00
4.06538874e-01 -2.99373269e-01 2.90869117e-01 -1.20656818e-01
3.32114518e-01 3.40527326e-01 -6.60364807e-01 -3.26828659e-01
-4.13861036e-01 2.02887893e-01 -2.58354068e-01 3.64225507e-01
-1.22530890e+00 8.62979829e-01 6.53315592e+00 6.51245773e-01
-8.11156392e-01 4.23573196e-01 4.89176512e-01 -4.63116765e-01
-4.12571520e-01 -3.99962962e-01 -4.31871921e-01 1.96663529e-01
1.25934029e+00 9.34486315e-02 3.82052571e-01 5.65492034e-01
-2.37820014e-01 -1.52758852e-01 -8.69286299e-01 1.26023793e+00
7.81963229e-01 -1.61382985e+00 5.27199388e-01 -6.90738916e-01
5.86224854e-01 1.46052375e-01 2.85018355e-01 7.79516697e-01
1.00614354e-01 -1.04470944e+00 6.53812170e-01 7.36415982e-01
7.94275284e-01 -7.40602314e-01 7.29480088e-01 2.56020222e-02
-1.15062535e+00 -5.86035907e-01 -2.00174481e-01 -3.94499339e-02
1.93366662e-01 -8.63452554e-02 -1.35381356e-01 6.12904549e-01
1.18730998e+00 9.71647024e-01 -1.01577711e+00 8.50496113e-01
-2.89157797e-02 8.14749241e-01 1.77455083e-01 3.28320265e-02
5.26075363e-01 4.43783671e-01 3.92421037e-01 1.11616528e+00
-6.08835311e-04 2.65743285e-01 1.15658559e-01 5.49322128e-01
-1.76420942e-01 1.06241673e-01 -3.08258861e-01 -2.32914954e-01
-4.13039327e-02 1.09805536e+00 -2.56876707e-01 -5.72780073e-01
-9.47572887e-01 1.03096366e+00 5.69356441e-01 8.87828529e-01
-9.72037435e-01 -1.97193250e-01 6.99005485e-01 -2.54934967e-01
6.65623724e-01 -1.67282641e-01 4.14308131e-01 -1.65007877e+00
-1.39416549e-02 -1.22014010e+00 1.12781155e+00 -1.20881557e+00
-1.33177698e+00 7.13367999e-01 -6.92942515e-02 -9.88607168e-01
-3.50694567e-01 -7.39308119e-01 -3.85036081e-01 3.52411002e-01
-1.74923289e+00 -1.25116289e+00 -5.81056237e-01 1.37662959e+00
9.93274152e-01 -4.10634726e-01 7.79131114e-01 5.06306767e-01
-5.47837257e-01 7.72409320e-01 -2.36964107e-01 3.16591829e-01
7.07858920e-01 -9.02012169e-01 1.76235363e-01 8.45501006e-01
3.45888555e-01 1.96796566e-01 2.09842771e-01 -3.62013668e-01
-1.81463790e+00 -1.04877543e+00 7.07126379e-01 -7.72065997e-01
5.84077299e-01 -2.48668537e-01 -1.12855482e+00 8.16339910e-01
6.55487418e-01 1.55912265e-01 6.84009254e-01 -1.68721154e-01
-7.32369900e-01 1.31491115e-02 -9.54432130e-01 4.44853634e-01
1.03886414e+00 -1.12535882e+00 -8.35565090e-01 4.35418844e-01
1.13141334e+00 -2.39000022e-01 -7.74063945e-01 3.26607525e-01
3.50111037e-01 -9.11264300e-01 1.14702392e+00 -1.14707589e+00
5.95534682e-01 3.05860341e-02 -4.65647578e-01 -6.71903312e-01
-5.39804757e-01 -6.20798886e-01 -7.41141260e-01 9.93425012e-01
1.51712656e-01 -2.02288628e-02 5.64351141e-01 2.20530987e-01
-7.45471939e-02 -6.45666122e-01 -9.48674917e-01 -4.43394899e-01
-3.61556956e-03 -6.58301294e-01 2.54701734e-01 8.39784145e-01
-2.58636296e-01 5.79166234e-01 -4.46867257e-01 -8.93365070e-02
2.01503545e-01 1.18092515e-01 6.89513803e-01 -7.39236712e-01
-2.21256599e-01 -3.07633847e-01 -3.26580197e-01 -1.28199816e+00
5.45376122e-01 -7.87150502e-01 -2.12599978e-01 -1.54657638e+00
3.78292114e-01 6.40111864e-01 -3.51338893e-01 3.29013020e-01
-3.36548060e-01 2.06360146e-01 4.23152328e-01 -1.38876975e-01
-1.50654638e+00 6.46651387e-01 1.34857130e+00 -3.94229323e-01
1.63671359e-01 -5.76490998e-01 -5.06667316e-01 5.82138062e-01
3.49981099e-01 3.24128605e-02 -5.52349746e-01 -1.05488038e+00
8.33473802e-02 3.97495747e-01 6.70303643e-01 -9.43615079e-01
1.05684966e-01 -4.16906327e-02 4.71903861e-01 -8.56119990e-01
5.43921709e-01 -6.02360666e-01 -4.64046866e-01 2.46280327e-01
-6.42800152e-01 5.82745314e-01 4.38618273e-01 7.70729125e-01
-4.00372207e-01 2.90086329e-01 3.03074688e-01 -1.20155439e-01
-1.48986185e+00 3.82303864e-01 -5.24127841e-01 5.30836225e-01
9.85239446e-01 1.21461250e-01 -8.47850323e-01 -1.09705949e+00
-7.98355818e-01 6.24631286e-01 -1.05222113e-01 9.57689285e-01
1.03997326e+00 -1.45303106e+00 -8.70856464e-01 1.41151352e-02
3.04448217e-01 -3.42310369e-01 9.13835347e-01 9.50463474e-01
-3.17119300e-01 7.46210337e-01 -3.01355511e-01 -7.06500649e-01
-1.20441580e+00 9.10373628e-01 2.79350519e-01 -9.87788215e-02
-4.16624308e-01 1.43367279e+00 1.82371676e-01 -1.37632355e-01
3.93506080e-01 -3.13165516e-01 -5.18652856e-01 2.43790492e-01
8.96968901e-01 3.09527546e-01 -7.26520047e-02 -9.26587999e-01
-5.06641150e-01 4.32223201e-01 -2.58210003e-01 1.75254881e-01
1.05704355e+00 -3.38426232e-01 2.49918520e-01 4.02205646e-01
1.36641133e+00 -4.72796202e-01 -1.30526841e+00 -4.77245361e-01
-3.05011868e-01 -4.10015672e-01 2.01219860e-02 -9.96407151e-01
-1.18020010e+00 1.06408882e+00 6.62172854e-01 -1.77204996e-01
1.21643698e+00 3.71167034e-01 1.05210638e+00 7.32730508e-01
-1.61685094e-01 -8.92053843e-01 8.60556722e-01 7.58009911e-01
1.20385230e+00 -1.37122130e+00 -3.12145740e-01 8.19121227e-02
-7.94194698e-01 9.58605409e-01 1.03304231e+00 -1.14280209e-01
4.10246462e-01 -2.55127996e-01 2.55517989e-01 -2.56528825e-01
-1.43433356e+00 -3.49579901e-01 7.96602666e-01 5.09296775e-01
2.88007230e-01 -4.44139212e-01 5.91466352e-02 8.89951706e-01
2.12353647e-01 1.65878534e-01 2.98204958e-01 9.94895339e-01
-2.57162094e-01 -4.38710332e-01 -2.30684862e-01 5.61832488e-01
-5.18652678e-01 -5.71234152e-03 -2.90780067e-01 7.44179308e-01
3.11655141e-02 1.21223187e+00 4.31444049e-01 -6.30628109e-01
2.96442270e-01 3.71560872e-01 4.74751502e-01 -2.63481647e-01
-7.66821265e-01 -2.20197976e-01 1.92503855e-01 -1.22166872e+00
-6.99331224e-01 -5.93965828e-01 -1.06340194e+00 -2.12891996e-01
2.59975363e-02 -1.55292777e-02 2.32499558e-02 1.13799822e+00
6.19402289e-01 6.73301578e-01 6.08008318e-02 -4.98969167e-01
-3.11491519e-01 -6.38045251e-01 -4.34375880e-03 6.72445118e-01
6.56213224e-01 -6.72022760e-01 -1.89025015e-01 1.81407303e-01] | [10.40866470336914, 1.0262707471847534] |
43e2f2a0-c944-4137-9f33-88af9cdd8caa | gessure-a-robust-face-authentication-enabled | 2207.11033 | null | https://arxiv.org/abs/2207.11033v2 | https://arxiv.org/pdf/2207.11033v2.pdf | GesSure- A Robust Face-Authentication enabled Dynamic Gesture Recognition GUI Application | Using physical interactive devices like mouse and keyboards hinders naturalistic human-machine interaction and increases the probability of surface contact during a pandemic. Existing gesture-recognition systems do not possess user authentication, making them unreliable. Static gestures in current gesture-recognition technology introduce long adaptation periods and reduce user compatibility. Our technology places a strong emphasis on user recognition and safety. We use meaningful and relevant gestures for task operation, resulting in a better user experience. This paper aims to design a robust, face-verification-enabled gesture recognition system that utilizes a graphical user interface and primarily focuses on security through user recognition and authorization. The face model uses MTCNN and FaceNet to verify the user, and our LSTM-CNN architecture for gesture recognition, achieving an accuracy of 95% with five classes of gestures. The prototype developed through our research has successfully executed context-dependent tasks like save, print, control video-player operations and exit, and context-free operating system tasks like sleep, shut-down, and unlock intuitively. Our application and dataset are available as open source. | ['Piyush Modi', 'Ayush Batra', 'Pratham G. Shenwai', 'Ishita', 'Siddharth Kotian', 'Ankit Jha'] | 2022-07-22 | null | null | null | null | ['gesture-recognition', 'face-model'] | ['computer-vision', 'computer-vision'] | [ 1.96651667e-01 -4.97695506e-01 -3.71937424e-01 -4.68178749e-01
2.09007189e-02 -5.63155353e-01 5.59966981e-01 -6.49502218e-01
-9.46626842e-01 2.32937858e-01 -7.97122121e-02 -7.99397409e-01
-3.92862409e-02 -3.54459673e-01 7.63487220e-02 -6.28267407e-01
-2.30444726e-02 3.53465192e-02 -6.94209859e-02 -1.49282683e-02
2.89618850e-01 1.03110039e+00 -1.46219182e+00 2.70602107e-01
-1.34704545e-01 1.00154042e+00 -1.48064464e-01 1.01909935e+00
-5.54067269e-02 4.29296881e-01 -8.67631614e-01 -1.09820431e-02
2.56984323e-01 -1.79739431e-01 -7.09540188e-01 -4.44651306e-01
-7.52352774e-02 -1.25947762e+00 -2.92570829e-01 5.24607718e-01
8.84965062e-01 3.09000820e-01 2.85444111e-01 -1.51283324e+00
-6.23676777e-01 -1.46864392e-02 -2.63078779e-01 -6.15270957e-02
7.40362346e-01 4.91936177e-01 2.61015266e-01 -5.70476830e-01
2.21741721e-01 1.11174083e+00 6.04694426e-01 1.44746137e+00
-5.61939240e-01 -1.17042458e+00 -1.30148292e-01 4.77464907e-02
-1.68314540e+00 -6.66368783e-01 2.73217082e-01 -2.39874482e-01
1.49882340e+00 6.30323470e-01 3.68439645e-01 1.47036839e+00
-3.66298147e-02 4.66440588e-01 7.24641442e-01 -5.49948752e-01
1.06241874e-01 -2.33473361e-01 2.76774049e-01 6.35758102e-01
7.93280452e-02 2.72371560e-01 -6.13261402e-01 -1.66576937e-01
1.21799850e+00 8.33197534e-01 -3.53954017e-01 3.47654909e-01
-1.08915067e+00 7.34476894e-02 1.64734945e-01 8.14583361e-01
-4.05328155e-01 2.60864142e-02 1.42818570e-01 2.63190776e-01
-3.01003456e-01 9.90750454e-03 -5.45868456e-01 -6.74234509e-01
-7.69068837e-01 -5.15142739e-01 1.05374444e+00 8.49706054e-01
-6.64454773e-02 -3.52510959e-02 -1.65363774e-01 3.22569966e-01
5.26961505e-01 8.18595767e-01 7.03074694e-01 -4.57383037e-01
5.96082397e-02 6.44537866e-01 2.58127183e-01 -7.41568565e-01
-6.88667536e-01 7.18076229e-01 -7.14033961e-01 5.62114775e-01
4.22854245e-01 -2.60816902e-01 -1.26682973e+00 1.38243699e+00
1.81808203e-01 3.42467457e-01 -3.44159514e-01 8.51208389e-01
9.72992063e-01 6.49847463e-02 4.99241978e-01 -8.49964619e-02
1.46558630e+00 -4.59377825e-01 -9.82588410e-01 3.38970214e-01
3.72267753e-01 -7.66466975e-01 1.39994514e+00 4.51560229e-01
-4.48033065e-01 -3.94531757e-01 -9.00868177e-01 2.74904788e-01
-6.45566463e-01 2.15128362e-01 7.10475981e-01 1.48134017e+00
-1.18688321e+00 4.07084405e-01 -1.34917140e+00 -8.97599101e-01
3.05777758e-01 1.04219830e+00 -5.69115877e-01 4.41389441e-01
-6.59488022e-01 8.87416124e-01 3.91572341e-02 4.19702202e-01
-4.13458556e-01 8.94445181e-02 -7.45463729e-01 -6.25453005e-03
1.22711763e-01 -1.98750719e-01 1.28834307e+00 -6.24360740e-01
-1.96954525e+00 7.84689248e-01 -4.30303991e-01 1.31225422e-01
4.27956581e-01 -4.51195151e-01 -9.87902403e-01 -5.01615629e-02
-6.09860301e-01 4.67679709e-01 9.01624203e-01 -7.22425044e-01
-3.74415457e-01 -4.63680625e-01 -1.56877637e-01 -3.66755165e-02
-6.94288194e-01 6.70650065e-01 -5.49157798e-01 -2.27593452e-01
-1.61191732e-01 -7.33850479e-01 3.38160425e-01 -1.77240167e-02
-2.13926136e-01 -2.00335026e-01 1.20141470e+00 -7.37337530e-01
1.44221520e+00 -2.00104332e+00 -6.28935218e-01 4.18893069e-01
6.36099949e-02 8.07506800e-01 -1.90210804e-01 2.34632090e-01
7.51902387e-02 3.37060988e-01 1.09614350e-01 -1.49686500e-01
-3.31291482e-02 2.56264359e-01 -1.29165545e-01 3.64228517e-01
-1.73606034e-02 9.73373055e-01 -5.69161415e-01 -2.82011688e-01
6.05239391e-01 8.15740228e-01 -3.25221390e-01 4.41267818e-01
5.40308237e-01 6.43518388e-01 -4.57727253e-01 1.22127032e+00
4.55115825e-01 -2.55769826e-02 3.92300665e-01 2.24441558e-01
-1.05327077e-01 1.49498194e-01 -1.03602922e+00 1.33104396e+00
-4.73105282e-01 6.59038067e-01 2.56510705e-01 -1.70956433e-01
6.70424223e-01 6.67799830e-01 3.72359604e-01 -7.25737393e-01
6.05640650e-01 3.85303572e-02 -7.65757337e-02 -1.17722702e+00
2.31025904e-01 2.55588293e-01 3.91013771e-01 8.21807563e-01
-3.35103631e-01 3.99575800e-01 -5.09303272e-01 -4.23382670e-01
1.13236785e+00 4.67364192e-01 3.47341657e-01 3.90820771e-01
4.44893211e-01 -5.41706800e-01 3.80765903e-03 7.21447051e-01
-6.22605443e-01 1.56175181e-01 -1.05911940e-01 -6.39949560e-01
-3.29988956e-01 -8.45236123e-01 2.64637560e-01 1.58054280e+00
-1.58849478e-01 -9.75397229e-02 -8.64457428e-01 -7.53117442e-01
-2.93864071e-01 4.14238781e-01 -3.38433444e-01 5.98618612e-02
-9.11939085e-01 -3.86288702e-01 1.12672210e+00 8.00223410e-01
5.66522539e-01 -1.60134935e+00 -1.29479814e+00 -9.08028185e-02
1.05794035e-01 -7.45534718e-01 -5.49409151e-01 -2.58075166e-02
-6.76944554e-01 -1.47093630e+00 -6.93304181e-01 -8.36091578e-01
7.87288964e-01 1.48091227e-01 4.14861262e-01 6.68017924e-01
-4.23289984e-01 5.59309781e-01 -3.24178308e-01 -3.91886771e-01
1.40435547e-01 -6.12665340e-02 6.44418955e-01 -5.66950068e-02
1.28052437e+00 -2.79082090e-01 -4.79304522e-01 6.72804177e-01
-8.10142159e-01 -5.26809931e-01 3.70287985e-01 7.98685968e-01
-1.92590266e-01 -5.37532628e-01 1.28560692e-01 -7.95807019e-02
9.63876128e-01 3.05814911e-02 -2.64291823e-01 6.11391544e-01
-5.88381171e-01 -3.96326929e-01 1.19297504e-01 -7.85601497e-01
-9.48826432e-01 1.80169344e-01 -3.26397806e-01 -2.89389282e-01
-8.21050167e-01 -1.27706215e-01 -3.08160305e-01 -3.64683151e-01
5.60472250e-01 2.32477501e-01 1.37568906e-01 -4.93976265e-01
-4.68969755e-02 1.56004047e+00 4.58018929e-01 -1.87852815e-01
4.39948708e-01 4.17988926e-01 -5.09873867e-01 -1.18595755e+00
3.33460957e-01 -6.56902730e-01 -9.41313505e-01 -4.41960275e-01
7.58971632e-01 -4.26509589e-01 -1.90490127e+00 1.00228274e+00
-1.22895610e+00 -5.62682390e-01 4.29456323e-01 6.35659873e-01
3.49118598e-02 2.96974987e-01 -5.37175894e-01 -1.42519331e+00
-6.03374004e-01 -8.79269242e-01 1.04619527e+00 4.32751656e-01
-7.17190087e-01 -5.53303659e-01 -3.11522037e-01 6.67175427e-02
7.87664175e-01 1.14902072e-01 3.04405034e-01 -8.37678432e-01
-1.81795746e-01 -5.53316712e-01 -2.39573777e-01 8.44624490e-02
6.49021864e-01 1.93456799e-01 -1.23283339e+00 -3.47791016e-01
1.50601156e-02 -1.37893602e-01 3.48953098e-01 1.82981282e-01
1.15622878e+00 -3.63450497e-01 -6.66047156e-01 6.57262146e-01
7.81976104e-01 9.19312239e-01 7.67583847e-01 1.89755917e-01
6.99346423e-01 4.81997311e-01 1.55272037e-01 3.83511603e-01
1.51374070e-02 5.98819315e-01 1.47083208e-01 -1.09269157e-01
3.21990341e-01 -2.50119288e-02 4.85702902e-01 3.32736045e-01
-5.73320389e-01 -2.82957196e-01 -1.14392114e+00 3.68028395e-02
-1.51279235e+00 -9.08052921e-01 6.72391653e-02 2.23679900e+00
5.65656662e-01 -3.02977681e-01 1.91120267e-01 1.20604888e-01
7.87668467e-01 -2.50194877e-01 -5.10949433e-01 -3.61258358e-01
5.15606225e-01 7.95520544e-01 4.24812883e-01 4.96476054e-01
-1.23180366e+00 9.80932117e-01 6.73631001e+00 3.07918310e-01
-1.69925928e+00 1.60841167e-01 2.67316639e-01 -5.60522735e-01
5.13136983e-01 -8.77685964e-01 -6.02764070e-01 3.00242066e-01
9.17138577e-01 7.19320714e-01 6.87895536e-01 8.46814573e-01
3.71017903e-01 4.10193764e-03 -1.24504232e+00 1.40288007e+00
1.30816996e-01 -8.98498476e-01 -1.07844934e-01 1.08765826e-01
-1.41167819e-01 -1.24096602e-01 -4.19478342e-02 2.38972187e-01
-1.65256798e-01 -1.55483675e+00 2.90871471e-01 3.99568349e-01
1.62708950e+00 -4.48209345e-01 7.04171896e-01 1.62111238e-01
-1.08506298e+00 -1.35350421e-01 3.57841820e-01 -4.28976357e-01
7.03435093e-02 -6.34315372e-01 -1.05971873e+00 -2.06367031e-01
9.23375845e-01 -1.00517944e-01 -1.68526605e-01 5.51490366e-01
-2.56621152e-01 3.76691222e-01 -6.55186832e-01 -6.88400149e-01
-4.65503559e-02 9.81328040e-02 7.12477937e-02 1.36165619e+00
2.06186533e-01 5.57150722e-01 -1.31866276e-01 2.78881907e-01
1.81877688e-01 -1.54334247e-01 -6.75850570e-01 -1.42409831e-01
6.07779860e-01 1.06793821e+00 -1.01263678e+00 -1.95909534e-02
-2.85142303e-01 1.29274213e+00 -4.74745721e-01 5.53262830e-01
-6.31894529e-01 -8.53915036e-01 9.22297478e-01 -2.07910851e-01
-1.41819328e-01 -6.03582859e-01 -5.11775434e-01 -9.21654046e-01
1.23247229e-01 -8.70109618e-01 2.88086981e-01 -3.23929846e-01
-7.19966292e-01 6.25268757e-01 -3.02039832e-01 -1.03737855e+00
-4.66269851e-01 -1.15997314e+00 -8.43294322e-01 1.03864086e+00
-8.72673988e-01 -1.32586181e+00 -6.07992172e-01 1.02752519e+00
2.20369428e-01 -2.61503398e-01 1.45848250e+00 4.43643749e-01
-7.11965263e-01 9.61389780e-01 -4.21404451e-01 7.41476595e-01
6.45257473e-01 -6.35175169e-01 7.09115148e-01 7.05831409e-01
-7.40078688e-02 1.53068638e+00 -8.56777057e-02 -7.64083087e-01
-1.55646765e+00 -4.70420778e-01 9.43466246e-01 -9.29765344e-01
2.37812981e-01 -4.58680391e-01 -5.75263321e-01 7.19817042e-01
-9.83005539e-02 -2.93330073e-01 1.04693186e+00 -3.57381850e-02
-3.14578354e-01 3.06630135e-01 -1.62874067e+00 9.46128488e-01
1.22552836e+00 -1.01407683e+00 -5.04915118e-01 -2.52633188e-02
3.68877977e-01 -3.57020229e-01 -2.63119668e-01 -2.50088815e-02
1.40352678e+00 -5.89493930e-01 9.07752931e-01 -9.76377130e-01
-4.26004916e-01 -2.38852441e-01 2.33556591e-02 -3.73110920e-01
4.81887646e-02 -1.00288141e+00 -2.39791796e-01 9.53268051e-01
2.39585176e-01 -9.81497765e-01 8.10868382e-01 1.46668386e+00
5.54035604e-01 -3.35588366e-01 -1.05844986e+00 -7.69675255e-01
-8.15859258e-01 -6.05610371e-01 1.09657168e+00 1.07719827e+00
4.74914551e-01 -1.74831659e-01 -3.69881511e-01 2.54835248e-01
6.66941032e-02 -5.75761139e-01 7.64571905e-01 -1.00789618e+00
3.92809585e-02 -7.11644590e-01 -2.35692322e-01 -8.10329616e-01
-2.26095557e-01 -3.36727083e-01 -9.23578367e-02 -9.88956451e-01
-2.74723709e-01 -1.67153597e-01 -3.64503652e-01 1.20601726e+00
3.51209939e-01 3.84333044e-01 1.38946638e-01 2.29719698e-01
-2.34027147e-01 -8.72851312e-02 6.67145193e-01 -6.25528097e-02
-7.56131589e-01 1.33387238e-01 -2.44238853e-01 6.94273651e-01
8.87370944e-01 -1.24683537e-01 -2.46541724e-02 -3.75436306e-01
-4.54972804e-01 -2.07213044e-01 4.83829141e-01 -8.30934882e-01
4.89332199e-01 -3.93375814e-01 8.28508794e-01 -1.77134395e-01
2.84765810e-01 -1.25303149e+00 -3.42435278e-02 9.32163358e-01
-4.44909036e-02 1.08644545e-01 2.03093246e-01 7.33387694e-02
2.98436880e-01 6.83357194e-02 1.62858143e-01 1.27420306e-01
-8.58235240e-01 1.81199759e-01 -6.46679342e-01 -7.62041450e-01
9.79201794e-01 -6.52333915e-01 -2.01637492e-01 -3.27183723e-01
-7.27094173e-01 -4.29698937e-02 3.32506388e-01 8.16471517e-01
9.35319185e-01 -1.09089339e+00 1.06014363e-01 8.74817431e-01
-1.15681522e-01 -4.62415278e-01 -1.18075460e-01 5.82579970e-01
-8.52102518e-01 7.07551658e-01 -5.24856269e-01 -4.26474422e-01
-1.85431278e+00 1.69912800e-01 2.81350970e-01 3.23604733e-01
-3.57992202e-01 8.77214134e-01 -4.45677906e-01 -5.32052934e-01
9.62426126e-01 -5.57462871e-01 -3.34668130e-01 -1.53496265e-01
1.19465661e+00 5.38632572e-01 1.26452774e-01 -4.12121266e-01
-9.79889691e-01 4.05091584e-01 2.68560320e-01 -3.30145359e-01
1.10083055e+00 1.92118913e-01 1.15246750e-01 7.49720931e-02
8.27571273e-01 -3.05507362e-01 -9.99157190e-01 2.69182235e-01
8.34370628e-02 -4.91787583e-01 -2.66302735e-01 -1.16186750e+00
-7.35497177e-01 1.02589214e+00 1.26641500e+00 1.32666081e-01
1.14323437e+00 -6.43513620e-01 8.54648769e-01 9.61215258e-01
6.81119561e-01 -1.02047527e+00 -1.80027977e-01 6.65905952e-01
6.92853093e-01 -1.24726295e+00 -3.93422782e-01 2.56117582e-01
-4.23914045e-01 1.25533140e+00 7.50235677e-01 5.80996454e-01
8.02785277e-01 6.05797470e-01 5.51644683e-01 -1.89058259e-01
-9.53785330e-03 -7.74033219e-02 3.45475048e-01 1.08288348e+00
7.18114913e-01 4.11755949e-01 -9.13629457e-02 7.68729329e-01
3.59606259e-02 4.76699263e-01 4.34633112e-03 1.41287148e+00
-1.77176803e-01 -1.03215241e+00 -6.67338431e-01 3.25861365e-01
-5.66494644e-01 -7.57781491e-02 -7.44540036e-01 8.26841712e-01
-4.01126593e-02 1.26949835e+00 2.13567570e-01 -8.67659211e-01
2.22039267e-01 5.82862198e-01 3.71525347e-01 -4.17973995e-01
-9.97215569e-01 -1.07433915e-01 -2.15185314e-01 -8.87342691e-01
-2.89462328e-01 -3.55991691e-01 -1.41010451e+00 -5.81850171e-01
-2.19048619e-01 -4.15212184e-01 1.02634764e+00 1.05043352e+00
3.18429917e-01 1.97755784e-01 1.62764028e-01 -1.10084283e+00
-4.28302258e-01 -1.21492481e+00 -3.26063454e-01 1.01315320e-01
5.37448525e-01 -4.18925494e-01 9.55424383e-02 1.12175569e-01] | [6.540956974029541, -0.21750518679618835] |
398e70cb-1056-495b-96a7-9c93f633804f | rffnet-scalable-and-interpretable-kernel | 2211.06410 | null | https://arxiv.org/abs/2211.06410v1 | https://arxiv.org/pdf/2211.06410v1.pdf | RFFNet: Scalable and interpretable kernel methods via Random Fourier Features | Kernel methods provide a flexible and theoretically grounded approach to nonlinear and nonparametric learning. While memory requirements hinder their applicability to large datasets, many approximate solvers were recently developed for scaling up kernel methods, such as random Fourier features. However, these scalable approaches are based on approximations of isotropic kernels, which are incapable of removing the influence of possibly irrelevant features. In this work, we design random Fourier features for automatic relevance determination kernels, widely used for variable selection, and propose a new method based on joint optimization of the kernel machine parameters and the kernel relevances. Additionally, we present a new optimization algorithm that efficiently tackles the resulting objective function, which is non-convex. Numerical validation on synthetic and real-world data shows that our approach achieves low prediction error and effectively identifies relevant predictors. Our solution is modular and uses the PyTorch framework. | ['Rafael Izbicki', 'Mateus P. Otto'] | 2022-11-11 | null | null | null | null | ['variable-selection'] | ['methodology'] | [-1.92724526e-01 -1.97872937e-01 -3.29080015e-01 -2.81066775e-01
-8.50295782e-01 -3.60477746e-01 3.22517276e-01 9.79178250e-02
-3.31675291e-01 1.06072569e+00 -1.45355850e-01 -2.15706006e-01
-6.80412173e-01 -5.65850139e-01 -5.05491674e-01 -7.86533833e-01
-3.71873289e-01 3.85754138e-01 1.80800423e-01 1.16613001e-01
4.34042513e-01 5.53186536e-01 -1.46517599e+00 -1.83878869e-01
1.33162725e+00 1.12693489e+00 6.24847133e-03 5.18563092e-01
1.57102853e-01 5.27560115e-01 -2.38246858e-01 -1.62737802e-01
2.32639372e-01 -1.41031727e-01 -5.88602006e-01 -2.44866446e-01
4.24744815e-01 -2.77979523e-01 4.32072952e-02 7.81230092e-01
4.60383862e-01 5.01025617e-01 8.85591567e-01 -1.14516723e+00
-5.71589172e-01 2.62169540e-01 -3.43369544e-01 1.83793344e-02
1.57515675e-01 -8.70419666e-02 9.05976295e-01 -1.09414601e+00
2.32489854e-01 8.28475356e-01 1.12541246e+00 3.27478498e-02
-1.63337076e+00 -2.55163819e-01 -1.87071413e-01 3.38435054e-01
-1.54399955e+00 -3.63630027e-01 6.60079539e-01 -7.21656442e-01
8.91560256e-01 5.32192826e-01 5.33552647e-01 7.83648014e-01
1.84012413e-01 5.77490807e-01 1.31437290e+00 -4.08184826e-01
5.12877524e-01 5.37144125e-01 4.28475082e-01 7.60688663e-01
2.97314346e-01 2.48508126e-01 -5.79252243e-01 -9.95654643e-01
9.48253453e-01 -1.51612848e-01 -5.19319832e-01 -8.14335167e-01
-1.12785292e+00 1.33479321e+00 -1.21231332e-01 -2.01037094e-01
-3.71508092e-01 -1.63472682e-01 3.21879685e-01 2.37345532e-01
8.33578706e-01 5.22268116e-01 -7.31782854e-01 -2.61462212e-01
-1.15577579e+00 4.48923022e-01 1.13593459e+00 6.14127457e-01
8.85191739e-01 -1.58535130e-02 -1.30463064e-01 8.29057097e-01
4.98761088e-02 5.32361388e-01 3.08133274e-01 -8.58662724e-01
2.29371451e-02 3.86158019e-01 4.42125827e-01 -9.58395422e-01
-7.07376480e-01 -1.75702214e-01 -7.54788339e-01 3.74482900e-01
5.94774902e-01 -1.62098594e-02 -5.70383608e-01 1.21547270e+00
5.38748026e-01 2.77847826e-01 -1.84049860e-01 1.10539258e+00
4.17063922e-01 4.37796712e-01 5.71085978e-03 -3.38404924e-01
8.97591114e-01 -9.38518226e-01 -4.05398101e-01 3.35608721e-01
5.64604580e-01 -8.75539839e-01 1.02630329e+00 5.38860738e-01
-1.09167576e+00 -2.68600106e-01 -7.43565321e-01 4.85456549e-03
-3.04583490e-01 4.41246510e-01 1.30549502e+00 6.55867100e-01
-9.53723848e-01 9.97509181e-01 -8.92207205e-01 2.26497725e-02
2.23956600e-01 7.10683405e-01 -3.78809959e-01 3.53480369e-01
-1.04569566e+00 1.03664494e+00 3.58119935e-01 1.29060730e-01
-1.81013659e-01 -1.04933357e+00 -7.27454901e-01 8.61952379e-02
3.60689014e-01 -6.50537133e-01 9.17426288e-01 -9.94485438e-01
-1.90970206e+00 2.19792992e-01 -1.20865852e-01 -4.43486542e-01
5.42051017e-01 -4.35239464e-01 -1.38396904e-01 1.45332575e-01
-1.45060092e-01 1.01166805e-02 1.26709998e+00 -5.15300214e-01
-2.62363136e-01 4.73280996e-03 -2.63380408e-01 -3.82854715e-02
-5.07539332e-01 1.42634496e-01 -1.79671869e-01 -6.31835163e-01
-2.04179168e-01 -7.94884562e-01 -5.15431523e-01 6.49951100e-02
-3.07122916e-01 -5.32591194e-02 4.92823064e-01 -7.58875966e-01
1.23100388e+00 -1.93642390e+00 1.98819026e-01 7.70894825e-01
3.05661350e-01 1.25818938e-01 1.58486411e-01 2.89489150e-01
-7.13771433e-02 -8.47470462e-02 -4.34001148e-01 -1.36070251e-01
3.52416374e-02 -1.14281125e-01 -4.60732877e-01 7.10362673e-01
1.66394144e-01 7.28797197e-01 -6.50314569e-01 -3.54845405e-01
3.73451144e-01 7.81808496e-01 -6.18229747e-01 1.59951627e-01
1.75369367e-01 4.99730818e-02 -7.01958001e-01 6.65095031e-01
8.13719809e-01 -3.28135103e-01 -8.46594200e-02 -1.89636767e-01
-2.90474415e-01 7.08085299e-02 -1.44599783e+00 1.11725760e+00
-4.02995318e-01 3.67991745e-01 2.56933033e-01 -1.22876799e+00
8.13254893e-01 3.55130597e-03 6.84359729e-01 -7.43436515e-02
-2.01112181e-01 4.60433602e-01 -5.30530572e-01 -3.39786679e-01
4.34692681e-01 1.69820227e-02 2.33571991e-01 1.94524333e-01
1.81636997e-02 -4.79803756e-02 1.31469473e-01 -1.58565298e-01
1.10015869e+00 4.19546783e-01 6.96302414e-01 -6.98770344e-01
5.86677432e-01 1.44522488e-01 2.97104120e-01 6.74368501e-01
1.22676939e-01 5.83368063e-01 6.14218354e-01 -6.32028162e-01
-7.53921926e-01 -1.23337376e+00 -5.94271302e-01 1.07255447e+00
-1.37667701e-01 -4.54405129e-01 -5.90107858e-01 -5.69193423e-01
5.91010273e-01 4.51965868e-01 -7.84042954e-01 -1.03727706e-01
-3.89275849e-01 -9.88446534e-01 2.98102885e-01 3.72714847e-01
-9.41526741e-02 -7.18756020e-01 -4.87578362e-01 3.31083000e-01
2.39294797e-01 -7.93433309e-01 -4.46285099e-01 4.35945600e-01
-1.07546020e+00 -1.19980621e+00 -6.97986245e-01 -2.97632128e-01
5.52513897e-01 -5.43049164e-02 8.87917161e-01 -2.49074951e-01
-5.96144319e-01 4.58655208e-01 -9.18971747e-03 9.07821581e-02
1.57461744e-02 1.37942016e-01 1.75710559e-01 5.32116257e-02
2.25534096e-01 -4.75346565e-01 -5.18350542e-01 3.09657037e-01
-5.71656406e-01 -8.15110579e-02 6.79883838e-01 1.26813126e+00
7.01230526e-01 -2.07178533e-01 6.18755758e-01 -9.11085725e-01
8.32305551e-01 -7.01956689e-01 -9.55547690e-01 2.71331906e-01
-9.65125203e-01 4.39862520e-01 9.26212609e-01 -8.63154829e-01
-9.10546303e-01 1.94772378e-01 3.19988728e-01 -5.41804194e-01
7.92507380e-02 5.93295217e-01 3.24627936e-01 -6.65500998e-01
8.16371024e-01 9.44285616e-02 1.23409897e-01 -5.54877400e-01
1.93434268e-01 3.52503896e-01 1.77996948e-01 -7.96618700e-01
8.51242483e-01 2.95573622e-01 2.94228882e-01 -1.10957432e+00
-5.23780227e-01 -6.19086802e-01 -4.86806452e-01 2.63538808e-01
2.78665334e-01 -6.24244392e-01 -8.89970362e-01 1.51230723e-01
-7.61022925e-01 -3.73348117e-01 -4.54094410e-01 8.13221097e-01
-8.10893357e-01 3.84429008e-01 -3.41809541e-01 -7.77824819e-01
-4.95631069e-01 -1.13184988e+00 1.03890777e+00 1.93526417e-01
-3.45362604e-01 -1.28469741e+00 2.44899064e-01 3.37367766e-02
8.58973205e-01 2.34906331e-01 8.39825928e-01 -6.01191461e-01
-4.55476671e-01 -2.54153848e-01 -2.86706567e-01 2.91292012e-01
4.53400463e-02 1.61441922e-01 -7.77717471e-01 -1.94625273e-01
-1.81672886e-01 -3.08953881e-01 8.15958202e-01 6.66370749e-01
1.24575889e+00 -3.04683179e-01 -3.90366048e-01 1.08662319e+00
1.24466503e+00 -6.28044665e-01 2.88109839e-01 2.84556776e-01
5.87705612e-01 4.04893667e-01 6.29680455e-01 7.26621211e-01
1.08543865e-01 7.75761008e-01 -1.76563695e-01 -1.69456989e-01
3.42650831e-01 2.47436985e-01 3.30622047e-01 3.80547553e-01
-5.21408439e-01 5.63326299e-01 -6.70391083e-01 2.89946854e-01
-2.18219924e+00 -8.06349754e-01 -3.98044169e-01 2.50866055e+00
1.05076492e+00 -2.48710498e-01 1.50711194e-01 -2.76966482e-01
4.05359447e-01 -3.84305239e-01 -5.47526658e-01 -4.12265182e-01
-4.96313088e-02 8.29759896e-01 7.53653526e-01 4.38876420e-01
-1.30810273e+00 7.36609817e-01 7.22752333e+00 9.30173099e-01
-1.10343349e+00 -3.99235524e-02 3.43814522e-01 -1.87926129e-01
-1.47853449e-01 1.43135220e-01 -8.53016257e-01 4.66952860e-01
9.83715236e-01 -3.24885666e-01 6.08567536e-01 1.23045671e+00
3.48918527e-01 -3.18738699e-01 -7.21666932e-01 8.89116764e-01
-2.50387967e-01 -1.40711319e+00 -3.38604629e-01 2.62099989e-02
6.28679395e-01 -1.57260612e-01 1.05381636e-02 2.93740362e-01
-1.95581205e-02 -1.04752374e+00 3.91381562e-01 9.12365019e-01
6.51257098e-01 -1.00080991e+00 5.35433531e-01 9.02987793e-02
-1.00225353e+00 6.74952045e-02 -6.76916718e-01 -8.30732584e-02
-2.05336496e-01 1.15130246e+00 -7.08770514e-01 3.78953129e-01
6.19847417e-01 5.17936051e-01 -5.87168634e-01 1.28987682e+00
1.02569379e-01 7.76300192e-01 -6.57313287e-01 -3.71051356e-02
-1.55500308e-01 -5.08669794e-01 5.17705441e-01 1.26317573e+00
3.97817343e-01 -2.49688327e-01 3.25226128e-01 1.03054190e+00
5.03024757e-01 6.15485728e-01 -4.77535844e-01 5.95474094e-02
1.01613775e-01 1.49179661e+00 -5.64670026e-01 -6.23112097e-02
-5.43740869e-01 8.84762764e-01 7.26623178e-01 6.53792024e-01
-8.19773436e-01 -4.79927599e-01 8.36914599e-01 1.63955048e-01
3.57459486e-01 -3.26766670e-01 -3.11915338e-01 -1.29688501e+00
1.10495090e-01 -6.46398544e-01 2.25639120e-01 -2.34833539e-01
-1.40512526e+00 1.97529554e-01 2.35759094e-01 -9.01667714e-01
-4.43059653e-01 -8.91481280e-01 -5.22020459e-01 1.12398601e+00
-1.46489763e+00 -9.84941781e-01 -2.75537428e-02 6.84872925e-01
-3.94471511e-02 1.15402900e-02 1.13958728e+00 3.49624082e-02
-3.16642672e-01 6.24698818e-01 6.57132268e-01 -4.79588389e-01
9.94339764e-01 -1.41163146e+00 -2.61535426e-03 3.96540910e-01
-3.07871372e-01 9.46811974e-01 6.81976736e-01 -6.02372468e-01
-1.66606987e+00 -8.22719812e-01 4.87803370e-01 -1.70889542e-01
9.70633507e-01 -3.35521489e-01 -1.10897148e+00 1.79567575e-01
-4.48082268e-01 3.87020350e-01 9.53465760e-01 3.57820213e-01
-2.13768944e-01 2.63633858e-03 -1.13491392e+00 3.10119867e-01
5.45694113e-01 -3.58866543e-01 -1.37665346e-01 3.93798262e-01
2.01327726e-01 -3.08652967e-01 -1.14618433e+00 5.08818626e-01
7.00448632e-01 -9.02243972e-01 1.19783139e+00 -5.37205458e-01
-6.25853762e-02 -1.84222370e-01 1.28060549e-01 -1.24421537e+00
-3.73538285e-01 -9.38631713e-01 -7.80222595e-01 7.43031919e-01
2.61514217e-01 -1.00664091e+00 7.39065230e-01 8.52307498e-01
1.00392491e-01 -1.09642410e+00 -9.82899427e-01 -9.32452023e-01
-3.37876566e-02 -3.37080717e-01 1.90705106e-01 9.90234792e-01
1.37709603e-01 -5.22869416e-02 -3.72665375e-01 9.75240320e-02
8.28602195e-01 3.86484325e-01 7.63337493e-01 -1.47760487e+00
-7.33572066e-01 -4.82428402e-01 -5.06291986e-01 -5.95181406e-01
3.68204772e-01 -7.66349673e-01 -2.02305466e-01 -1.01072502e+00
2.32400596e-01 -6.33653939e-01 -1.62938014e-01 5.69472492e-01
-4.08514023e-01 9.37245935e-02 -4.35903370e-01 9.44281891e-02
-1.91917241e-01 5.48729956e-01 8.66016388e-01 2.52386719e-01
-6.01172745e-01 2.14243576e-01 -3.51818681e-01 8.46840918e-01
8.71139288e-01 -2.68888205e-01 -3.28899562e-01 3.67636979e-01
1.31080940e-01 -1.31746709e-01 5.17756045e-01 -7.65617609e-01
1.36895716e-01 -5.76595843e-01 6.49339199e-01 -2.40874395e-01
3.54486912e-01 -5.32940209e-01 7.93048553e-03 2.52179038e-02
-3.92870186e-03 -2.81296968e-01 2.50992745e-01 3.85652155e-01
-9.50871129e-03 -2.97601938e-01 6.17661297e-01 3.42190087e-01
-5.14401019e-01 2.68378288e-01 -2.10338786e-01 1.83176976e-02
9.86149848e-01 -1.26627892e-01 -1.17727935e-01 -2.35248104e-01
-6.33884430e-01 -3.42803821e-02 5.88519514e-01 -4.11403961e-02
6.72274768e-01 -1.14468682e+00 -6.62681103e-01 2.79312402e-01
-6.15550987e-02 -3.29892784e-01 7.22767115e-02 1.29091072e+00
-4.10343140e-01 4.65876341e-01 1.09066688e-01 -4.48968142e-01
-1.11086643e+00 4.76578683e-01 2.38017887e-01 -4.23931003e-01
-5.41969121e-01 6.90302312e-01 1.15283586e-01 -5.00795305e-01
-1.59346759e-01 -3.94992441e-01 2.53333878e-02 -2.04902869e-02
5.86243808e-01 7.44036257e-01 6.78214952e-02 -3.60192835e-01
-3.12552184e-01 6.25849485e-01 4.33625169e-02 1.12800717e-01
1.40536964e+00 2.52401561e-01 -2.43088931e-01 3.51106375e-01
1.29174554e+00 2.38514900e-01 -1.40644622e+00 -2.60441825e-02
7.29913861e-02 -4.32400614e-01 2.37919360e-01 -4.78272945e-01
-6.42403841e-01 3.97731662e-01 4.13278818e-01 1.02406844e-01
1.12076247e+00 -2.40989283e-01 4.21577424e-01 6.32949352e-01
2.57213533e-01 -1.19841063e+00 -4.50544298e-01 5.61550081e-01
6.74293458e-01 -1.25412357e+00 5.02005517e-01 -5.58924377e-01
-4.24793184e-01 1.51238906e+00 3.50476891e-01 -1.92810148e-01
7.83203304e-01 2.97333300e-01 -2.46144965e-01 8.09305236e-02
-6.20367765e-01 -2.62776434e-01 8.19855809e-01 6.22587860e-01
4.90403652e-01 1.55085117e-01 -4.50360209e-01 6.93508208e-01
-1.13045700e-01 7.14368671e-02 1.94478512e-01 7.56016433e-01
-2.91575968e-01 -1.13897395e+00 -5.50402641e-01 8.24465990e-01
-4.06516999e-01 -3.52914006e-01 -9.14312750e-02 9.08819556e-01
-2.93043584e-01 4.04915690e-01 -4.39539939e-01 -6.90927058e-02
5.34131452e-02 2.37196267e-01 5.05649030e-01 -3.20192605e-01
-4.69177455e-01 -2.86403894e-02 -1.01742171e-01 -7.24338353e-01
-6.05338067e-02 -6.20390654e-01 -1.25545943e+00 -1.84455886e-01
-5.69021583e-01 4.45010185e-01 6.73786342e-01 8.66461217e-01
4.02141780e-01 6.97349384e-02 5.46354532e-01 -9.65190411e-01
-9.56752300e-01 -6.27472878e-01 -7.80356407e-01 6.99326396e-02
2.76198149e-01 -1.05079687e+00 -5.89329481e-01 -9.52222943e-02] | [7.599112510681152, 4.1388773918151855] |
883cd051-4d5f-4164-ae5c-0afe7a6012f6 | learning-to-bound-counterfactual-inference-in | 2212.02932 | null | https://arxiv.org/abs/2212.02932v2 | https://arxiv.org/pdf/2212.02932v2.pdf | Learning to Bound Counterfactual Inference from Observational, Biased and Randomised Data | We address the problem of integrating data from multiple, possibly biased, observational and interventional studies, to eventually compute counterfactuals in structural causal models. We start from the case of a single observational dataset affected by a selection bias. We show that the likelihood of the available data has no local maxima. This enables us to use the causal expectation-maximisation scheme to compute approximate bounds for partially identifiable counterfactual queries, which are the focus of this paper. We then show how the same approach can solve the general case of multiple datasets, no matter whether interventional or observational, biased or unbiased, by remapping it into the former one via graphical transformations. Systematic numerical experiments and a case study on palliative care show the effectiveness and accuracy of our approach, while hinting at the benefits of integrating heterogeneous data to get informative bounds in case of partial identifiability. | ['Rafael Cabañas', 'David Huber', 'Alessandro Antonucci', 'Marco Zaffalon'] | 2022-12-06 | null | null | null | null | ['counterfactual-inference', 'selection-bias'] | ['miscellaneous', 'natural-language-processing'] | [ 6.48440182e-01 7.13639438e-01 -6.15810990e-01 -1.42447069e-01
-8.10796320e-01 -4.32933629e-01 7.08773136e-01 1.24198601e-01
-5.68392217e-01 1.51941383e+00 7.26119578e-01 -7.09624767e-01
-8.27211618e-01 -6.03011549e-01 -9.28898573e-01 -7.64449000e-01
-3.98342520e-01 5.59949815e-01 -2.45453149e-01 2.26375222e-01
6.86733872e-02 3.83217663e-01 -1.16054046e+00 -1.38414733e-03
1.09720767e+00 3.40325177e-01 -1.08172126e-01 4.82149959e-01
2.27639660e-01 4.58069742e-01 -3.94316107e-01 -4.31342632e-01
1.68543145e-01 -4.71155465e-01 -7.49364257e-01 -8.07356834e-03
7.39555880e-02 -2.38533154e-01 1.75988957e-01 8.60382259e-01
6.68877065e-01 -2.49188796e-01 8.04298759e-01 -1.34761369e+00
-3.04042429e-01 8.74499917e-01 -6.55171096e-01 -8.87914654e-03
4.52437729e-01 -4.77177426e-02 7.86754012e-01 -2.35394418e-01
7.50075221e-01 1.46318853e+00 6.48948610e-01 3.61928195e-01
-1.60943902e+00 -5.82640469e-01 1.07574627e-01 -3.07779104e-01
-8.75405133e-01 -4.49006557e-01 4.53760058e-01 -5.08860826e-01
2.25259557e-01 4.62328881e-01 4.33636069e-01 1.33745909e+00
2.10095450e-01 3.97542387e-01 1.61620247e+00 -5.30203342e-01
4.84867066e-01 2.38825064e-02 1.14783220e-01 2.17475533e-01
8.85246992e-01 7.57107377e-01 -1.58077419e-01 -8.67021441e-01
7.22091019e-01 5.78740574e-02 -4.73171949e-01 -6.72388375e-01
-1.45051205e+00 1.07790565e+00 8.54988098e-02 1.10928580e-01
-8.19229305e-01 4.17279191e-02 2.21276194e-01 3.24360430e-01
4.00259554e-01 2.90855229e-01 -5.38905323e-01 2.27724224e-01
-8.45170379e-01 3.88535082e-01 9.18691039e-01 6.63960397e-01
1.14182636e-01 -2.64977872e-01 -3.07905704e-01 3.24417233e-01
5.51912934e-02 7.81388283e-01 1.89508498e-01 -9.86244917e-01
4.72234070e-01 3.40796709e-01 6.26654387e-01 -3.44906241e-01
-6.88213646e-01 -1.70894876e-01 -9.32284534e-01 1.60733879e-01
5.83884478e-01 -6.99960053e-01 -7.12375224e-01 2.13501573e+00
6.30103469e-01 1.78574577e-01 1.25601180e-02 5.81510782e-01
1.29887983e-01 5.89758866e-02 3.36740166e-01 -1.09460568e+00
1.25363386e+00 4.50330675e-02 -8.71131957e-01 3.13397259e-01
6.54866159e-01 -4.89704490e-01 6.78263187e-01 4.39828306e-01
-1.23575735e+00 1.13593698e-01 -6.60733104e-01 3.79327685e-01
-1.37130246e-01 -1.85482964e-01 6.16653860e-01 9.15320992e-01
-8.24001133e-01 4.76419747e-01 -5.36020875e-01 -3.32375377e-01
4.16055769e-01 4.81333315e-01 -1.51479438e-01 4.90107527e-03
-1.31184649e+00 6.77293360e-01 4.47605789e-01 -2.11160555e-01
-7.64961958e-01 -1.16960835e+00 -4.75219190e-01 1.28958970e-01
7.27152526e-01 -1.26809394e+00 9.38508749e-01 -1.00926745e+00
-1.03724587e+00 5.71380675e-01 -2.19128102e-01 -6.08835638e-01
9.47839081e-01 1.46499351e-01 -2.32086360e-01 -1.27648935e-01
2.46305153e-01 1.41951889e-01 5.34905910e-01 -1.24305356e+00
-6.39380813e-01 -5.58621407e-01 2.63246056e-02 4.06068526e-02
2.59600759e-01 2.62786835e-01 3.72913092e-01 -6.19935513e-01
-1.22652322e-01 -8.19731593e-01 -5.60598791e-01 -5.91041505e-01
-5.05316973e-01 3.12284864e-02 2.01690361e-01 -6.05143428e-01
1.21063495e+00 -1.74549866e+00 9.26577225e-02 3.52462381e-01
5.72172273e-03 -4.18905526e-01 2.18095139e-01 5.19372344e-01
-6.53909743e-01 3.46549094e-01 -6.01213753e-01 1.14803694e-01
4.42570046e-04 7.30142891e-02 -4.08028096e-01 7.00657606e-01
7.23515078e-02 9.05507207e-01 -7.40448236e-01 -5.78630447e-01
1.21010296e-01 1.22611687e-01 -5.57367384e-01 -1.30148962e-01
1.22673742e-01 5.84388733e-01 -6.31821990e-01 2.12007791e-01
8.38191926e-01 -5.71737438e-02 5.36144018e-01 1.73677400e-01
-3.89953613e-01 1.72552705e-01 -1.69538724e+00 1.25889158e+00
-6.31268620e-01 5.61803533e-03 1.67993829e-01 -1.21016371e+00
2.33808622e-01 5.93458772e-01 5.76737821e-01 -4.78953689e-01
2.06749186e-01 2.71782458e-01 8.42891857e-02 -3.80138218e-01
-3.44402529e-02 -8.84948015e-01 -2.59909302e-01 5.78375280e-01
-8.19856077e-02 3.87173802e-01 -3.31943110e-02 7.34097138e-02
9.82592404e-01 -9.04283598e-02 8.61950815e-01 -6.92544997e-01
2.48825267e-01 -1.28177464e-01 3.42669785e-01 1.06266344e+00
3.23134363e-01 5.15199602e-01 1.04782569e+00 -7.69533589e-02
-9.77489829e-01 -1.18368757e+00 -5.74215055e-01 3.94064665e-01
-3.27220619e-01 3.96511793e-01 -6.36342466e-01 -7.00072467e-01
1.72453433e-01 9.67939794e-01 -1.03556204e+00 -1.02586523e-01
-3.68087530e-01 -1.52223539e+00 1.85060039e-01 1.22731850e-01
1.80114340e-02 -8.61617148e-01 -9.38976645e-01 1.95018634e-01
-1.11333191e-01 -4.18198973e-01 -7.48166963e-02 6.04173914e-02
-1.21353579e+00 -1.39902318e+00 -9.43975925e-01 6.41985610e-02
4.34751540e-01 -2.19012901e-01 9.39336717e-01 -3.05342019e-01
4.94692586e-02 3.82622778e-01 7.22277984e-02 -5.94623566e-01
-5.59515297e-01 -2.74893790e-01 1.25335366e-01 7.75283799e-02
-6.75993934e-02 -6.51508451e-01 -7.55588353e-01 5.00709005e-02
-1.17867684e+00 -2.20021248e-01 5.81918478e-01 1.00773323e+00
2.44708046e-01 -3.06793123e-01 9.05163229e-01 -1.25691032e+00
7.28994310e-01 -8.02779078e-01 -8.95045161e-01 4.60506350e-01
-7.91379631e-01 2.46184900e-01 2.20220879e-01 -4.87342656e-01
-1.32877636e+00 -1.08405404e-01 4.23949659e-01 5.88033423e-02
-2.51333266e-01 6.89775348e-01 -4.17188615e-01 2.35795066e-01
6.04409695e-01 -3.51486236e-01 -8.77463296e-02 -5.07868946e-01
4.45528477e-01 6.07075274e-01 2.35573784e-01 -6.19939089e-01
2.41756305e-01 7.64399350e-01 4.54002738e-01 -4.25548553e-01
-3.81555468e-01 -1.95583582e-01 -3.35309595e-01 2.89280325e-01
5.50568044e-01 -7.39564121e-01 -1.07658088e+00 -1.66184574e-01
-1.02079582e+00 -1.70687139e-01 -6.77506387e-01 9.03785527e-01
-7.85196900e-01 1.59434229e-01 -1.09510617e-02 -1.26213324e+00
8.87470171e-02 -9.60818470e-01 9.89349306e-01 -1.38714716e-01
-2.87744582e-01 -1.36127961e+00 4.52446610e-01 8.38587359e-02
-4.93457429e-02 5.93254089e-01 9.71069753e-01 -7.52766252e-01
-3.43076676e-01 -2.00642034e-01 -1.87308580e-01 -4.09693599e-01
1.94272488e-01 -2.12937340e-01 -9.03243124e-01 -1.75861999e-01
1.86828926e-01 1.84140220e-01 6.88108385e-01 1.20785499e+00
8.57040584e-01 -7.36099243e-01 -5.72106838e-01 2.31831551e-01
1.44707608e+00 2.37870619e-01 5.44735491e-01 6.81735948e-02
3.00988585e-01 9.87876296e-01 6.96379721e-01 6.63206697e-01
3.39538008e-01 7.25212693e-01 4.01487231e-01 -2.66877472e-01
3.21705610e-01 -2.13676453e-01 -8.55030566e-02 -2.06232518e-01
-1.34521529e-01 -9.27458555e-02 -7.62435198e-01 8.09139013e-01
-1.98735058e+00 -1.02845573e+00 -6.07643604e-01 2.92748713e+00
8.43092084e-01 -9.13260505e-02 5.29794633e-01 -1.03560060e-01
8.21172655e-01 -3.96496981e-01 -2.59902716e-01 -5.56878507e-01
-2.19051778e-01 3.64835083e-01 1.07822919e+00 7.61512220e-01
-8.50367546e-01 6.76534772e-02 7.13451147e+00 6.05573237e-01
-5.73681056e-01 3.84255350e-01 7.71488130e-01 -2.20903397e-01
-6.45569444e-01 3.98784369e-01 -2.89989293e-01 5.35891414e-01
1.33927333e+00 -4.11576480e-01 1.62980676e-01 1.90371841e-01
8.79496634e-01 -6.07199371e-01 -1.07533956e+00 2.65991330e-01
-5.22946596e-01 -1.14186275e+00 -6.20084256e-02 4.99748945e-01
9.68808711e-01 -3.63561153e-01 -1.35153577e-01 -1.36314720e-01
9.22628522e-01 -1.00139797e+00 5.96647561e-01 6.63257003e-01
7.12766171e-01 -7.14401603e-01 8.39051187e-01 3.94164771e-01
-3.34328055e-01 -2.11382627e-01 -3.82541157e-02 -1.93935767e-01
4.56091821e-01 8.43215048e-01 -7.55416811e-01 1.14916873e+00
3.12300473e-01 1.15372211e-01 4.94224466e-02 1.16220105e+00
-4.03671861e-02 6.45346463e-01 -4.62343842e-01 2.29460299e-01
-6.18085489e-02 -3.55602056e-01 5.70510626e-01 9.45671320e-01
5.17218232e-01 1.79161802e-01 -4.54186052e-01 9.79093134e-01
1.40853748e-02 1.87016502e-01 -7.36079633e-01 4.43320870e-01
2.05487117e-01 7.56145298e-01 -5.64988673e-01 -3.96761119e-01
-4.68039542e-01 4.56245065e-01 -1.30205780e-01 4.81658310e-01
-6.49583578e-01 1.93258613e-01 1.33461922e-01 1.45132139e-01
-3.62549797e-02 5.31313896e-01 -5.46977460e-01 -9.89832520e-01
-5.74201532e-02 -9.06303942e-01 1.02708900e+00 -5.14409065e-01
-9.59353864e-01 -2.71138728e-01 9.22688484e-01 -8.48118603e-01
-3.98005188e-01 -2.76332110e-01 -4.90911871e-01 1.20772338e+00
-1.10146379e+00 -8.10391068e-01 4.47284251e-01 3.65117520e-01
-4.21587750e-02 4.82876986e-01 5.26009083e-01 2.77714673e-02
-4.21247125e-01 1.49891213e-01 2.82001555e-01 -6.72279835e-01
5.22723019e-01 -1.47260332e+00 -1.70791969e-01 7.82014012e-01
-2.85799950e-01 6.97695553e-01 1.04779494e+00 -8.91458750e-01
-8.30653071e-01 -6.24358952e-01 1.02100408e+00 -4.37048256e-01
8.15297842e-01 -1.51531532e-01 -5.74392796e-01 7.20595241e-01
1.79459378e-01 -4.21933204e-01 3.67419660e-01 5.45175433e-01
9.91344675e-02 1.26893982e-01 -1.36082506e+00 8.02532971e-01
1.12594759e+00 2.74866801e-02 -8.23333383e-01 3.03166807e-01
5.99465668e-01 7.75785930e-03 -8.71537864e-01 5.42154193e-01
5.92320979e-01 -9.55288470e-01 9.73281682e-01 -9.74820316e-01
2.82203048e-01 1.40119955e-01 1.32548794e-01 -1.32427442e+00
9.50989649e-02 -7.20983267e-01 3.72132957e-01 1.16000032e+00
5.31868935e-01 -9.62015569e-01 4.22473729e-01 6.66020989e-01
3.54462653e-01 -1.60091981e-01 -1.40885377e+00 -5.81208646e-01
3.62010062e-01 -2.80544519e-01 7.88915038e-01 1.11944008e+00
1.74913257e-01 1.56513989e-01 -4.30347621e-01 2.48600274e-01
8.75272274e-01 3.07214290e-01 5.23424089e-01 -1.41541290e+00
-3.57016146e-01 -1.88509494e-01 8.26447085e-02 -2.91038990e-01
7.89282024e-02 -4.10028249e-01 -3.30126196e-01 -1.28173196e+00
6.85217559e-01 -3.26264620e-01 -1.86131656e-01 1.51004851e-01
-4.66423512e-01 -3.18469882e-01 -5.90169290e-03 -2.27186650e-01
2.24843458e-03 2.80463576e-01 9.62308407e-01 1.85093969e-01
-3.59463513e-01 4.52023655e-01 -9.22850311e-01 6.76770151e-01
6.39631748e-01 -9.14422333e-01 -4.73391235e-01 3.53563726e-01
2.84882277e-01 6.89292490e-01 8.11825931e-01 -1.42211050e-01
-2.33621910e-01 -4.45068270e-01 6.15373552e-02 -3.07208300e-01
-2.88114846e-01 -1.09208131e+00 8.62022638e-01 8.06413531e-01
-4.83278275e-01 -1.05730236e-01 2.41980970e-01 6.04930520e-01
6.19569644e-02 -4.50795203e-01 3.75323325e-01 -2.32384410e-02
9.74675640e-02 -8.81576762e-02 -1.58233315e-01 1.45837262e-01
8.29029322e-01 6.93646148e-02 -1.66507125e-01 -4.34857488e-01
-9.37833190e-01 2.28665128e-01 3.72044772e-01 -9.55111459e-02
8.92074481e-02 -1.25685596e+00 -9.39833999e-01 -1.92134008e-01
2.72731800e-02 -4.00697231e-01 5.03433824e-01 1.54567766e+00
8.28353986e-02 6.24564588e-01 1.51940584e-02 -3.00915748e-01
-1.22232509e+00 1.14193988e+00 2.82417089e-01 -5.49357533e-01
-1.96652398e-01 -3.95214669e-02 7.80739069e-01 -2.80539989e-01
-1.71437025e-01 -4.10353273e-01 1.78092271e-02 2.36260265e-01
2.84634709e-01 7.59999096e-01 -3.92560586e-02 -2.59108484e-01
-3.13322812e-01 2.47939482e-01 4.19581443e-01 -5.87574363e-01
1.19390213e+00 -5.03867447e-01 -1.68407768e-01 4.71667767e-01
9.68750000e-01 3.03597838e-01 -9.98026133e-01 2.00176854e-02
2.25728497e-01 -2.01326013e-01 -1.15532465e-01 -8.50944340e-01
-5.46169221e-01 4.90549445e-01 6.39685988e-01 4.61774379e-01
1.33238995e+00 3.29550654e-02 -4.70233381e-01 -2.93197513e-01
3.05867374e-01 -6.69359684e-01 -9.24374402e-01 -4.86934483e-01
1.04852045e+00 -1.10436726e+00 3.28597158e-01 -2.77955085e-01
-4.08636928e-01 6.76468611e-01 -3.90301555e-01 -6.79113045e-02
5.95259190e-01 1.39334276e-01 -3.53405833e-01 -1.91996038e-01
-7.53772140e-01 -2.43907616e-01 2.37186477e-01 5.86114049e-01
2.34670550e-01 3.84078771e-01 -1.19573987e+00 5.23415387e-01
-3.63605730e-02 2.94387937e-01 6.80817246e-01 6.53199017e-01
2.42073908e-01 -1.12888527e+00 -7.56325364e-01 6.58901215e-01
-9.39203680e-01 -1.93962008e-01 -4.36679184e-01 1.48208225e+00
-3.67274880e-02 8.42664480e-01 -2.44829133e-02 5.24930656e-01
5.89899778e-01 1.06170207e-01 4.23716605e-01 -1.50697097e-01
-3.14946622e-01 4.30030346e-01 3.68829757e-01 -5.36912143e-01
-8.69069934e-01 -1.26880789e+00 -6.26800954e-01 -2.83810318e-01
-4.20675576e-01 3.17798585e-01 2.55776465e-01 9.10228729e-01
8.26086551e-02 5.61237097e-01 7.24155784e-01 -3.93040955e-01
-7.87468672e-01 -8.59003186e-01 -7.28207707e-01 2.49156147e-01
7.01690018e-01 -6.93375826e-01 -5.96953750e-01 -1.02064796e-01] | [7.924848556518555, 5.283501625061035] |
0083d8d0-0ea7-4faa-a22c-90211020dccb | a-simple-global-neural-discourse-parser | 2009.01312 | null | https://arxiv.org/abs/2009.01312v2 | https://arxiv.org/pdf/2009.01312v2.pdf | A Simple Global Neural Discourse Parser | Discourse parsing is largely dominated by greedy parsers with manually-designed features, while global parsing is rare due to its computational expense. In this paper, we propose a simple chart-based neural discourse parser that does not require any manually-crafted features and is based on learned span representations only. To overcome the computational challenge, we propose an independence assumption between the label assigned to a node in the tree and the splitting point that separates its children, which results in tractable decoding. We empirically demonstrate that our model achieves the best performance among global parsers, and comparable performance to state-of-art greedy parsers, using only learned span representations. | ['Vivek Srikumar', 'Yichu Zhou', 'Omri Koshorek', 'Jonathan Berant'] | 2020-09-02 | null | null | null | null | ['discourse-parsing'] | ['natural-language-processing'] | [ 3.51667516e-02 6.99317217e-01 -3.05706292e-01 -3.55857670e-01
-1.12880504e+00 -7.40052760e-01 4.33122307e-01 6.01656020e-01
-2.70982057e-01 6.47039771e-01 5.96190512e-01 -6.18971825e-01
4.35329527e-02 -8.85599017e-01 -5.34644961e-01 -4.12605196e-01
-1.91717848e-01 3.98448825e-01 4.01337713e-01 -1.17837258e-01
2.06402272e-01 1.79022074e-01 -1.18343163e+00 2.13166237e-01
7.31807113e-01 8.39347303e-01 1.50011584e-01 8.12956393e-01
-4.81850147e-01 1.19888735e+00 -6.98878348e-01 -3.52132678e-01
-1.94528550e-01 -7.36792803e-01 -1.13264370e+00 -1.92152783e-01
3.36369604e-01 -3.98456872e-01 -3.44212770e-01 6.38905048e-01
2.01215371e-01 9.88433324e-03 5.06650031e-01 -6.31894171e-01
-5.53592801e-01 9.73099887e-01 -3.29680771e-01 2.02811018e-01
4.50057328e-01 -2.34673500e-01 1.45963848e+00 -2.94499129e-01
6.90095007e-01 1.14978254e+00 6.89853430e-01 5.73117018e-01
-1.24117100e+00 -1.55423477e-01 4.85332489e-01 4.17273007e-02
-7.42667496e-01 -3.99443001e-01 8.20873260e-01 -3.53623778e-01
1.11332047e+00 9.02614463e-03 3.95276546e-01 9.51075613e-01
3.86003926e-02 7.15963483e-01 8.95599425e-01 -8.37033153e-01
5.11294365e-01 -5.37663877e-01 6.66551292e-01 1.14749539e+00
9.79078561e-02 -2.66490251e-01 -6.28977895e-01 -1.97448909e-01
4.87837940e-01 -5.89583933e-01 -6.08482510e-02 -1.19789988e-01
-7.25900233e-01 1.18485463e+00 1.22595645e-01 4.37346339e-01
-1.62791774e-01 3.50831389e-01 6.76479816e-01 2.81102210e-01
2.89296418e-01 5.01608312e-01 -4.47683185e-01 -5.82723796e-01
-1.09157944e+00 1.13926582e-01 1.06316674e+00 9.35973108e-01
5.86460769e-01 -7.05958977e-02 -3.55447084e-01 5.39687812e-01
1.32284060e-01 -5.48616461e-02 4.24799472e-01 -1.21835232e+00
6.49775207e-01 6.68847263e-01 4.17627133e-02 -7.48604715e-01
-7.01539159e-01 -2.08001509e-01 -2.61636317e-01 -3.84556055e-02
8.22102547e-01 -3.47957134e-01 -7.72110879e-01 2.01195097e+00
1.92984924e-01 -1.84131861e-01 4.20987271e-02 5.88363230e-01
8.87183249e-01 4.68524218e-01 2.69636005e-01 -3.98456544e-01
1.51368916e+00 -1.11990285e+00 -5.86514890e-01 -1.95674658e-01
9.17187035e-01 -2.78892010e-01 9.79669154e-01 1.78458273e-01
-1.18067718e+00 -1.01915725e-01 -1.11705935e+00 -4.18384522e-01
1.36406228e-01 2.11146429e-01 8.20189953e-01 8.05464089e-01
-9.55052137e-01 7.02299237e-01 -1.06765032e+00 -2.24079356e-01
2.54284084e-01 1.07521921e-01 -3.27702105e-01 2.09411249e-01
-9.44798410e-01 8.81218791e-01 4.01878595e-01 -6.18894957e-02
-6.45375431e-01 -2.37289146e-01 -1.05047405e+00 3.85504603e-01
6.12769127e-01 -5.65368831e-01 1.55476499e+00 -6.30542755e-01
-1.92007244e+00 6.32652819e-01 -5.63520789e-01 -5.40089488e-01
3.86961967e-01 -3.69229704e-01 1.65386051e-01 4.78987604e-01
1.22691907e-01 3.59970927e-01 5.81824124e-01 -8.88149142e-01
-3.99723470e-01 -4.92911562e-02 5.13332605e-01 -2.08031405e-02
-3.29546779e-01 3.05356920e-01 -3.40878785e-01 -4.81353015e-01
3.94177884e-01 -6.99879169e-01 -3.32009792e-01 -3.11895519e-01
-5.71867347e-01 -5.08749783e-01 4.59924787e-01 -8.21367800e-01
1.50570869e+00 -1.91610694e+00 1.86246634e-01 -1.64196491e-01
1.39528349e-01 9.79291499e-02 -8.07385147e-02 6.09645844e-01
3.13929826e-01 1.19407870e-01 -2.77765751e-01 -4.85451728e-01
-3.39098200e-02 2.47387186e-01 -2.83701450e-01 2.95425028e-01
3.03359807e-01 6.98663294e-01 -1.10430658e+00 -6.66587234e-01
-9.71201286e-02 -1.35536899e-03 -5.24580359e-01 4.23216611e-01
-5.48597157e-01 3.62364382e-01 -6.59216583e-01 4.91428494e-01
2.04007223e-01 -2.85535067e-01 8.53133142e-01 1.55351982e-01
-2.73527145e-01 1.13517010e+00 -8.61197948e-01 1.85912764e+00
-4.28074777e-01 6.21192575e-01 8.96799117e-02 -1.04102230e+00
1.00160456e+00 4.52443331e-01 5.22972830e-02 -4.10132617e-01
2.84908026e-01 7.32637569e-02 -4.31960858e-02 -4.63337213e-01
4.84907568e-01 1.06625266e-01 -5.03266156e-01 6.17571652e-01
1.81165963e-01 2.08062232e-01 5.92076600e-01 1.98405579e-01
1.60856295e+00 3.72641742e-01 5.50488770e-01 -2.15922669e-01
3.47086489e-01 9.35553983e-02 7.82393694e-01 8.58425379e-01
-1.36922985e-01 5.70587754e-01 1.18182719e+00 -4.69252318e-01
-9.32486236e-01 -8.70012522e-01 7.18522221e-02 1.48045075e+00
-1.44053951e-01 -8.76699150e-01 -1.14058387e+00 -8.53639066e-01
-3.22721809e-01 9.10704613e-01 -7.28431761e-01 3.00014198e-01
-1.21423745e+00 -3.47959578e-01 7.05035210e-01 9.43766117e-01
2.10305005e-01 -9.16035771e-01 -1.02979636e+00 5.17192364e-01
-7.14558363e-02 -1.10048747e+00 -1.10063106e-01 4.74742949e-01
-1.08130038e+00 -1.29773140e+00 -2.62061268e-01 -8.44041288e-01
5.75220585e-01 -5.72282150e-02 1.10069644e+00 8.86839926e-02
8.21246058e-02 1.33333236e-01 -5.62258959e-01 -9.60181952e-02
-5.17181754e-01 5.89931548e-01 -5.38891792e-01 -5.88240623e-01
2.00928986e-01 -4.68063116e-01 -2.19767809e-01 -1.68973178e-01
-3.34974349e-01 3.04864030e-02 3.93431723e-01 1.04739213e+00
1.56289175e-01 -2.94837385e-01 5.04882872e-01 -1.04803813e+00
6.71826422e-01 -4.06982809e-01 -4.93343711e-01 3.71463686e-01
-1.34817988e-01 4.37000245e-01 8.82064223e-01 -2.03273058e-01
-1.13504565e+00 5.86117133e-02 -8.99892449e-02 1.62393451e-01
-2.37432852e-01 6.97733819e-01 -8.91239718e-02 3.49413007e-01
5.96833766e-01 -1.37743190e-01 -1.19321704e-01 -7.60125339e-01
6.31726265e-01 3.50645095e-01 5.08289635e-01 -9.26105022e-01
4.77630138e-01 1.24871589e-01 5.45915961e-02 -8.12493384e-01
-1.08620679e+00 8.53303596e-02 -7.25499690e-01 8.37199092e-02
1.05309486e+00 -7.50038326e-01 -5.17726779e-01 4.34942693e-02
-1.49618578e+00 -3.01842123e-01 -1.83596194e-01 3.33276898e-01
-7.17387736e-01 5.33511877e-01 -9.69399750e-01 -8.35604608e-01
-3.65100384e-01 -8.84916842e-01 8.44966650e-01 2.42890149e-01
-6.01253986e-01 -8.56196463e-01 2.32097935e-02 1.65638566e-01
1.36572003e-01 3.97869736e-01 1.27185667e+00 -9.05275464e-01
-6.30124986e-01 5.79036353e-03 -2.65430778e-01 3.51508968e-02
2.39945622e-03 1.70458443e-02 -8.63654852e-01 1.03371199e-02
-8.38311911e-02 -4.97573376e-01 1.03800845e+00 3.89669895e-01
9.02093232e-01 -2.38710433e-01 -2.25199908e-01 4.55414444e-01
1.04403710e+00 -5.02878167e-02 2.34624907e-01 5.97669840e-01
5.43486297e-01 6.40087605e-01 3.97810012e-01 3.33542407e-01
6.76114261e-01 3.66788745e-01 3.07647914e-01 4.21464741e-01
-8.49085599e-02 -4.02672321e-01 3.41894150e-01 8.64393055e-01
-2.08740473e-01 -2.71946847e-01 -8.04424047e-01 6.11068845e-01
-1.89444518e+00 -6.92020655e-01 -1.24338843e-01 1.67504644e+00
9.40327346e-01 3.86367738e-01 1.18833803e-01 1.17035516e-01
6.02066875e-01 5.34232795e-01 -2.16162518e-01 -9.83958840e-01
9.98116508e-02 4.93033141e-01 4.07498419e-01 5.65191686e-01
-1.37504017e+00 1.16080618e+00 7.57217360e+00 4.07050967e-01
-7.78029025e-01 2.23184824e-01 3.04256856e-01 -5.46261705e-02
-2.31508315e-01 2.54746825e-01 -8.04715633e-01 2.14591086e-01
1.21769524e+00 -6.31226227e-02 2.19623670e-01 9.60039198e-01
8.11116099e-02 -1.81126297e-02 -1.33345711e+00 2.77669609e-01
-1.04175076e-01 -1.43884969e+00 -2.96809465e-01 -2.15360209e-01
2.75421619e-01 -2.21005127e-01 -3.26616824e-01 2.92839289e-01
6.27390981e-01 -9.99214888e-01 9.39628065e-01 1.51652619e-01
5.22331953e-01 -4.85231340e-01 4.37256366e-01 3.76909047e-01
-1.19742489e+00 -2.75841951e-01 -3.24254990e-01 -5.72809696e-01
3.01757812e-01 4.87952888e-01 -7.56110787e-01 4.23742861e-01
2.86480129e-01 2.13746935e-01 -2.48255521e-01 6.76951408e-01
-8.67508173e-01 1.16720235e+00 -3.14318806e-01 -2.20683411e-01
4.40758675e-01 1.30826235e-01 4.39804554e-01 1.37427354e+00
1.89751193e-01 1.24398798e-01 3.60150844e-01 6.46209121e-01
-1.43790945e-01 2.15376109e-01 -3.60177428e-01 -2.36694124e-02
8.15445781e-01 9.55661058e-01 -7.87499309e-01 -2.91700006e-01
-5.59400737e-01 5.24260283e-01 1.05924129e+00 1.11721702e-01
-5.91126084e-01 -2.69321412e-01 3.76981109e-01 -1.11585759e-01
7.77496219e-01 -6.72487736e-01 -4.74902689e-01 -9.84655678e-01
1.52544484e-01 -5.22513866e-01 4.84187841e-01 -1.70069903e-01
-9.80059087e-01 6.08216345e-01 -2.16492191e-02 -6.92701042e-01
-6.94156885e-01 -6.57828689e-01 -1.01132846e+00 7.69008815e-01
-1.49602365e+00 -1.25852764e+00 1.00125976e-01 2.35706419e-02
4.68443364e-01 2.01776829e-02 1.19482255e+00 -2.96651065e-01
-6.55512512e-01 7.55963206e-01 1.25293704e-02 4.78313208e-01
4.31964666e-01 -1.40305674e+00 5.23459435e-01 7.87929535e-01
-4.57577258e-02 7.37718821e-01 7.94947565e-01 -4.93272275e-01
-1.29841983e+00 -8.03057790e-01 1.28838325e+00 -2.51166880e-01
7.77434051e-01 -2.80442506e-01 -1.01708317e+00 8.61757815e-01
2.14074627e-01 -1.82751626e-01 8.10334265e-01 6.64796829e-01
-6.37789249e-01 3.02655876e-01 -7.28771448e-01 3.03854913e-01
9.65133905e-01 -3.55413198e-01 -1.10440016e+00 1.02671117e-01
7.85383761e-01 -6.34307921e-01 -9.01357293e-01 -1.09293535e-02
3.90838593e-01 -9.07852352e-01 5.50079465e-01 -7.12762952e-01
6.05709553e-01 9.30340365e-02 -1.60933360e-02 -9.37613487e-01
-4.05428141e-01 -5.91302574e-01 -4.34073746e-01 1.32647288e+00
5.08910000e-01 -4.00182426e-01 9.17812765e-01 6.46600008e-01
-3.07183653e-01 -8.53400588e-01 -1.23387289e+00 -8.15488100e-01
4.01033878e-01 -2.82552838e-01 5.53125560e-01 7.14057267e-01
4.32004988e-01 4.74833220e-01 -2.64724761e-01 7.72155002e-02
3.60393465e-01 5.04277825e-01 5.65428853e-01 -1.23588145e+00
-5.36757410e-01 -5.07940471e-01 -1.34780884e-01 -1.22331858e+00
4.35578793e-01 -6.48144722e-01 1.41859084e-01 -1.61276686e+00
1.12952646e-02 -4.77268696e-01 -1.10284939e-01 6.16878390e-01
-3.08063775e-01 -3.40098917e-01 2.39633873e-01 -3.11418623e-02
-7.01261580e-01 3.81238282e-01 8.76273811e-01 1.10727981e-01
-3.83123964e-01 -2.85405487e-01 -8.97315741e-01 9.61969316e-01
8.66952598e-01 -5.50277233e-01 -2.13516399e-01 -7.47358978e-01
9.53104421e-02 3.38481098e-01 -1.55305400e-01 -7.28798032e-01
2.49357969e-01 -1.40215531e-01 7.90273584e-03 -3.38929266e-01
1.64119482e-01 -9.61509943e-02 -4.51808333e-01 3.03426445e-01
-6.97238982e-01 3.13562155e-02 -1.24481637e-02 5.12923896e-01
-1.73987225e-01 -8.96366119e-01 3.98601115e-01 -3.05279016e-01
-3.85019004e-01 -2.24794775e-01 -5.35001814e-01 2.42289141e-01
8.48670244e-01 7.68156201e-02 -4.53245252e-01 -2.68261194e-01
-7.12138176e-01 1.34072065e-01 4.08714056e-01 8.63980353e-02
1.34711578e-01 -8.48855019e-01 -6.09867156e-01 -1.81978598e-01
-2.78195977e-01 1.38425007e-01 -9.42911059e-02 4.77437079e-01
-6.17622137e-01 4.12912041e-01 1.05995111e-01 -2.63330221e-01
-1.24900782e+00 4.60700423e-01 -2.12182298e-01 -7.67464221e-01
-9.96673107e-01 6.96863830e-01 -1.40713602e-01 -1.52024314e-01
3.16932797e-01 -4.45406199e-01 -3.31258297e-01 2.30367154e-01
4.21412647e-01 3.31738889e-01 -1.55068962e-02 -5.01956284e-01
-3.32536012e-01 3.42991352e-01 -1.62645966e-01 -9.12450850e-02
1.30536461e+00 1.87419251e-01 -4.96003777e-02 4.83910680e-01
8.88635635e-01 1.38601676e-01 -1.24913990e+00 -1.71567798e-01
4.13358182e-01 -1.88803405e-01 5.79070263e-02 -5.21208763e-01
-6.36788070e-01 9.58952427e-01 -2.22060934e-01 2.85314500e-01
8.63623798e-01 1.37351662e-01 1.01346231e+00 6.05797410e-01
3.85197252e-01 -1.15673792e+00 4.19893563e-02 8.96741927e-01
4.10907984e-01 -7.84491658e-01 6.37804940e-02 -5.45771062e-01
-4.82407719e-01 1.44628608e+00 3.68716687e-01 -4.10849303e-01
2.92715102e-01 3.90443772e-01 8.95915460e-03 3.36106904e-02
-1.06144118e+00 -1.45330086e-01 -1.78661332e-01 4.95941520e-01
7.06553936e-01 6.21810965e-02 -7.89078474e-01 9.48519349e-01
-4.06309932e-01 -5.97303733e-02 5.00658572e-01 1.30311441e+00
-7.86430597e-01 -1.38369846e+00 -2.23388031e-01 3.17041814e-01
-5.94701111e-01 -1.20366178e-01 -1.90902203e-01 6.77095115e-01
-1.70136213e-01 1.00790560e+00 1.73586354e-01 -1.02408543e-01
1.37811735e-01 4.83385265e-01 7.28413105e-01 -7.09927380e-01
-6.85291231e-01 -4.02423106e-02 8.53890002e-01 -4.77786124e-01
-3.82124305e-01 -8.36944103e-01 -1.51460493e+00 -1.75715983e-01
-2.31697947e-01 2.71177232e-01 4.89681751e-01 1.10596657e+00
2.11872265e-01 6.26576185e-01 3.78247529e-01 -6.01625383e-01
-7.83124387e-01 -9.35571432e-01 -3.11226249e-01 4.81802933e-02
2.41598129e-01 -7.54427850e-01 -7.61524290e-02 -1.04821688e-02] | [10.559646606445312, 9.478950500488281] |
1ac99487-9603-4f4f-9243-0a0371f5b278 | lightweight-improved-residual-network-for | 2307.03998 | null | https://arxiv.org/abs/2307.03998v1 | https://arxiv.org/pdf/2307.03998v1.pdf | Lightweight Improved Residual Network for Efficient Inverse Tone Mapping | The display devices like HDR10 televisions are increasingly prevalent in our daily life for visualizing high dynamic range (HDR) images. But the majority of media images on the internet remain in 8-bit standard dynamic range (SDR) format. Therefore, converting SDR images to HDR ones by inverse tone mapping (ITM) is crucial to unlock the full potential of abundant media images. However, existing ITM methods are usually developed with complex network architectures requiring huge computational costs. In this paper, we propose a lightweight Improved Residual Network (IRNet) by enhancing the power of popular residual block for efficient ITM. Specifically, we propose a new Improved Residual Block (IRB) to extract and fuse multi-layer features for fine-grained HDR image reconstruction. Experiments on three benchmark datasets demonstrate that our IRNet achieves state-of-the-art performance on both the ITM and joint SR-ITM tasks. The code, models and data will be publicly available at https://github.com/ThisisVikki/ITM-baseline. | ['Jun Xu', 'XianTong Zhen', 'Lei Zhang', 'Yan Liu', 'Yongbao Song', 'Tianyi Xu', 'Liqi Xue'] | 2023-07-08 | null | null | null | null | ['image-reconstruction', 'tone-mapping', 'inverse-tone-mapping'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [ 3.35080534e-01 -3.50405633e-01 -3.32068026e-01 -3.76265049e-01
-5.88202119e-01 -2.11166799e-01 3.73198450e-01 -7.31499612e-01
-1.03214934e-01 4.92450655e-01 2.90137529e-01 -4.20221657e-01
1.05008200e-01 -7.81782031e-01 -7.79209554e-01 -4.54963535e-01
1.25943959e-01 -2.95923084e-01 3.75818044e-01 -4.08541054e-01
-2.66606494e-05 4.68494087e-01 -1.50842726e+00 5.97517431e-01
7.64525473e-01 1.15905607e+00 5.09411275e-01 7.20828235e-01
-1.79388747e-02 1.24922299e+00 -3.45798850e-01 -1.76418349e-01
4.69468117e-01 -1.81641415e-01 -6.13910496e-01 -1.76048011e-01
4.08279896e-01 -8.75582278e-01 -1.07047117e+00 1.10833406e+00
5.77151716e-01 1.41902566e-01 4.12507243e-02 -1.21588492e+00
-8.54263902e-01 6.93759441e-01 -9.12275434e-01 2.57955939e-01
3.04229200e-01 1.86078116e-01 6.69633806e-01 -8.20768237e-01
7.31815279e-01 1.35316014e+00 4.33064312e-01 4.12140608e-01
-1.21050751e+00 -1.12282097e+00 -5.60409203e-02 3.62713307e-01
-1.52880561e+00 -5.68388104e-01 7.67174780e-01 7.41972327e-02
9.06111240e-01 4.19807673e-01 4.99739766e-01 8.93260300e-01
6.70193955e-02 5.95605850e-01 1.47278214e+00 -1.52503783e-02
-3.26943874e-01 -2.25246996e-01 -1.41132146e-01 4.18626249e-01
-6.69994205e-02 6.13326058e-02 -8.11122477e-01 4.37286049e-01
1.33390629e+00 2.26722762e-01 -5.84510148e-01 5.65324724e-02
-1.22969580e+00 4.75275964e-01 6.12245023e-01 1.49954528e-01
-1.01586103e-01 3.74215931e-01 2.92368114e-01 7.12479949e-01
7.02148020e-01 -2.23052770e-01 -1.75730690e-01 -1.06199495e-01
-8.95742238e-01 -2.23449081e-01 3.35896909e-01 8.91710579e-01
7.73618877e-01 1.91681262e-03 6.53687790e-02 1.19653893e+00
3.57239664e-01 7.25730836e-01 1.79825321e-01 -1.31669915e+00
5.84382415e-01 4.85154569e-01 -1.38720617e-01 -1.09219170e+00
-1.97852641e-01 -2.24680841e-01 -1.40018702e+00 3.38930279e-01
-1.13317207e-01 2.85970837e-01 -9.60432231e-01 1.37385488e+00
1.90397471e-01 5.16027689e-01 -1.71467081e-01 1.23214698e+00
1.09706938e+00 1.33700931e+00 -1.17147155e-01 -3.73952165e-02
1.11152542e+00 -9.04240966e-01 -7.05934107e-01 3.31399473e-03
1.75143048e-01 -8.62455249e-01 1.46594369e+00 4.86651778e-01
-1.33935606e+00 -8.59804273e-01 -1.28048599e+00 -6.23959541e-01
-1.17922023e-01 -8.67442712e-02 4.52797830e-01 3.10099363e-01
-1.29214931e+00 6.04312897e-01 -6.16398692e-01 2.80741621e-02
3.42550576e-01 2.70448595e-01 -4.11292940e-01 -6.02863789e-01
-1.28546393e+00 4.73939896e-01 7.09662735e-02 2.34754607e-01
-7.14263856e-01 -8.80319655e-01 -6.62763715e-01 -1.04055934e-01
1.83281913e-01 -4.29672509e-01 9.60864604e-01 -8.05433929e-01
-1.68808568e+00 8.91833544e-01 1.97677299e-01 -2.55625278e-01
5.06103575e-01 -2.27938563e-01 -6.64968967e-01 3.43068510e-01
-3.15902501e-01 8.16635549e-01 9.14974749e-01 -1.22049129e+00
-4.06415582e-01 -8.60547870e-02 -2.30940897e-02 1.59648746e-01
-2.49700338e-01 2.62798727e-01 -8.03657651e-01 -7.90698409e-01
9.68518704e-02 -7.84971178e-01 3.12830396e-02 3.12633902e-01
-3.59495193e-01 2.00309306e-01 1.10774183e+00 -9.60087597e-01
1.28271616e+00 -2.41727161e+00 -1.57909486e-02 1.69318840e-01
5.84315002e-01 4.16343093e-01 -3.56974840e-01 3.46252061e-02
-2.15062886e-01 -5.79875521e-02 2.26147994e-02 -1.89518094e-01
1.72722072e-03 -8.01900998e-02 -5.58943272e-01 5.30407906e-01
-2.89655536e-01 8.27951074e-01 -4.13343877e-01 -4.19017047e-01
6.47583306e-01 1.10170352e+00 -2.47831777e-01 3.36342514e-01
-4.63199336e-03 6.20498300e-01 -1.54212676e-02 4.98649806e-01
1.14580929e+00 -6.39935672e-01 1.62031353e-01 -7.04424322e-01
-2.48705015e-01 3.08123201e-01 -1.21415794e+00 1.79293752e+00
-6.57247484e-01 8.67089808e-01 6.43898696e-02 -4.55876917e-01
1.04590917e+00 -4.11384292e-02 3.75676095e-01 -1.39266658e+00
-2.60290615e-02 2.41562366e-01 -2.84644574e-01 -9.44374129e-02
7.46118903e-01 2.95856297e-01 1.18977383e-01 3.94086182e-01
-4.06783074e-01 2.06645355e-01 1.05551966e-02 3.31781179e-01
9.50776815e-01 1.14501797e-01 1.08981542e-01 -3.02165770e-03
4.13865238e-01 -6.31060243e-01 4.79276568e-01 4.81805503e-01
1.48261152e-02 9.40533876e-01 2.87968725e-01 -5.52334964e-01
-1.32479358e+00 -1.36858928e+00 -1.15220346e-01 1.11349940e+00
5.03071368e-01 -3.78894538e-01 -3.03359151e-01 -3.98399010e-02
-2.49286056e-01 3.00595403e-01 -1.51363105e-01 3.58860120e-02
-7.61963010e-01 -5.28451145e-01 3.85631412e-01 2.79086113e-01
1.17365336e+00 -1.02256572e+00 -3.50986421e-01 -4.72969748e-02
-4.78340685e-01 -1.12081158e+00 -7.65725672e-01 -2.14480668e-01
-6.79485977e-01 -6.85016513e-01 -8.47047806e-01 -5.25354505e-01
2.82679290e-01 8.37451041e-01 1.34495521e+00 1.77846342e-01
-3.91599029e-01 -4.03700769e-03 -4.40125257e-01 3.72430086e-01
-2.90668100e-01 -2.41272952e-02 -3.43998671e-01 -5.26106469e-02
6.91592470e-02 -7.80038476e-01 -1.12619102e+00 4.61256951e-01
-1.16050243e+00 6.98558569e-01 6.88120127e-01 2.72583961e-01
9.42727685e-01 2.25948751e-01 2.69284368e-01 -7.79990554e-01
1.54043451e-01 -4.44042593e-01 -6.04099810e-01 9.56661552e-02
-5.09510100e-01 -2.29421988e-01 5.29394209e-01 -4.24954683e-01
-1.18361604e+00 -3.99694055e-01 -2.82791376e-01 -5.44210672e-01
1.38553068e-01 5.51556461e-02 -2.73059815e-01 -2.13912606e-01
2.59680033e-01 2.89053053e-01 -1.45370856e-01 -5.19483089e-01
4.59343612e-01 8.77181709e-01 6.06227994e-01 -3.29021394e-01
9.01417196e-01 6.78454399e-01 -1.24407232e-01 -6.27940476e-01
-7.52984822e-01 -3.35216224e-01 3.05005256e-02 -5.09354234e-01
7.48642504e-01 -1.37817192e+00 -7.55909145e-01 7.65981495e-01
-8.10466826e-01 -8.77564669e-01 -1.05487488e-01 2.37013936e-01
-3.98720086e-01 2.21397504e-01 -1.03451085e+00 -2.00256363e-01
-5.54672122e-01 -1.15801132e+00 1.05995595e+00 3.64172906e-01
3.58766913e-01 -5.48690319e-01 1.79274715e-02 3.79119664e-01
9.54906106e-01 -6.78842738e-02 5.60853064e-01 3.43211859e-01
-1.09182072e+00 4.07534778e-01 -1.05022848e+00 3.68657678e-01
-1.01849958e-02 -1.78089559e-01 -9.02969420e-01 -3.99064541e-01
-1.75619796e-01 -3.60852927e-01 1.11461008e+00 4.78504807e-01
1.67100382e+00 -1.99128628e-01 -1.57932993e-02 1.24342084e+00
1.70953941e+00 -4.45133746e-02 1.40168917e+00 4.08198476e-01
1.03345954e+00 2.68564075e-01 5.71144521e-01 4.78866667e-01
4.81743157e-01 7.64718831e-01 3.92245650e-01 -4.72231179e-01
-6.96204484e-01 -2.05223799e-01 5.84741175e-01 1.02479684e+00
-1.00977764e-01 -2.68526316e-01 -6.30838156e-01 1.09663703e-01
-1.56549358e+00 -8.48124206e-01 -7.84794018e-02 1.99300277e+00
9.76568520e-01 -3.48037407e-02 -7.59337842e-02 2.08240142e-03
9.50038970e-01 6.98535740e-01 -7.22755075e-01 -1.08897582e-01
-3.91895652e-01 1.31358832e-01 6.74194753e-01 3.11804175e-01
-8.41628015e-01 6.72691405e-01 5.27956104e+00 1.08962250e+00
-1.31242752e+00 3.00876170e-01 1.11561263e+00 -3.28466445e-01
-4.06273961e-01 -2.92371333e-01 -6.93653882e-01 6.91000164e-01
1.05091715e+00 2.27202773e-01 9.42057490e-01 5.25023639e-01
3.81473154e-01 1.08526826e-01 -5.26590347e-01 1.54263890e+00
-8.18436816e-02 -1.39473188e+00 6.79909717e-03 9.59095359e-02
7.99683154e-01 2.97118247e-01 5.74795365e-01 1.26748130e-01
2.67670274e-01 -9.57043707e-01 5.62754691e-01 4.54153210e-01
1.68694961e+00 -8.10824692e-01 4.20941174e-01 -3.29624683e-01
-1.50229824e+00 1.43243343e-01 -4.94833648e-01 2.92059451e-01
1.38698250e-01 7.79507458e-01 7.56717101e-02 2.22395107e-01
1.29171646e+00 1.06762052e+00 -5.95390737e-01 6.13106191e-01
-2.62401029e-02 3.57927442e-01 -1.63743287e-01 6.76137745e-01
-1.56445950e-01 -2.21020311e-01 3.29576492e-01 1.06733310e+00
4.05690968e-01 6.30315244e-02 -1.00333713e-01 7.07171917e-01
-6.20348275e-01 -1.09815381e-01 -4.89998788e-01 1.42303377e-01
4.52325940e-01 1.37165141e+00 -6.60772085e-01 -1.17542647e-01
-7.02466726e-01 1.18635356e+00 7.00867176e-02 3.23298216e-01
-1.12869537e+00 -4.44735050e-01 7.91941285e-01 3.81983668e-01
2.21022502e-01 -1.23600952e-01 3.63388583e-02 -1.32217276e+00
3.55262570e-02 -1.11822069e+00 1.61951378e-01 -1.19432020e+00
-1.24786282e+00 5.19136369e-01 -2.76905090e-01 -1.44752419e+00
3.39469403e-01 -4.89057124e-01 -2.83423811e-01 7.42796898e-01
-1.99158716e+00 -1.10713911e+00 -8.24678421e-01 9.02318180e-01
5.33870697e-01 1.46947682e-01 1.45846009e-01 7.98748732e-01
-5.05178869e-01 5.07464826e-01 2.29179755e-01 3.75258252e-02
1.03829610e+00 -9.71719921e-01 6.16009414e-01 9.42417026e-01
-2.89738268e-01 4.93823886e-01 4.38138574e-01 -5.47198594e-01
-1.61166048e+00 -1.35001528e+00 2.54182994e-01 1.76760957e-01
5.27714908e-01 -4.29084033e-01 -1.08599496e+00 7.22056866e-01
2.29539424e-01 2.99648404e-01 4.25542980e-01 -3.64910185e-01
-7.67514050e-01 -5.57059705e-01 -1.05028534e+00 6.41637146e-01
1.12000036e+00 -7.30608225e-01 2.52948105e-01 1.41906872e-01
1.24261165e+00 -4.86182451e-01 -1.14097273e+00 3.26320827e-01
5.48102915e-01 -1.24735904e+00 1.23995078e+00 2.68950790e-01
7.64399409e-01 -6.37383938e-01 -5.19554257e-01 -8.96965146e-01
-2.40963995e-01 -8.41412604e-01 -3.75084579e-01 1.22431040e+00
-5.97183593e-02 -6.49360776e-01 5.18541634e-01 3.72739255e-01
-7.10383281e-02 -5.14987767e-01 -6.53079867e-01 -6.24889851e-01
-3.69191408e-01 -4.44179714e-01 7.33715653e-01 7.95213759e-01
-5.45826077e-01 1.09087661e-01 -8.54851842e-01 -3.95503007e-02
8.78442824e-01 1.62213892e-01 6.89704120e-01 -8.03275347e-01
-3.93955857e-01 -2.06972539e-01 -2.65505284e-01 -1.25476575e+00
-3.69996950e-02 -7.78845429e-01 -1.72215894e-01 -1.45453632e+00
6.15535855e-01 -6.28521025e-01 -4.38418537e-01 2.02363536e-01
7.07022399e-02 9.16511357e-01 4.81553435e-01 5.42863190e-01
-1.04367995e+00 3.55031163e-01 1.44826841e+00 2.93647014e-02
-1.66522294e-01 -5.66693008e-01 -6.44888699e-01 4.69833076e-01
8.25100660e-01 -1.75462633e-01 -4.05191898e-01 -6.86294138e-01
6.31182551e-01 2.22560853e-01 4.68614727e-01 -1.00659156e+00
6.86327666e-02 -2.66592707e-02 5.84154546e-01 -6.53747141e-01
3.46235663e-01 -7.69529760e-01 6.47659481e-01 2.43696481e-01
-3.49553466e-01 5.37694581e-02 -3.80259119e-02 3.94805282e-01
-2.45459467e-01 4.08483386e-01 1.17642844e+00 3.63786938e-03
-1.01762068e+00 6.36667013e-01 2.32448548e-01 -7.00285360e-02
6.31900072e-01 1.77095400e-03 -1.07066023e+00 -5.03846407e-01
-1.49531275e-01 -1.45636365e-01 8.52085590e-01 4.24464822e-01
1.00302482e+00 -1.45777214e+00 -7.03946233e-01 1.84207767e-01
-1.66285709e-01 3.06825805e-02 9.26160991e-01 7.57588148e-01
-9.28739607e-01 7.85809755e-02 -3.66318852e-01 -4.00188804e-01
-1.16401684e+00 4.69283164e-01 1.82807028e-01 -3.54779243e-01
-1.19098699e+00 4.41879809e-01 4.01093423e-01 -1.90387055e-01
1.55988708e-01 -3.48298363e-02 4.13108096e-02 -3.45720470e-01
1.00749779e+00 6.71262741e-01 -2.17915848e-01 -6.51261389e-01
-1.58740692e-02 6.33708477e-01 -2.50012010e-01 7.60263726e-02
1.52543473e+00 -6.88332200e-01 -4.26872075e-01 3.01456660e-01
1.55962861e+00 -2.58133262e-01 -1.58547759e+00 -3.72364849e-01
-6.64533257e-01 -8.72298300e-01 3.71144593e-01 -5.94528019e-01
-1.58578527e+00 7.62152731e-01 9.63496208e-01 -1.37241557e-01
1.75427353e+00 -1.26335463e-02 1.35491002e+00 8.85099545e-02
3.66336226e-01 -8.47324550e-01 2.64584213e-01 1.42219976e-01
8.29136550e-01 -1.20965326e+00 1.02143072e-01 -4.08021241e-01
-4.52241361e-01 9.46623802e-01 5.28570771e-01 -1.87074259e-01
6.67191386e-01 4.57512081e-01 7.90177882e-02 8.47376511e-02
-7.79711246e-01 2.37016883e-02 6.82889223e-02 4.44089949e-01
4.42049503e-01 4.36302722e-02 6.92600086e-02 -4.65675630e-02
4.95414343e-03 4.84801978e-02 6.61946952e-01 6.54787898e-01
-3.98198187e-01 -8.72309983e-01 -2.68448114e-01 5.09530008e-01
-6.37421429e-01 -3.44013572e-01 2.70413667e-01 6.27744317e-01
-2.21949115e-01 8.19840252e-01 1.76704749e-01 -6.10025108e-01
4.29549068e-02 -6.24750853e-01 4.31199968e-01 -1.47307396e-01
-1.90496624e-01 1.40547082e-02 -2.05755800e-01 -1.16201866e+00
-5.91142535e-01 -1.90278932e-01 -1.06029797e+00 -9.95622039e-01
1.70648709e-01 -5.92196643e-01 8.40755463e-01 3.13090861e-01
5.00252306e-01 5.80921650e-01 7.83669770e-01 -8.90223145e-01
1.68490736e-03 -7.35083401e-01 -7.66739547e-01 3.84117097e-01
4.06145573e-01 -2.99390376e-01 -3.16947281e-01 1.69164062e-01] | [10.860194206237793, -2.118788003921509] |
20f2b4a1-d094-4828-a106-be94d80c794c | evaluating-graph-generative-models-with | 2206.06234 | null | https://arxiv.org/abs/2206.06234v1 | https://arxiv.org/pdf/2206.06234v1.pdf | Evaluating Graph Generative Models with Contrastively Learned Features | A wide range of models have been proposed for Graph Generative Models, necessitating effective methods to evaluate their quality. So far, most techniques use either traditional metrics based on subgraph counting, or the representations of randomly initialized Graph Neural Networks (GNNs). We propose using representations from contrastively trained GNNs, rather than random GNNs, and show this gives more reliable evaluation metrics. Neither traditional approaches nor GNN-based approaches dominate the other, however: we give examples of graphs that each approach is unable to distinguish. We demonstrate that Graph Substructure Networks (GSNs), which in a way combine both approaches, are better at distinguishing the distances between graph datasets. | ['Danica J. Sutherland', 'Kaveh Hassani', 'Hamed Shirzad'] | 2022-06-13 | null | null | null | null | ['subgraph-counting'] | ['graphs'] | [ 2.38531530e-01 3.85988951e-01 -1.72025293e-01 -2.56483674e-01
-1.74641833e-01 -6.74081802e-01 1.21913278e+00 1.28383785e-01
4.43730280e-02 6.40871882e-01 2.05419511e-01 -5.36501706e-01
-5.06499887e-01 -1.43907297e+00 -4.63471860e-01 -5.55830002e-01
-4.28906560e-01 8.11487794e-01 2.56695122e-01 -3.98119509e-01
1.78696588e-01 7.32889712e-01 -1.27117562e+00 -1.51763454e-01
6.94711864e-01 3.72806400e-01 -2.77852535e-01 9.52300131e-01
-3.47929955e-01 9.40843463e-01 -8.52769911e-01 -5.90717256e-01
1.87306911e-01 -9.33631897e-01 -7.39006519e-01 -4.10917960e-02
6.18538558e-01 3.20876390e-02 -7.86119103e-01 1.08983684e+00
2.80004412e-01 1.64758235e-01 9.56376255e-01 -1.51671052e+00
-1.23507798e+00 1.20494437e+00 -2.13211387e-01 2.97923654e-01
4.98686314e-01 8.14181939e-03 1.24879992e+00 -2.88725138e-01
7.60146201e-01 1.42780709e+00 9.86423314e-01 5.19761026e-01
-1.48636127e+00 -3.98007542e-01 -1.21044181e-02 -9.79586244e-02
-1.19783044e+00 -9.25754905e-02 7.95690656e-01 -2.81549275e-01
1.15284503e+00 2.72703081e-01 7.82639682e-01 1.35725427e+00
1.59654897e-02 4.83033121e-01 1.09510887e+00 -4.95821178e-01
8.24039429e-02 -2.61692315e-01 3.60932380e-01 8.56365919e-01
1.01538658e+00 2.72500366e-01 -4.39805463e-02 -2.90620953e-01
1.09099853e+00 5.58479801e-02 -3.13904017e-01 -6.90359712e-01
-9.61659193e-01 1.04545248e+00 7.68485725e-01 7.42632270e-01
-1.80609927e-01 5.09318173e-01 2.31739074e-01 4.78271157e-01
2.99462914e-01 6.76348269e-01 6.37265220e-02 1.89469144e-01
-9.20442045e-01 2.28069589e-01 1.03998530e+00 9.68220472e-01
8.19614887e-01 4.00821716e-01 -4.85761315e-02 4.53663915e-01
2.86525398e-01 1.40032470e-01 3.49050403e-01 -4.08217102e-01
1.22185662e-01 9.24021184e-01 -6.34288728e-01 -1.40977097e+00
-3.93037111e-01 -4.47344661e-01 -8.92275035e-01 8.79400894e-02
4.60538238e-01 1.56815574e-01 -1.44540644e+00 1.65704966e+00
-2.80832350e-01 7.28602484e-02 -1.03684263e-02 3.01775008e-01
1.16512525e+00 2.52526194e-01 3.70404273e-02 2.34464779e-01
6.90121233e-01 -7.81529427e-01 -3.77023369e-01 -1.69703409e-01
6.58491075e-01 -3.85460794e-01 7.29051888e-01 2.70715564e-01
-1.11128783e+00 -4.21638191e-01 -1.27505028e+00 3.70632976e-01
-8.20616305e-01 -4.94116753e-01 1.02021408e+00 1.14697886e+00
-1.80278397e+00 1.19862890e+00 -7.47444272e-01 -6.92685068e-01
4.23071206e-01 3.82032514e-01 -2.48908505e-01 -1.54604390e-01
-9.76577342e-01 8.93891633e-01 6.42304599e-01 -1.75889999e-01
-1.02076149e+00 -1.14733372e-02 -1.14205980e+00 1.42623276e-01
6.81662112e-02 -7.36040115e-01 8.45224679e-01 -9.83137131e-01
-1.05074501e+00 7.98099697e-01 3.91130209e-01 -6.83989048e-01
1.45246148e-01 3.86453629e-01 -6.02639437e-01 1.47825137e-01
-2.43508130e-01 5.42723477e-01 5.61590195e-01 -1.43015766e+00
1.28151104e-01 -6.66049868e-02 3.94736350e-01 -7.50585720e-02
-1.41630769e-01 -1.26102999e-01 -1.01527870e-02 -6.31341457e-01
2.68539369e-01 -8.62606227e-01 -5.01974106e-01 -5.07696927e-01
-8.21530521e-01 -3.83180797e-01 6.98537052e-01 -2.40312323e-01
1.23368764e+00 -1.62797678e+00 -5.03384834e-03 5.98511934e-01
9.52189267e-01 4.02589053e-01 -5.58476806e-01 8.08764040e-01
-3.15458119e-01 6.25036597e-01 -1.88385755e-01 -1.59167305e-01
2.47414440e-01 6.10675037e-01 -3.19387503e-02 3.96152318e-01
2.56486714e-01 1.19489741e+00 -1.03907931e+00 -3.18798363e-01
1.94963560e-01 5.77796042e-01 -2.51292080e-01 -2.36240923e-02
-2.31154963e-01 -1.09579079e-01 -1.23756260e-01 4.75482106e-01
5.84906638e-01 -5.99279940e-01 5.95040381e-01 2.46465594e-01
6.28511071e-01 4.63261694e-01 -1.06282723e+00 1.15832531e+00
2.40017492e-02 6.95289493e-01 -5.56446433e-01 -1.09143150e+00
1.13015759e+00 -4.86544445e-02 -2.93565206e-02 -5.94169259e-01
1.19269662e-01 1.49652049e-01 4.20157582e-01 1.60627365e-01
4.57951725e-01 4.35994193e-02 7.30373859e-02 6.37614667e-01
6.05728984e-01 -1.75631836e-01 6.84621513e-01 6.75356984e-01
1.79748380e+00 5.44435605e-02 6.07837319e-01 -2.32748806e-01
1.13605402e-01 -1.21691428e-01 -3.45738642e-02 1.11662745e+00
-4.48136553e-02 8.14633012e-01 7.90081382e-01 -5.36647141e-01
-1.00890183e+00 -1.34281123e+00 3.19147199e-01 8.03235888e-01
1.08984560e-02 -9.46996808e-01 -6.81884348e-01 -1.11485338e+00
-4.27973382e-02 6.18619204e-01 -7.96704113e-01 -3.07447255e-01
-5.30335724e-01 -8.09854746e-01 8.06436300e-01 6.99784160e-01
2.99591906e-02 -1.20458686e+00 9.17152986e-02 1.12187997e-01
3.72804075e-01 -8.70647132e-01 6.94625378e-02 2.87470222e-01
-1.26750755e+00 -1.26279879e+00 -5.91779649e-01 -7.30937660e-01
9.23272192e-01 3.67991418e-01 1.91366971e+00 8.45926702e-01
-5.64243784e-03 4.98822421e-01 -4.35138226e-01 -1.66040529e-02
-9.77977574e-01 1.84562132e-01 -1.92954242e-01 -5.25509179e-01
3.80572110e-01 -1.10579085e+00 -1.86247170e-01 7.51696751e-02
-9.70091760e-01 -2.78116077e-01 8.24562669e-01 6.57066584e-01
2.10991159e-01 1.26898224e-02 2.53124565e-01 -1.34244764e+00
1.21336174e+00 -5.41988432e-01 -3.58490050e-01 2.31010929e-01
-1.00415814e+00 3.84224892e-01 7.95674860e-01 -4.43928540e-01
-1.14769772e-01 -5.00495195e-01 -1.00328967e-01 -3.33339423e-01
-2.91694820e-01 6.18961573e-01 5.77482115e-03 -4.13718790e-01
1.04799891e+00 2.19690323e-01 9.46145952e-02 -1.78385288e-01
6.35421872e-01 -1.37096450e-01 3.35200757e-01 -3.28123510e-01
1.12369967e+00 9.38628763e-02 2.53056765e-01 -6.01340890e-01
-3.41202557e-01 -1.00261256e-01 -5.40608585e-01 -1.53022900e-01
5.13518095e-01 -3.86828303e-01 -1.85497612e-01 2.47598320e-01
-9.90360737e-01 -2.28410527e-01 -4.19365048e-01 3.32245559e-01
-3.84809643e-01 6.33720577e-01 -7.71634281e-01 -6.57379866e-01
-8.75153169e-02 -7.56130695e-01 6.36227608e-01 1.69346765e-01
-3.01995784e-01 -1.46293771e+00 4.38316286e-01 -3.61264735e-01
7.62782335e-01 7.28232205e-01 1.17944026e+00 -1.15049970e+00
-6.60887122e-01 -3.11940759e-01 -3.55085850e-01 2.77954578e-01
2.52682239e-01 3.28548312e-01 -6.85333073e-01 -3.95864189e-01
-5.80666184e-01 -8.40736553e-02 1.03683662e+00 5.63546896e-01
7.75418222e-01 -3.72997344e-01 -5.74291170e-01 5.23723662e-01
1.77549207e+00 -5.14817201e-02 1.10622239e+00 1.30140856e-02
1.04684901e+00 2.86512733e-01 -3.61852467e-01 -1.97512165e-01
3.32017720e-01 1.68872356e-01 6.45312905e-01 -2.66372859e-01
-5.27474105e-01 -4.41154093e-01 2.83123881e-01 1.11039913e+00
-6.72216833e-01 -8.19723129e-01 -9.94962811e-01 4.29369271e-01
-1.52187467e+00 -9.93094087e-01 -4.84183371e-01 1.89661658e+00
2.30473846e-01 4.35754955e-01 2.96333134e-01 1.82386115e-01
9.11583781e-01 5.33323944e-01 -2.13018253e-01 -4.25479919e-01
-3.39900970e-01 7.47459292e-01 4.31891680e-01 2.36843750e-01
-9.45010006e-01 7.24745750e-01 8.16045570e+00 5.44197202e-01
-6.06867790e-01 -2.20298290e-01 4.07977164e-01 4.98938948e-01
-7.12960064e-01 3.12232345e-01 -2.50704765e-01 9.29604024e-02
1.29233098e+00 -2.98395127e-01 5.39907455e-01 8.91836822e-01
-6.60131514e-01 3.20093006e-01 -1.27144337e+00 8.32032979e-01
3.29227120e-01 -1.39436316e+00 5.13923705e-01 2.56775469e-01
7.76635766e-01 1.68565020e-01 -1.43629238e-01 6.01691186e-01
1.21193504e+00 -1.48614359e+00 2.65125453e-01 6.44720197e-01
3.38321179e-01 -6.71408713e-01 7.56327450e-01 4.48801294e-02
-1.43622124e+00 3.19977701e-01 -4.92429703e-01 -1.18583292e-01
-2.00008482e-01 5.42088628e-01 -9.64219034e-01 9.49249685e-01
3.04515243e-01 6.81985438e-01 -1.22063816e+00 1.11991096e+00
-4.20680106e-01 7.96825886e-01 -1.12123534e-01 -4.33133036e-01
3.18819612e-01 -3.86190593e-01 5.45108557e-01 1.16589200e+00
4.00162250e-01 -5.67390084e-01 1.05650388e-01 1.18096709e+00
-1.93714261e-01 1.85660720e-02 -1.28779316e+00 -7.16265500e-01
1.82359383e-01 1.28253198e+00 -1.36130989e+00 -3.27178061e-01
-3.32938552e-01 6.21546388e-01 5.21843493e-01 3.06659847e-01
-7.75239110e-01 -4.75842625e-01 3.94596219e-01 2.24953309e-01
2.30952889e-01 -4.41703439e-01 2.83605933e-01 -8.48614573e-01
-2.68284678e-01 -1.04020786e+00 5.75033307e-01 -6.66238070e-01
-1.67987227e+00 1.14023256e+00 1.05280146e-01 -9.72573102e-01
-5.57818413e-01 -7.24117279e-01 -8.74132454e-01 6.23513162e-01
-1.03447413e+00 -1.14259577e+00 -4.53813761e-01 3.94438744e-01
-2.15126529e-01 -1.10512279e-01 9.96927798e-01 1.03709891e-01
-2.33459085e-01 4.32833076e-01 -2.23665982e-01 4.40661430e-01
1.38707995e-01 -1.71969068e+00 1.12387204e+00 1.04581022e+00
8.69957328e-01 9.13336039e-01 6.84932590e-01 -6.34059250e-01
-1.09154522e+00 -9.71864343e-01 5.99303603e-01 -5.91121733e-01
5.17144561e-01 -4.85190451e-01 -9.55091178e-01 8.85787547e-01
3.54353517e-01 8.77178386e-02 4.96154398e-01 4.70328003e-01
-6.49583638e-01 3.83024186e-01 -9.82985258e-01 6.27531826e-01
1.52371252e+00 -4.79857028e-01 -5.07916093e-01 3.62676144e-01
6.71630263e-01 -9.74777713e-02 -7.41729736e-01 4.09140259e-01
1.91099554e-01 -1.33268547e+00 9.86004353e-01 -9.24881458e-01
1.96521878e-01 -1.32418081e-01 -2.00673882e-02 -1.45083320e+00
-5.45534551e-01 -5.37155032e-01 -2.17265144e-01 1.11497104e+00
5.30528665e-01 -9.56418693e-01 1.03852236e+00 5.34197353e-02
4.33849879e-02 -4.81963068e-01 -4.08712119e-01 -1.20345473e+00
1.24025764e-02 -1.96626619e-01 9.43141639e-01 1.01255202e+00
-3.24038386e-01 5.41272283e-01 -1.80817656e-02 -5.03086783e-02
5.55321038e-01 5.42195365e-02 9.23593581e-01 -1.68900430e+00
-3.09541732e-01 -9.62074518e-01 -1.27778530e+00 -6.41314685e-01
1.29431054e-01 -1.39588392e+00 -2.20935941e-01 -2.25162339e+00
2.82852739e-01 -2.58237302e-01 -3.49076927e-01 3.36798966e-01
-7.71036148e-02 3.07011127e-01 -1.45074353e-02 -2.90861204e-02
-6.60854101e-01 1.32824108e-01 9.96111691e-01 -2.99559593e-01
6.96707740e-02 -1.49697393e-01 -8.62472296e-01 7.30957448e-01
8.19726229e-01 -6.34580851e-01 -7.19831824e-01 -5.55145647e-03
3.79525840e-01 -3.49372506e-01 6.08434260e-01 -1.42624712e+00
6.69615045e-02 1.65219203e-01 4.42347646e-01 -4.47218478e-01
-8.34441930e-02 -2.08353817e-01 5.71654618e-01 4.97963548e-01
-1.69725388e-01 5.28775752e-01 -1.55527219e-01 7.20511317e-01
-1.90101370e-01 -3.81863207e-01 5.83307981e-01 -5.15819192e-01
-5.06418765e-01 5.03770053e-01 -7.42966905e-02 1.50810421e-01
5.35538316e-01 -5.82887650e-01 -6.81061149e-01 -8.03548396e-01
-7.78312862e-01 -3.81603837e-01 6.54561937e-01 1.74135625e-01
6.74944878e-01 -1.43446076e+00 -7.18382120e-01 8.75744000e-02
-1.47845242e-02 -3.52146983e-01 -2.39298284e-01 5.77355146e-01
-7.70299077e-01 4.65955352e-03 -3.24455976e-01 -5.14717340e-01
-1.01583898e+00 6.95806324e-01 4.80699003e-01 -8.26436639e-01
-5.46499252e-01 9.16085362e-01 1.17781349e-01 -8.23694229e-01
-6.99151233e-02 -4.43195105e-01 -3.03024262e-01 -1.08742371e-01
2.47385111e-02 2.76154906e-01 1.26786679e-01 -5.23205400e-01
-2.10559398e-01 2.32141078e-01 1.89404376e-02 2.47519121e-01
1.37964940e+00 3.25163752e-01 -2.08014026e-01 2.68530846e-01
1.02914059e+00 -1.38983279e-02 -5.53601503e-01 5.63550927e-03
2.00986251e-01 -3.59629929e-01 -3.89394999e-01 -5.14182866e-01
-1.14278483e+00 7.12816179e-01 2.96614438e-01 1.23582065e+00
8.89226317e-01 2.40913838e-01 4.03921127e-01 4.63053733e-01
4.55895394e-01 -4.77966249e-01 1.76052451e-01 4.99422371e-01
7.45040834e-01 -8.02964568e-01 2.51580834e-01 -3.78183395e-01
-2.03776941e-01 1.29080129e+00 3.45610976e-01 -7.72378922e-01
4.19776738e-01 1.83997989e-01 -2.49883950e-01 -7.14792252e-01
-5.76859057e-01 -6.73239172e-01 4.21523213e-01 1.14517546e+00
4.27164644e-01 2.38555849e-01 -7.86098018e-02 1.22539259e-01
-4.73548174e-01 -5.32012284e-01 7.02716649e-01 7.31081903e-01
-2.45087028e-01 -1.30304503e+00 2.03040726e-02 8.72109115e-01
-2.15509474e-01 -3.42080176e-01 -1.03963757e+00 1.36889803e+00
-2.03630492e-01 8.57053638e-01 -1.11532144e-01 -7.75574028e-01
2.42880508e-01 -9.62246358e-02 8.90367806e-01 -7.07205176e-01
-6.23462617e-01 -4.27998543e-01 4.41267878e-01 -5.03790140e-01
-5.07983983e-01 -1.65139914e-01 -8.84069383e-01 -7.04799771e-01
-6.32599652e-01 1.05455160e-01 2.89762586e-01 5.71879506e-01
1.39587194e-01 5.58506787e-01 3.90955508e-01 -9.20678377e-01
-1.86428189e-01 -1.03118098e+00 -8.78853858e-01 5.54290116e-01
-2.50662933e-03 -7.13395357e-01 -8.25227022e-01 -5.41330874e-01] | [6.9526519775390625, 6.240691184997559] |
5ab37a86-4536-4a14-885a-1a1504c99f4a | linear-transformations-for-cross-lingual | 1807.04172 | null | http://arxiv.org/abs/1807.04172v1 | http://arxiv.org/pdf/1807.04172v1.pdf | Linear Transformations for Cross-lingual Semantic Textual Similarity | Cross-lingual semantic textual similarity systems estimate the degree of the
meaning similarity between two sentences, each in a different language.
State-of-the-art algorithms usually employ machine translation and combine vast
amount of features, making the approach strongly supervised, resource rich, and
difficult to use for poorly-resourced languages.
In this paper, we study linear transformations, which project monolingual
semantic spaces into a shared space using bilingual dictionaries. We propose a
novel transformation, which builds on the best ideas from prior works. We
experiment with unsupervised techniques for sentence similarity based only on
semantic spaces and we show they can be significantly improved by the word
weighting. Our transformation outperforms other methods and together with word
weighting leads to very promising results on several datasets in different
languages. | ['Tomáš Brychcín'] | 2018-07-11 | null | null | null | null | ['cross-lingual-semantic-textual-similarity'] | ['natural-language-processing'] | [ 6.39453754e-02 -4.60742801e-01 -3.79018456e-01 -6.09605968e-01
-9.10869658e-01 -7.83663690e-01 8.99531364e-01 3.65967959e-01
-6.72741294e-01 6.35735035e-01 6.51189506e-01 -2.16980502e-01
-4.22284976e-02 -7.91521072e-01 -2.40373686e-01 -4.71766829e-01
7.01630354e-01 5.47193408e-01 2.53935069e-01 -7.92066693e-01
4.92595911e-01 -1.80466380e-02 -1.20023656e+00 4.52884614e-01
1.00062025e+00 4.32936817e-01 3.81838322e-01 1.36055559e-01
-7.79465020e-01 3.96622211e-01 -9.29674208e-02 -5.52254021e-01
2.61724502e-01 -7.17333317e-01 -1.08594131e+00 -3.33708346e-01
4.94163066e-01 6.12381995e-01 -9.79579315e-02 1.46556628e+00
5.55313945e-01 9.17548984e-02 5.74102402e-01 -9.71511364e-01
-9.70165193e-01 6.93570614e-01 -2.66602665e-01 1.67017281e-01
7.50434637e-01 -4.52148646e-01 1.29663169e+00 -1.08702481e+00
7.47689366e-01 1.37774825e+00 9.94459689e-01 2.84563184e-01
-1.16313529e+00 -4.13644075e-01 -2.05747492e-04 6.13978922e-01
-1.35127640e+00 -4.34824407e-01 7.63015747e-01 -2.39251107e-01
1.21045196e+00 2.17696652e-01 3.16556454e-01 9.39525247e-01
1.22070387e-01 4.06398565e-01 1.45661783e+00 -8.81184876e-01
-4.38556224e-02 4.30347890e-01 2.58943588e-01 5.45542121e-01
-3.41010094e-02 -3.58351827e-01 -4.12062496e-01 -1.46190777e-01
1.17181137e-01 1.70280665e-01 -9.92313847e-02 -4.26405072e-01
-1.55629241e+00 1.06197047e+00 1.98329926e-01 1.16778588e+00
4.18679081e-02 -4.42892253e-01 6.52980268e-01 7.89482415e-01
7.54506230e-01 6.13767743e-01 -5.53874195e-01 -6.35867789e-02
-8.26181531e-01 1.31056875e-01 7.13962018e-01 9.82583404e-01
9.69290018e-01 -5.15473068e-01 -6.55360892e-02 1.30154371e+00
1.61676973e-01 6.60970747e-01 1.07893825e+00 -5.71942449e-01
4.18692648e-01 6.68121397e-01 -2.30987817e-01 -9.63005781e-01
-1.97642431e-01 -9.68675390e-02 -5.75628817e-01 -3.39409828e-01
2.48248041e-01 1.09032743e-01 -4.67677474e-01 1.76129651e+00
1.85937718e-01 2.39819754e-02 4.08285648e-01 8.11801195e-01
7.34217286e-01 4.85780746e-01 5.13278805e-02 -8.72563794e-02
1.46527278e+00 -1.24501657e+00 -6.79833710e-01 -2.05138639e-01
1.04227185e+00 -1.37087822e+00 1.46681833e+00 6.14395626e-02
-8.43565226e-01 -5.99466622e-01 -8.47330272e-01 -2.65479416e-01
-7.76018918e-01 -1.12269193e-01 6.37285948e-01 5.74557006e-01
-1.14277554e+00 8.28178525e-01 -3.84799600e-01 -1.17846596e+00
-2.35740319e-01 4.29494260e-03 -5.78489959e-01 -2.58000314e-01
-1.46573889e+00 1.39445674e+00 5.73246717e-01 -5.80239892e-01
-6.00700267e-03 -4.41730738e-01 -1.01237178e+00 -1.48993284e-01
2.66981155e-01 -8.07798922e-01 8.48153353e-01 -1.06637466e+00
-1.49865746e+00 1.30344248e+00 -2.68811315e-01 -3.02930355e-01
1.77802756e-01 -9.45999622e-02 -6.18727505e-01 -2.06971601e-01
4.90774661e-01 3.23914528e-01 4.56581622e-01 -7.58596718e-01
-6.12939835e-01 -4.04558361e-01 -6.90209344e-02 4.28003341e-01
-8.12971711e-01 5.26044130e-01 -3.29429120e-01 -8.96979272e-01
1.44778684e-01 -9.47545707e-01 -2.17019692e-01 -3.65048319e-01
7.56217018e-02 -3.64565104e-01 5.12405157e-01 -6.61933780e-01
1.12418640e+00 -2.06842494e+00 3.58206362e-01 -2.97227837e-02
-2.10532993e-01 1.98422194e-01 -3.64329636e-01 8.70047033e-01
-9.91928577e-02 -5.66330645e-03 -4.80179191e-01 -2.37793013e-01
1.48562089e-01 3.92412841e-01 -2.89075136e-01 3.58412594e-01
-2.79734313e-01 7.88174629e-01 -1.24162531e+00 -6.85302854e-01
1.36420637e-01 2.13627785e-01 -3.25075060e-01 1.65341705e-01
3.13575625e-01 2.07306758e-01 -3.85338128e-01 2.93653071e-01
3.71650487e-01 1.08160339e-01 4.69576061e-01 -2.45595366e-01
-2.29105726e-02 5.72775483e-01 -8.97057056e-01 2.37425065e+00
-8.90552461e-01 4.00318086e-01 -4.67973083e-01 -1.34186959e+00
1.15779293e+00 3.32555711e-01 3.22883457e-01 -7.07458258e-01
1.58034831e-01 5.59328735e-01 -1.21576212e-01 -5.22245407e-01
5.23859084e-01 -5.60633063e-01 -2.49047264e-01 6.42454743e-01
3.59121948e-01 -5.67272365e-01 3.86864811e-01 2.18921378e-02
9.45297837e-01 9.69569981e-02 7.38951325e-01 -8.28275740e-01
9.44716930e-01 -1.25900894e-01 4.69667703e-01 3.97040188e-01
-8.47707316e-02 4.61242288e-01 8.07709768e-02 -3.66208822e-01
-1.17398906e+00 -1.10525215e+00 -8.48759860e-02 1.31738520e+00
2.57538587e-01 -6.51584566e-01 -7.68804669e-01 -9.79659021e-01
-1.57208622e-01 6.96779430e-01 -2.94920176e-01 -2.37755805e-01
-5.27145803e-01 -7.02825904e-01 4.68133807e-01 4.43315566e-01
2.21519917e-01 -8.53807151e-01 2.74360120e-01 1.01276271e-01
-3.37388724e-01 -1.41190195e+00 -7.41998613e-01 -1.23527974e-01
-9.16192591e-01 -7.91152298e-01 -7.03044474e-01 -1.17243505e+00
5.09851575e-01 4.61282909e-01 1.24119115e+00 -9.49776769e-02
4.41322587e-02 1.86553925e-01 -6.61058784e-01 -8.14006850e-03
-5.56290984e-01 2.90086806e-01 4.94907916e-01 2.92013213e-02
8.66492450e-01 -6.44401014e-01 -4.95459139e-03 2.34619439e-01
-7.08405554e-01 -1.18237145e-01 3.84989589e-01 9.62939262e-01
4.70861226e-01 -2.81591564e-01 4.44465727e-01 -1.07426500e+00
8.10025752e-01 -4.99079823e-01 -9.40312073e-02 5.48815310e-01
-8.84129584e-01 6.45869792e-01 8.73924434e-01 -2.26613671e-01
-1.02555335e+00 -2.85761058e-01 -8.81660655e-02 -2.90277088e-03
-9.11166817e-02 3.39257747e-01 -5.73787391e-02 -2.34074384e-01
6.13637626e-01 2.53627777e-01 -2.80219078e-01 -7.80710280e-01
7.29029179e-01 8.83038819e-01 4.10377771e-01 -7.33565569e-01
7.79192328e-01 4.01632458e-01 -2.56518096e-01 -6.23643875e-01
-9.72890496e-01 -8.28938544e-01 -8.48371327e-01 3.06516469e-01
8.02202106e-01 -8.17204833e-01 5.34540899e-02 1.54513732e-01
-1.11357224e+00 1.92928135e-01 -2.43072316e-01 7.77496219e-01
-4.30860460e-01 8.02148879e-01 -4.32545245e-01 -7.96957612e-02
-4.57728297e-01 -8.49617481e-01 1.01384068e+00 -1.64324209e-01
-3.94227415e-01 -1.47603047e+00 6.53784215e-01 4.40035582e-01
6.14216149e-01 -3.79850358e-01 9.34567750e-01 -1.01135039e+00
2.41181910e-01 1.21570900e-02 -1.91887110e-01 5.44128716e-01
4.97373790e-01 -3.89510214e-01 -6.51790082e-01 -3.14137697e-01
3.14174473e-01 -2.34464914e-01 8.25053871e-01 -1.78641856e-01
6.89614654e-01 -1.11489333e-01 -2.13758811e-01 4.75919455e-01
1.43700576e+00 -2.14461014e-01 3.36861044e-01 4.62708712e-01
7.18832850e-01 7.74460435e-01 6.24636531e-01 5.78399561e-02
4.86663371e-01 9.62201774e-01 -3.71603459e-01 -8.19907635e-02
-1.78606912e-01 -2.28649095e-01 4.32276189e-01 1.93794608e+00
-4.19465713e-02 1.24414913e-01 -8.58151138e-01 8.47575128e-01
-2.01436353e+00 -9.01197076e-01 -1.48686588e-01 2.12562728e+00
1.19301617e+00 -1.31948367e-01 -1.64512992e-01 -5.09017482e-02
7.99407244e-01 2.32493192e-01 1.53316379e-01 -7.24413872e-01
-4.18955326e-01 5.20914614e-01 5.28901875e-01 8.06608975e-01
-9.36159194e-01 1.46656919e+00 6.31329155e+00 1.10678196e+00
-9.26147342e-01 6.89182878e-01 6.98464364e-02 2.26208508e-01
-7.17375755e-01 3.25651288e-01 -5.26649177e-01 4.32157159e-01
7.92810500e-01 -5.98213613e-01 4.08625156e-01 6.82925165e-01
-4.92604598e-02 2.19029456e-01 -1.09667218e+00 1.15045094e+00
6.53318226e-01 -9.22513664e-01 4.58624996e-02 -5.04167557e-01
9.83565867e-01 2.50635296e-01 -3.24214250e-01 2.34795541e-01
4.88798469e-01 -7.08611369e-01 3.84328902e-01 4.88972157e-01
5.77042341e-01 -6.57546222e-01 9.74134386e-01 9.00293291e-02
-1.29394412e+00 4.28143799e-01 -5.99419057e-01 -1.57491535e-01
1.25265822e-01 5.23551702e-01 -3.49110156e-01 7.88587213e-01
5.27953625e-01 1.06952631e+00 -7.01394737e-01 5.87607443e-01
-4.89260048e-01 2.50711024e-01 -1.93216756e-01 -2.43957072e-01
3.96325111e-01 -4.99284536e-01 4.80521768e-01 1.50539029e+00
5.94716132e-01 -2.87925780e-01 3.44756842e-01 5.35100341e-01
3.60434130e-02 9.73188698e-01 -8.81926715e-01 -6.15641649e-04
2.80191332e-01 1.21255040e+00 -5.38782179e-01 -5.91449916e-01
-6.55326426e-01 1.36129081e+00 5.11578083e-01 -3.11487056e-02
-5.49068689e-01 -6.19260609e-01 7.17917681e-01 -3.32687169e-01
-2.16456931e-02 -2.14745849e-01 -2.54258811e-01 -1.66442907e+00
1.52338192e-01 -8.40129495e-01 3.77360880e-01 -5.02152383e-01
-1.95201492e+00 7.14882553e-01 -1.27260283e-01 -1.24997509e+00
-2.90414751e-01 -6.65888608e-01 -4.81662512e-01 8.66843998e-01
-1.55453074e+00 -1.12918961e+00 1.53623605e-02 8.00484240e-01
7.14685798e-01 -5.68767607e-01 1.14716136e+00 5.05630910e-01
-3.61564606e-02 6.30278826e-01 4.83120650e-01 -1.13175258e-01
1.33518016e+00 -1.30638635e+00 6.49146616e-01 7.60471404e-01
6.88065171e-01 7.21058726e-01 6.39742017e-01 -3.59978557e-01
-1.20048046e+00 -7.89973855e-01 1.97177362e+00 -5.10191977e-01
1.12087524e+00 -3.87004405e-01 -1.00478804e+00 2.94200450e-01
5.28040290e-01 -1.86987102e-01 9.82450783e-01 4.36915070e-01
-6.41198456e-01 -9.07540768e-02 -1.07178235e+00 6.54032052e-01
1.34837103e+00 -1.04723072e+00 -1.33905005e+00 6.64551497e-01
7.34260678e-01 1.67322949e-01 -8.22640002e-01 1.31044686e-01
3.11138958e-01 -7.74666309e-01 8.38632643e-01 -9.24664676e-01
2.56058425e-01 -2.96207100e-01 -4.50934261e-01 -1.60345483e+00
-3.48655045e-01 -3.43278080e-01 6.95485353e-01 1.33217728e+00
3.04559648e-01 -8.11599016e-01 1.45657510e-01 4.90687303e-02
-6.54887035e-02 -2.61589229e-01 -8.02850127e-01 -1.14112437e+00
3.87350857e-01 -4.10082817e-01 6.48045301e-01 1.50382483e+00
6.19216561e-01 7.44101763e-01 -2.82648057e-01 -4.19899285e-01
4.55143511e-01 3.39574099e-01 4.54133481e-01 -1.08537328e+00
-2.90698916e-01 -6.23535275e-01 -6.83506727e-01 -6.43599808e-01
7.34704673e-01 -1.53292799e+00 -1.07805461e-01 -1.31165636e+00
4.69029367e-01 -2.77233481e-01 -4.72064465e-01 5.52061319e-01
-4.44028497e-01 5.04400253e-01 1.54062390e-01 2.43317634e-01
-5.82693517e-01 5.73769867e-01 7.96774209e-01 -2.62086272e-01
1.95396990e-01 -3.96324366e-01 -6.47256851e-01 8.58584106e-01
8.15761089e-01 -6.55048788e-01 -2.90534317e-01 -7.17880964e-01
2.65847921e-01 -4.79030162e-01 -1.78887114e-01 -8.11091542e-01
1.05680339e-01 -2.67811120e-01 -2.73296446e-01 7.83055834e-03
-4.51412238e-03 -8.09224904e-01 -6.04071692e-02 3.22427124e-01
-4.75497156e-01 3.56501400e-01 -2.59463519e-01 2.03592613e-01
-6.30379975e-01 -5.88885248e-01 7.16458321e-01 -2.56715566e-01
-7.35936999e-01 -2.29082983e-02 -1.25925198e-01 3.79497766e-01
7.92249084e-01 1.13839075e-01 9.14241970e-02 -1.36989266e-01
-4.42804992e-01 -1.60214558e-01 7.92808235e-01 9.37494457e-01
1.75823912e-01 -1.83560896e+00 -9.35371280e-01 5.31486273e-02
5.92375815e-01 -1.02709544e+00 -7.33907372e-02 7.81766415e-01
-3.58377516e-01 6.59465909e-01 -2.86191672e-01 -2.10362494e-01
-1.39976764e+00 8.20519149e-01 -6.60751539e-04 -3.61078680e-01
-3.98921609e-01 3.99155200e-01 3.19216959e-02 -1.06892979e+00
-3.27532470e-01 -1.52560055e-01 -3.28101337e-01 1.01297230e-01
3.74248326e-01 2.84264505e-01 1.52738497e-01 -1.00749481e+00
-5.28221726e-01 1.19235861e+00 3.90087292e-02 -2.12363079e-01
1.13798356e+00 -2.95336425e-01 -5.77705085e-01 5.91097057e-01
1.54621589e+00 1.78153604e-01 -9.06718597e-02 -9.36736882e-01
4.41409975e-01 -6.67503655e-01 -1.36544108e-01 -3.40267628e-01
-8.92109632e-01 7.93765485e-01 5.24169505e-01 4.13277596e-02
9.78255212e-01 1.07114404e-01 9.93972957e-01 6.33359313e-01
5.16990662e-01 -1.31182432e+00 -2.75360346e-01 8.40859056e-01
5.85964084e-01 -1.42391467e+00 -5.23384959e-02 -3.75388652e-01
-6.88679516e-01 1.13805187e+00 1.26943693e-01 -2.16172159e-01
5.51622212e-01 1.21902592e-01 3.25957209e-01 2.49534957e-02
-4.89018440e-01 -4.20609921e-01 5.63743353e-01 4.34381455e-01
8.72997642e-01 1.27178609e-01 -1.24413884e+00 4.72151756e-01
-3.59976918e-01 -3.19111437e-01 8.22662041e-02 7.17940152e-01
-4.33421135e-01 -1.91210377e+00 -2.04698369e-01 4.38851304e-02
-5.05014122e-01 -7.05445051e-01 -5.42511880e-01 3.67859185e-01
2.01074228e-01 8.72176528e-01 -1.98259681e-01 -3.35741132e-01
2.21729726e-01 3.59840810e-01 5.41496396e-01 -8.26962531e-01
-6.84983611e-01 -2.30360851e-01 2.04474986e-01 -5.62763453e-01
-6.45654857e-01 -7.56246924e-01 -1.05495560e+00 -2.43594781e-01
-1.68474242e-01 3.67005795e-01 7.09767222e-01 1.30856490e+00
1.62137181e-01 2.79493118e-03 7.47951508e-01 -3.44581962e-01
-5.44410884e-01 -1.10771847e+00 -5.35340846e-01 1.00232959e+00
-3.06398064e-01 -4.17713702e-01 -3.02830964e-01 1.61395922e-01] | [10.940764427185059, 9.78098201751709] |
194e973d-b5bf-4c8c-9298-52258ef14fbf | particle-filter-recurrent-neural-networks | 1905.12885 | null | https://arxiv.org/abs/1905.12885v2 | https://arxiv.org/pdf/1905.12885v2.pdf | Particle Filter Recurrent Neural Networks | Recurrent neural networks (RNNs) have been extraordinarily successful for prediction with sequential data. To tackle highly variable and noisy real-world data, we introduce Particle Filter Recurrent Neural Networks (PF-RNNs), a new RNN family that explicitly models uncertainty in its internal structure: while an RNN relies on a long, deterministic latent state vector, a PF-RNN maintains a latent state distribution, approximated as a set of particles. For effective learning, we provide a fully differentiable particle filter algorithm that updates the PF-RNN latent state distribution according to the Bayes rule. Experiments demonstrate that the proposed PF-RNNs outperform the corresponding standard gated RNNs on a synthetic robot localization dataset and 10 real-world sequence prediction datasets for text classification, stock price prediction, etc. | ['Wee Sun Lee', 'Xiao Ma', 'Peter Karkus', 'David Hsu'] | 2019-05-30 | null | null | null | null | ['stock-price-prediction'] | ['time-series'] | [ 1.10011384e-01 3.78433168e-02 -3.23567063e-01 -1.52049940e-02
-3.44484091e-01 -8.17299113e-02 9.15771961e-01 -7.07035810e-02
-4.95869458e-01 1.02403665e+00 3.65847021e-01 -3.48307848e-01
-1.64693266e-01 -7.51763582e-01 -9.62878883e-01 -7.50759900e-01
-1.07508220e-01 9.52260196e-01 2.00837821e-01 -4.91106361e-02
2.94832766e-01 3.78486156e-01 -1.54053187e+00 -2.68336922e-01
5.10202289e-01 8.59596133e-01 7.07169414e-01 9.16069508e-01
-9.57443863e-02 1.42594051e+00 -6.18992150e-01 2.31342122e-01
-5.97230420e-02 -2.72686183e-01 -3.39999765e-01 -3.55186760e-01
-2.79337257e-01 -1.18894078e-01 -5.23391128e-01 1.21578789e+00
2.28502035e-01 7.21497178e-01 7.54037559e-01 -9.73565757e-01
-7.89822459e-01 9.85321820e-01 1.78528711e-01 2.36481577e-01
-2.29347851e-02 -1.09150268e-01 1.11390650e+00 -7.05350637e-01
3.33001912e-01 1.53701746e+00 1.09962940e+00 4.89649296e-01
-1.30513871e+00 -4.56173986e-01 4.34906811e-01 9.50791389e-02
-9.25959766e-01 -1.14990607e-01 4.76279259e-01 -2.33459428e-01
1.20420456e+00 -8.41273069e-02 7.34670639e-01 1.74064600e+00
7.64674962e-01 1.23075700e+00 6.13688588e-01 -1.39158845e-01
5.32468736e-01 -1.95676535e-01 4.50037152e-01 5.44558167e-01
8.43320116e-02 5.07897317e-01 -5.07766008e-01 -4.92321789e-01
9.16209400e-01 6.01671815e-01 -2.73154736e-01 -3.54867309e-01
-1.32354832e+00 9.86460984e-01 1.40502647e-01 1.33923247e-01
-7.08852112e-01 6.73121512e-01 3.12790334e-01 1.34934381e-01
5.96637130e-01 1.93552285e-01 -7.29913473e-01 -4.87906069e-01
-8.35497677e-01 2.53861457e-01 1.13290250e+00 7.00492978e-01
5.39475322e-01 4.59470689e-01 -2.38675788e-01 6.60343945e-01
8.09700191e-01 8.94623101e-01 1.17740691e+00 -7.24463165e-01
-5.79807535e-02 1.26752734e-01 6.85945153e-01 -1.00303340e+00
-6.27500713e-01 -6.89673781e-01 -1.26295996e+00 -1.25212610e-01
-3.18628661e-02 -3.07195902e-01 -1.05894256e+00 1.59678102e+00
-1.01927459e-01 8.62536609e-01 5.09920597e-01 5.42826831e-01
5.11252522e-01 1.18149376e+00 -1.70588464e-01 -4.85064417e-01
8.40559602e-01 -1.10680044e+00 -8.77719283e-01 -2.98264772e-01
1.38755485e-01 -1.41364068e-01 5.59872627e-01 5.01314759e-01
-7.39173114e-01 -7.88956285e-01 -8.49188149e-01 3.26019555e-01
-3.32951486e-01 1.57063946e-01 3.77625138e-01 3.10291708e-01
-9.98686135e-01 1.17587972e+00 -1.58446550e+00 -1.66316286e-01
-1.12255067e-02 3.70772511e-01 1.52244478e-01 4.41403002e-01
-1.32476735e+00 8.49196076e-01 6.29098237e-01 6.61480904e-01
-1.23672414e+00 -5.14674306e-01 -6.39167786e-01 9.11224782e-02
1.65447161e-01 -5.08402109e-01 1.63978958e+00 -4.76539791e-01
-2.27535772e+00 -2.79187202e-01 -1.65143237e-01 -1.20055044e+00
1.60332501e-01 -6.08082891e-01 -5.00705063e-01 -2.98309863e-01
-2.50855535e-01 4.08014953e-01 1.31737936e+00 -8.72484863e-01
-7.82029808e-01 1.05161212e-01 -6.27614081e-01 1.28821135e-02
1.19709954e-01 -4.92924035e-01 1.36054873e-01 -7.09320009e-01
2.19051167e-01 -1.13703656e+00 -7.15613723e-01 -8.89273047e-01
-4.01526153e-01 -6.17191195e-01 9.56339240e-01 -2.02214360e-01
9.03661728e-01 -1.81973612e+00 3.21792871e-01 1.09191574e-01
5.98403402e-02 2.81957120e-01 -1.78812310e-01 3.98151577e-01
6.02680668e-02 -2.52349228e-01 7.61082023e-02 -7.28094041e-01
4.63942617e-01 7.55488873e-01 -1.09932101e+00 5.92015445e-01
-2.55881310e-01 9.89035428e-01 -1.12693346e+00 1.42575905e-01
2.80673355e-01 6.93909287e-01 -1.23020314e-01 1.09692931e-01
-7.20885158e-01 1.88695997e-01 -4.44007397e-01 2.03572914e-01
9.83286574e-02 -5.47124743e-01 3.04193143e-02 5.34166396e-02
-6.84035569e-02 2.35184953e-01 -1.24587989e+00 1.35523391e+00
-2.58356363e-01 6.61315799e-01 -3.78712803e-01 -9.03252244e-01
1.10989952e+00 2.69726574e-01 3.93702835e-01 -1.67562306e-01
1.78788856e-01 3.59518602e-02 -3.05320621e-01 9.39081386e-02
1.02882814e+00 -1.59624368e-01 -1.26653403e-01 5.81183195e-01
2.25949287e-01 8.65476578e-02 1.64437070e-02 -4.38619033e-02
1.16655338e+00 1.45333573e-01 2.01524287e-01 -1.57759599e-02
4.05637085e-01 -3.45370770e-01 9.18972135e-01 1.68894315e+00
-1.94299117e-01 4.34132963e-01 1.81214616e-01 -6.80937707e-01
-7.98203468e-01 -1.15665317e+00 1.71391785e-01 1.12679839e+00
-1.09808087e-01 -3.59884262e-01 -9.01489630e-02 -5.04276395e-01
2.45070159e-02 1.01710105e+00 -6.01689637e-01 -1.59477681e-01
-3.89290571e-01 -1.12178481e+00 3.14098895e-01 5.56169629e-01
2.08813593e-01 -1.53089392e+00 -6.51877820e-01 9.43014503e-01
-1.54493432e-02 -8.57853293e-01 -3.28358829e-01 6.54666603e-01
-8.64729702e-01 -6.33111119e-01 -4.53627735e-01 -5.78632712e-01
3.64548057e-01 -2.99366653e-01 1.03190410e+00 -5.11435151e-01
2.39605814e-01 5.60183465e-01 -4.10163164e-01 -6.41182721e-01
-7.87384510e-01 3.85003090e-02 5.42767882e-01 -1.61562592e-01
2.48026654e-01 -5.93784451e-01 -2.35168412e-01 1.88855112e-01
-6.08147740e-01 -1.63491637e-01 5.20271659e-01 1.34127736e+00
8.70699108e-01 4.08553690e-01 4.24964756e-01 -8.37846160e-01
9.02668774e-01 -3.16440970e-01 -1.12409532e+00 2.81804174e-01
-6.28892243e-01 3.91001940e-01 6.83240771e-01 -7.98258662e-01
-9.14146066e-01 1.95295066e-01 -1.75028130e-01 -5.22916198e-01
-2.89218817e-02 6.18884027e-01 5.13044000e-01 4.37662899e-01
4.05757248e-01 7.53247738e-01 1.82323679e-01 -3.18126023e-01
3.71469438e-01 3.42646748e-01 8.13323319e-01 -3.32436085e-01
6.20881438e-01 4.16189969e-01 -1.57063697e-02 -6.17751777e-01
-1.15548062e+00 -3.41368973e-01 -4.94376093e-01 1.06197082e-01
6.03978515e-01 -8.76505017e-01 -1.08930993e+00 5.98566830e-01
-1.17389023e+00 -6.16139412e-01 -7.75915444e-01 8.94168019e-01
-9.64233041e-01 2.68399328e-01 -9.95670915e-01 -1.29946661e+00
-6.04088426e-01 -9.10972416e-01 1.00184679e+00 2.68741459e-01
-8.90040025e-02 -1.29473424e+00 7.17689514e-01 -6.33410454e-01
4.13533211e-01 -1.92802712e-01 4.30181801e-01 -9.54703629e-01
-5.41036487e-01 -4.01911736e-01 2.42989272e-01 5.75071454e-01
1.74481362e-01 -5.58226891e-02 -5.09823024e-01 -3.69114906e-01
4.01281893e-01 -3.22105624e-02 1.05585182e+00 7.84246147e-01
6.84102356e-01 -2.83257782e-01 -5.05997062e-01 2.89222568e-01
1.21893871e+00 2.10155845e-01 3.96325529e-01 1.87059209e-01
6.04463816e-01 -1.27331465e-01 4.72948968e-01 6.17997766e-01
2.21542165e-01 1.42202582e-02 4.07994747e-01 6.18192136e-01
5.24587035e-01 -5.98227859e-01 8.06078076e-01 1.21850109e+00
1.17421530e-01 -5.48405290e-01 -7.54511058e-01 1.59826532e-01
-2.61233449e+00 -1.30028415e+00 1.98904604e-01 1.86259627e+00
4.58869934e-01 3.87286484e-01 -6.32945150e-02 -1.29676014e-01
7.23122478e-01 2.84571111e-01 -9.09638524e-01 3.66416126e-02
-1.99619219e-01 -1.53976440e-01 7.67193437e-01 5.38044274e-01
-1.17536139e+00 1.04217243e+00 7.28564310e+00 7.19477296e-01
-8.31894040e-01 6.40197992e-02 8.85325968e-02 9.67126042e-02
-5.30342981e-02 -2.50077933e-01 -1.50831282e+00 6.17408872e-01
1.57079911e+00 -6.17487077e-03 3.45280886e-01 9.75612283e-01
3.55516553e-01 4.07775529e-02 -9.62673545e-01 1.10131526e+00
-1.62211910e-01 -1.71052492e+00 4.67276648e-02 -9.47350860e-02
6.52218103e-01 8.62487972e-01 3.52701843e-01 8.15952659e-01
1.28509521e+00 -1.00515580e+00 5.55602014e-01 1.26349986e+00
-1.24392763e-01 -8.25120091e-01 9.08425152e-01 8.88030648e-01
-9.21016395e-01 -4.03433502e-01 -9.93372560e-01 -1.53509468e-01
5.27391732e-01 8.09924781e-01 -8.14907253e-01 9.16727334e-02
6.34161294e-01 1.34720623e+00 -1.08588658e-01 8.45429420e-01
-2.21841291e-01 7.60454774e-01 -5.26110053e-01 -5.43708622e-01
4.69526291e-01 -3.88379991e-01 8.36393178e-01 9.95618820e-01
3.72113615e-01 -1.37160107e-01 2.87507713e-01 7.67730534e-01
1.09584667e-01 -4.27970320e-01 -3.87734026e-01 -2.38684863e-01
3.58014047e-01 1.04882860e+00 -9.42730784e-01 -3.12531650e-01
-6.46784902e-02 9.81274605e-01 4.01258945e-01 4.69107807e-01
-8.76969695e-01 -1.17085911e-01 8.51667583e-01 -6.79089546e-01
8.22779000e-01 -4.22631502e-01 5.12839913e-01 -1.21646357e+00
-6.39843643e-01 -5.13939023e-01 1.80587441e-01 -7.59792626e-01
-1.69545531e+00 8.32817197e-01 -3.49657208e-01 -1.14030516e+00
-8.21375072e-01 -7.89500356e-01 -3.02336842e-01 5.72265744e-01
-1.44291663e+00 -6.55926406e-01 3.93673629e-01 3.91071379e-01
5.36264837e-01 -5.40188611e-01 9.19346333e-01 -4.25188631e-01
-7.77937353e-01 5.26187941e-02 8.76947224e-01 1.41457096e-01
1.08928442e-01 -1.46080756e+00 6.83973730e-01 6.19663954e-01
5.36753058e-01 7.63469517e-01 1.16763568e+00 -9.85996604e-01
-1.50093079e+00 -1.42952800e+00 4.79921997e-01 -6.58981204e-01
1.05081630e+00 -2.96762526e-01 -8.72381389e-01 1.05930638e+00
-5.53688407e-02 1.78522423e-01 2.62100875e-01 1.26618281e-01
1.56243384e-01 1.46575779e-01 -7.59447694e-01 5.24021626e-01
6.97327495e-01 -6.38626695e-01 -8.86722744e-01 4.95578349e-01
1.04163623e+00 -6.51531518e-01 -7.48396039e-01 5.04228055e-01
4.31038201e-01 -7.09261775e-01 9.96205926e-01 -4.58147436e-01
-2.73933351e-01 -3.18098813e-01 -1.32651389e-01 -1.67432249e+00
-7.12039888e-01 -9.53929245e-01 -6.47051990e-01 6.09191000e-01
2.61508584e-01 -8.59941483e-01 1.13781393e+00 1.78811222e-01
-1.40165582e-01 -6.53755724e-01 -9.11045253e-01 -8.98860574e-01
-2.64036119e-01 -7.80898392e-01 5.48610568e-01 2.07562134e-01
-2.22018167e-01 5.14769495e-01 -7.65337348e-01 5.52133441e-01
6.24618351e-01 1.87502876e-02 4.56733406e-01 -1.56041396e+00
-4.78153050e-01 -3.79840523e-01 -3.07620257e-01 -1.59058595e+00
8.37416053e-01 -4.15206671e-01 6.69589818e-01 -1.49441111e+00
-2.43472725e-01 -7.44627565e-02 -6.10033393e-01 4.81171394e-03
4.34747599e-02 -2.02705696e-01 -1.33963944e-02 3.27031970e-01
-1.13905287e+00 9.81302619e-01 6.82286978e-01 7.96721503e-03
-4.91109937e-01 6.47887170e-01 -2.73801386e-02 1.00006890e+00
5.99980831e-01 -6.31362915e-01 -5.38753808e-01 1.33355945e-01
5.22593200e-01 1.80495262e-01 1.86767504e-01 -1.11127400e+00
7.68449485e-01 5.55973966e-03 5.15193582e-01 -1.46125019e+00
4.41334784e-01 -7.66473353e-01 3.23974073e-01 7.79081166e-01
-4.59154069e-01 2.31393769e-01 2.54093353e-02 1.34153271e+00
-1.17363259e-01 -3.42016429e-01 5.07598519e-01 -1.81300089e-01
-6.66542649e-01 4.84560728e-01 -9.48722005e-01 -2.62513310e-01
4.62439954e-01 5.95788248e-02 -1.07012711e-01 -4.74289805e-01
-9.50843632e-01 2.21518517e-01 -2.19967842e-01 5.34668446e-01
7.98530996e-01 -1.22061515e+00 -4.05417919e-01 2.18940824e-01
-5.54371715e-01 6.58438504e-02 4.35665175e-02 3.79233479e-01
-1.29213035e-02 7.89256871e-01 1.38412684e-01 -7.93433130e-01
-6.29707158e-01 5.27204096e-01 4.98472124e-01 -5.65963626e-01
-9.24653888e-01 1.02407897e+00 -2.36288399e-01 -8.96048546e-01
5.40837169e-01 -9.59716916e-01 -4.91009146e-01 7.75890052e-02
5.99857330e-01 4.49643940e-01 -3.29000652e-01 -4.46094930e-01
1.10936716e-01 -2.45039016e-02 -2.27744743e-01 -1.28134698e-01
1.55411696e+00 -3.88844132e-01 -9.09997076e-02 1.22244668e+00
8.90944302e-01 -5.96368074e-01 -1.68442595e+00 -5.12071311e-01
3.30013573e-01 1.95456803e-01 1.79053754e-01 -4.02729511e-01
-5.05638301e-01 2.74436116e-01 6.41794324e-01 3.59040231e-01
4.39453274e-01 -3.00363958e-01 8.92358661e-01 9.83703971e-01
3.93669248e-01 -1.15020967e+00 9.53000337e-02 1.42457497e+00
5.69489777e-01 -1.00393796e+00 -8.10913816e-02 5.07595897e-01
-4.71277535e-01 1.18175197e+00 1.64660543e-01 -5.16204119e-01
1.26054931e+00 2.17991948e-01 -2.69813329e-01 1.56805098e-01
-1.34212184e+00 -6.09586835e-02 1.13007545e-01 5.37277400e-01
-7.72414580e-02 1.79132801e-02 4.76633847e-01 7.50102043e-01
-4.98493105e-01 1.63018376e-01 6.50227427e-01 7.86501288e-01
-7.13098347e-01 -7.59792507e-01 -3.82485867e-01 7.05590844e-01
-1.38884038e-01 -6.24670982e-02 5.70322692e-01 4.95740175e-01
-4.31292862e-01 7.39302337e-01 5.01331270e-01 -2.32751802e-01
1.18948177e-01 2.63380120e-03 1.83343157e-01 -7.19216883e-01
-3.31636459e-01 1.76782116e-01 -3.55693609e-01 -6.30934536e-01
-3.95699322e-01 -9.75127816e-01 -1.47505438e+00 -2.78024115e-02
-3.81242961e-01 6.16973042e-01 6.67263687e-01 1.16857576e+00
1.68000370e-01 6.95409715e-01 3.33767354e-01 -1.14760852e+00
-1.03732204e+00 -1.16024125e+00 -9.64823902e-01 -3.92860442e-01
8.38830829e-01 -5.94219565e-01 -6.27644002e-01 -2.41334110e-01] | [6.982832431793213, 3.4141311645507812] |
a9647eb5-cc09-44ae-896e-9d4dc0b1f393 | dectecting-invasive-ductal-carcinoma-with | 1911.06216 | null | https://arxiv.org/abs/1911.06216v2 | https://arxiv.org/pdf/1911.06216v2.pdf | Detecting Invasive Ductal Carcinoma with Semi-Supervised Conditional GANs | Invasive ductal carcinoma (IDC) comprises nearly 80% of all breast cancers. The detection of IDC is a necessary preprocessing step in determining the aggressiveness of the cancer, determining treatment protocols, and predicting patient outcomes, and is usually performed manually by an expert pathologist. Here, we describe a novel algorithm for automatically detecting IDC using semi-supervised conditional generative adversarial networks (cGANs). The framework is simple and effective at improving scores on a range of metrics over a baseline CNN. | ['Jeremiah W. Johnson'] | 2019-11-14 | null | null | null | null | ['predicting-patient-outcomes'] | ['medical'] | [ 4.63119477e-01 4.12967801e-01 -4.17797565e-01 -3.65882993e-01
-1.17507732e+00 -5.91161728e-01 5.65963507e-01 3.71468544e-01
-4.61377710e-01 4.43909645e-01 2.35540494e-01 -9.06735420e-01
3.17529857e-01 -7.10428417e-01 -5.10542095e-01 -9.79291737e-01
-5.04781418e-02 8.48462164e-01 -3.98696028e-03 9.77272093e-02
-1.51755050e-01 9.80232954e-01 -5.24612069e-01 3.74215752e-01
7.05047309e-01 9.07365024e-01 -1.63757429e-01 1.00628042e+00
-4.97295409e-02 8.81529868e-01 -3.05163860e-01 -5.32058179e-01
-2.49505788e-01 -6.41961277e-01 -8.27310383e-01 -3.02210748e-01
1.80343106e-01 -2.09626928e-01 -2.43134066e-01 1.14218748e+00
2.88223624e-01 -7.01067924e-01 1.10147500e+00 -7.71365106e-01
-3.05852294e-02 6.47652268e-01 -2.02478349e-01 4.23212312e-02
-1.67712271e-01 -4.66466919e-02 6.35171235e-01 -6.42784655e-01
6.30405903e-01 7.00179815e-01 9.36649680e-01 8.57861102e-01
-1.23168755e+00 -5.65411568e-01 -4.84229892e-01 -1.28921360e-01
-1.10298502e+00 -3.62184703e-01 5.71464300e-01 -5.05602539e-01
3.72968793e-01 2.68176317e-01 5.55646718e-01 1.13561046e+00
6.35584295e-01 6.20712340e-01 8.33049655e-01 -4.88758832e-01
4.81833309e-01 7.69397020e-02 8.60199034e-02 8.84652019e-01
2.80472547e-01 1.38612688e-01 1.85633689e-01 -2.20438108e-01
5.72137952e-01 2.49796420e-01 1.08311968e-02 -1.88929588e-01
-5.91508329e-01 8.84999931e-01 4.90293533e-01 2.59591430e-01
-7.58865327e-02 2.75479406e-01 4.46766198e-01 -1.11012749e-01
2.57756233e-01 2.83663332e-01 9.75050852e-02 1.40665427e-01
-7.12468326e-01 -2.56816328e-01 6.84377849e-01 5.25239766e-01
1.65424973e-01 -3.60625744e-01 -5.10764048e-02 6.28202260e-01
1.55628234e-01 6.64275408e-01 7.02380896e-01 -7.32938886e-01
-1.80825979e-01 9.81639326e-01 -2.01430947e-01 -7.63204455e-01
-6.56085432e-01 -4.24523205e-01 -1.24553287e+00 2.41920710e-01
3.28948617e-01 -2.22374909e-02 -1.13001204e+00 1.34680653e+00
5.78621738e-02 -2.85278022e-01 5.64294457e-02 5.04872859e-01
8.06140363e-01 1.95813119e-01 6.14348352e-01 1.73709154e-01
1.26183522e+00 -6.06594503e-01 -5.61414182e-01 -4.10927922e-01
9.32761908e-01 -4.29036528e-01 3.36978942e-01 -1.03551798e-01
-7.45331109e-01 6.84897155e-02 -1.07856083e+00 -1.87890768e-01
-4.44353908e-01 3.43072236e-01 8.72768462e-01 7.85451412e-01
-8.64820600e-01 3.32819700e-01 -1.45155692e+00 -3.46106887e-01
8.71835530e-01 3.12085122e-01 -7.33653665e-01 -3.52490395e-01
-7.21827388e-01 7.55335271e-01 1.91844165e-01 -1.64799929e-01
-1.06198561e+00 -5.83966553e-01 -8.43246818e-01 -9.07437578e-02
2.26763152e-02 -4.38618481e-01 1.30284607e+00 -1.01989007e+00
-1.06700563e+00 1.21788764e+00 -1.61643088e-01 -6.17776453e-01
4.64523584e-01 1.11731313e-01 -3.75895947e-01 2.55311906e-01
-6.13922812e-02 4.41063493e-01 6.63000405e-01 -8.80033255e-01
-7.12827086e-01 -5.80342948e-01 -3.46243769e-01 -1.85867369e-01
3.10293175e-02 -1.90506577e-01 -5.76566577e-01 -7.04635739e-01
1.40400916e-01 -1.08679819e+00 -5.96849561e-01 4.01669770e-01
-3.81963998e-01 6.52663456e-03 8.42727542e-01 -7.66621709e-01
7.36433923e-01 -2.38799286e+00 -9.68327820e-02 2.57510871e-01
3.55271786e-01 4.46340144e-01 8.90009254e-02 -5.29711209e-02
-5.90005368e-02 5.18035173e-01 -3.34974647e-01 -1.95013151e-01
-2.39017889e-01 2.05675960e-01 2.41621152e-01 6.13990366e-01
4.90332514e-01 1.28990340e+00 -9.10908520e-01 -6.99867785e-01
-2.03750865e-03 5.12817621e-01 -3.71113986e-01 1.13806523e-01
-5.47616556e-02 3.65819365e-01 -3.39272738e-01 1.00004804e+00
2.82606363e-01 -4.42380846e-01 4.26932812e-01 7.06321225e-02
5.09256840e-01 -3.14434990e-02 -4.40754831e-01 1.13226926e+00
-2.06860602e-01 8.18453014e-01 1.35016009e-01 -9.17758167e-01
5.79039693e-01 1.34054542e-01 2.60879725e-01 -3.36279869e-01
2.72646278e-01 4.11974937e-01 9.09967348e-02 -1.68978572e-01
-2.24462599e-01 -1.62715197e-01 -1.99443430e-01 2.17083901e-01
4.96751592e-02 9.60650016e-03 4.13579307e-02 1.83201909e-01
1.71677172e+00 -5.82694173e-01 7.65672624e-01 -1.96150362e-01
4.77563828e-01 2.26056218e-01 8.37297738e-01 6.72228694e-01
-4.50418115e-01 5.83122075e-01 8.15228760e-01 -5.85779011e-01
-6.47757828e-01 -9.59654212e-01 -3.08660418e-01 4.24338222e-01
-1.66337132e-01 1.07035019e-01 -4.11086529e-01 -9.68514621e-01
2.69321412e-01 3.25807959e-01 -1.19185448e+00 -3.16302776e-01
-4.64468092e-01 -6.57604158e-01 7.62994409e-01 9.19824719e-01
3.73912603e-01 -7.39662707e-01 -1.12712935e-01 2.71421999e-01
-2.72005284e-03 -1.04836059e+00 -3.22295278e-01 6.71141624e-01
-8.91710877e-01 -1.65265036e+00 -7.81092525e-01 -9.91639674e-01
1.24747860e+00 -2.16482252e-01 1.02473915e+00 1.34629533e-01
-9.99384046e-01 -1.36717707e-01 -1.94310397e-01 -6.61827326e-01
-1.22971475e+00 5.64899817e-02 -4.15232092e-01 -1.62337720e-01
5.41028976e-01 2.61335110e-04 -6.49668157e-01 9.96368080e-02
-7.09918499e-01 4.69864495e-02 1.05615997e+00 7.26576149e-01
9.32824731e-01 2.31427431e-01 1.00708008e-01 -1.47939801e+00
1.85508281e-01 -3.31857860e-01 -3.61741960e-01 -5.84119596e-02
-3.64844978e-01 -1.16856344e-01 7.85713911e-01 -2.37683460e-01
-8.63472819e-01 5.24753273e-01 -4.11060959e-01 5.54152168e-02
-4.73411918e-01 4.15640593e-01 -1.09232940e-01 -3.06177318e-01
5.93748033e-01 -5.25403544e-02 1.89211398e-01 -1.15284763e-01
-3.96094918e-01 5.01819372e-01 8.24728966e-01 2.33976766e-01
9.03067112e-01 7.26424515e-01 3.80823374e-01 -5.15063882e-01
-8.90290320e-01 -5.86854577e-01 -4.71965462e-01 -2.33854931e-02
8.33127975e-01 -7.65127659e-01 -3.46542865e-01 6.75389111e-01
-7.80431867e-01 -5.56855738e-01 2.30974592e-02 3.14739496e-01
-6.44842535e-02 -7.08032027e-02 -8.30012202e-01 -2.11021423e-01
-5.79486072e-01 -9.46031153e-01 1.11699474e+00 3.96360189e-01
-2.60918677e-01 -1.28479791e+00 1.03392333e-01 1.61561280e-01
6.32726431e-01 6.60078168e-01 1.30756354e+00 -8.63322437e-01
-9.15371999e-02 -1.11161864e+00 -1.49666056e-01 2.79861391e-01
2.51523256e-01 2.81020224e-01 -7.79731989e-01 -2.00580969e-01
-4.26417023e-01 -1.65159911e-01 9.59205389e-01 4.55755621e-01
1.22763753e+00 -1.58507556e-01 -1.09980357e+00 8.88724625e-01
1.59591174e+00 4.34501052e-01 5.84523559e-01 1.24888524e-01
2.94578999e-01 1.04223743e-01 1.38690263e-01 1.34674739e-02
-1.19972127e-02 7.73474667e-03 5.16283035e-01 -5.46047032e-01
-2.21804380e-01 -2.94670761e-01 -1.67479277e-01 5.10956488e-05
4.60075773e-03 -2.94232965e-01 -1.30709124e+00 5.21265924e-01
-1.18145680e+00 -6.32531345e-01 6.90446794e-02 1.60970700e+00
8.04769695e-01 2.67083228e-01 -3.78395885e-01 3.27746928e-01
6.63329124e-01 -2.35616043e-01 -6.36203587e-01 -3.49055022e-01
7.42385313e-02 2.45065704e-01 8.77246439e-01 2.04779416e-01
-1.28886127e+00 4.83365595e-01 7.66563463e+00 3.25429231e-01
-1.37014413e+00 -1.80156395e-01 1.13717997e+00 3.88854921e-01
1.56026125e-01 -2.28551030e-01 -8.45066428e-01 3.14389706e-01
7.10008800e-01 -3.59999426e-02 -2.27686390e-01 1.04262936e+00
-2.28084475e-02 -1.87685028e-01 -1.32315123e+00 5.26160896e-01
1.75229669e-01 -1.36761093e+00 -1.87262490e-01 1.80517033e-01
6.42801404e-01 -6.10492751e-02 -1.00033559e-01 3.31185788e-01
6.29880369e-01 -1.18141055e+00 -8.32678974e-02 5.33770680e-01
1.22202563e+00 -7.65455663e-01 1.46108258e+00 2.88683087e-01
-6.86304927e-01 -1.12916697e-02 1.10215232e-01 6.01479650e-01
-2.79015452e-01 6.92987621e-01 -1.11974239e+00 -1.28618181e-01
5.04874289e-01 3.37439895e-01 -9.36082423e-01 8.69548261e-01
-2.22341523e-01 9.85162675e-01 -2.04956427e-01 -7.08305165e-02
3.30392607e-02 6.06383145e-01 2.28579178e-01 1.20468569e+00
1.29236728e-01 1.61886290e-01 -6.61192164e-02 4.37788129e-01
-2.52864510e-01 -2.86765397e-02 -2.54058093e-01 -4.72992837e-01
3.29448342e-01 1.42298269e+00 -8.43584955e-01 -4.03202623e-02
-2.03327209e-01 7.93156505e-01 2.08138376e-01 1.01097837e-01
-6.33271098e-01 -4.66905534e-01 2.06407711e-01 3.17184329e-01
1.60405815e-01 3.93011779e-01 -3.80462319e-01 -5.69030523e-01
-3.01001847e-01 -6.94979489e-01 4.40014005e-01 -3.06221336e-01
-1.03900409e+00 3.43926489e-01 -7.12994158e-01 -1.06894028e+00
-4.06698644e-01 -9.30750668e-01 -1.04324281e+00 5.39851010e-01
-1.55170715e+00 -1.04936242e+00 -7.95646906e-01 2.37435982e-01
2.10776612e-01 -2.14847058e-01 1.46761405e+00 -1.85053155e-01
-7.80086935e-01 7.79611230e-01 1.64583310e-01 6.25604451e-01
6.74543798e-01 -1.60920978e+00 6.37347326e-02 6.74774885e-01
-7.62143850e-01 2.26747155e-01 4.78775769e-01 -4.18130696e-01
-1.36993349e+00 -1.62160337e+00 8.06188405e-01 1.33183738e-03
5.32811046e-01 -1.81798071e-01 -5.87575376e-01 7.08749354e-01
-2.92569369e-01 4.99249220e-01 1.26452017e+00 -2.27015048e-01
-1.69874087e-01 -2.25965351e-01 -1.39800763e+00 4.53643858e-01
3.83792996e-01 -3.48227352e-01 2.37656534e-02 4.36302125e-01
1.45118341e-01 -4.65222687e-01 -1.02962768e+00 7.52990723e-01
5.84267318e-01 -5.69722712e-01 7.09115326e-01 -2.70229191e-01
8.03159297e-01 9.85069424e-02 1.77648380e-01 -1.06717539e+00
-5.70993781e-01 -3.50129217e-01 6.41866624e-02 8.32431257e-01
4.59479332e-01 -5.64972341e-01 1.20414591e+00 6.13085389e-01
6.42105564e-03 -6.77931249e-01 -6.67013347e-01 -3.73750597e-01
2.34623209e-01 -7.76175782e-02 3.55375648e-01 6.09549761e-01
-2.32503153e-02 -1.86811015e-01 5.38413584e-01 2.23642066e-01
7.33421266e-01 -3.06010246e-01 5.12680769e-01 -1.21618819e+00
-1.52731553e-01 -7.46587217e-01 -8.15249026e-01 -2.48685196e-01
-3.55548412e-02 -1.00466835e+00 2.57145036e-02 -1.43611491e+00
3.54307055e-01 -3.80039990e-01 -2.98788607e-01 7.73364782e-01
-2.43476048e-01 5.56976914e-01 -4.99096036e-01 1.77975699e-01
-3.36290747e-01 -9.72973555e-02 1.08958364e+00 -4.80368674e-01
1.46358773e-01 2.80832112e-01 -8.23059201e-01 1.08410394e+00
8.83948028e-01 -5.23534179e-01 1.74140707e-01 3.61015717e-03
-9.10417065e-02 2.90459275e-01 5.62079966e-01 -9.69405770e-01
1.75060019e-01 -2.06942886e-01 8.03518414e-01 -6.88145459e-01
-1.61999375e-01 -7.83391297e-01 1.73630312e-01 1.02455032e+00
-4.75501716e-01 -5.29435813e-01 3.06113601e-01 6.28618240e-01
-2.39291444e-01 -3.31393093e-01 1.13248062e+00 -2.95287687e-02
-5.16129196e-01 1.80395111e-01 -7.24467576e-01 -2.08538964e-01
1.27106011e+00 1.08016156e-01 -4.03624415e-01 -1.72314331e-01
-6.04617536e-01 1.44409865e-01 5.40855646e-01 6.14636093e-02
5.18217623e-01 -1.18542945e+00 -8.14704239e-01 2.87063479e-01
3.78707260e-01 2.54814893e-01 -1.84478909e-02 7.20786750e-01
-1.06017864e+00 4.64226991e-01 8.80213901e-02 -3.88220727e-01
-1.47160101e+00 1.46630600e-01 7.47330666e-01 -7.89885640e-01
-5.40734887e-01 9.55508530e-01 -5.02817146e-03 -1.25981644e-01
4.67543602e-01 -2.37510782e-02 -2.42235795e-01 -4.57973808e-01
6.05208576e-01 -1.15940943e-02 2.00423449e-01 -3.45162511e-01
-3.48244458e-01 1.03455953e-01 -5.49347997e-01 4.33098584e-01
1.12989795e+00 5.51840842e-01 -9.33751613e-02 8.69115740e-02
1.45770264e+00 -2.94507593e-01 -7.92449951e-01 -2.04203315e-02
-1.86732993e-01 1.73302516e-01 3.30058545e-01 -9.87116516e-01
-1.29993510e+00 4.65635121e-01 7.99402773e-01 -1.47948623e-01
1.16912222e+00 1.98257342e-01 6.21965706e-01 3.09523523e-01
1.81527540e-01 -6.63339436e-01 -2.10072577e-01 1.73426613e-01
6.31291151e-01 -1.58905506e+00 -3.72383446e-02 -4.62853074e-01
-2.75220275e-01 1.15039337e+00 3.75759006e-01 -3.27470273e-01
9.11989093e-01 6.91901028e-01 3.58690143e-01 -1.03628039e-01
-7.15190113e-01 -1.67379547e-02 1.11708045e-01 6.12180769e-01
5.03270030e-01 3.60878348e-01 -2.44734049e-01 7.03215361e-01
3.94611694e-02 6.63646311e-03 2.71438926e-01 1.11769640e+00
-3.44088405e-01 -8.74456465e-01 -7.98859298e-02 7.96509206e-01
-9.52148318e-01 1.47265941e-01 -7.88257420e-01 9.63829160e-01
-1.05989993e-01 4.84925687e-01 1.30618840e-01 -1.32384852e-01
-8.34668695e-04 3.67489308e-02 -5.42823449e-02 -4.58441794e-01
-3.30751806e-01 -8.08471739e-02 -5.72042912e-02 -4.50304389e-01
-1.83163464e-01 -6.03087008e-01 -1.31647956e+00 1.37212843e-01
-2.22253114e-01 -5.71819954e-02 9.07671273e-01 7.96990275e-01
1.40817657e-01 6.40276611e-01 7.09471107e-01 -2.92887926e-01
-3.23617399e-01 -1.01854599e+00 -5.73498785e-01 4.64013934e-01
2.56713510e-01 -2.12253645e-01 -7.83807933e-01 3.12334538e-01] | [15.160795211791992, -2.9843456745147705] |
fe0468be-7e40-4faa-9ef3-f4cc5e145d5b | the-emergence-of-compositional-languages-for | 1910.05291 | null | https://arxiv.org/abs/1910.05291v1 | https://arxiv.org/pdf/1910.05291v1.pdf | The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents | Since first introduced, computer simulation has been an increasingly important tool in evolutionary linguistics. Recently, with the development of deep learning techniques, research in grounded language learning has also started to focus on facilitating the emergence of compositional languages without pre-defined elementary linguistic knowledge. In this work, we explore the emergence of compositional languages for numeric concepts in multi-agent communication systems. We demonstrate that compositional language for encoding numeric concepts can emerge through iterated learning in populations of deep neural network agents. However, language properties greatly depend on the input representations given to agents. We found that compositional languages only emerge if they require less iterations to be fully learnt than other non-degenerate languages for agents on a given input representation. | ['Serhii Havrylov', 'Yi Ren', 'Ivan Titov', 'Stella Frank', 'Shangmin Guo', 'Kenny Smith'] | 2019-10-11 | null | null | null | null | ['grounded-language-learning'] | ['natural-language-processing'] | [-1.58878081e-02 9.02496576e-02 2.69055218e-01 -1.35484844e-01
-1.05764873e-01 -6.54236138e-01 7.99467027e-01 3.50391537e-01
-6.79769158e-01 8.62958670e-01 5.16627841e-02 -3.44809920e-01
-9.18816924e-02 -1.00639641e+00 -5.67887604e-01 -7.30403602e-01
-5.04713118e-01 8.52753222e-01 -2.03933567e-01 -7.48745918e-01
-3.43149006e-02 2.44535998e-01 -1.75456059e+00 2.18015686e-01
9.91841197e-01 2.07018673e-01 3.03578734e-01 7.81174719e-01
-4.23138618e-01 7.76930571e-01 -7.17421949e-01 -9.57842991e-02
2.53354847e-01 -1.08809042e+00 -5.96895754e-01 6.57520667e-02
-9.09572095e-02 9.73786190e-02 -7.89882615e-02 1.06741035e+00
2.84389526e-01 1.48985595e-01 7.29655266e-01 -1.26009953e+00
-9.88378882e-01 1.33439863e+00 -2.07761809e-01 -5.92320487e-02
1.46241322e-01 3.06542188e-01 1.14789402e+00 -6.36827588e-01
5.33222258e-01 1.41593087e+00 5.45716643e-01 8.42933953e-01
-1.33390057e+00 -7.06333935e-01 7.08366707e-02 -1.98890865e-01
-1.28246379e+00 -4.47263569e-02 5.91212213e-01 -2.85867453e-01
1.20758379e+00 -2.47330964e-01 1.32621658e+00 9.02984619e-01
1.97245896e-01 6.50306523e-01 1.13174331e+00 -8.48473787e-01
5.11060774e-01 1.88953549e-01 -1.22068420e-01 1.03110719e+00
3.80629957e-01 5.35577893e-01 -5.58553517e-01 -2.58664191e-01
8.07542086e-01 -5.42499125e-01 2.52834469e-01 -1.81692213e-01
-9.26790714e-01 1.25186884e+00 2.47254223e-01 6.90207422e-01
-2.96606362e-01 4.61293101e-01 3.47018361e-01 8.08980942e-01
1.18355341e-01 9.76913571e-01 -2.71632463e-01 -1.48860469e-01
-3.96825761e-01 1.54513597e-01 9.02730644e-01 6.01474524e-01
6.71989262e-01 3.22707862e-01 5.96217573e-01 6.45870447e-01
2.04638198e-01 4.35913295e-01 6.78241789e-01 -8.77870917e-01
-6.94251284e-02 1.01125574e+00 -3.01045448e-01 -5.15977204e-01
-4.42564905e-01 -3.05324823e-01 -9.29602444e-01 2.09241062e-01
3.48931700e-01 -6.17779374e-01 -5.57890534e-01 2.07299733e+00
8.95909779e-03 -7.71251321e-02 6.98158145e-01 5.85411549e-01
3.04794699e-01 8.70359898e-01 -4.54126894e-02 -3.73469800e-01
9.11551416e-01 -5.90498030e-01 -3.45103323e-01 -2.43256316e-01
6.77797973e-01 -2.96899199e-01 1.15653229e+00 2.82435983e-01
-1.09710824e+00 -3.28188390e-01 -1.02860546e+00 3.24253976e-01
-4.50148791e-01 -4.62867081e-01 1.04419589e+00 8.43493223e-01
-1.34987557e+00 1.96501538e-01 -8.17270160e-01 -5.19117057e-01
2.15408891e-01 7.66440868e-01 -3.43266875e-02 5.67448258e-01
-1.28588164e+00 9.03646052e-01 5.59467494e-01 -7.12219179e-02
-1.04329181e+00 -3.48559320e-01 -5.92874646e-01 -8.99756551e-02
2.20964655e-01 -8.58969629e-01 1.22676241e+00 -1.86964750e+00
-1.95754552e+00 7.80177712e-01 1.66795015e-01 -6.37522995e-01
-1.25288917e-02 2.70590127e-01 -2.64323562e-01 1.23144761e-01
-2.66242981e-01 8.43287110e-01 6.32356942e-01 -1.37251353e+00
-8.03449392e-01 -2.39637997e-02 3.38671982e-01 4.54895288e-01
-4.60390687e-01 1.49364874e-01 3.90216857e-01 -3.91895890e-01
-3.75462264e-01 -1.04937398e+00 -4.46098208e-01 -1.21363468e-01
2.22936735e-01 -5.82156539e-01 3.11050951e-01 7.55584240e-02
6.85361207e-01 -1.97817457e+00 6.45154893e-01 3.66044134e-01
2.86914170e-01 1.55799627e-01 -3.40387166e-01 6.94802999e-01
2.70546198e-01 2.13716149e-01 -5.40485859e-01 -3.76442298e-02
4.66311090e-02 4.35577452e-01 -3.83294553e-01 3.01876277e-01
2.52627909e-01 9.64556098e-01 -1.12587094e+00 -3.85834664e-01
-5.95489666e-02 3.86307716e-01 -8.28518212e-01 1.32233769e-01
-6.00587130e-01 2.04783261e-01 -2.22497299e-01 1.06085919e-01
-6.55795261e-02 -3.18017185e-01 5.47240317e-01 7.23531008e-01
-2.14398175e-01 4.54638004e-02 -8.82724643e-01 1.45716560e+00
-8.13342214e-01 7.71331847e-01 4.80066575e-02 -1.06507838e+00
7.77562380e-01 3.39977354e-01 2.90937334e-01 -6.40943587e-01
4.84850526e-01 5.25915921e-01 1.01534092e+00 -2.55700171e-01
3.90219957e-01 -5.40012300e-01 -2.68156409e-01 1.05503118e+00
2.30683237e-01 -4.91937518e-01 4.52148199e-01 9.28445607e-02
6.91190422e-01 -2.72047967e-01 4.06589806e-01 -5.42815149e-01
5.14284730e-01 1.56059042e-01 2.05247939e-01 7.84766436e-01
1.09391518e-01 -7.36524761e-02 2.47905806e-01 -5.76183677e-01
-1.15586424e+00 -1.06019664e+00 1.74804613e-01 1.41711509e+00
2.16874048e-01 -2.36822352e-01 -8.77016723e-01 -9.34148300e-03
-2.63875306e-01 7.68846095e-01 -5.15691459e-01 -4.87897605e-01
-9.10461962e-01 -9.46200967e-01 9.60866392e-01 2.13531226e-01
3.22341889e-01 -1.62366390e+00 -1.13952911e+00 3.68676215e-01
3.36927742e-01 -5.21753311e-01 -2.66372025e-01 4.95157540e-01
-8.06050181e-01 -6.02491796e-01 -4.96244669e-01 -1.33509779e+00
9.75122035e-01 -2.79892087e-01 1.05379367e+00 5.91300547e-01
-3.39920312e-01 5.80341339e-01 -1.05701491e-01 -2.88233161e-01
-1.03567290e+00 2.55477011e-01 3.76968712e-01 -2.80604988e-01
2.71445513e-01 -7.38011003e-01 -4.22732532e-02 -1.38923883e-01
-9.93295312e-01 2.32220426e-01 4.89345521e-01 1.07885635e+00
2.13854220e-02 1.88486516e-01 7.13859677e-01 -3.09855700e-01
1.39782321e+00 -3.20960402e-01 -7.32561469e-01 4.27199721e-01
-3.11793923e-01 6.73022211e-01 9.76706445e-01 -8.32667589e-01
-9.33716118e-01 -9.08460245e-02 5.39681017e-02 3.62920761e-01
-1.63083166e-01 7.62862325e-01 2.91550398e-01 6.51615635e-02
7.85021722e-01 5.64183652e-01 2.21504137e-01 1.89331353e-01
5.60943067e-01 6.45512342e-01 1.41464904e-01 -1.14646459e+00
6.17788434e-01 2.06260577e-01 -1.30373508e-01 -1.25357044e+00
-1.30320758e-01 2.85589248e-01 -5.86867392e-01 -9.20572355e-02
7.46230245e-01 -7.93853939e-01 -8.20099115e-01 5.89549482e-01
-1.07035589e+00 -7.01139212e-01 -4.80707914e-01 3.01362246e-01
-5.85630298e-01 1.06323482e-02 -5.02615690e-01 -9.92324173e-01
-2.40633816e-01 -1.16334414e+00 5.54536104e-01 3.10197055e-01
-3.91567737e-01 -1.28099132e+00 4.38524783e-01 -4.83566999e-01
4.08827722e-01 -3.02353024e-01 1.40229547e+00 -5.43709934e-01
-3.96878034e-01 3.62584800e-01 3.48513544e-01 -7.05100819e-02
2.89308339e-01 1.34233758e-01 -3.80005479e-01 -4.01828259e-01
-1.51086956e-01 -6.54932559e-01 4.94610190e-01 1.81532249e-01
4.41306412e-01 -3.16904068e-01 -1.32400706e-01 4.20248330e-01
1.28790712e+00 6.73626840e-01 1.28800736e-03 3.55567694e-01
1.74270213e-01 7.39396751e-01 -2.81407148e-01 1.54253289e-01
5.12462318e-01 8.53507370e-02 5.51285455e-03 1.56457439e-01
1.04115233e-01 -1.85790628e-01 6.32903159e-01 1.17057312e+00
-1.79592073e-01 -4.39012349e-01 -1.23674679e+00 6.23620272e-01
-1.65783048e+00 -9.72133577e-01 5.20317316e-01 1.72776389e+00
1.25388157e+00 -2.59470213e-02 2.87930429e-01 -2.76273638e-01
7.50047266e-01 -4.06719476e-01 -6.27407789e-01 -6.55165613e-01
-5.95964372e-01 6.04189694e-01 -9.73713174e-02 8.79153132e-01
-5.51457644e-01 1.30775499e+00 6.77881193e+00 2.53874391e-01
-1.22084093e+00 -1.46012753e-01 4.38023031e-01 -2.85167154e-02
-5.82898319e-01 -6.51155040e-02 -5.66437542e-01 2.14998797e-01
1.00228941e+00 -7.33928502e-01 9.11779284e-01 3.54120135e-01
-1.09793849e-01 -7.21450299e-02 -1.14676166e+00 8.44571292e-01
-2.72049289e-02 -1.33862829e+00 4.04155374e-01 1.25124738e-01
9.82762098e-01 3.32426429e-02 1.98384449e-01 3.43383253e-01
1.07824183e+00 -1.35193884e+00 7.42528260e-01 1.07719921e-01
3.23730588e-01 -1.00925231e+00 3.58153999e-01 6.28226101e-01
-1.07774913e+00 -4.30600286e-01 -4.38141733e-01 -5.64111710e-01
1.50130332e-01 -6.85451180e-02 -7.60127187e-01 -2.68344563e-02
3.50433558e-01 2.90735066e-01 -4.22262400e-01 6.21725261e-01
-1.29179418e-01 4.78022158e-01 -6.38908505e-01 -7.56693602e-01
6.29480660e-01 -4.24925953e-01 3.29523772e-01 9.18597281e-01
3.93629670e-01 3.20537299e-01 3.03320587e-01 9.78868544e-01
-6.17745444e-02 8.26942399e-02 -7.54618406e-01 -5.21561742e-01
3.60599667e-01 8.23777795e-01 -1.01919580e+00 -2.82487690e-01
-2.36526161e-01 6.83018923e-01 5.01153529e-01 1.38926908e-01
-6.30168676e-01 -2.33654752e-01 6.86898708e-01 -2.49164715e-01
1.62469640e-01 -6.07128263e-01 2.44150646e-02 -9.95644212e-01
-5.80043912e-01 -1.28775585e+00 1.01593763e-01 -3.04368049e-01
-1.33134520e+00 9.53591406e-01 3.87495533e-02 -6.29469872e-01
-8.14419031e-01 -5.53716898e-01 -5.59904695e-01 4.71899331e-01
-7.62404978e-01 -9.29500163e-01 1.72455505e-01 5.96510768e-01
3.65679711e-01 -9.82090056e-01 1.12850022e+00 -1.40815318e-01
-2.93652207e-01 4.43956733e-01 1.05652250e-01 1.69130087e-01
-9.05707553e-02 -1.14783406e+00 3.68963480e-01 6.26221418e-01
6.64984405e-01 1.00048673e+00 6.69577062e-01 -4.29201066e-01
-1.36555779e+00 -5.48983693e-01 6.39406323e-01 8.01993255e-03
8.64369988e-01 -6.78671956e-01 -6.39373124e-01 6.23117685e-01
9.34347808e-01 -5.08198977e-01 7.04877973e-01 -3.64761911e-02
-1.95635170e-01 1.57385051e-01 -6.70562327e-01 1.18166506e+00
1.20660484e+00 -7.51636028e-01 -8.93114567e-01 1.14254944e-01
8.76755714e-01 6.44742697e-02 -3.11460018e-01 3.03224027e-02
4.17234063e-01 -6.55190766e-01 6.98582530e-01 -7.42770612e-01
2.37717375e-01 -3.73263299e-01 -8.68539885e-02 -1.61243069e+00
-1.07606634e-01 -8.87209833e-01 2.29555503e-01 7.40951955e-01
7.71618724e-01 -8.12443614e-01 6.41492248e-01 1.32176593e-01
7.82825798e-02 -3.16450596e-01 -8.46417069e-01 -7.35468924e-01
7.62877107e-01 -1.34951293e-01 5.90454578e-01 8.28418493e-01
4.10639703e-01 7.28432715e-01 3.41679173e-04 -6.81413859e-02
4.08435583e-01 4.13644582e-01 3.62786382e-01 -1.18853092e+00
-5.43294549e-01 -9.58241761e-01 -1.22119442e-01 -9.39767599e-01
6.60130143e-01 -1.25356543e+00 2.47823536e-01 -1.10246229e+00
1.17865972e-01 -4.88645285e-01 -1.25374636e-02 3.32385242e-01
1.21715896e-01 -1.38525004e-02 2.24358693e-01 -1.09034002e-01
-3.62649202e-01 7.70903587e-01 1.03208649e+00 -1.99010357e-01
-4.77093965e-01 -3.09959143e-01 -8.39633048e-01 7.62529314e-01
1.18050778e+00 -5.06788194e-01 -7.89349079e-01 -7.15741873e-01
9.43928182e-01 -2.03441992e-01 6.01373762e-02 -9.51304317e-01
4.22641307e-01 -2.90299326e-01 -1.14702955e-01 -6.52555898e-02
1.79605961e-01 -6.49716735e-01 2.04349518e-01 1.00690234e+00
-7.04150558e-01 5.33934057e-01 2.72521168e-01 1.50987983e-01
-1.12054706e-01 -4.94245917e-01 5.79955816e-01 -5.46493709e-01
-6.27651870e-01 -7.44168237e-02 -1.30208051e+00 2.60266185e-01
1.15684569e+00 -7.05344677e-02 -5.18482104e-02 -3.53774875e-01
-6.68444693e-01 2.52560019e-01 5.25483370e-01 4.33675766e-01
7.97265112e-01 -9.18540359e-01 -8.42961729e-01 1.27281785e-01
-1.56876639e-01 -1.52874753e-01 -4.51242447e-01 1.54331222e-01
-7.44784057e-01 1.85324714e-01 -5.11154950e-01 -5.17654955e-01
-9.46947038e-01 3.57678413e-01 7.17255712e-01 -1.84641387e-02
-5.05013108e-01 9.76022840e-01 3.17005783e-01 -8.48457873e-01
1.49816453e-01 -4.17094618e-01 -6.53923750e-02 4.48072441e-02
2.63048202e-01 -1.44232199e-01 -5.75657189e-01 -5.12877643e-01
-2.26973355e-01 5.80052674e-01 6.64680526e-02 -6.63113296e-01
1.56106579e+00 1.82719916e-01 -4.80436772e-01 6.98228598e-01
8.14172924e-01 -6.64115995e-02 -8.36514711e-01 -9.44525469e-03
3.25289845e-01 3.82184386e-01 -3.59953701e-01 -5.07929087e-01
-8.30162227e-01 7.61028528e-01 3.56564999e-01 3.25284600e-01
9.20350194e-01 1.30194589e-01 3.56763154e-01 9.95685101e-01
7.16977954e-01 -1.05088770e+00 5.64906538e-01 9.33471441e-01
7.54913092e-01 -1.01525116e+00 -2.64167666e-01 1.02802694e-01
-6.58684075e-01 1.30529559e+00 6.06543124e-01 -3.64196926e-01
6.99825943e-01 6.42606676e-01 1.45364385e-02 -1.29599586e-01
-1.10384119e+00 -3.30459505e-01 -1.44606397e-01 9.04962659e-01
4.97996002e-01 2.28127297e-02 -8.90760198e-02 2.56884575e-01
-7.67921925e-01 -3.40204328e-01 7.44347990e-01 7.94848800e-01
-6.08060122e-01 -1.27254057e+00 4.13782633e-04 1.36288121e-01
-1.90578196e-02 -3.47260505e-01 -7.49284267e-01 8.77628505e-01
4.04553205e-01 7.26989985e-01 4.24002588e-01 -9.65133384e-02
-1.49719000e-01 6.12225719e-02 9.86912310e-01 -8.59661937e-01
-1.02843618e+00 -3.90460253e-01 -5.20117879e-02 1.77200973e-01
-6.82240605e-01 -8.56744945e-01 -1.86326778e+00 -3.26411515e-01
-2.73403466e-01 4.88612711e-01 1.72738940e-01 8.60159695e-01
-2.88807321e-03 3.85099143e-01 2.35392034e-01 -5.57296634e-01
-2.85242379e-01 -5.18599987e-01 -2.83238202e-01 -2.73351539e-02
3.44388515e-01 -3.90897125e-01 -4.03101981e-01 1.17054515e-01] | [4.413423538208008, 1.6376776695251465] |
ddfe97f2-82e9-420f-828c-c841b98b7c1e | semantic-segmentation-on-vspw-dataset-through-1 | 2306.03508 | null | https://arxiv.org/abs/2306.03508v1 | https://arxiv.org/pdf/2306.03508v1.pdf | Semantic Segmentation on VSPW Dataset through Contrastive Loss and Multi-dataset Training Approach | Video scene parsing incorporates temporal information, which can enhance the consistency and accuracy of predictions compared to image scene parsing. The added temporal dimension enables a more comprehensive understanding of the scene, leading to more reliable results. This paper presents the winning solution of the CVPR2023 workshop for video semantic segmentation, focusing on enhancing Spatial-Temporal correlations with contrastive loss. We also explore the influence of multi-dataset training by utilizing a label-mapping technique. And the final result is aggregating the output of the above two models. Our approach achieves 65.95% mIoU performance on the VSPW dataset, ranked 1st place on the VSPW challenge at CVPR 2023. | ['Qian Wang', 'Qianxiong Ning', 'Min Yan'] | 2023-06-06 | null | null | null | null | ['scene-parsing', 'video-semantic-segmentation'] | ['computer-vision', 'computer-vision'] | [ 3.29963177e-01 1.76070005e-01 -5.09798050e-01 -6.37661994e-01
-8.47360849e-01 -4.38130945e-01 5.35193622e-01 -1.28992677e-01
-5.81458092e-01 3.91417682e-01 2.18031645e-01 -1.08166032e-01
8.54222402e-02 -5.00279307e-01 -8.81020665e-01 -3.08574200e-01
4.80111167e-02 2.36274332e-01 9.48660433e-01 1.31547228e-01
1.87719733e-01 4.77262847e-02 -1.49777818e+00 9.04790282e-01
5.31442106e-01 1.29148853e+00 4.96209204e-01 6.99330032e-01
-2.50070542e-01 1.01993906e+00 -2.33457550e-01 -3.82561654e-01
2.03570738e-01 -3.79747689e-01 -1.31222618e+00 3.12546715e-02
8.39832723e-01 -2.78319921e-02 -1.66810557e-01 8.40807080e-01
7.97765478e-02 2.36000925e-01 2.42745444e-01 -1.16923130e+00
-1.31524056e-01 8.04138064e-01 -6.54855371e-01 4.92664427e-01
3.12039495e-01 -9.82093439e-02 1.23924708e+00 -5.20880759e-01
1.01201010e+00 1.23158467e+00 6.61596358e-01 5.30012488e-01
-1.05344367e+00 -4.20053869e-01 5.44886112e-01 7.23386168e-01
-1.11945903e+00 -2.09820971e-01 5.74602365e-01 -4.88195598e-01
1.18562555e+00 2.89890826e-01 6.48007333e-01 1.03877890e+00
-1.58805743e-01 1.28716707e+00 1.03767431e+00 -2.52102524e-01
6.59810007e-03 -1.39611572e-01 3.41078103e-01 5.52326262e-01
-3.30629081e-01 9.58329253e-03 -6.54749990e-01 3.04849684e-01
3.79757851e-01 -2.92803645e-01 -2.10604034e-02 -3.20879459e-01
-9.33934212e-01 4.71558064e-01 4.25716519e-01 3.78528953e-01
-1.45500436e-01 2.68241495e-01 5.48626304e-01 -1.59612626e-01
5.84548533e-01 1.94861025e-01 -6.68302238e-01 -3.78886044e-01
-1.29398608e+00 2.95016825e-01 4.35083389e-01 9.90333974e-01
3.86228353e-01 -1.73417062e-01 -3.84733230e-01 8.31966877e-01
4.20187414e-01 1.90560728e-01 1.47721648e-01 -1.60462070e+00
7.01789677e-01 2.97623456e-01 -3.92560065e-02 -7.61370242e-01
-5.33959389e-01 -1.19628713e-01 -1.58891231e-01 -7.88343418e-03
5.11199713e-01 1.32671356e-01 -1.25637686e+00 1.81214380e+00
2.47585744e-01 6.52152717e-01 -1.82879761e-01 8.86783481e-01
8.52711916e-01 7.47716427e-01 6.57664895e-01 3.15209404e-02
1.25302827e+00 -1.33810508e+00 -6.06902957e-01 -4.05472428e-01
6.49900675e-01 -6.61474884e-01 8.79194260e-01 4.40904111e-01
-1.04195905e+00 -6.55198693e-01 -9.45574880e-01 -2.36942291e-01
-2.62830734e-01 -1.13055967e-01 6.62590623e-01 4.49365050e-01
-1.19157481e+00 7.95863569e-01 -1.00211120e+00 -3.26415300e-01
5.75106978e-01 2.41023481e-01 -1.76211149e-01 -1.67442545e-01
-1.09977734e+00 6.94318175e-01 5.80871463e-01 -2.18303204e-01
-4.52516556e-01 -1.01561189e+00 -8.19837034e-01 -2.23416105e-01
5.18103719e-01 -2.47756153e-01 1.37839496e+00 -9.53848541e-01
-1.04833221e+00 1.06198204e+00 -4.03995723e-01 -9.26777422e-01
8.44805658e-01 -4.43871349e-01 -3.69076014e-01 4.04212743e-01
2.70641655e-01 1.33797026e+00 3.37694108e-01 -1.11343849e+00
-8.93648028e-01 -2.17519224e-01 -7.00293258e-02 2.47740507e-01
1.61611289e-01 8.74044523e-02 -1.04949701e+00 -4.85714436e-01
1.45588219e-01 -9.62410271e-01 -3.18640113e-01 -4.36721981e-01
-2.53134221e-01 -1.84111908e-01 1.15011597e+00 -1.07326353e+00
1.10828078e+00 -2.26548910e+00 1.93015307e-01 -1.21276692e-01
-2.47995704e-02 2.01717883e-01 -1.09592468e-01 7.17383176e-02
-1.45967007e-01 4.59224939e-01 -1.54124200e-01 -5.68461061e-01
-2.67232209e-01 2.29135662e-01 -2.55220175e-01 5.70375696e-02
3.29213828e-01 1.00079811e+00 -7.17501640e-01 -7.80387282e-01
3.89633298e-01 2.80635327e-01 -6.46771550e-01 -2.23580152e-01
-5.61822414e-01 5.00173211e-01 -3.89524937e-01 4.04931128e-01
4.98371720e-01 -3.25877517e-01 1.79490939e-01 -2.10446760e-01
-1.20896012e-01 4.36843723e-01 -8.78342569e-01 1.96446776e+00
-1.55821592e-01 9.29997325e-01 -2.75751054e-01 -9.13269937e-01
5.45993924e-01 2.63490707e-01 8.80020261e-01 -1.17759156e+00
-5.98040819e-02 -1.96183056e-01 -2.34008893e-01 -3.68759215e-01
6.44267917e-01 1.50324509e-01 -4.00421619e-02 -8.58827010e-02
1.15830362e-01 -6.05519162e-03 4.99691099e-01 4.47158635e-01
9.69440997e-01 6.56367838e-01 -1.24962412e-01 -3.34959328e-01
2.70202368e-01 2.37802044e-01 8.31424594e-01 8.51875901e-01
-4.11157012e-01 9.20637846e-01 5.39836109e-01 -3.12502950e-01
-9.09602165e-01 -1.07957518e+00 -1.75902948e-01 8.85916770e-01
4.47298765e-01 -4.84125733e-01 -8.79433155e-01 -9.73970294e-01
-3.36982816e-01 8.92673016e-01 -5.79714715e-01 2.94082006e-03
-9.14744794e-01 -6.27719700e-01 5.03943026e-01 8.75899911e-01
7.34471738e-01 -1.08435011e+00 -5.54830730e-01 5.12585156e-02
-8.28222811e-01 -1.82523966e+00 -1.85967788e-01 9.10359994e-02
-1.03772795e+00 -1.15086043e+00 -3.99004370e-01 -8.18033397e-01
1.30227590e-02 1.34867713e-01 1.20719147e+00 -1.31901160e-01
-4.68645304e-01 3.96301001e-01 -5.97994804e-01 -2.11166531e-01
-1.90702483e-01 1.76290914e-01 -3.99846762e-01 -3.01322043e-01
3.55645984e-01 -1.86421975e-01 -3.91794682e-01 2.36573040e-01
-5.06878078e-01 4.11881775e-01 1.77808881e-01 4.28615332e-01
8.20110142e-01 -7.59457797e-02 2.98190475e-01 -1.11217856e+00
-1.44325420e-01 -2.71389425e-01 -6.05854154e-01 2.72027910e-01
-5.19859672e-01 -9.26623773e-03 2.29877084e-01 -2.63058394e-01
-1.36345673e+00 2.14628905e-01 -3.05034041e-01 -3.38927954e-01
-2.05308691e-01 1.83406189e-01 -2.03496829e-01 1.87684447e-01
3.31277400e-01 -7.63204023e-02 -4.64428961e-01 -5.53740561e-01
5.06835341e-01 1.74198776e-01 7.60807335e-01 -5.78497469e-01
3.08257967e-01 4.21287298e-01 -6.12806194e-02 -7.22449303e-01
-1.04526007e+00 -7.06973314e-01 -7.45913982e-01 -2.81383812e-01
1.46191776e+00 -9.26809251e-01 -3.74552488e-01 4.81096655e-01
-1.15926874e+00 -6.15266085e-01 -3.67168158e-01 3.64768475e-01
-6.25269353e-01 4.42632914e-01 -8.54711056e-01 -4.98417646e-01
1.55127108e-01 -1.21312535e+00 1.15344858e+00 2.35375673e-01
-3.13026100e-01 -7.93210745e-01 -1.55695975e-01 9.55495775e-01
-1.23230251e-03 6.43489882e-02 6.85230374e-01 -6.42252684e-01
-8.67146611e-01 2.95016617e-02 -4.71845984e-01 4.55386907e-01
-3.75527948e-01 6.88199848e-02 -1.15797055e+00 2.53716916e-01
-2.39203289e-01 -1.58503562e-01 1.44418025e+00 7.05380023e-01
1.41711986e+00 2.47487277e-01 -3.82512182e-01 4.57370818e-01
1.31347382e+00 2.94778705e-01 9.02130961e-01 4.68060672e-01
8.43641162e-01 7.25665212e-01 9.80455041e-01 8.88691023e-02
6.46717072e-01 9.50632334e-01 3.42741817e-01 6.23294115e-02
-4.94924843e-01 -3.31056684e-01 1.77603334e-01 5.71033716e-01
-3.91864218e-02 -4.20046687e-01 -1.15925145e+00 5.31069338e-01
-1.94587469e+00 -9.57571447e-01 -5.34258485e-01 1.77093506e+00
4.90670085e-01 2.88259804e-01 1.63418293e-01 6.28835103e-03
6.34239018e-01 4.16870922e-01 -2.85073161e-01 -2.70636410e-01
-2.78437138e-01 1.14304103e-01 7.60397255e-01 5.62597513e-01
-1.50214279e+00 1.48495841e+00 7.15604496e+00 8.79354894e-01
-9.08047140e-01 3.37518781e-01 9.66433644e-01 -1.26333073e-01
-1.65303200e-02 1.17894545e-01 -8.70193243e-01 5.02072632e-01
1.02668691e+00 2.42094949e-01 1.46206379e-01 8.49487841e-01
2.13531420e-01 -4.54464585e-01 -9.33503389e-01 7.45141983e-01
2.15345360e-02 -1.52756023e+00 -2.12901428e-01 -1.30762309e-01
7.56032169e-01 4.68719661e-01 8.00995305e-02 2.12349951e-01
1.59078643e-01 -8.82874548e-01 1.05544114e+00 3.67259622e-01
3.53121817e-01 -4.83078659e-01 6.70283973e-01 1.63747892e-01
-1.27937305e+00 -3.38376909e-02 1.58757672e-01 1.36420041e-01
5.98816156e-01 3.62409472e-01 -6.28203571e-01 5.27584314e-01
1.06059170e+00 9.01462317e-01 -7.41426110e-01 1.12155139e+00
-1.38360545e-01 8.32803071e-01 -2.69071490e-01 2.47252613e-01
3.21246743e-01 -1.19442321e-01 3.96714807e-01 1.48936820e+00
-2.64073480e-02 4.81598489e-02 3.62935156e-01 4.56553251e-01
-4.95904721e-02 -6.76725581e-02 -2.71959692e-01 -2.34607700e-02
1.90463156e-01 1.01918268e+00 -1.11365128e+00 -4.00759161e-01
-4.73398596e-01 1.04824424e+00 9.70119610e-02 2.83402592e-01
-1.10878599e+00 4.41734880e-01 4.36461091e-01 9.76506472e-02
4.31969404e-01 -1.98201314e-01 -6.68311596e-01 -8.63942504e-01
7.76187554e-02 -4.83755946e-01 5.40428936e-01 -8.11206222e-01
-8.91309500e-01 4.89835083e-01 3.15663368e-01 -8.93574178e-01
-2.23343447e-01 -5.67039669e-01 -2.18327060e-01 4.58423644e-01
-1.39209116e+00 -1.15124810e+00 -1.80841297e-01 1.99226514e-01
8.72654796e-01 1.94500506e-01 3.49608749e-01 5.70702136e-01
-5.07667363e-01 3.35586548e-01 -3.84904236e-01 4.73941676e-02
4.65507150e-01 -1.29177988e+00 6.08800650e-01 1.13010955e+00
4.37789202e-01 -6.78355768e-02 5.88889539e-01 -7.60188282e-01
-7.25543439e-01 -1.23727989e+00 9.30145919e-01 -7.75937021e-01
5.06907225e-01 -2.78200090e-01 -8.42881262e-01 7.76595533e-01
1.16769902e-01 -8.73847678e-02 3.68697345e-01 1.94669336e-01
-5.16315699e-01 1.15857288e-01 -1.01126969e+00 5.59578776e-01
1.35969639e+00 -4.38171208e-01 -4.52564031e-01 1.30539015e-01
1.15404272e+00 -5.26039958e-01 -6.66988730e-01 7.23533511e-01
3.90853316e-01 -9.24191356e-01 1.15550196e+00 -6.63929582e-01
7.15063512e-01 -4.86405455e-02 -4.00907576e-01 -6.24252617e-01
-2.45842487e-01 -1.06372915e-01 1.43732697e-01 1.28138542e+00
6.34128213e-01 4.87513654e-02 1.21186483e+00 6.96991920e-01
-2.25806803e-01 -5.93071818e-01 -9.58052933e-01 -8.15661013e-01
-5.52342013e-02 -1.01773822e+00 8.77267122e-02 7.70193279e-01
-3.94394487e-01 1.18907981e-01 -4.90642965e-01 1.94046181e-02
5.44661462e-01 -4.86920699e-02 3.23151648e-01 -1.00094271e+00
-4.39696372e-01 -5.35361409e-01 -5.86768031e-01 -1.13402474e+00
2.09029034e-01 -9.49069977e-01 1.86666936e-01 -1.66465819e+00
3.31810892e-01 -3.44980657e-01 -4.07666087e-01 5.17307520e-01
-1.51066601e-01 5.02780676e-01 6.06449962e-01 -1.48384154e-01
-1.20565462e+00 6.90824613e-02 1.03346276e+00 -7.89470822e-02
-1.78474009e-01 -1.65885180e-01 -4.60539222e-01 8.55181336e-01
8.69903684e-01 -3.97982270e-01 -4.96235937e-01 -6.34893239e-01
-1.74440071e-01 1.25955278e-02 4.41580862e-01 -1.05164206e+00
5.02457656e-02 -2.12141946e-01 4.02677149e-01 -7.78571665e-01
5.83378673e-01 -5.78875959e-01 5.82919866e-02 3.37825477e-01
-4.46972013e-01 -1.40061542e-01 4.33094263e-01 6.37984633e-01
-4.24137205e-01 -1.87494874e-01 8.91398013e-01 -1.41449898e-01
-1.48978424e+00 1.97714314e-01 -8.16875100e-02 2.96699584e-01
1.06485701e+00 -3.55295151e-01 -2.40107790e-01 -4.60758917e-02
-1.07814324e+00 4.20351088e-01 2.87819147e-01 8.37101161e-01
3.63217890e-01 -9.07288849e-01 -4.06257242e-01 -1.59167603e-01
5.58123598e-03 -1.41042367e-01 5.60351253e-01 8.25867653e-01
-5.25696039e-01 4.58353817e-01 -2.33370904e-03 -9.10797894e-01
-1.47697532e+00 2.33232036e-01 2.62776226e-01 -4.61395651e-01
-7.78564990e-01 1.12395322e+00 2.62595236e-01 -1.83145508e-01
2.80343294e-01 -2.13569000e-01 -2.69432962e-01 2.09042318e-02
3.98062766e-01 3.79022330e-01 3.23960260e-02 -6.89711869e-01
-5.92463613e-01 5.15820146e-01 -1.52003214e-01 -4.83674645e-01
1.19461238e+00 -1.84679732e-01 1.10225610e-01 4.85096514e-01
1.16297412e+00 -2.66587079e-01 -1.50766242e+00 -5.73804118e-02
5.54332674e-01 -2.69370884e-01 1.34691060e-01 -1.06366074e+00
-1.09091318e+00 8.58336151e-01 7.27331460e-01 -6.72782734e-02
1.09066057e+00 3.38371783e-01 9.12400961e-01 -4.87966500e-02
3.36261272e-01 -1.36588800e+00 -1.95514108e-03 5.38227856e-01
4.52515095e-01 -1.34187829e+00 -1.68576017e-01 -9.05486643e-01
-1.03982723e+00 7.29368210e-01 6.64134026e-01 5.01777679e-02
3.99643332e-01 3.42804909e-01 4.39887419e-02 4.03265655e-02
-6.95676565e-01 -2.27196708e-01 5.72704792e-01 5.15940726e-01
3.08749974e-01 1.82024017e-02 -3.62624049e-01 6.86435878e-01
-9.23868492e-02 -8.00344348e-02 4.85315584e-02 7.33115733e-01
-3.59637350e-01 -1.33349872e+00 1.87490419e-01 3.48308474e-01
-6.51406288e-01 -1.79498106e-01 -4.70415443e-01 8.17199290e-01
3.28113794e-01 9.67103720e-01 7.73208663e-02 -3.87690008e-01
2.40779519e-01 2.19525129e-01 4.80759293e-01 -5.12600005e-01
-3.44261080e-01 1.98254541e-01 4.24053609e-01 -1.10684538e+00
-6.01577759e-01 -9.58655596e-01 -1.55813098e+00 3.01018115e-02
2.09573265e-02 4.31813411e-02 8.14165831e-01 1.03984165e+00
3.56949538e-01 7.09371328e-01 1.94925413e-01 -6.05255365e-01
7.44485483e-02 -5.95992923e-01 -2.10049152e-01 5.02114832e-01
-3.55243273e-02 -4.83176082e-01 -2.87410077e-02 3.29534292e-01] | [9.186338424682617, 0.04475310444831848] |
56000e75-111d-4c2c-aa25-2d88dde48fda | co-optimization-of-adaptive-cruise-control | 2303.01218 | null | https://arxiv.org/abs/2303.01218v2 | https://arxiv.org/pdf/2303.01218v2.pdf | Co-Optimization of Adaptive Cruise Control and Hybrid Electric Vehicle Energy Management via Model Predictive Mixed Integer Control | In this paper, a model predictive mixed integer control method for BYD Qin Plus DM-i (Dual Model intelligent) plug-in hybrid electric vehicle (PHEV) is proposed for co-optimization to reduce fuel consumption during car following. First, the adaptive cruise control (ACC) model for energy-saving driving is established. Then, a control-oriented energy management strategy (EMS) model considering the clutch engagement and disengagement is constructed. Finally, the co-optimization structure by integrating ACC model and EMS model is created and is converted to the mixed integer nonlinear programming (MINLP). The results show that this modeling method can be applied to EMS based on the model predictive control (MPC) framework and verify that co-optimization can achieve a 5.1$\%$ reduction in fuel consumption compared to sequential optimization with the guarantee of ACC performance. | ['Yuan Lin', 'Changfu Gong', 'Qitao Li'] | 2023-03-02 | null | null | null | null | ['energy-management'] | ['time-series'] | [-1.31801531e-01 2.44589701e-01 -8.51553679e-01 1.78771354e-02
-6.48850575e-02 -2.62713253e-01 5.19324005e-01 3.84868905e-02
-1.22450531e-01 8.67977440e-01 -5.91356039e-01 -6.69506848e-01
-9.25202966e-01 -9.69308615e-01 -5.34931600e-01 -8.11450005e-01
1.11363910e-01 4.41892385e-01 -4.20455247e-01 -1.75290734e-01
6.78171292e-02 6.09730721e-01 -1.57021701e+00 -4.89989460e-01
1.32272458e+00 9.96690571e-01 7.61943042e-01 3.45860660e-01
2.50420421e-01 6.56271219e-01 -5.39470650e-02 1.09159946e-01
3.48657161e-01 -2.44089231e-01 -4.78191793e-01 1.34709150e-01
-1.01355159e+00 -3.40718746e-01 8.97100866e-02 8.69948149e-01
2.16732785e-01 6.81684434e-01 6.29844606e-01 -2.25345063e+00
7.80571550e-02 1.17785148e-01 -3.86814088e-01 -2.06031471e-01
-3.81181180e-01 3.38744432e-01 6.44559920e-01 -6.40294075e-01
3.24543625e-01 1.00030088e+00 -9.30301547e-02 3.14860255e-01
-1.21438992e+00 -4.91170794e-01 2.63739407e-01 5.09089410e-01
-1.42667580e+00 9.42382589e-02 7.82562256e-01 -3.55984807e-01
1.45272994e+00 7.55611777e-01 1.37503791e+00 -7.87989050e-02
6.30063117e-01 6.96112156e-01 9.41396594e-01 -3.59919906e-01
3.82234693e-01 3.96086961e-01 2.18693659e-01 2.38235995e-01
4.03477818e-01 5.19986093e-01 2.11456165e-01 3.37899059e-01
-4.85484898e-02 -6.51384331e-03 2.48983413e-01 -2.51916230e-01
-6.69262052e-01 1.01104152e+00 1.01012558e-01 -5.07519916e-02
-5.63936651e-01 -6.35717586e-02 2.67937601e-01 -7.07361251e-02
4.52674210e-01 5.43788910e-01 -4.21339750e-01 -2.26607323e-02
-7.93145657e-01 5.82511663e-01 8.61790121e-01 1.21634912e+00
5.05709350e-01 4.39267814e-01 -2.96291590e-01 7.31615067e-01
6.75057054e-01 5.26047349e-01 -3.93345207e-02 -1.33216381e+00
5.72724752e-02 8.08365643e-01 4.16533738e-01 -5.98556101e-01
-4.94271934e-01 -1.67563289e-01 -6.02650285e-01 5.72899401e-01
-4.09147114e-01 -4.69320863e-01 -5.38102210e-01 1.10234988e+00
1.78939566e-01 -2.38361165e-01 1.66995525e-01 5.85915565e-01
2.42957294e-01 1.28132236e+00 1.76073670e-01 -8.85440052e-01
1.18135250e+00 -1.34801948e+00 -1.17280519e+00 -1.17366262e-01
4.79802191e-01 -1.81125075e-01 1.11271560e-01 2.90553778e-01
-1.43971729e+00 -4.00491476e-01 -1.39616156e+00 -3.12594920e-02
-6.50578737e-01 2.38063410e-01 2.36942291e-01 5.54086149e-01
-8.34382832e-01 2.86098152e-01 -5.01967669e-01 5.77554330e-02
-1.67109475e-01 6.47499084e-01 2.59763718e-01 2.45605946e-01
-1.14035380e+00 1.42507052e+00 7.74596989e-01 5.69793999e-01
-8.02833498e-01 -1.03628087e+00 -9.30333912e-01 -7.61128962e-02
6.91922605e-01 -4.16794479e-01 1.11949515e+00 -6.48554921e-01
-1.99577343e+00 2.71159589e-01 -3.34942579e-01 -3.61518502e-01
5.02522349e-01 1.13280773e-01 -2.80134499e-01 1.48449175e-03
-3.33115697e-01 5.63084424e-01 2.94095486e-01 -1.21258819e+00
-1.04515588e+00 1.33309498e-01 2.63306759e-02 3.49286139e-01
1.84708938e-01 -3.80300432e-02 -1.17946751e-01 -1.04334779e-01
-6.98064983e-01 -1.00245523e+00 -5.06262720e-01 -3.99228185e-01
-4.19914752e-01 -6.51091099e-01 1.11085331e+00 -9.35580492e-01
1.56335378e+00 -1.69748926e+00 5.31651795e-01 5.47626972e-01
-2.25121304e-01 2.31403366e-01 2.85519272e-01 4.06881034e-01
-4.12730351e-02 1.77178025e-01 -1.25800058e-01 -2.85147488e-01
4.71794784e-01 5.92026293e-01 2.61355847e-01 3.10727417e-01
3.14758062e-01 9.37350094e-01 -6.83849812e-01 -2.56638855e-01
8.89869630e-01 7.81071410e-02 -4.88778770e-01 4.26505297e-01
-3.88480246e-01 -1.15502737e-01 -4.64275777e-01 4.92816478e-01
1.00684154e+00 6.63989484e-01 3.53070945e-01 -3.49829525e-01
-1.02693009e+00 -4.37309653e-01 -1.20624232e+00 8.10776353e-01
-6.60639465e-01 4.22298968e-01 9.40183640e-01 -1.37809813e+00
7.82036066e-01 1.38430595e-01 9.41519678e-01 -9.51701105e-01
3.50467801e-01 1.37408882e-01 -1.79485366e-01 -4.67191190e-01
8.05479228e-01 -9.46679488e-02 8.29112828e-02 -5.44986203e-02
-1.07522406e-01 -3.85599673e-01 5.66711009e-01 -3.62244844e-01
2.44813666e-01 1.23937167e-01 3.33102830e-02 -1.03182399e+00
1.03805304e+00 5.92358112e-01 9.50929105e-01 -1.92863211e-01
-2.66801510e-02 -7.03901470e-01 6.03668272e-01 1.85416773e-01
-1.23368418e+00 -5.28408825e-01 -2.18320668e-01 6.03486836e-01
7.19525635e-01 -1.62216816e-02 -6.41608953e-01 -5.69481291e-02
1.98377237e-01 1.55415332e+00 -1.41059235e-02 -3.86018395e-01
-6.06981397e-01 -8.42545569e-01 -3.49736094e-01 3.58624011e-01
3.52374345e-01 -2.60147989e-01 -7.41011262e-01 4.00502682e-01
2.48397142e-01 -8.19005251e-01 -2.56185293e-01 4.75081265e-01
-4.06397671e-01 -9.19520855e-01 -2.95917064e-01 -7.84462988e-01
7.67722964e-01 7.05100298e-02 6.55006051e-01 8.43618885e-02
-1.20328523e-01 1.88224196e-01 8.60661343e-02 -8.88110340e-01
-3.62671852e-01 -2.24054843e-01 1.11328967e-01 -7.55956098e-02
1.05052322e-01 2.28708595e-01 -3.70912641e-01 6.14468694e-01
-6.47429228e-01 5.78012645e-01 1.17792569e-01 8.59155774e-01
9.09818172e-01 8.22392106e-01 9.44609463e-01 -1.26976535e-01
7.58100450e-01 -5.72288513e-01 -1.34154308e+00 2.97399044e-01
-1.25681078e+00 -7.52964094e-02 6.74648881e-01 -1.48035139e-01
-1.30808246e+00 1.63657978e-01 -1.52608469e-01 -4.74729985e-01
3.46505493e-01 2.74776638e-01 -6.80969179e-01 -3.84494290e-02
-9.11306977e-01 1.47385672e-01 7.21988738e-01 -2.44720787e-01
4.16306145e-02 4.19911921e-01 1.64715409e-01 -5.45111120e-01
8.69003236e-01 -1.67516887e-01 6.01781487e-01 -4.59459424e-01
1.47269949e-01 -1.70153767e-01 -2.64486402e-01 -6.60209119e-01
1.22945440e+00 -8.58621478e-01 -1.32407236e+00 4.49704826e-01
-7.50082731e-01 -6.14510298e-01 -3.22315872e-01 5.81804395e-01
-8.33622634e-01 -1.08285613e-01 -7.91354775e-02 -1.39637971e+00
-1.40128806e-01 -1.65855742e+00 2.50416458e-01 5.17424941e-01
1.77406996e-01 -1.01158464e+00 -3.12338024e-01 3.34811360e-01
3.89690757e-01 5.57840824e-01 1.03375506e+00 -1.26458360e-02
-7.16542482e-01 8.91485363e-02 7.76610300e-02 6.83553100e-01
-3.60583425e-01 4.79442328e-01 -2.61708707e-01 -4.48601931e-01
-9.67994332e-02 3.31605554e-01 -2.94862892e-02 5.48117578e-01
1.04173422e+00 -6.83193147e-01 -6.15896881e-01 4.81198102e-01
2.20773864e+00 1.27480876e+00 4.26989615e-01 5.08793294e-01
2.03779235e-01 7.79751301e-01 1.22800374e+00 3.65492642e-01
5.93287051e-01 8.71462524e-01 8.73733878e-01 -2.81058073e-01
6.45184636e-01 1.82159748e-02 4.12331134e-01 4.64325249e-01
-2.39938572e-01 -2.20050275e-01 -5.46817482e-01 5.73666036e-01
-1.82888532e+00 -8.35820496e-01 -5.75434864e-01 1.96317446e+00
5.10749578e-01 -7.16886148e-02 1.39603302e-01 2.55268991e-01
6.81984782e-01 -3.64490479e-01 -5.20997047e-01 -1.43546021e+00
1.85923338e-01 -7.04207867e-02 1.21013355e+00 6.82637811e-01
-6.12963855e-01 9.24859270e-02 5.76070786e+00 1.15761912e+00
-8.43237996e-01 1.70822162e-02 7.92385817e-01 -3.61264437e-01
-3.77961934e-01 4.04580496e-02 -8.45111072e-01 8.85256648e-01
1.40564406e+00 -1.10042882e+00 8.73298705e-01 7.50816226e-01
1.08539152e+00 -5.36081672e-01 -8.82985771e-01 4.97824967e-01
-4.50981230e-01 -1.18456364e+00 -6.69550717e-01 3.75863791e-01
8.02705586e-01 -5.09992719e-01 -4.06719923e-01 6.50201857e-01
6.14666119e-02 -8.84943545e-01 1.01600099e+00 7.48375237e-01
2.45041087e-01 -1.60038507e+00 7.74716198e-01 8.50827992e-01
-1.31156349e+00 -6.95915520e-01 5.32917194e-02 -2.18653549e-02
8.96529734e-01 3.15598935e-01 -3.72185528e-01 1.03365910e+00
3.68785709e-01 4.03049588e-01 4.37754653e-02 8.75528038e-01
1.92622304e-01 1.05917767e-01 -3.19105148e-01 -4.79179978e-01
2.68513381e-01 -1.01908553e+00 6.51969194e-01 8.31298888e-01
3.35883617e-01 2.08256647e-01 1.54741541e-01 1.23902750e+00
6.99214756e-01 -9.10383761e-02 -3.12280357e-01 -1.72764942e-01
3.16544205e-01 1.34054244e+00 -3.08363110e-01 -1.50295824e-01
-2.35345736e-01 3.63319695e-01 -5.73417127e-01 3.79700661e-01
-1.36890364e+00 -6.57655299e-01 8.81409883e-01 2.57997513e-02
-4.15283181e-02 -2.25682527e-01 -3.61580312e-01 -2.68528789e-01
-1.79366469e-01 -7.35255778e-02 -1.77913770e-01 -7.64317989e-01
-7.20024109e-01 -6.83638453e-02 8.13389301e-01 -1.02042019e+00
-3.93821239e-01 -8.25783789e-01 -8.66258025e-01 1.07196689e+00
-2.08238816e+00 -7.55562901e-01 3.36888470e-02 2.80953795e-02
7.18703866e-01 -1.48683833e-02 1.98366433e-01 7.32879460e-01
-1.40522575e+00 5.86420819e-02 5.73368132e-01 -8.45562935e-01
-1.95269868e-01 -1.08149862e+00 -8.10976505e-01 9.35650945e-01
-1.68489313e+00 -3.01923193e-02 8.51983905e-01 -4.27555710e-01
-2.30227947e+00 -1.30759239e+00 8.91202450e-01 4.44005817e-01
4.56490993e-01 -6.63893372e-02 -4.35716271e-01 2.07572758e-01
8.96448314e-01 -5.56341946e-01 1.31399268e-02 -8.33439052e-01
1.03670406e+00 -4.44729120e-01 -1.53073573e+00 4.19647098e-01
4.04379040e-01 8.15002173e-02 -9.62385442e-03 4.09557521e-02
8.85341167e-01 -3.20830673e-01 -1.27625883e+00 5.99727392e-01
3.29471111e-01 6.78340942e-02 9.38228786e-01 -2.40734935e-01
4.14171778e-02 -4.89089459e-01 1.16772272e-01 -1.46813321e+00
-2.99052924e-01 -8.16781759e-01 -4.91804302e-01 1.35685158e+00
3.78791779e-01 -6.50125682e-01 1.92122936e-01 1.19000149e+00
-6.78518951e-01 -1.06334805e+00 -1.33697879e+00 -1.11777890e+00
2.02974394e-01 -3.76819581e-01 6.25753820e-01 4.89870876e-01
2.53828764e-01 -6.89106584e-02 -2.74526745e-01 1.85723126e-01
6.24192774e-01 -2.26966769e-01 4.38303113e-01 -8.41176867e-01
1.23962507e-01 -6.61694646e-01 1.89542830e-01 -4.28872049e-01
5.38867116e-01 -9.38778818e-01 1.70298368e-01 -1.92025590e+00
-9.42730904e-02 -6.00285940e-02 -2.07776651e-01 3.00159544e-01
5.81075922e-02 -4.43320334e-01 5.25210619e-01 -4.01607662e-01
-3.56707238e-02 8.68967116e-01 1.24963701e+00 -4.71364677e-01
-4.50601608e-01 1.44218579e-01 -4.10521477e-01 2.69711256e-01
9.07559514e-01 -1.28949359e-01 -5.84076643e-01 1.91235602e-01
8.95252973e-02 4.45398271e-01 4.23552871e-01 -6.92842185e-01
1.16095655e-01 -9.54430163e-01 -3.89090210e-01 -1.09371054e+00
2.27976203e-01 -1.68416274e+00 8.52905273e-01 8.54469717e-01
1.25370994e-01 1.83070555e-01 4.59226370e-01 3.02663535e-01
-2.06492558e-01 -4.09668326e-01 8.04874420e-01 4.85855609e-01
-8.87047470e-01 7.94476196e-02 -9.53410864e-01 -6.93932235e-01
2.15468359e+00 -5.38224399e-01 -2.94142544e-01 2.32630759e-01
-5.29391646e-01 1.34894073e+00 -7.58476183e-03 4.05441880e-01
1.64767265e-01 -1.42178988e+00 -3.99648130e-01 -5.43989129e-02
-4.71656680e-01 -1.73500553e-01 6.13849521e-01 1.17908788e+00
-4.55447406e-01 9.05680180e-01 -3.29568624e-01 -3.66323382e-01
-1.09538949e+00 7.68507957e-01 6.66122437e-01 -3.61394316e-01
-6.82864115e-02 3.87428552e-02 -3.29436362e-01 -4.56919998e-01
-1.93773597e-01 -3.67686629e-01 -1.23269401e-01 2.01933816e-01
-5.11439145e-02 1.30740130e+00 -6.18752316e-02 -6.03234947e-01
-3.51898134e-01 2.28340402e-01 8.48431706e-01 5.25541157e-02
1.37833726e+00 -3.07391137e-01 -3.15255404e-01 6.69941828e-02
1.48058534e+00 -5.02465248e-01 -1.46168995e+00 7.24245906e-01
-3.12687129e-01 1.94188803e-02 6.00124061e-01 -7.60040998e-01
-1.19735467e+00 2.79382944e-01 5.44781029e-01 3.27304870e-01
1.45928288e+00 -5.98647654e-01 4.92587000e-01 1.27800748e-01
9.10387859e-02 -1.91277099e+00 -7.45762050e-01 4.81625497e-01
8.28074813e-01 -6.46491408e-01 4.65745069e-02 -3.97542059e-01
-7.19453871e-01 1.08592772e+00 8.51143301e-01 -4.55179960e-02
1.00644374e+00 5.62651336e-01 -9.64486420e-01 2.80278236e-01
-9.31594670e-01 -2.64022872e-02 1.97817177e-01 2.22368211e-01
-3.13661188e-01 3.74628872e-01 -1.07903194e+00 9.51661944e-01
4.38684225e-01 2.63993114e-01 3.33613425e-01 1.03951371e+00
-3.68193120e-01 -9.52745855e-01 -3.44592571e-01 3.47119987e-01
-7.59204626e-02 5.41148961e-01 3.86913091e-01 1.12163889e+00
5.98685920e-01 1.37492192e+00 4.30410534e-01 -3.22221994e-01
7.73977935e-01 1.97766814e-02 -2.37562996e-03 7.17121810e-02
-4.99785602e-01 3.93272936e-03 3.91228288e-01 -3.57366085e-01
-4.56883222e-01 -3.48432302e-01 -1.44845843e+00 -5.30458570e-01
-6.28894806e-01 4.48921204e-01 1.13185835e+00 1.01264918e+00
3.94424528e-01 9.35554743e-01 1.18618476e+00 -9.18978095e-01
-3.14380109e-01 -2.85364866e-01 -7.75053740e-01 -4.72892970e-01
6.62304163e-02 -9.29219723e-01 -5.58589935e-01 -2.50771552e-01] | [5.565412521362305, 2.2616865634918213] |
ab5ea0c0-a7c4-4582-93ec-09f04d980a78 | cumulative-progress-in-language-models-for | null | null | https://aclanthology.org/U13-1013 | https://aclanthology.org/U13-1013.pdf | Cumulative Progress in Language Models for Information Retrieval | null | ['Antti Puurula'] | 2013-12-01 | cumulative-progress-in-language-models-for-1 | https://aclanthology.org/U13-1013 | https://aclanthology.org/U13-1013.pdf | alta-2013-12 | ['ad-hoc-information-retrieval'] | ['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] | [-7.426943778991699, 3.609996795654297] |
4d4e720e-172c-4328-8b82-ff52fd23d2ca | using-twitter-to-predict-football-outcomes | 1411.1243 | null | http://arxiv.org/abs/1411.1243v1 | http://arxiv.org/pdf/1411.1243v1.pdf | Using Twitter to predict football outcomes | Twitter has been proven to be a notable source for predictive modelling on
various domains such as the stock market, the dissemination of diseases or
sports outcomes. However, such a study has not been conducted in football
(soccer) so far. The purpose of this research was to study whether data mined
from Twitter can be used for this purpose. We built a set of predictive models
for the outcome of football games of the English Premier League for a 3 month
period based on tweets and we studied whether these models can overcome
predictive models which use only historical data and simple football
statistics. Moreover, combined models are constructed using both Twitter and
historical data. The final results indicate that data mined from Twitter can
indeed be a useful source for predicting games in the Premier League. The final
Twitter-based model performs significantly better than chance when measured by
Cohen's kappa and is comparable to the model that uses simple statistics and
historical data. Combining both models raises the performance higher than it
was achieved by each individual model. Thereby, this study provides evidence
that Twitter derived features can indeed provide useful information for the
prediction of football (soccer) outcomes. | ['Andreas Adamides', 'Stylianos Kampakis'] | 2014-11-05 | null | null | null | null | ['game-of-football'] | ['playing-games'] | [-4.73080903e-01 -1.29158407e-01 -7.25995302e-01 2.91328738e-03
-6.55144691e-01 -1.16903782e-01 8.53686929e-01 1.04107606e+00
-9.11892116e-01 9.69098032e-01 4.34880823e-01 -2.62627423e-01
-3.06678712e-01 -1.25080943e+00 -6.12081587e-01 -4.51028347e-01
-1.45362198e-01 3.52774054e-01 5.27066410e-01 -6.28567100e-01
5.50679982e-01 3.53725284e-01 -2.09805131e+00 2.61900693e-01
4.66271579e-01 8.67975235e-01 6.03486784e-02 3.10047269e-01
-1.27435075e-02 1.07172894e+00 -6.43767118e-01 -4.44852531e-01
7.09147155e-02 -2.04069227e-01 -4.53067005e-01 -5.75435400e-01
-1.64911121e-01 -1.53272040e-02 9.02321637e-02 5.64821720e-01
3.94249588e-01 1.44597620e-01 3.18745136e-01 -1.24447131e+00
1.43306069e-02 7.65159369e-01 -2.61706948e-01 4.74294901e-01
6.97353721e-01 -5.14310524e-02 8.57120335e-01 -6.03803635e-01
8.88001263e-01 8.99854422e-01 8.40142488e-01 -2.94386387e-01
-9.01481211e-01 -1.17557299e+00 -4.00788374e-02 2.42063388e-01
-1.24290371e+00 2.56047565e-02 1.86330304e-01 -7.56600380e-01
5.40717840e-01 3.80933940e-01 1.33035839e+00 7.69117117e-01
3.93405467e-01 4.28176582e-01 1.56389666e+00 -2.69122452e-01
-4.24850509e-02 5.31900644e-01 1.49398774e-01 1.42410966e-02
4.97901618e-01 3.81921649e-01 -9.97657716e-01 -1.19546786e-01
1.81576610e-01 1.43566832e-01 2.23705053e-01 5.59232891e-01
-1.29823506e+00 1.14264047e+00 2.65552610e-01 4.78018194e-01
-6.99131310e-01 -1.10472009e-01 5.60267806e-01 3.98888588e-01
1.14999354e+00 5.04781008e-01 -2.69743621e-01 -5.66346765e-01
-1.39579320e+00 6.98071837e-01 7.71911383e-01 2.12123945e-01
4.27941173e-01 -9.12472308e-02 6.28083497e-02 5.72521329e-01
3.00646245e-01 4.16991591e-01 5.07529914e-01 -3.11790496e-01
8.73880759e-02 8.37423980e-01 2.58066058e-02 -1.52803516e+00
-7.04751313e-01 -4.95859802e-01 -2.28696167e-01 1.35547921e-01
6.27703309e-01 -2.86571294e-01 -3.72313619e-01 1.16046035e+00
3.98549497e-01 1.17200539e-01 -3.02182794e-01 8.54710281e-01
1.25590944e+00 6.71847165e-01 3.91785443e-01 -2.33766496e-01
1.38006270e+00 -3.39269370e-01 -7.09275961e-01 -1.02166459e-01
7.03629494e-01 -8.46386433e-01 6.35826528e-01 5.49228728e-01
-9.46024656e-01 -5.28484523e-01 -8.52576971e-01 4.87830698e-01
-6.76060796e-01 -2.89105833e-01 6.49555981e-01 7.61096179e-01
-9.18695211e-01 6.64353549e-01 -6.12506509e-01 -4.11277503e-01
1.28973648e-01 1.92572579e-01 -3.51668209e-01 3.02637041e-01
-1.51809311e+00 1.17012620e+00 4.19471592e-01 -4.25288558e-01
-2.97208905e-01 -6.01135671e-01 -6.04176521e-01 -5.37679791e-01
1.94706365e-01 -2.52705693e-01 7.55525887e-01 -6.67312503e-01
-1.01766109e+00 1.15393150e+00 1.53326645e-01 -7.88603723e-01
5.78081071e-01 -1.89172074e-01 -4.96409118e-01 -1.42693236e-01
6.98128521e-01 1.70000680e-02 9.64075103e-02 -7.83898413e-01
-1.12486434e+00 -4.28991139e-01 -5.75586185e-02 -1.48386225e-01
-2.41977483e-01 5.49369574e-01 -9.42315981e-02 -7.75439858e-01
-1.57769576e-01 -9.48412359e-01 -2.82084763e-01 -7.70811737e-01
-8.38612765e-02 -3.33220124e-01 1.37107491e-01 -7.08116353e-01
1.78510630e+00 -1.77797270e+00 -5.33471644e-01 4.56828266e-01
5.58225140e-02 1.45144135e-01 6.39820576e-01 1.00669169e+00
1.50978878e-01 2.52296180e-01 5.05182922e-01 1.61485389e-01
-2.96977580e-01 -1.20817432e-02 -1.66012928e-01 5.90871990e-01
-1.11722298e-01 7.21385956e-01 -8.66906703e-01 -5.76845169e-01
1.84867620e-01 2.88354754e-01 -3.60900223e-01 -4.08552915e-01
1.53356701e-01 4.45750147e-01 -4.43608552e-01 3.84168357e-01
3.54594201e-01 -4.00755778e-02 2.97651459e-02 3.12685579e-01
-7.53081858e-01 4.88509417e-01 -9.25169289e-01 8.86839390e-01
-2.84620643e-01 9.34263766e-01 -4.72641975e-01 -8.22993815e-01
1.30091667e+00 2.20051691e-01 6.45145655e-01 -8.28602076e-01
3.61305565e-01 1.99676707e-01 6.72098845e-02 -4.86978441e-01
5.89905560e-01 -7.65708268e-01 -1.51068151e-01 4.47246104e-01
-4.92259443e-01 4.74816561e-02 2.75889665e-01 -1.00847334e-01
7.48743832e-01 1.02319084e-02 3.47651184e-01 -3.26748550e-01
2.97345132e-01 5.19585490e-01 3.63899976e-01 6.56974375e-01
6.86977431e-02 2.37254500e-01 4.65903938e-01 -5.41146457e-01
-6.73626423e-01 -6.23393476e-01 -3.70805323e-01 1.36004519e+00
1.22244388e-01 -7.03669310e-01 -2.20393643e-01 1.45437539e-01
2.81099707e-01 7.30216801e-01 -7.21849799e-01 3.25425081e-02
-1.53735578e-01 -1.15204453e+00 3.71885449e-01 2.04025730e-01
2.33185798e-01 -9.13669229e-01 -7.50694573e-01 4.04533863e-01
-2.69571126e-01 -7.99421191e-01 4.09163475e-01 -1.55953407e-01
-8.89824808e-01 -1.17113733e+00 -4.46666062e-01 -3.76102746e-01
-1.77654237e-01 -3.11194621e-02 1.09264302e+00 2.09708154e-01
2.54114389e-01 1.20789059e-01 -5.61786592e-01 -1.16056085e+00
-5.04274607e-01 3.22725922e-01 1.29342347e-01 6.49375468e-02
7.02108562e-01 -4.19671535e-01 -4.68976229e-01 3.95649165e-01
-7.46121168e-01 -5.05168065e-02 3.45128655e-01 2.90481716e-01
3.64340663e-01 -2.68455409e-03 1.11827731e+00 -9.82191861e-01
6.55034781e-01 -1.08533633e+00 -2.28781223e-01 -5.18525720e-01
-7.69439280e-01 -5.09129047e-01 2.10035816e-02 -2.42411107e-01
-5.61237335e-01 -4.38906372e-01 -4.75095123e-01 2.00891659e-01
-1.52140155e-01 1.21133554e+00 7.38164902e-01 1.81633174e-01
7.80592680e-01 -8.36609602e-02 4.37391102e-01 -5.12775540e-01
-4.01070774e-01 7.94057488e-01 2.33461317e-02 -1.74574524e-01
5.28257310e-01 6.20573819e-01 -5.22143096e-02 -1.08522844e+00
-8.74907434e-01 -7.46522725e-01 -4.56322700e-01 -8.95232379e-01
8.61293137e-01 -1.12179446e+00 -1.06879008e+00 3.94612253e-01
-5.62697172e-01 1.23277502e-02 -1.52936965e-01 1.03173423e+00
-1.85119152e-01 -2.96137720e-01 -4.46806818e-01 -9.80005026e-01
1.31451376e-02 -7.03521550e-01 3.98265421e-01 8.77690911e-02
-5.94132304e-01 -1.10089922e+00 3.65079343e-01 5.84145546e-01
4.68458652e-01 9.96731758e-01 3.25256765e-01 -1.16441751e+00
-1.48090616e-01 -9.54171479e-01 1.62436560e-01 -9.49271917e-02
-8.41846243e-02 1.19803898e-01 -7.97132552e-01 -9.04820412e-02
-9.31402147e-02 -4.60693017e-02 8.09449077e-01 4.26513880e-01
4.68798429e-01 -7.58495554e-02 -3.81674647e-01 -2.51516514e-02
1.21797490e+00 6.40508682e-02 4.40442294e-01 1.32535815e+00
1.00026235e-01 7.79591560e-01 1.13441944e+00 7.02330112e-01
6.27142310e-01 6.06153667e-01 3.29361379e-01 1.18384197e-01
2.27028459e-01 -3.12128335e-01 3.92143667e-01 7.44826615e-01
-7.72966921e-01 3.39355588e-01 -1.28275681e+00 7.60675311e-01
-1.74663854e+00 -1.19260097e+00 -7.82898068e-01 2.21908092e+00
4.54822570e-01 6.49969101e-01 8.07276845e-01 5.61709404e-01
6.53570831e-01 1.87419325e-01 2.20166728e-01 -5.16153812e-01
-1.01849087e-01 4.10233706e-01 7.80572772e-01 4.58571268e-03
-9.19220388e-01 5.13015509e-01 6.91943026e+00 8.92438412e-01
-1.24424827e+00 2.31749415e-01 3.54607105e-01 -3.55264306e-01
-1.35261551e-01 3.04598995e-02 -8.41397762e-01 5.70936382e-01
1.44404292e+00 -5.12101173e-01 -5.23487747e-01 7.57770181e-01
6.93748713e-01 -5.75173378e-01 -4.24209356e-01 4.96721953e-01
-1.46433309e-01 -1.63191330e+00 -2.05672517e-01 3.86870563e-01
5.87055922e-01 1.63433224e-01 -6.17811410e-03 3.75862569e-01
1.34811789e-01 -9.48270738e-01 9.60745156e-01 7.53182352e-01
4.15686637e-01 -8.45913351e-01 1.16954887e+00 6.49058282e-01
-7.70071447e-01 -5.96714988e-02 1.22550040e-01 -8.98672402e-01
2.62403250e-01 6.40640318e-01 -8.88139188e-01 3.58306915e-01
8.63226473e-01 1.03023481e+00 -5.47600567e-01 1.29373074e+00
2.09531993e-01 1.08851445e+00 -2.80704975e-01 -3.87025714e-01
4.56061840e-01 2.62347609e-02 6.08190656e-01 1.19341755e+00
3.48928541e-01 -2.06221923e-01 1.50213584e-01 1.37000099e-01
5.01650572e-01 8.36009920e-01 -7.96505034e-01 5.32345846e-02
2.25990355e-01 7.20894933e-01 -9.97682869e-01 -2.48127356e-01
-6.32258892e-01 -1.66931838e-01 -1.51951373e-01 -3.23382884e-01
-7.35762596e-01 -1.02847423e-02 4.67111439e-01 1.18117177e+00
-1.26857147e-01 1.18233152e-01 -3.69514525e-01 -5.90060532e-01
-4.42159534e-01 -5.62884986e-01 4.22214329e-01 -5.40056050e-01
-1.11360979e+00 4.22632724e-01 3.40460807e-01 -1.44182050e+00
-2.92108417e-01 -2.72807002e-01 -5.91831803e-01 6.54083490e-01
-1.21702218e+00 -8.95890772e-01 -8.73571262e-03 3.60670120e-01
4.35224846e-02 -1.43659085e-01 5.47429144e-01 2.36454442e-01
-3.41906011e-01 -2.27223411e-02 1.23035312e-01 1.01998918e-01
6.85236096e-01 -7.95513511e-01 -1.35680825e-01 3.40242028e-01
-1.26886040e-01 3.20789456e-01 1.03156400e+00 -1.06037199e+00
-6.84727311e-01 -8.08204830e-01 1.14214897e+00 -4.70063657e-01
1.01423991e+00 3.20525676e-01 -4.64026004e-01 5.62943637e-01
-1.92452490e-01 -5.98809183e-01 1.28850853e+00 4.32236731e-01
3.96742612e-01 -1.02404855e-01 -8.26560736e-01 3.04787248e-01
2.88293362e-01 -2.21168101e-01 -6.45429373e-01 3.22449952e-01
1.65380239e-01 -3.23215336e-01 -1.36081898e+00 1.95070684e-01
8.91431987e-01 -1.16448164e+00 9.82633650e-01 -7.15019047e-01
8.66600394e-01 -4.88063740e-03 1.05996817e-01 -1.13176572e+00
-8.54119584e-02 -2.84074545e-02 6.14030659e-01 1.18548751e+00
7.10186660e-01 -7.35267162e-01 7.96210289e-01 6.34282172e-01
1.34168193e-01 -7.33112097e-01 -9.35784519e-01 -7.20658839e-01
2.93323368e-01 -9.80463207e-01 4.45178360e-01 1.05377543e+00
1.52963102e-01 -1.98511779e-02 -5.00313461e-01 -3.50123942e-01
2.57388890e-01 8.49991962e-02 1.02637458e+00 -1.70434618e+00
1.96887493e-01 -4.66096908e-01 -1.05617499e+00 -1.43892199e-01
-2.91573107e-02 -9.85111833e-01 -5.40421188e-01 -1.66758847e+00
6.90328851e-02 -5.87090433e-01 -2.64288664e-01 1.25582337e-01
-9.54385400e-02 7.11570680e-01 3.94156635e-01 3.67991358e-01
-1.44163236e-01 -1.04623996e-01 1.18095958e+00 3.19297701e-01
-3.66565526e-01 5.00543952e-01 -7.61419356e-01 7.63756394e-01
8.29734147e-01 -7.19083726e-01 1.08975850e-01 4.45217401e-01
9.90157783e-01 2.54116237e-01 3.98134112e-01 -9.42300379e-01
1.90112695e-01 -3.37079167e-01 2.24476621e-01 -5.40437102e-01
2.26939827e-01 -5.12178540e-01 5.25138140e-01 7.89145589e-01
-1.69260815e-01 1.76109642e-01 3.84454906e-01 5.46660841e-01
-6.65041745e-01 -5.21789826e-02 3.24283779e-01 -1.39492750e-01
-5.62457144e-01 -1.91079024e-02 -9.11691427e-01 2.59026047e-02
1.31028152e+00 -7.06796706e-01 -6.19871616e-02 -7.34644532e-01
-1.13278222e+00 1.38827518e-01 2.73708522e-01 4.72307324e-01
2.69805968e-01 -1.22834313e+00 -1.11066198e+00 -1.60912886e-01
6.22026958e-02 -5.79952121e-01 5.94244292e-03 1.41109276e+00
-7.49563456e-01 4.22448933e-01 -4.46120292e-01 -4.35165286e-01
-1.27870059e+00 3.82736713e-01 -2.12599188e-01 -2.74934947e-01
-5.91632605e-01 5.22692680e-01 -3.44350159e-01 -1.35464519e-01
-2.42443949e-01 -1.90287799e-01 -8.71126413e-01 1.05625021e+00
6.27796710e-01 7.09881067e-01 6.37323856e-02 -1.15878940e+00
-4.14763749e-01 2.71285772e-01 2.39126742e-01 -1.24043487e-01
1.80813897e+00 -1.19610481e-01 -1.82385251e-01 1.27819300e+00
7.26792395e-01 3.97824615e-01 -3.63213599e-01 2.69747395e-02
3.26544702e-01 -6.39201343e-01 1.31954983e-01 -4.69156653e-01
-9.34803963e-01 4.16844159e-01 3.11244696e-01 8.47528934e-01
6.70106113e-01 -9.18380693e-02 5.56088448e-01 -3.58324468e-01
4.32226181e-01 -1.16801703e+00 -3.60021979e-01 2.79748917e-01
7.67890632e-01 -1.24157894e+00 1.62187234e-01 -2.58532107e-01
-7.48921633e-01 1.06402111e+00 -5.60460566e-03 -4.64920461e-01
1.40578103e+00 4.99183647e-02 -8.97911862e-02 -3.73516709e-01
-7.30095446e-01 -4.57900077e-01 3.88302594e-01 4.35409665e-01
7.51581252e-01 3.85537267e-01 -1.08077025e+00 9.37398195e-01
-9.07436728e-01 4.78978395e-01 7.42308199e-01 9.19092953e-01
-6.75318837e-01 -8.51446092e-01 -6.64815068e-01 1.04777491e+00
-1.14418209e+00 5.96983619e-02 -2.18855709e-01 1.34547532e+00
2.92459428e-01 1.11278367e+00 1.53782815e-01 -6.52937710e-01
3.59644771e-01 1.06960669e-01 -2.10414335e-01 -6.07157886e-01
-1.26661074e+00 -1.47432372e-01 5.04949808e-01 -4.49344933e-01
-9.88376141e-01 -9.46825087e-01 -8.34614635e-01 -9.52925920e-01
-3.22135806e-01 3.55043828e-01 6.52945161e-01 1.00709653e+00
-2.50842012e-02 2.87104189e-01 4.66169000e-01 -7.18218625e-01
1.38663143e-01 -9.94012892e-01 -8.87959540e-01 3.10508430e-01
8.14548433e-02 -9.28439379e-01 -3.37860167e-01 -1.64345101e-01] | [8.312126159667969, 9.931244850158691] |
27f1fd52-d812-4e27-b269-cd501d7c0957 | all-you-need-in-sign-language-production | 2201.01609 | null | https://arxiv.org/abs/2201.01609v2 | https://arxiv.org/pdf/2201.01609v2.pdf | All You Need In Sign Language Production | Sign Language is the dominant form of communication language used in the deaf and hearing-impaired community. To make an easy and mutual communication between the hearing-impaired and the hearing communities, building a robust system capable of translating the spoken language into sign language and vice versa is fundamental. To this end, sign language recognition and production are two necessary parts for making such a two-way system. Sign language recognition and production need to cope with some critical challenges. In this survey, we review recent advances in Sign Language Production (SLP) and related areas using deep learning. To have more realistic perspectives to sign language, we present an introduction to the Deaf culture, Deaf centers, psychological perspective of sign language, the main differences between spoken language and sign language. Furthermore, we present the fundamental components of a bi-directional sign language translation system, discussing the main challenges in this area. Also, the backbone architectures and methods in SLP are briefly introduced and the proposed taxonomy on SLP is presented. Finally, a general framework for SLP and performance evaluation, and also a discussion on the recent developments, advantages, and limitations in SLP, commenting on possible lines for future research are presented. | ['Mohammad Sabokrou', 'Vassilis Athitsos', 'Sergio Escalera', 'Kourosh Kiani', 'Razieh Rastgoo'] | 2022-01-05 | null | null | null | null | ['sign-language-recognition', 'sign-language-translation', 'sign-language-production'] | ['computer-vision', 'computer-vision', 'natural-language-processing'] | [-2.85318419e-02 -8.43775049e-02 -1.64759889e-01 -3.08552057e-01
-6.69426203e-01 -4.90898818e-01 3.44051689e-01 -8.80136371e-01
-3.70738000e-01 6.51945472e-01 7.64612496e-01 -1.89583346e-01
-5.13770664e-03 -5.46733856e-01 -3.20596069e-01 -9.70758438e-01
-3.55717749e-03 1.72624514e-01 -4.17641401e-02 -4.86272454e-01
2.32238382e-01 7.08422244e-01 -1.93353224e+00 3.73304158e-01
7.41053820e-01 5.89676797e-01 4.75525230e-01 8.23188663e-01
-5.08174241e-01 7.66253054e-01 -4.76593763e-01 -4.05071899e-02
7.81790167e-02 -7.60914087e-01 -8.24500144e-01 1.05380699e-01
5.71535647e-01 -7.80169308e-01 -1.70652732e-01 7.22834527e-01
1.13425601e+00 -2.51675993e-01 6.99543417e-01 -1.23190737e+00
-7.67398238e-01 4.05313492e-01 2.94664502e-01 -5.28333306e-01
5.46387970e-01 1.96134731e-01 7.83085108e-01 -1.12930954e+00
7.66744971e-01 1.27323079e+00 3.31588626e-01 1.00534689e+00
-6.08472168e-01 -7.34936416e-01 4.83711421e-01 2.35950232e-01
-1.09870017e+00 -6.32127821e-01 5.27543902e-01 -5.29585123e-01
1.03458798e+00 1.63543671e-01 1.12886691e+00 9.80571747e-01
-2.40439728e-01 1.35175204e+00 1.30332923e+00 -9.24942911e-01
-3.32541652e-02 -1.83747426e-01 2.67677993e-01 4.92696643e-01
1.20405100e-01 2.27170661e-01 -9.86312747e-01 3.06479454e-01
7.03495920e-01 -6.18375480e-01 -5.28178155e-01 -3.51886362e-01
-1.18340158e+00 3.20762813e-01 1.50920257e-01 7.51389146e-01
-2.59180158e-01 1.33316472e-01 2.87129223e-01 7.16827929e-01
-5.01489699e-01 -2.00128276e-02 -3.10764730e-01 -4.13405240e-01
-5.66163242e-01 8.55151787e-02 9.34337616e-01 9.80370164e-01
-2.65569568e-01 3.19083035e-01 -2.80111909e-01 1.20223701e+00
9.66129363e-01 9.59458530e-01 5.83793044e-01 -6.07891440e-01
2.50402033e-01 3.61628920e-01 -1.33281723e-01 -2.05391571e-01
-3.57960433e-01 3.79801132e-02 -6.37127638e-01 9.95905221e-01
4.57481235e-01 -1.10911928e-01 -1.48762870e+00 1.46645224e+00
-2.49495670e-01 -3.34561735e-01 1.88499644e-01 9.72827911e-01
1.25744820e+00 2.55163103e-01 1.05926245e-01 -2.28038698e-01
1.26666117e+00 -9.06139195e-01 -9.48324442e-01 -1.19030267e-01
4.16595578e-01 -9.73730862e-01 1.07321656e+00 3.53961110e-01
-1.08886921e+00 -2.26130828e-01 -7.36362696e-01 -3.66156012e-01
-3.72653753e-01 2.42504150e-01 5.22682369e-01 7.16758370e-01
-1.37425804e+00 -4.97731529e-02 -7.36132920e-01 -1.00206125e+00
2.49084249e-01 3.86331022e-01 -4.67240751e-01 -1.25685081e-01
-8.74605536e-01 1.22490859e+00 1.01439461e-01 2.95322925e-01
-1.69441357e-01 -2.44759247e-01 -6.34536386e-01 -4.87437695e-01
-5.19383073e-01 -6.79804623e-01 1.78905511e+00 -7.31974185e-01
-2.15396118e+00 1.31314015e+00 -3.91901344e-01 1.54223055e-01
8.49408746e-01 -2.42599949e-01 -5.44901907e-01 -1.44475773e-01
-2.74625570e-01 6.29713058e-01 4.89979118e-01 -1.33414900e+00
-1.08392072e+00 -1.54333502e-01 -4.17000711e-01 2.74862915e-01
2.65486062e-01 6.49998367e-01 -3.66185039e-01 -4.87686306e-01
6.12869084e-01 -6.92237616e-01 3.83164912e-01 7.63899744e-01
1.46777334e-03 -3.25918972e-01 6.41478598e-01 -9.24580634e-01
1.08942640e+00 -2.18053150e+00 1.48355111e-01 1.62508652e-01
8.23373944e-02 6.39713526e-01 -2.81569481e-01 8.85708690e-01
2.08186075e-01 -3.67236972e-01 -3.55712384e-01 -1.63936272e-01
2.57955730e-01 6.57788336e-01 -4.53565776e-01 2.42321834e-01
-1.15158759e-01 1.00449455e+00 -9.20472264e-01 -3.18261892e-01
2.75823951e-01 7.02866852e-01 -2.13344231e-01 1.71889618e-01
1.37833774e-01 6.92063987e-01 -2.72257887e-02 1.21946001e+00
6.48664713e-01 3.23778808e-01 1.68297350e-01 2.06743747e-01
-6.70561016e-01 4.53763008e-01 -1.15697801e+00 1.25018895e+00
-6.57274604e-01 9.29057419e-01 5.58543921e-01 -6.06357932e-01
9.33218658e-01 7.02513039e-01 6.51215091e-02 -7.64015019e-01
1.79272234e-01 1.28763819e+00 2.45895356e-01 -1.02411473e+00
-1.63674593e-01 -4.32754695e-01 3.40140671e-01 5.28862655e-01
7.81895965e-02 -4.52652901e-01 3.16980451e-01 -4.20336843e-01
4.81135190e-01 3.23825553e-02 4.34532195e-01 2.19531149e-01
7.42535233e-01 -5.04544437e-01 2.72602588e-01 4.91927147e-01
-5.14324367e-01 5.77985942e-01 -1.86636823e-03 -1.88220888e-01
-5.02497613e-01 -1.24707842e+00 -1.84242010e-01 9.49703336e-01
-2.37535343e-01 2.48210892e-01 -3.75191957e-01 -1.99525684e-01
6.59870589e-03 4.88156408e-01 6.83514327e-02 3.51359636e-01
-8.39733124e-01 -2.57054538e-01 7.09509075e-01 7.57922232e-01
8.98064017e-01 -1.85703325e+00 -4.29767430e-01 9.53275189e-02
-3.71180743e-01 -8.86957526e-01 -1.43750891e-01 -3.54465276e-01
-5.84452569e-01 -1.04042554e+00 -1.40525973e+00 -2.06279445e+00
6.55405581e-01 1.85510397e-01 4.48503941e-01 2.32913911e-01
7.93412253e-02 5.43895721e-01 -6.10997319e-01 -5.17532051e-01
-7.94558764e-01 -4.30430084e-01 2.62700915e-01 -3.13569337e-01
5.78021646e-01 -7.57477939e-01 -2.02380612e-01 1.36554288e-02
-6.08622611e-01 2.28853449e-01 9.41019714e-01 8.94113183e-01
1.62326500e-01 -7.63968527e-01 2.67416775e-01 3.16103429e-01
8.25390756e-01 3.96166533e-01 -3.33193719e-01 4.44580853e-01
-2.91453302e-01 -1.79475714e-02 -4.92674038e-02 -3.25281292e-01
-8.53487253e-01 -2.68214270e-02 -6.32987618e-01 7.04122305e-01
-2.37137794e-01 2.96168953e-01 -4.01751876e-01 -4.78723139e-01
4.07752931e-01 7.93235540e-01 3.37951660e-01 -6.80719137e-01
4.81563240e-01 1.42099655e+00 5.67467928e-01 -2.02987775e-01
6.85758770e-01 4.19782460e-01 -2.96105385e-01 -1.20083487e+00
-5.85384220e-02 -4.59552377e-01 -9.73766625e-01 -5.51892459e-01
5.27749658e-01 -5.37444890e-01 -7.45271325e-01 1.62229931e+00
-1.39299285e+00 -4.85255122e-01 -3.07336956e-01 9.41415131e-01
-8.59032214e-01 2.94866711e-01 -5.05300522e-01 -9.81221616e-01
-3.32579285e-01 -1.17647040e+00 9.42928433e-01 1.81817621e-01
-2.76497006e-01 -5.49947619e-01 3.15093607e-01 2.75520056e-01
5.96842945e-01 -8.76897797e-02 8.61420453e-01 -4.39615287e-02
-5.96478879e-01 -2.31107548e-01 -3.97916466e-01 7.96476722e-01
3.43443751e-01 -3.85843776e-02 -9.53071952e-01 -1.21880963e-01
-4.82343167e-01 -4.01205868e-01 6.56722963e-01 4.77952033e-01
1.61290392e-01 -1.31778538e-01 -1.16697073e-01 6.07440054e-01
9.75627661e-01 5.47658086e-01 6.89963937e-01 1.28747925e-01
2.85097480e-01 8.61303627e-01 1.48254678e-01 -3.31737734e-02
5.20813048e-01 6.01045012e-01 -1.81893572e-01 -7.24922344e-02
-1.09795177e+00 -4.66096252e-01 6.77950740e-01 1.55192482e+00
-4.91192520e-01 -4.29277634e-03 -8.77428412e-01 6.18884146e-01
-1.51730454e+00 -9.55859184e-01 -1.80494130e-01 2.00161862e+00
7.93258131e-01 -4.42068994e-01 9.60340798e-02 7.12851286e-01
4.94827151e-01 -1.77267849e-01 -2.49930725e-01 -4.78102237e-01
-6.02661490e-01 4.36692089e-01 1.01001292e-01 9.71353292e-01
-7.70040572e-01 1.14214170e+00 7.57039738e+00 4.59399372e-02
-1.67940474e+00 -2.59132743e-01 -5.39414346e-01 1.58959135e-01
6.02885671e-02 -3.06916326e-01 -7.16182530e-01 2.21274346e-01
1.91682339e-01 1.29980799e-02 4.29787755e-01 5.01959443e-01
5.42126715e-01 3.02357972e-02 -9.74434137e-01 1.32299221e+00
2.65129387e-01 -9.57645059e-01 2.45693982e-01 1.00142357e-03
4.92045462e-01 4.33194846e-01 -1.40423551e-01 2.86527008e-01
2.15686098e-01 -8.57360780e-01 9.03829873e-01 4.96541440e-01
1.12733972e+00 1.85086828e-04 6.27754807e-01 8.51175040e-02
-1.13757193e+00 -1.54373735e-01 3.68107140e-01 -4.70444709e-01
7.39169657e-01 -1.42166261e-02 -5.40098488e-01 6.47970736e-02
5.02590001e-01 4.07669961e-01 8.37380886e-02 1.62742460e+00
-1.00779498e+00 4.27092165e-01 -3.27167630e-01 -4.50779736e-01
-3.86133301e-03 -3.49885263e-02 6.15786314e-01 1.35389280e+00
6.20370984e-01 1.61942899e-01 -1.96873799e-01 3.75170022e-01
2.32623130e-01 5.22497833e-01 -5.10560274e-01 -1.59587324e-01
2.33541653e-01 4.09452051e-01 -2.29574487e-01 -1.89413831e-01
-7.13161230e-01 1.08409011e+00 -2.08724335e-01 5.84359586e-01
-5.18845953e-02 -5.48363268e-01 1.07439888e+00 3.49993296e-02
-1.02643326e-01 -5.35056829e-01 -3.85760307e-01 -9.94322479e-01
5.41831851e-01 -9.33341622e-01 -7.36546740e-02 -8.58954012e-01
-1.09940612e+00 2.95673370e-01 -2.04208881e-01 -1.64381790e+00
-3.54525000e-01 -1.30585015e+00 -3.73045743e-01 9.70643580e-01
-1.83269000e+00 -1.73889291e+00 -4.58074421e-01 4.39805955e-01
4.91325557e-01 -2.29140520e-01 1.19645846e+00 4.06316102e-01
4.44405340e-02 6.18829727e-01 9.99194905e-02 5.05820870e-01
6.24125838e-01 -7.92582810e-01 2.42808402e-01 8.12994897e-01
5.22632375e-02 3.90586495e-01 3.92002374e-01 -5.00959277e-01
-1.03228354e+00 -3.03181529e-01 1.85593736e+00 3.74054303e-03
4.48901325e-01 -1.27146199e-01 -4.29413468e-01 5.33059359e-01
1.85551390e-01 -4.37982947e-01 6.47727251e-01 -3.44071060e-01
-4.10041302e-01 1.50005683e-01 -1.13543868e+00 1.01260638e+00
1.72103608e+00 -6.76362634e-01 -8.44286919e-01 4.61920708e-01
2.52083033e-01 -3.42376351e-01 -2.07494497e-01 1.37232065e-01
1.40412843e+00 -7.50894308e-01 5.92974067e-01 -4.44519490e-01
9.71036125e-03 -5.24682641e-01 -3.08536083e-01 -1.11389863e+00
-1.44065678e-01 -7.19400942e-01 9.56980363e-02 8.62209439e-01
1.84395760e-01 -1.09337676e+00 3.75355691e-01 5.32024205e-01
-3.25477272e-01 -3.24295819e-01 -1.12395656e+00 -1.00887895e+00
3.52819264e-01 -7.12804973e-01 3.19956422e-01 4.83719498e-01
4.58354086e-01 -9.44689140e-02 -2.75122255e-01 -2.46721841e-02
3.03254068e-01 -5.67660725e-04 8.60415816e-01 -1.21409500e+00
-1.49186822e-02 -1.09671593e+00 -7.13878870e-01 -1.32727981e+00
-1.23038523e-01 -1.04931724e+00 1.31294757e-01 -2.34145308e+00
-3.35451305e-01 1.95176944e-01 5.04113995e-02 6.01445258e-01
6.05252564e-01 5.35877459e-02 4.71894145e-01 2.38560289e-01
4.81321335e-01 3.46610993e-01 1.67822599e+00 -1.19124249e-01
-5.14213860e-01 3.32870424e-01 -5.41751802e-01 7.46465325e-01
8.64222348e-01 2.19031274e-01 -9.49167758e-02 -6.95189774e-01
-1.39943510e-01 -4.59798187e-01 2.43087679e-01 -8.54070246e-01
3.52181554e-01 -2.08314389e-01 -3.54453295e-01 -6.96310163e-01
2.14963526e-01 -5.90466440e-01 -4.17173505e-01 8.68036389e-01
-5.91025986e-02 -4.21956569e-01 -1.08547293e-01 -2.93038815e-01
-6.12736106e-01 -2.32485421e-02 1.01607144e+00 -9.64459702e-02
-1.20471168e+00 -1.82880580e-01 -9.96355712e-01 -4.00740594e-01
8.16098392e-01 -5.87033987e-01 -4.16895747e-03 -6.16195619e-01
-8.96235466e-01 2.85119116e-01 2.66697966e-02 6.68328583e-01
8.00075829e-01 -1.42753875e+00 -9.19189334e-01 7.51383364e-01
4.20926064e-01 -3.66659939e-01 3.06160748e-02 9.19717968e-01
-1.05141234e+00 7.91080177e-01 -5.36098838e-01 -1.08890660e-01
-1.64708483e+00 -3.00746739e-01 5.59780538e-01 3.27927589e-01
-7.53563821e-01 1.11583114e+00 -2.00479001e-01 -7.91752756e-01
7.72339225e-01 -8.07047904e-01 -4.06291366e-01 -7.82142133e-02
8.08751822e-01 2.39361763e-01 2.47877138e-03 -9.48917508e-01
-5.53600252e-01 1.06654251e+00 3.03379118e-01 -6.01840854e-01
1.03016782e+00 -1.71350002e-01 -4.22617286e-01 3.75075608e-01
8.65686059e-01 5.65972738e-02 -5.68184853e-01 -2.48378247e-01
-4.82581854e-02 -3.06620747e-01 -2.00339660e-01 -1.31766939e+00
-7.90940583e-01 1.04572701e+00 9.43749964e-01 -5.14797330e-01
1.24399638e+00 1.15309067e-01 8.81409824e-01 5.10249376e-01
7.27037966e-01 -1.42404747e+00 -2.45838270e-01 8.59359741e-01
1.81237948e+00 -1.02695513e+00 -6.98928058e-01 -3.47136974e-01
-4.08504009e-01 1.26535726e+00 3.00382048e-01 1.87766775e-01
9.75945652e-01 4.01248246e-01 1.04091907e+00 1.66712388e-01
-3.63698266e-02 -6.86909854e-01 2.72909164e-01 1.28948998e+00
9.20056880e-01 2.80000597e-01 -1.01780415e+00 1.85130522e-01
-6.82298839e-01 4.83704358e-01 2.22834200e-01 1.26057804e+00
-6.49784088e-01 -1.63561654e+00 -5.82493186e-01 7.50121921e-02
3.29823434e-01 8.89745727e-02 -6.99982762e-01 7.73904681e-01
3.57006818e-01 9.47639704e-01 -2.93322533e-01 -1.93997130e-01
7.78890312e-01 5.65152764e-01 7.29477644e-01 -3.39762241e-01
-4.15774770e-02 -1.27942294e-01 1.98829457e-01 -2.70447165e-01
-5.52330911e-01 -7.69685090e-01 -1.50045180e+00 -8.10441524e-02
1.70733884e-01 -6.60660505e-01 9.04416621e-01 9.99166369e-01
-4.68434095e-02 1.60263374e-01 9.80368722e-03 -6.89715803e-01
-4.19762939e-01 -1.11023307e+00 -7.67067075e-01 -6.45971745e-02
6.29097342e-01 -4.31949794e-01 -4.42160547e-01 6.70391023e-02] | [9.088021278381348, -6.396602153778076] |
5b62abaa-5cba-4a6d-a612-e458db685e5f | my-way-of-telling-a-story-persona-based-1 | null | null | https://aclanthology.org/W19-3402 | https://aclanthology.org/W19-3402.pdf | ``My Way of Telling a Story'': Persona based Grounded Story Generation | Visual storytelling is the task of generating stories based on a sequence of images. Inspired by the recent works in neural generation focusing on controlling the form of text, this paper explores the idea of generating these stories in different personas. However, one of the main challenges of performing this task is the lack of a dataset of visual stories in different personas. Having said that, there are independent datasets for both visual storytelling and annotated sentences for various persona. In this paper we describe an approach to overcome this by getting labelled persona data from a different task and leveraging those annotations to perform persona based story generation. We inspect various ways of incorporating personality in both the encoder and the decoder representations to steer the generation in the target direction. To this end, we propose five models which are incremental extensions to the baseline model to perform the task at hand. In our experiments we use five different personas to guide the generation process. We find that the models based on our hypotheses perform better at capturing words while generating stories in the target persona. | ['Alan W. black', 'Ch', 'Shrimai Prabhumoye', 'Ruslan Salakhutdinov', 'Khyathi u'] | 2019-08-01 | null | null | null | ws-2019-8 | ['visual-storytelling'] | ['natural-language-processing'] | [ 2.81071782e-01 5.23934066e-01 2.70480335e-01 -5.01848936e-01
-5.94605744e-01 -5.43815911e-01 1.23037577e+00 -2.71173716e-01
1.06303710e-02 7.34109044e-01 9.62773085e-01 8.21076706e-02
4.40427154e-01 -7.97850311e-01 -6.85039818e-01 -3.81282240e-01
5.54488897e-01 7.40644574e-01 6.68406412e-02 -3.86208177e-01
4.28361535e-01 9.83892903e-02 -1.41323376e+00 1.01223660e+00
5.07258892e-01 3.27547908e-01 3.71006638e-01 9.63875473e-01
-1.78229257e-01 1.15780401e+00 -9.99248028e-01 -6.64062262e-01
4.43062223e-02 -1.07948589e+00 -8.70391011e-01 5.33982337e-01
5.41427076e-01 -4.24596578e-01 -2.74480909e-01 5.13453960e-01
7.08008707e-01 8.76348466e-02 1.07100391e+00 -1.28015041e+00
-9.42791224e-01 1.07208169e+00 -4.83024985e-01 -2.18430966e-01
8.05516005e-01 2.51998752e-01 6.88592196e-01 -9.19435501e-01
9.76463616e-01 1.52656543e+00 4.11628932e-01 1.12790954e+00
-1.19505024e+00 -3.35877746e-01 1.40592352e-01 -4.13043983e-02
-1.18965518e+00 -6.03377283e-01 7.53177166e-01 -6.99932218e-01
7.65565217e-01 8.37101489e-02 9.11763072e-01 1.72727036e+00
-1.95226297e-01 1.03324485e+00 1.03900802e+00 -7.07682848e-01
1.05323322e-01 3.58853370e-01 -2.88144946e-01 4.06043261e-01
-2.55222227e-02 2.16191206e-02 -8.44100952e-01 1.67964529e-02
9.00069654e-01 -4.12467569e-01 -1.10072032e-01 -3.58369887e-01
-1.47501278e+00 1.03741324e+00 1.84086680e-01 1.87406138e-01
-3.43013257e-01 3.24556321e-01 3.38251829e-01 5.39432792e-03
3.79096597e-01 7.89804459e-01 3.33866179e-01 -6.07102439e-02
-1.16359782e+00 1.02394509e+00 7.54347265e-01 1.18221962e+00
3.18748057e-01 7.63436481e-02 -1.07081091e+00 7.08104014e-01
2.41850361e-01 1.68328673e-01 4.28080320e-01 -6.66087210e-01
7.01145291e-01 4.74628180e-01 4.09501195e-01 -7.36303568e-01
-5.44485822e-02 8.67782161e-02 -5.05537391e-01 2.31259733e-01
6.06507719e-01 -3.09706956e-01 -1.25893736e+00 1.63778472e+00
5.42521626e-02 -2.15495855e-01 1.39394641e-01 8.73610318e-01
9.05479014e-01 9.47195530e-01 8.05929676e-02 1.81468382e-01
1.50724411e+00 -1.10569870e+00 -7.17789412e-01 -4.30117846e-01
3.27615291e-01 -8.07468891e-01 1.15699804e+00 1.89864442e-01
-1.35421884e+00 -7.49970555e-01 -1.09350216e+00 -3.75610620e-01
-2.80143410e-01 2.17340603e-01 3.11309665e-01 4.12750959e-01
-1.14184630e+00 3.14440280e-01 -3.08009505e-01 -7.28004336e-01
3.93698066e-01 -3.46323013e-01 -1.10432036e-01 -7.40120336e-02
-1.14379621e+00 1.05408025e+00 5.35446227e-01 -1.76541775e-01
-1.18871057e+00 -2.20843062e-01 -9.10221398e-01 -2.55863637e-01
1.81098267e-01 -1.17348802e+00 1.47722733e+00 -1.09914303e+00
-1.24708986e+00 9.64994729e-01 -2.49321371e-01 -5.20901442e-01
9.68980312e-01 -1.35599837e-01 1.11412823e-01 -3.19620669e-02
3.48325521e-01 1.28480375e+00 8.99990201e-01 -1.55705214e+00
-4.36038405e-01 -1.97380811e-01 1.92386031e-01 4.90452975e-01
-1.18005700e-01 1.33519202e-01 -3.97427976e-01 -9.29887116e-01
-4.96767998e-01 -8.22654068e-01 -2.96584159e-01 -2.91700125e-01
-7.73713291e-01 -2.72834986e-01 5.99512875e-01 -7.13368237e-01
9.49125290e-01 -1.75644350e+00 5.08469641e-01 -1.06459945e-01
1.73738405e-01 -5.60942106e-02 -1.40487939e-01 8.83091271e-01
5.11915237e-02 1.89379022e-01 -2.03628447e-02 -6.86356664e-01
-7.27928989e-03 -1.79361165e-01 -4.71714944e-01 -1.61415204e-01
3.33713740e-01 9.63269949e-01 -8.78023446e-01 -7.08830118e-01
7.88319949e-03 6.56347930e-01 -3.72681290e-01 5.17681956e-01
-5.68331659e-01 5.80130756e-01 -4.05964226e-01 1.63601428e-01
7.41517544e-02 -6.33569285e-02 2.50407457e-02 8.92531052e-02
-9.56552699e-02 2.93252915e-01 -9.56738174e-01 1.79848409e+00
-3.04003775e-01 9.08073843e-01 -4.77142543e-01 -4.76180345e-01
1.01497710e+00 6.57168627e-01 -1.27442822e-01 -2.72207141e-01
3.82235944e-02 -1.61455899e-01 -1.63198739e-01 -6.73759222e-01
8.46146345e-01 -4.74985480e-01 -3.44804645e-01 7.65197873e-01
-1.59002542e-02 -5.01238227e-01 5.52356958e-01 4.51474994e-01
7.71557927e-01 5.28362691e-01 2.99240261e-01 9.73775908e-02
1.66055039e-01 2.58007288e-01 -1.37288168e-01 1.00998569e+00
9.02236998e-02 1.20044684e+00 5.21831930e-01 -4.32069600e-01
-1.56854141e+00 -8.64458978e-01 4.06870425e-01 8.94222558e-01
-2.49723375e-01 -6.32221520e-01 -9.84676778e-01 -4.83620882e-01
-4.07036811e-01 1.23138177e+00 -8.44940066e-01 4.59773876e-02
-6.52965069e-01 -3.28832865e-01 5.63825548e-01 6.04057193e-01
4.19617593e-01 -1.48107088e+00 -9.04925823e-01 1.02883391e-01
-4.65881884e-01 -9.71075296e-01 -4.97008562e-01 -4.77665216e-01
-3.35979015e-01 -5.47146857e-01 -1.26776814e+00 -7.75690556e-01
7.49321699e-01 1.83969676e-01 1.23170161e+00 -1.73485443e-01
-3.94983552e-02 3.30570936e-01 -5.71219921e-01 -9.17164385e-01
-8.53842795e-01 1.70216620e-01 -5.06826162e-01 -1.99613683e-02
1.09179206e-01 -2.59114683e-01 -4.11700249e-01 -7.22642615e-02
-9.75014865e-01 1.06301630e+00 4.24138963e-01 5.70882857e-01
7.32984617e-02 -1.50863960e-01 4.38980073e-01 -9.96228933e-01
1.01612103e+00 -4.39307183e-01 1.82120483e-02 1.79890171e-01
-1.50789514e-01 6.31952435e-02 4.77041662e-01 -4.00380522e-01
-1.27711105e+00 1.76835924e-01 1.46372184e-01 -1.61642015e-01
-2.84701347e-01 1.49477348e-01 -1.20663881e-01 7.84011424e-01
7.00588942e-01 1.48165628e-01 -1.61033705e-01 -1.38329864e-01
7.51834154e-01 5.84867775e-01 3.40113759e-01 -4.23236787e-01
8.68152142e-01 3.92975986e-01 -4.59295899e-01 -5.03066003e-01
-8.65346193e-01 -9.92364716e-03 -4.67560887e-01 -8.33988309e-01
1.23343146e+00 -9.35538471e-01 -1.43521219e-01 4.55930650e-01
-1.56893635e+00 -4.86982971e-01 -4.04402614e-01 -3.56846936e-02
-1.01945090e+00 -1.42900363e-01 -3.07872891e-01 -9.09179270e-01
-1.88625470e-01 -1.00916111e+00 1.28317058e+00 2.98514038e-01
-8.18832517e-01 -7.35991180e-01 2.22436622e-01 5.52876234e-01
2.63528645e-01 5.62946022e-01 7.10455000e-01 -3.85255396e-01
-4.98349637e-01 -1.68247923e-01 -1.11466847e-01 -1.40715227e-01
-1.51756005e-02 -1.18075229e-01 -9.66807485e-01 -3.90097761e-04
-1.13901459e-01 -6.23008966e-01 8.70717645e-01 2.64515281e-01
7.94514894e-01 -3.71634871e-01 -3.12032074e-01 1.74147606e-01
1.08066118e+00 2.83579439e-01 9.57729697e-01 2.74663478e-01
9.99285221e-01 1.07665527e+00 6.43926382e-01 3.81672591e-01
7.51774907e-01 8.63020718e-01 8.32743570e-02 -1.01120040e-01
-4.79935259e-01 -9.34363782e-01 5.47091067e-01 2.05419362e-01
-3.58344823e-01 -6.62937284e-01 -8.52957487e-01 9.90984857e-01
-2.04136252e+00 -1.44856894e+00 -1.36885002e-01 1.82260132e+00
8.63557756e-01 -8.38889182e-02 5.73420584e-01 8.91438685e-03
8.28684509e-01 4.68871564e-01 -1.27623975e-01 -6.58517063e-01
-1.14545308e-01 -3.60198021e-01 1.40272364e-01 4.42281157e-01
-8.55421603e-01 1.06402886e+00 6.54500771e+00 4.48035657e-01
-8.68312299e-01 -7.08628744e-02 7.85975337e-01 -4.04255062e-01
-4.43882406e-01 9.05571878e-02 -8.45216274e-01 3.37260425e-01
7.91752160e-01 -2.46544614e-01 3.49262238e-01 7.16518819e-01
6.09998286e-01 3.52304392e-02 -1.25241625e+00 7.78469384e-01
6.97868645e-01 -1.42752731e+00 4.75376099e-01 -1.86633646e-01
9.35690045e-01 -7.60255754e-01 -2.57053394e-02 2.27228761e-01
5.81266165e-01 -1.30279207e+00 1.49849796e+00 7.11317003e-01
6.70085788e-01 -6.87497318e-01 3.47759813e-01 3.15007895e-01
-6.51874304e-01 1.50412172e-01 -1.91526666e-01 -2.25251168e-01
6.77305102e-01 2.49983028e-01 -1.42034733e+00 2.21413359e-01
4.31607574e-01 5.37546217e-01 -6.19605184e-01 7.15831697e-01
-4.81236815e-01 3.23041171e-01 4.47436064e-01 -2.39454865e-01
1.12659752e-01 9.60333496e-02 6.12512529e-01 1.24340844e+00
4.77989972e-01 -1.52963042e-01 1.51429191e-01 1.18357301e+00
8.62109214e-02 1.05506729e-03 -1.02204645e+00 -2.94818372e-01
1.81835011e-01 1.05959308e+00 -7.40340710e-01 -5.34461737e-01
-2.96258986e-01 1.27803373e+00 3.17397535e-01 2.96118796e-01
-8.63502502e-01 -2.29788885e-01 -3.80725078e-02 6.24946296e-01
2.54983068e-01 -1.10145226e-01 -3.38628709e-01 -9.96814728e-01
-1.15785532e-01 -9.59629059e-01 7.40803108e-02 -1.55922139e+00
-1.19686103e+00 6.49751604e-01 4.40780967e-01 -8.95153046e-01
-7.54996717e-01 -2.51217395e-01 -8.48925769e-01 9.08020735e-01
-9.25730824e-01 -1.68337023e+00 -3.97641987e-01 3.50628734e-01
1.11146641e+00 -1.14120908e-01 5.83221436e-01 -2.28191197e-01
-2.42887288e-01 2.17528895e-01 -6.16028666e-01 1.50791854e-01
8.97637963e-01 -1.31760943e+00 8.69770885e-01 9.77914333e-01
3.31416667e-01 4.33927745e-01 1.13828242e+00 -9.16769385e-01
-7.94187903e-01 -9.72409844e-01 1.26897657e+00 -7.16923058e-01
3.47225308e-01 -7.38901913e-01 -4.83645260e-01 8.99878323e-01
7.77730048e-01 -9.70374823e-01 5.36236823e-01 -1.80301383e-01
-2.36726582e-01 5.08100629e-01 -8.93647611e-01 1.10998821e+00
1.16352737e+00 -2.31621534e-01 -6.66767597e-01 3.09003592e-01
6.41093910e-01 -4.58341867e-01 -2.88616896e-01 -1.48077220e-01
5.27507007e-01 -1.04121161e+00 8.17183316e-01 -7.09390879e-01
1.30736291e+00 -4.27170336e-01 2.19477549e-01 -1.52483296e+00
-4.12255645e-01 -5.77017367e-01 6.85025901e-02 1.59454024e+00
4.83938009e-01 -2.03938386e-03 7.52182126e-01 4.93505865e-01
-7.86489099e-02 -2.92717606e-01 -3.38690370e-01 -3.41430664e-01
-2.80720647e-03 -2.70280689e-01 5.66229761e-01 5.71097314e-01
-3.23052146e-02 8.20395172e-01 -9.44167554e-01 -4.25594300e-01
3.39417577e-01 -6.76850497e-04 1.19695568e+00 -8.27437341e-01
-3.78394008e-01 -1.75226182e-01 -2.04029784e-01 -8.18954468e-01
-1.48304448e-01 -8.10403287e-01 3.50481868e-01 -2.11634707e+00
6.95477784e-01 1.45107716e-01 4.57319677e-01 3.63748401e-01
-3.63851905e-01 3.42657804e-01 7.02754200e-01 1.05791695e-01
-4.81662065e-01 4.32534665e-01 1.59872043e+00 -8.77751261e-02
-1.49430349e-01 -1.21415488e-01 -1.16501856e+00 6.70716584e-01
8.62172365e-01 -3.16787779e-01 -7.69118905e-01 -6.63102031e-01
4.02649701e-01 1.09837867e-01 6.66932166e-01 -9.83539581e-01
-4.26442772e-02 -2.43379280e-01 7.51320541e-01 -6.78087473e-01
5.89945912e-01 -1.91968843e-01 2.20949054e-01 9.50337052e-02
-8.73238623e-01 2.14768678e-01 -7.27787390e-02 4.14243191e-01
-5.34480959e-02 -2.95137823e-01 6.19284213e-01 -6.11840844e-01
-4.20481801e-01 -6.50985315e-02 -6.69792056e-01 7.45620057e-02
1.10070586e+00 -5.42821586e-01 -3.43628764e-01 -1.14279628e+00
-6.62037611e-01 1.75517902e-01 7.55770087e-01 7.04526007e-01
7.29775608e-01 -1.56726635e+00 -1.21639788e+00 -1.57012969e-01
3.34410489e-01 3.62894200e-02 1.35784641e-01 1.47534087e-01
-4.68789637e-01 3.48760277e-01 -4.12986875e-01 -2.88652390e-01
-1.23716986e+00 4.61949319e-01 1.76124126e-01 -3.12035531e-01
-5.25056303e-01 8.77317786e-01 4.59633887e-01 3.37535553e-02
-4.70723696e-02 3.03391993e-01 -5.66572547e-01 1.70650765e-01
9.11702096e-01 2.13830456e-01 -5.17538369e-01 -8.38980556e-01
2.36589685e-01 2.28165224e-01 -2.78847277e-01 -8.58771384e-01
1.32452786e+00 -1.41395703e-01 2.68869072e-01 7.64810324e-01
5.88641882e-01 2.64544357e-02 -1.45012152e+00 2.70421535e-01
-8.94227177e-02 -4.26852942e-01 -4.90453452e-01 -1.01031935e+00
-6.61232710e-01 8.59454095e-01 1.61484122e-01 3.72455329e-01
7.96951950e-01 3.40648293e-01 5.89708328e-01 -1.77188694e-01
2.53073573e-01 -1.07190859e+00 4.04732108e-01 3.60504508e-01
1.54566026e+00 -9.77549076e-01 -5.75061031e-02 -2.49029607e-01
-1.31734264e+00 1.01679778e+00 7.83877850e-01 -1.23189658e-01
-2.04572365e-01 -3.30490731e-02 1.57599345e-01 -3.33506078e-01
-8.98933113e-01 -1.84845850e-01 2.76950121e-01 9.01125014e-01
7.57983387e-01 4.33976203e-02 -3.86177599e-01 4.54185665e-01
-6.64630055e-01 4.56439564e-03 8.98286402e-01 7.36977875e-01
-1.86352924e-01 -1.09679365e+00 -6.03747666e-01 2.85633415e-01
-2.52003521e-01 3.80594879e-02 -1.07836509e+00 6.78721130e-01
1.09218724e-01 1.05541515e+00 1.83366276e-02 -1.75061345e-01
3.41111511e-01 2.92879313e-01 7.06597447e-01 -9.70535755e-01
-5.33355236e-01 -8.48173723e-02 5.60284555e-01 -1.85287669e-01
-4.91560698e-01 -9.27217543e-01 -9.17723179e-01 -1.23413481e-01
1.30280674e-01 -1.87435761e-01 4.54671502e-01 8.55722964e-01
1.03440076e-01 5.14358640e-01 3.02625090e-01 -1.18837810e+00
-1.02342792e-01 -1.17624259e+00 -1.83646798e-01 8.21771502e-01
-6.32915795e-02 -4.25241321e-01 3.46356928e-02 5.15939415e-01] | [11.140279769897461, 0.811137318611145] |
d35ce362-9f3b-4672-861a-c0466e7cafbd | backtranslation-in-neural-morphological | null | null | https://aclanthology.org/2021.insights-1.13 | https://aclanthology.org/2021.insights-1.13.pdf | Backtranslation in Neural Morphological Inflection | Backtranslation is a common technique for leveraging unlabeled data in low-resource scenarios in machine translation. The method is directly applicable to morphological inflection generation if unlabeled word forms are available. This paper evaluates the potential of backtranslation for morphological inflection using data from six languages with labeled data drawn from the SIGMORPHON shared task resource and unlabeled data from different sources. Our core finding is that backtranslation can offer modest improvements in low-resource scenarios, but only if the unlabeled data is very clean and has been filtered by the same annotation standards as the labeled data. | ['Mans Hulden', 'Ling Liu'] | null | null | null | null | emnlp-insights-2021-11 | ['morphological-inflection'] | ['natural-language-processing'] | [ 2.47734994e-01 1.02954894e-01 -6.62988007e-01 -5.77162504e-01
-1.23039377e+00 -1.16495216e+00 6.37783349e-01 2.70967990e-01
-8.93055141e-01 1.22188962e+00 6.34779692e-01 -7.32576251e-01
4.78445530e-01 -3.98383975e-01 -5.45943677e-01 -1.31349280e-01
4.70574021e-01 9.29364145e-01 -4.06533569e-01 -6.24403715e-01
6.33160844e-02 1.87429756e-01 -7.66152501e-01 4.66328174e-01
1.34646654e+00 -9.52567067e-03 -2.11784360e-03 2.73838490e-01
-5.11415422e-01 2.53426254e-01 -6.65041685e-01 -8.30571175e-01
6.79045439e-01 -5.01899958e-01 -1.11851013e+00 1.03015333e-01
7.62957692e-01 1.24699265e-01 -3.51349674e-02 1.07210600e+00
7.01567292e-01 3.04063708e-01 5.99736333e-01 -5.32149911e-01
-1.39584970e+00 1.32436335e+00 -2.74576843e-01 6.17050648e-01
2.81430155e-01 1.64265901e-01 9.86194789e-01 -1.57140028e+00
1.07485449e+00 1.43199766e+00 5.87946415e-01 6.08888328e-01
-1.44575322e+00 -4.96969700e-01 8.83847196e-03 1.92712415e-02
-1.17431402e+00 -7.21248448e-01 3.18631679e-01 -7.90008605e-02
1.41020668e+00 2.71851599e-01 2.46046826e-01 1.15223360e+00
-8.77364166e-03 5.95770478e-01 1.44755197e+00 -1.03786886e+00
-5.95120154e-02 2.36489862e-01 2.36291304e-01 4.73612636e-01
4.17096406e-01 1.19502194e-01 -6.06675744e-01 -1.10687904e-01
4.59768951e-01 -5.20528495e-01 -7.12142214e-02 3.73592347e-01
-1.60167754e+00 8.55373621e-01 1.37924999e-01 4.33992505e-01
-2.08796769e-01 -2.99699247e-01 5.26494801e-01 8.49411070e-01
8.35337102e-01 1.14353788e+00 -9.66373622e-01 -1.31394500e-02
-9.65620756e-01 1.83578044e-01 6.96703792e-01 1.30789006e+00
8.87890756e-01 4.80706930e-01 -3.27180058e-01 1.05637729e+00
-1.16956621e-01 8.97957444e-01 1.02620113e+00 -6.71759963e-01
9.49736536e-01 3.88793796e-01 2.43678242e-01 -1.05198182e-01
-8.46957341e-02 -3.61515760e-01 -4.30257134e-02 -1.88147485e-01
4.99244899e-01 -7.97559202e-01 -1.45016289e+00 1.89424133e+00
2.39875600e-01 -6.82451308e-01 3.57151926e-01 7.18222141e-01
7.87349939e-01 4.47268426e-01 1.48241267e-01 -3.81005943e-01
1.22936964e+00 -1.03895259e+00 -9.69408274e-01 -6.23466730e-01
9.13803041e-01 -1.33901238e+00 1.55855453e+00 2.43083552e-01
-1.06652272e+00 -6.32147193e-01 -9.91313398e-01 -5.79925299e-01
-6.44533813e-01 4.91188131e-02 8.07589948e-01 8.94580960e-01
-9.91435945e-01 3.09992850e-01 -5.85454822e-01 -6.40640438e-01
-8.44759867e-02 1.24942049e-01 -3.84292096e-01 -2.73565203e-01
-1.23870444e+00 1.33162439e+00 5.98286152e-01 -9.16968659e-02
-5.05203366e-01 -6.55217946e-01 -7.84500778e-01 -5.41779280e-01
2.41403595e-01 -5.36065996e-01 1.67486596e+00 -1.27342319e+00
-1.18174195e+00 8.36141467e-01 -3.79546732e-01 -3.44669014e-01
4.26270306e-01 -2.66945899e-01 -7.17373192e-01 -3.70294631e-01
3.84773463e-01 7.67345011e-01 6.10180318e-01 -1.06894982e+00
-5.63093424e-01 -5.60157776e-01 -3.69003445e-01 5.79470336e-01
-4.38111335e-01 4.09693241e-01 1.94691289e-02 -1.18795383e+00
3.89831178e-02 -1.02530921e+00 -3.06094140e-01 -7.98506916e-01
-3.34344864e-01 -1.80270270e-01 4.82799858e-01 -1.05081844e+00
9.93916214e-01 -1.55954027e+00 1.00701019e-01 -6.86015328e-03
-3.66165161e-01 2.98846960e-01 -3.73293608e-01 4.75345075e-01
-3.33988965e-02 4.99486834e-01 -2.75727808e-01 -2.07332566e-01
-1.19506255e-01 4.35574561e-01 -3.42372298e-01 7.91696459e-02
2.77098119e-01 1.29498935e+00 -1.14033067e+00 -5.26357353e-01
-1.87579513e-01 -1.30993888e-01 -3.12291622e-01 -3.50589380e-02
-3.30182791e-01 4.74832565e-01 8.17855541e-03 7.59109497e-01
3.43871742e-01 3.76148880e-01 3.76943380e-01 1.74861893e-01
-3.28455389e-01 7.22279906e-01 -7.48638332e-01 2.07715011e+00
-7.58964479e-01 4.64179486e-01 -2.25464940e-01 -7.78354704e-02
1.02153897e+00 5.60649633e-01 -1.76929235e-02 -6.71966672e-01
-1.43056735e-01 8.61053586e-01 3.00926447e-01 -2.75629193e-01
9.72440064e-01 -6.93891823e-01 -2.82400668e-01 6.79358125e-01
4.29768890e-01 -5.92045009e-01 5.65814376e-01 1.11551769e-01
8.22053552e-01 1.18929967e-01 2.54393995e-01 -6.14566326e-01
7.17985481e-02 7.52910674e-01 6.89330816e-01 4.17548239e-01
1.03618801e-01 3.75738621e-01 -5.21781504e-01 -3.23017001e-01
-1.33155966e+00 -1.06841922e+00 -1.69253290e-01 1.34587014e+00
-4.04118180e-01 -4.29416537e-01 -6.71749890e-01 -9.93675470e-01
-2.70866841e-01 1.07043886e+00 -4.16278094e-01 1.46480314e-02
-9.08465683e-01 -9.41185534e-01 8.83072555e-01 3.53982806e-01
5.66084795e-02 -1.25411832e+00 3.22573259e-02 4.76011366e-01
-5.41345954e-01 -9.05994713e-01 -7.29434490e-01 4.32675451e-01
-1.07148480e+00 -5.03748000e-01 -6.12035215e-01 -1.06965113e+00
6.17162645e-01 2.69765586e-01 1.48978221e+00 -1.17592730e-01
1.62078962e-01 -3.65973055e-01 -5.24242580e-01 -7.08536208e-01
-7.61565089e-01 4.32508320e-01 2.72730738e-01 -3.78822803e-01
8.07933271e-01 -2.27898031e-01 -3.33708432e-03 -7.06277862e-02
-8.89111221e-01 -2.40716994e-01 4.51415509e-01 7.79460371e-01
6.93437636e-01 -5.30357599e-01 8.99589479e-01 -1.37807667e+00
9.17189360e-01 -5.23317814e-01 -3.86033729e-02 3.52438360e-01
-7.54899561e-01 1.80861533e-01 8.02151442e-01 -4.33213890e-01
-1.54351544e+00 -2.07991116e-02 -3.88008133e-02 -8.43875706e-02
-2.40135774e-01 6.67614162e-01 -1.72840774e-01 2.97257453e-01
1.20832181e+00 -2.19826877e-01 -3.99613887e-01 -9.77831900e-01
9.96711075e-01 7.98735142e-01 5.89283049e-01 -8.53838682e-01
6.75108671e-01 1.47823468e-01 -5.25669038e-01 -6.45472109e-01
-8.90453041e-01 -2.35603750e-01 -9.92879391e-01 3.30671996e-01
5.72403848e-01 -8.68321836e-01 6.72238648e-01 5.86339179e-03
-1.16241848e+00 -3.02855998e-01 -8.98630202e-01 5.80951810e-01
-3.68979514e-01 2.24930748e-01 -8.64535451e-01 -3.25866431e-01
-7.46108294e-01 -9.40089345e-01 6.87613785e-01 1.10489868e-01
-6.18629575e-01 -1.13540542e+00 3.69060516e-01 3.26552898e-01
2.43422896e-01 -1.11617930e-01 1.32320571e+00 -1.10840499e+00
3.46618369e-02 7.40443030e-03 1.40102327e-01 3.29564065e-01
7.23701477e-01 -1.44548833e-01 -6.62319005e-01 -3.47507894e-01
2.44435370e-02 -7.80838013e-01 5.24676263e-01 -4.69448231e-03
2.96958506e-01 -5.21146655e-01 1.71677321e-01 4.91286367e-01
1.17654848e+00 -5.85032366e-02 4.80168648e-02 1.34064510e-01
7.68652976e-01 6.86270177e-01 6.76106036e-01 -2.70550162e-01
3.70525956e-01 4.70788985e-01 -3.78153831e-01 -4.50396657e-01
-7.33534753e-01 -5.70326865e-01 5.18163085e-01 1.55874133e+00
2.34765261e-01 -2.07091704e-01 -1.10063636e+00 9.21041787e-01
-1.62835646e+00 -6.83444500e-01 -4.05695826e-01 2.12423158e+00
1.50248253e+00 -2.35856120e-02 -2.32929643e-02 -2.80001551e-01
8.01623046e-01 -1.46370932e-01 -4.13732857e-01 -1.04300952e+00
-6.11768544e-01 7.18618214e-01 7.89727271e-01 7.08938837e-01
-6.79883659e-01 1.64230764e+00 7.67766714e+00 8.41453552e-01
-8.75269592e-01 6.44242227e-01 3.27541977e-01 -1.11771211e-01
-7.65345156e-01 1.86370090e-01 -8.28418672e-01 2.06003413e-01
1.30507684e+00 -5.58088541e-01 3.30373675e-01 4.47763085e-01
4.05956715e-01 3.47616822e-01 -1.09437203e+00 4.96704340e-01
2.69618243e-01 -1.01363182e+00 4.54310060e-01 -1.22431755e-01
1.08975458e+00 5.17126322e-01 8.21773633e-02 4.59204465e-01
9.05969024e-01 -8.66117954e-01 8.26530039e-01 -2.57132024e-01
1.28850389e+00 -8.98828149e-01 4.70000178e-01 3.42027366e-01
-7.15055287e-01 2.55698323e-01 -5.98263621e-01 1.29451873e-02
4.07774717e-01 3.31794739e-01 -1.46358943e+00 5.55625916e-01
-4.15227981e-03 4.11251903e-01 -9.99672115e-01 8.01754534e-01
-6.19615436e-01 9.83789623e-01 -2.08685637e-01 1.94973022e-01
4.53623295e-01 -3.96881551e-01 5.02125621e-01 1.79131341e+00
2.60820091e-01 -2.16803998e-01 6.12883985e-01 4.47812349e-01
-3.86840910e-01 8.75236988e-01 -7.47265339e-01 -1.17828749e-01
5.34679651e-01 1.17980897e+00 -6.59216821e-01 -7.01690555e-01
-3.64354879e-01 1.08201540e+00 5.29621959e-01 4.48093861e-01
-2.04902202e-01 -3.88461441e-01 4.76095974e-01 -1.00088276e-01
-2.03464895e-01 -4.18297172e-01 -6.89447463e-01 -1.38042569e+00
-1.39948621e-01 -1.48286307e+00 5.48886299e-01 -5.16842425e-01
-1.43003953e+00 8.66814673e-01 -4.06117290e-02 -8.58824670e-01
-4.72968757e-01 -5.59847832e-01 -1.79806337e-01 1.33299732e+00
-1.25568557e+00 -1.43118727e+00 4.46940690e-01 5.45779586e-01
1.31738579e+00 -2.42754355e-01 1.10175467e+00 2.64890969e-01
-4.63581085e-01 7.31578887e-01 1.97420552e-01 1.54957280e-01
1.22969031e+00 -1.51124132e+00 1.23711646e+00 1.54303443e+00
1.01994658e+00 8.40397060e-01 6.32456243e-01 -1.15690458e+00
-1.22117770e+00 -1.26591694e+00 1.56322980e+00 -9.00199175e-01
7.22731709e-01 -4.62060630e-01 -1.01405525e+00 1.03052318e+00
5.99040270e-01 -1.90955147e-01 9.17088151e-01 3.20660651e-01
-4.92325723e-01 6.16653562e-01 -1.14760911e+00 7.57268965e-01
1.22098482e+00 -6.07061267e-01 -1.28008151e+00 8.06653798e-01
9.21459854e-01 -3.42411160e-01 -7.16995895e-01 1.72367454e-01
1.31060882e-02 7.32295439e-02 4.22738492e-01 -1.30653107e+00
2.08240569e-01 -1.76058725e-01 -4.01988715e-01 -2.13987350e+00
-3.59110892e-01 -9.56827402e-01 1.22929044e-01 1.42298687e+00
1.24704957e+00 -3.49839538e-01 4.53295618e-01 4.48543757e-01
-4.48979676e-01 -8.89381394e-02 -8.84485066e-01 -1.08175516e+00
7.16457307e-01 -2.82095432e-01 7.60997534e-01 1.20833600e+00
1.49897113e-01 1.03186846e+00 -5.49065396e-02 -3.50793302e-01
3.57084811e-01 3.72215249e-02 4.10090089e-01 -7.52587259e-01
-2.52466828e-01 4.86156791e-02 2.02618912e-01 -7.02461362e-01
5.13207555e-01 -1.62637937e+00 1.30045772e-01 -1.50368977e+00
8.95556659e-02 -5.65490425e-01 -1.82401761e-01 7.70047188e-01
-5.80635667e-01 5.32528937e-01 1.58591673e-01 3.58041614e-01
-1.19973235e-02 2.42287651e-01 1.15389109e+00 -1.13277838e-01
-3.12525630e-01 -3.53968292e-01 -8.17592025e-01 6.78501964e-01
1.01569843e+00 -5.96245825e-01 -4.63598579e-01 -1.24474418e+00
7.81721920e-02 -3.30222011e-01 -5.92450082e-01 -3.57388437e-01
-1.38441518e-01 -4.37183261e-01 3.51270348e-01 -2.48148188e-01
1.87151194e-01 -4.11239922e-01 -7.30565488e-02 1.67898178e-01
-5.65182447e-01 9.87990260e-01 1.90359414e-01 2.37546787e-01
6.35638386e-02 -4.20774788e-01 6.31728113e-01 -4.92634535e-01
-7.84742177e-01 1.39929786e-01 -5.10979414e-01 6.81950629e-01
4.02509898e-01 -1.16605371e-01 -4.15762007e-01 6.73006922e-02
-5.34632504e-01 -1.67167887e-01 8.74540269e-01 8.64433944e-01
2.20144525e-01 -1.46076369e+00 -1.24204600e+00 2.92152911e-01
3.74374837e-01 -5.04745781e-01 -6.96553290e-01 3.03607821e-01
-2.24672049e-01 2.73473769e-01 -3.58709753e-01 -5.46732023e-02
-8.48721623e-01 8.41682971e-01 6.23527318e-02 -4.10391800e-02
-4.95632261e-01 7.86952019e-01 -4.37051088e-01 -9.86798048e-01
-3.06759775e-01 -2.06850126e-01 1.11805253e-01 1.44141987e-01
4.13948417e-01 2.47308433e-01 7.94468343e-01 -1.00705814e+00
-1.00622363e-01 -9.04477164e-02 -3.91785800e-01 -9.81531978e-01
9.81517136e-01 -2.65939742e-01 -7.63129368e-02 6.58991754e-01
7.87856519e-01 6.47129118e-01 -5.26059389e-01 -4.85130966e-01
6.61861897e-01 -5.52226186e-01 -1.65695459e-01 -1.16239846e+00
-6.36360288e-01 6.40063941e-01 1.50553524e-01 -4.00152415e-01
5.96416652e-01 -3.00693512e-01 8.85362923e-01 5.36688507e-01
6.19556367e-01 -1.46081543e+00 -3.09221029e-01 8.25018823e-01
7.39415705e-01 -1.14108121e+00 -1.92524016e-01 -3.64682913e-01
-7.65971422e-01 6.84971809e-01 6.21032596e-01 1.08045883e-01
2.29977816e-01 2.26238117e-01 7.05510437e-01 -8.07776395e-03
-7.37315536e-01 -1.55143157e-01 1.88069358e-01 7.23455310e-01
1.05693829e+00 4.39596802e-01 -9.28934157e-01 2.43996859e-01
-6.73254430e-01 -3.59924525e-01 6.87686622e-01 9.58278120e-01
-3.26333165e-01 -1.71735740e+00 -2.77578056e-01 6.00707471e-01
-8.43854249e-01 -7.86899090e-01 -9.65684175e-01 5.43878734e-01
2.93823957e-01 1.23752046e+00 -5.58064021e-02 3.56843919e-02
3.05459321e-01 6.20334864e-01 6.38813317e-01 -1.50378752e+00
-1.07913017e+00 7.66388923e-02 6.38359964e-01 -5.97986989e-02
-1.24419823e-01 -7.81643867e-01 -1.17181945e+00 -2.50888020e-02
-3.55307043e-01 6.20277584e-01 7.21874297e-01 8.04621458e-01
3.19716692e-01 -2.11832654e-02 4.66703773e-01 -4.64913309e-01
-8.73609900e-01 -1.34246719e+00 -1.72496438e-01 5.80993950e-01
-5.40774018e-02 -1.83670968e-01 2.83822026e-02 3.56241107e-01] | [11.439751625061035, 10.261609077453613] |
977bb868-8923-43dc-9dd5-ad2dcfc026a5 | acquire-augment-segment-enjoy-weakly | 1807.02001 | null | http://arxiv.org/abs/1807.02001v2 | http://arxiv.org/pdf/1807.02001v2.pdf | Acquire, Augment, Segment & Enjoy: Weakly Supervised Instance Segmentation of Supermarket Products | Grocery stores have thousands of products that are usually identified using
barcodes with a human in the loop. For automated checkout systems, it is
necessary to count and classify the groceries efficiently and robustly. One
possibility is to use a deep learning algorithm for instance-aware semantic
segmentation. Such methods achieve high accuracies but require a large amount
of annotated training data.
We propose a system to generate the training annotations in a weakly
supervised manner, drastically reducing the labeling effort. We assume that for
each training image, only the object class is known. The system automatically
segments the corresponding object from the background. The obtained training
data is augmented to simulate variations similar to those seen in real-world
setups. | ['Tobias Böttger', 'Bertram Drost', 'Patrick Follmann'] | 2018-07-05 | null | null | null | null | ['weakly-supervised-instance-segmentation'] | ['computer-vision'] | [ 2.48483196e-01 2.58597076e-01 -3.11212271e-01 -5.13374090e-01
-5.63560963e-01 -7.18953967e-01 3.51287961e-01 6.87915564e-01
-5.49150229e-01 3.77304435e-01 -8.50990355e-01 -1.16277315e-01
3.63051593e-01 -1.12219322e+00 -9.51178610e-01 -6.09264374e-01
2.99451321e-01 1.19607460e+00 4.14776087e-01 1.68797541e-02
1.96072921e-01 3.89178425e-01 -1.64491761e+00 3.60550284e-01
7.40039885e-01 1.08594894e+00 5.03576458e-01 6.34155989e-01
-3.66622925e-01 6.37939215e-01 -6.36848629e-01 -5.79487681e-01
6.77267551e-01 -4.36216116e-01 -5.61035097e-01 7.83727825e-01
4.02342498e-01 -7.87883550e-02 2.39803895e-01 1.34475935e+00
-2.12615237e-01 8.22022110e-02 4.94732618e-01 -1.07954979e+00
-4.53100214e-03 4.09674853e-01 -7.52628148e-01 -1.16418719e-01
4.68284339e-02 1.32290274e-01 7.87874103e-01 -4.08298165e-01
7.23966956e-01 9.03983414e-01 3.56013030e-01 1.36133566e-01
-1.23383284e+00 -5.25312006e-01 1.52841419e-01 3.61152962e-02
-1.30978394e+00 -3.00744921e-02 7.77065754e-01 -6.17299020e-01
2.17873633e-01 -8.79780725e-02 6.76742852e-01 7.27667868e-01
-7.27534518e-02 1.02342057e+00 1.05885792e+00 -4.74304616e-01
5.20320714e-01 6.71260774e-01 3.16091686e-01 9.46530879e-01
5.41121960e-01 -2.58625001e-01 -1.24692269e-01 8.76181498e-02
8.33942115e-01 2.13021383e-01 2.40025908e-01 -8.42320085e-01
-1.04472530e+00 8.07242811e-01 3.75479072e-01 3.00306022e-01
-4.84461516e-01 1.16717398e-01 2.96288252e-01 -1.20161884e-01
2.46836990e-01 4.55206603e-01 -5.09781122e-01 3.89347881e-01
-1.16944301e+00 2.90550053e-01 8.95565569e-01 9.76182401e-01
1.12859082e+00 -3.36859971e-01 1.64082542e-01 6.40267551e-01
2.20174953e-01 2.63357580e-01 1.94774881e-01 -8.00870359e-01
4.61136281e-01 8.65848303e-01 5.49792767e-01 -1.07818472e+00
-4.33400452e-01 -7.69462943e-01 -3.32039952e-01 3.53582710e-01
1.00095141e+00 1.22253142e-01 -1.27660453e+00 9.06300068e-01
5.70881367e-01 -3.81294359e-03 -2.76423603e-01 9.46116507e-01
2.27473393e-01 4.87396359e-01 1.95285082e-01 2.05477774e-01
1.56321931e+00 -1.08347774e+00 -5.88387966e-01 -4.47038740e-01
6.69721425e-01 -8.65611613e-01 1.10461366e+00 7.99922943e-01
-6.33136928e-01 -6.43879116e-01 -1.17069244e+00 1.35305285e-01
-6.77813947e-01 7.23802149e-01 7.09270597e-01 8.01053464e-01
-1.86935261e-01 5.21692514e-01 -9.61184382e-01 -2.60098159e-01
3.96189421e-01 3.77228379e-01 -3.17246735e-01 -1.91102043e-01
-6.63006544e-01 6.87853456e-01 1.00375450e+00 2.86736757e-01
-8.88140023e-01 6.08476251e-02 -1.24852526e+00 1.19393721e-01
7.90960073e-01 -2.26093352e-01 1.27106178e+00 -1.31728077e+00
-1.29451931e+00 1.20914936e+00 1.34685069e-01 -6.38983488e-01
6.53555393e-01 -1.37140363e-01 -2.00721305e-02 2.01108441e-01
2.13062227e-01 5.11070073e-01 9.00118053e-01 -1.59442747e+00
-8.51491511e-01 -5.18197834e-01 1.93320557e-01 -1.38410434e-01
2.63409585e-01 -1.56032249e-01 -7.27404654e-01 -2.71190315e-01
3.31170857e-01 -1.19307625e+00 -6.73836887e-01 -2.56318539e-01
-4.86240685e-01 1.03726886e-01 6.11361504e-01 -7.37675905e-01
5.61144888e-01 -2.06896710e+00 -5.03994524e-01 5.22716045e-01
-4.95428033e-02 4.07358706e-01 1.51244521e-01 -1.23753592e-01
3.00095856e-01 -2.28459984e-01 -2.25408465e-01 -3.80507946e-01
-1.78113673e-02 4.26415950e-01 8.63013119e-02 5.67852139e-01
1.66088313e-01 8.09259951e-01 -9.99792278e-01 -7.04326928e-01
4.81999904e-01 8.10682103e-02 -4.40943807e-01 1.32848145e-02
-6.26874924e-01 6.48186505e-01 -4.54412580e-01 6.75053537e-01
7.54106402e-01 -2.69399852e-01 2.92591274e-01 -2.71787569e-02
1.24774851e-01 3.01857591e-02 -1.63636982e+00 1.52314639e+00
-6.38669431e-01 2.73157179e-01 1.80829391e-01 -1.32545245e+00
1.10340285e+00 -8.43422711e-02 3.44663292e-01 -7.02541530e-01
3.90562028e-01 3.53993267e-01 -5.42212985e-02 -4.11432892e-01
7.86026657e-01 -2.13812590e-02 -4.16471869e-01 2.57023394e-01
2.85244465e-01 -3.74457985e-02 6.49633288e-01 -5.99038899e-02
7.02389538e-01 2.72106558e-01 2.76937187e-01 -1.44378290e-01
2.98663229e-01 4.85119849e-01 6.07143402e-01 8.21042001e-01
-1.18141726e-01 6.18936181e-01 4.11705852e-01 -6.87805414e-01
-1.15408027e+00 -7.45620847e-01 1.54212117e-01 9.41067636e-01
5.91045022e-01 1.23654325e-02 -1.09437525e+00 -9.98996913e-01
2.95507591e-02 5.46324730e-01 -5.77622652e-01 2.62836248e-01
-5.56324363e-01 -5.68142653e-01 -2.47828290e-02 4.24613208e-01
6.43846691e-01 -9.29452598e-01 -8.30824435e-01 3.86035502e-01
-1.45562246e-01 -1.31134653e+00 1.35187525e-02 4.31040466e-01
-7.19675839e-01 -1.33778286e+00 -5.69926977e-01 -8.09478343e-01
1.00206482e+00 1.53873423e-02 1.10804379e+00 1.15532158e-02
-5.66647887e-01 -7.42992312e-02 -3.05951566e-01 -4.82724160e-01
-4.92702663e-01 2.45338500e-01 -3.09041411e-01 4.62007284e-01
6.05461299e-01 1.51260883e-01 -5.01190662e-01 5.01917660e-01
-7.90695727e-01 -6.37901053e-02 7.09482849e-01 6.11894727e-01
9.27043617e-01 3.74026924e-01 2.28488162e-01 -1.40975785e+00
-7.38082752e-02 -1.22624047e-01 -1.17475152e+00 1.93191245e-01
-8.04455951e-02 9.76644456e-02 4.28117573e-01 -4.08885688e-01
-1.01520705e+00 1.03933585e+00 -6.21335581e-02 -1.56591609e-01
-7.53518641e-01 1.14488877e-01 -2.41335645e-01 6.99759424e-02
6.13633990e-01 -8.23301077e-02 -5.19109905e-01 -6.04145825e-01
3.78126651e-01 6.35487497e-01 6.92371786e-01 -5.11300862e-01
7.87479699e-01 4.58184063e-01 -2.51321822e-01 -6.75978422e-01
-1.07438660e+00 -7.93946862e-01 -8.82450640e-01 -2.03293815e-01
8.69906008e-01 -6.67503536e-01 -7.42881536e-01 2.37160936e-01
-1.03008485e+00 -5.11771619e-01 -2.97180116e-01 4.88984525e-01
-4.44422901e-01 1.04025632e-01 -5.12027264e-01 -8.17191303e-01
1.28376663e-01 -1.08067143e+00 1.27354383e+00 4.76153135e-01
-7.32732331e-03 -6.12854719e-01 -2.95619756e-01 7.30489254e-01
-1.74003169e-02 3.70123655e-01 3.82612973e-01 -8.77014875e-01
-7.84375727e-01 -7.59974837e-01 -1.97569847e-01 3.97753865e-01
-5.23994379e-02 -1.91438898e-01 -8.21113765e-01 2.31730148e-01
-4.04496789e-02 2.88596116e-02 7.15137899e-01 3.80114496e-01
1.25505793e+00 9.41080675e-02 -4.13000733e-01 1.17331564e-01
1.37426126e+00 2.97547311e-01 4.74643886e-01 2.72281080e-01
5.42305171e-01 7.67063022e-01 1.18887138e+00 1.94724485e-01
6.29701614e-02 7.46731281e-01 3.77440274e-01 -1.88804448e-01
3.28181893e-01 -3.50692272e-01 -1.36185631e-01 8.28728005e-02
4.73343953e-02 -1.23649493e-01 -8.89873207e-01 7.71971166e-01
-1.90853059e+00 -6.68127716e-01 -3.60499382e-01 2.18267322e+00
4.65732187e-01 4.82270032e-01 2.03619823e-01 3.88100266e-01
9.79273081e-01 -3.73169512e-01 -2.34458506e-01 -1.45468488e-01
2.51298130e-01 2.18609735e-01 9.85271990e-01 5.58743119e-01
-1.45927608e+00 9.05441821e-01 5.63368464e+00 6.75398290e-01
-9.38203275e-01 1.12934425e-01 9.75156069e-01 8.66472870e-02
3.66325229e-01 -1.00155890e-01 -1.05930471e+00 5.94481766e-01
6.22746408e-01 3.76365632e-01 9.19514745e-02 1.27458942e+00
6.72589242e-02 -7.29295433e-01 -1.07848668e+00 1.01308715e+00
4.74818982e-02 -1.16068518e+00 -3.02311420e-01 3.80429253e-02
8.45846534e-01 -4.11291033e-01 -1.10857986e-01 2.85872519e-01
4.40288544e-01 -6.56376600e-01 7.13226497e-01 2.38420784e-01
1.87985539e-01 -7.77921557e-01 9.88949060e-01 5.63689232e-01
-1.09060562e+00 -1.56111717e-01 -2.10709572e-01 -1.20184040e-02
1.66412726e-01 8.47979724e-01 -1.08983195e+00 1.93245187e-01
3.91049206e-01 7.92215690e-02 -6.65567160e-01 1.35949659e+00
-4.17747378e-01 5.28721690e-01 -5.11263013e-01 1.17833391e-01
3.36121172e-01 -3.90688896e-01 -5.71636595e-02 1.16735351e+00
1.91385120e-01 -1.14195436e-01 6.27420068e-01 8.72264266e-01
-2.71990746e-02 1.28353044e-01 -4.46898788e-01 -1.50232352e-02
-1.01392649e-01 1.47000849e+00 -1.64519894e+00 -5.61325908e-01
-2.02180460e-01 1.27675045e+00 -8.93711224e-02 1.33880332e-01
-8.28238368e-01 -4.05454278e-01 9.48203877e-02 4.78126466e-01
5.30117869e-01 -3.82103384e-01 -2.45980620e-01 -9.30339098e-01
3.47965136e-02 -5.16046643e-01 3.55850548e-01 -4.95173603e-01
-9.11238372e-01 2.71930605e-01 -1.87205538e-01 -1.02184749e+00
-3.68781716e-01 -8.30587029e-01 -9.96653885e-02 4.24059033e-01
-1.31026185e+00 -1.14386761e+00 -4.96825963e-01 2.53078759e-01
6.64137721e-01 2.02848032e-01 3.82379800e-01 6.04861736e-01
-5.18915534e-01 2.50957251e-01 -1.82847127e-01 4.48364258e-01
3.50568086e-01 -1.40794206e+00 1.94315359e-01 6.76198781e-01
5.83764732e-01 4.35420066e-01 9.24694180e-01 -4.86598462e-01
-7.75849044e-01 -1.12259400e+00 6.49052858e-01 -3.38241339e-01
4.41097200e-01 -7.30469227e-01 -8.67387950e-01 7.75758624e-01
-1.94222942e-01 4.10407722e-01 3.18321288e-01 -8.04859027e-02
-7.55352750e-02 -1.41326591e-01 -1.32220888e+00 6.97154086e-03
4.44085687e-01 -2.77125984e-01 -3.50103706e-01 5.79465747e-01
1.70665592e-01 -6.79753065e-01 -4.21159625e-01 1.52329445e-01
2.55231649e-01 -7.56192863e-01 7.21177638e-01 -1.76031172e-01
1.90008909e-01 -6.13258600e-01 2.41667494e-01 -9.47594345e-01
3.18857431e-01 -1.46929294e-01 1.07783400e-01 1.02563608e+00
4.63780016e-01 -2.43329957e-01 1.44697309e+00 7.58603454e-01
2.05598950e-01 -2.93210387e-01 -4.79063690e-01 -7.90552378e-01
-5.36398947e-01 -2.80582726e-01 4.59788829e-01 9.47482109e-01
-2.60047197e-01 1.78446069e-01 -8.66991803e-02 4.56803054e-01
6.28088176e-01 3.85363579e-01 1.02519274e+00 -1.40901899e+00
-6.24669492e-01 4.00790907e-02 -7.35835910e-01 -9.57649171e-01
3.25815342e-02 -6.29477322e-01 3.79152328e-01 -1.41092527e+00
8.24608728e-02 -7.54407287e-01 -1.30692378e-01 3.70770633e-01
-2.36309804e-02 7.01420665e-01 1.83780640e-01 -2.52112120e-01
-9.97364342e-01 -2.60588229e-01 8.68318200e-01 -2.21584007e-01
-2.57593602e-01 4.45483178e-01 -2.08468705e-01 1.03071856e+00
1.00699520e+00 -4.90736872e-01 -8.20670500e-02 -1.40231252e-01
2.11825490e-01 -7.62368515e-02 3.70317280e-01 -9.89416182e-01
6.56201690e-02 -1.56963959e-01 4.91376877e-01 -7.28817344e-01
2.39627257e-01 -1.11428905e+00 1.77503258e-01 4.64731038e-01
-2.44440779e-01 -5.51064909e-01 -1.01445336e-02 5.95593452e-01
-3.02434862e-01 -8.71304095e-01 8.47390711e-01 -5.95692813e-01
-7.41433620e-01 -2.26693414e-02 -3.65250289e-01 -5.54438293e-01
1.33827579e+00 -2.11435482e-01 9.20301378e-02 -7.79003873e-02
-1.05691147e+00 9.64974090e-02 6.33301198e-01 1.28302559e-01
-7.24161640e-02 -9.29526091e-01 -3.07377428e-01 1.35150984e-01
2.65690237e-01 2.34775126e-01 9.91353169e-02 3.76749367e-01
-8.57941151e-01 2.98902214e-01 -1.77567720e-01 -7.54181027e-01
-1.11722410e+00 8.86785448e-01 3.94778341e-01 -6.54120862e-01
-5.16815424e-01 4.53951240e-01 1.71909034e-01 -4.82773453e-01
3.59931067e-02 -5.58355212e-01 -8.44105259e-02 6.28995970e-02
5.87756634e-01 1.30440310e-01 2.99260557e-01 -5.11826277e-01
-3.59716415e-02 3.00458431e-01 -8.18094313e-02 8.45808461e-02
1.08289397e+00 1.37686551e-01 3.90103757e-01 2.86152422e-01
8.99366379e-01 3.24897356e-02 -1.31817305e+00 -2.52697319e-01
4.48699117e-01 -7.11979747e-01 -1.22401573e-01 -6.00342333e-01
-1.27213633e+00 8.95265341e-01 6.00615799e-01 2.77192384e-01
8.17720473e-01 2.01481342e-01 6.63324833e-01 5.37327945e-01
7.72181869e-01 -1.32759023e+00 4.68012504e-02 1.59729496e-02
1.42101899e-01 -1.48989260e+00 -5.32852188e-02 -7.85096049e-01
-7.20355093e-01 9.65492189e-01 5.23266196e-01 -4.06375170e-01
2.33855411e-01 4.88614202e-01 1.41766220e-01 -3.35752428e-01
5.09787239e-02 -6.00175560e-01 -5.53470068e-02 5.88169694e-01
1.43481106e-01 1.19646162e-01 -2.36512497e-01 6.05926752e-01
-2.81209592e-02 -4.14350703e-02 5.47283649e-01 9.29926455e-01
-5.75980067e-01 -1.17506814e+00 -7.86634266e-01 3.80406976e-01
-5.92436314e-01 4.16088939e-01 -1.32503107e-01 8.33106518e-01
5.13504446e-01 8.19658875e-01 2.73046821e-01 1.53971389e-01
2.68998623e-01 1.25875965e-01 5.45361817e-01 -9.20898020e-01
-6.76988661e-01 1.67480096e-01 9.32057500e-02 -4.61550593e-01
-3.77133191e-01 -5.65558791e-01 -1.40331101e+00 1.51166826e-01
-5.27882516e-01 1.52768999e-01 1.04778290e+00 9.65631545e-01
3.87684884e-03 3.61155808e-01 3.80539447e-01 -1.10566068e+00
3.58340293e-02 -6.64986789e-01 -8.89059782e-01 6.76639080e-01
6.74078939e-03 -7.34705210e-01 8.18575919e-02 4.67130661e-01] | [9.437297821044922, 0.7150502800941467] |
bad3ae7d-db60-4f2b-a7e2-b5aba015acfb | contextualized-diachronic-word | null | null | https://aclanthology.org/W19-4705 | https://aclanthology.org/W19-4705.pdf | Contextualized Diachronic Word Representations | Diachronic word embeddings play a key role in capturing interesting patterns about how language evolves over time. Most of the existing work focuses on studying corpora spanning across several decades, which is understandably still not a possibility when working on social media-based user-generated content. In this work, we address the problem of studying semantic changes in a large Twitter corpus collected over five years, a much shorter period than what is usually the norm in diachronic studies. We devise a novel attentional model, based on Bernoulli word embeddings, that are conditioned on contextual extra-linguistic (social) features such as network, spatial and socio-economic variables, which are associated with Twitter users, as well as topic-based features. We posit that these social features provide an inductive bias that helps our model to overcome the narrow time-span regime problem. Our extensive experiments reveal that our proposed model is able to capture subtle semantic shifts without being biased towards frequency cues and also works well when certain contextual features are absent. Our model fits the data better than current state-of-the-art dynamic word embedding models and therefore is a promising tool to study diachronic semantic changes over small time periods. | ["Djam{\\'e} Seddah", 'Ganesh Jawahar'] | 2019-08-01 | null | null | null | ws-2019-8 | ['diachronic-word-embeddings'] | ['natural-language-processing'] | [-2.52141535e-01 -2.61375219e-01 -4.56890404e-01 -1.08226866e-01
-6.39241859e-02 -5.34796536e-01 1.28319097e+00 9.22224879e-01
-1.02235413e+00 6.18334711e-01 7.26553321e-01 -3.07516962e-01
-2.38120943e-01 -1.08679473e+00 -4.73313183e-01 -5.98006308e-01
-3.03341120e-01 3.17323565e-01 4.69803452e-01 -5.54808199e-01
2.71161079e-01 1.94067925e-01 -1.53889513e+00 -4.10291523e-01
6.41977012e-01 4.23688889e-01 9.13914666e-02 4.83054072e-01
-3.55007857e-01 2.64091074e-01 -3.52429897e-01 -3.80655199e-01
-5.92768528e-02 3.62419039e-02 -6.23306632e-01 -3.77206922e-01
2.80338407e-01 2.85462201e-01 -6.48460031e-01 1.06872582e+00
5.07451713e-01 3.01447809e-01 6.98714554e-01 -9.01833713e-01
-9.12978590e-01 7.62430429e-01 -4.69521552e-01 9.21343029e-01
1.40798181e-01 7.30496570e-02 1.45477343e+00 -7.58758307e-01
7.27437198e-01 1.32849753e+00 8.97763550e-01 9.67918113e-02
-1.32570851e+00 -4.76879746e-01 4.35327262e-01 2.90634662e-01
-1.27780974e+00 -1.86710224e-01 1.02097261e+00 -7.37972081e-01
7.39807427e-01 1.67213202e-01 8.03388953e-01 1.58693874e+00
3.70659053e-01 3.27109665e-01 9.20887113e-01 -4.42517281e-01
5.77338003e-02 3.20861250e-01 3.98215681e-01 2.72563428e-01
3.29872072e-01 -3.13052163e-02 -6.46924078e-01 -2.73886770e-01
3.64507109e-01 4.45847303e-01 -1.76428035e-01 -2.39400446e-01
-1.28703833e+00 1.15999353e+00 5.12607813e-01 1.20726061e+00
-4.19297636e-01 2.51747698e-01 4.61703867e-01 3.15683693e-01
1.21283162e+00 5.91544688e-01 -6.13546789e-01 -5.30747414e-01
-7.83852637e-01 4.17688578e-01 4.61275280e-01 3.06898475e-01
8.38661611e-01 -1.90355703e-01 -5.38338758e-02 8.82693648e-01
2.73016065e-01 4.44672436e-01 9.67522919e-01 -2.18997955e-01
2.17323646e-01 5.46954453e-01 7.55908936e-02 -1.47691298e+00
-4.70063835e-01 -3.52790892e-01 -4.70528394e-01 -4.72356111e-01
4.63029981e-01 -9.22962651e-02 -5.16005635e-01 2.12313724e+00
3.94847870e-01 5.33005118e-01 -4.18532670e-01 5.13832927e-01
4.95748520e-01 5.95530331e-01 3.10320079e-01 -1.76269442e-01
1.43711114e+00 -3.78639281e-01 -8.18875492e-01 -2.22836003e-01
6.21852577e-01 -5.40095747e-01 1.34053969e+00 -1.14917181e-01
-6.74874127e-01 -3.78312379e-01 -6.53842330e-01 5.62675260e-02
-1.22104287e+00 -7.91405380e-01 7.89798081e-01 5.78552902e-01
-1.02484655e+00 5.82018971e-01 -6.78242505e-01 -1.04992902e+00
1.65502459e-01 -7.82146603e-02 -1.73158824e-01 1.23643629e-01
-1.78279138e+00 9.46750760e-01 1.12305611e-01 -2.53637969e-01
-1.94542572e-01 -9.03804243e-01 -8.51545513e-01 -6.73645758e-04
2.26865202e-01 -5.60825944e-01 8.73247027e-01 -6.48213387e-01
-1.15200603e+00 8.52677763e-01 -2.73615897e-01 -3.47630948e-01
2.31914148e-01 -7.67690036e-03 -7.03049481e-01 -1.62137344e-01
1.24978855e-01 2.81197727e-01 7.07455218e-01 -9.22205091e-01
-5.01262188e-01 -6.10501587e-01 2.26404816e-01 -6.93998188e-02
-1.26732266e+00 -1.61323264e-01 -3.29402477e-01 -9.85461473e-01
-4.02717859e-01 -9.34280097e-01 -1.36408195e-01 -1.27728418e-01
6.15574680e-02 -6.80238485e-01 6.37746692e-01 -4.04014975e-01
1.88285983e+00 -2.15164471e+00 2.76690036e-01 6.41477033e-02
3.03360611e-01 2.53773838e-01 -1.63840950e-01 8.57881665e-01
1.30462661e-01 4.13050860e-01 -2.02325717e-01 -3.64194185e-01
1.23414211e-01 2.20872313e-01 -1.30897313e-01 6.71314359e-01
1.82935949e-02 9.82370734e-01 -1.32997787e+00 -2.24385068e-01
1.46083936e-01 5.04722536e-01 -6.55672610e-01 -1.80252329e-01
-1.95619419e-01 2.48256430e-01 -5.26875377e-01 3.20036203e-01
3.45676452e-01 -1.02042787e-01 1.18302174e-01 2.35775664e-01
-4.74039912e-01 3.01653385e-01 -6.40250802e-01 1.70375311e+00
-8.07772458e-01 1.03395081e+00 -3.32455039e-01 -1.10106385e+00
6.69865191e-01 3.58018726e-02 6.26032591e-01 -9.26683307e-01
2.32891902e-01 -1.26006365e-01 1.03071332e-01 -6.98939145e-01
7.09832370e-01 -3.54088962e-01 -3.76732707e-01 5.23738682e-01
-1.07380673e-01 1.10005073e-01 1.69661045e-01 1.06097423e-01
1.26080501e+00 -4.40646052e-01 2.74667114e-01 -6.48971677e-01
4.44422722e-01 -3.37564260e-01 4.24865454e-01 6.03279471e-01
-4.02019382e-01 1.77007869e-01 5.07276058e-01 -3.37656796e-01
-1.02926993e+00 -8.93741786e-01 -4.93023336e-01 1.45928490e+00
1.44509897e-01 -6.23876333e-01 -2.93675750e-01 -4.57594365e-01
4.34184074e-01 7.84410596e-01 -1.13077986e+00 -2.44990930e-01
-4.11245793e-01 -1.08285856e+00 2.61598915e-01 3.24020326e-01
-1.55082911e-01 -8.37134778e-01 -1.66170090e-01 4.27187741e-01
1.06603041e-01 -8.03722322e-01 -3.48430127e-01 -9.64272991e-02
-6.83174133e-01 -9.03575897e-01 -6.72591507e-01 -4.39311713e-01
1.98946059e-01 4.10423845e-01 1.09164536e+00 -1.22354254e-01
-2.47288898e-01 6.00677133e-01 -6.10539377e-01 -5.98939300e-01
6.29141107e-02 4.36548054e-01 3.18875641e-01 2.73736149e-01
9.21190143e-01 -8.79222691e-01 -7.49485135e-01 -9.82841328e-02
-1.14772999e+00 -5.33365786e-01 1.53126076e-01 8.41546893e-01
3.36369649e-02 9.59383100e-02 7.66053140e-01 -1.13928592e+00
8.05490255e-01 -1.31367946e+00 -1.31784454e-01 -1.99442282e-01
-9.87746418e-01 -2.59943400e-02 5.12204528e-01 -7.54695892e-01
-7.89141476e-01 -8.32462192e-01 -4.29322869e-02 6.28695032e-03
3.86430100e-02 7.28433371e-01 3.05002987e-01 2.82033145e-01
5.50987124e-01 9.27455630e-03 -1.47908390e-01 -6.63333118e-01
4.98772174e-01 8.92892420e-01 -4.08129506e-02 -4.66678530e-01
8.80417943e-01 7.42270291e-01 -3.80780786e-01 -1.29633367e+00
-7.02428639e-01 -9.20837164e-01 -6.77786648e-01 -6.44416809e-02
8.15300584e-01 -7.34823227e-01 -3.35641980e-01 3.74600291e-01
-9.26675856e-01 -2.49492869e-01 -2.37611234e-01 4.63404208e-01
-7.23494738e-02 1.41944274e-01 -3.81225765e-01 -5.36211550e-01
4.08745855e-02 -5.99235654e-01 8.27404261e-01 5.15399575e-02
-5.74734271e-01 -1.91291618e+00 7.34783769e-01 -3.61954905e-02
8.04939389e-01 4.35986876e-01 1.02595472e+00 -7.76776671e-01
-7.69451857e-02 -1.69780493e-01 -1.40969038e-01 -1.00032829e-01
4.48626965e-01 -3.12829167e-02 -8.71435046e-01 -3.86487782e-01
-2.56701857e-01 8.34606364e-02 1.03757846e+00 1.62066549e-01
1.06932664e+00 -3.09228718e-01 -5.63601673e-01 1.38880655e-01
1.47388756e+00 -1.90412357e-01 2.70383775e-01 5.51495135e-01
6.46883070e-01 5.18783689e-01 2.93446928e-01 7.05083728e-01
7.74917841e-01 7.73717999e-01 3.47119272e-01 2.43914500e-03
1.45718336e-01 -3.76030117e-01 2.99348652e-01 1.15582383e+00
3.35721709e-02 -3.35442990e-01 -1.15865684e+00 1.28042042e+00
-1.78137457e+00 -1.11094308e+00 -2.38578007e-01 1.99025548e+00
9.33850706e-01 2.64358371e-01 1.75009549e-01 1.54813349e-01
4.79251266e-01 9.43042397e-01 -2.78948665e-01 -4.40849423e-01
4.35478706e-03 4.11661178e-01 5.97429872e-01 5.99430859e-01
-1.03273129e+00 8.95083606e-01 5.63026237e+00 5.99175513e-01
-1.19994009e+00 4.26676929e-01 3.98785733e-02 -1.05894677e-01
-8.44384253e-01 -2.29174301e-01 -5.90501249e-01 9.11461830e-01
1.38776565e+00 -3.65177274e-01 1.82456911e-01 4.70387787e-01
4.80989069e-01 3.40221636e-02 -9.61673021e-01 7.74253309e-01
3.95240694e-01 -1.20359290e+00 -8.91516432e-02 1.08053759e-01
7.83767343e-01 2.57185131e-01 2.30071872e-01 2.93023229e-01
2.37077460e-01 -8.45563650e-01 6.42252922e-01 6.54583216e-01
6.48573995e-01 -5.80374956e-01 6.97148144e-01 2.26755485e-01
-1.00851953e+00 -1.96494743e-01 -1.55387402e-01 -2.33072892e-01
1.60089225e-01 8.47043753e-01 -6.19304895e-01 2.75772154e-01
7.75335968e-01 1.33345103e+00 -7.01034188e-01 7.40577757e-01
4.54163365e-02 8.09201300e-01 -1.75712049e-01 -3.87134165e-01
5.93029261e-01 -8.81847292e-02 7.45466292e-01 1.46925056e+00
3.64033639e-01 -2.53839761e-01 -2.29204684e-01 5.50510645e-01
-2.02289656e-01 2.60167629e-01 -1.08351672e+00 -3.98183733e-01
6.47771180e-01 9.23054278e-01 -5.71710408e-01 -1.67806059e-01
-8.41467798e-01 7.27824926e-01 4.73969191e-01 2.69370705e-01
-6.94061220e-01 -4.44682300e-01 1.14812171e+00 5.31637788e-01
3.81163597e-01 -4.93945718e-01 -9.69137810e-03 -1.26246476e+00
-1.53494745e-01 -3.99625599e-01 2.80972302e-01 -1.78112254e-01
-1.62882543e+00 2.35125348e-01 1.02948314e-02 -8.34553897e-01
-2.12430954e-02 -5.26327074e-01 -8.04265380e-01 7.10290670e-01
-1.84215617e+00 -1.02630556e+00 -2.75803711e-02 4.00398940e-01
6.22230530e-01 1.10706300e-01 7.34470904e-01 5.48420668e-01
-5.96295059e-01 3.96456391e-01 5.50917447e-01 -1.24503866e-01
8.09419870e-01 -1.35088384e+00 3.13750714e-01 6.15545154e-01
3.47324491e-01 9.54138815e-01 9.08531308e-01 -4.51936215e-01
-1.18846512e+00 -1.07533395e+00 1.50378549e+00 -7.67268896e-01
1.44245601e+00 -5.56286097e-01 -9.42938864e-01 6.27276242e-01
3.21720690e-01 -1.41316578e-01 9.75096524e-01 6.46715105e-01
-3.31210911e-01 -1.30390912e-01 -7.79952288e-01 6.31016433e-01
1.20876813e+00 -7.09882557e-01 -9.91208255e-01 2.41834015e-01
9.62089539e-01 2.96778560e-01 -8.72590721e-01 9.25549492e-03
4.85150844e-01 -5.61424255e-01 9.62627649e-01 -7.09963620e-01
2.80729920e-01 8.49874467e-02 -1.46754816e-01 -1.68454516e+00
-5.03184259e-01 -5.10370851e-01 2.88280360e-02 1.48464429e+00
3.55225056e-01 -1.01875281e+00 3.53523254e-01 1.58450574e-01
1.40182048e-01 -5.13445497e-01 -1.09993482e+00 -7.66747236e-01
5.09842873e-01 -4.78321761e-01 7.14172900e-01 1.45558321e+00
4.84748073e-02 1.95183024e-01 -1.80201814e-01 -1.16770998e-01
1.68757379e-01 -1.83083981e-01 5.56251645e-01 -1.68632388e+00
7.71027133e-02 -7.07093954e-01 -5.57282805e-01 -6.84483469e-01
4.62796479e-01 -9.46770728e-01 -3.88348579e-01 -1.10240245e+00
1.39165834e-01 -6.59147620e-01 -6.08974457e-01 -3.14341346e-03
-2.27139667e-01 2.34266996e-01 -9.79466364e-02 -1.33474797e-01
-4.10923839e-01 8.24493527e-01 9.03121591e-01 -1.98367670e-01
-1.43492788e-01 -3.23000968e-01 -8.51728261e-01 7.07943499e-01
5.90254784e-01 -6.17553949e-01 -3.50449055e-01 -4.50838447e-01
6.82319999e-01 -5.65072477e-01 1.68992966e-01 -5.60269058e-01
5.77075705e-02 -3.69618535e-01 -1.07703082e-01 -1.17729567e-01
1.84490457e-01 -9.55456018e-01 -2.20721945e-01 2.89826840e-01
-3.21246207e-01 4.01827842e-01 3.94506045e-02 1.02541184e+00
-3.28732073e-01 3.94454747e-02 4.38044280e-01 -2.42129527e-02
-7.44224787e-01 5.71450830e-01 -5.14341950e-01 3.29857469e-01
9.98229086e-01 -2.89663877e-02 -1.16980344e-01 -1.74356267e-01
-5.87888718e-01 2.15348542e-01 5.62248230e-01 9.82383013e-01
1.20056264e-01 -1.48138964e+00 -4.94193405e-01 -8.68177041e-03
4.88307625e-01 -5.33845127e-01 1.76624864e-01 7.84354091e-01
-1.40085831e-01 5.79358459e-01 1.69848233e-01 -3.36884439e-01
-9.36589181e-01 6.23772323e-01 -8.82261917e-02 -2.75701702e-01
-5.64071655e-01 7.27061152e-01 -1.43708035e-01 -3.59315783e-01
-5.58596104e-02 -4.98381108e-01 -5.63988090e-01 9.96524215e-01
3.11501235e-01 4.25609857e-01 -1.25070870e-01 -8.95632803e-01
-3.21496397e-01 7.06477404e-01 1.56712085e-01 -1.38378531e-01
1.89795482e+00 -5.49763680e-01 -6.84631094e-02 1.26282704e+00
1.49043024e+00 3.03758502e-01 -6.36375666e-01 -7.24797308e-01
2.30824947e-01 -6.72249079e-01 2.17204869e-01 -3.02972853e-01
-6.47186100e-01 9.44316089e-01 4.64791179e-01 8.14319849e-01
4.83145863e-01 1.67362764e-01 1.08485305e+00 -1.57563716e-01
3.03158075e-01 -1.21787858e+00 2.05186903e-01 6.49548471e-01
7.05663562e-01 -1.35030675e+00 -1.85151413e-01 1.36457309e-01
-1.16396919e-01 8.37116480e-01 2.75583267e-01 -1.51512936e-01
1.26500094e+00 -3.25977027e-01 -2.69931465e-01 -3.63834679e-01
-7.71667242e-01 -5.09568155e-01 1.37345567e-01 3.36216092e-01
4.91411209e-01 2.52322495e-01 -7.81525195e-01 4.37462330e-01
-2.90462941e-01 -3.37707579e-01 4.70773876e-01 8.09522986e-01
-3.18794638e-01 -1.23895097e+00 -1.55853420e-01 4.11893904e-01
-7.14173496e-01 -4.26849611e-02 -1.53060585e-01 9.77703989e-01
3.65116179e-01 6.70744240e-01 5.15217423e-01 -3.08190674e-01
1.94493264e-01 3.12265396e-01 1.22142360e-01 -8.05966794e-01
-4.59640503e-01 -4.53721911e-01 -4.97420225e-03 -4.06310380e-01
-5.40918231e-01 -9.77807045e-01 -6.60248160e-01 -6.61148608e-01
-1.03276826e-01 -6.17242418e-02 6.55779660e-01 8.28671873e-01
3.32531810e-01 4.59774077e-01 7.99403310e-01 -8.43021274e-01
-1.72058716e-01 -1.24247229e+00 -5.71601570e-01 9.08000410e-01
5.69717526e-01 -1.02643192e+00 -7.25907624e-01 -2.12902591e-01] | [10.115984916687012, 8.899441719055176] |
07370d1d-8838-43ce-8402-5bd32fed17cd | forecasting-individualized-disease | 1810.10489 | null | http://arxiv.org/abs/1810.10489v1 | http://arxiv.org/pdf/1810.10489v1.pdf | Forecasting Individualized Disease Trajectories using Interpretable Deep Learning | Disease progression models are instrumental in predicting individual-level
health trajectories and understanding disease dynamics. Existing models are
capable of providing either accurate predictions of patients prognoses or
clinically interpretable representations of disease pathophysiology, but not
both. In this paper, we develop the phased attentive state space (PASS) model
of disease progression, a deep probabilistic model that captures complex
representations for disease progression while maintaining clinical
interpretability. Unlike Markovian state space models which assume memoryless
dynamics, PASS uses an attention mechanism to induce "memoryful" state
transitions, whereby repeatedly updated attention weights are used to focus on
past state realizations that best predict future states. This gives rise to
complex, non-stationary state dynamics that remain interpretable through the
generated attention weights, which designate the relationships between the
realized state variables for individual patients. PASS uses phased LSTM units
(with time gates controlled by parametrized oscillations) to generate the
attention weights in continuous time, which enables handling
irregularly-sampled and potentially missing medical observations. Experiments
on data from a realworld cohort of patients show that PASS successfully
balances the tradeoff between accuracy and interpretability: it demonstrates
superior predictive accuracy and learns insightful individual-level
representations of disease progression. | ['Mihaela van der Schaar', 'Ahmed M. Alaa'] | 2018-10-24 | null | null | null | null | ['disease-trajectory-forecasting'] | ['medical'] | [ 3.21667314e-01 3.06707054e-01 -4.10847574e-01 -2.24903688e-01
-6.07958257e-01 -2.95384154e-02 6.76583648e-01 4.59876478e-01
-4.65838006e-03 7.04155385e-01 6.40137851e-01 -5.28748155e-01
-5.22226155e-01 -6.55866086e-01 -1.96837679e-01 -7.08494842e-01
-7.71017969e-01 9.75630224e-01 -1.38184696e-01 -6.88562123e-03
-1.22353710e-01 2.79604703e-01 -9.49068546e-01 3.79584283e-01
7.60510027e-01 6.13076389e-01 -1.79432593e-02 1.04717088e+00
-1.02762692e-01 1.06430125e+00 -4.75437611e-01 1.86846524e-01
-5.38501918e-01 -4.52455550e-01 -8.31366479e-01 -1.56155556e-01
-2.88224369e-01 -1.35014102e-01 -6.28151953e-01 6.31793320e-01
1.56211734e-01 -6.66530058e-02 7.03047037e-01 -9.33760822e-01
-1.12200403e+00 5.23034692e-01 2.10016333e-02 6.46190405e-01
1.82379529e-01 6.33141398e-01 8.22623134e-01 -1.07731536e-01
4.30941314e-01 1.35017002e+00 9.20634210e-01 9.10578251e-01
-1.67204702e+00 -1.01920687e-01 4.51963544e-01 1.43271357e-01
-1.02923644e+00 -1.96866781e-01 4.29187685e-01 -6.61770761e-01
1.28000784e+00 3.66414219e-01 9.87417698e-01 1.56471527e+00
1.22127676e+00 6.16685033e-01 7.45317698e-01 5.78212971e-03
3.39138865e-01 -3.98465216e-01 6.65348887e-01 6.84088588e-01
1.17481455e-01 3.59935194e-01 -2.80748874e-01 -5.19301236e-01
1.00050569e+00 7.55050004e-01 -3.19249600e-01 2.05615714e-01
-1.34560549e+00 5.96368134e-01 5.52438319e-01 2.91173816e-01
-9.39210176e-01 7.33432472e-01 2.25715667e-01 1.96137011e-01
4.42910910e-01 5.00451684e-01 -5.86724401e-01 -1.29098743e-01
-6.52051210e-01 3.92567227e-03 4.50841606e-01 2.90885776e-01
2.00953022e-01 2.44447470e-01 -8.54481995e-01 2.72139430e-01
3.68088514e-01 6.12012506e-01 9.02271450e-01 -6.27541780e-01
-4.72661704e-02 7.49235690e-01 3.00637454e-01 -6.57333314e-01
-8.98936093e-01 -6.90358222e-01 -1.21277213e+00 -3.16305190e-01
2.86506098e-02 -6.35089278e-02 -1.54807580e+00 2.14114881e+00
-1.10411353e-01 5.17534614e-01 2.12528601e-01 4.30186689e-01
4.47695941e-01 9.18880761e-01 7.37394154e-01 -1.40310347e-01
1.53427529e+00 -3.94184828e-01 -9.82602000e-01 -3.67214233e-01
5.59274077e-01 1.56438842e-01 9.80408967e-01 -6.63213357e-02
-1.25163186e+00 -2.81081915e-01 -5.26005983e-01 1.50697157e-01
-2.26235032e-01 -1.86171874e-01 7.10475981e-01 2.23544344e-01
-1.42050898e+00 9.00849044e-01 -1.96659172e+00 -2.74593592e-01
5.95727086e-01 5.76730490e-01 8.63784850e-02 2.59900421e-01
-1.57267809e+00 1.05057395e+00 2.14407519e-01 3.74514937e-01
-1.07507777e+00 -1.00715244e+00 -7.44730473e-01 5.25674045e-01
-2.62115091e-01 -1.44911730e+00 1.30899930e+00 -7.33454168e-01
-1.41974556e+00 4.13481027e-01 -3.82065773e-01 -8.70068908e-01
1.16957277e-01 -1.32765025e-01 -6.05779886e-01 -5.60453273e-02
-3.64357054e-01 6.71765208e-01 6.17273986e-01 -5.17066717e-01
-1.95223063e-01 -3.08229297e-01 -4.98980463e-01 9.98825505e-02
-8.90707374e-02 -3.25506240e-01 -7.07371533e-02 -5.42767346e-01
7.68241286e-02 -8.82888615e-01 -9.09694552e-01 3.47499996e-02
-4.46633130e-01 -1.91946924e-01 4.23792183e-01 -7.18915343e-01
1.61359882e+00 -1.76134038e+00 1.86980218e-01 3.92920449e-02
5.18842518e-01 1.36989310e-01 -5.40509857e-02 5.21856010e-01
-2.85597831e-01 1.94170892e-01 -3.47916037e-01 -4.44461524e-01
-2.53433228e-01 6.26459479e-01 -3.16148937e-01 2.89919764e-01
8.17078531e-01 1.40618813e+00 -1.09944189e+00 -2.04626560e-01
1.53368741e-01 8.44239354e-01 -5.29846907e-01 7.78926238e-02
-3.88461769e-01 6.03387117e-01 -7.33040214e-01 3.43701422e-01
-3.34118344e-02 -1.05245984e+00 2.91455060e-01 3.57721359e-01
3.22695136e-01 5.75804412e-01 -6.21067703e-01 1.24189222e+00
-4.84153569e-01 4.77014214e-01 -3.47333789e-01 -7.90771484e-01
6.17848158e-01 5.88660419e-01 5.17279565e-01 -3.72171819e-01
8.47449154e-02 -1.91031933e-01 2.35432431e-01 -3.92762542e-01
1.14614807e-01 -4.38057452e-01 -2.39956141e-01 6.32433295e-01
-1.46036133e-01 1.79477870e-01 -2.75933832e-01 1.40816316e-01
1.53641856e+00 -2.77767509e-01 4.52275664e-01 -2.13856846e-01
3.43629986e-01 2.64318753e-02 6.92855477e-01 8.62163603e-01
-3.84267747e-01 2.74716467e-01 6.31538332e-01 -9.22946811e-01
-8.02454591e-01 -1.51153100e+00 -2.49559283e-01 5.55004954e-01
-2.07062960e-01 -1.77804083e-01 -3.05006295e-01 -1.43946230e-01
-2.43389547e-01 7.29001701e-01 -1.06417596e+00 -9.21806276e-01
-6.51841640e-01 -1.32097757e+00 2.06171542e-01 7.98937738e-01
-1.00995667e-01 -1.41949260e+00 -8.03038120e-01 7.55686998e-01
-1.85938627e-01 -1.67848736e-01 -3.74703556e-01 3.51732731e-01
-1.23332703e+00 -9.60393965e-01 -5.97993255e-01 -5.90045810e-01
7.63255119e-01 -6.19163334e-01 1.21523273e+00 9.01073888e-02
-5.12846947e-01 3.60839099e-01 2.78489977e-01 -2.78956443e-01
-7.58405089e-01 -4.00112905e-02 1.32375270e-01 -1.79354429e-01
2.43521795e-01 -5.60967565e-01 -9.28648412e-01 -3.68990302e-01
-9.36606169e-01 2.90508062e-01 5.76665103e-01 1.12437129e+00
8.05891454e-01 -3.30646932e-01 7.42604554e-01 -9.60935533e-01
8.23217630e-01 -8.23905766e-01 -5.40033057e-02 2.57396549e-01
-7.80538142e-01 4.82388735e-01 6.82720244e-01 -6.11486018e-01
-1.01344156e+00 -3.64085734e-02 -1.82539478e-01 -4.42089289e-01
-1.17183432e-01 6.22284055e-01 5.57561100e-01 7.62061179e-01
5.54055333e-01 7.13044524e-01 2.23717868e-01 -2.94484168e-01
2.16534898e-01 2.60140389e-01 5.69839418e-01 -2.29951099e-01
9.44999978e-02 4.35836464e-01 1.10866770e-01 -3.54817688e-01
-8.09321880e-01 7.58890482e-03 -2.87954062e-01 1.29396096e-01
8.58267009e-01 -7.44799078e-01 -7.96502650e-01 3.75065267e-01
-9.17026222e-01 -6.61756992e-01 -7.64223993e-01 4.10364509e-01
-7.64192700e-01 -2.57246822e-01 -1.38675511e+00 -7.87796676e-01
-6.66904330e-01 -9.80737865e-01 1.11030746e+00 1.80503502e-01
-9.45987761e-01 -1.64984071e+00 5.42967618e-01 -5.13926089e-01
5.99203646e-01 4.26269054e-01 1.46348989e+00 -4.81199950e-01
-4.20576811e-01 -2.81647235e-01 1.62161574e-01 -2.62885064e-01
3.36655736e-01 3.27947214e-02 -5.91679335e-01 -2.07528099e-01
-3.37524116e-02 3.14383417e-01 9.38664079e-01 1.03184140e+00
1.14335787e+00 -7.39708364e-01 -8.26155245e-01 4.78361726e-01
9.99927938e-01 4.38543290e-01 6.20837390e-01 -1.49203703e-01
3.44485581e-01 2.76531190e-01 -1.56896263e-01 3.78281742e-01
5.62592983e-01 2.46230692e-01 3.61072838e-01 -2.40214050e-01
-6.50036931e-02 -3.36879015e-01 3.08753788e-01 6.61311269e-01
1.86015829e-01 -3.80799443e-01 -1.29787624e+00 7.09110081e-01
-1.87482345e+00 -1.09941030e+00 -1.68326035e-01 1.92525256e+00
1.04367805e+00 3.10812980e-01 -8.15889686e-02 -1.60202563e-01
5.37564695e-01 -2.26540957e-02 -8.49822342e-01 -5.63550830e-01
1.71314299e-01 3.42337310e-01 1.73699081e-01 6.07964754e-01
-8.70734990e-01 6.43421054e-01 7.49692917e+00 1.98268637e-01
-1.23930848e+00 2.14500278e-01 1.02584863e+00 -2.82569051e-01
-4.83219862e-01 -2.16618121e-01 -4.83895779e-01 6.86442077e-01
1.73691249e+00 -1.69629216e-01 -2.10402645e-02 3.43856037e-01
6.32040381e-01 2.90391147e-01 -1.23502898e+00 4.58678842e-01
-6.45860910e-01 -1.64262450e+00 2.70574391e-01 -7.66033754e-02
7.05190837e-01 1.76348984e-01 5.30188918e-01 3.58482033e-01
9.06386733e-01 -1.17229366e+00 2.92111397e-01 1.26942372e+00
7.33290374e-01 -4.39344913e-01 4.50621814e-01 4.05791163e-01
-8.53495121e-01 -3.53613496e-01 1.38945356e-01 -3.21945027e-02
5.28710365e-01 4.34401572e-01 -1.09884906e+00 -2.82529835e-02
4.41234767e-01 8.74613225e-01 -3.65711153e-01 8.13589454e-01
-1.08185075e-01 1.02998984e+00 -3.03323805e-01 5.90104386e-02
3.97949040e-01 2.43282691e-01 6.06917918e-01 1.03885996e+00
3.28958690e-01 1.69863716e-01 6.28209040e-02 1.13534009e+00
4.44354028e-01 -6.70384288e-01 -3.14346552e-01 -2.66546816e-01
2.58314222e-01 7.43463516e-01 -7.00265944e-01 -5.80115438e-01
2.25037441e-01 8.07181478e-01 1.50115043e-01 4.70781833e-01
-7.61820257e-01 1.72867760e-01 9.63446856e-01 3.81350428e-01
-1.33115975e-02 -1.39740929e-01 -3.23404729e-01 -9.87253010e-01
-6.42013192e-01 -4.14227545e-01 8.06251824e-01 -5.82980812e-01
-1.21351182e+00 9.28523779e-01 -3.73830676e-01 -9.07231569e-01
-6.84422374e-01 -3.09727758e-01 -1.15646696e+00 1.04580462e+00
-1.29549730e+00 -1.00394642e+00 1.98698401e-01 3.95070881e-01
4.42066848e-01 4.60089684e-01 1.21766949e+00 -1.48027748e-01
-9.86942112e-01 1.44670591e-01 5.25388680e-02 -2.14440569e-01
1.56718835e-01 -1.35147500e+00 8.31512094e-01 4.86251414e-01
-2.38241360e-01 9.02913511e-01 8.07934999e-01 -1.03065610e+00
-1.02452707e+00 -1.41114450e+00 1.08260119e+00 -8.15578222e-01
7.43262947e-01 5.08475825e-02 -1.42348814e+00 9.72749710e-01
-1.96989685e-01 -2.17006020e-02 7.60676801e-01 1.17982119e-01
1.48005292e-01 3.16880792e-01 -1.04856730e+00 7.41306901e-01
7.39517391e-01 -4.38404649e-01 -7.21363962e-01 4.32748020e-01
8.79401684e-01 -3.15847099e-01 -1.01285708e+00 2.10387096e-01
2.66523182e-01 -2.95607746e-01 1.08268118e+00 -1.38990831e+00
4.23923463e-01 -4.74237874e-02 5.30250847e-01 -1.53376937e+00
-8.74852598e-01 -6.99112058e-01 -7.55473256e-01 4.97974485e-01
5.01996458e-01 -8.34963560e-01 7.89301932e-01 8.63814354e-01
-2.46636182e-01 -1.19672108e+00 -8.52466047e-01 -4.89720255e-01
8.27457085e-02 -2.06457600e-01 6.59992874e-01 6.42756283e-01
2.84820110e-01 1.68183476e-01 -1.96301311e-01 2.75581360e-01
2.12690458e-01 2.52494011e-02 -3.28551620e-01 -1.25121200e+00
-4.20214593e-01 -6.32163763e-01 -3.94508511e-01 -6.77416980e-01
-1.07114784e-01 -8.02739501e-01 7.00851306e-02 -1.74176049e+00
3.11168253e-01 -4.80395168e-01 -7.74972856e-01 6.94848657e-01
-6.24386132e-01 -1.45214036e-01 -1.69545978e-01 4.69184339e-01
-4.78432566e-01 5.89937210e-01 1.21963739e+00 -6.56316057e-02
-6.20352507e-01 3.39160889e-01 -6.73470378e-01 5.65388501e-01
7.57249892e-01 -4.74020958e-01 -4.16262358e-01 -3.39067578e-01
1.58841982e-01 6.27663136e-01 6.91247225e-01 -8.75122428e-01
1.66795060e-01 -3.22280854e-01 6.00008667e-01 -6.58113658e-01
5.22473037e-01 -3.51274103e-01 6.03810012e-01 1.39028728e+00
-6.75707579e-01 2.57303029e-01 1.82726905e-01 1.08926368e+00
3.24236415e-02 3.86885405e-01 6.30841017e-01 -1.83668911e-01
-3.94502550e-01 8.23587418e-01 -1.12378788e+00 -1.42493635e-01
8.75991642e-01 2.89769080e-02 -2.48876765e-01 -5.02723873e-01
-1.40011370e+00 4.63236094e-01 2.60329396e-02 3.69478643e-01
5.14746308e-01 -1.17935002e+00 -6.42984927e-01 2.67012477e-01
-1.68554559e-01 -7.69273713e-02 7.47990966e-01 7.84146130e-01
-4.47120279e-01 8.36878181e-01 -1.02370590e-01 -7.85097778e-01
-6.25317216e-01 5.27466953e-01 6.38051808e-01 -9.07742023e-01
-8.84397030e-01 6.25328183e-01 2.37086400e-01 -1.16635069e-01
-1.78053930e-01 -8.62962127e-01 -1.69663772e-01 -1.55649781e-01
7.03548074e-01 2.14570090e-02 -2.32213333e-01 -1.46535322e-01
-3.67210299e-01 1.75762419e-02 -2.20923185e-01 1.00942202e-01
1.45076156e+00 -1.61308408e-01 2.51327842e-01 6.58788025e-01
7.63856113e-01 -1.07246053e+00 -1.53097272e+00 -2.40786970e-01
1.37226522e-01 2.89238602e-01 1.41900837e-01 -1.03361666e+00
-6.99893534e-01 1.06985021e+00 7.11256564e-01 3.97435397e-01
1.01271391e+00 1.44980118e-01 1.03594577e+00 1.66444272e-01
-4.52929586e-02 -4.27415758e-01 -2.02523265e-02 4.60684896e-01
5.95853806e-01 -8.55005741e-01 -4.71003443e-01 1.70107245e-01
-4.82652634e-01 9.32978213e-01 3.92999053e-01 -2.81829655e-01
8.17366123e-01 2.36940414e-01 -1.27695307e-01 -4.43743080e-01
-1.60749507e+00 1.60508499e-01 2.39342988e-01 5.78876197e-01
3.52740645e-01 4.45397824e-01 2.17037901e-01 8.86335433e-01
1.16518483e-01 2.82233566e-01 4.40845191e-01 7.34036624e-01
-4.06872332e-01 -8.45566154e-01 -2.92484164e-01 8.42128932e-01
-3.68205994e-01 -2.16009110e-01 9.94567573e-02 4.50788885e-01
-3.54129791e-01 3.06361914e-01 6.67759955e-01 -1.80356149e-02
1.01152211e-01 3.33637774e-01 1.98505878e-01 -7.92814195e-01
-6.21381879e-01 -2.34079614e-01 -2.45532736e-01 -6.32647932e-01
1.90204859e-01 -6.89757645e-01 -1.44936037e+00 -1.79330721e-01
1.30030677e-01 -1.56778261e-01 1.58883691e-01 7.32108772e-01
8.82579148e-01 1.28505874e+00 3.18720847e-01 -5.34063935e-01
-7.73820162e-01 -7.91662812e-01 -2.35094398e-01 1.69459879e-01
9.35106814e-01 -4.49946404e-01 -1.11375116e-01 1.67591259e-01] | [7.8302531242370605, 5.911077976226807] |
7f90d7ba-f84a-4af6-97da-5cff11d0c686 | resunet-an-advanced-architecture-for-medical | 1911.07067 | null | https://arxiv.org/abs/1911.07067v1 | https://arxiv.org/pdf/1911.07067v1.pdf | ResUNet++: An Advanced Architecture for Medical Image Segmentation | Accurate computer-aided polyp detection and segmentation during colonoscopy examinations can help endoscopists resect abnormal tissue and thereby decrease chances of polyps growing into cancer. Towards developing a fully automated model for pixel-wise polyp segmentation, we propose ResUNet++, which is an improved ResUNet architecture for colonoscopic image segmentation. Our experimental evaluations show that the suggested architecture produces good segmentation results on publicly available datasets. Furthermore, ResUNet++ significantly outperforms U-Net and ResUNet, two key state-of-the-art deep learning architectures, by achieving high evaluation scores with a dice coefficient of 81.33%, and a mean Intersection over Union (mIoU) of 79.27% for the Kvasir-SEG dataset and a dice coefficient of 79.55%, and a mIoU of 79.62% with CVC-612 dataset. | ['Thomas de Lange', 'Michael A. Riegler', 'Pal Halvorsen', 'Dag Johansen', 'Debesh Jha', 'Pia H. Smedsrud', 'Havard D. Johansen'] | 2019-11-16 | null | null | null | null | ['polyp-segmentation'] | ['computer-vision'] | [ 7.77212111e-03 2.68587530e-01 -2.40979642e-01 -1.02162413e-01
-8.48788798e-01 -6.55406952e-01 -5.47075970e-03 4.49049294e-01
-4.83078271e-01 4.52326894e-01 -1.72329053e-01 -9.20978785e-01
1.71138719e-01 -7.64015019e-01 -7.94797003e-01 -5.75768948e-01
-3.01045477e-01 2.30924621e-01 3.86588871e-01 2.67148137e-01
3.32958326e-02 -6.94324151e-02 -5.16703725e-01 5.11752486e-01
1.44376814e+00 9.87292647e-01 1.17822751e-01 1.15966940e+00
2.19309539e-01 4.36020970e-01 -3.32110435e-01 -5.95512450e-01
4.65542853e-01 -4.01092619e-01 -8.66497219e-01 -2.83768803e-01
5.11117101e-01 -2.84683168e-01 -1.59929588e-01 1.25382459e+00
5.21279037e-01 -1.52989596e-01 7.23541498e-01 -1.34433404e-01
-6.98032916e-01 7.42352307e-01 -8.73996139e-01 5.03864646e-01
7.07972236e-03 3.06664497e-01 5.64269304e-01 -2.10802630e-01
4.37276721e-01 6.71943247e-01 1.17913175e+00 3.27228427e-01
-7.96194315e-01 -2.23166957e-01 -1.18343011e-01 -4.93519843e-01
-1.11182964e+00 4.05292779e-01 -1.62491038e-01 -4.72439349e-01
9.61583257e-01 5.36769092e-01 1.13732100e+00 3.17987740e-01
7.11139679e-01 1.20818365e+00 7.75200248e-01 -3.30099523e-01
-7.94865787e-02 -2.06934869e-01 5.24850525e-02 1.20302653e+00
8.22849691e-01 -1.48079991e-02 5.19890845e-01 9.18186903e-02
1.15267909e+00 -4.66367863e-02 -4.67984527e-01 -2.40610138e-01
-1.46072459e+00 6.04825497e-01 1.24134588e+00 4.64151889e-01
-3.90149087e-01 1.81085587e-01 6.18804097e-01 -1.39476717e-01
1.18002065e-01 8.63085926e-01 -1.90753043e-01 1.80110365e-01
-8.37481201e-01 -1.47913694e-01 7.61959732e-01 9.08184409e-01
-3.19985412e-02 -1.91486895e-01 -3.36753696e-01 5.78309715e-01
2.91173249e-01 3.53501141e-01 1.04672515e+00 -7.20018625e-01
2.18834057e-01 9.57132399e-01 1.69909209e-01 -7.10341454e-01
-6.74652696e-01 -8.63834620e-01 -1.14561689e+00 -1.62883684e-01
5.82123399e-01 -3.40224385e-01 -1.45254362e+00 1.04979992e+00
1.19994521e-01 2.67118365e-01 1.02077462e-01 9.79800582e-01
1.24540305e+00 4.39772636e-01 1.32301375e-01 2.11189270e-01
1.50221252e+00 -1.29870892e+00 -3.26023012e-01 -2.38328591e-01
1.01402962e+00 -7.54717588e-01 7.59184778e-01 5.60648024e-01
-1.34240067e+00 -5.87128282e-01 -1.25605810e+00 -2.14817554e-01
7.14347214e-02 5.58983982e-01 6.92082524e-01 9.96668994e-01
-1.07503724e+00 3.87056142e-01 -1.41364181e+00 -1.70781597e-01
7.93727815e-01 4.02284235e-01 9.46892425e-02 -7.65890554e-02
-7.30385363e-01 6.80417597e-01 3.74790668e-01 3.91851179e-02
-9.30305660e-01 -1.03572345e+00 -9.21317518e-01 2.66312603e-02
1.40527442e-01 -1.17652893e+00 1.62371492e+00 -5.47536075e-01
-1.21455574e+00 1.00524342e+00 2.66939461e-01 -1.18118334e+00
8.32716823e-01 -1.35972291e-01 -2.10764334e-02 2.77178586e-01
-4.07720022e-02 9.69078720e-01 -1.11949388e-02 -9.25563037e-01
-9.26469088e-01 -1.74167812e-01 -5.05862106e-03 3.43968660e-01
4.76736054e-02 -5.72216153e-01 -7.80275285e-01 -4.57960099e-01
3.42599116e-02 -1.16033900e+00 -1.01924372e+00 2.44005218e-01
-6.61812603e-01 2.42704242e-01 2.68099368e-01 -9.43917990e-01
1.35909986e+00 -1.83846807e+00 -3.35093915e-01 1.78597137e-01
5.09436369e-01 1.09849238e+00 9.75702107e-02 -5.57021558e-01
1.12286411e-01 3.90647292e-01 -5.53208351e-01 5.31277321e-02
-4.84032094e-01 -1.36650845e-01 5.44082701e-01 5.22398889e-01
-2.43623942e-01 1.28656709e+00 -1.28409970e+00 -5.00568449e-01
7.19131827e-01 3.90825897e-01 -7.39254057e-01 -5.89662120e-02
-1.63316011e-01 3.13012093e-01 -4.67373401e-01 6.30039155e-01
6.86106265e-01 -6.50091469e-01 3.42271537e-01 -1.85711250e-01
-1.40614823e-01 9.55344066e-02 -7.97891736e-01 1.98958790e+00
-5.62478781e-01 6.30555630e-01 6.77616820e-02 -6.50661528e-01
5.58103323e-01 2.94950217e-01 5.70797503e-01 -5.82145035e-01
5.69695532e-01 6.28299892e-01 5.55138886e-01 -5.62236845e-01
3.16511571e-01 2.91154176e-01 1.13231562e-01 5.65518662e-02
-2.00880766e-01 -1.89806223e-01 4.97045815e-01 -4.46172357e-02
9.62175846e-01 -2.05848634e-01 8.03493440e-01 -7.97025800e-01
4.16349798e-01 3.00931603e-01 3.85471940e-01 9.24579382e-01
-5.15006542e-01 8.35446239e-01 2.96059012e-01 -8.04788291e-01
-8.39174151e-01 -9.72498178e-01 -4.35907364e-01 4.31822389e-02
4.62001592e-01 9.00005549e-02 -9.83565092e-01 -8.21610332e-01
-1.95933893e-01 4.06600952e-01 -6.35860205e-01 8.32891837e-02
-7.26429582e-01 -1.21983099e+00 4.70263213e-01 6.42186999e-01
8.38088155e-01 -6.81647420e-01 -1.02544224e+00 3.28156233e-01
-3.11006963e-01 -7.64835000e-01 -5.33613563e-01 -1.32725835e-01
-1.02104342e+00 -1.41618657e+00 -1.43184471e+00 -1.37133121e+00
9.28175211e-01 2.27899164e-01 1.36390734e+00 2.32547715e-01
-7.21039772e-01 -2.57993430e-01 -1.85566291e-01 -4.16132301e-01
-6.17071331e-01 1.90572321e-01 -7.02822983e-01 -6.33683622e-01
1.60014972e-01 7.17311352e-02 -1.51175129e+00 2.95946896e-01
-7.62269080e-01 1.63018718e-01 6.36568725e-01 9.09957290e-01
1.01167691e+00 -1.84059009e-01 1.63200587e-01 -1.05259395e+00
5.25101125e-01 -2.39130259e-01 -7.05830574e-01 3.23263437e-01
-5.74490130e-01 -5.25488377e-01 4.96490806e-01 -2.87543356e-01
-8.94225717e-01 1.24005444e-01 -2.46543124e-01 -1.99776683e-02
2.52554230e-02 6.16003394e-01 8.15822184e-01 -2.54170299e-01
1.04519022e+00 1.17616348e-01 6.92185163e-02 -3.01814601e-02
2.64746428e-01 4.97455418e-01 7.01677024e-01 7.37018064e-02
-2.84005795e-02 4.85565305e-01 -3.02696079e-01 -4.52482343e-01
-6.24298632e-01 -7.95420825e-01 -3.00246119e-01 2.42493898e-01
1.14496052e+00 -1.03104353e+00 -5.40095329e-01 5.39692581e-01
-7.49598801e-01 -3.87239933e-01 -3.74376267e-01 7.21706450e-01
-1.92978755e-01 5.96991658e-01 -1.18858898e+00 -1.99215189e-01
-1.02900243e+00 -1.70408309e+00 7.21505880e-01 8.25160205e-01
-3.92606527e-01 -1.29289174e+00 -1.97329912e-02 1.66032106e-01
4.95142698e-01 6.43759310e-01 6.36243165e-01 -6.96455002e-01
-6.54033720e-01 -6.01317108e-01 -6.11518741e-01 2.56641030e-01
2.14582652e-01 -1.05801858e-01 -4.53607053e-01 -4.67024356e-01
-2.39795819e-01 1.33285701e-01 1.16039324e+00 1.47171128e+00
1.34224093e+00 5.48820160e-02 -8.06706548e-01 1.16887474e+00
1.47661483e+00 7.83822954e-01 5.70306957e-01 3.00336540e-01
5.63367784e-01 -6.33417889e-02 4.15575325e-01 1.73587427e-01
3.14164132e-01 -6.36217892e-02 6.94669425e-01 -6.59510612e-01
-4.66523230e-01 -2.69099716e-02 -5.33492804e-01 7.70512700e-01
2.21083000e-01 -4.54021275e-01 -1.22131228e+00 1.04682839e+00
-1.61055911e+00 -2.63319492e-01 -5.74277043e-01 1.92070889e+00
6.97411954e-01 7.11649582e-02 -1.14215955e-01 -3.59944075e-01
6.03430152e-01 -2.24836603e-01 -6.53571248e-01 -2.57850140e-01
2.22388536e-01 1.72950327e-01 6.69122815e-01 5.38875520e-01
-1.59442449e+00 4.98305142e-01 6.19518518e+00 7.12905049e-01
-1.08705592e+00 -1.93215773e-01 1.15928459e+00 3.28779131e-01
9.84942541e-02 -5.58491349e-01 -3.44788313e-01 3.92873168e-01
6.06104136e-01 -4.95478213e-02 -2.03162000e-01 7.86126554e-01
-2.37130255e-01 -2.22168684e-01 -8.10361147e-01 5.81660807e-01
-2.33209595e-01 -1.58676922e+00 -1.68917149e-01 -1.19405640e-02
1.36606717e+00 4.08717513e-01 3.49583656e-01 1.88390866e-01
5.35477042e-01 -1.09089100e+00 -7.35525489e-02 1.01840086e-01
1.02638364e+00 -5.74034274e-01 1.24117589e+00 9.12685171e-02
-1.11299646e+00 2.48227939e-01 -3.20290506e-01 4.74427998e-01
1.21255264e-01 6.73048735e-01 -1.37901795e+00 5.51367342e-01
5.95486403e-01 8.86155248e-01 -4.40034896e-01 2.14129496e+00
-2.85531227e-02 5.19349277e-01 -3.66500437e-01 -1.64031997e-01
6.70776010e-01 -4.09555174e-02 4.64949638e-01 1.63704801e+00
6.13988757e-01 -4.15088870e-02 1.85405597e-01 6.73233271e-01
-1.84781224e-01 1.68069318e-01 -1.36527382e-02 2.80846328e-01
2.13201389e-01 1.30809236e+00 -1.15862989e+00 -6.47499859e-01
-1.82783082e-01 6.71847463e-01 -4.59695429e-01 -2.58651786e-02
-9.70285058e-01 -4.11697119e-01 8.69101435e-02 -1.49156153e-01
1.45995378e-01 3.86933982e-01 -5.57229757e-01 -9.02042985e-01
-1.43748268e-01 -8.67354095e-01 5.01135826e-01 -3.05560738e-01
-1.02331650e+00 8.44310343e-01 -4.28495914e-01 -1.53262162e+00
2.54756138e-02 -9.51011658e-01 -7.34750032e-01 8.19883823e-01
-1.79428947e+00 -1.03278136e+00 -5.47538519e-01 -6.44562487e-03
4.89467114e-01 5.43114617e-02 7.71111310e-01 2.03403816e-01
-5.01265943e-01 7.89617181e-01 2.88313746e-01 4.39241439e-01
3.64472836e-01 -1.83432317e+00 8.25535595e-01 8.39754045e-01
-2.11869985e-01 6.52133167e-01 2.25754738e-01 -6.29707694e-01
-8.00525725e-01 -1.39169443e+00 2.42910787e-01 -1.27298340e-01
4.03384954e-01 5.02711177e-01 -5.65215111e-01 6.54287577e-01
2.42316902e-01 1.98912233e-01 7.53767669e-01 -4.22904700e-01
1.75091639e-01 2.91449517e-01 -1.46649814e+00 7.71148860e-01
5.86111009e-01 2.48300910e-01 -2.52069324e-01 4.89975601e-01
8.99473071e-01 -1.36461127e+00 -1.21925223e+00 6.53494537e-01
6.73038483e-01 -1.02934456e+00 1.17298353e+00 4.94183712e-02
5.12041032e-01 -1.42049477e-01 5.27678251e-01 -1.29753375e+00
-3.13474327e-01 -5.59115946e-01 2.30751425e-01 1.93801463e-01
8.64631414e-01 -5.48861265e-01 1.09739876e+00 3.16967487e-01
-8.74851644e-01 -1.15833247e+00 -7.61099100e-01 -2.43397772e-01
3.34957957e-01 -6.45459518e-02 3.43382657e-01 8.92119169e-01
-1.78687707e-01 -4.28078383e-01 1.35719433e-01 8.31286162e-02
4.34356868e-01 1.33147538e-01 2.85859644e-01 -9.13069248e-01
-1.73464641e-01 -7.58928061e-01 -5.26168384e-02 -1.39835644e+00
-7.49805510e-01 -9.77376044e-01 -1.06137298e-01 -2.14709973e+00
2.88510650e-01 -3.53244662e-01 -3.81310612e-01 2.71609187e-01
-4.14765388e-01 3.26740026e-01 -2.18621701e-01 5.99414073e-02
-5.57304025e-01 -3.08261484e-01 2.10303211e+00 -2.16613278e-01
-4.81759429e-01 4.50452387e-01 -8.24247062e-01 1.03183115e+00
8.04977059e-01 -1.00211740e-01 -1.61599174e-01 -6.07373774e-01
-1.23069361e-01 2.72844136e-01 8.12676549e-02 -1.14053106e+00
6.62900358e-02 3.14622760e-01 5.99402010e-01 -6.46435320e-01
-1.80243149e-01 -5.89103937e-01 -1.57698989e-01 1.55062556e+00
-4.30828094e-01 -1.81647107e-01 4.51908708e-01 4.19297695e-01
-2.96486795e-01 -2.19411135e-01 1.14058411e+00 -6.08076572e-01
-4.40767974e-01 2.75259495e-01 -2.34452963e-01 9.57573950e-03
1.10301054e+00 -3.00228089e-01 -4.37578887e-01 1.44459248e-01
-6.09852076e-01 6.21011972e-01 2.39810303e-01 5.35422526e-02
4.99970078e-01 -9.31493640e-01 -7.64480948e-01 2.51427591e-01
-9.94263366e-02 7.39032805e-01 5.39558411e-01 1.17993832e+00
-1.55719709e+00 8.68499219e-01 1.19600378e-01 -8.19174886e-01
-1.09699559e+00 1.35326996e-01 9.76669908e-01 -8.86278808e-01
-7.57596493e-01 1.63192940e+00 3.31098735e-01 -4.15397733e-01
1.69558916e-02 -1.39285409e+00 -1.10191293e-01 -4.26926941e-01
4.75339472e-01 3.38323087e-01 3.01448703e-01 -1.13165095e-01
-1.17727198e-01 3.76821131e-01 -4.62038875e-01 5.91830373e-01
7.60927260e-01 1.27407953e-01 1.13911346e-01 -3.78238678e-01
9.17602897e-01 -3.18510085e-01 -1.13533354e+00 -2.08957806e-01
-3.09164256e-01 -3.08942974e-01 3.03356737e-01 -1.43049419e+00
-1.24285007e+00 7.44277120e-01 1.02950680e+00 3.28983724e-01
1.05111659e+00 -4.76984650e-01 1.33666801e+00 -7.43272295e-03
5.28534800e-02 -4.14173007e-01 -1.48270637e-01 1.56607777e-01
4.07544494e-01 -1.42320037e+00 4.48815562e-02 -5.09961426e-01
-5.74475050e-01 9.13971603e-01 6.69651449e-01 -5.19455791e-01
4.68317002e-01 2.23218709e-01 3.15839559e-01 -8.16911459e-02
-1.26810372e-01 9.74651724e-02 7.99315989e-01 5.50430477e-01
8.81163716e-01 4.68552560e-01 -4.63999867e-01 4.52119946e-01
-1.86445847e-01 1.35711476e-01 5.09810209e-01 7.30754435e-01
-5.96761167e-01 -6.81492925e-01 -1.02301389e-01 8.01477373e-01
-1.04786539e+00 -2.45758370e-01 1.22612901e-01 1.00727713e+00
1.27866581e-01 6.34239018e-01 -4.70211759e-04 9.25128907e-02
3.24969411e-01 -7.15376616e-01 3.17909151e-01 -6.31139994e-01
-1.09454894e+00 5.75053632e-01 1.10821920e-02 -3.02145004e-01
-2.62154698e-01 -3.74190778e-01 -1.39733100e+00 8.52024332e-02
-3.39611620e-01 1.19547099e-01 5.13992250e-01 4.59152609e-01
9.94719639e-02 1.09188318e+00 -7.73780746e-03 -6.10516429e-01
-3.40482295e-01 -8.73273015e-01 -2.15961844e-01 1.74136236e-01
4.64748412e-01 1.39504746e-01 -1.88106559e-02 -1.15378030e-01] | [14.492087364196777, -2.848069667816162] |
06c4bd54-64dd-4eab-99bf-f651b008747e | paradise-exploiting-parallel-data-for | 2108.01887 | null | https://arxiv.org/abs/2108.01887v1 | https://arxiv.org/pdf/2108.01887v1.pdf | PARADISE: Exploiting Parallel Data for Multilingual Sequence-to-Sequence Pretraining | Despite the success of multilingual sequence-to-sequence pretraining, most existing approaches rely on monolingual corpora, and do not make use of the strong cross-lingual signal contained in parallel data. In this paper, we present PARADISE (PARAllel & Denoising Integration in SEquence-to-sequence models), which extends the conventional denoising objective used to train these models by (i) replacing words in the noised sequence according to a multilingual dictionary, and (ii) predicting the reference translation according to a parallel corpus instead of recovering the original sequence. Our experiments on machine translation and cross-lingual natural language inference show an average improvement of 2.0 BLEU points and 6.7 accuracy points from integrating parallel data into pretraining, respectively, obtaining results that are competitive with several popular models at a fraction of their computational cost. | ['Mikel Artetxe', 'Machel Reid'] | 2021-08-04 | null | https://aclanthology.org/2022.naacl-main.58 | https://aclanthology.org/2022.naacl-main.58.pdf | naacl-2022-7 | ['cross-lingual-natural-language-inference'] | ['natural-language-processing'] | [ 3.51978183e-01 -3.16574812e-01 -1.73497915e-01 -3.44150662e-01
-1.45859349e+00 -1.00308669e+00 8.32699060e-01 -8.03617612e-02
-8.10302556e-01 1.00982630e+00 2.79787391e-01 -7.37924755e-01
6.08418882e-01 -3.00719142e-01 -1.14325392e+00 -6.49063647e-01
5.06715119e-01 6.28659487e-01 -1.15737736e-01 -3.76261741e-01
3.61189470e-02 -3.10597494e-02 -1.00556314e+00 3.55704635e-01
1.09444821e+00 3.99469465e-01 4.88577425e-01 5.81449091e-01
-2.42328107e-01 5.28859079e-01 -4.71283585e-01 -8.13827515e-01
2.73315132e-01 -9.94116902e-01 -5.39924145e-01 -1.80052593e-01
5.58099687e-01 -9.37863141e-02 -1.25915691e-01 1.27624249e+00
6.25217438e-01 -1.07135482e-01 4.21509355e-01 -4.76022899e-01
-7.47876525e-01 9.02620792e-01 -5.99420130e-01 1.75380021e-01
3.87808323e-01 9.77336839e-02 1.12936532e+00 -1.11179590e+00
9.62540388e-01 1.24430788e+00 9.40750182e-01 4.08246994e-01
-1.55936503e+00 -6.31153345e-01 -1.59421772e-01 2.81225383e-01
-1.33556187e+00 -7.92273283e-01 3.60113144e-01 -2.97934175e-01
1.37322843e+00 7.98868909e-02 2.90609390e-01 1.39592469e+00
4.69989270e-01 8.02617848e-01 1.42462242e+00 -7.91501582e-01
-1.50056109e-01 -3.80825549e-02 -1.31912470e-01 5.82737088e-01
-2.00121254e-01 3.01540673e-01 -4.72239166e-01 2.85880156e-02
3.09716523e-01 -5.51086664e-01 -1.40696838e-01 6.97171167e-02
-1.24833703e+00 8.12167168e-01 -6.27622306e-02 5.33790290e-01
-4.94082540e-01 -5.32689579e-02 7.06443727e-01 7.14019656e-01
6.62893414e-01 1.10806160e-01 -5.61386764e-01 -2.94959575e-01
-1.21410656e+00 -4.60067540e-02 6.22312427e-01 9.01204526e-01
8.44176173e-01 2.93939948e-01 1.22065581e-01 9.61507678e-01
8.97639990e-02 8.92751932e-01 8.05500150e-01 -7.94600308e-01
6.58160985e-01 -2.24704165e-02 -1.78402126e-01 -5.26451170e-01
2.86510959e-02 -6.75661206e-01 -7.84906566e-01 -2.74197638e-01
4.69169587e-01 -2.54658759e-01 -8.27596545e-01 1.91319180e+00
3.80429104e-02 1.31634280e-01 2.87260264e-01 6.52540267e-01
2.93929160e-01 8.70207310e-01 -1.78616811e-02 -5.33637345e-01
1.11290097e+00 -1.00731301e+00 -8.25441241e-01 -3.68092328e-01
8.48800719e-01 -1.35751259e+00 1.13569689e+00 5.10534823e-01
-1.16378272e+00 -7.58040667e-01 -1.04408431e+00 -3.26499969e-01
-1.45598292e-01 1.40186593e-01 -2.38236655e-02 5.59707284e-01
-1.07619989e+00 6.94025517e-01 -8.39440763e-01 -2.31837675e-01
-2.04143509e-01 1.03785746e-01 -4.71954912e-01 -4.14494306e-01
-1.30461526e+00 1.29791236e+00 4.18083072e-01 -3.07356343e-02
-8.97149146e-01 -6.11108184e-01 -8.32577884e-01 -2.38362625e-01
2.00024337e-01 -5.48576593e-01 1.28240561e+00 -1.36980522e+00
-1.53594863e+00 7.96532154e-01 -5.10106027e-01 -6.40603840e-01
7.29822457e-01 -4.43518966e-01 -3.44722182e-01 -2.14216784e-01
2.30626732e-01 5.58125615e-01 5.49170613e-01 -1.03463733e+00
-6.24394357e-01 -3.37227553e-01 -4.18635279e-01 3.42606157e-01
3.10222898e-02 1.58005401e-01 -5.73703706e-01 -7.86757112e-01
-5.62485605e-02 -9.64490950e-01 -1.43140048e-01 -6.86590075e-01
-2.87147433e-01 -1.04877383e-01 3.97518128e-01 -1.44127786e+00
1.06819499e+00 -1.79815900e+00 4.88381892e-01 4.36604163e-03
-4.15424734e-01 4.24996078e-01 -5.92254698e-01 6.36564016e-01
-3.84528413e-02 -7.57660195e-02 -3.72029513e-01 -5.31415284e-01
-5.65228052e-02 5.23153305e-01 -2.63362944e-01 4.86421287e-01
5.74176759e-02 9.33741093e-01 -1.00592315e+00 -3.09446126e-01
3.85041796e-02 5.91497004e-01 -3.83743286e-01 6.17673062e-02
-1.26780912e-01 6.25434041e-01 1.66016176e-01 2.33750284e-01
4.92248178e-01 4.19829071e-01 6.79775238e-01 7.32351746e-03
-1.62580058e-01 9.10840213e-01 -7.36882389e-01 2.10331368e+00
-6.61777794e-01 5.79147696e-01 3.25515866e-02 -9.95924592e-01
7.87706137e-01 5.63059270e-01 1.63902387e-01 -9.94789898e-01
-5.69899380e-02 7.56984591e-01 2.35372484e-01 -3.44511122e-01
3.68956864e-01 -6.13510787e-01 9.08583496e-03 4.51934367e-01
3.94819736e-01 8.81444383e-03 4.70402420e-01 -4.34559062e-02
8.85521770e-01 6.68839514e-01 4.59070385e-01 -2.83940256e-01
7.56878853e-01 2.12243386e-02 7.18010366e-01 5.71893632e-01
1.69575661e-01 4.30681944e-01 3.22244465e-01 -2.79077530e-01
-1.40675437e+00 -1.08212709e+00 5.85919656e-02 1.01647615e+00
-4.81577814e-01 -4.64179188e-01 -8.98986995e-01 -7.67239869e-01
-3.52507472e-01 9.85699117e-01 -2.21774295e-01 2.59314805e-01
-1.02710438e+00 -9.07755375e-01 8.93510163e-01 3.55567902e-01
2.09818453e-01 -8.45158458e-01 2.94717163e-01 5.00650764e-01
-7.80889690e-01 -1.13306558e+00 -8.63564491e-01 4.25610900e-01
-9.59009349e-01 -6.84066176e-01 -6.34976149e-01 -9.18066382e-01
3.45706373e-01 1.02528017e-02 1.43310738e+00 -1.50837675e-01
3.86286110e-01 -3.32942635e-01 -2.33543932e-01 -8.57162401e-02
-1.04359198e+00 3.44791532e-01 2.34638482e-01 -2.77313888e-01
5.88753998e-01 -6.42203033e-01 4.34366614e-02 9.13313329e-02
-7.94312954e-01 -4.09130305e-02 8.76173079e-01 1.21180320e+00
7.52034426e-01 -4.19469029e-01 7.27316141e-01 -9.08947229e-01
4.91034538e-01 -2.81564265e-01 -6.05903745e-01 2.37438306e-01
-7.54862368e-01 2.30991960e-01 8.46304655e-01 -3.80159527e-01
-9.62429225e-01 1.61452562e-01 -7.01263607e-01 -1.83645174e-01
-7.83620998e-02 6.70655549e-01 -2.04259500e-01 2.53521621e-01
6.62635267e-01 7.82078445e-01 1.89805273e-02 -6.43086553e-01
5.82545936e-01 6.05073333e-01 6.47638321e-01 -5.77419281e-01
7.19173074e-01 -1.06362395e-01 -3.86245638e-01 -6.31374538e-01
-8.08176875e-01 -4.14719999e-01 -9.67620850e-01 1.79836988e-01
7.68540859e-01 -1.13809907e+00 -1.61120430e-01 2.59635955e-01
-1.36293411e+00 -2.07781613e-01 6.74382374e-02 7.10857272e-01
-5.46565056e-01 7.34854817e-01 -1.01100516e+00 -4.27866608e-01
-4.56877679e-01 -1.29570305e+00 8.66920352e-01 -5.05733728e-01
-3.11190605e-01 -1.04874778e+00 4.16757405e-01 4.37521368e-01
2.42844447e-01 -1.99727461e-01 9.45071936e-01 -6.91798270e-01
-3.66473764e-01 -1.44138649e-01 7.85648823e-02 8.45639408e-01
1.18180178e-01 -3.33503336e-01 -7.22368062e-01 -3.79248381e-01
1.96306959e-01 -3.13927352e-01 7.04011261e-01 1.87235922e-01
2.82781959e-01 -2.82525569e-01 -1.65435467e-02 5.61986089e-01
1.54351926e+00 8.48507658e-02 6.57300830e-01 2.64388204e-01
6.00105166e-01 5.13565183e-01 3.20482969e-01 -2.13601544e-01
3.08252156e-01 6.73003078e-01 -5.13737537e-02 3.22078019e-02
-2.81963378e-01 -5.63834369e-01 9.08992231e-01 1.83014846e+00
-5.73557578e-02 -1.66675672e-01 -7.62075603e-01 7.09638894e-01
-1.61692834e+00 -9.69591975e-01 -3.15165371e-01 2.20023203e+00
1.25749862e+00 5.44034205e-02 -5.28422073e-02 -6.62901103e-02
5.14551282e-01 -2.31266692e-02 -1.87574953e-01 -5.75941026e-01
-4.39749330e-01 3.14171135e-01 6.50067747e-01 9.97647464e-01
-6.64734662e-01 1.27694702e+00 6.61268568e+00 1.14050412e+00
-1.18101633e+00 4.53460723e-01 4.64335978e-01 1.77001134e-01
-3.41763645e-01 1.22051463e-01 -8.83701801e-01 4.28528041e-01
1.54129136e+00 -1.90137122e-02 6.16579533e-01 3.67799044e-01
2.92680740e-01 1.12747759e-01 -1.08499491e+00 7.09544659e-01
2.70339638e-01 -1.03551519e+00 1.12439811e-01 -1.40543267e-01
9.29390192e-01 4.73104298e-01 -1.99145630e-01 4.96286660e-01
4.66810405e-01 -9.57670271e-01 7.26102531e-01 2.48760208e-01
7.65303075e-01 -8.61699879e-01 9.54217196e-01 7.05198765e-01
-8.62589538e-01 5.65452516e-01 -3.67522091e-01 1.77185871e-02
3.55798811e-01 4.66011703e-01 -8.53041112e-01 8.72307599e-01
3.34463537e-01 7.96798706e-01 -2.52880514e-01 4.60391045e-01
-5.50210536e-01 1.01266110e+00 -2.63688833e-01 2.71898597e-01
4.24636960e-01 -5.37699044e-01 4.43566650e-01 1.67331767e+00
4.90720421e-01 -4.54666227e-01 2.09522665e-01 4.28093255e-01
-2.90742159e-01 4.69209284e-01 -4.99392420e-01 -5.34328930e-02
1.57325730e-01 8.36174488e-01 -2.75072783e-01 -6.31761312e-01
-7.80396402e-01 1.41640937e+00 4.01478112e-01 3.20047796e-01
-7.19456851e-01 -2.51171082e-01 4.62810397e-01 -1.26090825e-01
3.59571218e-01 -4.52914625e-01 -3.62005979e-01 -1.22647309e+00
1.66702151e-01 -1.54542315e+00 -6.99863657e-02 -5.31050384e-01
-1.32661390e+00 8.81374359e-01 -4.43047762e-01 -1.09130847e+00
-6.95748687e-01 -4.01702881e-01 -1.38547376e-01 1.46691310e+00
-1.56508636e+00 -1.27169657e+00 5.54024696e-01 3.35814059e-01
7.48578250e-01 -1.43953398e-01 9.97782588e-01 6.35208070e-01
-2.72335768e-01 6.06625378e-01 6.01094306e-01 1.67525217e-01
1.04532003e+00 -1.22544765e+00 8.28091919e-01 1.11952162e+00
3.87488842e-01 8.34257782e-01 7.77483463e-01 -7.22614408e-01
-1.33566380e+00 -9.65114057e-01 1.70800304e+00 -5.56195974e-01
9.35776353e-01 -5.36074102e-01 -1.05404699e+00 9.70061898e-01
7.01117098e-01 -5.04080892e-01 6.60128474e-01 1.42457157e-01
-5.46227098e-01 1.29995914e-02 -7.44579673e-01 6.59275711e-01
1.00734651e+00 -8.03439319e-01 -8.08194876e-01 2.39949480e-01
4.74870384e-01 -3.24748784e-01 -8.09738100e-01 2.38311008e-01
6.35915995e-01 -7.35328853e-01 8.68313611e-01 -6.69998229e-01
5.24967015e-01 -2.61088461e-01 -3.99978101e-01 -1.69597065e+00
-1.74352884e-01 -5.72490335e-01 3.28818023e-01 1.23101842e+00
6.48936331e-01 -4.67148811e-01 4.17957634e-01 -4.87947881e-01
-3.40304673e-01 -3.48413110e-01 -1.00550997e+00 -9.59994316e-01
5.70760250e-01 -4.57427770e-01 1.18994452e-01 1.05514061e+00
-2.45623827e-01 8.72768283e-01 -7.63179779e-01 5.97324828e-03
5.75632572e-01 -1.06882043e-01 6.73107922e-01 -7.45835125e-01
-5.96885383e-01 -3.53627145e-01 3.61228809e-02 -1.42779005e+00
4.49442178e-01 -1.29182947e+00 4.60989475e-01 -1.33460557e+00
1.99240386e-01 -1.03427552e-01 -8.55595469e-02 3.29500079e-01
-4.29714859e-01 6.22519970e-01 1.27551779e-01 2.46092498e-01
-2.55687684e-01 5.49789488e-01 1.03172910e+00 -6.37275130e-02
9.28519815e-02 -3.07685792e-01 -4.99603301e-01 6.22313559e-01
6.42994404e-01 -6.31451190e-01 -1.39564231e-01 -9.31796968e-01
5.83858974e-02 2.55280703e-01 -2.15916663e-01 -6.68252885e-01
-1.12253502e-01 8.23552236e-02 2.97478735e-01 -5.38106978e-01
2.62603462e-01 -6.59881413e-01 2.52696037e-01 6.51157439e-01
-2.46458039e-01 5.40991068e-01 3.34740788e-01 3.86244118e-01
-4.17327344e-01 -2.58724451e-01 8.15850496e-01 -1.95780486e-01
-3.87297928e-01 -2.25244984e-01 -6.59805655e-01 6.33555744e-03
3.86819750e-01 1.76968396e-01 -1.43279076e-01 -3.08585793e-01
-7.06109464e-01 -1.17096506e-01 5.00010014e-01 4.18505400e-01
-4.36375849e-03 -1.35270655e+00 -1.14794266e+00 2.36532629e-01
-1.77730188e-01 -5.99009931e-01 2.26510484e-02 1.03655708e+00
-5.15079319e-01 6.22808874e-01 -9.81661677e-02 -6.57007515e-01
-1.27221632e+00 4.88430440e-01 2.28230745e-01 -6.16250694e-01
-3.08527499e-01 6.15389228e-01 -4.07164320e-02 -9.29863632e-01
-2.42138654e-02 -1.00324806e-02 3.87782991e-01 4.15110867e-03
4.30327833e-01 9.98785421e-02 4.72391218e-01 -9.84743893e-01
-2.64679223e-01 6.29221380e-01 -1.31650895e-01 -6.06419981e-01
1.22745299e+00 -3.18694085e-01 -2.98491538e-01 6.19426966e-01
1.21148038e+00 4.46538061e-01 -9.07128036e-01 -6.08814716e-01
4.18770313e-01 -1.80273235e-01 -1.51901484e-01 -1.05302632e+00
-6.91879511e-01 1.00716031e+00 3.96028221e-01 -4.20042336e-01
9.81990159e-01 -4.22539234e-01 1.05960333e+00 3.26656759e-01
3.80946815e-01 -9.67622161e-01 -4.07094508e-01 9.36674595e-01
7.54014015e-01 -1.17028296e+00 -1.84522435e-01 -1.70559570e-01
-4.75087941e-01 9.97472763e-01 7.74795115e-02 -1.66930676e-01
2.17963457e-01 4.72995788e-01 6.40458047e-01 4.87266898e-01
-8.01315904e-01 -6.97580948e-02 3.35730880e-01 5.48374534e-01
9.49750245e-01 -3.17457393e-02 -8.00306797e-01 2.24312320e-01
-3.52724314e-01 -1.87843442e-02 1.85109675e-01 5.43591619e-01
-2.85633326e-01 -1.71390808e+00 -4.18652713e-01 -4.19860482e-02
-8.78408134e-01 -7.30451822e-01 -2.78517306e-01 4.75439340e-01
1.90904766e-01 9.62883651e-01 -1.34353444e-01 -2.59121269e-01
2.19860896e-01 6.33366704e-01 5.81744373e-01 -4.74139839e-01
-8.48432839e-01 6.06681824e-01 3.65094900e-01 -3.02137971e-01
-3.28262806e-01 -8.60735238e-01 -8.65840435e-01 -4.57697958e-01
-1.06147408e-01 2.52905518e-01 8.01491380e-01 1.23561001e+00
7.04075024e-02 4.45759118e-01 3.07027012e-01 -7.04801977e-01
-7.46025205e-01 -1.38562655e+00 -1.13055594e-01 3.50971103e-01
2.53885567e-01 -5.02061993e-02 -1.36374190e-01 4.45660770e-01] | [11.649006843566895, 10.272026062011719] |
e8fc4957-eecd-41a2-8abd-2af3ea62c46d | a-lifetime-extended-energy-management | 2302.06236 | null | https://arxiv.org/abs/2302.06236v1 | https://arxiv.org/pdf/2302.06236v1.pdf | A Lifetime Extended Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles via Self-Learning Fuzzy Reinforcement Learning | Modeling difficulty, time-varying model, and uncertain external inputs are the main challenges for energy management of fuel cell hybrid electric vehicles. In the paper, a fuzzy reinforcement learning-based energy management strategy for fuel cell hybrid electric vehicles is proposed to reduce fuel consumption, maintain the batteries' long-term operation, and extend the lifetime of the fuel cells system. Fuzzy Q-learning is a model-free reinforcement learning that can learn itself by interacting with the environment, so there is no need for modeling the fuel cells system. In addition, frequent startup of the fuel cells will reduce the remaining useful life of the fuel cells system. The proposed method suppresses frequent fuel cells startup by considering the penalty for the times of fuel cell startups in the reward of reinforcement learning. Moreover, applying fuzzy logic to approximate the value function in Q-Learning can solve continuous state and action space problems. Finally, a python-based training and testing platform verify the effectiveness and self-learning improvement of the proposed method under conditions of initial state change, model change and driving condition change. | ['Rachid Outbib', 'Zhongliang Li', 'Liang Guo'] | 2023-02-13 | null | null | null | null | ['self-learning', 'energy-management'] | ['natural-language-processing', 'time-series'] | [-5.37073553e-01 6.52469248e-02 -4.81650054e-01 -1.02082640e-01
1.72885448e-01 -5.30662775e-01 1.27607867e-01 3.95313427e-02
-4.68379140e-01 1.31752491e+00 -6.45289302e-01 -1.84670985e-01
-3.82495612e-01 -1.12863135e+00 -7.09326327e-01 -9.42637324e-01
2.30089441e-01 2.99940109e-01 3.88922125e-01 -3.94761056e-01
3.08775783e-01 4.11747843e-01 -1.64398766e+00 -2.84202218e-01
1.16604090e+00 1.13124192e+00 5.65345168e-01 3.15300912e-01
-1.78615674e-02 7.13166416e-01 -5.23416877e-01 3.68046105e-01
-1.18431754e-01 -1.80685297e-01 -1.47646904e-01 -2.89526850e-01
-7.84150720e-01 -3.68441522e-01 -4.86025214e-01 1.01438880e+00
4.35471565e-01 5.45272708e-01 4.44330096e-01 -2.01265168e+00
-7.49071315e-02 3.56930465e-01 1.35432139e-01 1.96438566e-01
-2.16080308e-01 5.67119241e-01 1.24502862e-02 -3.86353612e-01
2.32140958e-01 1.04997265e+00 3.39129448e-01 7.63206899e-01
-4.81531620e-01 -7.98526347e-01 2.02863455e-01 7.82360911e-01
-1.56602979e+00 -2.04767674e-01 5.52712321e-01 -1.05301224e-01
1.44907343e+00 1.28529876e-01 1.29177690e+00 2.02936038e-01
6.50529027e-01 4.33909148e-01 1.03172803e+00 -2.72585541e-01
7.32367039e-01 2.03917161e-01 -2.40131781e-01 4.74741876e-01
3.82113636e-01 5.52369833e-01 1.86105832e-01 1.15522996e-01
2.67730981e-01 2.24112168e-01 2.13157654e-01 -2.17320040e-01
-4.11845833e-01 4.96799737e-01 1.39592066e-01 7.20981061e-02
-1.51941374e-01 2.93558657e-01 3.97354335e-01 1.03222154e-01
-2.66624629e-01 1.78435758e-01 -4.19566214e-01 -1.54470205e-01
-5.65880358e-01 3.99860442e-01 6.29861355e-01 1.14205849e+00
6.86023712e-01 7.07742691e-01 -1.53799728e-01 3.72402161e-01
4.38724041e-01 8.96226346e-01 6.32922053e-01 -1.33615208e+00
-8.77636597e-02 7.39904523e-01 5.15221536e-01 -3.42659891e-01
-4.36128706e-01 1.00865193e-01 -5.79405904e-01 5.10949254e-01
-2.17183128e-01 -6.23554766e-01 -7.55023062e-01 1.37524557e+00
3.32471758e-01 2.19569713e-01 4.30787772e-01 5.34731388e-01
2.63894826e-01 1.10619533e+00 1.73096731e-01 -1.10346580e+00
7.97976494e-01 -8.13376427e-01 -1.48673260e+00 2.15889383e-02
2.08363429e-01 9.67308432e-02 4.44303393e-01 1.48870736e-01
-1.23360968e+00 -4.46935266e-01 -1.55252075e+00 6.21604323e-01
-8.29691112e-01 -2.72108614e-01 3.49511296e-01 4.22243327e-01
-7.32868016e-01 5.77166080e-01 -8.53086114e-01 9.49968621e-02
1.45465359e-01 6.73335135e-01 3.16224813e-01 9.08362046e-02
-1.69379687e+00 1.33525538e+00 8.21609139e-01 1.73996598e-01
-9.99207795e-01 -5.48411965e-01 -7.03357160e-01 5.58570214e-02
6.21328533e-01 -1.65816769e-01 1.27826726e+00 -6.74463451e-01
-1.68473351e+00 -1.84209943e-01 -3.75381932e-02 -3.96736264e-01
4.32492912e-01 5.48340857e-01 -8.15784812e-01 -4.77922894e-02
-3.33875507e-01 5.64258039e-01 4.54737544e-01 -9.08200085e-01
-1.03200233e+00 -2.92748120e-02 -2.32260570e-01 3.02953392e-01
-1.99485183e-01 -6.80954099e-01 8.80978927e-02 1.74174726e-01
-6.33183658e-01 -8.27327847e-01 -3.01102668e-01 -3.77705276e-01
5.57438254e-01 -8.39847445e-01 1.08303225e+00 -2.70363748e-01
1.34819508e+00 -2.12685251e+00 -1.45408824e-01 2.81892538e-01
-6.12673879e-01 3.17507714e-01 2.41675660e-01 2.61143088e-01
4.56798702e-01 2.53792942e-01 1.55848349e-02 7.60041833e-01
1.07779987e-01 6.99596167e-01 1.41816318e-01 -1.14752941e-01
3.86782140e-01 8.83918822e-01 -1.05422449e+00 -5.47499239e-01
5.69333017e-01 2.46416032e-01 -2.63120145e-01 2.51496136e-01
-5.24938703e-01 1.87617783e-02 -5.58062017e-01 4.49343503e-01
8.30664337e-01 5.13969123e-01 2.99180865e-01 -1.83851674e-01
-5.11955202e-01 -4.38891470e-01 -1.41486537e+00 9.38120544e-01
-4.51150596e-01 9.25610363e-02 3.14093262e-01 -1.18566251e+00
8.88780296e-01 2.08776504e-01 6.95557833e-01 -1.38685524e+00
3.14567357e-01 3.53206486e-01 -1.41362756e-01 -7.35439122e-01
3.66650343e-01 -2.56709427e-01 1.27570227e-01 -6.85693622e-02
8.49694684e-02 -4.12984371e-01 6.47577763e-01 -3.08373600e-01
6.32929504e-01 1.28941596e-01 3.54499407e-02 -4.02029306e-01
7.31325388e-01 1.05315045e-01 1.18684793e+00 1.28483415e-01
-3.91845584e-01 -7.67995656e-01 2.39787504e-01 -2.32398778e-01
-8.44348192e-01 -7.92032719e-01 -1.55440465e-01 7.31740177e-01
8.21421921e-01 1.62757143e-01 -7.07510710e-01 -3.39913368e-01
2.81407654e-01 1.19582295e+00 -5.46613522e-02 -7.33182549e-01
-4.86798167e-01 -6.64244115e-01 6.76920190e-02 5.70996106e-01
4.91990238e-01 -1.05786037e+00 -8.11239898e-01 4.69996572e-01
2.32229650e-01 -7.41470039e-01 -1.56900719e-01 4.19673115e-01
-7.51091301e-01 -1.09028900e+00 -1.96983233e-01 -8.73390853e-01
6.70507073e-01 -1.52382106e-01 5.14825225e-01 3.44503999e-01
8.13542679e-02 1.80961713e-01 2.15007722e-01 -6.54922009e-01
-4.30638403e-01 -2.71416575e-01 3.27649921e-01 -5.71536601e-01
2.48764321e-01 2.18610894e-02 -4.14730757e-01 4.85659152e-01
-8.45772386e-01 -1.42594099e-01 8.85246173e-02 9.80159342e-01
9.90628481e-01 1.06262851e+00 1.43311799e+00 -1.57272652e-01
6.04565799e-01 -3.85140777e-01 -1.08288026e+00 5.52722037e-01
-1.39002943e+00 7.61341900e-02 9.07252848e-01 -4.73368526e-01
-1.15097654e+00 1.29120603e-01 1.29361913e-01 -3.14270228e-01
3.08492333e-01 8.50474536e-02 -5.77681601e-01 -1.38344020e-02
-1.21596351e-01 3.66945356e-01 4.51743543e-01 2.30699956e-01
-7.95464367e-02 6.31459534e-01 3.66580486e-01 -3.26844811e-01
5.19879282e-01 -1.98949620e-01 4.76465851e-01 -1.43274561e-01
1.98893756e-01 1.71429127e-01 -7.06828460e-02 -6.70688093e-01
5.70348680e-01 -1.02354908e+00 -1.45697701e+00 5.34809172e-01
-5.71488202e-01 -4.89445031e-01 -2.36866295e-01 2.66056508e-01
-7.19112396e-01 -1.64682701e-01 -2.21917868e-01 -1.23161530e+00
-2.08828777e-01 -1.06833076e+00 -3.03158015e-02 1.04769123e+00
4.66514468e-01 -8.89330685e-01 -1.29871249e-01 -1.10696852e-01
4.84120101e-01 1.63301811e-01 1.00337732e+00 1.53591027e-02
-5.44880986e-01 -8.93558096e-03 4.95801181e-01 5.81944823e-01
-4.48014177e-02 9.32534486e-02 -5.38420558e-01 -6.38328791e-01
-1.89288005e-01 -1.85582325e-01 2.50050783e-01 3.86098772e-01
1.15110195e+00 -5.33735693e-01 -5.60171723e-01 3.56434584e-01
1.83709264e+00 1.32822454e+00 8.04425955e-01 4.10175085e-01
2.72424966e-01 3.22208852e-01 1.29686558e+00 5.14430285e-01
6.33919358e-01 1.90745652e-01 7.58481979e-01 2.06798300e-01
4.91307139e-01 -2.47295499e-01 5.55124521e-01 4.62400496e-01
1.43603086e-01 -1.23089351e-01 -5.66436589e-01 4.77372676e-01
-1.93465352e+00 -1.21235859e+00 1.90285757e-01 2.25964642e+00
7.32125223e-01 3.37846130e-01 7.47910589e-02 3.38486880e-01
7.28255033e-01 -6.39878869e-01 -1.17950130e+00 -7.75530219e-01
-8.58865976e-02 -2.65953928e-01 8.31357121e-01 5.91852248e-01
-4.65948194e-01 5.63127816e-01 6.17822456e+00 9.52291250e-01
-1.35920978e+00 -2.22671777e-01 5.84819674e-01 -3.03401232e-01
-3.75087768e-01 -6.46955967e-02 -7.28262663e-01 9.53982592e-01
1.29666662e+00 -8.24370623e-01 1.06379879e+00 7.13277280e-01
7.01187372e-01 -5.33924639e-01 -8.14571381e-01 7.05995381e-01
-2.82293439e-01 -1.22544110e+00 -3.82908881e-01 -4.77113426e-01
6.91813409e-01 -3.16050231e-01 -3.72850984e-01 9.39133048e-01
-8.72559324e-02 -9.31788325e-01 8.70726287e-01 8.95668447e-01
6.68415129e-01 -1.41200209e+00 9.30519283e-01 6.74535275e-01
-1.19878054e+00 -9.57924783e-01 -3.54808718e-01 -1.17947742e-01
1.19401872e-01 1.59322783e-01 -5.01984119e-01 3.57316226e-01
6.56512618e-01 3.36249530e-01 -3.86499435e-01 7.81474829e-01
3.29742014e-01 3.00695837e-01 -3.64616275e-01 -6.79035902e-01
-1.33325249e-01 -3.66661102e-01 2.73203403e-02 7.01130092e-01
4.82925057e-01 3.37985575e-01 1.95661992e-01 7.76735961e-01
3.94840509e-01 -2.74513215e-01 -5.23813605e-01 -2.17332348e-01
1.01149070e+00 1.25141490e+00 -5.20161450e-01 -3.76807183e-01
-5.36456630e-02 1.28727034e-01 -2.61925250e-01 4.71100956e-01
-1.08961642e+00 -8.00882995e-01 2.77868360e-01 3.22726756e-01
1.51266888e-01 3.14456038e-02 -1.50900736e-01 -4.63101417e-01
-1.95769161e-01 -2.53510594e-01 9.06545967e-02 -8.60022247e-01
-7.86056578e-01 -1.28570482e-01 1.13284789e-01 -1.02082837e+00
-5.47404349e-01 -4.98484135e-01 -8.41175377e-01 6.85671926e-01
-1.86655283e+00 -4.55563843e-01 -2.78273761e-01 5.68011224e-01
3.33566457e-01 -3.95167500e-01 5.19603550e-01 4.07444149e-01
-8.82042766e-01 2.61153817e-01 6.90257370e-01 -5.44080377e-01
3.48225832e-01 -9.85143781e-01 -6.84200108e-01 4.68465984e-01
-1.37581944e+00 -1.47860557e-01 6.34763658e-01 -6.58627868e-01
-2.01828599e+00 -1.09945726e+00 2.94556260e-01 3.28913122e-01
3.43535781e-01 -3.36695090e-02 -8.80429089e-01 -4.13320623e-02
4.71067995e-01 1.93378836e-01 6.50228281e-03 -8.25102210e-01
7.11269915e-01 -9.07259643e-01 -1.54351580e+00 3.21803540e-01
3.68335515e-01 -1.07847355e-01 -9.74932387e-02 -1.89606801e-01
5.69427371e-01 -3.26374739e-01 -9.45014179e-01 7.72200048e-01
5.61040640e-01 -2.25956038e-01 5.13480365e-01 -4.29842204e-01
-2.61825025e-01 -6.90491021e-01 2.77851187e-02 -1.44639575e+00
-5.02331018e-01 -3.98523808e-01 -6.58753157e-01 1.28520977e+00
2.06568643e-01 -5.58795094e-01 5.50893903e-01 5.99298120e-01
-2.99868703e-01 -9.96330500e-01 -1.35942185e+00 -9.01052952e-01
2.77563065e-01 1.92351192e-01 9.88918304e-01 5.83001614e-01
4.12132263e-01 -1.16480395e-01 8.47555622e-02 1.03470750e-01
4.42086726e-01 -4.45078403e-01 1.04046740e-01 -7.09811926e-01
2.10633710e-01 -3.62784177e-01 -2.10660398e-01 4.11526710e-02
4.00479496e-01 -7.47893393e-01 4.38168406e-01 -1.86343312e+00
-4.17450303e-03 -4.41689044e-01 -9.10406053e-01 5.63720644e-01
-1.81569368e-01 -5.29961526e-01 1.89423889e-01 -2.84670413e-01
-7.24860072e-01 8.78721297e-01 1.26365125e+00 -6.53211892e-01
-2.67270744e-01 -3.13346949e-03 -1.88229457e-01 2.80914754e-01
9.55735624e-01 -3.07164371e-01 -9.42324460e-01 3.23265567e-02
2.57467091e-01 5.75297534e-01 1.07964225e-01 -1.17028093e+00
4.50024843e-01 -1.03142273e+00 3.53269935e-01 -6.68847084e-01
-1.21602647e-01 -1.26773310e+00 6.14588261e-01 1.10078049e+00
1.03958361e-01 1.71823010e-01 4.18112993e-01 5.74085176e-01
-6.43819347e-02 -5.04838824e-01 8.70220602e-01 1.68764472e-01
-9.11264837e-01 1.21566124e-01 -9.92121339e-01 -8.12284574e-02
1.74326921e+00 -3.54400635e-01 -2.94432133e-01 6.51541278e-02
-4.20450836e-01 1.23875666e+00 2.51367271e-01 5.57258368e-01
5.66434860e-01 -1.51288009e+00 -2.09938869e-01 3.17435175e-01
-1.82540461e-01 -1.20240033e-01 4.67065632e-01 4.04494107e-01
-1.89622432e-01 1.79110333e-01 -7.44723141e-01 -2.26142883e-01
-7.38329232e-01 6.97045207e-01 9.06076550e-01 3.59473191e-02
1.11096032e-01 -1.32670090e-01 -5.71874380e-01 -1.52085781e-01
1.07586868e-01 -2.68565863e-01 -3.36704701e-01 1.39815345e-01
2.69695878e-01 9.94735360e-01 8.45999364e-03 -9.16755348e-02
-4.98819262e-01 1.53133020e-01 4.27469522e-01 4.09352593e-02
1.03815055e+00 -1.11485474e-01 1.92077309e-02 5.79137385e-01
5.55295646e-01 -6.81715488e-01 -1.61241460e+00 4.93550420e-01
-2.77899832e-01 1.32162586e-01 4.29814547e-01 -1.19899106e+00
-1.04641569e+00 4.79893684e-01 1.21182966e+00 2.76149869e-01
1.26213062e+00 -7.20078707e-01 6.35936856e-01 5.71180463e-01
5.39156616e-01 -2.18315101e+00 -2.71425873e-01 5.85000634e-01
5.51231325e-01 -9.55656767e-01 -3.02986950e-02 2.62914807e-01
-6.58574283e-01 1.05065334e+00 1.20731425e+00 -3.56204361e-02
8.42265427e-01 6.01790488e-01 -3.04110020e-01 4.92254883e-01
-1.13115418e+00 2.97548205e-01 -4.32668865e-01 7.22248077e-01
-3.36740434e-01 2.68862426e-01 -5.80560505e-01 1.07590902e+00
5.03107548e-01 6.05249822e-01 5.94144404e-01 1.07800615e+00
-8.65820169e-01 -8.18341196e-01 -2.85911620e-01 3.88225168e-01
3.89511473e-02 6.41188502e-01 3.28785241e-01 6.99139833e-01
8.15107107e-01 1.13010287e+00 3.49621087e-01 -2.00557858e-01
6.61690950e-01 2.12071046e-01 3.80260855e-01 6.09289669e-02
-2.47614101e-01 -1.88703462e-01 -3.27254474e-01 -2.53702521e-01
-1.51644185e-01 -4.36291724e-01 -2.41363883e+00 -2.64502168e-01
-4.92427200e-01 5.58619082e-01 9.04100299e-01 1.01094007e+00
3.79378498e-01 8.45819533e-01 1.17493773e+00 -4.14810032e-01
-7.81045377e-01 -7.25932717e-01 -7.54950941e-01 -9.43911895e-02
1.49623603e-01 -9.89353240e-01 -4.50488061e-01 -2.17942014e-01] | [5.518857955932617, 2.310990810394287] |
1cb1ec47-b24e-4f40-8927-e17560c1e7be | dual-path-adaptation-from-image-to-video | 2303.09857 | null | https://arxiv.org/abs/2303.09857v1 | https://arxiv.org/pdf/2303.09857v1.pdf | Dual-path Adaptation from Image to Video Transformers | In this paper, we efficiently transfer the surpassing representation power of the vision foundation models, such as ViT and Swin, for video understanding with only a few trainable parameters. Previous adaptation methods have simultaneously considered spatial and temporal modeling with a unified learnable module but still suffered from fully leveraging the representative capabilities of image transformers. We argue that the popular dual-path (two-stream) architecture in video models can mitigate this problem. We propose a novel DualPath adaptation separated into spatial and temporal adaptation paths, where a lightweight bottleneck adapter is employed in each transformer block. Especially for temporal dynamic modeling, we incorporate consecutive frames into a grid-like frameset to precisely imitate vision transformers' capability that extrapolates relationships between tokens. In addition, we extensively investigate the multiple baselines from a unified perspective in video understanding and compare them with DualPath. Experimental results on four action recognition benchmarks prove that pretrained image transformers with DualPath can be effectively generalized beyond the data domain. | ['Kwanghoon Sohn', 'Jiyoung Lee', 'Jungin Park'] | 2023-03-17 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Park_Dual-Path_Adaptation_From_Image_to_Video_Transformers_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Park_Dual-Path_Adaptation_From_Image_to_Video_Transformers_CVPR_2023_paper.pdf | cvpr-2023-1 | ['action-classification', 'activity-recognition-in-videos', 'video-understanding', 'action-recognition-in-videos-2'] | ['computer-vision', 'computer-vision', 'computer-vision', 'computer-vision'] | [ 2.85300404e-01 -5.06939255e-02 -4.70378786e-01 -4.50595886e-01
-5.36419034e-01 -5.56351364e-01 7.50795126e-01 -5.73044538e-01
-3.94708991e-01 3.58949125e-01 3.91144156e-01 -3.61930549e-01
5.14933057e-02 -5.89345217e-01 -1.26547706e+00 -5.45895815e-01
1.33506238e-01 2.91103512e-01 6.20260656e-01 -1.42922729e-01
-2.39917589e-03 4.19374295e-02 -1.43247092e+00 8.79082620e-01
7.53366113e-01 7.41765141e-01 3.66093099e-01 7.46833920e-01
-2.70490170e-01 1.44071710e+00 -2.13092849e-01 -4.74001080e-01
3.01548958e-01 -3.20359707e-01 -1.04879153e+00 2.33030632e-01
7.51501501e-01 -9.49434698e-01 -8.06684613e-01 5.60078979e-01
7.13118091e-02 1.35495111e-01 2.47669816e-01 -1.38052166e+00
-7.84529269e-01 7.85414219e-01 -5.79215169e-01 4.38596100e-01
2.76551515e-01 5.58796465e-01 8.97584856e-01 -8.55741441e-01
5.66128612e-01 1.29389620e+00 6.36898816e-01 8.43823552e-01
-8.47836077e-01 -6.10799134e-01 9.81300414e-01 9.05728519e-01
-8.80701661e-01 -6.02588415e-01 4.29649472e-01 -3.46527815e-01
1.26618409e+00 6.07018992e-02 7.74829805e-01 1.47140610e+00
-7.03776702e-02 1.39380252e+00 8.00746620e-01 -1.01787090e-01
-1.87245339e-01 -2.21129790e-01 1.75105929e-01 7.06703782e-01
-2.58127332e-01 6.40166178e-02 -8.86310518e-01 4.76458609e-01
1.04954565e+00 2.15798631e-01 -3.32497150e-01 -4.29317623e-01
-1.32378626e+00 4.09008771e-01 3.24775070e-01 1.35586336e-01
-1.41850337e-01 5.53381681e-01 7.03976750e-01 3.94951701e-01
3.03501248e-01 -5.66341281e-02 -6.74690902e-01 -4.15990323e-01
-8.18249285e-01 -3.58902887e-02 5.05577564e-01 1.16051829e+00
6.60370946e-01 2.42705241e-01 -3.93905073e-01 3.55130076e-01
1.29383549e-01 2.32614487e-01 5.22671700e-01 -1.20832086e+00
5.53196549e-01 5.72037220e-01 -3.75249162e-02 -5.27817428e-01
-3.68605852e-02 -2.69308925e-01 -6.42589092e-01 -1.46741420e-01
5.06932795e-01 1.25621140e-01 -1.16750109e+00 1.83113599e+00
2.89419472e-01 1.09923995e+00 -6.24639075e-03 9.12172556e-01
6.68636322e-01 7.05858409e-01 3.31377804e-01 2.22609490e-02
1.31223035e+00 -1.66440046e+00 -4.89400864e-01 -3.94947469e-01
6.03893161e-01 -3.82812887e-01 1.29995573e+00 3.60960811e-01
-1.25422180e+00 -7.83756256e-01 -9.33709085e-01 -4.41614121e-01
-1.97910979e-01 -1.17369108e-02 7.41075456e-01 3.08862537e-01
-1.20297194e+00 4.87710804e-01 -1.34746981e+00 -3.58286798e-01
5.16583264e-01 1.88328847e-01 -3.85388643e-01 -1.91613793e-01
-1.06058562e+00 7.52184212e-01 2.39100590e-01 1.64888009e-01
-1.54870605e+00 -1.07456243e+00 -8.93510759e-01 -4.41022497e-03
6.35519683e-01 -1.19605899e+00 1.43352640e+00 -1.44594407e+00
-1.60009110e+00 6.61871672e-01 -4.58684981e-01 -7.72522688e-01
6.34393990e-01 -7.12372303e-01 -9.20167491e-02 3.60358477e-01
-1.30733326e-01 7.51282990e-01 1.15100312e+00 -1.07970393e+00
-6.98235214e-01 -2.20585734e-01 8.15612733e-01 3.26060236e-01
-5.26127815e-01 -8.27415138e-02 -8.96246195e-01 -5.96364975e-01
-2.55289495e-01 -8.37327182e-01 -1.25879779e-01 2.24619299e-01
-1.23151310e-01 -1.24402091e-01 9.76163805e-01 -5.82020998e-01
1.24623358e+00 -1.90080941e+00 5.66046238e-01 -3.94471198e-01
1.18948720e-01 4.24033493e-01 -4.62677389e-01 4.17972505e-01
-1.36750147e-01 -7.28368834e-02 -6.81419969e-02 -6.55711651e-01
5.68853086e-03 6.71420157e-01 -6.79011226e-01 1.51069030e-01
1.64660558e-01 1.14432812e+00 -9.85295415e-01 -3.43057781e-01
3.26785207e-01 5.51094711e-01 -7.07099020e-01 3.00210893e-01
-4.40914065e-01 5.69011569e-01 -4.59596515e-01 5.54747641e-01
5.80741405e-01 -4.05877113e-01 1.83475405e-01 -4.99137968e-01
4.79123183e-02 3.14127982e-01 -7.33794868e-01 2.29838467e+00
-5.73299825e-01 5.63418746e-01 -7.71990344e-02 -1.24601686e+00
2.44572639e-01 3.66768926e-01 4.77005273e-01 -7.53336370e-01
-4.61458325e-01 -2.98598200e-01 -2.28939950e-01 -7.44262218e-01
4.50659811e-01 3.71703580e-02 2.76348263e-01 5.18409491e-01
3.27799648e-01 4.06309575e-01 1.86415493e-01 4.83324140e-01
1.00563896e+00 9.51785386e-01 -1.03724726e-01 1.62880436e-01
5.06587029e-01 -1.20706804e-01 6.99470699e-01 8.81489038e-01
-2.97286451e-01 6.64740503e-01 4.28648859e-01 -6.57609403e-01
-1.00712037e+00 -1.16963208e+00 2.91942835e-01 1.48180974e+00
2.30597660e-01 -7.42009580e-01 -7.36586392e-01 -9.34122801e-01
-2.75093913e-01 4.76619482e-01 -7.28384793e-01 -2.40487710e-01
-9.28281009e-01 -5.41819155e-01 6.44233286e-01 1.16567469e+00
7.72384405e-01 -7.44544089e-01 -6.63316727e-01 1.60587132e-01
-4.76257294e-01 -1.57755005e+00 -6.15055919e-01 -2.01662809e-01
-9.42133904e-01 -1.14948285e+00 -5.14126360e-01 -5.14545023e-01
4.04514104e-01 7.19646275e-01 1.32821000e+00 1.79196522e-01
3.52577702e-03 9.38396215e-01 -5.99959016e-01 -2.28391424e-01
-7.11064637e-02 -1.70160327e-02 -1.23072274e-01 1.75757959e-01
3.66610795e-01 -6.33072555e-01 -9.20227110e-01 4.77778077e-01
-1.07537127e+00 5.98285258e-01 4.85086709e-01 7.75390267e-01
3.27962071e-01 -4.45701450e-01 4.17376876e-01 -6.75076425e-01
-1.05303168e-01 -5.49349487e-01 -2.03109622e-01 6.21415555e-01
-2.13166624e-01 4.35835831e-02 5.54869771e-01 -5.55933595e-01
-1.42762399e+00 -2.67220363e-02 9.80901569e-02 -7.97640145e-01
4.52838577e-02 3.01176310e-01 -2.08996072e-01 3.01192589e-02
1.59762517e-01 6.70527041e-01 -3.77583280e-02 -3.74140292e-01
6.99965060e-01 8.30461532e-02 5.79465866e-01 -8.15889001e-01
9.04423475e-01 8.70962262e-01 -4.37154412e-01 -5.32996237e-01
-9.82808709e-01 -4.14223284e-01 -6.78826272e-01 -3.21531683e-01
9.21296537e-01 -1.28890359e+00 -7.94076502e-01 7.57029295e-01
-1.09540927e+00 -7.85121620e-01 -4.29927766e-01 4.81116146e-01
-8.82574499e-01 5.90962291e-01 -8.12054098e-01 -3.59688759e-01
-8.88805557e-03 -1.15597045e+00 1.08855355e+00 1.83923841e-01
1.90498665e-01 -1.11790526e+00 -1.37245789e-01 7.81814814e-01
3.82635593e-01 -1.98434606e-01 6.67366922e-01 -2.68716514e-01
-1.13202333e+00 4.54615057e-01 -2.67871886e-01 3.84667516e-01
-3.43548991e-02 -8.88353959e-03 -1.13622403e+00 -3.36609244e-01
1.61944896e-01 -4.69948113e-01 1.28782272e+00 3.38888615e-01
1.36343694e+00 -2.73442954e-01 -2.51994610e-01 1.05197048e+00
1.25082088e+00 -7.49289698e-04 8.85371506e-01 5.10746241e-01
1.00724757e+00 3.50731790e-01 4.91039962e-01 3.70740116e-01
9.20052588e-01 7.10511863e-01 6.32978439e-01 -4.39086258e-02
-3.09533060e-01 -4.71201837e-01 9.54875171e-01 7.64511466e-01
-5.24851978e-01 -2.41036475e-01 -6.79197550e-01 6.62069023e-01
-2.33169889e+00 -1.14051509e+00 1.86951816e-01 1.95662761e+00
7.82579064e-01 -4.04526107e-02 1.71285734e-01 -2.12641403e-01
2.99954832e-01 4.19781983e-01 -7.17538297e-01 -8.47812742e-02
-1.57506645e-01 7.41728842e-02 4.82447267e-01 3.08146417e-01
-1.03304052e+00 1.19216537e+00 6.53283024e+00 7.73835778e-01
-9.46714342e-01 1.75485969e-01 4.59486663e-01 -2.29404971e-01
-3.61687899e-01 2.31609493e-01 -7.58706510e-01 2.87737548e-01
9.47451949e-01 -1.56236947e-01 2.88498342e-01 4.18152779e-01
3.00928980e-01 7.75964856e-02 -1.39322472e+00 8.13016653e-01
8.56293514e-02 -1.43147910e+00 6.19591594e-01 -1.90534562e-01
6.39310718e-01 5.45009971e-02 3.76578838e-01 5.32664239e-01
2.65805870e-01 -1.06799912e+00 8.19881558e-01 5.84040165e-01
5.68763554e-01 -2.91954666e-01 2.16192856e-01 2.22311169e-01
-1.59103990e+00 -2.08590403e-01 -2.89788485e-01 -1.51340663e-01
3.98157001e-01 -1.56732164e-02 -5.33725083e-01 8.26104224e-01
7.44650662e-01 1.42773747e+00 -5.82701921e-01 7.22911417e-01
-2.39463001e-01 7.39374459e-01 -8.05446431e-02 7.51318634e-01
6.13467813e-01 -1.89783990e-01 4.00030434e-01 1.07784939e+00
2.24188223e-01 7.24154711e-02 1.43400669e-01 5.79342306e-01
1.20622292e-01 -3.63555819e-01 -5.40875673e-01 -3.91071513e-02
1.40223250e-01 8.71552885e-01 -3.65463346e-01 -6.57828450e-01
-1.03924739e+00 1.15001953e+00 3.34536999e-01 7.11255074e-01
-1.28269660e+00 4.49570000e-01 8.57410967e-01 1.09640390e-01
6.34830117e-01 -4.12213355e-01 9.94539484e-02 -1.67233562e+00
1.83237389e-01 -1.13883018e+00 5.10642707e-01 -9.32387769e-01
-1.03890359e+00 3.96070391e-01 2.30001867e-01 -1.23464644e+00
-2.65023232e-01 -6.70285046e-01 -5.97258091e-01 2.48710021e-01
-1.87886822e+00 -1.89975405e+00 -4.00152683e-01 1.28446889e+00
1.16915858e+00 6.88497871e-02 6.52836263e-01 3.42792094e-01
-7.37112164e-01 6.42530501e-01 -1.30279213e-01 1.58654913e-01
7.74673760e-01 -1.29878676e+00 5.81673384e-01 9.98445034e-01
3.39973867e-01 5.01563132e-01 4.88642931e-01 -2.74704814e-01
-1.57202458e+00 -1.11701405e+00 2.95992583e-01 -6.87640905e-01
8.83560896e-01 -2.18074396e-01 -1.14384210e+00 1.45684528e+00
4.68585134e-01 -2.59049665e-02 3.97536844e-01 2.80786064e-02
-8.10240149e-01 -2.22552449e-01 -4.85868841e-01 6.45005703e-01
1.51804996e+00 -7.16442466e-01 -5.13907433e-01 2.86383271e-01
8.91127527e-01 -4.26794380e-01 -7.26490021e-01 3.86824191e-01
7.31357276e-01 -1.22280061e+00 1.31720555e+00 -1.05597389e+00
5.84255397e-01 -2.88014948e-01 2.29015760e-02 -9.96535778e-01
-1.32769659e-01 -6.94929600e-01 -4.15874183e-01 1.10757160e+00
2.69448701e-02 -3.46647739e-01 8.93542290e-01 5.60333312e-01
-3.39444160e-01 -6.49107218e-01 -7.61744380e-01 -8.80216718e-01
1.37646064e-01 -5.88654160e-01 4.92840320e-01 7.69620359e-01
-7.90795162e-02 1.07414037e-01 -7.59016275e-01 1.26668513e-01
5.30979753e-01 -1.03033129e-02 9.36560571e-01 -4.80535537e-01
-6.55258954e-01 -1.46572381e-01 -3.38926792e-01 -1.80738652e+00
3.60132903e-01 -6.24229372e-01 -2.25347623e-01 -1.34360743e+00
5.70987821e-01 -1.52038023e-01 -5.76024592e-01 5.55317640e-01
-2.62054980e-01 6.39812201e-02 4.67439175e-01 2.53505290e-01
-8.67594957e-01 6.07430398e-01 1.47895157e+00 -3.42587382e-01
2.10491046e-01 -1.91220686e-01 -5.32731950e-01 9.60069180e-01
4.60516781e-01 -4.01056334e-02 -1.11370623e+00 -1.28228748e+00
3.36842649e-02 -2.66948976e-02 6.75246954e-01 -9.22304094e-01
5.30230761e-01 -3.20862710e-01 1.90317333e-02 -2.67442256e-01
5.46133220e-01 -7.41570175e-01 1.10038124e-01 1.78885117e-01
-3.56488317e-01 1.02147549e-01 4.19523150e-01 8.13077390e-01
-3.73194546e-01 1.86241835e-01 4.52186048e-01 -2.31954947e-01
-1.43413877e+00 6.55074358e-01 -1.61967978e-01 2.17041979e-03
1.16794670e+00 -4.77345020e-01 -5.28817475e-01 -4.77980196e-01
-8.92349958e-01 3.94339621e-01 4.38991219e-01 6.21145248e-01
7.99445093e-01 -1.08562875e+00 -6.45880759e-01 2.50387955e-02
1.64504930e-01 -4.56338339e-02 7.97139704e-01 1.09036028e+00
-2.53571063e-01 3.03293496e-01 -3.42134953e-01 -8.64710987e-01
-1.12335455e+00 6.64180100e-01 5.06050825e-01 -4.23722833e-01
-8.33688557e-01 9.94305253e-01 9.12588656e-01 -2.74783839e-02
2.28061542e-01 -5.16262472e-01 -3.85826305e-02 -1.31514743e-01
7.36648321e-01 2.30705410e-01 -2.98620492e-01 -5.52986622e-01
-3.02743852e-01 8.71424079e-01 -3.66273463e-01 8.28665216e-03
1.28163016e+00 -4.09546673e-01 1.93355545e-01 4.88938481e-01
8.95473301e-01 -5.14502525e-01 -1.98769593e+00 -4.60969776e-01
-2.70639837e-01 -4.55704272e-01 -2.04494566e-01 -6.15396023e-01
-1.33474910e+00 1.00635576e+00 2.99969077e-01 -2.17838779e-01
1.32678533e+00 -1.58491641e-01 1.02168870e+00 3.02167028e-01
3.40595663e-01 -9.33266819e-01 3.46767217e-01 5.34049869e-01
7.18168318e-01 -1.28381896e+00 -2.77911544e-01 -2.95932591e-01
-7.73628294e-01 1.11405575e+00 9.76237714e-01 -6.97342753e-02
3.90395314e-01 3.15756112e-01 -1.79389011e-04 -3.61847766e-02
-1.37294078e+00 -1.96741387e-01 1.16569944e-01 6.84728742e-01
2.65706509e-01 -3.29655111e-01 1.45275503e-01 3.37829739e-01
4.28520620e-01 3.98017466e-01 5.20201623e-01 8.88902187e-01
-2.16833144e-01 -1.14080393e+00 8.83231238e-02 -1.17909350e-01
-3.69536042e-01 -2.29675338e-01 6.63890541e-02 9.01381373e-01
9.44747962e-03 7.10365176e-01 1.93185240e-01 -3.59891027e-01
2.54588932e-01 -7.03900296e-04 7.64217615e-01 -3.38584453e-01
-5.16327739e-01 -2.27899164e-01 -2.46474650e-02 -1.17439163e+00
-1.01269925e+00 -4.29004371e-01 -1.01161289e+00 -2.57482260e-01
8.05419385e-02 -1.44372478e-01 2.62919664e-01 1.16076970e+00
4.20579046e-01 7.38625526e-01 2.84414142e-01 -7.18279958e-01
-5.52207589e-01 -7.69537151e-01 -1.46710873e-01 4.26057070e-01
3.90395939e-01 -5.74812055e-01 -1.32907793e-01 6.92796707e-01] | [9.186174392700195, 0.7394708395004272] |
45c9c74d-dbbc-4be7-a240-977a3dee34bd | bridging-spectral-embedding-and-matrix | 2305.19818 | null | https://arxiv.org/abs/2305.19818v1 | https://arxiv.org/pdf/2305.19818v1.pdf | Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning | Self-supervised methods received tremendous attention thanks to their seemingly heuristic approach to learning representations that respect the semantics of the data without any apparent supervision in the form of labels. A growing body of literature is already being published in an attempt to build a coherent and theoretically grounded understanding of the workings of a zoo of losses used in modern self-supervised representation learning methods. In this paper, we attempt to provide an understanding from the perspective of a Laplace operator and connect the inductive bias stemming from the augmentation process to a low-rank matrix completion problem. To this end, we leverage the results from low-rank matrix completion to provide theoretical analysis on the convergence of modern SSL methods and a key property that affects their downstream performance. | ['Ivan Oseledets', 'Marina Munkhoeva'] | 2023-05-31 | null | null | null | null | ['low-rank-matrix-completion', 'matrix-completion'] | ['methodology', 'methodology'] | [ 4.87286597e-01 4.23222959e-01 -4.67206448e-01 -6.73247099e-01
-5.43583810e-01 -3.67729634e-01 6.29914820e-01 3.77619952e-01
-2.39189535e-01 4.72213417e-01 4.06876713e-01 -3.06281865e-01
-2.86500514e-01 -5.36840796e-01 -6.31469965e-01 -5.56729436e-01
-4.35124636e-02 2.15167731e-01 -4.23735529e-01 -3.38707566e-01
2.30260715e-01 4.16841775e-01 -1.25144100e+00 9.35256183e-02
6.91404998e-01 8.02599370e-01 -9.86223221e-02 1.71083465e-01
-1.26352593e-01 1.06296325e+00 5.42192571e-02 -4.18198884e-01
3.85666072e-01 -4.35674280e-01 -9.47694659e-01 3.15353543e-01
4.26368237e-01 -3.22856046e-02 -6.44139230e-01 1.01159167e+00
1.39368087e-01 3.26130539e-01 8.80522847e-01 -1.23520339e+00
-4.31534082e-01 7.05689192e-01 -5.77393234e-01 1.40693069e-01
1.31616637e-01 -1.51477486e-01 1.45763826e+00 -9.65769112e-01
6.08075142e-01 1.04397666e+00 8.13345194e-01 2.76715726e-01
-1.52380741e+00 -3.36957306e-01 1.20284788e-01 -2.49022748e-02
-1.34194088e+00 -6.41741216e-01 8.02870452e-01 -6.56070054e-01
3.65437329e-01 -1.33907944e-01 2.12219477e-01 1.09617591e+00
-1.54085785e-01 8.44458401e-01 1.15773988e+00 -6.98527515e-01
2.57341832e-01 4.72185850e-01 5.52094638e-01 7.11333275e-01
3.08020800e-01 1.60881147e-01 -8.62217307e-01 -1.49777457e-01
6.39175355e-01 -2.10537259e-02 -1.08084440e-01 -1.02106202e+00
-7.29655325e-01 1.17264748e+00 5.36818385e-01 3.07376087e-01
-1.40463918e-01 2.27073193e-01 6.70944929e-01 3.59133512e-01
6.36106908e-01 4.76750821e-01 -2.67897189e-01 1.16722926e-01
-9.96290624e-01 -1.88173071e-01 7.19386458e-01 7.88375258e-01
9.41633165e-01 1.36752784e-01 1.13603123e-01 6.56511426e-01
4.69384968e-01 9.69545841e-02 4.80719328e-01 -9.64578390e-01
3.78937304e-01 4.88447636e-01 -1.27688035e-01 -9.65745568e-01
-1.62834510e-01 -7.27181554e-01 -8.56139839e-01 5.52261882e-02
4.21944708e-01 1.13107925e-02 -3.89348865e-01 1.79284441e+00
-4.51853424e-02 2.47825891e-01 2.28362620e-01 7.28605747e-01
2.56564438e-01 3.76417965e-01 4.34877761e-02 -1.92296326e-01
8.44191968e-01 -8.36774647e-01 -5.98452449e-01 -3.22236866e-01
9.68788803e-01 -4.28801686e-01 1.04893827e+00 1.81320414e-01
-8.93243253e-01 -1.97172821e-01 -1.18780470e+00 -1.30671069e-01
-2.41337344e-01 1.82385802e-01 1.04957676e+00 5.96632421e-01
-8.91811848e-01 8.41535151e-01 -7.26821423e-01 -5.33090770e-01
5.40758550e-01 1.40498742e-01 -5.37875175e-01 -1.94702908e-01
-1.01520145e+00 8.73597503e-01 3.25018615e-02 1.19085126e-01
-6.91507399e-01 -7.82445490e-01 -7.86011398e-01 -7.43577164e-03
2.82722890e-01 -5.04748583e-01 1.15364289e+00 -1.14229321e+00
-1.15416086e+00 1.13910878e+00 -1.09313875e-01 -6.39640927e-01
5.35749078e-01 -5.13978720e-01 5.70837297e-02 2.40154266e-01
2.13788003e-01 2.21494734e-01 1.11408889e+00 -1.22536683e+00
-3.91495973e-01 -5.95594108e-01 -6.21953867e-02 8.00787657e-02
-6.19650364e-01 -2.37630635e-01 -1.12834692e-01 -7.98577011e-01
2.89607823e-01 -9.48804021e-01 -3.29876781e-01 1.03617478e-02
-3.37271482e-01 -8.12482536e-02 2.34564975e-01 -3.69981855e-01
1.11233413e+00 -2.51214433e+00 2.94804871e-01 3.43962431e-01
3.08458686e-01 1.72619551e-01 -5.46141379e-02 8.77645016e-01
-3.94622982e-01 -1.93555001e-02 -5.15172243e-01 -6.05315626e-01
-1.23862132e-01 1.59386471e-01 -9.43192780e-01 8.17724347e-01
1.92650393e-01 6.05551898e-01 -1.00632405e+00 -2.30006173e-01
1.11629456e-01 3.82304996e-01 -4.77017403e-01 2.35966980e-01
1.16988510e-01 2.33570263e-01 -4.90087628e-01 1.86339006e-01
2.50316828e-01 -3.88711959e-01 3.72630298e-01 -2.97139317e-01
1.92697404e-03 5.06045043e-01 -1.03377557e+00 1.98856890e+00
-4.24343377e-01 7.48861134e-01 3.27061832e-01 -1.54961884e+00
7.55524695e-01 1.53222442e-01 6.05172038e-01 -2.09700391e-01
1.69776678e-01 1.36504531e-01 -3.45974952e-01 -7.04131350e-02
3.84361655e-01 -5.26625931e-01 2.54394174e-01 6.68223500e-01
1.72738805e-01 7.29212984e-02 2.28663817e-01 7.13587403e-01
1.07193196e+00 2.88541615e-02 2.53058553e-01 -4.02574301e-01
4.73044872e-01 -6.06497079e-02 3.51706803e-01 8.82833302e-01
7.69057870e-02 4.23270434e-01 4.18058515e-01 -2.33649939e-01
-8.59747887e-01 -1.18838835e+00 -3.80230844e-01 1.12991130e+00
-3.16282660e-01 -5.79819977e-01 -4.28791672e-01 -6.45990789e-01
1.74437448e-01 6.06505394e-01 -6.81722105e-01 -4.72227752e-01
-2.01216608e-01 -6.20036721e-01 4.73860741e-01 6.19412601e-01
2.17873514e-01 -6.81131959e-01 -2.15563446e-01 -2.53443769e-03
2.02585906e-01 -1.11053407e+00 -1.46510884e-01 5.15500128e-01
-1.28277707e+00 -1.16433549e+00 -4.74219441e-01 -7.16257513e-01
9.70663428e-01 3.09972703e-01 8.72206450e-01 -1.37811750e-01
-2.51343876e-01 7.86922097e-01 -3.31230313e-01 -2.40674525e-01
-3.09909940e-01 3.29466045e-01 2.62258798e-01 2.50218183e-01
1.57833487e-01 -8.47815454e-01 -1.67390183e-01 9.45755765e-02
-1.08981025e+00 -1.70619376e-02 7.21417964e-01 8.47945511e-01
2.36226097e-01 -7.35790282e-02 6.46490872e-01 -1.24036396e+00
6.00939512e-01 -7.75591195e-01 -4.55382615e-01 1.03961341e-01
-1.02125335e+00 4.02304322e-01 5.24467587e-01 -1.45164743e-01
-1.11332977e+00 3.21341723e-01 1.71606153e-01 -4.55029994e-01
1.26298741e-01 7.36432433e-01 1.36172414e-01 6.89208359e-02
8.17972183e-01 1.47243589e-01 3.06728303e-01 -6.95143104e-01
8.13434362e-01 4.45697457e-01 5.24730444e-01 -7.56546021e-01
1.14137936e+00 8.17688406e-01 2.71279544e-01 -8.54069531e-01
-1.54969931e+00 -6.67421341e-01 -8.24337304e-01 1.07982665e-01
2.69186676e-01 -1.02041876e+00 -2.57503390e-01 2.12120742e-01
-5.85557699e-01 -2.60238409e-01 -7.88304806e-01 5.43634057e-01
-8.17099988e-01 4.53103065e-01 -7.64302135e-01 -8.94812405e-01
-1.94693834e-01 -4.85621512e-01 6.30945921e-01 -1.45369127e-01
-2.60259300e-01 -1.19145119e+00 6.05771691e-02 3.96730542e-01
3.50070983e-01 -2.31163517e-01 8.05937171e-01 -7.16959476e-01
-3.40971947e-01 -2.34200627e-01 -3.83161038e-01 6.99530065e-01
8.43315795e-02 -3.66368383e-01 -1.11501777e+00 -3.93330097e-01
1.99110448e-01 -4.67408895e-01 1.14344215e+00 2.31746405e-01
7.63634980e-01 -1.49059370e-01 -1.73726767e-01 6.57034159e-01
1.46910477e+00 -5.43798923e-01 2.86275059e-01 2.18680218e-01
6.32815123e-01 8.85221183e-01 4.27806944e-01 5.65459669e-01
-1.76299006e-01 3.07756901e-01 1.44647822e-01 -1.02161691e-01
1.48039712e-02 -6.46050572e-01 1.84842497e-01 7.56433487e-01
3.82168770e-01 1.77095115e-01 -8.54955256e-01 3.69253963e-01
-2.00880527e+00 -7.21008420e-01 -1.70641989e-02 2.24371147e+00
9.09287751e-01 1.48755714e-01 -2.16389745e-02 4.42598253e-01
6.00704134e-01 2.87773311e-01 -4.66803879e-01 -1.12842508e-01
-6.20835908e-02 6.07748441e-02 5.59950709e-01 3.67459387e-01
-1.04628599e+00 9.94306803e-01 6.99920988e+00 7.00543225e-01
-7.83280909e-01 -1.67368621e-01 4.89592254e-01 -3.79966060e-03
-2.77019829e-01 3.02981764e-01 -5.36451340e-01 -6.50974661e-02
8.21870446e-01 -1.60715133e-01 5.26579142e-01 8.63719702e-01
1.84191585e-01 3.95543799e-02 -1.46587539e+00 9.50535893e-01
1.43143639e-01 -1.26346874e+00 7.37842172e-02 8.18713754e-02
6.68593287e-01 5.71190678e-02 2.87366360e-01 1.52460381e-01
5.11782289e-01 -1.06396365e+00 4.72854197e-01 5.87376773e-01
7.22832799e-01 -4.13759530e-01 4.00824606e-01 1.86620116e-01
-8.01846206e-01 -1.95850208e-01 -2.16749594e-01 -4.79703307e-01
6.65519387e-02 9.02374268e-01 -7.93808818e-01 4.09606814e-01
1.72110811e-01 1.13443828e+00 -4.09206659e-01 7.24209070e-01
-3.28839719e-01 1.04252756e+00 -3.00620496e-01 4.96630937e-01
2.13565752e-01 -4.26597804e-01 4.61202234e-01 1.03376389e+00
-1.65038005e-01 -7.25910217e-02 -5.15220175e-03 7.63938427e-01
-2.97257513e-01 3.41919690e-01 -8.42922747e-01 -3.97527158e-01
1.46813765e-01 1.10706568e+00 -5.03132641e-01 -1.37403861e-01
-5.71246862e-01 8.18275750e-01 5.74218214e-01 3.91008794e-01
-2.05367774e-01 -4.27383482e-02 6.56599283e-01 2.29109883e-01
5.56328781e-02 -3.84097308e-01 -4.13096875e-01 -1.14303207e+00
5.42861456e-03 -7.05644727e-01 4.42511678e-01 -5.61419666e-01
-1.69166338e+00 -1.97422169e-02 -8.15844461e-02 -8.91243279e-01
-1.52879298e-01 -5.71983695e-01 -5.13940036e-01 6.28344059e-01
-1.61891341e+00 -8.26214910e-01 7.12634102e-02 4.89027530e-01
2.67691731e-01 -3.11226219e-01 7.97190845e-01 2.29686350e-01
-6.79705024e-01 4.27832723e-01 4.95155394e-01 2.61685759e-01
7.40518630e-01 -1.05793250e+00 -1.61744305e-03 6.58295631e-01
5.09451389e-01 9.81593490e-01 7.95703948e-01 -4.21440631e-01
-1.64944899e+00 -8.12447131e-01 6.95064247e-01 -4.49213624e-01
1.03238213e+00 -8.86099488e-02 -7.19423711e-01 8.77535701e-01
-2.35091999e-01 2.29203790e-01 9.08376813e-01 6.29623771e-01
-6.55531526e-01 -2.24318251e-01 -7.98470736e-01 3.66123706e-01
9.76660848e-01 -9.70594406e-01 -7.09429681e-01 2.53910333e-01
2.62108803e-01 1.82876065e-01 -6.35034502e-01 3.01295280e-01
3.42999458e-01 -7.66719162e-01 9.52090740e-01 -9.31035101e-01
5.46778738e-01 1.79168880e-02 -2.94938922e-01 -1.04775369e+00
-1.68367520e-01 -6.48989558e-01 3.04941088e-02 1.26635015e+00
1.94032192e-01 -5.56996286e-01 1.02623868e+00 5.02902806e-01
-2.98504569e-02 -7.98551798e-01 -6.77554429e-01 -7.46618748e-01
2.18787357e-01 -5.47841191e-01 -2.22638115e-01 1.04667139e+00
3.38068128e-01 7.29887128e-01 -3.59052628e-01 -5.04094549e-02
8.63757730e-01 9.66979787e-02 5.33149421e-01 -1.54133463e+00
-1.18692741e-01 -1.74197808e-01 -4.00095701e-01 -1.06535852e+00
5.70137739e-01 -1.38701868e+00 -1.29919872e-01 -1.13179326e+00
2.50759244e-01 -5.43313324e-01 -4.95077878e-01 3.63395810e-01
1.93837106e-01 1.03470989e-01 5.87184392e-02 5.02394617e-01
-6.20901763e-01 7.61932135e-01 5.34638166e-01 -3.46359573e-02
-1.28121361e-01 -7.11083338e-02 -9.43149507e-01 8.88028264e-01
8.04436147e-01 -4.94115651e-01 -6.72184646e-01 -3.03844482e-01
6.18500173e-01 -2.32472435e-01 2.79096335e-01 -7.16243207e-01
1.66623577e-01 1.66887507e-01 6.60347641e-02 -1.11362021e-02
2.53084064e-01 -6.80401027e-01 -4.27239299e-01 1.56055823e-01
-9.62001860e-01 -3.19675922e-01 -1.33837625e-01 9.50260937e-01
-2.24266440e-01 -6.02248549e-01 6.63583398e-01 -5.49012087e-02
-5.32014191e-01 1.83713242e-01 -4.10397738e-01 5.10684609e-01
7.17586517e-01 2.12952971e-01 1.89958632e-01 -4.20175701e-01
-8.55208278e-01 5.30904084e-02 5.13124049e-01 2.47318432e-01
3.78417969e-01 -1.17146719e+00 -5.13266385e-01 2.13126287e-01
1.51102483e-01 -3.80957514e-01 -1.51108786e-01 6.74406767e-01
-3.12526375e-02 4.01375175e-01 3.29068936e-02 -2.24485815e-01
-7.22953379e-01 5.15605807e-01 9.19562727e-02 -2.40795344e-01
-7.16057420e-01 6.40233576e-01 1.52496412e-01 -2.40867674e-01
4.90120262e-01 1.83706522e-01 -1.33590139e-02 2.70199716e-01
2.82027394e-01 5.22911906e-01 -7.11963372e-03 -5.15446067e-01
-1.63955957e-01 2.72861630e-01 -3.16165350e-02 -2.26234168e-01
1.49151444e+00 -2.48490348e-01 2.83111017e-02 8.49050939e-01
1.36112320e+00 -3.12919021e-02 -1.14986944e+00 -6.51207209e-01
2.80140460e-01 -3.93876821e-01 2.81450659e-01 -2.83637106e-01
-9.86098111e-01 9.72427905e-01 3.45521629e-01 8.12369063e-02
7.48161256e-01 7.57035017e-02 4.63847339e-01 6.86391413e-01
2.05156446e-01 -1.24365151e+00 1.49629578e-01 4.19978112e-01
7.31377661e-01 -1.24794900e+00 2.31617495e-01 -5.57767630e-01
-5.66155732e-01 8.98655295e-01 7.58313090e-02 -3.17424923e-01
7.78004050e-01 9.19383988e-02 -1.24067634e-01 -2.16508284e-01
-5.31722844e-01 -1.70636594e-01 1.01415738e-01 6.12009883e-01
5.71120143e-01 -3.01899284e-01 -1.73930749e-01 3.92718971e-01
-3.56198661e-03 -7.36594498e-02 3.86956394e-01 8.49961877e-01
-2.45846793e-01 -1.25797451e+00 -1.83122314e-03 6.15132034e-01
-3.59033436e-01 -2.41038367e-01 -3.78968149e-01 3.78853589e-01
-5.11359215e-01 9.07834828e-01 -2.56999671e-01 1.29707856e-02
1.26187384e-01 4.11642432e-01 3.33531171e-01 -8.42764854e-01
-3.01026553e-01 -2.89603263e-01 1.72891486e-02 -5.08013427e-01
-4.44314837e-01 -8.92207086e-01 -1.21644235e+00 -7.78531581e-02
-2.31502429e-01 3.49925309e-01 6.10143304e-01 1.01151037e+00
2.10462779e-01 1.71426415e-01 7.46683538e-01 -7.14689672e-01
-1.08653522e+00 -7.13062346e-01 -8.64766300e-01 6.58970654e-01
2.38513395e-01 -5.43041468e-01 -7.51668513e-01 -2.77488716e-02] | [9.095806121826172, 3.149845600128174] |
d040fd42-3527-4265-b06c-538070a734d8 | adversarial-discriminative-heterogeneous-face | 1709.03675 | null | http://arxiv.org/abs/1709.03675v1 | http://arxiv.org/pdf/1709.03675v1.pdf | Adversarial Discriminative Heterogeneous Face Recognition | The gap between sensing patterns of different face modalities remains a
challenging problem in heterogeneous face recognition (HFR). This paper
proposes an adversarial discriminative feature learning framework to close the
sensing gap via adversarial learning on both raw-pixel space and compact
feature space. This framework integrates cross-spectral face hallucination and
discriminative feature learning into an end-to-end adversarial network. In the
pixel space, we make use of generative adversarial networks to perform
cross-spectral face hallucination. An elaborate two-path model is introduced to
alleviate the lack of paired images, which gives consideration to both global
structures and local textures. In the feature space, an adversarial loss and a
high-order variance discrepancy loss are employed to measure the global and
local discrepancy between two heterogeneous distributions respectively. These
two losses enhance domain-invariant feature learning and modality independent
noise removing. Experimental results on three NIR-VIS databases show that our
proposed approach outperforms state-of-the-art HFR methods, without requiring
of complex network or large-scale training dataset. | ['Man Zhang', 'Xiang Wu', 'Ran He', 'Lingxiao Song'] | 2017-09-12 | null | null | null | null | ['heterogeneous-face-recognition', 'face-hallucination'] | ['computer-vision', 'computer-vision'] | [ 5.52083194e-01 -9.67764482e-02 3.39906543e-01 -3.59195650e-01
-1.16146100e+00 -3.00599128e-01 4.42778885e-01 -7.68230855e-01
-6.98051527e-02 7.69647658e-01 7.86042213e-02 2.76639134e-01
-2.12219238e-01 -8.65791917e-01 -7.34374344e-01 -1.08367348e+00
4.12865490e-01 -1.28708124e-01 -2.42293045e-01 -1.04482256e-01
-3.47683728e-01 6.91983461e-01 -1.47594225e+00 2.23284677e-01
8.78934979e-01 1.32454383e+00 4.00717221e-02 1.49858743e-01
1.01418354e-01 6.57244325e-01 -3.24786574e-01 -4.12868977e-01
6.58591926e-01 -5.53446591e-01 -1.98023632e-01 3.71725082e-01
5.75586557e-01 2.20779628e-02 -7.88229287e-01 1.41068995e+00
1.00071931e+00 1.29829720e-01 6.32766366e-01 -1.20723152e+00
-1.12803364e+00 1.79574221e-01 -7.24110842e-01 -2.54991531e-01
3.39290828e-01 3.15218240e-01 3.54860127e-01 -1.17633545e+00
4.47421461e-01 1.26308668e+00 9.01598454e-01 6.02764726e-01
-1.35374510e+00 -8.99615467e-01 -1.93645120e-01 1.12978287e-01
-1.76475918e+00 -6.49438858e-01 1.52515709e+00 -4.76487011e-01
3.15651834e-01 3.83478224e-01 3.32382172e-01 1.18615162e+00
1.00107409e-01 2.88995147e-01 1.62672746e+00 -3.34010422e-01
-7.15796053e-02 1.06482789e-01 -6.40700042e-01 6.89621985e-01
-2.00690031e-01 4.84135568e-01 -6.38825774e-01 -1.76919147e-01
9.28920388e-01 3.65445405e-01 -5.10707676e-01 -5.67398846e-01
-8.02034616e-01 7.29795098e-01 5.86938202e-01 2.48530775e-01
-4.50809777e-01 -1.57176480e-01 6.28173575e-02 3.73318583e-01
4.18468267e-01 -6.90779909e-02 -8.69219154e-02 6.24630392e-01
-8.87871742e-01 -8.55462030e-02 3.98571223e-01 6.94876492e-01
8.48573506e-01 4.82422620e-01 -3.32734674e-01 1.21578228e+00
5.16356111e-01 1.15710378e+00 2.86192626e-01 -9.94709313e-01
2.86682963e-01 1.84428751e-01 -9.22951847e-02 -1.19227457e+00
-6.33630902e-02 -5.80422223e-01 -1.16947973e+00 5.18910944e-01
1.87718436e-01 -1.44477174e-01 -8.87912214e-01 1.89130998e+00
4.79026467e-01 3.93129021e-01 1.02295011e-01 1.00612056e+00
8.04354846e-01 3.93479049e-01 -5.47462404e-02 -4.46513593e-01
1.04820132e+00 -6.51162446e-01 -7.61658132e-01 -1.26407593e-01
-3.71457636e-01 -1.10877693e+00 8.46138060e-01 1.16609782e-01
-1.17480457e+00 -8.91097248e-01 -1.05744302e+00 1.83204189e-02
-1.50456220e-01 -3.93023752e-02 2.47843444e-01 8.02996278e-01
-8.68614137e-01 4.00452971e-01 -4.91190076e-01 -2.21935734e-02
7.25749671e-01 1.28005832e-01 -6.44774973e-01 -5.92999101e-01
-1.18721735e+00 5.53527176e-01 -5.30622490e-02 3.65739971e-01
-9.98174429e-01 -8.99133384e-01 -9.25509930e-01 -2.50740111e-01
2.71059364e-01 -8.48193824e-01 3.42396706e-01 -1.18052948e+00
-1.55768239e+00 1.02098596e+00 6.96395487e-02 1.55578256e-01
6.57155395e-01 5.89800104e-02 -8.75532568e-01 1.22142799e-01
4.86464798e-02 1.37329936e-01 1.43633986e+00 -1.53817868e+00
1.91580966e-01 -8.66414726e-01 -4.52685356e-01 2.40591541e-01
-2.12036386e-01 -1.44358292e-01 -2.77787179e-01 -9.69498158e-01
3.14225286e-01 -7.21888185e-01 -7.58506171e-03 3.61300647e-01
-4.03434098e-01 3.77015531e-01 9.32930768e-01 -8.99306595e-01
5.78017294e-01 -2.39087439e+00 2.28180051e-01 4.61090028e-01
1.53180704e-01 9.43162739e-02 -3.95715773e-01 1.04960471e-01
-3.06452394e-01 -4.62393880e-01 -5.10185361e-01 -1.70101434e-01
-2.62145861e-03 6.00248314e-02 -9.85217541e-02 1.01386702e+00
2.55859315e-01 8.18896055e-01 -7.07733810e-01 -4.15991664e-01
3.36522609e-01 1.04797351e+00 -3.76610279e-01 3.94833237e-01
1.56521723e-01 9.01179373e-01 -4.19856936e-01 9.70790625e-01
1.38451767e+00 2.32115582e-01 -3.54617927e-03 -4.95538622e-01
2.41458893e-01 -6.08045459e-01 -1.20071888e+00 2.00317621e+00
-5.32036722e-01 7.31539801e-02 3.98544014e-01 -1.17219901e+00
1.15566301e+00 2.50689596e-01 5.69884121e-01 -8.25532138e-01
3.88412438e-02 3.59277576e-01 -2.58130193e-01 -4.45753425e-01
-1.43353328e-01 -6.87091172e-01 5.71678206e-02 -3.92677560e-02
2.68666387e-01 -1.47855580e-01 -6.64937079e-01 -4.65345889e-01
8.08023453e-01 1.44525185e-01 7.78258070e-02 -1.82278439e-01
8.72144222e-01 -8.29058766e-01 7.51944304e-01 5.24461806e-01
-3.04042250e-01 9.20491993e-01 -3.86551581e-02 -5.71390018e-02
-9.10175264e-01 -1.42640579e+00 -3.14431190e-01 8.16783011e-01
2.37853467e-01 3.82780582e-01 -5.05303741e-01 -6.04406297e-01
1.82285577e-01 2.56034106e-01 -7.99657285e-01 -3.03982764e-01
-2.87107408e-01 -5.04696906e-01 5.32827020e-01 2.79437602e-01
7.97381222e-01 -9.83891070e-01 2.02363163e-01 -8.27402174e-02
-1.60407960e-01 -1.06149733e+00 -5.47542691e-01 -1.04817584e-01
-3.83833528e-01 -1.00550795e+00 -9.93060708e-01 -9.05218899e-01
5.45179486e-01 2.69417822e-01 8.49604964e-01 -3.19787472e-01
-5.62875748e-01 6.78079307e-01 -1.34085104e-01 -5.46673499e-02
-4.12168741e-01 -5.44159949e-01 -1.05451234e-02 6.72237456e-01
1.88920781e-01 -1.03574920e+00 -8.23476911e-01 4.20711279e-01
-9.91450787e-01 -3.76332283e-01 6.30699337e-01 1.24990833e+00
8.84350538e-01 -6.94451556e-02 6.75323188e-01 -6.78991318e-01
1.99316084e-01 -5.09410203e-01 -3.70415896e-01 3.83875638e-01
-3.97920281e-01 -2.07232326e-01 7.02913821e-01 -4.39057052e-01
-1.31527555e+00 1.21206999e-01 -2.42875814e-01 -9.60899293e-01
-1.72564894e-01 2.83532351e-01 -8.84781122e-01 -6.03484035e-01
7.04621434e-01 5.85487068e-01 1.73099190e-01 -1.82267219e-01
5.13544261e-01 4.97044325e-01 8.79638374e-01 -5.78692198e-01
1.41125882e+00 6.09561145e-01 2.60388404e-01 -8.30558062e-01
-6.73693061e-01 -3.03974390e-01 -4.38752681e-01 -3.06463301e-01
6.93247437e-01 -1.19149804e+00 -4.62770700e-01 6.91526055e-01
-7.59700835e-01 3.71214710e-02 -5.78501284e-01 2.32728183e-01
-7.31135428e-01 4.94699568e-01 -2.77228564e-01 -7.95703351e-01
-2.42053792e-01 -9.87320006e-01 1.04581845e+00 3.39370072e-01
6.21912956e-01 -8.45547497e-01 -4.94826362e-02 5.76956630e-01
5.97038984e-01 6.05264902e-01 4.16078120e-01 -1.56154290e-01
-4.68500644e-01 -2.36589804e-01 -2.07544386e-01 7.94540763e-01
2.30702460e-01 -4.50176448e-01 -1.38829434e+00 -5.16311407e-01
3.63400787e-01 -4.57263887e-01 9.08830404e-01 2.52289265e-01
1.46014214e+00 -1.05305657e-01 -5.24416827e-02 1.04479170e+00
1.65179038e+00 5.33430651e-02 9.74722862e-01 -2.73086429e-01
9.35350478e-01 6.20163023e-01 3.79245192e-01 5.48263431e-01
-6.80793077e-02 6.25862241e-01 4.40221995e-01 -2.39322126e-01
-5.28580844e-01 -3.76383841e-01 4.70786154e-01 5.01976252e-01
-3.06903943e-02 8.09600297e-03 -4.83290225e-01 3.28920990e-01
-1.54686022e+00 -1.24599755e+00 4.87646341e-01 2.19877028e+00
7.02541232e-01 -4.73205000e-01 -3.02800685e-01 1.22348778e-01
8.58347297e-01 4.56511140e-01 -8.04828346e-01 2.83828259e-01
-6.74302459e-01 3.79237384e-01 2.78573126e-01 4.54871565e-01
-1.13053846e+00 6.21077180e-01 4.92333269e+00 1.19329774e+00
-1.22906268e+00 4.79508013e-01 5.96579731e-01 1.13966703e-01
-5.54735959e-01 -4.52225387e-01 -2.13613436e-01 4.26906854e-01
4.31870908e-01 1.71886623e-01 7.93623507e-01 5.95564187e-01
-5.43070957e-02 4.41460967e-01 -6.77894771e-01 1.42947936e+00
4.20853198e-01 -9.93660867e-01 -1.22236662e-01 -2.30432414e-02
9.42583263e-01 -1.37271300e-01 6.68575346e-01 1.19177938e-01
-1.71753708e-02 -1.18912983e+00 5.38153350e-01 1.03815019e+00
1.18847740e+00 -8.60099316e-01 5.72485328e-01 -1.49420097e-01
-1.15039039e+00 -1.41634628e-01 -4.89064932e-01 4.88962114e-01
-4.22341041e-02 6.98745131e-01 -4.59789708e-02 8.02777350e-01
6.23114824e-01 6.44704044e-01 -3.57518286e-01 6.16281092e-01
-8.33024904e-02 1.46385372e-01 -7.37503469e-02 7.72240400e-01
-2.91014016e-01 -4.61168557e-01 7.83819377e-01 7.58676231e-01
4.74985808e-01 9.44558010e-02 3.46006840e-01 1.02895498e+00
-3.80906910e-01 2.54642256e-02 -8.67404580e-01 1.51873752e-01
4.69399124e-01 1.30107307e+00 -7.87340254e-02 1.63810700e-01
-4.67452854e-01 1.37078905e+00 1.67289022e-02 6.01349890e-01
-8.72402370e-01 -2.64992416e-01 6.35775387e-01 2.00683698e-01
4.11638200e-01 1.82854384e-01 -1.69052735e-01 -1.17512536e+00
2.25652754e-01 -8.51275563e-01 1.23262160e-01 -7.45401978e-01
-1.86150455e+00 5.16918838e-01 -6.38632894e-01 -1.23256814e+00
6.76290616e-02 -3.70029598e-01 -4.77377445e-01 1.16947281e+00
-1.80850291e+00 -1.81000865e+00 -5.21951199e-01 1.29240847e+00
1.27389133e-01 -6.19972825e-01 8.58708560e-01 6.14587843e-01
-4.21197802e-01 1.13862932e+00 4.01907921e-01 9.59866047e-02
7.49140203e-01 -7.27183938e-01 -4.40555662e-01 9.15043235e-01
-1.56897664e-01 3.56490463e-01 4.96178746e-01 -3.82296354e-01
-1.53709865e+00 -1.41215277e+00 2.28683367e-01 -5.41428477e-02
3.76017064e-01 -1.88660249e-01 -8.86819124e-01 4.04266387e-01
8.64370838e-02 9.57166791e-01 9.58689332e-01 -2.08428085e-01
-8.49914670e-01 -5.02063572e-01 -1.72762704e+00 2.99017996e-01
1.22147083e+00 -1.09854412e+00 -2.13599592e-01 3.62003893e-01
4.81466830e-01 -2.33590648e-01 -1.25932288e+00 5.93087673e-01
6.72135174e-01 -1.05420184e+00 1.24376512e+00 -2.05516115e-01
3.67008239e-01 -4.96457368e-01 -7.71362245e-01 -1.27993095e+00
-2.50086784e-01 -8.05836558e-01 5.71205914e-02 1.42053950e+00
8.76284838e-02 -7.07914114e-01 4.61179793e-01 7.51709715e-02
-2.21275359e-01 -4.85762477e-01 -1.09651792e+00 -6.76300764e-01
1.53038025e-01 -1.90032855e-01 5.65498292e-01 1.07063794e+00
-5.75853288e-01 3.93105149e-02 -5.79993308e-01 5.04405141e-01
1.21206570e+00 2.15986237e-01 5.28635085e-01 -1.02370107e+00
-4.32004362e-01 -5.55932559e-02 -5.27335167e-01 -5.61568499e-01
5.46572328e-01 -9.67583954e-01 1.24201551e-01 -9.11596417e-01
4.09495890e-01 -2.99062639e-01 -5.99920571e-01 3.42476040e-01
-6.04707636e-02 7.49917984e-01 9.14619043e-02 1.51249498e-01
-3.32232505e-01 1.16156471e+00 1.45205128e+00 -4.27846551e-01
1.99995175e-01 -2.26254940e-01 -6.98040724e-01 5.09623945e-01
4.83460635e-01 -3.04089993e-01 -3.56847167e-01 -1.26286238e-01
-2.64974177e-01 3.46104711e-01 7.32414186e-01 -1.26851726e+00
1.22564919e-01 -2.45125353e-01 8.62761140e-01 -1.96771130e-01
5.69054246e-01 -1.19024229e+00 4.37787175e-01 1.23587944e-01
-1.25553772e-01 -5.63366771e-01 7.26662204e-02 8.00229669e-01
-3.71307552e-01 4.33089048e-01 1.51416779e+00 3.01789325e-02
-4.43416446e-01 5.94535708e-01 4.02300358e-01 2.93804035e-02
1.13107383e+00 -2.35458985e-01 -1.93430930e-01 -2.42694616e-01
-9.99463558e-01 -2.82740474e-01 4.69890743e-01 3.02669048e-01
9.28644359e-01 -1.72636509e+00 -8.58381808e-01 7.13320911e-01
2.07465634e-01 -3.27672809e-01 1.05515647e+00 7.32309580e-01
-1.72738537e-01 -1.39595136e-01 -5.91532469e-01 -4.34301227e-01
-1.05004740e+00 6.26380622e-01 7.02761292e-01 -6.87693357e-02
-4.02323574e-01 9.36414361e-01 2.51865327e-01 -7.79030621e-01
-1.66888945e-02 5.58544815e-01 1.82083458e-01 -9.00196135e-02
5.01165926e-01 3.19567412e-01 -8.38890821e-02 -1.01134419e+00
-3.16127509e-01 7.90667117e-01 2.25913972e-01 -7.72070419e-03
1.32424343e+00 -3.77237171e-01 -2.35251874e-01 1.27365291e-01
1.50504494e+00 1.75931633e-01 -1.53289127e+00 -5.76984882e-01
-7.83425152e-01 -7.56321609e-01 1.34879142e-01 -8.52480650e-01
-1.52259731e+00 7.36400425e-01 1.23705852e+00 -4.18826491e-02
1.52100909e+00 -1.03349768e-01 7.33231068e-01 -1.83881626e-01
2.24291936e-01 -8.68748248e-01 2.73009747e-01 1.84614822e-01
1.28129959e+00 -1.35636210e+00 -1.29265696e-01 -6.42741561e-01
-3.80470157e-01 8.00644398e-01 4.68073487e-01 -1.53731421e-01
9.99362886e-01 2.79233642e-02 1.23677835e-01 -9.61896628e-02
1.57126114e-02 -1.94212452e-01 3.65727961e-01 1.05487394e+00
1.54078618e-01 1.32753670e-01 1.22021204e-02 5.85828543e-01
2.87923459e-02 4.64318600e-03 -4.89578322e-02 5.29496014e-01
-4.74929586e-02 -8.64321887e-01 -6.13013685e-01 1.19668208e-01
-5.10855436e-01 1.14168972e-01 3.98396850e-02 4.95539963e-01
5.29420555e-01 9.50767279e-01 -2.18578160e-01 -5.15749335e-01
3.43099952e-01 5.78164496e-02 8.49041343e-01 -1.95983231e-01
-1.79917544e-01 1.91769525e-01 -4.49810147e-01 -6.98599458e-01
-5.75360239e-01 -6.32327378e-01 -7.07138300e-01 -3.29612166e-01
-1.82402372e-01 -2.61616468e-01 4.17564273e-01 6.72662258e-01
3.78118902e-01 5.44678211e-01 1.20458937e+00 -8.70035827e-01
-7.78842151e-01 -9.22832966e-01 -1.21514988e+00 5.98016679e-01
4.67746705e-01 -7.76383221e-01 -3.23331654e-01 3.84793431e-02] | [13.048041343688965, 0.19379930198192596] |
166e60d4-f6ad-40fc-9217-7023539cdbe4 | sentiment-analysis-on-brazilian-portuguese | 2112.05459 | null | https://arxiv.org/abs/2112.05459v1 | https://arxiv.org/pdf/2112.05459v1.pdf | Sentiment Analysis on Brazilian Portuguese User Reviews | Sentiment Analysis is one of the most classical and primarily studied natural language processing tasks. This problem had a notable advance with the proposition of more complex and scalable machine learning models. Despite this progress, the Brazilian Portuguese language still disposes only of limited linguistic resources, such as datasets dedicated to sentiment classification, especially when considering the existence of predefined partitions in training, testing, and validation sets that would allow a more fair comparison of different algorithm alternatives. Motivated by these issues, this work analyzes the predictive performance of a range of document embedding strategies, assuming the polarity as the system outcome. This analysis includes five sentiment analysis datasets in Brazilian Portuguese, unified in a single dataset, and a reference partitioning in training, testing, and validation sets, both made publicly available through a digital repository. A cross-evaluation of dataset-specific models over different contexts is conducted to evaluate their generalization capabilities and the feasibility of adopting a unique model for addressing all scenarios. | ['João Filho', 'Frederico Souza'] | 2021-12-10 | null | null | null | null | ['document-embedding'] | ['methodology'] | [ 6.52332380e-02 5.12052923e-02 -2.72149086e-01 -4.63077784e-01
-3.99436176e-01 -6.92533255e-01 8.82544875e-01 9.36919212e-01
-8.82652879e-01 6.33182645e-01 2.28319541e-01 -3.08218241e-01
-2.60902643e-01 -8.97226989e-01 8.38577151e-02 -5.90610802e-01
1.61101595e-01 5.27775228e-01 -4.05506231e-02 -3.98715913e-01
2.76162654e-01 5.02410173e-01 -1.79282725e+00 3.79236728e-01
6.35455608e-01 9.90752876e-01 1.70652255e-01 3.32175434e-01
-3.45985085e-01 5.31911910e-01 -6.56230390e-01 -9.27439630e-01
5.34315966e-02 -4.00219375e-04 -7.86307275e-01 -2.01850280e-01
-8.54825694e-03 3.39937598e-01 1.78061843e-01 8.47141504e-01
6.59303546e-01 7.18020797e-02 6.04650557e-01 -1.11329925e+00
-5.75798512e-01 6.53868020e-01 -1.50014628e-02 1.75603013e-02
4.36611712e-01 -8.74776170e-02 1.33900297e+00 -6.93781078e-01
7.24812388e-01 8.59778285e-01 6.68235183e-01 3.77213657e-01
-1.07396269e+00 -2.47086674e-01 5.04987799e-02 2.35822260e-01
-1.04102790e+00 -1.34419248e-01 9.76975858e-01 -4.06373858e-01
1.05179334e+00 1.98875472e-01 6.84654355e-01 1.14655042e+00
2.31330499e-01 4.80082631e-01 1.58549654e+00 -7.53889203e-01
3.03625345e-01 1.09234357e+00 5.81416309e-01 1.72497109e-01
5.93015075e-01 -2.59099573e-01 -3.47951174e-01 -7.56117180e-02
-3.22372973e-01 -3.14765483e-01 -1.54719323e-01 -3.29284102e-01
-7.11662889e-01 9.85710263e-01 3.96046117e-02 9.93528903e-01
-2.84413636e-01 -7.86694229e-01 7.66722500e-01 3.69945347e-01
6.74131095e-01 5.42497993e-01 -8.13059866e-01 -3.06566238e-01
-9.23957884e-01 7.30854720e-02 9.74108458e-01 4.37827438e-01
7.08406985e-01 2.59366948e-02 1.82917610e-01 7.80621290e-01
3.16242486e-01 4.38652962e-01 9.42963481e-01 -2.06326857e-01
5.46753526e-01 1.00495362e+00 -6.22651428e-02 -1.42028284e+00
-8.40973854e-01 -4.19839799e-01 -5.76343238e-01 -4.19162512e-02
3.35388660e-01 -2.31536373e-01 -2.29976922e-01 1.49641919e+00
3.17012489e-01 -6.42341971e-01 3.30298394e-01 4.51907158e-01
5.77678442e-01 4.98036057e-01 1.93011969e-01 -1.63923308e-01
1.40933681e+00 -5.25808632e-01 -5.44290245e-01 -2.47388333e-01
9.11646903e-01 -7.19267070e-01 1.26912498e+00 6.58346355e-01
-6.29108429e-01 -5.20361245e-01 -1.09364307e+00 -1.78278059e-01
-1.32874215e+00 3.00371110e-01 7.90754855e-01 1.28935349e+00
-8.99512529e-01 3.73498529e-01 -6.25032902e-01 -5.54803848e-01
1.92484096e-01 3.62188727e-01 -5.74848175e-01 1.54552177e-01
-1.29745853e+00 1.29553735e+00 3.40396941e-01 1.61078349e-01
7.91581869e-02 -5.00077903e-01 -8.32093596e-01 1.25864923e-01
-2.80161109e-02 -3.27847391e-01 7.07675874e-01 -1.27749407e+00
-1.33389378e+00 1.15787947e+00 -4.14615963e-03 -5.59888184e-01
5.86290836e-01 2.90133003e-02 -6.98790014e-01 -1.08240053e-01
1.01470843e-01 3.23287606e-01 3.93352419e-01 -1.02358174e+00
-5.47270238e-01 -7.22279251e-01 2.88240522e-01 -5.63826747e-02
-1.01998210e+00 1.78240404e-01 -1.07229590e-01 -5.19388914e-01
-3.53364915e-01 -8.57427239e-01 -1.44730702e-01 -6.51357651e-01
-7.13738054e-02 -2.05010116e-01 5.53794265e-01 -4.01881486e-01
1.58607507e+00 -2.14776540e+00 9.38974395e-02 1.99143544e-01
-2.92312682e-01 2.23091081e-01 8.84783361e-03 7.54149675e-01
-3.25349867e-01 3.60577255e-01 -2.89731979e-01 -5.80335736e-01
1.80468366e-01 1.87046900e-01 -3.19599003e-01 4.10260975e-01
2.82759607e-01 3.96429539e-01 -7.01362014e-01 -4.41773117e-01
2.99120843e-01 6.55748904e-01 -4.46521372e-01 -3.59668344e-01
7.50560015e-02 1.27983078e-01 -4.97074962e-01 3.63733053e-01
3.74483168e-01 3.69076766e-02 5.27877986e-01 -1.06313325e-01
-3.26081187e-01 3.92741889e-01 -1.21396768e+00 1.23467445e+00
-7.14909375e-01 8.13082457e-01 -3.99663836e-01 -1.15717471e+00
1.06119311e+00 3.10200155e-01 6.43278003e-01 -7.30324328e-01
5.68356931e-01 2.87893355e-01 -3.91823500e-02 -4.51176941e-01
9.66475546e-01 -2.01105937e-01 -2.49451399e-01 3.18509012e-01
1.51338845e-01 -2.29367673e-01 7.97676444e-01 -1.58899456e-01
6.42583370e-01 -1.37964800e-01 4.25893128e-01 -4.83156502e-01
1.02064884e+00 1.45663768e-01 2.63138562e-01 3.35136026e-01
-2.38437966e-01 4.71344113e-01 7.90908337e-01 -4.40138638e-01
-7.90384531e-01 -4.72956240e-01 -6.27322435e-01 8.93978238e-01
-1.51503235e-01 -6.44133449e-01 -6.03258848e-01 -6.73080683e-01
-6.19142093e-02 7.97055185e-01 -9.15348053e-01 4.09106202e-02
-2.19374210e-01 -1.20014763e+00 4.83956963e-01 1.45736292e-01
1.65754169e-01 -1.18711281e+00 -8.63551557e-01 9.54506919e-02
-2.09139995e-02 -9.20910537e-01 5.42033911e-01 4.51675743e-01
-8.16530466e-01 -1.30737042e+00 -2.64530480e-01 -5.50253749e-01
4.23420787e-01 -2.14983359e-01 1.14524519e+00 -5.79925664e-02
-5.80429025e-02 3.78675789e-01 -6.35300994e-01 -7.67648637e-01
-5.88371575e-01 5.20259261e-01 4.99318279e-02 7.43360966e-02
7.39175379e-01 -1.49072081e-01 -1.65819705e-01 -2.27223206e-02
-1.12778962e+00 -5.43763578e-01 3.16292971e-01 7.22483575e-01
2.81222373e-01 2.02083975e-01 6.37079835e-01 -1.14557242e+00
9.98572350e-01 -5.91353297e-01 -5.81978142e-01 1.73503950e-01
-1.00641024e+00 -2.08755866e-01 1.03275239e+00 -1.84338074e-02
-1.03610861e+00 -4.12168711e-01 -2.95170784e-01 2.49424055e-01
-3.86427194e-01 9.57188189e-01 -1.53012693e-01 3.16988617e-01
5.96343160e-01 -1.19431745e-02 -1.36322409e-01 -3.77932101e-01
1.62826777e-01 8.65147650e-01 -8.29829648e-02 -4.72540140e-01
4.47767913e-01 3.94882292e-01 -1.66388854e-01 -1.11668360e+00
-7.09985495e-01 -4.86842185e-01 -8.29732478e-01 -1.12208761e-01
6.67946279e-01 -6.27804935e-01 -5.53185880e-01 3.07279080e-01
-8.59679341e-01 2.58215815e-02 -4.43075657e-01 4.97791559e-01
-1.56710520e-01 3.26178849e-01 -1.49562076e-01 -6.63635671e-01
-2.25765765e-01 -1.26206386e+00 6.85431182e-01 1.00693524e-01
-5.96869648e-01 -1.52448845e+00 3.45475554e-01 3.84698182e-01
4.16999966e-01 1.59300536e-01 1.08522511e+00 -1.10691428e+00
3.40987384e-01 -6.35629773e-01 1.69783622e-01 7.47124076e-01
1.76663831e-01 3.87845606e-01 -1.15664709e+00 -3.38286489e-01
2.52449155e-01 -1.88376456e-01 6.10323966e-01 -4.98489812e-02
7.04757988e-01 8.99229124e-02 -1.66913141e-02 4.58327606e-02
1.69364071e+00 1.50766879e-01 3.94350827e-01 9.16400611e-01
8.49214047e-02 1.13267624e+00 6.48011982e-01 3.81044477e-01
5.75449169e-01 4.36538547e-01 1.46281704e-01 2.98252165e-01
1.67547554e-01 1.74098954e-01 4.42379355e-01 1.08292687e+00
3.77405658e-02 -3.30306143e-01 -1.04276705e+00 6.08605683e-01
-1.36372852e+00 -9.00854766e-01 -2.92187203e-02 2.11035228e+00
4.06394869e-01 2.59462535e-01 6.09982833e-02 8.11431885e-01
3.81342590e-01 4.21377987e-01 4.07711267e-02 -8.21966231e-01
-5.36559105e-01 4.62082565e-01 2.22571164e-01 2.26210997e-01
-1.16785145e+00 5.47461450e-01 5.93727398e+00 4.02409285e-01
-1.62939274e+00 2.15079412e-02 6.06419802e-01 7.24238753e-02
-4.28571075e-01 -2.23181918e-01 -6.95945144e-01 6.04231060e-01
1.18259227e+00 -1.89077005e-01 6.60847593e-03 7.30599880e-01
2.92430252e-01 -9.30252075e-02 -7.52659738e-01 5.77469170e-01
3.12522411e-01 -1.19708502e+00 1.40637919e-01 -1.49550080e-01
6.48403466e-01 1.56705037e-01 3.02579165e-01 4.52681243e-01
-2.78572202e-01 -7.98195064e-01 7.99532473e-01 7.24926740e-02
4.54535365e-01 -7.63217390e-01 1.07265234e+00 4.26779725e-02
-7.23013341e-01 -4.54260141e-01 -1.78984001e-01 -2.15277776e-01
-6.67887107e-02 4.86739963e-01 -4.47795480e-01 9.79865313e-01
8.00518334e-01 8.64839256e-01 -9.39508021e-01 5.24966359e-01
-1.38556942e-01 6.28279686e-01 -1.43217131e-01 -3.62153411e-01
3.29477549e-01 -4.26420420e-01 3.53469193e-01 1.35683417e+00
1.72326401e-01 -4.90374655e-01 -1.71021312e-01 2.53955483e-01
1.53952539e-01 8.63023579e-01 -5.99811018e-01 -1.16634682e-01
2.44559705e-01 1.46426082e+00 -9.31530952e-01 -9.94660929e-02
-7.77481318e-01 3.35905790e-01 2.88689137e-01 7.82857984e-02
-6.17910385e-01 -4.92137492e-01 4.33807611e-01 -8.39594230e-02
4.57700044e-02 -5.16930735e-03 -6.60811841e-01 -1.28174281e+00
1.44720584e-01 -8.51403356e-01 4.55327719e-01 -5.30454516e-01
-1.18578422e+00 8.01508665e-01 1.22215927e-01 -1.12987256e+00
-1.49393931e-01 -1.15309656e+00 -3.31649899e-01 8.02941620e-01
-1.63490891e+00 -1.09608400e+00 -1.10836297e-01 3.78778785e-01
2.04509392e-01 -3.64305615e-01 1.07327092e+00 5.37363768e-01
-6.69297159e-01 3.97143900e-01 2.41116405e-01 -4.15011384e-02
7.33761966e-01 -1.32038164e+00 -2.42695957e-01 6.39172375e-01
1.98900908e-01 6.49665892e-01 8.14045131e-01 -1.42684206e-01
-1.03734648e+00 -7.09742606e-01 1.26451135e+00 -4.78014767e-01
9.72072661e-01 -3.11666727e-01 -7.79950500e-01 5.57866633e-01
2.45278388e-01 -4.48341399e-01 1.04649389e+00 3.29784930e-01
-1.46729633e-01 -2.28708625e-01 -1.07206404e+00 6.87115610e-01
2.05727354e-01 -6.16218686e-01 -8.07846963e-01 -1.41878342e-02
8.42093900e-02 7.21306279e-02 -1.09414864e+00 3.06021631e-01
6.38196349e-01 -1.16472352e+00 6.60660863e-01 -4.68968570e-01
6.60206914e-01 -6.68937042e-02 -3.61741424e-01 -1.24189103e+00
2.07510263e-01 -1.53299540e-01 5.10096908e-01 1.42710268e+00
7.32058764e-01 -1.02577531e+00 8.71734023e-01 4.56673026e-01
3.76134850e-02 -9.68513191e-01 -9.52497661e-01 -3.72197717e-01
4.38007295e-01 -7.32721329e-01 6.68198884e-01 1.14619684e+00
1.39096126e-01 4.34502333e-01 1.10394739e-01 -1.09911487e-01
-9.76173282e-02 2.99488485e-01 7.85556972e-01 -1.46967113e+00
4.90681157e-02 -6.93595707e-01 -6.16504908e-01 -1.53381884e-01
3.87617618e-01 -1.02310538e+00 -5.88969767e-01 -1.44386101e+00
-1.49840981e-01 -5.82075715e-01 -4.49694961e-01 3.29599559e-01
1.21098403e-02 2.60552973e-01 3.52297008e-01 -1.00393318e-01
-6.34735748e-02 4.16961759e-01 7.00158179e-01 -2.43145704e-01
-1.29613146e-01 -9.63659436e-02 -8.73165190e-01 7.69851089e-01
9.27525222e-01 -5.62087595e-01 -4.71283287e-01 -3.07323962e-01
6.77621186e-01 -3.91839981e-01 -1.43432155e-01 -9.05713677e-01
6.15630113e-02 1.36860266e-01 1.25770107e-01 -2.93540210e-01
3.15670490e-01 -1.15041864e+00 4.78979573e-02 3.39212954e-01
-3.38968635e-01 3.48499775e-01 4.27987009e-01 1.51774094e-01
-6.36156976e-01 -6.11482143e-01 5.54820478e-01 1.90406516e-01
-6.74673736e-01 -6.45700246e-02 -3.83413136e-01 -5.62579706e-02
1.16580319e+00 -4.90844369e-01 -1.70833915e-01 6.18888363e-02
-6.67535961e-01 -4.24900576e-02 5.81706345e-01 7.33948588e-01
7.45680407e-02 -6.78112924e-01 -5.56560338e-01 1.57882810e-01
3.77103418e-01 -4.00637716e-01 3.02856922e-01 8.28972697e-01
-5.25306761e-01 6.58140600e-01 -3.11291456e-01 -2.95910269e-01
-1.22864866e+00 5.58462799e-01 2.04983801e-01 -7.20978916e-01
-4.79639955e-02 1.55329317e-01 -4.84310210e-01 -7.15842664e-01
-2.75136858e-01 -2.17562094e-01 -8.90109301e-01 8.58696818e-01
1.96192771e-01 3.94815534e-01 4.69742805e-01 -1.01406276e+00
-3.62899125e-01 4.59090114e-01 2.01828733e-01 -5.38406894e-02
1.30200839e+00 -1.12189807e-01 -3.76953423e-01 8.16751599e-01
1.19873846e+00 5.33849537e-01 -2.70957172e-01 2.89467990e-01
3.71672928e-01 -8.11749920e-02 -1.26146585e-01 -7.74253309e-01
-9.48072970e-01 9.05135691e-01 4.79602754e-01 7.87046850e-01
1.08152521e+00 -5.21348774e-01 -2.81558670e-02 4.05253559e-01
3.69020104e-01 -1.16764569e+00 -4.28615481e-01 6.32375121e-01
5.23311615e-01 -1.26842988e+00 1.65302008e-01 -5.87103032e-02
-6.97193503e-01 1.26751649e+00 1.58679694e-01 1.12433940e-01
9.42322433e-01 1.03774378e-02 3.16965908e-01 -1.68464109e-01
-5.91929257e-01 -5.81725948e-02 -1.47147728e-02 4.17485893e-01
8.73385668e-01 4.50459048e-02 -9.45530832e-01 8.58018577e-01
-5.82395077e-01 -1.32625580e-01 7.48796582e-01 8.54144752e-01
8.87609050e-02 -1.46077859e+00 -9.93859023e-02 4.54211056e-01
-8.81413758e-01 4.52825986e-02 -3.58072579e-01 1.26291645e+00
1.94585010e-01 1.21870744e+00 -1.49156842e-02 -1.63839877e-01
6.52164876e-01 2.44162247e-01 1.87434927e-01 -5.34270585e-01
-1.21181762e+00 -6.41213536e-01 2.02829123e-01 -1.52515262e-01
-7.97468722e-01 -8.09578717e-01 -9.26691771e-01 -2.19762817e-01
-2.93213159e-01 4.91439968e-01 9.99624252e-01 8.29588234e-01
3.64601046e-01 4.30308133e-01 6.34034157e-01 -5.79441369e-01
-4.32332158e-01 -1.01525307e+00 -6.13072217e-01 6.81885719e-01
-4.62544896e-02 -4.95806485e-01 -4.82519388e-01 -1.14281125e-01] | [11.100207328796387, 7.139816761016846] |
d0affa41-b0b0-4116-9db6-a823dadc3428 | unsupervised-multi-view-object-segmentation | 2210.00489 | null | https://arxiv.org/abs/2210.00489v2 | https://arxiv.org/pdf/2210.00489v2.pdf | Unsupervised Multi-View Object Segmentation Using Radiance Field Propagation | We present radiance field propagation (RFP), a novel approach to segmenting objects in 3D during reconstruction given only unlabeled multi-view images of a scene. RFP is derived from emerging neural radiance field-based techniques, which jointly encodes semantics with appearance and geometry. The core of our method is a novel propagation strategy for individual objects' radiance fields with a bidirectional photometric loss, enabling an unsupervised partitioning of a scene into salient or meaningful regions corresponding to different object instances. To better handle complex scenes with multiple objects and occlusions, we further propose an iterative expectation-maximization algorithm to refine object masks. RFP is one of the first unsupervised approach for tackling 3D real scene object segmentation for neural radiance field (NeRF) without any supervision, annotations, or other cues such as 3D bounding boxes and prior knowledge of object class. Experiments demonstrate that RFP achieves feasible segmentation results that are more accurate than previous unsupervised image/scene segmentation approaches, and are comparable to existing supervised NeRF-based methods. The segmented object representations enable individual 3D object editing operations. | ['Chi-Keung Tang', 'Yu-Wing Tai', 'Huai Yu', 'Jiaben Chen', 'Xinhang Liu'] | 2022-10-02 | null | null | null | null | ['scene-segmentation'] | ['computer-vision'] | [ 9.0656877e-01 1.5702368e-01 1.2853917e-01 -8.2738829e-01
-5.5059534e-01 -6.0395622e-01 4.1925862e-01 1.3044107e-01
-2.7865791e-01 1.8008524e-01 -2.6647702e-01 -7.7840246e-02
-3.9287083e-02 -9.3675810e-01 -9.3082231e-01 -6.2307250e-01
2.7426425e-01 4.4679502e-01 7.0896339e-01 -9.9984042e-02
2.7707776e-01 1.0999677e+00 -1.5384412e+00 5.9917990e-02
7.2078323e-01 1.0794218e+00 7.2270596e-01 6.9342130e-01
-4.6762419e-01 1.0469935e+00 -3.5916626e-01 -5.4724041e-02
5.9458917e-01 -1.0405847e-02 -1.0434800e+00 5.8654231e-01
7.1361643e-01 -4.7104624e-01 -5.5088226e-02 1.3047032e+00
1.1170950e-01 4.4328293e-01 8.1872821e-01 -1.0240842e+00
-6.6485524e-01 1.9298957e-01 -7.9043746e-01 5.5578724e-02
2.6237023e-01 -7.9531521e-02 6.8492985e-01 -8.4252948e-01
6.3197881e-01 1.1983646e+00 5.7698506e-01 3.2967982e-01
-1.3491474e+00 -6.4302713e-02 5.2316529e-01 -3.4368637e-01
-1.3804141e+00 -1.6213225e-01 1.1751361e+00 -6.0678804e-01
9.7987443e-01 5.1481903e-01 5.7645088e-01 2.1446685e-01
-1.2396707e-01 9.4886637e-01 9.2169261e-01 -4.5295691e-01
2.6004940e-01 3.9341930e-01 2.4403241e-01 7.0696551e-01
-2.6117769e-01 -2.2481413e-01 -1.5717272e-01 -1.2060890e-01
1.1139181e+00 2.6723668e-01 -4.2461720e-01 -6.4500630e-01
-1.2077469e+00 4.4590828e-01 7.3263174e-01 -6.5401673e-02
-4.8661333e-01 2.0667256e-01 -2.3643509e-01 -1.2645559e-01
9.7486329e-01 2.1999370e-01 -5.5590075e-01 6.7572969e-01
-9.9307412e-01 1.6886118e-01 2.7535045e-01 1.2263178e+00
1.2690755e+00 7.8250572e-02 5.8975671e-03 1.0332570e+00
6.0267383e-01 6.3545328e-01 -1.9966969e-01 -1.3184682e+00
8.5436188e-02 8.0798686e-01 5.9805933e-02 -9.0131211e-01
-3.6902380e-01 -1.4903988e-01 -6.6667759e-01 3.8906869e-01
8.9641966e-02 2.8281707e-01 -1.4608666e+00 1.4416562e+00
9.6369374e-01 3.8998272e-02 1.0211242e-01 9.9712312e-01
1.0202012e+00 9.0232587e-01 -1.6152069e-01 1.2873308e-01
1.2036079e+00 -1.0439490e+00 -1.8231498e-01 -2.4174500e-01
2.8696308e-01 -6.9297355e-01 8.7582892e-01 3.5274848e-01
-1.1758717e+00 -5.4018760e-01 -7.0737600e-01 -4.5496330e-01
-4.4548193e-01 -1.8590423e-01 9.3052757e-01 6.9602090e-01
-9.9042666e-01 2.7788594e-01 -5.1598358e-01 -7.4415036e-02
7.6845032e-01 2.2259867e-01 -2.7008858e-01 -1.7224504e-01
-5.8496994e-01 4.9385041e-01 5.0944513e-01 1.1495746e-01
-1.1944607e+00 -1.0262889e+00 -9.7157818e-01 -2.7064338e-01
2.8665316e-01 -7.9260826e-01 1.2167675e+00 -1.0470551e+00
-1.4074703e+00 1.2218611e+00 -1.2776303e-01 -6.3611776e-02
-7.3505817e-03 -2.7069372e-01 -1.4833543e-02 3.6704817e-01
1.7214943e-01 1.0997864e+00 7.9083526e-01 -1.8143569e+00
-6.2137002e-01 -4.4915065e-01 3.4796005e-01 6.8404156e-01
1.7247282e-01 7.3881060e-02 -6.7678803e-01 -5.1783872e-01
5.4684538e-01 -4.4220302e-01 -6.9083899e-01 2.7099285e-01
-6.8841088e-01 -9.4535537e-02 9.0767902e-01 -3.3208483e-01
3.8799158e-01 -2.0678980e+00 4.7606159e-02 3.3969909e-01
1.7519785e-01 -3.3680394e-01 -6.0610421e-02 -2.4431054e-01
2.6458759e-02 -6.0478617e-02 -9.0764815e-01 -2.1749139e-01
-1.7329265e-01 1.6087008e-01 -3.0922523e-01 6.3421166e-01
2.6822910e-01 6.7745447e-01 -8.8716298e-01 -4.5052791e-01
6.1955833e-01 6.8684864e-01 -6.6529119e-01 2.4529845e-01
-8.0020636e-01 8.5650474e-01 -6.5028888e-01 7.5157654e-01
1.1894410e+00 -2.2172019e-01 -4.1140974e-01 -3.1287870e-01
-2.0658486e-01 1.1505524e-01 -1.4360951e+00 2.0736778e+00
-3.0009076e-01 4.2597693e-01 2.3850787e-01 -7.9286343e-01
9.5143300e-01 -9.8274507e-02 8.1169230e-01 -4.7985867e-01
2.1723637e-01 -1.8533449e-01 -8.6111355e-01 -3.4653661e-01
8.0180603e-01 -2.0497611e-02 7.5889923e-02 5.3897715e-01
1.6365065e-01 -1.0006081e+00 -1.0368495e-01 2.4640679e-01
6.1489618e-01 5.1620317e-01 -6.3146718e-02 -3.5190254e-01
4.3068483e-01 1.3247859e-01 4.6470428e-01 8.2441920e-01
1.6441549e-01 1.1678041e+00 -2.2789012e-01 -2.7342826e-01
-7.9275113e-01 -1.2382356e+00 -5.3454107e-01 1.0993968e+00
8.1459856e-01 2.0992830e-01 -9.5969594e-01 -6.2696213e-01
-2.1100937e-01 8.0515921e-01 -2.7669010e-01 2.9022363e-01
-3.5642698e-01 -8.8207150e-01 2.2405571e-01 3.0487275e-01
6.6018635e-01 -9.2070848e-01 -8.8760525e-01 -6.8966679e-02
-3.0237129e-01 -1.3218030e+00 -4.8743531e-01 4.9406838e-01
-9.8579264e-01 -9.4536865e-01 -8.8619429e-01 -8.7353724e-01
1.1577406e+00 6.4447254e-01 1.1715654e+00 -6.9758818e-02
-5.2488005e-01 8.5295802e-01 -1.8083093e-01 -3.5825363e-01
-2.6821899e-01 -3.1243163e-01 -3.4073240e-01 9.0970740e-02
1.3439541e-01 -6.3644147e-01 -6.5515882e-01 4.4252807e-01
-1.3099626e+00 4.6572837e-01 4.3040791e-01 1.2426214e-01
1.1981145e+00 2.0948635e-01 -2.7867672e-01 -1.1779256e+00
-1.8873630e-01 -3.8398758e-01 -8.4339762e-01 4.0561411e-01
-1.8399896e-01 -1.1599831e-01 1.6979881e-01 -1.8202071e-01
-1.7812796e+00 5.0309956e-01 -1.0639285e-01 -3.0785215e-01
-9.3311203e-01 -1.1346470e-01 -2.7439564e-01 -1.9352463e-01
7.4565285e-01 2.6997069e-01 -6.4115858e-01 -5.4380721e-01
8.3332527e-01 3.9762270e-01 7.1678936e-01 -4.9597120e-01
7.5752163e-01 1.0046232e+00 -3.5443090e-02 -9.7913015e-01
-1.0679730e+00 -9.0971112e-01 -1.1653776e+00 -4.0220886e-01
1.2120736e+00 -1.0024447e+00 -1.7034747e-01 5.1942021e-01
-1.4599496e+00 -6.4262635e-01 -5.9185928e-01 3.4793091e-01
-7.2020888e-01 3.8255253e-01 -4.1915452e-01 -8.8825274e-01
-1.7427632e-01 -1.0579674e+00 1.5135012e+00 4.4560543e-01
3.1038314e-01 -9.0202063e-01 -7.3634379e-02 6.0646617e-01
-5.4597929e-02 4.0025723e-01 8.7590152e-01 -4.3946918e-02
-1.0639516e+00 3.3235672e-01 -4.8367068e-01 4.9724570e-01
1.5976486e-01 -1.6000682e-01 -1.3808949e+00 1.8093051e-01
1.9303286e-01 -1.8793152e-01 8.3328038e-01 6.2423289e-01
1.4465823e+00 1.3974344e-02 -3.0811355e-01 9.1647989e-01
1.6815163e+00 1.8739529e-01 5.8795691e-01 2.6971921e-02
1.2076020e+00 9.1081977e-01 5.2198046e-01 1.7749010e-01
3.9057493e-01 3.9841360e-01 7.0623052e-01 -4.3050808e-01
-1.2793179e-01 -1.3490342e-01 1.7877790e-01 4.1706622e-01
-3.7070926e-02 -4.1817775e-01 -7.0929068e-01 5.4009056e-01
-1.4198539e+00 -6.4057714e-01 -5.2032071e-01 1.9467605e+00
7.4606502e-01 -1.3290174e-01 -2.4022685e-01 -4.0148962e-02
6.2019521e-01 2.7040675e-01 -7.3462659e-01 -1.8902570e-01
-2.4625874e-01 2.0110095e-02 7.6663506e-01 7.5034034e-01
-1.1785767e+00 1.1716046e+00 6.3220353e+00 6.7694587e-01
-7.6973063e-01 1.0287802e-01 7.9344213e-01 2.0834106e-01
-8.2368994e-01 2.9544191e-02 -8.1130332e-01 -2.8608820e-01
1.0476438e-01 6.6518450e-01 3.5804030e-01 8.5061127e-01
8.1089884e-02 -5.4288250e-01 -9.5830882e-01 9.3636066e-01
3.1840578e-01 -1.0931422e+00 1.1762429e-01 -2.3251340e-01
1.1857128e+00 3.2528520e-01 -8.7766066e-02 -2.6306778e-01
5.5942386e-01 -7.6135486e-01 1.1438410e+00 7.8361696e-01
6.0169405e-01 -4.6804377e-01 -6.0498539e-02 4.3926680e-01
-1.1326369e+00 3.5321757e-01 -6.2766749e-01 4.4319680e-01
4.1151011e-01 9.7748965e-01 -7.2153550e-01 6.0227257e-01
1.1190041e+00 6.1773318e-01 -4.2094892e-01 8.7303239e-01
-1.7442147e-01 2.9000613e-01 -7.2793967e-01 3.2365662e-01
1.1356276e-01 -3.5518521e-01 6.8825102e-01 1.1317383e+00
-1.1297226e-01 3.4080589e-01 2.2767511e-01 1.4771901e+00
-1.1795773e-01 1.1028405e-01 -5.4097593e-01 3.9670673e-01
1.6763946e-02 1.4083569e+00 -1.2955743e+00 -1.9718155e-01
-2.9773217e-01 1.3752074e+00 4.0073756e-02 7.3818094e-01
-7.5011295e-01 -3.3460993e-01 2.3461935e-01 1.7029086e-01
3.8617688e-01 -3.3275601e-01 -3.4995052e-01 -9.7000247e-01
-1.1790500e-02 -1.6162314e-01 1.5919250e-02 -1.4099277e+00
-1.0941405e+00 4.9223867e-01 3.9604020e-01 -8.9926463e-01
2.9235482e-01 -6.0446441e-01 -4.1075659e-01 7.0007879e-01
-1.9409094e+00 -1.2673695e+00 -4.1575733e-01 7.2263741e-01
7.6124674e-01 3.7423733e-01 5.0188333e-01 1.6624454e-01
-1.1751787e-01 -1.5759668e-01 6.2480047e-02 -5.5269878e-02
1.3358730e-01 -1.5078944e+00 2.4738130e-01 9.5893115e-01
4.2166904e-01 2.5454876e-01 3.4214154e-01 -5.5798137e-01
-1.0854235e+00 -1.4973252e+00 2.5743917e-01 -6.3870335e-01
-9.6919380e-02 -5.3748935e-01 -7.5900751e-01 6.7849863e-01
-5.2682549e-02 9.6287906e-02 6.0486633e-01 -2.8667325e-01
-1.6547905e-01 -8.3351246e-04 -1.3594140e+00 5.1199389e-01
1.2029033e+00 -5.3806913e-01 -4.6655270e-01 5.8676112e-01
9.2561418e-01 -6.6065490e-01 -8.7344027e-01 7.1485633e-01
-6.3290805e-02 -1.0836968e+00 1.4406613e+00 -7.4864410e-02
1.2621908e-01 -7.6054740e-01 -4.6078426e-01 -9.5896047e-01
-1.1542565e-01 -3.2220003e-01 3.2086310e-01 1.1369398e+00
3.6347333e-01 -1.9667214e-01 7.2302854e-01 6.9566202e-01
-4.4862819e-01 -3.7387258e-01 -5.1105100e-01 -1.8269821e-01
-2.2918376e-01 -1.0116514e+00 5.3613955e-01 9.5686954e-01
-1.0258681e+00 7.3644742e-02 2.4964133e-02 6.4433861e-01
1.0438875e+00 4.6763173e-01 8.8142556e-01 -1.1963842e+00
-2.9064065e-01 -3.4547010e-01 -2.1001866e-01 -1.6973940e+00
1.8992582e-02 -1.1981391e+00 5.3322679e-01 -1.8741422e+00
1.6470151e-01 -6.9834906e-01 -7.8558132e-02 3.4616324e-01
6.7515522e-02 5.8972067e-01 -1.1716391e-01 1.6224362e-01
-8.4601533e-01 7.0825207e-01 1.3870486e+00 -4.0714946e-01
-3.8907212e-01 -6.9050118e-02 -5.5652297e-01 1.1013216e+00
5.5343682e-01 -5.2094114e-01 -7.2486275e-01 -9.2522395e-01
-8.6097037e-03 -4.2710558e-01 7.5832337e-01 -6.7383713e-01
2.7128869e-01 -4.3625292e-01 4.3843430e-01 -1.0732410e+00
4.1284981e-01 -9.6863455e-01 2.0815194e-01 -3.2360041e-01
-1.8239085e-01 -6.1545765e-01 1.3446407e-01 7.1517843e-01
4.3990023e-02 -3.6378682e-01 8.5294765e-01 -4.6980837e-01
-1.1099578e+00 4.6757838e-01 -4.2874074e-01 -1.7245683e-01
1.0286671e+00 -4.6975178e-01 8.6746447e-02 -9.0166014e-03
-6.5867692e-01 1.9931681e-01 4.2642999e-01 2.6216450e-01
9.4788951e-01 -1.0109671e+00 -4.2900389e-01 2.4935462e-01
1.8701673e-01 1.1366557e+00 5.1576781e-01 5.5386353e-01
-8.4855795e-01 8.3925866e-02 1.3288300e-01 -1.1411331e+00
-1.2108713e+00 2.9336050e-01 6.8437761e-01 3.5534412e-01
-9.5965493e-01 1.1639493e+00 9.7610056e-01 -1.0836043e+00
2.3171353e-01 -6.3361335e-01 -1.6579324e-01 -4.9072838e-01
3.3053553e-01 1.4839432e-01 -6.5492071e-02 -8.1196630e-01
-1.5976954e-01 9.3199867e-01 2.9727513e-02 -1.5072970e-01
1.3964720e+00 -4.9882346e-01 -2.4411377e-01 5.7299137e-01
1.0295740e+00 -1.4388566e-01 -1.5172162e+00 -5.2654934e-01
-3.3559635e-01 -5.8466929e-01 6.1727023e-01 -6.5613264e-01
-1.1731783e+00 8.0783576e-01 5.5599970e-01 7.8994662e-02
1.2698253e+00 4.1499439e-01 6.7888314e-01 3.0536035e-01
5.5270588e-01 -1.0130405e+00 -4.6259187e-02 4.4290602e-01
7.1364999e-01 -1.1495723e+00 1.8428630e-01 -8.1956363e-01
-3.2430243e-01 9.6289724e-01 5.8011091e-01 -4.4081374e-03
9.8517430e-01 1.7556296e-01 4.6968564e-02 -5.2780640e-01
-8.9227982e-02 -3.2200235e-01 5.8088332e-01 7.8077358e-01
1.4939912e-01 -2.4989301e-01 6.3688558e-01 1.2580895e-01
1.3214524e-01 -5.0991935e-01 2.0121054e-01 9.0998679e-01
-6.6250783e-01 -6.5405041e-01 -4.6743140e-01 2.0404975e-01
-3.0133682e-01 -9.6658781e-02 -2.8453377e-01 3.0622539e-01
3.5027447e-01 6.6332138e-01 3.0858135e-01 -5.8755474e-03
3.6745080e-01 -2.1017334e-01 7.7525198e-01 -8.6244708e-01
-2.7873185e-01 3.3817723e-01 -4.0041444e-01 -5.4130703e-01
-1.0394181e+00 -4.3604794e-01 -1.5709720e+00 2.0205775e-01
-5.5486202e-01 -1.8358195e-01 7.8910625e-01 7.8555518e-01
6.2122121e-02 6.0321164e-01 8.5690451e-01 -1.2519057e+00
3.5443664e-01 -4.4316566e-01 -7.4824518e-01 3.4300804e-01
2.8161249e-01 -5.2424222e-01 -1.9303066e-01 5.3995085e-01] | [8.841636657714844, -2.9120452404022217] |
085587f5-f145-43f7-aa7e-04400a97ab4d | credit-card-fraud-detection-using | null | null | https://link.springer.com/chapter/10.1007/978-3-319-46675-0_53 | https://link.springer.com/chapter/10.1007/978-3-319-46675-0_53 | Credit Card Fraud Detection Using Convolutional Neural Networks | Credit card is becoming more and more popular in financial transactions, at the same time frauds are also increasing. Conventional methods use rule-based expert systems to detect fraud behaviors, neglecting diverse situations, extreme imbalance of positive and negative samples. In this paper, we propose a CNN-based fraud detection framework, to capture the intrinsic patterns of fraud behaviors learned from labeled data. Abundant transaction data is represented by a feature matrix, on which a convolutional neural network is applied to identify a set of latent patterns for each sample. Experiments on real-world massive transactions of a major commercial bank demonstrate its superior performance compared with some state-of-the-art methods. | ['and Liqing Zhang', 'Yi Tu', 'Dawei Cheng', 'Kang Fu'] | 2016-10-16 | null | null | null | international-conference-on-neural-3 | ['fraud-detection'] | ['miscellaneous'] | [-5.01164019e-01 -7.34273791e-01 -3.35905492e-01 -6.03165507e-01
5.16486503e-02 -4.95709255e-02 1.44094899e-02 1.63117632e-01
-3.63623321e-01 6.35625482e-01 -1.43910617e-01 -2.85682768e-01
2.36388907e-01 -1.06658852e+00 -2.38721341e-01 -3.74432176e-01
-2.45045707e-01 4.92087454e-01 -2.00551450e-01 -2.56067902e-01
7.18192637e-01 3.28933209e-01 -1.15952158e+00 8.27185988e-01
7.03259468e-01 1.33375609e+00 -6.70879602e-01 7.74723589e-02
-2.56885737e-01 1.12523961e+00 -4.61648047e-01 -7.89519191e-01
3.73523682e-01 -3.29795599e-01 -1.86588317e-01 1.29004881e-01
-1.01614386e-01 -7.73932457e-01 -5.11987090e-01 1.22249246e+00
4.61579598e-02 -2.92408884e-01 6.04399502e-01 -1.34974313e+00
-8.23503673e-01 4.22790200e-01 -8.98049176e-01 5.81113219e-01
3.51478718e-02 3.06913853e-01 8.66307974e-01 -1.09210777e+00
4.34840053e-01 9.64070916e-01 1.19805086e+00 3.09647709e-01
-8.42830658e-01 -1.07969213e+00 -2.71775592e-02 3.40059668e-01
-8.86170208e-01 -1.18454387e-02 9.37602401e-01 -5.36715031e-01
1.26020050e+00 -3.39167535e-01 1.04570758e+00 1.14464641e+00
3.37634206e-01 9.59488869e-01 5.47021687e-01 -1.15818352e-01
2.25779787e-01 -2.50636898e-02 4.89384413e-01 6.13397300e-01
1.10320866e+00 2.05756336e-01 -7.33846664e-01 -5.90734482e-01
8.59066129e-01 9.43000197e-01 1.33424237e-01 -4.71676499e-01
-9.04012918e-01 1.02405465e+00 2.50351131e-01 2.06737697e-01
-7.19883382e-01 -2.40801778e-02 9.91742492e-01 7.87309110e-01
6.42705023e-01 -3.39246206e-02 -4.30768222e-01 -1.82829484e-01
-1.08125770e+00 7.72688627e-01 1.04607999e+00 5.51224887e-01
5.86636782e-01 1.37310699e-01 1.34768710e-01 6.26855969e-01
4.37225729e-01 -2.36193044e-03 9.35545504e-01 -4.66184229e-01
1.00637114e+00 1.37418234e+00 3.35234374e-01 -1.35300970e+00
-3.56040090e-01 -5.02951562e-01 -1.41467106e+00 1.95290878e-01
5.26097715e-01 -1.78960130e-01 -6.65991902e-01 9.41187322e-01
-1.11922450e-01 8.04915801e-02 -1.40343020e-02 1.05941677e+00
-1.03378855e-01 2.36619592e-01 -7.71164671e-02 -2.31368765e-01
1.15899169e+00 -6.62377775e-01 -7.77257502e-01 -2.14656994e-01
5.66352785e-01 -4.29234326e-01 6.39865398e-01 1.05342662e+00
-6.30146086e-01 -1.62278309e-01 -1.00101054e+00 2.54227728e-01
-3.57132435e-01 3.01303089e-01 1.03307605e+00 5.69981754e-01
-2.58550078e-01 8.03615689e-01 -9.93204236e-01 -1.77102555e-02
1.02382886e+00 1.01814702e-01 -3.03218305e-01 -1.13672949e-01
-1.14518166e+00 7.14251041e-01 6.40103579e-01 7.25795746e-01
-6.46788180e-01 -2.49770090e-01 -6.26763999e-01 1.74355984e-01
-6.08468754e-03 -4.50357199e-01 1.27219796e+00 -1.37373900e+00
-1.00385273e+00 8.97248209e-01 2.86519587e-01 -9.15770531e-01
1.02396452e+00 -5.62625349e-01 -6.78861558e-01 -2.37992287e-01
1.86185192e-04 -3.49654824e-01 6.16499603e-01 -8.27683270e-01
-8.15114737e-01 -7.54714847e-01 -6.29634976e-01 -7.86839947e-02
-6.09824479e-01 1.67510301e-01 -1.04772924e-02 -8.51784587e-01
5.74774265e-01 -2.50379473e-01 -1.76865160e-01 -1.36112445e-03
-3.16687107e-01 -2.98825413e-01 9.69198823e-01 -7.37149596e-01
1.47039819e+00 -1.97471130e+00 -5.91385305e-01 4.29542601e-01
2.57127970e-01 3.23620677e-01 5.40645063e-01 5.53104460e-01
-5.78600019e-02 -7.71564916e-02 -4.54695523e-01 -2.24321619e-01
-7.60301426e-02 1.40694812e-01 -5.94063818e-01 5.86559057e-01
4.69920427e-01 7.77011693e-01 -8.45618069e-01 -1.97034448e-01
3.89099047e-02 -6.56708628e-02 -3.79570663e-01 3.19402754e-01
3.00234500e-02 -7.77616426e-02 -5.19868910e-01 1.17352045e+00
1.02510381e+00 -2.50787258e-01 4.05846000e-01 9.30939242e-02
2.53613532e-01 3.55387405e-02 -1.11145484e+00 1.31363165e+00
1.30470783e-01 3.98208380e-01 -2.92517960e-01 -1.75583649e+00
1.23931479e+00 3.14837456e-01 3.01733315e-01 -7.12252796e-01
1.66465137e-02 7.69419372e-01 4.11553979e-02 -7.62279809e-01
3.00590396e-01 -6.15161061e-01 -1.67057574e-01 5.98827064e-01
-6.49134591e-02 7.14144051e-01 8.64853114e-02 -1.17884541e-03
8.96113634e-01 -4.39010561e-02 3.86850297e-01 -1.34061143e-01
1.80531204e-01 2.11040065e-01 1.10531902e+00 7.18650997e-01
-5.93891621e-01 4.30566877e-01 7.82998443e-01 -1.52109063e+00
-1.04689789e+00 -7.57034779e-01 -1.25640005e-01 5.44061184e-01
1.20860651e-01 2.63758034e-01 -4.25628364e-01 -8.01324368e-01
8.27370465e-01 2.56731033e-01 -7.85004616e-01 -2.70386666e-01
-8.05682182e-01 -1.33445978e+00 7.09844649e-01 6.87194347e-01
9.14057136e-01 -1.64068508e+00 -8.59775126e-01 6.81174278e-01
-1.27561437e-02 -5.24720132e-01 -8.04167762e-02 2.22521022e-01
-1.52157593e+00 -1.50505650e+00 -4.34990108e-01 -7.13375032e-01
6.41438246e-01 9.73083377e-02 1.29809725e+00 3.46411586e-01
-3.88222456e-01 -8.07149529e-01 -2.32122466e-01 -4.43425626e-01
-3.14359665e-02 -7.34380037e-02 5.98521978e-02 4.05985594e-01
1.36723173e+00 -4.35763299e-01 -7.51684487e-01 4.01681177e-02
-8.92353594e-01 -1.67861372e-01 6.03762627e-01 1.22591770e+00
1.22438431e-01 8.26619938e-02 9.60854053e-01 -1.29032421e+00
9.48492527e-01 -1.06446779e+00 -2.81023026e-01 2.06413046e-01
-1.01152802e+00 -3.85051519e-01 6.48276329e-01 -2.15659916e-01
-1.03448892e+00 -3.53436410e-01 5.31125665e-01 -5.27239978e-01
-1.14705451e-01 8.23531866e-01 1.96821257e-01 5.48266649e-01
4.89184260e-01 2.90453792e-01 -1.46207765e-01 -6.84719324e-01
-2.20492110e-01 9.87545609e-01 5.31548083e-01 -2.71985471e-01
3.01355332e-01 5.88694394e-01 -5.47208846e-01 8.38508904e-02
-6.69678509e-01 -6.69691026e-01 -4.99274820e-01 1.20162934e-01
8.39984566e-02 -8.84835541e-01 -6.77560687e-01 1.33923161e+00
-1.15486836e+00 9.71269980e-02 -1.47548979e-02 5.56045830e-01
-4.06151980e-01 3.18255574e-01 -1.16822207e+00 -1.09654689e+00
-6.06864095e-01 -3.27302128e-01 5.52185833e-01 2.27171540e-01
-2.14078128e-02 -8.78214002e-01 2.85654902e-01 2.72908896e-01
2.20992908e-01 3.60898226e-01 8.01217437e-01 -1.06775665e+00
-2.72160709e-01 -7.73470044e-01 -4.31031704e-01 5.96072316e-01
2.07680613e-01 1.95579585e-02 -6.42610669e-01 -4.24742520e-01
3.73028189e-01 -4.57951427e-01 1.28067994e+00 -3.36910551e-03
1.26851845e+00 -5.07122755e-01 -2.64265656e-01 7.27888227e-01
1.64947557e+00 4.11120236e-01 6.50543451e-01 6.63909137e-01
5.26348293e-01 4.23332155e-01 5.72419226e-01 8.75414968e-01
2.59144098e-01 5.52193150e-02 3.70808870e-01 5.63178211e-03
8.03760767e-01 -3.34026694e-01 2.45487124e-01 7.78559625e-01
-1.46108016e-01 -2.83903703e-02 -1.16757905e+00 7.04958558e-01
-2.42258501e+00 -1.16274583e+00 -1.23537794e-01 1.90924025e+00
6.08428180e-01 5.42216241e-01 1.71486080e-01 3.77700269e-01
9.32923496e-01 -3.05874795e-01 -1.03364599e+00 -2.11676836e-01
-2.17522651e-01 -1.30907362e-02 4.17194039e-01 -3.16344857e-01
-1.13879597e+00 5.96878886e-01 6.22467375e+00 3.61625373e-01
-1.02614069e+00 -8.20181742e-02 1.11912441e+00 -9.86453891e-02
-3.80145162e-02 -1.15377255e-01 -3.42871636e-01 8.65100145e-01
4.64987904e-01 -1.19076148e-01 1.43450394e-01 9.10034537e-01
8.29195827e-02 1.26089394e-01 -1.06643641e+00 1.06855488e+00
-8.13794062e-02 -1.34173393e+00 2.96394646e-01 -6.45673089e-03
6.39984846e-01 4.85937707e-02 -1.42798990e-01 4.77148980e-01
2.61663020e-01 -1.10889101e+00 5.77247977e-01 9.07938421e-01
2.42907152e-01 -9.33856368e-01 1.47051013e+00 3.56688201e-01
-7.38645732e-01 -4.62247282e-01 -5.38870513e-01 -5.65623343e-01
-1.57335624e-01 8.97773087e-01 -3.64569038e-01 5.44255316e-01
9.95271981e-01 1.15366518e+00 -1.90633908e-01 1.13827264e+00
1.90556824e-01 8.30293894e-01 -1.21858567e-01 1.19016252e-01
1.86344594e-01 -5.48377931e-01 -1.08543091e-01 1.36717761e+00
3.28127921e-01 -1.14914283e-01 5.20143658e-02 1.07629275e+00
-3.37815017e-01 1.08998492e-01 -7.89245367e-01 7.08676949e-02
2.37940654e-01 1.06022859e+00 -7.08311796e-01 -6.27838492e-01
-5.75267434e-01 1.01428986e+00 5.54593146e-01 3.08802992e-01
-3.34359348e-01 -5.78871310e-01 5.69319665e-01 -3.73626240e-02
3.08707893e-01 5.07331640e-02 -7.63145328e-01 -1.80623221e+00
5.35324454e-01 -9.76739049e-01 7.23131478e-01 -2.84757465e-01
-2.20832324e+00 3.28878798e-02 -5.58650970e-01 -1.70681298e+00
-2.49473751e-01 -8.62680078e-01 -1.03103745e+00 9.39459980e-01
-1.48848879e+00 -6.78368270e-01 -2.70336926e-01 6.44812763e-01
4.23095196e-01 -6.65871978e-01 6.53391421e-01 3.99721652e-01
-9.18624520e-01 4.88038361e-01 4.66923475e-01 8.50486100e-01
3.87859911e-01 -9.90683973e-01 7.54346132e-01 7.93163240e-01
5.97445667e-02 8.82416248e-01 2.04873860e-01 -8.53087008e-01
-1.09314466e+00 -8.90268207e-01 9.29509342e-01 -1.96278602e-01
6.30014956e-01 -1.72173530e-01 -1.33456695e+00 7.65703857e-01
-2.25856647e-01 2.63200521e-01 7.37407029e-01 7.49131888e-02
-6.40653789e-01 -3.19589138e-01 -1.51522458e+00 -1.17042707e-02
6.33058608e-01 -4.27178174e-01 -7.88707733e-01 3.66249308e-02
2.29517147e-02 -4.15356345e-02 -4.39055413e-01 3.41845810e-01
8.75251055e-01 -1.36099935e+00 5.19114554e-01 -1.10302556e+00
6.32075787e-01 4.09687385e-02 2.58300841e-01 -1.00152445e+00
-1.70097575e-01 -1.53200507e-01 -6.12674177e-01 7.50240684e-01
-5.79223484e-02 -9.03419197e-01 1.26721096e+00 4.18576747e-01
3.37586552e-01 -9.39077258e-01 -1.00661635e+00 -4.90516275e-01
1.46985874e-01 -2.17459202e-01 7.12961733e-01 1.57465720e+00
4.95331168e-01 -2.50536948e-01 -4.62162435e-01 -2.35987604e-01
7.15725899e-01 4.33840275e-01 4.55702931e-01 -1.42021990e+00
-8.65354165e-02 -5.67585111e-01 -6.11242175e-01 -4.92224455e-01
-2.81073213e-01 -5.24743676e-01 -4.17160749e-01 -1.00706482e+00
3.07207435e-01 -3.38786364e-01 -1.05662012e+00 3.68252486e-01
-1.98796809e-01 2.04843760e-01 -1.35391057e-01 8.12514067e-01
-5.02304673e-01 3.68670881e-01 6.86524153e-01 -1.44646555e-01
-1.41380103e-02 1.01060204e-01 -6.48499429e-01 9.92002547e-01
1.27163923e+00 -5.26884615e-01 1.12800069e-01 -4.41662550e-01
5.95469117e-01 1.52480572e-01 4.06559378e-01 -8.02591443e-01
2.12539643e-01 -3.54751199e-01 8.01019967e-01 -6.65840685e-01
-3.80000800e-01 -5.71328342e-01 -1.34650826e-01 9.62870181e-01
-1.67963192e-01 2.21501693e-01 -1.09791644e-01 7.27306604e-01
-8.04694355e-01 -2.72237837e-01 4.64123487e-01 -4.32080895e-01
-5.49078226e-01 4.58802015e-01 -1.14241280e-01 -9.57503319e-02
7.92750180e-01 -4.00713682e-01 -2.47781858e-01 2.07882002e-02
-4.00335163e-01 3.25065315e-01 1.88785091e-01 3.70212585e-01
9.64561403e-01 -1.58233082e+00 -1.02722979e+00 6.21197343e-01
3.74387234e-01 1.54056683e-01 1.91038862e-01 4.94305253e-01
-1.08941150e+00 2.12465465e-01 -6.92465305e-01 -1.77019492e-01
-5.02767444e-01 3.26931149e-01 6.41449749e-01 -7.25770295e-01
-6.75705314e-01 6.80972815e-01 -2.07282454e-01 -4.43086952e-01
3.50102335e-02 -4.94006693e-01 -2.47180790e-01 5.68819046e-02
4.52729642e-01 5.24048746e-01 1.93151861e-01 -9.15969908e-02
-2.96670318e-01 -5.40790223e-02 -5.26340842e-01 2.84565449e-01
1.51618123e+00 3.87278795e-01 -1.97814971e-01 6.61799669e-01
9.73384976e-01 -7.30336010e-01 -1.26272726e+00 -3.14326733e-01
6.63407624e-01 -7.93341398e-01 -3.30183446e-01 -6.54564977e-01
-1.40047824e+00 1.06797576e+00 5.81653655e-01 4.58209574e-01
8.94219875e-01 -7.80405998e-01 1.04934192e+00 6.91674948e-01
6.29586220e-01 -1.38386464e+00 4.34127897e-02 3.21182996e-01
6.08693063e-01 -1.48038590e+00 -1.32338420e-01 1.43459111e-01
-6.74687088e-01 1.48481929e+00 8.10920596e-01 -9.81950819e-01
8.34826469e-01 5.03944568e-02 2.51637518e-01 -5.11682749e-01
-8.20837379e-01 6.62625968e-01 -4.55679804e-01 3.80119145e-01
5.27433097e-01 2.26345375e-01 -4.34937030e-01 1.02896619e+00
2.90921591e-02 6.79161906e-01 3.18566531e-01 9.79724646e-01
-3.37763608e-01 -8.87085974e-01 -1.87349990e-01 1.06202805e+00
-8.43524873e-01 -6.19130246e-02 -1.79516792e-01 7.05042899e-01
3.51459205e-01 5.55006206e-01 6.27728641e-01 -2.59876549e-01
3.97813529e-01 2.77159184e-01 -8.90068859e-02 -5.35031676e-01
-1.00774670e+00 -3.94584805e-01 -2.85022408e-01 -5.10546446e-01
-2.72652715e-01 -8.94989431e-01 -1.01404166e+00 -3.93783748e-01
-2.96675920e-01 1.38230203e-02 1.30589336e-01 6.47881746e-01
1.39712289e-01 4.89960164e-02 7.63920605e-01 -3.03111881e-01
-1.08146393e+00 -1.35227585e+00 -1.03738284e+00 1.08442700e+00
3.75253558e-01 -5.52333176e-01 -3.79411936e-01 9.73046273e-02] | [7.436163902282715, 5.716022491455078] |
8cec2074-8127-4c42-8be4-9bf7613c068b | automatic-tagging-and-retrieval-of-e-commerce | null | null | https://aclanthology.org/N16-2004 | https://aclanthology.org/N16-2004.pdf | Automatic tagging and retrieval of E-Commerce products based on visual features | null | ['Vasu Sharma', 'Harish Karnick'] | 2016-06-01 | null | null | null | naacl-2016-6 | ['product-categorization'] | ['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] | [-7.408280849456787, 3.6767075061798096] |
b1f359ab-8dfc-445a-8f66-5806aad6db09 | socialdial-a-benchmark-for-socially-aware | 2304.12026 | null | https://arxiv.org/abs/2304.12026v1 | https://arxiv.org/pdf/2304.12026v1.pdf | SocialDial: A Benchmark for Socially-Aware Dialogue Systems | Dialogue systems have been widely applied in many scenarios and are now more powerful and ubiquitous than ever before. With large neural models and massive available data, current dialogue systems have access to more knowledge than any people in their life. However, current dialogue systems still do not perform at a human level. One major gap between conversational agents and humans lies in their abilities to be aware of social norms. The development of socially-aware dialogue systems is impeded due to the lack of resources. In this paper, we present the first socially-aware dialogue corpus - SocialDial, based on Chinese social culture. SocialDial consists of two parts: 1,563 multi-turn dialogues between two human speakers with fine-grained labels, and 4,870 synthetic conversations generated by ChatGPT. The human corpus covers five categories of social norms, which have 14 sub-categories in total. Specifically, it contains social factor annotations including social relation, context, social distance, and social norms. However, collecting sufficient socially-aware dialogues is costly. Thus, we harness the power of ChatGPT and devise an ontology-based synthetic data generation framework. This framework is able to generate synthetic data at scale. To ensure the quality of synthetic dialogues, we design several mechanisms for quality control during data collection. Finally, we evaluate our dataset using several pre-trained models, such as BERT and RoBERTa. Comprehensive empirical results based on state-of-the-art neural models demonstrate that modeling of social norms for dialogue systems is a promising research direction. To the best of our knowledge, SocialDial is the first socially-aware dialogue dataset that covers multiple social factors and has fine-grained labels. | ['Gholamreza Haffari', 'Zhaleh Semnani-Azad', 'Ingrid Zukerman', 'Suraj Sharma', 'Lay-Ki Soon', 'Lizhen Qu', 'Yuncheng Hua', 'Xiaoxi Kang', 'Tao Feng', 'Linhao Luo', 'YuFei Wang', 'Zhuang Li', 'Haolan Zhan'] | 2023-04-24 | null | null | null | null | ['synthetic-data-generation', 'synthetic-data-generation', 'culture'] | ['medical', 'miscellaneous', 'speech'] | [-1.93647936e-01 6.69243276e-01 9.13598388e-02 -6.99818611e-01
-2.42496803e-01 -4.15891171e-01 9.88301218e-01 -2.65107691e-01
-4.25587416e-01 1.21883726e+00 6.75935090e-01 4.92943451e-02
1.89433411e-01 -7.95676947e-01 -1.31491289e-01 -3.30564797e-01
9.74656492e-02 8.95050764e-01 1.16109669e-01 -9.45102692e-01
6.54316992e-02 -2.22682223e-01 -1.45771182e+00 4.05045450e-01
1.33873224e+00 5.49002349e-01 -4.61744005e-03 8.36239278e-01
-2.56659746e-01 9.68929052e-01 -1.09527838e+00 -7.26199150e-01
-1.20592892e-01 -9.42921281e-01 -1.14393759e+00 2.01796889e-01
-1.52519912e-01 -6.20158017e-01 -1.84672832e-01 7.69868553e-01
7.25164294e-01 2.71895111e-01 6.52254760e-01 -1.42773724e+00
-8.32353473e-01 1.10630882e+00 2.43102804e-01 -5.00056267e-01
6.73213780e-01 3.42967153e-01 1.19419205e+00 -5.28087616e-01
7.70877779e-01 1.61349237e+00 4.47672158e-01 1.20083833e+00
-8.74406219e-01 -3.89133900e-01 -1.98191926e-01 -4.37700190e-02
-6.89728379e-01 -6.43313229e-01 6.18761659e-01 -4.38223988e-01
1.01441193e+00 2.60444254e-01 8.98326635e-01 1.60477495e+00
-3.68059427e-01 8.46975744e-01 1.29920232e+00 -5.73253036e-01
2.03909889e-01 3.15369934e-01 -6.76299781e-02 7.37601876e-01
-3.97839487e-01 -1.67881414e-01 -6.70069933e-01 -2.57554978e-01
5.15681624e-01 -5.22628903e-01 -1.39419273e-01 1.24749608e-01
-1.39047945e+00 1.00821149e+00 4.34433706e-02 5.16843736e-01
5.37368320e-02 -2.90609539e-01 5.67677855e-01 7.55994380e-01
5.56009233e-01 8.77805293e-01 -4.61043209e-01 -8.50429118e-01
-1.87225387e-01 4.50347185e-01 1.59083271e+00 1.13901877e+00
6.41070724e-01 -1.02992199e-01 -3.72265846e-01 1.67180085e+00
3.49841505e-01 4.71353322e-01 4.89622772e-01 -1.45759940e+00
3.36815089e-01 9.52748299e-01 4.76984084e-02 -9.47772563e-01
-5.86333752e-01 3.04657280e-01 -8.13695669e-01 -3.16597313e-01
8.02209556e-01 -6.60715580e-01 -7.96521455e-02 1.88115251e+00
3.12880099e-01 -3.86223376e-01 4.67833221e-01 6.57751560e-01
1.19943523e+00 6.60770059e-01 -1.88871115e-01 -1.03887722e-01
1.24691248e+00 -1.18648791e+00 -9.38745975e-01 -4.62166965e-02
9.10134614e-01 -4.98902977e-01 1.46816552e+00 1.90917015e-01
-9.14320648e-01 -1.73666537e-01 -7.84870207e-01 -1.12515479e-01
-3.42775136e-01 -1.31979913e-01 8.53255868e-01 8.32349122e-01
-9.94934499e-01 3.63720596e-01 -1.69735312e-01 -6.74702346e-01
-8.93147290e-02 5.31194359e-02 -1.71081722e-01 2.80415446e-01
-1.91681790e+00 1.03989434e+00 2.12124974e-01 -1.43752605e-01
-5.30157208e-01 -2.03552693e-01 -8.76330376e-01 -1.84125751e-01
5.53747952e-01 -4.23176974e-01 1.65911460e+00 -8.15304518e-01
-2.26277494e+00 9.82127011e-01 1.19109578e-01 -1.97427303e-01
7.89949536e-01 1.48068309e-01 -3.63501340e-01 -1.27735645e-01
2.31481910e-01 6.96298838e-01 2.04470962e-01 -1.11408818e+00
-6.80746317e-01 -4.83202934e-02 5.95767915e-01 4.35611546e-01
-6.31480634e-01 2.25084394e-01 -3.59033465e-01 -2.48539418e-01
-5.84105194e-01 -1.07392514e+00 -1.53655902e-01 -2.84351677e-01
-5.97411215e-01 -6.69384360e-01 3.66301030e-01 -4.43421602e-01
1.07907724e+00 -1.81344938e+00 1.97834775e-01 -1.01388365e-01
2.85768688e-01 4.03425783e-01 -7.78631940e-02 6.70772612e-01
7.88449109e-01 2.79207438e-01 -2.31303304e-01 -5.17263830e-01
4.19084519e-01 4.41358745e-01 1.19341582e-01 -1.02021642e-01
-6.59218617e-03 8.11350644e-01 -1.21333277e+00 -6.25612855e-01
1.82058185e-01 8.83743167e-02 -8.74955177e-01 7.13581324e-01
-5.73401690e-01 7.15433061e-01 -3.76220077e-01 2.50212491e-01
1.38733953e-01 -1.78565115e-01 4.26531196e-01 3.64000708e-01
3.58851701e-02 4.92481053e-01 -5.68993092e-01 1.72702324e+00
-6.62485361e-01 6.48033798e-01 1.70027167e-01 -3.94411355e-01
1.23761880e+00 5.22851944e-01 4.36412632e-01 -5.59387028e-01
3.58847499e-01 2.36655638e-01 2.94303983e-01 -7.64008999e-01
8.94100130e-01 -1.51367690e-02 -5.61692834e-01 9.14187968e-01
2.31605440e-01 -5.16174376e-01 7.52456486e-01 3.31877053e-01
9.61019576e-01 -2.29510024e-01 2.24086165e-01 -1.17319554e-01
6.49018645e-01 -4.75302078e-02 6.53946698e-01 6.38063788e-01
-5.78205585e-01 2.35785469e-01 1.02257943e+00 -2.38240972e-01
-9.28970695e-01 -5.67490697e-01 9.24913809e-02 1.57731628e+00
-1.75936848e-01 -5.19329309e-01 -1.07797503e+00 -8.10870886e-01
-2.29620785e-01 7.86682844e-01 -5.11224031e-01 6.64429665e-02
-4.78458136e-01 -6.13573492e-01 1.13905370e+00 -1.07869536e-01
9.26206291e-01 -1.56022966e+00 -4.02698368e-02 3.16842198e-01
-5.55805862e-01 -1.34063005e+00 -3.84197891e-01 -5.15405416e-01
-2.41132930e-01 -1.30437076e+00 -5.29393673e-01 -7.19172120e-01
3.02062005e-01 -3.57632190e-02 1.29061234e+00 2.46986613e-01
3.49316031e-01 1.65909261e-01 -6.73189580e-01 -3.00934136e-01
-1.31359279e+00 4.17536885e-01 1.30496889e-01 -1.16877280e-01
5.21235883e-01 -4.83927608e-01 -2.26537660e-01 8.09636116e-01
-4.18373108e-01 3.90617728e-01 5.20780683e-02 1.01315320e+00
-5.71693838e-01 -3.21817607e-01 1.02251184e+00 -1.23696625e+00
1.51097715e+00 -4.32695597e-01 -4.14738953e-02 1.37617335e-01
-3.03259224e-01 -2.41040289e-01 8.30574930e-01 -1.83453128e-01
-1.52295506e+00 -5.99954188e-01 -2.26031989e-01 5.43698072e-01
-3.43792617e-01 3.84716332e-01 -2.78358936e-01 5.03150880e-01
9.84072149e-01 -9.56703909e-03 3.96661967e-01 -2.10175231e-01
7.38280475e-01 1.46582222e+00 1.57431230e-01 -1.08247387e+00
2.18526989e-01 9.35037434e-03 -7.94763327e-01 -1.31018150e+00
-8.79930735e-01 -1.13136128e-01 -5.01442313e-01 -7.38218188e-01
7.78060496e-01 -6.45579875e-01 -1.01095438e+00 9.07989144e-01
-1.26728749e+00 -8.33989501e-01 -2.05355048e-01 2.56822973e-01
-6.97249234e-01 3.21827054e-01 -1.07160270e+00 -8.55251312e-01
-2.57750660e-01 -1.15264773e+00 6.15437686e-01 2.32815117e-01
-7.13032901e-01 -1.19915617e+00 2.42382228e-01 1.05917287e+00
5.77283442e-01 5.32079525e-02 7.29418099e-01 -9.37688887e-01
1.69597901e-02 1.32777900e-01 -2.62518644e-01 5.06341696e-01
3.66147131e-01 2.06341282e-01 -9.92274702e-01 -2.87728268e-04
-1.90049410e-01 -1.04851305e+00 1.61232218e-01 -2.78672516e-01
4.52745557e-01 -6.16466939e-01 1.50314748e-01 -9.51975584e-02
2.23018244e-01 3.78667653e-01 4.69581246e-01 1.34814888e-01
6.87159717e-01 1.23510182e+00 5.34997225e-01 5.52058935e-01
1.15966892e+00 6.00730956e-01 -9.97852441e-03 1.63257882e-01
1.13714419e-01 -2.22827286e-01 4.29368168e-01 1.54315221e+00
-2.59895712e-01 -3.07817161e-01 -9.69308794e-01 4.75179136e-01
-2.06295109e+00 -9.07678306e-01 -4.55090627e-02 1.51997232e+00
1.49271941e+00 -4.81125601e-02 2.48136103e-01 -1.18024826e-01
8.46064568e-01 4.25071985e-01 -4.85764384e-01 -6.65216684e-01
-2.76733518e-01 -5.58297575e-01 -3.45181108e-01 7.29743779e-01
-8.45674932e-01 1.24069202e+00 5.80334139e+00 5.71325600e-01
-5.32146454e-01 7.16078356e-02 6.34290338e-01 1.31863728e-01
-1.74634695e-01 -2.07618773e-01 -7.01648414e-01 5.88999748e-01
8.96174252e-01 -2.87468433e-01 7.41837680e-01 7.36988187e-01
3.55082631e-01 7.44747370e-02 -1.14371812e+00 5.70523977e-01
1.54873386e-01 -1.05223703e+00 -1.85460851e-01 4.28798459e-02
8.84547591e-01 -2.51752939e-02 -5.37394941e-01 7.74344265e-01
9.63195443e-01 -9.50036168e-01 3.49533349e-01 4.38241035e-01
6.26994729e-01 -4.48412418e-01 7.83244848e-01 6.74528718e-01
-5.06187260e-01 1.07449576e-01 -2.30812535e-01 -3.64358932e-01
2.14209735e-01 3.92189384e-01 -1.12154913e+00 1.23639196e-01
5.32142341e-01 8.73987794e-01 -2.33254567e-01 2.65489012e-01
-4.12641138e-01 4.78834122e-01 -1.52472213e-01 -6.90351546e-01
1.93880141e-01 -4.24976528e-01 3.47831696e-01 1.22072661e+00
-2.47218590e-02 8.19903240e-03 2.58183777e-01 8.18839788e-01
-3.75991464e-01 3.40423286e-01 -8.16503286e-01 -2.59640098e-01
7.22062826e-01 1.13523650e+00 -1.03467830e-01 -2.18604848e-01
-5.27081251e-01 6.80854023e-01 5.44089198e-01 5.63842021e-02
-4.48078066e-01 -3.45987976e-01 6.75554574e-01 -2.33548179e-01
-6.76030278e-01 -1.87709406e-01 9.79362335e-03 -1.32600486e+00
-1.86964542e-01 -1.39753008e+00 1.17661029e-01 -4.82719243e-01
-1.65590513e+00 7.40675509e-01 -1.90238938e-01 -7.86334813e-01
-8.07540536e-01 -4.19411063e-01 -4.94680941e-01 5.63150525e-01
-9.81628060e-01 -1.15798903e+00 -4.06523675e-01 3.65376800e-01
7.54593074e-01 -7.22511232e-01 1.22244692e+00 1.36849895e-01
-5.31622529e-01 5.38245916e-01 -2.88948100e-02 6.15069211e-01
1.02730656e+00 -1.37528312e+00 4.54539269e-01 4.86059971e-02
-4.08960134e-01 5.32521188e-01 5.68715453e-01 -5.67154825e-01
-8.58574808e-01 -7.03919709e-01 1.13285315e+00 -4.22148138e-01
8.91143084e-01 -7.21093476e-01 -7.66862810e-01 4.41243738e-01
6.49956346e-01 -7.03927517e-01 9.50799108e-01 4.74046081e-01
-8.91498923e-02 1.57648057e-01 -1.24163330e+00 1.04877627e+00
1.18418169e+00 -5.84098816e-01 -7.26748168e-01 5.33881068e-01
8.63543570e-01 -4.41820234e-01 -1.24346268e+00 1.27713963e-01
4.50049877e-01 -1.43876278e+00 3.71351272e-01 -5.49254596e-01
6.34667516e-01 2.71922857e-01 -6.87998161e-02 -1.79878640e+00
2.79287338e-01 -1.13125908e+00 7.96979666e-02 1.68105972e+00
7.24085331e-01 -7.85229862e-01 7.85053492e-01 1.10126615e+00
-2.20538914e-01 -6.80830956e-01 -8.26944232e-01 -4.26831901e-01
2.26387069e-01 -2.53768265e-01 9.62890804e-01 1.37598467e+00
7.41873085e-01 9.43828344e-01 -6.63828015e-01 -6.87088430e-01
2.98848361e-01 -1.77158996e-01 1.34787464e+00 -1.21790707e+00
-2.08965436e-01 -5.24437428e-01 1.52288109e-01 -1.19536889e+00
5.35910428e-01 -6.82562649e-01 7.96082765e-02 -1.56150734e+00
-1.19517796e-01 -8.09549391e-01 5.55404544e-01 4.04969603e-01
-1.17226712e-01 -5.09972908e-02 1.63568914e-01 1.52041674e-01
-7.41706014e-01 1.16941118e+00 1.72717071e+00 -1.05527371e-01
-4.62907672e-01 -9.55667049e-02 -7.18514085e-01 8.72012675e-01
1.12441576e+00 -8.47190619e-02 -4.79422629e-01 -2.29724422e-01
2.99264699e-01 2.79091895e-01 -2.27982149e-01 -5.66477358e-01
2.57439762e-01 -3.79880190e-01 -5.97512424e-01 4.62368689e-02
5.33920825e-01 -2.68952668e-01 -4.80025411e-01 2.97389440e-02
-7.72320390e-01 -3.62783164e-01 -4.36766416e-01 2.45540977e-01
-2.82505155e-01 -2.25050524e-01 6.52594566e-01 -3.99334311e-01
-3.81364107e-01 -1.63338289e-01 -7.85101235e-01 5.92182934e-01
8.51777911e-01 1.01271600e-01 -8.63237143e-01 -9.58463430e-01
-5.68929017e-01 7.02385902e-01 4.68045175e-01 7.83484101e-01
3.04510027e-01 -1.17072201e+00 -9.29205954e-01 -1.04091130e-02
3.24087977e-01 -2.23276298e-03 1.81217045e-01 3.66481274e-01
-5.65735102e-01 3.49916369e-01 -2.76739329e-01 -3.90710711e-01
-9.61645186e-01 -2.14426532e-01 3.70702773e-01 -3.61949533e-01
-3.17948192e-01 5.43209612e-01 -2.65102684e-01 -1.54036021e+00
2.81496376e-01 1.49432365e-02 -5.96289337e-01 2.84568965e-01
5.25200188e-01 5.46768546e-01 -4.24310595e-01 -8.54466617e-01
2.36032382e-01 -3.15408967e-02 2.51132384e-04 -2.80597478e-01
1.19596040e+00 -2.83267409e-01 -5.32317698e-01 7.29877830e-01
8.33424211e-01 -3.55554968e-02 -1.12554598e+00 -4.61480886e-01
-1.79274920e-02 -3.87906551e-01 -6.41402423e-01 -9.11440849e-01
-7.74302125e-01 6.10807180e-01 -1.84453696e-01 7.56539643e-01
3.34089577e-01 -1.79653704e-01 9.12465453e-01 8.70360732e-01
6.04710519e-01 -1.61552572e+00 4.21586603e-01 1.20659959e+00
1.08860135e+00 -1.46868062e+00 -4.01969463e-01 -5.21497309e-01
-1.21648908e+00 7.56665766e-01 1.09992862e+00 2.24061683e-01
4.00347769e-01 -1.11916274e-01 6.13676369e-01 -1.39693722e-01
-9.78773773e-01 -7.23445937e-02 -1.95973948e-01 6.43948376e-01
7.34411299e-01 2.53763229e-01 -3.67538750e-01 6.99776828e-01
-8.13496232e-01 -1.81046918e-01 8.31462264e-01 6.45065367e-01
-4.11073565e-01 -1.32852101e+00 -3.61151248e-02 4.25672710e-01
-1.22189879e-01 6.49892017e-02 -9.33560491e-01 6.70628488e-01
-2.23373696e-01 1.67075861e+00 -2.52562672e-01 -5.92320979e-01
5.07887006e-01 1.65966108e-01 -9.68340319e-03 -8.16354156e-01
-9.37961996e-01 -4.66578811e-01 1.18086410e+00 -2.61008710e-01
-6.80653036e-01 -3.80950123e-01 -1.11326265e+00 -7.61978149e-01
-2.06297725e-01 6.05087936e-01 4.84509587e-01 9.76137400e-01
2.16728345e-01 3.38375747e-01 7.51727343e-01 -7.09517181e-01
-4.26634908e-01 -1.55633759e+00 -4.88265514e-01 6.16526127e-01
-2.68301725e-01 -5.88094771e-01 -4.85908717e-01 -2.92080939e-01] | [12.901918411254883, 8.13329792022705] |
486b7c2a-96f2-4d03-b3bc-fd8fa00c905e | deep-and-confident-prediction-for-time-series | 1709.01907 | null | http://arxiv.org/abs/1709.01907v1 | http://arxiv.org/pdf/1709.01907v1.pdf | Deep and Confident Prediction for Time Series at Uber | Reliable uncertainty estimation for time series prediction is critical in
many fields, including physics, biology, and manufacturing. At Uber,
probabilistic time series forecasting is used for robust prediction of number
of trips during special events, driver incentive allocation, as well as
real-time anomaly detection across millions of metrics. Classical time series
models are often used in conjunction with a probabilistic formulation for
uncertainty estimation. However, such models are hard to tune, scale, and add
exogenous variables to. Motivated by the recent resurgence of Long Short Term
Memory networks, we propose a novel end-to-end Bayesian deep model that
provides time series prediction along with uncertainty estimation. We provide
detailed experiments of the proposed solution on completed trips data, and
successfully apply it to large-scale time series anomaly detection at Uber. | ['Lingxue Zhu', 'Nikolay Laptev'] | 2017-09-06 | null | null | null | null | ['probabilistic-time-series-forecasting'] | ['time-series'] | [-5.36874950e-01 -2.36741498e-01 1.06689334e-02 -6.85063362e-01
-9.37101662e-01 -4.78358418e-01 5.32834411e-01 4.18127835e-01
-1.90812662e-01 7.65252590e-01 4.16385174e-01 -2.94977039e-01
-6.51062846e-01 -7.59447992e-01 -1.08436680e+00 -3.79970223e-01
-2.54447997e-01 6.04780853e-01 1.37517765e-01 -1.32544756e-01
8.09048191e-02 6.26136482e-01 -1.53242671e+00 -2.41937399e-01
5.88148594e-01 1.38910329e+00 -2.53298461e-01 4.84440893e-01
-5.63450018e-03 4.85422850e-01 -5.23900270e-01 -3.66930991e-01
2.01582521e-01 4.79516685e-01 -1.80631168e-02 -4.63004917e-01
-2.63536781e-01 -4.74706471e-01 -1.05627847e+00 5.63796818e-01
2.78953135e-01 7.35934615e-01 5.49126208e-01 -1.76489139e+00
-3.72160524e-01 9.40009892e-01 -5.03099024e-01 2.57242680e-01
-2.50627995e-01 2.81106144e-01 5.99789262e-01 -4.60242838e-01
-1.00798585e-01 1.21211505e+00 7.41245568e-01 2.72622585e-01
-6.93646371e-01 -7.45142937e-01 3.08596671e-01 4.28805888e-01
-1.25899005e+00 -9.96278971e-02 7.81551719e-01 -4.31440651e-01
9.37505066e-01 1.94837421e-01 3.40236604e-01 1.30452919e+00
6.61257148e-01 9.22549248e-01 7.40272164e-01 3.09512913e-01
4.97822762e-01 -4.56571579e-01 3.24365407e-01 -9.45550203e-02
-3.70191745e-02 6.41130149e-01 -7.42947936e-01 -3.25733691e-01
1.09671429e-01 6.00999534e-01 5.29909790e-01 3.56182665e-01
-8.65189373e-01 4.17297512e-01 3.03937286e-01 -1.72939762e-01
-5.90203643e-01 8.25589359e-01 2.66614139e-01 -7.94389993e-02
6.15725517e-01 1.11096598e-01 -5.51823020e-01 -8.61459136e-01
-8.88173223e-01 5.67426026e-01 6.56290174e-01 9.65004921e-01
2.93689400e-01 2.00027615e-01 -6.49775565e-01 4.64663684e-01
1.74686819e-01 7.77799964e-01 1.99662402e-01 -9.70287681e-01
2.96576381e-01 9.78090912e-02 6.04176700e-01 -1.05902290e+00
-7.39903212e-01 -4.45685089e-01 -6.75932705e-01 -2.92738587e-01
1.85226530e-01 -3.56933892e-01 -9.83234286e-01 1.76680255e+00
1.49821728e-01 9.84852791e-01 -2.70501435e-01 7.69344866e-01
1.25838235e-01 9.15975094e-01 4.14745435e-02 2.61680987e-02
8.71104240e-01 -3.03643823e-01 -8.11989427e-01 -2.31445387e-01
2.38345549e-01 -4.83827114e-01 4.04624075e-01 5.21756053e-01
-6.16738915e-01 -2.69847780e-01 -6.84111893e-01 1.66501254e-01
-5.48687100e-01 -1.58890486e-01 6.90629959e-01 4.42772567e-01
-4.47304577e-01 7.52633393e-01 -1.26262236e+00 3.22083384e-02
3.48376125e-01 1.73105568e-01 3.21778655e-02 -1.39708772e-01
-1.26814497e+00 9.76250052e-01 4.31586027e-01 5.99757135e-01
-9.72677708e-01 -7.91191757e-01 -8.08178782e-01 2.39862591e-01
3.06861550e-01 -3.31101716e-01 1.21957719e+00 1.35748833e-01
-1.35875320e+00 -1.01632677e-01 -1.39942601e-01 -1.14924431e+00
3.45837772e-01 -4.83798176e-01 -9.61232364e-01 -6.60444915e-01
-2.61914581e-01 3.69961977e-01 7.45785415e-01 -5.65750122e-01
-7.22563624e-01 -4.04408842e-01 -1.42799512e-01 -4.00384009e-01
-2.42401645e-01 -6.58648759e-02 -7.51608312e-02 -6.08891845e-01
-3.88884768e-02 -1.07507324e+00 -5.14577270e-01 -4.07839954e-01
-3.83198649e-01 -4.00927395e-01 8.51268589e-01 -8.58525753e-01
1.26439393e+00 -2.23225021e+00 -1.77955940e-01 4.94638354e-01
-2.29538716e-02 -2.83884108e-01 5.05071878e-02 5.68528295e-01
1.15484715e-01 -2.47092202e-01 -2.03900859e-01 -4.54680204e-01
5.97920299e-01 4.32350218e-01 -9.86184418e-01 5.05063534e-01
2.16981813e-01 9.61506248e-01 -7.85615265e-01 1.02530405e-01
4.58560079e-01 3.21934789e-01 -9.26756561e-02 -1.22734159e-03
-6.97434306e-01 2.59214938e-01 -3.60411167e-01 7.02608705e-01
6.12920284e-01 8.65307227e-02 -4.92224604e-01 1.29700778e-02
-1.97685584e-01 1.25127822e-01 -1.23577857e+00 1.41612518e+00
-3.88965994e-01 7.21837342e-01 -4.59099770e-01 -7.23166108e-01
9.12605464e-01 -5.63132018e-03 6.60685718e-01 -4.45761919e-01
3.25089931e-01 -3.19966897e-02 -1.11399390e-01 -2.19919726e-01
9.46943462e-01 1.04924381e-01 -5.84589183e-01 3.96302998e-01
-2.89784878e-01 -2.63898551e-01 1.68931216e-01 7.80813918e-02
1.14386916e+00 9.04388875e-02 -3.71818930e-01 1.82874233e-01
-1.85518637e-01 -1.35400340e-01 7.69942701e-01 4.70168293e-01
-2.32089996e-01 3.51958811e-01 3.56422722e-01 -4.54385847e-01
-7.45660007e-01 -1.09606826e+00 -2.73771584e-01 8.49041760e-01
7.63047785e-02 -2.62857974e-01 -1.07016280e-01 -2.34084681e-01
5.49388528e-01 1.42241883e+00 -4.90777165e-01 -4.71587092e-01
-1.75521523e-01 -7.41221368e-01 4.48592484e-01 9.18334663e-01
4.53367159e-02 -5.35585046e-01 -2.79589236e-01 5.17570496e-01
4.20118589e-03 -1.06688428e+00 -4.39990193e-01 2.13947501e-02
-6.32440090e-01 -5.35409451e-01 -1.54922277e-01 2.85725296e-01
1.18388854e-01 -1.62475750e-01 8.86772931e-01 -5.77439964e-01
-2.40368277e-01 6.37245536e-01 7.60329440e-02 -1.08690178e+00
-1.14145204e-01 -3.53264540e-01 5.86751401e-01 1.36922579e-02
6.18068278e-01 -6.45244956e-01 -4.56589788e-01 4.23088253e-01
-9.09006894e-01 -4.82572258e-01 2.60056496e-01 7.20328331e-01
7.80898035e-01 5.45423687e-01 9.51488972e-01 -5.33105955e-02
6.17521107e-01 -8.50406468e-01 -1.12898374e+00 1.77601606e-01
-5.77998459e-01 -2.78575858e-03 2.65878260e-01 -2.81214029e-01
-8.59445572e-01 -1.63922533e-01 -1.81580499e-01 -8.00790966e-01
-2.22970486e-01 8.62730622e-01 2.72274166e-01 3.70835692e-01
3.63564879e-01 -2.78099719e-02 -3.24955404e-01 -2.69697487e-01
4.73091781e-01 7.22976208e-01 7.40894973e-01 -7.98931897e-01
7.28694737e-01 5.76638579e-01 1.63264111e-01 -4.74394739e-01
-8.12762380e-01 -3.88663560e-01 -1.78446934e-01 -3.70285034e-01
3.78526926e-01 -9.37022030e-01 -9.04409587e-01 5.08980691e-01
-9.93620276e-01 -1.68294758e-01 -4.53328371e-01 8.85512710e-01
-5.49463391e-01 -9.78563651e-02 -3.57704461e-01 -1.31347287e+00
3.32293920e-02 -8.57531250e-01 1.15202928e+00 2.67488390e-01
-1.61473900e-01 -8.92776847e-01 8.52821246e-02 7.20411986e-02
6.31111145e-01 4.01078999e-01 5.66043019e-01 -5.86746514e-01
-7.81821370e-01 -9.08782601e-01 -4.09331992e-02 3.35841596e-01
-2.37854645e-01 2.58674711e-01 -1.00828767e+00 -2.15013158e-02
-2.22999528e-01 -6.76698685e-02 8.25406671e-01 8.54665935e-01
1.87200046e+00 1.21036517e-02 -4.84257519e-01 4.12425518e-01
8.19496930e-01 2.15622578e-02 4.72190470e-01 6.34015352e-03
4.60434914e-01 7.20067024e-01 9.62153912e-01 8.83441329e-01
7.83720374e-01 3.18394482e-01 7.79529214e-01 6.96191311e-01
5.19340098e-01 -4.45050418e-01 3.69902790e-01 6.01364017e-01
3.86800170e-01 -4.71451759e-01 -1.00992835e+00 8.25226188e-01
-2.12704849e+00 -1.05684352e+00 -2.52641849e-02 2.46560597e+00
3.74192059e-01 3.80249560e-01 1.75270468e-01 -2.50638604e-01
4.35974598e-01 -8.78958963e-03 -1.03430021e+00 -1.08544692e-01
-6.84118718e-02 -3.14124435e-01 9.47486997e-01 6.55390844e-02
-9.84862924e-01 5.43851376e-01 6.80967331e+00 1.11734605e+00
-9.99097526e-01 7.45527074e-02 9.39946949e-01 -6.76451027e-01
-5.25161147e-01 -1.17176995e-01 -9.07818437e-01 8.31294060e-01
1.64328539e+00 -5.59313953e-01 4.23568577e-01 8.76906753e-01
4.54687893e-01 -8.99317488e-02 -1.11236215e+00 1.09509027e+00
-3.38650614e-01 -1.46793008e+00 -6.20584428e-01 -1.16284274e-01
7.72018373e-01 6.18441164e-01 3.53022724e-01 6.68823898e-01
6.36523843e-01 -1.13181603e+00 5.46917319e-01 9.36851323e-01
1.78302079e-01 -1.20406532e+00 6.31192684e-01 5.09740472e-01
-7.93031752e-01 -4.81477261e-01 -3.38242680e-01 -9.24312919e-02
7.58466899e-01 1.21800137e+00 -4.81484950e-01 4.03414249e-01
8.94677937e-01 7.41149247e-01 5.38237207e-02 1.17031515e+00
1.36603385e-01 8.97793591e-01 -1.11540246e+00 1.93249397e-02
1.80529565e-01 -1.76084071e-01 7.64795899e-01 6.06530309e-01
7.87504852e-01 -8.73071104e-02 3.58589850e-02 1.15402913e+00
-3.49233635e-02 -6.56238854e-01 -6.57416105e-01 -5.46709538e-01
5.76167941e-01 1.18962932e+00 -2.80197918e-01 6.40887991e-02
-2.37779498e-01 2.93754876e-01 -1.39778554e-01 5.02460659e-01
-1.24970126e+00 -1.06713869e-01 9.04756188e-01 -1.17759563e-01
4.14448641e-02 -6.92534804e-01 -3.40332001e-01 -8.17738891e-01
1.36193797e-01 -2.49431580e-01 3.81638944e-01 -8.33953261e-01
-1.74583983e+00 2.81447113e-01 3.85330468e-01 -1.32626474e+00
-6.66569829e-01 -5.45588613e-01 -7.58617997e-01 9.20036137e-01
-1.43665504e+00 -1.11523187e+00 1.07625589e-01 4.00001585e-01
2.10614279e-01 -9.19885039e-02 3.58145893e-01 2.21096367e-01
-8.53505790e-01 3.47383559e-01 4.82670009e-01 -3.60952049e-01
5.23928285e-01 -1.08896101e+00 7.15367913e-01 1.05855250e+00
-5.85523322e-02 4.64224160e-01 1.06485558e+00 -8.58132482e-01
-1.69363666e+00 -1.35807586e+00 4.80240524e-01 -7.63084054e-01
1.21273005e+00 -2.43087858e-01 -8.69483590e-01 7.78907001e-01
-2.21489102e-01 7.75241405e-02 6.33441448e-01 2.99941450e-01
3.99569701e-03 -3.14245671e-01 -1.07753348e+00 4.57322687e-01
5.66914856e-01 -6.12891555e-01 -3.86641383e-01 6.76451087e-01
1.06434655e+00 -8.31986070e-01 -1.09094489e+00 4.34681088e-01
5.39046288e-01 -3.47908258e-01 7.51816273e-01 -6.72591329e-01
1.59445599e-01 -2.48653486e-01 -3.10006320e-01 -1.52585006e+00
-6.22878075e-02 -9.66585040e-01 -5.86558700e-01 1.19043684e+00
3.36918056e-01 -8.91592801e-01 5.14124870e-01 1.43275845e+00
-3.75424147e-01 -5.77355981e-01 -1.24551308e+00 -1.04207063e+00
-1.77969724e-01 -1.48400688e+00 1.21718311e+00 3.92964661e-01
-1.72249883e-01 -3.96504104e-01 -6.78482890e-01 7.27456212e-01
6.62247300e-01 2.57358104e-01 7.00701475e-01 -1.27079272e+00
-3.26081425e-01 -3.35290670e-01 -5.26687086e-01 -9.80101585e-01
4.59023774e-01 -3.22109997e-01 4.29091543e-01 -1.26423585e+00
-3.49754959e-01 -4.57462400e-01 -6.31861150e-01 2.50618994e-01
8.70446954e-03 -4.09251124e-01 -3.15074593e-01 -1.78766638e-01
-4.36213583e-01 1.06943536e+00 2.65961170e-01 -1.34409204e-01
4.89652120e-02 6.56019568e-01 -4.31138813e-01 6.15993142e-01
8.52890968e-01 -5.61012745e-01 -3.91194731e-01 -3.20160240e-01
6.29977822e-01 3.00346166e-01 5.34271836e-01 -9.49541867e-01
4.68107760e-01 -6.47637963e-01 1.82984382e-01 -1.41955400e+00
6.22803986e-01 -1.03308868e+00 1.96513802e-01 -9.33878869e-02
-2.09347606e-01 3.35913599e-01 7.38165379e-01 1.28305304e+00
-3.04743767e-01 2.36017898e-01 5.89471683e-02 5.40215850e-01
-9.75926757e-01 8.64983439e-01 -2.79883474e-01 -4.40390915e-01
1.11223447e+00 2.58235514e-01 -4.80537027e-01 -7.07597136e-01
-6.97782874e-01 1.00881028e+00 -1.27353668e-01 8.77582073e-01
5.97583175e-01 -1.44107497e+00 -5.77452600e-01 -2.27491055e-02
2.73827612e-01 1.05318643e-01 8.52840781e-01 7.31602192e-01
6.03687055e-02 4.16407675e-01 1.25082225e-01 -8.04494262e-01
-2.62507349e-01 5.07806063e-01 2.24402934e-01 5.66049293e-02
-3.16545665e-01 6.87452793e-01 -3.12851608e-01 -5.00426412e-01
3.31814766e-01 -6.56650186e-01 2.39229277e-01 -2.57353604e-01
6.68749213e-01 5.89763761e-01 1.68550849e-01 -3.12677711e-01
-1.31956518e-01 -5.04324324e-02 2.83646017e-01 -2.10964441e-01
1.35633957e+00 -4.18879688e-01 4.00609076e-02 1.09505451e+00
6.05263889e-01 -3.86864454e-01 -1.53144002e+00 -1.87870428e-01
7.59466663e-02 -4.41623688e-01 4.06220734e-01 -7.55393386e-01
-8.33870292e-01 9.12956715e-01 6.58652127e-01 1.70928314e-01
8.58854473e-01 -2.74060339e-01 1.27094197e+00 5.69800377e-01
5.51585317e-01 -1.28655279e+00 -6.00959837e-01 5.85221946e-01
9.41500485e-01 -1.40649188e+00 -3.06228578e-01 2.74232775e-01
-4.32275921e-01 8.27694058e-01 5.05752504e-01 -2.43028216e-02
1.15007138e+00 4.70077425e-01 -4.28797394e-01 -3.58570330e-02
-1.22963893e+00 -6.19362593e-02 4.75744814e-01 5.28137684e-01
-4.84012999e-02 5.13385892e-01 2.81681687e-01 9.48763728e-01
-1.83118954e-01 2.22811937e-01 3.71394157e-01 5.91578126e-01
-1.17653728e-01 -7.32748449e-01 -3.57537687e-01 8.21035206e-01
-2.60515183e-01 2.15759084e-01 3.83676082e-01 2.38849834e-01
-3.81477892e-01 1.13311195e+00 4.84249055e-01 -4.77627128e-01
3.30794454e-01 -4.15161764e-03 -1.13240883e-01 -1.11684874e-01
-1.44852832e-01 -2.21565217e-01 6.00548610e-02 -8.09877396e-01
2.58181721e-01 -7.86372483e-01 -1.30362618e+00 -6.68996215e-01
-6.64219260e-02 -4.46476862e-02 1.16871071e+00 1.26949239e+00
7.65448391e-01 7.23505020e-01 6.41505599e-01 -7.97628999e-01
-8.42153549e-01 -1.09221530e+00 -7.66508758e-01 -1.35888699e-02
3.18642616e-01 -7.87157297e-01 -2.53251553e-01 -4.83592331e-01] | [6.889160633087158, 3.1603000164031982] |
aba7d13f-f1c5-470d-a14c-8030be42c9f0 | causal-reasoning-and-large-language-models | 2305.00050 | null | https://arxiv.org/abs/2305.00050v2 | https://arxiv.org/pdf/2305.00050v2.pdf | Causal Reasoning and Large Language Models: Opening a New Frontier for Causality | The causal capabilities of large language models (LLMs) is a matter of significant debate, with critical implications for the use of LLMs in societally impactful domains such as medicine, science, law, and policy. We further our understanding of LLMs and their causal implications, considering the distinctions between different types of causal reasoning tasks, as well as the entangled threats of construct and measurement validity. LLM-based methods establish new state-of-the-art accuracies on multiple causal benchmarks. Algorithms based on GPT-3.5 and 4 outperform existing algorithms on a pairwise causal discovery task (97%, 13 points gain), counterfactual reasoning task (92%, 20 points gain), and actual causality (86% accuracy in determining necessary and sufficient causes in vignettes). At the same time, LLMs exhibit unpredictable failure modes and we provide some techniques to interpret their robustness. Crucially, LLMs perform these causal tasks while relying on sources of knowledge and methods distinct from and complementary to non-LLM based approaches. Specifically, LLMs bring capabilities so far understood to be restricted to humans, such as using collected knowledge to generate causal graphs or identifying background causal context from natural language. We envision LLMs to be used alongside existing causal methods, as a proxy for human domain knowledge and to reduce human effort in setting up a causal analysis, one of the biggest impediments to the widespread adoption of causal methods. We also see existing causal methods as promising tools for LLMs to formalize, validate, and communicate their reasoning especially in high-stakes scenarios. In capturing common sense and domain knowledge about causal mechanisms and supporting translation between natural language and formal methods, LLMs open new frontiers for advancing the research, practice, and adoption of causality. | ['Chenhao Tan', 'Amit Sharma', 'Robert Ness', 'Emre Kiciman'] | 2023-04-28 | null | null | null | null | ['causal-discovery', 'common-sense-reasoning'] | ['knowledge-base', 'reasoning'] | [ 4.76587147e-01 7.91777372e-01 -8.95909131e-01 -2.03767613e-01
-5.39558947e-01 -7.00302184e-01 1.06537664e+00 6.45466745e-01
-2.20849231e-01 1.03992176e+00 9.12038863e-01 -1.04250574e+00
-7.89101183e-01 -9.20370460e-01 -8.83539796e-01 -9.20031443e-02
-3.92752975e-01 4.12762105e-01 -8.21854547e-02 -1.06459528e-01
3.45759511e-01 1.89490736e-01 -9.37656701e-01 3.45907509e-01
1.07983804e+00 2.15593696e-01 -3.19809288e-01 3.41224402e-01
1.93597928e-01 1.20051384e+00 -2.65170246e-01 -7.31312573e-01
-2.68048346e-01 -4.20572668e-01 -1.04997420e+00 -6.93119049e-01
9.83474553e-02 -2.75440931e-01 8.44220072e-03 6.38474941e-01
2.05010444e-01 -2.79783785e-01 6.65611446e-01 -1.54719555e+00
-8.71890247e-01 1.32609248e+00 -4.85843182e-01 1.74242109e-01
9.48884189e-01 4.07040060e-01 1.16422129e+00 -1.44446880e-01
8.07805002e-01 1.87629318e+00 6.78661048e-01 3.50103557e-01
-1.48731863e+00 -8.00013006e-01 2.11208925e-01 1.60983190e-01
-6.94514453e-01 -3.48118365e-01 3.20901573e-01 -7.37156987e-01
8.86409461e-01 4.88894761e-01 5.54775417e-01 1.60285008e+00
3.21594745e-01 3.15270185e-01 1.54098499e+00 -4.83956277e-01
2.23798141e-01 -3.14217687e-01 4.51686680e-02 4.54294950e-01
8.13076198e-01 5.32089591e-01 -5.91759801e-01 -7.23517239e-01
8.58745456e-01 -4.18853641e-01 -1.64294645e-01 1.40657604e-01
-1.54941905e+00 1.02033865e+00 3.93751681e-01 1.69782102e-01
-5.66327214e-01 5.63142776e-01 1.82685241e-01 4.44763154e-02
2.01801643e-01 7.77831852e-01 -5.97205400e-01 -1.88231930e-01
-6.02665901e-01 7.00407922e-01 7.83781588e-01 4.31883484e-01
5.94688058e-02 -4.79229003e-01 -2.76517183e-01 1.85468361e-01
4.33447897e-01 5.99737287e-01 -7.33338222e-02 -1.00603783e+00
4.51909155e-01 8.79231393e-01 3.13248217e-01 -1.16415966e+00
-6.19817734e-01 -8.14130157e-02 -7.16336966e-01 -1.35865301e-01
5.36505699e-01 -1.52208418e-01 -4.26408529e-01 2.01624870e+00
4.03655231e-01 2.90429652e-01 -1.46390229e-01 7.27083743e-01
4.78639901e-01 2.45675460e-01 7.58118033e-01 -3.67514253e-01
1.35757554e+00 1.13756955e-01 -6.24826193e-01 -2.90991992e-01
7.15303242e-01 -5.71312070e-01 1.26511681e+00 1.57784730e-01
-9.63982880e-01 1.22166865e-01 -5.79228997e-01 9.19960290e-02
-1.21859297e-01 -5.80588937e-01 1.21637011e+00 6.35590374e-01
-6.04231060e-01 6.25182092e-01 -5.14141440e-01 -3.81491721e-01
5.37258863e-01 7.70036206e-02 -2.64553308e-01 -1.16492286e-01
-1.73833585e+00 1.01538730e+00 3.79207164e-01 -2.29852404e-02
-8.02099466e-01 -1.33445084e+00 -6.62069738e-01 1.11347064e-02
5.73008358e-01 -1.06080532e+00 1.06699872e+00 -5.09439409e-01
-7.04999089e-01 5.50717890e-01 -1.35775268e-01 -5.06342351e-01
7.43775010e-01 -1.85419664e-01 -4.64626431e-01 -2.23683596e-01
5.57250500e-01 3.46164018e-01 1.59883007e-01 -1.08725250e+00
-4.84588116e-01 -1.18661381e-01 2.48108566e-01 -2.77953684e-01
1.64980322e-01 3.34531337e-01 5.60027242e-01 -3.74770790e-01
-3.47030848e-01 -6.77017510e-01 -4.41007316e-01 -4.94799018e-01
-5.27597487e-01 -2.29646742e-01 4.12178546e-01 -4.34466988e-01
1.39531267e+00 -1.55507994e+00 -1.23573124e-01 2.56834120e-01
3.27548563e-01 -8.73789564e-02 -8.75688784e-06 7.26782918e-01
-2.99734712e-01 8.29343677e-01 -1.54629275e-01 5.39802849e-01
9.94814038e-02 1.16518348e-01 -6.45022869e-01 2.73565114e-01
3.86615872e-01 1.20528138e+00 -1.38411152e+00 -4.50839341e-01
2.87845433e-01 8.36457908e-02 -7.47229397e-01 -1.17048122e-01
-3.13641787e-01 3.98687780e-01 -3.61443937e-01 4.06921118e-01
1.60591081e-01 -2.97728598e-01 6.84810936e-01 1.33730590e-01
-2.91237533e-01 7.94045031e-01 -1.11997557e+00 9.72601295e-01
-4.02453035e-01 3.14440072e-01 -3.61705244e-01 -5.58742523e-01
4.05395925e-01 5.18601656e-01 2.92101800e-01 -6.51925445e-01
-1.16072394e-01 4.32014726e-02 2.60272831e-01 -6.21277690e-01
5.22734784e-02 -3.67958367e-01 -1.92593202e-01 6.82794631e-01
-2.30710909e-01 -7.04450160e-02 2.48137057e-01 3.45610529e-01
1.30590153e+00 6.45555332e-02 7.31548309e-01 -4.45719302e-01
-4.47884761e-02 3.41549784e-01 5.85463464e-01 8.15648675e-01
1.64669678e-01 2.41138041e-02 1.06513703e+00 -5.24412036e-01
-8.03829074e-01 -1.03606653e+00 -2.65130341e-01 6.80016398e-01
-2.44804382e-01 -4.18041050e-01 -3.62896740e-01 -6.30859137e-01
2.87393719e-01 1.38041794e+00 -9.41341102e-01 -2.38471225e-01
-4.53538954e-01 -1.04354656e+00 7.99365819e-01 3.88864517e-01
9.15175080e-02 -8.99239480e-01 -8.81162703e-01 3.34351152e-01
-4.99731749e-01 -1.04694784e+00 1.58802047e-01 -2.29648009e-01
-7.18669772e-01 -1.73738277e+00 7.19661787e-02 3.00580114e-01
3.18404347e-01 -9.83505696e-02 1.27188838e+00 -1.72209106e-02
-6.80774376e-02 1.84928238e-01 -1.86176792e-01 -7.18290031e-01
-8.83488834e-01 -3.59932452e-01 9.90027115e-02 -6.08276904e-01
3.09412390e-01 -7.24436045e-01 -4.91001576e-01 2.30178878e-01
-9.36250389e-01 1.46189466e-01 4.75329101e-01 6.36787176e-01
-4.60425951e-02 -1.45976022e-01 8.68543208e-01 -1.06726182e+00
1.20599878e+00 -8.40723872e-01 -5.22399068e-01 3.24869186e-01
-1.03094947e+00 -2.76716892e-02 2.93574065e-01 -3.92599344e-01
-1.19596934e+00 -8.18166971e-01 3.29083860e-01 3.59269887e-01
-1.25714436e-01 8.79201889e-01 3.06892712e-02 4.73145634e-01
1.14143860e+00 -7.67942786e-01 -3.50341469e-01 2.27700621e-02
7.93903708e-01 1.55381143e-01 3.15320969e-01 -1.05846131e+00
7.01438844e-01 4.35860455e-01 1.02635935e-01 -8.30501392e-02
-7.57614672e-01 -1.13411909e-02 -3.23959857e-01 -1.95908785e-01
6.17351890e-01 -6.92002475e-01 -1.22811580e+00 -3.16093296e-01
-1.20056272e+00 -6.41799986e-01 -1.66087076e-01 5.81693828e-01
-3.63034368e-01 -4.37791683e-02 -3.85345548e-01 -8.78582001e-01
-1.90600548e-02 -8.63759458e-01 8.59784842e-01 -4.03193273e-02
-1.16320717e+00 -1.28911197e+00 2.17155844e-01 4.15961921e-01
1.05014980e-01 6.91406846e-01 1.58161664e+00 -3.99601698e-01
-3.67777556e-01 -2.76819989e-02 -3.71722817e-01 -4.47296172e-01
2.07196563e-01 2.53135115e-01 -7.78685749e-01 3.31568509e-01
-4.81567979e-01 -2.64164597e-01 4.12697732e-01 5.58166325e-01
6.60562575e-01 -8.07272196e-01 -6.06230199e-01 -1.42249063e-01
1.16846025e+00 1.69556767e-01 5.21385849e-01 2.93859780e-01
5.90308368e-01 1.06364369e+00 4.74706650e-01 3.77187878e-01
6.70796573e-01 3.47429991e-01 3.92891526e-01 -9.77535695e-02
1.08219080e-01 -8.42580795e-01 1.73039034e-01 3.65064926e-02
-2.87430197e-01 -5.86817041e-03 -1.41913366e+00 6.20148659e-01
-2.10096145e+00 -1.18273199e+00 -7.98513293e-01 2.19203424e+00
1.13161743e+00 3.00019979e-01 7.23451152e-02 9.54295546e-02
4.33932424e-01 -1.57316998e-01 -1.86651736e-01 -5.74252248e-01
-2.90594958e-02 1.19201407e-01 5.66930950e-01 5.60866356e-01
-7.37550020e-01 8.05648804e-01 7.00851917e+00 3.95198494e-01
-6.89784229e-01 9.19496939e-02 7.03961611e-01 3.47040147e-02
-9.96651411e-01 6.23412549e-01 -2.28882909e-01 2.97473043e-01
1.12352002e+00 -3.38563710e-01 3.77365381e-01 4.41366434e-01
9.64534819e-01 -3.13540697e-01 -1.38343573e+00 2.48186842e-01
-6.69550061e-01 -1.72565377e+00 1.37502834e-01 2.06908375e-01
9.15518820e-01 -3.80108446e-01 -2.53390342e-01 -9.85419452e-02
1.19230902e+00 -1.45227659e+00 8.50292802e-01 4.64513004e-01
8.16656351e-01 -4.35381770e-01 7.51959920e-01 7.35105500e-02
-6.14148438e-01 -1.81611389e-01 -6.80078343e-02 -7.73263574e-01
3.61837298e-01 1.12467909e+00 -1.08957541e+00 6.95311368e-01
5.14221549e-01 3.34484935e-01 -1.67503446e-01 4.96108383e-01
-6.93201065e-01 1.18998659e+00 -8.53013545e-02 6.26638606e-02
8.26028287e-02 2.39488319e-01 4.03420091e-01 1.25177050e+00
-1.45662442e-01 2.27625370e-01 -2.38994017e-01 1.36948931e+00
2.78298035e-02 -1.81672722e-01 -8.05875897e-01 -2.96938181e-01
7.45080173e-01 8.03091228e-01 -5.33275306e-01 -1.16483167e-01
-2.92065203e-01 5.69498837e-02 1.03219166e-01 3.76414984e-01
-9.68149781e-01 4.88873184e-01 6.19599044e-01 2.90208220e-01
-7.92145312e-01 5.77218346e-02 -7.49202907e-01 -8.15743029e-01
-2.40912408e-01 -1.05044031e+00 6.11289322e-01 -6.81643248e-01
-1.29901516e+00 -2.50633866e-01 6.44467175e-01 -5.06171048e-01
-4.40815240e-01 -3.18339139e-01 -6.28862739e-01 8.34785342e-01
-1.16928864e+00 -1.24880612e+00 8.33048820e-02 3.21395904e-01
-2.17409190e-02 5.16620696e-01 8.28575969e-01 -4.71089929e-02
-3.75265032e-01 1.26422778e-01 -6.12662435e-01 -3.04599572e-02
8.65097046e-01 -1.15646219e+00 6.15267515e-01 7.98017442e-01
-1.82697892e-01 1.08582091e+00 8.64572704e-01 -1.16295433e+00
-1.26845038e+00 -9.15875971e-01 1.22877479e+00 -8.35639119e-01
1.20800769e+00 -2.65344501e-01 -5.96150339e-01 7.96089053e-01
-8.09857026e-02 -5.38983285e-01 6.81813419e-01 9.20384645e-01
-5.85004508e-01 2.89882720e-01 -1.10237670e+00 1.00364506e+00
1.36826479e+00 -3.47818077e-01 -9.47971106e-01 2.79006571e-01
9.42313612e-01 -4.00034934e-02 -9.46841300e-01 4.54159945e-01
7.45943725e-01 -8.34506989e-01 9.42908883e-01 -1.00651073e+00
1.03872776e+00 -1.84183288e-02 -8.13538581e-03 -1.16647089e+00
-4.99418110e-01 -7.73716927e-01 2.57308275e-01 1.31536424e+00
6.43001258e-01 -8.62637818e-01 1.43599644e-01 1.07342684e+00
3.45668912e-01 -4.58724976e-01 -7.62101948e-01 -3.49566758e-01
2.52950072e-01 -8.77377748e-01 8.17982495e-01 1.58119965e+00
2.55374908e-01 3.29672307e-01 -2.09934544e-02 2.99522430e-01
6.41658604e-01 1.13671862e-01 7.01605558e-01 -1.49950862e+00
-8.74572396e-02 -5.32251894e-01 -2.50721741e-02 3.24240476e-02
1.72766760e-01 -7.63119578e-01 -6.25549853e-01 -1.77229965e+00
4.27031577e-01 -7.18181252e-01 3.33220400e-02 6.62674546e-01
-4.66177225e-01 -4.17144179e-01 2.01287940e-01 1.52892936e-02
1.37948403e-02 5.51260523e-02 1.04544735e+00 2.08131224e-02
-1.52373940e-01 -3.89052033e-01 -1.25182617e+00 9.36363518e-01
6.07497334e-01 -7.70447314e-01 -5.95821202e-01 -1.17167957e-01
9.05269682e-01 3.11279118e-01 1.19050646e+00 -3.09477448e-01
2.44818125e-02 -1.08939624e+00 2.18431294e-01 1.04992084e-01
-5.66764772e-01 -5.00965118e-01 4.96404648e-01 6.66021943e-01
-6.94748521e-01 5.97501360e-02 3.43617350e-01 4.45108175e-01
1.73857734e-01 9.84937996e-02 7.88713992e-02 -2.15856463e-01
-5.04964530e-01 -2.31767818e-01 -9.44255069e-02 2.91778803e-01
7.52891839e-01 1.38393730e-01 -9.02487755e-01 -3.19294006e-01
-2.72708595e-01 2.99789906e-01 2.03101575e-01 6.39132380e-01
3.45333636e-01 -1.03502727e+00 -9.78624582e-01 -4.26098228e-01
2.72914413e-02 -2.79711306e-01 1.89145222e-01 1.02728379e+00
-4.84989248e-02 7.29392946e-01 1.64531695e-03 -1.84782058e-01
-7.30952859e-01 6.89416945e-01 6.25183992e-03 -4.68254179e-01
-3.04922491e-01 5.08706748e-01 4.69916224e-01 -3.34797531e-01
-2.81908780e-01 -5.97312629e-01 8.89308006e-02 1.05476655e-01
4.68338281e-01 5.79122424e-01 -2.87124455e-01 1.03346348e-01
-6.29710078e-01 -3.69047672e-02 4.87610936e-01 -3.21511149e-01
1.35455501e+00 5.89130856e-02 -5.06463051e-01 5.02605915e-01
3.40321779e-01 4.13779914e-01 -8.71265888e-01 2.62165010e-01
3.39827806e-01 -2.73879141e-01 -2.44510666e-01 -1.54467857e+00
-1.90881014e-01 3.68798703e-01 8.80310690e-05 3.04926157e-01
8.25475514e-01 1.21034876e-01 1.06559088e-02 -2.15519831e-01
4.58492339e-01 -6.19901955e-01 -4.19097811e-01 -9.14935991e-02
1.15674293e+00 -1.08183599e+00 2.38190383e-01 -4.39720541e-01
-3.97185177e-01 7.79989421e-01 1.67401150e-01 1.71284303e-01
2.48770863e-01 4.29993004e-01 -1.93139955e-01 -3.51358950e-01
-1.16074336e+00 -1.33845843e-02 2.08713636e-01 6.01402164e-01
8.37482989e-01 7.05830216e-01 -8.03929865e-01 7.51447022e-01
-3.57958794e-01 2.62470812e-01 5.12274146e-01 4.42237556e-01
1.80061445e-01 -1.13188207e+00 -7.00631499e-01 5.04285336e-01
-6.34817898e-01 -4.38578188e-01 -6.79427683e-01 1.23841894e+00
2.24138290e-01 1.45164156e+00 -3.26160878e-01 -1.68499380e-01
2.95823961e-01 -4.27311324e-02 3.42599273e-01 -2.64389187e-01
-6.21514916e-01 -3.10827017e-01 7.62875259e-01 -8.58163655e-01
-6.26212537e-01 -7.97981620e-01 -1.23847413e+00 -7.07601845e-01
-4.75133434e-02 -4.09680307e-02 3.24499428e-01 1.13532197e+00
2.99980164e-01 5.59921086e-01 9.27745476e-02 -1.08086631e-01
-3.11214805e-01 -7.50674784e-01 1.43680736e-01 4.19278413e-01
4.05267142e-02 -8.74483943e-01 -1.13971584e-01 -6.37937784e-02] | [8.134244918823242, 5.504613876342773] |
03715cd4-3490-4e7d-9c50-952b7ce7e8db | fast-text-conditional-discrete-denoising-on | 2211.07292 | null | https://arxiv.org/abs/2211.07292v2 | https://arxiv.org/pdf/2211.07292v2.pdf | A Novel Sampling Scheme for Text- and Image-Conditional Image Synthesis in Quantized Latent Spaces | Recent advancements in the domain of text-to-image synthesis have culminated in a multitude of enhancements pertaining to quality, fidelity, and diversity. Contemporary techniques enable the generation of highly intricate visuals which rapidly approach near-photorealistic quality. Nevertheless, as progress is achieved, the complexity of these methodologies increases, consequently intensifying the comprehension barrier between individuals within the field and those external to it. In an endeavor to mitigate this disparity, we propose a streamlined approach for text-to-image generation, which encompasses both the training paradigm and the sampling process. Despite its remarkable simplicity, our method yields aesthetically pleasing images with few sampling iterations, allows for intriguing ways for conditioning the model, and imparts advantages absent in state-of-the-art techniques. To demonstrate the efficacy of this approach in achieving outcomes comparable to existing works, we have trained a one-billion parameter text-conditional model, which we refer to as "Paella". In the interest of fostering future exploration in this field, we have made our source code and models publicly accessible for the research community. | ['Marc Aubreville', 'Pablo Pernias', 'Dominic Rampas'] | 2022-11-14 | null | null | null | null | ['conditional-image-generation'] | ['computer-vision'] | [ 5.54329157e-01 4.07741666e-02 2.05008358e-01 -8.83622915e-02
-6.22245491e-01 -6.26544595e-01 8.65635991e-01 -1.29049182e-01
2.14340109e-02 6.56839788e-01 3.42488080e-01 -2.55468339e-01
1.69493273e-01 -5.95840514e-01 -7.06126630e-01 -4.47710067e-01
2.56926209e-01 1.84097588e-02 1.38231060e-02 -1.67242363e-01
4.15343344e-01 6.12380326e-01 -1.79740644e+00 2.34848186e-01
8.60822558e-01 8.33649516e-01 1.26840696e-01 5.48699617e-01
7.03703389e-02 7.60515928e-01 -5.10704756e-01 -8.71804416e-01
3.03725451e-01 -6.52491391e-01 -6.03673875e-01 3.26134890e-01
6.33163571e-01 -2.42749661e-01 -1.72750875e-01 7.44903147e-01
5.01854658e-01 -3.69408913e-02 7.39911854e-01 -1.12028861e+00
-9.56483424e-01 1.89324599e-02 -7.08801150e-01 -1.71663433e-01
3.91398400e-01 4.94004250e-01 1.16601562e+00 -7.81635046e-01
8.01503122e-01 1.14017570e+00 5.37439287e-01 6.19459927e-01
-1.59853435e+00 -5.53265035e-01 -7.71114007e-02 -1.46293133e-01
-1.26629961e+00 -8.87634397e-01 7.86931038e-01 -4.54394400e-01
8.16829920e-01 3.24060798e-01 9.14219499e-01 1.18420088e+00
7.88723230e-02 5.95292687e-01 1.24128556e+00 -6.23409748e-01
1.51558742e-01 2.94316232e-01 -6.61319554e-01 5.41133404e-01
2.16686100e-01 3.17954987e-01 -6.05968714e-01 5.20225987e-02
9.12537575e-01 -3.67065638e-01 -1.86059594e-01 -6.43311083e-01
-9.47842836e-01 5.06550491e-01 2.64829844e-01 2.36138090e-01
-2.16884121e-01 2.58037746e-01 1.76850874e-02 1.16599396e-01
4.86938566e-01 7.20001876e-01 1.66986302e-01 -3.52504224e-01
-1.13201380e+00 3.54300588e-01 6.51373327e-01 9.73720908e-01
6.03169739e-01 1.78070068e-01 -1.13028139e-02 8.03778887e-01
1.39312670e-01 3.09122890e-01 5.17994678e-03 -1.13892436e+00
1.90442339e-01 5.74160993e-01 3.01696509e-01 -1.09608090e+00
7.70354867e-02 -4.88191366e-01 -4.84980434e-01 7.04156280e-01
2.11389631e-01 6.72282651e-02 -9.75644827e-01 1.52077854e+00
3.10845405e-01 -3.66850525e-01 -1.66313142e-01 6.84970796e-01
3.26473027e-01 6.57033801e-01 1.35432243e-01 6.08443990e-02
1.16701663e+00 -9.26274955e-01 -5.90587199e-01 -1.96517542e-01
3.36513877e-01 -1.23575747e+00 1.45476866e+00 6.22307062e-01
-1.48228848e+00 -3.65870178e-01 -1.12613082e+00 -1.08290076e-01
-1.63753152e-01 -1.18070960e-01 6.33712173e-01 8.58078182e-01
-1.25357342e+00 6.59442902e-01 -5.24199188e-01 -4.77686197e-01
7.41324365e-01 -1.74945164e-02 -3.18737090e-01 -6.88261613e-02
-4.70558792e-01 9.34357762e-01 -4.35795970e-02 -1.39253527e-01
-6.75698638e-01 -7.91733146e-01 -5.50834298e-01 4.08999659e-02
3.15395415e-01 -8.91791642e-01 1.31873500e+00 -1.14200294e+00
-1.64822567e+00 8.92439008e-01 -9.13590640e-02 -1.04308479e-01
7.05358446e-01 -1.04094356e-01 -1.83051959e-01 1.25762314e-01
-1.21332280e-01 1.00663757e+00 1.08807564e+00 -1.67348087e+00
-5.72356880e-01 1.16458759e-02 4.72067902e-03 2.98158675e-01
-4.74557519e-01 1.16087005e-01 -3.74227524e-01 -8.03025007e-01
-2.52798170e-01 -7.67077446e-01 -1.48897901e-01 3.54145676e-01
-2.65681028e-01 2.44404897e-01 6.50886953e-01 -3.51011962e-01
1.05177498e+00 -2.24548554e+00 1.46698639e-01 -1.35701135e-01
3.13292027e-01 1.54305220e-01 -7.51669481e-02 8.07401776e-01
8.49813446e-02 4.29989517e-01 -1.33392215e-01 -6.30880356e-01
5.54244518e-02 -8.24604705e-02 -3.85720104e-01 2.55544156e-01
5.06049693e-01 9.49743807e-01 -6.84439421e-01 -6.57625794e-01
3.42210412e-01 6.45200491e-01 -6.60736680e-01 1.59221739e-01
-3.14503729e-01 5.46274304e-01 -1.17913328e-01 6.95303082e-01
4.83191669e-01 -3.08158427e-01 4.83327955e-02 -2.00191706e-01
-4.05455321e-01 6.18177168e-02 -8.73205245e-01 1.65409231e+00
-5.38679779e-01 8.14688325e-01 -4.51436490e-02 -4.62564975e-01
8.05336237e-01 1.91655964e-01 2.64164329e-01 -9.50795472e-01
1.39674857e-01 2.85208553e-01 -1.26796797e-01 -3.74027193e-01
8.57862711e-01 -5.11028051e-01 2.76820987e-01 3.48056942e-01
-7.67071918e-02 -7.28005052e-01 3.90558392e-01 2.87863940e-01
7.28978455e-01 5.49396694e-01 9.05015618e-02 -1.62399366e-01
6.67027682e-02 3.13328803e-02 -5.80600947e-02 4.58738893e-01
-6.10133931e-02 8.24508071e-01 3.74061763e-01 -2.58771241e-01
-1.56415653e+00 -1.26901436e+00 -1.37942463e-01 6.45568967e-01
3.08744460e-02 -5.09699166e-01 -7.06380486e-01 -2.21267596e-01
-1.26774177e-01 6.37630463e-01 -6.67539477e-01 -2.96817487e-03
-3.79067570e-01 -3.74001652e-01 4.36359644e-01 3.73419315e-01
3.41816097e-01 -9.11109269e-01 -7.90984273e-01 3.51060741e-02
-1.10663380e-02 -1.01648939e+00 -4.80496466e-01 -2.42233947e-01
-8.80403101e-01 -7.42914855e-01 -9.06615794e-01 -5.60480654e-01
6.67691648e-01 3.49054605e-01 1.36863327e+00 1.13150865e-01
-5.72229862e-01 4.89365041e-01 -3.52795899e-01 -4.14345592e-01
-5.39558589e-01 -1.27221078e-01 -4.65015531e-01 -7.11707165e-03
-2.15863898e-01 -8.11231315e-01 -8.45754623e-01 1.17401339e-01
-1.17378843e+00 4.83149588e-01 6.60858691e-01 5.90308309e-01
3.85746479e-01 -7.69037157e-02 3.69561762e-01 -6.24440551e-01
6.61170900e-01 -1.52457058e-01 -6.40075266e-01 2.03359704e-02
-8.62515450e-01 -8.04573521e-02 5.60873270e-01 -3.22362065e-01
-1.19224489e+00 -6.08827285e-02 3.84567119e-02 -1.82113469e-01
-1.58163115e-01 2.61661023e-01 9.59049910e-02 -3.20610762e-01
7.59202480e-01 6.62811100e-02 1.88742727e-02 -3.49607050e-01
6.54130518e-01 4.39543843e-01 4.73518342e-01 -5.67768931e-01
1.04408741e+00 5.23903906e-01 5.00387289e-02 -8.01797867e-01
-5.35352767e-01 9.24215913e-02 -2.33009905e-01 -4.40928489e-01
5.71716428e-01 -8.24005246e-01 -5.28768301e-01 4.54068065e-01
-9.41977024e-01 -3.93944323e-01 -6.61523640e-01 -8.17647611e-04
-5.67439258e-01 3.32130253e-01 -3.35878611e-01 -9.98125315e-01
-3.44513245e-02 -1.07790375e+00 1.08722913e+00 4.15194958e-01
-3.60498101e-01 -9.54149365e-01 -4.02586646e-02 5.39080262e-01
7.56484807e-01 4.10287172e-01 7.97076523e-01 2.54290462e-01
-9.50866699e-01 -1.05869494e-01 -4.37158287e-01 3.09942245e-01
5.94670214e-02 3.58102977e-01 -1.02778792e+00 -1.84313029e-01
-2.69619972e-01 -5.77016711e-01 5.08048296e-01 2.04319999e-01
9.12541866e-01 -1.59073621e-01 -1.85710698e-01 6.46753311e-01
1.37639093e+00 1.69579461e-01 8.38403404e-01 4.36773598e-01
5.35564244e-01 7.63207912e-01 3.85774046e-01 4.84845608e-01
3.56374532e-01 6.41721487e-01 3.42740864e-01 -5.25034845e-01
-5.16981006e-01 -5.48991859e-01 -3.24959345e-02 6.12445712e-01
-4.35162447e-02 -4.44224685e-01 -7.60593891e-01 6.83074296e-01
-1.45011389e+00 -8.92171919e-01 1.24561176e-01 2.04090285e+00
9.72190499e-01 6.17859550e-02 1.34437531e-01 6.53795004e-02
3.51875871e-01 3.04373145e-01 -3.49725991e-01 -6.43451869e-01
-1.86320618e-01 3.03278118e-01 1.52305871e-01 3.43003273e-01
-7.31275856e-01 1.02638173e+00 7.19135141e+00 8.89599085e-01
-1.15125966e+00 -3.97709727e-01 9.26645100e-01 -2.54688829e-01
-5.90543449e-01 1.81104749e-01 -4.51363176e-01 2.86569029e-01
7.86314011e-01 -2.82722384e-01 7.21488357e-01 6.16607010e-01
3.87043744e-01 -4.23457205e-01 -1.03676271e+00 8.54099512e-01
2.12285683e-01 -1.43741822e+00 2.22066656e-01 2.17617199e-01
8.47266197e-01 -4.21584815e-01 4.70985562e-01 -7.46045783e-02
1.52876735e-01 -1.26672745e+00 9.99267042e-01 4.02027845e-01
1.19662642e+00 -7.34489858e-01 1.88921895e-02 -7.32333139e-02
-8.89214993e-01 1.45841107e-01 -2.62767728e-02 -2.50437975e-01
2.47407988e-01 5.28915823e-01 -7.05285549e-01 4.47350949e-01
6.06741369e-01 3.96812350e-01 -5.27399361e-01 1.10978711e+00
-7.28785843e-02 4.23909783e-01 -5.09103872e-02 3.41534987e-02
1.06301017e-01 -2.64082789e-01 3.89508426e-01 1.02778018e+00
3.55286062e-01 -1.02794178e-01 -2.08125547e-01 1.14813876e+00
-1.69065103e-01 3.38152975e-01 -7.99708545e-01 -4.24163073e-01
3.02858055e-01 1.29625106e+00 -7.75278330e-01 -1.15066923e-01
-2.79966623e-01 1.03188026e+00 2.87114292e-01 3.85893226e-01
-7.12140143e-01 -4.19368863e-01 4.77442831e-01 3.70121092e-01
3.41039687e-01 -4.36230659e-01 -6.81112289e-01 -9.29336905e-01
1.50913402e-01 -1.21430314e+00 -2.26906598e-01 -1.03684294e+00
-1.18389809e+00 6.04344726e-01 7.17115030e-03 -1.15048611e+00
-1.18466742e-01 -4.67465371e-01 -4.32399809e-01 9.07536387e-01
-1.52767479e+00 -1.32445455e+00 -3.02224576e-01 1.97013155e-01
4.21426773e-01 1.03985332e-01 6.86721623e-01 1.91175863e-01
-2.82972604e-01 5.78110039e-01 7.98114538e-02 -5.16504228e-01
9.00676429e-01 -9.51417923e-01 6.39349043e-01 8.82326186e-01
1.79085493e-01 6.31036162e-01 1.03604162e+00 -4.37101990e-01
-1.44453526e+00 -6.85284853e-01 7.63415635e-01 -5.05311072e-01
6.85584784e-01 -5.03253162e-01 -4.36667502e-01 3.71479511e-01
4.10578251e-01 -4.39909816e-01 5.82705855e-01 -2.19928013e-04
-4.15023744e-01 -8.11527073e-02 -1.12452877e+00 1.22763729e+00
1.09651017e+00 -4.23187047e-01 -1.79339170e-01 -2.15838873e-03
5.87413371e-01 -2.99127311e-01 -7.78241038e-01 2.09246174e-01
6.75372958e-01 -1.35851550e+00 9.00468826e-01 -1.29087180e-01
9.72247958e-01 -2.05181807e-01 -1.92649178e-02 -1.24953878e+00
-3.32514733e-01 -9.84371245e-01 1.41637340e-01 1.35536027e+00
4.32213068e-01 -4.27137971e-01 8.67523849e-01 6.95558608e-01
-1.62059337e-01 -8.33522201e-01 -6.77824020e-01 -6.36521399e-01
1.90434143e-01 -2.68263757e-01 5.26338637e-01 6.63059533e-01
-7.70300999e-02 3.49615127e-01 -5.73078036e-01 -2.42909640e-01
6.04056954e-01 1.03140227e-01 9.81637061e-01 -1.02391624e+00
-4.70560074e-01 -7.64938951e-01 -1.83120281e-01 -1.06483531e+00
-4.45817769e-01 -5.18543184e-01 3.70373502e-02 -1.41000986e+00
3.77246529e-01 -3.81876349e-01 1.81268796e-01 1.93854377e-01
-1.85525715e-01 7.79656649e-01 4.57203001e-01 2.31753886e-01
-2.84903765e-01 6.28639519e-01 1.61643803e+00 1.61492392e-01
-1.26438245e-01 -3.79129499e-01 -1.10650325e+00 3.98823202e-01
8.42874348e-01 -2.36433864e-01 -6.25386775e-01 -4.70691830e-01
2.69142061e-01 -1.63025305e-01 4.38592851e-01 -1.14042461e+00
-9.01034027e-02 -2.17239290e-01 4.41552311e-01 -2.89314181e-01
6.87541425e-01 -6.17120028e-01 4.06476527e-01 2.07466364e-01
-2.76037723e-01 9.83373523e-02 3.21681291e-01 3.79620463e-01
-1.03804544e-01 -1.18392676e-01 9.08704698e-01 -3.27955484e-02
-2.48953998e-01 7.75609314e-02 -3.33539456e-01 3.93188447e-02
9.80640948e-01 -5.53820968e-01 -4.19212699e-01 -6.30982816e-01
-2.57592231e-01 -9.35780331e-02 1.21048629e+00 3.62849444e-01
4.65623558e-01 -1.13777709e+00 -5.86296439e-01 1.25016406e-01
1.67631879e-01 -2.92429864e-01 2.68139571e-01 6.33495450e-01
-6.51038349e-01 2.49792248e-01 -3.39478403e-01 -4.26876307e-01
-1.13223660e+00 5.47251761e-01 1.13773681e-01 -7.12890849e-02
-6.44149363e-01 7.46710062e-01 3.34258944e-01 8.15006942e-02
1.67489886e-01 8.77936333e-02 2.51313508e-01 -1.26164019e-01
3.44311893e-01 2.47998714e-01 -1.18437022e-01 -4.21303540e-01
-2.35545635e-03 4.46956605e-01 -8.17788988e-02 -5.43441951e-01
1.31979930e+00 -1.32648438e-01 9.99290794e-02 3.38313311e-01
8.94798994e-01 3.61115456e-01 -1.59454942e+00 2.36500740e-01
-3.35184187e-01 -8.81266057e-01 5.52113354e-02 -1.08730018e+00
-8.72573912e-01 9.12522614e-01 4.62227464e-01 3.60427529e-01
1.28717458e+00 -1.20705135e-01 7.61423469e-01 -1.36754617e-01
1.66010931e-01 -9.61072087e-01 3.58886927e-01 7.13983625e-02
9.90273118e-01 -1.00730312e+00 1.32169098e-01 -3.75494063e-01
-7.12910950e-01 9.48940814e-01 4.37540054e-01 -4.65312833e-03
8.40081871e-02 4.39063221e-01 2.24312350e-01 -1.32485598e-01
-8.61910522e-01 -3.11415959e-02 2.79150128e-01 7.73655117e-01
7.48426914e-01 -1.96702659e-01 -3.34312260e-01 -1.32562026e-01
-3.32651436e-01 6.85923547e-02 6.14070833e-01 1.02396452e+00
-3.28032643e-01 -1.41137052e+00 -3.40210438e-01 2.18423888e-01
-4.62186843e-01 -3.33043069e-01 -5.09203613e-01 8.57813120e-01
-9.92422923e-02 1.04730082e+00 -1.51072100e-01 -2.00788468e-01
3.95684004e-01 -1.19116068e-01 8.12632799e-01 -3.37612867e-01
-5.62877417e-01 1.77113011e-01 2.94889987e-01 -5.29791415e-01
-1.63278639e-01 -6.64597809e-01 -5.66777885e-01 -4.73292798e-01
-2.87281215e-01 -1.59390032e-01 8.70098472e-01 5.09706557e-01
6.37214422e-01 4.17998254e-01 5.96348405e-01 -1.19217253e+00
-4.15281832e-01 -6.58112168e-01 -3.43093634e-01 4.58714396e-01
1.48891628e-01 -5.32833993e-01 -2.51613528e-01 2.93028355e-01] | [11.363227844238281, -0.3856285810470581] |
e204b3c3-5c51-4342-8aca-292b0c06a539 | event-based-simultaneous-localization-and | 2304.09793 | null | https://arxiv.org/abs/2304.09793v1 | https://arxiv.org/pdf/2304.09793v1.pdf | Event-based Simultaneous Localization and Mapping: A Comprehensive Survey | In recent decades, visual simultaneous localization and mapping (vSLAM) has gained significant interest in both academia and industry. It estimates camera motion and reconstructs the environment concurrently using visual sensors on a moving robot. However, conventional cameras are limited by hardware, including motion blur and low dynamic range, which can negatively impact performance in challenging scenarios like high-speed motion and high dynamic range illumination. Recent studies have demonstrated that event cameras, a new type of bio-inspired visual sensor, offer advantages such as high temporal resolution, dynamic range, low power consumption, and low latency. This paper presents a timely and comprehensive review of event-based vSLAM algorithms that exploit the benefits of asynchronous and irregular event streams for localization and mapping tasks. The review covers the working principle of event cameras and various event representations for preprocessing event data. It also categorizes event-based vSLAM methods into four main categories: feature-based, direct, motion-compensation, and deep learning methods, with detailed discussions and practical guidance for each approach. Furthermore, the paper evaluates the state-of-the-art methods on various benchmarks, highlighting current challenges and future opportunities in this emerging research area. A public repository will be maintained to keep track of the rapid developments in this field at {\url{https://github.com/kun150kun/ESLAM-survey}}. | ['DaCheng Tao', 'Jing Zhang', 'Sen Zhang', 'Kunping Huang'] | 2023-04-19 | null | null | null | null | ['simultaneous-localization-and-mapping', 'motion-compensation'] | ['computer-vision', 'computer-vision'] | [ 1.57231297e-02 -8.65195870e-01 -2.09065333e-01 -8.51751640e-02
-5.52848756e-01 -5.00551820e-01 6.11396968e-01 1.16512544e-01
-4.81292844e-01 6.59030735e-01 4.50491644e-02 3.12960505e-01
-3.83817926e-02 -4.39977199e-01 -6.63378298e-01 -8.35568845e-01
-1.18297659e-01 -1.21202826e-01 5.92882991e-01 3.80194396e-01
2.39737004e-01 7.64372051e-01 -1.77050591e+00 1.17179856e-01
2.98432052e-01 9.94061232e-01 7.37014413e-01 7.61564851e-01
1.50654107e-01 9.52228010e-01 -7.14261830e-01 3.64299685e-01
-1.62068203e-01 -4.75161105e-01 -2.90365249e-01 -1.67262852e-01
1.69326320e-01 -3.31999749e-01 -7.96594441e-01 7.88996220e-01
7.65359759e-01 2.07665637e-01 2.53777295e-01 -1.53260219e+00
-5.46138763e-01 1.04104457e-02 -7.05444038e-01 7.02725053e-01
6.68507636e-01 2.00850263e-01 3.21604908e-01 -1.06620145e+00
7.61201799e-01 9.00120854e-01 7.58303225e-01 4.15636063e-01
-9.76792455e-01 -7.50501990e-01 1.99205771e-01 7.69931138e-01
-1.44431520e+00 -6.54080093e-01 6.20025575e-01 -3.62545639e-01
1.26873970e+00 -5.16724400e-03 7.30499923e-01 1.39732289e+00
7.15986431e-01 9.15199041e-01 6.83556318e-01 -2.29079291e-01
3.21181864e-01 -2.75490642e-01 -1.67824209e-01 5.56100070e-01
3.75800639e-01 3.44840914e-01 -1.26634598e+00 -1.32115915e-01
9.08944309e-01 3.37313145e-01 -5.43900907e-01 -5.69210351e-01
-1.74427176e+00 5.17027140e-01 2.49997318e-01 1.46322533e-01
-5.27249038e-01 6.61051631e-01 4.79824960e-01 -1.07874125e-01
1.34887084e-01 -1.52480826e-01 -2.31912076e-01 -3.67755562e-01
-8.85952652e-01 -5.52717037e-02 5.16098499e-01 1.08809388e+00
5.62644243e-01 2.83521265e-01 -7.39569124e-03 5.08695543e-01
4.01119322e-01 8.06505024e-01 5.55524290e-01 -1.11261010e+00
2.11725906e-02 5.17251417e-02 2.56440133e-01 -9.53491986e-01
-4.43208516e-01 1.25528261e-01 -8.04826558e-01 3.28016579e-01
1.03277162e-01 -6.24645762e-02 -5.78515053e-01 1.46297693e+00
2.38467455e-01 6.84409082e-01 6.84548914e-02 1.05163264e+00
1.09909141e+00 9.81731713e-01 1.22052175e-03 -4.25420761e-01
1.17662323e+00 -8.34695280e-01 -1.04778016e+00 -4.87092048e-01
-1.79842144e-01 -8.05339873e-01 6.41634703e-01 2.78416634e-01
-8.79311025e-01 -5.14475405e-01 -1.21130919e+00 -4.91366796e-02
-3.47434819e-01 4.38477725e-01 8.26522052e-01 1.07020617e-01
-1.03235567e+00 3.32230479e-01 -1.60479820e+00 -9.82719123e-01
3.30380082e-01 2.13186309e-01 -2.67800957e-01 -1.26995698e-01
-9.63971257e-01 8.06042314e-01 7.75703639e-02 8.65965560e-02
-1.11632180e+00 -4.97048289e-01 -8.86397958e-01 -2.73198247e-01
4.09593210e-02 -4.71848845e-01 1.33190918e+00 -4.49663520e-01
-1.44323587e+00 5.91676176e-01 -6.16554081e-01 -4.42242593e-01
3.60020131e-01 -2.70995498e-01 -4.15465862e-01 4.10363913e-01
2.10491791e-01 7.06846774e-01 5.85941017e-01 -8.73678386e-01
-9.21180546e-01 -1.41320050e-01 -3.36175561e-01 1.63147449e-01
-2.34729186e-01 1.80697262e-01 -6.26659453e-01 -4.58012760e-01
2.34608762e-02 -7.08751380e-01 -8.99568200e-02 4.03785199e-01
1.30752668e-01 -5.69939315e-02 1.04791880e+00 -3.17964137e-01
1.00640786e+00 -2.14051938e+00 -1.90799728e-01 -5.92607439e-01
-1.06846184e-01 6.06998242e-03 9.43225995e-02 7.92196691e-01
2.93078452e-01 -6.09022558e-01 5.26213534e-02 -3.91623467e-01
-3.56578261e-01 2.83114854e-02 -4.79223728e-01 1.05742991e+00
-1.06345743e-01 8.33726108e-01 -1.20875108e+00 -3.74650925e-01
9.95840073e-01 8.00570905e-01 2.79910803e-01 -1.12139080e-02
1.20514490e-01 6.31628573e-01 -2.54454792e-01 9.17783558e-01
5.55249572e-01 -4.06348735e-01 5.40110469e-02 -3.05014610e-01
-5.65682232e-01 3.42166573e-02 -1.31889176e+00 1.93484604e+00
-3.75499487e-01 1.40923452e+00 -2.46015284e-02 -6.48758948e-01
7.93404579e-01 3.61667693e-01 7.50582278e-01 -7.86781192e-01
8.52999687e-02 1.21930510e-01 -7.94245541e-01 -4.37964499e-01
5.89560866e-01 3.99597436e-01 -2.33167913e-02 2.39096090e-01
7.53801763e-02 1.78341985e-01 1.52645722e-01 5.66689894e-02
1.25377786e+00 4.72561836e-01 6.78421378e-01 1.17525771e-01
3.41532499e-01 2.74478287e-01 6.65489554e-01 7.41997123e-01
-4.84700710e-01 5.64326882e-01 -2.30349943e-01 -4.27456796e-01
-6.34103656e-01 -1.31330597e+00 -1.12890214e-01 7.85577595e-01
9.43803728e-01 -2.05625623e-01 -6.58753738e-02 -2.89456956e-02
1.56154819e-02 3.92404735e-01 -2.71171778e-01 -1.31114587e-01
-6.53687716e-01 -8.94212723e-01 5.52646875e-01 8.65200877e-01
5.71533322e-01 -1.06211817e+00 -1.59619987e+00 2.99887687e-01
-4.61499453e-01 -1.39414620e+00 -1.65810928e-01 2.46305123e-01
-8.20160329e-01 -1.12377024e+00 -5.74492395e-01 -8.98314416e-01
4.36973840e-01 8.56174827e-01 8.31109345e-01 -3.99347901e-01
-6.61059618e-01 8.96739006e-01 -2.49986216e-01 -5.46789467e-01
2.75909096e-01 -4.80210602e-01 1.86787084e-01 -1.60194620e-01
5.49993157e-01 -5.02380252e-01 -7.39474058e-01 2.97057241e-01
-6.30064845e-01 -5.49544543e-02 4.66757864e-01 5.77620089e-01
9.15263176e-01 -1.01502806e-01 2.78684646e-01 8.99251923e-03
5.53525873e-02 -5.86847961e-01 -1.01050782e+00 8.17880258e-02
-3.28355759e-01 -4.28506255e-01 3.39011282e-01 -6.88459098e-01
-1.10516238e+00 6.04144514e-01 3.77556682e-01 -6.40891194e-01
-2.79430777e-01 2.22709253e-01 7.07385987e-02 -2.14964390e-01
5.49860001e-01 6.01877749e-01 -8.84052813e-02 -1.68741554e-01
2.42525607e-01 6.20601714e-01 9.93295789e-01 -7.54036084e-02
4.18435603e-01 1.26189613e+00 -9.17216316e-02 -9.85534906e-01
-3.27320218e-01 -8.72989416e-01 -4.80232239e-01 -7.07011819e-01
7.13429332e-01 -1.36668444e+00 -6.88713908e-01 8.30376387e-01
-1.38858581e+00 -4.23074901e-01 -1.41490251e-01 9.62868869e-01
-6.34998441e-01 3.52548897e-01 -7.73186743e-01 -7.17209518e-01
-2.55323112e-01 -9.60878909e-01 1.15643835e+00 6.33263648e-01
-1.13694549e-01 -9.64671373e-01 2.48657942e-01 -2.08241537e-01
4.16406304e-01 5.92115521e-01 -1.00457445e-01 -1.25791272e-02
-1.09759760e+00 -3.48153055e-01 -1.18887290e-01 -2.07724914e-01
1.37632757e-01 6.94572320e-03 -1.04419863e+00 -4.23432112e-01
6.72837347e-03 -1.21123679e-01 7.66538441e-01 8.46319318e-01
7.38727450e-01 3.27371985e-01 -9.66783822e-01 8.77501667e-01
1.72357702e+00 5.30795991e-01 5.11349261e-01 5.00657558e-01
4.85574841e-01 5.73874488e-02 9.74242926e-01 8.15287828e-01
4.28082764e-01 5.97160041e-01 5.36605477e-01 1.78298131e-01
-2.37992674e-01 -5.25683016e-02 6.59958243e-01 4.63656306e-01
8.45415443e-02 -6.00823820e-01 -8.59351158e-01 8.70123863e-01
-2.11492848e+00 -1.02322626e+00 -4.08831149e-01 2.19999409e+00
2.71902621e-01 -3.53132784e-01 -2.40391359e-01 -1.93894908e-01
9.81926680e-01 4.80147868e-01 -7.72991538e-01 2.38413110e-01
-3.33469361e-01 -2.33783305e-01 7.55740285e-01 2.03255728e-01
-1.24238157e+00 8.50816667e-01 6.37218952e+00 4.36480790e-01
-1.43082988e+00 2.57809877e-01 -1.45937949e-01 -4.39531296e-01
5.32225549e-01 -6.59151152e-02 -1.02887559e+00 6.34885550e-01
1.05943167e+00 -3.67408544e-01 3.41844201e-01 7.20700681e-01
5.71582437e-01 -6.20430946e-01 -1.10552216e+00 1.45141768e+00
3.35235655e-01 -1.61597598e+00 -4.35606509e-01 -1.05485603e-01
5.28041244e-01 6.49829447e-01 -2.79261917e-01 -2.77717859e-01
1.77668840e-01 -5.27214170e-01 9.69310045e-01 6.78819597e-01
8.49375069e-01 -5.88578403e-01 6.20459080e-01 2.63786376e-01
-1.79656017e+00 -1.25143096e-01 -5.07226527e-01 -1.81232601e-01
6.48812771e-01 6.59633279e-01 -3.15777451e-01 4.50663000e-01
1.20540416e+00 1.29432893e+00 -2.72591889e-01 1.42295253e+00
-1.48622349e-01 2.66247213e-01 -4.20515478e-01 -3.68684568e-02
-9.47441459e-02 1.72790781e-01 7.43042529e-01 1.41779304e+00
5.98767400e-01 5.36025176e-03 1.76007852e-01 6.29531503e-01
2.69855171e-01 -6.24681115e-01 -7.75021017e-01 1.64224938e-01
1.01050794e+00 1.18866360e+00 -8.91060054e-01 -2.31503516e-01
-7.64724374e-01 1.32638597e+00 1.08631738e-02 3.97291422e-01
-1.12808430e+00 -5.90676546e-01 7.10508168e-01 -2.97555447e-01
3.61475706e-01 -7.43776023e-01 4.28780764e-02 -1.00891042e+00
3.18066776e-02 -2.05527753e-01 3.84037435e-01 -1.04382813e+00
-9.23648119e-01 2.42559060e-01 1.37414947e-01 -1.58612370e+00
-3.59924845e-02 -4.43983167e-01 -4.38919961e-01 5.12126803e-01
-1.47496545e+00 -1.04779518e+00 -9.85625684e-01 5.98225236e-01
8.85045528e-01 -1.41799450e-02 4.87270921e-01 3.70731175e-01
-5.12553573e-01 -6.07871599e-02 4.43238854e-01 -5.96743710e-02
1.03502679e+00 -8.79632950e-01 3.72648239e-01 1.18706906e+00
4.68051285e-02 3.34661573e-01 5.02033234e-01 -6.84979320e-01
-1.97339392e+00 -1.38470459e+00 7.34636843e-01 -6.15278423e-01
6.48424864e-01 -2.80431569e-01 -6.47051871e-01 9.30986583e-01
2.42228553e-01 3.98919284e-01 3.61929864e-01 -8.28292072e-01
2.51437783e-01 -3.08797985e-01 -8.23845625e-01 2.95241684e-01
1.05569255e+00 -5.27815759e-01 -3.24483633e-01 2.92721361e-01
4.43733543e-01 -6.67727292e-01 -5.35971642e-01 2.21619770e-01
5.72023213e-01 -9.15929556e-01 1.12345099e+00 3.39401186e-01
-1.31221309e-01 -8.30654562e-01 -1.13152832e-01 -8.53940904e-01
-4.92495865e-01 -4.91721183e-01 -5.50652146e-01 1.15298748e+00
-3.60994339e-01 -6.22604191e-01 5.67274809e-01 -7.53794536e-02
-1.75050125e-01 -3.79966527e-01 -9.69799697e-01 -1.08200383e+00
-7.40752041e-01 -4.42817956e-01 1.70371130e-01 7.33949721e-01
-8.94621387e-02 9.65843946e-02 -5.22846162e-01 4.96103793e-01
8.30549359e-01 1.87335253e-01 5.76547265e-01 -9.00976777e-01
1.12312101e-01 -3.48891579e-02 -6.33506835e-01 -1.24800944e+00
-4.67758849e-02 -4.98199910e-01 3.48844081e-01 -1.96587646e+00
2.27395236e-01 1.40373617e-01 -2.06037626e-01 2.42173225e-01
1.90461695e-01 3.58262599e-01 -4.32479568e-02 4.97590035e-01
-9.94842410e-01 4.75861698e-01 5.62403262e-01 6.26296736e-03
-2.24020347e-01 -2.28326485e-01 -2.71814615e-02 7.09658802e-01
6.79128528e-01 -3.87582302e-01 -3.93627614e-01 -7.49556839e-01
-4.97950241e-02 1.36595249e-01 8.37581038e-01 -1.28962219e+00
1.02510464e+00 -2.80692190e-01 6.78011179e-01 -9.91463840e-01
4.99837428e-01 -8.79630327e-01 6.15448356e-01 6.42824769e-01
1.15702100e-01 4.81635064e-01 3.99437249e-01 1.02002656e+00
-3.18620414e-01 2.06721514e-01 7.81655192e-01 -1.87089235e-01
-1.64943290e+00 1.95780411e-01 -9.74058509e-01 -3.00259382e-01
1.38172555e+00 -4.36954319e-01 -4.52311069e-01 -3.22709352e-01
-2.51223624e-01 2.83636093e-01 5.71141422e-01 5.67661881e-01
9.02652085e-01 -1.36087406e+00 -3.71315926e-01 -3.94753702e-02
2.12290183e-01 -4.69786003e-02 3.20694357e-01 1.09444284e+00
-7.05692291e-01 5.60002089e-01 -3.57528895e-01 -1.04572630e+00
-1.22570312e+00 5.03790557e-01 2.17845604e-01 3.43596041e-01
-9.41797256e-01 6.95580423e-01 3.32189761e-02 1.52141795e-01
4.78648007e-01 -2.58390874e-01 -7.24752396e-02 -4.15013917e-02
7.90095270e-01 8.77053320e-01 -9.32530910e-02 -5.64935267e-01
-9.55141366e-01 6.89190447e-01 4.40271914e-01 -5.59117757e-02
1.12219703e+00 -6.82255030e-01 2.68962197e-02 8.05885792e-01
8.76884520e-01 -1.91623464e-01 -1.56443822e+00 -1.27176568e-01
-4.66907956e-02 -3.87146354e-01 1.02538235e-01 -5.63295901e-01
-8.93016458e-01 8.69873464e-01 9.36019778e-01 -2.99540967e-01
1.38281083e+00 1.26120180e-01 8.18595350e-01 2.93762267e-01
8.00985038e-01 -8.71067822e-01 2.55632490e-01 5.53896666e-01
7.24510074e-01 -1.19594836e+00 1.31801173e-01 -2.18787670e-01
-4.61506635e-01 1.18311048e+00 5.66915333e-01 -1.19554467e-01
5.00596225e-01 5.50865531e-01 5.54656051e-03 -6.36621490e-02
-8.61632407e-01 -1.25144526e-01 -2.65700072e-01 9.35682535e-01
1.83525160e-01 -2.70722359e-01 2.78596990e-02 2.52194911e-01
3.77768755e-01 3.68898034e-01 5.61707616e-01 1.38111973e+00
-4.29603934e-01 -5.51098585e-01 -5.33808112e-01 5.47184311e-02
-1.83108106e-01 1.86207563e-01 -1.92178220e-01 8.15812111e-01
1.14028662e-01 1.03726983e+00 3.12394023e-01 -3.11170250e-01
3.23757350e-01 -2.98077047e-01 4.33697253e-01 -2.61368722e-01
-8.81926417e-02 8.61363783e-02 -1.69138908e-01 -1.05251122e+00
-7.40310311e-01 -9.03066695e-01 -1.56324840e+00 -2.77950674e-01
-1.42119989e-01 -2.76175857e-01 8.09211373e-01 6.14460468e-01
7.01558948e-01 4.99769568e-01 2.48816013e-01 -1.25663853e+00
5.56311347e-02 -5.16448975e-01 -4.61307019e-01 -2.18613178e-01
5.91843724e-01 -8.93348455e-01 -4.74522114e-01 4.79092270e-01] | [8.52540397644043, -1.299190878868103] |
52e5f085-60b9-4e95-adb9-521efa220022 | misc210k-a-large-scale-dataset-for-multi | null | null | http://openaccess.thecvf.com//content/CVPR2023/html/Sun_MISC210K_A_Large-Scale_Dataset_for_Multi-Instance_Semantic_Correspondence_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Sun_MISC210K_A_Large-Scale_Dataset_for_Multi-Instance_Semantic_Correspondence_CVPR_2023_paper.pdf | MISC210K: A Large-Scale Dataset for Multi-Instance Semantic Correspondence | Semantic correspondence have built up a new way for object recognition. However current single-object matching schema can be hard for discovering commonalities for a category and far from the real-world recognition tasks. To fill this gap, we design the multi-instance semantic correspondence task which aims at constructing the correspondence between multiple objects in an image pair. To support this task, we build a multi-instance semantic correspondence (MISC) dataset from COCO Detection 2017 task called MISC210K. We construct our dataset as three steps: (1) category selection and data cleaning; (2) keypoint design based on 3D models and object description rules; (3) human-machine collaborative annotation. Following these steps, we select 34 classes of objects with 4,812 challenging images annotated via a well designed semi-automatic workflow, and finally acquire 218,179 image pairs with instance masks and instance-level keypoint pairs annotated. We design a dual-path collaborative learning pipeline to train instance-level co-segmentation task and fine-grained level correspondence task together. Benchmark evaluation and further ablation results with detailed analysis are provided with three future directions proposed. Our project is available on https://github.com/YXSUNMADMAX/MISC210K. | ['Wenqiang Zhang', 'Weifeng Ge', 'Yizhou Yu', 'Runmin Wu', 'Yuzhou Zhao', 'Haijing Guo', 'Yiwen Huang', 'Yixuan Sun'] | 2023-01-01 | null | null | null | cvpr-2023-1 | ['object-recognition', 'semantic-correspondence'] | ['computer-vision', 'computer-vision'] | [ 2.61639744e-01 -5.25045320e-02 -2.19366342e-01 -7.36346185e-01
-1.11331117e+00 -7.43558347e-01 7.52035558e-01 2.93481201e-01
-1.90243557e-01 2.02410277e-02 -5.87572306e-02 -4.23679426e-02
-2.93900132e-01 -6.47633314e-01 -9.91943002e-01 -2.91057229e-01
1.16469443e-01 8.67774367e-01 5.03467143e-01 2.05403909e-01
4.46605176e-01 3.40571493e-01 -1.93780494e+00 7.92733908e-01
7.36951888e-01 1.29466307e+00 3.53393763e-01 4.52805310e-01
-4.88487154e-01 3.61877680e-01 -1.94776654e-01 -4.75095212e-01
5.17575026e-01 -2.40760028e-01 -1.25592792e+00 2.66738236e-01
9.43486631e-01 8.63370374e-02 4.53517102e-02 1.19430590e+00
2.77353793e-01 9.76791829e-02 4.72313195e-01 -1.59251118e+00
-7.54479468e-01 6.73728764e-01 -6.13572776e-01 7.76308104e-02
4.32077460e-02 3.12429518e-01 1.16423476e+00 -1.24662828e+00
6.40625477e-01 1.29394341e+00 8.09491515e-01 4.77804095e-01
-1.08890438e+00 -8.21689665e-01 1.57750562e-01 4.22583818e-01
-1.52748489e+00 -4.23944801e-01 5.31113803e-01 -4.62202072e-01
9.44858313e-01 4.65810150e-01 5.76488912e-01 6.25133336e-01
-6.44009113e-01 9.91110146e-01 1.07384813e+00 -2.73915052e-01
-1.18060417e-01 3.85222323e-02 4.60450619e-01 5.54649591e-01
7.48417005e-02 -1.37067184e-01 -3.39334339e-01 -1.47801423e-02
5.17813861e-01 1.35379527e-02 1.35143742e-01 -4.44872051e-01
-1.47560453e+00 4.14217502e-01 9.00806487e-01 2.94187129e-01
-1.48594216e-01 1.93138927e-01 4.42338198e-01 1.06317952e-01
2.53997147e-01 7.33250380e-01 -6.57067657e-01 2.56688625e-01
-7.50718594e-01 4.31690454e-01 4.87532973e-01 1.56656325e+00
9.45931733e-01 -8.43366444e-01 -3.28737795e-01 1.21626306e+00
2.15095818e-01 1.61817819e-01 2.67091155e-01 -8.63378406e-01
5.53676903e-01 1.04971874e+00 -1.43187344e-01 -8.34682345e-01
-4.68158275e-01 -4.76892054e-01 -4.35558736e-01 -1.83257401e-01
5.24976969e-01 5.31119704e-01 -1.20596266e+00 1.33406770e+00
6.43620431e-01 5.24645030e-01 -2.99411565e-01 1.04026318e+00
1.34574509e+00 3.10108155e-01 2.96550065e-01 5.12777388e-01
1.76756108e+00 -1.31068158e+00 -3.61632466e-01 -1.81188881e-01
6.15414619e-01 -8.11949134e-01 1.10614109e+00 1.14523834e-02
-9.34018731e-01 -7.18082786e-01 -7.37338185e-01 -2.75818676e-01
-7.50186801e-01 2.21749455e-01 7.89439023e-01 1.01355761e-01
-6.95757031e-01 3.25963736e-01 -6.10380769e-01 -4.37224209e-01
9.58818793e-01 2.12146506e-01 -4.77276832e-01 -2.55201876e-01
-8.69990230e-01 8.18534970e-01 6.58145785e-01 1.14519149e-01
-7.38543868e-01 -1.19596350e+00 -8.10109794e-01 -1.93643302e-01
5.76798618e-01 -8.12576056e-01 1.19472563e+00 -8.70867729e-01
-6.95290923e-01 1.76019526e+00 9.60301086e-02 -1.90065965e-01
4.31343764e-01 -1.25335425e-01 -2.78526008e-01 -7.89043605e-02
6.88486397e-01 1.08957529e+00 4.87856030e-01 -1.41594243e+00
-1.16148770e+00 -5.21546185e-01 -7.83279911e-02 1.52736660e-02
2.12743789e-01 3.48119050e-01 -1.18416321e+00 -5.84527254e-01
4.94168431e-01 -8.60766470e-01 -1.53214723e-01 1.45368055e-01
-7.11319625e-01 -6.25980318e-01 5.77620506e-01 -5.13391018e-01
8.97701919e-01 -2.00680232e+00 -1.81537885e-02 1.90456912e-01
2.70005047e-01 2.04145208e-01 -2.49265537e-01 -5.97342327e-02
-2.84845471e-01 6.14785291e-02 -3.77852976e-01 -6.30540907e-01
1.27262726e-01 -1.28328847e-03 -1.17007762e-01 2.95460463e-01
4.75256950e-01 1.33392787e+00 -9.07474160e-01 -5.79722047e-01
2.42277831e-01 2.79318597e-02 -4.77577329e-01 2.99645513e-01
-3.55209410e-01 4.43922639e-01 -3.28013301e-01 1.19251287e+00
6.87252522e-01 -4.72955078e-01 -8.89146999e-02 -6.91515446e-01
1.85152423e-02 2.23612234e-01 -1.37881160e+00 2.06848574e+00
-2.72562563e-01 3.50704551e-01 -1.27781764e-01 -1.06990659e+00
8.50479722e-01 -1.61327094e-01 5.70156515e-01 -8.69250834e-01
9.99557525e-02 4.65496778e-01 -3.26787502e-01 -6.46998048e-01
3.49684447e-01 2.33600900e-01 -2.47170463e-01 2.17779040e-01
3.38316023e-01 -1.97581440e-01 2.33245000e-01 1.84057727e-01
9.36142147e-01 2.58564055e-01 9.65935290e-02 -2.67014444e-01
2.92477608e-01 4.70377058e-01 6.76898718e-01 8.51499319e-01
-3.56323868e-01 9.28941905e-01 2.79165238e-01 -5.16152620e-01
-1.04656756e+00 -9.49284852e-01 -4.02461052e-01 9.86517012e-01
5.90142608e-01 -3.71467978e-01 -6.25235856e-01 -8.19392681e-01
4.39447582e-01 3.68867278e-01 -8.10396075e-01 1.16576865e-01
-5.54347992e-01 -5.99072516e-01 5.74242234e-01 5.43543220e-01
6.40594006e-01 -1.17933619e+00 -1.26438841e-01 1.97953992e-02
-2.84037381e-01 -1.42699957e+00 -6.82956994e-01 4.65459637e-02
-4.87803221e-01 -1.58801556e+00 -2.78097719e-01 -9.09048855e-01
7.79971600e-01 4.27337468e-01 1.49741793e+00 3.91433150e-01
-7.62416959e-01 3.80591005e-01 -3.05880904e-01 -4.19274032e-01
-1.90658033e-01 7.00007826e-02 -2.28732646e-01 1.26586646e-01
6.35117352e-01 -1.39168248e-01 -7.27628827e-01 6.61719322e-01
-7.50725925e-01 4.15114462e-01 5.79165339e-01 5.14472485e-01
1.15305412e+00 -2.34584689e-01 5.08979440e-01 -8.65658998e-01
-2.07003783e-02 -6.14587069e-01 -7.64820516e-01 4.65763569e-01
-4.64615703e-01 -3.34252387e-01 6.44346997e-02 -1.87995106e-01
-8.47033143e-01 4.48495626e-01 -3.36265527e-02 -5.58328211e-01
-4.75922078e-01 8.71230364e-02 -5.22426546e-01 1.27817497e-01
5.61495602e-01 -1.47703821e-02 -1.34475023e-01 -7.69574165e-01
7.42519259e-01 7.78188527e-01 1.02741385e+00 -7.49223769e-01
8.03127408e-01 4.35263366e-01 -3.38145345e-01 -2.75220454e-01
-1.21477103e+00 -1.08185935e+00 -1.00192320e+00 -1.35370865e-01
1.14533746e+00 -1.02493572e+00 -4.67434108e-01 5.79355121e-01
-9.94449198e-01 -4.51273769e-01 -3.06557178e-01 1.80269971e-01
-4.63957101e-01 -7.94178620e-02 -1.67190582e-01 -2.31050462e-01
-2.77841479e-01 -1.14953613e+00 1.35884774e+00 3.12893987e-01
-2.51809116e-02 -5.52217305e-01 -3.11314315e-01 9.21687007e-01
1.55691311e-01 1.98753446e-01 5.51474392e-01 -8.04295778e-01
-9.07805860e-01 -2.55098283e-01 -7.57287264e-01 2.58875161e-01
1.21994212e-01 -3.94852199e-02 -9.52172697e-01 9.41856802e-02
-6.48773611e-01 -2.92369962e-01 9.58961844e-01 1.19918495e-01
1.71887314e+00 5.78298001e-03 -6.44962132e-01 9.33828652e-01
1.34213030e+00 -1.30566314e-01 4.66308177e-01 5.97279012e-01
1.19149172e+00 7.95265436e-01 9.73004401e-01 2.01951303e-02
6.89004242e-01 9.37563300e-01 5.02239048e-01 -1.27932876e-01
-5.71470857e-01 -2.70216048e-01 -4.43881929e-01 3.53364557e-01
1.90362006e-01 1.84390143e-01 -1.20790660e+00 9.50637639e-01
-1.90001476e+00 -7.79847562e-01 -5.45887768e-01 1.97296727e+00
9.15925384e-01 6.28968328e-02 2.04838321e-01 -1.58893868e-01
1.03891397e+00 -4.11932141e-01 -5.02963424e-01 2.83226937e-01
-8.81432891e-02 4.29127440e-02 5.33842921e-01 2.27191731e-01
-1.50387251e+00 1.12128377e+00 4.68642473e+00 9.19206381e-01
-7.05304444e-01 3.49468708e-01 6.26480758e-01 5.86212203e-02
-1.97215542e-01 2.07326815e-01 -1.01525676e+00 5.99254787e-01
2.07127795e-01 2.92962223e-01 6.08236380e-02 8.46903741e-01
-1.94671184e-01 5.67912310e-02 -1.29186320e+00 1.34564817e+00
-1.00378312e-01 -1.69561315e+00 4.15966362e-02 -3.28579664e-01
7.57673323e-01 2.97869802e-01 -3.71714801e-01 3.37181360e-01
1.43120021e-01 -1.01438594e+00 9.20416355e-01 4.88123506e-01
7.40152359e-01 -3.37620467e-01 4.25407737e-01 9.49004218e-02
-1.45813024e+00 -3.74427773e-02 -1.58446595e-01 5.38410127e-01
-1.05390020e-01 6.43241704e-01 -5.40332735e-01 6.72709167e-01
1.22561848e+00 8.53820324e-01 -9.74510789e-01 1.47164440e+00
-1.57988340e-01 3.50836813e-01 -4.65498358e-01 4.37185884e-01
2.29630888e-01 5.08389203e-03 4.07299012e-01 1.43423903e+00
-1.05936758e-01 1.40398517e-01 2.23503083e-01 1.20597482e+00
-2.46167555e-01 -1.43045127e-01 -1.29785910e-01 2.47229904e-01
8.22834969e-01 1.51085436e+00 -1.09953868e+00 -4.87026632e-01
-3.99055451e-01 9.29547727e-01 3.60183239e-01 -8.74343291e-02
-9.31118190e-01 -3.19761515e-01 9.48250532e-01 2.94798948e-02
9.60546881e-02 1.18533611e-01 -5.86973190e-01 -1.18544948e+00
1.63412228e-01 -7.19259918e-01 6.98793411e-01 -6.63749635e-01
-1.64093614e+00 2.84384042e-01 1.14692949e-01 -1.21060479e+00
4.07966405e-01 -4.79828596e-01 -5.50349236e-01 7.17312396e-01
-1.55302215e+00 -1.68097043e+00 -8.72359812e-01 4.48246688e-01
7.58124471e-01 9.96148363e-02 5.74022412e-01 7.89945960e-01
-6.59584999e-01 6.45682037e-01 -4.22098190e-01 3.60746562e-01
7.56989658e-01 -1.28160310e+00 7.34743953e-01 6.57093525e-01
2.00408548e-01 4.22215670e-01 2.98545301e-01 -5.84976733e-01
-1.33683300e+00 -1.57848144e+00 7.83404052e-01 -1.04660428e+00
5.14976561e-01 -5.58628440e-01 -1.10406601e+00 7.31810212e-01
-3.21678668e-01 5.99129617e-01 4.40931797e-01 2.92648580e-02
-6.36135817e-01 -6.08112849e-02 -1.12346101e+00 2.15078011e-01
1.68243074e+00 -4.26090717e-01 -6.58141255e-01 6.12215817e-01
8.28326702e-01 -7.51572430e-01 -9.70960081e-01 6.27976239e-01
3.88332635e-01 -5.39619029e-01 1.21031570e+00 -7.29875028e-01
4.33528870e-01 -6.87906682e-01 -2.46846616e-01 -9.07052815e-01
-3.43692183e-01 -2.88858026e-01 2.51128614e-01 1.59319925e+00
5.28696477e-01 -4.08134788e-01 6.62488043e-01 7.13523209e-01
-5.71673334e-01 -7.83574522e-01 -7.44443536e-01 -8.89355958e-01
-8.55988860e-02 -6.97350383e-01 9.58547950e-01 1.25210631e+00
-4.56172824e-01 1.18931867e-01 2.04808190e-01 3.98585021e-01
8.90409529e-01 5.18598735e-01 1.00636542e+00 -1.00176013e+00
-1.84299245e-01 -7.66624033e-01 -5.16417563e-01 -8.49531233e-01
8.23437497e-02 -1.44277120e+00 5.98845780e-02 -1.64682949e+00
5.49830556e-01 -1.30007088e+00 -2.51690477e-01 8.66359472e-01
-4.40600961e-01 5.99214792e-01 1.25176281e-01 5.96849144e-01
-9.49148118e-01 2.12004736e-01 1.06534564e+00 -2.85263479e-01
6.40894333e-03 -1.21069409e-01 -8.11915457e-01 4.65018481e-01
5.73730707e-01 -4.86078829e-01 -1.30935907e-01 -5.86276650e-01
-3.14732268e-02 -5.36259651e-01 8.35293651e-01 -8.66163611e-01
2.54651874e-01 -2.05370322e-01 3.30233753e-01 -8.13731015e-01
-2.35290453e-02 -9.25209463e-01 3.17314535e-01 1.45029902e-01
-3.39787722e-01 -2.95150399e-01 1.52277932e-01 3.51345360e-01
-2.48024896e-01 -1.31530026e-02 9.15773034e-01 -2.25900874e-01
-1.34041083e+00 6.62871599e-01 4.84425932e-01 1.33397132e-01
1.27709198e+00 -3.51607978e-01 -4.09641296e-01 5.53402781e-01
-9.50208604e-01 7.32612908e-01 3.79495025e-01 9.85322297e-01
3.35665971e-01 -1.37685823e+00 -7.60406435e-01 9.86284763e-03
8.02743196e-01 5.22004962e-01 3.33095878e-01 8.66031647e-01
-3.04047406e-01 3.30161780e-01 -1.13418259e-01 -1.01284587e+00
-1.30647254e+00 4.65416461e-01 6.38279557e-01 1.89559922e-01
-7.76292741e-01 1.10068583e+00 2.79831976e-01 -9.13775623e-01
1.60046041e-01 -2.15829894e-01 -1.40852362e-01 1.54263005e-01
4.15011823e-01 1.34672776e-01 4.47710872e-01 -6.10351801e-01
-7.96966314e-01 7.54048169e-01 -9.81115852e-04 4.03934062e-01
1.27880144e+00 -8.73805508e-02 -3.23350608e-01 8.26484412e-02
1.42327905e+00 -5.84681809e-01 -1.14373493e+00 -5.10485351e-01
4.37738001e-01 -7.01629817e-01 -2.45637983e-01 -9.04290497e-01
-1.09531248e+00 2.87908137e-01 6.41768157e-01 -5.63977659e-03
9.36100245e-01 7.22593546e-01 6.81374967e-01 1.04408264e-02
3.15351218e-01 -1.18601215e+00 9.89445578e-03 3.12085569e-01
1.00771320e+00 -1.72331047e+00 -2.44748756e-01 -8.40266228e-01
-3.88797402e-01 7.94171989e-01 9.97488260e-01 -1.19194351e-01
6.43920660e-01 6.85034366e-03 4.66897935e-02 -6.40166819e-01
-5.70432544e-01 -5.64029634e-01 6.92508340e-01 4.71349329e-01
2.43073180e-01 3.06664646e-01 -9.72417220e-02 8.12540650e-01
-4.26476821e-02 -1.71360776e-01 -5.68290465e-02 7.71441102e-01
-3.54402572e-01 -1.00787830e+00 -3.54733169e-01 6.83548868e-01
-1.49212375e-01 2.62797084e-02 -3.97882521e-01 6.36326671e-01
5.77467859e-01 7.75507927e-01 4.33323056e-01 -2.91974008e-01
7.18687177e-01 -1.60962008e-02 4.44834739e-01 -8.75495553e-01
-6.14797115e-01 -3.76686662e-01 1.48576409e-01 -9.39290822e-01
-3.57442051e-01 -7.73490012e-01 -1.48082137e+00 1.13704195e-02
-4.01427358e-01 -1.61436766e-01 8.96071613e-01 9.66840148e-01
6.28978670e-01 4.78933305e-01 4.35030013e-01 -8.63409996e-01
-1.47053599e-01 -8.26787114e-01 -1.23070769e-01 9.24851596e-01
-5.75166456e-02 -7.90824354e-01 -1.77186370e-01 2.43538499e-01] | [9.53165054321289, 1.5626201629638672] |
8937ab0f-79bd-4352-a2b9-bacb4bc8c279 | diffusion-based-conditional-ecg-generation | 2301.08227 | null | https://arxiv.org/abs/2301.08227v2 | https://arxiv.org/pdf/2301.08227v2.pdf | Diffusion-based Conditional ECG Generation with Structured State Space Models | Synthetic data generation is a promising solution to address privacy issues with the distribution of sensitive health data. Recently, diffusion models have set new standards for generative models for different data modalities. Also very recently, structured state space models emerged as a powerful modeling paradigm to capture long-term dependencies in time series. We put forward SSSD-ECG, as the combination of these two technologies, for the generation of synthetic 12-lead electrocardiograms conditioned on more than 70 ECG statements. Due to a lack of reliable baselines, we also propose conditional variants of two state-of-the-art unconditional generative models. We thoroughly evaluate the quality of the generated samples, by evaluating pretrained classifiers on the generated data and by evaluating the performance of a classifier trained only on synthetic data, where SSSD-ECG clearly outperforms its GAN-based competitors. We demonstrate the soundness of our approach through further experiments, including conditional class interpolation and a clinical Turing test demonstrating the high quality of the SSSD-ECG samples across a wide range of conditions. | ['Nils Strodthoff', 'Juan Miguel Lopez Alcaraz'] | 2023-01-19 | null | null | null | null | ['synthetic-data-generation', 'synthetic-data-generation'] | ['medical', 'miscellaneous'] | [ 3.80274981e-01 4.52562720e-01 2.09056720e-01 -6.42883301e-01
-1.40276408e+00 -5.17867029e-01 5.73630512e-01 -9.90887135e-02
-1.45075604e-01 1.13181436e+00 3.26791555e-01 -1.47215858e-01
1.07385464e-01 -6.06780171e-01 -6.81266129e-01 -5.62359631e-01
-2.51505733e-01 6.70293272e-01 -3.87139618e-01 9.62735340e-02
-3.81910205e-01 7.94237480e-02 -9.45072651e-01 3.25868100e-01
9.40388501e-01 9.68395948e-01 -5.72161734e-01 7.04279721e-01
6.12764716e-01 5.55765510e-01 -1.03643000e+00 -8.21358919e-01
1.32509410e-01 -1.02167499e+00 -5.38967073e-01 -1.92467287e-01
-6.71585500e-02 -4.23299193e-01 -3.42757590e-02 6.88138783e-01
9.58488405e-01 -4.19764727e-01 5.80498219e-01 -1.22739971e+00
-5.88302255e-01 6.80569947e-01 8.15087631e-02 -5.21189310e-02
5.06762505e-01 3.38103980e-01 5.89028120e-01 -3.74071360e-01
9.36677873e-01 7.02730179e-01 9.80590820e-01 1.02632618e+00
-1.64574552e+00 -5.44488311e-01 -4.77333546e-01 -3.20103288e-01
-1.32576764e+00 -3.87448013e-01 7.95403719e-01 -2.87309140e-01
6.21602476e-01 4.74014848e-01 7.62501717e-01 2.03427172e+00
4.30334717e-01 6.71400130e-01 1.47503901e+00 -1.25128523e-01
5.97389400e-01 2.27001473e-01 -2.46908009e-01 3.40170830e-01
1.17192030e-01 3.67613167e-01 -6.26551092e-01 -7.23871052e-01
6.83920026e-01 -1.82564691e-01 -2.99175322e-01 -2.29865357e-01
-1.26985121e+00 6.61564469e-01 9.53963250e-02 1.06894307e-01
-5.73281229e-01 2.20646247e-01 4.17754382e-01 2.23234847e-01
5.93712986e-01 3.89439315e-01 -1.85792968e-01 -3.39566141e-01
-1.17377877e+00 4.43782359e-01 9.58029687e-01 1.08973312e+00
-3.86459590e-03 1.94270715e-01 -6.78407669e-01 3.78718644e-01
2.12616757e-01 6.43945456e-01 2.75207490e-01 -6.76469028e-01
3.51547599e-01 -4.55509722e-02 1.53920159e-01 -5.52965939e-01
-1.15827158e-01 -6.28670812e-01 -1.34800756e+00 -1.75022587e-01
4.46170092e-01 -6.76770389e-01 -1.01981318e+00 2.06014204e+00
1.16900809e-01 3.23016077e-01 3.23904067e-01 5.42516232e-01
6.97773159e-01 4.04490560e-01 1.62059069e-01 -3.47071558e-01
9.80553031e-01 -2.44660810e-01 -8.19695055e-01 1.15697235e-01
2.81652957e-01 -2.74800807e-01 7.06445158e-01 3.78555506e-01
-1.25682116e+00 -5.10762036e-01 -7.42095828e-01 3.29191446e-01
1.09217048e-01 -2.23773047e-01 4.23639923e-01 1.09413159e+00
-1.14554632e+00 6.50649905e-01 -1.14049339e+00 -7.62476549e-02
9.26759899e-01 1.37441620e-01 -3.06642979e-01 3.93265337e-02
-1.56570446e+00 6.78880930e-01 -9.52546522e-02 2.98711043e-02
-1.20621717e+00 -9.16817605e-01 -7.00668931e-01 -7.66874403e-02
-1.72129720e-01 -1.08723974e+00 9.12781656e-01 -5.80650866e-01
-1.37380362e+00 9.86792505e-01 2.99785212e-02 -8.80377889e-01
1.10117662e+00 -2.88420916e-02 -6.80277824e-01 -9.81207043e-02
-5.91632538e-02 4.46069181e-01 8.88356984e-01 -1.12454140e+00
-2.73100212e-02 -1.89350843e-01 -5.54459631e-01 -3.01302493e-01
2.52092797e-02 -1.88468829e-01 5.76935150e-02 -8.22080374e-01
-3.76199633e-01 -1.00839746e+00 -4.65960413e-01 -3.66849661e-01
-8.63277316e-01 2.18700826e-01 2.82314271e-01 -8.25405538e-01
1.10605049e+00 -2.09560561e+00 -1.36919171e-01 4.31377620e-01
1.43782049e-01 1.22910589e-01 9.49734673e-02 4.31415498e-01
-1.54558539e-01 2.52660900e-01 -6.21790946e-01 -5.38347363e-01
9.92858410e-02 1.77804932e-01 -5.02830684e-01 3.07983637e-01
4.41398948e-01 1.30943143e+00 -7.94204473e-01 -3.35115522e-01
-2.62640566e-01 8.51300716e-01 -5.93226194e-01 4.83430803e-01
-1.08273134e-01 1.07465279e+00 -3.06292236e-01 2.99635112e-01
4.53494519e-01 -3.62077981e-01 2.30297178e-01 1.07611097e-01
6.87707961e-01 1.34281814e-01 -8.27834725e-01 2.07110095e+00
-1.03877597e-02 1.36295527e-01 -4.20072854e-01 -6.22250676e-01
9.65289891e-01 8.67728710e-01 5.72492301e-01 -5.05598187e-01
3.22780572e-02 1.28249824e-01 -1.82152204e-02 -3.94678831e-01
8.14205408e-02 -5.37876129e-01 -5.04774034e-01 5.93121469e-01
1.25248298e-01 -3.23544770e-01 -2.10753247e-01 1.79431990e-01
1.23308027e+00 3.36902857e-01 7.02172518e-02 -5.14208414e-02
-1.00193299e-01 -4.05781120e-01 5.30338168e-01 1.01562095e+00
-1.87448218e-01 1.17048144e+00 5.15372634e-01 -3.78113389e-01
-9.78657424e-01 -1.29108787e+00 -2.77148008e-01 5.53493947e-02
-3.95705909e-01 -4.86944884e-01 -1.05895352e+00 -8.37180436e-01
-3.13669205e-01 1.03392851e+00 -9.28299844e-01 -3.06309402e-01
-2.30618164e-01 -1.22975802e+00 1.12756324e+00 6.22039795e-01
2.60085791e-01 -9.76605237e-01 -9.53020692e-01 3.85290027e-01
-4.11688626e-01 -9.68917549e-01 -1.93849504e-01 1.05073303e-01
-9.19124722e-01 -6.71288967e-01 -1.03070009e+00 -2.79156089e-01
4.64415282e-01 -1.03535044e+00 1.53928256e+00 -2.77664691e-01
-3.95643950e-01 3.55307430e-01 -1.72563300e-01 -6.40760362e-01
-1.06005406e+00 5.19890822e-02 -2.09587947e-01 2.81360507e-01
2.37763077e-02 -7.68032789e-01 -8.16126704e-01 5.45084104e-02
-9.34641242e-01 1.44602895e-01 2.81234562e-01 1.02508342e+00
7.70146489e-01 -4.72473979e-01 1.03463662e+00 -1.35037100e+00
8.98119509e-01 -5.54305673e-01 -2.39346668e-01 2.45338261e-01
-8.81631851e-01 7.78732002e-02 3.58899176e-01 -3.00036013e-01
-9.63381112e-01 -4.27839048e-02 -4.81181204e-01 -3.11901182e-01
-3.64441514e-01 5.80329359e-01 -1.09372050e-01 5.06973743e-01
1.03020120e+00 4.95407254e-01 1.00453489e-01 -2.73090839e-01
4.92366105e-01 6.55776918e-01 7.02588677e-01 -6.24791622e-01
4.63235795e-01 4.30814266e-01 2.35511176e-02 -2.85304248e-01
-4.36377257e-01 2.83344030e-01 -3.38777810e-01 7.80157885e-03
9.19656456e-01 -9.42503095e-01 -4.54718173e-01 6.86494529e-01
-1.04992366e+00 -3.69700402e-01 -9.18878615e-01 2.40359589e-01
-8.25318754e-01 9.50925425e-02 -7.56276548e-01 -9.20266271e-01
-6.62645876e-01 -8.16539526e-01 1.30754519e+00 -2.14162320e-01
-6.49608493e-01 -1.09545958e+00 4.93730396e-01 9.56365615e-02
7.12949872e-01 1.10084796e+00 7.77949393e-01 -7.02114999e-01
-3.27163994e-01 -6.26226902e-01 4.39745098e-01 4.83645737e-01
1.33563131e-01 -2.83540517e-01 -1.22989678e+00 -4.17505085e-01
3.46671939e-01 -3.43763262e-01 4.75071937e-01 4.44471657e-01
1.20778632e+00 -2.27743044e-01 -2.50035703e-01 7.38710582e-01
1.18566251e+00 1.17086828e-01 1.14856827e+00 -4.25808907e-01
4.24960881e-01 2.27856323e-01 2.05146641e-01 6.50453866e-01
3.94869596e-01 4.01758939e-01 1.63479477e-01 -3.32174927e-01
4.96485904e-02 -5.40445328e-01 6.67588115e-02 7.85958230e-01
-1.52235210e-01 -3.81111115e-01 -8.19887996e-01 5.61009407e-01
-1.46016705e+00 -1.05631971e+00 -1.18432157e-02 2.31474638e+00
1.12895346e+00 5.27473018e-02 2.50245214e-01 1.75322607e-01
2.98726708e-01 -1.50829136e-01 -6.07440293e-01 -1.30892456e-01
-2.49075696e-01 7.30514407e-01 8.28082040e-02 2.15663319e-03
-9.09584403e-01 3.20928186e-01 7.52178049e+00 3.98667783e-01
-1.14300907e+00 2.21484572e-01 1.18010259e+00 -5.53666465e-02
-5.19412041e-01 -2.65357941e-01 -3.74608308e-01 8.05163741e-01
1.44460869e+00 -1.82534769e-01 1.28712147e-01 5.40751874e-01
-1.16247557e-01 2.25663945e-01 -1.42255020e+00 9.86764371e-01
1.00564569e-01 -1.52935493e+00 -1.44316599e-01 9.34724882e-02
9.60325658e-01 -3.36240493e-02 2.89835870e-01 9.65315625e-02
2.89045095e-01 -1.29463100e+00 7.19504535e-01 7.64807820e-01
1.35645521e+00 -4.02808219e-01 6.96573734e-01 3.96198958e-01
-4.44109976e-01 4.11721349e-01 1.95303947e-01 4.46027428e-01
4.69276488e-01 6.89100921e-01 -9.82006848e-01 8.99519920e-01
5.17704606e-01 6.16361141e-01 -5.29893756e-01 8.33518922e-01
-2.30221361e-01 1.11305881e+00 -3.42231929e-01 2.81125754e-01
-3.91835898e-01 1.63626865e-01 4.69119817e-01 1.07076132e+00
4.87457424e-01 -2.34089643e-02 -2.55595833e-01 1.27339125e+00
4.34246436e-02 -2.11474434e-01 -6.90118313e-01 -1.06740430e-01
2.04761833e-01 8.99734855e-01 -2.79180050e-01 -3.34118158e-01
-4.63127857e-03 1.06008720e+00 -8.79754126e-02 4.14968967e-01
-1.11392260e+00 -1.04647040e-01 1.89490020e-01 2.33351871e-01
7.42621049e-02 1.71192393e-01 -3.69192064e-01 -1.28224134e+00
1.58691891e-02 -1.22710979e+00 6.32112145e-01 -8.42406034e-01
-1.48986495e+00 1.17687285e+00 2.70812633e-03 -1.38632953e+00
-9.64410484e-01 1.53492808e-01 -2.97745466e-01 1.24768448e+00
-1.03219783e+00 -1.21695948e+00 -1.34592623e-01 6.62435949e-01
-5.33566922e-02 -4.29281890e-02 1.62318039e+00 2.54758567e-01
-1.38107136e-01 8.77656698e-01 -1.70909837e-02 2.09228456e-01
5.63382030e-01 -1.21757019e+00 8.54758322e-01 7.47135460e-01
3.02558243e-01 5.83559990e-01 6.27681077e-01 -6.99515522e-01
-1.07938004e+00 -1.16384435e+00 6.82177246e-01 -9.27893102e-01
-6.43245205e-02 -6.47022367e-01 -9.60101604e-01 7.76583493e-01
2.39266068e-01 3.81282493e-02 1.03878045e+00 -1.75561145e-01
-1.32691726e-01 -1.33012801e-01 -1.47705376e+00 2.76121378e-01
8.48796725e-01 -5.56774735e-01 -4.43452269e-01 1.98505923e-01
3.85110021e-01 -6.12731636e-01 -1.39216399e+00 3.94274354e-01
4.53388304e-01 -1.03056180e+00 7.02041864e-01 -7.81098425e-01
5.97202122e-01 -4.61039506e-02 8.19761585e-03 -1.51174176e+00
-2.46124081e-02 -1.20123374e+00 -1.48336813e-01 1.29573226e+00
6.56509042e-01 -7.38529205e-01 9.30523694e-01 1.01679432e+00
1.97607651e-01 -6.84869468e-01 -1.05040550e+00 -6.30782545e-01
4.18086722e-02 -5.00844121e-01 9.18519378e-01 8.96418869e-01
-8.15358832e-02 2.50821501e-01 -7.97361434e-01 -1.22851677e-01
7.96000957e-01 8.99931937e-02 8.81824851e-01 -1.01966679e+00
-7.42547452e-01 2.17718169e-01 -4.39048558e-01 -5.12277246e-01
-1.33567512e-01 -9.62118864e-01 7.80887306e-02 -1.26800919e+00
8.81352276e-02 -6.36497617e-01 -4.05201048e-01 3.21044356e-01
-2.89748847e-01 4.65443254e-01 -1.61544643e-02 -2.98345312e-02
-2.23867327e-01 4.88764673e-01 1.18718314e+00 1.39173403e-01
-5.74235059e-02 2.30504319e-01 -8.04389417e-01 1.55857220e-01
6.33060694e-01 -6.18345857e-01 -6.30647123e-01 -1.59034476e-01
2.07564861e-01 5.99859357e-01 5.39662361e-01 -1.14814091e+00
-2.09503487e-01 2.43851706e-01 5.25554538e-01 -2.15081379e-01
4.25484985e-01 -6.80514991e-01 1.13554370e+00 5.80303669e-01
-6.43440187e-01 -3.31815779e-02 1.44543499e-01 7.28086412e-01
-2.12499604e-01 4.72603828e-01 6.05762959e-01 -9.54036694e-03
6.96730241e-02 3.75918180e-01 -4.38542701e-02 6.30683362e-01
8.77346992e-01 -6.00564890e-02 -7.88470805e-02 -7.65612900e-01
-1.10379112e+00 -1.50650829e-01 2.65803546e-01 2.00073570e-01
7.00720310e-01 -1.24817145e+00 -1.14275515e+00 6.89940214e-01
1.34017631e-01 1.21116210e-02 3.21172088e-01 7.86289990e-01
-3.02369773e-01 3.21136531e-03 -1.77974835e-01 -7.79557645e-01
-9.60146248e-01 4.98983234e-01 3.95468146e-01 -4.86248612e-01
-7.00572431e-01 7.38720894e-01 5.07501327e-02 -2.31691942e-01
4.85526659e-02 -4.41616237e-01 4.18057919e-01 -3.74304593e-01
3.36733907e-01 2.80773286e-02 1.13473222e-01 -2.47495607e-01
-4.02307421e-01 -8.67803395e-02 3.60383928e-01 -5.01521170e-01
1.40680981e+00 1.08393997e-01 1.98483199e-01 4.91253793e-01
8.33948493e-01 -1.48249403e-01 -1.29010570e+00 1.17206238e-01
-3.30241799e-01 -3.09736460e-01 -5.64909697e-01 -1.37480998e+00
-9.16554034e-01 8.95391643e-01 8.35875452e-01 3.05746138e-01
1.17715538e+00 -2.42415473e-01 7.02716053e-01 -3.71612996e-01
7.14103937e-01 -4.68052119e-01 -2.36081988e-01 -1.54171020e-01
8.36406052e-01 -9.90191698e-01 -2.38966972e-01 -2.49009162e-01
-9.14823949e-01 4.80519474e-01 -4.15839031e-02 -7.19682947e-02
7.62926698e-01 5.43772638e-01 4.04116780e-01 -2.24902434e-03
-8.17762434e-01 5.32946765e-01 3.17639589e-01 1.02010465e+00
4.11471248e-01 2.61879593e-01 -1.16864473e-01 8.61121595e-01
-3.47998589e-01 5.18097639e-01 3.57675523e-01 7.79211581e-01
7.69459724e-01 -1.38410127e+00 -1.03374831e-01 5.59763074e-01
-8.76327276e-01 -2.08962902e-01 -1.64857641e-01 4.17167723e-01
-2.32485193e-03 7.29705215e-01 -2.61401236e-01 -2.69940466e-01
3.17988068e-01 3.44694644e-01 5.36424696e-01 -3.60693783e-01
-9.31520820e-01 4.52967398e-02 1.20327346e-01 -4.17537659e-01
-3.14038515e-01 -8.67043197e-01 -7.96531200e-01 9.31194872e-02
-8.42559040e-02 2.02633366e-01 5.25795817e-01 5.17029226e-01
8.46454263e-01 7.26646066e-01 4.84404266e-01 -3.44305336e-01
-9.65134025e-01 -8.93043339e-01 -6.35130346e-01 9.53013837e-01
2.05171555e-01 9.36932713e-02 -4.11357880e-02 4.25514996e-01] | [14.311424255371094, 3.0419936180114746] |
dc4e819e-2150-4dd5-86ec-78be50b3d972 | eyelovegan-exploiting-domain-shifts-to-boost | 2203.05344 | null | https://arxiv.org/abs/2203.05344v1 | https://arxiv.org/pdf/2203.05344v1.pdf | EyeLoveGAN: Exploiting domain-shifts to boost network learning with cycleGANs | This paper presents our contribution to the REFUGE challenge 2020. The challenge consisted of three tasks based on a dataset of retinal images: Segmentation of optic disc and cup, classification of glaucoma, and localization of fovea. We propose employing convolutional neural networks for all three tasks. Segmentation is performed using a U-Net, classification is performed by a pre-trained InceptionV3 network, and fovea detection is performed by employing stacked hour-glass for heatmap prediction. The challenge dataset contains images from three different data sources. To enhance performance, cycleGANs were utilized to create a domain-shift between the data sources. These cycleGANs move images across domains, thus creating artificial images which can be used for training. | ['Jakob Mølkjær Slipsager', 'Kristine Aavild Juhl', 'Josefine Vilsbøll Sundgaard'] | 2022-03-10 | null | null | null | null | ['fovea-detection'] | ['medical'] | [ 3.56541723e-01 3.92732292e-01 1.40489832e-01 -3.31281960e-01
-4.41414177e-01 -4.83566642e-01 4.54993159e-01 -5.65588355e-01
-2.86418051e-01 6.08772039e-01 2.27358826e-02 -5.67031264e-01
2.23729372e-01 -6.27917528e-01 -7.48450398e-01 -5.90307415e-01
-6.41861185e-02 -1.64708961e-02 4.77659583e-01 8.09513032e-02
3.14013541e-01 4.12229538e-01 -1.77349067e+00 8.45650673e-01
8.28429818e-01 1.32952738e+00 4.77944314e-02 9.11789358e-01
1.41700506e-01 6.18809104e-01 -5.66648424e-01 -1.25577733e-01
8.26975048e-01 -6.05309844e-01 -7.67943263e-01 3.25650275e-01
6.80648685e-01 -2.02449471e-01 -2.81831324e-02 1.04859829e+00
6.57185674e-01 -2.98983216e-01 5.25839746e-01 -8.77235532e-01
-4.76261973e-01 -3.68309673e-03 -5.63109517e-01 1.89154312e-01
-3.34779769e-02 4.35447842e-01 3.46517265e-01 -5.01901448e-01
9.87842739e-01 1.08393490e+00 5.06517768e-01 7.45698690e-01
-1.00103343e+00 -4.48490977e-01 -6.11028075e-01 1.75232574e-01
-9.96491730e-01 -3.41611296e-01 3.99340540e-01 -8.46385360e-01
7.94228494e-01 3.17375630e-01 1.12473714e+00 4.60929453e-01
3.57390791e-01 4.90425587e-01 1.63511777e+00 -5.69345832e-01
1.28557518e-01 -6.06950298e-02 -1.59779996e-01 6.01039469e-01
2.12154642e-01 3.22460115e-01 -1.23050921e-01 2.42335707e-01
9.79030013e-01 -4.46018428e-01 -2.15040177e-01 -9.80204791e-02
-8.56521547e-01 5.74226975e-01 8.82279277e-01 -1.32143512e-01
-1.77548021e-01 -3.49426605e-02 2.61467427e-01 3.07993650e-01
3.74237329e-01 6.66075230e-01 -3.07192147e-01 3.33172321e-01
-9.07497823e-01 3.98589611e-01 1.77599356e-01 7.51786232e-01
8.01995158e-01 -1.85706392e-01 -4.29387599e-01 5.60584188e-01
4.09836352e-01 2.79258877e-01 7.79640377e-01 -1.05097759e+00
5.16808927e-02 1.11096931e+00 5.11353128e-02 -5.50766826e-01
-6.21521413e-01 -3.85774404e-01 -5.16745508e-01 9.60359633e-01
4.87781942e-01 -7.09272981e-01 -2.10344839e+00 8.40884745e-01
1.93834066e-01 2.67922223e-01 -9.59260166e-02 1.04799008e+00
9.96992350e-01 1.64225772e-01 -3.35113198e-01 2.35856414e-01
1.48272002e+00 -1.15407956e+00 -5.23595214e-01 -3.50331604e-01
7.68502176e-01 -9.65260088e-01 5.80659091e-01 2.83993125e-01
-1.23180151e+00 -6.62481010e-01 -1.02088249e+00 -5.30837774e-01
-8.25651765e-01 4.96049404e-01 4.76240307e-01 5.34960032e-01
-1.63039362e+00 1.10557243e-01 -5.08298993e-01 -3.27020347e-01
8.47709835e-01 3.71209234e-01 -2.99731910e-01 -4.05861177e-02
-8.27853024e-01 8.55124950e-01 6.63823903e-01 1.29033580e-01
-4.75596339e-01 -5.71850777e-01 -8.97879601e-01 -3.72693241e-01
-2.41641074e-01 -9.58396316e-01 1.08335590e+00 -1.07656801e+00
-1.25239480e+00 1.54089272e+00 -3.82190458e-02 -1.19761777e+00
7.26912856e-01 4.60645519e-02 -4.63079363e-01 3.37468565e-01
-2.32732985e-02 1.10056615e+00 1.05048001e+00 -7.76256979e-01
-1.12456119e+00 -3.65818352e-01 -1.15170076e-01 -7.86045045e-02
4.41573620e-01 3.29291858e-02 -7.89418161e-01 -4.01612163e-01
1.26036048e-01 -1.11493909e+00 -9.66282114e-02 -1.16827346e-01
-7.22584784e-01 1.09343089e-01 8.21661830e-01 -9.03917253e-01
1.15997148e+00 -2.10544825e+00 -1.45547256e-01 1.91392824e-01
5.71118355e-01 6.58984601e-01 -8.75987262e-02 -2.59716779e-01
-2.96502948e-01 6.66224584e-02 -1.62662357e-01 -2.33165994e-01
-5.78018785e-01 -8.34123865e-02 1.67341277e-01 3.64266783e-01
4.45987195e-01 1.16830707e+00 -4.35466558e-01 -4.52670217e-01
3.91854972e-01 3.36174726e-01 -5.58460534e-01 1.09241214e-02
-3.19990009e-01 4.75711823e-01 1.70833066e-01 7.52362251e-01
7.79223263e-01 -2.29712024e-01 -5.80962859e-02 -5.95652461e-02
-2.59968787e-01 -6.31219149e-02 -7.57173359e-01 1.36723065e+00
-5.62002584e-02 1.09419751e+00 -3.24409157e-01 -4.10426438e-01
8.38519096e-01 -3.03759221e-02 3.42175245e-01 -8.35665643e-01
3.19665998e-01 2.23389030e-01 4.87808228e-01 -5.90071499e-01
3.75732362e-01 3.41733277e-01 3.18430603e-01 -3.89565118e-02
-9.91522074e-02 -1.25803337e-01 3.91536057e-01 -3.33623171e-01
7.66100109e-01 2.48551697e-01 -1.45834997e-01 -2.74582487e-02
2.96671391e-01 2.11373419e-01 3.90089095e-01 3.88598263e-01
-4.00834143e-01 1.10727584e+00 8.35845351e-01 -8.44111979e-01
-1.33408666e+00 -7.09853411e-01 -4.09792453e-01 2.71070451e-01
-1.15414210e-01 -5.57084344e-02 -1.07476079e+00 -4.97836858e-01
2.89877038e-02 -7.30693489e-02 -1.16172326e+00 2.93954220e-02
-2.56042928e-01 -7.02997386e-01 2.97546923e-01 3.25314552e-01
9.37566936e-01 -9.57147956e-01 -1.09527445e+00 -9.81621891e-02
3.41135979e-01 -9.04489577e-01 -1.74185261e-01 -1.67816117e-01
-7.42853105e-01 -1.70304310e+00 -1.10472512e+00 -1.17130768e+00
8.64113033e-01 -2.75844634e-02 9.08358574e-01 -2.54127920e-01
-8.69563103e-01 -1.68037131e-01 -8.80554169e-02 -9.14144993e-01
-1.57532394e-01 -1.04182269e-02 -3.33110541e-01 3.19214970e-01
6.54383600e-01 -5.60629256e-02 -1.30053139e+00 7.66645670e-02
-7.12152123e-01 2.37991288e-01 7.57189035e-01 7.37304389e-01
8.14213157e-01 -1.62730247e-01 1.11609951e-01 -1.02019536e+00
4.87948447e-01 -1.93058923e-01 -9.95307744e-01 4.42635305e-02
-5.07779658e-01 -3.69582266e-01 -1.16427921e-01 9.71866846e-02
-8.17830861e-01 2.81828284e-01 2.19813839e-01 -4.83752072e-01
-1.42358199e-01 2.66126245e-01 3.35204214e-01 -4.47026730e-01
1.04234254e+00 -3.57423648e-02 6.63709521e-01 -3.40716481e-01
4.18927521e-01 9.97199416e-01 8.03510427e-01 4.89325970e-01
2.62167931e-01 4.53811139e-01 1.89814150e-01 -6.59116268e-01
-7.18474865e-01 -5.36085248e-01 -6.17802978e-01 -3.19042712e-01
1.26607704e+00 -7.98699319e-01 -3.60274822e-01 1.00201356e+00
-8.84677351e-01 -5.00975966e-01 -2.05366731e-01 3.33359689e-01
-4.48731512e-01 -1.33568496e-01 -3.19173515e-01 -3.57384205e-01
-4.52165037e-01 -1.25059927e+00 8.25995624e-01 7.59176016e-01
2.85165012e-01 -8.39923143e-01 -8.73170048e-02 5.64277351e-01
4.01268512e-01 6.71313822e-01 7.37234235e-01 -2.38977954e-01
-5.99784315e-01 -2.99637258e-01 -6.46184444e-01 7.66771078e-01
4.71825860e-02 2.68071830e-01 -1.25482655e+00 -1.43910363e-01
-4.57631916e-01 -4.82364297e-02 1.19684339e+00 1.07528853e+00
1.38599110e+00 4.51160111e-02 -4.35081631e-01 1.07908475e+00
1.35225248e+00 4.30641502e-01 1.31874728e+00 6.61189318e-01
5.95633209e-01 5.83482444e-01 4.00936604e-01 5.25227040e-02
3.99507016e-01 3.23726118e-01 6.03625357e-01 -6.04575396e-01
-7.64181376e-01 2.11185008e-01 -3.29579622e-01 1.00022674e-01
-3.76294136e-01 1.32531941e-01 -1.31723750e+00 8.12162876e-01
-1.53579819e+00 -3.84170145e-01 -4.03038800e-01 2.12933922e+00
7.07637370e-01 7.60207698e-02 2.72950172e-01 -1.78273335e-01
6.80734396e-01 -3.29392612e-01 -6.20928407e-01 -1.92221671e-01
-2.37540200e-01 3.41637999e-01 8.33747327e-01 2.59300113e-01
-1.46938491e+00 9.84566748e-01 7.32812357e+00 1.86801970e-01
-1.70093894e+00 -1.40805975e-01 9.86003995e-01 -2.48492941e-01
2.88370103e-01 -2.04255104e-01 -5.91888428e-01 7.32818425e-01
7.78674960e-01 8.45075622e-02 4.26815860e-02 4.61337745e-01
-7.94081111e-03 -2.92704910e-01 -4.14041936e-01 9.45453763e-01
-1.11921839e-01 -1.63572550e+00 -1.33044347e-01 2.30215326e-01
1.16203451e+00 5.58035910e-01 3.85413647e-01 -1.05931140e-01
2.31774393e-02 -1.13572752e+00 -1.00276627e-01 9.33436036e-01
1.23651242e+00 -5.36146164e-01 8.93697798e-01 -4.24436957e-01
-4.82899696e-01 -1.34403124e-01 -3.66187721e-01 1.49707437e-01
-3.16107363e-01 4.71129656e-01 -1.23696589e+00 2.99306005e-01
8.89655232e-01 7.44104326e-01 -1.02088392e+00 1.88174438e+00
-2.52328306e-01 3.71386558e-01 -2.05776058e-02 4.13767785e-01
2.43344158e-01 -3.43108445e-01 4.36028719e-01 8.95362735e-01
2.94269472e-01 -4.56832796e-01 -2.43986651e-01 6.99822128e-01
-1.50433779e-01 -8.40326995e-02 -6.73960209e-01 4.79848720e-02
1.71191275e-01 1.16601062e+00 -5.03234267e-01 -3.14767182e-01
-3.31214815e-01 7.08318651e-01 -2.65603393e-01 5.54620087e-01
-4.12926376e-01 -8.63665938e-01 6.32894456e-01 5.95704675e-01
2.92653531e-01 1.81922197e-01 -5.94151914e-01 -7.35996783e-01
-1.26353651e-01 -5.66462457e-01 2.59437621e-01 -1.12773478e+00
-5.44341922e-01 7.23537266e-01 -4.29113299e-01 -1.52753615e+00
-4.05765444e-01 -9.89354432e-01 -6.03907287e-01 1.35513651e+00
-1.96593499e+00 -1.46770072e+00 -5.54422021e-01 4.49568629e-01
1.46379754e-01 -7.20825732e-01 4.52940196e-01 1.92765594e-01
-4.41989750e-01 2.62502044e-01 5.55765964e-02 2.46688321e-01
1.01161277e+00 -1.51031482e+00 6.76664412e-01 1.01061118e+00
-5.50840259e-01 3.90530288e-01 2.39446744e-01 -7.63759017e-01
-9.07913208e-01 -1.63726425e+00 6.56306148e-01 -3.38871151e-01
3.33422154e-01 1.24185104e-02 -6.81825280e-01 6.73623919e-01
3.48329693e-01 4.40057486e-01 4.75527585e-01 -3.09880346e-01
4.04661223e-02 8.14733654e-03 -1.09861875e+00 3.96672010e-01
5.52498579e-01 -3.94564092e-01 -2.69540131e-01 5.36473215e-01
4.90103126e-01 -1.06711519e+00 -7.65047729e-01 2.56744087e-01
5.19734383e-01 -1.01025045e+00 6.08018756e-01 -7.40286827e-01
8.67287517e-01 -4.44540083e-01 4.22580063e-01 -1.29080009e+00
7.30785634e-03 -6.85471535e-01 -7.73760751e-02 5.41655183e-01
4.32323247e-01 -8.59338284e-01 9.61043715e-01 3.15298170e-01
-2.67299563e-01 -6.88858271e-01 -6.93552494e-01 -3.60464185e-01
4.91545200e-02 -4.55217734e-02 5.75898051e-01 5.77572823e-01
-6.02343380e-01 2.93017235e-02 -1.88958675e-01 8.22717696e-02
4.68551844e-01 3.65708433e-02 7.50678062e-01 -1.21630168e+00
1.08918980e-01 -4.90826488e-01 -1.08042002e+00 -4.46226895e-01
-5.69073260e-01 -7.74653673e-01 -2.56902695e-01 -1.65300894e+00
-4.40989196e-01 -1.62119046e-01 -2.09131330e-01 5.99131703e-01
2.14880519e-02 8.60077798e-01 -1.90223511e-02 1.20378494e-01
-6.57089353e-02 -2.78689921e-01 1.78494298e+00 -9.76333916e-02
-4.20771956e-01 2.73125827e-01 -6.02734208e-01 6.25765920e-01
1.03141356e+00 1.20818704e-01 -4.92744356e-01 -4.86227512e-01
1.28893152e-01 -2.05143720e-01 6.00596905e-01 -1.40420699e+00
2.86712348e-01 3.22548181e-01 6.31430149e-01 -6.40652359e-01
6.96797520e-02 -2.78801411e-01 -1.36698499e-01 4.89652723e-01
-5.46791824e-03 -4.11449522e-01 5.43176174e-01 2.31198266e-01
-3.89910340e-01 9.58099216e-02 1.13983321e+00 -1.95301473e-01
-9.07274842e-01 2.82250524e-01 3.81840803e-02 -1.23728737e-01
1.34941649e+00 -4.91124034e-01 -6.20959282e-01 4.75455113e-02
-1.05933213e+00 3.51474464e-01 6.14854515e-01 3.41830552e-01
6.17225826e-01 -1.05152476e+00 -7.92858899e-01 7.30149865e-01
2.63801575e-01 3.85453343e-01 3.96958560e-01 8.29491973e-01
-1.11885941e+00 5.65647662e-01 -7.86190212e-01 -7.87785172e-01
-1.40283406e+00 2.44800419e-01 9.93819773e-01 2.84697503e-01
-4.58390325e-01 1.00373220e+00 4.09646481e-02 -1.34928569e-01
1.77846953e-01 -6.15050673e-01 -6.56833708e-01 2.50489116e-01
7.62137830e-01 2.37662852e-01 2.79295832e-01 -2.58630842e-01
2.53128372e-02 6.33303881e-01 -3.02141279e-01 8.77982229e-02
1.09655368e+00 -5.78740016e-02 -4.52395052e-01 -5.06272316e-02
9.45900381e-01 -5.18656969e-01 -1.32263494e+00 -1.52350277e-01
-2.14986935e-01 -4.02484775e-01 4.20054644e-01 -1.28569448e+00
-1.21681333e+00 9.94916320e-01 1.41874218e+00 3.22228044e-01
1.51868641e+00 -2.85182238e-01 5.72734356e-01 -2.45361581e-01
4.57103960e-02 -1.11557043e+00 -4.17265981e-01 3.20067167e-01
8.63952100e-01 -1.42949653e+00 -2.76801139e-01 -2.80698121e-01
-5.93024790e-01 1.17468679e+00 7.74809003e-01 -8.30890164e-02
5.21972179e-01 -1.25653863e-01 6.23885155e-01 -2.96176553e-01
-4.55548465e-01 -7.12749898e-01 9.28332746e-01 9.10611331e-01
2.00172290e-01 1.01659082e-01 -3.30633551e-01 1.19512871e-01
-2.79265851e-01 4.21331376e-01 6.99760079e-01 9.18037236e-01
-3.53514642e-01 -9.66769040e-01 -1.88008025e-01 9.98566628e-01
-6.27472639e-01 -1.25704750e-01 -5.41093171e-01 7.05946624e-01
7.04781830e-01 4.65176880e-01 4.04584259e-01 -4.20733005e-01
3.45881805e-02 2.84257475e-02 3.40616554e-01 -7.11344957e-01
-4.44488883e-01 2.28541374e-01 1.34784132e-01 -6.43023610e-01
-3.48286957e-01 -3.94002974e-01 -8.63314748e-01 2.08527610e-01
2.83279598e-01 -4.16401416e-01 9.08936083e-01 5.83796501e-01
8.19955051e-01 8.49874973e-01 4.50746477e-01 -6.71965301e-01
1.67470589e-01 -1.23260462e+00 -6.22740567e-01 1.92595154e-01
6.83716774e-01 -4.68712002e-01 -3.05481348e-02 4.51860696e-01] | [15.81045150756836, -3.985072612762451] |
93794d28-18f3-4b4b-96c6-c069fd7f47bb | text-is-text-no-matter-what-unifying-text | 2107.12087 | null | https://arxiv.org/abs/2107.12087v2 | https://arxiv.org/pdf/2107.12087v2.pdf | Text is Text, No Matter What: Unifying Text Recognition using Knowledge Distillation | Text recognition remains a fundamental and extensively researched topic in computer vision, largely owing to its wide array of commercial applications. The challenging nature of the very problem however dictated a fragmentation of research efforts: Scene Text Recognition (STR) that deals with text in everyday scenes, and Handwriting Text Recognition (HTR) that tackles hand-written text. In this paper, for the first time, we argue for their unification -- we aim for a single model that can compete favourably with two separate state-of-the-art STR and HTR models. We first show that cross-utilisation of STR and HTR models trigger significant performance drops due to differences in their inherent challenges. We then tackle their union by introducing a knowledge distillation (KD) based framework. This is however non-trivial, largely due to the variable-length and sequential nature of text sequences, which renders off-the-shelf KD techniques that mostly works with global fixed-length data inadequate. For that, we propose three distillation losses all of which are specifically designed to cope with the aforementioned unique characteristics of text recognition. Empirical evidence suggests that our proposed unified model performs on par with individual models, even surpassing them in certain cases. Ablative studies demonstrate that naive baselines such as a two-stage framework, and domain adaption/generalisation alternatives do not work as well, further verifying the appropriateness of our design. | ['Yi-Zhe Song', 'Pinaki Nath Chowdhury', 'Aneeshan Sain', 'Ayan Kumar Bhunia'] | 2021-07-26 | null | http://openaccess.thecvf.com//content/ICCV2021/html/Bhunia_Text_Is_Text_No_Matter_What_Unifying_Text_Recognition_Using_ICCV_2021_paper.html | http://openaccess.thecvf.com//content/ICCV2021/papers/Bhunia_Text_Is_Text_No_Matter_What_Unifying_Text_Recognition_Using_ICCV_2021_paper.pdf | iccv-2021-1 | ['scene-text-recognition', 'handwriting-recognition'] | ['computer-vision', 'computer-vision'] | [ 5.94007254e-01 -2.95039713e-01 -7.27100298e-02 -2.24724114e-01
-5.60021281e-01 -6.96799397e-01 1.05715513e+00 -9.32637602e-02
-6.66060686e-01 5.14996290e-01 1.00303337e-01 -4.05551553e-01
-2.60883272e-01 -2.45693743e-01 -4.48529720e-01 -7.05992460e-01
4.39632177e-01 6.42757535e-01 4.82331902e-01 -3.08016658e-01
5.52940428e-01 6.16133749e-01 -1.67548692e+00 4.18947071e-01
7.01074898e-01 7.90951848e-01 3.12053472e-01 8.67057085e-01
-4.11893219e-01 8.12757134e-01 -5.17354846e-01 -5.81295967e-01
2.22402573e-01 -3.17698807e-01 -7.45077252e-01 4.80023533e-01
5.42796850e-01 -2.02889740e-01 -5.12847185e-01 6.23091161e-01
5.24306595e-01 -7.70703703e-02 7.34102011e-01 -8.56977046e-01
-6.01700306e-01 3.36996138e-01 -5.03039122e-01 1.25461608e-01
4.08393383e-01 8.17871839e-02 9.22330141e-01 -8.27135026e-01
7.15695739e-01 9.29915130e-01 9.08970535e-01 4.78913188e-01
-1.10547721e+00 -7.00004101e-02 2.19781607e-01 1.24600619e-01
-1.23162115e+00 -6.81419075e-01 6.01161838e-01 -4.72652763e-01
1.39915299e+00 4.56466556e-01 1.91335067e-01 1.42380357e+00
7.82871619e-02 1.19863594e+00 1.16057396e+00 -8.20852101e-01
1.06116481e-01 1.42370090e-01 1.69679686e-01 4.23755318e-01
2.80563563e-01 -1.43653229e-01 -6.22634590e-01 2.03371152e-01
6.06283426e-01 -2.04660356e-01 -3.58549595e-01 -4.29850906e-01
-1.31677270e+00 5.63261330e-01 -3.56078744e-01 6.86464608e-01
-2.53497273e-01 -3.84579897e-01 7.06655562e-01 4.87254292e-01
2.30769128e-01 3.95608634e-01 -3.91596943e-01 -5.42024612e-01
-1.50841403e+00 2.41636217e-01 1.03694010e+00 8.83757353e-01
4.25401449e-01 1.23681359e-01 -1.27969205e-01 1.00688338e+00
6.62262589e-02 3.22390497e-01 7.84442067e-01 -2.94048488e-01
6.71136796e-01 5.21785140e-01 -1.46113977e-01 -8.93121064e-01
-2.44610727e-01 -2.33026803e-01 -8.27097356e-01 -3.25746983e-02
6.28166914e-01 1.12754926e-01 -1.04047060e+00 1.07835460e+00
-7.75074959e-02 -6.47469833e-02 7.26302490e-02 8.53875816e-01
3.66377711e-01 3.94069433e-01 -2.05164358e-01 -2.15942904e-01
1.20185602e+00 -1.10035455e+00 -6.54838204e-01 -4.46950376e-01
6.71296060e-01 -9.28801835e-01 1.05194426e+00 7.96830416e-01
-8.22752535e-01 -3.93074512e-01 -1.10434341e+00 -1.61236703e-01
-5.56822717e-01 3.32242697e-01 3.36067736e-01 9.65014338e-01
-1.07357728e+00 4.85314250e-01 -7.54510462e-01 -7.95048773e-01
1.83464393e-01 3.33409131e-01 -3.67739141e-01 -4.69023436e-02
-7.69722402e-01 1.05410981e+00 3.36296678e-01 1.46447808e-01
-2.85112649e-01 -3.16380024e-01 -4.93491024e-01 -2.31327474e-01
6.77989960e-01 -4.08143491e-01 1.20261681e+00 -1.09129512e+00
-1.70367706e+00 1.09264457e+00 -8.59734863e-02 -6.61589861e-01
1.09336424e+00 -4.38869357e-01 -4.57354665e-01 7.87742063e-02
-2.69990236e-01 3.19795936e-01 1.19326806e+00 -1.03658760e+00
-5.84193349e-01 -4.15700406e-01 -2.31441602e-01 3.38901609e-01
-4.94788319e-01 1.25556946e-01 -7.34174728e-01 -9.12708819e-01
-1.03370152e-01 -8.22102785e-01 -5.58232814e-02 -2.69689500e-01
-4.03252959e-01 -4.08802778e-02 1.02837479e+00 -5.78456640e-01
1.42813158e+00 -2.09709263e+00 1.59649655e-01 -1.37438133e-01
-6.42230883e-02 6.55308604e-01 -1.49661452e-01 8.67413580e-01
5.06594367e-02 -8.09059739e-02 -2.82643259e-01 -4.50852871e-01
1.67916089e-01 3.64345074e-01 -6.49202108e-01 5.91210306e-01
2.71705776e-01 8.84745836e-01 -4.84163135e-01 -3.76659662e-01
4.42364603e-01 3.89130771e-01 -1.77255198e-01 -1.91338032e-01
-3.77134174e-01 1.34301022e-01 -4.48597908e-01 5.73688388e-01
5.27458727e-01 -9.35420468e-02 1.58507645e-01 1.50056444e-02
-3.65135044e-01 9.99975875e-02 -1.36868048e+00 1.66030777e+00
4.20716911e-04 8.20778430e-01 -4.86526750e-02 -1.26377022e+00
9.12595093e-01 2.28668481e-01 2.86461413e-01 -7.07809031e-01
1.19156092e-01 4.47215229e-01 -1.09266266e-01 -6.34430170e-01
9.18587983e-01 -5.98243624e-02 1.62096053e-01 2.88169116e-01
-4.53162752e-02 5.01909181e-02 3.03738266e-01 -1.37631238e-01
1.19409561e+00 4.17837024e-01 4.30532724e-01 -1.22530818e-01
7.52079308e-01 1.07656188e-01 2.18128040e-02 1.14804018e+00
-2.72631764e-01 9.15158510e-01 3.89751434e-01 -3.15256476e-01
-1.19734240e+00 -5.62899649e-01 -2.08652899e-01 1.07380295e+00
-1.29023409e-02 -3.03291798e-01 -6.58656359e-01 -7.52928495e-01
-5.60798906e-02 5.73105335e-01 -5.61299562e-01 3.17951053e-01
-6.52122617e-01 -7.79632211e-01 9.06494796e-01 3.81638169e-01
6.28479183e-01 -9.19937253e-01 -8.99352491e-01 2.93250382e-01
1.81963742e-01 -1.41048753e+00 -1.55198157e-01 2.93776870e-01
-8.27565193e-01 -8.61987472e-01 -1.12220550e+00 -4.52370971e-01
2.35503197e-01 3.71275991e-01 8.61877024e-01 -1.08777776e-01
-3.17064017e-01 6.31498277e-01 -7.71036386e-01 -1.90881491e-01
-5.67485690e-01 2.68485725e-01 -1.10822901e-01 1.96281075e-01
5.71086109e-01 -2.94498444e-01 -2.46041298e-01 3.78189981e-01
-1.17477512e+00 6.81332946e-02 9.56597626e-01 7.38736093e-01
1.29111022e-01 -7.55281420e-03 3.31456065e-01 -9.80746150e-01
6.96534872e-01 -6.53141662e-02 -3.59055370e-01 6.03564858e-01
-6.57695115e-01 -3.17758471e-02 6.24968231e-01 -5.88958621e-01
-9.61286962e-01 1.14370108e-01 -1.19553857e-01 -5.12345612e-01
-6.71884179e-01 5.68983614e-01 9.37765390e-02 -1.77887548e-02
7.24231958e-01 8.24464917e-01 -4.12268415e-02 -5.50391495e-01
2.61944026e-01 9.71194267e-01 6.05817080e-01 -5.91746092e-01
7.28126287e-01 4.36631680e-01 -1.51190981e-01 -1.35971475e+00
-5.14119387e-01 -6.27350867e-01 -8.56314301e-01 4.86424342e-02
6.20576322e-01 -6.08783185e-01 -3.95415664e-01 8.14789474e-01
-1.01349640e+00 -3.74523431e-01 -1.18177839e-01 2.18390346e-01
-7.11842179e-01 1.01849413e+00 -4.66373652e-01 -9.76708531e-01
-1.23006716e-01 -1.03474128e+00 1.29103065e+00 -1.32080376e-01
-5.18452786e-02 -1.04845917e+00 6.09206893e-02 4.69317555e-01
4.62426394e-01 -1.22922054e-02 6.19811058e-01 -1.10109055e+00
-2.98499376e-01 -3.52605283e-01 -4.02404636e-01 3.57793957e-01
-2.90494668e-03 8.62519443e-02 -1.10878193e+00 -3.52881312e-01
6.03942722e-02 -2.88555056e-01 9.66899037e-01 1.45350054e-01
7.07375765e-01 2.92037684e-03 -7.79551119e-02 2.98441678e-01
1.45571649e+00 1.38429940e-01 7.89650559e-01 7.10538864e-01
5.96423566e-01 7.34201431e-01 4.48045462e-01 5.33659935e-01
2.77112007e-01 8.38640094e-01 2.78507005e-02 1.80765428e-02
-1.91915721e-01 2.03574263e-02 4.88732487e-01 7.26041615e-01
-5.83636500e-02 -5.11290312e-01 -1.29616117e+00 4.96890962e-01
-2.12911391e+00 -9.67653513e-01 -3.87054592e-01 2.20484972e+00
6.36565268e-01 2.73307472e-01 2.60804534e-01 4.73467082e-01
5.09700060e-01 2.20548809e-01 -3.53636861e-01 -4.46456909e-01
-4.85925138e-01 5.13198711e-02 5.70382833e-01 1.96247384e-01
-1.14982283e+00 1.02972960e+00 6.42504978e+00 1.07202542e+00
-1.33211684e+00 -2.16922909e-01 2.93187618e-01 1.65704310e-01
2.76035726e-01 -1.16635114e-01 -9.15502548e-01 3.68614733e-01
9.28644180e-01 -2.15593893e-02 4.30482745e-01 5.02100587e-01
1.30360112e-01 -2.04879969e-01 -1.17403758e+00 1.18231845e+00
4.63972688e-01 -1.31518173e+00 2.49850750e-01 1.11881055e-01
5.28681755e-01 1.10489875e-01 4.23901305e-02 3.00797671e-01
-6.14303872e-02 -8.89132202e-01 8.76581371e-01 3.99420321e-01
5.57693303e-01 -2.25721896e-01 6.23466432e-01 5.12567163e-01
-9.90891159e-01 2.00466737e-02 -1.80846244e-01 -1.21122360e-01
-8.97338688e-02 3.83773774e-01 -7.49442399e-01 1.01921821e+00
3.24049056e-01 7.35078573e-01 -8.65187466e-01 8.60199809e-01
1.69744939e-01 5.56288838e-01 -3.50299209e-01 6.46020323e-02
5.30162096e-01 -2.22112108e-02 6.11738741e-01 1.79146707e+00
8.04240480e-02 -2.79907435e-01 1.21944755e-01 4.29080635e-01
2.16702566e-01 3.07179481e-01 -6.99440122e-01 -2.59838462e-01
1.59807205e-01 9.16774035e-01 -9.61445689e-01 -3.52127016e-01
-7.59090304e-01 1.32592666e+00 1.86817363e-01 3.72063518e-01
-6.29697800e-01 -2.50114113e-01 1.11255497e-01 -7.91132972e-02
7.36055851e-01 -3.39261472e-01 -5.43598235e-01 -1.54345155e+00
3.08256030e-01 -1.21168578e+00 3.19485992e-01 -4.51620936e-01
-1.36651194e+00 5.96442938e-01 -1.55495465e-01 -1.10633540e+00
-3.63998055e-01 -7.66721010e-01 -1.90159306e-01 7.38649905e-01
-1.76784384e+00 -1.25019002e+00 -9.80466604e-02 6.06769204e-01
1.07633913e+00 -1.92365378e-01 6.22075438e-01 1.82871222e-01
-6.41825795e-01 7.00958371e-01 4.33644176e-01 8.55517387e-02
7.91396558e-01 -1.19112945e+00 5.72374344e-01 1.05332196e+00
4.09599513e-01 4.71869051e-01 8.22605014e-01 -6.36280596e-01
-1.81373572e+00 -8.28224242e-01 9.89159882e-01 -6.72546089e-01
8.49370003e-01 -4.79124546e-01 -1.14349282e+00 4.60716993e-01
9.00814012e-02 -2.72005469e-01 3.62893313e-01 6.23454712e-03
-5.16278267e-01 2.92886466e-01 -7.84016132e-01 7.16077149e-01
8.89483333e-01 -5.31348765e-01 -8.70003045e-01 1.49607688e-01
8.59363601e-02 -3.18555415e-01 -5.38446844e-01 2.90711790e-01
5.91826618e-01 -1.29854870e+00 7.43700266e-01 -3.05231631e-01
4.95042920e-01 -1.01594158e-01 -3.84817243e-01 -5.53012431e-01
7.24650323e-02 -7.45279908e-01 -7.84249082e-02 1.34952307e+00
1.43563509e-01 -6.75821126e-01 9.10804331e-01 4.83884692e-01
-8.45559016e-02 -5.29379606e-01 -9.89534378e-01 -1.16327310e+00
1.14048667e-01 -6.34304762e-01 5.24895638e-02 1.17321682e+00
-1.60985529e-01 4.04245973e-01 -4.98251170e-01 -8.89495239e-02
2.73001403e-01 -4.67705727e-02 9.33041155e-01 -1.16557193e+00
-4.16430384e-01 -8.05741191e-01 -5.79448998e-01 -1.32130241e+00
-7.32732713e-02 -6.19499624e-01 6.04723841e-02 -1.33697629e+00
1.90871097e-02 -1.65848970e-01 9.71245114e-03 4.46695685e-01
9.94088948e-02 2.20360413e-01 3.50372732e-01 4.46624964e-01
-5.96985459e-01 3.79717290e-01 8.03070128e-01 2.52404623e-02
-2.72688240e-01 -2.94520974e-01 -3.59413445e-01 5.83578408e-01
5.09856522e-01 -5.79542331e-02 -4.06481415e-01 -5.52385509e-01
8.82521570e-02 -7.77825043e-02 3.57688814e-01 -1.06402302e+00
5.19362569e-01 -4.76874188e-02 7.30883703e-02 -5.81933498e-01
1.38881207e-01 -8.88882220e-01 -4.25545909e-02 1.41055197e-01
-3.03608268e-01 -1.37065172e-01 3.08595687e-01 6.27732575e-01
-2.03574926e-01 -4.12257552e-01 5.90732932e-01 5.42402416e-02
-8.13240290e-01 -6.02085330e-02 -5.65560341e-01 -5.84484860e-02
9.43439484e-01 -1.03424692e+00 -3.32576424e-01 -1.52340800e-01
-3.77368569e-01 -1.05940297e-01 6.29268050e-01 7.58680463e-01
3.96866113e-01 -6.38299286e-01 -8.16457450e-01 2.05770850e-01
1.63712978e-01 -2.30830491e-01 2.39920691e-01 1.04468381e+00
-5.10925651e-01 8.05852652e-01 1.38851320e-02 -7.44525433e-01
-1.27298498e+00 5.75094461e-01 1.25511095e-01 -5.19578636e-01
-8.85384142e-01 4.21282738e-01 1.23891674e-01 -1.72393084e-01
4.38242376e-01 -9.75088105e-02 -1.21057602e-02 1.74551606e-01
4.34901863e-01 3.89338106e-01 4.75040764e-01 -6.71732187e-01
-3.06803674e-01 6.61796153e-01 -4.48856235e-01 -1.53611332e-01
1.22789288e+00 -2.22857744e-01 2.28838027e-01 5.68180799e-01
7.22533464e-01 -1.84905112e-01 -1.23273802e+00 -2.83587992e-01
5.05197525e-01 -4.61575866e-01 4.16523963e-02 -9.77730632e-01
-4.75458890e-01 8.52466702e-01 3.93569857e-01 3.10743004e-01
1.19019175e+00 -3.94184172e-01 5.54430723e-01 6.50359035e-01
2.22162113e-01 -1.17829216e+00 -7.62579739e-02 6.94730759e-01
7.62998998e-01 -1.12123179e+00 8.56218413e-02 -2.58896291e-01
-7.55693436e-01 1.38686931e+00 1.93415463e-01 -2.72555985e-02
8.87896121e-02 4.03265476e-01 4.93393093e-02 -1.06681779e-03
-8.37396383e-01 -4.06706393e-01 2.54453778e-01 5.91298580e-01
4.29107249e-01 -4.49190259e-01 -3.52483481e-01 2.66482979e-01
8.35543498e-02 2.44988620e-01 4.88884240e-01 1.27890909e+00
-4.34267610e-01 -1.29744399e+00 -4.86483037e-01 3.73578697e-01
-4.76341993e-01 -7.20514581e-02 -6.96055174e-01 1.08338296e+00
-1.92430422e-01 8.87609482e-01 -2.27845669e-01 -2.99094021e-01
4.67590123e-01 4.31126714e-01 5.87668955e-01 -3.76640260e-01
-8.46517265e-01 3.51421773e-01 7.02468455e-02 -1.34406865e-01
-4.91445601e-01 -8.57393503e-01 -7.34617531e-01 -2.78705388e-01
-3.77113104e-01 -3.46674085e-01 7.44852602e-01 1.15431380e+00
3.27164233e-01 1.95541322e-01 3.50372970e-01 -8.92212868e-01
-8.94977808e-01 -8.12229156e-01 -5.29943764e-01 3.70812088e-01
3.74380052e-01 -4.04184490e-01 -1.43658102e-01 4.36479628e-01] | [11.83598518371582, 2.4036309719085693] |
506979c9-2678-4828-a95d-5169f7b414cf | deep-packgen-a-deep-reinforcement-learning | 2305.11039 | null | https://arxiv.org/abs/2305.11039v1 | https://arxiv.org/pdf/2305.11039v1.pdf | Deep PackGen: A Deep Reinforcement Learning Framework for Adversarial Network Packet Generation | Recent advancements in artificial intelligence (AI) and machine learning (ML) algorithms, coupled with the availability of faster computing infrastructure, have enhanced the security posture of cybersecurity operations centers (defenders) through the development of ML-aided network intrusion detection systems (NIDS). Concurrently, the abilities of adversaries to evade security have also increased with the support of AI/ML models. Therefore, defenders need to proactively prepare for evasion attacks that exploit the detection mechanisms of NIDS. Recent studies have found that the perturbation of flow-based and packet-based features can deceive ML models, but these approaches have limitations. Perturbations made to the flow-based features are difficult to reverse-engineer, while samples generated with perturbations to the packet-based features are not playable. Our methodological framework, Deep PackGen, employs deep reinforcement learning to generate adversarial packets and aims to overcome the limitations of approaches in the literature. By taking raw malicious network packets as inputs and systematically making perturbations on them, Deep PackGen camouflages them as benign packets while still maintaining their functionality. In our experiments, using publicly available data, Deep PackGen achieved an average adversarial success rate of 66.4\% against various ML models and across different attack types. Our investigation also revealed that more than 45\% of the successful adversarial samples were out-of-distribution packets that evaded the decision boundaries of the classifiers. The knowledge gained from our study on the adversary's ability to make specific evasive perturbations to different types of malicious packets can help defenders enhance the robustness of their NIDS against evolving adversarial attacks. | ['Nathaniel D. Bastian', 'Tapas K. Das', 'Ankit Shah', 'Diwas Paudel', 'Jalal Ghadermazi', 'Soumyadeep Hore'] | 2023-05-18 | null | null | null | null | ['network-intrusion-detection'] | ['miscellaneous'] | [ 2.23114341e-01 -1.21560045e-01 -2.11536303e-01 1.44152135e-01
-1.92277536e-01 -1.11978197e+00 7.01462030e-01 -1.18844375e-01
-3.59844536e-01 6.65813506e-01 -4.57311124e-01 -9.81046915e-01
-1.42699759e-02 -1.01742303e+00 -7.73103178e-01 -7.69480944e-01
-4.56070632e-01 2.38256499e-01 1.98504746e-01 -5.38076282e-01
5.59606493e-01 1.12892175e+00 -1.15675926e+00 3.57697397e-01
5.21148086e-01 9.66923892e-01 -6.74457848e-01 1.03581810e+00
-5.27502969e-02 7.86499202e-01 -1.31821132e+00 -4.71732646e-01
8.04447591e-01 -2.87754565e-01 -3.89511973e-01 -4.47159559e-01
7.60637894e-02 -4.19937909e-01 -6.86637700e-01 1.05577886e+00
2.86282241e-01 -2.46978283e-01 2.66909599e-01 -1.75499797e+00
-4.68741387e-01 4.10116106e-01 -3.18661302e-01 5.92060328e-01
2.13319749e-01 8.57095540e-01 6.32905364e-01 -5.80973700e-02
4.30232137e-01 1.39464164e+00 4.44912940e-01 9.60739017e-01
-1.17281330e+00 -1.20830846e+00 -8.81342590e-03 -2.25528777e-02
-7.63737082e-01 -5.01666546e-01 8.24582577e-01 -2.08133772e-01
7.53078222e-01 4.17401463e-01 4.40313220e-01 1.61173356e+00
7.56117761e-01 3.78997058e-01 9.91621852e-01 -2.65192211e-01
3.67630243e-01 2.71140128e-01 -3.52264851e-01 5.53892195e-01
5.69227040e-01 1.09150314e+00 9.90057364e-02 -5.99154115e-01
6.78857148e-01 6.24457113e-02 -6.73345253e-02 -2.40775384e-02
-5.14696002e-01 1.22426558e+00 5.70944011e-01 1.49672702e-01
-4.45082337e-01 -6.67429492e-02 5.27853072e-01 5.73681474e-01
6.45508021e-02 1.24194002e+00 -5.73161542e-01 -2.99505517e-02
-1.94588184e-01 7.97905475e-02 1.16211867e+00 3.58654261e-01
4.23018396e-01 7.96973884e-01 6.61959499e-02 8.47122148e-02
5.35281524e-02 6.87981844e-01 2.38672346e-01 -6.36160195e-01
2.07693696e-01 6.11608505e-01 -1.46737322e-01 -1.39735281e+00
-2.25032955e-01 -4.75713015e-01 -5.95244706e-01 6.69457257e-01
5.98176122e-01 -6.59770608e-01 -9.01372433e-01 1.63617206e+00
2.88817018e-01 2.99699664e-01 3.01390767e-01 4.62011755e-01
-1.73659511e-02 5.64275682e-01 3.58623236e-01 5.08598424e-02
9.91740525e-01 -3.75245035e-01 -1.71034992e-01 -2.88088143e-01
4.51288313e-01 -4.83135730e-01 6.96500599e-01 2.45738715e-01
-6.19270623e-01 -2.81868875e-01 -1.20104134e+00 1.32222223e+00
-8.23093891e-01 -9.38641131e-01 7.41056859e-01 1.34176064e+00
-7.66118228e-01 5.12613714e-01 -6.05212331e-01 5.72937988e-02
7.22120285e-01 5.85323393e-01 -2.46295452e-01 7.75236785e-02
-1.49735618e+00 8.04292500e-01 1.88228026e-01 -1.92904159e-01
-1.32819593e+00 -7.91932225e-01 -6.29551113e-01 2.43176762e-02
4.46571320e-01 -2.89485335e-01 7.35381186e-01 -1.19474030e+00
-1.28587496e+00 3.89240712e-01 5.74898124e-01 -8.62748444e-01
4.43037987e-01 2.18839496e-01 -9.48029220e-01 3.84054601e-01
-2.84019768e-01 3.05336326e-01 1.27498949e+00 -1.38041055e+00
-5.14859319e-01 -1.66453764e-01 4.31155324e-01 -4.22405630e-01
-4.21154410e-01 1.79708138e-01 5.89096785e-01 -6.97623432e-01
-5.91046095e-01 -9.52552021e-01 -3.59965205e-01 -2.26390213e-01
-4.70515907e-01 3.21689010e-01 1.32034242e+00 -2.20346123e-01
8.61874521e-01 -2.05324364e+00 -2.16243431e-01 5.80895245e-01
3.46216500e-01 1.09491992e+00 -3.39802146e-01 5.23754656e-01
-1.50207654e-01 6.91620350e-01 9.65565890e-02 4.23369944e-01
-1.55665010e-01 2.79148668e-01 -8.30994010e-01 3.95144016e-01
4.27139610e-01 6.82927907e-01 -7.89925396e-01 7.46419802e-02
3.01550567e-01 1.55061468e-01 -7.30091333e-01 4.75258410e-01
-2.39948288e-01 4.67331439e-01 -5.69932520e-01 8.85575473e-01
5.83305240e-01 2.63482958e-01 6.26372471e-02 3.05251628e-01
2.75600910e-01 -1.23024262e-01 -4.85156715e-01 2.97965795e-01
-2.09077239e-01 3.89162868e-01 2.04491630e-01 -9.65591013e-01
8.44099343e-01 1.50477096e-01 4.01203156e-01 -8.91562343e-01
4.15406018e-01 6.61207661e-02 6.43917203e-01 -2.66923875e-01
-1.07229076e-01 -2.28217185e-01 -2.26165399e-01 6.45434499e-01
-1.80479541e-01 6.27426729e-02 -6.09165579e-02 1.56202018e-01
1.63924193e+00 -7.27349460e-01 -3.28271487e-03 1.13799237e-02
6.68790996e-01 7.06700012e-02 5.59343576e-01 1.26531529e+00
-6.35900319e-01 -4.03022200e-01 7.80499458e-01 -7.79477239e-01
-9.85565841e-01 -1.39067233e+00 1.19902462e-01 9.51505661e-01
-5.53870834e-02 -6.35894910e-02 -7.58327544e-01 -1.19011903e+00
2.40963563e-01 8.62873971e-01 -6.66601479e-01 -1.04067230e+00
-6.52789891e-01 -7.81357408e-01 1.38519859e+00 2.78526366e-01
5.16129732e-01 -1.33197916e+00 -5.36071181e-01 2.74776697e-01
5.79899549e-01 -1.17822397e+00 4.39540520e-02 8.46533701e-02
-4.69210416e-01 -1.59308338e+00 1.62074894e-01 -2.81273603e-01
6.83937252e-01 1.22474451e-02 6.96977794e-01 5.67084312e-01
-7.23698974e-01 3.64073157e-01 -5.38572311e-01 -7.07447886e-01
-1.11847496e+00 -1.18747748e-01 4.79763001e-01 -4.82215965e-03
2.68595159e-01 -5.70233107e-01 -1.83806047e-01 4.19883668e-01
-1.27371573e+00 -8.24415445e-01 7.42323935e-01 8.66777480e-01
-2.28841975e-01 4.83894825e-01 9.23070252e-01 -1.09981930e+00
8.54712069e-01 -7.52989173e-01 -7.51299620e-01 8.85613486e-02
-5.67184389e-01 7.96090737e-02 1.36422193e+00 -8.95145655e-01
-6.01128578e-01 -5.91211200e-01 -1.88378468e-01 -6.73497021e-01
-3.83185863e-01 -9.98459011e-02 -2.52612174e-01 -7.08410203e-01
9.36114132e-01 2.49128923e-01 3.93286616e-01 1.18171260e-01
1.76223554e-02 3.15136611e-01 1.58104062e-01 -8.23970735e-01
1.47420192e+00 2.99772471e-01 1.76260754e-01 -8.10741186e-01
-4.73888963e-01 3.03661734e-01 -2.50181998e-04 -2.18353480e-01
3.28154236e-01 -1.02535360e-01 -1.02206540e+00 7.02187955e-01
-8.55266929e-01 -2.45447010e-01 -1.01456396e-01 -2.34733522e-02
-1.43797711e-01 2.36997083e-01 -7.61970699e-01 -8.19332242e-01
-3.46166372e-01 -1.21714163e+00 1.94420576e-01 3.27254474e-01
-3.08920606e-03 -1.03805327e+00 2.53388081e-02 2.55713165e-01
1.01529586e+00 6.11685276e-01 1.27220595e+00 -1.37933159e+00
-4.81125295e-01 -8.02077293e-01 9.52594504e-02 5.78948975e-01
1.58783302e-01 2.96395659e-01 -8.27646613e-01 -4.98550564e-01
1.52626455e-01 -2.25360394e-01 2.24884465e-01 -6.96738288e-02
1.11681342e+00 -8.53631556e-01 -2.46003896e-01 7.38140941e-01
1.13351262e+00 8.82863283e-01 7.07019508e-01 5.41797698e-01
4.49968636e-01 5.40795684e-01 2.85126776e-01 4.67889100e-01
-4.25447881e-01 1.68496281e-01 8.71558726e-01 -6.19488172e-02
4.14314896e-01 -1.55901462e-01 5.19197583e-01 -2.24317417e-01
2.63785094e-01 -4.48892236e-01 -7.65016139e-01 -2.21815959e-01
-1.07139719e+00 -1.31893623e+00 5.01343489e-01 1.96878505e+00
5.06269932e-01 8.21704149e-01 2.11289555e-01 2.49481663e-01
6.47283673e-01 1.75283134e-01 -8.47154796e-01 -8.36764574e-01
-5.14479503e-02 5.45709670e-01 7.38712251e-01 4.49914783e-01
-1.13753736e+00 1.22187555e+00 6.65888214e+00 5.84703684e-01
-1.26978123e+00 -4.52821195e-01 6.51308835e-01 5.02085350e-02
-6.06777593e-02 2.94644516e-02 -6.84798777e-01 5.92256188e-01
1.40283644e+00 -2.51097888e-01 7.83864141e-01 8.43277872e-01
9.77861583e-02 3.10336888e-01 -7.81732619e-01 1.81114659e-01
-4.86257896e-02 -1.46446669e+00 2.76676655e-01 3.02140623e-01
2.96037048e-01 -2.74181962e-01 4.70376700e-01 7.17657089e-01
7.88896739e-01 -1.22068465e+00 1.30869865e-01 1.91539705e-01
3.58856082e-01 -1.17584848e+00 8.20351362e-01 3.06842566e-01
-6.49907589e-01 -5.94641387e-01 -1.52797386e-01 -1.35250807e-01
-2.24381223e-01 1.18239716e-01 -1.15633070e+00 9.59747285e-02
4.01499152e-01 9.76596400e-02 -6.39854908e-01 4.00235742e-01
-1.70055449e-01 8.71134996e-01 -1.23910829e-01 -6.23755716e-02
4.76134598e-01 1.52118310e-01 8.30384016e-01 8.19935024e-01
-4.14910495e-01 5.61192594e-02 3.73217165e-01 8.31218839e-01
-2.85957847e-03 -4.84337807e-01 -8.99571478e-01 -6.61185145e-01
7.14649498e-01 1.15097463e+00 -4.93329495e-01 -5.07601127e-02
7.73415640e-02 5.00316262e-01 2.43056635e-03 3.53161365e-01
-1.02303219e+00 -6.62928283e-01 1.36959863e+00 1.11820437e-01
-8.88120830e-02 -1.22837432e-01 -1.01248458e-01 -8.73131931e-01
-4.39147621e-01 -1.52324009e+00 4.72404867e-01 4.52588918e-03
-1.61465335e+00 8.89508665e-01 -2.38959596e-01 -8.39965105e-01
-3.92891318e-01 -7.63372362e-01 -9.08337772e-01 5.85580111e-01
-1.22348559e+00 -8.92567098e-01 1.76280349e-01 7.97995269e-01
2.55881876e-01 -8.03702533e-01 8.71630967e-01 -3.92463617e-02
-8.98476005e-01 9.73806500e-01 -2.35889554e-01 6.83358014e-01
3.11394811e-01 -7.04652011e-01 5.54433227e-01 1.14494288e+00
-2.57630408e-01 6.89326584e-01 7.05325365e-01 -7.99651086e-01
-1.66403973e+00 -9.00776565e-01 -7.09626600e-02 -4.51630592e-01
1.07762516e+00 -3.66085231e-01 -7.75072992e-01 6.16742730e-01
-1.72849998e-01 9.17758122e-02 7.57797956e-01 -3.28062773e-01
-7.45282888e-01 1.12496479e-03 -1.71004629e+00 8.88106704e-01
6.44800782e-01 -4.65792626e-01 -1.86548039e-01 1.58531651e-01
8.51984978e-01 5.22023663e-02 -4.96471047e-01 3.68205816e-01
3.05161506e-01 -8.95798326e-01 1.30480957e+00 -1.43763435e+00
6.34052232e-02 3.39086764e-02 -2.02399775e-01 -1.20561242e+00
-1.41639739e-01 -7.28356540e-01 -3.28290313e-01 9.46041822e-01
1.99938476e-01 -1.21836066e+00 8.59335244e-01 4.80058014e-01
1.05306342e-01 -6.47138238e-01 -8.28529418e-01 -8.89534771e-01
3.26479346e-01 -2.75288880e-01 5.54543138e-01 9.17169452e-01
-1.66632250e-01 -2.55760044e-01 -2.90919036e-01 4.88430858e-01
7.95991898e-01 -4.61675465e-01 8.26114893e-01 -1.04189837e+00
-4.31743264e-01 -6.60345197e-01 -6.75356567e-01 1.34864869e-02
5.68614423e-01 -6.66401923e-01 -4.09809917e-01 -3.54902774e-01
-5.01241028e-01 -7.51870751e-01 -3.37333739e-01 7.08831489e-01
-7.13844448e-02 8.82356167e-02 3.62069339e-01 6.27382100e-02
-7.27087557e-02 1.98848844e-01 9.16690290e-01 -2.18805358e-01
-8.25232789e-02 2.76385844e-01 -9.00350213e-01 6.35120630e-01
1.05298543e+00 -6.86807811e-01 -2.82966554e-01 1.65987268e-01
-2.38058835e-01 3.45648229e-02 4.70084608e-01 -1.10463846e+00
-2.22233459e-02 -5.21821320e-01 6.13654137e-01 1.95118025e-01
1.39453858e-01 -9.30448711e-01 -1.44453347e-01 1.23022604e+00
-1.91065311e-01 3.59156072e-01 5.42165458e-01 6.35218322e-01
2.29118392e-01 8.32720548e-02 1.11427283e+00 -7.85113722e-02
-5.62283993e-01 4.20099378e-01 -9.19899344e-01 2.65955091e-01
1.60601473e+00 -1.04257174e-01 -7.23625362e-01 -2.48340830e-01
-2.62742549e-01 -2.38648076e-02 4.41352099e-01 6.18801355e-01
7.86412299e-01 -7.57005870e-01 -5.28099477e-01 8.11485052e-01
-2.59477347e-01 -9.30220306e-01 9.03835446e-02 2.71979004e-01
-6.73643351e-01 3.04532915e-01 -7.01189101e-01 -1.38952494e-01
-9.94430065e-01 1.00386286e+00 5.59692860e-01 -3.28172117e-01
-3.00192505e-01 6.86368644e-01 -5.95423952e-02 -4.28597808e-01
1.40637442e-01 5.57568192e-01 9.07720474e-04 -4.95132118e-01
7.57405758e-01 3.09465051e-01 -2.83858120e-01 -3.23315054e-01
-4.93838459e-01 -2.01338068e-01 -4.64997172e-01 1.67920247e-01
1.05332386e+00 6.80903673e-01 6.60596937e-02 -4.14387733e-01
1.07273185e+00 5.89680932e-02 -1.05441344e+00 1.70276880e-01
-3.17200320e-03 -7.73033261e-01 -2.47651383e-01 -1.02158093e+00
-1.26709521e+00 5.87917864e-01 2.93120503e-01 6.36749268e-01
1.06975687e+00 -5.45165718e-01 7.99662113e-01 4.49130118e-01
4.79863673e-01 -4.15826112e-01 4.06959981e-01 4.91462350e-01
3.17399234e-01 -1.01820219e+00 -4.71592903e-01 -1.11469232e-01
-5.07552803e-01 1.24605477e+00 9.51153517e-01 -5.13622642e-01
5.31131804e-01 6.47572160e-01 1.69389144e-01 -1.04033783e-01
-7.74854422e-01 4.25813496e-01 -1.63336813e-01 9.13738608e-01
-3.95693451e-01 4.43240143e-02 2.77595371e-01 1.98426992e-01
-9.71950740e-02 -7.07850993e-01 7.01656997e-01 1.13805068e+00
-5.09333313e-01 -1.28509176e+00 -6.87969327e-01 4.43741679e-01
-4.65893954e-01 2.42748414e-03 -7.59322882e-01 1.05019689e+00
-5.32252155e-02 1.29813051e+00 -1.29015446e-01 -9.45851386e-01
1.24545284e-01 -9.24479589e-02 8.43723267e-02 -2.65788287e-01
-9.44032848e-01 -5.85427642e-01 -3.23830582e-02 -6.44722581e-01
3.06282878e-01 -3.38753045e-01 -9.92886364e-01 -1.06904781e+00
-4.21583913e-02 3.15381914e-01 5.86126029e-01 9.51595247e-01
5.32849848e-01 6.22294724e-01 1.22691679e+00 -7.09661663e-01
-1.03880167e+00 -4.15754437e-01 -3.39368790e-01 3.29928845e-01
3.63477677e-01 -7.16518462e-01 -9.70276773e-01 -5.86039603e-01] | [5.508810520172119, 7.513881206512451] |
95ded325-2243-4064-ad94-ba12d7c522e5 | instant-domain-augmentation-for-lidar | 2303.14378 | null | https://arxiv.org/abs/2303.14378v1 | https://arxiv.org/pdf/2303.14378v1.pdf | Instant Domain Augmentation for LiDAR Semantic Segmentation | Despite the increasing popularity of LiDAR sensors, perception algorithms using 3D LiDAR data struggle with the 'sensor-bias problem'. Specifically, the performance of perception algorithms significantly drops when an unseen specification of LiDAR sensor is applied at test time due to the domain discrepancy. This paper presents a fast and flexible LiDAR augmentation method for the semantic segmentation task, called 'LiDomAug'. It aggregates raw LiDAR scans and creates a LiDAR scan of any configurations with the consideration of dynamic distortion and occlusion, resulting in instant domain augmentation. Our on-demand augmentation module runs at 330 FPS, so it can be seamlessly integrated into the data loader in the learning framework. In our experiments, learning-based approaches aided with the proposed LiDomAug are less affected by the sensor-bias issue and achieve new state-of-the-art domain adaptation performances on SemanticKITTI and nuScenes dataset without the use of the target domain data. We also present a sensor-agnostic model that faithfully works on the various LiDAR configurations. | ['Jaesik Park', 'Soonmin Hwang', 'Kwonyoung Ryu'] | 2023-03-25 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Ryu_Instant_Domain_Augmentation_for_LiDAR_Semantic_Segmentation_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Ryu_Instant_Domain_Augmentation_for_LiDAR_Semantic_Segmentation_CVPR_2023_paper.pdf | cvpr-2023-1 | ['lidar-semantic-segmentation'] | ['computer-vision'] | [ 3.93322289e-01 1.69230085e-02 -1.48191795e-01 -5.70375860e-01
-7.43536890e-01 -7.02704549e-01 3.75759780e-01 3.16053838e-01
-5.57792425e-01 5.57269156e-01 -5.90500474e-01 -2.30890676e-01
-8.82698596e-03 -9.10385728e-01 -8.98331583e-01 -4.59574819e-01
3.24095726e-01 1.10686994e+00 9.20067072e-01 -1.41524881e-01
1.59272224e-01 5.75802922e-01 -2.26795864e+00 -1.14731699e-01
1.12907243e+00 1.12998021e+00 4.85720217e-01 4.84178543e-01
-6.31892860e-01 -9.89516526e-02 -4.84062731e-01 -1.18795834e-01
5.73193729e-01 4.86468464e-01 -2.61511594e-01 2.43107796e-01
8.91877711e-01 -2.38593727e-01 1.70209497e-01 9.01316285e-01
7.58665383e-01 -2.91265715e-02 3.37477088e-01 -1.53515899e+00
-4.91406657e-02 2.82694936e-01 -6.05846822e-01 4.31171432e-02
2.24022284e-01 4.93115708e-02 5.59704244e-01 -9.34904158e-01
6.75325811e-01 1.25292850e+00 6.00022912e-01 3.91151249e-01
-1.32486701e+00 -8.19857895e-01 3.47886562e-01 2.81487465e-01
-1.29946375e+00 -1.70732155e-01 9.28494096e-01 -4.40449208e-01
6.98050797e-01 2.42160000e-02 5.38355052e-01 1.12494791e+00
-2.44452074e-01 6.37712598e-01 1.18858886e+00 -2.15662077e-01
6.48663223e-01 3.77518654e-01 5.89240268e-02 2.94174552e-01
5.64877450e-01 6.18552156e-02 -7.43813396e-01 1.38790727e-01
6.22579217e-01 -3.55706006e-01 2.89477706e-01 -9.73510623e-01
-8.24852526e-01 6.17731392e-01 1.81404993e-01 -2.17185602e-01
-1.23971269e-01 -1.95768684e-01 4.30570066e-01 1.47286072e-01
4.94310319e-01 1.55615788e-02 -7.74925828e-01 -2.07111627e-01
-8.35441828e-01 3.41225117e-01 5.38729310e-01 1.31762373e+00
1.06028688e+00 1.33419886e-01 4.17913735e-01 8.22242856e-01
7.83441961e-02 7.07628846e-01 3.62642020e-01 -8.81526649e-01
5.85061729e-01 8.10165048e-01 9.29319113e-02 -2.61002839e-01
-5.00001013e-01 -3.76484364e-01 -3.05240571e-01 5.32041609e-01
3.39115113e-01 -7.09388927e-02 -1.26742756e+00 1.53158712e+00
9.32648301e-01 2.84264147e-01 9.54150409e-02 7.89259076e-01
6.96707368e-01 1.19856797e-01 2.59928733e-01 6.32827133e-02
1.25850916e+00 -6.76729620e-01 -3.97758037e-01 -6.78895652e-01
2.74700165e-01 -6.69793665e-01 1.44003475e+00 5.65843344e-01
-6.98606074e-01 -9.95893061e-01 -1.39319861e+00 -1.34540245e-01
-7.38173425e-01 -6.79043531e-02 5.87188303e-01 9.07504678e-01
-7.61600077e-01 4.81701016e-01 -9.46885407e-01 -7.05019057e-01
3.91988099e-01 4.30816680e-01 -2.17898816e-01 -2.94719287e-03
-6.76848352e-01 8.64759445e-01 6.29499555e-01 -2.97679633e-01
-5.76675177e-01 -1.00490832e+00 -8.06285560e-01 -3.75358284e-01
7.51523077e-01 -4.39750373e-01 1.33124363e+00 -6.36829317e-01
-1.44378161e+00 8.12375307e-01 -5.34623489e-02 -4.89995033e-01
8.42851341e-01 -5.55772185e-01 -4.07260597e-01 -7.05358908e-02
1.89524978e-01 9.68147874e-01 9.22177732e-01 -1.53898501e+00
-8.57178032e-01 -6.26300693e-01 -1.48600996e-01 3.51253659e-01
-1.25739112e-01 -7.17787743e-01 -4.50741112e-01 -1.86377913e-01
4.59169894e-01 -8.72879565e-01 -1.32699192e-01 1.20357558e-01
-1.45176187e-01 -9.61532891e-02 1.35129988e+00 -5.07071838e-02
5.59397638e-01 -2.28873110e+00 -3.81255358e-01 3.96189950e-02
-4.18047249e-01 3.43755275e-01 -2.08314329e-01 1.81634679e-01
-1.16482261e-03 -1.42856106e-01 -4.22381759e-01 -5.37893057e-01
3.77977230e-02 7.27171242e-01 -3.02211493e-01 1.87412992e-01
3.26339662e-01 3.74933094e-01 -8.34295571e-01 -7.79861867e-01
6.66527629e-01 2.85993308e-01 -6.14270270e-01 3.28807086e-01
-6.11830592e-01 5.38603544e-01 -3.73538524e-01 9.62799191e-01
1.33139348e+00 2.81250209e-01 -1.24470480e-02 -1.55382887e-01
-2.66616940e-01 3.27701837e-01 -1.57767284e+00 2.27463388e+00
-4.27847028e-01 2.06014261e-01 1.45803332e-01 -8.30157042e-01
1.32244885e+00 -1.51922837e-01 5.88671267e-01 -7.25104988e-01
-1.19102880e-01 4.22045738e-01 -2.52978891e-01 -3.75076324e-01
5.76491952e-01 7.47873709e-02 -1.26260191e-01 1.71174798e-02
7.99601004e-02 -6.55210793e-01 9.84068066e-02 -2.41496891e-01
7.42071450e-01 8.54622781e-01 1.82988942e-01 -1.59429461e-01
4.11187828e-01 3.61606449e-01 5.79086661e-01 5.88623881e-01
-1.27952322e-01 5.71618259e-01 -3.45606394e-02 -2.61017352e-01
-1.14226270e+00 -1.62191260e+00 -4.63200033e-01 1.16759384e+00
3.65678579e-01 1.84474373e-03 -6.38810277e-01 -5.75605512e-01
4.68429446e-01 8.25964272e-01 -1.32158980e-01 1.29235135e-02
-3.76011193e-01 -4.61722016e-01 3.27682644e-01 7.16446877e-01
8.59740019e-01 -7.08246112e-01 -1.07746398e+00 3.69102597e-01
9.80690122e-03 -1.64124930e+00 1.24255233e-01 4.60341305e-01
-1.10821140e+00 -9.10584092e-01 3.89420288e-03 -4.29665834e-01
2.86371648e-01 2.57507235e-01 9.47377264e-01 -4.02909428e-01
-1.85034022e-01 4.02022809e-01 -3.57300073e-01 -9.06938136e-01
-2.72079468e-01 3.97672653e-01 1.87498420e-01 -2.91304678e-01
6.08600020e-01 -1.05213320e+00 -4.47061330e-01 3.32725883e-01
-8.34539354e-01 -1.05344109e-01 4.04602230e-01 3.84711415e-01
9.07496333e-01 -1.10014640e-01 5.71165204e-01 -7.99378633e-01
2.07391888e-01 -1.34182826e-01 -9.79779541e-01 -6.49880022e-02
-8.59627485e-01 8.39704797e-02 3.62822711e-01 -6.40394211e-01
-1.01835740e+00 5.98003268e-01 -8.90553892e-02 -5.57053149e-01
-6.38457239e-01 9.69138276e-03 -5.53936958e-01 -1.50386110e-01
8.62668395e-01 -1.11839408e-03 -6.08526133e-02 -7.89419889e-01
4.45836484e-01 7.41198123e-01 8.84772241e-01 -8.22178304e-01
1.07142532e+00 5.84989429e-01 1.76989257e-01 -8.95636976e-01
-7.16717482e-01 -6.32987618e-01 -1.00708330e+00 -1.63308069e-01
5.22069991e-01 -1.08451951e+00 -4.71009105e-01 3.75739843e-01
-9.72573280e-01 -1.40701637e-01 -6.86457038e-01 2.55596697e-01
-6.26509726e-01 4.33945358e-01 1.97197035e-01 -9.95007277e-01
-3.38268615e-02 -1.11073089e+00 1.23009920e+00 3.01096886e-01
9.67984051e-02 -4.43400502e-01 3.03448401e-02 4.43511516e-01
7.97878057e-02 3.86878014e-01 7.54720330e-01 -7.70092010e-01
-7.75047421e-01 -6.91623762e-02 -3.09951633e-01 4.29403156e-01
-1.18061667e-02 -1.94580182e-02 -1.43154347e+00 -2.36950293e-01
-2.09737122e-01 -3.05441916e-01 4.88781661e-01 5.44443401e-03
1.12685764e+00 3.05339396e-01 -1.57786667e-01 5.60088813e-01
1.59556496e+00 1.63893387e-01 2.50346988e-01 5.83615899e-01
5.54014623e-01 5.34470797e-01 1.16512048e+00 4.34062213e-01
5.49743712e-01 6.87264681e-01 9.13970828e-01 -1.07328609e-01
-2.60145981e-02 -4.75473464e-01 1.40201703e-01 3.20177704e-01
8.00342709e-02 -4.98889275e-02 -9.39056396e-01 5.80724955e-01
-1.74230957e+00 -3.60718876e-01 -7.54494146e-02 2.42912173e+00
5.62702775e-01 5.38176775e-01 2.24853858e-01 3.25822383e-01
5.30529261e-01 -1.88382529e-02 -9.97641504e-01 -6.30607486e-01
1.91959906e-02 5.85564196e-01 8.78585815e-01 3.49631935e-01
-1.08148825e+00 1.13868034e+00 5.91537809e+00 6.29424930e-01
-1.09898758e+00 2.00126395e-01 -1.31764993e-01 1.07272021e-01
-8.98563340e-02 -9.42003876e-02 -1.00835729e+00 3.78043294e-01
8.97728980e-01 1.11271434e-01 2.06690863e-01 1.41196942e+00
1.77720204e-01 -4.41917717e-01 -1.04702890e+00 8.61956835e-01
-2.58228034e-01 -8.26745391e-01 1.54601317e-02 3.06799728e-02
2.92561412e-01 2.86530554e-01 -3.15816924e-02 2.96286553e-01
1.90610409e-01 -4.84140933e-01 8.46077085e-01 -1.09693840e-01
1.07304168e+00 -8.22783172e-01 5.63169360e-01 5.29865861e-01
-1.28588462e+00 -1.64051086e-01 -6.16462409e-01 4.26716171e-03
9.72868577e-02 5.96551061e-01 -1.36389041e+00 6.49577260e-01
7.32807219e-01 2.48811245e-01 -6.72998965e-01 9.95519340e-01
-1.03357524e-01 3.74773681e-01 -8.10549140e-01 3.36323529e-01
-9.57660303e-02 -2.41379157e-01 6.08524621e-01 1.05702078e+00
5.47915697e-01 -3.13766599e-01 4.38433141e-01 6.06066108e-01
2.65753061e-01 2.95023788e-02 -6.05260313e-01 2.34396279e-01
8.49423289e-01 1.16823447e+00 -6.53429270e-01 -1.67065948e-01
-1.77115828e-01 7.61459351e-01 1.43572152e-01 5.70616350e-02
-8.75633299e-01 1.13217786e-01 8.10664415e-01 4.96785760e-01
4.30188715e-01 -3.83325994e-01 -7.46075690e-01 -6.78880453e-01
3.29832226e-01 -4.62003261e-01 2.97321975e-01 -8.67428422e-01
-1.15071702e+00 3.29705179e-01 2.77100295e-01 -1.47610545e+00
-2.18250588e-01 -6.72243953e-01 -1.26552075e-01 5.35340011e-01
-1.85573244e+00 -1.36950421e+00 -7.97169447e-01 6.70590460e-01
7.30425298e-01 8.34096596e-02 6.96920156e-01 4.56527114e-01
-2.51014829e-01 5.53837359e-01 -2.54995286e-01 -4.76822555e-01
7.83501983e-01 -1.52479875e+00 4.27517384e-01 7.48957098e-01
-9.20181349e-03 -8.42318460e-02 9.11333382e-01 -7.58017898e-01
-1.20484734e+00 -1.22333050e+00 4.48323548e-01 -4.99974996e-01
4.47985709e-01 -6.87861681e-01 -1.01778817e+00 4.74619091e-01
-2.37536848e-01 -7.48296455e-02 3.77658099e-01 -3.34254690e-02
-4.27133530e-01 -6.20153129e-01 -1.56063843e+00 2.65659809e-01
1.35899150e+00 -3.01387131e-01 -5.71698904e-01 2.65907168e-01
1.00249946e+00 -7.87654936e-01 -7.17727065e-01 8.50175858e-01
4.11870062e-01 -1.13028252e+00 1.16887093e+00 -2.52596915e-01
3.76723111e-02 -4.15640086e-01 -2.86091655e-01 -9.32738602e-01
1.76164448e-01 -3.02707523e-01 1.36189923e-01 1.34543169e+00
1.94357738e-01 -7.45748758e-01 1.06396437e+00 3.03253800e-01
-3.11076790e-01 -2.23114118e-01 -1.41066122e+00 -9.17221367e-01
-1.69181600e-01 -8.05069864e-01 8.27724874e-01 6.35022402e-01
-5.20447433e-01 2.31578723e-01 1.96272910e-01 5.70948958e-01
7.54825830e-01 7.15892762e-02 1.21553588e+00 -1.60790300e+00
-7.79732913e-02 6.24713376e-02 -5.18444777e-01 -9.61599469e-01
-1.59895092e-01 -5.30158639e-01 2.58260906e-01 -1.24526417e+00
-3.52596492e-01 -6.83314085e-01 2.24911999e-02 4.24428135e-01
7.24349022e-02 8.66000503e-02 1.56414092e-01 -4.10844944e-02
-6.68255016e-02 4.21144813e-01 1.14533746e+00 1.61475167e-02
-4.04443085e-01 1.61456481e-01 -3.71743649e-01 7.72370577e-01
8.27159584e-01 -3.83765578e-01 -8.13738406e-01 -4.35105383e-01
-1.17258184e-01 -3.36960465e-01 4.24026221e-01 -1.44627357e+00
1.41256833e-02 -2.50965863e-01 2.03624904e-01 -1.16560733e+00
7.61729181e-01 -1.25172281e+00 1.32525653e-01 1.51332825e-01
2.93776691e-01 1.91876918e-01 5.84997714e-01 5.24175346e-01
1.45731881e-01 -8.44336376e-02 9.29306924e-01 3.49748768e-02
-9.96509850e-01 2.09669992e-01 -1.27979830e-01 -7.96195269e-02
1.04450846e+00 -7.76835382e-01 -1.55964702e-01 1.63086310e-01
-6.50474966e-01 2.14568615e-01 6.98400795e-01 4.13277477e-01
4.09746200e-01 -1.01959312e+00 -3.14209521e-01 4.75276321e-01
3.30833733e-01 8.30720007e-01 1.31925374e-01 3.38243693e-01
-2.24831879e-01 5.88293076e-02 -2.76579320e-01 -1.10080338e+00
-1.00246787e+00 5.03159940e-01 1.56247243e-01 -2.13144105e-02
-5.41956723e-01 6.33472204e-01 -2.44400233e-01 -6.65290534e-01
2.67380774e-01 -4.71372426e-01 8.22213963e-02 1.77525058e-01
-6.04187101e-02 3.07840675e-01 3.72713625e-01 -2.56649375e-01
-4.37428355e-01 6.92612529e-01 1.36540085e-01 -2.28483379e-01
1.09496522e+00 -9.36350301e-02 4.70244467e-01 6.73003078e-01
4.90915328e-01 -6.60236254e-02 -1.56514561e+00 -2.07675532e-01
1.60227850e-01 -5.72329640e-01 -1.69533402e-01 -9.39941823e-01
-7.08608329e-01 1.04359591e+00 1.15437293e+00 -7.15313628e-02
1.08781517e+00 -1.07379876e-01 7.08898664e-01 2.62156606e-01
6.04204893e-01 -1.46327341e+00 -8.39288086e-02 2.77356476e-01
5.24221957e-01 -1.34329283e+00 3.28873359e-02 -7.36792922e-01
-6.02852046e-01 8.40573072e-01 1.01604068e+00 2.62778495e-02
4.36708391e-01 5.17746687e-01 2.57715166e-01 6.72784001e-02
-3.99283558e-01 -4.75119650e-01 -3.31356265e-02 1.29367363e+00
-1.85918152e-01 1.37948215e-01 -7.93969259e-02 2.62050569e-01
-4.71396267e-01 5.43681569e-02 3.45454365e-01 1.03399575e+00
-7.75907397e-01 -1.29820776e+00 -4.38933194e-01 1.46677792e-01
3.63812923e-01 3.04567575e-01 -2.65850902e-01 1.16013026e+00
7.77098775e-01 7.74712324e-01 3.03865880e-01 -4.17264432e-01
7.97932088e-01 3.53835911e-01 4.26542073e-01 -7.25188196e-01
-1.91693276e-01 1.33822933e-01 1.52064532e-01 -7.12468207e-01
-4.69287574e-01 -9.71643746e-01 -1.38909984e+00 -8.10143054e-02
-1.75629467e-01 -1.33326709e-01 1.12885725e+00 7.76245236e-01
4.40422416e-01 2.75119096e-01 4.51305091e-01 -8.61690402e-01
-7.61327088e-01 -8.41391206e-01 -4.14937854e-01 3.25153291e-01
1.20451085e-01 -1.11521697e+00 -1.38421282e-01 -2.08759401e-02] | [8.1012544631958, -2.650712490081787] |
9973abe0-a2f5-4cfd-90e1-21b34ee6cbcf | rethinking-online-action-detection-in | 2003.12041 | null | https://arxiv.org/abs/2003.12041v1 | https://arxiv.org/pdf/2003.12041v1.pdf | Rethinking Online Action Detection in Untrimmed Videos: A Novel Online Evaluation Protocol | The Online Action Detection (OAD) problem needs to be revisited. Unlike traditional offline action detection approaches, where the evaluation metrics are clear and well established, in the OAD setting we find very few works and no consensus on the evaluation protocols to be used. In this work we propose to rethink the OAD scenario, clearly defining the problem itself and the main characteristics that the models which are considered online must comply with. We also introduce a novel metric: the Instantaneous Accuracy ($IA$). This new metric exhibits an \emph{online} nature and solves most of the limitations of the previous metrics. We conduct a thorough experimental evaluation on 3 challenging datasets, where the performance of various baseline methods is compared to that of the state-of-the-art. Our results confirm the problems of the previous evaluation protocols, and suggest that an IA-based protocol is more adequate to the online scenario. The baselines models and a development kit with the novel evaluation protocol are publicly available: https://github.com/gramuah/ia. | ['S. Maldonado-Bascón', 'F. Javier Acevedo-Rodríguez', 'Roberto J. López-Sastre', 'Marcos Baptista Rios', 'Jan van Gemert', 'Fabian Caba Heilbron'] | 2020-03-26 | null | null | null | null | ['online-action-detection'] | ['computer-vision'] | [ 3.23750675e-02 -1.32353902e-01 -3.99147272e-01 -2.91161507e-01
-7.36915529e-01 -6.26111507e-01 7.16563225e-01 2.45622620e-01
-6.75982118e-01 5.85404813e-01 8.15196633e-02 -1.70676261e-01
-3.26574683e-01 -4.13733453e-01 -2.95517564e-01 -4.89298612e-01
-3.04790288e-01 2.55360901e-01 7.75618255e-01 -2.56744623e-01
3.23028743e-01 3.54672492e-01 -1.81294572e+00 2.14889497e-01
4.07760024e-01 1.19996154e+00 -2.01875418e-01 7.06890166e-01
5.73160090e-02 9.74187613e-01 -7.59988785e-01 -3.77869248e-01
5.81064165e-01 -4.96703684e-01 -1.07471418e+00 1.02818534e-01
3.52126867e-01 -6.52963638e-01 -3.37577581e-01 7.82394528e-01
5.47673523e-01 1.66568667e-01 1.67433381e-01 -1.50602126e+00
-3.16637784e-01 3.99000734e-01 -2.20341504e-01 4.11298990e-01
9.14530873e-01 3.25529367e-01 1.14635217e+00 -6.90414548e-01
7.46171296e-01 1.06421852e+00 5.98628283e-01 5.18845558e-01
-8.83936882e-01 -1.22352697e-01 5.74240983e-01 5.73692679e-01
-1.31423783e+00 -4.21563029e-01 4.96505320e-01 -4.23038840e-01
9.72235560e-01 3.69543701e-01 5.99363506e-01 1.36644363e+00
-1.62717283e-01 1.16327560e+00 1.21735990e+00 -6.04156792e-01
4.31579202e-01 1.46360829e-01 2.45753512e-01 4.99267995e-01
2.77614653e-01 -4.88844700e-02 -5.00867784e-01 -3.46018001e-02
4.76686954e-01 -1.64137393e-01 -1.55615598e-01 -5.31597614e-01
-1.23832762e+00 5.79518616e-01 -2.07650840e-01 4.25655335e-01
-2.90405720e-01 1.04853235e-01 6.55728281e-01 3.51008207e-01
3.78358334e-01 3.90894264e-01 -4.76545155e-01 -8.88994813e-01
-8.14873397e-01 4.43118870e-01 9.20527279e-01 6.99075282e-01
4.37039912e-01 -3.86242032e-01 -3.81029040e-01 6.14056766e-01
1.90099403e-01 9.26904231e-02 3.83935422e-01 -1.37669754e+00
3.57546180e-01 8.93687606e-01 5.86607397e-01 -8.14325035e-01
-4.25033391e-01 -1.39642835e-01 -1.60165593e-01 3.89048576e-01
9.11747336e-01 -5.52929975e-02 -3.41855228e-01 1.55478656e+00
4.85053062e-01 1.88229680e-02 -1.05396882e-01 8.73873115e-01
3.47260088e-01 1.70937404e-01 1.32628402e-03 -1.68477714e-01
1.04502296e+00 -1.12916434e+00 -9.26079869e-01 -1.60342783e-01
8.92890036e-01 -6.59751475e-01 1.27044451e+00 5.76365471e-01
-1.02448893e+00 -4.12588686e-01 -1.06097960e+00 1.67854652e-01
-6.20478153e-01 1.78824648e-01 7.13231087e-01 6.97610855e-01
-1.20264232e+00 7.28328168e-01 -9.76186931e-01 -8.58218968e-01
1.54635549e-01 1.40699133e-01 -2.43247777e-01 1.76587343e-01
-1.17113030e+00 1.17540169e+00 2.53569782e-01 -2.97911279e-02
-1.05488181e+00 -2.23614961e-01 -4.72546160e-01 -3.56812745e-01
8.76748204e-01 -2.39511892e-01 1.84765840e+00 -8.90211403e-01
-1.75119829e+00 1.00720966e+00 1.74372792e-01 -6.39715552e-01
1.14618599e+00 -4.25220668e-01 -3.14814031e-01 2.14982107e-01
9.88022164e-02 2.88303375e-01 3.26196432e-01 -8.67100716e-01
-9.28933263e-01 -2.63684392e-02 8.78275335e-01 2.59155873e-02
-2.04550177e-01 3.40282619e-01 -5.54594815e-01 -3.90134454e-01
-3.10983211e-01 -9.32449639e-01 -1.77775249e-01 5.06281070e-02
-2.67737538e-01 -3.79233181e-01 5.67794740e-01 -3.99895340e-01
1.76211917e+00 -2.11573386e+00 -8.92007798e-02 -1.79481298e-01
-1.83810536e-02 3.26166689e-01 -1.36481030e-02 8.81522775e-01
-7.38610281e-03 1.98016301e-01 -1.51993364e-01 -4.49235231e-01
5.07930636e-01 1.24955237e-01 6.36746436e-02 5.67625701e-01
-7.60231391e-02 5.03144264e-01 -1.06240547e+00 -4.09502983e-01
3.62640738e-01 3.47444601e-02 -3.01311880e-01 2.77787507e-01
-2.04932541e-01 1.20560504e-01 -4.28132951e-01 8.24739456e-01
3.85953933e-01 -2.37378329e-01 3.11353505e-01 1.30213931e-01
-4.08462763e-01 4.15851355e-01 -1.68920791e+00 1.67513394e+00
-5.07411510e-02 4.20902938e-01 2.15032813e-03 -9.90142524e-01
5.17850280e-01 3.76424104e-01 8.24420750e-01 -6.20935202e-01
1.34584159e-01 2.65026540e-01 -5.55435643e-02 -5.82181036e-01
4.52665627e-01 4.93436664e-01 -9.44237858e-02 5.95275462e-01
4.87563722e-02 4.41498995e-01 6.95614219e-01 1.78222314e-01
1.60846281e+00 5.40634811e-01 6.42494917e-01 -1.28097907e-01
6.11233771e-01 1.01659544e-01 4.45212483e-01 1.12970591e+00
-8.65423024e-01 3.18470329e-01 7.14124739e-01 -4.20166194e-01
-6.17313623e-01 -7.28809178e-01 1.19660839e-01 1.21261179e+00
2.76468456e-01 -8.04163039e-01 -9.74934220e-01 -9.84629750e-01
-7.00801089e-02 4.25292403e-01 -7.38070309e-01 1.26818866e-01
-3.50819707e-01 -6.26354814e-01 5.57167709e-01 4.29406881e-01
5.83728075e-01 -8.52229834e-01 -9.20281708e-01 3.40966761e-01
-3.28926116e-01 -1.42625320e+00 -1.57964423e-01 -1.05570540e-01
-7.04496980e-01 -1.29539216e+00 -4.14883733e-01 -1.22907706e-01
1.38435081e-01 2.97888041e-01 1.09878802e+00 1.68387592e-01
-7.49485642e-02 8.45799327e-01 -9.32845294e-01 -5.69703519e-01
-3.51805836e-01 8.93308446e-02 1.37760147e-01 2.56679922e-01
5.64916849e-01 -3.77204746e-01 -8.42430174e-01 6.14402711e-01
-7.30494082e-01 -2.74774253e-01 4.79886264e-01 2.27083892e-01
5.07976830e-01 -2.22006321e-01 3.55384767e-01 -7.81265318e-01
5.05119681e-01 -3.23155463e-01 -6.70656323e-01 1.53214276e-01
-8.33386183e-01 -1.67346582e-01 2.61429310e-01 -3.83350343e-01
-7.51469672e-01 1.47914207e-02 -1.20523021e-01 -2.00692266e-01
-4.40144390e-01 3.28112066e-01 -1.40764102e-01 1.71642192e-02
6.67803824e-01 -2.66150031e-02 -2.08600134e-01 -8.20446730e-01
1.39892355e-01 4.89187747e-01 1.56085894e-01 -4.45969552e-01
4.63432729e-01 6.42717838e-01 -2.39618242e-01 -4.06104416e-01
-9.74511683e-01 -6.58760726e-01 -7.64330029e-01 -5.88631511e-01
7.64924943e-01 -7.26572573e-01 -7.62543082e-01 6.79918826e-01
-1.01614773e+00 -6.44711971e-01 -6.71124756e-01 4.61185873e-01
-8.20695102e-01 5.38435876e-01 -4.70563412e-01 -1.08422947e+00
6.33920878e-02 -1.05778229e+00 1.02970886e+00 -4.55371775e-02
-3.32043618e-01 -8.16256464e-01 3.51903230e-01 3.61205786e-01
4.22249466e-01 5.51215827e-01 1.16622381e-01 -7.40774155e-01
-4.06918943e-01 -4.93337303e-01 3.76969799e-02 5.29830873e-01
1.84187721e-02 1.26065090e-01 -9.44827318e-01 -1.68765843e-01
-1.43928215e-01 -1.72084540e-01 5.80741644e-01 1.52837172e-01
9.79204774e-01 -2.19853431e-01 -1.09740742e-01 -6.83875754e-02
1.43590128e+00 2.96790093e-01 7.65265286e-01 9.44999933e-01
3.95082757e-02 4.93163675e-01 1.11880648e+00 8.20671439e-01
5.50938249e-01 1.03319800e+00 6.75752699e-01 1.67203128e-01
-2.54501007e-03 -1.15156978e-01 9.30250168e-01 4.95752811e-01
-3.40303153e-01 -5.31309962e-01 -8.38535249e-01 6.60796165e-01
-2.27008414e+00 -1.06039417e+00 -5.83897717e-02 2.28489017e+00
6.05215430e-01 3.28400224e-01 7.04579532e-01 4.42571163e-01
5.22476077e-01 3.65851700e-01 -1.77097723e-01 -4.86416519e-01
7.84911811e-02 7.55890161e-02 3.81426901e-01 4.26882565e-01
-1.46401882e+00 7.21710324e-01 6.88394642e+00 6.66888475e-01
-7.25871205e-01 4.29846466e-01 1.56438842e-01 -1.54208913e-01
4.91612047e-01 2.37828076e-01 -8.59769464e-01 3.91192585e-01
1.24516153e+00 -1.00718282e-01 2.21312091e-01 1.00527704e+00
6.22209609e-01 -4.79965001e-01 -1.40593302e+00 7.75205970e-01
-6.82020187e-02 -9.94887471e-01 -2.82557756e-01 3.01027130e-02
3.82505774e-01 1.04279719e-01 -3.46328110e-01 4.70165223e-01
3.47551763e-01 -4.93680269e-01 9.41929519e-01 6.30860925e-01
4.73140091e-01 -6.95979074e-02 7.45649934e-01 2.52358496e-01
-1.08058095e+00 -2.18434155e-01 5.06295860e-02 -3.94428909e-01
1.51390314e-01 3.17554474e-01 -5.16434014e-01 7.49530733e-01
8.33532214e-01 8.77259076e-01 -8.29980135e-01 1.22184205e+00
-3.38605553e-01 6.19524181e-01 -2.81148463e-01 -1.98887676e-01
4.17724133e-01 -9.94392186e-02 6.28506422e-01 1.25307190e+00
1.37603194e-01 -1.04056150e-01 3.44032347e-01 3.82370204e-01
1.63383827e-01 2.78618813e-01 -3.96782607e-01 -1.03045434e-01
2.28415981e-01 1.03644812e+00 -5.33063233e-01 -3.62032861e-01
-6.79758489e-01 9.24739003e-01 6.06310926e-02 1.02495626e-02
-1.10616040e+00 -2.53718913e-01 7.31843650e-01 2.90488034e-01
2.70627230e-01 -3.07161391e-01 2.15723902e-01 -1.10352659e+00
4.24388140e-01 -1.07542229e+00 7.71078825e-01 -5.40360808e-01
-9.03015137e-01 2.16397315e-01 3.09583247e-01 -1.73538113e+00
-1.46124095e-01 -7.15943336e-01 -4.55308408e-01 1.04743116e-01
-1.53966868e+00 -7.46352851e-01 -4.27791357e-01 5.55163860e-01
5.53176880e-01 2.41014257e-01 8.00577819e-01 6.08651817e-01
-7.75774240e-01 5.59758723e-01 -3.76594104e-02 1.10232309e-01
7.93958604e-01 -1.26067781e+00 1.24665931e-01 1.03961909e+00
-1.79358087e-02 1.72124833e-01 7.89562345e-01 -2.17297167e-01
-1.36256957e+00 -7.86885381e-01 8.14756691e-01 -7.76632190e-01
1.02791095e+00 -2.79017329e-01 -5.63639164e-01 7.57492781e-01
7.93319941e-02 4.05506260e-04 6.28165841e-01 -4.29872684e-02
-1.51065215e-01 -1.65322155e-01 -9.36406851e-01 4.66823399e-01
1.40403748e+00 -3.03209990e-01 -4.63338315e-01 5.89848280e-01
5.53682387e-01 -3.07114005e-01 -8.36521804e-01 2.63533562e-01
6.85309589e-01 -1.34855604e+00 6.45983934e-01 -6.47497356e-01
1.25184944e-02 -3.83083940e-01 -2.48016566e-01 -7.43251204e-01
-6.17206320e-02 -8.53076041e-01 -2.95340508e-01 1.21238077e+00
4.34354872e-01 -7.54676700e-01 6.14619255e-01 5.06520808e-01
7.54085854e-02 -7.25253999e-01 -1.03918052e+00 -1.26029086e+00
-2.96151191e-01 -6.95006549e-01 3.97193104e-01 7.34787822e-01
1.17616110e-01 -8.77786949e-02 -3.96189570e-01 -9.88653861e-03
3.49549472e-01 -3.75109203e-02 1.09462106e+00 -1.03185010e+00
-4.80212957e-01 -4.88562703e-01 -6.85473859e-01 -9.89419341e-01
-3.89581263e-01 -4.21180785e-01 -2.05395654e-01 -1.54409611e+00
7.99147487e-02 -1.74924284e-01 -5.93641043e-01 7.62000918e-01
2.25323841e-01 -1.83669850e-02 3.06483150e-01 2.06704915e-01
-1.39606416e+00 4.46149498e-01 8.17048430e-01 9.78685543e-02
-2.10959762e-01 -2.23045461e-02 -5.80151200e-01 8.22404504e-01
9.17089343e-01 -5.78067660e-01 -1.72710344e-01 -3.86173636e-01
1.26347199e-01 -3.00972193e-01 4.09174442e-01 -1.30897057e+00
1.41048357e-01 -3.24890405e-01 -4.17901427e-01 -2.28674501e-01
3.05062741e-01 -8.15857172e-01 -4.60371263e-02 4.07902211e-01
-3.01363766e-01 -2.47124843e-02 -1.67270694e-02 5.31378686e-01
-2.45168269e-01 -2.18095139e-01 6.55892253e-01 -2.46863589e-01
-9.47239876e-01 1.90010905e-01 -4.88912523e-01 1.37069717e-01
1.24641073e+00 -3.99123698e-01 -3.55985790e-01 -5.18088400e-01
-8.10631454e-01 2.60631204e-01 4.49939460e-01 5.10119498e-01
1.80283427e-01 -1.15162921e+00 -6.10427976e-01 -3.67668629e-01
4.06829268e-01 -6.42947316e-01 2.00779457e-02 1.43897879e+00
-5.16480446e-01 3.13558042e-01 -7.18104765e-02 -4.05932575e-01
-1.04159629e+00 5.08252919e-01 4.69668686e-01 -6.07464373e-01
-4.55419213e-01 3.46974015e-01 -3.78760308e-01 -2.19034806e-01
6.28939986e-01 -3.68765175e-01 -2.23929822e-01 2.21134827e-01
5.87029040e-01 8.12273681e-01 1.72064602e-01 -4.26270783e-01
-6.38246298e-01 1.96916595e-01 1.19249478e-01 -1.47056922e-01
1.39254296e+00 -3.31210911e-01 1.96603060e-01 6.65384412e-01
8.34418535e-01 -1.43557578e-01 -1.12244236e+00 -1.93530619e-01
4.72203702e-01 -6.18343115e-01 -2.00711235e-01 -8.76023710e-01
-6.76679850e-01 6.13559008e-01 9.61603642e-01 6.23878062e-01
1.16955554e+00 -1.01364471e-01 4.86253649e-01 2.93009669e-01
5.51766813e-01 -1.67114711e+00 7.65141249e-02 5.15082002e-01
9.42218482e-01 -1.27511060e+00 1.43818945e-01 -3.51697177e-01
-4.55609858e-01 1.02428627e+00 6.17219925e-01 -1.71289980e-01
5.34363091e-01 7.57024959e-02 1.29665241e-01 -2.41013780e-01
-8.19606841e-01 -6.30353570e-01 -1.45666525e-01 2.48047799e-01
2.30383605e-01 -1.11064620e-01 -8.95577550e-01 6.13051474e-01
2.79848963e-01 2.77630895e-01 6.69239104e-01 1.44693947e+00
-2.97677279e-01 -1.43122232e+00 -1.92218393e-01 9.36042964e-02
-6.38925672e-01 4.30025190e-01 -8.17381859e-01 1.22033453e+00
1.71084642e-01 1.26635575e+00 -3.05437565e-01 -6.06229007e-01
8.39121819e-01 2.57586896e-01 3.58596861e-01 -4.85495657e-01
-6.06250107e-01 -2.83629894e-01 4.28915799e-01 -1.29236472e+00
-9.46764171e-01 -9.83611643e-01 -8.80375862e-01 -1.94495976e-01
-2.08950281e-01 -2.90246587e-02 4.94373113e-01 7.87174881e-01
4.41401154e-01 1.28277659e-01 7.09095597e-01 -7.23313272e-01
-6.98879421e-01 -8.32130075e-01 -3.91989976e-01 5.65050781e-01
8.78098011e-02 -9.68792558e-01 -6.72329903e-01 -8.59795660e-02] | [8.18074893951416, 0.5016990303993225] |
0e639aea-65fa-43e5-bdb5-8b87436cf9ae | mocha-a-multi-task-training-approach-for | 2210.14650 | null | https://arxiv.org/abs/2210.14650v1 | https://arxiv.org/pdf/2210.14650v1.pdf | MOCHA: A Multi-Task Training Approach for Coherent Text Generation from Cognitive Perspective | Teaching neural models to generate narrative coherent texts is a critical problem. Recent pre-trained language models have achieved promising results, but there is still a gap between human written texts and machine-generated outputs. In this work, we propose a novel multi-task training strategy for coherent text generation grounded on the cognitive theory of writing, which empowers the model to learn essential subskills needed for writing including planning and reviewing besides end-to-end generation. We extensively evaluate our model on three open-ended generation tasks including story generation, news article writing and argument generation. Experiments show that our model achieves better results on both few-shot and fully-supervised settings than strong baselines, and human evaluations confirm that our model can generate more coherent outputs. | ['Lifu Huang', 'Hou Pong Chan', 'Zhe Hu'] | 2022-10-26 | null | null | null | null | ['story-generation'] | ['natural-language-processing'] | [ 2.95795858e-01 6.11176968e-01 -2.91742027e-01 -1.67088956e-01
-1.18758500e+00 -4.82435137e-01 1.33977234e+00 -7.64729604e-02
-1.21047787e-01 1.17732036e+00 1.35485637e+00 -1.25508532e-01
2.53068924e-01 -9.97051954e-01 -5.83504975e-01 -1.13347378e-02
7.56105304e-01 7.68913507e-01 -1.43758431e-01 -6.24581158e-01
4.77580249e-01 -2.48291612e-01 -1.12894833e+00 1.00012040e+00
1.19358122e+00 1.80298001e-01 3.17679375e-01 9.29980099e-01
-3.40683967e-01 1.57546222e+00 -1.00577378e+00 -8.39227319e-01
-3.63742292e-01 -9.31385994e-01 -1.15604281e+00 -1.45006090e-01
1.55465692e-01 -5.66659689e-01 -3.05480361e-01 5.03374159e-01
7.99510598e-01 3.11970145e-01 1.12238467e+00 -7.83880174e-01
-1.32243276e+00 1.49513197e+00 -1.07633378e-02 4.89872061e-02
5.66622555e-01 3.49805653e-01 1.09252810e+00 -9.81938601e-01
9.72549021e-01 1.28701746e+00 5.33332884e-01 1.02390838e+00
-1.12448263e+00 -3.93367052e-01 -3.92659493e-02 8.49513412e-02
-5.85090816e-01 -6.60554469e-01 7.30566919e-01 -4.53241885e-01
1.17657435e+00 -4.44128476e-02 6.14415169e-01 2.04187965e+00
2.73642153e-01 1.10662472e+00 8.83555472e-01 -5.54248154e-01
5.11434674e-02 -1.72161818e-01 5.43844253e-02 4.20474291e-01
8.73546824e-02 6.01692125e-02 -8.47620130e-01 1.25287056e-01
6.09524786e-01 -5.48877418e-01 -1.96195915e-01 5.42079270e-01
-1.44646943e+00 1.27286434e+00 1.01096660e-01 2.69587338e-01
-3.71425629e-01 3.74651283e-01 4.89002645e-01 1.28438687e-02
7.45582998e-01 9.56199586e-01 2.19823301e-01 -4.18472439e-01
-1.05530608e+00 6.99159324e-01 9.53749537e-01 9.88269508e-01
-7.96810389e-02 3.88756961e-01 -1.18279088e+00 8.84626031e-01
2.01651137e-02 4.33011174e-01 9.19476688e-01 -7.45509088e-01
9.85965908e-01 2.49049872e-01 2.19768927e-01 -6.99552476e-01
-2.36697659e-01 -3.27415705e-01 -8.10756624e-01 -2.49605447e-01
1.91923320e-01 -5.40726960e-01 -6.20790780e-01 1.72753906e+00
-2.98137754e-01 -1.07758179e-01 6.07848883e-01 7.04819322e-01
1.28265536e+00 1.00187457e+00 1.89434037e-01 -2.08925366e-01
1.16758728e+00 -1.49769962e+00 -1.10235381e+00 -5.02114177e-01
4.63491201e-01 -7.95135379e-01 1.30670726e+00 4.09443788e-02
-1.60744560e+00 -5.98137081e-01 -9.58220840e-01 -4.68012154e-01
2.80463360e-02 3.97624642e-01 4.77232993e-01 1.32209674e-01
-7.98646867e-01 6.16772592e-01 -5.27967453e-01 -4.53130864e-02
6.22516036e-01 -5.38654923e-01 1.04185864e-01 1.30469754e-01
-1.46395838e+00 1.23956597e+00 6.67431712e-01 -2.16224119e-01
-9.76188004e-01 -6.75893247e-01 -7.51982272e-01 1.24680191e-01
3.85577142e-01 -1.30748558e+00 1.92309272e+00 -5.04734993e-01
-1.97396696e+00 6.12766981e-01 -9.57261622e-02 -6.08427048e-01
7.36480534e-01 -4.88617539e-01 -7.67213404e-02 3.81855927e-02
2.66345292e-01 7.49432802e-01 5.03301799e-01 -1.02299690e+00
-2.71168917e-01 2.77962953e-01 -5.78933619e-02 4.77838010e-01
-3.92944127e-01 -5.19557158e-03 2.74403065e-01 -1.11789799e+00
-5.82442284e-01 -4.93571758e-01 -2.83689469e-01 -6.75680220e-01
-6.95915222e-01 -6.80640221e-01 9.45054367e-02 -7.77976632e-01
1.29782474e+00 -1.18926525e+00 2.60439903e-01 -6.22393429e-01
3.75296287e-02 1.21320136e-01 -4.28241551e-01 8.88866246e-01
2.40671650e-01 2.52483010e-01 -6.92351907e-02 -4.32960749e-01
2.77249664e-01 -1.49512917e-01 -9.96165454e-01 -4.78713602e-01
4.36305225e-01 1.66279936e+00 -1.18013251e+00 -5.00049472e-01
-2.22076192e-01 1.55327320e-01 -4.15835619e-01 4.02632594e-01
-8.85696709e-01 1.38591096e-01 -4.41022992e-01 1.28823906e-01
-1.28802001e-01 -5.20799160e-01 4.04653326e-02 2.78988957e-01
-2.26986296e-02 9.51761007e-01 -4.84329909e-01 1.89458466e+00
-5.69897234e-01 7.20299244e-01 -8.72616351e-01 -5.84129512e-01
8.63485277e-01 7.06788123e-01 -5.43664157e-01 -7.40245044e-01
1.39833644e-01 -1.97841302e-02 -1.38430744e-01 -5.71313381e-01
1.00119400e+00 -3.99421841e-01 -3.10679168e-01 1.31924677e+00
1.55494794e-01 -6.71035469e-01 5.11928737e-01 6.28259122e-01
8.11244965e-01 4.89680469e-01 3.06334287e-01 4.40515019e-03
-5.53457215e-02 2.10487261e-01 -2.75392532e-02 9.71221507e-01
4.56148237e-01 7.62801826e-01 5.52334547e-01 -1.54182762e-01
-1.15276396e+00 -1.02855885e+00 4.94327873e-01 1.13135707e+00
-2.66975522e-01 -6.01873636e-01 -1.01492548e+00 -5.55716693e-01
-5.34449339e-01 1.60612035e+00 -5.20209372e-01 -1.78936437e-01
-7.07081616e-01 -6.51071608e-01 8.72200549e-01 7.85095870e-01
2.97644258e-01 -1.77766073e+00 -7.99419940e-01 5.64717293e-01
-7.91799188e-01 -1.02962065e+00 -5.24537444e-01 -2.68804163e-01
-7.70829916e-01 -6.74089134e-01 -7.33391762e-01 -8.35879207e-01
4.67368722e-01 4.42463048e-02 1.47805583e+00 -8.67596120e-02
8.69494826e-02 -1.09349743e-01 -4.55540985e-01 -6.83380783e-01
-9.98033881e-01 4.47002590e-01 -3.68905365e-01 -6.56239510e-01
-1.66430727e-01 -3.93917173e-01 -1.59176290e-01 -3.68609607e-01
-7.56925464e-01 1.16446602e+00 5.72292924e-01 1.14565516e+00
1.21567495e-01 -6.11035764e-01 1.23984420e+00 -9.39448237e-01
1.69318223e+00 -4.27746743e-01 -9.23904683e-03 4.61512238e-01
-5.35438359e-01 2.91335046e-01 8.44881773e-01 -4.55707312e-01
-1.63175464e+00 -5.68977833e-01 -2.51296442e-02 2.50651836e-01
1.05158061e-01 8.90114784e-01 2.37517416e-01 1.10475802e+00
1.03807890e+00 3.21352750e-01 -1.51497215e-01 -1.62763327e-01
8.51628125e-01 4.35079873e-01 6.90019786e-01 -8.41597319e-01
7.59553373e-01 5.08174598e-02 -4.19377238e-01 -2.73215592e-01
-1.44770849e+00 4.52616483e-01 -2.47058913e-01 -3.19460213e-01
8.32876742e-01 -1.04989266e+00 -1.68234482e-01 2.43801445e-01
-1.80027986e+00 -8.22317958e-01 -6.19561434e-01 2.49898076e-01
-8.78456771e-01 2.00741813e-02 -9.25984085e-01 -6.51420772e-01
-9.46574509e-01 -6.34298921e-01 9.05374169e-01 4.44119334e-01
-9.12884653e-01 -1.16417933e+00 3.79613936e-01 6.04147971e-01
4.80597317e-01 3.20266336e-01 1.02506685e+00 -6.57741189e-01
-4.50655371e-01 3.39028090e-02 -5.39433360e-02 -3.23730484e-02
-2.57362455e-01 -1.11105785e-01 -8.75975192e-01 3.84845287e-01
-2.29525566e-01 -1.11034179e+00 1.11259675e+00 2.45495498e-01
8.61907840e-01 -7.28835046e-01 -1.06030807e-01 1.70904472e-01
7.50929892e-01 -8.59206468e-02 7.92100370e-01 1.75885439e-01
5.72597861e-01 6.85042858e-01 5.64155579e-01 5.15747845e-01
7.68995881e-01 4.62448925e-01 -1.30201980e-01 1.16501905e-01
-4.77532089e-01 -9.06770408e-01 6.44397199e-01 9.98488665e-01
-1.33794278e-01 -7.86414921e-01 -8.38724375e-01 6.80903375e-01
-2.09711695e+00 -1.76444900e+00 -2.36778811e-01 1.43615389e+00
1.51674819e+00 1.92980915e-01 -1.65978044e-01 -2.60124356e-01
4.91612852e-01 4.73613650e-01 -3.62574816e-01 -5.99114418e-01
-3.87659758e-01 6.01474941e-01 -4.05110836e-01 5.48950970e-01
-7.39744902e-01 1.38918126e+00 6.65232801e+00 9.40681934e-01
-7.20879138e-01 2.42942587e-01 7.48704493e-01 -4.11706328e-01
-6.88122213e-01 -8.73088688e-02 -7.17958987e-01 3.92695069e-01
1.03020525e+00 -9.32592630e-01 1.99457303e-01 7.21073508e-01
4.30330366e-01 1.76996872e-01 -1.19542623e+00 5.12471437e-01
4.93069321e-01 -2.11803675e+00 5.09741366e-01 -2.94523835e-01
1.31482089e+00 -3.72224659e-01 -1.08806074e-01 7.11865187e-01
8.91696513e-01 -1.46941483e+00 1.13236415e+00 7.54536092e-01
7.16523588e-01 -6.42763257e-01 5.65498888e-01 6.84226215e-01
-6.42279506e-01 1.83884010e-01 -2.44945854e-01 -5.30833006e-01
8.01449418e-01 4.13888872e-01 -1.08522892e+00 3.82076383e-01
-2.21927166e-01 7.49054015e-01 -4.92479056e-01 4.14409876e-01
-1.06005347e+00 6.20592713e-01 5.05607784e-01 -5.82578897e-01
1.94708660e-01 9.41737965e-02 3.23206037e-01 1.31200612e+00
4.97775614e-01 3.45254600e-01 6.48792014e-02 1.35764849e+00
-6.09959662e-01 5.01068607e-02 -5.76309919e-01 -6.02662146e-01
4.46826696e-01 1.11873078e+00 -4.22720104e-01 -7.50425279e-01
3.55594791e-02 9.78640616e-01 5.77221751e-01 3.06183338e-01
-9.02116537e-01 -3.57543975e-01 5.19508943e-02 -3.49164866e-02
6.78635389e-02 -1.27347365e-01 -7.65786529e-01 -1.22202480e+00
-1.11026481e-01 -9.86902356e-01 7.26519674e-02 -1.21258402e+00
-1.32900965e+00 6.48168743e-01 -4.12367322e-02 -8.79985154e-01
-1.06387103e+00 -1.37329116e-01 -1.18166041e+00 8.63009512e-01
-1.34930503e+00 -1.34142244e+00 -1.86549574e-01 -1.09796170e-02
1.17339933e+00 -4.74015415e-01 1.01108444e+00 -4.25090969e-01
-3.29530567e-01 4.65959102e-01 -1.51538357e-01 2.32812122e-01
6.85627341e-01 -1.10741735e+00 9.85120296e-01 9.18006659e-01
2.27967948e-01 5.93190968e-01 5.77775538e-01 -9.82220411e-01
-8.93908143e-01 -1.06664145e+00 1.38841021e+00 -6.52160764e-01
5.87667644e-01 -2.96254069e-01 -5.12444913e-01 6.25856817e-01
9.38491344e-01 -9.07567263e-01 8.03894341e-01 -9.92980506e-03
-3.04841548e-01 7.04445243e-01 -5.74718595e-01 1.10970616e+00
1.23879063e+00 -5.01210451e-01 -1.15421069e+00 6.96798563e-01
1.00767028e+00 -5.40335715e-01 -4.44633335e-01 -1.78904105e-02
5.60714126e-01 -5.99900067e-01 7.32559621e-01 -9.55860734e-01
1.87122023e+00 1.88513264e-01 4.19502407e-01 -1.92099702e+00
-2.68309861e-01 -8.74148905e-01 -4.59464192e-01 1.24037242e+00
6.74416721e-01 -1.05788834e-01 4.48922962e-01 3.46514493e-01
-6.74862802e-01 -6.54117942e-01 -4.50824052e-01 -5.32764614e-01
4.13750380e-01 -1.19336717e-01 5.02912521e-01 8.45195770e-01
4.26749825e-01 1.29838395e+00 -4.45127308e-01 -7.69245028e-01
2.73871869e-01 2.75409102e-01 8.40128958e-01 -1.09428954e+00
-4.18899328e-01 -8.84941459e-01 6.83096290e-01 -9.48031664e-01
5.76139390e-01 -1.30656588e+00 1.96541607e-01 -2.39951372e+00
5.57792425e-01 1.65102109e-01 5.78516185e-01 4.56105262e-01
-5.40932775e-01 -2.53403354e-02 3.22761476e-01 5.20922355e-02
-6.20512366e-01 8.92390430e-01 1.58749115e+00 -1.37819260e-01
-2.28487954e-01 -2.69028306e-01 -1.27454329e+00 4.86349702e-01
7.35530555e-01 -2.95916945e-01 -5.07534444e-01 -7.98234463e-01
4.90556210e-01 3.37267756e-01 2.04270929e-01 -6.53965175e-01
1.43713951e-01 -5.04825294e-01 4.87846613e-01 -6.00592911e-01
1.82994157e-01 4.06636447e-01 -6.12242706e-02 3.27107698e-01
-1.23541760e+00 8.47254992e-02 6.89459220e-02 2.15148225e-01
-6.85061067e-02 -4.74993825e-01 5.20792663e-01 -3.82936627e-01
-2.02707022e-01 -1.56260610e-01 -5.42734683e-01 6.02830708e-01
7.49601066e-01 5.93417436e-02 -9.96623039e-01 -8.84130538e-01
-3.50738198e-01 2.21805617e-01 1.04253963e-01 6.52413964e-01
8.54908049e-01 -1.56717896e+00 -1.43174410e+00 -3.82586449e-01
4.76330221e-02 9.36419740e-02 1.50208334e-02 2.42081583e-01
-4.37256515e-01 6.09212220e-01 -1.02549158e-01 9.58876610e-02
-8.88922393e-01 4.91394848e-02 -7.66560435e-02 -8.35200667e-01
-6.76843166e-01 8.23318005e-01 -1.01412490e-01 -2.48880118e-01
1.08127738e-03 -1.83061585e-01 -3.78363639e-01 2.77430415e-01
9.04708385e-01 3.12850446e-01 -3.84977400e-01 -9.41404924e-02
4.78871554e-01 2.63182595e-02 -2.55578339e-01 -7.18673527e-01
1.36087430e+00 2.82487720e-01 1.62814468e-01 5.08255899e-01
5.25460720e-01 -4.16264832e-02 -1.15056455e+00 -4.62593697e-02
2.00669393e-01 1.52743561e-02 -2.74653733e-01 -1.27717543e+00
-2.34218970e-01 1.05456460e+00 -4.83682036e-01 -2.04649009e-02
4.76950467e-01 7.29629546e-02 1.16792536e+00 6.15194261e-01
3.72409970e-02 -1.40169382e+00 9.21290994e-01 1.08031702e+00
1.44768751e+00 -1.03054345e+00 -9.82941985e-02 9.29502621e-02
-1.29066253e+00 1.19743478e+00 8.00785542e-01 -1.17650323e-01
-3.24261308e-01 1.69929668e-01 -5.39633855e-02 -6.73155710e-02
-1.41816425e+00 5.74495830e-02 2.82572031e-01 4.90091115e-01
9.65887249e-01 9.83955786e-02 -5.84948361e-01 1.15917194e+00
-8.74735892e-01 1.96088701e-01 9.33790624e-01 5.94752431e-01
-4.77868259e-01 -9.79559898e-01 -6.50400296e-02 4.68793094e-01
-2.23640591e-01 -4.02748197e-01 -6.98568583e-01 4.16130036e-01
-4.26806271e-01 9.96498883e-01 5.00657037e-02 1.64089911e-02
1.54707789e-01 4.90176141e-01 6.89866900e-01 -1.08116436e+00
-9.05341446e-01 -1.80040017e-01 7.05634117e-01 -3.89943495e-02
-1.67356402e-01 -4.94506001e-01 -1.42487395e+00 -2.83485770e-01
-1.19052224e-01 1.17987014e-01 3.63979578e-01 1.00286067e+00
3.11402768e-01 1.04189408e+00 2.70853043e-01 -7.69629657e-01
-9.15594578e-01 -1.43386424e+00 2.62491047e-01 4.99558300e-01
-1.23915054e-01 -1.44921064e-01 -4.13688784e-03 4.33319151e-01] | [11.689026832580566, 8.90648365020752] |
e3233783-92d8-4f18-9fde-9915ae0307a2 | real-time-emotion-recognition-via-attention | 1911.09075 | null | https://arxiv.org/abs/1911.09075v1 | https://arxiv.org/pdf/1911.09075v1.pdf | Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network | Real-time emotion recognition (RTER) in conversations is significant for developing emotionally intelligent chatting machines. Without the future context in RTER, it becomes critical to build the memory bank carefully for capturing historical context and summarize the memories appropriately to retrieve relevant information. We propose an Attention Gated Hierarchical Memory Network (AGHMN) to address the problems of prior work: (1) Commonly used convolutional neural networks (CNNs) for utterance feature extraction are less compatible in the memory modules; (2) Unidirectional gated recurrent units (GRUs) only allow each historical utterance to have context before it, preventing information propagation in the opposite direction; (3) The Soft Attention for summarizing loses the positional and ordering information of memories, regardless of how the memory bank is built. Particularly, we propose a Hierarchical Memory Network (HMN) with a bidirectional GRU (BiGRU) as the utterance reader and a BiGRU fusion layer for the interaction between historical utterances. For memory summarizing, we propose an Attention GRU (AGRU) where we utilize the attention weights to update the internal state of GRU. We further promote the AGRU to a bidirectional variant (BiAGRU) to balance the contextual information from recent memories and that from distant memories. We conduct experiments on two emotion conversation datasets with extensive analysis, demonstrating the efficacy of our AGHMN models. | ['Michael R. Lyu', 'Irwin King', 'Wenxiang Jiao'] | 2019-11-20 | null | null | null | null | ['emotion-recognition-in-conversation'] | ['natural-language-processing'] | [-4.01443131e-02 1.26526833e-01 7.16107711e-02 -4.40696269e-01
-5.17920196e-01 -6.27782494e-02 3.73421609e-01 -5.07355817e-02
-3.29968125e-01 6.41293824e-01 7.58656502e-01 -3.57543007e-02
4.23041165e-01 -7.30834603e-01 -4.98517901e-01 -7.43892014e-01
1.38415456e-01 3.39684300e-02 2.61776913e-02 -5.35589516e-01
3.02108735e-01 1.84196413e-01 -1.32575262e+00 5.93393028e-01
6.56334579e-01 1.24698138e+00 4.18579847e-01 7.53577709e-01
-4.29658532e-01 1.52593100e+00 -7.63286531e-01 -2.32973039e-01
-4.57532436e-01 -6.91133440e-01 -1.20594645e+00 -1.25578746e-01
-4.99266922e-01 -3.27869743e-01 -5.76313496e-01 6.40294790e-01
6.00225627e-01 7.81868279e-01 3.40471268e-01 -8.77707064e-01
-8.71596277e-01 8.97750437e-01 -3.45792770e-01 3.24728966e-01
2.86134213e-01 -1.47580564e-01 9.63793993e-01 -9.81502116e-01
5.07868052e-01 1.19157660e+00 4.11695778e-01 8.13555539e-01
-4.10905182e-01 -5.55570424e-01 7.74490356e-01 5.98118424e-01
-1.14248514e+00 -5.87133467e-01 9.12593186e-01 -3.01148240e-02
1.60792553e+00 4.26574320e-01 7.35732913e-01 1.28782773e+00
2.37267345e-01 1.04101646e+00 5.42187572e-01 -2.37096891e-01
2.01345697e-01 -1.14182100e-01 6.26953959e-01 4.91011471e-01
-7.23908365e-01 -2.48713285e-01 -7.79264152e-01 4.40329276e-02
5.51744878e-01 1.90562204e-01 -2.92828918e-01 5.68034649e-01
-6.58367991e-01 7.99132526e-01 5.46702862e-01 6.64467871e-01
-5.07981896e-01 1.29193463e-03 6.18175685e-01 5.15092313e-01
4.71142888e-01 2.90188909e-01 -2.51167953e-01 -2.53990620e-01
-4.87559408e-01 -3.91884625e-01 5.59278131e-01 7.95147359e-01
8.11782718e-01 2.40575895e-01 -2.90413558e-01 1.16083813e+00
2.63692196e-02 -1.73124105e-01 9.85493243e-01 -6.92456961e-01
3.57427478e-01 7.78092980e-01 -1.47088006e-01 -1.03266513e+00
-3.92385781e-01 -2.09348083e-01 -1.09977579e+00 -5.83218694e-01
-4.50156838e-01 -2.30150759e-01 -7.49333799e-01 1.95469761e+00
-4.69998196e-02 2.27735475e-01 2.45872363e-01 8.85423839e-01
1.31605339e+00 1.20041502e+00 2.55675167e-01 -5.67769408e-01
1.17426050e+00 -1.23705101e+00 -1.09049606e+00 -5.97278297e-01
6.16812170e-01 -5.10869980e-01 9.34561968e-01 4.22747731e-02
-1.23429346e+00 -5.52361727e-01 -1.00521302e+00 -4.74633992e-01
-4.19461846e-01 -2.02748075e-01 3.44912857e-01 -1.31961303e-02
-1.05465412e+00 2.55155653e-01 -5.95632732e-01 -2.20520005e-01
-1.76815733e-01 3.85861635e-01 -1.99042276e-01 2.75150836e-01
-1.90979898e+00 1.05557001e+00 3.16591293e-01 8.52047205e-01
-7.11968541e-01 -2.30130404e-02 -9.56295490e-01 3.44892681e-01
1.19031429e-01 -4.40373272e-01 1.16613495e+00 -1.28370583e+00
-1.79555404e+00 4.86609846e-01 -5.33158362e-01 -3.45518172e-01
-1.26610219e-01 -2.41906881e-01 -4.57327336e-01 6.35972992e-02
-5.13913810e-01 5.54364383e-01 6.64666176e-01 -1.09019077e+00
-3.58968645e-01 -3.07442605e-01 -1.54978052e-01 3.85158718e-01
-5.10983765e-01 1.43661097e-01 -4.25360560e-01 -7.10546315e-01
1.36089280e-01 -6.27950966e-01 -1.20603688e-01 -9.88836825e-01
-2.86612660e-01 -3.60130757e-01 1.10599041e+00 -9.34271753e-01
1.92248487e+00 -2.19745302e+00 5.57735145e-01 -7.12078484e-03
8.80190358e-02 1.69128373e-01 -2.10284412e-01 4.68811244e-01
-1.08045943e-01 2.38682851e-02 -7.79675394e-02 -6.15575314e-01
-1.21380687e-01 5.53869665e-01 -6.48256421e-01 -1.79040432e-01
2.66530454e-01 1.22185266e+00 -6.92745924e-01 -4.33448404e-01
-7.77321309e-02 5.21123827e-01 -3.49235028e-01 8.75072896e-01
2.69934572e-02 2.83814311e-01 -3.96828026e-01 4.10328776e-01
1.09329976e-01 -2.43052289e-01 3.50555897e-01 -2.24129885e-01
-8.65439549e-02 5.66795886e-01 -6.92591965e-01 1.35666442e+00
-7.02759206e-01 5.18051147e-01 3.00567627e-01 -8.81462693e-01
1.25612044e+00 6.37529850e-01 6.37220293e-02 -1.02189159e+00
5.01621008e-01 -2.32065380e-01 -1.55238748e-01 -6.02515161e-01
9.35984135e-01 -3.48771870e-01 -3.16904128e-01 7.11361468e-01
2.38711730e-01 4.00206149e-01 -3.23403329e-01 3.81904215e-01
1.03848279e+00 -4.15979773e-01 1.90234676e-01 2.48412475e-01
5.23266315e-01 -7.39886403e-01 9.21275675e-01 4.49092269e-01
-3.35334301e-01 5.86941481e-01 4.91855711e-01 -4.58277255e-01
-5.89538932e-01 -4.64153141e-01 4.52434421e-01 1.76928103e+00
8.35183561e-02 -4.40365136e-01 -6.33915603e-01 -3.94684553e-01
-6.72418833e-01 6.97768629e-01 -8.69612813e-01 -6.87618256e-01
-8.46188605e-01 -7.86158025e-01 4.00393575e-01 9.73231733e-01
6.36316538e-01 -1.76652396e+00 -5.69836557e-01 3.95943224e-01
-7.45614827e-01 -7.99610376e-01 -6.31927252e-01 4.40973610e-01
-5.52639902e-01 -5.38461208e-01 -4.00677890e-01 -8.57435226e-01
5.04525959e-01 1.28674388e-01 1.09559369e+00 3.19991350e-01
2.18023509e-01 2.54883140e-01 -6.71765983e-01 6.47951365e-02
-1.32090017e-01 2.74782330e-01 -1.42317772e-01 2.04549655e-01
2.70122141e-01 -6.62978649e-01 -5.22359073e-01 2.99422801e-01
-8.63596618e-01 1.97580710e-01 4.10621524e-01 1.16872168e+00
2.83882022e-01 -2.48184204e-01 1.08473444e+00 -7.61464357e-01
7.98007071e-01 -7.41889656e-01 1.18809000e-01 4.03590173e-01
-1.58995166e-01 -1.12370402e-01 5.15235484e-01 -5.42642772e-01
-1.43766880e+00 -3.37096781e-01 -4.83313739e-01 -4.04350072e-01
2.55844623e-01 5.85210323e-01 -4.05652434e-01 3.86095107e-01
-1.95354130e-02 2.90914357e-01 -3.08635384e-01 -2.32771665e-01
2.49919638e-01 9.72206175e-01 4.70214218e-01 -6.19941890e-01
-3.51094723e-01 -1.98363867e-02 -8.19847405e-01 -7.70755172e-01
-7.36949384e-01 -2.36720935e-01 -3.79617661e-01 -4.07370687e-01
1.08331215e+00 -6.40042067e-01 -8.24860156e-01 5.03675461e-01
-1.25619078e+00 -5.05232155e-01 2.29485035e-02 1.42159402e-01
-3.04735661e-01 1.87754139e-01 -1.36148000e+00 -1.23479593e+00
-7.86449850e-01 -1.11905158e+00 7.80389607e-01 4.59178925e-01
-5.65929472e-01 -9.90448534e-01 -6.19235896e-02 3.58609915e-01
5.56877375e-01 -1.14782274e-01 1.04719496e+00 -6.17144406e-01
-1.33623376e-01 3.83627787e-02 -1.23780288e-01 2.65041411e-01
-2.08842278e-01 -8.18923861e-02 -1.27555931e+00 -7.11054653e-02
2.95449197e-01 -6.71027899e-01 1.23069859e+00 1.77156672e-01
1.07766783e+00 -5.57935834e-01 -1.09271958e-01 1.14884593e-01
7.99792230e-01 6.57839060e-01 8.72294664e-01 1.43756583e-01
7.61723757e-01 7.16901481e-01 3.60458195e-01 4.34058249e-01
6.47898912e-01 3.24059606e-01 3.04719061e-01 5.30718034e-03
2.47393414e-01 -2.66073525e-01 7.24746704e-01 1.74151993e+00
-6.36142045e-02 -3.26420069e-01 -5.22921026e-01 6.15530550e-01
-2.29100037e+00 -9.03383136e-01 3.99730802e-01 1.71880615e+00
8.67252886e-01 -4.41231877e-02 -2.94156700e-01 -1.63995042e-01
8.61663043e-01 5.17636359e-01 -5.48515141e-01 -9.49904144e-01
-3.29921663e-01 1.05710618e-01 -3.44140112e-01 6.92954063e-01
-7.43206859e-01 9.87774730e-01 5.74764776e+00 6.28007650e-01
-1.21158922e+00 2.76186824e-01 1.05699575e+00 -2.54263043e-01
-3.14862639e-01 -1.85416430e-01 -5.83096027e-01 4.25827235e-01
1.03468549e+00 1.43691689e-01 2.51355469e-01 7.23531365e-01
3.28807756e-02 3.40108983e-02 -8.35469127e-01 9.16151524e-01
1.74344897e-01 -1.13251448e+00 1.07013099e-01 -4.27003294e-01
4.77779627e-01 -2.75061846e-01 3.44824493e-02 8.26816618e-01
2.26855487e-01 -1.04287636e+00 5.55851102e-01 8.01231205e-01
2.03173116e-01 -1.06083345e+00 9.54787314e-01 2.89009988e-01
-1.30799317e+00 -2.67554224e-01 -3.96923333e-01 -1.88257620e-01
3.78880084e-01 1.83782145e-01 -4.50404584e-01 4.70937580e-01
6.54949009e-01 6.19718015e-01 -3.12598467e-01 1.45889565e-01
-1.81315213e-01 5.67393303e-01 4.49211970e-02 -1.17465667e-01
3.78915608e-01 -1.20450288e-01 2.86219388e-01 1.43572104e+00
2.29400754e-01 6.38421714e-01 -7.06350356e-02 6.21722937e-01
-3.39149684e-01 3.69892381e-02 -2.35947803e-01 -2.81216372e-02
7.42207110e-01 1.27937293e+00 -4.01364118e-01 -3.78495425e-01
-1.46321505e-01 1.18773055e+00 7.95394957e-01 4.89299923e-01
-6.60434484e-01 -3.21804523e-01 6.37538195e-01 -3.85471106e-01
2.27950066e-01 -5.17039970e-02 -1.07958481e-01 -1.08433259e+00
-1.53769776e-01 -5.54342508e-01 6.97639763e-01 -1.03080761e+00
-1.21756518e+00 1.06957448e+00 -5.46323061e-01 -6.57965124e-01
-3.23201537e-01 -8.79820138e-02 -1.08447504e+00 7.67739952e-01
-1.26291990e+00 -1.08885169e+00 -2.23145424e-03 5.90949595e-01
8.21929455e-01 1.11286983e-01 9.95854080e-01 3.46097112e-01
-1.20123935e+00 6.51460230e-01 -4.96040612e-01 2.87351668e-01
6.55337214e-01 -8.89101505e-01 -8.60367995e-03 7.76900887e-01
-2.86919057e-01 1.07221305e+00 4.05578405e-01 -6.18811727e-01
-1.35305738e+00 -1.11053813e+00 1.06781137e+00 -1.28304943e-01
5.71229696e-01 -4.66243654e-01 -1.46826351e+00 9.76175129e-01
6.21437252e-01 -4.15886313e-01 9.07275975e-01 3.75847965e-01
-3.04582417e-01 6.93849847e-02 -6.17112994e-01 5.05357862e-01
7.32212901e-01 -8.12989891e-01 -8.11985850e-01 -2.47007027e-01
1.06722367e+00 -2.53492534e-01 -7.73428619e-01 4.24131900e-01
5.92165411e-01 -1.01535082e+00 4.85522598e-01 -6.09212995e-01
5.79505384e-01 -4.42105606e-02 -1.98760495e-01 -1.30144334e+00
-3.55118811e-01 -6.61424100e-01 -4.88609701e-01 1.59573436e+00
2.81919867e-01 -4.50245827e-01 3.67182434e-01 8.33332837e-01
-4.60114211e-01 -1.12653363e+00 -9.62248862e-01 -1.07553843e-02
-2.04829544e-01 -3.81241828e-01 6.34716034e-01 1.14868093e+00
6.14028394e-01 9.35447097e-01 -8.19229066e-01 -4.30492610e-02
-4.25977767e-01 3.49312991e-01 2.53280908e-01 -6.61219895e-01
-1.11421913e-01 -6.05334103e-01 7.47113824e-02 -1.22626555e+00
4.76861000e-01 -4.97983277e-01 2.77526796e-01 -1.47510374e+00
3.21651429e-01 -1.68586746e-01 -5.91337562e-01 5.70520639e-01
-5.63525736e-01 -1.03933506e-01 1.55234963e-01 5.62244058e-02
-1.02846527e+00 1.02185857e+00 1.00239134e+00 9.92918238e-02
-3.23857874e-01 -4.09560263e-01 -7.54908562e-01 5.72014809e-01
6.32902563e-01 7.33738244e-02 -2.74895549e-01 -3.90822589e-01
3.58303338e-01 3.57895106e-01 1.02491099e-02 -4.85122859e-01
6.28379226e-01 1.25716910e-01 3.61777246e-01 -6.99844718e-01
5.04862845e-01 -5.01996338e-01 4.89068292e-02 -1.25625706e-03
-5.57370603e-01 2.40114972e-01 5.42476662e-02 2.72916913e-01
-5.46875477e-01 2.28280108e-02 6.02177858e-01 -2.42699414e-01
-9.29800868e-01 1.79984838e-01 -8.10926914e-01 -1.88793316e-01
5.45079231e-01 7.22323358e-02 -3.99795741e-01 -7.66084909e-01
-9.66517866e-01 6.70708418e-01 -8.22214223e-03 6.46462858e-01
8.84994924e-01 -1.42658675e+00 -2.74027079e-01 2.16200039e-01
-4.92930831e-03 2.77938787e-02 8.68668139e-01 6.42958879e-01
1.35339394e-01 1.87244162e-01 -1.23730235e-01 6.63609244e-03
-1.22797608e+00 5.42585969e-01 4.26472098e-01 -4.83037919e-01
-3.73243570e-01 1.09986973e+00 4.91036087e-01 -4.24414724e-01
3.65196258e-01 -1.93411902e-01 -6.35244846e-01 5.22129118e-01
8.08394432e-01 3.39855999e-01 1.86059773e-01 -8.03719699e-01
-1.18424281e-01 1.20553471e-01 -3.83079827e-01 -7.38905650e-03
1.31632984e+00 -5.54077327e-01 -5.19491494e-01 8.63668203e-01
1.18975735e+00 -3.52840662e-01 -9.52673912e-01 -1.98558912e-01
-1.31282076e-01 1.98459268e-01 1.29236475e-01 -5.75860262e-01
-1.15565252e+00 1.13003373e+00 2.57799458e-02 2.62817562e-01
1.39532363e+00 -3.33233215e-02 1.40657294e+00 3.05747360e-01
-3.95882223e-03 -1.41198802e+00 2.65792787e-01 1.05785728e+00
9.94044423e-01 -8.26961994e-01 -5.69331288e-01 9.12384987e-02
-1.07951355e+00 1.14075053e+00 9.37745452e-01 1.16107315e-01
5.34168005e-01 3.70186925e-01 1.89395905e-01 -2.53766418e-01
-1.39355958e+00 -1.33099973e-01 -5.71910813e-02 8.02792422e-03
5.54923177e-01 -4.71816100e-02 -1.45512223e-01 1.37306952e+00
-7.66116455e-02 -4.31073308e-01 2.10335195e-01 1.01110482e+00
-6.06227934e-01 -8.81952524e-01 -1.18162014e-01 1.19589426e-01
-3.00146401e-01 -2.06088409e-01 -8.87063622e-01 3.20305437e-01
-1.83275685e-01 1.09306526e+00 2.52158225e-01 -7.89899826e-01
2.51214981e-01 5.95122278e-01 -3.66402082e-02 -5.17250240e-01
-1.08935642e+00 2.70376444e-01 1.60280675e-01 -5.55618048e-01
-2.81133950e-01 -2.10575685e-01 -1.61249161e+00 -2.14308560e-01
-4.18337137e-01 4.70440120e-01 1.35343343e-01 1.12747860e+00
5.74513137e-01 8.71603847e-01 8.49329233e-01 -8.03264737e-01
9.26854536e-02 -1.21763873e+00 -4.98268515e-01 2.15064332e-01
3.42994571e-01 -5.13171792e-01 -2.17513710e-01 -1.49964079e-01] | [13.041813850402832, 6.066465377807617] |
0c09b606-3a65-4b27-8d5b-e5fa4b623b03 | 0-1-constrained-optimization-solving-sample | 2210.11889 | null | https://arxiv.org/abs/2210.11889v3 | https://arxiv.org/pdf/2210.11889v3.pdf | 0/1 Constrained Optimization Solving Sample Average Approximation for Chance Constrained Programming | Sample average approximation (SAA) is a tractable approach to deal with the chance constrained programming, a challenging issue in stochastic programming. The constraint is usually characterized by the 0/1 loss function which results in enormous difficulties in designing numerical algorithms. Most existing methods have been created based on the SAA reformulation, such as binary integer programming or the relaxation, and no viable algorithms have been developed to tackle SAA directly, not to mention theoretical guarantees. In this paper, we investigate a general 0/1 constrained optimization that includes SAA as a special case and thus provide a new way to address SAA. We first show that the new model has some advantageous statistic properties. Then by deriving the Bouligand tangent and Frechet normal cones of the 0/1 constraint, we establish several optimality conditions including the one that can be equivalently expressed by a system of equations, thereby allowing us to design a smoothing Newton type method. We show that the proposed algorithm has a locally quadratic convergence rate and nice numerical performance in comparison with two select algorithms and GUROBI. | [] | 2022-10-21 | null | null | null | null | ['face-generation'] | ['computer-vision'] | [ 1.17487617e-01 8.54979530e-02 -4.21620756e-01 -2.44507954e-01
-8.01349342e-01 -6.09008372e-01 1.88955277e-01 7.79723078e-02
-2.96418130e-01 1.09356701e+00 -1.84553295e-01 -3.86830688e-01
-6.78941011e-01 -6.39236808e-01 -6.46169484e-01 -1.17429519e+00
-7.16078728e-02 5.87144256e-01 -1.36420131e-01 -1.54642060e-01
3.25805128e-01 4.65807348e-01 -1.31518984e+00 -5.35096765e-01
1.37189341e+00 1.20299459e+00 1.13381922e-01 3.78583401e-01
-1.58360645e-01 1.22648910e-01 -4.08367068e-01 -3.77678066e-01
5.47532797e-01 -5.10580659e-01 -5.52527010e-01 -3.25208791e-02
5.79265319e-02 -4.82649282e-02 2.24433973e-01 1.41850805e+00
4.41510528e-01 4.60059941e-01 8.63599777e-01 -1.42262220e+00
-3.35465550e-01 6.46136999e-01 -8.37778866e-01 -9.10658110e-03
2.77642787e-01 -2.89798528e-01 1.22742331e+00 -7.55592048e-01
2.79533207e-01 1.29996300e+00 5.53038895e-01 2.96849340e-01
-1.25219536e+00 -5.17539158e-02 2.81258553e-01 -2.19227113e-02
-1.42951703e+00 2.60014497e-02 7.00578570e-01 -2.99072832e-01
2.93758690e-01 7.81386971e-01 5.59296966e-01 5.44311821e-01
-8.10156204e-03 1.06144798e+00 1.33664072e+00 -5.83684921e-01
5.11565924e-01 2.42453381e-01 4.63516951e-01 5.41105270e-01
5.33099294e-01 -2.24210143e-01 3.97992693e-02 -3.12555373e-01
4.08909619e-01 -1.89893261e-01 -4.50236827e-01 -5.70523620e-01
-1.01043355e+00 1.03339875e+00 1.98234916e-01 1.18003920e-01
-3.12249243e-01 -2.67834459e-02 1.91882491e-01 -6.44652396e-02
4.01570231e-01 2.78463542e-01 -1.74368724e-01 1.41012579e-01
-1.11581552e+00 7.13697493e-01 1.12218726e+00 1.02631795e+00
4.14668769e-01 1.47153139e-01 -5.10251880e-01 7.26577520e-01
2.71083951e-01 6.33544147e-01 1.47386447e-01 -7.39084899e-01
5.33901691e-01 2.20383137e-01 4.50477391e-01 -1.20939863e+00
-2.86426246e-01 -6.51402295e-01 -7.97675908e-01 2.33471692e-01
7.32606769e-01 -1.73713073e-01 -4.98819113e-01 1.63288474e+00
3.64864439e-01 -1.42581835e-01 -1.79526228e-02 9.69613731e-01
1.12479158e-01 9.04633522e-01 -4.47937667e-01 -8.67377341e-01
9.82259810e-01 -1.03667068e+00 -8.91978800e-01 2.99578935e-01
4.84357804e-01 -6.49332941e-01 9.88964677e-01 7.92248845e-01
-1.29654121e+00 -7.23328162e-03 -1.08234966e+00 2.15699106e-01
-3.80265713e-01 1.05158903e-01 7.24601150e-01 9.43986535e-01
-8.30464602e-01 5.72903931e-01 -5.18436909e-01 -9.39180627e-02
1.67578906e-01 3.75220597e-01 9.76787284e-02 1.65230338e-03
-9.24073339e-01 8.17532182e-01 3.79016012e-01 6.64493322e-01
-4.73986894e-01 -4.89119202e-01 -7.13840902e-01 2.49323323e-01
8.33147526e-01 -5.71873128e-01 9.70068395e-01 -6.13753915e-01
-1.61841309e+00 5.52221417e-01 -3.42716128e-01 -3.69015247e-01
1.05545282e+00 -2.17260458e-02 8.62749219e-02 -2.85962373e-01
5.73381297e-02 -2.37632781e-01 4.99354035e-01 -1.15886784e+00
-4.80011046e-01 -4.09169555e-01 3.11138391e-01 2.23822325e-01
-1.73754394e-01 1.45013124e-01 -7.67597929e-02 -7.22545445e-01
1.63501725e-01 -6.76067531e-01 -7.78938770e-01 -3.55455726e-01
-6.51925087e-01 -2.37970635e-01 2.46030390e-01 -3.50157380e-01
1.53497529e+00 -1.67219627e+00 4.31158751e-01 6.65486813e-01
-1.93116218e-01 1.71477839e-01 2.99262673e-01 3.38911176e-01
-4.76626456e-02 2.31538132e-01 -6.33866727e-01 -2.97505319e-01
4.09949005e-01 1.01775691e-01 -3.09543818e-01 6.37366712e-01
-1.73370391e-01 4.11924034e-01 -9.76716638e-01 -4.31912661e-01
-2.39576772e-02 2.94068679e-02 -6.27246916e-01 2.46281195e-02
-3.70197237e-01 8.84364992e-02 -7.11732805e-01 7.44995892e-01
1.10883701e+00 1.95050254e-01 6.25387952e-02 9.57421735e-02
-4.31128323e-01 -2.11805910e-01 -1.72087121e+00 1.27249968e+00
-4.79915828e-01 1.97757706e-01 5.34066916e-01 -1.52221262e+00
9.67788041e-01 2.12532859e-02 5.08963704e-01 2.46103555e-02
3.70828390e-01 4.70455080e-01 -2.39056185e-01 -4.09762114e-01
4.46417570e-01 -3.18379849e-01 -2.00601637e-01 8.63690898e-02
-4.86813545e-01 -2.40094751e-01 4.87755507e-01 -1.17156588e-01
5.18333018e-01 -1.09619409e-01 4.59826261e-01 -8.28824043e-01
8.65219116e-01 6.55811429e-02 7.69988358e-01 9.46529329e-01
7.23814638e-03 5.96728921e-01 9.50327814e-01 -4.35395569e-01
-8.39014888e-01 -8.46520960e-01 -4.87700582e-01 4.89248812e-01
1.56559616e-01 -1.03856802e-01 -7.89245844e-01 -3.75946105e-01
1.35183439e-01 7.55854368e-01 -5.46840310e-01 1.97278216e-01
-4.22165215e-01 -1.22465670e+00 -7.47269616e-02 1.53934821e-01
5.47309220e-01 -3.61975670e-01 -1.99599147e-01 2.11165324e-01
3.82969640e-02 -7.43394434e-01 -5.38307667e-01 2.49757513e-01
-7.49617338e-01 -7.69189656e-01 -1.12119865e+00 -5.16462445e-01
6.27923727e-01 8.99464414e-02 7.67872512e-01 -2.42408961e-01
-1.69540524e-01 -3.59251164e-02 -1.64918795e-01 -4.97975498e-01
5.79511784e-02 -3.82276215e-02 2.80477792e-01 2.94126600e-01
3.64702791e-02 -4.49367017e-01 -3.99906844e-01 3.66568565e-01
-8.30883324e-01 -3.34744811e-01 3.97930056e-01 9.77578938e-01
8.52922738e-01 3.88185889e-01 6.49165392e-01 -9.90484834e-01
7.82695949e-01 -5.09905517e-01 -1.23220325e+00 4.34358239e-01
-7.07816601e-01 9.83738229e-02 7.99941182e-01 -9.59775895e-02
-9.40244317e-01 1.99136257e-01 -4.48205434e-02 -2.67464757e-01
2.76767969e-01 7.81478226e-01 -5.02767801e-01 -1.85143635e-01
2.11903676e-01 1.78407058e-01 -2.05503359e-01 -5.01604974e-01
2.99162328e-01 6.29886508e-01 3.70861143e-01 -1.02275896e+00
6.90017283e-01 4.06691790e-01 4.72406298e-01 -7.56363392e-01
-1.05777621e+00 -4.18545872e-01 -4.54288512e-01 -1.71096116e-01
7.47222483e-01 -3.22789788e-01 -9.91365790e-01 1.87587142e-01
-9.69318092e-01 3.52226086e-02 -3.20990831e-01 5.48939228e-01
-8.78826439e-01 4.94846404e-01 -1.36841729e-01 -1.52388620e+00
-2.68293750e-02 -1.31175482e+00 5.95444739e-01 3.72931331e-01
1.83832094e-01 -9.76584733e-01 8.64226930e-03 3.68925631e-01
3.21910560e-01 6.83630526e-01 7.61560440e-01 -4.35475200e-01
-5.09772718e-01 -2.60037452e-01 -1.47464067e-01 4.34297323e-01
-3.24480683e-01 1.31738648e-01 -5.35397828e-01 -3.56492579e-01
4.43510175e-01 -1.82801131e-02 8.26251268e-01 7.99261510e-01
1.22314048e+00 -5.18522799e-01 -2.51559973e-01 9.54369903e-01
1.50046146e+00 2.11624533e-01 3.22568506e-01 3.13331306e-01
3.55107456e-01 5.07778645e-01 9.01915491e-01 7.91773021e-01
9.63121876e-02 6.09309793e-01 4.98858184e-01 1.95840999e-01
6.62906110e-01 5.56938313e-02 1.39079884e-01 7.73844957e-01
-2.71985620e-01 -2.03394622e-01 -7.15438604e-01 5.14593303e-01
-2.12400961e+00 -8.61952901e-01 -4.75391448e-01 2.65156150e+00
7.42163837e-01 1.24388807e-01 1.96179166e-01 3.11243474e-01
8.05364072e-01 1.48607448e-01 -2.60481060e-01 -9.00332332e-01
-2.78889835e-01 1.26594782e-01 8.07513118e-01 8.76258790e-01
-1.03111005e+00 4.82508153e-01 6.84765720e+00 1.26835549e+00
-7.43647397e-01 -1.09335788e-01 6.54707074e-01 -1.67489007e-01
-5.74538946e-01 1.80983067e-01 -9.46629763e-01 7.54798293e-01
3.79613787e-01 -5.09748578e-01 4.15313184e-01 1.08756852e+00
4.86001968e-01 -3.65979910e-01 -8.26568544e-01 8.27397287e-01
-3.38594168e-02 -1.00770581e+00 -9.24375653e-02 3.14247668e-01
1.10402930e+00 -8.89391184e-01 1.91082016e-01 1.43767133e-01
1.15082800e-01 -1.16720366e+00 6.08036757e-01 6.39599860e-01
3.80670398e-01 -1.00424039e+00 1.00199521e+00 4.56870347e-01
-8.76761556e-01 -6.53445125e-02 -6.52450502e-01 -3.54899615e-01
3.64846855e-01 1.01035070e+00 -2.48903841e-01 8.78251851e-01
3.47882420e-01 3.55808884e-01 7.02281445e-02 1.56566787e+00
1.02352716e-01 4.42886472e-01 -6.73398316e-01 -5.02785325e-01
4.25676435e-01 -1.02212477e+00 1.00693500e+00 9.73046243e-01
5.53375781e-01 1.62918866e-01 1.69107124e-01 1.01767981e+00
1.45891622e-01 4.79459703e-01 -4.25800622e-01 1.71641886e-01
2.38590434e-01 1.05761659e+00 -8.78797650e-01 -4.71165106e-02
-4.25490618e-01 6.70859873e-01 1.35076910e-01 3.98907840e-01
-8.80137563e-01 -6.03420794e-01 5.58462858e-01 -1.65618256e-01
2.82642037e-01 -2.60370791e-01 -5.57875633e-01 -1.24897647e+00
4.19019639e-01 -7.53175378e-01 5.08570194e-01 -2.41591871e-01
-1.20665789e+00 4.12814766e-01 2.85495192e-01 -1.01936615e+00
-1.81249410e-01 -8.26068223e-01 -7.24916697e-01 1.09570956e+00
-1.41955483e+00 -7.20244765e-01 -2.62192432e-02 4.26817477e-01
2.46404156e-01 5.14566749e-02 5.79553366e-01 2.89345115e-01
-9.87694383e-01 6.62110806e-01 7.51625597e-01 -4.85512108e-01
2.50557125e-01 -1.52816272e+00 -4.88454551e-01 1.04824674e+00
-4.78437334e-01 5.50087631e-01 1.21951377e+00 -3.28815877e-01
-1.46883595e+00 -5.57748437e-01 9.56306577e-01 -1.60685658e-01
6.92703307e-01 -3.28497440e-01 -6.14918590e-01 4.28015530e-01
-1.02121897e-01 3.20366956e-02 3.90743136e-01 2.01192096e-01
1.92716286e-01 -2.69200861e-01 -1.34694028e+00 4.75550473e-01
7.87521303e-01 2.29100481e-01 -3.55962992e-01 5.93420804e-01
4.95273978e-01 -4.43414778e-01 -7.11451828e-01 3.84603947e-01
3.92763376e-01 -9.95112300e-01 9.29537177e-01 -6.42359495e-01
2.78776467e-01 -2.81158179e-01 -3.45092535e-01 -1.13829720e+00
-1.30533516e-01 -9.92819548e-01 7.55570456e-02 1.32673490e+00
3.76436055e-01 -8.65892410e-01 7.40729451e-01 7.12577283e-01
-9.04378965e-02 -1.27421582e+00 -1.06473279e+00 -1.14136291e+00
2.97134906e-01 -3.06534827e-01 4.76816922e-01 8.59321535e-01
1.46137834e-01 -2.58551240e-01 -4.84024256e-01 1.95866719e-01
8.99700999e-01 4.22542423e-01 5.26248395e-01 -1.00844431e+00
-5.12299538e-01 -8.23052287e-01 -2.80884564e-01 -1.09384274e+00
1.02974042e-01 -8.59505117e-01 7.70600960e-02 -1.33048618e+00
1.61127225e-01 -7.52062917e-01 -2.07721636e-01 -9.93632749e-02
-1.52122825e-01 -2.10575655e-01 8.02388415e-02 2.38523688e-02
-3.13028842e-01 6.57244921e-01 1.21581519e+00 5.57761677e-02
-3.48181576e-01 5.86985648e-01 -6.61513209e-01 8.25185478e-01
6.24865294e-01 -2.41312757e-01 -2.57455111e-01 -1.37613311e-01
4.80679750e-01 2.65728682e-01 3.26899104e-02 -8.00314009e-01
1.43435732e-01 -5.22858262e-01 -8.72167498e-02 -7.23823667e-01
1.95499256e-01 -8.16212058e-01 4.93720137e-02 3.04228723e-01
-3.45929146e-01 -4.17266712e-02 -1.84629232e-01 6.20960355e-01
-2.76306868e-01 -1.04045832e+00 8.04888368e-01 -1.27181932e-01
-1.40288353e-01 2.13777259e-01 -2.79201597e-01 1.26679182e-01
1.16912711e+00 1.54005801e-02 1.56794712e-01 -3.94729108e-01
-9.06073928e-01 6.80421948e-01 2.02955842e-01 -4.21437711e-01
2.34543443e-01 -1.37818360e+00 -6.63834214e-01 -1.40979439e-01
-4.29870903e-01 2.21178606e-01 1.87953144e-01 1.10964966e+00
-7.21891642e-01 6.23224735e-01 4.12058048e-02 -4.27921057e-01
-8.35322917e-01 7.35149562e-01 2.55606413e-01 -4.98972893e-01
-7.76586682e-02 8.56479764e-01 -3.38675119e-02 -2.37046212e-01
3.70295674e-01 -4.26842570e-01 -9.18990597e-02 2.67207980e-01
3.24144691e-01 7.08116472e-01 -1.28317282e-01 -3.96347702e-01
-3.29218686e-01 5.89708924e-01 2.43425593e-01 -1.14164323e-01
1.30788636e+00 -2.07156971e-01 -4.09994572e-01 4.40760195e-01
1.14736247e+00 2.89552599e-01 -8.94492269e-01 -1.24478817e-01
-1.10824615e-01 -7.49970615e-01 6.23971000e-02 -4.91428941e-01
-9.21812534e-01 5.89511991e-01 7.95773938e-02 6.86048329e-01
1.18133068e+00 -2.67890453e-01 5.56114137e-01 3.43860477e-01
5.21537721e-01 -1.17726052e+00 -5.54586589e-01 5.24150431e-01
1.00614393e+00 -1.21519637e+00 1.43942833e-01 -7.60081708e-01
-2.79087722e-01 1.23495817e+00 2.16622144e-01 -3.55381250e-01
6.84702814e-01 1.65601030e-01 -4.04580057e-01 3.42464179e-01
-2.61772156e-01 -3.22242886e-01 1.70937479e-01 3.51561099e-01
2.20475286e-01 2.90559113e-01 -1.21862912e+00 1.13274491e+00
-4.27271396e-01 -1.48010999e-01 6.03472948e-01 5.21965086e-01
-3.22433859e-01 -1.02794719e+00 -5.94969928e-01 4.09952760e-01
-6.00891173e-01 -4.37909365e-02 3.86192687e-02 8.23990464e-01
-6.47734627e-02 7.70995617e-01 -3.45079005e-01 3.39934193e-02
2.59540260e-01 9.46107414e-03 4.38358009e-01 -2.63491124e-01
-1.49852917e-01 1.72570851e-02 -7.43079334e-02 -3.94061267e-01
-3.21075261e-01 -9.63326454e-01 -8.17644715e-01 -3.57219845e-01
-5.76509655e-01 4.74125326e-01 7.53435791e-01 8.49998772e-01
-2.46915042e-01 2.02747181e-01 8.85374427e-01 -8.72917831e-01
-1.03169763e+00 -5.88082671e-01 -1.04393935e+00 -1.71446785e-01
2.87094086e-01 -8.17072034e-01 -7.81036496e-01 -4.97043163e-01] | [6.514327049255371, 4.266393184661865] |
f8e97778-61a1-4f4d-b32a-7eb0fd215c44 | group-sampling-for-unsupervised-person-re | 2107.03024 | null | https://arxiv.org/abs/2107.03024v3 | https://arxiv.org/pdf/2107.03024v3.pdf | Rethinking Sampling Strategies for Unsupervised Person Re-identification | Unsupervised person re-identification (re-ID) remains a challenging task. While extensive research has focused on the framework design and loss function, this paper shows that sampling strategy plays an equally important role. We analyze the reasons for the performance differences between various sampling strategies under the same framework and loss function. We suggest that deteriorated over-fitting is an important factor causing poor performance, and enhancing statistical stability can rectify this problem. Inspired by that, a simple yet effective approach is proposed, termed group sampling, which gathers samples from the same class into groups. The model is thereby trained using normalized group samples, which helps alleviate the negative impact of individual samples. Group sampling updates the pipeline of pseudo-label generation by guaranteeing that samples are more efficiently classified into the correct classes. It regulates the representation learning process, enhancing statistical stability for feature representation in a progressive fashion. Extensive experiments on Market-1501, DukeMTMC-reID and MSMT17 show that group sampling achieves performance comparable to state-of-the-art methods and outperforms the current techniques under purely camera-agnostic settings. Code has been available at https://github.com/ucas-vg/GroupSampling. | ['Jianbin Jiao', 'Gang Pan', 'Jian Zhao', 'Guorong Li', 'Zhenjun Han', 'Qixiang Ye', 'Xuehui Yu', 'Xumeng Han'] | 2021-07-07 | null | null | null | null | ['unsupervised-person-re-identification'] | ['computer-vision'] | [-1.08689331e-02 -1.48209676e-01 -3.75797451e-01 -6.51956737e-01
-6.96246743e-01 -3.52942854e-01 6.98111296e-01 3.38676795e-02
-7.28049219e-01 7.62884259e-01 2.75724828e-01 1.57185867e-01
4.07306701e-02 -5.27733088e-01 -5.31937242e-01 -6.66591525e-01
1.80649802e-01 6.53524637e-01 2.57068351e-02 2.32938021e-01
3.06128472e-01 4.16395992e-01 -1.83005047e+00 -9.05716568e-02
9.13795233e-01 4.73495722e-01 1.40432656e-01 4.66846138e-01
-5.94713874e-02 4.30709600e-01 -6.52330935e-01 -8.20511103e-01
4.57438409e-01 -4.74727601e-01 -7.21162736e-01 1.73750237e-01
7.15487123e-01 -4.86213177e-01 -1.92987889e-01 1.03468919e+00
8.93692017e-01 3.41139078e-01 8.59938622e-01 -1.22904563e+00
-5.11184394e-01 5.36007643e-01 -7.20841825e-01 -1.72707997e-02
3.19065750e-01 -2.27029055e-01 8.82250667e-01 -8.90268326e-01
5.06364644e-01 1.43397236e+00 7.54460573e-01 9.84685600e-01
-1.36946595e+00 -1.00008643e+00 1.69131637e-01 2.62043625e-01
-1.56333172e+00 -7.37107217e-01 4.31089073e-01 -3.62288237e-01
5.06757319e-01 3.31933945e-01 3.70107263e-01 1.15852988e+00
-2.34129176e-01 9.66814995e-01 1.00265837e+00 -5.65667093e-01
1.20109476e-01 5.90450704e-01 4.92142707e-01 3.39233518e-01
4.57340896e-01 -2.26276331e-02 -5.28571129e-01 -3.55461061e-01
5.51103294e-01 1.21779524e-01 -1.94450736e-01 -4.24111277e-01
-7.65957773e-01 8.58559608e-01 3.08311701e-01 1.01106733e-01
-1.36167824e-01 -9.32325497e-02 5.04096687e-01 1.35311961e-01
6.07136905e-01 3.41052413e-01 -1.65071011e-01 -1.11838497e-01
-1.08684111e+00 5.47802210e-01 5.68658233e-01 9.42163229e-01
6.55397534e-01 -3.60035509e-01 -2.13409573e-01 1.24060130e+00
2.37322286e-01 3.18237126e-01 6.92807555e-01 -9.58099008e-01
2.87784010e-01 7.01746762e-01 2.23889485e-01 -7.78546333e-01
-2.67551482e-01 -5.00888288e-01 -7.15777636e-01 9.03746262e-02
7.05146134e-01 1.60494242e-02 -7.42866457e-01 1.77401018e+00
3.77260298e-01 1.16126560e-01 -2.37569571e-01 9.08688664e-01
7.07011640e-01 2.06944153e-01 2.24507213e-01 -3.80878821e-02
1.52397907e+00 -8.05810511e-01 -6.01042986e-01 -2.35827893e-01
5.12729704e-01 -6.20204866e-01 8.82296681e-01 2.31528610e-01
-8.60615969e-01 -6.90261722e-01 -8.51612806e-01 -1.82390362e-02
-4.10278261e-01 4.51977462e-01 5.92827260e-01 1.01811802e+00
-8.41438890e-01 5.91912508e-01 -4.22843903e-01 -7.99834192e-01
5.34961462e-01 3.63498539e-01 -4.44753259e-01 -2.32593983e-01
-9.41335559e-01 6.90201998e-01 3.90487053e-02 -7.73860514e-02
-4.16559964e-01 -6.87439620e-01 -6.86408341e-01 -2.36336395e-01
7.81919286e-02 -5.46415746e-01 1.21667457e+00 -8.87078583e-01
-1.30128062e+00 1.08174872e+00 -5.46462655e-01 -5.78333020e-01
9.49544847e-01 -2.70909667e-01 -2.51021594e-01 -6.19736947e-02
3.51646006e-01 8.91626894e-01 8.59528422e-01 -1.40408945e+00
-7.03060508e-01 -4.89538282e-01 -2.62469292e-01 3.05288941e-01
-4.99784440e-01 2.79333621e-01 -6.25377774e-01 -5.80906034e-01
-1.74541190e-01 -9.99990523e-01 -1.35754898e-01 -1.81856379e-01
-2.90710241e-01 -5.22195935e-01 4.43685353e-01 -6.41423643e-01
1.25443494e+00 -2.00775743e+00 -1.32083029e-01 1.81349605e-01
1.08645558e-01 3.14064801e-01 7.92231336e-02 2.29795456e-01
-1.33411527e-01 1.05418123e-01 -6.08060025e-02 -1.05306375e+00
-2.26076432e-02 -7.71518201e-02 -8.34343210e-02 6.89975500e-01
-1.74766481e-01 5.59275687e-01 -7.70573676e-01 -4.74756956e-01
2.13245615e-01 4.38656390e-01 -4.14222181e-01 2.25671530e-01
3.43012720e-01 4.10581082e-01 -1.77045867e-01 6.18628383e-01
9.96425390e-01 -8.22809339e-02 1.15644112e-01 -6.19905517e-02
-1.39632337e-02 9.33691785e-02 -1.43535709e+00 1.20517361e+00
4.26016860e-02 4.45114851e-01 -3.25533487e-02 -8.67648244e-01
1.06957388e+00 -7.34041408e-02 2.79956907e-01 -6.40600085e-01
1.30845129e-01 1.13103777e-01 -2.23143697e-01 -1.37825042e-01
8.59744430e-01 9.67521071e-02 7.36631081e-02 5.02238393e-01
-1.75116658e-01 4.30339843e-01 2.32589230e-01 2.37974495e-01
5.57536006e-01 2.15521440e-01 3.35818350e-01 -2.98722506e-01
4.06418473e-01 -1.38994321e-01 6.95351362e-01 1.05372536e+00
-4.82097417e-01 8.61307323e-01 1.10101864e-01 -8.78707469e-02
-1.15132272e+00 -8.96893144e-01 -3.57753664e-01 1.24390519e+00
1.76411077e-01 -4.60661769e-01 -9.83790755e-01 -7.31228590e-01
2.62770206e-01 7.19732046e-01 -8.46884608e-01 -1.01677328e-01
-5.33025861e-01 -9.85321283e-01 5.60089231e-01 4.36815321e-01
6.23403907e-01 -6.94994688e-01 -2.78298676e-01 5.85493632e-02
-2.39494264e-01 -8.32084179e-01 -6.35259092e-01 -2.47157499e-01
-6.86179280e-01 -1.14012730e+00 -1.06569159e+00 -6.64680600e-01
1.04086781e+00 5.84645212e-01 9.06066358e-01 1.23935662e-01
-3.02108586e-01 3.76133442e-01 -4.32707638e-01 -4.89810288e-01
-2.79507190e-01 2.49732867e-01 2.92738020e-01 2.18775243e-01
8.00692618e-01 -1.37135670e-01 -6.55438006e-01 6.39040232e-01
-4.70061272e-01 -1.03615679e-01 2.29447022e-01 8.30006838e-01
4.07176942e-01 -1.91636849e-02 7.16104031e-01 -1.05799353e+00
5.19447207e-01 -4.32378531e-01 -3.89187455e-01 1.06062435e-01
-7.92847157e-01 -1.96031719e-01 5.16065240e-01 -5.86519718e-01
-1.08669162e+00 -1.98124768e-03 -1.05025750e-02 -2.12762132e-01
-1.79912731e-01 -9.38553885e-02 -1.79782927e-01 8.84772539e-02
6.07640684e-01 2.64079839e-01 3.09770048e-01 -7.48992860e-01
4.08100858e-02 9.04671729e-01 3.54022175e-01 -4.73628968e-01
6.54591858e-01 6.02298558e-01 -3.86493832e-01 -7.53186584e-01
-6.69965804e-01 -7.83557236e-01 -5.92517912e-01 -3.02949190e-01
5.47691643e-01 -1.12340629e+00 -5.55429995e-01 6.87770665e-01
-7.91767001e-01 -2.43493766e-01 -9.26031694e-02 4.57228363e-01
-1.46765083e-01 4.30689573e-01 -4.26126540e-01 -9.66735125e-01
-3.52133632e-01 -9.34852183e-01 1.03071010e+00 5.95084488e-01
-5.23949206e-01 -7.80663610e-01 -1.51796758e-01 5.41828454e-01
2.21810624e-01 -5.91871217e-02 2.37113848e-01 -7.89788723e-01
-1.97009265e-01 -4.64430660e-01 -3.19671452e-01 3.36265743e-01
1.52196467e-01 -8.82255360e-02 -1.24203825e+00 -6.70891762e-01
-3.72585088e-01 -7.34219141e-03 8.90597105e-01 4.82905567e-01
1.17975247e+00 4.85537089e-02 -6.41537905e-01 5.61992347e-01
1.10944414e+00 -1.04519643e-01 6.57010436e-01 6.19539082e-01
6.64259374e-01 8.86419654e-01 7.15097964e-01 5.26746809e-01
7.30660439e-01 8.56325626e-01 -2.52852459e-02 -2.08358262e-02
-2.18171284e-01 -3.29501778e-01 3.31270397e-01 2.62820929e-01
-5.31978086e-02 -4.96690720e-02 -6.30892634e-01 4.92636412e-01
-1.92841840e+00 -1.09652185e+00 -1.99652731e-01 2.49178362e+00
7.64915109e-01 -8.21630061e-02 6.53299391e-01 1.58757284e-01
1.05376160e+00 -1.19929649e-01 -5.10614872e-01 3.36826928e-02
-1.44562900e-01 -3.11450481e-01 7.92018354e-01 4.72984642e-01
-1.01590919e+00 8.26949537e-01 6.23230457e+00 8.47131670e-01
-7.24603295e-01 4.28242609e-02 7.33043015e-01 -6.96284249e-02
8.32052901e-02 -3.15465033e-01 -1.38124144e+00 8.17012370e-01
8.05489659e-01 -2.67994821e-01 3.02855521e-01 8.36482525e-01
2.72265673e-01 -3.12849969e-01 -1.01301360e+00 1.22233868e+00
3.23127568e-01 -8.97541463e-01 -1.20905511e-01 2.32890368e-01
5.68652272e-01 -2.02958301e-01 -1.18784411e-02 2.94401914e-01
3.15146029e-01 -7.43009031e-01 8.11694622e-01 5.90964794e-01
7.26211667e-01 -8.92098129e-01 9.25313950e-01 2.05702841e-01
-1.14865935e+00 -1.14813320e-01 -5.89787424e-01 8.47002212e-03
-2.17623487e-02 6.86620951e-01 -9.78409171e-01 6.11875057e-01
9.57811594e-01 7.36834764e-01 -1.06737685e+00 1.20960164e+00
1.03276409e-02 7.29265928e-01 -1.33333236e-01 1.37637913e-01
-3.51270348e-01 -1.97227195e-01 4.28335279e-01 1.31658340e+00
1.52132764e-01 -2.03296363e-01 6.32864982e-02 6.10546827e-01
2.40217783e-02 2.41497736e-02 -4.44569349e-01 4.13063496e-01
8.50071549e-01 1.19122756e+00 -7.28747070e-01 -4.12886113e-01
-3.38857949e-01 1.07401872e+00 4.44094419e-01 2.68563867e-01
-7.30179250e-01 -2.57048994e-01 8.15942407e-01 3.04312259e-01
1.50830820e-01 -5.20612113e-03 -3.10702056e-01 -1.05658090e+00
-5.71298227e-02 -8.30967247e-01 6.21244490e-01 -2.84687281e-01
-1.61080074e+00 2.98981458e-01 1.56590834e-01 -1.27504992e+00
-2.92992711e-01 -3.80853742e-01 -4.04359281e-01 9.04657483e-01
-1.48788881e+00 -9.25957739e-01 -5.19784570e-01 4.44517851e-01
5.08054137e-01 -2.61977464e-01 6.28111899e-01 5.39814889e-01
-9.42096412e-01 1.22774541e+00 2.25471199e-01 2.58107722e-01
1.20650125e+00 -1.29285634e+00 4.54395562e-01 8.95118833e-01
-3.53480816e-01 8.45920682e-01 7.28501618e-01 -6.99129403e-01
-1.01188242e+00 -1.15624952e+00 9.18600440e-01 -6.16897106e-01
1.68274611e-01 -6.09548151e-01 -8.38866591e-01 4.22578275e-01
-1.79059729e-01 -3.10070843e-01 9.13858414e-01 7.93115944e-02
-3.03379536e-01 -1.62727386e-01 -1.46603990e+00 6.29020631e-01
1.17702007e+00 -4.06876117e-01 -3.66952479e-01 1.11372195e-01
2.62553751e-01 -1.67733535e-01 -7.38343954e-01 6.09877668e-02
6.66786194e-01 -1.00646150e+00 9.97760177e-01 -1.25514522e-01
-1.79736078e-01 -3.33638519e-01 4.09833938e-02 -1.27241731e+00
-5.14891565e-01 -5.65583527e-01 2.00029239e-02 1.77791488e+00
1.14787623e-01 -1.03366339e+00 9.55201209e-01 9.55364048e-01
2.81532854e-01 -3.88159871e-01 -7.61260033e-01 -9.21539068e-01
1.91829950e-02 -2.25825384e-01 8.23497534e-01 9.50585067e-01
-2.80952036e-01 1.29033804e-01 -5.03480852e-01 -1.01180952e-02
1.09800529e+00 -3.19541931e-01 1.16261566e+00 -1.40332377e+00
7.23844543e-02 -4.37334150e-01 -2.67714351e-01 -9.52100515e-01
2.55022168e-01 -7.95522273e-01 -1.15230352e-01 -1.34084237e+00
5.40025592e-01 -6.32385135e-01 -4.52316180e-02 3.25782895e-01
-4.43667948e-01 3.89768749e-01 2.80387819e-01 4.66729403e-01
-5.35888255e-01 3.38958681e-01 9.40118551e-01 1.67662963e-01
-2.05108777e-01 2.02530965e-01 -9.57271516e-01 4.02845234e-01
9.50503111e-01 -3.71925056e-01 -2.31018096e-01 -1.61899537e-01
-2.52596825e-01 -7.06049204e-01 4.13970590e-01 -9.98916149e-01
3.23897094e-01 1.90103605e-01 6.36553407e-01 -5.04134119e-01
2.32463896e-01 -7.30369985e-01 1.98858663e-01 3.70088786e-01
-3.75231057e-01 2.54608598e-03 -7.84009881e-03 4.24714923e-01
1.25216573e-01 -4.52003509e-01 9.15716588e-01 -4.11312915e-02
-6.45226240e-01 2.90157169e-01 -1.27968937e-01 -1.26172960e-01
8.59262347e-01 -5.63059986e-01 -2.85726160e-01 -2.65853256e-01
-3.79767567e-01 3.82507294e-01 7.93560505e-01 5.18065095e-01
2.64340669e-01 -1.33484221e+00 -8.95752490e-01 3.38788837e-01
1.77507550e-01 -2.08128452e-01 2.04174563e-01 6.61492348e-01
-3.97427380e-02 7.21362382e-02 3.13451290e-02 -5.95341980e-01
-1.63297760e+00 1.42529994e-01 3.20302933e-01 -4.50227857e-02
-5.24939299e-01 8.65117848e-01 7.58986399e-02 -6.14374816e-01
4.65528071e-01 2.18242303e-01 -4.10906911e-01 4.72745031e-01
1.04293466e+00 8.22038591e-01 -6.96485415e-02 -7.93226898e-01
-4.71591741e-01 5.17383873e-01 -6.23002470e-01 8.44003707e-02
1.19219279e+00 -4.14742887e-01 5.30170798e-02 2.20237091e-01
1.17468083e+00 -4.03234735e-02 -1.31018043e+00 -2.78284550e-01
-3.69206257e-02 -7.33237565e-01 -2.75201410e-01 -5.58743298e-01
-7.51685441e-01 3.23012263e-01 8.04168940e-01 2.05017149e-01
8.34501505e-01 4.37078252e-02 5.38234353e-01 -5.89004206e-03
4.80191946e-01 -1.28960168e+00 -1.47237107e-01 2.49329984e-01
6.12446904e-01 -1.48026431e+00 2.55020827e-01 -4.63614464e-01
-6.91473603e-01 7.94032454e-01 6.93465173e-01 -1.06638297e-01
3.39957714e-01 -3.73872556e-02 -2.61431411e-02 2.08272666e-01
-1.74291939e-01 -1.64300740e-01 1.71205580e-01 7.37958193e-01
4.27916229e-01 2.20597923e-01 -3.09971958e-01 6.31828308e-01
-4.23575133e-01 -4.37383540e-02 3.73834938e-01 7.54696131e-01
-1.99353158e-01 -1.29930151e+00 -7.21219957e-01 6.58231199e-01
-4.57540423e-01 2.52227366e-01 -3.82911831e-01 8.41614962e-01
1.42818302e-01 9.70783293e-01 1.36686236e-01 -3.00323308e-01
3.32660377e-01 2.93161776e-02 4.30945724e-01 -5.57696223e-01
-5.69531500e-01 -1.37061223e-01 2.61845440e-01 -3.89031887e-01
-5.42439520e-01 -1.24165714e+00 -9.67840314e-01 -5.61776161e-01
-4.12930548e-01 2.31166959e-01 4.83422697e-01 6.13672197e-01
3.94641668e-01 1.63996622e-01 6.94280386e-01 -1.00326192e+00
-5.75834095e-01 -1.08627367e+00 -6.29854679e-01 6.47413194e-01
2.52775788e-01 -8.50203931e-01 -5.67663908e-01 -1.91543661e-02] | [14.745272636413574, 1.0548495054244995] |
6af6b043-2000-46e4-8e5c-8bedb117044d | towards-an-imu-based-pen-online-handwriting | 2105.12434 | null | https://arxiv.org/abs/2105.12434v1 | https://arxiv.org/pdf/2105.12434v1.pdf | Towards an IMU-based Pen Online Handwriting Recognizer | Most online handwriting recognition systems require the use of specific writing surfaces to extract positional data. In this paper we present a online handwriting recognition system for word recognition which is based on inertial measurement units (IMUs) for digitizing text written on paper. This is obtained by means of a sensor-equipped pen that provides acceleration, angular velocity, and magnetic forces streamed via Bluetooth. Our model combines convolutional and bidirectional LSTM networks, and is trained with the Connectionist Temporal Classification loss that allows the interpretation of raw sensor data into words without the need of sequence segmentation. We use a dataset of words collected using multiple sensor-enhanced pens and evaluate our model on distinct test sets of seen and unseen words achieving a character error rate of 17.97% and 17.08%, respectively, without the use of a dictionary or language model | ['Bjoern Eskofier', 'Dario Zanca', 'Peter Kaempf', 'Jens Barth', 'Tim Hamann', 'Mohamad Wehbi'] | 2021-05-26 | null | null | null | null | ['handwriting-recognition'] | ['computer-vision'] | [ 4.12458986e-01 -4.27202910e-01 -2.54368305e-01 -8.24408308e-02
-6.11443445e-02 -7.16038287e-01 5.18073797e-01 1.18543811e-01
-9.41801727e-01 6.05922461e-01 -3.32052588e-01 -6.98837459e-01
-1.42931014e-01 -6.44864202e-01 -9.26739693e-01 -3.06225687e-01
3.93674046e-01 5.34620464e-01 1.16677545e-01 -6.24958724e-02
4.41766292e-01 1.00467002e+00 -8.83185148e-01 -1.27100259e-01
3.70360494e-01 9.19663906e-01 3.70557785e-01 1.29990995e+00
-2.44788185e-01 5.54098010e-01 -1.03344405e+00 -2.73574293e-01
9.35253799e-02 -9.39176902e-02 -4.35444623e-01 1.02230851e-02
4.13455039e-01 -8.74879956e-01 -7.60508835e-01 6.36772156e-01
5.71950614e-01 -9.02906135e-02 3.19232285e-01 -4.40677762e-01
-7.13479221e-01 6.46751761e-01 -3.74736302e-02 1.65524423e-01
4.77047116e-01 -5.21705039e-02 4.33532536e-01 -6.46596611e-01
7.85829961e-01 5.12990475e-01 8.94934237e-01 4.69477862e-01
-1.02350998e+00 -2.54880458e-01 -2.95742810e-01 1.75113901e-01
-1.22200036e+00 -2.59435743e-01 6.75342500e-01 -3.22977602e-01
1.70444846e+00 1.85276940e-01 7.13719249e-01 1.70832300e+00
3.88881892e-01 8.73870492e-01 5.94893992e-01 -6.53186500e-01
3.81452739e-01 -2.08955154e-01 4.90513235e-01 5.51099300e-01
1.63679361e-01 -1.14390738e-01 -1.04923916e+00 1.62361786e-01
1.12307894e+00 1.95406437e-01 -2.81311542e-01 9.38450322e-02
-1.20383668e+00 -7.40080886e-03 1.24533828e-02 2.96199173e-01
-3.13016593e-01 3.59030604e-01 3.12037736e-01 1.76438361e-01
-4.42890190e-02 3.15737933e-01 -3.16351563e-01 -9.41093385e-01
-8.86698067e-01 -3.44676316e-01 9.57461178e-01 1.19252384e+00
-2.50179060e-02 3.89718473e-01 1.51455104e-01 5.07115841e-01
1.94818512e-01 9.39224005e-01 8.73676121e-01 -1.59193382e-01
7.24953115e-01 4.44414914e-01 2.77285278e-01 -8.88766110e-01
-4.60346729e-01 -2.58877873e-02 -5.66280901e-01 -2.29482934e-01
4.35879886e-01 -3.77139270e-01 -1.14639652e+00 9.21350479e-01
-5.48742294e-01 4.03251946e-01 -2.63310403e-01 1.01352334e+00
2.77869970e-01 2.23003849e-01 -3.84966850e-01 7.42049664e-02
7.32980549e-01 -5.00727117e-01 -1.03562450e+00 -1.83855481e-02
3.02229553e-01 -4.89319116e-01 1.08219397e+00 5.93194902e-01
-8.51337373e-01 -5.09055674e-01 -1.60984468e+00 -3.05354148e-01
-6.93942428e-01 5.06244779e-01 3.96528900e-01 7.94722736e-01
-8.89657557e-01 9.05519187e-01 -1.55494380e+00 -4.29046005e-01
1.34669552e-02 7.10506320e-01 -9.89664569e-02 6.30976200e-01
-9.82688487e-01 9.79210913e-01 6.55432269e-02 4.69369262e-01
-3.49917412e-01 -1.45223379e-01 -5.86133718e-01 -2.81806469e-01
-2.63840646e-01 6.78598881e-02 9.45670962e-01 -4.21429992e-01
-2.16169953e+00 4.17003691e-01 -2.20495656e-01 -6.91671908e-01
8.45550895e-01 -4.39056039e-01 -5.28039694e-01 1.13512293e-01
-5.65641999e-01 -6.68904930e-02 9.06436741e-01 -4.45735425e-01
-1.93497553e-01 -4.16555882e-01 -5.95210671e-01 -1.44314840e-01
-8.45644772e-01 -2.44008094e-01 -6.53669775e-01 -5.32372713e-01
1.59531936e-01 -6.90345168e-01 5.77237606e-01 -1.72463849e-01
-6.13703609e-01 1.26939774e-01 1.03792882e+00 -1.16549313e+00
9.94843662e-01 -1.69530392e+00 1.02677688e-01 2.56855488e-01
-1.72304407e-01 6.27237022e-01 8.73504207e-02 2.45050266e-01
5.79109609e-01 -2.10685551e-01 -2.94316970e-02 -4.87308532e-01
3.70055474e-02 3.41972172e-01 -9.64579701e-01 4.19963419e-01
1.51982918e-01 8.51933539e-01 -8.24479759e-01 1.35333300e-01
7.11982071e-01 6.64473414e-01 2.21843660e-01 -3.12780440e-02
-1.58709034e-01 6.90179989e-02 -1.98605090e-01 8.12882364e-01
2.36855090e-01 3.71139832e-02 4.27369148e-01 1.00107670e-01
-9.43613648e-02 7.24871159e-01 -1.01558173e+00 1.67623425e+00
-5.62605500e-01 1.30428016e+00 -2.08058923e-01 -4.79343295e-01
1.25639009e+00 1.47484154e-01 1.02062477e-02 -6.59021497e-01
4.13141429e-01 4.44331557e-01 -5.10184109e-01 -4.50089604e-01
9.41072345e-01 6.22573853e-01 2.02199787e-01 6.49933100e-01
9.71416309e-02 9.74144712e-02 5.79849444e-03 -2.37294152e-01
1.14083457e+00 4.50321972e-01 -6.83421373e-01 2.65166581e-01
5.50326519e-02 -2.43052304e-01 8.92797038e-02 9.60304499e-01
6.44472055e-03 5.47122955e-01 -4.72822413e-02 -4.91590530e-01
-1.15893149e+00 -1.02661204e+00 -2.96721399e-01 5.50273716e-01
3.46575379e-01 -1.37605563e-01 -4.68198717e-01 -1.17938884e-01
3.42170924e-01 6.39937639e-01 -9.31573287e-02 1.10367343e-01
-7.75944769e-01 -4.11549091e-01 1.05292892e+00 1.06122112e+00
5.39016783e-01 -7.94971764e-01 -1.00843847e+00 5.99175513e-01
2.62535185e-01 -1.23817599e+00 -1.16518699e-01 3.12949747e-01
-8.23970795e-01 -7.47529447e-01 -5.99817216e-01 -5.89166760e-01
5.13827026e-01 -2.75278986e-01 4.22232151e-01 -3.06325287e-01
-3.29698861e-01 6.09758615e-01 -2.58725137e-01 -2.95158684e-01
6.38149530e-02 4.73926485e-01 5.77551067e-01 -5.09733669e-02
9.11126673e-01 -4.19727802e-01 9.93933342e-03 1.83640674e-01
-5.08781314e-01 8.77257213e-02 2.22504258e-01 6.81433499e-01
3.71023357e-01 -6.45092487e-01 -6.69302493e-02 1.02682039e-01
9.70814109e-01 1.41564369e-01 -6.83493316e-01 3.34952831e-01
-5.13900399e-01 -2.87913904e-03 8.68367612e-01 -7.45818257e-01
-5.52319109e-01 2.40094569e-02 -2.77010147e-02 -3.81327927e-01
-3.15742642e-02 2.92801738e-01 2.38489032e-01 -2.44053707e-01
4.11223561e-01 7.87115633e-01 -1.78220913e-01 -6.65747106e-01
-7.41364136e-02 1.56983757e+00 9.69150484e-01 -2.26186022e-01
2.79796049e-02 4.51937526e-01 -2.52841800e-01 -1.35552645e+00
2.95641869e-01 1.35762751e-01 -8.14944088e-01 -3.03645521e-01
5.17473280e-01 -2.96170563e-01 -1.27765977e+00 1.15715086e+00
-1.46964669e+00 -6.24111712e-01 1.55386534e-02 6.64639652e-01
-4.00976896e-01 3.99981856e-01 -1.22371995e+00 -1.01219547e+00
-4.03105527e-01 -8.58843148e-01 1.10754204e+00 3.38887900e-01
-3.73232961e-01 -9.74114299e-01 -3.79619360e-01 1.96618922e-02
5.05370498e-01 -2.76833922e-02 1.81784913e-01 -4.40212458e-01
-5.47938228e-01 -8.01929057e-01 8.46977457e-02 3.41862947e-01
2.09767506e-01 2.02765033e-01 -9.10598159e-01 -3.44781071e-01
8.54295620e-04 -2.32681856e-01 7.49859571e-01 1.61115035e-01
1.14396143e+00 9.47932433e-03 -3.82106751e-01 7.19085872e-01
1.26982641e+00 5.40164351e-01 5.36158800e-01 3.73412699e-01
9.29203510e-01 -2.69606382e-01 -6.51015192e-02 6.05135918e-01
1.84864640e-01 5.62452555e-01 -1.41349077e-01 4.02944654e-01
6.61615655e-02 -5.66145003e-01 4.44581956e-01 9.92453933e-01
-2.03524098e-01 -5.00030100e-01 -1.27723956e+00 5.29821575e-01
-1.55723798e+00 -3.89207542e-01 5.21384776e-02 2.11583018e+00
9.35756564e-01 2.86373764e-01 -2.88078696e-01 4.67361748e-01
8.44730735e-01 -5.53778931e-02 -9.01468217e-01 -7.10326254e-01
-1.27629861e-01 3.36751580e-01 1.29358780e+00 8.47419322e-01
-8.79547834e-01 1.02141464e+00 6.42028475e+00 3.02998632e-01
-1.92043233e+00 -4.47600514e-01 1.64475888e-01 -2.29270577e-01
2.67310351e-01 -6.21091247e-01 -1.01842618e+00 8.16441596e-01
1.17609560e+00 2.25053951e-01 6.95368171e-01 4.21214134e-01
5.67257628e-02 -1.13682285e-01 -1.22683036e+00 1.14341784e+00
1.30014703e-01 -1.34363198e+00 -4.99718301e-02 -3.05521697e-01
1.68133765e-01 1.69309258e-01 5.04150949e-02 -3.53764445e-01
-1.04271919e-01 -9.01773036e-01 7.69638240e-01 1.05188453e+00
1.12432027e+00 -3.02966863e-01 5.53774536e-01 3.18126649e-01
-5.66342831e-01 2.12446734e-01 -2.20949590e-01 -6.68737650e-01
1.83941752e-01 3.09631795e-01 -1.11370170e+00 1.04009159e-01
2.41447672e-01 7.64545977e-01 -1.56095624e-01 5.13634324e-01
-2.43193820e-01 8.64540339e-01 -9.29883301e-01 -8.82921457e-01
-5.89227229e-02 -1.71808735e-01 5.32225072e-01 1.27602613e+00
3.39983881e-01 -2.69506514e-01 -4.73748624e-01 7.48391211e-01
-1.11626185e-01 -5.89767933e-01 -4.88730371e-01 -5.28562963e-01
7.26534367e-01 5.72157681e-01 -5.50819337e-01 -1.82899073e-01
-3.00933998e-02 1.48476946e+00 -3.02859638e-02 4.14744049e-01
-4.53487873e-01 -1.16628587e+00 2.40974069e-01 -1.75590232e-01
3.06629837e-01 -1.19063699e+00 -9.79345739e-01 -1.24875391e+00
6.27336621e-01 -2.91270435e-01 -4.75383550e-01 -6.65219963e-01
-8.77086461e-01 3.63697559e-01 -8.54640067e-01 -8.40351105e-01
-5.81010997e-01 -1.20381367e+00 -1.67207643e-01 1.09716785e+00
-1.06888700e+00 -6.83228850e-01 -2.67639309e-01 3.33281457e-01
3.43620181e-01 -4.41713482e-01 9.06457365e-01 9.80804712e-02
-6.64237916e-01 8.28016520e-01 6.16208971e-01 6.99320316e-01
3.89067173e-01 -1.20907712e+00 1.00640535e+00 7.98464656e-01
2.22921610e-01 7.61191905e-01 3.98745447e-01 -8.25951457e-01
-2.22271466e+00 -7.37133026e-01 1.14124548e+00 -7.77035832e-01
7.26714730e-01 -6.71492934e-01 -5.35426080e-01 8.99011254e-01
-1.61534160e-01 -2.44381860e-01 4.58308160e-01 -3.06801051e-01
-4.54245508e-02 -5.37351631e-02 -9.57858443e-01 4.83537585e-01
1.00150979e+00 -1.13139582e+00 -6.31877899e-01 2.47290358e-01
1.21232532e-01 -1.05033267e+00 -7.71766007e-01 -8.54617357e-02
1.02423704e+00 -4.28765953e-01 6.37647510e-01 -5.31722069e-01
2.46071994e-01 -1.10857107e-01 1.41594326e-02 -8.50883782e-01
2.35333711e-01 -7.87989378e-01 -5.12578726e-01 7.81933188e-01
3.34243864e-01 -9.18279886e-01 8.14561069e-01 1.04353368e+00
2.33648732e-01 -4.88407284e-01 -1.00196970e+00 -1.06300199e+00
-3.58057737e-01 -8.64815176e-01 4.80580926e-01 7.82631695e-01
5.08325517e-01 9.39974636e-02 -3.46067607e-01 1.38181880e-01
4.22778577e-01 -1.79048076e-01 3.44538957e-01 -5.76111555e-01
-3.09091628e-01 -3.35130572e-01 -8.05817008e-01 -1.59385800e+00
-8.19814391e-03 -5.42320848e-01 -1.62831128e-01 -1.25275731e+00
-7.00391650e-01 -8.52363408e-02 -6.63000671e-03 5.00232935e-01
5.04396737e-01 1.64313674e-01 -1.53935803e-02 1.41344488e-01
-2.32688099e-01 2.65608400e-01 6.36115432e-01 -4.36400801e-01
-3.22414517e-01 -1.24998190e-01 3.94233137e-01 4.47340399e-01
6.93834007e-01 2.05889791e-01 1.09287977e-01 -1.26724398e+00
2.10103065e-01 6.12444133e-02 2.77487695e-01 -1.06029737e+00
8.14854324e-01 3.37105036e-01 8.77313077e-01 -5.52574933e-01
3.28936517e-01 -6.21489704e-01 -3.12224567e-01 6.97939456e-01
-3.73516858e-01 2.59393118e-02 4.89201158e-01 4.35562313e-01
8.48222151e-02 -3.99935022e-02 4.14432958e-02 5.93942583e-01
-5.97060442e-01 -2.42812127e-01 -6.92116201e-01 -8.54894698e-01
6.02098286e-01 -4.78077352e-01 -3.19097996e-01 -2.11536825e-01
-6.08953238e-01 -1.23501115e-01 3.84467900e-01 7.50330865e-01
7.71724761e-01 -1.08127069e+00 -1.81548521e-01 7.92211592e-01
-5.91193736e-01 -2.43813902e-01 -3.49892229e-01 3.69791240e-01
-1.13607013e+00 1.02539408e+00 -1.18712373e-01 -5.76533258e-01
-9.05466735e-01 -8.62081274e-02 5.48315108e-01 4.34116393e-01
-7.15579033e-01 8.37268651e-01 -1.66298425e+00 -2.32174143e-01
6.87852979e-01 -6.83760464e-01 2.87230909e-01 -2.00396091e-01
5.91568768e-01 6.57688916e-01 4.98569429e-01 -6.98750168e-02
-5.50777495e-01 5.01304924e-01 -6.07277378e-02 -4.97361571e-01
1.09537268e+00 3.02189440e-01 9.21965018e-02 8.15944493e-01
8.28082144e-01 -3.54059100e-01 -1.36269939e+00 -4.65651937e-02
2.09402293e-01 -5.34924388e-01 1.90321039e-02 -9.87422824e-01
-5.56626797e-01 9.94901240e-01 7.62685120e-01 1.72110155e-01
4.85297680e-01 -7.19008088e-01 1.09695959e+00 1.11167037e+00
5.64878404e-01 -1.74535346e+00 -4.33649600e-01 1.20809472e+00
6.29901886e-01 -6.62305236e-01 -4.35738593e-01 4.37760592e-01
-1.11577153e-01 1.58460271e+00 2.47799248e-01 -1.98638201e-01
3.33835065e-01 8.79110873e-01 1.46518752e-01 2.65962571e-01
-2.68639594e-01 3.40021402e-01 -2.62947440e-01 5.42003810e-01
3.47376049e-01 2.51863748e-01 -4.67558920e-01 6.35124624e-01
-2.43730024e-01 3.80614698e-01 5.87725520e-01 1.30293715e+00
-3.88223566e-02 -8.98223937e-01 -3.01338911e-01 5.64930081e-01
-1.11885183e-01 1.15594208e-01 -7.61700392e-01 1.38327166e-01
-3.07084620e-01 6.46778584e-01 7.06173897e-01 -8.51207554e-01
3.44164371e-01 2.26928756e-01 7.74024308e-01 9.14926231e-02
-2.59881854e-01 -5.43845892e-01 -1.03505254e-01 -2.45693147e-01
1.59871727e-01 -5.36240220e-01 -1.41608346e+00 -3.19196612e-01
-4.67599422e-01 -4.47898030e-01 1.51766706e+00 1.12071311e+00
5.85706651e-01 5.02759457e-01 3.17158908e-01 -1.02132952e+00
-7.16027021e-01 -1.06276262e+00 -7.10482299e-01 5.00449464e-02
4.97772664e-01 -2.25380346e-01 4.49034199e-02 1.00427151e-01] | [11.872705459594727, 2.539796829223633] |
6250c7c2-2a4c-4bf0-affb-0fee8967c993 | docdiff-document-enhancement-via-residual | 2305.03892 | null | https://arxiv.org/abs/2305.03892v1 | https://arxiv.org/pdf/2305.03892v1.pdf | DocDiff: Document Enhancement via Residual Diffusion Models | Removing degradation from document images not only improves their visual quality and readability, but also enhances the performance of numerous automated document analysis and recognition tasks. However, existing regression-based methods optimized for pixel-level distortion reduction tend to suffer from significant loss of high-frequency information, leading to distorted and blurred text edges. To compensate for this major deficiency, we propose DocDiff, the first diffusion-based framework specifically designed for diverse challenging document enhancement problems, including document deblurring, denoising, and removal of watermarks and seals. DocDiff consists of two modules: the Coarse Predictor (CP), which is responsible for recovering the primary low-frequency content, and the High-Frequency Residual Refinement (HRR) module, which adopts the diffusion models to predict the residual (high-frequency information, including text edges), between the ground-truth and the CP-predicted image. DocDiff is a compact and computationally efficient model that benefits from a well-designed network architecture, an optimized training loss objective, and a deterministic sampling process with short time steps. Extensive experiments demonstrate that DocDiff achieves state-of-the-art (SOTA) performance on multiple benchmark datasets, and can significantly enhance the readability and recognizability of degraded document images. Furthermore, our proposed HRR module in pre-trained DocDiff is plug-and-play and ready-to-use, with only 4.17M parameters. It greatly sharpens the text edges generated by SOTA deblurring methods without additional joint training. Available codes: https://github.com/Royalvice/DocDiff | ['Xing Zhang', 'Junjie Zhou', 'Ziqi Liu', 'Xiaojun Tang', 'Guibin Wu', 'Lan Yi', 'Yongping Xiong', 'Baolin Liu', 'Zongyuan Yang'] | 2023-05-06 | null | null | null | null | ['document-enhancement', 'deblurring'] | ['computer-vision', 'computer-vision'] | [ 3.05232048e-01 -5.51835239e-01 4.66046147e-02 2.94287712e-03
-7.78854847e-01 -2.49913722e-01 5.15047669e-01 -1.65449128e-01
-6.31047711e-02 3.63768756e-01 5.71870267e-01 -1.05183549e-01
5.82454912e-02 -5.58599234e-01 -4.27418619e-01 -1.05927753e+00
1.37863621e-01 -3.00290734e-01 6.06331453e-02 1.12797059e-02
2.53073603e-01 3.10740590e-01 -1.19456959e+00 3.58159482e-01
1.12681699e+00 1.08441854e+00 4.62451160e-01 9.51860487e-01
2.64891595e-01 7.80404389e-01 -5.75004280e-01 -3.78798246e-01
5.08583523e-02 -1.68329164e-01 -3.12621057e-01 1.60722151e-01
5.49070656e-01 -8.00913513e-01 -8.84508729e-01 1.18114567e+00
8.72518063e-01 8.00795034e-02 6.04442775e-01 -6.81192636e-01
-1.32874751e+00 2.94027150e-01 -1.03354466e+00 2.08191887e-01
1.55317053e-01 3.30048174e-01 7.17667878e-01 -1.20403886e+00
5.56661129e-01 1.09915423e+00 9.12617564e-01 4.57623571e-01
-1.11198986e+00 -5.67923307e-01 -4.36383523e-02 4.10748661e-01
-1.43473089e+00 -6.69442475e-01 8.09924901e-01 -2.21231326e-01
8.17713678e-01 2.74726003e-01 2.05070779e-01 1.12215316e+00
4.17133123e-01 9.75106180e-01 9.84875858e-01 -3.89804542e-01
-8.22064579e-02 -3.13890994e-01 2.49988392e-01 5.42436719e-01
2.87917733e-01 1.25595048e-01 -5.67896545e-01 2.05273986e-01
6.62241220e-01 9.90861580e-02 -1.07082021e+00 -6.10653087e-02
-8.98686826e-01 2.13816836e-01 3.31343085e-01 3.29523116e-01
-3.43818724e-01 2.69546267e-03 2.35195190e-01 7.62039423e-02
5.03450334e-01 -4.63564731e-02 -2.54119158e-01 -1.58104181e-01
-1.22815275e+00 -2.68769413e-02 3.38458568e-01 6.38020396e-01
4.39040989e-01 1.18314708e-02 -5.40337324e-01 1.18555176e+00
2.76765555e-01 7.10726917e-01 6.30969822e-01 -6.61213338e-01
6.56555831e-01 2.33928189e-01 5.48279919e-02 -1.30519426e+00
-4.31456827e-02 -5.93396604e-01 -1.45896220e+00 5.22193499e-02
8.70500579e-02 7.45086232e-03 -1.11611366e+00 1.17600751e+00
6.73861206e-02 8.05931538e-02 -1.25241941e-02 1.11064708e+00
5.45569062e-01 1.08562768e+00 -3.00269991e-01 -2.50965327e-01
1.26412773e+00 -1.14298332e+00 -9.66264844e-01 -2.66483784e-01
2.84139425e-01 -1.00747991e+00 1.08084905e+00 6.86513066e-01
-1.14661586e+00 -6.38958395e-01 -1.24622095e+00 -4.33764338e-01
-9.34118554e-02 5.51080048e-01 5.75886928e-02 6.50469005e-01
-9.81588542e-01 6.34418428e-01 -6.09023631e-01 2.35677860e-03
6.17431998e-01 1.18142823e-02 -2.54126966e-01 -7.09139764e-01
-1.00102198e+00 7.39414454e-01 4.21972573e-02 4.39518124e-01
-7.84502804e-01 -6.43659294e-01 -7.03601599e-01 2.40156561e-01
1.45712852e-01 -4.33169365e-01 8.01544189e-01 -7.38241553e-01
-1.57665455e+00 5.44452488e-01 -2.29462892e-01 -2.02111930e-01
7.00781345e-01 -4.75780010e-01 -6.50153697e-01 2.69463450e-01
-2.32397512e-01 2.22867981e-01 1.32088971e+00 -1.30920315e+00
-3.06926876e-01 -5.01576781e-01 -6.60709202e-01 1.40945137e-01
-6.56255186e-01 -1.32332101e-01 -1.08793855e+00 -1.28489208e+00
4.66348976e-02 -4.57221717e-01 2.88567364e-01 2.59171098e-01
-4.03398305e-01 3.17135155e-01 1.18145728e+00 -1.59327543e+00
1.48428071e+00 -2.57837033e+00 5.17265610e-02 -1.34756774e-01
1.37154415e-01 6.40047729e-01 -4.84731644e-01 1.97333589e-01
2.51888614e-02 -2.80249920e-02 -3.84924293e-01 -6.04771078e-01
-8.06501582e-02 -3.31303984e-01 -4.18505222e-01 6.89386904e-01
2.31253933e-02 7.93691754e-01 -6.46757901e-01 -2.41007969e-01
2.88104892e-01 1.01646984e+00 -1.53873235e-01 1.38354823e-01
-1.28208194e-02 -3.09011005e-02 -1.07129805e-01 7.25413859e-01
1.37745929e+00 -1.79405496e-01 -3.43108289e-02 -5.44133902e-01
-2.11385489e-02 -1.16666751e-02 -1.24889660e+00 1.58126807e+00
-4.16887283e-01 1.02465260e+00 3.78299683e-01 -4.86855626e-01
8.57408345e-01 1.02886640e-01 6.22533001e-02 -8.82851899e-01
1.16690315e-01 2.04968140e-01 -6.48145914e-01 -4.78941381e-01
7.98984706e-01 4.50604051e-01 5.15282631e-01 3.37186396e-01
-2.60247946e-01 3.87127958e-02 -9.74558294e-03 1.79423407e-01
1.11106133e+00 8.10009539e-02 -1.13355488e-01 1.11338548e-01
6.43469334e-01 -4.07238036e-01 3.98789197e-01 5.52833438e-01
-2.98357420e-02 1.04111683e+00 1.49589375e-01 2.48261113e-02
-1.09797418e+00 -8.24569523e-01 -1.29472658e-01 7.44024873e-01
5.21153390e-01 -3.09657514e-01 -8.68939221e-01 -4.15233493e-01
-9.06100646e-02 6.33151174e-01 -3.15091729e-01 -3.05457085e-01
-4.55650806e-01 -8.07843268e-01 5.04556596e-01 3.95613611e-01
9.32483077e-01 -6.24925077e-01 4.97807935e-02 8.97592083e-02
-3.29356372e-01 -9.91369426e-01 -1.17186666e+00 -1.05436765e-01
-6.73919559e-01 -8.81535411e-01 -1.22476768e+00 -8.54525924e-01
8.15609097e-01 8.33768189e-01 6.45560861e-01 1.77178770e-01
-3.60356361e-01 1.43437177e-01 -3.64231378e-01 1.25608832e-01
-2.76164383e-01 -3.00239205e-01 -3.50263983e-01 2.79829949e-01
1.68483406e-01 -3.03791612e-01 -9.33323741e-01 4.17938292e-01
-1.15721440e+00 3.90662514e-02 7.93949485e-01 1.20844638e+00
3.64820480e-01 4.69642699e-01 1.83613807e-01 -3.41245532e-01
9.01849926e-01 -3.77464406e-02 -5.06545305e-01 2.36188412e-01
-1.00105345e+00 -1.35787144e-01 7.14390516e-01 -5.55915117e-01
-1.34282017e+00 -4.07193184e-01 1.54931694e-01 -3.21677536e-01
6.93972483e-02 5.20688593e-01 -3.21553588e-01 -8.13431963e-02
6.42228305e-01 6.83493137e-01 -1.91851822e-03 -7.82738686e-01
3.28455001e-01 1.25545382e+00 9.25806582e-01 -1.80999190e-01
8.66566598e-01 4.22583938e-01 -3.42395246e-01 -9.32934940e-01
-5.40493965e-01 -4.74400759e-01 -1.24403141e-01 -2.20767215e-01
4.27065581e-01 -1.15325630e+00 -3.96868020e-01 1.36222816e+00
-1.20547748e+00 -4.40990299e-01 -3.29804532e-02 2.96765000e-01
-5.75717986e-02 9.50191498e-01 -1.00383115e+00 -5.92521369e-01
-7.68167555e-01 -9.02473211e-01 1.09723747e+00 4.81723934e-01
2.44812444e-01 -6.48673713e-01 -2.68897504e-01 5.33715904e-01
5.72441220e-01 -2.45692819e-01 7.91966021e-01 1.99338228e-01
-5.85189700e-01 -3.46345395e-01 -7.00093150e-01 8.95699441e-01
2.06261441e-01 -1.21208213e-01 -1.08621883e+00 -7.36996949e-01
-2.14403383e-02 -2.65969168e-02 1.25047123e+00 6.12307668e-01
1.18580437e+00 -2.99637944e-01 -1.80892929e-01 7.68308401e-01
1.47337735e+00 7.74334148e-02 1.17052662e+00 3.37060124e-01
6.65612519e-01 1.78671628e-01 5.55312574e-01 5.24477184e-01
2.41730496e-01 7.59651601e-01 1.58329919e-01 -3.16345811e-01
-8.13813210e-01 -1.60856575e-01 7.09478259e-01 7.93477356e-01
2.21305981e-01 -6.53027356e-01 -7.08279967e-01 5.83100915e-01
-1.71676242e+00 -8.30905318e-01 -1.33301198e-01 2.15808582e+00
1.14082348e+00 2.51016561e-02 -3.69429350e-01 3.27219307e-01
1.02801549e+00 5.61665595e-01 -6.03426874e-01 -1.91682782e-02
-4.84167010e-01 3.22092627e-03 5.50713897e-01 6.04327559e-01
-1.04226661e+00 7.22368538e-01 5.19968987e+00 1.20865595e+00
-1.23009086e+00 -4.01492082e-02 7.75080919e-01 7.52731189e-02
6.96249306e-03 -2.60987937e-01 -6.50690079e-01 7.36082792e-01
6.14717245e-01 5.42449951e-02 6.26210690e-01 5.07652998e-01
5.88321924e-01 -6.28669336e-02 -6.17673814e-01 1.05427837e+00
3.21264774e-01 -1.38327157e+00 -5.18388674e-02 -2.25470811e-02
8.02871048e-01 -2.71336794e-01 3.64617705e-01 -2.03493431e-01
4.89499792e-03 -9.03425813e-01 6.94888234e-01 6.67132199e-01
1.01512003e+00 -5.85407436e-01 6.92907333e-01 1.88032433e-01
-1.07724094e+00 -1.48483410e-01 -3.72438222e-01 3.87519896e-01
6.91916123e-02 1.20961642e+00 -2.67316312e-01 5.60374439e-01
7.67844737e-01 1.09125245e+00 -3.76237899e-01 1.17687786e+00
-4.42131639e-01 6.11344934e-01 6.93345815e-02 2.53803730e-01
-1.70905575e-01 -1.78482383e-01 6.14963114e-01 1.52805293e+00
4.32899892e-01 -1.18697314e-02 -2.90067881e-01 6.39475346e-01
-3.28780621e-01 -2.34521538e-01 5.47002517e-02 1.14552744e-01
4.03193384e-01 1.20394838e+00 -3.12397480e-01 -2.01301292e-01
-2.27661043e-01 1.50295591e+00 -2.60220379e-01 6.52336359e-01
-7.23286271e-01 -8.92386317e-01 6.16073310e-01 8.49299952e-02
6.55145466e-01 -2.84412146e-01 -3.96469295e-01 -1.37720644e+00
5.70978045e-01 -1.19632864e+00 1.55256791e-02 -1.13357985e+00
-1.17088485e+00 3.90972108e-01 -7.07286954e-01 -1.19710171e+00
3.87316912e-01 -6.13946736e-01 -4.42755371e-01 1.16959512e+00
-1.97194171e+00 -1.16618609e+00 -7.87510335e-01 4.13839668e-01
6.74662828e-01 7.57016465e-02 3.77032697e-01 5.19297481e-01
-8.99479926e-01 6.36553586e-01 7.50739157e-01 1.37457207e-01
1.06951404e+00 -9.86448705e-01 6.00458026e-01 1.34595835e+00
-3.54847729e-01 3.76275510e-01 5.25356710e-01 -7.15245843e-01
-1.59969664e+00 -1.20594299e+00 7.04400063e-01 1.22018106e-01
3.79055172e-01 -1.52381852e-01 -1.17830944e+00 7.51449019e-02
1.62389994e-01 -5.39186485e-02 1.47260338e-01 -4.53482330e-01
-4.93431509e-01 -3.63491684e-01 -1.14970386e+00 5.76982439e-01
6.92891836e-01 -6.69810176e-01 -2.09190801e-01 1.50949359e-01
4.49323356e-01 -4.81790662e-01 -6.55369997e-01 5.05214706e-02
5.57126760e-01 -9.23645139e-01 1.07586730e+00 2.36559942e-01
7.62663782e-01 -4.90582913e-01 7.86128920e-03 -1.25687754e+00
-5.13860464e-01 -9.18347538e-01 -6.42604649e-01 1.50005162e+00
8.03586468e-02 -4.75940764e-01 6.31483436e-01 2.49138430e-01
-1.22689195e-01 -5.43866158e-01 -6.09195709e-01 -7.79308140e-01
-2.82207787e-01 -2.01602504e-01 4.36047584e-01 7.57952690e-01
-2.87576348e-01 1.12364151e-01 -7.25888252e-01 4.91249919e-01
7.62196422e-01 -1.39660314e-01 5.02715766e-01 -8.11654270e-01
-3.11847538e-01 -3.72031242e-01 -2.30213657e-01 -1.80570436e+00
-3.12128663e-01 -4.28707153e-01 2.77146250e-01 -1.66492105e+00
2.21901119e-01 -1.16957702e-01 -7.49428719e-02 2.72306353e-01
-4.40783262e-01 2.89851993e-01 1.10647418e-01 5.32708049e-01
-2.82935321e-01 7.06487298e-01 1.43151343e+00 -6.75126672e-01
-1.53491646e-01 -2.92495608e-01 -7.41742671e-01 4.07190502e-01
4.61227179e-01 -2.79496670e-01 -1.32396132e-01 -8.65372360e-01
-4.07194383e-02 -1.15199812e-01 4.84826833e-01 -9.28114653e-01
4.03937876e-01 2.35460903e-02 8.06564033e-01 -5.47901273e-01
1.90841332e-01 -6.80095136e-01 -4.21098918e-02 3.73061568e-01
-1.46553829e-01 -3.26656491e-01 1.83794916e-01 6.22717083e-01
-3.46484184e-01 -2.23267153e-01 1.13252962e+00 3.40524256e-01
-5.64515710e-01 1.10598661e-01 -2.70669550e-01 -3.11977178e-01
7.40826905e-01 -4.27148938e-01 -8.59285474e-01 -4.53606904e-01
-2.33623534e-01 -3.27350274e-02 6.17919981e-01 3.64745885e-01
8.58065248e-01 -9.61828232e-01 -8.78201187e-01 1.87402129e-01
-2.29500055e-01 1.05811181e-02 7.12332547e-01 7.38730073e-01
-6.88666046e-01 2.82406867e-01 1.31330222e-01 -3.35316479e-01
-1.35293114e+00 3.55056614e-01 3.33249122e-01 -3.62490743e-01
-9.13708508e-01 8.50961924e-01 -7.29172230e-02 2.23732755e-01
3.92689884e-01 -2.93672353e-01 3.49560357e-03 -1.30613431e-01
9.56393361e-01 6.80508792e-01 2.65565544e-01 -4.98477072e-01
-1.16873495e-01 7.17694044e-01 -4.62354153e-01 1.37357220e-01
1.46486580e+00 -4.42815602e-01 -9.82307345e-02 -2.48926148e-01
1.17823005e+00 2.25627571e-01 -1.67021203e+00 -2.73598284e-01
-3.74485314e-01 -7.63323724e-01 7.93822765e-01 -1.11815345e+00
-1.25437915e+00 8.06396127e-01 8.06856930e-01 -3.56974173e-03
1.73865712e+00 -6.20107174e-01 1.14931607e+00 -6.02245778e-02
-1.19834602e-01 -1.14736760e+00 4.36516166e-01 3.20897639e-01
1.05863357e+00 -8.59849036e-01 3.32740009e-01 -3.71512055e-01
-4.85408813e-01 1.15012801e+00 3.23740780e-01 1.80508167e-01
3.84452909e-01 2.96669751e-01 1.04509607e-01 2.08764181e-01
-5.77522099e-01 3.05242956e-01 2.88588732e-01 7.43909597e-01
2.60514915e-01 -2.62449265e-01 -5.50719276e-02 5.37498891e-01
3.30395728e-01 2.11773932e-01 6.03185773e-01 9.29632187e-01
-3.18683684e-01 -8.25287700e-01 -6.60298944e-01 3.82620811e-01
-3.52455407e-01 -4.30380523e-01 -9.36216563e-02 1.19085856e-01
1.85627770e-02 1.05469096e+00 -1.42169610e-01 -3.53915632e-01
2.98227042e-01 -4.19836044e-01 2.19166189e-01 -3.15870009e-02
-3.66225630e-01 1.61953345e-01 -2.29594693e-01 -3.42451513e-01
-1.07842378e-01 -5.30251801e-01 -8.26068878e-01 -5.89899778e-01
-7.59334683e-01 -1.99898273e-01 6.85259163e-01 5.49554467e-01
7.59945095e-01 5.42631507e-01 8.06490600e-01 -8.13316941e-01
-5.29362559e-01 -1.06804574e+00 -7.74802804e-01 2.72845566e-01
7.75330544e-01 -2.08587438e-01 -5.91194808e-01 4.95037943e-01] | [11.276101112365723, -2.2823166847229004] |
04c79104-12d6-4b92-a037-b7beac94daf9 | neural-crossbreed-neural-based-image | 2009.00905 | null | https://arxiv.org/abs/2009.00905v1 | https://arxiv.org/pdf/2009.00905v1.pdf | Neural Crossbreed: Neural Based Image Metamorphosis | We propose Neural Crossbreed, a feed-forward neural network that can learn a semantic change of input images in a latent space to create the morphing effect. Because the network learns a semantic change, a sequence of meaningful intermediate images can be generated without requiring the user to specify explicit correspondences. In addition, the semantic change learning makes it possible to perform the morphing between the images that contain objects with significantly different poses or camera views. Furthermore, just as in conventional morphing techniques, our morphing network can handle shape and appearance transitions separately by disentangling the content and the style transfer for rich usability. We prepare a training dataset for morphing using a pre-trained BigGAN, which generates an intermediate image by interpolating two latent vectors at an intended morphing value. This is the first attempt to address image morphing using a pre-trained generative model in order to learn semantic transformation. The experiments show that Neural Crossbreed produces high quality morphed images, overcoming various limitations associated with conventional approaches. In addition, Neural Crossbreed can be further extended for diverse applications such as multi-image morphing, appearance transfer, and video frame interpolation. | ['Sanghun Park', 'Kwanggyoon Seo', 'Junyong Noh'] | 2020-09-02 | null | null | null | null | ['image-morphing'] | ['computer-vision'] | [ 5.92630684e-01 2.63952911e-01 -1.98080689e-02 -4.21306074e-01
-4.50550854e-01 -5.32331109e-01 5.35901070e-01 -5.45542538e-01
-1.01886056e-01 4.61775959e-01 2.45038643e-02 2.20655650e-02
3.94397527e-01 -1.07287931e+00 -1.29399419e+00 -6.70126081e-01
3.41001689e-01 3.07274163e-01 7.47411251e-02 -2.93118864e-01
-1.00192264e-01 4.17718887e-01 -1.44470823e+00 4.55158055e-01
8.91015649e-01 8.74643564e-01 3.27105373e-01 7.01053500e-01
-2.26324067e-01 4.65330243e-01 -6.41928256e-01 -5.76125741e-01
6.11608982e-01 -1.00913167e+00 -7.58239627e-01 4.04258221e-01
8.27033460e-01 -5.12263536e-01 -2.45529398e-01 1.08656943e+00
1.83105275e-01 9.91234109e-02 5.68960428e-01 -1.42826664e+00
-1.28969550e+00 3.56488526e-01 -3.71902645e-01 -4.68918771e-01
4.51239169e-01 3.41922730e-01 8.12038064e-01 -7.90917397e-01
7.00273573e-01 1.42501485e+00 6.74775183e-01 7.85412312e-01
-1.46893883e+00 -8.26934576e-01 -8.71419013e-02 -4.46168184e-02
-1.14603281e+00 -3.00023854e-01 1.06816864e+00 -4.14776266e-01
3.87888014e-01 1.64058000e-01 1.02646720e+00 1.13517928e+00
1.54524922e-01 6.79062903e-01 9.36704338e-01 -4.20470774e-01
1.00680655e-02 -7.77741103e-03 -6.65408194e-01 9.34677839e-01
-2.50047818e-02 8.80026296e-02 -4.50441957e-01 3.03224087e-01
1.27483881e+00 2.22341672e-01 -3.83544654e-01 -5.79330504e-01
-1.37188792e+00 7.58197784e-01 7.76824176e-01 1.34289742e-01
-2.43886575e-01 4.07579392e-01 8.33066329e-02 4.45814103e-01
3.02125067e-01 8.19518805e-01 -3.40734631e-01 2.54176050e-01
-9.23081517e-01 1.04489721e-01 5.57329416e-01 9.49428558e-01
1.21135831e+00 3.78735512e-01 -1.42395630e-01 6.56995475e-01
1.90532804e-01 4.83330011e-01 5.15307784e-01 -1.26996219e+00
3.77125829e-01 4.95821625e-01 5.48346608e-04 -1.08111894e+00
2.53588051e-01 -1.26817739e-02 -9.87887383e-01 4.14291799e-01
2.58710146e-01 -1.57002836e-01 -1.16317892e+00 1.93977141e+00
1.54334739e-01 2.36689121e-01 1.21303938e-01 6.62840903e-01
7.03691840e-01 8.81656647e-01 -1.06574789e-01 4.82591018e-02
1.18460667e+00 -1.19673574e+00 -7.81868935e-01 -3.03071380e-01
1.20268568e-01 -7.68897712e-01 1.32842791e+00 1.86642453e-01
-1.24224591e+00 -8.28333318e-01 -1.10565853e+00 -2.22474620e-01
-4.14137125e-01 -2.36760870e-01 6.23032153e-01 2.90619969e-01
-1.19978476e+00 6.60268247e-01 -7.73915827e-01 -2.43133515e-01
3.42960477e-01 3.41659933e-01 -6.34366751e-01 6.80957660e-02
-1.14669454e+00 7.80890286e-01 4.71342057e-01 9.01023746e-02
-7.82044470e-01 -7.77725160e-01 -1.23760998e+00 1.06551370e-03
-6.75591230e-02 -1.11038756e+00 9.60435569e-01 -1.81821287e+00
-2.00453854e+00 8.44179451e-01 3.47908330e-03 -7.99547210e-02
4.64467436e-01 4.36519682e-02 -2.75491804e-01 -5.63275963e-02
8.48517269e-02 1.23250198e+00 1.16718948e+00 -1.45760906e+00
-3.44426870e-01 -9.61187705e-02 1.16810672e-01 2.77662963e-01
-2.13868231e-01 -2.44802505e-01 -6.42311156e-01 -1.03007078e+00
1.63080413e-02 -9.04908121e-01 -1.98499396e-01 2.90303260e-01
-2.14176804e-01 3.50111991e-01 1.12871504e+00 -7.54397869e-01
6.63231075e-01 -2.08903837e+00 5.94524324e-01 6.58207014e-03
4.20572087e-02 1.92117259e-01 -4.83781248e-01 3.36704046e-01
-2.86310405e-01 9.27754566e-02 -4.92592841e-01 -3.75096858e-01
-1.48702770e-01 4.46744829e-01 -2.65357077e-01 1.85163766e-01
3.25220555e-01 1.25297523e+00 -9.63254333e-01 -2.54884809e-01
2.34066904e-01 6.12873435e-01 -8.67968619e-01 6.58078313e-01
-4.12688881e-01 8.73236656e-01 1.21497260e-02 1.58304632e-01
6.13016188e-01 -1.86856613e-01 -7.88939893e-02 -4.83188063e-01
1.54007122e-01 -7.16193616e-02 -9.35691893e-01 2.12259436e+00
-7.61931598e-01 8.07629108e-01 -9.28470269e-02 -8.97726297e-01
8.48035812e-01 1.93812773e-01 4.15505260e-01 -6.35367870e-01
1.09140813e-01 -7.72557640e-03 -2.90821522e-01 -4.43303406e-01
5.84623575e-01 -3.92645568e-01 -2.38337874e-01 4.97692198e-01
3.15471917e-01 -6.30785048e-01 -2.32730597e-01 -3.43589410e-02
5.20393848e-01 3.48557562e-01 1.88929476e-02 2.28932977e-01
2.48185873e-01 -3.99910957e-01 4.93504643e-01 2.80773491e-01
3.82127583e-01 9.52558100e-01 2.20461458e-01 -5.80711484e-01
-1.14632177e+00 -1.17972314e+00 2.26706401e-01 7.39752531e-01
3.05196822e-01 -1.73539177e-01 -9.74513292e-01 -6.12465262e-01
-2.52076387e-01 5.59795022e-01 -5.98005950e-01 -4.71691608e-01
-7.36801445e-01 -3.12183082e-01 3.47139180e-01 3.72557253e-01
7.83840537e-01 -1.24247706e+00 -2.70633936e-01 1.15697883e-01
-3.55451941e-01 -1.03456426e+00 -9.95795965e-01 -7.42360996e-03
-8.07472646e-01 -8.59049380e-01 -8.24944198e-01 -1.13677013e+00
1.13415861e+00 7.21034855e-02 9.17067230e-01 4.98386985e-03
-2.89640158e-01 1.35989383e-01 -2.00218186e-01 3.75654250e-02
-8.67230356e-01 -3.18167210e-02 -2.66945630e-01 3.21493983e-01
-2.76041627e-01 -8.57074797e-01 -6.54367566e-01 2.25302771e-01
-1.35525119e+00 7.12596655e-01 5.15622675e-01 9.62934136e-01
4.97491807e-01 -1.07757837e-01 2.81232953e-01 -9.62943435e-01
2.39920244e-01 -1.47734672e-01 -5.79569638e-01 2.95997858e-01
-4.00157422e-01 4.31128383e-01 7.71789432e-01 -6.49642646e-01
-1.10785735e+00 2.33682528e-01 -3.04922819e-01 -4.76399958e-01
-6.17522225e-02 9.58438367e-02 -5.18563807e-01 -1.76898971e-01
5.09979606e-01 1.85861245e-01 2.07094908e-01 -2.16486275e-01
9.64080453e-01 3.69863033e-01 8.15479398e-01 -4.09122437e-01
1.15139651e+00 3.77484083e-01 -2.46395797e-01 -4.82837081e-01
-6.63705707e-01 2.71927774e-01 -7.78016746e-01 -9.50503275e-02
1.28556550e+00 -7.32782125e-01 -3.43708366e-01 7.59993255e-01
-1.34986842e+00 -7.10750043e-01 -6.36344314e-01 1.80211306e-01
-8.05997372e-01 2.28660136e-01 -6.86274648e-01 1.14993848e-01
-1.74418136e-01 -1.24966264e+00 1.00058019e+00 1.99332193e-01
-1.73654318e-01 -1.08931541e+00 4.10256945e-02 2.24508971e-01
3.24840873e-01 6.30999207e-01 9.64624286e-01 9.79760736e-02
-7.86994457e-01 1.32447615e-01 -2.40538195e-02 4.68063593e-01
7.65527904e-01 -1.93425156e-02 -6.39823794e-01 -4.44291323e-01
-1.38874695e-01 -2.16808587e-01 6.58749938e-01 8.48218948e-02
1.35084605e+00 -6.58638716e-01 -6.36265427e-02 1.22583628e+00
1.30888867e+00 3.51517856e-01 7.82615244e-01 1.59578770e-01
1.24543524e+00 3.57347429e-01 1.59250274e-02 -4.99690697e-02
3.71929377e-01 8.73355269e-01 3.96763682e-01 -6.34428501e-01
-5.75374067e-01 -7.55061388e-01 4.96843010e-01 9.64989901e-01
4.41300571e-02 -1.46985516e-01 -4.40321714e-01 3.21360320e-01
-1.52916360e+00 -9.52128589e-01 3.82193595e-01 2.07596374e+00
1.11234307e+00 -3.32692713e-01 -1.83481857e-01 -2.14744434e-01
8.09241891e-01 2.15144575e-01 -5.98265767e-01 -4.80600536e-01
1.85751200e-01 5.23329437e-01 4.62492198e-01 7.39819884e-01
-8.36351633e-01 1.30367649e+00 6.57978344e+00 5.88443696e-01
-1.43634129e+00 1.63894489e-01 5.48096418e-01 2.07861364e-01
-7.66676188e-01 8.68378952e-02 -2.65785396e-01 4.41500068e-01
6.49793148e-01 1.94505036e-01 6.93926454e-01 5.54120660e-01
-7.19401315e-02 2.96962559e-01 -1.14170015e+00 1.01558626e+00
3.07623059e-01 -1.56136477e+00 6.20889425e-01 -1.05690710e-01
1.08972597e+00 -5.12842953e-01 2.66722858e-01 1.21742621e-01
5.11073530e-01 -1.09582043e+00 8.54720414e-01 5.48960984e-01
1.32651055e+00 -6.34889364e-01 2.99792826e-01 3.33483778e-02
-9.61496472e-01 3.02848458e-01 -1.50672138e-01 1.58456892e-01
3.17162216e-01 8.80606994e-02 -6.28830194e-01 5.31201065e-01
4.32389826e-01 7.92594433e-01 -4.15514082e-01 5.45409322e-01
-5.20238280e-01 2.69708157e-01 8.13152343e-02 5.28909564e-01
-1.12899952e-01 -4.05197382e-01 2.33458728e-01 8.59227121e-01
5.97986162e-01 -2.19615862e-01 9.83288046e-03 1.19174230e+00
-3.48131150e-01 -2.44618014e-01 -7.35737860e-01 -4.45377082e-02
2.18528882e-01 1.00044274e+00 -6.39140069e-01 -3.02824050e-01
-3.49456161e-01 1.76822793e+00 1.81208223e-01 5.84464133e-01
-9.97994065e-01 -5.94746828e-01 5.96089303e-01 1.91396743e-01
3.73372585e-01 -2.51000941e-01 1.66938324e-02 -1.41970479e+00
-1.81124702e-01 -9.56310689e-01 -9.75261703e-02 -1.00277722e+00
-1.05099356e+00 7.72556245e-01 -1.02014646e-01 -1.22436357e+00
-4.66742098e-01 -4.42605913e-01 -6.35644436e-01 8.00169826e-01
-1.30778587e+00 -1.49418056e+00 -4.89761859e-01 7.30395198e-01
7.36216605e-01 -1.12519711e-01 9.06472504e-01 3.10569644e-01
-2.30874971e-01 7.82729089e-01 -1.72896594e-01 3.39885920e-01
8.64432395e-01 -1.17170024e+00 6.84759319e-01 9.24232721e-01
2.55472451e-01 4.70558584e-01 5.46720505e-01 -4.17797863e-01
-1.28970456e+00 -1.37888670e+00 4.38727677e-01 -3.46180052e-01
1.84144959e-01 -5.30301988e-01 -8.31458986e-01 9.39285517e-01
5.25166094e-01 1.36567965e-01 5.12133896e-01 -3.74322623e-01
-4.45011705e-01 -2.50750273e-01 -1.02862251e+00 7.84252822e-01
1.07678926e+00 -7.43325949e-01 -5.31069994e-01 9.37597652e-04
1.05906582e+00 -6.78821564e-01 -8.15249920e-01 1.75272897e-01
5.99458098e-01 -9.49586570e-01 1.07401657e+00 -4.33861017e-01
6.88192129e-01 -3.98097217e-01 1.24007694e-01 -1.60412800e+00
-2.82469034e-01 -7.85791218e-01 1.84510022e-01 1.33036935e+00
2.57126302e-01 -5.73749781e-01 7.62827694e-01 6.40168965e-01
-1.21682823e-01 -3.61961722e-01 -4.79326874e-01 -7.01381147e-01
1.54441506e-01 -3.92796397e-02 1.02235937e+00 1.16095269e+00
-4.07527298e-01 3.05341512e-01 -6.78512096e-01 -1.35599365e-02
3.25006336e-01 2.77397633e-01 1.00724971e+00 -8.72272789e-01
-6.25072300e-01 -2.27335870e-01 -3.79480481e-01 -1.31091154e+00
4.68274534e-01 -1.10691369e+00 1.94868967e-01 -1.43208337e+00
5.20428829e-02 -5.10127604e-01 6.15038350e-02 6.86549187e-01
-1.38474151e-01 4.83248442e-01 3.46219540e-01 1.61895066e-01
-1.19431652e-01 8.53643596e-01 1.95377445e+00 -2.23007947e-01
-2.61237025e-01 -2.37280652e-01 -7.21020937e-01 6.81949496e-01
6.87219441e-01 -5.07629275e-01 -6.28889740e-01 -7.06685603e-01
1.76234514e-01 2.28056580e-01 4.50678408e-01 -8.27777207e-01
-3.07065789e-02 -3.46661359e-01 5.07263839e-01 -6.85625002e-02
3.74155611e-01 -8.79713356e-01 7.43472219e-01 3.83695990e-01
-4.22045887e-01 1.02794342e-01 6.77345246e-02 4.16745394e-01
-4.53705341e-01 -8.41521844e-02 9.25928473e-01 -2.94563174e-01
-5.89532495e-01 5.63437939e-01 -1.36973962e-01 1.14399632e-02
9.97748911e-01 -5.14762938e-01 -6.50857110e-03 -5.92251301e-01
-5.72200537e-01 -2.61380285e-01 8.96606624e-01 5.67544043e-01
6.60541713e-01 -1.75052226e+00 -2.84677982e-01 6.86792314e-01
3.21947485e-02 3.67176265e-01 1.03013895e-01 2.09218442e-01
-6.60212517e-01 -2.60510892e-01 -7.41504431e-01 -4.76704597e-01
-9.15533900e-01 4.74246681e-01 3.89207661e-01 2.63283569e-02
-6.35699391e-01 7.34296083e-01 5.62415898e-01 -5.83282828e-01
-1.87403485e-01 -4.60010022e-01 1.95143431e-01 -1.84278190e-01
3.02089244e-01 -2.08993286e-01 -2.00328782e-01 -6.30184233e-01
2.37526998e-01 7.42328644e-01 2.03341857e-01 -3.20130140e-01
1.32126999e+00 -3.01578846e-02 -3.54806185e-01 3.02337170e-01
1.55139184e+00 -5.12038171e-03 -1.78271878e+00 -9.89395976e-02
-5.79465091e-01 -6.12185299e-01 -7.27722049e-02 -4.76764232e-01
-1.42551422e+00 8.28585148e-01 4.58327532e-01 -1.15012333e-01
1.19340599e+00 -5.03696725e-02 1.12866426e+00 4.68998365e-02
3.94963771e-01 -6.76959693e-01 5.12073100e-01 3.23206574e-01
1.10060155e+00 -1.11978042e+00 -4.04169530e-01 -2.97360092e-01
-5.39044917e-01 1.10012805e+00 7.76400924e-01 -1.25564814e-01
3.35037649e-01 1.65498823e-01 1.09797187e-01 2.46140156e-02
-1.96832880e-01 1.37692526e-01 4.74733710e-01 6.72313929e-01
2.43841007e-01 1.13730505e-02 1.35700211e-01 1.47035584e-01
-4.81844604e-01 -1.53477058e-01 3.70819658e-01 5.62115610e-01
-6.99506998e-02 -1.61273682e+00 -2.26064995e-01 -3.45887220e-03
-7.79497027e-02 -8.63486826e-02 -2.06709921e-01 7.44689107e-01
3.94781888e-01 3.34957987e-01 3.72714430e-01 -4.59262133e-01
2.04369456e-01 -1.13262730e-02 7.68220305e-01 -8.21680129e-01
-4.07570809e-01 -1.55048713e-01 -3.84447843e-01 -6.52015805e-01
-4.68847126e-01 -2.95235217e-01 -1.14622116e+00 -2.03010231e-01
-4.45436826e-03 1.03188688e-02 4.80206132e-01 7.21604109e-01
3.92471433e-01 6.58540726e-01 6.22374058e-01 -1.16662526e+00
-5.09445183e-02 -5.33193469e-01 -3.23273838e-01 8.45058978e-01
4.85240221e-01 -4.77622360e-01 -1.36895865e-01 7.78499246e-01] | [11.655019760131836, -0.5109860301017761] |
1e8aff4f-69fd-4237-89bf-a3c2e18faa59 | betrayed-by-captions-joint-caption-grounding | 2301.00805 | null | https://arxiv.org/abs/2301.00805v1 | https://arxiv.org/pdf/2301.00805v1.pdf | Betrayed by Captions: Joint Caption Grounding and Generation for Open Vocabulary Instance Segmentation | In this work, we focus on instance-level open vocabulary segmentation, intending to expand a segmenter for instance-wise novel categories without mask annotations. We investigate a simple yet effective framework with the help of image captions, focusing on exploiting thousands of object nouns in captions to discover instances of novel classes. Rather than adopting pretrained caption models or using massive caption datasets with complex pipelines, we propose an end-to-end solution from two aspects: caption grounding and caption generation. In particular, we devise a joint Caption Grounding and Generation (CGG) framework based on a Mask Transformer baseline. The framework has a novel grounding loss that performs explicit and implicit multi-modal feature alignments. We further design a lightweight caption generation head to allow for additional caption supervision. We find that grounding and generation complement each other, significantly enhancing the segmentation performance for novel categories. We conduct extensive experiments on the COCO dataset with two settings: Open Vocabulary Instance Segmentation (OVIS) and Open Set Panoptic Segmentation (OSPS). The results demonstrate the superiority of our CGG framework over previous OVIS methods, achieving a large improvement of 6.8% mAP on novel classes without extra caption data. Our method also achieves over 15% PQ improvements for novel classes on the OSPS benchmark under various settings. | ['Chen Change Loy', 'Yunhai Tong', 'Guangliang Cheng', 'Xia Li', 'Henghui Ding', 'Xiangtai Li', 'Jianzong Wu'] | 2023-01-02 | null | null | null | null | ['panoptic-segmentation'] | ['computer-vision'] | [ 6.07652843e-01 5.44341624e-01 -1.61061957e-01 -5.40005088e-01
-1.30777550e+00 -7.86831975e-01 6.87342465e-01 -1.70420278e-02
-4.30005819e-01 4.92223591e-01 7.94737339e-02 -2.20051005e-01
3.29796582e-01 -6.46136880e-01 -1.14862621e+00 -5.23647070e-01
1.81115568e-01 7.22882450e-01 4.04602110e-01 -1.55517027e-01
3.93296331e-02 -1.29041243e-02 -1.48331487e+00 3.29238951e-01
1.22727609e+00 1.02159095e+00 2.00208515e-01 5.36313355e-01
-2.29663387e-01 1.18329063e-01 -4.45633590e-01 -8.03938806e-01
6.08538508e-01 -1.57242209e-01 -9.06735957e-01 4.37829852e-01
9.14949179e-01 -3.48909236e-02 -7.41025060e-02 9.31367517e-01
3.30860555e-01 -1.10700220e-01 5.87004125e-01 -1.10196459e+00
-8.70388031e-01 8.22377861e-01 -8.31025064e-01 1.60321742e-01
-1.07756272e-01 4.64715809e-01 1.48640621e+00 -8.56605649e-01
6.28494620e-01 1.17021823e+00 5.87225080e-01 6.53743207e-01
-1.35685420e+00 -6.53348625e-01 5.36719620e-01 5.05539887e-02
-1.35481369e+00 -2.81733096e-01 4.47138071e-01 -4.88851577e-01
8.18408370e-01 2.79581100e-01 2.50062704e-01 9.47436690e-01
-4.53175306e-01 1.15086806e+00 8.52998853e-01 -3.57277632e-01
1.08987927e-01 1.38984039e-01 4.43164736e-01 4.39728588e-01
3.25268507e-01 -2.28990689e-01 -1.56362444e-01 2.30652213e-01
4.23104078e-01 -2.39772081e-01 -2.28997618e-01 -2.14694530e-01
-1.50165081e+00 8.95463228e-01 8.27461600e-01 -1.86760798e-02
-3.34933460e-01 1.32274866e-01 2.90624171e-01 -9.03315768e-02
7.34498441e-01 7.44428575e-01 -6.02136970e-01 3.01317185e-01
-1.08635461e+00 3.03660005e-01 5.63116014e-01 1.08558679e+00
8.81387889e-01 -3.37645173e-01 -7.77283370e-01 8.90597343e-01
2.66317129e-01 6.40518069e-01 2.85735101e-01 -7.69562125e-01
8.39420617e-01 6.28261626e-01 -8.11952278e-02 -5.82092881e-01
-9.41241756e-02 -7.43109643e-01 -3.90591890e-01 -5.05188763e-01
1.94006532e-01 -2.31762379e-01 -1.70187616e+00 1.79970658e+00
4.71915752e-01 4.43445235e-01 1.19315989e-01 7.62155294e-01
9.52152431e-01 8.34776402e-01 3.67872387e-01 1.11646764e-01
1.56939769e+00 -1.42383862e+00 -4.73132044e-01 -5.18090129e-01
5.92408776e-01 -5.65323234e-01 1.18991470e+00 -5.76270297e-02
-7.97610521e-01 -4.84585464e-01 -8.85191858e-01 -3.81617881e-02
-3.96015286e-01 -7.58512691e-02 6.28436685e-01 4.12247926e-01
-9.50753570e-01 1.12744801e-01 -6.27265394e-01 -1.95038259e-01
7.64044821e-01 3.53672236e-01 -5.83705083e-02 -1.18960395e-01
-9.64284718e-01 4.83932823e-01 6.87470496e-01 -8.65876488e-03
-7.18081892e-01 -9.86474752e-01 -1.09851694e+00 1.63628668e-01
5.57737470e-01 -7.15900242e-01 1.31238937e+00 -1.13632488e+00
-9.00933444e-01 1.11916327e+00 -9.84352231e-02 -7.21917510e-01
3.69289726e-01 -1.85223565e-01 -9.90747213e-02 2.38180459e-01
5.49814522e-01 1.56675506e+00 6.91873789e-01 -1.35929215e+00
-7.66002297e-01 -1.31526902e-01 1.52047530e-01 2.27696136e-01
-2.76122391e-01 -1.28329203e-01 -8.89548838e-01 -8.29777479e-01
9.21890363e-02 -1.13935149e+00 -4.05024648e-01 -2.67509252e-01
-6.39104128e-01 -3.81695062e-01 5.46015561e-01 -7.08422482e-01
9.60216582e-01 -2.01696420e+00 6.70270622e-02 -1.75793692e-02
2.23330051e-01 4.19538200e-01 -4.08233464e-01 -6.73382804e-02
1.27351865e-01 3.63530159e-01 -8.17155898e-01 -4.82846141e-01
1.48694202e-01 3.54508907e-01 -6.09782815e-01 -1.09428532e-01
7.29571342e-01 1.36658025e+00 -7.99962938e-01 -5.62962413e-01
-7.57836774e-02 2.33832151e-01 -8.84465575e-01 1.33195907e-01
-7.77616858e-01 5.09707153e-01 -2.80946195e-01 8.09198260e-01
7.59972811e-01 -5.52440047e-01 -1.14167616e-01 1.92048177e-02
1.14288092e-01 1.63536161e-01 -8.64218593e-01 1.74391282e+00
-4.07314241e-01 3.97520095e-01 -1.57504037e-01 -8.90323341e-01
8.02531779e-01 9.20334384e-02 1.63118079e-01 -6.37704253e-01
5.00305071e-02 3.63300830e-01 -4.76368144e-02 -3.38724285e-01
3.79051298e-01 -4.24782224e-02 -3.95635188e-01 1.08026810e-01
4.23701525e-01 -1.58743113e-01 5.27310789e-01 4.50326085e-01
9.18424189e-01 2.05609605e-01 -1.28603473e-01 -2.20106423e-01
3.45250517e-01 2.22230807e-01 5.91875434e-01 8.17868590e-01
-5.61316721e-02 1.05218172e+00 4.99997139e-01 -2.12286875e-01
-9.51266289e-01 -1.14267612e+00 -3.55590492e-01 1.11466157e+00
3.13519746e-01 -1.87792689e-01 -9.44821119e-01 -9.33965683e-01
-1.01506583e-01 6.55529141e-01 -6.19161606e-01 2.15305462e-01
-5.73396862e-01 -1.08685374e+00 3.58055919e-01 5.41362166e-01
7.33606339e-01 -1.09514475e+00 -1.42799214e-01 1.25326410e-01
-5.12093186e-01 -1.56699312e+00 -6.85721695e-01 2.81687994e-02
-5.92395246e-01 -8.59783530e-01 -1.09309089e+00 -9.83710468e-01
6.80819631e-01 1.80998072e-01 1.20411885e+00 -1.18607730e-01
-2.75010973e-01 2.14631006e-01 -5.59444606e-01 -4.84823793e-01
-2.57010251e-01 5.97350717e-01 -4.11841244e-01 3.46014321e-01
3.68414879e-01 -3.37786794e-01 -5.93244791e-01 2.43916556e-01
-9.69251096e-01 4.59881008e-01 7.93850005e-01 6.56876624e-01
8.43801618e-01 -6.71794832e-01 6.50325477e-01 -1.00484586e+00
5.61367385e-02 -6.88861966e-01 -7.26694942e-01 3.14510971e-01
-5.21603048e-01 7.15952963e-02 2.29166523e-01 -3.05023581e-01
-8.99925411e-01 1.81986347e-01 -2.64209598e-01 -3.78895402e-01
-2.38116771e-01 2.88970619e-01 -3.08966488e-01 1.35632515e-01
5.95412791e-01 1.87060654e-01 -3.20005894e-01 -5.23031175e-01
6.72830999e-01 8.24205756e-01 7.53287137e-01 -5.59672236e-01
9.46521282e-01 3.31039816e-01 -5.37430167e-01 -4.80260879e-01
-1.41306353e+00 -6.81897700e-01 -6.38662457e-01 1.49415419e-01
1.16706920e+00 -1.34408557e+00 -1.05539694e-01 2.65897542e-01
-1.07049298e+00 -3.05124521e-01 -2.85028428e-01 1.25757411e-01
-3.43821824e-01 2.52864063e-01 -4.05343980e-01 -2.53020197e-01
-5.76495945e-01 -1.31940317e+00 1.52254581e+00 3.63156915e-01
1.68479055e-01 -6.60577655e-01 -3.40259820e-02 9.01652992e-01
1.02331601e-01 4.78676170e-01 4.63879228e-01 -9.71705139e-01
-9.66345310e-01 -8.97127539e-02 -6.43607080e-01 4.25909668e-01
-1.63141727e-01 -2.97348380e-01 -1.15814459e+00 -1.87789500e-01
-5.24481058e-01 -3.00335050e-01 1.33618903e+00 1.83015972e-01
1.19726276e+00 -3.61966759e-01 -4.27545369e-01 8.51916790e-01
1.46857238e+00 -1.10807128e-01 5.84493995e-01 3.91825259e-01
1.00112605e+00 6.44120276e-01 6.21223092e-01 -2.82489825e-02
5.88144481e-01 6.12750053e-01 5.14795303e-01 -3.08291644e-01
-3.71007442e-01 -2.27550685e-01 1.16163932e-01 5.15474677e-01
3.53621483e-01 -4.78510052e-01 -1.18116212e+00 1.23264408e+00
-1.80511332e+00 -5.35090685e-01 -1.80385873e-01 1.96970272e+00
1.02835011e+00 1.76128447e-01 -3.74002084e-02 -2.44221419e-01
1.00348103e+00 3.47114839e-02 -7.18080163e-01 -2.09550336e-01
-5.83261400e-02 4.31649238e-01 6.56096160e-01 5.04895866e-01
-1.48010671e+00 1.29599988e+00 5.31383944e+00 8.30839157e-01
-8.69360447e-01 2.25113437e-01 9.50813651e-01 -7.93883130e-02
-4.14149702e-01 7.90524259e-02 -1.20630109e+00 5.56940854e-01
8.54118168e-01 9.93959680e-02 6.61897436e-02 6.55900061e-01
-2.53105283e-01 1.42897397e-01 -8.90485585e-01 9.39270258e-01
2.02010080e-01 -1.43894780e+00 4.10163701e-01 -1.06507074e-02
1.08335543e+00 4.90497142e-01 3.36819403e-02 5.56203127e-01
3.18493187e-01 -8.21101606e-01 7.22419083e-01 -6.35067970e-02
7.43628561e-01 -4.42874104e-01 6.59917951e-01 -2.86387391e-02
-1.02485013e+00 4.65711206e-02 -7.76708573e-02 1.94627628e-01
3.49054784e-01 4.99377936e-01 -9.29529488e-01 5.32725990e-01
5.78208447e-01 5.64890325e-01 -8.81172061e-01 1.31681752e+00
-3.68307352e-01 9.91197646e-01 -4.85137761e-01 3.72807771e-01
8.11305702e-01 9.88610089e-03 4.88825917e-01 1.18234944e+00
-3.58676091e-02 -4.54725474e-02 4.16127652e-01 9.81335163e-01
-5.30373156e-01 1.31858706e-01 -1.39413655e-01 -2.35661864e-02
2.86654204e-01 1.41580188e+00 -9.32934165e-01 -5.46968102e-01
-4.47541237e-01 9.45055783e-01 1.42233044e-01 3.29746187e-01
-1.18173611e+00 -4.57389027e-01 6.09357595e-01 1.82166576e-01
7.70112455e-01 2.18369201e-01 -4.65197951e-01 -1.34404433e+00
2.94609636e-01 -7.17510819e-01 4.66874272e-01 -5.42169511e-01
-1.26806319e+00 5.87021649e-01 8.51087719e-02 -8.96762133e-01
1.08132428e-02 -4.31959838e-01 -5.49094439e-01 6.94205046e-01
-1.91866755e+00 -1.69047868e+00 -2.75170326e-01 2.19012931e-01
8.54709566e-01 2.15738580e-01 3.96557927e-01 4.05006468e-01
-6.53324723e-01 7.15479076e-01 -1.52386948e-01 3.05784494e-01
6.26101196e-01 -1.43322754e+00 9.10908878e-01 1.08744943e+00
3.92586112e-01 2.71727562e-01 6.47665203e-01 -6.16174757e-01
-6.94536448e-01 -1.68275476e+00 8.57148528e-01 -6.44978881e-01
5.84818423e-01 -7.13348389e-01 -9.81119573e-01 9.20563102e-01
2.08227098e-01 1.29310787e-01 6.46059692e-01 2.02454478e-01
-4.82442439e-01 1.65302485e-01 -9.93574142e-01 5.16160071e-01
1.20510733e+00 -6.21772371e-02 -7.33610392e-01 6.43294871e-01
1.54065430e+00 -4.78027135e-01 -6.22625470e-01 6.58833802e-01
1.21570073e-01 -3.52682114e-01 9.92826462e-01 -4.52086568e-01
4.87376451e-01 -4.12718683e-01 -1.87103212e-01 -9.69840467e-01
-1.10592842e-01 -6.28159583e-01 1.73798651e-01 1.54343343e+00
8.54122341e-01 -6.01777852e-01 6.42531335e-01 5.89724243e-01
-4.67056066e-01 -6.90174162e-01 -7.84505427e-01 -8.22175741e-01
2.11826429e-01 -4.32349712e-01 7.02254474e-01 8.08150887e-01
-4.88164812e-01 6.25050247e-01 -5.21916635e-02 5.30379772e-01
5.28725207e-01 4.14175391e-01 7.64629841e-01 -1.12265861e+00
-3.07475477e-01 -2.16893852e-01 -2.52008468e-01 -1.11792409e+00
1.60109997e-01 -1.22717464e+00 2.50436813e-01 -1.76049888e+00
3.78706008e-01 -5.68102658e-01 -2.73093730e-01 8.34833324e-01
-5.97495139e-01 8.19759011e-01 3.81825656e-01 2.59571582e-01
-1.02439344e+00 5.65403521e-01 1.29374456e+00 -4.03287798e-01
-2.73658305e-01 -1.94531813e-01 -1.09004676e+00 5.03452659e-01
6.88155532e-01 -4.90130872e-01 -3.16712826e-01 -7.73438573e-01
-7.05105439e-02 -4.86334711e-01 4.96775746e-01 -9.84427750e-01
-1.05885617e-01 1.34347886e-01 -6.86086565e-02 -6.40856087e-01
4.20813151e-02 -3.37650687e-01 -2.58857667e-01 1.46879837e-01
-3.46177906e-01 -3.89792681e-01 4.05968696e-01 6.57300055e-01
-1.89384565e-01 -1.46919116e-01 7.49310911e-01 -6.07308373e-02
-9.98594761e-01 5.92664838e-01 1.94918573e-01 4.94508833e-01
1.19287014e+00 -9.10585225e-02 -3.52893561e-01 1.25645056e-01
-8.06775749e-01 7.00178146e-01 4.10733640e-01 7.22433567e-01
1.17737368e-01 -1.04098058e+00 -9.86202419e-01 7.95396194e-02
5.76523364e-01 6.38090372e-01 1.33542985e-01 6.15691662e-01
-4.64223772e-01 4.73774552e-01 2.71201342e-01 -9.33805048e-01
-1.00440204e+00 4.86141771e-01 2.06512406e-01 -4.02526140e-01
-5.91943026e-01 1.16876173e+00 7.92169929e-01 -6.53476655e-01
4.52587306e-02 -3.97821814e-01 -6.05571456e-02 1.09335281e-01
3.99175078e-01 -2.75518835e-01 2.69835033e-02 -7.08086550e-01
-1.71961144e-01 4.71706778e-01 -3.64300966e-01 7.86757022e-02
1.33321309e+00 -1.66380674e-01 3.80039066e-02 1.45849418e-02
1.01570106e+00 -4.16218251e-01 -1.45991504e+00 -3.16791028e-01
1.79792047e-01 -2.47706130e-01 7.47758150e-02 -1.15961862e+00
-1.05180466e+00 7.51375735e-01 5.04665673e-01 -1.00598246e-01
9.71880496e-01 4.63206887e-01 1.19792759e+00 2.01871753e-01
1.34455025e-01 -9.10157084e-01 -5.74923456e-02 4.62581307e-01
8.28196943e-01 -1.51846075e+00 -4.51772600e-01 -7.94591844e-01
-7.45403767e-01 4.86971438e-01 7.58777440e-01 -1.65584758e-02
2.67293572e-01 -1.80501342e-01 6.55344862e-04 -3.19281697e-01
-4.98422056e-01 -8.13878119e-01 5.95017254e-01 4.65732753e-01
3.01151890e-02 1.19632803e-01 -9.96502414e-02 5.89169860e-01
-1.32365718e-01 -2.25355744e-01 3.23663801e-01 4.96488988e-01
-5.14530480e-01 -9.66106474e-01 -3.35947841e-01 5.85200965e-01
-4.79618460e-01 -5.65668941e-01 -1.60725802e-01 6.21531725e-01
3.31657737e-01 8.04088116e-01 4.41495121e-01 1.70753654e-02
2.11025462e-01 1.91165194e-01 1.94568947e-01 -1.11887062e+00
-4.99755204e-01 7.28754699e-03 -1.67601518e-02 -3.00285727e-01
-3.08473051e-01 -6.21763229e-01 -1.15904307e+00 3.01429421e-01
-4.95695025e-01 1.04697064e-01 5.66799521e-01 9.18737113e-01
6.12242579e-01 5.82607687e-01 4.10944343e-01 -7.87756860e-01
-2.70797670e-01 -9.95748341e-01 -8.99061412e-02 6.36279404e-01
1.21408917e-01 -5.43013394e-01 -2.87581295e-01 2.52782822e-01] | [9.708316802978516, 0.7708637714385986] |
dcbd4f0c-3b9a-49dc-9f41-24266b8eeac1 | adversarial-examples-detection-with-enhanced | 2305.04436 | null | https://arxiv.org/abs/2305.04436v1 | https://arxiv.org/pdf/2305.04436v1.pdf | Adversarial Examples Detection with Enhanced Image Difference Features based on Local Histogram Equalization | Deep Neural Networks (DNNs) have recently made significant progress in many fields. However, studies have shown that DNNs are vulnerable to adversarial examples, where imperceptible perturbations can greatly mislead DNNs even if the full underlying model parameters are not accessible. Various defense methods have been proposed, such as feature compression and gradient masking. However, numerous studies have proven that previous methods create detection or defense against certain attacks, which renders the method ineffective in the face of the latest unknown attack methods. The invisibility of adversarial perturbations is one of the evaluation indicators for adversarial example attacks, which also means that the difference in the local correlation of high-frequency information in adversarial examples and normal examples can be used as an effective feature to distinguish the two. Therefore, we propose an adversarial example detection framework based on a high-frequency information enhancement strategy, which can effectively extract and amplify the feature differences between adversarial examples and normal examples. Experimental results show that the feature augmentation module can be combined with existing detection models in a modular way under this framework. Improve the detector's performance and reduce the deployment cost without modifying the existing detection model. | ['Bin Luo', 'Wanli Lyu', 'Jianteng Peng', 'Hang Su', 'Shaowei Zhu', 'Zhaoxia Yin'] | 2023-05-08 | null | null | null | null | ['feature-compression'] | ['computer-vision'] | [ 2.19047323e-01 -2.65520096e-01 2.50459373e-01 -1.64820075e-01
-2.88738489e-01 -7.69685566e-01 7.73327827e-01 -2.20707104e-01
-3.77243310e-01 4.42252964e-01 1.17798448e-02 -1.89966902e-01
1.00459859e-01 -9.98648405e-01 -5.33373058e-01 -9.83288288e-01
-1.10226534e-01 -3.99580181e-01 4.16215301e-01 -4.97092783e-01
1.10288315e-01 8.49272728e-01 -1.46277666e+00 2.22682148e-01
6.72689438e-01 1.08306992e+00 -3.95960659e-02 4.90976155e-01
-7.67790973e-02 5.51538706e-01 -1.14074433e+00 -4.10349637e-01
6.84917033e-01 -3.76451105e-01 -8.70636553e-02 -3.97041529e-01
3.80724221e-01 -5.93980134e-01 -1.09810710e+00 1.80759120e+00
8.27354729e-01 -1.63856044e-01 2.78016657e-01 -1.42570317e+00
-7.02880621e-01 6.19023085e-01 -3.45935762e-01 5.77943742e-01
1.00074224e-01 3.90322924e-01 2.64308900e-01 -6.20386839e-01
1.43234089e-01 1.55163026e+00 5.45580089e-01 8.77563715e-01
-6.85149312e-01 -1.25680029e+00 2.89589792e-01 4.64678645e-01
-1.18326819e+00 -3.44218194e-01 1.06132722e+00 -2.23651901e-02
3.69346052e-01 4.16844189e-01 4.40504342e-01 1.48101652e+00
2.60794699e-01 7.86060750e-01 9.03566837e-01 -1.72804996e-01
3.71347107e-02 2.53200114e-01 -1.24749564e-01 3.80833536e-01
3.52188230e-01 7.22264528e-01 -1.56547263e-01 -2.81925321e-01
6.79313958e-01 3.27409267e-01 -6.85008228e-01 1.43123165e-01
-8.10960352e-01 7.74580121e-01 8.29557896e-01 3.12490433e-01
-6.68511614e-02 -7.62486681e-02 6.01147413e-01 5.45570612e-01
9.03154537e-02 3.03587526e-01 -1.50788963e-01 2.80656427e-01
-1.85270086e-01 2.34854355e-01 4.67608541e-01 6.29499078e-01
5.76952636e-01 5.77408135e-01 -8.66771117e-02 4.88761544e-01
3.20403457e-01 7.95592844e-01 7.67314851e-01 -2.38849461e-01
4.96934116e-01 6.44979060e-01 -4.18642372e-01 -1.48119354e+00
-1.44731611e-01 -6.20196402e-01 -1.02694058e+00 5.56201458e-01
7.68136531e-02 -4.77273583e-01 -8.87400866e-01 1.86698186e+00
3.76171470e-01 4.60593551e-01 3.77574950e-01 8.73189986e-01
9.46510673e-01 4.98766154e-01 -1.08123340e-01 3.93842496e-02
1.06894934e+00 -5.61142683e-01 -9.15249527e-01 -4.10651356e-01
2.63932377e-01 -7.62095153e-01 6.89493537e-01 2.38713309e-01
-4.60939914e-01 -6.68047845e-01 -1.61370063e+00 5.29100001e-01
-6.38495386e-01 -2.74928600e-01 5.67591846e-01 1.24817967e+00
-5.87511122e-01 5.58481872e-01 -5.69393158e-01 2.12030888e-01
6.25089347e-01 3.21450621e-01 -3.71985435e-01 -1.66222736e-01
-1.83046794e+00 7.90433824e-01 6.43052936e-01 3.93554598e-01
-1.10241175e+00 -4.80871677e-01 -6.68923616e-01 -7.97992423e-02
1.52604170e-02 -3.49668972e-02 7.68542886e-01 -1.10972357e+00
-1.07301939e+00 3.81514847e-01 6.32018924e-01 -5.87019444e-01
7.71980226e-01 -7.91253671e-02 -1.11383593e+00 3.10940295e-01
-3.27495188e-01 2.33616710e-01 1.19365585e+00 -9.69449043e-01
-4.98605043e-01 -4.94854599e-01 1.69840842e-01 7.79388025e-02
-9.04019773e-01 2.36737296e-01 -4.25755754e-02 -9.97384846e-01
1.42356053e-01 -6.73378766e-01 -1.99310362e-01 2.13224605e-01
-5.21303117e-01 3.39373350e-01 1.62233210e+00 -4.19081897e-01
1.04996026e+00 -2.46887946e+00 -5.48923433e-01 3.11029226e-01
2.60449469e-01 9.42775071e-01 -1.48524418e-01 2.76387870e-01
-3.38586599e-01 1.49528280e-01 -1.47384778e-01 2.81989843e-01
-1.03705816e-01 6.83254823e-02 -6.74565315e-01 6.80800736e-01
3.22082400e-01 6.48556411e-01 -8.23359907e-01 -6.13889992e-02
1.69555932e-01 5.87264061e-01 -2.61357099e-01 2.43156865e-01
1.58697605e-01 2.45271340e-01 -6.31116033e-01 5.20755649e-01
1.20289636e+00 5.73978841e-01 -3.09283584e-01 -2.15962619e-01
3.14836204e-01 -5.14032841e-02 -1.39433992e+00 7.82710254e-01
1.82833865e-01 7.58765638e-01 4.56612445e-02 -1.06180573e+00
1.16208792e+00 3.54194671e-01 -7.15151010e-03 -5.06646812e-01
3.63272369e-01 1.07813135e-01 3.96494389e-01 -4.45915252e-01
-4.04285006e-02 3.94145735e-02 9.48389806e-03 9.22787413e-02
-2.13986337e-01 3.42854381e-01 -3.44691068e-01 1.33758008e-01
1.39075875e+00 -4.78090882e-01 7.05150366e-02 8.87757167e-02
6.68883383e-01 -3.67697656e-01 7.26811230e-01 8.44720781e-01
-3.88966620e-01 3.63932490e-01 2.69994169e-01 -4.76118237e-01
-6.33082151e-01 -1.16974878e+00 -3.60991657e-01 5.83543479e-01
3.72571617e-01 -2.36829650e-02 -8.62198532e-01 -9.80614901e-01
3.06502338e-02 2.73819238e-01 -5.22334814e-01 -1.06612909e+00
-4.84665543e-01 -8.89656186e-01 1.21162248e+00 5.81234574e-01
1.15130305e+00 -1.08770740e+00 -2.90164500e-01 1.35762468e-01
2.65923440e-01 -1.22552705e+00 -2.95568377e-01 6.57208115e-02
-6.46346629e-01 -1.03244543e+00 -4.14550513e-01 -7.61192203e-01
7.46355116e-01 3.82175416e-01 4.01057661e-01 2.54021108e-01
-3.87688667e-01 -6.05321899e-02 -4.36841697e-01 -7.59869635e-01
-7.29040861e-01 -5.81743419e-01 5.90529263e-01 2.04722688e-01
4.22823071e-01 -6.41237199e-01 -5.27785361e-01 2.90687174e-01
-1.27466106e+00 -7.05965877e-01 7.11467028e-01 7.64618695e-01
1.26696080e-01 5.01019418e-01 8.41322482e-01 -8.20985615e-01
6.85104072e-01 -3.47946972e-01 -5.44657648e-01 -3.28554250e-02
-3.19698095e-01 -1.70745775e-02 1.19374776e+00 -9.50063288e-01
-8.45593393e-01 -1.94482148e-01 -4.20012414e-01 -7.43798137e-01
-3.89653206e-01 2.61428952e-01 -8.76891553e-01 -6.68342769e-01
8.70219529e-01 4.51219201e-01 -6.39431626e-02 -3.37229937e-01
7.71037349e-03 6.15803719e-01 6.97161078e-01 -1.44496143e-01
1.44302893e+00 3.25067997e-01 1.24720875e-02 -7.14737475e-01
-4.04023111e-01 4.75359261e-02 -1.61799073e-01 -1.89987525e-01
2.51239657e-01 -8.03510547e-01 -5.28275073e-01 1.06304741e+00
-1.06624150e+00 2.37805858e-01 -1.57805234e-02 4.51710254e-01
8.03567022e-02 7.33754575e-01 -4.56864476e-01 -7.52831936e-01
-3.06602895e-01 -1.20118439e+00 3.80898476e-01 5.07501841e-01
4.40881729e-01 -8.01741719e-01 -2.22737640e-01 -2.27603912e-01
5.34004033e-01 5.70433080e-01 7.99596429e-01 -1.17929733e+00
-5.52496254e-01 -8.59458804e-01 -7.69848824e-02 7.81077921e-01
1.93496764e-01 3.78862470e-02 -1.37286198e+00 -4.10411716e-01
5.10591090e-01 -1.54063478e-01 8.13375592e-01 -7.64261466e-03
1.16552889e+00 -6.65445089e-01 -3.76744062e-01 7.94504344e-01
1.31502199e+00 4.18975502e-01 9.13042188e-01 4.15347636e-01
7.82837629e-01 2.37998798e-01 3.97905797e-01 1.80947855e-01
-5.02770245e-01 4.37864900e-01 9.47691977e-01 -1.88742056e-01
2.71264967e-02 -1.83218136e-01 6.48572147e-01 3.59896213e-01
2.54222989e-01 -2.50148147e-01 -6.23277009e-01 1.77387357e-01
-1.45995593e+00 -1.31802821e+00 1.18107907e-01 2.05225945e+00
6.88282430e-01 6.35846972e-01 -2.30589449e-01 5.20094395e-01
1.01304984e+00 3.25980216e-01 -8.24385345e-01 -2.51196176e-01
-2.85066813e-01 1.22304251e-02 5.02267063e-01 -4.29146737e-02
-1.40379930e+00 6.71168864e-01 6.04869604e+00 9.70296443e-01
-1.33418512e+00 -2.30472222e-01 4.82418597e-01 1.57626182e-01
-3.87985446e-02 -4.27697748e-01 -7.66165316e-01 7.01139510e-01
6.59002721e-01 -2.66512096e-01 1.44083261e-01 1.24485672e+00
-1.15436949e-01 6.35110497e-01 -9.12826121e-01 8.76483977e-01
5.24211265e-02 -1.04682577e+00 3.10213804e-01 6.99393544e-03
4.43595827e-01 -1.47659764e-01 4.20077145e-01 4.75310564e-01
1.55203819e-01 -8.11858952e-01 4.01688933e-01 1.98396996e-01
4.92708355e-01 -1.12256420e+00 1.04396355e+00 5.56608021e-01
-1.14998567e+00 -2.37939492e-01 -6.88457727e-01 8.03430676e-02
-2.81913102e-01 4.41498399e-01 -7.89576292e-01 5.02124429e-01
6.78668022e-01 4.30472374e-01 -5.63960910e-01 9.92032409e-01
-3.38735163e-01 5.42270124e-01 -2.90631443e-01 -6.63151890e-02
2.16968819e-01 3.93323116e-02 8.86061907e-01 1.05104244e+00
1.58175319e-01 -3.01906690e-02 1.36342168e-01 7.84607708e-01
-2.13538468e-01 -1.13793187e-01 -9.85506594e-01 -1.93352569e-02
8.09689999e-01 1.11628008e+00 -4.60635543e-01 -8.17906931e-02
-2.65532583e-01 8.44339669e-01 5.19552715e-02 3.37768674e-01
-8.94992471e-01 -8.51217687e-01 9.65337515e-01 -2.90827930e-01
2.33070403e-01 1.56732947e-01 3.05994302e-02 -9.58702326e-01
2.14745000e-01 -1.20987499e+00 3.25717390e-01 -1.69109955e-01
-1.44936550e+00 7.02861488e-01 -3.32373917e-01 -1.54311287e+00
-1.77372694e-02 -7.50320733e-01 -1.05645263e+00 8.33363831e-01
-1.29328513e+00 -7.76367188e-01 -2.44987220e-01 9.81231093e-01
2.78684914e-01 -5.69008648e-01 8.28052282e-01 3.91296297e-01
-7.78479576e-01 1.16467941e+00 1.02649964e-01 8.13875377e-01
4.84625965e-01 -9.34397578e-01 5.13555527e-01 1.48143291e+00
3.70848663e-02 6.46481574e-01 7.32054532e-01 -5.16429484e-01
-1.26756716e+00 -1.32746792e+00 -2.30487864e-02 -2.42318437e-02
5.67226231e-01 -4.55357432e-01 -1.14245999e+00 3.75130028e-01
-1.26083344e-01 3.84503365e-01 5.10284841e-01 -5.19459009e-01
-5.24608016e-01 -3.26043129e-01 -1.50223148e+00 8.95516217e-01
9.51389670e-01 -5.76812983e-01 -6.58781767e-01 1.85715571e-01
8.65942180e-01 -3.23265493e-01 -4.09139037e-01 7.28457391e-01
2.75028735e-01 -1.00219166e+00 1.21814466e+00 -5.61952889e-01
1.79832846e-01 -4.16791409e-01 -1.74214438e-01 -1.21343231e+00
-1.53596997e-01 -6.72654927e-01 -3.02854925e-01 1.39210927e+00
1.13882430e-01 -1.02975678e+00 5.44950843e-01 2.66576976e-01
-1.20972976e-01 -5.22787750e-01 -9.97509062e-01 -9.86251771e-01
-2.00657845e-01 -4.08077985e-01 8.02207589e-01 1.00515580e+00
-3.42463195e-01 -8.06615353e-02 -2.46738732e-01 7.73324609e-01
5.49492836e-01 -4.64357436e-01 6.46237731e-01 -1.02901185e+00
-1.23543210e-01 -5.00337720e-01 -1.20294368e+00 -7.40977705e-01
6.94500506e-02 -6.52534068e-01 -4.86742966e-02 -9.01378691e-01
-2.35812172e-01 -3.50275159e-01 -6.64822757e-01 3.62576485e-01
-5.60620964e-01 3.62797379e-01 -6.27120666e-04 5.38789853e-02
4.71907035e-02 5.93087792e-01 1.01363373e+00 -3.50865632e-01
1.73121318e-01 2.53899038e-01 -8.22003007e-01 8.81251991e-01
7.79588878e-01 -6.43779159e-01 -5.39889872e-01 -6.34080619e-02
-2.80140221e-01 -4.41022158e-01 4.48720306e-01 -1.46396756e+00
1.51648715e-01 5.43950796e-02 6.64199650e-01 -3.71959060e-01
1.21565141e-01 -1.07358897e+00 -1.75860003e-01 7.36467361e-01
-1.26546338e-01 6.59412891e-02 4.83147949e-01 9.07517433e-01
-3.31543684e-01 -2.98414230e-01 9.57221627e-01 6.06417581e-02
-8.70902419e-01 5.84445477e-01 -3.26248735e-01 -4.02871668e-02
1.20682967e+00 -2.72507459e-01 -5.16385198e-01 -2.68672585e-01
-2.62787759e-01 -1.08080909e-01 1.43698931e-01 5.98955989e-01
9.22727466e-01 -1.57702279e+00 -6.43748820e-01 6.91906452e-01
-8.12769234e-02 -3.05361301e-01 3.66678327e-01 2.99430907e-01
-3.81531954e-01 -1.24512434e-01 -4.00004536e-01 -3.64442915e-01
-1.35915685e+00 1.01034164e+00 4.74152803e-01 1.69205591e-02
-6.08188093e-01 8.56769502e-01 3.53765935e-01 -2.05878153e-01
4.41697031e-01 1.62313923e-01 -4.15258467e-01 -2.41635963e-01
1.03223336e+00 1.87507600e-01 4.53835353e-02 -5.50539136e-01
-4.40118313e-01 2.91962534e-01 -4.29945529e-01 3.46048802e-01
1.01004946e+00 1.98797762e-01 1.41469166e-01 -3.53571363e-02
1.23978996e+00 5.24080023e-02 -1.13919914e+00 -2.97145963e-01
-3.64021659e-01 -6.05196834e-01 1.08331233e-01 -5.17458439e-01
-1.31652248e+00 9.26087022e-01 1.03077209e+00 5.84061980e-01
1.40673637e+00 -3.99965644e-01 7.85586238e-01 4.46289182e-01
1.30891562e-01 -6.85274899e-01 1.48527429e-01 3.02358419e-01
7.19440401e-01 -1.13281333e+00 -1.79296032e-01 -3.50193918e-01
-3.23400378e-01 1.21663284e+00 8.54017437e-01 -2.94503927e-01
6.90676391e-01 4.90770012e-01 3.15849930e-01 5.86676709e-02
-3.98419142e-01 1.36681959e-01 1.96259916e-01 9.24367487e-01
-3.11973006e-01 -1.77686498e-01 4.26867865e-02 5.97698510e-01
-2.39404708e-01 -6.60246491e-01 3.32349628e-01 8.42362881e-01
-5.64485610e-01 -1.01565897e+00 -6.98949635e-01 2.86669761e-01
-6.50553703e-01 -1.35252520e-01 -5.00729024e-01 7.33400583e-01
2.44475096e-01 9.69521582e-01 -2.44225562e-01 -9.67948318e-01
4.32126254e-01 -1.94928497e-01 8.58759582e-02 -3.67819995e-01
-5.77378392e-01 -3.62289518e-01 -3.25969249e-01 -3.86986494e-01
-7.60204643e-02 -3.51737678e-01 -1.06332815e+00 -3.49773824e-01
-5.36919832e-01 -7.63172358e-02 4.80013907e-01 1.03739882e+00
1.10535257e-01 6.50252342e-01 1.20857406e+00 -7.06918061e-01
-1.04517150e+00 -8.82292807e-01 -4.46997583e-01 4.91347492e-01
6.19122922e-01 -5.88545918e-01 -8.26538146e-01 -3.49105835e-01] | [5.510412693023682, 7.914054870605469] |
4bd3a483-4051-4abb-85b4-e2db2e193e1d | distinguishing-natural-and-computer-generated | 2110.09428 | null | https://arxiv.org/abs/2110.09428v2 | https://arxiv.org/pdf/2110.09428v2.pdf | Distinguishing Natural and Computer-Generated Images using Multi-Colorspace fused EfficientNet | The problem of distinguishing natural images from photo-realistic computer-generated ones either addresses natural images versus computer graphics or natural images versus GAN images, at a time. But in a real-world image forensic scenario, it is highly essential to consider all categories of image generation, since in most cases image generation is unknown. We, for the first time, to our best knowledge, approach the problem of distinguishing natural images from photo-realistic computer-generated images as a three-class classification task classifying natural, computer graphics, and GAN images. For the task, we propose a Multi-Colorspace fused EfficientNet model by parallelly fusing three EfficientNet networks that follow transfer learning methodology where each network operates in different colorspaces, RGB, LCH, and HSV, chosen after analyzing the efficacy of various colorspace transformations in this image forensics problem. Our model outperforms the baselines in terms of accuracy, robustness towards post-processing, and generalizability towards other datasets. We conduct psychophysics experiments to understand how accurately humans can distinguish natural, computer graphics, and GAN images where we could observe that humans find difficulty in classifying these images, particularly the computer-generated images, indicating the necessity of computational algorithms for the task. We also analyze the behavior of our model through visual explanations to understand salient regions that contribute to the model's decision making and compare with manual explanations provided by human participants in the form of region markings, where we could observe similarities in both the explanations indicating the powerful nature of our model to take the decisions meaningfully. | ['Lajish V L', 'Anoop K', 'Manjary P Gangan'] | 2021-10-18 | null | null | null | null | ['image-forensics'] | ['computer-vision'] | [ 5.65777004e-01 2.58265942e-01 4.38069165e-01 -6.88546523e-02
-5.91096818e-01 -8.54649067e-01 7.74404049e-01 -1.13139749e-01
-4.80228812e-01 3.86416852e-01 -4.07994501e-02 -5.83015800e-01
7.42284209e-02 -5.83511591e-01 -7.86596179e-01 -6.28366232e-01
3.17275614e-01 2.88284630e-01 -8.77177864e-02 -9.07273293e-02
6.16696596e-01 7.75139630e-01 -1.62264657e+00 3.37931067e-01
6.37745202e-01 8.43702376e-01 -1.08858638e-01 7.32496560e-01
3.90578061e-02 8.72114718e-01 -7.38934159e-01 -5.57020485e-01
6.85033560e-01 -4.94081348e-01 -6.11922920e-01 3.48902613e-01
8.77719760e-01 -4.69004512e-01 -9.51886177e-02 1.07800627e+00
4.06882703e-01 1.71714842e-01 7.26661921e-01 -1.57699490e+00
-1.02612185e+00 2.18870610e-01 -8.04048777e-01 2.11200178e-01
3.80656451e-01 6.85526311e-01 5.68446040e-01 -4.36837226e-01
5.87188542e-01 1.40275538e+00 4.13966537e-01 5.38005292e-01
-1.34055650e+00 -8.91231060e-01 -1.84447020e-02 2.00483546e-01
-9.86819565e-01 -4.37381148e-01 8.06557178e-01 -6.28932536e-01
5.67703664e-01 1.84872553e-01 5.24986684e-01 1.46118522e+00
1.94650203e-01 4.14056003e-01 1.67182732e+00 -4.34667498e-01
3.29530269e-01 2.96065837e-01 -5.16977813e-03 5.41650534e-01
3.25249344e-01 4.46017087e-01 -5.40151954e-01 -2.29734272e-01
9.43154573e-01 -3.44711542e-01 -4.40187514e-01 -2.39478230e-01
-9.47898388e-01 7.86535800e-01 3.06337446e-01 1.80283651e-01
-5.05542278e-01 2.21899331e-01 1.68599144e-01 4.48983423e-02
1.42762363e-01 7.18928695e-01 7.07637593e-02 -1.99882742e-02
-8.86863291e-01 1.50251076e-01 4.79093492e-01 6.38264537e-01
5.03471732e-01 5.27520597e-01 -5.60829937e-02 3.34514618e-01
-1.35590062e-01 2.75051564e-01 4.64133233e-01 -1.04880750e+00
1.66017458e-01 3.64940524e-01 3.73443402e-02 -1.14977705e+00
-9.81657505e-02 -1.73425376e-01 -7.81438053e-01 9.01500583e-01
8.52758944e-01 3.82939056e-02 -1.01555967e+00 1.67350376e+00
7.13923350e-02 4.95192148e-02 -3.71184088e-02 1.07359362e+00
3.08895707e-01 4.80290830e-01 3.20266038e-01 1.37583584e-01
1.41059959e+00 -5.55616438e-01 -3.03250968e-01 -3.89098048e-01
-8.25382993e-02 -6.52194977e-01 1.37240362e+00 6.76336706e-01
-1.03740823e+00 -8.33432317e-01 -1.05595124e+00 -1.45664662e-01
-4.73763883e-01 3.56848724e-02 6.50651991e-01 9.73549843e-01
-1.00263464e+00 6.18582785e-01 -4.94519114e-01 -4.37042713e-01
4.03422028e-01 1.31530717e-01 -3.45974118e-01 -1.84029620e-02
-8.33587229e-01 8.90898407e-01 3.38369280e-01 -3.02120596e-02
-8.50491941e-01 -5.50322592e-01 -7.52377748e-01 1.85323566e-01
2.53399372e-01 -5.36325395e-01 8.46079886e-01 -1.44230890e+00
-1.06361210e+00 1.04297519e+00 1.35282561e-01 -4.59212273e-01
7.32082963e-01 2.19802320e-01 -3.24740350e-01 3.07239830e-01
7.54857436e-02 8.71993423e-01 1.13261163e+00 -1.60824764e+00
-3.56705487e-01 -4.81562346e-01 2.62001812e-01 -1.99617390e-02
-9.69039649e-02 -1.57758340e-01 -1.96003374e-02 -6.88720286e-01
-2.71410257e-01 -1.02069676e+00 4.62663546e-02 2.94563234e-01
-4.51774120e-01 1.21602617e-01 6.09778106e-01 -8.56387019e-01
3.17290187e-01 -2.21376157e+00 -3.70033205e-01 1.61311790e-01
3.53540808e-01 1.72863930e-01 -2.20491573e-01 7.81503543e-02
-4.40684110e-01 3.78663123e-01 -1.78177595e-01 -1.87105179e-01
9.01058987e-02 -6.70751780e-02 -5.62382638e-01 6.60621226e-01
2.31583759e-01 7.81620324e-01 -7.26776898e-01 -3.15861940e-01
3.70056361e-01 5.40425897e-01 -2.01592594e-01 1.98631257e-01
4.54561040e-02 4.82893914e-01 -7.94345289e-02 4.50841278e-01
7.23314166e-01 -8.06949288e-02 2.40082014e-02 -3.48478109e-01
8.78611580e-02 -3.43478233e-01 -7.91785479e-01 1.14699638e+00
-2.66562015e-01 9.82799113e-01 -1.39860958e-02 -7.96025038e-01
7.21830070e-01 9.46751535e-02 1.42564848e-01 -1.04654467e+00
2.58508593e-01 -3.18840221e-02 1.93128422e-01 -2.40693510e-01
6.75980985e-01 -1.88248262e-01 7.39921033e-02 8.59342217e-01
-1.83269575e-01 -1.82743266e-01 -1.40414592e-02 2.54647464e-01
8.33390951e-01 1.33077413e-01 1.64851084e-01 -4.64307889e-02
1.56341001e-01 3.04505266e-02 2.08451912e-01 9.79508996e-01
-2.98084468e-01 8.60650003e-01 5.72620809e-01 -3.80762815e-01
-1.14112663e+00 -1.06909919e+00 2.86131650e-01 9.91357684e-01
2.94508964e-01 8.00449476e-02 -9.64280725e-01 -4.41782326e-01
-5.52341454e-02 1.26982021e+00 -8.77099931e-01 -2.70854354e-01
-2.89382130e-01 -4.51202989e-01 6.97521687e-01 3.46623659e-01
5.38595259e-01 -1.32013953e+00 -1.11436343e+00 -2.82223910e-01
-6.91539049e-02 -1.27207184e+00 -4.61237013e-01 -6.14152737e-02
-4.60911483e-01 -1.38207459e+00 -3.10114384e-01 -1.71756849e-01
6.07340693e-01 4.70695972e-01 1.13705873e+00 2.09027797e-01
-5.51635623e-01 7.14655042e-01 -2.32722670e-01 -3.60854715e-01
-6.02120578e-01 -5.77519357e-01 -2.24965319e-01 9.09177065e-02
1.94948912e-01 -5.09726584e-01 -5.62097132e-01 1.14867128e-01
-1.23630035e+00 1.61670178e-01 6.28446698e-01 5.24683237e-01
1.70036361e-01 2.09957972e-01 -1.18590303e-01 -9.76105392e-01
8.84489417e-01 -2.52652794e-01 -5.24952054e-01 3.78396899e-01
-5.84705353e-01 8.94586518e-02 7.73309946e-01 -4.92655128e-01
-1.03944588e+00 -1.24958627e-01 4.20763463e-01 -5.02166510e-01
-6.00874662e-01 -8.89712386e-03 -4.54051234e-03 -3.28227878e-01
8.78715694e-01 2.65516222e-01 -7.49103772e-03 -4.62721400e-02
6.30340695e-01 3.87378067e-01 8.97868216e-01 -7.28162348e-01
9.79001284e-01 6.24105215e-01 -1.53534621e-01 -8.40972304e-01
-3.15570951e-01 2.37780344e-02 -4.16802526e-01 -4.16690677e-01
9.28382874e-01 -6.58459604e-01 -8.56731832e-01 5.56123614e-01
-1.29888892e+00 -2.23168030e-01 -2.19619632e-01 1.09069459e-01
-6.32591665e-01 5.86251795e-01 -5.55244744e-01 -1.00805092e+00
-2.20988616e-01 -1.16053367e+00 9.46240842e-01 1.43599898e-01
-2.58318931e-01 -8.15487504e-01 -5.12430608e-01 5.70104718e-01
4.61960524e-01 6.46005690e-01 1.23551190e+00 -5.76079726e-01
-6.32211387e-01 1.31496601e-02 -5.25113523e-01 2.61322856e-01
-4.44728881e-02 -1.52522083e-02 -1.27353585e+00 -1.85656577e-01
2.17488602e-01 -4.86828536e-01 7.28258073e-01 2.69337088e-01
1.34068263e+00 -1.98838398e-01 1.96064487e-01 5.33200204e-01
1.40962648e+00 3.37088764e-01 9.41756248e-01 3.01237851e-01
5.93834758e-01 8.32622230e-01 1.92956418e-01 1.11438736e-01
9.51002762e-02 3.15691382e-01 5.82784235e-01 -4.50493068e-01
-2.44825214e-01 -2.07321212e-01 3.43116462e-01 -3.02798934e-02
6.09314702e-02 -5.67643583e-01 -7.28035629e-01 3.21829438e-01
-1.42807841e+00 -1.09720850e+00 1.08244151e-01 2.25655103e+00
2.57506043e-01 1.82370573e-01 1.30053610e-01 -3.93196605e-02
1.00058496e+00 2.31523998e-02 -8.63754690e-01 -5.18034339e-01
-1.39833838e-01 2.78714508e-01 6.57670557e-01 1.17230907e-01
-7.45960891e-01 7.02372849e-01 6.42385530e+00 6.99840128e-01
-1.42307544e+00 -1.03715897e-01 1.12258041e+00 1.13421343e-01
-1.28473401e-01 9.50449035e-02 5.49357198e-02 4.93080229e-01
6.76253200e-01 -3.93411741e-02 8.28622401e-01 7.95289099e-01
2.38289759e-01 -2.58954525e-01 -1.06505072e+00 1.29510748e+00
3.36853325e-01 -1.08940339e+00 2.20281973e-01 2.15183109e-01
4.19196397e-01 -4.01332647e-01 4.39362645e-01 -1.07178040e-01
5.22739291e-01 -1.20088112e+00 9.13138151e-01 4.04875576e-01
7.05962956e-01 -4.54602212e-01 2.59164065e-01 1.80053636e-01
-7.32604086e-01 -1.38842925e-01 -1.83245778e-01 1.47193149e-02
5.58713824e-02 2.17708051e-01 -7.22212136e-01 1.65061504e-01
4.51317817e-01 2.03527033e-01 -8.65169942e-01 6.60965204e-01
-1.65677115e-01 4.23297822e-01 1.06913941e-02 4.31311548e-01
1.39551267e-01 -1.87698811e-01 2.28784859e-01 8.33229482e-01
3.08245480e-01 1.07474059e-01 -4.83635329e-02 1.48466682e+00
1.69708893e-01 -1.68329000e-01 -5.09361565e-01 -2.39075348e-01
3.53768229e-01 1.30216050e+00 -1.13208902e+00 -1.02151453e-01
-3.41877863e-02 1.22121561e+00 -4.66602184e-02 5.67607462e-01
-9.23863709e-01 -2.11711153e-01 3.26375127e-01 2.45018765e-01
2.51724496e-02 -1.49582908e-01 -3.50775719e-01 -9.58544612e-01
-3.06821000e-02 -1.08649814e+00 2.10589528e-01 -1.40343654e+00
-1.47110581e+00 9.20780599e-01 5.27668297e-02 -1.01896703e+00
-4.95672703e-01 -8.59853983e-01 -7.36731350e-01 8.03180993e-01
-1.28582382e+00 -1.25249231e+00 -6.53597891e-01 6.34564102e-01
3.47390383e-01 -1.10457100e-01 3.61243546e-01 -8.40570629e-02
-2.40090877e-01 5.10169446e-01 -2.59618163e-01 1.89885214e-01
7.54865408e-01 -1.17189121e+00 7.14435518e-01 1.09295297e+00
2.26720661e-01 7.44864464e-01 6.66047812e-01 -4.74064559e-01
-1.12001276e+00 -7.57091939e-01 4.88184914e-02 -2.72250056e-01
3.38098139e-01 -3.49680185e-01 -8.12676132e-01 3.43202412e-01
4.29990023e-01 -2.29519039e-01 5.12260318e-01 -2.98242807e-01
-6.67508662e-01 3.30485672e-01 -1.41027641e+00 5.60462296e-01
8.29101741e-01 -7.98224032e-01 -4.55592513e-01 1.66902974e-01
3.92239392e-01 -1.43608168e-01 -4.05503660e-01 -4.65573668e-02
6.53786182e-01 -1.39498544e+00 9.71875608e-01 -5.08252263e-01
5.70669234e-01 -2.59565890e-01 2.28216709e-03 -1.27576053e+00
-1.16542257e-01 -3.62531215e-01 4.53143001e-01 1.12822258e+00
8.06935038e-03 -7.05011606e-01 7.73262382e-01 1.01391995e+00
2.63287872e-01 -1.44184217e-01 -6.84954047e-01 -5.40002346e-01
9.86720473e-02 -4.25368279e-01 5.25374174e-01 9.68453825e-01
-5.51101685e-01 1.05462499e-01 -4.03161287e-01 3.97591069e-02
8.55991662e-01 2.05015630e-01 8.73955965e-01 -1.06578040e+00
-5.09802818e-01 -6.17645025e-01 -4.78500962e-01 -4.05590802e-01
2.96279490e-01 -5.75054348e-01 -9.16575864e-02 -1.11348557e+00
1.52712107e-01 -2.10052118e-01 9.00315866e-02 4.78536665e-01
-5.80957197e-02 4.61893141e-01 6.86791122e-01 1.37795687e-01
-9.60667953e-02 2.10618734e-01 9.55967128e-01 -1.65171713e-01
1.64827660e-01 -5.01538396e-01 -1.13895571e+00 6.38806045e-01
6.97684824e-01 -2.56323844e-01 -5.86715698e-01 -4.78492826e-01
-1.29569098e-01 6.62819855e-03 9.54562247e-01 -1.12773490e+00
1.23261698e-01 -2.61583090e-01 7.62981057e-01 -1.10400662e-01
3.71706694e-01 -7.43715167e-01 4.53943044e-01 2.58571327e-01
-3.09111178e-01 1.98898554e-01 3.42833728e-01 4.82676864e-01
2.53848135e-02 1.78990178e-02 8.56526911e-01 -4.26994026e-01
-8.62376869e-01 4.58214469e-02 -4.17868435e-01 6.31830841e-03
8.68616521e-01 -7.40323901e-01 -6.88889086e-01 -8.24739099e-01
-5.24132729e-01 -3.23231637e-01 8.48878443e-01 4.38916922e-01
5.96374094e-01 -1.02654779e+00 -5.38754404e-01 2.06452444e-01
2.57508885e-02 -5.38980722e-01 3.55779320e-01 3.94966662e-01
-5.93357444e-01 -1.22537920e-02 -6.67170703e-01 -3.35632265e-01
-1.02692270e+00 7.10777223e-01 3.24885398e-01 1.10246070e-01
-2.81588078e-01 4.22314286e-01 6.66423142e-01 -1.52179182e-01
-1.76369343e-02 -3.82510386e-02 9.26030874e-02 -2.13675573e-01
4.34443146e-01 4.22654957e-01 -7.77170211e-02 -8.37109685e-01
-2.17118151e-02 4.54245627e-01 1.47562876e-01 -2.23012343e-01
1.02166533e+00 7.01863691e-02 -2.69059222e-02 2.06750900e-01
1.04629612e+00 -3.26574221e-02 -1.25920653e+00 2.94976234e-01
-2.99359888e-01 -8.04346502e-01 -1.02860644e-01 -8.95664334e-01
-1.30204034e+00 9.97152269e-01 9.46542799e-01 5.02863601e-02
1.28079772e+00 -2.62813181e-01 5.38576365e-01 1.66511014e-02
2.66114146e-01 -8.76929462e-01 2.89981842e-01 -1.35398254e-01
7.20985830e-01 -1.02454674e+00 2.16108784e-02 -2.95341104e-01
-8.71120572e-01 1.22371626e+00 8.14672828e-01 -2.45100215e-01
2.47690342e-02 -4.59667929e-02 2.28196114e-01 -2.36446843e-01
-3.17631841e-01 -9.89122540e-02 1.98334932e-01 9.08304930e-01
2.12605581e-01 -1.14482597e-01 1.31183729e-01 2.18261912e-01
-3.32881719e-01 -2.16405794e-01 8.48527074e-01 6.16822064e-01
1.78281032e-02 -8.95158410e-01 -7.93528259e-01 3.44344348e-01
-3.39935243e-01 -7.39633217e-02 -7.80304253e-01 1.06706059e+00
2.63022095e-01 9.83867049e-01 1.53654665e-01 -3.88164967e-01
7.15274885e-02 -4.06874157e-02 5.41233063e-01 -2.02633664e-01
-6.98044658e-01 -2.10323185e-01 -3.44232857e-01 -5.53444684e-01
-3.79156917e-01 -5.45574844e-01 -8.47666323e-01 -3.61672342e-01
-1.70774072e-01 -9.27238017e-02 7.70251989e-01 8.42219412e-01
3.33241999e-01 2.05279514e-01 2.87909031e-01 -1.10824037e+00
-4.02936488e-01 -6.44355416e-01 -5.99396408e-01 1.06114113e+00
1.72825575e-01 -5.43744624e-01 -7.01594830e-01 1.54192209e-01] | [11.861541748046875, 0.7496405243873596] |
28825fd7-5dd2-4f6a-aa20-1cf902b75c1e | a-distance-aware-multi-task-framework-for | null | null | https://aclanthology.org/2022.coling-1.76 | https://aclanthology.org/2022.coling-1.76.pdf | A Distance-Aware Multi-Task Framework for Conversational Discourse Parsing | Conversational discourse parsing aims to construct an implicit utterance dependency tree to reflect the turn-taking in a multi-party conversation. Existing works are generally divided into two lines: graph-based and transition-based paradigms, which perform well for short-distance and long-distance dependency links, respectively. However, there is no study to consider the advantages of both paradigms to facilitate conversational discourse parsing. As a result, we propose a distance-aware multi-task framework DAMT that incorporates the strengths of transition-based paradigm to facilitate the graph-based paradigm from the encoding and decoding process. To promote multi-task learning on two paradigms, we first introduce an Encoding Interactive Module (EIM) to enhance the flow of semantic information between both two paradigms during the encoding step. And then we apply a Distance-Aware Graph Convolutional Network (DAGCN) in the decoding process, which can incorporate the different-distance dependency links predicted by the transition-based paradigm to facilitate the decoding of the graph-based paradigm. The experimental results on the datasets STAC and Molweni show that our method can significantly improve the performance of the SOTA graph-based paradigm on long-distance dependency links. | ['Qiaoming Zhu', 'Fang Kong', 'Peifeng Li', 'Yaxin Fan'] | null | null | null | null | coling-2022-10 | ['discourse-parsing'] | ['natural-language-processing'] | [ 9.76835042e-02 3.75028908e-01 2.41686795e-02 -5.79847634e-01
-6.38564706e-01 -3.98241490e-01 5.96518397e-01 4.91008162e-04
-6.87630624e-02 4.10856724e-01 7.38787711e-01 -5.63131213e-01
4.48605083e-02 -1.03550553e+00 -4.47314382e-01 -3.93295288e-01
6.67707901e-03 5.41416287e-01 4.19113427e-01 -6.62206590e-01
2.75154799e-01 -2.18596533e-01 -1.02515543e+00 9.27621484e-01
1.12342203e+00 6.07194781e-01 4.15466875e-01 8.03552687e-01
-8.53690088e-01 1.10672438e+00 -5.93398035e-01 -3.99137050e-01
-2.91392386e-01 -8.42673898e-01 -1.33347273e+00 -1.10300586e-01
-2.18807787e-01 -3.24787199e-01 -3.57219517e-01 7.57149160e-01
5.83190799e-01 2.49284819e-01 3.15936297e-01 -1.12043107e+00
-6.89318299e-01 1.10750210e+00 -2.19930172e-01 1.59818873e-01
7.73868203e-01 2.36964654e-02 1.13848841e+00 -4.30976659e-01
5.89393556e-01 1.56955945e+00 4.31037903e-01 5.54273665e-01
-3.52476805e-01 -5.54072142e-01 5.90093911e-01 6.33786142e-01
-8.23810279e-01 -2.60753661e-01 1.19865119e+00 -2.45046467e-01
1.30968308e+00 1.42098904e-01 5.06795406e-01 1.08440900e+00
-4.83026393e-02 1.10624051e+00 9.28486526e-01 -3.11647087e-01
-2.40674779e-01 -4.39162880e-01 5.75272620e-01 8.39561522e-01
-5.04642427e-01 -1.33843124e-01 -5.24060547e-01 1.40742943e-01
3.54162306e-01 -5.08595586e-01 -2.85181612e-01 1.64348885e-01
-1.01909554e+00 8.58190775e-01 6.56836927e-01 5.18296659e-01
8.16420466e-02 -1.93635508e-01 8.53764713e-01 4.78458524e-01
5.35132706e-01 4.99051288e-02 -1.77598730e-01 -3.53437603e-01
-2.39274934e-01 -1.73775351e-03 1.01740921e+00 1.15537810e+00
7.03933179e-01 -3.34593445e-01 -5.38587451e-01 9.54529941e-01
5.40947497e-01 -1.18805528e-01 3.96718532e-01 -5.62090874e-01
1.21632791e+00 1.09055662e+00 -4.61913884e-01 -1.02948499e+00
-8.20693851e-01 -9.30125415e-02 -7.67259061e-01 -3.49645555e-01
5.21020174e-01 -2.73743331e-01 -4.58470255e-01 1.75138986e+00
5.20310163e-01 2.47488692e-01 3.53289455e-01 9.13936079e-01
1.49785042e+00 8.30952048e-01 7.16862604e-02 -2.49847069e-01
1.54313707e+00 -1.62632704e+00 -1.03281796e+00 -3.61284465e-01
1.32818782e+00 -7.15202212e-01 1.12865138e+00 -1.06046952e-01
-8.49290848e-01 -7.03948081e-01 -1.12273991e+00 -5.20359397e-01
-2.30665237e-01 -2.60161787e-01 5.18396676e-01 3.93206537e-01
-7.84018457e-01 2.66352892e-01 -4.57165837e-01 -6.85423389e-02
1.03721663e-01 -2.70354822e-02 -1.60599038e-01 -2.36425370e-01
-1.67085779e+00 9.75421786e-01 5.92029035e-01 5.16659439e-01
-4.08837736e-01 -2.36711726e-01 -1.12415111e+00 1.03838906e-01
3.59155059e-01 -6.25658393e-01 1.29246294e+00 -9.01883185e-01
-1.77208149e+00 6.87066495e-01 -2.39806846e-01 -1.23615757e-01
4.36767310e-01 6.04779087e-02 -1.89674407e-01 5.64578772e-02
1.56439946e-03 3.58576566e-01 1.40137956e-01 -9.76561308e-01
-5.80127597e-01 -3.02466750e-01 6.76480174e-01 7.72466302e-01
-7.08897039e-02 -4.04180698e-02 -6.16744876e-01 -3.21967632e-01
1.15803763e-01 -9.42314267e-01 1.36229739e-01 -5.30311048e-01
-6.69420600e-01 -7.56864727e-01 1.05701172e+00 -9.46888864e-01
1.46627855e+00 -1.92398894e+00 4.25154001e-01 -3.49030823e-01
2.27852240e-01 4.24248159e-01 -3.97846341e-01 7.57191718e-01
1.02288418e-01 -5.81498584e-03 -1.37976781e-01 -4.38368291e-01
-1.38652578e-01 4.13842678e-01 2.15372041e-01 -3.05678360e-02
1.43452823e-01 1.10858428e+00 -1.15648472e+00 -6.07584596e-01
1.71995297e-01 1.63761303e-01 -4.44911450e-01 6.77877545e-01
-4.42934960e-01 7.28053510e-01 -6.99611008e-01 2.34966546e-01
6.21679544e-01 -2.37159669e-01 7.55260348e-01 -3.47661912e-01
-1.37028098e-02 9.45104897e-01 -6.42569900e-01 2.12979960e+00
-6.57381773e-01 5.30160189e-01 1.83548674e-01 -1.15766442e+00
1.03783822e+00 4.64941204e-01 -5.71627282e-02 -8.35753679e-01
2.68073410e-01 4.06788997e-02 4.77937251e-01 -9.21720147e-01
4.85853463e-01 -7.53851458e-02 -3.50015610e-01 5.58534205e-01
-9.95011330e-02 1.70331746e-01 -1.16578368e-02 3.76076400e-01
1.14300358e+00 2.27696925e-01 4.09505405e-02 -6.33910969e-02
8.58255327e-01 -8.39669779e-02 6.15015030e-01 2.30837181e-01
-2.73580998e-01 3.66312206e-01 9.52005923e-01 -3.53475243e-01
-5.38542569e-01 -4.44282591e-01 3.76471996e-01 1.39499795e+00
3.62684757e-01 -5.23594499e-01 -8.27902377e-01 -1.16580999e+00
-3.70368689e-01 7.15238035e-01 -5.33363879e-01 -1.06948726e-01
-1.07115316e+00 -6.83324099e-01 6.07044339e-01 5.30047894e-01
9.65510249e-01 -1.13001704e+00 3.20432559e-02 3.25387359e-01
-7.71008909e-01 -1.31505811e+00 -5.00211596e-01 -8.14555585e-02
-4.48808044e-01 -1.32302678e+00 -3.08115274e-01 -1.06572127e+00
4.46788818e-01 3.76652628e-01 8.80668879e-01 5.56150138e-01
4.18228120e-01 -1.33098068e-03 -9.14002240e-01 3.71154808e-02
-6.32505059e-01 4.06872690e-01 -7.27669895e-01 -1.48673400e-01
3.01630586e-01 -5.54095685e-01 -3.30815434e-01 2.83469975e-01
-4.00602758e-01 7.83969581e-01 2.25343525e-01 8.01655769e-01
-8.19372684e-02 -3.69374961e-01 8.92123640e-01 -1.34142053e+00
1.03428304e+00 -6.62010729e-01 -6.55051470e-02 4.51562494e-01
-3.20764661e-01 5.80029339e-02 7.09757507e-01 -1.96614847e-01
-1.36147690e+00 -3.74638498e-01 -5.04731059e-01 2.02101946e-01
1.57829702e-01 8.08333278e-01 -6.27811432e-01 3.45085531e-01
1.05383001e-01 1.12713255e-01 -6.20132722e-02 -3.77854347e-01
5.56819558e-01 1.10675180e+00 3.18252504e-01 -8.64180148e-01
1.60247803e-01 -1.03521712e-01 -2.78708011e-01 -5.14987648e-01
-1.02246809e+00 -3.09281617e-01 -7.30332792e-01 -4.14892316e-01
1.31578422e+00 -7.02451289e-01 -8.69782746e-01 7.16044843e-01
-1.64381790e+00 -6.62768781e-01 3.23146939e-01 2.20513508e-01
-5.01505017e-01 7.13011801e-01 -9.25599039e-01 -6.55669451e-01
-4.87561494e-01 -1.41517699e+00 9.03178036e-01 3.36577684e-01
-5.31077422e-02 -1.41913307e+00 -3.67036648e-02 9.99235928e-01
1.74767017e-01 1.89494699e-01 1.32781529e+00 -1.05889082e+00
-5.57039380e-01 2.59069979e-01 -5.28488219e-01 1.56272277e-01
2.02447668e-01 -2.94731915e-01 -9.52577710e-01 -1.05442427e-01
-2.15383679e-01 -3.20993602e-01 5.22960007e-01 -5.41396029e-02
9.65663493e-01 -1.65503979e-01 -3.16433042e-01 4.57471699e-01
8.44368875e-01 4.05169874e-01 7.57887721e-01 3.88078868e-01
1.07159400e+00 8.87036383e-01 6.45510733e-01 -5.86909056e-02
1.35358357e+00 7.39190936e-01 3.63026619e-01 -7.28686079e-02
-4.83231962e-01 -3.46438289e-01 3.35813016e-01 1.66370165e+00
-2.92064901e-03 -5.82567751e-01 -1.03511894e+00 3.62681776e-01
-2.28590250e+00 -7.41815686e-01 -5.44910967e-01 1.50504267e+00
8.06408167e-01 2.87886053e-01 3.83413397e-02 -1.25495732e-01
9.18980658e-01 5.47944188e-01 -3.55972022e-01 -7.74588645e-01
1.01243537e-02 -2.97027439e-01 -2.06913784e-01 7.71218359e-01
-8.52795660e-01 1.00767100e+00 5.58936644e+00 6.46135151e-01
-9.34018970e-01 1.91900536e-01 4.00427848e-01 3.76414806e-01
-4.53736126e-01 1.37633011e-01 -6.95882916e-01 5.12785137e-01
9.01869535e-01 -2.18609750e-01 2.12668344e-01 6.59808993e-01
1.52776256e-01 1.20203465e-01 -1.15346944e+00 6.81289673e-01
1.54986726e-02 -1.42465138e+00 9.75218639e-02 -2.41920739e-01
1.64709494e-01 -1.14979170e-01 -5.48031509e-01 7.79231310e-01
2.93450236e-01 -8.09387207e-01 3.53949547e-01 3.18654686e-01
4.34947520e-01 -7.45130658e-01 9.32069778e-01 7.31468797e-01
-1.60328472e+00 5.08402362e-02 -1.51329860e-01 -3.96265715e-01
3.42960894e-01 3.11613500e-01 -8.39717090e-01 1.16519761e+00
3.30421567e-01 7.46463060e-01 -2.44594246e-01 4.46199089e-01
-6.36789680e-01 5.26611090e-01 1.10413596e-01 -2.81189412e-01
5.50137401e-01 -4.96222794e-01 4.48161691e-01 1.49555469e+00
-1.34219406e-02 3.71868104e-01 5.31644166e-01 4.17308718e-01
-2.39184797e-01 1.00853443e-01 -4.70587879e-01 1.59135848e-01
6.95853055e-01 1.20157349e+00 -4.30557758e-01 -3.43501598e-01
-6.84769332e-01 9.97130930e-01 8.31738830e-01 1.23290539e-01
-8.36025298e-01 -4.54200923e-01 4.04350966e-01 -1.76820889e-01
1.19177990e-01 -3.84502798e-01 -9.56308693e-02 -9.15124178e-01
9.88102928e-02 -8.96988809e-01 6.07506335e-01 -7.97874808e-01
-1.24134338e+00 8.61794293e-01 6.42486289e-02 -9.12533939e-01
-2.66790390e-01 -4.23969835e-01 -1.19453621e+00 1.05224729e+00
-1.73631895e+00 -1.60172844e+00 -4.02041435e-01 4.21974540e-01
8.93770874e-01 4.24225815e-02 8.82771790e-01 3.10980022e-01
-9.05267477e-01 5.13453960e-01 -2.78449893e-01 5.72311580e-01
4.72513765e-01 -1.14567637e+00 4.89055991e-01 6.72166884e-01
-3.39810789e-01 2.89549321e-01 1.54207304e-01 -6.27188087e-01
-1.34010303e+00 -9.93645966e-01 9.28306520e-01 -2.08072022e-01
5.72878897e-01 -3.52410197e-01 -1.27936065e+00 8.27775717e-01
5.02214432e-01 -3.89664382e-01 8.51679683e-01 6.63013160e-01
-4.21096355e-01 2.65930265e-01 -6.77382767e-01 3.97198409e-01
1.26085889e+00 -6.61649585e-01 -1.00300252e+00 3.90916884e-01
1.07711005e+00 -7.69816279e-01 -9.21241403e-01 3.92067283e-01
2.33803406e-01 -1.04236734e+00 6.73550010e-01 -5.37423909e-01
7.08363295e-01 -8.61100256e-02 1.08668901e-01 -1.37351167e+00
-3.04051220e-01 -5.90225756e-01 -7.90748596e-02 1.56966984e+00
4.86053586e-01 -5.86847961e-01 5.08838594e-01 2.61503100e-01
-7.07521319e-01 -8.36897075e-01 -1.07654142e+00 -4.52589542e-01
2.74594247e-01 -4.05787408e-01 7.70948827e-01 1.18508375e+00
5.17155468e-01 1.09884465e+00 -1.87842578e-01 1.70527101e-02
2.22452749e-02 4.38976645e-01 8.49408209e-01 -9.09794033e-01
-1.33547142e-01 -4.91090953e-01 1.22098021e-01 -1.71089828e+00
5.10715544e-01 -1.24471080e+00 5.79443686e-02 -2.12564325e+00
-5.39153535e-03 -6.95181489e-01 6.15028627e-02 3.98290664e-01
-5.81036508e-01 -4.94172990e-01 3.19821179e-01 1.79102853e-01
-7.55884349e-01 7.98106611e-01 1.68603086e+00 -1.30496696e-01
-2.58979917e-01 -1.32900521e-01 -7.70161867e-01 7.49708712e-01
7.13475227e-01 -2.50228852e-01 -7.14819252e-01 -8.56571555e-01
1.03761636e-01 5.97607791e-01 -1.18555225e-01 -5.79578221e-01
4.01737601e-01 -1.00277320e-01 -3.66429269e-01 -7.57961631e-01
3.50337982e-01 -2.88081646e-01 -4.26714957e-01 1.60024077e-01
-3.73844922e-01 7.07894564e-04 1.38885528e-01 4.62360233e-01
-3.47669423e-01 -9.11210999e-02 3.78475547e-01 -7.36389607e-02
-7.21641183e-01 -2.06603725e-02 -2.53781676e-01 2.28302374e-01
8.71130168e-01 -1.48823122e-02 -9.10426915e-01 -4.90498722e-01
-5.82748353e-01 8.39183033e-01 -1.84315622e-01 7.30112314e-01
4.64136899e-01 -1.25323594e+00 -9.11732554e-01 2.16646716e-02
7.71236420e-02 3.64410251e-01 3.77994239e-01 8.52545917e-01
-5.20212889e-01 1.85029089e-01 -7.99842328e-02 -4.95570272e-01
-1.49129081e+00 3.59008640e-01 3.07655931e-01 -7.97165811e-01
-6.63039625e-01 9.56485987e-01 2.37756342e-01 -8.90315235e-01
9.64366719e-02 -2.67962128e-01 -6.46375418e-01 1.75831035e-01
4.42779601e-01 1.96173653e-01 -1.18310833e-02 -7.79778779e-01
-3.26874793e-01 4.24701601e-01 -1.86190099e-01 1.65582359e-01
1.13709104e+00 -3.96404177e-01 -3.17936540e-01 4.74515945e-01
1.21589410e+00 -1.71357334e-01 -1.03971672e+00 -2.92810172e-01
9.39649865e-02 -9.82948393e-02 -8.54584053e-02 -7.37321913e-01
-8.54177058e-01 1.18205333e+00 -7.28405714e-02 5.89040101e-01
1.05972433e+00 -8.21421146e-02 1.18982053e+00 3.39076936e-01
1.31275341e-01 -9.92825150e-01 1.41301915e-01 1.08302331e+00
9.52203929e-01 -9.70343351e-01 -2.96896189e-01 -1.00771761e+00
-7.88794696e-01 1.34532225e+00 9.22978461e-01 7.88614228e-02
4.85506207e-01 1.81717604e-01 2.16375098e-01 -2.76764274e-01
-8.66144896e-01 -2.93563902e-01 1.86963722e-01 7.37175345e-01
8.30872536e-01 1.09265000e-01 -5.10221660e-01 7.10353613e-01
-2.39181608e-01 -3.77792150e-01 3.41831982e-01 7.21475184e-01
-4.76993054e-01 -1.48546994e+00 7.96501711e-02 7.01079890e-02
2.01556429e-01 -1.84933111e-01 -5.95825791e-01 8.28474164e-01
3.63496430e-02 1.33088136e+00 1.22268073e-01 -7.24876344e-01
4.87095535e-01 3.07533830e-01 3.15845490e-01 -7.74603069e-01
-9.76707697e-01 -1.27195656e-01 9.73358214e-01 -4.05972660e-01
-5.78712344e-01 -2.45468110e-01 -1.69158602e+00 -4.74161416e-01
-4.84441698e-01 2.95263410e-01 4.07902449e-01 1.39978647e+00
3.02255571e-01 1.05204415e+00 6.29942834e-01 -4.84491646e-01
-1.23235226e-01 -1.15855205e+00 -4.10426408e-02 3.36545378e-01
-2.65662838e-02 -4.25237954e-01 -9.91951972e-02 -3.68183732e-01] | [12.358169555664062, 7.878538131713867] |
5d722b89-788d-449e-a3c7-994f109f22c0 | training-set-cleansing-of-backdoor-poisoning | 2210.10272 | null | https://arxiv.org/abs/2210.10272v2 | https://arxiv.org/pdf/2210.10272v2.pdf | Training set cleansing of backdoor poisoning by self-supervised representation learning | A backdoor or Trojan attack is an important type of data poisoning attack against deep neural network (DNN) classifiers, wherein the training dataset is poisoned with a small number of samples that each possess the backdoor pattern (usually a pattern that is either imperceptible or innocuous) and which are mislabeled to the attacker's target class. When trained on a backdoor-poisoned dataset, a DNN behaves normally on most benign test samples but makes incorrect predictions to the target class when the test sample has the backdoor pattern incorporated (i.e., contains a backdoor trigger). Here we focus on image classification tasks and show that supervised training may build stronger association between the backdoor pattern and the associated target class than that between normal features and the true class of origin. By contrast, self-supervised representation learning ignores the labels of samples and learns a feature embedding based on images' semantic content. %We thus propose to use unsupervised representation learning to avoid emphasising backdoor-poisoned training samples and learn a similar feature embedding for samples of the same class. Using a feature embedding found by self-supervised representation learning, a data cleansing method, which combines sample filtering and re-labeling, is developed. Experiments on CIFAR-10 benchmark datasets show that our method achieves state-of-the-art performance in mitigating backdoor attacks. | ['G. Kesidis', 'D. J. Miller', 'Z. Xiang', 'J. Chen', 'E. Emamjomeh-Zadeh', 'H. Ritter', 'O. Dia', 'S. Karami', 'H. Wang'] | 2022-10-19 | null | null | null | null | ['data-poisoning'] | ['adversarial'] | [ 5.00930190e-01 3.73713598e-02 -5.24514198e-01 -2.63697773e-01
-4.65400457e-01 -9.63204622e-01 6.32139027e-01 2.63263881e-01
-3.11788797e-01 5.45579433e-01 -7.55823776e-02 -5.59843659e-01
1.75119236e-01 -1.10714006e+00 -1.18120015e+00 -1.09541500e+00
-4.93226685e-02 1.15536146e-01 1.44819811e-01 3.36549804e-02
1.51278630e-01 6.82474673e-01 -1.36581838e+00 8.38071346e-01
1.69569150e-01 1.10503542e+00 -3.06750000e-01 5.18203437e-01
-1.16342917e-01 1.15300620e+00 -1.28394592e+00 -4.42105651e-01
5.96376777e-01 -3.29962492e-01 -6.63945436e-01 -1.25709968e-02
9.44931209e-01 -4.95519787e-01 -8.42445135e-01 1.57307601e+00
5.94048873e-02 -3.13297689e-01 7.35871315e-01 -1.54176843e+00
-8.58090639e-01 5.74700058e-01 -2.22428471e-01 3.96361083e-01
1.18549757e-01 4.45276439e-01 6.99084640e-01 -7.49270499e-01
4.72206354e-01 1.07070065e+00 6.49262488e-01 1.07598448e+00
-1.31872916e+00 -1.30424488e+00 1.84597597e-01 1.71035483e-01
-1.10613775e+00 -3.51510614e-01 8.64335001e-01 -3.48356336e-01
4.91683096e-01 4.47259039e-01 3.56065720e-01 1.82942820e+00
4.23619658e-01 7.67189562e-01 9.07581568e-01 -2.36333117e-01
5.05825698e-01 4.40079182e-01 5.25380850e-01 6.86346531e-01
5.21976590e-01 6.78220987e-01 -3.90460193e-01 -5.22968531e-01
2.71510873e-02 5.06639957e-01 -3.34523976e-01 -4.13125813e-01
-6.90284729e-01 1.23645580e+00 7.04530597e-01 4.63682562e-02
-9.52817723e-02 6.01201393e-02 5.82998276e-01 5.59872925e-01
1.82639256e-01 5.78182518e-01 -3.92185867e-01 7.58588493e-01
-4.57337201e-01 1.69267043e-01 8.20733786e-01 7.41236031e-01
7.57634819e-01 2.09028348e-01 -1.10389099e-01 3.10716689e-01
1.40349090e-01 6.23249233e-01 7.08788216e-01 -2.72653371e-01
4.45745826e-01 6.92018926e-01 -1.99161604e-01 -9.36683059e-01
8.69152024e-02 -4.94387060e-01 -7.70628095e-01 5.48372626e-01
5.01891553e-01 -6.71608895e-02 -1.14376712e+00 1.70381796e+00
3.98963481e-01 2.51284093e-01 5.34908652e-01 5.23002028e-01
7.88713396e-01 6.86430693e-01 1.57400325e-01 1.99275818e-02
1.47552955e+00 -6.49503648e-01 -7.49792457e-01 -2.86510646e-01
8.68958533e-01 -1.48601145e-01 8.86004686e-01 5.42952895e-01
-1.16985671e-01 -3.01499456e-01 -1.65209568e+00 4.67624754e-01
-1.10184491e+00 -5.61404645e-01 5.66556036e-01 1.29255366e+00
-4.78297651e-01 6.70563638e-01 -3.59551102e-01 -1.82871874e-02
1.04408884e+00 4.80639040e-01 -7.55953491e-01 -5.03553808e-01
-1.31655788e+00 5.44277430e-01 5.41716635e-01 -4.49408591e-01
-1.71193779e+00 -8.72147620e-01 -8.27981114e-01 -2.05266133e-01
2.14010388e-01 -1.36401549e-01 8.07792902e-01 -1.08596599e+00
-7.67213643e-01 7.68376052e-01 3.90330285e-01 -9.50020432e-01
3.56647462e-01 -7.65270814e-02 -8.88228476e-01 4.25542563e-01
1.16862245e-01 4.53121841e-01 1.65736997e+00 -1.41927123e+00
-5.31708598e-01 -5.86192727e-01 -2.29826048e-02 -4.64068770e-01
-9.73356605e-01 -7.09453085e-03 5.71047008e-01 -7.83781767e-01
-6.28748536e-02 -4.71427411e-01 -1.93848070e-02 9.24968198e-02
-9.99640107e-01 6.94409152e-03 1.60297179e+00 -5.11255208e-03
8.67615521e-01 -2.35484576e+00 -6.62874460e-01 3.79089803e-01
5.12957573e-01 7.61427104e-01 -2.44087458e-01 2.61785150e-01
-7.49976218e-01 3.51932615e-01 -3.45316768e-01 4.53447513e-02
-2.33622372e-01 3.22964519e-01 -1.22375083e+00 9.26267266e-01
2.80186981e-01 5.27366698e-01 -1.11294627e+00 -1.21243075e-02
1.14745364e-01 3.94082129e-01 -2.95974404e-01 1.63917527e-01
-1.53663546e-01 1.61971878e-02 -4.22861993e-01 7.03661442e-01
7.87566781e-01 1.14681788e-01 -2.13272318e-01 -2.32006297e-01
3.13749373e-01 2.24536598e-01 -8.41022968e-01 7.33448863e-01
2.46459842e-02 5.14837801e-01 -3.89126182e-01 -9.32289422e-01
9.68664229e-01 3.53703082e-01 4.75234911e-02 -3.19222063e-01
3.30656379e-01 2.66244132e-02 -4.71812598e-02 -4.29625690e-01
-4.48239595e-02 -1.68786034e-01 4.26711738e-02 6.96237683e-01
3.07999253e-01 4.49830294e-01 -3.18822682e-01 3.49347800e-01
1.59637713e+00 -5.36931157e-01 1.76032320e-01 -1.89041451e-01
3.31708997e-01 9.21809822e-02 5.60140610e-01 1.11726010e+00
-4.28083658e-01 3.22839439e-01 6.21717572e-01 -8.72788727e-01
-7.85942137e-01 -1.34012234e+00 -3.54645580e-01 9.20225322e-01
-6.65101185e-02 -3.21203083e-01 -9.51425791e-01 -1.50965929e+00
3.27214032e-01 7.34468699e-01 -1.12786472e+00 -9.58656847e-01
-1.00278184e-01 -7.35700369e-01 1.07396209e+00 2.23268807e-01
5.62979400e-01 -1.11297643e+00 -4.05915707e-01 -5.59243597e-02
5.62087297e-01 -8.18459153e-01 -4.18357819e-01 8.39299858e-01
-8.03169429e-01 -1.50650072e+00 -8.23378637e-02 -7.32312739e-01
1.03388786e+00 2.86543220e-01 5.52229822e-01 1.93489745e-01
-3.98119301e-01 2.12206289e-01 -3.87242436e-01 -6.57522917e-01
-6.67781532e-01 -4.52241629e-01 4.73189116e-01 4.32475805e-01
6.65330768e-01 -3.47958177e-01 -2.84154177e-01 2.13552862e-01
-1.28296804e+00 -7.27580965e-01 4.03665990e-01 8.75516355e-01
4.99746412e-01 5.15725791e-01 6.73279047e-01 -1.47478449e+00
3.29875410e-01 -8.49324584e-01 -2.57665277e-01 2.22817227e-01
-3.23541820e-01 5.88935241e-02 1.25431800e+00 -1.14552414e+00
-2.47013673e-01 3.30457270e-01 7.07744211e-02 -1.12766099e+00
-4.48462367e-01 -2.27252394e-01 -7.19342411e-01 -3.12977791e-01
1.23371446e+00 6.11205578e-01 -4.71539609e-03 -3.39069337e-01
2.23954499e-01 5.88743865e-01 7.79095650e-01 -3.22882324e-01
1.38427651e+00 7.06869841e-01 -1.73090454e-02 -9.24541652e-01
-9.26077962e-01 -1.99571684e-01 -2.45748043e-01 1.77294370e-02
6.36014938e-01 -6.53597176e-01 -4.64763165e-01 6.79620445e-01
-1.01567185e+00 -1.57708779e-01 -5.81992328e-01 1.62589639e-01
-2.94126086e-02 3.16624254e-01 -3.40800881e-01 -7.49769211e-01
-2.00338691e-01 -9.87499952e-01 3.96069080e-01 -8.79075155e-02
-4.57106605e-02 -8.72124791e-01 -1.00570701e-01 3.33424509e-02
-9.81383249e-02 4.32267904e-01 1.12555063e+00 -1.75292683e+00
-3.30060869e-01 -8.15787196e-01 1.62768409e-01 8.03538263e-01
3.13610673e-01 -2.89753407e-01 -1.58836734e+00 -4.53340411e-01
6.47940755e-01 -5.72810650e-01 1.04335737e+00 -1.69737056e-01
1.55500138e+00 -8.95983934e-01 -3.92608047e-01 7.22902536e-01
1.31907213e+00 3.13727766e-01 6.84123158e-01 3.65772218e-01
9.31452930e-01 5.90326726e-01 1.79019973e-01 1.15225494e-01
-3.62501532e-01 1.08177446e-01 9.14318681e-01 2.70342920e-03
4.34179530e-02 -7.09202528e-01 6.63248718e-01 -1.54764891e-01
9.46706831e-01 -2.76529253e-01 -6.39369249e-01 3.19277376e-01
-1.26990771e+00 -1.08975077e+00 5.47359101e-02 2.34738469e+00
7.99927413e-01 3.57132405e-01 1.06982835e-01 7.93461621e-01
7.71947145e-01 2.17261016e-01 -7.93329775e-01 -3.60714406e-01
-2.73676097e-01 3.08438122e-01 8.23818803e-01 1.95300117e-01
-1.58653855e+00 9.74401951e-01 5.93808746e+00 1.00035858e+00
-1.12744844e+00 -2.47249976e-02 7.71224082e-01 1.18172206e-01
-2.59548515e-01 -3.52839172e-01 -9.42785740e-01 4.19219673e-01
9.53437984e-01 2.30740264e-01 3.66767734e-01 1.11021304e+00
-3.83402467e-01 4.29039568e-01 -1.64437532e+00 7.71250010e-01
3.41275424e-01 -1.54175460e+00 5.44245899e-01 3.86079550e-01
5.30032039e-01 -1.63169235e-01 4.54643279e-01 3.45799804e-01
3.36966306e-01 -1.11481559e+00 7.08432019e-01 3.18873860e-02
6.47705972e-01 -1.02340734e+00 5.63810408e-01 4.73220348e-01
-7.20290840e-01 -4.89460260e-01 -5.60139835e-01 2.37539247e-01
-8.68802547e-01 4.67417330e-01 -9.51084912e-01 -1.18211424e-02
7.25615323e-01 7.07458198e-01 -6.92752957e-01 7.73011684e-01
-4.40086007e-01 7.90548146e-01 8.09924584e-03 5.81656210e-02
3.30163419e-01 2.55468935e-01 7.29923964e-01 9.89776611e-01
-3.69802594e-01 -3.04958709e-02 8.31984803e-02 9.54741657e-01
-4.74590093e-01 -2.66144246e-01 -1.45447218e+00 -2.70307600e-01
6.40885651e-01 1.00838530e+00 -6.27180874e-01 -4.63075370e-01
-1.22832924e-01 8.07231724e-01 1.63041309e-01 3.47616732e-01
-5.05407333e-01 -5.47011077e-01 9.65528190e-01 -5.46675213e-02
2.45035782e-01 5.64004064e-01 -3.22204411e-01 -8.04290116e-01
-2.36694038e-01 -9.82021213e-01 6.09745681e-01 -2.37731338e-01
-1.69114637e+00 6.38404310e-01 -3.27493131e-01 -1.43876350e+00
4.63931412e-02 -1.04810286e+00 -8.58615398e-01 5.24208903e-01
-1.24769759e+00 -7.93539703e-01 3.47524732e-01 1.01926112e+00
1.62073269e-01 -7.51049817e-01 1.17966056e+00 -6.79976121e-02
-6.53075337e-01 1.05042899e+00 1.54677695e-02 7.50100911e-01
4.04696375e-01 -1.01023257e+00 2.37013817e-01 9.47030604e-01
4.02551264e-01 7.90635049e-01 6.52791262e-01 -7.62208998e-01
-1.49927831e+00 -1.79167879e+00 7.44783223e-01 -6.73890710e-01
7.70234704e-01 -7.23260880e-01 -1.15241337e+00 6.81623816e-01
-2.11119056e-01 6.33667290e-01 1.12382233e+00 -4.29446518e-01
-1.29750061e+00 -2.88474739e-01 -1.82956529e+00 4.52875972e-01
7.57932603e-01 -9.16767895e-01 -8.09732616e-01 6.65908754e-01
8.85138750e-01 1.49640962e-01 -3.66729319e-01 6.33404106e-02
2.34167621e-01 -7.53725052e-01 1.17156875e+00 -1.07619512e+00
2.16117591e-01 -3.43847960e-01 -4.75652933e-01 -1.06959581e+00
-1.21931814e-01 -3.35042030e-01 -5.26331484e-01 9.47179377e-01
1.00910217e-01 -8.28809679e-01 1.02555311e+00 1.34167820e-01
-3.13556865e-02 -6.74693704e-01 -9.54722106e-01 -1.12046599e+00
4.55824956e-02 -4.49048251e-01 7.70428777e-01 1.39818883e+00
-6.93082958e-02 1.88043639e-02 -2.35100493e-01 6.79375947e-01
1.13432360e+00 -4.03378963e-01 6.53522968e-01 -1.15457559e+00
-1.73778944e-02 -6.97029382e-02 -6.95295453e-01 -4.91536736e-01
4.40828919e-01 -1.08538008e+00 -1.59766093e-01 -5.16165257e-01
1.87240522e-02 -2.20518336e-01 -7.72332728e-01 8.76600385e-01
1.50640458e-01 6.73713624e-01 -8.10090452e-02 1.58124790e-01
-3.10162902e-01 3.11159402e-01 8.47944438e-01 -6.54148757e-01
4.40450460e-02 7.70611167e-02 -9.41628039e-01 6.68282986e-01
7.52150595e-01 -1.22272921e+00 -5.70460916e-01 -3.96036431e-02
-1.99638531e-01 -4.55027908e-01 7.27352917e-01 -1.08906460e+00
1.57013774e-01 8.02162141e-02 7.73901522e-01 -4.20517623e-01
1.87709942e-01 -1.12737203e+00 -1.66674271e-01 1.02930772e+00
-5.99753380e-01 -3.55685353e-01 1.40240476e-01 9.87804472e-01
1.12796195e-01 -5.18076539e-01 9.12029564e-01 -4.76254299e-02
-5.14778733e-01 5.31386316e-01 -5.65945864e-01 -7.26519525e-02
1.16984236e+00 -5.20032465e-01 -6.11381114e-01 8.77749324e-02
-2.87848532e-01 -1.21003583e-01 2.76813626e-01 3.64716440e-01
1.14087760e+00 -1.33203936e+00 -4.16297615e-01 8.15662444e-01
5.70341945e-01 -2.87797481e-01 -1.56748533e-01 -2.49310583e-02
-1.39756396e-01 1.09580547e-01 -1.39215007e-01 -4.46359992e-01
-1.07974017e+00 9.83418226e-01 3.95541489e-01 1.11790493e-01
-8.31718504e-01 9.43360806e-01 5.41309416e-01 -4.26772952e-01
4.09630179e-01 -5.85496351e-02 -2.09780008e-01 -8.01441446e-02
1.17657030e+00 -2.05620471e-02 1.51899368e-01 -5.87768972e-01
-3.91280204e-01 -1.80625811e-01 -5.72724640e-01 3.91848892e-01
1.05672181e+00 7.79197097e-01 5.10794781e-02 2.99487144e-01
1.67388916e+00 -1.79103389e-01 -1.22818923e+00 -3.02583367e-01
1.38319274e-02 -6.57755196e-01 1.60117298e-01 -7.55780816e-01
-1.31693745e+00 7.04178214e-01 8.88402402e-01 1.76542073e-01
7.82662392e-01 -4.43337746e-02 5.78748763e-01 7.84617186e-01
2.43390277e-01 -5.71296871e-01 4.12951916e-01 3.40089142e-01
5.38087845e-01 -1.00506079e+00 -2.29973704e-01 -1.65680677e-01
-2.90080875e-01 1.03763199e+00 5.25498629e-01 -6.02985978e-01
6.96383357e-01 1.11027867e-01 5.61443530e-02 -3.39505166e-01
-6.31646752e-01 4.27442670e-01 -6.92010969e-02 1.08036280e+00
-4.93421286e-01 5.29481173e-02 6.22729301e-01 6.82835996e-01
-3.12453091e-01 -5.79439342e-01 4.38795388e-01 9.60575938e-01
-5.53925812e-01 -9.76945102e-01 -7.44850874e-01 6.32889688e-01
-5.11720538e-01 -1.48023859e-01 -6.90695524e-01 7.57976711e-01
3.88500184e-01 9.74112868e-01 1.93780839e-01 -1.01988423e+00
1.60729751e-01 2.56243438e-01 2.94541746e-01 -9.34083581e-01
-8.63638997e-01 -5.45960307e-01 -3.35910618e-01 -4.18903977e-01
1.99227422e-01 -2.97602206e-01 -1.18618107e+00 -1.57088086e-01
-2.06659928e-01 1.03661470e-01 5.96733153e-01 9.44717586e-01
-1.01368129e-01 3.20648193e-01 1.23533750e+00 -3.23426008e-01
-8.63829792e-01 -5.42013586e-01 -7.30252206e-01 6.00884855e-01
9.19817209e-01 -6.36601388e-01 -8.29535663e-01 -1.73911508e-02] | [5.745940208435059, 7.769559383392334] |
dc147c12-1451-485e-9a7f-9509e8df4af9 | streaming-hypergraph-partitioning-algorithms | 2103.05394 | null | https://arxiv.org/abs/2103.05394v1 | https://arxiv.org/pdf/2103.05394v1.pdf | Streaming Hypergraph Partitioning Algorithms on Limited Memory Environments | Many well-known, real-world problems involve dynamic data which describe the relationship among the entities. Hypergraphs are powerful combinatorial structures that are frequently used to model such data. For many of today's data-centric applications, this data is streaming; new items arrive continuously, and the data grows with time. With paradigms such as Internet of Things and Edge Computing, such applications become more natural and more practical. In this work, we assume a streaming model where the data is modeled as a hypergraph, which is generated at the edge. This data then partitioned and sent to remote nodes via an algorithm running on a memory-restricted device such as a single board computer. Such a partitioning is usually performed by taking a connectivity metric into account to minimize the communication cost of later analyses that will be performed in a distributed fashion. Although there are many offline tools that can partition static hypergraphs excellently, algorithms for the streaming settings are rare. We analyze a well-known algorithm from the literature and significantly improve its running time by altering its inner data structure. For instance, on a medium-scale hypergraph, the new algorithm reduces the runtime from 17800 seconds to 10 seconds. We then propose sketch- and hash-based algorithms, as well as ones that can leverage extra memory to store a small portion of the data to enable the refinement of partitioning when possible. We experimentally analyze the performance of these algorithms and report their run times, connectivity metric scores, and memory uses on a high-end server and four different single-board computer architectures. | ['Bora Uçar', 'Kamer Kaya', 'Berkay Demireller', 'Fatih Taşyaran'] | 2021-03-09 | null | null | null | null | ['hypergraph-partitioning'] | ['graphs'] | [ 2.40369756e-02 -2.75401399e-02 -2.76818544e-01 1.05029523e-01
-4.59956110e-01 -8.94922316e-01 1.07373968e-01 8.17643166e-01
-3.11965168e-01 4.16801840e-01 -3.60143743e-02 -4.06722337e-01
-3.45869839e-01 -1.42183065e+00 -6.00665629e-01 -3.90602767e-01
-6.84233487e-01 1.05528593e+00 7.34830976e-01 -1.49948180e-01
1.61841661e-01 4.36062753e-01 -1.43887579e+00 3.50417159e-02
4.16112363e-01 9.64555621e-01 3.70146818e-02 8.25312972e-01
-2.79583842e-01 1.51751637e-01 -3.67860675e-01 -5.30139685e-01
6.36904836e-01 -3.48059982e-02 -8.78217638e-01 2.94115782e-01
-3.86490561e-02 -1.79762259e-01 -4.54404533e-01 8.67540002e-01
3.79614502e-01 -7.48082669e-03 1.15897879e-01 -1.37246799e+00
1.01608925e-01 9.65953827e-01 -8.93410504e-01 1.91523522e-01
5.41541517e-01 -5.85163198e-02 1.14079583e+00 -5.12487829e-01
7.99493670e-01 7.60927618e-01 5.07071733e-01 -1.43339664e-01
-1.40170836e+00 -4.81835872e-01 4.25542239e-03 3.28411281e-01
-1.65202391e+00 -2.20198512e-01 5.51725507e-01 -3.32008004e-02
5.12438595e-01 5.98745108e-01 8.07134151e-01 1.74642727e-01
-1.09437674e-01 5.32925129e-01 5.40385127e-01 -2.86018699e-01
5.01915097e-01 -1.31736919e-01 2.07169637e-01 4.79817659e-01
8.59232008e-01 -4.26561505e-01 -4.96915877e-01 -4.93138045e-01
5.35096467e-01 1.36641309e-01 -2.45207757e-01 -6.37060881e-01
-1.03221250e+00 6.80944800e-01 2.94638246e-01 2.01544583e-01
-3.53883207e-01 1.65444627e-01 5.16563952e-01 4.43746120e-01
2.12939456e-01 1.44906461e-01 -2.23284066e-01 -1.53068915e-01
-1.06757486e+00 5.61084859e-02 1.45146513e+00 1.17416930e+00
8.68046999e-01 -7.33051777e-01 3.03265691e-01 4.12020624e-01
-7.93643072e-02 2.09615141e-01 -1.59300223e-01 -6.93198740e-01
6.87553823e-01 8.50748420e-01 -1.87794238e-01 -1.38932586e+00
-5.69430113e-01 -1.64948359e-01 -9.53191400e-01 -2.81807512e-01
4.09890205e-01 7.40793645e-02 -4.73998010e-01 1.24050617e+00
7.66214013e-01 3.41950625e-01 -3.05202574e-01 7.55784452e-01
3.28015178e-01 8.32410157e-01 -4.70033973e-01 -3.19055021e-01
1.52511573e+00 -7.94344783e-01 -2.92284191e-01 1.09818228e-01
8.66837740e-01 -5.79208791e-01 7.54362345e-01 5.80234230e-01
-1.38333714e+00 -1.04655521e-02 -9.90838647e-01 -4.77994345e-02
-3.16288471e-01 -5.37972748e-01 5.97002387e-01 8.26239049e-01
-1.16245472e+00 4.49609607e-01 -9.38348651e-01 -3.58168811e-01
1.36728704e-01 5.63261032e-01 -3.85331333e-01 -2.38204807e-01
-8.75423312e-01 1.79549903e-01 3.85798812e-01 -1.69753000e-01
-4.22397405e-01 -7.91457057e-01 -4.46165711e-01 6.95871890e-01
9.37425256e-01 -7.26682007e-01 9.24130261e-01 -4.73914027e-01
-1.02871180e+00 5.86111367e-01 1.51024505e-01 -4.03088301e-01
1.55755758e-01 3.56872171e-01 -1.86068505e-01 4.88317251e-01
-3.92875701e-01 2.27219928e-02 3.91270012e-01 -9.90669072e-01
-6.64732635e-01 -4.51139390e-01 4.75419253e-01 7.42376670e-02
-7.06018984e-01 -2.46654361e-01 -1.00229418e+00 -1.91673234e-01
1.63878262e-01 -1.13878191e+00 -4.91120368e-01 1.27359005e-02
-4.12143379e-01 -1.92602023e-01 5.40278912e-01 -1.93302616e-01
1.66176248e+00 -2.17278266e+00 1.16049863e-01 8.41262221e-01
5.96652091e-01 2.05164418e-01 3.25982869e-02 1.09176719e+00
3.75015318e-01 3.32700193e-01 -2.35197708e-01 -1.28542945e-01
-5.58528602e-02 4.82442677e-02 -8.24506879e-02 5.27306080e-01
-4.78120953e-01 5.09324133e-01 -6.91118419e-01 -3.89572978e-01
-1.37402043e-01 1.22161448e-01 -9.47249949e-01 -1.88759901e-02
-3.18038464e-01 -2.81667411e-01 -4.21774000e-01 3.48248899e-01
8.02259088e-01 -7.45631218e-01 7.10734367e-01 -6.32319972e-02
-1.82876196e-02 1.26348481e-01 -1.76036370e+00 1.58819830e+00
-4.50062394e-01 3.17088604e-01 4.89229530e-01 -9.59774435e-01
5.87777674e-01 1.52202740e-01 6.32137299e-01 -2.81250983e-01
-7.09090829e-02 2.11700678e-01 -2.48736501e-01 -3.27668518e-01
7.19168544e-01 3.11735690e-01 -1.92030564e-01 8.42665255e-01
-6.60753012e-01 5.09427972e-02 6.09956801e-01 7.45112300e-01
1.84862113e+00 -8.22184443e-01 2.05273628e-01 -2.31042519e-01
2.36384094e-01 2.27047384e-01 3.45231920e-01 5.34149826e-01
3.75200808e-01 3.96498621e-01 7.55012453e-01 -5.19939721e-01
-1.10077512e+00 -8.43500257e-01 7.90225565e-02 7.95919299e-01
5.69830477e-01 -1.04341722e+00 -6.04862869e-01 -3.00541520e-01
1.52927637e-01 1.88730299e-01 -2.18643427e-01 7.87106305e-02
-3.68664593e-01 -5.04095316e-01 1.05310492e-01 3.40816200e-01
7.21351281e-02 -5.58319867e-01 -7.15917945e-01 3.95513088e-01
7.00513348e-02 -1.04301679e+00 -5.98997831e-01 -1.45140603e-01
-9.13754702e-01 -1.09537911e+00 -1.53141499e-01 -5.53319097e-01
6.90158963e-01 6.53083324e-01 1.11635065e+00 5.45913875e-01
-4.20890421e-01 4.14154351e-01 -3.81726474e-01 1.98973883e-02
9.78924036e-02 4.15005028e-01 -1.79253459e-01 -9.43782215e-04
1.23776816e-01 -8.89635205e-01 -7.08491325e-01 2.87860662e-01
-1.48330629e+00 -4.43154052e-02 4.98302013e-01 4.82820958e-01
6.57134414e-01 5.08803427e-01 2.97227919e-01 -1.21924078e+00
3.48984003e-01 -1.01651847e+00 -9.58661616e-01 1.20091192e-01
-5.83648741e-01 -5.83599927e-03 8.28963637e-01 -4.26743448e-01
-3.99042517e-01 8.84103626e-02 2.40107119e-01 -2.13176385e-01
3.37636411e-01 8.67210805e-01 -1.85949713e-01 3.90468910e-02
1.94685563e-01 -4.10833955e-02 -1.93434209e-01 -2.92904079e-01
4.00736630e-01 6.51203394e-01 3.18937629e-01 -6.28864586e-01
9.07452881e-01 7.35554516e-01 3.74572754e-01 -8.00791025e-01
-3.36384296e-01 -8.15687299e-01 -2.34650388e-01 -6.60075843e-02
2.54943579e-01 -6.82199121e-01 -1.16767681e+00 2.21262481e-02
-8.04064453e-01 -3.16734791e-01 -1.74475297e-01 1.46478042e-01
-3.06231081e-01 4.54903334e-01 -5.12888193e-01 -5.54910004e-01
-3.26032490e-01 -8.25021029e-01 9.98925805e-01 1.41054699e-02
-9.14376974e-02 -8.58766794e-01 2.53496200e-01 3.89308445e-02
4.33012456e-01 9.28864479e-02 9.00084078e-01 -7.79833794e-01
-1.12501287e+00 -3.15874726e-01 -2.77444780e-01 -4.95024949e-01
-2.65793622e-01 -1.03656612e-01 -2.59873956e-01 -5.28157830e-01
-2.81809390e-01 5.55091761e-02 5.05815387e-01 -9.10275429e-02
1.45421934e+00 -4.28630143e-01 -7.13443279e-01 6.95971787e-01
1.62404168e+00 -6.07865639e-02 6.34698212e-01 6.82970807e-02
5.49688756e-01 5.04193485e-01 3.79844964e-01 8.23478699e-01
7.48739958e-01 6.76288784e-01 4.85174030e-01 -1.48064308e-02
2.34307662e-01 -1.76387951e-01 1.06089711e-01 1.09688187e+00
2.49039918e-01 -6.39759481e-01 -9.52872813e-01 6.93487823e-01
-1.79523957e+00 -8.26048613e-01 -2.95186460e-01 2.52276969e+00
7.11551249e-01 2.26840973e-01 4.52746749e-01 5.13867140e-01
7.91243553e-01 -2.29932349e-02 -4.01569575e-01 -3.14119399e-01
2.83449650e-01 2.56631076e-01 8.63035560e-01 2.08999485e-01
-5.73219717e-01 4.18902516e-01 5.65610123e+00 7.34815061e-01
-9.09159124e-01 -1.84579685e-01 5.35044253e-01 -3.70155334e-01
-6.04587376e-01 2.88387179e-01 -6.44312143e-01 5.55731893e-01
1.29509854e+00 -8.40474069e-01 6.79170489e-01 8.25174093e-01
-4.95559201e-02 -3.93537521e-01 -1.26220465e+00 1.15339577e+00
-1.56399444e-01 -1.55050361e+00 -2.75097966e-01 5.73491335e-01
7.03938484e-01 -7.48698637e-02 -2.45836094e-01 -8.92533883e-02
2.74672866e-01 -6.32903695e-01 3.23150039e-01 2.93681473e-01
7.98764169e-01 -8.58460665e-01 5.24738729e-01 4.75625455e-01
-1.61995852e+00 -5.86363971e-02 -3.19754124e-01 -6.22848049e-02
4.23542112e-01 1.11228538e+00 -6.20933950e-01 6.14939749e-01
6.73278034e-01 1.59263372e-01 -3.69598240e-01 1.39876199e+00
5.54251671e-01 6.48132801e-01 -1.10597587e+00 -1.61297336e-01
-9.73628089e-02 -2.84677625e-01 5.50918996e-01 9.02987242e-01
4.90943372e-01 5.26996732e-01 3.98776114e-01 3.66787642e-01
-5.21505952e-01 2.90132821e-01 -7.05898702e-01 -3.75784039e-02
8.88244808e-01 1.49324071e+00 -1.21451473e+00 -4.65273917e-01
-6.34129226e-01 6.26026154e-01 2.91645437e-01 1.30439429e-02
-8.16610932e-01 -5.58780789e-01 5.73467970e-01 7.95549750e-01
5.10455966e-01 -4.36474144e-01 -2.61483371e-01 -1.02517092e+00
3.45132589e-01 -6.76927149e-01 7.37192571e-01 -2.79131621e-01
-1.22179222e+00 4.01521027e-01 -6.28127083e-02 -9.47937310e-01
6.20050617e-02 -1.30119696e-01 -4.50649947e-01 2.91652441e-01
-1.01432371e+00 -4.27217036e-01 -2.77115285e-01 5.86448550e-01
1.27254725e-01 4.56580818e-01 5.68845034e-01 6.07552171e-01
-3.94246310e-01 5.23887515e-01 1.90481260e-01 -2.55875140e-01
3.56784374e-01 -9.74325716e-01 5.01174927e-01 7.44342387e-01
2.21219406e-01 4.56661910e-01 5.13468742e-01 -5.57761073e-01
-2.24015450e+00 -7.02579618e-01 7.20770299e-01 5.30613512e-02
8.50469351e-01 -6.22771084e-01 -8.95600736e-01 4.99342203e-01
-1.18060336e-01 4.11206365e-01 4.96332914e-01 2.18563050e-01
-2.10990459e-01 -4.63686824e-01 -9.77126598e-01 5.19163966e-01
1.26164711e+00 -3.67134005e-01 1.60626061e-02 3.50696653e-01
5.79342663e-01 -3.54986191e-01 -1.10273874e+00 1.47829074e-02
4.06335056e-01 -8.47304344e-01 7.08681524e-01 -2.72882402e-01
1.22744195e-01 -4.19600219e-01 7.90903643e-02 -1.02418959e+00
-1.91595599e-01 -1.16410744e+00 -3.83703172e-01 1.03219879e+00
4.19793308e-01 -6.18595898e-01 1.10686946e+00 7.50846386e-01
2.46336713e-01 -7.87765980e-01 -8.68541598e-01 -8.03725898e-01
-5.26291609e-01 -3.26939315e-01 8.28222632e-01 7.02607930e-01
5.83616495e-01 3.79784077e-01 1.45574018e-01 3.60671997e-01
6.09502077e-01 5.27148247e-01 1.04867494e+00 -1.39466035e+00
-4.31381136e-01 -2.78650790e-01 -6.29694104e-01 -1.22854328e+00
-3.56173545e-01 -1.02740121e+00 -3.86494130e-01 -1.40258610e+00
3.26369226e-01 -8.51051807e-01 2.08591163e-01 2.25356445e-01
1.38857394e-01 9.87003148e-02 2.64633119e-01 1.13255426e-01
-9.09226835e-01 7.22097829e-02 7.87060261e-01 1.11219086e-01
-3.20965111e-01 8.63346905e-02 -4.41190094e-01 3.65964979e-01
5.87189376e-01 -5.02242386e-01 -5.10592520e-01 -4.00446773e-01
8.69916081e-01 5.53024411e-01 -5.67642087e-03 -9.46614206e-01
8.55544448e-01 4.71450128e-02 -2.92703569e-01 -6.67019010e-01
2.08582729e-01 -1.31063652e+00 7.17729986e-01 3.62667918e-01
-7.76078627e-02 4.31300521e-01 -5.27116694e-02 7.46783793e-01
-1.16191030e-01 -5.32602407e-02 4.45187509e-01 1.87775463e-01
-1.59900829e-01 7.87770987e-01 -4.98690046e-02 2.17828825e-01
1.56415081e+00 -1.77616835e-01 -4.33548272e-01 -6.33787036e-01
-6.49678826e-01 4.69586581e-01 8.70224178e-01 -1.18463365e-02
4.01912659e-01 -1.09584022e+00 -5.90595901e-01 1.19266286e-01
-2.11267211e-02 2.76818871e-01 2.46339872e-01 9.15955007e-01
-6.84517264e-01 1.75983965e-01 1.61012188e-01 -4.51055974e-01
-1.29453409e+00 1.03406930e+00 -3.19103032e-01 -5.65301061e-01
-7.84095287e-01 4.34272557e-01 1.24983229e-01 2.78113008e-01
1.32146835e-01 -1.18048154e-01 3.55167508e-01 1.77379549e-01
6.46527827e-01 8.21548581e-01 2.41938293e-01 -5.09616137e-02
-2.92607099e-01 2.22837448e-01 5.73508367e-02 -5.99958897e-02
1.60206234e+00 -4.14938897e-01 -4.39745635e-01 2.27367237e-01
1.10677278e+00 3.08149397e-01 -7.76732445e-01 -3.41646522e-01
1.34109795e-01 -4.68290478e-01 -1.41053841e-01 -5.20118624e-02
-1.40032685e+00 4.95746821e-01 -6.41010702e-02 1.12114203e+00
1.45560122e+00 1.55639008e-01 1.29460907e+00 2.38770783e-01
8.30971181e-01 -9.07667220e-01 -2.42160499e-01 2.95521319e-01
2.59540856e-01 -5.81012845e-01 1.96739808e-01 -9.18758810e-01
-1.60380289e-01 1.08312190e+00 2.33841822e-01 -1.46840796e-01
8.73597085e-01 6.97631896e-01 -6.74790919e-01 -3.13625544e-01
-1.15831208e+00 -1.12864919e-01 -2.33085409e-01 1.30329922e-01
-2.10445985e-01 1.92938700e-01 -5.34381509e-01 6.62182093e-01
-1.63575813e-01 -6.35528043e-02 8.37842822e-01 8.48009229e-01
-4.20077682e-01 -1.30679440e+00 -3.57737213e-01 7.01342106e-01
-4.05086994e-01 -1.77083001e-01 -1.21063463e-01 4.87083733e-01
-3.58621269e-01 7.72678494e-01 3.89696896e-01 -2.93352932e-01
2.21353576e-01 -3.09012771e-01 1.93746641e-01 -6.81713283e-01
-6.42712533e-01 -2.04830840e-01 1.56527981e-01 -7.83041477e-01
6.74892068e-02 -4.50327247e-01 -1.35485160e+00 -9.44776595e-01
-3.29559028e-01 2.56684482e-01 7.58037806e-01 4.72029716e-01
7.57912934e-01 1.19006328e-01 9.80492592e-01 -6.54750586e-01
-3.83901805e-01 -3.64756823e-01 -7.74077415e-01 2.10986704e-01
-5.38649745e-02 -2.94348180e-01 -3.45696241e-01 -4.35328372e-02] | [6.945619106292725, 5.179756164550781] |
70fa2362-c6c3-460d-92d1-46baeea92c40 | egru-event-based-gru-for-activity-sparse | 2206.06178 | null | https://arxiv.org/abs/2206.06178v3 | https://arxiv.org/pdf/2206.06178v3.pdf | Efficient recurrent architectures through activity sparsity and sparse back-propagation through time | Recurrent neural networks (RNNs) are well suited for solving sequence tasks in resource-constrained systems due to their expressivity and low computational requirements. However, there is still a need to bridge the gap between what RNNs are capable of in terms of efficiency and performance and real-world application requirements. The memory and computational requirements arising from propagating the activations of all the neurons at every time step to every connected neuron, together with the sequential dependence of activations, contribute to the inefficiency of training and using RNNs. We propose a solution inspired by biological neuron dynamics that makes the communication between RNN units sparse and discrete. This makes the backward pass with backpropagation through time (BPTT) computationally sparse and efficient as well. We base our model on the gated recurrent unit (GRU), extending it with units that emit discrete events for communication triggered by a threshold so that no information is communicated to other units in the absence of events. We show theoretically that the communication between units, and hence the computation required for both the forward and backward passes, scales with the number of events in the network. Our model achieves efficiency without compromising task performance, demonstrating competitive performance compared to state-of-the-art recurrent network models in real-world tasks, including language modeling. The dynamic activity sparsity mechanism also makes our model well suited for novel energy-efficient neuromorphic hardware. Code is available at https://github.com/KhaleelKhan/EvNN/. | ['David Kappel', 'Christian Mayr', 'Mark Schöne', 'Khaleelulla Khan Nazeer', 'Anand Subramoney'] | 2022-06-13 | null | null | null | null | ['gesture-recognition', 'sequential-image-classification'] | ['computer-vision', 'computer-vision'] | [ 5.52550852e-01 -1.75727159e-01 3.20909508e-02 1.31789416e-01
1.68694615e-01 -3.49279583e-01 5.83116889e-01 -5.15367873e-02
-7.76719928e-01 8.25850666e-01 -7.38776987e-03 -2.68950224e-01
7.64840171e-02 -1.02308309e+00 -8.22161555e-01 -9.64294851e-01
-2.04874620e-01 8.55871364e-02 4.84635204e-01 -1.23988777e-01
9.00152102e-02 7.73950934e-01 -1.65998209e+00 2.87058026e-01
2.14161575e-01 9.38257158e-01 7.24732041e-01 6.13226354e-01
-6.29014745e-02 1.12562478e+00 -3.98069024e-01 2.78662175e-01
-4.89328951e-02 -6.10759556e-01 -4.80236828e-01 -4.37891543e-01
-3.23057204e-01 -5.27909910e-03 -8.78678560e-01 6.31653845e-01
6.48990273e-01 4.78046834e-01 3.11288863e-01 -8.86926472e-01
-4.25708085e-01 7.13873029e-01 -2.05592752e-01 5.25921404e-01
-2.56996214e-01 3.70106217e-03 8.29541028e-01 -7.88426757e-01
6.51319087e-01 5.87199867e-01 5.91884971e-01 1.05515730e+00
-1.34372127e+00 -7.91769803e-01 2.44631290e-01 1.57520369e-01
-1.24750423e+00 -8.48558187e-01 4.13007349e-01 3.97765525e-02
1.86235452e+00 1.48589432e-01 9.77919698e-01 1.15697205e+00
4.16370690e-01 5.92088938e-01 6.94518983e-01 -3.61518264e-01
6.33065939e-01 -4.72972423e-01 5.84816374e-02 5.85905612e-01
1.15095660e-01 6.07772507e-02 -8.90334249e-01 1.03200786e-01
9.96456683e-01 4.64568287e-01 -3.28460336e-01 2.28028208e-01
-9.71713364e-01 4.52618659e-01 5.34252107e-01 6.43586874e-01
-4.84549969e-01 9.75867391e-01 3.50437492e-01 2.80888915e-01
7.49956965e-02 1.16678238e-01 -1.50931716e-01 -2.35101655e-01
-1.21166730e+00 -1.07618116e-01 7.54090250e-01 6.72726274e-01
5.42857766e-01 4.71540123e-01 6.89589977e-02 8.91981483e-01
9.31363553e-02 2.18942508e-01 8.69305849e-01 -8.10770452e-01
1.78562514e-02 4.24039483e-01 -4.31088656e-01 -6.25951529e-01
-5.50092399e-01 -5.32451391e-01 -1.16849339e+00 5.36777861e-02
1.11556381e-01 -1.54566970e-02 -1.03581476e+00 2.08522248e+00
-2.51200169e-01 2.94413805e-01 3.37704346e-02 6.35697544e-01
5.12066543e-01 1.05756187e+00 -5.30666746e-02 -5.19774199e-01
1.10012662e+00 -7.82058895e-01 -6.14026725e-01 -4.88359362e-01
6.61961734e-01 -3.11700284e-01 6.26918256e-01 2.00993747e-01
-1.50223982e+00 -2.69311368e-01 -1.02857912e+00 -1.69696197e-01
-3.86295468e-01 -6.49872050e-02 7.01078176e-01 4.15128648e-01
-1.40942347e+00 7.13302195e-01 -1.31680667e+00 -2.54015744e-01
4.02277172e-01 9.73389089e-01 6.55111074e-02 1.76129565e-01
-1.07877147e+00 7.29698479e-01 2.44705677e-01 2.87075043e-01
-8.88229966e-01 -4.72460121e-01 -4.38747108e-01 3.70631576e-01
-1.00211196e-01 -6.89256608e-01 1.23571658e+00 -9.04232085e-01
-1.44513571e+00 5.69355607e-01 -5.08449852e-01 -9.31098044e-01
-6.67799311e-03 3.21633756e-01 -2.22046554e-01 -1.89256612e-02
-5.46115100e-01 8.31372797e-01 4.86669004e-01 -6.57503903e-01
-3.55247110e-01 -2.45618343e-01 -2.69750506e-01 2.19365254e-01
-5.57017803e-01 -6.77389279e-02 -4.80552167e-01 -6.71022952e-01
1.21554695e-01 -1.10876036e+00 -2.78803855e-01 -1.86722264e-01
5.82163446e-02 -2.01601282e-01 8.25066745e-01 -1.51269183e-01
1.30025792e+00 -2.19460440e+00 3.17795753e-01 1.40034094e-01
2.63616681e-01 1.51728094e-01 -3.98466736e-02 5.12664437e-01
-1.08993612e-02 -1.32186502e-01 -3.35026711e-01 -3.51693302e-01
-4.14673537e-01 5.51145017e-01 -5.76679289e-01 3.60624939e-01
7.05307573e-02 1.06217778e+00 -7.62275279e-01 6.77699372e-02
-1.56523839e-01 7.82603145e-01 -3.03830147e-01 -1.11455813e-01
-1.44562483e-01 1.54223487e-01 -1.68233871e-01 3.68111104e-01
1.24858841e-01 -4.38180089e-01 4.15738016e-01 7.82978535e-02
-4.10347581e-01 7.01781452e-01 -8.73541474e-01 1.60586321e+00
-6.59666359e-01 8.57786894e-01 -1.68179572e-02 -1.15744853e+00
7.25332737e-01 4.39086616e-01 4.14300412e-01 -1.15539932e+00
3.01051736e-01 4.44907010e-01 2.58646339e-01 2.57963449e-01
4.13423628e-01 -7.97369927e-02 1.69025615e-01 8.56142998e-01
3.55694532e-01 2.13801116e-01 4.54217374e-01 2.44228393e-01
1.52298582e+00 -2.23373801e-01 -9.52800587e-02 -1.80070743e-01
-4.79611866e-02 -3.91304255e-01 5.22847891e-01 7.86273599e-01
2.08547339e-01 2.93583333e-01 2.10157067e-01 -2.20366165e-01
-1.13203466e+00 -9.74509001e-01 1.02960475e-01 1.17915142e+00
3.17676156e-03 -3.18262547e-01 -6.35976195e-01 2.60340005e-01
-4.31088150e-01 4.51781929e-01 -4.32021290e-01 -3.94628525e-01
-8.92583489e-01 -8.67057383e-01 7.49883652e-01 5.15543401e-01
4.82432961e-01 -1.46180117e+00 -1.31332219e+00 5.59902370e-01
5.78941777e-02 -9.64319646e-01 -4.27834123e-01 1.08776188e+00
-1.33757341e+00 -4.21553791e-01 -7.43024826e-01 -8.65345478e-01
8.48684311e-01 2.37117290e-01 9.17337656e-01 2.29438394e-01
-5.42416692e-01 1.43604532e-01 5.25375865e-02 -1.57015681e-01
7.86453765e-03 1.90657958e-01 1.33166566e-01 -3.00966799e-01
3.77896950e-02 -1.17251933e+00 -7.70118356e-01 5.10810390e-02
-1.11128545e+00 3.90368342e-01 5.74431837e-01 7.96205223e-01
9.16714907e-01 6.55132383e-02 5.34361005e-01 -7.57967651e-01
4.90450025e-01 -5.63959539e-01 -4.72779334e-01 -5.98267764e-02
-4.45263684e-01 2.34817296e-01 8.18965852e-01 -6.99648023e-01
-7.52940416e-01 2.32512340e-01 -1.20079495e-01 -1.61866874e-01
3.85124207e-01 3.10680449e-01 4.62539226e-01 -1.88855350e-01
5.53109586e-01 6.41938388e-01 -2.87961513e-01 -1.03176743e-01
3.13733406e-02 1.30081564e-01 3.60538036e-01 -3.39889944e-01
1.69970989e-01 6.11977816e-01 2.12465584e-01 -9.35911953e-01
-1.85911030e-01 -1.44229695e-01 -1.40029967e-01 -3.22217822e-01
3.69263232e-01 -7.83430755e-01 -9.25109267e-01 5.77264965e-01
-1.23173547e+00 -7.18071878e-01 -5.86192250e-01 3.39448452e-01
-6.43756509e-01 -1.66560858e-01 -1.11191785e+00 -1.09844196e+00
-5.89572728e-01 -7.51402676e-01 4.48740751e-01 3.87226790e-01
-2.66005486e-01 -9.56660450e-01 -8.38268735e-03 -3.73428345e-01
7.02708721e-01 -2.62556940e-01 1.00253618e+00 -3.66299093e-01
-7.23159313e-01 1.39732748e-01 -4.43575382e-02 1.20819239e-02
-2.01004684e-01 -3.58120620e-01 -9.00041223e-01 -2.25462288e-01
2.26818770e-01 -3.37675035e-01 1.38229775e+00 5.77541590e-01
1.21341598e+00 -4.35549885e-01 -5.16806424e-01 4.79130447e-01
1.50884354e+00 2.62884110e-01 8.23226213e-01 -1.35153383e-01
4.52760518e-01 2.22398788e-01 -4.71476048e-01 3.42559725e-01
-3.97018343e-02 4.55574393e-01 3.90999794e-01 1.98484887e-03
-3.41183841e-01 -1.13186114e-01 6.66333318e-01 1.46561050e+00
-2.81127453e-01 -5.45807183e-01 -7.79956579e-01 6.57686472e-01
-2.07126474e+00 -1.16201198e+00 1.66930541e-01 2.23928618e+00
1.10639381e+00 2.71257848e-01 -1.49559051e-01 2.65678972e-01
4.90280151e-01 8.90337601e-02 -8.06306541e-01 -7.46196687e-01
-2.41867974e-01 7.09405184e-01 7.21771300e-01 1.60202235e-01
-2.86271602e-01 7.66386747e-01 6.30952740e+00 9.32881892e-01
-1.22758269e+00 3.40605497e-01 6.23323262e-01 -8.02056909e-01
-2.73147553e-01 -1.91002876e-01 -1.07193792e+00 5.10070264e-01
1.73947871e+00 -7.46287405e-02 1.05214095e+00 2.49702930e-01
2.32883707e-01 -2.46392548e-01 -1.12641215e+00 1.00439370e+00
-1.83088988e-01 -1.72736347e+00 -9.33137238e-02 1.30963713e-01
7.02324927e-01 5.78575015e-01 8.70906040e-02 3.49564217e-02
3.56059104e-01 -1.19307029e+00 7.11960375e-01 4.67911035e-01
5.86433828e-01 -7.34020591e-01 2.50461817e-01 5.39602041e-01
-1.31475449e+00 -2.41537571e-01 -3.91365647e-01 -3.98155481e-01
1.44355386e-01 8.67359817e-01 -4.95036632e-01 -4.45099846e-02
6.27988040e-01 5.40076792e-01 1.14967652e-01 7.95068383e-01
2.33933963e-02 6.17648542e-01 -7.39914834e-01 -3.92588615e-01
1.61815181e-01 -3.38480584e-02 2.02669621e-01 1.31986094e+00
5.78289688e-01 2.57501066e-01 -4.15095210e-01 1.06796157e+00
-5.60934842e-01 -3.96450222e-01 -6.46836042e-01 -3.21203500e-01
7.73224354e-01 1.06006718e+00 -1.13081396e+00 -7.61157200e-02
-1.41334340e-01 1.09368408e+00 5.00133753e-01 4.63654160e-01
-6.12983525e-01 -4.19843435e-01 3.14934909e-01 8.50480869e-02
3.08992714e-01 -7.30600893e-01 -4.17350262e-01 -7.76431739e-01
3.60532738e-02 -2.93036908e-01 7.66294524e-02 -5.29262364e-01
-7.39895403e-01 6.44185483e-01 -6.87499881e-01 -7.07518339e-01
-2.63975441e-01 -3.76605719e-01 -5.02991915e-01 7.42526233e-01
-1.43266928e+00 -5.73188484e-01 7.26481527e-02 6.13366187e-01
5.29929578e-01 2.00925037e-01 1.05131316e+00 4.56875503e-01
-6.14251554e-01 4.61923331e-01 1.51213765e-01 -1.82015777e-01
-8.01872909e-02 -6.49935901e-01 5.42930067e-01 7.78728545e-01
3.59292239e-01 8.56011271e-01 5.03556848e-01 -3.66843909e-01
-1.79664004e+00 -1.00189316e+00 1.04304707e+00 1.67548910e-01
6.36942923e-01 -7.54386723e-01 -8.52196574e-01 4.75994200e-01
9.99739617e-02 7.68034309e-02 6.52058899e-01 -1.61008149e-01
-2.60840893e-01 5.58745973e-02 -7.07999647e-01 9.24919248e-01
1.47438014e+00 -6.77739382e-01 -9.08152759e-02 2.83639163e-01
4.82860625e-01 -1.76184788e-01 -4.81852323e-01 8.12598541e-02
5.60634732e-01 -6.51314676e-01 7.69449472e-01 -1.26768634e-01
2.23849416e-01 -1.75166667e-01 -1.28302053e-01 -1.00150716e+00
-2.53416151e-01 -6.70506060e-01 -5.61856210e-01 7.57144690e-01
5.93298137e-01 -7.50990689e-01 7.76837885e-01 4.38232839e-01
-1.41859487e-01 -9.89566147e-01 -1.27296674e+00 -8.03846359e-01
-2.34274596e-01 -3.46996278e-01 -1.12339742e-01 4.40541267e-01
2.00276479e-01 3.77207041e-01 -2.52972245e-01 -1.94851488e-01
2.44041726e-01 -7.15740549e-04 -1.55748948e-01 -9.77130830e-01
-5.16156673e-01 -5.88543117e-01 -2.14133829e-01 -1.26881933e+00
2.93687340e-02 -1.06702459e+00 8.32993463e-02 -1.45836449e+00
2.46721700e-01 -5.60216784e-01 -5.31031489e-01 8.24565232e-01
6.58438087e-01 4.70861763e-01 1.72170505e-01 5.26224554e-01
-4.65691030e-01 4.51877147e-01 7.23945618e-01 1.31402418e-01
-3.92590970e-01 -2.11268768e-01 -2.61135697e-01 4.82911378e-01
8.85735452e-01 -7.02468097e-01 -4.97343451e-01 -6.31368637e-01
5.85780442e-01 -2.38432940e-02 2.49701545e-01 -1.28264165e+00
1.06261897e+00 1.42982870e-01 3.75993460e-01 -3.28287870e-01
7.54607439e-01 -6.78496063e-01 3.67360026e-01 9.27516460e-01
-5.12488127e-01 1.78950340e-01 3.03233653e-01 5.17891109e-01
9.18327495e-02 -2.75371850e-01 7.48670697e-01 -1.93587869e-01
-5.01557648e-01 3.17286372e-01 -9.98748362e-01 -1.41800508e-01
7.39672065e-01 -4.54824209e-01 -4.47036296e-01 -1.79244459e-01
-7.30990112e-01 -1.30971581e-01 2.32137963e-01 9.21892375e-02
7.62991726e-01 -1.07339239e+00 -2.01342568e-01 2.47418448e-01
-5.42139411e-01 -2.32678577e-01 2.97993630e-01 7.65346169e-01
-1.55858457e-01 6.01532519e-01 -4.35013026e-01 -2.62698710e-01
-1.01680219e+00 1.34438664e-01 4.18901533e-01 -3.13230395e-01
-6.27458513e-01 1.07406938e+00 7.78763294e-02 4.87258360e-02
3.71735662e-01 -1.85089007e-01 1.50251672e-01 -1.26090392e-01
4.78247434e-01 3.06939989e-01 2.83753216e-01 -9.45063755e-02
-3.42280298e-01 2.58819103e-01 -1.87415212e-01 -2.62887269e-01
1.53387856e+00 1.85119346e-01 -3.74767214e-01 7.93304980e-01
1.01799798e+00 -3.95522624e-01 -1.08380437e+00 -1.97178453e-01
-1.45782396e-01 2.97309637e-01 3.76993954e-01 -5.55748940e-01
-1.27452242e+00 9.85387564e-01 5.43334305e-01 2.01899946e-01
1.32150638e+00 -1.62329212e-01 1.17299688e+00 6.07421339e-01
4.89151925e-01 -1.30926406e+00 4.53298055e-02 9.65017617e-01
4.27810580e-01 -3.00314784e-01 -3.38183224e-01 -2.95115653e-02
-6.96039721e-02 1.14891374e+00 3.02475899e-01 -3.29735607e-01
5.74241102e-01 8.82561624e-01 -7.09863424e-01 -8.19025785e-02
-1.38574803e+00 -3.28694247e-02 -3.65039259e-01 2.40227312e-01
5.42343497e-01 3.13464627e-02 -3.86524707e-01 5.01213133e-01
2.54176389e-02 3.32751632e-01 4.98271376e-01 1.15339494e+00
-6.55096114e-01 -1.14766753e+00 2.36604303e-01 6.33715212e-01
-4.24310803e-01 -4.93458718e-01 -1.13903262e-01 1.87040538e-01
-1.50925547e-01 7.12503195e-01 4.28825796e-01 -3.20648700e-01
-5.03958128e-02 1.12135755e-02 7.82762766e-01 -6.96631491e-01
-8.59029949e-01 -4.38701883e-02 -1.87497661e-02 -4.57946986e-01
-2.51747549e-01 -3.15781802e-01 -1.97622097e+00 -5.69624603e-01
-1.74516305e-01 -5.68370447e-02 8.43219697e-01 7.76499927e-01
7.24427342e-01 9.87137437e-01 3.76318604e-01 -9.81944978e-01
-2.16474056e-01 -4.27590221e-01 -4.85339761e-01 -2.79201657e-01
2.33143926e-01 -2.93635935e-01 -2.65019566e-01 2.97811124e-02] | [8.184164047241211, 2.6009700298309326] |
da08708c-d03e-44f4-add9-7c661b952f53 | intent-segmentation-of-user-queries-via | null | null | https://aclanthology.org/2020.iwdp-1.7 | https://aclanthology.org/2020.iwdp-1.7.pdf | Intent Segmentation of User Queries Via Discourse Parsing | In this paper, we explore a new approach based on discourse analysis for the task of intent segmentation. Our target texts are user queries from a real-world chatbot. Our results show the feasibility of our approach with an F1-score of 82.97 points, and some advantages and disadvantages compared to two machine learning baselines: BERT and LSTM+CRF. | ['Changjian Hu', 'Xiaohua Wang', 'Ruosen Li', 'Ziyue Wen', 'Yibing Yang', 'Vicente Ivan Sanchez Carmona'] | null | null | null | null | aacl-iwdp-2020-12 | ['discourse-parsing'] | ['natural-language-processing'] | [ 4.02937308e-02 6.73891246e-01 -1.72425255e-01 -4.69950616e-01
-1.03253567e+00 -3.97549301e-01 7.66472042e-01 -2.80411452e-01
-6.67698503e-01 8.70639980e-01 5.12780190e-01 -4.16968495e-01
4.88626629e-01 -2.99423456e-01 2.59328224e-02 -2.50695795e-01
7.68712536e-02 5.83259404e-01 3.61604691e-01 -5.05907178e-01
7.30099320e-01 -5.06963804e-02 -6.60454273e-01 7.59644449e-01
6.72601819e-01 7.61534035e-01 2.91040987e-01 8.63478184e-01
-3.74391168e-01 1.70427859e+00 -1.28322983e+00 -5.38013935e-01
-3.61615211e-01 -2.58386821e-01 -1.66582203e+00 -1.62618861e-01
-4.07514200e-02 -4.23593670e-01 -3.82896245e-01 6.05392277e-01
2.76032746e-01 4.53512102e-01 3.95075232e-01 -9.24722493e-01
-4.99144852e-01 7.65074670e-01 -1.67335317e-01 4.07818824e-01
7.88066864e-01 -1.17897928e-01 1.19616663e+00 -5.45344770e-01
8.39419186e-01 1.30842412e+00 7.67493844e-01 7.04024017e-01
-8.52282703e-01 -1.68799400e-01 3.33775990e-02 2.03060701e-01
-8.63469779e-01 -4.75893825e-01 8.16528201e-01 -5.41169167e-01
1.62795103e+00 2.76147455e-01 5.84533848e-02 1.33292043e+00
2.03770116e-01 1.22876883e+00 1.10449696e+00 -6.45972013e-01
-6.73959106e-02 3.97541285e-01 5.59423089e-01 6.88886464e-01
-8.17642033e-01 -4.50783074e-01 -5.00822186e-01 -3.44754457e-01
5.60703397e-01 -4.72156584e-01 -4.00369279e-02 6.90914929e-01
-7.80546784e-01 1.35340500e+00 3.84631008e-01 8.17287624e-01
-3.06136698e-01 5.35458401e-02 5.52500248e-01 3.88850540e-01
9.70886230e-01 6.51911259e-01 -3.18410695e-01 -8.36207151e-01
-5.08839130e-01 1.78106487e-01 1.36852884e+00 9.60364103e-01
2.75386542e-01 -1.80874139e-01 -6.62601888e-01 9.13552225e-01
4.36504960e-01 3.59066091e-02 5.04045665e-01 -1.09964871e+00
7.97227681e-01 5.28794706e-01 1.99003577e-01 -7.74585426e-01
-5.09121060e-01 2.12911889e-01 -2.46395841e-01 -3.77415448e-01
2.99845308e-01 -5.10184169e-01 -5.00852168e-01 1.36468172e+00
-1.14878632e-01 -1.45737618e-01 2.03037485e-02 4.88244802e-01
1.27618229e+00 9.06816006e-01 2.10346341e-01 -4.38178509e-01
1.28100586e+00 -1.55836284e+00 -1.17364883e+00 -2.29247645e-01
8.03406060e-01 -9.35258985e-01 1.13553393e+00 1.53123483e-01
-1.00121212e+00 -4.32886630e-01 -4.19382542e-01 -2.27675945e-01
-8.95300508e-02 2.33536646e-01 6.61378026e-01 7.08654881e-01
-1.02320671e+00 2.34841064e-01 -6.75621152e-01 -3.30517799e-01
-5.88155352e-02 4.52466369e-01 1.69951618e-01 5.15682817e-01
-1.25743961e+00 1.13056064e+00 3.62356037e-01 -6.24398887e-02
-3.73241216e-01 -1.64934680e-01 -7.48170972e-01 3.00791673e-02
3.60376120e-01 3.00083403e-02 2.20550990e+00 -6.08214200e-01
-2.13791084e+00 7.81295002e-01 -3.11676800e-01 -7.19774842e-01
2.93250114e-01 -4.59638387e-01 1.18845500e-01 9.36164856e-02
-3.41420770e-02 4.90073949e-01 3.03904325e-01 -8.21750641e-01
-6.69607878e-01 1.60573088e-02 6.00905478e-01 4.05493349e-01
-1.87477186e-01 7.23305106e-01 -2.54846483e-01 -3.45343292e-01
-3.96629483e-01 -9.41720545e-01 -2.34825253e-01 -1.02444255e+00
-3.46727937e-01 -8.63673568e-01 8.02996278e-01 -1.16478682e+00
1.48179686e+00 -1.80586505e+00 -2.16398746e-01 -3.87543023e-01
1.66889399e-01 3.99852991e-01 1.10017210e-01 6.56644404e-01
5.72171807e-01 3.10223401e-01 7.26962313e-02 -4.94969457e-01
-8.71985927e-02 5.14830612e-02 -2.75443256e-01 -5.01424596e-02
1.64701104e-01 1.11265779e+00 -8.52167308e-01 -7.98953295e-01
1.05248421e-01 2.89276510e-01 -3.23833644e-01 8.16759288e-01
-5.56054890e-01 4.04406697e-01 -7.28160560e-01 2.48825952e-01
-9.08014178e-02 -2.53732830e-01 3.28433394e-01 4.05809820e-01
-3.17691684e-01 1.17260897e+00 -1.17924228e-01 1.60203636e+00
-6.00083709e-01 1.13847315e+00 1.48382068e-01 -7.67590761e-01
8.30266654e-01 8.05824995e-01 5.93856461e-02 -4.46278423e-01
3.32037836e-01 2.27057305e-03 6.50802255e-03 -8.75579238e-01
7.41544724e-01 1.62618905e-02 -2.92859554e-01 7.15629280e-01
2.39846200e-01 7.24855959e-02 3.67546566e-02 2.04179361e-01
1.11936140e+00 -2.98496764e-02 3.88174653e-01 -3.75367776e-02
5.82354605e-01 7.93001428e-02 2.02985555e-01 9.20335948e-01
-4.82338250e-01 3.35761487e-01 7.35265255e-01 -2.76686013e-01
-4.48819220e-01 -3.93385708e-01 3.49754989e-01 1.61041701e+00
-3.01567018e-01 -3.14463437e-01 -1.00144184e+00 -1.20703030e+00
-7.40977466e-01 8.59486818e-01 -6.18351758e-01 4.56856519e-01
-1.23306096e+00 -5.51490784e-01 7.93022037e-01 4.11010653e-01
7.00561821e-01 -1.58945060e+00 -6.29805386e-01 3.35620522e-01
-8.79506350e-01 -1.45911014e+00 -3.71284276e-01 -9.71868262e-02
-6.19781256e-01 -7.43255198e-01 -3.62925649e-01 -9.50562835e-01
-2.54075769e-02 2.16940284e-01 1.24958086e+00 3.47701728e-01
2.14121595e-01 2.10903212e-01 -6.07323349e-01 -3.93482119e-01
-6.05523586e-01 5.84630787e-01 -5.52875698e-01 -4.46213156e-01
4.11938757e-01 -2.79113382e-01 -1.92777678e-01 7.54793286e-02
-3.25168163e-01 1.27857566e-01 4.77061212e-01 7.92776883e-01
-4.26487356e-01 -5.16989768e-01 7.61104107e-01 -1.20668113e+00
1.26038635e+00 -4.04190689e-01 -1.53761670e-01 3.72860104e-01
-2.35273555e-01 -3.00839722e-01 2.40604043e-01 -2.98859358e-01
-1.66124690e+00 -1.23957455e-01 -6.23537540e-01 1.52770147e-01
-3.86252791e-01 6.60175622e-01 1.34328306e-01 3.17081243e-01
4.81237054e-01 -1.79531068e-01 -7.16759562e-02 -5.99796653e-01
2.64756560e-01 1.41857886e+00 1.09136432e-01 -2.85588652e-01
-2.66704559e-02 -5.73134683e-02 -9.13676023e-01 -1.13857210e+00
-1.06574750e+00 -8.58065784e-01 -5.56833386e-01 -3.77096683e-01
1.03668213e+00 -5.38078308e-01 -1.01342332e+00 3.31435680e-01
-1.78541481e+00 -5.81327438e-01 1.42993763e-01 3.31849545e-01
-6.32725656e-01 3.41893494e-01 -1.44508564e+00 -1.23689449e+00
-6.60160720e-01 -9.44211662e-01 7.04964995e-01 2.81012774e-01
-6.70092762e-01 -1.29095340e+00 2.45245889e-01 9.98505235e-01
5.48637152e-01 -8.45898390e-02 6.08656406e-01 -1.49377286e+00
-2.15568587e-01 -4.55536358e-02 -1.42969355e-01 1.56242996e-01
-2.00793110e-02 -1.31766945e-01 -1.19160807e+00 7.99825564e-02
6.06662273e-01 -6.64384365e-01 5.36421001e-01 2.58393079e-01
5.54567516e-01 -7.83907354e-01 -2.77163506e-01 -5.37329316e-01
9.19818878e-01 7.59755909e-01 6.65717006e-01 3.31514508e-01
4.58006144e-01 9.54234481e-01 8.44071746e-01 1.33222595e-01
6.23441994e-01 7.60877550e-01 4.79395464e-02 9.80821252e-02
1.83239967e-01 -2.33650312e-01 3.38323325e-01 1.09738564e+00
1.27185648e-03 -4.51960325e-01 -1.10875463e+00 4.35950220e-01
-2.14544010e+00 -1.04207051e+00 -2.33679175e-01 1.42363322e+00
9.38891590e-01 2.78304845e-01 5.19822121e-01 -3.37065160e-01
7.75166690e-01 4.49476153e-01 1.66260898e-01 -8.50341618e-01
4.34576690e-01 1.87206224e-01 -4.22960743e-02 1.03061175e+00
-1.36706686e+00 1.27493000e+00 7.27224398e+00 7.44296849e-01
-8.19430590e-01 4.86083478e-01 7.81756103e-01 2.45550454e-01
1.19612873e-01 -1.26938954e-01 -6.23330176e-01 3.02735567e-01
1.42952061e+00 2.47596111e-02 2.05149770e-01 8.85156512e-01
7.72323012e-02 -1.35595292e-01 -7.23317623e-01 2.89642692e-01
4.59800929e-01 -1.40283895e+00 -5.55063248e-01 -7.56261721e-02
3.08918059e-01 1.48713231e-01 -2.89327383e-01 8.58764231e-01
4.73391980e-01 -1.06948912e+00 2.32225776e-01 1.49872258e-01
2.89949179e-01 -3.52097094e-01 1.17771482e+00 8.27490747e-01
-6.49980068e-01 1.74439758e-01 2.91675515e-02 -6.25471413e-01
5.64892948e-01 -8.38083327e-02 -1.67552245e+00 3.51659209e-01
4.31010485e-01 3.94381493e-01 -3.30351114e-01 5.23566067e-01
-3.88145357e-01 1.08875942e+00 -1.09352492e-01 -6.88616216e-01
5.35357952e-01 7.31247887e-02 3.43161345e-01 1.65585768e+00
-3.65000337e-01 3.78520012e-01 2.74346054e-01 6.85096145e-01
-2.11792693e-01 2.19106376e-01 -5.66434741e-01 -1.49810091e-01
3.82414550e-01 1.16670728e+00 -8.24567318e-01 -4.18080091e-01
-5.11316180e-01 7.26960480e-01 5.25506973e-01 1.98434681e-01
-8.67328644e-01 -4.31587607e-01 -4.75085676e-02 -4.33089912e-01
1.48581624e-01 -1.24969169e-01 -3.58596712e-01 -8.60898972e-01
-8.75638127e-02 -9.13537502e-01 3.01897615e-01 -4.08281535e-01
-1.29374731e+00 1.02779615e+00 6.74679130e-02 -7.51335323e-01
-6.59778535e-01 -5.18908441e-01 -9.67371285e-01 5.61411142e-01
-1.00683737e+00 -1.30203402e+00 3.12313195e-02 4.20907252e-02
1.15780818e+00 -1.89609826e-01 9.44977820e-01 2.75154551e-03
-4.88663882e-01 2.65026659e-01 -2.63355613e-01 6.21693671e-01
4.73744154e-01 -1.30346656e+00 8.12853575e-01 3.15197229e-01
2.01548621e-01 5.42528927e-01 7.14631557e-01 -4.37379926e-01
-7.60762036e-01 -5.51965535e-01 1.45047116e+00 -6.43520653e-01
7.34071910e-01 -5.28920054e-01 -9.95761871e-01 1.17911148e+00
1.09276819e+00 -9.96365786e-01 9.33203876e-01 6.15308344e-01
8.99701044e-02 8.05551827e-01 -1.22016978e+00 3.18871051e-01
4.57581013e-01 -6.17154181e-01 -1.17703187e+00 6.59217119e-01
1.03162384e+00 -5.76246381e-01 -9.29967880e-01 3.70439380e-01
4.41583633e-01 -9.28017080e-01 6.55387402e-01 -6.59691930e-01
4.09017861e-01 4.28809911e-01 2.24103779e-02 -7.53705382e-01
1.46344587e-01 -8.38573158e-01 -1.17671028e-01 1.34988916e+00
6.27725959e-01 -5.09447992e-01 7.99753666e-01 8.04727376e-01
-2.59309322e-01 -7.31606841e-01 -9.70451772e-01 -4.26554173e-01
8.79572481e-02 -4.18646455e-01 -2.22181790e-02 9.17571723e-01
7.42861748e-01 1.31885791e+00 -4.52304453e-01 -4.49741423e-01
-1.28143430e-01 8.03253800e-02 6.12898707e-01 -1.03809834e+00
-2.01838568e-01 -4.79032815e-01 1.10874653e-01 -1.44109309e+00
5.86566508e-01 -2.40742326e-01 3.86330754e-01 -1.67260122e+00
1.96303591e-01 -1.65807545e-01 6.94586486e-02 3.83376986e-01
-9.20667052e-02 5.57004511e-02 3.01802367e-01 2.58727580e-01
-1.06187594e+00 4.57220078e-01 6.74252748e-01 -1.46936849e-01
-6.20227993e-01 4.05998051e-01 -4.23233777e-01 9.95620906e-01
1.26204026e+00 -4.23722118e-01 -1.08547784e-01 -2.54370779e-01
-2.36745477e-01 4.76464331e-01 -3.00541669e-01 -4.07517821e-01
1.84587181e-01 -2.47179940e-01 -4.18438405e-01 -7.37277091e-01
5.18318951e-01 -1.66498542e-01 -5.53209364e-01 5.14924884e-01
-8.03605735e-01 -5.96078075e-02 4.83383201e-02 1.42120704e-01
-4.38936144e-01 -7.52416730e-01 2.29810670e-01 -2.82748044e-01
-4.42429185e-01 -6.20132744e-01 -1.06447160e+00 2.34428212e-01
8.10500979e-01 2.27603063e-01 -8.27876806e-01 -9.99832153e-01
-5.84916532e-01 2.11391374e-01 -6.28584698e-02 6.25621974e-01
4.92466211e-01 -7.17635095e-01 -5.92281520e-01 -3.94697011e-01
-2.87798733e-01 -3.87747109e-01 -6.60217926e-02 9.30178583e-01
-5.18496871e-01 1.00653338e+00 8.25712457e-02 -4.52740103e-01
-1.69000912e+00 1.72335729e-01 1.16845392e-01 -9.17747676e-01
-4.62614149e-01 9.68810141e-01 -2.83033028e-02 -5.91624081e-01
5.60292423e-01 -9.10238475e-02 -8.18611920e-01 1.64229237e-02
4.64811176e-01 4.77208346e-01 -9.75051075e-02 -6.69929683e-01
-2.11634859e-01 -2.56279707e-01 -3.60380173e-01 -5.89960814e-01
1.13214517e+00 -7.21679255e-02 -2.82641590e-01 8.59610617e-01
1.03982079e+00 -2.19316520e-02 -5.96498609e-01 -1.90126866e-01
6.38693273e-01 -3.28109890e-01 -4.30013061e-01 -9.49519098e-01
-3.07418734e-01 8.16419482e-01 2.13261455e-01 1.01411784e+00
6.74076736e-01 2.94777393e-01 9.77218449e-01 8.86146724e-01
1.51701093e-01 -1.16890693e+00 3.95798743e-01 1.23409557e+00
9.31862652e-01 -1.26446497e+00 -3.66486520e-01 -4.72541898e-01
-1.11179876e+00 8.06267321e-01 8.47938061e-01 -7.24475980e-02
2.36130267e-01 1.60047606e-01 5.84595203e-01 -3.12144816e-01
-1.10606444e+00 -2.32157513e-01 1.08369701e-01 3.23621213e-01
1.09106219e+00 -1.36535361e-01 -5.05872309e-01 5.03923357e-01
-4.36343253e-01 -1.60619661e-01 5.40196240e-01 1.18090677e+00
-6.06425703e-01 -9.50741410e-01 8.60139541e-03 2.95605987e-01
-9.56505954e-01 -1.10546127e-02 -9.97374892e-01 1.00743508e+00
-6.74884081e-01 1.46228015e+00 -2.12724768e-02 -5.34549296e-01
2.79124707e-01 4.27862972e-01 1.46104619e-01 -9.93319273e-01
-1.31060660e+00 8.75902399e-02 8.98710430e-01 -2.96700150e-01
-8.80475581e-01 -5.20128667e-01 -1.17488921e+00 -1.37409583e-01
-7.77209580e-01 6.26747072e-01 5.24275601e-01 1.31245220e+00
8.34556744e-02 3.77743155e-01 8.03799927e-01 -7.22568631e-01
-4.10595626e-01 -1.87155509e+00 2.22621694e-01 7.89853707e-02
2.23907903e-01 -2.63376474e-01 -2.09974989e-01 6.94922656e-02] | [12.75971508026123, 7.853498458862305] |
13c07323-1d57-4fe1-9401-178ebb4d0e9b | training-deep-boltzmann-networks-with-sparse | 2303.10728 | null | https://arxiv.org/abs/2303.10728v1 | https://arxiv.org/pdf/2303.10728v1.pdf | Training Deep Boltzmann Networks with Sparse Ising Machines | The slowing down of Moore's law has driven the development of unconventional computing paradigms, such as specialized Ising machines tailored to solve combinatorial optimization problems. In this paper, we show a new application domain for probabilistic bit (p-bit) based Ising machines by training deep generative AI models with them. Using sparse, asynchronous, and massively parallel Ising machines we train deep Boltzmann networks in a hybrid probabilistic-classical computing setup. We use the full MNIST dataset without any downsampling or reduction in hardware-aware network topologies implemented in moderately sized Field Programmable Gate Arrays (FPGA). Our machine, which uses only 4,264 nodes (p-bits) and about 30,000 parameters, achieves the same classification accuracy (90%) as an optimized software-based restricted Boltzmann Machine (RBM) with approximately 3.25 million parameters. Additionally, the sparse deep Boltzmann network can generate new handwritten digits, a task the 3.25 million parameter RBM fails at despite achieving the same accuracy. Our hybrid computer takes a measured 50 to 64 billion probabilistic flips per second, which is at least an order of magnitude faster than superficially similar Graphics and Tensor Processing Unit (GPU/TPU) based implementations. The massively parallel architecture can comfortably perform the contrastive divergence algorithm (CD-n) with up to n = 10 million sweeps per update, beyond the capabilities of existing software implementations. These results demonstrate the potential of using Ising machines for traditionally hard-to-train deep generative Boltzmann networks, with further possible improvement in nanodevice-based realizations. | ['Kerem Y. Camsari', 'Yao Qin', 'Shuvro Chowdhury', 'Masoud Mohseni', 'Navid Anjum Aadit', 'Shaila Niazi'] | 2023-03-19 | null | null | null | null | ['combinatorial-optimization'] | ['methodology'] | [ 2.29298130e-01 -9.76220742e-02 3.34778965e-01 -2.36756042e-01
-7.63979137e-01 -5.18800557e-01 8.18786263e-01 -2.47633472e-01
-7.02097714e-01 9.89598274e-01 -4.30136353e-01 -5.68238080e-01
5.22804745e-02 -1.24586070e+00 -9.97399092e-01 -1.23892367e+00
-9.00665298e-02 1.22987711e+00 2.88489312e-01 -1.03150241e-01
4.08096969e-01 5.58010101e-01 -1.49161482e+00 1.37114644e-01
5.61922193e-01 1.12436557e+00 -1.63962930e-01 1.26432443e+00
4.72181700e-02 3.35673451e-01 -4.55304265e-01 -5.41619182e-01
2.27455586e-01 -4.78320792e-02 -4.43647146e-01 -9.84014094e-01
6.21643662e-01 -4.48362321e-01 -5.27922332e-01 1.00380909e+00
5.51021934e-01 5.87377027e-02 9.40857291e-01 -9.00399983e-01
-5.27215719e-01 9.27827656e-01 -2.01377198e-01 2.82270968e-01
-2.75718540e-01 4.43662792e-01 6.73282981e-01 -6.77356958e-01
1.08524680e-01 9.76808369e-01 7.87912369e-01 7.14571774e-01
-1.30079854e+00 -7.36541450e-01 -6.85268879e-01 -1.92534570e-02
-1.50724268e+00 -1.96802929e-01 4.25143749e-01 -1.37022272e-01
1.78994751e+00 2.91561186e-01 1.03645146e+00 1.41050291e+00
9.55541372e-01 2.28658095e-01 1.09268582e+00 -3.10184985e-01
9.33945715e-01 -2.53851324e-01 3.01470429e-01 6.56830788e-01
8.50372791e-01 2.02637613e-01 -5.84300876e-01 -5.49066305e-01
9.74846125e-01 -1.69341907e-01 4.79863882e-01 5.14206253e-02
-1.23086739e+00 9.15045679e-01 4.28251177e-01 1.71927974e-01
-4.08766359e-01 1.21636391e+00 2.79768556e-01 -4.55023378e-01
8.76602009e-02 4.03581947e-01 -4.41861361e-01 -6.73055887e-01
-1.12201166e+00 4.55847502e-01 1.30606055e+00 7.49724567e-01
6.88849032e-01 7.32861519e-01 2.38109708e-01 1.73046812e-01
3.29704612e-01 9.08152878e-01 4.45509255e-01 -7.85776436e-01
1.54390633e-02 -1.17368773e-01 -1.78140506e-01 -5.42563796e-01
-2.68029690e-01 -4.02933925e-01 -1.27715266e+00 3.02522033e-01
2.67654568e-01 -1.91547424e-01 -1.35206079e+00 1.24203622e+00
1.68449476e-01 3.74135822e-02 -2.15797126e-02 6.78814054e-01
3.06761563e-01 1.20696485e+00 5.44664785e-02 4.13892061e-01
1.39314866e+00 -5.60382605e-01 1.03094205e-01 -2.99118906e-01
2.90201217e-01 -5.77321231e-01 6.87754035e-01 7.14351177e-01
-9.72203970e-01 -2.75404423e-01 -1.47093105e+00 7.77823702e-02
-3.51398587e-01 -4.27223623e-01 1.49264681e+00 1.34182787e+00
-1.34372878e+00 8.88281405e-01 -1.39620245e+00 3.29985544e-02
6.08615100e-01 8.60678136e-01 1.91771328e-01 -4.14852127e-02
-9.88551080e-01 6.70525253e-01 6.78178787e-01 -8.93474929e-03
-1.12108672e+00 -6.19167745e-01 -4.09663171e-01 1.16233662e-01
-4.63715017e-01 -1.15953362e+00 9.34917748e-01 -5.84830225e-01
-2.21541691e+00 3.96481097e-01 1.67839676e-01 -9.26133692e-01
-4.93921079e-02 1.35987625e-01 -1.49805278e-01 -1.17221288e-01
-5.52224457e-01 9.48691308e-01 7.72179246e-01 -5.96996307e-01
-4.57145572e-02 -4.18676138e-01 -3.58780622e-01 -2.41775915e-01
-3.17430407e-01 -2.88717836e-01 1.59014985e-01 -4.79622841e-01
2.42163807e-01 -1.37598789e+00 -4.01692599e-01 -4.71952438e-01
-2.32787564e-01 -1.15659751e-01 3.72167915e-01 -3.46576095e-01
5.21863580e-01 -1.68369174e+00 1.52148485e-01 4.39607471e-01
1.21479496e-01 1.80183247e-01 5.65925613e-02 1.37425706e-01
4.08068538e-01 -7.35586807e-02 -4.40096557e-01 9.80492681e-02
1.25174761e-01 4.54371095e-01 -4.97781605e-01 3.39170337e-01
-7.02196583e-02 1.07626641e+00 -6.15187109e-01 -8.73049870e-02
6.90220445e-02 8.17030251e-01 -8.42372060e-01 -4.29095060e-01
-2.88704783e-01 6.11144602e-02 -1.97146475e-01 6.78214848e-01
7.69905686e-01 -2.29246631e-01 2.14898348e-01 -3.15660745e-01
1.12366006e-01 3.34426045e-01 -7.08248079e-01 1.85072315e+00
-4.92307186e-01 6.18447542e-01 -3.55306685e-01 -7.84611702e-01
9.85819280e-01 -8.32928643e-02 -1.33837610e-01 -5.20090997e-01
2.48434454e-01 5.43171406e-01 3.95738840e-01 4.36078370e-01
7.69302368e-01 -3.97889614e-01 -3.48289192e-01 3.51750076e-01
6.50718451e-01 -7.48183727e-01 -2.99334079e-02 1.49120137e-01
1.22215831e+00 -3.71075720e-02 -1.83899313e-01 -6.15078807e-01
-2.36060023e-01 -1.30439615e-02 1.81951299e-01 1.28587091e+00
7.61445984e-02 2.06809103e-01 1.63236305e-01 -8.83532226e-01
-1.48231781e+00 -1.44907594e+00 -4.47393090e-01 1.05886161e+00
-1.30739063e-01 -3.12566161e-01 -8.91393363e-01 1.22437827e-01
-5.44282086e-02 9.54264581e-01 -3.76456350e-01 -2.26994753e-01
-5.16938746e-01 -1.64959717e+00 1.07610834e+00 5.88900268e-01
6.22058868e-01 -6.59990430e-01 -6.50063217e-01 4.83621150e-01
6.73456132e-01 -6.28136694e-01 3.75173956e-01 7.40044057e-01
-1.27631319e+00 -3.21868211e-02 -5.42170405e-01 -3.38886380e-01
3.56683016e-01 -6.08506382e-01 1.21984136e+00 -6.08230710e-01
-6.86466873e-01 -1.89668644e-04 2.24246249e-01 -3.12717021e-01
-4.88388449e-01 2.58860439e-01 4.67218518e-01 -7.03913271e-01
4.58959639e-01 -1.14939773e+00 -7.49966800e-01 -3.56796890e-01
-7.73247302e-01 3.24639231e-01 9.30281997e-01 1.01996124e+00
4.95808065e-01 -4.41367179e-02 2.37221047e-01 -4.76060569e-01
1.14600256e-01 -3.32788706e-01 -8.31816018e-01 -3.80436778e-02
-6.29247367e-01 6.93935513e-01 7.06995010e-01 -6.28902555e-01
-9.80171561e-01 -4.67197411e-03 -4.98930424e-01 1.27270997e-01
-1.13534965e-01 2.84648836e-01 2.78476715e-01 -6.31682932e-01
9.06175673e-01 5.04398406e-01 -4.64002490e-01 1.10724136e-01
3.81965637e-01 4.55550492e-01 5.02114773e-01 -1.12045228e+00
3.31770837e-01 4.50603366e-01 3.75301212e-01 -7.56824195e-01
-3.54485512e-01 5.03544986e-01 -2.01864466e-01 3.02130952e-02
7.47954488e-01 -6.61309838e-01 -9.13575351e-01 8.56051445e-01
-1.24686050e+00 -4.54020143e-01 -2.05144390e-01 6.10954046e-01
-5.24438024e-01 1.96329858e-02 -1.18377209e+00 -8.18037212e-01
-8.94650638e-01 -1.05458438e+00 8.56694579e-01 5.20319045e-01
-1.02006651e-01 -7.37365901e-01 4.71833020e-01 2.29673818e-01
9.97529387e-01 -1.03176825e-01 1.01541591e+00 -6.10525548e-01
-8.72218132e-01 -4.29182172e-01 -1.14035800e-01 1.92692816e-01
-5.20823479e-01 1.32158041e-01 -1.02770257e+00 -2.29140669e-01
1.45584762e-01 -4.74557072e-01 1.03820562e+00 4.49620038e-01
1.24536109e+00 -3.25529069e-01 -2.21370980e-01 8.51132035e-01
1.49755657e+00 2.26157904e-01 9.60474789e-01 -1.22390396e-03
7.88903058e-01 -3.02954793e-01 -4.19917643e-01 5.16538560e-01
5.24385981e-02 3.70067298e-01 3.91801924e-01 6.06065273e-01
1.41831085e-01 -9.87308100e-02 3.61607343e-01 1.29311299e+00
-4.83057141e-01 -1.09179586e-01 -1.30697513e+00 -6.34803921e-02
-1.31577277e+00 -6.87865257e-01 5.06544486e-02 2.33644962e+00
1.22234237e+00 4.85382557e-01 -4.78962153e-01 -2.77274579e-01
4.34506685e-01 -2.16548238e-02 -8.02418113e-01 -8.68708372e-01
6.86258078e-02 1.23559833e+00 9.85454679e-01 1.58538789e-01
-8.90000522e-01 9.75333810e-01 6.33043671e+00 1.46584189e+00
-1.38687098e+00 2.48557881e-01 1.00786519e+00 -2.70729363e-01
-3.60631913e-01 1.72850087e-01 -1.12637031e+00 7.41399765e-01
2.00157809e+00 1.12209819e-01 7.83234894e-01 1.11410904e+00
-8.89329612e-01 -3.59307885e-01 -1.09675813e+00 1.32076895e+00
7.75611848e-02 -1.88847136e+00 3.17097306e-01 3.34568441e-01
8.93317640e-01 5.42978704e-01 3.86906534e-01 4.57988560e-01
7.69415557e-01 -1.36054337e+00 6.34551942e-01 4.67921764e-01
8.01401913e-01 -1.08612967e+00 5.86692095e-01 1.17152162e-01
-5.73647916e-01 3.02792698e-01 -8.60617101e-01 -3.41226220e-01
3.94879580e-02 1.03077281e+00 -7.98764229e-01 2.99176574e-02
7.31770098e-01 -9.10249129e-02 -1.79942071e-01 6.18245125e-01
3.38020295e-01 9.00022626e-01 -1.10618138e+00 -7.65148938e-01
4.62163687e-01 -2.50026762e-01 3.67279172e-01 1.21096611e+00
6.79877162e-01 1.37196993e-02 -6.12215340e-01 1.08714437e+00
-8.71825814e-02 -7.00320601e-01 -3.87295276e-01 -2.63026774e-01
5.53378105e-01 1.41262197e+00 -1.06121385e+00 -6.05250239e-01
3.35432351e-01 1.19337952e+00 1.43052757e-01 -4.34655920e-02
-1.05274975e+00 -4.86971170e-01 4.85821396e-01 -3.46626461e-01
3.58422309e-01 -7.64847279e-01 -7.49523640e-01 -9.97459054e-01
-4.89628822e-01 -6.80182993e-01 -2.77928203e-01 -5.89517534e-01
-1.30621850e+00 5.93115389e-01 -3.55196297e-01 -3.30010772e-01
-3.46762985e-01 -1.03743088e+00 -5.66474557e-01 8.41529787e-01
-6.89112663e-01 -1.13097966e+00 5.05442768e-02 1.25369549e-01
-4.44925129e-02 -1.64196372e-01 1.28341472e+00 -1.84433833e-02
-4.28687721e-01 5.46775401e-01 5.15317261e-01 -5.82139455e-02
1.18688859e-01 -1.02833855e+00 1.00350833e+00 5.67831874e-01
4.31786954e-01 6.64122581e-01 7.55223334e-01 -6.57123327e-01
-2.21382809e+00 -8.86228979e-01 1.42353117e-01 -5.14120936e-01
8.11235309e-01 -6.13173366e-01 -6.48961484e-01 4.22955543e-01
6.07911460e-02 2.78802309e-02 7.29184330e-01 1.49786368e-01
-5.84618449e-01 -1.07722998e-01 -1.18236494e+00 5.42039454e-01
7.38606870e-01 -5.15879691e-01 -3.18348855e-01 5.90974927e-01
4.18668270e-01 -5.49687982e-01 -7.78268695e-01 2.62229472e-01
8.72146010e-01 -8.33770275e-01 1.14333296e+00 -3.92167747e-01
3.15168768e-01 1.17571384e-01 -4.04417038e-01 -9.68204677e-01
-3.67789894e-01 -5.15327871e-01 -4.51104105e-01 8.08573663e-01
2.34595701e-01 -8.53539109e-01 1.02069855e+00 8.89297187e-01
-1.36370376e-01 -8.47182751e-01 -1.50324249e+00 -7.80505002e-01
4.38191533e-01 -6.22836947e-01 4.34255093e-01 4.05163676e-01
-2.68857211e-01 8.66285637e-02 -3.42957638e-02 -8.82143155e-03
9.97478783e-01 -2.08257571e-01 2.54325002e-01 -1.04751253e+00
-7.46171355e-01 -5.43960869e-01 -8.63119662e-01 -7.91199327e-01
1.66940428e-02 -9.16024804e-01 8.98373276e-02 -9.57342088e-01
4.25043464e-01 -7.97007501e-01 -1.80511847e-01 3.00810903e-01
3.61773700e-01 5.77705443e-01 -3.16653699e-01 2.29841284e-02
-3.20472777e-01 6.07858419e-01 3.38014305e-01 -2.48057917e-01
2.46620670e-01 -4.78638828e-01 -2.91491151e-01 7.66587794e-01
8.13762486e-01 -6.42005205e-01 2.49901358e-02 -5.58788598e-01
7.48726964e-01 -2.81187177e-01 6.01337254e-01 -1.68235147e+00
6.15866959e-01 5.82048520e-02 7.79357493e-01 -4.18412298e-01
6.50543094e-01 -1.71205938e-01 5.10103405e-01 7.57241189e-01
1.09446794e-01 -1.73860714e-02 4.57768232e-01 4.53939736e-01
4.12095577e-01 -3.62835914e-01 7.61088550e-01 -2.07329318e-01
-3.93675268e-01 3.27858806e-01 -7.73573101e-01 -1.90075353e-01
8.52144420e-01 -1.24338210e-01 -4.91800994e-01 9.46390405e-02
-1.86781883e-01 -7.91961312e-01 4.78443593e-01 -3.09525192e-01
6.27936304e-01 -1.12228703e+00 -4.22478527e-01 1.89783648e-01
-5.76297760e-01 1.90560415e-01 5.46453834e-01 3.75516683e-01
-1.18352044e+00 6.53431654e-01 -5.74685752e-01 -8.48449111e-01
-4.41827625e-01 8.37772191e-02 2.77097851e-01 -2.30567485e-01
-4.69349593e-01 1.31815159e+00 -1.73012912e-01 -2.25287274e-01
-3.60558927e-01 -3.66693616e-01 8.45458388e-01 -6.02077723e-01
4.08834130e-01 3.74061763e-01 3.92543495e-01 1.35616988e-01
-4.68871891e-01 1.54625833e-01 -2.30989590e-01 -4.98247236e-01
1.42248809e+00 7.20649242e-01 -5.66671133e-01 4.70004737e-01
8.83443117e-01 -3.75815153e-01 -1.16251206e+00 4.54966754e-01
-3.83413196e-01 3.61622050e-02 4.20845538e-01 -6.67949438e-01
-6.32649302e-01 1.07558215e+00 7.35876799e-01 -2.02005610e-01
3.21938783e-01 -6.77357912e-02 1.12501276e+00 9.73640203e-01
1.10547912e+00 -1.00923193e+00 -1.44143835e-01 8.85650635e-01
3.52747530e-01 -6.96520984e-01 3.49548869e-02 3.45151246e-01
-6.93359599e-02 1.36849046e+00 4.74845171e-01 -6.92203045e-01
6.84053957e-01 9.36245263e-01 -7.81248927e-01 6.11547846e-03
-7.14928925e-01 6.40494645e-01 -4.34230193e-02 5.65321326e-01
2.49102131e-01 6.16651058e-01 2.37140775e-01 6.53818846e-01
-5.00642478e-01 2.78038736e-02 4.19830501e-01 9.40773368e-01
-4.71976191e-01 -9.47356820e-01 -2.63308883e-01 8.62969339e-01
-1.87619463e-01 -7.49511063e-01 3.31456095e-01 1.58331290e-01
-3.19795549e-01 1.48789003e-01 6.65261328e-01 -5.24913907e-01
-6.39412165e-01 2.28602722e-01 1.16841114e+00 -2.94745177e-01
-5.19638956e-01 -6.26911700e-01 -1.94607228e-01 -3.87766629e-01
1.94422022e-01 -2.90354878e-01 -1.30304492e+00 -1.00828207e+00
-1.65260330e-01 -1.09279931e-01 1.44445264e+00 7.93978930e-01
6.94975853e-01 4.53037769e-01 -1.26957595e-01 -1.75587714e+00
-8.36158872e-01 -8.03931117e-01 -5.91155767e-01 -5.10007083e-01
-4.20194358e-01 -5.13726294e-01 -3.85059357e-01 -3.25796485e-01] | [5.583192825317383, 4.876694679260254] |
24a18e08-ecbd-4262-a8ce-49fdda873a32 | synthetic-combinations-a-causal-inference | 2303.14226 | null | https://arxiv.org/abs/2303.14226v1 | https://arxiv.org/pdf/2303.14226v1.pdf | Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions | We consider a setting with $N$ heterogeneous units and $p$ interventions. Our goal is to learn unit-specific potential outcomes for any combination of these $p$ interventions, i.e., $N \times 2^p$ causal parameters. Choosing combinations of interventions is a problem that naturally arises in many applications such as factorial design experiments, recommendation engines (e.g., showing a set of movies that maximizes engagement for users), combination therapies in medicine, selecting important features for ML models, etc. Running $N \times 2^p$ experiments to estimate the various parameters is infeasible as $N$ and $p$ grow. Further, with observational data there is likely confounding, i.e., whether or not a unit is seen under a combination is correlated with its potential outcome under that combination. To address these challenges, we propose a novel model that imposes latent structure across both units and combinations. We assume latent similarity across units (i.e., the potential outcomes matrix is rank $r$) and regularity in how combinations interact (i.e., the coefficients in the Fourier expansion of the potential outcomes is $s$ sparse). We establish identification for all causal parameters despite unobserved confounding. We propose an estimation procedure, Synthetic Combinations, and establish finite-sample consistency under precise conditions on the observation pattern. Our results imply Synthetic Combinations consistently estimates unit-specific potential outcomes given $\text{poly}(r) \times (N + s^2p)$ observations. In comparison, previous methods that do not exploit structure across both units and combinations have sample complexity scaling as $\min(N \times s^2p, \ \ r \times (N + 2^p))$. We use Synthetic Combinations to propose a data-efficient experimental design mechanism for combinatorial causal inference. We corroborate our theoretical findings with numerical simulations. | ['Suhas Vijaykumar', 'Anish Agarwal', 'Abhineet Agarwal'] | 2023-03-24 | null | null | null | null | ['experimental-design'] | ['methodology'] | [ 4.24160093e-01 -6.07961006e-02 -8.38943243e-01 3.95414466e-03
-5.92893422e-01 -6.56477034e-01 1.37347460e-01 2.02450439e-01
-3.69363755e-01 8.68572533e-01 2.33160958e-01 -5.36243021e-01
-7.04976797e-01 -9.48282480e-01 -1.00114465e+00 -7.13696420e-01
-5.86306691e-01 2.24122033e-01 -4.85682815e-01 2.19274625e-01
1.62186980e-01 1.80567279e-01 -1.38047409e+00 -1.87409595e-01
9.55273151e-01 5.77258527e-01 2.86385473e-02 4.93903309e-01
3.66265386e-01 4.39360052e-01 -1.30772829e-01 -1.71324492e-01
4.46257114e-01 -6.32022858e-01 -2.93316573e-01 -4.24364349e-03
2.70913512e-01 -2.28558347e-01 -4.36308503e-01 9.76158559e-01
3.88886601e-01 7.90743828e-02 7.42100298e-01 -1.23979855e+00
-4.33341652e-01 7.70434618e-01 -9.70217168e-01 -1.16978437e-02
2.73503155e-01 2.95857072e-01 1.20761871e+00 -5.93911946e-01
5.16730487e-01 1.22019148e+00 2.61979073e-01 1.66925743e-01
-1.69918633e+00 -1.12423658e+00 2.77897179e-01 -2.73952335e-01
-1.23739624e+00 -3.07871550e-01 5.39681613e-01 -6.34475768e-01
4.00537848e-01 3.62218827e-01 3.50858301e-01 1.07924044e+00
7.17957392e-02 4.26776856e-01 1.17239952e+00 -4.00118142e-01
4.03585285e-01 -2.28420272e-01 1.09468602e-01 7.03317821e-01
6.10845745e-01 2.31792450e-01 -5.59633672e-01 -4.99053031e-01
1.08364749e+00 3.25737625e-01 -1.44005671e-01 -1.00990690e-01
-1.22360861e+00 1.06127918e+00 6.34777918e-02 1.20189987e-01
-6.30975664e-01 4.79590684e-01 -9.74977911e-02 1.76267073e-01
2.28672028e-02 5.98845124e-01 -6.03660762e-01 -1.05466060e-01
-7.41507709e-01 3.87969047e-01 4.30230498e-01 1.08244324e+00
5.84501684e-01 -1.96458295e-01 -3.60757589e-01 7.33048439e-01
9.52577498e-03 9.71898854e-01 -5.95998429e-02 -1.27269113e+00
5.14788568e-01 5.59959471e-01 3.83330941e-01 -9.55311298e-01
-4.31833863e-01 -2.51070380e-01 -1.31552362e+00 -3.29798281e-01
6.11842215e-01 -6.26552463e-01 -6.15733147e-01 2.46168423e+00
2.27214530e-01 3.82470459e-01 -4.83026266e-01 5.15159190e-01
2.25545943e-01 4.93955523e-01 2.07508102e-01 -1.05982459e+00
1.62866700e+00 -1.71429649e-01 -6.95032418e-01 -1.57030150e-01
5.69484591e-01 -6.50976956e-01 1.10650408e+00 2.24622250e-01
-1.50290251e+00 -1.52804956e-01 -4.92281824e-01 4.42674965e-01
1.95842028e-01 8.80900845e-02 8.76381218e-01 5.94756126e-01
-6.73322380e-01 5.52043855e-01 -4.73327398e-01 1.16548598e-01
3.65907282e-01 7.42356300e-01 -5.96771836e-02 -3.04977149e-01
-1.16409719e+00 1.46654010e-01 -3.50421876e-01 -2.37920120e-01
-8.69989812e-01 -1.13804972e+00 -5.42333901e-01 2.73095697e-01
9.53643739e-01 -9.57197726e-01 8.58212233e-01 -3.17210525e-01
-9.00095463e-01 2.88980573e-01 -4.27723169e-01 -6.27656952e-02
2.27848127e-01 8.65145028e-02 -1.60226837e-01 -1.76398233e-02
3.68140340e-01 1.94809496e-01 6.11828744e-01 -8.29138458e-01
-5.59680402e-01 -5.25746763e-01 2.25035205e-01 1.55171856e-01
-2.28670299e-01 1.33747116e-01 -3.50007147e-01 -5.93171299e-01
1.61991179e-01 -1.07028329e+00 -6.54526055e-01 -3.06090981e-01
-6.19379640e-01 -7.64512941e-02 6.15884811e-02 -3.64440680e-01
1.53921461e+00 -2.08618641e+00 3.14604282e-01 5.28785527e-01
5.29398441e-01 -4.58724260e-01 -1.55141905e-01 5.27764738e-01
-1.79779574e-01 5.59570253e-01 -1.22703940e-01 -1.25649869e-01
1.10626658e-02 -6.59805536e-02 -3.70901190e-02 4.70961004e-01
-1.60785124e-01 5.63454926e-01 -7.55710661e-01 -3.52219909e-01
-1.53742954e-01 1.18666746e-01 -8.42074573e-01 5.07735424e-02
-2.17685893e-01 4.24208015e-01 -6.62623882e-01 5.45955420e-01
5.72478771e-01 -7.18909323e-01 6.46125257e-01 -6.08357601e-02
-2.04690948e-01 3.57551165e-02 -1.47618389e+00 1.15594304e+00
-5.09679794e-01 -4.05053012e-02 3.90201178e-03 -1.24708140e+00
3.54055673e-01 5.73415756e-01 9.07259643e-01 -4.68676448e-01
1.04333289e-01 2.52816379e-01 1.69870749e-01 -4.54397231e-01
-4.45408328e-03 -3.73373628e-01 -3.06705683e-01 5.36018848e-01
-2.83261687e-01 4.27119017e-01 2.31981874e-01 2.21377358e-01
1.62638760e+00 -6.61230683e-01 3.57225299e-01 -3.49464089e-01
-3.24262977e-02 -3.17171127e-01 8.65719378e-01 1.18112719e+00
-1.47557082e-02 2.29943037e-01 1.16307306e+00 1.25643432e-01
-1.07458687e+00 -8.61271858e-01 -1.64827839e-01 7.78418362e-01
1.21472307e-01 -7.45009258e-02 -5.03647327e-01 -4.35101032e-01
7.05836788e-02 5.25786042e-01 -9.49027836e-01 6.65811822e-02
-5.75072765e-01 -1.07154858e+00 3.22756581e-02 3.91107291e-01
1.99520946e-01 -7.61040390e-01 -2.89591461e-01 1.44381002e-01
-1.05341196e-01 -7.35017240e-01 -8.36390436e-01 1.86975554e-01
-8.48454952e-01 -1.16874409e+00 -5.65343440e-01 -4.51844215e-01
8.71290207e-01 3.67308050e-01 8.71919453e-01 -2.12567091e-01
-1.78992391e-01 2.90208489e-01 3.46033983e-02 -1.71942353e-01
9.78696719e-02 -3.74777168e-01 3.13530207e-01 -1.43816605e-01
1.49988756e-01 -8.33405495e-01 -1.18662548e+00 2.64484316e-01
-8.93706024e-01 -1.10597797e-01 7.14934528e-01 9.69120026e-01
7.27631092e-01 2.58619338e-01 6.76829875e-01 -1.18312609e+00
5.36447346e-01 -7.75972664e-01 -7.69904673e-01 2.03534365e-01
-5.89942634e-01 8.83062482e-02 7.27906644e-01 -8.91783714e-01
-6.52576745e-01 -1.07066326e-01 3.81073564e-01 -4.48574781e-01
1.00245021e-01 8.80440533e-01 -2.47273907e-01 4.93607551e-01
7.10671604e-01 -1.91443279e-01 -4.11529839e-02 -2.66556978e-01
2.98654407e-01 2.35965207e-01 -7.74252266e-02 -7.73921788e-01
4.95484263e-01 4.10796493e-01 4.46970493e-01 -6.01244390e-01
-5.11910498e-01 -2.36799732e-01 1.91766784e-01 2.93517023e-01
7.40730107e-01 -8.69754970e-01 -1.39760625e+00 -1.19499974e-01
-6.10980451e-01 -3.92891556e-01 -2.86673069e-01 9.48942959e-01
-6.03700399e-01 -6.00315146e-02 -3.77779156e-01 -1.08712804e+00
8.56056586e-02 -1.31667244e+00 7.79671431e-01 1.54624721e-02
-3.85585159e-01 -6.86162531e-01 7.40130013e-03 2.47667417e-01
8.23897347e-02 1.55598700e-01 1.32391775e+00 -2.01309308e-01
-7.90016890e-01 -1.91474676e-01 -3.06594849e-01 -3.13290626e-01
3.52800518e-01 -1.85946286e-01 -2.36116037e-01 -2.21318007e-01
-1.51178449e-01 7.87462667e-02 4.49239820e-01 1.31947017e+00
1.42582357e+00 -8.42668235e-01 -5.79585552e-01 2.08095908e-01
1.26873899e+00 5.88499844e-01 4.02161956e-01 -4.67886597e-01
4.84207481e-01 6.47376239e-01 3.54311377e-01 8.53012383e-01
1.47610649e-01 7.36571014e-01 1.06708288e-01 -2.12570429e-01
3.71940255e-01 -2.58997589e-01 2.10743025e-01 3.95172983e-01
-5.06312884e-02 -2.34078407e-01 -5.30276239e-01 5.78896523e-01
-1.68990695e+00 -9.18766201e-01 -7.39685297e-02 2.77989650e+00
1.20920360e+00 8.33321363e-03 3.45689505e-01 -2.41592452e-01
7.21573412e-01 -3.06327671e-01 -7.47893989e-01 -7.72833154e-02
4.43415716e-03 6.37619674e-01 8.38017464e-01 4.60994363e-01
-6.57901943e-01 2.67687112e-01 5.70653868e+00 1.09906733e+00
-6.29034221e-01 8.53194892e-02 1.09908760e+00 -5.62243819e-01
-5.87895155e-01 3.01055551e-01 -7.41864383e-01 7.14901447e-01
9.33357894e-01 -2.82866359e-01 5.17589152e-01 3.68542790e-01
8.44747543e-01 -2.61902928e-01 -1.28898847e+00 7.76897907e-01
-4.43451405e-01 -1.25133526e+00 -2.38964915e-01 5.84488332e-01
9.45998490e-01 -5.72653234e-01 3.87973517e-01 1.07225738e-01
8.09998333e-01 -1.11922491e+00 2.21415281e-01 9.01662111e-02
1.14094961e+00 -7.05876172e-01 1.66628674e-01 3.69816333e-01
-9.82183874e-01 -3.44833106e-01 -1.89668491e-01 -8.50902796e-02
1.49201497e-01 9.22341049e-01 -3.82085413e-01 3.93447012e-01
5.42171001e-01 3.60231876e-01 2.12045193e-01 5.91836631e-01
7.73400664e-02 8.37193251e-01 -5.49010694e-01 -1.61383618e-02
-1.38678610e-01 -4.65646416e-01 4.18483824e-01 5.93130052e-01
7.16199577e-01 7.80529022e-01 7.64838383e-02 8.68501186e-01
-3.08103830e-01 2.94754595e-01 -7.55530596e-01 -2.58181006e-01
8.19114387e-01 7.08361328e-01 -6.01516962e-01 -2.67210037e-01
-4.51951116e-01 3.96214843e-01 -1.20990090e-02 5.65872252e-01
-8.14010799e-01 3.79662551e-02 6.91924334e-01 3.41896415e-01
1.39068544e-01 -9.76364836e-02 -5.67383111e-01 -1.15232933e+00
-8.51800740e-02 -9.58678722e-01 5.91758192e-01 -3.04764628e-01
-1.31313860e+00 -2.12282136e-01 3.61307263e-01 -1.11753166e+00
1.02841176e-01 -1.80786267e-01 -2.89495170e-01 9.64030087e-01
-9.57010448e-01 -6.17637515e-01 3.28994632e-01 5.14287710e-01
1.99600458e-01 2.22340107e-01 8.00670922e-01 3.34574312e-01
-1.01943719e+00 7.43717670e-01 2.59082288e-01 -3.38783741e-01
5.88529766e-01 -1.04648411e+00 -3.61015707e-01 6.04272723e-01
-1.53568029e-01 1.18473637e+00 8.65485668e-01 -8.84449780e-01
-1.53805315e+00 -7.24549294e-01 8.49936724e-01 -1.07976735e-01
7.81612158e-01 -3.47449869e-01 -4.18540090e-01 6.37315929e-01
-1.15667053e-01 -3.36044192e-01 9.97615993e-01 5.87222338e-01
-2.54149109e-01 -1.30127668e-01 -1.07954347e+00 1.29619896e+00
1.33322191e+00 -1.10779762e-01 3.59902292e-01 5.82439125e-01
8.91889393e-01 -8.30421522e-02 -1.02577782e+00 6.34172857e-01
5.70962906e-01 -6.21255875e-01 1.02920020e+00 -7.24155247e-01
8.23820114e-01 1.16384424e-01 -3.27233523e-01 -9.87486839e-01
-3.42666060e-01 -7.04629242e-01 -4.29843478e-02 8.57918084e-01
7.60394275e-01 -6.29153490e-01 7.55975008e-01 1.05128098e+00
3.75850677e-01 -7.69985974e-01 -8.97736549e-01 -4.77706909e-01
2.29094192e-01 -2.33499840e-01 4.25920725e-01 1.19538486e+00
1.03570305e-01 3.48114491e-01 -5.82869530e-01 3.36304039e-01
7.11627781e-01 3.22183847e-01 5.42084634e-01 -8.80270183e-01
-9.06579316e-01 -4.80996609e-01 2.41719723e-01 -1.01985335e+00
-1.99504137e-01 -3.07356596e-01 -2.90775985e-01 -1.01571071e+00
8.03267658e-01 -1.12313473e+00 -3.15972298e-01 4.69457865e-01
-5.86023331e-01 -2.92360842e-01 -1.00291453e-01 1.45005673e-01
-1.88486263e-01 2.84468919e-01 1.30612612e+00 9.58496332e-03
-5.58768749e-01 1.42559215e-01 -1.02227008e+00 4.33586925e-01
6.88654244e-01 -4.89452273e-01 -6.66526735e-01 2.57586613e-02
6.35654986e-01 9.16615009e-01 2.32913181e-01 -2.86209017e-01
-3.65516841e-02 -8.56183529e-01 7.00484775e-03 -2.31676862e-01
1.14968352e-01 -7.54311860e-01 5.77079475e-01 5.10502934e-01
-6.41602933e-01 -3.77740562e-02 8.56088661e-03 6.61035895e-01
2.55079359e-01 -1.14247225e-01 3.74750584e-01 -1.02421619e-01
3.38076621e-01 5.36245883e-01 -2.33305812e-01 3.13760526e-02
9.36163247e-01 1.88532278e-01 -4.29101855e-01 -5.81646144e-01
-6.59029484e-01 4.13372040e-01 2.21441403e-01 -3.20327096e-02
2.76175737e-01 -1.35700238e+00 -6.12908125e-01 -4.09895740e-02
-7.95195624e-02 -5.63530624e-02 7.97404587e-01 1.12553513e+00
1.62475482e-01 2.88327008e-01 2.65970826e-01 -4.02133614e-01
-1.18154085e+00 8.06563556e-01 -5.46179749e-02 -5.73743820e-01
-5.69520555e-02 7.77317345e-01 7.97972500e-01 -1.25100790e-02
-1.95354726e-02 -1.79529428e-01 -3.49242054e-02 -6.00166246e-03
2.86292106e-01 3.70067000e-01 -4.41305399e-01 4.52221185e-02
-1.06567316e-01 4.52132344e-01 -1.33737385e-01 -4.51457411e-01
1.29132617e+00 -4.92247231e-02 -2.56959140e-01 4.83813524e-01
1.20159674e+00 4.06123400e-01 -1.21551692e+00 -2.78445184e-01
-4.60395962e-01 -4.50146228e-01 -2.64032215e-01 -5.33241689e-01
-1.06801283e+00 4.51485395e-01 4.73775148e-01 2.80250400e-01
1.28728378e+00 5.29700108e-02 1.68663457e-01 -1.35832086e-01
3.74001175e-01 -7.73248017e-01 4.13083956e-02 -1.55126631e-01
5.61076224e-01 -1.06086445e+00 1.46347508e-01 -6.39303207e-01
-3.35431427e-01 3.46603185e-01 3.08828890e-01 -1.48374392e-02
9.04670060e-01 -2.43525561e-02 -6.30872726e-01 -5.02592087e-01
-8.62465203e-01 7.39913806e-02 -5.04923146e-03 1.73319783e-02
5.51559269e-01 6.15983784e-01 -9.42239106e-01 7.35970318e-01
5.37230968e-02 -1.01431012e-02 5.79114139e-01 8.51912677e-01
-6.08874522e-02 -1.53614056e+00 -3.76068980e-01 1.07070506e+00
-7.13379860e-01 -3.62408876e-01 1.88806608e-01 5.93245387e-01
1.48204729e-01 1.07517898e+00 -1.11672036e-01 -1.35125399e-01
4.51703817e-01 -1.47482529e-01 4.10889149e-01 -6.58837557e-01
-3.26872438e-01 5.58962822e-01 -9.65712294e-02 -6.29708946e-01
-4.07258511e-01 -1.02304840e+00 -1.03863490e+00 -6.35331929e-01
-4.18799073e-01 1.61151633e-01 2.99533248e-01 7.36025512e-01
4.73238319e-01 4.05040830e-01 1.10431850e+00 -3.03423524e-01
-5.05147755e-01 -7.54820526e-01 -9.39648628e-01 4.56693083e-01
1.07229702e-01 -8.87609005e-01 -4.28158671e-01 8.83582830e-02] | [7.60601282119751, 5.055535793304443] |
0c4e3a67-89f3-46ea-adf2-f8774e44ba28 | herald-an-annotation-efficient-method-to | 2106.00162 | null | https://arxiv.org/abs/2106.00162v2 | https://arxiv.org/pdf/2106.00162v2.pdf | HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations | Open-domain dialog systems have a user-centric goal: to provide humans with an engaging conversation experience. User engagement is one of the most important metrics for evaluating open-domain dialog systems, and could also be used as real-time feedback to benefit dialog policy learning. Existing work on detecting user disengagement typically requires hand-labeling many dialog samples. We propose HERALD, an efficient annotation framework that reframes the training data annotation process as a denoising problem. Specifically, instead of manually labeling training samples, we first use a set of labeling heuristics to label training samples automatically. We then denoise the weakly labeled data using the Shapley algorithm. Finally, we use the denoised data to train a user engagement detector. Our experiments show that HERALD improves annotation efficiency significantly and achieves 86% user disengagement detection accuracy in two dialog corpora. | ['Zhou Yu', 'Kai-Hui Liang', 'Weixin Liang'] | 2021-06-01 | null | https://aclanthology.org/2021.acl-long.283 | https://aclanthology.org/2021.acl-long.283.pdf | acl-2021-5 | ['open-domain-dialog'] | ['natural-language-processing'] | [-6.21959716e-02 5.49185753e-01 -2.43430212e-01 -7.23213673e-01
-8.72361541e-01 -9.83200133e-01 7.89269745e-01 2.23043617e-02
-5.28435826e-01 7.15324640e-01 8.25412273e-01 -2.70643592e-01
3.79320621e-01 -3.29482496e-01 2.40075022e-01 -3.68625849e-01
3.76528382e-01 1.01894546e+00 1.22588277e-01 -4.74938273e-01
1.05424888e-01 1.59296364e-01 -8.74702215e-01 3.82586926e-01
8.91743362e-01 6.33191168e-01 -2.15773612e-01 8.70704353e-01
-2.28338867e-01 1.21485913e+00 -9.67775881e-01 -4.78962839e-01
7.04497620e-02 -6.64765358e-01 -1.50174987e+00 3.43337297e-01
3.25111263e-02 -7.18898416e-01 1.39408307e-02 9.47427452e-01
4.65431184e-01 4.86052841e-01 5.52015841e-01 -1.19778299e+00
-1.62855387e-01 7.70541430e-01 -2.00578332e-01 3.04143131e-02
6.63290501e-01 3.61473590e-01 1.28900588e+00 -7.27738023e-01
6.39817059e-01 1.58363724e+00 3.36772144e-01 9.27756965e-01
-1.48928785e+00 -3.83481145e-01 3.49670202e-02 -2.67601401e-01
-6.13607883e-01 -7.09618807e-01 7.97168732e-01 -6.71634138e-01
6.65363610e-01 4.21389759e-01 3.06998849e-01 1.49868083e+00
-6.09908342e-01 9.16988671e-01 9.63227808e-01 -4.07778203e-01
3.15549821e-01 3.87927413e-01 9.07188654e-01 6.95121050e-01
-4.02197152e-01 -1.82102695e-01 -3.84468436e-01 -7.22509146e-01
4.70065087e-01 -2.31459484e-01 -1.45712987e-01 -2.21369863e-01
-9.51203883e-01 1.20324290e+00 1.48318231e-01 3.13804805e-01
-1.61547363e-01 -4.45388883e-01 6.07751369e-01 5.73385239e-01
5.84058821e-01 8.64184260e-01 -4.00633454e-01 -5.87438881e-01
-3.49321872e-01 4.45071548e-01 1.52157712e+00 7.53760695e-01
6.15242600e-01 -4.37182784e-01 -5.45969605e-01 1.34906840e+00
3.39317352e-01 -1.64073762e-02 4.58401948e-01 -1.55275381e+00
3.70490462e-01 7.90021539e-01 5.80857933e-01 -3.50136071e-01
-4.85735029e-01 4.16489720e-01 -3.26969653e-01 2.36538857e-01
1.06117177e+00 -6.85642481e-01 -2.07099855e-01 1.87380540e+00
4.02100146e-01 -4.23081249e-01 2.95170039e-01 9.09096777e-01
8.07998717e-01 3.87611210e-01 2.54531413e-01 -3.34957182e-01
1.66529238e+00 -1.15044165e+00 -1.04562342e+00 -2.96263635e-01
9.18472886e-01 -7.19500184e-01 1.53531551e+00 4.24729615e-01
-1.07531667e+00 -1.72747836e-01 -7.98413992e-01 -4.01732683e-01
-1.80216823e-02 -9.38104391e-02 3.14261138e-01 6.39800787e-01
-6.09827101e-01 2.86071509e-01 -6.41329110e-01 -3.60334605e-01
1.44327819e-01 1.47267818e-01 -5.75213060e-02 4.36827213e-01
-1.23989475e+00 1.08645582e+00 8.52527618e-02 -4.01880682e-01
-5.48938811e-01 -3.43999386e-01 -8.78487885e-01 3.02358419e-01
6.78594291e-01 -2.82905549e-01 2.13915849e+00 -7.63769627e-01
-1.92700160e+00 1.04508245e+00 -1.30618945e-01 -2.88016856e-01
5.74553728e-01 -5.01382649e-01 -4.33908124e-03 -1.03959836e-01
-3.52468826e-02 4.94349301e-01 5.09148121e-01 -1.22417486e+00
-5.08991778e-01 -2.36382961e-01 3.14773709e-01 5.02366662e-01
-5.79543829e-01 2.68608272e-01 -1.12616673e-01 -3.20549250e-01
-2.41998225e-01 -1.00169182e+00 -3.02146763e-01 -4.28799063e-01
-5.19024551e-01 -8.67121875e-01 1.02425742e+00 -6.52276814e-01
1.22476494e+00 -2.12327194e+00 1.49289981e-01 6.17455952e-02
8.12980890e-01 3.55201721e-01 1.32060215e-01 3.93728435e-01
3.09143782e-01 -1.20777547e-01 -4.21791188e-02 -6.66856170e-01
3.12495947e-01 1.52667865e-01 -2.03860268e-01 2.90537812e-02
-6.50500581e-02 7.40320444e-01 -1.06033397e+00 -4.10551220e-01
3.69402349e-01 -1.79653391e-01 -7.05659747e-01 9.39105988e-01
-6.76897824e-01 8.42416763e-01 -4.12062198e-01 1.01232760e-01
3.23572487e-01 -2.98983812e-01 5.44343650e-01 1.53490275e-01
1.37838200e-01 7.38171637e-01 -7.46821046e-01 1.65336192e+00
-4.59647387e-01 5.76727211e-01 5.56946635e-01 -5.35122216e-01
9.74632680e-01 4.54700351e-01 5.14243186e-01 -1.10854752e-01
4.91596282e-01 -2.28686288e-01 7.91642219e-02 -5.96562564e-01
6.07855797e-01 -6.78103939e-02 -5.90802610e-01 9.65580046e-01
1.77461222e-01 -8.51733983e-02 -9.32481363e-02 5.76744437e-01
1.31467366e+00 -4.37882960e-01 5.19415081e-01 -2.39601746e-01
6.51403904e-01 5.51788788e-03 4.91159111e-01 5.79615533e-01
-6.17438197e-01 1.64177954e-01 1.01521838e+00 -2.60758758e-01
-8.06678712e-01 -8.50692511e-01 2.29815558e-01 1.71546876e+00
-8.58364850e-02 -4.34306562e-01 -1.22520971e+00 -1.07300937e+00
-2.87910372e-01 7.79314518e-01 -1.70476049e-01 -1.68878064e-01
-5.52663028e-01 -3.81198347e-01 7.55092204e-01 2.76744455e-01
5.80845833e-01 -1.37448061e+00 -4.89326000e-01 1.65155426e-01
-7.71604478e-01 -1.12734139e+00 -6.26186848e-01 2.82203138e-01
-4.51597542e-01 -1.17833185e+00 -1.73602909e-01 -8.81957233e-01
3.48456860e-01 9.98798907e-02 1.24060440e+00 1.46438941e-01
1.38222352e-01 2.25908086e-01 -2.90153295e-01 -1.28865708e-02
-9.92015302e-01 2.05524310e-01 9.59340334e-02 -1.97443455e-01
9.56149578e-01 -2.31213704e-01 -3.86039466e-01 5.08036554e-01
-3.90378565e-01 -9.00531039e-02 -5.53477891e-02 1.27551222e+00
-4.01239812e-01 -4.62815821e-01 8.16407502e-01 -1.41311455e+00
1.52230287e+00 -2.53687590e-01 -4.29550976e-01 5.56498505e-02
-4.19759840e-01 1.40040755e-01 5.63263535e-01 -5.09266078e-01
-1.57506299e+00 2.47296259e-01 -4.53121662e-01 -1.03250325e-01
-5.51466048e-01 6.21949360e-02 -5.04321158e-01 5.07823110e-01
1.01406240e+00 -4.84031647e-01 2.91626364e-01 -5.43063283e-01
7.85525799e-01 1.26590049e+00 5.80649137e-01 -7.80580044e-01
3.82549584e-01 -3.07719335e-02 -8.69439781e-01 -8.85692000e-01
-1.20198309e+00 -7.89204001e-01 -6.14118338e-01 -1.28936738e-01
1.10484779e+00 -6.90458596e-01 -1.24694276e+00 1.69868097e-01
-1.22856593e+00 -7.23467171e-01 -1.88264087e-01 5.66399135e-02
-5.93644023e-01 4.95000362e-01 -1.01920068e+00 -9.80806231e-01
-3.40306818e-01 -1.11523902e+00 8.71830523e-01 9.38861817e-02
-1.13051605e+00 -1.15838289e+00 3.09294581e-01 9.28002059e-01
3.17528881e-02 -9.76886302e-02 7.04348028e-01 -1.47479570e+00
-1.48268379e-02 -1.59701109e-01 8.22371393e-02 3.73702556e-01
2.76124120e-01 -5.66409349e-01 -1.34811139e+00 -1.70604885e-01
4.60569084e-01 -1.05726230e+00 3.97133231e-01 -6.10008501e-02
7.77552247e-01 -6.69045269e-01 -1.01877160e-01 -9.76824686e-02
4.20160115e-01 1.06637239e-01 2.47900128e-01 -2.26019204e-01
4.53356266e-01 9.92209554e-01 8.27713072e-01 7.51778662e-01
2.99055010e-01 6.49084747e-01 -7.65623599e-02 4.16785479e-02
2.70364583e-01 -2.86064625e-01 3.63500148e-01 4.93751049e-01
3.39105934e-01 -3.29685241e-01 -7.24399984e-01 2.48752043e-01
-2.10759449e+00 -9.71615851e-01 -1.10800795e-01 1.77469170e+00
1.33965635e+00 1.53227672e-01 5.97934783e-01 -2.84275673e-02
6.78673804e-01 1.55289426e-01 -4.31684643e-01 -4.27190840e-01
4.24224228e-01 5.17423227e-02 2.43840460e-02 1.13584423e+00
-1.05743766e+00 1.34648705e+00 6.12224531e+00 3.39157075e-01
-3.83222073e-01 4.29821640e-01 6.71114564e-01 4.76947501e-02
2.14219898e-01 4.74443287e-02 -7.78525352e-01 3.83039892e-01
9.43323195e-01 1.61107201e-02 5.08326471e-01 1.03576791e+00
4.02766764e-01 -1.86234206e-01 -1.46349716e+00 7.43096650e-01
-2.60493219e-01 -8.23341489e-01 -6.92749560e-01 7.53432289e-02
4.61455405e-01 -3.93998414e-01 -3.39550346e-01 6.70369864e-01
1.22715878e+00 -8.03389609e-01 2.64273491e-02 3.83204296e-02
3.22741568e-01 -5.21618962e-01 5.66385329e-01 7.74117529e-01
-6.16323769e-01 -3.77830230e-02 -9.40997377e-02 -1.75005898e-01
3.20364326e-01 2.02599540e-01 -1.32313621e+00 -3.44814181e-01
2.55741984e-01 3.80278438e-01 -1.95456728e-01 2.04990759e-01
-4.19948995e-01 6.42446876e-01 -2.04116806e-01 -1.69192567e-01
5.71447499e-02 -2.49547303e-01 5.84609866e-01 1.09880018e+00
-4.99442220e-01 5.70066392e-01 7.06833661e-01 8.77942204e-01
-3.50041956e-01 -1.01065397e-01 -6.34532511e-01 -4.78573851e-02
7.98413992e-01 1.49180257e+00 -3.22895288e-01 -6.56496763e-01
-4.55410779e-01 1.17324686e+00 5.39066851e-01 1.82538271e-01
-5.58571160e-01 -2.55324334e-01 8.48995507e-01 -2.53171951e-01
-2.41617918e-01 -7.52884001e-02 -4.05133635e-01 -1.28529596e+00
-3.85417730e-01 -1.15192497e+00 5.30316770e-01 -2.43501216e-01
-1.60066915e+00 4.35170442e-01 -2.36844063e-01 -8.66639435e-01
-8.14924121e-01 -5.20360231e-01 -7.74606526e-01 8.37290943e-01
-6.31101251e-01 -7.13630855e-01 -6.57222867e-01 5.07665277e-01
9.45354402e-01 -1.71473965e-01 1.14266860e+00 1.82835199e-02
-6.03289485e-01 5.62314510e-01 -2.29955003e-01 5.53370833e-01
1.22166967e+00 -1.73090816e+00 3.94888997e-01 3.74835581e-01
-1.25115216e-01 8.13323259e-01 8.79779279e-01 -6.41666293e-01
-7.96461165e-01 -6.59249365e-01 7.74308205e-01 -8.55381250e-01
7.96053469e-01 -6.73627138e-01 -1.04320669e+00 8.25783432e-01
6.23585522e-01 -5.21526814e-01 8.79849494e-01 5.88619947e-01
-2.33540192e-01 5.47613323e-01 -1.22631478e+00 6.83150172e-01
9.47718799e-01 -6.10917091e-01 -1.05804431e+00 5.50078630e-01
7.00439870e-01 -5.47822893e-01 -9.02463019e-01 -6.99592903e-02
2.72043675e-01 -8.72271836e-01 7.67639101e-01 -7.31722116e-01
8.59417915e-02 2.65759438e-01 1.82103962e-01 -1.41487432e+00
-2.27536168e-02 -1.05041897e+00 -2.58999377e-01 1.43810737e+00
2.57230759e-01 -3.92385542e-01 1.00578964e+00 1.26867867e+00
8.25188681e-02 -1.18292496e-01 -4.51804847e-01 -4.33022469e-01
7.21987784e-02 3.66384573e-02 2.79562920e-01 1.14137387e+00
1.07567596e+00 1.36919141e+00 -5.88241696e-01 -3.10990602e-01
2.93066770e-01 -1.42848432e-01 1.16295040e+00 -1.59813416e+00
-1.40974239e-01 -3.86366665e-01 3.74372393e-01 -1.69789076e+00
5.58271110e-01 -5.54369450e-01 4.02240038e-01 -1.10567510e+00
5.05581684e-02 -4.50278938e-01 3.44403148e-01 5.41695893e-01
-3.49732310e-01 -1.16598934e-01 -1.76607698e-01 2.61345237e-01
-7.57490396e-01 5.40955842e-01 9.28079784e-01 9.52896252e-02
-7.78884172e-01 3.58996749e-01 -8.92498314e-01 8.56919646e-01
9.00352895e-01 -1.70339689e-01 -5.05719781e-01 1.40177891e-01
-4.14232552e-01 3.42263907e-01 1.07894026e-01 -4.86393571e-01
1.51872382e-01 -2.70516336e-01 -1.28216505e-01 -3.77346575e-01
6.15921021e-01 -7.29923248e-01 -5.43728232e-01 3.46419394e-01
-9.63005483e-01 -3.14004809e-01 -3.35517764e-01 3.52458149e-01
-3.71095836e-02 -4.35950398e-01 1.07304239e+00 -1.45216152e-01
-3.54000211e-01 -1.94010347e-01 -8.76664162e-01 4.11858350e-01
9.56085205e-01 3.53445411e-01 -5.88685274e-01 -8.31144273e-01
-9.76231575e-01 6.32709026e-01 5.12528896e-01 4.56185311e-01
1.90521479e-01 -1.04607856e+00 -3.00878346e-01 8.09455067e-02
1.29728541e-01 -1.19730026e-01 -3.28753948e-01 4.10896599e-01
-1.36536971e-01 2.63932467e-01 -5.33681996e-02 -4.94027317e-01
-1.60899961e+00 3.28062952e-01 2.60053277e-01 -4.80349869e-01
-6.30440414e-01 6.94036245e-01 1.67790860e-01 -7.65809357e-01
7.24399984e-01 -1.20191254e-01 -3.93501848e-01 2.15716854e-01
6.22447014e-01 3.26781958e-01 -1.08806059e-01 -3.15816313e-01
-4.62346748e-02 -5.52865148e-01 -2.74942160e-01 -7.05591917e-01
9.66098785e-01 -2.37310722e-01 3.83359380e-02 4.60132211e-01
9.55836475e-01 1.13824725e-01 -1.25044417e+00 -5.10935187e-01
4.61118788e-01 -3.69740009e-01 -4.35514510e-01 -8.80370855e-01
-2.49110311e-01 6.14347219e-01 1.74561799e-01 7.08381176e-01
6.00540102e-01 2.06861481e-01 8.96645784e-01 8.17640007e-01
-5.39718419e-02 -1.25810802e+00 8.34874153e-01 1.00718200e+00
6.59961581e-01 -1.61550009e+00 -4.19993758e-01 -5.81298470e-01
-1.22675192e+00 8.20160508e-01 1.12971711e+00 4.17803600e-02
4.23852921e-01 3.67888987e-01 5.88861287e-01 -3.91743928e-01
-9.04584050e-01 -1.69741333e-01 -2.49229986e-02 4.37600464e-01
7.42767155e-01 -2.86441538e-02 -2.88097113e-01 8.85373235e-01
-3.78114164e-01 -4.30303067e-01 5.22700667e-01 8.82964551e-01
-7.71555722e-01 -1.43710685e+00 -2.24820182e-01 4.61792618e-01
-1.54549792e-01 1.33841693e-01 -1.23264706e+00 3.13981444e-01
-5.21771014e-01 1.45479250e+00 -1.53893217e-01 -4.82680708e-01
3.85207146e-01 7.64075935e-01 1.16046043e-02 -1.07691431e+00
-1.13622832e+00 1.39594659e-01 7.33127177e-01 -4.72068965e-01
-2.10415304e-01 -6.23767197e-01 -1.24328899e+00 -4.90876228e-01
-5.80337107e-01 5.68122268e-01 7.93545395e-02 1.08658886e+00
1.00145482e-01 2.56466568e-01 7.88385928e-01 -5.66781521e-01
-9.89611208e-01 -1.61186063e+00 -1.08230963e-01 8.68535936e-01
3.12923253e-01 -6.43010378e-01 -3.80416393e-01 -2.10754108e-02] | [12.861246109008789, 7.982020378112793] |
47c19db3-dc47-4d20-af0b-ad3f15ae594d | align-and-attend-multimodal-summarization | 2303.07284 | null | https://arxiv.org/abs/2303.07284v3 | https://arxiv.org/pdf/2303.07284v3.pdf | Align and Attend: Multimodal Summarization with Dual Contrastive Losses | The goal of multimodal summarization is to extract the most important information from different modalities to form output summaries. Unlike the unimodal summarization, the multimodal summarization task explicitly leverages cross-modal information to help generate more reliable and high-quality summaries. However, existing methods fail to leverage the temporal correspondence between different modalities and ignore the intrinsic correlation between different samples. To address this issue, we introduce Align and Attend Multimodal Summarization (A2Summ), a unified multimodal transformer-based model which can effectively align and attend the multimodal input. In addition, we propose two novel contrastive losses to model both inter-sample and intra-sample correlations. Extensive experiments on two standard video summarization datasets (TVSum and SumMe) and two multimodal summarization datasets (Daily Mail and CNN) demonstrate the superiority of A2Summ, achieving state-of-the-art performances on all datasets. Moreover, we collected a large-scale multimodal summarization dataset BLiSS, which contains livestream videos and transcribed texts with annotated summaries. Our code and dataset are publicly available at ~\url{https://boheumd.github.io/A2Summ/}. | ['Zhaowen Wang', 'Abhinav Shrivastava', 'Trung Bui', 'JieLin Qiu', 'Jun Wang', 'Bo He'] | 2023-03-13 | null | http://openaccess.thecvf.com//content/CVPR2023/html/He_Align_and_Attend_Multimodal_Summarization_With_Dual_Contrastive_Losses_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/He_Align_and_Attend_Multimodal_Summarization_With_Dual_Contrastive_Losses_CVPR_2023_paper.pdf | cvpr-2023-1 | ['supervised-video-summarization', 'extractive-document-summarization'] | ['computer-vision', 'natural-language-processing'] | [ 2.68730044e-01 -6.68696389e-02 -2.79700518e-01 -4.21210647e-01
-1.59124935e+00 -6.22290850e-01 8.05540979e-01 3.45001191e-01
-1.16440922e-01 8.52549911e-01 1.16602433e+00 2.42177814e-01
2.57511418e-02 -3.09806913e-01 -6.20668113e-01 -5.58773100e-01
1.86796322e-01 1.65752053e-01 -1.41663194e-01 -1.27802297e-01
3.43402416e-01 -2.70284951e-01 -1.33204472e+00 8.85507643e-01
1.22063565e+00 7.93290854e-01 1.60594553e-01 1.00701320e+00
-1.25362843e-01 9.32113349e-01 -7.36959636e-01 -6.71926737e-01
-2.62786984e-01 -9.46052849e-01 -7.80489683e-01 6.01229928e-02
9.13249373e-01 -6.11451566e-01 -7.55244255e-01 9.23456073e-01
1.03064668e+00 3.58734012e-01 6.55264318e-01 -1.20941997e+00
-7.08368361e-01 9.49655771e-01 -6.68399096e-01 4.37301956e-02
8.98758352e-01 2.25498497e-01 1.14032650e+00 -8.06220233e-01
6.38464630e-01 1.28015506e+00 4.09233958e-01 5.21669388e-01
-1.11740005e+00 -3.83347154e-01 4.81777824e-02 2.07644865e-01
-9.21156645e-01 -8.33525836e-01 7.30400980e-01 -3.46776769e-02
7.06761241e-01 7.08215952e-01 4.49011356e-01 1.50079215e+00
-2.48592608e-02 1.48949301e+00 6.74855769e-01 4.17929096e-03
-2.10214987e-01 -2.09175095e-01 2.90166229e-01 5.68940699e-01
-2.76271552e-02 -6.07567132e-01 -1.11052072e+00 -2.07278654e-01
1.85551196e-01 2.62538791e-02 -5.96468866e-01 2.06763253e-01
-1.80386090e+00 5.69315135e-01 2.04093724e-01 1.54023170e-01
-4.32657987e-01 1.70948163e-01 9.00863051e-01 2.57916570e-01
4.99568701e-01 2.73084104e-01 1.44643605e-01 -4.43495810e-01
-1.23030138e+00 1.96406081e-01 7.49700904e-01 1.10188401e+00
5.62781990e-01 -3.57430540e-02 -9.68495965e-01 1.04048038e+00
9.07941256e-03 7.97990203e-01 4.48636532e-01 -1.38978398e+00
1.02474356e+00 4.82222885e-01 -1.04185402e-01 -1.04195571e+00
-2.07627714e-01 4.33569262e-03 -1.28364658e+00 -7.19241440e-01
-1.11262975e-02 -2.39904508e-01 -5.30324757e-01 1.67208672e+00
-7.87373260e-02 5.89183979e-02 3.08370292e-01 8.44671249e-01
1.81331813e+00 1.03748310e+00 -1.32333785e-01 -3.65793914e-01
1.15202451e+00 -1.24647462e+00 -1.03961408e+00 -6.78977668e-02
3.22977602e-01 -7.84295201e-01 1.01511860e+00 9.58142430e-02
-1.57376957e+00 -3.75360042e-01 -8.71266127e-01 -4.55445528e-01
1.05259210e-01 3.90858531e-01 2.33180240e-01 -1.02221765e-01
-1.10571134e+00 5.86307943e-01 -7.02982008e-01 -5.36996126e-01
4.30555135e-01 -7.60728493e-04 -5.63828707e-01 -1.41861379e-01
-1.03963566e+00 5.27313650e-01 4.22841787e-01 7.56168067e-02
-7.61427283e-01 -5.57705164e-01 -1.06139410e+00 6.92802370e-02
2.10350290e-01 -1.15300906e+00 1.39582694e+00 -8.68638933e-01
-1.41527259e+00 6.25012696e-01 -6.33528590e-01 -2.48990759e-01
5.97298503e-01 -3.82649750e-01 -1.61060691e-01 6.34829402e-01
2.32809231e-01 8.88839304e-01 5.86556435e-01 -1.27416813e+00
-5.35843551e-01 -8.64573196e-02 -1.32618621e-01 5.68681717e-01
-4.76092786e-01 -1.34308398e-01 -6.33964181e-01 -6.40636563e-01
-2.18050808e-01 -4.96027470e-01 1.92125008e-01 -5.96935034e-01
-1.06007552e+00 -1.94699347e-01 6.92114651e-01 -1.06106210e+00
1.49469638e+00 -2.06032920e+00 7.49575019e-01 -4.26678270e-01
3.63948464e-01 9.65922198e-04 -5.00727534e-01 1.07550478e+00
2.85690397e-01 -1.00931443e-01 -4.00517046e-01 -9.86356676e-01
2.93515831e-01 -1.12300448e-01 -4.73285109e-01 2.56325424e-01
1.56076759e-01 1.20768046e+00 -1.04047251e+00 -7.51050174e-01
-6.66412245e-03 3.82895678e-01 -2.36938715e-01 3.67971510e-01
-5.69387898e-02 5.45402586e-01 -3.54308844e-01 6.73347831e-01
4.16180372e-01 -2.66956061e-01 3.66335502e-03 -6.06307209e-01
9.77944359e-02 2.54585654e-01 -6.81249321e-01 2.15086055e+00
-8.96583274e-02 1.04847789e+00 -9.18635502e-02 -8.63080084e-01
5.63475072e-01 4.42536891e-01 3.67335349e-01 -6.99282765e-01
1.88098520e-01 1.10544391e-01 -7.07781315e-01 -6.27021611e-01
1.33405185e+00 2.45312780e-01 -3.80404800e-01 4.64298487e-01
2.31014013e-01 -1.59202501e-01 6.22128725e-01 8.85541260e-01
9.70161915e-01 -3.91573533e-02 1.74334869e-01 1.13365248e-01
3.36364597e-01 -6.94191381e-02 4.06740218e-01 8.46852422e-01
-5.53192645e-02 1.10375226e+00 8.64906549e-01 2.17267245e-01
-8.35045159e-01 -1.05941606e+00 3.61999124e-01 1.04436636e+00
4.01287198e-01 -7.36780524e-01 -5.98563194e-01 -5.95399022e-01
-2.47502849e-01 9.14491355e-01 -4.12316591e-01 -1.83509022e-01
-4.23518747e-01 -6.50062978e-01 6.84031129e-01 4.19662416e-01
6.39442325e-01 -9.14954126e-01 -3.36386025e-01 -8.70569646e-02
-1.25078154e+00 -1.01198649e+00 -9.90442812e-01 -5.06112695e-01
-9.02194798e-01 -9.42139328e-01 -1.11945617e+00 -5.75621068e-01
4.76524979e-01 4.81495649e-01 1.24996555e+00 -1.94189921e-01
1.11807466e-01 9.32232797e-01 -4.01644289e-01 -6.02221750e-02
-3.78015906e-01 3.40826601e-01 -2.06560358e-01 1.59865413e-02
-2.87381932e-02 -5.12430727e-01 -6.62804663e-01 -9.50599983e-02
-9.41464186e-01 5.11535823e-01 4.96253431e-01 8.34040165e-01
4.39540207e-01 -4.47024375e-01 1.01984859e+00 -5.42244077e-01
1.03140342e+00 -6.32048666e-01 2.00515866e-01 3.54852974e-01
7.02501088e-02 -2.09533751e-01 4.18740571e-01 -3.78244132e-01
-1.12516868e+00 -4.69251722e-01 1.55357361e-01 -3.14463288e-01
1.09271705e-01 7.96936512e-01 -1.67551413e-01 7.95720577e-01
1.95960462e-01 6.21800780e-01 -4.93162200e-02 -2.57013291e-01
5.19298196e-01 6.91597939e-01 1.02474427e+00 -3.94852161e-01
4.26231474e-01 3.87779146e-01 -2.77032733e-01 -9.72141206e-01
-9.03961182e-01 -4.45596993e-01 -3.28363776e-01 -4.58403707e-01
8.44692111e-01 -1.20601153e+00 -6.29384816e-01 5.90318978e-01
-1.36443627e+00 -2.67791003e-01 -3.85410488e-01 3.87037873e-01
-6.62143707e-01 8.93908381e-01 -7.07671344e-01 -6.37345195e-01
-8.81993234e-01 -9.10992324e-01 1.37515807e+00 5.36260128e-01
-3.90843779e-01 -9.17327642e-01 1.44087747e-01 6.71821654e-01
2.71866649e-01 4.29294109e-01 5.48680782e-01 -6.57065988e-01
-4.90862876e-01 -2.71439344e-01 -3.74808252e-01 3.53998482e-01
4.24567722e-02 2.17520416e-01 -7.85253763e-01 -3.13359171e-01
-5.00116408e-01 -6.71296418e-01 1.44571328e+00 5.13940752e-01
7.80081689e-01 -5.09312212e-01 -1.22672416e-01 1.99839815e-01
9.05455530e-01 -3.59155715e-01 7.80895650e-01 -9.24863666e-02
8.52534115e-01 6.01452351e-01 5.78114867e-01 5.86350381e-01
8.98626566e-01 3.21240991e-01 2.13846684e-01 1.09009072e-01
-3.84970725e-01 -3.50186467e-01 8.14173579e-01 1.53577578e+00
2.98433639e-02 -7.66333938e-01 -5.57601750e-01 7.13646472e-01
-2.35043502e+00 -1.32279003e+00 -3.22116703e-01 2.00653148e+00
9.71909642e-01 -3.81453037e-01 2.53775179e-01 -3.87941122e-01
7.71143675e-01 5.56162655e-01 -4.71806079e-01 -7.08057806e-02
-6.43674314e-01 -5.33319533e-01 -1.35129765e-02 4.90675449e-01
-1.04325235e+00 6.11351788e-01 5.64784288e+00 9.70666111e-01
-7.95460880e-01 1.34310061e-02 5.02398551e-01 -5.93620718e-01
-6.32955253e-01 -3.30952346e-01 -3.91226202e-01 6.58003211e-01
8.69958401e-01 -4.74238127e-01 2.64358938e-01 1.86535239e-01
2.24108383e-01 -4.25086081e-01 -1.28533864e+00 1.12027085e+00
5.75522661e-01 -1.37956047e+00 3.32694590e-01 -3.65936905e-01
9.86184597e-01 6.26984909e-02 8.10479522e-02 3.73245478e-01
1.76876877e-02 -8.13642859e-01 7.34377444e-01 1.10553050e+00
8.56466293e-01 -7.51202166e-01 7.98394680e-01 2.40185425e-01
-1.10941386e+00 1.76725984e-01 -1.15539260e-01 2.76940495e-01
5.83010435e-01 4.91039544e-01 -3.04916501e-01 1.08140528e+00
5.23591936e-01 1.28495979e+00 -6.43790483e-01 9.20531631e-01
-5.66324666e-02 4.69666898e-01 1.31638572e-02 -7.60924071e-03
1.20223485e-01 -2.84973860e-01 1.04011428e+00 1.60918784e+00
5.08137107e-01 1.04445396e-02 -7.50500336e-02 6.27910733e-01
-5.15772283e-01 -8.58095288e-02 -5.09508967e-01 -4.13948894e-01
5.42608261e-01 1.24224782e+00 -2.60382891e-01 -7.00934470e-01
-3.57197106e-01 1.25263822e+00 1.87872395e-01 6.40333652e-01
-8.08174491e-01 -5.48580408e-01 2.79083312e-01 -3.41784298e-01
1.19183533e-01 -4.42080870e-02 -1.44651324e-01 -1.68300772e+00
6.48957491e-02 -9.91301596e-01 5.21601498e-01 -8.86475921e-01
-1.46498227e+00 3.46833438e-01 1.96394473e-01 -1.25505185e+00
-2.27380276e-01 1.91380814e-01 -9.11281705e-01 6.21295869e-01
-1.33685815e+00 -1.31111741e+00 -6.28304183e-01 4.01111841e-01
8.56117070e-01 -2.58834720e-01 5.16438067e-01 3.38219076e-01
-7.96056867e-01 5.34446836e-01 3.09211701e-01 -8.54654238e-02
1.28093576e+00 -1.23193133e+00 5.91695905e-02 7.31968999e-01
-3.29164833e-01 3.29123855e-01 8.37660670e-01 -6.01394236e-01
-1.64642179e+00 -1.10263252e+00 9.18205023e-01 -5.72398782e-01
5.17279685e-01 4.72971536e-02 -8.85364115e-01 7.63948023e-01
1.10367632e+00 -7.54242182e-01 8.05908561e-01 -1.96572855e-01
-2.13742003e-01 1.69351306e-02 -7.62650669e-01 8.11533391e-01
8.89725387e-01 -5.86577773e-01 -7.93975234e-01 2.66957372e-01
8.42927456e-01 -3.98112327e-01 -8.63924086e-01 4.40762043e-01
5.82388818e-01 -1.05339134e+00 8.31958234e-01 -4.91757274e-01
1.24633741e+00 -4.76597250e-02 -3.57320547e-01 -1.59540570e+00
8.35374445e-02 -8.28236580e-01 -5.66056967e-01 1.74641013e+00
2.26467296e-01 -3.73900890e-01 1.82966158e-01 3.80996317e-01
-3.97798061e-01 -5.18839538e-01 -7.26678371e-01 -3.61574620e-01
-1.50985807e-01 -9.80704874e-02 4.08104837e-01 8.94607127e-01
4.01420683e-01 7.50775635e-01 -7.20449567e-01 -1.75704986e-01
7.41442621e-01 3.74948233e-01 1.05308974e+00 -6.33604705e-01
-3.95796970e-02 -7.26189077e-01 1.81487147e-02 -1.31654775e+00
3.31730068e-01 -9.89494801e-01 4.10951450e-02 -2.22090483e+00
1.02007675e+00 5.12969077e-01 -1.69427488e-02 2.63171345e-01
-5.72570682e-01 2.22301960e-01 4.08388495e-01 2.19171420e-01
-1.45269680e+00 1.16391671e+00 1.30437613e+00 -4.11363304e-01
-1.20205536e-01 -3.06470275e-01 -9.00305867e-01 4.38780397e-01
6.44643724e-01 -9.49351117e-02 -3.25265259e-01 -6.62165403e-01
2.37244770e-01 5.28421462e-01 5.00149369e-01 -6.46677852e-01
4.08679932e-01 6.94219442e-03 1.56590626e-01 -1.26125920e+00
5.17734587e-01 -1.83341965e-01 9.56507213e-03 -3.54925357e-02
-7.20954835e-01 4.40802686e-02 2.12678686e-01 7.02699006e-01
-5.49099684e-01 -4.30950709e-02 2.94868499e-01 1.61023766e-01
-3.81168991e-01 1.34588823e-01 -3.09748769e-01 3.72462511e-01
6.19731367e-01 8.08628127e-02 -9.24681604e-01 -1.01365566e+00
-4.41267580e-01 8.67712677e-01 4.18459743e-01 4.01901752e-01
7.83147156e-01 -1.58240986e+00 -1.28876388e+00 -4.81606424e-01
6.95800334e-02 -2.19966453e-02 9.01793778e-01 1.38405824e+00
-2.05219001e-01 2.51923412e-01 -2.57826801e-02 -6.41443372e-01
-1.43217397e+00 1.06970549e-01 1.59501433e-02 -9.28312019e-02
-6.13450706e-01 6.11433685e-01 2.47979745e-01 -3.99369478e-01
3.33348393e-01 -1.44193411e-01 -2.02919155e-01 6.07494593e-01
7.93211222e-01 8.52361321e-01 -3.65047783e-01 -7.15853095e-01
-6.40456676e-02 2.13115588e-01 4.11086343e-02 -1.84796989e-01
1.25723803e+00 -6.62901998e-01 -3.85348320e-01 7.96031833e-01
1.31425107e+00 5.24800830e-02 -1.12783265e+00 -3.40187967e-01
-3.19931805e-01 -2.81163275e-01 -2.16403544e-01 -6.57732904e-01
-8.73009622e-01 7.50760496e-01 -1.69086754e-01 2.96767622e-01
1.23631608e+00 1.06481619e-01 1.22105515e+00 4.68842685e-01
-2.93069869e-01 -9.92489040e-01 4.59485412e-01 5.15613675e-01
1.35446703e+00 -1.45519745e+00 2.44695082e-01 -3.13543193e-02
-1.29025221e+00 1.07518339e+00 3.53784978e-01 2.07271859e-01
-1.14654399e-01 -2.35627457e-01 -1.93440497e-01 -1.29075944e-01
-9.60461318e-01 4.18883115e-02 5.80046117e-01 2.83025384e-01
4.72171575e-01 3.98381576e-02 -2.56978959e-01 8.62396777e-01
-6.89894259e-02 -1.51601836e-01 7.14264393e-01 7.77979732e-01
-2.93354452e-01 -6.17731094e-01 -2.49132872e-01 6.33024395e-01
-3.01873416e-01 -8.08702558e-02 -7.24181056e-01 4.01141137e-01
-6.54033720e-01 1.17131507e+00 -4.14943732e-02 -3.64955485e-01
4.47693139e-01 -6.36658669e-02 3.98533404e-01 -3.16852331e-01
-4.68104661e-01 1.25584215e-01 4.37468916e-01 -5.29379606e-01
-7.20107973e-01 -8.43403697e-01 -1.07085359e+00 -6.87407613e-01
8.62680674e-02 6.34828806e-02 3.41612965e-01 6.23726368e-01
6.07677281e-01 8.03740621e-01 5.98733246e-01 -1.29557610e+00
-4.34306055e-01 -1.10643101e+00 -3.78075927e-01 4.60218728e-01
5.90892375e-01 -2.90049110e-02 -3.09790105e-01 2.75212556e-01] | [10.671018600463867, 0.6856414675712585] |
d50f574d-49e7-45c7-b78c-e26e39ab364c | analysing-the-effectiveness-of-a-generative | 2211.01886 | null | https://arxiv.org/abs/2211.01886v1 | https://arxiv.org/pdf/2211.01886v1.pdf | Analysing the effectiveness of a generative model for semi-supervised medical image segmentation | Image segmentation is important in medical imaging, providing valuable, quantitative information for clinical decision-making in diagnosis, therapy, and intervention. The state-of-the-art in automated segmentation remains supervised learning, employing discriminative models such as U-Net. However, training these models requires access to large amounts of manually labelled data which is often difficult to obtain in real medical applications. In such settings, semi-supervised learning (SSL) attempts to leverage the abundance of unlabelled data to obtain more robust and reliable models. Recently, generative models have been proposed for semantic segmentation, as they make an attractive choice for SSL. Their ability to capture the joint distribution over input images and output label maps provides a natural way to incorporate information from unlabelled images. This paper analyses whether deep generative models such as the SemanticGAN are truly viable alternatives to tackle challenging medical image segmentation problems. To that end, we thoroughly evaluate the segmentation performance, robustness, and potential subgroup disparities of discriminative and generative segmentation methods when applied to large-scale, publicly available chest X-ray datasets. | ['Ben Glocker', 'Daniel Coelho de Castro', 'Miguel Monteiro', 'Fabio De Sousa Ribeiro', 'Margherita Rosnati'] | 2022-11-03 | null | null | null | null | ['semi-supervised-medical-image-segmentation'] | ['computer-vision'] | [ 6.62123501e-01 3.15715998e-01 -3.64938557e-01 -6.20999813e-01
-1.13700330e+00 -5.13428807e-01 3.02086800e-01 2.18019247e-01
-3.81025165e-01 6.03905678e-01 5.54351173e-02 -2.33007163e-01
7.56983012e-02 -6.79285705e-01 -4.19854254e-01 -9.03422713e-01
3.63969177e-01 9.65664625e-01 1.40939742e-01 1.29867971e-01
-1.04494192e-01 4.16885734e-01 -1.13962996e+00 1.63184956e-01
1.04132843e+00 9.08441424e-01 3.48391712e-01 6.40242815e-01
-1.29892319e-01 7.39583850e-01 -2.81502366e-01 -2.54196107e-01
9.17803869e-03 -8.42442989e-01 -8.83961976e-01 5.20095170e-01
4.12032427e-03 -2.59465277e-01 -1.88113898e-01 1.13593149e+00
6.40860200e-01 6.54857829e-02 8.84385765e-01 -8.43083024e-01
-2.01525077e-01 4.47893411e-01 -4.12519276e-01 1.80414394e-01
-8.05984214e-02 2.23273590e-01 8.17889690e-01 -3.63984287e-01
6.88707650e-01 8.09958100e-01 5.50771475e-01 6.13737047e-01
-1.22860432e+00 -1.57366008e-01 -2.72362798e-01 -8.21407288e-02
-1.10171354e+00 -2.43418708e-01 7.67437100e-01 -5.54415524e-01
4.03920799e-01 4.38312322e-01 5.17292023e-01 9.84987319e-01
1.77058339e-01 1.28995526e+00 1.28994620e+00 -3.73400807e-01
3.06932807e-01 9.72969085e-02 8.44598189e-02 7.54593194e-01
3.84908319e-02 -1.13599911e-01 -1.83628723e-01 -1.68065324e-01
8.89502823e-01 2.78576016e-01 -3.42140436e-01 -3.95911783e-01
-9.94141459e-01 9.68922734e-01 6.26774132e-01 3.93467665e-01
-5.19423842e-01 5.19907521e-03 2.00179458e-01 -2.97153831e-01
7.08045125e-01 5.64858258e-01 -2.19117671e-01 -1.76636100e-01
-1.39948046e+00 -1.93739325e-01 6.41962409e-01 6.56194806e-01
5.65929294e-01 -1.52150199e-01 -2.79084712e-01 9.16153252e-01
3.41492623e-01 2.93462843e-01 6.65549219e-01 -7.44263113e-01
7.75314346e-02 6.84652328e-01 -4.28474307e-01 -6.43956602e-01
-6.55661225e-01 -6.88811243e-01 -1.00883722e+00 -1.94076106e-01
3.38019043e-01 -4.70327772e-03 -1.50572610e+00 1.39884675e+00
3.31520617e-01 -2.71417499e-02 -1.45724982e-01 9.08666551e-01
8.33819211e-01 2.52835423e-01 1.61295891e-01 -1.80571556e-01
1.15856218e+00 -9.34312522e-01 -5.72627306e-01 -3.83408487e-01
6.78796649e-01 -7.80854642e-01 7.38803267e-01 2.27480158e-01
-9.32417750e-01 -3.80940497e-01 -6.75508499e-01 4.12637033e-02
-6.96610287e-02 2.09077150e-01 6.49763942e-01 7.83916831e-01
-9.32718396e-01 5.84863484e-01 -1.39487982e+00 -3.37249249e-01
9.47079659e-01 4.31037217e-01 -8.25802013e-02 -4.41884488e-01
-8.68753493e-01 6.22396827e-01 3.49901170e-01 1.91899449e-01
-8.31001401e-01 -3.70107383e-01 -9.13678765e-01 -6.66467771e-02
5.33868074e-01 -7.56365538e-01 1.37857568e+00 -8.10112119e-01
-1.32402062e+00 1.11360002e+00 -6.83623925e-02 -4.50132489e-01
6.57133400e-01 2.80153006e-02 1.14661016e-01 4.48772132e-01
1.20231599e-01 8.67403507e-01 8.96346331e-01 -1.15473986e+00
-3.16677481e-01 -5.40621758e-01 -4.53117609e-01 7.13587403e-02
6.88097328e-02 -1.98806614e-01 -6.10738635e-01 -7.10545897e-01
4.08268273e-01 -1.20508111e+00 -6.75605118e-01 -2.03134730e-01
-7.18829513e-01 5.19967936e-02 6.32234812e-01 -7.74554968e-01
1.06793070e+00 -1.93924189e+00 1.65084988e-01 3.08968097e-01
5.51643252e-01 3.64164323e-01 3.78802270e-01 -2.03890335e-02
3.29477072e-01 1.04463488e-01 -7.30998099e-01 -3.20875585e-01
-1.29805252e-01 4.72123533e-01 1.85019553e-01 4.87079084e-01
1.87007517e-01 1.31115925e+00 -8.04103613e-01 -7.92557418e-01
3.67180258e-01 5.04085958e-01 -5.49259067e-01 3.60950857e-01
-4.09702957e-01 1.04171181e+00 -6.99220181e-01 7.54316390e-01
2.50460595e-01 -7.61172831e-01 2.96259493e-01 -3.34614329e-02
3.89750719e-01 1.14899412e-01 -6.34687364e-01 1.77984238e+00
-2.22476795e-01 4.33290482e-01 -6.07742257e-02 -1.22203600e+00
6.49415791e-01 2.51121640e-01 8.71223629e-01 -6.07334197e-01
4.68554050e-01 2.55344331e-01 3.03853285e-02 -5.19087195e-01
1.21383354e-01 -4.80480164e-01 -8.42042491e-02 4.87198830e-01
1.12341397e-01 -3.67260098e-01 1.13951966e-01 1.64952725e-01
1.03955948e+00 -1.11841327e-02 2.23141536e-01 -8.06818232e-02
1.44214168e-01 1.37628928e-01 5.20603299e-01 7.52204061e-01
-2.61193246e-01 1.12828791e+00 3.13691080e-01 -1.04303509e-01
-7.73366809e-01 -9.88088131e-01 -3.47209066e-01 6.77100182e-01
1.08955847e-02 -2.89347004e-02 -1.05636203e+00 -1.02042794e+00
-2.28890240e-01 4.09553915e-01 -5.94660997e-01 -2.02880144e-01
-4.57955927e-01 -1.13336051e+00 2.96257973e-01 8.06590676e-01
3.91157866e-01 -1.03887951e+00 -7.65171289e-01 4.80580181e-01
-3.44918728e-01 -1.13898098e+00 -3.55968326e-01 4.02733594e-01
-1.08810389e+00 -1.27099729e+00 -1.03228033e+00 -5.77858210e-01
9.90229130e-01 -6.02939688e-02 1.22731400e+00 1.87123138e-02
-8.19891095e-01 4.84223723e-01 -2.96824306e-01 -2.84451604e-01
-5.52483022e-01 3.12625974e-01 -4.65344697e-01 -1.79586783e-02
1.51576266e-01 -1.59145296e-01 -8.65288436e-01 3.56689662e-01
-1.15357220e+00 1.66052163e-01 7.82807469e-01 1.04015410e+00
1.17185283e+00 -4.05577645e-02 4.35522527e-01 -1.44811392e+00
3.31784904e-01 -5.10942459e-01 -2.33873889e-01 3.22160602e-01
-6.50702357e-01 2.98970863e-02 3.52875531e-01 -8.86470154e-02
-9.54444408e-01 2.41145343e-01 -5.63868284e-01 -3.84143353e-01
-3.92479837e-01 6.78876221e-01 7.40739256e-02 -7.12229684e-02
4.70556289e-01 2.39204615e-01 2.31913492e-01 -5.54373145e-01
3.08652341e-01 6.96077168e-01 6.07116640e-01 -3.87779117e-01
3.11159700e-01 6.45974040e-01 7.94015452e-02 -7.33788729e-01
-1.20832777e+00 -8.24441552e-01 -8.37808490e-01 -7.23997280e-02
1.27601290e+00 -5.38436651e-01 4.38245982e-02 4.02570039e-01
-6.31817222e-01 -4.01588678e-01 -3.82138193e-01 4.71340299e-01
-7.42979825e-01 4.34930831e-01 -6.66534722e-01 -4.75683451e-01
-4.60142195e-01 -1.70571685e+00 1.23829067e+00 3.62988502e-01
-3.73754889e-01 -1.30172575e+00 5.99797852e-02 8.00856888e-01
3.88649493e-01 4.70375419e-01 7.84007490e-01 -9.07336950e-01
-5.28717458e-01 -4.34457719e-01 -1.59814686e-01 5.90788424e-01
3.58008921e-01 -2.13897720e-01 -9.57594931e-01 -2.76294500e-01
7.81274289e-02 -4.66936409e-01 1.04779947e+00 8.05728197e-01
1.40432787e+00 3.53925116e-02 -4.35427845e-01 7.36842394e-01
1.12299693e+00 8.63579139e-02 4.66290563e-01 -1.34043932e-01
9.24847603e-01 4.04392153e-01 4.94646519e-01 2.25407243e-01
3.69714350e-01 4.30973291e-01 2.35506132e-01 -5.98016620e-01
-3.02468479e-01 -1.57211870e-01 -4.49956566e-01 8.72704923e-01
1.34865940e-01 -2.33583719e-01 -1.26468134e+00 3.79766494e-01
-1.79428315e+00 -5.05358338e-01 -2.05290131e-02 1.86474729e+00
9.61656451e-01 1.94687232e-01 1.92077719e-02 1.40122309e-01
6.01804137e-01 -1.47647589e-01 -6.05725944e-01 3.30867380e-01
6.23664185e-02 4.06742066e-01 4.10823107e-01 1.34630069e-01
-1.29078543e+00 7.34459162e-01 6.46868706e+00 8.88291657e-01
-1.35024810e+00 2.80991852e-01 1.20792687e+00 2.04287007e-01
-1.70761079e-01 -2.16525033e-01 -6.23789966e-01 6.24085665e-01
7.37793267e-01 4.62087154e-01 -1.07912116e-01 8.37394476e-01
9.99110043e-02 -4.91895676e-01 -9.91681218e-01 9.79629874e-01
1.81555778e-01 -1.36108172e+00 -1.49976328e-01 1.44614324e-01
1.00867772e+00 1.37693197e-01 2.05213040e-01 7.06526786e-02
1.68245882e-01 -1.15141916e+00 1.57848343e-01 3.92653704e-01
8.27797115e-01 -4.95069146e-01 9.58141506e-01 4.24691290e-01
-6.73801303e-01 3.43189448e-01 -1.18212946e-01 5.86265862e-01
3.14258367e-01 7.43274927e-01 -1.08062160e+00 5.03272474e-01
3.46874475e-01 6.36808455e-01 -6.23730063e-01 1.16552317e+00
-2.18208238e-01 9.57145095e-01 -3.35722148e-01 3.89843822e-01
3.96130770e-01 -2.42517516e-01 2.16090381e-01 1.09857893e+00
3.70803662e-02 1.22907132e-01 5.75176597e-01 7.91854262e-01
-2.64560372e-01 3.60875949e-02 -2.42726520e-01 -2.36618146e-01
-1.20704606e-01 1.21108246e+00 -1.51285315e+00 -4.03444499e-01
-1.41609043e-01 7.81028688e-01 6.83764592e-02 2.08083794e-01
-6.63142264e-01 2.12775365e-01 3.18858214e-02 1.81646556e-01
3.70318927e-02 -1.28157705e-01 -4.10046130e-01 -1.00746775e+00
-3.57785165e-01 -8.01777959e-01 6.20259762e-01 -4.15031761e-01
-1.24441087e+00 5.86523175e-01 -1.48058468e-02 -9.76658940e-01
-4.31667864e-01 -4.39604342e-01 -4.13398355e-01 5.84950030e-01
-1.54476559e+00 -1.18512011e+00 -4.14369881e-01 3.24701190e-01
7.50404119e-01 -3.54840383e-02 6.26569331e-01 2.72762358e-01
-6.62137151e-01 2.83671290e-01 3.13412219e-01 1.88722014e-01
5.84758580e-01 -1.46153283e+00 1.21314041e-01 6.31466329e-01
4.14467752e-01 3.36993277e-01 4.52747017e-01 -6.39013648e-01
-1.11470425e+00 -1.14271617e+00 2.81032681e-01 -3.26471359e-01
1.75237730e-01 -7.52320364e-02 -9.63576913e-01 4.38507497e-01
-3.03275198e-01 3.11894506e-01 1.06835222e+00 -2.17275888e-01
2.10288644e-01 3.24232817e-01 -1.18297207e+00 2.00598896e-01
5.69499314e-01 -5.03080487e-01 -2.16489077e-01 4.43520188e-01
2.63700366e-01 -6.90549791e-01 -8.98305237e-01 6.05580032e-01
2.06741482e-01 -8.35211754e-01 9.22174931e-01 -3.34744513e-01
4.89763767e-01 4.26011123e-02 5.69188595e-02 -1.20659864e+00
7.23125553e-03 -4.66832012e-01 1.11690365e-01 9.16056812e-01
3.94558161e-01 -5.40849864e-01 1.06561446e+00 8.36573660e-01
-2.25503713e-01 -1.15397108e+00 -5.88880837e-01 -3.65083694e-01
-1.72892418e-02 -4.52144712e-01 1.73729628e-01 8.83076370e-01
-3.87674421e-01 8.94082859e-02 1.50920982e-02 -2.36742690e-01
6.87330365e-01 2.49335781e-01 4.61011112e-01 -1.18872976e+00
-5.47396898e-01 -4.99293119e-01 -4.40235287e-01 -9.36391175e-01
1.24182023e-01 -1.17690361e+00 1.59240708e-01 -1.93805015e+00
3.95157933e-01 -7.32250273e-01 -2.30403781e-01 4.61427897e-01
-5.07880151e-01 6.59173012e-01 -2.14099698e-02 4.79890943e-01
-6.89259648e-01 4.58367914e-01 1.58325815e+00 -1.56585619e-01
-7.08154589e-02 4.20901984e-01 -5.79824090e-01 8.56378317e-01
8.65076721e-01 -4.57332402e-01 -5.02899289e-01 -2.04760194e-01
-2.41391987e-01 2.40095645e-01 2.88766026e-01 -8.26536715e-01
1.04144856e-01 1.55276842e-02 4.96714264e-01 -5.41135967e-01
1.01286598e-01 -6.14855230e-01 -5.90789318e-02 3.25379401e-01
-3.48063409e-01 -4.20844078e-01 -3.98688130e-02 5.84586382e-01
-5.99857211e-01 -3.11171144e-01 9.04129744e-01 -4.52066541e-01
-4.53757882e-01 4.33858216e-01 -1.43112451e-01 3.62466931e-01
1.00843072e+00 -1.89383864e-01 -1.19339135e-02 -2.27558479e-01
-1.10077631e+00 1.83208272e-01 3.88950735e-01 4.38553207e-02
5.71096361e-01 -8.32510829e-01 -4.85301256e-01 1.59102499e-01
9.59814340e-03 5.77128828e-01 3.62582833e-01 1.12736857e+00
-6.21816099e-01 5.19437373e-01 3.29351835e-02 -9.97447670e-01
-1.09379101e+00 2.93354094e-01 3.01075697e-01 -6.33217871e-01
-6.19150698e-01 9.07121003e-01 3.54355931e-01 -3.76619637e-01
-1.20562054e-02 -3.42022479e-01 -4.79740426e-02 5.90645559e-02
7.29685575e-02 1.41732857e-01 3.34241569e-01 -5.62325120e-01
-1.90073252e-01 3.44138414e-01 -2.43218601e-01 1.10886835e-01
1.26300764e+00 -7.36172944e-02 6.69614449e-02 2.17146769e-01
1.24098408e+00 -4.94372934e-01 -1.29619634e+00 -3.05818439e-01
6.64541870e-02 -2.83939064e-01 3.87104273e-01 -7.19351649e-01
-1.28763139e+00 1.07877612e+00 4.52861369e-01 1.61058486e-01
1.12639523e+00 3.13515097e-01 9.38220561e-01 -4.67121229e-02
3.10749590e-01 -9.99036074e-01 1.24921806e-01 -2.82052867e-02
3.30121547e-01 -1.69709051e+00 5.74111380e-03 -5.76986969e-01
-7.95635700e-01 8.98020327e-01 3.16060692e-01 1.83479950e-01
6.12976193e-01 1.71417236e-01 2.58422613e-01 -4.32632476e-01
-2.29565576e-01 -4.49847907e-01 6.11865401e-01 4.28069085e-01
5.09220123e-01 2.17885286e-01 -2.21260190e-02 4.76256251e-01
4.58007269e-02 -8.11490864e-02 1.83382198e-01 1.18624735e+00
-2.41575107e-01 -1.24894881e+00 -2.74533242e-01 9.30765927e-01
-7.89157331e-01 5.39086089e-02 -2.36194506e-01 5.04323423e-01
-8.61459747e-02 6.61618829e-01 -2.28064999e-01 9.98833776e-02
-5.05894050e-02 6.63319156e-02 5.64824998e-01 -8.99596035e-01
-4.72577602e-01 4.86178309e-01 -3.30437809e-01 -3.45073730e-01
-5.02065778e-01 -6.79125965e-01 -1.28827798e+00 4.24046636e-01
-3.49423319e-01 -2.14742497e-03 7.20585465e-01 1.10056496e+00
1.45613059e-01 7.69446373e-01 5.44744611e-01 -8.34268212e-01
-5.66618443e-01 -7.44798899e-01 -4.35314387e-01 6.12334490e-01
1.49430141e-01 -5.47034144e-01 -1.17014877e-01 3.12309563e-01] | [14.628130912780762, -2.253631591796875] |
9b83e92c-a2ff-4d1b-9d44-272e343b9029 | forgetting-to-learn-logic-programs | 1911.06643 | null | https://arxiv.org/abs/1911.06643v1 | https://arxiv.org/pdf/1911.06643v1.pdf | Forgetting to learn logic programs | Most program induction approaches require predefined, often hand-engineered, background knowledge (BK). To overcome this limitation, we explore methods to automatically acquire BK through multi-task learning. In this approach, a learner adds learned programs to its BK so that they can be reused to help learn other programs. To improve learning performance, we explore the idea of forgetting, where a learner can additionally remove programs from its BK. We consider forgetting in an inductive logic programming (ILP) setting. We show that forgetting can significantly reduce both the size of the hypothesis space and the sample complexity of an ILP learner. We introduce Forgetgol, a multi-task ILP learner which supports forgetting. We experimentally compare Forgetgol against approaches that either remember or forget everything. Our experimental results show that Forgetgol outperforms the alternative approaches when learning from over 10,000 tasks. | ['Andrew Cropper'] | 2019-11-15 | null | null | null | null | ['program-induction'] | ['computer-code'] | [ 2.13480651e-01 1.35117158e-01 -5.52410424e-01 -2.97002643e-01
-8.59545708e-01 -5.94466865e-01 2.10185140e-01 3.77694368e-01
-5.42535484e-01 1.20260906e+00 -2.54707754e-01 -6.40086949e-01
-3.99894565e-02 -1.04057884e+00 -1.41255510e+00 -3.98439169e-01
-9.58840251e-02 5.06453753e-01 5.52115202e-01 1.90632671e-01
1.86381236e-01 6.02469370e-02 -1.88545251e+00 6.89555407e-01
1.10615790e+00 4.86486018e-01 3.47107142e-01 7.96640754e-01
-4.74496007e-01 1.12043238e+00 -4.64124829e-01 -4.10486221e-01
-2.09738329e-01 -5.89155406e-02 -9.83323753e-01 -5.34516931e-01
5.09931386e-01 -3.55529711e-02 1.64410219e-01 8.56759191e-01
1.10430770e-01 2.89331287e-01 1.99674934e-01 -1.46978021e+00
-4.65875447e-01 1.03568530e+00 -3.15162778e-01 1.92439020e-01
4.70929235e-01 -6.10798709e-02 1.02394271e+00 -1.04549611e+00
4.68419909e-01 1.10018969e+00 9.39012110e-01 5.57617486e-01
-1.68455136e+00 -7.77888775e-01 3.23645741e-01 2.67290741e-01
-1.15594828e+00 -3.12401086e-01 6.67122722e-01 -4.42177624e-01
1.13691127e+00 1.45369753e-01 5.88488936e-01 8.84168208e-01
2.44331405e-01 1.12798774e+00 1.24786472e+00 -8.93354416e-01
2.56109208e-01 5.21573782e-01 6.76534534e-01 1.30771327e+00
4.77081388e-01 -6.18910752e-02 -9.41865206e-01 -4.94471788e-01
1.47123978e-01 -4.50710431e-02 -1.25169545e-01 -6.11666262e-01
-1.04842103e+00 7.88679898e-01 -2.01389939e-01 1.24072425e-01
1.06413893e-01 3.23828161e-01 5.33256650e-01 8.01418602e-01
3.47815573e-01 4.61210489e-01 -9.21622932e-01 8.20172485e-03
-7.44413137e-01 3.75093609e-01 1.19455040e+00 1.11280203e+00
1.28280354e+00 -2.33652636e-01 -3.88365507e-01 6.74648762e-01
8.10064841e-03 3.83431166e-01 3.97268772e-01 -5.73317647e-01
4.28345591e-01 6.97940469e-01 -5.72552942e-02 -4.55732971e-01
-1.00181043e-01 2.33852901e-02 -1.68244123e-01 2.32976928e-01
2.59510159e-01 -1.91687375e-01 -8.57020140e-01 1.73210537e+00
2.29548290e-01 1.86200842e-01 -1.32163435e-01 9.53675155e-03
5.62517524e-01 3.92553866e-01 1.60276383e-01 -3.42399985e-01
1.05189657e+00 -1.15438402e+00 -3.41616452e-01 -4.22516942e-01
8.98379028e-01 -1.84997037e-01 1.59441984e+00 8.14948916e-01
-8.51673961e-01 -5.96908212e-01 -1.00196385e+00 1.49836347e-01
-5.85256398e-01 3.71634811e-02 9.30122852e-01 7.29075372e-01
-8.40813935e-01 5.62204540e-01 -6.45160675e-01 8.79364535e-02
3.72518778e-01 3.12692940e-01 -2.71394253e-01 -3.22885811e-01
-1.11947787e+00 9.79166389e-01 9.53152061e-01 -5.59464514e-01
-1.25423729e+00 -1.02927744e+00 -9.32025015e-01 4.37879711e-02
7.62260973e-01 -6.52954578e-01 1.43260741e+00 -8.97720873e-01
-1.29948843e+00 6.93418622e-01 -3.77516270e-01 -5.15311897e-01
2.83195317e-01 -5.98085821e-01 -4.48154584e-02 -2.97398090e-01
-1.51392907e-01 2.64984399e-01 1.18207741e+00 -1.33634496e+00
-9.40717220e-01 -6.27975315e-02 5.09559929e-01 -2.37877846e-01
-4.32625860e-01 -2.01323926e-01 -3.33584040e-01 -4.42876607e-01
-3.76138628e-01 -9.92469728e-01 -9.21812933e-03 -3.59629154e-01
-1.40098915e-01 -5.05667388e-01 8.08649600e-01 -2.75984138e-01
1.34007430e+00 -2.06958866e+00 1.67378709e-01 1.15741834e-01
3.76116097e-01 1.89483732e-01 -1.10859297e-01 -2.30711158e-02
-4.70040087e-03 1.92324579e-01 -3.26232761e-02 -3.32623333e-01
-1.11052521e-01 6.57057822e-01 -4.68903780e-01 -1.20267533e-01
1.21185131e-01 8.73092234e-01 -9.61849570e-01 -6.25427186e-01
-5.77300191e-02 3.05005517e-02 -9.17215884e-01 1.70345411e-01
-9.03534651e-01 4.56419811e-02 -2.34660372e-01 4.89994764e-01
4.67083514e-01 -2.04955295e-01 2.69406766e-01 2.26313859e-01
9.05685201e-02 5.17320871e-01 -1.20353746e+00 1.52178812e+00
-9.82799709e-01 4.29326206e-01 -2.15319663e-01 -1.08874404e+00
8.16296399e-01 1.28378227e-01 -1.02279708e-01 -1.16682172e-01
-5.11433899e-01 8.44726339e-02 -2.14256674e-01 -4.19729888e-01
1.36617720e-01 -5.01753688e-01 -1.92999840e-01 7.15318501e-01
5.10712445e-01 5.65838963e-02 3.84417981e-01 8.31557736e-02
1.26511049e+00 8.26972798e-02 5.12324035e-01 -2.83526599e-01
6.34150624e-01 6.73788711e-02 7.27797866e-01 1.37878251e+00
2.25959048e-01 -2.52289534e-01 5.65179765e-01 -6.51532531e-01
-5.59077919e-01 -1.06918907e+00 2.72874564e-01 1.96835089e+00
-4.15577680e-01 -6.96269393e-01 -2.53844500e-01 -1.20870709e+00
5.72946429e-01 1.01353192e+00 -7.14313328e-01 -3.53525698e-01
-7.37941086e-01 -5.08714080e-01 5.42623758e-01 6.32923603e-01
3.28204691e-01 -1.12066233e+00 -7.36246943e-01 2.61155933e-01
-4.88793664e-02 -6.34245992e-01 -2.06562474e-01 9.20265436e-01
-1.00844419e+00 -1.22997105e+00 -5.51671945e-02 -8.07047188e-01
7.93287396e-01 5.54445684e-02 1.43362141e+00 1.97287306e-01
-8.80672857e-02 5.71289241e-01 -2.46199876e-01 -7.06521928e-01
-5.90197325e-01 4.32882190e-01 1.36705026e-01 -5.49293756e-01
5.98369420e-01 -5.62020063e-01 4.98737484e-01 -1.81583539e-01
-7.17344165e-01 1.36265635e-01 6.28127098e-01 1.09797370e+00
5.28954029e-01 4.98491108e-01 6.33910418e-01 -1.64559662e+00
6.15664542e-01 -2.80927122e-01 -7.40573406e-01 8.08948815e-01
-9.32870448e-01 7.25001276e-01 6.83978081e-01 -8.59491289e-01
-1.13325989e+00 2.02388391e-01 3.00854534e-01 -4.51127857e-01
-1.20431045e-02 8.94103765e-01 -9.04632807e-02 -4.20358419e-01
7.93358326e-01 4.49441344e-01 -3.27504277e-01 -4.02121425e-01
4.09313560e-01 5.22290617e-02 2.55980849e-01 -1.35607648e+00
7.89557695e-01 -8.29449669e-02 -2.77791739e-01 -4.37081575e-01
-1.30262208e+00 -1.54061571e-01 -7.32601702e-01 -2.87081134e-02
6.19148761e-02 -7.32419491e-01 -8.92951727e-01 1.25992253e-01
-1.08994353e+00 -9.32581127e-01 -3.05538476e-01 1.58507705e-01
-5.31400025e-01 -3.55954431e-02 -4.25123096e-01 -8.46597552e-01
-2.32478723e-01 -9.14479375e-01 5.95515370e-01 -1.01721458e-01
-2.87791491e-01 -1.24697053e+00 3.22482824e-01 2.15601008e-02
2.74751753e-01 -5.66812977e-02 1.60958087e+00 -8.36190522e-01
-5.42295992e-01 -3.35073075e-03 9.86678749e-02 4.60349739e-01
6.32694140e-02 -3.02764475e-01 -9.77709949e-01 -2.47648135e-01
9.76494849e-02 -7.00864792e-01 1.19989252e+00 -7.70805404e-02
1.40746355e+00 -6.05338991e-01 -5.58423400e-01 3.81210357e-01
1.48983192e+00 1.49042666e-01 3.92150879e-01 5.38686752e-01
6.92343652e-01 2.49891356e-01 6.34751916e-01 3.57087493e-01
3.16498548e-01 2.33095631e-01 -3.06929022e-01 4.61500019e-01
8.62492714e-03 -5.42752802e-01 5.29455006e-01 6.21075511e-01
8.72164592e-02 2.90367544e-01 -1.29733992e+00 5.12146413e-01
-1.72930253e+00 -6.55094624e-01 3.60400498e-01 2.31079745e+00
1.61438882e+00 6.07063174e-01 3.95071022e-02 2.79280156e-01
3.53245884e-01 -1.76751792e-01 -5.69331944e-01 -4.17929918e-01
1.62200719e-01 7.05097675e-01 4.79251921e-01 7.26184845e-01
-1.13502526e+00 1.01016581e+00 7.15304852e+00 5.66720903e-01
-9.66480672e-01 3.86759520e-01 1.76617429e-01 -1.65229384e-02
-4.34617698e-01 1.86060637e-01 -1.26598144e+00 3.16930473e-01
9.74750936e-01 -5.99919319e-01 6.60360634e-01 1.36779678e+00
-6.18365467e-01 -4.35972750e-01 -1.53729594e+00 6.76090181e-01
2.85857052e-01 -1.23274279e+00 2.03754708e-01 -4.70744848e-01
6.93997562e-01 -1.64362803e-01 -5.67607917e-02 1.18881488e+00
7.36122072e-01 -7.96314657e-01 5.36728740e-01 6.68089271e-01
6.29461944e-01 -8.31360102e-01 5.02921879e-01 6.00413918e-01
-1.08414340e+00 -2.59137183e-01 -1.20180301e-01 -3.06256145e-01
-4.02947992e-01 9.10237789e-01 -1.10354555e+00 2.86309868e-01
6.43840492e-01 3.63693744e-01 -9.21084404e-01 8.85928035e-01
-5.43712914e-01 8.10164094e-01 -1.37221918e-01 -1.57579735e-01
-3.80674750e-01 3.03926110e-01 2.09638134e-01 1.26142979e+00
9.58502814e-02 2.59456169e-02 6.26911342e-01 8.13084304e-01
-1.23389296e-01 -1.66480213e-01 -9.34575140e-01 -2.14378107e-02
4.40707713e-01 8.97595227e-01 -3.73920083e-01 -6.90771461e-01
-5.31425774e-01 7.16087878e-01 7.29760885e-01 2.65610367e-01
-7.76408076e-01 -4.86849517e-01 3.20616931e-01 -3.40079106e-02
3.89965266e-01 -1.82938829e-01 -3.09050024e-01 -1.10569739e+00
1.48596853e-01 -1.01009166e+00 6.24058247e-01 -4.61767673e-01
-1.16958785e+00 1.03921704e-01 2.46138021e-01 -3.71370256e-01
2.39052884e-02 -7.45607376e-01 -5.31486511e-01 5.89135468e-01
-1.48392045e+00 -9.74119782e-01 -2.64081329e-01 5.01619518e-01
5.08161068e-01 -1.78973287e-01 9.01380122e-01 1.32690415e-01
-3.82350683e-01 7.98947811e-01 -2.82661080e-01 -1.70651585e-01
8.11086535e-01 -1.52784598e+00 -6.58495426e-02 5.96562505e-01
6.83173612e-02 9.66314137e-01 6.32386446e-01 -8.22960138e-01
-1.85361195e+00 -1.34345317e+00 9.08319354e-01 -7.67360389e-01
6.96993053e-01 -4.52368170e-01 -1.08183229e+00 1.24290919e+00
-2.02438265e-01 5.15911467e-02 8.66616130e-01 8.79837632e-01
-8.28819811e-01 -3.61343414e-01 -9.42714632e-01 4.09396768e-01
8.30586731e-01 -7.13846147e-01 -1.11321330e+00 3.01100850e-01
8.91731024e-01 -3.36547285e-01 -6.61882877e-01 3.85160893e-01
4.67480451e-01 -5.82564652e-01 7.29228199e-01 -7.50589669e-01
1.78059191e-01 -2.04742387e-01 1.41435236e-01 -1.35464621e+00
-1.42379776e-01 -4.33894992e-01 -8.39139760e-01 1.00598252e+00
4.90686268e-01 -7.15891778e-01 7.59260297e-01 6.29509211e-01
6.24639876e-02 -5.93313515e-01 -6.01805806e-01 -1.06805217e+00
2.28708133e-01 -6.61487460e-01 3.61163855e-01 8.66346359e-01
3.99194151e-01 6.62271261e-01 -3.12419176e-01 -4.88912724e-02
6.18426859e-01 3.06715757e-01 9.11901414e-01 -1.58176112e+00
-6.78196609e-01 -3.65436636e-02 2.19122157e-01 -6.69082046e-01
7.16038704e-01 -1.19328344e+00 2.30852976e-01 -9.38305497e-01
5.12361407e-01 -7.72680104e-01 -4.98644024e-01 1.21979773e+00
-4.66337979e-01 -4.52646971e-01 -2.74534281e-02 -1.89762175e-01
-9.50488091e-01 1.98043883e-01 8.66041780e-01 -2.95207620e-01
-4.00782555e-01 1.46368191e-01 -7.73351133e-01 8.40059757e-01
7.86367297e-01 -8.53099048e-01 -5.57363570e-01 -2.42890269e-01
5.13758421e-01 -1.47736236e-01 3.23942423e-01 -1.16573787e+00
4.84176219e-01 -1.90583915e-01 2.67440766e-01 -5.20419419e-01
-1.39734715e-01 -6.07256949e-01 1.02320977e-01 6.10384941e-01
-5.87093353e-01 -7.39024654e-02 6.22143745e-01 6.17525697e-01
-1.35944951e-02 -6.81768835e-01 6.45745337e-01 -3.98263872e-01
-7.04280376e-01 -4.18441594e-02 -3.31270635e-01 7.74335042e-02
1.09130120e+00 3.11205208e-01 -2.84793526e-01 2.11822376e-01
-7.78421521e-01 3.10670942e-01 2.79654264e-01 2.34669447e-01
7.11849570e-01 -1.08801627e+00 -2.09497571e-01 4.14227247e-01
3.76667827e-01 5.97778782e-02 -2.90189266e-01 7.34289885e-01
-1.09589182e-01 5.96578419e-01 -9.09384787e-02 -3.08548391e-01
-1.58302951e+00 1.04430175e+00 -5.26563637e-02 -5.77924073e-01
-5.93541920e-01 8.64489734e-01 -1.11665793e-01 -7.93096185e-01
5.11731863e-01 -6.06333673e-01 1.32446736e-01 -7.19436165e-03
8.04999590e-01 1.66708872e-01 1.85592309e-01 5.91404617e-01
-3.24361205e-01 -1.15581276e-02 -5.11683345e-01 -4.58560996e-02
1.33539867e+00 4.09855336e-01 -4.51002896e-01 1.06934786e+00
7.31854975e-01 8.93758312e-02 -9.12133098e-01 -5.40789723e-01
7.56102502e-01 -5.06028056e-01 -1.54567897e-01 -9.19113934e-01
-5.23687243e-01 6.49812102e-01 2.60993361e-01 -1.02117591e-01
1.06953597e+00 -2.49599665e-03 3.83409053e-01 1.28409743e+00
1.00690019e+00 -1.02780855e+00 3.01535100e-01 8.82685661e-01
5.72653234e-01 -1.16063225e+00 8.55288506e-02 -2.52905637e-01
-3.71363670e-01 1.10421133e+00 9.43961024e-01 1.03521466e-01
6.75898731e-01 5.99961400e-01 -5.19761205e-01 5.21155484e-02
-1.37179160e+00 -6.53866455e-02 -5.74943284e-03 5.52130163e-01
4.29670006e-01 -9.04721618e-02 -1.84363816e-02 8.08869004e-01
1.31524475e-02 5.37420213e-01 3.35057110e-01 1.40017712e+00
-7.24826634e-01 -1.33309126e+00 -2.43504792e-01 7.37806618e-01
-1.21897466e-01 -3.62493753e-01 -1.63086504e-01 6.56685889e-01
4.24093723e-01 4.09619689e-01 -3.35952401e-01 -3.63145262e-01
2.22175926e-01 9.13614213e-01 8.34881544e-01 -1.11113834e+00
-4.36211795e-01 -5.71387589e-01 2.24864975e-01 -2.57040173e-01
-3.03690106e-01 -3.94696653e-01 -9.52631056e-01 -1.98981166e-01
-3.83536220e-01 3.67129773e-01 1.90872580e-01 9.58152473e-01
9.55819562e-02 5.32140672e-01 2.26992831e-01 -2.37808868e-01
-4.90214646e-01 -8.53230953e-01 -3.67703974e-01 -1.29436791e-01
4.76469129e-01 -1.01708221e+00 -3.19219679e-01 3.52598727e-01] | [8.635811805725098, 7.230319499969482] |
01fa2f33-82d4-40be-9872-0bfdaf122814 | cogview-mastering-text-to-image-generation | 2105.13290 | null | https://arxiv.org/abs/2105.13290v3 | https://arxiv.org/pdf/2105.13290v3.pdf | CogView: Mastering Text-to-Image Generation via Transformers | Text-to-Image generation in the general domain has long been an open problem, which requires both a powerful generative model and cross-modal understanding. We propose CogView, a 4-billion-parameter Transformer with VQ-VAE tokenizer to advance this problem. We also demonstrate the finetuning strategies for various downstream tasks, e.g. style learning, super-resolution, text-image ranking and fashion design, and methods to stabilize pretraining, e.g. eliminating NaN losses. CogView achieves the state-of-the-art FID on the blurred MS COCO dataset, outperforming previous GAN-based models and a recent similar work DALL-E. | ['Jie Tang', 'Hongxia Yang', 'Zhou Shao', 'Xu Zou', 'Junyang Lin', 'Da Yin', 'Chang Zhou', 'Wendi Zheng', 'Wenyi Hong', 'Zhuoyi Yang', 'Ming Ding'] | 2021-05-26 | null | http://proceedings.neurips.cc/paper/2021/hash/a4d92e2cd541fca87e4620aba658316d-Abstract.html | http://proceedings.neurips.cc/paper/2021/file/a4d92e2cd541fca87e4620aba658316d-Paper.pdf | neurips-2021-12 | ['zero-shot-text-to-image-generation'] | ['natural-language-processing'] | [ 2.24577412e-01 1.44596204e-01 -1.56507418e-01 -5.32329142e-01
-1.20695674e+00 -6.52248979e-01 7.03150630e-01 -8.83752823e-01
-1.50615692e-01 9.68070626e-01 6.12039983e-01 -1.86956033e-01
1.47948056e-01 -5.81866026e-01 -9.66987967e-01 -5.64987838e-01
5.58729053e-01 8.37502420e-01 -3.05901468e-01 -2.91352332e-01
-6.82161003e-02 -2.47848593e-02 -9.46614385e-01 4.67391759e-01
9.02828038e-01 1.08377600e+00 4.13825542e-01 7.00946569e-01
-1.51467368e-01 7.39390433e-01 -7.06840694e-01 -9.05902207e-01
1.32158518e-01 -6.38702214e-01 -6.25746787e-01 1.75280303e-01
8.24592829e-01 -3.62862438e-01 -4.24416840e-01 8.78329694e-01
8.08704734e-01 9.26370174e-02 7.55817711e-01 -1.08912623e+00
-1.46155453e+00 1.05235028e+00 -7.80560851e-01 9.65057015e-02
-2.36447647e-01 3.88141066e-01 1.28122985e+00 -9.39991057e-01
7.38935292e-01 1.65605342e+00 3.80817205e-01 1.01149058e+00
-1.55503702e+00 -8.94871354e-01 1.98359907e-01 -2.77627744e-02
-9.47941780e-01 -4.99561936e-01 6.15371048e-01 -2.77876168e-01
8.14229608e-01 4.21705320e-02 4.43685859e-01 1.89218080e+00
1.82263821e-01 1.04328907e+00 1.31070662e+00 -3.20792824e-01
-1.65885054e-02 -5.66253066e-03 -3.48090440e-01 6.68558836e-01
-2.84374822e-02 1.47607878e-01 -8.27026129e-01 2.56000340e-01
1.27152956e+00 -3.96102935e-01 3.79601195e-02 5.54727800e-02
-9.23340261e-01 1.03394699e+00 3.35961699e-01 -5.19401804e-02
-1.37641236e-01 7.06576407e-01 3.87939721e-01 4.31312084e-01
7.94178009e-01 7.91079283e-01 -6.47874773e-01 -2.03304574e-01
-1.05069804e+00 4.75257427e-01 3.88039082e-01 1.45704150e+00
2.67950833e-01 6.15027189e-01 -6.03653014e-01 1.08698916e+00
9.47102904e-02 5.71024239e-01 3.42941433e-01 -1.01054525e+00
7.13544726e-01 -5.52496593e-03 -2.02223763e-01 -3.83648984e-02
1.12494588e-01 -7.70236969e-01 -1.10799825e+00 3.09835561e-02
2.29790956e-01 -5.02174377e-01 -1.40878403e+00 2.16999626e+00
-2.51103610e-01 1.03675358e-01 -1.48523211e-01 8.06869924e-01
7.84681022e-01 6.68720007e-01 1.24990799e-01 2.34441876e-01
1.44769740e+00 -1.32946432e+00 -6.73902929e-01 -5.37570834e-01
1.01928443e-01 -8.70091021e-01 1.44914711e+00 4.98535424e-01
-1.35597360e+00 -6.28789604e-01 -6.89658165e-01 -4.30494994e-01
-4.63564172e-02 4.15126979e-01 8.81845355e-01 5.09326279e-01
-1.13162363e+00 4.08137053e-01 -5.59138536e-01 -2.78354257e-01
9.66062069e-01 -5.08008488e-02 -1.50339350e-01 -1.34002015e-01
-1.09150505e+00 7.34049797e-01 1.73974976e-01 -2.14643538e-01
-1.31503344e+00 -9.81379926e-01 -5.92606723e-01 2.09835917e-01
4.43204731e-01 -1.46409500e+00 1.43927062e+00 -1.06364512e+00
-1.91335952e+00 8.01883817e-01 -8.31427723e-02 -6.20718181e-01
5.62563956e-01 -7.37900734e-01 -3.29248369e-01 -2.71378279e-01
2.71203667e-01 1.06212771e+00 1.27785039e+00 -1.14387572e+00
-5.78736961e-01 -1.91761687e-01 -9.58034918e-02 2.89725155e-01
-9.95507762e-02 -7.60427192e-02 -6.25907600e-01 -1.38524461e+00
-5.81578553e-01 -9.28147793e-01 -2.16056257e-01 -2.21189231e-01
-7.14256108e-01 -2.59512186e-01 6.57715261e-01 -8.50267768e-01
8.98082435e-01 -1.99863064e+00 4.47426826e-01 -2.33828768e-01
1.86193407e-01 5.85078038e-02 -5.22659004e-01 1.53348237e-01
-8.88397545e-02 2.35745400e-01 2.07577586e-01 -7.17210352e-01
1.31498948e-01 1.05432987e-01 -5.81933081e-01 -7.03546554e-02
4.68012393e-01 1.27826560e+00 -6.27582729e-01 -4.58296418e-01
6.52920753e-02 3.58753890e-01 -9.73648071e-01 4.46290314e-01
-7.59688020e-01 5.79980314e-01 -3.76606911e-01 5.15571415e-01
4.05678749e-01 -5.96066654e-01 1.64339307e-03 -1.88274726e-01
1.85639948e-01 2.50726104e-01 -5.26292920e-01 2.29055858e+00
-7.86064208e-01 7.89843380e-01 1.35132670e-01 -6.39294267e-01
6.81430340e-01 1.24767102e-01 -4.40496355e-02 -7.90330172e-01
1.12623446e-01 -4.96958233e-02 -3.44469875e-01 -1.49878547e-01
7.74285138e-01 -1.84786692e-01 -2.87290961e-01 2.32377887e-01
5.30882359e-01 -2.16256469e-01 6.33344725e-02 5.30007958e-01
7.60384619e-01 5.09833395e-01 -2.11067498e-01 -3.93347561e-01
-3.98466825e-01 -8.22320133e-02 4.66889560e-01 9.62583959e-01
4.59356636e-01 8.24119925e-01 4.93064880e-01 5.09773642e-02
-1.48675478e+00 -1.26366842e+00 6.07550181e-02 1.38294017e+00
-2.54735529e-01 -4.00267601e-01 -9.49743927e-01 -6.41724408e-01
-6.68749139e-02 1.08406425e+00 -6.08257949e-01 -4.49780747e-02
-5.58658421e-01 -7.52694190e-01 6.75739288e-01 7.67992258e-01
6.10780239e-01 -9.11953092e-01 1.83252171e-02 2.46874541e-01
-3.28724355e-01 -1.01125276e+00 -1.00738680e+00 3.09450150e-01
-8.28317344e-01 -3.83799762e-01 -8.61016393e-01 -7.85412073e-01
3.70824248e-01 -8.71019810e-02 1.75898862e+00 -5.10986626e-01
-1.60170645e-01 1.13427900e-01 -2.81160980e-01 -4.07565773e-01
-4.62909997e-01 3.75304729e-01 -2.49024034e-01 -3.66520792e-01
-9.46329162e-02 -6.10316396e-01 -7.14500725e-01 1.38750955e-01
-7.38368034e-01 5.30433714e-01 9.99071598e-01 1.47951078e+00
6.96908176e-01 -2.42949516e-01 7.99764216e-01 -1.25626349e+00
7.29444742e-01 -2.93513179e-01 -6.23158693e-01 3.51436377e-01
-6.57350063e-01 3.58194888e-01 7.32448578e-01 -4.90548104e-01
-1.64380014e+00 -2.27926433e-01 -2.67511189e-01 -7.06241667e-01
-3.99566330e-02 2.20605627e-01 -4.59651649e-01 4.02898699e-01
6.28171980e-01 2.05116943e-01 -2.08823889e-01 -7.28031576e-01
1.16327512e+00 3.79672647e-01 8.79306197e-01 -8.33176315e-01
8.44879448e-01 9.18179378e-02 -2.17248499e-01 -5.06210208e-01
-1.22286689e+00 9.66971368e-02 -1.35304421e-01 2.81044304e-01
9.79660332e-01 -1.44127941e+00 -3.98480445e-01 5.42542577e-01
-1.18442094e+00 -7.52875924e-01 -5.82674801e-01 -4.98392284e-02
-8.05033863e-01 -1.49367094e-01 -9.85418558e-01 -3.92662138e-01
-8.12772036e-01 -9.54574287e-01 1.20841038e+00 3.21445078e-01
-7.08350539e-02 -8.43726337e-01 -1.01758517e-01 6.85925841e-01
6.00796938e-01 -7.02156723e-02 9.71598089e-01 -1.25687838e-01
-8.56826961e-01 5.07327795e-01 -4.15181875e-01 5.78532994e-01
-1.13812588e-01 -3.35676223e-01 -1.00008416e+00 -3.37523073e-01
-3.78527015e-01 -7.03833699e-01 1.26455903e+00 6.75187588e-01
1.54952431e+00 -3.56168509e-01 -1.99712679e-01 1.17443895e+00
1.18911183e+00 -3.67776826e-02 8.68475139e-01 3.32249030e-02
9.19818103e-01 1.13060169e-01 4.58218306e-01 3.41869533e-01
2.46898085e-01 6.01177037e-01 1.64408281e-01 -4.90146607e-01
-7.33582973e-01 -7.38163412e-01 2.88894922e-01 7.04389334e-01
4.27827276e-02 -6.64196670e-01 -1.57621369e-01 5.07079184e-01
-1.78686333e+00 -1.06446433e+00 2.02348828e-01 1.48054731e+00
1.11168766e+00 1.35353684e-01 8.94738808e-02 -7.44730413e-01
5.69006205e-01 2.63841808e-01 -8.07340384e-01 -2.78864443e-01
-5.04709899e-01 5.86193562e-01 6.13739312e-01 2.23109692e-01
-1.14172912e+00 1.53040159e+00 7.03978682e+00 1.47054279e+00
-8.62359345e-01 4.18207198e-01 1.21489894e+00 -3.37368488e-01
-5.98286390e-01 -1.39593378e-01 -9.47383165e-01 5.09020865e-01
7.36524463e-01 7.73781165e-02 9.74075198e-01 9.77308571e-01
8.74329060e-02 2.42126361e-01 -1.04416156e+00 1.04335213e+00
1.13130473e-01 -1.60714102e+00 2.81226307e-01 -6.43698201e-02
1.07999146e+00 1.57675579e-01 4.47729319e-01 5.10791302e-01
1.09338319e+00 -1.23873794e+00 9.97975886e-01 4.35123265e-01
1.55812621e+00 -5.57171524e-01 1.31543860e-01 -1.92834347e-01
-8.83122146e-01 1.15727514e-01 -3.69963259e-01 4.90895927e-01
3.69829595e-01 7.45934665e-01 -5.77519178e-01 3.81614029e-01
7.03453898e-01 6.65806174e-01 -4.96042937e-01 6.28102839e-01
-4.07706946e-01 1.07041609e+00 -7.28362650e-02 2.02589080e-01
1.15285508e-01 -1.67960957e-01 5.09731889e-01 1.26210713e+00
4.86128896e-01 -9.29013416e-02 -1.27261028e-01 1.39160717e+00
-5.74246287e-01 -3.49103570e-01 -3.11419755e-01 -2.65325934e-01
3.65430385e-01 1.26266527e+00 -2.37264216e-01 -3.05265814e-01
-3.64225775e-01 1.37880266e+00 3.82945329e-01 6.12451613e-01
-1.02703846e+00 -2.85812229e-01 8.32348943e-01 -5.14882675e-04
6.66240275e-01 -5.38370982e-02 -5.20540476e-01 -1.47544873e+00
-2.58193552e-01 -1.17344701e+00 3.14038008e-01 -1.05014014e+00
-1.73065031e+00 6.41588449e-01 -9.29376483e-02 -7.21492887e-01
-3.65741879e-01 -5.08585930e-01 -5.78496575e-01 1.04556704e+00
-1.39468563e+00 -1.76037812e+00 1.80774536e-02 7.49090731e-01
9.98415470e-01 -5.04308820e-01 5.41566014e-01 3.46202224e-01
-4.54938143e-01 9.70366538e-01 2.40820378e-01 1.08674191e-01
1.00937545e+00 -1.53832030e+00 9.84794974e-01 8.47523570e-01
2.63309777e-01 3.71987313e-01 6.52549565e-01 -6.95703030e-01
-1.38956296e+00 -1.32607639e+00 3.55393350e-01 -5.63676119e-01
7.13559031e-01 -8.74101758e-01 -3.50625992e-01 1.08541024e+00
6.96505189e-01 -3.48559499e-01 3.73242527e-01 4.96024936e-01
-6.44867957e-01 -2.19982237e-01 -8.43863189e-01 7.41834581e-01
1.52737951e+00 -5.59409201e-01 -2.77765960e-01 2.12267533e-01
1.11289954e+00 -5.26265681e-01 -6.54983997e-01 -2.19750367e-02
4.05574620e-01 -4.77291852e-01 9.89486575e-01 -8.86767209e-01
9.85579014e-01 1.75691336e-01 -4.80006076e-02 -1.88489914e+00
-8.31708968e-01 -1.02997732e+00 3.12970169e-02 1.73686326e+00
5.45720041e-01 -2.80973643e-01 9.14077461e-01 1.41779914e-01
-4.37077731e-01 -5.95768392e-01 -7.24789083e-01 -6.79477572e-01
3.49400342e-01 -2.67677784e-01 6.42745376e-01 6.81663752e-01
-5.91884851e-01 1.13392174e+00 -1.08053696e+00 -4.37207878e-01
7.19398677e-01 1.20316826e-01 7.67485738e-01 -8.88792217e-01
-7.92456865e-01 -5.28149247e-01 2.65679747e-01 -1.51365089e+00
1.79932013e-01 -9.25992250e-01 -6.22367933e-02 -1.47899055e+00
4.34186459e-01 -5.17258584e-01 -3.19157913e-02 3.62612098e-01
-3.18286568e-01 1.67540550e-01 2.69398719e-01 -1.12663537e-01
-6.64332628e-01 8.23465049e-01 1.72664523e+00 -2.91542590e-01
1.76743612e-01 -2.55077451e-01 -1.21578336e+00 2.85491675e-01
6.51670992e-01 -3.12835604e-01 -6.34745836e-01 -9.59092677e-01
2.97177672e-01 2.28627950e-01 4.01362598e-01 -5.29402435e-01
-2.31233820e-01 -2.37764508e-01 5.94856858e-01 -5.43962717e-01
4.81050193e-01 -4.04615909e-01 1.87187925e-01 -5.88370934e-02
-6.88963294e-01 2.27422103e-01 1.96815088e-01 6.52202189e-01
7.03175291e-02 1.30700558e-01 8.40789497e-01 -2.96638459e-01
-6.00872874e-01 4.22074318e-01 -1.32110089e-01 5.81262767e-01
4.10419017e-01 3.19185287e-01 -8.57010007e-01 -7.46785462e-01
-5.89277148e-01 2.52564728e-01 3.12083900e-01 5.88660181e-01
5.52318335e-01 -1.57519484e+00 -1.11896992e+00 -1.34412646e-02
-9.14736837e-02 1.20788641e-01 2.81144321e-01 2.70704806e-01
-5.82946613e-02 3.39500695e-01 -2.13857368e-01 -3.15679282e-01
-9.92461085e-01 3.95400316e-01 1.60354003e-01 -6.18564188e-01
-5.81362665e-01 1.20946658e+00 7.30018258e-01 -2.87451874e-02
-1.07389688e-03 -1.14728011e-01 2.28459463e-01 -1.76918611e-01
2.57082909e-01 6.62866458e-02 -2.63379186e-01 -9.95615795e-02
1.35760561e-01 2.97252089e-01 -3.24269891e-01 -2.78678805e-01
1.43747473e+00 -2.50104100e-01 9.01164636e-02 1.07099190e-01
8.20617139e-01 -1.64657161e-01 -1.52644861e+00 -3.10590357e-01
-3.89701664e-01 -4.84944016e-01 1.50422707e-01 -1.33517683e+00
-1.38916314e+00 8.23316336e-01 4.86278355e-01 -2.23857194e-01
1.21571553e+00 3.56796324e-01 1.04354298e+00 2.89893392e-02
3.13584775e-01 -1.19215906e+00 6.00404441e-01 5.03157377e-01
1.11597085e+00 -1.08658803e+00 -1.33442968e-01 -2.81520456e-01
-1.10780227e+00 6.35633409e-01 8.06259394e-01 -1.15593836e-01
2.91413605e-01 4.24726188e-01 -1.04844920e-01 -7.25765750e-02
-1.16542566e+00 -8.58533531e-02 4.14446235e-01 5.87807894e-01
5.40037453e-01 2.93363422e-01 6.12213612e-02 8.36503029e-01
-4.44305390e-01 3.40637639e-02 2.55912066e-01 2.76487559e-01
5.55338003e-02 -1.20350897e+00 -1.13505520e-01 7.60290384e-01
-6.97325051e-01 -6.25878930e-01 -1.89166948e-01 5.44337988e-01
-6.34995401e-02 7.65757680e-01 2.03618482e-01 -3.00705880e-01
1.62445381e-01 3.32551561e-02 7.23252118e-01 -6.21855795e-01
-6.05309963e-01 5.92991710e-01 4.45815027e-01 -3.59173119e-01
-3.70530151e-02 -5.35194695e-01 -6.09865308e-01 -5.57226837e-01
-4.59360480e-01 -1.49296373e-01 4.37671483e-01 5.97292066e-01
6.90343440e-01 7.89792955e-01 3.81641120e-01 -5.51405013e-01
-6.58029675e-01 -1.16150129e+00 -6.70180857e-01 5.53878367e-01
1.22861899e-01 -3.78162175e-01 6.73990548e-02 2.55759329e-01] | [11.44284439086914, -0.24534466862678528] |
e7dd430d-e3ea-48b7-807d-d6b491e07908 | saaformer-spectral-spatial-axial-aggregation | 2306.16759 | null | https://arxiv.org/abs/2306.16759v2 | https://arxiv.org/pdf/2306.16759v2.pdf | SaaFormer: Spectral-spatial Axial Aggregation Transformer for Hyperspectral Image Classification | Hyperspectral images (HSI) captured from earth observing satellites and aircraft is becoming increasingly important for applications in agriculture, environmental monitoring, mining, etc. Due to the limited available hyperspectral datasets, the pixel-wise random sampling is the most commonly used training-test dataset partition approach, which has significant overlap between samples in training and test datasets. Furthermore, our experimental observations indicates that regions with larger overlap often exhibit higher classification accuracy. Consequently, the pixel-wise random sampling approach poses a risk of data leakage. Thus, we propose a block-wise sampling method to minimize the potential for data leakage. Our experimental findings also confirm the presence of data leakage in models such as 2DCNN. Further, We propose a spectral-spatial axial aggregation transformer model, namely SaaFormer, to address the challenges associated with hyperspectral image classifier that considers HSI as long sequential three-dimensional images. The model comprises two primary components: axial aggregation attention and multi-level spectral-spatial extraction. The axial aggregation attention mechanism effectively exploits the continuity and correlation among spectral bands at each pixel position in hyperspectral images, while aggregating spatial dimension features. This enables SaaFormer to maintain high precision even under block-wise sampling. The multi-level spectral-spatial extraction structure is designed to capture the sensitivity of different material components to specific spectral bands, allowing the model to focus on a broader range of spectral details. The results on six publicly available datasets demonstrate that our model exhibits comparable performance when using random sampling, while significantly outperforming other methods when employing block-wise sampling partition. | ['Dazhi Zhang', 'Yao Li', 'Zhichang Guo', 'Enzhe Zhao'] | 2023-06-29 | null | null | null | null | ['hyperspectral-image-classification'] | ['computer-vision'] | [ 7.20537007e-01 -5.72681248e-01 -3.11316699e-01 -1.48473769e-01
-4.67295915e-01 -5.47109008e-01 1.94057763e-01 -1.17693255e-02
2.56483834e-02 6.09778345e-01 -2.65779704e-01 -3.59412283e-01
-5.37552238e-01 -1.12899649e+00 -4.59555298e-01 -1.13441300e+00
-8.76185969e-02 -3.24120671e-01 -2.27761358e-01 2.74992473e-02
8.43489543e-03 7.67041624e-01 -1.87668395e+00 3.22118521e-01
1.46187067e+00 1.52654564e+00 4.22465920e-01 2.40173891e-01
2.34912299e-02 3.29536080e-01 -2.86215574e-01 1.70869470e-01
6.70196712e-01 -2.46550038e-01 -5.65817356e-01 4.50226694e-01
4.28411782e-01 -3.64098042e-01 -7.52495676e-02 1.52197862e+00
3.95616174e-01 2.17356607e-01 4.62216228e-01 -1.21479881e+00
-7.82282352e-01 2.74111271e-01 -1.07439816e+00 8.79193023e-02
-1.90545022e-01 3.04871976e-01 1.06831968e+00 -6.75022721e-01
-1.73372015e-01 7.87597060e-01 6.86721742e-01 -1.39726788e-01
-1.35988271e+00 -8.05740595e-01 2.63716280e-01 2.66905010e-01
-1.66351688e+00 -2.58302595e-02 9.90808368e-01 -4.67688948e-01
7.31992424e-01 6.94449604e-01 7.60958731e-01 3.89750391e-01
9.52438824e-03 8.08339059e-01 1.47820580e+00 -2.73571879e-01
2.36641802e-02 5.32312356e-02 2.91346282e-01 3.11640322e-01
4.46494639e-01 2.22166374e-01 -2.09779352e-01 -7.76592568e-02
5.41896582e-01 2.59773552e-01 -7.81070828e-01 -3.26244324e-01
-8.23716044e-01 7.35987186e-01 9.04595554e-01 1.64993986e-01
-6.25724018e-01 -5.94865263e-01 2.33195767e-01 8.00777634e-04
6.07336998e-01 4.98253316e-01 -4.37829882e-01 7.59565055e-01
-1.04955959e+00 -1.06968738e-01 7.02309608e-02 8.15031528e-01
1.01875782e+00 9.14311856e-02 -1.25200555e-01 1.05446553e+00
9.01622474e-02 6.59410059e-01 5.28756499e-01 -4.38918442e-01
4.46797699e-01 8.43449175e-01 -1.19767614e-01 -1.29042077e+00
-4.08520013e-01 -7.59555757e-01 -1.26563716e+00 9.22668800e-02
-1.01005800e-01 1.55686848e-02 -8.94191802e-01 1.53323233e+00
2.39616230e-01 1.62578672e-01 7.34063387e-02 1.05060804e+00
5.45769274e-01 9.37188327e-01 1.50823221e-01 -5.10615051e-01
1.38567519e+00 -7.75670409e-01 -5.24909973e-01 -2.08686367e-01
2.44831845e-01 -3.27604741e-01 1.21456790e+00 3.66172761e-01
-5.89141726e-01 -5.52034199e-01 -1.34069753e+00 1.34212583e-01
-7.38870978e-01 5.04975438e-01 6.83489680e-01 7.13780165e-01
-4.90321755e-01 5.11285782e-01 -5.19456089e-01 -2.13782325e-01
7.35682726e-01 1.66349351e-01 -2.60104358e-01 -1.75507084e-01
-1.17620778e+00 3.60981882e-01 7.05080569e-01 3.85668546e-01
-2.77388781e-01 -9.14967775e-01 -7.67663598e-01 2.71221727e-01
2.84381032e-01 1.05376439e-02 5.75276017e-01 -9.68837023e-01
-1.09710073e+00 4.93097842e-01 -2.82097645e-02 -2.86137283e-01
6.02345681e-03 -6.04948848e-02 -6.61585748e-01 2.60259539e-01
1.14194982e-01 5.13685763e-01 7.95533359e-01 -1.28917062e+00
-6.93564773e-01 -6.78701341e-01 -1.65341109e-01 3.70244235e-01
-9.60553467e-01 -4.63040948e-01 1.07594579e-01 -6.33102775e-01
5.55482924e-01 -7.34972060e-01 7.01984204e-03 -6.42106170e-03
-6.04949296e-01 2.92181045e-01 1.28821230e+00 -5.82497835e-01
1.31643760e+00 -2.27196217e+00 -2.63124198e-01 3.55434150e-01
-1.16969682e-02 5.37224770e-01 -2.94095427e-01 5.82945794e-02
-5.61914802e-01 2.48026475e-01 -6.14656091e-01 4.16629076e-01
-3.00963819e-01 -3.05192411e-01 -3.81653726e-01 4.21962827e-01
4.63739991e-01 6.47864163e-01 -8.18593800e-01 -6.89240322e-02
3.24999362e-01 2.27528557e-01 -2.61381477e-01 4.87200767e-02
5.10153510e-02 5.62975705e-02 -4.47379500e-01 1.07517517e+00
1.24438477e+00 -4.12810028e-01 8.38083923e-02 -9.77442682e-01
-4.41167235e-01 -2.02841967e-01 -9.98762608e-01 1.17475533e+00
-1.01068161e-01 4.45536256e-01 1.62706837e-01 -1.10123980e+00
8.22106183e-01 1.96486875e-01 6.71695292e-01 -6.97876394e-01
-5.20964004e-02 1.41271263e-01 -7.84856007e-02 -3.84591371e-01
5.28239012e-01 -9.72535238e-02 3.96710336e-01 1.71526924e-01
-3.65404487e-01 -1.98545694e-01 4.22334410e-02 -3.69951367e-01
4.74920273e-01 -1.80866882e-01 4.54028428e-01 -5.32706439e-01
6.36240363e-01 1.05062321e-01 5.69551468e-01 4.25408006e-01
-3.95513177e-01 3.47159356e-01 1.27354354e-01 -2.87508279e-01
-8.04941177e-01 -5.25937974e-01 -6.21172905e-01 7.60612309e-01
3.68546754e-01 1.54254362e-01 -4.69248444e-01 -5.48926950e-01
2.17164859e-01 5.41615725e-01 -5.06220758e-01 -2.59802341e-01
1.17150784e-01 -1.38289404e+00 3.11564207e-01 3.92252207e-01
1.06879878e+00 -7.55601883e-01 -7.37929583e-01 1.50073823e-02
-2.89545506e-01 -8.04464757e-01 -1.92822933e-01 5.03765404e-01
-9.23841476e-01 -1.16234398e+00 -5.71543634e-01 -3.96785140e-01
7.27618873e-01 9.45161641e-01 5.98870277e-01 -1.49878502e-01
-4.34879512e-01 7.13605725e-04 -4.28222567e-01 -5.89465141e-01
2.62419820e-01 1.81277674e-02 -2.54803956e-01 2.86877543e-01
5.30859172e-01 -3.91790926e-01 -7.83113241e-01 3.56297821e-01
-1.33853507e+00 6.79759458e-02 6.41781569e-01 1.11741090e+00
7.32494771e-01 8.02066624e-01 4.21599478e-01 -7.12036967e-01
4.41714734e-01 -6.17337167e-01 -6.46296561e-01 3.16365421e-01
-6.63293898e-01 -4.60839659e-01 7.41522312e-01 -3.67907405e-01
-9.48059976e-01 9.76894349e-02 3.74587685e-01 -3.59837025e-01
-2.76477188e-01 9.35987413e-01 -6.05599046e-01 -2.58277535e-01
6.14665389e-01 4.14894283e-01 -1.98231050e-04 -2.80257732e-01
-1.24195062e-01 9.42351520e-01 2.19679132e-01 -2.64908671e-01
7.12832510e-01 4.57639068e-01 5.79227805e-02 -1.17450190e+00
-7.97766268e-01 -4.62639809e-01 -4.24653351e-01 -1.42047718e-01
5.67543209e-01 -1.00663733e+00 -4.59059447e-01 7.71439493e-01
-6.22142076e-01 -6.70355186e-02 -1.36044934e-01 4.84546930e-01
-5.19869365e-02 4.26298589e-01 -3.55545342e-01 -9.35702085e-01
-4.49098706e-01 -1.15355170e+00 9.12293434e-01 3.41493487e-01
2.34034166e-01 -6.07940674e-01 -6.75558627e-01 3.01933080e-01
2.90808648e-01 3.01230431e-01 1.23586714e+00 -3.61096978e-01
-6.20154023e-01 -2.04019457e-01 -7.53498375e-01 6.86023474e-01
6.72685981e-01 -2.66187917e-03 -1.24956143e+00 -4.59357500e-01
1.10995606e-01 -2.86678970e-01 9.37556088e-01 6.39215350e-01
1.74801624e+00 -2.26894662e-01 -2.64181286e-01 8.92980278e-01
1.77960801e+00 4.51255292e-01 6.35445654e-01 3.65340263e-01
7.67259121e-01 7.82363772e-01 8.08863103e-01 3.58664304e-01
-1.45196810e-01 1.86512738e-01 8.56550515e-01 -5.35961330e-01
2.80480862e-01 1.74453005e-01 -3.65843922e-02 3.44742477e-01
1.72722176e-01 -3.18047673e-01 -7.11548567e-01 5.78714430e-01
-1.40821898e+00 -1.03811121e+00 -1.94566607e-01 2.29992628e+00
6.81983471e-01 -4.29774255e-01 -2.18844414e-01 5.43079495e-01
8.18497241e-01 4.76333767e-01 -9.49331224e-01 2.33476281e-01
-5.41538775e-01 9.29850191e-02 8.53564739e-01 3.14795487e-02
-1.44460773e+00 4.26100612e-01 5.74522018e+00 7.92840183e-01
-1.52924931e+00 -2.72714823e-01 8.33895445e-01 1.02317845e-02
-2.51726389e-01 -2.71481812e-01 -4.70583439e-01 5.92025995e-01
3.07849318e-01 5.44695705e-02 4.82593060e-01 4.36756730e-01
2.27207631e-01 -2.01789513e-01 -6.40001595e-01 8.46631229e-01
-1.53255954e-01 -9.26825225e-01 2.08312333e-01 2.10745245e-01
8.10809493e-01 -1.23570248e-01 3.58770281e-01 -1.58090144e-01
-5.41805755e-03 -8.41445565e-01 5.33968031e-01 1.89770550e-01
9.99775529e-01 -6.71127081e-01 6.28639221e-01 2.63726562e-01
-1.42280424e+00 -6.49981976e-01 -4.67467576e-01 2.59668052e-01
-3.50440621e-01 9.80949938e-01 -4.14789021e-01 9.91537035e-01
7.31552243e-01 8.89923751e-01 -4.03205663e-01 1.07315516e+00
1.94944203e-01 5.42612433e-01 -2.97056377e-01 3.25472504e-01
3.05564582e-01 -5.70137918e-01 3.80431145e-01 8.77402067e-01
7.87243545e-01 4.73939747e-01 2.07386687e-01 8.89746666e-01
1.07433043e-01 1.98181838e-01 -5.80171406e-01 -3.01653415e-01
6.39690042e-01 1.20780110e+00 -5.72651863e-01 -1.64402556e-03
-4.29908335e-01 7.16095984e-01 -1.64674670e-01 5.98014951e-01
-6.92647159e-01 -4.73072439e-01 7.44714141e-01 -7.12637752e-02
3.56384754e-01 5.21064624e-02 -4.74357486e-01 -8.42882037e-01
6.96211532e-02 -1.04569054e+00 4.27195996e-01 -1.07534158e+00
-1.28880262e+00 6.03077352e-01 -9.82395932e-02 -1.59544218e+00
6.08846784e-01 -7.92651415e-01 -3.18826675e-01 1.15918744e+00
-2.11978531e+00 -1.13325083e+00 -8.20646763e-01 4.90022779e-01
3.92661959e-01 -9.74980369e-02 7.81581700e-01 3.11396778e-01
-1.03224444e+00 3.54420990e-01 2.44112730e-01 -6.73234835e-02
3.65601718e-01 -8.77221107e-01 -3.61932606e-01 1.06243348e+00
-2.81563222e-01 5.07361531e-01 3.07118893e-01 -5.93924105e-01
-1.20545542e+00 -1.52759910e+00 9.64783132e-02 4.32729244e-01
4.95252132e-01 2.66896069e-01 -1.13326645e+00 2.97714233e-01
2.39336118e-03 9.68081355e-02 9.39962149e-01 -3.15530360e-01
-3.31045091e-01 -6.78809464e-01 -1.32805479e+00 3.55788350e-01
6.85614407e-01 -6.01195693e-01 1.04305752e-01 4.00859773e-01
5.05128622e-01 3.22918594e-02 -9.26373005e-01 9.07308221e-01
4.63056237e-01 -9.96506870e-01 9.10429835e-01 -1.76744297e-01
5.91726601e-01 -5.44300854e-01 -3.50733668e-01 -1.47039187e+00
-7.52134740e-01 -2.79975012e-02 1.29561573e-01 1.08837557e+00
3.31349164e-01 -9.05356348e-01 6.37279809e-01 4.08317745e-01
-4.44622301e-02 -5.11547506e-01 -5.27278185e-01 -7.91136920e-01
-2.00088799e-01 -1.86463565e-01 1.15299726e+00 1.28647614e+00
-2.82163650e-01 -1.89227000e-01 -8.70556459e-02 8.33711147e-01
7.56123066e-01 5.70906699e-01 2.08025634e-01 -1.49359000e+00
1.02743506e-01 -6.82514668e-01 -1.47634268e-01 -9.26717699e-01
5.59624918e-02 -8.12729418e-01 -1.97990555e-02 -1.21938229e+00
2.46177167e-01 -5.92317224e-01 -6.02454245e-01 7.01490402e-01
-3.96197081e-01 4.38068122e-01 -9.98895317e-02 3.60287935e-01
2.64197081e-01 5.19800305e-01 1.38485241e+00 -6.47600651e-01
-2.83379525e-01 -1.12025805e-01 -9.08229649e-01 4.45788682e-01
7.92033195e-01 -8.52298364e-02 -6.18667006e-01 -4.02975559e-01
-1.01589881e-01 -3.33618641e-01 4.28607553e-01 -1.10353553e+00
7.68628046e-02 -5.63998878e-01 6.83084428e-01 -8.93395007e-01
1.77990183e-01 -1.27328694e+00 3.73376071e-01 2.58427650e-01
-9.34224576e-02 -5.61822534e-01 5.56049347e-01 3.80200297e-01
-3.50970268e-01 -4.48086672e-02 9.51668799e-01 -8.83613154e-03
-8.10417175e-01 6.11078918e-01 -1.32616282e-01 -6.43808603e-01
1.14719796e+00 -6.15361214e-01 -3.78211796e-01 1.02310069e-01
-2.91148216e-01 2.50887394e-01 3.82656127e-01 7.86901712e-02
4.12885487e-01 -1.33424222e+00 -5.65403104e-01 7.75034010e-01
3.72200876e-01 1.06755793e-01 6.35965586e-01 7.43002594e-01
-3.24792534e-01 4.66041386e-01 -2.85376698e-01 -7.65258312e-01
-1.20145249e+00 4.72433507e-01 4.68387276e-01 -8.56121704e-02
-1.76879883e-01 7.83446372e-01 4.38677788e-01 -3.54725659e-01
-1.83027327e-01 -4.68380094e-01 -2.99928010e-01 4.03297424e-01
5.27265489e-01 4.90692466e-01 3.31325650e-01 -6.67850852e-01
-1.55864179e-01 5.71785569e-01 2.03221589e-01 5.24443209e-01
1.34643650e+00 -1.29457474e-01 -4.13101733e-01 1.78849444e-01
1.12738657e+00 -2.17295960e-01 -1.38342750e+00 -2.37227768e-01
-4.47844595e-01 -6.81295335e-01 5.80137730e-01 -8.76733601e-01
-1.35632455e+00 8.64406645e-01 7.75239050e-01 6.74139857e-01
1.89115047e+00 -7.20665991e-01 5.39248407e-01 1.85583144e-01
2.12202072e-01 -1.06782269e+00 -4.37448114e-01 2.68658459e-01
6.71732068e-01 -1.19501066e+00 3.51637304e-01 -6.59935534e-01
-3.49866629e-01 9.69045103e-01 7.28112578e-01 4.10730749e-01
6.34388685e-01 6.52942806e-02 -9.72366184e-02 -1.47869170e-01
-1.62911788e-01 -2.89835453e-01 4.12811667e-01 6.60402119e-01
2.17819065e-01 3.30891162e-01 6.74289390e-02 4.25361454e-01
1.21440351e-01 -1.39374509e-01 1.62147820e-01 8.93535495e-01
-4.83480692e-01 -7.02474713e-01 -6.53793991e-01 8.31207395e-01
-2.08470136e-01 -3.32848579e-01 -2.33034268e-01 4.52578217e-01
2.46826708e-01 1.04038417e+00 1.00722671e-01 -3.97360027e-01
3.40394139e-01 2.04058550e-02 7.41650313e-02 -4.07134145e-01
-3.40680152e-01 1.27740234e-01 -4.38076258e-01 -3.81156266e-01
-6.28973305e-01 -6.01293266e-01 -8.09532702e-01 -2.06071332e-01
-9.26813781e-01 9.22267586e-02 5.68939924e-01 6.39832258e-01
4.76674974e-01 5.80353558e-01 1.03494751e+00 -8.74047339e-01
-5.69353461e-01 -9.11613703e-01 -1.15364432e+00 2.21498489e-01
5.80838442e-01 -5.56884110e-01 -4.63255763e-01 4.64754999e-02] | [9.940954208374023, -1.5981656312942505] |
4125b20c-1bad-470e-9584-9fd71878027e | real-time-simultaneous-localization-and | 2301.09257 | null | https://arxiv.org/abs/2301.09257v2 | https://arxiv.org/pdf/2301.09257v2.pdf | Real-Time Simultaneous Localization and Mapping with LiDAR intensity | We propose a novel real-time LiDAR intensity image-based simultaneous localization and mapping method , which addresses the geometry degeneracy problem in unstructured environments. Traditional LiDAR-based front-end odometry mostly relies on geometric features such as points, lines and planes. A lack of these features in the environment can lead to the failure of the entire odometry system. To avoid this problem, we extract feature points from the LiDAR-generated point cloud that match features identified in LiDAR intensity images. We then use the extracted feature points to perform scan registration and estimate the robot ego-movement. For the back-end, we jointly optimize the distance between the corresponding feature points, and the point to plane distance for planes identified in the map. In addition, we use the features extracted from intensity images to detect loop closure candidates from previous scans and perform pose graph optimization. Our experiments show that our method can run in real time with high accuracy and works well with illumination changes, low-texture, and unstructured environments. | ['Giovanni Beltrame', 'Wenqiang Du'] | 2023-01-23 | null | null | null | null | ['simultaneous-localization-and-mapping'] | ['computer-vision'] | [ 1.28189832e-01 -2.55104542e-01 2.19795736e-03 -4.54103380e-01
-6.05015457e-01 -3.79744500e-01 2.70737618e-01 2.89849490e-01
-6.03204608e-01 5.74705005e-01 -4.22879130e-01 -4.68387790e-02
-1.53971210e-01 -1.10222852e+00 -7.70716548e-01 -2.46097028e-01
3.74701852e-03 1.25397348e+00 6.22068107e-01 -2.57119358e-01
6.16432250e-01 1.02812493e+00 -1.57191312e+00 -8.13900828e-01
1.01845944e+00 6.02694213e-01 4.65583116e-01 3.24825406e-01
-2.25279018e-01 -6.88588843e-02 -7.83718079e-02 2.34783009e-01
4.04814154e-01 1.03186443e-01 -2.11359620e-01 1.75698355e-01
5.97322404e-01 -4.14026439e-01 -2.11452648e-01 1.11422598e+00
3.92841130e-01 1.66528299e-02 3.94105524e-01 -1.26778555e+00
3.10584664e-01 -3.04469556e-01 -1.01675749e+00 -2.63584375e-01
6.10436797e-01 -3.54051515e-02 4.68597651e-01 -1.27582192e+00
8.26077580e-01 1.14827108e+00 8.54245305e-01 -1.92542881e-01
-1.22407842e+00 -7.43098021e-01 -2.37485364e-01 -5.24020605e-02
-1.88304484e+00 -4.65923637e-01 8.77959907e-01 -3.43235046e-01
7.86152244e-01 -2.28236943e-01 6.83891654e-01 1.63181216e-01
3.62932354e-01 -1.69886768e-01 6.59865558e-01 -5.91485679e-01
4.41371929e-03 -9.64675993e-02 -9.69698057e-02 1.18091786e+00
7.07018197e-01 1.93232089e-01 -5.86219370e-01 -6.75754771e-02
1.02523458e+00 2.09344834e-01 1.43598225e-02 -1.10731316e+00
-1.33510518e+00 8.35924745e-01 5.43239057e-01 -1.65126473e-01
-1.94263816e-01 2.31515709e-03 -2.27424815e-01 1.27052873e-01
1.35371685e-01 2.16218412e-01 -9.47661325e-02 -1.05614461e-01
-5.90383112e-01 1.79979697e-01 6.69782102e-01 1.30051231e+00
1.73585892e+00 -2.99095452e-01 7.99484909e-01 4.87019658e-01
3.28288734e-01 1.08970416e+00 -5.44522218e-02 -1.11298013e+00
7.04479337e-01 8.68160367e-01 2.81628728e-01 -1.20333111e+00
-7.72334814e-01 5.60155213e-02 -4.06935692e-01 3.43878746e-01
3.19783121e-01 -1.42032076e-02 -8.72832656e-01 1.14994609e+00
6.47654831e-01 -4.36633416e-02 -1.83957413e-01 8.93814623e-01
3.04024398e-01 2.31057853e-01 -7.50099301e-01 -2.18633981e-03
1.08918798e+00 -3.81333619e-01 -4.42311257e-01 -6.06959701e-01
7.28117228e-01 -9.06309664e-01 7.77087331e-01 5.64541034e-02
-6.13410830e-01 -3.93113703e-01 -1.34627974e+00 -1.53183669e-01
-6.83953762e-02 1.37912882e-02 2.50734955e-01 2.85261214e-01
-9.15861845e-01 3.87147397e-01 -8.99054587e-01 -4.29911524e-01
-2.77350098e-01 7.47097194e-01 -4.58014578e-01 -2.38115564e-01
-7.32802212e-01 1.09309042e+00 3.03733945e-01 4.39852923e-02
-1.18619815e-01 -3.65086049e-01 -1.22577059e+00 -4.04867858e-01
5.01264155e-01 -6.18878663e-01 8.91711771e-01 -1.41781837e-01
-1.31009281e+00 8.55803967e-01 -6.23621941e-01 -1.44622341e-01
3.73358279e-01 -3.01470906e-01 6.97522312e-02 1.22228712e-02
5.09605050e-01 5.77137947e-01 3.81303281e-01 -1.34670341e+00
-8.23007464e-01 -9.27306652e-01 -2.98827857e-01 5.30638695e-01
4.23954457e-01 -5.98432004e-01 -6.82332635e-01 3.78637582e-01
1.15216637e+00 -1.27388787e+00 -4.25267965e-01 1.28851011e-01
-3.85089695e-01 2.28268921e-01 1.08934069e+00 -7.21519217e-02
5.00244379e-01 -2.20721507e+00 -2.59541154e-01 7.65870333e-01
2.89127976e-02 -3.59847069e-01 1.13467962e-01 3.91150713e-01
5.75421453e-01 -3.90304297e-01 -3.35053578e-02 -2.64907092e-01
-3.77242357e-01 4.53819782e-01 -4.27424014e-02 8.26028526e-01
-7.93866143e-02 4.91969675e-01 -9.57926810e-01 -6.60164237e-01
4.57648069e-01 3.51670861e-01 -3.48867685e-01 -6.02532066e-02
9.50643644e-02 4.90511507e-01 -5.83012164e-01 5.82858920e-01
1.00128579e+00 2.15124905e-01 8.04945733e-03 -1.29002228e-01
-5.99497318e-01 4.57422584e-01 -1.60886824e+00 1.84554613e+00
-4.07239169e-01 6.06558442e-01 2.05924526e-01 -4.66573387e-01
1.40954375e+00 -2.89110929e-01 5.53140104e-01 -7.36390829e-01
-5.77843189e-02 6.96556747e-01 -2.22566366e-01 -1.89138159e-01
8.54838669e-01 1.11201890e-01 -1.34349182e-01 1.76074475e-01
-4.45296109e-01 -7.96345413e-01 -6.96320385e-02 -1.40310869e-01
8.27990413e-01 2.73851484e-01 3.84552747e-01 -9.51582938e-02
4.39960837e-01 4.52864468e-01 6.11225367e-01 5.14216244e-01
1.81306377e-01 4.88712758e-01 -6.76848739e-02 -3.26450139e-01
-1.23042309e+00 -1.23825908e+00 -1.85936540e-01 2.84951925e-01
1.00225174e+00 -2.93680698e-01 -2.29059249e-01 -9.99245942e-02
4.65532452e-01 1.54750422e-01 -7.81744253e-03 5.44831865e-02
-8.77062619e-01 -9.24237669e-02 9.95098725e-02 3.48640949e-01
6.01442218e-01 -3.87664199e-01 -9.60410655e-01 4.25675809e-01
-2.37330645e-01 -1.19593143e+00 -1.44500852e-01 3.00467759e-01
-1.12687862e+00 -1.10845232e+00 -2.63475068e-02 -8.09141874e-01
8.69326413e-01 7.44612336e-01 7.33635008e-01 5.35914488e-02
-1.85341522e-01 8.22582319e-02 7.22758248e-02 -4.20180529e-01
5.38397767e-03 -3.92980985e-02 2.74993449e-01 -4.48007107e-01
4.20531362e-01 -5.92499554e-01 -3.85100305e-01 7.16293693e-01
-9.31075141e-02 -3.20857279e-02 3.58074069e-01 5.88902771e-01
1.01210594e+00 -1.10770665e-01 -1.25198975e-01 -4.14808810e-01
6.62894920e-02 -1.11868195e-02 -1.30736792e+00 -3.37331325e-01
-5.63067853e-01 2.35997885e-01 -2.02367026e-02 -1.33604020e-01
-5.68517804e-01 7.65692472e-01 1.87739313e-01 -2.83755630e-01
-3.32275815e-02 6.32723212e-01 -2.74858233e-02 -5.53335845e-01
6.76117301e-01 1.59008689e-02 2.61350900e-01 -3.69649559e-01
1.82631016e-01 5.49312830e-01 6.47606909e-01 -4.32255983e-01
1.20484614e+00 9.78182495e-01 5.81543982e-01 -1.05792117e+00
-5.31770110e-01 -8.52248013e-01 -1.16312277e+00 -6.80256560e-02
5.55449784e-01 -1.04667294e+00 -6.25069261e-01 1.72290847e-01
-1.37724590e+00 1.04129747e-01 -4.19254415e-02 8.44233751e-01
-6.33235097e-01 4.84583914e-01 -9.90022719e-02 -9.03166831e-01
-8.50743130e-02 -1.30113375e+00 1.32255864e+00 2.05572560e-01
-4.44384553e-02 -6.54617786e-01 3.84093732e-01 -1.04922615e-01
-1.61280498e-01 3.97435725e-01 5.65469086e-01 1.18675880e-01
-1.06741679e+00 -3.77474517e-01 -2.41526470e-01 -6.66699231e-01
2.03740478e-01 1.40723111e-02 -6.56524956e-01 -3.24262768e-01
2.10479815e-02 7.96441212e-02 5.13475478e-01 2.40994617e-01
2.63853163e-01 3.34486991e-01 -8.47793043e-01 8.97410691e-01
1.65337896e+00 1.77552909e-01 5.06063759e-01 7.40555167e-01
7.74563313e-01 5.74382424e-01 1.15859687e+00 3.36108983e-01
6.78572953e-01 1.05072427e+00 6.21947885e-01 -6.88615367e-02
3.70511293e-01 -4.86758322e-01 2.09091946e-01 6.83459222e-01
-2.92131561e-03 3.29914302e-01 -1.26459086e+00 5.12805998e-01
-1.81974435e+00 -4.32207674e-01 -5.89005172e-01 2.58740473e+00
2.93793648e-01 2.54983962e-01 -1.97414652e-01 6.18701763e-02
7.76985645e-01 -3.21858406e-01 -4.89168525e-01 -1.41211748e-01
2.43325129e-01 2.00178847e-02 1.17024338e+00 9.10560250e-01
-8.07642102e-01 1.13794017e+00 5.65039587e+00 7.02073053e-02
-1.17694771e+00 -1.82364956e-01 -5.55859566e-01 2.07990199e-01
-1.20923117e-01 3.72600377e-01 -1.19385648e+00 5.72659448e-02
5.85749745e-01 -1.05635554e-01 2.01898143e-01 9.54895198e-01
2.10266829e-01 -6.31208181e-01 -8.72899473e-01 1.05063677e+00
-9.65425298e-02 -9.92120564e-01 -3.89373392e-01 5.40031314e-01
5.12712836e-01 5.44104755e-01 -2.59729177e-01 -1.57484710e-01
2.00554878e-01 -5.71967661e-01 6.58050478e-01 1.62338763e-01
8.82264853e-01 -9.56926942e-01 6.00589037e-01 8.34416866e-01
-1.59931958e+00 1.44386142e-01 -6.21558368e-01 -2.97659844e-01
3.83346468e-01 8.18300903e-01 -1.37860155e+00 6.54175997e-01
4.29477245e-01 4.57145184e-01 -3.84499013e-01 1.18597758e+00
-2.43108973e-01 -2.87421912e-01 -9.56522763e-01 6.63551390e-02
1.09928153e-01 -6.13131940e-01 6.52666926e-01 6.73470438e-01
6.96923852e-01 -2.52872318e-01 6.00076914e-01 7.61023223e-01
3.02031696e-01 -1.57933161e-02 -1.16222775e+00 5.61358631e-01
8.37195098e-01 1.04629779e+00 -7.76391625e-01 -1.12308525e-01
-3.17781597e-01 7.79997349e-01 2.52008647e-01 1.06870793e-01
-5.66618145e-01 -6.40884161e-01 6.52923763e-01 5.06582022e-01
8.55771452e-02 -1.13243115e+00 -4.86821592e-01 -1.00731826e+00
2.90172130e-01 -2.35812128e-01 -1.54976472e-01 -6.96935833e-01
-4.91245568e-01 2.42216006e-01 -1.03212222e-01 -1.47862649e+00
-5.06139755e-01 -3.40568542e-01 -3.59900177e-01 9.14236963e-01
-1.72019160e+00 -8.62036586e-01 -7.53465652e-01 6.50990367e-01
2.64877558e-01 4.70081389e-01 6.50685906e-01 1.50281116e-01
5.59229590e-02 -5.99838942e-02 4.75813933e-02 7.09898546e-02
7.66287744e-01 -1.03521299e+00 6.25464320e-01 7.37613022e-01
1.87537983e-01 7.58623660e-01 6.04261339e-01 -1.15295291e+00
-1.69389439e+00 -8.97453666e-01 9.26862657e-01 -3.34208906e-01
3.90426487e-01 -3.87789220e-01 -7.46206880e-01 6.67440593e-01
-6.15030169e-01 -4.21929583e-02 -1.22977771e-01 -2.54982337e-02
-6.38947636e-02 -1.70643076e-01 -1.15552878e+00 4.21090513e-01
1.27017450e+00 -4.01084393e-01 -4.57589746e-01 2.04580575e-01
4.98775959e-01 -9.74801123e-01 -4.94686455e-01 5.41973054e-01
6.75442994e-01 -7.96117246e-01 1.10161150e+00 3.66247296e-01
-3.17096233e-01 -6.47820294e-01 -1.20289572e-01 -1.15238094e+00
-1.42095774e-01 -4.93770421e-01 4.01484102e-01 7.84374952e-01
2.45052829e-01 -8.59274924e-01 1.09678686e+00 1.52579099e-01
-6.88628033e-02 -1.32899046e-01 -1.22836769e+00 -1.00071311e+00
-4.92596895e-01 -2.60945916e-01 6.49610758e-01 6.01451814e-01
-1.01781599e-01 5.71870625e-01 -3.61521579e-02 6.29318476e-01
1.04648829e+00 4.64503884e-01 1.40810752e+00 -1.81806099e+00
3.55686307e-01 1.27319619e-01 -7.87880659e-01 -1.27535188e+00
1.06849670e-01 -5.73597074e-01 5.45840025e-01 -1.57965386e+00
-3.49696159e-01 -9.03710961e-01 5.25614262e-01 1.58171654e-01
1.37760997e-01 2.52057165e-01 -3.93544771e-02 5.90421855e-01
-1.59367368e-01 3.22829485e-01 9.69813883e-01 1.21178888e-01
-6.04506910e-01 -8.95907283e-02 1.14274763e-01 9.74481285e-01
6.74061418e-01 -6.30437493e-01 -1.64189756e-01 -5.78787625e-01
2.55824506e-01 1.35155216e-01 1.62810594e-01 -1.23420763e+00
4.39419985e-01 -4.31774378e-01 3.84990156e-01 -1.25543916e+00
7.67154515e-01 -1.07963705e+00 1.66931987e-01 6.86029911e-01
5.43903172e-01 3.22032273e-01 -3.01744621e-02 5.08632421e-01
-5.46572730e-02 -2.78431833e-01 6.66035235e-01 -1.10795580e-01
-7.70389080e-01 2.87078500e-01 -9.80935618e-02 -3.93637657e-01
9.94979918e-01 -7.92371750e-01 -1.97330266e-01 -4.28934395e-01
-2.55307466e-01 4.72215772e-01 1.32856226e+00 1.54994026e-01
9.33737218e-01 -1.28509951e+00 -4.79271442e-01 5.87605655e-01
5.64960539e-01 6.53136432e-01 -3.43712717e-01 1.01289570e+00
-9.30360734e-01 4.15421396e-01 -1.59763500e-01 -1.31658936e+00
-1.25439394e+00 3.15935403e-01 2.31050104e-01 1.46914303e-01
-8.28233004e-01 2.96839207e-01 -1.21969670e-01 -6.93159163e-01
-2.17820615e-01 -3.11174452e-01 1.80543169e-01 -2.64035970e-01
1.41883016e-01 3.64212036e-01 1.77526087e-01 -9.43328679e-01
-5.78406274e-01 1.36651850e+00 2.89280951e-01 -5.57161331e-01
1.11169028e+00 -6.13615334e-01 1.35937026e-02 4.08877969e-01
1.10378742e+00 3.76168936e-01 -1.08259511e+00 -3.58234525e-01
2.19285935e-01 -7.90248275e-01 -1.26911119e-01 1.30737886e-01
-5.68764448e-01 9.21944261e-01 7.14872956e-01 -2.42136508e-01
4.50301588e-01 -2.13794217e-01 7.60986924e-01 7.30069220e-01
1.13434184e+00 -1.02157700e+00 -1.20773651e-01 9.87513661e-01
5.34760177e-01 -1.14971960e+00 3.05612504e-01 -9.30144727e-01
-7.73194134e-02 1.35153186e+00 5.00745714e-01 -2.40759507e-01
2.80672312e-01 4.94833499e-01 1.76006049e-01 -2.63955116e-01
6.86905161e-02 -3.78884524e-01 -7.97168314e-02 9.27834749e-01
-7.69353434e-02 -9.79141295e-02 -8.26724395e-02 -5.91012359e-01
-4.97593939e-01 -1.49715066e-01 6.15978479e-01 1.31794214e+00
-1.19298697e+00 -1.17322600e+00 -8.88038397e-01 1.39331594e-01
3.21272463e-01 2.97241122e-01 -2.67422587e-01 8.85070801e-01
2.64902208e-02 7.55334198e-01 5.47361135e-01 -4.93406296e-01
5.98792851e-01 -9.53445733e-02 6.84199035e-01 -7.26998150e-01
1.26327172e-01 2.48577729e-01 1.17555797e-01 -7.36923456e-01
-2.10038975e-01 -6.35012865e-01 -1.80946493e+00 -1.78402230e-01
-6.51719272e-01 5.91089949e-02 1.24892569e+00 7.91454256e-01
5.04743159e-01 -2.41020128e-01 7.03728795e-01 -1.08076608e+00
-3.60625714e-01 -6.25954092e-01 -5.53081930e-01 -7.93534890e-03
5.39593279e-01 -1.08381760e+00 -2.04314277e-01 -2.93700457e-01] | [7.4362030029296875, -2.265137195587158] |
98af7da0-d289-4c5b-a380-d72ba3c61a43 | stvgbert-a-visual-linguistic-transformer | null | null | http://openaccess.thecvf.com//content/ICCV2021/html/Su_STVGBert_A_Visual-Linguistic_Transformer_Based_Framework_for_Spatio-Temporal_Video_Grounding_ICCV_2021_paper.html | http://openaccess.thecvf.com//content/ICCV2021/papers/Su_STVGBert_A_Visual-Linguistic_Transformer_Based_Framework_for_Spatio-Temporal_Video_Grounding_ICCV_2021_paper.pdf | STVGBert: A Visual-Linguistic Transformer Based Framework for Spatio-Temporal Video Grounding | Spatio-temporal video grounding (STVG) aims to localize a spatio-temporal tube of a target object in an untrimmed video based on a query sentence. In this work, we propose a one-stage visual-linguistic transformer based framework called STVGBert for the STVG task, which can simultaneously localize the target object in both spatial and temporal domains. Specifically, without resorting to pre-generated object proposals, our STVGBert directly takes a video and a query sentence as the input, and then produces the cross-modal features by using the newly introduced cross-modal feature learning module ST-ViLBert. Based on the cross-modal features, our method then generates bounding boxes and predicts the starting and ending frames to produce the predicted object tube. To the best of our knowledge, our STVGBert is the first one-stage method, which can handle the STVG task without relying on any pre-trained object detectors. Comprehensive experiments demonstrate our newly proposed framework outperforms the state-of-the-art multi-stage methods on two benchmark datasets Vid-STG and HC-STVG. | ['Dong Xu', 'Qian Yu', 'Rui Su'] | 2021-01-01 | null | null | null | iccv-2021-1 | ['video-grounding', 'spatio-temporal-video-grounding'] | ['computer-vision', 'computer-vision'] | [-4.35127616e-02 -1.14125490e-01 -8.77238214e-02 -1.46283388e-01
-8.59404683e-01 -4.62133259e-01 6.44187570e-01 -2.76778992e-02
-4.08636063e-01 2.82216072e-01 2.05172431e-02 -1.15768112e-01
2.73532093e-01 -5.97398579e-01 -9.13592219e-01 -5.41791499e-01
3.13495159e-01 2.66216844e-01 9.33815479e-01 -9.63135809e-02
1.46123528e-01 1.64768621e-01 -1.43598306e+00 6.41092300e-01
4.44536418e-01 1.35019135e+00 7.19274998e-01 5.24748147e-01
-2.67845970e-02 8.04801226e-01 -5.60622811e-02 -4.49618638e-01
2.88395211e-02 -5.67658007e-01 -8.15914571e-01 4.20740664e-01
2.57242113e-01 -1.78079277e-01 -3.61231834e-01 8.81012022e-01
1.59087092e-01 2.63366044e-01 7.34385550e-01 -1.30236912e+00
-4.86216396e-01 3.66883546e-01 -6.51416898e-01 4.36477989e-01
5.38792312e-01 3.61307055e-01 9.94186819e-01 -1.16615796e+00
8.47612441e-01 1.26245749e+00 4.27997023e-01 3.71854931e-01
-8.84472132e-01 -3.51762891e-01 5.93894362e-01 3.90403807e-01
-1.39694297e+00 -3.25436085e-01 9.96871293e-01 -6.42854512e-01
8.46601486e-01 -8.25381503e-02 7.02751100e-01 9.42711890e-01
1.60961181e-01 1.01591909e+00 8.24967325e-01 -3.91886145e-01
1.37755513e-01 8.31743106e-02 -2.57484227e-01 1.16677666e+00
-3.91981810e-01 5.67460172e-02 -6.40751541e-01 1.22512296e-01
7.44722545e-01 1.12369545e-02 -2.97326893e-01 -6.52957857e-01
-1.55083847e+00 6.91329598e-01 4.40811425e-01 5.66690505e-01
-3.39780003e-01 1.79878205e-01 5.27173758e-01 -1.48353577e-01
4.28388625e-01 -1.14726834e-01 -3.76173496e-01 1.22718930e-01
-1.03808439e+00 2.36358792e-02 3.44874352e-01 1.07583177e+00
8.45953763e-01 -3.71761061e-02 -5.70497453e-01 3.06133687e-01
5.48533082e-01 3.17896008e-01 4.41873670e-01 -5.63085318e-01
7.55877376e-01 6.70210421e-01 2.39828780e-01 -1.05489802e+00
-2.24087492e-01 -4.28815871e-01 -3.85268569e-01 -8.27968717e-02
3.42986792e-01 2.01358527e-01 -9.29007769e-01 1.39749575e+00
6.60579979e-01 5.12898028e-01 8.49081725e-02 1.23892128e+00
1.03682876e+00 9.02104080e-01 9.81397182e-02 -3.57319713e-01
1.39932060e+00 -1.26415825e+00 -5.02706587e-01 -2.93006569e-01
4.95563358e-01 -6.46685302e-01 1.12995481e+00 6.08639307e-02
-1.00202954e+00 -6.65834844e-01 -7.96390772e-01 -7.78864399e-02
-1.76269695e-01 6.14751875e-01 2.03947857e-01 6.82506412e-02
-8.43297899e-01 1.72019973e-01 -1.02514064e+00 -4.26583827e-01
4.52340931e-01 5.19192070e-02 -4.79554236e-01 -8.08949769e-02
-8.35641623e-01 7.55315185e-01 5.59716761e-01 3.21938634e-01
-1.27424693e+00 -2.84311473e-01 -1.08682799e+00 -1.50434926e-01
7.55624235e-01 -6.72257662e-01 1.18404686e+00 -9.41767812e-01
-1.35996926e+00 9.21726644e-01 -5.73775589e-01 -2.91791528e-01
5.59402406e-01 1.76283401e-02 -2.96402156e-01 4.93253052e-01
3.13292146e-01 5.79679012e-01 1.04746437e+00 -1.20709205e+00
-8.52693856e-01 -2.72962719e-01 5.41495681e-02 2.63092816e-01
-5.47008514e-02 1.59158155e-01 -8.68778646e-01 -5.22600293e-01
1.29385769e-01 -5.74485719e-01 2.95643434e-02 1.09949097e-01
-3.98029029e-01 -4.71673489e-01 1.09955549e+00 -4.51524794e-01
9.36810672e-01 -2.14848995e+00 2.89963096e-01 -2.73727000e-01
1.07952051e-01 3.14933091e-01 -1.25244513e-01 3.35999697e-01
2.44908094e-01 -2.61591494e-01 3.75705282e-03 -6.20977581e-01
-2.13612065e-01 -5.99841215e-02 -3.15113068e-01 6.87844038e-01
1.90083086e-01 1.08920026e+00 -1.09885788e+00 -1.03349066e+00
6.54959679e-01 4.13436830e-01 -3.36783111e-01 3.82194787e-01
-5.73393106e-01 5.79729855e-01 -6.22548819e-01 6.85463309e-01
3.40405762e-01 -3.32440257e-01 -1.96867883e-01 -5.62901258e-01
-3.13569963e-01 -1.70179754e-02 -7.47354031e-01 2.05644560e+00
-2.94880360e-01 4.72160876e-01 -3.48272204e-01 -1.12971044e+00
8.20044994e-01 2.64754057e-01 3.75819802e-01 -5.80431700e-01
3.62396598e-01 2.17322171e-01 -4.51676905e-01 -8.08177710e-01
2.52211541e-01 3.42393517e-02 -8.86409730e-02 1.16689228e-01
4.45480615e-01 2.58719265e-01 2.52890706e-01 2.35950798e-01
7.60346591e-01 6.06125832e-01 3.55044454e-01 1.05390280e-01
8.56477201e-01 8.90121311e-02 6.93626523e-01 4.34167057e-01
-2.71252126e-01 6.41040742e-01 3.93330544e-01 -3.53774995e-01
-8.99374247e-01 -1.01548839e+00 3.45777929e-01 1.12831616e+00
5.23332775e-01 -3.59472424e-01 -5.85051537e-01 -8.66996288e-01
-2.54954010e-01 4.51621503e-01 -5.77390850e-01 6.55965433e-02
-5.03016174e-01 -1.83357727e-02 2.19252691e-01 5.28539658e-01
6.23071194e-01 -1.17123687e+00 -8.95493686e-01 1.93825915e-01
-4.67729926e-01 -1.54538906e+00 -9.57894683e-01 -1.09313801e-01
-5.92998266e-01 -1.02840090e+00 -7.18244135e-01 -1.15667176e+00
6.07060611e-01 3.12995434e-01 8.47688675e-01 -7.50068575e-02
-1.92918301e-01 2.44775355e-01 -5.98655760e-01 9.15930569e-02
-5.79709187e-02 -1.02574974e-01 -1.91451013e-01 5.09948015e-01
1.58923328e-01 -2.62747496e-01 -7.52608836e-01 5.37392497e-01
-5.64850211e-01 5.56535959e-01 4.65028316e-01 7.30863154e-01
9.69120979e-01 -1.42802343e-01 2.67571658e-01 -4.58458155e-01
-1.89022243e-01 -3.58147770e-01 -7.98644483e-01 4.52920020e-01
-2.83223465e-02 5.06183393e-02 7.28186071e-01 -4.78329360e-01
-8.38474929e-01 5.52889466e-01 7.85434097e-02 -1.06314206e+00
-3.86460125e-02 4.11521584e-01 -2.69996524e-01 7.29718357e-02
3.04089338e-01 7.27625549e-01 -4.03341919e-01 -4.39902663e-01
5.25929809e-01 4.26459193e-01 9.09209549e-01 -3.26360643e-01
7.94417918e-01 6.67625368e-01 -8.48085508e-02 -4.66339082e-01
-9.55460548e-01 -6.84175670e-01 -9.23955321e-01 -4.89954621e-01
1.34523118e+00 -9.62109506e-01 -7.84290135e-01 2.46457964e-01
-1.31123447e+00 -1.99009717e-01 3.74254137e-02 4.69081700e-01
-9.06770289e-01 3.27123195e-01 -2.63854504e-01 -8.91966820e-01
-2.18509719e-01 -1.21856785e+00 1.47650552e+00 6.39238162e-04
3.49809438e-01 -7.80229509e-01 -2.16828510e-01 4.06705111e-01
-1.05524808e-01 3.86780053e-01 4.66275245e-01 -4.49170142e-01
-9.00161028e-01 -4.46379259e-02 -2.89894193e-01 -3.82827893e-02
5.78302965e-02 -2.00338587e-01 -7.69567549e-01 -2.82530129e-01
-9.97023806e-02 -2.53213644e-01 9.18199480e-01 3.00413758e-01
9.65468168e-01 -3.48805785e-01 -5.42401314e-01 7.12688088e-01
1.42631304e+00 3.83676410e-01 2.83704102e-01 2.68944860e-01
9.12836909e-01 3.92726719e-01 1.23230219e+00 3.98470461e-01
5.68807423e-01 9.32277441e-01 6.51632726e-01 -1.41768798e-01
4.76201661e-02 -5.82997561e-01 5.54145873e-01 3.61382991e-01
1.98173523e-02 -4.99526978e-01 -7.54193008e-01 7.57538378e-01
-2.12447548e+00 -9.86412942e-01 -1.74831715e-03 1.67142344e+00
4.43869859e-01 1.43305557e-02 3.14318091e-01 -5.93117997e-02
9.10541654e-01 3.36515039e-01 -6.36158884e-01 2.29743615e-01
1.65776178e-01 -2.61092842e-01 2.59451538e-01 1.80958599e-01
-1.46046221e+00 1.19682574e+00 4.69885492e+00 8.49546015e-01
-1.20514643e+00 3.77398878e-01 5.09210885e-01 -3.70398015e-02
3.79662067e-02 3.88172120e-02 -8.09704006e-01 5.69512367e-01
5.28341234e-01 -1.67058572e-01 2.24408343e-01 8.96586180e-01
4.55467373e-01 -2.09781174e-02 -1.18245852e+00 1.18337524e+00
3.55775774e-01 -1.50627398e+00 -3.18640806e-02 -3.79846364e-01
4.41294312e-01 -4.61858064e-02 2.09176373e-02 1.67907983e-01
-2.54186988e-01 -7.02677906e-01 1.35156143e+00 5.91790915e-01
8.55691969e-01 -5.78150749e-01 7.18668401e-01 4.04892236e-01
-1.82727325e+00 -4.28524911e-02 -2.68624991e-01 3.00287217e-01
3.83576930e-01 2.12500617e-01 -8.00010264e-01 7.35461056e-01
6.32170916e-01 1.02593791e+00 -4.61502135e-01 1.12644672e+00
-2.29706243e-01 4.89809752e-01 -1.07215643e-01 8.00068378e-02
4.18688208e-01 1.35666311e-01 6.02416337e-01 1.11573243e+00
4.97780293e-01 1.89317688e-01 6.21209800e-01 9.16949391e-01
2.27715179e-01 2.27228791e-01 -5.77944577e-01 -2.65385602e-02
2.15410888e-01 1.19070053e+00 -9.30870116e-01 -3.26223582e-01
-5.73316157e-01 1.21481645e+00 3.07557732e-01 3.65267694e-01
-1.12717962e+00 -2.51231074e-01 3.04732658e-02 3.14748317e-01
8.47289741e-01 -8.18145871e-02 2.26967916e-01 -1.49691069e+00
2.58667320e-01 -4.45321470e-01 4.90354657e-01 -1.17363727e+00
-8.69776249e-01 8.55902672e-01 -3.89809012e-02 -1.63757753e+00
-2.99186021e-01 -3.53885621e-01 -4.98473823e-01 6.04389429e-01
-1.40980613e+00 -1.69721520e+00 -4.34122622e-01 9.30680692e-01
8.29226017e-01 -1.67231023e-01 3.21866184e-01 8.20332617e-02
-5.29271066e-01 4.09969062e-01 -2.12725550e-01 2.14718372e-01
4.13436145e-01 -7.93056667e-01 1.42930895e-01 1.05491853e+00
3.28179568e-01 1.29904717e-01 6.22134864e-01 -6.29128218e-01
-1.34050369e+00 -1.57688487e+00 8.05449486e-01 -3.02518874e-01
6.13580942e-01 -5.41639745e-01 -7.05313742e-01 8.09741795e-01
6.29213229e-02 5.48428178e-01 -6.64218664e-02 -6.14452183e-01
-2.42229223e-01 -1.06107242e-01 -9.06989574e-01 3.04052979e-01
1.15767455e+00 -5.99231005e-01 -6.65946960e-01 4.15418208e-01
9.14956629e-01 -7.77303874e-01 -4.62378174e-01 2.60533750e-01
3.81565809e-01 -9.77539718e-01 9.93288517e-01 -3.54718745e-01
4.94822621e-01 -7.77453780e-01 -1.77835375e-01 -9.38841879e-01
-1.94182739e-01 -4.15969372e-01 -3.71428356e-02 1.21948922e+00
1.37609497e-01 -2.29659155e-01 6.00732327e-01 5.16376868e-02
-4.83407438e-01 -8.51693511e-01 -1.05900288e+00 -8.56977642e-01
-5.64402401e-01 -5.69496870e-01 3.79134953e-01 4.80588019e-01
-1.15457498e-01 1.68527991e-01 -5.72938085e-01 2.62593001e-01
5.37465215e-01 5.00604749e-01 7.00642049e-01 -7.99142241e-01
-2.98086911e-01 -9.42834094e-03 -8.02597463e-01 -1.19200361e+00
1.80702373e-01 -8.99408638e-01 2.74356037e-01 -1.61083663e+00
1.82173312e-01 2.14339942e-02 -2.39446506e-01 6.25787139e-01
-8.36252570e-02 4.80124325e-01 3.34096611e-01 8.26427490e-02
-1.22291577e+00 8.76309276e-01 1.36876726e+00 -1.76649183e-01
-2.11726978e-01 -1.71487287e-01 -3.30961823e-01 7.93233752e-01
4.14420247e-01 -5.01825750e-01 -5.27853549e-01 -3.46565425e-01
-3.04388732e-01 3.61519724e-01 7.54509151e-01 -8.69406521e-01
2.91529059e-01 -4.19269919e-01 3.60127866e-01 -1.11490571e+00
5.24827123e-01 -7.79387474e-01 6.16650991e-02 3.71112764e-01
-1.13509305e-01 6.26301542e-02 1.35727227e-01 8.00454319e-01
-2.65143275e-01 6.49904758e-02 7.69109786e-01 -7.17276707e-02
-1.06841505e+00 4.55720544e-01 -3.42394084e-01 -4.60666232e-02
1.49600244e+00 -2.81925708e-01 -3.32755506e-01 -4.02344391e-02
-8.47264111e-01 2.98097432e-01 3.71942699e-01 3.97271931e-01
9.47309852e-01 -1.32923174e+00 -4.08122659e-01 8.80571380e-02
4.16559637e-01 1.63574070e-02 3.95365834e-01 1.05033720e+00
-2.43497625e-01 6.33473217e-01 -2.65099313e-02 -9.29950953e-01
-1.41655004e+00 9.89955544e-01 3.77940834e-01 -1.70991212e-01
-9.32285428e-01 8.57263088e-01 6.22374296e-01 1.56190738e-01
1.19276673e-01 -4.92312878e-01 -3.28113735e-01 -1.10544816e-01
3.54885459e-01 -2.60320380e-02 -1.59155577e-01 -1.20407164e+00
-6.58718824e-01 8.02025199e-01 -4.90507111e-03 -2.01535061e-01
1.15728354e+00 -2.66406983e-01 1.34131014e-01 6.23462319e-01
1.31697810e+00 -4.73559886e-01 -1.42024863e+00 -4.35729772e-01
-2.73155153e-01 -5.94091356e-01 2.71736411e-03 -4.99074131e-01
-1.21205068e+00 8.04049551e-01 4.22489673e-01 -3.48782539e-01
1.24527264e+00 4.37876672e-01 7.59006023e-01 1.33583933e-01
6.72695756e-01 -6.07572854e-01 5.60482562e-01 2.41809368e-01
8.89651656e-01 -1.07020593e+00 -2.13170603e-01 -5.56894064e-01
-8.58939946e-01 9.44733024e-01 8.52204800e-01 -1.04574122e-01
4.64874625e-01 -2.08584845e-01 -1.49549335e-01 -1.91689983e-01
-7.99842238e-01 -4.77378786e-01 4.76083964e-01 4.57889050e-01
5.22733703e-02 -1.93746418e-01 -2.07026452e-01 5.60447395e-01
9.04151425e-02 2.64078975e-01 1.70292169e-01 7.74637938e-01
-4.36891943e-01 -8.18753660e-01 -3.21591586e-01 2.28611276e-01
-2.22959280e-01 2.56864987e-02 -1.29016608e-01 7.45167911e-01
4.28720325e-01 8.98623049e-01 5.12352511e-02 -6.06091499e-01
3.22227269e-01 -1.55622900e-01 3.90012354e-01 -6.44493163e-01
-4.25483555e-01 5.11364579e-01 -1.55453771e-01 -8.33924890e-01
-7.10083485e-01 -8.57004404e-01 -1.43186331e+00 2.76502281e-01
-3.26010585e-01 2.01878995e-01 3.87557417e-01 1.14642334e+00
3.08727503e-01 4.61045831e-01 5.69586515e-01 -1.08784544e+00
3.98300476e-02 -7.69579947e-01 -3.54778588e-01 3.26584876e-01
5.36161125e-01 -1.00354087e+00 -2.55996436e-01 3.36005151e-01] | [9.667292594909668, 0.6526778340339661] |
13ad19c7-43dc-44d4-991a-932ccc357eb4 | document-level-event-argument-extraction-by | 2104.05919 | null | https://arxiv.org/abs/2104.05919v1 | https://arxiv.org/pdf/2104.05919v1.pdf | Document-Level Event Argument Extraction by Conditional Generation | Event extraction has long been treated as a sentence-level task in the IE community. We argue that this setting does not match human information-seeking behavior and leads to incomplete and uninformative extraction results. We propose a document-level neural event argument extraction model by formulating the task as conditional generation following event templates. We also compile a new document-level event extraction benchmark dataset WikiEvents which includes complete event and coreference annotation. On the task of argument extraction, we achieve an absolute gain of 7.6% F1 and 5.7% F1 over the next best model on the RAMS and WikiEvents datasets respectively. On the more challenging task of informative argument extraction, which requires implicit coreference reasoning, we achieve a 9.3% F1 gain over the best baseline. To demonstrate the portability of our model, we also create the first end-to-end zero-shot event extraction framework and achieve 97% of fully supervised model's trigger extraction performance and 82% of the argument extraction performance given only access to 10 out of the 33 types on ACE. | ['Jiawei Han', 'Heng Ji', 'Sha Li'] | 2021-04-13 | null | https://aclanthology.org/2021.naacl-main.69 | https://aclanthology.org/2021.naacl-main.69.pdf | naacl-2021-4 | ['document-level-event-extraction'] | ['natural-language-processing'] | [ 5.28485537e-01 1.16680396e+00 -3.77095282e-01 -4.98498440e-01
-1.57031262e+00 -7.01022685e-01 1.00013864e+00 6.01483643e-01
-7.75817811e-01 1.05244684e+00 8.45907807e-01 -3.09806019e-01
3.68111581e-02 -7.01391876e-01 -9.67367232e-01 -3.46898846e-02
9.05869752e-02 5.98082304e-01 2.53396899e-01 -5.85044362e-02
-3.07686049e-02 -1.51093319e-01 -1.26197791e+00 9.13733602e-01
6.51034236e-01 8.43977928e-01 -3.49142253e-01 7.08677173e-01
-3.45176756e-02 1.20447397e+00 -7.50582814e-01 -9.04335082e-01
-1.15626745e-01 -1.96469337e-01 -1.42873847e+00 -7.55326927e-01
2.51057863e-01 -2.55217522e-01 -2.72928208e-01 5.33429682e-01
6.19997025e-01 -1.11487374e-01 7.26463735e-01 -9.98410463e-01
-2.39342511e-01 1.55876732e+00 -2.81393141e-01 4.75471050e-01
4.51327711e-01 -3.00910652e-01 1.47763085e+00 -8.01619172e-01
1.31082177e+00 1.11194515e+00 5.94629765e-01 3.73658806e-01
-1.07644892e+00 -5.50220072e-01 1.89578786e-01 2.41203919e-01
-6.45208657e-01 -5.91080070e-01 6.60857975e-01 -2.40995437e-02
1.56150639e+00 2.86523193e-01 3.82290453e-01 1.56317306e+00
-8.74878019e-02 1.29684067e+00 8.18690598e-01 -5.04558802e-01
1.78703126e-02 -1.80579782e-01 6.87918901e-01 4.55284357e-01
2.56402105e-01 -3.50834057e-02 -8.36141229e-01 -3.18194509e-01
4.79116775e-02 -5.35583556e-01 -8.56313407e-02 4.21254784e-01
-1.32545578e+00 8.63942921e-01 1.84589610e-01 5.69841936e-02
-6.95905149e-01 1.78969279e-01 7.65267074e-01 6.43853173e-02
3.95547241e-01 4.93986249e-01 -9.42052543e-01 -4.51676875e-01
-7.65525758e-01 6.76865935e-01 1.27184117e+00 9.10848618e-01
-6.04523309e-02 -3.57761353e-01 -6.21543825e-01 6.39070094e-01
-1.32792005e-02 2.51040399e-01 1.52729258e-01 -9.13856447e-01
9.72354889e-01 6.16218209e-01 3.20690513e-01 -4.97367859e-01
-4.99579817e-01 -4.90502775e-01 -2.30036288e-01 -2.68926233e-01
5.85259020e-01 -5.40797591e-01 -5.06732285e-01 2.12325120e+00
5.03111184e-01 -1.22763805e-01 5.02570987e-01 4.82389420e-01
1.18728054e+00 7.06370771e-01 4.62185204e-01 -4.07613307e-01
1.74338675e+00 -8.99182558e-01 -1.06084394e+00 -4.62716609e-01
7.61359334e-01 -6.53549790e-01 8.31297696e-01 2.52812207e-01
-1.44789076e+00 9.98443589e-02 -1.19413435e+00 -3.91537189e-01
-2.88655847e-01 2.37601809e-02 8.79648030e-01 -2.77013946e-02
-6.64547235e-02 4.78040099e-01 -8.96989882e-01 3.58267389e-02
4.60444450e-01 6.00580350e-02 -3.11680168e-01 4.10118878e-01
-1.63419867e+00 1.07521117e+00 8.86423230e-01 -3.50617737e-01
-6.61796868e-01 -1.01377797e+00 -8.22108090e-01 2.49089047e-01
9.16757107e-01 -5.79069257e-01 1.79138505e+00 -3.79420549e-01
-9.13059473e-01 9.60171998e-01 -2.00047985e-01 -9.37554121e-01
5.13866723e-01 -7.76953042e-01 -4.15465832e-01 1.83901295e-01
4.22666937e-01 4.69088346e-01 2.04935208e-01 -6.35344625e-01
-7.80643463e-01 -1.23658687e-01 -3.71670537e-02 2.03275204e-01
1.56082278e-02 4.58564550e-01 -1.64777771e-01 -6.81321383e-01
-2.49701232e-01 -7.55812049e-01 1.39025539e-01 -4.51613426e-01
-7.23741889e-01 -6.78090036e-01 6.76158249e-01 -8.55596542e-01
1.27161860e+00 -1.92226887e+00 7.09713390e-03 -3.26827943e-01
-1.08111827e-02 1.64168045e-01 5.18109314e-02 5.60371816e-01
-4.88954693e-01 9.78421867e-02 -3.09943378e-01 -2.89273173e-01
3.76799971e-01 9.87093672e-02 -5.85498273e-01 5.19178957e-02
5.89271605e-01 1.14221621e+00 -1.03350687e+00 -7.51567066e-01
-3.52927446e-01 3.94733012e-01 -6.96523309e-01 2.01928094e-01
-5.26946962e-01 -1.04804322e-01 -6.17956936e-01 4.05926079e-01
1.72244936e-01 -3.96861970e-01 3.85669500e-01 -4.27140236e-01
1.08331889e-02 1.34938228e+00 -1.05606019e+00 1.82439804e+00
-2.20423102e-01 5.52128077e-01 -1.54719099e-01 -8.29873323e-01
3.17668885e-01 7.62510300e-01 2.86551774e-01 -6.97054327e-01
1.27643794e-01 2.40682006e-01 2.87455786e-02 -3.03992927e-01
5.09164631e-01 2.51804926e-02 -6.58484638e-01 6.69102311e-01
3.88534874e-01 3.57986003e-01 4.74935740e-01 7.31913924e-01
1.39669812e+00 2.78450072e-01 6.48331583e-01 -2.16923505e-01
1.20662369e-01 2.24346951e-01 6.71921194e-01 9.11725402e-01
2.16543540e-01 4.40350950e-01 8.34811747e-01 -4.29978579e-01
-8.36930513e-01 -9.89048660e-01 -3.01376671e-01 9.85426366e-01
-3.81248236e-01 -9.20105159e-01 -7.57463574e-01 -1.22943938e+00
-2.64607370e-01 1.23305678e+00 -7.48813570e-01 1.38829097e-01
-9.72032070e-01 -1.12266779e+00 1.04452872e+00 7.14959443e-01
6.51145279e-01 -1.32286966e+00 -1.06444907e+00 5.38176835e-01
-9.12579656e-01 -1.40797830e+00 -1.82886407e-01 5.33293247e-01
-3.21208149e-01 -1.36102581e+00 -9.72387493e-02 -4.81517583e-01
-3.15287858e-02 -7.69291997e-01 1.66659975e+00 -1.95159055e-02
-2.22323239e-01 -1.16203137e-01 -3.79844576e-01 -8.66825640e-01
-3.57227802e-01 3.71419340e-01 -4.87988919e-01 -5.14072418e-01
5.19242048e-01 -4.53379720e-01 -4.84168112e-01 -3.08367431e-01
-6.63288295e-01 2.81704068e-01 4.45986271e-01 1.06916690e+00
4.98882234e-01 -3.41317683e-01 8.84234905e-01 -1.39100039e+00
6.35347605e-01 -4.77964848e-01 -2.02770382e-01 2.03995362e-01
-6.14245474e-01 3.41224909e-01 3.24674070e-01 -2.22727180e-01
-1.66261506e+00 -7.81632811e-02 -3.27478945e-01 5.33213973e-01
-1.64715275e-01 6.96590602e-01 -1.37747303e-01 1.06003606e+00
9.14303541e-01 -2.60281324e-01 -4.16987836e-01 -3.88698131e-01
5.07573605e-01 6.39495432e-01 9.59654272e-01 -8.61273468e-01
3.85955840e-01 3.28005701e-01 -2.84500271e-01 -3.30929428e-01
-1.70365322e+00 -1.55472621e-01 -2.20241457e-01 3.26364875e-01
1.00511241e+00 -9.62715685e-01 -7.85227835e-01 1.46338910e-01
-1.57427204e+00 -3.53965074e-01 -5.02442837e-01 2.63516188e-01
-5.18088877e-01 1.69935465e-01 -9.83061790e-01 -8.34388077e-01
-1.02011991e+00 -6.37205660e-01 1.17477429e+00 6.42553419e-02
-7.65624583e-01 -6.02557480e-01 1.58785835e-01 2.84400463e-01
-1.29617974e-01 6.17482543e-01 1.03244340e+00 -1.20847821e+00
-2.82962531e-01 -1.16087109e-01 -2.94176489e-01 -2.56857127e-01
-3.16702545e-01 -3.30267817e-01 -1.04368544e+00 3.02479744e-01
-1.96002796e-01 -5.72837472e-01 1.01863670e+00 1.18179947e-01
6.62028790e-01 -4.41208899e-01 -5.29887736e-01 1.78032368e-01
1.10489905e+00 3.37915793e-02 5.97762704e-01 5.26015639e-01
2.35574052e-01 6.17030621e-01 7.97259748e-01 3.90037119e-01
3.86260003e-01 6.40311420e-01 2.55825430e-01 5.39695583e-02
-3.65818441e-01 -5.22563934e-01 2.32507974e-01 2.45108068e-01
3.77353504e-02 -4.73551452e-01 -7.69264042e-01 8.19828570e-01
-2.16059422e+00 -1.36268795e+00 -3.07127625e-01 1.66744149e+00
1.38570774e+00 5.68536282e-01 1.18155994e-01 3.15435171e-01
2.97440976e-01 8.55125859e-02 -2.77799338e-01 -3.79928380e-01
-2.88416266e-01 5.87158084e-01 3.29878539e-01 4.72556084e-01
-1.44692099e+00 9.39064443e-01 5.94068146e+00 5.97689331e-01
-4.34122533e-01 1.87759995e-01 4.50696826e-01 -2.80057132e-01
-3.18528384e-01 1.75359339e-01 -1.20285153e+00 4.65513378e-01
1.40935993e+00 -1.84268668e-01 -7.71149844e-02 5.50304174e-01
-1.75544202e-01 -2.04497017e-02 -1.39426506e+00 5.74497700e-01
-1.08609617e-01 -1.70623159e+00 -1.76608995e-01 -1.30630419e-01
3.46012980e-01 1.73263267e-01 -4.43411261e-01 6.71911359e-01
6.54633045e-01 -8.53955269e-01 9.20640469e-01 1.41416743e-01
5.46985328e-01 -7.73106158e-01 6.86019123e-01 4.87651855e-01
-1.08661997e+00 2.12296844e-02 1.92882657e-01 6.88601509e-02
8.75188947e-01 5.72155774e-01 -1.04257596e+00 6.76533937e-01
6.64968371e-01 5.72195351e-01 -3.09024602e-01 5.49695611e-01
-7.35862970e-01 8.90556872e-01 -7.65407741e-01 -3.69404182e-02
1.49576485e-01 5.55506468e-01 7.95449078e-01 1.64779532e+00
-1.38629839e-01 3.74022752e-01 -1.19270571e-01 8.24435711e-01
-5.90210259e-01 -5.23972549e-02 -4.27728564e-01 -2.29415312e-01
5.78503549e-01 1.20073760e+00 -3.73730123e-01 -6.47794545e-01
-3.34441811e-01 8.62843156e-01 7.10800171e-01 5.47020771e-02
-1.20256233e+00 -6.05760217e-01 1.95197687e-01 -2.38731399e-01
2.92706221e-01 4.26581562e-01 -5.89059964e-02 -1.13522744e+00
1.43233106e-01 -8.65290642e-01 1.11704016e+00 -6.04227006e-01
-1.10306466e+00 5.05034566e-01 4.07841593e-01 -4.55107003e-01
-9.72662330e-01 -4.49598998e-01 -6.26185417e-01 6.37872934e-01
-1.45001614e+00 -1.32399464e+00 1.08771309e-01 2.38452956e-01
6.07028782e-01 1.36400327e-01 1.10220075e+00 4.78580266e-01
-3.29514831e-01 6.48973227e-01 -6.77349329e-01 6.06608570e-01
7.99543798e-01 -1.41431618e+00 5.75337112e-01 8.94829631e-01
1.87843934e-01 5.52866995e-01 8.26993108e-01 -7.99974382e-01
-1.24876976e+00 -1.06444752e+00 1.66147339e+00 -8.83254230e-01
6.10498667e-01 -3.24624479e-01 -7.88699567e-01 1.19903374e+00
6.10911191e-01 -2.79222488e-01 6.37251914e-01 6.31074369e-01
-5.34102201e-01 4.90430087e-01 -1.02464581e+00 6.86753392e-01
1.35194027e+00 -4.72009450e-01 -1.33777153e+00 4.42746520e-01
9.93647635e-01 -6.71001971e-01 -9.32421625e-01 6.76855087e-01
4.65256751e-01 -4.97924656e-01 1.14138460e+00 -1.02535486e+00
7.37921536e-01 6.25548735e-02 -1.24786124e-01 -7.19205916e-01
9.89480410e-03 -6.39692783e-01 -5.83252072e-01 1.49179924e+00
1.09861994e+00 -2.84801155e-01 5.22054493e-01 7.15800345e-01
-2.38314345e-01 -6.43614650e-01 -7.96538115e-01 -4.38442707e-01
4.56080362e-02 -6.62083387e-01 3.48024637e-01 7.70468473e-01
3.10469568e-01 1.07186115e+00 -1.55213997e-01 2.11572014e-02
6.43821061e-01 4.52343136e-01 4.18529540e-01 -1.21587610e+00
-5.07153988e-01 -9.07850489e-02 4.73112822e-01 -6.55456245e-01
5.25321662e-01 -1.09477115e+00 -9.28160362e-03 -1.58096576e+00
5.73474050e-01 5.26907034e-02 -2.17124328e-01 7.14933693e-01
-2.62768358e-01 -6.58240244e-02 -1.51120946e-01 -1.60374746e-01
-7.32489944e-01 3.29862535e-01 6.76061809e-01 1.46904979e-02
-4.21431214e-02 -4.08800155e-01 -9.33739960e-01 9.13265765e-01
5.49872160e-01 -7.35912263e-01 -2.60676324e-01 -4.26476836e-01
6.49911821e-01 3.49521965e-01 3.64877105e-01 -4.20704544e-01
1.44050717e-01 1.66129112e-01 2.93224782e-01 -8.96731257e-01
4.32597578e-01 -3.01870078e-01 6.29131049e-02 2.70694405e-01
-7.51085460e-01 7.80125335e-03 2.79757023e-01 6.03216529e-01
-1.74789026e-01 -3.43145132e-01 2.32604891e-01 -8.15538839e-02
-4.49883401e-01 -1.25893474e-01 -1.34413630e-01 8.27656209e-01
6.64508462e-01 3.81058156e-01 -6.84432626e-01 -6.72117025e-02
-8.14638972e-01 1.49063945e-01 -2.05704883e-01 2.46254116e-01
2.71539003e-01 -1.05112362e+00 -1.13143837e+00 -3.39115858e-01
4.80322056e-02 7.92627558e-02 -8.98150057e-02 7.80507088e-01
5.37178852e-02 4.04851198e-01 3.53197843e-01 -1.04155868e-01
-1.36950064e+00 3.15669477e-01 -7.06093535e-02 -8.75404954e-01
-8.69674683e-01 7.72858202e-01 -1.08693138e-01 -2.94366598e-01
1.45576611e-01 -2.63860464e-01 -2.24089473e-01 1.61191702e-01
6.38526857e-01 6.44880533e-02 1.90507546e-01 -5.68191819e-02
-5.36174476e-01 -3.12653810e-01 -4.03047889e-01 -5.32621741e-01
1.52491105e+00 4.91378248e-01 2.29112685e-01 5.31507544e-02
8.84907365e-01 1.63702682e-01 -1.00129724e+00 -6.68566450e-02
4.58587706e-01 2.02870205e-01 -7.74360150e-02 -1.40131366e+00
-4.63111788e-01 5.20858586e-01 -7.54853636e-02 1.14556789e-01
6.82151020e-01 4.41901445e-01 9.40175831e-01 6.75162911e-01
1.45579025e-03 -1.16051531e+00 -3.36520135e-01 6.09790444e-01
9.00310993e-01 -1.08337343e+00 -9.23838317e-02 -6.53861165e-01
-4.56345737e-01 5.91557741e-01 3.32526118e-01 -8.25283825e-02
3.03990275e-01 7.78436124e-01 -4.52175707e-01 -5.00468731e-01
-1.33831811e+00 5.21102920e-03 2.38361552e-01 7.17701241e-02
8.26457918e-01 -3.17895561e-02 -8.26785862e-01 1.29205739e+00
-3.30808401e-01 -1.69505421e-02 8.41789395e-02 1.01990986e+00
-9.81080309e-02 -1.19822025e+00 2.98651844e-01 4.32325304e-01
-1.22258127e+00 -3.64410311e-01 -5.21812260e-01 1.07492423e+00
-3.53874236e-01 8.84140909e-01 -1.08376838e-01 3.00214171e-01
5.23974478e-01 6.13170683e-01 4.55823600e-01 -5.05997062e-01
-1.00993073e+00 -8.87987912e-02 1.31738794e+00 -6.59817636e-01
-4.79124695e-01 -8.40564489e-01 -1.84193063e+00 3.05822468e-03
-2.41351932e-01 4.32100773e-01 3.71893585e-01 1.14447188e+00
4.82599527e-01 7.16412425e-01 -3.11901480e-01 -1.98812440e-01
-6.34843886e-01 -1.05438411e+00 1.82816818e-01 8.47051620e-01
-1.40712243e-02 -5.86159110e-01 -2.38285705e-01 1.05432585e-01] | [9.079776763916016, 9.192380905151367] |
d2ab8e1f-79d2-47fe-9086-1ad64e610c53 | stock-index-prediction-with-multi-task | 2008.07605 | null | https://arxiv.org/abs/2008.07605v1 | https://arxiv.org/pdf/2008.07605v1.pdf | Stock Index Prediction with Multi-task Learning and Word Polarity Over Time | Sentiment-based stock prediction systems aim to explore sentiment or event signals from online corpora and attempt to relate the signals to stock price variations. Both the feature-based and neural-networks-based approaches have delivered promising results. However, the frequently minor fluctuations of the stock prices restrict learning the sentiment of text from price patterns, and learning market sentiment from text can be biased if the text is irrelevant to the underlying market. In addition, when using discrete word features, the polarity of a certain term can change over time according to different events. To address these issues, we propose a two-stage system that consists of a sentiment extractor to extract the opinion on the market trend and a summarizer that predicts the direction of the index movement of following week given the opinions of the news over the current week. We adopt BERT with multitask learning which additionally predicts the worthiness of the news and propose a metric called Polarity-Over-Time to extract the word polarity among different event periods. A Weekly-Monday prediction framework and a new dataset, the 10-year Reuters financial news dataset, are also proposed. | ['Kerstin Voigt', 'Yue Zhou'] | 2020-08-17 | null | null | null | null | ['stock-prediction'] | ['time-series'] | [-3.51433992e-01 -5.38318217e-01 -6.18965387e-01 -6.15573049e-01
-4.41181660e-01 -6.40840888e-01 7.49100924e-01 2.46053800e-01
-3.76823723e-01 7.89979935e-01 7.15941846e-01 -1.33826479e-01
2.88592018e-02 -1.03007388e+00 -4.25820589e-01 -4.76782441e-01
1.00169100e-01 -7.18708634e-02 2.46721670e-01 -5.99278033e-01
8.74498010e-01 -1.03707975e-02 -1.24028099e+00 4.64381158e-01
3.77285779e-01 1.58797204e+00 -2.26258729e-02 2.71313041e-01
-6.80837452e-01 1.25603819e+00 -8.21637750e-01 -1.94068611e-01
2.07752869e-01 -3.35740685e-01 -2.37810105e-01 -3.84078138e-02
-2.32907131e-01 -6.50568530e-02 -3.51196118e-02 9.45850551e-01
1.74143180e-01 -1.76494956e-01 4.81579870e-01 -1.01916230e+00
-6.10986471e-01 8.75603080e-01 -6.17470026e-01 7.63173580e-01
-1.02097355e-01 -3.33482653e-01 1.47961831e+00 -8.06778073e-01
3.83747905e-01 5.85983336e-01 4.05218452e-01 -6.14783801e-02
-5.52530348e-01 -7.53309727e-01 6.85971141e-01 1.35212466e-01
-5.04946351e-01 -1.32440731e-01 1.27097321e+00 -5.89912474e-01
7.26623237e-01 3.04541439e-02 8.42726350e-01 9.80703235e-01
8.22576880e-01 6.74102724e-01 1.19756055e+00 -1.74226929e-02
3.01429898e-01 4.06502992e-01 4.40860540e-01 -5.30163832e-02
1.34559050e-01 -2.93912083e-01 -9.83326554e-01 -3.26538295e-01
-4.37294208e-02 4.18348342e-01 -1.08326860e-01 1.03990324e-01
-1.12578833e+00 1.00803781e+00 2.56106675e-01 4.19342935e-01
-7.46977150e-01 -4.56387460e-01 6.60865963e-01 6.46747351e-01
1.28750348e+00 3.55768651e-01 -1.27175748e+00 -8.25105831e-02
-1.02864254e+00 4.95115638e-01 1.09549725e+00 2.08829790e-01
5.93960702e-01 2.71525294e-01 1.13298021e-01 4.51238751e-01
3.85115892e-01 5.15978515e-01 1.27972031e+00 -3.84510681e-03
6.10090852e-01 5.90616584e-01 2.56967753e-01 -1.36731660e+00
-6.51744902e-01 -5.97780287e-01 -4.23271179e-01 6.37327181e-03
1.39826521e-01 -7.32238412e-01 -4.05469656e-01 1.37290907e+00
1.25513345e-01 1.94394544e-01 2.19465062e-01 4.27980155e-01
7.38818884e-01 1.05675900e+00 -2.66771644e-01 -6.76745892e-01
1.17164922e+00 -6.18646622e-01 -8.98180246e-01 -4.14886326e-01
3.01052928e-01 -6.73555791e-01 5.39779723e-01 4.35772151e-01
-6.68645680e-01 -2.18456835e-01 -1.20377302e+00 5.67562044e-01
-8.16968441e-01 -1.40131146e-01 4.34668034e-01 2.64858484e-01
-3.46793622e-01 5.96742332e-01 -5.46710908e-01 4.28984225e-01
-7.67409801e-02 -1.52911376e-02 3.01217556e-01 7.61998951e-01
-1.52881753e+00 9.53401625e-01 3.91357571e-01 4.67577390e-02
8.11112300e-03 -5.75406611e-01 -6.04128063e-01 1.07368425e-01
3.07448745e-01 -5.50984591e-02 1.16351342e+00 -1.25461507e+00
-1.48098552e+00 2.35556334e-01 -2.22347751e-02 -6.11311555e-01
2.35451967e-01 1.60485581e-02 -9.49518383e-01 -2.99472511e-01
2.01378316e-01 -3.86869639e-01 9.87151086e-01 -3.18386376e-01
-1.21233189e+00 -3.62244546e-01 -1.77546665e-01 9.30820182e-02
-5.93316734e-01 1.45032451e-01 1.16616480e-01 -1.04272676e+00
1.11148683e-02 -6.46043241e-01 3.07547543e-02 -9.18386281e-01
-1.42426684e-01 -4.64750677e-01 6.94229245e-01 -4.05325860e-01
1.35959482e+00 -2.07083416e+00 -3.73968154e-01 3.23180884e-01
-2.38881797e-01 -2.42060393e-01 9.97488052e-02 3.80134255e-01
-1.13868631e-01 -1.76131919e-01 2.06083164e-01 1.55491069e-01
-4.22283337e-02 -1.42218396e-01 -1.09208214e+00 3.00384670e-01
1.90122366e-01 6.65626884e-01 -5.03367424e-01 -4.26990073e-03
-3.30292314e-01 -1.81550980e-02 -1.38940334e-01 -5.77372238e-02
-4.36216354e-01 2.03305148e-02 -6.89517260e-01 4.47510719e-01
2.34133363e-01 -3.60981524e-01 -5.31936660e-02 -4.77708131e-02
-5.74043512e-01 8.40107501e-01 -1.13413489e+00 7.99983799e-01
-3.44366729e-01 6.05858445e-01 -4.24554169e-01 -1.13849866e+00
1.19063532e+00 3.57082844e-01 4.62979257e-01 -7.75206983e-01
1.95696920e-01 4.48052257e-01 -6.56593740e-02 -2.19923809e-01
7.10593104e-01 -2.55578429e-01 -2.54689336e-01 6.84455276e-01
-3.22426826e-01 -6.42113993e-03 3.70454639e-01 -2.84022212e-01
6.10017717e-01 -2.17815325e-01 4.04067278e-01 -2.92577177e-01
4.33299571e-01 -5.24710678e-03 8.04579258e-01 2.48642161e-01
1.46494210e-01 2.30808482e-01 7.75879800e-01 -9.43231881e-01
-5.53600430e-01 -4.06570852e-01 -1.65184125e-01 1.22892988e+00
5.51991053e-02 -2.10912377e-01 -6.74749166e-03 -5.50485909e-01
1.51642919e-01 7.13972986e-01 -7.54502654e-01 1.70059279e-01
-2.98957795e-01 -1.43170929e+00 -2.27857053e-01 2.44651049e-01
2.67131090e-01 -1.18905699e+00 -4.56545353e-01 5.09169996e-01
-9.03623104e-02 -8.25684607e-01 -4.38992232e-01 5.40549874e-01
-5.62796772e-01 -8.71533334e-01 -6.45541668e-01 -6.41995728e-01
2.10439816e-01 -1.44445896e-01 9.23679292e-01 -5.06736457e-01
6.18381619e-01 -2.47092187e-01 -3.90651554e-01 -1.14720953e+00
1.14187233e-01 3.72778803e-01 5.82322432e-03 4.82787162e-01
5.59996665e-01 -3.93073320e-01 -4.11787659e-01 3.48590016e-02
-7.54133523e-01 -3.36569428e-01 3.45843017e-01 5.74258089e-01
4.58659172e-01 3.90247911e-01 1.21302378e+00 -9.01800513e-01
1.04799068e+00 -8.91664207e-01 -7.19453037e-01 2.67382432e-02
-1.08315241e+00 8.25842172e-02 6.88946247e-01 -4.87731040e-01
-1.03114486e+00 -3.84276658e-01 2.01580346e-01 3.18309993e-01
5.06511450e-01 1.29161191e+00 3.61187249e-01 5.57502806e-01
2.10473940e-01 5.51180124e-01 -2.82932371e-01 -2.65958756e-01
-1.86387330e-01 6.87136233e-01 1.96034208e-01 -2.94274073e-02
5.94758868e-01 4.38423097e-01 -4.02589768e-01 -4.78073925e-01
-1.50955915e+00 -4.51350242e-01 -1.43221244e-01 -1.22361585e-01
4.66193438e-01 -1.13556194e+00 -2.78294563e-01 8.41677666e-01
-9.54257131e-01 1.08278915e-01 -2.20466033e-01 7.01089561e-01
-1.65763646e-01 -1.53110296e-01 -6.48649931e-01 -7.23020673e-01
-6.05294585e-01 -8.27261209e-01 3.82765800e-01 2.80571818e-01
-3.77008677e-01 -1.07409596e+00 5.78770757e-01 -1.89681530e-01
5.85926652e-01 2.58529395e-01 7.72364497e-01 -1.37532115e+00
-1.21629551e-01 -6.12943649e-01 3.20472009e-02 4.01559651e-01
5.89277744e-01 1.33409783e-01 -6.03483677e-01 8.97739604e-02
6.14086926e-01 -1.46506444e-01 9.42132235e-01 7.11294234e-01
4.85961378e-01 -5.21908045e-01 1.11587361e-01 2.38800123e-01
1.15073109e+00 4.07323271e-01 2.91935401e-03 1.03234553e+00
2.07431108e-01 4.47975546e-01 4.99004453e-01 8.08479548e-01
5.92455566e-01 1.32818028e-01 4.06959802e-02 2.73471534e-01
7.92192638e-01 -8.32264051e-02 7.27384686e-01 1.29213023e+00
1.43239945e-01 -3.19726169e-02 -5.16578555e-01 5.41388452e-01
-1.75765467e+00 -1.02617681e+00 -2.16526887e-03 1.66328645e+00
8.09395015e-01 8.89788568e-01 1.59768969e-01 1.76262870e-01
5.55821478e-01 9.25295830e-01 -6.81279182e-01 -1.82711765e-01
-5.01771152e-01 -1.32750079e-01 6.91164017e-01 1.72725439e-01
-1.25357807e+00 4.49066430e-01 5.84801817e+00 4.17212456e-01
-1.65781355e+00 -2.26415247e-01 8.27976048e-01 -2.69228488e-01
-4.42046463e-01 -2.40994871e-01 -1.13779163e+00 8.78657520e-01
9.43112791e-01 -7.46058404e-01 -1.24649316e-01 1.00406086e+00
4.50960934e-01 -2.46648621e-02 -6.69245720e-01 5.80231547e-01
2.92923719e-01 -1.43865991e+00 4.03533094e-02 -1.92955025e-02
8.57337832e-01 5.79650760e-01 2.77669817e-01 2.36116126e-01
-9.68216285e-02 -1.03379324e-01 1.09145081e+00 6.97253406e-01
-1.87781870e-01 -8.82059216e-01 1.01389003e+00 5.19442677e-01
-1.22762072e+00 -9.42539871e-02 -2.56971627e-01 -5.84467828e-01
1.42996103e-01 1.02967322e+00 -4.44584697e-01 3.65517706e-01
6.87750936e-01 1.13041317e+00 -4.03119981e-01 4.98634875e-01
-1.32077247e-01 5.97656906e-01 -1.50741115e-01 -6.27322614e-01
3.21876705e-01 -3.12001407e-01 3.81675929e-01 8.31675708e-01
4.38942522e-01 -6.52936613e-03 1.05297439e-01 3.01398933e-01
-1.97636217e-01 6.03292942e-01 -4.71446663e-01 -1.05870105e-01
1.55505287e-02 1.21498561e+00 -7.97957480e-01 -4.96204048e-01
-1.00439000e+00 4.77455199e-01 -7.42910579e-02 2.31399238e-01
-3.95176560e-01 -4.65971082e-01 5.94236851e-01 -9.31413695e-02
6.48192942e-01 5.60092591e-02 -4.92455512e-01 -1.48190570e+00
2.93709576e-01 -6.74062788e-01 2.81310171e-01 -5.51634192e-01
-1.55494881e+00 7.25052774e-01 -3.92260373e-01 -1.36041367e+00
-4.23248261e-01 -5.26474118e-01 -1.11565042e+00 7.16223121e-01
-2.04520750e+00 -2.98939109e-01 4.51048911e-01 4.32312459e-01
7.33602285e-01 -6.95710003e-01 4.45323616e-01 -2.32662618e-01
-3.94536763e-01 -1.59849584e-01 4.71577227e-01 4.42066222e-01
6.93105817e-01 -1.20127034e+00 5.47970057e-01 6.56787395e-01
2.09899515e-01 1.50355086e-01 6.86156392e-01 -7.15698898e-01
-9.43640292e-01 -9.30676222e-01 1.32358599e+00 -2.88106769e-01
1.57602453e+00 6.01544566e-02 -8.04820478e-01 5.33244133e-01
2.54740775e-01 -2.45791420e-01 8.69573712e-01 1.31098762e-01
-3.31722140e-01 -4.06759501e-01 -6.27986908e-01 3.93742055e-01
-4.97564189e-02 -4.80450869e-01 -1.12847400e+00 1.94917127e-01
6.28779829e-01 -1.43539280e-01 -6.13452971e-01 2.37737462e-01
6.76906466e-01 -7.26498723e-01 3.90660524e-01 -4.17485744e-01
5.15875638e-01 -2.14390501e-01 -1.04934983e-01 -1.82418668e+00
-1.76076293e-01 -2.81559467e-01 8.31676573e-02 1.09840906e+00
9.37018633e-01 -1.04014516e+00 5.92937529e-01 6.51339412e-01
3.31231833e-01 -6.63478196e-01 -6.85350835e-01 -4.06017244e-01
-5.19014746e-02 -4.58201259e-01 8.39695513e-01 9.85917747e-01
4.55544204e-01 4.70610023e-01 -4.70693022e-01 2.91304267e-03
6.24215417e-02 7.27690041e-01 3.59120429e-01 -1.45555663e+00
-1.09560698e-01 -5.76111138e-01 2.01828349e-02 -7.80187488e-01
3.36757869e-01 -6.25828326e-01 -1.63286552e-01 -1.03853846e+00
-1.65929511e-01 3.19403648e-01 -8.42717171e-01 6.33323053e-03
-1.40942156e-01 -9.18000117e-02 7.44558945e-02 4.74510491e-01
-3.13274503e-01 5.22112727e-01 9.56715524e-01 -3.73147368e-01
-4.54681396e-01 5.79490006e-01 -7.21235752e-01 1.02470517e+00
9.97269213e-01 -5.39346516e-01 -1.36369288e-01 -3.34930955e-03
1.05223012e+00 7.94854760e-02 -4.03848469e-01 -5.35030842e-01
3.93460631e-01 -3.66448700e-01 5.26425362e-01 -1.03471231e+00
-9.15770307e-02 -6.49338543e-01 -2.50542283e-01 3.13364029e-01
-5.46713412e-01 4.99385118e-01 -1.69745862e-01 5.84662974e-01
-8.06991756e-01 -1.77463263e-01 1.86550185e-01 -2.48968855e-01
-4.96400833e-01 2.93178290e-01 -6.79610848e-01 9.27444324e-02
6.93554997e-01 1.80749297e-01 -2.94323057e-01 -5.69089055e-01
-3.22359085e-01 3.64803731e-01 -2.49194115e-01 7.45903313e-01
3.31407279e-01 -1.11955285e+00 -1.00140154e+00 2.44479716e-01
-1.78726539e-02 -4.75693166e-01 -3.61613035e-02 5.55144966e-01
-1.27466582e-02 4.54368830e-01 8.90923589e-02 3.37473042e-02
-7.86819518e-01 3.07824105e-01 1.27076015e-01 -4.58429217e-01
-1.53604269e-01 4.40558195e-01 1.65361185e-02 3.92100960e-02
-3.69401388e-02 -6.93418920e-01 -8.79006743e-01 1.26580012e+00
8.08620214e-01 9.93893594e-02 2.53190875e-01 -5.01820922e-01
-1.07032217e-01 5.19503534e-01 -3.37437391e-01 -8.20524022e-02
1.90172613e+00 -1.75479636e-01 -2.48539716e-01 1.24717081e+00
9.84661758e-01 9.45576727e-02 -1.02633238e+00 -5.43775618e-01
6.85921013e-01 -1.55169005e-03 2.21260175e-01 -5.16379476e-01
-1.22719920e+00 1.64513379e-01 1.10241681e-01 9.45868909e-01
9.22058761e-01 -1.62407219e-01 9.46105838e-01 5.06776035e-01
-3.89631316e-02 -1.56756723e+00 -2.08014905e-01 8.23012710e-01
7.15061843e-01 -1.32571745e+00 -3.41780446e-02 3.19006562e-01
-8.28817844e-01 1.38429773e+00 -2.34340113e-02 -3.43435138e-01
1.50763428e+00 2.26576179e-01 5.22223830e-01 -2.62694061e-01
-1.06315279e+00 3.98371704e-02 3.83020669e-01 -1.23720549e-01
4.63282883e-01 -6.88841417e-02 -4.53220427e-01 8.43575656e-01
-5.99809170e-01 -1.99171975e-02 6.78662837e-01 8.13391268e-01
-6.38756037e-01 -7.39915907e-01 -1.87269777e-01 7.36921370e-01
-1.18723202e+00 -1.01604663e-01 -3.39372903e-01 2.97660321e-01
-1.76205009e-01 8.51960182e-01 4.70052391e-01 -2.11196706e-01
4.78272557e-01 4.31728721e-01 -6.21328115e-01 -5.03496349e-01
-6.88977063e-01 2.76190937e-01 1.53357182e-02 -9.30549279e-02
-8.87029350e-01 -8.75476599e-01 -1.01564050e+00 1.79268457e-02
-3.53024095e-01 3.86755079e-01 8.24980319e-01 1.37940967e+00
2.33342480e-02 4.50151920e-01 1.42877138e+00 -6.24902427e-01
-6.13537490e-01 -1.04861677e+00 -1.02003527e+00 1.49260953e-01
7.19803214e-01 -2.46510208e-01 -6.98053479e-01 1.71814300e-02] | [4.418448448181152, 4.332669258117676] |
83497d4d-ef71-4ece-9281-e11d4b3354e3 | visual-entailment-a-novel-task-for-fine | 1901.06706 | null | http://arxiv.org/abs/1901.06706v1 | http://arxiv.org/pdf/1901.06706v1.pdf | Visual Entailment: A Novel Task for Fine-Grained Image Understanding | Existing visual reasoning datasets such as Visual Question Answering (VQA),
often suffer from biases conditioned on the question, image or answer
distributions. The recently proposed CLEVR dataset addresses these limitations
and requires fine-grained reasoning but the dataset is synthetic and consists
of similar objects and sentence structures across the dataset.
In this paper, we introduce a new inference task, Visual Entailment (VE) -
consisting of image-sentence pairs whereby a premise is defined by an image,
rather than a natural language sentence as in traditional Textual Entailment
tasks. The goal of a trained VE model is to predict whether the image
semantically entails the text. To realize this task, we build a dataset SNLI-VE
based on the Stanford Natural Language Inference corpus and Flickr30k dataset.
We evaluate various existing VQA baselines and build a model called Explainable
Visual Entailment (EVE) system to address the VE task. EVE achieves up to 71%
accuracy and outperforms several other state-of-the-art VQA based models.
Finally, we demonstrate the explainability of EVE through cross-modal attention
visualizations. The SNLI-VE dataset is publicly available at
https://github.com/ necla-ml/SNLI-VE. | ['Asim Kadav', 'Ning Xie', 'Derek Doran', 'Farley Lai'] | 2019-01-20 | null | null | null | null | ['visual-entailment'] | ['reasoning'] | [-1.69340502e-02 2.17718527e-01 1.35229632e-01 -7.72558510e-01
-7.65500665e-01 -6.89127564e-01 8.53357017e-01 -1.62840217e-01
-7.62194544e-02 5.20593584e-01 4.11385000e-01 -7.21647620e-01
4.34782624e-01 -6.67734861e-01 -1.27767050e+00 5.04962541e-02
5.07304847e-01 5.81067324e-01 3.88017036e-02 -8.61797184e-02
3.08178931e-01 1.08745635e-01 -1.46338463e+00 1.16361415e+00
6.92311943e-01 9.25547540e-01 2.09488422e-01 1.07584906e+00
-3.13138604e-01 1.62108922e+00 -5.73334694e-01 -8.96897018e-01
-1.76256120e-01 -7.31117368e-01 -1.36351824e+00 2.47473791e-02
1.10180140e+00 -5.88744283e-01 -4.73753929e-01 9.67326164e-01
-7.89896958e-03 -4.76378091e-02 9.38970625e-01 -1.80439961e+00
-1.68636644e+00 5.22668839e-01 -4.15426850e-01 1.82279348e-01
6.96731508e-01 4.62755829e-01 1.45381606e+00 -1.38547277e+00
8.13699126e-01 1.58687079e+00 3.62119019e-01 7.22592652e-01
-1.30212224e+00 -3.90948862e-01 2.18130246e-01 6.50852501e-01
-1.31826901e+00 -4.14954543e-01 8.53064597e-01 -4.72145259e-01
1.14235401e+00 5.80915749e-01 6.29567623e-01 1.26528573e+00
1.16369538e-01 1.20529366e+00 1.12333643e+00 -2.67919153e-01
1.05382286e-01 6.70277234e-03 2.55867928e-01 1.08454430e+00
-1.74171060e-01 -1.57372370e-01 -4.64064896e-01 3.17777008e-01
5.93912899e-01 -7.45059475e-02 -3.98574650e-01 -4.28850412e-01
-1.40879548e+00 9.50096548e-01 9.76603210e-01 -5.90582518e-03
-1.46440268e-01 7.20467210e-01 3.97210032e-01 2.54994214e-01
1.88525826e-01 4.47835475e-01 -7.02826828e-02 2.91846395e-01
-7.13704467e-01 4.54181582e-01 6.32582664e-01 1.11670947e+00
6.68484867e-01 -1.39486551e-01 -5.96472204e-01 2.49982610e-01
5.15126884e-01 5.56760311e-01 -3.68582271e-02 -1.24868584e+00
7.35027134e-01 7.60375142e-01 7.09006786e-02 -9.01301086e-01
-1.02423757e-01 1.19806513e-01 -7.39430845e-01 2.73008078e-01
5.16027510e-01 3.83019865e-01 -1.11121833e+00 1.61360037e+00
2.73420930e-01 1.65440105e-02 2.37298951e-01 1.16935027e+00
1.64312434e+00 9.38235044e-01 3.87317449e-01 3.38000864e-01
1.62778449e+00 -1.29357016e+00 -8.14392328e-01 -4.23179805e-01
3.46255392e-01 -6.06865406e-01 1.96049261e+00 8.71473029e-02
-1.16078794e+00 -7.12170005e-01 -9.96971965e-01 -8.55375767e-01
-4.82782960e-01 1.33227214e-01 4.36333477e-01 5.32064885e-02
-1.12039113e+00 -1.61030814e-01 -4.02450234e-01 -1.06391937e-01
7.89272904e-01 -3.30167562e-01 -3.97719443e-01 -4.64595824e-01
-1.16384792e+00 9.36825693e-01 5.16313128e-02 1.91141263e-01
-1.43983710e+00 -7.89476573e-01 -1.31501627e+00 1.68423295e-01
2.37014696e-01 -1.18751180e+00 1.40452600e+00 -1.20700574e+00
-8.15025628e-01 1.38176966e+00 -4.85321134e-01 -4.40705299e-01
6.48160577e-01 -2.95496851e-01 -2.15306073e-01 4.16150481e-01
2.98213810e-01 9.73996162e-01 8.82299840e-01 -1.57343853e+00
-6.94269128e-03 -2.73498595e-01 7.72870779e-01 6.11149929e-02
4.66003418e-01 -2.37292156e-01 -4.99859512e-01 -4.15274084e-01
-3.15637350e-01 -5.30833185e-01 1.71423241e-01 3.93051267e-01
-7.40452051e-01 -4.33552474e-01 8.03993762e-01 -6.99599028e-01
7.68611312e-01 -2.06620836e+00 2.03418434e-01 -3.10279518e-01
5.14836133e-01 -8.07264894e-02 -3.10596019e-01 3.87638152e-01
-1.70174569e-01 2.15752393e-01 -2.26809949e-01 -4.38145250e-01
4.33665186e-01 5.07937789e-01 -5.86631477e-01 3.03580374e-01
6.82988763e-01 1.64705265e+00 -7.98998535e-01 -9.22255754e-01
3.72895002e-01 4.99897629e-01 -5.95619023e-01 4.32690531e-01
-7.75479794e-01 2.98613161e-01 -2.47614771e-01 7.09331632e-01
5.38138747e-01 -7.93803513e-01 -1.64579824e-01 -7.05410361e-01
2.75557637e-01 -3.56837288e-02 -5.47132373e-01 1.87141800e+00
-3.96922588e-01 1.15790927e+00 -2.90113866e-01 -9.02454913e-01
6.55443013e-01 1.32570520e-01 -3.75434339e-01 -9.77596045e-01
1.49106860e-01 -3.47587794e-01 -3.64421397e-01 -9.73368227e-01
5.00438631e-01 -1.80129081e-01 -1.18512884e-01 3.63199353e-01
6.75087795e-02 -4.86465782e-01 1.86016500e-01 8.73362362e-01
7.99563348e-01 3.13425630e-01 2.63743013e-01 -2.27281619e-02
5.46580970e-01 3.71450841e-01 3.01347077e-02 8.52417886e-01
-5.26258171e-01 7.34991372e-01 7.74889112e-01 -6.19801044e-01
-1.17645848e+00 -1.50130939e+00 5.31177176e-03 9.92244244e-01
5.31365454e-01 -4.67264295e-01 -6.58696413e-01 -9.64771807e-01
1.30279571e-01 1.30336785e+00 -1.08867252e+00 4.86814752e-02
-3.05973262e-01 1.39662847e-01 6.30646110e-01 6.96508110e-01
6.70665205e-01 -1.44933558e+00 -5.46686769e-01 -5.29154718e-01
-7.23409593e-01 -1.37436557e+00 -3.77753377e-01 -4.40968961e-01
-2.21081793e-01 -1.24049938e+00 -2.84713954e-01 -8.04260969e-01
7.33569980e-01 1.72346027e-03 2.01159978e+00 3.96275491e-01
-3.44527364e-01 7.97265708e-01 -3.11897784e-01 -4.90166813e-01
-4.43274379e-01 -5.61911762e-01 -6.28095031e-01 -1.27399281e-01
4.34490174e-01 1.33016437e-01 -8.44852328e-01 2.03517545e-02
-1.00810826e+00 6.11077189e-01 3.93384665e-01 8.11487734e-01
9.63038862e-01 -5.44629395e-01 4.30961341e-01 -9.07374084e-01
4.96406913e-01 -4.00517136e-01 -1.97928548e-01 7.04616010e-01
-1.14198476e-01 1.85389742e-01 4.64583248e-01 -1.80816755e-01
-1.29783356e+00 3.38053443e-02 -2.21342951e-01 -5.87162554e-01
-3.17197353e-01 3.84558022e-01 -2.65778184e-01 4.52165812e-01
7.24648595e-01 1.33830428e-01 -6.49640039e-02 1.31687120e-01
1.20168424e+00 4.27644879e-01 9.22587991e-01 -4.68218029e-01
6.22259319e-01 5.93731880e-01 -1.76938131e-01 -5.52629650e-01
-1.32794869e+00 -1.01647682e-01 -5.15161455e-01 -5.12542188e-01
1.40279484e+00 -9.83339250e-01 -9.12313402e-01 -1.77568942e-01
-1.58581960e+00 -5.15240073e-01 -3.05520177e-01 -7.18530193e-02
-7.50313997e-01 2.85047263e-01 -5.47288656e-01 -6.37631357e-01
-4.82187778e-01 -1.16524887e+00 1.22434533e+00 2.30036564e-02
-4.72534716e-01 -9.23904538e-01 -1.78571209e-01 1.00161111e+00
2.04030409e-01 5.17736137e-01 1.05156016e+00 -2.27302909e-01
-8.86044145e-01 1.23340681e-01 -8.21301877e-01 1.18902802e-01
-3.57990682e-01 1.99009940e-01 -9.96442914e-01 9.57345590e-02
-1.95120707e-01 -1.09738517e+00 9.87005770e-01 3.12360227e-01
1.46337485e+00 -3.03268373e-01 -1.28675113e-02 3.50933582e-01
1.46278274e+00 -3.32596809e-01 8.60525668e-01 1.87545139e-02
1.03867495e+00 5.14008820e-01 6.95033610e-01 5.53171290e-03
8.81392956e-01 2.62460977e-01 1.02827513e+00 -3.97236258e-01
-5.58207810e-01 -5.10319471e-01 1.37053728e-01 2.96970248e-01
2.10434988e-01 -3.59332830e-01 -9.76831496e-01 7.24932075e-01
-1.93443048e+00 -1.24567592e+00 -5.68652570e-01 1.33092105e+00
7.53589809e-01 -2.33435079e-01 -2.09095389e-01 -2.12305188e-01
3.21402341e-01 2.73154646e-01 -6.20832920e-01 -6.76543236e-01
-1.38582975e-01 -5.71727380e-02 -2.75666118e-01 7.47234941e-01
-9.86798406e-01 9.38404381e-01 5.89574432e+00 4.07887071e-01
-6.30168498e-01 8.68077502e-02 8.08548987e-01 -1.03184193e-01
-8.75698268e-01 -3.92171293e-02 -2.31906220e-01 3.62654752e-03
4.75738287e-01 1.66342333e-01 3.27874839e-01 8.02119195e-01
-8.96152928e-02 -1.15518451e-01 -1.53152561e+00 1.08243155e+00
6.04660869e-01 -1.66910613e+00 4.90398645e-01 -5.63269436e-01
4.84024137e-01 -6.25674352e-02 1.77292362e-01 5.19869328e-01
2.95864463e-01 -1.60510111e+00 1.09583497e+00 7.05415606e-01
1.03424144e+00 -4.99565482e-01 6.26959383e-01 1.07053414e-01
-1.20859873e+00 2.73900479e-01 -3.41751903e-01 -1.71252862e-01
3.95523608e-01 1.88832045e-01 -6.44552886e-01 3.61178666e-01
9.17544425e-01 7.03986287e-01 -8.28034580e-01 3.75531763e-01
-7.60264575e-01 4.20941144e-01 3.21555346e-01 -1.79245025e-01
3.36546779e-01 1.66380242e-01 2.32979462e-01 1.13483918e+00
-1.73196316e-01 1.17584601e-01 -2.33381733e-01 1.66379368e+00
-3.70759904e-01 -2.66211838e-01 -7.80741751e-01 -6.60772473e-02
2.39204228e-01 1.14331269e+00 -2.85607755e-01 -5.60211480e-01
-7.15467215e-01 1.34486711e+00 8.60495090e-01 7.00808525e-01
-1.28880215e+00 -1.94795653e-01 5.02496541e-01 -1.73418209e-01
3.85232955e-01 6.06674030e-02 -1.86270595e-01 -1.27544761e+00
-9.00167157e-04 -1.04367650e+00 5.99136591e-01 -1.77996707e+00
-1.50429749e+00 6.52153671e-01 -1.63849428e-01 -7.72179782e-01
-4.84297127e-02 -8.50270391e-01 -5.78272521e-01 7.31647015e-01
-1.52276683e+00 -1.70357084e+00 -7.76318192e-01 9.48626697e-01
8.30100000e-01 2.30408341e-01 7.45168507e-01 -7.08781034e-02
-2.48821855e-01 3.36911887e-01 -6.87431872e-01 3.32861125e-01
5.67602754e-01 -1.48652709e+00 5.77338040e-01 7.72534549e-01
6.56163514e-01 3.91113043e-01 9.42801654e-01 -3.99411350e-01
-1.47265983e+00 -1.25139248e+00 9.40799475e-01 -1.28247535e+00
6.47353888e-01 -4.54719067e-01 -9.49956179e-01 1.24335051e+00
7.94947088e-01 2.86611497e-01 4.97859806e-01 -2.11265504e-01
-7.68663168e-01 2.30069906e-01 -1.05577052e+00 8.31593335e-01
1.06411147e+00 -9.77842629e-01 -1.01494801e+00 3.76807839e-01
1.07870853e+00 -5.46043217e-01 -6.81792140e-01 2.57105380e-01
5.54613352e-01 -1.09407246e+00 1.22017109e+00 -1.13754773e+00
1.31588793e+00 -5.40695786e-01 -4.28604692e-01 -1.06367838e+00
-2.75729954e-01 2.03325078e-01 -2.84100980e-01 1.22218180e+00
6.02435172e-01 1.46125769e-02 5.18758476e-01 7.32152879e-01
-2.55062860e-02 -7.52044320e-01 -7.46176660e-01 -3.06245893e-01
-2.91525852e-03 -5.90685070e-01 5.78281820e-01 9.53730285e-01
-1.43039286e-01 9.52804983e-01 -3.53955865e-01 2.41657615e-01
6.90907359e-01 6.27327323e-01 1.05417430e+00 -4.62379575e-01
-3.79320413e-01 -1.72061309e-01 -2.83237308e-01 -1.13037038e+00
3.52202594e-01 -1.00117421e+00 5.54864295e-02 -2.19451237e+00
6.02506995e-01 2.16615394e-01 1.51384130e-01 4.69689906e-01
-3.55494738e-01 5.21670222e-01 3.13137352e-01 -1.16314396e-01
-1.17066920e+00 6.91837609e-01 1.71717668e+00 -6.48963630e-01
4.28785414e-01 -7.08175123e-01 -6.05946362e-01 7.22609103e-01
6.38446093e-01 1.48681561e-02 -6.63414419e-01 -9.69938874e-01
4.48368907e-01 1.90354824e-01 1.06140089e+00 -3.26337188e-01
-6.60613105e-02 -1.03489764e-01 7.52272964e-01 -9.45523977e-01
3.62365484e-01 -7.88270891e-01 -2.75285030e-03 2.52323747e-01
-5.99175155e-01 4.27105874e-01 1.37413159e-01 6.17267489e-01
-4.46089149e-01 6.32794797e-02 4.59017426e-01 -1.86388999e-01
-1.14091015e+00 1.84997022e-01 -2.97104474e-02 5.60732126e-01
1.13163149e+00 1.02270380e-01 -1.02243257e+00 -6.47789001e-01
-6.50986195e-01 5.71741641e-01 3.42789024e-01 3.84063810e-01
1.26472628e+00 -1.48678899e+00 -8.95808518e-01 -1.58453763e-01
6.97223783e-01 8.34790245e-02 5.03601909e-01 6.60065293e-01
-8.69049191e-01 3.16128105e-01 -2.23902270e-01 -8.00402939e-01
-1.49426293e+00 9.03916776e-01 3.94700646e-01 1.35662645e-01
-5.96769452e-01 1.15951633e+00 7.13681698e-01 -3.89665037e-01
5.04923984e-02 -5.55290461e-01 -1.90579847e-01 -5.12727976e-01
6.53167844e-01 -2.16813385e-01 -5.01936853e-01 -7.48082221e-01
-5.06511152e-01 3.30856472e-01 9.41849947e-02 1.74767356e-02
8.51023316e-01 -2.98501521e-01 -1.25474542e-01 4.34285045e-01
1.17202020e+00 -3.95951688e-01 -1.13663363e+00 -9.02355686e-02
-4.47895020e-01 -4.20752108e-01 -3.30506802e-01 -8.77018034e-01
-8.65199804e-01 1.17472208e+00 2.54733592e-01 1.73238888e-01
8.87979448e-01 7.92959929e-01 4.12272871e-01 2.62863904e-01
-1.35938391e-01 -5.03344893e-01 6.51025534e-01 3.16817611e-01
1.67590356e+00 -1.63939333e+00 -8.03294703e-02 -2.71323174e-01
-1.24308479e+00 7.29821682e-01 9.46216464e-01 -1.26882672e-01
2.08799943e-01 -6.26935735e-02 2.37654477e-01 -7.39805996e-01
-8.59567463e-01 -2.68749207e-01 6.79789364e-01 5.30126572e-01
5.36859453e-01 2.06729740e-01 1.76885247e-01 6.05459273e-01
-3.06543052e-01 -2.12449953e-01 2.47846588e-01 4.97484505e-01
-6.63603693e-02 -3.93336713e-01 -2.38021567e-01 2.34826148e-01
-1.59667730e-01 -2.82115489e-01 -8.55273366e-01 1.02837467e+00
-1.04783773e-01 1.00536966e+00 2.83705503e-01 -1.19321838e-01
3.39485735e-01 2.50203665e-02 7.76222825e-01 -2.02081248e-01
-2.06753552e-01 -6.97212338e-01 4.09844875e-01 -9.24862325e-01
-4.63696659e-01 -2.92945385e-01 -1.53455305e+00 -4.45352346e-01
9.62197334e-02 -2.41146773e-01 3.81436497e-01 1.07266831e+00
1.69020191e-01 7.84792662e-01 -7.00715408e-02 -5.13266623e-01
-1.86072335e-01 -6.70678675e-01 -1.86426446e-01 1.12360322e+00
5.34618318e-01 -4.05107021e-01 -2.70292193e-01 4.93649811e-01] | [10.858098983764648, 1.8121591806411743] |
3c1af40e-94ce-4e35-89e8-823c857a1bd6 | adaptive-representation-selection-in | 1802.00981 | null | https://arxiv.org/abs/1802.00981v4 | https://arxiv.org/pdf/1802.00981v4.pdf | Contextual Bandit with Adaptive Feature Extraction | We consider an online decision making setting known as contextual bandit problem, and propose an approach for improving contextual bandit performance by using an adaptive feature extraction (representation learning) based on online clustering. Our approach starts with an off-line pre-training on unlabeled history of contexts (which can be exploited by our approach, but not by the standard contextual bandit), followed by an online selection and adaptation of encoders. Specifically, given an input sample (context), the proposed approach selects the most appropriate encoding function to extract a feature vector which becomes an input for a contextual bandit, and updates both the bandit and the encoding function based on the context and on the feedback (reward). Our experiments on a variety of datasets, and both in stationary and non-stationary environments of several kinds demonstrate clear advantages of the proposed adaptive representation learning over the standard contextual bandit based on "raw" input contexts. | ['Djallel Bouneffouf', 'Baihan Lin', 'Irina Rish', 'Guillermo Cecchi'] | 2018-02-03 | null | null | null | null | ['online-clustering'] | ['computer-vision'] | [ 6.29054546e-01 -2.12056190e-01 -9.04349923e-01 -4.63103175e-01
-1.12354255e+00 -5.26273608e-01 6.53664887e-01 1.85518533e-01
-5.78978598e-01 9.71576095e-01 1.59149587e-01 -5.12110293e-01
-5.51771164e-01 -6.32833481e-01 -9.74607885e-01 -1.01183200e+00
-6.29387200e-02 5.37654757e-01 -3.41123603e-02 3.86669785e-01
4.33248669e-01 1.45681202e-01 -1.56022370e+00 5.38271368e-01
8.48224759e-01 1.60319984e+00 4.69827384e-01 8.93778801e-01
-2.91801631e-01 7.58391023e-01 -4.93655056e-01 -6.06071576e-02
2.97675788e-01 -8.41159940e-01 -1.05219805e+00 3.06969464e-01
1.66279733e-01 -1.83485091e-01 4.05154377e-02 8.81119490e-01
1.41099095e-01 7.82458723e-01 6.50070548e-01 -6.22762144e-01
-6.32911742e-01 8.13079238e-01 -1.75824076e-01 6.03199959e-01
1.05545335e-01 -7.67252222e-02 1.23430967e+00 -4.38282460e-01
4.32058692e-01 9.57501471e-01 3.31945121e-01 5.09480000e-01
-1.40175688e+00 -4.94447947e-01 6.15283728e-01 5.24193525e-01
-7.60182559e-01 -4.25542355e-01 9.77350295e-01 -3.43408614e-01
6.14175677e-01 3.79269630e-01 1.03502190e+00 1.13359392e+00
-5.38614929e-01 1.21013963e+00 1.31740892e+00 -7.91311264e-01
1.03626716e+00 1.54359445e-01 5.78221858e-01 2.73242503e-01
-6.63048103e-02 4.23313022e-01 -6.11193061e-01 -5.27258635e-01
4.12618697e-01 2.83234388e-01 -1.18957892e-01 -5.25833428e-01
-9.02646899e-01 9.16992903e-01 5.54513037e-01 2.90162534e-01
-8.24831724e-01 4.86152351e-01 2.23032430e-01 3.81065935e-01
7.22906649e-01 2.20659167e-01 -4.97951299e-01 -1.67847753e-01
-1.06441081e+00 1.05510324e-01 4.56567734e-01 7.81242847e-01
1.22930610e+00 -1.48289725e-01 -4.63542163e-01 9.68465984e-01
5.43938391e-02 4.38721567e-01 1.05280113e+00 -7.13139057e-01
6.71930969e-01 3.01671267e-01 4.96312529e-01 -4.23877805e-01
5.40887180e-04 -6.10995412e-01 -3.60097468e-01 -1.92201391e-01
2.15380877e-01 -4.34251547e-01 -1.16133475e+00 1.56331837e+00
5.32370687e-01 6.26694083e-01 2.04760153e-02 7.84930646e-01
9.64724869e-02 7.50178039e-01 5.74464351e-02 -6.79901600e-01
8.68267834e-01 -9.26225066e-01 -6.82692170e-01 -5.25374353e-01
4.97778565e-01 -2.53172755e-01 7.83843517e-01 5.12448847e-01
-7.68980563e-01 -5.27801991e-01 -1.03162766e+00 4.93131995e-01
-3.93312603e-01 6.70187846e-02 7.73272693e-01 7.45695889e-01
-6.41398370e-01 6.56088948e-01 -7.75275290e-01 -2.99565971e-01
4.26278651e-01 4.67787057e-01 -3.51130739e-02 -1.58827275e-01
-8.24014485e-01 3.63286495e-01 7.67896414e-01 -2.95639038e-04
-1.07906353e+00 -2.74408370e-01 -6.80035114e-01 -5.31054428e-03
6.99062288e-01 -5.29902041e-01 1.36766505e+00 -1.80682075e+00
-1.69739342e+00 1.05141208e-01 -4.18529689e-01 -1.07064927e+00
2.53777295e-01 -4.61677730e-01 4.56334911e-02 2.69692481e-01
-1.56472445e-01 2.09655970e-01 1.31771755e+00 -1.12065887e+00
-9.78659868e-01 -3.88020545e-01 1.37705192e-01 3.31605166e-01
-4.23287183e-01 -8.06001872e-02 -3.90046656e-01 -4.36751992e-01
1.30942658e-01 -1.00863969e+00 -2.35968441e-01 -7.56624103e-01
-1.87214330e-01 -7.40816211e-03 6.90002620e-01 -6.93487704e-01
1.23692465e+00 -2.19108868e+00 1.09700412e-01 4.59438205e-01
-6.36273146e-01 8.90459046e-02 1.08297817e-01 1.53887272e-01
-1.84250087e-01 1.04718812e-01 -2.80276269e-01 -3.85759294e-01
-1.21647500e-01 2.93060273e-01 -4.01488096e-01 4.16205794e-01
-1.66959703e-01 5.78986704e-01 -1.04362392e+00 -4.59231049e-01
3.00916791e-01 -1.80010229e-01 -7.43101537e-01 3.82154971e-01
-5.28569877e-01 5.27284324e-01 -7.32163370e-01 4.39967811e-01
2.18943998e-01 -2.16602430e-01 2.75309980e-01 4.66576368e-01
-2.72939540e-03 3.89140069e-01 -1.29263210e+00 1.53087068e+00
-5.84055781e-01 3.89528245e-01 -2.15935558e-01 -1.66266489e+00
7.15428531e-01 3.54486167e-01 5.27339578e-01 -3.35723758e-01
-8.95029902e-02 -4.15785089e-02 -2.74545431e-01 -3.53731006e-01
3.27758342e-01 4.05316707e-04 3.18110287e-02 6.13193631e-01
3.50683510e-01 3.33124042e-01 -2.07805000e-02 -1.37262553e-01
9.30258334e-01 3.70841652e-01 6.16335332e-01 3.81450504e-02
3.30963910e-01 4.77147140e-02 5.66119432e-01 1.23907459e+00
-1.46069437e-01 2.46582866e-01 1.92979753e-01 -6.81588709e-01
-6.21180713e-01 -4.36545253e-01 -5.64129150e-04 1.64887750e+00
-3.97665426e-02 -1.61072090e-02 -6.09302640e-01 -1.04085279e+00
4.25281972e-02 6.21428788e-01 -9.77236867e-01 -1.36665016e-01
-4.85075474e-01 -8.95283937e-01 -2.73191929e-01 3.94259959e-01
5.21914005e-01 -1.27924097e+00 -7.60093689e-01 3.89726460e-01
-1.66434869e-01 -6.11828864e-01 -3.63334656e-01 9.38145816e-01
-1.13107908e+00 -8.32829773e-01 -4.40229923e-01 -4.60961163e-01
4.03190792e-01 2.11593911e-01 6.84406817e-01 -1.79828763e-01
6.26011863e-02 4.06642258e-01 -6.49917662e-01 -3.57129455e-01
-1.81028713e-02 3.44277740e-01 -2.90579021e-01 7.54304767e-01
7.98129588e-02 -3.74674082e-01 -8.45333695e-01 1.25645548e-01
-8.53110671e-01 -1.09583415e-01 6.56805933e-01 1.26071548e+00
8.95982504e-01 -9.43371132e-02 8.18698943e-01 -1.28401899e+00
4.60071594e-01 -7.91110158e-01 -7.47410119e-01 2.87908792e-01
-6.45497739e-01 2.31278166e-01 6.24577343e-01 -5.13177097e-01
-1.34373236e+00 2.19034627e-01 2.69954711e-01 -4.59405988e-01
-2.23664045e-01 6.11043394e-01 2.15679333e-01 2.02194870e-01
6.92641854e-01 2.39963591e-01 -5.61498106e-01 -5.60314655e-01
5.75898051e-01 8.83222818e-01 3.47198665e-01 -8.60343277e-01
2.89984882e-01 3.56266528e-01 -4.05785382e-01 -4.48152065e-01
-9.88155544e-01 -7.41438687e-01 -6.44925237e-01 -1.47931296e-02
6.31715834e-01 -6.48149610e-01 -3.66853863e-01 -1.91180438e-01
-6.65130138e-01 -7.17428565e-01 -5.30890048e-01 7.68285632e-01
-8.88304293e-01 -6.89481795e-02 -2.56158739e-01 -1.50575483e+00
-2.43905157e-01 -9.67971325e-01 9.39834595e-01 1.60241440e-01
3.14778537e-02 -8.08293223e-01 8.97697806e-02 5.04014552e-01
1.07411131e-01 3.54542769e-02 9.40479100e-01 -9.06908929e-01
-7.76189268e-01 -1.83177784e-01 4.08695973e-02 3.56958210e-01
1.84390366e-01 -3.31929475e-01 -1.29108155e+00 -2.29576454e-01
-2.66760848e-02 -3.80569369e-01 1.15337133e+00 7.28699386e-01
1.32404125e+00 -5.73599458e-01 -4.37840581e-01 7.31457114e-01
1.42485058e+00 8.01321208e-01 9.82872546e-02 4.77822334e-01
2.39711225e-01 1.93489626e-01 9.68403161e-01 5.37829220e-01
-1.03091650e-01 6.95196331e-01 5.51303327e-01 3.35654587e-01
3.06465447e-01 -1.80495515e-01 2.57127851e-01 2.94656903e-01
-1.18585341e-01 1.23291470e-01 -5.81059694e-01 8.13412249e-01
-2.41247678e+00 -1.12657535e+00 7.48645604e-01 2.53560257e+00
8.82480025e-01 5.67112789e-02 4.20449167e-01 1.75417334e-01
8.39098096e-01 1.20095953e-01 -9.91499543e-01 -5.16296208e-01
2.68723249e-01 3.30964714e-01 5.26276231e-01 4.84153330e-01
-1.36922514e+00 9.84954596e-01 6.31439257e+00 7.36581206e-01
-1.29945385e+00 2.31751531e-01 9.86807525e-01 -4.23430830e-01
8.77715833e-03 1.23397559e-01 -6.21022940e-01 6.15012527e-01
1.17433441e+00 -4.80266176e-02 9.84038234e-01 1.30702138e+00
2.15597153e-02 -2.82086760e-01 -1.14482152e+00 9.89426136e-01
-2.12734550e-01 -1.42245483e+00 -1.80397451e-01 -4.63746376e-02
9.17638481e-01 -1.25211105e-02 1.20765217e-01 5.22626340e-01
5.95824540e-01 -4.94752973e-01 7.59283185e-01 4.13821489e-01
4.72001016e-01 -8.95831287e-01 6.46678209e-01 5.59330463e-01
-9.44623232e-01 -7.68787742e-01 -3.69268060e-01 1.20576108e-02
-5.15241504e-01 3.52036208e-01 -9.26164627e-01 6.22976482e-01
6.69696689e-01 6.50442541e-01 -2.76939690e-01 1.10229731e+00
-1.50148988e-01 1.13430560e+00 -2.54310697e-01 -2.27738291e-01
5.17617524e-01 -2.60365725e-01 1.42654762e-01 1.37073314e+00
2.16925830e-01 -6.77479105e-03 5.15088260e-01 2.70559698e-01
-8.01524669e-02 3.81856501e-01 -5.82569122e-01 2.60182351e-01
5.98850965e-01 8.50272417e-01 -5.30068815e-01 -8.22905481e-01
-2.81115741e-01 8.36220205e-01 6.12814188e-01 7.71372497e-01
-6.18476391e-01 8.00623298e-02 3.80924851e-01 -3.98285240e-01
8.55073690e-01 2.61785150e-01 -2.79039890e-01 -9.78511035e-01
-8.48092735e-02 -5.97550988e-01 9.43642378e-01 -5.19955277e-01
-9.42428112e-01 3.09549361e-01 3.84947389e-01 -1.08595240e+00
-6.86175048e-01 -1.17948666e-01 -4.44415390e-01 5.86869359e-01
-1.64176428e+00 -7.28417337e-01 1.37994111e-01 8.70356023e-01
7.37148821e-01 3.06973457e-02 6.78718388e-01 -1.13510631e-01
-5.67089260e-01 3.07914108e-01 5.19116580e-01 -1.37927338e-01
4.30863619e-01 -1.51046884e+00 -2.64706284e-01 7.94884801e-01
4.54296082e-01 5.64365327e-01 4.94175822e-01 -3.61370623e-01
-1.36409521e+00 -1.35008633e+00 2.09839180e-01 -5.42267300e-02
4.72862482e-01 -2.06629381e-01 -4.72775698e-01 1.08691859e+00
1.59597546e-01 3.05311799e-01 8.40755165e-01 3.69587719e-01
-1.14992924e-01 -5.16783655e-01 -1.20440626e+00 3.72878253e-01
1.07790101e+00 -4.58575547e-01 -7.99056828e-01 3.87079298e-01
6.47870302e-01 -1.20490842e-01 -4.00080115e-01 5.68250939e-02
5.58471084e-01 -7.66116798e-01 7.95834839e-01 -7.76858509e-01
-1.51294231e-01 5.51102869e-02 -3.00271064e-01 -1.54559815e+00
-4.67447251e-01 -1.03986287e+00 -3.89864117e-01 8.84941459e-01
3.11200917e-01 -6.78779542e-01 9.19709146e-01 4.60752904e-01
-1.85643137e-02 -6.56900465e-01 -1.24408579e+00 -5.62963843e-01
-3.51554364e-01 -7.45046735e-01 6.65522039e-01 6.18561685e-01
8.66115317e-02 2.41163135e-01 -5.19671559e-01 1.35596037e-01
4.40653563e-01 8.62116516e-01 8.26640129e-01 -1.01979816e+00
-7.43391037e-01 -1.98782966e-01 -6.94724172e-02 -1.25589740e+00
1.15726411e-01 -7.23603785e-01 3.25490981e-01 -1.05397773e+00
1.84704527e-01 -4.90295976e-01 -1.08213675e+00 5.67235291e-01
-2.89347410e-01 -1.25128075e-01 1.58267111e-01 2.47893482e-01
-8.85907650e-01 3.14229041e-01 7.54992604e-01 -1.89029843e-01
-5.39407611e-01 4.56804425e-01 -7.69724786e-01 5.87284625e-01
5.75912476e-01 -5.64136684e-01 -5.92318833e-01 -1.27405941e-01
-3.76250781e-02 5.08001983e-01 1.12400264e-01 -9.10947502e-01
1.08914264e-01 -5.26963651e-01 4.84074324e-01 -6.17961645e-01
4.10717368e-01 -1.05243003e+00 -1.47278056e-01 2.85443902e-01
-8.16064298e-01 -2.62624979e-01 -8.25038180e-02 1.11944532e+00
-1.56934515e-01 -4.80705678e-01 5.73403776e-01 -2.59362072e-01
-5.67014158e-01 2.69325942e-01 -3.26465756e-01 -3.59401733e-01
9.78858888e-01 -1.33520171e-01 -5.67126833e-02 -4.41320807e-01
-1.23293352e+00 -7.77378976e-02 -4.26950259e-03 -1.49244905e-01
3.33969027e-01 -1.27664042e+00 -1.77467987e-01 3.23952943e-01
1.17521390e-01 -5.67366146e-02 -1.26383349e-01 4.94132251e-01
2.06488460e-01 5.29106498e-01 2.29830429e-01 -7.14760303e-01
-9.72764432e-01 9.33756113e-01 2.12630972e-01 -6.39445841e-01
-3.21732193e-01 6.65664315e-01 1.36877373e-01 1.41119018e-01
3.79810363e-01 -7.19683647e-01 -1.51866689e-01 2.66326487e-01
4.60183024e-01 1.19128153e-01 3.31325531e-01 -5.80967516e-02
1.50428489e-02 2.37302110e-01 -1.01805001e-01 -4.76617575e-01
1.45741498e+00 -1.00042067e-01 4.01118368e-01 8.15482080e-01
9.09808755e-01 -3.38152111e-01 -1.45578265e+00 -6.85061693e-01
3.80708665e-01 -6.65586531e-01 1.64912909e-01 -7.87262797e-01
-7.18005002e-01 5.47193527e-01 7.37105966e-01 6.28474355e-01
1.25815380e+00 -1.36434838e-01 4.66146946e-01 6.94438994e-01
5.55656850e-01 -1.34496725e+00 -1.10625243e-02 3.35177958e-01
5.77546299e-01 -1.07985580e+00 -1.91098288e-01 1.88185290e-01
-5.20474970e-01 8.53332341e-01 1.54921740e-01 -4.09404069e-01
8.40103745e-01 -3.11774701e-01 -1.88962832e-01 2.35366836e-01
-1.09209144e+00 -5.85404634e-01 1.51924759e-01 4.77269381e-01
3.16006765e-02 2.13009864e-01 -1.74293473e-01 4.31771606e-01
3.99261676e-02 1.13777019e-01 -1.22534126e-01 1.04346216e+00
-6.26158714e-01 -9.47670162e-01 -5.83428085e-01 6.25879169e-01
-4.97731596e-01 3.40527222e-02 -3.46991658e-01 4.83180672e-01
2.38011941e-01 1.00291824e+00 2.02055331e-02 -2.07513332e-01
-5.28243072e-02 6.17348135e-01 3.32244039e-01 -8.78744125e-01
-6.98388219e-01 5.07392824e-01 1.27096713e-01 -4.14743662e-01
-6.28445029e-01 -9.73044097e-01 -7.53935933e-01 5.17331779e-01
-5.36351979e-01 5.16835153e-01 9.19667304e-01 1.23489368e+00
2.13344291e-01 3.68499786e-01 1.07843900e+00 -9.99526501e-01
-4.92793024e-01 -1.15833175e+00 -3.41465890e-01 6.80045664e-01
6.81328118e-01 -7.69034266e-01 -3.85329425e-01 2.76748836e-01] | [4.503096103668213, 3.0958240032196045] |
c9e172f6-51a4-4716-a600-dcb9b73925e3 | avatar-adversarial-self-supervised-domain | 2305.00082 | null | https://arxiv.org/abs/2305.00082v2 | https://arxiv.org/pdf/2305.00082v2.pdf | AVATAR: Adversarial self-superVised domain Adaptation network for TARget domain | This paper presents an unsupervised domain adaptation (UDA) method for predicting unlabeled target domain data, specific to complex UDA tasks where the domain gap is significant. Mainstream UDA models aim to learn from both domains and improve target discrimination by utilizing labeled source domain data. However, the performance boost may be limited when the discrepancy between the source and target domains is large or the target domain contains outliers. To explicitly address this issue, we propose the Adversarial self-superVised domain Adaptation network for the TARget domain (AVATAR) algorithm. It outperforms state-of-the-art UDA models by concurrently reducing domain discrepancy while enhancing discrimination through domain adversarial learning, self-supervised learning, and sample selection strategy for the target domain, all guided by deep clustering. Our proposed model significantly outperforms state-of-the-art methods on three UDA benchmarks, and extensive ablation studies and experiments demonstrate the effectiveness of our approach for addressing complex UDA tasks. | ['Hyunsoo Yoon', 'Jun Kataoka'] | 2023-04-28 | null | null | null | null | ['deep-clustering', 'deep-clustering'] | ['miscellaneous', 'natural-language-processing'] | [ 3.02702814e-01 1.13695867e-01 -5.48707545e-01 -4.24136013e-01
-1.16867602e+00 -8.13357294e-01 7.44731665e-01 -1.22115515e-01
-1.80401251e-01 9.31018651e-01 1.20068155e-03 -1.40205279e-01
-4.09948193e-02 -6.89743459e-01 -7.49841034e-01 -6.02980673e-01
3.17137361e-01 1.04330790e+00 1.66212007e-01 -2.24338815e-01
-1.72623798e-01 2.49281600e-01 -1.12053430e+00 2.55649716e-01
1.42244685e+00 1.04389608e+00 -2.36423716e-01 8.70437250e-02
-2.43216291e-01 5.94611704e-01 -7.74322033e-01 -3.22222114e-01
5.08636951e-01 -5.80542386e-01 -8.58016491e-01 1.29030868e-01
4.42248940e-01 -2.21689895e-01 -1.53502911e-01 1.12941241e+00
5.38480520e-01 1.06004216e-01 1.27605927e+00 -1.43341303e+00
-1.02809775e+00 2.69090176e-01 -5.58553278e-01 -1.89670045e-02
4.11847606e-02 1.42623201e-01 8.22029889e-01 -8.61917019e-01
7.08191216e-01 1.12610376e+00 8.45471561e-01 9.04937923e-01
-1.59113204e+00 -9.68547583e-01 2.62372881e-01 -5.41141145e-02
-1.01346731e+00 -2.55880684e-01 1.12492836e+00 -6.55371726e-01
5.87667763e-01 -2.62792677e-01 -3.67528945e-03 1.85808122e+00
-2.64548510e-01 8.86921227e-01 1.11148131e+00 -3.05505544e-01
7.01201141e-01 1.58129081e-01 2.18599990e-01 4.55757231e-02
1.42406881e-01 4.55437899e-01 -1.79758742e-01 -4.72205967e-01
4.98930782e-01 -1.21030502e-01 3.46619964e-01 -1.07450116e+00
-1.04336047e+00 9.84710217e-01 2.63013572e-01 -1.05540492e-01
-2.94736832e-01 -5.44000924e-01 7.57597983e-01 5.53520858e-01
7.99209595e-01 6.74120247e-01 -6.68625534e-01 2.00067207e-01
-6.71481788e-01 4.43185091e-01 5.16551197e-01 1.11773479e+00
5.28110027e-01 3.32295656e-01 -2.33103797e-01 1.31434524e+00
8.14520717e-02 7.20419168e-01 6.74617112e-01 -8.44147146e-01
4.10045594e-01 8.49058330e-01 1.79928422e-01 -2.73631096e-01
-2.28903875e-01 -3.82107288e-01 -8.30083549e-01 5.05417645e-01
9.06625926e-01 -3.07348430e-01 -1.28623605e+00 1.79973638e+00
4.65833426e-01 2.33873412e-01 5.71237504e-01 8.90852988e-01
7.63796628e-01 3.29223841e-01 4.40914154e-01 1.62017867e-01
8.74983609e-01 -9.89257336e-01 -4.09041524e-01 -6.90133274e-01
5.68694830e-01 -5.06110370e-01 1.28024304e+00 1.97914913e-01
-7.23457634e-01 -8.15796196e-01 -1.19171584e+00 1.59534261e-01
-4.56907272e-01 7.38444030e-02 2.37202570e-01 7.32570171e-01
-3.95158142e-01 3.77977282e-01 -4.53895330e-01 -4.58810776e-01
8.66674244e-01 3.64502937e-01 -3.42110664e-01 -4.07441169e-01
-1.42062414e+00 6.62894964e-01 4.45310742e-01 -8.49246442e-01
-1.22574508e+00 -1.01426721e+00 -9.70136464e-01 -2.43168473e-01
2.02601835e-01 -6.14298999e-01 1.28361285e+00 -1.29552364e+00
-1.42319357e+00 1.27942216e+00 2.14898393e-01 -7.59184361e-01
6.04323328e-01 -2.75106698e-01 -7.57873118e-01 -2.46677324e-01
4.24788564e-01 5.02416372e-01 1.18217635e+00 -1.45639837e+00
-5.31560004e-01 -6.21844947e-01 -3.15602243e-01 1.52114511e-01
-3.86993885e-01 -3.02662581e-01 1.41018936e-02 -9.30159807e-01
-1.41777828e-01 -8.62430096e-01 -2.19319031e-01 -1.41191915e-01
-1.18025243e-01 -2.79337883e-01 1.16061127e+00 -4.81585890e-01
8.02153409e-01 -2.44528079e+00 1.52847050e-02 1.97346434e-01
1.62415206e-01 6.54921710e-01 -3.67742777e-01 -1.04331374e-02
-4.34878588e-01 -2.54312068e-01 -5.44548273e-01 -3.89853679e-02
7.48054385e-02 2.01113030e-01 -6.52191162e-01 4.13080692e-01
5.33179462e-01 6.74209118e-01 -1.04939473e+00 -2.73202986e-01
1.79822315e-02 -3.11237741e-02 -5.99528313e-01 5.92405021e-01
-5.00909507e-01 7.34043300e-01 -4.66837972e-01 7.81257689e-01
9.87182140e-01 -2.28899732e-01 2.71376967e-01 1.51665851e-01
6.05799258e-01 2.23254994e-01 -1.04905534e+00 1.79072917e+00
-1.96439222e-01 2.74116635e-01 -4.00616042e-02 -1.41010916e+00
1.35751760e+00 -6.50323480e-02 5.97438872e-01 -9.44514215e-01
-2.21219864e-02 3.06749552e-01 3.49973813e-02 -1.21208036e-03
8.88338089e-02 -3.10797602e-01 -4.46595222e-01 3.46862167e-01
2.35537186e-01 7.57150427e-02 -1.74553022e-01 9.96729210e-02
1.07671106e+00 3.61623794e-01 4.91406560e-01 -2.73308665e-01
4.41859514e-01 4.64871407e-01 8.06260169e-01 7.02100098e-01
-7.11902201e-01 7.26057053e-01 5.68307400e-01 -2.76295543e-01
-1.26616561e+00 -1.57282400e+00 -4.05804291e-02 1.38189852e+00
3.31530184e-01 2.66995519e-01 -7.16065228e-01 -1.33096349e+00
3.77310961e-01 7.96676815e-01 -8.16561520e-01 -6.18334472e-01
-3.00773114e-01 -6.74954414e-01 6.49931490e-01 8.12008202e-01
5.93240023e-01 -9.52791691e-01 2.60810941e-01 1.54644892e-01
-7.69024864e-02 -1.13231945e+00 -4.11332846e-01 3.25902641e-01
-8.83071601e-01 -1.04284585e+00 -8.79807770e-01 -9.91945505e-01
5.47930896e-01 4.79846783e-02 1.41790056e+00 -8.04474056e-01
1.51378348e-01 2.37532437e-01 -3.32058817e-01 -5.53387225e-01
-8.81428480e-01 2.70329446e-01 3.03381026e-01 -5.40515184e-02
8.00155818e-01 -7.24118173e-01 -3.96010280e-01 5.92297614e-01
-7.67878056e-01 -4.14130837e-01 5.04658997e-01 1.19344521e+00
6.34532750e-01 -6.73663542e-02 1.20086575e+00 -1.51667249e+00
7.52397954e-01 -8.58333111e-01 -4.54728603e-01 8.70470628e-02
-9.19816315e-01 8.55130423e-03 9.78709042e-01 -9.40569580e-01
-1.21871626e+00 1.81998923e-01 5.37477247e-02 -8.28246534e-01
-6.30672872e-01 4.00048085e-02 -6.64572060e-01 2.24628761e-01
1.40173709e+00 2.43589774e-01 2.74350852e-01 -3.61746818e-01
3.44589144e-01 7.44402230e-01 6.60234571e-01 -9.03490365e-01
9.81845438e-01 4.83871311e-01 -4.24548298e-01 -3.12660217e-01
-8.45113933e-01 -5.78116119e-01 -9.71333981e-01 1.95213199e-01
5.78114986e-01 -1.36582136e+00 -9.82842967e-03 5.80055296e-01
-7.95788705e-01 -5.48287809e-01 -6.29707396e-01 1.85323238e-01
-7.18451977e-01 2.10434988e-01 -1.34227678e-01 -4.28931087e-01
-1.94402561e-01 -9.03878927e-01 8.41669500e-01 1.29146473e-02
-4.50133353e-01 -1.12845242e+00 1.61120787e-01 3.76333326e-01
1.55592382e-01 4.24765110e-01 9.47951972e-01 -1.45412481e+00
1.36896484e-02 -1.22102521e-01 -2.61613101e-01 6.30755663e-01
2.69265562e-01 -7.07807600e-01 -1.10454476e+00 -3.00087124e-01
-2.81521201e-01 -7.22737134e-01 7.56025314e-01 3.63760918e-01
1.03146851e+00 1.44083984e-03 -3.79323721e-01 6.06421947e-01
1.10067976e+00 2.67018110e-01 4.69787955e-01 5.64586222e-01
5.84532976e-01 3.94285947e-01 1.13237357e+00 4.46458846e-01
1.60005689e-01 4.75902677e-01 4.26238209e-01 -3.23753804e-01
-3.46720666e-01 -3.94801855e-01 3.67010564e-01 6.45674840e-02
5.21188200e-01 -3.39692868e-02 -1.21994007e+00 1.02539241e+00
-1.79323590e+00 -8.02739859e-01 2.06881166e-01 2.10396695e+00
8.81329954e-01 3.71700525e-01 7.31174648e-01 -1.07707195e-01
8.00347805e-01 1.46876378e-02 -1.39237452e+00 -2.38594577e-01
-1.55683979e-01 2.15148017e-01 5.01068532e-01 6.29928857e-02
-1.44595182e+00 9.97690380e-01 6.61355591e+00 1.01911008e+00
-7.66564131e-01 1.85666725e-01 5.39056242e-01 2.24014953e-01
-1.55366346e-01 -3.10064375e-01 -5.74029386e-01 5.59178889e-01
8.37665558e-01 -2.88649589e-01 3.12340260e-01 1.55606878e+00
-3.21548849e-01 4.07914847e-01 -1.23276484e+00 7.83142269e-01
-5.07036261e-02 -1.03996670e+00 -2.57723983e-02 1.55663326e-01
1.01903760e+00 9.85106155e-02 3.76326710e-01 9.51763928e-01
9.98688519e-01 -8.11151743e-01 1.89388871e-01 -2.60279298e-01
1.12851274e+00 -8.82270277e-01 5.27125299e-01 3.56661409e-01
-6.45258069e-01 -2.61574149e-01 -4.39450145e-01 7.87392184e-02
-4.67753172e-01 4.44822073e-01 -9.99656200e-01 3.36864144e-01
6.78788841e-01 9.10050571e-01 -4.69683439e-01 5.05510747e-01
5.55168428e-02 8.56352031e-01 3.70283909e-02 5.25289834e-01
1.90264925e-01 -1.86117873e-01 5.50178409e-01 1.00149810e+00
-1.76569354e-02 -1.39156148e-01 3.65036100e-01 9.73943651e-01
-4.27401781e-01 1.65472757e-02 -1.00229108e+00 -3.83188985e-02
6.00188375e-01 6.84790313e-01 -2.07132876e-01 -3.31099868e-01
-5.44321001e-01 1.16999340e+00 4.14092332e-01 4.89955425e-01
-9.66582239e-01 -2.75834650e-01 1.29274929e+00 2.58037031e-01
1.97122261e-01 8.11265409e-02 -7.69649982e-01 -1.12365782e+00
-1.46872178e-01 -1.29494512e+00 8.24892461e-01 -3.64642769e-01
-2.11889458e+00 3.87386054e-01 -2.86214322e-01 -1.84684908e+00
-3.51691127e-01 -5.73072612e-01 -4.78747100e-01 9.48500335e-01
-1.55696774e+00 -1.27176952e+00 -1.08826064e-01 1.05452120e+00
5.97025633e-01 -9.41026211e-01 1.00938904e+00 3.17102343e-01
-3.58337134e-01 1.06729281e+00 8.15661669e-01 4.99002099e-01
1.49087763e+00 -1.39082015e+00 7.45756924e-01 7.36224890e-01
-3.66983443e-01 3.41761827e-01 4.35096532e-01 -7.05154955e-01
-8.72977674e-01 -1.54816115e+00 1.85231373e-01 -7.19509602e-01
6.34974420e-01 -5.08747756e-01 -1.12141025e+00 7.73756683e-01
-3.10987923e-02 3.89890671e-01 9.88667309e-01 4.01918024e-01
-9.05585706e-01 -1.30072638e-01 -1.65580475e+00 3.47054154e-01
1.06334293e+00 -4.76577669e-01 -8.16820920e-01 3.05283993e-01
7.24360943e-01 -4.73011583e-01 -1.03314769e+00 5.45856655e-01
3.08971465e-01 -7.83668995e-01 1.41121340e+00 -1.11815286e+00
6.02397978e-01 -6.47953749e-02 -5.70837967e-02 -1.75699377e+00
-4.31251675e-01 -1.49276912e-01 -2.56306678e-01 1.34196389e+00
2.93246537e-01 -5.69288373e-01 1.10543501e+00 4.76294070e-01
3.88765074e-02 -8.27074572e-02 -7.75486887e-01 -1.20077813e+00
7.76925385e-01 -2.07105875e-01 6.12204731e-01 1.49221134e+00
-2.04497814e-01 6.65721238e-01 -3.80510211e-01 3.07602555e-01
8.76928329e-01 3.35587859e-01 1.06107950e+00 -1.59421766e+00
-1.93173647e-01 -2.82475948e-01 -1.34915575e-01 -8.97228241e-01
6.12273753e-01 -9.85614955e-01 -1.56894192e-01 -1.09666908e+00
-1.65517572e-02 -5.08644462e-01 -4.40468401e-01 4.04324085e-01
-2.61050045e-01 4.87321727e-02 2.04714835e-02 3.46828610e-01
-5.67592025e-01 6.20238841e-01 1.22019577e+00 -5.08125126e-01
-3.75285715e-01 1.48577467e-01 -9.58874047e-01 5.90319812e-01
7.93018043e-01 -5.51086068e-01 -6.10898256e-01 -1.68021128e-01
-6.33057654e-01 -1.24844790e-01 1.83546349e-01 -1.02325237e+00
-9.96400788e-02 -3.70553017e-01 7.78125525e-01 -3.39524508e-01
1.57069176e-01 -1.04646623e+00 -4.47256804e-01 2.77113825e-01
-4.05035824e-01 -5.66034496e-01 4.48051006e-01 8.74571800e-01
-3.29787612e-01 2.69394875e-01 1.37837851e+00 1.95137694e-01
-1.16555262e+00 2.37776220e-01 -7.63512030e-02 6.82259738e-01
1.36821425e+00 -1.85695931e-01 -3.43350410e-01 -1.91160247e-01
-9.11452770e-01 3.58787060e-01 5.13406456e-01 5.98937690e-01
3.99866492e-01 -1.64185035e+00 -8.57326508e-01 5.37252486e-01
6.26681447e-01 2.08204284e-01 1.65798888e-01 1.10044606e-01
1.95714339e-04 7.32853040e-02 -6.34197414e-01 -6.24888957e-01
-9.74039555e-01 9.37575161e-01 3.81777138e-01 -5.39970577e-01
-3.11810225e-01 6.73431873e-01 6.11148953e-01 -1.17381930e+00
1.94618881e-01 2.11254239e-01 -7.17816949e-02 -1.05394088e-01
3.72016281e-01 3.65545511e-01 -2.17999872e-02 -3.41945440e-01
-4.19363946e-01 1.47891417e-01 -3.50735337e-01 2.71761924e-01
1.11286628e+00 -5.77645302e-02 5.49582481e-01 -2.30101738e-02
1.04313111e+00 -2.44601965e-01 -1.60118067e+00 -7.58144557e-01
1.86365452e-02 -3.29612166e-01 -4.54295248e-01 -1.28316212e+00
-7.01257408e-01 7.86402404e-01 7.85291970e-01 -1.86889008e-01
1.38109207e+00 2.65860688e-02 7.89158165e-01 1.17283382e-01
1.51845468e-02 -1.35785234e+00 5.08793414e-01 6.75201833e-01
6.22178018e-01 -1.75458431e+00 -2.55923480e-01 -3.12253326e-01
-1.17558861e+00 6.25660360e-01 1.23777092e+00 -4.72563416e-01
5.29549062e-01 1.42246187e-01 3.57161492e-01 2.79614717e-01
-4.21322465e-01 -2.91796058e-01 2.66778499e-01 1.48041248e+00
3.57287526e-02 8.48965645e-02 7.13920519e-02 1.13918293e+00
1.93791613e-01 -1.92342281e-01 9.87132564e-02 6.25224411e-01
-1.30586311e-01 -1.44241524e+00 -6.70762062e-01 4.07632202e-01
-3.95442158e-01 1.10143721e-01 -7.35913277e-01 1.01638877e+00
3.31103653e-02 7.03689158e-01 -4.76382161e-03 -4.16250825e-01
6.97550833e-01 4.16914225e-01 1.85867667e-01 -6.06313765e-01
-3.48250955e-01 -5.87754734e-02 -1.85799524e-01 -3.39442134e-01
-2.25365326e-01 -7.60975182e-01 -1.12799704e+00 -9.17881951e-02
2.04251394e-01 -7.38227889e-02 2.07577452e-01 7.68678367e-01
6.28515303e-01 4.97005939e-01 7.38059819e-01 -3.45813423e-01
-9.67610180e-01 -1.00433218e+00 -7.87696362e-01 1.05807602e+00
3.68276328e-01 -9.11986649e-01 -9.64147225e-02 2.94144511e-01] | [10.335722923278809, 3.0928754806518555] |
1b16d068-7880-4917-ab0a-f17f99d2aa9c | sketch-qnet-a-quadruplet-convnet-for-color | 2104.11130 | null | https://arxiv.org/abs/2104.11130v1 | https://arxiv.org/pdf/2104.11130v1.pdf | Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Image Retrieval | Architectures based on siamese networks with triplet loss have shown outstanding performance on the image-based similarity search problem. This approach attempts to discriminate between positive (relevant) and negative (irrelevant) items. However, it undergoes a critical weakness. Given a query, it cannot discriminate weakly relevant items, for instance, items of the same type but different color or texture as the given query, which could be a serious limitation for many real-world search applications. Therefore, in this work, we present a quadruplet-based architecture that overcomes the aforementioned weakness. Moreover, we present an instance of this quadruplet network, which we call Sketch-QNet, to deal with the color sketch-based image retrieval (CSBIR) problem, achieving new state-of-the-art results. | ['Jose M. Saavedra', 'Anibal Fuentes'] | 2021-04-22 | null | null | null | null | ['sketch-based-image-retrieval'] | ['computer-vision'] | [ 2.58578986e-01 -7.50483274e-01 -4.36363399e-01 -1.81062892e-01
-8.80151570e-01 -6.53488457e-01 5.63346446e-01 2.09924370e-01
-6.36953950e-01 7.91423023e-01 -4.85737801e-01 -7.55566210e-02
-5.43963730e-01 -8.72080624e-01 -5.80727518e-01 -6.64806843e-01
2.00444572e-02 5.39715111e-01 4.29753482e-01 -5.37223458e-01
6.61247373e-01 8.05098355e-01 -1.68718684e+00 2.95493454e-01
5.11273980e-01 1.43754828e+00 -8.48919600e-02 1.07743973e-02
-2.98885524e-01 4.40203369e-01 -6.45453751e-01 -8.17873776e-01
3.14188898e-01 -3.62874240e-01 -6.20913386e-01 -6.17302775e-01
1.12940717e+00 -1.35256708e-01 -1.90738842e-01 1.27585852e+00
5.67407489e-01 8.59771296e-02 6.75552011e-01 -1.61853814e+00
-7.42923915e-01 2.21750528e-01 -4.36874151e-01 1.53933808e-01
3.45158637e-01 -1.39245316e-01 1.53081417e+00 -1.25846708e+00
6.64851248e-01 1.10608947e+00 4.24288839e-01 7.10217834e-01
-1.24341083e+00 -9.58775699e-01 1.85397621e-02 7.18006194e-01
-1.57279181e+00 -2.97997482e-02 1.10656047e+00 1.82332247e-01
6.08087659e-01 6.07485116e-01 7.75278687e-01 1.26159406e+00
3.82056572e-02 1.14140236e+00 9.97139573e-01 -2.06073239e-01
1.93524763e-01 5.46609648e-02 3.24991755e-02 6.41269982e-01
3.55475008e-01 9.92253572e-02 -7.15792060e-01 -2.62301952e-01
7.31154740e-01 7.75912628e-02 -1.84056610e-01 -9.91123080e-01
-1.33298731e+00 8.76141906e-01 8.76160324e-01 6.04713261e-01
-1.25678182e-01 2.87943333e-01 4.50476319e-01 6.31896317e-01
7.69524574e-02 6.36221766e-01 -8.41529816e-02 2.44957536e-01
-1.01722765e+00 3.04583013e-01 6.76682353e-01 6.43353462e-01
8.28489125e-01 -1.35567114e-01 -3.29739749e-01 9.56233382e-01
1.83483604e-02 6.06340110e-01 1.94178283e-01 -6.08846068e-01
4.43298399e-01 5.91035664e-01 -1.07677802e-02 -1.35929978e+00
-2.06369117e-01 -5.06040931e-01 -1.18470991e+00 2.30322331e-01
4.32581335e-01 6.13306224e-01 -7.21408725e-01 1.85972059e+00
-3.66468504e-02 -9.88463387e-02 -1.64353713e-01 1.30371809e+00
1.06905496e+00 2.75914371e-01 -8.75847340e-02 1.33715585e-01
1.29024231e+00 -1.05442607e+00 -3.03162634e-01 -9.01274681e-02
-3.10944226e-02 -7.00125992e-01 1.15343440e+00 5.51324546e-01
-1.21674311e+00 -5.59183419e-01 -1.14070153e+00 9.46027115e-02
-7.15673864e-01 -6.70280457e-02 6.13512993e-01 5.37560821e-01
-1.18769383e+00 6.16463244e-01 -7.01110736e-02 -4.25854295e-01
2.91412681e-01 4.24875408e-01 -4.00901616e-01 -2.56366789e-01
-1.42688107e+00 7.26299107e-01 1.45162374e-01 9.59785655e-02
-6.31623864e-01 -4.78410721e-01 -5.56768239e-01 4.65508848e-01
6.35294914e-01 -5.11079133e-01 7.33667195e-01 -1.25277400e+00
-1.13150692e+00 1.11834025e+00 1.69490099e-01 -3.36173505e-01
6.55917168e-01 2.28177980e-01 -4.87513632e-01 2.98004597e-01
-2.79963128e-02 7.37264037e-01 1.06458139e+00 -1.20763028e+00
-4.70230877e-01 -5.07665157e-01 1.80348963e-01 -9.93298665e-02
-5.58500946e-01 5.27768321e-02 -7.44656563e-01 -1.01518095e+00
7.22866729e-02 -9.04030800e-01 1.64191976e-01 6.73893750e-01
-1.38100773e-01 -6.11089051e-01 6.07149959e-01 2.85728630e-02
1.21966052e+00 -2.04793692e+00 1.40043244e-01 5.59421420e-01
1.31160051e-01 6.54458284e-01 -8.11681867e-01 6.56438947e-01
-1.58716217e-01 1.85714811e-01 -2.44833380e-01 7.13595003e-02
1.91747770e-01 3.74042653e-02 -3.80220860e-01 2.40824655e-01
5.59505939e-01 1.12113285e+00 -1.07177258e+00 -7.20270813e-01
-8.49015824e-03 2.81807929e-01 -1.75579026e-01 -1.07585572e-01
-8.18611160e-02 -1.77877039e-01 -5.34821689e-01 8.76170754e-01
9.15138721e-01 -2.39099935e-01 7.76113421e-02 -4.38401163e-01
1.07966937e-01 -1.92697972e-01 -1.19087279e+00 1.69807088e+00
-2.06079394e-01 6.59941494e-01 8.40037093e-02 -1.13978279e+00
1.07734489e+00 -9.92821157e-03 5.24201035e-01 -1.37343156e+00
-2.73704290e-01 6.50854886e-01 -1.75960027e-02 -2.63045188e-02
6.11243546e-01 -2.00892776e-01 -1.05768186e-03 4.85429287e-01
1.36114436e-03 -1.10430405e-01 4.79441077e-01 2.44835898e-01
1.00617063e+00 -1.72233298e-01 -1.40631348e-02 -1.27429560e-01
1.05468404e+00 -2.69705772e-01 1.30651727e-01 9.58834827e-01
-4.13206249e-01 7.65300691e-01 5.32998860e-01 -6.84223652e-01
-8.62504005e-01 -1.33333087e+00 -3.88908908e-02 1.11945415e+00
6.36857152e-01 -3.17537248e-01 -7.09620118e-02 -1.00266576e+00
2.23374441e-01 -1.64359361e-02 -6.93959534e-01 -2.89697587e-01
-6.52737975e-01 -4.43980694e-01 6.05787992e-01 5.30408502e-01
5.52308917e-01 -1.37385011e+00 -5.27646720e-01 1.94904748e-02
-2.70367235e-01 -5.54770112e-01 -5.60963988e-01 1.38225272e-01
-4.43795592e-01 -1.20922410e+00 -1.31471062e+00 -9.24772620e-01
4.69570339e-01 4.98015970e-01 1.45928752e+00 5.11171937e-01
-2.82661527e-01 4.20309722e-01 -3.51410717e-01 3.37703601e-02
6.00996129e-02 1.10358380e-01 -2.77075171e-01 1.76025197e-01
2.77993262e-01 -1.21464394e-01 -8.28650475e-01 6.84724689e-01
-1.26796567e+00 -4.83425915e-01 6.98846459e-01 1.34238911e+00
6.59660935e-01 -1.14811696e-01 6.77979171e-01 -2.10798070e-01
8.17949295e-01 -1.15068339e-01 -5.18670559e-01 8.40739906e-01
-6.48311257e-01 1.56645760e-01 8.25451255e-01 -4.73001868e-01
-5.52401841e-01 -9.60342661e-02 -2.91709416e-02 -5.78313410e-01
1.62951946e-01 4.58444417e-01 1.53697252e-01 -5.85778236e-01
4.22803491e-01 4.79564101e-01 -2.85630882e-01 -4.01671797e-01
7.78671354e-02 2.52898842e-01 4.66651380e-01 -6.09098256e-01
9.42601323e-01 5.29086888e-01 3.70555699e-01 -4.84814018e-01
-6.02350771e-01 -6.42440617e-01 -3.41843665e-01 -1.24578737e-01
3.47504348e-01 -4.21344608e-01 -9.78188872e-01 3.94631088e-01
-1.00751042e+00 9.81333628e-02 -2.56707340e-01 1.03568897e-01
-4.41012472e-01 6.20946050e-01 -4.62169886e-01 -6.98755443e-01
-5.96002698e-01 -9.35354412e-01 9.45209801e-01 1.56123132e-01
1.92824706e-01 -6.79977894e-01 -1.29815843e-02 5.58381248e-03
7.09039032e-01 -1.30256265e-01 1.07845342e+00 -7.37064660e-01
-8.10906410e-01 -2.70355374e-01 -7.73761988e-01 3.21015924e-01
-1.05467573e-01 -2.16155732e-03 -5.10478377e-01 -7.04428554e-01
-3.81554335e-01 -8.02162170e-01 1.23079526e+00 -2.13266939e-01
1.27478647e+00 -3.35443839e-02 -1.03915669e-01 5.20656407e-01
1.62959933e+00 2.05171369e-02 6.98163867e-01 4.72969919e-01
2.39195302e-01 5.26582837e-01 7.28354752e-01 2.31706858e-01
-2.55185068e-02 9.93283749e-01 5.82532227e-01 -2.59977490e-01
-1.85568526e-01 -2.89177746e-01 -3.81010436e-02 4.37987417e-01
7.07661361e-02 -4.74079281e-01 -5.95318973e-01 5.76902092e-01
-1.79775846e+00 -1.13930130e+00 6.53959215e-02 2.42442584e+00
6.15723789e-01 2.45832745e-02 1.14576675e-01 1.38212517e-01
5.77735305e-01 4.33808804e-01 -7.61084080e-01 -2.52838254e-01
-5.50365746e-01 5.21839678e-01 1.35058016e-01 -2.01917976e-01
-1.08993495e+00 8.00949395e-01 5.87114668e+00 1.45835841e+00
-1.50918376e+00 -2.97512412e-01 4.34516430e-01 1.82465538e-01
-5.88325381e-01 -2.72909611e-01 -3.05444360e-01 3.85379881e-01
1.51036769e-01 -7.51531273e-02 5.28426349e-01 4.02052790e-01
-5.40589988e-01 -2.59453468e-02 -1.19983006e+00 1.25864708e+00
4.80554014e-01 -1.17950511e+00 5.92127502e-01 -1.82794303e-01
5.44901192e-01 -6.03773966e-02 4.65150446e-01 3.04315746e-01
-3.00963700e-01 -9.12557781e-01 7.04256356e-01 4.07409668e-01
9.40129876e-01 -7.68461347e-01 6.58740878e-01 1.66152958e-02
-1.25986385e+00 -5.96293099e-02 -5.15244782e-01 4.59633648e-01
-2.69901842e-01 1.19260803e-01 -2.05980539e-01 6.81444764e-01
8.38433087e-01 5.99840760e-01 -8.96891952e-01 1.56129348e+00
-9.88752097e-02 1.80241302e-01 -3.77116114e-01 -3.80782902e-01
4.97606456e-01 -2.48072773e-01 4.93400276e-01 8.91823888e-01
3.57938230e-01 -4.10382360e-01 -1.80196747e-01 1.15913963e+00
-3.06168348e-01 3.77927661e-01 -6.74039960e-01 8.63352865e-02
1.52575895e-01 1.22893548e+00 -8.55204105e-01 -3.59889269e-01
-3.55338037e-01 1.09260058e+00 4.01372045e-01 3.71739566e-01
-6.99124515e-01 -5.89436650e-01 4.12080586e-01 -3.05807382e-01
5.73433995e-01 1.60292670e-01 1.62407801e-01 -1.25969851e+00
3.22171062e-01 -9.96901155e-01 6.75118029e-01 -6.80277944e-01
-1.84578061e+00 5.06328702e-01 -3.61049145e-01 -1.53418279e+00
4.92048413e-02 -7.53952503e-01 -6.12143517e-01 6.57337487e-01
-1.81911826e+00 -1.09527838e+00 -3.72020543e-01 7.99977422e-01
1.76725537e-01 -1.44818202e-01 6.94734097e-01 5.30213952e-01
-1.89572692e-01 1.12041855e+00 2.95112669e-01 9.87781063e-02
1.12026095e+00 -1.14317191e+00 3.13173234e-01 2.83462852e-01
6.02816463e-01 7.06090271e-01 1.77011564e-01 -2.80905306e-01
-1.68149698e+00 -6.43979192e-01 9.69832301e-01 -1.36006147e-01
6.36423469e-01 -2.59680986e-01 -9.58214104e-01 -2.22450927e-01
-8.08332264e-02 1.02637671e-01 4.16714102e-01 -8.73069391e-02
-8.94268394e-01 -6.21216893e-01 -1.17201161e+00 7.09618747e-01
1.06536007e+00 -6.85000300e-01 -3.30193937e-01 7.76343718e-02
1.07847437e-01 6.52580857e-02 -6.25589728e-01 4.98565853e-01
1.08862233e+00 -1.39568353e+00 1.45825028e+00 -6.19987667e-01
3.85180891e-01 -1.31839350e-01 -1.69468164e-01 -1.10804057e+00
-3.91534984e-01 -1.96307465e-01 2.13927075e-01 8.82043540e-01
3.94841760e-01 -6.19793475e-01 1.06388438e+00 1.51925489e-01
3.31846476e-01 -8.49854648e-01 -1.19401395e+00 -1.19857943e+00
2.19382167e-01 -8.44198391e-02 7.53050029e-01 8.37392509e-01
-2.24775404e-01 2.71917969e-01 -4.26422179e-01 -4.91565049e-01
6.58061802e-01 6.03032529e-01 4.90898669e-01 -1.46755338e+00
6.82436079e-02 -9.89802361e-01 -4.32274103e-01 -8.88904095e-01
2.32698709e-01 -9.78474319e-01 -5.59635535e-02 -1.31967866e+00
4.95651424e-01 -6.20223820e-01 -1.03332984e+00 4.23546404e-01
-7.19072223e-02 9.66543198e-01 6.37026012e-01 2.42752597e-01
-9.82794940e-01 5.63178658e-01 1.26491547e+00 -7.53623188e-01
3.63579661e-01 8.10452849e-02 -3.97400141e-01 1.94996789e-01
5.99802732e-01 -2.84643263e-01 -1.85120136e-01 -3.88249695e-01
8.52005303e-01 9.02560428e-02 6.86682284e-01 -9.60998356e-01
3.39363992e-01 -1.31591290e-01 3.22026879e-01 -7.88782775e-01
5.10202944e-01 -1.09672296e+00 -1.30020097e-01 6.65463448e-01
-5.40981829e-01 3.24302763e-01 3.84703465e-02 5.23686886e-01
-6.91913784e-01 -3.71036112e-01 5.50020754e-01 -6.27371967e-02
-7.38285363e-01 4.41630453e-01 1.98478177e-02 1.07660018e-01
6.92433059e-01 -4.04070616e-01 -6.07409477e-01 -5.11992097e-01
-2.20606714e-01 1.89410195e-01 6.56347454e-01 5.12203813e-01
1.04324841e+00 -1.77425992e+00 -7.50022113e-01 3.35831344e-01
6.93164349e-01 -7.13601768e-01 2.45895818e-01 7.76303530e-01
-2.79260457e-01 7.01779246e-01 -6.00007653e-01 -3.41454566e-01
-1.24574745e+00 8.64922643e-01 2.48632863e-01 -4.20447916e-01
5.41885477e-03 8.61922860e-01 2.83385366e-01 -2.77764708e-01
3.49556625e-01 1.00696839e-01 -9.82750729e-02 2.19356269e-01
3.09740007e-01 4.26131427e-01 2.64633149e-01 -5.83204210e-01
-6.19775772e-01 8.79890800e-01 4.53015044e-02 5.85588031e-02
1.09735394e+00 2.74273962e-01 -3.22983593e-01 1.64988607e-01
1.47162950e+00 -1.97137117e-01 -7.36762643e-01 -4.47208226e-01
7.60557726e-02 -5.96822083e-01 -3.21629673e-01 -1.10084867e+00
-1.38857114e+00 1.14234209e+00 8.19846988e-01 3.52207124e-01
1.10046172e+00 -1.20548368e-01 9.29970741e-01 8.95977378e-01
6.51966929e-01 -1.13856328e+00 4.73215818e-01 4.26491112e-01
1.15739787e+00 -1.48560417e+00 -9.25421268e-02 1.05812788e-01
-2.41117865e-01 1.22868586e+00 6.80503368e-01 -1.30515158e-01
4.41623390e-01 -4.68677342e-01 -6.76943436e-02 -3.44514310e-01
-6.63639665e-01 -4.06436592e-01 8.64996314e-01 4.41236407e-01
2.35959142e-01 -7.44605586e-02 -7.30069339e-01 9.38373581e-02
3.73823553e-01 -1.78175300e-01 -4.57206368e-02 7.32698202e-01
-1.04265667e-01 -1.33269274e+00 -4.08983052e-01 4.43515599e-01
-3.65108550e-01 -2.98126042e-01 -9.48415458e-01 7.13876128e-01
-2.52774246e-02 6.09504342e-01 1.66159086e-02 -2.06780046e-01
4.77662623e-01 -1.38918608e-01 6.41048789e-01 5.97876171e-03
-9.75996315e-01 -1.87023833e-01 -2.87207156e-01 -6.99695468e-01
-4.04691309e-01 -1.49615929e-01 -5.79320133e-01 -1.34609371e-01
-4.60277498e-01 1.30937994e-01 5.36540687e-01 3.42014551e-01
1.43038496e-01 -6.09669313e-02 7.31532216e-01 -6.39789224e-01
-7.86616623e-01 -5.41836679e-01 -6.05398774e-01 8.27497959e-01
3.61607969e-01 -6.53636336e-01 -2.05424875e-01 -7.21421838e-01] | [11.360757827758789, 0.6696395874023438] |
b7c0e398-e48a-4f06-a951-aa8487a06a27 | partial-explainer-abductive-natural-language | 2105.03417 | null | https://arxiv.org/abs/2105.03417v2 | https://arxiv.org/pdf/2105.03417v2.pdf | Diff-Explainer: Differentiable Convex Optimization for Explainable Multi-hop Inference | This paper presents Diff-Explainer, the first hybrid framework for explainable multi-hop inference that integrates explicit constraints with neural architectures through differentiable convex optimization. Specifically, Diff-Explainer allows for the fine-tuning of neural representations within a constrained optimization framework to answer and explain multi-hop questions in natural language. To demonstrate the efficacy of the hybrid framework, we combine existing ILP-based solvers for multi-hop Question Answering (QA) with Transformer-based representations. An extensive empirical evaluation on scientific and commonsense QA tasks demonstrates that the integration of explicit constraints in an end-to-end differentiable framework can significantly improve the performance of non-differentiable ILP solvers (8.91% - 13.3%). Moreover, additional analysis reveals that Diff-Explainer is able to achieve strong performance when compared to standalone Transformers and previous multi-hop approaches while still providing structured explanations in support of its predictions. | ['André Freitas', 'Julia Rozanova', 'Deborah Ferreira', 'Marco Valentino', 'Mokanarangan Thayaparan'] | 2021-05-07 | null | null | null | null | ['multi-hop-question-answering'] | ['knowledge-base'] | [ 9.76087525e-02 9.38645244e-01 -1.82715982e-01 -6.18201554e-01
-1.24621177e+00 -5.85888386e-01 5.06821573e-01 -1.05793968e-01
1.96024701e-01 9.81793582e-01 2.11359203e-01 -7.73908973e-01
-5.18736899e-01 -7.55301893e-01 -1.09973371e+00 8.96374285e-02
1.85458824e-01 9.40010548e-01 -3.69788259e-01 -4.34011370e-01
3.18132192e-01 2.58176982e-01 -1.47164476e+00 5.64286113e-01
1.46333647e+00 9.26737428e-01 -3.47310044e-02 5.91452241e-01
-4.87466782e-01 1.09932446e+00 -4.26169217e-01 -6.31728888e-01
3.31359752e-03 -2.43273735e-01 -1.28916025e+00 -5.16604602e-01
8.57811153e-01 -1.56978607e-01 8.15197229e-02 6.27247095e-01
-4.15293984e-02 1.67439058e-01 3.77854705e-01 -1.32624054e+00
-1.16295469e+00 9.80308831e-01 1.42818373e-02 3.26084010e-02
5.44659972e-01 4.00770098e-01 1.65414310e+00 -9.18989241e-01
4.97645825e-01 1.62571836e+00 6.65367544e-01 5.42594075e-01
-1.45162463e+00 -4.20084745e-01 3.01474094e-01 5.91697752e-01
-9.18327153e-01 -1.75174713e-01 6.45938993e-01 -1.22681089e-01
1.60114443e+00 6.41735256e-01 4.80560511e-01 9.60437655e-01
2.22314849e-01 6.60519898e-01 1.15239596e+00 -1.39029443e-01
1.45875365e-01 2.28072301e-01 6.60829008e-01 1.12700665e+00
2.15944543e-01 3.56448106e-02 -7.82097936e-01 -8.54737014e-02
3.66887212e-01 -3.89965534e-01 -2.60876656e-01 -8.72682855e-02
-1.12414467e+00 1.06641972e+00 8.01379025e-01 1.98714808e-01
-4.86095786e-01 6.13488436e-01 1.34379804e-01 1.09034531e-01
4.74062592e-01 1.23483717e+00 -8.45010221e-01 -1.76972702e-01
-1.11143124e+00 6.32514358e-01 1.12580585e+00 8.34753990e-01
8.16531420e-01 2.66743302e-01 -5.72844207e-01 1.88132137e-01
3.37506175e-01 3.63674223e-01 1.78686827e-02 -1.60421610e+00
6.31017089e-01 8.41551900e-01 3.62225100e-02 -9.29288507e-01
-4.08148795e-01 -8.60298693e-01 -4.71321791e-01 -1.66534800e-02
3.56452823e-01 -1.03078611e-01 -7.81765223e-01 1.76754797e+00
1.60291076e-01 1.94123298e-01 1.54433221e-01 9.83928561e-01
1.07507050e+00 7.97320008e-01 1.10972278e-01 1.16925724e-01
1.39208901e+00 -1.33574343e+00 -6.66929722e-01 -4.38539505e-01
3.46592456e-01 1.23464586e-02 1.44360030e+00 5.02122998e-01
-1.49121130e+00 -3.19410682e-01 -8.93382251e-01 -7.80849516e-01
-4.61715460e-01 5.56273619e-03 9.94971931e-01 3.78168613e-01
-1.11328018e+00 5.83612680e-01 -4.87109303e-01 2.26294622e-01
5.44401288e-01 4.59282786e-01 -8.56801942e-02 -1.34722650e-01
-1.11054063e+00 1.23482430e+00 3.14165711e-01 -3.10674403e-02
-8.14673126e-01 -1.47909486e+00 -7.83810616e-01 7.89977372e-01
5.74622452e-01 -1.33674526e+00 1.20601499e+00 -6.61315978e-01
-1.51868558e+00 4.65469271e-01 -6.36062860e-01 -8.31089377e-01
4.27601099e-01 -5.23371339e-01 5.81399128e-02 2.66524583e-01
8.70952234e-02 7.90567100e-01 4.46905047e-01 -1.19546270e+00
-9.95901451e-02 -1.74673483e-01 5.97411752e-01 -1.08070999e-01
9.55993757e-02 -3.70841652e-01 -1.30745947e-01 -9.17603001e-02
-6.79918826e-02 -5.63816845e-01 -1.41307712e-01 4.74135093e-02
-7.56924689e-01 -3.92079800e-01 6.08182609e-01 -7.95873642e-01
7.93953955e-01 -1.41372871e+00 5.44906318e-01 2.02985108e-02
4.76333857e-01 -7.20459148e-02 -3.49265158e-01 1.27730832e-01
-2.52278298e-01 3.23361754e-01 -4.19632733e-01 -5.94900072e-01
6.04998767e-01 5.94179869e-01 -6.31251752e-01 -8.69636610e-02
7.21428633e-01 1.52010143e+00 -6.90284610e-01 -3.59076351e-01
5.93349449e-02 6.02913439e-01 -1.14298046e+00 2.28920937e-01
-9.74872530e-01 2.90899992e-01 -3.90894234e-01 6.32376790e-01
4.79776382e-01 -6.87876105e-01 3.84935811e-02 -2.07169205e-01
2.86458116e-02 8.00907671e-01 -7.86552548e-01 1.82687855e+00
-6.43998086e-01 7.63788700e-01 6.51144981e-02 -1.09315121e+00
7.35570908e-01 9.91153643e-02 9.40777585e-02 -7.93570876e-01
-1.54178470e-01 2.06433162e-01 -3.03292543e-01 -4.39025909e-01
8.09992731e-01 -1.50949448e-01 1.38413534e-01 3.37183565e-01
1.43169910e-01 -3.30973476e-01 1.73352733e-01 3.16131234e-01
1.02793157e+00 3.20874989e-01 -4.79142591e-02 -3.65762204e-01
8.22564840e-01 4.26629782e-01 4.83733445e-01 8.53296041e-01
3.24088693e-01 3.73075038e-01 7.26048827e-01 -5.51626742e-01
-8.24599385e-01 -9.33442652e-01 7.91288093e-02 1.11681199e+00
-1.83883265e-01 -4.77739871e-01 -7.90226161e-01 -7.87057161e-01
2.27976143e-01 1.61221564e+00 -6.63190782e-01 5.64296506e-02
-6.33281767e-01 -3.66767347e-01 6.89427853e-01 5.19274652e-01
3.55043530e-01 -1.01706564e+00 -6.44267917e-01 1.20649286e-01
-4.51219827e-01 -1.08380818e+00 2.06990063e-01 3.50302219e-01
-8.33353519e-01 -1.06875384e+00 -1.61347941e-01 -2.54718304e-01
4.81607437e-01 -1.30786240e-01 1.59821296e+00 2.81804472e-01
-2.12790892e-01 4.49913174e-01 4.64849211e-02 -2.60989070e-01
-3.13753217e-01 3.33844543e-01 -4.41373229e-01 -5.97589314e-01
7.18742684e-02 -6.56555593e-01 -2.87379622e-01 -1.54228985e-01
-7.03313470e-01 1.99354678e-01 2.84628034e-01 9.67769384e-01
5.08530736e-01 -5.94619751e-01 6.45228565e-01 -9.80507076e-01
8.83428872e-01 -6.69315875e-01 -7.84607530e-01 5.63554525e-01
-1.12846661e+00 6.50635421e-01 7.23109603e-01 -1.10799566e-01
-9.98041153e-01 -3.37048978e-01 -1.05212308e-01 -2.85934806e-01
7.78693408e-02 8.15534770e-01 -3.82598839e-03 2.60034762e-02
7.01202571e-01 1.34202421e-01 -7.05438927e-02 -3.33577633e-01
9.94259894e-01 -1.94830317e-02 6.50630355e-01 -8.94055426e-01
1.05839026e+00 3.19564790e-02 1.26301706e-01 -1.15790322e-01
-1.37284744e+00 1.93742245e-01 -1.06346458e-01 2.06441090e-01
8.85376632e-01 -7.03748643e-01 -1.25147676e+00 -4.56359118e-01
-1.51276481e+00 -2.88292915e-01 -4.72530186e-01 1.04141012e-01
-7.19688892e-01 1.30887061e-01 -4.57621366e-01 -6.84446990e-01
-7.43798256e-01 -1.12729990e+00 1.06562579e+00 4.38380361e-01
-4.25276041e-01 -1.06418455e+00 -2.05471322e-01 1.20793581e+00
7.43428946e-01 2.38706991e-01 1.45434117e+00 -9.13109422e-01
-1.07710111e+00 2.76805639e-01 -4.39986497e-01 5.51403053e-02
-4.50134128e-01 -2.51221031e-01 -1.00108647e+00 2.80752897e-01
-2.57872313e-01 -4.82898474e-01 7.38170922e-01 1.91523507e-01
1.41666746e+00 -8.07649493e-01 9.29571167e-02 7.44672894e-01
1.44590604e+00 -5.22134006e-01 5.60688555e-01 4.21929508e-01
5.62629640e-01 4.00355339e-01 4.40493822e-01 4.06631708e-01
9.17433202e-01 3.82031739e-01 9.51467514e-01 -2.44300961e-02
1.04406752e-01 -2.67326593e-01 1.72175035e-01 3.14826697e-01
2.13142764e-03 -1.31920755e-01 -9.38864648e-01 4.25699025e-01
-1.83716142e+00 -9.23460603e-01 -4.42527860e-01 1.49098182e+00
9.56567228e-01 -7.43226409e-02 -2.92137444e-01 -2.10800186e-01
1.51189715e-01 -5.99078014e-02 -9.72384691e-01 -9.01328743e-01
-1.65069878e-01 6.70996010e-01 4.17038426e-02 8.13034654e-01
-4.21057880e-01 1.14634323e+00 7.16289330e+00 5.16048491e-01
-7.08646715e-01 1.04591027e-02 4.29258168e-01 -2.13171035e-01
-1.12518430e+00 1.74196869e-01 -6.18297160e-01 -4.54461612e-02
1.18932712e+00 -3.93044949e-01 1.06858468e+00 8.71043503e-01
1.98569328e-01 2.47702852e-01 -1.39904428e+00 6.48614466e-01
-2.19624918e-02 -2.04042363e+00 2.61181802e-01 -8.02288800e-02
6.75113678e-01 -4.24078964e-02 1.57674626e-01 7.35069215e-01
3.98792744e-01 -1.58724296e+00 6.45014107e-01 8.79718959e-01
3.51493925e-01 -7.59940982e-01 5.31467438e-01 5.16451776e-01
-6.49152219e-01 -2.56668627e-01 -2.86192298e-01 -1.80824101e-01
2.37261549e-01 5.79730511e-01 -9.77345526e-01 8.50800872e-01
4.31953102e-01 5.63456714e-01 -5.43311298e-01 5.87734401e-01
-6.14682138e-01 8.30732882e-01 -1.30698800e-01 -1.42041314e-03
4.50587392e-01 -1.12237856e-01 5.19633591e-01 1.21625698e+00
2.08219707e-01 1.09913766e-01 -2.65440106e-01 2.17803931e+00
-1.95837826e-01 -2.90988773e-01 -1.84945375e-01 -2.46826872e-01
3.77764493e-01 1.26912344e+00 3.24461818e-01 -5.22104383e-01
3.17365788e-02 7.53615737e-01 7.93659329e-01 3.41635436e-01
-1.28524005e+00 -1.21510856e-01 7.40673959e-01 -1.43948421e-01
3.39844942e-01 -2.44703114e-01 -8.46447945e-01 -1.17922938e+00
3.86449881e-02 -1.31833804e+00 2.83204019e-01 -1.33325672e+00
-1.23977768e+00 5.96578658e-01 -1.27654761e-01 -2.52625316e-01
-6.32440686e-01 -6.60047948e-01 -5.86617887e-01 1.21950495e+00
-2.01141644e+00 -1.41061747e+00 -4.69941586e-01 4.02990699e-01
4.24230456e-01 1.04857236e-01 1.04214919e+00 -1.57665908e-01
-5.92670321e-01 5.88747501e-01 -2.78829724e-01 -4.63891476e-01
8.24233294e-02 -1.69817019e+00 3.15109551e-01 4.56022769e-01
8.34569782e-02 9.39502060e-01 9.19033468e-01 -3.12561005e-01
-1.96147609e+00 -8.69102120e-01 1.18449152e+00 -5.17886877e-01
7.12653339e-01 -2.30914112e-02 -1.15148830e+00 8.31995666e-01
5.11798978e-01 -1.87318876e-01 3.97807330e-01 4.15685922e-01
-6.77410305e-01 5.36478199e-02 -1.28097939e+00 4.62528765e-01
8.31838250e-01 -5.79347312e-01 -1.04758012e+00 5.45522571e-01
1.13823581e+00 -5.27016819e-01 -9.69269693e-01 1.89688295e-01
2.42339477e-01 -1.06363475e+00 1.16566384e+00 -9.97331917e-01
1.20973635e+00 -9.45879072e-02 -2.30392054e-01 -1.07043886e+00
-2.38020793e-01 -7.33873427e-01 -5.70926785e-01 1.05086994e+00
7.45724738e-01 -7.76027262e-01 8.15507829e-01 1.16699481e+00
-2.50977665e-01 -1.09464180e+00 -1.03495717e+00 -4.07096505e-01
4.33666497e-01 -4.92792100e-01 8.66861999e-01 7.84818947e-01
2.09206343e-02 5.05035341e-01 -2.07645863e-01 3.92281830e-01
6.61066711e-01 4.50156838e-01 6.86828375e-01 -1.17712820e+00
-6.84794843e-01 -4.88971114e-01 1.45778492e-01 -1.11813867e+00
7.00625658e-01 -1.23890114e+00 -7.67809078e-02 -1.96616387e+00
9.21091288e-02 -1.28986731e-01 -6.71776459e-02 9.20031190e-01
-3.15627366e-01 -2.50593007e-01 3.68774742e-01 -2.53760099e-01
-5.08592963e-01 7.67956257e-01 1.14377987e+00 -3.90465230e-01
2.03597590e-01 -4.26778197e-01 -1.17939878e+00 4.00111556e-01
7.19370723e-01 -3.72823387e-01 -2.72319734e-01 -8.13032031e-01
4.78589892e-01 2.42635190e-01 7.94609368e-01 -7.16748059e-01
1.98664695e-01 -2.27806658e-01 7.52847046e-02 -5.57223082e-01
6.13776326e-01 -5.76869071e-01 -6.72471896e-02 4.29282993e-01
-7.41574526e-01 1.72628775e-01 4.76556450e-01 2.80831575e-01
-1.81383550e-01 -1.22236647e-01 3.41618150e-01 -2.28555933e-01
-3.85868341e-01 -1.63189530e-01 -6.64345920e-02 3.49690795e-01
5.71151495e-01 -2.93294229e-02 -8.34666669e-01 -4.61921394e-01
-5.56408644e-01 5.60807407e-01 -1.20579422e-01 1.62735522e-01
7.00346589e-01 -8.10356736e-01 -7.63642967e-01 -2.78568327e-01
-2.71530986e-01 -1.05719278e-02 3.71982716e-02 7.03300118e-01
-3.54461432e-01 9.95134950e-01 -5.13500385e-02 -3.68793756e-01
-1.01522100e+00 3.43048096e-01 6.52233839e-01 -7.27349102e-01
-4.63410974e-01 7.72739828e-01 -1.94266662e-01 -9.11692321e-01
1.46221548e-01 -6.29798770e-01 -7.25979079e-03 -4.04201001e-01
1.28714979e-01 4.34478998e-01 -1.76720381e-01 4.40939032e-02
-4.16262120e-01 2.08775356e-01 1.40859753e-01 -9.09927711e-02
1.79885900e+00 1.84136644e-01 -3.56243283e-01 1.78682148e-01
8.98644328e-01 -2.21940964e-01 -9.67547715e-01 -4.43784334e-03
-3.58643755e-02 -6.43540174e-02 1.44652694e-01 -1.60082960e+00
-9.51397717e-01 1.04881823e+00 -1.29563600e-01 2.50240117e-02
8.18822443e-01 2.77201794e-02 7.05519736e-01 8.60183299e-01
1.04553305e-01 -5.51349878e-01 3.80658335e-03 6.99182510e-01
1.30710447e+00 -9.62406576e-01 8.01002458e-02 -4.54367727e-01
-6.62079394e-01 1.17322814e+00 7.33180404e-01 -1.60688668e-01
-9.59278420e-02 -1.03844278e-01 -2.41864264e-01 -4.85956848e-01
-1.24630082e+00 9.18402448e-02 7.34861135e-01 3.07084382e-01
4.53590184e-01 -7.65873343e-02 -3.75077315e-02 8.83304715e-01
-6.47611558e-01 9.64658175e-05 3.70269895e-01 3.21265966e-01
-3.54462087e-01 -1.00457358e+00 -2.45196477e-01 1.65294886e-01
-2.35419288e-01 -4.42052662e-01 -6.25793934e-01 8.77084196e-01
1.89340971e-02 1.04469943e+00 -1.73056945e-01 -5.75432032e-02
2.34508738e-01 2.74875671e-01 3.60698551e-01 -3.67385536e-01
-1.25570798e+00 -6.52487457e-01 4.48851973e-01 -9.88884926e-01
-6.19488060e-02 -1.98729977e-01 -1.59903276e+00 -3.64682376e-01
-2.16877863e-01 3.36974889e-01 8.62995267e-01 1.28376055e+00
8.74860704e-01 9.41069722e-01 4.00985330e-02 -4.01470810e-01
-9.91718829e-01 -6.88045740e-01 4.59938236e-02 1.87660884e-02
4.20371890e-01 -3.78310025e-01 -4.34957653e-01 -1.91248864e-01] | [9.700113296508789, 7.30706262588501] |
6c50fc89-a80a-4bb6-b539-87436b6c9b38 | monotonic-neural-additive-models-pursuing | 2209.10070 | null | https://arxiv.org/abs/2209.10070v1 | https://arxiv.org/pdf/2209.10070v1.pdf | Monotonic Neural Additive Models: Pursuing Regulated Machine Learning Models for Credit Scoring | The forecasting of credit default risk has been an active research field for several decades. Historically, logistic regression has been used as a major tool due to its compliance with regulatory requirements: transparency, explainability, and fairness. In recent years, researchers have increasingly used complex and advanced machine learning methods to improve prediction accuracy. Even though a machine learning method could potentially improve the model accuracy, it complicates simple logistic regression, deteriorates explainability, and often violates fairness. In the absence of compliance with regulatory requirements, even highly accurate machine learning methods are unlikely to be accepted by companies for credit scoring. In this paper, we introduce a novel class of monotonic neural additive models, which meet regulatory requirements by simplifying neural network architecture and enforcing monotonicity. By utilizing the special architectural features of the neural additive model, the monotonic neural additive model penalizes monotonicity violations effectively. Consequently, the computational cost of training a monotonic neural additive model is similar to that of training a neural additive model, as a free lunch. We demonstrate through empirical results that our new model is as accurate as black-box fully-connected neural networks, providing a highly accurate and regulated machine learning method. | ['Weicheng Ye', 'Dangxing Chen'] | 2022-09-21 | null | null | null | null | ['additive-models'] | ['methodology'] | [ 9.62719172e-02 2.56469458e-01 -5.33475101e-01 -9.03940678e-01
-2.94533134e-01 -2.02115923e-01 2.28700846e-01 1.01391479e-01
-3.75203043e-01 9.81304049e-01 -2.49111801e-02 -5.64121485e-01
-2.08726659e-01 -8.97616744e-01 -5.38992465e-01 -4.53385770e-01
2.49962062e-01 3.32135588e-01 -2.94462413e-01 -9.89016239e-03
2.77950823e-01 4.94342178e-01 -1.08478153e+00 3.23738396e-01
1.33074498e+00 1.15425062e+00 -6.99647188e-01 1.53051587e-02
-3.38818505e-02 1.23187900e+00 -5.10585785e-01 -8.78959239e-01
3.67542565e-01 -4.19976771e-01 -5.27403831e-01 -6.08451188e-01
3.36584747e-01 -7.45830774e-01 -1.52876660e-01 9.40597713e-01
8.04932117e-02 1.62028596e-01 8.87409449e-01 -1.30315924e+00
-1.10331619e+00 8.81492198e-01 -5.32444179e-01 -2.37613171e-01
-2.45711893e-01 -1.58361971e-01 1.19601500e+00 -5.82173705e-01
-7.54405707e-02 9.59720671e-01 9.13886786e-01 7.10721672e-01
-1.28809118e+00 -1.08457828e+00 3.00070286e-01 9.35787335e-02
-1.10983372e+00 -2.66764075e-01 7.31717288e-01 -3.08619797e-01
7.93921530e-01 3.67904514e-01 4.25040126e-01 7.99035609e-01
3.35519940e-01 4.18403596e-01 1.04413319e+00 -3.43322486e-01
3.62842798e-01 4.00886446e-01 4.56393600e-01 3.92154187e-01
8.37040305e-01 2.98201412e-01 -4.66969013e-01 -3.39001387e-01
8.37019265e-01 2.73203164e-01 -2.59934723e-01 -2.63167024e-01
-5.59632957e-01 1.19081175e+00 5.97560525e-01 1.20308980e-01
-1.58996031e-01 2.82320917e-01 1.23497844e-01 3.09956193e-01
5.88885486e-01 6.35738492e-01 -4.34783071e-01 1.41370118e-01
-1.10427165e+00 3.37164283e-01 8.97779644e-01 4.17799532e-01
4.10918534e-01 4.54922408e-01 2.35495582e-01 7.80142665e-01
4.22016531e-01 3.26462299e-01 2.31788158e-01 -1.27100658e+00
3.62170845e-01 8.69239271e-01 2.22959861e-01 -1.12160552e+00
-5.74452758e-01 -6.16103172e-01 -1.25761926e+00 8.60594690e-01
8.68327022e-01 -6.01700470e-02 -3.75745147e-01 1.58220339e+00
-1.58375025e-01 -4.01036978e-01 -4.26899679e-02 9.41108048e-01
3.02451789e-01 5.11613548e-01 4.90815192e-02 -2.19385207e-01
9.38280225e-01 -6.46086812e-01 -7.33812153e-01 -1.43059731e-01
5.16597867e-01 -1.80143312e-01 1.18014908e+00 8.34253848e-01
-1.13687801e+00 -1.01888061e-01 -1.24397516e+00 -1.24413833e-01
-1.04650572e-01 -8.32458884e-02 8.62691820e-01 1.04600906e+00
-4.93330896e-01 8.81136537e-01 -6.63120627e-01 3.79471868e-01
7.24915445e-01 5.08262396e-01 -3.51099491e-01 6.09748438e-02
-1.33910882e+00 1.06542671e+00 1.09196559e-01 2.56548315e-01
-1.28714576e-01 -7.21934915e-01 -6.84204876e-01 7.38944829e-01
1.86277300e-01 -4.85902190e-01 1.23362494e+00 -1.23056746e+00
-1.47535622e+00 3.04912746e-01 1.56475350e-01 -7.60741591e-01
7.33051836e-01 -4.62984949e-01 -1.44859776e-01 -2.95283854e-01
-3.51114661e-01 2.75941193e-01 5.35831809e-01 -1.04599965e+00
-3.76071483e-01 -3.61831158e-01 8.65079537e-02 -1.17189400e-01
-5.59002221e-01 1.73561230e-01 3.85127753e-01 -7.73608983e-01
3.34493928e-02 -6.80066288e-01 -3.38682324e-01 3.47879559e-01
-2.43065745e-01 7.87412301e-02 2.94699222e-01 -5.39777994e-01
1.44839621e+00 -1.96030533e+00 -6.21189117e-01 4.82727885e-01
3.83100927e-01 8.12489316e-02 4.82605904e-01 -1.66958451e-01
-1.40405938e-01 4.65851307e-01 -5.34995139e-01 -1.01600610e-01
1.89386934e-01 -3.28525342e-02 -3.83259445e-01 3.85419607e-01
2.68561870e-01 7.25245118e-01 -4.23706114e-01 -1.72330901e-01
-9.59263667e-02 4.64634866e-01 -7.35162199e-01 6.87962323e-02
1.89578444e-01 -9.21482816e-02 -2.38559484e-01 6.33614421e-01
6.87087953e-01 -2.79764563e-01 2.42571533e-01 1.68225124e-01
1.22070827e-01 3.06812435e-01 -1.02667606e+00 5.90080202e-01
-4.29570943e-01 6.62644863e-01 -2.44952679e-01 -1.13460541e+00
1.22718298e+00 3.21883231e-01 1.42507717e-01 -8.13839138e-01
4.91283908e-02 4.08531547e-01 5.23157008e-02 -1.00893185e-01
3.98909777e-01 -5.56757092e-01 -8.90036896e-02 7.20903158e-01
-6.01223171e-01 1.51096463e-01 -3.10929179e-01 -1.86171710e-01
5.86855650e-01 -1.56870577e-02 6.01303756e-01 -3.61881666e-02
1.56222329e-01 -6.19688369e-02 9.79852617e-01 7.30050623e-01
-2.49232322e-01 5.64028323e-01 7.91064322e-01 -8.74346375e-01
-9.43370879e-01 -9.07011390e-01 -1.40655383e-01 9.00483608e-01
-2.68482000e-01 2.49621823e-01 -7.38674462e-01 -6.79889798e-01
3.27104479e-01 1.07604301e+00 -7.86788285e-01 -3.66386563e-01
-6.10650063e-01 -8.75340521e-01 7.62981892e-01 8.30004275e-01
4.71179396e-01 -7.58142591e-01 -7.12734401e-01 1.45927846e-01
2.17444912e-01 -5.72454095e-01 -3.92062306e-01 4.82396454e-01
-1.10250545e+00 -1.03240871e+00 -5.03320396e-01 -3.16258818e-01
7.61405647e-01 2.95858663e-02 1.03124940e+00 2.81545073e-01
2.29108796e-01 -4.75336611e-01 -3.79066132e-02 -5.90347230e-01
-3.45940828e-01 -1.49206728e-01 1.31579921e-01 3.17627750e-02
4.79705215e-01 -4.39473242e-01 -3.90694886e-01 4.15413618e-01
-7.59932637e-01 2.85833161e-02 5.07638693e-01 1.06638491e+00
3.74549657e-01 -3.28682959e-02 1.14474869e+00 -1.33320272e+00
7.37603784e-01 -4.40005988e-01 -7.31841445e-01 1.69512942e-01
-1.39417386e+00 7.20423758e-02 8.25986326e-01 -4.51299399e-01
-1.27718711e+00 4.38802801e-02 2.15318173e-01 -3.05815563e-02
1.31103441e-01 8.16255629e-01 -2.13892221e-01 -1.16220422e-01
9.50423717e-01 -2.96768874e-01 5.79630286e-02 -5.12525797e-01
3.11289012e-01 7.76312709e-01 4.21043694e-01 -4.21544492e-01
6.41575813e-01 3.00584435e-01 -2.16256585e-02 -1.55045018e-01
-8.64183426e-01 2.37396270e-01 -4.14600194e-01 -1.25278965e-01
6.61345005e-01 -5.00297070e-01 -8.85879219e-01 3.17783564e-01
-1.07672417e+00 -2.33025312e-01 -1.23961113e-01 6.89392030e-01
-2.96636432e-01 2.13005319e-01 -5.03188491e-01 -1.15239596e+00
-4.41991091e-01 -7.79652178e-01 -6.25715703e-02 2.50694692e-01
-6.34377420e-01 -9.41743433e-01 -2.86209106e-01 4.99861658e-01
6.61795080e-01 4.52713430e-01 1.23485577e+00 -1.00748098e+00
-3.63994390e-01 -6.33399069e-01 -4.26773190e-01 5.51414609e-01
4.81009968e-02 8.05005878e-02 -9.47785735e-01 2.16633737e-01
1.99810565e-01 -2.32888311e-01 8.69506061e-01 5.14872849e-01
1.24624753e+00 -8.02215695e-01 2.36025915e-01 5.55894196e-01
1.05474746e+00 4.33903694e-01 4.51700538e-01 5.96181929e-01
4.45207536e-01 8.80670190e-01 2.63996840e-01 3.82054061e-01
4.52937871e-01 3.78799886e-01 6.15942538e-01 -1.38818458e-01
6.46109343e-01 4.85727284e-03 3.06294322e-01 2.56149709e-01
-3.28770995e-01 8.13019946e-02 -9.35163140e-01 1.15053624e-01
-1.93725407e+00 -1.13330269e+00 -3.67676198e-01 2.50941396e+00
1.01144874e+00 4.63148206e-01 4.57769930e-02 4.08705533e-01
5.58444560e-01 -2.77439713e-01 -6.60032153e-01 -9.42085922e-01
-1.56192645e-01 -6.43672049e-02 5.58641791e-01 4.68984455e-01
-1.01741517e+00 4.59180176e-01 6.56036139e+00 3.33486676e-01
-9.15930569e-01 -9.00125057e-02 1.19901633e+00 -4.23600227e-01
-5.21592021e-01 -2.37007201e-01 -4.54260916e-01 4.02797401e-01
9.69927728e-01 -3.37950736e-01 3.48271728e-01 1.16601014e+00
5.22800446e-01 8.39253217e-02 -1.29058850e+00 5.67676067e-01
-1.25401393e-01 -1.42100465e+00 1.06473975e-01 8.48502759e-03
7.45076537e-01 -4.70799148e-01 2.88596898e-01 3.57813835e-01
4.14164007e-01 -1.67575645e+00 7.88404286e-01 5.75399041e-01
6.02892280e-01 -1.06829059e+00 1.05725503e+00 3.48200709e-01
-3.90870005e-01 -2.86410779e-01 -5.04082561e-01 -5.69445252e-01
8.14509615e-02 8.36656272e-01 -2.89400250e-01 1.40178740e-01
6.61041915e-01 3.21963876e-01 -1.12451784e-01 1.01348197e+00
-2.82535970e-01 7.94780970e-01 -1.73191577e-01 -3.69409956e-02
-1.11685914e-03 -1.25562266e-01 -1.03466965e-01 1.03305674e+00
2.02779204e-01 1.03749596e-01 -3.62471730e-01 1.21123338e+00
-2.94411659e-01 1.13080189e-01 -4.02732283e-01 7.08366707e-02
3.32540959e-01 8.23675036e-01 -3.20247829e-01 -1.99890167e-01
-6.08257294e-01 3.70257765e-01 3.47589314e-01 3.66189361e-01
-8.85304272e-01 -5.22172749e-01 5.54039359e-01 1.54620558e-01
-1.97241664e-01 3.01166959e-02 -1.37880373e+00 -9.18165743e-01
1.03020042e-01 -8.32633793e-01 3.33854437e-01 -5.77697635e-01
-1.40223706e+00 5.18658340e-01 -2.58256227e-01 -1.25492036e+00
-3.10419947e-01 -5.40371656e-01 -7.19691217e-01 9.76730824e-01
-1.54055381e+00 -8.58013809e-01 -2.21151009e-01 2.85813928e-01
-3.96297313e-03 -2.68580407e-01 8.67746115e-01 3.73682410e-01
-6.06409848e-01 9.91608858e-01 3.12974483e-01 1.31620824e-01
8.77487361e-01 -1.26936531e+00 2.02264756e-01 5.76655090e-01
-9.87971276e-02 9.34927940e-01 5.27102709e-01 -4.54905838e-01
-5.61482251e-01 -1.04214609e+00 1.16577041e+00 -2.16020852e-01
6.01322651e-01 -2.05497220e-01 -1.40812516e+00 6.00402296e-01
-2.07666725e-01 -1.00310385e-01 1.02666414e+00 2.26558864e-01
-7.10938692e-01 -4.18712199e-01 -1.24953973e+00 4.61039513e-01
3.53879005e-01 -4.25454199e-01 -5.22623241e-01 -8.97678919e-03
6.39152169e-01 -8.05386528e-02 -8.73068690e-01 1.32912308e-01
9.98123884e-01 -1.09790015e+00 6.79000020e-01 -8.18027735e-01
8.17871749e-01 4.60870527e-02 2.33384897e-04 -9.37137961e-01
-3.94100159e-01 -4.24629360e-01 -3.75057340e-01 1.06675589e+00
9.36154544e-01 -9.40582991e-01 1.08473229e+00 1.52723753e+00
1.88312575e-01 -1.10565186e+00 -9.39570248e-01 -9.75942254e-01
5.72500169e-01 -5.39095104e-01 6.56407237e-01 1.22809863e+00
3.07545304e-01 -1.83233023e-01 -7.12022781e-01 -8.65982547e-02
6.54970348e-01 -5.86631447e-02 3.65693599e-01 -1.53604031e+00
-2.99436212e-01 -9.00935292e-01 -5.53433001e-02 -7.53710568e-01
1.07293814e-01 -7.13217795e-01 -2.53279716e-01 -1.26804173e+00
1.97798043e-01 -5.71968019e-01 -6.74721062e-01 8.96276593e-01
-1.58042699e-01 2.69151479e-01 2.21261322e-01 3.55316430e-01
9.24388617e-02 2.51765639e-01 7.04030633e-01 -2.13871315e-01
-3.36097866e-01 4.24352586e-01 -1.27942383e+00 9.11997736e-01
9.87318933e-01 -7.20866740e-01 -2.69943148e-01 -3.99698198e-01
6.76852345e-01 -1.09163016e-01 4.08050030e-01 -4.72383082e-01
8.05580467e-02 -4.92470980e-01 5.51403403e-01 -4.66162004e-02
1.99733209e-02 -1.00356746e+00 1.93391636e-01 6.08038723e-01
-7.26395130e-01 -1.56753287e-01 -5.23049906e-02 2.99469024e-01
-2.11261958e-01 -3.58244807e-01 8.65921974e-01 1.54005811e-01
5.24705537e-02 4.99103684e-03 -2.76409775e-01 -2.46026382e-01
8.15205395e-01 -4.64619666e-01 -4.74076688e-01 -5.85433543e-01
-5.37116587e-01 1.47672221e-01 3.73138934e-01 2.42117569e-01
5.63246429e-01 -1.17156792e+00 -8.21355939e-01 1.50968721e-02
-2.38240987e-01 -1.04020104e-01 3.78889441e-02 6.63837194e-01
-5.31713784e-01 3.31846982e-01 -2.54194081e-01 1.67311370e-01
-9.25431430e-01 3.57360512e-01 4.78679240e-01 -4.11969244e-01
-3.82958412e-01 6.22416675e-01 3.67074013e-01 -2.38104090e-01
4.06998515e-01 -4.33522493e-01 -4.00783122e-01 -1.18778408e-01
7.06912637e-01 6.00285590e-01 -1.63031846e-01 -1.64857969e-01
-1.85908645e-01 1.04365081e-01 -1.35854945e-01 1.13416553e-01
1.57896125e+00 1.99786201e-01 -1.77981034e-02 3.91666949e-01
6.39857948e-01 -9.48261023e-02 -1.25444198e+00 4.06433232e-02
1.64402410e-01 -4.76836890e-01 1.94160700e-01 -1.14929092e+00
-1.16178524e+00 1.11070561e+00 1.48108944e-01 3.39517802e-01
1.05736148e+00 -6.84458733e-01 4.74898905e-01 6.72284305e-01
1.39867991e-01 -1.12206984e+00 -3.08275193e-01 2.41689265e-01
9.73805964e-01 -1.40582919e+00 1.93083152e-01 -2.09853441e-01
-8.10826123e-01 1.31231546e+00 6.04117990e-01 -1.15489617e-01
5.36299169e-01 1.97328120e-01 1.61161810e-01 3.00577343e-01
-5.69203854e-01 7.73914456e-01 1.97974175e-01 5.48848510e-01
6.41327560e-01 7.12817311e-02 -3.79055083e-01 1.56405830e+00
-2.80088186e-01 2.00773433e-01 8.63000929e-01 4.66409653e-01
-5.17915070e-01 -8.52600515e-01 -3.30260247e-01 7.91687250e-01
-7.81768262e-01 -2.36968368e-01 -5.03418386e-01 8.15720916e-01
-1.06159031e-01 8.95474255e-01 4.33801338e-02 -3.16326708e-01
2.88681775e-01 2.81749889e-02 -2.13353038e-01 -3.56721997e-01
-8.09310436e-01 -4.05067891e-01 1.92384392e-01 -4.40089852e-01
-5.65445758e-02 -6.31822050e-01 -1.46593392e+00 -7.18125343e-01
-5.44699788e-01 4.94964942e-02 5.64672709e-01 9.21232820e-01
1.41645908e-01 4.24757749e-01 6.52617931e-01 -4.77698922e-01
-1.12335885e+00 -6.58714771e-01 -6.31870151e-01 6.67648911e-02
2.14629695e-01 -5.97827554e-01 -4.89240348e-01 5.04286587e-02] | [8.852985382080078, 5.326560020446777] |
42e965ff-a3b6-45f9-a0df-480bd4f80817 | interformer-real-time-interactive-image | 2304.02942 | null | https://arxiv.org/abs/2304.02942v1 | https://arxiv.org/pdf/2304.02942v1.pdf | InterFormer: Real-time Interactive Image Segmentation | Interactive image segmentation enables annotators to efficiently perform pixel-level annotation for segmentation tasks. However, the existing interactive segmentation pipeline suffers from inefficient computations of interactive models because of the following two issues. First, annotators' later click is based on models' feedback of annotators' former click. This serial interaction is unable to utilize model's parallelism capabilities. Second, the model has to repeatedly process the image, the annotator's current click, and the model's feedback of the annotator's former clicks at each step of interaction, resulting in redundant computations. For efficient computation, we propose a method named InterFormer that follows a new pipeline to address these issues. InterFormer extracts and preprocesses the computationally time-consuming part i.e. image processing from the existing process. Specifically, InterFormer employs a large vision transformer (ViT) on high-performance devices to preprocess images in parallel, and then uses a lightweight module called interactive multi-head self attention (I-MSA) for interactive segmentation. Furthermore, the I-MSA module's deployment on low-power devices extends the practical application of interactive segmentation. The I-MSA module utilizes the preprocessed features to efficiently response to the annotator inputs in real-time. The experiments on several datasets demonstrate the effectiveness of InterFormer, which outperforms previous interactive segmentation models in terms of computational efficiency and segmentation quality, achieve real-time high-quality interactive segmentation on CPU-only devices. | ['Liujuan Cao', 'Rongrong Ji', 'Guannan Jiang', 'Shengchuan Zhang', 'Ke Sun', 'Hao Yang', 'You Huang'] | 2023-04-06 | null | null | null | null | ['interactive-segmentation'] | ['computer-vision'] | [ 3.81708652e-01 -3.16067436e-03 6.61175232e-03 -3.62894714e-01
-9.41050529e-01 -6.21359825e-01 -1.79018840e-01 3.44352536e-02
-7.71113932e-01 -1.13931753e-01 -3.70953172e-01 -4.18171376e-01
4.51867640e-01 -5.08211315e-01 -4.61714387e-01 -4.81862754e-01
5.90825617e-01 4.75314975e-01 9.97672558e-01 3.14425856e-01
3.68349880e-01 3.32887858e-01 -1.64718461e+00 3.75790000e-01
1.03320754e+00 1.07863605e+00 7.72174656e-01 9.26813960e-01
-2.80779928e-01 2.54442096e-01 -4.75270241e-01 -1.93415627e-01
3.02634627e-01 -1.15692668e-01 -6.57099664e-01 7.32967779e-02
3.08699071e-01 -7.38016307e-01 5.93589172e-02 1.02123129e+00
4.54686701e-01 -1.98612362e-01 1.58514932e-01 -1.29965043e+00
-1.51855871e-01 5.28548956e-01 -7.98236191e-01 1.29182309e-01
3.22699815e-01 6.38410926e-01 8.91501725e-01 -8.70572031e-01
4.75844979e-01 9.21575427e-01 6.85603619e-01 3.48274678e-01
-1.01145756e+00 -6.30904615e-01 2.53555059e-01 8.83082673e-03
-1.22138989e+00 -1.54234961e-01 4.34241712e-01 -3.90822768e-01
8.61819685e-01 4.13708121e-01 8.90716076e-01 4.04821634e-01
8.96492675e-02 1.25448179e+00 9.07954156e-01 -2.97782630e-01
3.55808586e-01 -2.46834406e-03 5.08106887e-01 7.72582710e-01
-1.10258557e-01 -3.70443821e-01 -4.76127654e-01 1.79981723e-01
8.34783435e-01 -8.30543637e-02 -2.88585812e-01 7.51469508e-02
-1.12255728e+00 4.67267156e-01 2.61973053e-01 4.57476750e-02
-4.62793171e-01 1.33582801e-01 5.27112663e-01 -1.34761244e-01
1.32297322e-01 1.54769942e-01 -5.14301956e-01 -3.57786715e-01
-1.24373734e+00 -1.49623126e-01 7.18392849e-01 1.08003068e+00
8.34160268e-01 -2.68655360e-01 -1.97628438e-01 6.53241038e-01
3.46090049e-01 5.17422915e-01 5.00914156e-01 -9.92898583e-01
3.31352949e-01 8.40231180e-01 6.03376469e-03 -7.56456435e-01
-5.08694828e-01 -1.11429483e-01 -5.29125988e-01 1.23314030e-01
4.73876715e-01 -1.50280669e-01 -1.02068734e+00 1.09820700e+00
5.34798741e-01 -1.34283658e-02 -3.52150798e-01 1.30817246e+00
1.01124370e+00 5.91635764e-01 3.53547305e-01 -1.09970294e-01
1.67112660e+00 -1.25301147e+00 -6.52025998e-01 -2.52007306e-01
4.43696111e-01 -9.43102002e-01 1.59496701e+00 4.69788611e-01
-1.22591257e+00 -8.50372612e-01 -9.80493248e-01 -3.96616846e-01
-1.92260191e-01 5.38089335e-01 8.12121809e-01 5.67871392e-01
-9.34546173e-01 3.84928018e-01 -1.17211235e+00 -1.68599069e-01
3.72806877e-01 7.10176528e-01 -8.84619635e-03 2.69307107e-01
-7.44698763e-01 2.56939054e-01 3.01463902e-01 2.64860243e-01
-2.49013975e-01 -7.57086456e-01 -5.39621711e-01 2.35155895e-01
7.05079556e-01 -5.77653050e-01 1.57664979e+00 -1.19809151e+00
-1.67717528e+00 7.53268003e-01 -2.45549068e-01 -9.31928009e-02
6.38675034e-01 -3.70696485e-01 2.57293507e-02 4.52598602e-01
2.38000959e-01 8.97503674e-01 6.51530504e-01 -9.14306343e-01
-8.78294468e-01 -4.68739092e-01 1.20679510e-03 3.87195587e-01
-2.74067461e-01 -3.13910954e-02 -1.55431628e+00 -3.23160261e-01
2.91892976e-01 -1.01583540e+00 -2.49675706e-01 2.38211006e-01
-5.55395186e-01 -1.84121430e-01 1.05432785e+00 -4.98972714e-01
1.32141995e+00 -2.32014084e+00 -3.26353729e-01 1.86203301e-01
1.87611714e-01 6.92557395e-01 5.91726974e-02 4.26429696e-03
2.12580189e-01 1.43795013e-02 -5.66325784e-02 -5.41511416e-01
-3.31614465e-02 3.11120510e-01 8.83245468e-02 9.16897133e-02
-9.31970924e-02 9.75696802e-01 -5.45287609e-01 -1.04702151e+00
3.88235688e-01 1.48510084e-01 -6.36277437e-01 3.88700634e-01
-1.61520332e-01 2.27349356e-01 -5.63944042e-01 7.13254035e-01
7.79434264e-01 -4.59867448e-01 -8.75668484e-05 -5.73367655e-01
-4.86414313e-01 -3.39321047e-02 -1.26926935e+00 1.79168224e+00
-2.65473932e-01 3.76595676e-01 4.64596510e-01 -5.80253422e-01
4.53844875e-01 2.25785255e-01 3.83742094e-01 -6.47363842e-01
2.35278890e-01 2.59898305e-01 -3.02093953e-01 -7.20613301e-01
5.40097415e-01 6.36966407e-01 7.21722394e-02 6.06766582e-01
-3.53456497e-01 -9.46120471e-02 2.40528762e-01 3.39675009e-01
1.05968583e+00 4.09728616e-01 1.65215880e-02 7.18768165e-02
4.54801410e-01 3.45201224e-01 6.69704378e-01 9.21628833e-01
-2.74923712e-01 5.40567935e-01 2.96582371e-01 -4.12732542e-01
-8.57811511e-01 -7.58988678e-01 2.15710193e-01 1.33041596e+00
4.38066125e-01 -4.91837740e-01 -1.26867771e+00 -7.84959435e-01
-3.11224490e-01 4.35116231e-01 -2.08865464e-01 3.60588670e-01
-4.89730775e-01 -3.28061640e-01 2.69220233e-01 9.24982965e-01
8.09553623e-01 -1.20197940e+00 -1.42376935e+00 1.71651363e-01
-2.43974879e-01 -1.13814425e+00 -9.34112668e-01 5.13131805e-02
-7.76807070e-01 -9.97309446e-01 -2.83215165e-01 -5.88938355e-01
8.68332386e-01 3.51949334e-01 7.76507795e-01 2.67236173e-01
-5.87367952e-01 2.09936097e-01 -2.98077971e-01 -2.50785142e-01
-8.23625177e-02 2.07319379e-01 -3.57747167e-01 -1.34393781e-01
3.62237602e-01 -2.44847164e-01 -9.62268054e-01 5.29396296e-01
-1.00768113e+00 7.07933843e-01 8.04864228e-01 5.88321269e-01
1.04546964e+00 -2.49222428e-01 1.66182071e-01 -1.19526994e+00
3.25260997e-01 1.33519657e-02 -9.74479318e-01 1.77873850e-01
-4.98433411e-01 -1.83307230e-01 6.82092369e-01 -4.17385519e-01
-1.06032658e+00 7.22569823e-01 -2.99927771e-01 -5.22955596e-01
-1.50866732e-01 4.04459625e-01 -2.73672193e-01 9.90261361e-02
2.07309559e-01 1.60881087e-01 -4.23284173e-02 -4.18430209e-01
2.20364258e-01 9.16829109e-01 8.41319203e-01 -2.24171922e-01
4.28087443e-01 2.53268093e-01 -4.75417048e-01 -5.56766808e-01
-6.63878918e-01 -7.28173554e-01 -7.12815166e-01 -4.68419969e-01
1.09013653e+00 -7.61098802e-01 -1.33771837e+00 6.18670046e-01
-1.16882193e+00 -3.68077457e-01 -2.38772221e-02 3.88088852e-01
-3.09189588e-01 4.61447537e-01 -7.19058335e-01 -7.58281231e-01
-7.78314948e-01 -1.60412562e+00 1.31272638e+00 8.07434082e-01
-2.86988020e-01 -4.10460979e-01 -6.54821455e-01 8.11899483e-01
1.57637388e-01 -2.69297779e-01 6.09602809e-01 -5.31324804e-01
-9.17220235e-01 -3.23691785e-01 -6.72645330e-01 1.95978031e-01
-2.60935128e-01 2.49549121e-01 -9.69736040e-01 2.74865888e-02
-2.98525393e-01 -1.33524165e-01 3.86012822e-01 4.44401085e-01
1.49460351e+00 -4.95282002e-02 -4.99035358e-01 5.56644201e-01
1.38092649e+00 4.06201959e-01 5.33471107e-01 1.32586688e-01
7.76121736e-01 2.89226085e-01 9.95993197e-01 2.99319863e-01
4.11178201e-01 6.62410378e-01 3.41231167e-01 -5.32763362e-01
5.49563728e-02 -5.39793670e-02 1.95723906e-01 9.99139130e-01
-1.94567125e-02 -4.59409058e-02 -9.50946748e-01 3.76432747e-01
-2.04828143e+00 -5.68886101e-01 -5.82809806e-01 2.11774540e+00
7.23999619e-01 2.96424747e-01 -5.02652042e-02 -2.12109517e-02
6.03550732e-01 -2.90291697e-01 -9.64781940e-01 -4.85109061e-01
5.68440020e-01 2.63123125e-01 7.28427768e-01 2.78169453e-01
-1.05611956e+00 1.17779195e+00 5.42185593e+00 8.92376184e-01
-1.09489632e+00 1.45070836e-01 6.84572101e-01 5.02321832e-02
8.96987021e-02 3.07817310e-02 -9.67190921e-01 6.55425012e-01
6.88148081e-01 3.81164014e-01 2.13661119e-01 1.17275047e+00
5.33404768e-01 -7.65989840e-01 -1.06266844e+00 1.01419330e+00
-1.44960716e-01 -1.11401772e+00 -1.99050412e-01 -1.86887071e-01
2.07721025e-01 -5.39022982e-02 -1.83798328e-01 1.35439813e-01
4.40415069e-02 -5.38678288e-01 6.74952984e-01 3.68794113e-01
8.99856806e-01 -6.47596836e-01 8.21221113e-01 4.02807832e-01
-1.20972478e+00 1.26903474e-01 3.64115611e-02 1.32578775e-01
3.36726457e-01 5.84543407e-01 -8.23873520e-01 2.85577357e-01
8.89577568e-01 4.38401960e-02 -6.15306914e-01 8.59816432e-01
-1.66967839e-01 7.56324887e-01 -5.64037263e-01 -6.79502115e-02
3.82948101e-01 -2.46514246e-01 1.81047514e-01 1.32854700e+00
7.92159438e-02 3.82382125e-01 5.30485272e-01 6.82105422e-01
1.88528374e-01 2.72421926e-01 2.31117249e-01 -1.69308241e-02
4.74178791e-01 1.63599586e+00 -1.22789824e+00 -7.23637402e-01
-4.70148593e-01 1.40664899e+00 1.92153966e-03 1.42491981e-01
-1.22458518e+00 -7.05979466e-01 8.43187794e-02 1.71708912e-01
3.81140023e-01 -1.11651860e-01 -6.65190160e-01 -7.72713602e-01
1.75263554e-01 -7.49001443e-01 2.27059856e-01 -1.09893036e+00
-6.73658133e-01 5.27259231e-01 -3.33491147e-01 -8.15738738e-01
1.52930811e-01 -3.45277935e-01 -6.09319091e-01 8.06213200e-01
-1.06281996e+00 -1.35544419e+00 -7.69107223e-01 6.75950468e-01
1.03970444e+00 3.66958767e-01 6.33488297e-01 3.05553794e-01
-9.04612482e-01 5.63324690e-01 -5.38798749e-01 1.84272394e-01
5.05254328e-01 -1.34351182e+00 5.44689894e-01 7.56291926e-01
-6.89109415e-02 4.39424902e-01 3.96781385e-01 -7.24554718e-01
-1.63147795e+00 -8.68272245e-01 6.53112173e-01 5.23737594e-02
2.92067468e-01 -3.26262414e-01 -8.40664506e-01 5.23825645e-01
7.76384175e-02 5.87104298e-02 6.56002879e-01 -2.80884176e-01
8.38905573e-02 -1.21644467e-01 -9.95757759e-01 7.26651430e-01
8.66545737e-01 -2.80790091e-01 -2.83480018e-01 3.31749439e-01
5.93509853e-01 -6.15245640e-01 -6.06290460e-01 1.56645119e-01
8.24703038e-01 -9.92329359e-01 5.39648235e-01 8.87202248e-02
3.14373881e-01 -5.13418853e-01 3.29194814e-01 -5.44682980e-01
-1.49359312e-02 -6.85109794e-01 2.74661511e-01 1.19510543e+00
4.66425568e-01 -4.88463342e-01 8.46022904e-01 1.23584974e+00
-2.70189643e-01 -8.87241125e-01 -6.00915134e-01 -8.22992027e-02
-8.49276364e-01 -6.84825242e-01 4.18201596e-01 4.57853734e-01
-1.30310014e-01 2.57991880e-01 1.81993857e-01 4.01977241e-01
4.96586829e-01 2.47700021e-01 1.00500369e+00 -9.60075080e-01
-5.70847094e-01 -1.95334122e-01 -6.24157004e-02 -1.45546103e+00
-3.23238671e-01 -4.85503495e-01 3.18129480e-01 -1.55827773e+00
2.34150916e-01 -5.09412229e-01 1.62439927e-01 7.45432973e-01
-3.67010087e-01 5.21714866e-01 3.49264264e-01 4.37542737e-01
-9.79721844e-01 -1.22535259e-01 1.35293937e+00 5.15591204e-02
-5.28748751e-01 1.41864896e-01 -3.21412593e-01 1.02573502e+00
4.47689772e-01 -3.24181378e-01 -4.32602167e-01 -4.50942278e-01
-9.66111140e-04 1.45253271e-01 2.90943027e-01 -1.10017169e+00
7.46086121e-01 -8.46670344e-02 4.34687674e-01 -1.01229250e+00
2.92047083e-01 -8.80474329e-01 1.87043145e-01 4.91957426e-01
-9.73554626e-02 6.64764270e-02 1.87077790e-01 3.18816751e-01
-4.79545854e-02 -3.82079214e-01 7.07503200e-01 -2.19418317e-01
-8.04926455e-01 2.80792415e-01 -6.96561813e-01 -2.18119740e-01
1.17891622e+00 -8.04896474e-01 8.58913362e-03 6.98478147e-02
-9.45093870e-01 3.86272579e-01 4.70088184e-01 4.94115502e-02
4.33261156e-01 -6.63552821e-01 -1.54779747e-01 3.13435197e-01
-1.53437197e-01 4.39679265e-01 5.35360038e-01 1.14506614e+00
-9.91875529e-01 1.92575797e-01 9.06887427e-02 -8.42147291e-01
-1.63264132e+00 2.49949828e-01 -8.32107142e-02 -3.04320484e-01
-7.67603219e-01 8.42679799e-01 2.28593871e-01 -1.38859982e-02
1.77750930e-01 -5.51826656e-01 7.83697143e-02 1.45151675e-01
3.79680455e-01 3.10498238e-01 8.65136310e-02 -2.51080871e-01
-3.16822439e-01 6.85302913e-01 -3.93600553e-01 -2.08625898e-01
9.67224240e-01 -2.90360689e-01 3.96818109e-02 3.07226002e-01
8.40055645e-01 -1.16584025e-01 -1.48149359e+00 1.28050059e-01
-2.43132174e-01 -4.74312752e-01 1.92338988e-01 -9.94500458e-01
-1.24051797e+00 7.57810175e-01 6.27133191e-01 -5.29439189e-02
1.46145284e+00 -2.49145538e-01 1.20141315e+00 6.91432878e-02
3.27693760e-01 -1.66802263e+00 -5.68864979e-02 1.80151448e-01
4.12705392e-01 -1.13123059e+00 -3.67050655e-02 -7.30635464e-01
-8.50317478e-01 1.00591838e+00 1.00391531e+00 2.57855803e-01
4.43307340e-01 5.73585689e-01 3.32831472e-01 -1.64430767e-01
-4.48161095e-01 -1.75844491e-01 9.50553343e-02 1.56587481e-01
1.41413882e-01 6.32099435e-02 -4.50952053e-01 7.63481319e-01
-5.26541173e-02 1.39864638e-01 3.01771581e-01 9.46717918e-01
-4.39947665e-01 -8.71050715e-01 -3.62392128e-01 4.52516496e-01
-4.40696746e-01 8.14571977e-02 -3.11624348e-01 6.09804571e-01
3.71582091e-01 9.17869866e-01 2.52579719e-01 -2.64284164e-01
2.84659177e-01 -3.58809717e-02 -1.00324981e-01 -6.17148876e-01
-1.05950963e+00 4.81770545e-01 -1.87079370e-01 -1.03076029e+00
-2.46497840e-01 -4.28886443e-01 -1.65892160e+00 -5.83608523e-02
-6.00698173e-01 3.26548517e-02 1.05116200e+00 8.59519303e-01
6.14976406e-01 5.40116727e-01 3.39950621e-01 -9.48929191e-01
-1.89863965e-01 -7.35545456e-01 -2.30151221e-01 3.34063441e-01
-2.20629781e-01 -2.21742377e-01 -3.05947233e-02 4.17409539e-01] | [9.526150703430176, -0.01348385401070118] |
788465b4-bf36-451a-94ea-88a99e4b56eb | tracking-multiple-deformable-objects-in | null | null | http://openaccess.thecvf.com//content/CVPR2023/html/Huang_Tracking_Multiple_Deformable_Objects_in_Egocentric_Videos_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Huang_Tracking_Multiple_Deformable_Objects_in_Egocentric_Videos_CVPR_2023_paper.pdf | Tracking Multiple Deformable Objects in Egocentric Videos | Most existing multiple object tracking (MOT) methods that solely rely on appearance features struggle in tracking highly deformable objects. Other MOT methods that use motion clues to associate identities across frames have difficulty handling egocentric videos effectively or efficiently. In this work, we propose DETracker, a new MOT method that jointly detects and tracks deformable objects in egocentric videos. DETracker uses three novel modules, namely the motion disentanglement network (MDN), the patch association network (PAN) and the patch memory network (PMN), to explicitly tackle the difficulties caused by severe ego motion and fast morphing target objects. DETracker is end-to-end trainable and achieves near real-time speed. We also present DogThruGlasses, a large-scale deformable multi-object tracking dataset, with 150 videos and 73K annotated frames, collected by smart glasses. DETracker outperforms existing state-of-the-art method on the DogThruGlasses dataset and YouTube-Hand dataset. | ['Siwei Lyu', 'Honghong Peng', 'Jun Hu', 'Xiaoxing Li', 'Mingzhen Huang'] | 2023-01-01 | null | null | null | cvpr-2023-1 | ['multiple-object-tracking', 'motion-disentanglement', 'multi-object-tracking', 'disentanglement'] | ['computer-vision', 'computer-vision', 'computer-vision', 'methodology'] | [-3.87942493e-01 -3.00834984e-01 -2.04744548e-01 6.73523396e-02
-6.18901908e-01 -5.92649758e-01 1.93152487e-01 -5.55520892e-01
-3.69282216e-01 5.73032796e-01 5.58206737e-02 5.36307037e-01
4.05057333e-02 -2.29774624e-01 -9.46069658e-01 -7.74263680e-01
-9.53851342e-02 4.81187135e-01 7.76828110e-01 2.77642936e-01
-5.09544052e-02 2.15356007e-01 -1.79086256e+00 1.57053977e-01
3.05729389e-01 8.41420174e-01 2.28696302e-01 9.18498933e-01
6.40697718e-01 9.53324854e-01 -1.13483325e-01 -4.12627369e-01
4.19791520e-01 1.83317792e-02 -5.94321907e-01 -2.88636476e-01
1.51325095e+00 -8.10517251e-01 -7.34463751e-01 1.08940661e+00
6.14266753e-01 3.78172755e-01 3.01776409e-01 -1.64432716e+00
-8.60331118e-01 3.98534685e-01 -7.51214802e-01 8.17731261e-01
3.39343548e-01 3.60431790e-01 6.50411963e-01 -9.25909996e-01
8.19005430e-01 1.48367679e+00 8.63912761e-01 1.00284314e+00
-8.95293474e-01 -9.65994954e-01 3.77421111e-01 3.18583012e-01
-1.31801164e+00 -6.58939123e-01 4.24926162e-01 -7.91166663e-01
8.97882104e-01 1.53915226e-01 7.61684895e-01 1.21771407e+00
2.80174732e-01 1.11295581e+00 6.21036649e-01 1.49455130e-01
-3.53106827e-01 -2.71091431e-01 2.80379551e-03 9.46911871e-01
4.42669690e-01 2.73932606e-01 -5.17017126e-01 -1.63771614e-01
9.72487390e-01 2.57171988e-01 -3.41207713e-01 -6.24387503e-01
-1.55640614e+00 3.69874924e-01 2.49434337e-01 1.76370994e-03
-1.21234372e-01 7.48332858e-01 2.99753457e-01 5.18200323e-02
2.96540320e-01 -1.31767783e-02 -4.83328730e-01 -1.73375532e-01
-7.13003933e-01 5.18225968e-01 3.58883530e-01 1.25532961e+00
5.47360957e-01 1.50427669e-01 -3.87494355e-01 3.20029765e-01
6.16147220e-01 7.43830562e-01 5.56466401e-01 -9.31002140e-01
3.50937545e-01 3.75984132e-01 2.65736878e-01 -1.14225650e+00
-3.46877396e-01 1.57385334e-01 -2.51161993e-01 5.33044823e-02
5.20691931e-01 -2.01632008e-01 -7.88710654e-01 1.98608315e+00
9.87897038e-01 1.06691611e+00 -1.26557156e-01 1.28835559e+00
1.39049232e+00 1.58753723e-01 3.21376324e-01 9.79358181e-02
1.47433150e+00 -1.50079083e+00 -6.90283597e-01 -7.83346072e-02
6.77923262e-01 -5.78964233e-01 6.70795202e-01 4.81259674e-02
-1.16557086e+00 -7.43818760e-01 -6.28721237e-01 -1.40695646e-01
-2.48352066e-01 3.31011951e-01 6.09588385e-01 4.95130777e-01
-9.49696541e-01 6.87201917e-01 -1.21363330e+00 -2.89152890e-01
6.42032564e-01 6.94923162e-01 -6.13746285e-01 1.95977300e-01
-6.83068454e-01 6.16027594e-01 3.45423073e-01 2.58990347e-01
-1.26977253e+00 -8.42273772e-01 -8.98089051e-01 -2.38291577e-01
5.43108642e-01 -1.15701318e+00 9.76171315e-01 -8.68291914e-01
-1.31607616e+00 9.72093165e-01 -5.62112778e-03 -2.86082417e-01
7.01708734e-01 -7.33521640e-01 -5.25835574e-01 2.82654613e-01
1.15723580e-01 9.30610716e-01 1.04717791e+00 -7.23815918e-01
-6.87253177e-01 -3.21342260e-01 -4.13891487e-02 9.90974754e-02
-2.79079914e-01 3.44166160e-01 -5.57522357e-01 -8.60998452e-01
-4.21694219e-01 -1.45098853e+00 2.35126436e-01 4.15959060e-01
-3.33087057e-01 -5.39236903e-01 1.42389178e+00 -4.25078154e-01
9.65653062e-01 -2.01444197e+00 5.70978880e-01 -4.67790335e-01
6.14314675e-01 4.23633009e-01 -2.56049037e-01 -2.15347871e-01
1.24865137e-01 -3.64021242e-01 4.85829562e-01 -5.75795293e-01
1.08849727e-01 7.68026114e-02 7.99588114e-03 8.92925382e-01
-4.23430391e-02 1.22362256e+00 -1.18338299e+00 -7.38431633e-01
2.94419199e-01 3.63381296e-01 -5.33152699e-01 9.08723474e-02
-2.03108191e-01 3.85864228e-01 -4.22990829e-01 1.10071039e+00
7.61868954e-01 -4.38111931e-01 -1.98689789e-01 -4.77137893e-01
-2.34777443e-02 -5.02239168e-01 -1.25472796e+00 1.90700376e+00
2.33552068e-01 8.36606383e-01 -5.11726178e-02 -2.08854035e-01
3.71455580e-01 2.83954352e-01 8.01920772e-01 -2.55593300e-01
2.14285061e-01 4.20426019e-02 -2.34357581e-01 -8.06155622e-01
7.60635376e-01 4.14814293e-01 1.77476823e-01 1.77686065e-01
3.43088239e-01 7.35886335e-01 2.18457744e-01 1.32914171e-01
1.18291271e+00 6.47810876e-01 -3.91611159e-02 -2.70718426e-01
3.59965026e-01 -1.69450790e-01 9.70620334e-01 5.44446707e-01
-7.93505371e-01 6.08530641e-01 -1.96163580e-01 -7.29043901e-01
-7.63370752e-01 -1.17019355e+00 8.23755190e-02 1.18709350e+00
8.11563730e-01 -4.20802951e-01 -4.39294755e-01 -7.78356671e-01
3.95544857e-01 -2.08292797e-01 -8.95303667e-01 6.61184341e-02
-8.82769227e-01 -6.61192954e-01 5.83606184e-01 8.56653154e-01
3.97718638e-01 -1.08756876e+00 -6.57670319e-01 2.09018558e-01
-2.61719227e-01 -1.54426956e+00 -1.07373464e+00 -5.64626396e-01
-6.98310614e-01 -1.44219232e+00 -8.79921198e-01 -7.40694523e-01
5.14750898e-01 7.46357441e-01 8.97421241e-01 -8.28901604e-02
-4.42812055e-01 7.66503870e-01 -1.00221373e-01 -5.46482503e-02
1.36144564e-01 -1.71924531e-01 4.69917506e-01 9.47894678e-02
4.57821906e-01 -4.20843512e-01 -9.41493809e-01 7.81329334e-01
-5.64633191e-01 3.77495401e-02 3.69745314e-01 4.41465914e-01
6.31804168e-01 -6.00636363e-01 2.97365308e-01 -4.50298786e-01
-3.03826481e-01 -5.82073867e-01 -7.11051583e-01 3.82280767e-01
-5.73971309e-02 -3.35298896e-01 1.00279458e-01 -1.09700119e+00
-6.15418434e-01 3.45657349e-01 4.19728488e-01 -1.36306906e+00
-5.48567437e-02 -3.47885847e-01 6.45640865e-02 -6.43713892e-01
3.35593075e-01 -3.62258032e-02 -1.92985669e-01 -4.44866002e-01
3.12654674e-01 2.11013511e-01 8.26632082e-01 -3.83081794e-01
9.41208303e-01 7.43547738e-01 -1.74886525e-01 -5.29780269e-01
-8.74456465e-01 -7.38534272e-01 -7.88177788e-01 -6.55355811e-01
1.35927105e+00 -1.51388073e+00 -1.12957847e+00 6.90243840e-01
-1.06069291e+00 -4.02172089e-01 -3.99806276e-02 7.98484564e-01
-6.03597999e-01 3.35352033e-01 -6.74581409e-01 -4.77306873e-01
-4.38751996e-01 -9.61445391e-01 1.47335160e+00 5.62369049e-01
-6.36992604e-02 -9.53132093e-01 3.30527395e-01 5.17690957e-01
1.64901301e-01 7.43242264e-01 -7.66459703e-02 -2.77655125e-01
-1.21251214e+00 3.69011424e-02 -2.01914594e-01 -1.80331662e-01
1.20581202e-01 1.36345923e-01 -8.98788035e-01 -7.60699689e-01
-3.94575387e-01 -2.93882608e-01 9.92167354e-01 5.33307254e-01
7.67474890e-01 -4.31497216e-01 -7.92496145e-01 9.30526972e-01
1.34767103e+00 -6.35081455e-02 4.55280751e-01 3.98340851e-01
1.37818825e+00 1.02946900e-01 7.01080024e-01 2.29444295e-01
7.88633049e-01 1.04430830e+00 5.84129274e-01 1.70835093e-01
-4.40529466e-01 2.93599870e-02 7.56327927e-01 6.58794940e-01
-3.19683522e-01 -2.54711181e-01 -4.52744961e-01 7.86145687e-01
-2.30369139e+00 -1.40208483e+00 -2.00231165e-01 1.71752667e+00
3.11596483e-01 -1.74963504e-01 6.60721242e-01 -7.00691879e-01
1.06173515e+00 1.54908761e-01 -7.63376534e-01 4.71858412e-01
-2.25464195e-01 -4.51280981e-01 5.38940132e-01 6.69346526e-02
-1.66213512e+00 1.03904343e+00 5.55566645e+00 6.51901245e-01
-8.49470854e-01 4.53131288e-01 -2.08801702e-01 -6.11895978e-01
2.83378035e-01 -1.85152993e-01 -1.30134761e+00 6.61906838e-01
5.66498220e-01 1.21839112e-02 1.68525070e-01 1.08958244e+00
-1.05691597e-01 3.29833664e-02 -1.18533099e+00 1.19955850e+00
2.45955974e-01 -1.42114019e+00 -1.37338296e-01 -1.46260606e-02
7.54291296e-01 3.96012396e-01 1.96664646e-01 2.43460551e-01
2.65386373e-01 -5.61899781e-01 1.02051914e+00 6.99009717e-01
5.02272904e-01 -2.14678675e-01 4.33010221e-01 -1.12847313e-01
-1.88597095e+00 -9.38531607e-02 -4.94876742e-01 3.46670270e-01
2.37223357e-01 -1.40457362e-01 -2.80241102e-01 4.89971131e-01
1.13476610e+00 1.44746912e+00 -7.85584092e-01 1.40605962e+00
2.86414713e-01 1.18690580e-01 -3.82153183e-01 1.99736804e-01
1.69458181e-01 1.74565032e-01 1.08736217e+00 1.08506536e+00
2.59877771e-01 4.70011346e-02 3.54207098e-01 6.41583800e-01
2.20469795e-02 -2.94078082e-01 -4.64739740e-01 6.27765805e-02
3.10068697e-01 1.49613893e+00 -7.22674787e-01 -4.18472230e-01
-5.80022216e-01 9.45485532e-01 3.55544001e-01 1.02407292e-01
-1.33474708e+00 5.77743351e-02 1.13282144e+00 -6.10564537e-02
8.81285667e-01 -1.98117495e-01 8.77428591e-01 -1.65661204e+00
1.38053209e-01 -6.02107346e-01 6.15625024e-01 -9.13126230e-01
-1.21507764e+00 4.60852355e-01 5.50204795e-03 -1.71619439e+00
7.38356262e-02 -4.88308132e-01 -4.55306709e-01 1.27738938e-01
-1.45714676e+00 -1.65527093e+00 -7.16461778e-01 9.31224942e-01
4.43661511e-01 -2.08453208e-01 4.52430278e-01 8.32301319e-01
-9.28125620e-01 7.33278871e-01 2.84959208e-02 3.98062408e-01
1.00017524e+00 -1.09004295e+00 3.64568233e-01 8.49004805e-01
2.64399767e-01 5.56442916e-01 5.15773237e-01 -7.82241225e-01
-1.76119459e+00 -1.58252966e+00 1.62398368e-01 -1.18190348e+00
7.28374600e-01 -3.65104198e-01 -7.29235291e-01 1.13340890e+00
-5.88338335e-05 8.85558724e-01 5.21890581e-01 -4.16415572e-01
-3.44548553e-01 1.02471583e-01 -1.06020570e+00 4.04839635e-01
1.60629034e+00 -3.47343445e-01 -4.64593679e-01 3.85487020e-01
9.03097808e-01 -1.04669416e+00 -1.06568885e+00 3.55323195e-01
1.01401472e+00 -7.33054459e-01 1.16572499e+00 -7.84724712e-01
-1.56937152e-01 -7.90941179e-01 -1.01680957e-01 -7.11778641e-01
-4.64819908e-01 -1.08519149e+00 -8.62069726e-01 1.18217778e+00
-2.33477548e-01 -3.22616547e-01 9.73916829e-01 4.88262922e-01
-2.04909116e-01 -4.59830284e-01 -1.02990460e+00 -1.10190976e+00
-3.98891419e-01 2.78037637e-02 5.07215798e-01 1.05149078e+00
-5.31534970e-01 -9.96392295e-02 -8.68010819e-01 3.65635991e-01
9.97951627e-01 3.55115205e-01 1.12499976e+00 -1.29779863e+00
-3.39155257e-01 -5.71754798e-02 -9.93366480e-01 -1.12931514e+00
2.12448508e-01 -7.99129426e-01 -1.51633784e-01 -9.81922925e-01
4.48468834e-01 -2.89700240e-01 -3.89394939e-01 4.94947314e-01
-3.39485377e-01 5.73153019e-01 4.64290172e-01 4.17674869e-01
-1.49939704e+00 6.64444685e-01 1.46462286e+00 -1.91119760e-01
-1.27123550e-01 -2.31600270e-01 -2.92204916e-01 7.71356761e-01
3.21837157e-01 -8.79292190e-01 -6.69007152e-02 -6.88196421e-01
-1.21434018e-01 -1.04776010e-01 1.05286980e+00 -1.16147530e+00
5.75307906e-01 -9.42527428e-02 4.60757434e-01 -9.05981719e-01
5.50958872e-01 -6.93622530e-01 5.86177707e-01 5.20047069e-01
1.58065483e-01 6.18060946e-01 4.34220999e-01 9.62531507e-01
1.23129591e-01 3.33816528e-01 7.12681592e-01 4.99210991e-02
-1.16874254e+00 9.23036873e-01 -7.27721304e-02 2.57550538e-01
1.52259421e+00 -4.57652450e-01 -6.30825698e-01 3.32514495e-01
-9.29804385e-01 5.49460053e-01 5.06217539e-01 9.59585011e-01
6.19123399e-01 -1.69582808e+00 -5.57573795e-01 -5.63038792e-03
1.42792746e-01 -1.20322622e-01 6.76603317e-01 1.22256887e+00
-2.97297806e-01 1.87974244e-01 -4.06816572e-01 -9.39046383e-01
-1.86038983e+00 6.05314434e-01 4.62268859e-01 9.45589393e-02
-1.04091668e+00 1.05853128e+00 4.21599686e-01 -2.87311282e-02
1.45976305e-01 -4.52463418e-01 -1.55868754e-01 8.67098123e-02
5.72656810e-01 5.95529675e-01 -4.79128212e-01 -1.05468035e+00
-6.93183839e-01 1.07437646e+00 -2.02912703e-01 4.14167762e-01
1.24946189e+00 -2.66018718e-01 1.27450019e-01 2.08739534e-01
1.03991663e+00 -2.68761307e-01 -1.71996260e+00 -2.36592770e-01
-2.58764714e-01 -8.45314085e-01 -1.37447298e-01 -1.54223144e-01
-1.36846542e+00 3.22832048e-01 1.04414535e+00 -1.33715644e-01
6.34382129e-01 1.17349766e-01 1.24697757e+00 3.97153825e-01
5.39073110e-01 -9.77570593e-01 4.93893623e-01 1.75874352e-01
5.22249222e-01 -1.44230974e+00 9.63257335e-04 -2.55433559e-01
-5.14579475e-01 1.05287969e+00 1.21395361e+00 -3.15314353e-01
6.09811604e-01 1.70177981e-01 -7.74839520e-02 -3.63241285e-01
-7.46687353e-01 -2.16630027e-01 4.73051637e-01 6.10001266e-01
-1.51224166e-01 -2.46758446e-01 4.22282279e-01 2.67155439e-01
2.02932671e-01 1.58703223e-01 2.48586938e-01 8.45370173e-01
-1.91843674e-01 -6.41510129e-01 -3.44122797e-01 1.14039533e-01
-5.47061682e-01 2.99984783e-01 -8.54879990e-02 1.06640267e+00
3.31102908e-01 6.36036634e-01 2.28241220e-01 -4.84548211e-01
1.72133625e-01 -5.54058552e-01 8.58194530e-01 -3.62482756e-01
-7.24400043e-01 8.36821645e-02 -8.77337009e-02 -9.99793172e-01
-1.04033566e+00 -1.03780806e+00 -1.09707022e+00 -4.20217574e-01
-6.12590790e-01 -2.79118836e-01 1.03548348e-01 8.74748766e-01
6.13025188e-01 5.01155734e-01 6.66864216e-02 -1.35206497e+00
-5.63604012e-02 -7.23030388e-01 -3.64559621e-01 3.99558902e-01
8.09997141e-01 -1.27425611e+00 -1.66821793e-01 2.20295012e-01] | [6.289285182952881, -1.9994313716888428] |
633fa174-0f48-4ab5-a901-16dfface87aa | sparse-coding-approach-for-multi-frame-image | 1402.3926 | null | http://arxiv.org/abs/1402.3926v1 | http://arxiv.org/pdf/1402.3926v1.pdf | Sparse Coding Approach for Multi-Frame Image Super Resolution | An image super-resolution method from multiple observation of low-resolution
images is proposed. The method is based on sub-pixel accuracy block matching
for estimating relative displacements of observed images, and sparse signal
representation for estimating the corresponding high-resolution image. Relative
displacements of small patches of observed low-resolution images are accurately
estimated by a computationally efficient block matching method. Since the
estimated displacements are also regarded as a warping component of image
degradation process, the matching results are directly utilized to generate
low-resolution dictionary for sparse image representation. The matching scores
of the block matching are used to select a subset of low-resolution patches for
reconstructing a high-resolution patch, that is, an adaptive selection of
informative low-resolution images is realized. When there is only one
low-resolution image, the proposed method works as a single-frame
super-resolution method. The proposed method is shown to perform comparable or
superior to conventional single- and multi-frame super-resolution methods
through experiments using various real-world datasets. | ['Hideitsu Hino', 'Noboru Murata', 'Toshiyuki Kato'] | 2014-02-17 | null | null | null | null | ['multi-frame-super-resolution'] | ['computer-vision'] | [ 8.73205721e-01 -3.22919011e-01 -2.20298424e-01 -8.26718733e-02
-1.35662568e+00 3.01507348e-03 2.79872566e-01 -3.55053037e-01
-1.09026909e-01 9.35880303e-01 3.48683596e-01 7.39396513e-01
-1.67477980e-01 -8.47066700e-01 -5.72596431e-01 -1.14773667e+00
1.05891079e-01 8.77767727e-02 5.19798636e-01 -1.41403407e-01
5.21038115e-01 6.22683525e-01 -1.91876066e+00 5.58248401e-01
7.03485429e-01 7.63489425e-01 8.53221059e-01 5.70646226e-01
2.84011930e-01 7.47273624e-01 -3.02867323e-01 7.47453332e-01
1.29536316e-01 -5.54285109e-01 -5.26361406e-01 3.29633027e-01
5.33223987e-01 -5.87477386e-01 -3.22331451e-02 1.16271436e+00
4.12225306e-01 2.92996913e-01 3.23474497e-01 -8.97512510e-02
-5.03023028e-01 2.12713391e-01 -1.09018338e+00 7.86944807e-01
8.80091190e-01 -5.15496194e-01 6.42619133e-01 -1.36778712e+00
8.68813097e-01 1.30952156e+00 4.96274173e-01 5.89402616e-02
-1.64804947e+00 -4.74435985e-01 -3.92452985e-01 2.19419569e-01
-1.81031740e+00 -7.43607759e-01 1.18225288e+00 -2.11053848e-01
5.31809509e-01 2.94044614e-01 1.68297380e-01 4.39496130e-01
4.81678128e-01 1.85377263e-02 1.24988544e+00 -5.80521822e-01
5.77197373e-02 1.64377149e-02 -2.29888916e-01 5.55673957e-01
3.41573328e-01 4.59515631e-01 -7.88391173e-01 -4.70921844e-01
1.45714736e+00 -1.32564642e-02 -6.97670817e-01 -5.90824187e-02
-1.24371004e+00 5.19938946e-01 1.69407263e-01 7.25080907e-01
-8.97618234e-01 -2.99729049e-01 -2.41747051e-01 -5.60933091e-02
6.14636600e-01 5.00015095e-02 1.48778975e-01 3.41310918e-01
-1.16478217e+00 8.93133879e-02 -2.01897509e-02 5.93959212e-01
1.05763853e+00 4.20183420e-01 -4.05984595e-02 1.00286222e+00
5.28780557e-02 5.23197293e-01 4.26353216e-01 -1.34354925e+00
1.44248337e-01 1.76866829e-01 6.01915181e-01 -1.28926444e+00
-1.13376483e-01 -2.90719002e-01 -1.12157500e+00 2.50981539e-01
6.04769625e-02 4.35226440e-01 -5.60767651e-01 1.42541146e+00
5.87351918e-01 5.44948995e-01 1.33098930e-01 1.12815022e+00
5.52995503e-01 9.71432567e-01 -4.16152120e-01 -9.27958190e-01
1.37115633e+00 -4.57076907e-01 -9.19894338e-01 -1.09073319e-01
-3.32082868e-01 -9.11751688e-01 6.10421121e-01 2.88025439e-01
-1.48607743e+00 -1.15056014e+00 -1.19747841e+00 -2.49410491e-03
5.76957881e-01 2.23575741e-01 -2.01060459e-01 -1.18598342e-01
-7.90537238e-01 7.19365120e-01 -6.12677157e-01 6.03334345e-02
1.50468513e-01 1.28321335e-01 -4.61491942e-01 -4.38262343e-01
-1.08095360e+00 7.84778893e-01 2.53722519e-01 -2.47995574e-02
-9.40773070e-01 -7.73551345e-01 -8.71013284e-01 -3.84010165e-03
-2.28001252e-02 -4.85301733e-01 5.47621787e-01 -9.12327349e-01
-1.23216856e+00 7.47563839e-01 -6.65282428e-01 -9.73972231e-02
-1.09979086e-01 2.14247018e-01 -6.49595976e-01 8.47141922e-01
3.91475379e-01 5.56403119e-03 1.46675563e+00 -1.62993562e+00
-8.68770421e-01 -4.33167100e-01 -4.86453116e-01 3.90717536e-01
2.56152153e-01 1.01500489e-01 -4.76889089e-02 -7.51416087e-01
6.68502808e-01 -4.52413231e-01 -3.03353459e-01 -2.85259157e-01
1.62062287e-01 5.34500718e-01 9.63276148e-01 -9.87547576e-01
1.18698871e+00 -2.28444815e+00 3.40412885e-01 5.33066317e-02
2.19429508e-01 -6.21034577e-02 -1.49448395e-01 1.57990038e-01
-1.56445384e-01 -4.50986326e-01 -3.75709534e-01 -3.94661762e-02
-1.03766143e+00 2.10560914e-02 -1.98797435e-01 9.70979869e-01
1.17289640e-01 1.44441798e-01 -8.00957501e-01 -7.23133028e-01
4.39774036e-01 9.49139297e-01 -1.72355190e-01 3.59269619e-01
3.94918621e-01 1.04564369e+00 -6.10981643e-01 5.82088947e-01
9.83763576e-01 -3.24543595e-01 -1.47181479e-02 -7.04966843e-01
-4.13857192e-01 -2.08857104e-01 -1.43847811e+00 1.63544071e+00
-4.50988621e-01 3.32704723e-01 4.40562665e-01 -8.97762775e-01
1.13676763e+00 4.17000711e-01 7.67464280e-01 -7.92611122e-01
-1.49484441e-01 2.22586989e-01 -4.87811148e-01 -4.50805962e-01
5.39111018e-01 -3.38076860e-01 2.55917370e-01 2.69201666e-01
-3.22364807e-01 8.24271962e-02 1.24637268e-01 -1.51742250e-01
7.97156990e-01 1.24370724e-01 6.75425589e-01 -2.99893945e-01
1.05683982e+00 -4.20615487e-02 6.01831317e-01 4.27182376e-01
9.41991732e-02 9.65092540e-01 -4.29903358e-01 -4.86983478e-01
-1.54158020e+00 -9.87080216e-01 -4.53140348e-01 5.31260192e-01
5.19247413e-01 -1.64677259e-02 -6.11987412e-01 4.15498763e-01
-3.66465628e-01 3.05318832e-01 -4.89147484e-01 1.12980701e-01
-9.16405201e-01 -6.75149202e-01 -2.36805037e-01 1.82031170e-01
7.04891562e-01 -8.07988584e-01 -7.98763514e-01 3.90933007e-01
-6.77865326e-01 -1.31168914e+00 -3.89932871e-01 -2.98591465e-01
-1.16256249e+00 -8.77435446e-01 -8.80211949e-01 -9.49103951e-01
9.00853336e-01 9.14578021e-01 8.92110050e-01 9.43812206e-02
-3.28842312e-01 -1.12943705e-02 -1.97500721e-01 5.76262474e-01
-4.93459225e-01 -6.32671714e-01 9.07270983e-02 5.03226876e-01
-7.21403733e-02 -7.47601390e-01 -7.74982452e-01 5.21845996e-01
-7.91900098e-01 1.34569526e-01 7.22280324e-01 1.16974831e+00
1.40900111e+00 7.73302495e-01 3.76090914e-01 -6.68637574e-01
2.77192831e-01 -3.00623804e-01 -7.86386967e-01 -8.27313215e-02
-4.91939634e-01 -7.16957636e-03 7.34897375e-01 -5.92052817e-01
-1.64241886e+00 1.52399957e-01 1.91635206e-01 -6.20615184e-01
-9.11608562e-02 3.30501944e-01 4.78323316e-03 -3.88759047e-01
7.23045826e-01 7.15688229e-01 2.73628905e-02 -5.80078661e-01
4.26196344e-02 6.01957679e-01 8.26019108e-01 -3.35006177e-01
8.81249845e-01 9.80501890e-01 1.22623369e-01 -1.09646213e+00
-7.18416154e-01 -6.12080097e-01 -7.77649701e-01 -1.23349324e-01
8.50205660e-01 -1.26402378e+00 -2.16280222e-01 2.23804310e-01
-8.64539504e-01 2.01890990e-01 -2.11126372e-01 6.62104428e-01
-5.53341091e-01 6.60420597e-01 -5.51280379e-01 -8.08617592e-01
-1.39543951e-01 -1.14186251e+00 1.39596260e+00 2.78059989e-01
9.37707257e-03 -6.25645161e-01 1.00543909e-01 5.91809690e-01
4.34794217e-01 3.51013780e-01 6.41628027e-01 3.54494363e-01
-9.37780559e-01 -7.90982172e-02 -1.90152109e-01 1.19583942e-01
3.99378836e-01 -3.94231915e-01 -7.83215642e-01 -7.04259217e-01
5.87984025e-01 1.19444905e-02 3.65732014e-01 8.69067013e-01
7.73270190e-01 -2.08325192e-01 -3.35320532e-01 6.60071135e-01
1.92156100e+00 2.09061787e-01 8.53117704e-01 2.56401896e-01
4.47265029e-01 3.39125603e-01 1.20692492e+00 5.93626678e-01
-1.57653801e-02 1.06925297e+00 1.19988106e-01 -2.71104693e-01
-3.99850130e-01 -1.02730155e-01 1.96254015e-01 6.56201243e-01
-5.16959488e-01 4.51645285e-01 -2.59125769e-01 5.98981321e-01
-1.57752192e+00 -1.54850304e+00 -1.63400918e-01 2.44509149e+00
7.10629284e-01 -2.89174497e-01 -1.73628569e-01 1.77154988e-01
1.18336582e+00 4.28888351e-01 -5.04210234e-01 2.39480555e-01
-3.94092679e-01 2.23011434e-01 4.18068558e-01 8.16011190e-01
-8.01217318e-01 4.98302072e-01 6.53905058e+00 1.01647794e+00
-8.38454962e-01 3.43188792e-01 4.50403988e-01 9.16451812e-02
-2.30961218e-01 7.76322372e-03 -8.36204052e-01 3.98577631e-01
7.85662055e-01 -3.26213062e-01 5.38870513e-01 4.15073633e-01
6.79304779e-01 -5.49784362e-01 -5.42036593e-01 1.25055182e+00
2.16274142e-01 -1.40979421e+00 7.54277557e-02 -4.11411189e-02
1.04719448e+00 -4.39005762e-01 -7.66369700e-02 -5.85649610e-01
-1.82133466e-01 -8.44236195e-01 4.57777500e-01 5.94512880e-01
1.19556725e+00 -8.17195892e-01 5.22121668e-01 2.68492609e-01
-1.65621948e+00 -2.32986808e-01 -7.06911922e-01 1.88523307e-01
5.50998509e-01 6.70519531e-01 -1.58262402e-01 6.39643252e-01
8.30390036e-01 7.91890442e-01 1.62084457e-02 4.44694757e-01
1.23072891e-02 2.32261896e-01 -8.28497708e-02 9.63246346e-01
-2.49278679e-01 -5.28572679e-01 8.11028302e-01 6.94496632e-01
6.22968614e-01 7.27634668e-01 1.69211954e-01 9.04976726e-01
2.79677182e-01 -5.31692617e-02 -6.07071877e-01 3.99190575e-01
7.15935826e-01 1.23800850e+00 -4.91409123e-01 -3.50539893e-01
-4.88424569e-01 1.01991403e+00 -4.91465665e-02 5.00830352e-01
-6.17881536e-01 4.08590510e-02 3.62916172e-01 4.95574802e-01
5.88246822e-01 -1.14833236e-01 -1.32895410e-01 -1.15959799e+00
-1.10815994e-01 -9.05000150e-01 3.04757774e-01 -1.12892807e+00
-7.36124873e-01 7.58609831e-01 8.93107429e-02 -1.73228645e+00
-4.09699678e-01 2.94331521e-01 -1.61400363e-01 1.25817013e+00
-1.69964242e+00 -9.29195344e-01 -5.84092557e-01 8.61243904e-01
8.11736286e-01 -1.30778685e-01 7.11611450e-01 3.23248386e-01
-2.01167524e-01 -1.22207470e-01 3.72616798e-01 -3.08643371e-01
4.78430092e-01 -5.48321664e-01 -2.83414006e-01 1.19938314e+00
-1.56836763e-01 3.64019841e-01 9.40411448e-01 -8.12597394e-01
-1.32083654e+00 -8.62540066e-01 6.10906422e-01 6.42578080e-02
1.49893403e-01 1.70091912e-01 -1.24996257e+00 4.22727108e-01
-1.01899929e-01 2.99342364e-01 3.97231668e-01 -7.38170564e-01
9.01851282e-02 -2.49340773e-01 -1.58786082e+00 1.28064603e-01
7.41668224e-01 -6.48172259e-01 -5.14111638e-01 -9.41017270e-02
3.33140552e-01 -5.02768874e-01 -1.37207377e+00 3.79794657e-01
5.28239667e-01 -1.01282871e+00 1.49050474e+00 3.09296489e-01
5.05753458e-01 -8.57458949e-01 -4.50897634e-01 -1.02664673e+00
-1.04905605e+00 -2.92048842e-01 -5.40632829e-02 9.69900906e-01
-6.45019114e-02 -3.80860656e-01 4.75132734e-01 1.15380455e-02
2.36382902e-01 -3.42368007e-01 -9.70828354e-01 -4.68135983e-01
-6.77641988e-01 5.08975387e-01 3.03689241e-01 9.10821497e-01
-4.58368897e-01 3.26799214e-01 -7.25120544e-01 6.68884754e-01
1.52021956e+00 6.27527118e-01 3.81320357e-01 -1.06896818e+00
-2.28225827e-01 1.48906693e-01 -2.95006216e-01 -8.57843041e-01
-5.02758399e-02 -3.13360184e-01 3.49795632e-02 -1.24438047e+00
3.76844883e-01 -1.21453606e-01 -2.80015230e-01 -2.15296388e-01
-7.76279047e-02 6.86985373e-01 -3.31961542e-01 9.04630601e-01
-1.21352533e-02 3.49645734e-01 1.44856477e+00 8.33744332e-02
-1.85658187e-01 -8.93955454e-02 -5.14780104e-01 4.94569391e-01
3.04578066e-01 -3.62343311e-01 -4.58625197e-01 -1.54834330e-01
-3.20229173e-01 8.47723246e-01 2.59482026e-01 -9.35975790e-01
4.86228056e-02 -3.41180652e-01 6.50794148e-01 -7.53866673e-01
6.63230300e-01 -8.83986831e-01 8.17487240e-01 3.09491485e-01
-2.81368434e-01 -2.02115223e-01 -1.28593087e-01 5.90581119e-01
-5.69505692e-01 -1.36935607e-01 1.56634343e+00 -3.35461706e-01
-9.06569064e-01 1.41941890e-01 -2.95837313e-01 -4.19613510e-01
8.58422697e-01 -6.84905410e-01 -4.51112911e-02 -3.28328848e-01
-7.08937466e-01 -4.63685662e-01 7.35993803e-01 -2.41409726e-02
1.11456549e+00 -1.45444953e+00 -1.03905869e+00 4.94158655e-01
-4.94596921e-02 1.01503916e-01 7.27371037e-01 7.93114841e-01
-4.46743906e-01 1.65166616e-01 -5.69656312e-01 -7.65555680e-01
-1.56172776e+00 6.29603803e-01 1.94825634e-01 -2.67228782e-01
-1.15820920e+00 3.40861052e-01 3.20644140e-01 6.08275115e-01
-3.45913500e-01 6.25178665e-02 -4.65711623e-01 -2.30183989e-01
1.24912560e+00 4.99306709e-01 -1.49371803e-01 -1.31641197e+00
-2.11578861e-01 1.33318377e+00 1.44405678e-01 -1.01168498e-01
1.52550018e+00 -8.65410745e-01 -3.02962780e-01 4.44016486e-01
1.12027526e+00 1.82489932e-01 -1.34870517e+00 -5.58519542e-01
-3.43130499e-01 -1.05679750e+00 5.06808698e-01 -1.93224519e-01
-1.10604513e+00 3.87298137e-01 7.89318979e-01 -6.46584630e-02
1.71193647e+00 7.94231147e-03 6.55781031e-01 -2.83646613e-01
8.10772896e-01 -9.08668578e-01 3.63857932e-02 -1.97020829e-01
1.04914200e+00 -1.12746358e+00 6.23019218e-01 -4.87779498e-01
-2.35216826e-01 1.04302931e+00 3.14501971e-01 -3.80294472e-01
2.99926668e-01 3.77503037e-01 -2.55373001e-01 -1.45614639e-01
-5.75660467e-01 -5.38981892e-03 1.40225694e-01 6.93812549e-01
2.54168719e-01 -3.17690670e-01 -3.62722307e-01 8.79450887e-02
3.88059437e-01 2.49993905e-01 6.82348907e-01 6.54518664e-01
-8.24609518e-01 -6.61760747e-01 -1.09550667e+00 1.20375164e-01
-4.49416935e-01 5.49524426e-02 4.12640512e-01 3.92435551e-01
-1.36156067e-01 9.05606449e-01 1.32274806e-01 -1.64255589e-01
1.85366049e-01 -5.39806843e-01 6.93467259e-01 -3.99976850e-01
1.30329207e-01 5.20730317e-01 -6.48261830e-02 -8.87427390e-01
-8.50460887e-01 -6.94632232e-01 -1.17862105e+00 -1.46181315e-01
-2.92441100e-01 1.88944459e-01 3.32778245e-01 5.49660504e-01
2.80258089e-01 3.60672325e-01 1.02091789e+00 -1.43809688e+00
-2.37509668e-01 -7.32362986e-01 -1.06100309e+00 4.94546711e-01
6.63864732e-01 -7.91755617e-01 -6.10536635e-01 4.80840504e-01] | [11.049928665161133, -2.176532030105591] |
d7f7e794-78ab-4550-a548-582dcf326328 | systematic-generalization-with-edge-1 | 2112.00578 | null | https://arxiv.org/abs/2112.00578v1 | https://arxiv.org/pdf/2112.00578v1.pdf | Systematic Generalization with Edge Transformers | Recent research suggests that systematic generalization in natural language understanding remains a challenge for state-of-the-art neural models such as Transformers and Graph Neural Networks. To tackle this challenge, we propose Edge Transformer, a new model that combines inspiration from Transformers and rule-based symbolic AI. The first key idea in Edge Transformers is to associate vector states with every edge, that is, with every pair of input nodes -- as opposed to just every node, as it is done in the Transformer model. The second major innovation is a triangular attention mechanism that updates edge representations in a way that is inspired by unification from logic programming. We evaluate Edge Transformer on compositional generalization benchmarks in relational reasoning, semantic parsing, and dependency parsing. In all three settings, the Edge Transformer outperforms Relation-aware, Universal and classical Transformer baselines. | ['Dzmitry Bahdanau', "Timothy J. O'Donnell", 'Leon Bergen'] | 2021-12-01 | systematic-generalization-with-edge | http://proceedings.neurips.cc/paper/2021/hash/0a4dc6dae338c9cb08947c07581f77a2-Abstract.html | http://proceedings.neurips.cc/paper/2021/file/0a4dc6dae338c9cb08947c07581f77a2-Paper.pdf | neurips-2021-12 | ['relational-reasoning', 'systematic-generalization'] | ['natural-language-processing', 'reasoning'] | [ 3.73794258e-01 7.97854066e-01 -4.39826787e-01 -3.32478911e-01
-9.12543014e-02 -6.69163883e-01 7.24789977e-01 2.99859196e-01
6.33755233e-03 3.64698857e-01 5.65209150e-01 -9.52997506e-01
3.53220850e-02 -1.42336297e+00 -1.19401574e+00 -1.02721937e-01
1.59001574e-01 8.80972266e-01 3.92171621e-01 -7.48456001e-01
-4.64453958e-02 4.02286857e-01 -1.02058268e+00 6.40554368e-01
6.24615848e-01 1.02622414e+00 -2.63121217e-01 2.81765640e-01
-5.29976070e-01 1.29264605e+00 1.30103612e-02 -9.74888802e-01
1.21893212e-02 -4.49082166e-01 -1.12461293e+00 -6.42301559e-01
7.94796884e-01 -1.98606953e-01 -7.10831404e-01 1.04498637e+00
-4.97747548e-02 3.15020770e-01 4.84485984e-01 -1.30015421e+00
-1.40810847e+00 1.66287851e+00 -1.96782686e-02 3.04978281e-01
2.68622577e-01 1.03921063e-01 1.74609911e+00 -3.77775669e-01
6.21215820e-01 1.58842778e+00 1.08189487e+00 6.65706873e-01
-1.72048879e+00 -4.06958789e-01 7.43210137e-01 4.13123250e-01
-9.20297563e-01 -3.01838607e-01 6.95406616e-01 -2.86466274e-02
1.78855586e+00 2.29693875e-02 7.02693045e-01 1.13070011e+00
3.02830845e-01 6.87776685e-01 5.95413387e-01 -2.19914064e-01
5.47303595e-02 -3.85845274e-01 6.73068285e-01 1.00540900e+00
1.65561348e-01 1.22597590e-01 -3.95808905e-01 9.09540337e-03
6.84277892e-01 -2.82423645e-02 -5.58422646e-04 -5.19766152e-01
-9.53864574e-01 8.66708219e-01 9.51852977e-01 2.16387868e-01
-3.89506042e-01 8.69238079e-01 7.08316743e-01 4.15245414e-01
1.36352465e-01 5.48003793e-01 -7.21954167e-01 1.74064159e-01
-1.87944755e-01 3.36165816e-01 9.35377300e-01 8.76859546e-01
5.77861905e-01 2.29399741e-01 -3.28254133e-01 3.39246899e-01
2.70029545e-01 3.19252253e-01 3.94823223e-01 -8.98579717e-01
4.92016196e-01 1.06322193e+00 -7.29720235e-01 -7.59877682e-01
-4.42903072e-01 -4.97029185e-01 -6.61794662e-01 -2.44666040e-01
1.43833414e-01 3.32095057e-01 -9.88970101e-01 2.20465589e+00
5.47696985e-02 4.45563078e-01 2.58151054e-01 3.79417419e-01
1.16004395e+00 5.94203830e-01 2.41250530e-01 2.06837803e-01
1.42849088e+00 -1.15927565e+00 -4.58687395e-01 -6.36722803e-01
5.94844878e-01 2.64005393e-01 1.07412815e+00 2.73195297e-01
-1.25846076e+00 -3.82472038e-01 -9.14465845e-01 -5.11180520e-01
-6.72823668e-01 -6.38109684e-01 1.19406307e+00 4.43257928e-01
-1.39306974e+00 6.60703003e-01 -9.04651940e-01 -3.05928051e-01
4.77944434e-01 3.28896612e-01 -5.34697950e-01 -4.05290164e-02
-1.49993443e+00 1.17191625e+00 6.03997469e-01 -4.36930786e-05
-8.26045215e-01 -9.84051466e-01 -1.39564168e+00 6.18596196e-01
5.53558528e-01 -1.12334228e+00 1.63302279e+00 -6.58585787e-01
-1.47337818e+00 6.91789806e-01 -1.91849530e-01 -1.06694233e+00
-1.86154291e-01 -9.89739969e-02 -1.44337982e-01 -1.51916802e-01
-1.07334115e-01 6.49877369e-01 2.89761305e-01 -1.04130554e+00
-3.26694787e-01 -4.82712537e-01 4.70833480e-01 4.69876602e-02
2.28773598e-02 -2.75078863e-01 -3.51007253e-01 -2.59717792e-01
2.19841883e-01 -7.88995326e-01 -3.11727673e-01 -4.62861389e-01
-5.28291285e-01 -8.00966442e-01 5.90266407e-01 -5.02992213e-01
1.13449562e+00 -1.82204056e+00 6.02281511e-01 6.01067245e-02
4.46603477e-01 9.35417563e-02 -1.41668752e-01 4.64506030e-01
-4.55132723e-01 1.54398248e-01 -3.81009817e-01 -2.74549931e-01
4.67700541e-01 6.71387851e-01 -7.02878833e-01 -6.75767735e-02
3.69309306e-01 1.72155356e+00 -1.16657758e+00 -1.36746883e-01
-1.55433118e-02 2.23446444e-01 -9.78575110e-01 -1.13834396e-01
-8.46974909e-01 -9.52453762e-02 -1.40589535e-01 5.46910465e-01
3.50179791e-01 -3.59974235e-01 4.70039129e-01 -5.46663046e-01
2.92313755e-01 1.10040462e+00 -8.84037435e-01 1.90963006e+00
-5.37148476e-01 4.37085629e-01 -4.52420235e-01 -1.37835324e+00
6.09008253e-01 2.91917980e-01 -4.10120301e-02 -8.75230968e-01
3.88532840e-02 -1.87160715e-01 1.37924314e-01 -1.69533998e-01
5.58292985e-01 -3.32803994e-01 -3.20238352e-01 6.40595019e-01
4.06848907e-01 -2.46327162e-01 1.31967843e-01 6.77645683e-01
1.22249997e+00 4.32940990e-01 2.74934590e-01 -8.89665335e-02
3.30189198e-01 -2.25027263e-01 6.29513502e-01 8.40390980e-01
2.48769343e-01 -4.84648310e-02 1.05035508e+00 -6.12649143e-01
-5.17723560e-01 -1.36517775e+00 2.54942924e-01 1.42485523e+00
-1.37008354e-01 -7.99462736e-01 -5.24901628e-01 -9.40532804e-01
2.40693659e-01 1.06134033e+00 -9.57834244e-01 -7.80113518e-01
-8.27701271e-01 -2.61609465e-01 8.62655163e-01 1.17954159e+00
3.21084321e-01 -1.36684704e+00 -3.96373689e-01 2.82137990e-01
4.21615914e-02 -1.16790140e+00 -1.56089231e-01 6.57005906e-01
-8.97223592e-01 -9.30946052e-01 3.74012351e-01 -8.03010702e-01
3.91630232e-01 -3.52625281e-01 1.78764284e+00 9.34616104e-02
3.19927871e-01 3.72087657e-01 -1.47565275e-01 -1.50225952e-01
-5.49812794e-01 3.95907342e-01 -2.36683175e-01 -3.17745864e-01
3.32756042e-01 -8.41679573e-01 4.09528874e-02 -2.67207533e-01
-7.61959195e-01 -1.59451086e-02 3.20987016e-01 9.33904231e-01
5.22234976e-01 -1.65022716e-01 4.75966811e-01 -1.40806997e+00
8.24329138e-01 -6.03799045e-01 -6.52362049e-01 5.73535740e-01
-6.41542196e-01 5.77687085e-01 8.65894198e-01 -2.58352369e-01
-9.72247362e-01 -2.22763196e-01 -6.95131496e-02 -3.49899918e-01
1.14811957e-01 9.50114608e-01 -2.58758336e-01 4.80295047e-02
7.43427694e-01 2.22107068e-01 -2.84347624e-01 -1.85684934e-01
1.08587468e+00 1.71143729e-02 1.08756554e+00 -1.04979646e+00
5.93828201e-01 1.01024017e-01 3.68361682e-01 -2.34935716e-01
-8.80372405e-01 1.60514504e-01 -3.06714058e-01 5.43999434e-01
7.99867570e-01 -5.10718882e-01 -1.09452641e+00 4.51222897e-01
-1.38528144e+00 -9.58694935e-01 -6.52015388e-01 -4.72083464e-02
-3.94039840e-01 2.43334666e-01 -9.69980240e-01 -3.65752995e-01
-4.70925748e-01 -1.19874823e+00 8.63522649e-01 1.33517563e-01
-2.59210974e-01 -1.31824791e+00 4.95598018e-02 2.72304229e-02
7.12270439e-01 -4.91094477e-02 1.59485710e+00 -9.06072795e-01
-6.00921750e-01 8.73623490e-02 -3.25820178e-01 3.50388944e-01
2.37599649e-02 -2.26533860e-01 -7.10603356e-01 2.02770695e-01
-3.74491096e-01 -4.10467863e-01 1.10432971e+00 1.62260562e-01
1.02952611e+00 -2.85815746e-01 -5.22194088e-01 8.51033747e-01
1.08193457e+00 1.39799297e-01 7.18742251e-01 1.97838638e-02
9.36451077e-01 1.03964515e-01 -2.64837891e-01 -2.69262165e-01
1.08160543e+00 5.27896106e-01 7.39423096e-01 2.99084097e-01
-3.04439038e-01 -7.42602885e-01 2.77058005e-01 3.75746012e-01
-3.55103277e-02 -3.29146266e-01 -1.01336539e+00 5.40757954e-01
-1.82742202e+00 -9.85811055e-01 4.35300022e-02 1.80811691e+00
9.56206977e-01 2.52993852e-01 -1.38476223e-01 -4.79653142e-02
3.09753448e-01 1.50423840e-01 -5.59235334e-01 -9.57761824e-01
-1.05022818e-01 8.94771159e-01 3.39248419e-01 7.08670199e-01
-8.10343564e-01 1.55232275e+00 6.22656155e+00 9.93936285e-02
-1.04094565e+00 4.77567539e-02 3.68426800e-01 3.01672876e-01
-7.08282351e-01 3.24174851e-01 -8.03172350e-01 -6.70868084e-02
1.09317958e+00 -8.16420913e-02 9.74063098e-01 6.31038725e-01
-8.28637481e-01 3.66067290e-01 -1.69797969e+00 4.79173511e-01
1.34264290e-01 -1.74136615e+00 4.24402088e-01 -3.16806942e-01
4.50587451e-01 3.43820721e-01 5.88318631e-02 8.54478121e-01
1.07024407e+00 -1.17355037e+00 7.89199114e-01 2.68748999e-01
4.78953362e-01 -3.91849458e-01 5.06293714e-01 -1.33798227e-01
-1.54466653e+00 -2.51325816e-01 -1.27991617e-01 -1.98725000e-01
3.04483622e-01 -5.46898097e-02 -6.12395048e-01 6.00530386e-01
6.05957925e-01 8.68384659e-01 -4.95012492e-01 4.06387269e-01
-9.83004630e-01 6.69424236e-01 -2.89293855e-01 2.37055764e-01
3.41211647e-01 -8.81896317e-02 3.44739050e-01 1.24198747e+00
-1.24926463e-01 1.17880709e-01 -4.18956541e-02 1.15157318e+00
-5.73324442e-01 -5.41132987e-01 -7.89270997e-01 -2.28011906e-01
5.66805482e-01 1.11724901e+00 -3.63875180e-01 -5.30122042e-01
-5.68201184e-01 8.37769389e-01 9.57778573e-01 4.14519101e-01
-8.24525595e-01 -9.64624137e-02 5.47888398e-01 -6.23343140e-02
5.65778732e-01 -1.77579261e-02 -1.89048082e-01 -1.02712786e+00
-6.03918731e-02 -9.24323738e-01 7.91972041e-01 -8.50585580e-01
-1.30562675e+00 6.42531693e-01 1.51010484e-01 -1.65480122e-01
-4.58513409e-01 -9.25798416e-01 -7.83411860e-01 7.38274157e-01
-1.40086019e+00 -1.62242031e+00 -6.31250739e-02 7.20523536e-01
8.24107900e-02 6.33763373e-02 9.95100200e-01 6.75597228e-03
-5.86740971e-01 8.43968689e-01 -7.45577514e-01 3.53503406e-01
3.25689763e-02 -1.51210165e+00 1.32330191e+00 8.67909610e-01
5.32121539e-01 1.01662016e+00 3.33060026e-01 -5.46155810e-01
-1.78093088e+00 -1.00353944e+00 1.06912792e+00 -6.70088530e-01
1.10404348e+00 -4.42751050e-01 -1.14464593e+00 1.70483375e+00
3.46911252e-01 4.13731396e-01 1.77778155e-01 5.17290294e-01
-1.16503370e+00 -1.03454173e-01 -8.06542099e-01 6.87257826e-01
1.72461545e+00 -9.03157234e-01 -1.12823379e+00 4.14587259e-02
1.32586908e+00 -6.75179422e-01 -8.65548849e-01 3.82249981e-01
4.66743559e-01 -7.23085701e-01 1.22693169e+00 -1.41366613e+00
3.14981401e-01 -7.72171319e-02 -3.66948456e-01 -1.79001296e+00
-6.57540083e-01 -5.65572798e-01 -6.31194890e-01 1.23464549e+00
7.68824995e-01 -1.16898906e+00 7.09403217e-01 5.63223422e-01
-7.14525640e-01 -6.57247007e-01 -8.43952596e-01 -7.76362658e-01
3.56080711e-01 -5.62667727e-01 9.54897404e-01 9.13530827e-01
4.11109060e-01 1.00994205e+00 2.21288100e-01 1.83306322e-01
3.45243633e-01 2.94644922e-01 4.88311768e-01 -1.44963133e+00
-6.61419690e-01 -8.49095702e-01 -4.32935238e-01 -1.04289281e+00
8.58004451e-01 -1.61048305e+00 -2.23259106e-01 -2.02977586e+00
3.91947776e-02 -3.94196659e-01 -4.98211175e-01 1.14105904e+00
-9.07481909e-02 -8.29268768e-02 6.45896047e-02 -6.93659604e-01
-4.30135667e-01 4.51923937e-01 1.04765379e+00 -5.17008603e-01
-1.25920484e-02 -4.00461406e-01 -1.27250433e+00 4.71951634e-01
6.36407614e-01 -3.37410033e-01 -6.35856628e-01 -7.90372074e-01
9.72985446e-01 -6.07077815e-02 6.77572429e-01 -5.85367978e-01
4.49332178e-01 -1.34501263e-01 -2.57966936e-01 -1.80500612e-01
3.07521671e-01 -6.94775939e-01 8.26632325e-03 4.00057316e-01
-3.93995345e-01 5.57940185e-01 4.25475121e-01 4.32362467e-01
-7.51422942e-02 1.32716730e-01 3.37229133e-01 -3.65978420e-01
-8.53408277e-01 2.73591369e-01 8.80695954e-02 3.99602920e-01
4.50375348e-01 1.69407353e-01 -9.74505126e-01 -2.72690058e-01
-6.70617342e-01 1.35710627e-01 1.85423419e-01 4.51494157e-01
4.43814874e-01 -1.32477510e+00 -5.69422781e-01 2.48852357e-01
2.24903569e-01 2.71272510e-01 -1.15436807e-01 8.69476676e-01
-1.45477310e-01 5.21249294e-01 -1.08395636e-01 -1.78303361e-01
-6.82862163e-01 9.41861093e-01 6.60451710e-01 -5.40226042e-01
-6.32218778e-01 1.09441078e+00 3.85403723e-01 -8.51879597e-01
1.60924762e-01 -1.21890998e+00 -8.01532790e-02 -2.70721108e-01
1.76297590e-01 -3.87097299e-02 2.62125760e-01 -4.70586479e-01
-4.19577986e-01 3.82744968e-01 -1.07995071e-01 4.29688469e-02
1.32404852e+00 4.90611851e-01 -5.32400727e-01 3.59818995e-01
7.67492354e-01 -1.80832371e-01 -7.92297184e-01 -6.17351234e-01
2.17653010e-02 2.59378433e-01 9.65774804e-02 -9.02068973e-01
-1.22098112e+00 9.20873523e-01 -1.38833106e-01 3.89496297e-01
7.63031900e-01 4.13115799e-01 7.71315515e-01 8.37080181e-01
2.60620087e-01 -4.23792124e-01 -1.90527618e-01 1.08801913e+00
7.83989787e-01 -8.09652150e-01 -2.43235692e-01 -2.55727917e-01
-4.88835633e-01 7.72948325e-01 7.51841903e-01 -1.62586734e-01
4.04110909e-01 4.02626097e-01 -5.39685369e-01 -4.47750419e-01
-1.21247995e+00 -2.01922774e-01 2.71842897e-01 6.64267004e-01
4.09667522e-01 2.15807140e-01 2.54221559e-01 1.01063740e+00
-2.09978402e-01 7.21234679e-02 1.38632506e-01 7.62787998e-01
2.54067741e-02 -1.25305998e+00 2.34523430e-01 4.45394754e-01
-1.12653397e-01 -8.20486665e-01 -4.62460250e-01 7.72008240e-01
-6.72878250e-02 6.13281548e-01 2.99186528e-01 -4.50588912e-01
5.94078541e-01 3.58934224e-01 8.79126847e-01 -7.89275408e-01
-1.02243590e+00 -8.67796361e-01 4.85507101e-01 -8.30353916e-01
1.06574312e-01 -4.82529253e-01 -1.60086966e+00 -2.29410768e-01
-1.58577710e-01 1.77399948e-01 3.34046781e-01 8.48911166e-01
4.36267853e-01 8.20494771e-01 -9.71546397e-02 -4.95780498e-01
-5.52077174e-01 -8.93443286e-01 -7.16819167e-02 4.35284495e-01
2.36232802e-01 -6.23987019e-01 -2.00905278e-01 -2.45447919e-01] | [9.140504837036133, 7.52302360534668] |
211289f8-63c9-43f0-9bb2-d83e07483ea2 | qfa2sr-query-free-adversarial-transfer | 2305.14097 | null | https://arxiv.org/abs/2305.14097v1 | https://arxiv.org/pdf/2305.14097v1.pdf | QFA2SR: Query-Free Adversarial Transfer Attacks to Speaker Recognition Systems | Current adversarial attacks against speaker recognition systems (SRSs) require either white-box access or heavy black-box queries to the target SRS, thus still falling behind practical attacks against proprietary commercial APIs and voice-controlled devices. To fill this gap, we propose QFA2SR, an effective and imperceptible query-free black-box attack, by leveraging the transferability of adversarial voices. To improve transferability, we present three novel methods, tailored loss functions, SRS ensemble, and time-freq corrosion. The first one tailors loss functions to different attack scenarios. The latter two augment surrogate SRSs in two different ways. SRS ensemble combines diverse surrogate SRSs with new strategies, amenable to the unique scoring characteristics of SRSs. Time-freq corrosion augments surrogate SRSs by incorporating well-designed time-/frequency-domain modification functions, which simulate and approximate the decision boundary of the target SRS and distortions introduced during over-the-air attacks. QFA2SR boosts the targeted transferability by 20.9%-70.7% on four popular commercial APIs (Microsoft Azure, iFlytek, Jingdong, and TalentedSoft), significantly outperforming existing attacks in query-free setting, with negligible effect on the imperceptibility. QFA2SR is also highly effective when launched over the air against three wide-spread voice assistants (Google Assistant, Apple Siri, and TMall Genie) with 60%, 46%, and 70% targeted transferability, respectively. | ['Fu Song', 'Zhe Zhao', 'Yedi Zhang', 'Guangke Chen'] | 2023-05-23 | null | null | null | null | ['speaker-recognition'] | ['speech'] | [ 1.93640366e-01 -8.11544061e-02 5.51609062e-02 -1.12734877e-01
-1.38024986e+00 -1.18725133e+00 3.69995594e-01 -3.78048033e-01
-3.41018379e-01 3.90535951e-01 1.90879062e-01 -6.36279047e-01
-1.67686090e-01 -3.92536372e-01 -3.72378320e-01 -5.17883360e-01
-2.15972319e-01 -3.10307950e-01 2.95414388e-01 -4.73336041e-01
-1.89425781e-01 5.83435953e-01 -1.08429933e+00 2.26664573e-01
8.41830552e-01 1.05005002e+00 -3.35051060e-01 1.00542116e+00
2.26179913e-01 5.41320980e-01 -1.38461971e+00 -7.85926819e-01
2.59531409e-01 -6.94047511e-02 -2.34728247e-01 -9.26495492e-01
3.78571302e-01 -3.02733511e-01 -6.53473914e-01 8.28392625e-01
1.11470127e+00 -2.42816389e-01 1.66243166e-01 -1.31909180e+00
-3.46115351e-01 6.99322224e-01 -1.88176647e-01 2.77336299e-01
6.75275385e-01 4.03868884e-01 9.86534297e-01 -3.31687450e-01
1.33068925e-02 1.32269812e+00 8.23389292e-01 8.79770160e-01
-9.93839085e-01 -1.32868230e+00 4.75355573e-02 -1.43177137e-01
-1.48540354e+00 -6.47209048e-01 7.75678694e-01 -4.66016270e-02
7.67028332e-01 1.03791130e+00 3.67577709e-02 1.56030142e+00
-5.48582636e-02 5.50023198e-01 1.01128626e+00 -9.17181447e-02
2.23821193e-01 2.98349291e-01 -1.41182588e-02 1.92145661e-01
-2.08982095e-01 6.01797163e-01 -7.07476377e-01 -8.75592053e-01
2.90754765e-01 -2.65164703e-01 -7.08215773e-01 2.64881343e-01
-9.17404175e-01 6.09280586e-01 9.74425524e-02 4.21968587e-02
-2.35590171e-02 9.34044495e-02 3.95450741e-01 5.69538534e-01
1.42367125e-01 5.04613459e-01 -5.85478127e-01 -4.15721804e-01
-6.68584228e-01 2.64410019e-01 9.66631949e-01 9.13836360e-01
1.42658487e-01 5.33588290e-01 -4.05700356e-01 6.34539127e-01
5.89259386e-01 1.17408204e+00 5.29568493e-01 -5.27166009e-01
7.46278763e-01 -8.06012675e-02 -6.17957972e-02 -6.96879745e-01
-2.02251136e-01 -7.21298397e-01 -2.75671005e-01 2.26896062e-01
3.69695872e-01 -5.19027352e-01 -6.13676012e-01 1.92666900e+00
2.55242288e-01 9.77310613e-02 2.59049922e-01 5.47192037e-01
6.04470789e-01 5.49648464e-01 1.57296155e-02 -3.51646729e-02
1.46343184e+00 -6.18560076e-01 -7.73126960e-01 -9.76757109e-02
1.72060937e-01 -9.91966069e-01 1.41472507e+00 5.45017123e-01
-8.42236459e-01 -4.18348253e-01 -1.53353858e+00 5.44712663e-01
-3.16561431e-01 -1.83342546e-01 2.07750469e-01 1.79734445e+00
-8.88424575e-01 2.51592875e-01 -5.19367337e-01 1.82829827e-01
1.74686238e-01 6.59892917e-01 -2.65386909e-01 3.91635507e-01
-1.65792334e+00 5.76520205e-01 -4.95265484e-01 -2.38764986e-01
-9.55698967e-01 -1.10614657e+00 -5.36338687e-01 8.33508745e-02
1.72606409e-01 -3.07409734e-01 1.41214406e+00 -5.47842741e-01
-2.14766955e+00 4.74478990e-01 2.48389825e-01 -5.76065063e-01
6.61290824e-01 -4.39710379e-01 -1.31647182e+00 1.09053977e-01
-4.16191995e-01 -3.23550217e-03 1.46246326e+00 -8.84615004e-01
-1.33123010e-01 -3.35877627e-01 8.32742155e-02 -1.40394270e-01
-6.57697082e-01 4.90443885e-01 -1.17471159e-01 -1.13524544e+00
-4.71849382e-01 -8.24251831e-01 1.74296588e-01 -3.13537151e-01
-7.30568886e-01 3.22309554e-01 1.24001646e+00 -7.41488755e-01
1.35535038e+00 -2.64028692e+00 -2.95614868e-01 3.33607852e-01
8.99776220e-02 8.32440674e-01 -2.45747149e-01 4.16548073e-01
-8.10694844e-02 2.09832504e-01 -9.03776512e-02 -1.57315910e-01
3.12501252e-01 -2.77018726e-01 -8.27762425e-01 3.65147471e-01
1.08517036e-01 6.31026030e-01 -4.74080265e-01 1.49614304e-01
-3.99825685e-02 7.33915448e-01 -6.07796311e-01 4.28922445e-01
1.38871908e-01 2.76765615e-01 -4.07960832e-01 6.34970129e-01
7.19573081e-01 5.40176094e-01 -1.12231307e-01 -7.48244971e-02
1.22573584e-01 5.17648816e-01 -1.13676858e+00 9.53856528e-01
-5.48982680e-01 5.13968647e-01 4.49603140e-01 -2.35008895e-01
1.05382574e+00 5.13697982e-01 6.96642278e-03 -5.64587533e-01
8.19058418e-02 3.59369308e-01 -7.01263547e-02 -2.41431952e-01
7.72977620e-02 -3.10332719e-02 -4.31021422e-01 3.58388424e-01
-5.07553481e-02 -2.45494053e-01 -6.16596103e-01 2.22449765e-01
1.24516702e+00 -3.87611061e-01 -1.02903828e-01 -2.75408980e-02
7.99494803e-01 -9.25475121e-01 3.82928133e-01 9.43897367e-01
-5.49407959e-01 5.53794980e-01 3.42594624e-01 2.54667819e-01
-3.79991472e-01 -1.44951630e+00 3.87434177e-02 1.22761345e+00
-3.12794447e-02 -4.99688774e-01 -8.96744668e-01 -8.63800645e-01
1.24239601e-01 7.13423312e-01 -1.63410604e-01 -4.88051534e-01
-6.19108558e-01 -2.44921178e-01 1.80690849e+00 1.96424797e-01
5.85591376e-01 -6.57545209e-01 -1.32479385e-01 4.94107269e-02
5.14376722e-02 -1.27151513e+00 -1.08033323e+00 -1.64215192e-02
-2.70143539e-01 -6.79057181e-01 -6.80215418e-01 -2.51043528e-01
-1.05880417e-01 1.50681600e-01 6.26223862e-01 -3.15172344e-01
-1.67919591e-01 5.72655141e-01 -1.85521558e-01 -5.75298190e-01
-6.60799980e-01 1.61325801e-02 3.63784879e-01 2.38680229e-01
5.80815710e-02 -6.44561291e-01 -3.54216307e-01 7.49397397e-01
-7.70134807e-01 -9.96963203e-01 3.47259700e-01 6.23651624e-01
-1.31540403e-01 -1.40950710e-01 9.40707862e-01 -3.94223243e-01
8.10766101e-01 -2.19590753e-01 -5.25381744e-01 1.71346292e-01
-3.01973999e-01 -1.40256092e-01 7.55154729e-01 -9.44917142e-01
-8.57593656e-01 -2.72969961e-01 -7.47393191e-01 -3.08901221e-01
1.23605214e-01 -2.27404628e-02 -7.56112039e-01 -5.74768960e-01
8.96094084e-01 2.19160423e-01 7.11377487e-02 -5.10974884e-01
4.30153430e-01 1.15163338e+00 6.88516021e-01 -2.78545082e-01
1.32543766e+00 2.18537793e-01 -7.17186093e-01 -9.95899498e-01
-8.41420963e-02 -2.33629718e-01 4.34371203e-01 3.18152830e-02
5.42024970e-01 -8.37816894e-01 -1.15314972e+00 8.69643748e-01
-9.18575943e-01 -1.11126192e-01 -1.16618887e-01 4.96784449e-01
-2.30891719e-01 4.45621967e-01 -5.96898079e-01 -9.76504624e-01
-8.41921508e-01 -1.08297527e+00 9.61473823e-01 1.27803460e-01
-3.09325427e-01 -4.71472234e-01 2.96293199e-03 7.21689463e-01
1.04001176e+00 5.44738024e-02 6.63353324e-01 -1.11817169e+00
-2.55847842e-01 -6.05756104e-01 2.32753634e-01 6.99303567e-01
1.05920218e-01 -1.92671679e-02 -1.56713843e+00 -5.16351879e-01
3.43400568e-01 1.05773949e-03 1.97783694e-01 3.28338109e-02
7.66083360e-01 -6.39146745e-01 -1.55802161e-01 7.17644513e-01
7.68332660e-01 4.62434471e-01 6.90013468e-01 1.41560376e-01
3.88640374e-01 2.50031233e-01 2.04214022e-01 3.94802302e-01
-3.27032804e-02 1.08289504e+00 4.61583555e-01 1.36080906e-01
-1.06682315e-01 -3.47064286e-01 1.07682288e+00 5.41824162e-01
4.50329363e-01 -3.71685565e-01 -4.70783144e-01 5.49334064e-02
-9.19944167e-01 -9.00260150e-01 2.04882935e-01 2.42113113e+00
9.28618431e-01 4.74258274e-01 4.03911889e-01 4.45596069e-01
6.89353466e-01 3.88802797e-01 -5.64835310e-01 -5.29597104e-01
-1.63708851e-01 4.66174096e-01 6.60079777e-01 7.35626101e-01
-1.07225370e+00 8.01005840e-01 6.12484407e+00 9.97651100e-01
-1.38107276e+00 3.19021225e-01 2.05318645e-01 -3.35621804e-01
-2.54595816e-01 -4.04729843e-01 -8.71896029e-01 5.09443939e-01
1.30397522e+00 -1.89910501e-01 5.73191106e-01 7.81395912e-01
1.44363213e-02 7.16479659e-01 -7.44664609e-01 8.63238633e-01
-2.13093627e-02 -9.67620671e-01 -2.82638699e-01 9.83171016e-02
4.71192924e-03 -5.87800108e-02 6.34808242e-01 4.47131127e-01
1.93331406e-01 -9.74379301e-01 7.40255475e-01 2.54177884e-03
1.07244277e+00 -7.73591757e-01 5.22928536e-01 -1.63062420e-02
-9.66059446e-01 -3.48332882e-01 2.30446026e-01 3.07458133e-01
2.18402818e-02 2.47671813e-01 -6.74652874e-01 4.33391571e-01
6.63670719e-01 -2.91041046e-01 -3.78656685e-01 6.14985347e-01
-2.53907949e-01 1.04570270e+00 -4.92331237e-01 -2.11251825e-01
-5.79657741e-02 4.81678933e-01 1.12772179e+00 1.13913214e+00
9.23433378e-02 -2.38045916e-01 -3.09320927e-01 5.74138224e-01
1.12156691e-02 -1.17526092e-01 -3.87188107e-01 -3.63570489e-02
9.39645708e-01 1.05520725e+00 3.63058448e-01 2.31745690e-01
2.29933392e-02 9.25129831e-01 -4.74925995e-01 5.66955090e-01
-1.11250091e+00 -1.12735248e+00 1.18231869e+00 1.57857742e-02
2.35578373e-01 -1.93341672e-01 -1.97417103e-02 -7.21673846e-01
2.17021704e-01 -1.67737675e+00 2.73808867e-01 -4.07090306e-01
-1.16349053e+00 1.03117764e+00 -2.43873700e-01 -1.19957149e+00
-2.70044655e-01 -3.53540927e-01 -7.72785544e-01 1.03244138e+00
-1.19217670e+00 -1.11298382e+00 -1.97161771e-02 9.56043363e-01
1.39480561e-01 -6.30624056e-01 1.03728294e+00 6.30943060e-01
-5.36829233e-01 1.63295352e+00 3.86702046e-02 1.61703587e-01
6.77227974e-01 -9.66870427e-01 8.70689392e-01 7.06159174e-01
6.21493645e-02 9.04116094e-01 7.85575986e-01 -2.37914398e-01
-1.60038388e+00 -8.28123927e-01 5.30624092e-01 -5.23657680e-01
8.07126939e-01 -9.06655550e-01 -8.30391347e-01 2.42878228e-01
2.02784106e-01 -4.03324701e-02 8.80912006e-01 -2.87395895e-01
-1.03907526e+00 -5.53797781e-01 -1.54325140e+00 7.27061749e-01
6.43398404e-01 -1.02985680e+00 -3.35392267e-01 1.93435416e-01
1.26622903e+00 -1.97749093e-01 -7.44461715e-01 2.81452626e-01
6.95028186e-01 -8.24491143e-01 1.24236917e+00 -4.93890911e-01
-6.45860612e-01 -2.54602134e-01 -4.06903684e-01 -1.06987631e+00
2.21586958e-01 -1.76704562e+00 -1.62327975e-01 1.55632317e+00
5.81025600e-01 -1.19837403e+00 6.01198018e-01 3.56039017e-01
1.57970693e-02 -3.66313964e-01 -1.22343683e+00 -1.20266747e+00
-1.01790717e-02 -7.36925244e-01 9.32337523e-01 6.08838022e-01
6.29545376e-02 8.83539915e-02 -4.82361823e-01 6.85873687e-01
4.45561469e-01 -7.76949763e-01 8.60970497e-01 -6.30456686e-01
-7.23243296e-01 -4.26265955e-01 -5.16206503e-01 -9.61590886e-01
-9.63977948e-02 -4.27823395e-01 -3.05619985e-01 -3.26382518e-01
-6.65496826e-01 -4.34557199e-01 -3.08772147e-01 3.92535955e-01
-6.90472201e-02 2.02588245e-01 3.76628280e-01 -9.13401544e-02
7.05726668e-02 4.45486397e-01 5.91215968e-01 -4.01989043e-01
-4.37373638e-01 6.66225970e-01 -7.13049293e-01 4.98236239e-01
8.19148898e-01 -4.02726889e-01 -5.79834700e-01 3.14455442e-02
-2.08759680e-01 5.33268750e-02 2.42928401e-01 -1.27120626e+00
7.09047094e-02 2.18548015e-01 -3.29487860e-01 -3.67572941e-02
5.02829313e-01 -7.38952577e-01 1.91288650e-01 5.12629807e-01
-4.07693088e-01 -1.36533640e-02 4.77302253e-01 6.27505004e-01
-5.41964173e-02 1.12464905e-01 7.61977851e-01 5.91362417e-01
3.20337005e-02 6.47492781e-02 -4.93273526e-01 1.04650863e-01
7.99068093e-01 -5.37630096e-02 -6.32237732e-01 -7.77314365e-01
-4.61884290e-01 -2.55625099e-01 -1.97156206e-01 7.74519682e-01
5.41422009e-01 -1.03726816e+00 -6.94997668e-01 7.29386449e-01
-3.69554609e-02 -8.49342823e-01 3.25883120e-01 5.73625803e-01
-2.36083195e-01 4.09744084e-01 2.77944595e-01 -4.12827462e-01
-1.62630451e+00 4.84419942e-01 5.94375193e-01 -4.01608236e-02
-3.17170501e-01 1.11915123e+00 1.26972407e-01 -6.96349919e-01
8.41352880e-01 -1.11613810e-01 6.63879365e-02 -3.80987406e-01
8.55659902e-01 4.47011322e-01 3.87930602e-01 -4.57291394e-01
-7.42806733e-01 4.71159220e-01 -9.36550125e-02 -4.30064082e-01
6.08883679e-01 1.42852172e-01 4.24823433e-01 -8.50167572e-02
1.35903096e+00 9.43509817e-01 -9.65558052e-01 -1.43604681e-01
-9.08700079e-02 -3.24140221e-01 -1.80660665e-01 -1.17432070e+00
-1.01004112e+00 7.79164970e-01 9.33016360e-01 5.70436299e-01
1.15064180e+00 -3.55836391e-01 1.07607007e+00 -1.06648375e-04
3.76637518e-01 -5.40705442e-01 1.52049288e-01 2.23565608e-01
9.29831684e-01 -6.27121270e-01 -3.98683757e-01 -4.63566661e-01
-6.82435989e-01 6.83376014e-01 3.20193321e-01 2.87590504e-01
6.74063981e-01 6.09376967e-01 4.97932523e-01 2.15497047e-01
-5.13978541e-01 4.02105808e-01 3.26076359e-01 8.94472361e-01
-1.00712245e-02 1.17387794e-01 2.59435605e-02 1.03868628e+00
-5.07690251e-01 -6.41830802e-01 1.81000859e-01 7.33705163e-01
-1.26748025e-01 -1.18380344e+00 -7.73775876e-01 -1.99777670e-02
-9.29831505e-01 -1.94731817e-01 -6.01154685e-01 5.92241526e-01
-3.16728055e-01 1.52462828e+00 -5.09857535e-01 -9.13932979e-01
6.81132793e-01 -6.52517453e-02 -1.31576911e-01 -7.46000558e-02
-1.28203177e+00 1.60093993e-01 2.81504005e-01 -5.42343557e-01
3.63530904e-01 -3.84002149e-01 -9.14418519e-01 -4.00442809e-01
-6.37792468e-01 1.78285226e-01 8.01337302e-01 6.70318484e-01
6.99630201e-01 5.59187889e-01 1.19830716e+00 -1.52165845e-01
-1.42656231e+00 -8.75493944e-01 -4.41236645e-01 -1.72483101e-02
6.60504401e-01 -3.24419945e-01 -9.23263371e-01 -6.32241189e-01] | [13.971423149108887, 5.826022148132324] |
c1dfb67b-9327-46bc-bfeb-3737fda5f8b8 | sapa-similarity-aware-point-affiliation-for | 2209.12866 | null | https://arxiv.org/abs/2209.12866v2 | https://arxiv.org/pdf/2209.12866v2.pdf | SAPA: Similarity-Aware Point Affiliation for Feature Upsampling | We introduce point affiliation into feature upsampling, a notion that describes the affiliation of each upsampled point to a semantic cluster formed by local decoder feature points with semantic similarity. By rethinking point affiliation, we present a generic formulation for generating upsampling kernels. The kernels encourage not only semantic smoothness but also boundary sharpness in the upsampled feature maps. Such properties are particularly useful for some dense prediction tasks such as semantic segmentation. The key idea of our formulation is to generate similarity-aware kernels by comparing the similarity between each encoder feature point and the spatially associated local region of decoder features. In this way, the encoder feature point can function as a cue to inform the semantic cluster of upsampled feature points. To embody the formulation, we further instantiate a lightweight upsampling operator, termed Similarity-Aware Point Affiliation (SAPA), and investigate its variants. SAPA invites consistent performance improvements on a number of dense prediction tasks, including semantic segmentation, object detection, depth estimation, and image matting. Code is available at: https://github.com/poppinace/sapa | ['Zhiguo Cao', 'Yuliang Liu', 'Hongtao Fu', 'Zixuan Ye', 'Wenze Liu', 'Hao Lu'] | 2022-09-26 | null | null | null | null | ['image-matting'] | ['computer-vision'] | [ 1.60582438e-01 2.31640100e-01 -2.40080401e-01 -5.75900018e-01
-8.49657238e-01 -2.64477879e-01 6.37998581e-01 2.19733357e-01
-1.23333866e-02 3.46794724e-01 3.00101042e-01 3.09725493e-01
4.06062696e-03 -8.65442693e-01 -9.77674007e-01 -5.10879934e-01
8.72274861e-02 3.84792507e-01 5.75140178e-01 4.63888422e-02
3.83115560e-01 5.81905842e-01 -1.50858510e+00 5.18209636e-01
1.02021539e+00 1.04886997e+00 4.92724866e-01 3.63182873e-01
-1.88078269e-01 2.98340321e-01 -1.43489078e-01 -3.20402861e-01
2.47755006e-01 -3.13802779e-01 -9.49532807e-01 3.02997351e-01
6.84015810e-01 -2.33869836e-01 -1.93846196e-01 1.11638772e+00
1.95882730e-02 1.45308018e-01 6.16675079e-01 -1.18798125e+00
-5.65340042e-01 5.60620844e-01 -7.21636474e-01 6.71837330e-02
1.60314709e-01 -4.71366122e-02 1.15576398e+00 -1.22473192e+00
5.55163085e-01 1.14628875e+00 8.07282686e-01 4.01416570e-01
-1.20013344e+00 -3.22060138e-01 2.67792702e-01 1.71838582e-01
-1.31338310e+00 -4.03049439e-01 8.79269719e-01 -4.91885036e-01
4.36171800e-01 9.26416740e-02 7.80220091e-01 7.05341637e-01
-3.86470295e-02 1.28452730e+00 7.77132511e-01 -2.46730804e-01
4.44847703e-01 9.73939821e-02 2.60963082e-01 8.40640008e-01
1.84497628e-02 -2.00385213e-01 -6.39551461e-01 -1.89450026e-01
1.29609263e+00 2.12902218e-01 -4.63479936e-01 -8.45412254e-01
-1.22288358e+00 9.64001477e-01 9.19117510e-01 4.65062261e-02
-3.83254588e-01 3.32009435e-01 1.45347238e-01 -1.70533851e-01
6.83040500e-01 3.01931709e-01 -2.73851722e-01 2.29806956e-02
-1.07444108e+00 1.76742747e-01 4.54061836e-01 1.15818453e+00
1.31970823e+00 -3.48354101e-01 -2.02258065e-01 8.21968019e-01
2.89084315e-01 1.93014964e-01 4.28952813e-01 -1.16905940e+00
1.94577828e-01 6.60195470e-01 4.59991209e-02 -7.97752440e-01
-1.04494900e-01 -2.55561560e-01 -5.70940614e-01 7.05760270e-02
4.03380424e-01 1.36265889e-01 -9.48028624e-01 1.55723858e+00
6.04667068e-01 6.12455964e-01 -1.38342291e-01 1.03593576e+00
6.29223526e-01 6.73492968e-01 -2.59230375e-01 3.83158118e-01
1.35882807e+00 -1.15310872e+00 -2.27047130e-01 -1.92852288e-01
5.39725482e-01 -6.50437593e-01 1.13365340e+00 6.72317296e-02
-1.16312623e+00 -5.36977112e-01 -8.84353697e-01 -3.65175724e-01
-1.53390855e-01 1.70221120e-01 8.78598034e-01 1.43490091e-01
-1.14110959e+00 8.55929494e-01 -1.00270247e+00 -3.57161611e-01
7.39580572e-01 2.05728486e-01 -2.29366183e-01 -1.04050659e-01
-8.50674152e-01 4.79766190e-01 2.10251257e-01 -1.65980101e-01
-6.28598273e-01 -1.09225368e+00 -1.10346222e+00 -2.30537932e-02
-2.60779280e-02 -8.70311320e-01 1.27444935e+00 -1.11524773e+00
-1.12803578e+00 1.02661216e+00 -4.33780670e-01 -4.90836054e-01
4.12213147e-01 -4.14163351e-01 5.21571115e-02 3.44908506e-01
4.41360384e-01 9.61230457e-01 1.21703041e+00 -1.17844284e+00
-8.10293913e-01 -4.44942117e-01 -5.74229807e-02 3.15539956e-01
-5.11699542e-03 -2.86134064e-01 -5.92376709e-01 -7.59742022e-01
4.73554581e-01 -6.35368288e-01 -3.05056900e-01 4.51300770e-01
-5.82680345e-01 -9.66480523e-02 8.78779411e-01 -3.31382364e-01
8.16082835e-01 -2.49893475e+00 1.80061057e-01 3.19139630e-01
3.44898045e-01 -1.07707731e-01 -1.74242351e-02 1.25350937e-01
-3.07210386e-02 -3.56765747e-01 -5.67532718e-01 -4.86228973e-01
-7.60562718e-02 1.06752165e-01 -3.92939091e-01 5.73863029e-01
3.62827659e-01 1.04245591e+00 -1.07198262e+00 -2.66741574e-01
3.43526423e-01 6.68413162e-01 -7.30738878e-01 7.31824040e-02
-2.45935857e-01 3.35337251e-01 -8.34185064e-01 7.07307577e-01
7.07499981e-01 -5.16422153e-01 -6.05148137e-01 -4.15605515e-01
-2.18445417e-02 1.90461218e-01 -1.16289425e+00 2.13671899e+00
-2.04500243e-01 5.35105288e-01 8.75654817e-02 -7.57547557e-01
8.73363972e-01 -1.47923410e-01 4.64833230e-01 -2.31146112e-01
-1.66432366e-01 2.07288116e-01 -5.29996216e-01 -1.36685103e-01
5.74473441e-01 -1.08909803e-02 1.02662496e-01 1.42343238e-01
8.95099416e-02 -2.99566537e-01 -2.52993345e-01 3.38727862e-01
9.87785518e-01 1.06246136e-01 2.70061851e-01 -4.13316160e-01
3.86713296e-01 1.21407010e-01 4.26060289e-01 5.01850903e-01
-2.04799399e-01 1.03148317e+00 3.80321741e-01 -3.37186009e-01
-1.13142419e+00 -1.41047204e+00 -5.17783582e-01 8.67462277e-01
4.89626378e-01 -2.97926486e-01 -9.63372350e-01 -6.95578873e-01
2.59524822e-01 3.85651231e-01 -7.64826357e-01 -6.36730269e-02
-3.76450449e-01 -3.30708057e-01 1.65049374e-01 7.79019117e-01
6.14206195e-01 -8.10210943e-01 -5.28021812e-01 -2.78012808e-02
1.21836010e-02 -9.87600505e-01 -8.46838236e-01 1.92159116e-01
-9.67411876e-01 -1.02700305e+00 -1.06240690e+00 -8.81352961e-01
9.31483269e-01 3.44703346e-01 9.82720554e-01 -2.00814888e-01
-2.15997338e-01 4.20094103e-01 -4.60355937e-01 1.10755451e-02
-1.80653650e-02 7.35232979e-02 -1.37750104e-01 1.96699083e-01
2.84524351e-01 -4.40096974e-01 -8.83703291e-01 1.69725999e-01
-7.95247376e-01 3.96599203e-01 5.04756629e-01 6.49713457e-01
8.70351315e-01 -4.39873666e-01 2.82651365e-01 -8.74382615e-01
1.99626163e-01 -5.50052881e-01 -4.76026148e-01 -2.26271097e-02
-8.26189853e-03 2.63067216e-01 3.75377715e-01 -1.51975647e-01
-6.66196644e-01 3.47345412e-01 -2.29440242e-01 -6.53762102e-01
-3.34118396e-01 -5.20685427e-02 -2.30740428e-01 -7.44911805e-02
5.33382297e-01 3.20767730e-01 1.12404801e-01 -4.63065565e-01
7.58986652e-01 4.05427277e-01 5.03526092e-01 -5.66283464e-01
7.14724600e-01 9.37614799e-01 -2.59938002e-01 -8.84231985e-01
-1.00386393e+00 -6.87655866e-01 -7.25532591e-01 3.01510114e-02
8.45840693e-01 -9.03793931e-01 -2.66671389e-01 4.02255982e-01
-1.09352684e+00 -4.03842837e-01 -8.55687320e-01 3.18943024e-01
-1.04621100e+00 2.02223808e-01 -6.66681707e-01 -2.47993708e-01
-1.28956988e-01 -1.22614348e+00 1.53389943e+00 3.36172968e-01
-2.74056166e-01 -1.06329811e+00 4.22409587e-02 8.80596042e-02
1.24883987e-01 1.63311943e-01 8.37109566e-01 -4.79817271e-01
-7.47089684e-01 -8.17185938e-02 -4.39217091e-01 2.76127040e-01
1.89040899e-01 -9.57668200e-02 -1.07297683e+00 -1.39568344e-01
-1.29973322e-01 -8.32178369e-02 9.99283254e-01 8.43496501e-01
1.25625503e+00 -9.28180590e-02 -5.72860897e-01 1.02545857e+00
1.37389576e+00 -3.16697121e-01 5.02834201e-01 2.23262325e-01
9.29507196e-01 5.43033659e-01 6.76222503e-01 6.09256208e-01
2.74852216e-01 6.86137080e-01 3.86492342e-01 -2.36615539e-01
-2.45898768e-01 -5.15416622e-01 2.28712365e-01 3.91615540e-01
2.07542524e-01 3.50912929e-01 -6.82734489e-01 7.09177315e-01
-1.98888254e+00 -5.96884549e-01 -2.88527250e-01 2.11999154e+00
7.31965959e-01 -2.11065769e-01 2.08801717e-01 -1.45223588e-01
9.20364201e-01 1.91004977e-01 -6.44990265e-01 -1.77768037e-01
2.97176912e-02 3.00680608e-01 4.62025315e-01 6.85774446e-01
-1.18140471e+00 1.13307261e+00 5.71048832e+00 1.06561565e+00
-8.59704316e-01 6.73733465e-03 7.59224296e-01 3.93171329e-03
-5.13962746e-01 9.84780565e-02 -9.62589025e-01 5.68771243e-01
2.83524036e-01 -9.34104621e-02 1.35611296e-01 1.14231253e+00
1.58013225e-01 -1.62404299e-01 -1.31114197e+00 8.71725857e-01
-4.13615182e-02 -1.76555765e+00 3.40783894e-01 -1.39039144e-01
8.16436887e-01 9.18986797e-02 1.80143505e-01 -1.37878671e-01
2.48873040e-01 -8.26236367e-01 8.26456845e-01 4.78118956e-01
7.15352416e-01 -7.76838899e-01 2.96001852e-01 6.19962253e-02
-1.33757114e+00 1.39256820e-01 -5.55834353e-01 1.35442570e-01
1.91486061e-01 9.29189146e-01 -6.95262372e-01 3.07402402e-01
6.16268873e-01 1.17740846e+00 -4.17078763e-01 1.27142966e+00
-2.54805803e-01 2.94506043e-01 -3.75151992e-01 3.93460006e-01
4.38313812e-01 -2.27394775e-01 4.35431361e-01 1.11628604e+00
3.72539192e-01 -5.59799820e-02 -4.89928983e-02 1.22502100e+00
1.86278094e-02 -1.91017482e-02 -5.80059350e-01 4.03504968e-01
6.04004502e-01 1.10314941e+00 -9.17093933e-01 -4.24105376e-01
-4.26259905e-01 1.45442581e+00 4.90111768e-01 4.28876787e-01
-8.99010181e-01 -3.37356567e-01 1.20456898e+00 4.98530388e-01
5.54128706e-01 -8.08992535e-02 -5.16666830e-01 -1.11771131e+00
9.18981209e-02 -2.67619997e-01 1.04003444e-01 -8.24464500e-01
-1.22011232e+00 2.34646380e-01 -9.08128992e-02 -1.32161999e+00
1.07836619e-01 -4.10967886e-01 -7.91242719e-01 8.89314651e-01
-1.50958812e+00 -1.08677208e+00 -4.75769907e-01 8.07790279e-01
7.74181604e-01 3.25998515e-01 4.92843270e-01 1.07173715e-02
-3.71823460e-01 4.56301868e-01 1.11981742e-01 2.87256613e-02
5.19963503e-01 -1.33171523e+00 6.29323721e-01 6.99546397e-01
2.09796458e-01 4.91289288e-01 4.01042432e-01 -6.65432632e-01
-9.66959536e-01 -1.40430856e+00 5.79060674e-01 -3.74960333e-01
6.39822781e-01 -3.38565171e-01 -9.85037386e-01 7.89718151e-01
-2.58446097e-01 2.81526983e-01 3.73978198e-01 -1.41491637e-01
-3.07736009e-01 -2.68498082e-02 -1.16265798e+00 6.05643749e-01
9.75326300e-01 -5.22584260e-01 -4.82200980e-01 2.98485219e-01
7.34607339e-01 -4.90925997e-01 -7.87165701e-01 3.23051065e-01
2.09008753e-01 -1.19154286e+00 1.17315006e+00 -1.62151128e-01
6.25220895e-01 -3.66791636e-01 -1.12389512e-01 -1.21576726e+00
-5.74237645e-01 -4.56693977e-01 -2.37035796e-01 1.00797415e+00
3.21912140e-01 -5.00577152e-01 1.11689770e+00 5.15584469e-01
-5.58058262e-01 -1.07853544e+00 -7.81322241e-01 -6.13531888e-01
6.96719736e-02 -4.35169280e-01 6.35573387e-01 9.55554307e-01
1.24437198e-01 -1.42184362e-01 3.41168530e-02 4.08534497e-01
7.77656376e-01 2.61019826e-01 5.87692797e-01 -8.88490021e-01
-2.63658643e-01 -6.04600310e-01 -7.87453532e-01 -1.60790646e+00
-2.59033591e-02 -1.08895099e+00 4.49200384e-02 -1.57584834e+00
1.90859720e-01 -6.90365970e-01 -1.11429468e-02 3.22727531e-01
-2.78428257e-01 3.93348753e-01 -3.11073996e-02 3.52647543e-01
-5.40691257e-01 6.76203132e-01 1.34164035e+00 2.14316726e-01
-1.74710900e-01 5.89006916e-02 -6.00497186e-01 9.90171909e-01
7.72288799e-01 -1.48647070e-01 -4.57193524e-01 -4.24158365e-01
-2.44013742e-01 -1.93103209e-01 7.19834805e-01 -1.17481208e+00
1.70229658e-01 -8.03172588e-02 4.15669769e-01 -5.42404413e-01
4.66410428e-01 -5.99325180e-01 -2.65846327e-02 2.80043095e-01
-3.88009369e-01 -2.59585291e-01 -6.43172935e-02 6.05578721e-01
-2.47783810e-01 -2.87051111e-01 9.56816196e-01 -1.46113783e-01
-1.16407931e+00 5.87117612e-01 5.38780354e-04 1.79752082e-01
1.37812662e+00 -6.83574617e-01 -1.82147939e-02 -1.16874486e-01
-7.45372415e-01 1.42097235e-01 9.11374211e-01 2.67034918e-01
1.05866051e+00 -1.38120306e+00 -4.98665184e-01 6.13988221e-01
2.86942929e-01 5.11093378e-01 1.99207246e-01 8.77104282e-01
-6.21607840e-01 1.75958067e-01 1.82134714e-02 -9.66495275e-01
-8.83869469e-01 2.98454940e-01 3.25771540e-01 3.51873428e-01
-1.20856512e+00 1.31417477e+00 8.05821955e-01 5.84015921e-02
1.94489390e-01 -8.41750681e-01 1.82086766e-01 -1.61994994e-01
5.92620134e-01 2.59476960e-01 -1.16193973e-01 -5.74773788e-01
-3.31400275e-01 8.25706601e-01 -2.72516459e-01 9.78528857e-02
1.06172025e+00 -1.11557968e-01 5.55810221e-02 5.34883857e-01
1.29441106e+00 -9.20426324e-02 -1.90950000e+00 -3.48085850e-01
-8.74864459e-02 -6.66914701e-01 -5.28095057e-03 -1.24891013e-01
-1.12510681e+00 7.14356899e-01 2.44669095e-01 -5.82110547e-02
8.44512820e-01 7.03390241e-01 9.65750635e-01 -1.00735970e-01
5.11634290e-01 -8.56407583e-01 7.79505372e-02 4.27140951e-01
7.73844361e-01 -1.16429412e+00 -3.28221232e-01 -7.20305383e-01
-7.73980141e-01 9.26211774e-01 5.64280212e-01 -6.80439413e-01
7.72302628e-01 2.84637719e-01 -1.71471760e-01 -2.70131916e-01
-3.42441201e-01 -3.32101971e-01 3.20651144e-01 6.92605853e-01
3.16151172e-01 9.95202586e-02 1.33213952e-01 4.62359160e-01
-2.42202818e-01 -1.60258904e-01 1.93149462e-01 6.94284081e-01
-7.70522296e-01 -7.64090896e-01 -3.01789463e-01 5.50473094e-01
1.47357076e-01 -2.50135273e-01 -1.34968653e-01 5.19776344e-01
1.26174584e-01 1.88919187e-01 5.32161832e-01 -1.72402114e-01
1.65626809e-01 -1.15631320e-01 4.43891019e-01 -9.16350901e-01
-1.84267253e-01 -1.30609032e-02 -3.30784887e-01 -9.32238042e-01
-1.93280160e-01 -6.85907364e-01 -1.62850559e+00 -1.70578972e-01
-1.00143492e-01 1.06634624e-01 4.34852928e-01 7.68381000e-01
4.50281084e-01 2.38368079e-01 5.97478390e-01 -1.05587769e+00
-3.05938005e-01 -5.90790033e-01 -7.82517016e-01 4.84831065e-01
4.65875894e-01 -6.39680266e-01 -2.60646582e-01 1.09911345e-01] | [9.603850364685059, 0.3909594416618347] |
58091173-b880-4ab7-9641-35d243a8902a | hallucinated-iqa-no-reference-image-quality | 1804.01681 | null | http://arxiv.org/abs/1804.01681v1 | http://arxiv.org/pdf/1804.01681v1.pdf | Hallucinated-IQA: No-Reference Image Quality Assessment via Adversarial Learning | No-reference image quality assessment (NR-IQA) is a fundamental yet
challenging task in low-level computer vision community. The difficulty is
particularly pronounced for the limited information, for which the
corresponding reference for comparison is typically absent. Although various
feature extraction mechanisms have been leveraged from natural scene statistics
to deep neural networks in previous methods, the performance bottleneck still
exists. In this work, we propose a hallucination-guided quality regression
network to address the issue. We firstly generate a hallucinated reference
constrained on the distorted image, to compensate the absence of the true
reference. Then, we pair the information of hallucinated reference with the
distorted image, and forward them to the regressor to learn the perceptual
discrepancy with the guidance of an implicit ranking relationship within the
generator, and therefore produce the precise quality prediction. To demonstrate
the effectiveness of our approach, comprehensive experiments are evaluated on
four popular image quality assessment benchmarks. Our method significantly
outperforms all the previous state-of-the-art methods by large margins. The
code and model will be publicly available on the project page
https://kwanyeelin.github.io/projects/HIQA/HIQA.html. | ['Kwan-Yee Lin', 'Guanxiang Wang'] | 2018-04-05 | hallucinated-iqa-no-reference-image-quality-1 | http://openaccess.thecvf.com/content_cvpr_2018/html/Lin_Hallucinated-IQA_No-Reference_Image_CVPR_2018_paper.html | http://openaccess.thecvf.com/content_cvpr_2018/papers/Lin_Hallucinated-IQA_No-Reference_Image_CVPR_2018_paper.pdf | cvpr-2018-6 | ['no-reference-image-quality-assessment'] | ['computer-vision'] | [ 2.82868832e-01 -2.19519109e-01 -7.09612817e-02 -2.77040601e-01
-1.23835039e+00 -1.88434809e-01 4.23724532e-01 -2.10697457e-01
-6.33389503e-02 6.23387277e-01 4.17180061e-01 2.93709747e-02
-5.82288727e-02 -5.18282473e-01 -5.67933500e-01 -7.90594757e-01
3.80789369e-01 -9.00033042e-02 6.52534701e-03 -5.65470122e-02
4.02465492e-01 1.63951814e-01 -1.36294889e+00 2.53332406e-01
1.22991550e+00 1.27136207e+00 3.87387782e-01 4.55420047e-01
3.50412905e-01 8.86139929e-01 -5.32920122e-01 -4.27144855e-01
4.20148164e-01 -6.71499074e-01 -5.82881570e-01 3.00595134e-01
5.97699463e-01 -5.48084259e-01 -6.09090090e-01 1.39891684e+00
7.72841156e-01 1.78459257e-01 5.87875962e-01 -1.28092909e+00
-9.87233520e-01 2.02058002e-01 -6.87316895e-01 2.79494315e-01
2.80076504e-01 5.66819131e-01 9.78496671e-01 -1.29429293e+00
4.81088042e-01 1.16102719e+00 1.78695515e-01 4.14579928e-01
-1.14393401e+00 -6.65425897e-01 -7.76908398e-02 4.53348219e-01
-1.38360322e+00 -8.70136142e-01 9.21065509e-01 -4.58948910e-01
4.77878213e-01 -4.89160269e-02 2.79239148e-01 1.00642180e+00
2.42381960e-01 6.66548014e-01 1.14328539e+00 -2.20065355e-01
7.79189914e-02 -6.50400966e-02 -3.51982750e-02 7.02761114e-01
-5.81177473e-02 3.64797711e-01 -5.13498008e-01 1.03411324e-01
6.02856874e-01 -9.58519652e-02 -6.94718421e-01 -3.79027814e-01
-1.27511632e+00 5.35588980e-01 8.52217615e-01 3.06887906e-02
-4.92886484e-01 -1.01642579e-01 1.70448110e-01 3.48384887e-01
3.62255692e-01 4.18080926e-01 8.64915922e-03 8.71452168e-02
-1.06769109e+00 2.35178754e-01 3.81399572e-01 7.36768544e-01
6.68265879e-01 1.38562620e-01 -4.52145755e-01 1.07947338e+00
2.34794930e-01 4.85728830e-01 3.35913986e-01 -1.36845446e+00
6.27526641e-01 3.24716538e-01 1.94955483e-01 -1.18429911e+00
3.60687450e-02 -7.52025425e-01 -1.14418769e+00 4.91009086e-01
3.75104338e-01 1.86040431e-01 -6.84776366e-01 1.63097358e+00
1.58162728e-01 1.50275007e-01 4.38082207e-04 1.30429077e+00
9.00283277e-01 7.70673811e-01 -1.47014663e-01 -3.02764237e-01
1.08236158e+00 -1.25374961e+00 -5.98967254e-01 -4.73427773e-02
7.42259473e-02 -8.96794915e-01 1.21070147e+00 6.20184481e-01
-1.32307851e+00 -9.30821240e-01 -1.19612432e+00 -2.55018860e-01
1.78633049e-01 3.26525182e-01 1.34874672e-01 2.78317124e-01
-1.19889116e+00 6.01301789e-01 -4.08931345e-01 2.20487523e-03
6.40992224e-01 5.55122606e-02 -1.14570931e-01 -4.57948178e-01
-1.13924623e+00 8.11011314e-01 1.41105905e-01 1.84242472e-01
-1.15663934e+00 -6.16307914e-01 -8.82021308e-01 -1.52621027e-02
4.60602432e-01 -8.34596395e-01 1.20146608e+00 -1.11566901e+00
-1.47081530e+00 6.68746293e-01 -1.45210788e-01 -1.26007065e-01
6.22628808e-01 -2.25077614e-01 -4.29600656e-01 4.33556698e-02
3.29965413e-01 7.76588678e-01 8.80242944e-01 -1.51835179e+00
-4.16832477e-01 -2.44162783e-01 9.72096622e-02 4.25013363e-01
-1.20463865e-02 -2.76180618e-02 -7.15913057e-01 -6.42244697e-01
5.86676598e-02 -5.69622695e-01 -1.67904347e-01 2.54410207e-01
-5.55059433e-01 -6.28429875e-02 3.74341279e-01 -8.45820844e-01
1.19861627e+00 -2.31450629e+00 1.22237250e-01 -5.72088622e-02
4.25419360e-01 2.06941694e-01 -3.83930266e-01 3.33412111e-01
3.18980590e-02 -2.16943741e-01 -4.15058702e-01 -1.80840686e-01
-7.48224556e-02 -2.97149301e-01 -4.02586162e-01 5.90638876e-01
3.99162441e-01 7.86940277e-01 -9.97424960e-01 -4.77877229e-01
1.31228730e-01 4.84112620e-01 -4.36296344e-01 6.03528976e-01
4.41072211e-02 6.11645401e-01 -1.82566360e-01 7.56504834e-01
7.46206045e-01 -4.57332551e-01 -2.61617959e-01 -6.28576398e-01
-3.80373001e-02 2.59719104e-01 -1.04766953e+00 1.86737871e+00
-4.16138500e-01 5.24778783e-01 -1.10752590e-01 -7.49265611e-01
9.38514471e-01 1.21322505e-01 2.87253290e-01 -1.01544142e+00
-5.69039807e-02 2.37097949e-01 1.79001316e-01 -5.20652473e-01
4.59616274e-01 6.76526576e-02 2.30201915e-01 1.88514814e-01
8.05044249e-02 -1.73466653e-01 1.41418979e-01 2.62874275e-01
9.37141955e-01 2.27001041e-01 4.29202527e-01 5.60436808e-02
7.22207129e-01 -1.88904613e-01 7.44785666e-01 6.36286139e-01
-6.01605356e-01 1.11126173e+00 4.48116422e-01 -1.12791315e-01
-1.21576095e+00 -1.34206820e+00 -2.34277975e-02 7.30006039e-01
4.81178731e-01 -2.18966529e-01 -6.08488858e-01 -4.96629328e-01
-3.22823733e-01 5.57171881e-01 -3.76051545e-01 -2.45304808e-01
-3.03480685e-01 -4.94883150e-01 2.36171246e-01 2.92631477e-01
7.91857600e-01 -1.16747284e+00 -1.59199879e-01 9.40022767e-02
-4.57947999e-01 -1.00037754e+00 -7.10666716e-01 -3.96298915e-01
-6.15481913e-01 -9.79177594e-01 -8.43321085e-01 -5.61455786e-01
5.71904778e-01 4.97108579e-01 1.26906657e+00 2.28518799e-01
-1.06539726e-01 -1.61221158e-02 -1.36210829e-01 7.15046674e-02
-3.36053491e-01 -3.34965676e-01 -1.57050863e-01 1.14016727e-01
-4.66770083e-02 -5.40637195e-01 -1.05728495e+00 3.58894020e-01
-8.86728823e-01 2.63616532e-01 7.03773260e-01 1.14978337e+00
7.50587106e-01 6.61846399e-02 7.25961924e-01 -5.79851210e-01
6.53147757e-01 -5.13761699e-01 -5.47216952e-01 6.97448626e-02
-6.04601204e-01 -4.04112190e-02 6.24558866e-01 -2.18371257e-01
-1.05399346e+00 -1.50039062e-01 -1.94909990e-01 -5.86743355e-01
-9.67439637e-02 3.79639357e-01 -6.95232749e-01 1.28402337e-01
5.62265813e-01 3.48397434e-01 -1.45514473e-01 -2.92993158e-01
3.47938031e-01 6.35061383e-01 8.27674210e-01 -3.82458001e-01
9.08064902e-01 2.81158268e-01 -1.33597627e-01 -4.79823440e-01
-1.01613569e+00 -4.05792117e-01 -4.05662715e-01 -3.32639754e-01
6.05339289e-01 -1.02415419e+00 -3.20865721e-01 4.15243030e-01
-1.13618290e+00 -2.77455807e-01 -1.72462001e-01 3.90816748e-01
-6.23001099e-01 4.93463784e-01 -5.60171127e-01 -5.73825955e-01
-3.96548808e-01 -1.41798890e+00 9.12448704e-01 3.28996956e-01
7.30462372e-02 -4.81598288e-01 5.23658656e-02 5.44236779e-01
4.19947714e-01 1.43635333e-01 7.21909463e-01 -2.12115556e-01
-7.85049558e-01 7.18271434e-02 -7.19948649e-01 6.21154070e-01
1.36631578e-01 -9.90290642e-02 -9.52435791e-01 -2.87338227e-01
8.83368477e-02 -5.22344649e-01 8.96270216e-01 2.92063385e-01
1.32347488e+00 -2.40422398e-01 2.15771869e-01 7.62222826e-01
1.49329376e+00 3.63691002e-02 9.12721992e-01 3.02802354e-01
6.22120142e-01 5.42328298e-01 7.53919303e-01 3.16003233e-01
5.05364954e-01 8.37731540e-01 4.89948481e-01 -1.38606399e-01
-5.92467546e-01 -2.38406718e-01 4.65851218e-01 1.00111842e+00
1.83362775e-02 -3.52518708e-01 -7.62420833e-01 4.84443665e-01
-1.58255255e+00 -9.63130891e-01 1.93394497e-02 2.15326023e+00
8.91667426e-01 9.22947153e-02 -1.57840639e-01 2.54752070e-01
6.66741431e-01 3.79177392e-01 -7.47031271e-01 -2.94812117e-03
-9.80754942e-02 -1.33002505e-01 -4.79439721e-02 4.80496407e-01
-9.73132670e-01 6.33688986e-01 5.02178621e+00 9.67953026e-01
-9.67348456e-01 9.11256149e-02 9.70528781e-01 -8.68843868e-02
-1.26408026e-01 -9.21400413e-02 -3.24253976e-01 5.27374327e-01
7.05986440e-01 -1.96242169e-01 5.39414108e-01 5.94680250e-01
5.42028010e-01 -1.83402926e-01 -1.04358149e+00 1.27707922e+00
2.93364257e-01 -8.91935587e-01 9.66503769e-02 -1.10456303e-01
9.02218997e-01 -3.87918353e-02 3.95262450e-01 2.00522557e-01
-2.35797907e-03 -1.04771316e+00 5.94056427e-01 8.04742694e-01
9.91381705e-01 -6.62143707e-01 6.39037967e-01 1.82470709e-01
-8.57992113e-01 6.45263214e-03 -6.28388107e-01 7.32299536e-02
8.59462023e-02 8.49235415e-01 -3.29855651e-01 6.61226928e-01
5.67469299e-01 8.53932559e-01 -7.03436136e-01 1.30332005e+00
-3.47709596e-01 4.98708636e-01 3.36648911e-01 5.04843116e-01
2.93224193e-02 -2.43064597e-01 4.42890048e-01 8.64771903e-01
5.26619256e-01 2.23090619e-01 7.92520493e-02 1.03935218e+00
-3.77325743e-01 1.83460101e-01 -4.45505321e-01 2.82338589e-01
2.78417140e-01 1.28461480e+00 -2.27969587e-01 -3.05650771e-01
-5.24809957e-01 1.07899630e+00 3.87225777e-01 4.82018888e-01
-7.10274994e-01 -3.95037502e-01 6.33892596e-01 1.03733115e-01
1.42720910e-02 -3.34021705e-03 -2.54543841e-01 -1.33670962e+00
2.52650112e-01 -1.25582778e+00 1.72017664e-01 -1.15500820e+00
-1.47057617e+00 8.24285626e-01 -3.07833225e-01 -1.70318222e+00
-2.44865164e-01 -3.25516582e-01 -6.68512344e-01 1.14522529e+00
-1.74776375e+00 -8.71743798e-01 -6.90997839e-01 5.98674059e-01
7.34209180e-01 -1.81890875e-01 4.63094085e-01 4.25529540e-01
-5.37173569e-01 6.46144867e-01 -9.47783410e-05 1.74803913e-01
1.00528991e+00 -1.04371262e+00 2.44649127e-01 1.09668553e+00
3.74479615e-03 2.85786182e-01 6.43311381e-01 -5.48100412e-01
-1.23870802e+00 -1.08650947e+00 6.05733156e-01 -2.75229722e-01
6.02758765e-01 -9.62426811e-02 -1.19383693e+00 -3.14719826e-02
4.79337603e-01 2.77780205e-01 4.66234297e-01 -4.20682430e-01
-5.88929176e-01 -3.00055146e-01 -9.67848420e-01 6.56399190e-01
1.02531040e+00 -5.01415849e-01 -3.48205507e-01 6.77839816e-02
7.61407733e-01 -2.83242851e-01 -7.32884407e-01 4.48021144e-01
4.32764381e-01 -1.28154016e+00 9.59585547e-01 -1.20103024e-01
1.01684988e+00 -5.91442704e-01 -2.72639155e-01 -1.50096285e+00
-3.84723604e-01 -3.03580821e-01 -1.69351548e-01 1.24273336e+00
2.58937925e-01 -3.51713538e-01 4.44417447e-01 2.97517627e-01
-2.19825462e-01 -8.40269446e-01 -7.22034574e-01 -6.09081805e-01
-9.95432660e-02 -2.25900412e-01 5.21481156e-01 6.35545671e-01
-3.55912805e-01 3.49161536e-01 -6.51254773e-01 2.22027242e-01
9.76683795e-01 1.94337890e-01 7.54373729e-01 -7.36419141e-01
-5.41294336e-01 -4.86823827e-01 -4.22100067e-01 -1.16010141e+00
-2.26294957e-02 -7.34813809e-01 3.24640900e-01 -1.51065862e+00
4.12688822e-01 -1.97966635e-01 -4.58875209e-01 7.36338422e-02
-4.85553384e-01 4.48612303e-01 2.87792712e-01 4.52751249e-01
-7.87449777e-01 8.77698839e-01 1.63752437e+00 -3.62850577e-01
-3.14708948e-02 -6.55983910e-02 -8.81593168e-01 4.90515381e-01
9.50601220e-01 -3.66639197e-01 -4.81749266e-01 -5.95214427e-01
-2.18357798e-02 3.54288489e-01 6.44104362e-01 -1.19837320e+00
3.03310722e-01 -1.17276989e-01 5.67884564e-01 -4.44414943e-01
3.77846628e-01 -5.40966153e-01 -2.58311201e-02 2.02306718e-01
-5.26784778e-01 4.57926206e-02 -2.28681818e-01 4.58650678e-01
-5.38115680e-01 -9.57957581e-02 1.00102448e+00 1.70449056e-02
-5.68355381e-01 5.91547906e-01 1.82904080e-01 2.07541794e-01
5.89781582e-01 3.58000584e-02 -5.72568119e-01 -6.20498896e-01
-4.48378772e-01 1.50177568e-01 6.24882102e-01 3.52127969e-01
1.05652130e+00 -1.49971771e+00 -1.13062978e+00 9.13538784e-02
2.66901582e-01 -1.68202877e-01 4.28712904e-01 8.72946143e-01
-1.83528692e-01 1.32613361e-01 -3.62085968e-01 -4.86250669e-01
-9.54037488e-01 7.34971642e-01 4.71769542e-01 -1.83087751e-01
-5.20193219e-01 4.56657678e-01 5.23275495e-01 -4.17907573e-02
2.79357344e-01 2.27624420e-02 -2.58384734e-01 -2.47432575e-01
8.03531766e-01 3.06616694e-01 2.94597391e-02 -8.75914276e-01
1.61058065e-02 4.44392204e-01 -3.85759957e-02 -1.61579609e-01
1.21441770e+00 -4.66763496e-01 -3.25372331e-02 3.42266649e-01
1.27030373e+00 -1.07149296e-01 -1.51383424e+00 -5.18918872e-01
-1.84450969e-01 -9.53074872e-01 1.22925505e-01 -9.34176385e-01
-1.28588080e+00 9.43030417e-01 7.98438489e-01 -1.12607576e-01
1.59255421e+00 -8.99734870e-02 6.31754696e-01 1.16699770e-01
2.16459095e-01 -6.93215549e-01 3.95444870e-01 2.37006530e-01
1.33692396e+00 -1.57543361e+00 8.25282559e-02 -3.20491463e-01
-8.18813086e-01 8.20495069e-01 8.20628107e-01 -2.45738074e-01
4.91234511e-01 -1.27324998e-01 2.92572558e-01 -1.64793152e-02
-8.08492541e-01 -2.02328369e-01 5.49899757e-01 6.78216815e-01
4.55838352e-01 -1.64774507e-01 -1.55060470e-01 5.41401923e-01
-5.94781227e-02 -2.57820562e-02 6.40495300e-01 2.79234201e-01
-3.01257551e-01 -9.41586673e-01 -3.57729226e-01 4.04666752e-01
-4.55926389e-01 -3.77480686e-01 -1.41057130e-02 3.27321738e-01
1.01265185e-01 1.12685239e+00 -2.29012579e-01 -3.32928151e-01
3.84782910e-01 -3.74601722e-01 2.36883327e-01 -4.11578745e-01
-3.12674105e-01 1.57726213e-01 -1.44693941e-01 -9.15712893e-01
-4.52221185e-01 -5.19957542e-01 -8.20811152e-01 -1.83622122e-01
-1.38131484e-01 -1.21465929e-01 3.70365471e-01 5.55346727e-01
2.29478389e-01 5.66198468e-01 9.33802009e-01 -9.60630834e-01
-6.54893219e-01 -9.10473645e-01 -3.97621065e-01 5.48800766e-01
4.66106683e-01 -6.08159125e-01 -4.65410322e-01 8.24567825e-02] | [11.823880195617676, -1.8305304050445557] |
a24a484f-c912-4cd2-8b60-8a1d3a032efd | triplere-knowledge-graph-embeddings-via | 2209.08271 | null | https://arxiv.org/abs/2209.08271v1 | https://arxiv.org/pdf/2209.08271v1.pdf | TripleRE: Knowledge Graph Embeddings via Tripled Relation Vectors | Translation-based knowledge graph embedding has been one of the most important branches for knowledge representation learning since TransE came out. Although many translation-based approaches have achieved some progress in recent years, the performance was still unsatisfactory. This paper proposes a novel knowledge graph embedding method named TripleRE with two versions. The first version of TripleRE creatively divide the relationship vector into three parts. The second version takes advantage of the concept of residual and achieves better performance. In addition, attempts on using NodePiece to encode entities achieved promising results in reducing the parametric size, and solved the problems of scalability. Experiments show that our approach achieved state-of-the-art performance on the large-scale knowledge graph dataset, and competitive performance on other datasets. | ['Yafeng Deng', 'Hongzhu Li', 'Deng Lin', 'Huanyong Liu', 'Zhicong Luo', 'Long Yu'] | 2022-09-17 | null | null | null | null | ['knowledge-graph-embedding', 'knowledge-graph-embeddings', 'knowledge-graph-embeddings'] | ['graphs', 'graphs', 'methodology'] | [-3.34978253e-01 8.92674550e-02 -6.25259399e-01 2.89444383e-02
-4.04768258e-01 -3.88525009e-01 5.91067433e-01 1.58657327e-01
-4.61456597e-01 6.79359078e-01 1.89536303e-01 -2.27307752e-01
-3.58709127e-01 -1.05370080e+00 -3.60211968e-01 -5.13456762e-01
-1.70277193e-01 5.54276645e-01 4.37863231e-01 -4.53306377e-01
7.40690827e-02 2.94331670e-01 -1.10972500e+00 -9.05687269e-03
7.10723996e-01 6.99684680e-01 -2.46988058e-01 2.00644910e-01
-5.97758472e-01 7.77371585e-01 -3.53221059e-01 -8.90159070e-01
1.46705404e-01 -2.67414331e-01 -1.05903006e+00 -2.28327721e-01
7.99801424e-02 2.07525611e-01 -8.21567535e-01 9.15581703e-01
3.99184614e-01 9.47592333e-02 3.97015542e-01 -1.56878579e+00
-1.22982490e+00 9.22679901e-01 -5.42469680e-01 2.06666902e-01
4.71391380e-01 -5.03452718e-01 1.36462307e+00 -9.53375638e-01
7.50746846e-01 1.10804319e+00 8.55157733e-01 3.23936790e-01
-1.32797647e+00 -6.70096338e-01 5.10107875e-02 7.39928544e-01
-1.78701150e+00 -2.29264274e-02 9.70294654e-01 -2.95495152e-01
1.35081351e+00 -1.41826477e-02 8.56737733e-01 7.68958926e-01
7.07246810e-02 6.96124852e-01 1.07054615e+00 -5.92548728e-01
-1.42280534e-01 4.29662734e-01 3.76863241e-01 1.11531115e+00
5.45432329e-01 -8.24650750e-02 -3.30455929e-01 -3.40620697e-01
6.49327278e-01 -2.28160977e-01 -4.88592982e-01 -7.17485547e-01
-1.14238977e+00 1.21169972e+00 6.37155890e-01 7.32198238e-01
-8.42056349e-02 2.11108372e-01 4.04679894e-01 5.69552958e-01
5.36326885e-01 5.39825916e-01 -4.53932613e-01 -8.18476230e-02
-4.30412859e-01 -5.22208102e-02 9.41840768e-01 7.61109114e-01
6.43733919e-01 8.03102925e-02 3.97247411e-02 8.71699572e-01
-1.62582826e-02 6.42100489e-03 5.28588831e-01 -4.06006724e-01
4.68910068e-01 1.00199544e+00 -2.54928082e-01 -1.41560411e+00
-2.90686816e-01 -4.37991709e-01 -6.73350573e-01 -2.39382312e-01
1.33527786e-01 7.64098391e-02 -8.62677693e-01 1.51195955e+00
1.75795406e-01 2.93534994e-01 1.60778478e-01 6.02919638e-01
9.64154065e-01 6.26028121e-01 -1.32109031e-01 1.08275395e-02
1.16344249e+00 -1.15941334e+00 -8.12630832e-01 1.99174926e-01
7.73407698e-01 -4.35143977e-01 6.99253082e-01 9.29306373e-02
-7.72391140e-01 -2.90621310e-01 -9.94638205e-01 1.21927187e-02
-8.37621689e-01 -8.13765302e-02 1.23817015e+00 8.14190626e-01
-1.19851923e+00 4.08417583e-01 -7.09500372e-01 -5.72606862e-01
3.87145668e-01 4.25527811e-01 -8.10871422e-01 -1.67370304e-01
-1.40481281e+00 1.03942740e+00 8.43302369e-01 -9.98490974e-02
-2.12138146e-01 -5.06044388e-01 -9.97938156e-01 2.63201267e-01
7.33333051e-01 -8.31303298e-01 5.67611217e-01 -3.86091411e-01
-1.31038976e+00 6.06559575e-01 7.14314431e-02 -2.84478426e-01
1.56347558e-01 -6.57814518e-02 -6.90017879e-01 -3.90302092e-02
-2.07229406e-01 4.45192039e-01 5.53718090e-01 -1.05122566e+00
-3.05841118e-01 -2.88096994e-01 2.72155046e-01 -6.10550381e-02
-9.90366876e-01 -8.25574696e-02 -7.48828888e-01 -6.59219921e-01
8.71395990e-02 -1.00569451e+00 -8.93303677e-02 -2.49468014e-01
-1.61902845e-01 -6.29698217e-01 7.59760201e-01 -5.35590470e-01
1.56565833e+00 -1.96862698e+00 5.78813672e-01 2.17902079e-01
3.41593117e-01 5.06940246e-01 -2.03667104e-01 8.98687124e-01
-3.23620886e-01 3.52605075e-01 -1.84302181e-02 4.70310822e-02
8.28990433e-03 3.61408263e-01 -2.28458524e-01 2.40964368e-01
1.48975616e-02 1.27166820e+00 -1.00255895e+00 -5.49976051e-01
-8.32421854e-02 7.91707397e-01 -6.13353610e-01 -1.53150961e-01
2.15510707e-02 -1.86140537e-01 -5.39260626e-01 5.86726785e-01
2.50678599e-01 -3.81221205e-01 5.71880817e-01 -4.83278990e-01
1.84088275e-01 1.01506062e-01 -1.17143524e+00 1.59363055e+00
-2.18732625e-01 6.26830637e-01 -4.81808603e-01 -1.05748367e+00
8.26547980e-01 3.87716800e-01 6.22328222e-01 -5.07481158e-01
1.23224474e-01 2.70900317e-02 2.05230247e-03 -3.83227587e-01
8.46854210e-01 -1.07356608e-01 6.39646351e-02 1.37791276e-01
6.64104894e-02 5.36379144e-02 1.10107400e-01 4.10059303e-01
1.16134012e+00 2.58835286e-01 6.02261364e-01 5.90253286e-02
4.81609821e-01 1.26535326e-01 5.97655773e-01 1.85299754e-01
-3.14510502e-02 1.65727049e-01 5.61651289e-01 -4.42651361e-01
-5.95456600e-01 -9.38001633e-01 1.45345524e-01 6.97625697e-01
1.46030799e-01 -1.10320723e+00 -2.57432938e-01 -1.02046657e+00
3.22802246e-01 6.74670815e-01 -7.25830495e-01 -3.59017044e-01
-5.50562501e-01 -6.97101116e-01 7.09098876e-01 9.05900538e-01
4.66650844e-01 -7.68170059e-01 6.35755807e-02 2.60348350e-01
-2.07268879e-01 -1.02893150e+00 -3.75536680e-01 -1.20174676e-01
-7.86887288e-01 -1.14971960e+00 -4.82537538e-01 -1.05140615e+00
5.97770333e-01 4.84795630e-01 9.71395135e-01 1.83307022e-01
-3.82582635e-01 5.03879786e-01 -6.64283752e-01 -1.09554783e-01
4.17493880e-02 2.12009102e-01 -1.12926252e-01 -2.28274867e-01
4.63408709e-01 -5.75519979e-01 -1.02177307e-01 1.82341397e-01
-9.54375625e-01 -4.31053400e-01 5.55615366e-01 1.09031856e+00
5.77452898e-01 4.32890326e-01 6.77830756e-01 -8.55339408e-01
8.20316315e-01 -2.37749413e-01 -3.94832790e-01 4.28407490e-01
-1.13082862e+00 3.42254728e-01 4.74503577e-01 -2.24830583e-01
-6.36867166e-01 -2.50482291e-01 6.44472893e-03 -5.72645366e-01
4.99032319e-01 9.84187663e-01 8.12700316e-02 -4.52563196e-01
3.60205144e-01 2.31969520e-01 -1.93198174e-01 -5.26044250e-01
6.52168989e-01 5.21047711e-01 1.17173225e-01 -5.09891450e-01
8.99610937e-01 1.50340661e-01 -8.12927410e-02 -9.01352048e-01
-6.31897688e-01 -5.30418873e-01 -4.45746213e-01 2.91290879e-01
7.16301739e-01 -7.28591859e-01 -5.32701910e-01 1.04001209e-01
-9.52009976e-01 2.55507231e-01 -3.27699721e-01 5.05313575e-01
-1.36261865e-01 6.46763980e-01 -5.10427535e-01 -3.38258386e-01
-2.89738119e-01 -7.92999446e-01 3.48798722e-01 3.59316282e-02
1.31093681e-01 -1.32967675e+00 4.11802649e-01 3.70432913e-01
5.35134435e-01 1.90836072e-01 1.25502253e+00 -7.02419341e-01
-5.54286838e-01 -4.59037632e-01 -3.31219852e-01 2.69634664e-01
2.28842303e-01 -1.55521646e-01 -4.56660837e-01 -4.57096338e-01
-6.36253297e-01 -1.79875359e-01 1.11727476e+00 -2.49740198e-01
1.09506428e+00 -8.15725997e-02 -7.25417376e-01 6.39607787e-01
1.69323409e+00 2.65915915e-02 7.06297338e-01 4.82921511e-01
9.21747088e-01 1.41719297e-01 4.19765294e-01 -2.90204678e-03
7.95330286e-01 1.03742361e+00 2.36975417e-01 1.27042070e-01
-3.29777092e-01 -4.18802619e-01 3.24052423e-01 1.26987135e+00
-5.22426069e-01 -2.98744112e-01 -9.08249021e-01 8.54703784e-01
-1.94907844e+00 -1.12370050e+00 2.27696020e-02 1.83683407e+00
6.47954345e-01 4.73818816e-02 1.68421358e-01 1.57695234e-01
4.04326975e-01 3.31316411e-01 -1.26420632e-01 -5.05357265e-01
-2.04900444e-01 3.48819464e-01 5.04272342e-01 3.22630078e-01
-9.16437805e-01 1.32728612e+00 6.62585115e+00 6.26927137e-01
-7.94479072e-01 2.36929059e-01 -1.69120997e-01 4.06252503e-01
-5.44176638e-01 2.24825755e-01 -6.63390815e-01 5.33789396e-02
6.29887998e-01 -4.92822349e-01 3.16098094e-01 7.59500742e-01
-6.42966092e-01 2.91554898e-01 -8.98158193e-01 1.05482638e+00
4.06948090e-01 -1.32995439e+00 2.46457592e-01 4.57039885e-02
7.02394485e-01 -5.65225594e-02 -1.74265191e-01 7.15273261e-01
2.78550774e-01 -1.02540529e+00 5.48192821e-02 4.59940463e-01
7.67435253e-01 -9.17371511e-01 9.45566356e-01 -4.38424433e-03
-1.54294658e+00 -6.16255812e-02 -5.22172630e-01 1.33758569e-02
1.41319439e-01 4.85950887e-01 -8.82030249e-01 1.16104937e+00
6.01578951e-01 9.25329566e-01 -7.67746449e-01 1.10444832e+00
-4.82402027e-01 6.20423198e-01 -6.40643016e-02 -1.77158102e-01
1.31731987e-01 -3.97534102e-01 5.07685304e-01 1.24172604e+00
8.58337656e-02 -4.25325260e-02 2.68510789e-01 6.00140095e-01
-3.59938890e-01 1.72922328e-01 -7.83676863e-01 -5.53552628e-01
4.08208907e-01 1.18142605e+00 -4.89760250e-01 -1.79245308e-01
-6.84899747e-01 1.07837689e+00 8.16495955e-01 2.58259982e-01
-8.98775220e-01 -8.07044208e-01 5.69018900e-01 -1.48573339e-01
7.38221288e-01 -3.82561892e-01 2.24726260e-01 -1.46234298e+00
1.54726982e-01 -6.08497441e-01 6.82020962e-01 -4.55905825e-01
-1.35475755e+00 6.35700226e-01 1.34960845e-01 -8.60144734e-01
7.80674489e-03 -6.18185222e-01 -1.55743167e-01 6.15898669e-01
-1.66881859e+00 -1.31410980e+00 -1.36495128e-01 5.63832760e-01
4.46263961e-02 -2.82487273e-01 1.30063164e+00 5.62263846e-01
-7.16347933e-01 1.02592313e+00 1.71926528e-01 4.21587646e-01
5.55772185e-01 -1.22819412e+00 2.68700361e-01 5.49722314e-01
5.42730153e-01 6.37873948e-01 2.98269153e-01 -5.26716292e-01
-1.71261692e+00 -8.89108539e-01 1.21691871e+00 -4.17066723e-01
9.62605655e-01 -1.18815444e-01 -9.75440323e-01 1.05759883e+00
2.59963691e-01 6.04911447e-02 7.84000039e-01 4.79220808e-01
-8.01962316e-01 -9.87545103e-02 -9.16354835e-01 4.70099658e-01
1.17304564e+00 -5.90960026e-01 -1.17497540e+00 1.30574644e-01
8.25895071e-01 -1.70047715e-01 -1.29959333e+00 4.79819804e-01
5.95300913e-01 -6.19687259e-01 1.08419704e+00 -8.35670292e-01
1.53292999e-01 -3.53922516e-01 -1.29649699e-01 -1.58737612e+00
-7.20322251e-01 -4.35483515e-01 -5.19489765e-01 1.29339111e+00
4.15123105e-01 -9.76851225e-01 8.62838268e-01 2.47914091e-01
-1.10868299e-02 -1.05351245e+00 -7.45119512e-01 -1.18559599e+00
3.96203548e-02 5.75665906e-02 5.00488579e-01 1.45713890e+00
2.86361068e-01 6.34344935e-01 -3.98402750e-01 -5.76408841e-02
4.25725579e-01 4.06607956e-01 6.44416869e-01 -1.26486790e+00
-2.66422480e-01 -4.60794777e-01 -1.05536723e+00 -7.71584034e-01
3.93858790e-01 -1.54684532e+00 -7.43382156e-01 -2.10227466e+00
4.02285606e-01 -3.88327718e-01 -6.82832301e-01 9.75664675e-01
-3.62198830e-01 2.64291435e-01 2.07684070e-01 1.39402160e-02
-4.83234316e-01 7.27820277e-01 1.02158403e+00 -3.55542898e-01
-1.41431734e-01 -4.68621761e-01 -8.10695171e-01 3.83766085e-01
8.43362927e-01 -4.53891486e-01 -5.87115169e-01 -4.10887361e-01
4.02069986e-01 -2.66806126e-01 1.90612823e-01 -6.54131055e-01
2.74079949e-01 -1.25926360e-02 -1.15268305e-02 -5.12872159e-01
3.82732570e-01 -9.03981388e-01 4.06422019e-01 3.34034532e-01
5.73190153e-02 2.76989400e-01 1.84878081e-01 8.53557229e-01
-5.11621237e-01 5.52233905e-02 3.97575378e-01 9.82580259e-02
-1.13144410e+00 3.72609228e-01 2.61295706e-01 5.69575988e-02
1.06739044e+00 -2.69900352e-01 -5.29825270e-01 -6.85553104e-02
-4.92319882e-01 1.96655482e-01 3.92902404e-01 6.85272813e-01
8.71185482e-01 -1.47363102e+00 -6.11509025e-01 -4.29507717e-02
4.32736278e-01 -5.78513503e-01 -2.58568764e-01 8.98781478e-01
-2.67346025e-01 6.71831250e-01 -4.77365665e-02 -1.65655762e-01
-1.20491219e+00 7.67744541e-01 8.13274086e-02 -6.09742045e-01
-9.12891328e-01 8.73182297e-01 -3.05548519e-01 -4.38925236e-01
1.44195005e-01 1.14691548e-01 -4.43646044e-01 1.30550489e-01
2.97839224e-01 6.40932441e-01 3.64063866e-02 -6.93053365e-01
-6.20400369e-01 8.03796470e-01 -3.36842328e-01 2.18321517e-01
1.49510849e+00 2.56025225e-01 -3.47483575e-01 3.77936095e-01
1.37206805e+00 1.72631845e-01 -3.49978000e-01 -4.72097903e-01
7.39835650e-02 -5.80948412e-01 2.70112991e-01 -8.11227143e-01
-1.31170249e+00 5.04641235e-01 3.17408323e-01 1.72208250e-01
9.10803795e-01 -2.65866648e-02 9.43910420e-01 6.63107157e-01
8.17911088e-01 -8.58820021e-01 -6.55108178e-03 6.72017097e-01
6.06426120e-01 -1.08207047e+00 3.61745656e-01 -6.58977449e-01
-5.36987305e-01 1.01199257e+00 4.41165149e-01 7.37299472e-02
8.59521806e-01 -2.29112178e-01 -1.78334773e-01 -4.77734506e-01
-6.29063010e-01 -2.78263003e-01 5.28712809e-01 6.06806874e-01
5.28314173e-01 2.34733909e-01 -7.73109794e-01 6.35243177e-01
-4.11956795e-02 2.87734903e-02 3.16644073e-01 1.00933719e+00
-2.75591463e-01 -1.56372666e+00 9.78339836e-02 4.27443206e-01
-4.15886521e-01 -1.31567538e-01 -5.97737908e-01 1.20057607e+00
7.36909220e-04 7.47979164e-01 -4.77538466e-01 -7.86261141e-01
6.24516249e-01 2.92528152e-01 7.24503696e-01 -5.29600322e-01
-6.08009994e-01 -5.26515841e-01 3.39921951e-01 -6.46367729e-01
-4.90452290e-01 -2.52545327e-01 -1.29091048e+00 -4.72925514e-01
-6.97033226e-01 5.46948850e-01 5.18735588e-01 5.29745579e-01
5.75190246e-01 5.65559864e-01 4.52852517e-01 -4.13760662e-01
-4.82851446e-01 -6.84330642e-01 -7.44842410e-01 3.38724792e-01
-1.45836368e-01 -9.61312294e-01 -2.99052119e-01 -2.73697197e-01] | [8.735809326171875, 7.849104404449463] |
8ca03873-8c13-4777-89e7-1d8ed585a35f | motion-puzzle-arbitrary-motion-style-transfer | 2202.05274 | null | https://arxiv.org/abs/2202.05274v2 | https://arxiv.org/pdf/2202.05274v2.pdf | Motion Puzzle: Arbitrary Motion Style Transfer by Body Part | This paper presents Motion Puzzle, a novel motion style transfer network that advances the state-of-the-art in several important respects. The Motion Puzzle is the first that can control the motion style of individual body parts, allowing for local style editing and significantly increasing the range of stylized motions. Designed to keep the human's kinematic structure, our framework extracts style features from multiple style motions for different body parts and transfers them locally to the target body parts. Another major advantage is that it can transfer both global and local traits of motion style by integrating the adaptive instance normalization and attention modules while keeping the skeleton topology. Thus, it can capture styles exhibited by dynamic movements, such as flapping and staggering, significantly better than previous work. In addition, our framework allows for arbitrary motion style transfer without datasets with style labeling or motion pairing, making many publicly available motion datasets available for training. Our framework can be easily integrated with motion generation frameworks to create many applications, such as real-time motion transfer. We demonstrate the advantages of our framework with a number of examples and comparisons with previous work. | ['Sung-Hee Lee', 'Soomin Park', 'Deok-Kyeong Jang'] | 2022-02-10 | null | null | null | null | ['motion-style-transfer'] | ['computer-code'] | [-5.45529127e-02 -1.46425650e-01 -3.01100850e-01 -3.42764631e-02
-1.49751693e-01 -8.05413902e-01 5.59366465e-01 -6.62533164e-01
-3.02269131e-01 6.87179148e-01 3.75502586e-01 8.89964178e-02
2.82227963e-01 -8.98042023e-01 -5.98187625e-01 -6.49061382e-01
2.27869779e-01 4.62644637e-01 4.06846344e-01 -4.96417701e-01
-1.64209213e-02 6.18675411e-01 -1.14425778e+00 2.19824165e-01
6.64242983e-01 6.63410425e-01 3.12202245e-01 7.95744121e-01
-9.63074118e-02 5.74087322e-01 -6.91191792e-01 -3.67075264e-01
1.88406631e-01 -6.93978667e-01 -8.43428493e-01 -2.72114594e-02
5.33572376e-01 -4.66508955e-01 -6.10053957e-01 6.64153159e-01
6.94191396e-01 3.30782652e-01 6.41567528e-01 -1.30564070e+00
-8.73804450e-01 2.96701729e-01 -5.75078547e-01 -1.96835190e-01
4.09939885e-01 5.16788185e-01 8.70305121e-01 -6.01392448e-01
1.06692827e+00 1.54011214e+00 6.61138058e-01 1.26633203e+00
-1.13439119e+00 -6.14111900e-01 8.01220983e-02 6.83586597e-02
-7.36924171e-01 -1.62682146e-01 9.73318696e-01 -2.99501002e-01
6.34102464e-01 2.01839998e-01 1.01408565e+00 1.71500540e+00
2.64690340e-01 1.15838182e+00 5.33627152e-01 -6.44204840e-02
1.40376568e-01 -7.09229887e-01 -4.13525254e-01 6.56449080e-01
-1.20196104e-01 -7.97322765e-02 -5.50854623e-01 1.06032686e-02
1.49272335e+00 -2.35682011e-01 -2.50315428e-01 -6.01279199e-01
-1.72790599e+00 4.63852286e-01 4.40286964e-01 2.15166792e-01
-1.51865371e-02 6.64381087e-01 5.09386718e-01 1.55423313e-01
1.37178913e-01 4.46593404e-01 -5.20607889e-01 -4.65391546e-01
-7.54388094e-01 6.43861115e-01 6.32340848e-01 1.25158310e+00
5.49282134e-01 3.13035488e-01 -5.64334631e-01 7.00492680e-01
-1.72714405e-02 5.41684389e-01 6.69881880e-01 -1.52152419e+00
5.50123155e-01 3.95681977e-01 7.52142519e-02 -9.66071010e-01
-4.92290437e-01 1.44005001e-01 -1.06668341e+00 3.73753786e-01
5.75210214e-01 -4.41081554e-01 -8.54470313e-01 2.07905602e+00
3.02972525e-01 8.04827437e-02 -2.87635356e-01 9.03701365e-01
8.90558898e-01 5.92088580e-01 1.83050796e-01 4.15027916e-01
1.26180053e+00 -1.35850894e+00 -6.64581180e-01 -2.37151191e-01
5.69452763e-01 -6.67356491e-01 1.45891452e+00 4.88503762e-02
-1.21406364e+00 -7.86247432e-01 -7.70833194e-01 -4.26289111e-01
-5.39040864e-02 8.32132250e-02 7.92208552e-01 2.98305303e-01
-1.09068918e+00 1.10911524e+00 -1.11802411e+00 -6.12016022e-01
4.33535188e-01 2.79625237e-01 -5.07629991e-01 3.26731026e-01
-9.74493921e-01 5.89726031e-01 9.38603878e-02 -1.35161817e-01
-4.48904693e-01 -8.65247309e-01 -1.14012599e+00 -1.50341034e-01
-4.33910638e-02 -1.54675257e+00 1.28707528e+00 -1.04641879e+00
-2.07774854e+00 7.23001361e-01 -5.07767908e-02 1.68271899e-01
9.77021635e-01 -4.98914570e-01 -1.28568068e-01 1.62437126e-01
1.58276051e-01 1.22481012e+00 7.99024403e-01 -7.78617918e-01
-3.71876061e-01 -6.16082624e-02 5.91802374e-02 2.78428853e-01
-2.53633142e-01 -1.16563365e-01 -9.16123271e-01 -1.49849474e+00
-2.11683810e-01 -1.14725578e+00 -2.12946996e-01 6.05044663e-01
-2.97038436e-01 1.81870591e-02 1.20631170e+00 -4.97972429e-01
1.05680323e+00 -1.98611009e+00 1.02062249e+00 -2.22732678e-01
2.45383810e-02 1.89137712e-01 -4.66217101e-01 3.62803131e-01
5.24702063e-03 1.04084037e-01 -3.83479893e-01 -4.54805255e-01
-8.87417346e-02 4.04879570e-01 -1.11518919e-01 9.08613652e-02
3.30148607e-01 1.44032991e+00 -1.04352355e+00 -4.68276322e-01
8.74208733e-02 3.08637649e-01 -8.52387369e-01 3.24051559e-01
-2.49359027e-01 1.21066391e+00 -4.84491646e-01 5.69869637e-01
3.31807882e-01 -6.27080202e-02 8.45407024e-02 -1.60692573e-01
2.71075130e-01 -5.56523539e-03 -1.13911986e+00 2.43559647e+00
-4.87245589e-01 6.32912636e-01 8.86748210e-02 -3.39941591e-01
7.04811037e-01 1.85681969e-01 6.14381194e-01 -3.35044831e-01
1.39906153e-01 -8.26933607e-02 -1.57379806e-01 -4.64649439e-01
5.57215869e-01 -2.18146127e-02 -2.84321815e-01 6.41613603e-01
1.57178447e-01 -4.08424526e-01 9.26183090e-02 -4.78799567e-02
9.12622690e-01 8.26681852e-01 1.53706625e-01 -2.15828136e-01
3.89746219e-01 -1.41365469e-01 8.77368152e-01 2.45053679e-01
-2.11504236e-01 9.94772375e-01 4.20335561e-01 -6.15101933e-01
-1.19570088e+00 -1.28417337e+00 3.97343338e-01 1.17278159e+00
3.07501405e-01 -3.76035184e-01 -9.47132945e-01 -6.73608720e-01
8.78521577e-02 2.53579110e-01 -8.36246729e-01 -1.07724510e-01
-1.10795939e+00 -3.05835426e-01 7.75834978e-01 1.11177623e+00
6.51982486e-01 -1.56475830e+00 -6.12001836e-01 2.34671295e-01
-3.00413609e-01 -9.13786113e-01 -1.09324455e+00 -5.14016807e-01
-1.12197590e+00 -8.41729581e-01 -1.31413603e+00 -7.74921477e-01
4.18623149e-01 4.32113670e-02 1.24957108e+00 2.01988235e-01
-2.55787134e-01 3.35545659e-01 -2.86784649e-01 -4.74000629e-03
-4.29864496e-01 4.61582363e-01 9.33902189e-02 -1.86170325e-01
-2.43356496e-01 -9.03536677e-01 -8.30780327e-01 4.55480993e-01
-1.01127064e+00 2.68960863e-01 2.11299375e-01 9.31686401e-01
4.32006985e-01 -5.79984963e-01 3.96504849e-01 -7.50534594e-01
4.75453377e-01 -1.88806117e-01 -6.81525990e-02 -1.05999568e-02
6.27436265e-02 1.36690706e-01 5.84550619e-01 -7.58637249e-01
-1.13799655e+00 4.78437766e-02 -1.99933469e-01 -4.40665364e-01
-3.16293329e-01 -1.40086561e-01 -5.44325113e-01 -5.63011505e-03
5.24019718e-01 2.94908397e-02 2.90735140e-02 -6.76214814e-01
8.36350977e-01 1.33327171e-02 9.70668972e-01 -9.95896220e-01
8.91078770e-01 6.62919164e-01 1.43333882e-01 -6.90723300e-01
-3.95925999e-01 -2.59313006e-02 -1.19895458e+00 -3.87179144e-02
1.05244303e+00 -6.15443408e-01 -6.32233083e-01 9.07918513e-01
-1.22833467e+00 -8.49174142e-01 -4.24459845e-01 5.21175638e-02
-1.05995524e+00 6.58535838e-01 -1.15732098e+00 -1.30419433e-01
-3.88078809e-01 -1.07253790e+00 1.22436333e+00 2.43795797e-01
-9.44905460e-01 -1.14319932e+00 1.56625226e-01 -1.87793240e-01
3.04157227e-01 6.25850856e-01 8.63681912e-01 3.37364703e-01
-1.79229185e-01 1.84863776e-01 2.42045119e-01 -6.37797415e-02
4.26746130e-01 2.76754946e-01 -6.45337999e-01 -3.34873408e-01
-5.26597798e-01 -2.49759853e-01 6.97897792e-01 2.56779969e-01
1.19502163e+00 -2.54424006e-01 -2.86848426e-01 1.21818078e+00
8.35130095e-01 9.98831913e-03 7.92616785e-01 5.13362229e-01
1.18759882e+00 5.66262245e-01 4.50224668e-01 2.72033215e-01
2.62065381e-01 9.79724467e-01 1.77475348e-01 -1.57641545e-01
-4.90605980e-01 -5.24366200e-01 4.68964040e-01 7.78527141e-01
-4.01115239e-01 -8.84015635e-02 -5.08968771e-01 4.59384888e-01
-1.93619871e+00 -1.08567166e+00 3.64779420e-02 1.76154208e+00
8.72953415e-01 -1.10040650e-01 5.73068798e-01 -6.30908236e-02
4.70654964e-01 3.14039767e-01 -6.74857914e-01 -3.68225247e-01
-1.24503955e-01 3.72344673e-01 1.26795560e-01 2.44151935e-01
-1.20482397e+00 1.30908644e+00 6.77951241e+00 7.13255048e-01
-1.14080238e+00 -1.09705985e-01 3.74031812e-01 -3.25782686e-01
-3.79497141e-01 -3.36923093e-01 -4.37781036e-01 5.29191971e-01
2.41134301e-01 -7.42748454e-02 3.77950013e-01 8.89798164e-01
2.56870002e-01 3.70394170e-01 -1.29037988e+00 9.80633616e-01
-2.93001056e-01 -1.40310836e+00 4.69093412e-01 -1.94048122e-01
8.96127939e-01 -3.69258076e-01 1.69874623e-01 9.00599584e-02
3.91415358e-01 -9.58932936e-01 1.03090429e+00 4.71203029e-01
1.10278058e+00 -7.24674404e-01 2.53190219e-01 2.19540358e-01
-1.33568740e+00 1.75387517e-01 -2.78168619e-01 -1.02934793e-01
4.00676429e-01 6.46580979e-02 2.87354998e-02 6.37532294e-01
7.41054356e-01 1.00817025e+00 -4.74647790e-01 8.21636021e-01
-4.06637490e-01 2.83904672e-01 -1.15571320e-01 2.30487153e-01
1.40243903e-01 -4.15444851e-01 6.50821984e-01 1.25619781e+00
6.06619120e-01 -7.17093498e-02 -7.41759539e-02 1.02642477e+00
-4.36422341e-02 8.20771884e-03 -7.25095451e-01 2.08003864e-01
4.04019684e-01 1.29096341e+00 -6.69715941e-01 -3.12073886e-01
-1.85021564e-01 1.68922591e+00 3.58405083e-01 4.14512902e-01
-9.09746408e-01 -4.08312827e-01 1.09233010e+00 -1.26723304e-01
3.11197817e-01 -5.98476350e-01 -4.95285869e-01 -1.38466692e+00
-1.10005386e-01 -8.51449907e-01 2.47160703e-01 -7.68610835e-01
-1.23260164e+00 5.32370269e-01 -1.50604248e-01 -1.44742787e+00
-4.54533994e-01 -7.52654195e-01 -1.07848382e+00 8.72603416e-01
-6.74074471e-01 -1.55153239e+00 -4.58249032e-01 5.22804141e-01
6.86019301e-01 -2.51360387e-02 7.55899906e-01 2.35009953e-01
-5.67783475e-01 7.65808403e-01 -3.32871616e-01 3.96389663e-01
1.12301815e+00 -1.33372521e+00 1.15354991e+00 6.30975187e-01
4.20246013e-02 5.41831493e-01 5.00716150e-01 -6.65242970e-01
-1.26787007e+00 -1.17306662e+00 4.33796287e-01 -7.54650474e-01
5.00554383e-01 -3.41936171e-01 -8.64005685e-01 7.93022513e-01
1.74862325e-01 -1.79423597e-02 4.34708744e-01 -2.57463425e-01
-2.65011430e-01 1.24008968e-01 -8.92655313e-01 1.21245742e+00
1.71622181e+00 -1.68013260e-01 -6.25917435e-01 -1.15186483e-01
5.61726213e-01 -8.18819225e-01 -8.66745710e-01 3.72296751e-01
7.47156203e-01 -8.46973479e-01 1.13148081e+00 -1.04064691e+00
8.64655316e-01 -3.44232738e-01 2.59289324e-01 -1.61286831e+00
-7.84375191e-01 -9.23610151e-01 -3.23704064e-01 1.34380329e+00
1.44646689e-01 -1.17911287e-01 9.94820654e-01 5.73341548e-01
-8.27481002e-02 -5.63041508e-01 -6.90289080e-01 -8.01270783e-01
5.47531307e-01 -2.62765795e-01 7.90101767e-01 1.02288890e+00
-1.97073102e-01 1.54823273e-01 -6.86343074e-01 -3.07097673e-01
3.07368994e-01 1.97857276e-01 1.24349868e+00 -8.95869017e-01
-6.83400393e-01 -6.86570227e-01 -2.94597924e-01 -1.43016613e+00
2.88097203e-01 -8.68362308e-01 -2.26567522e-01 -1.42175508e+00
-1.49980068e-01 -2.14672402e-01 1.49302885e-01 6.38600826e-01
-3.84014398e-01 4.01282996e-01 5.75305581e-01 2.32058838e-01
-1.78110316e-01 9.03564572e-01 2.21105981e+00 -1.32299185e-01
-3.47186238e-01 3.78464162e-02 -5.27910531e-01 1.02008152e+00
7.07640231e-01 -1.04209900e-01 -3.10455322e-01 -7.56730616e-01
-1.32357076e-01 1.19049892e-01 3.32089275e-01 -1.09374404e+00
-6.64610714e-02 -3.36381435e-01 7.08774745e-01 -3.47623557e-01
2.16523588e-01 -4.42916483e-01 3.57755363e-01 5.08778512e-01
-2.35392109e-01 4.52818245e-01 4.24901664e-01 6.01823628e-01
6.64053336e-02 1.88151747e-01 9.20660615e-01 -2.88876444e-01
-8.99901867e-01 5.12501717e-01 -3.42365921e-01 1.07145011e-01
1.04557025e+00 -2.31860638e-01 -6.90444112e-02 -5.60033143e-01
-9.25181329e-01 1.51776329e-01 1.02500343e+00 8.04433227e-01
2.38572583e-01 -1.94637215e+00 -4.81525719e-01 1.72144428e-01
4.27002609e-02 2.15123668e-01 2.15477958e-01 4.09114927e-01
-9.24334407e-01 -2.73440741e-02 -8.44780743e-01 -6.06114447e-01
-1.02560437e+00 5.90511441e-01 3.07231754e-01 -4.65771630e-02
-1.05137336e+00 6.03343248e-01 5.36436975e-01 -5.80194533e-01
-1.36299804e-01 -5.44576228e-01 2.33498178e-02 -2.74767578e-01
5.63402116e-01 5.86761296e-01 -4.29961413e-01 -5.81344485e-01
-1.42969832e-01 1.03722394e+00 4.21876132e-01 -2.54015535e-01
1.06839895e+00 -9.79026929e-02 -1.15625173e-01 4.10773188e-01
9.11292136e-01 9.53828767e-02 -1.79875267e+00 1.62361473e-01
-1.83573887e-01 -4.01217014e-01 -6.06830835e-01 -5.25425553e-01
-1.35441875e+00 9.47497487e-01 7.87602514e-02 -4.66014057e-01
9.92997110e-01 -1.48792803e-01 1.19547963e+00 1.67340711e-01
5.45816720e-01 -1.05681133e+00 3.43836665e-01 6.06971383e-01
1.17581201e+00 -7.80065715e-01 -4.12296057e-01 -4.41486597e-01
-8.12268615e-01 1.19138885e+00 9.22628999e-01 -3.58549744e-01
3.61924529e-01 3.32078785e-01 3.14358890e-01 2.25589782e-01
-4.25744951e-01 1.61507741e-01 6.17709696e-01 9.24788117e-01
6.19378448e-01 -8.74476787e-03 -2.79458046e-01 5.67706883e-01
-3.88646305e-01 -1.88023299e-02 2.74178624e-01 7.54687726e-01
-2.56276857e-02 -1.62344813e+00 -2.55151540e-01 -9.51575302e-03
-3.40692192e-01 2.05854371e-01 -6.53564572e-01 9.92614269e-01
5.77192493e-02 3.93865615e-01 1.13542214e-01 -4.33601320e-01
5.28295398e-01 1.62710138e-02 6.98463500e-01 -5.91482699e-01
-5.22915483e-01 6.85435906e-02 -1.10889815e-01 -9.90532041e-01
-2.30641544e-01 -5.35820782e-01 -1.18108332e+00 -5.61382890e-01
4.98239130e-01 -4.07372445e-01 -3.63366716e-02 5.69132209e-01
5.88896334e-01 6.48665965e-01 1.79757476e-01 -1.57523692e+00
-2.40383074e-01 -8.73879492e-01 -6.21306837e-01 9.92047548e-01
1.39380231e-01 -8.01168382e-01 1.47651851e-01 4.11518842e-01] | [10.762748718261719, -0.6841039061546326] |
69da6d59-b6b0-4647-b643-6f656c93f0f2 | gradient-based-learning-applied-to-document | null | null | https://ieeexplore.ieee.org/document/726791 | https://ieeexplore.ieee.org/document/726791 | Gradient-based learning applied to document recognition | Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed to deal with the variability of 2D shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation recognition, and language modeling. A new learning paradigm, called graph transformer networks (GTN), allows such multimodule systems to be trained globally using gradient-based methods so as to minimize an overall performance measure. Two systems for online handwriting recognition are described. Experiments demonstrate the advantage of global training, and the flexibility of graph transformer networks. A graph transformer network for reading a bank cheque is also described. It uses convolutional neural network character recognizers combined with global training techniques to provide record accuracy on business and personal cheques. It is deployed commercially and reads several million cheques per day. | ['P. Haffner', 'Y. Bengio', 'L. Bottou', 'Y. LeCun'] | 1998-11-01 | null | null | null | proceedings-of-the-ieee-1998-11 | ['handwriting-recognition', 'handwritten-digit-recognition'] | ['computer-vision', 'computer-vision'] | [ 1.45094350e-01 -3.56983274e-01 -2.45059267e-01 -5.80209494e-01
-1.43023342e-01 -4.80689913e-01 3.33108723e-01 -1.56433195e-01
-3.97871941e-01 4.59162265e-01 -4.70262468e-01 -8.08381319e-01
-1.46772295e-01 -9.95787323e-01 -4.22448218e-01 -4.68147606e-01
1.21111432e-02 6.92595959e-01 3.10012847e-01 -3.10529947e-01
6.89967990e-01 1.29709208e+00 -1.07881618e+00 5.31485498e-01
5.28638422e-01 1.24236035e+00 8.45261365e-02 1.18249929e+00
-5.70427418e-01 1.21408176e+00 -8.43738556e-01 -3.92506212e-01
2.63936877e-01 -1.91386923e-01 -5.34336269e-01 3.80072296e-01
7.37778127e-01 -5.16604781e-01 -4.63406175e-01 6.25955284e-01
5.38907707e-01 -3.14068049e-02 8.37682903e-01 -7.69649208e-01
-6.49928808e-01 4.56546843e-01 -1.81977421e-01 2.41226092e-01
8.06203932e-02 -4.45303768e-02 5.95483065e-01 -9.49647903e-01
3.22458178e-01 1.09462607e+00 1.11912024e+00 5.01211464e-01
-9.30945098e-01 -2.70221323e-01 -4.79993299e-02 2.11281464e-01
-9.52335179e-01 -1.63479030e-01 9.42110896e-01 -5.54018319e-01
1.63780606e+00 2.43036970e-01 5.72638333e-01 5.69870293e-01
5.25005102e-01 1.15530837e+00 8.72185111e-01 -8.30799103e-01
1.64493993e-01 9.49218050e-02 6.52825296e-01 1.23007786e+00
1.26366362e-01 -2.26255488e-02 -4.85731632e-01 -1.15112355e-02
1.03217924e+00 2.91201156e-02 -1.03432782e-01 -2.38740414e-01
-7.50277579e-01 8.33194673e-01 3.99350554e-01 3.70836854e-01
-1.58469453e-01 9.68063995e-02 3.56394678e-01 4.41288054e-01
1.16811596e-01 6.63472056e-01 -3.19136679e-01 -9.35799628e-02
-1.16718471e+00 2.67903972e-02 1.29726434e+00 9.69545305e-01
7.09740937e-01 6.97976708e-01 -2.51815207e-02 1.16346133e+00
2.85249293e-01 5.17752111e-01 6.36268497e-01 -3.30426931e-01
5.62643409e-01 8.86928678e-01 -2.39697427e-01 -1.24216557e+00
-5.86863041e-01 -3.09876829e-01 -8.77918720e-01 7.23236084e-01
5.43760419e-01 -4.03780550e-01 -1.41094601e+00 5.48785329e-01
-3.46398085e-01 -5.51353574e-01 -9.47704017e-02 7.11358488e-01
5.31372905e-01 7.24667013e-01 -4.53294933e-01 3.27781796e-01
8.27432334e-01 -1.10234737e+00 -4.10476863e-01 -4.39799219e-01
4.34821397e-01 -5.85702360e-01 7.59374440e-01 7.06187367e-01
-1.01463306e+00 -4.38503772e-01 -1.49709439e+00 8.58806968e-02
-8.04707825e-01 4.61030006e-01 6.24229312e-01 1.10050476e+00
-9.72781599e-01 9.24353182e-01 -9.65502143e-01 -2.11419538e-01
4.77237999e-01 6.92294836e-01 6.22962229e-02 9.07323733e-02
-7.67231345e-01 1.10118079e+00 4.89369720e-01 5.24012029e-01
-4.74692672e-01 -9.86537337e-02 -7.38946140e-01 9.80885848e-02
-1.57056406e-01 2.54484912e-04 1.25781500e+00 -1.13130438e+00
-2.03021526e+00 6.13973320e-01 1.36834700e-02 -4.16148186e-01
5.75214922e-01 2.20422953e-01 -4.11259979e-01 1.33531913e-01
-4.89037901e-01 1.55905575e-01 1.20177329e+00 -5.77677786e-01
-5.17502666e-01 -2.77730137e-01 -5.14044285e-01 -3.79218196e-04
-5.22075772e-01 8.70940555e-03 -3.09771627e-01 -5.99031150e-01
1.34512052e-01 -4.67681766e-01 -1.66658819e-01 -7.40031749e-02
-3.22969228e-01 -1.54685855e-01 1.20556557e+00 -7.47424424e-01
1.03629506e+00 -1.77398956e+00 -2.49584541e-01 7.98321962e-01
-1.64586846e-02 5.88725209e-01 -5.64181618e-02 2.70939559e-01
1.52034879e-01 -1.53549314e-01 -3.19127321e-01 3.12948972e-02
-4.83865403e-02 2.30284840e-01 -9.63134319e-02 1.87468067e-01
4.42089826e-01 1.06202960e+00 -4.69922364e-01 -1.22077115e-01
3.41312140e-01 2.56805867e-01 -4.15453613e-02 2.37403084e-02
-1.68127209e-01 -4.96072680e-01 -2.69919306e-01 9.82374728e-01
5.45103967e-01 -3.91502738e-01 2.87227988e-01 -1.19912149e-02
-2.45162435e-02 -5.06595708e-02 -1.14742279e+00 8.72057259e-01
-3.35346520e-01 1.11628091e+00 3.50380130e-02 -1.29501355e+00
1.66946363e+00 -9.22337268e-03 4.89370786e-02 -6.58605039e-01
2.02263251e-01 6.44465268e-01 -1.92074716e-01 -4.01742131e-01
5.18350542e-01 1.05743796e-01 2.40926340e-01 4.99113172e-01
2.61770755e-01 -3.76497030e-01 2.60171801e-01 -1.76587805e-01
9.40380812e-01 -1.73774704e-01 1.30846491e-02 -2.26132914e-01
3.89114499e-01 3.99088025e-01 1.36450186e-01 1.02519500e+00
1.10193633e-01 5.99738717e-01 3.82027954e-01 -1.00043166e+00
-1.20140588e+00 -5.82803190e-01 4.59885560e-02 1.00850880e+00
-2.75216371e-01 2.27833956e-01 -5.86007833e-01 -6.04637027e-01
2.08587795e-01 3.69621217e-01 -2.86280602e-01 2.52894104e-01
-7.71555007e-01 -8.78335595e-01 8.06145132e-01 8.98093939e-01
9.21551466e-01 -1.16737759e+00 -6.33709669e-01 6.59187496e-01
6.99215949e-01 -8.19884956e-01 -3.18370759e-01 6.20810986e-01
-1.25339997e+00 -1.09175825e+00 -1.27100289e+00 -1.33720040e+00
6.30623996e-01 -2.58896381e-01 9.77752924e-01 6.92889914e-02
-5.60336649e-01 4.41533744e-01 -1.27212062e-01 -4.87663776e-01
-4.78222668e-01 3.51557016e-01 -1.67994469e-01 2.72402894e-02
7.24245548e-01 -2.47366711e-01 -9.83846411e-02 3.60595107e-01
-6.00932062e-01 -2.24049374e-01 7.22862601e-01 1.16484952e+00
2.86086410e-01 -6.61544651e-02 3.92996281e-01 -8.32698464e-01
1.17712379e+00 9.78586171e-03 -8.03160846e-01 5.91314495e-01
-9.11021650e-01 1.35883629e-01 8.31931353e-01 -5.95449567e-01
-8.45002055e-01 2.31492102e-01 -7.96184242e-02 -1.83117390e-01
-1.30603105e-01 6.41504705e-01 3.10047030e-01 -6.76262677e-01
1.06256604e+00 5.32762468e-01 3.43573838e-01 -4.51443940e-01
-1.10700235e-01 1.08481765e+00 5.76915741e-01 -3.35950851e-01
3.17721903e-01 -1.61307342e-02 -1.18913442e-01 -1.18063247e+00
-1.32643491e-01 -3.24340254e-01 -7.57217288e-01 -3.20849121e-01
5.57516396e-01 -2.58426607e-01 -6.00845933e-01 1.35700190e+00
-1.09947371e+00 -8.58028889e-01 3.57570797e-02 3.00758779e-01
-4.41108763e-01 3.91969413e-01 -9.98256683e-01 -7.85457969e-01
-6.02247059e-01 -8.62670541e-01 5.57693124e-01 4.90502506e-01
6.61618784e-02 -1.42688394e+00 -2.21871436e-01 -1.43723309e-01
7.87089944e-01 2.64934041e-02 1.03026724e+00 -8.37737620e-01
-4.51766968e-01 -6.39129281e-01 -2.20606014e-01 8.38631868e-01
2.05861300e-01 1.65067866e-01 -7.69208848e-01 -2.11909145e-01
-2.84330666e-01 -3.74002904e-01 8.43760610e-01 3.57548296e-01
1.00342691e+00 -3.19073647e-01 -1.61869437e-01 5.28951108e-01
1.43492591e+00 7.26578474e-01 7.55571246e-01 5.47866285e-01
8.16671550e-01 1.96512833e-01 -1.20864928e-01 2.52235562e-01
-9.39563215e-02 1.99341863e-01 -8.05241093e-02 -1.17990859e-01
-4.27071378e-02 -1.85797755e-02 2.07776710e-01 8.39939773e-01
-1.31812200e-01 -1.88001171e-01 -1.43043208e+00 2.11423114e-01
-1.65021050e+00 -7.90762722e-01 -8.00029282e-03 1.78289843e+00
5.96237659e-01 3.21676791e-01 7.63339596e-03 3.18772525e-01
7.79467702e-01 -1.46556363e-01 -7.88402319e-01 -1.05664301e+00
-2.23773673e-01 4.64850098e-01 8.45582306e-01 5.66823423e-01
-1.12141955e+00 9.13932323e-01 7.80775785e+00 6.77052021e-01
-1.66024864e+00 -6.56455278e-01 8.59955072e-01 3.90901923e-01
2.65712112e-01 -6.10435247e-01 -1.03879225e+00 2.12566629e-01
8.02230000e-01 2.53848881e-01 5.22618055e-01 1.10406637e+00
-1.39520273e-01 -2.24355143e-03 -1.13480580e+00 1.20806730e+00
3.66309792e-01 -1.79124331e+00 2.09849358e-01 -2.69393206e-01
6.03420615e-01 3.04812845e-02 6.75207525e-02 2.63368726e-01
1.56335890e-01 -1.30290258e+00 4.83406693e-01 7.36962259e-01
6.51084304e-01 -7.26876915e-01 7.55766690e-01 2.66286433e-01
-8.48569930e-01 -2.05218285e-01 -4.65997517e-01 -1.01157911e-01
-1.08303167e-01 4.70751047e-01 -1.08124399e+00 7.22399354e-03
5.37703753e-01 6.97000623e-01 -5.89794040e-01 1.21645153e+00
8.73126015e-02 5.36662221e-01 -5.14557004e-01 -9.57024872e-01
5.91510892e-01 -1.92608550e-01 2.82165617e-01 1.77957642e+00
1.76122561e-01 -1.22129470e-01 1.68058872e-02 8.48301947e-01
7.88009241e-02 1.24060586e-01 -4.90067869e-01 -4.36664462e-01
1.12002455e-01 8.96314681e-01 -9.16983724e-01 -5.39399445e-01
-2.14911953e-01 1.14918303e+00 2.80205399e-01 4.68168944e-01
-9.94429141e-02 -1.26494443e+00 -6.22798316e-03 1.14463074e-02
5.93279302e-01 -6.30268216e-01 -6.77948236e-01 -9.48550999e-01
1.30898908e-01 -1.15697324e+00 1.27233595e-01 -4.89523977e-01
-1.30009067e+00 6.60995722e-01 -4.56537306e-01 -8.74026895e-01
-5.39061606e-01 -1.70708168e+00 -7.39844918e-01 1.01372707e+00
-1.30950856e+00 -7.62154460e-01 -2.94591069e-01 5.64808965e-01
6.23972774e-01 -9.48609233e-01 8.43024194e-01 4.36930098e-02
-4.68469560e-01 8.47545266e-01 5.14155388e-01 7.98969209e-01
2.28429854e-01 -1.37279224e+00 5.26636183e-01 5.68663836e-01
7.32891485e-02 3.29403669e-01 4.79983427e-02 -5.80712020e-01
-1.61025071e+00 -9.17274117e-01 6.98696911e-01 -4.70970050e-02
4.17633027e-01 -1.85702905e-01 -1.02302861e+00 5.57395577e-01
-6.79864287e-02 -2.18432590e-01 3.68601471e-01 -5.15214391e-02
-3.05128843e-01 -1.72392726e-01 -1.20877469e+00 4.12162274e-01
3.51936162e-01 -5.37288785e-01 -5.15344977e-01 3.11650127e-01
-3.41712981e-01 -6.04989946e-01 -6.97135687e-01 -2.39689704e-02
8.15571308e-01 -8.41252863e-01 6.36503875e-01 -6.33338571e-01
2.99426794e-01 6.81892708e-02 4.75503542e-02 -1.18308604e+00
-3.93895566e-01 -5.98080516e-01 -3.04498792e-01 7.14390159e-01
8.17200720e-01 -8.42530012e-01 1.22138464e+00 7.41529167e-01
1.21703938e-01 -8.21875215e-01 -6.18164062e-01 -1.09236491e+00
2.97751456e-01 -1.59534007e-01 2.84717917e-01 7.49972045e-01
9.99081656e-02 3.66406471e-01 -2.57589072e-01 -1.10938005e-01
4.73695397e-01 -1.23105128e-03 4.67636287e-01 -1.05761397e+00
-4.43452150e-01 -9.55874622e-01 -9.94632125e-01 -1.40872967e+00
-1.64779380e-01 -7.52342880e-01 2.56957542e-02 -1.58973849e+00
-4.12241131e-01 -5.49513578e-01 5.64271472e-02 7.14680195e-01
2.63861060e-01 1.80021137e-01 1.45781457e-01 1.54174373e-01
2.30598636e-02 -6.50265664e-02 9.38596547e-01 -6.96947336e-01
-5.05478442e-01 1.81614414e-01 -1.11632667e-01 5.49897075e-01
1.18120170e+00 3.84027092e-03 -1.59461573e-01 -6.55693829e-01
4.69970219e-02 -1.91157192e-01 5.02609313e-02 -1.18427920e+00
6.18935883e-01 9.51720104e-02 9.94897723e-01 -5.69242716e-01
9.87074897e-02 -6.13334537e-01 -4.02933657e-01 5.31118274e-01
-3.23854744e-01 3.77535596e-02 3.84725690e-01 2.78429627e-01
-3.82842571e-01 -7.05318928e-01 8.53878140e-01 -2.60305375e-01
-9.69083607e-01 1.91408440e-01 -9.66806769e-01 -3.79856229e-01
6.77514613e-01 -7.34488428e-01 -2.08191171e-01 -4.22810853e-01
-7.19301820e-01 -1.54627776e-02 -3.17921117e-02 2.08172023e-01
8.92652988e-01 -1.18684697e+00 -6.91740572e-01 5.53009868e-01
-3.17575037e-01 -2.75237888e-01 -3.27668995e-01 2.30358094e-01
-1.38526547e+00 4.96779442e-01 -4.91457492e-01 -5.69929421e-01
-1.11597931e+00 2.03900337e-01 1.05980301e+00 -2.30909660e-01
-6.88195109e-01 8.61523509e-01 -8.94592404e-01 -5.77366114e-01
5.22167385e-01 -4.53183621e-01 -1.32468700e-01 -1.26557663e-01
6.70791209e-01 4.97007936e-01 5.39352775e-01 8.18011723e-03
-2.85988212e-01 6.19506478e-01 -4.23166573e-01 -8.10192749e-02
1.27066851e+00 5.43193996e-01 -2.65155695e-02 4.07619119e-01
1.21110618e+00 -4.53923911e-01 -1.14768016e+00 -1.78396076e-01
3.63527000e-01 -1.36561051e-01 1.10852525e-01 -1.01322854e+00
-1.10159731e+00 1.03642142e+00 7.02863336e-01 4.64196146e-01
1.01323807e+00 -5.99146187e-01 5.88826597e-01 1.35751498e+00
1.95124015e-01 -1.61114001e+00 1.16128191e-01 1.04356849e+00
8.93708706e-01 -1.11111248e+00 -1.35822579e-01 5.26565574e-02
-4.09486949e-01 2.32882094e+00 4.26502258e-01 -5.66273212e-01
7.13070333e-01 7.14886844e-01 3.99030685e-01 -6.31549284e-02
-2.69114614e-01 3.69063258e-01 3.02243143e-01 7.05145717e-01
4.14785892e-01 1.69334278e-01 7.30374008e-02 1.98902026e-01
-5.77537529e-02 1.19836174e-01 4.50277239e-01 1.39229357e+00
-6.56679094e-01 -9.98111606e-01 -5.11385322e-01 8.49530756e-01
-2.39160433e-01 -1.06180541e-01 -8.17472339e-01 5.53234816e-01
-4.92297500e-01 7.03280389e-01 1.98326960e-01 -5.14325440e-01
3.29342514e-01 3.19124103e-01 6.34619296e-01 -3.13175440e-01
-7.19070077e-01 -3.77523243e-01 3.82240675e-02 -2.18450055e-01
2.89642229e-03 -2.04667211e-01 -9.84765112e-01 -3.92508447e-01
-3.81498754e-01 -8.23560357e-02 9.71954286e-01 7.68910468e-01
6.98730499e-02 3.74850929e-01 5.97612023e-01 -1.03930867e+00
-8.48802984e-01 -9.11715746e-01 -8.77152324e-01 -2.58406103e-01
3.54353100e-01 -7.90082291e-02 -1.33394524e-01 1.01233251e-01] | [11.799497604370117, 2.642153739929199] |
b90a5986-e47f-41dc-9f05-342cbe21bf19 | to-catch-a-chorus-verse-intro-or-anything | 2205.14700 | null | https://arxiv.org/abs/2205.14700v1 | https://arxiv.org/pdf/2205.14700v1.pdf | To catch a chorus, verse, intro, or anything else: Analyzing a song with structural functions | Conventional music structure analysis algorithms aim to divide a song into segments and to group them with abstract labels (e.g., 'A', 'B', and 'C'). However, explicitly identifying the function of each segment (e.g., 'verse' or 'chorus') is rarely attempted, but has many applications. We introduce a multi-task deep learning framework to model these structural semantic labels directly from audio by estimating "verseness," "chorusness," and so forth, as a function of time. We propose a 7-class taxonomy (i.e., intro, verse, chorus, bridge, outro, instrumental, and silence) and provide rules to consolidate annotations from four disparate datasets. We also propose to use a spectral-temporal Transformer-based model, called SpecTNT, which can be trained with an additional connectionist temporal localization (CTL) loss. In cross-dataset evaluations using four public datasets, we demonstrate the effectiveness of the SpecTNT model and CTL loss, and obtain strong results overall: the proposed system outperforms state-of-the-art chorus-detection and boundary-detection methods at detecting choruses and boundaries, respectively. | ['Jordan B. L. Smith', 'Yun-Ning Hung', 'Ju-Chiang Wang'] | 2022-05-29 | null | null | null | null | ['boundary-detection'] | ['computer-vision'] | [ 1.22001104e-01 -4.51433510e-01 -1.57533914e-01 -2.03408405e-01
-8.32484782e-01 -8.69663715e-01 5.45406163e-01 -9.97253507e-02
-5.80309518e-02 2.29411051e-01 4.39002037e-01 1.19569302e-01
-1.20699249e-01 -3.09395820e-01 -5.39786339e-01 -6.06777906e-01
-1.24781253e-03 2.63128579e-01 1.02890059e-01 -1.51515424e-01
1.82457134e-01 -3.16401720e-02 -1.39960718e+00 6.52686715e-01
5.08211315e-01 1.26942301e+00 -5.18148802e-02 5.29180765e-01
-5.39256707e-02 8.43362033e-01 -8.34286511e-01 -3.58318686e-01
-7.58492351e-02 -8.35423946e-01 -9.68146920e-01 1.27549693e-01
2.66383678e-01 -1.29695132e-01 1.43744517e-02 6.49925530e-01
4.78881359e-01 2.99787410e-02 5.05415201e-01 -1.28369212e+00
-2.66080320e-01 1.01366401e+00 -6.97436094e-01 -4.23178338e-02
6.23543859e-01 -6.62202761e-02 1.56071436e+00 -6.66074932e-01
5.79165518e-01 9.55731273e-01 1.09333968e+00 4.06221122e-01
-1.52004278e+00 -7.87290215e-01 5.33846132e-02 2.54443109e-01
-1.45388436e+00 -4.58490521e-01 9.72702086e-01 -7.17171371e-01
5.90050817e-01 5.26093960e-01 8.39358747e-01 1.40743983e+00
-2.14812055e-01 1.04823709e+00 1.03159392e+00 -2.60445148e-01
5.63792437e-02 -3.81134391e-01 -1.39925197e-01 4.68388468e-01
-7.62763858e-01 -2.23606214e-01 -9.12463129e-01 1.05563179e-01
4.91605997e-01 -2.33132303e-01 -3.51496965e-01 -1.04862809e-01
-1.44255912e+00 5.03220320e-01 1.47552863e-01 4.34897780e-01
-1.10294752e-01 3.00807804e-01 9.19423819e-01 2.58208752e-01
5.14506698e-01 5.38220286e-01 -3.81252706e-01 -6.04827046e-01
-1.27007186e+00 2.72242367e-01 7.46192694e-01 7.28626013e-01
3.39043707e-01 -1.44692525e-01 -4.91879135e-01 1.21897066e+00
-1.85007825e-02 -2.07375884e-01 4.11113262e-01 -1.05680585e+00
2.19149530e-01 2.89303303e-01 2.84864139e-02 -5.64517558e-01
-6.92056477e-01 -6.47349596e-01 -6.77339494e-01 -3.42824519e-01
2.34405205e-01 5.56655079e-02 -6.76247537e-01 2.06402779e+00
1.24161139e-01 6.16923332e-01 -3.78936350e-01 9.72368062e-01
8.81757021e-01 5.59886396e-01 -1.04264811e-01 -1.61322460e-01
1.51866245e+00 -1.12426484e+00 -7.61056364e-01 4.33266200e-02
6.85860813e-01 -8.85829806e-01 1.47351289e+00 7.55257249e-01
-9.28126991e-01 -5.51867962e-01 -7.84007192e-01 -1.46138743e-01
1.18234925e-01 5.11153340e-01 5.74480593e-01 3.31809551e-01
-7.55183041e-01 8.74690890e-01 -9.12892997e-01 -1.71218023e-01
9.68941301e-02 5.79666793e-02 -7.40133077e-02 5.41933954e-01
-1.03669620e+00 3.04358333e-01 2.18572661e-01 3.30322310e-02
-1.04805827e+00 -7.59193957e-01 -6.34485126e-01 6.94800960e-03
2.46104479e-01 -4.78037447e-01 1.31776559e+00 -1.09946644e+00
-1.57543457e+00 1.13777554e+00 -8.50970373e-02 -3.94886255e-01
3.95977378e-01 -4.73386049e-01 -5.08379221e-01 2.70177275e-01
2.31092960e-01 6.85280263e-01 7.29359508e-01 -1.17561960e+00
-7.04159737e-01 -4.78113554e-02 1.72188774e-01 2.58062661e-01
-4.21152562e-01 4.65437084e-01 -5.11900187e-01 -9.59524632e-01
2.89598882e-01 -1.03521514e+00 5.04176557e-01 -1.26738504e-01
-7.92577744e-01 -4.11714405e-01 7.36059546e-01 -1.01611757e+00
1.76773429e+00 -2.48879766e+00 2.39906579e-01 -9.88611802e-02
1.65540233e-01 -1.55896157e-01 -2.71044467e-02 4.30023283e-01
2.14200770e-03 5.73685281e-02 -2.65627950e-01 -5.23718715e-01
2.78837532e-01 1.62488017e-02 -3.79634291e-01 3.68485034e-01
-1.64865673e-01 5.62845349e-01 -8.09947729e-01 -4.14407581e-01
-4.88287071e-03 4.53603238e-01 -6.76599503e-01 7.60467798e-02
-2.00164393e-01 6.55835271e-01 -2.71186475e-02 7.02130198e-01
3.89783680e-02 -1.57006592e-01 1.58992320e-01 -3.85840833e-01
-3.28180730e-01 9.97232974e-01 -1.01633036e+00 1.90833473e+00
-5.70657969e-01 8.20648193e-01 1.00791067e-01 -7.68015921e-01
9.33431447e-01 6.20083630e-01 7.23175526e-01 -4.37019616e-01
3.74220051e-02 1.71753511e-01 1.72932476e-01 -2.93851286e-01
4.06284779e-01 -2.00273365e-01 -5.06608903e-01 4.25349325e-01
3.63669172e-02 -8.08626488e-02 2.35457867e-01 -1.63767695e-01
1.19465685e+00 4.48735893e-01 -1.89054646e-02 -2.66338624e-02
3.34176242e-01 -4.31916267e-01 7.70696044e-01 2.94367254e-01
-2.38020673e-01 8.65324199e-01 9.56514835e-01 -1.72430754e-01
-9.07090724e-01 -1.03939390e+00 3.91274951e-02 1.59422791e+00
1.55921966e-01 -9.54462528e-01 -8.00627232e-01 -3.45147491e-01
-1.59714997e-01 5.99378288e-01 -5.91736317e-01 -1.52159065e-01
-7.11716533e-01 -1.81397513e-01 1.12024796e+00 5.53078949e-01
5.03402054e-01 -1.04457188e+00 -4.14721400e-01 2.37154678e-01
-8.07810128e-01 -1.06194830e+00 -9.55513656e-01 1.98771238e-01
-3.30983579e-01 -6.74427927e-01 -4.15648222e-01 -8.22122514e-01
-2.61847973e-01 3.71954851e-02 1.06172645e+00 -2.08521992e-01
-5.35529852e-02 1.66683257e-01 -6.59637213e-01 6.11571372e-02
-1.20936953e-01 2.21274897e-01 -7.31563643e-02 4.38514203e-01
-1.38530554e-02 -1.01879954e+00 -6.60245240e-01 6.62503183e-01
-5.17394602e-01 1.64293244e-01 1.10120155e-01 7.59522617e-01
5.84811389e-01 -1.53731510e-01 4.41605896e-01 -6.77891254e-01
5.97125888e-01 -2.16237023e-01 3.40738855e-02 -2.75985133e-02
-2.86871195e-01 -3.31098914e-01 7.12430418e-01 -7.22570181e-01
-7.21895993e-01 -7.97214508e-02 -2.69893795e-01 -6.95343196e-01
-5.63754663e-02 6.29898012e-01 -2.69755244e-01 3.23049694e-01
4.42090392e-01 1.33869126e-01 -4.73216921e-01 -7.43308723e-01
2.96724021e-01 7.21605659e-01 9.21572387e-01 -6.82785213e-01
4.02508259e-01 4.15387899e-01 -2.70880640e-01 -7.43197739e-01
-1.18083382e+00 -8.11477304e-01 -5.09882629e-01 -3.92410934e-01
9.40942049e-01 -1.05881357e+00 -8.08781207e-01 5.32123327e-01
-1.13650227e+00 -5.33278048e-01 -3.27586681e-01 4.49385464e-01
-7.73255229e-01 3.85778129e-01 -9.23340380e-01 -5.30643165e-01
-3.47849846e-01 -8.26265574e-01 1.28094053e+00 -1.18301667e-01
-8.80231082e-01 -6.81640148e-01 8.21500868e-02 6.40569985e-01
-7.01496452e-02 4.61679339e-01 8.43694270e-01 -5.75689793e-01
-1.91845402e-01 1.13627359e-01 -5.10197841e-02 4.19359267e-01
2.12823469e-02 4.97425497e-02 -1.03757119e+00 -5.32066822e-02
-1.10789716e-01 -5.58304608e-01 1.00277078e+00 3.06880146e-01
1.28684807e+00 -4.34538484e-01 -1.73049226e-01 9.51656520e-01
8.13412964e-01 1.08958907e-01 5.75701594e-01 1.94876686e-01
7.32434154e-01 3.44219685e-01 5.33673882e-01 7.93619215e-01
3.46779972e-01 9.98537600e-01 2.81326413e-01 6.12087920e-02
-3.89938474e-01 -3.73027951e-01 7.29909778e-01 9.93178070e-01
-1.60419539e-01 -2.74812102e-01 -7.40932941e-01 6.22933567e-01
-1.64811671e+00 -1.00749147e+00 -8.71550664e-02 1.97204912e+00
1.04345322e+00 2.31018439e-01 4.45002109e-01 5.55040181e-01
8.35554779e-01 5.11140645e-01 -4.17027026e-01 -4.36391413e-01
-9.14205238e-02 2.46272042e-01 -3.53905633e-02 9.57798436e-02
-1.42308688e+00 1.08439124e+00 5.78744602e+00 1.12578094e+00
-1.42811859e+00 2.77019322e-01 2.54872203e-01 -2.39922732e-01
-2.80157804e-01 2.30267555e-01 -4.78390336e-01 5.83588183e-01
6.69546068e-01 2.32981086e-01 7.79372871e-01 5.90356648e-01
3.35829645e-01 2.42264703e-01 -1.36818230e+00 1.12380719e+00
1.87475115e-01 -1.14475465e+00 -2.56315619e-01 -2.14435503e-01
5.30217290e-01 -2.28413269e-01 -7.30110407e-02 4.70799774e-01
-1.25546575e-01 -8.05895329e-01 1.44170129e+00 2.86780864e-01
1.05033755e+00 -5.27878046e-01 1.85999900e-01 9.29151624e-02
-1.60214472e+00 -2.86095515e-02 3.43224019e-01 -9.93867218e-02
2.14575738e-01 3.12442839e-01 -5.05038619e-01 4.65232879e-01
6.42844021e-01 9.84538734e-01 -2.80078411e-01 1.02444816e+00
-5.02842903e-01 1.17518723e+00 -2.68466532e-01 2.27109894e-01
1.02504656e-01 -2.47506872e-01 6.86812758e-01 1.29009008e+00
4.75351602e-01 -2.48054072e-01 3.85296166e-01 9.72321153e-01
-1.95407137e-01 1.42157853e-01 1.03306375e-01 -2.89927930e-01
5.42684495e-01 1.26687419e+00 -9.23318744e-01 9.92223546e-02
-1.07215412e-01 1.23410535e+00 -1.25537645e-02 1.14753164e-01
-1.15462589e+00 -5.25253713e-01 6.49713635e-01 2.38530710e-01
3.62961739e-01 -1.80258930e-01 -2.94754386e-01 -9.74638939e-01
3.31201963e-03 -8.02189529e-01 4.54708964e-01 -8.36674809e-01
-1.03569698e+00 3.89806688e-01 -2.65956491e-01 -1.39980805e+00
-1.56571954e-01 -1.31847441e-01 -8.21561635e-01 4.29944575e-01
-7.94204652e-01 -1.38491952e+00 -1.63549170e-01 5.12987614e-01
4.83616322e-01 5.64668439e-02 6.28305972e-01 7.30006635e-01
-4.74212468e-01 7.66678989e-01 -1.28819585e-01 5.55720866e-01
8.91270101e-01 -1.26109910e+00 1.14465512e-01 4.16378647e-01
5.51265299e-01 2.62353957e-01 7.45335102e-01 -2.27537632e-01
-8.49873006e-01 -1.11556542e+00 9.51779664e-01 -1.59428909e-01
8.72071266e-01 -6.96496427e-01 -6.38423681e-01 6.81985378e-01
-3.19794081e-02 -2.47482702e-01 7.42625952e-01 7.00063169e-01
-6.61397457e-01 -2.40659654e-01 -5.92012346e-01 5.38107634e-01
1.32708883e+00 -7.62701988e-01 -5.10536373e-01 2.31115803e-01
8.88358533e-01 -4.13768619e-01 -8.22451532e-01 4.11593884e-01
8.12107384e-01 -1.28370798e+00 8.85826230e-01 -1.83649540e-01
4.74251807e-01 -2.18702465e-01 -4.68496792e-02 -1.18400300e+00
-2.27059171e-01 -9.54133391e-01 5.54321744e-02 1.65400565e+00
2.53839761e-01 -6.58479407e-02 5.94896317e-01 -3.42786580e-01
-7.99847782e-01 -5.33840477e-01 -1.15176356e+00 -8.91619802e-01
-2.14435503e-01 -6.80723131e-01 4.37188506e-01 1.28525138e+00
2.27911994e-01 7.09006906e-01 -6.24200106e-01 -2.72815466e-01
7.87077695e-02 4.39384460e-01 5.93385756e-01 -1.36191440e+00
-4.74955380e-01 -8.84586573e-01 -2.74293870e-01 -1.04054439e+00
2.54499108e-01 -1.02087045e+00 8.91679451e-02 -1.48412967e+00
8.01301152e-02 -3.62215698e-01 -3.94193381e-01 7.05169261e-01
3.94875109e-01 5.00588179e-01 1.41904399e-01 4.13239866e-01
-8.47336233e-01 5.69750965e-01 1.08849490e+00 -1.64249077e-01
-4.76228148e-01 1.07481211e-01 -3.40051234e-01 8.80900741e-01
6.33783937e-01 -3.41807246e-01 -1.68336734e-01 -2.41913542e-01
5.03922999e-01 2.99835563e-01 4.12422270e-01 -1.16535425e+00
-6.43301681e-02 1.08463757e-01 -8.49569812e-02 -5.25368214e-01
7.00109601e-01 -1.20152794e-01 2.17191651e-01 1.79052949e-01
-6.36749148e-01 -3.84029597e-01 -6.92316294e-02 2.30424047e-01
-5.14861584e-01 9.18764025e-02 6.92220509e-01 2.08661750e-01
-4.54674125e-01 -4.74160314e-02 -7.44328275e-02 2.51915932e-01
5.74710548e-01 -1.24251708e-01 3.72660495e-02 -4.91400421e-01
-9.82729077e-01 1.09113961e-01 1.68616831e-01 3.97343844e-01
3.60844105e-01 -1.57995689e+00 -7.32814372e-01 -1.16564684e-01
2.91286886e-01 -2.89572924e-01 3.33973736e-01 1.17697835e+00
-3.38709146e-01 1.70226507e-02 -1.85614917e-02 -7.61272371e-01
-1.34339082e+00 2.61179745e-01 2.28057712e-01 -3.55147004e-01
-7.55103707e-01 9.47041571e-01 3.49906772e-01 -3.47539634e-01
5.69324851e-01 -5.68471551e-01 -2.33522072e-01 5.49593627e-01
5.57352602e-02 3.83281022e-01 -9.43644345e-02 -7.19078898e-01
-3.02963912e-01 5.01887918e-01 3.11843246e-01 -3.16390425e-01
9.91840959e-01 -1.43159300e-01 -1.88629031e-01 9.39596474e-01
1.06963170e+00 1.92482471e-01 -1.21602058e+00 -9.98050794e-02
1.15792871e-01 -1.05711423e-01 -5.23093119e-02 -8.52764845e-01
-7.51530230e-01 1.03789723e+00 2.25524783e-01 3.29290271e-01
1.29361093e+00 2.85641968e-01 1.05635214e+00 2.88069155e-02
9.08004493e-02 -1.27791345e+00 4.28058237e-01 6.79001272e-01
1.08150744e+00 -5.94872594e-01 -3.65957886e-01 -2.70951957e-01
-7.61681080e-01 8.11794996e-01 2.72814423e-01 1.23111752e-03
4.44412231e-01 1.25368968e-01 -1.61704093e-01 -9.15904269e-02
-7.28864014e-01 -3.90409797e-01 4.79384571e-01 1.04166001e-01
7.08786726e-01 2.85016060e-01 -4.56517518e-01 1.04586196e+00
-7.03606963e-01 -1.39943182e-01 4.09024358e-01 4.35451627e-01
-2.29417130e-01 -8.80685747e-01 -2.27997899e-01 2.27062851e-01
-6.45983458e-01 -1.68596506e-01 -6.08446419e-01 7.72297382e-01
5.94496548e-01 8.77954066e-01 2.02971101e-01 -8.67493868e-01
1.42171323e-01 2.14442387e-01 5.37557960e-01 -6.91280901e-01
-9.02418137e-01 8.64365041e-01 3.75226945e-01 -3.41809332e-01
-4.85738099e-01 -8.06751370e-01 -1.17587495e+00 -9.13449600e-02
-1.16909847e-01 1.15535438e-01 3.56281728e-01 9.76813078e-01
2.90132742e-02 6.62870347e-01 7.20673382e-01 -7.71315873e-01
-2.76857913e-01 -1.09838986e+00 -8.04183483e-01 7.24028111e-01
2.49583796e-01 -6.36499584e-01 -4.04021263e-01 2.92186707e-01] | [15.812104225158691, 5.317692756652832] |
733c1a35-b20d-44c6-8201-8ab0792fa26b | litevl-efficient-video-language-learning-with | 2210.11929 | null | https://arxiv.org/abs/2210.11929v1 | https://arxiv.org/pdf/2210.11929v1.pdf | LiteVL: Efficient Video-Language Learning with Enhanced Spatial-Temporal Modeling | Recent large-scale video-language pre-trained models have shown appealing performance on various downstream tasks. However, the pre-training process is computationally expensive due to the requirement of millions of video-text pairs and the redundant data structure of each video. To mitigate these problems, we propose LiteVL, which adapts a pre-trained image-language model BLIP into a video-text model directly on downstream tasks, without heavy pre-training. To enhance the temporal modeling lacking in the image-language model, we propose to add temporal attention modules in the image encoder of BLIP with dynamic temporal scaling. Besides the model-wise adaptation, we also propose a non-parametric pooling mechanism to adaptively reweight the fine-grained video embedding conditioned on the text. Experimental results on text-video retrieval and video question answering show that the proposed LiteVL even outperforms previous video-language pre-trained models by a clear margin, though without any video-language pre-training. | ['Qun Liu', 'Xin Jiang', 'Lifeng Shang', 'Lu Hou', 'Chaofan Tao', 'Dongsheng Chen'] | 2022-10-21 | null | null | null | null | ['video-question-answering'] | ['computer-vision'] | [ 4.67239283e-02 -3.53971243e-01 -1.70532182e-01 -5.89221120e-01
-9.69950795e-01 -3.97138149e-01 7.25350499e-01 -3.08216691e-01
-8.58120441e-01 2.43685052e-01 4.20142442e-01 -3.18861485e-01
3.31984788e-01 -2.43047327e-01 -1.03301358e+00 -5.37942469e-01
1.06608659e-01 -1.40664518e-01 3.77888024e-01 1.20963581e-01
1.59673706e-01 -1.42247230e-01 -1.31809270e+00 8.22207510e-01
4.46946174e-01 1.12155986e+00 7.29876161e-01 9.41388071e-01
-2.32986882e-01 1.11093020e+00 -1.73260406e-01 -3.81959468e-01
2.33097374e-01 -4.66903567e-01 -5.31553686e-01 1.32890001e-01
9.04553533e-01 -8.91888142e-01 -9.96019125e-01 7.35221803e-01
3.07783306e-01 2.89038509e-01 3.28945398e-01 -1.17662108e+00
-1.09932041e+00 3.85766685e-01 -5.59513330e-01 4.36580658e-01
2.07341149e-01 2.43537948e-01 1.03559053e+00 -1.26756132e+00
5.34428596e-01 1.40929377e+00 4.88290548e-01 5.98273039e-01
-8.90214980e-01 -7.50507951e-01 6.60093486e-01 6.32221282e-01
-1.56901979e+00 -6.53699160e-01 4.85992402e-01 -3.52310449e-01
1.21111131e+00 -1.81567267e-01 4.14742291e-01 1.22496402e+00
3.64028513e-01 1.06781077e+00 6.38178468e-01 -9.34556499e-02
-1.19589768e-01 -4.84914593e-02 -7.79116824e-02 8.83377016e-01
-2.61781454e-01 -1.86783493e-01 -7.85752416e-01 8.36923793e-02
8.08279932e-01 2.64644265e-01 -2.45320171e-01 -1.76427349e-01
-1.17705035e+00 6.20043755e-01 3.28224421e-01 2.72273779e-01
-2.87874728e-01 6.69493198e-01 6.68963075e-01 4.59498256e-01
4.50497627e-01 -1.66436493e-01 -5.52085876e-01 -6.10110871e-02
-1.26162934e+00 -1.54485449e-01 2.97546029e-01 1.19405961e+00
7.66315460e-01 -5.00819385e-02 -5.68473041e-01 6.51330888e-01
4.83047664e-01 3.26382905e-01 8.47727895e-01 -8.53721678e-01
7.27295697e-01 3.76996309e-01 -1.84249073e-01 -8.27642977e-01
1.07853457e-01 5.85425012e-02 -6.62849784e-01 -6.02504492e-01
1.46208242e-01 1.51688494e-02 -1.19643915e+00 1.66149175e+00
-3.33151571e-03 5.83820939e-01 -4.14940789e-02 9.98568416e-01
7.35294342e-01 1.17992961e+00 2.95841068e-01 -1.81115478e-01
1.13799453e+00 -1.75285387e+00 -8.00413489e-01 -1.77034155e-01
7.74755955e-01 -6.62905574e-01 1.27167630e+00 -4.68487777e-02
-1.18637776e+00 -8.91522586e-01 -7.70634890e-01 -6.48181915e-01
-3.03371191e-01 2.40741864e-01 3.45341325e-01 1.28390267e-01
-1.29475999e+00 1.42517611e-01 -8.46178293e-01 -3.13919514e-01
1.98013112e-01 3.40490073e-01 -3.83551747e-01 -4.71295089e-01
-1.17500126e+00 3.87669295e-01 2.30657041e-01 3.40400249e-01
-1.06402099e+00 -5.83068609e-01 -9.61275160e-01 3.16176444e-01
4.61862743e-01 -8.36824179e-01 1.24435711e+00 -1.28182650e+00
-1.66561615e+00 6.19854987e-01 -5.05882740e-01 -4.44190800e-01
4.86039042e-01 -4.92157966e-01 -2.71326900e-01 7.50629783e-01
-5.29017448e-02 1.04523456e+00 1.53487301e+00 -8.05357039e-01
-5.30528963e-01 -8.84529650e-02 2.46643215e-01 3.37050855e-01
-8.47412407e-01 8.32257494e-02 -1.46050692e+00 -8.80531132e-01
-3.09726477e-01 -7.37461865e-01 -2.00520247e-01 2.75639236e-01
2.29837984e-01 -2.38478646e-01 1.27222562e+00 -8.69639874e-01
1.47628164e+00 -2.23282743e+00 1.36126682e-01 -3.22292715e-01
3.89745757e-02 4.01750922e-01 -7.98505783e-01 3.92800689e-01
-3.99859697e-02 -2.19822880e-02 1.21811278e-01 -5.23160219e-01
-1.90506637e-01 1.77397177e-01 -4.02215838e-01 4.21620250e-01
4.07261819e-01 1.28381824e+00 -6.79825068e-01 -7.86971271e-01
2.15362012e-01 5.92601240e-01 -9.40841854e-01 4.58245575e-01
-4.76521075e-01 1.02934361e-01 -5.54207206e-01 4.92492527e-01
4.96246785e-01 -5.34460306e-01 6.44564625e-06 -3.49033177e-01
8.69686007e-02 1.35190561e-01 -5.75517416e-01 2.19335032e+00
-4.83286172e-01 7.60282755e-01 3.02182168e-01 -1.21713686e+00
2.18969345e-01 4.55665201e-01 4.96791452e-01 -8.95285189e-01
5.27699180e-02 -6.10575676e-02 -2.78186142e-01 -9.87920165e-01
6.07171416e-01 8.96228105e-02 -1.20556258e-01 3.66828650e-01
4.58702505e-01 2.32024282e-01 1.92715570e-01 6.13769352e-01
1.11227846e+00 4.15949702e-01 -2.66160518e-01 1.19555378e-02
9.58797157e-01 -3.10852498e-01 2.79640794e-01 6.68418884e-01
-2.74232477e-01 6.91848695e-01 1.32172570e-01 -1.57053754e-01
-9.61796522e-01 -6.83771491e-01 2.36175686e-01 1.55901372e+00
1.50061324e-01 -7.42377043e-01 -7.49455631e-01 -6.50507510e-01
-1.12795003e-01 1.20917283e-01 -4.35831845e-01 -2.69821584e-01
-7.38281488e-01 -3.52481693e-01 4.33612049e-01 5.99316716e-01
5.14748812e-01 -7.56208777e-01 -1.47980750e-01 3.02653700e-01
-2.95748323e-01 -1.68792725e+00 -1.27324939e+00 -2.92680651e-01
-8.75091732e-01 -6.98014855e-01 -1.05938792e+00 -1.19421768e+00
7.85612345e-01 6.54404521e-01 8.50416422e-01 2.97569156e-01
-1.49698645e-01 7.52985060e-01 -5.71779490e-01 2.62014508e-01
-4.13580518e-03 -7.83409178e-02 -1.88317835e-01 2.80919433e-01
4.40745622e-01 -3.06227833e-01 -8.30027819e-01 3.52149278e-01
-1.23883390e+00 1.52650312e-01 7.41401851e-01 1.08230197e+00
5.71619809e-01 -2.72935897e-01 4.79965389e-01 -3.39961559e-01
4.40845609e-01 -4.37944263e-01 -5.86450517e-01 5.28225124e-01
-3.46436322e-01 7.15605766e-02 6.94139004e-01 -7.39730835e-01
-1.02413058e+00 2.45005656e-02 -3.40371914e-02 -1.07825434e+00
1.87430844e-01 6.70477927e-01 -1.20923780e-02 -4.37614582e-02
-6.84616566e-02 3.21345985e-01 -1.50773108e-01 -4.61046070e-01
5.09848893e-01 6.00343108e-01 4.55187231e-01 -4.18910563e-01
7.74937391e-01 4.32333589e-01 -4.79677469e-01 -8.67809296e-01
-8.45213771e-01 -8.65202785e-01 -5.86757064e-01 -7.64326453e-02
1.19294596e+00 -1.46997559e+00 -4.73010480e-01 5.28669000e-01
-1.23140371e+00 -5.62163591e-01 1.45695880e-01 5.64058602e-01
-5.49695849e-01 7.20710456e-01 -1.07107174e+00 -4.68712032e-01
-3.28608096e-01 -1.11384463e+00 1.35454655e+00 -1.13800317e-01
4.35303718e-01 -8.18575203e-01 -3.22320640e-01 6.94119275e-01
3.48443955e-01 -6.59530580e-01 7.63955593e-01 -2.93761283e-01
-9.98010695e-01 -2.27066934e-01 -5.58304310e-01 5.84079206e-01
-1.75153002e-01 -1.73242792e-01 -7.52974629e-01 -5.76116800e-01
9.37831849e-02 -6.17634177e-01 1.23467457e+00 3.85508657e-01
1.62972569e+00 -2.78076261e-01 -1.39327765e-01 7.20207512e-01
1.44501185e+00 -2.36411709e-02 5.11157215e-01 3.15415412e-02
7.91613460e-01 3.80440891e-01 5.48746645e-01 9.95077863e-02
6.23057485e-01 4.84801114e-01 7.03885108e-02 -3.19162966e-03
-2.43897393e-01 -5.31525850e-01 9.78125155e-01 1.29796362e+00
2.28449389e-01 -5.69553733e-01 -5.18537283e-01 5.96122742e-01
-2.02665639e+00 -1.01771653e+00 1.86236024e-01 1.79616153e+00
5.22264481e-01 -8.30941573e-02 -1.81530192e-01 -4.86759633e-01
6.39926434e-01 3.39844853e-01 -5.62886477e-01 -1.79433808e-01
5.59190102e-03 -5.85815161e-02 4.22126800e-01 4.89665687e-01
-1.05539906e+00 1.34822011e+00 6.35902214e+00 8.67499709e-01
-1.30091703e+00 4.73934770e-01 5.35733938e-01 -5.25696814e-01
-1.86138913e-01 -4.74085584e-02 -7.66878843e-01 4.66666996e-01
1.26175284e+00 -1.81692958e-01 3.41392934e-01 5.23882270e-01
4.60697562e-01 -5.37401624e-02 -1.22261214e+00 1.13931072e+00
5.19005358e-01 -1.43847370e+00 4.14018542e-01 -1.60806879e-01
7.66650259e-01 2.63897866e-01 1.64133627e-02 7.31292367e-01
-2.65851587e-01 -7.66906738e-01 7.71448314e-01 3.32264185e-01
9.23638523e-01 -3.00753236e-01 4.00046706e-01 2.83465624e-01
-1.46313822e+00 -2.72016227e-01 -3.58592570e-01 1.03944570e-01
4.32937980e-01 9.23539326e-02 -3.44009936e-01 3.14622462e-01
9.07795429e-01 1.02003026e+00 -5.06666124e-01 6.24322951e-01
2.15603542e-02 5.70637703e-01 -1.58046708e-01 2.06317291e-01
7.72872448e-01 -9.91652980e-02 1.63803056e-01 1.38654721e+00
4.35199887e-01 2.11121559e-01 2.76593089e-01 4.61490482e-01
-3.96690905e-01 1.57189980e-01 -3.43491524e-01 -5.65638244e-01
-9.31908414e-02 1.06184351e+00 -2.73774862e-01 -6.58711255e-01
-1.14933562e+00 1.62652636e+00 2.01511085e-01 8.22915256e-01
-1.03888035e+00 -1.53877139e-01 6.11840606e-01 1.32077679e-01
6.98212743e-01 -5.48384249e-01 6.10271811e-01 -1.61680722e+00
2.51603723e-01 -7.16356516e-01 3.82944107e-01 -1.02082646e+00
-1.20911670e+00 5.44495821e-01 -1.46482632e-01 -1.09243381e+00
-2.55830318e-01 -7.19305575e-01 -2.80641109e-01 7.06401527e-01
-1.85432041e+00 -1.43754721e+00 -1.59320980e-01 1.01213694e+00
1.14284587e+00 -1.11828700e-01 3.47701937e-01 6.85105443e-01
-5.74643254e-01 8.10880363e-01 2.17787459e-01 1.79611608e-01
1.04507291e+00 -4.65511620e-01 2.46199533e-01 9.07011747e-01
-1.78715568e-02 6.43187702e-01 1.33879259e-01 -4.78689492e-01
-1.87379181e+00 -1.29639006e+00 9.04833555e-01 -3.09932292e-01
1.09971952e+00 -6.59159720e-01 -9.63478923e-01 8.70835125e-01
5.14453113e-01 2.91015595e-01 5.31318486e-01 -4.16659802e-01
-4.25338477e-01 -3.74657474e-02 -5.84558129e-01 6.36843324e-01
9.76554394e-01 -1.09966588e+00 -6.06557786e-01 3.59345675e-01
1.12945008e+00 -9.99827757e-02 -6.91264331e-01 2.44667128e-01
4.97905731e-01 -6.24297798e-01 1.04004741e+00 -7.39795089e-01
6.31892323e-01 -1.33678257e-01 -2.71648288e-01 -6.50387287e-01
-2.73557812e-01 -6.79795742e-01 -2.66786844e-01 1.11702335e+00
1.92344099e-01 -1.49127573e-01 8.08827996e-01 5.42660475e-01
-1.72767177e-01 -5.99793792e-01 -9.15075302e-01 -6.91934288e-01
-3.97670418e-02 -4.51082796e-01 -4.63355072e-02 7.49733984e-01
-7.84540400e-02 5.89056969e-01 -6.81453228e-01 1.23574898e-01
1.76198363e-01 6.74167052e-02 6.50057316e-01 -4.13145870e-01
-5.13808310e-01 -3.16164553e-01 -1.66547924e-01 -1.84673524e+00
4.85680610e-01 -9.34831798e-01 2.59330362e-01 -1.34289277e+00
4.39617127e-01 6.83279410e-02 -4.90662038e-01 2.42281869e-01
-4.20151740e-01 2.69819766e-01 2.38214344e-01 2.64172584e-01
-1.10802066e+00 8.42453301e-01 1.37704408e+00 -2.41421476e-01
4.45526652e-02 -6.13115132e-01 -2.65558392e-01 6.43038034e-01
3.03476989e-01 -3.52169335e-01 -6.33639932e-01 -1.10259736e+00
3.66383785e-04 1.69293731e-01 3.79011065e-01 -6.63765490e-01
3.79607081e-01 -2.58449316e-02 2.33526289e-01 -6.54711902e-01
6.83032930e-01 -8.87812793e-01 -4.76272285e-01 2.40556449e-01
-5.65787435e-01 2.59301037e-01 3.15669566e-01 9.73729491e-01
-6.16534650e-01 -1.01862885e-01 4.56052631e-01 -1.17770404e-01
-1.06907809e+00 7.69898236e-01 -6.66114330e-01 -5.17529212e-02
8.28893721e-01 -6.37503574e-03 -1.02791265e-01 -6.48011327e-01
-5.44131756e-01 6.32049918e-01 2.93024451e-01 8.77674699e-01
7.06119537e-01 -1.28738678e+00 -4.26353186e-01 2.74702996e-01
2.48970076e-01 -2.90120125e-01 5.87964475e-01 9.06663060e-01
-3.03393453e-01 8.06455553e-01 1.62039757e-01 -5.74758410e-01
-1.23098969e+00 8.82237554e-01 5.59401028e-02 -2.32527137e-01
-6.48344755e-01 1.08874118e+00 7.40685880e-01 1.34595027e-02
4.87812042e-01 -4.59513694e-01 1.46382824e-01 -5.91256991e-02
6.44496918e-01 -2.78946310e-01 -1.93074748e-01 -7.04269707e-01
-2.33722538e-01 6.91212893e-01 -3.42310876e-01 -1.78337216e-01
1.21694148e+00 -6.03721976e-01 1.77126676e-02 2.28076518e-01
1.77788818e+00 -3.99295688e-01 -1.50447476e+00 -4.57077831e-01
-8.33446383e-02 -4.03615803e-01 3.95336062e-01 -2.68621683e-01
-1.03076267e+00 1.24143279e+00 3.87925535e-01 -4.81095046e-01
1.21790755e+00 -7.73365349e-02 1.25122547e+00 7.72612691e-01
4.90939841e-02 -1.38289058e+00 6.26054943e-01 7.05319047e-01
9.16746199e-01 -1.31765628e+00 -2.07688540e-01 -1.11235522e-01
-4.02333796e-01 9.85144019e-01 7.59212971e-01 -2.14855045e-01
8.42149436e-01 1.11187613e-02 1.97611079e-02 1.37347370e-01
-1.35326171e+00 2.46549360e-02 4.21237588e-01 1.05086654e-01
4.23423201e-01 -6.33988798e-01 -3.00524950e-01 4.85661328e-01
5.44695437e-01 3.31315160e-01 2.04216555e-01 9.77806687e-01
-2.26764128e-01 -1.10852659e+00 -5.25104366e-02 2.91035622e-01
-5.30825555e-01 -5.66607535e-01 -8.46804306e-02 4.97812271e-01
-1.81321979e-01 7.45813668e-01 2.93357581e-01 -4.33523476e-01
-7.06853941e-02 2.53518224e-01 4.79054719e-01 -5.00104427e-01
-4.87580001e-01 6.05642319e-01 -1.58244833e-01 -8.09062183e-01
-6.07291043e-01 -3.49323273e-01 -1.12237859e+00 -6.42437339e-02
-3.03257674e-01 8.71975198e-02 5.57149291e-01 9.70700860e-01
6.21655166e-01 3.68568391e-01 4.43142027e-01 -1.05233812e+00
-4.37890232e-01 -8.01225901e-01 -1.79829404e-01 4.10410374e-01
4.97614205e-01 -2.24008143e-01 -3.44837189e-01 5.87193012e-01] | [10.2954740524292, 0.9500704407691956] |
611df8e5-72ce-4747-9970-adad372b2f4a | cross-guided-optimization-of-radiance-fields | null | null | http://openaccess.thecvf.com//content/CVPR2023/html/Yoon_Cross-Guided_Optimization_of_Radiance_Fields_With_Multi-View_Image_Super-Resolution_for_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Yoon_Cross-Guided_Optimization_of_Radiance_Fields_With_Multi-View_Image_Super-Resolution_for_CVPR_2023_paper.pdf | Cross-Guided Optimization of Radiance Fields With Multi-View Image Super-Resolution for High-Resolution Novel View Synthesis | Novel View Synthesis (NVS) aims at synthesizing an image from an arbitrary viewpoint using multi-view images and camera poses. Among the methods for NVS, Neural Radiance Fields (NeRF) is capable of NVS for an arbitrary resolution as it learns a continuous volumetric representation. However, radiance fields rely heavily on the spectral characteristics of coordinate-based networks. Thus, there is a limit to improving the performance of high-resolution novel view synthesis (HRNVS). To solve this problem, we propose a novel framework using cross-guided optimization of the single-image super-resolution (SISR) and radiance fields. We perform multi-view image super-resolution (MVSR) on train-view images during the radiance fields optimization process. It derives the updated SR result by fusing the feature map obtained from SISR and voxel-based uncertainty fields generated by integrated errors of train-view images. By repeating the updates during radiance fields optimization, train-view images for radiance fields optimization have multi-view consistency and high-frequency details simultaneously, ultimately improving the performance of HRNVS. Experiments of HRNVS and MVSR on various benchmark datasets show that the proposed method significantly surpasses existing methods. | ['Kuk-Jin Yoon', 'Youngho Yoon'] | 2023-01-01 | null | null | null | cvpr-2023-1 | ['image-super-resolution', 'novel-view-synthesis'] | ['computer-vision', 'computer-vision'] | [ 2.02322230e-01 -2.43641630e-01 1.70264423e-01 -5.22055209e-01
-1.15930724e+00 -4.09265369e-01 5.23870528e-01 -6.55503869e-01
-7.77608762e-03 7.44083941e-01 2.02810735e-01 3.60250443e-01
-4.53566134e-01 -1.10180509e+00 -9.54784572e-01 -7.98788011e-01
5.73713422e-01 2.06065387e-01 1.81923270e-01 -3.44758153e-01
1.31943107e-01 6.65091038e-01 -1.67515349e+00 3.06802630e-01
7.74114847e-01 1.06126106e+00 5.38205504e-01 5.14234483e-01
1.15761429e-01 7.48777449e-01 -2.58950114e-01 -9.24188346e-02
4.41310734e-01 -2.24346206e-01 -4.50864643e-01 -1.71480879e-01
9.26361084e-01 -6.09844804e-01 -3.32943797e-01 1.20955622e+00
4.84378308e-01 4.37137902e-01 3.88063639e-01 -6.69043720e-01
-8.36571276e-01 3.81561995e-01 -7.50222802e-01 3.02475750e-01
3.18709224e-01 -6.69756308e-02 6.70613468e-01 -1.27978277e+00
1.00323927e+00 1.21402001e+00 4.70867366e-01 3.73325378e-01
-1.17412865e+00 -4.30107296e-01 2.38714993e-01 -8.05710480e-02
-1.52622080e+00 -2.70503253e-01 8.94731164e-01 -2.98336178e-01
8.52804720e-01 4.26349878e-01 4.52872157e-01 8.96990776e-01
5.82158923e-01 3.03567737e-01 1.30486906e+00 8.42921063e-02
1.50734693e-01 2.00528473e-01 -4.59316432e-01 7.88451910e-01
-7.26046190e-02 5.58446944e-01 -7.79264808e-01 -8.09335802e-03
1.38162184e+00 9.94898900e-02 -6.84625208e-01 -3.30347717e-01
-1.34060550e+00 6.96581244e-01 7.82264352e-01 1.36140153e-01
-4.44844663e-01 7.76569499e-03 -1.28813893e-01 -1.40856311e-01
7.88055778e-01 4.41758037e-01 -3.89293998e-01 4.32820112e-01
-9.55533504e-01 1.12816505e-01 -2.54407302e-02 7.55054533e-01
9.00503933e-01 5.75318635e-01 -8.17727149e-02 7.47524679e-01
1.65527403e-01 7.12207019e-01 1.93408549e-01 -1.25673282e+00
3.60090047e-01 4.47206646e-01 7.42301997e-03 -1.08376110e+00
-4.28245217e-01 -6.61140382e-01 -1.20156538e+00 5.06533742e-01
-4.53167781e-02 1.60346687e-01 -9.82203066e-01 1.50616241e+00
7.15981185e-01 1.70442030e-01 2.11212754e-01 1.22096932e+00
1.28794277e+00 8.23740065e-01 -5.46148002e-01 -4.41972435e-01
1.02623892e+00 -7.91001558e-01 -7.02440858e-01 -2.39042975e-02
-9.34230611e-02 -6.01457119e-01 7.14175463e-01 4.54536885e-01
-1.24937296e+00 -7.89221525e-01 -1.13102043e+00 -3.32383901e-01
-1.25071192e-02 -1.87716801e-02 3.42552900e-01 2.18889371e-01
-9.67023134e-01 5.91903448e-01 -6.13700628e-01 4.46161002e-01
3.54831606e-01 5.16194627e-02 -4.95003402e-01 -3.52238506e-01
-1.19752705e+00 6.33665264e-01 1.45943373e-01 2.12080792e-01
-8.51171911e-01 -1.37987030e+00 -1.10954511e+00 -9.08893049e-02
4.25724238e-01 -1.14341819e+00 5.68460524e-01 -6.18142307e-01
-1.53224719e+00 5.08280575e-01 -1.10301413e-01 6.50459602e-02
4.19662952e-01 4.56982478e-02 -4.50294971e-01 3.38897705e-01
1.96673200e-01 4.51845109e-01 9.57455635e-01 -1.68710303e+00
-6.41665339e-01 -5.97907007e-01 1.54777057e-02 5.63889384e-01
4.39678997e-01 -4.40426081e-01 -3.01535428e-01 -4.65084761e-01
5.68365932e-01 -4.75067914e-01 -2.64714181e-01 -9.43874493e-02
-2.75907874e-01 2.47179180e-01 4.36102211e-01 -8.20092499e-01
6.79430723e-01 -1.99752176e+00 5.86646616e-01 4.85663973e-02
4.63982105e-01 -3.17061841e-01 9.16593522e-02 -2.73306131e-01
-3.87777109e-03 -1.32661700e-01 -2.73198575e-01 -2.54393667e-01
-4.96374249e-01 5.41653223e-02 -2.64851242e-01 6.89233363e-01
6.65297080e-03 9.16665971e-01 -8.60337615e-01 -4.47441638e-01
6.54601932e-01 1.14414775e+00 -4.47214425e-01 2.17216879e-01
-1.92874908e-01 1.07556772e+00 -5.93559086e-01 5.77976346e-01
1.12021649e+00 -4.50220913e-01 -2.00408489e-01 -8.07068944e-01
-3.85010183e-01 -3.52261215e-01 -1.34913433e+00 2.08562708e+00
-8.85401249e-01 1.99678972e-01 9.26338881e-02 -3.84770542e-01
8.96350026e-01 -1.19833782e-01 7.33801067e-01 -9.83434260e-01
2.62156129e-02 -4.72892784e-02 -7.75941670e-01 -2.73928642e-01
6.89985871e-01 -2.46564016e-01 1.62943289e-01 6.66023418e-02
3.90852466e-02 -4.44006592e-01 -3.66718829e-01 1.70695350e-01
4.59024817e-01 5.30402601e-01 3.01550090e-01 7.62907937e-02
7.56087422e-01 -1.80638552e-01 5.54994524e-01 3.97732854e-01
3.97215962e-01 1.21936488e+00 -2.29626909e-01 -5.66576123e-01
-1.15244889e+00 -1.51974678e+00 -4.75910872e-01 6.20701313e-01
3.21858734e-01 -1.44757241e-01 -6.13202989e-01 -3.81955713e-01
-2.95411319e-01 6.35717511e-01 -6.81200266e-01 1.36591077e-01
-7.23823011e-01 -6.15611911e-01 -1.42613471e-01 3.86095643e-01
7.04516053e-01 -6.22167468e-01 -7.00661600e-01 -3.85068245e-02
-5.20437777e-01 -1.47146893e+00 -4.78960425e-01 -7.66959488e-02
-8.28242242e-01 -7.85682976e-01 -8.05785894e-01 -1.54656991e-01
6.15864515e-01 4.24668312e-01 1.26698494e+00 -1.98181450e-01
-3.47920150e-01 3.62483293e-01 3.73781845e-02 2.24987030e-01
-3.40536892e-01 -2.03712612e-01 -2.25805808e-02 1.44421816e-01
-6.06130660e-01 -8.91595721e-01 -8.22274387e-01 2.64584512e-01
-1.01106882e+00 4.62448239e-01 5.95407248e-01 8.10786009e-01
1.40738928e+00 2.12089986e-01 1.97046682e-01 -8.65536571e-01
-1.32369995e-01 -3.69983941e-01 -1.08459079e+00 3.28418881e-01
-6.56396210e-01 2.03874230e-01 7.61225164e-01 -1.21799717e-02
-1.56583774e+00 1.92719743e-01 -8.82267058e-02 -9.87451553e-01
1.44536681e-02 1.69717818e-01 -2.75781512e-01 -3.39616597e-01
6.46857917e-01 6.40976131e-01 -2.68405527e-01 -2.53504217e-01
5.39404094e-01 9.38707888e-02 7.42937684e-01 -2.20829397e-01
9.48160827e-01 9.30758357e-01 3.60304803e-01 -7.41156459e-01
-1.12694836e+00 -2.19687641e-01 -5.95808029e-01 -5.19449294e-01
1.22981119e+00 -1.27708423e+00 -6.07227147e-01 1.91164181e-01
-9.72051442e-01 5.38222007e-02 -2.51858026e-01 5.67120314e-01
-6.24329209e-01 2.16103569e-01 -1.66328490e-01 -6.53688431e-01
-3.39775741e-01 -1.43124974e+00 1.48958170e+00 4.41420853e-01
5.21451950e-01 -8.61868680e-01 -1.92603911e-03 7.12099493e-01
3.18456858e-01 7.15652585e-01 6.53330982e-01 4.67902780e-01
-1.32441723e+00 4.83747810e-01 -2.75332719e-01 3.66341233e-01
-4.88382718e-03 -2.21215531e-01 -1.11427224e+00 -2.31686085e-01
4.15945709e-01 -7.75332749e-02 7.05374658e-01 9.03943062e-01
1.13690639e+00 1.15048699e-03 1.18347974e-02 1.43203330e+00
2.14953661e+00 -2.73060240e-03 5.63416302e-01 3.23231757e-01
1.15350628e+00 4.33507234e-01 5.66689432e-01 4.94459629e-01
4.68049794e-01 9.58284497e-01 7.98165798e-01 3.07522230e-02
-2.38038614e-01 -2.43785277e-01 1.69922844e-01 6.80658519e-01
-3.80292624e-01 -9.10341293e-02 -3.55113357e-01 2.70591736e-01
-1.56232250e+00 -9.62501407e-01 -1.75911754e-01 2.13397384e+00
4.31060344e-01 -2.87427396e-01 -5.25095344e-01 -3.52183968e-01
4.65619206e-01 5.98328829e-01 -9.02210176e-01 1.79296155e-02
-3.98897946e-01 3.21509540e-02 6.11073971e-01 7.54446566e-01
-6.84017122e-01 6.59911752e-01 5.11760759e+00 7.25474536e-01
-1.07117057e+00 2.69789547e-01 7.78262854e-01 -3.88974577e-01
-8.34852278e-01 -4.00512129e-01 -1.03909624e+00 8.59495029e-02
4.83739763e-01 1.22882821e-01 8.63486052e-01 8.07791531e-01
4.72360961e-02 -2.77355999e-01 -8.81337285e-01 1.33453488e+00
4.17158365e-01 -1.81857455e+00 2.55536228e-01 -7.26436228e-02
1.28726053e+00 2.39870638e-01 4.24517184e-01 -9.15933624e-02
1.38451204e-01 -1.09925318e+00 6.88352644e-01 7.95943022e-01
1.09981370e+00 -9.96494889e-01 4.11752850e-01 2.69174874e-01
-1.24083412e+00 1.17238671e-01 -4.01273608e-01 6.71731412e-01
5.91306627e-01 7.27068901e-01 -2.09481210e-01 1.46568656e+00
9.33133841e-01 7.55160987e-01 -4.21595901e-01 2.79418528e-01
1.24603793e-01 -3.23191106e-01 -1.35392085e-01 7.31106400e-01
1.47794560e-01 -5.35773575e-01 6.52087092e-01 3.28795910e-01
3.91991973e-01 2.93593705e-01 -1.08024463e-01 1.34928334e+00
1.45014092e-01 -7.88364708e-02 -5.25960326e-01 6.65411532e-01
8.08922499e-02 1.47996211e+00 -5.63376009e-01 -1.56514779e-01
-3.24008971e-01 8.65116417e-01 2.91333646e-01 4.34605241e-01
-9.67806578e-01 3.07921648e-01 5.15464127e-01 2.57013232e-01
2.88132906e-01 5.68375806e-04 -3.39886457e-01 -1.43261838e+00
2.19923630e-01 -7.60105848e-01 1.98911712e-01 -1.34904492e+00
-9.97896373e-01 1.08916104e+00 2.61776537e-01 -1.25347745e+00
-3.50090027e-01 -1.68889984e-01 -2.62134639e-03 1.12208676e+00
-1.91747212e+00 -1.13356316e+00 -7.99187541e-01 6.85485065e-01
8.15766573e-01 2.02447604e-02 4.27893996e-01 1.19192347e-01
-1.83798179e-01 2.08149374e-01 1.93433613e-01 -3.73111159e-01
4.46080416e-01 -9.80382264e-01 2.85145313e-01 7.23640621e-01
1.58312708e-01 2.39425227e-01 5.33390343e-01 -6.09279573e-01
-1.49843800e+00 -1.35175550e+00 6.22865409e-02 -5.81378222e-01
3.92983295e-03 -8.28056931e-02 -9.46353674e-01 5.46787441e-01
-1.27056837e-01 5.88160932e-01 1.13020010e-01 -5.61148107e-01
-2.08129823e-01 -1.41417176e-01 -1.38351774e+00 3.34289849e-01
1.13805985e+00 -5.52108049e-01 -1.96396261e-01 2.67935306e-01
9.33146894e-01 -1.13260055e+00 -1.28828788e+00 6.91606760e-01
3.84245574e-01 -1.40863681e+00 1.55959010e+00 -7.04204955e-04
8.22236478e-01 -5.77386022e-01 -6.17032468e-01 -1.43084168e+00
-3.31088990e-01 -2.71767527e-01 -1.01510584e-01 9.59381640e-01
5.05540557e-02 -5.76603591e-01 4.90643471e-01 2.62052059e-01
-2.61180490e-01 -8.74121845e-01 -9.50874269e-01 -5.17445087e-01
-1.00807086e-01 -1.95204884e-01 7.84988642e-01 9.48731720e-01
-1.02572083e+00 2.13770851e-01 -4.08340931e-01 8.28796029e-01
1.22832441e+00 4.68861252e-01 4.74540114e-01 -1.02165926e+00
-4.68817234e-01 -6.94030849e-03 -9.03434306e-02 -7.94781208e-01
1.40783176e-01 -8.45073998e-01 -9.52665657e-02 -1.63076830e+00
1.19012289e-01 -2.52289534e-01 -1.14998907e-01 -3.10242832e-01
-9.22389850e-02 4.12236959e-01 9.42524988e-04 1.19524531e-01
-2.76123405e-01 7.09255576e-01 1.83609390e+00 1.38148054e-01
-1.95140511e-01 -3.22424144e-01 -4.91442412e-01 6.88594520e-01
4.20454502e-01 -3.20354789e-01 -7.61417449e-01 -6.25136733e-01
5.39164543e-01 6.34325624e-01 5.44285119e-01 -8.91518772e-01
1.41171515e-01 -3.14580113e-01 8.58437061e-01 -1.02035189e+00
6.92745268e-01 -7.70059884e-01 6.99716985e-01 -4.32325266e-02
-1.23210654e-01 1.03693426e-01 -6.99539036e-02 7.05733120e-01
-1.08399048e-01 2.19754055e-01 1.09562814e+00 -5.02781093e-01
-7.45353520e-01 5.34909070e-01 2.49567002e-01 7.81410560e-02
7.53170252e-01 -3.25399041e-01 -3.24984938e-01 -1.37079909e-01
-6.43113613e-01 -3.13776769e-02 5.47387064e-01 4.68074858e-01
1.12587786e+00 -1.39850950e+00 -6.63236260e-01 5.07688522e-01
1.00583784e-01 8.50109458e-01 1.04935300e+00 6.19999230e-01
-4.62355375e-01 1.71494514e-01 -2.50085086e-01 -8.94830525e-01
-1.13580966e+00 6.14490390e-01 6.56981647e-01 -2.39997447e-01
-1.08527136e+00 8.09970021e-01 7.89002538e-01 -5.65467417e-01
-2.38969371e-01 -2.83358067e-01 -4.07538414e-01 -3.58336002e-01
7.03102469e-01 3.72859180e-01 1.30557492e-01 -9.05888021e-01
-1.78444847e-01 1.13215673e+00 7.89571926e-02 -1.91359907e-01
1.64014566e+00 -4.44529712e-01 1.26882698e-02 4.91742760e-01
1.26784086e+00 3.91040109e-02 -1.57076764e+00 -2.30695978e-01
-8.45150054e-01 -7.48762846e-01 7.25931108e-01 -6.56844854e-01
-1.51020133e+00 4.02573526e-01 7.63283551e-01 -5.10290205e-01
1.20915389e+00 -4.43435609e-02 7.25372434e-01 -8.91466439e-02
6.39500916e-01 -7.57743001e-01 9.21322592e-03 1.50130525e-01
1.10990238e+00 -1.31355774e+00 4.82410014e-01 -5.98059237e-01
-5.82073390e-01 1.02888691e+00 7.01689720e-01 -1.78748235e-01
6.15976632e-01 2.09662735e-01 -3.45413238e-02 -3.98710132e-01
-5.52275181e-01 2.16566876e-01 5.89225113e-01 5.84905565e-01
-4.40658815e-02 -1.97110370e-01 3.88510168e-01 2.60863125e-01
-2.56137818e-01 -1.41850725e-01 5.76107979e-01 4.45532352e-01
-5.18068261e-02 -4.26405549e-01 -4.84041721e-01 2.09853336e-01
-2.67265201e-01 -6.88540712e-02 1.99110150e-01 6.14049852e-01
2.10308373e-01 4.62498665e-01 9.47899744e-02 -3.82370591e-01
3.45541894e-01 -4.61153418e-01 7.95100033e-01 -3.97097439e-01
-4.29666787e-01 5.33420779e-02 -2.61121452e-01 -1.04721892e+00
-5.43802440e-01 -4.83670026e-01 -1.13906622e+00 -2.24310830e-01
-2.25254804e-01 -1.65085897e-01 8.43215227e-01 7.52577186e-01
2.64886886e-01 9.20954883e-01 1.01426971e+00 -1.02246416e+00
-3.05504680e-01 -3.46160233e-01 -6.83474779e-01 3.78722884e-02
5.21436810e-01 -7.83395708e-01 -5.65446854e-01 -1.79386735e-01] | [9.788714408874512, -2.6280386447906494] |
e02051ea-5657-42ae-a4b6-bdcacb7859e4 | learning-soccer-juggling-skills-with-layer | null | null | https://dl.acm.org/doi/10.1145/3528233.3530735 | https://www.cs.ubc.ca/~van/papers/2022-SIGGRAPH-juggle/soccer_juggling.pdf | Learning Soccer Juggling Skills with Layer-wise Mixture-of-Experts | Learning physics-based character controllers that can successfully integrate diverse motor skills using a single policy remains a challenging problem. We present a system to learn control policies for multiple soccer juggling skills, based on deep reinforcement learning. We introduce a task-description framework for these skills which facilitates the specification of individual soccer juggling tasks and the transitions between them. Desired motions can be authored using interpolation of crude reference poses or based on motion capture data. We show that a layer-wise mixture-of-experts architecture offers significant benefits. During training, transitions are chosen with the help of an adaptive random walk, in support of efficient learning. We demonstrate foot, head, knee, and chest juggles, foot stalls, the challenging around-the-world trick, as well as robust transitions. Our work provides a significant step towards realizing physics-based characters capable of the precision-based motor skills of human athletes. | ['Michiel Van de Panne', 'Hung Yu Ling', 'Sebastian Starke', 'Zhaoming Xie'] | 2022-07-24 | null | null | null | siggraph-2022-7 | ['humanoid-control'] | ['robots'] | [-2.10101381e-01 -6.07360750e-02 -3.34031790e-01 1.56499311e-01
-6.83881998e-01 -6.03682995e-01 4.24603909e-01 -2.43124872e-01
-7.82605708e-01 8.99023652e-01 -1.80935025e-01 -1.60650700e-01
-2.54891217e-01 -4.03334737e-01 -1.03311861e+00 -6.66978478e-01
-2.33169109e-01 9.63820219e-01 6.25932455e-01 -9.29968834e-01
2.96860576e-01 6.42132044e-01 -1.53891361e+00 1.10240340e-01
8.52596521e-01 3.68436217e-01 6.24311149e-01 1.34441745e+00
3.46281946e-01 9.03186560e-01 -5.54661512e-01 -1.74406767e-01
3.31629544e-01 -3.28234047e-01 -3.65465611e-01 -3.30558419e-02
3.75530452e-01 -2.62286603e-01 -3.06133449e-01 3.76066327e-01
7.68414617e-01 7.98099399e-01 6.34866595e-01 -1.15696430e+00
-8.66014287e-02 3.99258882e-01 -2.11646110e-01 -1.70735925e-01
4.57469970e-01 9.05748248e-01 7.48086452e-01 -2.76422113e-01
7.52569616e-01 1.11957824e+00 7.20805585e-01 9.54681337e-01
-1.02529538e+00 -5.97966194e-01 6.29425794e-02 1.43797994e-01
-9.75633085e-01 -7.96348304e-02 3.97331208e-01 -5.95633268e-01
9.39807773e-01 -1.87771648e-01 1.24287450e+00 1.47825015e+00
7.23768115e-01 1.07652891e+00 8.34926963e-01 -1.70002267e-01
2.99599379e-01 -4.89777744e-01 -4.72834677e-01 7.61105955e-01
6.00189641e-02 2.64432341e-01 -7.70571411e-01 1.17688678e-01
1.22444999e+00 -3.49744618e-01 1.45506784e-01 -6.81515634e-01
-1.05323708e+00 3.96250069e-01 2.05680788e-01 -2.72157460e-01
-5.18275976e-01 9.15622592e-01 2.52860904e-01 1.45276086e-02
-4.15350407e-01 8.59838009e-01 -6.50214791e-01 -7.00947940e-01
-1.00339007e+00 1.25819063e+00 7.77325034e-01 1.06166935e+00
2.24454582e-01 4.41546053e-01 -2.69366920e-01 3.39159369e-01
-1.91209149e-02 4.51914579e-01 1.38819396e-01 -1.54623151e+00
2.81253397e-01 2.20610037e-01 5.29680133e-01 -2.81578332e-01
-5.36420047e-01 -5.12713492e-01 -1.12609588e-01 9.34793651e-01
5.56853294e-01 -4.57481742e-01 -1.05033648e+00 1.55505359e+00
4.24162596e-01 3.92365158e-01 -5.72352074e-02 1.02649915e+00
2.67344683e-01 3.69928539e-01 4.43633050e-01 3.52420300e-01
1.08217287e+00 -9.87161398e-01 -4.57110643e-01 -3.41537267e-01
1.92637190e-01 -3.12085479e-01 1.20858729e+00 7.89365709e-01
-1.50135064e+00 -8.05525839e-01 -9.33086395e-01 4.47009206e-02
8.92198533e-02 2.17710286e-01 4.70024526e-01 2.33000383e-01
-8.13578606e-01 1.12351179e+00 -1.43209851e+00 -7.23770307e-03
-1.04503840e-01 5.77704132e-01 -2.82298893e-01 4.34709489e-01
-1.04874039e+00 1.39970970e+00 3.64376038e-01 -5.82221001e-02
-1.51714993e+00 -7.33902037e-01 -7.89840639e-01 -2.57090926e-01
4.19538051e-01 -8.65156531e-01 1.39633512e+00 -5.97877622e-01
-2.15560579e+00 7.07229555e-01 5.22513509e-01 -4.36837167e-01
8.42693567e-01 -9.01033998e-01 1.01934373e-01 1.51092574e-01
2.60172691e-02 8.57724011e-01 8.01177680e-01 -1.05137599e+00
-6.34468615e-01 1.99284151e-01 4.99633998e-02 5.75952113e-01
1.34180427e-01 -2.24595591e-01 -6.53773904e-01 -4.54385102e-01
-5.37324309e-01 -1.30121493e+00 -6.16000891e-01 6.59064054e-02
-3.64024282e-01 -3.90350781e-02 3.92807990e-01 -6.23641849e-01
8.41979504e-01 -1.69493890e+00 9.24449325e-01 2.23688744e-02
-7.94548616e-02 3.08639377e-01 -7.30094388e-02 5.62947452e-01
3.75778079e-01 -4.59153026e-01 2.70559378e-02 -1.02758914e-01
8.83807465e-02 3.36587727e-01 -1.94732398e-02 1.51021540e-01
2.69750983e-01 9.54446673e-01 -1.17495334e+00 -4.33988214e-01
2.11197346e-01 3.40193331e-01 -7.47286856e-01 5.69239199e-01
-7.04117537e-01 1.15624678e+00 -6.62894964e-01 4.75545496e-01
-1.03774503e-01 2.69717604e-01 2.81034589e-01 2.19945326e-01
-3.68506849e-01 9.01741069e-03 -1.17248893e+00 2.05989742e+00
-4.20188695e-01 1.62302598e-01 3.52199167e-01 -7.27824569e-01
8.93078685e-01 1.99443936e-01 6.08431876e-01 -1.41142309e-01
2.68316567e-01 3.08472037e-01 2.29099199e-01 -5.33495128e-01
7.48785436e-01 -1.08010277e-01 -3.03971916e-01 7.22680753e-03
3.70826453e-01 -8.26338828e-01 5.36922812e-01 -3.17375660e-01
1.06766534e+00 1.42965138e+00 -1.68268979e-02 -2.13857099e-01
1.32578909e-01 4.24369842e-01 4.97777104e-01 8.61850619e-01
-2.57954925e-01 5.37415385e-01 2.81385183e-01 -3.02884072e-01
-1.24807227e+00 -1.33368194e+00 6.11364126e-01 1.38287187e+00
5.51854409e-02 -1.41488925e-01 -7.72516251e-01 -5.98738119e-02
1.78522825e-01 6.21240616e-01 -3.01455498e-01 -2.54876584e-01
-1.36929882e+00 -9.12809595e-02 6.10241294e-01 7.97464013e-01
2.95553833e-01 -1.29364192e+00 -1.29843676e+00 6.06045127e-01
-6.16232632e-03 -1.11682665e+00 -4.07343924e-01 2.86404490e-01
-8.04983616e-01 -1.24510050e+00 -1.02831411e+00 -7.02077091e-01
-2.66115107e-02 -4.15974498e-01 1.15260363e+00 -8.98209661e-02
-3.97031158e-01 5.65784991e-01 -8.54623169e-02 -2.79633582e-01
-5.25914669e-01 8.46389756e-02 3.85939658e-01 -7.54633248e-01
-3.32407296e-01 -6.73874795e-01 -7.37440169e-01 2.47820273e-01
-3.59359860e-01 2.38246188e-01 6.38089776e-01 7.40463674e-01
7.17615902e-01 -3.99709076e-01 6.67313933e-02 -4.16752212e-02
7.91737556e-01 -1.57537371e-01 -5.36927581e-01 2.16715306e-01
8.28516111e-02 8.73787925e-02 6.16211355e-01 -9.26789165e-01
-8.85722339e-01 5.15476227e-01 -2.37681076e-01 -5.05371392e-01
-1.59162223e-01 1.15368059e-02 2.12647855e-01 -2.44006321e-01
9.40669477e-01 2.95987457e-01 3.68229970e-02 -1.93844020e-01
6.74001396e-01 4.71823290e-03 1.01547420e+00 -1.39022374e+00
7.13457763e-01 4.34198417e-02 2.81805724e-01 -6.75357163e-01
-4.61440235e-01 -2.11862519e-01 -8.57907116e-01 -7.29478300e-01
1.17323887e+00 -9.77047145e-01 -1.42143893e+00 5.39172232e-01
-8.06005001e-01 -1.21977615e+00 -4.67540950e-01 7.58010864e-01
-1.33296490e+00 5.10694273e-02 -9.68406558e-01 -8.34431291e-01
-1.29648581e-01 -1.38961780e+00 1.14876235e+00 5.22029638e-01
-5.71154773e-01 -6.73891068e-01 5.10704339e-01 2.03146920e-01
2.63775170e-01 7.13842094e-01 4.84029740e-01 -2.05145136e-01
-4.58516777e-01 -1.29607871e-01 7.99745440e-01 3.72696891e-02
-3.67721975e-01 2.82984763e-01 -1.03532501e-01 -5.61988294e-01
-7.09902644e-01 -9.31057990e-01 3.93020034e-01 5.34043550e-01
8.57275426e-01 2.36947477e-01 -1.44930735e-01 5.39352357e-01
9.76368964e-01 -4.33453824e-03 4.09822494e-01 6.44301951e-01
7.11731434e-01 5.64846158e-01 8.10840130e-01 4.90524411e-01
3.80794227e-01 8.87020707e-01 4.69509959e-01 2.67279267e-01
-2.07758427e-01 -5.04180729e-01 5.54727793e-01 3.81041795e-01
-7.31406569e-01 3.18718664e-02 -9.69140530e-01 4.94042039e-01
-1.87839758e+00 -8.36859643e-01 -2.97363698e-02 1.95105946e+00
8.08060110e-01 4.23674077e-01 5.59892714e-01 -1.56196937e-01
5.53138375e-01 -3.86941105e-01 -9.10723031e-01 -4.34293687e-01
3.34951162e-01 7.10240901e-01 6.12955153e-01 3.72496992e-01
-9.41431940e-01 1.43056393e+00 6.71915102e+00 7.23234951e-01
-9.04137433e-01 -2.81717122e-01 -1.55178055e-01 -1.90590009e-01
1.21940643e-01 -5.07436171e-02 -1.03292024e+00 2.59383023e-01
8.02334487e-01 2.33877555e-01 3.32421005e-01 8.44424427e-01
3.97797316e-01 -5.92528209e-02 -9.38534558e-01 4.53274757e-01
-4.74114150e-01 -1.24818659e+00 -3.74664158e-01 -4.28606391e-01
8.78572226e-01 -2.64836818e-01 1.35657564e-01 7.60202050e-01
1.18470597e+00 -1.09392047e+00 1.13897121e+00 7.68991292e-01
6.72655165e-01 -8.60518694e-01 -2.40492132e-02 6.38352633e-01
-1.16848123e+00 -2.68994212e-01 -2.39065234e-02 -1.37709424e-01
4.22715157e-01 -1.71241924e-01 -5.20347774e-01 3.51423323e-01
4.34780210e-01 4.01537538e-01 -5.66267706e-02 1.06410515e+00
-6.49444520e-01 4.82756406e-01 -2.98263788e-01 -3.52700859e-01
4.01100844e-01 -1.75001845e-01 6.52414858e-01 1.09321213e+00
2.81623513e-01 8.59790966e-02 7.47571826e-01 7.27905273e-01
5.66093266e-01 -1.55236185e-01 -2.23189905e-01 2.63139158e-02
2.11229622e-01 1.11418211e+00 -5.37968576e-01 -2.02636480e-01
4.55671191e-01 1.01801550e+00 4.62534338e-01 2.70641804e-01
-1.06141138e+00 -2.82766968e-01 9.23906267e-01 2.04335183e-01
1.34500608e-01 -8.79377246e-01 -1.67057421e-02 -9.83188391e-01
-1.76053554e-01 -1.05325377e+00 -9.03434977e-02 -8.19674075e-01
-6.38436735e-01 1.28430367e-01 2.94713199e-01 -1.27455854e+00
-6.32769883e-01 -6.32570207e-01 -8.13077867e-01 6.14439487e-01
-9.59032118e-01 -1.05131924e+00 -2.01259732e-01 4.93266761e-01
6.09874249e-01 -1.43501043e-01 7.62843132e-01 -2.76859049e-02
-3.01328987e-01 2.93178529e-01 -1.68135226e-01 -7.04814196e-02
7.22669959e-01 -1.35335338e+00 6.20488584e-01 4.08955365e-01
-2.95891404e-01 3.26579601e-01 1.23422563e+00 -8.77257884e-01
-1.45812678e+00 -6.60428584e-01 1.64137006e-01 -4.31129456e-01
6.62377596e-01 -1.57253772e-01 -5.63134134e-01 5.30280471e-01
-8.18015486e-02 -2.73532003e-01 1.96461290e-01 -2.51634717e-01
3.09729725e-01 1.82350576e-01 -6.93980038e-01 1.15496159e+00
9.45585370e-01 -3.66243385e-02 -6.89963698e-01 3.68852973e-01
3.42734963e-01 -1.12983620e+00 -6.98053598e-01 3.04673433e-01
9.49889660e-01 -6.73084199e-01 1.17215598e+00 -1.03499198e+00
7.16724217e-01 -2.96829253e-01 3.80431563e-01 -1.47198534e+00
-3.32850695e-01 -8.16455185e-01 -3.58000904e-01 3.58913779e-01
-2.97496226e-02 2.94356912e-01 1.15016532e+00 2.95478225e-01
-3.50029349e-01 -6.84836745e-01 -7.25539625e-01 -8.52562964e-01
4.09920752e-01 -3.78419012e-01 6.28294349e-02 3.68416369e-01
-1.60600580e-02 -1.09122783e-01 -8.67119610e-01 1.39566651e-02
7.27431357e-01 -2.19305679e-01 1.21024323e+00 -8.12055171e-01
-9.55244303e-01 -5.44797003e-01 -3.38375121e-01 -1.18860233e+00
2.93893874e-01 -3.94648850e-01 5.03349960e-01 -1.58812189e+00
-2.79166698e-01 -2.16264769e-01 6.78115040e-02 4.22087580e-01
-3.31159800e-01 -8.07152167e-02 4.56393778e-01 5.56342828e-04
-4.77922708e-01 4.08572555e-01 1.92529607e+00 2.08354816e-01
-4.53237265e-01 2.50234365e-01 -6.32940000e-03 6.46803737e-01
9.69969153e-01 -3.20081800e-01 -4.60792631e-01 -1.99929535e-01
2.05879822e-01 7.50564158e-01 4.10824418e-01 -1.58850706e+00
3.43922436e-01 -5.77530980e-01 4.01137501e-01 -3.31700653e-01
6.38732374e-01 -2.50921667e-01 2.69154578e-01 1.09970105e+00
-5.76031685e-01 8.02763104e-02 2.37470806e-01 5.51250875e-01
2.30925560e-01 1.03748627e-01 9.07546818e-01 -4.44349825e-01
-9.09838021e-01 9.40753222e-02 -8.17277372e-01 1.85306162e-01
1.30378175e+00 -4.24189478e-01 2.44886890e-01 -2.95844585e-01
-1.15829325e+00 6.41422093e-01 2.97155499e-01 3.68701786e-01
5.19075692e-01 -9.75142360e-01 -7.40436077e-01 -1.89962313e-01
-2.43577421e-01 -4.32383008e-02 2.33378500e-01 5.55449128e-01
-1.02622473e+00 -1.25355840e-01 -1.01518214e+00 -5.67549467e-01
-1.04523289e+00 9.81749892e-02 5.20616174e-01 -5.81510007e-01
-8.23540747e-01 8.47143292e-01 -2.65750557e-01 -6.30160689e-01
1.22624047e-01 -1.18966155e-01 -2.70744890e-01 -6.27325416e-01
2.27458067e-02 4.32430774e-01 -3.66993576e-01 -9.02310833e-02
-1.31381854e-01 7.70281613e-01 3.17030907e-01 -4.69683409e-01
1.10164320e+00 3.36518377e-01 5.77031434e-01 3.60261708e-01
1.88466147e-01 -2.04425469e-01 -2.24267125e+00 4.16255116e-01
-7.63483942e-02 -6.76019937e-02 -5.66631675e-01 -7.54990280e-01
-4.95262593e-01 8.70710015e-01 3.51859570e-01 -7.57062137e-01
6.05771601e-01 -4.46001559e-01 7.98138082e-01 5.52224278e-01
6.71567023e-01 -1.54414845e+00 5.77675402e-01 8.19370329e-01
8.64484668e-01 -7.99446881e-01 -1.08423186e-02 7.75945038e-02
-1.04492557e+00 1.27993989e+00 1.08793843e+00 -9.83298182e-01
7.88308829e-02 6.90347672e-01 -1.17878411e-02 1.15350775e-01
-9.19864297e-01 -3.60344946e-01 3.34073156e-01 8.94607365e-01
2.95980304e-01 1.48372099e-01 -2.74446934e-01 4.01390284e-01
-3.00382733e-01 6.99853972e-02 4.76908654e-01 1.36049914e+00
-8.18868995e-01 -1.27709913e+00 -4.11537051e-01 -2.01739334e-02
-2.97871858e-01 3.00554037e-01 -1.56078324e-01 1.17752087e+00
2.94392735e-01 3.37973148e-01 -1.87534034e-01 -4.05209124e-01
6.24592423e-01 4.18839306e-02 1.21891093e+00 -6.48940146e-01
-9.60184872e-01 -6.93890303e-02 1.04902104e-01 -8.08071554e-01
3.06625273e-02 -4.91123259e-01 -1.53374016e+00 -2.70059109e-01
1.62172973e-01 -1.43363159e-02 5.13208568e-01 8.09794903e-01
-3.99367958e-02 9.67756331e-01 -9.37206112e-03 -1.60752356e+00
-8.99698734e-01 -7.45448053e-01 -4.52173501e-01 3.09584111e-01
1.35149270e-01 -1.06754780e+00 1.71950847e-01 8.60725865e-02] | [4.784039497375488, 0.8927969932556152] |
d53a568a-8c5e-4d56-8a07-0adc0dbf2b43 | towards-ghost-free-shadow-removal-via-dual | 1911.08718 | null | https://arxiv.org/abs/1911.08718v2 | https://arxiv.org/pdf/1911.08718v2.pdf | Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN | Shadow removal is an essential task for scene understanding. Many studies consider only matching the image contents, which often causes two types of ghosts: color in-consistencies in shadow regions or artifacts on shadow boundaries. In this paper, we tackle these issues in two ways. First, to carefully learn the border artifacts-free image, we propose a novel network structure named the dual hierarchically aggregation network~(DHAN). It contains a series of growth dilated convolutions as the backbone without any down-samplings, and we hierarchically aggregate multi-context features for attention and prediction, respectively. Second, we argue that training on a limited dataset restricts the textural understanding of the network, which leads to the shadow region color in-consistencies. Currently, the largest dataset contains 2k+ shadow/shadow-free image pairs. However, it has only 0.1k+ unique scenes since many samples share exactly the same background with different shadow positions. Thus, we design a shadow matting generative adversarial network~(SMGAN) to synthesize realistic shadow mattings from a given shadow mask and shadow-free image. With the help of novel masks or scenes, we enhance the current datasets using synthesized shadow images. Experiments show that our DHAN can erase the shadows and produce high-quality ghost-free images. After training on the synthesized and real datasets, our network outperforms other state-of-the-art methods by a large margin. The code is available: http://github.com/vinthony/ghost-free-shadow-removal/ | ['Chi-Man Pun', 'Xiaodong Cun', 'Cheng Shi'] | 2019-11-20 | null | null | null | null | ['shadow-removal'] | ['computer-vision'] | [ 7.38525927e-01 5.03064431e-02 2.74961442e-01 -4.92436975e-01
-4.00136739e-01 -4.57672626e-01 3.72246027e-01 -8.21431279e-01
2.65177456e-03 7.55512834e-01 4.10322919e-02 -4.77822751e-01
4.38482553e-01 -8.08082283e-01 -1.08606291e+00 -1.00349247e+00
4.26238358e-01 4.61820513e-02 5.49742639e-01 -2.67181635e-01
2.00055391e-02 4.00721788e-01 -1.40307295e+00 5.43777943e-01
1.16300678e+00 9.48432803e-01 6.67768955e-01 7.66658664e-01
-8.86641592e-02 8.55219722e-01 -8.18010688e-01 -4.03888077e-01
5.51563323e-01 -6.31714046e-01 -3.49867791e-01 9.63893235e-02
7.19082892e-01 -9.19653237e-01 -6.43338263e-01 1.00756228e+00
4.19907451e-01 -3.44995260e-02 3.44965249e-01 -1.47611833e+00
-9.35810030e-01 2.92288512e-01 -5.56040347e-01 -1.21450141e-01
-1.64393298e-02 3.49925816e-01 6.01770222e-01 -9.07961607e-01
3.70417118e-01 1.39085007e+00 6.02899790e-01 5.49452245e-01
-9.82614577e-01 -1.16219938e+00 2.79701710e-01 2.94176459e-01
-1.24845243e+00 -3.79005373e-01 9.40540671e-01 6.26225071e-03
2.99440444e-01 5.05279422e-01 6.43573403e-01 1.47534609e+00
3.35390985e-01 9.56383765e-01 1.68317628e+00 -2.96688318e-01
2.46836543e-02 7.14014098e-02 -2.97174633e-01 8.39403868e-01
1.90690935e-01 2.38781542e-01 -4.69714791e-01 9.84510034e-02
9.15230930e-01 1.92367807e-01 -7.54747629e-01 -1.86287180e-01
-1.09560800e+00 5.09158134e-01 6.41209722e-01 -1.18764184e-01
6.89593926e-02 3.07277262e-01 -1.66758955e-01 1.78906754e-01
3.15451205e-01 1.87073261e-01 -3.80315602e-01 5.16300917e-01
-7.58265197e-01 1.40298963e-01 5.29080629e-01 1.11230636e+00
9.32965100e-01 2.43850455e-01 -1.69685110e-01 6.42285287e-01
6.72756135e-02 9.76556003e-01 1.66772515e-01 -1.00694656e+00
3.40265900e-01 3.17239851e-01 1.93527430e-01 -1.10006523e+00
-6.12571463e-02 -3.29598397e-01 -1.09154093e+00 4.66261625e-01
3.78799707e-01 -2.04614669e-01 -1.36720967e+00 1.79014421e+00
3.06780368e-01 5.65266192e-01 -1.22141908e-03 8.84388566e-01
1.00382900e+00 7.36869752e-01 -4.19201702e-01 -5.98272681e-02
1.14705825e+00 -1.45016491e+00 -8.64814281e-01 -5.02352953e-01
1.16377696e-02 -9.32688117e-01 1.45487261e+00 3.21564913e-01
-7.93136477e-01 -7.03661978e-01 -1.29425383e+00 -1.00455016e-01
-4.22067285e-01 1.09408312e-02 7.14124382e-01 6.67887151e-01
-9.16006982e-01 4.83040571e-01 -4.71973360e-01 1.51362503e-02
4.64776397e-01 1.14176489e-01 5.45490459e-02 -4.87141609e-01
-1.19033158e+00 6.75005078e-01 1.80165932e-01 3.70345891e-01
-1.05658066e+00 -8.36854160e-01 -7.14042783e-01 -1.62339747e-01
7.39524662e-01 -5.51147282e-01 1.10048020e+00 -1.37242460e+00
-1.42024386e+00 5.68818629e-01 -1.22600816e-01 -6.11591451e-02
8.08332682e-01 -3.80036145e-01 -5.30716538e-01 -1.42289132e-01
2.38123704e-02 4.91466761e-01 1.22130501e+00 -1.97556424e+00
-5.24995506e-01 6.99064732e-02 2.06311166e-01 3.29228997e-01
4.16487716e-02 -2.39873916e-01 -8.02757084e-01 -9.69466388e-01
-2.53270343e-02 -9.40258384e-01 -1.39503151e-01 1.93042591e-01
-7.93168604e-01 6.18101776e-01 1.22258687e+00 -8.58633339e-01
9.61515069e-01 -2.15702510e+00 -2.18005762e-01 7.79506639e-02
2.69067705e-01 2.09569529e-01 -2.81374276e-01 1.52086854e-01
4.51127999e-02 -1.05715647e-01 -6.01925433e-01 -4.80633914e-01
-1.74643651e-01 5.02905369e-01 -7.42983043e-01 2.96215236e-01
2.91602989e-03 1.00113702e+00 -8.14443052e-01 -4.22985703e-01
2.85179377e-01 5.25448382e-01 -2.19362006e-01 5.50047517e-01
-3.60048175e-01 5.36695480e-01 -2.70241320e-01 8.22216928e-01
1.19675112e+00 -1.23481326e-01 1.79805726e-01 -4.19887036e-01
1.09706864e-01 -1.01879746e-01 -1.13193071e+00 1.49298787e+00
-5.29773116e-01 9.52964604e-01 1.59275770e-01 -3.49846154e-01
6.81196630e-01 -1.74557716e-01 7.58533329e-02 -8.83608997e-01
1.09145038e-01 2.08779424e-01 -1.00798383e-01 -2.45971873e-01
4.56364870e-01 1.62974253e-01 1.54525533e-01 3.29477489e-01
-4.00442898e-01 -1.78606272e-01 -3.59988213e-01 9.79484469e-02
1.10808647e+00 1.11252397e-01 -1.41159773e-01 -1.69568211e-01
2.24907294e-01 -2.91952610e-01 7.34728038e-01 9.29761887e-01
-2.15334855e-02 1.05827606e+00 3.32133532e-01 -3.68774742e-01
-9.62275863e-01 -1.22124660e+00 4.43776585e-02 9.93639529e-01
7.85430908e-01 -1.14820339e-01 -8.81953776e-01 -6.40297771e-01
-8.95351991e-02 7.77590334e-01 -7.90942430e-01 -1.18613705e-01
-7.71411955e-01 -7.71900892e-01 5.64349592e-01 3.62270296e-01
1.05346608e+00 -1.28217232e+00 -6.56397581e-01 -1.82372361e-01
-2.67915517e-01 -1.20099437e+00 -5.96064448e-01 1.08144678e-01
-3.04342538e-01 -1.14299726e+00 -7.83963561e-01 -5.88559568e-01
7.58246243e-01 7.47521222e-01 1.24894810e+00 3.45672876e-01
-2.69539237e-01 -9.86201763e-02 -3.26697826e-01 -5.15355051e-01
-4.52304214e-01 -3.44267815e-01 -2.52557516e-01 3.18487674e-01
-3.41041714e-01 -6.78800941e-01 -1.11912918e+00 4.64754492e-01
-1.13709426e+00 7.79550970e-01 8.88881922e-01 8.65054190e-01
3.86767715e-01 5.55701330e-02 2.56543513e-02 -1.21364748e+00
2.43806675e-01 -1.43650517e-01 -6.34538651e-01 4.22394037e-01
-5.90255678e-01 -1.44267440e-01 8.55119705e-01 -5.14020562e-01
-1.41599035e+00 -3.10353208e-02 1.67141244e-01 -7.11797178e-01
-2.14597344e-01 -2.53537476e-01 -7.04962730e-01 -3.90758723e-01
4.20665801e-01 4.04057354e-01 -4.06678081e-01 -3.45136613e-01
5.58255136e-01 3.20825309e-01 7.13708818e-01 -4.30536151e-01
1.28295529e+00 7.02969372e-01 -1.17975704e-01 -6.92377985e-01
-1.01861298e+00 8.04500431e-02 -4.02881533e-01 -2.49873698e-01
6.55931056e-01 -7.63393104e-01 -3.96286339e-01 9.76835847e-01
-1.09905100e+00 -1.11314499e+00 -8.44986066e-02 -1.52306572e-01
-3.15477192e-01 4.98598874e-01 -3.86357665e-01 -5.90282917e-01
-2.03337640e-01 -1.23207414e+00 1.06622112e+00 3.07294875e-01
4.35936540e-01 -5.48263490e-01 -2.56660730e-01 3.22952360e-01
4.21077102e-01 4.72646534e-01 9.30227578e-01 2.33341213e-02
-1.09973955e+00 3.83139700e-01 -6.79112017e-01 5.10887682e-01
3.00263733e-01 -1.34115994e-01 -1.25566757e+00 -2.42208928e-01
-2.71556620e-02 -2.04574868e-01 1.10929251e+00 2.92624384e-01
1.65453494e+00 -4.38145101e-01 -1.68263972e-01 1.15994823e+00
1.51778209e+00 3.17183971e-01 9.60335732e-01 1.81143165e-01
1.20820820e+00 3.91666740e-01 7.15672433e-01 2.37537012e-01
1.62866056e-01 5.41533649e-01 6.37845933e-01 -6.93795681e-01
-6.51844621e-01 -1.93058819e-01 3.75828594e-01 3.49700212e-01
4.78419326e-02 -7.01519847e-01 -5.70438743e-01 3.26943815e-01
-1.75089860e+00 -7.06306815e-01 -2.42682591e-01 1.96861172e+00
7.94226825e-01 5.96974157e-02 -4.17394847e-01 -1.80366367e-01
6.46053076e-01 6.71298385e-01 -8.53264689e-01 -1.18168397e-02
-5.12787402e-01 2.87681520e-01 8.79795194e-01 7.28609800e-01
-8.68495047e-01 1.24405599e+00 5.22792435e+00 1.03493655e+00
-1.03232718e+00 5.84109463e-02 8.24214339e-01 6.92083016e-02
-5.44156373e-01 9.46820602e-02 -5.67715406e-01 7.67649889e-01
3.28866899e-01 3.97592485e-01 7.25109637e-01 5.54876089e-01
1.05204387e-02 -2.77760655e-01 -7.48097301e-01 9.98924375e-01
3.77610981e-01 -1.24986660e+00 1.45635018e-02 -5.10744564e-02
1.01407361e+00 -1.55348703e-01 2.45425776e-01 1.59250051e-01
3.71248156e-01 -1.00936449e+00 8.44825447e-01 4.83771324e-01
1.07399762e+00 -5.42276382e-01 5.67499518e-01 3.21910717e-02
-1.15811133e+00 4.48442511e-02 -2.49815598e-01 2.34244689e-01
6.10500276e-02 6.60442293e-01 -6.46919608e-01 5.57044148e-01
8.72368336e-01 3.19081783e-01 -7.23061621e-01 7.41519511e-01
-4.65256006e-01 4.74023432e-01 -1.40105948e-01 3.18349004e-01
1.37647614e-02 -2.96137869e-01 2.86168665e-01 1.18605518e+00
2.21993461e-01 2.61246681e-01 1.56359524e-01 9.40025210e-01
-2.00942144e-01 -4.34932083e-01 -5.08843362e-01 4.29043621e-01
4.57317591e-01 1.17649603e+00 -8.08986127e-01 -4.05632496e-01
-4.06602144e-01 1.69909728e+00 -3.93184572e-02 7.29714096e-01
-1.30728245e+00 -3.58949363e-01 7.15625882e-01 9.32460930e-03
2.19121769e-01 2.29768688e-03 -3.25852424e-01 -1.20181382e+00
1.44089729e-01 -1.16281557e+00 -1.25827760e-01 -1.17286432e+00
-1.08717775e+00 6.07397318e-01 -8.28884989e-02 -9.55975771e-01
3.09632421e-01 -6.34082019e-01 -7.34340906e-01 7.99163043e-01
-1.76378906e+00 -1.44898641e+00 -1.03995192e+00 7.78872907e-01
7.38427699e-01 1.50862813e-01 5.64995348e-01 2.48487502e-01
-6.01325810e-01 6.88630819e-01 2.46351734e-01 1.48047984e-01
1.04834235e+00 -1.22566199e+00 6.33609593e-01 1.10360932e+00
-1.92346573e-01 2.27896139e-01 7.46759295e-01 -7.56371498e-01
-1.18037164e+00 -1.32333958e+00 2.40250647e-01 -3.79981667e-01
3.93397659e-01 -7.54912972e-01 -1.09129584e+00 6.20928824e-01
3.80787194e-01 4.17275652e-02 2.31190979e-01 -4.73128438e-01
-4.80604559e-01 -3.95018965e-01 -8.72657657e-01 1.00902843e+00
1.32589591e+00 -4.72711772e-01 -1.34577438e-01 5.14813483e-01
1.12669635e+00 -7.51024604e-01 -3.36219698e-01 6.08499706e-01
6.34143054e-01 -1.47610152e+00 1.09393609e+00 -8.55938569e-02
6.19489789e-01 -4.91149664e-01 -3.57311249e-01 -1.05667508e+00
-4.43702228e-02 -7.56804764e-01 -1.96697265e-01 1.19255900e+00
2.56887883e-01 -6.76668406e-01 7.85602808e-01 3.81239742e-01
-4.94545072e-01 -9.63325620e-01 -4.20250773e-01 -6.31341755e-01
-2.53668904e-01 -3.33283931e-01 8.39816988e-01 7.94179082e-01
-1.17225611e+00 1.17087647e-01 -8.55265677e-01 4.84396607e-01
8.09767723e-01 6.43645525e-01 1.09199810e+00 -6.66645467e-01
-5.37063241e-01 -1.65788338e-01 3.22030187e-01 -1.11706340e+00
4.92146760e-02 -2.69030452e-01 3.13505679e-01 -1.22557020e+00
2.76147962e-01 -6.21222675e-01 -2.56338507e-01 6.09713495e-01
-4.31240827e-01 5.05020201e-01 3.25366884e-01 1.62780836e-01
-3.98195535e-01 6.84010804e-01 1.63450170e+00 -6.42327592e-02
-1.52809590e-01 4.20025624e-02 -5.69139004e-01 8.25897574e-01
8.49109054e-01 -2.73870796e-01 -5.64962149e-01 -4.41137344e-01
-9.49253440e-02 -1.79882213e-01 7.46817768e-01 -9.18393910e-01
-1.71039745e-01 -5.01538813e-01 6.78538501e-01 -7.21027315e-01
6.48085713e-01 -8.48841548e-01 3.64738852e-01 4.66209918e-01
-1.31901531e-02 -1.70502678e-01 1.52753621e-01 6.66530848e-01
1.07207231e-01 1.94342300e-01 8.73454034e-01 -2.09658608e-01
-9.07461286e-01 3.16959858e-01 -3.69147747e-05 -1.10599928e-01
8.62465203e-01 -2.67290592e-01 -7.42268980e-01 -4.54908669e-01
-8.41351748e-02 4.42027636e-02 7.95450687e-01 3.92530948e-01
7.75012434e-01 -1.11918342e+00 -4.55821604e-01 4.68374372e-01
-1.26878217e-01 3.68234187e-01 5.56651294e-01 5.28753757e-01
-7.18475223e-01 -5.37144057e-02 -2.59037077e-01 -3.03175926e-01
-1.28466010e+00 5.17501652e-01 2.87863940e-01 -4.83401716e-02
-7.32951224e-01 9.22464252e-01 1.11962211e+00 -3.06029379e-01
2.83611864e-01 -4.08754855e-01 4.02793407e-01 -4.66413528e-01
3.75242770e-01 1.87354177e-01 -1.12559445e-01 -3.97833377e-01
-7.27768913e-02 4.31360871e-01 3.29874642e-02 3.55257876e-02
9.85055804e-01 -1.12674527e-01 -5.69323078e-02 2.06823602e-01
1.00311804e+00 2.52491653e-01 -1.75857830e+00 -1.36116281e-01
-7.62640536e-01 -8.82062554e-01 -1.25477597e-01 -9.65452433e-01
-1.31937170e+00 6.81654453e-01 7.18381822e-01 -5.87734766e-02
1.50543833e+00 -2.51670331e-01 1.10993350e+00 2.40373120e-01
1.11834586e-01 -7.68106163e-01 3.06079239e-01 3.74620974e-01
1.09413648e+00 -1.25662410e+00 5.97271919e-02 -7.27002263e-01
-6.11609578e-01 7.21558809e-01 9.47875798e-01 -1.99063659e-01
4.41754758e-01 4.08749908e-01 3.07425857e-01 -3.19919102e-02
-4.22291517e-01 -2.10757881e-01 2.44236797e-01 7.33132243e-01
-1.77966937e-01 1.49121493e-01 2.27304906e-01 3.81151438e-01
-3.10373157e-01 -5.58044970e-01 5.56571722e-01 7.67715573e-01
-2.90942848e-01 -1.04387784e+00 -5.90490043e-01 2.91566610e-01
-1.40120924e-01 -4.49212432e-01 -7.09375978e-01 9.99255061e-01
4.77319688e-01 8.63122463e-01 -1.81726694e-01 -6.05285823e-01
9.49957967e-02 -3.74767870e-01 4.47811633e-01 -3.26529056e-01
-2.01783657e-01 8.36870223e-02 -7.26257041e-02 -8.66864622e-01
-1.88078970e-01 -2.82695204e-01 -1.01341581e+00 -6.19430780e-01
-3.44110459e-01 -3.98058653e-01 4.02095556e-01 7.69362688e-01
2.56524354e-01 9.03306484e-01 7.05089808e-01 -1.01942241e+00
-6.95965290e-02 -6.45817697e-01 -5.67843616e-01 3.63239050e-01
6.36329532e-01 -6.28222287e-01 -3.87203723e-01 5.28311431e-02] | [10.84699821472168, -4.0940728187561035] |
3206dbac-32ee-446d-ac90-e9722c73f82c | partially-shuffling-the-training-data-to-1 | 1903.04167 | null | http://arxiv.org/abs/1903.04167v2 | http://arxiv.org/pdf/1903.04167v2.pdf | Partially Shuffling the Training Data to Improve Language Models | Although SGD requires shuffling the training data between epochs, currently
none of the word-level language modeling systems do this. Naively shuffling all
sentences in the training data would not permit the model to learn
inter-sentence dependencies. Here we present a method that partially shuffles
the training data between epochs. This method makes each batch random, while
keeping most sentence ordering intact. It achieves new state of the art results
on word-level language modeling on both the Penn Treebank and WikiText-2
datasets. | ['Ofir Press'] | 2019-03-11 | partially-shuffling-the-training-data-to | null | null | arxiv-2019-3 | ['sentence-ordering'] | ['natural-language-processing'] | [-2.53282309e-01 2.92864501e-01 -3.02942663e-01 -9.04492795e-01
-6.77442729e-01 -7.27528274e-01 3.22999418e-01 2.97624767e-01
-7.86763906e-01 8.89934301e-01 3.99958193e-01 -1.06346262e+00
2.56066710e-01 -6.23970807e-01 -5.54594576e-01 -2.19318315e-01
-1.82698891e-01 7.14231372e-01 1.51349440e-01 -3.85390073e-01
-5.33184782e-02 2.19073713e-01 -7.44611621e-01 6.41149461e-01
6.88535750e-01 1.78020477e-01 5.60333729e-01 8.03485572e-01
-7.76743591e-01 9.46031511e-01 -6.51261091e-01 -5.65438986e-01
6.19244352e-02 -3.09701413e-01 -1.01983666e+00 -1.40689045e-01
4.35392886e-01 -7.24743381e-02 -5.17045319e-01 7.59924769e-01
2.81033248e-01 1.97620898e-01 1.56692579e-01 -6.87476397e-01
-6.10218406e-01 1.31718326e+00 -1.72401682e-01 5.83063006e-01
1.07567951e-01 -3.14174086e-01 1.30397701e+00 -6.45442188e-01
5.61546028e-01 1.33782530e+00 5.36782980e-01 8.62347424e-01
-1.47214711e+00 -5.23224890e-01 6.11916184e-01 -1.18663318e-01
-9.62853074e-01 -4.50139135e-01 8.04645896e-01 -1.99326754e-01
1.78567731e+00 1.04669519e-01 5.19307613e-01 8.69883239e-01
4.19878185e-01 9.58310962e-01 8.86527002e-01 -8.24913025e-01
4.26571779e-02 5.36201037e-02 1.03699708e+00 5.61990798e-01
2.98461646e-01 -3.86292994e-01 -7.63368428e-01 -6.33451268e-02
3.21832180e-01 -3.33356529e-01 1.34578601e-01 -2.76823845e-02
-7.91062355e-01 7.14732647e-01 -1.46336839e-01 6.34185493e-01
-1.78553671e-01 -3.47123062e-03 6.20103657e-01 6.17503047e-01
8.99562180e-01 3.17886204e-01 -1.22896242e+00 -2.68926412e-01
-1.15167987e+00 1.53061971e-01 9.79400635e-01 7.72996306e-01
6.01063907e-01 1.13226078e-01 -2.43114270e-02 1.08671618e+00
3.19835454e-01 1.60512738e-02 8.03025246e-01 -4.61232245e-01
9.28655088e-01 3.33055735e-01 -2.27442890e-01 -4.53550875e-01
-4.97678936e-01 -3.40581864e-01 -3.74714255e-01 -1.81608573e-01
3.32479864e-01 -5.63766360e-01 -9.62926984e-01 1.91864002e+00
-2.94698160e-02 1.81203242e-02 3.79089147e-01 8.40069726e-02
9.11208272e-01 7.46507883e-01 4.59767818e-01 -1.53137416e-01
1.18040037e+00 -9.90458012e-01 -8.74293685e-01 -1.11416686e+00
1.26857388e+00 -5.41099846e-01 1.24428165e+00 1.90213218e-01
-1.44166625e+00 -5.93137443e-01 -1.08828998e+00 -2.65825629e-01
-4.13516581e-01 -9.13837701e-02 7.83109725e-01 6.79008484e-01
-1.22945499e+00 4.61872667e-01 -1.17585146e+00 -1.26071393e-01
-3.80186252e-02 3.83860111e-01 -5.08445382e-01 2.31520291e-02
-1.66103196e+00 1.24189436e+00 6.77217245e-01 1.25929946e-02
-4.09276932e-01 -9.17949915e-01 -1.25666559e+00 1.18770689e-01
-3.04794371e-01 -4.29744869e-01 1.53628254e+00 -4.31680351e-01
-1.41928291e+00 1.17598081e+00 -6.80731654e-01 -7.51299322e-01
-5.39849512e-03 -4.01488632e-01 -3.56637627e-01 -6.91079021e-01
-2.46353298e-01 6.58164978e-01 2.00265735e-01 -8.96145165e-01
-4.75458145e-01 -3.82623911e-01 -1.59291893e-01 2.94639081e-01
-4.05809939e-01 3.72695684e-01 -2.65379936e-01 -6.41372085e-01
-1.15435220e-01 -7.49911010e-01 -3.79312843e-01 -8.96082044e-01
-3.10529560e-01 -5.78633189e-01 2.60416061e-01 -8.93217564e-01
1.54788816e+00 -2.04378080e+00 -5.09174690e-02 -3.21763337e-01
-2.55787671e-01 4.69149441e-01 -5.26171207e-01 6.15256488e-01
-3.29928815e-01 3.33984852e-01 -2.18749568e-01 -1.10679162e+00
7.58266449e-02 8.30042481e-01 -3.42258871e-01 1.64272234e-01
7.01493174e-02 1.02271652e+00 -7.52069294e-01 -4.42726821e-01
2.38908142e-01 2.47841716e-01 -5.99665880e-01 3.56745452e-01
-3.00349474e-01 5.28939441e-02 -5.18267825e-02 -1.03083305e-01
7.62494385e-01 1.10783704e-01 7.03429818e-01 3.80717158e-01
-1.13588817e-01 1.49822628e+00 -7.67633855e-01 1.92650700e+00
-7.36996949e-01 7.20662117e-01 -4.82464209e-02 -9.87827361e-01
9.13620114e-01 4.51773345e-01 1.82070762e-01 -5.11454761e-01
-2.51842976e-01 1.83256716e-02 2.21455768e-01 -2.41473958e-01
4.16787922e-01 -5.78721941e-01 -3.68655503e-01 4.18708801e-01
4.77399617e-01 -3.64037991e-01 3.47925752e-01 3.42210472e-01
1.23438764e+00 -1.83164507e-01 1.90128148e-01 -4.60942328e-01
2.77233869e-01 -3.80009450e-02 5.92353344e-01 7.11208701e-01
6.11126386e-02 3.48880053e-01 4.38820541e-01 -6.28338218e-01
-8.27480197e-01 -1.16989148e+00 -1.49202377e-01 1.54113793e+00
-5.20715296e-01 -8.59086215e-01 -7.63756096e-01 -9.55733240e-01
-1.64338537e-02 1.43349087e+00 -5.18283844e-01 -1.73495132e-02
-9.43069458e-01 -9.84351277e-01 6.26054347e-01 4.19698954e-01
1.06296524e-01 -1.33260357e+00 2.32522637e-01 5.12440860e-01
-2.29257405e-01 -1.04809618e+00 -4.95951533e-01 8.43999267e-01
-1.02072716e+00 -4.45761412e-01 -2.84573268e-02 -1.28139448e+00
6.01866841e-01 -8.31395239e-02 1.59946692e+00 1.52032580e-02
1.90067172e-01 -3.30620378e-01 -2.12226585e-01 -3.43476892e-01
-6.64150000e-01 5.53995788e-01 -3.56907174e-02 -6.85334980e-01
9.44520772e-01 -3.95381629e-01 5.76929115e-02 -3.06816399e-01
-6.80177748e-01 -2.68786363e-02 2.60272145e-01 6.57132506e-01
2.59706080e-01 -4.91637224e-03 5.45343220e-01 -1.38764119e+00
9.51484978e-01 -4.33383226e-01 -3.15596342e-01 3.14312130e-01
-2.75335133e-01 3.47603053e-01 6.94593728e-01 -1.90420300e-01
-1.18964863e+00 -6.45512491e-02 -6.95135951e-01 3.80365700e-01
-3.04823220e-01 7.61479378e-01 -2.17426375e-01 4.27945405e-01
3.22651118e-01 2.69429386e-01 -4.01879191e-01 -1.01695621e+00
4.09263819e-01 5.82495689e-01 2.08199069e-01 -3.99983734e-01
4.65797096e-01 -2.32310742e-01 -6.14005327e-01 -8.95054877e-01
-1.31893635e+00 -4.60625708e-01 -1.10851681e+00 4.92487967e-01
8.30163717e-01 -8.31674397e-01 -2.39309579e-01 3.50684255e-01
-1.67297733e+00 -8.54177415e-01 -4.06289667e-01 4.29965973e-01
-1.47247478e-01 2.13392675e-01 -1.01335120e+00 -5.94978273e-01
-3.49878341e-01 -7.37152398e-01 6.43484294e-01 -2.33760759e-01
-6.88672781e-01 -1.61919892e+00 6.04905307e-01 1.77857652e-01
1.76608607e-01 -5.28598130e-01 1.08935499e+00 -1.21679699e+00
2.29396120e-01 -1.83532193e-01 3.21397662e-01 6.95473015e-01
3.75329643e-01 -1.83724895e-01 -6.26228273e-01 -1.47943750e-01
2.65472293e-01 -3.21495235e-01 8.16151500e-01 4.96005684e-01
9.25508738e-01 -2.67971098e-01 -2.00601339e-01 4.01271164e-01
1.10379124e+00 1.56804398e-01 3.42809141e-01 3.68699789e-01
5.41983902e-01 6.87251925e-01 1.73737183e-01 9.55593362e-02
6.68043733e-01 2.56463468e-01 -4.59728949e-02 -1.87108353e-01
-1.01218976e-01 -4.04994100e-01 6.87451780e-01 1.48488367e+00
7.27262795e-01 -4.64525342e-01 -1.18747449e+00 7.70802617e-01
-1.62861347e+00 -7.28240550e-01 -1.13941461e-01 1.89218485e+00
1.44725358e+00 5.63776255e-01 -3.84753078e-01 -1.72660246e-01
3.91127616e-01 5.81889451e-01 -9.48518440e-02 -1.04254723e+00
-2.24343643e-01 5.78137815e-01 4.81960446e-01 1.24122667e+00
-9.88229692e-01 1.54217529e+00 7.97637987e+00 4.64645267e-01
-7.61962295e-01 1.95918366e-01 6.46144748e-01 -3.64336908e-01
-4.95280653e-01 6.77661821e-02 -1.54612565e+00 4.42757159e-01
1.52726865e+00 -2.68503398e-01 1.33506641e-01 6.11035883e-01
2.50045776e-01 1.15656845e-01 -1.20673931e+00 5.32035589e-01
1.13797914e-02 -1.22844565e+00 1.48360670e-01 -3.07103932e-01
5.30314326e-01 6.08006895e-01 -4.38878536e-01 6.18396759e-01
1.11741734e+00 -1.04014993e+00 5.13390601e-01 1.29733667e-01
3.29444081e-01 -7.47623801e-01 6.69227719e-01 7.71771312e-01
-8.41348588e-01 3.90510857e-01 -5.71684539e-01 -4.67104495e-01
5.66623747e-01 7.82868207e-01 -8.58354390e-01 1.61207840e-01
3.21115106e-01 7.25034177e-01 -5.92629075e-01 5.77161670e-01
-6.24812961e-01 1.23943233e+00 -3.57141376e-01 -1.74431279e-01
3.08493406e-01 -6.92931637e-02 3.53317291e-01 1.71626759e+00
-1.28905758e-01 -1.03907222e-02 2.14824438e-01 1.29975438e-01
-1.74034357e-01 9.51240137e-02 -4.93185788e-01 1.23062335e-01
5.27890563e-01 8.41755629e-01 -2.32806131e-01 -5.16382396e-01
-6.80464447e-01 9.20182347e-01 9.36353266e-01 3.46275747e-01
-3.85572195e-01 -3.60154241e-01 1.03497243e+00 1.30982688e-02
2.77963609e-01 -9.61712658e-01 -5.40717006e-01 -1.39207971e+00
1.87296607e-02 -6.35011613e-01 5.71172953e-01 -3.85564119e-01
-1.41793394e+00 7.09642112e-01 -9.13057327e-02 -2.47234285e-01
-4.12255675e-01 -8.82759750e-01 -7.68045008e-01 1.14044046e+00
-1.48228967e+00 -8.74823689e-01 5.09804904e-01 1.46401107e-01
9.60897028e-01 2.79663056e-02 1.08016360e+00 2.15967357e-01
-6.52366340e-01 5.74751139e-01 1.45544976e-01 5.00687003e-01
6.25837207e-01 -1.53212512e+00 1.28506470e+00 7.84635961e-01
5.76865673e-01 9.92936611e-01 8.08441639e-01 -6.83079720e-01
-9.21988130e-01 -8.38896573e-01 2.06762600e+00 -6.32679403e-01
1.01398218e+00 -9.88417447e-01 -1.25903726e+00 1.31217551e+00
6.74534857e-01 9.31479260e-02 1.02108121e+00 6.85426950e-01
-9.89416763e-02 -1.11243121e-01 -5.51276505e-01 5.79909325e-01
9.03177738e-01 -5.74478447e-01 -1.27896810e+00 5.29529095e-01
1.01300204e+00 -2.91769177e-01 -6.57630801e-01 1.75872803e-01
2.42730945e-01 -3.25959653e-01 7.96502233e-01 -1.33960474e+00
1.57739058e-01 2.12580830e-01 -5.40949143e-02 -1.83096147e+00
-5.11157691e-01 -6.61561489e-01 -2.28230730e-02 1.36133850e+00
1.06053579e+00 -6.60013855e-01 1.16574848e+00 9.49845850e-01
-3.88421595e-01 -5.25784314e-01 -9.95825112e-01 -1.07166827e+00
7.32426107e-01 -6.70287728e-01 4.41823840e-01 9.22076225e-01
5.60739994e-01 6.34995341e-01 -1.40203267e-01 -5.27540334e-02
3.73250991e-01 -2.55693913e-01 3.78327280e-01 -9.16641831e-01
-4.24711704e-01 -2.70305783e-01 -6.77938834e-02 -1.41584182e+00
7.72480965e-01 -1.19616127e+00 2.70080924e-01 -1.81230676e+00
-1.10441081e-01 -4.87753928e-01 -5.04147828e-01 8.07998538e-01
-3.61254573e-01 -2.94281751e-01 -3.31981033e-02 -2.53100872e-01
-4.70690817e-01 4.46485549e-01 7.08630979e-01 7.30053335e-02
-2.87068158e-01 -4.77507077e-02 -5.68056524e-01 7.17665017e-01
1.10003364e+00 -8.73700678e-01 -4.83244300e-01 -1.14581025e+00
1.63027823e-01 -5.57319447e-02 -2.20612764e-01 -5.86112916e-01
2.86036253e-01 -2.24591881e-01 1.00747496e-01 -6.62435114e-01
1.49814367e-01 -4.47915345e-01 -1.49944797e-01 4.48438674e-01
-7.60003209e-01 3.31116945e-01 6.85187817e-01 -2.47124974e-02
-3.92060578e-01 -5.69954216e-01 7.08351135e-01 -3.33001971e-01
-5.72555602e-01 6.05891831e-02 -7.73189187e-01 3.68001223e-01
5.41939735e-01 1.77895710e-01 -1.32470489e-01 2.89366394e-02
-9.74159956e-01 2.98924506e-01 8.68983567e-02 6.51809037e-01
1.00098252e-01 -9.65056241e-01 -8.75093699e-01 4.68970239e-01
-3.85975003e-01 5.35248257e-02 9.75678340e-02 1.88719928e-01
-3.07026654e-01 8.70898843e-01 2.09049374e-01 -3.90480421e-02
-1.42533326e+00 3.32861006e-01 3.10271531e-01 -9.45911646e-01
-2.74146825e-01 1.36438668e+00 1.25454843e-01 -9.88541663e-01
1.52397484e-01 -4.80504811e-01 -2.03490362e-01 2.11252309e-02
5.28510332e-01 -1.90169647e-01 4.89805609e-01 -2.16777802e-01
-5.81434011e-01 4.37300168e-02 -5.86602807e-01 -3.41304123e-01
1.68452728e+00 -1.94341317e-01 -2.92141974e-01 8.37129414e-01
1.30285251e+00 1.34936154e-01 -9.92082417e-01 -3.17869574e-01
5.23016155e-01 -3.24890986e-02 -3.12060006e-02 -6.98572576e-01
-5.34883142e-01 1.10512114e+00 -3.33402425e-01 4.01441962e-01
6.92623496e-01 9.35127884e-02 9.90007818e-01 5.93408346e-01
2.10176811e-01 -1.02802968e+00 -3.61580700e-01 1.30889332e+00
4.83935505e-01 -1.03757477e+00 -2.49773994e-01 -2.64879197e-01
-4.83916759e-01 8.47308099e-01 5.81975818e-01 -3.40647310e-01
1.05344927e+00 8.61221254e-01 1.77999765e-01 -6.08524904e-02
-1.30302310e+00 1.84916690e-01 7.50999600e-02 2.02270597e-01
1.25370157e+00 1.26095429e-01 -5.16836345e-01 8.83565366e-01
-5.84029555e-01 -2.83070534e-01 2.82746434e-01 1.01444304e+00
-6.51175022e-01 -1.84378719e+00 1.94411010e-01 4.16771740e-01
-6.85101032e-01 -8.31106365e-01 -4.32772011e-01 6.79035842e-01
-1.59169018e-01 9.12610412e-01 4.78282064e-01 -7.08875358e-02
4.97510523e-01 6.51293099e-01 3.04618537e-01 -1.26439416e+00
-8.20754170e-01 -3.24308038e-01 6.42575979e-01 -1.67972654e-01
3.09848338e-02 -6.62203014e-01 -1.52880299e+00 -3.84966224e-01
-7.52266198e-02 6.14280283e-01 6.95169151e-01 1.08059275e+00
2.99710393e-01 4.62684691e-01 2.87342459e-01 -5.07242680e-01
-4.40088660e-01 -1.18833411e+00 -5.90044320e-01 2.70888001e-01
3.57252151e-01 2.01943591e-02 -4.24011528e-01 1.89621717e-01] | [10.659965515136719, 9.123229026794434] |
5d82f1ab-e611-4a2b-bc9f-e4fd696c84b7 | the-neural-hype-and-comparisons-against-weak | null | null | https://dl.acm.org/citation.cfm?id=3308781 | http://sigir.org/wp-content/uploads/2019/01/p040.pdf | The Neural Hype and Comparisons Against Weak Baselines | Recently, the machine learning community paused in a moment of self-reflection. In a widely discussed paper at ICLR 2018, Sculley et al. wrote: "We observe that the rate of empirical advancement may not have been matched by consistent increase in the level of empirical rigor across the field as a whole." Their primary complaint is the development of a "research and publication culture that emphasizes wins" (emphasis in original), which typically means "demonstrating that a new method beats previous methods on a given task or benchmark". An apt description might be "leaderboard chasing"-and for many vision and NLP tasks, this isn't a metaphor. There are literally centralized leaderboards1 that track incremental progress, down to the fifth decimal point, some persisting over years, accumulating dozens of entries.
Sculley et al. remind us that "the goal of science is not wins, but knowledge". The structure of the scientific enterprise today (pressure to publish, pace of progress, etc.) means that "winning" and "doing good science" are often not fully aligned. To wit, they cite a number of papers showing that recent advances in neural networks could very well be attributed to mundane issues like better hyperparameter optimization. Many results can't be reproduced, and some observed improvements might just be noise. | ['Jimmy Lin'] | 2018-12-01 | null | null | null | acm-sigir-forum-volume-52-issue-2-2018-12 | ['ad-hoc-information-retrieval'] | ['natural-language-processing'] | [-4.41079140e-02 3.27182724e-03 -3.89400750e-01 -3.96526843e-01
-8.52756143e-01 -6.58616483e-01 8.84381711e-01 1.81319699e-01
-6.39571786e-01 7.35109985e-01 4.82274532e-01 -5.62697232e-01
-2.62111127e-01 -1.56478658e-01 -8.66564214e-01 -6.50724649e-01
3.74152839e-01 4.02723372e-01 -2.69071937e-01 -4.11283106e-01
6.26892030e-01 1.45584002e-01 -1.44202137e+00 5.94338439e-02
5.20173848e-01 4.70935285e-01 1.57561332e-01 3.32257897e-01
-2.95618683e-01 8.29723537e-01 -7.20375955e-01 -6.09490931e-01
1.01460807e-01 -2.09817216e-01 -1.03947866e+00 -4.49326396e-01
6.99699342e-01 2.04854980e-01 -3.14516425e-01 1.00160158e+00
2.73711383e-01 -1.45837227e-02 1.25609696e-01 -1.07864845e+00
-8.45844269e-01 1.00084746e+00 -6.06052101e-01 4.47642177e-01
-8.00367668e-02 3.07494938e-01 1.25172794e+00 -5.15564561e-01
7.86162674e-01 1.08631754e+00 9.95410979e-01 3.53993416e-01
-1.25772607e+00 -7.26687133e-01 3.50491345e-01 2.53576368e-01
-1.04026997e+00 -3.17054927e-01 4.53208238e-01 -8.47298026e-01
9.79359627e-01 4.87076670e-01 8.12683225e-01 1.43031943e+00
3.12493265e-01 4.03548419e-01 1.30942738e+00 -3.64705890e-01
8.12849924e-02 2.67645001e-01 1.39044642e-01 3.34053099e-01
6.64861858e-01 7.00871870e-02 -8.23232234e-01 -6.62276372e-02
2.56538481e-01 -1.15964770e-01 -2.44103566e-01 2.34499305e-01
-1.48678184e+00 8.27969015e-01 9.37625915e-02 6.86887264e-01
-2.41592020e-01 1.45558119e-01 7.55012870e-01 4.92433399e-01
5.16077459e-01 1.01234603e+00 -5.33730388e-01 -7.15200543e-01
-1.01946914e+00 3.25712621e-01 9.97046709e-01 4.21701759e-01
3.87814254e-01 -1.50183961e-02 1.80215135e-01 8.15256655e-01
9.45130214e-02 3.28926086e-01 7.41569579e-01 -1.14990771e+00
6.21826835e-02 4.91496533e-01 1.08673848e-01 -1.08968520e+00
-4.49180782e-01 -8.46902728e-01 -7.65863895e-01 3.71859431e-01
5.62167823e-01 -2.28011176e-01 -5.67769349e-01 1.78085756e+00
-1.79588914e-01 -1.66008055e-01 -2.36637354e-01 1.00559092e+00
8.00857186e-01 5.06338000e-01 1.72563881e-01 -3.28298211e-02
1.17944634e+00 -7.96843588e-01 -6.52581632e-01 -4.00466233e-01
5.71545899e-01 -8.09297800e-01 1.29102087e+00 7.91886926e-01
-1.14491796e+00 -4.34165329e-01 -1.27730465e+00 -8.18470120e-02
-4.59926635e-01 -4.74050976e-02 7.06303835e-01 4.01316494e-01
-9.64359105e-01 7.83115566e-01 -5.19844174e-01 -4.73669738e-01
4.01948929e-01 -6.35898635e-02 -3.59640688e-01 2.80804992e-01
-7.64669120e-01 1.19242597e+00 3.15627426e-01 4.90455255e-02
-7.55257666e-01 -9.77266908e-01 -1.42051995e-01 -1.37654930e-01
7.04389691e-01 -8.34406137e-01 1.16976333e+00 -1.18872988e+00
-1.13695431e+00 1.29989350e+00 -2.04921857e-01 -5.40580869e-01
6.16060436e-01 -5.70438921e-01 -5.27401149e-01 -4.18289781e-01
3.94323375e-03 4.45755005e-01 4.58694696e-01 -1.21138144e+00
-7.73299813e-01 -6.28933728e-01 7.43629411e-03 5.80806658e-02
-1.98806852e-01 4.62077141e-01 -1.33727910e-02 -5.65967381e-01
1.19352251e-01 -7.47025251e-01 -1.01836301e-01 -3.74623388e-01
-3.05150568e-01 -5.18771529e-01 6.08580291e-01 -3.69841874e-01
1.30537570e+00 -2.13604903e+00 -1.77290991e-01 -1.99693829e-01
6.11954570e-01 3.59704904e-02 7.82256052e-02 4.76620197e-01
-1.52850881e-01 5.92230499e-01 7.13051930e-02 -3.03333383e-02
2.01415002e-01 1.38787419e-01 -6.35036230e-01 5.16114593e-01
4.66517918e-03 9.40315247e-01 -8.96766007e-01 -1.59653276e-02
-2.15760753e-01 6.15857422e-01 -1.12316823e-02 -4.03311133e-01
-1.18428029e-01 2.94459134e-01 -6.25227466e-02 3.85137767e-01
3.09843063e-01 -8.05029333e-01 2.43099913e-01 1.53661063e-02
-7.11094379e-01 5.52854717e-01 -1.10631514e+00 1.60779548e+00
5.03878891e-02 1.23903310e+00 4.52460572e-02 -1.07261145e+00
8.91430616e-01 2.39882961e-01 2.95180678e-01 -6.11290455e-01
2.64893204e-01 3.18986803e-01 4.69689578e-01 -5.31344533e-01
5.17408013e-01 5.89503087e-02 2.48317540e-01 3.44390571e-01
-3.79583061e-01 -1.44145295e-01 -6.62473217e-02 -7.17156008e-02
1.04168487e+00 1.89796150e-01 4.52661291e-02 -4.79286104e-01
1.72925547e-01 5.02543628e-01 7.37095356e-01 1.00881243e+00
-2.20597833e-01 4.44467902e-01 4.68935728e-01 -7.00725436e-01
-1.40803099e+00 -8.62789452e-01 -2.15959400e-01 1.37150848e+00
-3.85213226e-01 -4.91939098e-01 -6.15147710e-01 -1.62459448e-01
-5.53972274e-02 4.59865242e-01 -7.34170556e-01 1.05724521e-01
-3.94303739e-01 -7.93118060e-01 6.36214018e-01 1.81556284e-01
4.31116074e-01 -1.04490745e+00 -1.01679718e+00 8.28343183e-02
6.54832125e-02 -9.45552707e-01 1.52807698e-01 3.53283465e-01
-9.28840876e-01 -6.04347706e-01 -5.57337523e-01 -4.48436856e-01
1.38149172e-01 2.18308493e-01 1.26093578e+00 1.01682864e-01
-2.88622618e-01 -1.20772677e-03 -2.13244528e-01 -8.59085798e-01
-4.85500664e-01 7.07650259e-02 6.82697743e-02 -5.67256272e-01
6.90323353e-01 -6.25535965e-01 -6.16181731e-01 -1.34003907e-01
-6.96173370e-01 -3.09738796e-02 8.43459368e-01 8.68175745e-01
2.91085124e-01 -3.42259407e-01 7.49744892e-01 -1.08758044e+00
6.39958680e-01 -4.34353203e-01 -3.04279149e-01 1.17967159e-01
-1.22135711e+00 -1.39222756e-01 4.68291909e-01 -3.24689239e-01
-6.52640164e-01 -8.08403969e-01 1.33491512e-02 -2.11420536e-01
-2.84970999e-01 6.33981586e-01 3.36928487e-01 1.88538060e-01
9.10888910e-01 3.69981937e-02 1.08467460e-01 -6.17067993e-01
1.23419523e-01 5.92772484e-01 6.58951759e-01 -7.66700566e-01
5.56150377e-01 5.33838987e-01 -2.12464690e-01 -7.85037816e-01
-9.37772989e-01 -3.74031752e-01 -1.51227951e-01 -2.08995249e-02
6.26304686e-01 -7.29415298e-01 -9.17679787e-01 1.66187659e-01
-1.24641764e+00 -3.29503775e-01 -5.66541970e-01 8.69456828e-01
-2.24421665e-01 1.12786554e-01 -3.39259923e-01 -7.09997773e-01
-2.56327301e-01 -9.41614389e-01 5.08532763e-01 4.83119190e-01
-5.21447957e-01 -9.94373798e-01 2.38190681e-01 6.19678974e-01
6.61329985e-01 1.79863364e-01 8.99601519e-01 -8.34180593e-01
-2.69567579e-01 -1.05868503e-01 -2.64563620e-01 5.03605366e-01
-9.45405811e-02 2.12429747e-01 -1.13501894e+00 -1.20972790e-01
1.84291527e-01 -1.88642904e-01 6.27809286e-01 3.12009156e-01
1.09068763e+00 -4.88889903e-01 -2.90256441e-01 4.44454044e-01
1.69698453e+00 4.29366559e-01 4.91183251e-01 9.15757895e-01
6.34537458e-01 7.22367823e-01 2.35572353e-01 4.62195188e-01
2.29338229e-01 3.61749798e-01 2.46264543e-02 9.37812254e-02
3.55509333e-02 -1.06874324e-01 1.28148541e-01 8.36836755e-01
-4.04435247e-01 1.26587957e-01 -1.28265321e+00 5.67171574e-01
-1.69196033e+00 -1.20163977e+00 -3.67021054e-01 2.27488780e+00
8.29306901e-01 5.05841970e-01 1.82751343e-01 -1.65866688e-01
5.05447567e-01 1.80819929e-01 -6.81933641e-01 -7.06990659e-01
-4.38906938e-01 1.09165482e-01 5.24320126e-01 2.90508151e-01
-6.60556912e-01 7.87727356e-01 7.36433649e+00 6.93088174e-01
-1.55423677e+00 2.30241761e-01 6.99268818e-01 -1.09307982e-01
-5.29734612e-01 3.08522195e-01 -6.47211790e-01 5.08357823e-01
9.60501850e-01 -4.28283870e-01 2.76165247e-01 6.00895166e-01
3.34817886e-01 -1.12645537e-01 -1.04189575e+00 9.61502790e-01
3.86533625e-02 -1.61995625e+00 -1.77114934e-01 1.11461328e-02
6.69810355e-01 7.17951596e-01 3.01563650e-01 7.00856373e-02
5.53965211e-01 -1.57296157e+00 6.54341817e-01 5.18715143e-01
4.14676875e-01 -3.71996552e-01 4.93511856e-01 4.34524208e-01
-2.74719059e-01 -1.25936776e-01 -3.05583686e-01 -3.66084874e-01
-2.09385887e-01 6.55470788e-01 -7.25265920e-01 2.90115088e-01
1.04976082e+00 3.54702771e-01 -6.09528005e-01 1.06977332e+00
7.42300674e-02 1.00276732e+00 -1.53162330e-01 -2.98684865e-01
4.59718227e-01 -1.62219554e-01 9.47239935e-01 1.50535095e+00
3.65927108e-02 -2.03638449e-01 -3.01609516e-01 8.70824873e-01
4.61371392e-02 1.80615380e-01 -6.89924657e-01 -5.01846313e-01
7.02742517e-01 1.33166981e+00 -5.77575326e-01 -1.31318510e-01
-5.58825195e-01 3.66459608e-01 5.60007691e-02 3.45028132e-01
-6.07766449e-01 -2.18199208e-01 5.31716466e-01 4.56539355e-02
-3.00505245e-03 -2.41012633e-01 -7.58911550e-01 -7.64923453e-01
6.09276891e-02 -1.18053842e+00 6.62787408e-02 -6.99925661e-01
-1.29393959e+00 4.02855754e-01 -2.41133198e-01 -7.08191812e-01
2.32727110e-01 -6.10953271e-01 -5.04616022e-01 7.18616128e-01
-1.29995751e+00 -7.19032228e-01 -1.70760974e-01 -9.11800116e-02
4.56568122e-01 -3.13002139e-01 6.29452944e-01 1.47036001e-01
-5.00209332e-01 6.77785099e-01 3.86020988e-01 -9.27191079e-02
8.09714556e-01 -1.09741545e+00 3.53895724e-01 3.89641583e-01
4.18165922e-01 8.39497089e-01 1.24624574e+00 -4.40576017e-01
-1.45772028e+00 -3.54521215e-01 9.34123695e-01 -7.51701355e-01
8.91213238e-01 -1.28801924e-03 -1.12854350e+00 8.45233679e-01
5.42712450e-01 -6.00825250e-01 5.75547874e-01 6.22057617e-01
-7.60388613e-01 -1.03349827e-01 -7.66275704e-01 6.17235601e-01
9.62555945e-01 -4.37454015e-01 -8.58602703e-01 4.26261485e-01
6.85682058e-01 -2.32364044e-01 -7.14970946e-01 4.02697444e-01
1.00655019e+00 -9.39199030e-01 6.93879664e-01 -9.46173310e-01
6.35746539e-01 -1.75443012e-02 -1.27973825e-01 -1.19060850e+00
-3.19006056e-01 -8.34522367e-01 3.23834985e-01 1.13929212e+00
5.59387863e-01 -7.54081726e-01 8.67299259e-01 5.13122380e-01
-3.11512947e-01 -9.81989503e-01 -8.52754056e-01 -8.76727521e-01
5.07793605e-01 -5.87547600e-01 4.45942253e-01 1.49447024e+00
1.05966739e-01 6.26959503e-01 9.58063975e-02 -3.84995997e-01
3.41553450e-01 -1.90435424e-01 7.53135622e-01 -1.56055820e+00
-3.74541044e-01 -1.09273517e+00 -3.21523994e-01 -5.29533982e-01
-2.46956661e-01 -1.06639850e+00 -2.10546285e-01 -1.31042516e+00
6.04334950e-01 -3.11912835e-01 -5.18478036e-01 2.36663878e-01
-2.03756075e-02 -2.51263790e-02 2.14940071e-01 5.60688198e-01
-3.40599298e-01 -1.80303246e-01 1.02226388e+00 -9.99502540e-02
-9.49296132e-02 -5.40139258e-01 -1.43138456e+00 9.13994849e-01
8.69677484e-01 -2.44767964e-01 -1.93717405e-01 -5.88218808e-01
9.84705448e-01 -4.60105747e-01 7.27417767e-01 -1.04035103e+00
2.71556467e-01 -3.65844280e-01 2.45678678e-01 -1.81375340e-01
2.28451207e-01 -4.84837025e-01 4.12161946e-01 4.37958539e-01
-5.54929912e-01 4.09571826e-01 3.96900952e-01 2.82871544e-01
-2.25067250e-02 -2.35448420e-01 4.92817909e-01 -1.60573319e-01
-6.98360205e-01 -6.85592666e-02 7.28241950e-02 3.88363332e-01
7.98609793e-01 -3.58825028e-01 -9.19037879e-01 -1.54832467e-01
-4.34680194e-01 3.19443643e-02 4.51132715e-01 5.75588763e-01
2.97403902e-01 -8.34608078e-01 -1.09655893e+00 -4.34070498e-01
2.97488887e-02 -1.26989588e-01 3.02289546e-01 1.23119581e+00
-3.34854633e-01 5.01120865e-01 -1.84711471e-01 -5.02498031e-01
-9.57660615e-01 2.15704188e-01 1.92739069e-01 8.14389624e-03
-1.03822052e+00 9.47291195e-01 -5.37503473e-02 -8.57722480e-03
4.54961360e-01 -1.11623384e-01 -1.32345572e-01 1.67840496e-01
4.76734996e-01 5.45305610e-01 -5.51370345e-02 -1.67203918e-01
-2.31138930e-01 4.01427120e-01 -4.37683791e-01 -4.19496775e-01
1.60294116e+00 1.54328838e-01 -1.98405609e-01 1.26558781e+00
1.03059769e+00 2.15264298e-02 -9.41885650e-01 -5.91208227e-02
1.55815512e-01 -3.18779230e-01 -6.34029731e-02 -1.31522095e+00
-6.10642850e-01 8.83649945e-01 6.65394962e-01 3.52016658e-01
6.49335861e-01 1.55262738e-01 4.76327211e-01 5.81061244e-01
9.50409248e-02 -1.64084613e+00 -1.81795046e-01 5.72115481e-01
1.05310547e+00 -1.18451345e+00 1.51733279e-01 3.19636047e-01
-6.79662287e-01 9.09994006e-01 4.43266869e-01 -5.99396527e-02
3.96368593e-01 2.92666227e-01 8.27791393e-02 -5.04736125e-01
-1.05903494e+00 1.80467099e-01 -2.91555598e-02 3.55898619e-01
8.83452713e-01 1.03243381e-01 -8.62096965e-01 4.71733660e-01
-6.45553887e-01 2.35319436e-01 4.60453480e-01 5.50112724e-01
-6.79112315e-01 -8.89732659e-01 -5.05681098e-01 5.67295432e-01
-8.91868770e-01 -1.64016765e-02 -5.53488433e-01 1.06891072e+00
4.22859997e-01 8.11525881e-01 5.63906915e-02 -4.03707206e-01
2.11972713e-01 2.59048074e-01 3.51651073e-01 -3.23177665e-01
-7.55310774e-01 -1.89542443e-01 1.10671133e-01 -3.08976918e-01
-2.40169570e-01 -6.47567153e-01 -1.08798778e+00 -9.12038386e-01
4.14303280e-02 3.17383796e-01 1.14841688e+00 9.32849050e-01
3.52742165e-01 4.20754969e-01 2.10716724e-01 -1.10813461e-01
-7.43673265e-01 -9.27199602e-01 -3.84951591e-01 1.96028993e-01
3.33691716e-01 -2.76279181e-01 -4.24024075e-01 -1.11192964e-01] | [9.007275581359863, 6.348455429077148] |
3ad98b71-06d1-45de-b419-ec76e60e0ebe | avlnet-learning-audio-visual-language | 2006.09199 | null | https://arxiv.org/abs/2006.09199v2 | https://arxiv.org/pdf/2006.09199v2.pdf | AVLnet: Learning Audio-Visual Language Representations from Instructional Videos | Current methods for learning visually grounded language from videos often rely on text annotation, such as human generated captions or machine generated automatic speech recognition (ASR) transcripts. In this work, we introduce the Audio-Video Language Network (AVLnet), a self-supervised network that learns a shared audio-visual embedding space directly from raw video inputs. To circumvent the need for text annotation, we learn audio-visual representations from randomly segmented video clips and their raw audio waveforms. We train AVLnet on HowTo100M, a large corpus of publicly available instructional videos, and evaluate on image retrieval and video retrieval tasks, achieving state-of-the-art performance. We perform analysis of AVLnet's learned representations, showing our model utilizes speech and natural sounds to learn audio-visual concepts. Further, we propose a tri-modal model that jointly processes raw audio, video, and text captions from videos to learn a multi-modal semantic embedding space useful for text-video retrieval. Our code, data, and trained models will be released at avlnet.csail.mit.edu | ['James Glass', 'Antonio Torralba', 'Brian Kingsbury', 'Rameswar Panda', 'Hilde Kuehne', 'Kartik Audhkhasi', 'Dhiraj Joshi', 'Brian Chen', 'Samuel Thomas', 'David Harwath', 'Angie Boggust', 'Andrew Rouditchenko', 'Rogerio Feris', 'Michael Picheny'] | 2020-06-16 | null | null | null | null | ['text-annotation'] | ['natural-language-processing'] | [ 3.26467633e-01 -1.25786617e-01 -2.95770586e-01 -3.66330266e-01
-1.41410458e+00 -8.04941714e-01 6.13236964e-01 7.23036677e-02
-2.53405929e-01 3.81395131e-01 6.03992701e-01 -2.28179380e-01
1.73107997e-01 -2.17238203e-01 -1.23341465e+00 -3.08381677e-01
-1.39777884e-01 1.25411674e-02 7.52121508e-02 1.65823847e-01
1.85566559e-01 -6.99230060e-02 -1.81079698e+00 1.02688408e+00
3.12922686e-01 1.01055479e+00 3.16800624e-01 1.11674356e+00
-2.62188703e-01 1.23357403e+00 -5.72111845e-01 2.89334040e-02
-1.65104449e-01 -4.93807286e-01 -9.50845778e-01 1.09763376e-01
8.83136332e-01 -6.08382344e-01 -8.90809119e-01 7.85082936e-01
3.81394923e-01 4.37131345e-01 7.38282084e-01 -1.48575556e+00
-1.18828714e+00 7.61084318e-01 -1.55790731e-01 1.92109779e-01
9.08790290e-01 1.13764316e-01 1.02921259e+00 -1.27046645e+00
6.99011445e-01 1.28464830e+00 3.43427867e-01 6.85002804e-01
-1.01840174e+00 -7.01771975e-01 2.05864340e-01 4.16887105e-01
-1.49708593e+00 -6.21994555e-01 7.88528919e-01 -7.54760563e-01
7.88922489e-01 9.95741561e-02 6.57894015e-01 1.57888114e+00
1.66277681e-02 1.40336919e+00 4.41477537e-01 -6.58053160e-01
6.55997843e-02 1.10779256e-01 -7.90724903e-02 8.72633159e-01
-4.52116400e-01 -2.36176193e-01 -1.12818933e+00 5.76604977e-02
7.74910033e-01 1.98860262e-02 -4.80452627e-01 -5.06619632e-01
-1.22452426e+00 8.45575750e-01 2.21851826e-01 1.69079885e-01
-2.45351437e-02 5.04480302e-01 6.33537948e-01 4.71020609e-01
3.71750802e-01 6.56637596e-03 -2.02545174e-03 -4.56972092e-01
-9.80947971e-01 -1.61315486e-01 3.67849171e-01 1.25417280e+00
5.54284334e-01 2.86319494e-01 -2.05885395e-01 8.28869164e-01
6.53227627e-01 6.52606785e-01 8.04385185e-01 -9.92843509e-01
4.39456493e-01 2.69216627e-01 -1.83142766e-01 -8.80327165e-01
1.89142078e-01 4.44774538e-01 -7.14729130e-02 -2.01349407e-01
-3.69527638e-02 1.49087876e-01 -1.01646769e+00 1.50843883e+00
-1.81976289e-01 5.05091250e-01 2.67972291e-01 9.07988012e-01
1.45111680e+00 1.16989231e+00 1.90880045e-01 1.32273555e-01
1.04145539e+00 -1.26494575e+00 -9.01186168e-01 -2.36664247e-02
6.73423707e-01 -7.94694364e-01 1.34731221e+00 3.93023252e-01
-1.16929305e+00 -5.86848319e-01 -8.39856565e-01 -3.13880056e-01
-3.15058947e-01 3.73320729e-01 1.44502044e-01 1.93500891e-01
-1.23026311e+00 1.28894687e-01 -8.79685521e-01 -3.78563613e-01
3.96948755e-01 -1.02294736e-01 -5.65135241e-01 -2.89624721e-01
-9.63395119e-01 2.42074177e-01 3.00941199e-01 -1.39159217e-01
-1.71074927e+00 -6.54582322e-01 -1.38321102e+00 9.79815722e-02
3.08070451e-01 -2.80425966e-01 1.49633110e+00 -1.31291544e+00
-1.48154259e+00 8.92508447e-01 -1.02096302e-02 -4.15739119e-01
1.33014740e-02 -4.65164781e-01 -4.81441647e-01 1.14671147e+00
-1.09114852e-02 1.20905995e+00 1.37919784e+00 -1.14964783e+00
-4.86200638e-02 8.63062516e-02 1.36774272e-01 2.14514742e-03
-8.51425350e-01 1.24662511e-01 -4.97013390e-01 -8.82635653e-01
-2.95164764e-01 -9.07967806e-01 3.01455766e-01 2.61250883e-01
-1.59192950e-01 -4.16328967e-01 1.02131152e+00 -6.27019763e-01
1.14417422e+00 -2.68215823e+00 1.82991296e-01 -1.98227063e-01
7.51691908e-02 1.32875353e-01 -7.93472409e-01 7.22602248e-01
-2.90063173e-01 -5.62501997e-02 2.28871405e-01 -3.22815686e-01
3.16692702e-02 5.53271957e-02 -5.85964561e-01 2.77791083e-01
2.72880733e-01 8.71468127e-01 -1.07480741e+00 -7.81231523e-01
3.58978242e-01 7.54765153e-01 -6.80566370e-01 3.92071426e-01
-3.08980405e-01 1.53430849e-01 -2.97702998e-01 6.41670704e-01
-1.57908008e-01 -2.86791235e-01 -1.44065335e-01 -1.90251753e-01
9.75204036e-02 1.91758081e-01 -8.69287610e-01 2.32587004e+00
-5.54975271e-01 1.39954031e+00 1.04020715e-01 -1.08386409e+00
7.25865841e-01 8.02403569e-01 6.28420055e-01 -4.49398577e-01
7.45373592e-02 -5.12786023e-02 -8.84253442e-01 -9.62363005e-01
4.31194961e-01 1.81519449e-01 -1.69828922e-01 5.30678391e-01
8.17104697e-01 -1.75626040e-01 1.56206250e-01 7.24699438e-01
1.00757158e+00 2.64236033e-01 -1.61917672e-01 1.10358432e-01
5.27525365e-01 -6.60836790e-03 -7.85302743e-02 4.93333250e-01
-1.61991701e-01 8.96494210e-01 2.26490825e-01 -2.53504187e-01
-6.94723368e-01 -1.35301006e+00 1.82535455e-01 1.71547055e+00
-1.37292713e-01 -9.30597961e-01 -6.07864499e-01 -4.59583849e-01
-1.87124103e-01 4.33931381e-01 -4.66538310e-01 -3.43901992e-01
-2.30791882e-01 4.44144666e-01 5.99044144e-01 6.76256239e-01
-1.92303747e-01 -1.35131645e+00 -2.66216964e-01 5.42939380e-02
-3.36947024e-01 -1.36382413e+00 -8.15628588e-01 -2.56431818e-01
-5.15144169e-01 -1.06193149e+00 -8.13722551e-01 -1.31590366e+00
5.94733179e-01 5.61166406e-01 9.69986081e-01 -1.16627783e-01
-5.24055660e-01 1.50315273e+00 -6.29223585e-01 -2.55667150e-01
-4.19943959e-01 -3.88986439e-01 1.37894541e-01 4.54321429e-02
2.94311523e-01 -3.04052919e-01 -3.26476902e-01 2.43506227e-02
-1.26560831e+00 -1.33569874e-02 1.78118616e-01 7.67562866e-01
5.79155982e-01 -4.33854640e-01 4.17563647e-01 -2.39338592e-01
4.64375883e-01 -4.30546820e-01 -3.80131334e-01 2.83382088e-01
2.41119266e-01 -1.51714280e-01 3.98552746e-01 -7.57487297e-01
-6.60569608e-01 1.69455811e-01 1.00677975e-01 -1.35019636e+00
-2.62023598e-01 6.18371367e-01 8.97544697e-02 -2.83660553e-02
5.01617014e-01 3.88696462e-01 4.29047905e-02 -3.76455665e-01
6.13372147e-01 9.38644946e-01 8.20740819e-01 -6.80694997e-01
6.08975172e-01 2.98495054e-01 -6.25693798e-01 -1.17919552e+00
-9.25966382e-01 -6.26355171e-01 -4.28446770e-01 -6.21268332e-01
1.23292220e+00 -1.53248370e+00 -5.89152932e-01 9.56640914e-02
-1.15679455e+00 -4.27081525e-01 -2.65301347e-01 8.25164914e-01
-8.75738084e-01 3.09496045e-01 -9.14940238e-01 -6.33432448e-01
-1.45254865e-01 -1.08900225e+00 1.31564200e+00 -3.11044082e-02
-2.15130091e-01 -1.00468326e+00 1.11302212e-01 7.46277690e-01
-2.09189057e-02 6.26907498e-03 6.70237720e-01 -7.37958729e-01
-7.65536487e-01 -1.44804001e-01 -4.01929319e-02 5.45954168e-01
-1.05406672e-01 2.92085022e-01 -1.06221688e+00 -5.89425802e-01
-5.26526451e-01 -1.18596792e+00 8.50443900e-01 3.14381897e-01
1.61134839e+00 -3.97090733e-01 -3.10783759e-02 3.24366599e-01
1.18937206e+00 4.59306426e-02 3.57656568e-01 9.61729437e-02
7.21016467e-01 5.07492006e-01 4.69194710e-01 4.33221906e-01
2.90152162e-01 3.63999367e-01 2.82704055e-01 2.40615383e-01
-2.13350296e-01 -7.89349794e-01 9.61395800e-01 1.46421647e+00
3.56182009e-01 -3.43435913e-01 -8.86917770e-01 8.71002674e-01
-1.61554813e+00 -1.13676572e+00 3.41771692e-01 1.76636231e+00
8.51091862e-01 -4.89510186e-02 1.06763355e-02 -2.45937845e-03
5.66186488e-01 1.70880675e-01 -2.56074876e-01 -2.94805288e-01
1.91567779e-01 1.16179489e-01 -1.61362678e-01 3.85927916e-01
-1.15917981e+00 8.34052444e-01 6.35499430e+00 6.97613060e-01
-1.23288131e+00 1.95633262e-01 4.01491597e-02 -5.02219677e-01
-4.50311691e-01 -4.36271727e-01 -3.20664734e-01 2.43683517e-01
1.26419842e+00 -3.34378868e-01 4.72935021e-01 8.77040088e-01
1.09714150e-01 3.22653770e-01 -1.41999805e+00 1.39557528e+00
7.59593487e-01 -1.52742589e+00 5.19752324e-01 -4.22270060e-01
7.08761275e-01 -3.90051119e-02 1.68504030e-01 6.40878439e-01
8.36655796e-02 -1.10988152e+00 8.72799277e-01 4.53771919e-01
1.09582007e+00 -4.44329828e-01 1.61859378e-01 -2.36947425e-02
-1.42004526e+00 -1.32466495e-01 6.98469253e-03 1.94554254e-01
6.62084967e-02 -8.31818953e-02 -6.54969096e-01 2.40785554e-01
9.84553933e-01 1.19460833e+00 -5.36176980e-01 8.37178528e-01
-2.03784838e-01 8.02500367e-01 2.65696831e-02 9.13481116e-02
5.00721693e-01 1.71779230e-01 4.98797208e-01 1.49406016e+00
1.95240125e-01 6.31017163e-02 5.32590747e-01 5.66046119e-01
-3.34058613e-01 1.21448249e-01 -1.02715313e+00 -8.46098244e-01
4.08537865e-01 1.02997124e+00 -4.65931982e-01 -3.92006218e-01
-6.74848318e-01 7.83952534e-01 1.32110268e-02 6.93494141e-01
-7.28539169e-01 -6.19268239e-01 6.16909742e-01 7.41304224e-03
2.62867928e-01 -3.77903342e-01 6.52938724e-01 -1.30176008e+00
-8.05432275e-02 -8.80427897e-01 2.69832313e-01 -1.50307763e+00
-1.21247339e+00 5.41952610e-01 1.11089937e-01 -1.55913305e+00
-4.72827196e-01 -6.56055033e-01 -4.56590712e-01 7.55382478e-02
-1.13260674e+00 -9.59061742e-01 -3.19267988e-01 9.75984275e-01
1.14056695e+00 -4.19026434e-01 8.07964146e-01 4.75510120e-01
-2.19768256e-01 6.07705593e-01 4.63264771e-02 5.37876725e-01
1.04962468e+00 -9.08050239e-01 -1.70406625e-01 4.13200110e-01
6.48912668e-01 4.58404720e-01 4.53768164e-01 -2.34200031e-01
-1.74765944e+00 -1.10741699e+00 5.29540658e-01 -5.74718654e-01
1.09495258e+00 -6.78942025e-01 -9.11003649e-01 1.09029520e+00
6.26904786e-01 1.46126583e-01 1.20695889e+00 -3.51280361e-01
-4.96020436e-01 1.22863330e-01 -5.94305396e-01 4.38420683e-01
8.32966328e-01 -1.27136528e+00 -9.68691945e-01 5.79058468e-01
1.31507075e+00 -3.36219132e-01 -8.84528518e-01 -7.31125996e-02
5.06329834e-01 -3.19004327e-01 1.17634523e+00 -8.62270772e-01
8.66311669e-01 -9.56273526e-02 -4.36388224e-01 -1.20885849e+00
1.25753313e-01 -6.37052536e-01 -8.54985192e-02 1.18432069e+00
1.69953436e-01 7.88277835e-02 5.01871943e-01 1.26423642e-01
-4.22157288e-01 -3.99587274e-01 -9.31466222e-01 -7.73435891e-01
-1.94242224e-01 -7.00048804e-01 -1.02309529e-02 1.13526332e+00
3.48483533e-01 4.99152124e-01 -3.53543818e-01 4.06286456e-02
4.38087106e-01 4.58328947e-02 6.28113627e-01 -9.18282926e-01
-7.57051855e-02 -4.71131504e-02 -6.49218917e-01 -1.10480154e+00
7.28006959e-01 -1.05872333e+00 2.20216930e-01 -1.43573833e+00
2.42117539e-01 2.99439847e-01 -3.54150742e-01 7.13396013e-01
3.87619942e-01 5.27361095e-01 4.02419567e-01 -5.42331040e-02
-1.23356307e+00 8.56855690e-01 1.11152256e+00 -5.68913162e-01
-1.02089331e-01 -6.63327754e-01 -1.33671969e-01 6.13327563e-01
3.76526028e-01 -3.11242759e-01 -6.41442776e-01 -8.11946630e-01
7.54024535e-02 4.33020860e-01 5.59208333e-01 -9.91437435e-01
2.63399541e-01 -5.86921908e-02 3.91561717e-01 -6.64104760e-01
6.90500796e-01 -7.69559920e-01 -4.04132783e-01 1.97489522e-02
-8.80343020e-01 4.68157753e-02 5.25814950e-01 7.15380311e-01
-7.38765597e-01 -2.39258304e-01 2.34177440e-01 4.91993688e-02
-8.53817046e-01 1.70465589e-01 -9.61320817e-01 1.15655303e-01
9.64224398e-01 -4.81363162e-02 -2.85212100e-01 -8.68538558e-01
-1.11476731e+00 4.04937267e-01 1.77720144e-01 1.02477479e+00
1.18053389e+00 -1.68018878e+00 -4.77708668e-01 2.92056203e-01
5.74560940e-01 -3.64782900e-01 3.21350634e-01 3.45084995e-01
-3.31770152e-01 6.68904006e-01 -1.72949687e-01 -9.53996122e-01
-1.42407763e+00 6.30168259e-01 -2.38228455e-01 5.61794221e-01
-5.29583812e-01 7.20865548e-01 2.24073291e-01 -2.02970684e-01
6.70314372e-01 -4.08813268e-01 -2.06067681e-01 4.22259569e-02
8.22348535e-01 -4.27013682e-03 -3.13478261e-01 -6.56691313e-01
-1.62814870e-01 5.07601559e-01 1.73506558e-01 -2.50888735e-01
1.33775270e+00 -1.64029315e-01 2.46637017e-01 9.12077785e-01
1.77696025e+00 -2.34461576e-01 -1.17652857e+00 -3.08962405e-01
-3.14146191e-01 -3.50592315e-01 1.45930365e-01 -2.74865478e-01
-9.04608190e-01 1.23576581e+00 5.06811440e-01 -9.42178369e-02
1.04533446e+00 2.22458899e-01 9.11481321e-01 6.98357642e-01
1.69973791e-01 -1.06580853e+00 9.63543296e-01 5.19583762e-01
1.01747239e+00 -1.27063608e+00 -2.81672060e-01 -2.93197427e-02
-6.83460474e-01 1.28987563e+00 6.03958845e-01 1.45726530e-02
6.28333569e-01 -7.32256770e-02 1.97860181e-01 -6.87458143e-02
-1.08063602e+00 1.02028139e-01 5.71045101e-01 5.30934274e-01
5.37625790e-01 -1.57914057e-01 4.35104847e-01 4.79729444e-01
3.36298496e-02 1.40127510e-01 6.92687452e-01 1.28036690e+00
-4.97902989e-01 -6.87395513e-01 -4.37111765e-01 1.00271136e-01
-3.20465147e-01 -1.85270861e-01 -4.51740086e-01 5.06072640e-01
-5.20809352e-01 9.35064614e-01 4.10441846e-01 -3.00283551e-01
8.25249255e-02 3.44247729e-01 5.43366671e-01 -9.37711895e-01
-1.67955995e-01 2.47966334e-01 -2.73627847e-01 -7.60897756e-01
-5.74174166e-01 -4.27370638e-01 -1.37302220e+00 1.97237954e-01
9.01131406e-02 4.11945581e-01 8.21837068e-01 6.69064820e-01
3.32657874e-01 5.54984570e-01 5.00463009e-01 -9.80180979e-01
-2.41696924e-01 -7.99129784e-01 -1.89398468e-01 4.79785949e-01
6.84389234e-01 -5.85816503e-01 -4.28959429e-01 7.19784617e-01] | [10.423304557800293, 1.0858670473098755] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.