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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bcc8721a-748c-410f-a15c-a74551de0026 | sparse-label-smoothing-regularization-for | 1809.04976 | null | http://arxiv.org/abs/1809.04976v3 | http://arxiv.org/pdf/1809.04976v3.pdf | Sparse Label Smoothing Regularization for Person Re-Identification | Person re-identification (re-id) is a cross-camera retrieval task which
establishes a correspondence between images of a person from multiple cameras.
Deep Learning methods have been successfully applied to this problem and have
achieved impressive results. However, these methods require a large amount of
labeled training data. Currently labeled datasets in person re-id are limited
in their scale and manual acquisition of such large-scale datasets from
surveillance cameras is a tedious and labor-intensive task. In this paper, we
propose a framework that performs intelligent data augmentation and assigns
partial smoothing label to generated data. Our approach first exploits the
clustering property of existing person re-id datasets to create groups of
similar objects that model cross-view variations. Each group is then used to
generate realistic images through adversarial training. Our aim is to emphasize
feature similarity between generated samples and the original samples. Finally,
we assign a non-uniform label distribution to the generated samples and define
a regularized loss function for training. The proposed approach tackles two
problems (1) how to efficiently use the generated data and (2) how to address
the over-smoothness problem found in current regularization methods. Extensive
experiments on four larges cale datasets show that our regularization method
significantly improves the Re-ID accuracy compared to existing methods. | ['Guangchun Luo', 'Jean-Paul Ainam', 'Ke Qin', 'Guisong Liu'] | 2018-09-13 | null | null | null | null | ['semi-supervised-person-re-identification'] | ['computer-vision'] | [ 3.32756370e-01 -2.40288407e-01 8.04339871e-02 -4.56377774e-01
-8.38012516e-01 -4.44300354e-01 7.37796187e-01 -2.31606394e-01
-5.69484234e-01 7.14425921e-01 1.69665769e-01 3.73508751e-01
9.87513438e-02 -6.20848060e-01 -7.29033232e-01 -6.08695686e-01
3.18110615e-01 6.09488904e-01 -5.19506335e-02 1.43733740e-01
1.99693311e-02 5.21285653e-01 -1.61580575e+00 6.50155321e-02
8.97443652e-01 6.34240508e-01 8.83252826e-03 5.87786078e-01
1.49513707e-01 5.34012079e-01 -6.51987255e-01 -7.09191740e-01
6.99127197e-01 -4.63020384e-01 -7.18333125e-01 5.91200113e-01
8.96564722e-01 -3.78926754e-01 -3.30537707e-01 1.24960351e+00
6.23717546e-01 4.04759556e-01 7.36927569e-01 -1.38799953e+00
-7.97901690e-01 -3.97766605e-02 -7.41203308e-01 9.37804207e-02
3.39263976e-01 -7.19812438e-02 4.23824012e-01 -7.62120128e-01
4.78912681e-01 1.23422623e+00 1.00572550e+00 1.10113478e+00
-1.37540376e+00 -7.05384135e-01 -6.02856986e-02 1.31129354e-01
-1.63805616e+00 -4.19369072e-01 8.20143759e-01 -6.43485188e-01
4.62951183e-01 1.39974579e-01 4.55604851e-01 1.27148652e+00
-4.22525048e-01 4.68221724e-01 9.52326357e-01 -4.44117159e-01
-4.68849875e-02 4.37399983e-01 1.57241613e-01 5.12423337e-01
2.30211437e-01 1.79764256e-02 -1.05219953e-01 -1.09409153e-01
8.53214800e-01 4.16348130e-01 -2.88632244e-01 -2.36482039e-01
-9.62373555e-01 7.64183283e-01 3.20017278e-01 1.87461570e-01
-2.66010076e-01 4.15791646e-02 3.65005016e-01 9.56776068e-02
4.56802011e-01 2.00549394e-01 -3.88646722e-02 3.18338454e-01
-9.06474411e-01 4.74117607e-01 3.27146500e-01 9.48518991e-01
7.15650678e-01 -1.76850021e-01 -3.10294151e-01 1.25546432e+00
2.86023095e-02 6.97086751e-01 5.79190433e-01 -8.45631242e-01
5.91203928e-01 6.34739459e-01 4.19167787e-01 -1.21365762e+00
-2.18850717e-01 -8.89526755e-02 -1.20382905e+00 1.34063363e-01
8.07170868e-01 -2.04631865e-01 -8.27745199e-01 1.81341493e+00
3.33869457e-01 5.30646265e-01 1.36272728e-01 9.83418643e-01
6.69073582e-01 5.24956703e-01 1.96728766e-01 7.92224705e-03
1.29959655e+00 -9.95047510e-01 -5.40571094e-01 -1.86423689e-01
1.98672503e-01 -6.69479251e-01 9.35878575e-01 8.36859271e-02
-1.03175342e+00 -8.60345304e-01 -8.23864222e-01 5.44058010e-02
-3.64299685e-01 4.17903811e-01 2.49637902e-01 7.97684431e-01
-9.13613617e-01 4.68043655e-01 -4.24710721e-01 -4.94083464e-01
5.01511455e-01 4.57106054e-01 -6.90926731e-01 -2.11331770e-01
-9.55361664e-01 6.17773950e-01 3.40543360e-01 5.55322133e-02
-7.72004366e-01 -7.02491939e-01 -8.03206742e-01 -7.79614076e-02
2.95502633e-01 -8.03675354e-01 7.56906211e-01 -1.31115329e+00
-1.34536409e+00 1.28287852e+00 -2.24531129e-01 -4.00062889e-01
7.03006387e-01 -1.81260437e-01 -5.29251337e-01 1.36726111e-01
2.64211267e-01 6.55449152e-01 1.12478399e+00 -1.58831835e+00
-6.64598286e-01 -5.52787840e-01 -7.39035755e-02 1.50588512e-01
-4.03103948e-01 7.14159831e-02 -8.39989245e-01 -9.40925121e-01
-2.82661974e-01 -1.17913532e+00 -2.36784175e-01 -1.64068028e-01
-4.26113993e-01 -2.06992611e-01 6.58491969e-01 -8.96157801e-01
7.90028095e-01 -2.02167988e+00 1.83808848e-01 1.80781320e-01
1.26376152e-01 6.16971254e-01 -2.07603097e-01 4.67477292e-02
-1.99052289e-01 -4.78265025e-02 -2.17946455e-01 -7.83022940e-01
-5.59134074e-02 -1.18142091e-01 -9.45928246e-02 4.90651786e-01
3.18351835e-02 7.60318935e-01 -7.39753425e-01 -5.09162128e-01
3.87594938e-01 7.15507209e-01 -4.37710315e-01 7.06140697e-01
1.18133448e-01 6.26738667e-01 -2.11182609e-01 4.18153584e-01
9.05024767e-01 -9.97036770e-02 -1.60147384e-01 -4.26453829e-01
1.99059486e-01 -5.53634942e-01 -1.27870333e+00 1.43640137e+00
-3.35892439e-01 4.05600399e-01 -2.19057072e-02 -1.12773204e+00
1.01486182e+00 1.94497719e-01 4.80097800e-01 -3.90554100e-01
1.33623794e-01 -7.58131966e-02 -5.41518569e-01 -5.93043685e-01
5.16505539e-01 -1.73569053e-01 -7.79598067e-03 4.37196732e-01
-1.27281398e-01 1.84913307e-01 1.36290148e-01 -2.87514739e-02
5.47728777e-01 -5.37880659e-02 -7.19402637e-03 -1.15363941e-01
9.45042670e-01 -1.77919924e-01 7.32561111e-01 8.57936025e-01
-2.78543979e-01 1.02155876e+00 -6.26672879e-02 -6.75210834e-01
-1.44930065e+00 -8.37716043e-01 1.44887790e-02 7.00033844e-01
2.47245371e-01 2.48751547e-02 -1.09576988e+00 -7.85264254e-01
-3.76422517e-02 4.31567937e-01 -7.31746614e-01 -7.64881521e-02
-6.99233711e-01 -1.01965618e+00 6.05836511e-01 5.60627997e-01
8.85568202e-01 -8.88135791e-01 -1.20151982e-01 -5.45717950e-04
-3.97397816e-01 -1.28376997e+00 -9.05244589e-01 -5.26316226e-01
-5.24729729e-01 -1.27063227e+00 -1.21147203e+00 -1.06395352e+00
1.13557398e+00 4.05991673e-01 9.94972765e-01 7.00050220e-02
-4.30210263e-01 7.73749352e-01 -2.49557644e-01 -2.50304282e-01
-3.31671238e-01 -2.11522013e-01 3.59251857e-01 5.95186234e-01
6.78089082e-01 -2.05702171e-01 -5.76153100e-01 4.86403227e-01
-9.41765785e-01 -1.46407634e-01 2.52336651e-01 9.51077998e-01
5.69391370e-01 8.58286172e-02 6.16046190e-01 -8.58786047e-01
6.72648907e-01 -2.08790690e-01 -6.41751170e-01 4.85645324e-01
-3.08426023e-01 -1.22713804e-01 7.23075926e-01 -6.16603553e-01
-1.18016255e+00 2.39522800e-01 7.87638947e-02 -5.53376913e-01
-4.66567338e-01 -1.20801210e-01 -3.24147195e-01 -1.06557474e-01
3.86720210e-01 2.46505409e-01 1.12515926e-01 -4.05994862e-01
2.13858351e-01 7.48280346e-01 8.19568932e-01 -6.02226555e-01
1.02189696e+00 6.89691246e-01 -1.41205460e-01 -8.33819807e-01
-8.09825540e-01 -4.58929837e-01 -7.94977963e-01 -1.56011239e-01
1.15895557e+00 -1.01380777e+00 -7.38802612e-01 7.20904529e-01
-1.13182843e+00 -2.30255127e-01 -3.35577399e-01 3.52986962e-01
-4.00373310e-01 7.28456080e-01 -2.88151145e-01 -6.78660095e-01
-4.37758088e-01 -1.00809205e+00 1.05041468e+00 4.31416839e-01
6.57534748e-02 -1.06237221e+00 1.87418237e-01 6.80702150e-01
2.50115544e-01 3.40005696e-01 3.61347556e-01 -4.93549883e-01
-3.92276615e-01 -4.95757192e-01 -4.29739565e-01 5.71201146e-01
3.24110955e-01 -3.38346153e-01 -9.05534387e-01 -5.34016192e-01
-1.18477792e-01 -3.12311441e-01 7.27926791e-01 3.00344557e-01
1.39403331e+00 -2.37931982e-01 -4.48601604e-01 8.20153832e-01
1.34258401e+00 3.60533483e-02 6.66127205e-01 3.65768731e-01
9.61440206e-01 8.01402628e-01 3.79458219e-01 4.65645820e-01
3.54999304e-01 1.00058687e+00 1.05253592e-01 -2.04532340e-01
-1.95595533e-01 -2.87921101e-01 1.37677491e-01 3.03445816e-01
-3.62744421e-01 -2.49990925e-01 -6.44866168e-01 6.17962956e-01
-1.96539640e+00 -1.30276823e+00 -2.76438259e-02 2.38169360e+00
6.02005601e-01 -3.68603855e-01 3.52794319e-01 -5.12933172e-02
1.27371871e+00 -1.35832787e-01 -4.52427238e-01 2.07845077e-01
-1.57165796e-01 -2.59105712e-01 5.07641137e-01 4.70419317e-01
-1.43932462e+00 8.48014057e-01 5.85830927e+00 6.90538108e-01
-6.91368639e-01 6.61504120e-02 6.34321213e-01 5.56070916e-02
1.46598876e-01 -4.38167363e-01 -1.00017738e+00 7.36128926e-01
5.66490352e-01 -2.04360545e-01 4.76332605e-01 6.84641242e-01
1.78148881e-01 1.39714524e-01 -1.16613305e+00 1.61843681e+00
5.56196630e-01 -1.09400272e+00 1.55318141e-01 -9.32267532e-02
9.41615880e-01 -4.80937719e-01 1.09378062e-01 5.91271110e-02
3.96282703e-01 -1.05901408e+00 3.64471853e-01 7.85892367e-01
8.69227409e-01 -8.87767434e-01 8.67525756e-01 1.67709231e-01
-1.20358038e+00 -7.92558491e-02 -6.01044834e-01 3.57807368e-01
2.53887326e-01 3.96416485e-01 -5.65439761e-01 4.17177409e-01
8.83571029e-01 7.89768517e-01 -7.36398041e-01 9.17297482e-01
2.40335763e-02 1.38180658e-01 -9.30125713e-02 4.04998600e-01
-9.65715870e-02 -5.11656344e-01 4.01007891e-01 1.27103984e+00
3.11912477e-01 3.03560821e-03 3.17999244e-01 8.68544817e-01
-1.88443035e-01 -1.48631543e-01 -6.01178050e-01 3.23100179e-01
2.41491035e-01 1.13673031e+00 -4.12235767e-01 -4.90138501e-01
-4.77354765e-01 1.48050570e+00 4.35216159e-01 4.60322082e-01
-8.13606799e-01 -2.27706149e-01 6.76123738e-01 1.89555317e-01
1.86321646e-01 2.88245524e-03 1.60693884e-01 -1.41045380e+00
2.25434005e-02 -8.39729846e-01 5.57528615e-01 -5.56172132e-01
-1.88211870e+00 7.56300271e-01 2.60357913e-02 -1.33694232e+00
-2.85214871e-01 -4.68984276e-01 -4.98140663e-01 9.42415655e-01
-1.34319878e+00 -1.42440426e+00 -8.62609625e-01 1.08884358e+00
5.19318342e-01 -6.88462079e-01 7.57669270e-01 6.86878681e-01
-7.31529117e-01 9.24661100e-01 2.10110009e-01 4.87865359e-01
8.82562160e-01 -1.20740545e+00 3.31922174e-01 1.00446308e+00
-1.54677123e-01 5.95753133e-01 4.27272052e-01 -6.73290610e-01
-9.42177296e-01 -1.47133207e+00 7.18699992e-01 -5.65540552e-01
2.02987224e-01 -2.76109368e-01 -8.45808148e-01 8.16147685e-01
7.24230602e-04 2.70553589e-01 7.12475777e-01 -2.68837929e-01
-2.47972682e-01 -2.52874076e-01 -1.43705153e+00 4.76156443e-01
9.29245532e-01 -4.18310076e-01 -4.84016389e-01 4.34269398e-01
2.42813468e-01 -7.44974464e-02 -7.19526410e-01 1.89022958e-01
3.05704594e-01 -9.61293697e-01 1.41705859e+00 -6.80474937e-01
1.51707798e-01 -4.16546255e-01 3.50553952e-02 -1.31120050e+00
-2.88805187e-01 -4.73628074e-01 2.81391323e-01 1.71460307e+00
-1.75618753e-01 -5.55281103e-01 9.95421886e-01 1.10917628e+00
3.12990069e-01 -6.29078746e-02 -6.88262820e-01 -8.42629850e-01
-7.22439364e-02 2.71448754e-02 5.46527982e-01 9.81479824e-01
-5.16885638e-01 6.84819445e-02 -8.76724541e-01 3.33240598e-01
1.27705085e+00 -1.35132089e-01 1.14521253e+00 -1.23417282e+00
-1.80848345e-01 -5.75798750e-02 -3.99602264e-01 -8.01160216e-01
5.04108191e-01 -8.34934413e-01 -1.30201057e-01 -1.27301145e+00
5.75989485e-01 -7.33880639e-01 3.16864811e-02 2.18478128e-01
-5.16453922e-01 5.32343924e-01 3.25883567e-01 3.92127216e-01
-5.23473799e-01 5.10761380e-01 9.04303789e-01 -3.77001703e-01
-1.49457291e-01 2.32791871e-01 -4.25611287e-01 8.16863894e-01
7.71628082e-01 -3.72066766e-01 -3.47716331e-01 -5.37164271e-01
-3.65844369e-01 -2.34470218e-01 8.79347205e-01 -1.21838498e+00
2.02583119e-01 6.25580223e-03 7.00013816e-01 -3.67614359e-01
3.69883597e-01 -1.14224052e+00 3.40825349e-01 1.45756543e-01
-3.92356634e-01 6.57703876e-02 -4.08378206e-02 6.65355742e-01
-1.99162215e-01 -5.16094565e-01 1.11913633e+00 -3.21087152e-01
-5.97275674e-01 4.67795610e-01 -3.39826234e-02 1.89990178e-01
1.19600856e+00 -1.23357929e-01 2.63397750e-02 -2.64691323e-01
-7.36820281e-01 3.28422189e-02 5.94137967e-01 4.85509127e-01
5.67609608e-01 -1.58074498e+00 -8.18686843e-01 3.07216287e-01
9.36786905e-02 -1.64548419e-02 3.74099195e-01 2.61253774e-01
-3.56490761e-01 1.92186311e-01 -2.74520576e-01 -5.12732208e-01
-1.56096256e+00 8.45409155e-01 4.64581639e-01 -3.03693146e-01
-7.11301982e-01 7.33000576e-01 1.76112249e-01 -4.92280781e-01
3.36581081e-01 2.45786771e-01 -3.57612073e-01 -1.51601220e-02
8.07448268e-01 5.52674532e-01 -3.01494271e-01 -1.05155253e+00
-2.48659655e-01 1.00570798e+00 -2.27651596e-01 9.88783985e-02
1.35251677e+00 -2.39047885e-01 9.90417413e-03 -8.51444751e-02
1.40930104e+00 -1.76246300e-01 -1.54165244e+00 -3.61546487e-01
-1.95754945e-01 -7.06561923e-01 -3.16344142e-01 -3.68385851e-01
-1.25080597e+00 6.81317210e-01 9.70725060e-01 -1.06822506e-01
1.03232265e+00 -1.10970832e-01 9.56803024e-01 2.71742612e-01
2.46287584e-01 -1.30248380e+00 2.80621141e-01 3.48365344e-02
7.64805794e-01 -1.64519620e+00 -4.55466025e-02 -4.03952003e-01
-7.65704453e-01 8.65397692e-01 7.03629196e-01 -2.98536032e-01
4.03840333e-01 -3.32701914e-02 8.90802965e-02 1.48229524e-01
9.10321847e-02 -1.92411825e-01 3.84896785e-01 1.03326511e+00
4.13583592e-02 -9.74592417e-02 -3.01410239e-02 6.21163905e-01
7.77262300e-02 8.38699713e-02 3.45654309e-01 5.01394689e-01
1.68771520e-02 -1.22541976e+00 -8.05044353e-01 1.90328136e-01
-5.14696479e-01 2.05162689e-01 -2.76534736e-01 6.52229011e-01
3.55266869e-01 9.34239924e-01 1.34112284e-01 -2.85819054e-01
4.54980165e-01 -1.19517557e-01 4.05098736e-01 -3.32765281e-01
-4.88399476e-01 -1.90491468e-01 -3.05733025e-01 -2.97994405e-01
-7.74260104e-01 -7.17044771e-01 -7.05257773e-01 -2.79415250e-01
-4.20843158e-03 5.22123687e-02 4.22027647e-01 6.90238774e-01
2.78876305e-01 3.06769550e-01 6.02363944e-01 -1.18953252e+00
-5.21429598e-01 -7.27712095e-01 -5.30400097e-01 1.30603683e+00
2.83635885e-01 -6.99649811e-01 -3.00569355e-01 6.65810883e-01] | [14.665738105773926, 1.0250188112258911] |
0d046d99-feee-44f3-89ce-fff11f6f5b85 | iit-dhanbad-lt-edi-acl2022-hope-speech | null | null | https://aclanthology.org/2022.ltedi-1.32 | https://aclanthology.org/2022.ltedi-1.32.pdf | IIT Dhanbad @LT-EDI-ACL2022- Hope Speech Detection for Equality, Diversity, and Inclusion | Hope is considered significant for the wellbeing,recuperation and restoration of humanlife by health professionals. Hope speech reflectsthe belief that one can discover pathwaysto their desired objectives and become rousedto utilise those pathways. Hope speech offerssupport, reassurance, suggestions, inspirationand insight. Hate speech is a prevalent practicethat society has to struggle with everyday.The freedom of speech and ease of anonymitygranted by social media has also resulted inincitement to hatred. In this paper, we workto identify and promote positive and supportivecontent on these platforms. We work withseveral machine learning models to classify socialmedia comments as hope speech or nonhopespeech in English. This paper portraysour work for the Shared Task on Hope SpeechDetection for Equality, Diversity, and Inclusionat LT-EDI-ACL 2022. | ['Rajendra Pamula', 'Ritesh Kumar', 'Vishesh Gupta'] | null | null | null | null | ltedi-acl-2022-5 | ['hope-speech-detection'] | ['natural-language-processing'] | [-5.81516325e-01 8.03852677e-01 -1.00352085e+00 -3.75146382e-02
-7.18275130e-01 -2.35898346e-01 1.01122749e+00 7.08407640e-01
-4.24328744e-01 1.03277814e+00 1.52498519e+00 -2.26775020e-01
5.39902821e-02 -1.96486160e-01 8.75232443e-02 -2.93935686e-01
3.25674415e-01 -2.67672509e-01 -3.75781476e-01 -6.03258073e-01
3.59914750e-01 4.32847530e-01 -7.30932355e-01 2.75641710e-01
7.97557294e-01 7.32696056e-03 -6.78604722e-01 7.36536264e-01
-3.58407050e-01 1.61693728e+00 -6.04827285e-01 -9.09375370e-01
-5.26947975e-01 -4.74260718e-01 -1.06777143e+00 2.89245546e-02
1.17297836e-01 -4.51760858e-01 -4.03835386e-01 9.76782262e-01
6.83871508e-01 -5.56908995e-02 3.77241760e-01 -1.37727439e+00
-8.53409767e-01 9.42297816e-01 -3.77622604e-01 4.76417154e-01
7.14297116e-01 5.80228530e-02 6.34524405e-01 -1.05531323e+00
1.07268631e+00 1.18428338e+00 7.05241263e-01 5.73443949e-01
-1.14121294e+00 -8.20692122e-01 -6.91690207e-01 -1.14991389e-01
-1.00938296e+00 -1.44328856e+00 7.86996603e-01 -6.02466226e-01
8.49309683e-01 6.12058759e-01 1.20386589e+00 1.32660174e+00
1.73259154e-01 6.57890916e-01 9.40319955e-01 -2.32686862e-01
-1.51907401e-02 6.78151071e-01 1.69304296e-01 6.01899505e-01
-2.32156217e-02 -3.46040577e-01 -9.49325204e-01 -6.21565104e-01
9.88431182e-03 1.13238089e-01 -4.98867244e-01 5.34023881e-01
-9.79929924e-01 1.04607117e+00 5.05381882e-01 4.70944256e-01
-4.84804064e-01 -2.72978038e-01 6.41668558e-01 2.49275759e-01
8.91484618e-01 3.90133828e-01 5.05148232e-01 -7.85030425e-01
-8.14530671e-01 -8.90827700e-02 1.06592000e+00 2.41729513e-01
1.81394190e-01 -4.42242362e-02 5.28168492e-03 1.22522759e+00
4.57320958e-01 5.53047895e-01 2.64837831e-01 -1.18768203e+00
7.81353265e-02 2.32730135e-01 2.26499583e-03 -1.62528706e+00
-5.78848183e-01 -4.84575391e-01 -6.15932465e-01 1.57898694e-01
2.21166387e-01 -4.84799236e-01 -6.08131625e-02 1.33561742e+00
3.20608348e-01 -3.77987206e-01 3.03172201e-01 5.83967447e-01
1.08595812e+00 5.94016254e-01 3.14355046e-01 -4.86907959e-01
1.06015944e+00 -6.62772596e-01 -1.40448761e+00 -1.22066386e-01
1.14092612e+00 -1.37846708e+00 7.41616070e-01 3.91131997e-01
-1.26704526e+00 4.29617405e-01 -8.44851851e-01 -2.90324807e-01
-1.65058464e-01 -6.22362375e-01 4.00556862e-01 8.83878827e-01
-1.20191741e+00 7.09180832e-01 -1.85642868e-01 -9.81207192e-01
9.55582917e-01 -4.05615300e-01 -7.08244741e-01 1.06410451e-01
-1.09126830e+00 9.13672864e-01 -8.74032751e-02 -2.56370246e-01
-2.19486788e-01 -4.40773547e-01 -6.51932776e-01 -4.54891384e-01
2.98332330e-03 -2.33093753e-01 1.01347470e+00 -9.68156159e-01
-8.95702958e-01 1.35044682e+00 2.00749338e-01 -3.27021122e-01
3.13677490e-01 -4.29488927e-01 -7.70372450e-01 3.28850210e-01
3.17149639e-01 6.76200807e-01 4.94137704e-01 -6.48570001e-01
-1.12727284e-02 -2.97588080e-01 -5.27441837e-02 9.58869606e-02
-1.14628208e+00 9.03922677e-01 7.92688847e-01 -6.45788193e-01
-7.04962164e-02 -5.03299654e-01 1.84800774e-01 2.31406257e-01
-1.02020955e+00 -1.19599849e-01 8.24484706e-01 -1.00143421e+00
1.27318847e+00 -2.35753036e+00 -3.45317930e-01 -2.86993325e-01
8.44218314e-01 1.80056110e-01 4.82535422e-01 9.85213459e-01
5.40830716e-02 8.17512929e-01 4.97230411e-01 -2.69839942e-01
-6.37080818e-02 9.50355977e-02 -3.58357886e-03 9.37975347e-01
-1.68858878e-02 4.14283186e-01 -1.40717888e+00 -6.88633144e-01
-3.42015654e-01 8.59806061e-01 -5.14290512e-01 1.11117112e-02
6.52238131e-01 -3.86358947e-02 -1.69339925e-01 5.50769448e-01
3.64934593e-01 -3.61656040e-01 1.51895598e-01 4.27411824e-01
-7.45660722e-01 4.66188341e-01 -1.39485523e-01 1.14204323e+00
8.19970667e-02 9.42022443e-01 4.54406291e-01 -6.36975914e-02
1.05958962e+00 6.05780661e-01 2.85295874e-01 -1.22693896e-01
2.79240847e-01 2.37737328e-01 -8.89134929e-02 -7.58405805e-01
5.94622314e-01 -6.37632310e-01 9.43221152e-02 4.48862344e-01
-4.77942318e-01 -1.70069352e-01 -7.49503911e-01 7.35957682e-01
7.15846002e-01 -5.35634577e-01 5.76688111e-01 -4.47884679e-01
7.27490708e-02 -1.43268585e-01 2.20408067e-01 3.03632557e-01
-9.44533229e-01 1.85575217e-01 6.62179172e-01 -1.25410184e-01
-1.06601214e+00 -6.04538321e-01 -1.71974152e-01 9.81209695e-01
-5.63321292e-01 -4.23983186e-01 -4.27535743e-01 -2.16168031e-01
-3.96101028e-01 1.18425441e+00 -3.25907737e-01 -2.70994067e-01
1.10160321e-01 -2.26028755e-01 8.31178904e-01 -6.70996159e-02
5.32232344e-01 -7.86476672e-01 -3.28901440e-01 -6.85786009e-02
-4.40779924e-01 -7.02279568e-01 -6.08495712e-01 -3.44407111e-01
-4.71153170e-01 -7.57989585e-01 -9.12061810e-01 -6.44795060e-01
1.66989475e-01 3.18406224e-01 4.83954728e-01 3.36770713e-01
-9.09228474e-02 3.09140027e-01 -3.81563485e-01 -5.01626551e-01
-8.60668600e-01 -1.74381167e-01 -5.64358458e-02 -2.88134784e-01
3.74599069e-01 -5.60746908e-01 -2.61264116e-01 -5.36483705e-01
-3.67124081e-01 2.92263329e-01 -3.22146952e-01 7.64260769e-01
-4.57694739e-01 -5.47905564e-01 6.78182781e-01 -8.06321442e-01
8.91790450e-01 -1.22452581e+00 6.48893595e-01 -3.58951449e-01
-5.95159650e-01 -6.75000191e-01 3.85638960e-02 -1.04114218e-02
-9.55266654e-01 -5.20886958e-01 -4.89008605e-01 6.39544353e-02
-1.82234988e-01 4.31304544e-01 3.16812038e-01 1.70769840e-01
9.93073046e-01 -2.92796224e-01 2.96136588e-01 -2.87748367e-01
3.60458940e-01 1.17197502e+00 2.11789265e-01 7.81127438e-02
3.88293833e-01 4.89041567e-01 -4.06380534e-01 -1.54172838e+00
-8.07662249e-01 -5.41325748e-01 2.12464631e-02 -7.12827802e-01
1.08359301e+00 -7.91791499e-01 -7.16627479e-01 4.58383441e-01
-1.37164056e+00 1.11581400e-01 -2.88515806e-01 5.18629849e-01
-9.38799009e-02 3.66712689e-01 -8.91243696e-01 -1.46303618e+00
-5.64890385e-01 -1.04193203e-01 7.64048398e-02 3.56792808e-01
-8.49001527e-01 -1.20386755e+00 2.52454728e-01 6.30709827e-01
5.05250394e-01 6.50407434e-01 5.12808979e-01 -9.91914451e-01
3.54489416e-01 -2.13681117e-01 -1.43350929e-01 -1.60942283e-02
5.89264221e-02 5.03586326e-03 -1.11296201e+00 3.89540270e-02
1.65444911e-01 -1.06335187e+00 3.62676024e-01 -9.63995755e-02
3.52058381e-01 -1.28226364e+00 -2.38036867e-02 1.14879332e-01
8.46284568e-01 -2.59918302e-01 7.73815334e-01 5.86670876e-01
2.74995059e-01 9.16352212e-01 1.61597714e-01 1.06316054e+00
5.10098994e-01 1.67160362e-01 2.77350605e-01 -2.52281874e-01
-2.00301066e-01 -5.63837588e-01 4.70780581e-01 9.90705609e-01
-8.03058445e-02 -8.02533701e-02 -1.35973239e+00 6.26518428e-01
-1.31433940e+00 -1.50929439e+00 -7.70960808e-01 1.87261486e+00
8.09573591e-01 2.60478318e-01 5.96880913e-01 2.41222829e-01
5.42706668e-01 5.26842535e-01 -2.14781426e-02 -9.86054599e-01
-2.56652445e-01 -5.81408083e-01 1.86676264e-01 7.44665205e-01
-5.76514423e-01 5.83710134e-01 6.58078003e+00 3.50250602e-01
-1.01742589e+00 6.52615488e-01 1.02370441e+00 -2.32890815e-01
-5.21236181e-01 -2.24106103e-01 -3.07751268e-01 -3.49638872e-02
1.26278543e+00 -6.83805346e-01 3.66447657e-01 6.11519277e-01
7.17109621e-01 1.16622247e-01 -2.91966319e-01 7.48127937e-01
3.62124056e-01 -1.38552308e+00 -7.90661633e-01 -3.55698094e-02
3.19669515e-01 2.29964435e-01 4.13928419e-01 -1.24807470e-01
2.29695320e-01 -9.16043639e-01 6.22424483e-01 5.17912149e-01
6.97193205e-01 -7.83742845e-01 4.81963664e-01 3.76093268e-01
-1.43745869e-01 -1.13716125e-01 -1.35423675e-01 -3.30794185e-01
3.28871936e-01 6.34989142e-01 -1.29604733e+00 -1.76294908e-01
3.81237745e-01 1.12073088e+00 -1.57143652e-01 1.10098004e+00
-3.30986589e-01 7.90155888e-01 1.97056666e-01 -3.66028547e-01
1.93096012e-01 3.64746928e-01 1.06858790e+00 1.48320127e+00
2.05537647e-01 1.18554428e-01 -1.85735838e-03 4.67344642e-01
-2.10746035e-01 6.79489195e-01 -9.70642269e-01 -1.07492185e+00
6.17146432e-01 1.14918637e+00 -5.27266026e-01 -8.47936571e-02
-3.74350965e-01 7.53931642e-01 2.45654970e-01 -6.97091827e-03
-3.01269144e-01 -3.95175964e-01 5.09802699e-01 7.74704933e-01
-7.02985346e-01 2.57081762e-02 -2.33412743e-01 -8.85489881e-01
-7.17215478e-01 -7.79418051e-01 4.70595509e-01 -8.93212855e-01
-1.21901715e+00 3.97916913e-01 -4.39993262e-01 -5.32442451e-01
-2.45999619e-02 2.15270802e-01 -6.04119658e-01 6.51832342e-01
-1.37059128e+00 -1.11010039e+00 1.85881987e-01 2.46961311e-01
4.09597874e-01 -1.30105845e-03 9.42172229e-01 1.28448173e-01
-4.62879479e-01 4.76317734e-01 -7.23289102e-02 7.37042725e-02
1.02166808e+00 -7.56535828e-01 -1.46592960e-01 3.74065042e-01
-6.05502486e-01 5.28492689e-01 1.07881773e+00 -8.29783797e-01
-1.19052935e+00 -5.65590620e-01 1.91422343e+00 -1.02839135e-01
1.30226767e+00 -1.59312766e-02 -7.81739175e-01 3.89248550e-01
8.49403977e-01 -5.35710096e-01 1.33292246e+00 5.62239885e-01
-4.75739419e-01 5.35140812e-01 -1.45187891e+00 7.17122495e-01
9.90707636e-01 -8.98976862e-01 -6.86909139e-01 1.06706011e+00
8.05280089e-01 8.86474252e-02 -1.05942476e+00 -1.01154625e+00
4.79915887e-01 -1.13513827e+00 7.66960680e-01 -9.33554888e-01
1.01643038e+00 6.72930598e-01 1.15840919e-02 -1.19252491e+00
-3.42419326e-01 -1.40669990e+00 1.66331619e-01 1.52990758e+00
2.93934166e-01 -7.02853978e-01 8.21800232e-01 1.27648628e+00
-4.41478819e-01 -4.27406400e-01 -9.67714369e-01 -3.26142818e-01
5.65570295e-01 -1.32624403e-01 2.88613409e-01 1.92415917e+00
1.11008775e+00 5.14486015e-01 -8.75784934e-01 -3.97215098e-01
4.65562701e-01 -9.08887446e-01 4.75292593e-01 -1.07769454e+00
-1.21017769e-01 -5.56241870e-01 -3.89158815e-01 -1.51999563e-01
-1.54028669e-01 -1.07714260e+00 -4.47635740e-01 -1.43878675e+00
6.62297964e-01 -9.05295275e-03 1.21731892e-01 7.85508811e-01
2.25759014e-01 1.21764779e-01 3.49261850e-01 3.39929044e-01
-5.56108236e-01 3.05669308e-01 1.19849312e+00 4.19436917e-02
-3.09278846e-01 -5.07472932e-01 -1.37077558e+00 6.08783484e-01
9.59512591e-01 -6.77048683e-01 -2.65893579e-01 1.60433501e-01
7.54652441e-01 4.36686575e-01 4.89900798e-01 -5.75262904e-01
2.03100383e-01 -3.59764069e-01 4.35403734e-02 -1.66550055e-01
6.75488293e-01 -2.25911126e-01 1.72523081e-01 9.05394435e-01
-6.12533808e-01 -1.28278494e-01 -6.91758394e-02 1.47374645e-01
2.20803574e-01 -3.95539612e-01 7.71276772e-01 1.46919206e-01
2.38994822e-01 -3.62717152e-01 -7.64148295e-01 4.21549052e-01
6.73990130e-01 -1.06675573e-01 -9.04006422e-01 -1.27431190e+00
-1.06721663e+00 -9.67163369e-02 7.34849453e-01 1.33335456e-01
8.38525355e-01 -1.27492714e+00 -1.23365915e+00 -3.15237790e-01
1.81871410e-02 -1.21730971e+00 2.68495768e-01 1.41833234e+00
-1.40161276e-01 -5.13840280e-03 -7.12177679e-02 1.63116530e-01
-1.43883860e+00 4.67788965e-01 1.18912533e-01 4.50865626e-01
-8.74435365e-01 9.14767265e-01 -6.36628509e-01 -9.39810202e-02
5.55898920e-02 7.20211446e-01 -5.15164912e-01 3.36788535e-01
1.20372546e+00 8.65224421e-01 -5.25850356e-01 -1.18891466e+00
-3.04304838e-01 -5.43420851e-01 -2.06369579e-01 -7.20894039e-02
1.62348330e+00 -2.13555962e-01 -3.56512457e-01 6.22213066e-01
1.36906826e+00 3.87850285e-01 -3.49738091e-01 3.58054817e-01
1.02442965e-01 -1.04940009e+00 4.35333341e-01 -7.24436760e-01
-4.61416960e-01 7.12786138e-01 4.24028516e-01 7.51697361e-01
3.82656664e-01 1.20317705e-01 9.33255136e-01 6.16226904e-02
-2.66387254e-01 -1.02684033e+00 4.72721547e-01 1.11104347e-01
1.35334170e+00 -1.26580489e+00 -5.70100509e-02 -4.48642731e-01
-7.23938525e-01 1.31533062e+00 -3.97367440e-02 6.69165552e-01
8.96596134e-01 -6.85286745e-02 1.15187444e-01 -3.86590034e-01
-6.68766797e-01 4.85959440e-01 -3.65586579e-01 7.92827427e-01
1.08781004e+00 2.60255724e-01 -8.72249842e-01 4.47465241e-01
-2.63459325e-01 1.33103639e-01 1.02245414e+00 6.85724795e-01
-9.73116398e-01 -7.72053897e-01 -4.76535082e-01 2.81402320e-01
-9.47421849e-01 -8.88466835e-02 -8.96355450e-01 5.39978206e-01
-1.74719334e-01 1.43755817e+00 -3.60153675e-01 -3.21732491e-01
-7.37588182e-02 7.51226321e-02 -4.37238872e-01 -4.57542866e-01
-7.91627765e-01 3.16161633e-01 1.30357909e+00 -1.14367187e-01
-4.35769558e-01 -1.02396238e+00 -1.24482477e+00 -1.12936699e+00
-1.08181119e-01 2.97478020e-01 7.48017609e-01 6.19181335e-01
3.46260428e-01 1.53378127e-02 4.97766614e-01 -8.47395733e-02
-2.60464013e-01 -5.42585611e-01 -6.38279736e-01 1.47329509e-01
4.29072708e-01 2.35400591e-02 -3.52091908e-01 -3.79260391e-01] | [8.897224426269531, 10.645051002502441] |
78e6ba64-330c-4670-a746-46d3052a0879 | cross-view-image-synthesis-using-geometry | 1808.05469 | null | https://arxiv.org/abs/1808.05469v2 | https://arxiv.org/pdf/1808.05469v2.pdf | Cross-view image synthesis using geometry-guided conditional GANs | We address the problem of generating images across two drastically different views, namely ground (street) and aerial (overhead) views. Image synthesis by itself is a very challenging computer vision task and is even more so when generation is conditioned on an image in another view. Due the difference in viewpoints, there is small overlapping field of view and little common content between these two views. Here, we try to preserve the pixel information between the views so that the generated image is a realistic representation of cross view input image. For this, we propose to use homography as a guide to map the images between the views based on the common field of view to preserve the details in the input image. We then use generative adversarial networks to inpaint the missing regions in the transformed image and add realism to it. Our exhaustive evaluation and model comparison demonstrate that utilizing geometry constraints adds fine details to the generated images and can be a better approach for cross view image synthesis than purely pixel based synthesis methods. | ['Krishna Regmi', 'Ali Borji'] | 2018-08-14 | null | null | null | null | ['cross-view-image-to-image-translation'] | ['computer-vision'] | [ 6.39654219e-01 2.78991014e-01 3.38454545e-01 -6.98483512e-02
-3.64330262e-01 -8.70055795e-01 7.31170416e-01 -5.50467849e-01
2.62793720e-01 7.82107711e-01 1.38748050e-01 -8.24096277e-02
2.98450083e-01 -1.17639577e+00 -8.99892271e-01 -6.63468361e-01
6.36022389e-01 1.37508675e-01 3.83834720e-01 -4.74175185e-01
1.31797522e-01 7.35175371e-01 -1.55689800e+00 5.34768403e-01
6.18495762e-01 5.31877637e-01 3.34285468e-01 7.46394753e-01
2.89763510e-02 5.42682350e-01 -5.66662669e-01 -5.50296128e-01
8.53605807e-01 -7.12537825e-01 -6.32408857e-01 7.55707860e-01
7.28005946e-01 -4.27051008e-01 -4.44549561e-01 1.08665693e+00
1.90503657e-01 -2.41411086e-02 4.99826252e-01 -1.28034496e+00
-4.72504497e-01 1.39538944e-01 -8.71082127e-01 -4.69245821e-01
8.22266698e-01 1.69894621e-01 5.91063678e-01 -5.88625252e-01
1.05979276e+00 1.28652346e+00 3.71582717e-01 4.07059938e-01
-1.42365193e+00 -3.74398768e-01 1.38145104e-01 -2.84546852e-01
-1.19922400e+00 -3.96841466e-01 1.05823398e+00 -4.03171360e-01
2.55882084e-01 4.40204203e-01 6.84418201e-01 9.77452815e-01
5.46392858e-01 1.83028102e-01 1.37961340e+00 -5.54553211e-01
4.66958694e-02 3.15221757e-01 -7.41856456e-01 6.02586389e-01
5.34578487e-02 3.63336504e-01 -2.33879015e-01 -2.75484603e-02
1.18114698e+00 3.24873924e-01 -8.91135037e-01 -7.86531329e-01
-1.33630776e+00 6.84369564e-01 3.45613390e-01 5.80032282e-02
-3.91380012e-01 -3.17144170e-02 -2.75883883e-01 2.74685681e-01
1.73511088e-01 4.57455903e-01 -1.14161305e-01 5.37578940e-01
-9.35162485e-01 4.44536448e-01 6.46939278e-01 1.00552940e+00
8.65755796e-01 2.88628042e-01 1.17840894e-01 5.24078727e-01
9.28149074e-02 6.28045261e-01 1.91219896e-02 -1.19465053e+00
6.16632223e-01 5.40487230e-01 3.00334424e-01 -1.25504363e+00
2.33915538e-01 -1.40013248e-01 -8.07889521e-01 8.43711317e-01
4.14528847e-01 -2.86040336e-01 -1.06450343e+00 1.58589602e+00
3.03002864e-01 -2.57460207e-01 8.23821649e-02 6.45476520e-01
5.08683622e-01 8.24720800e-01 -6.17029727e-01 -1.40412971e-01
1.06391609e+00 -8.00486386e-01 -7.13383555e-01 -4.19602871e-01
-2.69335378e-02 -1.18344092e+00 6.92437291e-01 2.71538854e-01
-1.42716467e+00 -6.56491816e-01 -1.24545538e+00 -1.02344356e-01
-2.82653630e-01 -3.57762016e-02 1.62510961e-01 5.38404167e-01
-9.78275418e-01 5.08550107e-01 -4.45516020e-01 -2.32479244e-01
-1.25139475e-01 1.05914682e-01 -7.71468043e-01 -3.89320076e-01
-1.02337325e+00 8.22267175e-01 2.92251259e-01 -2.18260258e-01
-6.23516738e-01 -6.41486168e-01 -9.16269302e-01 5.94641455e-02
2.57507503e-01 -9.07898903e-01 6.89341843e-01 -1.16199338e+00
-1.45128405e+00 9.79340136e-01 3.97742242e-02 3.03122438e-02
7.63951361e-01 2.86603659e-01 -1.75586417e-01 1.72254547e-01
3.39612737e-02 8.17533255e-01 1.07001746e+00 -2.03523421e+00
-5.11154056e-01 -2.70213634e-01 3.32714885e-01 3.87667954e-01
4.59400743e-01 -3.37068915e-01 -4.71997201e-01 -6.47665858e-01
4.26241398e-01 -1.03118753e+00 -9.69505534e-02 2.09205970e-01
-4.92508471e-01 8.43279779e-01 1.10924590e+00 -8.59090686e-01
6.02889836e-01 -2.02211499e+00 3.80024463e-01 1.46407962e-01
5.24518862e-02 2.82460153e-02 -4.68869507e-02 8.89113784e-01
-2.80567169e-01 -1.85152993e-01 -3.00653428e-01 -1.87618911e-01
-5.78614056e-01 3.47932309e-01 -5.78730881e-01 3.68673086e-01
-4.10564989e-02 5.84992707e-01 -7.37167180e-01 -1.71170354e-01
4.83174980e-01 6.11677885e-01 -5.62885880e-01 4.59740639e-01
-1.63590074e-01 9.01931703e-01 -1.83942616e-01 2.25741923e-01
1.05177248e+00 1.33542925e-01 2.35511363e-01 -4.17307228e-01
-3.82372625e-02 -2.53972590e-01 -1.22745180e+00 1.73202395e+00
-5.91336429e-01 5.14102459e-01 1.96287736e-01 -6.46188200e-01
8.95147026e-01 3.71717751e-01 4.09991533e-01 -4.45177495e-01
1.39287576e-01 -6.95557743e-02 -2.67579202e-02 -2.50723481e-01
4.59380209e-01 -5.05468547e-01 1.28830686e-01 3.88546914e-01
-9.26400945e-02 -9.12365317e-01 4.03829524e-03 -8.76925047e-03
5.58945537e-01 2.80638695e-01 2.03833178e-01 2.75889263e-02
5.13323128e-01 -2.30791941e-01 4.20792013e-01 3.49263906e-01
4.59046632e-01 1.47059703e+00 5.27116656e-01 -4.62684005e-01
-1.42054486e+00 -1.12071002e+00 2.30987892e-01 6.29647821e-02
3.92609149e-01 -1.26927555e-01 -9.07342792e-01 -6.09934807e-01
-2.71553785e-01 7.40696013e-01 -5.90388298e-01 -1.05056919e-01
-5.97075641e-01 -1.19571388e-01 -2.57158768e-03 2.49601185e-01
6.66562855e-01 -7.28426874e-01 -7.83528984e-01 -2.01034453e-02
-4.51018989e-01 -1.40747654e+00 -6.58396304e-01 -5.18392920e-02
-7.50854552e-01 -1.14046311e+00 -9.79527116e-01 -6.90206587e-01
1.02974033e+00 6.17804885e-01 1.20527220e+00 -2.06274450e-01
-1.89012513e-01 1.89033121e-01 -2.35845238e-01 -1.74198896e-01
-7.18494594e-01 -5.55875421e-01 -2.28769094e-01 4.29310262e-01
-5.32223463e-01 -7.60105014e-01 -6.58943653e-01 5.37408233e-01
-1.30158782e+00 6.12148404e-01 2.75349736e-01 8.10859740e-01
4.85906184e-01 2.41014346e-01 -2.27395803e-01 -9.01650190e-01
1.94912568e-01 -1.05307952e-01 -7.09347904e-01 2.60657370e-01
-1.11827984e-01 -2.84555159e-03 9.03721690e-01 -2.16664001e-01
-1.28369081e+00 3.44308347e-01 1.62031092e-02 -6.72284365e-01
-1.26948267e-01 -2.01322153e-01 -5.53690374e-01 -1.71801671e-01
4.44065839e-01 3.21446180e-01 2.37488240e-01 -2.58787006e-01
4.98785079e-01 1.88586339e-01 4.94971991e-01 -2.69424558e-01
1.05607939e+00 1.00138760e+00 2.41125643e-01 -7.71495879e-01
-4.59063858e-01 8.04814994e-02 -8.84707570e-01 -9.60602239e-02
1.09883344e+00 -7.85499036e-01 -2.56196052e-01 2.04818308e-01
-1.37385857e+00 -7.30523318e-02 -4.97453481e-01 2.91529834e-01
-8.32923830e-01 4.74274188e-01 -1.01800263e-01 -3.46423924e-01
8.57209712e-02 -1.47057724e+00 1.20793128e+00 1.62436470e-01
-3.58872637e-02 -1.02972341e+00 1.61861554e-02 3.64696860e-01
6.09108284e-02 6.87570751e-01 8.71807992e-01 3.45823199e-01
-8.45562935e-01 -1.54167846e-01 -4.00657021e-02 5.39547503e-01
4.81639743e-01 2.28432804e-01 -8.86469305e-01 -3.02101314e-01
2.81000316e-01 5.22925965e-02 5.10981500e-01 4.32134658e-01
6.09349549e-01 -1.85193464e-01 -2.84628361e-01 8.14312339e-01
1.71667862e+00 5.22747874e-01 1.09483349e+00 -5.69967851e-02
7.66585290e-01 9.25752938e-01 3.32376122e-01 7.36002997e-02
-1.02432847e-01 9.59912777e-01 4.52959746e-01 -5.36697865e-01
-3.36250603e-01 -6.74352169e-01 2.01073006e-01 3.02335113e-01
-1.64704472e-01 -5.80083847e-01 -4.79106635e-01 3.65392268e-01
-1.46989608e+00 -1.18398356e+00 -1.37273930e-02 2.46343398e+00
3.26157838e-01 -1.96686134e-01 -2.25787923e-01 1.11242466e-01
8.00866485e-01 2.72412300e-01 -7.22020492e-02 -4.46005225e-01
-8.95030946e-02 -2.60740612e-02 5.65850973e-01 6.93125725e-01
-6.24997139e-01 5.86166024e-01 6.78802061e+00 5.67763388e-01
-1.31229043e+00 -1.65454477e-01 6.94882452e-01 7.10948482e-02
-4.99165118e-01 3.56085896e-01 -3.82237762e-01 5.01781642e-01
1.85096323e-01 9.32757482e-02 3.26844424e-01 4.27938133e-01
1.91223189e-01 -2.92208344e-01 -1.01335287e+00 1.00084102e+00
2.59448409e-01 -1.33707190e+00 4.40441787e-01 2.92888254e-01
1.31003296e+00 -6.08412325e-01 1.88707143e-01 -4.95674372e-01
2.72615790e-01 -1.03433859e+00 6.14685059e-01 6.12208128e-01
9.39514935e-01 -7.83897638e-01 4.90778983e-01 3.98393482e-01
-9.26066875e-01 3.17557722e-01 -4.31528807e-01 1.30291700e-01
5.96999526e-01 3.68531197e-01 -3.92058492e-01 8.13535571e-01
3.58236670e-01 2.91840345e-01 -2.05084831e-01 4.79741901e-01
-1.64763302e-01 -2.79497951e-01 -5.24303988e-02 9.07931626e-01
5.79014681e-02 -6.46432281e-01 6.28074348e-01 4.47095156e-01
5.67471802e-01 9.66969207e-02 2.04534605e-01 1.15725851e+00
6.94589093e-02 -3.31380904e-01 -1.29861891e+00 3.01478088e-01
-3.32189798e-02 1.10607636e+00 -7.48639882e-01 -3.13068449e-01
-5.74690819e-01 1.48058927e+00 -2.70717144e-01 4.29033905e-01
-8.03912818e-01 -2.62594491e-01 4.96018022e-01 6.32629871e-01
4.35278505e-01 -8.40186104e-02 -8.86688605e-02 -1.38398409e+00
4.55225371e-02 -9.99629676e-01 -2.85295725e-01 -1.23869359e+00
-7.71710575e-01 7.48366714e-01 1.22951411e-01 -1.70164216e+00
-3.98811340e-01 -3.38503063e-01 -7.01710701e-01 1.21777296e+00
-1.23396003e+00 -1.39171004e+00 -4.19817984e-01 6.27515793e-01
5.88162303e-01 -8.72026309e-02 6.72578812e-01 3.42519283e-02
1.38267979e-01 1.73322350e-01 2.45535105e-01 6.79857098e-03
6.39535785e-01 -1.04864550e+00 4.02568996e-01 1.03468704e+00
8.19156989e-02 4.53266948e-01 7.13611662e-01 -6.03521585e-01
-1.24363720e+00 -1.02704442e+00 5.20981550e-01 -4.74829167e-01
-6.09073937e-02 -2.09014624e-01 -6.38178110e-01 7.10382462e-01
6.89994633e-01 -7.18514696e-02 1.72000691e-01 -7.55418122e-01
-1.58885896e-01 -5.07738814e-02 -1.28953493e+00 6.62633121e-01
6.44879997e-01 -3.87292653e-01 -3.72064084e-01 7.55689964e-02
5.04696369e-01 -5.78293145e-01 -6.48573875e-01 2.54660219e-01
6.33719981e-01 -1.58819163e+00 1.08579326e+00 -1.60868689e-01
9.06681120e-01 -5.58453619e-01 -2.91733503e-01 -1.70378006e+00
-1.12139247e-01 -6.74738944e-01 5.84245801e-01 1.21879542e+00
1.23810895e-01 -5.77010274e-01 7.54007280e-01 3.67187113e-01
1.24209315e-01 -4.93815958e-01 -4.70672697e-01 -6.31914377e-01
2.93823630e-02 2.13356465e-01 6.16728127e-01 9.11452949e-01
-4.00126219e-01 3.50066304e-01 -6.38704717e-01 2.85536230e-01
5.56607008e-01 5.60888648e-01 1.01996422e+00 -8.54782164e-01
-6.41063988e-01 2.89826971e-02 -3.95644575e-01 -9.59544778e-01
-2.23904461e-01 -5.24313152e-01 -6.35943338e-02 -1.47432673e+00
-3.43762822e-02 -9.60037932e-02 6.43272460e-01 -1.69526730e-02
1.00223005e-01 5.67632020e-01 4.85946745e-01 3.18888831e-03
5.01350343e-01 3.87400389e-01 1.95342743e+00 2.56890710e-03
-1.91303954e-01 6.83042929e-02 -6.54610395e-01 7.78937936e-01
4.54305410e-01 -1.80246234e-01 -7.68319666e-01 -4.44687009e-01
2.90477159e-03 6.67047620e-01 3.67942035e-01 -1.02589095e+00
-1.47599176e-01 -2.35264987e-01 7.06540406e-01 -4.72149998e-01
7.82554030e-01 -1.11298442e+00 8.03579390e-01 3.56921345e-01
-5.69372177e-02 2.69895047e-01 5.57066454e-03 4.74446237e-01
-4.18811619e-01 -2.03505173e-01 1.23349953e+00 -6.15637600e-01
-1.69283971e-01 2.19836846e-01 5.12551405e-02 -1.60357788e-01
1.13266897e+00 -6.70732796e-01 1.75118037e-02 -7.30183125e-01
-6.65636301e-01 -3.17927390e-01 1.09137821e+00 2.50843346e-01
8.05547535e-01 -1.30209887e+00 -5.91943204e-01 7.54060209e-01
-9.25396830e-02 7.92463943e-02 3.67915034e-01 4.52316284e-01
-9.67480421e-01 2.65040934e-01 -6.23371959e-01 -5.07981002e-01
-1.40432584e+00 7.56794453e-01 3.77697021e-01 -2.41488487e-01
-7.29214013e-01 3.93877923e-01 9.63548362e-01 -4.20934826e-01
-2.57037878e-01 -1.44431651e-01 1.71631034e-02 -2.47976094e-01
4.35243934e-01 1.31405205e-01 -1.02835611e-01 -9.24424887e-01
2.07759246e-01 1.02356815e+00 2.39466168e-02 -4.56575722e-01
1.12198877e+00 -2.63954192e-01 -9.09943506e-03 1.23209387e-01
1.17055798e+00 5.96992433e-01 -1.48463333e+00 1.41724244e-01
-9.77808475e-01 -1.04449332e+00 -9.40727070e-02 -4.38334227e-01
-1.37102056e+00 1.00239396e+00 4.17182773e-01 2.59041607e-01
1.26248610e+00 -3.47032905e-01 6.31886899e-01 -2.01266855e-01
4.64185476e-01 -7.35617101e-01 -8.27473029e-02 1.36927053e-01
1.20233214e+00 -1.00215364e+00 2.96919286e-01 -9.06391859e-01
-6.99807048e-01 1.22053480e+00 5.48273385e-01 -3.64333868e-01
3.63169074e-01 1.14964887e-01 7.71925151e-02 -1.25835240e-01
-4.25475061e-01 3.50494422e-02 3.06345433e-01 8.78687024e-01
3.37805361e-01 -2.27290079e-01 -7.20437095e-02 -4.46089894e-01
-2.25052267e-01 -3.14342678e-01 9.63286757e-01 7.72928715e-01
-6.61842078e-02 -1.37167168e+00 -7.82478034e-01 2.69575417e-02
-3.50193769e-01 8.98462385e-02 -4.89344507e-01 8.73010397e-01
3.16957235e-01 8.34798276e-01 -4.99035977e-03 -2.40227818e-01
3.45872700e-01 -1.30699933e-01 8.18890750e-01 -6.44084752e-01
-2.04001069e-01 2.40021989e-01 -1.51514784e-01 -5.77614188e-01
-4.20595467e-01 -2.17322305e-01 -7.15953767e-01 -4.15094435e-01
-2.04143524e-01 -2.02360556e-01 5.40690839e-01 6.67760611e-01
2.01074332e-01 4.57957208e-01 9.54747260e-01 -1.16633606e+00
-1.70512542e-01 -3.46637845e-01 -7.50493824e-01 6.45524204e-01
3.61109793e-01 -5.50427318e-01 -4.00576383e-01 5.56168675e-01] | [9.42789077758789, -2.726391077041626] |
186dc54c-e0d5-4182-a5ea-25a953d3d3dc | a-causal-inference-framework-for-leveraging | 2305.08969 | null | https://arxiv.org/abs/2305.08969v1 | https://arxiv.org/pdf/2305.08969v1.pdf | A Causal Inference Framework for Leveraging External Controls in Hybrid Trials | We consider the challenges associated with causal inference in settings where data from a randomized trial is augmented with control data from an external source to improve efficiency in estimating the average treatment effect (ATE). Through the development of a formal causal inference framework, we outline sufficient causal assumptions about the exchangeability between the internal and external controls to identify the ATE and establish the connection to a novel graphical criteria. We propose estimators, review efficiency bounds, develop an approach for efficient doubly-robust estimation even when unknown nuisance models are estimated with flexible machine learning methods, and demonstrate finite-sample performance through a simulation study. To illustrate the ideas and methods, we apply the framework to a trial investigating the effect of risdisplam on motor function in patients with spinal muscular atrophy for which there exists an external set of control patients from a previous trial. | ['Michael R Kosorok', 'Michele Jonsson Funk', 'Stephen R Cole', 'Jiawen Zhu', 'Herb Pang', 'Michael Valancius'] | 2023-05-15 | null | null | null | null | ['causal-inference', 'causal-inference'] | ['knowledge-base', 'miscellaneous'] | [ 6.81914091e-01 3.72081906e-01 -1.20614338e+00 -3.35847199e-01
-9.74570036e-01 -3.27590048e-01 4.66343254e-01 1.16894409e-01
-5.56215107e-01 1.11608946e+00 6.26506567e-01 -5.02850533e-01
-7.08901465e-01 -5.14540970e-01 -9.49993074e-01 -6.12261772e-01
-5.00490665e-01 4.02264029e-01 -4.88745332e-01 5.12790143e-01
1.30040526e-01 8.70412588e-02 -9.27822769e-01 -2.68642213e-02
1.13058007e+00 2.55546600e-01 3.41492854e-02 3.84872377e-01
5.44187129e-01 5.73464334e-01 -1.67486012e-01 -1.11686796e-01
2.85189655e-02 -5.05446732e-01 -6.78299665e-01 1.49588302e-01
3.28733623e-01 -5.38531482e-01 -1.44218266e-01 8.74770463e-01
5.26840508e-01 -1.51701659e-01 9.48990941e-01 -1.42016256e+00
-4.17724967e-01 9.40959752e-01 -7.43305564e-01 -8.53768960e-02
1.08505405e-01 -2.59318855e-03 9.03549075e-01 -3.09761465e-01
6.85168982e-01 1.47964120e+00 8.03473294e-01 3.80637050e-01
-1.71682489e+00 -6.85308993e-01 2.01938972e-01 -2.53661066e-01
-8.17286372e-01 -5.20689309e-01 5.31529970e-02 -5.49862742e-01
2.80914873e-01 1.92166835e-01 4.21717077e-01 1.33170962e+00
4.05940980e-01 4.79574710e-01 1.30004573e+00 -5.06808937e-01
4.99458641e-01 -4.50938374e-01 4.75711256e-01 5.72658181e-01
5.29886186e-01 7.63882995e-01 -3.48779589e-01 -8.83467257e-01
1.01140344e+00 -1.21887431e-01 -4.11570162e-01 -6.30528033e-01
-1.09880424e+00 1.20614052e+00 3.07628840e-01 -1.47493735e-01
-5.39183557e-01 5.11777639e-01 4.36643243e-01 1.49470195e-01
2.20967039e-01 -4.30888422e-02 -5.79094112e-01 3.09010953e-01
-5.42540312e-01 2.02150881e-01 5.53591013e-01 6.78040266e-01
-1.12930693e-01 -1.78666651e-01 -5.02475441e-01 6.49455607e-01
3.06764454e-01 7.26567566e-01 1.39603153e-01 -1.27440941e+00
5.78920186e-01 8.92600641e-02 5.09706378e-01 -4.87097919e-01
-6.42667532e-01 -2.60807633e-01 -8.64813089e-01 1.07204966e-01
6.79229796e-01 -5.62938869e-01 -7.05584824e-01 2.25518322e+00
4.94870335e-01 9.61797610e-02 -3.64088237e-01 5.35731792e-01
-1.19474798e-01 1.48340343e-02 5.26074886e-01 -9.08918023e-01
1.29281056e+00 -2.96445578e-01 -9.59875703e-01 -1.51538879e-01
1.11139178e+00 -1.23391300e-01 7.64186859e-01 2.88383156e-01
-1.34672117e+00 1.42639149e-02 -5.63628376e-01 1.51733875e-01
2.22413957e-01 1.88109487e-01 7.37097085e-01 6.89412475e-01
-6.21399403e-01 7.00869024e-01 -9.20683384e-01 -2.66396523e-01
6.05226040e-01 4.95106429e-01 -3.95366967e-01 -1.59383923e-01
-1.20881414e+00 6.75401509e-01 1.76561236e-01 -7.19264299e-02
-1.02361631e+00 -1.27564025e+00 -6.28531039e-01 1.27662256e-01
4.81421113e-01 -1.35349894e+00 1.13171446e+00 -8.21824849e-01
-7.95194030e-01 4.63765740e-01 -1.94150418e-01 -3.60304534e-01
6.55469298e-01 1.65322572e-02 -5.86828329e-02 -6.63020881e-04
6.29561424e-01 2.54104882e-02 6.23664200e-01 -8.69098663e-01
-8.19650412e-01 -8.43556762e-01 -2.60087043e-01 1.60129908e-02
-3.31250243e-02 2.73845285e-01 7.75371194e-02 -7.31014073e-01
-1.83306709e-01 -9.20780361e-01 -6.41201556e-01 -2.51323402e-01
-6.92483604e-01 -8.00270811e-02 1.27649438e-02 -5.72205007e-01
1.30242348e+00 -1.94732141e+00 9.62033346e-02 3.40231985e-01
2.00643033e-01 -4.74190891e-01 -1.38817534e-01 4.65616167e-01
-7.29070365e-01 2.49749735e-01 -5.17168105e-01 1.32929116e-01
-6.13024691e-03 4.54079881e-02 -9.57917329e-03 8.76499534e-01
-1.08002909e-01 6.82933033e-01 -7.58680344e-01 -3.20961237e-01
-5.51781990e-03 1.02141522e-01 -8.12276721e-01 -6.28614426e-02
2.56212592e-01 3.14702719e-01 -7.10146546e-01 5.68608269e-02
4.41052496e-01 -4.94413435e-01 7.92143524e-01 7.31127486e-02
-8.06175917e-02 2.19730854e-01 -1.33554125e+00 1.28515911e+00
-2.27102116e-01 -1.30418375e-01 4.69678402e-01 -1.20248735e+00
-9.62586030e-02 5.16811728e-01 5.46624064e-01 -2.96572834e-01
9.38089713e-02 1.55282661e-01 1.23701818e-01 -6.05535150e-01
-4.19833660e-01 -5.69805980e-01 -1.95487350e-01 4.35803473e-01
-7.26834014e-02 5.00098884e-01 1.14859134e-01 2.74108738e-01
1.53240132e+00 -2.19507545e-01 7.00066388e-01 -5.56946814e-01
-2.77759116e-02 3.07851285e-03 7.09603190e-01 1.33095193e+00
4.14350368e-02 1.89447388e-01 8.18563402e-01 9.25041270e-03
-1.02865958e+00 -1.16406906e+00 -6.99075699e-01 6.57493293e-01
-6.66601241e-01 -1.11384273e-01 -6.00547194e-01 -7.30318308e-01
4.84919250e-01 6.82068169e-01 -1.10183847e+00 -1.60182431e-01
-1.23656280e-01 -1.35661447e+00 3.19252551e-01 7.75206089e-01
7.13578537e-02 -2.54161924e-01 -3.65067333e-01 2.30070144e-01
-1.80571690e-01 -3.74672621e-01 -5.78019261e-01 1.47653311e-01
-1.21296251e+00 -1.55339813e+00 -7.15980887e-01 -2.29786575e-01
6.24415994e-01 -1.18695408e-01 9.20439601e-01 -1.03657894e-01
-1.42166421e-01 5.21228731e-01 1.90345287e-01 -3.61398816e-01
-3.43117386e-01 -4.04930264e-01 3.20508271e-01 -4.02200818e-01
3.43631320e-02 -4.54672635e-01 -7.64747679e-01 -1.28130466e-02
-7.16920853e-01 -1.92943037e-01 4.76007640e-01 1.19948316e+00
2.98117995e-01 -9.03796330e-02 9.03164029e-01 -1.10608435e+00
4.65973347e-01 -8.35859478e-01 -8.33739936e-01 2.67465889e-01
-8.52341592e-01 -4.60570678e-03 -1.63010314e-01 -4.96959209e-01
-1.23849702e+00 -1.63691882e-02 4.72178429e-01 4.35201079e-02
8.62642899e-02 8.21692586e-01 -2.33913809e-01 3.51110280e-01
5.21817088e-01 -6.21591985e-01 3.68150622e-01 -5.38002908e-01
4.88871843e-01 4.88097161e-01 3.99999619e-01 -6.81748271e-01
2.96836853e-01 6.01502001e-01 3.53364766e-01 -3.99530262e-01
-5.90885937e-01 -8.04945827e-02 -2.93274671e-01 2.57539183e-01
7.53889918e-01 -1.19619012e+00 -1.31650794e+00 4.44521941e-02
-7.71902323e-01 -6.75296962e-01 -2.97169656e-01 1.22695577e+00
-1.02940333e+00 -2.38351710e-02 -6.93776131e-01 -9.98018622e-01
6.71172291e-02 -9.87517834e-01 7.74477601e-01 -3.42008740e-01
-4.73762929e-01 -1.26212490e+00 3.34873706e-01 2.31633738e-01
-1.24409340e-01 2.54644096e-01 1.38511896e+00 -3.65214705e-01
-2.17985749e-01 -2.22032920e-01 -2.26644024e-01 -2.63480186e-01
3.99137467e-01 -1.63977802e-01 -4.09897089e-01 -4.19578612e-01
1.06974088e-01 -1.97952539e-01 6.94550335e-01 1.46694744e+00
1.16231012e+00 -5.68712056e-01 -8.20336342e-01 8.54605883e-02
1.32761693e+00 8.53070021e-02 3.86385411e-01 6.69685155e-02
5.39889753e-01 8.35864723e-01 3.99699092e-01 7.01028228e-01
3.81780952e-01 7.60726213e-01 1.44618273e-01 -1.68603748e-01
1.90398216e-01 -3.43234420e-01 1.32213980e-01 1.28282100e-01
3.42014059e-02 -1.98614940e-01 -5.17144024e-01 6.02492273e-01
-1.91442728e+00 -9.44279075e-01 -7.09388554e-01 2.69594550e+00
1.04006970e+00 -2.05379650e-01 5.55506408e-01 -1.36342376e-01
9.85548913e-01 -5.61236382e-01 -4.42164451e-01 -2.58789718e-01
1.37573600e-01 1.20556228e-01 9.57908571e-01 5.66787660e-01
-8.09952855e-01 1.33721724e-01 8.45495892e+00 7.14170933e-01
-2.75208205e-01 3.05298090e-01 6.81316733e-01 -2.32869700e-01
-2.95262635e-01 2.33634084e-01 -3.87098670e-01 3.43496621e-01
1.28418839e+00 -9.99524966e-02 9.85997990e-02 2.14747772e-01
1.02779436e+00 -3.05587590e-01 -1.32268155e+00 2.02587485e-01
-5.83499372e-01 -1.10416162e+00 -5.06410182e-01 5.05311012e-01
8.23222876e-01 -7.43717253e-02 -8.63597095e-02 -1.79547638e-01
1.15417790e+00 -9.61369514e-01 2.54215449e-01 4.00033623e-01
9.78858292e-01 -6.31072223e-01 4.43588793e-01 1.94775760e-01
-3.04646760e-01 -5.18139839e-01 -1.85992438e-02 -1.76434517e-01
2.95648336e-01 9.14277017e-01 -5.05233347e-01 6.17946267e-01
3.79250824e-01 4.95270759e-01 1.01589292e-01 9.72948849e-01
-2.78831273e-01 9.91691649e-01 -2.28217453e-01 6.83392763e-01
-1.54361397e-01 -1.12635814e-01 3.05838197e-01 6.57808900e-01
2.99965799e-01 3.86919767e-01 -2.48730183e-01 9.54850852e-01
-1.03608534e-01 4.32494618e-02 -6.77812278e-01 5.31005412e-02
4.19980019e-01 7.22149372e-01 -5.05070686e-01 -1.36266172e-01
-5.69658518e-01 3.15729469e-01 7.59032071e-02 5.21097481e-01
-5.20931184e-01 2.95342386e-01 2.48231262e-01 9.59315076e-02
-4.37347740e-02 3.13090265e-01 -4.11858022e-01 -8.70055676e-01
-2.48165250e-01 -1.02183056e+00 1.13936651e+00 -6.96924806e-01
-1.47415102e+00 -7.47906744e-01 5.52043200e-01 -6.09815538e-01
-3.65772545e-01 -3.33576620e-01 -4.44132060e-01 1.00914752e+00
-7.27484047e-01 -7.40858257e-01 4.95409578e-01 5.10210931e-01
-6.37777522e-02 4.50840682e-01 6.45558119e-01 1.10944040e-01
-8.03990304e-01 3.41236800e-01 4.34578091e-01 -2.34251469e-01
8.02164137e-01 -1.33260930e+00 -1.35402799e-01 6.87427521e-01
-4.69125748e-01 8.38840127e-01 7.28840053e-01 -1.30712831e+00
-1.34342301e+00 -7.30184555e-01 6.71856105e-01 -4.95442510e-01
9.40287054e-01 -9.24491212e-02 -5.36491275e-01 1.17652380e+00
4.10367697e-02 -2.66466886e-01 7.03223705e-01 7.80406356e-01
-1.45370260e-01 1.79020703e-01 -1.14090490e+00 6.74620152e-01
1.11954701e+00 -1.48167431e-01 -5.15841484e-01 4.43099797e-01
5.54902494e-01 -2.33260076e-02 -1.28135407e+00 6.70232117e-01
6.85399771e-01 -5.19649148e-01 9.05572653e-01 -1.21480000e+00
5.54281771e-01 3.29456031e-02 -8.73683989e-02 -1.31764388e+00
-3.60805035e-01 -4.58493650e-01 3.06194246e-01 1.18421710e+00
3.30854386e-01 -6.21755302e-01 5.38924038e-01 1.02307487e+00
1.49456814e-01 -4.34068628e-02 -1.11191213e+00 -7.03499138e-01
5.98601818e-01 -2.82941252e-01 1.70318931e-01 1.17370224e+00
4.28754717e-01 2.72696108e-01 -5.36525667e-01 2.28443414e-01
1.02078223e+00 -7.40289837e-02 4.60612178e-01 -1.23759127e+00
-4.20982540e-01 6.51194202e-03 5.30751571e-02 -3.15736651e-01
2.13274062e-01 -5.99857986e-01 -2.09394246e-01 -1.33951235e+00
1.04120326e+00 -4.44677234e-01 -1.43236995e-01 5.63698947e-01
-3.57425362e-01 -4.09656942e-01 -9.36897472e-02 -1.79025203e-01
-3.16677988e-02 4.45549518e-01 1.00201166e+00 2.96048038e-02
-2.18822524e-01 3.15881878e-01 -9.11608100e-01 7.21212566e-01
4.56645489e-01 -9.21764314e-01 -6.52022958e-01 -2.52605025e-02
1.37232453e-01 7.83553421e-01 7.68083215e-01 -6.50804937e-02
-1.41586155e-01 -4.67045814e-01 4.80588973e-01 -1.93867132e-01
-3.58430982e-01 -8.23803246e-01 4.68748093e-01 8.99567723e-01
-9.48993742e-01 -5.75128011e-02 1.35527551e-01 8.50122511e-01
3.43866676e-01 -3.59758377e-01 4.01939064e-01 1.92185014e-01
2.89474338e-01 1.04443006e-01 -5.39840996e-01 1.09048359e-01
5.64438760e-01 4.53336895e-01 -4.76242751e-01 -3.34595829e-01
-1.11174154e+00 3.96724731e-01 2.62907237e-01 6.98539168e-02
1.62320450e-01 -1.52932847e+00 -8.58384609e-01 -2.28640735e-01
6.95201382e-02 -8.19081306e-01 4.29151893e-01 1.34512925e+00
4.41038787e-01 2.92008340e-01 1.14710927e-01 -2.09187075e-01
-1.21032500e+00 9.47780907e-01 9.64578837e-02 -2.13052779e-01
-5.11236727e-01 1.78198442e-01 8.46700370e-01 -1.42581359e-01
8.91870558e-02 -1.83913723e-01 1.40765533e-01 -2.71771215e-02
6.06953979e-01 8.34833264e-01 -1.68838844e-01 -8.27824175e-02
-2.49390095e-01 2.21658722e-02 2.29941413e-01 -4.76363271e-01
1.14170110e+00 -6.09894693e-01 -3.27270359e-01 4.68602151e-01
1.01215529e+00 3.15246219e-03 -1.20631897e+00 -6.78932890e-02
8.07974190e-02 -3.18295985e-01 1.89144880e-01 -8.41883361e-01
-8.73744905e-01 3.49451244e-01 8.58015060e-01 2.29699947e-02
9.79688048e-01 -4.15347852e-02 -3.24317545e-01 -1.04751848e-01
2.76982099e-01 -9.63823318e-01 -4.67399836e-01 -2.91025072e-01
8.45078528e-01 -1.05644977e+00 1.47705212e-01 -4.16075170e-01
-1.38424322e-01 5.33914268e-01 -1.18954904e-01 -8.92279446e-02
7.17113614e-01 2.63197333e-01 -5.31404674e-01 -2.90988415e-01
-8.81585658e-01 4.13411446e-02 1.82684273e-01 6.53686702e-01
5.22773325e-01 3.14500123e-01 -1.06579041e+00 6.27774000e-01
2.86572665e-01 4.81842577e-01 7.11224973e-01 6.63488925e-01
2.23112047e-01 -1.25492811e+00 -5.27663648e-01 9.48212743e-01
-8.88431728e-01 -2.22781956e-01 2.87906453e-02 1.16399908e+00
-2.92978942e-01 1.10642803e+00 2.23954827e-01 4.69538957e-01
3.87664706e-01 -1.01129822e-02 6.14080548e-01 -4.16086316e-01
-7.46069923e-02 5.64051270e-01 4.16477263e-01 -6.28857315e-01
-7.68013120e-01 -1.13644826e+00 -9.54257488e-01 -3.17407250e-01
-4.92081493e-01 1.86589569e-01 2.15213299e-01 1.15266919e+00
2.00827554e-01 6.14498317e-01 7.42769599e-01 -2.43163154e-01
-8.67396772e-01 -7.58329213e-01 -8.81467044e-01 1.34147421e-01
3.74121547e-01 -8.33750069e-01 -5.49103439e-01 -5.68804592e-02] | [7.979881286621094, 5.2996087074279785] |
41592609-da98-4690-accf-98aafebb4fbf | detecting-tiny-objects-in-aerial-images-a | 2206.13996 | null | https://arxiv.org/abs/2206.13996v1 | https://arxiv.org/pdf/2206.13996v1.pdf | Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark | Tiny object detection (TOD) in aerial images is challenging since a tiny object only contains a few pixels. State-of-the-art object detectors do not provide satisfactory results on tiny objects due to the lack of supervision from discriminative features. Our key observation is that the Intersection over Union (IoU) metric and its extensions are very sensitive to the location deviation of the tiny objects, which drastically deteriorates the quality of label assignment when used in anchor-based detectors. To tackle this problem, we propose a new evaluation metric dubbed Normalized Wasserstein Distance (NWD) and a new RanKing-based Assigning (RKA) strategy for tiny object detection. The proposed NWD-RKA strategy can be easily embedded into all kinds of anchor-based detectors to replace the standard IoU threshold-based one, significantly improving label assignment and providing sufficient supervision information for network training. Tested on four datasets, NWD-RKA can consistently improve tiny object detection performance by a large margin. Besides, observing prominent noisy labels in the Tiny Object Detection in Aerial Images (AI-TOD) dataset, we are motivated to meticulously relabel it and release AI-TOD-v2 and its corresponding benchmark. In AI-TOD-v2, the missing annotation and location error problems are considerably mitigated, facilitating more reliable training and validation processes. Embedding NWD-RKA into DetectoRS, the detection performance achieves 4.3 AP points improvement over state-of-the-art competitors on AI-TOD-v2. Datasets, codes, and more visualizations are available at: https://chasel-tsui.github.io/AI-TOD-v2/ | ['Gui-Song Xia', 'Lei Yu', 'Huai Yu', 'Wen Yang', 'Jinwang Wang', 'Chang Xu'] | 2022-06-28 | null | null | null | null | ['object-detection-in-aerial-images'] | ['computer-vision'] | [-5.54531477e-02 -1.86907172e-01 -1.04880638e-01 -2.36028105e-01
-8.72059286e-01 -6.92364156e-01 2.61604518e-01 1.43777266e-01
-4.64307696e-01 3.06724161e-01 -2.46840492e-01 -1.96031705e-01
5.03776455e-03 -6.83928132e-01 -6.91380024e-01 -8.18637967e-01
-7.92813003e-02 1.78699717e-01 8.40437531e-01 -1.44114986e-01
-2.53704578e-01 3.59014660e-01 -1.45099354e+00 -9.90900304e-03
6.04747534e-01 1.51801586e+00 3.36179465e-01 3.64247024e-01
1.81522623e-01 3.52575213e-01 -6.38851941e-01 -2.28455618e-01
7.71916091e-01 -9.10420120e-02 -3.11044455e-01 -1.32818222e-02
8.54837418e-01 -5.18016696e-01 -2.54911959e-01 1.13744855e+00
7.28326142e-01 -1.50754482e-01 7.45708823e-01 -1.21736479e+00
-5.17726421e-01 5.30169368e-01 -8.92842352e-01 3.90732467e-01
-1.31124919e-02 2.52225846e-01 1.11069405e+00 -1.15490532e+00
4.50804234e-01 9.95731294e-01 9.16214108e-01 4.51326638e-01
-1.12068629e+00 -6.74907207e-01 3.23509812e-01 -7.20761120e-02
-1.74965644e+00 -5.67721762e-02 3.05432409e-01 -5.07701755e-01
4.18476701e-01 4.40218657e-01 4.31232274e-01 8.71320248e-01
-2.29973122e-01 1.05566418e+00 8.52334857e-01 -2.31212333e-01
2.19725698e-01 2.34561369e-01 9.53079537e-02 8.72732878e-01
4.38171297e-01 -5.57595231e-02 -9.99081135e-02 -6.05183244e-02
5.43325067e-01 2.91311771e-01 -2.63094366e-01 -6.41149998e-01
-1.15905797e+00 6.49943054e-01 1.01897895e+00 1.15650199e-01
-1.34317309e-01 4.87823710e-02 5.12423337e-01 1.73587576e-01
4.13372517e-01 3.36174160e-01 -4.80166733e-01 4.20477360e-01
-7.55883813e-01 1.41268522e-01 2.87505627e-01 1.05955482e+00
4.76756364e-01 -1.36609629e-01 -7.43122578e-01 6.39252901e-01
1.33543804e-01 8.26090276e-01 3.37709069e-01 -5.16126513e-01
5.21767557e-01 8.25612783e-01 3.09447259e-01 -8.38433385e-01
-5.71387351e-01 -6.64893150e-01 -6.69941068e-01 3.29495668e-01
6.28022909e-01 -2.41775841e-01 -1.05668783e+00 1.64915991e+00
6.20018125e-01 -5.51304780e-02 -1.42589465e-01 1.18992329e+00
1.03957379e+00 4.95512456e-01 -9.40101780e-03 1.16385967e-01
1.41146660e+00 -8.40083599e-01 -1.50672004e-01 -2.46146604e-01
9.62340713e-01 -5.56126475e-01 1.13717890e+00 3.39328200e-02
-5.52792907e-01 -6.68444395e-01 -1.20985937e+00 3.03989410e-01
-4.17578429e-01 6.52781665e-01 5.26738226e-01 4.84209865e-01
-6.50581658e-01 4.09112692e-01 -6.25485361e-01 -4.91441727e-01
8.66411150e-01 2.68481016e-01 -3.64984363e-01 -2.11722061e-01
-9.16357458e-01 6.37155771e-01 3.50432962e-01 1.13097325e-01
-1.05592656e+00 -4.86345083e-01 -6.72364235e-01 -1.39639959e-01
8.69007051e-01 -4.08797413e-01 1.11568594e+00 -3.74346107e-01
-8.02497327e-01 9.19109643e-01 2.33579025e-01 -5.63578546e-01
7.77178168e-01 -1.24987163e-01 -2.28677869e-01 -1.91538259e-02
4.42840487e-01 7.15205610e-01 9.91680086e-01 -1.04621398e+00
-9.39874053e-01 -5.71037829e-01 1.02095500e-01 -3.33299721e-03
-7.49094725e-01 -9.89545137e-02 -4.42460299e-01 -6.86569989e-01
2.06228450e-01 -9.11545455e-01 -1.01098083e-01 5.21387458e-01
-5.68549395e-01 -6.15512311e-01 9.87035990e-01 6.17649741e-02
1.27933073e+00 -2.19048524e+00 -8.55388567e-02 -9.50886607e-02
3.22421402e-01 6.03536069e-01 -2.37041906e-01 -1.48776248e-02
1.57717049e-01 1.14626594e-01 -2.06831992e-01 -2.74013668e-01
4.27338667e-02 -1.42433807e-01 -2.74879843e-01 6.11688912e-01
3.03974003e-01 8.04615438e-01 -9.15386975e-01 -4.72910494e-01
2.47536644e-01 2.09420785e-01 -6.34729955e-03 2.38904338e-02
-1.38990581e-01 1.70961767e-02 -8.00305784e-01 1.23571706e+00
7.31489241e-01 -1.93648338e-01 -4.02831852e-01 -3.30292046e-01
-1.27839193e-01 -1.05916157e-01 -1.27798808e+00 1.45250070e+00
-5.46313189e-02 5.03809869e-01 -7.21750930e-02 -7.34046638e-01
1.05716801e+00 9.28614661e-02 3.87618005e-01 -4.15521830e-01
3.22642326e-01 3.21305841e-01 -1.28540322e-01 -3.30364347e-01
1.61243632e-01 1.48684159e-01 -1.86469778e-01 1.06707044e-01
-8.93611610e-02 4.81904484e-02 4.73667860e-01 2.34781846e-01
1.21768904e+00 6.64599538e-02 2.89259166e-01 -2.56164014e-01
2.17732206e-01 9.76075418e-03 7.71832585e-01 8.36642861e-01
-5.11824429e-01 7.47526944e-01 2.93270856e-01 -5.67351937e-01
-6.91079438e-01 -9.31137502e-01 -6.65460885e-01 1.11357737e+00
4.36004549e-01 -5.01554966e-01 -7.33731747e-01 -1.13286209e+00
4.15555447e-01 2.77495325e-01 -9.28037226e-01 -1.61033481e-01
-1.94392592e-01 -1.00346839e+00 5.81409752e-01 7.86135733e-01
4.89103258e-01 -7.81553149e-01 -9.23029661e-01 -4.89661703e-04
2.35557556e-02 -1.13142431e+00 -4.64916170e-01 5.60434461e-01
-7.45306432e-01 -1.03820300e+00 -9.57895339e-01 -5.80810308e-01
6.94174528e-01 7.24969506e-01 7.85867333e-01 7.65077863e-03
-6.62862062e-01 -8.80091935e-02 -6.13909066e-01 -6.64443672e-01
5.31059504e-02 4.26600091e-02 3.57299328e-01 -4.97025289e-02
4.76435184e-01 -1.82229996e-01 -8.08696270e-01 8.51874411e-01
-8.03205907e-01 -3.03443521e-01 8.44808936e-01 7.94063210e-01
7.62635946e-01 -5.72822019e-02 3.45888764e-01 -5.87778986e-01
3.50805894e-02 -2.78481901e-01 -8.79280627e-01 2.56375760e-01
-5.36015868e-01 -1.64246202e-01 6.16150796e-01 -5.51054776e-01
-3.80555004e-01 2.97228158e-01 6.08933121e-02 -6.73760593e-01
-2.23864391e-01 5.55269271e-02 -2.27187961e-01 -2.36824408e-01
1.03587604e+00 -8.84389430e-02 -6.93720877e-01 -4.77048635e-01
4.51485813e-02 7.93725789e-01 4.08272028e-01 -2.49787465e-01
1.02698159e+00 5.53973556e-01 -1.08821012e-01 -5.76952994e-01
-1.26529777e+00 -8.30230117e-01 -7.90339053e-01 -9.09005702e-02
6.78314805e-01 -1.13386154e+00 -3.27511549e-01 4.34203476e-01
-8.20666254e-01 -3.61178100e-01 -5.39303184e-01 3.29160810e-01
2.30233576e-02 9.33411792e-02 -2.88731307e-01 -7.19875813e-01
-3.48902255e-01 -1.16399288e+00 1.36922467e+00 3.38394910e-01
2.07124054e-01 -3.87929231e-01 -2.42688686e-01 2.89155513e-01
1.84154719e-01 5.29085755e-01 3.64570826e-01 -6.10499620e-01
-4.30894375e-01 -8.34392071e-01 -5.01018703e-01 4.52834606e-01
3.61524057e-03 -8.75595659e-02 -1.12473333e+00 -5.05890012e-01
-4.04378742e-01 -6.84085369e-01 1.35795283e+00 4.25795138e-01
1.06137455e+00 9.61439833e-02 -5.89692652e-01 6.39487863e-01
1.45792508e+00 -2.08151504e-01 1.90629497e-01 4.92576122e-01
7.24812388e-01 2.53301829e-01 1.01306391e+00 6.04097605e-01
8.67523402e-02 8.73217881e-01 8.44634056e-01 -1.92236990e-01
-2.15837091e-01 -2.34562159e-01 4.22467023e-01 1.17144771e-01
-1.62623271e-01 -4.26769465e-01 -7.09741890e-01 5.96922755e-01
-1.90237331e+00 -6.60016716e-01 -3.78342748e-01 2.20236826e+00
5.55579603e-01 4.19662565e-01 3.43784660e-01 1.29944995e-01
7.29971111e-01 2.16362327e-01 -7.84226835e-01 3.96769881e-01
-2.76855677e-01 -4.34921652e-01 9.44057286e-01 -1.98291168e-01
-1.67852557e+00 9.88847196e-01 4.82362652e+00 1.17603767e+00
-8.81029844e-01 2.03143194e-01 4.28342849e-01 -1.07578710e-01
3.72911870e-01 -1.82898641e-01 -1.40417945e+00 3.31605911e-01
3.60334277e-01 2.23808140e-01 -1.87392294e-01 1.27821481e+00
1.24657437e-01 -7.85605013e-02 -9.72895324e-01 1.01504719e+00
-1.26823753e-01 -9.51116741e-01 2.15088911e-02 -5.10734357e-02
7.32994676e-01 3.12192738e-01 1.73552245e-01 3.12196523e-01
1.39387161e-01 -6.50823414e-01 9.32488024e-01 -1.04331926e-01
9.78333771e-01 -4.56267864e-01 1.06164515e+00 3.26793313e-01
-1.53579295e+00 -5.13255179e-01 -1.05539179e+00 1.76431656e-01
-5.04003800e-02 7.20832109e-01 -6.32842779e-01 3.84177387e-01
1.16028595e+00 7.52271533e-01 -9.69554484e-01 1.36668193e+00
-3.54113132e-01 6.12022996e-01 -5.77856660e-01 -6.30712062e-02
5.13509691e-01 1.88198790e-01 6.99764788e-01 1.08071613e+00
3.93963873e-01 1.49832457e-01 4.61211175e-01 8.10132444e-01
-4.90157962e-01 9.18410644e-02 -5.63223541e-01 2.29854777e-01
5.46336293e-01 1.69998264e+00 -1.07117391e+00 -2.56755650e-01
-3.01311135e-01 7.60506570e-01 2.25642130e-01 -1.99455805e-02
-8.98056328e-01 -3.65787506e-01 5.24403751e-01 2.72320867e-01
7.58435369e-01 1.46181896e-01 4.41746898e-02 -9.90276933e-01
3.78169745e-01 -5.94515979e-01 4.49616462e-01 -5.51926792e-01
-1.28679442e+00 7.49621332e-01 -1.08571067e-01 -1.61315417e+00
4.36975718e-01 -8.44044685e-01 -5.42990088e-01 3.61290842e-01
-1.44851005e+00 -1.35028160e+00 -7.46738553e-01 4.48425770e-01
5.44447482e-01 -1.22560710e-01 7.02828825e-01 3.33976865e-01
-9.21861470e-01 8.15744102e-01 2.70029306e-01 4.10450071e-01
9.41889644e-01 -1.31070101e+00 3.59682888e-01 1.02430975e+00
3.56451243e-01 1.43413916e-01 6.32173955e-01 -3.05762231e-01
-1.08130026e+00 -1.49910009e+00 1.54859915e-01 -7.47279048e-01
6.83192909e-01 -4.79928762e-01 -7.33859420e-01 4.27127063e-01
-5.01361430e-01 8.42057824e-01 3.13036650e-01 -3.40838939e-01
-5.02382517e-01 -3.83301795e-01 -9.52605247e-01 2.40815148e-01
1.16243732e+00 -1.60031393e-01 -2.55172610e-01 6.71079338e-01
8.06488454e-01 -2.90354311e-01 -7.35254824e-01 7.60676324e-01
4.69706625e-01 -1.02547252e+00 1.03571999e+00 -2.29913428e-01
-1.01537677e-03 -7.51018286e-01 -3.27452064e-01 -1.02304089e+00
-2.91842490e-01 -3.39810640e-01 -2.35517230e-03 1.25835431e+00
4.21535492e-01 -4.12907273e-01 5.49916863e-01 1.72040626e-01
-1.80932432e-01 -8.91599178e-01 -8.57400537e-01 -1.23004401e+00
-2.13557944e-01 -3.87870014e-01 4.35028791e-01 6.32706642e-01
-3.66805315e-01 2.09399387e-01 -2.97058076e-01 4.52051908e-01
7.19790041e-01 2.26428956e-01 7.92384088e-01 -1.47275007e+00
-1.78212881e-01 -3.29496324e-01 -6.75455749e-01 -1.24773872e+00
-4.02601004e-01 -8.20575655e-01 3.42206717e-01 -1.42099404e+00
1.73941404e-01 -7.72343695e-01 -5.75248659e-01 7.87443042e-01
-2.85662830e-01 8.70801568e-01 3.35464984e-01 3.95375788e-01
-1.01504397e+00 6.70998156e-01 1.06791186e+00 -4.01445568e-01
-1.14412494e-01 2.27439106e-01 -5.07150292e-01 7.90041625e-01
7.41527736e-01 -8.39330018e-01 -5.43455556e-02 -4.59968418e-01
-2.00994182e-02 -4.42495555e-01 5.59796631e-01 -1.34667397e+00
1.55888990e-01 2.48507842e-01 5.64610362e-01 -5.52393496e-01
1.44267514e-01 -7.96755433e-01 -5.45830190e-01 4.84139949e-01
-1.02781758e-01 -2.38703609e-01 2.61417478e-01 7.81155527e-01
-2.45671347e-02 -2.97479331e-01 8.48290980e-01 -1.50939580e-02
-9.95373070e-01 5.23886561e-01 -7.91496187e-02 6.69485927e-02
1.39046085e+00 -2.57538378e-01 -3.84165585e-01 1.93256393e-01
-4.06253189e-01 4.70027119e-01 4.63190407e-01 3.55820090e-01
5.70634067e-01 -1.25389504e+00 -7.69162655e-01 1.16799548e-01
7.13206828e-01 3.54925603e-01 -1.39741814e-02 1.13163221e+00
-2.99880713e-01 3.78921986e-01 -1.79718155e-02 -8.09196472e-01
-1.49857819e+00 4.99182254e-01 2.64839232e-01 -5.22666797e-02
-7.19213545e-01 1.24436426e+00 3.26869190e-01 -3.55619162e-01
5.10898948e-01 -5.68144143e-01 -6.65664971e-02 9.48392674e-02
6.78946972e-01 3.88042718e-01 1.00514680e-01 -5.50587296e-01
-5.62326252e-01 7.50619769e-01 -2.82451864e-02 5.71708262e-01
1.21594572e+00 2.86097396e-02 3.94293427e-01 3.29108655e-01
8.39332759e-01 -2.45251447e-01 -1.42331362e+00 -3.96699250e-01
-4.72369306e-02 -4.96715993e-01 2.01368436e-01 -6.53002560e-01
-1.05212569e+00 9.04915214e-01 1.13699067e+00 3.02324444e-01
9.71179724e-01 2.69190848e-01 8.06715906e-01 6.29593968e-01
4.69693363e-01 -9.49120104e-01 4.74578142e-02 1.63261399e-01
7.78954327e-01 -1.71978140e+00 2.25593984e-01 -3.03645909e-01
-4.66871351e-01 1.01213753e+00 7.16546178e-01 1.92763451e-02
4.33228344e-01 3.33549351e-01 2.08514288e-01 -2.02875271e-01
-3.10836703e-01 -6.46578968e-01 3.43464166e-01 4.54822421e-01
1.04787566e-01 8.06471184e-02 6.27907813e-02 5.20454228e-01
2.38420606e-01 -2.37946987e-01 1.83619529e-01 7.68485546e-01
-7.28533685e-01 -7.09542394e-01 -4.71697301e-01 5.81184745e-01
-3.51031601e-01 2.02266704e-02 -4.09056991e-01 9.13155079e-01
4.77658540e-01 7.63048172e-01 -2.19745755e-01 -6.32663131e-01
5.55181682e-01 -3.43369514e-01 1.31573543e-01 -6.28756762e-01
-3.10023844e-01 1.30446255e-01 -2.66898543e-01 -5.91611385e-01
-3.46478134e-01 -5.01836419e-01 -1.21614301e+00 2.08525117e-02
-1.03840733e+00 1.75652523e-02 3.80005628e-01 6.61754847e-01
1.78682849e-01 4.68698204e-01 5.00885427e-01 -9.95203137e-01
-9.55998302e-01 -1.03893483e+00 -7.97089934e-01 3.05576742e-01
2.08489731e-01 -9.14350331e-01 -4.69940543e-01 -2.89217353e-01] | [8.721695899963379, -0.49043598771095276] |
5c0d2f6e-a83b-4516-b0b2-98ce218d4428 | singsong-generating-musical-accompaniments | 2301.12662 | null | https://arxiv.org/abs/2301.12662v1 | https://arxiv.org/pdf/2301.12662v1.pdf | SingSong: Generating musical accompaniments from singing | We present SingSong, a system that generates instrumental music to accompany input vocals, potentially offering musicians and non-musicians alike an intuitive new way to create music featuring their own voice. To accomplish this, we build on recent developments in musical source separation and audio generation. Specifically, we apply a state-of-the-art source separation algorithm to a large corpus of music audio to produce aligned pairs of vocals and instrumental sources. Then, we adapt AudioLM (Borsos et al., 2022) -- a state-of-the-art approach for unconditional audio generation -- to be suitable for conditional "audio-to-audio" generation tasks, and train it on the source-separated (vocal, instrumental) pairs. In a pairwise comparison with the same vocal inputs, listeners expressed a significant preference for instrumentals generated by SingSong compared to those from a strong retrieval baseline. Sound examples at https://g.co/magenta/singsong | ['Jesse Engel', 'Neil Zeghidour', 'Olivier Pietquin', 'Ian Simon', 'Mauro Verzetti', 'Andrea Agostinelli', 'Philippe Esling', 'Ethan Manilow', 'Adam Roberts', 'Antoine Caillon', 'Chris Donahue'] | 2023-01-30 | null | null | null | null | ['audio-generation'] | ['audio'] | [ 2.26791680e-01 -8.01420659e-02 2.75021344e-01 -7.47855380e-02
-1.58559012e+00 -1.05162942e+00 4.12595153e-01 -1.40218988e-01
1.40898973e-01 5.61502695e-01 6.39751315e-01 2.09790900e-01
-3.68659705e-01 -4.90376085e-01 -5.12218118e-01 -6.74185932e-01
-7.91498572e-02 4.85701621e-01 -1.52817249e-01 -5.73893368e-01
1.46936998e-01 1.84793919e-01 -1.92459655e+00 6.56125247e-01
5.35132825e-01 5.76496184e-01 2.26513520e-01 1.15980816e+00
-1.92206576e-01 5.21416485e-01 -9.03851628e-01 -1.87064648e-01
2.12986797e-01 -1.07149374e+00 -7.27657735e-01 -6.25866890e-01
6.13146663e-01 1.18539177e-01 1.11996487e-01 7.93167651e-01
1.01912165e+00 3.19039345e-01 7.42817044e-01 -1.01828551e+00
-5.13277233e-01 1.52960122e+00 -7.37238377e-02 -4.16022651e-02
7.55124867e-01 2.59098392e-02 1.41750932e+00 -8.71921062e-01
5.86462259e-01 1.17883885e+00 6.38265431e-01 8.35840225e-01
-1.56910443e+00 -1.01335907e+00 -4.65582430e-01 -2.20571220e-01
-1.26189888e+00 -1.02473724e+00 9.74912465e-01 -4.45983320e-01
5.92903018e-01 7.10591257e-01 8.29810977e-01 1.29291356e+00
-4.52877909e-01 8.58286738e-01 8.71177733e-01 -6.97100163e-01
4.55150343e-02 2.71567442e-02 -2.57660627e-01 -1.03125200e-01
-6.03355348e-01 4.43275332e-01 -1.22544754e+00 -2.72706419e-01
6.07405961e-01 -9.18598473e-01 -4.47471738e-01 2.89604962e-01
-1.54454899e+00 4.56807166e-01 2.41593033e-01 6.88845456e-01
-4.56839859e-01 4.56596106e-01 2.22745299e-01 5.45912981e-01
1.11395635e-01 9.96945322e-01 -1.70518443e-01 -4.60900038e-01
-1.47973180e+00 7.50219643e-01 9.26689088e-01 8.91965687e-01
2.70535707e-01 4.30250615e-01 -4.00597602e-01 1.12651718e+00
3.04245859e-01 4.52608377e-01 7.25156128e-01 -1.15823627e+00
6.65213317e-02 -2.79640079e-01 -4.90860380e-02 -4.37689304e-01
1.08642660e-01 -5.84758759e-01 -5.95552325e-01 2.41926402e-01
3.88159722e-01 -6.61916584e-02 -5.66762507e-01 1.95894778e+00
1.96525790e-02 2.87768096e-01 9.61199328e-02 8.48094285e-01
9.20580864e-01 7.78667092e-01 -2.89310545e-01 -2.42234051e-01
1.03935647e+00 -1.03439212e+00 -5.54877818e-01 1.10678807e-01
-1.88307725e-02 -1.46180403e+00 1.39692926e+00 7.04048216e-01
-1.42796350e+00 -9.74260390e-01 -8.39895129e-01 1.29112855e-01
-5.39708845e-02 1.39241636e-01 2.27019325e-01 6.32019460e-01
-1.07165384e+00 8.37303579e-01 -2.18249604e-01 -7.28459805e-02
-1.42673120e-01 8.23939592e-02 -1.88416153e-01 6.16214573e-01
-1.22619987e+00 3.81140232e-01 4.12309557e-01 -2.45612174e-01
-1.27419591e+00 -1.06124115e+00 -2.47813016e-01 -5.96035793e-02
-3.19998786e-02 -7.81753182e-01 1.78601706e+00 -9.35841858e-01
-1.78008032e+00 6.70809090e-01 8.27355683e-02 -3.20140570e-01
2.12594301e-01 -5.51208377e-01 -6.62565649e-01 1.71215653e-01
2.44460836e-01 6.50510550e-01 1.16196489e+00 -1.40350258e+00
-4.92172182e-01 1.79987296e-01 -4.21584487e-01 2.36328542e-01
-1.00087374e-01 4.12381589e-01 -6.12708852e-02 -1.14687026e+00
-2.89342199e-02 -9.54754233e-01 1.71272099e-01 -6.06584191e-01
-7.73874819e-01 -1.64298221e-01 2.31574312e-01 -4.69024688e-01
1.26165104e+00 -2.46427751e+00 3.95873964e-01 3.75033528e-01
-1.93658024e-01 2.66247839e-02 -4.80322808e-01 7.83418834e-01
-4.93773997e-01 4.05613184e-02 -1.28002644e-01 -5.20350635e-01
3.45573843e-01 -2.16362372e-01 -8.68353188e-01 -1.78638324e-01
-1.08225912e-01 5.11483848e-01 -1.18908930e+00 -2.87200361e-01
-1.07387178e-01 5.69065332e-01 -6.45132065e-01 5.61965406e-01
-3.02446485e-01 7.34146357e-01 1.38381030e-02 5.15028775e-01
1.22231439e-01 5.27305841e-01 -9.13940221e-02 -3.12135350e-02
-2.60092318e-01 8.00180554e-01 -1.45341218e+00 2.06439233e+00
-4.31603700e-01 5.39421618e-01 4.08118874e-01 -1.41110197e-01
9.79499876e-01 7.75072157e-01 3.46789896e-01 2.31758170e-02
4.16592322e-02 8.10439110e-01 2.14342162e-01 -2.07090810e-01
6.73629344e-01 -6.66706443e-01 -4.67993319e-02 5.25944293e-01
4.64109808e-01 -9.03909087e-01 3.66201431e-01 2.47233555e-01
7.96228945e-01 3.78924757e-01 6.15573935e-02 -1.10360079e-01
3.53363603e-01 -3.15329581e-01 5.62635027e-02 8.67260695e-01
2.64214158e-01 1.07988322e+00 5.34079596e-02 4.38680708e-01
-7.85525382e-01 -1.56551635e+00 1.15033135e-01 1.48655832e+00
-5.20521879e-01 -8.50887597e-01 -8.85094583e-01 1.29399911e-01
-8.32818076e-02 1.05007100e+00 -2.64891922e-01 -1.01213470e-01
-4.97220039e-01 -5.68312779e-02 1.28573978e+00 3.35454971e-01
-2.96900094e-01 -1.60032666e+00 -1.81760624e-01 4.97734994e-01
-5.31572998e-01 -3.19421858e-01 -7.10246682e-01 3.07408422e-01
-3.86490524e-01 -6.50021553e-01 -9.77599263e-01 -7.77123988e-01
-1.94839016e-01 1.30277956e-02 1.39892650e+00 -2.70561695e-01
-3.58933389e-01 5.10561585e-01 -4.52366263e-01 -6.72375083e-01
-1.04926360e+00 9.39809084e-02 4.18675810e-01 -7.16540441e-02
-1.55098483e-01 -1.06737363e+00 -2.33786196e-01 -6.47203578e-03
-9.34364080e-01 -8.76910985e-02 4.29761410e-01 5.75669169e-01
5.45996904e-01 1.40407085e-02 9.46259737e-01 -4.75096107e-01
1.07528365e+00 -2.73842186e-01 -1.43993318e-01 -2.37762898e-01
-2.46308982e-01 -1.56960443e-01 6.48473918e-01 -5.51184773e-01
-8.15041304e-01 -6.84485883e-02 -5.20396233e-01 -4.83632267e-01
-2.98481017e-01 5.72045982e-01 -9.11329687e-02 3.23202908e-01
1.07995808e+00 3.15216660e-01 -2.22681418e-01 -8.91562700e-01
8.78915846e-01 8.24286699e-01 1.15223825e+00 -9.54053044e-01
9.22034085e-01 -1.33592144e-01 -2.48417988e-01 -9.65248346e-01
-6.61683738e-01 -5.95272362e-01 -5.31174660e-01 -3.67225230e-01
6.07383311e-01 -7.28724360e-01 -4.12626624e-01 3.90548110e-01
-1.07751906e+00 -3.41601372e-01 -7.90062428e-01 6.36897683e-01
-9.18772280e-01 -2.57436913e-02 -6.16078138e-01 -1.05199957e+00
-4.90078032e-01 -6.70868933e-01 1.12601268e+00 1.35502070e-01
-8.98050010e-01 -4.16506410e-01 8.01382661e-01 1.79401815e-01
3.91887635e-01 4.37859334e-02 6.64813399e-01 -7.17189014e-01
-1.32782489e-01 3.07738408e-02 4.54096884e-01 6.72849476e-01
2.94570327e-01 2.07450524e-01 -1.43283963e+00 -1.20639153e-01
-1.83556467e-01 -4.49924558e-01 7.13316679e-01 2.82199651e-01
6.09810770e-01 -2.91103631e-01 1.57776162e-01 5.07768929e-01
7.97311366e-01 3.52922976e-02 5.21134734e-01 -4.89844158e-02
4.28854465e-01 6.57506406e-01 4.27067041e-01 3.47569495e-01
-2.84877032e-01 7.43588090e-01 1.45650908e-01 1.39025301e-01
-6.23790920e-01 -6.61566377e-01 7.89932191e-01 1.36636019e+00
-3.00674409e-01 -1.48738801e-01 -4.52976167e-01 8.59599173e-01
-1.43223929e+00 -1.30617082e+00 -3.78170848e-01 2.26762486e+00
1.49554765e+00 -1.10910207e-01 5.78083515e-01 5.32281280e-01
6.75778151e-01 7.05322102e-02 1.19118541e-01 -2.41263196e-01
-2.85771251e-01 9.19176936e-01 -3.48787755e-01 4.24629629e-01
-8.46398473e-01 8.78859103e-01 6.77179909e+00 1.18961823e+00
-1.03516662e+00 -1.45663038e-01 -2.02672228e-01 -5.79064727e-01
-5.13200998e-01 2.54690938e-04 -4.70543355e-01 3.88252616e-01
1.32862866e+00 -3.26238781e-01 9.25300717e-01 5.96118271e-01
1.86387539e-01 3.14039558e-01 -1.28122056e+00 9.85135257e-01
4.30088192e-02 -1.13179290e+00 8.00702870e-02 -2.93983936e-01
6.30481064e-01 -7.82178119e-02 1.69254467e-01 2.33411297e-01
1.65207893e-01 -1.15177286e+00 1.42714477e+00 4.84442890e-01
7.80127048e-01 -6.62941158e-01 1.98126122e-01 1.55050367e-01
-1.30087340e+00 2.32109591e-01 -1.90984067e-02 1.30255744e-01
5.40139437e-01 5.15892565e-01 -9.71924663e-01 8.32727253e-01
7.16992497e-01 3.10825944e-01 -3.02661926e-01 1.13197553e+00
-4.45122600e-01 1.23114753e+00 -4.09501046e-01 2.43905813e-01
-1.59441773e-02 -7.72042125e-02 1.14723051e+00 1.48949075e+00
8.49947929e-01 -2.09508032e-01 -7.17991516e-02 1.13522923e+00
7.52826110e-02 4.88354892e-01 -5.21404266e-01 -4.59054589e-01
6.14482880e-01 1.31694555e+00 -4.35483098e-01 -3.38732302e-01
3.37886125e-01 9.06990826e-01 -2.03230411e-01 1.51967585e-01
-5.78686059e-01 -7.82795608e-01 5.34726501e-01 1.34699225e-01
-1.26363849e-02 2.08129752e-02 5.22438549e-02 -8.05159867e-01
-3.25334221e-01 -1.24259591e+00 1.59905002e-01 -1.30533290e+00
-1.47393525e+00 8.31088722e-01 -6.84925914e-02 -1.47516632e+00
-8.61552417e-01 -2.47970551e-01 -7.80973136e-01 1.17441988e+00
-9.09225523e-01 -1.12540400e+00 -5.94984703e-02 6.70235693e-01
3.35444033e-01 -3.98790509e-01 1.25864518e+00 4.54111725e-01
3.22399735e-01 3.62573743e-01 -3.14500444e-02 -2.16963403e-02
1.35301530e+00 -1.52067113e+00 2.81453431e-01 5.26918054e-01
9.40486610e-01 8.34752023e-01 9.90945995e-01 -3.84171486e-01
-1.04207182e+00 -9.09167171e-01 9.74672914e-01 -6.22390985e-01
8.01529527e-01 -2.97879308e-01 -6.39041007e-01 3.60714763e-01
6.00330532e-01 -6.94937468e-01 1.22806180e+00 2.30400816e-01
-4.59765345e-01 -9.20348018e-02 -6.50459826e-01 6.83545291e-01
1.03256392e+00 -8.76641631e-01 -1.07421696e+00 4.62531485e-02
7.93420792e-01 -1.39507592e-01 -7.05557406e-01 1.13868415e-01
7.82020926e-01 -1.11397243e+00 1.07071877e+00 -5.03161311e-01
4.49421346e-01 -7.30931699e-01 -2.84929544e-01 -1.74017954e+00
-2.94063449e-01 -1.45633554e+00 3.59261632e-01 1.89847171e+00
4.65200365e-01 -1.02016062e-01 5.99245727e-02 -3.46729308e-01
-5.96869409e-01 2.50673711e-01 -8.09251130e-01 -1.06173778e+00
1.08708903e-01 -7.64801383e-01 6.26111031e-01 7.49178588e-01
1.61399543e-01 6.02264345e-01 -5.11032641e-01 -2.10925266e-01
4.69324946e-01 3.05157751e-01 1.00661671e+00 -1.24060822e+00
-9.33434546e-01 -6.63179994e-01 4.51488942e-02 -6.49425328e-01
4.33909800e-03 -1.29097378e+00 5.54318726e-01 -1.19677949e+00
-2.88938373e-01 -3.35113704e-01 -5.44987798e-01 4.67909068e-01
-1.29471882e-03 6.79179788e-01 6.44948900e-01 3.00782293e-01
-6.46224841e-02 4.55341876e-01 1.05276167e+00 -4.21994328e-02
-5.48442960e-01 3.32311660e-01 -9.41827893e-01 5.63159049e-01
6.58373415e-01 -7.00464427e-01 -4.49812770e-01 1.97987650e-02
3.36789697e-01 1.50954530e-01 3.04228574e-01 -1.37134707e+00
7.55848289e-02 1.42055809e-01 -3.23154032e-02 -5.05958974e-01
6.01481438e-01 -1.90042123e-01 7.33451366e-01 1.28398910e-01
-7.10416555e-01 -3.18992198e-01 2.64741570e-01 1.60477981e-01
-5.02825439e-01 -5.71764171e-01 5.52203774e-01 -9.36194509e-02
-6.88941218e-03 -2.58046001e-01 -5.34255028e-01 2.26713941e-01
2.51111835e-01 2.71499544e-01 -6.30817711e-02 -7.11598396e-01
-8.56326163e-01 -5.19421101e-01 1.15703583e-01 4.48692024e-01
4.71279681e-01 -1.60747671e+00 -1.11987877e+00 2.76117802e-01
1.29411250e-01 -3.64691764e-01 8.30684453e-02 6.57628298e-01
-2.55143106e-01 1.97150186e-01 -9.02990177e-02 -2.06684723e-01
-1.37203407e+00 1.87222570e-01 4.52132933e-02 1.44318148e-01
-2.00019896e-01 1.38412964e+00 -1.20889889e-02 -6.27120733e-01
1.29163519e-01 -1.72357053e-01 -1.04074683e-02 3.68936837e-01
5.80313027e-01 3.52688551e-01 -5.92653193e-02 -6.29321873e-01
-3.04013014e-01 4.25087333e-01 5.28302014e-01 -1.08122110e+00
1.19910920e+00 2.66384929e-01 -3.29884022e-01 1.02673972e+00
8.09013486e-01 1.04947269e+00 -4.82852995e-01 2.16397524e-01
-1.67108431e-01 -3.94165218e-01 -1.59097075e-01 -1.12282801e+00
-5.09997249e-01 7.97385514e-01 2.98461467e-01 6.36098504e-01
1.04151213e+00 1.06478207e-01 6.72497153e-01 8.06080475e-02
2.61552632e-01 -1.01223981e+00 1.96619019e-01 5.80427885e-01
1.37590659e+00 -4.69448656e-01 -4.95087266e-01 -1.79647952e-01
-5.51402450e-01 1.14300752e+00 8.55561495e-02 -1.48290068e-01
5.20007730e-01 3.24458033e-01 4.84243423e-01 1.08958609e-01
-7.19935179e-01 -3.14562023e-01 7.21879721e-01 7.06228495e-01
1.01813388e+00 1.88534617e-01 1.96557702e-03 9.67461050e-01
-1.17575812e+00 -1.24438843e-02 3.18902791e-01 5.17791450e-01
-2.95695931e-01 -1.53862381e+00 -7.47461319e-01 1.00559860e-01
-5.14282167e-01 -6.48473024e-01 -8.18132162e-01 3.20319831e-01
1.62385583e-01 1.26437151e+00 -2.61560231e-01 -5.25204301e-01
3.28990996e-01 5.17593563e-01 5.27484238e-01 -9.60705400e-01
-1.13006711e+00 9.72349405e-01 3.04323316e-01 -2.17974201e-01
-5.56072533e-01 -7.37310886e-01 -1.25958323e+00 6.99054226e-02
-2.72437841e-01 6.01520419e-01 6.06809676e-01 3.75623256e-01
2.03993201e-01 9.57920969e-01 5.46468616e-01 -1.31748104e+00
-6.14687443e-01 -1.29641151e+00 -9.86043274e-01 3.71437699e-01
2.49146491e-01 -1.82072863e-01 -6.80218101e-01 3.85534018e-01] | [15.724095344543457, 5.654480934143066] |
93140872-5be0-451d-b966-fe4b1883562e | mining-interest-trends-and-adaptively | 2306.11610 | null | https://arxiv.org/abs/2306.11610v1 | https://arxiv.org/pdf/2306.11610v1.pdf | Mining Interest Trends and Adaptively Assigning SampleWeight for Session-based Recommendation | Session-based Recommendation (SR) aims to predict users' next click based on their behavior within a short period, which is crucial for online platforms. However, most existing SR methods somewhat ignore the fact that user preference is not necessarily strongly related to the order of interactions. Moreover, they ignore the differences in importance between different samples, which limits the model-fitting performance. To tackle these issues, we put forward the method, Mining Interest Trends and Adaptively Assigning Sample Weight, abbreviated as MTAW. Specifically, we model users' instant interest based on their present behavior and all their previous behaviors. Meanwhile, we discriminatively integrate instant interests to capture the changing trend of user interest to make more personalized recommendations. Furthermore, we devise a novel loss function that dynamically weights the samples according to their prediction difficulty in the current epoch. Extensive experimental results on two benchmark datasets demonstrate the effectiveness and superiority of our method. | ['Yu Zhao', 'Shuangyong Song', 'Hai-Tao Zheng', 'Zuotong Xie', 'Miaoxin Chen', 'Xianghong Xu', 'Kai Ouyang'] | 2023-06-20 | null | null | null | null | ['session-based-recommendations'] | ['miscellaneous'] | [ 3.34279845e-03 -5.62605619e-01 -7.30581164e-01 -6.98872149e-01
-1.94343820e-01 -3.60900223e-01 2.50734895e-01 -7.94659834e-03
-3.61331582e-01 5.06093264e-01 3.91575962e-01 -2.46900111e-01
-4.79207516e-01 -7.17637420e-01 -2.62015074e-01 -5.22822618e-01
-1.09101959e-01 -9.37607735e-02 4.96132195e-01 -1.18439928e-01
6.38345242e-01 -5.86622283e-02 -1.38151526e+00 1.27323881e-01
1.24007082e+00 1.35591531e+00 2.99314767e-01 -1.76126789e-02
-4.84951884e-02 4.88573670e-01 -8.59891102e-02 -1.60052061e-01
1.17974222e-01 -3.90774757e-01 -3.56595218e-01 1.39042279e-02
2.77041346e-02 -4.74236161e-01 -4.05055553e-01 6.99945152e-01
1.91554248e-01 6.03179336e-01 2.34041646e-01 -8.86116385e-01
-5.12571216e-01 5.76252580e-01 -5.51014662e-01 5.21182597e-01
3.45812887e-01 -1.95698425e-01 1.40152407e+00 -6.43968761e-01
1.66998625e-01 7.93211818e-01 4.00926560e-01 4.96635467e-01
-9.99834895e-01 -7.18718648e-01 1.04116976e+00 4.91062194e-01
-9.05149877e-01 -1.79611787e-01 9.84421790e-01 -1.99823976e-01
2.71044463e-01 5.35043240e-01 6.41669512e-01 7.84259737e-01
-2.38471881e-01 1.18049562e+00 7.27395415e-01 1.67211682e-01
1.95731342e-01 3.07353824e-01 4.77304012e-01 1.45840511e-01
-4.41999687e-03 -2.60789990e-01 -4.20768201e-01 -2.54656255e-01
4.13079321e-01 6.68962300e-01 -3.44215989e-01 -2.96543270e-01
-9.34872508e-01 6.73651636e-01 3.24210793e-01 3.97189856e-01
-2.32835546e-01 -4.94426548e-01 1.63610339e-01 3.69038939e-01
6.39185488e-01 6.88274279e-02 -6.51054144e-01 -1.48612589e-01
-6.81299448e-01 8.58165026e-02 5.27051985e-01 6.93916142e-01
6.47416830e-01 -3.35551411e-01 -3.15533727e-01 9.74573016e-01
4.59109068e-01 -1.39398918e-01 8.11109364e-01 -5.46972036e-01
4.66288298e-01 6.94289684e-01 3.86383593e-01 -1.09092283e+00
-2.16878563e-01 -8.66995752e-01 -6.46715403e-01 -6.84278846e-01
2.73642063e-01 -8.27139169e-02 -1.81298181e-01 1.57926083e+00
3.82273853e-01 5.24321496e-01 -3.75584990e-01 8.75341535e-01
4.76187736e-01 5.21445572e-01 -7.72363842e-02 -7.78566480e-01
8.75204563e-01 -1.02574944e+00 -5.74160159e-01 -1.21006407e-01
3.60624224e-01 -4.01365280e-01 1.32195354e+00 5.04390478e-01
-9.77471709e-01 -5.14467955e-01 -7.63481021e-01 2.50441700e-01
4.03566584e-02 6.85335100e-02 9.28861618e-01 4.89297539e-01
-3.67692500e-01 8.15095723e-01 -5.94399214e-01 3.22992317e-02
3.05215180e-01 3.65125179e-01 4.84484136e-01 3.57842714e-01
-1.21053088e+00 2.71220542e-02 8.96116346e-02 8.35126340e-02
-2.34098092e-01 -8.98633957e-01 -2.68215179e-01 2.82670856e-01
6.01484179e-01 -2.48377696e-01 1.34604871e+00 -8.99646103e-01
-1.50857031e+00 2.54969478e-01 -6.06305301e-01 -4.18116003e-01
6.56650066e-01 -2.13474944e-01 -8.70965838e-01 -4.31498557e-01
-2.20873162e-01 -1.65456712e-01 6.73513710e-01 -8.72304022e-01
-1.42609406e+00 -3.80549937e-01 2.95781076e-01 3.30664873e-01
-1.00000155e+00 -3.04820359e-01 -8.31534982e-01 -3.99636149e-01
2.27430582e-01 -5.64342678e-01 -3.61308813e-01 -4.47674602e-01
4.52986583e-02 -5.28773487e-01 7.23740280e-01 -4.27919805e-01
2.04756284e+00 -2.16857171e+00 -1.85898617e-01 5.13467371e-01
9.84369516e-02 1.90445036e-01 2.12145746e-02 2.07764670e-01
3.83430243e-01 1.45365074e-02 1.49526745e-01 4.61915545e-02
1.04358690e-02 2.05988288e-02 -4.91825253e-01 7.48640448e-02
-4.87300605e-01 6.33747816e-01 -1.03973734e+00 -1.97976217e-01
8.04134831e-02 1.30728140e-01 -7.96984076e-01 2.86962360e-01
-2.07737163e-01 4.89795536e-01 -1.11863017e+00 2.29520246e-01
6.40935004e-01 -6.48911178e-01 3.93199831e-01 -1.88403770e-01
-1.87024921e-01 7.38065600e-01 -1.04591656e+00 1.23020697e+00
-5.67428231e-01 9.19260643e-03 -2.65464067e-01 -1.06689036e+00
7.60517955e-01 1.33977141e-02 7.22828627e-01 -9.78717744e-01
-8.00080001e-02 1.37944967e-01 -4.25611697e-02 -3.50045294e-01
4.83046323e-01 2.86203355e-01 1.81737974e-01 4.48486537e-01
-6.75555408e-01 9.14600670e-01 3.44939232e-01 1.19107962e-01
6.13462031e-01 -4.11141440e-02 3.11516434e-01 1.08793133e-03
9.73647177e-01 -5.72877705e-01 8.92313302e-01 6.17163420e-01
-2.43609771e-01 2.75034308e-01 3.96195054e-01 -4.18032616e-01
-3.87480944e-01 -7.81331658e-01 -5.35836034e-02 1.47366166e+00
5.91209412e-01 -3.20790827e-01 -2.88895607e-01 -1.03761232e+00
-1.14326896e-02 7.27545917e-01 -6.89860225e-01 -3.03432167e-01
-5.48513114e-01 -9.22099769e-01 -3.95620048e-01 3.47597688e-01
2.74097502e-01 -8.34001958e-01 1.12731978e-01 4.03822929e-01
-3.77286494e-01 -6.90790415e-01 -1.14384091e+00 -6.68379843e-01
-9.81322467e-01 -9.45078850e-01 -6.21238828e-01 -7.38075435e-01
6.88255370e-01 9.18490827e-01 9.61721301e-01 2.44456396e-01
3.14840585e-01 2.30785102e-01 -5.53022683e-01 1.40055567e-02
3.51497620e-01 2.40003079e-01 -3.14923115e-02 5.77480972e-01
4.59704578e-01 -8.41387391e-01 -1.29641271e+00 7.60634899e-01
-7.36264825e-01 -1.61553204e-01 3.47740471e-01 5.63837111e-01
6.56360030e-01 2.77049571e-01 8.60979080e-01 -1.06224298e+00
7.85947680e-01 -9.19691265e-01 -4.03415024e-01 4.14243281e-01
-1.10538745e+00 -3.60650241e-01 8.22442532e-01 -6.75287902e-01
-1.23278606e+00 -3.33148599e-01 -1.61308497e-01 1.40262157e-01
3.24771166e-01 6.22424185e-01 -1.78668573e-01 1.60565421e-01
-8.71018879e-03 6.23153687e-01 -3.13665599e-01 -6.78062677e-01
-3.13915499e-02 6.52010143e-01 -4.44252696e-03 -3.47655594e-01
5.60205162e-01 3.18171889e-01 -4.67579365e-01 -3.99118274e-01
-1.30895317e+00 -9.07220364e-01 -1.28631428e-01 -1.73808545e-01
9.96603817e-02 -6.93775117e-01 -1.15226948e+00 2.25701317e-01
-3.95577341e-01 -1.16899861e-02 -3.80040123e-03 6.43169820e-01
-2.23582223e-01 7.44812667e-01 -5.23579597e-01 -9.94048059e-01
-4.67398465e-01 -6.07742071e-01 2.94078231e-01 7.13994265e-01
1.13944225e-01 -1.04813552e+00 -8.96173194e-02 3.66559297e-01
4.84100461e-01 -3.84238869e-01 6.02243602e-01 -7.94647574e-01
-4.26471651e-01 -3.97123784e-01 -3.37171882e-01 2.01639026e-01
5.11005282e-01 -2.07059771e-01 -4.67402935e-01 -3.38766456e-01
-7.16168620e-03 1.58708140e-01 7.21285820e-01 3.46741855e-01
1.81515419e+00 -5.34620702e-01 -3.19334090e-01 2.69894511e-01
1.15615404e+00 4.08611268e-01 5.34930706e-01 2.24200308e-01
5.02316475e-01 4.68398541e-01 1.09205687e+00 8.27584922e-01
6.61666930e-01 7.46288002e-01 3.78490299e-01 3.41568798e-01
6.01701558e-01 -4.85219747e-01 3.19828689e-01 1.02767313e+00
-3.60991210e-01 -1.36982232e-01 -5.10384962e-02 2.76993215e-01
-2.14224815e+00 -9.85935092e-01 -1.58091038e-01 2.66025114e+00
7.16504097e-01 4.63344187e-01 4.69617337e-01 -3.41988131e-02
6.17775083e-01 1.89679965e-01 -8.88573468e-01 2.16421902e-01
3.56499761e-01 -2.34006956e-01 2.63594031e-01 3.13125014e-01
-8.51298988e-01 5.46843350e-01 5.38359165e+00 1.13063633e+00
-1.09015131e+00 -3.62858176e-02 7.56720781e-01 -3.15048844e-01
-5.60352862e-01 -2.35496223e-01 -1.04454553e+00 1.15506220e+00
5.87285459e-01 -5.72812676e-01 6.41263783e-01 9.32632804e-01
7.08463848e-01 1.71101183e-01 -8.02605987e-01 6.10039830e-01
-6.76021650e-02 -9.65588093e-01 -4.54481505e-02 1.12908132e-01
6.79372489e-01 -2.12728530e-01 2.31872857e-01 5.31313181e-01
1.96132496e-01 -2.38463849e-01 3.05599451e-01 8.09153914e-01
1.50884101e-02 -8.09080839e-01 4.05088037e-01 6.65857375e-01
-1.41619790e+00 -3.52917165e-01 -4.53424186e-01 -1.04994386e-01
1.36467755e-01 7.66625047e-01 -3.79694700e-01 5.94836235e-01
6.82119012e-01 1.20629346e+00 -3.48642081e-01 1.27106559e+00
1.12105429e-01 9.23501253e-01 -2.01446220e-01 -3.13789874e-01
8.70081261e-02 -6.66728258e-01 3.15408587e-01 7.15793371e-01
5.51255643e-01 1.34743139e-01 2.29543775e-01 3.70011449e-01
1.30409363e-03 5.38695931e-01 1.35074899e-01 2.33245958e-02
5.47552705e-01 1.31616080e+00 -3.74363869e-01 -1.62291840e-01
-7.22872794e-01 7.97482193e-01 1.63199008e-01 2.76959598e-01
-8.29637349e-01 -2.98523039e-01 6.19663417e-01 3.40880036e-01
5.27485251e-01 -4.52255271e-03 -6.91780746e-02 -1.42717409e+00
3.36616725e-01 -5.31857491e-01 5.65937400e-01 -5.09616546e-02
-1.58382964e+00 1.62818477e-01 -4.33311164e-01 -1.80015469e+00
9.45321247e-02 -1.57815859e-01 -1.05446982e+00 4.60517675e-01
-1.58517504e+00 -6.64810717e-01 -3.00183266e-01 5.70963562e-01
7.43469298e-01 1.26374170e-01 2.93768495e-01 6.33825481e-01
-7.95540333e-01 8.59941006e-01 4.96622056e-01 -3.10899794e-01
5.77122152e-01 -9.87316191e-01 1.81170374e-01 3.19103271e-01
-1.83256969e-01 9.93757904e-01 5.41049302e-01 -3.60639215e-01
-1.07933366e+00 -1.01334405e+00 9.66509402e-01 -6.34952709e-02
8.13855588e-01 -1.13473170e-01 -1.12939656e+00 4.92962956e-01
-4.21187013e-01 -1.16088346e-01 1.19032228e+00 6.38007343e-01
-2.12130681e-01 -5.94545960e-01 -8.55545640e-01 7.66181171e-01
1.25499725e+00 -1.02063954e-01 -3.50287944e-01 3.84318173e-01
6.13074064e-01 1.17596202e-02 -9.02002215e-01 4.70174909e-01
8.89802337e-01 -9.67177272e-01 9.94845510e-01 -5.70672035e-01
1.97921067e-01 -1.54764920e-01 8.66210833e-02 -1.07976639e+00
-6.34162426e-01 -5.43095529e-01 -5.46562135e-01 1.24921191e+00
4.42251831e-01 -8.64723682e-01 1.00621188e+00 8.59070182e-01
1.27903759e-01 -9.36736703e-01 -4.15223420e-01 -6.57030225e-01
-5.44162035e-01 -1.90462768e-01 8.40533674e-01 9.53138173e-01
2.07263723e-01 2.83485204e-01 -8.27603459e-01 -1.67029984e-02
5.10645568e-01 6.30874872e-01 4.98520643e-01 -1.45592833e+00
-6.06951892e-01 -6.14519536e-01 1.85211122e-01 -1.73907733e+00
-2.40167543e-01 -4.89501029e-01 -1.73885822e-01 -1.27244246e+00
4.09724206e-01 -6.33322656e-01 -1.14599431e+00 -9.63664148e-03
-5.93365371e-01 -1.99747887e-02 -2.95073003e-01 5.27175128e-01
-1.21011615e+00 5.80177426e-01 1.31447852e+00 1.80318058e-01
-5.98278165e-01 9.33500051e-01 -1.05433786e+00 5.87480783e-01
8.20254326e-01 -9.61103812e-02 -7.65811443e-01 6.75775984e-04
3.56388569e-01 -5.88352233e-02 -1.97857991e-01 -7.57187307e-01
1.27976522e-01 -6.45765305e-01 1.22532994e-01 -7.07398653e-01
-4.66520861e-02 -8.23514163e-01 -1.32632598e-01 2.94296473e-01
-6.70577824e-01 -5.97365677e-01 -4.29163188e-01 1.13497388e+00
-3.62220816e-02 -1.66144535e-01 2.74055362e-01 2.00505823e-01
-7.11260915e-01 9.34300005e-01 -1.22819178e-01 -1.10154025e-01
8.63167167e-01 -1.11500069e-01 2.18210831e-01 -4.01523083e-01
-7.43520617e-01 6.92503214e-01 2.21134380e-01 6.72491372e-01
3.27678621e-01 -1.41606402e+00 -3.25066686e-01 5.12678735e-02
2.67860115e-01 -3.70439112e-01 6.81264102e-01 8.82022321e-01
3.63650918e-01 3.82808506e-01 2.48704687e-01 -9.44784954e-02
-1.36571968e+00 6.09414816e-01 6.82860911e-02 -5.75300276e-01
-3.11236054e-01 5.66961527e-01 3.51982832e-01 -2.47449443e-01
4.33298677e-01 -6.99041039e-02 -8.56166124e-01 1.25005186e-01
8.97972882e-01 5.11517227e-01 -2.68606376e-02 -8.61316249e-02
-1.56738058e-01 2.60281086e-01 -6.99151456e-01 4.49845910e-01
1.25111151e+00 -6.41625464e-01 1.90271094e-01 5.63028038e-01
1.03912592e+00 2.43575305e-01 -1.41418457e+00 -8.17794204e-01
9.63668227e-02 -8.25885892e-01 9.71865654e-02 -4.78794545e-01
-1.29813278e+00 4.97202545e-01 3.79425704e-01 5.90773046e-01
1.19717801e+00 -3.86852413e-01 1.26213932e+00 3.37160677e-01
3.55288386e-01 -1.26472723e+00 9.25264042e-03 3.44955444e-01
3.20285350e-01 -1.15088904e+00 -1.18261110e-02 -5.03552794e-01
-5.59793770e-01 7.17332363e-01 7.05182850e-01 -9.20554972e-04
1.00888801e+00 -5.27357101e-01 -3.36631149e-01 4.03515309e-01
-7.94218123e-01 -8.26526731e-02 5.67886412e-01 1.17804460e-01
5.64138055e-01 9.21172798e-02 -1.03129303e+00 1.20011091e+00
2.33487859e-01 2.67934263e-01 5.92120551e-02 7.06342340e-01
-6.66337132e-01 -1.27973461e+00 3.39334220e-01 9.63326871e-01
-6.08790100e-01 -3.80262733e-02 -4.01291028e-02 5.20828031e-02
-8.99222195e-02 9.95687544e-01 1.72048267e-02 -6.38697982e-01
4.21461105e-01 -3.14086378e-01 2.07746904e-02 -3.17688912e-01
-4.38424528e-01 2.27373168e-01 -1.54757813e-01 -4.82972264e-01
-3.15090328e-01 -7.08465219e-01 -1.03984034e+00 -3.82666081e-01
-3.92026603e-01 5.50442874e-01 2.79110491e-01 1.03175700e+00
5.02434373e-01 3.72479498e-01 1.49527800e+00 -5.05221188e-01
-7.09637105e-01 -7.27284431e-01 -7.60754943e-01 4.30133045e-01
4.82894331e-02 -4.76631969e-01 -4.66465056e-01 -2.58756697e-01] | [10.1459379196167, 5.570515155792236] |
e846e7ad-46ad-43a3-a6b5-4ce8889bb876 | grammar-based-patches-generation-for | null | null | https://aclanthology.org/2021.findings-acl.111 | https://aclanthology.org/2021.findings-acl.111.pdf | Grammar-Based Patches Generation for Automated Program Repair | null | ['Muyun Yang', 'Ming Zhou', 'Furu Wei', 'Shujie Liu', 'Ambrosio Blanco', 'Long Zhou', 'Yu Tang'] | null | null | null | null | findings-acl-2021-8 | ['program-repair', 'program-repair'] | ['computer-code', 'reasoning'] | [-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] | [-7.230523109436035, 3.6383047103881836] |
6984b088-a981-4aaf-b42e-3bad2ca0f66e | weakly-supervised-action-segmentation-using | 1904.03116 | null | https://arxiv.org/abs/1904.03116v4 | https://arxiv.org/pdf/1904.03116v4.pdf | Fast Weakly Supervised Action Segmentation Using Mutual Consistency | Action segmentation is the task of predicting the actions for each frame of a video. As obtaining the full annotation of videos for action segmentation is expensive, weakly supervised approaches that can learn only from transcripts are appealing. In this paper, we propose a novel end-to-end approach for weakly supervised action segmentation based on a two-branch neural network. The two branches of our network predict two redundant but different representations for action segmentation and we propose a novel mutual consistency (MuCon) loss that enforces the consistency of the two redundant representations. Using the MuCon loss together with a loss for transcript prediction, our proposed approach achieves the accuracy of state-of-the-art approaches while being $14$ times faster to train and $20$ times faster during inference. The MuCon loss proves beneficial even in the fully supervised setting. | ['Yaser Souri', 'Luca Minciullo', 'Mohsen Fayyaz', 'Juergen Gall', 'Gianpiero Francesca'] | 2019-04-05 | null | null | null | null | ['weakly-supervised-action-segmentation'] | ['computer-vision'] | [ 7.19283462e-01 5.40008962e-01 -5.83945632e-01 -5.90833366e-01
-1.15563858e+00 -4.28073347e-01 2.82036453e-01 -2.20678654e-02
-4.49128002e-01 6.26909554e-01 2.43818596e-01 -1.46802887e-01
1.96812078e-01 -2.22784698e-01 -1.02499044e+00 -5.46503425e-01
-7.37374201e-02 3.26133579e-01 3.28921646e-01 3.49619538e-01
-2.98585389e-02 1.12622105e-01 -1.35399592e+00 5.37934422e-01
5.19199193e-01 1.33761084e+00 1.48998750e-02 7.49413013e-01
1.14375316e-01 1.36745870e+00 -1.16771698e-01 -5.50740004e-01
4.93080199e-01 -7.10830390e-01 -1.25700128e+00 3.83934081e-01
6.27896130e-01 -5.14685929e-01 -4.20546472e-01 7.89342999e-01
1.58778191e-01 1.88920349e-01 3.37390810e-01 -1.19966972e+00
7.75483111e-03 7.61161566e-01 -5.84355772e-01 6.25663996e-02
3.22695971e-01 1.04190916e-01 1.51082647e+00 -4.77773517e-01
5.94967961e-01 1.16140342e+00 6.88938975e-01 5.98668873e-01
-1.23540044e+00 -3.92479748e-01 5.61802089e-01 1.55871630e-01
-1.14120162e+00 -3.65291238e-01 5.77251971e-01 -3.06595951e-01
9.88015473e-01 -4.79289219e-02 4.11308467e-01 9.49851990e-01
-1.16944402e-01 1.37280822e+00 8.03794861e-01 -1.28126979e-01
2.02822596e-01 -2.57584929e-01 1.47218913e-01 1.09496653e+00
-1.13514557e-01 -3.77098829e-01 -6.03644848e-01 -4.36138324e-02
7.31906235e-01 -2.51913667e-02 -1.53030366e-01 -4.31121022e-01
-9.57729638e-01 6.20516300e-01 1.78036436e-01 2.65054069e-02
-2.66515821e-01 6.83411837e-01 5.94707072e-01 7.20733702e-02
5.37870347e-01 1.93389848e-01 -7.19242990e-01 -5.62689900e-01
-1.04290903e+00 1.40431300e-01 7.00001657e-01 9.26076174e-01
6.37758791e-01 -2.84566849e-01 -3.31787884e-01 6.19040787e-01
1.97774008e-01 1.44912433e-02 2.05720559e-01 -1.57290864e+00
6.04174197e-01 6.08818829e-01 1.64339364e-01 -5.77199280e-01
-2.85789460e-01 -9.87072885e-02 -4.04261738e-01 -1.32080629e-01
6.60468400e-01 -2.30074316e-01 -8.57743025e-01 1.98859048e+00
3.08143467e-01 6.14515424e-01 -1.98537469e-01 8.07545960e-01
2.53729194e-01 4.72907335e-01 1.74497023e-01 -2.13274315e-01
1.02107215e+00 -1.27342927e+00 -4.51471329e-01 -3.41896117e-01
8.94863665e-01 -4.62751389e-01 8.69036376e-01 3.71534020e-01
-1.32785594e+00 -4.24842745e-01 -7.96153843e-01 -3.72704864e-01
2.33605996e-01 3.55561346e-01 8.22635472e-01 3.06746840e-01
-8.37683558e-01 9.58865762e-01 -1.40133464e+00 -8.36704597e-02
7.81325638e-01 4.68373030e-01 -2.77666986e-01 -1.63770080e-01
-6.22436643e-01 5.29464900e-01 1.72765136e-01 -9.31300037e-03
-9.75809097e-01 -4.77031171e-01 -1.06092513e+00 1.23360567e-01
6.70939684e-01 -4.09201294e-01 1.46349919e+00 -1.42569935e+00
-1.63260865e+00 8.62280548e-01 -3.90628010e-01 -8.93478215e-01
8.39603126e-01 -6.56237245e-01 2.05316946e-01 6.41667604e-01
2.15907276e-01 9.60592389e-01 7.52019346e-01 -8.29813361e-01
-8.10878098e-01 -1.52200237e-01 3.41179997e-01 1.00372292e-01
1.23667605e-02 -9.05223265e-02 -8.07443917e-01 -5.51829040e-01
8.11461136e-02 -1.18683422e+00 -4.28021759e-01 2.95400947e-01
-4.49633539e-01 -4.48734730e-01 5.73374093e-01 -8.06923807e-01
9.94256616e-01 -2.14368916e+00 2.18624726e-01 -2.12726802e-01
-6.75658137e-02 1.44313857e-01 -3.06466639e-01 2.79363394e-02
4.06658836e-02 -7.79169202e-02 -4.21723366e-01 -7.27430165e-01
7.34726489e-02 2.66680360e-01 -1.67798832e-01 5.24593055e-01
4.66551870e-01 8.08889091e-01 -1.01189053e+00 -5.12031615e-01
-1.01132266e-01 3.57579708e-01 -7.94029951e-01 2.66390562e-01
-4.75172490e-01 5.79669297e-01 -3.58365148e-01 6.82714105e-01
3.61495405e-01 -5.00725865e-01 5.59887946e-01 -1.03786036e-01
2.48885944e-01 4.38996851e-01 -8.93027902e-01 2.11405063e+00
-3.82708222e-01 4.69975144e-01 1.01130441e-01 -1.38287163e+00
3.67062807e-01 3.93939704e-01 7.71364331e-01 -3.39121670e-01
1.90499902e-01 1.11137822e-01 -3.23602349e-01 -4.42751527e-01
1.51760697e-01 -2.66256988e-01 -2.42026284e-01 5.68790615e-01
3.27296346e-01 1.78652078e-01 4.18962032e-01 1.84420973e-01
1.39071286e+00 8.49068224e-01 -1.12381177e-02 8.02513212e-02
3.47425312e-01 -2.03456521e-01 9.10928726e-01 6.95232689e-01
-3.20861906e-01 6.55451715e-01 9.65758204e-01 -4.69373792e-01
-7.24198222e-01 -7.75643766e-01 2.87606508e-01 1.17858338e+00
2.35894462e-03 -3.47874373e-01 -9.43740129e-01 -1.28715479e+00
-1.65669069e-01 4.92108971e-01 -4.83842045e-01 -4.82662283e-02
-6.96003079e-01 -2.10886136e-01 6.43420517e-01 9.97857034e-01
5.38915157e-01 -7.30651855e-01 -6.00250304e-01 1.54710576e-01
-4.37127799e-01 -1.57674372e+00 -5.25134027e-01 2.05841511e-01
-1.05485022e+00 -1.26540816e+00 -4.92801756e-01 -7.24358916e-01
7.66891181e-01 1.72406714e-02 1.12185252e+00 1.11140288e-01
-7.73728192e-02 3.25261444e-01 -3.10702592e-01 -1.00260451e-02
-1.31841108e-01 4.94303815e-02 -1.07090145e-01 2.24571884e-01
3.52623999e-01 -5.75412869e-01 -5.01934886e-01 2.19386190e-01
-7.92335212e-01 8.15824866e-02 5.88192523e-01 7.19103694e-01
9.00834560e-01 -1.50018528e-01 2.63125539e-01 -9.77075875e-01
-1.31744891e-01 -2.89547026e-01 -5.77230036e-01 1.19774342e-01
-2.95013458e-01 2.40492731e-01 6.76706195e-01 -2.69031793e-01
-1.01181960e+00 7.78712571e-01 -1.03381217e-01 -5.46618700e-01
-2.23562151e-01 3.05738926e-01 -2.25500658e-01 2.00424060e-01
7.81646818e-02 -1.92483570e-02 -1.30124837e-01 -7.11584270e-01
2.99783170e-01 2.73580134e-01 5.09495974e-01 -5.19202113e-01
4.13554013e-01 6.22968793e-01 7.82263130e-02 -5.49946487e-01
-1.41657007e+00 -5.01356661e-01 -9.12235975e-01 8.29649996e-03
1.08198798e+00 -1.10126400e+00 -7.12797344e-01 3.99058491e-01
-1.02322710e+00 -6.33792579e-01 -4.98872757e-01 6.44227266e-01
-1.05393386e+00 6.08253539e-01 -8.19432378e-01 -7.62070060e-01
-7.29604810e-02 -1.09999275e+00 1.25654125e+00 1.25984382e-02
-3.48147035e-01 -6.84417725e-01 -1.89679358e-02 9.21257019e-01
-2.38256797e-01 2.59109259e-01 7.33268559e-01 -5.44783890e-01
-7.88640499e-01 -3.26954901e-01 -2.05313727e-01 6.85456395e-01
-3.08393016e-02 -1.83684230e-01 -9.31358218e-01 -2.15827897e-01
-2.73882717e-01 -7.97143281e-01 1.33738458e+00 4.66117531e-01
1.33284724e+00 -4.84531850e-01 -1.59409493e-01 5.70101619e-01
1.30553234e+00 -1.11064933e-01 6.32423699e-01 -1.94444992e-02
8.49188149e-01 5.19639075e-01 7.95963645e-01 5.47796011e-01
3.76072735e-01 6.64310634e-01 3.41952652e-01 3.68641913e-02
2.77864672e-02 -4.45715308e-01 7.12298632e-01 3.82021397e-01
-2.38961220e-01 -1.98587805e-01 -5.88437200e-01 6.18626475e-01
-2.17241311e+00 -1.01998174e+00 2.05745921e-01 2.17219114e+00
1.00335491e+00 4.08770055e-01 2.95215011e-01 -4.37805988e-02
5.12986600e-01 3.37706923e-01 -7.13146865e-01 -3.74441385e-01
2.72119850e-01 2.84981966e-01 5.50590932e-01 5.20983875e-01
-1.49132383e+00 1.04619968e+00 6.28467798e+00 6.83393359e-01
-8.52963686e-01 9.89164859e-02 7.97324121e-01 -4.89271075e-01
8.01520124e-02 1.78199202e-01 -7.65369952e-01 4.35396820e-01
1.05967557e+00 3.64886254e-01 1.46670073e-01 1.00712788e+00
2.78947473e-01 -3.23508412e-01 -1.38606012e+00 7.28745461e-01
1.01319313e-01 -1.30172634e+00 -8.13276768e-02 -3.99763184e-03
7.75616586e-01 1.24171533e-01 -2.03121632e-01 1.64375439e-01
4.08147454e-01 -8.51856887e-01 7.34274983e-01 3.64325285e-01
5.55218995e-01 -9.00823772e-01 7.53931880e-01 2.73078203e-01
-1.14942610e+00 -1.97333559e-01 -5.64003512e-02 -2.47487247e-01
3.65829110e-01 4.46491510e-01 -5.09901345e-01 2.84358829e-01
4.97458607e-01 9.32451904e-01 -4.05746400e-01 6.64204478e-01
-4.35196429e-01 9.41447020e-01 -2.57301688e-01 3.44164938e-01
5.83669901e-01 -8.25181752e-02 2.48236358e-01 1.18672359e+00
2.91311238e-02 1.53379783e-01 6.12403750e-01 5.44113457e-01
-4.91909653e-01 -2.81765729e-01 -3.20261151e-01 -4.72186685e-01
-1.89769268e-03 1.00506926e+00 -8.25976968e-01 -4.57194179e-01
-5.58579922e-01 1.42200601e+00 4.30815071e-01 1.40377074e-01
-9.87659752e-01 -1.49174765e-01 6.38900995e-01 3.08333300e-02
7.46485531e-01 -6.39722869e-02 -2.69939989e-01 -1.11154342e+00
2.53498822e-01 -7.18371451e-01 4.65772897e-01 -3.24769467e-01
-1.08531475e+00 2.24049702e-01 -1.13840327e-01 -1.24835885e+00
-3.36420834e-01 -4.72112209e-01 -4.23083574e-01 2.72243321e-01
-1.46573746e+00 -1.16818690e+00 9.65516567e-02 3.34390581e-01
7.89348602e-01 2.90654808e-01 6.69504106e-01 1.80280641e-01
-6.16603732e-01 5.22257566e-01 -1.88850835e-01 4.63578552e-01
4.18138236e-01 -1.24779105e+00 3.45457464e-01 8.94072652e-01
2.47486249e-01 3.43081355e-01 5.34884989e-01 -4.47654665e-01
-1.13521504e+00 -1.13096333e+00 9.79865670e-01 -3.33468914e-01
4.56680357e-01 -2.96504825e-01 -5.97454786e-01 1.02285862e+00
1.39025748e-02 3.16168725e-01 8.45375955e-01 7.99606070e-02
-5.11549652e-01 -1.50055140e-01 -9.54636335e-01 4.03019845e-01
1.13009894e+00 -5.97512364e-01 -2.66868353e-01 5.45540512e-01
7.40838289e-01 -2.75258929e-01 -6.98198795e-01 2.49492332e-01
6.10278428e-01 -9.58269417e-01 7.12837100e-01 -7.89624155e-01
7.29379475e-01 -1.66453883e-01 -2.09815547e-01 -6.30893350e-01
-5.49863800e-02 -7.29219317e-01 -2.51054943e-01 1.01259828e+00
6.23626530e-01 -3.82424183e-02 1.24766922e+00 7.97915041e-01
-2.33439170e-02 -1.03839052e+00 -9.75234807e-01 -8.58132303e-01
-2.12985948e-01 -5.34907043e-01 -3.98347005e-02 7.36961782e-01
1.47495478e-01 3.97765249e-01 -6.40331924e-01 8.75314549e-02
6.35516465e-01 2.49767169e-01 6.09709442e-01 -9.89459991e-01
-7.73249567e-01 -1.35232374e-01 -5.12174487e-01 -1.51060987e+00
5.33869684e-01 -6.64996743e-01 3.78213942e-01 -1.45368433e+00
4.67112780e-01 -6.44435734e-02 -3.70239973e-01 7.26395547e-01
-1.11347713e-01 3.55653822e-01 2.64096588e-01 -2.54747476e-02
-1.20527124e+00 4.61199701e-01 8.77386749e-01 -1.70076460e-01
-6.86636567e-02 1.61387637e-01 -4.84837860e-01 1.19074953e+00
6.68350935e-01 -6.07130587e-01 -4.71095026e-01 -6.27286375e-01
-4.85485457e-02 1.55160680e-01 2.94050395e-01 -1.01784134e+00
-1.22622205e-02 -4.88000214e-02 2.06054986e-01 -5.56267858e-01
5.71154714e-01 -6.90678477e-01 -3.89667332e-01 3.76099735e-01
-6.99483693e-01 -3.65207016e-01 -8.22033882e-02 9.25490856e-01
-3.09427351e-01 -1.19325772e-01 8.68957341e-01 -3.36468101e-01
-5.38023651e-01 3.68879735e-01 -2.19042048e-01 2.57019460e-01
1.02801704e+00 -1.24036245e-01 1.64894938e-01 -4.45710123e-01
-8.20298314e-01 2.40393981e-01 3.37178648e-01 1.66219175e-01
4.77566957e-01 -9.39517796e-01 -5.27175426e-01 -1.64640605e-01
-2.37027809e-01 7.37210885e-02 1.64496943e-01 1.06189036e+00
-3.15343589e-01 3.45422924e-01 -4.29715812e-02 -4.97048140e-01
-1.41373074e+00 2.29065537e-01 1.83269933e-01 -7.58282423e-01
-5.30051529e-01 1.23198950e+00 8.15085098e-02 -2.70771861e-01
5.29325604e-01 -3.81987423e-01 7.89202899e-02 -4.66166809e-03
4.98710304e-01 4.18152094e-01 -2.33009696e-01 -7.00761616e-01
-4.76226389e-01 3.02326381e-01 -1.75224572e-01 -2.81491846e-01
1.47173345e+00 5.78320026e-02 5.28815314e-02 4.51826006e-01
1.37280786e+00 -2.75943220e-01 -2.02493787e+00 -2.13797957e-01
1.92570522e-01 -4.78656322e-01 -9.58313271e-02 -6.49359226e-01
-1.21729791e+00 8.56720865e-01 3.04418057e-01 -2.32332751e-01
1.06166315e+00 1.43197984e-01 1.20924532e+00 4.87900794e-01
3.35305840e-01 -1.50644553e+00 1.93772912e-01 4.79933500e-01
3.14793527e-01 -1.21255600e+00 5.26901260e-02 -4.89958078e-01
-8.38635385e-01 7.84571528e-01 4.47169989e-01 -2.25818798e-01
3.62848520e-01 9.41094235e-02 -1.75149664e-01 -1.83191784e-02
-9.40883815e-01 -3.99492502e-01 7.74797574e-02 2.96615034e-01
5.49578965e-01 -2.09312484e-01 -4.78689611e-01 6.06238842e-01
4.07230139e-01 3.16298544e-01 2.99519360e-01 1.12454939e+00
-3.53595793e-01 -1.06275344e+00 2.15390205e-01 4.38390732e-01
-8.97207141e-01 5.13958484e-02 -5.62525511e-01 3.65609229e-01
1.79236963e-01 1.07084239e+00 1.55911714e-01 -2.69109517e-01
1.62946552e-01 3.33587915e-01 6.11691058e-01 -6.37996137e-01
-2.83544451e-01 7.82568753e-02 3.73588413e-01 -1.15589416e+00
-8.48610103e-01 -8.27952087e-01 -1.54955256e+00 3.50540876e-03
-1.19238853e-01 2.34582517e-02 2.68914551e-01 1.21927691e+00
3.79656553e-01 2.29508102e-01 6.76836252e-01 -8.73847067e-01
-5.64222574e-01 -7.60327816e-01 -4.93382454e-01 6.12969756e-01
2.87764132e-01 -5.26426792e-01 -2.39482060e-01 4.84441042e-01] | [8.480198860168457, 0.5983633995056152] |
46c086a3-6f99-4286-90f0-7fe65034f193 | selective-transfer-with-reinforced-transfer | 1905.10756 | null | https://arxiv.org/abs/1905.10756v4 | https://arxiv.org/pdf/1905.10756v4.pdf | Selective Transfer with Reinforced Transfer Network for Partial Domain Adaptation | One crucial aspect of partial domain adaptation (PDA) is how to select the relevant source samples in the shared classes for knowledge transfer. Previous PDA methods tackle this problem by re-weighting the source samples based on their high-level information (deep features). However, since the domain shift between source and target domains, only using the deep features for sample selection is defective. We argue that it is more reasonable to additionally exploit the pixel-level information for PDA problem, as the appearance difference between outlier source classes and target classes is significantly large. In this paper, we propose a reinforced transfer network (RTNet), which utilizes both high-level and pixel-level information for PDA problem. Our RTNet is composed of a reinforced data selector (RDS) based on reinforcement learning (RL), which filters out the outlier source samples, and a domain adaptation model which minimizes the domain discrepancy in the shared label space. Specifically, in the RDS, we design a novel reward based on the reconstruct errors of selected source samples on the target generator, which introduces the pixel-level information to guide the learning of RDS. Besides, we develope a state containing high-level information, which used by the RDS for sample selection. The proposed RDS is a general module, which can be easily integrated into existing DA models to make them fit the PDA situation. Extensive experiments indicate that RTNet can achieve state-of-the-art performance for PDA tasks on several benchmark datasets. | ['Ke Fang', 'Chao Chen', 'Zhihong Chen', 'Zhaowei Cheng', 'Xinyu Jin', 'Boyuan Jiang'] | 2019-05-26 | selective-transfer-with-reinforced-transfer-1 | http://openaccess.thecvf.com/content_CVPR_2020/html/Chen_Selective_Transfer_With_Reinforced_Transfer_Network_for_Partial_Domain_Adaptation_CVPR_2020_paper.html | http://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_Selective_Transfer_With_Reinforced_Transfer_Network_for_Partial_Domain_Adaptation_CVPR_2020_paper.pdf | cvpr-2020-6 | ['partial-domain-adaptation'] | ['methodology'] | [ 2.07611397e-01 -8.69898275e-02 -3.60238135e-01 -3.95236731e-01
-7.21818209e-01 -2.48265162e-01 2.62279928e-01 4.74900790e-02
-3.76852870e-01 8.51066709e-01 -7.24028796e-02 2.76039869e-01
-9.38955322e-02 -1.10324669e+00 -7.98831046e-01 -9.84710872e-01
1.84809923e-01 3.84925187e-01 7.19085872e-01 -1.18302166e-01
2.23698556e-01 5.22375584e-01 -1.54604340e+00 5.13625264e-01
1.26037323e+00 1.36057484e+00 5.78145444e-01 -5.87485433e-02
-3.35810155e-01 6.35152340e-01 -6.58175290e-01 3.45312059e-02
2.61016846e-01 -4.95964378e-01 -5.47688007e-01 1.24070356e-02
8.71475413e-02 -3.19277197e-01 -9.72956792e-02 1.07970953e+00
7.12151825e-01 1.80358171e-01 8.46140325e-01 -1.50568867e+00
-7.71692276e-01 4.72188950e-01 -6.17971957e-01 2.09618300e-01
-2.55737267e-02 3.55582207e-01 8.13649654e-01 -8.75599325e-01
5.75735927e-01 1.22506177e+00 4.05834049e-01 6.53441966e-01
-1.08394611e+00 -8.83040607e-01 5.05003512e-01 4.32621837e-01
-1.20994508e+00 -1.91893384e-01 1.19690716e+00 -3.98375034e-01
4.69357014e-01 -2.72066027e-01 5.01420736e-01 1.30872631e+00
1.02115512e-01 1.13683164e+00 1.22913468e+00 -4.61222917e-01
5.78268588e-01 5.96306443e-01 5.91192394e-02 4.83790517e-01
1.29119277e-01 2.77249366e-01 -6.16512537e-01 -8.62897038e-02
8.60378623e-01 -3.83469388e-02 -1.01407036e-01 -9.22416210e-01
-1.06863356e+00 8.68925691e-01 6.25785649e-01 1.98907539e-01
-3.38375926e-01 -2.90241331e-01 2.55014151e-01 4.70968455e-01
4.48797077e-01 3.34410042e-01 -6.62627339e-01 2.80604899e-01
-6.04583442e-01 1.60014480e-01 4.34719443e-01 1.04003298e+00
8.96630466e-01 -4.44460958e-02 -6.02395058e-01 1.19468403e+00
5.04128456e-01 5.17640591e-01 6.75361514e-01 -8.01969230e-01
4.99329686e-01 9.06138301e-01 -1.28662540e-02 -8.25613737e-01
-2.60328710e-01 -6.42948270e-01 -7.41856277e-01 6.07282877e-01
4.48933542e-01 -1.49235159e-01 -9.01297450e-01 1.97140944e+00
4.49133992e-01 2.56154448e-01 1.15172975e-01 8.76199186e-01
6.86294198e-01 5.51687002e-01 8.04650038e-02 -1.69436097e-01
1.01564467e+00 -9.22567666e-01 -3.73127878e-01 -2.90413231e-01
4.17883724e-01 -3.27042401e-01 1.28693151e+00 4.72992361e-01
-8.38566780e-01 -7.77804673e-01 -1.22754741e+00 3.09574902e-01
-3.85140061e-01 4.10971969e-01 2.53643245e-01 4.84776288e-01
-6.67014539e-01 7.63240039e-01 -4.72746730e-01 -3.98079515e-01
8.07176054e-01 3.59028518e-01 -3.54105816e-03 -6.44357875e-02
-1.36595976e+00 6.45494759e-01 4.50226247e-01 -2.69907326e-01
-1.10950375e+00 -8.08511734e-01 -6.69021249e-01 2.35610479e-03
4.12913263e-01 -5.50537169e-01 1.12072647e+00 -1.28295922e+00
-1.83078134e+00 6.57434106e-01 9.35398862e-02 -2.52410650e-01
5.78683257e-01 7.80805275e-02 -6.12004101e-01 9.27869976e-02
1.56717986e-01 8.54161143e-01 1.18663478e+00 -1.49217737e+00
-1.11530983e+00 -2.98748076e-01 -2.62718827e-01 4.08689857e-01
-5.30477762e-01 -3.33468318e-01 -2.65188992e-01 -8.02964926e-01
-5.13082929e-02 -6.58385158e-01 -1.00713447e-01 2.26842716e-01
-1.13581635e-01 -4.36707467e-01 7.37224162e-01 -3.45124722e-01
1.11992574e+00 -2.39784789e+00 6.74773008e-02 4.25151229e-01
3.66581008e-02 3.43224674e-01 -3.27678442e-01 5.44708641e-03
3.79649810e-02 -3.63090247e-01 -3.79676074e-01 5.70833385e-02
4.01466861e-02 9.18727815e-02 -4.05737221e-01 1.42770633e-01
4.63093489e-01 4.55194622e-01 -1.06538332e+00 -4.32638943e-01
6.65055867e-03 5.63287437e-02 -4.98532206e-01 2.76092678e-01
-3.59205365e-01 5.47761261e-01 -6.87000453e-01 5.33143461e-01
9.51986432e-01 -1.65323585e-01 -9.81718898e-02 -1.99301735e-01
1.51102394e-01 1.93766624e-01 -1.40029562e+00 1.67318738e+00
-1.86940759e-01 3.93830948e-02 -7.65808374e-02 -9.06094253e-01
1.44644606e+00 -6.54136837e-02 5.07834792e-01 -9.09314930e-01
-5.67885563e-02 4.06517297e-01 5.86262555e-04 -1.93938166e-01
1.69671580e-01 -6.93883523e-02 8.52519423e-02 2.59409696e-01
9.99397039e-02 7.52892718e-02 5.06592356e-02 -7.18389079e-03
9.89440203e-01 3.91182065e-01 1.42575085e-01 -2.35784963e-01
7.98369765e-01 2.50238851e-02 9.05874074e-01 5.87332904e-01
-4.63777304e-01 5.29011607e-01 5.49207985e-01 -1.63987190e-01
-8.39620709e-01 -1.34064007e+00 -3.59281339e-02 1.13490105e+00
3.70453954e-01 1.98004708e-01 -6.52017355e-01 -1.23971677e+00
1.84637070e-01 7.46921062e-01 -4.92727697e-01 -7.37187207e-01
-4.53645259e-01 -6.31263852e-01 2.73148537e-01 6.00380421e-01
7.91224360e-01 -1.50617516e+00 -2.74218142e-01 2.85376996e-01
1.31141081e-01 -6.09481037e-01 -4.55370516e-01 4.17945385e-01
-9.11173284e-01 -9.25619841e-01 -8.67061079e-01 -9.90215898e-01
8.15285623e-01 1.57151774e-01 8.56043518e-01 -3.93570453e-01
1.07830919e-01 1.40157074e-01 -4.02994186e-01 -4.38182503e-01
-3.19416702e-01 2.88922429e-01 4.42740023e-02 1.55689374e-01
5.77813804e-01 -5.53367674e-01 -5.78548789e-01 5.92117071e-01
-8.43535542e-01 -2.41185442e-01 8.07375968e-01 9.79610682e-01
8.18980455e-01 1.89269125e-01 1.23350859e+00 -9.07831013e-01
6.20942891e-01 -5.69744408e-01 -4.74793583e-01 2.51464546e-01
-7.47266471e-01 1.79397970e-01 8.82708907e-01 -5.71209729e-01
-1.30427027e+00 1.00575633e-01 -9.00930986e-02 -5.09374559e-01
-2.75109023e-01 1.53793514e-01 -5.32686114e-01 1.07049376e-01
7.95946062e-01 2.91776896e-01 1.47917464e-01 -5.59602678e-01
4.31721248e-02 7.19040155e-01 1.26104355e-01 -8.28520238e-01
5.69457114e-01 3.42598259e-01 -3.14649493e-01 -2.91423678e-01
-8.83863270e-01 -2.70277709e-01 -6.91713512e-01 1.19924702e-01
4.65407729e-01 -9.17971611e-01 -3.72947931e-01 6.56670213e-01
-7.81227827e-01 -6.51714921e-01 -8.23595345e-01 4.17053223e-01
-7.22841918e-01 1.21599823e-01 -3.24648440e-01 -4.88381416e-01
-1.01754209e-02 -1.18405056e+00 7.63893127e-01 2.33414054e-01
1.75802946e-01 -8.59675109e-01 1.54021429e-02 -8.03038329e-02
1.89148560e-01 4.36041094e-02 1.10187614e+00 -8.10041785e-01
-4.44106996e-01 2.88566500e-01 -3.25877964e-01 6.58213437e-01
2.67182291e-01 -2.37839401e-01 -9.93154347e-01 -3.87577772e-01
-1.00379199e-01 -3.97100002e-01 1.13886297e+00 5.15126348e-01
1.40079403e+00 -2.23241746e-02 -5.03167033e-01 4.79984015e-01
1.25120068e+00 3.94877374e-01 7.41613388e-01 4.87957716e-01
5.44825554e-01 5.57877779e-01 1.01732898e+00 5.25177538e-01
3.51059377e-01 6.00664079e-01 3.45251501e-01 -1.86264105e-02
-4.69327867e-01 -3.30254287e-01 6.56358838e-01 5.13944149e-01
4.16119099e-01 -7.06560165e-02 -5.79407454e-01 6.09827876e-01
-1.88550293e+00 -7.58505762e-01 2.96337575e-01 2.33410835e+00
1.10606575e+00 3.02764237e-01 3.77631545e-01 -1.49195231e-02
8.88447285e-01 1.53555302e-02 -1.06266916e+00 -1.28153369e-01
-1.42304480e-01 1.00169733e-01 3.43982071e-01 1.26341686e-01
-1.06192470e+00 7.88140833e-01 5.72138262e+00 1.23509192e+00
-1.06240165e+00 -7.91770592e-02 6.21646225e-01 1.77781016e-01
-2.80045211e-01 -3.75570416e-01 -1.11326885e+00 7.34103560e-01
4.96028066e-01 4.20776084e-02 3.34512204e-01 1.09796727e+00
-5.94309159e-03 -7.40544647e-02 -1.14696050e+00 7.04284251e-01
-1.26278132e-01 -9.65643108e-01 1.53720260e-01 -1.68218896e-01
7.88798273e-01 -1.47479743e-01 2.97879964e-01 6.73797607e-01
5.68230331e-01 -6.41498625e-01 4.83807743e-01 5.17188311e-01
7.45234489e-01 -9.12865341e-01 5.28264761e-01 3.95581484e-01
-9.66312826e-01 -4.18453783e-01 -7.10710466e-01 3.06945711e-01
-4.62281883e-01 7.72584915e-01 -8.88818860e-01 4.98814881e-01
7.76455522e-01 9.95674133e-01 -5.42001188e-01 1.06330729e+00
-3.08224410e-01 5.13180256e-01 -1.60962433e-01 1.07513063e-01
4.47647311e-02 -1.38801798e-01 4.40986305e-01 9.19433594e-01
5.59398890e-01 -2.92772114e-01 2.98691750e-01 9.57383692e-01
-1.53924435e-01 8.85917023e-02 -3.92645091e-01 4.24460292e-01
7.31150150e-01 1.11526334e+00 -5.96935093e-01 -3.11174303e-01
-2.67716527e-01 9.74408448e-01 5.37854075e-01 3.47768694e-01
-7.47899532e-01 -4.99942601e-01 6.39816821e-01 -9.65684769e-04
5.89202344e-01 3.29100251e-01 -4.17574257e-01 -9.93188918e-01
5.51100746e-02 -8.67505372e-01 7.03733921e-01 -5.08966804e-01
-1.85591280e+00 4.01784509e-01 -1.67318046e-01 -1.59392297e+00
1.06117234e-01 -6.45449817e-01 -4.99539286e-01 8.70004952e-01
-2.01877952e+00 -8.51420343e-01 -3.71651381e-01 9.90453601e-01
4.80410606e-01 -5.16222298e-01 5.71684241e-01 3.30501109e-01
-5.75617969e-01 7.96201348e-01 4.13094848e-01 -6.16423711e-02
1.20721960e+00 -1.30864191e+00 -7.76827708e-02 4.25773382e-01
-2.73436606e-01 2.07642689e-01 2.30126902e-01 -6.78806663e-01
-7.82436430e-01 -1.39419878e+00 3.18204671e-01 -1.30281717e-01
4.30574238e-01 -1.71099156e-01 -1.04341161e+00 4.04385448e-01
-1.08115390e-01 3.00852150e-01 5.21314859e-01 -1.02334656e-01
-3.05529356e-01 -7.18490958e-01 -1.57893026e+00 4.23852354e-01
1.00339770e+00 -1.29828900e-01 -5.67856669e-01 1.67472079e-01
7.12942958e-01 -2.58307785e-01 -7.97341406e-01 3.94283503e-01
1.44580111e-01 -8.53297949e-01 9.85669494e-01 -3.04912120e-01
4.38603491e-01 -5.75287163e-01 2.94131637e-02 -1.83890653e+00
-6.21710420e-01 -2.67743580e-02 -8.02209675e-02 1.36932945e+00
3.16428363e-01 -6.43086195e-01 8.45453084e-01 1.53641686e-01
-1.97356567e-01 -6.99352384e-01 -9.41803992e-01 -9.69675899e-01
2.86595941e-01 -5.87582178e-02 7.83031523e-01 8.94168794e-01
-1.62707344e-01 2.93297350e-01 -1.98625386e-01 1.86461791e-01
4.19158906e-01 1.73354939e-01 4.52928603e-01 -1.51709044e+00
-3.30788374e-01 -3.56056243e-01 -6.72904253e-02 -1.15759063e+00
1.55279264e-01 -1.00075614e+00 1.58775181e-01 -1.42713082e+00
2.25727763e-02 -9.48882163e-01 -9.20257449e-01 5.49814463e-01
-1.81596979e-01 -1.55931100e-01 1.24742121e-01 2.55237609e-01
-6.14645481e-01 8.82561088e-01 1.57067454e+00 -1.74421161e-01
-5.94690681e-01 1.12848707e-01 -7.65227437e-01 7.10923016e-01
8.39882493e-01 -5.99032760e-01 -5.79797566e-01 -2.06029207e-01
-9.56545472e-02 -2.04009697e-01 2.69749492e-01 -1.27900946e+00
1.54358298e-01 -3.51150095e-01 7.88787901e-01 -6.35895848e-01
1.60512969e-01 -1.11306548e+00 -4.07663256e-01 4.64744389e-01
-5.58133841e-01 -5.28041959e-01 8.76666456e-02 6.84669197e-01
-1.52091846e-01 -2.99822837e-01 1.12332129e+00 -1.14061043e-01
-9.67149675e-01 4.18320447e-01 -9.07169133e-02 8.89762565e-02
1.31973231e+00 -2.55490422e-01 -3.46625865e-01 6.42710328e-02
-6.36443377e-01 4.14702803e-01 3.10010791e-01 3.60303938e-01
6.04650259e-01 -1.69176948e+00 -5.73556244e-01 4.16138947e-01
3.57395589e-01 2.94456959e-01 1.51647910e-01 5.44193208e-01
3.44531983e-02 -5.92601672e-02 -6.46665335e-01 -5.47623456e-01
-7.31863618e-01 7.07168341e-01 2.15161145e-01 -4.22858953e-01
-3.75341028e-01 8.67826462e-01 3.67029518e-01 -7.38853872e-01
2.69964933e-01 -3.47994059e-01 -4.13541466e-01 2.10100815e-01
5.36004186e-01 3.90746981e-01 3.28395031e-02 -8.06946233e-02
-3.32641006e-01 3.81995618e-01 -2.90520787e-01 1.59790397e-01
1.34060478e+00 -1.87917799e-01 1.45323470e-01 4.64217275e-01
9.91839945e-01 -9.61309001e-02 -1.85055089e+00 -6.46253943e-01
-2.06164308e-02 -3.73159766e-01 -1.27867281e-01 -1.13917923e+00
-1.17738318e+00 8.92883182e-01 8.73985291e-01 -1.24145165e-01
1.42058289e+00 -1.64741695e-01 8.03273916e-01 2.67222881e-01
3.18737745e-01 -1.59776914e+00 4.89981204e-01 5.21274865e-01
8.50278974e-01 -1.29037726e+00 -1.89440653e-01 -3.56771737e-01
-1.01300108e+00 1.08319938e+00 1.14363194e+00 -4.40919906e-01
6.32039130e-01 1.95225906e-02 -1.17251143e-01 1.35789990e-01
-5.80717206e-01 -1.49155200e-01 1.86109617e-01 1.07285428e+00
1.33629255e-02 -1.14102893e-01 -1.26561239e-01 9.13507998e-01
2.82601237e-01 1.93251699e-01 1.46939412e-01 7.47033119e-01
-8.39331746e-01 -1.34866035e+00 -3.91176552e-01 5.67743540e-01
4.50964831e-02 1.27068460e-01 -2.18111262e-01 5.12542725e-01
5.66337705e-01 7.36689210e-01 1.15209863e-01 -3.72509688e-01
4.77456838e-01 6.15908280e-02 3.23552698e-01 -6.34037673e-01
-4.54274774e-01 -8.66952911e-02 -3.07341725e-01 -3.46710414e-01
-3.24188679e-01 -6.44383609e-01 -1.43049276e+00 4.52856123e-02
-1.89540952e-01 -7.12456182e-02 3.48729879e-01 7.60721505e-01
5.96419513e-01 7.46094763e-01 1.05957544e+00 -4.01735008e-01
-8.15556169e-01 -7.43249238e-01 -9.62124228e-01 3.91205877e-01
2.14267820e-01 -9.34400380e-01 -1.24557048e-01 -1.44208997e-01] | [10.286778450012207, 3.0299108028411865] |
13d5e609-f7f8-4fec-bf1e-db359c868228 | the-cocktail-fork-problem-three-stem-audio | 2110.09958 | null | https://arxiv.org/abs/2110.09958v2 | https://arxiv.org/pdf/2110.09958v2.pdf | The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks | The cocktail party problem aims at isolating any source of interest within a complex acoustic scene, and has long inspired audio source separation research. Recent efforts have mainly focused on separating speech from noise, speech from speech, musical instruments from each other, or sound events from each other. However, separating an audio mixture (e.g., movie soundtrack) into the three broad categories of speech, music, and sound effects (understood to include ambient noise and natural sound events) has been left largely unexplored, despite a wide range of potential applications. This paper formalizes this task as the cocktail fork problem, and presents the Divide and Remaster (DnR) dataset to foster research on this topic. DnR is built from three well-established audio datasets (LibriSpeech, FMA, FSD50k), taking care to reproduce conditions similar to professionally produced content in terms of source overlap and relative loudness, and made available at CD quality. We benchmark standard source separation algorithms on DnR, and further introduce a new multi-resolution model to better address the variety of acoustic characteristics of the three source types. Our best model produces SI-SDR improvements over the mixture of 11.0 dB for music, 11.2 dB for speech, and 10.8 dB for sound effects. | ['Jonathan Le Roux', 'Zhong-Qiu Wang', 'Gordon Wichern', 'Darius Petermann'] | 2021-10-19 | null | null | null | null | ['audio-source-separation'] | ['audio'] | [ 1.92281902e-01 -7.17459202e-01 1.80890530e-01 1.06262468e-01
-1.55793035e+00 -9.63144422e-01 3.79796654e-01 -3.80401425e-02
-1.27700344e-02 3.28321189e-01 6.72473907e-01 8.25295523e-02
-3.30133289e-01 -1.76227048e-01 -3.70452404e-01 -8.75165343e-01
-2.15475127e-01 -2.66607180e-02 2.23566175e-01 -2.26514369e-01
-1.89837918e-01 3.97181660e-01 -1.90433359e+00 3.67913216e-01
5.36714852e-01 1.00292099e+00 1.89037666e-01 1.03292847e+00
1.72169968e-01 6.64412796e-01 -1.02094436e+00 -2.05183085e-02
1.78630322e-01 -7.80677140e-01 -1.92828074e-01 -2.99490273e-01
5.15638888e-01 -6.73677679e-03 -2.95299917e-01 1.03551280e+00
1.12690008e+00 3.33146334e-01 4.78500366e-01 -1.09693432e+00
-1.56157210e-01 1.05803370e+00 -5.28477252e-01 4.28121299e-01
4.44740355e-01 -1.41007945e-01 1.11534131e+00 -8.27197433e-01
4.26809415e-02 1.31548059e+00 6.59736931e-01 2.89670169e-01
-1.35625076e+00 -1.11445284e+00 -3.41772050e-01 8.56576338e-02
-1.45216906e+00 -9.95581150e-01 1.07231009e+00 -3.79367113e-01
5.60949922e-01 6.52583659e-01 3.59773844e-01 1.46401238e+00
-3.01237106e-01 7.48693705e-01 1.07482779e+00 -4.96118993e-01
2.97039300e-01 1.30642727e-02 1.56048268e-01 -3.83813679e-01
-1.42230839e-01 2.93516278e-01 -1.02862430e+00 -4.79263872e-01
5.00967145e-01 -5.76883256e-01 -7.59522855e-01 2.37908468e-01
-9.74613070e-01 3.97122443e-01 -1.21570326e-01 4.28549469e-01
-3.89164574e-02 7.07553998e-02 1.81018800e-01 2.42008641e-01
3.35401982e-01 4.78976816e-01 -3.17961633e-01 -3.66079450e-01
-1.12323093e+00 4.68592227e-01 9.94661689e-01 8.13094258e-01
2.15568587e-01 5.92005670e-01 3.63289751e-02 1.58296347e+00
3.44438493e-01 8.29549551e-01 4.00599271e-01 -1.05304801e+00
3.25471431e-01 -4.29218560e-01 1.83397368e-01 -9.75588560e-01
-3.66434246e-01 -6.71398044e-01 -7.00002551e-01 1.56861350e-01
5.55037677e-01 -2.52520382e-01 -7.30985343e-01 1.80452657e+00
2.07558393e-01 4.55652565e-01 4.14554141e-02 9.84965622e-01
1.14216650e+00 8.39315772e-01 -2.66273528e-01 -2.49969304e-01
1.46445775e+00 -7.45676458e-01 -8.86960149e-01 -2.84794420e-01
-1.30641520e-01 -1.28632140e+00 7.83007205e-01 9.62280154e-01
-1.22487748e+00 -6.98404431e-01 -9.18358922e-01 1.94508255e-01
4.22678068e-02 -6.29922897e-02 1.54511109e-01 1.02111006e+00
-7.54036903e-01 4.02878404e-01 -4.40411001e-01 2.06451818e-01
2.13002861e-02 -1.14102721e-01 -8.73814821e-02 3.13915461e-02
-1.34186864e+00 3.11410427e-01 -2.21130759e-01 -8.08877125e-03
-1.15303576e+00 -1.11259604e+00 -7.07227349e-01 1.06356420e-01
4.08729970e-01 -1.16841525e-01 1.53211844e+00 -7.67302632e-01
-1.52623546e+00 4.48038250e-01 -1.60428539e-01 -2.93181628e-01
6.55957386e-02 -5.05863309e-01 -1.28348815e+00 1.45626917e-01
-1.14970148e-01 -1.19927770e-03 1.10268641e+00 -1.48094261e+00
-6.39568329e-01 -1.95663139e-01 -3.12950373e-01 2.03373149e-01
-8.05855021e-02 7.29514182e-01 -3.93840551e-01 -1.19047058e+00
2.22858980e-01 -8.72754455e-01 8.27084556e-02 -6.29824281e-01
-4.83400851e-01 3.67004722e-01 3.92411411e-01 -7.31353641e-01
1.26045215e+00 -2.67552519e+00 1.39365820e-02 7.73559213e-02
1.55003428e-01 5.28093129e-02 -2.25168049e-01 2.63611197e-01
-4.55891311e-01 -1.16784628e-02 -6.78152218e-02 -4.38820183e-01
8.70769843e-02 -1.89415172e-01 -6.56178653e-01 4.15728867e-01
-1.98896915e-01 2.01498792e-01 -8.46603036e-01 -2.26513788e-01
-1.97799608e-01 5.70963025e-01 -5.33989251e-01 1.87951162e-01
1.65236473e-01 4.88595843e-01 4.18514609e-02 7.82581449e-01
7.09952533e-01 5.86421669e-01 -2.94991583e-01 -1.76399887e-01
-2.27644816e-01 5.09093225e-01 -1.73224902e+00 1.57872736e+00
-3.57902497e-01 8.11764479e-01 9.52286422e-01 -2.03700081e-01
9.07276213e-01 7.87040174e-01 5.05749881e-01 -2.90734082e-01
1.40571684e-01 5.26697040e-01 4.16381449e-01 -3.44070286e-01
5.68465769e-01 -4.22729552e-01 -8.58011376e-03 2.51438111e-01
2.47175008e-01 -4.39143360e-01 9.31185633e-02 -1.78987544e-03
1.17349112e+00 -4.81202781e-01 -4.51306775e-02 -7.84957334e-02
1.31688967e-01 -4.84457016e-01 6.52761281e-01 7.86728203e-01
-4.31856900e-01 9.59384859e-01 1.00255996e-01 6.11711562e-01
-4.26391989e-01 -1.49651027e+00 -2.74411410e-01 1.48772502e+00
-7.51619115e-02 -5.64638913e-01 -5.24848282e-01 1.57366157e-01
-5.83995953e-02 7.37573087e-01 -9.56342816e-02 -1.60380572e-01
-6.10284328e-01 -6.20736122e-01 1.13355386e+00 2.74752557e-01
3.48384455e-02 -9.42365527e-01 -5.32245077e-02 2.00159103e-01
-5.46686828e-01 -9.82494831e-01 -7.28451133e-01 4.70262140e-01
-1.59240380e-01 -7.16695249e-01 -7.49025524e-01 -5.59764683e-01
-3.53237122e-01 4.91848707e-01 1.21537697e+00 -7.88058043e-01
-2.69700527e-01 5.56059539e-01 -5.66125512e-01 -8.22023869e-01
-7.06874192e-01 -4.51172173e-01 4.85814363e-01 3.00280273e-01
-8.16267263e-03 -9.68574703e-01 -3.05524081e-01 6.00352764e-01
-8.59988689e-01 -4.70329165e-01 2.69938350e-01 2.86883056e-01
4.01164591e-01 5.87859988e-01 8.58287930e-01 -2.98655748e-01
7.70146966e-01 -6.43700719e-01 -2.11526632e-01 -4.05635089e-01
1.58433780e-01 -6.45807803e-01 4.99482185e-01 -7.45468915e-01
-1.28684878e+00 -2.51485348e-01 -4.05261397e-01 -6.78262293e-01
-5.73180676e-01 2.27732435e-01 -7.12699175e-01 1.78180099e-01
7.87546635e-01 1.34551033e-01 -5.31507850e-01 -9.91299510e-01
2.81875968e-01 1.04618382e+00 1.05224812e+00 -6.26524508e-01
7.32053518e-01 2.94749528e-01 -3.64370823e-01 -1.29769051e+00
-6.11094415e-01 -7.77348936e-01 -1.61764547e-01 -9.76377949e-02
5.78462780e-01 -1.13193345e+00 -2.43902937e-01 6.90832019e-01
-9.07057583e-01 -1.39820918e-01 -4.70235020e-01 9.41019535e-01
-4.59474385e-01 1.45561337e-01 -6.13635778e-01 -1.20046723e+00
-6.08837716e-02 -1.01310563e+00 8.10222626e-01 5.45666926e-02
-5.65933704e-01 -4.32271689e-01 3.70902598e-01 2.81189084e-01
3.71919960e-01 -3.57420146e-02 5.40164351e-01 -7.19614685e-01
-1.59411639e-01 -7.63642415e-02 4.07705218e-01 5.57238340e-01
4.13785040e-01 -1.00399246e-02 -1.55342674e+00 -5.23127466e-02
5.50462544e-01 -1.54069632e-01 8.06891561e-01 6.87396109e-01
6.75948203e-01 3.54633629e-02 -1.26052946e-01 5.37903428e-01
8.01372349e-01 5.72464228e-01 4.89001095e-01 -1.79967254e-01
4.87307101e-01 5.67510664e-01 2.88967371e-01 4.47389990e-01
-1.72807053e-01 7.73782313e-01 2.13222310e-01 -6.06677122e-02
-5.61638057e-01 -8.11599866e-02 5.02237380e-01 1.06013393e+00
2.13946864e-01 -3.69344264e-01 -6.94708347e-01 7.00178683e-01
-1.17175579e+00 -1.11420298e+00 -3.33658665e-01 2.21524572e+00
1.08377016e+00 -2.95890048e-02 3.56170028e-01 7.52291918e-01
7.58463919e-01 3.33088577e-01 -2.99491704e-01 -2.26716086e-01
-5.08036196e-01 4.07532662e-01 1.95828557e-01 3.96482825e-01
-1.17864287e+00 3.37124228e-01 6.64972162e+00 1.25570130e+00
-9.16226268e-01 9.12791640e-02 7.24715218e-02 -6.52557850e-01
-2.02041656e-01 -3.87590051e-01 -7.22335100e-01 4.30779010e-01
1.20453179e+00 -2.10041180e-01 7.23774374e-01 4.73581970e-01
4.20333892e-01 -8.54131058e-02 -1.20739186e+00 1.32053876e+00
1.67669073e-01 -6.44713402e-01 -3.75121087e-01 -2.74182618e-01
4.98360187e-01 9.85903665e-02 3.16794246e-01 3.93387705e-01
2.58628249e-01 -9.81395543e-01 1.21379125e+00 1.70270726e-01
6.33754313e-01 -7.64285088e-01 1.16376214e-01 3.65248024e-01
-1.29104674e+00 -1.98303595e-01 1.27778590e-01 6.92552626e-02
1.44561887e-01 8.69507074e-01 -3.69985312e-01 5.67543447e-01
1.03925407e+00 4.40338522e-01 -8.52927566e-02 1.32060051e+00
-3.35282236e-02 1.25761127e+00 -5.29722095e-01 4.99023318e-01
-2.76125103e-01 9.05020833e-02 1.25006998e+00 1.44215214e+00
3.31134707e-01 7.00096115e-02 4.82915062e-03 7.98152506e-01
-5.69436140e-02 -1.90623645e-02 -2.71707356e-01 -4.15499024e-02
6.96576893e-01 1.17489207e+00 -5.74350238e-01 -2.39216182e-02
-1.75197989e-01 5.06372571e-01 -4.89781648e-01 5.52238941e-01
-1.02601969e+00 -5.96813977e-01 1.10285068e+00 2.37220954e-02
3.17126900e-01 -6.98378235e-02 -9.43864509e-02 -8.98084819e-01
-5.47094978e-02 -1.36749494e+00 1.44184098e-01 -8.28828752e-01
-1.30403244e+00 5.86267233e-01 -1.03668511e-01 -1.50366330e+00
-1.25425905e-01 -3.38214397e-01 -6.24454379e-01 1.12505758e+00
-1.06421876e+00 -4.67534453e-01 -1.03085348e-02 6.01068616e-01
6.35236382e-01 -3.77885386e-04 8.80415738e-01 8.39907825e-01
-5.20337880e-01 5.14919043e-01 4.21535879e-01 7.71481097e-02
1.03386283e+00 -1.22592783e+00 1.99845284e-01 7.35737979e-01
4.47464615e-01 5.28443098e-01 1.03351212e+00 -2.53032714e-01
-1.24832308e+00 -1.12676656e+00 4.01064754e-01 -5.41867733e-01
8.20529103e-01 -6.61781371e-01 -9.20509219e-01 2.72671670e-01
8.94045085e-02 -5.48857152e-02 1.05484712e+00 1.52557969e-01
-6.86765611e-01 -2.92894572e-01 -7.71200240e-01 6.31124794e-01
8.90378356e-01 -6.49503529e-01 -6.01477623e-01 -7.54900500e-02
7.63171434e-01 -3.65712076e-01 -6.53300226e-01 1.11673616e-01
5.27618945e-01 -1.07417178e+00 1.23248518e+00 -3.14570546e-01
2.75729805e-01 -4.68722761e-01 -5.32668948e-01 -1.73822343e+00
-3.78851891e-01 -1.13206172e+00 -1.07091457e-01 1.97637665e+00
2.59809017e-01 -3.15821797e-01 1.63228661e-01 2.62311906e-01
-3.01121294e-01 -3.55088562e-02 -8.88105750e-01 -1.17637062e+00
4.19638194e-02 -1.11793971e+00 5.04327536e-01 8.30569625e-01
-3.29479724e-02 5.08737206e-01 -5.17224312e-01 4.52754438e-01
6.36955559e-01 1.31491274e-01 7.22126067e-01 -1.14556170e+00
-7.71848977e-01 -6.81225479e-01 -1.79610793e-02 -1.02323341e+00
-1.07820839e-01 -7.13091493e-01 4.47962701e-01 -1.05937421e+00
-2.60609269e-01 -4.68901396e-01 -4.98639673e-01 8.35497677e-02
-1.69508457e-01 2.65163392e-01 3.06831986e-01 1.27432197e-01
-2.85619318e-01 4.39758658e-01 7.70415008e-01 -2.43568644e-01
-4.16231990e-01 4.79487360e-01 -9.36137855e-01 1.18523204e+00
6.29296064e-01 -6.66620851e-01 -3.86970907e-01 -2.63633221e-01
-6.30664155e-02 3.62773180e-01 2.45579883e-01 -1.26267827e+00
1.64947346e-01 3.66889052e-02 -1.63365565e-02 -4.92436409e-01
7.45475829e-01 -7.80877233e-01 4.67367709e-01 -2.20030606e-01
-5.94052374e-01 -7.36506641e-01 5.45488358e-01 6.28968954e-01
-4.06318784e-01 -1.65057510e-01 8.84914100e-01 9.75676924e-02
-1.61354959e-01 -1.79005221e-01 -6.37429535e-01 4.86386865e-01
3.94279987e-01 1.29877910e-01 -2.12661222e-01 -6.79031968e-01
-7.64830947e-01 -2.76783884e-01 -2.04173207e-01 6.32115781e-01
3.25318247e-01 -1.27145112e+00 -9.48230743e-01 1.13624029e-01
-4.84757796e-02 -2.61315823e-01 5.92567384e-01 6.37167692e-01
1.20526783e-01 1.32877082e-01 2.29655296e-01 -3.89828682e-01
-1.42882264e+00 3.85930330e-01 4.48140353e-01 1.87618688e-01
-4.00582403e-01 1.14287066e+00 5.37560403e-01 -3.97769250e-02
5.61786652e-01 -4.04555023e-01 -2.47337967e-01 2.05308348e-01
9.13443029e-01 9.21599746e-01 1.88847646e-01 -8.22183967e-01
-3.63810629e-01 3.59779119e-01 4.67569500e-01 -4.99551237e-01
1.04305208e+00 -1.40902311e-01 -6.03574738e-02 9.49516594e-01
1.27275336e+00 1.01409316e+00 -7.65435696e-01 -4.03383642e-01
-1.97630748e-01 -4.80264604e-01 1.87750638e-01 -9.79175866e-01
-8.49082172e-01 7.58590221e-01 4.94695723e-01 7.38789737e-01
1.39965296e+00 4.47855704e-02 7.39375412e-01 -6.30789697e-02
2.46069193e-01 -7.40816712e-01 1.19888894e-02 4.46474403e-01
1.15160334e+00 -7.51561761e-01 -3.69886547e-01 -3.77181560e-01
-3.30244988e-01 7.55305350e-01 1.38793543e-01 1.30302221e-01
8.79686952e-01 9.16933656e-01 3.50860834e-01 1.72004014e-01
-4.48636919e-01 -3.01366240e-01 4.43780124e-01 6.11325800e-01
4.28712666e-01 7.30161741e-02 4.63327497e-01 1.42153490e+00
-7.37961590e-01 -4.74989533e-01 4.19187516e-01 5.78521252e-01
-5.08706927e-01 -7.42481291e-01 -1.15440881e+00 2.22112089e-01
-9.15675104e-01 -3.47026646e-01 -4.32931602e-01 1.88085124e-01
1.40885636e-01 1.72271550e+00 -7.29474872e-02 -3.76666754e-01
7.17203915e-01 1.14099003e-01 2.09603325e-01 -5.26823282e-01
-6.39323175e-01 1.01405919e+00 2.19119132e-01 -2.35330120e-01
-2.31090546e-01 -7.55114079e-01 -9.20581102e-01 8.27717409e-03
-5.36972165e-01 3.37865263e-01 6.54837489e-01 4.71671820e-01
8.39163810e-02 1.07865775e+00 6.81810796e-01 -1.17357862e+00
-3.92385840e-01 -1.07905126e+00 -1.25087059e+00 1.92576021e-01
7.42160857e-01 -5.06847680e-01 -8.57165813e-01 2.58147389e-01] | [15.331538200378418, 5.532061576843262] |
3a63cf36-7553-4b10-b776-b5ceb08622dc | multi-modal-extreme-classification | null | null | http://openaccess.thecvf.com//content/CVPR2022/html/Mittal_Multi-Modal_Extreme_Classification_CVPR_2022_paper.html | http://openaccess.thecvf.com//content/CVPR2022/papers/Mittal_Multi-Modal_Extreme_Classification_CVPR_2022_paper.pdf | Multi-Modal Extreme Classification | This paper develops the MUFIN technique for extreme classification (XC) tasks with millions of labels where datapoints and labels are endowed with visual and textual descriptors. Applications of MUFIN to product-to-product recommendation and bid query prediction over several millions of products are presented. Contemporary multi-modal methods frequently rely on purely embedding-based methods. On the other hand, XC methods utilize classifier architectures to offer superior accuracies than embedding-only methods but mostly focus on text-based categorization tasks. MUFIN bridges this gap by reformulating multi-modal categorization as an XC problem with several millions of labels. This presents the twin challenges of developing multi-modal architectures that can offer embeddings sufficiently expressive to allow accurate categorization over millions of labels; and training and inference routines that scale logarithmically in the number of labels. MUFIN develops an architecture based on cross-modal attention and trains it in a modular fashion using pre-training and positive and negative mining. A novel product-to-product recommendation dataset MM-AmazonTitles-300K containing over 300K products was curated from publicly available amazon.com listings with each product endowed with a title and multiple images. On the MM-AmazonTitles-300K and Polyvore datasets, and a dataset with over 4 million labels curated from click logs of the Bing search engine, MUFIN offered at least 3% higher accuracy than leading text-based, image-based and multi-modal techniques. | ['Manik Varma', 'Purushottam Kar', 'Sumeet Agarwal', 'Keng-hao Chang', 'Jitendra Ajmera', 'Seba Kuruvilla', 'Janani Ramaswamy', 'Shreya Malani', 'Kunal Dahiya', 'Anshul Mittal'] | 2022-01-01 | null | null | null | cvpr-2022-1 | ['product-recommendation'] | ['miscellaneous'] | [-2.87495971e-01 -3.86017114e-01 -6.47531748e-01 -6.05169177e-01
-1.01994443e+00 -1.18806148e+00 8.41572225e-01 4.14476126e-01
-3.34660172e-01 -9.96359736e-02 -3.71039435e-02 -3.61282855e-01
-3.28830332e-01 -8.37082207e-01 -6.15948737e-01 -2.88695514e-01
-2.47140273e-01 8.47729921e-01 -3.84069026e-01 -1.88803166e-01
2.28880093e-01 3.13967764e-01 -1.83454514e+00 8.23826611e-01
2.01710805e-01 2.08851433e+00 -2.77325243e-01 6.83578312e-01
-3.10136855e-01 4.64060575e-01 -1.55420452e-01 -9.68603253e-01
7.68692970e-01 4.58116293e-01 -5.52859128e-01 1.50325850e-01
1.14231503e+00 -2.00986415e-01 -9.04677361e-02 7.44085133e-01
4.12658334e-01 -4.38257903e-02 1.04051805e+00 -1.59403670e+00
-1.61584163e+00 3.70432138e-01 -8.49593878e-01 2.21030831e-01
3.04572165e-01 1.20512389e-01 1.76270115e+00 -1.46728516e+00
5.18515289e-01 1.27432215e+00 8.09791386e-01 2.46933758e-01
-1.71816051e+00 -4.32030499e-01 3.60992402e-02 2.33880073e-01
-1.36716270e+00 -1.81398969e-02 4.12140369e-01 -9.21724677e-01
1.22616744e+00 3.69713247e-01 6.05347991e-01 1.07845962e+00
5.29236495e-02 8.65987241e-01 1.04347456e+00 -2.98644751e-01
-1.05293375e-02 8.95115852e-01 4.88176882e-01 5.08468330e-01
-3.59932780e-02 1.63948074e-01 -6.42389417e-01 -2.84368724e-01
3.00061792e-01 3.95584881e-01 3.26957971e-01 -5.60652852e-01
-1.22492945e+00 1.43732429e+00 5.86031735e-01 1.82171360e-01
-3.01984400e-01 2.68781543e-01 9.79419649e-01 5.65932155e-01
8.58036757e-01 7.04904556e-01 -6.65880263e-01 2.48291790e-01
-9.15816724e-01 2.93382138e-01 6.48444891e-01 1.07882738e+00
9.23861682e-01 -1.61641359e-01 -1.10089801e-01 9.23461914e-01
3.02904606e-01 3.64422381e-01 7.82427549e-01 -7.74122715e-01
3.93278271e-01 7.06975520e-01 1.70392066e-01 -1.19863951e+00
-2.39671350e-01 -3.89021069e-01 -5.42511582e-01 3.64317477e-01
1.33558422e-01 4.26016778e-01 -7.52641797e-01 1.21977055e+00
2.73474604e-01 -3.97829384e-01 -2.18853623e-01 8.12512457e-01
8.10646713e-01 5.98379910e-01 1.02612168e-01 3.71147901e-01
1.77017415e+00 -1.29849029e+00 -3.70068431e-01 -6.50591403e-02
1.04520500e+00 -7.42019534e-01 1.69153392e+00 6.79950595e-01
-8.23146820e-01 -8.13159466e-01 -1.18365514e+00 -3.82040888e-01
-1.39462554e+00 1.47141933e-01 1.02323329e+00 6.52063370e-01
-1.05901504e+00 5.85926592e-01 -1.06898837e-01 -8.12894478e-02
5.59397459e-01 3.57412487e-01 -5.35883248e-01 -2.73948997e-01
-1.14081681e+00 9.65880215e-01 2.72597790e-01 -1.92625239e-01
-7.52966106e-01 -1.04534125e+00 -9.92086411e-01 4.16756906e-02
1.78181887e-01 -3.71267915e-01 1.16134620e+00 -1.10425854e+00
-9.38569367e-01 1.09615970e+00 2.62872607e-01 -4.87413883e-01
2.69584209e-01 -2.04434454e-01 -8.00665617e-01 3.18046808e-02
3.27178031e-01 9.22823846e-01 9.65248585e-01 -9.56900656e-01
-7.73017287e-01 -6.42634690e-01 2.16763034e-01 -1.09082513e-01
-8.54911447e-01 -1.15862802e-01 -2.69599825e-01 -4.56374705e-01
-1.99405581e-01 -8.15886378e-01 1.54519588e-01 1.29329532e-01
-2.77822226e-01 -8.73063087e-01 8.48109961e-01 -2.23125353e-01
9.90642190e-01 -2.37370944e+00 -1.02616727e-01 -3.75574715e-02
5.53241730e-01 -1.72841832e-01 -4.68730271e-01 5.02350807e-01
-2.48338550e-01 1.69657186e-01 7.31746256e-01 -6.06386125e-01
8.17863286e-01 -9.81333330e-02 -5.17562687e-01 5.60512185e-01
1.58320829e-01 1.49988186e+00 -5.45644403e-01 -5.42730987e-01
4.06255454e-01 3.97228450e-01 -5.26791811e-01 -3.59770395e-02
-4.60989714e-01 -5.19729614e-01 -8.42333511e-02 1.14683831e+00
5.98432600e-01 -6.69087112e-01 -4.57526594e-01 -5.28907418e-01
-9.24578384e-02 -1.07967339e-01 -8.95750821e-01 1.59474695e+00
-8.30363274e-01 5.57396293e-01 -1.98909730e-01 -8.47531378e-01
4.28877115e-01 2.21632477e-02 6.02524400e-01 -7.30906487e-01
1.75831169e-01 2.40731761e-01 -5.32911420e-01 -2.93263853e-01
7.66647995e-01 -2.15294510e-01 -4.43360060e-01 6.10778451e-01
4.02456731e-01 8.01697299e-02 2.78568655e-01 3.72620970e-01
7.87457883e-01 -1.45991907e-01 -2.61569381e-01 -1.50601909e-01
1.44246191e-01 2.82016546e-01 -1.03689820e-01 5.76532841e-01
1.42212287e-02 3.55274469e-01 4.07514572e-01 -9.49266076e-01
-1.28706229e+00 -1.05635166e+00 -6.38161719e-01 1.97071886e+00
-8.77999216e-02 -7.36607313e-01 -1.38651952e-01 -8.21246207e-01
8.49819183e-01 6.66034818e-01 -1.23310006e+00 1.25869038e-02
2.82680541e-01 -5.40281355e-01 3.11831057e-01 5.40002763e-01
5.20944931e-02 -8.97636354e-01 -1.50360286e-01 9.59139392e-02
3.97235155e-01 -8.51681352e-01 -6.57980859e-01 4.17700022e-01
-4.38639730e-01 -7.63456821e-01 -8.69290829e-01 -8.01471114e-01
2.22108290e-01 1.52452976e-01 1.43175268e+00 -5.21226406e-01
-6.56773269e-01 6.31535947e-01 -2.90870786e-01 -3.42468619e-01
5.21032885e-02 2.37843722e-01 2.34346822e-01 2.49048173e-01
9.66519296e-01 -3.25210005e-01 -7.36963928e-01 3.00001144e-01
-8.79756153e-01 -3.06037545e-01 6.29895031e-01 9.13661718e-01
6.82786465e-01 -1.80666730e-01 5.86761236e-01 -1.04038477e+00
5.19199491e-01 -7.61279523e-01 -6.03356481e-01 2.66939759e-01
-1.15060472e+00 -2.16022998e-01 6.30701780e-01 -8.46624196e-01
-3.83799434e-01 7.95780346e-02 1.20562896e-01 -8.99622679e-01
-3.80549463e-03 5.32732069e-01 2.37968445e-01 -9.00976211e-02
8.30286205e-01 1.12551019e-01 -2.00414419e-01 -6.34907782e-01
1.17454886e+00 9.47596133e-01 3.58874381e-01 -2.08809316e-01
4.69195515e-01 3.60106170e-01 -3.31516802e-01 -4.01852101e-01
-1.08113694e+00 -9.04832602e-01 -6.83143020e-01 -4.12386023e-02
7.95376420e-01 -9.99510050e-01 -1.18796563e+00 8.67029205e-02
-5.67660272e-01 -6.92156851e-02 -5.07435620e-01 2.42170066e-01
-5.46337306e-01 8.95669833e-02 -9.99690771e-01 -5.36604702e-01
-4.04961050e-01 -7.71855474e-01 1.40462530e+00 -2.45474011e-01
-8.22951272e-02 -1.03612947e+00 1.48812933e-02 4.51833248e-01
6.03749752e-01 -4.90522496e-02 1.12194681e+00 -9.08301830e-01
-3.24923187e-01 -7.10215092e-01 -5.48964918e-01 3.19118619e-01
-2.26750791e-01 -3.26661527e-01 -1.16230476e+00 -4.56409544e-01
-3.61596763e-01 -1.13635159e+00 1.00116682e+00 1.70794219e-01
1.18727636e+00 -3.39476019e-01 -2.60731608e-01 5.08336186e-01
1.66938603e+00 -3.11792374e-01 8.90567601e-02 3.96424800e-01
7.72547781e-01 6.73564672e-01 6.98296607e-01 4.76011217e-01
3.81118387e-01 8.87956083e-01 6.29647434e-01 -9.21730101e-02
1.26105919e-01 -2.85636634e-01 2.41741106e-01 4.81643617e-01
6.26302421e-01 -8.78931060e-02 -5.47580302e-01 6.54779792e-01
-1.51725447e+00 -8.95164311e-01 1.35884285e-01 1.97348666e+00
6.62924290e-01 1.25800490e-01 3.35440964e-01 -5.91301434e-02
3.61032665e-01 1.62044033e-01 -9.80809867e-01 -6.57718778e-01
-2.24758387e-01 -1.21844806e-01 6.18734479e-01 1.83206066e-01
-1.46786332e+00 7.45267928e-01 6.11264181e+00 1.12600589e+00
-1.11368132e+00 4.92495596e-01 8.29266727e-01 -5.16928494e-01
-4.93849874e-01 -5.17578304e-01 -1.01423609e+00 3.83982927e-01
1.26218939e+00 -2.58377045e-02 4.02474850e-01 1.41211820e+00
-5.26158690e-01 1.43563017e-01 -1.51114762e+00 1.36832142e+00
3.32688570e-01 -1.58217537e+00 7.93379825e-03 5.00623524e-01
6.55374527e-01 3.45769614e-01 8.80780816e-01 7.23210454e-01
4.77220505e-01 -1.19999373e+00 9.17422056e-01 1.41284347e-01
1.27740288e+00 -5.99248111e-01 5.97578943e-01 3.53196599e-02
-1.19799042e+00 -4.90622163e-01 -4.94731456e-01 2.56734222e-01
1.32817253e-01 4.73800302e-01 -4.32459056e-01 1.70709372e-01
9.30828989e-01 1.14535403e+00 -8.51006210e-01 4.91416037e-01
6.08796179e-01 1.17552541e-01 -2.91851580e-01 -5.58994077e-02
5.41419804e-01 -1.86979800e-01 -2.92698085e-01 1.33162737e+00
1.77270725e-01 -3.53690177e-01 3.14295232e-01 7.91439533e-01
-2.01234221e-01 4.07506138e-01 -8.45697284e-01 -4.13705528e-01
7.46373832e-02 1.70868647e+00 -4.52996403e-01 -4.92886871e-01
-8.65663230e-01 1.07410622e+00 5.78406751e-01 1.89540043e-01
-8.16170633e-01 -2.68481851e-01 5.69582283e-01 2.90671557e-01
4.96373296e-01 6.78438321e-02 -1.76893353e-01 -1.14412975e+00
-5.67942522e-02 -5.96908867e-01 6.11743093e-01 -8.20330679e-01
-2.11862588e+00 7.65633643e-01 -1.70467272e-01 -1.13532388e+00
-2.74750382e-01 -1.08725250e+00 2.52044976e-01 9.08787727e-01
-1.37400830e+00 -1.74748695e+00 1.85961686e-02 4.75975394e-01
5.25858998e-01 -3.37205321e-01 1.07017446e+00 7.32904971e-01
-2.57573247e-01 8.10350776e-01 4.07913804e-01 3.31483968e-02
7.14458764e-01 -1.60810328e+00 2.53311545e-01 -1.99982315e-01
6.88559234e-01 5.34738660e-01 3.32533270e-01 -1.28091082e-01
-1.52276373e+00 -1.04443645e+00 8.32453489e-01 -9.88132834e-01
1.18239069e+00 -7.99654365e-01 -4.42573637e-01 9.61727142e-01
2.63887078e-01 4.78925645e-01 1.08003807e+00 5.19042969e-01
-1.06161869e+00 -1.88092023e-01 -9.92964268e-01 1.84554577e-01
6.75744116e-01 -9.87744987e-01 -3.54945511e-01 9.43674088e-01
8.36827099e-01 3.66510451e-02 -1.28153026e+00 -1.65496003e-02
7.37782478e-01 -7.42862344e-01 1.20728445e+00 -9.39868510e-01
5.69225609e-01 3.45016606e-02 -5.94667614e-01 -1.16097760e+00
-5.50172448e-01 1.17358185e-01 -1.26780108e-01 1.15338743e+00
7.14669585e-01 -5.99643648e-01 7.56792784e-01 5.54399848e-01
1.13542806e-02 -1.05993485e+00 -7.32989490e-01 -7.68479347e-01
1.96000338e-01 -6.82295799e-01 5.14679849e-01 9.24077868e-01
5.94499148e-03 5.62230766e-01 -2.73194909e-01 -2.67805696e-01
5.28899968e-01 5.97402155e-01 5.54742694e-01 -1.26435697e+00
-5.09497583e-01 -4.43774879e-01 -6.01633489e-01 -9.90372419e-01
2.98373997e-01 -1.17283452e+00 -5.08340359e-01 -1.11156869e+00
3.52651745e-01 -6.68513656e-01 -4.96123433e-01 6.25457466e-01
5.74371755e-01 1.00572252e+00 1.61954269e-01 3.28747183e-01
-9.31855500e-01 3.30493212e-01 7.17318892e-01 -6.14583671e-01
1.82702258e-01 -8.91460478e-02 -6.94638669e-01 3.07998359e-01
3.20111692e-01 -2.05549255e-01 -3.08585823e-01 -2.65108377e-01
8.00143838e-01 -3.75958830e-01 3.91797394e-01 -5.10727942e-01
-3.27743776e-02 3.15729976e-01 6.33215010e-01 -8.86287332e-01
7.61570930e-01 -9.61448431e-01 -2.38549476e-03 1.05324946e-01
-7.93213904e-01 3.80424589e-01 8.84319991e-02 7.77937710e-01
-2.95234263e-01 -1.12364992e-01 4.11541998e-01 -1.70385212e-01
-9.01956379e-01 4.54600781e-01 1.34284850e-02 -1.54036522e-01
1.20476365e+00 -1.38206765e-01 -4.44288701e-01 -2.97034293e-01
-1.05585623e+00 2.70337224e-01 2.56277442e-01 7.87744403e-01
2.60072261e-01 -1.71536613e+00 -4.91063595e-01 2.67961472e-01
8.17289472e-01 -7.35967219e-01 2.47667432e-01 5.90115905e-01
-2.53991485e-01 9.43452179e-01 -5.66821136e-02 -6.71635032e-01
-1.02414107e+00 1.34993339e+00 1.35615617e-01 -2.87140101e-01
-2.93536484e-01 1.01455021e+00 2.21825689e-01 -5.44199288e-01
2.60264903e-01 -1.59489304e-01 -1.29913375e-01 7.90059924e-01
7.63192534e-01 1.66260466e-01 2.55536854e-01 -8.73183668e-01
-1.84308812e-01 6.89587533e-01 -3.52430642e-01 -2.04298750e-01
1.26147735e+00 -1.78732917e-01 8.07509795e-02 8.76149476e-01
1.84970462e+00 -3.24315757e-01 -1.01343453e+00 -3.16278011e-01
5.07615581e-02 -5.56330800e-01 2.22557276e-01 -1.07083607e+00
-1.08919930e+00 1.05550897e+00 8.81712317e-01 7.49688923e-01
6.70754969e-01 4.79170769e-01 7.03965604e-01 1.27157539e-01
4.53119040e-01 -9.79265273e-01 4.84884977e-01 1.71941463e-02
8.07421148e-01 -1.70750022e+00 -1.08257487e-01 -3.88271622e-02
-7.46331453e-01 8.23034704e-01 5.46794474e-01 -6.07012287e-02
9.33724523e-01 -1.74737461e-02 1.26163036e-01 -6.72037780e-01
-9.36797261e-01 -3.19204703e-02 7.01134801e-01 3.73083234e-01
2.44217068e-01 1.44657269e-01 1.97658941e-01 6.82616234e-01
-1.79383516e-01 -1.57528818e-01 -1.37154669e-01 4.59553719e-01
-2.04521149e-01 -1.00152886e+00 -7.15296119e-02 9.65555429e-01
-5.03238559e-01 -2.94009417e-01 -1.11938059e-01 6.64972663e-01
2.99215704e-01 8.19183946e-01 3.16103369e-01 -5.80687642e-01
2.50581294e-01 2.51758903e-01 1.72528535e-01 -7.31807768e-01
-8.28476250e-01 -2.77860630e-02 -6.86271563e-02 -7.42325544e-01
2.01269332e-02 -5.59391916e-01 -5.37330389e-01 -5.46499133e-01
-5.99486053e-01 1.03663750e-01 8.30208421e-01 3.55200678e-01
7.25512743e-01 -3.63525725e-03 6.59125388e-01 -1.10886788e+00
-9.12133753e-01 -1.01619947e+00 -1.20337975e+00 7.52082646e-01
3.57995212e-01 -7.40616381e-01 -6.78874254e-01 -7.43683428e-02] | [9.603663444519043, 4.404982089996338] |
f4e06115-d2f0-4346-8fb7-6c99c238c7d2 | learning-backward-compatible-embeddings | 2206.03040 | null | https://arxiv.org/abs/2206.03040v1 | https://arxiv.org/pdf/2206.03040v1.pdf | Learning Backward Compatible Embeddings | Embeddings, low-dimensional vector representation of objects, are fundamental in building modern machine learning systems. In industrial settings, there is usually an embedding team that trains an embedding model to solve intended tasks (e.g., product recommendation). The produced embeddings are then widely consumed by consumer teams to solve their unintended tasks (e.g., fraud detection). However, as the embedding model gets updated and retrained to improve performance on the intended task, the newly-generated embeddings are no longer compatible with the existing consumer models. This means that historical versions of the embeddings can never be retired or all consumer teams have to retrain their models to make them compatible with the latest version of the embeddings, both of which are extremely costly in practice. Here we study the problem of embedding version updates and their backward compatibility. We formalize the problem where the goal is for the embedding team to keep updating the embedding version, while the consumer teams do not have to retrain their models. We develop a solution based on learning backward compatible embeddings, which allows the embedding model version to be updated frequently, while also allowing the latest version of the embedding to be quickly transformed into any backward compatible historical version of it, so that consumer teams do not have to retrain their models. Under our framework, we explore six methods and systematically evaluate them on a real-world recommender system application. We show that the best method, which we call BC-Aligner, maintains backward compatibility with existing unintended tasks even after multiple model version updates. Simultaneously, BC-Aligner achieves the intended task performance similar to the embedding model that is solely optimized for the intended task. | ['Jure Leskovec', 'Karthik Subbian', 'Nikhil Rao', 'Kaidi Cao', 'Rajas Bansal', 'Weihua Hu'] | 2022-06-07 | null | null | null | null | ['product-recommendation'] | ['miscellaneous'] | [-1.14844143e-01 -8.48359987e-03 -1.07253663e-01 -1.20368846e-01
-1.11703783e-01 -7.03278899e-01 2.45003492e-01 2.24136710e-01
-5.18981874e-01 3.14981312e-01 -1.65492192e-01 -3.29521120e-01
-3.47032070e-01 -7.43575752e-01 -7.75766909e-01 -6.88102722e-01
5.42624667e-02 6.15460396e-01 6.52045384e-02 -4.24100369e-01
1.86171621e-01 1.50237203e-01 -1.60597587e+00 7.37036467e-02
7.91096568e-01 7.13378787e-01 5.25157928e-01 6.95365429e-01
-3.81907709e-02 2.20254675e-01 -4.19529408e-01 -6.98542655e-01
5.94514489e-01 1.02609200e-02 -5.14180005e-01 1.32309616e-01
1.15453221e-01 -4.96135443e-01 -2.91765273e-01 1.14330995e+00
1.42612144e-01 3.42690617e-01 4.37377781e-01 -1.66385794e+00
-1.23109531e+00 6.22971952e-01 -2.74209559e-01 -9.37277973e-02
-5.54575734e-02 -1.14803687e-01 1.27051270e+00 -9.48535025e-01
5.79705715e-01 5.26880562e-01 7.34629750e-01 5.54736137e-01
-1.40570545e+00 -5.92097759e-01 6.44061565e-01 2.53957242e-01
-9.67031837e-01 -1.02176704e-01 6.61392093e-01 -5.70611954e-01
1.05155504e+00 3.82003278e-01 7.29792714e-01 1.03385901e+00
3.89480323e-01 4.98555243e-01 3.97810131e-01 -1.98215529e-01
3.76732320e-01 7.67092228e-01 4.63780254e-01 3.34320158e-01
6.44644797e-01 -7.18527660e-02 -3.95290732e-01 -3.75931770e-01
4.58870202e-01 5.58259428e-01 -3.24372143e-01 -7.70237803e-01
-1.19125259e+00 9.73965883e-01 3.46673131e-01 3.24233651e-01
-5.88326156e-01 1.80385038e-01 3.71105999e-01 8.25768411e-01
4.56209540e-01 9.17877376e-01 -9.25246119e-01 -1.54750701e-02
-4.22008157e-01 2.99144715e-01 7.85996318e-01 9.93307769e-01
8.83129418e-01 -3.41444194e-01 3.26865375e-01 8.74226511e-01
3.09702158e-01 6.82514757e-02 8.13649654e-01 -7.72482216e-01
3.95705074e-01 6.28365219e-01 3.74702185e-01 -9.89300311e-01
-7.63969719e-02 -4.86521721e-01 -7.00928569e-01 -3.58560011e-02
1.80240244e-01 -1.22165114e-01 -5.28830051e-01 1.73296082e+00
3.57217550e-01 4.78799641e-01 9.64083523e-03 6.86234355e-01
6.58592582e-02 7.26232231e-01 -3.48597080e-01 -2.01372370e-01
1.22274315e+00 -1.12932420e+00 -5.96402705e-01 -2.45702446e-01
1.06009471e+00 -7.24561214e-01 1.00917637e+00 7.51437783e-01
-6.37627900e-01 -7.65140891e-01 -1.29540122e+00 3.79509851e-02
-4.17185634e-01 -5.13030067e-02 5.56323826e-01 3.68363053e-01
-8.86023581e-01 1.05188584e+00 -6.34520948e-01 -1.89648598e-01
-1.36353761e-01 4.88179892e-01 -5.18149853e-01 -1.99749902e-01
-1.22139168e+00 8.10916007e-01 2.80825466e-01 2.88969219e-01
-6.29562497e-01 -8.30825925e-01 -7.36331940e-01 4.85135838e-02
3.34166020e-01 -8.61513674e-01 1.35855770e+00 -1.02092385e+00
-1.27285242e+00 2.66942263e-01 1.75452083e-01 -2.82669455e-01
4.37983364e-01 -3.56435031e-01 -5.93415260e-01 -5.45543432e-01
7.81839490e-02 9.77333188e-02 1.11307406e+00 -9.65945005e-01
-9.11964595e-01 -2.88735479e-01 2.46827245e-01 1.15061350e-01
-1.12635183e+00 -4.38873231e-01 -5.18930256e-01 -5.54643095e-01
9.05404314e-02 -1.38672531e+00 -3.62961859e-01 2.03320771e-01
-3.90435122e-02 -3.95018250e-01 7.67295122e-01 -4.45994049e-01
1.38566387e+00 -2.36591840e+00 4.98821944e-01 1.09529451e-01
4.24780339e-01 2.60756344e-01 -3.76662225e-01 4.63111877e-01
-2.44080365e-01 4.04150486e-02 3.95830348e-02 -7.27796078e-01
1.86795875e-01 5.73085964e-01 -3.62422794e-01 3.91355157e-01
-6.83330074e-02 6.47787571e-01 -1.05356812e+00 2.63635218e-01
5.17864749e-02 2.84787506e-01 -8.96650434e-01 2.87452459e-01
-1.24069236e-01 -2.11823016e-01 -3.14638913e-01 -2.61039697e-02
6.54934943e-01 -2.80755669e-01 3.16734374e-01 -2.75631756e-01
4.62916261e-03 2.07340837e-01 -1.56897640e+00 1.61039639e+00
-8.30835640e-01 3.75752747e-01 -7.89129362e-02 -1.15867305e+00
7.51795650e-01 2.32432678e-01 5.93682647e-01 -3.80181223e-01
-2.82319814e-01 2.45796517e-01 7.30226710e-02 -3.82405967e-01
6.97970867e-01 -3.58476117e-02 -2.16232330e-01 8.92236054e-01
-2.76747681e-02 2.47848645e-01 -4.50330712e-02 2.17963085e-01
1.20280743e+00 -1.70128524e-01 -9.19090398e-03 2.76177842e-03
2.76118994e-01 -1.35895848e-01 7.21051097e-01 6.13179207e-01
4.56099696e-02 2.95966417e-01 3.71472269e-01 -6.97559476e-01
-1.27730048e+00 -9.48935986e-01 4.13719658e-03 1.23744786e+00
1.95691973e-01 -7.51713395e-01 -3.44562024e-01 -1.12590194e+00
4.49287593e-01 6.89526260e-01 -8.89760494e-01 -7.28345811e-01
-4.44289148e-01 -4.39351261e-01 -1.23840153e-01 5.30635774e-01
1.18041318e-03 -7.16381729e-01 -4.03686434e-01 7.01354444e-01
2.28177980e-01 -4.59202617e-01 -9.31917071e-01 3.40061903e-01
-7.73986995e-01 -1.00855017e+00 -6.16618574e-01 -6.66301668e-01
8.22362185e-01 4.74452972e-01 8.21911752e-01 2.42302716e-01
8.85046795e-02 2.29070306e-01 -3.62363189e-01 -1.08487606e-01
-2.99809217e-01 1.61721230e-01 5.87516785e-01 1.83108926e-01
3.24460417e-01 -4.53273863e-01 -4.74229306e-01 5.55697680e-01
-1.02970719e+00 -6.81928098e-02 3.31373215e-01 1.14536500e+00
4.78464067e-01 3.31513852e-01 7.41307557e-01 -1.15037990e+00
7.34667957e-01 -6.53337598e-01 -5.47996044e-01 1.99686408e-01
-1.06992292e+00 2.23196104e-01 8.28256428e-01 -1.09006631e+00
-6.04042590e-01 -7.18277842e-02 -2.69542933e-02 -7.14965641e-01
5.56304634e-01 4.94818360e-01 -5.58290780e-02 3.94677311e-01
5.32125831e-01 3.61295417e-02 -1.53967487e-02 -8.02374542e-01
4.78742748e-01 9.12730277e-01 2.92981297e-01 -2.94291437e-01
9.31815207e-01 5.13569675e-02 -6.23283803e-01 -4.70780700e-01
-6.69279158e-01 -5.14801025e-01 -5.07317781e-01 1.63004711e-01
4.63720948e-01 -6.91769540e-01 -5.83441675e-01 3.07131708e-01
-1.16371465e+00 -1.91075623e-01 -5.10430753e-01 5.39300025e-01
-3.59480262e-01 3.36748838e-01 -5.19961476e-01 -4.09898400e-01
-1.69906303e-01 -1.18284535e+00 8.66969407e-01 -6.68089613e-02
-3.75788957e-01 -1.10522950e+00 3.08713377e-01 -6.97764605e-02
3.29575360e-01 -1.82278559e-01 1.11182785e+00 -8.80399585e-01
-1.07821807e-01 -3.92732799e-01 2.05738619e-01 8.07686329e-01
3.12997997e-01 -3.43694799e-02 -5.82867324e-01 -5.36441267e-01
1.87130406e-01 3.05514097e-01 6.08746409e-01 -4.14080285e-02
1.02158463e+00 -5.00927091e-01 -5.30304551e-01 4.94937629e-01
1.09262562e+00 2.11478069e-01 3.02311778e-01 5.07223964e-01
6.76283240e-01 4.87242937e-01 7.14589536e-01 3.55249465e-01
2.59881437e-01 8.41105878e-01 2.75023103e-01 2.54923970e-01
3.15951258e-01 -4.04467523e-01 5.53980350e-01 1.22627187e+00
2.15694249e-01 -8.95468071e-02 -3.69720310e-01 5.56797683e-01
-2.27000642e+00 -6.28874481e-01 -9.83839482e-02 2.46510434e+00
6.54777884e-01 3.45229656e-01 3.22160055e-03 9.52926502e-02
5.84072769e-01 -2.15211183e-01 -8.70726287e-01 -8.24414730e-01
5.60638487e-01 -8.03919323e-03 3.39012563e-01 3.16173255e-01
-8.82306755e-01 4.27068770e-01 5.69170713e+00 3.34580898e-01
-8.01608205e-01 4.81609702e-01 9.12421122e-02 -2.69596905e-01
-5.60821891e-01 1.85626000e-01 -8.05514753e-01 7.85877764e-01
1.04805326e+00 -6.07412219e-01 5.56673229e-01 1.31251943e+00
-1.77001655e-01 2.96260834e-01 -1.80563605e+00 9.31672394e-01
5.13042398e-02 -1.34182358e+00 -5.44990078e-02 3.80135238e-01
7.42508769e-01 -4.00639996e-02 1.87614650e-01 7.83980846e-01
4.58088547e-01 -5.07753789e-01 6.12376809e-01 4.19250995e-01
4.54165697e-01 -8.80722165e-01 8.76177669e-01 4.89498675e-01
-1.12516606e+00 -4.48210299e-01 -7.58284390e-01 5.37756458e-03
1.31343499e-01 7.41477728e-01 -5.93848705e-01 5.22410512e-01
6.89802468e-01 1.00596714e+00 -3.61569762e-01 7.78389335e-01
4.00661789e-02 1.24875844e-01 -1.81622878e-01 1.54737979e-01
6.61194101e-02 -4.61110264e-01 3.88244271e-01 5.99200904e-01
6.59774065e-01 -1.91116467e-01 1.64322555e-01 7.23827541e-01
-1.66176587e-01 7.81302974e-02 -8.85749638e-01 -9.91635099e-02
5.60132682e-01 1.20766973e+00 -1.12091519e-01 -3.93259913e-01
-4.52040076e-01 1.33219624e+00 5.64686358e-01 1.85270518e-01
-9.79995728e-01 -5.05151451e-01 1.40350318e+00 1.54557452e-01
4.71087784e-01 -1.43214002e-01 5.74881509e-02 -1.24021673e+00
2.50859320e-01 -7.78074265e-01 3.48292947e-01 -5.33764720e-01
-1.68542612e+00 5.78207791e-01 -2.88473338e-01 -1.33689106e+00
-2.66924769e-01 -5.94995618e-01 -5.41851282e-01 7.23850429e-01
-1.25541389e+00 -6.84201539e-01 3.22912857e-02 3.88820559e-01
5.89203596e-01 -2.30184287e-01 8.88923824e-01 5.06078124e-01
-8.55191529e-01 6.77107394e-01 4.38424289e-01 -2.30251625e-01
7.72121251e-01 -1.13208246e+00 3.57141256e-01 6.59825385e-01
3.40109766e-01 9.02840555e-01 7.10345924e-01 -5.80330670e-01
-1.62953949e+00 -1.34820724e+00 9.19530571e-01 -6.01561666e-01
9.39463377e-01 -6.49537683e-01 -1.05047548e+00 1.01636505e+00
-3.00154090e-01 6.61147982e-02 6.45065606e-01 4.04784352e-01
-4.60072368e-01 -3.81325662e-01 -9.15045440e-01 4.93021697e-01
9.14023459e-01 -4.52468455e-01 -6.27154052e-01 5.63838243e-01
9.79451656e-01 1.23206805e-02 -9.64040279e-01 5.41818282e-03
6.29560888e-01 -5.13698220e-01 7.55180955e-01 -9.97519970e-01
1.33185819e-01 -3.89835626e-01 -1.43205196e-01 -1.68154597e+00
-6.37025774e-01 -5.24113774e-01 -5.49417377e-01 1.08220160e+00
5.78261971e-01 -1.18136883e+00 5.82560956e-01 9.79386032e-01
-1.21216312e-01 -6.76937580e-01 -8.90333056e-01 -1.11364508e+00
1.53246550e-02 -4.11615133e-01 7.68944681e-01 1.12911892e+00
1.23148203e-01 4.95073080e-01 -5.00307143e-01 2.60984033e-01
3.81028414e-01 2.00001493e-01 9.60704088e-01 -1.36364877e+00
-7.81603694e-01 -2.26895645e-01 -2.77998328e-01 -1.14855921e+00
1.79623812e-01 -9.29937661e-01 -1.03389502e-01 -1.43600714e+00
1.53974950e-01 -9.61504102e-01 -6.34785593e-01 6.29078090e-01
-1.44460514e-01 2.50402410e-02 1.72744453e-01 3.39927882e-01
-2.27624938e-01 4.23561722e-01 9.37723637e-01 -2.31656253e-01
-4.96945888e-01 2.37593397e-01 -1.00588095e+00 5.00718653e-01
6.11999452e-01 -8.96423876e-01 -7.94828117e-01 -4.69812304e-01
6.07026935e-01 -4.30117518e-01 -8.09178129e-02 -5.20585477e-01
2.66664147e-01 -2.36297809e-02 2.44165808e-01 -1.63768947e-01
3.03718418e-01 -1.16023672e+00 7.49554574e-01 6.02682114e-01
-2.22946867e-01 5.24665415e-01 -5.33297062e-02 8.30362976e-01
2.43395582e-01 -6.03368163e-01 4.00981635e-01 3.09925497e-01
-5.16059995e-01 4.55513149e-01 -2.01867968e-01 -5.32580376e-01
1.54949772e+00 -2.02546641e-01 -1.67507127e-01 4.35953811e-02
-1.04047298e+00 3.79278690e-01 6.66655302e-01 8.10190499e-01
5.61649323e-01 -1.62062895e+00 -5.11816502e-01 4.37816173e-01
3.22891951e-01 -1.23921633e-01 1.50435969e-01 8.52518737e-01
5.33494875e-02 3.95168476e-02 1.52369618e-01 -4.03876632e-01
-1.08154702e+00 1.17039275e+00 2.14158788e-01 -4.74344075e-01
-8.38704228e-01 6.70915306e-01 1.98595822e-01 -5.61411917e-01
8.60358030e-02 -6.38847470e-01 -4.47266437e-02 2.53985494e-01
5.73576748e-01 2.40147635e-01 3.11509848e-01 -7.34766126e-02
-2.16441751e-01 2.68036366e-01 -6.24305844e-01 1.60142183e-01
1.61368775e+00 -7.57542774e-02 1.03770094e-02 5.90480387e-01
1.41794336e+00 -1.82158396e-01 -1.06071711e+00 -2.95383692e-01
-7.13466331e-02 -6.57404661e-01 1.76555529e-01 -2.81485826e-01
-1.23780417e+00 5.12175083e-01 4.08693820e-01 3.98665279e-01
8.29624891e-01 -2.08971187e-01 9.78235900e-01 6.65342689e-01
4.97250974e-01 -1.35266209e+00 1.54977933e-01 2.50337511e-01
7.65080214e-01 -8.07486475e-01 -4.25620750e-02 1.56771373e-02
-7.85869956e-01 8.82997036e-01 5.81762016e-01 -3.16999376e-01
1.03515577e+00 7.27897584e-02 -3.42466295e-01 -5.45671321e-02
-1.13919485e+00 1.92188576e-01 1.04920343e-01 6.20728970e-01
-1.17365040e-01 1.92933813e-01 -1.10598225e-02 9.44306850e-01
-1.30256653e-01 -1.74766466e-01 5.24189830e-01 7.99585044e-01
-2.23813608e-01 -1.44017947e+00 -8.91779289e-02 8.14265132e-01
1.35810018e-01 4.82680351e-02 -7.93566480e-02 5.94525814e-01
3.37121069e-01 8.73128235e-01 3.15285861e-01 -6.88336432e-01
7.18904018e-01 4.13254835e-02 3.59035641e-01 -9.92456615e-01
-4.97697413e-01 -2.47043878e-01 4.48632427e-02 -4.50611800e-01
2.04258651e-01 -7.25958467e-01 -9.16117191e-01 -5.37431896e-01
-8.10922325e-01 3.49155068e-01 7.56391168e-01 5.99239588e-01
5.46730220e-01 5.05727828e-01 1.12094533e+00 -7.22372532e-01
-1.00520396e+00 -7.97214389e-01 -8.27692211e-01 5.50130963e-01
2.74101675e-01 -8.74548793e-01 -4.56180930e-01 2.52718236e-02] | [10.123334884643555, 5.5449371337890625] |
836c61e7-4224-48d6-af46-1aa18556938e | conditional-score-guidance-for-text-driven | 2305.18007 | null | https://arxiv.org/abs/2305.18007v1 | https://arxiv.org/pdf/2305.18007v1.pdf | Conditional Score Guidance for Text-Driven Image-to-Image Translation | We present a novel algorithm for text-driven image-to-image translation based on a pretrained text-to-image diffusion model. Our method aims to generate a target image by selectively editing the regions of interest in a source image, defined by a modifying text, while preserving the remaining parts. In contrast to existing techniques that solely rely on a target prompt, we introduce a new score function, which considers both a source prompt and a source image, tailored to address specific translation tasks. To this end, we derive the conditional score function in a principled manner, decomposing it into a standard score and a guiding term for target image generation. For the gradient computation, we adopt a Gaussian distribution of the posterior distribution, estimating its mean and variance without requiring additional training. In addition, to enhance the conditional score guidance, we incorporate a simple yet effective mixup method. This method combines two cross-attention maps derived from the source and target latents, promoting the generation of the target image by a desirable fusion of the original parts in the source image and the edited regions aligned with the target prompt. Through comprehensive experiments, we demonstrate that our approach achieves outstanding image-to-image translation performance on various tasks. | ['Bohyung Han', 'Minsoo Kang', 'Hyunsoo Lee'] | 2023-05-29 | null | null | null | null | ['image-to-image-translation', 'image-to-image-translation'] | ['computer-vision', 'miscellaneous'] | [ 8.84832561e-01 9.68865082e-02 -1.95895080e-02 -4.97089982e-01
-1.11239862e+00 -5.32973647e-01 9.54297483e-01 -3.38409483e-01
-3.68365735e-01 4.97454464e-01 2.85192192e-01 -5.90123283e-03
2.75534630e-01 -5.97924829e-01 -9.31472421e-01 -9.58347023e-01
6.90646708e-01 2.87566692e-01 2.90060729e-01 -1.63744718e-01
3.73357087e-01 2.17851877e-01 -1.05182159e+00 3.93583417e-01
1.22513962e+00 8.90654504e-01 6.44426882e-01 5.12287378e-01
-1.17915064e-01 6.80527031e-01 -6.84704363e-01 -5.65345645e-01
2.90040702e-01 -1.00847673e+00 -5.75472832e-01 4.04286951e-01
4.82143641e-01 -3.47496569e-01 -1.85787752e-01 1.22596502e+00
4.73029464e-01 1.83209330e-02 8.46090496e-01 -1.03808928e+00
-1.14051664e+00 4.31895614e-01 -8.57680142e-01 1.67261660e-02
2.89398700e-01 3.04156274e-01 7.46538997e-01 -1.12673247e+00
8.81510973e-01 1.06088746e+00 1.60742164e-01 5.23066282e-01
-1.44786525e+00 -5.42181969e-01 1.59461290e-01 -9.44552198e-02
-1.17509747e+00 -5.26059985e-01 1.02290082e+00 -5.01971483e-01
3.83641720e-01 1.48888573e-01 4.63814795e-01 1.09110832e+00
4.54560786e-01 8.36142540e-01 1.26351762e+00 -5.90747535e-01
6.11971729e-02 3.41699392e-01 -5.70765793e-01 7.58867383e-01
-2.43296087e-01 1.59481943e-01 -6.49175823e-01 -6.78177476e-02
8.56034994e-01 -2.02173918e-01 -4.48071301e-01 -7.07452893e-01
-1.52193177e+00 7.90399373e-01 4.39695835e-01 3.09667647e-01
-5.43710649e-01 2.65721437e-02 -7.45232925e-02 8.50599930e-02
6.97602451e-01 1.64621934e-01 -1.13458112e-01 2.06605405e-01
-1.25936234e+00 1.26765013e-01 2.40263224e-01 9.14201021e-01
8.25905740e-01 -5.09151351e-03 -7.64734745e-01 7.36792028e-01
2.85531312e-01 7.39315748e-01 3.98594886e-01 -9.38684225e-01
5.70818841e-01 4.65267450e-01 1.97650120e-01 -8.71254921e-01
2.63036370e-01 -5.04701495e-01 -8.40052307e-01 2.64819652e-01
2.84028888e-01 -5.93783408e-02 -1.07469690e+00 2.05589819e+00
4.04731423e-01 -1.07444823e-01 -1.52858168e-01 9.73982632e-01
2.29789793e-01 8.22806478e-01 -1.20624043e-01 -3.43310148e-01
1.07754850e+00 -1.32214725e+00 -7.30020344e-01 -2.52160370e-01
2.43654966e-01 -9.77635562e-01 1.25519526e+00 -5.78306355e-02
-1.35871196e+00 -5.57129383e-01 -9.19617534e-01 -2.03176782e-01
2.25665625e-02 3.77866894e-01 -3.17911059e-02 3.20275784e-01
-1.35183179e+00 3.85739833e-01 -5.29334247e-01 -2.47376114e-01
1.99141487e-01 4.27941456e-02 -2.41865978e-01 -1.35954008e-01
-9.80457544e-01 8.82548451e-01 1.88923493e-01 -1.66140437e-01
-8.24426532e-01 -5.99283755e-01 -8.35181892e-01 3.07451971e-02
1.96724728e-01 -1.00542808e+00 1.11625731e+00 -1.48787522e+00
-1.81236148e+00 9.68663692e-01 -4.33115661e-01 -1.55662149e-01
7.44788766e-01 -1.47608947e-02 -5.78860156e-02 3.86326700e-01
4.25876260e-01 9.89348710e-01 1.53268707e+00 -1.49289846e+00
-5.07347643e-01 -1.22658759e-01 -2.17529431e-01 4.84644115e-01
-4.18833464e-01 1.74309239e-01 -9.24148560e-01 -1.09947240e+00
-1.12839174e-02 -8.97186100e-01 -1.49057940e-01 2.22825930e-01
-3.58461946e-01 2.54386127e-01 6.46725655e-01 -8.14299583e-01
1.11025286e+00 -2.22349882e+00 4.50867087e-01 1.34107530e-01
2.84724116e-01 4.59247865e-02 -4.58362222e-01 3.05125833e-01
4.75116335e-02 -1.41805157e-01 -7.21887112e-01 -3.70510727e-01
-1.93650544e-01 -1.93292052e-01 -4.48227555e-01 2.77191132e-01
4.04153317e-01 1.22422433e+00 -1.02579963e+00 -6.82443857e-01
1.40969962e-01 5.72906077e-01 -4.98326182e-01 2.90517062e-01
-1.75156608e-01 6.57246232e-01 -3.68807226e-01 2.53008455e-01
6.70046747e-01 -3.72482836e-01 2.33224756e-03 -1.72142372e-01
2.94449702e-02 -2.19058208e-02 -7.22985327e-01 1.82731616e+00
-4.05722290e-01 4.97513831e-01 2.08193913e-01 -6.97477043e-01
9.99418318e-01 8.50677937e-02 5.51688433e-01 -7.98681498e-01
8.14726297e-03 3.03915441e-01 -1.70452103e-01 -2.18559608e-01
5.20358741e-01 -2.23846763e-01 1.37814032e-02 7.42831886e-01
5.06959967e-02 -2.91928649e-01 1.85492128e-01 5.08343458e-01
6.47302866e-01 4.72834617e-01 2.21418813e-02 -1.35679558e-01
5.46263874e-01 -5.46876900e-02 2.51001596e-01 6.38697922e-01
-2.35366344e-01 1.10512519e+00 3.68667275e-01 -2.23425180e-02
-1.23153079e+00 -1.19001710e+00 1.93400666e-01 1.01052701e+00
2.33946219e-01 -2.03996614e-01 -1.16803646e+00 -8.78133476e-01
-3.97544384e-01 7.98766851e-01 -7.28596807e-01 -3.63367707e-01
-5.38242877e-01 -6.04142010e-01 1.72877654e-01 2.40205452e-01
5.81317008e-01 -9.92088735e-01 -3.86512816e-01 1.97663069e-01
-5.94707310e-01 -9.39746857e-01 -1.46183515e+00 -1.75166696e-01
-7.29292929e-01 -5.92088819e-01 -1.34339130e+00 -9.91996944e-01
1.04541063e+00 5.44485152e-01 9.85501766e-01 -1.56201765e-01
1.47932187e-01 3.43825161e-01 -1.62326559e-01 1.46457125e-02
-6.67110682e-01 -6.90692514e-02 -2.49308780e-01 5.17890394e-01
-2.39607304e-01 -3.30902010e-01 -6.87357605e-01 3.20659906e-01
-1.18562758e+00 5.76240659e-01 8.66682410e-01 1.00311255e+00
6.31288111e-01 -3.22356105e-01 1.93633720e-01 -5.54109931e-01
7.18214393e-01 -2.23428473e-01 -4.49150980e-01 3.40814233e-01
-6.89579368e-01 1.59204260e-01 5.04684210e-01 -6.19503081e-01
-1.27734303e+00 3.25011641e-01 4.62342380e-03 -4.89817739e-01
2.06993431e-01 2.30968460e-01 -1.45953342e-01 1.10244937e-02
5.98881364e-01 8.13257158e-01 2.34034389e-01 -1.61696568e-01
6.92968369e-01 5.42122900e-01 6.09216809e-01 -5.41702449e-01
1.00236475e+00 5.12247324e-01 -4.20977682e-01 -4.33510929e-01
-7.59228051e-01 -1.70209959e-01 -7.06579804e-01 -3.28510910e-01
9.31681514e-01 -7.67944038e-01 -9.78108123e-02 5.65453351e-01
-1.33345711e+00 -4.95436996e-01 -4.13637429e-01 2.95247346e-01
-7.60278046e-01 3.64314049e-01 -5.44402659e-01 -3.95483762e-01
-4.25386131e-01 -1.27139020e+00 1.37601411e+00 9.17023197e-02
-2.30560917e-02 -8.70247841e-01 8.70828554e-02 2.44762719e-01
6.14684165e-01 6.47652745e-02 8.57227445e-01 -2.25911766e-01
-7.27008283e-01 -3.26549374e-02 -4.79070127e-01 3.69123220e-01
2.50656903e-01 -1.00052133e-01 -5.93541145e-01 -4.22662705e-01
2.62064159e-01 -1.26444191e-01 8.94807041e-01 4.69878078e-01
7.41687000e-01 -3.33053201e-01 -1.71283334e-01 5.91129005e-01
1.32483149e+00 2.25956380e-01 6.24017715e-01 2.53769338e-01
6.70823574e-01 6.09378159e-01 4.64113265e-01 1.18639000e-01
4.15099651e-01 8.56280088e-01 4.24435697e-02 -4.62671727e-01
-5.31951666e-01 -5.99461555e-01 6.85436189e-01 6.98903501e-01
1.79209962e-01 -2.62279838e-01 -4.62406218e-01 5.67553699e-01
-1.78589916e+00 -8.57420504e-01 1.35427594e-01 2.29262090e+00
1.01942682e+00 -2.27392204e-02 -5.62976673e-02 -4.16736811e-01
1.01910436e+00 4.31171507e-01 -7.22483099e-01 3.91379222e-02
-2.26988792e-01 -7.02482834e-02 2.79622614e-01 7.54265130e-01
-7.63101757e-01 1.13411641e+00 6.83566523e+00 1.15946031e+00
-1.33370960e+00 3.24863046e-01 8.64202380e-01 -1.14676408e-01
-6.37999237e-01 3.10315248e-02 -4.52959657e-01 5.95914781e-01
6.05665922e-01 -3.16655070e-01 4.70321655e-01 5.38098454e-01
4.48929667e-01 2.65931804e-02 -7.15076029e-01 7.79499292e-01
2.99223542e-01 -1.28898942e+00 4.25412148e-01 8.43505785e-02
1.07323396e+00 -2.31504053e-01 2.93983787e-01 -3.46206352e-02
1.91530213e-01 -6.67411685e-01 1.16371882e+00 5.21294117e-01
1.07417798e+00 -4.31937456e-01 2.85607964e-01 2.56726772e-01
-9.52222705e-01 2.37038478e-01 -1.11942023e-01 4.18380439e-01
2.99441338e-01 7.23886609e-01 -3.75219554e-01 4.77046043e-01
3.08375388e-01 5.88597476e-01 -5.13901889e-01 6.71734810e-01
-4.71157521e-01 2.78652251e-01 4.28416692e-02 2.57343709e-01
1.93672061e-01 -5.38692892e-01 6.86000586e-01 1.06944394e+00
5.29571295e-01 -1.99996009e-01 9.41196680e-02 1.24327981e+00
-1.40707523e-01 3.72161388e-01 -5.35010755e-01 1.63067073e-01
1.62805989e-01 1.29431999e+00 -6.69580102e-01 -5.61687708e-01
-2.90308565e-01 1.76573265e+00 2.74647474e-01 7.09891737e-01
-1.02870619e+00 -4.55018163e-01 1.76502034e-01 1.47335932e-01
4.21747535e-01 -1.28736019e-01 -3.66416007e-01 -1.27376473e+00
3.70587975e-01 -8.94631505e-01 -3.86739708e-02 -1.07158482e+00
-9.37390029e-01 8.27407002e-01 9.81226563e-03 -1.29917681e+00
-3.07660818e-01 -2.19573662e-01 -6.89514935e-01 1.13995481e+00
-1.57668042e+00 -1.33014512e+00 -1.59483775e-01 7.09011078e-01
6.22034252e-01 -5.63495718e-02 3.38721335e-01 1.56749427e-01
-4.09323037e-01 6.06964529e-01 2.20971838e-01 -6.24374710e-02
1.07890832e+00 -1.06125712e+00 5.34732997e-01 1.15590274e+00
7.98477903e-02 5.98018110e-01 5.61566591e-01 -7.41288483e-01
-1.03864324e+00 -1.11333477e+00 1.03060222e+00 -3.43639135e-01
4.63261932e-01 -2.98723280e-01 -7.86447287e-01 5.17544091e-01
5.29025614e-01 -2.02992886e-01 1.35154068e-01 -6.01209641e-01
-2.97054917e-01 -1.15475757e-02 -9.96914506e-01 8.83399546e-01
9.87755895e-01 -5.88516176e-01 -3.11651886e-01 2.98962057e-01
8.00614715e-01 -5.04256129e-01 -4.87557471e-01 1.73744693e-01
3.92131209e-01 -9.21812892e-01 8.28548193e-01 -1.23563275e-01
9.46405292e-01 -4.93013084e-01 4.20414507e-02 -1.51124740e+00
-5.77866614e-01 -8.03096235e-01 2.51874384e-02 1.23899198e+00
5.34265637e-01 -4.72742200e-01 6.54007792e-01 4.96838719e-01
-1.05450608e-01 -7.28852928e-01 -7.25094318e-01 -6.06703520e-01
9.81940106e-02 -5.67912199e-02 4.09842551e-01 6.45266175e-01
-2.63365120e-01 4.47386056e-01 -6.70006692e-01 -1.37803823e-01
6.44421399e-01 2.97136635e-01 6.52428150e-01 -5.64034104e-01
-2.85601348e-01 -6.85522795e-01 1.56668648e-01 -1.47724092e+00
-1.73439570e-02 -9.51565742e-01 3.10880721e-01 -1.57580435e+00
6.08610690e-01 -8.54862258e-02 -2.29802310e-01 2.61947751e-01
-5.63202441e-01 5.52992582e-01 3.61159146e-01 5.76616347e-01
-3.08740616e-01 9.18285787e-01 1.78987825e+00 -3.17598492e-01
-1.69348180e-01 -1.96073204e-01 -9.78495240e-01 3.77312303e-01
6.49863720e-01 -5.84317923e-01 -5.21151245e-01 -6.78610206e-01
-1.49557680e-01 2.50752382e-02 2.65138060e-01 -6.16545618e-01
1.77933440e-01 -3.37488979e-01 4.01621670e-01 -3.49587500e-01
3.00080895e-01 -5.23614526e-01 9.22165364e-02 3.93520504e-01
-6.27325416e-01 4.35173512e-02 -1.79903492e-01 6.12640500e-01
-3.07755828e-01 -1.19809009e-01 1.10780632e+00 2.52232440e-02
-3.66657674e-01 3.66751969e-01 -1.77987441e-01 -1.76953122e-01
1.05753005e+00 -2.17224777e-01 -1.82387948e-01 -7.19484925e-01
-4.44298267e-01 -1.20691210e-02 8.35426450e-01 4.83841091e-01
7.91146278e-01 -1.64235723e+00 -1.01044035e+00 3.51525456e-01
1.58297196e-01 -3.36418629e-01 2.17959613e-01 1.03842425e+00
-2.77509570e-01 2.60970622e-01 -1.61705017e-01 -6.42328501e-01
-1.05536163e+00 6.66472435e-01 2.54185528e-01 -3.82642746e-01
-6.02863431e-01 6.54579103e-01 8.38928282e-01 -4.45606589e-01
-7.61161000e-02 -5.08763678e-02 1.38891160e-01 -2.38100499e-01
6.72372401e-01 -1.14135839e-01 -1.83489442e-01 -8.73624146e-01
-3.06741670e-02 7.61083007e-01 -1.59764722e-01 -6.97199821e-01
9.17457223e-01 -5.14130533e-01 -7.82717615e-02 9.34056044e-02
1.15410042e+00 3.11547756e-01 -1.76124489e+00 -4.69284385e-01
-3.89224946e-01 -6.04132950e-01 6.23783655e-02 -9.61148620e-01
-1.25339103e+00 7.61429965e-01 5.52988768e-01 -2.03774482e-01
1.38464069e+00 -4.33665402e-02 8.32577288e-01 -2.73884445e-01
1.08707383e-01 -8.91876519e-01 3.98014367e-01 3.13786477e-01
1.18524349e+00 -1.16909659e+00 -2.79521525e-01 -3.42990786e-01
-8.97724867e-01 9.17715430e-01 3.97140950e-01 1.02771774e-01
2.20228583e-01 3.74776870e-02 3.41444790e-01 1.83952637e-02
-5.33408403e-01 -7.54375085e-02 5.05273163e-01 6.89969063e-01
3.16742718e-01 -1.83773741e-01 -3.82421881e-01 1.17429525e-01
1.02999218e-01 3.98992486e-02 3.74189436e-01 7.51118422e-01
-3.06315958e-01 -1.20045066e+00 -5.31702220e-01 2.36349598e-01
-2.66320288e-01 -4.32736218e-01 -5.28277755e-01 3.39363635e-01
-8.77795964e-02 8.21839988e-01 1.93577595e-02 -3.34897012e-01
2.01356634e-01 8.04727972e-02 4.99934584e-01 -4.48278755e-01
-3.05152565e-01 4.75847155e-01 -4.61307734e-01 -4.50479686e-01
-3.88733685e-01 -6.10647500e-01 -8.68487597e-01 -1.18689775e-01
-2.21951768e-01 -6.33696169e-02 7.11261809e-01 8.40678930e-01
5.86925209e-01 4.34247673e-01 8.59740555e-01 -1.10456264e+00
-3.75043184e-01 -9.25991118e-01 -3.87780011e-01 5.47538400e-01
2.77388275e-01 -3.11927199e-01 -1.32357657e-01 4.19488698e-01] | [11.479564666748047, -0.25330403447151184] |
c8da0553-fb4d-4f08-b9df-89d69789fd4c | dirty-pixels-optimizing-image-classification | 1701.06487 | null | https://arxiv.org/abs/1701.06487v2 | https://arxiv.org/pdf/1701.06487v2.pdf | Dirty Pixels: Towards End-to-End Image Processing and Perception | Real-world imaging systems acquire measurements that are degraded by noise, optical aberrations, and other imperfections that make image processing for human viewing and higher-level perception tasks challenging. Conventional cameras address this problem by compartmentalizing imaging from high-level task processing. As such, conventional imaging involves processing the RAW sensor measurements in a sequential pipeline of steps, such as demosaicking, denoising, deblurring, tone-mapping and compression. This pipeline is optimized to obtain a visually pleasing image. High-level processing, on the other hand, involves steps such as feature extraction, classification, tracking, and fusion. While this siloed design approach allows for efficient development, it also dictates compartmentalized performance metrics, without knowledge of the higher-level task of the camera system. For example, today's demosaicking and denoising algorithms are designed using perceptual image quality metrics but not with domain-specific tasks such as object detection in mind. We propose an end-to-end differentiable architecture that jointly performs demosaicking, denoising, deblurring, tone-mapping, and classification. The architecture learns processing pipelines whose outputs differ from those of existing ISPs optimized for perceptual quality, preserving fine detail at the cost of increased noise and artifacts. We demonstrate on captured and simulated data that our model substantially improves perception in low light and other challenging conditions, which is imperative for real-world applications. Finally, we found that the proposed model also achieves state-of-the-art accuracy when optimized for image reconstruction in low-light conditions, validating the architecture itself as a potentially useful drop-in network for reconstruction and analysis tasks beyond the applications demonstrated in this work. | ['Felix Heide', 'Gordon Wetzstein', 'Stephen Boyd', 'Frank Julca-Aguilar', 'Steven Diamond', 'Vincent Sitzmann'] | 2017-01-23 | null | null | null | null | ['tone-mapping'] | ['computer-vision'] | [ 6.63439512e-01 -3.12269837e-01 4.95324910e-01 -3.92710716e-01
-7.11133718e-01 -4.26940739e-01 2.72462100e-01 -2.34177662e-03
-6.31644070e-01 1.55324697e-01 1.53369367e-01 -1.87211707e-01
-1.83600578e-02 -4.12059098e-01 -8.25873673e-01 -7.92877138e-01
-2.45780312e-02 -1.67357065e-02 3.47715020e-01 4.59183939e-02
2.49039859e-01 6.28209770e-01 -1.81537414e+00 2.84078985e-01
6.34062767e-01 1.33240569e+00 3.97347242e-01 9.84272838e-01
4.95424867e-01 7.48994231e-01 -4.82918978e-01 -3.00913036e-01
6.00450695e-01 -1.36560380e-01 -1.07231237e-01 4.06717658e-01
1.00282097e+00 -9.17481601e-01 -2.76401043e-01 1.15921557e+00
5.70451856e-01 -5.03478572e-02 3.03480804e-01 -7.90309608e-01
-5.70773602e-01 -4.20933291e-02 -5.65540671e-01 -5.64319640e-02
1.11729048e-01 6.88277960e-01 6.92210078e-01 -9.59477484e-01
1.18877143e-01 9.47814047e-01 7.51922846e-01 2.85129249e-01
-1.29563642e+00 -5.72295725e-01 -1.71289951e-01 1.13650896e-01
-9.76456285e-01 -6.69537127e-01 5.76160610e-01 -4.94723260e-01
8.05170178e-01 3.55440229e-02 4.92553532e-01 8.24708462e-01
3.95537704e-01 2.65391737e-01 1.14484465e+00 -1.37073949e-01
2.59704620e-01 -1.07433751e-01 -2.44284905e-02 4.14651960e-01
4.70668763e-01 2.45013461e-01 -5.50631225e-01 3.88299018e-01
8.70385408e-01 -4.98636104e-02 -6.04215026e-01 -2.90433407e-01
-1.28641844e+00 6.68565854e-02 3.00666928e-01 -3.21285836e-02
-6.03516400e-01 3.97772223e-01 6.32125288e-02 3.73149514e-01
2.67521113e-01 5.79567075e-01 -3.14680308e-01 3.98298912e-02
-1.22955751e+00 -1.76048607e-01 4.01643097e-01 7.91527927e-01
7.10870743e-01 2.90449083e-01 -7.28839412e-02 6.60433769e-01
1.16395123e-01 5.61035037e-01 2.47924268e-01 -1.48302817e+00
3.32208902e-01 6.39706179e-02 3.51936877e-01 -8.89840126e-01
-5.11477530e-01 -8.12368989e-01 -9.01163757e-01 8.66976202e-01
4.64237422e-01 -1.31596774e-01 -9.64075625e-01 1.54787016e+00
8.27313438e-02 1.79579109e-01 -8.49490389e-02 1.49464762e+00
4.69111115e-01 5.44001937e-01 -1.49690434e-01 -1.62606671e-01
1.47362268e+00 -6.74080729e-01 -6.25992715e-01 -3.94677848e-01
-1.72837600e-01 -9.08289671e-01 1.21077120e+00 9.67794120e-01
-1.47594893e+00 -7.04834938e-01 -1.27326739e+00 -3.94251138e-01
1.87186971e-01 1.66064188e-01 4.08926398e-01 6.99571192e-01
-1.30954206e+00 6.31753802e-01 -9.23863828e-01 -2.63656139e-01
3.09801012e-01 2.86268055e-01 -2.89062321e-01 -3.18804145e-01
-5.38594127e-01 8.78798306e-01 -2.25596689e-02 2.03238681e-01
-1.06473649e+00 -8.20116162e-01 -5.28426111e-01 2.25636348e-01
4.06903505e-01 -9.41540658e-01 1.12304568e+00 -9.62214947e-01
-1.60558903e+00 6.33650362e-01 9.72885452e-03 -5.15273690e-01
4.43706810e-01 -3.40527713e-01 -3.82318139e-01 3.98736775e-01
-2.52407581e-01 4.22770888e-01 1.45055068e+00 -1.32354093e+00
-5.60153544e-01 -3.55307728e-01 6.20636120e-02 3.70982289e-01
-2.82846570e-01 -2.30375286e-02 -6.58706963e-01 -4.78578001e-01
4.13044900e-01 -5.24779022e-01 -9.46645215e-02 4.91792858e-01
-4.92949672e-02 6.79840386e-01 7.56935596e-01 -8.76448810e-01
7.33811915e-01 -2.27232361e+00 -7.52947256e-02 -1.23044923e-01
4.66856897e-01 2.17233315e-01 -3.02557379e-01 1.51316002e-01
-1.66570410e-01 -1.52563065e-01 -2.42087558e-01 -6.57378018e-01
-2.37262875e-01 -1.78295687e-01 -1.37706712e-01 7.74777889e-01
3.12410623e-01 5.70023477e-01 -7.52906024e-01 -1.03780024e-01
6.23532891e-01 5.49509525e-01 -7.14064837e-01 3.38819951e-01
-1.94445655e-01 6.48041546e-01 1.28592983e-01 6.63322151e-01
7.38190174e-01 -3.34993571e-01 -6.11718893e-02 -9.21625853e-01
-3.33612084e-01 -2.47622877e-02 -1.22637832e+00 1.59094954e+00
-6.88977242e-01 9.74562287e-01 8.16145360e-01 -7.03233540e-01
4.62707520e-01 7.21626431e-02 5.51226676e-01 -8.10341120e-01
1.09908581e-01 2.74835140e-01 4.21560742e-02 -6.63698792e-01
6.57694578e-01 -1.39372781e-01 2.43771762e-01 1.07822962e-01
5.35557345e-02 -4.22469914e-01 -4.57631126e-02 5.80810085e-02
1.28949022e+00 2.25177556e-02 1.85783934e-02 4.21801955e-02
1.61234364e-01 -9.09200981e-02 3.35084468e-01 7.51249015e-01
-1.10731952e-01 1.11796117e+00 2.20935315e-01 -1.08899705e-01
-1.30004156e+00 -1.30125582e+00 -1.78816661e-01 8.05402815e-01
3.90739739e-01 -1.12369381e-01 -7.93637276e-01 5.13666384e-02
-3.59917760e-01 6.47814631e-01 -1.16059646e-01 -1.02270870e-02
-5.20653367e-01 -6.51389301e-01 1.80213600e-01 6.76372945e-02
7.40355134e-01 -4.76070732e-01 -9.45982039e-01 2.45702013e-01
-7.54759833e-02 -1.41388595e+00 -5.51807880e-01 9.81516168e-02
-6.81729615e-01 -1.09798253e+00 -5.16219139e-01 -3.65782559e-01
6.42451525e-01 7.02179730e-01 1.13729525e+00 -1.35504246e-01
-2.95971870e-01 6.42520547e-01 -1.51951835e-01 -1.55966386e-01
-2.59624511e-01 -6.13254130e-01 9.76196676e-02 3.51519436e-01
-2.39933476e-01 -8.88704956e-01 -1.17455506e+00 3.98298204e-01
-1.24414670e+00 2.43767276e-01 9.74107862e-01 8.15000057e-01
4.54588056e-01 3.74346286e-01 8.87963325e-02 -3.26899976e-01
4.33797389e-01 -8.89763981e-02 -8.91861558e-01 4.73097758e-03
-6.36978328e-01 -2.86080211e-01 6.95361078e-01 -3.12021255e-01
-1.06321692e+00 8.28733370e-02 9.16790962e-03 -6.01108253e-01
-1.96710467e-01 2.02217460e-01 -2.49201640e-01 -3.60654563e-01
7.59508789e-01 3.60483646e-01 2.90877849e-01 -3.71882975e-01
1.25568002e-01 6.98538542e-01 9.80143249e-01 -2.13591903e-01
8.42103720e-01 6.95633650e-01 2.77595311e-01 -1.16945302e+00
-7.64173210e-01 -3.55440468e-01 -2.61374682e-01 -4.94141608e-01
1.04732001e+00 -1.27070415e+00 -1.02167237e+00 8.14082921e-01
-1.05691767e+00 -3.07308465e-01 -3.37057531e-01 6.29510522e-01
-4.03135478e-01 4.91238594e-01 -5.83702922e-01 -5.42527020e-01
-1.54286727e-01 -1.31120670e+00 1.14254487e+00 1.97766334e-01
2.36624062e-01 -5.21430492e-01 -5.44246137e-01 6.70762777e-01
7.82759726e-01 -5.76488264e-02 6.66043937e-01 1.93455741e-01
-1.08390963e+00 3.85437571e-02 -4.84496623e-01 8.27689707e-01
-1.84447795e-01 -2.09511653e-01 -1.26779461e+00 -4.39121813e-01
5.06889343e-01 -2.16128841e-01 8.07377577e-01 6.25157297e-01
1.30831838e+00 -9.31194127e-02 3.96403342e-01 1.14331985e+00
1.56082273e+00 -5.33410944e-02 8.22738707e-01 2.08714440e-01
5.76684117e-01 7.10589707e-01 4.59856719e-01 2.52163321e-01
2.51069039e-01 8.26595724e-01 8.45337272e-01 -4.38867837e-01
-6.34312391e-01 2.32452855e-01 5.71329117e-01 4.33341235e-01
2.09990859e-01 -3.07871848e-01 -8.16069841e-01 4.02920783e-01
-1.44054794e+00 -8.17018211e-01 -1.37044489e-01 2.33156943e+00
7.03146040e-01 8.52779448e-02 -2.62030721e-01 1.87099050e-03
4.83207226e-01 8.61762837e-02 -8.47954094e-01 5.60619049e-02
-2.17379883e-01 1.89718366e-01 9.64579105e-01 5.01680970e-01
-8.13953757e-01 5.29232383e-01 5.56454229e+00 5.08824468e-01
-1.46150219e+00 1.46888375e-01 6.31002545e-01 -5.24807990e-01
-7.18742833e-02 -1.03483252e-01 -3.78946662e-01 5.64260364e-01
7.63940811e-01 3.29750746e-01 7.49522805e-01 3.66374731e-01
5.75247645e-01 -4.23858255e-01 -1.20984793e+00 1.31494904e+00
1.73136592e-01 -1.08913076e+00 -1.66530281e-01 -9.43847150e-02
4.64570791e-01 2.25600734e-01 4.21819597e-01 -2.62352556e-01
9.99268293e-02 -9.46521759e-01 9.91204619e-01 5.64157248e-01
8.71782601e-01 -2.29224846e-01 3.59526783e-01 1.65585265e-01
-7.62501478e-01 -2.35541403e-01 -1.33244738e-01 1.80694349e-02
3.74399602e-01 1.07511485e+00 -5.09205580e-01 4.14891660e-01
8.41781199e-01 6.02053940e-01 -5.32300413e-01 1.19444788e+00
-6.85392246e-02 5.74623108e-01 -2.53594965e-01 5.40104806e-01
-4.46433239e-02 -3.33580911e-01 6.52107716e-01 1.05547583e+00
4.62424755e-01 2.21422568e-01 -3.89551185e-02 7.74157405e-01
1.35604262e-01 -6.38534725e-01 -3.01044405e-01 2.99894869e-01
3.09366047e-01 1.39797688e+00 -4.33454603e-01 -7.87888989e-02
-4.61851597e-01 1.06439102e+00 -2.92712629e-01 5.52991807e-01
-7.14483857e-01 -2.86476314e-01 9.78473306e-01 5.18616140e-01
2.47541949e-01 -5.77857018e-01 -5.76641798e-01 -1.31038940e+00
3.17029893e-01 -9.49691176e-01 -1.66186228e-01 -1.22652340e+00
-1.16908753e+00 3.29910159e-01 -2.62735605e-01 -1.41539168e+00
3.70866470e-02 -8.75681996e-01 -3.25995386e-01 9.46590126e-01
-1.74520290e+00 -1.10408878e+00 -7.25953996e-01 5.74859798e-01
5.11694312e-01 1.85193256e-01 1.69376463e-01 5.68145156e-01
-4.64969665e-01 1.79639161e-01 1.07484914e-01 -7.39230812e-02
8.72251093e-01 -1.01785648e+00 2.20131069e-01 1.43009460e+00
-3.17049056e-01 4.49847221e-01 9.28233922e-01 -4.32978123e-01
-1.81894779e+00 -1.12165070e+00 1.32251963e-01 -8.58412981e-02
5.77921987e-01 -4.62027490e-01 -7.42272615e-01 2.43169278e-01
1.52047142e-01 1.39415890e-01 1.06162399e-01 -3.73837113e-01
-2.51344502e-01 -5.42059004e-01 -1.13381922e+00 5.97570539e-01
9.78654385e-01 -5.90691984e-01 -3.87428254e-02 2.10502759e-01
6.23667955e-01 -5.12395084e-01 -7.48156607e-01 2.47195736e-01
6.77931249e-01 -1.47435617e+00 1.17827690e+00 5.71202189e-02
5.49454331e-01 -6.95119202e-01 -3.23160768e-01 -1.22046268e+00
-3.08738053e-01 -7.29478657e-01 3.00086904e-02 1.02078247e+00
1.68357342e-01 -6.09293818e-01 6.60039067e-01 5.89829206e-01
-4.93864089e-01 -2.69780219e-01 -7.10090518e-01 -6.35256231e-01
-4.00469065e-01 -6.12180412e-01 1.77786648e-01 7.38258243e-01
-6.93595409e-01 1.67542532e-01 -4.38969314e-01 7.33170509e-01
1.27798033e+00 -4.46750149e-02 7.76189268e-01 -9.07840669e-01
-6.42737925e-01 -3.09988827e-01 -3.81480038e-01 -1.28939593e+00
-2.75741130e-01 -3.01030666e-01 2.25500450e-01 -1.38483608e+00
-1.51071832e-01 -2.93683589e-01 4.85541821e-02 -5.14700823e-02
8.98996070e-02 4.01538342e-01 3.20331633e-01 3.03057700e-01
-4.23053592e-01 2.52881199e-01 1.23477662e+00 -6.42867610e-02
7.36692697e-02 -2.79390872e-01 -7.33729362e-01 6.07006848e-01
5.02766311e-01 -1.28957048e-01 -4.21865016e-01 -1.02861750e+00
2.65291810e-01 1.92427099e-01 8.13192189e-01 -1.46055746e+00
6.67003095e-01 -4.53054123e-02 5.75095654e-01 -2.91825354e-01
7.81564474e-01 -1.20458210e+00 3.55719894e-01 3.21783811e-01
-2.19880491e-01 -1.20490760e-01 1.15402145e-02 5.18631101e-01
-2.37337127e-01 9.42220613e-02 1.20841181e+00 4.49979398e-03
-7.45281279e-01 1.02364935e-01 -2.93760389e-01 -1.29198134e-01
8.58142257e-01 -5.17734528e-01 -5.64018488e-01 -6.58592939e-01
-5.07169485e-01 9.74753872e-03 7.83299208e-01 -4.59804498e-02
7.74441898e-01 -6.36209130e-01 -8.01568449e-01 4.63416040e-01
-1.45239651e-01 7.80144185e-02 3.89525980e-01 1.01137578e+00
-7.46962786e-01 -1.15573741e-01 -3.68840694e-01 -8.29076409e-01
-1.04012406e+00 2.78257489e-01 5.51366687e-01 2.12967079e-02
-5.78468382e-01 6.33839369e-01 2.75725037e-01 1.11023083e-01
2.68998444e-01 -5.54857552e-01 2.71851778e-01 -1.92887738e-01
5.45601249e-01 3.28002781e-01 4.55928147e-01 -2.53182203e-01
-9.50812735e-03 7.46784866e-01 9.33390632e-02 -1.78484768e-01
1.36614060e+00 -5.30814111e-01 -2.42803749e-02 1.92983121e-01
1.01091194e+00 -5.02378680e-02 -1.81966722e+00 -1.97753370e-01
-4.31809545e-01 -6.85107410e-01 6.73372865e-01 -8.91525805e-01
-1.21507490e+00 9.73231614e-01 8.10969114e-01 6.68017892e-03
1.73534000e+00 -3.40410113e-01 6.37371242e-01 2.09998950e-01
3.76216233e-01 -9.62419748e-01 3.19208592e-01 2.86152393e-01
8.19557428e-01 -1.27450824e+00 7.20358640e-02 -2.57382840e-01
-3.53412211e-01 9.30875003e-01 5.66369057e-01 4.75175753e-02
4.19410348e-01 6.09560847e-01 8.21873993e-02 -6.60171285e-02
-7.58003354e-01 -1.30616724e-01 1.85736224e-01 6.26560032e-01
1.37393147e-01 -3.00445169e-01 1.68411985e-01 2.36188412e-01
-2.61920802e-02 -1.09951712e-01 8.17921519e-01 6.35577381e-01
-5.90951979e-01 -5.91271579e-01 -6.30894423e-01 5.16591728e-01
-4.20887470e-01 -3.33471507e-01 8.06442276e-02 4.53293592e-01
9.75136533e-02 1.14954937e+00 2.22640306e-01 -4.13547009e-01
4.74935979e-01 -5.58079660e-01 4.72781271e-01 -5.40221751e-01
-7.37955868e-01 1.54719204e-02 9.16031301e-02 -9.62762415e-01
-2.66333342e-01 -5.67337811e-01 -8.15967917e-01 -2.54531235e-01
-4.32181498e-03 -4.96237099e-01 1.04752374e+00 4.69159454e-01
5.02334177e-01 6.01235747e-01 5.74276030e-01 -1.28944755e+00
-5.87416649e-01 -6.63279235e-01 -6.05371773e-01 4.61127758e-01
8.21902454e-01 -2.94853479e-01 -4.59432364e-01 3.12211633e-01] | [10.758069038391113, -2.4210689067840576] |
a47d6d70-1eb7-4583-88b8-ea4467680b3b | fairness-aware-differentially-private | 2303.09527 | null | https://arxiv.org/abs/2303.09527v1 | https://arxiv.org/pdf/2303.09527v1.pdf | Fairness-aware Differentially Private Collaborative Filtering | Recently, there has been an increasing adoption of differential privacy guided algorithms for privacy-preserving machine learning tasks. However, the use of such algorithms comes with trade-offs in terms of algorithmic fairness, which has been widely acknowledged. Specifically, we have empirically observed that the classical collaborative filtering method, trained by differentially private stochastic gradient descent (DP-SGD), results in a disparate impact on user groups with respect to different user engagement levels. This, in turn, causes the original unfair model to become even more biased against inactive users. To address the above issues, we propose \textbf{DP-Fair}, a two-stage framework for collaborative filtering based algorithms. Specifically, it combines differential privacy mechanisms with fairness constraints to protect user privacy while ensuring fair recommendations. The experimental results, based on Amazon datasets, and user history logs collected from Etsy, one of the largest e-commerce platforms, demonstrate that our proposed method exhibits superior performance in terms of both overall accuracy and user group fairness on both shallow and deep recommendation models compared to vanilla DP-SGD. | ['Yiming Ying', 'Xiaoting Zhao', 'Dingxian Wang', 'Congzhe Su', 'Yingqiang Ge', 'Zhenhuan Yang'] | 2023-03-16 | null | null | null | null | ['collaborative-filtering'] | ['miscellaneous'] | [-1.14871167e-01 -2.84810573e-01 -6.80385977e-02 -9.32798147e-01
-4.94742751e-01 -7.63415873e-01 4.50063080e-01 -1.96784595e-03
-5.15987158e-01 6.03049040e-01 2.68749803e-01 -5.43867946e-01
-1.44447327e-01 -7.38322973e-01 -2.19004422e-01 -6.14424169e-01
-8.45443923e-03 -1.42206118e-01 -4.47161466e-01 -7.12518161e-03
2.83286095e-01 3.18618298e-01 -1.31665838e+00 2.87219107e-01
9.29984093e-01 1.09843349e+00 -6.63543582e-01 1.85454324e-01
1.33525148e-01 5.40222943e-01 -1.26757354e-01 -1.32919383e+00
9.67949867e-01 -3.30230892e-01 -5.06596804e-01 -4.80589032e-01
5.14411807e-01 -6.48628831e-01 -6.21781349e-01 1.09892213e+00
5.86459756e-01 5.53856134e-01 3.30271780e-01 -1.36872339e+00
-9.53147829e-01 6.66352153e-01 -6.01419985e-01 -7.92987272e-02
-2.87167747e-02 4.71302532e-02 1.46098542e+00 -6.36495590e-01
2.40315557e-01 1.12312031e+00 7.29792655e-01 7.45762527e-01
-1.47287679e+00 -1.02597880e+00 2.84060717e-01 -3.71138006e-01
-1.26486158e+00 -5.86796522e-01 4.37543154e-01 -3.06759387e-01
1.95906982e-01 7.38604009e-01 3.43249053e-01 1.07059181e+00
1.62287220e-01 9.12011147e-01 1.31599152e+00 -5.35345748e-02
5.21793246e-01 3.82684320e-01 3.82228136e-01 3.79788548e-01
5.90499163e-01 2.62531608e-01 -4.84496713e-01 -7.93350458e-01
4.53928500e-01 4.38282758e-01 -2.30840728e-01 -6.95846498e-01
-3.72297257e-01 8.98064017e-01 1.44529015e-01 7.03903511e-02
-2.57712334e-01 -8.13412443e-02 5.85504532e-01 5.72163284e-01
7.38536119e-01 2.66868353e-01 -5.16677797e-01 1.90254718e-01
-8.84618640e-01 6.64497674e-01 1.03147829e+00 6.08828306e-01
3.38508219e-01 -4.02364850e-01 -5.76173663e-01 6.11541033e-01
5.03307164e-01 3.06898840e-02 3.16628993e-01 -1.13447785e+00
4.38990623e-01 3.86715114e-01 5.48702359e-01 -1.34020686e+00
1.68181315e-01 -6.41899168e-01 -9.91197288e-01 3.27924401e-01
7.38189280e-01 -4.91443396e-01 -1.02196254e-01 2.13229489e+00
3.49444985e-01 -1.05965741e-01 -1.21160045e-01 1.02030504e+00
2.27294996e-01 1.27325326e-01 3.26197684e-01 -1.85544640e-01
1.02856338e+00 -7.10083127e-01 -6.26120806e-01 9.11011919e-02
5.94679892e-01 -3.36563885e-01 1.22150600e+00 3.46417397e-01
-9.94893968e-01 -1.09700948e-01 -7.56414711e-01 -1.83856055e-01
-1.60297111e-01 -8.71978626e-02 1.02429271e+00 1.52711630e+00
-8.27281356e-01 8.11557233e-01 -5.70453703e-01 -1.29991412e-01
9.97786164e-01 3.68092448e-01 -2.36422390e-01 5.95441572e-02
-1.20960557e+00 9.74654183e-02 -2.71897048e-01 4.77199890e-02
-3.40490133e-01 -9.93144214e-01 -2.53006816e-01 4.14501786e-01
2.50813544e-01 -7.21236706e-01 1.16768014e+00 -1.16537476e+00
-1.54851222e+00 9.48305428e-01 1.56464159e-01 -6.61129236e-01
1.29262066e+00 -5.11517346e-01 -2.97928095e-01 -7.07477629e-01
-2.32102513e-01 -5.64534366e-02 6.18387878e-01 -1.05574870e+00
-6.92611635e-01 -1.00054657e+00 2.49928340e-01 3.01309317e-01
-6.60490632e-01 2.66006351e-01 -6.17577806e-02 -7.37340868e-01
-2.27962509e-01 -8.42792392e-01 -4.26107854e-01 3.20791721e-01
-2.48567030e-01 -1.38241157e-01 5.95584750e-01 -5.89043736e-01
1.40851140e+00 -2.31386662e+00 -3.65861923e-01 5.27220130e-01
3.91442925e-01 3.27290148e-01 1.63750857e-01 4.12077196e-02
3.01918268e-01 3.93691212e-01 -2.36277166e-03 -7.36237943e-01
2.83922791e-01 -9.69735608e-02 -4.12761450e-01 6.67144835e-01
-7.50609696e-01 6.54087305e-01 -6.49183154e-01 -6.63920343e-02
-1.90044597e-01 1.94338486e-01 -9.86948907e-01 2.27499172e-01
6.52803853e-02 4.55784619e-01 -5.90207338e-01 2.69133449e-01
1.13776112e+00 1.66036710e-02 4.93082404e-01 2.79809237e-01
-1.32750839e-01 1.83893979e-01 -1.13495767e+00 1.56659412e+00
-1.64215192e-01 5.75414002e-02 4.27306741e-01 -5.17540574e-01
5.97623765e-01 2.67701298e-01 4.85123515e-01 -5.60899198e-01
3.82191896e-01 5.05962707e-02 -1.56287208e-01 4.54046242e-02
6.54191375e-01 6.92537725e-02 6.39880002e-02 9.20032978e-01
-3.48036051e-01 5.90822101e-01 -5.16355872e-01 2.32395247e-01
8.72816503e-01 -2.14452311e-01 1.14306686e-02 -5.19606054e-01
4.27157193e-01 -6.98033571e-01 8.29667330e-01 1.26448679e+00
-6.74747407e-01 4.21492010e-01 2.93992907e-01 -4.79055882e-01
-6.59611523e-01 -7.77621031e-01 2.66437531e-02 1.53409362e+00
1.92387551e-01 -4.55781698e-01 -8.13063085e-01 -1.05146980e+00
5.01756012e-01 8.76862884e-01 -5.90996504e-01 -2.20799044e-01
-1.87056318e-01 -7.85079598e-01 6.62405550e-01 1.49916774e-02
6.41597092e-01 -4.23520714e-01 -4.18469578e-01 -1.07423544e-01
1.88310251e-01 -6.20547473e-01 -1.04504645e+00 -3.11453968e-01
-9.35585082e-01 -7.90459216e-01 -5.86945236e-01 -5.68092801e-02
5.38756549e-01 6.84184849e-01 8.00598562e-01 6.19613715e-02
4.29916382e-02 3.80210221e-01 -1.98706895e-01 -3.39563102e-01
-8.28413591e-02 -5.98039590e-02 1.99195132e-01 6.57001495e-01
7.10775554e-01 -6.52586937e-01 -1.13255751e+00 4.51997101e-01
-8.64693582e-01 -2.41369173e-01 8.45182687e-02 5.14004946e-01
2.71422178e-01 2.95959134e-02 4.78719682e-01 -1.51377642e+00
1.14958882e+00 -6.15802407e-01 -4.85005885e-01 2.42533371e-01
-1.22947681e+00 -3.02980930e-01 8.63391221e-01 -1.97393045e-01
-1.49351239e+00 -3.42266202e-01 1.65227540e-02 -1.64841935e-01
1.75016522e-02 1.50494769e-01 -3.23047191e-01 -1.76827878e-01
6.74296618e-01 -4.13836762e-02 6.60431907e-02 -6.88368678e-01
6.29761159e-01 9.73375142e-01 1.60516888e-01 -6.52798593e-01
3.75401348e-01 5.30572355e-01 -3.34969193e-01 -3.28494340e-01
-9.16671336e-01 -2.61312872e-01 -1.28481746e-01 1.29819602e-01
4.36907947e-01 -8.35824847e-01 -8.70628059e-01 6.34755731e-01
-6.50261104e-01 4.12167311e-02 -2.77494371e-01 4.32898670e-01
-2.00502828e-01 6.43383920e-01 -6.67030632e-01 -1.11877453e+00
-8.36832345e-01 -6.19708896e-01 2.35939756e-01 3.15577686e-01
-1.98487163e-01 -7.96595871e-01 -4.83142212e-02 6.79260790e-01
6.74216211e-01 -3.76410559e-02 7.83881068e-01 -1.12515819e+00
-2.95517504e-01 -4.54751104e-01 -2.23276719e-01 5.45764804e-01
1.36867553e-01 -3.37532997e-01 -1.06243169e+00 -7.41372228e-01
2.39889503e-01 -2.21955255e-01 4.73617584e-01 1.32667050e-01
1.67923403e+00 -7.16072559e-01 3.12797241e-02 7.01712251e-01
1.26815927e+00 7.08370237e-03 4.41317976e-01 7.71676144e-03
4.37372565e-01 5.42929232e-01 3.97652090e-01 9.20811355e-01
2.95065880e-01 4.90154952e-01 3.45999688e-01 5.26814647e-02
5.19306362e-01 -5.24569094e-01 1.38736665e-01 1.25736237e-01
-1.34538949e-01 -1.91799819e-01 -2.20570400e-01 1.66948419e-03
-2.09886479e+00 -9.56956267e-01 8.16147309e-03 2.83664489e+00
7.03691244e-01 -2.57193714e-01 3.55093539e-01 -1.48049250e-01
6.55110776e-01 1.35376424e-01 -8.30196142e-01 -4.84352797e-01
-4.27048318e-02 1.48860708e-01 7.86293209e-01 1.10013969e-01
-9.98857081e-01 6.36710882e-01 5.83542156e+00 6.81778729e-01
-8.95792305e-01 3.97812575e-01 1.09348118e+00 -5.10952711e-01
-5.70664942e-01 -6.14618063e-02 -4.23836023e-01 6.83725417e-01
7.31750488e-01 -5.67233503e-01 6.60257876e-01 7.66418159e-01
3.61694604e-01 3.56022358e-01 -1.13652277e+00 1.00198925e+00
-3.87332976e-01 -1.05764925e+00 -1.43845752e-01 4.11254227e-01
8.97197545e-01 -1.26546264e-01 4.10708159e-01 3.67831856e-01
7.97337711e-01 -8.18404496e-01 7.47872412e-01 3.62788081e-01
3.29579204e-01 -8.69158089e-01 4.99093741e-01 4.16843712e-01
-4.20904279e-01 -1.95171297e-01 -4.64518785e-01 -1.27495930e-01
-1.64549068e-01 7.04634428e-01 2.57833041e-02 4.95029271e-01
8.15174818e-01 1.61669537e-01 -5.13286181e-02 9.11548197e-01
1.54114768e-01 7.40719259e-01 -1.44079566e-01 5.26950508e-02
-4.80181761e-02 -6.44259095e-01 3.12638372e-01 8.72220933e-01
1.52939022e-01 2.56305605e-01 -1.09679565e-01 1.03624809e+00
-6.69696569e-01 5.60025513e-01 -5.21048963e-01 -8.27936754e-02
5.56689262e-01 1.30680501e+00 -1.78464234e-01 1.32654548e-01
-6.72961771e-01 1.16528988e+00 3.61192256e-01 3.20771575e-01
-6.98316336e-01 -1.21396035e-01 1.35853636e+00 1.53853357e-01
-2.18037143e-02 -1.78289369e-01 -5.30975282e-01 -1.33084345e+00
3.54645737e-02 -1.04601109e+00 6.63794279e-01 1.11400776e-01
-1.67746747e+00 -1.92456525e-02 -6.86979592e-01 -7.04349339e-01
3.88994813e-01 -9.79153737e-02 -4.87266421e-01 1.12961411e+00
-1.09943712e+00 -8.41958940e-01 5.23565933e-02 7.11236775e-01
2.52246503e-02 -2.57439792e-01 8.87326062e-01 6.51257992e-01
-6.79660141e-01 1.47738171e+00 6.89252317e-01 4.30811085e-02
7.62734175e-01 -9.30949152e-01 4.23735768e-01 7.71685481e-01
1.21775188e-01 1.07281554e+00 5.36692739e-01 -4.45367366e-01
-1.45612097e+00 -1.15280890e+00 7.09913492e-01 -5.17041683e-01
3.38426203e-01 -5.72154164e-01 -8.23583722e-01 7.24627495e-01
-1.34435371e-01 4.26234640e-02 1.33601522e+00 4.00363326e-01
-6.21593535e-01 -2.34612048e-01 -1.96860540e+00 8.62298965e-01
1.37792170e+00 -6.63391113e-01 -4.72349934e-02 1.88026667e-01
6.65807426e-01 -1.66393146e-01 -7.95926154e-01 1.49435615e-02
1.06639802e+00 -1.44455087e+00 7.10725069e-01 -1.11691558e+00
4.53128405e-02 8.86859596e-02 -3.93241435e-01 -9.15093541e-01
-5.58270872e-01 -1.05295599e+00 -8.49521756e-02 1.32808387e+00
3.26070160e-01 -9.51105535e-01 1.23724473e+00 1.77454519e+00
6.78747237e-01 -6.82747185e-01 -6.95803940e-01 -5.40106535e-01
2.62816787e-01 -2.43319049e-01 8.64317477e-01 1.22515297e+00
-2.68624157e-01 -1.77461386e-01 -8.35859179e-01 1.06168635e-01
8.04255188e-01 1.99842438e-01 9.29808855e-01 -1.31434417e+00
-4.95755106e-01 -3.05481732e-01 7.41595849e-02 -1.05615342e+00
1.91254377e-01 -9.04102206e-01 -5.19943774e-01 -8.09187472e-01
1.78113654e-01 -8.03907931e-01 -7.22829759e-01 3.30327868e-01
-6.00082539e-02 1.85744185e-02 1.53326109e-01 3.59040588e-01
-4.93702263e-01 3.70223671e-01 9.19273496e-01 1.81992933e-01
-3.58853042e-01 7.30539441e-01 -1.49894774e+00 3.54734212e-01
8.48540783e-01 -3.96264493e-01 -4.17638004e-01 -4.58632886e-01
2.67427355e-01 -2.19894111e-01 3.67783010e-02 -5.28749228e-01
1.79352820e-01 -2.56010354e-01 1.28379330e-01 1.10965073e-01
-2.21878976e-01 -1.00276852e+00 2.22638845e-01 3.50581676e-01
-8.54515135e-01 -1.99215263e-01 -2.95215487e-01 8.91098917e-01
2.48520076e-01 3.32421400e-02 8.22081208e-01 -1.19211093e-01
-1.16473563e-01 7.82715797e-01 -8.77458006e-02 2.23978050e-02
8.83315921e-01 -1.24480553e-01 -7.19284490e-02 -5.18659770e-01
-3.96740526e-01 3.14405054e-01 5.19412279e-01 4.91734087e-01
1.25893563e-01 -1.10788977e+00 -6.19080722e-01 2.50196010e-01
-4.17228304e-02 -4.90152448e-01 4.73326027e-01 5.74749291e-01
-2.08522403e-03 1.81087762e-01 4.76631783e-02 1.69426382e-01
-1.35557818e+00 3.89282167e-01 3.70643735e-01 -1.55040294e-01
-4.53429133e-01 1.00110435e+00 1.54398814e-01 -5.69486141e-01
5.18768013e-01 9.48672965e-02 1.95005551e-01 -2.15706915e-01
5.66486657e-01 6.94803536e-01 7.03697950e-02 -2.80941397e-01
-8.14137012e-02 -2.90167511e-01 -5.23549795e-01 9.04253349e-02
1.12534916e+00 -4.37802523e-01 -1.15498073e-01 -1.18988074e-01
1.03502095e+00 5.55576503e-01 -1.26132524e+00 -5.15834391e-01
-9.61367711e-02 -1.22392595e+00 2.50666380e-01 -9.60476518e-01
-1.30268514e+00 2.96364069e-01 8.20632696e-01 3.66903603e-01
8.72475564e-01 -7.31954336e-01 8.72829497e-01 2.55288661e-01
7.37794638e-01 -1.03214848e+00 -6.86829567e-01 1.51856124e-01
3.35983545e-01 -1.25059891e+00 -4.28166166e-02 -1.57293171e-01
-5.19860268e-01 4.49163347e-01 5.28253615e-01 -7.57831261e-02
8.70548546e-01 -1.67995021e-01 1.26463026e-01 2.15779528e-01
-5.14005482e-01 5.19905150e-01 -5.33316880e-02 2.39425316e-01
6.19262815e-01 4.16210711e-01 -8.30078185e-01 1.24153543e+00
6.07718341e-03 2.96422243e-01 7.20237643e-02 9.14352179e-01
4.11164798e-02 -1.37080097e+00 4.01244126e-02 7.63539493e-01
-1.06136894e+00 6.35606274e-02 -6.11364245e-01 2.79041171e-01
-1.12217158e-01 9.64213192e-01 -1.96639329e-01 -4.64916289e-01
2.92048454e-01 4.91510332e-03 2.45117471e-01 -3.26312363e-01
-1.24956155e+00 -6.44344926e-01 -4.72625438e-03 -7.60069132e-01
4.59301919e-02 -6.68674529e-01 -8.00364017e-01 -9.30769384e-01
-3.25520277e-01 4.60486799e-01 5.35769105e-01 6.21777236e-01
9.26537931e-01 -2.65171081e-01 1.09932458e+00 -2.21539363e-01
-1.32951009e+00 -3.60040486e-01 -1.06734407e+00 7.77861655e-01
-1.20984809e-02 -1.72054708e-01 -5.95990419e-01 -7.28290319e-01] | [5.973433017730713, 6.686766147613525] |
1675dbf3-4330-4db1-a980-ca20ae218f4b | post-train-adaptive-mobilenet-for-fast-anti | 2207.13410 | null | https://arxiv.org/abs/2207.13410v2 | https://arxiv.org/pdf/2207.13410v2.pdf | Post-Train Adaptive MobileNet for Fast Anti-Spoofing | Many applications require high accuracy of neural networks as well as low latency and user data privacy guaranty. Face anti-spoofing is one of such tasks. However, a single model might not give the best results for different device performance categories, while training multiple models is time consuming. In this work we present Post-Train Adaptive (PTA) block. Such a block is simple in structure and offers a drop-in replacement for the MobileNetV2 Inverted Residual block. The PTA block has multiple branches with different computation costs. The branch to execute can be selected on-demand and at runtime; thus, offering different inference times and configuration capability for multiple device tiers. Crucially, the model is trained once and can be easily reconfigured after training, even directly on a mobile device. In addition, the proposed approach shows substantially better overall performance in comparison to the original MobileNetV2 as tested on CelebA-Spoof dataset. Different PTA block configurations are sampled at training time, which also decreases overall wall-clock time needed to train the model. While we present computational results for the anti-spoofing problem, the MobileNetV2 with PTA blocks is applicable to any problem solvable with convolutional neural networks, which makes the results presented practically significant. | ['Kostiantyn Khabarlak'] | 2022-07-27 | null | null | null | null | ['face-anti-spoofing'] | ['computer-vision'] | [ 3.51511061e-01 -4.82801674e-03 -3.71888697e-01 -3.53902489e-01
3.43107060e-02 -5.73886693e-01 3.42463791e-01 -1.34864738e-02
-7.08807349e-01 5.54560721e-01 -6.25067472e-01 -9.02130604e-01
-2.23915577e-01 -7.76786506e-01 -8.29817832e-01 -6.42753422e-01
-1.89315245e-01 5.37834585e-01 4.40727830e-01 -4.79868464e-02
-1.40688300e-01 8.84257436e-01 -1.48039949e+00 2.17190534e-01
4.76136893e-01 1.25140703e+00 -1.46710828e-01 8.15345168e-01
3.35140854e-01 4.99826759e-01 -8.10700297e-01 -7.81416833e-01
3.41258645e-01 2.33801112e-01 -6.81059778e-01 -4.61613089e-01
5.48086286e-01 -5.20342767e-01 -1.75269589e-01 8.90754402e-01
6.72214448e-01 -2.51339257e-01 1.10313594e-01 -1.52389956e+00
1.02907389e-01 6.23830795e-01 -2.54745603e-01 -9.20159463e-03
-1.09466901e-02 -8.71373564e-02 4.71612662e-01 -3.40018004e-01
4.70928133e-01 1.16881335e+00 9.03861403e-01 6.68370783e-01
-1.16011584e+00 -1.03543377e+00 -2.91530371e-01 2.75163591e-01
-1.28448629e+00 -7.72941947e-01 6.20323002e-01 -4.69343103e-02
1.04769635e+00 4.39225465e-01 5.00709832e-01 1.37893796e+00
-2.41017081e-02 5.02194703e-01 8.69813859e-01 -1.30863398e-01
2.36870348e-01 3.91972125e-01 4.32046652e-02 7.59498060e-01
7.01054037e-01 8.27698708e-02 -3.01016271e-01 -3.45295489e-01
4.70387489e-01 1.50319427e-01 -5.95031343e-02 -3.84481281e-01
-7.31891036e-01 5.95290601e-01 4.17554677e-01 2.35159189e-01
-2.84072578e-01 4.23156202e-01 8.14675212e-01 5.68613052e-01
1.23197876e-01 2.16094390e-01 -7.34276295e-01 -4.53645401e-02
-1.31084657e+00 1.90053225e-01 1.04997444e+00 6.83322608e-01
6.85298502e-01 8.00365880e-02 2.16813475e-01 6.30169094e-01
8.77449587e-02 6.82454765e-01 2.04337284e-01 -7.77914762e-01
4.29946810e-01 1.90349102e-01 -1.78632721e-01 -1.50461030e+00
-5.61998308e-01 -5.76070905e-01 -1.22889054e+00 2.52959818e-01
4.19275552e-01 -3.45958471e-01 -7.62882054e-01 1.56775320e+00
4.60807025e-01 5.97720087e-01 -2.04092264e-01 3.02117676e-01
5.91036320e-01 3.78173530e-01 -1.70845196e-01 -1.81592703e-01
1.47684884e+00 -9.46715832e-01 -6.08491898e-01 -1.92878276e-01
7.47764468e-01 -6.13600433e-01 5.06546855e-01 4.66341674e-01
-7.74671733e-01 -4.97557253e-01 -1.23865736e+00 5.94016388e-02
-6.80561960e-01 3.58008966e-02 6.72761440e-01 1.40082753e+00
-1.38225162e+00 7.86597013e-01 -8.89970422e-01 -2.77134240e-01
5.80814898e-01 1.20676553e+00 -5.23248196e-01 2.81180531e-01
-1.20345473e+00 5.52451134e-01 5.30075252e-01 2.06634417e-01
-7.75530219e-01 -3.69529426e-01 -7.62470424e-01 1.77741647e-01
3.45050991e-01 -4.95597720e-01 9.42509055e-01 -8.14522147e-01
-1.80536449e+00 6.61717713e-01 -2.33446330e-01 -8.70039463e-01
6.52674139e-01 1.27033545e-02 -5.92642307e-01 1.20825760e-01
-3.20681363e-01 5.35056174e-01 1.32246912e+00 -1.01204503e+00
-4.15736109e-01 -2.51227081e-01 1.67269811e-01 -5.66390038e-01
-6.81298852e-01 1.00994237e-01 -5.63942790e-01 -3.77483487e-01
-2.69745052e-01 -1.14147246e+00 -9.88323428e-03 -1.02261499e-01
-3.70620608e-01 9.30382013e-02 1.32357526e+00 -6.15097046e-01
1.18817139e+00 -2.06641912e+00 -4.81659412e-01 7.15524852e-01
1.53551102e-01 1.17984319e+00 -1.13818802e-01 1.66664496e-02
-2.80216299e-02 2.83406377e-01 -9.99032110e-02 -6.34202719e-01
-2.19282478e-01 2.40436077e-01 -3.71618345e-02 5.71982026e-01
9.88901928e-02 7.39794910e-01 -6.74409688e-01 -5.15324175e-01
3.98744524e-01 7.93609560e-01 -8.92894924e-01 -9.94639173e-02
7.93009810e-03 3.43944639e-01 -3.03538322e-01 6.04491711e-01
1.14938259e+00 -3.23941261e-01 5.47308207e-01 -9.52890292e-02
4.15913910e-01 3.92610788e-01 -1.21611142e+00 1.12597322e+00
-8.82844448e-01 7.94701695e-01 4.52765584e-01 -1.09061110e+00
8.47783983e-01 4.64950502e-01 3.62560511e-01 -6.26605690e-01
4.32769537e-01 4.15972441e-01 -1.30996304e-02 -5.35895526e-01
4.99710023e-01 3.99795145e-01 1.68365359e-01 3.33914846e-01
3.41499777e-04 4.59073931e-01 -1.81438744e-01 -2.39301682e-01
1.09374845e+00 -1.49957657e-01 1.61850885e-01 -1.93906710e-01
8.26307356e-01 -6.17653966e-01 4.51226264e-01 9.49889004e-01
-2.94186383e-01 4.68039103e-02 5.12769520e-01 -6.34247899e-01
-8.32228065e-01 -6.32592916e-01 -1.33281425e-01 9.80787933e-01
1.65056810e-01 -5.12144685e-01 -9.66436982e-01 -1.04848051e+00
-6.63859397e-02 3.86362255e-01 -5.03905416e-01 1.05282009e-01
-1.02381146e+00 -5.04604399e-01 1.10098004e+00 1.62920505e-01
8.20329607e-01 -1.11868572e+00 -8.84440124e-01 1.09822288e-01
-5.29588498e-02 -1.26117051e+00 4.97384444e-02 2.35739470e-01
-7.47106194e-01 -1.15682757e+00 -1.92479253e-01 -7.77609229e-01
4.80372459e-01 3.19901735e-01 8.39312375e-01 4.61998940e-01
2.09935576e-01 -1.56698167e-01 -1.74079500e-02 -3.06543320e-01
-4.64726388e-01 6.01434469e-01 2.05639213e-01 2.29706109e-01
3.72133285e-01 -7.68718541e-01 -4.83630985e-01 3.99719238e-01
-8.87665033e-01 -1.49077639e-01 2.27333739e-01 8.86024773e-01
1.61926359e-01 3.41571897e-01 3.47663373e-01 -1.02949929e+00
3.02799821e-01 -4.09448385e-01 -7.48169899e-01 1.99219570e-01
-7.56924152e-01 -1.76646829e-01 8.01559687e-01 -5.38798809e-01
-6.12321854e-01 1.34218642e-02 -3.74310344e-01 -5.38997591e-01
-2.41667271e-01 -1.52740106e-01 -3.61927897e-01 -3.86978686e-01
4.05819237e-01 -2.03778759e-01 2.46803492e-01 -3.35599780e-01
-7.36725107e-02 1.04362702e+00 2.39244729e-01 -1.90846115e-01
7.34359682e-01 5.67148864e-01 2.99285948e-01 -1.13371539e+00
-1.81051408e-04 -1.29182264e-01 -4.34411943e-01 2.48180758e-02
5.25444925e-01 -5.47345281e-01 -1.37024748e+00 7.91791081e-01
-1.34533632e+00 -2.92610496e-01 2.01302052e-01 8.06923211e-02
-6.76629692e-02 3.51840079e-01 -5.67634881e-01 -7.47076809e-01
-5.87714314e-01 -1.53826571e+00 9.44415808e-01 7.14275911e-02
-2.04546854e-01 -1.08060050e+00 -5.54084539e-01 2.14874864e-01
6.72806859e-01 2.77904749e-01 6.06989324e-01 -9.43807781e-01
-4.06458527e-01 -5.61882973e-01 -2.70586967e-01 5.03957450e-01
8.09579939e-02 -1.09537125e-01 -1.33937192e+00 -7.13429272e-01
4.92957570e-02 -3.01144551e-02 7.40477204e-01 3.05700272e-01
1.59022808e+00 -6.74348354e-01 -5.73087156e-01 9.30628717e-01
1.19499838e+00 1.70940667e-01 5.78748524e-01 3.96904945e-01
8.44119370e-01 5.89763403e-01 2.74221301e-01 8.35180879e-02
7.76302740e-02 9.24969494e-01 7.18651593e-01 -1.40776828e-01
9.64695886e-02 -1.37628078e-01 4.46162224e-01 3.89184743e-01
1.26316026e-02 -4.74352032e-01 -8.53183031e-01 2.24147573e-01
-1.56962335e+00 -9.48838174e-01 -1.27197534e-01 2.35284472e+00
3.31739753e-01 2.55032778e-01 1.71803728e-01 5.76240420e-01
7.46230721e-01 3.87125254e-01 -3.15194041e-01 -6.73509240e-01
9.51302722e-02 5.47940433e-01 9.74267304e-01 7.35159159e-01
-1.13623989e+00 9.74807322e-01 6.08001423e+00 1.17211401e+00
-1.52470911e+00 4.38515991e-01 6.31983101e-01 -1.91132873e-01
1.18094176e-01 -1.97098896e-01 -8.69915128e-01 5.43097615e-01
1.23747396e+00 6.18412852e-01 7.16157198e-01 9.68065381e-01
8.17790702e-02 3.22828859e-01 -8.75405312e-01 1.19353259e+00
-1.43779844e-01 -1.26448345e+00 -1.18697762e-01 3.87272328e-01
3.60314995e-01 1.57168493e-01 1.60166368e-01 -5.07914051e-02
3.01232561e-03 -9.85572696e-01 4.42070305e-01 -2.45327681e-01
1.01335216e+00 -1.05999422e+00 1.04084051e+00 2.78622270e-01
-1.02817202e+00 -3.17800373e-01 -3.31491351e-01 1.85363442e-01
3.41982916e-02 6.19735003e-01 -1.05394411e+00 5.08192062e-01
7.72439241e-01 3.69110435e-01 -6.63684964e-01 5.94526112e-01
-6.96187094e-02 7.04619169e-01 -6.85501277e-01 -1.98895440e-01
4.48743533e-03 2.09285647e-01 4.48594600e-01 1.35707045e+00
3.91988784e-01 -6.76174939e-01 -2.63488144e-01 1.15221620e-01
-2.02464104e-01 -1.13958567e-01 -6.80630147e-01 7.89654553e-02
7.01131821e-01 1.11245573e+00 -7.53412247e-01 -3.65147829e-01
-1.49920909e-03 1.00314641e+00 2.08793521e-01 1.96365416e-01
-1.02041316e+00 -4.22943830e-01 9.25966263e-01 3.81529003e-01
4.82992291e-01 -9.35223997e-02 -2.69513845e-01 -9.11829412e-01
-4.14301753e-02 -1.05651736e+00 2.51556605e-01 -1.41357973e-01
-6.90634131e-01 8.34317148e-01 -1.47793964e-01 -8.56518269e-01
-3.97082508e-01 -9.03553367e-01 -1.78241298e-01 4.90523279e-01
-1.37282741e+00 -1.14587116e+00 -1.69112056e-01 7.57514596e-01
4.93111238e-02 -3.06410372e-01 9.87062871e-01 7.17189372e-01
-7.32638061e-01 1.20348632e+00 6.00911789e-02 6.18533343e-02
4.97191221e-01 -6.58237994e-01 6.79233372e-01 8.75710845e-01
8.68914127e-02 9.34334278e-01 5.72367489e-01 -6.08386874e-01
-1.21202719e+00 -1.02993166e+00 1.05191553e+00 -2.68613696e-01
3.47960085e-01 -5.83924651e-01 -7.11893559e-01 5.53816617e-01
7.92469308e-02 1.49775907e-01 5.39747715e-01 6.74561784e-02
-5.31365871e-01 -4.44596946e-01 -1.54990637e+00 3.84857982e-01
9.95312750e-01 -6.59788013e-01 4.22287643e-01 2.43627146e-01
6.07173145e-01 -4.27386492e-01 -5.09155869e-01 3.81100535e-01
8.00626397e-01 -1.32000101e+00 1.06962824e+00 -3.78712595e-01
-1.54457033e-01 -2.04138115e-01 7.47964578e-03 -6.88993573e-01
-2.90454049e-02 -1.02763045e+00 -6.76615894e-01 1.12499738e+00
4.02467817e-01 -1.05121338e+00 1.10338390e+00 2.30261430e-01
5.93571603e-01 -8.45663249e-01 -1.20903671e+00 -7.40810692e-01
-3.87153924e-01 -8.15272391e-01 1.17888045e+00 9.00781393e-01
-5.63400030e-01 6.37665316e-02 -8.28281760e-01 3.96054715e-01
5.10822713e-01 -4.82867986e-01 1.05284750e+00 -1.26484215e+00
-5.52651405e-01 -3.23373765e-01 -4.44576025e-01 -1.04255068e+00
2.16211140e-01 -7.50649214e-01 -3.23855788e-01 -8.13356459e-01
-4.33953434e-01 -7.53899336e-01 -3.47701699e-01 6.11436903e-01
2.64171720e-01 5.42615056e-01 1.98427930e-01 3.20974961e-02
-1.59029737e-01 -1.69044346e-01 8.15412998e-01 -1.64266139e-01
-2.39246815e-01 4.46998835e-01 -2.19429985e-01 6.99964643e-01
1.09773505e+00 -6.88782811e-01 -5.99018872e-01 -5.24683595e-01
2.70310760e-01 -1.37377575e-01 5.52640021e-01 -1.20510447e+00
2.18676820e-01 3.54398459e-01 3.49800110e-01 -3.93462241e-01
5.22357285e-01 -1.28633988e+00 3.55339706e-01 8.69456112e-01
1.29421055e-01 1.38006821e-01 2.18129322e-01 3.17358226e-01
2.70988166e-01 -2.08607942e-01 8.92432630e-01 3.16760093e-01
-1.70097381e-01 4.29202557e-01 -1.83072895e-01 -6.14537537e-01
8.45341384e-01 -5.21946192e-01 -3.01591963e-01 -1.84069321e-01
-4.89662439e-01 -9.72428024e-02 5.13295114e-01 4.54975069e-01
3.28718036e-01 -9.39908028e-01 -1.83617026e-01 6.43512189e-01
-3.44013572e-01 -4.42205593e-02 2.14898422e-01 7.22959518e-01
-8.44459772e-01 5.16557753e-01 -2.46267959e-01 -6.58321202e-01
-1.67148972e+00 7.53920436e-01 3.98857266e-01 -5.05223036e-01
-3.57258677e-01 7.36170709e-01 -3.52405787e-01 -5.32149076e-01
4.64943767e-01 9.66548324e-02 -1.13561749e-01 2.20827330e-02
7.90553749e-01 6.65829420e-01 3.24336290e-01 -6.60178304e-01
-5.82345605e-01 2.44587079e-01 -8.06368813e-02 7.55356997e-02
1.20458806e+00 -1.20206224e-02 -3.18575978e-01 -2.30379462e-01
1.47986305e+00 1.46707192e-01 -8.42390060e-01 4.86408100e-02
-1.04298890e-01 -4.25761282e-01 -8.11067894e-02 -4.75305378e-01
-1.38031054e+00 9.64034021e-01 8.40481162e-01 4.30150688e-01
1.18086720e+00 -5.15404046e-01 9.65696692e-01 5.73795974e-01
6.71967089e-01 -7.48556077e-01 -2.58969307e-01 3.54025215e-01
2.05650643e-01 -8.90358448e-01 -2.11897194e-01 -5.58352768e-01
-9.27206725e-02 9.77638781e-01 4.67419863e-01 8.50877389e-02
8.58676493e-01 3.72700751e-01 -5.89681603e-02 -2.98353825e-02
-1.54400051e-01 3.55387062e-01 -2.37615168e-01 9.09499228e-01
-3.85918468e-02 1.27073586e-01 -7.93985501e-02 2.23943274e-02
-4.68888402e-01 -4.66421572e-03 1.42683789e-01 8.01320016e-01
7.31547475e-02 -1.50261986e+00 -2.08947048e-01 3.65449816e-01
-7.97128677e-01 9.57550406e-02 -1.67404026e-01 5.48479319e-01
6.03917360e-01 1.21624684e+00 9.16792825e-02 -8.68743181e-01
-6.98976144e-02 -1.67350948e-01 2.29553625e-01 -8.35152119e-02
-9.57207918e-01 -4.09437299e-01 2.49360010e-01 -7.78271258e-01
-3.23192060e-01 -3.05232048e-01 -7.14560807e-01 -1.02373755e+00
-5.19539833e-01 1.06976025e-01 9.76056993e-01 8.35065663e-01
7.11663008e-01 3.38746637e-01 6.91780806e-01 -8.87857080e-01
-2.19124824e-01 -7.78270423e-01 -1.47286922e-01 -6.85712248e-02
7.11208820e-01 -5.11249006e-01 -1.31365567e-01 -3.55188578e-01] | [13.107894897460938, 1.163994312286377] |
1e6606ca-9277-40e2-8bb0-fe6a88f6d5b1 | global-road-damage-detection-state-of-the-art | 2011.08740 | null | https://arxiv.org/abs/2011.08740v1 | https://arxiv.org/pdf/2011.08740v1.pdf | Global Road Damage Detection: State-of-the-art Solutions | This paper summarizes the Global Road Damage Detection Challenge (GRDDC), a Big Data Cup organized as a part of the IEEE International Conference on Big Data'2020. The Big Data Cup challenges involve a released dataset and a well-defined problem with clear evaluation metrics. The challenges run on a data competition platform that maintains a leaderboard for the participants. In the presented case, the data constitute 26336 road images collected from India, Japan, and the Czech Republic to propose methods for automatically detecting road damages in these countries. In total, 121 teams from several countries registered for this competition. The submitted solutions were evaluated using two datasets test1 and test2, comprising 2,631 and 2,664 images. This paper encapsulates the top 12 solutions proposed by these teams. The best performing model utilizes YOLO-based ensemble learning to yield an F1 score of 0.67 on test1 and 0.66 on test2. The paper concludes with a review of the facets that worked well for the presented challenge and those that could be improved in future challenges. | ['Yoshihide Sekimoto', 'Takehiro Kashiyama', 'Hiroshi Omata', 'Durga Toshniwal', 'Sanjay Kumar Ghosh', 'Hiroya Maeda', 'Deeksha Arya'] | 2020-11-17 | null | null | null | null | ['road-damage-detection'] | ['computer-vision'] | [-3.96791995e-01 8.39414150e-02 7.89939463e-02 -5.37103079e-02
-1.20738411e+00 -1.47432208e-01 5.92523038e-01 2.69804839e-02
-3.34383368e-01 7.69268394e-01 6.50727987e-01 2.34237045e-01
-1.17402665e-01 -9.34563875e-01 -6.20165348e-01 -5.99754572e-01
-2.18944669e-01 3.31854373e-01 2.69406170e-01 -3.62308830e-01
3.52082074e-01 3.66137624e-01 -2.00886774e+00 6.01776540e-01
1.19722390e+00 8.24926674e-01 4.37071576e-05 8.30629766e-01
2.82494247e-01 9.38300371e-01 -8.71372700e-01 -3.35684925e-01
1.80877477e-01 -2.19836347e-02 -9.52953637e-01 -2.23091692e-01
8.72709334e-01 2.78113987e-02 -2.43603095e-01 5.96446335e-01
8.02969813e-01 -6.40100762e-02 5.86548150e-01 -1.31655514e+00
-7.05588579e-01 2.12719828e-01 -4.92588282e-01 5.04534721e-01
2.51817137e-01 -4.77795117e-02 9.29105639e-01 -1.01317203e+00
8.74784291e-01 1.09255672e+00 7.08539903e-01 1.92380086e-01
-6.42861545e-01 -2.33435005e-01 -3.38080861e-02 9.73379731e-01
-1.25821257e+00 -2.55454838e-01 2.55695373e-01 -7.29547501e-01
1.27813828e+00 4.09879506e-01 9.31350812e-02 7.90804386e-01
1.03922725e-01 7.35439956e-01 1.23868728e+00 -3.26030493e-01
3.06493849e-01 -5.71341105e-02 5.59358895e-01 3.10613781e-01
4.22394484e-01 2.77023733e-01 -3.60089213e-01 1.40481979e-01
-1.98457986e-01 -3.58489037e-01 1.07328817e-01 1.06313668e-01
-9.57590759e-01 8.48027706e-01 5.72994590e-01 3.08830757e-03
-5.10421813e-01 -1.39505103e-01 4.91151273e-01 4.75390404e-01
7.23536491e-01 1.16599686e-01 -1.88712895e-01 -2.65923202e-01
-4.06152278e-01 5.87854981e-01 6.26606226e-01 5.72268426e-01
6.75778925e-01 -1.02304868e-01 -4.90644798e-02 1.19621515e+00
3.04361526e-02 4.78108823e-01 -1.05670229e-01 -1.14427841e+00
1.10319841e+00 5.89121401e-01 1.16955139e-01 -1.14831591e+00
-7.26575732e-01 -1.39870215e-02 -8.74017894e-01 3.59290600e-01
3.07287872e-01 -5.55521786e-01 -9.71131444e-01 9.94658709e-01
2.54924864e-01 1.89490438e-01 1.09362140e-01 8.16469312e-01
1.19607961e+00 7.05485046e-01 -7.36719221e-02 3.40340942e-01
1.37832618e+00 -1.28118575e+00 -6.18472874e-01 -1.18329450e-01
8.54970276e-01 -6.46529496e-01 8.80972683e-01 7.24487007e-01
-9.05421674e-01 -7.72947967e-01 -1.02323961e+00 -1.01793587e-01
-1.01959491e+00 -1.03050739e-01 7.40380138e-02 7.80188203e-01
-9.85337138e-01 4.87714499e-01 -2.06341356e-01 -5.80785930e-01
5.87522566e-01 -2.26647466e-01 -4.13240403e-01 -4.12016362e-01
-1.24208117e+00 1.26585066e+00 3.52351442e-02 2.94136435e-01
-9.56351578e-01 -7.07203746e-01 -5.74941874e-01 -3.32409710e-01
1.10022679e-01 -2.43353799e-01 6.98434830e-01 4.76372913e-02
-6.39486730e-01 1.08427870e+00 2.51859576e-01 -6.92462742e-01
4.84560698e-01 -8.55642378e-01 -1.01725364e+00 3.37235890e-02
4.61855352e-01 5.10930061e-01 2.94049293e-01 -1.12477815e+00
-1.30088174e+00 -5.38432777e-01 -1.38476431e-01 4.39729169e-02
-3.28549370e-02 5.11237860e-01 -5.68105042e-01 -5.55693805e-01
-5.08024633e-01 -8.95622194e-01 -3.92394394e-01 -9.08553541e-01
-5.14530420e-01 -3.77837062e-01 9.74143505e-01 -7.76093245e-01
1.37824190e+00 -2.04113865e+00 -1.70620546e-01 2.01728687e-01
2.77558506e-01 2.82403529e-01 -2.73794830e-01 9.09210324e-01
-1.06438451e-01 4.13940370e-01 -2.03270242e-01 -3.14530551e-01
-2.10247204e-01 2.06584692e-01 -3.33363593e-01 5.95222473e-01
7.24547580e-02 6.73874438e-01 -4.67794329e-01 -1.60388336e-01
2.58387893e-01 3.29411089e-01 5.06928340e-02 2.91726217e-02
4.21058863e-01 1.35127157e-01 -1.78082809e-01 5.91439605e-01
8.44713986e-01 3.12232733e-01 -4.25587475e-01 8.14461485e-02
-5.28139293e-01 2.92016212e-02 -1.18732750e+00 1.19524276e+00
-1.49941862e-01 8.36295009e-01 -7.98150748e-02 -1.05163980e+00
1.09596241e+00 2.63161659e-01 5.55646896e-01 -1.02084851e+00
-2.49642253e-01 2.84482419e-01 -4.39602464e-01 -9.33010817e-01
6.30317748e-01 3.56544912e-01 -4.28780794e-01 2.85724610e-01
-3.77011627e-01 -1.64208338e-01 5.75686693e-01 1.44466311e-01
1.32819533e+00 -2.50630558e-01 -1.63045362e-01 -1.55739471e-01
5.17261863e-01 2.00045153e-01 6.37102783e-01 6.42431974e-01
-5.08163154e-01 1.20153189e+00 5.27222812e-01 -9.53533828e-01
-1.13998163e+00 -6.85610294e-01 -1.67724282e-01 8.59696329e-01
-4.71518114e-02 -5.66629529e-01 -8.08268547e-01 -5.71946979e-01
-5.29898293e-02 4.78852928e-01 -8.45187545e-01 2.46605799e-01
-6.38918102e-01 -1.07817030e+00 8.67372215e-01 4.54870462e-01
7.47942328e-01 -1.27486134e+00 -4.94638503e-01 -8.68563056e-02
-4.72408414e-01 -1.16884387e+00 9.53882560e-02 -3.44374269e-01
-6.43601000e-01 -1.27461112e+00 -6.41983867e-01 -7.05985785e-01
1.99161932e-01 4.08800185e-01 1.21012616e+00 3.10784560e-02
-5.74632823e-01 2.45901607e-02 -7.01442599e-01 -7.22170115e-01
1.67075023e-01 3.07127506e-01 -2.97322899e-01 -1.07166775e-01
4.77656573e-01 -3.98186855e-02 -3.72854173e-01 7.35693157e-01
-4.09318209e-01 -3.21233600e-01 3.52366656e-01 4.66557920e-01
4.74951655e-01 1.69991419e-01 1.05791819e+00 -8.21304202e-01
6.44072294e-01 -6.77937925e-01 -5.63743889e-01 5.99962138e-02
-7.12735593e-01 -4.44368988e-01 2.17542738e-01 6.56158507e-01
-1.07606626e+00 -9.22009721e-02 -2.61401385e-01 2.48084605e-01
-4.65334058e-01 5.82972586e-01 -2.94089645e-01 2.24453807e-01
9.64739442e-01 -5.07179260e-01 -2.16971233e-01 -8.89216006e-01
4.18620735e-01 1.01431072e+00 8.09451222e-01 -4.13292706e-01
6.61445856e-01 4.84797686e-01 -3.24180037e-01 -1.09174812e+00
-8.76752079e-01 -9.69610810e-01 -6.34041190e-01 -3.77271593e-01
1.10345674e+00 -1.22978950e+00 -3.23860288e-01 1.10814154e+00
-1.06777799e+00 -2.73976743e-01 -3.91364008e-01 2.12137341e-01
-3.14570993e-01 8.07358176e-02 -3.30443084e-01 -4.92419153e-01
-4.85296935e-01 -8.37930620e-01 1.17527223e+00 2.29965881e-01
5.79960048e-02 -8.47824395e-01 7.30107725e-01 1.10214102e+00
5.56028306e-01 8.86475146e-01 3.01401466e-01 -2.63519287e-01
-4.12426591e-01 -8.61312151e-01 -5.51617384e-01 4.31141973e-01
-2.21731201e-01 2.22591817e-01 -1.46223962e+00 -6.88237697e-02
-6.45518124e-01 -6.09180391e-01 1.46370196e+00 4.02160913e-01
1.08826435e+00 8.43697116e-02 -2.54765213e-01 1.90796591e-02
1.35936213e+00 -1.12588726e-01 1.55298948e+00 8.17470849e-01
8.11583996e-01 9.79593694e-01 8.00828576e-01 2.53536552e-01
1.05889249e+00 6.34356618e-01 6.83723211e-01 -1.42540962e-01
-4.21785682e-01 1.19095862e-01 4.21545774e-01 5.31957686e-01
-7.66277790e-01 -9.77019072e-02 -1.44832253e+00 9.61063206e-01
-1.81636095e+00 -1.30833256e+00 -1.10894656e+00 2.19080448e+00
2.02282295e-01 1.08708814e-01 5.85131109e-01 4.17703569e-01
6.47521734e-01 4.22198057e-01 3.07530444e-02 -6.13424182e-01
-7.41307259e-01 1.01302996e-01 6.38410628e-01 4.52470422e-01
-1.45948398e+00 8.11982572e-01 6.64474726e+00 6.37101829e-01
-6.19289041e-01 3.19161892e-01 4.18089688e-01 -1.44737616e-01
9.04706642e-02 -1.33015409e-01 -1.11044371e+00 3.60228717e-01
1.58198822e+00 -5.66205978e-02 -2.92520914e-02 5.69120169e-01
4.63849783e-01 -2.23884583e-01 -2.49147221e-01 5.43076873e-01
1.59528002e-01 -1.42568517e+00 -5.88529050e-01 5.48582375e-01
1.16663742e+00 1.03921008e+00 -1.35062292e-01 5.83156884e-01
3.13171566e-01 -1.28124130e+00 3.67396355e-01 6.47678494e-01
4.50425804e-01 -7.96277106e-01 1.08919406e+00 1.62856996e-01
-9.32440102e-01 -5.13499498e-01 -7.26275146e-01 -3.79446656e-01
3.20053786e-01 8.32099020e-01 -4.27271426e-01 1.03759456e+00
1.38185692e+00 1.17069399e+00 -9.36217546e-01 1.48404717e+00
-3.27899903e-01 8.44681203e-01 -1.58223167e-01 4.52601552e-01
2.67769337e-01 8.53432119e-02 3.91992211e-01 1.17966235e+00
3.28555107e-01 -1.40582904e-01 2.09750667e-01 -1.17261626e-01
-1.08285517e-01 -2.89824512e-02 -9.08004522e-01 6.39285564e-01
4.17591929e-01 1.40843916e+00 -1.09602392e-01 -2.35540092e-01
-4.30727988e-01 4.48269129e-01 2.34784573e-01 1.84206903e-01
-6.39212012e-01 -5.73321342e-01 6.31639957e-01 1.87726226e-02
6.58033937e-02 9.58962590e-02 -7.98160672e-01 -8.12067270e-01
1.03080291e-02 -7.98299432e-01 8.65468442e-01 -8.73240590e-01
-1.36043894e+00 6.56237066e-01 -9.88227036e-03 -1.48508418e+00
1.61028907e-01 -4.56125498e-01 -9.63149190e-01 9.15499985e-01
-1.74162245e+00 -1.30858815e+00 -8.32473457e-01 4.31350052e-01
5.62074065e-01 -2.77278364e-01 8.06891739e-01 7.51898646e-01
-1.08674014e+00 2.05932096e-01 3.07408333e-01 -1.62029509e-02
8.90979171e-01 -1.41841614e+00 8.52677524e-01 9.92245257e-01
-1.34808227e-01 -2.32697546e-01 3.78297120e-01 -5.71868360e-01
-5.96374512e-01 -1.43715811e+00 1.60397398e+00 -1.03349423e+00
3.87261033e-01 2.20036115e-02 -8.86085033e-01 3.16982478e-01
5.25205135e-01 1.95410684e-01 5.75446784e-01 3.72833818e-01
-3.58669847e-01 -4.70067084e-01 -1.02659214e+00 -4.83051538e-02
7.19600976e-01 -2.70390451e-01 -4.46554124e-01 4.87861037e-01
2.39941284e-01 -2.98347205e-01 -1.02671385e+00 2.31148884e-01
4.16103482e-01 -1.10090768e+00 1.07717621e+00 -7.78598309e-01
6.85121357e-01 -3.42934489e-01 -3.34047884e-01 -1.39823115e+00
-1.94703519e-01 -1.98382437e-01 1.12074107e-01 1.18928099e+00
4.92488086e-01 -4.14190739e-01 6.59086049e-01 4.72403795e-01
-7.41180956e-01 -4.76717889e-01 -1.13841128e+00 -1.05023909e+00
5.25203347e-01 -8.97650838e-01 4.66338128e-01 5.66587389e-01
-3.42263669e-01 3.41367543e-01 -7.11850762e-01 3.11022431e-01
9.43124890e-01 -3.01369756e-01 1.17534709e+00 -1.61368144e+00
7.28891790e-01 -3.20834488e-01 -7.44112015e-01 -2.15219408e-01
-3.94082546e-01 -6.40706897e-01 -9.65262055e-02 -1.98173058e+00
-1.36842564e-01 -4.07484502e-01 -3.64459544e-01 7.60503829e-01
-2.21775323e-01 5.72698176e-01 1.86043486e-01 3.66395622e-01
-6.38217747e-01 3.15869600e-01 8.66792440e-01 -2.05722943e-01
4.33900729e-02 9.51367393e-02 -9.07811284e-01 4.16424185e-01
1.00464165e+00 -3.27610582e-01 -6.57004192e-02 -6.13559008e-01
3.49974394e-01 -6.41288877e-01 5.14471471e-01 -1.19849539e+00
1.05693854e-01 1.14559578e-02 -3.35962214e-02 -1.10735309e+00
3.61711755e-02 -4.73589659e-01 -1.94997657e-02 2.61952698e-01
-4.47809100e-02 3.18531655e-02 1.74137056e-01 3.39804411e-01
-5.13861120e-01 4.25056629e-02 6.78538144e-01 2.96356410e-01
-1.26970637e+00 -2.44284701e-02 -2.42270961e-01 4.07449037e-01
1.38539946e+00 -2.05188572e-01 -1.00026309e+00 -1.93032533e-01
-6.84932768e-01 8.66943121e-01 -4.70934696e-02 1.07838809e+00
6.74017370e-01 -1.38728166e+00 -1.51230693e+00 -8.42851475e-02
5.05746305e-01 -4.06219363e-02 8.08992445e-01 1.10840797e+00
-5.42715251e-01 5.25093734e-01 -3.71478915e-01 -2.91526735e-01
-1.39498258e+00 2.72864252e-01 1.66644737e-01 -5.12627423e-01
-7.39539027e-01 4.36762720e-01 -4.34773237e-01 -8.26884151e-01
-1.96403870e-03 4.59082536e-02 -7.45502710e-01 5.09301960e-01
9.81126189e-01 1.28578699e+00 6.38338327e-01 -7.41667807e-01
-4.38266695e-01 8.32200468e-01 1.58697829e-01 1.33210614e-01
1.85886979e+00 -3.85912418e-01 5.92381544e-02 2.87294835e-01
1.03958690e+00 -1.63229018e-01 -8.25049162e-01 7.70845115e-02
4.27332282e-01 -4.21338111e-01 1.54210076e-01 -1.28663385e+00
-1.16806042e+00 1.10973895e+00 8.93030941e-01 4.05014843e-01
1.03615749e+00 8.48686248e-02 9.29928958e-01 2.36599833e-01
2.93448776e-01 -1.57995713e+00 -2.47816056e-01 7.38642573e-01
1.54564714e+00 -1.38509858e+00 -1.43068790e-01 -9.74526033e-02
-9.36266065e-01 8.41923594e-01 5.59248388e-01 -2.81054825e-01
7.80026615e-01 -2.40097567e-02 2.47607693e-01 -6.08994484e-01
-8.28279674e-01 -4.78657931e-01 3.21944058e-01 1.00245249e+00
8.75555426e-02 1.18970640e-01 -4.17185456e-01 3.70437354e-01
-1.36413306e-01 1.70995608e-01 7.74617553e-01 7.78497934e-01
-8.72023284e-01 -1.03149521e+00 -7.12317526e-01 4.60195839e-01
-2.97892272e-01 2.71321207e-01 -6.17049873e-01 7.30867445e-01
3.17440063e-01 1.42475700e+00 -3.62079144e-02 -6.05571508e-01
1.09154820e+00 -4.06773150e-01 -2.57964849e-01 -5.03366351e-01
-5.29231966e-01 -2.44052514e-01 8.30082536e-01 -6.76407218e-01
-3.97010595e-01 -8.22519660e-01 -1.11530316e+00 -6.07665718e-01
8.19696188e-02 6.31265640e-02 7.25861967e-01 6.18788123e-01
7.31580913e-01 2.65703827e-01 9.18148100e-01 -6.00705504e-01
-1.27860278e-01 -1.06971693e+00 -6.67570174e-01 3.74521524e-01
2.47244969e-01 -6.85772300e-01 -2.51888752e-01 1.21199466e-01] | [7.428684234619141, 1.104286789894104] |
23ed4570-f516-4950-ae65-8993f7e17acb | opera-operation-pivoted-discrete-reasoning-1 | null | null | https://aclanthology.org/2022.naacl-main.119 | https://aclanthology.org/2022.naacl-main.119.pdf | OPERA: Operation-Pivoted Discrete Reasoning over Text | Machine reading comprehension (MRC) that requires discrete reasoning involving symbolic operations, e.g., addition, sorting, and counting, is a challenging task. According to this nature, semantic parsing-based methods predict interpretable but complex logical forms. However, logical form generation is nontrivial and even a little perturbation in a logical form will lead to wrong answers. To alleviate this issue, multi-predictor -based methods are proposed to directly predict different types of answers and achieve improvements. However, they ignore the utilization of symbolic operations and encounter a lack of reasoning ability and interpretability. To inherit the advantages of these two types of methods, we propose OPERA, an operation-pivoted discrete reasoning framework, where lightweight symbolic operations (compared with logical forms) as neural modules are utilized to facilitate the reasoning ability and interpretability. Specifically, operations are first selected and then softly executed to simulate the answer reasoning procedure. Extensive experiments on both DROP and RACENum datasets show the reasoning ability of OPERA. Moreover, further analysis verifies its interpretability. | ['Tiejun Zhao', 'Xiaodong He', 'Youzheng Wu', 'Jing Zhao', 'Yifan Wang', 'Jiahui Liang', 'Haipeng Sun', 'Chaoqun Duan', 'Junwei Bao', 'Yongwei Zhou'] | null | null | null | null | naacl-2022-7 | ['machine-reading-comprehension'] | ['natural-language-processing'] | [ 4.22733188e-01 2.45500535e-01 1.05150767e-01 -7.22321570e-01
-2.19022706e-01 -5.24822891e-01 2.82469898e-01 2.77761668e-01
4.30382378e-02 5.28200150e-01 8.00765306e-02 -8.29112828e-01
-1.62218645e-01 -1.29572463e+00 -8.23008835e-01 -1.03677124e-01
4.16402251e-01 2.53779739e-01 3.05605769e-01 -4.13773537e-01
4.34571534e-01 1.19675202e-02 -1.86801052e+00 7.35627353e-01
1.58064651e+00 1.01872170e+00 7.07207471e-02 3.47628832e-01
-8.90731335e-01 1.31639957e+00 -5.50656259e-01 -4.85098600e-01
-5.07359989e-02 -5.36524832e-01 -1.07830226e+00 -4.71687555e-01
-2.61740703e-02 -6.64845824e-01 4.20468068e-03 9.93349910e-01
-1.27855316e-02 2.52105426e-02 2.78272033e-01 -1.30359781e+00
-7.85380721e-01 9.42017496e-01 -7.59227648e-02 -1.97905824e-01
1.16876197e+00 3.33161056e-01 1.07333422e+00 -6.45306766e-01
2.20125660e-01 1.59593344e+00 4.71201956e-01 5.22605062e-01
-8.20163548e-01 -6.26536727e-01 4.72679853e-01 6.07230961e-01
-1.10574949e+00 -3.11798036e-01 7.08881676e-01 1.13872960e-02
9.81545568e-01 5.61264455e-01 5.89746654e-01 7.18391597e-01
4.99369651e-02 1.19126105e+00 1.26366901e+00 -5.04342973e-01
4.34408933e-01 -1.21686392e-01 5.97250462e-01 9.61324334e-01
2.90134728e-01 -3.29752922e-01 -5.58821857e-01 1.63314164e-01
2.61170208e-01 1.21878460e-01 -2.87776142e-01 7.62733072e-02
-1.05519080e+00 5.56293666e-01 4.41128701e-01 -2.00843415e-03
-1.78734869e-01 -4.73754518e-02 5.11152387e-01 4.38058704e-01
-2.44690299e-01 5.66173136e-01 -4.79657531e-01 -2.43592069e-01
-5.40923774e-01 2.46701360e-01 1.02467227e+00 1.10895193e+00
6.18100643e-01 -8.54876935e-02 -3.62186462e-01 3.66716206e-01
2.95049936e-01 4.92020518e-01 5.21090090e-01 -8.06693077e-01
5.90134144e-01 1.51654243e+00 -4.95099649e-02 -1.19184065e+00
-5.59623659e-01 -1.72072232e-01 -7.03345180e-01 6.59523159e-02
3.46766382e-01 1.41802356e-01 -5.47780812e-01 1.68741167e+00
3.69545370e-01 1.36201158e-01 2.38121137e-01 9.70180392e-01
9.27088439e-01 6.24956906e-01 1.46857366e-01 -1.00674681e-01
1.58081734e+00 -9.79511857e-01 -8.45632732e-01 -2.02075273e-01
6.69880629e-01 -2.62696207e-01 1.56446588e+00 5.77165008e-01
-1.16441596e+00 -5.12102425e-01 -1.22734153e+00 -3.14896494e-01
-4.15249497e-01 -1.21935569e-01 1.12358630e+00 3.84740978e-01
-5.42181730e-01 4.01504397e-01 -6.99299037e-01 1.01771221e-01
3.68711621e-01 2.44890079e-01 -3.32982168e-02 -3.66778344e-01
-1.44178748e+00 6.81928039e-01 7.33000100e-01 4.05203253e-01
-3.75388771e-01 -4.22770917e-01 -9.89967883e-01 4.90973383e-01
7.74272621e-01 -7.61390984e-01 1.33755195e+00 -1.01173043e+00
-1.60648513e+00 3.23815078e-01 -5.02671361e-01 -3.30822080e-01
4.58609045e-01 -3.70906085e-01 -3.25828165e-01 2.04274401e-01
-3.54393609e-02 2.53974944e-01 5.36081731e-01 -9.44742560e-01
-5.53601921e-01 -3.84861290e-01 7.36948907e-01 1.70857579e-01
-1.91094950e-01 -1.22833088e-01 -1.51806623e-01 -1.85922816e-01
6.43332303e-01 -4.47127134e-01 1.65146530e-01 -1.20414518e-01
-5.45908630e-01 -3.61059070e-01 3.39129239e-01 -8.93820465e-01
1.45674086e+00 -1.86873651e+00 7.86805153e-02 1.83823287e-01
3.97587270e-01 1.30713895e-01 4.79619429e-02 9.79986563e-02
6.67993054e-02 3.27439934e-01 -2.33528614e-01 9.17892009e-02
4.46110576e-01 3.32253247e-01 -4.55252707e-01 -2.01260567e-01
5.30962527e-01 1.03180349e+00 -9.13235188e-01 -4.87998337e-01
9.45965126e-02 -3.91092628e-01 -8.57784033e-01 4.12047297e-01
-7.80450881e-01 1.77604929e-01 -7.27229714e-01 1.00602317e+00
9.17571723e-01 -2.90902734e-01 3.79522532e-01 3.24207470e-02
1.17447205e-01 6.53084397e-01 -1.26429927e+00 1.51343262e+00
-8.23267937e-01 -2.41399799e-02 -1.83775753e-01 -9.55372036e-01
9.01006103e-01 3.30079198e-02 -4.03677046e-01 -9.88441944e-01
7.07063302e-02 4.33925748e-01 2.71151960e-01 -7.89289594e-01
3.94212842e-01 -5.34681454e-02 -1.71230733e-01 4.58803535e-01
-5.06034434e-01 1.93044525e-02 1.55423209e-01 1.70313284e-01
1.31013906e+00 5.84681153e-01 5.06389022e-01 1.06739335e-01
9.93333817e-01 1.30142376e-01 7.65958250e-01 7.65781105e-01
5.40231774e-03 1.69771150e-01 8.36985826e-01 -5.96281707e-01
-5.91481090e-01 -8.89560282e-01 1.62256941e-01 1.05805004e+00
5.18848777e-01 -6.09992921e-01 -8.25020432e-01 -6.20814681e-01
-1.97699264e-01 1.13494432e+00 -1.19154744e-01 -5.07140696e-01
-8.68471146e-01 -4.10843760e-01 5.50322711e-01 7.53312528e-01
8.81797850e-01 -1.17104077e+00 -8.27380776e-01 1.64701939e-01
-4.79314804e-01 -1.02020645e+00 2.04053953e-01 5.43974712e-03
-7.57317543e-01 -1.09113979e+00 2.52342761e-01 -6.48143589e-01
8.55119765e-01 8.72097984e-02 1.19260585e+00 7.31464982e-01
1.26971960e-01 -1.61339983e-01 -7.13678300e-01 -2.71060735e-01
-3.72605741e-01 -2.25354861e-02 -2.69850969e-01 -1.69441327e-01
6.63285553e-01 -5.41631520e-01 -4.72471923e-01 1.75427929e-01
-8.55750084e-01 5.91636717e-01 6.50181472e-01 9.33600962e-01
3.42565179e-01 2.05789074e-01 5.70766628e-01 -7.95172751e-01
8.50830436e-01 -4.84809995e-01 -5.04196942e-01 6.96219563e-01
-5.44831097e-01 4.45473284e-01 1.37507987e+00 -1.22297034e-01
-1.35330701e+00 -1.80783346e-01 -3.37760374e-02 5.48126129e-03
-3.07438999e-01 6.90099478e-01 -5.68639159e-01 3.54852229e-01
4.18359995e-01 5.70503712e-01 -6.43305108e-02 -2.08857134e-01
2.11105779e-01 6.22027516e-01 4.80605036e-01 -1.23327005e+00
7.66910672e-01 7.68088102e-02 7.63657177e-03 6.55197799e-02
-8.61668646e-01 1.15978591e-01 -2.50055522e-01 5.22046424e-02
6.41127884e-01 -6.37731194e-01 -1.30613852e+00 3.35608959e-01
-1.44897056e+00 -1.07294112e-01 9.73411128e-02 9.76228118e-02
-4.94043648e-01 3.38445544e-01 -5.74115038e-01 -9.69693959e-01
-4.76091027e-01 -1.27917862e+00 9.15993154e-01 5.08476257e-01
-5.07687151e-01 -5.22434711e-01 -7.11393476e-01 5.60085773e-01
2.95193762e-01 1.39527991e-01 1.64307785e+00 -7.48562753e-01
-9.12363231e-01 -9.43110958e-02 -3.90314966e-01 1.73303843e-01
-1.69210136e-01 -6.56922832e-02 -7.75834203e-01 3.25414330e-01
4.06015255e-02 -4.70689833e-01 3.11772436e-01 -3.12171817e-01
1.70231259e+00 -4.80501026e-01 -2.22414024e-02 5.09158075e-01
1.10169613e+00 4.17937577e-01 8.16582263e-01 4.08032775e-01
3.56743038e-01 5.83291233e-01 7.37280726e-01 4.32512850e-01
8.28134954e-01 3.40016216e-01 4.36339378e-01 2.19589591e-01
1.56799972e-01 -5.92359960e-01 2.53754586e-01 8.23124170e-01
-1.36095256e-01 -7.51074329e-02 -9.92166877e-01 4.98426426e-03
-1.79181337e+00 -8.87475550e-01 -3.52722466e-01 1.93032157e+00
1.17294765e+00 3.38543296e-01 -3.85954678e-01 5.14411032e-01
4.98714209e-01 -1.05036467e-01 -6.72636330e-01 -6.36289179e-01
-2.44794916e-02 4.33742791e-01 -2.09882185e-01 3.79847020e-01
-4.74894315e-01 1.06998134e+00 5.25767517e+00 6.82380855e-01
-9.35301781e-01 -3.66178334e-01 4.73302603e-01 2.51041800e-01
-5.58113992e-01 1.95726410e-01 -5.90478897e-01 4.08106357e-01
5.14075100e-01 -4.26252633e-02 8.04340363e-01 8.95366371e-01
4.66605164e-02 -2.61024922e-01 -1.39171350e+00 6.40874326e-01
-1.52769879e-01 -9.82350767e-01 3.44521403e-01 -7.63728797e-01
4.86494489e-02 -1.05714476e+00 -2.62107134e-01 7.93534100e-01
1.17885144e-02 -1.20845616e+00 1.01079333e+00 6.85792685e-01
3.63319635e-01 -7.23406315e-01 8.53215635e-01 5.30070364e-01
-1.08541703e+00 -2.69726753e-01 -3.47281426e-01 -7.34488368e-01
6.37113154e-02 4.17148173e-01 -4.49053377e-01 7.73896158e-01
6.30014300e-01 5.14394104e-01 -7.97082543e-01 6.16346478e-01
-9.84886467e-01 5.79608202e-01 -2.87237674e-01 -4.66212481e-01
-1.02765501e-01 -8.21436122e-02 1.34214044e-01 7.23959088e-01
2.47358784e-01 5.17556667e-01 1.21713176e-01 1.25762737e+00
1.60934806e-01 1.65599957e-02 -1.12545088e-01 3.79481986e-02
7.40432799e-01 9.35943723e-01 -5.27549505e-01 -6.00065827e-01
-3.52951497e-01 8.76379609e-01 5.08526146e-01 2.93319076e-01
-1.14413142e+00 -6.42049074e-01 3.63265693e-01 6.26701415e-02
-4.88006882e-02 -9.84741673e-02 -1.01491547e+00 -1.41174221e+00
6.77827418e-01 -1.23659217e+00 2.30008632e-01 -1.09091091e+00
-9.17613864e-01 3.67871910e-01 1.13230139e-01 -8.94276857e-01
-9.15822759e-02 -7.00487018e-01 -9.04863119e-01 9.09028828e-01
-1.50639963e+00 -8.76356006e-01 -7.49924839e-01 3.30668420e-01
4.93262291e-01 1.30739197e-01 8.60288441e-01 -5.27712852e-02
-7.43972003e-01 8.01661432e-01 -5.53144872e-01 -5.30616269e-02
-2.95792092e-02 -1.27215147e+00 1.25246763e-01 7.96268702e-01
-4.96904194e-01 1.24659944e+00 4.99451697e-01 -3.93303305e-01
-1.88529384e+00 -7.05925226e-01 8.82654965e-01 -1.96972638e-01
5.93202174e-01 -3.57192665e-01 -1.18030953e+00 7.08055615e-01
-2.70019136e-02 -3.41429293e-01 5.55453420e-01 1.92291662e-01
-4.23875630e-01 -1.59048155e-01 -1.08767664e+00 9.68742132e-01
1.33586693e+00 -3.74098092e-01 -1.18865705e+00 1.77916065e-01
9.91630793e-01 -5.57735145e-01 -5.46870053e-01 4.03575599e-01
5.27859151e-01 -1.25005269e+00 8.10739100e-01 -7.34973073e-01
1.08383918e+00 -6.33224010e-01 -1.05599664e-01 -9.34828222e-01
-8.23367313e-02 -2.91924447e-01 -3.66382986e-01 1.26728249e+00
3.04708123e-01 -9.06244338e-01 4.90676731e-01 9.88098919e-01
-2.60255039e-01 -9.60010409e-01 -5.64752460e-01 -6.11280203e-01
-9.08467621e-02 -5.27691960e-01 1.26654065e+00 7.09507644e-01
4.29635435e-01 3.87764454e-01 1.25697017e-01 2.06112564e-01
2.07212150e-01 6.49052203e-01 7.32910573e-01 -1.11888814e+00
-4.26457256e-01 -4.85496670e-01 -9.87674668e-02 -1.21857274e+00
4.11277086e-01 -1.03584027e+00 3.58581096e-02 -1.50909686e+00
-6.10873140e-02 -6.03579581e-01 -1.78526059e-01 8.42936993e-01
-4.94397193e-01 -5.52619040e-01 1.32070988e-01 6.08345419e-02
-7.45736659e-01 4.56920892e-01 1.38129592e+00 -2.44003147e-01
8.64464641e-02 -1.51418447e-01 -8.07209492e-01 8.49342227e-01
8.83183181e-01 -1.27379447e-01 -5.75400710e-01 -6.27188146e-01
7.02149570e-01 3.30904871e-01 4.70835686e-01 -1.10363710e+00
2.10617915e-01 -5.18465996e-01 1.75623000e-01 -4.29162890e-01
5.22939898e-02 -7.28931129e-01 -1.22296318e-01 5.93368053e-01
-4.77501363e-01 2.16568783e-01 6.30933940e-02 2.83405811e-01
-3.99727911e-01 -4.12550211e-01 2.39690989e-01 -1.97307318e-01
-9.65206504e-01 -3.19356412e-01 -1.86368108e-01 8.52590203e-02
9.42412257e-01 -2.92813003e-01 -4.61104274e-01 -8.68270621e-02
-4.17031676e-01 5.10472894e-01 2.73470342e-01 1.68152437e-01
7.94035912e-01 -1.14528322e+00 -3.70377451e-01 2.89647669e-01
2.29611456e-01 6.65311038e-01 2.32209548e-01 8.54178607e-01
-8.88946235e-01 2.54780442e-01 -1.65987387e-01 -2.95170486e-01
-9.12356257e-01 6.67983890e-01 2.61378706e-01 -3.37973297e-01
-5.30217767e-01 6.48848772e-01 4.21264358e-02 -7.73622751e-01
1.50179407e-02 -8.61362278e-01 -2.24926159e-01 -3.94838333e-01
7.75315285e-01 2.25857317e-01 -7.80413747e-02 2.36972332e-01
-4.74727780e-01 2.84122437e-01 -1.87947247e-02 4.62799788e-01
1.06747437e+00 3.72151621e-02 -4.98724401e-01 2.23014757e-01
5.25740325e-01 -8.46119374e-02 -8.19749355e-01 -1.41042992e-01
1.36331499e-01 -3.73877943e-01 -4.65433091e-01 -1.13704348e+00
-6.20115280e-01 1.10976541e+00 -1.22988388e-01 2.70871103e-01
1.45021582e+00 -3.17111343e-01 8.37301373e-01 8.06806803e-01
5.59213698e-01 -9.52899158e-01 -1.01640232e-01 6.52890146e-01
7.88912952e-01 -1.11683333e+00 -1.66770712e-01 -8.53377044e-01
-2.41157934e-01 1.45231330e+00 1.25189698e+00 2.49392956e-01
-1.71213016e-01 3.22011679e-01 -2.85096556e-01 1.12326033e-02
-8.79193008e-01 1.47280604e-01 -1.50551841e-01 3.53774309e-01
4.17714477e-01 6.20722212e-02 -6.41677141e-01 1.15854776e+00
-4.49234456e-01 3.72584939e-01 4.77887094e-01 1.28382158e+00
-4.42361623e-01 -7.59330571e-01 -5.13399184e-01 3.84909749e-01
-4.04591374e-02 -4.12352502e-01 -2.01091781e-01 5.66161692e-01
1.51456088e-01 9.74883318e-01 -1.70807108e-01 -4.36762094e-01
3.52390677e-01 3.48098099e-01 3.11388880e-01 -4.47469115e-01
-6.03766978e-01 -8.34341526e-01 1.60122186e-01 -7.10973442e-01
-5.66541962e-02 -2.79013693e-01 -1.99804401e+00 -6.07894838e-01
-1.95788413e-01 -3.46525609e-02 2.66008407e-01 1.33033180e+00
2.75543928e-01 8.54217649e-01 3.09265822e-01 -6.43069521e-02
-9.34191883e-01 -6.40795946e-01 -1.81107298e-01 5.76936424e-01
-6.85745329e-02 -5.49011886e-01 -2.87188351e-01 -9.07039493e-02] | [9.593992233276367, 7.451225280761719] |
b07268cc-2c6c-40fd-8ef7-ddb2bbef82de | source-aware-spatial-spectral-integrated | 2212.06466 | null | https://arxiv.org/abs/2212.06466v1 | https://arxiv.org/pdf/2212.06466v1.pdf | Source-Aware Spatial-Spectral-Integrated Double U-Net for Image Fusion | In image fusion tasks, pictures from different sources possess distinctive properties, therefore treating them equally will lead to inadequate feature extracting. Besides, multi-scaled networks capture information more sufficiently than single-scaled models in pixel-wised problems. In light of these factors, we propose a source-aware spatial-spectral-integrated double U-shaped network called $\rm{(SU)^2}$Net. The network is mainly composed of a spatial U-net and a spectral U-net, which learn spatial details and spectral characteristics discriminately and hierarchically. In contrast with most previous works that simply apply concatenation to integrate spatial and spectral information, a novel structure named the spatial-spectral block (called $\rm{S^2}$Block) is specially designed to merge feature maps from different sources effectively. Experiment results show that our method outperforms the representative state-of-the-art (SOTA) approaches in both quantitative and qualitative evaluations for a variety of image fusion missions, including remote sensing pansharpening and hyperspectral image super-resolution (HISR). | ['Xiao Wu', 'Chenhao Guo', 'Siran Peng'] | 2022-12-13 | null | null | null | null | ['pansharpening'] | ['computer-vision'] | [ 8.54161739e-01 -4.22804892e-01 6.98895529e-02 -4.31728303e-01
-8.26198936e-01 -2.79336214e-01 4.10655707e-01 -1.84299022e-01
-1.46010503e-01 8.98792446e-01 1.34551480e-01 -4.19731997e-02
-6.48112416e-01 -1.06592810e+00 -5.05772054e-01 -1.12597847e+00
7.29490444e-02 -4.96435761e-01 2.17648610e-01 -6.85081482e-01
-1.19407587e-01 5.24842024e-01 -1.84889126e+00 2.47423634e-01
1.52343225e+00 1.41620111e+00 6.76833808e-01 1.74388871e-01
1.18436562e-02 7.25183129e-01 -1.53262749e-01 -8.72880965e-02
5.82386196e-01 -5.83480716e-01 -2.43339613e-01 3.08140278e-01
6.28565729e-01 -2.45919630e-01 -3.39379251e-01 1.78251648e+00
5.32873213e-01 3.26486379e-01 2.68308938e-01 -9.24324989e-01
-9.92532790e-01 7.67047882e-01 -1.06729448e+00 8.94193575e-02
-9.03885663e-02 7.54836053e-02 8.84077728e-01 -9.35305119e-01
3.12772363e-01 1.03861403e+00 8.52335989e-01 -2.08085179e-01
-1.16657174e+00 -8.37531090e-01 2.13571623e-01 1.74279988e-01
-1.56046700e+00 -2.94662416e-01 9.74886477e-01 -1.56354934e-01
4.96826231e-01 4.92883027e-01 5.83284974e-01 3.85237962e-01
-8.22980180e-02 6.14239335e-01 1.57777226e+00 -1.66775301e-01
-1.48113742e-01 -2.52887338e-01 6.44636378e-02 4.83521014e-01
3.44972253e-01 1.53749287e-01 -5.91797173e-01 1.06449112e-01
1.03080928e+00 3.25698704e-01 -8.10809076e-01 -9.87455025e-02
-1.27145863e+00 5.40048897e-01 1.13771439e+00 4.19433326e-01
-8.24948728e-01 -3.61475497e-01 -1.12574056e-01 1.57629251e-01
5.23339510e-01 3.47664475e-01 -3.76558959e-01 7.14144886e-01
-1.08699620e+00 2.13878811e-04 -2.41943095e-02 7.73457050e-01
1.27562177e+00 3.89477760e-01 -1.28353626e-01 1.13145447e+00
2.01465696e-01 6.85878873e-01 1.90962702e-01 -1.09493673e+00
3.07860434e-01 8.09386790e-01 5.17184511e-02 -1.05431640e+00
-4.61317360e-01 -7.57492781e-01 -1.57839191e+00 2.47057170e-01
-5.98992445e-02 -2.13117212e-01 -1.10208023e+00 1.61526227e+00
2.11861566e-01 2.76757538e-01 3.07146519e-01 1.08398163e+00
1.20795119e+00 7.42676616e-01 -3.24847586e-02 -4.68272328e-01
1.35136080e+00 -9.72621858e-01 -7.55763054e-01 -2.24173784e-01
1.99032146e-02 -7.43564010e-01 5.21240354e-01 1.56199530e-01
-1.10084927e+00 -9.03472900e-01 -1.18910325e+00 5.38863093e-02
-5.53151429e-01 1.78074330e-01 6.57583475e-01 3.91097665e-01
-1.10016179e+00 7.40537882e-01 -1.53424114e-01 -5.74504323e-02
4.98284698e-01 -8.54272861e-03 -5.94151139e-01 -4.64497417e-01
-1.32825136e+00 7.51895010e-01 7.54310906e-01 5.40119290e-01
-4.30912584e-01 -6.58406317e-01 -8.67409468e-01 8.78144335e-03
5.77010632e-01 -6.69524848e-01 6.59112871e-01 -9.65467572e-01
-9.50529873e-01 4.52318430e-01 -1.37305140e-01 -2.28488430e-01
1.31467149e-01 1.91963017e-01 -8.81941795e-01 3.27360809e-01
5.98372752e-03 6.88661218e-01 8.86004210e-01 -1.66832745e+00
-1.01306593e+00 -6.45109832e-01 1.04706138e-01 5.19724309e-01
-3.27169925e-01 -1.41737700e-01 -1.43914893e-01 -8.89555275e-01
6.60739005e-01 -3.54827970e-01 -3.65187705e-01 -1.18338175e-01
-2.50819504e-01 1.91532940e-01 9.22554851e-01 -9.13159728e-01
1.15568399e+00 -2.08587933e+00 1.88705966e-01 1.66001976e-01
3.79811645e-01 5.51936448e-01 -3.71421337e-01 2.87967741e-01
-3.92285317e-01 2.07686536e-02 -7.75541961e-01 1.97690707e-02
-3.62214684e-01 1.74089968e-01 5.37034906e-02 3.51287544e-01
1.54542744e-01 8.41039181e-01 -9.69929636e-01 -3.88040692e-01
4.92766708e-01 6.33998692e-01 1.18517078e-01 4.06957325e-03
-1.97325572e-02 3.89388740e-01 -4.74590689e-01 9.95038092e-01
1.29205322e+00 -2.59050548e-01 -2.97298849e-01 -7.55857527e-01
-4.96519893e-01 -3.68897796e-01 -1.30593300e+00 1.72414517e+00
-1.26590729e-01 1.61682487e-01 6.79905415e-01 -7.94233561e-01
1.03336453e+00 1.38749421e-01 5.83019197e-01 -8.96616578e-01
4.09205072e-02 2.85127074e-01 -1.76979035e-01 -2.62019008e-01
6.72254503e-01 -2.49357879e-01 4.43994135e-01 -1.47480473e-01
1.53313994e-01 -2.39810750e-01 9.83146951e-02 -2.77306512e-02
6.22260690e-01 4.74985652e-02 3.15968573e-01 -2.27498651e-01
8.75541866e-01 -1.06198154e-01 7.53536820e-01 8.90561581e-01
-3.36452276e-01 7.21572459e-01 -7.09077492e-02 -2.00148612e-01
-1.06721151e+00 -8.47443402e-01 -2.08528474e-01 9.10724342e-01
4.71378595e-01 9.69386287e-03 -4.04727846e-01 -2.41004631e-01
-2.10440028e-02 5.45747101e-01 -4.32769299e-01 5.01054339e-02
-2.17297405e-01 -1.14296186e+00 2.19711870e-01 4.66502547e-01
1.21111584e+00 -9.06249881e-01 -1.71334267e-01 2.07467228e-01
-3.21630180e-01 -1.00343668e+00 -2.23864704e-01 1.01120256e-01
-6.16125584e-01 -1.15566623e+00 -8.45747113e-01 -4.62518871e-01
4.75801438e-01 1.24723339e+00 8.64290774e-01 -3.00632209e-01
-1.98672041e-01 7.44280294e-02 -6.61674798e-01 -4.45875645e-01
-3.75581384e-02 -3.13433677e-01 -3.28565985e-01 4.84099448e-01
1.45651042e-01 -7.19634295e-01 -8.10288787e-01 3.17110538e-01
-1.38541532e+00 3.59061778e-01 9.94314969e-01 8.95073891e-01
8.43101382e-01 6.15575552e-01 5.92267096e-01 -5.63846469e-01
4.46942359e-01 -2.89944053e-01 -5.59120476e-01 5.44493377e-01
-4.74237204e-01 -3.00202221e-01 5.34272552e-01 3.98880132e-02
-1.54882252e+00 1.50497779e-01 1.23190144e-02 -3.87941837e-01
-2.53945082e-01 7.52317071e-01 -2.93487340e-01 -4.36041802e-01
5.30897915e-01 6.81824327e-01 1.17307246e-01 -4.60994750e-01
5.18318951e-01 7.86793470e-01 9.59133744e-01 -7.99137652e-02
1.06023288e+00 7.45477855e-01 1.62092179e-01 -1.05853283e+00
-1.09882617e+00 -6.15787148e-01 -6.42520845e-01 -3.67439300e-01
8.28168333e-01 -1.38612628e+00 -3.11012268e-01 9.22972858e-01
-8.13146830e-01 1.75587744e-01 -3.37275743e-01 3.77989054e-01
-1.23317234e-01 4.07638192e-01 -2.49492735e-01 -8.48107636e-01
-4.16270018e-01 -9.95112479e-01 1.19989657e+00 7.04207838e-01
7.28616118e-01 -6.04988098e-01 -4.44103867e-01 5.46754181e-01
7.95180798e-01 4.03147966e-01 4.42650288e-01 -2.59453617e-02
-5.87468803e-01 -1.09746959e-02 -1.05663073e+00 8.73687029e-01
4.46817219e-01 -1.89162061e-01 -9.82405782e-01 -2.18591541e-01
1.88998997e-01 -5.82996234e-02 1.35178709e+00 5.73869526e-01
1.19732332e+00 -7.41635263e-02 -5.21342875e-03 7.97397554e-01
1.69838977e+00 8.58862102e-02 7.28835523e-01 1.13854639e-01
8.96240652e-01 6.26527905e-01 3.79364640e-01 3.50088924e-01
3.07508528e-01 1.57280564e-01 8.01090598e-01 -6.12802744e-01
-2.57961750e-01 7.65842944e-02 1.54137000e-01 4.18063611e-01
-5.41549623e-01 -7.53884960e-04 -4.23431545e-01 3.82741779e-01
-1.86202884e+00 -1.17616272e+00 -3.43929976e-01 1.97667730e+00
6.30347908e-01 -4.36888248e-01 -2.93783545e-01 8.17070454e-02
1.02468705e+00 7.86097646e-01 -7.11403668e-01 5.21706641e-01
-1.08079970e+00 1.40288576e-01 8.84311080e-01 2.74079055e-01
-1.19904304e+00 6.67102993e-01 5.41057920e+00 1.24520707e+00
-9.66104388e-01 1.91206083e-01 5.13005197e-01 2.91913897e-01
-4.00435418e-01 -5.75422086e-02 -4.27870870e-01 2.40471393e-01
3.47134620e-01 6.26901984e-02 5.29538989e-01 3.14508915e-01
2.05695793e-01 -3.63350362e-01 -2.74709135e-01 1.08809769e+00
1.52644768e-01 -1.33636701e+00 1.44817144e-01 -1.11706294e-01
1.09958661e+00 2.51724273e-01 4.57657129e-02 -8.64565969e-02
4.81147975e-01 -8.48444283e-01 5.47077477e-01 6.04385972e-01
8.23045373e-01 -5.59717298e-01 8.46590936e-01 2.45467901e-01
-1.73551750e+00 -3.44982803e-01 -3.85580778e-01 2.18844846e-01
2.19341204e-01 9.62959409e-01 6.86724409e-02 1.62562478e+00
8.53493869e-01 1.08670187e+00 -6.05745435e-01 9.84699726e-01
-1.96736008e-01 2.71075964e-01 -2.52855152e-01 7.16432810e-01
4.12414968e-01 -6.14451230e-01 5.88871360e-01 8.74148011e-01
6.32067323e-01 5.90411365e-01 2.35568091e-01 8.27413023e-01
-3.36805135e-02 -3.85221168e-02 -5.37223339e-01 1.27725929e-01
4.19864178e-01 1.62244010e+00 -4.48846817e-01 -4.40793931e-01
-5.45701802e-01 6.69302523e-01 -2.71378934e-01 4.49660331e-01
-4.88166392e-01 -3.28123271e-01 6.97287798e-01 -1.43369272e-01
4.61651117e-01 -5.73976198e-03 -2.04400897e-01 -1.15316045e+00
-3.67810167e-02 -7.76372731e-01 3.88977617e-01 -1.40963018e+00
-1.49926984e+00 7.97060251e-01 6.82368409e-03 -1.55404079e+00
5.19532740e-01 -5.04399419e-01 -2.89152056e-01 1.19595861e+00
-2.20735455e+00 -1.49705946e+00 -9.20607984e-01 8.70050728e-01
2.43437529e-01 -1.19173914e-01 4.90052879e-01 2.00716883e-01
-5.65251112e-01 -1.67867586e-01 3.75018299e-01 -1.12906858e-01
5.49575269e-01 -1.02174938e+00 -1.09267481e-01 1.27098310e+00
-2.45534182e-01 2.10785761e-01 4.72097993e-01 -6.42329574e-01
-1.18953693e+00 -1.46602023e+00 2.22075507e-01 2.84267962e-01
7.19643831e-01 3.73127013e-01 -1.12675893e+00 2.19932377e-01
3.82512838e-01 3.00903946e-01 5.02427876e-01 -3.29511374e-01
-5.31621516e-01 -6.11020684e-01 -1.24840724e+00 2.98843324e-01
1.12422550e+00 -4.29400980e-01 -3.30340326e-01 3.27708423e-01
8.19922030e-01 -1.45926073e-01 -1.17223632e+00 1.02169871e+00
2.77057618e-01 -1.46549380e+00 1.17858446e+00 4.02938165e-02
5.01148164e-01 -7.63163626e-01 -5.26916623e-01 -1.51328242e+00
-6.47890329e-01 -2.87671357e-01 1.96875721e-01 1.12600052e+00
2.15121597e-01 -8.39048564e-01 2.06164435e-01 -1.65904928e-02
-3.91274631e-01 -3.74502838e-01 -7.93165028e-01 -6.62715971e-01
-2.66887695e-01 -1.34727493e-01 9.29357171e-01 1.13044643e+00
-5.94853044e-01 1.40206322e-01 -4.70025092e-01 5.18735170e-01
9.78303730e-01 3.73628706e-01 1.85719684e-01 -1.52412641e+00
9.50563625e-02 -8.84615242e-01 -3.44134457e-02 -7.13681936e-01
-2.15154976e-01 -6.45453155e-01 2.98055224e-02 -1.71274030e+00
3.35905522e-01 -3.58002275e-01 -7.47857273e-01 6.38798177e-01
-4.77857649e-01 5.06126463e-01 2.58248180e-01 2.90693939e-01
-3.41082305e-01 6.64690077e-01 1.63063323e+00 -1.56190947e-01
-8.05322900e-02 -2.39358410e-01 -1.06987488e+00 7.20308781e-01
5.52751660e-01 6.10413253e-02 -2.25430131e-01 -4.07988012e-01
1.42821074e-01 2.70487964e-01 4.90724325e-01 -1.13582897e+00
4.09764975e-01 -3.25451374e-01 5.13972998e-01 -1.00617826e+00
4.46592093e-01 -8.85892510e-01 4.04748321e-01 -9.59038362e-02
-4.11089249e-02 -3.29087704e-01 -7.80750997e-03 4.92408991e-01
-6.67458951e-01 6.09357916e-02 9.18415427e-01 -4.19124961e-01
-1.02918768e+00 6.03928745e-01 2.18509123e-01 -6.52743876e-01
8.54344606e-01 -4.47349995e-01 -7.14185774e-01 -3.33905935e-01
-3.55578959e-01 5.04628479e-01 2.63547927e-01 2.62163669e-01
6.35946214e-01 -1.20107508e+00 -1.03346443e+00 2.84937203e-01
3.39776605e-01 4.52517062e-01 1.06252146e+00 8.74078870e-01
-2.18149468e-01 1.08702183e-01 -4.21293914e-01 -4.61926937e-01
-1.10428596e+00 3.51262659e-01 4.75480258e-01 -2.16411695e-01
-2.74875820e-01 9.48530674e-01 2.03934640e-01 -3.86549026e-01
-3.25224519e-01 -3.42787169e-02 -4.54073429e-01 4.00920063e-01
7.20176220e-01 3.94378603e-01 2.33516004e-02 -1.12899303e+00
1.77142043e-02 5.72821856e-01 2.25887641e-01 2.17991218e-01
1.75989819e+00 -3.84818107e-01 -7.47268796e-01 1.44245967e-01
8.68517220e-01 -3.92120302e-01 -1.41591823e+00 -9.81681705e-01
-7.65741229e-01 -5.54559112e-01 4.89287198e-01 -9.57804620e-01
-1.47244573e+00 6.24814391e-01 6.58939421e-01 5.02485216e-01
1.86846066e+00 -2.41207361e-01 6.06466889e-01 1.71409622e-01
2.85601526e-01 -1.02751350e+00 -2.65309334e-01 3.61013591e-01
9.27513659e-01 -1.48145235e+00 2.50914186e-01 -6.71175599e-01
-5.56669772e-01 9.59327579e-01 5.21619022e-01 1.37191474e-01
6.12177610e-01 -1.68097150e-02 -7.55848959e-02 -2.08688825e-01
-1.56162500e-01 -7.45646656e-01 5.39974511e-01 6.13718569e-01
8.44957158e-02 2.43888572e-01 2.59263092e-03 3.64720017e-01
1.35644330e-02 -7.24100396e-02 3.68003577e-01 9.15413201e-01
-9.17695343e-01 -8.27604413e-01 -7.23471642e-01 6.72876596e-01
1.83231421e-02 -3.75308782e-01 -3.62498797e-02 4.64116037e-01
5.57640970e-01 1.08424199e+00 -1.26461565e-01 -5.97490191e-01
3.70159566e-01 -1.85081914e-01 2.24442810e-01 -2.17393145e-01
-4.18162405e-01 2.60698557e-01 -2.99240083e-01 -4.75550681e-01
-1.21171236e+00 -6.10051930e-01 -7.12151408e-01 -1.66240588e-01
-5.64823985e-01 -1.64279372e-01 4.99343693e-01 7.94343710e-01
1.44255877e-01 7.96469748e-01 7.73693562e-01 -1.22081470e+00
-3.25937212e-01 -1.18250477e+00 -1.16130388e+00 2.27171794e-01
5.51972330e-01 -6.06925130e-01 -3.92070144e-01 2.73466716e-03] | [10.25715160369873, -1.8894933462142944] |
4eb43762-447d-47a7-b75e-8e5b300298e0 | a-variational-observation-model-of-3d-object | 1809.05225 | null | http://arxiv.org/abs/1809.05225v1 | http://arxiv.org/pdf/1809.05225v1.pdf | A Variational Observation Model of 3D Object for Probabilistic Semantic SLAM | We present a Bayesian object observation model for complete probabilistic
semantic SLAM. Recent studies on object detection and feature extraction have
become important for scene understanding and 3D mapping. However, 3D shape of
the object is too complex to formulate the probabilistic observation model;
therefore, performing the Bayesian inference of the object-oriented features as
well as their pose is less considered. Besides, when the robot equipped with an
RGB mono camera only observes the projected single view of an object, a
significant amount of the 3D shape information is abandoned. Due to these
limitations, semantic SLAM and viewpoint-independent loop closure using
volumetric 3D object shape is challenging. In order to enable the complete
formulation of probabilistic semantic SLAM, we approximate the observation
model of a 3D object with a tractable distribution. We also estimate the
variational likelihood from the 2D image of the object to exploit its observed
single view. In order to evaluate the proposed method, we perform pose and
feature estimation, and demonstrate that the automatic loop closure works
seamlessly without additional loop detector in various environments. | ['H. W. Yu', 'B. H. Le'] | 2018-09-14 | null | null | null | null | ['semantic-slam'] | ['computer-vision'] | [ 1.31286159e-01 1.03255883e-01 -1.24461606e-01 -3.79591018e-01
-4.75065082e-01 -5.66472113e-01 5.32394469e-01 1.02416202e-01
-4.24498081e-01 4.38831955e-01 -3.24432850e-01 -1.95543110e-01
-1.74939707e-01 -5.32221079e-01 -8.52184534e-01 -6.77425265e-01
3.25854391e-01 9.48849678e-01 3.88204247e-01 3.94814104e-01
2.51383215e-01 8.56393933e-01 -1.53196299e+00 -5.38959622e-01
6.39895737e-01 1.09683132e+00 9.44325507e-01 4.48164195e-01
-1.06864080e-01 2.05575690e-01 -2.30866030e-01 1.85838029e-01
2.10995078e-01 1.76301319e-02 -3.10259759e-01 5.73857784e-01
2.73006290e-01 -5.73561609e-01 -4.42543596e-01 1.27060270e+00
1.06042936e-01 7.95417726e-02 7.29807556e-01 -1.41029680e+00
-1.15480691e-01 -1.41136050e-01 -6.33371532e-01 -5.20927727e-01
5.47742069e-01 -2.58731902e-01 8.74540865e-01 -1.09187675e+00
6.50548995e-01 1.28226030e+00 3.98501843e-01 1.11579262e-01
-1.03012705e+00 -3.81418616e-01 2.55864978e-01 1.95477217e-01
-1.78036284e+00 -4.93312448e-01 1.12754858e+00 -3.52053851e-01
5.71047962e-01 1.15933195e-02 6.90810859e-01 7.42370963e-01
2.48494998e-01 9.23316240e-01 9.68314528e-01 -3.90369028e-01
3.53796154e-01 4.41531807e-01 1.94663499e-02 8.45526695e-01
6.41606450e-01 -7.84157440e-02 -7.00394928e-01 -2.12173000e-01
7.51857460e-01 4.58287448e-01 -6.18626690e-03 -1.29892826e+00
-1.14915538e+00 7.18070686e-01 3.54178697e-01 -2.46739641e-01
-3.77652764e-01 3.13912660e-01 -2.06783414e-01 -3.74271929e-01
2.23400265e-01 -1.26134723e-01 -2.60123938e-01 -6.15134314e-02
-6.17116988e-01 2.24935353e-01 6.97202206e-01 1.63817000e+00
1.13131392e+00 -2.19883934e-01 3.12307656e-01 3.43093663e-01
9.54969645e-01 1.21549380e+00 -2.78637946e-01 -1.15852129e+00
2.58841366e-01 6.20992541e-01 5.47185719e-01 -9.86329734e-01
-4.00483251e-01 -3.37600946e-01 -5.85877597e-01 3.78253579e-01
2.63676435e-01 4.16261107e-01 -8.56344819e-01 1.45535684e+00
7.04213858e-01 -1.85968861e-01 6.72950447e-02 1.02731609e+00
4.25655842e-01 3.30279738e-01 -4.77317810e-01 -2.45901167e-01
1.47081125e+00 -3.69365036e-01 -7.59811044e-01 -5.50555646e-01
3.39852184e-01 -8.08768392e-01 4.54172134e-01 2.94866979e-01
-6.07321858e-01 -1.92462638e-01 -1.08962965e+00 -2.24072829e-01
7.78815076e-02 1.68862164e-01 6.76897705e-01 3.01339537e-01
-5.16741395e-01 1.07353084e-01 -1.25908267e+00 -6.27698123e-01
1.94823429e-01 1.45305544e-01 -5.94824612e-01 -4.09676492e-01
-5.05575716e-01 1.07285511e+00 5.05189955e-01 2.55658865e-01
-9.76791263e-01 -1.62766039e-01 -1.21738708e+00 -2.94994384e-01
5.99301755e-01 -7.71856904e-01 9.93423879e-01 -7.68764764e-02
-1.30755675e+00 8.02954912e-01 -6.19686067e-01 -1.67135417e-01
5.80086112e-01 -4.87145692e-01 3.26186121e-01 1.45854563e-01
2.65378237e-01 4.23145801e-01 9.06660199e-01 -1.61153817e+00
-4.71524656e-01 -9.96539295e-01 3.89568359e-02 6.15811467e-01
3.73898119e-01 -4.26880926e-01 -4.69272286e-01 2.00878993e-01
1.20701599e+00 -1.09540272e+00 -1.95142776e-01 3.67455453e-01
-4.94478613e-01 9.71002653e-02 1.05117059e+00 -3.17389041e-01
1.77028403e-01 -2.28194261e+00 1.07448131e-01 -1.80987902e-02
6.17959537e-02 -5.18821478e-01 3.37696582e-01 1.47508532e-01
7.13798642e-01 -3.64608049e-01 -1.64301097e-01 -8.21793318e-01
1.04025275e-01 5.51783204e-01 -3.60702306e-01 1.02593637e+00
-7.44383261e-02 5.78213990e-01 -9.15499866e-01 -5.75818419e-01
6.49344265e-01 6.19637966e-01 -6.32234693e-01 3.37345004e-01
-2.33119696e-01 6.87030137e-01 -9.68544662e-01 7.03588068e-01
1.16149664e+00 -6.75836876e-02 5.34115210e-02 -3.34644526e-01
-2.10836664e-01 1.14097238e-01 -1.43409240e+00 2.19798946e+00
-4.38247710e-01 2.27215186e-01 2.50771910e-01 -5.70053458e-01
9.67128396e-01 6.10343032e-02 4.12263870e-01 -2.21969455e-01
1.14635564e-02 2.23128259e-01 -5.21149933e-01 -3.30550611e-01
8.21077943e-01 -2.47683734e-01 -1.78083777e-01 2.00285539e-01
3.56535763e-02 -7.79256225e-01 -5.05453229e-01 3.18009257e-01
8.50060642e-01 6.56990886e-01 5.21466911e-01 -4.46643680e-03
1.86577246e-01 1.23918332e-01 5.89242101e-01 8.28541219e-01
-3.75345014e-02 6.05657041e-01 -1.15649626e-01 -8.64558518e-02
-9.19286132e-01 -1.52601981e+00 -3.19408059e-01 1.95223063e-01
1.02200913e+00 -9.34018195e-02 -1.69052050e-01 -3.99493337e-01
3.17066044e-01 8.48614156e-01 -1.42492801e-01 -1.36830509e-01
-1.27080590e-01 -4.86726254e-01 -1.35438040e-01 1.24432489e-01
4.22723442e-01 -5.24689734e-01 -1.22582519e+00 7.26041496e-02
-3.59813452e-01 -1.41006744e+00 -4.25109863e-02 2.89299816e-01
-9.16354895e-01 -1.12467360e+00 -2.21034169e-01 -3.40862781e-01
9.23051953e-01 7.49096334e-01 5.20191073e-01 -2.98585951e-01
-2.51801550e-01 6.43934488e-01 -3.49079490e-01 -4.49216634e-01
-2.20584288e-01 -4.42157954e-01 4.36682940e-01 6.08254410e-02
3.17748219e-01 -6.14889622e-01 -4.41057086e-01 3.46909612e-01
-3.46187234e-01 2.30100721e-01 6.23574615e-01 5.69860160e-01
8.85941207e-01 7.31747225e-02 -1.28393590e-01 -2.95889169e-01
-2.55974293e-01 -1.34433120e-01 -9.42777038e-01 -4.03875709e-02
-2.86664099e-01 1.02489395e-02 -1.13239989e-01 -2.94239342e-01
-1.23851430e+00 6.84893727e-01 2.36994594e-01 -6.66542470e-01
-2.30715677e-01 3.18202257e-01 -4.54849303e-01 -1.55892130e-03
3.30524117e-01 4.12089825e-01 1.45135552e-01 -7.01610327e-01
4.12146181e-01 6.34521723e-01 3.11291277e-01 -4.88661498e-01
9.58181679e-01 1.09198618e+00 4.77335215e-01 -1.07018852e+00
-9.71709907e-01 -7.29472458e-01 -9.43798423e-01 -1.76575691e-01
7.85679281e-01 -1.11030471e+00 -8.39400947e-01 2.33227789e-01
-1.50066185e+00 2.30512097e-01 -2.14978531e-01 1.03985858e+00
-8.73087585e-01 5.54275811e-01 -1.05246399e-02 -1.43339133e+00
2.37742886e-01 -1.36782789e+00 1.55719352e+00 -8.13834071e-02
2.51947735e-02 -5.13068676e-01 -2.33257622e-01 2.44618922e-01
-1.30581960e-01 1.36870712e-01 5.11376202e-01 -2.16898128e-01
-1.20552146e+00 -4.53420132e-01 -3.34785104e-01 -9.18515697e-02
1.44774050e-01 -3.01594079e-01 -1.01933014e+00 -2.67377019e-01
6.26955450e-01 -6.16209097e-02 5.44025660e-01 3.51630867e-01
4.99087393e-01 3.00231457e-01 -6.50222182e-01 6.43226624e-01
1.41397345e+00 1.11305006e-01 -8.06939136e-03 9.74133164e-02
7.71847725e-01 5.59862435e-01 1.15199292e+00 8.07453871e-01
5.43080986e-01 6.99882925e-01 1.05898345e+00 5.64929366e-01
1.18293844e-01 -5.81556559e-01 1.83391809e-01 5.96446395e-01
1.20159097e-01 -1.14305310e-01 -7.21464276e-01 3.08490694e-01
-1.77438271e+00 -2.34296858e-01 -1.67520523e-01 2.40347862e+00
9.16973054e-02 2.54765563e-02 -5.59143126e-01 -1.94358863e-02
5.82210362e-01 1.23228710e-02 -7.32769668e-01 4.91093040e-01
6.36552125e-02 -6.09767199e-01 7.17967987e-01 8.34257722e-01
-7.40211725e-01 1.01148796e+00 5.24140215e+00 4.71476078e-01
-6.18682206e-01 1.51538149e-01 -3.81236523e-01 1.62869692e-01
-4.57107127e-01 6.90560997e-01 -1.31459713e+00 6.60099508e-03
2.25509748e-01 1.41558960e-01 2.28502095e-01 9.51674759e-01
1.24632418e-01 -7.74845183e-01 -1.27090621e+00 1.26057267e+00
5.73175177e-02 -6.81497097e-01 6.01773970e-02 5.03803730e-01
3.12773436e-01 1.27513379e-01 -1.62313312e-01 7.26752076e-03
1.24135539e-01 -3.87577057e-01 1.30323243e+00 5.99187613e-01
5.48217177e-01 -4.10088807e-01 5.77772081e-01 9.75212514e-01
-9.96629119e-01 1.07804157e-01 -6.55205190e-01 -2.51863778e-01
6.26604915e-01 1.03021014e+00 -1.06435311e+00 7.03351557e-01
5.91227710e-01 5.78675985e-01 -2.26140872e-01 9.60557461e-01
-4.01427388e-01 -4.56599183e-02 -8.96779895e-01 6.18335083e-02
-1.80177242e-01 -3.72082680e-01 1.14335692e+00 3.99983644e-01
6.40445948e-01 1.69873908e-02 4.08495575e-01 1.15578651e+00
2.86215484e-01 -2.27924347e-01 -7.97832489e-01 2.50116348e-01
5.28720796e-01 1.04981911e+00 -9.46712732e-01 1.70968901e-02
-2.57927954e-01 1.09925330e+00 1.58726171e-01 3.79475802e-01
-6.83743596e-01 5.93526065e-02 5.26126444e-01 -1.33338630e-01
2.89938927e-01 -8.10850799e-01 -2.57462531e-01 -1.29631937e+00
2.96389371e-01 7.88906440e-02 -1.65497229e-01 -1.11465204e+00
-7.62020767e-01 2.00405285e-01 2.79920965e-01 -1.36737812e+00
-1.26389399e-01 -5.28076231e-01 7.09765330e-02 9.04539704e-01
-1.41127086e+00 -1.25718558e+00 -5.32495975e-01 3.75550151e-01
3.54757816e-01 4.11924541e-01 6.80218875e-01 -2.55374730e-01
9.93202105e-02 -2.40322828e-01 -5.14144218e-03 -4.52282161e-01
4.75583285e-01 -9.61399138e-01 -7.16037452e-02 6.88805461e-01
2.50933051e-01 5.14438629e-01 1.08973897e+00 -9.34218705e-01
-2.06775117e+00 -8.35633457e-01 5.91455579e-01 -8.16595137e-01
4.33408499e-01 -7.98666060e-01 -5.82729220e-01 8.43183279e-01
-5.60771108e-01 2.11799592e-01 -3.82512249e-02 -2.28953045e-02
-1.08465292e-01 -5.91851100e-02 -1.08278620e+00 3.57326150e-01
1.17568576e+00 -6.79982543e-01 -6.86122775e-01 3.26436311e-01
9.41477001e-01 -6.28883243e-01 -5.41760147e-01 6.70233250e-01
6.30762756e-01 -8.53111982e-01 9.18244004e-01 1.12629190e-01
-4.23726857e-01 -7.04430759e-01 -7.64181256e-01 -9.26936448e-01
1.34123743e-01 -2.84638137e-01 -2.49960318e-01 9.42222297e-01
-9.97485593e-02 -6.15214646e-01 1.02412331e+00 3.27412933e-01
-1.55014351e-01 -7.52171427e-02 -1.33422410e+00 -8.02854717e-01
-6.86302304e-01 -8.02344978e-01 2.10545450e-01 4.07297015e-01
-4.21934366e-01 2.84933060e-01 -2.85223186e-01 9.66348350e-01
1.26121175e+00 5.95346808e-01 1.05517840e+00 -1.39970684e+00
-3.37065831e-02 2.34448239e-01 -6.55485451e-01 -1.70655596e+00
2.62782127e-01 -7.08999693e-01 5.63099623e-01 -1.51177144e+00
4.26196486e-01 -5.72543144e-01 5.47109693e-02 -1.16529644e-01
2.66502500e-01 2.91314442e-03 1.07920252e-01 3.41393322e-01
-6.43034935e-01 9.66603696e-01 1.18216443e+00 -2.80587431e-02
-1.79807972e-02 1.36979163e-01 -1.56632006e-01 1.09097135e+00
2.73319960e-01 -6.75717235e-01 -3.37925136e-01 -5.51035166e-01
2.30521008e-01 3.35732669e-01 7.12236106e-01 -7.01544702e-01
3.28906029e-01 -2.46463031e-01 3.20661575e-01 -1.34755480e+00
1.07007515e+00 -1.31821799e+00 2.67067194e-01 3.72793317e-01
2.45764181e-01 -4.68222946e-01 -2.10675254e-01 9.66269493e-01
-4.45896797e-02 -4.78161782e-01 5.25374949e-01 -2.47130483e-01
-7.45782971e-01 4.56156135e-01 -2.18694717e-01 -4.30926055e-01
8.05292964e-01 -3.63316000e-01 3.24570805e-01 -4.38437074e-01
-8.21331680e-01 9.34552699e-02 1.06654239e+00 3.28376442e-01
9.88337100e-01 -1.25322437e+00 -2.75399059e-01 4.21155572e-01
4.37345803e-01 7.52356887e-01 3.18193555e-01 8.92526388e-01
-3.94897699e-01 4.74030465e-01 1.69681489e-01 -1.36539245e+00
-9.83710468e-01 6.84261680e-01 -2.39110012e-02 4.57990080e-01
-7.10335791e-01 5.20135283e-01 6.35842681e-01 -7.19983101e-01
8.20675641e-02 -3.45529318e-01 2.63046324e-01 -3.95645082e-01
3.01312029e-01 1.98279187e-01 -2.72832751e-01 -9.79170918e-01
-5.36083639e-01 8.20225060e-01 2.34238476e-01 -2.15904340e-01
1.06468451e+00 -8.25064898e-01 -1.71691537e-01 8.71050954e-01
9.75035906e-01 7.97906369e-02 -1.57695496e+00 -5.49221337e-01
-1.45299390e-01 -7.34197676e-01 8.55595246e-02 -1.18355952e-01
-3.31767976e-01 1.05207908e+00 4.86558408e-01 -2.95565277e-01
5.24833024e-01 3.35594058e-01 1.75755948e-01 6.98322892e-01
1.29081154e+00 -6.18901074e-01 -1.74779817e-01 6.56438708e-01
8.25241208e-01 -1.37717104e+00 4.00907218e-01 -8.06153357e-01
-1.79553807e-01 9.04092312e-01 2.27713570e-01 1.64843127e-02
6.83351219e-01 8.24891403e-02 -2.67929733e-01 -9.27400440e-02
-2.83948541e-01 -1.20488673e-01 1.06176883e-01 6.02285504e-01
-3.35405648e-01 1.15742005e-01 4.03597534e-01 1.24721579e-01
-7.66439363e-02 -2.38525495e-01 5.00262260e-01 1.13564873e+00
-7.14410484e-01 -6.43932581e-01 -6.05891466e-01 -4.07464206e-02
-6.14025109e-02 1.25072539e-01 2.28784736e-02 7.64616787e-01
-2.03006774e-01 7.25865483e-01 7.31932595e-02 -1.69679016e-01
1.96062952e-01 -3.40148658e-02 9.40699816e-01 -7.00855732e-01
9.18475747e-01 2.67807066e-01 -1.88908309e-01 -6.79540038e-01
-4.42152143e-01 -8.31074059e-01 -1.44775605e+00 2.79705226e-01
-7.39995182e-01 8.40093270e-02 1.40077722e+00 1.12499249e+00
6.99653774e-02 4.68543433e-02 4.54111218e-01 -1.19033933e+00
-7.10009456e-01 -8.69479358e-01 -1.11044347e+00 7.82220960e-02
4.69357401e-01 -1.29586768e+00 -5.62507868e-01 -2.06580356e-01] | [7.352316379547119, -2.470386505126953] |
09a52070-1e33-45f6-82e1-7d7f8d0f6f3e | multi-hierarchical-convolutional-network-for | 2104.02260 | null | https://arxiv.org/abs/2104.02260v2 | https://arxiv.org/pdf/2104.02260v2.pdf | Non-contact PPG Signal and Heart Rate Estimation with Multi-hierarchical Convolutional Network | Heartbeat rhythm and heart rate (HR) are important physiological parameters of the human body. This study presents an efficient multi-hierarchical spatio-temporal convolutional network that can quickly estimate remote physiological (rPPG) signal and HR from face video clips. First, the facial color distribution characteristics are extracted using a low-level face feature generation (LFFG) module. Then, the three-dimensional (3D) spatio-temporal stack convolution module (STSC) and multi-hierarchical feature fusion module (MHFF) are used to strengthen the spatio-temporal correlation of multi-channel features. In the MHFF, sparse optical flow is used to capture the tiny motion information of faces between frames and generate a self-adaptive region of interest (ROI) skin mask. Finally, the signal prediction module (SP) is used to extract the estimated rPPG signal. The heart rate estimation results show that the proposed network overperforms the state-of-the-art methods on three datasets, 1) UBFC-RPPG, 2) COHFACE, 3) our dataset, with the mean absolute error (MAE) of 2.15, 5.57, 1.75 beats per minute (bpm) respectively. | ['Hong Fu', 'Panpan Zhang', 'Jinye Peng', 'Bin Li'] | 2021-04-06 | null | null | null | null | ['heart-rate-estimation'] | ['medical'] | [-1.36901423e-01 -4.05670255e-01 2.54451632e-01 -3.25199157e-01
-1.90367699e-01 4.40664627e-02 7.88183808e-02 -6.20316505e-01
-2.91746020e-01 7.87306786e-01 1.81477293e-01 4.25932437e-01
1.97122514e-01 -4.46621597e-01 -2.46762082e-01 -1.02030301e+00
-4.96464878e-01 -7.50115752e-01 -2.96560172e-02 1.58005685e-01
1.11311048e-01 5.92891932e-01 -1.50770867e+00 2.61230707e-01
5.42041719e-01 1.45563889e+00 -4.26714987e-01 8.85934055e-01
1.87216416e-01 8.64843190e-01 -3.49822074e-01 -1.33646354e-01
2.73902655e-01 -7.85560131e-01 -4.80505288e-01 -7.44683966e-02
3.51787984e-01 -4.49907094e-01 -4.53972787e-01 6.14332616e-01
1.07171583e+00 9.01501998e-02 2.02253297e-01 -1.25933087e+00
-2.24969521e-01 9.43615194e-03 -9.62562203e-01 7.11525142e-01
1.46868899e-01 4.16801423e-01 1.35037616e-01 -1.05944753e+00
5.10476410e-01 1.36007881e+00 8.57784867e-01 5.87603807e-01
-8.77258062e-01 -9.68694746e-01 -3.19297820e-01 2.80881882e-01
-1.51383567e+00 -7.13002801e-01 9.36608315e-01 -3.38782281e-01
4.66907829e-01 2.42638439e-01 9.83331800e-01 8.26807857e-01
6.44431412e-01 2.22040653e-01 1.37404323e+00 -2.80808322e-02
-1.80403650e-01 -1.39880806e-01 -3.77146244e-01 1.01122892e+00
-2.78125197e-01 1.68098420e-01 -8.38044822e-01 -7.01955408e-02
1.21479809e+00 -7.20881820e-02 -4.74431634e-01 3.26670557e-01
-1.23549533e+00 4.98018652e-01 2.42561862e-01 3.71756107e-01
-6.64080024e-01 2.86242783e-01 5.00798464e-01 -3.04618236e-02
4.15619999e-01 -1.75135776e-01 -3.36110920e-01 -1.04210287e-01
-1.08794332e+00 -1.03088036e-01 6.67445898e-01 3.43634963e-01
6.67461634e-01 3.78285527e-01 -5.91130793e-01 7.60825217e-01
6.06095731e-01 5.03643453e-01 6.09679103e-01 -1.41240001e+00
-1.22305013e-01 1.59254432e-01 -3.59282307e-02 -1.32566965e+00
-6.24959946e-01 -3.87111247e-01 -1.09174526e+00 -1.17061101e-01
1.54402509e-01 -5.23500621e-01 -4.01136130e-01 1.61410737e+00
8.21514785e-01 8.47071946e-01 -7.69644231e-02 1.35143268e+00
1.18678665e+00 6.70114338e-01 2.46301517e-01 -9.60941255e-01
1.49654877e+00 -7.01100826e-01 -8.99004817e-01 2.90104181e-01
-3.44175100e-02 -6.80069923e-01 6.65817440e-01 2.00807109e-01
-1.08374715e+00 -9.61386561e-01 -8.01749885e-01 2.22531825e-01
1.81566298e-01 3.84123951e-01 5.61556458e-01 5.01418173e-01
-9.91703570e-01 7.92454123e-01 -7.00039029e-01 -1.46781549e-01
6.08207822e-01 2.09558114e-01 -4.68222022e-01 7.09511116e-02
-1.32834888e+00 4.45227385e-01 -8.02107304e-02 7.53444791e-01
-9.96628761e-01 -9.68656182e-01 -6.30538821e-01 -2.11422995e-01
-1.74772799e-01 -7.40842640e-01 6.21613562e-01 -1.25324774e+00
-1.90256166e+00 7.06134140e-01 -2.27885038e-01 -9.19754878e-02
3.78049403e-01 -1.40565664e-01 -6.53934002e-01 7.84583092e-01
-1.37407646e-01 6.85623109e-01 1.15109837e+00 -6.83264971e-01
-8.04031938e-02 -3.82479995e-01 -5.57607293e-01 3.38617593e-01
-1.80976257e-01 5.06227314e-01 -2.94627458e-01 -4.29387987e-01
-5.88241965e-02 -5.98018348e-01 2.36000657e-01 3.10899138e-01
-1.95865870e-01 1.10218778e-01 8.00682247e-01 -1.00320208e+00
1.30023730e+00 -2.19966316e+00 -9.58921164e-02 -7.72776781e-03
3.19218487e-01 3.08096886e-01 1.06527992e-02 -9.98895541e-02
-1.47860587e-01 1.30546950e-02 7.54877646e-03 -6.13613725e-02
-5.57246089e-01 -3.64571512e-01 2.92628676e-01 9.92104292e-01
9.34144482e-02 9.02070224e-01 -6.24522567e-01 -9.10200655e-01
4.46766376e-01 9.42834795e-01 -1.60890535e-01 2.50677228e-01
6.50657058e-01 7.66694844e-01 -2.98893511e-01 6.46387279e-01
8.71066689e-01 -6.66252046e-04 -1.31749019e-01 -7.13665545e-01
-4.34088469e-01 -4.32191551e-01 -1.27988172e+00 1.57874620e+00
-2.08949253e-01 5.11232972e-01 1.10506542e-01 -6.01016998e-01
1.18188322e+00 6.56297445e-01 1.12853956e+00 -6.09768748e-01
3.74168962e-01 -1.73280478e-01 9.03760940e-02 -8.98942411e-01
-3.64626765e-01 -2.31424481e-01 4.14117754e-01 2.07129359e-01
1.65360242e-01 5.51720142e-01 -1.44308731e-01 -1.94206014e-01
9.40201223e-01 2.25572377e-01 4.07761782e-02 -4.12770420e-01
1.02476573e+00 -7.61099994e-01 1.00664520e+00 1.24166772e-01
-8.88583958e-01 4.72136945e-01 4.87751514e-01 -7.11547554e-01
-6.46568418e-01 -8.40708911e-01 -7.83121362e-02 5.71834922e-01
6.19176142e-02 -3.04374367e-01 -8.15088332e-01 -3.28660637e-01
-5.34339920e-02 -2.73597062e-01 -7.86050141e-01 -1.40030578e-01
-5.62898695e-01 -8.88168156e-01 6.17484152e-01 3.78573388e-01
1.18089044e+00 -1.31428635e+00 -1.05752480e+00 3.03753227e-01
-3.21877301e-01 -1.09127891e+00 -5.20018339e-01 -6.15765750e-01
-8.19651902e-01 -9.84088004e-01 -7.28979468e-01 -2.74010897e-01
2.89822966e-01 2.88160611e-02 8.15147519e-01 1.49004525e-02
-9.74002123e-01 3.59861106e-01 -8.76301453e-02 -2.21339449e-01
2.84576923e-01 -6.20800674e-01 2.25901008e-02 6.43042088e-01
1.96772337e-01 -7.29071915e-01 -1.21783304e+00 2.62669235e-01
-3.31168830e-01 4.98113558e-02 4.47753161e-01 5.52620590e-01
6.14018798e-01 -1.62895694e-01 7.35935569e-01 -3.47508758e-01
3.45077872e-01 -3.59731972e-01 -4.51630205e-01 6.74836040e-02
-2.04233706e-01 -4.39240068e-01 4.59914237e-01 -6.25239789e-01
-1.22304797e+00 3.12481910e-01 1.69899926e-01 -8.41755211e-01
-1.12150878e-01 1.19201943e-01 1.27972052e-01 -1.85013130e-01
6.53177142e-01 3.52807522e-01 1.94659904e-01 -4.42143455e-02
9.02021006e-02 5.07029712e-01 7.56818295e-01 -2.30453074e-01
4.93621111e-01 5.20763755e-01 3.14271510e-01 -9.71449614e-01
-6.55322015e-01 -4.08082604e-01 -7.72086143e-01 -9.03413415e-01
1.21914470e+00 -1.24262404e+00 -1.18402755e+00 8.72469962e-01
-1.12590122e+00 -1.72050759e-01 1.65195853e-01 7.85732150e-01
-4.14561093e-01 3.15952212e-01 -9.44019616e-01 -1.06460190e+00
-9.97731209e-01 -6.32348239e-01 8.63817513e-01 7.33029127e-01
8.74861553e-02 -6.25180483e-01 -8.35522786e-02 3.74237120e-01
7.06374943e-01 1.03747225e+00 2.26331472e-01 3.65955442e-01
-3.08779031e-01 1.69334605e-01 -3.09479564e-01 4.24107492e-01
8.73270929e-02 3.45948309e-01 -1.32451499e+00 -3.06865554e-02
1.58314198e-01 -2.03930423e-01 5.19094825e-01 9.35232103e-01
1.28880131e+00 -1.13751955e-01 2.88308132e-02 8.78231943e-01
1.31773663e+00 9.18430462e-02 9.93136048e-01 -3.94034386e-01
7.48822391e-01 5.21183848e-01 5.61191142e-01 8.91352594e-01
3.48285407e-01 3.98678988e-01 3.17144364e-01 -4.74912524e-01
-2.43294105e-01 1.56948790e-01 6.01942420e-01 5.63515484e-01
-6.03966236e-01 4.60890174e-01 -3.79560709e-01 2.36137614e-01
-1.53352320e+00 -1.13903725e+00 -4.26114917e-01 2.06057405e+00
8.21533918e-01 -5.00096500e-01 4.28514510e-01 1.38424352e-01
9.80274498e-01 7.80098736e-02 -6.30074799e-01 -1.98657170e-01
-6.27241805e-02 3.78528118e-01 1.94806784e-01 1.18916869e-01
-1.23998237e+00 6.83724463e-01 5.49491072e+00 1.34134576e-01
-1.44651711e+00 2.60642350e-01 9.14741576e-01 -1.69073746e-01
3.66984606e-01 -3.43139023e-01 -5.03893495e-01 7.46644080e-01
1.21974111e+00 5.35779558e-02 5.11391222e-01 5.19252419e-01
6.18329823e-01 -1.89967230e-01 -4.51749384e-01 1.50259876e+00
2.32230246e-01 -1.04440022e+00 -6.55945122e-01 -6.37968555e-02
3.09726775e-01 -2.33673245e-01 -2.39318162e-01 3.08199078e-02
-5.53709447e-01 -1.11014414e+00 2.10379779e-01 1.17326796e+00
1.12593651e+00 -7.92971492e-01 6.87954366e-01 -1.29138693e-01
-1.55980742e+00 -2.19241589e-01 -3.48639905e-01 2.35707596e-01
-1.06348202e-01 9.36233282e-01 -1.47589266e-01 3.84342849e-01
1.02814412e+00 8.61711383e-01 -2.81515270e-01 1.00114226e+00
-4.21133637e-02 4.36224759e-01 -1.65157333e-01 3.12080741e-01
-2.31650561e-01 -9.36093275e-03 3.39763016e-01 1.12337267e+00
3.07870716e-01 4.40659881e-01 -1.00316234e-01 9.45921600e-01
7.95187894e-03 1.70137972e-01 -9.60935801e-02 1.36851355e-01
3.96526217e-01 2.06878233e+00 -5.14296770e-01 -2.95077682e-01
-3.87407988e-01 9.86431420e-01 -2.55618483e-01 2.33692765e-01
-1.19515765e+00 -6.26342773e-01 5.99629521e-01 5.47288992e-02
-3.25208195e-02 2.60065980e-02 2.30287597e-01 -1.15947425e+00
-8.26082751e-03 -5.17646134e-01 4.47789192e-01 -8.95509064e-01
-1.00233567e+00 4.16549116e-01 -4.49988276e-01 -1.03558362e+00
1.20418996e-01 -9.31866616e-02 -8.87564123e-01 1.21977317e+00
-1.78220260e+00 -8.22295427e-01 -1.05149293e+00 1.09221745e+00
2.99878389e-01 1.26632884e-01 6.71775222e-01 6.60084248e-01
-9.82581079e-01 4.57297564e-01 -6.70514047e-01 2.71170884e-01
8.30696166e-01 -7.40819633e-01 -3.44660193e-01 8.44892740e-01
-5.98062813e-01 4.02141988e-01 1.46911755e-01 -4.25317407e-01
-1.63856757e+00 -1.18557060e+00 6.40024483e-01 7.75669739e-02
1.35601953e-01 -2.53836185e-01 -7.21006215e-01 9.45825726e-02
6.42242357e-02 1.03398728e+00 6.14588439e-01 -5.35865963e-01
-3.97201516e-02 -7.17322350e-01 -1.46548462e+00 1.89835709e-02
6.48503125e-01 -3.03063631e-01 7.22624660e-02 -4.95975688e-02
2.91735798e-01 -3.96161616e-01 -1.57289696e+00 3.88360202e-01
1.13023865e+00 -1.22231507e+00 8.39214325e-01 -2.07023799e-01
3.81728381e-01 -6.14975274e-01 2.12326452e-01 -8.60040307e-01
-4.02381122e-01 -8.59763980e-01 -3.19632471e-01 1.29402804e+00
-2.33363077e-01 -4.05444622e-01 5.12927949e-01 4.69452709e-01
1.15530209e-04 -7.64751077e-01 -8.66995752e-01 -3.03173929e-01
-4.73289549e-01 -2.08199713e-02 3.24848205e-01 9.60158527e-01
-1.34356365e-01 2.05690071e-01 -6.08952701e-01 6.52060658e-02
6.63659692e-01 2.32904721e-02 4.62192804e-01 -1.41646838e+00
3.86826582e-02 1.97559576e-02 -3.83188188e-01 -2.93612927e-01
4.53522094e-02 -4.03748244e-01 -1.36706112e-02 -1.06072235e+00
1.86732039e-01 -1.72005389e-02 -6.97788179e-01 4.50495780e-01
-2.13019639e-01 5.41753352e-01 4.94932346e-02 -4.26615588e-02
-4.20122594e-01 4.75204229e-01 1.45590520e+00 4.91074294e-01
-3.61913621e-01 -3.27605009e-01 -3.83612067e-01 3.74563217e-01
7.96693742e-01 -1.72925681e-01 -3.44431043e-01 2.03048930e-01
-4.10763323e-01 6.66872442e-01 7.00508475e-01 -1.37655723e+00
-1.21477088e-02 -9.67553928e-02 1.34545255e+00 -3.32669288e-01
4.39753562e-01 -4.33890045e-01 2.63357401e-01 7.52835274e-01
-6.10246733e-02 5.76147693e-04 7.96997845e-02 1.40738755e-01
-1.12400822e-01 5.26974320e-01 1.30126309e+00 -3.74685496e-01
-3.30703378e-01 7.03906357e-01 -1.80839449e-01 -5.00246510e-02
1.10387814e+00 -1.91892490e-01 -3.68984938e-01 -1.54805169e-01
-6.85615718e-01 -3.02759819e-02 -2.23732382e-01 2.17920035e-01
8.35577488e-01 -1.53377545e+00 -7.63569236e-01 3.93843234e-01
-2.75052607e-01 -4.37105745e-01 8.73167038e-01 1.62059629e+00
-4.11886036e-01 6.79867864e-02 -7.30389178e-01 -6.24943435e-01
-1.29115963e+00 1.16498671e-01 8.34132493e-01 1.55871257e-01
-5.92428088e-01 9.47025657e-01 -1.52459800e-01 2.66289532e-01
-6.21938668e-02 5.64564541e-02 -3.52247179e-01 1.68458804e-01
8.62436593e-01 7.83495545e-01 -3.26252311e-01 -8.99905324e-01
-5.69099069e-01 8.34330976e-01 4.57355976e-01 1.08035639e-01
1.22166169e+00 -3.53478432e-01 -4.12493974e-01 3.26583833e-01
1.27538359e+00 -3.19150060e-01 -1.54508674e+00 1.58380121e-01
-5.80103338e-01 -4.61258441e-01 2.07367375e-01 -7.46963680e-01
-1.66522634e+00 1.14810812e+00 1.22506046e+00 -2.45196447e-01
1.56556225e+00 -5.25921345e-01 8.94598961e-01 -4.63885784e-01
-6.37357160e-02 -1.00208771e+00 2.24275380e-01 2.92475466e-02
8.46062481e-01 -8.22230458e-01 9.17202309e-02 -4.69241351e-01
-7.20110714e-01 1.53359103e+00 8.20528507e-01 -1.76573843e-01
7.93621480e-01 1.38515621e-01 1.23951666e-01 -1.70341954e-01
-7.52064645e-01 -3.18650864e-02 2.25886956e-01 4.17289525e-01
6.77882254e-01 -2.53804594e-01 -2.94236779e-01 3.97165805e-01
5.73340058e-02 5.26702821e-01 2.89027900e-01 4.55420583e-01
-3.14538509e-01 -2.81183600e-01 -2.56267369e-01 3.64904553e-01
-7.70790160e-01 8.22348148e-03 3.71591784e-02 5.41895926e-01
4.80843425e-01 9.57706094e-01 5.05342558e-02 -4.38367039e-01
-5.43452874e-02 2.72307605e-01 4.95915771e-01 -1.80675507e-01
-7.07071483e-01 4.77243960e-01 -1.65117636e-01 -1.19716811e+00
-8.22595119e-01 -5.96257091e-01 -1.38068914e+00 -2.08250031e-01
8.46508667e-02 -8.62188712e-02 6.40652239e-01 7.06420898e-01
5.30763447e-01 5.35918295e-01 1.03563988e+00 -7.14993358e-01
2.35203385e-01 -1.03326035e+00 -7.94998705e-01 3.59433144e-01
4.19517487e-01 -5.59146643e-01 -3.62363964e-01 3.60364944e-01] | [13.901602745056152, 2.7370409965515137] |
e7e0bcd2-0747-44fa-9a0b-cfe28080c4bb | sphere2vec-a-general-purpose-location | 2306.17624 | null | https://arxiv.org/abs/2306.17624v2 | https://arxiv.org/pdf/2306.17624v2.pdf | Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions | Generating learning-friendly representations for points in space is a fundamental and long-standing problem in ML. Recently, multi-scale encoding schemes (such as Space2Vec and NeRF) were proposed to directly encode any point in 2D/3D Euclidean space as a high-dimensional vector, and has been successfully applied to various geospatial prediction and generative tasks. However, all current 2D and 3D location encoders are designed to model point distances in Euclidean space. So when applied to large-scale real-world GPS coordinate datasets, which require distance metric learning on the spherical surface, both types of models can fail due to the map projection distortion problem (2D) and the spherical-to-Euclidean distance approximation error (3D). To solve these problems, we propose a multi-scale location encoder called Sphere2Vec which can preserve spherical distances when encoding point coordinates on a spherical surface. We developed a unified view of distance-reserving encoding on spheres based on the DFS. We also provide theoretical proof that the Sphere2Vec preserves the spherical surface distance between any two points, while existing encoding schemes do not. Experiments on 20 synthetic datasets show that Sphere2Vec can outperform all baseline models on all these datasets with up to 30.8% error rate reduction. We then apply Sphere2Vec to three geo-aware image classification tasks - fine-grained species recognition, Flickr image recognition, and remote sensing image classification. Results on 7 real-world datasets show the superiority of Sphere2Vec over multiple location encoders on all three tasks. Further analysis shows that Sphere2Vec outperforms other location encoder models, especially in the polar regions and data-sparse areas because of its nature for spherical surface distance preservation. Code and data are available at https://gengchenmai.github.io/sphere2vec-website/. | ['Ni Lao', 'Krzysztof Janowicz', 'Stefano Ermon', 'Jiaming Song', 'Yutong He', 'Wenyun Zuo', 'Yao Xuan', 'Gengchen Mai'] | 2023-06-30 | null | null | null | null | ['metric-learning', 'metric-learning', 'remote-sensing-image-classification'] | ['computer-vision', 'methodology', 'miscellaneous'] | [-1.20628789e-01 -1.49103999e-01 -6.14322461e-02 -3.39566797e-01
-7.97864914e-01 -7.39899337e-01 6.85642838e-01 1.28559698e-03
-2.80175596e-01 6.03338003e-01 3.91020119e-01 -3.76843691e-01
4.11352050e-03 -1.27524340e+00 -1.16797328e+00 -7.63527930e-01
-4.26788568e-01 2.32063249e-01 -8.32323283e-02 -3.99777025e-01
4.63251807e-02 6.64774239e-01 -1.65339148e+00 -1.17045462e-01
9.00597751e-01 9.00251508e-01 1.36953384e-01 6.01336241e-01
-1.75557122e-01 2.50520527e-01 -4.88564491e-01 -5.31061292e-01
5.29976785e-01 1.88580025e-02 -4.51420397e-01 -3.67396742e-01
3.65796566e-01 -2.71194339e-01 -9.07522023e-01 1.05362678e+00
6.62487209e-01 1.92938447e-01 7.46279895e-01 -1.47548902e+00
-1.32486570e+00 3.71055305e-01 -3.88375968e-01 9.18258056e-02
1.38949947e-02 -3.58512729e-01 9.51480091e-01 -1.01059985e+00
4.16694671e-01 9.97799695e-01 1.00424802e+00 2.13329151e-01
-7.66969860e-01 -6.38953388e-01 -2.07415432e-01 1.78142175e-01
-2.23973227e+00 -6.34969771e-02 6.11058414e-01 -4.89559680e-01
9.72037375e-01 7.09767938e-01 4.13278639e-01 1.04617476e+00
1.89071938e-01 6.85786128e-01 5.97409368e-01 8.56621638e-02
1.16975434e-01 -1.56912282e-02 -4.06389177e-01 3.63564998e-01
3.59032959e-01 1.68166175e-01 -2.00413510e-01 -1.70201197e-01
1.09248173e+00 3.18655461e-01 -4.79187906e-01 -4.49785471e-01
-1.33724046e+00 1.18969047e+00 1.16223228e+00 4.24585432e-01
-2.66191214e-01 2.87867039e-01 2.25718379e-01 -4.31629568e-02
7.96248972e-01 3.72766256e-01 -2.23366573e-01 -1.69101670e-01
-8.44693780e-01 1.28484696e-01 4.89379227e-01 1.19533217e+00
7.35685587e-01 1.50245503e-01 -6.47302195e-02 7.86574304e-01
2.30820000e-01 1.07873428e+00 5.69135249e-01 -4.02562052e-01
5.14619768e-01 5.11211157e-01 -1.57912299e-02 -1.87748718e+00
-2.49193788e-01 -5.24762034e-01 -1.29171872e+00 -3.35102588e-01
-1.76773936e-01 5.86636923e-02 -7.63082922e-01 1.66800761e+00
4.41062659e-01 7.39380717e-01 1.26062885e-01 9.94938135e-01
1.04847598e+00 1.11592078e+00 -3.16996515e-01 4.42013860e-01
1.01592648e+00 -6.08902395e-01 -3.17161143e-01 2.01550201e-02
8.81922662e-01 -3.28807622e-01 8.58226299e-01 -2.50424802e-01
-5.06913066e-01 -5.81269383e-01 -1.02598464e+00 -3.30816776e-01
-9.67887938e-01 2.07689345e-01 8.83119941e-01 6.29032612e-01
-1.09225488e+00 5.17281055e-01 -7.41597116e-01 -3.16510379e-01
4.50471580e-01 1.78766221e-01 -6.11330271e-01 -4.46851663e-02
-1.39955127e+00 6.15328431e-01 1.59375876e-01 1.33421972e-01
-4.84717935e-01 -8.46987128e-01 -1.33216238e+00 1.48207441e-01
-3.56171191e-01 -3.64315271e-01 4.90950525e-01 -3.99171442e-01
-7.86500096e-01 7.16749191e-01 -1.01237886e-01 -4.54013467e-01
3.09224099e-01 -1.46239296e-01 -7.15164542e-01 -1.66812629e-01
4.00543332e-01 5.98216653e-01 3.97189915e-01 -1.15909076e+00
-3.56063575e-01 -4.92689669e-01 8.26577842e-02 4.63087261e-01
-3.97911131e-01 -4.26914871e-01 -3.47957850e-01 -8.93897891e-01
2.25296706e-01 -1.00394022e+00 -1.42669067e-01 9.52531323e-02
-3.49900901e-01 -1.95424750e-01 5.80058336e-01 -6.62439227e-01
1.24922979e+00 -2.33594966e+00 2.21570715e-01 9.48365331e-02
1.59126550e-01 1.69876203e-01 -1.87783882e-01 5.14416516e-01
-1.18205048e-01 3.40230584e-01 -3.31606150e-01 -1.79655612e-01
1.60524860e-01 3.97470832e-01 -5.51658750e-01 9.00275588e-01
2.78062597e-02 1.04539859e+00 -1.12743723e+00 -1.96835861e-01
4.92309719e-01 1.08851051e+00 -4.43162888e-01 3.91066633e-02
3.20228904e-01 -4.72345464e-02 -2.73583323e-01 6.27107680e-01
1.10279596e+00 -2.85299182e-01 -4.51758325e-01 -1.81159347e-01
-7.61996135e-02 1.92785300e-02 -1.09177208e+00 1.95871532e+00
-4.47961539e-01 6.22872591e-01 -5.76129436e-01 -7.82355905e-01
1.14186835e+00 -6.76636100e-02 6.01247430e-01 -5.78710794e-01
-7.40566999e-02 2.76099324e-01 -4.92208570e-01 -9.79481488e-02
8.26125979e-01 1.35545477e-01 -3.60668242e-01 -3.18486318e-02
-1.77277997e-02 -2.26818055e-01 -3.00512284e-01 2.14410990e-01
7.00158536e-01 5.89981535e-03 8.97945687e-02 -1.84875876e-01
3.39191049e-01 -1.49224147e-01 3.73991966e-01 4.85223651e-01
-9.60004702e-03 1.02943134e+00 6.67067524e-03 -5.32029331e-01
-1.06059635e+00 -1.10839462e+00 -5.02554119e-01 8.03652346e-01
4.95036751e-01 -5.76942444e-01 -4.72610950e-01 -5.92044771e-01
4.58292097e-01 8.07946384e-01 -9.54706907e-01 -2.33544275e-01
-2.70039380e-01 -9.35551167e-01 9.62443590e-01 6.26245916e-01
4.10486132e-01 -3.47156614e-01 -1.89874858e-01 4.66982747e-05
-2.24845007e-01 -7.22069263e-01 -5.72943032e-01 -5.79459965e-02
-3.80742460e-01 -1.01640606e+00 -1.01019239e+00 -6.07716382e-01
5.74716210e-01 7.37422824e-01 8.03248525e-01 -2.51541674e-01
-1.09870538e-01 2.06781238e-01 -4.97748166e-01 -3.53623211e-01
2.24714577e-01 7.04382956e-02 2.76014626e-01 8.01344514e-02
7.39667773e-01 -4.84447837e-01 -6.37943387e-01 3.63554686e-01
-9.78643835e-01 -6.62488639e-02 2.44754478e-01 7.02528715e-01
8.49633396e-01 7.00296611e-02 4.19276744e-01 -3.34108829e-01
2.95749068e-01 -1.01311421e+00 -4.05360818e-01 2.43470833e-01
-1.99376404e-01 -6.10084981e-02 6.28874898e-01 -1.33181274e-01
-1.91851109e-01 -1.03126243e-01 -3.09127837e-01 -7.04991579e-01
4.77464385e-02 5.36993504e-01 -2.38233179e-01 -2.26538509e-01
6.97721362e-01 8.38868618e-01 -2.41667137e-01 -2.68098861e-01
5.98231435e-01 9.87275720e-01 3.94295275e-01 -2.18636498e-01
9.51786876e-01 4.49561477e-01 -7.45622963e-02 -1.03455937e+00
-4.91274923e-01 -5.01870990e-01 -6.44028664e-01 1.65773273e-01
7.03969181e-01 -1.30695808e+00 -3.58839929e-01 4.35342848e-01
-1.02096224e+00 -7.53287459e-03 -3.29423815e-01 4.91482645e-01
-4.19985414e-01 3.80732447e-01 -2.01281995e-01 -5.19158304e-01
-3.73838931e-01 -1.02066624e+00 1.51493478e+00 5.29609881e-02
2.04384655e-01 -1.19353986e+00 2.48068839e-01 -1.59367219e-01
5.56911230e-01 5.39543748e-01 3.79210711e-01 -6.46145761e-01
-3.77828717e-01 -2.83882529e-01 -3.08538377e-01 3.16808522e-01
2.53823459e-01 -2.69706994e-01 -8.67598891e-01 -4.26282048e-01
-2.83662736e-01 1.29720382e-02 7.74423778e-01 3.01545471e-01
1.45619476e+00 -4.44928259e-01 -4.01217163e-01 1.43132627e+00
1.50430882e+00 -1.96875725e-02 6.92144692e-01 2.34947667e-01
1.04864693e+00 8.89395773e-02 4.92995858e-01 4.97336477e-01
8.13252866e-01 7.11104691e-01 6.38026595e-01 -3.97054777e-02
-1.33967400e-01 -6.88517332e-01 1.75371841e-01 1.03217757e+00
4.55445051e-02 -4.11301196e-01 -8.90140593e-01 8.42917323e-01
-1.64541924e+00 -1.03095591e+00 -1.89715505e-01 2.22896624e+00
5.43642044e-01 -5.87240160e-01 -2.66799331e-01 7.17454553e-02
6.58046544e-01 5.23417711e-01 -5.92066407e-01 -1.46664381e-01
-6.09503567e-01 2.41328627e-02 1.06264353e+00 4.34424490e-01
-1.49399161e+00 9.54598725e-01 5.32486820e+00 1.05741727e+00
-1.41833496e+00 3.03866398e-02 4.60659206e-01 -6.17591999e-02
-6.74217522e-01 -5.09928286e-01 -7.40930736e-01 8.85533154e-01
8.55848193e-01 -5.04157364e-01 3.81723046e-01 1.03015101e+00
-2.70172089e-01 4.73289818e-01 -6.99035227e-01 1.61437178e+00
3.98631811e-01 -1.56113565e+00 3.01048428e-01 2.39651456e-01
7.34495640e-01 5.57535768e-01 2.56983817e-01 3.48890722e-01
9.00839865e-02 -1.40413618e+00 5.79094291e-01 1.90434843e-01
1.45443332e+00 -9.51089978e-01 7.77445436e-01 9.45870355e-02
-1.50657487e+00 2.72521824e-01 -9.95017350e-01 1.94433331e-01
7.33318850e-02 4.54862326e-01 -7.57228792e-01 8.97144079e-01
7.99822390e-01 1.16733456e+00 -7.09236085e-01 1.11822319e+00
-7.23279193e-02 3.02147657e-01 -6.25883400e-01 -2.72852760e-02
4.93096262e-01 -2.00866416e-01 4.28649575e-01 1.17257857e+00
9.88326013e-01 8.59716386e-02 -2.13986337e-01 8.15574706e-01
-1.86075550e-02 1.58504635e-01 -1.23194766e+00 1.46647617e-01
9.42646623e-01 9.70380545e-01 -2.82694340e-01 -1.05031431e-01
-2.36248612e-01 1.20989454e+00 1.71707600e-01 2.27417439e-01
-1.27623057e+00 -8.25253308e-01 1.16027939e+00 -6.04689904e-02
4.68907505e-01 -4.95550543e-01 -2.67081738e-01 -1.43819702e+00
-5.20454384e-02 -3.92679423e-01 6.58017844e-02 -7.94443071e-01
-1.06696510e+00 8.31258714e-01 -2.44433686e-01 -1.49375415e+00
1.39334267e-02 -5.04577637e-01 -3.70902270e-01 9.21089649e-01
-1.52664292e+00 -1.27964163e+00 -4.87129599e-01 8.19075048e-01
9.63376015e-02 -1.95637688e-01 1.05041718e+00 5.09030700e-01
-2.65647233e-01 8.71381879e-01 8.18773746e-01 3.20423573e-01
4.39892292e-01 -1.37567699e+00 9.42380726e-01 7.72158802e-01
5.89637995e-01 5.89691162e-01 2.70681262e-01 -5.76160908e-01
-1.70167077e+00 -1.76909077e+00 1.13897669e+00 -5.44184566e-01
5.44251859e-01 -6.00587964e-01 -8.66700530e-01 7.31802106e-01
-3.11681300e-01 2.96247244e-01 1.02518535e+00 -1.63232744e-01
-5.53884387e-01 -6.28854781e-02 -1.15397835e+00 4.21586156e-01
1.30109203e+00 -7.36987412e-01 -4.34371114e-01 6.60237908e-01
9.37725484e-01 -6.21444046e-01 -1.18987668e+00 4.55061704e-01
2.99657583e-01 -6.04485095e-01 1.26226497e+00 -4.16421443e-01
3.83102179e-01 -5.55513859e-01 -8.94696712e-01 -1.69637728e+00
-5.81750393e-01 -1.12318948e-01 -3.76714282e-02 1.04990506e+00
1.44129992e-01 -7.56444931e-01 5.44352531e-01 1.69323131e-01
-2.78492600e-01 -7.94495761e-01 -1.16892457e+00 -9.54253435e-01
3.31529558e-01 -4.83002067e-01 1.34004784e+00 1.19818759e+00
-3.39829385e-01 2.84295587e-04 -4.35222775e-01 6.70534372e-01
5.09635210e-01 1.65308222e-01 9.30579007e-01 -9.40960944e-01
1.96231201e-01 -3.40360850e-01 -1.08319616e+00 -1.28948069e+00
1.04338892e-01 -1.33622921e+00 -2.16207877e-01 -1.67699838e+00
-2.52577841e-01 -7.42096484e-01 -2.05942154e-01 3.38510960e-01
-1.24331504e-01 3.87397140e-01 1.36246923e-02 2.34770641e-01
-3.71863127e-01 1.04437351e+00 8.15376163e-01 -2.52345502e-01
1.05864130e-01 -3.23482275e-01 -8.00163031e-01 2.42084309e-01
7.31427908e-01 -1.42038047e-01 -4.36426073e-01 -9.85390186e-01
2.71640301e-01 -3.46142620e-01 4.83630866e-01 -1.22229326e+00
2.76530117e-01 -7.05421939e-02 4.43360209e-01 -7.83874989e-01
4.31942731e-01 -8.54448378e-01 4.59730715e-01 8.02975893e-02
5.19134402e-02 -3.23657207e-02 1.97849244e-01 7.36559808e-01
-3.61576945e-01 3.35573792e-01 5.17381191e-01 2.39471257e-01
-9.22843695e-01 8.52744699e-01 3.24298024e-01 -2.99686398e-02
1.34375656e+00 -2.77387947e-01 -3.94132197e-01 -4.03105110e-01
-3.04430693e-01 1.67782098e-01 6.81270659e-01 8.02334130e-01
7.56498575e-01 -1.92171478e+00 -9.42351103e-01 6.43233478e-01
3.64608973e-01 4.02332008e-01 4.38024610e-01 4.54984188e-01
-9.10177827e-01 6.60814106e-01 -4.96273898e-02 -6.99229717e-01
-7.34824777e-01 5.69037139e-01 3.94805759e-01 3.65191936e-01
-5.75515747e-01 1.29924715e+00 3.68419319e-01 -8.09720159e-01
1.58035487e-01 -3.30058426e-01 3.30226682e-02 -3.01890243e-02
6.67358994e-01 2.71117747e-01 1.35455757e-01 -1.36551988e+00
-5.57328343e-01 7.75308430e-01 4.29257512e-01 4.12875623e-01
1.59678292e+00 -2.65117716e-02 3.53128240e-02 3.82624805e-01
1.66174901e+00 -1.48889244e-01 -9.44791555e-01 -1.87170714e-01
-4.06288356e-01 -8.69064629e-01 9.75512713e-03 -2.15352461e-01
-1.20463836e+00 9.73961353e-01 4.94686067e-01 2.29175657e-01
6.82506859e-01 -1.37735024e-01 9.64160502e-01 1.70014799e-01
6.97856069e-01 -6.48752451e-01 -5.56790888e-01 5.60920835e-01
1.16684222e+00 -1.15084136e+00 -1.97766304e-01 -2.04449013e-01
-7.75593162e-01 7.47508168e-01 4.69199151e-01 -3.60474676e-01
9.43047464e-01 -1.00655042e-01 -2.09593639e-01 -5.98409437e-02
-2.06395254e-01 -1.40943125e-01 4.56438929e-01 8.36157739e-01
2.67561495e-01 5.94051421e-01 9.26174894e-02 6.53483748e-01
-7.43666768e-01 -2.67627627e-01 3.06390315e-01 5.29658318e-01
-2.59428769e-01 -6.98938668e-01 -3.61963391e-01 5.29798508e-01
-1.06598526e-01 -3.33769679e-01 -2.14575350e-01 5.83608687e-01
2.88774520e-01 6.65598214e-01 4.74194735e-01 -7.73395658e-01
2.72666305e-01 -3.47923994e-01 1.28533885e-01 -3.88304651e-01
-1.40023202e-01 -3.94869357e-01 -3.35091144e-01 -6.84909403e-01
-1.29123166e-01 -6.37175083e-01 -1.08662713e+00 -7.06152141e-01
-2.30363101e-01 3.35819066e-01 8.79100561e-01 2.31447816e-01
8.78295064e-01 1.47785306e-01 9.66488659e-01 -1.05792129e+00
-5.72533190e-01 -8.00610781e-01 -1.01926291e+00 4.95497882e-01
3.15892041e-01 -7.62116015e-01 -5.07457972e-01 -4.00144458e-01] | [7.73219633102417, -2.040626049041748] |
60350f11-1044-4181-abdb-4c8344aae0ce | learning-to-embed-adopting-transformer-based | 2212.03725 | null | https://arxiv.org/abs/2212.03725v1 | https://arxiv.org/pdf/2212.03725v1.pdf | Learning-To-Embed: Adopting Transformer based models for E-commerce Products Representation Learning | Learning low-dimensional representation for large number of products present in an e-commerce catalogue plays a vital role as they are helpful in tasks like product ranking, product recommendation, finding similar products, modelling user-behaviour etc. Recently, a lot of tasks in the NLP field are getting tackled using the Transformer based models and these deep models are widely applicable in the industries setting to solve various problems. With this motivation, we apply transformer based model for learning contextual representation of products in an e-commerce setting. In this work, we propose a novel approach of pre-training transformer based model on a users generated sessions dataset obtained from a large fashion e-commerce platform to obtain latent product representation. Once pre-trained, we show that the low-dimension representation of the products can be obtained given the product attributes information as a textual sentence. We mainly pre-train BERT, RoBERTa, ALBERT and XLNET variants of transformer model and show a quantitative analysis of the products representation obtained from these models with respect to Next Product Recommendation(NPR) and Content Ranking(CR) tasks. For both the tasks, we collect an evaluation data from the fashion e-commerce platform and observe that XLNET model outperform other variants with a MRR of 0.5 for NPR and NDCG of 0.634 for CR. XLNET model also outperforms the Word2Vec based non-transformer baseline on both the downstream tasks. To the best of our knowledge, this is the first and novel work for pre-training transformer based models using users generated sessions data containing products that are represented with rich attributes information for adoption in e-commerce setting. These models can be further fine-tuned in order to solve various downstream tasks in e-commerce, thereby eliminating the need to train a model from scratch. | ['Sreekanth Vempati', 'Lakshya Kumar'] | 2022-12-07 | null | null | null | null | ['product-recommendation'] | ['miscellaneous'] | [ 1.18173212e-01 -1.73381940e-01 -2.35999048e-01 -7.44248331e-01
-7.00695336e-01 -8.63963902e-01 6.33713245e-01 3.10232043e-01
-5.68858683e-02 2.36969844e-01 5.36960065e-01 -3.38976353e-01
-5.80715299e-01 -1.05893767e+00 -7.69554913e-01 -5.39156377e-01
-8.97107869e-02 8.47968161e-01 -1.77110955e-01 -5.31769216e-01
1.97198167e-01 6.16870150e-02 -1.57638621e+00 7.70207882e-01
4.55374628e-01 1.20921445e+00 3.88626486e-01 4.48978245e-01
-5.78271374e-02 4.25327718e-01 -1.03462346e-01 -9.28812742e-01
5.86044550e-01 -5.53094335e-02 -7.41308808e-01 3.35871130e-01
2.66074657e-01 -1.39462516e-01 -7.97472447e-02 8.31807733e-01
4.03775960e-01 3.66076976e-01 8.42099488e-01 -8.87589991e-01
-1.10757184e+00 8.74531984e-01 -4.46937829e-01 -3.51050906e-02
1.62668809e-01 -2.23224267e-01 1.53300238e+00 -8.42222869e-01
5.47555745e-01 1.30576587e+00 5.94190598e-01 6.02711812e-02
-1.06819034e+00 -4.01348174e-01 3.31805229e-01 5.15920743e-02
-8.05096805e-01 4.78313267e-02 7.49271154e-01 -3.15971613e-01
1.14410400e+00 3.35807025e-01 4.47498947e-01 1.19577968e+00
1.60393834e-01 9.72566783e-01 1.01579463e+00 -2.77444929e-01
-1.25621006e-01 6.54291153e-01 5.18956602e-01 3.72249782e-01
-1.38639167e-01 1.44967791e-02 -2.14305162e-01 1.02401838e-01
6.90778434e-01 4.30359811e-01 1.97050527e-01 -2.81618983e-01
-9.91924405e-01 1.29281366e+00 5.76785505e-01 3.89105469e-01
-7.81183243e-01 -7.79096261e-02 5.95640004e-01 7.02676892e-01
6.96154892e-01 5.99171996e-01 -1.20315075e+00 9.54916030e-02
-3.51411790e-01 4.22087193e-01 8.26825142e-01 1.08433509e+00
2.98508227e-01 -2.75676370e-01 -4.82819498e-01 1.09994960e+00
5.39515674e-01 1.03573903e-01 7.49781549e-01 -2.72873819e-01
5.32333255e-01 4.53392982e-01 -7.81104192e-02 -8.85845721e-01
-1.92076370e-01 -1.09335494e+00 -7.93520629e-01 -4.73905861e-01
3.46079737e-01 1.17504001e-01 -1.09246254e+00 1.40607738e+00
1.91336185e-01 2.18335143e-03 1.68012708e-01 7.25218475e-01
9.00818884e-01 9.91855919e-01 2.03972980e-01 6.69449121e-02
1.79711115e+00 -1.20677114e+00 -5.38152218e-01 1.25819325e-01
9.37074304e-01 -1.14014733e+00 1.15235519e+00 6.63127542e-01
-6.28468513e-01 -7.81405032e-01 -9.23710644e-01 -1.93788826e-01
-7.65189528e-01 2.95090646e-01 1.14651668e+00 6.06141210e-01
-6.58272684e-01 7.88283229e-01 -3.19967180e-01 -6.62942171e-01
3.27962458e-01 4.97430950e-01 -2.28494361e-01 -3.29881400e-01
-1.37533653e+00 6.98267102e-01 2.48002663e-01 3.01924109e-01
-8.25781167e-01 -7.28509128e-01 -8.50651979e-01 1.45214945e-01
2.36381471e-01 -6.82276011e-01 1.18300045e+00 -7.41797686e-01
-1.42608917e+00 5.98071754e-01 2.60331959e-01 -5.99867523e-01
1.04466259e-01 -3.45484436e-01 -5.81133366e-01 -5.86421251e-01
1.23497518e-02 4.28016007e-01 5.66710889e-01 -1.05917907e+00
-6.75164282e-01 -6.17979586e-01 3.32907796e-01 2.53677815e-01
-4.72018331e-01 -1.59741882e-02 -4.57722574e-01 -6.32358551e-01
-6.72259107e-02 -1.09043431e+00 -4.13390428e-01 -7.98515439e-01
-3.87576610e-01 -4.91053998e-01 4.38745141e-01 -6.20536685e-01
8.28079522e-01 -2.07634830e+00 -8.59793052e-02 3.20621192e-01
-1.57120317e-01 2.21866116e-01 -6.27282202e-01 5.81358016e-01
-5.88774011e-02 2.38106120e-02 4.91244763e-01 -2.19782189e-01
3.46637845e-01 9.78716686e-02 -4.84938949e-01 1.09900162e-01
2.59744711e-02 1.25690472e+00 -7.05739856e-01 4.15978059e-02
1.57870173e-01 6.53576314e-01 -6.07445300e-01 8.62299427e-02
-3.91020954e-01 1.71291262e-01 -6.54802859e-01 5.75570166e-01
6.78202510e-01 -2.44249046e-01 2.22257838e-01 -5.84952056e-01
2.63957173e-01 5.38065910e-01 -9.13563848e-01 1.76505637e+00
-1.08650994e+00 9.50752497e-02 -2.29133084e-01 -1.13665783e+00
1.07025337e+00 3.23356360e-01 3.86053324e-01 -1.00941753e+00
3.11047912e-01 8.56430531e-02 1.36789521e-02 -4.32570130e-01
7.18713760e-01 -2.53282994e-01 -2.22449437e-01 4.16059375e-01
3.02824080e-01 2.48737976e-01 2.58083522e-01 1.19182654e-01
6.78670049e-01 1.70392960e-01 -2.79045682e-02 -1.38190940e-01
4.16295916e-01 -7.15500712e-02 1.89908713e-01 5.91028929e-01
4.21457857e-01 4.58963752e-01 3.28049809e-01 -6.70702040e-01
-9.42087948e-01 -7.91748881e-01 -2.84793496e-01 1.58534062e+00
-1.56475648e-01 -6.91544592e-01 -2.56685555e-01 -9.21705425e-01
1.30983815e-01 7.73154616e-01 -7.85011709e-01 -1.73960105e-01
-3.56729895e-01 -8.44792485e-01 -1.44305006e-01 6.26945198e-01
3.36531550e-01 -1.10296226e+00 2.67871350e-01 4.13560897e-01
4.97547053e-02 -1.04087782e+00 -5.80236673e-01 4.93201166e-01
-1.06637299e+00 -6.08980536e-01 -6.38106763e-01 -1.11232901e+00
3.84774297e-01 1.26235560e-01 1.40506077e+00 -3.42509121e-01
-1.21047162e-02 1.27421796e-01 -6.83601856e-01 -4.02487546e-01
-1.94165424e-01 4.03003037e-01 -1.96547493e-01 1.38509393e-01
8.53333473e-01 -5.11808932e-01 -6.85564816e-01 3.88709486e-01
-7.51982033e-01 -1.88991785e-01 8.91760826e-01 8.77612829e-01
6.26205325e-01 5.88802576e-01 8.30534279e-01 -1.54688716e+00
9.68075752e-01 -6.86669588e-01 -3.88835043e-01 1.03371978e-01
-8.56881022e-01 1.26195580e-01 6.65771127e-01 -7.41953194e-01
-1.00311589e+00 8.92517865e-02 -4.58194047e-01 -1.14607707e-01
-1.01823568e-01 8.40677023e-01 -1.75988868e-01 6.64872468e-01
4.04490978e-01 9.78163853e-02 -4.11975056e-01 -1.06534994e+00
6.72917306e-01 7.95047998e-01 1.37957418e-02 -4.19627279e-01
6.93424463e-01 -1.32826194e-01 1.18509596e-02 -2.46136650e-01
-1.22660589e+00 -7.83811688e-01 -5.03284991e-01 4.96471763e-01
5.36326647e-01 -9.20907080e-01 -7.31367350e-01 2.86991149e-03
-8.44811797e-01 6.84883147e-02 -3.23061734e-01 6.04372144e-01
-3.37493449e-01 -7.68596828e-02 -9.37774241e-01 -5.71949899e-01
-7.21051753e-01 -1.02624154e+00 1.19775355e+00 -2.74412274e-01
-7.18620047e-02 -1.13975430e+00 4.56348918e-02 6.39321208e-01
5.20647287e-01 -1.80568218e-01 1.22887850e+00 -1.13268816e+00
-3.10048461e-01 -4.69445646e-01 -6.21270053e-02 5.02587974e-01
1.99585930e-01 -7.76453435e-01 -8.65915656e-01 -3.40549678e-01
3.42782657e-03 -2.10719228e-01 1.07372737e+00 3.94069344e-01
8.60285878e-01 -5.23689926e-01 -1.59159720e-01 3.66025001e-01
1.54124641e+00 9.51762348e-02 6.54279470e-01 3.77441734e-01
6.98332369e-01 9.58927572e-01 9.26683903e-01 3.06034237e-01
3.60250622e-01 7.58781612e-01 2.67247677e-01 -7.30507374e-02
1.64228920e-02 -6.66615605e-01 2.80182809e-01 7.42627084e-01
9.73607749e-02 -3.67961556e-01 -1.49221852e-01 6.51564002e-01
-1.91957355e+00 -7.69906819e-01 -1.85790211e-01 2.07410741e+00
6.08120978e-01 1.16616160e-01 2.52666235e-01 -6.39724657e-02
3.43890548e-01 -1.21889338e-01 -3.76005083e-01 -6.68809772e-01
1.88721105e-01 3.52585495e-01 4.67092425e-01 2.09650904e-01
-1.38944256e+00 9.83453155e-01 5.11627722e+00 9.77408290e-01
-7.56014228e-01 2.65296191e-01 7.58309007e-01 2.33417228e-02
-4.59775209e-01 -1.97865278e-01 -1.00030529e+00 2.54930437e-01
1.19333839e+00 1.58322193e-02 3.25882673e-01 1.00782859e+00
8.37269127e-02 5.07272840e-01 -1.42432654e+00 1.08857870e+00
-1.27504602e-01 -1.04774034e+00 2.62034506e-01 3.71777445e-01
7.17827380e-01 -3.63312811e-02 7.12161839e-01 8.59332740e-01
5.34112930e-01 -1.10519254e+00 3.76973361e-01 -4.28107986e-03
3.94140869e-01 -8.19600523e-01 1.20513153e+00 1.85630500e-01
-1.27721167e+00 -1.99607998e-01 -6.50414884e-01 6.35108203e-02
1.98685870e-01 6.41936421e-01 -9.05404449e-01 6.63889050e-01
5.67998827e-01 1.12222672e+00 -4.81915921e-01 6.40437424e-01
2.27457523e-01 4.85546321e-01 1.70621946e-02 -9.14901569e-02
5.88023543e-01 -4.11558717e-01 -2.60828137e-02 1.26050210e+00
5.83999872e-01 -1.53713435e-01 1.27261907e-01 7.50813723e-01
-2.62812972e-01 5.68175733e-01 -6.31285250e-01 -2.80765831e-01
-2.79094696e-01 1.73748672e+00 -5.79182863e-01 -1.62744462e-01
-5.21106660e-01 9.49449897e-01 4.41369116e-02 3.06728959e-01
-5.50337911e-01 -2.20647156e-01 5.90355873e-01 2.44855255e-01
7.81176984e-01 8.20192844e-02 8.85093585e-02 -1.01097012e+00
-5.21678776e-02 -9.69811440e-01 3.35631430e-01 -4.64191556e-01
-1.85355520e+00 9.58883941e-01 -1.66072637e-01 -1.41838670e+00
-4.68367398e-01 -7.96898663e-01 -1.55426204e-01 8.91196370e-01
-1.52542377e+00 -1.51686227e+00 2.42131561e-01 5.35258770e-01
9.27755773e-01 -3.48323137e-01 8.48831654e-01 4.96938258e-01
-2.60714829e-01 5.95076323e-01 3.74609351e-01 3.32549587e-02
5.96399724e-01 -1.32127166e+00 4.31300789e-01 3.03770244e-01
5.14349580e-01 1.07910025e+00 6.00714207e-01 -4.64366883e-01
-1.64374399e+00 -1.46099234e+00 1.03965890e+00 -6.20905459e-01
5.70723712e-01 -6.70257747e-01 -4.72047001e-01 9.41511273e-01
2.72359908e-01 -3.16226661e-01 8.56006324e-01 8.09124947e-01
-5.16118705e-01 -3.61102402e-01 -1.21758747e+00 2.62751102e-01
8.79472792e-01 -3.51157755e-01 -4.01971877e-01 8.62110317e-01
9.07607973e-01 1.06476858e-01 -1.20734894e+00 2.74794936e-01
6.46957994e-01 -5.41268826e-01 1.15736067e+00 -8.35754931e-01
4.67389137e-01 1.82697162e-01 -3.97930801e-01 -1.56075978e+00
-6.89913869e-01 -2.96576530e-01 1.68105260e-01 1.60755515e+00
7.50453711e-01 -4.57614124e-01 7.91940868e-01 4.06029820e-01
5.22630960e-02 -9.21790957e-01 -1.12551026e-01 -6.83323562e-01
3.94342840e-02 -4.49975222e-01 8.39303374e-01 7.18495607e-01
-1.63655788e-01 1.09179997e+00 -5.44821799e-01 -2.15133756e-01
4.18393970e-01 4.92305636e-01 5.50022423e-01 -1.33462858e+00
-6.19415224e-01 -1.22205853e-01 -3.18128765e-01 -1.44552147e+00
1.81442883e-03 -1.33769906e+00 -2.83254236e-01 -1.61548591e+00
3.55414003e-01 -5.72506607e-01 -7.03599751e-01 2.46574491e-01
3.02282393e-01 3.84282917e-01 9.90142748e-02 -2.65945364e-02
-5.61168730e-01 4.63731170e-01 1.38144398e+00 -3.34782362e-01
-2.77066737e-01 3.96824539e-01 -1.14639533e+00 2.77175069e-01
6.64220929e-01 -4.00498360e-01 -8.72598350e-01 -3.08007836e-01
5.84196210e-01 -2.17569113e-01 -7.15406463e-02 -1.31301522e-01
-1.41041160e-01 2.90640324e-01 4.88127470e-01 -7.07117200e-01
3.44817996e-01 -1.06794810e+00 2.21696958e-01 1.43545702e-01
-6.41971052e-01 1.00651816e-01 1.29546793e-02 6.49480760e-01
-2.53171712e-01 -3.88835877e-01 1.11987740e-01 -4.10753340e-01
-6.10801637e-01 4.96686906e-01 -1.25494495e-01 -5.26282728e-01
6.42464697e-01 5.76199070e-02 -8.35926980e-02 -2.97956675e-01
-8.35769117e-01 -1.07530123e-02 -2.80901670e-01 9.24453497e-01
4.38107252e-01 -1.44424701e+00 -7.72895813e-01 3.05784971e-01
3.36101830e-01 -4.68639880e-01 2.34321326e-01 6.40854955e-01
-9.10987779e-02 9.86073732e-01 -7.40089938e-02 -2.45302305e-01
-1.07615077e+00 1.04763007e+00 -5.18394783e-02 -9.49463248e-01
-5.19038737e-01 7.33723581e-01 5.12510955e-01 -7.43639171e-01
7.63352588e-02 -4.35261130e-01 -7.17693567e-01 1.62602812e-01
4.01930273e-01 1.39598036e-02 4.59637851e-01 -7.37816632e-01
-3.76022719e-02 7.02010453e-01 -7.93463290e-01 4.18592691e-02
1.81992638e+00 -1.62467495e-01 2.91974004e-02 1.37280852e-01
1.68615282e+00 -1.54149354e-01 -6.96480393e-01 -5.26076972e-01
3.06902863e-02 -5.49576521e-01 3.01004201e-01 -9.17545080e-01
-1.43814147e+00 6.65610552e-01 8.08296025e-01 3.29756379e-01
1.08385491e+00 2.12750822e-01 1.05897808e+00 3.85076880e-01
4.57673967e-01 -7.21694887e-01 6.41102791e-02 3.60966742e-01
1.02626967e+00 -1.16825449e+00 -2.88558424e-01 -5.08426964e-01
-9.95525181e-01 7.47108161e-01 2.86427140e-01 -2.50273883e-01
1.00194204e+00 -6.04576468e-02 9.55312029e-02 -4.85471517e-01
-8.61507833e-01 -2.73851037e-01 5.98963439e-01 5.71129382e-01
8.68765771e-01 1.34978801e-01 -3.09715390e-01 8.45523000e-01
-4.18103755e-01 -2.14438606e-02 1.89569034e-02 4.35199440e-01
5.53848408e-02 -1.52996004e+00 2.21079737e-01 8.08864594e-01
-6.32649958e-01 -4.12855923e-01 -8.07407498e-02 3.47312152e-01
-1.61533672e-02 1.14362991e+00 -1.92608863e-01 -6.25205457e-01
5.97780466e-01 -8.05292279e-02 5.04592538e-01 -8.52246225e-01
-1.09729588e+00 3.96131098e-01 4.07192677e-01 -3.39269251e-01
-2.33684257e-01 -4.47317690e-01 -6.08690143e-01 -1.90299600e-01
-5.34945905e-01 3.11131328e-01 7.96697319e-01 7.12655962e-01
4.14478034e-01 5.63621402e-01 6.81270599e-01 -5.72006345e-01
-8.44309449e-01 -1.36213517e+00 -1.13270593e+00 8.97211969e-01
-3.59500125e-02 -5.10728896e-01 -7.84429070e-03 -5.48064522e-02] | [10.102323532104492, 5.8666253089904785] |
e9539760-fc0c-41b6-ba97-5fd8c762b292 | deep-learning-based-dominant-index-lesion | 2303.03494 | null | https://arxiv.org/abs/2303.03494v1 | https://arxiv.org/pdf/2303.03494v1.pdf | Deep Learning Based Dominant Index Lesion Segmentation for MR-guided Radiation Therapy of Prostate Cancer | Dose escalation radiotherapy allows increased control of prostate cancer (PCa) but requires segmentation of dominant index lesions (DIL), motivating the development of automated methods for fast, accurate, and consistent segmentation of PCa DIL. We evaluated five deep-learning networks on apparent diffusion coefficient (ADC) MRI from 500 lesions in 365 patients arising from internal training Dataset 1 (1.5Tesla GE MR with endorectal coil), external ProstateX Dataset 2 (3Tesla Siemens MR), and internal inter-rater Dataset 3 (3Tesla Philips MR). The networks include: multiple resolution residually connected network (MRRN) and MRRN regularized in training with deep supervision (MRRN-DS), Unet, Unet++, ResUnet, and fast panoptic segmentation (FPSnet) as well as fast panoptic segmentation with smoothed labels (FPSnet-SL). Models were evaluated by volumetric DIL segmentation accuracy using Dice similarity coefficient (DSC) and detection accuracy, as a function of lesion aggressiveness, size, and location (Dataset 1 and 2), and accuracy with respect to two-raters (on Dataset 3). In general MRRN-DS more accurately segmented tumors than other methods on the testing datasets. MRRN-DS significantly outperformed ResUnet in Dataset2 (DSC of 0.54 vs. 0.44, p<0.001) and the Unet++ in Dataset3 (DSC of 0.45 vs. p=0.04). FPSnet-SL was similarly accurate as MRRN-DS in Dataset2 (p = 0.30), but MRRN-DS significantly outperformed FPSnet and FPSnet-SL in both Dataset1 (0.60 vs 0.51 [p=0.01] and 0.54 [p=0.049] respectively) and Dataset3 (0.45 vs 0.06 [p=0.002] and 0.24 [p=0.004] respectively). Finally, MRRN-DS produced slightly higher agreement with experienced radiologist than two radiologists in Dataset 3 (DSC of 0.45 vs. 0.41). | ['Harini Veeraraghavan', 'Neelam Tyagi', 'Michael Zelefsky', 'Andreas Wibmer', 'Anton Nosov', 'Jue Jiang', 'Josiah Simeth'] | 2023-03-06 | null | null | null | null | ['panoptic-segmentation', 'lesion-segmentation'] | ['computer-vision', 'medical'] | [ 1.34007469e-01 3.09057981e-01 -4.91503745e-01 -3.11787367e-01
-1.06044590e+00 -1.01305604e+00 6.14705980e-01 3.52906972e-01
-7.68850029e-01 8.02006662e-01 3.37122291e-01 -6.08494699e-01
-5.46239972e-01 -6.91576242e-01 -3.22472900e-01 -8.09539855e-01
-5.82808316e-01 7.49242008e-01 3.98573250e-01 2.35965148e-01
-9.86491679e-04 8.23968947e-01 -1.24692880e-01 1.23605646e-01
8.58600318e-01 8.06146383e-01 4.11671698e-01 1.07332504e+00
1.48897439e-01 8.56052339e-01 -2.73402184e-01 -3.51121515e-01
2.60089338e-01 -4.69109237e-01 -8.10802102e-01 -2.05096081e-01
7.24788308e-01 -2.46267095e-01 -6.69057369e-01 9.39972401e-01
6.76522195e-01 -2.01671705e-01 7.97042012e-01 -5.71333647e-01
-6.21283054e-01 8.55487645e-01 -8.09660137e-01 7.25556254e-01
-4.25020546e-01 5.93833983e-01 2.29713738e-01 -2.20756963e-01
8.47123086e-01 7.36406147e-01 1.31529915e+00 7.23604202e-01
-1.31516206e+00 -6.11721873e-01 -3.17242712e-01 -2.53949195e-01
-9.95222151e-01 -7.73189142e-02 -4.45157439e-02 -3.43423128e-01
6.58093333e-01 7.50020683e-01 8.10602844e-01 8.35488856e-01
1.04816616e+00 3.79009485e-01 1.30271697e+00 2.45982438e-01
3.87323558e-01 -1.75659150e-01 2.48425439e-01 5.36990762e-01
3.13283741e-01 -1.31974304e-02 5.85725367e-01 -2.48463646e-01
1.43253195e+00 -8.20097476e-02 -3.35676074e-01 -1.32108241e-01
-9.46867406e-01 9.34602499e-01 1.09224212e+00 6.12219393e-01
-4.54740047e-01 2.27922902e-01 7.07448125e-01 -1.23181142e-01
7.25810155e-02 5.24577677e-01 -6.69087693e-02 4.29861955e-02
-9.59423900e-01 2.79047340e-02 5.99985838e-01 4.44632262e-01
-4.14576769e-01 -1.05442151e-01 -1.43318027e-01 1.02299166e+00
1.00537762e-01 3.60756427e-01 1.27451468e+00 -1.17163169e+00
4.07552607e-02 1.96345180e-01 -2.62410015e-01 -7.79169142e-01
-1.04191351e+00 -1.08211148e+00 -1.32089877e+00 -2.22249124e-02
7.57262111e-01 5.87562583e-02 -1.50115442e+00 1.38547266e+00
-1.90602064e-01 -3.96631211e-01 5.51549345e-02 9.37150180e-01
8.13355863e-01 2.22897306e-01 4.30210203e-01 -2.61799186e-01
1.39430642e+00 -9.91289437e-01 -3.49739909e-01 -2.87931979e-01
1.00936902e+00 -3.51134032e-01 7.77054369e-01 3.23047549e-01
-1.32185125e+00 -3.19370449e-01 -7.82515943e-01 2.55707383e-01
8.21963027e-02 2.19956208e-02 7.10667729e-01 9.97614503e-01
-1.45301962e+00 8.82624507e-01 -1.54507720e+00 -4.63711232e-01
9.69703078e-01 8.28344584e-01 -5.18610358e-01 -5.04074037e-01
-7.77312398e-01 1.18524969e+00 2.60511458e-01 2.58216690e-02
-1.32323837e+00 -1.04284155e+00 -7.42816627e-01 -3.69093686e-01
-1.42474577e-01 -4.62726772e-01 1.11702168e+00 -6.97827041e-01
-1.03102994e+00 8.73890042e-01 1.95336580e-01 -8.38295698e-01
9.50341702e-01 4.26122248e-01 -4.07890171e-01 3.29848588e-01
3.13899636e-01 8.39997947e-01 7.21176947e-03 -1.29067552e+00
-3.77625197e-01 -9.48993921e-01 -2.78063267e-01 3.93190950e-01
2.17304602e-01 -1.65877119e-01 -1.45253256e-01 -1.26084223e-01
4.97481972e-01 -1.02255821e+00 -9.32342708e-01 7.25942180e-02
-5.14339387e-01 1.67219698e-01 5.21167517e-01 -1.32058573e+00
5.64463854e-01 -1.89726758e+00 -2.17086881e-01 4.01469260e-01
6.89867556e-01 3.12691569e-01 5.25970384e-02 -6.55580938e-01
-4.33646590e-01 4.42601681e-01 -7.16733217e-01 -1.78751219e-02
-5.97971022e-01 2.95861781e-01 5.45235336e-01 9.50242400e-01
-2.22054526e-01 1.07148063e+00 -1.08336771e+00 -4.14747268e-01
4.21244532e-01 3.60962093e-01 -8.35347623e-02 -4.05195385e-01
5.04583120e-01 6.77628934e-01 -1.65032417e-01 4.10615176e-01
7.88671315e-01 -2.98698515e-01 3.69969785e-01 -2.39163607e-01
-2.14395434e-01 -1.90246925e-01 -7.13923752e-01 1.46348846e+00
-3.97762448e-01 7.29446232e-01 3.50204408e-01 -4.46326137e-01
9.43645000e-01 1.76957741e-01 6.70381665e-01 -1.02755952e+00
8.51280056e-03 6.43311620e-01 8.29319239e-01 -2.11810321e-02
3.41386139e-01 -5.04632115e-01 2.54326612e-01 9.11207423e-02
-1.55138776e-01 -3.34095240e-01 7.29155913e-02 2.77989239e-01
1.55285180e+00 -6.11244261e-01 8.58521760e-02 -6.20851994e-01
4.98922706e-01 2.64780492e-01 3.39012086e-01 9.54771519e-01
-8.20835054e-01 6.64593160e-01 6.71418190e-01 -3.30702186e-01
-1.05388236e+00 -1.42505264e+00 -8.38202357e-01 1.77409485e-01
1.78060994e-01 1.17697068e-01 -5.08843064e-01 -9.92366135e-01
1.30175408e-02 8.47482502e-01 -6.80434525e-01 4.03386354e-02
-7.81076550e-01 -1.20751154e+00 8.34725618e-01 8.84405494e-01
4.88459796e-01 -8.53708982e-01 -2.46594250e-01 2.10143179e-01
2.02554926e-01 -7.62697458e-01 -1.82580426e-01 5.23563445e-01
-1.39547932e+00 -9.34278071e-01 -1.31983244e+00 -4.13336903e-01
7.44074881e-01 -2.31850132e-01 9.17408764e-01 -1.62527978e-01
-3.91114622e-01 3.05160791e-01 3.60569358e-01 1.61984935e-01
-5.97707570e-01 7.76823461e-02 -2.29551092e-01 -8.36321533e-01
1.71080288e-02 -2.00090036e-01 -7.21030593e-01 3.61191452e-01
-9.29469705e-01 -2.01453194e-01 9.37226713e-01 6.25661910e-01
8.73345017e-01 8.40953365e-03 3.79345298e-01 -7.56935060e-01
6.73890352e-01 -4.36561048e-01 -3.65735203e-01 -3.64077948e-02
-5.97265124e-01 -5.10654509e-01 6.08210325e-01 -4.27451670e-01
-7.56979346e-01 -4.56607640e-02 1.80247080e-04 -3.17629069e-01
-2.43244246e-01 2.71651745e-01 4.65451866e-01 -3.43360215e-01
9.28057790e-01 1.31009609e-01 1.48164019e-01 9.21551138e-03
1.21692672e-01 2.82074273e-01 9.11044121e-01 -7.12303370e-02
3.82109880e-01 4.99590725e-01 2.23731562e-01 -3.69352877e-01
-3.00351292e-01 -2.29804188e-01 -7.20853508e-01 1.93305705e-02
1.14994907e+00 -7.09323049e-01 -3.00824314e-01 3.92173290e-01
-4.98163849e-01 -8.05022240e-01 -5.99286795e-01 8.05326402e-01
-3.99598598e-01 2.65188664e-01 -1.11012495e+00 -2.43030399e-01
-5.97663164e-01 -1.67588079e+00 4.35686290e-01 5.57237685e-01
-3.84369045e-01 -1.48742843e+00 -1.91633422e-02 2.00016499e-01
8.12807739e-01 5.72370410e-01 6.48587704e-01 -1.05620646e+00
-8.05213377e-02 -3.72202218e-01 -7.65215158e-01 1.88352361e-01
3.91004533e-01 -3.28237355e-01 -5.35006166e-01 -3.66560280e-01
2.05748767e-01 3.06431819e-02 7.24476159e-01 1.18367195e+00
1.36470509e+00 1.98487073e-01 -5.97837210e-01 5.78529298e-01
1.59996748e+00 8.20428252e-01 7.33866155e-01 4.98525977e-01
7.52860427e-01 1.15297876e-01 -3.85877863e-02 -3.58574241e-01
2.03588650e-01 2.63591230e-01 4.32419300e-01 -2.49224395e-01
-3.39587927e-01 2.07974851e-01 -1.40966438e-02 2.59490490e-01
-7.41305500e-02 5.75911924e-02 -1.38611329e+00 6.91501975e-01
-1.06033540e+00 -3.66079271e-01 -8.35947096e-01 2.06594634e+00
6.24318540e-01 3.48457277e-01 -6.82740435e-02 -3.18696350e-01
9.10362542e-01 9.43897069e-02 -7.67912924e-01 -5.68613350e-01
1.63088843e-01 1.98777482e-01 1.29675424e+00 4.85598207e-01
-9.55349803e-01 2.54317194e-01 5.45748377e+00 7.59861767e-01
-1.19335365e+00 3.87244672e-01 1.27090561e+00 -2.50417565e-04
-3.95480692e-02 -2.42372662e-01 -6.28424704e-01 5.20189524e-01
1.36055219e+00 -1.02419421e-01 5.93436882e-02 6.00754917e-01
-9.25886557e-02 -5.90913475e-01 -1.02813601e+00 6.88272417e-01
-5.13977893e-02 -1.38596630e+00 -6.60242140e-01 4.00944084e-01
7.30071485e-01 5.09517968e-01 1.18050307e-01 3.76400471e-01
5.35034120e-01 -1.47288489e+00 -3.71313728e-02 4.39654320e-01
9.39507425e-01 -4.44491625e-01 1.16547382e+00 -3.62079181e-02
-9.18236375e-01 1.78493842e-01 -1.88813642e-01 4.19434011e-01
3.62092666e-02 4.31218773e-01 -1.07128894e+00 5.81756473e-01
5.96770346e-01 5.21046937e-01 -6.79116368e-01 1.11913693e+00
3.85286659e-02 6.23520970e-01 -4.57191110e-01 3.28068554e-01
7.04118848e-01 1.99373841e-01 4.30676222e-01 1.22450244e+00
3.40690976e-03 1.85616210e-01 -2.00334728e-01 7.21325874e-01
-3.03853732e-02 -2.32382447e-01 -1.01189539e-02 6.42837510e-02
1.51085377e-01 1.64709151e+00 -1.44237173e+00 -3.21768165e-01
-3.96193080e-02 7.03977466e-01 -2.33594358e-01 -9.11009908e-02
-6.92350805e-01 -2.21314251e-01 -2.99018800e-01 3.26303303e-01
-1.70701459e-01 2.12125555e-01 -6.04983032e-01 -4.18671519e-01
-4.43641871e-01 -5.06309509e-01 7.68722117e-01 -5.47828853e-01
-1.47820556e+00 7.10599422e-01 -2.47093305e-01 -5.95344186e-01
8.90939310e-02 -5.82706392e-01 -6.20290041e-01 1.23899257e+00
-1.14681661e+00 -5.96664965e-01 -5.58187187e-01 2.79678643e-01
4.19087529e-01 2.64831245e-01 7.43005276e-01 1.55241147e-01
-2.65513927e-01 4.40791517e-01 1.79539710e-01 4.54162657e-01
6.66411340e-01 -1.55270183e+00 1.30786762e-01 2.81774610e-01
-8.84131968e-01 5.04908741e-01 1.40106911e-02 -1.05265975e+00
-1.01433063e+00 -1.29809189e+00 2.84936219e-01 -4.56071258e-01
6.76094592e-01 4.64260608e-01 -7.59179354e-01 8.65257382e-01
5.06474413e-02 3.38590920e-01 7.16184199e-01 -4.86421436e-01
4.20609891e-01 1.69076249e-01 -2.04431581e+00 3.89600307e-01
5.41573882e-01 4.92002927e-02 -2.80532986e-01 4.81152356e-01
3.71715218e-01 -1.16289902e+00 -1.69006896e+00 5.50767303e-01
3.89151573e-01 -7.86458433e-01 9.26352441e-01 -4.89284582e-02
4.48620021e-01 2.89395805e-02 -2.45266110e-02 -1.13541090e+00
-5.82813680e-01 1.26490682e-01 3.06551188e-01 6.35022044e-01
3.69929522e-01 -6.92817092e-01 9.92946863e-01 1.11617100e+00
-7.16205180e-01 -8.43466818e-01 -1.02216840e+00 -6.47728860e-01
5.94927132e-01 -1.63159788e-01 -1.07423700e-01 1.22453451e+00
-4.81371373e-01 -4.78061348e-01 5.32054543e-01 1.29776776e-01
6.08956277e-01 -5.60927451e-01 -1.53801084e-01 -9.80050445e-01
-1.26270175e-01 -7.75785208e-01 -6.01574004e-01 -2.50632942e-01
-4.75094795e-01 -1.33927691e+00 -4.84673500e-01 -2.19640112e+00
5.65067470e-01 -7.45994389e-01 -2.83155203e-01 3.97721171e-01
1.11219913e-01 3.37328821e-01 2.21251443e-01 5.32541275e-01
-2.62983423e-02 -1.02919959e-01 1.66335380e+00 -7.90018067e-02
-4.41953301e-01 4.58658524e-02 -7.24532783e-01 7.40510404e-01
9.67128873e-01 -5.00759184e-01 -2.02563301e-01 -1.25705764e-01
-7.12628007e-01 4.16179329e-01 5.82160473e-01 -1.21963155e+00
1.88162625e-01 2.11446255e-01 1.47974312e+00 -6.26717091e-01
1.18889101e-01 -5.36028981e-01 2.75456309e-01 1.29907930e+00
-3.75378191e-01 2.06462488e-01 6.08930051e-01 8.76765773e-02
3.47892433e-01 -4.49193716e-01 1.07852089e+00 -7.13874876e-01
-4.59451199e-01 3.27904284e-01 -4.59042907e-01 -4.52040620e-02
9.85836327e-01 -3.53765696e-01 -5.57063878e-01 -1.89928025e-01
-1.39495850e+00 2.63365924e-01 3.22711378e-01 -1.15808030e-03
4.53125238e-01 -1.22514141e+00 -4.88995314e-01 -2.98474669e-01
-6.17296040e-01 3.54178548e-01 5.10258317e-01 1.60921657e+00
-8.09301913e-01 5.83949149e-01 -3.10312688e-01 -9.12007451e-01
-9.47936833e-01 -2.97573339e-02 1.02623546e+00 -8.99774492e-01
-6.69996142e-01 1.00716722e+00 2.39565551e-01 -7.27410436e-01
-1.21984864e-02 -3.98766518e-01 3.38571295e-02 -2.70276099e-01
4.49608326e-01 5.27528703e-01 1.09746575e-01 -5.32203972e-01
-4.32327956e-01 3.61659795e-01 -6.81285918e-01 -8.73929113e-02
1.27998829e+00 6.24863803e-02 -2.04564020e-01 5.93706183e-02
1.08942151e+00 -2.42421567e-01 -1.02966714e+00 2.61920780e-01
-6.00145245e-03 -2.40547895e-01 4.46736157e-01 -1.36388934e+00
-1.20031774e+00 4.23565000e-01 1.56324124e+00 3.11343931e-02
8.34686995e-01 1.51382819e-01 4.92969513e-01 -2.95755565e-01
6.11577034e-02 -5.61846912e-01 -1.78528816e-01 1.38286054e-01
6.79102361e-01 -9.31902707e-01 1.14707425e-01 -1.53858021e-01
-9.62716997e-01 1.06500244e+00 7.32928395e-01 -3.54267687e-01
1.53070047e-01 3.03431004e-01 -6.81240633e-02 -3.29348654e-01
1.53415352e-02 6.12167001e-01 1.46711528e-01 6.47359848e-01
6.54755712e-01 4.39559609e-01 -4.46114063e-01 6.66155934e-01
-2.76445359e-01 -3.41586210e-02 7.40699410e-01 8.27227056e-01
-2.19331980e-01 -7.06357002e-01 -3.79149556e-01 9.88724828e-01
-5.20290494e-01 2.12844178e-01 -2.65923142e-01 1.42915344e+00
8.07333514e-02 2.66281426e-01 3.00118834e-01 1.94972754e-01
1.46999180e-01 -4.30344850e-01 5.06186843e-01 -3.83568585e-01
-9.98522103e-01 2.56937385e-01 1.29256532e-01 -4.58672732e-01
-6.91532269e-02 -8.10886860e-01 -1.57335079e+00 -1.77752465e-01
-1.32080361e-01 2.09280342e-01 8.96862388e-01 6.12487197e-01
-1.69315621e-01 9.30521190e-01 3.25921267e-01 -5.99521816e-01
-4.61290747e-01 -9.82746482e-01 -7.39686787e-01 -1.53730109e-01
4.43507880e-02 -1.94193795e-01 -4.33748960e-01 -5.72434008e-01] | [14.708224296569824, -2.5141289234161377] |
6f5de193-6ff7-47f9-b11b-d6e97166c403 | visual-social-relationship-recognition | 1812.05917 | null | http://arxiv.org/abs/1812.05917v1 | http://arxiv.org/pdf/1812.05917v1.pdf | Visual Social Relationship Recognition | Social relationships form the basis of social structure of humans. Developing
computational models to understand social relationships from visual data is
essential for building intelligent machines that can better interact with
humans in a social environment. In this work, we study the problem of visual
social relationship recognition in images. We propose a Dual-Glance model for
social relationship recognition, where the first glance fixates at the person
of interest and the second glance deploys attention mechanism to exploit
contextual cues. To enable this study, we curated a large scale People in
Social Context (PISC) dataset, which comprises of 23,311 images and 79,244
person pairs with annotated social relationships. Since visually identifying
social relationship bears certain degree of uncertainty, we further propose an
Adaptive Focal Loss to leverage the ambiguous annotations for more effective
learning. We conduct extensive experiments to quantitatively and qualitatively
demonstrate the efficacy of our proposed method, which yields state-of-the-art
performance on social relationship recognition. | ['Yongkang Wong', 'Mohan S. Kankanhalli', 'Junnan Li', 'Qi Zhao'] | 2018-12-13 | null | null | null | null | ['visual-social-relationship-recognition'] | ['computer-vision'] | [ 1.92127451e-01 1.43836319e-01 9.07269865e-03 -7.12611914e-01
1.63914993e-01 -2.48597324e-01 8.00392926e-01 3.73999715e-01
-4.41559941e-01 4.91427630e-01 5.20155907e-01 -5.47244325e-02
-1.95866346e-01 -3.72768551e-01 -6.44604087e-01 -3.25169027e-01
-4.63980883e-01 2.51172066e-01 9.76798218e-03 -7.08436891e-02
1.21769860e-01 1.49506941e-01 -1.41212106e+00 2.52776682e-01
7.61059999e-01 5.79799354e-01 -7.29031861e-02 9.12855864e-01
4.65566695e-01 1.04395008e+00 -4.01848584e-01 -9.42159534e-01
1.23651408e-01 -4.40987617e-01 -5.73172987e-01 2.38233179e-01
7.56061792e-01 -2.78453439e-01 -6.26426280e-01 9.95633364e-01
4.09485579e-01 2.24409640e-01 8.67697895e-01 -1.75474811e+00
-1.20221865e+00 7.22582221e-01 -1.02906120e+00 3.90931547e-01
8.04900467e-01 1.63132995e-01 1.26154745e+00 -6.65116727e-01
5.42441547e-01 1.81387854e+00 5.10407865e-01 3.84412140e-01
-8.63812804e-01 -7.93031752e-01 4.29952502e-01 3.43014568e-01
-1.17936742e+00 -3.31667930e-01 7.64323175e-01 -6.50513232e-01
7.45581031e-01 1.36369959e-01 8.83710623e-01 1.02906883e+00
-2.18580961e-01 7.69905031e-01 1.07541013e+00 -3.96233112e-01
-4.62144315e-01 8.63948688e-02 4.35884297e-01 9.00152385e-01
3.89064997e-01 1.28475070e-01 -7.87222445e-01 -2.35332623e-01
5.85050285e-01 3.32327187e-01 -2.96057500e-02 -5.28061867e-01
-1.26925743e+00 6.15208864e-01 1.15694797e+00 1.95989776e-02
-2.23602708e-02 3.95387232e-01 8.29953030e-02 2.80565172e-01
2.52210021e-01 2.23502517e-01 5.02856195e-01 1.27176434e-01
-2.38151327e-01 7.44049773e-02 4.02401030e-01 9.80405509e-01
5.01333058e-01 -6.66428506e-01 -2.94214606e-01 1.00941443e+00
7.32512236e-01 5.82364559e-01 -7.94255286e-02 -9.25990939e-01
6.39646769e-01 9.06632125e-01 -1.14780761e-01 -1.62902141e+00
-3.17529768e-01 -2.58296311e-01 -8.46892059e-01 -2.08374262e-01
3.33048731e-01 -6.61864132e-02 -3.19919139e-01 1.65398979e+00
3.37593198e-01 3.20571452e-01 1.96159020e-01 9.30874109e-01
1.06125116e+00 3.05273026e-01 1.68535069e-01 -6.07577618e-04
1.45970988e+00 -1.18682325e+00 -4.18241620e-01 -3.25665385e-01
4.20144051e-01 -5.45035481e-01 8.68096232e-01 -3.33736598e-01
-8.06612611e-01 -4.76785779e-01 -1.13958025e+00 -1.45737588e-01
-1.72416568e-01 -3.85202803e-02 8.62833917e-01 2.99797684e-01
-8.63858581e-01 4.38608050e-01 -3.64940256e-01 -8.98689568e-01
8.17864358e-01 1.71599060e-01 -4.99376357e-01 -5.87186068e-02
-9.86897945e-01 5.60811877e-01 3.97166051e-02 2.88008273e-01
-5.65915227e-01 -2.10101277e-01 -7.44841993e-01 -1.20393150e-01
4.10487324e-01 -7.78854430e-01 6.74517155e-01 -9.12984192e-01
-6.30877852e-01 1.41422153e+00 1.97245255e-02 -6.06227815e-01
7.24988401e-01 -4.36410069e-01 -3.32630306e-01 3.40221614e-01
1.43595070e-01 9.55783248e-01 7.61583030e-01 -1.71958137e+00
-5.72463512e-01 -4.75648552e-01 3.67945760e-01 4.06553239e-01
-4.74069417e-01 5.30286372e-01 -6.01667523e-01 -6.54288828e-01
-1.47278294e-01 -1.23279452e+00 4.52311486e-02 2.61034638e-01
-4.59978104e-01 -3.81101221e-01 5.53660274e-01 -5.34592628e-01
1.10178554e+00 -2.09925914e+00 1.79294169e-01 3.38216603e-01
8.27054679e-01 2.92746365e-01 -7.76752979e-02 3.38934869e-01
-1.14739612e-01 6.18095510e-02 4.13554907e-02 -8.63484442e-01
-2.44622603e-02 5.75342141e-02 -7.94165432e-02 4.17405099e-01
9.32535827e-02 1.21604335e+00 -1.06163824e+00 -9.34531569e-01
-9.40228477e-02 4.10499126e-01 -5.05388319e-01 3.97213727e-01
4.34104562e-01 5.01933813e-01 -4.08305615e-01 6.77913368e-01
4.17492986e-01 -6.33833945e-01 2.53844291e-01 -1.45463541e-01
4.42358464e-01 -4.36797172e-01 -6.37902319e-01 1.12538528e+00
5.07169887e-02 9.09553349e-01 -2.30590075e-01 -7.73838162e-01
9.45714116e-01 -2.64280081e-01 2.75166184e-01 -3.77451062e-01
2.81792641e-01 -3.91652942e-01 2.11840689e-01 -5.96826315e-01
3.95017564e-01 2.30353713e-01 -5.01211584e-02 5.92714906e-01
-2.02693403e-01 3.67305189e-01 8.22603032e-02 6.75590873e-01
8.65574419e-01 -1.89857408e-01 4.86878067e-01 -3.03354692e-02
5.59632242e-01 -5.31658411e-01 3.53763193e-01 9.24908876e-01
-7.89615989e-01 4.09518868e-01 7.64302254e-01 -4.60611135e-01
-7.31804907e-01 -1.03647637e+00 3.06896061e-01 1.23657501e+00
5.22209227e-01 -3.68595570e-01 -3.99920523e-01 -9.62361217e-01
4.42532122e-01 6.31337911e-02 -8.10233533e-01 -1.93701163e-01
-5.70667982e-01 -3.41105014e-01 3.07208598e-01 5.01799285e-01
7.89725244e-01 -1.18613052e+00 -2.86085606e-01 -4.85370189e-01
-5.72982244e-02 -1.47726154e+00 -7.28580773e-01 -7.22392499e-01
-1.99424312e-01 -1.48321760e+00 -5.63692868e-01 -9.89212096e-01
1.08414412e+00 7.25342929e-01 1.23740935e+00 7.01470494e-01
-2.59669930e-01 8.60508561e-01 -4.25962746e-01 -3.13024014e-01
-2.82113422e-02 -2.45245144e-01 1.49192989e-01 3.65733325e-01
4.67653036e-01 -5.94468594e-01 -7.28552282e-01 4.68638867e-01
-3.17936957e-01 1.81757122e-01 3.57871652e-01 6.71635151e-01
2.49128193e-02 -1.52290687e-01 5.44561028e-01 -8.84895444e-01
6.88608348e-01 -4.37287450e-01 -2.30199233e-01 6.02217972e-01
-2.27341354e-01 -3.88226122e-01 7.22606257e-02 -4.21830893e-01
-8.77015829e-01 -7.01372921e-02 7.43131578e-01 -2.03585014e-01
2.15445608e-01 1.56143352e-01 8.53593871e-02 -1.03700332e-01
4.59552020e-01 -3.89397502e-01 6.20115101e-02 -8.99840146e-03
3.02142084e-01 9.42715645e-01 6.69800282e-01 -5.45241296e-01
8.99211526e-01 5.35263479e-01 -8.70519653e-02 -7.09576964e-01
-1.16822636e+00 -6.46496713e-01 -7.52890706e-01 -8.44748855e-01
1.03038204e+00 -1.14422500e+00 -1.22360432e+00 4.86233085e-01
-8.95593107e-01 -2.26220310e-01 3.23884547e-01 3.12480420e-01
-3.00327122e-01 4.90700901e-01 -3.38286370e-01 -9.17601109e-01
-1.30254894e-01 -6.03450358e-01 8.37720573e-01 4.85226810e-01
-2.33883411e-01 -8.97823036e-01 -1.14439406e-01 1.14188778e+00
-1.37437731e-01 4.02731150e-01 5.31272590e-01 -5.71191370e-01
-7.45355070e-01 3.50921191e-02 -9.09024954e-01 1.40454128e-01
1.77856371e-01 2.69638691e-02 -7.94934869e-01 -3.79163265e-01
-7.93913364e-01 -5.37804246e-01 1.00673091e+00 -2.72503532e-02
9.52199221e-01 -4.53752419e-03 -5.65449536e-01 3.63092482e-01
8.10248911e-01 -4.89940792e-02 5.14804721e-01 -9.16969404e-02
1.23259377e+00 1.11222017e+00 8.12886953e-01 3.96467388e-01
9.51200545e-01 4.61792946e-01 2.68768132e-01 -9.96385515e-02
-1.63208559e-01 -4.75635141e-01 1.26484483e-01 5.17360866e-01
-3.43838394e-01 -3.49018633e-01 -1.04814816e+00 5.15631497e-01
-2.33812475e+00 -1.05140650e+00 8.87634084e-02 1.97075188e+00
5.69119871e-01 1.14770040e-01 3.35604340e-01 -1.90552264e-01
1.24117792e+00 3.70998472e-01 -4.91362154e-01 1.59228861e-01
-1.08209677e-01 -8.21591079e-01 1.03033207e-01 4.49819922e-01
-1.25869882e+00 1.02349079e+00 6.24959373e+00 2.80024230e-01
-4.28234041e-01 -3.45207483e-01 7.62000620e-01 -1.23196818e-01
9.66305193e-03 -1.17793247e-01 -9.00060833e-01 4.05722499e-01
2.77241826e-01 -3.55331823e-02 5.22757828e-01 4.43493158e-01
5.22534065e-02 -1.48185074e-01 -1.33682334e+00 1.50425756e+00
5.98497510e-01 -9.09114361e-01 -7.59229213e-02 1.75284028e-01
8.11395764e-01 -5.00418067e-01 1.93782389e-01 1.22115731e-01
5.63116491e-01 -1.12396860e+00 4.39036250e-01 8.73088121e-01
3.84004235e-01 -6.01514518e-01 6.02045059e-01 3.91886979e-02
-1.26704621e+00 -3.58338207e-01 -1.67998314e-01 -2.04832211e-01
1.96389720e-01 1.54619932e-01 -8.51137221e-01 1.63728818e-01
9.30570602e-01 1.41241324e+00 -1.27018809e+00 8.36119354e-01
-1.45863846e-01 1.50057703e-01 -1.27438903e-01 -3.11982453e-01
-1.61160648e-01 -2.05491096e-01 5.07538140e-01 9.36261594e-01
-1.17634237e-01 3.05831909e-01 2.00440839e-01 4.06268328e-01
-2.88476944e-01 -3.13232057e-02 -8.49154532e-01 -3.29648226e-01
5.56999981e-01 1.09138131e+00 -7.02201426e-01 -2.77793080e-01
-5.46819985e-01 8.87246668e-01 8.79220128e-01 3.86798888e-01
-9.79887486e-01 2.05955952e-02 3.97130609e-01 1.18531361e-01
-1.03760371e-02 -2.74296761e-01 2.13693902e-01 -1.17061079e+00
1.97846308e-01 -7.68293619e-01 6.36636376e-01 -9.50368643e-01
-1.77205992e+00 2.80711681e-01 2.01493710e-01 -9.84116852e-01
-2.54813824e-02 -3.46382469e-01 -5.28070033e-01 2.83234715e-01
-1.40125561e+00 -1.68863964e+00 -7.64310837e-01 5.67344069e-01
1.04138628e-01 -5.97389519e-01 7.18922094e-02 1.91005781e-01
-5.69165111e-01 8.45787942e-01 -4.93934900e-01 4.39810723e-01
1.08371353e+00 -1.12644351e+00 2.33815923e-01 7.46502101e-01
1.18632548e-01 9.06757951e-01 5.96958876e-01 -8.33711445e-01
-9.48894382e-01 -9.61989343e-01 1.02525651e+00 -5.21122098e-01
9.42930102e-01 -3.35275441e-01 -5.73522389e-01 8.30221593e-01
2.01531723e-01 1.79419458e-01 9.81216848e-01 4.11628813e-01
-5.92850089e-01 -2.01056778e-01 -1.01848197e+00 9.00402486e-01
1.88049471e+00 -8.26376379e-01 -6.42595291e-01 2.39130914e-01
7.19109178e-01 3.65821198e-02 -7.30470657e-01 3.22876453e-01
7.33850718e-01 -1.16538703e+00 1.41036546e+00 -5.98849475e-01
6.32239878e-01 -2.54234582e-01 -2.00953066e-01 -9.68550444e-01
-1.93677753e-01 -5.73379278e-01 -1.68947190e-01 1.60737133e+00
1.34290531e-01 -6.49616599e-01 6.43854320e-01 6.95264101e-01
4.33543712e-01 -5.37832856e-01 -3.23900282e-01 -4.33836281e-01
-4.00790900e-01 1.05797842e-01 5.98053753e-01 1.01140058e+00
-3.77366915e-02 6.17324591e-01 -7.69159496e-01 1.76029980e-01
9.04144824e-01 1.23401128e-01 1.05014086e+00 -1.14160264e+00
-4.58875030e-01 -1.62464529e-01 -7.70377576e-01 -9.49457824e-01
4.31328088e-01 -5.90251446e-01 -2.69362360e-01 -1.38084388e+00
9.36665177e-01 -4.59007531e-01 -3.20159554e-01 3.02318156e-01
-6.81640863e-01 5.01639903e-01 5.21492422e-01 2.37421617e-01
-1.34489655e+00 5.41419268e-01 1.41018009e+00 -3.97174686e-01
-8.20388794e-02 -1.08916752e-01 -1.12390244e+00 8.82125676e-01
5.31723559e-01 -6.72305003e-02 -5.74814558e-01 -3.45200092e-01
5.23124933e-01 -1.15053207e-01 9.61265624e-01 -8.80748987e-01
4.39215541e-01 -1.09738871e-01 3.33125681e-01 -5.90095460e-01
4.17460471e-01 -7.82830596e-01 -9.69778970e-02 3.00502449e-01
-7.97171652e-01 6.30718619e-02 -6.01824522e-01 9.79899347e-01
-4.72786874e-02 1.30307391e-01 6.95436597e-01 2.04714596e-01
-5.60839891e-01 2.85235584e-01 2.06574172e-01 3.79824825e-02
1.33925045e+00 -8.43372047e-02 -6.93412840e-01 -8.47476602e-01
-7.82428801e-01 8.64999890e-01 4.93566394e-01 6.35031283e-01
6.79433346e-01 -1.66556609e+00 -8.23229551e-01 -1.60607278e-01
6.73350275e-01 -4.47029859e-01 3.15374941e-01 3.88991684e-01
-3.23066235e-01 2.95790425e-03 -1.51924372e-01 -6.98787928e-01
-1.98827112e+00 6.56735659e-01 1.83711275e-01 6.04046546e-02
-4.12163407e-01 1.04992664e+00 3.66007209e-01 -2.88931549e-01
4.19292718e-01 6.24984764e-02 -7.58487761e-01 1.76612735e-01
5.62060714e-01 2.15206653e-01 -8.60708773e-01 -1.15434766e+00
-4.81654674e-01 8.79191101e-01 -1.67258009e-01 2.23336011e-01
1.27499092e+00 -4.66948599e-01 -1.50653675e-01 2.88536340e-01
1.21212733e+00 -1.75749347e-01 -1.38679802e+00 -6.10401034e-01
-1.87692717e-01 -9.58921850e-01 -4.59447205e-01 -5.47563136e-01
-8.83551300e-01 6.33501351e-01 4.70651895e-01 1.64820641e-01
8.04675221e-01 3.75382423e-01 5.73428631e-01 4.78003114e-01
1.88567266e-01 -8.69174480e-01 7.89761961e-01 2.29785085e-01
1.10421538e+00 -1.90658951e+00 4.99288380e-01 -8.13688934e-01
-1.05588996e+00 5.35602450e-01 7.55128384e-01 -2.61015892e-01
7.55532086e-01 -3.90859455e-01 -1.29818529e-01 -4.59521204e-01
-6.84002995e-01 -3.66263419e-01 5.28697014e-01 8.42876852e-01
1.56821281e-01 1.94279641e-01 -3.70718054e-02 3.55124712e-01
-2.24530071e-01 -4.35755521e-01 2.05983490e-01 7.23225653e-01
-2.63797373e-01 -8.53333533e-01 -2.77525425e-01 3.20425183e-01
-1.27266407e-01 4.84315827e-02 -8.70324790e-01 5.57646334e-01
1.28375575e-01 1.19611323e+00 2.23479033e-01 -3.94720525e-01
1.39894918e-01 -4.59641308e-01 5.38979948e-01 -3.66366595e-01
-5.12185276e-01 -3.62788707e-01 4.30039644e-01 -3.96461129e-01
-9.53247726e-01 -8.98276865e-01 -1.01449168e+00 -5.16308963e-01
7.09421560e-02 -1.61388606e-01 -3.42991278e-02 8.55665922e-01
2.59372741e-01 2.41500497e-01 7.63864338e-01 -6.43948257e-01
3.94661762e-02 -7.52537131e-01 -3.75483781e-01 8.91524494e-01
3.42351764e-01 -9.32483733e-01 -3.84334862e-01 2.80836284e-01] | [10.191871643066406, 1.6297980546951294] |
4b00a4a5-430b-4bd0-bdf4-9bcec44e99f0 | process-parameter-selection-for-production-of | null | null | https://scholar.google.com/citations?view_op=view_citation&hl=en&user=XDqUWuIAAAAJ&citation_for_view=XDqUWuIAAAAJ:9ZlFYXVOiuMC | https://www.mdpi.com/1996-1944/16/3/1050/pdf?version=1675738719 | Process Parameter Selection for Production of Stainless Steel 316L Using Efficient Multi-Objective Bayesian Optimization Algorithm | Additive manufacturing is a modern technique to produce parts with a complex geometry. However, the choice of the printing parameters is a time-consuming and costly process. In this study, the parameter optimization for the laser powder bed fusion process was investigated. Using state-of-the art multi-objective Bayesian optimization, the set of the most-promising process parameters (laser power, scanning speed, hatch distance, etc.), which would yield parts with the desired hardness and porosity, was established. The Gaussian process surrogate model was built on 57 empirical data points, and through efficient sampling in the design space, we were able to obtain three points in the Pareto front in just over six iterations. The produced parts had a hardness ranging from 224–235 HV and a porosity in the range of 0.2–0.37%. The trained model recommended using the following parameters for high-quality parts: 58 W, 257 mm/s, 45 µm, with a scan rotation angle of 131 degrees. The proposed methodology greatly reduces the number of experiments, thus saving time and resources. The candidate process parameters prescribed by the model were experimentally validated and tested. | ['Evlashin Stanislav A', 'Kuzminova Yulia O', 'Firsov Denis G', 'Dubinin Oleg N', 'Simonov Alexey P', 'Ryabov Alexander', 'Zhilyaev Petr', 'Chepiga Timur'] | 2023-01-25 | null | null | null | materials-2023-1 | ['bayesian-optimization'] | ['methodology'] | [-6.04237355e-02 -2.24302813e-01 1.48470119e-01 -1.53064921e-01
-5.44348359e-01 -1.00578405e-01 1.87877074e-01 2.24278748e-01
-2.22579196e-01 8.98368418e-01 -2.07394004e-01 1.64250106e-01
-1.07904232e+00 -8.20042074e-01 -4.75772679e-01 -1.16040134e+00
2.11351544e-01 9.60774779e-01 -3.54360975e-02 1.73323467e-01
7.14653254e-01 7.90779114e-01 -1.67672431e+00 -3.02719563e-01
1.00613177e+00 1.13084972e+00 7.33118653e-01 2.32877836e-01
1.01216987e-01 1.98782198e-02 -3.17695081e-01 -3.40017945e-01
1.33337289e-01 -3.20813566e-01 -3.43223631e-01 1.10865593e-01
-5.78896403e-01 -6.30213618e-02 2.85638601e-01 9.74465728e-01
5.72313249e-01 4.39545333e-01 1.09302247e+00 -6.64066732e-01
-5.92366040e-01 5.02452910e-01 -4.57000941e-01 -3.24244082e-01
-7.89115280e-02 9.79440659e-02 5.51149189e-01 -9.44224298e-01
3.89418691e-01 1.04136598e+00 3.34215234e-03 2.08853930e-01
-1.03361773e+00 -5.40685475e-01 -5.98121762e-01 3.01609449e-02
-1.71102381e+00 -1.63795143e-01 7.19079316e-01 -5.81023991e-01
3.96493584e-01 2.02124864e-01 8.82724643e-01 6.16777837e-01
1.07183373e+00 -7.08887801e-02 1.37717104e+00 -4.32219595e-01
6.10949695e-01 -2.09175628e-02 -3.70433986e-01 5.45386374e-01
6.06213093e-01 3.42449486e-01 -1.84751183e-01 -2.44797431e-02
1.01780093e+00 -1.12224162e-01 -4.24880646e-02 -3.28235239e-01
-7.52380610e-01 9.44719672e-01 2.53313836e-02 4.05906796e-01
-7.83183217e-01 -6.75351024e-02 -2.31653348e-01 -1.98905557e-01
4.01634008e-01 9.48741376e-01 -5.15083432e-01 -3.35113287e-01
-8.35850596e-01 2.37438262e-01 8.21448505e-01 9.41492498e-01
3.75906020e-01 -2.69503728e-03 -1.97867528e-01 7.69636869e-01
8.32843602e-01 6.34361625e-01 3.94313298e-02 -9.57594275e-01
2.62984745e-02 3.69628191e-01 3.58220607e-01 -5.34937739e-01
-1.34162590e-01 -3.71177405e-01 -6.46606207e-01 3.44448626e-01
3.30622375e-01 -4.11792964e-01 -9.33630466e-01 8.59450400e-01
5.28751671e-01 -4.91318941e-01 -9.75529999e-02 9.81521845e-01
2.57114619e-01 7.97956645e-01 -3.59504074e-02 -7.53239393e-01
1.43911219e+00 -5.46503425e-01 -8.95441234e-01 2.46380612e-01
2.61567794e-02 -1.39536142e+00 7.76001096e-01 6.80343390e-01
-1.25614536e+00 -4.76563752e-01 -1.13733757e+00 6.96079493e-01
1.11930236e-01 5.70203066e-01 6.12937272e-01 5.22692680e-01
-4.24661517e-01 1.02912366e+00 -6.49828732e-01 1.16759673e-01
2.12279752e-01 4.25273389e-01 9.86026451e-02 -1.06240883e-01
-8.16117883e-01 1.13976049e+00 4.30901319e-01 5.95181763e-01
-7.57281721e-01 -6.08751953e-01 -3.51354301e-01 -3.73415090e-03
3.96884471e-01 -8.57744336e-01 1.01868665e+00 -2.48506084e-01
-2.38726258e+00 8.14172626e-02 1.63959011e-01 8.37913081e-02
4.51419175e-01 -6.59197927e-01 -4.40005213e-01 2.41597801e-01
-2.67302513e-01 2.92895287e-02 7.95328856e-01 -1.38995862e+00
-3.96607220e-01 -2.83103645e-01 -4.42889571e-01 5.02694733e-02
3.52343321e-01 2.81266034e-01 -1.76165283e-01 -2.73274183e-01
3.29484582e-01 -8.96751344e-01 -4.43548977e-01 -4.72637296e-01
-4.67096597e-01 -2.29520962e-01 4.20387834e-01 -6.39876783e-01
8.23280215e-01 -1.81771505e+00 2.51800209e-01 7.60524035e-01
-2.86080897e-01 -2.66586810e-01 6.16654217e-01 5.29943526e-01
3.62762809e-01 -8.46808925e-02 -2.42901340e-01 1.35374933e-01
-4.98054698e-02 3.83953117e-02 3.83863240e-01 6.54559851e-01
-1.20833926e-01 4.07743037e-01 -6.19400680e-01 -5.11959553e-01
4.09092069e-01 4.63541150e-01 -3.30605477e-01 3.83223891e-01
-2.51144320e-01 3.01492482e-01 -6.77788317e-01 9.05751824e-01
5.76756299e-01 2.04886869e-01 -2.15317473e-01 -4.35501069e-01
-3.98568481e-01 -5.54877400e-01 -1.59979248e+00 1.21603167e+00
-5.07715523e-01 -7.86059648e-02 3.85863870e-01 -2.93487221e-01
1.66987157e+00 3.10682356e-01 8.44661832e-01 -2.63028324e-01
6.83773696e-01 4.45666075e-01 2.50467092e-01 -8.09867859e-01
4.60340559e-01 -5.62175333e-01 8.85890126e-02 5.13849519e-02
4.06105258e-02 -8.20278704e-01 2.05617934e-01 -6.67661190e-01
4.03507948e-01 2.38027200e-01 -3.76266949e-02 -5.37441611e-01
3.75445157e-01 -2.13272884e-01 3.71428400e-01 3.06280494e-01
4.32508558e-01 4.13690329e-01 1.22017510e-01 1.45228326e-01
-1.38267279e+00 -8.27991962e-01 -3.60655606e-01 1.77193016e-01
4.16287124e-01 1.58423260e-01 -5.56753993e-01 4.20672238e-01
-1.75876558e-01 9.11805570e-01 -1.34340957e-01 -2.41557255e-01
-4.21977878e-01 -6.19639933e-01 -2.04394504e-01 1.37938127e-01
3.61371636e-01 -8.59181762e-01 -5.56119442e-01 5.58418036e-01
3.69625360e-01 -7.22016275e-01 1.37219857e-02 2.70349652e-01
-1.20135367e+00 -9.65842426e-01 -6.34912550e-01 -5.57775319e-01
7.49623120e-01 -4.34034646e-01 8.14743578e-01 -1.58253968e-01
-3.95167112e-01 -4.11152141e-03 -3.79218042e-01 -4.41159368e-01
-5.09046674e-01 -2.66547471e-01 9.31354389e-02 -6.15430214e-02
-1.45153672e-01 -2.72346526e-01 -5.93531013e-01 6.43795371e-01
-5.36086321e-01 3.10679199e-03 1.05569565e+00 7.78730750e-01
1.05319893e+00 7.92676449e-01 3.12097609e-01 -4.46366966e-01
7.36988962e-01 -1.69950753e-01 -8.96928608e-01 2.95958936e-01
-7.56562114e-01 1.70135200e-01 5.32276154e-01 -5.54546297e-01
-1.26644289e+00 -8.49040002e-02 7.38874227e-02 -3.46914202e-01
-2.47666463e-01 5.69529176e-01 -3.86632085e-01 -2.43062563e-02
1.25217795e-01 -1.06141940e-01 2.61203110e-01 -6.08865261e-01
1.69104129e-01 3.01006913e-01 1.72845244e-01 -1.13315129e+00
8.16164196e-01 -1.47306800e-01 5.18017590e-01 -9.29253817e-01
-3.11814487e-01 -2.07502633e-01 -4.91851926e-01 -5.95323622e-01
9.57932591e-01 -3.47742796e-01 -9.21652019e-01 2.99445122e-01
-7.49138951e-01 -4.29983139e-02 -4.10535246e-01 1.15444398e+00
-6.92576587e-01 1.43653288e-01 -4.11672711e-01 -1.18501830e+00
-6.01859152e-01 -1.49138105e+00 7.07620144e-01 3.53091449e-01
-3.15433055e-01 -4.34714139e-01 -3.43696833e-01 3.92712623e-01
4.27261591e-01 3.42232347e-01 1.11235714e+00 -2.10651204e-01
-6.25271738e-01 -2.22960278e-01 2.88431585e-01 2.61538267e-01
2.78823882e-01 6.18454099e-01 -1.99411005e-01 -2.03230213e-02
4.70595062e-01 9.87767652e-02 1.24124020e-01 9.18949664e-01
1.04304075e+00 -1.79542024e-02 -1.97026283e-01 4.41179723e-01
1.78027105e+00 9.35711443e-01 6.50765598e-01 3.04278314e-01
3.48314524e-01 4.61768180e-01 1.13387334e+00 7.25052118e-01
-5.26248813e-01 6.02540493e-01 5.32102764e-01 2.23062977e-01
1.92961827e-01 9.10343155e-02 2.33777910e-02 6.12962246e-01
-7.37970173e-01 -1.85623050e-01 -5.39302766e-01 1.48805514e-01
-1.37806618e+00 -7.35864043e-01 -2.01209888e-01 2.34365630e+00
6.98070109e-01 2.39973277e-01 -5.83428890e-02 2.22891182e-01
8.64283323e-01 -4.49123770e-01 -3.62786688e-02 -5.52131534e-01
2.23052919e-01 6.64640784e-01 7.89648890e-01 4.49819773e-01
-6.63846731e-01 3.47787201e-01 5.48400259e+00 9.00295973e-01
-8.29073548e-01 -5.19194007e-01 1.63577721e-01 -2.37233922e-01
-2.87113428e-01 2.05523625e-01 -8.36189508e-01 7.37985373e-01
1.00901425e+00 -1.86365023e-01 4.67533976e-01 6.74778879e-01
5.10760784e-01 -5.23511767e-01 -6.72934294e-01 7.84737229e-01
-3.95264715e-01 -1.13726676e+00 -2.58537173e-01 3.25622529e-01
7.59117663e-01 -6.38464391e-01 -2.24321723e-01 -2.24870384e-01
3.43206525e-01 -1.03921402e+00 9.49119449e-01 9.85078752e-01
3.99205446e-01 -1.16478491e+00 1.20287406e+00 1.18436895e-01
-6.99312866e-01 -1.14910275e-01 -3.76387566e-01 3.68082464e-01
6.25838339e-01 1.09052885e+00 -8.45018268e-01 9.22731221e-01
5.73720276e-01 -9.75251049e-02 9.98710245e-02 1.35495543e+00
-2.45476067e-01 4.33813423e-01 -8.75758886e-01 -5.90447545e-01
-2.29372140e-02 -1.06025267e+00 5.54815769e-01 4.41149056e-01
1.15152264e+00 2.04991996e-01 -6.52906373e-02 9.61422145e-01
3.86887908e-01 2.85255939e-01 -2.16778740e-01 -8.06816220e-02
7.85603881e-01 8.75891924e-01 -8.75163615e-01 3.13209951e-01
3.63118082e-01 3.24622720e-01 -4.19596016e-01 1.25027508e-01
-1.03742397e+00 -1.71094730e-01 2.98294842e-01 1.57775179e-01
5.24476767e-01 -5.03063917e-01 -5.58172703e-01 -5.85810728e-02
-8.11342672e-02 -4.52034682e-01 -1.60763308e-01 -7.23253489e-01
-1.10920417e+00 1.71074927e-01 4.63176012e-01 -1.13274670e+00
2.86958776e-02 -7.49920428e-01 -5.29921591e-01 9.17447209e-01
-7.98070967e-01 -7.23630071e-01 -2.54093613e-02 5.10918982e-02
5.09874463e-01 -2.57278174e-01 6.69132888e-01 1.16235949e-01
-6.58380151e-01 1.65455916e-03 5.26413083e-01 -6.69954062e-01
3.13364953e-01 -8.77765238e-01 -5.47988474e-01 5.77326000e-01
-4.75407660e-01 5.16197085e-01 1.23285806e+00 -8.29801917e-01
-1.72998691e+00 -5.40629506e-01 2.79294848e-01 3.76258641e-01
5.55089355e-01 1.81217045e-02 -5.72516739e-01 -1.01744525e-01
-9.19022486e-02 -6.07950568e-01 5.37945807e-01 -2.64438540e-02
9.05452073e-01 -9.80055109e-02 -1.34011233e+00 6.08691096e-01
4.30646837e-01 2.22019956e-01 -3.14733624e-01 1.53785795e-01
2.12247744e-01 -5.85317373e-01 -1.69648910e+00 6.57352209e-01
6.37219906e-01 -3.86992693e-01 9.88926053e-01 -5.63574508e-02
5.42959392e-01 -2.93200731e-01 -1.33377373e-01 -1.28238082e+00
-5.73641598e-01 -5.88771760e-01 -7.55276829e-02 1.43058729e+00
5.78351438e-01 -5.12825549e-01 5.86857736e-01 6.82600200e-01
-5.09074986e-01 -1.44787681e+00 -9.55971301e-01 -7.71580637e-01
-2.09892407e-01 1.00948021e-01 6.12839401e-01 4.86468291e-03
-5.31258345e-01 1.24665521e-01 -1.32641941e-01 3.30617696e-01
7.52320528e-01 2.25078151e-01 4.34284747e-01 -1.44911563e+00
-2.57146508e-01 -2.46897310e-01 -4.06966638e-03 -5.21753013e-01
-3.23300779e-01 -2.75970966e-01 2.97702730e-01 -1.84331203e+00
-2.99837112e-01 -6.24420106e-01 5.60758375e-02 -1.57917872e-01
1.26420408e-01 -6.18811727e-01 -5.55447862e-02 2.96668261e-01
3.57250988e-01 8.59204054e-01 1.81094599e+00 -1.29890695e-01
-3.79013598e-01 4.98154342e-01 -3.77606302e-01 6.01948857e-01
9.68065500e-01 -4.86637622e-01 -4.80832189e-01 1.68943070e-02
6.48351461e-02 3.59951884e-01 -1.58809438e-01 -9.34282899e-01
3.22061032e-02 -6.69431329e-01 5.51447988e-01 -8.32302213e-01
7.61020780e-01 -1.39322710e+00 9.91080999e-01 4.68572646e-01
1.70654327e-01 -1.76858008e-01 -6.92005455e-02 4.41167504e-01
-8.98951665e-02 -8.51957917e-01 7.15838313e-01 2.74381507e-02
-3.67938608e-01 4.74338569e-02 -1.92019597e-01 -6.85144067e-01
1.30646002e+00 -4.93581742e-01 9.96323749e-02 2.48780057e-01
-5.62445045e-01 -4.68845777e-02 3.60275805e-01 3.30868699e-02
6.66140974e-01 -1.22646964e+00 -6.91940844e-01 5.85224293e-03
-4.58838761e-01 2.17367172e-01 4.85866219e-01 7.31929958e-01
-8.80188763e-01 7.45513514e-02 -1.93997741e-01 -5.67203760e-01
-1.03266835e+00 3.26348066e-01 1.53420091e-01 -9.29409936e-02
-4.67520535e-01 7.10998774e-01 -6.99918032e-01 2.48801231e-01
-4.16298687e-01 -4.42051142e-01 -2.62983978e-01 1.25534549e-01
-1.76921651e-01 8.85723352e-01 3.11231613e-01 -2.62877494e-01
-6.46140799e-02 8.66628587e-01 4.79914427e-01 -2.10954815e-01
1.54414237e+00 2.20394090e-01 -6.40840232e-02 1.97103888e-01
7.64816403e-01 1.41393751e-01 -1.23497987e+00 4.78703260e-01
-2.08138555e-01 -6.04698002e-01 2.78791070e-01 -6.77877188e-01
-8.08926821e-01 6.00534119e-02 5.06740987e-01 3.43353450e-02
9.07659531e-01 -5.05851470e-02 5.32221675e-01 3.97330448e-02
5.34087002e-01 -1.51669943e+00 -2.79486686e-01 3.36575538e-01
1.17683291e+00 -6.35856032e-01 6.16091907e-01 -6.75846040e-01
-3.60914409e-01 1.40086579e+00 5.08951068e-01 -1.07723139e-01
6.85691178e-01 3.10834110e-01 -4.17689294e-01 -6.02129340e-01
-2.74098933e-01 1.78771406e-01 2.62462080e-01 1.77820936e-01
2.84896523e-01 3.22831780e-01 -7.73502946e-01 4.72156197e-01
-4.66998994e-01 4.58741337e-02 1.54521510e-01 1.07803416e+00
-7.00230539e-01 -9.24633384e-01 -8.84230435e-01 5.74159741e-01
-4.27810043e-01 4.11963969e-01 3.26248586e-01 9.51640964e-01
1.48739547e-01 1.19761610e+00 -6.19512387e-02 -1.45533875e-01
6.10305369e-01 -2.34157555e-02 8.85696828e-01 -4.17409003e-01
-2.89314389e-01 4.34327751e-01 2.88920671e-01 -1.55430883e-01
-3.77098203e-01 -6.38906538e-01 -1.26510382e+00 -1.97626367e-01
-8.60199451e-01 4.26256627e-01 1.22565961e+00 9.54622328e-01
-1.53436229e-01 7.24357069e-01 8.14877450e-01 -8.36433530e-01
-6.99196935e-01 -1.10881305e+00 -9.46193039e-01 -5.00360392e-02
-6.35364115e-01 -1.23489869e+00 -3.87570679e-01 -2.32462853e-01] | [6.154257297515869, 3.3049066066741943] |
31fff4dd-ed90-4ab4-8b5d-4b8b716c2d2b | multi-resolution-fully-convolutional-neural | 1710.11473 | null | http://arxiv.org/abs/1710.11473v1 | http://arxiv.org/pdf/1710.11473v1.pdf | Multi-Resolution Fully Convolutional Neural Networks for Monaural Audio Source Separation | In deep neural networks with convolutional layers, each layer typically has
fixed-size/single-resolution receptive field (RF). Convolutional layers with a
large RF capture global information from the input features, while layers with
small RF size capture local details with high resolution from the input
features. In this work, we introduce novel deep multi-resolution fully
convolutional neural networks (MR-FCNN), where each layer has different RF
sizes to extract multi-resolution features that capture the global and local
details information from its input features. The proposed MR-FCNN is applied to
separate a target audio source from a mixture of many audio sources.
Experimental results show that using MR-FCNN improves the performance compared
to feedforward deep neural networks (DNNs) and single resolution deep fully
convolutional neural networks (FCNNs) on the audio source separation problem. | ['Emad M. Grais', 'Mark D. Plumbley', 'Hagen Wierstorf', 'Dominic Ward'] | 2017-10-28 | null | null | null | null | ['audio-source-separation'] | ['audio'] | [ 1.04313724e-01 -3.87046129e-01 2.10947514e-01 -2.70404220e-01
-8.53038371e-01 -3.37831259e-01 1.97426111e-01 -4.37567949e-01
-1.65912822e-01 4.52599376e-01 5.65748870e-01 3.40995014e-01
-3.27817053e-01 -8.25516641e-01 -5.83340764e-01 -6.25403821e-01
-3.70447606e-01 -2.58738577e-01 2.96450734e-01 -2.73893643e-02
-8.97841081e-02 6.89117908e-01 -1.77627742e+00 9.21187818e-01
3.63461196e-01 1.48089540e+00 4.05443609e-01 1.05557764e+00
-1.32392809e-01 1.12569952e+00 -8.94863188e-01 4.13494736e-01
8.61798674e-02 -7.22225234e-02 -7.08288491e-01 -4.54409778e-01
6.62443101e-01 -2.65732229e-01 -4.91150260e-01 9.73495305e-01
8.52615237e-01 3.00053447e-01 5.59057355e-01 -8.94742370e-01
-7.26407111e-01 9.17504549e-01 -5.02656460e-01 7.71945536e-01
-4.25618514e-02 -4.62234497e-01 8.41344476e-01 -1.13395619e+00
-1.00956030e-01 1.56414402e+00 8.75092030e-01 4.78569895e-01
-8.67426693e-01 -1.06905603e+00 2.68347651e-01 -8.40013921e-02
-1.60824764e+00 -5.08328438e-01 9.20575023e-01 -3.17574233e-01
1.01319683e+00 6.74556866e-02 2.07331538e-01 9.83811677e-01
3.32724974e-02 5.45814037e-01 8.07329714e-01 -1.57349870e-01
1.12801701e-01 -1.93832427e-01 1.99147686e-01 3.28892082e-01
2.09287509e-01 6.98777959e-02 -7.25142896e-01 -1.21601924e-01
1.49153328e+00 1.57597333e-01 -5.99997520e-01 4.36737299e-01
-9.05182779e-01 6.73273921e-01 9.13308561e-01 8.38641524e-01
-3.48942846e-01 3.07926953e-01 2.21124351e-01 3.54498923e-01
3.51192623e-01 2.60801166e-01 -4.44366008e-01 1.51835695e-01
-1.00886643e+00 1.80746187e-02 3.64648372e-01 7.98071802e-01
7.64286280e-01 6.46299124e-01 -9.11220089e-02 1.28692055e+00
9.38044861e-02 3.16356987e-01 8.43187153e-01 -7.76571035e-01
3.91326129e-01 5.49523830e-01 -3.05462480e-01 -9.50584531e-01
-4.22962964e-01 -7.40598202e-01 -1.45349836e+00 3.79815668e-01
5.96051440e-02 -3.75379056e-01 -1.04613781e+00 1.64166617e+00
-1.30335465e-01 3.77409995e-01 3.51995409e-01 1.19953692e+00
1.55441809e+00 1.00033152e+00 -2.18327194e-01 2.09280327e-01
1.36762333e+00 -9.09810662e-01 -6.30132854e-01 -4.35155272e-01
-2.31577978e-01 -8.15724254e-01 6.12067163e-01 4.52072144e-01
-1.06148326e+00 -1.47339153e+00 -1.09682584e+00 -1.43281758e-01
-4.93885279e-01 6.49188161e-01 2.82981157e-01 1.66779891e-01
-1.16902661e+00 6.32326901e-01 -5.59913158e-01 2.30045855e-01
5.31180024e-01 5.84213972e-01 -3.74029607e-01 1.16660036e-01
-1.38972282e+00 9.07871574e-02 2.81540185e-01 3.80961925e-01
-1.14896798e+00 -7.42201567e-01 -6.96621776e-01 4.79465842e-01
-1.28151048e-02 -3.45565110e-01 1.15764201e+00 -1.35163093e+00
-1.46608007e+00 1.08043849e-01 -1.39242392e-02 -3.29534620e-01
-2.03330919e-01 -5.99393845e-01 -7.41407394e-01 4.07380104e-01
-1.35171622e-01 7.54133940e-01 1.31379426e+00 -1.04997122e+00
-8.17643464e-01 -2.89534956e-01 4.39273054e-03 1.17312558e-01
-3.08777988e-01 3.51470888e-01 -5.53035922e-02 -9.24000740e-01
1.06894456e-01 -4.25732076e-01 -1.09145246e-01 -2.24355265e-01
-2.52691954e-01 -7.70887285e-02 1.05793667e+00 -3.92609537e-01
1.07781196e+00 -2.50202155e+00 1.50758624e-01 -2.47965872e-01
4.50789869e-01 5.76972365e-01 -5.53066015e-01 -1.41349941e-01
-2.82559782e-01 -2.14762203e-02 -5.15574291e-02 7.21641630e-02
-3.71277869e-01 -2.59291977e-02 -5.28742194e-01 -4.68264893e-03
4.83890474e-01 7.56804883e-01 -5.19458771e-01 -1.90852940e-01
-1.92456618e-02 1.13674986e+00 -2.86354482e-01 4.32869226e-01
3.82170647e-01 1.49224699e-01 -4.32643354e-01 4.59330827e-01
9.60290551e-01 -1.61895812e-01 -1.68257877e-01 -2.85411566e-01
-1.45926699e-01 2.15219676e-01 -1.58233249e+00 1.55900955e+00
-6.52406335e-01 8.97540808e-01 6.26363039e-01 -6.54346526e-01
1.30147576e+00 6.16127610e-01 1.74667671e-01 -4.45420653e-01
1.38672620e-01 1.07573427e-01 -6.71219528e-02 -6.99843466e-02
4.57413256e-01 -1.74375057e-01 -7.57866129e-02 2.50986904e-01
7.44275510e-01 5.65196931e-01 -4.16102201e-01 -1.02948613e-01
1.02100146e+00 -3.48614156e-01 4.66355607e-02 -1.25539884e-01
6.01362467e-01 -7.33065903e-01 7.69920051e-01 6.23387218e-01
-7.39597902e-02 1.17607820e+00 9.47717652e-02 -6.77604556e-01
-6.03556871e-01 -1.05684507e+00 -1.59173444e-01 1.31556273e+00
-2.30221778e-01 -2.98430622e-01 -6.13432467e-01 -2.62012541e-01
-9.20297205e-02 -2.29491353e-01 -5.38808227e-01 -1.38112813e-01
-7.67385125e-01 -4.43956077e-01 1.05139720e+00 1.06526780e+00
7.86515534e-01 -1.28657401e+00 -6.54873550e-01 4.06605721e-01
-1.75077230e-01 -1.10376644e+00 -2.06694409e-01 4.93966043e-01
-7.91140556e-01 -9.51205909e-01 -1.09918308e+00 -1.05662262e+00
2.82045901e-01 4.52590227e-01 9.26566958e-01 -3.32539737e-01
-3.51911515e-01 -5.34595698e-02 -2.76680946e-01 -3.97589386e-01
-1.99410096e-02 1.60301998e-01 1.83768466e-01 2.17936084e-01
3.55876327e-01 -7.79470980e-01 -6.29574120e-01 2.15936273e-01
-8.87389779e-01 -3.49933624e-01 8.65032613e-01 6.05020046e-01
5.85629284e-01 5.01949608e-01 8.75720918e-01 -5.64845085e-01
8.20587158e-01 -3.29247952e-01 -2.40102470e-01 -1.28219992e-01
1.89523652e-01 -7.71644264e-02 9.18851256e-01 -8.65398467e-01
-1.10585988e+00 -1.27395066e-02 -1.78870037e-01 -8.67891908e-01
-7.57113457e-01 2.14976832e-01 -1.04420833e-01 -3.28383669e-02
6.43496454e-01 6.19608387e-02 -5.33429563e-01 -1.15384519e+00
1.63201720e-01 9.18210268e-01 7.98993289e-01 -4.50298548e-01
5.32898128e-01 2.05046445e-01 -2.63203323e-01 -8.89156401e-01
-8.85742366e-01 -4.63133156e-01 -9.94118631e-01 -1.38042225e-02
9.23329234e-01 -1.46598184e+00 -3.01056951e-01 6.78993702e-01
-1.07189870e+00 -1.73542291e-01 -4.07868594e-01 7.80267179e-01
-1.56048894e-01 -3.87448847e-01 -8.74746501e-01 -8.84160995e-01
-4.26496714e-01 -9.36922431e-01 1.12984324e+00 6.64520144e-01
1.00903749e-01 -8.31480324e-01 2.15285316e-01 -2.41027698e-01
7.10537314e-01 2.04940617e-01 6.03065073e-01 -6.30707264e-01
-3.41663629e-01 3.19247134e-02 -4.27497923e-01 6.17204905e-01
5.04568219e-01 -7.03199357e-02 -1.70342422e+00 -3.06855589e-01
-1.60777152e-01 -3.27216715e-01 1.36755955e+00 8.13322365e-01
1.19341683e+00 -4.92998272e-01 6.12562662e-03 8.01098526e-01
1.54340136e+00 1.79702863e-02 3.44474882e-01 -2.98101790e-02
8.09975147e-01 2.35942453e-01 6.43790886e-02 3.49826038e-01
-5.85750788e-02 3.15940350e-01 3.67833018e-01 -3.83295029e-01
-6.33182108e-01 -9.28472877e-02 5.79392314e-01 8.74114275e-01
-3.89574289e-01 1.70148268e-01 -4.21684802e-01 6.95356190e-01
-1.57530212e+00 -8.97127390e-01 1.82335436e-01 1.75946903e+00
6.73668444e-01 2.68415846e-02 2.01420233e-01 5.54304242e-01
1.12684762e+00 4.64725852e-01 -4.42799658e-01 -5.29326379e-01
-2.24404946e-01 7.93253541e-01 -4.77201976e-02 2.11616963e-01
-1.30472624e+00 7.26264119e-01 6.21904993e+00 8.89833272e-01
-1.48179603e+00 -5.59275523e-02 2.68222183e-01 -3.32068920e-01
3.23708713e-01 -6.08116269e-01 -9.61594284e-01 -1.50257219e-02
1.29442430e+00 3.21828246e-01 3.73712122e-01 9.42253470e-01
-2.38883838e-01 4.06957835e-01 -8.29845309e-01 1.06087124e+00
-2.69588143e-01 -1.22348380e+00 3.48674715e-01 3.42719420e-03
6.18419051e-01 1.33511573e-01 2.51672477e-01 3.49460751e-01
2.91997492e-01 -1.47196758e+00 5.34232080e-01 5.87642014e-01
1.00724995e+00 -1.29124212e+00 7.21277773e-01 1.83782056e-01
-1.98754561e+00 -5.95221400e-01 -9.73672867e-01 -2.59812742e-01
-3.81698877e-01 6.22204065e-01 -5.10989308e-01 3.92814547e-01
1.24582732e+00 7.45361447e-01 -4.53554392e-01 7.57297277e-01
8.83815289e-02 6.16059959e-01 -1.63449302e-01 3.71822149e-01
3.11235666e-01 4.13692921e-01 4.03854728e-01 1.70396137e+00
3.60039532e-01 1.01192676e-01 -4.62263934e-02 1.03146887e+00
-3.35004598e-01 -1.60247967e-01 -4.62172419e-01 8.40838701e-02
5.05150557e-01 1.70138407e+00 -5.27126491e-01 -9.56178084e-02
-3.60548407e-01 5.06272912e-01 4.39516217e-01 5.15219390e-01
-3.60428602e-01 -1.05372131e+00 1.15421462e+00 -4.90625501e-02
9.24380302e-01 -3.06094177e-02 2.09003035e-02 -9.41114008e-01
-2.86599189e-01 -6.76634610e-01 4.49486822e-01 -8.38224173e-01
-1.16859376e+00 1.40497756e+00 -3.04072291e-01 -1.33174169e+00
-1.68341205e-01 -8.26552093e-01 -6.97925150e-01 1.09890640e+00
-1.91600811e+00 -1.09693015e+00 -3.84698629e-01 1.13010144e+00
6.24544740e-01 -3.93798470e-01 1.00992382e+00 3.34445059e-01
-4.57949817e-01 5.85685313e-01 -1.77835166e-01 8.36563826e-01
5.71021318e-01 -1.21179378e+00 1.70889884e-01 5.86542845e-01
4.10456836e-01 7.60306120e-01 -6.01345561e-02 -1.17270730e-01
-8.63290429e-01 -1.57215250e+00 4.47463661e-01 2.15586513e-01
1.08623810e-01 -3.47977459e-01 -1.18720222e+00 5.56369126e-01
2.20825821e-01 5.54223001e-01 8.53385091e-01 2.06119791e-01
-7.50718951e-01 -3.92683893e-01 -1.00387990e+00 -1.39213517e-01
6.16684616e-01 -9.73713934e-01 -6.43468320e-01 -4.76409972e-01
7.89138973e-01 -2.00997204e-01 -1.07869875e+00 6.53270960e-01
5.62371373e-01 -9.05827761e-01 1.32853806e+00 -4.64421988e-01
4.08962071e-01 -3.71423453e-01 -4.14227039e-01 -1.36549091e+00
-9.51975644e-01 -4.03951943e-01 -2.91936398e-01 1.29566789e+00
1.66087076e-01 -1.43597901e-01 1.14448346e-01 -2.29656309e-01
-1.56226262e-01 -4.17109936e-01 -8.73761892e-01 -4.36911583e-01
2.75968134e-01 -3.48171711e-01 9.02320504e-01 7.09453583e-01
-5.07687092e-01 4.57652539e-01 -2.85146147e-01 6.19762480e-01
3.63677442e-01 3.81188065e-01 2.26060256e-01 -1.78686941e+00
-1.38750345e-01 -5.15510678e-01 -5.35720527e-01 -8.40861440e-01
5.96288554e-02 -5.07980049e-01 -1.09114520e-01 -1.41849720e+00
6.17809221e-02 -1.68165475e-01 -9.70316350e-01 5.70378304e-01
8.15027580e-03 6.05784237e-01 1.21284105e-01 1.21243693e-01
-5.01734853e-01 2.53706187e-01 1.17663503e+00 -1.05828732e-01
-3.90148878e-01 2.78008670e-01 -8.24022353e-01 1.01173925e+00
8.64711642e-01 -3.20158809e-01 -3.39927793e-01 -4.71087366e-01
-1.34393156e-01 -5.10869594e-03 5.21462739e-01 -1.54399526e+00
2.40038976e-01 1.55027688e-01 1.16048598e+00 -5.97910821e-01
4.40275341e-01 -6.01058602e-01 -9.34986100e-02 -1.21269068e-02
-8.26159418e-01 -2.45577291e-01 4.66216505e-01 4.42930609e-01
-7.36463368e-01 6.48230687e-02 9.48963404e-01 -4.56658304e-01
-6.62591934e-01 2.61474609e-01 -4.42295313e-01 -3.22427191e-02
2.21760288e-01 3.10185347e-02 -2.46011034e-01 -4.16846156e-01
-9.37865853e-01 -4.38416421e-01 -4.88711774e-01 7.75724351e-01
1.21226573e+00 -1.72223473e+00 -7.50402808e-01 5.59277594e-01
-2.79814720e-01 4.95581239e-01 3.91491294e-01 1.40595779e-01
7.32108904e-03 5.20388126e-01 -7.09983945e-01 -4.79547292e-01
-1.26206195e+00 3.68690580e-01 6.24880791e-01 -6.94372132e-02
-7.45610237e-01 1.27222800e+00 7.18279183e-01 -3.86352599e-01
5.13459802e-01 -7.37650812e-01 -7.80780911e-01 9.94354561e-02
1.20930552e+00 4.51696336e-01 -2.19256543e-02 -1.02018034e+00
-3.37496817e-01 9.43542302e-01 -2.44803913e-02 -5.91367334e-02
1.70881402e+00 4.22715507e-02 1.06370285e-01 5.38830221e-01
1.44809425e+00 2.60837283e-02 -1.41966021e+00 -6.79317057e-01
-4.13829207e-01 -1.73686519e-01 6.80202365e-01 -7.23858654e-01
-1.60441566e+00 1.49986231e+00 7.27118552e-01 5.85655645e-02
1.54290462e+00 -1.39726400e-02 6.75440788e-01 1.69918537e-01
-3.70117426e-02 -8.76572371e-01 3.93584132e-01 5.82805932e-01
1.07250535e+00 -6.46805942e-01 -3.23774636e-01 3.29480916e-02
-6.10378265e-01 1.68274033e+00 8.31936717e-01 -6.10696435e-01
1.05338132e+00 8.13625932e-01 1.94550097e-01 -1.06023945e-01
-9.43096220e-01 -5.14916480e-01 6.73626065e-01 7.14385390e-01
5.43633163e-01 3.91137190e-02 9.47187185e-01 1.33793366e+00
-2.56452322e-01 1.13785481e-02 1.20552644e-01 5.89619875e-01
-9.15657878e-01 -6.32358551e-01 -5.58809459e-01 6.62862808e-02
-6.99744523e-01 -1.42013997e-01 -5.43671548e-01 4.45974559e-01
3.13197821e-01 1.02186739e+00 5.02629519e-01 -7.32493281e-01
1.19058169e-01 -4.00919060e-04 2.37196133e-01 -5.00967801e-01
-8.76402020e-01 6.81728125e-01 -3.82081568e-01 -3.88408989e-01
-5.58223605e-01 -7.99282193e-02 -1.47747898e+00 6.19897395e-02
-2.75383234e-01 2.50527978e-01 4.61473078e-01 5.83274901e-01
3.75619113e-01 1.27342904e+00 7.73515224e-01 -1.07820642e+00
-1.45852789e-01 -1.34018803e+00 -8.92212570e-01 -2.90701210e-01
1.21076775e+00 -4.56008375e-01 -3.25422347e-01 3.84159274e-02] | [15.45818042755127, 5.491130828857422] |
509c2e2b-1a7b-430d-92d9-9385146f1392 | improved-marginal-unbiased-score-expansion | 2209.10512 | null | https://arxiv.org/abs/2209.10512v1 | https://arxiv.org/pdf/2209.10512v1.pdf | Improved Marginal Unbiased Score Expansion (MUSE) via Implicit Differentiation | We apply the technique of implicit differentiation to boost performance, reduce numerical error, and remove required user-tuning in the Marginal Unbiased Score Expansion (MUSE) algorithm for hierarchical Bayesian inference. We demonstrate these improvements on three representative inference problems: 1) an extended Neal's funnel 2) Bayesian neural networks, and 3) probabilistic principal component analysis. On our particular test cases, MUSE with implicit differentiation is faster than Hamiltonian Monte Carlo by factors of 155, 397, and 5, respectively, or factors of 65, 278, and 1 without implicit differentiation, and yields good approximate marginal posteriors. The Julia and Python MUSE packages have been updated to use implicit differentiation, and can solve problems defined by hand or with any of a number of popular probabilistic programming languages and automatic differentiation backends. | ['Marius Millea'] | 2022-09-21 | null | null | null | null | ['probabilistic-programming'] | ['methodology'] | [ 1.60637256e-02 2.79862928e-04 -1.16135038e-01 -3.65333468e-01
-1.25578046e+00 -6.76761985e-01 6.95569515e-01 4.48613875e-02
-7.31535435e-01 1.27012658e+00 1.34466877e-02 -5.23260832e-01
-3.34361762e-01 -6.62533879e-01 -4.68362182e-01 -9.68122542e-01
-2.03638598e-01 1.06288576e+00 4.30953830e-01 5.38576961e-01
3.90504509e-01 4.50246364e-01 -1.13183093e+00 -3.99420470e-01
8.97689998e-01 5.14679790e-01 -4.68198240e-01 8.85148704e-01
3.59852493e-01 2.48146772e-01 -2.00554669e-01 -6.67935431e-01
-1.33651823e-01 -2.12009266e-01 -5.46266496e-01 -8.00150573e-01
3.22357506e-01 -5.42255044e-01 -4.20896411e-02 1.05178940e+00
7.91246355e-01 2.95205206e-01 1.26635003e+00 -9.42940772e-01
-2.90051430e-01 9.63352203e-01 -9.54358637e-01 2.43329629e-01
2.51246504e-02 2.17255160e-01 8.09042215e-01 -8.09854686e-01
2.70668387e-01 1.59774196e+00 1.12605453e+00 4.88494597e-02
-1.90705764e+00 -8.33167434e-01 -4.77706343e-01 -2.53716528e-01
-1.88031769e+00 -5.18642128e-01 1.79076359e-01 -5.84720194e-01
8.36583912e-01 2.64981240e-01 4.08773541e-01 9.86534834e-01
2.77544647e-01 3.64710599e-01 1.19957149e+00 -2.50932187e-01
6.83003724e-01 -1.92230158e-02 5.67065477e-01 7.30683982e-01
3.37818146e-01 3.44565660e-01 -4.25415605e-01 -1.28156745e+00
7.23133743e-01 -5.49335003e-01 9.17287692e-02 -9.62119401e-02
-9.46966469e-01 1.15869641e+00 -3.30255508e-01 -3.97553384e-01
-2.18183696e-01 6.46360517e-01 2.49351844e-01 -5.99642217e-01
5.87121546e-01 2.36621618e-01 -3.77302438e-01 -4.13865298e-01
-1.29673254e+00 7.22506821e-01 9.68527257e-01 5.78901112e-01
7.31915653e-01 6.18285425e-02 -2.72046030e-01 8.57475221e-01
6.30458951e-01 8.56193304e-01 -1.94691475e-02 -1.72071064e+00
-1.12049319e-01 -2.30172545e-01 3.76286119e-01 -5.94793260e-01
-4.75493908e-01 -5.08983195e-01 -7.73634136e-01 1.06077552e-01
6.86195016e-01 -3.74273509e-01 -8.27162623e-01 1.78711665e+00
6.28793597e-01 2.13686582e-02 -3.60821515e-01 5.17455757e-01
4.05502945e-01 7.60225952e-01 2.57140309e-01 -3.61338139e-01
1.43047822e+00 -2.00382441e-01 -5.41399181e-01 2.29224400e-03
2.55301654e-01 -7.63152003e-01 7.68105328e-01 5.85374057e-01
-1.34549224e+00 9.57730133e-03 -8.85413408e-01 -2.08253413e-01
-4.15510274e-02 9.81332082e-03 8.86054575e-01 9.73432124e-01
-9.94076729e-01 8.04780245e-01 -1.25464809e+00 1.67075872e-01
3.58921856e-01 3.20815116e-01 2.73513943e-01 7.14346468e-02
-1.08803475e+00 8.03057611e-01 3.67236435e-01 -1.98008046e-01
-9.09534097e-01 -1.08011663e+00 -5.49586475e-01 3.36562932e-01
1.42108291e-01 -8.05106282e-01 1.24536002e+00 -1.10259622e-01
-1.52719247e+00 3.97668570e-01 -1.61956951e-01 -3.60025764e-01
6.46636724e-01 -1.15738818e-02 8.08267295e-02 4.37305905e-02
1.99770972e-01 8.33294272e-01 3.77691627e-01 -8.00601006e-01
-1.03471935e-01 -5.36903977e-01 -3.50135386e-01 -1.32771796e-02
-4.67216857e-02 1.81801736e-01 -6.06778920e-01 -4.28236574e-01
1.31216943e-01 -9.60340202e-01 -3.30694050e-01 -2.36523926e-01
-5.87039232e-01 -1.39061213e-01 -6.17888290e-03 -1.04940236e+00
1.01534247e+00 -1.92320263e+00 -1.25249103e-02 6.54901624e-01
-3.86566669e-02 -3.23749423e-01 2.89872944e-01 6.95194751e-02
1.78239778e-01 9.88764688e-02 -9.21755791e-01 -1.61685273e-01
3.72209579e-01 1.28417820e-01 8.85601640e-02 5.54036736e-01
-2.14772329e-01 4.04059589e-01 -7.24984050e-01 -7.11698472e-01
-1.41315579e-01 6.77238584e-01 -1.01212001e+00 -2.50685722e-01
-1.67542711e-01 2.27121070e-01 -1.67270958e-01 4.18116242e-01
8.06180298e-01 -3.13464046e-01 4.75728869e-01 -3.41800302e-02
-2.97370940e-01 4.38239962e-01 -1.49035323e+00 1.38184869e+00
-7.37585202e-02 3.70715290e-01 8.47082809e-02 -3.55662018e-01
4.41886336e-01 2.01781645e-01 -5.36111323e-03 6.30213916e-02
-1.55263320e-01 2.52831161e-01 -3.61182801e-02 1.34180158e-01
5.12594283e-01 -3.83696377e-01 -7.72337094e-02 5.25332928e-01
6.43685162e-02 -3.65919352e-01 3.47035527e-01 3.42138171e-01
1.02381229e+00 2.74169654e-01 3.27439576e-01 -7.16901660e-01
-6.11145943e-02 -3.88695113e-02 6.17400765e-01 1.19144464e+00
9.92976502e-02 5.20641565e-01 9.45302427e-01 2.50375308e-02
-1.01026642e+00 -1.52380979e+00 -7.92145371e-01 1.11709428e+00
-5.11735618e-01 -2.90948689e-01 -7.43246794e-01 1.21039459e-02
1.74774379e-01 1.17090726e+00 -2.78950006e-01 1.66749135e-01
-1.55577719e-01 -1.68692303e+00 1.01902664e+00 5.58006406e-01
2.11026654e-01 -4.59633887e-01 -3.40299040e-01 1.24419495e-01
-9.01608914e-02 -6.15727842e-01 -4.36093211e-01 2.25308910e-01
-9.82537210e-01 -7.04885781e-01 -8.20097327e-01 2.19548926e-01
3.15356284e-01 -5.31526327e-01 9.15765345e-01 -4.86424416e-01
-2.48118967e-01 1.65648952e-01 3.82229298e-01 -1.52831197e-01
-3.01947623e-01 5.01723774e-02 1.63092002e-01 -6.33305371e-01
1.34458825e-01 -9.77205575e-01 -3.26072782e-01 9.95485708e-02
-7.03480482e-01 -1.43915877e-01 2.66211271e-01 9.85303402e-01
3.13284099e-01 -1.80333912e-01 2.58383155e-01 -6.25424325e-01
6.48063183e-01 -4.52865064e-01 -1.32277083e+00 -6.48705959e-02
-7.28274167e-01 4.69721377e-01 -3.81134748e-02 -2.04854086e-01
-1.40143061e+00 -6.90554604e-02 -1.89267322e-01 -7.35575287e-03
2.67430007e-01 8.85113895e-01 2.68812686e-01 1.68414474e-01
7.47599363e-01 -1.82863146e-01 -1.35281011e-01 -6.22339666e-01
3.14216226e-01 5.74905515e-01 7.46977746e-01 -9.26587582e-01
4.52027142e-01 3.67893428e-01 3.23618919e-01 -5.49708247e-01
-5.48625946e-01 2.64984891e-02 -3.13380390e-01 1.71831384e-01
8.66374969e-01 -9.10958171e-01 -1.03987062e+00 3.88180077e-01
-1.07607710e+00 -3.89282286e-01 1.53439507e-01 7.59694040e-01
-2.32605264e-01 5.84941447e-01 -8.59060109e-01 -1.19930458e+00
-2.74140954e-01 -1.12673223e+00 8.79904389e-01 3.33518833e-01
-3.67579818e-01 -7.86287010e-01 3.96327317e-01 2.14236274e-01
2.75611073e-01 2.64844056e-02 1.10744178e+00 -3.86092812e-01
-3.33389580e-01 -7.48948082e-02 -4.27692592e-01 1.08137734e-01
-4.72097337e-01 5.41077733e-01 -1.02743590e+00 -1.02364153e-01
-3.54419976e-01 -8.23784843e-02 8.81727099e-01 8.05452049e-01
1.04664791e+00 -2.95740694e-01 -3.82735401e-01 5.64240336e-01
1.13416636e+00 1.12897698e-02 5.02025127e-01 -2.59394526e-01
2.58795410e-01 3.83415878e-01 -6.19800435e-03 7.99998462e-01
3.39959294e-01 6.95519865e-01 -1.02521189e-01 5.17205894e-01
3.25514585e-01 -1.23382255e-01 4.18017775e-01 7.63525069e-01
-3.10976654e-01 2.98532188e-01 -1.14548957e+00 4.15667742e-01
-1.80495310e+00 -1.01849473e+00 -5.47038794e-01 2.33881354e+00
1.33550644e+00 1.45410836e-01 1.00002557e-01 -3.35116267e-01
6.43573523e-01 -2.47926861e-01 -6.03550315e-01 -2.72983700e-01
1.59386903e-01 4.63668913e-01 8.25325251e-01 8.82957220e-01
-8.44704390e-01 6.06396973e-01 8.09484196e+00 1.12611759e+00
-3.49661261e-01 5.44148386e-01 7.76660442e-01 -2.94412434e-01
-3.47710043e-01 3.35856199e-01 -9.25346971e-01 4.91859347e-01
1.38812530e+00 -4.66908887e-02 5.76229274e-01 7.55714178e-01
1.09954663e-01 -6.31733000e-01 -9.76334691e-01 6.57153428e-01
-4.18977797e-01 -1.26187503e+00 -3.54338557e-01 2.02786312e-01
6.48009896e-01 1.82098627e-01 -1.25022218e-01 2.47011602e-01
1.03232718e+00 -9.50671315e-01 5.47802687e-01 6.67461276e-01
5.79648852e-01 -1.05769897e+00 7.23447144e-01 2.27629364e-01
-5.41198254e-01 4.16423380e-01 -4.37152267e-01 1.23814913e-02
3.92769873e-01 1.21904075e+00 -6.79919481e-01 3.55334044e-01
7.73138344e-01 -8.58261809e-02 -3.14761370e-01 1.00983655e+00
-3.07183057e-01 1.12810647e+00 -9.78191853e-01 -9.31235850e-02
8.93554538e-02 -4.48194444e-01 6.24333322e-01 1.31038249e+00
2.86511213e-01 1.25213891e-01 -5.27259588e-01 1.49404311e+00
3.03739816e-01 -4.70663428e-01 2.06648260e-02 1.17300600e-01
6.71290576e-01 1.12752259e+00 -7.36550689e-01 -4.49009061e-01
1.70917317e-01 3.12784195e-01 5.66087514e-02 5.32008231e-01
-9.67048526e-01 -5.15446305e-01 5.17453969e-01 -2.68576652e-01
3.38993907e-01 -3.39186847e-01 -5.12372494e-01 -8.94839525e-01
-4.81474876e-01 -6.28367662e-01 4.81432736e-01 -1.05457795e+00
-1.23963356e+00 -2.03611866e-01 6.79552853e-01 -6.08037896e-02
-6.56507730e-01 -6.23646975e-01 -4.17258978e-01 1.25200534e+00
-7.83695519e-01 -3.98896217e-01 3.75598937e-01 1.19630165e-01
-3.27384561e-01 2.48537675e-01 7.11476028e-01 4.05893922e-01
-6.32089555e-01 3.93456101e-01 5.44240594e-01 -1.85153872e-01
4.13061380e-01 -1.24713254e+00 2.76961327e-01 6.35082901e-01
-3.83683175e-01 9.41143274e-01 8.93459499e-01 -7.27459550e-01
-1.26300704e+00 -4.11352575e-01 7.23851025e-01 -4.58262593e-01
6.54412448e-01 -3.63592684e-01 -8.07869494e-01 8.06975543e-01
-5.97550981e-02 -4.51979429e-01 7.12343633e-01 6.74297035e-01
-4.46964383e-01 4.77760993e-02 -1.24223840e+00 7.42902160e-01
8.35213721e-01 -4.37984347e-01 -3.95120621e-01 4.37309802e-01
3.76844376e-01 -2.15724990e-01 -1.17344368e+00 2.98339427e-01
1.07855964e+00 -1.02471232e+00 1.15552318e+00 -2.29855135e-01
1.54829979e-01 -3.24844658e-01 -2.67104298e-01 -8.73692930e-01
-2.99623877e-01 -7.78709292e-01 -2.06608158e-02 1.30825841e+00
4.50484604e-01 -8.43219399e-01 5.19859910e-01 9.09274399e-01
-4.64275666e-03 -2.03001514e-01 -1.25081217e+00 -5.10633349e-01
2.79379249e-01 -6.51933908e-01 4.11562264e-01 5.98923385e-01
-7.94597343e-02 3.13518256e-01 -2.27779314e-01 2.28378206e-01
1.21458483e+00 -2.10349649e-01 5.69149554e-01 -1.27266109e+00
-8.45137477e-01 -6.10256195e-01 8.43345746e-02 -9.15538847e-01
4.24227081e-02 -7.85970032e-01 -1.51260002e-02 -1.15731192e+00
8.87059033e-01 -2.95217425e-01 1.21712118e-01 5.87469637e-01
-2.29701087e-01 1.72189698e-01 -3.20290148e-01 5.09557053e-02
-4.88279350e-02 5.89325368e-01 5.02312243e-01 1.89339370e-02
2.05219433e-01 -1.64552838e-01 -7.08774865e-01 1.03361702e+00
3.94137174e-01 -1.04786360e+00 3.48906070e-02 -8.78228843e-02
6.64826453e-01 2.96249926e-01 5.94731867e-01 -6.36825204e-01
-3.35584544e-02 -1.68045029e-01 6.66546762e-01 -8.61755967e-01
4.37588185e-01 6.70910329e-02 5.92219889e-01 5.80419600e-01
-2.18053758e-01 -2.34551076e-02 4.18434381e-01 2.30795756e-01
3.00613344e-01 -6.86407328e-01 9.16051507e-01 -1.74903292e-02
2.65673995e-01 -2.70205170e-01 -7.69528091e-01 1.33370578e-01
2.81587034e-01 2.85394102e-01 -3.54886681e-01 -4.60205376e-01
-7.52921224e-01 1.91751137e-01 3.58669579e-01 -5.77387571e-01
1.54489726e-01 -1.20394397e+00 -7.31034279e-01 -3.73824894e-01
-5.03414094e-01 -1.59375384e-01 2.17850685e-01 1.23241425e+00
-5.94048977e-01 2.98328459e-01 1.73464164e-01 -6.91698015e-01
-8.79235804e-01 4.44677174e-02 2.61861116e-01 -3.15534353e-01
-1.07133493e-01 7.15070426e-01 -1.48353213e-02 -8.13196123e-01
5.04330918e-02 -1.85470030e-01 4.00469363e-01 -2.20800787e-02
5.67704082e-01 1.07682049e+00 -2.91650891e-01 -3.72596718e-02
-4.98456955e-01 2.75161266e-01 2.31780797e-01 -1.04205322e+00
1.33349466e+00 2.12484971e-01 -5.00062585e-01 6.14609122e-01
8.77574623e-01 1.99538171e-01 -1.25200260e+00 1.28305286e-01
1.90112237e-02 -4.98766936e-02 2.97131956e-01 -9.30627406e-01
-4.92772698e-01 7.27001965e-01 4.57949281e-01 5.62136658e-02
5.30389249e-01 -1.11194439e-01 3.68666872e-02 3.89056087e-01
1.66537330e-01 -9.11757827e-01 -5.45439541e-01 4.11693007e-01
6.04636133e-01 -6.96547568e-01 6.72546983e-01 -1.08105212e-01
-1.75124556e-01 7.80228019e-01 6.18348755e-02 -1.49283111e-02
7.57458687e-01 4.47186351e-01 -6.66873872e-01 -1.46802530e-01
-7.14958787e-01 2.77907878e-01 3.29291731e-01 3.00650299e-01
5.08447587e-01 6.43151924e-02 -5.52325964e-01 6.44246936e-01
-2.42565274e-01 7.98551273e-03 3.91122252e-01 6.30932391e-01
-1.79434702e-01 -7.48287201e-01 -7.96945512e-01 6.32827401e-01
-5.72762072e-01 -5.80403090e-01 1.54735160e-03 7.53865004e-01
-3.93514007e-01 6.34153187e-01 2.33829141e-01 3.42713475e-01
-4.09651846e-01 4.60476756e-01 6.59356534e-01 -2.75111109e-01
-2.96722174e-01 5.11714220e-01 3.93461913e-01 -2.60519773e-01
-3.50628763e-01 -1.21325517e+00 -1.20314002e+00 -5.51413119e-01
-4.14627790e-01 3.13265771e-01 8.13601732e-01 1.01250911e+00
3.44294965e-01 2.10404113e-01 -1.50577888e-01 -1.04868770e+00
-9.06897366e-01 -1.26216722e+00 -7.37622023e-01 -5.33553541e-01
-2.23044485e-01 -8.03039432e-01 -7.08247542e-01 -2.60710776e-01] | [6.9558563232421875, 4.001534461975098] |
ebc3283f-0bbf-4a1c-a8a4-13f83fa84f97 | moving-object-detection-under-discontinuous | 1904.03175 | null | http://arxiv.org/abs/1904.03175v2 | http://arxiv.org/pdf/1904.03175v2.pdf | Moving Object Detection under Discontinuous Change in Illumination Using Tensor Low-Rank and Invariant Sparse Decomposition | Although low-rank and sparse decomposition based methods have been
successfully applied to the problem of moving object detection using structured
sparsity-inducing norms, they are still vulnerable to significant illumination
changes that arise in certain applications. We are interested in moving object
detection in applications involving time-lapse image sequences for which
current methods mistakenly group moving objects and illumination changes into
foreground. Our method relies on the multilinear (tensor) data low-rank and
sparse decomposition framework to address the weaknesses of existing methods.
The key to our proposed method is to create first a set of prior maps that can
characterize the changes in the image sequence due to illumination. We show
that they can be detected by a k-support norm. To deal with concurrent, two
types of changes, we employ two regularization terms, one for detecting moving
objects and the other for accounting for illumination changes, in the tensor
low-rank and sparse decomposition formulation. Through comprehensive
experiments using challenging datasets, we show that our method demonstrates a
remarkable ability to detect moving objects under discontinuous change in
illumination, and outperforms the state-of-the-art solutions to this
challenging problem. | ['Moein Shakeri', 'Hong Zhang'] | 2019-04-05 | moving-object-detection-under-discontinuous-1 | http://openaccess.thecvf.com/content_CVPR_2019/html/Shakeri_Moving_Object_Detection_Under_Discontinuous_Change_in_Illumination_Using_Tensor_CVPR_2019_paper.html | http://openaccess.thecvf.com/content_CVPR_2019/papers/Shakeri_Moving_Object_Detection_Under_Discontinuous_Change_in_Illumination_Using_Tensor_CVPR_2019_paper.pdf | cvpr-2019-6 | ['moving-object-detection'] | ['computer-vision'] | [ 6.25295579e-01 -7.56019592e-01 8.74873996e-02 -1.25506580e-01
-6.74753666e-01 -5.59512913e-01 3.84851098e-01 -6.56383097e-01
-1.21449614e-02 5.25664747e-01 9.63865817e-02 1.11950547e-01
-1.73067212e-01 -1.79152906e-01 -6.36999607e-01 -1.02712274e+00
-2.59734750e-01 -6.36178851e-02 4.75289047e-01 8.20676833e-02
2.82144189e-01 4.52857554e-01 -1.66403067e+00 5.95753968e-01
6.21346354e-01 9.60527956e-01 1.71891883e-01 6.99101388e-01
2.68534243e-01 1.00601339e+00 -3.67538393e-01 8.37544650e-02
5.61919808e-01 -1.95180610e-01 -6.36084497e-01 6.69671416e-01
9.13734436e-01 -3.18926394e-01 -3.77377331e-01 1.11934876e+00
2.22378850e-01 1.88828185e-01 4.89271820e-01 -1.36824560e+00
-3.69741261e-01 8.23227018e-02 -9.68277037e-01 7.43964851e-01
4.04776722e-01 3.13602760e-02 6.74329937e-01 -1.39328837e+00
6.58415794e-01 1.34805632e+00 6.93479538e-01 1.15011789e-01
-1.29687798e+00 -2.97886163e-01 4.35113877e-01 4.60678518e-01
-1.28469503e+00 -8.12771559e-01 9.99271572e-01 -8.10640633e-01
4.81410742e-01 6.15142524e-01 3.00929159e-01 9.07152593e-01
7.14260060e-03 8.37460697e-01 1.17748809e+00 -2.57163703e-01
1.11503070e-02 -2.18736917e-01 1.33105427e-01 6.00247800e-01
5.34545600e-01 -5.67588694e-02 -5.89181125e-01 -3.86037260e-01
6.39801383e-01 1.82723999e-01 -6.21202886e-01 -5.71739554e-01
-1.60010374e+00 4.87759888e-01 2.60525867e-02 4.20076460e-01
-5.69441557e-01 8.41874927e-02 2.11822137e-01 -4.27772887e-02
4.53479737e-01 5.96041977e-02 -3.18191767e-01 7.94961825e-02
-1.02901518e+00 1.10055871e-01 3.78249466e-01 7.39120007e-01
6.53633595e-01 2.86192983e-01 -2.22567037e-01 7.36135542e-01
2.12860391e-01 7.00407207e-01 2.89724559e-01 -1.09008825e+00
4.07151312e-01 3.14863265e-01 4.14756328e-01 -1.68992984e+00
-2.31683582e-01 -4.14287508e-01 -9.43374097e-01 -1.01565167e-01
5.26784182e-01 2.64541388e-01 -7.08365440e-01 1.49923217e+00
6.78686321e-01 7.74308860e-01 -2.36957744e-02 1.12235641e+00
5.12409270e-01 6.16019189e-01 -3.78745496e-01 -6.35428369e-01
1.48227835e+00 -7.66670704e-01 -9.62086976e-01 -2.36688644e-01
4.04417723e-01 -9.30038571e-01 6.98060095e-01 5.23201048e-01
-1.04083681e+00 -4.33809251e-01 -8.02850783e-01 1.17003396e-01
6.37767315e-02 3.54101926e-01 5.25228322e-01 5.07303238e-01
-7.86302388e-01 2.58219212e-01 -9.11379516e-01 -4.22122627e-01
9.72814634e-02 2.62235422e-02 -2.93799251e-01 -3.69227320e-01
-8.80549192e-01 7.20004141e-01 -1.07811540e-01 6.70084536e-01
-1.06407380e+00 -5.76154172e-01 -7.02312887e-01 -2.82709986e-01
6.03199124e-01 -5.86525619e-01 7.13392019e-01 -8.38987887e-01
-1.00400496e+00 7.39365280e-01 -4.52795595e-01 -4.90357652e-02
5.31039655e-01 -2.81998545e-01 -4.27646995e-01 5.04527807e-01
2.65697569e-01 -6.59810081e-02 1.49324369e+00 -1.56411850e+00
-7.31577933e-01 -4.09276307e-01 -1.05956249e-01 2.11446751e-02
-3.01567674e-01 1.67101637e-01 -6.01151466e-01 -9.10273731e-01
5.67176878e-01 -1.06388652e+00 -2.40506634e-01 -1.36727810e-01
-2.31256947e-01 1.46866724e-01 1.36986637e+00 -8.03182006e-01
1.04726803e+00 -2.18702507e+00 2.92567432e-01 1.41136590e-02
2.53579259e-01 2.52516896e-01 -2.39685431e-01 1.37210637e-01
-8.04115981e-02 -3.03833038e-01 -3.59219164e-01 -3.30790907e-01
-3.73099685e-01 2.84699231e-01 -4.27888930e-01 9.99394119e-01
2.54757941e-01 3.56612325e-01 -1.03880370e+00 -4.89756733e-01
6.70324862e-02 5.46989858e-01 -2.65958369e-01 1.37795731e-01
2.85618544e-01 5.86275399e-01 -4.58140671e-01 8.47289085e-01
9.13586974e-01 -2.73494899e-01 3.23038362e-02 -8.15183103e-01
-3.19934517e-01 -1.76704615e-01 -1.64084923e+00 1.46322668e+00
7.08941966e-02 6.54007614e-01 5.45694172e-01 -1.16833270e+00
4.37615126e-01 2.80911684e-01 8.87332320e-01 -2.84851670e-01
-2.45216675e-03 1.81108430e-01 -1.74470291e-01 -7.86472142e-01
5.75209916e-01 -1.11159561e-02 4.45922524e-01 2.13547304e-01
-3.71701598e-01 2.22658873e-01 5.93467176e-01 3.64637554e-01
1.31562173e+00 8.09266567e-02 -5.57156652e-02 -2.45980695e-01
8.29324245e-01 -1.87218830e-01 9.74031866e-01 6.71679556e-01
-2.41770834e-01 7.58643150e-01 2.02211842e-01 -5.02094150e-01
-7.01941848e-01 -7.25260377e-01 -1.31726190e-01 1.03199303e+00
1.96689695e-01 -2.62473226e-02 -4.13609058e-01 -4.67978209e-01
-5.28840646e-02 1.05780326e-01 -4.73275661e-01 1.48292169e-01
-7.28546143e-01 -1.10552835e+00 2.43176371e-01 3.46732914e-01
3.57526064e-01 -3.80682737e-01 -6.99411988e-01 2.42423877e-01
-7.52999306e-01 -1.72132349e+00 -5.18423855e-01 -1.92580909e-01
-9.56818581e-01 -1.21962905e+00 -8.85679543e-01 -5.23835123e-01
1.00123882e+00 1.01315892e+00 8.11574340e-01 -1.03274891e-02
-5.96920609e-01 8.80410671e-01 -4.50599521e-01 9.56236273e-02
-1.59669332e-02 -5.48053265e-01 3.80550891e-01 8.31250608e-01
-1.23265311e-01 -3.79756600e-01 -7.25581646e-01 7.57727742e-01
-1.17743325e+00 -2.32442543e-02 4.54759389e-01 6.36143982e-01
4.60655183e-01 2.21115917e-01 4.47504334e-02 -6.28309011e-01
1.31347492e-01 -4.22176808e-01 -7.40824401e-01 1.73520550e-01
-3.02225083e-01 -2.21890554e-01 2.55533934e-01 -7.62148380e-01
-9.66690421e-01 3.14771295e-01 5.10382712e-01 -6.73484266e-01
1.37792215e-01 4.53906327e-01 -9.54570994e-02 -5.51418185e-01
3.84211123e-01 4.61948156e-01 -2.40564182e-01 -4.28883553e-01
2.67659038e-01 2.51244247e-01 6.70052052e-01 -5.60252547e-01
1.21846426e+00 1.19162118e+00 2.62192428e-01 -1.17269278e+00
-8.81246924e-01 -9.36382711e-01 -7.03414261e-01 -4.84968841e-01
6.12255394e-01 -1.00803840e+00 -4.92656201e-01 6.74750686e-01
-1.17226243e+00 1.27008960e-01 -1.25036770e-02 4.95222718e-01
-3.89178008e-01 1.00572968e+00 -5.65174401e-01 -9.22656059e-01
1.57082453e-01 -9.68800545e-01 1.03009319e+00 -1.99777141e-01
2.92681873e-01 -7.60751128e-01 5.94249927e-02 6.25048220e-01
5.28741539e-01 4.93640989e-01 5.48039854e-01 -9.21332091e-02
-9.12330627e-01 -1.13403514e-01 -2.17716292e-01 4.10330802e-01
3.08800071e-01 -1.96211562e-02 -8.87217700e-01 -6.33088171e-01
4.74751770e-01 7.09645450e-02 8.98437500e-01 4.21103507e-01
7.02883303e-01 -3.35354090e-01 -3.57290447e-01 6.89935148e-01
1.28268063e+00 2.24375594e-02 5.41094840e-01 2.77565271e-01
1.16139829e+00 6.25736535e-01 8.25788498e-01 6.38344824e-01
3.07395935e-01 7.83661187e-01 4.71115589e-01 -1.56298369e-01
-8.13721493e-02 4.22185481e-01 5.76070666e-01 9.64076698e-01
-4.42874253e-01 -6.31743204e-03 -7.50586033e-01 6.86719656e-01
-2.18625617e+00 -1.12371194e+00 -7.40853190e-01 2.26979351e+00
4.34176981e-01 -2.20119908e-01 1.49501562e-01 3.27330321e-01
8.15065026e-01 3.91451716e-01 -5.18802166e-01 4.04935986e-01
-3.38897437e-01 -5.85248828e-01 5.56182742e-01 2.29321644e-01
-1.23229957e+00 5.72505832e-01 6.75971746e+00 3.70396107e-01
-1.10633063e+00 1.88953936e-01 1.72651172e-01 2.29391679e-02
5.16111404e-02 2.71910839e-02 -5.85186601e-01 3.92115891e-01
4.56777543e-01 1.88540056e-01 3.83558840e-01 4.41161782e-01
5.12198091e-01 -5.45835570e-02 -9.94257808e-01 1.08986425e+00
4.04117018e-01 -1.03563201e+00 -9.99306329e-03 -2.87989937e-02
8.98237646e-01 -1.93981841e-01 1.98934227e-01 -2.13757038e-01
-1.37572631e-01 -5.97316444e-01 6.46224678e-01 6.21705294e-01
3.54648024e-01 -1.25038683e-01 5.22769153e-01 1.88262001e-01
-1.44796002e+00 -5.82216904e-02 -3.40422153e-01 -7.47723207e-02
3.18705738e-01 9.90145802e-01 -3.62464309e-01 5.65607250e-01
7.14454532e-01 1.02008522e+00 -3.94293040e-01 1.06306291e+00
8.47863480e-02 6.51352465e-01 -2.82443434e-01 6.53543770e-01
1.35245055e-01 -3.65668386e-01 1.04559624e+00 1.18915737e+00
4.26616073e-01 2.86161900e-01 3.90934438e-01 6.97153866e-01
3.36821020e-01 -1.69895634e-01 -4.78250802e-01 -9.55399155e-05
2.92215608e-02 1.31422317e+00 -8.22966337e-01 -3.50325257e-01
-6.15781367e-01 1.11793375e+00 -9.95752290e-02 8.65440071e-01
-7.35679746e-01 4.51085269e-02 7.66305029e-01 1.72211364e-01
7.18714774e-01 -6.71373010e-01 1.48793653e-01 -1.72901809e+00
3.97011489e-01 -1.10135102e+00 3.59254479e-01 -6.13400757e-01
-1.24279010e+00 2.08820581e-01 -7.88170099e-02 -1.39988720e+00
5.74847646e-02 -6.58208013e-01 -4.13646936e-01 4.32066292e-01
-1.69707298e+00 -1.19324112e+00 -4.59368199e-01 9.55855906e-01
5.94817698e-01 9.94889364e-02 3.09322804e-01 7.39033639e-01
-8.21501613e-01 1.08459303e-02 3.52152050e-01 5.79065606e-02
7.08284497e-01 -9.56889987e-01 -1.10941760e-01 1.54341972e+00
5.47538958e-02 6.04482830e-01 1.00444126e+00 -5.47751427e-01
-2.09432387e+00 -1.10281551e+00 4.77415115e-01 -5.45115769e-01
8.30698490e-01 -2.09448218e-01 -1.05566752e+00 6.76889956e-01
-2.46567801e-01 6.59859717e-01 5.42343855e-01 -2.02002674e-01
-3.88793260e-01 -1.36988983e-01 -9.02455986e-01 1.54940948e-01
1.05418873e+00 -3.70567262e-01 -5.18509805e-01 4.70868528e-01
1.83038637e-01 -3.35830420e-01 -6.66558623e-01 5.69883525e-01
4.72125649e-01 -8.33709002e-01 1.23773313e+00 -6.09822631e-01
7.41820112e-02 -1.03105485e+00 -4.22955006e-01 -1.01660478e+00
-6.89895511e-01 -8.46898019e-01 -5.25406837e-01 1.14335561e+00
-1.62194178e-01 -4.48532313e-01 5.64184070e-01 4.57364380e-01
-4.45167068e-03 -2.59466112e-01 -9.89150465e-01 -9.87842381e-01
-6.57095909e-01 -3.90759468e-01 -6.19137958e-02 1.24291050e+00
-4.52719778e-01 9.27774161e-02 -9.75144744e-01 8.19177270e-01
1.14272666e+00 2.03854963e-01 8.42317045e-01 -1.11089206e+00
-1.03581369e-01 -5.18733747e-02 -6.29694045e-01 -1.08888924e+00
-9.17144045e-02 -4.06023264e-01 3.00693780e-01 -1.32854617e+00
4.40328270e-01 -1.06757037e-01 -3.87587667e-01 2.16479003e-01
-3.58718336e-01 5.46345711e-01 2.12954849e-01 6.06335819e-01
-8.08208287e-01 4.18118685e-01 9.55467045e-01 -3.21029723e-01
4.50554080e-02 -1.68547273e-01 -4.32647437e-01 9.25416768e-01
1.17327966e-01 -5.74572146e-01 -1.52084753e-01 -5.39576054e-01
2.70833403e-01 -1.89073365e-02 5.08617043e-01 -8.91184628e-01
2.97694296e-01 -3.28829914e-01 2.45429784e-01 -6.70969605e-01
3.18922788e-01 -1.00572705e+00 2.33287603e-01 4.04149622e-01
5.11395894e-02 1.38325877e-02 2.37054285e-02 8.97671819e-01
-2.73640454e-01 -7.34350085e-02 7.42775142e-01 -1.00431684e-03
-8.45775127e-01 2.70587683e-01 -6.78953052e-01 2.03963965e-02
8.97813916e-01 -2.75744259e-01 -2.23940402e-01 -2.64955580e-01
-6.67408884e-01 1.83435962e-01 2.76855022e-01 4.10014004e-01
7.65346587e-01 -1.36489582e+00 -8.67680371e-01 -5.54926635e-04
6.78309202e-02 -2.57654399e-01 3.38693589e-01 1.48578477e+00
-3.22632581e-01 1.33454487e-01 -2.69810539e-02 -9.34641600e-01
-1.46107662e+00 6.86840892e-01 1.20917901e-01 -1.54847264e-01
-6.95162594e-01 6.41454220e-01 3.99609357e-01 2.02801615e-01
2.12216973e-01 -4.37907994e-01 -1.49268314e-01 2.10344195e-01
7.59926200e-01 8.84940207e-01 -1.41236298e-02 -1.08028376e+00
-6.57418191e-01 9.81049240e-01 7.61385188e-02 1.49618819e-01
1.30372500e+00 -5.32369316e-01 -2.92160749e-01 6.31016612e-01
1.08934855e+00 9.56671238e-02 -1.31798160e+00 -4.35282290e-01
2.16807798e-02 -9.91207182e-01 1.19516484e-01 -1.97088793e-01
-1.19660616e+00 6.33151054e-01 7.65622497e-01 3.28899652e-01
1.22277868e+00 -3.32463831e-01 7.60851681e-01 3.33934426e-01
4.03939724e-01 -8.51293266e-01 2.81160951e-01 5.15491843e-01
8.41966569e-01 -1.31592953e+00 3.48159939e-01 -7.62868702e-01
-3.00698876e-01 1.00662839e+00 2.03561425e-01 -2.94010695e-02
2.97450185e-01 2.15672612e-01 1.33380622e-01 -1.65405884e-01
-5.52927434e-01 -3.45087290e-01 5.74588716e-01 5.93989849e-01
2.39909410e-01 -1.89146817e-01 -1.97285771e-01 -2.55993549e-02
4.80034471e-01 -1.91565081e-01 6.14571691e-01 1.06535423e+00
-4.19282734e-01 -6.60770476e-01 -1.09220695e+00 1.84432298e-01
-5.88601172e-01 1.91183686e-01 -1.99840918e-01 3.53037089e-01
1.55896336e-01 1.09453809e+00 -2.36253694e-01 -1.31021261e-01
2.96780318e-01 -1.80539683e-01 3.96464854e-01 -3.46045911e-01
-5.76742813e-02 3.82342458e-01 -9.29608643e-02 -8.52568567e-01
-1.04640627e+00 -1.06011724e+00 -7.30031252e-01 1.43165752e-01
-3.69565934e-01 -1.15771592e-01 5.52083552e-01 8.53527665e-01
1.89481646e-01 4.80995774e-01 7.31260300e-01 -1.19723916e+00
-3.63641292e-01 -7.02759922e-01 -7.50669062e-01 7.58952200e-01
7.04868376e-01 -9.34519649e-01 -7.89116204e-01 5.86434066e-01] | [9.011443138122559, -0.8171136975288391] |
c6d9a883-5784-46f1-93df-a559f6cb7446 | controllable-video-generation-by-learning-the | 2303.05323 | null | https://arxiv.org/abs/2303.05323v2 | https://arxiv.org/pdf/2303.05323v2.pdf | Controllable Video Generation by Learning the Underlying Dynamical System with Neural ODE | Videos depict the change of complex dynamical systems over time in the form of discrete image sequences. Generating controllable videos by learning the dynamical system is an important yet underexplored topic in the computer vision community. This paper presents a novel framework, TiV-ODE, to generate highly controllable videos from a static image and a text caption. Specifically, our framework leverages the ability of Neural Ordinary Differential Equations~(Neural ODEs) to represent complex dynamical systems as a set of nonlinear ordinary differential equations. The resulting framework is capable of generating videos with both desired dynamics and content. Experiments demonstrate the ability of the proposed method in generating highly controllable and visually consistent videos, and its capability of modeling dynamical systems. Overall, this work is a significant step towards developing advanced controllable video generation models that can handle complex and dynamic scenes. | ['Li Nanbo', 'Zhibin Li', 'Mohammadreze Kasaei', 'Hamidreza Kasaei', 'Zonghai Yao', 'Zijian Guo', 'Arushi Goel', 'Yucheng Xu'] | 2023-03-09 | null | null | null | null | ['video-generation'] | ['computer-vision'] | [ 2.23578900e-01 1.51387632e-01 -1.36163644e-02 9.04251114e-02
-1.22635454e-01 -9.19735432e-01 9.27547157e-01 -7.29502261e-01
3.58402371e-01 7.88284838e-01 4.13208663e-01 -1.47114679e-01
1.29000649e-01 -4.85399485e-01 -1.01154792e+00 -7.29836345e-01
-7.93354139e-02 -3.34110595e-02 -1.56344905e-01 -2.12558821e-01
-4.53483239e-02 6.48402035e-01 -1.50592041e+00 6.78520575e-02
8.07843924e-01 7.45899081e-01 2.29792044e-01 1.18674862e+00
3.04069936e-01 1.31168199e+00 -2.77923942e-01 -3.35423760e-02
2.83551633e-01 -4.97319937e-01 -3.04513663e-01 4.00698960e-01
7.38544524e-01 -5.02701163e-01 -8.40615690e-01 8.28440011e-01
2.74480969e-01 1.51023075e-01 8.76893699e-01 -1.47960293e+00
-1.18188500e+00 3.68691921e-01 -4.29843292e-02 1.12886555e-01
5.77973604e-01 8.35879445e-01 7.92919457e-01 -6.89122856e-01
1.08972502e+00 1.43138897e+00 5.56850255e-01 9.07990813e-01
-1.40511119e+00 -5.65014303e-01 2.46140599e-01 -7.34842569e-02
-1.03942430e+00 -7.06832230e-01 8.39109361e-01 -7.93817759e-01
7.40581810e-01 1.26336753e-01 9.76935625e-01 1.41581917e+00
4.43653375e-01 9.20634925e-01 8.72165799e-01 -5.04553132e-02
1.95889190e-01 -6.89347163e-02 -2.98733771e-01 8.16963315e-01
1.52074099e-01 3.72669637e-01 -2.70081580e-01 1.31063536e-01
1.18773031e+00 -1.37628270e-02 -5.51741064e-01 -7.63759971e-01
-1.51861870e+00 6.66903973e-01 1.78834751e-01 -1.80866513e-02
-4.00214255e-01 7.01662779e-01 2.09732935e-01 4.29880738e-01
2.70957917e-01 8.63905191e-01 3.84144783e-02 -2.04116940e-01
-6.95751369e-01 5.89701295e-01 9.24985588e-01 1.30124867e+00
7.93407410e-02 8.82886589e-01 -2.97313750e-01 1.16743952e-01
-8.87247548e-03 8.90762448e-01 9.27936360e-02 -1.44006109e+00
1.52726576e-01 3.19296747e-01 4.52113539e-01 -1.26587737e+00
6.68155625e-02 -3.94126885e-02 -9.45205510e-01 2.68149555e-01
4.95964959e-02 -5.11937201e-01 -8.92596066e-01 2.00966263e+00
3.24618489e-01 4.70630080e-01 2.00925544e-01 8.03117156e-01
5.11300743e-01 1.14709902e+00 -8.83106738e-02 -3.96244973e-01
5.20201921e-01 -8.12272072e-01 -9.59598184e-01 4.45470303e-01
-9.58539546e-02 -4.70699579e-01 9.24015701e-01 1.36262238e-01
-1.57516813e+00 -7.09924817e-01 -9.13980544e-01 7.10044950e-02
7.99090508e-03 -4.09346297e-02 4.87570703e-01 4.20571640e-02
-1.44338715e+00 5.09634435e-01 -1.06720173e+00 -2.64647931e-01
1.52271822e-01 3.42466414e-01 -2.44483858e-01 1.48152813e-01
-1.11723268e+00 5.41243672e-01 2.21115574e-01 -2.62890682e-02
-1.45131421e+00 -9.77011621e-01 -1.30371618e+00 1.35886922e-01
3.17374200e-01 -1.07298076e+00 1.35159814e+00 -1.10730612e+00
-1.68653941e+00 2.62787461e-01 1.54903680e-02 -4.36456084e-01
7.48767316e-01 -1.70633718e-01 -2.17835128e-01 4.40639496e-01
-1.44630969e-01 1.06997573e+00 1.30714738e+00 -1.42835033e+00
-2.92469263e-01 3.86428893e-01 2.58156240e-01 2.27707699e-01
-4.70218569e-01 -2.22717151e-01 -3.27607870e-01 -9.89155471e-01
-6.24648690e-01 -1.35822630e+00 -2.96330512e-01 4.28352028e-01
-3.98409367e-01 1.04792103e-01 1.08160734e+00 -4.54881430e-01
1.15567732e+00 -1.82846737e+00 7.82821655e-01 -2.35249221e-01
3.89939904e-01 4.00157183e-01 -2.21259564e-01 5.76936662e-01
-2.06483424e-01 1.05295092e-01 1.12415150e-01 -9.71851423e-02
-2.39684116e-02 2.91513111e-02 -6.80447578e-01 1.08657405e-01
6.49157107e-01 1.18136168e+00 -1.05730712e+00 -3.17079186e-01
4.26520735e-01 7.82564223e-01 -7.36421585e-01 4.45620924e-01
-5.69281280e-01 8.34045291e-01 -5.65395296e-01 4.18754101e-01
2.65118480e-01 -2.04202935e-01 6.19575791e-02 -1.08986527e-01
-3.17062199e-01 -4.17908818e-01 -1.04615057e+00 1.20084286e+00
-2.27035984e-01 9.03373599e-01 5.76107726e-02 -8.13145518e-01
5.81121147e-01 5.78352213e-01 5.95735848e-01 -2.35122651e-01
5.54768331e-02 -2.64256835e-01 -1.07948966e-01 -9.83172178e-01
4.57428396e-01 -7.56804831e-03 -6.16150312e-02 3.90099466e-01
1.32470941e-02 -6.56984210e-01 4.60690528e-01 3.53273273e-01
1.09217286e+00 4.22913194e-01 4.41600792e-02 -1.54722825e-01
3.62868249e-01 2.10259140e-01 2.95563072e-01 7.41924942e-01
-1.59154832e-01 5.28270423e-01 6.24412179e-01 -4.25907403e-01
-1.68338215e+00 -1.26331139e+00 2.35766381e-01 3.32951933e-01
-1.54721543e-01 9.73871723e-03 -9.34826374e-01 1.21022360e-02
4.18009944e-02 4.36697155e-01 -6.53960705e-01 -3.45087439e-01
-8.88213158e-01 2.97448542e-02 3.61164838e-01 5.43235838e-01
2.51869261e-01 -1.26615930e+00 -4.45822269e-01 1.65890247e-01
-1.33353159e-01 -1.27066767e+00 -7.95525074e-01 -5.20109713e-01
-5.79586089e-01 -8.39172721e-01 -1.03164637e+00 -1.09653640e+00
8.43264878e-01 3.91098171e-01 9.51972246e-01 -2.80057788e-01
-3.74480397e-01 1.01468599e+00 -1.57429148e-02 -7.82695189e-02
-8.34021986e-01 -2.60233432e-01 3.99365693e-01 9.91417021e-02
-6.19046926e-01 -6.27509415e-01 -5.46181619e-01 -1.35171339e-02
-1.26255560e+00 5.00384629e-01 2.03025490e-01 8.59258115e-01
4.39646125e-01 3.40972207e-02 4.27901655e-01 -6.01448417e-01
9.02855098e-01 -6.32462919e-01 -6.81254327e-01 1.41486943e-01
-1.96701840e-01 1.25648558e-01 1.16170442e+00 -9.54730511e-01
-1.18960810e+00 4.51418608e-01 4.58794743e-01 -9.67617214e-01
-1.33485213e-01 3.78624529e-01 -2.90437322e-02 -2.56678835e-02
5.11350691e-01 4.61456895e-01 2.86389440e-01 2.53729850e-01
6.31535113e-01 3.09312314e-01 9.37844992e-01 -5.99530697e-01
1.21044481e+00 5.44726014e-01 6.73272386e-02 -7.56946445e-01
-4.25661504e-01 -8.19382817e-02 -5.40528297e-01 -6.11168027e-01
9.67941463e-01 -1.01582396e+00 -8.15694869e-01 7.73030937e-01
-1.01889098e+00 -5.92408419e-01 -2.04886943e-01 1.21269889e-01
-9.36634898e-01 2.03770757e-01 -8.23885202e-01 -6.81969166e-01
-2.19552040e-01 -1.12407362e+00 1.09793460e+00 3.03186357e-01
-2.41506621e-01 -1.22896111e+00 2.13798597e-01 -2.54541989e-02
4.10603493e-01 1.03929639e+00 7.45991111e-01 2.95581758e-01
-1.04311848e+00 -2.40672320e-01 1.13664113e-01 3.32099438e-01
1.58358395e-01 6.07803881e-01 -4.80369836e-01 -4.69845831e-01
-5.10431714e-02 -5.17959416e-01 5.39905429e-01 5.60039878e-01
9.00700808e-01 -5.80446422e-01 -1.74360380e-01 5.49461126e-01
1.42774010e+00 2.92453706e-01 5.62626183e-01 -2.24642798e-01
9.36106980e-01 2.81239986e-01 3.52225393e-01 4.45828378e-01
3.98281366e-01 5.66778600e-01 3.85230243e-01 -1.79316569e-02
-1.89005062e-01 -4.07295972e-01 7.99880624e-01 8.49985242e-01
-9.89094377e-02 -4.01998937e-01 -7.57624745e-01 7.31934011e-01
-1.94335711e+00 -1.54715598e+00 2.84314770e-02 1.70608294e+00
7.29225636e-01 -1.12151586e-01 9.73974466e-02 -1.71889424e-01
8.53313327e-01 1.25980139e-01 -9.88098860e-01 -3.96962613e-01
-1.61467548e-02 -1.33696301e-02 1.38772698e-02 3.25864524e-01
-1.09975576e+00 1.05948877e+00 7.03605747e+00 1.97419286e-01
-1.33854473e+00 -5.03641427e-01 4.70824033e-01 -2.04828918e-01
-2.86570489e-01 -2.86722094e-01 -6.39565170e-01 5.31529427e-01
9.62509692e-01 -6.81443572e-01 7.13476717e-01 7.56966949e-01
9.28634286e-01 3.40713680e-01 -1.26813269e+00 7.52641976e-01
2.54100442e-01 -1.71003282e+00 6.09901249e-01 2.71496866e-02
1.29283273e+00 -5.37931740e-01 6.07418180e-01 3.43260378e-01
6.44804776e-01 -1.01321018e+00 9.57065463e-01 9.65090096e-01
1.07150114e+00 -4.76774722e-01 -2.44625029e-03 1.89167574e-01
-1.26544678e+00 -2.19448745e-01 -1.29962891e-01 -1.63684517e-01
4.33558941e-01 3.83867845e-02 -6.65852249e-01 3.03341728e-02
4.45672423e-01 1.21281374e+00 -1.69688404e-01 9.01239514e-01
-1.58363651e-03 5.58236778e-01 6.16179109e-02 -8.80504847e-02
3.59806627e-01 -1.28370687e-01 8.27871084e-01 1.08882844e+00
4.56682712e-01 2.25845665e-01 2.97838897e-01 1.09180808e+00
-2.68887486e-02 -4.08778250e-01 -1.20518816e+00 -5.16560733e-01
2.04103008e-01 1.15917063e+00 -3.45868319e-01 -4.30293381e-01
-2.21118107e-01 8.25377584e-01 3.52344692e-01 5.53153872e-01
-1.18000758e+00 -2.94511169e-02 7.62861192e-01 -1.86585747e-02
4.79040086e-01 -5.90051353e-01 3.63360345e-02 -1.60104227e+00
8.10261816e-02 -1.06595540e+00 -1.06108971e-01 -1.23075879e+00
-9.38821673e-01 3.78968239e-01 1.54173300e-01 -1.64629126e+00
-6.49765253e-01 -6.13322437e-01 -6.82428420e-01 3.03390712e-01
-1.17762351e+00 -1.22992921e+00 -4.49174374e-01 8.14488828e-01
7.41002500e-01 -6.47421032e-02 6.81200087e-01 3.04931551e-02
-5.86823821e-01 2.50669390e-01 1.83184415e-01 -9.21214819e-02
3.40169877e-01 -1.43079412e+00 6.08330965e-01 1.00797534e+00
-2.95211047e-01 6.93530917e-01 1.01767993e+00 -5.91633916e-01
-1.82302630e+00 -1.38533139e+00 3.14732254e-01 -5.38654447e-01
8.18721294e-01 -4.50691283e-01 -5.62220991e-01 6.01460457e-01
4.13703829e-01 -6.85000271e-02 1.67844057e-01 -9.37513888e-01
-6.52898550e-02 1.90157175e-01 -9.07776415e-01 1.10022068e+00
1.14045310e+00 -5.39205015e-01 -2.87680447e-01 2.34528705e-01
1.11652064e+00 -6.30195141e-01 -8.73327851e-01 2.60847449e-01
6.61637664e-01 -5.57932615e-01 9.91507947e-01 -8.30567420e-01
1.05962181e+00 -2.69761533e-01 2.04592839e-01 -1.56217992e+00
-4.28515643e-01 -1.24778306e+00 -6.68942511e-01 1.10885763e+00
1.57121867e-01 -1.07596889e-01 4.81205165e-01 8.69544268e-01
-2.83400178e-01 -4.82791960e-01 -2.55587131e-01 -7.25780308e-01
1.88701078e-01 -7.50052780e-02 2.00601250e-01 1.02532113e+00
-1.11399002e-01 7.54486620e-02 -8.73768210e-01 1.10376634e-01
3.95007998e-01 -2.09140107e-02 1.05736434e+00 -8.29139054e-01
-2.69698948e-01 -1.98488414e-01 -4.81704444e-01 -1.08858645e+00
5.51699102e-01 -5.67411304e-01 9.75654423e-02 -1.36810815e+00
1.84005991e-01 5.60735799e-02 4.72234823e-02 8.54077637e-02
-8.90266448e-02 1.44637719e-01 5.18418550e-01 1.57101005e-01
-5.08497298e-01 6.94356024e-01 1.80032325e+00 -1.94113806e-01
-2.14680761e-01 -2.86494702e-01 -5.20475090e-01 5.77449441e-01
5.17549813e-01 -1.20683961e-01 -7.97712743e-01 -4.25410390e-01
5.45294918e-02 5.04665434e-01 5.00243127e-01 -1.09793413e+00
1.30890727e-01 -5.18704653e-01 2.97048420e-01 -8.80183280e-02
3.04973006e-01 -8.26095879e-01 4.83882070e-01 6.32216930e-01
-5.55820763e-01 4.31147426e-01 2.66300768e-01 7.81421542e-01
-1.62065431e-01 5.03460467e-01 8.41957629e-01 -3.12611520e-01
-6.04634702e-01 5.33405781e-01 -6.49324358e-01 5.62857874e-02
1.36594641e+00 -7.46453181e-02 -3.14371347e-01 -9.67791140e-01
-9.28624809e-01 2.93417037e-01 6.14831507e-01 7.17312634e-01
7.87101924e-01 -1.43122160e+00 -5.47311008e-01 1.02704830e-01
-2.09653080e-01 -2.17991292e-01 1.22122064e-01 4.84177232e-01
-7.52180815e-01 4.41974640e-01 -4.00890917e-01 -7.36080110e-01
-1.00110400e+00 8.09856415e-01 4.32210505e-01 -1.20951742e-01
-6.64357901e-01 3.48223627e-01 3.56808692e-01 -2.94737965e-01
1.90994233e-01 -5.37556231e-01 -1.00969337e-01 -3.66532683e-01
5.01551867e-01 1.04774781e-01 -8.07628274e-01 -6.82738602e-01
3.67033988e-01 4.09769297e-01 8.09864048e-03 -8.60777572e-02
1.40718114e+00 -2.36169532e-01 1.58658102e-01 3.25201005e-01
9.97390211e-01 -3.25241417e-01 -1.93860054e+00 1.26896963e-01
-5.22692144e-01 -1.97715804e-01 -2.63760537e-01 -4.63249207e-01
-9.91876543e-01 5.97641110e-01 2.82071263e-01 2.45834067e-01
8.82977545e-01 -3.87987822e-01 9.40452754e-01 5.57893872e-01
9.59512517e-02 -7.48017728e-01 6.34429216e-01 5.88334143e-01
1.09395242e+00 -9.67964530e-01 -3.26499343e-01 -3.41541201e-01
-8.41781318e-01 1.18457413e+00 7.00998247e-01 -6.19264185e-01
4.68856871e-01 4.83207434e-01 -8.68290439e-02 -1.17371395e-01
-1.22896338e+00 1.01736605e-01 2.98441559e-01 7.37036884e-01
2.44896144e-01 -2.63099581e-01 8.35199282e-02 -2.41555005e-01
-1.51562616e-01 2.14831278e-01 9.58686829e-01 8.13229740e-01
-6.91573471e-02 -5.06710708e-01 -1.65512234e-01 1.79248989e-01
-2.92235911e-01 5.86102530e-02 -4.40997094e-01 7.60249257e-01
-2.31554583e-01 8.02883506e-01 4.35333103e-02 -1.07159548e-01
1.62442178e-01 -1.65440857e-01 3.80635530e-01 -5.54925799e-01
-2.35573605e-01 -7.40037262e-02 -1.77342504e-01 -4.75969136e-01
-5.85335135e-01 -9.43387449e-01 -1.03384006e+00 -3.58609259e-01
9.16891322e-02 -3.36512595e-01 3.24222386e-01 6.43576860e-01
5.71213484e-01 5.93474090e-01 8.86472166e-01 -1.22469914e+00
-3.74629438e-01 -4.80141371e-01 -1.97998628e-01 6.77537501e-01
7.30080009e-01 -6.22711539e-01 -3.28257859e-01 9.06507552e-01] | [10.840027809143066, -0.6560595035552979] |
4ce5db9e-def4-436b-83fc-66df1265109d | revisiting-spatio-temporal-layouts-for | 2111.01936 | null | https://arxiv.org/abs/2111.01936v1 | https://arxiv.org/pdf/2111.01936v1.pdf | Revisiting spatio-temporal layouts for compositional action recognition | Recognizing human actions is fundamentally a spatio-temporal reasoning problem, and should be, at least to some extent, invariant to the appearance of the human and the objects involved. Motivated by this hypothesis, in this work, we take an object-centric approach to action recognition. Multiple works have studied this setting before, yet it remains unclear (i) how well a carefully crafted, spatio-temporal layout-based method can recognize human actions, and (ii) how, and when, to fuse the information from layout and appearance-based models. The main focus of this paper is compositional/few-shot action recognition, where we advocate the usage of multi-head attention (proven to be effective for spatial reasoning) over spatio-temporal layouts, i.e., configurations of object bounding boxes. We evaluate different schemes to inject video appearance information to the system, and benchmark our approach on background cluttered action recognition. On the Something-Else and Action Genome datasets, we demonstrate (i) how to extend multi-head attention for spatio-temporal layout-based action recognition, (ii) how to improve the performance of appearance-based models by fusion with layout-based models, (iii) that even on non-compositional background-cluttered video datasets, a fusion between layout- and appearance-based models improves the performance. | ['Tinne Tuytelaars', 'Marie-Francine Moens', 'Gorjan Radevski'] | 2021-11-02 | null | null | null | null | ['few-shot-action-recognition'] | ['computer-vision'] | [ 5.18254220e-01 -2.28159666e-01 1.33102983e-01 -7.63863549e-02
-2.25795522e-01 -5.34614682e-01 8.09906662e-01 -1.10816076e-01
-3.86876345e-01 3.23965698e-01 3.58365208e-01 -3.40331942e-01
-3.51232290e-01 -5.24083734e-01 -8.33560467e-01 -7.85682261e-01
1.77149568e-03 4.54734921e-01 8.14776838e-01 -2.88418770e-01
2.73850322e-01 9.91289616e-01 -1.97491384e+00 6.32695258e-01
3.98654044e-01 8.30727220e-01 -1.26672864e-01 1.06117845e+00
-8.27283561e-02 1.46213245e+00 -5.16867936e-01 -2.52733350e-01
2.81708926e-01 -7.24141419e-01 -9.86310184e-01 6.47874713e-01
8.63618851e-01 -3.62834901e-01 -4.56599087e-01 7.75290310e-01
4.72538685e-03 3.43041658e-01 6.83172405e-01 -1.37568569e+00
-4.77207631e-01 1.83153600e-01 -4.58903790e-01 6.68764651e-01
4.20058489e-01 4.78863895e-01 7.70579815e-01 -5.81968546e-01
7.18683720e-01 1.46497643e+00 4.48592782e-01 3.91952187e-01
-1.23571324e+00 -1.02384776e-01 7.18864918e-01 5.99040210e-01
-1.24020517e+00 -5.66597581e-01 7.49100506e-01 -6.07728839e-01
9.93754685e-01 3.00112247e-01 7.93866813e-01 1.14595020e+00
9.35806707e-02 1.09698462e+00 1.17128778e+00 -7.45918393e-01
3.58289152e-01 -2.04267308e-01 2.13980958e-01 6.86377943e-01
4.24565077e-02 -1.01470850e-01 -4.14736807e-01 7.32711777e-02
1.00508690e+00 1.43237248e-01 -1.49164557e-01 -7.83231258e-01
-1.23884475e+00 3.85223776e-01 2.77574092e-01 7.81995356e-01
-5.18868327e-01 2.81086683e-01 3.39738399e-01 5.84277585e-02
3.15792859e-01 1.75378084e-01 -3.55973929e-01 -2.50683546e-01
-9.81721401e-01 1.40586540e-01 5.65896213e-01 8.18527460e-01
4.77581412e-01 6.80167675e-02 -4.13369089e-01 5.26130617e-01
-3.79309244e-02 4.87193942e-01 2.19540313e-01 -9.23584938e-01
3.27353865e-01 7.57522583e-01 2.33125031e-01 -1.00284505e+00
-4.43172097e-01 7.59981498e-02 -6.27159774e-01 3.85131389e-01
9.01869416e-01 2.78405517e-01 -1.01145661e+00 1.60812855e+00
3.24255109e-01 6.19943477e-02 -1.59153298e-01 8.84863913e-01
3.20991069e-01 1.96592987e-01 1.66263044e-01 -9.81332138e-02
1.50817394e+00 -1.21754158e+00 -7.23275244e-01 -2.85205066e-01
6.64847493e-01 -4.66492176e-01 9.30824935e-01 3.78963798e-01
-1.17659056e+00 -7.86925435e-01 -8.62299502e-01 4.00574654e-02
-6.37745023e-01 3.11968684e-01 3.82089913e-01 7.94903815e-01
-1.16642857e+00 3.74070823e-01 -9.40913439e-01 -7.11083889e-01
3.80082428e-01 2.22060889e-01 -5.79523742e-01 -1.24709621e-01
-8.14919531e-01 9.38264668e-01 4.14178729e-01 4.64211851e-02
-7.08930254e-01 -1.51599824e-01 -7.09700882e-01 -6.55071363e-02
8.15629959e-01 -6.60140276e-01 1.05691814e+00 -1.53074408e+00
-1.27648807e+00 7.36312807e-01 -3.34990382e-01 -5.56727469e-01
6.88429892e-01 -7.21836686e-02 -3.83611113e-01 4.99162436e-01
-1.43868387e-01 5.50683975e-01 8.91721368e-01 -1.22963774e+00
-6.63478553e-01 -5.50706625e-01 5.66103578e-01 4.93803322e-02
-1.35196105e-01 2.38680005e-01 -5.93079090e-01 -5.32181680e-01
5.10222502e-02 -1.01027453e+00 -1.55048788e-01 2.96542943e-01
-1.00612015e-01 -8.89309216e-03 8.65464151e-01 -7.93852925e-01
1.14962101e+00 -2.27341747e+00 3.45529318e-01 2.01047882e-02
-1.37163177e-01 4.94402200e-01 -2.36085102e-01 4.21103299e-01
-2.37326235e-01 -1.55763552e-01 -1.63118228e-01 -2.48163730e-01
6.34476990e-02 4.67901945e-01 -1.21978775e-01 6.33653045e-01
3.71909201e-01 9.83311832e-01 -8.50399435e-01 -5.15608370e-01
6.82082057e-01 3.94459754e-01 -3.45614135e-01 4.04784596e-03
-2.91500211e-01 4.34772551e-01 -4.13806945e-01 6.75865412e-01
4.43808734e-01 -1.33011147e-01 2.08907992e-01 -2.22003326e-01
-1.15830757e-01 -1.65179417e-01 -1.39038408e+00 1.40286255e+00
-2.48125330e-01 6.53849781e-01 7.16761872e-02 -9.81167972e-01
5.40814281e-01 1.96516678e-01 6.07702255e-01 -1.03357112e+00
-4.78924215e-02 -8.25606957e-02 1.02982491e-01 -6.82871640e-01
2.94575304e-01 -7.83755630e-03 2.07500815e-01 4.02178735e-01
-2.15648003e-02 5.75119793e-01 4.69270885e-01 9.06235725e-02
1.45311451e+00 4.74459469e-01 5.14335513e-01 -5.21635264e-02
8.30983758e-01 3.31673287e-02 2.00685173e-01 8.64638031e-01
-3.11289936e-01 6.86604083e-01 5.57125449e-01 -7.55975246e-01
-1.07133126e+00 -8.44093680e-01 2.10545450e-01 1.40633464e+00
1.54313937e-01 -2.02220723e-01 -8.37124109e-01 -9.33421612e-01
-1.14273548e-01 6.75411463e-01 -9.46288288e-01 5.26909903e-02
-8.62200618e-01 -3.45436335e-01 5.00012994e-01 9.75954950e-01
3.85601491e-01 -1.20211971e+00 -1.16858792e+00 1.26131281e-01
-1.45760700e-02 -1.30449355e+00 -3.19809705e-01 1.55277818e-01
-7.29172409e-01 -1.36886621e+00 -6.31003857e-01 -1.33651376e-01
7.93745279e-01 4.51564103e-01 1.00722361e+00 2.15280473e-01
-3.69979948e-01 1.05090475e+00 -6.81361020e-01 -1.67411864e-01
-2.40174681e-01 -4.75832671e-01 -1.69667602e-01 5.27196527e-01
2.57595181e-01 -4.06202644e-01 -4.28038150e-01 5.54573655e-01
-1.19675732e+00 1.36833832e-01 7.41645992e-01 5.47619641e-01
2.70289689e-01 1.40530914e-01 -2.52366543e-01 -6.09332144e-01
1.00066466e-02 1.76731557e-01 -4.47845131e-01 6.95710123e-01
8.05623680e-02 6.83771595e-02 5.47782779e-01 -5.12598276e-01
-9.82977927e-01 4.08978343e-01 1.20070286e-01 -7.98936963e-01
-6.20075881e-01 -1.21877573e-01 -4.67918128e-01 -8.76787603e-02
5.15306175e-01 3.51860434e-01 -1.17762268e-01 -3.85090858e-01
6.24479830e-01 2.45998383e-01 3.68118852e-01 -5.44187665e-01
5.39557040e-01 9.33757603e-01 1.53535977e-01 -1.03890610e+00
-5.75981677e-01 -7.16104984e-01 -1.44010341e+00 -4.64911580e-01
1.31854534e+00 -4.75391269e-01 -4.71604526e-01 4.94229704e-01
-1.24889648e+00 -6.38959408e-01 -3.19265813e-01 1.34348944e-01
-8.59787703e-01 5.49681664e-01 -2.12276429e-01 -1.32214284e+00
3.15149039e-01 -1.04054832e+00 1.31140816e+00 -2.88281143e-01
-1.89235404e-01 -1.12694502e+00 -9.16698352e-02 4.60955501e-01
1.63531691e-01 2.77979672e-01 8.16179812e-01 -6.86524570e-01
-8.08157742e-01 -1.53704956e-01 -3.31047595e-01 2.77871370e-01
-1.44785503e-02 1.45973891e-01 -9.46364701e-01 -3.98371518e-02
-8.77944455e-02 8.51139501e-02 8.89800549e-01 3.17063421e-01
9.87102747e-01 -2.08223090e-01 -2.64651597e-01 1.70060828e-01
1.18551838e+00 3.55089128e-01 9.43312049e-01 3.50640655e-01
8.16090763e-01 6.79693401e-01 7.12369859e-01 3.31291199e-01
1.55023813e-01 1.23812580e+00 3.69352132e-01 -1.54521808e-01
-4.15617466e-01 3.06429025e-02 4.73206133e-01 1.28821284e-01
-4.55054522e-01 -1.25236705e-01 -9.82162833e-01 4.16199297e-01
-2.26392269e+00 -1.38129020e+00 -2.50382900e-01 2.04791713e+00
2.28615418e-01 2.25656889e-02 5.98421574e-01 2.35473633e-01
5.77481210e-01 2.34352529e-01 -3.04859996e-01 -1.90190881e-01
-2.45147705e-01 -3.05530392e-02 3.82805198e-01 2.13965982e-01
-1.45986784e+00 8.16873789e-01 5.89449835e+00 7.37398624e-01
-9.69921470e-01 2.15900585e-01 3.49191993e-01 6.36638030e-02
1.92099154e-01 4.08740938e-02 -5.72510839e-01 2.88015902e-01
5.98895669e-01 3.91630411e-01 2.86484689e-01 8.34932625e-01
1.35246783e-01 -3.10332745e-01 -1.29983246e+00 7.27319419e-01
4.95152086e-01 -1.04619050e+00 4.38106852e-03 1.78854406e-01
4.93886173e-01 -5.56693017e-01 -2.48474002e-01 2.99688250e-01
1.27801031e-01 -8.56531620e-01 1.09366894e+00 7.11432934e-01
1.40270934e-01 -3.28579575e-01 6.01014555e-01 3.60814482e-01
-1.43636990e+00 -3.98581266e-01 -1.15515729e-02 -1.41734034e-01
2.16339722e-01 7.91759491e-02 -2.98796386e-01 6.70648992e-01
5.97395182e-01 7.48624682e-01 -1.05447161e+00 9.90873218e-01
-1.47659436e-01 1.12383619e-01 -6.94661662e-02 1.12631828e-01
4.76064295e-01 -1.86045781e-01 3.85465562e-01 1.33560979e+00
-5.24339154e-02 2.65975893e-01 2.63702512e-01 7.29836822e-01
6.63632691e-01 -6.81606084e-02 -6.34347260e-01 -1.37864858e-01
-2.03037709e-01 9.53578293e-01 -1.18086040e+00 -4.18813974e-01
-5.58626294e-01 1.08227754e+00 2.53338665e-01 4.67085600e-01
-9.59053159e-01 2.83945799e-01 3.95957768e-01 3.67703497e-01
8.50763857e-01 -3.65755200e-01 3.91754545e-02 -1.00787961e+00
2.19048977e-01 -1.02452540e+00 5.50769985e-01 -1.03717411e+00
-1.01412439e+00 4.55928087e-01 3.27844620e-01 -1.26753139e+00
-8.77491608e-02 -9.96173501e-01 -4.09649372e-01 3.86298418e-01
-1.16636109e+00 -1.40664482e+00 -2.52352446e-01 6.36481285e-01
6.96920097e-01 1.01795420e-01 6.16084933e-01 2.22078800e-01
-4.94409949e-01 1.52280584e-01 -2.16254011e-01 3.31580192e-01
3.17240536e-01 -1.20773542e+00 2.27919221e-01 9.93696213e-01
7.76133120e-01 5.72880566e-01 6.67326093e-01 -4.85859036e-01
-1.55683625e+00 -1.02295434e+00 5.94947696e-01 -8.06161284e-01
6.34098709e-01 -3.15378964e-01 -9.73439634e-01 6.97573602e-01
5.90860285e-02 2.26812556e-01 2.41420016e-01 5.92221506e-02
-4.46821332e-01 -1.52012212e-02 -7.90850222e-01 7.22805738e-01
1.19949698e+00 -5.72109222e-01 -7.91268826e-01 3.78427237e-01
1.89631149e-01 -1.29834056e-01 -4.26466048e-01 4.00166065e-01
7.10049570e-01 -1.49858141e+00 1.23837423e+00 -8.72441828e-01
1.85480684e-01 -5.89208484e-01 -2.83353180e-01 -6.67208254e-01
-4.32117134e-01 -7.97018856e-02 -1.91097140e-01 9.04833376e-01
5.33945439e-03 -2.67232209e-01 5.59455276e-01 5.46319187e-01
-8.50985665e-03 -6.89396560e-01 -9.52309012e-01 -1.05432224e+00
-1.92838252e-01 -4.53283429e-01 9.37976539e-02 5.64652085e-01
-3.14966947e-01 8.75350460e-02 -4.02077883e-01 1.66135177e-01
1.06432483e-01 1.29867390e-01 1.06661439e+00 -9.53784943e-01
-5.10506570e-01 -7.29103148e-01 -8.96715999e-01 -9.31541443e-01
9.02565122e-02 -1.43681169e-01 1.82401985e-02 -1.65510273e+00
2.06069022e-01 7.40091652e-02 -3.23744118e-01 5.97447336e-01
-7.26850182e-02 1.81936547e-01 4.68414396e-01 -2.51361877e-02
-1.24026239e+00 2.84669340e-01 1.09637535e+00 -2.18926936e-01
6.84214532e-02 -1.00963287e-01 -1.03463590e-01 7.82509029e-01
3.10883909e-01 -9.06123295e-02 -3.86248410e-01 -1.63866177e-01
-9.67022628e-02 6.91096634e-02 8.40788305e-01 -1.29034650e+00
3.36021096e-01 -4.02837455e-01 4.50741947e-01 -5.15093267e-01
6.88827157e-01 -1.10305130e+00 1.70437366e-01 4.63808537e-01
-3.17230701e-01 -3.53169367e-02 2.37189293e-01 7.35407352e-01
-9.78749245e-02 -1.41417369e-01 6.67634070e-01 -4.22448099e-01
-1.07544398e+00 2.44504958e-02 -4.81827110e-01 -1.12907141e-01
1.14739227e+00 -7.26068497e-01 -1.61498234e-01 -2.53895313e-01
-8.78185034e-01 -2.99399436e-01 7.14870095e-01 4.49697077e-01
3.26228440e-01 -1.20904899e+00 -3.20281744e-01 1.59811631e-01
4.13308471e-01 -5.96850455e-01 5.94007015e-01 1.39166367e+00
-3.59646410e-01 5.79740405e-01 -2.97808915e-01 -7.19788074e-01
-1.70109570e+00 1.06078255e+00 3.90867323e-01 -1.18831001e-01
-7.33338535e-01 5.43062687e-01 4.21964407e-01 1.21185653e-01
3.93378437e-01 -4.55772072e-01 -1.22927696e-01 4.89780046e-02
7.14501321e-01 4.51665163e-01 2.01394130e-02 -1.01908386e+00
-5.70249677e-01 8.25276315e-01 2.27247581e-01 -1.16491303e-01
9.66049552e-01 4.84693376e-03 9.63336229e-03 6.01999700e-01
8.00804973e-01 -2.28722274e-01 -1.44243014e+00 -9.75181907e-02
1.72706723e-01 -6.84534788e-01 -1.57445922e-01 -6.57515585e-01
-8.54429722e-01 1.04703927e+00 4.73729193e-01 4.50064778e-01
1.22101724e+00 -5.40427752e-02 1.31878465e-01 3.06198746e-01
4.68259484e-01 -1.04616654e+00 4.81609076e-01 4.23299670e-01
8.69975567e-01 -1.02960598e+00 8.85192677e-02 -2.90950090e-01
-7.99194872e-01 1.24403286e+00 5.98865569e-01 7.35158101e-02
2.73604512e-01 1.68972641e-01 -9.27597657e-02 -2.69741029e-01
-6.64121032e-01 -7.94626772e-01 5.77112973e-01 6.10727966e-01
1.66532233e-01 -1.57602251e-01 1.42245784e-01 1.68987691e-01
5.31515718e-01 -1.36725843e-01 1.76515669e-01 1.19831645e+00
-4.06645358e-01 -1.07851410e+00 -5.80917954e-01 1.32497353e-02
-2.47828923e-02 2.86550194e-01 -8.66347253e-01 1.02197433e+00
4.30305719e-01 8.61550927e-01 1.35732889e-01 -2.50612665e-02
5.50749600e-01 4.07995671e-01 8.87396336e-01 -3.70199382e-01
-5.23806512e-01 5.85331582e-02 1.70208573e-01 -8.35531533e-01
-7.64572620e-01 -9.26232994e-01 -8.35902631e-01 1.64130896e-01
-1.36206493e-01 -3.72606903e-01 3.59912157e-01 1.24457538e+00
2.15682790e-01 6.59244061e-01 1.28012910e-01 -9.50911820e-01
-2.86278337e-01 -7.59319663e-01 -5.22301972e-01 7.98760772e-01
2.15985343e-01 -8.83568823e-01 -2.80658692e-01 2.79117465e-01] | [8.263900756835938, 0.36622872948646545] |
5c7479a2-ac2f-4ce2-9a61-aff0272e03f5 | learning-to-grasp-on-the-moon-from-3d-octree | 2208.00818 | null | https://arxiv.org/abs/2208.00818v1 | https://arxiv.org/pdf/2208.00818v1.pdf | Learning to Grasp on the Moon from 3D Octree Observations with Deep Reinforcement Learning | Extraterrestrial rovers with a general-purpose robotic arm have many potential applications in lunar and planetary exploration. Introducing autonomy into such systems is desirable for increasing the time that rovers can spend gathering scientific data and collecting samples. This work investigates the applicability of deep reinforcement learning for vision-based robotic grasping of objects on the Moon. A novel simulation environment with procedurally-generated datasets is created to train agents under challenging conditions in unstructured scenes with uneven terrain and harsh illumination. A model-free off-policy actor-critic algorithm is then employed for end-to-end learning of a policy that directly maps compact octree observations to continuous actions in Cartesian space. Experimental evaluation indicates that 3D data representations enable more effective learning of manipulation skills when compared to traditionally used image-based observations. Domain randomization improves the generalization of learned policies to novel scenes with previously unseen objects and different illumination conditions. To this end, we demonstrate zero-shot sim-to-real transfer by evaluating trained agents on a real robot in a Moon-analogue facility. | ['Carol Martinez', 'Miguel Olivares-Mendez', 'Simon Bøgh', 'Andrej Orsula'] | 2022-08-01 | null | null | null | null | ['robotic-grasping'] | ['robots'] | [-8.29278454e-02 2.16786444e-01 -1.37581248e-02 -3.66505414e-01
-2.67921388e-01 -5.79139829e-01 8.07141900e-01 -4.09884870e-01
-7.62786090e-01 1.07937849e+00 -2.86258668e-01 -2.68611252e-01
-2.83692449e-01 -6.27308846e-01 -9.86878753e-01 -7.54731238e-01
-6.47533596e-01 1.11301565e+00 7.88950101e-02 -6.05128467e-01
8.35941061e-02 9.03961122e-01 -1.72864056e+00 -1.17437080e-01
6.14194453e-01 4.55951631e-01 7.39283383e-01 7.40601718e-01
4.57909465e-01 6.30730748e-01 -4.08098310e-01 5.14700055e-01
8.19251060e-01 -1.29312754e-01 -5.23756504e-01 2.64590114e-01
1.32734567e-01 -4.09029424e-01 -5.83097994e-01 5.38737237e-01
3.91974658e-01 7.01873362e-01 7.34012246e-01 -9.72604334e-01
-1.94939256e-01 2.49176130e-01 -3.61557722e-01 4.98336740e-02
2.42172495e-01 7.40806162e-01 3.99574906e-01 -2.27325693e-01
7.45185971e-01 1.49796820e+00 1.94613174e-01 6.03150308e-01
-1.09741008e+00 -3.11879456e-01 -3.99349667e-02 2.95650214e-01
-6.72054589e-01 -1.17879584e-01 4.84304696e-01 -3.55399609e-01
1.03773820e+00 -1.54148981e-01 1.08169425e+00 1.38427675e+00
6.74320161e-01 5.62257111e-01 1.25025582e+00 -4.24629718e-01
6.53528988e-01 -8.27888772e-02 -6.23564780e-01 8.61493587e-01
4.19257641e-01 8.20727646e-01 -4.07670975e-01 -5.72551675e-02
1.10711324e+00 -2.04273134e-01 -2.27025330e-01 -1.20787883e+00
-1.43028021e+00 7.82023489e-01 7.52680063e-01 -9.85555798e-02
-6.15147293e-01 5.03248692e-01 2.40601718e-01 6.59855723e-01
-1.90425426e-01 1.13459468e+00 -6.49518490e-01 -1.25216603e-01
-2.74081200e-01 7.47214437e-01 1.13864017e+00 1.14131415e+00
5.48506916e-01 7.13591397e-01 1.95799917e-01 5.79595745e-01
2.37501338e-01 9.53172147e-01 4.89965081e-01 -1.23645842e+00
1.21700831e-01 1.81618467e-01 6.31219804e-01 -2.73508310e-01
-6.77676082e-01 -4.77124900e-01 -1.40643597e-01 1.20907688e+00
2.82657802e-01 -1.59724176e-01 -1.18235111e+00 1.26461792e+00
5.32950938e-01 -2.70082742e-01 6.07479870e-01 1.31199479e+00
2.83690244e-01 4.97585565e-01 -8.95189419e-02 2.24031314e-01
1.22860229e+00 -9.70530272e-01 -2.59161759e-02 -5.65201044e-01
3.99357766e-01 -1.70862630e-01 1.11204576e+00 4.91277337e-01
-6.12014174e-01 -3.91711205e-01 -1.06678581e+00 1.08349770e-01
-1.55368924e-01 -6.47420809e-02 8.01246822e-01 1.99174643e-01
-7.96144187e-01 7.10220098e-01 -1.17888582e+00 -7.12273896e-01
3.30281198e-01 4.43506598e-01 -3.87016416e-01 -4.07675132e-02
-9.03116107e-01 1.37502861e+00 6.09344602e-01 -1.67536303e-01
-1.88604391e+00 -2.13962466e-01 -9.65951204e-01 -1.67342305e-01
3.26841682e-01 -8.56343210e-01 1.65901983e+00 -9.22721088e-01
-2.11970782e+00 6.74195647e-01 4.53002572e-01 -7.24851370e-01
5.95358312e-01 -4.04870212e-01 1.98551267e-01 1.88840792e-01
2.60085855e-02 8.80751073e-01 1.14590847e+00 -1.53292489e+00
-6.14125967e-01 -3.04410845e-01 1.83271036e-01 7.68169165e-01
2.81703234e-01 -5.23863494e-01 1.48663133e-01 -2.85898119e-01
7.63084963e-02 -1.23738563e+00 -3.28366250e-01 1.48430452e-01
3.82406503e-01 -1.08822212e-01 9.27408814e-01 -3.13709289e-01
-4.08186406e-01 -1.60990334e+00 6.00466549e-01 3.38666588e-02
-4.19477880e-01 -5.31653827e-03 -1.20928243e-01 4.93886948e-01
1.79912478e-01 -6.83294415e-01 -1.66988999e-01 1.55501798e-01
1.75032206e-02 6.96570516e-01 -3.51447761e-01 6.23492420e-01
-2.16438621e-01 8.69940758e-01 -1.24830651e+00 -9.96461287e-02
1.91123605e-01 5.17441779e-02 -3.92055213e-01 3.13142359e-01
-7.98634946e-01 9.94118512e-01 -8.30132067e-01 7.67860949e-01
2.18382269e-01 3.10777932e-01 1.58518210e-01 6.37498438e-01
-3.82358849e-01 -1.33237213e-01 -5.63030601e-01 2.16117024e+00
-6.21390522e-01 6.52585864e-01 5.16193748e-01 -1.06727612e+00
1.13153088e+00 -9.35138017e-02 2.51350641e-01 -8.12829018e-01
1.63480967e-01 1.57509208e-01 1.88425034e-01 -9.06710684e-01
6.93772137e-01 -3.98589015e-01 -1.48013338e-01 1.40961990e-01
1.12479262e-01 -1.10510409e+00 -1.47333577e-01 -2.52590746e-01
1.13418722e+00 9.50348556e-01 1.35647669e-01 -6.55967891e-01
-4.34618555e-02 7.53742099e-01 3.64410758e-01 1.01423776e+00
-4.29698750e-02 7.75801763e-02 3.65697257e-02 -7.56129861e-01
-1.33537078e+00 -1.14162564e+00 -4.54849005e-02 1.12670851e+00
4.27255392e-01 4.54472125e-01 -1.13727793e-01 -4.85401541e-01
4.49270487e-01 1.00827050e+00 -6.50681615e-01 -1.40594959e-01
-7.00462639e-01 -1.59892842e-01 1.42333046e-01 2.76871592e-01
4.32607085e-01 -1.70237088e+00 -1.56617284e+00 3.69773239e-01
2.45389879e-01 -7.58566558e-01 4.94060934e-01 5.29613435e-01
-9.88341212e-01 -1.10617077e+00 -7.05300152e-01 -7.24749386e-01
6.51402473e-01 4.78516579e-01 8.24235439e-01 -4.56064820e-01
-6.28863454e-01 9.71687376e-01 -5.25941730e-01 -8.09106231e-01
-4.66477007e-01 -1.77704364e-01 5.80919087e-01 -7.26276517e-01
2.27937084e-02 -4.93009001e-01 -4.29836035e-01 4.46115434e-01
-5.60513020e-01 -6.80244353e-04 9.51204658e-01 1.02868342e+00
3.21601987e-01 -3.36344689e-01 3.67691845e-01 -4.26807366e-02
4.75513816e-01 -4.09245849e-01 -9.47130561e-01 4.97706905e-02
-6.33919910e-02 4.42364812e-01 6.21311843e-01 -6.67586386e-01
-1.14891589e+00 1.16842873e-01 6.75423741e-01 -4.47666287e-01
-1.63989291e-01 1.54042169e-01 2.82434642e-01 -3.03287208e-01
1.10051548e+00 2.44326815e-01 2.46192411e-01 -1.16669595e-01
4.21350598e-01 5.42732418e-01 5.79121292e-01 -1.17228949e+00
7.26462841e-01 7.20293283e-01 2.07366332e-01 -1.14962065e+00
-2.27582812e-01 -2.98355192e-01 -4.67782199e-01 -1.65925354e-01
7.34057844e-01 -1.05574536e+00 -7.48399615e-01 2.28515297e-01
-6.65859580e-01 -1.14677143e+00 -6.29500568e-01 9.49212968e-01
-1.35334408e+00 1.58528075e-01 -5.50818490e-03 -6.40668094e-01
-1.14014938e-01 -1.04733086e+00 9.06802952e-01 5.17000377e-01
1.58980787e-01 -5.74858725e-01 2.97883034e-01 1.36510789e-01
2.27919072e-01 3.34595442e-01 4.69879508e-01 -2.19193116e-01
-7.19410777e-01 2.31039435e-01 1.99613675e-01 -8.69707689e-02
-6.87822793e-03 -6.07698262e-01 -6.81818068e-01 -9.39307690e-01
1.14833079e-01 -1.03469455e+00 8.34121943e-01 2.30851814e-01
8.08908641e-01 8.30259249e-02 -4.38141733e-01 6.76312506e-01
1.17061794e+00 4.34275717e-01 4.33981717e-01 1.13300729e+00
2.27798045e-01 5.72145462e-01 1.19656587e+00 5.41132271e-01
-2.33724695e-02 5.59336245e-01 9.16746616e-01 2.82153487e-01
2.74883389e-01 -1.80433393e-01 4.67455029e-01 -2.66893655e-01
-3.09665114e-01 -1.65481314e-01 -9.68123138e-01 7.67963409e-01
-1.82203102e+00 -8.52323949e-01 3.34829360e-01 2.02532387e+00
3.19181383e-01 -1.16215654e-01 -3.10145944e-01 -5.91283977e-01
3.22975904e-01 -9.72365215e-02 -1.07888591e+00 -4.32640225e-01
1.95817515e-01 -3.45453024e-02 7.52468288e-01 3.71994823e-01
-9.13096189e-01 1.23170185e+00 5.06742573e+00 2.30304450e-01
-1.12727892e+00 -2.46308908e-01 -2.27513611e-01 -1.62921965e-01
-5.58016188e-02 1.74274370e-01 -5.10328412e-01 2.69837938e-02
6.43249512e-01 6.46989867e-02 7.85678148e-01 1.35221553e+00
4.20941979e-01 -5.49046695e-01 -1.19342124e+00 7.52634346e-01
-6.61721379e-02 -8.42561305e-01 -1.65123418e-01 1.63286418e-01
7.40974128e-01 4.00764823e-01 -1.39446199e-01 7.21408844e-01
7.93729663e-01 -8.52074087e-01 8.63918364e-01 7.23357856e-01
6.36351883e-01 -5.74599802e-01 3.28142583e-01 6.39608681e-01
-5.45730233e-01 -4.41513598e-01 -7.70866930e-01 -2.74891794e-01
-1.86090041e-02 -2.46087730e-01 -1.53770018e+00 4.84836787e-01
7.73021400e-01 3.58966708e-01 7.72919804e-02 1.06460643e+00
-4.29497004e-01 1.21638037e-01 -5.93669951e-01 -5.64660728e-01
5.86597443e-01 -3.99497300e-01 9.88000810e-01 6.94739163e-01
3.65890443e-01 2.32808769e-01 3.10022712e-01 6.14456058e-01
1.86639294e-01 -4.15517569e-01 -1.04946852e+00 2.75036007e-01
1.20552585e-01 1.03153372e+00 -6.91785038e-01 -1.03382573e-01
-1.62103213e-02 7.52436876e-01 5.97436428e-01 4.82863933e-01
-7.50887752e-01 -3.25250119e-01 5.78198314e-01 7.63389319e-02
5.55938125e-01 -7.35492289e-01 1.53079376e-01 -1.08258688e+00
-2.63272434e-01 -7.77163684e-01 -6.62064105e-02 -1.05298233e+00
-7.26972222e-01 2.27527291e-01 3.28669846e-01 -1.42934906e+00
-4.16241318e-01 -7.56637216e-01 -4.04021055e-01 5.16933262e-01
-1.59112430e+00 -1.17460299e+00 -7.08388388e-01 3.44478548e-01
8.94184649e-01 -8.25683296e-01 7.64525890e-01 -8.74548018e-01
2.89859921e-01 -1.30629450e-01 6.38147593e-01 -3.93900931e-01
7.39772439e-01 -1.20480931e+00 1.51832670e-01 3.34854662e-01
-9.72311944e-02 1.81510448e-01 9.83198285e-01 -7.13360727e-01
-2.00738168e+00 -8.73224795e-01 -5.16167164e-01 -2.94101357e-01
5.93198538e-01 -2.77493238e-01 -6.77103102e-01 6.97770536e-01
1.44120604e-01 -3.29004787e-02 -1.63545802e-01 -1.35714874e-01
1.35774001e-01 -9.40336362e-02 -1.21750546e+00 6.00331664e-01
8.66770089e-01 8.27893093e-02 -1.05528152e+00 4.83881593e-01
3.01966220e-01 -7.03736782e-01 -5.19325972e-01 4.14293110e-01
6.81367576e-01 -6.01816952e-01 8.42440665e-01 -8.77853453e-01
2.42664933e-01 -3.65279913e-01 5.81698380e-02 -1.74502420e+00
-2.74919659e-01 -7.53224790e-01 -1.63964182e-03 -2.95718964e-02
-2.47531477e-02 -6.38891876e-01 9.11663473e-01 -2.38509215e-02
-4.27405238e-01 -3.73270869e-01 -9.55836952e-01 -1.07261348e+00
2.12043837e-01 2.13982716e-01 4.87129986e-02 5.63294232e-01
-2.40822062e-02 3.95463519e-02 -1.51139811e-01 4.46286708e-01
8.34117949e-01 3.04712921e-01 1.25934923e+00 -1.25192797e+00
-5.23311138e-01 1.30705282e-01 -4.59673852e-01 -1.03255427e+00
5.55410981e-01 -7.08547711e-01 5.11764944e-01 -1.65044963e+00
-2.15912655e-01 -6.93422079e-01 3.26635927e-01 5.44779897e-01
4.72746342e-01 -3.60651761e-01 1.42365828e-01 4.64151740e-01
-4.26273137e-01 1.03867733e+00 1.75953627e+00 -2.36066252e-01
-4.19275701e-01 6.45429362e-03 -3.61051895e-02 6.99034929e-01
1.04434633e+00 -4.11399722e-01 -5.27771115e-01 -6.70632243e-01
-2.21097632e-03 3.29522878e-01 6.19413912e-01 -1.30203235e+00
8.64905789e-02 -4.52662677e-01 5.79694867e-01 -2.75085658e-01
6.66124761e-01 -9.19804931e-01 -2.52853066e-01 9.43798423e-01
-8.11712444e-02 -4.01585668e-01 4.28081930e-01 1.12643957e+00
2.38295466e-01 -3.47402334e-01 8.39596093e-01 -7.73980916e-01
-1.15132046e+00 -1.56615198e-01 -5.20908892e-01 -1.46829158e-01
1.47102535e+00 -2.15795562e-01 -2.54132390e-01 -3.85866493e-01
-8.60708833e-01 6.15540445e-01 6.37767255e-01 4.38499629e-01
7.20192015e-01 -6.81640029e-01 -8.15762341e-01 2.59558916e-01
7.81583712e-02 3.44108820e-01 -3.42760049e-02 2.32905716e-01
-1.13870454e+00 2.95766264e-01 -8.33624542e-01 -7.52206087e-01
-1.09456134e+00 3.09339762e-01 5.92164218e-01 1.62954926e-02
-1.03282273e+00 6.67216361e-01 2.27161422e-01 -6.86269820e-01
4.99537773e-02 -5.34500539e-01 2.88789030e-02 -5.53033173e-01
6.84215203e-02 1.55588463e-01 -1.91632524e-01 -4.09529917e-03
8.09279457e-02 2.00519979e-01 -9.85861570e-02 -5.13871670e-01
1.64968681e+00 2.82391638e-01 2.76456118e-01 2.75194079e-01
3.20150584e-01 -4.72504467e-01 -2.06290030e+00 -5.34730144e-02
-2.76824385e-01 -4.43227917e-01 -2.40779798e-02 -6.89941406e-01
-2.04824299e-01 6.96046233e-01 5.34207702e-01 -2.23083526e-01
4.95387733e-01 3.01721971e-02 8.56407657e-02 1.57512152e+00
1.15212202e+00 -1.20327890e+00 3.94748747e-01 9.36682940e-01
1.48636091e+00 -1.27839482e+00 3.35980326e-01 5.31643927e-01
-9.71254170e-01 1.30703151e+00 7.51909137e-01 -4.87565815e-01
2.88112294e-02 -6.13078810e-02 3.95001993e-02 -1.60767362e-01
-5.07409751e-01 -1.14664115e-01 -2.03440160e-01 1.03275728e+00
-5.41727245e-01 6.13782816e-02 6.85682595e-02 -2.52125293e-01
-4.79609191e-01 -2.06434652e-01 8.36872697e-01 1.49882209e+00
-1.06309116e+00 -7.28102505e-01 -7.15190709e-01 1.42209530e-01
2.40172327e-01 5.46268940e-01 -5.81897311e-02 1.27220654e+00
-1.38652354e-01 4.61399704e-01 1.21540360e-01 2.92904139e-01
2.33526006e-01 -8.16654786e-02 1.06756282e+00 -6.04711175e-01
-2.25258410e-01 -2.41113931e-01 1.45919576e-01 -4.47275847e-01
-3.73965591e-01 -7.83109128e-01 -1.53935826e+00 3.38003159e-01
1.15108952e-01 3.33389670e-01 1.21501791e+00 7.42888391e-01
2.04412386e-01 6.22318923e-01 4.96376157e-01 -1.59652781e+00
-1.12447715e+00 -1.18302774e+00 -5.47473073e-01 1.12899691e-01
4.08504397e-01 -1.10088110e+00 -1.98565304e-01 -7.42059620e-03] | [4.551801681518555, 0.9600427746772766] |
cfe2c0e5-feb0-47ae-a2c1-2519c6b75a84 | temporal-complementarity-guided-reinforcement | null | null | http://openaccess.thecvf.com//content/CVPR2022/html/Wu_Temporal_Complementarity-Guided_Reinforcement_Learning_for_Image-to-Video_Person_Re-Identification_CVPR_2022_paper.html | http://openaccess.thecvf.com//content/CVPR2022/papers/Wu_Temporal_Complementarity-Guided_Reinforcement_Learning_for_Image-to-Video_Person_Re-Identification_CVPR_2022_paper.pdf | Temporal Complementarity-Guided Reinforcement Learning for Image-to-Video Person Re-Identification | Image-to-video person re-identification aims to retrieve the same pedestrian as the image-based query from a video-based gallery set. Existing methods treat it as a cross-modality retrieval task and learn the common latent embeddings from image and video modalities, which are both less effective and efficient due to large modality gap and redundant feature learning by utilizing all video frames. In this work, we first regard this task as point-to-set matching problem identical to human decision process, and propose a novel Temporal Complementarity-Guided Reinforcement Learning (TCRL) approach for image-to-video person re-identification. TCRL employs deep reinforcement learning to make sequential judgments on dynamically selecting suitable amount of frames from gallery videos, and accumulate adequate temporal complementary information among these frames by the guidance of the query image, towards balancing efficiency and accuracy. Specifically, TCRL formulates point-to-set matching procedure as Markov decision process, where a sequential judgement agent measures the uncertainty between the query image and all historical frames at each time step, and verifies that sufficient complementary clues are accumulated for judgment (same or different) or one more frames are requested to assist judgment. Moreover, TCRL maintains a sequential feature extraction module with a complementary residual detector to dynamically suppress redundant salient regions and thoroughly mine diverse complementary clues among these selected frames for enhancing frame-level representation. Extensive experiments demonstrate the superiority of our method. | ['Zheng-Jun Zha', 'Qibin Sun', 'Kecheng Zheng', 'Jiawei Liu', 'Wei Wu'] | 2022-01-01 | null | null | null | cvpr-2022-1 | ['image-to-video-person-re-identification', 'set-matching'] | ['computer-vision', 'computer-vision'] | [ 2.25989625e-01 -5.39482415e-01 -3.72271121e-01 -2.07358301e-01
-1.02901924e+00 -4.90172803e-01 5.15751302e-01 -6.19835295e-02
-7.22936332e-01 4.08734769e-01 2.99470603e-01 3.24061900e-01
-1.47243276e-01 -5.74078560e-01 -5.06952405e-01 -7.98945010e-01
2.17862710e-01 1.57535359e-01 4.22389686e-01 -3.83897126e-02
2.66910166e-01 1.95188016e-01 -1.79561758e+00 3.82382751e-01
4.75240231e-01 1.02182114e+00 2.09778711e-01 5.44260740e-01
2.69592881e-01 8.89529824e-01 -2.93411374e-01 -5.15789270e-01
3.60645175e-01 -4.33162987e-01 -7.27130294e-01 5.74886560e-01
4.55208570e-01 -7.11223185e-01 -7.89906144e-01 1.24684620e+00
7.90741682e-01 6.09564364e-01 4.98976856e-01 -1.46687090e+00
-7.40946352e-01 2.13035475e-02 -6.21068299e-01 6.93100512e-01
1.02593613e+00 5.90533018e-01 5.31665802e-01 -1.12973380e+00
4.71239448e-01 1.30110347e+00 4.18920487e-01 6.39419258e-01
-8.26550186e-01 -5.65912783e-01 3.96309108e-01 7.24881887e-01
-1.45197809e+00 -8.33249569e-01 9.42646980e-01 -3.69036347e-01
6.13594294e-01 1.56826049e-01 9.65113878e-01 1.01835227e+00
-1.12366118e-01 1.01441419e+00 9.01233852e-01 -4.72166628e-01
2.78594848e-02 1.81265920e-02 -2.14286596e-02 8.34257185e-01
-3.43310498e-02 4.38871026e-01 -8.22907209e-01 -5.53182475e-02
7.96531320e-01 4.63382423e-01 -2.97809929e-01 -2.07826540e-01
-1.51537931e+00 6.25235558e-01 2.07394227e-01 2.47902513e-01
-5.01343668e-01 -3.52767226e-03 4.97319877e-01 4.74989265e-01
-2.14229408e-03 -2.48625353e-01 7.03510940e-02 7.13006407e-02
-7.89381742e-01 2.35424876e-01 1.63904488e-01 8.71910393e-01
8.25227499e-01 -8.38466957e-02 -5.83122432e-01 6.50524497e-01
3.45583856e-01 5.83497345e-01 5.72879791e-01 -1.16777241e+00
5.15713394e-01 5.86177111e-01 3.70195597e-01 -1.41669154e+00
1.02910273e-01 -7.82620758e-02 -8.99137974e-01 1.22244125e-02
3.11823964e-01 -1.53781539e-02 -6.45065606e-01 1.50035644e+00
4.99429375e-01 4.44206983e-01 1.43162072e-01 1.41500902e+00
7.19052911e-01 6.68443620e-01 2.47479886e-01 -4.77688730e-01
1.56655657e+00 -8.52554739e-01 -4.42912340e-01 -1.96852922e-01
2.56687462e-01 -7.29867518e-01 7.07741261e-01 4.86475900e-02
-1.18480325e+00 -1.12994909e+00 -8.09448063e-01 1.18655793e-01
-1.47933394e-01 3.00764829e-01 1.70311242e-01 4.78600085e-01
-9.83317077e-01 2.20616698e-01 -3.08973610e-01 -2.91479915e-01
1.99286461e-01 2.52346218e-01 -5.96096516e-01 -5.29593706e-01
-1.45917213e+00 5.96345127e-01 4.82232809e-01 2.74829715e-01
-9.71258521e-01 -2.85412252e-01 -9.16930616e-01 -2.01343566e-01
6.22697532e-01 -9.20416534e-01 9.83283937e-01 -1.16860318e+00
-1.28417051e+00 1.17034113e+00 -3.51708472e-01 -3.89259934e-01
6.38665736e-01 -2.72560678e-02 -7.96938002e-01 6.13077819e-01
5.48861325e-01 7.72588193e-01 1.45394528e+00 -1.13515794e+00
-1.16769564e+00 -4.33026373e-01 1.48357838e-01 7.38445938e-01
-1.87122226e-01 3.24030161e-01 -1.10351264e+00 -6.65885985e-01
1.08042412e-01 -8.32595706e-01 2.44725551e-02 1.06295366e-02
6.57596961e-02 -5.83076537e-01 6.74600840e-01 -8.96804690e-01
1.14900005e+00 -1.97925198e+00 1.30372256e-01 1.09497450e-01
9.97185707e-02 1.85937539e-01 -3.01047802e-01 4.24223840e-02
4.29539792e-02 -3.73237044e-01 1.45232499e-01 -1.37740314e-01
-2.32669368e-01 -1.77482853e-03 -1.60193827e-03 6.24573946e-01
1.14054754e-01 9.77955282e-01 -1.14665723e+00 -9.98469114e-01
5.58897734e-01 2.93008894e-01 -2.15995222e-01 2.70876080e-01
2.40230069e-01 4.14963961e-01 -6.04943812e-01 9.92136180e-01
6.09834254e-01 -9.49959606e-02 -1.11861967e-01 -6.17966294e-01
4.91012521e-02 -5.08807242e-01 -1.36626005e+00 1.73341453e+00
9.00179148e-02 3.92861605e-01 -1.40924513e-01 -1.18452227e+00
6.82189643e-01 2.37121388e-01 7.97120452e-01 -1.13216817e+00
4.35401388e-02 -1.29446581e-01 -4.38290328e-01 -8.21470141e-01
4.92878586e-01 2.36751527e-01 -2.22779423e-01 3.75337541e-01
-3.86889465e-02 4.12171066e-01 2.85246193e-01 2.12525785e-01
6.99952960e-01 1.84028745e-01 9.77326855e-02 1.36791021e-01
1.12871647e+00 -7.92710707e-02 8.01400483e-01 7.69387007e-01
-8.20250988e-01 4.60916281e-01 -1.30702376e-01 -6.15507483e-01
-1.02074552e+00 -9.33929205e-01 3.77149045e-01 1.30950713e+00
8.72918487e-01 -1.10867791e-01 -4.73705798e-01 -6.16417825e-01
-8.88779685e-02 1.32347703e-01 -6.08698905e-01 -3.30910176e-01
-6.73050284e-01 -4.04685795e-01 3.47294003e-01 4.17890251e-01
1.04965365e+00 -1.01832426e+00 -5.92911124e-01 2.35756170e-02
-6.24536276e-01 -9.47723269e-01 -1.13500595e+00 -5.80458343e-01
-3.02085131e-01 -1.37042975e+00 -1.03938425e+00 -1.28459096e+00
5.77294469e-01 9.80521798e-01 8.27904820e-01 1.91571087e-01
-2.47145414e-01 8.02926362e-01 -4.73016560e-01 3.92528951e-01
-1.34476379e-01 -5.35415649e-01 3.87516379e-01 6.37883604e-01
5.48342466e-01 -2.16783602e-02 -1.02618170e+00 6.98809087e-01
-7.65852213e-01 -4.49934117e-02 4.88178223e-01 1.00582016e+00
7.75438726e-01 4.27809358e-01 3.50332379e-01 1.08224705e-01
6.01752341e-01 -1.61190823e-01 -2.38295883e-01 6.10921323e-01
-2.74333119e-01 -2.30787426e-01 2.14879841e-01 -6.14873767e-01
-1.03772771e+00 6.32121861e-02 2.29637474e-01 -9.02765393e-01
-1.79197323e-02 1.30854025e-01 -2.81529844e-01 1.68919023e-02
1.59186110e-01 7.86920190e-01 1.25484094e-01 5.55583388e-02
4.00601625e-01 6.16858900e-01 9.61457253e-01 -5.06554544e-01
6.83179736e-01 5.25281847e-01 -4.08400297e-01 -3.11690122e-01
-5.72513580e-01 -8.82508516e-01 -7.48466849e-01 -8.44008625e-01
1.12675118e+00 -1.26953948e+00 -1.09063613e+00 5.55007398e-01
-9.22201514e-01 1.30912021e-01 -2.91347921e-01 5.51819086e-01
-5.39121926e-01 7.29586780e-01 -4.85619992e-01 -9.01009798e-01
-2.74364293e-01 -1.09247351e+00 1.18807340e+00 6.38574183e-01
2.60644197e-01 -5.42864203e-01 -2.19764128e-01 6.49411023e-01
-3.52196507e-02 6.14086464e-02 2.92669475e-01 -1.65803134e-01
-6.31959736e-01 -3.39149415e-01 -4.23391938e-01 1.51744321e-01
7.12272897e-02 -3.19374353e-01 -6.39417768e-01 -5.77943742e-01
-3.60508598e-02 -2.02523634e-01 8.97486627e-01 3.36805999e-01
8.17098737e-01 -2.45644316e-01 -3.47223639e-01 3.25006515e-01
1.21402216e+00 3.13689440e-01 5.46195626e-01 5.00088334e-01
5.33824503e-01 5.91282904e-01 9.50995505e-01 3.29681784e-01
5.08382022e-01 7.20041215e-01 1.09801359e-01 6.95405826e-02
-1.79831773e-01 -3.87632549e-01 6.05028093e-01 5.73546171e-01
-6.80806488e-02 -1.06372148e-01 -4.06862587e-01 6.06137574e-01
-2.17330384e+00 -1.58983386e+00 3.90632898e-01 2.40314198e+00
4.57279712e-01 -3.45652811e-02 5.18717527e-01 2.75487453e-01
1.28527308e+00 1.62795722e-01 -8.61895144e-01 4.56079364e-01
-4.98717129e-01 -6.37346029e-01 3.21457505e-01 2.95158237e-01
-1.24102485e+00 8.33011031e-01 5.28442478e+00 1.06999743e+00
-6.53352976e-01 2.44544879e-01 7.83871710e-01 -7.09478259e-02
4.88528274e-02 6.72832206e-02 -6.43400848e-01 7.23034441e-01
2.50548363e-01 -1.38197452e-01 3.38780642e-01 5.41496098e-01
3.27171892e-01 -3.23654652e-01 -1.09572244e+00 1.71816862e+00
4.50419009e-01 -1.30290866e+00 2.46121988e-01 -2.29609773e-01
5.15954256e-01 -5.13366997e-01 1.64436355e-01 3.33221853e-01
2.45232880e-02 -6.85752392e-01 7.31927991e-01 1.05145311e+00
7.87815690e-01 -8.00983310e-01 6.34656012e-01 1.77626133e-01
-1.61543071e+00 -4.51786190e-01 -3.69626760e-01 1.42193332e-01
2.40039900e-01 3.57932299e-02 -2.23731264e-01 8.02514017e-01
9.73114431e-01 1.05911386e+00 -7.46280432e-01 8.59714925e-01
2.09276378e-01 9.86746773e-02 -7.90145695e-02 2.54424691e-01
5.14561385e-02 -2.89405823e-01 6.98367476e-01 9.33521688e-01
2.14294657e-01 2.05883026e-01 6.75734818e-01 3.09211761e-01
1.85122713e-01 -4.65454124e-02 -3.19615513e-01 3.98686111e-01
5.93095064e-01 8.95311058e-01 -5.21488786e-01 -5.91363370e-01
-4.87265229e-01 1.56388795e+00 3.37186549e-03 4.42548454e-01
-7.63178051e-01 4.98940749e-03 3.22324842e-01 2.07195096e-02
1.60510302e-01 6.30588233e-02 4.65672910e-01 -1.35901201e+00
2.15840638e-01 -8.95526886e-01 1.00503480e+00 -1.17435002e+00
-1.54212940e+00 4.45579380e-01 -6.12039715e-02 -1.78545260e+00
-2.43716836e-01 -1.33894101e-01 -5.37602901e-01 5.16448140e-01
-1.48477638e+00 -1.35739517e+00 -4.95487839e-01 1.39719057e+00
8.62699032e-01 -5.75185895e-01 3.03983241e-01 4.84745383e-01
-6.52121544e-01 6.95892334e-01 -5.13151251e-02 4.89135355e-01
7.97167242e-01 -7.69905806e-01 -1.01785712e-01 1.07412720e+00
-1.46935672e-01 3.48977119e-01 3.68611753e-01 -7.11518109e-01
-1.53550422e+00 -1.10551131e+00 6.03957653e-01 -3.31189960e-01
3.22210550e-01 2.59861439e-01 -6.26445055e-01 2.49017730e-01
1.22875616e-01 5.76059930e-02 4.06138659e-01 -5.22692919e-01
-1.58667326e-01 -2.62234896e-01 -9.64444518e-01 5.79225361e-01
1.12142038e+00 -7.82244503e-01 -8.82820249e-01 2.76515216e-01
6.10480666e-01 -2.15193897e-01 -8.11812699e-01 3.12347293e-01
6.91487193e-01 -9.45351243e-01 1.38042879e+00 -3.56160372e-01
-1.39940798e-01 -7.06781685e-01 -3.80271584e-01 -7.61638761e-01
-5.68010807e-01 -6.05562270e-01 -3.74765769e-02 1.31888509e+00
-4.83372480e-01 -2.96867698e-01 7.44415164e-01 6.34438932e-01
3.19158256e-01 -3.92351389e-01 -1.14295101e+00 -5.47829092e-01
-5.24341762e-01 -1.79597929e-01 5.36829650e-01 7.47066557e-01
-2.03127056e-01 1.52228922e-01 -7.91890860e-01 2.30032042e-01
9.21088278e-01 3.12527716e-01 7.65354335e-01 -9.97663379e-01
-1.66437060e-01 -3.65654588e-01 -5.98176956e-01 -1.14844537e+00
4.74135540e-02 -5.82044423e-01 -8.80307108e-02 -1.21711218e+00
4.90936399e-01 -1.46223456e-01 -5.97080886e-01 2.18108937e-01
-4.24914896e-01 4.30492312e-01 4.01481181e-01 8.03752959e-01
-1.18542361e+00 6.59111321e-01 1.15401733e+00 -5.54755807e-01
-1.95768863e-01 1.19330898e-01 -4.67401505e-01 5.87784648e-01
4.32759643e-01 -1.64988264e-01 -2.95429796e-01 -3.67970020e-01
-7.35330433e-02 5.59335291e-01 8.73192251e-01 -1.10855961e+00
6.59608066e-01 -1.51930884e-01 8.81220639e-01 -8.45790803e-01
4.71603513e-01 -6.63190961e-01 6.57674205e-03 4.72337216e-01
-3.76546651e-01 3.44362020e-01 -1.92635536e-01 1.12979627e+00
-3.52874637e-01 -5.97832240e-02 5.78491151e-01 -1.97462425e-01
-1.51000690e+00 7.18803525e-01 -4.77662653e-01 -1.99419811e-01
1.23276162e+00 -7.40083158e-01 3.39899249e-02 -5.00409067e-01
-8.49600911e-01 5.36414802e-01 4.14011091e-01 6.20715320e-01
1.07004368e+00 -1.70214307e+00 -8.30633163e-01 3.15240324e-01
2.61602074e-01 -3.88250530e-01 9.59258735e-01 5.87355137e-01
-3.34306136e-02 2.16043308e-01 -3.08429718e-01 -8.18826675e-01
-1.45540953e+00 9.51192856e-01 3.99826139e-01 -8.47534537e-02
-6.48674846e-01 7.63909042e-01 7.94294775e-02 5.68372495e-02
1.87985912e-01 2.30419561e-01 -4.03173149e-01 3.20921183e-01
7.53191173e-01 4.07470763e-01 -3.67722213e-01 -1.22211146e+00
-5.00147998e-01 8.54792058e-01 -1.01300888e-01 -2.17708692e-01
7.74621606e-01 -9.07406747e-01 2.10550889e-01 7.04597980e-02
1.25557125e+00 -3.63946587e-01 -1.55763340e+00 -7.94515252e-01
-4.97747928e-01 -8.95777166e-01 -2.47620717e-02 -4.20158565e-01
-1.07484281e+00 4.00126219e-01 1.18408585e+00 -1.31609097e-01
1.42557085e+00 -1.14866771e-01 8.53722394e-01 2.27071881e-01
3.51502597e-01 -1.41252851e+00 7.33565986e-01 -8.15023202e-03
6.51786983e-01 -1.50757551e+00 3.85732763e-02 -1.87716503e-02
-8.81662846e-01 8.47529113e-01 6.79430485e-01 -1.90283597e-01
4.88690436e-01 -4.56665635e-01 -2.84582645e-01 3.54236364e-02
-4.61713195e-01 -5.57131946e-01 2.79324830e-01 9.57775593e-01
-4.46861714e-01 -2.13540375e-01 8.72608423e-02 3.71463567e-01
3.53210658e-01 2.01081291e-01 5.39792329e-02 8.59002769e-01
-5.51816821e-01 -7.64639676e-01 -6.94087744e-01 2.05119938e-01
1.04203094e-02 1.20106474e-01 2.89577805e-02 4.98307467e-01
3.48397970e-01 1.35164905e+00 1.15954921e-01 -5.33250511e-01
1.92638054e-01 -1.10757545e-01 5.33604860e-01 -2.02139467e-02
-2.86631823e-01 1.86423451e-01 -2.73869693e-01 -5.24316370e-01
-9.40587878e-01 -9.17825043e-01 -8.10459793e-01 -2.71732360e-01
-2.04201207e-01 1.38683856e-01 -5.19317798e-02 1.04646337e+00
3.79810244e-01 1.73128709e-01 8.27158391e-01 -1.07693446e+00
-2.43465066e-01 -5.39609432e-01 -4.38820511e-01 7.71243393e-01
4.08131331e-01 -8.02057564e-01 -1.22701377e-02 5.03769577e-01] | [14.664393424987793, 0.9572824239730835] |
95adcf3b-2d13-4a40-b141-ebea34ae939b | pooling-of-causal-models-under-counterfactual | 1805.09866 | null | http://arxiv.org/abs/1805.09866v2 | http://arxiv.org/pdf/1805.09866v2.pdf | Pooling of Causal Models under Counterfactual Fairness via Causal Judgement Aggregation | In this paper we consider the problem of combining multiple probabilistic
causal models, provided by different experts, under the requirement that the
aggregated model satisfy the criterion of counterfactual fairness. We build
upon the work on causal models and fairness in machine learning, and we express
the problem of combining multiple models within the framework of opinion
pooling. We propose two simple algorithms, grounded in the theory of
counterfactual fairness and causal judgment aggregation, that are guaranteed to
generate aggregated probabilistic causal models respecting the criterion of
fairness, and we compare their behaviors on a toy case study. | ['Magdalena Ivanovska', 'Fabio Massimo Zennaro'] | 2018-05-24 | null | null | null | null | ['causal-judgment'] | ['reasoning'] | [ 2.26242125e-01 6.74466491e-01 -4.09679919e-01 -7.65986145e-01
-7.49950588e-01 -3.83095980e-01 7.98433363e-01 3.16934854e-01
-6.06516838e-01 1.29939163e+00 7.21118748e-01 -4.30797249e-01
-5.57286859e-01 -8.63844395e-01 -5.04227936e-01 -4.14686322e-01
-2.06450019e-02 4.29289907e-01 -2.50453860e-01 9.90761146e-02
6.55478358e-01 6.67501912e-02 -1.41487920e+00 5.93652308e-01
1.41432691e+00 6.40192449e-01 -5.79774022e-01 5.34867585e-01
7.37005547e-02 1.10332477e+00 -5.93516886e-01 -1.13338494e+00
3.17713350e-01 -5.27420700e-01 -9.77190673e-01 -3.67298603e-01
4.43363309e-01 -1.99030906e-01 8.95172432e-02 1.16454244e+00
4.84968454e-01 2.88383007e-01 1.03397453e+00 -1.70054817e+00
-9.37547863e-01 1.22400761e+00 -5.12267292e-01 3.28395590e-02
4.68596160e-01 -1.17291614e-01 1.41371369e+00 -3.77625793e-01
4.17180389e-01 1.91562331e+00 4.84252274e-01 8.22448850e-01
-1.58328235e+00 -6.46462142e-01 3.60795736e-01 1.50622532e-01
-8.99505079e-01 -4.36054021e-01 4.16229010e-01 -4.32353139e-01
4.08902258e-01 5.59663057e-01 3.20894748e-01 7.83196688e-01
4.16330665e-01 6.16210580e-01 1.77138770e+00 -5.13025165e-01
8.42979968e-01 8.58901516e-02 2.63929099e-01 2.36813664e-01
6.40158415e-01 6.22501016e-01 -7.74122655e-01 -8.54030430e-01
2.71654069e-01 -1.70683607e-01 -1.43841654e-01 -2.27882251e-01
-8.54127586e-01 1.45537174e+00 3.20751160e-01 1.07729752e-02
-5.91413736e-01 2.52709240e-01 4.11352366e-02 3.21390718e-01
7.60649025e-01 6.89702749e-01 -5.11211812e-01 5.65096915e-01
-9.04370546e-01 8.48346770e-01 1.11097622e+00 3.48519027e-01
3.20963621e-01 -3.16334426e-01 -5.68085611e-01 2.72856921e-01
6.05952740e-01 5.05110025e-01 7.86199272e-02 -1.60960472e+00
1.53499335e-01 1.15918495e-01 8.19040537e-01 -7.34583795e-01
-1.85418483e-02 7.27220401e-02 -4.51145381e-01 6.87112212e-01
3.98387849e-01 -5.26514530e-01 -3.96054655e-01 1.99806857e+00
3.48634720e-01 1.27691373e-01 1.64902464e-01 7.15947747e-01
4.20187354e-01 3.15291226e-01 6.63148820e-01 -8.27139854e-01
8.80740643e-01 -3.86969775e-01 -9.49609578e-01 2.40669355e-01
3.47062081e-01 -6.28525198e-01 6.49507344e-01 4.10294712e-01
-1.19767320e+00 -6.26778752e-02 -8.22886467e-01 2.32206196e-01
-1.39557615e-01 -5.82373619e-01 8.49389613e-01 1.08591115e+00
-1.02194655e+00 9.54549909e-01 -7.68554211e-03 1.11835655e-02
4.41531807e-01 9.94220078e-02 -6.42761365e-02 9.36794803e-02
-1.59376633e+00 1.27915239e+00 3.45903128e-01 -3.55814956e-02
-9.18837547e-01 -8.76297534e-01 -5.71600139e-01 1.24710307e-01
4.62705940e-01 -1.15828502e+00 1.32447517e+00 -1.17252278e+00
-1.30407298e+00 7.40733922e-01 -1.79372281e-01 -5.31246305e-01
1.06829321e+00 -3.48925442e-01 -3.45150530e-01 -3.44691128e-01
3.62709105e-01 4.44415003e-01 6.59694314e-01 -1.69322658e+00
-1.00327837e+00 -4.83481348e-01 3.20650339e-01 3.22211623e-01
1.45946458e-01 3.65349919e-01 8.27856004e-01 -4.45312887e-01
-6.03462338e-01 -7.11286187e-01 -7.74249792e-01 -2.77802736e-01
-5.15260756e-01 -5.02398551e-01 2.70526558e-01 -2.33200312e-01
1.11205828e+00 -1.72472811e+00 -4.92612980e-02 3.43163133e-01
2.25728959e-01 -2.50889093e-01 9.23706293e-02 -4.32715081e-02
-3.47903192e-01 8.06626678e-01 -5.44238806e-01 -2.29809716e-01
3.54750872e-01 6.39871880e-02 -5.99888027e-01 5.28601229e-01
-5.86953275e-02 6.58006489e-01 -1.02865720e+00 -6.79932773e-01
2.67701484e-02 -2.51338452e-01 -6.53179646e-01 3.29879045e-01
-2.53839403e-01 1.00121927e-02 -4.44497436e-01 6.71555549e-02
6.32286608e-01 2.22246811e-01 4.91829962e-01 1.75467744e-01
-2.34007046e-01 2.85235614e-01 -1.46082962e+00 1.01061726e+00
-2.25618139e-01 7.83895552e-02 4.99188602e-02 -6.38099790e-01
3.92555475e-01 5.82311749e-01 2.95264184e-01 -1.20248750e-01
1.58914164e-01 2.40675271e-01 -4.68860827e-02 -3.00813764e-01
2.69482940e-01 -1.03263509e+00 -4.35889363e-01 1.04600012e+00
-1.25856444e-01 -4.57291931e-01 6.71315938e-02 2.81780243e-01
5.11297822e-01 6.91088242e-03 9.10516262e-01 -7.07476318e-01
7.52388686e-02 1.04821436e-02 6.17581189e-01 1.36858737e+00
-4.03848469e-01 2.36022785e-01 7.11149633e-01 -4.67453599e-01
-9.02267277e-01 -1.27078342e+00 -9.68770832e-02 1.15049672e+00
2.69550923e-02 2.62695141e-02 -6.52037084e-01 -9.37840223e-01
2.96319395e-01 1.48224926e+00 -1.02018499e+00 9.03354287e-02
-7.69536868e-02 -1.20459950e+00 1.74727738e-01 1.84955224e-01
-2.40764562e-02 -8.38806510e-01 -7.26671338e-01 5.23688532e-02
-3.79587412e-01 -3.63598168e-01 -2.42889643e-01 -3.11469018e-01
-6.23750746e-01 -1.13578343e+00 -4.61055100e-01 2.79589176e-01
1.76584348e-01 -5.21050915e-02 1.36746669e+00 2.44199168e-02
1.45435467e-01 3.04351866e-01 -4.19108830e-02 -1.00233793e+00
-5.44249415e-01 -7.18473017e-01 2.72994697e-01 1.39908701e-01
3.36351573e-01 -5.98952472e-01 -4.55462486e-01 -1.37401953e-01
-8.58916700e-01 -6.77157715e-02 1.28421083e-01 7.57032812e-01
1.03754736e-01 8.91900137e-02 8.47958326e-01 -1.23242879e+00
1.12175357e+00 -7.03944147e-01 -5.11259019e-01 5.05969346e-01
-8.96064401e-01 6.23096935e-02 3.33171576e-01 5.27149066e-02
-1.84095788e+00 -3.70437920e-01 4.28937137e-01 1.95674375e-01
-9.23058838e-02 5.10749698e-01 -4.48203117e-01 2.64145136e-01
9.78063881e-01 -8.05395961e-01 -2.79991537e-01 -2.02076510e-01
1.15787435e+00 4.69863772e-01 8.58518854e-02 -8.32515597e-01
4.31847185e-01 6.90568507e-01 1.06257703e-02 9.67310295e-02
-1.32266772e+00 1.70953929e-01 -4.58736807e-01 -2.70949244e-01
8.64338815e-01 -6.04022324e-01 -9.12581325e-01 -1.10625252e-01
-1.41347539e+00 4.07628529e-02 -3.86593401e-01 5.15154600e-01
-8.89586806e-01 5.46423607e-02 -1.51091754e-01 -1.57832074e+00
-9.98332351e-02 -6.82062626e-01 5.60599327e-01 1.81389034e-01
-6.02309108e-01 -1.02752650e+00 3.86285901e-01 2.73624390e-01
1.30332783e-01 3.78862202e-01 1.03447270e+00 -7.34927237e-01
-2.26923451e-01 -6.21625260e-02 -1.36779279e-01 6.64381161e-02
3.23202200e-02 1.90583587e-01 -1.00094187e+00 2.50430465e-01
1.61433935e-01 -2.21093744e-01 1.06461787e+00 8.27824712e-01
8.47173870e-01 -8.04679453e-01 -3.28225702e-01 -3.18486422e-01
1.61172080e+00 9.95058939e-02 4.12073046e-01 -1.31323114e-01
3.03669095e-01 1.29475689e+00 5.53041518e-01 5.08921504e-01
5.59176564e-01 4.47230279e-01 3.45236123e-01 1.45071492e-01
4.91946101e-01 -1.68593898e-01 5.22238314e-02 -6.77896738e-02
-4.43930715e-01 -1.38305157e-01 -5.56902170e-01 6.52661681e-01
-2.41468787e+00 -1.53792858e+00 -2.62824714e-01 2.33510876e+00
9.97620285e-01 -9.62085724e-02 3.25388044e-01 -1.69914246e-01
1.11491477e+00 -1.49232987e-03 -1.54253408e-01 -9.80420291e-01
-7.88959041e-02 1.46809876e-01 4.99987483e-01 1.12707329e+00
-1.00968146e+00 4.91909891e-01 8.14395428e+00 7.53090858e-01
-2.52875984e-01 4.95933205e-01 1.05274725e+00 -4.32366818e-01
-1.12957799e+00 3.49694490e-01 -2.70758748e-01 4.89004642e-01
1.00244462e+00 -7.78855503e-01 2.06143066e-01 6.30514801e-01
4.92524475e-01 -3.48691911e-01 -1.26777995e+00 1.76707938e-01
-3.56874645e-01 -1.25917101e+00 3.49585623e-01 -1.65869996e-01
1.31661630e+00 -5.53592503e-01 -6.72871619e-02 -7.42450655e-02
1.57395136e+00 -1.39722848e+00 1.02046287e+00 8.28733742e-01
2.77103990e-01 -7.93871164e-01 1.01685941e+00 1.98829681e-01
-3.59120667e-01 -3.52607787e-01 -1.81112066e-01 -6.24517679e-01
5.40511966e-01 1.07739305e+00 -2.33875707e-01 8.59338164e-01
6.14374876e-01 2.55343825e-01 5.11944033e-02 9.50078368e-01
-6.02810264e-01 4.01136965e-01 1.42404041e-03 3.58462036e-02
-5.74998707e-02 5.61844744e-02 3.99528116e-01 9.69020128e-01
1.19803973e-01 3.10197920e-01 6.62862808e-02 1.14345133e+00
-9.98346414e-03 9.58493203e-02 -5.66288114e-01 4.77853477e-01
6.12317562e-01 8.17194343e-01 -2.04296425e-01 -5.80247700e-01
-2.13614181e-01 3.01251978e-01 2.36369297e-01 3.03531379e-01
-6.72142029e-01 1.97087139e-01 5.65736473e-01 -4.16718274e-01
-3.51245761e-01 6.12902164e-01 -9.77733970e-01 -1.11707211e+00
-2.59647697e-01 -8.00890625e-01 9.26024437e-01 -6.40132546e-01
-1.95334017e+00 9.44830198e-03 2.21263647e-01 -5.43114245e-01
-1.72176540e-01 -4.11743492e-01 -1.01536953e+00 1.21743202e+00
-1.34070790e+00 -8.74021351e-01 4.54890728e-01 4.20852900e-01
-6.58736303e-02 3.47122788e-01 8.83447945e-01 -1.99687332e-01
-1.50322422e-01 8.53873491e-02 -2.27305055e-01 -5.18570006e-01
8.22190523e-01 -1.65604901e+00 4.93020862e-02 8.54911685e-01
-1.90571085e-01 6.87681675e-01 1.19619930e+00 -7.86191285e-01
-4.12185311e-01 -9.34803247e-01 1.46937919e+00 -8.98924530e-01
4.83597189e-01 5.34209795e-02 -5.51521301e-01 6.43085659e-01
4.79882032e-01 -5.54651976e-01 1.04865241e+00 6.38790131e-01
-5.36386669e-01 3.02938614e-02 -1.59219444e+00 6.88188672e-01
9.91667509e-01 -3.21315646e-01 -1.24460232e+00 1.78288236e-01
7.25387037e-01 3.58304203e-01 -6.20458484e-01 4.65171605e-01
7.73207426e-01 -1.04558194e+00 8.10669184e-01 -1.28196275e+00
7.87727833e-01 -2.48705208e-01 -3.24919850e-01 -1.73660970e+00
-4.37631279e-01 -6.41288996e-01 1.85011268e-01 9.74162042e-01
7.60254979e-01 -7.11700320e-01 3.33100498e-01 1.27658856e+00
4.81413752e-01 -2.72413552e-01 -1.35709751e+00 -3.38974565e-01
5.18144429e-01 -3.46004158e-01 6.85334861e-01 1.22629833e+00
3.44529331e-01 2.89994180e-01 -6.51707888e-01 1.11165177e-03
1.13565302e+00 3.30087841e-01 2.68040657e-01 -1.56250238e+00
-1.99792802e-01 -7.66489625e-01 2.21322283e-01 9.06479210e-02
5.89243650e-01 -4.18011039e-01 1.70028418e-01 -1.49567211e+00
7.44007289e-01 -2.33197704e-01 -4.77479696e-01 2.56164163e-01
-9.07279968e-01 -7.61651248e-02 4.15961564e-01 -6.82088435e-02
-5.54955661e-01 4.88752335e-01 8.55601132e-01 -4.17976221e-03
1.33073509e-01 7.87267014e-02 -1.41258800e+00 9.13515747e-01
6.94858193e-01 -8.06521118e-01 -2.66658276e-01 -1.50150627e-01
5.58892071e-01 2.82080472e-01 6.19047344e-01 -1.04087695e-01
5.94828352e-02 -9.21736360e-01 2.13264182e-01 7.45711923e-02
-1.51541829e-01 -5.99336028e-01 2.21966028e-01 5.17718911e-01
-1.03644407e+00 -1.12650327e-01 -2.01853916e-01 6.65362835e-01
-1.15432627e-02 -3.33085984e-01 6.96435869e-01 -5.01319528e-01
-4.34088737e-01 3.27962190e-02 -3.81006956e-01 7.95928668e-03
8.95919979e-01 3.91096860e-01 -5.04795015e-01 -5.08036971e-01
-8.47276747e-01 2.74425834e-01 3.61136198e-01 1.64805964e-01
2.25820094e-01 -1.31715548e+00 -1.37442684e+00 -7.35163748e-01
-5.22297211e-02 -9.00473893e-01 4.31840539e-01 6.35393023e-01
2.75870651e-01 4.80673611e-01 -2.26781785e-01 2.61457711e-01
-8.68854940e-01 7.92573214e-01 5.22752523e-01 -3.78667325e-01
3.86430651e-01 7.68242836e-01 4.87830102e-01 -5.64666927e-01
-3.39275360e-01 2.84540355e-01 -3.49071145e-01 1.05954930e-01
6.81659043e-01 6.79884017e-01 -3.98256570e-01 -1.66338339e-01
-3.55770975e-01 -2.51633599e-02 3.28161269e-01 -6.95926666e-01
1.01876569e+00 -2.58423597e-01 -7.16912746e-01 4.58384544e-01
4.68439609e-01 2.81541109e-01 -9.66703296e-01 -1.60512177e-03
2.61991829e-01 -8.26552331e-01 -9.04711857e-02 -1.25490832e+00
-4.32329416e-01 5.57806373e-01 3.51801425e-01 5.96349895e-01
8.74219775e-01 -8.26229528e-02 -2.73367405e-01 -8.40892866e-02
4.89826262e-01 -1.08415473e+00 -6.21214867e-01 -1.16400473e-01
9.40515399e-01 -1.25917828e+00 1.84494048e-01 -3.77333939e-01
-7.19548702e-01 6.24093056e-01 2.81422824e-01 -3.36601704e-01
6.62114322e-01 -3.49256285e-02 4.08169851e-02 -6.42281175e-02
-1.10890675e+00 -1.03733033e-01 4.17165935e-01 5.58373094e-01
7.07376182e-01 9.91398036e-01 -1.14255404e+00 8.62823904e-01
-1.61956921e-01 1.69292882e-01 7.33817935e-01 5.50966084e-01
-2.81150758e-01 -9.60357547e-01 -5.91688335e-01 6.10704362e-01
-7.97452152e-01 -3.25840324e-01 -7.53301501e-01 3.68656754e-01
2.23554641e-01 1.50757182e+00 -1.80035889e-01 1.11592345e-01
2.46445164e-01 5.12102209e-02 4.99534816e-01 -6.13229573e-01
-5.81021786e-01 -2.67520964e-01 5.99510729e-01 -6.12645864e-01
-1.07050133e+00 -8.35256279e-01 -5.71768939e-01 -7.72915840e-01
-2.75660634e-01 6.59730673e-01 1.84791073e-01 1.32979488e+00
2.32393779e-02 3.20970625e-01 5.65092146e-01 -4.91430610e-01
-7.87144601e-01 -8.60844135e-01 -6.80065036e-01 5.06199300e-01
2.86191434e-01 -7.33181179e-01 -6.31362140e-01 -4.23354022e-02] | [8.631162643432617, 5.472385406494141] |
a926888f-f4e5-4efe-ad30-33c8ef1adbef | so-3-pose-so-3-equivariance-learning-for-6d | 2208.08338 | null | https://arxiv.org/abs/2208.08338v1 | https://arxiv.org/pdf/2208.08338v1.pdf | SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimation | 6D pose estimation of rigid objects from RGB-D images is crucial for object grasping and manipulation in robotics. Although RGB channels and the depth (D) channel are often complementary, providing respectively the appearance and geometry information, it is still non-trivial how to fully benefit from the two cross-modal data. From the simple yet new observation, when an object rotates, its semantic label is invariant to the pose while its keypoint offset direction is variant to the pose. To this end, we present SO(3)-Pose, a new representation learning network to explore SO(3)-equivariant and SO(3)-invariant features from the depth channel for pose estimation. The SO(3)-invariant features facilitate to learn more distinctive representations for segmenting objects with similar appearance from RGB channels. The SO(3)-equivariant features communicate with RGB features to deduce the (missed) geometry for detecting keypoints of an object with the reflective surface from the depth channel. Unlike most of existing pose estimation methods, our SO(3)-Pose not only implements the information communication between the RGB and depth channels, but also naturally absorbs the SO(3)-equivariance geometry knowledge from depth images, leading to better appearance and geometry representation learning. Comprehensive experiments show that our method achieves the state-of-the-art performance on three benchmarks. | ['Mingqiang Wei', 'Xuefeng Yan', 'Weiming Wang', 'Xuequan Lu', 'Yuanpeng Liu', 'Jun Zhou', 'Haoran Pan'] | 2022-08-17 | null | null | null | null | ['6d-pose-estimation-1', '6d-pose-estimation'] | ['computer-vision', 'computer-vision'] | [ 5.61645888e-02 7.64556974e-02 -1.01510361e-01 -4.36440736e-01
-5.48450947e-01 -6.50783658e-01 4.40856427e-01 -1.87905177e-01
-1.12545229e-01 -1.25272706e-01 -1.03361487e-01 5.19477017e-03
-1.99778557e-01 -7.40880549e-01 -9.70530987e-01 -9.52455819e-01
-7.82155544e-02 6.22716367e-01 3.09295356e-01 -3.45479935e-01
2.15388477e-01 9.58806872e-01 -1.63372934e+00 1.91035151e-01
2.27502123e-01 1.44097042e+00 2.98013806e-01 4.89395261e-01
-1.00032240e-01 1.74764961e-01 -1.55276507e-01 -4.90229502e-02
6.11012638e-01 1.63472444e-02 -7.73653090e-01 1.76271319e-01
6.67427301e-01 -4.94715959e-01 -5.47526062e-01 1.08771956e+00
1.50358960e-01 -1.88009232e-01 7.66665995e-01 -1.16112554e+00
-6.18026853e-01 1.60752401e-01 -6.85351610e-01 -4.02495116e-01
7.47027755e-01 6.17602915e-02 9.07556772e-01 -9.45075393e-01
7.87886322e-01 1.66940391e+00 3.10026407e-01 3.95625263e-01
-8.33908558e-01 -4.17688042e-01 4.17059869e-01 2.26804867e-01
-1.29005742e+00 1.68348908e-01 1.24279344e+00 -3.09233963e-01
4.13931549e-01 2.03624293e-01 7.88203895e-01 9.01422620e-01
1.14242733e-01 9.70474124e-01 1.05855632e+00 -1.94840550e-01
-8.40330273e-02 -1.10895164e-01 7.08140898e-03 9.19261217e-01
2.21690107e-02 4.00183164e-02 -3.11391473e-01 1.91737905e-01
1.23485887e+00 4.97016311e-01 -3.66309077e-01 -1.11164093e+00
-1.39041018e+00 5.12104750e-01 8.87682617e-01 -1.92170098e-01
-1.61448613e-01 1.50602907e-01 -2.19033677e-02 2.99006611e-01
-5.27356844e-03 2.97011495e-01 -7.50896096e-01 -2.00411472e-02
2.40427494e-01 1.22234538e-01 8.61535192e-01 1.44678080e+00
1.23232400e+00 -2.52156109e-01 1.55907452e-01 3.43236595e-01
6.54541016e-01 9.91193175e-01 1.10002927e-01 -1.01669025e+00
4.48142499e-01 9.57667708e-01 8.53294656e-02 -1.04244375e+00
-7.23205805e-01 -9.61905569e-02 -5.92260361e-01 2.87368864e-01
6.81518853e-01 4.05350536e-01 -9.04220462e-01 1.45658052e+00
6.12212002e-01 -3.20988178e-01 -1.00537963e-01 1.21378028e+00
9.79912639e-01 2.49548495e-01 -6.19890928e-01 1.13635890e-01
1.55285919e+00 -7.40628064e-01 -2.43622869e-01 -1.02352165e-01
3.25573862e-01 -8.90391767e-01 8.42175603e-01 3.21318984e-01
-8.71227682e-01 -4.65957820e-01 -9.82491672e-01 -3.07902336e-01
-4.86356944e-01 9.70501080e-02 9.68570650e-01 2.78306872e-01
-4.44031537e-01 3.13179851e-01 -8.53133321e-01 -2.16297016e-01
1.66749284e-01 4.90643173e-01 -8.04347336e-01 -3.12729746e-01
-7.22698927e-01 8.51171374e-01 1.45216912e-01 3.83979529e-01
-7.41796017e-01 -5.18057287e-01 -9.87321377e-01 -5.97718477e-01
5.16555786e-01 -4.19698089e-01 9.66417491e-01 -6.33075237e-01
-1.75974035e+00 1.10790396e+00 -5.29731996e-02 4.58329886e-01
7.08616614e-01 -2.75235951e-01 2.14050516e-01 4.92456019e-01
-1.99739993e-01 4.41365957e-01 1.13521278e+00 -1.74818480e+00
-4.54845071e-01 -1.15954244e+00 5.46675503e-01 4.31769520e-01
4.46102098e-02 -5.14998138e-01 -6.05756938e-01 -3.35308701e-01
1.27624691e+00 -1.05539441e+00 1.34638846e-01 5.46207547e-01
-3.61436963e-01 -3.81118357e-01 1.10329974e+00 -4.57656741e-01
1.80121884e-01 -2.08407331e+00 6.22987688e-01 2.24352270e-01
1.14588812e-01 -8.64541605e-02 -1.24263406e-01 1.37583345e-01
2.01705983e-03 -4.53530937e-01 2.84633487e-01 -7.98496231e-02
5.03996760e-02 2.60647058e-01 -2.14717239e-01 1.11612308e+00
3.49563003e-01 9.85867262e-01 -1.10358131e+00 -2.70534486e-01
5.38597345e-01 5.03497660e-01 -4.41571563e-01 3.63721400e-01
1.14635387e-02 7.34270275e-01 -8.69597495e-01 1.13593590e+00
9.56155896e-01 1.02859102e-01 -1.81734040e-01 -8.92999113e-01
2.16998514e-02 4.80242297e-02 -1.34060752e+00 1.99886715e+00
-3.17783177e-01 1.38156995e-01 6.14669733e-02 -1.02215469e+00
1.05107987e+00 8.06727484e-02 6.74243867e-01 -6.16827965e-01
3.47185314e-01 2.92039484e-01 -3.09244841e-01 -7.53407776e-01
1.00919150e-01 2.09061101e-01 -1.93615347e-01 1.53182447e-01
5.65118231e-02 -5.58897734e-01 -4.43346798e-01 -3.12782735e-01
6.75086856e-01 5.33490419e-01 5.58647588e-02 -1.04597853e-02
5.30666113e-01 -2.95644581e-01 3.05873960e-01 2.93574274e-01
-9.39671993e-02 7.61241496e-01 3.82239312e-01 -5.84138095e-01
-8.77944946e-01 -1.59644902e+00 -3.74157488e-01 7.46755719e-01
8.91306996e-01 1.30415365e-01 -3.80422801e-01 -5.92673481e-01
5.76433718e-01 -1.54596180e-01 -7.30550945e-01 -4.12279665e-01
-7.50843167e-01 -1.02370635e-01 8.80999565e-02 5.45266032e-01
4.30928141e-01 -6.84380293e-01 -8.20018351e-01 -1.76100075e-01
-5.70025481e-02 -1.16881025e+00 -1.74727350e-01 3.37598115e-01
-9.70334053e-01 -1.33619893e+00 -6.55703902e-01 -7.15652883e-01
9.42269385e-01 7.13482857e-01 4.98690695e-01 -2.64208019e-01
-4.27956343e-01 8.44819009e-01 -7.55961239e-01 -4.19778734e-01
6.33909851e-02 -1.66101888e-01 1.18404634e-01 -2.38652714e-03
3.20467383e-01 -5.38994431e-01 -6.59154534e-01 6.22408152e-01
-8.27941537e-01 -9.47479606e-02 6.89778745e-01 4.84412223e-01
8.55880916e-01 -4.06914711e-01 7.15690898e-03 -2.19659656e-01
-3.59331965e-01 -1.39267981e-01 -5.28112948e-01 2.26664186e-01
-1.32700250e-01 2.41142794e-01 2.92545289e-01 -5.72694957e-01
-7.73495078e-01 5.22599041e-01 2.09832773e-01 -7.58189142e-01
-1.94423079e-01 8.89992863e-02 -4.59455967e-01 -3.29630613e-01
3.34881306e-01 2.67322455e-02 2.20210314e-01 -6.42052472e-01
6.22153163e-01 5.79516470e-01 5.95911801e-01 -7.27412105e-01
1.10426188e+00 9.84541416e-01 4.46770400e-01 -7.77430952e-01
-8.74192059e-01 -7.25324571e-01 -1.11450958e+00 -3.48119259e-01
7.71960557e-01 -9.42410827e-01 -1.09512043e+00 7.38685131e-01
-1.37330091e+00 1.49441451e-01 -9.63304937e-02 6.20312452e-01
-8.30973804e-01 5.12932837e-01 -2.38385901e-01 -7.90455997e-01
1.44040748e-01 -1.32274711e+00 1.72168863e+00 1.41346276e-01
2.99541563e-01 -5.96339464e-01 -3.94891381e-01 2.33875409e-01
-3.05309772e-01 5.96347272e-01 8.96789193e-01 -6.70903549e-02
-9.31457937e-01 -4.56776559e-01 -3.27956647e-01 7.95413926e-02
3.01094085e-01 2.42848042e-02 -9.58981276e-01 -2.38556728e-01
6.64350465e-02 -3.48867297e-01 7.34637141e-01 7.79012591e-02
1.20707893e+00 6.94761798e-02 -4.98328730e-02 9.82003510e-01
1.28779948e+00 -1.41495526e-01 5.54703176e-01 4.26863313e-01
1.16347742e+00 8.27497661e-01 9.62271512e-01 4.64459866e-01
5.73282123e-01 9.23420668e-01 1.19173288e+00 7.48916566e-02
-3.99239659e-02 -2.72278368e-01 6.06649399e-01 7.91556835e-01
-4.99895155e-01 4.45283026e-01 -6.28783643e-01 3.47445011e-02
-1.67899442e+00 -4.66682553e-01 -3.58908296e-01 2.28497267e+00
7.97261834e-01 -1.94847926e-01 -1.08529618e-02 1.18394382e-01
4.93980944e-01 1.04816392e-01 -8.21818829e-01 -1.52481096e-02
-2.00252071e-01 9.66304243e-02 5.86549282e-01 2.18005151e-01
-1.01262856e+00 8.05968881e-01 4.92547321e+00 5.24851382e-01
-1.15934086e+00 -3.17478716e-01 -8.32505226e-02 1.97523713e-01
-2.51622051e-01 -5.32985888e-02 -6.89437687e-01 -4.13457043e-02
-1.67769134e-01 3.79777580e-01 3.11871916e-01 1.14876115e+00
-3.59173536e-01 -5.38399555e-02 -1.58178318e+00 1.12123775e+00
3.43514264e-01 -6.66823566e-01 8.05043727e-02 1.03854306e-01
5.64035892e-01 3.61085543e-03 7.16716126e-02 -9.22734514e-02
-1.69965565e-01 -7.11945653e-01 1.22418094e+00 5.15741765e-01
8.48561347e-01 -5.52022934e-01 6.74124658e-01 2.15025097e-01
-1.43701661e+00 -1.80401161e-01 -5.74812651e-01 -1.10144593e-01
-5.14669120e-02 3.45277995e-01 -4.31338549e-01 9.59145546e-01
8.84224057e-01 1.02214599e+00 -3.94895136e-01 6.84625983e-01
-4.17049348e-01 -4.06017393e-01 -3.22359145e-01 1.20619647e-01
1.28101468e-01 -4.02033865e-01 6.22878134e-01 6.46406710e-01
2.84265965e-01 7.48966560e-02 1.81018695e-01 8.04917753e-01
1.34297654e-01 -3.22392672e-01 -6.08527541e-01 2.80122876e-01
1.86772302e-01 1.29015338e+00 -7.93565035e-01 1.45066962e-01
-3.19697976e-01 1.03513670e+00 1.34251848e-01 3.56034577e-01
-6.01318777e-01 -2.80474871e-01 8.77938092e-01 -6.62371665e-02
4.89105225e-01 -6.20235562e-01 2.22571883e-02 -1.12718463e+00
4.86847460e-01 -5.34404755e-01 -2.63443273e-02 -9.64031219e-01
-1.30705881e+00 2.16152802e-01 1.72831893e-01 -1.65198517e+00
1.37416467e-01 -1.49726391e+00 6.31394004e-03 6.34580553e-01
-1.97128844e+00 -1.41050553e+00 -8.16674769e-01 8.01426351e-01
2.49690264e-01 2.50900418e-01 9.08236325e-01 -1.27366245e-01
-7.84524232e-02 3.64686489e-01 -4.70581055e-02 2.07302481e-01
6.47154987e-01 -1.27588141e+00 -2.24143699e-01 1.18789464e-01
6.82345703e-02 6.82954729e-01 3.78199875e-01 -1.33939266e-01
-2.52250028e+00 -7.91475356e-01 4.97711934e-02 -8.06410015e-01
4.52080935e-01 -3.93775463e-01 -5.24590015e-01 6.05169058e-01
-6.99877501e-01 2.43830889e-01 -8.71994346e-03 -2.22978026e-01
-9.47707355e-01 -2.76620120e-01 -1.02793944e+00 3.17560762e-01
1.29439127e+00 -8.21550429e-01 -7.67938614e-01 3.26600999e-01
8.15261900e-01 -9.57670569e-01 -1.06006515e+00 6.79513931e-01
1.10436285e+00 -8.77029419e-01 1.35135233e+00 -4.43738669e-01
4.80669856e-01 -5.22310257e-01 -4.90837634e-01 -8.36283684e-01
-1.12789370e-01 -3.87278646e-01 -2.21492335e-01 7.60028303e-01
-1.25247896e-01 -6.43701553e-01 7.29514718e-01 1.60769120e-01
-2.27206007e-01 -7.90368557e-01 -1.12420452e+00 -7.70350158e-01
-3.65555435e-02 -5.16783118e-01 6.60723090e-01 6.37205064e-01
-2.66240746e-01 -9.91973430e-02 1.76944316e-03 5.78131080e-01
5.69661319e-01 6.87763810e-01 1.02879679e+00 -1.53190708e+00
4.22816910e-02 -4.38209802e-01 -1.04974055e+00 -1.72262788e+00
8.70725736e-02 -9.11540747e-01 2.02686429e-01 -1.30293453e+00
9.38601866e-02 -4.06643718e-01 -1.91535175e-01 4.01027530e-01
9.98522416e-02 2.28915080e-01 1.35855973e-01 7.11853504e-02
-4.97810960e-01 6.19349718e-01 1.82694530e+00 -2.40617245e-01
-2.73539871e-02 -1.93923600e-02 -3.74097615e-01 8.78140271e-01
3.19187880e-01 -7.81865716e-02 -7.03347521e-03 -5.11886239e-01
4.36111957e-01 -1.30355641e-01 7.52081096e-01 -6.56845748e-01
-1.05487771e-01 -2.92275459e-01 5.02026141e-01 -8.10631335e-01
6.08420849e-01 -1.24009633e+00 -1.87412605e-01 4.12027359e-01
1.44006312e-01 -1.83774352e-01 -1.47144422e-01 7.85531580e-01
-1.13362789e-01 -6.10509999e-02 6.23323143e-01 -3.24880213e-01
-8.91451180e-01 6.38892412e-01 1.70144439e-01 -2.19779536e-01
1.01657224e+00 -6.25717580e-01 -2.90661722e-01 -3.50441962e-01
-4.73782212e-01 5.55351377e-02 7.40307033e-01 6.78841233e-01
9.18225706e-01 -1.46971679e+00 -2.80425161e-01 5.59774697e-01
6.05731428e-01 9.03039157e-01 9.15300027e-02 1.03455234e+00
-6.14618003e-01 2.85886526e-01 -4.10686195e-01 -1.22615373e+00
-9.77374196e-01 3.36731791e-01 1.51135072e-01 4.39650953e-01
-5.89229107e-01 9.63203490e-01 4.91064280e-01 -8.54166269e-01
5.39020240e-01 -5.88983953e-01 4.20239456e-02 -5.07308990e-02
3.38354379e-01 4.65214580e-01 -3.61775584e-03 -9.13010299e-01
-4.40370053e-01 1.41347575e+00 1.36547863e-01 1.83078870e-01
1.44092834e+00 -1.69822946e-01 -4.76447552e-01 7.34070837e-01
1.61050308e+00 -1.80732206e-01 -1.46645272e+00 -3.84348094e-01
-3.54160011e-01 -5.78532040e-01 -2.70227760e-01 -3.33815515e-01
-1.13733459e+00 1.12731147e+00 5.42474747e-01 -9.41380020e-03
9.40829396e-01 5.08003950e-01 4.77783918e-01 7.19963551e-01
7.91993916e-01 -8.96055579e-01 4.34787065e-01 6.79729939e-01
1.14103234e+00 -1.34580922e+00 1.64781973e-01 -7.00317800e-01
-2.26100713e-01 1.62542892e+00 5.63867927e-01 -2.58404374e-01
7.35292435e-01 -1.73398167e-01 7.84605667e-02 -4.58441585e-01
2.35353544e-01 -9.50524285e-02 6.23295069e-01 8.48771811e-01
-5.14870957e-02 2.57878155e-01 3.50139588e-01 3.43171716e-01
-1.02272183e-01 -6.83699548e-01 1.32191911e-01 9.74674821e-01
-4.39134061e-01 -9.90185440e-01 -4.23360020e-01 -6.20715730e-02
1.55401573e-01 5.86721778e-01 -5.40705919e-01 9.83912945e-01
2.58366048e-01 5.68285048e-01 9.83964801e-02 -5.16543686e-01
5.46495676e-01 -2.81715006e-01 1.20410264e+00 -5.33182144e-01
1.50999412e-01 -3.71708311e-02 -4.17838663e-01 -1.03598702e+00
-7.97148347e-01 -5.96810162e-01 -1.50425363e+00 3.75797972e-02
-4.24211234e-01 -4.48757023e-01 1.02932537e+00 8.80873561e-01
1.18513703e-02 4.71178830e-01 9.85738873e-01 -1.38347983e+00
-7.44027555e-01 -6.22723937e-01 -7.63380885e-01 6.25537872e-01
5.08015335e-01 -1.21453238e+00 -4.28583741e-01 -2.45187029e-01] | [7.463006019592285, -2.6768176555633545] |
53581ecd-b551-4d9d-85e9-04414ca0792f | qualitative-and-quantitative-analysis-of | 2109.05250 | null | https://arxiv.org/abs/2109.05250v2 | https://arxiv.org/pdf/2109.05250v2.pdf | Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes | Established cross-document coreference resolution (CDCR) datasets contain event-centric coreference chains of events and entities with identity relations. These datasets establish strict definitions of the coreference relations across related tests but typically ignore anaphora with more vague context-dependent loose coreference relations. In this paper, we qualitatively and quantitatively compare the annotation schemes of ECB+, a CDCR dataset with identity coreference relations, and NewsWCL50, a CDCR dataset with a mix of loose context-dependent and strict coreference relations. We propose a phrasing diversity metric (PD) that encounters for the diversity of full phrases unlike the previously proposed metrics and allows to evaluate lexical diversity of the CDCR datasets in a higher precision. The analysis shows that coreference chains of NewsWCL50 are more lexically diverse than those of ECB+ but annotating of NewsWCL50 leads to the lower inter-coder reliability. We discuss the different tasks that both CDCR datasets create for the CDCR models, i.e., lexical disambiguation and lexical diversity. Finally, to ensure generalizability of the CDCR models, we propose a direction for CDCR evaluation that combines CDCR datasets with multiple annotation schemes that focus of various properties of the coreference chains. | ['Bela Gipp', 'Felix Hamborg', 'Anastasia Zhukova'] | 2021-09-11 | towards-evaluation-of-cross-document | https://aclanthology.org/2022.lrec-1.522 | https://aclanthology.org/2022.lrec-1.522.pdf | lrec-2022-6 | ['cross-document-coreference-resolution'] | ['natural-language-processing'] | [-2.99410880e-01 3.35751265e-01 -4.99611646e-01 -3.15139860e-01
-8.20574164e-01 -1.12543702e+00 7.09204793e-01 3.45820546e-01
-5.41339457e-01 9.80346084e-01 8.97697151e-01 -1.82783410e-01
-9.38733518e-01 -5.41581750e-01 -1.53616562e-01 -2.64214128e-01
5.89026362e-02 1.04589045e+00 5.24571776e-01 -6.02612317e-01
1.34020984e-01 7.05290794e-01 -1.56825948e+00 6.73577070e-01
5.63454151e-01 3.07000220e-01 1.62039205e-01 2.71359771e-01
1.48580596e-02 8.88314128e-01 -7.38359749e-01 -8.89291048e-01
-1.74690917e-01 1.23894298e-02 -1.42170179e+00 -8.76220047e-01
3.82135779e-01 4.89840716e-01 -5.18667459e-01 1.08432555e+00
7.83662975e-01 2.44871825e-01 3.22674304e-01 -1.18994749e+00
-3.90628994e-01 1.42967641e+00 -4.29790050e-01 6.21737063e-01
1.16890597e+00 -3.67374480e-01 1.41988933e+00 -5.51486075e-01
1.42010152e+00 1.70698142e+00 8.16275120e-01 5.61607003e-01
-1.24956524e+00 -9.63591218e-01 7.20860139e-02 5.14153540e-01
-1.53642452e+00 -3.06382596e-01 4.78859097e-01 -2.85104007e-01
1.32433486e+00 6.36413097e-01 5.29632531e-03 1.55804920e+00
-1.13731794e-01 2.28249162e-01 1.06211662e+00 -3.62437010e-01
-5.75415194e-02 -6.34148195e-02 8.05332601e-01 -5.57096079e-02
7.38915384e-01 3.33032966e-01 -7.58086920e-01 -4.05261546e-01
3.35986406e-01 -6.55683458e-01 -6.25315070e-01 -2.54633546e-01
-9.86348331e-01 7.97797740e-01 1.47701830e-01 7.23347783e-01
3.82730700e-02 -5.10851979e-01 7.34117746e-01 3.55552644e-01
-2.13087425e-01 9.10200655e-01 -6.35300636e-01 -1.04856797e-01
-4.30420339e-01 4.67557013e-01 1.20400083e+00 1.34270608e+00
3.64095449e-01 -6.89256489e-01 -2.92202473e-01 1.12132120e+00
9.32495445e-02 4.04241085e-01 5.58274865e-01 -1.42830241e+00
6.03816211e-01 5.95796585e-01 2.92225033e-01 -1.15128469e+00
-8.59455407e-01 -1.89903602e-01 -2.95393616e-01 -3.48866999e-01
4.81599033e-01 1.82484046e-01 -2.82390937e-02 2.08910370e+00
1.74502060e-01 -3.17311108e-01 6.08996451e-01 1.10412574e+00
1.34138596e+00 1.74650073e-01 3.07383031e-01 -6.26222253e-01
1.86137640e+00 -5.28048813e-01 -1.21954298e+00 -4.67304746e-03
7.12692261e-01 -8.72105956e-01 7.61413515e-01 2.41498411e-01
-1.04712296e+00 -2.20046654e-01 -9.01456475e-01 -1.69387713e-01
-2.14452818e-01 -4.17622507e-01 6.12209022e-01 2.74698079e-01
-7.42146492e-01 3.21856350e-01 -4.04779375e-01 -7.41365433e-01
-4.84706104e-01 2.64981240e-01 -8.08754206e-01 1.58243343e-01
-1.94121182e+00 1.45939326e+00 9.61456895e-01 -4.46908236e-01
-4.59554911e-01 -7.31320143e-01 -8.72351468e-01 1.14475042e-01
6.05782032e-01 -1.82696745e-01 1.24175501e+00 -1.85997486e-01
-8.15106094e-01 1.30298519e+00 2.52253056e-01 -3.20483238e-01
3.38272393e-01 -2.53801674e-01 -1.08819020e+00 1.29516408e-01
4.65507060e-01 3.77417237e-01 -3.50895822e-01 -1.20018184e+00
-8.61516297e-01 -1.57442689e-01 2.42931247e-01 3.95269245e-01
2.51794398e-01 5.42994857e-01 -3.66859704e-01 -5.11295974e-01
2.10046515e-01 -8.29521000e-01 3.64184648e-01 -9.49790180e-01
-2.45244995e-01 -6.93021119e-01 5.82392693e-01 -1.66363806e-01
1.70886695e+00 -2.08319163e+00 2.16456965e-01 -3.37032750e-02
1.18830115e-01 2.15710178e-01 -2.29937583e-01 5.98098934e-01
-7.56823301e-01 8.12447071e-02 1.71231687e-01 2.33409107e-01
1.62445039e-01 5.50446630e-01 -6.06471658e-01 3.07281017e-01
8.69795866e-03 4.63330567e-01 -1.24332738e+00 -8.82309377e-01
-1.88548550e-01 1.41437337e-01 -5.83325028e-01 -3.46749611e-02
-4.18260656e-02 5.74456751e-02 -2.27237746e-01 3.48010093e-01
5.41634798e-01 2.15506449e-01 9.63455260e-01 -7.80757189e-01
-4.46539968e-01 8.28953087e-01 -1.37226343e+00 1.63794458e+00
-1.29450753e-01 4.31513250e-01 5.82332574e-02 -6.18242979e-01
1.03273535e+00 7.73398221e-01 3.00430119e-01 -7.85844743e-01
3.03191487e-02 2.80734390e-01 2.68799365e-01 -5.22087693e-01
8.98052633e-01 -2.86714081e-02 -6.34196043e-01 4.21348959e-01
3.87697011e-01 1.65673375e-01 6.02009594e-01 5.16750753e-01
1.24529648e+00 -2.44879853e-02 8.02996516e-01 -6.88763380e-01
6.10424757e-01 2.96486020e-01 1.35501754e+00 7.19555140e-01
-3.94143701e-01 3.93166035e-01 7.14579582e-01 -2.53515780e-01
-6.61621749e-01 -1.20119619e+00 -7.66080856e-01 1.14691377e+00
3.72636557e-01 -7.58503795e-01 -2.51971126e-01 -7.82325566e-01
-2.47294605e-02 1.10825992e+00 -5.37560523e-01 -3.26855034e-02
-8.79960597e-01 -7.01661348e-01 1.21683180e+00 3.99665862e-01
1.09027639e-01 -1.10350740e+00 -6.29998624e-01 1.12455226e-01
-8.73675704e-01 -1.27129459e+00 -3.12989354e-01 4.13646221e-01
-2.86370814e-01 -1.64791751e+00 1.54992953e-01 -8.25826645e-01
-7.82103390e-02 -2.38270611e-01 1.63190067e+00 -7.95389041e-02
-4.46106829e-02 4.45762575e-01 -7.84493983e-01 7.67178461e-02
-5.57455957e-01 1.39308318e-01 2.21801162e-01 -8.88087809e-01
1.10395837e+00 -4.59001303e-01 2.43863985e-02 7.59766638e-01
-5.68545341e-01 -4.58252668e-01 1.92183003e-01 8.49629164e-01
3.98512781e-01 -1.99841678e-01 5.58589041e-01 -1.14368808e+00
7.93362260e-01 -5.68856537e-01 -3.06485862e-01 5.30131817e-01
-5.54233372e-01 1.00623570e-01 -1.91709716e-02 -6.45371139e-01
-1.40870845e+00 -5.01902223e-01 -4.78343777e-02 -1.86522767e-01
-2.55620062e-01 3.28068018e-01 -3.11307698e-01 4.67830360e-01
1.06221974e+00 -5.78892946e-01 -7.62196541e-01 -4.79776680e-01
4.05164123e-01 7.37950563e-01 1.22131717e+00 -1.47241664e+00
1.78445324e-01 5.41950352e-02 -3.35203022e-01 -2.38752380e-01
-1.14750004e+00 -7.89851308e-01 -6.56407952e-01 1.44416392e-01
8.25791061e-01 -8.79669666e-01 -9.30911839e-01 -3.23136538e-01
-1.57063341e+00 7.34965801e-02 -4.09244031e-01 6.62494481e-01
-5.83092034e-01 3.05472046e-01 -8.42790604e-01 -4.41174835e-01
-2.12742597e-01 -9.18146551e-01 7.87564218e-01 -5.15210293e-02
-1.14119673e+00 -9.54083025e-01 6.23787999e-01 1.23701014e-01
-2.12542936e-01 1.64560229e-01 8.94877672e-01 -1.29767597e+00
2.99667478e-01 1.93291381e-01 -2.77289420e-01 -4.59002823e-01
-4.31730300e-02 -1.66857675e-01 -6.96171343e-01 -2.04820752e-01
-5.97958863e-02 -2.55066395e-01 4.20514107e-01 -7.10769221e-02
2.00609013e-01 -2.39690185e-01 -7.86417246e-01 2.12312862e-01
1.27016187e+00 5.21030128e-01 6.40137672e-01 7.24927187e-01
2.97992557e-01 9.53186095e-01 1.07114303e+00 1.24543771e-01
3.52814019e-01 9.65290070e-01 -1.37120873e-01 5.80001533e-01
-3.09254706e-01 -5.60747236e-02 1.81144968e-01 9.76826072e-01
-1.16668150e-01 -6.83573633e-02 -1.23732948e+00 6.77370608e-01
-1.93354976e+00 -1.28987932e+00 -4.94755208e-01 1.84445202e+00
1.45555043e+00 -7.31679611e-03 -2.34360799e-01 1.20245136e-01
1.21192157e+00 -9.79120135e-02 1.66856900e-01 -6.45639479e-01
-6.64331794e-01 1.28033474e-01 1.06415734e-01 8.61631513e-01
-8.84705901e-01 9.75446939e-01 6.57429028e+00 5.89263201e-01
-3.65856379e-01 2.57786781e-01 -4.61243689e-01 -1.09903447e-01
-3.34240407e-01 1.72070384e-01 -1.23962522e+00 2.73942173e-01
9.07339692e-01 -2.89178908e-01 1.89130530e-01 5.95966041e-01
-2.83317238e-01 8.08019638e-02 -1.43762195e+00 8.50232542e-01
-3.86178084e-02 -1.03606236e+00 -4.08516005e-02 -4.23805118e-01
6.56691551e-01 5.31116836e-02 -5.98062277e-01 3.88628870e-01
1.05617082e+00 -6.50510788e-01 7.36610353e-01 3.60792607e-01
7.88058996e-01 -6.87022328e-01 1.17263925e+00 -1.96142510e-01
-1.18072629e+00 -2.17529744e-01 -4.37518507e-01 1.29121989e-01
1.55514568e-01 4.00450587e-01 -1.77646667e-01 9.08990920e-01
1.08132017e+00 3.53003651e-01 -4.92889315e-01 6.72726214e-01
-5.12677491e-01 1.71343148e-01 -1.12406179e-01 4.06419426e-01
-2.71313936e-01 1.62204638e-01 1.00159228e+00 1.74616134e+00
6.21433780e-02 5.30492723e-01 1.53865349e-02 8.04041147e-01
2.39395984e-02 -1.03326939e-01 -4.85041261e-01 3.43002021e-01
1.61164796e+00 1.27206230e+00 -4.06958371e-01 -8.71514454e-02
-3.91910762e-01 3.35169405e-01 6.68815017e-01 5.64941987e-02
-8.11846018e-01 -4.68530297e-01 8.10424924e-01 -2.22379565e-01
-3.39065455e-02 4.54299182e-01 9.83038321e-02 -1.13518512e+00
-5.00740111e-01 -1.22249687e+00 1.35587311e+00 -8.14963818e-01
-1.61450875e+00 7.26756871e-01 5.67702711e-01 -9.44354653e-01
-3.84994268e-01 -4.21617717e-01 -2.64732480e-01 6.21789277e-01
-1.13905668e+00 -8.42871428e-01 -2.48429045e-01 7.62812316e-01
-1.21526979e-02 -1.50210224e-02 1.14205420e+00 5.26003897e-01
-4.39028084e-01 6.22859061e-01 -5.79481542e-01 4.75124598e-01
1.46917605e+00 -1.32571638e+00 -1.24062791e-01 5.97581089e-01
-1.44492686e-01 1.14332187e+00 1.14282537e+00 -8.01217854e-01
-6.79800332e-01 -8.12623203e-01 1.36514914e+00 -7.98920274e-01
9.02864754e-01 5.98343089e-02 -1.05354595e+00 1.14434183e+00
3.28565031e-01 -3.19212466e-01 8.23449433e-01 7.96953797e-01
-9.79708374e-01 3.54149267e-02 -1.23025453e+00 4.29631412e-01
1.49875271e+00 -6.63108706e-01 -1.86175990e+00 -5.59955649e-02
9.18073595e-01 -6.31882131e-01 -1.40243495e+00 7.51489699e-01
1.74995661e-01 -8.64834607e-01 8.92892480e-01 -7.24063694e-01
-5.27691515e-03 -4.11673129e-01 -5.85042000e-01 -1.08900285e+00
-6.75072312e-01 -3.26666623e-01 2.99543943e-02 1.93000972e+00
3.94996613e-01 -4.76374745e-01 2.35165469e-02 6.25409424e-01
-3.52464020e-01 2.79263824e-01 -1.04863906e+00 -7.93144763e-01
2.26945654e-01 -4.92679000e-01 6.31490707e-01 1.70158601e+00
9.89632249e-01 5.78666866e-01 2.32543528e-01 3.70466858e-01
4.83932644e-01 3.69671553e-01 9.78501961e-02 -1.74725986e+00
-7.87799992e-03 -4.57629383e-01 -2.32760787e-01 -1.45321399e-01
5.76994658e-01 -1.03499413e+00 -1.29888967e-01 -1.02900016e+00
4.89138633e-01 -4.68418121e-01 -2.25322589e-01 6.25211835e-01
-2.28745714e-02 -6.65770099e-02 7.26391524e-02 3.63002598e-01
-9.95548904e-01 -1.24142580e-01 8.44812572e-01 7.76150376e-02
-2.15095997e-01 -7.50078738e-01 -8.66014779e-01 8.46358478e-01
3.26135039e-01 -7.66523123e-01 -2.05756724e-01 -2.14666888e-01
5.60472250e-01 2.08488390e-01 -2.13963501e-02 -6.77913964e-01
5.87810516e-01 -1.58450119e-02 -6.02380969e-02 -4.66404676e-01
-2.00485349e-01 -6.40541792e-01 5.95622897e-01 2.84246743e-01
-5.84582448e-01 1.92353576e-01 3.39600384e-01 1.33564681e-01
-3.46414328e-01 -4.44460839e-01 6.49801672e-01 -2.73387507e-02
-7.54674733e-01 -4.82192308e-01 -2.01551631e-01 7.60786474e-01
8.05738688e-01 2.38293663e-01 -9.82656360e-01 1.23375833e-01
-1.03808188e+00 3.63984406e-01 2.83297956e-01 7.59299636e-01
1.32873103e-01 -1.40409088e+00 -7.51653969e-01 -4.04036522e-01
3.54280859e-01 -2.01405823e-01 -3.13602481e-03 8.80062282e-01
-1.08214520e-01 8.52746129e-01 -3.19370002e-01 -3.03874075e-01
-1.41871274e+00 9.06002223e-01 3.20741445e-01 -5.88433206e-01
-4.73803610e-01 4.09437805e-01 9.16145891e-02 -7.97446847e-01
3.87427598e-01 -8.10152516e-02 -7.77278960e-01 4.95828509e-01
5.37035346e-01 4.64336663e-01 7.52942264e-02 -9.14347529e-01
-7.79743850e-01 3.38003248e-01 -1.86640561e-01 -8.26745778e-02
1.00751221e+00 -2.43664458e-01 -4.25860912e-01 3.09645325e-01
6.14520788e-01 3.59711140e-01 -4.34983104e-01 -2.93136179e-01
7.42429614e-01 -1.63311839e-01 -2.71324158e-01 -1.20067537e+00
-6.54308200e-01 2.43341893e-01 3.21479887e-01 2.29084387e-01
8.14380944e-01 4.97042745e-01 -4.83741127e-02 4.06692088e-01
6.34228647e-01 -1.09268975e+00 -4.12072420e-01 7.80184388e-01
1.11284137e+00 -7.08377540e-01 -2.49403957e-02 -6.89256489e-01
-6.59658849e-01 9.69707727e-01 7.70508051e-01 2.26899311e-01
2.20705837e-01 8.17066789e-01 2.37464849e-02 -4.71150130e-01
-9.34038699e-01 -2.82930762e-01 1.36767477e-01 7.10478723e-01
7.65870750e-01 -2.72596311e-02 -1.21313202e+00 1.46466506e+00
-5.77518642e-01 -3.05830836e-01 3.48241121e-01 4.47834432e-01
-7.90847540e-02 -1.18931627e+00 -6.03781462e-01 -1.42993316e-01
-7.09204257e-01 -4.90962341e-02 -6.07652426e-01 1.35820735e+00
2.15087414e-01 1.06683636e+00 3.70362073e-01 -3.23721468e-01
8.36530626e-01 1.01290457e-01 4.38295990e-01 -5.76789021e-01
-7.21583545e-01 -2.38161683e-01 8.77654195e-01 -8.05290222e-01
-7.35964060e-01 -7.94258118e-01 -1.47330296e+00 -4.03739095e-01
-5.92194617e-01 7.83060730e-01 -1.29158229e-01 9.40145969e-01
7.91409165e-02 4.26730007e-01 1.21212322e-02 -1.62182659e-01
-3.43369186e-01 -1.05020821e+00 -5.24896562e-01 1.12440670e+00
-2.39118576e-01 -1.07718778e+00 -4.60107863e-01 -3.29579204e-01] | [9.285439491271973, 9.563652038574219] |
9bea17fa-865f-4b09-8fd8-a9e2c70af64b | efficient-contextformer-spatio-channel-window | 2306.14287 | null | https://arxiv.org/abs/2306.14287v1 | https://arxiv.org/pdf/2306.14287v1.pdf | Efficient Contextformer: Spatio-Channel Window Attention for Fast Context Modeling in Learned Image Compression | In this work, we introduce Efficient Contextformer (eContextformer) for context modeling in lossy learned image compression, which is built upon our previous work, Contextformer. The eContextformer combines the recent advancements in efficient transformers and fast context models with the spatio-channel attention mechanism. The proposed model enables content-adaptive exploitation of the spatial and channel-wise latent dependencies for a high performance and efficient entropy modeling. By incorporating several innovations, the eContextformer features improved decoding speed, model complexity and rate-distortion performance over previous work. For instance, compared to Contextformer, the eContextformer requires 145x less model complexity, 210x less decoding speed and achieves higher average bit savings on the Kodak, CLIC2020 and Tecnick datasets. Compared to the standard Versatile Video Coding (VVC) Test Model (VTM) 16.2, the proposed model provides up to 17.1% bitrate savings and surpasses various learning-based models. | ['Eckehard Steinbach', 'Elena Alshina', 'Atanas Boev', 'Panqi Jia', 'A. Burakhan Koyuncu'] | 2023-06-25 | null | null | null | null | ['image-compression'] | ['computer-vision'] | [ 3.79994214e-01 -3.62761766e-01 -1.79429665e-01 -1.53495535e-01
-7.14393020e-01 1.08842507e-01 4.63339388e-01 1.38318419e-01
-5.74717104e-01 8.82348657e-01 6.84101880e-01 -4.51844066e-01
-2.34678835e-01 -2.77757853e-01 -6.05154335e-01 -6.33656740e-01
-4.28911448e-01 -3.60521019e-01 -8.31929147e-02 1.39227480e-01
5.71258307e-01 1.11174710e-01 -1.41197693e+00 4.73709077e-01
6.84126139e-01 1.41038883e+00 9.03705299e-01 1.17525423e+00
-1.80976447e-02 1.16423464e+00 -3.87013018e-01 -3.77952576e-01
5.00007160e-03 -3.71130854e-01 -7.24304438e-01 -3.34693223e-01
5.24093270e-01 -5.86631775e-01 -7.79681861e-01 9.51078475e-01
6.86646342e-01 -4.26235050e-02 4.87583399e-01 -8.27230632e-01
-5.35961747e-01 4.61078882e-01 -5.71805120e-01 6.84974074e-01
2.78057128e-01 -1.50005579e-01 1.04725826e+00 -9.49094057e-01
5.28328180e-01 9.97682393e-01 5.67419767e-01 3.83396953e-01
-9.12409604e-01 -7.63829470e-01 1.53088242e-01 9.30019021e-01
-1.52624273e+00 -5.75942755e-01 6.38495862e-01 1.24875262e-01
1.58263612e+00 4.52494502e-01 7.95600414e-01 1.25184917e+00
8.08732748e-01 9.66701746e-01 8.14283133e-01 -5.36135614e-01
4.44581807e-01 -1.05678663e-01 -4.23238188e-01 5.57024777e-01
2.64057964e-02 2.61868298e-01 -8.46431911e-01 6.85620308e-02
8.30246150e-01 -1.49531990e-01 -5.98237038e-01 3.64127150e-03
-9.65465188e-01 5.85252464e-01 3.47896129e-01 2.86349714e-01
-2.65986294e-01 6.92222953e-01 5.48372626e-01 3.45240206e-01
4.11635667e-01 1.19418755e-01 -2.46564135e-01 -6.52096927e-01
-1.50256741e+00 -5.03316820e-02 6.66417360e-01 1.46655059e+00
9.07354429e-02 4.27521288e-01 -2.51559556e-01 8.19233656e-01
7.00030684e-01 4.96076673e-01 7.98089743e-01 -1.10403395e+00
8.48895848e-01 -1.10766694e-01 -2.13597849e-01 -9.89103675e-01
-1.40737712e-01 -8.42374086e-01 -1.03224444e+00 5.05450601e-03
-4.12355781e-01 2.20216677e-01 -8.33662629e-01 1.43888652e+00
-4.64432746e-01 6.02032006e-01 -1.02946451e-02 7.27162778e-01
6.12437665e-01 8.72601151e-01 3.76925290e-01 -4.87765998e-01
1.02346349e+00 -1.01822758e+00 -9.65546250e-01 -1.95098594e-01
4.06818509e-01 -9.34286356e-01 8.26608300e-01 7.11225510e-01
-1.28572416e+00 -4.81132209e-01 -1.52776265e+00 -2.65640438e-01
-1.79992288e-01 -1.52179942e-01 4.90119785e-01 6.93091869e-01
-1.33806455e+00 7.11491823e-01 -5.93088329e-01 -1.74726069e-01
6.12586141e-01 2.37994999e-01 -2.29848046e-02 -3.60006034e-01
-9.50685561e-01 5.72089791e-01 4.50463861e-01 -5.09756029e-01
-1.03415251e+00 -6.71044588e-01 -8.66270602e-01 5.29992878e-01
1.43015936e-01 -6.72981620e-01 1.12442505e+00 -7.68604279e-01
-1.50332820e+00 2.49628186e-01 -1.78552821e-01 -1.00013375e+00
2.90822297e-01 -5.45406580e-01 -4.81290907e-01 5.42124271e-01
-5.90553701e-01 8.43275905e-01 1.02866387e+00 -9.56185162e-01
-7.25203633e-01 1.95252508e-01 -2.07336813e-01 4.26268011e-01
-4.76630241e-01 -1.03089981e-01 -8.09903562e-01 -1.30085444e+00
-6.94276914e-02 -4.18441772e-01 -5.51072583e-02 2.62908638e-01
1.47921264e-01 3.89705062e-01 1.38333952e+00 -8.86719763e-01
1.80870724e+00 -2.24424124e+00 1.65993959e-01 -1.60265580e-01
2.78534412e-01 5.70214212e-01 -2.64070034e-01 2.94771552e-01
-2.21851356e-02 1.77444994e-01 -2.43342414e-01 -7.26873875e-01
-1.64640062e-02 3.71680826e-01 -1.47405922e-01 2.70047098e-01
-2.76320696e-01 9.22889411e-01 -7.17053771e-01 -6.35846496e-01
6.91644132e-01 8.50407958e-01 -1.07859313e+00 9.16756094e-02
-9.46624875e-02 -1.09923132e-01 4.54453193e-02 8.40991497e-01
6.46392465e-01 -1.51422858e-01 1.24176808e-01 -7.79071599e-02
1.86037898e-01 7.26021975e-02 -8.60424042e-01 2.08413935e+00
-8.98381293e-01 1.15946352e+00 1.94984779e-01 -8.63914490e-01
5.06433010e-01 5.37671566e-01 3.68779898e-01 -9.73930538e-01
2.01033384e-01 1.56328976e-01 -4.29924548e-01 -6.56394362e-01
9.10606682e-01 4.72741462e-02 4.41297293e-01 -8.13639089e-02
6.10039055e-01 1.68065667e-01 -8.31475258e-02 3.22866887e-01
1.05982530e+00 -5.08520044e-02 5.51438272e-01 -2.59893268e-01
4.10224825e-01 -9.10386503e-01 4.33084339e-01 7.14358389e-01
-3.86544108e-01 5.56622207e-01 2.65842453e-02 -1.46678969e-01
-1.14896846e+00 -9.66084599e-01 -1.75534919e-01 7.18727052e-01
3.06797177e-01 -1.04303241e+00 -4.58821267e-01 -4.16199654e-01
-3.71052176e-01 8.38882744e-01 -2.33243719e-01 -8.15204605e-02
-4.21880573e-01 -5.00678718e-01 4.29334491e-01 5.05260229e-01
9.65983510e-01 -7.93253303e-01 -7.74475634e-01 3.21992040e-01
-4.18184817e-01 -1.14041400e+00 -4.47057962e-01 1.07423857e-01
-1.15052760e+00 -5.97914577e-01 -7.26109445e-01 -6.43294752e-01
8.14347044e-02 3.06379553e-02 1.20402431e+00 3.36957797e-02
-3.57218057e-01 5.42012691e-01 -5.97586036e-01 -1.34248063e-01
8.22836068e-03 -1.71187669e-01 -2.97124088e-01 -3.07825118e-01
-1.65226441e-02 -8.12780321e-01 -8.98936868e-01 -1.08576626e-01
-1.06360686e+00 2.60509849e-01 8.32497835e-01 1.13549817e+00
9.10166502e-01 2.57129371e-01 4.96567070e-01 -5.13319016e-01
4.68085736e-01 -6.35344148e-01 -4.11277235e-01 1.94941819e-01
-1.14129984e+00 7.65237436e-02 5.65406442e-01 -1.45955965e-01
-1.12737453e+00 -2.82636195e-01 -5.12816250e-01 -6.08619511e-01
1.67425543e-01 5.08997560e-01 -1.56078234e-01 -3.86495829e-01
1.95440903e-01 5.31849921e-01 -4.95610476e-01 -5.15757859e-01
1.80262148e-01 6.02031410e-01 5.63778102e-01 -2.16075912e-01
2.07787976e-01 5.27095981e-02 2.55213697e-02 -9.72173333e-01
6.82764649e-02 -4.12945926e-01 -1.81950495e-01 -1.83710113e-01
7.97467828e-01 -1.09064877e+00 -2.33661249e-01 4.09669310e-01
-8.94077480e-01 -3.32506627e-01 -2.80477643e-01 6.80440664e-01
-8.73118997e-01 6.34874821e-01 -6.71400011e-01 -8.61916721e-01
-6.73804998e-01 -1.17287982e+00 9.44096982e-01 8.11180845e-03
6.58416152e-02 -1.14402843e+00 -4.72321004e-01 -8.75019934e-03
9.56776857e-01 -1.06552385e-01 8.09612095e-01 2.25061364e-02
-8.44478667e-01 -4.55640517e-02 -3.52344066e-01 5.03339827e-01
-3.18494081e-01 -5.46516478e-01 -9.08162475e-01 -5.66677272e-01
2.64655918e-01 -1.87314257e-01 1.06506515e+00 6.34984791e-01
1.70330119e+00 -6.26770616e-01 -1.08857021e-01 1.31181455e+00
1.98951244e+00 4.92355525e-01 1.07272387e+00 2.67625004e-01
3.26060563e-01 -2.74948776e-01 3.12717408e-01 7.20403910e-01
2.66517043e-01 6.57691360e-01 6.17891729e-01 1.83701381e-01
-6.24816000e-01 -3.49638492e-01 3.62535894e-01 1.18698585e+00
-5.59733100e-02 -5.86600780e-01 -5.32470882e-01 4.23987001e-01
-1.49387753e+00 -1.15249920e+00 4.39809412e-01 1.89389420e+00
6.96270764e-01 2.50699192e-01 -6.20103419e-01 3.94415826e-01
1.62491128e-01 4.54687834e-01 -5.36688209e-01 -6.11739337e-01
-8.68871883e-02 4.34524000e-01 7.08983183e-01 6.50622547e-01
-1.00464189e+00 5.53633094e-01 6.88968277e+00 1.34967077e+00
-1.01524818e+00 3.56224895e-01 7.21349776e-01 -6.83941960e-01
-2.72359133e-01 -2.04723656e-01 -4.57181007e-01 7.10595250e-01
1.38330400e+00 -3.16486955e-01 6.99552774e-01 9.60768759e-01
3.88314463e-02 -1.87000021e-01 -9.20138597e-01 1.62461782e+00
4.43664700e-01 -1.49808133e+00 8.07011798e-02 1.23568229e-01
6.49435103e-01 1.06448919e-01 3.52956176e-01 3.75531733e-01
-2.73966789e-01 -1.03625166e+00 7.77036667e-01 5.16864061e-01
1.23026669e+00 -8.84021938e-01 9.30770278e-01 -4.97152060e-02
-1.32253754e+00 -5.77908576e-01 -3.88904393e-01 8.53317678e-02
2.80005276e-01 4.62152630e-01 -4.56368566e-01 7.09144652e-01
8.84357452e-01 8.80152583e-01 -5.64639449e-01 1.41298521e+00
-2.37431191e-02 9.31446254e-01 -2.12509170e-01 2.36903682e-01
1.44240603e-01 3.40726465e-01 6.99219108e-01 1.66303623e+00
6.39378726e-01 2.62612730e-01 -2.70794719e-01 2.73141474e-01
-2.02320963e-01 7.94993937e-02 -3.47094417e-01 3.11826408e-01
4.88211244e-01 6.03711665e-01 -2.55645037e-01 -5.09560645e-01
-4.07897770e-01 1.35070491e+00 -8.32747146e-02 5.93202472e-01
-9.78299320e-01 -5.79581857e-01 4.59585726e-01 -1.14662342e-01
6.48479819e-01 -3.93409908e-01 -5.08664727e-01 -1.22243929e+00
-4.23478372e-02 -7.29499638e-01 2.63808548e-01 -1.04534197e+00
-5.15077591e-01 5.79469681e-01 2.51104176e-01 -1.27465928e+00
-1.40336677e-01 -4.10323322e-01 -1.80517286e-01 7.78756022e-01
-1.96792173e+00 -8.30231905e-01 -2.42220923e-01 5.44208288e-01
1.05457199e+00 -4.97279614e-01 7.86021650e-01 7.01840043e-01
-2.30847880e-01 1.03710151e+00 3.99333119e-01 -4.94775116e-01
4.00910079e-01 -9.78697956e-01 7.34073445e-02 1.02301121e+00
2.12721154e-01 3.04065526e-01 5.77669442e-01 -4.24585789e-01
-1.32807934e+00 -1.24858260e+00 1.00028563e+00 2.12741077e-01
2.92543888e-01 -2.08312720e-01 -5.32153070e-01 4.77275074e-01
6.41862929e-01 -5.93416654e-02 7.86621869e-01 -4.10834134e-01
-2.87603676e-01 -1.41883522e-01 -1.37325847e+00 5.99196434e-01
1.19745982e+00 -6.40481472e-01 -3.59116137e-01 -3.24236825e-02
8.51788938e-01 -4.26245838e-01 -8.15107882e-01 2.80570805e-01
7.04030693e-01 -1.10186231e+00 9.20516431e-01 1.07568629e-01
6.38096035e-01 3.67143862e-02 -9.28586900e-01 -9.00872052e-01
-5.07925093e-01 -6.37831450e-01 -8.73757303e-01 1.00539243e+00
-2.76576560e-02 -2.25810617e-01 6.09846294e-01 2.31713250e-01
-2.68436134e-01 -1.11703968e+00 -1.46700013e+00 -8.31085801e-01
-1.79878429e-01 -8.83690178e-01 4.56416845e-01 5.01174033e-01
1.35706253e-02 -8.27453211e-02 -8.01277936e-01 -6.97255880e-02
6.92451715e-01 -4.35345203e-01 -9.09718350e-02 -3.55228812e-01
-5.75049460e-01 -5.30249536e-01 -8.51333141e-01 -1.48170102e+00
-3.48825753e-01 -8.84579480e-01 -2.84807503e-01 -1.29464936e+00
1.54208392e-01 -3.36857975e-01 -7.82501996e-01 2.61567354e-01
-7.45351193e-03 2.92147279e-01 4.91552085e-01 -1.96068715e-02
-8.50023806e-01 9.81003106e-01 8.90850842e-01 -3.36821318e-01
1.98259234e-01 -4.09953117e-01 -5.59620202e-01 3.93342167e-01
7.86548913e-01 -2.19142690e-01 -7.54963815e-01 -8.36863399e-01
-7.96873122e-02 1.42901510e-01 2.68288046e-01 -1.59163558e+00
2.92544067e-01 2.40916580e-01 5.73256135e-01 -6.53326511e-01
5.47977090e-01 -1.11585021e+00 1.56806722e-01 5.59685588e-01
-3.56364757e-01 1.51130155e-01 4.30909038e-01 9.58095551e-01
-3.00834179e-01 -2.24721715e-01 7.87445128e-01 -7.48439059e-02
-1.10822511e+00 2.47072682e-01 -4.56840128e-01 -2.53396839e-01
8.20868134e-01 -2.60704488e-01 -1.45819589e-01 -6.04545295e-01
-6.47470474e-01 -5.35097010e-02 2.21602634e-01 2.88347393e-01
1.30240023e+00 -1.42265534e+00 -5.55413306e-01 3.90176326e-01
-2.26400033e-01 -5.04125178e-01 5.15983224e-01 6.06557369e-01
-7.06778109e-01 8.39837015e-01 -1.08467788e-01 -4.95220959e-01
-1.43155241e+00 4.56754446e-01 6.74025118e-02 -4.40327078e-01
-7.10231483e-01 1.11303782e+00 -5.76354899e-02 7.10337222e-01
6.23655558e-01 -4.56734240e-01 -7.01181963e-02 -5.21151423e-01
9.49609816e-01 4.09271210e-01 1.19081669e-01 -4.32709277e-01
-1.27886280e-01 3.68601292e-01 -1.29452720e-01 -1.64286762e-01
1.31407320e+00 -5.12781858e-01 4.00969535e-01 9.39778164e-02
1.43006659e+00 -2.37848848e-01 -1.41300690e+00 -1.09033510e-01
-2.11280629e-01 -8.60461950e-01 6.85073078e-01 -1.19155276e+00
-1.20968068e+00 8.36445630e-01 1.18637025e+00 -2.18423039e-01
1.81833553e+00 -4.19458389e-01 8.63792717e-01 1.53092310e-01
5.42551756e-01 -1.19045687e+00 1.11500129e-01 6.06223106e-01
1.09802616e+00 -1.00578558e+00 3.00911307e-01 2.24017333e-02
-3.24855715e-01 9.77790654e-01 3.37794870e-01 1.99433476e-01
9.72885132e-01 4.29634184e-01 -4.13228989e-01 1.50297776e-01
-1.20851350e+00 2.57751822e-01 2.08323747e-01 7.53077030e-01
3.60492349e-01 -7.86042139e-02 -4.07559276e-01 4.59243923e-01
-1.66979790e-01 2.36794323e-01 3.18455130e-01 9.86520231e-01
-4.54850376e-01 -9.91091132e-01 -2.09104866e-01 5.75870514e-01
-8.03286970e-01 -7.17552006e-01 4.49349016e-01 4.35170740e-01
2.20651746e-01 9.48986351e-01 -1.34135364e-02 -7.30483651e-01
-6.38705939e-02 -4.78865430e-02 5.05444765e-01 -1.64603651e-01
-2.78667331e-01 1.57281786e-01 5.40751405e-02 -8.70198309e-01
-3.95444155e-01 -4.21109229e-01 -6.92454219e-01 -2.95016855e-01
-3.22049499e-01 -2.05053255e-01 9.50070798e-01 7.63275862e-01
6.89001560e-01 7.76251376e-01 3.96141738e-01 -8.89797270e-01
-2.18700934e-02 -9.32252526e-01 -5.45565665e-01 4.52921912e-02
4.44055647e-01 -5.22896886e-01 -1.41585782e-01 3.21357638e-01] | [11.406956672668457, -1.585604190826416] |
011b818f-7edd-42f8-9a3a-8514b9c68768 | neural-scene-flow-prior | 2111.01253 | null | https://arxiv.org/abs/2111.01253v1 | https://arxiv.org/pdf/2111.01253v1.pdf | Neural Scene Flow Prior | Before the deep learning revolution, many perception algorithms were based on runtime optimization in conjunction with a strong prior/regularization penalty. A prime example of this in computer vision is optical and scene flow. Supervised learning has largely displaced the need for explicit regularization. Instead, they rely on large amounts of labeled data to capture prior statistics, which are not always readily available for many problems. Although optimization is employed to learn the neural network, the weights of this network are frozen at runtime. As a result, these learning solutions are domain-specific and do not generalize well to other statistically different scenarios. This paper revisits the scene flow problem that relies predominantly on runtime optimization and strong regularization. A central innovation here is the inclusion of a neural scene flow prior, which uses the architecture of neural networks as a new type of implicit regularizer. Unlike learning-based scene flow methods, optimization occurs at runtime, and our approach needs no offline datasets -- making it ideal for deployment in new environments such as autonomous driving. We show that an architecture based exclusively on multilayer perceptrons (MLPs) can be used as a scene flow prior. Our method attains competitive -- if not better -- results on scene flow benchmarks. Also, our neural prior's implicit and continuous scene flow representation allows us to estimate dense long-term correspondences across a sequence of point clouds. The dense motion information is represented by scene flow fields where points can be propagated through time by integrating motion vectors. We demonstrate such a capability by accumulating a sequence of lidar point clouds. | ['Simon Lucey', 'Jhony Kaesemodel Pontes', 'Xueqian Li'] | 2021-11-01 | null | http://proceedings.neurips.cc/paper/2021/hash/41263b9a46f6f8f22668476661614478-Abstract.html | http://proceedings.neurips.cc/paper/2021/file/41263b9a46f6f8f22668476661614478-Paper.pdf | neurips-2021-12 | ['scene-flow-estimation'] | ['computer-vision'] | [ 1.54725850e-01 -1.92808792e-01 -2.86717564e-01 -5.57756364e-01
-1.50242910e-01 -4.73728240e-01 7.41043210e-01 1.65514126e-01
-7.28424668e-01 6.09919667e-01 -1.38501097e-02 -1.99394122e-01
4.25737957e-03 -9.30237412e-01 -9.42099154e-01 -6.64610028e-01
1.28212152e-02 5.33439517e-01 4.08493310e-01 -1.69571444e-01
3.22195023e-01 8.31165433e-01 -1.80761957e+00 -1.20804980e-02
7.80249000e-01 7.42408872e-01 4.14824098e-01 8.34116161e-01
-5.11178017e-01 1.01383090e+00 -3.11037064e-01 -1.02169603e-01
5.63494682e-01 5.91942482e-02 -7.17544198e-01 7.14145005e-02
9.38414931e-01 -4.62139279e-01 -5.36581337e-01 8.06740105e-01
1.90203249e-01 4.82548743e-01 3.76589835e-01 -1.25423872e+00
-2.39916891e-01 2.60411464e-02 -4.64621246e-01 9.70128924e-02
7.44508281e-02 5.80605865e-01 8.79161775e-01 -7.75609910e-01
7.31066644e-01 1.16756177e+00 8.04287612e-01 4.12130475e-01
-1.46976125e+00 -2.74645746e-01 2.84378260e-01 1.90851405e-01
-9.53317404e-01 -4.60457653e-01 1.08876193e+00 -7.73033440e-01
1.07473063e+00 4.51746630e-03 8.03225636e-01 9.05850887e-01
2.32099332e-02 6.22138798e-01 7.06494689e-01 -3.35867196e-01
3.76839608e-01 1.70932323e-01 1.92477763e-01 7.68442929e-01
1.73590109e-01 4.16089654e-01 -3.86226296e-01 2.11916938e-01
9.29623485e-01 1.38219908e-01 -3.31902355e-01 -6.49941444e-01
-1.07443738e+00 8.97522748e-01 7.54383028e-01 1.89144854e-02
-1.65553927e-01 5.87905705e-01 3.34373564e-01 1.66208833e-01
4.11343008e-01 3.39502752e-01 -4.04781342e-01 -2.27148533e-01
-1.13914561e+00 1.41490310e-01 9.20256555e-01 7.96608090e-01
1.47282374e+00 2.17558756e-01 1.54216081e-01 6.34953201e-01
4.22792315e-01 5.34728944e-01 1.20167695e-01 -1.50919807e+00
3.56164873e-01 4.77649003e-01 7.28393123e-02 -1.19598651e+00
-3.34324211e-01 -4.21879649e-01 -7.82764733e-01 8.10843706e-01
7.05012739e-01 -5.56659885e-02 -9.88192499e-01 1.72788680e+00
3.21515828e-01 7.25913346e-01 -1.23412639e-01 9.79751587e-01
4.81034666e-01 6.76970959e-01 -1.04874745e-01 4.05663718e-03
7.58816242e-01 -9.88042772e-01 -3.51634145e-01 -3.80068630e-01
5.75931549e-01 -6.67646706e-01 1.14095414e+00 3.04113358e-01
-9.67716575e-01 -7.17252016e-01 -9.87061560e-01 -4.00410354e-01
-4.37417865e-01 -3.04547250e-01 8.93499970e-01 5.44351339e-01
-1.19143164e+00 7.42850542e-01 -1.03175676e+00 -3.42871666e-01
6.29941761e-01 2.93951243e-01 -3.00501913e-01 -1.36783108e-01
-6.45612121e-01 9.46156263e-01 1.73709169e-01 3.17216098e-01
-8.20510864e-01 -1.02420247e+00 -1.08366573e+00 -3.84821184e-02
1.09804578e-01 -1.09703743e+00 1.02178192e+00 -1.06035602e+00
-1.73715127e+00 7.38396943e-01 -4.52549428e-01 -5.60249209e-01
6.84741795e-01 -2.36434460e-01 1.93026066e-01 1.50407508e-01
1.49917584e-02 1.05037749e+00 8.85609984e-01 -1.46082532e+00
-5.70793748e-01 1.80207584e-02 3.85723382e-01 -7.53680663e-03
-4.22141366e-02 -3.64972860e-01 -4.13654804e-01 -1.82405069e-01
-1.14417486e-01 -8.61368477e-01 -5.39316773e-01 3.33981276e-01
-7.67541230e-02 9.02488977e-02 1.00269425e+00 -2.09411740e-01
6.91778302e-01 -1.98433065e+00 -7.77257681e-02 5.54383993e-02
2.09103152e-01 2.45778963e-01 -1.14528991e-01 1.42318457e-01
2.22857241e-02 -1.36939704e-01 -7.15538442e-01 -7.77738214e-01
-6.73112497e-02 7.12702572e-01 -5.13838112e-01 6.92803919e-01
4.59077716e-01 8.34592938e-01 -1.07265425e+00 -3.03777754e-01
8.02325368e-01 6.70876086e-01 -9.49452579e-01 6.22569174e-02
-4.75181192e-01 7.09966600e-01 -4.90123183e-02 2.53859878e-01
8.52132440e-01 -3.02206963e-01 -2.71312028e-01 -1.21531695e-01
-4.81389135e-01 2.85838276e-01 -1.25952065e+00 2.20624542e+00
-5.86573184e-01 9.88913596e-01 1.79880619e-01 -1.19372237e+00
7.97212601e-01 -6.99883029e-02 8.38700414e-01 -4.61578280e-01
1.02442518e-01 5.47282845e-02 -7.16710612e-02 -4.73210186e-01
5.99318445e-01 -1.02285750e-01 4.16376084e-01 1.93543449e-01
1.48084283e-01 -4.64270860e-01 4.62952554e-01 1.30460024e-01
1.10289025e+00 6.46025836e-01 -2.32986704e-01 -2.91515291e-01
6.59036875e-01 4.23332006e-01 8.44165146e-01 8.24288011e-01
-1.74496114e-01 7.77538359e-01 1.98805794e-01 -7.54334509e-01
-1.12634218e+00 -9.92793381e-01 -2.74525374e-01 7.89884865e-01
2.62254626e-01 -2.65580922e-01 -4.39060152e-01 -4.52881396e-01
1.75407812e-01 5.86056232e-01 -3.43460530e-01 1.09038241e-01
-8.78515661e-01 -5.66102266e-01 3.00141782e-01 5.17006397e-01
4.60998833e-01 -1.02600777e+00 -9.61300135e-01 4.15173233e-01
7.27066472e-02 -1.26913249e+00 -1.56972751e-01 2.24250272e-01
-1.03702796e+00 -1.12207985e+00 -3.86813134e-01 -4.34220642e-01
6.74875855e-01 2.67075568e-01 1.24453104e+00 -4.32807021e-02
-4.57378000e-01 7.29534149e-01 9.37117636e-02 -3.57367694e-01
-2.15407804e-01 -1.32335708e-01 -2.99216006e-02 1.08839989e-01
2.67743856e-01 -1.05024219e+00 -6.01066709e-01 -2.76543777e-02
-7.78288126e-01 -4.29601409e-02 2.87402064e-01 7.38186300e-01
4.25104499e-01 -2.44761437e-01 7.65223801e-02 -8.71299565e-01
1.50737390e-01 -3.21739882e-01 -1.01416981e+00 -1.96767077e-01
-3.61445457e-01 1.58987865e-01 6.36421978e-01 -3.49188030e-01
-1.10608816e+00 3.85047436e-01 -8.01655129e-02 -8.64725173e-01
-3.85469258e-01 3.16956609e-01 1.29787117e-01 -2.53961533e-01
7.43171692e-01 -1.17382370e-01 1.51456386e-01 -3.90034080e-01
6.72432959e-01 4.98787165e-02 7.20220506e-01 -7.90461063e-01
9.81645286e-01 1.00330794e+00 3.03110570e-01 -1.07452631e+00
-6.92001820e-01 -7.55853355e-01 -8.64295065e-01 -2.94242352e-01
8.43293846e-01 -8.26908052e-01 -8.34274411e-01 3.35544646e-01
-1.48723042e+00 -6.91056967e-01 -7.69839525e-01 8.02436650e-01
-7.49472201e-01 4.23831254e-01 -5.54044962e-01 -7.44048238e-01
1.32954344e-01 -1.16279733e+00 8.01259935e-01 1.96034223e-01
6.14032112e-02 -1.41835320e+00 3.45787197e-01 4.28473875e-02
4.52982008e-01 3.99430037e-01 4.10025299e-01 1.09171629e-01
-1.05614138e+00 7.42015168e-02 -3.36127281e-01 5.03668368e-01
5.04312962e-02 3.58466655e-01 -1.31384933e+00 -1.24282502e-01
1.25871554e-01 -1.64049029e-01 1.10026419e+00 5.99355698e-01
1.06115758e+00 -6.63201213e-02 -9.76460800e-02 1.20075142e+00
1.65034235e+00 -9.82799381e-02 6.21995807e-01 2.20159307e-01
1.16738594e+00 7.83425868e-01 1.80383340e-01 1.61616221e-01
4.69433129e-01 4.03604358e-01 7.12490201e-01 -1.60837173e-01
-2.80938953e-01 -1.25681147e-01 3.34493816e-01 8.25869739e-01
-3.34760845e-01 3.72429937e-02 -1.06243157e+00 4.84996259e-01
-1.95493114e+00 -1.02904952e+00 -4.60743695e-01 2.15994930e+00
5.88229954e-01 2.03672662e-01 -2.11932242e-01 3.43088731e-02
3.07742923e-01 3.03150386e-01 -6.06162667e-01 -4.85909194e-01
-7.83806443e-02 3.89869303e-01 7.32231259e-01 9.67455983e-01
-1.16256678e+00 1.02452683e+00 6.02767467e+00 2.44277909e-01
-1.41393960e+00 1.15323663e-01 1.93044931e-01 -1.21803865e-01
-3.06216240e-01 3.81585807e-01 -7.43173182e-01 3.23141068e-01
7.47532904e-01 1.72974899e-01 3.66838723e-01 8.51419032e-01
4.55836445e-01 -2.52496690e-01 -1.18075418e+00 1.08348870e+00
-2.84113109e-01 -1.63199174e+00 -7.70096853e-02 1.54636607e-01
6.75844371e-01 5.55796444e-01 -1.78918138e-01 1.15411311e-01
5.45381248e-01 -8.93491387e-01 6.07512355e-01 6.95532441e-01
5.84737837e-01 -4.35377628e-01 3.57529640e-01 5.28998554e-01
-1.05030644e+00 -7.73445331e-03 -5.88337183e-01 -4.02360559e-01
4.74930793e-01 9.39018548e-01 -5.99112034e-01 4.08924460e-01
6.20691895e-01 1.15708363e+00 -2.78343856e-01 1.24509835e+00
-2.15855986e-01 5.88808239e-01 -7.53246665e-01 4.18097496e-01
4.59707201e-01 -4.97275352e-01 6.39598131e-01 1.52924299e+00
1.13262096e-02 -2.72021592e-01 4.54781026e-01 1.00204051e+00
1.42544195e-01 -2.40019262e-01 -9.19198751e-01 3.94219577e-01
7.41004795e-02 1.34672308e+00 -6.05385840e-01 -2.11102918e-01
-5.53007245e-01 5.35056293e-01 4.24653083e-01 6.30784392e-01
-6.96613431e-01 -1.54726326e-01 8.79627645e-01 2.35369653e-01
2.03867972e-01 -7.37581313e-01 -5.02670467e-01 -1.29002702e+00
-8.29855502e-02 -2.00887337e-01 -1.59374401e-02 -5.63979566e-01
-1.28771198e+00 2.40389645e-01 -6.92717358e-02 -1.23606002e+00
-3.24411422e-01 -7.13909507e-01 -7.17279375e-01 9.47809100e-01
-2.09245443e+00 -1.00443590e+00 -6.51989937e-01 7.42653668e-01
3.22561741e-01 1.33774653e-01 5.06330311e-01 5.35208344e-01
-4.15687203e-01 -3.08461376e-02 -2.61842340e-01 1.77380875e-01
6.23949587e-01 -1.35348392e+00 2.35246405e-01 1.06538606e+00
3.56483907e-01 5.86405337e-01 6.53136909e-01 -3.50195289e-01
-1.28070545e+00 -1.07999563e+00 5.88072360e-01 -6.29511476e-01
6.57489061e-01 -3.92552733e-01 -1.02107477e+00 8.02655578e-01
1.87203690e-01 5.54934978e-01 2.52661616e-01 6.22448251e-02
-3.53730112e-01 -3.32878560e-01 -8.80882978e-01 3.74460191e-01
1.24485636e+00 -5.50405443e-01 -4.14593190e-01 1.42666906e-01
7.38151550e-01 -4.67165560e-01 -5.03805876e-01 5.39223433e-01
2.65425056e-01 -1.26024365e+00 1.11286700e+00 -5.40997267e-01
4.25300807e-01 -4.70917135e-01 -5.35807535e-02 -9.89805341e-01
-2.24691018e-01 -6.86777890e-01 -2.82447875e-01 9.70565379e-01
5.93229905e-02 -7.57960796e-01 1.10600615e+00 7.28678048e-01
-4.36679095e-01 -4.09154087e-01 -8.17185044e-01 -7.08349705e-01
1.81293990e-02 -8.90232623e-01 2.61927426e-01 1.16779196e+00
-7.20982313e-01 2.24024042e-01 -1.15933180e-01 1.94604114e-01
8.74607742e-01 -1.63995381e-02 1.17298460e+00 -1.35355365e+00
-3.63845438e-01 -6.46834910e-01 -5.52551687e-01 -1.41853356e+00
4.38952565e-01 -9.70959544e-01 2.94544220e-01 -1.40665352e+00
-4.34352964e-01 -8.01272035e-01 -4.65322435e-02 3.55139822e-01
1.39944494e-01 4.00650464e-02 3.15828651e-01 2.67702341e-01
-2.17081115e-01 5.48444211e-01 1.16179407e+00 -2.14470923e-01
-4.78395820e-01 -1.10962406e-01 -9.54757258e-02 1.10100758e+00
7.52513468e-01 -4.77560550e-01 -6.55016005e-01 -7.70071328e-01
4.85312678e-02 -2.85418212e-01 7.45643020e-01 -1.21076369e+00
5.86135924e-01 -4.04255211e-01 1.24184102e-01 -5.43199539e-01
5.98734856e-01 -8.79606962e-01 4.15344313e-02 3.38613540e-01
3.21407840e-02 -1.20265320e-01 2.21854597e-01 6.55987501e-01
-3.08209866e-01 -2.69475669e-01 8.19048822e-01 -3.13535720e-01
-9.71601129e-01 5.68942726e-01 -9.65594873e-02 1.01068251e-01
7.37498999e-01 -4.63856488e-01 -2.70559430e-01 -1.41560942e-01
-6.30083978e-01 1.70181885e-01 5.41650236e-01 2.24512964e-01
4.87707764e-01 -1.00538659e+00 -5.86829007e-01 2.87734181e-01
-8.37092102e-02 6.98028386e-01 -7.78295323e-02 8.06503177e-01
-8.98098946e-01 1.94937304e-01 -1.54482409e-01 -1.22534263e+00
-6.33576214e-01 4.21425998e-01 4.47209150e-01 -6.92059919e-02
-1.01112878e+00 8.58234167e-01 3.39433551e-01 -5.22819102e-01
1.89609632e-01 -4.91922855e-01 7.91810378e-02 -5.82112409e-02
1.65192887e-01 2.37254173e-01 -6.55274689e-02 -5.54300606e-01
-2.54603386e-01 7.70303190e-01 3.53352040e-01 -2.01012447e-01
1.41656220e+00 -8.91562104e-02 -1.38563782e-01 7.26981997e-01
1.34754884e+00 6.98237792e-02 -1.93349886e+00 -1.70480981e-01
5.87722547e-02 -7.08615899e-01 1.46788388e-01 -1.70849025e-01
-1.19168937e+00 1.29479110e+00 2.76497185e-01 5.87781630e-02
8.08135271e-01 -4.24095064e-01 6.00923598e-01 5.50592005e-01
3.98065299e-01 -9.44540262e-01 -7.37000480e-02 8.99785638e-01
5.97315013e-01 -1.45691335e+00 -1.36074200e-01 -3.73500139e-01
-1.60661772e-01 1.22157240e+00 4.86717373e-01 -5.96889615e-01
8.82728875e-01 4.66597915e-01 1.25705585e-01 9.66961682e-03
-6.85817003e-01 -4.55807716e-01 7.25049749e-02 6.92866623e-01
1.51320055e-01 -3.75556350e-01 2.22619340e-01 -3.42365623e-01
-2.39396080e-01 1.91598237e-01 5.19292831e-01 1.00999558e+00
-4.22862768e-01 -1.16914761e+00 -1.19556703e-01 2.09707439e-01
1.22408584e-01 5.47522195e-02 1.64881304e-01 7.16263413e-01
3.87986630e-01 7.80424297e-01 3.91692758e-01 -2.51451414e-02
3.01644772e-01 -1.04795285e-01 6.61002696e-01 -6.67508245e-01
-4.40536588e-01 -2.15547681e-01 -1.94026098e-01 -1.00225890e+00
-8.00137401e-01 -5.73924482e-01 -1.32389045e+00 -5.40237129e-01
4.51007448e-02 -9.67020839e-02 8.65086615e-01 8.16237032e-01
2.37405375e-01 5.01142323e-01 4.55134958e-01 -1.30832386e+00
-1.22749157e-01 -4.51991826e-01 -2.30976358e-01 4.52226818e-01
7.94566572e-01 -8.05457950e-01 -5.41700065e-01 3.92953694e-01] | [8.55419635772705, -2.0664303302764893] |
d1c35b42-0f69-4e08-a64b-c59bc68bdb5e | how-many-events-do-you-need-event-based | 2206.13673 | null | https://arxiv.org/abs/2206.13673v3 | https://arxiv.org/pdf/2206.13673v3.pdf | How Many Events do You Need? Event-based Visual Place Recognition Using Sparse But Varying Pixels | Event cameras continue to attract interest due to desirable characteristics such as high dynamic range, low latency, virtually no motion blur, and high energy efficiency. One of the potential applications that would benefit from these characteristics lies in visual place recognition for robot localization, i.e. matching a query observation to the corresponding reference place in the database. In this letter, we explore the distinctiveness of event streams from a small subset of pixels (in the tens or hundreds). We demonstrate that the absolute difference in the number of events at those pixel locations accumulated into event frames can be sufficient for the place recognition task, when pixels that display large variations in the reference set are used. Using such sparse (over image coordinates) but varying (variance over the number of events per pixel location) pixels enables frequent and computationally cheap updates of the location estimates. Furthermore, when event frames contain a constant number of events, our method takes full advantage of the event-driven nature of the sensory stream and displays promising robustness to changes in velocity. We evaluate our proposed approach on the Brisbane-Event-VPR dataset in an outdoor driving scenario, as well as the newly contributed indoor QCR-Event-VPR dataset that was captured with a DAVIS346 camera mounted on a mobile robotic platform. Our results show that our approach achieves competitive performance when compared to several baseline methods on those datasets, and is particularly well suited for compute- and energy-constrained platforms such as interplanetary rovers. | ['Michael Milford', 'Tobias Fischer'] | 2022-06-28 | null | null | null | null | ['visual-place-recognition'] | ['computer-vision'] | [ 1.77965894e-01 -6.40614629e-01 -1.26584828e-01 -3.33364964e-01
-7.44295597e-01 -6.43306017e-01 7.48054683e-01 3.30769777e-01
-7.74104059e-01 6.25345230e-01 -1.54019088e-01 1.56014815e-01
-2.30636343e-01 -7.43034184e-01 -9.73566771e-01 -7.77745664e-01
-5.20327687e-01 1.70748055e-01 7.76971340e-01 -1.76305950e-01
2.86013156e-01 9.10821617e-01 -1.98446083e+00 -2.68264443e-01
4.71644878e-01 1.30539572e+00 5.09676576e-01 6.39488161e-01
4.04767543e-01 8.11176896e-01 -4.32216883e-01 1.89867482e-01
4.52737272e-01 -3.49564925e-02 -1.52661413e-01 -3.87769602e-02
4.08365011e-01 -2.00263858e-01 -7.89812982e-01 7.35893786e-01
3.84564966e-01 7.41248012e-01 3.60200912e-01 -1.41876471e+00
1.44744977e-01 -1.80078775e-01 -6.33358657e-01 6.85471952e-01
4.34022069e-01 2.98989058e-01 6.32047415e-01 -8.11019659e-01
9.01916087e-01 6.95427477e-01 5.34984410e-01 1.03908256e-02
-9.33683574e-01 -5.08874536e-01 4.01596911e-02 6.65456295e-01
-1.62794447e+00 -6.29832506e-01 6.53053343e-01 -2.91225970e-01
1.22959185e+00 1.85363844e-01 5.15146673e-01 9.03796911e-01
4.96305943e-01 2.99625039e-01 7.01907754e-01 -4.61361073e-02
5.61873257e-01 -1.24595821e-01 -1.86102226e-01 4.74379927e-01
2.87132770e-01 2.85773486e-01 -1.12729657e+00 -1.12971544e-01
4.65154052e-01 3.64369482e-01 -4.45002705e-01 -5.72638214e-01
-1.61818373e+00 5.93038201e-01 5.08866787e-01 -7.90223181e-02
-7.12449372e-01 5.57571530e-01 2.56130308e-01 -5.93165345e-02
-4.84394096e-02 1.15848668e-01 -1.44543707e-01 -5.28455496e-01
-8.30307186e-01 6.49120435e-02 4.67434049e-01 1.23181474e+00
1.03109074e+00 6.38586879e-02 8.42014253e-02 3.97683531e-01
2.43652597e-01 9.05122697e-01 4.88104582e-01 -1.08300531e+00
5.82439780e-01 1.90796971e-01 4.08285528e-01 -1.24789548e+00
-3.03639889e-01 2.40609590e-02 -5.49727857e-01 3.00003618e-01
3.18379402e-01 4.58002230e-03 -6.52321339e-01 1.58546519e+00
4.31593925e-01 4.04431581e-01 3.23727459e-01 1.12184906e+00
4.61789489e-01 8.48483086e-01 -1.07913189e-01 -1.65784046e-01
1.45774460e+00 -3.53813946e-01 -4.96559501e-01 -5.76113045e-01
1.74617842e-01 -5.04633665e-01 5.90758860e-01 1.59142807e-01
-7.15854704e-01 -5.15153110e-01 -1.33425653e+00 3.21849398e-02
-4.32326347e-01 1.48481494e-02 5.46013534e-01 3.30521554e-01
-8.20795894e-01 2.84249067e-01 -1.00195491e+00 -7.29672849e-01
7.96583146e-02 3.14404488e-01 -4.74007577e-01 -1.63361728e-01
-9.43656385e-01 6.99813068e-01 3.83781463e-01 6.73487666e-04
-9.55605805e-01 -5.43070436e-01 -1.02942979e+00 8.02740641e-03
2.73250908e-01 -2.97082782e-01 1.08767414e+00 -6.09962821e-01
-1.09581208e+00 5.11945426e-01 -4.69959736e-01 -8.72952580e-01
3.88303041e-01 7.08563253e-02 -4.86610144e-01 4.71117765e-01
1.21862113e-01 7.30912089e-01 7.31658518e-01 -9.71433938e-01
-1.08997643e+00 -3.39183211e-01 -6.97151124e-02 4.16554898e-01
2.06424464e-02 -2.26322860e-01 -6.12312138e-01 -2.45102137e-01
3.46396595e-01 -1.12983930e+00 -2.74224877e-01 1.38796329e-01
2.09531769e-01 1.65997237e-01 9.02282894e-01 -1.01027355e-01
7.30922937e-01 -2.52980113e+00 -2.30214983e-01 2.12856844e-01
-2.69890964e-01 -3.96639943e-01 2.39806846e-01 5.90588689e-01
2.55388528e-01 -5.43463528e-01 -7.88151622e-02 -8.15296173e-02
-1.24008425e-01 4.19387341e-01 -6.49900854e-01 9.00455058e-01
6.63005859e-02 5.33419669e-01 -9.76564527e-01 -4.94159371e-01
6.44276261e-01 4.70318079e-01 -8.42492357e-02 -4.74755727e-02
3.99705768e-02 3.45455080e-01 -4.21023518e-01 6.37871683e-01
5.49088359e-01 -6.52061850e-02 -1.16936743e-01 -2.15330347e-01
-4.79014546e-01 1.89721972e-01 -1.43195832e+00 1.76148283e+00
-3.26892823e-01 1.14038968e+00 -1.58754662e-01 -5.35322309e-01
9.55135286e-01 6.02877066e-02 5.95278203e-01 -9.77292061e-01
-1.32793531e-01 2.15023637e-01 -3.30067277e-01 -3.00820768e-01
1.26212966e+00 2.24217862e-01 -4.08678353e-01 1.45571306e-01
-2.00207353e-01 8.77797082e-02 3.38320524e-01 2.76189744e-01
1.41464782e+00 -1.27490535e-01 5.82156658e-01 3.48237366e-03
1.80112168e-01 4.93142247e-01 6.58191502e-01 7.92513669e-01
-4.07826573e-01 7.55848646e-01 -6.22599497e-02 -2.12061465e-01
-8.78211498e-01 -1.10669672e+00 -2.81499147e-01 6.41072631e-01
9.89399970e-01 -1.97415739e-01 -2.50258390e-02 -2.05032036e-01
-5.61666023e-03 5.58507860e-01 -2.72805989e-01 -1.37730211e-01
-6.43306017e-01 -7.23861575e-01 4.40525651e-01 6.30363226e-01
7.04285383e-01 -7.74714530e-01 -1.56857502e+00 3.42568874e-01
-2.54262894e-01 -1.39818335e+00 -1.94216579e-01 4.54824269e-01
-7.21294820e-01 -8.30951452e-01 -3.63830477e-01 -6.10994220e-01
4.76088852e-01 8.22283924e-01 8.63770366e-01 -4.78283376e-01
-3.61118495e-01 7.91753292e-01 -2.56917208e-01 -2.96469092e-01
1.78370833e-01 -4.30576414e-01 1.57411352e-01 2.53434718e-01
2.71600187e-01 -3.99404377e-01 -7.85815656e-01 4.77120429e-01
-7.91720986e-01 -2.50908494e-01 4.16725665e-01 4.65121269e-01
1.02417696e+00 2.36010328e-01 2.03490451e-01 -2.11386979e-01
-1.45463988e-01 -7.39536762e-01 -9.72342074e-01 -7.11548179e-02
-3.25797081e-01 -2.44554460e-01 4.33799684e-01 -4.29309934e-01
-9.87906039e-01 6.39484346e-01 4.58582669e-01 -5.72965562e-01
-1.56833902e-01 1.87493622e-01 1.02875069e-01 -2.30325893e-01
6.05822682e-01 4.07286793e-01 -3.62506211e-01 2.49615356e-01
2.87182599e-01 3.94243598e-01 1.02843702e+00 -2.66818434e-01
7.63909638e-01 1.12431121e+00 2.11169854e-01 -9.38572407e-01
2.12183759e-01 -9.72157001e-01 -2.42656484e-01 -4.74774361e-01
8.31337631e-01 -1.31995595e+00 -7.22888827e-01 2.56398350e-01
-9.82613385e-01 -2.19660819e-01 -4.04431105e-01 7.64036357e-01
-6.83520555e-01 2.93258995e-01 -1.99885085e-01 -8.38401973e-01
7.99550712e-02 -1.03908467e+00 1.11911488e+00 5.70027590e-01
2.15022452e-02 -6.37713313e-01 1.75636727e-02 -1.60132214e-01
2.43571237e-01 6.12096310e-01 1.86478972e-01 -2.63767421e-01
-1.18271971e+00 -4.00521904e-01 -1.40614301e-01 -4.06555295e-01
-3.32047716e-02 -2.42869511e-01 -8.74526441e-01 -2.67291903e-01
-9.52420682e-02 6.17379062e-02 7.63354540e-01 2.99466610e-01
7.36939192e-01 1.20394535e-01 -6.35987222e-01 6.68670654e-01
1.73680389e+00 5.21220982e-01 7.03746021e-01 5.57378769e-01
4.17272389e-01 3.08579952e-01 1.20995331e+00 7.36363769e-01
4.83023882e-01 9.03158903e-01 6.60456121e-01 1.80508345e-01
4.16476540e-02 -1.23903118e-01 4.83874649e-01 1.95120171e-01
7.02620745e-02 -4.44694519e-01 -8.32781732e-01 9.34623539e-01
-1.96450126e+00 -1.13866353e+00 -2.13883460e-01 2.47804856e+00
1.79594055e-01 1.48871571e-01 -2.27070853e-01 -7.03107044e-02
6.59449041e-01 5.02743006e-01 -7.12786496e-01 -2.38534771e-02
-2.62560844e-01 -2.15481699e-01 1.24981451e+00 8.76404345e-02
-1.02381289e+00 4.70672339e-01 5.52766180e+00 5.93516409e-01
-1.16115499e+00 -3.30017321e-02 1.67788714e-01 -3.55064899e-01
2.13687271e-01 -7.60603603e-03 -9.89575088e-01 6.39277339e-01
1.19275558e+00 -2.21383005e-01 3.55999589e-01 8.58648300e-01
3.55300695e-01 -7.48072982e-01 -1.22639847e+00 1.32271516e+00
1.40524521e-01 -1.39729679e+00 -4.70903486e-01 9.87776145e-02
6.15837336e-01 5.74416935e-01 5.59945218e-02 -6.31721988e-02
-1.96337211e-03 -5.76909304e-01 1.11713362e+00 3.80737931e-01
6.57171071e-01 -7.35116303e-01 4.95734304e-01 2.50690758e-01
-1.58697975e+00 -9.39017013e-02 -4.69112486e-01 1.14034459e-01
4.55781966e-01 4.67002302e-01 -1.02060628e+00 5.51139116e-01
1.04917431e+00 8.63334477e-01 -4.77521181e-01 1.22061396e+00
1.75917953e-01 2.99431205e-01 -8.38520408e-01 -6.75576478e-02
1.83728591e-01 -4.64384742e-02 7.67017007e-01 1.09365308e+00
6.87956452e-01 2.29786307e-01 3.65772992e-02 5.79257846e-01
1.74166590e-01 -3.49981964e-01 -1.04123461e+00 4.17933524e-01
7.88674772e-01 1.24022090e+00 -9.45038259e-01 -2.95608968e-01
-5.45077980e-01 9.93828297e-01 -5.54685704e-02 3.78744423e-01
-1.11465240e+00 -5.45829594e-01 8.11167479e-01 -9.08854157e-02
7.23429918e-01 -6.40865624e-01 -9.20542553e-02 -8.62441480e-01
3.29186916e-01 -3.83718848e-01 2.90779054e-01 -1.06880593e+00
-7.53053308e-01 5.25248408e-01 9.80249718e-02 -1.80091643e+00
-3.23291212e-01 -3.06681097e-01 -3.75337124e-01 4.46464181e-01
-1.77914107e+00 -6.63151205e-01 -7.71303952e-01 7.47771740e-01
5.63263059e-01 1.05141737e-01 3.94253314e-01 4.09828395e-01
-2.66131490e-01 1.64168030e-01 2.72624731e-01 -1.95631504e-01
6.91108167e-01 -1.02299035e+00 3.20837051e-01 1.16844332e+00
3.92343163e-01 2.39646047e-01 7.91352570e-01 -5.29588819e-01
-1.92397678e+00 -1.29053962e+00 6.79195821e-01 -4.63107169e-01
5.23095071e-01 -2.21059665e-01 -6.43448353e-01 6.46741688e-01
6.64822385e-03 3.87839466e-01 1.98426887e-01 -6.43662393e-01
1.27737634e-02 -4.80198085e-01 -1.07872856e+00 5.48744023e-01
9.54126537e-01 -4.89714712e-01 -4.35126394e-01 1.82461321e-01
3.95527780e-01 -7.77571023e-01 -6.01370215e-01 3.35785717e-01
3.09148282e-01 -9.38880980e-01 1.09939778e+00 2.31792316e-01
-1.09433345e-01 -9.08994317e-01 -5.86793602e-01 -8.54882300e-01
-2.72106417e-02 -6.32419050e-01 -7.18527287e-02 1.18467176e+00
1.06339030e-01 -6.62735164e-01 6.14850163e-01 5.60942709e-01
-1.23138092e-01 -1.75370201e-01 -1.31497049e+00 -9.89645123e-01
-9.45045829e-01 -6.20503068e-01 3.34522516e-01 4.42712963e-01
-2.80440539e-01 -1.57058835e-01 -2.15620622e-01 7.74577022e-01
5.83137691e-01 2.39592373e-01 8.67607176e-01 -9.45103407e-01
-1.17039569e-01 2.41055891e-01 -9.24908757e-01 -1.18198800e+00
-2.02738509e-01 -5.61428130e-01 6.28231525e-01 -1.26012647e+00
-7.73161203e-02 -5.12752056e-01 -2.22442135e-01 1.76211566e-01
2.12491721e-01 4.72605050e-01 -7.22142821e-03 4.20571864e-01
-8.88368309e-01 4.56609726e-01 3.01640302e-01 4.38402295e-02
-1.99466243e-01 -2.39449978e-01 4.67647798e-02 5.82410693e-01
5.23082972e-01 -5.19178033e-01 -2.77960151e-01 -3.42477858e-01
2.04636738e-01 2.41000339e-01 6.62234366e-01 -1.57156694e+00
7.70621300e-01 -1.44557446e-01 3.89651507e-01 -8.83417547e-01
8.49807918e-01 -1.25935721e+00 6.58711195e-01 2.59419382e-01
5.23591116e-02 4.16920185e-01 3.19078892e-01 1.15290987e+00
-2.90075928e-01 -5.58266789e-02 6.42006457e-01 3.25458758e-02
-1.65940237e+00 1.67330950e-01 -6.55582488e-01 -1.61124423e-01
1.61892128e+00 -5.68797410e-01 -4.73499745e-01 -3.20166558e-01
3.62401567e-02 2.17752874e-01 7.26455629e-01 4.40819234e-01
7.11524427e-01 -1.36693108e+00 -2.49425471e-01 2.49269858e-01
5.29165089e-01 4.02504615e-02 2.64421165e-01 9.49051917e-01
-7.51505971e-01 3.48165661e-01 -2.31057599e-01 -1.13845456e+00
-1.17654240e+00 4.14098978e-01 9.74884927e-02 1.92886263e-01
-9.24381971e-01 4.73539114e-01 2.69877762e-02 2.78077662e-01
2.00183570e-01 -4.65822965e-01 1.53209478e-01 3.16862874e-02
5.58738768e-01 5.70861995e-01 2.02236548e-01 -9.34155047e-01
-7.14730203e-01 6.67368770e-01 3.22195947e-01 -2.70929128e-01
1.09390092e+00 -5.40343165e-01 4.07123387e-01 4.99844074e-01
1.10026824e+00 1.12249643e-01 -1.64603472e+00 -8.51844549e-02
1.10410992e-02 -5.50458789e-01 2.32753932e-01 -2.82180816e-01
-8.86622667e-01 4.77890462e-01 9.07687604e-01 -4.90684547e-02
1.19049811e+00 5.70063032e-02 7.92882025e-01 6.16780519e-01
1.00753188e+00 -8.56639206e-01 -1.70966059e-01 3.44571412e-01
4.78428930e-01 -1.35454488e+00 4.87558134e-02 -2.08285853e-01
-7.43401229e-01 1.00892353e+00 2.82343209e-01 -2.90243983e-01
2.29646996e-01 1.99827000e-01 -1.16053231e-01 -8.28932151e-02
-7.74848402e-01 -4.00612503e-01 -6.41494198e-03 6.72192156e-01
-4.38823730e-01 -1.25937209e-01 8.86256248e-02 7.67834187e-02
-1.53269833e-02 -1.80750549e-01 7.02938080e-01 1.29969680e+00
-6.13922000e-01 -3.64739597e-01 -6.13402784e-01 1.25697553e-01
-1.11216344e-01 1.94244087e-01 1.44424781e-01 8.93697977e-01
6.14149123e-02 1.08484149e+00 4.99313444e-01 -2.62809664e-01
4.83660281e-01 -2.58700669e-01 2.01902151e-01 -1.80117309e-01
-3.19345027e-01 -1.66468799e-01 7.72281066e-02 -1.07607436e+00
-4.78834867e-01 -1.10428464e+00 -1.61615789e+00 -2.25012138e-01
-1.05260685e-01 -8.46275762e-02 9.19324517e-01 6.02492034e-01
6.35540724e-01 3.31744075e-01 6.34570003e-01 -1.13044810e+00
-5.73711507e-02 -3.91759872e-01 -6.51134431e-01 2.88052142e-01
5.44166088e-01 -7.99209416e-01 -5.27037919e-01 3.75843495e-01] | [8.047865867614746, -1.5283316373825073] |
aed436f5-d0ce-4376-8058-e65e72f50bcf | copied-monolingual-data-improves-low-resource | null | null | https://aclanthology.org/W17-4715 | https://aclanthology.org/W17-4715.pdf | Copied Monolingual Data Improves Low-Resource Neural Machine Translation | null | ['Kenneth Heafield', 'Anna Currey', 'Antonio Valerio Miceli Barone'] | 2017-09-01 | null | null | null | ws-2017-9 | ['low-resource-neural-machine-translation'] | ['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] | [-7.268688678741455, 3.764174222946167] |
3e278120-7545-454c-8fc8-3729655846ce | self-labelling-via-simultaneous-clustering-1 | 1911.05371 | null | https://arxiv.org/abs/1911.05371v3 | https://arxiv.org/pdf/1911.05371v3.pdf | Self-labelling via simultaneous clustering and representation learning | Combining clustering and representation learning is one of the most promising approaches for unsupervised learning of deep neural networks. However, doing so naively leads to ill posed learning problems with degenerate solutions. In this paper, we propose a novel and principled learning formulation that addresses these issues. The method is obtained by maximizing the information between labels and input data indices. We show that this criterion extends standard crossentropy minimization to an optimal transport problem, which we solve efficiently for millions of input images and thousands of labels using a fast variant of the Sinkhorn-Knopp algorithm. The resulting method is able to self-label visual data so as to train highly competitive image representations without manual labels. Our method achieves state of the art representation learning performance for AlexNet and ResNet-50 on SVHN, CIFAR-10, CIFAR-100 and ImageNet and yields the first self-supervised AlexNet that outperforms the supervised Pascal VOC detection baseline. Code and models are available. | ['Christian Rupprecht', 'Yuki Markus Asano', 'Andrea Vedaldi'] | 2019-11-13 | null | https://openreview.net/forum?id=Hyx-jyBFPr | https://openreview.net/pdf?id=Hyx-jyBFPr | iclr-2020-1 | ['self-supervised-image-classification'] | ['computer-vision'] | [ 1.66908577e-01 -3.74379121e-02 -1.86917692e-01 -5.39282084e-01
-9.13884342e-01 -6.00407541e-01 4.84197825e-01 -1.20629750e-01
-8.29878688e-01 6.42150283e-01 -7.13000745e-02 -2.17504233e-01
-2.50681072e-01 -4.84946191e-01 -5.62514722e-01 -8.91983211e-01
5.73554225e-02 8.00799608e-01 4.54706252e-02 1.99775234e-01
1.71387449e-01 5.15020251e-01 -1.64132178e+00 2.20492169e-01
4.74098951e-01 1.20216441e+00 2.89544016e-01 6.68854833e-01
-2.22440511e-02 1.30105543e+00 -3.67890418e-01 -1.87219992e-01
2.88738608e-01 -3.61677885e-01 -1.15688062e+00 2.13911027e-01
8.73907387e-01 -2.31607873e-02 -8.63261893e-02 1.19656312e+00
4.65330958e-01 4.12979037e-01 1.23674321e+00 -9.90855932e-01
-6.40109897e-01 4.55365837e-01 -6.46928012e-01 2.22429186e-01
-4.81944203e-01 -2.38571286e-01 1.37118387e+00 -8.43122482e-01
6.03460729e-01 1.15725803e+00 5.44201553e-01 7.55573094e-01
-1.59337807e+00 -5.37393689e-01 -5.36367893e-02 -1.21044656e-02
-1.36474836e+00 -3.88548255e-01 5.85248709e-01 -7.40683138e-01
9.29735541e-01 -8.17061290e-02 3.95223171e-01 9.58341360e-01
-4.22840744e-01 8.27509999e-01 1.07036185e+00 -4.70464647e-01
5.24655700e-01 4.10389006e-01 3.40708822e-01 8.61308217e-01
1.08238421e-01 -6.20258152e-02 -1.39324576e-01 -7.76425004e-02
5.33316672e-01 3.25297080e-02 2.02936344e-02 -6.43464208e-01
-9.33583677e-01 1.20173836e+00 7.91048467e-01 4.67043705e-02
-8.02771449e-02 4.93988514e-01 3.96265179e-01 2.19932050e-01
6.99183583e-01 5.15111148e-01 -4.69385087e-01 2.93337226e-01
-1.13620591e+00 -8.16541016e-02 7.46493638e-01 8.96410644e-01
1.10085046e+00 3.07784945e-01 2.06473336e-01 1.03295004e+00
4.72677559e-01 3.05428743e-01 5.12652576e-01 -1.29970491e+00
1.45084783e-01 3.88000399e-01 -3.50367785e-01 -6.79076195e-01
-4.40773964e-01 -6.39019132e-01 -9.16354120e-01 5.75195611e-01
2.74087906e-01 -2.84248888e-01 -1.10812008e+00 1.51047111e+00
-3.45339552e-02 1.41361013e-01 2.36029878e-01 8.14747930e-01
7.67765284e-01 6.80109918e-01 1.91418529e-01 -1.95311874e-01
8.71310174e-01 -1.18182683e+00 -4.39265221e-01 -2.77597904e-01
9.71391678e-01 -4.92304921e-01 5.89549899e-01 2.92614907e-01
-7.10279107e-01 -4.12269562e-01 -9.03979599e-01 -2.39406377e-02
-4.78481501e-01 1.59759089e-01 7.39900291e-01 6.58112347e-01
-1.36808562e+00 7.35817254e-01 -7.20997632e-01 -3.37978721e-01
9.44036126e-01 6.07387245e-01 -2.95607507e-01 -6.91659302e-02
-5.77419043e-01 7.32060671e-01 6.40637457e-01 -3.82361203e-01
-1.04724371e+00 -6.31844342e-01 -6.86680198e-01 -5.57129420e-02
4.15567197e-02 -1.98667258e-01 1.13709569e+00 -1.33679080e+00
-1.35419738e+00 1.26797485e+00 1.36586204e-01 -8.52366209e-01
3.01750839e-01 -4.59065400e-02 8.59163702e-03 4.10361618e-01
7.05852313e-03 1.17714119e+00 8.72124195e-01 -1.37252915e+00
-3.51310998e-01 -2.02526927e-01 -3.60451788e-01 6.64550588e-02
-5.14798999e-01 -1.80625059e-02 -2.12956108e-02 -5.20480931e-01
5.70237450e-02 -1.01815605e+00 -3.50883752e-01 -1.00519978e-01
-4.76064086e-01 -3.26617509e-01 8.24196756e-01 -2.61495650e-01
4.75732803e-01 -2.15359688e+00 1.96898252e-01 3.01960915e-01
2.86421031e-01 3.97024155e-01 -2.94857174e-01 7.18397424e-02
-2.24589929e-01 1.86802939e-01 -5.42295337e-01 -5.96795857e-01
-5.68869859e-02 4.99481887e-01 -3.86552751e-01 8.16984355e-01
1.10112049e-01 9.32522833e-01 -8.51052523e-01 -6.52760386e-01
2.42982969e-01 5.49911439e-01 -5.80107391e-01 7.05629662e-02
-3.62221003e-01 3.87946278e-01 -1.15267828e-01 3.25424433e-01
6.16789401e-01 -4.88778681e-01 -1.82480988e-04 1.94780361e-02
6.94687963e-02 2.01418519e-01 -8.87756050e-01 1.70657814e+00
-3.35683703e-01 9.53301370e-01 -5.39244823e-02 -1.49957180e+00
8.66420686e-01 1.91472247e-01 7.25303829e-01 -3.64404500e-01
1.89706758e-01 1.58748418e-01 -3.19621623e-01 -3.14942867e-01
5.19836061e-02 -1.90937325e-01 3.03348780e-01 6.00252151e-01
7.22434640e-01 -9.42037329e-02 1.51095912e-01 2.70450532e-01
9.60685909e-01 -6.55644536e-02 9.65040922e-02 -5.25258899e-01
2.74625003e-01 1.15081118e-02 2.57356137e-01 7.77474344e-01
-8.35266411e-02 8.09638798e-01 3.12912405e-01 -4.12444144e-01
-9.34909105e-01 -1.07997775e+00 -2.74654835e-01 1.38198650e+00
-2.46109143e-01 -3.11695784e-01 -8.95332813e-01 -8.03216934e-01
-2.61260122e-01 6.64291441e-01 -5.57725728e-01 2.24300637e-03
-2.58476764e-01 -7.08625734e-01 5.23027778e-01 4.43525553e-01
5.52578986e-01 -1.19942749e+00 -4.07027900e-01 -5.04935496e-02
3.49780843e-02 -1.03358400e+00 -9.40276906e-02 7.10015595e-01
-1.05042899e+00 -9.65993822e-01 -7.41684258e-01 -1.25530529e+00
9.05722678e-01 1.51678801e-01 1.12487960e+00 -1.41672315e-02
-5.84678352e-01 3.99210513e-01 -2.58468777e-01 -2.53403068e-01
-1.49984270e-01 2.62855798e-01 1.18316468e-02 1.21799976e-01
4.18815643e-01 -4.55853850e-01 -4.46675956e-01 2.37396508e-01
-9.10963655e-01 -3.30356508e-01 5.32287359e-01 9.37872469e-01
1.00580370e+00 8.87421742e-02 4.35434937e-01 -1.25019538e+00
1.64702669e-01 -4.45866346e-01 -7.86780834e-01 1.64823741e-01
-6.64157450e-01 4.14028525e-01 7.45078862e-01 -4.71590996e-01
-8.54104578e-01 6.88384235e-01 -1.32639229e-01 -6.23279572e-01
-4.96644914e-01 2.07440019e-01 1.89791530e-01 -4.51248586e-01
9.14151549e-01 1.08038209e-01 -1.97146535e-01 -6.27815425e-01
6.64164126e-01 5.97301364e-01 3.85904223e-01 -4.78111446e-01
6.46784961e-01 6.62791908e-01 -2.66811321e-03 -1.06828010e+00
-1.25695407e+00 -1.00922525e+00 -8.50281060e-01 -1.25897318e-01
1.07590246e+00 -8.69598210e-01 -4.44593132e-01 2.71165699e-01
-1.06894994e+00 -4.92240936e-01 -6.22338176e-01 5.98287761e-01
-8.07599604e-01 4.26129764e-03 -7.25636721e-01 -6.85901284e-01
-1.56108037e-01 -1.03637969e+00 8.10724854e-01 3.93003598e-02
2.09012762e-01 -1.21437109e+00 3.63816053e-01 2.95674324e-01
2.67202377e-01 1.63529843e-01 6.48427844e-01 -8.65162015e-01
-4.55116302e-01 -7.69716799e-02 -4.35600102e-01 9.23564076e-01
-1.34534597e-01 -2.17945442e-01 -1.32724154e+00 -4.90811586e-01
4.13871035e-02 -1.12488794e+00 1.61849368e+00 4.34990317e-01
1.31860971e+00 -4.53680754e-01 -9.78554115e-02 1.10840094e+00
1.74184418e+00 -2.81711817e-01 4.85397577e-01 1.62499070e-01
1.02339292e+00 7.91764855e-01 -3.29591557e-02 5.18003739e-02
1.43596390e-02 2.60981560e-01 5.37927747e-01 -1.24717191e-01
-1.62509918e-01 2.32511405e-02 1.12866804e-01 9.14716721e-01
-1.76671043e-01 -1.02646753e-01 -8.64831984e-01 5.60667336e-01
-1.78507102e+00 -1.02590156e+00 -6.36895820e-02 2.08341241e+00
6.31149173e-01 -1.97137475e-01 2.65251081e-02 1.21936109e-02
5.79799831e-01 2.61306226e-01 -5.16583264e-01 -2.23522559e-01
-1.49150878e-01 3.85065347e-01 1.07696593e+00 3.82628530e-01
-1.44195044e+00 1.24996722e+00 6.83263111e+00 8.60182226e-01
-8.02561939e-01 3.52128476e-01 7.61232257e-01 4.03407924e-02
9.80079025e-02 -1.63734004e-01 -8.28417480e-01 4.48325910e-02
1.02370346e+00 3.40562552e-01 4.81399238e-01 1.07844710e+00
-3.45477432e-01 9.90139842e-02 -1.12168956e+00 1.30679572e+00
1.51308179e-01 -1.47649717e+00 -3.63741964e-02 2.60663599e-01
1.28069997e+00 6.54211342e-01 4.07872081e-01 5.25774732e-02
7.73927808e-01 -1.24491537e+00 4.33858484e-01 2.14580148e-01
7.87798405e-01 -8.00586343e-01 5.49470544e-01 3.00161898e-01
-9.09906864e-01 -9.16440934e-02 -9.16199982e-01 1.47776499e-01
-2.22643197e-01 5.21074414e-01 -5.92697918e-01 -4.30675149e-02
6.06646836e-01 1.15616477e+00 -6.40027404e-01 1.28806174e+00
-3.31170768e-01 8.56908739e-01 -3.72451484e-01 -5.96307963e-02
5.21236539e-01 -1.99972689e-01 2.38854691e-01 1.39320850e+00
-5.12113534e-02 -1.53444171e-01 1.59959808e-01 9.27463055e-01
-5.71971357e-01 1.70618623e-01 -8.06166768e-01 -3.48805785e-02
8.64089131e-02 1.36051297e+00 -9.77947235e-01 -2.91475445e-01
-2.57417887e-01 9.27696526e-01 9.22524393e-01 7.67448127e-01
-3.95852566e-01 -1.30409822e-01 4.65383530e-01 -1.23055898e-01
5.15274644e-01 -1.46032631e-01 -7.78333023e-02 -1.09552050e+00
-3.97502750e-01 -4.28175867e-01 4.71651107e-01 -4.34515983e-01
-1.48687601e+00 5.77463627e-01 -5.59542105e-02 -1.02178335e+00
-1.28644258e-01 -1.08398211e+00 -4.84182030e-01 3.79571080e-01
-1.67170703e+00 -8.91681015e-01 1.97620653e-02 7.01418936e-01
5.06671786e-01 -5.10870695e-01 9.40164804e-01 2.09492519e-01
-4.07919109e-01 5.17737091e-01 8.09326947e-01 5.06380200e-01
4.46238339e-01 -1.51536596e+00 7.50787742e-03 5.03877163e-01
6.81660771e-01 2.23039657e-01 4.15394664e-01 -1.31408408e-01
-7.77997851e-01 -1.45348144e+00 5.93881309e-01 -2.72318870e-01
6.94968998e-01 -4.10654217e-01 -8.41373980e-01 8.94542277e-01
2.39292294e-01 4.38743234e-01 7.44453073e-01 -1.22087806e-01
-7.21235037e-01 -1.29923850e-01 -9.19830620e-01 8.96940082e-02
8.67662668e-01 -6.82712913e-01 -5.06412804e-01 1.10596061e+00
6.18860960e-01 1.22860514e-01 -5.62583208e-01 8.12139884e-02
9.29219574e-02 -8.55205178e-01 1.09146154e+00 -6.63923264e-01
3.50171775e-01 1.25175327e-01 -3.61837476e-01 -1.35850298e+00
-2.43041843e-01 -5.73238790e-01 1.75154224e-01 1.15189910e+00
5.97512484e-01 -5.92394471e-01 8.92032683e-01 1.18895926e-01
-2.82825530e-02 -6.04482710e-01 -7.54356861e-01 -8.73372734e-01
3.58736843e-01 -3.59976292e-01 -1.41213238e-01 9.60164785e-01
-4.12864119e-01 3.60978335e-01 -3.74020636e-01 -1.88852876e-01
1.29276013e+00 -2.24707738e-01 2.42776960e-01 -1.42285085e+00
-2.83377737e-01 -4.68496323e-01 -6.01516664e-01 -1.02373803e+00
7.46888161e-01 -1.33010209e+00 3.00424159e-01 -1.53289485e+00
1.11838236e-01 -6.30035698e-01 -5.77855170e-01 4.20743436e-01
4.88412678e-01 6.49574995e-01 -4.57141213e-02 5.00712156e-01
-1.05609202e+00 3.60644341e-01 8.16654801e-01 -3.89144152e-01
4.02757153e-02 2.27490608e-02 -4.21818316e-01 8.86267006e-01
1.04696500e+00 -9.44009364e-01 -6.04028821e-01 -6.30605221e-01
6.62924647e-02 -6.84900284e-01 5.33785760e-01 -1.14382398e+00
4.53730464e-01 2.00031370e-01 3.75548393e-01 -4.87298340e-01
2.95182645e-01 -7.06552207e-01 -3.48812729e-01 2.49536470e-01
-9.96264637e-01 -2.16043964e-01 -1.76505566e-01 7.46242523e-01
-1.82350889e-01 -6.40172899e-01 1.22597706e+00 -4.61354882e-01
-7.58262694e-01 4.39125091e-01 -3.96404296e-01 4.55696493e-01
9.60782111e-01 1.69447348e-01 -4.73885536e-01 -1.98188767e-01
-6.30080998e-01 1.36844769e-01 3.01369965e-01 -5.42068249e-03
8.34362805e-01 -1.16437328e+00 -6.51598334e-01 6.06582388e-02
-1.30231970e-03 1.09595433e-01 -1.66741893e-01 6.17027223e-01
-9.46287990e-01 3.38051736e-01 -1.93962410e-01 -7.53984690e-01
-1.01659989e+00 6.06789112e-01 5.02384067e-01 -1.21372126e-01
-6.29756510e-01 1.34304667e+00 2.43994191e-01 -6.65708601e-01
6.31900966e-01 1.46828488e-01 -4.64994162e-01 1.42882213e-01
5.93003690e-01 3.02762389e-01 -6.84967786e-02 -9.90684211e-01
-2.19988227e-01 7.86077499e-01 -2.22165018e-01 -1.62703827e-01
1.49982774e+00 9.59917158e-02 -2.88683623e-01 5.23501158e-01
2.03432155e+00 -5.48917949e-01 -1.41668296e+00 -3.68435830e-01
1.94035098e-01 -5.70717230e-02 3.68972778e-01 -3.28602254e-01
-1.32721293e+00 1.32287872e+00 7.69114554e-01 1.07542261e-01
8.48785698e-01 3.86025131e-01 5.64221203e-01 9.66923118e-01
1.24186866e-01 -1.25440836e+00 3.83649021e-01 6.16403162e-01
2.71669924e-01 -1.50229144e+00 5.89161925e-02 2.99835447e-02
-6.00944281e-01 1.06414318e+00 3.85577291e-01 -5.73631346e-01
8.49111080e-01 5.91690317e-02 2.11673945e-01 -4.22135025e-01
-6.11212432e-01 -5.18835545e-01 3.73746365e-01 7.24114120e-01
2.72056401e-01 8.10889974e-02 2.54190624e-01 -1.00286365e-01
-1.32219613e-01 -4.96035188e-01 1.39227480e-01 7.94550240e-01
-7.11022556e-01 -7.90189922e-01 3.15235294e-02 5.93500495e-01
-6.03783846e-01 -1.91399962e-01 -4.54819739e-01 5.02388477e-01
1.64017193e-02 8.52621257e-01 2.10939974e-01 -2.99990505e-01
-2.01757610e-01 8.91323462e-02 4.22856390e-01 -8.27660739e-01
-4.01978076e-01 7.01467097e-02 -2.47814745e-01 -3.65267605e-01
-9.08270359e-01 -4.05679703e-01 -1.26377070e+00 2.87417155e-02
-4.83880252e-01 2.21663505e-01 7.76823044e-01 1.03563559e+00
-1.33757412e-01 3.43229413e-01 7.17158675e-01 -1.08654308e+00
-6.19026840e-01 -8.17257822e-01 -8.41999292e-01 5.14750898e-01
4.64673221e-01 -5.52540004e-01 -7.01464355e-01 3.04491222e-01] | [9.328363418579102, 2.833466053009033] |
a1399248-d2da-4312-8815-73e71b7934cf | exploring-contrast-consistency-of-open-domain | 2305.14441 | null | https://arxiv.org/abs/2305.14441v1 | https://arxiv.org/pdf/2305.14441v1.pdf | Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions | Contrast consistency, the ability of a model to make consistently correct predictions in the presence of perturbations, is an essential aspect in NLP. While studied in tasks such as sentiment analysis and reading comprehension, it remains unexplored in open-domain question answering (OpenQA) due to the difficulty of collecting perturbed questions that satisfy factuality requirements. In this work, we collect minimally edited questions as challenging contrast sets to evaluate OpenQA models. Our collection approach combines both human annotation and large language model generation. We find that the widely used dense passage retriever (DPR) performs poorly on our contrast sets, despite fitting the training set well and performing competitively on standard test sets. To address this issue, we introduce a simple and effective query-side contrastive loss with the aid of data augmentation to improve DPR training. Our experiments on the contrast sets demonstrate that DPR's contrast consistency is improved without sacrificing its accuracy on the standard test sets. | ['Meng Jiang', 'Mingxuan Ju', 'Zheng Ning', 'Wenhao Yu', 'Zhihan Zhang'] | 2023-05-23 | null | null | null | null | ['sentiment-analysis', 'reading-comprehension', 'open-domain-question-answering'] | ['natural-language-processing', 'natural-language-processing', 'natural-language-processing'] | [ 1.98602080e-01 1.06806837e-01 2.74174273e-01 -2.67998636e-01
-1.59586990e+00 -9.26206529e-01 6.32334530e-01 4.07056600e-01
-4.64105397e-01 9.41433311e-01 2.94284374e-01 -3.12410682e-01
-3.97733115e-02 -5.45662880e-01 -9.03582096e-01 -1.68372124e-01
1.93859339e-01 7.43574977e-01 5.15791416e-01 -7.78036475e-01
1.96357951e-01 8.28243643e-02 -1.38398004e+00 5.43331325e-01
1.43583715e+00 7.77654827e-01 -1.08504318e-01 7.33745933e-01
-8.22107270e-02 9.49271262e-01 -8.38054121e-01 -7.71565318e-01
2.55521059e-01 -3.67018461e-01 -1.24775839e+00 -4.06952858e-01
7.93043137e-01 -2.55343348e-01 -2.30714809e-02 7.52503693e-01
7.27249801e-01 4.79718238e-01 6.73436105e-01 -9.17701542e-01
-9.52118635e-01 3.93666953e-01 -1.34228900e-01 4.89098221e-01
7.24314690e-01 2.75501847e-01 1.60769475e+00 -8.56133401e-01
6.26489639e-01 9.50266421e-01 5.78676105e-01 6.80791616e-01
-1.30306745e+00 -1.70127064e-01 -1.97297670e-02 2.84409285e-01
-1.16695070e+00 -5.35986662e-01 4.16779757e-01 4.03909087e-02
1.11660230e+00 5.79439878e-01 -1.32699460e-01 1.23258018e+00
5.59813008e-02 7.13279307e-01 9.39870834e-01 -5.00084639e-01
3.16885948e-01 1.70524895e-01 3.33183199e-01 3.74714971e-01
1.11161411e-01 -2.07784981e-01 -5.66561460e-01 -2.68261492e-01
-1.95405539e-02 -6.21840656e-01 -7.45487869e-01 -7.64423385e-02
-1.04169333e+00 6.99612319e-01 3.31127554e-01 1.13581106e-01
-1.71061739e-01 -2.22611457e-01 2.85761803e-01 7.61013567e-01
5.34283459e-01 1.29675877e+00 -7.90020347e-01 -4.25790191e-01
-7.25156009e-01 7.55780935e-01 1.27384496e+00 7.81160116e-01
4.73766357e-01 -3.89650255e-01 -7.90691316e-01 1.06261063e+00
-1.82694480e-01 5.06289244e-01 4.94194359e-01 -1.13416171e+00
7.32076406e-01 4.77274030e-01 4.61405098e-01 -7.59526134e-01
-1.72368869e-01 -5.45884848e-01 -4.04173732e-01 -4.37931329e-01
7.59273231e-01 -4.63829450e-02 -5.80713034e-01 1.96861947e+00
3.43394160e-01 -2.14854568e-01 2.94311970e-01 7.22629130e-01
8.30750942e-01 9.21608269e-01 -1.06779998e-02 -9.67428237e-02
1.30448306e+00 -1.09479880e+00 -5.60355425e-01 -3.28376263e-01
7.99029410e-01 -7.19014287e-01 1.80783176e+00 3.00674438e-01
-1.25607133e+00 -2.26084724e-01 -8.46533000e-01 -6.02613389e-01
-2.35711232e-01 -4.97176975e-01 1.22171596e-01 2.51252741e-01
-9.57266986e-01 4.03325260e-01 -4.38018352e-01 -2.17321277e-01
2.55111426e-01 -6.60464317e-02 -3.50031823e-01 -4.09880012e-01
-1.47983170e+00 1.21298468e+00 -1.54979751e-01 -3.54068309e-01
-7.23882318e-01 -1.12980831e+00 -8.21505189e-01 4.15348083e-01
6.01335049e-01 -8.65819395e-01 1.84985602e+00 -5.51751137e-01
-1.40182185e+00 7.46159792e-01 -2.30072469e-01 -6.14549756e-01
6.72410131e-01 -5.14114559e-01 -1.45158440e-01 1.92184404e-01
1.88385606e-01 6.73623025e-01 5.39825380e-01 -1.04484439e+00
-1.31115004e-01 -2.29028881e-01 4.29122835e-01 3.87990743e-01
-3.90568048e-01 -1.41241461e-01 -2.91817337e-01 -3.23831946e-01
-9.68174078e-03 -7.17275858e-01 -2.72805274e-01 -2.74110049e-01
-5.12160778e-01 -4.51174796e-01 2.73971945e-01 -8.82810950e-01
1.20159435e+00 -1.79740012e+00 4.85403034e-05 -7.76417740e-03
6.46682829e-02 3.39459807e-01 -6.25384331e-01 6.50463045e-01
2.77992547e-01 1.64629728e-01 -4.88612145e-01 -2.35359579e-01
1.86029181e-01 1.34454489e-01 -7.34358191e-01 -8.02130923e-02
4.88489836e-01 1.05317974e+00 -8.68301451e-01 -3.63658547e-01
-5.07662117e-01 2.15908419e-03 -9.62671518e-01 3.73886645e-01
-9.41073060e-01 3.15020978e-01 -3.20839256e-01 5.02830207e-01
2.55486906e-01 -4.68463182e-01 -2.94145644e-01 6.92720711e-02
3.54008257e-01 8.61893773e-01 -7.22547233e-01 1.74916434e+00
-5.46805322e-01 4.41796452e-01 -1.91950500e-01 -4.99075949e-01
7.42333949e-01 2.63089180e-01 -4.35593687e-02 -1.13463509e+00
-7.47374669e-02 2.41210267e-01 1.80838361e-01 -6.81499779e-01
8.97432685e-01 -6.93057775e-02 -3.07401940e-02 6.69006169e-01
3.67812514e-02 -5.11245847e-01 4.84773159e-01 3.79928321e-01
1.51534247e+00 -1.62522838e-01 2.69937217e-02 -3.20719689e-01
4.23826933e-01 2.55154461e-01 3.14177752e-01 1.13283205e+00
-2.34794185e-01 7.78657258e-01 5.39346576e-01 -4.93978709e-03
-1.00687110e+00 -9.91042435e-01 -2.32058674e-01 1.14395452e+00
-1.03316881e-01 -3.75143319e-01 -8.28627229e-01 -7.76690841e-01
-8.34371597e-02 1.20754337e+00 -3.18209231e-01 -2.48386607e-01
-4.20063525e-01 -5.93795240e-01 6.48405492e-01 3.04969341e-01
3.88955593e-01 -1.00286436e+00 -2.92395264e-01 1.71148609e-02
-6.33773804e-01 -1.12932944e+00 -3.81016046e-01 -1.08509533e-01
-6.12717628e-01 -1.02719450e+00 -5.48763931e-01 -6.18067622e-01
3.89166296e-01 2.57512450e-01 1.81671977e+00 1.83341186e-02
8.02093074e-02 5.91380417e-01 -4.80835706e-01 -5.24218976e-01
-7.53484964e-01 5.12516320e-01 -2.71265358e-01 -3.85167927e-01
4.81915474e-01 -6.07490957e-01 -5.28713048e-01 4.16847765e-01
-1.03516114e+00 -1.27644241e-01 3.80286902e-01 8.89390469e-01
5.73035479e-01 -4.76911157e-01 9.66006398e-01 -9.51290786e-01
1.14957237e+00 -6.11248434e-01 -5.17009377e-01 4.95534360e-01
-4.76260632e-01 1.72041044e-01 7.13890970e-01 -2.60612905e-01
-9.48431909e-01 -7.93901801e-01 -4.71868217e-01 -4.93031032e-02
-7.42767192e-03 5.50988436e-01 -2.20107496e-01 1.77552804e-01
1.18803763e+00 1.55162305e-01 1.00846998e-01 -3.89097869e-01
5.07719934e-01 6.08277440e-01 4.72389102e-01 -7.68819034e-01
7.71826386e-01 9.13642049e-02 -3.91124845e-01 -6.09689593e-01
-1.44372654e+00 -4.04286623e-01 -4.67266291e-02 2.47269675e-01
5.09801745e-01 -8.80083203e-01 -3.13561678e-01 5.48729151e-02
-1.19265723e+00 -4.03822124e-01 -5.47132373e-01 5.58880195e-02
-5.06753087e-01 2.25179970e-01 -6.54505372e-01 -3.97054821e-01
-6.47368848e-01 -8.25586200e-01 1.03229654e+00 2.46472768e-02
-4.84615773e-01 -8.85645986e-01 5.80893159e-01 8.63102913e-01
5.27624965e-01 -1.07605822e-01 1.09816611e+00 -1.24594688e+00
-6.05743825e-01 -3.11432242e-01 2.01266445e-02 6.57711267e-01
-1.59796014e-01 -3.14538807e-01 -1.04746938e+00 -1.70540020e-01
1.10151976e-01 -8.10551763e-01 7.69889772e-01 -2.51737684e-01
1.15036535e+00 -3.96449596e-01 2.62825221e-01 7.17117861e-02
1.14165545e+00 -3.08614373e-01 7.91263521e-01 2.12670162e-01
4.05788213e-01 7.08708525e-01 5.37524879e-01 4.42849994e-02
5.02630591e-01 3.84255797e-01 1.87924579e-01 3.77553493e-01
-2.85067502e-02 -3.04831028e-01 3.39138627e-01 9.15357590e-01
3.75048876e-01 -5.45844495e-01 -9.51336503e-01 7.53901124e-01
-1.50398457e+00 -9.14868176e-01 6.01741932e-02 2.10379243e+00
1.29440951e+00 1.99504539e-01 -4.51440722e-01 4.93440079e-03
1.36240885e-01 2.53507406e-01 -5.54762065e-01 -4.93759245e-01
-3.01081240e-01 3.66485685e-01 -8.75596479e-02 6.00085258e-01
-5.93708813e-01 7.74477839e-01 6.05471039e+00 8.02140474e-01
-5.08146107e-01 2.89965391e-01 6.17203355e-01 -2.39288256e-01
-7.69834399e-01 -1.08435385e-01 -6.99981689e-01 2.94541419e-01
1.13464141e+00 -1.51705414e-01 3.36693048e-01 5.96778810e-01
9.83022228e-02 -1.56572118e-01 -1.50627518e+00 5.79367876e-01
2.88345814e-01 -1.18324733e+00 3.48371595e-01 -3.70883107e-01
9.01301503e-01 9.89345834e-02 7.42583722e-02 8.10491502e-01
2.80835152e-01 -1.09093654e+00 4.11657155e-01 3.73626590e-01
3.93314958e-01 -4.29778427e-01 6.75207078e-01 6.66567862e-01
-2.26362124e-01 -8.41518193e-02 -4.58966792e-01 -2.57761449e-01
1.57356262e-01 5.00736058e-01 -9.72916901e-01 4.20160770e-01
5.24857759e-01 2.04782158e-01 -7.91393816e-01 8.82353008e-01
-2.86446273e-01 9.28261697e-01 -4.31227624e-01 -2.52421677e-01
1.95640370e-01 6.87056109e-02 7.06356943e-01 7.06458807e-01
5.32538481e-02 1.64186120e-01 -1.97779238e-01 9.16411579e-01
-5.39573848e-01 2.89265394e-01 -5.67995906e-01 6.14485405e-02
4.44572210e-01 8.92074525e-01 2.15083748e-01 -1.35420382e-01
-5.18607795e-01 8.96230400e-01 8.25667679e-01 3.16192240e-01
-6.52513742e-01 -2.03290835e-01 4.43967044e-01 2.18639269e-01
1.69521391e-01 8.53768289e-02 -1.76446840e-01 -1.43978488e+00
6.37993157e-01 -1.31942832e+00 5.57196140e-01 -8.16284657e-01
-1.57158351e+00 5.86933434e-01 -1.39509052e-01 -1.02093029e+00
-3.60932916e-01 -3.01056117e-01 -5.59202611e-01 8.13570619e-01
-1.74887300e+00 -7.21905053e-01 -1.39471382e-01 4.64863479e-01
6.33500636e-01 7.99492449e-02 9.96690035e-01 2.41350308e-01
-4.62887019e-01 9.51739848e-01 2.96622157e-01 -5.06579764e-02
8.62379551e-01 -1.34664607e+00 3.99906427e-01 8.94135237e-01
2.91354626e-01 6.99604332e-01 9.62202966e-01 -2.41830349e-01
-1.19977582e+00 -9.82623100e-01 1.16201794e+00 -1.09356976e+00
7.18971789e-01 -2.94397712e-01 -1.36162066e+00 6.84410334e-01
3.45263422e-01 -8.05010274e-02 8.35709274e-01 3.43872160e-01
-5.99049985e-01 -1.51959568e-01 -1.03664470e+00 8.18672419e-01
8.65021825e-01 -6.31412804e-01 -1.13967979e+00 6.17187500e-01
1.17997098e+00 -6.15229666e-01 -7.89425790e-01 4.69027400e-01
1.22547252e-02 -8.34499061e-01 7.59777665e-01 -1.08423257e+00
7.19598293e-01 -1.00031160e-02 -3.58776540e-01 -1.46174932e+00
6.45962283e-02 -5.80425680e-01 -1.92642048e-01 1.30258703e+00
8.24276149e-01 -5.54722607e-01 4.99756962e-01 9.34825778e-01
-1.35255367e-01 -8.78199458e-01 -1.05282748e+00 -6.45698011e-01
5.53645313e-01 -3.55014592e-01 5.15901089e-01 7.54069448e-01
4.05190364e-02 8.83354664e-01 5.53778186e-02 2.07576305e-01
1.28199399e-01 8.28841701e-02 8.86509240e-01 -9.66909826e-01
-5.60333431e-01 -6.03497699e-02 1.09979726e-01 -1.19926143e+00
1.44553497e-01 -7.71892130e-01 1.09060526e-01 -1.55463398e+00
1.26813352e-01 -4.95016366e-01 -5.57511821e-02 1.48098186e-01
-5.67523539e-01 1.33832535e-02 8.03931206e-02 1.57990620e-01
-1.04194987e+00 8.19587469e-01 1.36561918e+00 -1.53736934e-01
-1.22838996e-01 -7.75396451e-03 -1.05735421e+00 3.27520400e-01
7.07293630e-01 -2.53352523e-01 -6.60677016e-01 -8.07104707e-01
6.32348776e-01 1.12444296e-01 3.04206818e-01 -1.01298451e+00
5.59911281e-02 2.00005561e-01 -1.23035334e-01 -3.19824576e-01
3.12777847e-01 -4.10933316e-01 -5.83272696e-01 1.10759400e-01
-8.27709019e-01 3.13381106e-01 2.66977400e-01 5.54069817e-01
-3.48623604e-01 -3.39735746e-01 5.17270505e-01 -1.05429702e-01
-3.44494522e-01 8.41142833e-02 -2.10706424e-02 9.74345267e-01
5.64882874e-01 2.83036470e-01 -7.38013983e-01 -6.21758580e-01
-3.54780018e-01 6.45408928e-01 3.85875344e-01 4.39099818e-01
3.52780282e-01 -8.74187350e-01 -1.09585452e+00 -1.22783899e-01
4.27788794e-01 4.31331426e-01 3.42476368e-01 6.76559031e-01
-4.65549231e-01 4.84413475e-01 2.50014365e-01 -4.85193074e-01
-8.15132558e-01 3.01486194e-01 4.33202922e-01 -8.97201955e-01
-2.18954265e-01 9.07395840e-01 -1.64364949e-02 -7.68243551e-01
2.39602625e-01 -2.86214143e-01 -1.98865950e-01 -2.00533047e-01
7.52348900e-01 2.13307023e-01 5.55235028e-01 -6.65342212e-02
1.23582602e-01 -8.02589506e-02 -5.35268307e-01 -2.42023632e-01
9.81710792e-01 -5.77186346e-02 -1.07252672e-01 2.69200087e-01
1.15324867e+00 2.16216072e-01 -8.96773040e-01 -3.61755997e-01
-2.25058906e-02 -2.48150066e-01 -3.51341397e-01 -1.16743505e+00
-2.88379282e-01 7.90028572e-01 1.82053640e-01 3.35867077e-01
7.92534769e-01 -6.92024305e-02 1.08593535e+00 9.99424279e-01
2.25989729e-01 -8.56434643e-01 2.58947164e-01 8.59097600e-01
1.17963552e+00 -1.50174987e+00 -2.77907461e-01 -2.03713283e-01
-6.63485825e-01 4.56639916e-01 9.76455390e-01 1.41304418e-01
1.71157718e-01 -2.43436486e-01 2.30627656e-01 -1.35231689e-01
-1.23683226e+00 7.29671866e-02 2.48365894e-01 3.14573437e-01
2.55327910e-01 -3.00646216e-01 -3.64661157e-01 6.94650531e-01
-6.01846218e-01 -2.10809812e-01 5.76995194e-01 8.68222713e-01
-4.56597149e-01 -8.49120319e-01 -1.88040391e-01 6.42874837e-01
-5.97285330e-01 -4.06944305e-01 -3.66328597e-01 6.37283027e-01
-5.11147738e-01 1.01219368e+00 1.66640431e-01 -4.17568348e-02
6.25315785e-01 3.11223030e-01 4.09000158e-01 -7.55302191e-01
-6.95423543e-01 -8.18638444e-01 4.98796612e-01 -5.10811985e-01
6.09903131e-03 -4.94671255e-01 -9.87622440e-01 -2.16682076e-01
-3.95874023e-01 6.22323990e-01 2.88794041e-01 1.05542815e+00
6.12670898e-01 3.24487895e-01 3.96231294e-01 -3.45606618e-02
-1.43267369e+00 -1.16288102e+00 -1.15541160e-01 8.02561164e-01
3.93763423e-01 -2.29921401e-01 -4.53214377e-01 -2.83569068e-01] | [11.248283386230469, 8.08476734161377] |
0cfb639c-fc8f-41d7-8e95-1c6fb5a9d55a | parallelizing-contextual-linear-bandits | 2105.10590 | null | https://arxiv.org/abs/2105.10590v2 | https://arxiv.org/pdf/2105.10590v2.pdf | Parallelizing Contextual Bandits | Standard approaches to decision-making under uncertainty focus on sequential exploration of the space of decisions. However, \textit{simultaneously} proposing a batch of decisions, which leverages available resources for parallel experimentation, has the potential to rapidly accelerate exploration. We present a family of (parallel) contextual bandit algorithms applicable to problems with bounded eluder dimension whose regret is nearly identical to their perfectly sequential counterparts -- given access to the same total number of oracle queries -- up to a lower-order ``burn-in" term. We further show these algorithms can be specialized to the class of linear reward functions where we introduce and analyze several new linear bandit algorithms which explicitly introduce diversity into their action selection. Finally, we also present an empirical evaluation of these parallel algorithms in several domains, including materials discovery and biological sequence design problems, to demonstrate the utility of parallelized bandits in practical settings. | ['Michael I. Jordan', 'Peter Bartlett', 'Yun S. Song', 'Nilesh Tripuraneni', 'Aldo Pacchiano', 'Jeffrey Chan'] | 2021-05-21 | null | null | null | null | ['decision-making-under-uncertainty', 'decision-making-under-uncertainty'] | ['medical', 'reasoning'] | [ 3.46933842e-01 2.49982268e-01 -7.60583341e-01 -4.29607481e-01
-1.61725008e+00 -1.00078309e+00 1.41639099e-01 4.45004962e-02
-5.79000711e-01 1.26599216e+00 5.87200336e-02 -1.06422043e+00
-5.83498776e-01 -4.38566476e-01 -1.03589308e+00 -8.99649978e-01
-3.32154453e-01 1.05876231e+00 -2.21500739e-01 2.34808832e-01
3.36619139e-01 2.55589247e-01 -1.05529296e+00 2.81541288e-01
5.83253741e-01 1.26732564e+00 -3.18533540e-01 8.46039295e-01
4.99913394e-02 5.52010357e-01 -2.98328608e-01 -7.07844675e-01
7.78921247e-01 -2.64185488e-01 -9.93098497e-01 -1.35339350e-01
5.23317568e-02 -8.37312996e-01 -1.69588700e-01 1.16424215e+00
4.87767726e-01 3.56536776e-01 2.40927413e-01 -8.52032840e-01
-3.39075536e-01 1.29770529e+00 -6.27226710e-01 5.52288413e-01
1.32131040e-01 1.68657050e-01 1.54903150e+00 -2.09968403e-01
4.23531622e-01 1.38825440e+00 4.84732658e-01 5.20278752e-01
-1.71985471e+00 -5.54441333e-01 5.41872561e-01 2.14046687e-01
-7.13403225e-01 -4.61441845e-01 4.77319062e-01 -6.54091462e-02
8.97020280e-01 7.45451510e-01 7.74294496e-01 1.06099927e+00
-4.69897091e-01 1.39052355e+00 1.36005425e+00 -4.75122631e-01
8.60420585e-01 -6.39914498e-02 3.03508371e-01 3.58037591e-01
5.68017423e-01 5.20563781e-01 -5.36167800e-01 -7.45892942e-01
4.73327339e-01 5.77730238e-02 -1.70797586e-01 -6.52786613e-01
-9.42290246e-01 1.02244973e+00 4.36164113e-03 -2.84108430e-01
-3.19446623e-01 6.44844115e-01 3.96270156e-01 5.72067559e-01
5.97529054e-01 5.85837126e-01 -6.99104786e-01 -4.37028110e-01
-9.34643030e-01 5.37641525e-01 1.04262447e+00 1.04968393e+00
5.70257246e-01 -3.02391082e-01 -4.94076163e-01 5.25302529e-01
8.48552957e-03 5.61716795e-01 3.51000987e-02 -1.12383068e+00
8.30276489e-01 -2.73862153e-01 9.93855596e-01 -2.95203209e-01
-2.42151827e-01 -6.60431862e-01 -4.07922179e-01 8.23997632e-02
4.91406411e-01 -4.80500638e-01 -8.91667962e-01 1.52207172e+00
6.31938040e-01 -2.03222334e-01 -5.20612895e-02 8.26158524e-01
-3.60685825e-01 4.27656144e-01 -2.36352980e-01 -5.51030517e-01
9.85308111e-01 -8.37915778e-01 -5.92306912e-01 -3.81931007e-01
5.26908457e-01 -2.64656574e-01 7.91629493e-01 6.74079001e-01
-1.30769157e+00 2.74433047e-01 -9.83800054e-01 9.89236534e-02
2.32445270e-01 -3.12429190e-01 1.35412514e+00 1.13645589e+00
-8.09485734e-01 7.64173508e-01 -9.14357781e-01 1.12572230e-01
9.19077754e-01 4.55770373e-01 2.55728543e-01 -1.61305234e-01
-6.36356652e-01 4.01488304e-01 3.46560329e-01 1.26028314e-01
-1.27567077e+00 -7.10791767e-01 -1.79472864e-01 1.38716727e-01
1.02129209e+00 -7.23423541e-01 1.86442018e+00 -8.97473335e-01
-1.61169302e+00 5.24065793e-01 -1.48565739e-01 -9.81535017e-01
1.00665450e+00 -5.45887530e-01 4.28781360e-01 -1.00120762e-02
7.81907216e-02 2.84059346e-01 4.73869294e-01 -6.87185407e-01
-9.94759023e-01 -5.55462956e-01 3.57062370e-01 3.36042225e-01
-1.09830186e-01 -2.75662970e-02 -1.56543851e-01 -4.89559889e-01
1.73549145e-01 -9.22600389e-01 -8.04358363e-01 -1.74686596e-01
-6.48569167e-01 -1.02790107e-03 -1.48931712e-01 -2.26839676e-01
9.69673932e-01 -1.87506974e+00 7.92298932e-03 4.18328434e-01
-2.15293974e-01 -3.17406893e-01 1.45104036e-01 4.12163496e-01
1.23303421e-01 4.34178770e-01 -1.70362696e-01 -3.60684991e-01
3.91698182e-01 2.77384490e-01 -7.68862128e-01 6.59671724e-01
-4.20206755e-01 9.15518284e-01 -8.46844852e-01 -1.12305105e-01
-3.08044970e-01 -6.72227859e-01 -8.12007606e-01 -4.52983454e-02
-8.56952012e-01 2.39549085e-01 -9.62581694e-01 6.67349160e-01
5.06054640e-01 -3.73349875e-01 3.58588248e-01 7.83405244e-01
1.57485917e-01 4.11687583e-01 -1.14350533e+00 1.61250424e+00
-8.14723149e-02 2.85880715e-01 1.98818877e-01 -1.25663173e+00
1.34324804e-01 1.83895364e-01 4.54909831e-01 -2.71026164e-01
8.61363858e-02 2.48782039e-01 -2.27437153e-01 -2.81054735e-01
1.20910354e-01 -2.96807468e-01 -9.46053341e-02 8.03829908e-01
-3.66523504e-01 1.81182310e-01 1.10899918e-01 -1.05435885e-01
1.21017063e+00 5.24127949e-03 2.91325539e-01 -1.72846481e-01
-2.71870732e-01 2.01550990e-01 7.32824326e-01 1.74940741e+00
-1.83910489e-01 1.37238041e-01 8.02873731e-01 -8.14840972e-01
-1.13237059e+00 -6.82391465e-01 -2.53933460e-01 1.51391685e+00
4.29443382e-02 9.74663720e-02 -5.21463513e-01 -7.38100171e-01
5.39086580e-01 9.67755914e-01 -9.82877135e-01 4.19181913e-01
-1.56255797e-01 -1.13995910e+00 3.52272123e-01 5.07277310e-01
1.99916080e-01 -5.76416373e-01 -9.59931672e-01 3.42126489e-01
1.10950492e-01 -6.96088493e-01 -3.88138503e-01 7.92938709e-01
-1.17613280e+00 -9.49386775e-01 -6.10498190e-01 2.40615811e-02
3.69735628e-01 9.84382853e-02 7.89426029e-01 -3.94866318e-01
-3.41480136e-01 4.19696897e-01 -2.58558601e-01 -7.37566113e-01
9.01055411e-02 -4.90294248e-02 -1.38955027e-01 -1.54551312e-01
2.69769847e-01 -4.58357394e-01 -7.37894356e-01 4.90645729e-02
-6.20772481e-01 7.85703659e-02 4.27776784e-01 1.28799319e+00
6.69867158e-01 -2.77198017e-01 1.63547412e-01 -1.21549547e+00
6.10896647e-01 -4.59163785e-01 -1.16857958e+00 4.65572387e-01
-6.58589602e-01 4.40993130e-01 2.06648484e-01 -4.97008681e-01
-1.04804122e+00 -1.78670675e-01 1.53038964e-01 -2.34027639e-01
2.76528955e-01 4.26156551e-01 2.63204604e-01 2.19808649e-02
6.96717441e-01 1.25448242e-01 -3.40544552e-01 -5.48875332e-01
5.80780447e-01 3.70089471e-01 1.25940308e-01 -1.25044775e+00
2.37225443e-01 6.04904830e-01 1.70439377e-01 -1.27182782e-01
-1.19910300e+00 -3.68890584e-01 1.88079715e-01 3.78842115e-01
1.58614963e-01 -7.00966895e-01 -1.18369973e+00 -1.54888809e-01
-7.95506060e-01 -5.77913284e-01 -7.45551825e-01 6.04887426e-01
-1.18981326e+00 2.75546104e-01 -5.48211277e-01 -1.68318963e+00
-3.50076437e-01 -9.22404945e-01 7.95593917e-01 3.76713052e-02
1.70534804e-01 -6.00729704e-01 1.98966816e-01 5.74744165e-01
1.69457614e-01 4.00688238e-02 8.40087533e-01 -1.09001088e+00
-1.06750941e+00 -4.81188446e-02 -4.69697192e-02 -9.67918038e-02
-4.23301190e-01 -6.04042053e-01 -9.08382356e-01 -5.74332535e-01
-3.31646018e-02 -6.20169103e-01 1.07115901e+00 7.38182008e-01
1.43042803e+00 -8.75452876e-01 -5.27631700e-01 8.19200635e-01
1.14697111e+00 4.49449301e-01 7.98991919e-02 6.95481837e-01
-1.69119105e-01 3.02930027e-01 8.51693094e-01 1.05908060e+00
-1.71202511e-01 4.63173240e-01 5.24573863e-01 2.28897139e-01
7.46929526e-01 -1.77449912e-01 -5.43475300e-02 -2.31548190e-01
-9.10886601e-02 -3.05108339e-01 -7.09217727e-01 6.37342453e-01
-2.37165475e+00 -9.81696010e-01 5.54197252e-01 2.48839402e+00
1.13305259e+00 2.30704427e-01 3.81361604e-01 -9.17415544e-02
4.72115159e-01 -3.96384783e-02 -1.37516558e+00 -5.45207143e-01
-7.34710693e-02 3.01505297e-01 1.21077144e+00 5.06281197e-01
-1.12553978e+00 7.61111438e-01 7.89021921e+00 8.79215777e-01
-6.27556622e-01 3.20356280e-01 1.27514267e+00 -9.67614055e-01
-6.29626691e-01 2.80850679e-01 -7.83517540e-01 2.41887465e-01
1.03125632e+00 -1.81289211e-01 9.19184268e-01 1.27481711e+00
-1.00852765e-01 -2.79685020e-01 -1.40560484e+00 8.60594094e-01
-6.26081705e-01 -1.66524613e+00 -3.21632504e-01 2.46576265e-01
1.07703209e+00 2.02833325e-01 2.37149149e-01 7.29989111e-02
1.37426591e+00 -8.30658019e-01 8.17151070e-01 1.62899435e-01
7.89207876e-01 -8.76854360e-01 5.70341349e-01 5.29162288e-01
-1.97388589e-01 -7.62584150e-01 -5.36764383e-01 -8.71711895e-02
-1.18961059e-01 5.84783018e-01 -9.77913678e-01 4.48187768e-01
9.58276510e-01 -2.78701503e-02 2.96688527e-01 1.36536455e+00
-4.52546217e-02 8.81196439e-01 -9.07957613e-01 -5.65484762e-01
5.51711977e-01 -1.59922689e-01 4.78250533e-01 1.03140080e+00
2.77932733e-01 3.92306238e-01 3.01639676e-01 5.78089178e-01
-1.46289393e-02 1.05973348e-01 -1.11320704e-01 -1.95922837e-01
4.97506768e-01 4.50963736e-01 -5.07510185e-01 -2.51887262e-01
9.94091574e-03 7.62267411e-01 5.78651667e-01 5.34414649e-01
-5.83897293e-01 -6.10330924e-02 7.64362812e-01 -3.31117243e-01
6.98682487e-01 1.19777136e-01 -6.54979944e-01 -1.00525212e+00
1.13372132e-01 -9.14174259e-01 7.95645595e-01 -2.91912526e-01
-1.13716626e+00 -1.14844523e-01 1.64418235e-01 -4.54082668e-01
-3.03931147e-01 -4.53975558e-01 -1.22020409e-01 6.46837890e-01
-1.35976851e+00 -6.43564641e-01 6.55031621e-01 3.26774567e-01
4.50814933e-01 7.32447654e-02 6.50234222e-01 -2.88111627e-01
-5.93413413e-01 6.92286551e-01 1.08648777e+00 -3.51247698e-01
1.01349570e-01 -1.51175165e+00 3.56908143e-01 6.60304904e-01
2.24626347e-01 6.37295425e-01 1.02375889e+00 -4.43202138e-01
-1.59545851e+00 -6.20801508e-01 1.76676765e-01 -2.08538935e-01
7.53213584e-01 -3.29684794e-01 -1.71565503e-01 1.18101263e+00
-1.36885718e-01 -1.69578250e-02 9.79649961e-01 7.73571491e-01
-4.25672501e-01 -4.36870813e-01 -1.23365426e+00 6.10185206e-01
1.26975179e+00 -2.11429447e-01 -3.28375220e-01 7.53559351e-01
7.44218588e-01 -6.49252057e-01 -5.69001317e-01 2.32550323e-01
8.34388793e-01 -9.33006704e-01 7.56539822e-01 -1.23155081e+00
-8.60753804e-02 2.12471724e-01 -2.29553521e-01 -9.38644409e-01
-3.00153434e-01 -1.55773652e+00 -3.02148014e-01 5.98529041e-01
5.60335100e-01 -7.24604011e-01 1.12321401e+00 8.45635116e-01
3.15808088e-01 -1.05374420e+00 -1.53032577e+00 -6.32446647e-01
1.49596617e-01 -6.64862573e-01 7.79818714e-01 4.13040668e-01
1.73816651e-01 -2.44427294e-01 -6.89116836e-01 4.31984998e-02
8.96500468e-01 5.56511998e-01 7.14523792e-01 -9.03202415e-01
-1.01776350e+00 -4.11316246e-01 2.25194529e-01 -1.69702148e+00
-2.55206347e-01 -5.07958651e-01 1.69459224e-01 -1.00751734e+00
6.53192461e-01 -7.28205860e-01 -6.74574614e-01 5.67821920e-01
-1.35634750e-01 -3.37383270e-01 2.74247415e-02 7.29450732e-02
-9.42411423e-01 4.21641469e-01 1.02531469e+00 -1.60583839e-01
-8.05826634e-02 5.48569024e-01 -1.23368752e+00 3.35151911e-01
4.76218075e-01 -7.12341785e-01 -4.11633343e-01 -3.45937997e-01
5.39832115e-01 5.93963981e-01 -6.46584034e-02 -4.92746413e-01
2.22228140e-01 -8.04511189e-01 2.74532557e-01 -6.29614711e-01
3.25205386e-01 -5.76122403e-01 2.67330203e-02 5.52625775e-01
-1.03402972e+00 -2.95263261e-01 1.20174304e-01 1.21086287e+00
4.86603200e-01 -3.67513716e-01 4.90194708e-01 -2.41154224e-01
1.05180122e-01 4.30065185e-01 -2.36316592e-01 1.32028073e-01
1.14568925e+00 -3.62871625e-02 -2.49964908e-01 -5.46652555e-01
-7.59599268e-01 5.60808301e-01 1.57371640e-01 -2.78634429e-01
2.01937512e-01 -8.10388744e-01 -6.11537635e-01 -2.08749160e-01
-6.08809330e-02 2.84641609e-02 1.35828942e-01 5.68993092e-01
-2.58054197e-01 9.24364865e-01 2.60118246e-01 -4.00245756e-01
-1.07587099e+00 9.14543569e-01 3.07744592e-01 -6.37488663e-01
-3.14254940e-01 1.34295750e+00 1.75768122e-01 -1.64568853e-02
6.33752704e-01 -3.94580632e-01 6.13737941e-01 -2.69701689e-01
5.91022551e-01 4.98382568e-01 -1.58756390e-01 6.51352108e-01
-4.37176302e-02 -1.77305669e-01 -4.55038816e-01 -5.93625247e-01
1.45364952e+00 -1.67354226e-01 7.75459558e-02 5.02916932e-01
5.48498452e-01 -1.44642830e-01 -1.60017776e+00 -6.16163790e-01
4.11575079e-01 -7.49773443e-01 5.67550659e-02 -9.73067760e-01
-4.57167149e-01 6.24544561e-01 4.27668810e-01 2.29376733e-01
8.55774939e-01 -6.61649704e-02 3.09182465e-01 1.11282301e+00
8.70897651e-01 -1.20090771e+00 -4.21147764e-01 6.45099133e-02
4.96965677e-01 -1.06023943e+00 2.35677823e-01 7.49066249e-02
-3.95792991e-01 9.20469105e-01 -7.29277283e-02 9.70971659e-02
4.35679495e-01 1.14109606e-01 -4.28369194e-01 2.50111789e-01
-1.23072267e+00 -1.17945999e-01 -1.19832091e-01 3.01757365e-01
-1.37839690e-01 4.50502515e-01 -2.78548628e-01 6.04487300e-01
-1.20608956e-01 6.77078292e-02 1.90153882e-01 1.04677093e+00
-6.64653122e-01 -1.07319236e+00 -4.89815205e-01 7.32368648e-01
-9.99141812e-01 -2.18940005e-01 -1.91414401e-01 2.45328039e-01
-4.49833035e-01 1.03833246e+00 -1.11567780e-01 1.88231185e-01
-2.47253537e-01 -7.39625189e-03 6.49759591e-01 -3.86001408e-01
-4.43011522e-01 3.28300267e-01 4.57437456e-01 -7.87354946e-01
-1.43529996e-01 -1.05050445e+00 -6.52921557e-01 -4.09606844e-01
-4.53297913e-01 6.30959630e-01 6.29237473e-01 9.90642011e-01
2.63113827e-01 -1.08682131e-02 6.87252045e-01 -4.39693242e-01
-1.63258851e+00 -7.61554778e-01 -7.52795935e-01 -1.88898183e-02
6.10745847e-01 -3.54770452e-01 -1.96171537e-01 -4.51880872e-01] | [4.513889789581299, 3.269376754760742] |
f3089e2b-7b73-43ec-ac09-d1b7231f4355 | correlated-time-series-forecasting-using-deep | 1808.09794 | null | http://arxiv.org/abs/1808.09794v2 | http://arxiv.org/pdf/1808.09794v2.pdf | Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results | Cyber-physical systems often consist of entities that interact with each
other over time. Meanwhile, as part of the continued digitization of industrial
processes, various sensor technologies are deployed that enable us to record
time-varying attributes (a.k.a., time series) of such entities, thus producing
correlated time series. To enable accurate forecasting on such correlated time
series, this paper proposes two models that combine convolutional neural
networks (CNNs) and recurrent neural networks (RNNs). The first model employs a
CNN on each individual time series, combines the convoluted features, and then
applies an RNN on top of the convoluted features in the end to enable
forecasting. The second model adds additional auto-encoders into the individual
CNNs, making the second model a multi-task learning model, which provides
accurate and robust forecasting. Experiments on two real-world correlated time
series data set suggest that the proposed two models are effective and
outperform baselines in most settings.
This report extends the paper "Correlated Time Series Forecasting using
Multi-Task Deep Neural Networks," to appear in ACM CIKM 2018, by providing
additional experimental results. | ['Gabriel-Marcel Muresan', 'Darius-Valer Micu', 'Razvan-Gabriel Cirstea', 'Chenjuan Guo', 'Bin Yang'] | 2018-08-29 | null | null | null | null | ['correlated-time-series-forecasting'] | ['time-series'] | [ 9.45448801e-02 -3.23899657e-01 1.16644122e-01 -3.41428190e-01
-4.96288687e-01 -4.12723899e-01 6.21019959e-01 7.06698596e-02
-4.96631041e-02 4.20447648e-01 1.75436437e-01 -4.10343379e-01
-2.08791390e-01 -5.95682025e-01 -7.46705115e-01 -7.08508372e-01
-4.50008810e-01 -2.75897980e-02 -2.48154014e-01 -2.52247185e-01
-2.87977718e-02 3.49514425e-01 -1.15104318e+00 1.93690732e-01
6.60996795e-01 1.66015387e+00 1.87966362e-01 6.46097243e-01
4.55024466e-02 1.15975630e+00 -7.63965786e-01 -1.02510206e-01
3.07539165e-01 9.14790556e-02 -3.50760758e-01 -2.05734640e-01
-3.03376883e-01 -3.25571001e-01 -4.93550897e-01 6.47804260e-01
1.91802576e-01 2.73509741e-01 4.27405119e-01 -1.36046457e+00
-1.00081730e+00 8.16565514e-01 -3.47937614e-01 2.02026635e-01
9.26799923e-02 7.19711408e-02 7.79560566e-01 -5.88215828e-01
4.52295542e-02 1.13057458e+00 8.69607151e-01 -9.92607921e-02
-9.36306536e-01 -7.74263442e-01 3.81113857e-01 8.89267847e-02
-9.73259091e-01 -1.45561188e-01 1.07956970e+00 -3.08131486e-01
1.27675474e+00 -4.80254926e-03 6.20488226e-01 1.38657248e+00
9.53756332e-01 7.17030823e-01 7.47325361e-01 8.96695331e-02
1.81523755e-01 -2.67573327e-01 8.53703246e-02 4.60328441e-03
-7.43627474e-02 1.66700408e-01 -1.18661217e-01 -1.28432870e-01
7.04612195e-01 9.57348943e-01 1.36958167e-01 2.18862221e-01
-1.55303025e+00 4.80456084e-01 7.23087132e-01 5.58975101e-01
-1.10193884e+00 3.10363173e-01 6.77518308e-01 6.55300975e-01
8.28861475e-01 5.56081831e-01 -7.93795407e-01 -1.60616115e-01
-3.98280114e-01 1.43153146e-01 8.00611675e-01 8.95088851e-01
3.23856264e-01 3.96906257e-01 3.90460566e-02 6.67708158e-01
-4.86880466e-02 5.28105915e-01 8.87287319e-01 -5.96535206e-01
7.36364901e-01 5.04244328e-01 1.41193390e-01 -1.01976001e+00
-7.30509341e-01 -5.90137243e-01 -1.35358882e+00 -3.03762883e-01
9.80631635e-02 -4.70263392e-01 -9.06591415e-01 1.63554418e+00
-3.41003947e-02 6.82344496e-01 2.30083466e-01 7.15820551e-01
2.44916439e-01 1.04520500e+00 9.99927521e-02 -2.71249861e-01
1.15130985e+00 -9.01358306e-01 -1.05430520e+00 2.48384461e-01
4.96290863e-01 -7.39022315e-01 4.20551717e-01 4.27878529e-01
-8.18651140e-01 -8.09523761e-01 -1.12632072e+00 8.93423855e-02
-9.62862968e-01 7.08345175e-02 7.99696684e-01 -1.16655380e-01
-7.69315958e-01 9.18907523e-01 -1.07416022e+00 1.44398257e-01
2.53572583e-01 3.02441269e-01 1.09843295e-02 1.90069437e-01
-1.55831826e+00 9.03861165e-01 2.36144692e-01 6.04910553e-01
-7.11434126e-01 -6.88043892e-01 -7.03878224e-01 1.50595769e-01
1.40938133e-01 -3.96936506e-01 1.41220951e+00 -7.98669159e-01
-1.61497140e+00 -2.41643354e-01 8.15471336e-02 -6.04622245e-01
1.41596660e-01 -5.26257575e-01 -1.15853083e+00 -4.41529363e-01
-1.37307554e-01 1.03998166e-02 8.91436219e-01 -6.97400272e-01
-6.98715746e-01 -1.94512203e-01 -1.46452695e-01 -2.38574401e-01
-4.26163644e-01 -7.76018528e-03 1.03791744e-01 -7.43190348e-01
1.62461512e-02 -1.04889870e+00 -5.81313550e-01 -7.58935630e-01
-6.32013381e-01 -6.89797699e-01 1.16909206e+00 -6.89398468e-01
1.15944493e+00 -2.20722556e+00 -8.64294916e-03 1.71273455e-01
3.81555289e-01 2.48559907e-01 -2.78616577e-01 7.46712923e-01
-5.44526517e-01 -2.46681646e-01 2.14340210e-01 -5.97854495e-01
-1.96649190e-02 1.13257412e-02 -9.51135933e-01 3.73307705e-01
5.49509108e-01 1.10494053e+00 -8.91946971e-01 2.70956129e-01
3.30472410e-01 6.55954123e-01 4.19296652e-01 2.85251647e-01
-2.50486732e-01 3.58940303e-01 -4.62948471e-01 6.02255046e-01
4.31279480e-01 -6.60454750e-01 -9.10800230e-03 -3.87069911e-01
-3.29101503e-01 3.72552544e-01 -8.01919043e-01 1.32792580e+00
-6.77984595e-01 5.56847870e-01 -5.85804403e-01 -1.15001929e+00
1.09008503e+00 8.28149021e-01 1.05934691e+00 -8.07855010e-01
3.00103903e-01 2.50625700e-01 -2.91850567e-02 -3.49310905e-01
5.80877662e-01 2.07660407e-01 -2.82210171e-01 4.05738115e-01
-1.16770059e-01 1.14895791e-01 -1.86547905e-01 -1.81903437e-01
1.21480954e+00 -2.27726437e-02 2.00122893e-01 2.73794353e-01
2.27422506e-01 -4.43758488e-01 5.97428322e-01 3.18549812e-01
9.16887820e-03 2.24366128e-01 2.91980505e-01 -1.08876002e+00
-1.22798467e+00 -7.50348985e-01 1.92205921e-01 9.33167696e-01
6.56716079e-02 -1.38022289e-01 1.67268038e-01 -3.85237962e-01
2.79958904e-01 4.86709863e-01 -7.35388875e-01 -3.08623284e-01
-6.28392339e-01 -5.08534789e-01 2.91596293e-01 9.32492614e-01
2.91402549e-01 -1.18152332e+00 -5.33217728e-01 7.94045568e-01
4.06495221e-02 -1.11133623e+00 -2.62230635e-01 6.11851573e-01
-7.32879162e-01 -7.24690020e-01 -7.57583857e-01 -5.65577507e-01
1.95675790e-01 4.24821228e-01 9.02948916e-01 -4.52892393e-01
1.06173791e-01 -2.66165007e-03 -4.10813570e-01 -8.97729039e-01
-4.39073630e-02 9.71387252e-02 2.48320088e-01 2.07949832e-01
3.71307045e-01 -8.53447437e-01 -4.08116013e-01 2.25220397e-02
-8.88136744e-01 -7.32826591e-02 6.70839965e-01 6.67919934e-01
4.73804444e-01 2.47522160e-01 1.00857890e+00 -5.23924768e-01
9.03404653e-01 -1.05933368e+00 -6.95245147e-01 2.90388823e-01
-6.47544503e-01 -1.30176574e-01 1.30831563e+00 -9.76673186e-01
-7.67782986e-01 -5.70055842e-02 2.82616198e-01 -9.98004615e-01
9.10693482e-02 1.00875235e+00 4.17232335e-01 5.21149278e-01
1.20646015e-01 1.86967835e-01 -8.72482583e-02 -5.39763808e-01
2.02323243e-01 6.71339273e-01 6.96322083e-01 -1.67989105e-01
7.82595813e-01 1.88075960e-01 -1.22188800e-03 -4.10521477e-01
-8.46119583e-01 -4.22171891e-01 -4.21449274e-01 -2.91279942e-01
6.89364910e-01 -1.24002278e+00 -9.20461595e-01 6.50587380e-01
-1.27821207e+00 -3.02753329e-01 -1.69643134e-01 9.15699661e-01
-3.51721793e-01 -2.70796567e-01 -9.09966588e-01 -9.76910174e-01
-4.58975017e-01 -8.06164205e-01 1.26259768e+00 1.12975515e-01
-1.97596192e-01 -1.16932523e+00 4.60903570e-02 -2.59972185e-01
7.50841737e-01 5.86272836e-01 6.32495046e-01 -9.88493741e-01
-4.13098067e-01 -8.26307595e-01 -1.04441211e-01 4.17139083e-01
5.39017379e-01 4.15261276e-02 -8.92493725e-01 -2.15526283e-01
6.14246614e-02 -1.24005921e-01 7.11636007e-01 5.69001257e-01
1.39892149e+00 -1.87332556e-01 -4.30207372e-01 5.22608399e-01
1.06045568e+00 7.08374560e-01 4.23823267e-01 1.04947753e-01
8.93666863e-01 2.19827041e-01 4.57265943e-01 6.04444027e-01
7.77406633e-01 3.97537410e-01 5.52534342e-01 -1.81756422e-01
4.32205200e-01 -3.29696201e-02 4.73915100e-01 1.63106692e+00
-3.18194658e-01 -2.33112350e-01 -7.61406064e-01 5.75819731e-01
-2.07182837e+00 -9.87038910e-01 3.26254256e-02 1.80288780e+00
4.54530001e-01 -2.11959183e-02 1.24737173e-01 1.37535453e-01
6.86145127e-01 3.54678422e-01 -1.08285832e+00 -3.26699495e-01
-6.00236394e-02 4.73860232e-03 5.32819211e-01 -1.12221584e-01
-1.42517042e+00 4.93797988e-01 6.02701139e+00 1.42182261e-01
-1.64331162e+00 -1.19085431e-01 5.66491127e-01 2.64503360e-02
-3.49775143e-02 -3.31704766e-01 -4.25036967e-01 7.89481759e-01
1.55053794e+00 -5.43694675e-01 5.59724033e-01 8.85886490e-01
2.76755244e-01 5.66392601e-01 -1.12547851e+00 7.79815018e-01
-3.56963307e-01 -1.17429173e+00 -3.36200476e-01 1.86390817e-01
8.26623321e-01 4.54735935e-01 4.58320200e-01 6.27302229e-01
7.38735437e-01 -9.42861378e-01 5.31323910e-01 9.38695073e-01
3.82146150e-01 -6.11698031e-01 1.17674303e+00 5.43487035e-02
-1.60175240e+00 -5.54922044e-01 -2.12277174e-01 -2.50353724e-01
2.47121453e-01 9.77057040e-01 -6.06654644e-01 8.37152481e-01
7.18775153e-01 1.39854717e+00 -1.47286355e-01 7.17711031e-01
4.16073143e-01 5.41633427e-01 -2.82206386e-01 -1.39368668e-01
2.52589136e-01 -2.11768612e-01 2.53894269e-01 7.86143482e-01
6.65621042e-01 -1.42000049e-01 3.80925328e-01 6.68269098e-01
-1.30765900e-01 -3.71930927e-01 -7.57298470e-01 -5.14377356e-01
5.76403677e-01 1.23297572e+00 -4.60345089e-01 -5.55716991e-01
-5.61600685e-01 6.95867062e-01 1.90864250e-01 5.79151809e-01
-8.95908773e-01 -5.20590961e-01 6.97123945e-01 -6.63018942e-01
2.80662537e-01 -5.21216929e-01 -3.04791063e-01 -1.16627753e+00
2.70730168e-01 -6.66370749e-01 3.41266096e-01 -6.85997009e-01
-1.87810934e+00 8.25029254e-01 -4.17122692e-01 -1.79073167e+00
-6.00326777e-01 -4.49948132e-01 -5.58058381e-01 9.43151593e-01
-1.43075848e+00 -1.12808490e+00 -2.07684129e-01 6.32482171e-01
6.01253152e-01 -2.63102591e-01 8.01709831e-01 2.70809442e-01
-7.69578218e-01 7.18027204e-02 4.04765040e-01 1.35263085e-01
5.63814223e-01 -1.18916607e+00 8.28098834e-01 6.97058260e-01
-3.49028677e-01 7.52787173e-01 3.57089937e-01 -6.75045133e-01
-1.77887678e+00 -1.61127484e+00 8.31212223e-01 -2.08728731e-01
1.05179441e+00 -2.16149762e-01 -9.66822147e-01 9.98865604e-01
1.91598147e-01 9.58357900e-02 6.14530623e-01 1.47578299e-01
-5.95409274e-01 -5.33275127e-01 -6.41924918e-01 3.17120880e-01
4.63047057e-01 -7.70332336e-01 -4.91332471e-01 5.33735871e-01
1.15805554e+00 -3.65884453e-01 -1.40667462e+00 5.61786354e-01
6.40184641e-01 -3.47012788e-01 8.91711771e-01 -6.36312187e-01
7.39087999e-01 -1.54985681e-01 -1.96896821e-01 -1.69725966e+00
-5.53257823e-01 -6.29844487e-01 -5.50699711e-01 9.19108629e-01
3.19943756e-01 -1.02654338e+00 2.78144404e-02 7.08215058e-01
-4.06513125e-01 -7.61985421e-01 -7.62498021e-01 -1.02882040e+00
-1.15875036e-01 -5.40881336e-01 1.21614802e+00 1.31241715e+00
1.67478904e-01 1.93620667e-01 -6.71653926e-01 3.99491876e-01
7.82694295e-02 3.57634813e-01 5.51115751e-01 -1.33426857e+00
9.91259366e-02 -4.67347383e-01 -2.72744477e-01 -8.37892771e-01
6.96203634e-02 -5.38953841e-01 5.60960025e-02 -1.09624648e+00
-4.09972459e-01 -2.90279418e-01 -1.02327573e+00 5.20913184e-01
-1.92510217e-01 -2.82535464e-01 2.12901503e-01 3.51687908e-01
-7.10462749e-01 6.65577471e-01 9.61636066e-01 -1.97100163e-01
-2.62495756e-01 2.83406645e-01 -4.30267811e-01 3.23881537e-01
8.54749739e-01 -5.31352125e-02 -3.75090092e-01 -4.00318831e-01
8.80491063e-02 4.88121092e-01 3.13308924e-01 -1.09674168e+00
5.13478577e-01 -1.84468314e-01 6.42807782e-01 -7.57359862e-01
5.90487957e-01 -1.27070105e+00 3.86801809e-01 4.11867648e-01
-5.88304043e-01 6.26633644e-01 3.31435800e-02 6.13502860e-01
-4.72652793e-01 6.70655131e-01 1.10192135e-01 1.75074264e-01
-4.17449087e-01 6.73786402e-01 -2.93808162e-01 -7.16143548e-01
9.86292720e-01 1.36439592e-01 -3.55327308e-01 -6.44374490e-01
-4.30654675e-01 3.84003729e-01 -3.16044480e-01 1.04273236e+00
4.14103240e-01 -1.61103857e+00 -4.43256408e-01 2.21196949e-01
-7.11078122e-02 3.57121639e-02 2.66629100e-01 8.21439922e-01
1.79736629e-01 6.29660189e-01 -1.36779338e-01 -4.22487944e-01
-5.81939816e-01 1.01419938e+00 1.49023101e-01 -4.23040003e-01
-6.40401959e-01 4.01076406e-01 -1.81430906e-01 -2.93684572e-01
2.74888247e-01 -9.07477558e-01 -2.34325767e-01 1.36637226e-01
5.52343965e-01 3.62124503e-01 1.22331809e-02 -3.59816968e-01
-1.54457062e-01 2.90032417e-01 -2.67407745e-01 2.87115276e-01
1.91438067e+00 -1.36245847e-01 -7.49720186e-02 1.15753686e+00
1.48679197e+00 -6.30124271e-01 -1.15452552e+00 -6.52155876e-01
2.19085932e-01 3.90961766e-02 -3.63859534e-02 -7.11338222e-01
-1.31084883e+00 6.80104375e-01 3.22878569e-01 1.02692246e+00
1.38722205e+00 -4.20193255e-01 1.22026098e+00 5.36273658e-01
4.11989599e-01 -1.05137765e+00 -2.18961630e-02 7.95009851e-01
8.08744550e-01 -1.09058166e+00 -2.64177799e-01 -3.45641822e-02
-6.05826855e-01 1.36258507e+00 3.43757629e-01 -3.76739293e-01
9.75246608e-01 3.81012619e-01 1.63153768e-01 -1.48287281e-01
-1.33740652e+00 5.06570153e-02 1.82729408e-01 2.89158553e-01
4.40008223e-01 3.41308653e-01 2.17480570e-01 8.53243172e-01
-3.20827246e-01 2.69246340e-01 1.92587420e-01 7.42003441e-01
2.97476828e-01 -6.42342329e-01 -1.61238179e-01 6.72928214e-01
-4.35600042e-01 2.49281079e-01 -2.53048800e-02 4.33762521e-01
-1.06425241e-01 1.23905957e+00 3.90205592e-01 -9.69374776e-01
4.68300372e-01 1.21032648e-01 -4.13314015e-01 -5.01887016e-02
-8.78686011e-01 5.64323999e-02 -1.05370820e-01 -7.46942937e-01
-3.21526974e-01 -6.74098253e-01 -9.87966239e-01 -4.57173824e-01
-3.48867565e-01 -4.01502959e-02 9.21392024e-01 1.06128430e+00
7.35613763e-01 1.26422477e+00 1.35435402e+00 -1.18825316e+00
-7.09104478e-01 -1.28673291e+00 -6.78654432e-01 4.14838135e-01
8.03104103e-01 -5.24897873e-01 -2.31346279e-01 1.52453646e-01] | [6.914088726043701, 2.93082857131958] |
70271b49-222d-4aa0-9a9e-858d1b3fc089 | temporal-knowledge-graph-completion-using-a | null | null | https://aclanthology.org/2021.naacl-main.202 | https://aclanthology.org/2021.naacl-main.202.pdf | Temporal Knowledge Graph Completion using a Linear Temporal Regularizer and Multivector Embeddings | Representation learning approaches for knowledge graphs have been mostly designed for static data. However, many knowledge graphs involve evolving data, e.g., the fact (The President of the United States is Barack Obama) is valid only from 2009 to 2017. This introduces important challenges for knowledge representation learning since the knowledge graphs change over time. In this paper, we present a novel time-aware knowledge graph embebdding approach, TeLM, which performs 4th-order tensor factorization of a Temporal knowledge graph using a Linear temporal regularizer and Multivector embeddings. Moreover, we investigate the effect of the temporal dataset{'}s time granularity on temporal knowledge graph completion. Experimental results demonstrate that our proposed models trained with the linear temporal regularizer achieve the state-of-the-art performances on link prediction over four well-established temporal knowledge graph completion benchmarks. | ['Jens Lehmann', 'Mojtaba Nayyeri', 'Yung-Yu Chen', 'Chengjin Xu'] | 2021-06-01 | null | null | null | naacl-2021-4 | ['temporal-knowledge-graph-completion'] | ['knowledge-base'] | [-4.02949363e-01 -6.79889470e-02 -8.57750595e-01 -3.89450341e-02
-7.56924897e-02 -6.14967346e-01 6.03543580e-01 4.85014617e-01
-2.40637287e-01 6.15128398e-01 3.79414767e-01 -5.32883465e-01
-6.72200501e-01 -9.08814192e-01 -8.75617385e-01 -3.79017949e-01
-6.28007114e-01 4.55477208e-01 2.14343041e-01 -2.40792170e-01
-1.32687867e-01 3.10713440e-01 -1.02950585e+00 8.36903304e-02
7.49292433e-01 7.76096880e-01 -2.94280440e-01 5.09492457e-01
-5.27865216e-02 1.12629139e+00 -2.42178351e-01 -8.46263051e-01
1.34906754e-01 2.37985715e-01 -1.26496112e+00 -5.25595620e-02
4.92007315e-01 -2.74804503e-01 -1.12041771e+00 7.47756779e-01
-9.60577428e-02 5.25327325e-01 4.33558971e-01 -1.35401022e+00
-1.23371542e+00 9.18322027e-01 -4.70038265e-01 5.75851977e-01
5.08400381e-01 -1.29685611e-01 1.41900325e+00 -6.35346234e-01
9.84679937e-01 1.08637714e+00 6.22723937e-01 6.37128502e-02
-1.21441913e+00 -3.77663314e-01 6.43681824e-01 9.53195095e-01
-1.52595568e+00 2.74584331e-02 8.22415709e-01 -6.37310624e-01
1.21510148e+00 -3.50245610e-02 8.41599643e-01 9.80717182e-01
3.74450505e-01 6.80881798e-01 5.84297657e-01 -2.34291986e-01
-1.19418643e-01 -4.64610696e-01 5.70381105e-01 1.01357877e+00
3.56892496e-01 -9.73059162e-02 -8.38983655e-01 -2.91594893e-01
4.96818542e-01 2.09630698e-01 -3.66705745e-01 -6.02663934e-01
-1.37094486e+00 6.60921991e-01 6.06852353e-01 4.02949214e-01
-3.76576334e-01 4.96100992e-01 6.37999535e-01 3.34913164e-01
2.91109741e-01 5.61296120e-02 -5.33041537e-01 -1.57910615e-01
-6.18221760e-01 1.13693401e-01 7.90249348e-01 1.01385736e+00
7.29718924e-01 1.06941640e-01 -1.63976267e-01 4.88737613e-01
1.28458902e-01 9.84819606e-02 3.46491724e-01 -5.41897655e-01
5.78012884e-01 8.24233055e-01 4.98915873e-02 -1.12152410e+00
-3.79766762e-01 -5.03831446e-01 -6.91228449e-01 -7.49701202e-01
4.93390411e-01 1.75092861e-01 -9.47439075e-01 1.43886399e+00
3.64731848e-01 7.21191108e-01 5.15585989e-02 7.24193037e-01
7.98814893e-01 5.42100847e-01 7.73663260e-03 -2.88801998e-01
1.29661953e+00 -9.71026421e-01 -9.99155164e-01 2.16489002e-01
7.89659798e-01 -4.30601805e-01 7.01229095e-01 1.42179564e-01
-6.80321693e-01 -3.39488953e-01 -8.96170318e-01 -1.21590599e-01
-6.84830844e-01 -1.13235608e-01 1.34695125e+00 2.89655805e-01
-7.80266821e-01 8.23416233e-01 -1.12648213e+00 -5.21033943e-01
2.71290779e-01 -2.03661732e-02 -5.48637390e-01 -5.23957849e-01
-1.49124849e+00 7.52456427e-01 7.69758105e-01 1.84398189e-01
-8.82761598e-01 -1.02316642e+00 -7.87802100e-01 5.41886576e-02
6.41202152e-01 -7.58687139e-01 8.48455966e-01 -1.90776840e-01
-1.08227098e+00 4.52731758e-01 -2.19391569e-01 -6.74536586e-01
2.78989136e-01 -3.19376320e-01 -1.03684974e+00 -7.86808729e-02
1.28707170e-01 -5.19259088e-02 7.66091108e-01 -9.51075852e-01
-3.57925445e-01 -3.33614141e-01 4.06789213e-01 -2.41292208e-01
-6.31163180e-01 -4.04921234e-01 -8.90985012e-01 -6.75489008e-01
-1.67186838e-02 -9.01146233e-01 -8.55766162e-02 -4.39658105e-01
-4.73661989e-01 -4.30668086e-01 9.68116701e-01 -1.02069414e+00
1.82831192e+00 -1.98414207e+00 3.94493848e-01 2.37006664e-01
2.83800095e-01 1.02481991e-01 -5.51066920e-02 7.66416728e-01
-3.00906777e-01 1.00651965e-01 2.87602067e-01 -5.04136086e-03
4.96682674e-02 5.49135208e-01 -5.67259192e-01 3.43883872e-01
-9.23533216e-02 1.18984866e+00 -1.27632153e+00 -4.40773606e-01
-9.99643579e-02 5.07232428e-01 -3.51745248e-01 -1.90575436e-01
-2.77380019e-01 1.40869468e-01 -5.04670262e-01 7.94984818e-01
3.10343683e-01 -7.83428192e-01 7.35772550e-01 -6.93956912e-01
1.31115839e-01 1.53773293e-01 -8.46340835e-01 2.02813363e+00
-1.40195668e-01 3.55809063e-01 -6.55979156e-01 -7.75005758e-01
5.11252522e-01 3.08183759e-01 8.58343840e-01 -6.08510375e-01
-1.33337319e-01 -1.19520731e-01 4.94622588e-02 -2.88294375e-01
8.99465084e-01 2.58563876e-01 5.18539771e-02 3.81040722e-01
2.22773090e-01 3.29854131e-01 6.32019818e-01 8.75332713e-01
1.55493760e+00 2.54751265e-01 1.06885068e-01 1.39483047e-04
1.81242436e-01 8.16710740e-02 7.79137135e-01 1.98135898e-01
-1.89661652e-01 -5.68260401e-02 6.54004455e-01 -6.68202579e-01
-7.14307845e-01 -1.26568425e+00 1.01050004e-01 9.81748641e-01
-5.71572781e-02 -1.05245793e+00 -2.44176053e-02 -1.08502281e+00
5.13583660e-01 6.49020016e-01 -8.18678141e-01 -4.18804228e-01
-4.17240351e-01 -4.62970287e-01 3.69011223e-01 5.81962585e-01
2.54683584e-01 -3.52432430e-01 1.92113087e-01 3.59880805e-01
-2.72487998e-01 -1.46721232e+00 -6.70448720e-01 -1.64898068e-01
-9.95693266e-01 -1.40820622e+00 -2.60787785e-01 -5.87334335e-01
5.06118417e-01 4.43081319e-01 1.10253990e+00 -4.47229557e-02
-2.03440994e-01 1.01221371e+00 -6.14300072e-01 1.55797243e-01
2.07766607e-01 -2.06761323e-02 1.78307980e-01 1.83239788e-01
1.43395737e-01 -8.16932559e-01 -4.93347436e-01 6.68077022e-02
-8.45805645e-01 -3.31659406e-01 2.33939126e-01 7.83105969e-01
7.07280576e-01 4.89634573e-01 5.57246864e-01 -9.50070798e-01
6.61414802e-01 -5.98609269e-01 -4.78586823e-01 7.52836764e-01
-9.12811995e-01 2.57809609e-01 4.37470794e-01 -6.02024436e-01
-8.78279865e-01 -1.52384937e-01 7.70479381e-01 -9.29099798e-01
8.41288865e-01 1.20305574e+00 3.42417508e-01 -1.45453364e-01
5.90761304e-01 2.01736271e-01 -4.51831132e-01 -4.08168823e-01
8.99729550e-01 -1.81370378e-01 5.30068398e-01 -8.00972462e-01
1.11143351e+00 6.57082856e-01 1.55995741e-01 -5.20257056e-01
-9.80247617e-01 -6.26409113e-01 -6.23905599e-01 -3.50035101e-01
5.98849058e-01 -1.03680873e+00 -8.13192904e-01 1.35731017e-02
-1.07458091e+00 -1.27395198e-01 -3.43038648e-01 5.90690494e-01
-2.71182269e-01 7.09301412e-01 -6.41392708e-01 -3.57196391e-01
-2.73512155e-01 -3.86695564e-01 4.80593145e-01 -2.37843916e-02
-3.60344052e-02 -1.34539723e+00 2.58673847e-01 6.17835879e-01
1.38336331e-01 4.09312874e-01 1.23620975e+00 -2.85776466e-01
-9.42766726e-01 -2.13779211e-01 -2.57616282e-01 1.30918071e-01
2.72584081e-01 2.16313958e-01 -4.95936006e-01 -5.00131428e-01
-8.79416227e-01 -1.54745504e-01 1.10051847e+00 1.26529187e-01
1.05407608e+00 -4.12741363e-01 -5.38068175e-01 3.97415459e-01
1.46416938e+00 -1.77120075e-01 4.93782014e-01 1.91696454e-02
1.23112774e+00 1.55764058e-01 7.29321301e-01 6.16598904e-01
9.38443244e-01 6.71402276e-01 3.14119339e-01 6.39486074e-01
-2.97454268e-01 -5.50646007e-01 2.83610046e-01 1.24841261e+00
-6.54063642e-01 -4.79624160e-02 -1.03021121e+00 1.11021996e+00
-2.24417853e+00 -9.78977144e-01 -2.92817920e-01 2.15845394e+00
7.64077306e-01 1.15440540e-01 -5.89802600e-02 -3.20666004e-03
4.61317837e-01 4.29206252e-01 -5.03772795e-01 -1.23388283e-01
-2.44938061e-02 1.03840508e-01 7.61807978e-01 3.50433230e-01
-9.58659172e-01 9.63175654e-01 5.63192272e+00 6.54752135e-01
-7.37901092e-01 3.48748326e-01 -3.25309664e-01 9.08821076e-02
-5.49649417e-01 5.26335895e-01 -5.43780684e-01 1.91439301e-01
8.07811975e-01 -7.43904769e-01 6.36716604e-01 6.18743539e-01
-1.04721241e-01 1.74575090e-01 -1.13894653e+00 1.09205651e+00
7.49429408e-03 -1.51372385e+00 2.43896782e-01 4.71953638e-02
1.01939297e+00 -2.07060985e-02 -8.72852057e-02 6.99644625e-01
6.26138330e-01 -7.27452934e-01 3.03149402e-01 1.04657400e+00
5.25205970e-01 -6.91606522e-01 4.01714295e-01 -1.87021136e-01
-1.82048249e+00 -2.11344305e-02 -1.51778147e-01 1.04022503e-01
2.76775450e-01 9.51930642e-01 -1.10491645e+00 1.46726108e+00
6.74383223e-01 1.25009274e+00 -7.07874775e-01 8.21981907e-01
-4.19254929e-01 6.67003632e-01 -3.05065997e-02 4.30925995e-01
-4.12416533e-02 -1.41663209e-01 4.87081856e-01 9.40902650e-01
1.28649548e-01 -1.07783899e-01 3.57854664e-01 4.27147478e-01
-3.80392313e-01 -1.89119317e-02 -6.84583664e-01 -7.82914162e-01
4.62954015e-01 1.09824681e+00 -2.81687409e-01 -1.68457612e-01
-5.97030640e-01 8.62072408e-01 6.98599756e-01 8.30276072e-01
-9.75946128e-01 -1.34921998e-01 6.55782998e-01 1.76000953e-01
5.15055239e-01 -5.99663436e-01 3.93969476e-01 -1.43137491e+00
2.36129716e-01 -3.56479526e-01 1.00177956e+00 -6.30323827e-01
-1.50766921e+00 5.18654846e-02 4.07373905e-03 -9.54939604e-01
-4.73924242e-02 -3.59727442e-01 -2.92053729e-01 4.29310828e-01
-1.69843328e+00 -1.68260777e+00 -1.21258818e-01 8.85929465e-01
-9.90650505e-02 -4.42944430e-02 6.87726796e-01 5.46169817e-01
-6.14978552e-01 5.31193912e-01 1.16103448e-01 3.67354572e-01
6.18639410e-01 -1.20152879e+00 2.92616785e-01 9.25625682e-01
4.11544323e-01 8.05872798e-01 3.90580833e-01 -9.47842836e-01
-2.15253735e+00 -1.40045476e+00 9.92468238e-01 -5.07519960e-01
1.40649152e+00 1.35306463e-01 -1.04667354e+00 1.42053616e+00
-3.86467949e-02 5.88295460e-01 6.23091638e-01 8.12315822e-01
-1.02881038e+00 -3.06418926e-01 -6.34918928e-01 4.53988463e-01
1.22042429e+00 -8.79309595e-01 -4.43833351e-01 6.07568204e-01
1.00390291e+00 -3.25240225e-01 -1.75050604e+00 5.25311708e-01
5.44637918e-01 -2.33785927e-01 1.05310690e+00 -1.21637678e+00
1.23988301e-01 -4.73830014e-01 -1.49623767e-01 -1.23335147e+00
-6.77024424e-01 -7.28591442e-01 -1.18492627e+00 1.03979301e+00
2.37345234e-01 -6.22355223e-01 8.09806228e-01 2.79587626e-01
-2.40193885e-02 -7.60119796e-01 -1.04043508e+00 -1.23447490e+00
-3.34896415e-01 -4.42606300e-01 4.51116234e-01 1.67407668e+00
2.75959730e-01 4.24728990e-01 -5.19341707e-01 3.97313654e-01
6.74649954e-01 3.65048081e-01 7.04116404e-01 -1.21696639e+00
-2.73808926e-01 -1.10023409e-01 -7.71775246e-01 -8.03736031e-01
4.18778151e-01 -1.31736457e+00 -8.81137550e-01 -1.94972479e+00
2.19024241e-01 -1.19057484e-01 -6.08818173e-01 7.63244033e-01
-1.48005694e-01 -5.62490165e-01 -6.50276095e-02 3.41627225e-02
-9.29523170e-01 8.11466217e-01 1.45442736e+00 -5.43554842e-01
4.09284048e-02 -4.47418898e-01 -3.66416007e-01 1.07761405e-01
5.02375245e-01 -2.35280931e-01 -7.75793791e-01 -4.57996249e-01
6.50736094e-01 3.21905203e-02 4.22590375e-01 -6.00132465e-01
5.00358045e-01 -3.36872727e-01 -5.87898307e-02 -5.35709739e-01
3.69042367e-01 -7.92689383e-01 5.71304560e-01 3.35808605e-01
3.45033854e-01 4.91113886e-02 2.80487090e-01 1.42275858e+00
-3.77626091e-01 3.83551538e-01 1.43848509e-01 2.74691105e-01
-1.09740460e+00 8.07201982e-01 3.01045060e-01 1.25405684e-01
1.02949476e+00 4.66012359e-02 -8.49889696e-01 -1.68538541e-01
-1.01804709e+00 5.48482776e-01 9.64283943e-02 7.76331961e-01
6.82206690e-01 -1.82137692e+00 -4.73939866e-01 -4.42075878e-01
6.13308907e-01 -2.34114900e-01 5.55333138e-01 1.01778448e+00
-5.91888428e-02 4.82733339e-01 7.91845843e-02 -2.26195768e-01
-8.72418225e-01 9.86735463e-01 4.27723974e-02 -7.97580719e-01
-6.87467158e-01 5.90974927e-01 -3.15402925e-01 -2.50475973e-01
1.56162217e-01 -4.90392238e-01 -2.44175762e-01 3.67741704e-01
1.10997163e-01 5.91793835e-01 1.77299261e-01 -3.93284380e-01
-5.50410748e-01 4.17710662e-01 -4.08490092e-01 3.80045593e-01
1.25229001e+00 1.76463187e-01 -2.49355704e-01 6.35531247e-01
1.06571257e+00 -1.36886910e-01 -8.31869423e-01 -7.03854024e-01
9.55696553e-02 -4.74707544e-01 1.39768302e-01 -5.30270576e-01
-1.29354775e+00 2.13302046e-01 1.69064894e-01 1.62665874e-01
7.88173318e-01 -7.03819701e-03 8.87194395e-01 5.92684686e-01
6.50803208e-01 -1.12201190e+00 2.04986513e-01 8.10818851e-01
9.02200937e-01 -1.02803373e+00 5.31156898e-01 -5.51229239e-01
-4.50253129e-01 9.53494549e-01 3.84154707e-01 1.03093892e-01
1.08137012e+00 -6.21918261e-01 -6.21036232e-01 -6.28190517e-01
-1.03487813e+00 -2.93920100e-01 5.11678934e-01 5.66009462e-01
2.47529760e-01 5.43118179e-01 -3.94631267e-01 4.41237390e-01
1.33836204e-02 8.49109218e-02 3.91522646e-01 1.04349482e+00
3.70665416e-02 -1.17992723e+00 -1.24525558e-02 5.31188965e-01
-1.31312370e-01 -5.88766020e-03 -2.27314144e-01 8.59103501e-01
-1.14300333e-01 7.18896329e-01 -3.22801828e-01 -6.75431848e-01
5.58262348e-01 2.03804761e-01 7.52297461e-01 -5.63445807e-01
-1.66245952e-01 -5.52607179e-01 4.66053903e-01 -6.32444024e-01
-3.96435291e-01 -5.88024080e-01 -1.39421618e+00 -6.41280234e-01
-2.80139714e-01 2.82435209e-01 3.15080732e-01 7.03855515e-01
5.85019946e-01 9.45377886e-01 3.10857534e-01 -1.87938839e-01
-2.99390793e-01 -8.35658312e-01 -8.33352208e-01 4.72908050e-01
8.86203274e-02 -9.84034956e-01 -7.66595155e-02 3.22352648e-01] | [8.521140098571777, 7.918104648590088] |
276267a9-cd96-4122-bb17-4ea3cb9221a1 | multi-hop-inference-for-sentence-level | 1805.11267 | null | http://arxiv.org/abs/1805.11267v1 | http://arxiv.org/pdf/1805.11267v1.pdf | Multi-hop Inference for Sentence-level TextGraphs: How Challenging is Meaningfully Combining Information for Science Question Answering? | Question Answering for complex questions is often modeled as a graph
construction or traversal task, where a solver must build or traverse a graph
of facts that answer and explain a given question. This "multi-hop" inference
has been shown to be extremely challenging, with few models able to aggregate
more than two facts before being overwhelmed by "semantic drift", or the
tendency for long chains of facts to quickly drift off topic. This is a major
barrier to current inference models, as even elementary science questions
require an average of 4 to 6 facts to answer and explain. In this work we
empirically characterize the difficulty of building or traversing a graph of
sentences connected by lexical overlap, by evaluating chance sentence
aggregation quality through 9,784 manually-annotated judgments across knowledge
graphs built from three free-text corpora (including study guides and Simple
Wikipedia). We demonstrate semantic drift tends to be high and aggregation
quality low, at between 0.04% and 3%, and highlight scenarios that maximize the
likelihood of meaningfully combining information. | ['Peter Jansen'] | 2018-05-29 | multi-hop-inference-for-sentence-level-1 | https://aclanthology.org/W18-1703 | https://aclanthology.org/W18-1703.pdf | ws-2018-6 | ['science-question-answering'] | ['miscellaneous'] | [ 1.85270868e-02 9.76799846e-01 -4.09031883e-02 -5.48186302e-01
-1.23880470e+00 -8.89492095e-01 4.95556504e-01 1.00621855e+00
-5.53242527e-02 1.20547950e+00 3.89496952e-01 -6.54669762e-01
-4.13913757e-01 -9.47911263e-01 -1.07417059e+00 1.06259219e-01
2.12074537e-02 9.12786365e-01 4.11732793e-01 -2.50894159e-01
2.99546421e-01 -1.84036866e-01 -1.28289199e+00 2.86735654e-01
1.47889566e+00 4.47810471e-01 1.65691748e-01 8.00291061e-01
-7.12858319e-01 1.15599740e+00 -9.19546187e-01 -1.04101205e+00
-3.52248192e-01 -5.43749332e-01 -1.43717945e+00 -3.10272843e-01
8.77136111e-01 1.01050407e-01 1.95718929e-02 1.18952346e+00
2.25038961e-01 2.93043014e-02 6.42237186e-01 -1.07692313e+00
-7.17920721e-01 1.22867048e+00 -2.31016636e-01 7.27419972e-01
9.02962625e-01 8.41471627e-02 1.57997680e+00 -3.21636468e-01
9.82566178e-01 1.17318952e+00 6.61394417e-01 2.99200535e-01
-1.18605816e+00 -3.29219937e-01 3.73078018e-01 1.99434265e-01
-1.03676093e+00 -1.91323459e-01 4.11350757e-01 -6.05874658e-01
1.33902061e+00 4.15395170e-01 7.06105232e-01 8.33595872e-01
3.51835072e-01 2.83927590e-01 8.35460424e-01 -2.06595182e-01
2.08030254e-01 1.36021197e-01 6.91534519e-01 9.41369355e-01
9.61254060e-01 -7.70153463e-01 -8.51561189e-01 -3.62085015e-01
1.71555042e-01 -9.20352519e-01 -2.38643616e-01 1.01722784e-01
-8.05163026e-01 8.24181855e-01 3.54031771e-01 1.81035519e-01
-3.51289690e-01 1.07892394e-01 7.56476074e-02 4.05817926e-01
3.92714351e-01 1.20303702e+00 -5.52390635e-01 -2.20174089e-01
-6.97520792e-01 7.50989914e-01 1.35981679e+00 1.13871145e+00
8.28454018e-01 -4.48104560e-01 -6.00116178e-02 4.74942327e-01
2.79986393e-02 2.75213331e-01 5.45266531e-02 -9.69493687e-01
8.24802458e-01 8.53307128e-01 1.68499917e-01 -1.28172016e+00
-5.08432746e-01 -5.95248044e-01 -1.59575671e-01 -4.50952172e-01
9.96537507e-01 -3.36992145e-01 -6.44537628e-01 1.92644119e+00
3.71189415e-01 -3.29120636e-01 -1.21718049e-01 5.81325650e-01
1.21852672e+00 3.65281045e-01 2.76836336e-01 -1.08610079e-01
1.54219162e+00 -5.78878999e-01 -8.36377501e-01 -6.99039340e-01
7.85443425e-01 -6.46014154e-01 1.34709942e+00 3.32874626e-01
-1.37006330e+00 -1.77996740e-01 -9.69591081e-01 -6.03419781e-01
-2.88115352e-01 -6.84830904e-01 7.96363711e-01 5.48970938e-01
-9.76891518e-01 4.71434176e-01 -4.20998275e-01 -3.25009465e-01
5.21182656e-01 1.50893731e-02 -3.75108905e-02 -2.06012875e-01
-1.38632894e+00 1.18548238e+00 3.25857371e-01 -3.14534605e-01
-5.34090102e-01 -1.15249097e+00 -6.85418665e-01 3.56688499e-01
7.99570620e-01 -1.30620122e+00 1.08853221e+00 -2.21641988e-01
-8.09714615e-01 7.45902777e-01 -4.70473647e-01 -4.32914585e-01
2.28279218e-01 -3.84941041e-01 -1.77833080e-01 8.40471685e-02
4.91489142e-01 2.81333625e-01 2.30088294e-01 -1.17757559e+00
-3.74191135e-01 -3.74194801e-01 5.88421524e-01 3.06629062e-01
1.93287693e-02 -1.12978339e-01 -7.54809156e-02 -2.08074346e-01
3.05382878e-01 -4.66135502e-01 -2.23935992e-01 -5.30257583e-01
-6.94066346e-01 -4.65437263e-01 7.21831173e-02 -9.50020432e-01
1.43753612e+00 -1.38692880e+00 1.55105904e-01 9.95023400e-02
7.02548027e-01 -4.92077440e-01 5.97926974e-02 4.15338427e-01
2.25797340e-01 4.59878892e-01 -2.35769898e-01 6.67908788e-02
1.36521131e-01 1.74027205e-01 -2.76571631e-01 -1.46084428e-01
2.26392135e-01 1.03685260e+00 -1.37798822e+00 -6.22275949e-01
-4.31194782e-01 -1.04135565e-01 -6.21932566e-01 -8.37434903e-02
-9.42739546e-01 -5.50189614e-02 -3.90262425e-01 5.53273380e-01
2.31238097e-01 -7.70254016e-01 2.20510468e-01 -1.22023998e-02
3.03230315e-01 1.28109610e+00 -1.01171732e+00 1.59053659e+00
-2.74893552e-01 5.54662406e-01 -1.88314453e-01 -5.46740234e-01
7.12079465e-01 -7.17003597e-03 -1.70786217e-01 -3.98717850e-01
-1.38706490e-01 1.43778756e-01 1.74050465e-01 -8.33945274e-01
5.81432045e-01 -1.66196361e-01 -9.51897725e-02 6.30414963e-01
1.94687590e-01 -8.73833060e-01 7.29925334e-01 8.62178981e-01
1.47957993e+00 -4.22351420e-01 -4.37196530e-03 -5.58789134e-01
1.33712068e-01 5.25257766e-01 4.09397006e-01 1.06301403e+00
2.40465879e-01 2.23016351e-01 1.15481710e+00 -2.79405326e-01
-9.42248464e-01 -1.24264205e+00 2.96818037e-02 7.24596620e-01
6.79088533e-02 -8.24797392e-01 -8.83504450e-01 -7.71220684e-01
4.73263226e-02 1.41638684e+00 -4.39588219e-01 -6.69581965e-02
-3.42025429e-01 -7.22441912e-01 4.75467056e-01 2.00353771e-01
2.49554008e-01 -6.84355438e-01 -1.91807613e-01 2.93900967e-01
-8.17441940e-01 -1.30224073e+00 -1.25979468e-01 -1.03673637e-01
-8.33186150e-01 -1.26799321e+00 5.74145466e-02 -4.72784162e-01
7.05257058e-01 -1.12143360e-01 1.98410845e+00 4.25567627e-01
-1.29191145e-01 3.52771133e-01 -2.21610263e-01 -5.69223821e-01
-4.82262760e-01 4.08028841e-01 -3.27242613e-01 -6.89863503e-01
6.78619683e-01 -6.32762730e-01 -4.15264994e-01 -1.40090555e-01
-5.77354431e-01 -1.23484470e-01 2.85130888e-01 6.15707159e-01
2.34353080e-01 1.59379318e-01 7.88144648e-01 -1.29319346e+00
1.19935346e+00 -9.22127724e-01 -3.82229865e-01 5.83843350e-01
-7.77479231e-01 1.83926672e-01 4.84840900e-01 2.15257965e-02
-9.57746923e-01 -4.09529537e-01 3.76258157e-02 4.85029727e-01
2.17128079e-02 8.94907415e-01 1.19758949e-01 1.92445114e-01
1.16200614e+00 -2.35358119e-01 -1.33284256e-01 -6.38631433e-02
6.19202793e-01 1.25707656e-01 3.09643209e-01 -9.72263098e-01
7.02198505e-01 1.16628140e-01 -1.23089105e-01 -8.57726753e-01
-1.60100293e+00 -1.88004583e-01 -2.04384595e-01 -2.86743730e-01
8.35435152e-01 -6.88496888e-01 -7.10035741e-01 -2.66329169e-01
-1.23393917e+00 -3.26944441e-01 -3.80076945e-01 2.64307976e-01
-2.08773568e-01 3.12843174e-01 -6.25335038e-01 -5.31982183e-01
-1.41767740e-01 -6.96593642e-01 6.58434868e-01 3.14219415e-01
-8.29244018e-01 -1.17845500e+00 2.20453944e-02 9.80401218e-01
2.91301876e-01 3.26417714e-01 1.44852531e+00 -6.22314751e-01
-7.94742048e-01 -8.01173002e-02 -2.72635013e-01 -1.22433633e-01
-7.21972734e-02 3.19993272e-02 -6.41739488e-01 1.40768290e-01
4.50820848e-02 -5.10728419e-01 6.57166123e-01 2.34533235e-01
9.02992368e-01 -5.70218682e-01 -2.66922146e-01 -9.90271419e-02
1.40222847e+00 -2.92313725e-01 4.69863743e-01 6.09194636e-02
5.93534350e-01 9.24507678e-01 8.28486532e-02 -2.27065221e-03
9.41265225e-01 7.80621618e-02 1.69835046e-01 5.40906072e-01
-1.75247893e-01 -5.54239571e-01 -1.27367139e-01 1.00359476e+00
3.70840426e-03 -3.32955033e-01 -1.18794811e+00 7.68224895e-01
-1.49045122e+00 -9.25253093e-01 -6.53048337e-01 1.81990373e+00
1.16928327e+00 6.31877959e-01 2.44246367e-02 -1.22949496e-01
3.84170860e-01 6.02388829e-02 -3.92082930e-01 -3.28912616e-01
-1.69619143e-01 2.92371482e-01 5.22437692e-02 1.18661475e+00
-3.27415317e-01 9.46228027e-01 6.97465181e+00 6.35644734e-01
-2.66047835e-01 -3.75658460e-02 5.27152717e-01 -8.25406685e-02
-1.16753197e+00 3.94976377e-01 -7.48424351e-01 3.80429953e-01
8.92118871e-01 -5.30263305e-01 4.71871674e-01 4.43027020e-01
-1.99335337e-01 -6.68526947e-01 -1.13390934e+00 3.39940369e-01
-6.47715805e-03 -1.40070248e+00 3.58383477e-01 -3.47517997e-01
9.10130918e-01 -2.08826691e-01 -2.95147687e-01 2.52861798e-01
9.13230181e-01 -1.21624553e+00 4.68699932e-01 6.23569846e-01
3.12233716e-01 -3.79118770e-01 5.55758715e-01 4.21887070e-01
-8.17131996e-01 7.16508031e-02 -2.65931070e-01 -3.67763937e-01
3.38299602e-01 1.11819923e+00 -9.24744904e-01 6.08757138e-01
5.94080627e-01 1.02671281e-01 -8.47426176e-01 8.03486645e-01
-7.31957138e-01 8.59253824e-01 -4.47480798e-01 -6.99375212e-01
1.23020090e-01 3.88824455e-02 4.87589568e-01 1.02719474e+00
1.14039920e-01 4.03282523e-01 -1.82277605e-01 1.13281870e+00
-2.52676219e-01 1.09018326e-01 -5.06179631e-01 -2.62315094e-01
6.69788182e-01 9.85362887e-01 -6.79956257e-01 -5.29599547e-01
-3.76413614e-01 4.99013633e-01 7.66881049e-01 4.04195994e-01
-7.46425450e-01 -5.20637274e-01 3.98077667e-01 2.27130800e-01
-7.76976496e-02 -2.55571961e-01 -7.95763135e-01 -1.18404365e+00
4.06965643e-01 -8.51495028e-01 5.20313501e-01 -9.72769737e-01
-1.41885698e+00 3.39320242e-01 -8.77808705e-02 -8.52594525e-02
-2.03359023e-01 -2.38209903e-01 -6.52276397e-01 9.08332944e-01
-1.18189156e+00 -5.17061114e-01 -4.69784975e-01 2.01908872e-01
3.98600787e-01 3.78974497e-01 5.22499323e-01 1.46676078e-01
-2.08757609e-01 4.87207055e-01 -5.75989604e-01 -1.55559912e-01
3.18022430e-01 -1.68645000e+00 6.72802031e-01 7.53477395e-01
2.92635918e-01 9.72799361e-01 1.14682937e+00 -1.04653883e+00
-1.25795555e+00 -5.51857829e-01 1.52466476e+00 -1.17883158e+00
9.69106555e-01 -3.15985709e-01 -1.32570791e+00 8.95099699e-01
2.41335526e-01 -6.15111768e-01 6.04173243e-01 7.74773180e-01
-6.82773948e-01 1.57282233e-01 -1.05369890e+00 6.78174734e-01
1.34811759e+00 -5.87841511e-01 -1.07569373e+00 8.39434445e-01
1.00854993e+00 -5.54240704e-01 -9.64014649e-01 1.87217385e-01
1.77942812e-01 -9.56372023e-01 6.67419732e-01 -8.85605454e-01
8.71953309e-01 -1.68026894e-01 1.60072625e-01 -1.39614129e+00
-2.63797104e-01 -7.92501807e-01 -1.65777370e-01 9.72057283e-01
1.20942032e+00 -5.45095444e-01 8.11447978e-01 9.50130582e-01
-9.46740434e-02 -7.52596676e-01 -7.30890810e-01 -5.46106160e-01
2.30301052e-01 -3.12897801e-01 6.07731879e-01 1.15193713e+00
4.07984167e-01 9.46409822e-01 4.52028900e-01 3.03624094e-01
7.84908831e-01 -7.45232031e-03 5.81682682e-01 -1.22153032e+00
-2.54157543e-01 -5.37520826e-01 -2.29290016e-02 -9.76952553e-01
-8.38502869e-02 -1.06163347e+00 -4.25316207e-02 -2.28518915e+00
2.36511528e-01 -3.40450406e-01 3.65248531e-01 -5.77956177e-02
-7.48726547e-01 -4.24235731e-01 -2.84769028e-01 -3.60193580e-01
-6.90899312e-01 2.02098370e-01 1.34273243e+00 -5.42127229e-02
1.70817509e-01 -3.38627279e-01 -1.19769263e+00 7.11895525e-01
6.48802817e-01 -4.27406371e-01 -6.86181545e-01 -7.10240901e-01
1.25026059e+00 1.96298137e-01 2.76621997e-01 -7.58596122e-01
5.03888011e-01 -5.16517013e-02 8.64571854e-02 -3.12086761e-01
1.07712753e-01 -2.25148454e-01 1.10079423e-01 3.20375472e-01
-6.57086194e-01 1.95166469e-01 2.25563481e-01 5.76641977e-01
-1.26111850e-01 -3.94414932e-01 1.61119491e-01 -4.52846885e-01
-2.43865490e-01 -1.16048925e-01 -1.23200186e-01 1.02964735e+00
6.74435973e-01 1.56149447e-01 -8.74480188e-01 -5.86000443e-01
-7.48136342e-01 5.76969504e-01 2.11477838e-02 1.66554824e-01
3.94827247e-01 -7.55232751e-01 -8.15100610e-01 -4.80007797e-01
-1.76184382e-02 2.72057503e-01 4.39215243e-01 4.56992358e-01
-7.72887051e-01 4.18325037e-01 3.17689091e-01 -2.75337964e-01
-8.35877180e-01 4.21125025e-01 1.78064480e-01 -4.40637112e-01
-4.42409396e-01 1.24728417e+00 -3.12092096e-01 -4.16929603e-01
7.34124854e-02 -6.37394667e-01 -1.03804499e-01 1.17257833e-01
2.76249886e-01 5.33897281e-01 2.14215536e-02 2.96337634e-01
-1.64422780e-01 4.11964744e-01 -1.81137234e-01 -5.78537397e-02
9.95327711e-01 -1.64659426e-01 -4.79126096e-01 4.43968326e-01
6.11588359e-01 2.57934093e-01 -6.64340734e-01 -1.01684183e-01
3.64579111e-01 -2.90148616e-01 -3.53279382e-01 -9.53292906e-01
-3.28341573e-01 5.19936621e-01 -6.00652575e-01 1.04406321e+00
3.69185954e-01 4.59277838e-01 8.70936334e-01 7.00482130e-01
3.65349114e-01 -1.00342965e+00 1.72587574e-01 4.72263962e-01
8.92372489e-01 -1.16316164e+00 2.61602670e-01 -8.45752299e-01
-3.03223789e-01 6.99894309e-01 8.02219629e-01 6.48577437e-02
3.76673490e-01 1.66949838e-01 -2.41668537e-01 -8.48426580e-01
-1.12470782e+00 -5.23371436e-02 2.29086563e-01 2.22257063e-01
4.99330252e-01 3.70336398e-02 -5.19231617e-01 4.94397879e-01
-9.17313337e-01 -2.30200797e-01 8.36568058e-01 5.26384830e-01
-6.86895728e-01 -6.09115839e-01 -4.46742810e-02 9.10336018e-01
-4.85434592e-01 -3.69245470e-01 -7.04141557e-01 7.25942194e-01
-2.38953009e-01 1.26681840e+00 -1.64151117e-02 -1.46763980e-01
2.69366741e-01 3.13006133e-01 7.71538079e-01 -7.78075218e-01
-6.06405079e-01 -8.30870986e-01 8.26488018e-01 -3.30954641e-01
-7.59861991e-02 -6.49024069e-01 -1.23926747e+00 -6.55609667e-01
-3.21939051e-01 5.55359662e-01 4.86793876e-01 1.14504158e+00
4.09016579e-01 6.77271724e-01 -2.34517425e-01 5.23513138e-01
-4.83547777e-01 -9.13385689e-01 -2.48365611e-01 3.69659275e-01
9.48374942e-02 -4.21306103e-01 -6.50255084e-01 -3.74249518e-02] | [11.044634819030762, 7.974188804626465] |
811172bb-56a2-4561-8a12-4773ab9f9ea3 | context-and-attribute-grounded-dense | 1904.01410 | null | http://arxiv.org/abs/1904.01410v1 | http://arxiv.org/pdf/1904.01410v1.pdf | Context and Attribute Grounded Dense Captioning | Dense captioning aims at simultaneously localizing semantic regions and
describing these regions-of-interest (ROIs) with short phrases or sentences in
natural language. Previous studies have shown remarkable progresses, but they
are often vulnerable to the aperture problem that a caption generated by the
features inside one ROI lacks contextual coherence with its surrounding context
in the input image. In this work, we investigate contextual reasoning based on
multi-scale message propagations from the neighboring contents to the target
ROIs. To this end, we design a novel end-to-end context and attribute grounded
dense captioning framework consisting of 1) a contextual visual mining module
and 2) a multi-level attribute grounded description generation module. Knowing
that captions often co-occur with the linguistic attributes (such as who, what
and where), we also incorporate an auxiliary supervision from hierarchical
linguistic attributes to augment the distinctiveness of the learned captions.
Extensive experiments and ablation studies on Visual Genome dataset demonstrate
the superiority of the proposed model in comparison to state-of-the-art
methods. | ['Lu Sheng', 'Bin Liu', 'Jing Shao', 'Xiaogang Wang', 'Nenghai Yu', 'Guojun Yin'] | 2019-04-02 | context-and-attribute-grounded-dense-1 | http://openaccess.thecvf.com/content_CVPR_2019/html/Yin_Context_and_Attribute_Grounded_Dense_Captioning_CVPR_2019_paper.html | http://openaccess.thecvf.com/content_CVPR_2019/papers/Yin_Context_and_Attribute_Grounded_Dense_Captioning_CVPR_2019_paper.pdf | cvpr-2019-6 | ['dense-captioning'] | ['computer-vision'] | [ 4.71515477e-01 4.56587732e-01 -2.26987123e-01 -8.50442111e-01
-1.03505659e+00 -4.00363237e-01 7.51947522e-01 3.42599720e-01
-1.54002696e-01 8.67044151e-01 8.03849280e-01 2.47144699e-01
2.19149128e-01 -5.79851806e-01 -9.41954851e-01 -6.60819590e-01
1.65072888e-01 3.56592149e-01 4.11648676e-02 -3.61863077e-02
1.51658552e-02 7.94504024e-03 -1.33504903e+00 8.10127199e-01
6.92584336e-01 9.33665454e-01 4.58934069e-01 1.59325585e-01
-4.52519178e-01 1.03259122e+00 -3.07958454e-01 -2.91050762e-01
-1.78962916e-01 -6.54923618e-01 -6.81637168e-01 2.20599771e-01
6.00184381e-01 -4.56400542e-03 -2.23530456e-01 1.03744626e+00
1.35251388e-01 1.70716550e-02 5.53584635e-01 -1.27880943e+00
-1.05722296e+00 7.52433300e-01 -7.38699138e-01 1.42188996e-01
2.32577264e-01 3.52399163e-02 1.35251260e+00 -9.55839038e-01
8.04882467e-01 1.26704407e+00 2.78778374e-01 6.18897498e-01
-1.07920897e+00 -5.73094189e-01 7.31504202e-01 9.94420126e-02
-1.38883924e+00 -2.91541725e-01 8.73104155e-01 -3.18670630e-01
4.49114054e-01 1.15141653e-01 3.42111051e-01 1.45587599e+00
-1.76684916e-01 8.35614622e-01 1.12731540e+00 -2.78443724e-01
1.82506919e-01 4.22489166e-01 -1.61734186e-02 7.89304435e-01
-3.87071259e-02 -3.32084954e-01 -5.26636660e-01 -2.04135105e-01
4.79016066e-01 -5.87589331e-02 -1.27834156e-01 -3.32212299e-01
-1.64973962e+00 9.46037531e-01 1.00446177e+00 3.78000796e-01
-5.89701891e-01 4.36009824e-01 1.83640823e-01 -5.07494807e-01
5.44767082e-01 3.38466495e-01 -1.80124819e-01 5.03981411e-01
-9.91366684e-01 1.54113442e-01 1.85367122e-01 1.41121101e+00
1.12155151e+00 -5.03125727e-01 -7.76190698e-01 6.52419984e-01
3.62953842e-01 3.68742913e-01 1.90656871e-01 -6.63444519e-01
8.21128249e-01 7.60741770e-01 1.17297731e-02 -1.09157169e+00
-1.92983091e-01 -5.25110483e-01 -8.02790463e-01 -4.66906518e-01
3.77429314e-02 -2.93601286e-02 -8.82462382e-01 2.05515075e+00
3.73013705e-01 4.65717256e-01 1.20845973e-01 1.17360139e+00
9.23252165e-01 8.22575569e-01 7.22100556e-01 9.05588493e-02
1.63306379e+00 -1.15838718e+00 -7.62554586e-01 -7.51658976e-01
3.19691032e-01 -4.59415585e-01 1.12905407e+00 -4.97454673e-01
-7.37880230e-01 -4.96735036e-01 -8.73160899e-01 -3.77576947e-01
-4.04089719e-01 1.54530540e-01 5.65870404e-01 3.39976400e-02
-9.21048880e-01 -2.60572210e-02 -3.18805754e-01 -4.15439665e-01
9.32207763e-01 -9.62546393e-02 -3.96334499e-01 -1.35413870e-01
-1.24949515e+00 6.35318279e-01 4.23424274e-01 3.04513518e-02
-1.09885740e+00 -7.20521271e-01 -1.07122302e+00 9.86392274e-02
4.37047631e-01 -9.23832417e-01 9.13231969e-01 -1.22635174e+00
-7.00181723e-01 1.16436267e+00 -5.56084037e-01 -3.67805898e-01
1.86798468e-01 -1.98071584e-01 -1.46963626e-01 3.92110318e-01
6.82923973e-01 1.10997999e+00 8.52871418e-01 -1.62265766e+00
-6.86373591e-01 -4.17883664e-01 1.45286351e-01 3.86775345e-01
-1.96622431e-01 1.13899454e-01 -4.75624651e-01 -6.66094780e-01
-4.69192080e-02 -7.57474124e-01 -3.62651110e-01 1.42477348e-01
-7.29943275e-01 -1.19220130e-01 7.68186152e-01 -5.20416737e-01
9.86112297e-01 -2.27514553e+00 3.02170012e-02 6.54091612e-02
2.67112970e-01 -1.97312430e-01 -1.61081821e-01 2.77950287e-01
-2.08790600e-02 2.60998994e-01 -6.73069298e-01 -4.75750715e-01
-9.58474278e-02 3.18631142e-01 -5.60561836e-01 4.50755149e-01
6.40822411e-01 1.17025602e+00 -1.26803958e+00 -1.14161479e+00
-4.39310335e-02 5.39782166e-01 -1.13314308e-01 3.12405914e-01
-5.26936710e-01 6.86668694e-01 -9.84011590e-01 7.53538609e-01
3.42176408e-01 -6.05693340e-01 -1.15691848e-01 -3.86099845e-01
8.88289809e-02 1.19544804e-01 -5.44280350e-01 2.00119424e+00
-5.87096512e-01 5.79913437e-01 9.38777030e-02 -9.12820518e-01
9.08650219e-01 3.32916677e-01 1.73262224e-01 -5.74052155e-01
-7.33268112e-02 -1.50729269e-01 -4.93060261e-01 -5.33099830e-01
2.80371517e-01 -1.74283221e-01 -4.27981138e-01 3.72056335e-01
-2.11836342e-02 1.48517936e-01 -1.17262281e-01 6.57912076e-01
8.01110029e-01 2.47063920e-01 3.70205134e-01 -2.19902873e-01
6.28514111e-01 1.53546214e-01 5.18926024e-01 6.53476059e-01
-3.30616325e-01 8.87798667e-01 6.16226912e-01 -1.66233644e-01
-1.21110249e+00 -1.00528061e+00 -1.92918658e-01 1.12829959e+00
4.75991726e-01 -3.51797253e-01 -8.51974487e-01 -8.68981421e-01
-1.91468507e-01 8.61956775e-01 -1.19847131e+00 -1.53399641e-02
-5.04196703e-01 -3.72631907e-01 3.83882493e-01 6.91299319e-01
7.33802795e-01 -1.31253970e+00 -4.25037324e-01 1.06500752e-01
-6.40932739e-01 -1.62364328e+00 -5.76475143e-01 -3.08519565e-02
-4.48295832e-01 -7.01255739e-01 -7.23690510e-01 -1.06594968e+00
1.03261733e+00 1.63526073e-01 1.27912116e+00 -5.86535558e-02
-1.42072305e-01 2.64380187e-01 -5.48106134e-01 -3.60590100e-01
-2.86419183e-01 9.72772241e-02 -4.35943395e-01 4.83436227e-01
2.34594807e-01 -3.20740163e-01 -6.49260223e-01 2.46520817e-01
-7.91458845e-01 5.03320038e-01 1.00142825e+00 7.50760078e-01
9.82799232e-01 -4.99336541e-01 7.57172227e-01 -1.18737233e+00
3.06890100e-01 -9.99019682e-01 -1.99962080e-01 5.50147891e-01
-2.65785724e-01 2.30875224e-01 4.66718435e-01 -2.51814216e-01
-1.23227608e+00 4.73968208e-01 2.34127477e-01 -3.60124588e-01
-4.48246062e-01 3.16924572e-01 -3.53849918e-01 4.76314485e-01
5.95633388e-01 4.31703597e-01 -2.29036123e-01 -1.20158270e-01
9.37263370e-01 7.25888968e-01 6.89303756e-01 -6.71090424e-01
8.21541131e-01 8.35360110e-01 -9.93498489e-02 -6.51229143e-01
-1.54362917e+00 -5.91224909e-01 -5.91470540e-01 -1.35710657e-01
1.30457175e+00 -1.23864865e+00 -6.58115819e-02 -1.79773688e-01
-1.35712790e+00 7.34662786e-02 -2.08053052e-01 1.18473500e-01
-8.07337642e-01 7.29351640e-02 -1.23171285e-01 -4.80387449e-01
-3.42635691e-01 -1.01958323e+00 1.44751549e+00 2.61460245e-01
-1.51940063e-01 -8.48160088e-01 -2.25381926e-01 5.27935386e-01
3.38401288e-01 6.39526665e-01 8.90333712e-01 -5.52892804e-01
-7.30329812e-01 5.69656200e-04 -7.28892326e-01 5.15303984e-02
1.57139882e-01 -4.19581354e-01 -1.20726097e+00 1.17096594e-02
-2.67828494e-01 -3.61221313e-01 8.38280857e-01 1.65174842e-01
1.21549177e+00 -4.67997283e-01 -5.64493060e-01 5.04450321e-01
1.46494985e+00 -2.87296176e-01 4.53547806e-01 3.03264052e-01
8.22612286e-01 8.77448738e-01 9.04783547e-01 2.35453367e-01
4.21406299e-01 5.57925880e-01 6.84733748e-01 -3.96152556e-01
-2.91446388e-01 -5.80224931e-01 1.99262977e-01 4.83143106e-02
3.79288018e-01 -1.09943904e-01 -7.45743215e-01 1.03186619e+00
-2.01982141e+00 -1.02804375e+00 1.64511800e-02 1.74398291e+00
9.37689602e-01 -1.21650249e-01 -8.65951404e-02 -5.66197217e-01
1.10982311e+00 4.90050733e-01 -6.31233811e-01 -3.84473540e-02
-3.43843818e-01 -3.23643476e-01 1.64127111e-01 2.10023418e-01
-1.22868550e+00 1.21558821e+00 5.01969385e+00 6.11203730e-01
-7.67779589e-01 2.69010156e-01 1.00546587e+00 6.22572936e-02
-6.15801156e-01 1.99023739e-01 -8.16137850e-01 3.64740133e-01
5.75187087e-01 -1.23546913e-01 -4.75089401e-02 8.84703875e-01
7.85342082e-02 5.37179522e-02 -1.15529299e+00 7.48328388e-01
3.85112196e-01 -1.40394223e+00 4.42106783e-01 -5.78514412e-02
8.18385959e-01 -7.18908086e-02 1.23038553e-01 7.05705807e-02
-3.78036313e-02 -1.11729300e+00 9.46871638e-01 6.07717991e-01
8.79655421e-01 -4.92721081e-01 7.04056621e-01 1.04224414e-01
-1.28112817e+00 -6.37588976e-03 -3.53218228e-01 3.40233505e-01
2.22957060e-01 6.13819897e-01 -9.84040797e-01 4.45554197e-01
5.46778202e-01 9.42890823e-01 -6.01305246e-01 7.41889954e-01
-6.84717298e-01 5.41668355e-01 4.15960141e-02 -2.18075484e-01
7.87174582e-01 1.31067574e-01 5.29190183e-01 1.43258595e+00
1.77677232e-03 2.69628286e-01 -8.60077366e-02 1.49299276e+00
-2.54771382e-01 2.58322179e-01 -8.27301502e-01 -8.16976279e-02
4.16380167e-01 1.51600099e+00 -6.15468860e-01 -4.06224966e-01
-5.65931439e-01 9.93801057e-01 5.53900719e-01 5.62523127e-01
-1.01653647e+00 -1.66826785e-01 6.12950444e-01 2.14131013e-01
4.24564242e-01 1.00354314e-01 -3.27573091e-01 -8.55287433e-01
2.54510045e-01 -4.02898431e-01 3.79552484e-01 -1.11962962e+00
-1.48055744e+00 7.73926795e-01 -7.72859901e-03 -1.15161288e+00
4.46945755e-03 -1.26485765e-01 -5.64318895e-01 9.93744493e-01
-1.81552422e+00 -1.66618609e+00 -6.24330938e-01 7.39123046e-01
6.42728508e-01 -2.82111950e-02 7.61871636e-01 -4.53490112e-03
-3.60896856e-01 4.48809594e-01 -4.31945115e-01 2.32641041e-01
6.93571866e-01 -1.11990929e+00 2.33337611e-01 8.33228946e-01
3.51790011e-01 5.87806642e-01 6.24609590e-01 -6.61660194e-01
-8.40525329e-01 -1.54300904e+00 1.03692722e+00 -4.85314995e-01
6.39621377e-01 -7.18890905e-01 -9.27979648e-01 8.01353574e-01
3.83235365e-01 2.64946699e-01 5.97723484e-01 4.92388718e-02
-5.80185831e-01 -1.18857704e-01 -1.07775080e+00 5.51896632e-01
1.15755260e+00 -7.29635298e-01 -7.89461970e-01 5.18943191e-01
1.06134522e+00 -2.20189746e-02 -4.51531976e-01 1.54696152e-01
1.06800653e-01 -6.55645430e-01 1.02823770e+00 -7.41028666e-01
8.22863400e-01 -4.62987274e-01 -3.34137946e-01 -1.14592230e+00
-4.77631330e-01 -3.54732990e-01 2.39076942e-01 1.69347334e+00
7.07631409e-01 -4.42055613e-03 6.44994497e-01 5.46369314e-01
-3.16113681e-01 -6.94037259e-01 -8.43480825e-01 -2.56985724e-01
-1.08826078e-01 -1.95044458e-01 5.65518022e-01 9.83609080e-01
-2.53863260e-03 6.90357268e-01 -3.07231426e-01 4.85321432e-01
7.24781334e-01 4.90942627e-01 3.54211152e-01 -8.28932941e-01
2.29439676e-01 -1.11947633e-01 -3.57616484e-01 -8.84089470e-01
4.73175734e-01 -9.75455523e-01 3.85588795e-01 -1.80258369e+00
6.73889160e-01 -5.97667396e-01 -3.77241313e-01 8.34390163e-01
-5.42944252e-01 1.69410497e-01 2.96093952e-02 2.65103132e-01
-1.09638131e+00 7.09189892e-01 1.35334778e+00 -3.29774380e-01
1.51190430e-01 -4.03784901e-01 -1.13338566e+00 5.29006720e-01
6.60712898e-01 -7.78103828e-01 -5.65992892e-01 -4.63102967e-01
1.78203911e-01 -7.92369246e-02 6.32329822e-01 -8.65482569e-01
2.20253512e-01 -1.62213519e-01 3.54153365e-01 -4.48302895e-01
2.48182088e-01 -8.22713912e-01 -3.12867790e-01 -1.83141246e-01
-8.43433738e-01 -3.74076510e-04 6.27634823e-02 8.85547698e-01
-4.33828562e-01 -5.10855243e-02 7.94405818e-01 -3.81402045e-01
-8.97262275e-01 4.02048647e-01 -1.18843555e-01 3.40621799e-01
1.33907545e+00 2.12271828e-02 -6.00109816e-01 -4.94744837e-01
-7.70466506e-01 4.22116995e-01 4.61511731e-01 5.62605560e-01
8.41040432e-01 -1.30145359e+00 -1.04867232e+00 -8.22878629e-02
7.16373920e-01 1.88546211e-01 2.86814749e-01 6.03991807e-01
-1.45442292e-01 4.82732952e-01 -1.40173137e-01 -6.99162364e-01
-1.04998100e+00 8.09008479e-01 1.36374921e-01 9.19180107e-04
-6.92715466e-01 1.04401326e+00 8.08618486e-01 1.26591157e-02
2.14535445e-01 -2.29320124e-01 -2.49648258e-01 6.26509860e-02
6.05758965e-01 -3.82321417e-01 -3.95433009e-01 -1.09220695e+00
-5.48720837e-01 5.62354267e-01 -1.74322531e-01 -4.70448397e-02
1.22171104e+00 -4.72483009e-01 -2.01554656e-01 4.36609149e-01
1.23916399e+00 -1.95937529e-01 -1.36329997e+00 -4.22150642e-01
3.83970775e-02 -3.19257855e-01 7.42345229e-02 -8.64401281e-01
-9.90417778e-01 8.71701360e-01 3.57993722e-01 -1.80087760e-01
1.06171751e+00 8.03676486e-01 6.90919995e-01 2.31673922e-02
1.82097167e-01 -7.54219174e-01 1.17099918e-01 6.47158474e-02
1.15195560e+00 -1.41230142e+00 -1.37005836e-01 -6.35753334e-01
-1.19502747e+00 6.20865285e-01 7.13935852e-01 7.64054283e-02
3.75263602e-01 -7.25566819e-02 1.60698995e-01 -3.18885416e-01
-7.83580124e-01 -4.10545588e-01 3.39223325e-01 6.29665315e-01
3.24043334e-01 1.59534533e-02 1.25088692e-02 6.34076118e-01
5.47860675e-02 -3.23530346e-01 3.43553871e-01 6.26592159e-01
-3.86210173e-01 -7.11801350e-01 -2.55026400e-01 2.10019439e-01
-2.60291159e-01 -4.26045328e-01 -5.86634994e-01 5.78958869e-01
2.19121173e-01 9.46787119e-01 2.78216749e-01 -4.63245139e-02
1.28698468e-01 4.93724123e-02 1.07247576e-01 -8.58941793e-01
-5.48879862e-01 -1.17761753e-01 1.25526920e-01 -6.97333455e-01
-6.73040569e-01 -7.73244917e-01 -1.58303082e+00 5.24441242e-01
8.97143483e-02 1.95422277e-01 6.32459521e-01 1.00623417e+00
5.20072639e-01 4.84338194e-01 4.72375721e-01 -3.91005397e-01
-6.83553591e-02 -9.25939739e-01 -4.28471476e-01 7.32154608e-01
5.62811732e-01 -5.57906449e-01 -2.99313724e-01 2.86336780e-01] | [10.582512855529785, 1.3635212182998657] |
9d598706-96bc-4cb9-af6c-4e1c4cc7c769 | exploring-syntactic-representations-for | null | null | https://aclanthology.info/papers/W13-1719/w13-1719 | https://www.aclweb.org/anthology/W13-1719v2 | Exploring Syntactic Representations for Native Language Identification | null | ['Ben Swanson'] | 2013-06-01 | exploring-syntactic-representations-for-1 | https://aclanthology.org/W13-1719 | https://aclanthology.org/W13-1719.pdf | ws-2013-6 | ['native-language-identification'] | ['natural-language-processing'] | [-2.44508207e-01 3.89024585e-01 -2.65282035e-01 -2.15905145e-01
-8.60921741e-02 -7.76765764e-01 4.48510379e-01 -7.23253429e-01
-5.48377395e-01 1.31954515e+00 3.66348401e-02 -9.49533224e-01
-2.40340635e-01 -1.05564880e+00 -8.44053447e-01 -8.75781775e-01
-7.42435038e-01 6.86515033e-01 1.44298598e-01 -6.52004302e-01
8.47113907e-01 6.29996777e-01 -1.62287033e+00 5.77558100e-01
6.81926727e-01 5.49597681e-01 5.66466339e-02 1.04480565e+00
6.13576770e-02 1.59847176e+00 -6.05450153e-01 -4.56729174e-01
1.43710867e-01 -1.88022718e-01 -5.35770595e-01 -3.36825520e-01
7.91536197e-02 -5.88986814e-01 -3.10633808e-01 6.07356608e-01
1.14270830e+00 -5.53557873e-02 1.07025254e+00 -1.51067197e+00
-7.97060013e-01 5.44234335e-01 2.30399013e-01 1.20632313e-01
6.10446513e-01 -1.79472014e-01 3.51212233e-01 -1.36621380e+00
6.32680655e-01 8.64870071e-01 9.47046995e-01 5.99273622e-01
-1.20647264e+00 -5.60552299e-01 -7.17137158e-01 -2.57835120e-01
-1.59567785e+00 -6.30042374e-01 6.23617955e-02 -3.34735900e-01
1.69142139e+00 6.72587395e-01 1.35647905e+00 1.47341585e+00
1.36649036e+00 4.72517729e-01 1.13904178e+00 -3.16340059e-01
3.65351558e-01 6.43754780e-01 -2.29148138e-02 5.51889002e-01
1.19686353e+00 6.76312149e-01 -5.60917914e-01 -7.92779744e-01
1.11365557e+00 -3.12949389e-01 2.60771513e-01 -7.06989706e-01
-1.06566191e+00 7.88466871e-01 -1.33808568e-01 2.20882341e-01
-3.46203089e-01 -9.92989019e-02 2.24548295e-01 4.12961632e-01
-2.94082850e-01 4.77862865e-01 -8.89795244e-01 -1.87686309e-01
-1.01472771e+00 1.91863477e-01 1.30615628e+00 1.45811689e+00
4.72722203e-03 3.70100170e-01 1.66493103e-01 2.89523482e-01
5.29429734e-01 1.05927479e+00 4.36951250e-01 -1.33365822e+00
-9.55119133e-02 4.20878716e-02 6.12505674e-01 -1.13473701e+00
-7.12930143e-01 -2.41300568e-01 -9.54724610e-01 5.18771529e-01
-1.59270123e-01 -4.59180593e-01 -7.59686172e-01 4.79171664e-01
-1.81984559e-01 -3.19489211e-01 5.45619786e-01 2.69257158e-01
7.28577793e-01 1.45816103e-01 9.25893057e-03 -4.73371416e-01
8.38296890e-01 -1.26899445e+00 -1.11426139e+00 2.33304992e-01
6.82289064e-01 -1.11704338e+00 4.06794518e-01 4.29345578e-01
-1.87200487e+00 -9.69799384e-02 -1.08317137e+00 1.19022481e-01
-7.97166348e-01 -2.57194549e-01 6.66624963e-01 1.49922979e+00
-1.63972652e+00 6.47176981e-01 -6.05021298e-01 5.40335439e-02
-4.73218322e-01 9.07614470e-01 -3.47142309e-01 2.90655226e-01
-1.28751957e+00 9.52449858e-01 -1.04219764e-01 3.03568155e-01
-3.30324143e-01 -1.84501112e-01 -1.03385210e+00 -6.24127567e-01
-2.59417385e-01 -1.07312346e+00 1.36302292e+00 1.09815992e-01
-1.30379498e+00 1.00962746e+00 -4.14315462e-01 -1.14109404e-01
6.61359608e-01 -1.52096570e-01 -8.18174660e-01 1.58321753e-01
2.87593510e-02 3.47163439e-01 5.30214727e-01 -9.69232559e-01
-6.31655395e-01 -1.00153096e-01 -2.54188716e-01 2.48816490e-01
1.43904146e-03 2.05205917e-01 6.38460100e-01 -9.53604504e-02
1.91062525e-01 -8.61961663e-01 -3.21419090e-01 -7.61404037e-01
-1.77353188e-01 -3.84736449e-01 5.59762537e-01 -2.92163283e-01
1.33848476e+00 -1.84365213e+00 -4.54683900e-01 2.94456817e-03
2.53527164e-01 3.89016122e-02 2.33101144e-01 1.23831403e+00
-2.43849114e-01 1.06667292e+00 3.98064762e-01 9.52541176e-03
3.13382268e-01 5.07273376e-01 2.86674555e-02 2.51206756e-01
9.43330750e-02 1.15280068e+00 -1.09214199e+00 -5.20940363e-01
5.57267785e-01 4.60968643e-01 -3.84588838e-01 6.24593735e-01
9.30012882e-01 2.99172718e-02 -8.94021094e-02 1.33241999e+00
1.05377018e+00 -2.90812284e-01 -2.46628653e-02 3.44544262e-01
-6.44541264e-01 6.00222833e-02 -7.41804183e-01 9.49429095e-01
1.31349964e-02 1.99757457e-01 1.74998537e-01 -6.80728197e-01
3.94654661e-01 1.10545933e+00 4.45659161e-01 -9.24297392e-01
-1.69569388e-01 9.00310338e-01 1.03920102e-01 -9.62983370e-01
6.40755475e-01 -1.72503099e-01 7.69825354e-02 1.40852645e-01
-3.61913115e-01 -3.84120375e-01 5.52458428e-02 4.19574350e-01
1.00224769e+00 -1.33707494e-01 5.48685491e-01 -8.72328460e-01
6.88946426e-01 -2.01589778e-01 3.00597936e-01 1.23978651e+00
-2.90862411e-01 9.21478033e-01 3.19022417e-01 -5.37574828e-01
-5.72780192e-01 -1.20098352e+00 -4.80556756e-01 9.86326516e-01
-1.58388391e-01 -3.87671381e-01 -7.10155964e-01 -2.63155133e-01
-1.85071185e-01 4.93483543e-01 -5.93591571e-01 5.23159266e-01
-5.14705896e-01 -6.85349941e-01 7.65277922e-01 3.17972392e-01
6.49624616e-02 -1.49228525e+00 -5.70813596e-01 3.34754556e-01
-1.07132711e-01 -5.39811492e-01 -1.57590687e-01 6.12205923e-01
-1.19366693e+00 -1.01526415e+00 -8.75530541e-01 -1.03603637e+00
7.18889177e-01 2.44572356e-01 1.18463767e+00 2.84042627e-01
-2.87709564e-01 6.49904788e-01 -1.31030381e-02 -2.67939389e-01
-3.16364132e-02 -5.78750819e-02 5.01899779e-01 -1.07851994e+00
6.46393359e-01 -3.92214775e-01 -1.00622165e+00 5.35368681e-01
-3.85821253e-01 -2.04611585e-01 7.85597622e-01 1.04281425e+00
1.42742008e-01 -1.33182362e-01 2.41971418e-01 -1.16735983e+00
1.11498392e+00 -4.85333532e-01 1.30341025e-02 2.62960047e-01
-8.53362501e-01 -4.53584343e-01 2.27881029e-01 -1.33037493e-02
-6.33760452e-01 -2.51423597e-01 -4.14545417e-01 3.22794706e-01
-4.06866640e-01 3.34393084e-02 2.24873364e-01 -5.26000679e-01
5.21005154e-01 1.50258854e-01 -4.07556817e-02 1.21735156e-01
6.30975887e-02 3.75316888e-01 3.67786407e-01 -7.01224983e-01
5.19809723e-01 1.93325520e-01 -3.00995037e-02 -1.28791058e+00
2.66786069e-01 -1.64763972e-01 -6.60750508e-01 -2.69126564e-01
7.75121748e-01 -9.50198710e-01 -6.35705650e-01 5.21708906e-01
-9.54387486e-01 -1.36340424e-01 -5.25335252e-01 6.30965471e-01
-7.02474535e-01 2.94757709e-02 -4.17852998e-01 -1.17976546e+00
-4.78847146e-01 -1.38869667e+00 9.59160328e-01 3.85633826e-01
-2.05811903e-01 -1.19790471e+00 3.38975668e-01 8.99848714e-02
4.29175526e-01 7.39965662e-02 5.03531873e-01 -2.80004859e-01
-2.98304528e-01 -2.85470933e-01 1.59573574e-02 -1.65876746e-01
-3.09365243e-02 4.80770379e-01 -5.48391879e-01 -4.37962860e-01
2.44738594e-01 -4.86500829e-01 -7.51581416e-02 7.11018145e-01
4.09077644e-01 -6.02920949e-01 -7.12544680e-01 5.56552589e-01
1.27709007e+00 4.72497940e-01 5.88340998e-01 6.77552521e-01
9.28869769e-02 5.17871320e-01 4.48484391e-01 2.08113909e-01
1.07506551e-01 1.08483166e-01 1.14217520e-01 -2.17137560e-01
9.45900455e-02 -1.75644696e-01 4.44304377e-01 1.09980536e+00
-8.23837519e-01 -2.15223029e-01 -4.88283783e-01 6.68056428e-01
-1.69156313e+00 -1.31570101e+00 -6.70152605e-01 9.76623476e-01
3.78074080e-01 3.38884830e-01 1.58041969e-01 1.21232189e-01
5.47049284e-01 -4.76693302e-01 -1.27305150e-01 -9.16352808e-01
-3.82233024e-01 4.21136379e-01 7.14838982e-01 6.51479006e-01
-6.10602558e-01 5.08361042e-01 1.25505590e+01 5.49717486e-01
-5.10860123e-02 1.27314463e-01 3.14815581e-01 1.99914098e-01
-2.24020526e-01 1.62632689e-01 -1.04165065e+00 9.26906094e-02
1.64754760e+00 -4.36735392e-01 3.93212438e-01 6.44444764e-01
3.94769877e-01 -1.96429595e-01 -9.78620768e-01 5.21999180e-01
1.12709433e-01 -1.50397491e+00 -3.76861334e-01 9.64888573e-01
5.80093563e-01 -1.81895152e-01 6.81941509e-01 4.33209062e-01
7.39425182e-01 -1.14519978e+00 7.88427055e-01 3.18626672e-01
8.87266219e-01 -8.18826377e-01 1.07315242e+00 2.76328743e-01
-1.04355454e+00 1.15487054e-02 -5.90443075e-01 -9.22581375e-01
1.62244976e-01 2.02188566e-01 -5.61583102e-01 4.06869203e-01
6.19966745e-01 2.15250537e-01 -8.53338003e-01 1.45581341e+00
-4.29231405e-01 4.22687940e-02 -3.00976187e-01 -4.39922899e-01
4.83290881e-01 5.28384298e-02 3.26606274e-01 1.02295005e+00
2.89785862e-01 5.45581102e-01 -2.62208551e-01 2.92286038e-01
6.63503349e-01 5.84383309e-03 -1.38496268e+00 -8.68683681e-02
3.54620427e-01 9.69217539e-01 -3.99494410e-01 -3.56748998e-02
-6.11456513e-01 6.62115753e-01 -1.66942239e-01 5.75146377e-01
-2.92761147e-01 -8.89406264e-01 4.33969021e-01 -2.30117049e-02
-2.88469017e-01 -1.35338321e-01 -3.23372036e-01 -1.02459288e+00
-6.06416404e-01 -3.90122980e-01 7.32179061e-02 -8.63867998e-01
-1.79313409e+00 6.85844719e-01 -3.50327820e-01 -1.03178740e+00
-9.29034173e-01 -9.72984850e-01 -2.90242791e-01 6.67755604e-01
-6.59234166e-01 -1.30476952e+00 1.77773401e-01 4.65253919e-01
1.82401046e-01 -5.88519633e-01 1.09945750e+00 -1.42670095e-01
-3.18711132e-01 1.08882773e+00 3.51253241e-01 -3.05974871e-01
8.32965672e-01 -1.16271269e+00 4.23785180e-01 1.09189451e-02
-6.59259140e-01 1.28460062e+00 6.81860268e-01 -6.81785107e-01
-1.16639841e+00 -1.52893141e-01 1.38110602e+00 -9.15031374e-01
5.27874053e-01 -1.02810413e-01 1.46300867e-01 6.57190859e-01
9.07351732e-01 -5.09461224e-01 1.08935249e+00 -1.13616258e-01
4.93123859e-01 8.23448122e-01 -1.38805819e+00 5.99272728e-01
1.21222687e+00 -4.81854081e-01 -8.27020168e-01 3.28937650e-01
9.94227231e-01 -5.60786903e-01 -1.34066856e+00 6.99696779e-01
1.14132881e+00 -1.04883564e+00 1.54237401e+00 -1.16912270e+00
4.08816934e-01 1.70770600e-01 -2.18455836e-01 -6.52935803e-01
-5.24122715e-01 -8.07741940e-01 -3.97186369e-01 3.40213925e-01
8.64144087e-01 -1.16800272e+00 5.53630650e-01 1.39166510e+00
-3.58625412e-01 -4.51715857e-01 -8.63314152e-01 -1.06149745e+00
-4.66870656e-03 1.81816339e-01 3.85523647e-01 8.18638563e-01
7.09820271e-01 2.02331603e-01 -2.05201268e-01 -4.37674336e-02
6.59316301e-01 -4.87512946e-01 5.82342803e-01 -8.74011815e-01
2.49149442e-01 -3.85976404e-01 -2.94489831e-01 -2.90531307e-01
-3.26795012e-01 -4.87107635e-01 -8.59293997e-01 -1.53084815e+00
8.49664882e-02 1.97367743e-01 -2.33256146e-01 3.44385266e-01
6.77823246e-01 2.45789096e-01 -2.27382466e-01 1.17054820e-01
-1.86927155e-01 -9.06788632e-02 9.18564737e-01 1.10557920e-03
-2.17724726e-01 3.92412305e-01 -1.01716614e+00 9.60534811e-01
7.85404518e-02 -6.09580100e-01 -5.51487744e-01 1.64939865e-01
5.71885824e-01 3.57775450e-01 4.49405432e-01 -9.70509052e-01
9.87445056e-01 -4.32846308e-01 6.12257063e-01 -1.43385470e+00
-2.65485227e-01 -9.00021493e-01 3.61826897e-01 6.29400074e-01
4.08042461e-01 3.53796333e-01 2.26811334e-01 -9.13986787e-02
-2.01378226e-01 -6.44658387e-01 4.43001747e-01 -7.45609999e-01
-4.55086857e-01 -3.90635371e-01 -1.02313221e+00 -9.67486948e-03
7.88939476e-01 -4.61360693e-01 -6.47767961e-01 -1.95199717e-02
-1.44608676e+00 7.30553791e-02 8.33678424e-01 1.34732248e-02
6.98022604e-01 -1.44444084e+00 -1.11748077e-01 6.18802965e-01
-5.42432606e-01 -4.98194307e-01 2.20674574e-01 1.06156552e+00
-1.31528914e+00 1.26915324e+00 -5.21896303e-01 -2.05424115e-01
-8.96585643e-01 7.19095051e-01 3.15837234e-01 1.75098896e-01
-3.93049836e-01 7.00151443e-01 1.12239346e-02 -6.58594191e-01
1.24011397e-01 2.97559589e-01 -4.87763733e-01 -2.52128989e-01
9.22277749e-01 1.17918742e+00 1.32526740e-01 -3.91715407e-01
-5.58191121e-01 4.39446121e-01 2.08604142e-01 -6.12734079e-01
1.38662541e+00 -2.20989168e-01 -7.44191706e-01 5.00318348e-01
7.50003338e-01 -7.33495504e-02 -3.28966863e-02 1.27011871e+00
4.80256975e-03 -5.47239244e-01 -3.11336160e-01 -7.82959402e-01
-3.42039734e-01 5.93214929e-01 6.17733955e-01 4.59080935e-01
9.69997942e-01 -6.47576571e-01 7.70057857e-01 7.64313757e-01
7.83133745e-01 -1.22997761e+00 -6.36951804e-01 3.69483382e-01
9.39836800e-01 -9.30032432e-01 1.30400375e-01 -3.14221263e-01
-5.55534840e-01 1.08689797e+00 5.38173854e-01 -1.62142932e-01
1.17091513e+00 6.96656525e-01 -1.75611794e-01 -4.53250527e-01
-1.04549897e+00 9.83817875e-02 2.10727617e-01 1.32608259e+00
8.26061428e-01 1.41275764e-01 -1.40426433e+00 8.46834600e-01
-6.34404242e-01 4.76996809e-01 9.47268784e-01 1.55018985e+00
-5.12773991e-01 -1.41692734e+00 -4.41162825e-01 2.31142953e-01
-2.82854587e-01 -3.49930972e-01 -8.62966061e-01 1.09929097e+00
1.97083559e-02 1.37330377e+00 -4.48758155e-01 -4.63731140e-01
8.27405751e-01 3.19600284e-01 4.41484600e-01 -1.25142381e-01
-8.94688129e-01 6.48750722e-01 3.84649158e-01 -1.05672014e+00
-7.94483483e-01 -1.27049911e+00 -1.08188879e+00 -1.16740942e+00
-3.07217389e-01 4.65777248e-01 2.31674016e-01 3.19533348e-01
-2.09303293e-02 1.56313553e-03 6.67447627e-01 -1.00111675e+00
-1.97397545e-01 -6.07395887e-01 -1.20775104e+00 -5.56946039e-01
3.94425273e-01 -5.85869551e-01 -1.15223050e+00 -6.24734610e-02] | [-1.5391390323638916, 15.869171142578125] |
7cfd081c-d610-46d5-b1eb-90718fb30d04 | logical-story-representations-via-framenet-1 | null | null | https://aclanthology.org/2022.distcurate-1.3 | https://aclanthology.org/2022.distcurate-1.3.pdf | Logical Story Representations via FrameNet + Semantic Parsing | We propose a means of augmenting FrameNet parsers with a formal logic parser to obtain rich semantic representations of events. These schematic representations of the frame events, which we call Episodic Logic (EL) schemas, abstract constants to variables, preserving their types and relationships to other individuals in the same text. Due to the temporal semantics of the chosen logical formalism, all identified schemas in a text are also assigned temporally bound “episodes” and related to one another in time. The semantic role information from the FrameNet frames is also incorporated into the schema’s type constraints. We describe an implementation of this method using a neural FrameNet parser, and discuss the approach’s possible applications to question answering and open-domain event schema learning. | ['Lenhart Schubert', 'Lane Lawley'] | null | null | null | null | naacl-distcurate-2022-7 | ['formal-logic'] | ['reasoning'] | [ 1.87865160e-02 7.48999000e-01 -3.59974951e-01 -6.81524038e-01
2.80914432e-03 -6.51306450e-01 1.02948725e+00 6.19213045e-01
-4.67201442e-01 1.13331187e+00 4.87006366e-01 1.07984804e-01
-3.89216900e-01 -1.37105334e+00 -7.62097359e-01 -3.46219301e-01
-2.15996221e-01 7.43910611e-01 7.12646723e-01 -3.89506161e-01
-2.49664381e-01 2.82165796e-01 -1.92194760e+00 6.22063816e-01
1.26367970e-03 8.85781050e-01 1.55064315e-01 3.19748849e-01
-8.03417206e-01 1.51984179e+00 -6.49364293e-01 -6.15754426e-01
-3.39438409e-01 -6.43417835e-01 -1.35631001e+00 3.88990231e-02
-1.02056146e-01 1.22062229e-01 -4.90084767e-01 8.33226800e-01
-2.04504892e-01 7.73432910e-01 -3.05825379e-02 -1.32109368e+00
-4.27721232e-01 1.18987274e+00 3.69086623e-01 4.56859171e-01
9.05103743e-01 -5.10669708e-01 1.22313190e+00 -2.57105798e-01
1.41755509e+00 1.55699456e+00 5.29518545e-01 6.84683263e-01
-1.23632634e+00 -4.15405259e-02 4.12601680e-01 5.60586751e-01
-1.08476174e+00 -4.32657301e-01 8.45071733e-01 -1.61644995e-01
1.45977032e+00 2.95372218e-01 9.48385060e-01 1.25071931e+00
1.20295577e-01 5.04524708e-01 6.66585982e-01 -8.06390584e-01
7.62047768e-01 1.50064230e-01 5.50998867e-01 6.25965416e-01
-1.75724421e-02 6.44858135e-03 -9.31486189e-01 -2.00315639e-01
7.44710863e-01 -3.01492780e-01 2.12046728e-01 -3.88483524e-01
-1.11620390e+00 8.00093055e-01 -3.54569145e-02 6.99497044e-01
-3.34963977e-01 5.47317445e-01 6.98447764e-01 1.50130704e-01
2.21941620e-01 1.80157527e-01 -4.67157573e-01 -2.77894605e-02
-4.23390985e-01 6.27178907e-01 9.99315321e-01 1.00950789e+00
6.52123094e-01 -2.16022342e-01 8.30187127e-02 5.02562165e-01
3.52896690e-01 -3.06115276e-03 5.12649417e-01 -1.13541126e+00
1.32186916e-02 6.49161696e-01 3.07164639e-01 -8.19442153e-01
-5.27974486e-01 1.62486985e-01 5.35835624e-02 -4.51053411e-01
2.28316635e-01 2.97058672e-01 -4.44962263e-01 2.23798132e+00
4.50684518e-01 4.69146013e-01 4.67071950e-01 3.90637189e-01
8.29127550e-01 6.86498165e-01 8.49204481e-01 -5.80068350e-01
1.82171917e+00 -1.07935160e-01 -1.17496574e+00 -1.27948508e-01
5.13247848e-01 8.04710612e-02 5.38508713e-01 -1.19606562e-01
-1.32429874e+00 -2.32316300e-01 -8.08770537e-01 -2.01065332e-01
-6.90214813e-01 -5.43993175e-01 1.04241943e+00 3.22289288e-01
-8.06098640e-01 4.83881861e-01 -1.17580700e+00 -7.63505399e-01
5.92977628e-02 3.07795674e-01 -2.52921522e-01 4.90177095e-01
-1.92723906e+00 8.65846574e-01 1.15469956e+00 -1.78501502e-01
-8.29164863e-01 -3.94021541e-01 -1.20684850e+00 1.80945337e-01
6.22732997e-01 -6.34154379e-01 1.58013177e+00 -1.09374809e+00
-1.22619891e+00 1.24163663e+00 -3.73449624e-01 -1.00048101e+00
-9.66989398e-02 2.36550614e-01 -1.07559896e+00 4.88846689e-01
1.38820395e-01 6.76929057e-01 4.65302765e-01 -8.44684243e-01
-8.61412466e-01 -3.04490745e-01 9.51596975e-01 6.97124973e-02
1.41178548e-01 4.72232252e-01 -2.70643175e-01 -5.09713292e-01
3.10890913e-01 -5.61482728e-01 -5.39216697e-02 -3.09960961e-01
8.13126191e-02 -5.55021346e-01 5.62203169e-01 -8.42002034e-02
1.26713943e+00 -1.93330038e+00 2.28659093e-01 -4.94052731e-02
-1.38902843e-01 -3.93391639e-01 2.85573989e-01 5.05718231e-01
-3.36990505e-01 -7.05634430e-02 3.25964801e-02 3.54461707e-02
2.86255151e-01 1.12531197e+00 -8.18122804e-01 2.33513758e-01
1.23702465e-02 8.48359585e-01 -1.07299697e+00 -7.38750458e-01
4.27228659e-01 2.16832548e-01 -3.68343145e-01 1.53382337e-02
-1.05744672e+00 -2.39719562e-02 -7.46975362e-01 2.84771562e-01
8.92994404e-02 -1.51938396e-02 8.30393016e-01 -1.21540479e-01
-1.40973300e-01 7.73073018e-01 -1.47564888e+00 1.88839328e+00
-2.63323396e-01 3.55222195e-01 -4.34826046e-01 -1.00077176e+00
6.50929332e-01 9.15454566e-01 4.98537540e-01 -7.27183580e-01
7.72865117e-02 -1.73013717e-01 -4.54491585e-01 -5.53619802e-01
5.98288774e-01 -6.12697065e-01 -5.86360216e-01 4.09582794e-01
5.17366230e-01 8.74358863e-02 7.18878686e-01 3.61038119e-01
8.27934682e-01 8.01712394e-01 7.48883545e-01 -4.45119768e-01
8.28597009e-01 1.94243073e-01 9.23469365e-01 6.86442792e-01
-2.05736518e-01 -1.64259583e-01 8.12544465e-01 -8.62649262e-01
-8.25038314e-01 -1.13479054e+00 -4.19603825e-01 1.23395622e+00
3.55044246e-01 -9.75893795e-01 -7.47533679e-01 -4.74152476e-01
-4.40637231e-01 1.04465103e+00 -7.09446073e-01 -1.02517959e-02
-7.86133528e-01 -3.96364778e-01 8.12602699e-01 7.35404372e-01
1.56845018e-01 -1.52846348e+00 -1.50319028e+00 7.11447299e-01
-3.13650072e-01 -1.14294434e+00 4.22856033e-01 4.67403263e-01
-7.33683586e-01 -1.20472729e+00 4.17182833e-01 -6.63940907e-01
2.60288686e-01 -6.76334143e-01 1.40670097e+00 -4.02879901e-02
2.08617374e-01 6.24859869e-01 -4.13699389e-01 -5.00148594e-01
-4.44266230e-01 -4.14066792e-01 -3.35133560e-02 -5.97501770e-02
5.67822874e-01 -5.29632568e-01 5.17636016e-02 6.58212751e-02
-1.26752090e+00 -3.33934911e-02 -7.29537070e-01 5.96240997e-01
7.50675917e-01 4.73937124e-01 2.63847768e-01 -1.12348628e+00
1.83230072e-01 -5.85713804e-01 -8.87563527e-01 5.98381341e-01
-3.48002277e-02 2.36487061e-01 4.02681589e-01 -3.91286999e-01
-1.70388627e+00 -1.07742645e-01 1.55698419e-01 -3.41406949e-02
-4.87155616e-01 7.09342837e-01 -4.48341459e-01 7.11087942e-01
6.29410326e-01 -1.69199675e-01 -5.04366398e-01 -1.15393870e-01
4.82434571e-01 -2.77015746e-01 8.86040151e-01 -1.20938909e+00
2.32762232e-01 7.29102671e-01 2.57705778e-01 -5.16113877e-01
-1.07883739e+00 -2.80682016e-02 -6.37268066e-01 -1.51703134e-01
1.15601146e+00 -7.87533879e-01 -8.14583540e-01 1.19349636e-01
-1.32637453e+00 -8.69705305e-02 -1.03448236e+00 3.08274448e-01
-1.04599869e+00 4.94941361e-02 -6.43293083e-01 -8.51206839e-01
4.35813278e-01 -6.85811639e-01 7.59638190e-01 3.35457921e-01
-6.05553389e-01 -1.42744827e+00 7.49411806e-02 -1.95912048e-01
-1.76900193e-01 3.38425815e-01 1.16311419e+00 -9.10759389e-01
-3.41794461e-01 1.58115625e-01 4.77767169e-01 -3.87896448e-01
-2.19189689e-01 -2.19633542e-02 -7.77871430e-01 3.23394060e-01
4.09827113e-01 -1.30076617e-01 3.36579591e-01 3.42278570e-01
8.28937113e-01 -3.61230344e-01 -5.65308392e-01 1.53646678e-01
1.57867742e+00 7.62264848e-01 7.45817363e-01 4.66695130e-01
1.31614935e-02 7.95550346e-01 4.90878910e-01 4.57594067e-01
4.64913040e-01 6.52285576e-01 1.60480030e-02 5.48761427e-01
-1.26795787e-02 -5.49135268e-01 3.77571881e-01 1.38745397e-01
-4.08864841e-02 -3.52455080e-01 -7.85285711e-01 6.18707299e-01
-2.11269474e+00 -1.72265577e+00 -1.13597073e-01 1.73434865e+00
9.22300994e-01 2.66818523e-01 -1.69472143e-01 5.57592362e-02
9.34839427e-01 4.06003952e-01 -1.88125193e-01 -4.54845011e-01
-6.09033108e-01 5.18107414e-01 1.05347142e-01 7.03109622e-01
-1.09379041e+00 1.25115478e+00 7.08577013e+00 4.04003829e-01
-5.20260036e-01 4.12143975e-01 1.07235447e-01 1.27180684e-02
-5.53597450e-01 7.07852244e-01 -7.52342939e-01 2.74001300e-01
1.45963264e+00 -4.53242272e-01 5.23292601e-01 5.50091624e-01
2.34947242e-02 -3.93080980e-01 -1.65968215e+00 5.82615077e-01
-1.28487289e-01 -1.81812322e+00 9.66325998e-02 -5.08869708e-01
2.30329558e-01 -5.45594990e-01 -7.66000986e-01 2.32045412e-01
4.40352559e-01 -5.94837487e-01 1.54486430e+00 7.24127233e-01
3.53961498e-01 -6.17869079e-01 3.81733507e-01 -2.56877206e-02
-1.35194933e+00 -1.99909016e-01 -3.65329117e-01 -3.83560181e-01
6.56135142e-01 3.26605141e-01 -2.87172884e-01 7.58758664e-01
6.62510931e-01 6.77619219e-01 -1.56320468e-01 3.83295864e-01
-6.37190640e-01 5.27792037e-01 -3.66912574e-01 1.02042750e-01
4.16876487e-02 -1.72433332e-01 6.41615987e-01 8.97843122e-01
-1.79996938e-02 6.61349297e-01 9.10754055e-02 1.12743688e+00
8.76633525e-02 -4.00981694e-01 -5.85344553e-01 -2.50810795e-02
7.09115207e-01 5.97645938e-01 -1.09252620e+00 -7.00011253e-01
-4.94360805e-01 4.79516357e-01 -1.25525966e-01 2.50301868e-01
-1.10654998e+00 -1.60052150e-01 5.71055233e-01 -6.31795973e-02
1.52782589e-01 4.98685054e-02 1.64056569e-01 -1.19122100e+00
-9.16512832e-02 -4.37790841e-01 1.07413065e+00 -1.23927414e+00
-8.93156528e-01 5.11536658e-01 7.36599684e-01 -5.62522531e-01
-4.48310554e-01 -4.41181391e-01 -3.35443854e-01 3.84198129e-01
-1.00387383e+00 -1.09195209e+00 1.62923962e-01 1.02667964e+00
3.98498178e-01 1.75767422e-01 1.24789000e+00 -3.65287177e-02
-3.62796873e-01 -1.29720539e-01 -6.50200367e-01 3.25200036e-02
9.17031318e-02 -1.12625241e+00 1.58364758e-01 9.46518779e-01
3.68229181e-01 7.92290032e-01 9.21624064e-01 -8.24780762e-01
-1.23171175e+00 -7.86699653e-01 1.51195812e+00 -6.54208899e-01
9.71655965e-01 -4.74306822e-01 -9.48627591e-01 1.57960391e+00
3.37450773e-01 -3.44722271e-02 5.76845109e-01 1.84393451e-01
-3.99719030e-01 2.86782812e-02 -1.10180795e+00 4.37018842e-01
1.35499513e+00 -9.03262794e-01 -1.68568993e+00 4.07213867e-01
1.01314867e+00 -6.08950019e-01 -9.17955577e-01 -3.45226340e-02
1.66420966e-01 -8.93533647e-01 9.62952495e-01 -1.12513423e+00
1.13877684e-01 -4.68644023e-01 -3.99711549e-01 -6.12286031e-01
-1.54904693e-01 -5.46713114e-01 -3.12721193e-01 1.29883718e+00
2.36790832e-02 -5.70726335e-01 3.80079180e-01 1.03423417e+00
-5.08600473e-02 9.66857821e-02 -1.23563647e+00 -6.37083173e-01
-2.42709965e-01 -7.96203494e-01 1.06718743e+00 1.11608613e+00
5.06934941e-01 3.30199122e-01 7.26446584e-02 1.59880117e-01
3.67449164e-01 2.03319043e-01 -3.27234536e-01 -1.57824397e+00
-1.61263883e-01 -8.34041685e-02 -5.03137529e-01 -2.53584951e-01
9.51778412e-01 -9.24671710e-01 -1.48895696e-01 -1.32334888e+00
-1.25257924e-01 -3.22523117e-01 -2.20542192e-01 8.32144976e-01
5.74107289e-01 -2.66068429e-01 -8.50425959e-02 -1.00671381e-01
-7.53583312e-01 2.54883170e-01 4.32325065e-01 3.23585384e-02
-2.33344004e-01 -5.19082010e-01 -3.67307872e-01 8.53628933e-01
4.47687209e-01 -6.17710888e-01 -8.53455544e-01 -3.73413503e-01
7.42388368e-01 6.30943179e-01 6.25016391e-01 -8.34648669e-01
3.22027296e-01 -5.48286557e-01 1.35860920e-01 -1.67932615e-01
2.87899286e-01 -9.46144700e-01 9.99671102e-01 2.04726219e-01
-8.17399383e-01 1.33661792e-01 3.23810846e-01 4.03932512e-01
-4.55299646e-01 -5.34945250e-01 7.24946439e-01 -3.63908291e-01
-1.29410267e+00 -1.80107668e-01 -6.09603584e-01 8.26041326e-02
1.20552957e+00 -4.12095375e-02 -2.55051136e-01 -1.93823744e-02
-1.36672819e+00 -5.32464348e-02 3.37543637e-01 3.92484605e-01
3.42921317e-01 -1.18784499e+00 1.13747381e-01 -2.46455055e-03
-2.70461254e-02 -1.09554023e-01 2.16967553e-01 3.92457396e-01
-3.10133457e-01 6.43382311e-01 -4.15908039e-01 -1.76575512e-01
-7.51556993e-01 7.38351047e-01 5.79665899e-01 -8.90047625e-02
-8.61665130e-01 4.85280216e-01 1.81280505e-02 1.20932302e-02
1.40038133e-01 -5.23101449e-01 -3.83274555e-01 2.90474832e-01
5.37042022e-01 3.14197014e-03 6.06437773e-02 -8.08296502e-01
-6.46533012e-01 -1.44747142e-02 3.39415520e-01 -4.86164451e-01
1.35395014e+00 -3.08578551e-01 -6.76863432e-01 7.15294302e-01
4.31520849e-01 -9.90364850e-02 -8.71787190e-01 -2.64399618e-01
6.22754276e-01 -2.17097610e-01 -3.15105021e-01 -5.89803100e-01
-6.22812748e-01 3.19742486e-02 1.91045791e-01 5.35595059e-01
9.65050995e-01 6.72444224e-01 3.54480416e-01 4.15235251e-01
6.94583178e-01 -1.18223226e+00 -3.47406864e-01 7.33090043e-01
6.23237908e-01 -2.44294703e-01 -2.23044217e-01 -4.10286546e-01
-5.11121333e-01 1.19687223e+00 2.69354522e-01 -4.07252572e-02
4.53055918e-01 3.27502161e-01 -2.34044209e-01 -4.47181791e-01
-1.08559310e+00 -2.94162750e-01 -2.94809133e-01 5.81278563e-01
2.95138896e-01 5.47726341e-02 -6.80321574e-01 9.93210852e-01
-1.49979100e-01 2.76126951e-01 7.72259891e-01 1.14576161e+00
-1.91504613e-01 -1.36337757e+00 -3.55426490e-01 -1.47044033e-01
-4.80176657e-01 1.69275731e-01 -8.37584808e-02 1.00083387e+00
5.94380260e-01 8.05609584e-01 7.21621871e-01 2.81927794e-01
4.87839788e-01 7.68830180e-01 8.87050927e-01 -7.58097589e-01
-5.59863091e-01 -9.20854807e-02 5.29466212e-01 -7.94972301e-01
-1.06634104e+00 -9.70132232e-01 -2.14363551e+00 5.51331416e-02
2.24105731e-01 4.00952160e-01 2.51127332e-01 1.23102987e+00
8.29873905e-02 4.69890863e-01 -9.41551179e-02 -1.41819462e-01
1.38298348e-01 -2.16687724e-01 -6.79350853e-01 7.68932164e-01
-9.01185535e-03 -9.79625583e-01 -8.53937790e-02 5.37352920e-01] | [10.159111022949219, 9.156777381896973] |
0e79b64a-6868-4efc-8d81-b35af809654e | a-novel-low-rank-tensor-method-for | 2305.00892 | null | https://arxiv.org/abs/2305.00892v1 | https://arxiv.org/pdf/2305.00892v1.pdf | A Novel Low-Rank Tensor Method for Undersampling Artifact Removal in Respiratory Motion-Resolved Multi-Echo 3D Cones MRI | We propose a novel low-rank tensor method for respiratory motion-resolved multi-echo image reconstruction. The key idea is to construct a 3-way image tensor (space $\times$ echo $\times$ motion state) from the conventional gridding reconstruction of highly undersampled multi-echo k-space raw data, and exploit low-rank tensor structure to separate it from undersampling artifacts. Healthy volunteers and patients with iron overload were recruited and imaged on a 3T clinical MRI system for this study. Results show that our proposed method Successfully reduced severe undersampling artifacts in respiratory motion-state resolved complex source images, as well as subsequent R2* and quantitative susceptibility mapping (QSM). Compared to conventional respiratory motion-resolved compressed sensing (CS) image reconstruction, the proposed method had a reconstruction time at least three times faster, accounting for signal evolution along the echo dimension in the multi-echo data. | ['Youngwook Kee', 'Heechul Jeong', 'Gerald Behr', 'MungSoo Kang', 'Seongho Jeong'] | 2023-05-01 | null | null | null | null | ['image-reconstruction'] | ['computer-vision'] | [ 6.55246913e-01 -4.57517058e-01 3.74876976e-01 -1.59588009e-01
-7.89749146e-01 -2.60920703e-01 4.56806421e-02 -6.32823586e-01
-6.31552398e-01 5.63068032e-01 3.73590767e-01 -1.53390855e-01
-8.18475842e-01 4.98532970e-03 -5.39651234e-03 -9.10867512e-01
-6.82374239e-01 3.40353578e-01 3.30706030e-01 -2.98033352e-03
3.88604045e-01 3.56474996e-01 -6.78426147e-01 2.23729670e-01
9.58189130e-01 7.10317969e-01 6.68098330e-01 7.39715099e-01
2.81678468e-01 1.26721478e+00 1.94171891e-01 2.47128278e-01
1.10196518e-02 -6.31855071e-01 -1.10265732e+00 6.56225681e-02
2.13373944e-01 -5.93261003e-01 -5.38509846e-01 8.98062110e-01
8.24370861e-01 3.52094084e-01 2.63866901e-01 -3.30896944e-01
-3.48451376e-01 7.35157788e-01 -7.41336524e-01 1.00477040e+00
-1.02435023e-01 1.30053665e-02 7.15328008e-02 -1.40172040e+00
6.20317757e-01 4.20379966e-01 7.91656137e-01 3.12392414e-01
-1.28196251e+00 -5.58828235e-01 -6.42207444e-01 2.87481308e-01
-1.03823590e+00 -6.32714033e-01 9.26612198e-01 -8.19394112e-01
7.59214342e-01 5.16464710e-01 6.41032696e-01 5.19935131e-01
6.31532729e-01 2.00481161e-01 1.93270302e+00 4.10578623e-02
-8.63947496e-02 -7.64518797e-01 3.92646462e-01 6.42719269e-01
3.53614807e-01 1.72262624e-01 -4.86133873e-01 -6.64039433e-01
9.28957403e-01 -6.64473101e-02 -7.02248871e-01 -2.85299063e-01
-2.26689053e+00 2.23830149e-01 3.17337550e-02 9.31257904e-01
-8.61300230e-01 1.32507205e-01 3.90358984e-01 -6.23223595e-02
3.65601152e-01 4.58566636e-01 4.95058224e-02 1.63760576e-02
-1.22464085e+00 -9.29102972e-02 -9.40617081e-03 1.46791935e-01
2.60901809e-01 5.54407060e-01 -3.40827465e-01 8.37549329e-01
3.42502683e-01 8.54921341e-01 1.01251709e+00 -1.35389555e+00
-5.54890512e-03 -2.44567707e-01 9.70437154e-02 -9.43701684e-01
-6.35687232e-01 -5.70063293e-01 -1.30131054e+00 -3.28032881e-01
3.00340116e-01 1.33539915e-01 -5.59672475e-01 1.17931640e+00
2.61602819e-01 4.60078657e-01 -1.36626139e-01 1.57180119e+00
4.69119906e-01 1.18954666e-01 -9.66077447e-02 -8.53611767e-01
1.41477501e+00 -5.79805613e-01 -1.09846413e+00 -8.14719126e-02
4.52349842e-01 -6.67279482e-01 6.06789708e-01 3.26468050e-01
-1.52288330e+00 -2.54548192e-01 -9.53331053e-01 4.18673187e-01
8.55474830e-01 -1.09409720e-01 6.12412333e-01 5.03048241e-01
-9.56574619e-01 9.20344055e-01 -1.27590561e+00 4.11318541e-01
-1.19319484e-01 9.05867144e-02 -5.19678414e-01 -5.81557453e-01
-1.31002378e+00 8.99907768e-01 -8.98576975e-02 5.54220378e-01
-8.16600502e-01 -1.11732495e+00 -4.27406728e-01 -7.41494954e-01
4.87734266e-02 -5.02978086e-01 7.25494027e-01 6.02553897e-02
-1.25981796e+00 7.29430676e-01 -1.01990283e-01 -7.36767426e-02
2.51040846e-01 -5.45548536e-02 -6.52720630e-01 8.78292143e-01
3.19211036e-01 -2.85548747e-01 1.16959715e+00 -8.71510088e-01
7.03862488e-01 -7.54205167e-01 -7.42431462e-01 1.57062083e-01
1.66242048e-01 3.01522195e-01 4.04268026e-01 -6.60867274e-01
1.24427879e+00 -1.11020696e+00 -5.18825352e-01 -4.27738190e-01
-6.74814880e-02 8.44035327e-01 1.74464673e-01 -1.39183009e+00
1.17773032e+00 -1.92365110e+00 1.62937626e-01 3.15772370e-02
9.28446472e-01 7.47583210e-02 -7.10166991e-02 -1.60100777e-02
-7.34812319e-01 -1.59480378e-01 -6.59337401e-01 3.73210132e-01
-7.68186688e-01 -1.22956693e-01 1.05813816e-01 1.10707784e+00
-2.55044460e-01 9.27246094e-01 -1.30518675e+00 -4.23412949e-01
-1.14228845e-01 7.53299892e-01 -3.42624664e-01 1.66871086e-01
8.87280345e-01 1.38347733e+00 -5.21256208e-01 2.32914254e-01
1.03686213e+00 -4.71629322e-01 6.03838980e-01 -9.15203631e-01
-4.38338876e-01 3.54028004e-03 -9.80712533e-01 1.95336449e+00
-1.90645270e-02 6.68937936e-02 5.06823242e-01 -9.77631092e-01
5.85391402e-01 6.55087650e-01 1.44741476e+00 -1.04411495e+00
-1.02529444e-01 5.98389626e-01 2.83197373e-01 -8.08812201e-01
3.85645270e-01 -8.47561240e-01 3.67175192e-01 8.18080068e-01
-3.81629616e-01 -1.08533695e-01 -8.92848372e-02 1.27934635e-01
1.26994395e+00 -1.67513698e-01 -3.58147889e-01 -8.80587697e-01
7.04166770e-01 -3.43626142e-01 4.58521903e-01 5.99704564e-01
-4.43124741e-01 6.36637032e-01 -1.55268595e-01 -5.15558124e-01
-1.24039626e+00 -9.14284825e-01 -5.48647344e-01 3.92689943e-01
-2.40431920e-01 -8.97620842e-02 -4.13902700e-01 -6.44421056e-02
-3.29142511e-01 1.16959073e-01 -2.77606368e-01 6.07807525e-02
-1.30130672e+00 -1.44529676e+00 5.52725852e-01 -1.46277873e-02
4.13564205e-01 -6.97248042e-01 -8.53483975e-01 6.08153939e-01
-8.98746192e-01 -1.18023634e+00 -7.25255311e-01 -1.27783269e-01
-1.45813692e+00 -1.06447327e+00 -1.40623224e+00 -4.19620350e-02
5.24196684e-01 6.82194531e-01 9.87161398e-01 -6.56281738e-03
-6.08149111e-01 3.20405483e-01 -1.60475448e-01 6.13320470e-01
-3.10433537e-01 -7.35862911e-01 3.48390490e-01 1.96135998e-01
-3.71014833e-01 -6.98285818e-01 -1.11228216e+00 4.48926955e-01
-1.08947372e+00 -2.46420316e-02 5.49907744e-01 9.38386321e-01
8.23641717e-01 -8.10460299e-02 3.52547109e-01 -4.65102494e-01
6.63064539e-01 -4.62927043e-01 -2.04778656e-01 1.39956269e-02
-7.48161972e-01 3.64504457e-01 7.26669580e-02 -4.19976115e-01
-8.06526363e-01 -5.23952246e-01 1.36531398e-01 -3.20156515e-01
4.82745558e-01 5.33562303e-01 8.05703759e-01 -5.44744730e-01
6.37905836e-01 7.61533320e-01 4.73790765e-01 -4.79462355e-01
-4.41353805e-02 1.22520059e-01 5.36905348e-01 -6.77737236e-01
4.27846640e-01 6.98183596e-01 4.66701955e-01 -1.06619012e+00
-4.50443238e-01 -4.40003842e-01 -7.99942493e-01 -4.69464213e-01
9.57405329e-01 -6.10598981e-01 -8.58499110e-01 6.35468841e-01
-7.26846159e-01 -2.79548347e-01 -1.54099971e-01 1.53744423e+00
-4.84223813e-01 1.04348361e+00 -1.01614904e+00 -4.87289667e-01
-6.35307074e-01 -1.37728965e+00 3.88448536e-01 -4.83535677e-01
2.05710694e-01 -7.33347058e-01 4.21737850e-01 7.44429231e-01
1.19834495e+00 3.72522980e-01 8.55775058e-01 2.33297408e-01
-3.78740251e-01 2.17353284e-01 -8.37935507e-02 3.76383901e-01
-1.24364629e-01 -9.63814378e-01 -2.66523212e-01 -4.69944894e-01
9.99388576e-01 -2.08142653e-01 5.90325654e-01 9.51215208e-01
9.45322692e-01 9.79373083e-02 1.78894207e-01 6.90768063e-01
1.17400169e+00 9.14568976e-02 7.69286633e-01 -1.94781065e-01
7.64651418e-01 4.25964057e-01 3.44442457e-01 3.66246253e-01
3.86673719e-01 5.06862283e-01 -1.10915706e-01 -6.86119124e-02
-3.91421914e-01 2.69517750e-01 2.32472703e-01 1.75849164e+00
-6.37023091e-01 8.24761033e-01 -1.11973715e+00 4.97876376e-01
-1.24867940e+00 -1.10933888e+00 -9.40904260e-01 2.32032418e+00
8.59896481e-01 -7.16242254e-01 -1.16928563e-01 1.44205138e-01
6.24200702e-01 3.81499261e-01 -6.23924136e-01 4.19784755e-01
-9.79615897e-02 3.25469106e-01 6.10217869e-01 7.72972047e-01
-4.36739981e-01 8.98953378e-02 7.23278093e+00 1.40084606e-02
-1.27880490e+00 8.28176022e-01 1.65665403e-01 -8.68013874e-02
-6.34407759e-01 -5.17184399e-02 1.60286203e-01 2.68005580e-01
1.16882586e+00 2.77493838e-02 8.82905066e-01 -5.49324714e-02
4.58850414e-01 -2.43651628e-01 -2.86348641e-01 1.21010315e+00
-8.30760747e-02 -1.21155131e+00 -5.01874685e-01 1.91056937e-01
2.46137232e-01 4.72227454e-01 -4.56001936e-03 -3.72001827e-01
-5.64927101e-01 -7.95449853e-01 3.68782490e-01 9.34598386e-01
1.31150961e+00 -1.89267024e-01 2.07981884e-01 1.57613680e-01
-1.01075494e+00 2.80790895e-01 -9.73043367e-02 1.75479978e-01
5.54184973e-01 1.24209261e+00 -4.27013099e-01 6.05452240e-01
5.61131775e-01 5.35846412e-01 -3.10122788e-01 6.46534443e-01
3.68903548e-01 4.81972486e-01 1.17595963e-01 8.65420580e-01
-5.54217994e-02 -5.58814764e-01 9.11311150e-01 7.14818180e-01
4.69995677e-01 8.45499098e-01 1.29558370e-02 8.11086595e-01
5.17368555e-01 -2.62699336e-01 -2.70031065e-01 -1.72475100e-01
-2.62446664e-02 1.30438709e+00 -6.61039829e-01 -3.66189122e-01
-1.60091460e-01 1.07660127e+00 -2.46290430e-01 5.57221830e-01
-5.85562289e-01 -6.59048930e-02 -7.93774873e-02 6.07202351e-01
-8.69967043e-02 -8.04381967e-01 1.77849948e-01 -1.66009963e+00
4.72295918e-02 -6.62748992e-01 5.09524792e-02 -8.77980411e-01
-1.09092975e+00 7.95074463e-01 1.78275883e-01 -8.05148542e-01
-6.95900470e-02 -1.21454902e-01 1.70256421e-01 1.23697174e+00
-1.68218207e+00 -5.05930662e-01 -1.63536042e-01 8.86660814e-01
-2.50459880e-01 3.19110960e-01 6.58197701e-01 7.70452023e-01
-2.17759863e-01 -1.88765734e-01 5.85711859e-02 -1.02242216e-01
5.51625311e-01 -9.00271177e-01 -1.34175584e-01 8.61362278e-01
-7.09102690e-01 1.08758080e+00 3.61795336e-01 -9.58171010e-01
-2.02077317e+00 -6.23576999e-01 7.05033362e-01 6.53950451e-03
7.87744582e-01 2.28030011e-01 -1.14779878e+00 2.99828500e-01
-1.24819212e-01 9.21869099e-01 8.41302514e-01 -7.10365713e-01
-7.75900781e-02 7.62041286e-02 -1.51226151e+00 -1.43345714e-01
9.08111930e-01 -6.71237409e-01 -4.82015461e-01 2.56481916e-01
4.10488665e-01 -4.19862896e-01 -1.79086602e+00 5.52552521e-01
7.42701352e-01 -9.12729800e-01 1.33473134e+00 -3.06040227e-01
1.13624349e-01 -4.67656672e-01 -1.44849271e-01 -1.08356082e+00
-1.03097498e+00 -9.25124645e-01 -2.04713717e-01 1.65757000e-01
-3.65938455e-01 -6.89888358e-01 4.02936131e-01 6.44751012e-01
-5.01936972e-01 -2.80223966e-01 -1.00499833e+00 -4.66805011e-01
-4.89630736e-02 -1.92173496e-01 2.63368115e-02 1.28597379e+00
-1.23679213e-01 1.26460409e-02 -4.86090779e-01 1.72054499e-01
1.55875242e+00 -1.75403785e-02 -5.36325872e-01 -9.11969364e-01
-3.08159530e-01 2.08767161e-01 2.55692840e-01 -6.01912200e-01
-9.49807912e-02 -1.16408789e+00 -4.36829589e-02 -1.18503630e+00
5.28792441e-01 -8.25018287e-01 -6.78659022e-01 -6.36940822e-02
-2.22840622e-01 5.57618797e-01 -3.30455601e-02 7.93223321e-01
-1.37354046e-01 3.54576141e-01 2.04296732e+00 1.30408004e-01
1.63804501e-01 -6.45555079e-01 -4.11678404e-01 3.09444994e-01
1.98028192e-01 -5.65969765e-01 -4.25823241e-01 -3.82787138e-01
4.90592957e-01 1.29449677e+00 4.57221568e-01 -1.00692022e+00
-1.37427211e-01 -2.51363933e-01 2.52055466e-01 -4.85794246e-01
1.84362680e-01 -5.83420694e-01 7.14999616e-01 8.27987671e-01
-1.62948132e-01 1.65234655e-01 -1.51298895e-01 -6.54880330e-02
5.60623407e-02 -8.99829790e-02 8.92373502e-01 -6.69843078e-01
-1.57319367e-01 6.58026040e-01 -4.90883082e-01 2.66053349e-01
3.26411992e-01 4.13572416e-02 -2.03068212e-01 2.09028691e-01
-1.15406334e+00 -4.43855703e-01 1.30793348e-01 -1.30295768e-01
1.21701252e+00 -1.47307301e+00 -9.35359001e-01 2.95633823e-01
-2.39372805e-01 -5.39844453e-01 1.25698125e+00 2.05510783e+00
-5.76641858e-01 4.29595828e-01 -4.49474543e-01 -7.51675189e-01
-5.75419784e-01 4.05844241e-01 8.43843460e-01 -5.87402284e-01
-1.01632559e+00 4.88349825e-01 -1.07520238e-01 -2.65526384e-01
-7.75015414e-01 -1.11734942e-01 -8.97169709e-02 -3.06131542e-01
1.07894254e+00 6.80626988e-01 3.29398423e-01 -1.05273390e+00
-7.20700324e-01 8.43611658e-01 1.80330709e-01 -3.73542130e-01
1.52925229e+00 -5.00528216e-01 -6.42820716e-01 5.31835079e-01
1.18874609e+00 -4.35689613e-02 -1.07732165e+00 -2.81022459e-01
-2.25832626e-01 -5.68304300e-01 7.59834707e-01 -7.58207083e-01
-1.18776405e+00 8.40198040e-01 9.26569402e-01 -6.74463362e-02
8.64901245e-01 -3.22904021e-01 1.10247135e+00 -2.06298068e-01
6.75941408e-01 -3.29704493e-01 3.53174508e-01 2.69430369e-01
1.13915539e+00 -7.09028482e-01 3.13954562e-01 -1.73172861e-01
-7.55566657e-01 9.46543515e-01 -2.88486302e-01 -1.25541940e-01
6.14339173e-01 2.21831501e-01 -1.39062613e-01 -7.84456789e-01
-2.65719950e-01 4.47413057e-01 3.65192115e-01 6.00883484e-01
9.26423907e-01 8.84401947e-02 -7.37346053e-01 1.99688435e-01
4.47798997e-01 2.92851776e-01 6.42814696e-01 8.61233592e-01
-4.42941897e-02 -8.73213410e-01 -7.18045235e-01 4.65334892e-01
-8.54709446e-01 -2.79040992e-01 5.40012658e-01 -5.68205826e-02
-2.51626790e-01 6.81957781e-01 -3.57056171e-01 -1.03482082e-01
1.72083512e-01 1.87003672e-01 1.16335940e+00 -2.18627378e-01
-4.69523937e-01 2.89454132e-01 -7.35000670e-02 -9.98597503e-01
-8.54715824e-01 -7.69864082e-01 -1.50174415e+00 4.15610150e-02
-8.35838914e-02 3.01840723e-01 9.59891617e-01 7.00115979e-01
3.65442127e-01 6.78775489e-01 8.64519417e-01 -9.67347920e-01
-5.62278092e-01 -1.09718597e+00 -1.06658506e+00 4.79865044e-01
5.91588438e-01 -6.16117835e-01 -3.78002346e-01 -6.25822321e-02] | [13.542413711547852, -2.3975493907928467] |
462bc9ff-4a39-42cd-8c63-5ab87e03d83f | alibaba-at-ijcnlp-2017-task-1-embedding | null | null | https://aclanthology.org/I17-4006 | https://aclanthology.org/I17-4006.pdf | Alibaba at IJCNLP-2017 Task 1: Embedding Grammatical Features into LSTMs for Chinese Grammatical Error Diagnosis Task | This paper introduces Alibaba NLP team system on IJCNLP 2017 shared task No. 1 Chinese Grammatical Error Diagnosis (CGED). The task is to diagnose four types of grammatical errors which are redundant words (R), missing words (M), bad word selection (S) and disordered words (W). We treat the task as a sequence tagging problem and design some handcraft features to solve it. Our system is mainly based on the LSTM-CRF model and 3 ensemble strategies are applied to improve the performance. At the identification level and the position level our system gets the highest F1 scores. At the position level, which is the most difficult level, we perform best on all metrics. | ['Linlin Li', 'Pengjun Xie', 'Yi Yang', 'Luo Si', 'Jun Tao', 'Guangwei Xu'] | 2017-12-01 | alibaba-at-ijcnlp-2017-task-1-embedding-1 | https://aclanthology.org/I17-4006 | https://aclanthology.org/I17-4006.pdf | ijcnlp-2017-12 | ['2d-human-pose-estimation'] | ['computer-vision'] | [-5.09221852e-02 1.07614495e-01 4.02033329e-01 -3.47471356e-01
-6.94014192e-01 -8.89036357e-02 -1.40817001e-01 2.77178138e-01
-6.75071836e-01 1.16512644e+00 1.41191661e-01 -6.02123678e-01
1.45800859e-01 -3.55678499e-01 -5.76526582e-01 -3.58024657e-01
-8.27617664e-03 4.91835922e-01 2.92356927e-02 -3.11220706e-01
5.35098910e-01 -7.91828856e-02 -1.00177753e+00 4.09004360e-01
1.66130757e+00 6.26522183e-01 5.32538116e-01 8.09494436e-01
-4.13481176e-01 1.13461637e+00 -8.53328288e-01 -5.59861779e-01
-4.34401095e-01 -4.17314023e-01 -1.44204879e+00 -4.60722357e-01
-3.12324557e-02 1.18582115e-01 1.23548426e-01 1.39297795e+00
7.98676372e-01 2.46194318e-01 4.89780992e-01 -8.33977461e-01
-6.39672041e-01 9.21299338e-01 -8.87125060e-02 3.07587981e-01
3.52719486e-01 -3.36293370e-01 8.65684390e-01 -1.27901530e+00
5.82669616e-01 1.33575475e+00 9.17685091e-01 8.35756302e-01
-5.86188316e-01 -5.06294787e-01 6.51123524e-02 6.00270927e-01
-1.26752782e+00 -3.71991724e-01 1.48246288e-01 -4.14595306e-01
1.79814625e+00 -3.37578133e-02 -5.54977031e-03 1.05284727e+00
6.38287485e-01 6.89139366e-01 7.99951375e-01 -8.78599405e-01
1.10178649e-01 -1.91680431e-01 6.91581964e-01 8.37163031e-01
1.49124622e-01 -2.16554672e-01 -4.36893135e-01 1.15480609e-01
2.81855762e-02 -2.44762897e-01 -2.42469311e-01 8.90272081e-01
-7.43003547e-01 6.66087985e-01 6.23557670e-03 6.31077588e-01
-4.15499300e-01 4.06942181e-02 4.32291865e-01 4.88487989e-01
5.45057058e-01 4.36559916e-01 -1.08558905e+00 -3.08005333e-01
-7.03027785e-01 1.17866650e-01 6.60839319e-01 1.19981933e+00
3.13163638e-01 9.17479396e-02 -4.66444343e-01 1.16300774e+00
4.70570505e-01 3.23550731e-01 8.66767585e-01 -2.37067834e-01
7.10848272e-01 4.29647118e-01 1.99587986e-01 -7.53611445e-01
-6.79805279e-01 -4.85172004e-01 -7.20309138e-01 -4.00102288e-01
2.88207047e-02 -6.04159534e-01 -1.34354210e+00 1.54449677e+00
-1.88609421e-01 1.25630632e-01 1.30484598e-02 5.46867728e-01
1.36255181e+00 7.38121569e-01 6.71005905e-01 -1.53956994e-01
1.33691406e+00 -1.09542787e+00 -1.16047335e+00 -2.84873635e-01
1.23846436e+00 -8.85561168e-01 6.35915160e-01 4.42423105e-01
-1.00928259e+00 -4.44851130e-01 -8.07273448e-01 -3.10801685e-01
-5.83245575e-01 4.72781986e-01 3.94460820e-02 3.86421889e-01
-1.02338457e+00 7.65061498e-01 -5.21621644e-01 -3.55359256e-01
-1.22222587e-01 4.30011064e-01 -4.84748095e-01 -8.89666453e-02
-1.65082181e+00 1.53056097e+00 8.47515404e-01 3.57113838e-01
-4.51430082e-01 -3.34918767e-01 -7.31527984e-01 -1.84687778e-01
-1.75589568e-03 -3.73908162e-01 1.06707859e+00 -6.03891015e-01
-1.24032068e+00 9.77767944e-01 -4.30288106e-01 -3.80886614e-01
2.88230628e-01 -4.56630498e-01 -7.78167307e-01 -4.45345849e-01
7.61479139e-03 3.36436480e-01 3.57001305e-01 -8.68508220e-01
-1.00788498e+00 -2.27971017e-01 -7.08268881e-01 -5.42214252e-02
1.26262456e-01 6.54199839e-01 -2.51432452e-02 -7.16941595e-01
5.26370034e-02 -6.67196274e-01 -2.33551767e-02 -1.11174011e+00
-6.34010196e-01 -1.03685749e+00 4.21522707e-01 -1.61827946e+00
1.77328324e+00 -1.94548595e+00 2.37969667e-01 -5.92549928e-02
1.58610478e-01 7.84478664e-01 -1.80969834e-01 5.24559915e-01
-2.02694178e-01 5.82712591e-01 -1.19382814e-02 -6.60499990e-01
-1.46978483e-01 2.28098989e-01 9.36848484e-03 1.50538504e-01
3.71400148e-01 7.64705658e-01 -8.72321606e-01 -6.04792058e-01
-1.91742525e-01 6.33839741e-02 -2.62093633e-01 4.88680124e-01
-1.94322810e-01 3.33585441e-01 -2.43362531e-01 6.58793807e-01
8.18494320e-01 3.53415385e-02 1.95859939e-01 1.12879768e-01
-2.31117353e-01 7.52798736e-01 -8.99219275e-01 1.47762930e+00
-4.46790367e-01 1.64112374e-01 -2.36059159e-01 -8.99850309e-01
1.18533957e+00 4.12575006e-01 -6.18722588e-02 -5.33086360e-01
2.11508274e-01 6.09253407e-01 3.27830791e-01 -9.98255908e-01
8.56955230e-01 1.13550238e-01 -1.89705834e-01 2.49287989e-02
5.86815953e-01 7.06331670e-01 9.77084115e-02 1.48850083e-01
1.46588182e+00 1.84311613e-01 3.59933347e-01 -3.31143647e-01
4.84262556e-01 -6.67163357e-02 1.17009950e+00 7.79098630e-01
-3.11810315e-01 4.80464876e-01 3.66521001e-01 -3.10877442e-01
-8.46122205e-01 -4.10946548e-01 -8.52782279e-02 1.09190559e+00
-1.05384126e-01 -4.13848341e-01 -5.76949120e-01 -1.03537023e+00
-1.58368155e-01 8.99380207e-01 -3.68300825e-01 -1.26455784e-01
-8.23823929e-01 -9.88597929e-01 9.23359931e-01 4.11038011e-01
4.67495173e-01 -1.67435944e+00 -5.93805388e-02 5.85742772e-01
-5.87035894e-01 -1.08035696e+00 -4.27904904e-01 6.67533636e-01
-5.27365983e-01 -8.83201599e-01 -4.22775835e-01 -1.22625029e+00
5.91538191e-01 -5.17435610e-01 1.42129362e+00 7.44110346e-01
-1.87704355e-01 -5.16130030e-01 -1.28931665e+00 -5.40834486e-01
-4.35918570e-01 8.53726864e-02 -5.25515750e-02 -4.77313310e-01
6.24546707e-01 7.72274509e-02 -1.25594400e-02 -2.89271083e-02
-1.73270732e-01 -2.75895923e-01 5.11308968e-01 1.21216178e+00
2.10589483e-01 1.28120452e-01 8.13447416e-01 -1.14064491e+00
8.13031614e-01 -5.33538520e-01 -4.15594615e-02 5.93940973e-01
-5.30146182e-01 7.64677674e-02 6.67463720e-01 -3.84870432e-02
-9.46260750e-01 -1.84704199e-01 -7.39744544e-01 5.91755435e-02
-2.66641259e-01 6.42601967e-01 -3.34331632e-01 3.89324725e-02
3.28087598e-01 2.57535458e-01 -5.47117710e-01 -9.54329610e-01
-2.07424641e-01 1.17146409e+00 1.96710274e-01 -4.34904844e-01
-2.38304526e-01 -8.66130412e-01 -5.42841792e-01 -5.57619810e-01
-8.66293371e-01 -2.48112977e-01 -6.50330663e-01 -1.04511939e-01
8.91422033e-01 -7.84343243e-01 -6.01262748e-01 8.13866019e-01
-1.67637885e+00 -1.45287648e-01 4.28290337e-01 2.83943474e-01
-1.62124615e-02 2.90948540e-01 -1.06215751e+00 -1.01116729e+00
-7.79161513e-01 -9.88116980e-01 9.65606451e-01 6.69209734e-02
-2.11331010e-01 -9.89695728e-01 -7.62358531e-02 4.48312983e-02
3.62821668e-01 1.72918603e-01 1.31157780e+00 -1.07660878e+00
1.27948374e-01 8.57760981e-02 4.50651273e-02 6.02783442e-01
-2.94815183e-01 1.05040369e-03 -6.09322786e-01 -4.89952043e-02
-1.19771592e-01 -1.82003438e-01 1.21280217e+00 2.92405963e-01
1.12700617e+00 -1.95794225e-01 -3.62050772e-01 2.65836120e-01
1.34005165e+00 6.46111906e-01 9.02884722e-01 1.54928997e-01
6.56135798e-01 4.74332213e-01 6.90834999e-01 2.23565087e-01
6.64027035e-01 5.79068124e-01 2.19759330e-01 1.76960677e-01
-1.69571102e-01 -3.11007142e-01 6.67802691e-01 1.44406521e+00
1.33924425e-01 -8.82263899e-01 -1.21108103e+00 6.59316838e-01
-2.01534009e+00 -5.18421769e-01 -7.31773257e-01 1.73662961e+00
9.11266685e-01 -8.66371021e-02 -1.85982004e-01 2.34683365e-01
1.09271216e+00 -3.66127282e-01 -1.95028353e-02 -9.76580262e-01
-2.57676333e-01 4.33380604e-01 3.19583625e-01 5.82064092e-01
-1.16558230e+00 1.55849349e+00 6.22540712e+00 1.11498487e+00
-6.81155860e-01 4.00217265e-01 4.82237190e-01 4.21781629e-01
-6.62888139e-02 4.10288274e-02 -1.35797429e+00 1.12856674e+00
1.08215201e+00 4.02748138e-01 7.71051422e-02 3.72419268e-01
2.30775326e-02 -2.64174044e-01 -7.97744751e-01 7.79567242e-01
1.93571776e-01 -9.65874791e-01 -1.55587539e-01 -2.73923844e-01
4.06385958e-01 6.21450096e-02 -4.99185890e-01 6.18848205e-01
7.55134702e-01 -1.36570072e+00 5.86790144e-01 8.62978697e-01
4.79371071e-01 -7.85580993e-01 1.39983678e+00 5.04172802e-01
-7.26494491e-01 -7.11016729e-02 -6.13772035e-01 2.96077337e-02
4.01360184e-01 9.61243331e-01 -4.62686092e-01 6.82672143e-01
7.85919964e-01 8.53944957e-01 -4.24873829e-01 1.15668845e+00
-6.23418629e-01 7.75639594e-01 9.38086510e-02 -3.22828382e-01
2.52451338e-02 -9.26394947e-03 5.09110808e-01 1.55866742e+00
6.43039405e-01 1.50562927e-01 1.22957855e-01 4.69768256e-01
-3.41462582e-01 1.35719985e-01 -1.83709845e-01 1.98385730e-01
7.60540187e-01 9.80707049e-01 -2.06584737e-01 -3.40909421e-01
4.00501713e-02 1.12061524e+00 8.58317435e-01 -8.49834234e-02
-5.32950699e-01 -7.23212183e-01 3.43280166e-01 -5.85051119e-01
3.06257755e-01 -1.77914537e-02 -2.98809737e-01 -1.16572380e+00
-8.32347497e-02 -9.33432996e-01 4.20885265e-01 -5.85262597e-01
-1.46344292e+00 9.63137150e-01 -7.30717123e-01 -8.10492337e-01
5.70251374e-03 -7.87837207e-01 -4.63135809e-01 1.12803817e+00
-1.48907733e+00 -9.52752829e-01 4.93681431e-02 3.55912507e-01
6.14431381e-01 -4.75906044e-01 1.00483775e+00 8.21907699e-01
-1.09977949e+00 8.52156937e-01 6.10940084e-02 3.23028624e-01
7.51108766e-01 -1.42214859e+00 2.46362552e-01 1.04558551e+00
-2.18419895e-01 3.18540692e-01 6.72162294e-01 -1.10063207e+00
-8.81256521e-01 -1.26719689e+00 2.20717430e+00 -3.37360054e-01
2.06404805e-01 -2.29808286e-01 -9.38597143e-01 5.85262120e-01
1.23930536e-01 -6.81965053e-02 4.71277624e-01 2.77408481e-01
2.99024165e-01 5.44974208e-01 -1.28558838e+00 -8.07169303e-02
1.01047182e+00 -2.07100704e-01 -6.83248937e-01 5.78547895e-01
7.59285688e-01 -6.47785962e-01 -1.02347195e+00 3.25624228e-01
4.08858154e-03 -4.93722826e-01 3.10957342e-01 -9.81553674e-01
6.95165217e-01 -2.41626158e-01 -7.90483132e-02 -1.73469770e+00
-4.35961366e-01 -2.47619733e-01 7.61230290e-02 1.58888412e+00
7.40001857e-01 -5.42525351e-01 3.48419584e-02 3.14205050e-01
-6.15232885e-01 -6.41849995e-01 -9.10604596e-01 -8.77977014e-01
2.91456759e-01 -3.13324958e-01 5.61137497e-01 1.08887827e+00
1.56001881e-01 3.29350948e-01 -8.23919654e-01 1.03997648e-01
1.11395992e-01 -3.28518182e-01 -9.20030326e-02 -1.18719041e+00
1.75305769e-01 -1.98176950e-01 -2.72382081e-01 -7.86338270e-01
5.24664402e-01 -9.85004187e-01 5.98874450e-01 -1.47682595e+00
1.16484426e-02 -5.80775738e-01 -4.13273633e-01 8.24521959e-01
-6.34719610e-01 -1.93643034e-01 1.23737022e-01 -8.00320879e-02
-7.99988210e-01 4.80191171e-01 6.68042958e-01 3.15892845e-01
8.71761516e-02 -3.08889151e-01 -4.79629368e-01 5.92759013e-01
7.73683012e-01 -9.40585196e-01 5.13070226e-01 -9.19286430e-01
4.71683145e-01 1.52166292e-01 -2.30774507e-01 -6.85020328e-01
2.51992851e-01 2.65015364e-01 2.03082591e-01 -5.51706731e-01
-3.04645747e-01 -3.58548939e-01 -1.13308266e-01 6.66908085e-01
-2.96437144e-01 5.77060342e-01 2.97216121e-02 3.22007760e-02
-2.79581398e-01 -8.59028101e-01 7.76817381e-01 -2.80458897e-01
-8.30366910e-01 1.65909566e-02 -5.57545900e-01 1.77414700e-01
6.76717281e-01 3.18576783e-01 -5.79316616e-01 7.69810332e-03
-1.13883579e+00 6.16671443e-01 -1.34039715e-01 5.50123870e-01
6.94635153e-01 -1.01826823e+00 -1.14956081e+00 1.20953247e-01
9.70272347e-02 -3.26033235e-01 1.13276601e-01 7.60840297e-01
-4.85586077e-01 3.97462100e-01 -6.21718168e-02 -8.18519294e-02
-1.33096611e+00 -7.16043860e-02 5.54043174e-01 -8.10689151e-01
-4.39241856e-01 1.36210358e+00 -7.69950867e-01 -7.00684249e-01
3.75205785e-01 3.82145122e-02 -8.21233273e-01 -4.49653231e-02
4.71128583e-01 6.45806432e-01 6.33871675e-01 -8.56501877e-01
-6.42327011e-01 2.94985592e-01 -2.68032193e-01 5.70301175e-01
1.33949137e+00 -2.28941351e-01 -5.59629798e-01 1.50865823e-01
8.82700980e-01 -2.59326011e-01 -2.96009272e-01 -1.46332875e-01
6.13719225e-01 -4.04427573e-02 1.76452562e-01 -1.42099237e+00
-8.70560408e-01 9.49416697e-01 5.72542489e-01 6.55596256e-02
7.44687498e-01 -2.66052037e-01 1.16362834e+00 6.27489090e-02
2.88932890e-01 -1.48700738e+00 -4.85527813e-01 1.58226645e+00
7.40186214e-01 -1.26715994e+00 -5.17032027e-01 -3.57684791e-01
-7.89324939e-01 1.04301751e+00 7.44939685e-01 -2.26127893e-01
6.58812225e-01 3.05534422e-01 -2.59950943e-02 -1.22506380e-01
-9.60486531e-01 -3.67619097e-01 2.81964391e-01 2.39496782e-01
8.76501322e-01 2.47156724e-01 -1.06405509e+00 1.02871287e+00
-1.68257311e-01 -1.45960018e-01 4.08536404e-01 6.45527780e-01
-6.22908473e-01 -1.41411889e+00 5.31794354e-02 6.67002320e-01
-1.00058544e+00 -5.01725852e-01 -3.72893035e-01 3.62457663e-01
6.64102435e-01 1.35065556e+00 3.32201049e-02 -7.19064891e-01
3.69241625e-01 4.47285593e-01 2.19354078e-01 -7.80041158e-01
-1.10654104e+00 -2.71232992e-01 4.60225523e-01 -4.17805880e-01
-1.62024289e-01 -5.18661380e-01 -1.46463144e+00 -3.02552640e-01
-6.86424494e-01 3.30847323e-01 6.16583169e-01 1.47427678e+00
4.70194250e-01 6.76636875e-01 2.43309930e-01 -6.61758631e-02
-3.95171136e-01 -1.55118179e+00 -6.85754180e-01 3.42914313e-01
2.31571466e-01 -5.04833460e-01 -2.01133892e-01 -1.31074399e-01] | [11.064170837402344, 10.785006523132324] |
160074fe-6dd3-43b9-a0a1-b981d23afd00 | hierarchical-graph-network-for-multi-hop | 1911.03631 | null | https://arxiv.org/abs/1911.03631v4 | https://arxiv.org/pdf/1911.03631v4.pdf | Hierarchical Graph Network for Multi-hop Question Answering | In this paper, we present Hierarchical Graph Network (HGN) for multi-hop question answering. To aggregate clues from scattered texts across multiple paragraphs, a hierarchical graph is created by constructing nodes on different levels of granularity (questions, paragraphs, sentences, entities), the representations of which are initialized with pre-trained contextual encoders. Given this hierarchical graph, the initial node representations are updated through graph propagation, and multi-hop reasoning is performed via traversing through the graph edges for each subsequent sub-task (e.g., paragraph selection, supporting facts extraction, answer prediction). By weaving heterogeneous nodes into an integral unified graph, this hierarchical differentiation of node granularity enables HGN to support different question answering sub-tasks simultaneously. Experiments on the HotpotQA benchmark demonstrate that the proposed model achieves new state of the art, outperforming existing multi-hop QA approaches. | ['Shuohang Wang', 'Rohit Pillai', 'Jingjing Liu', 'Zhe Gan', 'Yuwei Fang', 'Siqi Sun'] | 2019-11-09 | null | https://aclanthology.org/2020.emnlp-main.710 | https://aclanthology.org/2020.emnlp-main.710.pdf | emnlp-2020-11 | ['multi-hop-question-answering'] | ['knowledge-base'] | [ 6.72084838e-02 9.81304467e-01 -9.20922086e-02 -2.45897427e-01
-1.27309656e+00 -7.21137702e-01 4.43807602e-01 8.17862749e-01
-1.02719352e-01 9.29486394e-01 6.67652965e-01 -4.61554885e-01
-1.30621523e-01 -1.25655639e+00 -7.10333288e-01 -5.51550575e-02
1.20227620e-01 7.93281257e-01 7.39601672e-01 -3.35421950e-01
1.90373078e-01 -7.02653676e-02 -1.04448891e+00 6.50079966e-01
1.15282297e+00 9.21099126e-01 -2.52946429e-02 9.35880959e-01
-6.90156817e-01 1.42177320e+00 -6.17727757e-01 -9.44298923e-01
-3.31290096e-01 -3.29209358e-01 -1.47805321e+00 -2.46454421e-02
6.27823293e-01 -4.19967920e-01 -4.56392139e-01 9.78750646e-01
2.08202213e-01 2.70273209e-01 4.33920741e-01 -9.78130639e-01
-1.05317116e+00 1.15631711e+00 -2.58335412e-01 2.03782797e-01
7.57525206e-01 -1.27063721e-01 1.98631895e+00 -6.86633885e-01
7.22506583e-01 1.44089067e+00 4.22593027e-01 3.85949671e-01
-1.06671846e+00 -2.26142094e-01 4.33419853e-01 4.07685012e-01
-9.05483305e-01 1.43568050e-02 8.04222345e-01 -2.36834347e-01
1.24237204e+00 2.27644578e-01 3.28266293e-01 8.92272592e-01
8.39191303e-02 1.03261447e+00 5.47095776e-01 -2.69982874e-01
1.06017269e-01 -2.24854991e-01 8.85779500e-01 1.33633709e+00
4.16633993e-01 -8.98748457e-01 -6.26582205e-01 -4.26329792e-01
4.79638636e-01 -4.19954181e-01 -4.10364002e-01 -1.78033542e-02
-1.02176785e+00 1.05992651e+00 7.97389209e-01 2.47167215e-01
-7.13265896e-01 6.89751655e-02 3.43434811e-01 3.56687278e-01
2.54957587e-01 6.85845137e-01 -5.15682876e-01 4.31777060e-01
-6.21774495e-01 1.46720752e-01 1.08509541e+00 1.18070531e+00
9.83221710e-01 -4.42482620e-01 -1.03452492e+00 6.13734841e-01
3.82754415e-01 1.10416286e-01 6.80530593e-02 -9.91913378e-01
1.18147743e+00 1.28884101e+00 -7.47953802e-02 -1.13052595e+00
-5.13262510e-01 -3.81552845e-01 -9.13905025e-01 -8.35020185e-01
2.61358082e-01 -3.40667218e-01 -9.92659867e-01 1.51968026e+00
6.07250869e-01 -9.15243030e-02 1.72843665e-01 6.83135629e-01
1.46898496e+00 8.35986078e-01 3.99706632e-01 1.03238076e-01
1.71609151e+00 -1.37425482e+00 -7.86235034e-01 -1.73499703e-01
5.45281529e-01 -2.29281157e-01 9.70672369e-01 4.08285409e-02
-1.19661677e+00 -5.58043420e-01 -7.28828073e-01 -7.92644143e-01
-4.03881997e-01 -1.16462164e-01 3.43939573e-01 4.26015854e-02
-1.36689925e+00 1.18557885e-01 -3.48616183e-01 -1.97383478e-01
2.96789020e-01 1.16515592e-01 -9.52852219e-02 -2.35467091e-01
-1.78023064e+00 6.23758912e-01 6.45379603e-01 -7.87313953e-02
-8.27018201e-01 -5.89054644e-01 -1.11504102e+00 5.61417460e-01
6.61348403e-01 -1.46768892e+00 1.21739686e+00 -1.80561859e-02
-1.17692971e+00 6.25871301e-01 -4.09650743e-01 -5.53269088e-01
-3.25841382e-02 -2.70835549e-01 -3.70424241e-01 6.67640328e-01
5.80956161e-01 6.43278778e-01 6.94876373e-01 -1.33387494e+00
-7.85570621e-01 -2.53120422e-01 7.74274170e-01 3.91491085e-01
-1.83075443e-01 -3.19281906e-01 -8.97841990e-01 -8.85380656e-02
1.39404833e-01 -3.18343371e-01 -2.90745676e-01 -7.45663583e-01
-1.04011333e+00 -9.08328354e-01 3.86162102e-01 -1.15133381e+00
1.70509076e+00 -1.50672626e+00 5.26086092e-01 2.01420590e-01
8.64915907e-01 -2.76393473e-01 -1.82274967e-01 6.57930017e-01
5.47374547e-01 2.28616044e-01 -2.79730231e-01 -2.69152403e-01
2.35871390e-01 2.73272246e-01 -2.91942239e-01 -2.80452102e-01
4.12778020e-01 1.39325440e+00 -1.27961099e+00 -1.13467085e+00
-3.43171358e-01 1.53149441e-01 -5.43399811e-01 3.27329248e-01
-7.02454746e-01 2.26464391e-01 -1.02907944e+00 6.99057341e-01
1.96114570e-01 -1.00927699e+00 2.24365368e-01 -2.93774366e-01
4.29227769e-01 6.77602589e-01 -6.76585793e-01 1.66151977e+00
-4.17694122e-01 2.90128261e-01 7.86333978e-02 -7.77608037e-01
8.07914853e-01 2.92620301e-01 1.64984409e-02 -6.43558145e-01
-1.79944128e-01 -1.44597605e-01 -2.91102678e-01 -6.56973839e-01
8.02976668e-01 5.26602507e-01 -2.29963914e-01 2.44543448e-01
5.36551952e-01 -9.26199853e-02 6.48965478e-01 9.14751470e-01
1.39994240e+00 -2.26126522e-01 1.99194729e-01 8.63182452e-03
8.89060676e-01 3.00487995e-01 1.41075432e-01 9.23983693e-01
1.76927954e-01 2.87432402e-01 1.00099766e+00 -1.27045065e-01
-6.24458253e-01 -1.10961795e+00 4.28494334e-01 1.29269934e+00
1.19825713e-01 -6.68682098e-01 -7.46726274e-01 -1.29218793e+00
1.25910953e-01 8.39536369e-01 -7.51484394e-01 -3.08970846e-02
-7.99450755e-01 -2.71887124e-01 5.39093673e-01 5.10776341e-01
7.83495486e-01 -1.26885939e+00 -1.73046127e-01 5.51721215e-01
-6.73774242e-01 -1.37027848e+00 -2.65994370e-01 -1.26014963e-01
-8.33313763e-01 -1.19880414e+00 -3.45097959e-01 -1.08718848e+00
6.89957201e-01 1.99723020e-01 1.98513067e+00 5.40347040e-01
2.64564812e-01 7.50494361e-01 -6.46368265e-01 1.39034554e-01
-2.01633200e-01 4.84603286e-01 -7.69194424e-01 2.15694234e-02
1.18681878e-01 -2.95392424e-01 -8.73607934e-01 -1.47359431e-01
-8.42812836e-01 -1.24621112e-02 5.18825352e-01 8.93402755e-01
7.45948672e-01 -8.73730332e-02 8.19202244e-01 -1.42185211e+00
1.13779509e+00 -8.51852000e-01 -4.28529799e-01 9.54497337e-01
-4.21387613e-01 2.80197024e-01 8.12704504e-01 7.91900530e-02
-1.31248391e+00 -6.28013372e-01 -2.92816758e-01 6.19914643e-02
-8.74067191e-03 9.42140281e-01 -1.75733715e-01 3.45882177e-01
5.40782094e-01 9.02981684e-02 -6.52695656e-01 -1.97630212e-01
9.92291152e-01 3.88696164e-01 4.97771025e-01 -7.31443763e-01
7.60183334e-01 4.61158641e-02 -1.37536481e-01 -5.14404953e-01
-1.48907578e+00 -5.48179567e-01 -6.11680269e-01 -1.62737846e-01
1.42573524e+00 -7.42598891e-01 -6.93891406e-01 -1.67565465e-01
-1.40600121e+00 -3.15821588e-01 -1.79080427e-01 -1.59012079e-01
-5.12159429e-02 3.75794142e-01 -1.04778993e+00 -6.43102765e-01
-7.17885256e-01 -7.99259722e-01 1.25406051e+00 5.35332441e-01
-1.47563398e-01 -1.30792379e+00 2.68871244e-02 1.05293453e+00
7.57557750e-02 1.24370605e-01 1.55214107e+00 -8.50355864e-01
-9.12276268e-01 -7.70952478e-02 -5.28045237e-01 -7.73688778e-02
3.65279652e-02 -2.91598499e-01 -6.53357208e-01 5.72570134e-03
-3.73739243e-01 -6.54668868e-01 1.08142221e+00 1.03102572e-01
1.20732939e+00 -6.34080231e-01 -3.76178414e-01 5.39391115e-03
1.24677825e+00 -1.36029527e-01 4.24969554e-01 3.16762835e-01
1.08141506e+00 6.84163094e-01 3.70738626e-01 1.27851948e-01
1.11056566e+00 -3.71216261e-03 7.67711818e-01 5.36154583e-02
-2.72485822e-01 -6.19435906e-01 -1.24196395e-01 9.47697878e-01
1.55034527e-01 -6.27251208e-01 -8.63525927e-01 6.84444070e-01
-1.80691481e+00 -7.94897556e-01 -5.58706164e-01 1.66605997e+00
7.58867979e-01 7.27183297e-02 -7.97980875e-02 -2.84270912e-01
7.56549180e-01 4.73550856e-01 -5.32666445e-01 -1.00686602e-01
-1.24243498e-01 3.10591131e-01 -3.41606960e-02 8.98221850e-01
-8.90702426e-01 1.23200417e+00 5.45547247e+00 4.79768842e-01
-2.36946464e-01 1.05520919e-01 5.64816535e-01 5.47467053e-01
-7.87722290e-01 8.05589855e-02 -8.11725974e-01 3.95606644e-02
5.47415376e-01 -7.15903491e-02 1.65686235e-01 4.63463455e-01
-5.32167912e-01 1.14181824e-01 -8.12898338e-01 3.40718359e-01
8.61384422e-02 -1.68387604e+00 6.64477527e-01 -4.92878139e-01
8.04890573e-01 -1.16543032e-01 -3.12005818e-01 8.18304479e-01
9.95550931e-01 -7.09713042e-01 1.89108178e-01 4.22724545e-01
3.35244954e-01 -5.29518604e-01 7.51599848e-01 2.94123530e-01
-1.48161483e+00 -1.61919966e-01 -3.66419077e-01 3.98964942e-01
3.99584889e-01 4.89006460e-01 -8.78213048e-01 1.33328474e+00
5.81215441e-01 2.62915462e-01 -8.00214887e-01 6.55305982e-01
-8.49946439e-01 9.24866736e-01 1.50670588e-01 -3.42968762e-01
6.02923572e-01 -2.44803235e-01 3.10423911e-01 1.25330079e+00
1.72680601e-01 4.64667588e-01 1.93917215e-01 7.65810311e-01
-7.28307128e-01 1.53267607e-01 -3.70318353e-01 9.18954387e-02
6.31073952e-01 1.52339995e+00 -5.04502892e-01 -7.92086661e-01
-7.02865422e-01 9.54711854e-01 1.15373576e+00 7.14433193e-01
-6.49805784e-01 -6.41539752e-01 7.43146688e-02 -3.12045008e-01
3.76143813e-01 -8.60361680e-02 -1.36147365e-01 -1.25489843e+00
7.68230334e-02 -7.45585680e-01 1.26889682e+00 -9.48968053e-01
-1.48502898e+00 7.97884524e-01 -3.72262627e-01 -5.99180996e-01
-6.69685900e-02 -2.75384843e-01 -7.09129393e-01 8.88526618e-01
-1.65539634e+00 -1.28408110e+00 -3.29318851e-01 8.06195736e-01
5.08528352e-01 8.41237083e-02 7.27555275e-01 -1.05221048e-01
-4.76230085e-01 4.39383060e-01 -5.38372815e-01 4.41470653e-01
2.24848524e-01 -1.68086493e+00 4.36609805e-01 8.56338739e-01
5.09837747e-01 6.47105396e-01 3.11112642e-01 -9.24688756e-01
-1.30364752e+00 -1.26131546e+00 1.39087832e+00 -5.81027091e-01
1.19311452e+00 -1.49445340e-01 -1.32574129e+00 7.83880651e-01
7.12062716e-01 -4.76583630e-01 6.85936689e-01 4.67205316e-01
-6.21711433e-01 1.67684436e-01 -8.50401819e-01 5.87971568e-01
9.08840060e-01 -7.40963876e-01 -1.15493548e+00 5.86451590e-01
1.51948607e+00 -4.59728360e-01 -1.11423314e+00 2.73602188e-01
-1.55782580e-01 -6.76066756e-01 9.77248013e-01 -1.11404598e+00
7.21797645e-01 -1.45501867e-01 -3.50481048e-02 -1.20565820e+00
-7.05286264e-01 -5.68160653e-01 -8.41672838e-01 1.33616161e+00
9.82031941e-01 -4.90926743e-01 6.64674401e-01 3.12898576e-01
-4.11335528e-01 -1.04412258e+00 -7.71926105e-01 -1.16993494e-01
-1.34508416e-01 5.00592440e-02 7.59724259e-01 8.69428158e-01
1.82975307e-01 1.22083509e+00 2.27357522e-02 7.58411944e-01
7.88834035e-01 5.14611900e-01 4.18720365e-01 -1.31244266e+00
-2.69917011e-01 -4.22246575e-01 2.01550528e-01 -1.48641610e+00
2.46528536e-01 -1.02346003e+00 -9.86378416e-02 -2.67841935e+00
8.20530653e-02 -2.60524433e-02 -3.60720336e-01 3.42012584e-01
-1.06697547e+00 -2.98833460e-01 -5.25956489e-02 -5.84095567e-02
-1.33233964e+00 4.46806341e-01 1.61577785e+00 -4.74710852e-01
-7.11988658e-02 -2.19874084e-01 -1.01313829e+00 3.84503335e-01
7.39688873e-01 -2.11052075e-01 -6.64973140e-01 -8.58993471e-01
5.69978058e-01 6.52808666e-01 1.32535025e-01 -5.50019681e-01
6.98899448e-01 2.25550324e-01 2.01390296e-01 -6.83013320e-01
1.24363437e-01 -3.70026529e-01 -6.51929379e-01 1.93444625e-01
-7.20369458e-01 1.29328042e-01 -1.26361385e-01 7.95232534e-01
-5.10837615e-01 -1.47648215e-01 5.57547398e-02 -2.21578419e-01
-5.56336761e-01 5.96997797e-01 -6.82408735e-02 6.05507135e-01
4.37538832e-01 3.64962280e-01 -8.98539424e-01 -5.66594362e-01
-8.60480785e-01 1.03355837e+00 -2.66713202e-01 2.57663071e-01
7.39999950e-01 -1.23815918e+00 -8.54579329e-01 -4.17659432e-01
2.50320941e-01 5.64011574e-01 5.12148023e-01 5.59953034e-01
-3.40345323e-01 6.08801246e-01 2.96602339e-01 -2.30135396e-01
-9.45430219e-01 5.87945461e-01 -1.24135306e-02 -1.25320470e+00
-5.78581095e-01 1.10361302e+00 1.73977345e-01 -3.91848594e-01
1.53842345e-01 -3.88691485e-01 -9.66172695e-01 3.01670730e-01
2.32242748e-01 3.26407582e-01 4.32468764e-02 -2.25232795e-01
6.99652284e-02 3.57270271e-01 -2.37307593e-01 1.37839630e-01
1.01150477e+00 -3.70160758e-01 -5.69962800e-01 2.34063983e-01
7.98074365e-01 -1.91849582e-02 -8.31037402e-01 -4.42218632e-01
3.64887953e-01 2.12639958e-01 -3.46376449e-01 -7.41652787e-01
-8.34852993e-01 7.54668176e-01 -5.05835354e-01 9.33191061e-01
9.94540393e-01 6.01436675e-01 1.04241776e+00 7.39521384e-01
3.64239067e-01 -7.70831764e-01 3.43898147e-01 8.45015228e-01
9.73369002e-01 -1.03061676e+00 -2.87035376e-01 -5.68840861e-01
-6.52174354e-01 9.72455561e-01 9.29665327e-01 7.45155243e-03
2.05540389e-01 -2.99223661e-01 -1.30004868e-01 -7.90336847e-01
-9.77474093e-01 -5.25446892e-01 6.23049021e-01 3.93150449e-01
3.45109314e-01 5.86630553e-02 -1.82628796e-01 7.27902055e-01
-2.87423700e-01 -5.71622312e-01 2.21268728e-01 6.52664840e-01
-7.70462215e-01 -7.70211816e-01 -8.51612687e-02 7.56297886e-01
-3.90251189e-01 -4.50715303e-01 -6.93997085e-01 7.80951321e-01
-1.96243927e-01 1.36832607e+00 -1.00229912e-01 -3.09474617e-01
4.62288618e-01 4.37095612e-01 2.86482543e-01 -7.96910644e-01
-8.49050105e-01 -5.13238132e-01 6.95197225e-01 -4.71254319e-01
2.15818360e-03 -2.60960847e-01 -1.43900561e+00 1.25850543e-01
-1.82701200e-01 6.70605958e-01 -7.89831113e-03 9.57963824e-01
5.45818925e-01 1.02746689e+00 4.08451349e-01 -8.96133110e-03
-2.53181219e-01 -1.03449881e+00 -1.99294850e-01 3.80325496e-01
3.78508598e-01 -2.60838479e-01 -2.41524383e-01 -1.23215742e-01] | [10.704163551330566, 7.8748369216918945] |
593c4e0a-72aa-4b02-be14-448f1913e5f6 | mask-aware-iou-for-anchor-assignment-in-real | 2110.09734 | null | https://arxiv.org/abs/2110.09734v1 | https://arxiv.org/pdf/2110.09734v1.pdf | Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation | This paper presents Mask-aware Intersection-over-Union (maIoU) for assigning anchor boxes as positives and negatives during training of instance segmentation methods. Unlike conventional IoU or its variants, which only considers the proximity of two boxes; maIoU consistently measures the proximity of an anchor box with not only a ground truth box but also its associated ground truth mask. Thus, additionally considering the mask, which, in fact, represents the shape of the object, maIoU enables a more accurate supervision during training. We present the effectiveness of maIoU on a state-of-the-art (SOTA) assigner, ATSS, by replacing IoU operation by our maIoU and training YOLACT, a SOTA real-time instance segmentation method. Using ATSS with maIoU consistently outperforms (i) ATSS with IoU by $\sim 1$ mask AP, (ii) baseline YOLACT with fixed IoU threshold assigner by $\sim 2$ mask AP over different image sizes and (iii) decreases the inference time by $25 \%$ owing to using less anchors. Then, exploiting this efficiency, we devise maYOLACT, a faster and $+6$ AP more accurate detector than YOLACT. Our best model achieves $37.7$ mask AP at $25$ fps on COCO test-dev establishing a new state-of-the-art for real-time instance segmentation. Code is available at https://github.com/kemaloksuz/Mask-aware-IoU | ['Emre Akbas', 'Sinan Kalkan', 'Zeynep Sonat Baltaci', 'Fehmi Kahraman', 'Baris Can Cam', 'Kemal Oksuz'] | 2021-10-19 | null | null | null | null | ['real-time-instance-segmentation'] | ['computer-vision'] | [ 1.00126334e-01 2.71197706e-01 -2.11413667e-01 -1.27633214e-01
-1.19178426e+00 -5.74821353e-01 -9.00707860e-03 1.02499850e-01
-5.93853652e-01 5.50647914e-01 -8.10168862e-01 -3.32892805e-01
2.98076570e-01 -8.24291706e-01 -1.27376533e+00 -3.65434945e-01
-5.41850850e-02 7.80993283e-01 8.92195225e-01 3.42556834e-01
-4.43299999e-03 2.14639530e-01 -1.40081882e+00 2.21899584e-01
7.07593799e-01 1.39981830e+00 1.43653914e-01 7.57150054e-01
-7.29658157e-02 2.40840614e-01 -8.51149797e-01 -5.82506239e-01
6.17655277e-01 -3.36171120e-01 -6.92807615e-01 -9.04182643e-02
9.36965585e-01 -3.86701763e-01 1.52893767e-01 8.77248228e-01
4.30978835e-01 4.02196571e-02 6.34920657e-01 -1.10163629e+00
-1.15134075e-01 6.14530027e-01 -1.10764682e+00 4.58975255e-01
1.19734988e-01 3.08239758e-01 1.14240396e+00 -8.94014001e-01
6.70234978e-01 9.04102325e-01 7.33391166e-01 4.29010987e-01
-1.24177170e+00 -8.78340244e-01 2.39458695e-01 -1.45145476e-01
-1.69558418e+00 -3.24700139e-02 2.96856165e-01 -2.53556997e-01
9.92717624e-01 4.93290603e-01 4.57536876e-01 5.02834499e-01
-1.48557246e-01 1.28307307e+00 9.70853388e-01 -4.24936593e-01
2.42194623e-01 1.37096569e-01 2.39114627e-01 1.01399624e+00
9.99725610e-02 -2.31834456e-01 -1.75587177e-01 3.01889442e-02
8.51704717e-01 -1.59452379e-01 -7.42887855e-02 -1.00211486e-01
-1.03160512e+00 4.44989800e-01 6.19854271e-01 2.29324967e-01
-4.39313799e-02 3.67480844e-01 3.82317692e-01 -4.72055152e-02
4.20517296e-01 4.88843352e-01 -6.34049058e-01 -2.37960845e-01
-1.30405593e+00 1.20794602e-01 4.71095115e-01 1.09443736e+00
8.45302999e-01 3.60657535e-02 -3.17350119e-01 6.91158772e-01
-4.22364324e-02 5.71356773e-01 2.54529297e-01 -9.58514810e-01
6.02488577e-01 7.67444015e-01 5.99224381e-02 -5.60731828e-01
-1.87488899e-01 -7.08807290e-01 -3.31946105e-01 2.07326159e-01
7.67339647e-01 -1.05998956e-01 -1.14867723e+00 1.51068425e+00
5.54588556e-01 6.13720715e-01 -4.02256310e-01 8.44029963e-01
5.87412298e-01 6.04358673e-01 -9.65295285e-02 -2.00340729e-02
1.58409774e+00 -9.67640996e-01 -2.91553378e-01 -4.20019299e-01
8.81834507e-01 -6.19616449e-01 1.44116759e+00 5.30322790e-01
-1.21993291e+00 -5.90086460e-01 -1.09859371e+00 -4.61614877e-02
-3.90772998e-01 3.91331762e-01 6.75827563e-01 8.43249321e-01
-9.44366455e-01 4.18856293e-01 -9.75660145e-01 -2.67083403e-02
7.97142506e-01 5.95778823e-01 -1.73439905e-01 1.34302869e-01
-7.55255640e-01 3.82061511e-01 2.34307662e-01 -1.86577156e-01
-6.06961906e-01 -8.91739309e-01 -9.40404713e-01 1.13402143e-01
9.19494212e-01 -4.34734732e-01 1.27782774e+00 -6.90275013e-01
-1.12142038e+00 9.98311818e-01 -3.38411629e-01 -8.56545985e-01
7.90758431e-01 -3.69962275e-01 4.03341614e-02 1.44727618e-01
4.08756852e-01 1.07617104e+00 5.91561675e-01 -1.17540359e+00
-8.63367379e-01 -3.40575546e-01 1.52099922e-01 -1.24390446e-01
1.49935763e-02 -1.49582058e-01 -1.00785470e+00 -5.59408426e-01
7.51898736e-02 -7.08660901e-01 -1.85800165e-01 1.51334956e-01
-6.37836158e-01 -3.91171098e-01 8.36087465e-01 -4.27360326e-01
1.58836162e+00 -2.18095040e+00 -3.89311761e-01 2.98170388e-01
2.15856060e-01 5.83803594e-01 1.19897112e-01 -2.47972861e-01
1.36744708e-01 2.51491666e-01 -5.78880370e-01 -7.40476727e-01
2.66525205e-02 2.42684096e-01 -9.72928256e-02 3.29666227e-01
1.31582320e-01 8.19119871e-01 -8.46584737e-01 -7.71310449e-01
3.39616358e-01 1.78302348e-01 -6.15855992e-01 4.66633216e-02
-3.33745271e-01 4.16725464e-02 -2.90939540e-01 9.31600690e-01
7.87661493e-01 -2.29075834e-01 -1.38965860e-01 -1.23169295e-01
5.94402142e-02 3.37211229e-02 -1.34650517e+00 1.53923011e+00
-3.83412421e-01 4.98168647e-01 2.78427396e-02 -7.40162671e-01
8.63507867e-01 1.35922432e-01 3.92986178e-01 -6.99693680e-01
4.24382478e-01 4.44317102e-01 -1.44013345e-01 4.64113727e-02
1.87012777e-01 3.01664621e-01 -3.75794545e-02 3.21346968e-01
-1.61604080e-02 -1.87322661e-01 5.46988070e-01 2.70342439e-01
1.27249539e+00 2.12572679e-01 3.13145906e-01 -1.69371247e-01
4.11075979e-01 -1.57382980e-01 6.71092331e-01 9.81389403e-01
-5.58206618e-01 9.09458697e-01 5.26227653e-01 -2.83466786e-01
-8.16215098e-01 -1.09707415e+00 -4.74470735e-01 8.51668477e-01
2.14537293e-01 -2.80695200e-01 -1.29011226e+00 -1.10204530e+00
7.05004632e-02 7.16586232e-01 -7.72878230e-01 3.65390390e-01
-6.91683114e-01 -6.46183968e-01 7.52224505e-01 7.83593595e-01
6.26502991e-01 -9.39201236e-01 -8.87431502e-01 -5.01080230e-02
1.33291066e-01 -1.36752141e+00 -9.06383693e-01 2.63940811e-01
-7.87538826e-01 -1.12230349e+00 -7.00038433e-01 -4.37547088e-01
8.78731310e-01 -5.97572215e-02 1.21170056e+00 1.80425510e-01
-4.44441378e-01 1.39040172e-01 -2.06103757e-01 -5.65621018e-01
3.27950753e-02 6.52499571e-02 -2.87988871e-01 -2.97861159e-01
3.75055999e-01 -3.65136504e-01 -7.47391403e-01 6.18695378e-01
-7.84099162e-01 1.17861189e-01 4.70144749e-01 7.34981477e-01
1.13034320e+00 -2.56339192e-01 3.80441308e-01 -1.31073868e+00
-1.27755448e-01 -1.41543463e-01 -8.76965344e-01 1.06876358e-01
-4.98956889e-01 -3.12085867e-01 6.37050688e-01 -3.28607649e-01
-5.31601608e-01 6.86982945e-02 -3.20391536e-01 -7.67471075e-01
-3.75686169e-01 -8.74799024e-03 -1.98321536e-01 2.22935274e-01
7.92715907e-01 -1.37980998e-01 -3.00882399e-01 -3.39723885e-01
1.80022061e-01 4.22230542e-01 5.79221189e-01 -6.36005759e-01
5.44733226e-01 6.27664745e-01 -1.52298823e-01 -3.81338239e-01
-8.54456604e-01 -6.89198434e-01 -6.21438205e-01 -5.99889830e-02
7.98082471e-01 -7.32654691e-01 -8.36810470e-01 1.59703240e-01
-9.46429610e-01 -6.08875394e-01 -3.98685962e-01 1.80206388e-01
-3.11065137e-01 1.50695339e-01 -5.89335203e-01 -9.09235001e-01
-4.71333981e-01 -1.23286057e+00 1.36502779e+00 1.66152090e-01
-2.62495577e-01 -6.14379525e-01 -3.00885051e-01 6.32663131e-01
-2.01885253e-01 3.79750043e-01 3.89067113e-01 -6.02800667e-01
-6.94840491e-01 -5.11397600e-01 -5.08956790e-01 3.78611296e-01
-1.18808612e-01 -9.88433976e-03 -1.14832962e+00 -1.72317073e-01
-3.84991884e-01 -4.83039394e-02 8.34519327e-01 6.07871771e-01
1.40046251e+00 -2.67185401e-02 -5.43498397e-01 5.93984723e-01
1.48008609e+00 4.46276069e-01 5.77246845e-01 3.60812128e-01
6.41601026e-01 6.43626973e-02 9.38029051e-01 3.53139341e-01
2.29549617e-01 8.38740587e-01 4.71422762e-01 -3.92888784e-01
-2.07093358e-01 -1.09422617e-01 1.43212989e-01 1.96931124e-01
1.12080555e-02 -3.46165597e-01 -9.54827964e-01 7.06105590e-01
-1.80640233e+00 -5.81200480e-01 -1.81345060e-01 2.38129807e+00
8.61014545e-01 6.84564650e-01 4.19764429e-01 2.48610184e-01
6.02457166e-01 -7.91696683e-02 -5.55687964e-01 -4.66753572e-01
1.45522773e-01 6.84691846e-01 7.95438468e-01 4.94823545e-01
-1.21933270e+00 1.10021472e+00 4.86160421e+00 1.32505536e+00
-9.04523015e-01 2.49001935e-01 1.25848174e+00 -2.67934948e-01
1.52139336e-01 -2.58042008e-01 -1.03488696e+00 5.84377527e-01
6.75826132e-01 4.14971530e-01 1.00247733e-01 1.17585671e+00
7.21334815e-02 -6.08952582e-01 -1.19298148e+00 7.43993104e-01
5.14456723e-03 -1.27487314e+00 -1.80398554e-01 -1.03551582e-01
6.75059021e-01 -1.54234678e-01 3.54356542e-02 4.88189399e-01
1.91912219e-01 -8.86077404e-01 1.02559853e+00 -1.31640688e-01
9.72015679e-01 -6.89252317e-01 9.86639977e-01 3.14108938e-01
-1.39630258e+00 2.50298619e-01 -1.85148656e-01 5.18638603e-02
-1.28699150e-02 6.59900069e-01 -1.12747896e+00 4.69835222e-01
9.02843297e-01 3.82949084e-01 -6.31909490e-01 9.69427764e-01
-1.85792640e-01 9.46666896e-01 -7.37042665e-01 1.71944544e-01
3.86362046e-01 4.19296399e-02 5.24361968e-01 1.52027738e+00
1.46167293e-01 7.11304694e-02 3.92441481e-01 9.84085798e-01
-1.70185447e-01 3.20592988e-03 -1.81131497e-01 3.58600169e-01
5.86835027e-01 1.01147962e+00 -1.31438327e+00 -5.22178829e-01
-1.81126058e-01 8.69763553e-01 2.04451904e-01 5.74649014e-02
-1.28745615e+00 -2.88703054e-01 3.79159957e-01 4.14892286e-01
6.33900762e-01 5.85326776e-02 -8.00459802e-01 -7.23449111e-01
3.24544996e-01 -6.01787090e-01 5.78793645e-01 -4.79456812e-01
-7.20259547e-01 6.20230138e-01 3.76804732e-02 -1.21766818e+00
1.73574179e-01 -7.14927435e-01 -6.26801610e-01 6.37703955e-01
-1.29451513e+00 -1.18637717e+00 -1.05551943e-01 1.71326101e-01
7.84983099e-01 4.17105734e-01 4.88195747e-01 5.10605633e-01
-9.62995470e-01 1.01096535e+00 -3.72561514e-01 4.43729073e-01
6.21331096e-01 -1.59669924e+00 5.78307450e-01 9.24734354e-01
3.75337929e-01 5.79233766e-01 6.06442034e-01 -5.64236522e-01
-7.98171401e-01 -1.06807554e+00 3.95337492e-01 -6.10898137e-01
3.82890970e-01 -4.29967493e-01 -8.45631421e-01 8.18364203e-01
-1.57679677e-01 4.03851986e-01 4.11738694e-01 -3.11036240e-02
-2.29206949e-01 -2.50549644e-01 -1.50265825e+00 5.26764989e-01
1.04773188e+00 -1.44575059e-01 -1.39636338e-01 8.94965678e-02
7.25788534e-01 -1.01564991e+00 -6.75397098e-01 5.96578181e-01
4.63358760e-01 -1.20717788e+00 9.49872494e-01 7.65823945e-02
2.87769139e-01 -6.15492582e-01 7.88868740e-02 -6.02474272e-01
1.40117660e-01 -3.19483280e-01 -9.11105573e-02 1.10410035e+00
7.33112037e-01 -5.36007047e-01 1.15871310e+00 4.39195514e-01
-4.09649014e-01 -1.35346925e+00 -1.20698559e+00 -7.89255679e-01
-1.21196188e-01 -9.35030878e-01 4.96819526e-01 6.45004153e-01
-3.40759128e-01 -1.05034612e-01 1.57149583e-01 2.56084293e-01
3.15342993e-01 -8.62512589e-02 8.89954805e-01 -7.14102447e-01
-5.70639670e-01 -4.98775512e-01 -4.80625987e-01 -1.22766972e+00
-2.04808652e-01 -7.17999220e-01 1.47655517e-01 -1.29925847e+00
-1.06146839e-02 -6.39383018e-01 -2.06129476e-01 7.55373895e-01
-4.23930377e-01 7.72252560e-01 2.41480067e-01 -1.14838798e-02
-8.82574081e-01 -4.97088432e-02 1.10618353e+00 -4.57740650e-02
-2.35577241e-01 1.59884661e-01 -3.32581073e-01 8.63698006e-01
5.43685198e-01 -4.20436472e-01 -1.50331408e-01 -3.66967916e-01
-1.43832993e-02 -6.42839223e-02 3.24139118e-01 -1.25019586e+00
-6.98718876e-02 2.57256269e-01 4.06023771e-01 -7.14417994e-01
4.41023380e-01 -7.68977523e-01 -1.69492856e-01 3.60714495e-01
1.13706604e-01 2.52500325e-02 6.14560008e-01 2.88875312e-01
-1.10090889e-01 -3.28922153e-01 8.76507461e-01 -2.18011186e-01
-6.92541718e-01 2.91745454e-01 3.43993306e-02 4.82168198e-02
1.25578260e+00 -7.02470899e-01 -2.55776346e-01 2.09811747e-01
-7.63597488e-01 5.05520344e-01 4.20097083e-01 -1.59030467e-01
4.09197569e-01 -7.00603783e-01 -3.02404672e-01 1.23819560e-01
-4.41319831e-02 6.18963718e-01 1.84242666e-01 9.18981671e-01
-6.47059917e-01 2.68936515e-01 3.61686707e-01 -9.80456173e-01
-1.52203190e+00 2.17813835e-01 3.78407210e-01 -5.89666009e-01
-4.02075082e-01 1.41185510e+00 4.68228012e-01 -2.58274227e-01
2.68201977e-01 -7.53843784e-01 2.26994202e-01 -2.13661164e-01
3.76218587e-01 4.39426392e-01 1.56397387e-01 -2.76541978e-01
-4.15293336e-01 4.71863806e-01 -1.54048756e-01 -9.50229093e-02
8.37977231e-01 2.36286029e-01 2.90469110e-01 3.55600923e-01
8.11201155e-01 1.37906894e-01 -1.52073312e+00 -1.22734858e-02
-4.50540148e-02 -6.51989937e-01 -8.41756910e-02 -9.31034327e-01
-1.08540094e+00 7.43248165e-01 6.03106439e-01 -9.36810300e-02
9.71446991e-01 1.17987446e-01 1.03011894e+00 -1.23485904e-02
5.98889768e-01 -9.22434986e-01 -2.18495112e-02 2.16735110e-01
4.93701547e-01 -1.25149405e+00 9.70941037e-02 -7.95819819e-01
-5.02451360e-01 7.05422878e-01 1.13247812e+00 -2.19545618e-01
4.57937092e-01 4.91657943e-01 7.90718570e-02 -6.61403760e-02
-3.92686188e-01 -3.31080496e-01 3.74121547e-01 2.77971208e-01
4.02868807e-01 1.41402215e-01 -2.23798886e-01 6.50889099e-01
-2.83819526e-01 -1.10153370e-01 9.68310982e-02 8.82082224e-01
-3.63550156e-01 -9.73890126e-01 -5.63546181e-01 6.65501952e-01
-6.43735051e-01 -1.00885801e-01 -1.78369001e-01 1.03676200e+00
6.68748617e-01 6.47466481e-01 4.07950997e-01 -1.21305026e-01
4.36066657e-01 -1.02468073e-01 3.72250080e-01 -8.95340979e-01
-7.77519226e-01 2.60931641e-01 -3.87115441e-02 -5.96641362e-01
-1.60797611e-02 -5.86324930e-01 -1.78034306e+00 -1.09644428e-01
-6.56012714e-01 1.56735852e-01 3.33639205e-01 9.34650362e-01
3.85131657e-01 6.50705934e-01 2.66094625e-01 -8.18903148e-01
3.41912061e-02 -9.35248673e-01 -3.87814075e-01 1.78560629e-01
3.19867283e-02 -7.50639439e-01 -2.20189080e-01 -4.41076271e-02] | [9.351394653320312, 0.07632551342248917] |
09e36849-1384-4b1f-afea-122a8db21ecf | on-exploring-pose-estimation-as-an-auxiliary | 2201.03859 | null | https://arxiv.org/abs/2201.03859v2 | https://arxiv.org/pdf/2201.03859v2.pdf | On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identification | Visible-infrared person re-identification (VI-ReID) has been challenging due to the existence of large discrepancies between visible and infrared modalities. Most pioneering approaches reduce intra-class variations and inter-modality discrepancies by learning modality-shared and ID-related features. However, an explicit modality-shared cue, i.e., body keypoints, has not been fully exploited in VI-ReID. Additionally, existing feature learning paradigms imposed constraints on either global features or partitioned feature stripes, which neglect the prediction consistency of global and part features. To address the above problems, we exploit Pose Estimation as an auxiliary learning task to assist the VI-ReID task in an end-to-end framework. By jointly training these two tasks in a mutually beneficial manner, our model learns higher quality modality-shared and ID-related features. On top of it, the learnings of global features and local features are seamlessly synchronized by Hierarchical Feature Constraint (HFC), where the former supervises the latter using the knowledge distillation strategy. Experimental results on two benchmark VI-ReID datasets show that the proposed method consistently improves state-of-the-art methods by significant margins. Specifically, our method achieves nearly 20$\%$ mAP improvements against the state-of-the-art method on the RegDB dataset. Our intriguing findings highlight the usage of auxiliary task learning in VI-ReID. | ['Jungong Han', 'Qiang Zhang', 'Xiao Ma', 'Nianchang Huang', 'Yunqi Miao'] | 2022-01-11 | null | null | null | null | ['auxiliary-learning'] | ['methodology'] | [-2.33405251e-02 -2.73281664e-01 -7.98030049e-02 -5.30274630e-01
-7.95791268e-01 -4.24639285e-01 6.84012532e-01 -1.17151782e-01
-5.25872409e-01 5.22670805e-01 3.83604616e-01 3.92407060e-01
-2.23428950e-01 -3.15258831e-01 -6.39829516e-01 -8.56211603e-01
2.62156457e-01 1.73901632e-01 -1.27091721e-01 -1.35381833e-01
-2.57222299e-02 2.54897267e-01 -1.70661199e+00 1.29198536e-01
8.28714132e-01 1.04402983e+00 -1.45394191e-01 5.39437309e-02
3.83086428e-02 4.14088786e-01 -1.31785169e-01 -6.31714165e-01
5.81974149e-01 -2.25389510e-01 -4.70927626e-01 -1.04415007e-01
9.37370300e-01 -1.68535516e-01 -6.03437364e-01 8.34247470e-01
7.97712922e-01 3.08350593e-01 4.18684095e-01 -1.34198368e+00
-7.37213671e-01 1.17685877e-01 -1.00681806e+00 -6.94136322e-03
6.31539583e-01 1.48352578e-01 7.46662974e-01 -9.28603947e-01
4.83589083e-01 1.24450099e+00 8.17558885e-01 6.29083097e-01
-1.31659245e+00 -8.86562645e-01 4.63619381e-01 3.88190508e-01
-1.67865705e+00 -5.75830400e-01 1.00614643e+00 -4.06941891e-01
5.53115189e-01 3.72204065e-01 4.07277197e-01 1.23176134e+00
-1.66370034e-01 7.13555872e-01 1.12223935e+00 -3.74974549e-01
-9.93929580e-02 2.83498794e-01 2.27910072e-01 5.73331773e-01
1.85543746e-01 3.09473783e-01 -9.66110289e-01 -2.37487018e-01
3.80161941e-01 2.46552542e-01 -2.40907356e-01 -5.29766798e-01
-1.14955664e+00 3.84529829e-01 5.76444685e-01 1.55171845e-02
-2.57444412e-01 -2.37490624e-01 4.18432802e-01 1.82751998e-01
5.15387237e-01 -8.24522078e-02 -5.02494097e-01 1.03092395e-01
-5.30150950e-01 2.94892639e-01 3.25541079e-01 9.83418047e-01
7.72807539e-01 -3.53904992e-01 -3.84932876e-01 9.25643861e-01
4.29211885e-01 6.14074409e-01 1.08733311e-01 -4.37232822e-01
6.00097597e-01 5.66505969e-01 7.64630884e-02 -7.82199740e-01
-5.90303481e-01 -6.07503474e-01 -9.56167996e-01 -5.65090775e-02
5.40957451e-01 -6.15081266e-02 -8.96195590e-01 2.07120872e+00
8.92305970e-01 1.95300847e-01 -2.37286299e-01 1.19817924e+00
9.32605326e-01 7.12871775e-02 3.78894985e-01 -2.71099024e-02
1.52825499e+00 -8.49099934e-01 -4.48458642e-01 -1.08037286e-01
4.56101447e-01 -6.73314273e-01 5.84174514e-01 1.29233867e-01
-6.54236376e-01 -8.47277343e-01 -6.84029400e-01 -1.03971682e-01
-3.15697342e-01 3.34737509e-01 5.69314361e-01 6.97992980e-01
-8.36206615e-01 2.64272839e-01 -5.66020191e-01 -4.67773378e-01
3.20917547e-01 4.64066684e-01 -8.21619093e-01 -2.49577656e-01
-9.79818702e-01 6.08377218e-01 2.22538039e-01 4.48093742e-01
-2.75805026e-01 -9.11825001e-01 -1.05380309e+00 -3.51752788e-01
4.44046408e-01 -1.09389853e+00 6.99592531e-01 -7.14900792e-01
-1.47569358e+00 9.68844116e-01 -3.37303787e-01 7.63289630e-02
7.95431435e-01 -4.31881011e-01 -5.31626582e-01 4.47535217e-02
1.01081744e-01 5.75896680e-01 9.09983933e-01 -1.52588773e+00
-7.46782303e-01 -8.35902989e-01 -1.68835685e-01 3.64266723e-01
-4.55712855e-01 -1.54032912e-02 -8.69354904e-01 -5.55016816e-01
1.29815817e-01 -1.14077532e+00 2.42771640e-01 2.52280504e-01
-4.96923327e-01 -5.56064367e-01 6.21981025e-01 -7.89074481e-01
7.31962204e-01 -2.28054643e+00 2.57560581e-01 3.47596496e-01
2.00439662e-01 1.04638301e-01 -2.54338235e-01 3.30091894e-01
-2.42282078e-01 -3.10508072e-01 2.04041302e-01 -8.06039989e-01
5.84322102e-02 -1.84668630e-01 -5.21441642e-03 1.00066924e+00
-2.01897532e-01 7.81418025e-01 -7.93229580e-01 -5.31637669e-01
4.69301969e-01 8.69577765e-01 -3.48743886e-01 1.68362617e-01
2.82912225e-01 1.04355943e+00 -4.45522606e-01 7.83844709e-01
9.89215195e-01 -2.05335915e-02 1.31066563e-02 -5.31922340e-01
-1.61762312e-01 1.82868466e-02 -1.22309923e+00 2.17814875e+00
-2.45464280e-01 5.42022921e-02 2.17316439e-03 -7.98514009e-01
8.26008856e-01 1.74317837e-01 6.68275893e-01 -1.01652050e+00
8.32222849e-02 -5.40507473e-02 -3.63256395e-01 -4.54844236e-01
3.67282271e-01 3.29764485e-02 -6.30511269e-02 1.12497069e-01
2.45143590e-03 7.21589088e-01 -2.56552279e-01 8.64679962e-02
6.07444227e-01 5.09964883e-01 -2.33349502e-02 -6.00829646e-02
7.27883518e-01 -4.19847727e-01 8.79855394e-01 7.44331181e-01
-2.69477636e-01 7.21734226e-01 -7.15231970e-02 -3.39939922e-01
-6.28319621e-01 -1.16127515e+00 -2.60397106e-01 1.40750325e+00
6.14315748e-01 -4.50701237e-01 -4.89390999e-01 -8.09721053e-01
3.72069120e-01 1.83678702e-01 -9.51505184e-01 -3.82835008e-02
-5.09231865e-01 -6.73788011e-01 3.04034591e-01 6.38867497e-01
5.61297536e-01 -4.94345725e-01 -8.41098130e-02 -9.93139744e-02
-1.96136728e-01 -1.21097481e+00 -6.57535911e-01 -3.09415042e-01
-5.26595354e-01 -1.07860124e+00 -9.49125350e-01 -5.87644994e-01
7.07119465e-01 7.93459415e-01 6.36629462e-01 4.19907719e-02
-4.36736733e-01 7.72862732e-01 -3.94815475e-01 -1.60851896e-01
4.15085047e-01 1.05629250e-01 2.59431720e-01 4.48391885e-01
4.67889696e-01 -4.87936109e-01 -9.37392831e-01 4.82868314e-01
-4.15027857e-01 -1.16499122e-02 5.06945610e-01 9.17464733e-01
6.62753344e-01 -4.44668382e-01 4.66079175e-01 -5.42623341e-01
2.77621839e-02 -3.86949837e-01 -4.30003732e-01 4.57809180e-01
-5.24183452e-01 2.72647068e-02 3.46463084e-01 -3.43220323e-01
-1.38987684e+00 2.69407779e-01 1.22641735e-02 -3.77627850e-01
-3.12331140e-01 1.80882335e-01 -5.91575325e-01 -2.73106992e-01
4.48161513e-01 3.34699392e-01 -8.51638615e-02 -7.52381802e-01
3.71366471e-01 6.02874577e-01 8.66111398e-01 -7.24036992e-01
1.14763367e+00 6.72129571e-01 1.98218375e-02 -7.56154478e-01
-6.88345671e-01 -9.70145822e-01 -8.46481025e-01 -1.60656676e-01
7.89548099e-01 -1.45933723e+00 -9.46169376e-01 7.58774281e-01
-8.48715961e-01 1.70734197e-01 -1.50205791e-01 5.16944826e-01
-1.64588302e-01 5.58860242e-01 -3.74340683e-01 -7.51039326e-01
-4.59873170e-01 -7.58651912e-01 1.39247644e+00 5.99192500e-01
9.55523849e-02 -6.09658599e-01 1.81348607e-01 7.69092143e-01
2.83189237e-01 3.51912528e-01 4.10113633e-01 -4.43046093e-01
-3.43643934e-01 -3.88872057e-01 -5.31180382e-01 -1.05857961e-01
2.52532035e-01 -5.57095349e-01 -1.39499474e+00 -5.87370157e-01
-5.34125984e-01 -3.30619931e-01 1.04041827e+00 1.98210869e-02
1.20532548e+00 1.04217999e-01 -5.76609373e-01 8.74967515e-01
1.20971072e+00 -2.78605908e-01 4.95400190e-01 3.51039171e-01
1.15331793e+00 7.78205335e-01 5.91866791e-01 5.25301814e-01
9.57335114e-01 1.14112449e+00 2.28773788e-01 -1.11589320e-01
-1.91550329e-01 -2.87671030e-01 1.56464264e-01 2.79632717e-01
-4.78558004e-01 1.22808777e-01 -5.91446996e-01 3.05260032e-01
-2.01713777e+00 -9.27029371e-01 -8.68775547e-02 2.46525836e+00
6.64128721e-01 -3.33644599e-01 4.45423514e-01 -4.72049117e-02
8.12904894e-01 1.77191496e-01 -5.95523715e-01 3.81305486e-01
-1.29756123e-01 -1.55837774e-01 4.68622655e-01 6.95921257e-02
-1.40612233e+00 6.75390482e-01 4.64928341e+00 5.89710355e-01
-1.06372356e+00 2.39256576e-01 1.59994960e-01 -3.04385304e-01
-8.87473375e-02 -2.43754417e-01 -9.90785003e-01 4.62997913e-01
4.69911397e-01 1.36290893e-01 3.66252065e-01 7.40928173e-01
5.28803207e-02 -2.81338654e-02 -1.22161078e+00 1.41772556e+00
3.25942189e-01 -6.86397791e-01 -3.78526181e-01 1.53903306e-01
6.23042941e-01 -8.20775628e-02 1.67384222e-01 3.51425439e-01
-1.62883863e-01 -7.43902445e-01 9.70547438e-01 6.15196109e-01
9.57809150e-01 -8.84239018e-01 7.30288744e-01 4.55177426e-02
-1.65887213e+00 -3.78254987e-02 -3.13837051e-01 2.09043786e-01
1.10854274e-02 3.63422394e-01 -1.61592335e-01 1.17899001e+00
8.31582308e-01 7.78239131e-01 -6.59261763e-01 1.23113441e+00
-1.28069490e-01 1.59888372e-01 -3.18250090e-01 5.37724495e-01
-3.22637796e-01 6.39523147e-03 4.03992623e-01 1.14141679e+00
-1.12412751e-01 1.43590152e-01 4.26540256e-01 6.94292784e-01
-7.03606531e-02 -3.43545489e-02 -2.39637882e-01 5.88511527e-01
3.92152131e-01 1.36323428e+00 -1.49502248e-01 5.27010970e-02
-6.52926087e-01 1.19710815e+00 3.97077054e-01 5.13648450e-01
-8.51550162e-01 -1.49051666e-01 9.42332029e-01 4.69593666e-02
2.95562088e-01 -1.34276211e-01 -1.78989857e-01 -1.38298547e+00
4.62744832e-01 -5.73056400e-01 6.22931123e-01 -2.43513450e-01
-1.78125000e+00 2.93528944e-01 2.85282303e-02 -1.41234612e+00
-8.13715234e-02 -3.12785327e-01 -4.21466798e-01 1.12415719e+00
-1.83673012e+00 -1.85814333e+00 -7.53802001e-01 1.01762819e+00
1.00100562e-01 -1.07687056e-01 7.12901533e-01 4.60109919e-01
-8.53329599e-01 1.32279468e+00 1.57670468e-01 3.29967111e-01
1.23668230e+00 -9.90607917e-01 1.07890129e-01 7.95580566e-01
-8.15793201e-02 7.35417426e-01 4.76269603e-01 -6.37921035e-01
-1.89769435e+00 -1.10330260e+00 6.83598161e-01 -5.25548160e-01
1.56121790e-01 -5.33335149e-01 -7.89362013e-01 5.65640450e-01
-1.45458400e-01 6.17561102e-01 8.90175760e-01 5.82123339e-01
-9.36909258e-01 -4.60707426e-01 -1.10583520e+00 1.86706573e-01
1.55798388e+00 -7.95130849e-01 -3.90982151e-01 1.44013584e-01
3.20149660e-01 -5.89455307e-01 -8.88229966e-01 3.75065267e-01
1.01075077e+00 -8.72020602e-01 1.28284252e+00 -3.84583056e-01
-1.49116278e-01 -4.28164274e-01 -3.64832878e-02 -1.00551236e+00
-5.02252698e-01 -3.47621411e-01 -3.68603840e-02 1.60905254e+00
-1.09534897e-01 -8.59500945e-01 5.60141385e-01 1.02206326e+00
4.47649956e-02 -4.71051425e-01 -1.13468492e+00 -8.92211795e-01
-1.97501004e-01 -2.27825850e-01 5.25411308e-01 9.00699735e-01
-1.06421560e-01 2.32332461e-02 -6.16374552e-01 4.37512338e-01
1.03812754e+00 1.80994526e-01 1.10048687e+00 -1.38870895e+00
-2.32464254e-01 -1.80211529e-01 -4.71303821e-01 -8.79842699e-01
2.80570835e-01 -7.55368292e-01 -2.63227355e-02 -1.23211133e+00
6.25645936e-01 -6.84679151e-01 -6.54505670e-01 6.69566512e-01
-5.55335999e-01 3.21617901e-01 4.48178858e-01 2.64517456e-01
-8.26930165e-01 7.80142426e-01 9.25121725e-01 -2.97068089e-01
-3.28688800e-01 -1.51215374e-01 -8.78540039e-01 4.54230100e-01
4.41654831e-01 -3.28117192e-01 -2.86480755e-01 -4.15428877e-01
-9.38431993e-02 -3.01131606e-01 8.21438074e-01 -9.44459319e-01
4.80744600e-01 -2.95288004e-02 8.92776549e-01 -5.69804311e-01
4.81024712e-01 -8.24612439e-01 1.58590600e-01 1.67031195e-02
-1.60562873e-01 -3.13361853e-01 1.20938860e-01 9.13010001e-01
4.72217891e-03 5.01389384e-01 5.60458422e-01 2.38796353e-01
-8.13990831e-01 5.04062772e-01 5.19442856e-01 -1.16326377e-01
9.45354342e-01 -1.99066222e-01 -4.26870346e-01 2.95652039e-02
-3.74814510e-01 3.50141495e-01 5.31695902e-01 8.74702990e-01
4.57617342e-01 -1.40125644e+00 -8.61119330e-01 3.07733119e-01
6.23727620e-01 -5.17300516e-03 7.95823693e-01 1.10326600e+00
2.75228173e-01 3.13831180e-01 -8.56310725e-02 -7.54147828e-01
-1.49863029e+00 5.64941704e-01 3.05048645e-01 -1.37834683e-01
-7.82745123e-01 9.25256729e-01 4.46471184e-01 -4.89954323e-01
4.34139013e-01 3.06787252e-01 -1.55900508e-01 7.49239549e-02
8.54266405e-01 3.88016909e-01 7.55187497e-02 -1.03646886e+00
-8.40778887e-01 1.00443935e+00 -3.19626480e-01 1.52487114e-01
1.28216171e+00 -4.36879426e-01 1.81624055e-01 3.66321988e-02
1.16734087e+00 1.92562845e-02 -1.37992585e+00 -6.17648482e-01
-3.44194621e-01 -7.36441553e-01 -1.34557158e-01 -9.19003844e-01
-1.15720713e+00 4.91220802e-01 1.02958918e+00 -4.77241963e-01
1.20190716e+00 1.00248829e-01 8.10712099e-01 1.20176256e-01
7.24721313e-01 -1.04834783e+00 -1.63783774e-01 1.09950595e-01
7.47519255e-01 -1.57938111e+00 1.60701036e-01 -5.95550120e-01
-5.19205511e-01 8.65503967e-01 6.96021318e-01 1.90958917e-01
4.90713477e-01 -2.18759820e-01 3.75620909e-02 4.14944701e-02
-2.34523997e-01 -3.77262473e-01 8.08872700e-01 7.41504371e-01
3.77595395e-01 3.42759043e-02 -1.97950915e-01 7.65128732e-01
9.69770849e-02 5.44593558e-02 -4.55257893e-01 9.67546225e-01
9.26183015e-02 -1.12395704e+00 -6.90305054e-01 8.23461264e-02
-1.75900027e-01 2.46511698e-01 -2.81200618e-01 7.59668708e-01
4.78019267e-01 1.00298035e+00 -1.93592206e-01 -7.29459226e-01
4.17738199e-01 1.22837757e-03 6.81423545e-01 -1.69119447e-01
-6.98702693e-01 -2.81039234e-02 -3.85625698e-02 -7.79105067e-01
-5.65541625e-01 -9.16108608e-01 -9.59399343e-01 -4.66770768e-01
-2.56545305e-01 -1.35153428e-01 6.37696087e-01 1.02100241e+00
6.54516935e-01 2.62467414e-01 6.99691296e-01 -1.09899318e+00
-6.18217051e-01 -8.28716397e-01 -5.15657306e-01 7.98860908e-01
3.93632323e-01 -9.17150259e-01 -1.44121259e-01 -7.47605711e-02] | [14.679570198059082, 0.9183653593063354] |
75ed5f73-c223-4cc2-a254-cfb1f5254b06 | natural-language-inference-prompts-for-zero | 2209.06701 | null | https://arxiv.org/abs/2209.06701v2 | https://arxiv.org/pdf/2209.06701v2.pdf | Natural Language Inference Prompts for Zero-shot Emotion Classification in Text across Corpora | Within textual emotion classification, the set of relevant labels depends on the domain and application scenario and might not be known at the time of model development. This conflicts with the classical paradigm of supervised learning in which the labels need to be predefined. A solution to obtain a model with a flexible set of labels is to use the paradigm of zero-shot learning as a natural language inference task, which in addition adds the advantage of not needing any labeled training data. This raises the question how to prompt a natural language inference model for zero-shot learning emotion classification. Options for prompt formulations include the emotion name anger alone or the statement "This text expresses anger". With this paper, we analyze how sensitive a natural language inference-based zero-shot-learning classifier is to such changes to the prompt under consideration of the corpus: How carefully does the prompt need to be selected? We perform experiments on an established set of emotion datasets presenting different language registers according to different sources (tweets, events, blogs) with three natural language inference models and show that indeed the choice of a particular prompt formulation needs to fit to the corpus. We show that this challenge can be tackled with combinations of multiple prompts. Such ensemble is more robust across corpora than individual prompts and shows nearly the same performance as the individual best prompt for a particular corpus. | ['Roman Klinger', 'María-Teresa Martín-Valdivia', 'Flor Miriam Plaza-del-Arco'] | 2022-09-14 | null | https://aclanthology.org/2022.coling-1.592 | https://aclanthology.org/2022.coling-1.592.pdf | coling-2022-10 | ['emotion-classification', 'emotion-classification'] | ['computer-vision', 'natural-language-processing'] | [ 3.19516659e-01 6.91508204e-02 -7.68662915e-02 -8.06061804e-01
-4.66565847e-01 -6.20094657e-01 1.03148377e+00 7.38532543e-01
-7.79249012e-01 6.32599235e-01 1.77280173e-01 -1.52377337e-01
-4.19106632e-01 -6.56479418e-01 -5.85588887e-02 -6.20087862e-01
2.94631183e-01 6.87130392e-01 2.78488666e-01 -6.39661193e-01
2.20487714e-01 4.16355252e-01 -1.85922658e+00 4.22419041e-01
4.61238205e-01 9.47766244e-01 2.73290742e-02 6.58180296e-01
-6.36995137e-01 9.97453332e-01 -7.70644069e-01 -3.55408013e-01
-8.32804143e-02 -4.83324289e-01 -1.00837445e+00 1.52549222e-01
-8.20372179e-02 1.07227325e-01 5.60560763e-01 8.80577743e-01
5.48995197e-01 3.33567828e-01 8.73841941e-01 -1.10808265e+00
9.75108966e-02 6.94104493e-01 6.01166002e-02 2.50565529e-01
5.79769552e-01 -4.80109677e-02 9.33993459e-01 -7.09784269e-01
8.26042533e-01 9.73942637e-01 4.31116879e-01 5.74958801e-01
-1.09635270e+00 -2.35767528e-01 7.11754188e-02 3.42469901e-01
-1.17433143e+00 -3.93059075e-01 9.41187382e-01 -5.86236238e-01
8.30958009e-01 2.19441444e-01 2.98418581e-01 1.35759568e+00
-9.84403938e-02 1.71963468e-01 1.32571232e+00 -8.89355063e-01
7.73434639e-01 7.72809029e-01 5.76867878e-01 1.98167875e-01
-3.17441553e-01 -2.08324164e-01 -4.44284528e-01 -3.60259771e-01
-1.58254877e-01 -3.19910705e-01 -4.00744118e-02 -7.29060099e-02
-7.26538181e-01 1.11973190e+00 -1.85215622e-01 9.16787207e-01
-3.91375095e-01 -4.19332236e-01 8.35353374e-01 4.75510269e-01
5.58673918e-01 6.48565829e-01 -6.66756451e-01 -4.16503966e-01
-7.69262016e-01 1.81266382e-01 1.10651970e+00 4.67675418e-01
8.27630818e-01 -1.59831852e-01 -2.31494129e-01 1.00278163e+00
-8.62976909e-02 -1.31537139e-01 6.16258204e-01 -4.76017594e-01
-1.33077666e-01 5.65658331e-01 2.10121885e-01 -9.33657825e-01
-7.04939246e-01 -2.13990897e-01 -4.63371813e-01 2.49648333e-01
6.03343666e-01 -5.13015211e-01 -3.92968625e-01 1.74074054e+00
5.38073659e-01 -2.59176781e-03 3.33784550e-01 7.32258976e-01
8.41012716e-01 6.17292225e-01 2.27970257e-01 -6.26258016e-01
1.63978875e+00 -3.41427028e-01 -9.56364036e-01 -1.61087826e-01
1.00550222e+00 -7.19078362e-01 1.16264343e+00 5.41920483e-01
-3.89691323e-01 -3.21691304e-01 -9.00274336e-01 1.84200659e-01
-8.60731959e-01 -2.76939660e-01 3.40652168e-01 5.58270872e-01
-5.51848233e-01 5.43324888e-01 -8.17770660e-02 -6.70880854e-01
-3.49436939e-01 2.28640273e-01 -1.91236332e-01 2.67683983e-01
-1.62491155e+00 1.19419384e+00 5.93078256e-01 -9.61531028e-02
-1.86644688e-01 -4.16472614e-01 -6.78566217e-01 1.23979449e-01
7.28196263e-01 -3.06593716e-01 1.33246458e+00 -1.48704624e+00
-1.71306396e+00 1.00449252e+00 -4.94637005e-02 -3.69274735e-01
4.65157956e-01 8.12504590e-02 -5.95923185e-01 6.55242428e-02
-7.46606616e-03 3.41958076e-01 9.29484069e-01 -1.09247005e+00
-5.06639123e-01 -1.65400103e-01 1.84087649e-01 -1.50995165e-01
-3.56002957e-01 5.82424939e-01 2.15314820e-01 -2.24063173e-01
-5.50133228e-01 -7.83072233e-01 -2.84870028e-01 -4.71478552e-01
-1.48997262e-01 -6.04839921e-01 7.76767552e-01 -3.40004005e-02
1.23306060e+00 -2.18131399e+00 2.11229604e-02 1.15616649e-01
-2.42374808e-01 2.22663265e-02 2.17229560e-01 6.44199193e-01
-3.69458050e-01 4.77834046e-02 -2.07891762e-01 -1.88811466e-01
3.34556133e-01 3.76800090e-01 -4.24252093e-01 2.67548114e-01
1.41906455e-01 4.70057756e-01 -8.73527884e-01 -7.38435566e-01
2.94183314e-01 4.71684456e-01 -4.08712059e-01 3.29697251e-01
-3.60347688e-01 2.85403669e-01 -4.26292449e-01 5.85978478e-02
2.48287451e-02 -1.30038649e-01 1.18441172e-01 -1.04526632e-01
-2.47797683e-01 6.02247939e-02 -1.31983602e+00 1.26716971e+00
-5.51308870e-01 3.69517177e-01 -2.18563825e-01 -1.05546820e+00
1.26831031e+00 7.05379784e-01 5.28764367e-01 -4.35945481e-01
5.32636344e-01 1.41370535e-01 2.10805517e-02 -7.97320068e-01
2.34032497e-01 -7.11905777e-01 -5.07247925e-01 5.80458641e-01
4.68670607e-01 -9.75984633e-02 3.42206836e-01 4.32966724e-02
9.58159745e-01 -6.54401854e-02 6.92800164e-01 -4.35340971e-01
6.38540268e-01 -1.55625697e-02 4.44466412e-01 6.55754685e-01
-1.26781061e-01 2.35389993e-01 8.36548626e-01 -6.21239066e-01
-6.52295291e-01 -3.24075252e-01 -3.75767380e-01 1.55392182e+00
-2.53088415e-01 -4.77564931e-01 -7.31217980e-01 -6.09249055e-01
-5.71202636e-01 1.11274552e+00 -8.61754775e-01 -2.26570182e-02
-1.79373637e-01 -6.65369034e-01 3.04716349e-01 -2.92442799e-01
-1.58156097e-01 -1.36548984e+00 -1.21533203e+00 3.26986372e-01
-1.91228926e-01 -1.01897275e+00 1.71744332e-01 9.33374822e-01
-2.73902684e-01 -9.05941486e-01 -1.89297676e-01 -3.33074421e-01
3.99261713e-01 -5.70502877e-01 1.09806168e+00 -2.04458207e-01
-4.98763062e-02 5.90361297e-01 -9.33514476e-01 -6.41823769e-01
-6.44430280e-01 1.29857302e-01 -5.88550419e-02 4.96702045e-01
5.67961037e-01 -4.15989667e-01 -3.56899947e-02 -1.17834702e-01
-1.20298111e+00 -2.38835365e-01 -3.54033634e-02 6.32584929e-01
8.10543001e-02 1.42743856e-01 7.72424400e-01 -1.20353293e+00
1.03224730e+00 -5.77303529e-01 -2.38564193e-01 3.53629082e-01
-4.00362104e-01 2.41010100e-01 8.23598742e-01 -6.35580719e-01
-1.04795074e+00 2.48573214e-01 -3.46838415e-01 -1.94983274e-01
-7.32181549e-01 5.74799180e-01 -9.35949385e-02 1.13235950e-01
8.88778150e-01 -2.35823631e-01 -1.97503284e-01 -3.02619845e-01
3.33190411e-01 6.73496962e-01 9.29017365e-02 -7.48085976e-01
2.88238823e-01 7.23474547e-02 -2.01569647e-01 -9.82845008e-01
-8.79908383e-01 -5.44895530e-01 -7.86694586e-01 -5.57485402e-01
8.21824908e-01 -2.76652575e-01 -6.59310699e-01 6.26322404e-02
-1.28895485e+00 -3.30880165e-01 -4.60559428e-01 2.21838132e-01
-6.14669502e-01 9.77177620e-02 -3.00660878e-01 -1.06954074e+00
-2.13443384e-01 -9.94785488e-01 8.36546838e-01 3.15963663e-02
-8.87856662e-01 -1.14890218e+00 1.76967949e-01 -1.62650511e-01
4.10718739e-01 4.12205607e-01 1.17775071e+00 -1.28577054e+00
4.49863642e-01 -3.30950826e-01 3.69904697e-01 9.88410115e-02
2.27758825e-01 2.32038766e-01 -1.11294723e+00 1.62927419e-01
5.41823268e-01 -5.29253542e-01 4.56828535e-01 -1.69841535e-02
7.10853457e-01 -4.20563042e-01 1.10999778e-01 -1.48290419e-03
1.54271138e+00 1.64405450e-01 3.45427275e-01 3.32082003e-01
2.29551449e-01 1.19046497e+00 7.59480059e-01 7.90309310e-01
1.31078020e-01 9.01399493e-01 2.20714182e-01 1.47189364e-01
6.12775922e-01 2.56831169e-01 2.12615520e-01 4.44276601e-01
2.12054476e-01 -8.43508691e-02 -9.61190164e-01 2.46413678e-01
-1.85654104e+00 -1.17176402e+00 -4.23041396e-02 2.04406381e+00
9.56717312e-01 2.68002540e-01 2.65948147e-01 4.00123626e-01
3.42142403e-01 3.78054172e-01 -6.75114095e-02 -1.10737514e+00
-2.38186698e-02 1.84065163e-01 -8.73439908e-02 7.60880768e-01
-9.76652324e-01 7.50308692e-01 5.36099148e+00 7.08939135e-01
-1.47552228e+00 2.76734918e-01 4.28084999e-01 -6.63958713e-02
-2.38118172e-01 1.03560261e-01 -7.77456582e-01 5.19581735e-01
1.29655349e+00 -3.03993970e-01 2.01402634e-01 7.11743355e-01
3.47606391e-01 -2.97774434e-01 -1.26384771e+00 7.61894941e-01
1.61238492e-01 -9.87931371e-01 -2.85323799e-01 -2.16990590e-01
1.19868256e-01 -2.38112271e-01 -5.19901395e-01 5.15332103e-01
1.03243150e-01 -9.02259827e-01 6.25258744e-01 7.16424882e-01
3.68961185e-01 -7.07986832e-01 7.06907570e-01 8.18889081e-01
-7.07659423e-01 -1.74774483e-01 -1.07246473e-01 -3.62135530e-01
3.39146554e-01 4.99037266e-01 -6.95630014e-01 3.13265502e-01
5.35511315e-01 1.96150124e-01 -5.25756061e-01 4.55722064e-01
-7.01170787e-02 5.26178777e-01 -4.11283433e-01 -4.89490956e-01
3.17184061e-01 1.02803938e-01 4.65815276e-01 1.60501909e+00
1.40948802e-01 3.38598967e-01 2.36647055e-01 5.12553573e-01
4.41943139e-01 6.80541396e-01 -7.36060500e-01 1.17067300e-01
2.66416758e-01 1.43987477e+00 -8.35714698e-01 -4.08858061e-01
-3.23529392e-01 6.55601859e-01 4.27614093e-01 3.49615157e-01
-5.98317266e-01 -2.46442601e-01 2.56495208e-01 1.97192103e-01
1.27241194e-01 2.00296476e-01 4.64827232e-02 -8.71258140e-01
-3.61318886e-01 -8.87027204e-01 5.33936739e-01 -7.37925708e-01
-1.42254817e+00 7.85360813e-01 3.07140023e-01 -1.13868272e+00
-5.93702614e-01 -5.78592718e-01 -7.62262285e-01 5.27828395e-01
-1.20483220e+00 -6.49022520e-01 -2.33326685e-02 6.31472886e-01
4.99701172e-01 6.89777136e-02 1.30588984e+00 3.47555965e-01
-2.76617110e-01 1.18856318e-01 -5.07426798e-01 -1.42021671e-01
1.02190995e+00 -1.23616564e+00 -6.14547372e-01 5.07426739e-01
2.20292658e-01 3.31108034e-01 1.37133086e+00 -2.20002785e-01
-9.79979992e-01 -6.80429459e-01 1.45251262e+00 -2.60423362e-01
9.57842648e-01 -3.65134865e-01 -1.20754611e+00 3.49138439e-01
5.35141826e-01 1.11075535e-01 1.02640486e+00 4.19449240e-01
-2.32938141e-01 -5.00613898e-02 -1.00925660e+00 3.46296608e-01
3.10851485e-01 -5.56712329e-01 -8.07702303e-01 3.91370595e-01
6.80547535e-01 -3.58403567e-03 -8.40308964e-01 4.08352494e-01
2.47359782e-01 -9.87730801e-01 3.47048104e-01 -8.41288626e-01
3.12920392e-01 -6.85392916e-02 -1.84438348e-01 -1.29844928e+00
-4.86810878e-02 -3.72621268e-01 2.14873642e-01 1.58211970e+00
3.60739440e-01 -4.50917393e-01 1.52853504e-01 9.23526585e-01
3.20693403e-01 -7.97447979e-01 -1.07222295e+00 -2.94894993e-01
-2.66866237e-02 -6.59830093e-01 3.93087626e-01 1.35830772e+00
5.25762737e-01 8.31705749e-01 -4.55747902e-01 -1.59772798e-01
8.35175216e-02 9.21696201e-02 7.31374204e-01 -1.56905448e+00
-2.93124795e-01 -5.13271868e-01 -2.65929312e-01 -1.45545557e-01
4.49015111e-01 -6.99278831e-01 1.47833019e-01 -1.20463574e+00
-1.47481784e-01 -3.26580316e-01 -1.76652730e-01 4.93871629e-01
-1.07285753e-02 -2.35350549e-01 1.58501595e-01 -2.04291880e-01
-6.12174928e-01 3.92092615e-01 5.07841468e-01 1.26645584e-02
-3.08601469e-01 -6.85920864e-02 -5.24349272e-01 8.41976762e-01
7.29206145e-01 -6.29313290e-01 -3.34231019e-01 2.47473478e-01
6.60688818e-01 1.26944676e-01 1.79907992e-01 -6.61062479e-01
3.74722064e-01 -2.71528482e-01 -8.29253048e-02 7.67843425e-03
3.29444855e-01 -1.10260248e+00 1.78347230e-01 1.12633534e-01
-7.26858735e-01 -1.09203674e-01 8.50852653e-02 2.58235902e-01
-2.14694649e-01 -8.52099955e-01 8.64182115e-01 -2.40255311e-01
-9.75966692e-01 -4.31910120e-02 -7.30236411e-01 1.18676215e-01
1.07928967e+00 -1.25169396e-01 -3.12819257e-02 -3.34922701e-01
-1.04150510e+00 -3.74281928e-02 3.03377599e-01 5.55158436e-01
1.74868554e-01 -9.52330887e-01 -6.68994308e-01 -1.18580028e-01
4.42215085e-01 -4.28013712e-01 1.23215981e-01 7.90451467e-01
1.99995294e-01 1.04091831e-01 -6.79320619e-02 -4.14113134e-01
-1.21906018e+00 7.69262254e-01 4.73513752e-01 -3.21109325e-01
-4.71992671e-01 4.80986863e-01 -2.20196649e-01 -4.24038738e-01
1.84703603e-01 -4.57323194e-02 -6.98286891e-01 7.84893334e-01
5.25241077e-01 -1.90528497e-01 1.33291334e-01 -9.15659487e-01
-2.88713485e-01 3.67447406e-01 1.62283152e-01 -2.03035578e-01
1.25380099e+00 -7.68464357e-02 -8.71483907e-02 1.35303473e+00
1.07329118e+00 -3.31844352e-02 -7.26506114e-01 -3.24220717e-01
4.79002029e-01 -1.22383004e-02 -1.23998366e-01 -7.35262811e-01
-5.02370119e-01 7.51229525e-01 3.90079021e-01 6.49158120e-01
1.01907885e+00 8.44566077e-02 8.22637081e-02 2.87597150e-01
4.53993976e-01 -1.32806218e+00 1.75448805e-02 7.07161129e-01
8.67785156e-01 -1.29821897e+00 -1.82688177e-01 -1.33676097e-01
-7.71963537e-01 1.36018980e+00 3.89308333e-01 1.07932184e-03
9.07276273e-01 4.45586056e-01 4.14515793e-01 -4.61821467e-01
-1.01817286e+00 -3.61213535e-01 6.95428401e-02 2.23597944e-01
5.03508389e-01 7.32403472e-02 -7.73396194e-01 7.67090619e-01
-2.63048083e-01 7.72467256e-02 4.98253912e-01 7.26566792e-01
-6.03530884e-01 -1.22515953e+00 -3.65791351e-01 3.49786401e-01
-4.50157464e-01 5.67820594e-02 -7.00968087e-01 5.02116621e-01
3.88277143e-01 1.16585290e+00 -1.04942150e-01 -1.11967638e-01
2.61159003e-01 7.61110008e-01 1.45662457e-01 -9.02677059e-01
-9.44204450e-01 -1.14018418e-01 3.78949225e-01 -2.56727040e-01
-7.05788732e-01 -6.40693724e-01 -1.23034370e+00 5.32237552e-02
-2.77102798e-01 4.96521056e-01 5.89046717e-01 1.56637287e+00
-3.18875089e-02 4.12570149e-01 5.03987789e-01 -7.39126503e-01
-4.04540211e-01 -9.15934384e-01 -5.18829823e-01 6.15085065e-01
2.05604941e-01 -7.35977292e-01 -5.40594637e-01 1.17341951e-01] | [12.760376930236816, 6.327703475952148] |
55558c20-ade3-4a51-843f-26d5f9b2c0f0 | finger-vein-recognition-by-generating-code | 2101.08415 | null | https://arxiv.org/abs/2101.08415v1 | https://arxiv.org/pdf/2101.08415v1.pdf | Finger Vein Recognition by Generating Code | Finger vein recognition has drawn increasing attention as one of the most popular and promising biometrics due to its high distinguishes ability, security and non-invasive procedure. The main idea of traditional schemes is to directly extract features from finger vein images or patterns and then compare features to find the best match. However, the features extracted from images contain much redundant data, while the features extracted from patterns are greatly influenced by image segmentation methods. To tack these problems, this paper proposes a new finger vein recognition by generating code. The proposed method does not require an image segmentation algorithm, is simple to calculate and has a small amount of data. Firstly, the finger vein images were divided into blocks to calculate the mean value. Then the centrosymmetric coding is performed by using the generated eigenmatrix. The obtained codewords are concatenated as the feature codewords of the image. The similarity between vein codes is measured by the ratio of minimum Hamming distance to codeword length. Extensive experiments on two public finger vein databases verify the effectiveness of the proposed method. The results indicate that our method outperforms the state-of-theart methods and has competitive potential in performing the matching task. | ['Mingwen Wang', 'Zhongxia Zhang'] | 2021-01-21 | null | null | null | null | ['finger-vein-recognition'] | ['computer-vision'] | [ 4.68189329e-01 -5.96671581e-01 -6.01249114e-02 -3.70204419e-01
-2.21182406e-01 -5.94255865e-01 4.11480039e-01 4.33984660e-02
-4.86252218e-01 3.96212637e-01 -2.11498171e-01 7.87420496e-02
-2.46642753e-01 -8.27557862e-01 6.37945011e-02 -9.61699963e-01
2.96516299e-01 1.99807331e-01 3.23045701e-01 1.89986780e-01
8.19965422e-01 8.64911020e-01 -1.33737338e+00 -2.15497121e-01
9.57374096e-01 1.15773177e+00 -3.28932852e-02 3.50625604e-01
-3.59511286e-01 -4.42550071e-02 -2.69966990e-01 -6.22254968e-01
5.92123389e-01 -6.15930974e-01 -3.12893152e-01 3.19638520e-01
1.26115158e-01 -2.27858812e-01 -5.13612568e-01 1.06181884e+00
7.60775387e-01 -2.12394774e-01 7.58210838e-01 -7.72390604e-01
-3.13204199e-01 -4.98001985e-02 -8.22258592e-01 6.03916543e-03
2.04197451e-01 6.94492981e-02 4.42981094e-01 -6.39503479e-01
5.12613297e-01 1.00432539e+00 4.07096177e-01 4.56266195e-01
-1.15181112e+00 -8.45477402e-01 -6.22485399e-01 3.02756280e-01
-1.43599927e+00 -2.97797561e-01 8.31153154e-01 -3.84566605e-01
3.37817818e-01 4.01450306e-01 8.57477844e-01 4.63930994e-01
2.56260723e-01 4.05466318e-01 1.42795861e+00 -4.45751250e-01
-1.18790671e-01 1.41212463e-01 3.07690293e-01 7.20856547e-01
5.68616629e-01 2.61586886e-02 -9.72567275e-02 -2.27625877e-01
9.33499396e-01 5.22466898e-01 -2.47191787e-01 -1.69486701e-01
-1.10158002e+00 5.52048743e-01 4.06048983e-01 5.07781863e-01
-3.65173608e-01 -2.56656498e-01 1.05502173e-01 -7.64098316e-02
-3.97678584e-01 9.95420069e-02 2.66839892e-01 -2.86975652e-01
-9.76997554e-01 1.19906567e-01 7.36501098e-01 6.29452109e-01
6.12594664e-01 -5.79216599e-01 -1.77761525e-01 7.99555182e-01
3.65084320e-01 6.62548780e-01 3.45614344e-01 -5.36166906e-01
2.91500986e-01 8.26202154e-01 -1.30695969e-01 -1.40796483e+00
-1.63346604e-01 -1.61974058e-01 -9.62578595e-01 1.29092112e-02
7.94259667e-01 5.77786863e-02 -8.47465396e-01 9.03266191e-01
-8.68940577e-02 9.67200398e-02 -2.07451001e-01 8.61312985e-01
6.21126533e-01 3.43231261e-01 -2.97208905e-01 -1.93305612e-01
1.45015156e+00 -5.65417111e-01 -5.58725417e-01 2.13489935e-01
-1.40583381e-01 -1.14357233e+00 3.99194628e-01 3.22118431e-01
-7.32825398e-01 -6.49715960e-01 -9.00349081e-01 3.45022529e-01
-1.45829823e-02 4.05292094e-01 5.08517504e-01 9.17736471e-01
-3.77956450e-01 3.78993064e-01 -7.34873235e-01 -4.27167416e-01
3.97330821e-01 5.26335239e-01 -2.88831353e-01 -7.14393631e-02
-5.96391559e-01 4.26558226e-01 3.98887366e-01 3.27403516e-01
2.13783115e-01 -1.01056537e-02 -4.34293568e-01 -9.60967131e-03
3.03188600e-02 -1.61572266e-02 5.37285864e-01 -5.52017033e-01
-1.29513264e+00 6.54050410e-01 -4.86100972e-01 1.17946826e-01
4.63893324e-01 3.86371791e-01 -3.04356247e-01 4.23470736e-01
-6.98613226e-02 1.99283838e-01 7.46380329e-01 -7.96891332e-01
-5.42184114e-01 -6.18134320e-01 -5.43889165e-01 -7.68521056e-02
-3.43944639e-01 -7.32814893e-02 -7.32512772e-01 -4.17138666e-01
7.07849503e-01 -9.35630322e-01 -1.70427799e-01 -2.76114270e-02
-3.92434090e-01 -1.62045687e-01 6.35584176e-01 -7.47292697e-01
1.23166525e+00 -2.27340388e+00 -1.63154021e-01 1.16380811e+00
1.89403474e-01 3.18025470e-01 2.33612508e-02 5.28923869e-01
1.81609333e-01 -1.51061252e-01 -2.45416239e-01 5.01198828e-01
-3.64360034e-01 -1.26103133e-01 1.07443951e-01 3.97880077e-01
5.19637242e-02 5.85335374e-01 -5.44293761e-01 -8.24775159e-01
3.10243696e-01 4.30285841e-01 -2.47427002e-01 1.73805967e-01
4.49014336e-01 5.21826267e-01 -6.69535637e-01 6.82577729e-01
1.03304791e+00 -7.88234100e-02 2.62989134e-01 -5.34680128e-01
-1.40097275e-01 -2.90758580e-01 -1.45875001e+00 1.04356050e+00
2.42423818e-01 3.43398988e-01 -4.40871596e-01 -8.49199355e-01
1.49178886e+00 3.56211327e-02 6.88089550e-01 -6.96657360e-01
3.37230504e-01 5.13091803e-01 3.35398585e-01 -7.02644944e-01
-3.62939723e-02 9.46309492e-02 2.54847705e-01 4.07580495e-01
-3.06285471e-01 4.13673706e-02 4.62570429e-01 -1.12173453e-01
7.60976732e-01 -1.75704360e-01 3.00566912e-01 5.38671911e-02
9.08863544e-01 -2.25958228e-01 4.36489165e-01 5.09245157e-01
-1.12208076e-01 4.90569413e-01 4.33891714e-01 -3.93179148e-01
-9.61326540e-01 -9.14299488e-01 -6.30059302e-01 -2.00296357e-01
6.52742207e-01 -2.19263971e-01 -7.89184213e-01 -6.14187777e-01
1.86774582e-01 -1.85767263e-01 -2.23619521e-01 1.89174518e-01
-5.76685011e-01 -5.60845554e-01 5.08052111e-01 2.68883407e-01
1.11879838e+00 -9.07852769e-01 -6.93819940e-01 1.83792278e-01
-1.20427832e-02 -8.21205318e-01 -4.81769145e-01 -5.86488783e-01
-8.97663474e-01 -1.39658523e+00 -1.04665482e+00 -1.05345070e+00
9.84697163e-01 2.92188615e-01 7.55567774e-02 2.77088821e-01
-8.38180661e-01 -1.55341076e-02 -2.24215701e-01 1.18678352e-02
1.13209672e-01 2.14660000e-02 -2.50379980e-01 4.51635271e-01
8.45474720e-01 -3.27123433e-01 -9.41999137e-01 3.56236845e-01
-6.60184503e-01 -2.17714101e-01 1.07279646e+00 9.03892756e-01
6.22744560e-01 2.00945452e-01 1.02952391e-01 -5.93721986e-01
8.23244035e-01 1.11177377e-01 -5.86168766e-01 4.16764557e-01
-6.24325693e-01 2.28768095e-01 4.99594122e-01 -1.74966723e-01
-8.46540153e-01 3.02171320e-01 1.03091337e-01 3.30156446e-01
-1.27596721e-01 3.02727282e-01 -2.15278473e-02 -5.56959331e-01
3.20968300e-01 6.76679969e-01 4.15024459e-01 -3.73246193e-01
-8.31310824e-02 1.15106487e+00 4.91923332e-01 -3.92203093e-01
8.46557081e-01 3.69796783e-01 3.73737246e-01 -1.03229296e+00
1.00498997e-01 -5.84106803e-01 -6.67732954e-01 -2.78186709e-01
7.35982895e-01 3.23686823e-02 -1.15842998e+00 7.37909496e-01
-9.78753865e-01 7.65514433e-01 3.94132137e-01 6.26649141e-01
-1.37786746e-01 1.10402906e+00 -5.56231439e-01 -1.02873898e+00
-5.74037492e-01 -1.26774764e+00 4.61630255e-01 8.44352245e-01
8.19508359e-02 -4.48755413e-01 -1.62282646e-01 2.26451248e-01
4.47924286e-01 2.99878240e-01 1.00742471e+00 -4.58841264e-01
-6.37794435e-01 -7.72404373e-01 -7.10807681e-01 4.05027568e-02
5.70092499e-01 8.43621269e-02 -5.28520644e-01 -1.72200084e-01
-1.18135303e-01 1.54050380e-01 7.31181324e-01 1.22277901e-01
1.29293621e+00 -7.81177059e-02 -4.69710052e-01 5.14353335e-01
1.54581726e+00 6.87835217e-01 8.91720057e-01 2.98106641e-01
4.08737540e-01 5.88358223e-01 5.43178380e-01 5.46670854e-01
-2.19505206e-02 5.85174561e-01 -2.04352662e-02 -1.65603533e-01
1.08215131e-01 9.04741511e-02 -2.53919661e-01 7.53418803e-01
-5.00018716e-01 2.39858076e-01 -7.02507854e-01 1.36425108e-01
-1.65463495e+00 -1.08841848e+00 -3.83443028e-01 2.38997960e+00
7.70200551e-01 -4.52258512e-02 1.82381406e-01 3.61481100e-01
8.92375886e-01 -1.46208793e-01 -4.94816452e-01 -1.46897003e-01
1.66229419e-02 7.85987735e-01 5.81315279e-01 2.14550942e-01
-8.92066240e-01 5.66051722e-01 5.17783737e+00 6.43578410e-01
-1.21092033e+00 -5.27303934e-01 4.09394830e-01 3.13566864e-01
7.77585655e-02 6.39782697e-02 -6.86084270e-01 7.81410933e-01
1.64042860e-01 -1.50428545e-02 5.05408883e-01 3.54433149e-01
8.91085993e-03 -2.63438404e-01 -7.00721025e-01 1.50296295e+00
4.36406508e-02 -1.06954730e+00 9.01244432e-02 3.05791587e-01
3.10299873e-01 -7.05592155e-01 7.77651649e-03 -5.10337770e-01
-6.57555163e-01 -9.91079450e-01 6.53558224e-02 1.07021606e+00
7.83338845e-01 -7.23033726e-01 9.90782559e-01 -6.84323534e-02
-1.35953712e+00 1.12281181e-01 -5.92333496e-01 2.50333548e-01
-1.04357049e-01 3.92925352e-01 -5.44180751e-01 3.93891633e-01
2.98395842e-01 5.20227909e-01 -7.66121268e-01 1.65050924e+00
1.53689340e-01 3.48023564e-01 -3.96070898e-01 -5.90756476e-01
-1.06736575e-03 -8.00140619e-01 2.03715146e-01 1.13643086e+00
4.64351416e-01 1.15714066e-01 1.64332222e-02 7.38840282e-01
1.81658909e-01 6.33906484e-01 -3.05608541e-01 -3.78849983e-01
6.94785476e-01 1.15328670e+00 -9.64024544e-01 -1.88420758e-01
-5.17888427e-01 1.13783884e+00 -3.06343883e-01 2.40750328e-01
-3.56522262e-01 -1.18850994e+00 4.56521958e-02 5.05905077e-02
2.88622767e-01 -2.03931287e-01 -4.97824103e-01 -9.99946117e-01
3.42569172e-01 -7.74897277e-01 1.97040975e-01 -6.92568347e-03
-1.23716354e+00 4.92679775e-01 -3.91628087e-01 -1.36981666e+00
-1.12175934e-01 -7.28494585e-01 -4.79305983e-01 1.18785405e+00
-1.21659493e+00 -8.23724270e-01 -8.85964036e-01 6.64745629e-01
1.07562348e-01 -4.75298733e-01 8.52183878e-01 1.63910300e-01
-4.55472469e-01 7.47511387e-01 3.35115463e-01 6.28199697e-01
7.54351854e-01 -8.44253123e-01 9.30456072e-02 7.44213879e-01
-1.90665320e-01 9.77474034e-01 2.12682247e-01 -7.27724373e-01
-1.38069463e+00 -2.58232296e-01 8.88428748e-01 2.68652678e-01
9.36716944e-02 4.85361591e-02 -5.16016841e-01 -6.64480627e-02
-4.88354899e-02 -1.55195624e-01 8.68561804e-01 -4.83253956e-01
-2.38374099e-01 -4.62930322e-01 -1.42849731e+00 5.34328341e-01
7.20591128e-01 -2.02095866e-01 -3.96118701e-01 -5.74601777e-02
-4.25290257e-01 -1.23281479e-01 -9.46193814e-01 2.65198141e-01
1.27048051e+00 -1.04499733e+00 7.12289155e-01 -1.12830192e-01
2.40486279e-01 -4.12606150e-01 9.34096798e-02 -6.01062536e-01
-4.00709927e-01 -3.11541796e-01 3.96287262e-01 1.15875685e+00
1.67049542e-01 -9.63756800e-01 1.11371720e+00 6.68249488e-01
6.18920803e-01 -7.25416660e-01 -5.95285416e-01 -5.92298985e-01
-5.15852153e-01 3.15431029e-01 6.04672134e-01 5.34317255e-01
1.54579654e-01 -7.03732222e-02 -2.23742440e-01 -1.63157627e-01
1.17285812e+00 5.36355436e-01 7.55598366e-01 -1.50260365e+00
-2.97243744e-01 -4.06843692e-01 -1.00820196e+00 -9.91557300e-01
-4.58004355e-01 -8.15435767e-01 -2.80168504e-01 -1.42275798e+00
4.20596391e-01 -6.68982625e-01 -2.01832697e-01 3.02507937e-01
-1.43823475e-01 4.86084610e-01 2.06616744e-01 5.02171338e-01
8.76305625e-02 -3.51048224e-02 1.31995761e+00 -1.02225259e-01
-3.62872303e-01 1.87876791e-01 -5.46024919e-01 2.37437308e-01
9.38954234e-01 -8.70497301e-02 -9.56608076e-03 2.01707296e-02
-3.36167514e-01 4.94502857e-02 -3.23547870e-02 -1.06039464e+00
3.80553097e-01 -1.38460815e-01 7.61072040e-01 -5.46631038e-01
6.35389686e-02 -9.83014166e-01 5.32017127e-02 9.53334630e-01
1.32971872e-02 -1.47256806e-01 -1.27795607e-01 2.83163518e-01
-1.84321031e-01 -6.25126362e-01 7.34599531e-01 -1.13210315e-02
-6.07600749e-01 4.14554894e-01 -1.36323720e-01 -4.43811297e-01
1.06164885e+00 -8.90903771e-01 -1.25618517e-01 -1.39744729e-01
-3.39342922e-01 -2.08487377e-01 4.46506113e-01 6.41561523e-02
9.78186965e-01 -1.30704391e+00 -7.70443916e-01 7.64978409e-01
2.53773898e-01 -4.47792321e-01 5.52587025e-02 8.60585988e-01
-9.75113153e-01 4.83345360e-01 -4.99976754e-01 -6.61628664e-01
-1.54398799e+00 1.63216367e-01 1.95064351e-01 1.93251491e-01
-5.39202392e-01 3.69700164e-01 -4.14793253e-01 1.53149813e-01
1.56663612e-01 1.29683748e-01 -3.71032655e-01 -1.28435120e-01
5.60821116e-01 3.96193981e-01 -9.79509801e-02 -6.20151937e-01
-4.14165139e-01 1.37607181e+00 -2.51502454e-01 -1.35467649e-01
1.13145173e+00 2.78426260e-01 -4.87670839e-01 -3.18423659e-01
1.13302422e+00 3.40984136e-01 -7.54164994e-01 -1.51419923e-01
-3.76079120e-02 -1.05787241e+00 -3.73079985e-01 -6.00719094e-01
-1.11198783e+00 8.56547236e-01 1.09895003e+00 7.28823319e-02
1.07965851e+00 -3.26315701e-01 1.11184216e+00 2.92085141e-01
4.81184185e-01 -8.51980507e-01 -2.14238882e-01 4.63799387e-02
5.65714359e-01 -9.23741937e-01 -8.19777101e-02 -7.17936337e-01
-3.40570807e-01 1.72980940e+00 4.10919517e-01 -3.67914140e-01
7.03483701e-01 -5.24005219e-02 1.05776496e-01 -1.76362544e-02
3.76765966e-01 -2.46929020e-01 3.82917434e-01 5.48708558e-01
5.29197037e-01 -8.01136866e-02 -1.24618864e+00 2.81054497e-01
-2.12015435e-01 5.19989431e-02 1.34553537e-01 8.93637002e-01
-4.24424112e-01 -1.68447614e+00 -4.18750942e-01 8.91844451e-01
-4.25363809e-01 1.55704662e-01 -4.78263587e-01 4.26689118e-01
9.72399339e-02 9.05498683e-01 -1.17584258e-01 -6.22008681e-01
2.20348060e-01 -5.98567389e-02 9.15300786e-01 -1.46882385e-02
-3.62271816e-01 3.65026444e-01 -4.22114491e-01 -2.59212732e-01
-4.00880367e-01 -6.37259960e-01 -1.21824050e+00 -2.39647165e-01
-3.81457359e-01 4.13254946e-01 7.14312613e-01 7.98266709e-01
2.01861471e-01 -5.48385270e-02 9.71677899e-01 -3.88792008e-01
-5.46432734e-01 -7.59154737e-01 -6.25468910e-01 7.36531258e-01
-1.12534679e-01 -4.65061426e-01 -8.07035044e-02 -5.22532351e-02] | [13.069938659667969, 1.0179909467697144] |
e7b79af2-f1d1-4726-a034-31341dc95000 | lof-structure-aware-line-tracking-based-on | 2109.08466 | null | https://arxiv.org/abs/2109.08466v1 | https://arxiv.org/pdf/2109.08466v1.pdf | LOF: Structure-Aware Line Tracking based on Optical Flow | Lines provide the significantly richer geometric structural information about the environment than points, so lines are widely used in recent Visual Odometry (VO) works. Since VO with lines use line tracking results to locate and map, line tracking is a crucial component in VO. Although the state-of-the-art line tracking methods have made great progress, they are still heavily dependent on line detection or the predicted line segments. In order to relieve the dependencies described above to track line segments completely, accurately, and robustly at higher computational efficiency, we propose a structure-aware Line tracking algorithm based entirely on Optical Flow (LOF). Firstly, we propose a gradient-based strategy to sample pixels on lines that are suitable for line optical flow calculation. Then, in order to align the lines by fully using the structural relationship between the sampled points on it and effectively removing the influence of sampled points on it occluded by other objects, we propose a two-step structure-aware line segment alignment method. Furthermore, we propose a line refinement method to refine the orientation, position, and endpoints of the aligned line segments. Extensive experimental results demonstrate that the proposed LOF outperforms the state-of-the-art performance in line tracking accuracy, robustness, and efficiency, which also improves the location accuracy and robustness of VO system with lines. | ['Xiao Liu', 'Zheng Chai', 'Meixiang Quan'] | 2021-09-17 | null | null | null | null | ['line-detection'] | ['computer-vision'] | [-2.57504910e-01 -5.91556370e-01 -2.02958778e-01 1.02516832e-02
2.18973324e-01 -2.97481686e-01 2.69141555e-01 3.24759126e-01
-4.05697763e-01 7.14238882e-01 -1.19796477e-01 3.40842456e-02
-3.16715315e-02 -8.50987732e-01 -6.17732704e-01 -3.87035161e-01
9.19452161e-02 1.82591632e-01 8.88013899e-01 -1.89112276e-01
5.11880875e-01 8.09065282e-01 -1.17758691e+00 -5.26704252e-01
1.13738966e+00 7.29810417e-01 -6.89954981e-02 4.37202960e-01
-4.23616081e-01 5.78696132e-01 -2.52734870e-01 -9.05857384e-02
3.64488244e-01 -3.95253927e-01 -2.71935612e-01 5.08468509e-01
7.11447895e-01 -4.51807678e-01 -5.68532407e-01 1.08623207e+00
3.76972139e-01 1.69940278e-01 3.62141728e-01 -1.40724277e+00
-1.96232229e-01 -9.83988959e-03 -1.14682257e+00 1.76354535e-02
5.10151088e-01 1.79883510e-01 4.23517376e-01 -8.33373249e-01
7.71871328e-01 9.48061466e-01 9.81524467e-01 1.09648526e-01
-1.03019226e+00 -5.95939219e-01 1.21591136e-01 1.47826806e-01
-1.50105703e+00 -3.38729173e-01 1.13687181e+00 -5.41776597e-01
4.95847702e-01 -2.82647796e-02 1.03753757e+00 3.61709237e-01
-2.30965689e-02 5.57030141e-01 6.18481874e-01 -5.63495636e-01
-5.35891615e-02 9.59538668e-03 7.34843761e-02 1.22442102e+00
4.88933295e-01 -7.75604229e-03 -7.08294690e-01 6.86889440e-02
1.41199315e+00 7.45224953e-02 -7.26863265e-01 -1.14945102e+00
-1.47479224e+00 4.91397947e-01 6.57660365e-01 1.88056320e-01
-2.95018882e-01 1.41337380e-01 2.28188127e-01 -2.48274669e-01
2.69178689e-01 9.19137150e-02 9.60428119e-02 -1.02111444e-01
-1.05714631e+00 1.05430648e-01 5.80453098e-01 1.12144685e+00
1.06079328e+00 -4.11063284e-02 -1.49009824e-01 6.56296015e-01
4.32560027e-01 7.12207794e-01 3.51235211e-01 -8.00991952e-01
6.86024427e-01 8.00909340e-01 4.71748382e-01 -1.43755853e+00
-6.49709284e-01 -4.96518403e-01 -7.25556016e-01 2.76386350e-01
4.99151468e-01 -2.21722439e-01 -5.74026108e-01 1.04829371e+00
6.02290094e-01 4.92060721e-01 -3.23950678e-01 8.29974115e-01
3.50103050e-01 6.24786019e-01 -3.76358211e-01 -2.80043066e-01
9.83130217e-01 -1.20000327e+00 -7.25774705e-01 -1.17410332e-01
7.04390347e-01 -8.65247190e-01 7.77603209e-01 7.82279968e-02
-8.24347138e-01 -7.50970244e-01 -1.24116766e+00 -1.42265156e-01
1.48538023e-01 2.75442481e-01 5.42128384e-01 3.76677752e-01
-7.03785837e-01 3.53899270e-01 -8.10912311e-01 -3.17438900e-01
3.27929139e-01 8.60924423e-02 -4.51016009e-01 -3.91822755e-02
-6.95575714e-01 5.51171541e-01 3.21541488e-01 4.24199820e-01
-2.87059490e-02 -8.02664936e-01 -1.09511757e+00 1.65676679e-02
4.60722566e-01 -9.10126925e-01 8.26610565e-01 -4.60044831e-01
-1.56945562e+00 4.51700538e-01 -5.58642387e-01 -4.27608877e-01
1.00863492e+00 -4.72449124e-01 -2.36021847e-01 3.13116580e-01
1.08229667e-01 6.14617944e-01 5.39940894e-01 -1.40940320e+00
-9.85436678e-01 -2.04586893e-01 -3.71563345e-01 4.16123092e-01
-7.15149045e-02 -4.60971296e-01 -7.89768875e-01 -2.67483778e-02
6.03887498e-01 -8.39574456e-01 -2.91012704e-01 7.54787862e-01
-5.33481598e-01 -6.38116375e-02 1.02521622e+00 -4.28848863e-01
1.44273341e+00 -2.10853291e+00 -4.72999573e-01 4.24662262e-01
2.24790931e-01 6.07882857e-01 3.68234932e-01 3.14952493e-01
3.96216959e-01 -4.16408032e-01 -1.38741076e-01 -3.20578933e-01
-2.98762262e-01 -1.98223710e-01 -1.56947657e-01 7.32902050e-01
-3.77054922e-02 5.65426290e-01 -1.00803590e+00 -6.47667050e-01
8.11847210e-01 6.01878226e-01 -4.04756993e-01 -1.68331061e-02
4.10838500e-02 5.90210557e-01 -5.17756879e-01 2.91041672e-01
8.31570923e-01 -4.14776467e-02 -2.88943201e-01 -4.37788367e-01
-7.05298901e-01 -1.59853920e-01 -1.60827768e+00 1.71588588e+00
-1.72794342e-01 7.91431844e-01 -4.86206740e-01 -3.69434237e-01
1.36286092e+00 -5.85358068e-02 7.42401719e-01 -6.34147227e-01
-9.56255421e-02 2.22643182e-01 -2.17682883e-01 -4.32984889e-01
5.90371430e-01 4.81152505e-01 3.99043649e-01 -1.12211011e-01
-4.83881682e-01 -1.52632385e-01 3.00944537e-01 -4.66266759e-02
5.39457977e-01 6.76780164e-01 4.82316852e-01 1.12925768e-01
9.53135788e-01 2.49710709e-01 8.70514989e-01 4.07201588e-01
-5.22124112e-01 5.36827922e-01 9.93914232e-02 -4.41625834e-01
-1.07505190e+00 -7.98812270e-01 -7.92229697e-02 -4.60452139e-02
9.45238292e-01 -3.79092336e-01 -7.10238993e-01 -3.41222346e-01
8.27140361e-02 2.35818967e-01 -1.30830064e-01 1.52513549e-01
-8.96988273e-01 -1.06900103e-01 2.54692435e-01 5.65243125e-01
1.18442738e+00 -6.29888535e-01 -7.17153668e-01 4.48359221e-01
-8.50672722e-02 -1.29700959e+00 -7.69621551e-01 -4.95817721e-01
-7.81290174e-01 -1.10550427e+00 -8.46479058e-01 -8.47462952e-01
9.08719957e-01 7.86513805e-01 3.77549648e-01 6.60742149e-02
-2.48165373e-02 1.12808727e-01 5.82163967e-02 -2.34923646e-01
2.29338616e-01 -1.56612083e-01 -1.15585871e-01 1.52428061e-01
1.17062047e-01 -2.24598020e-01 -8.22658479e-01 5.05974233e-01
-3.60565871e-01 3.65637243e-01 2.33323753e-01 5.09878635e-01
7.43826687e-01 -3.31656896e-02 -1.59301609e-03 -6.55343771e-01
2.21622080e-01 1.12955987e-01 -1.04254699e+00 1.17271103e-01
-4.40297425e-01 -8.02851394e-02 4.52965826e-01 -1.07061461e-01
-1.00917315e+00 3.62630635e-01 7.85017908e-02 -5.60862124e-01
-8.15060809e-02 9.17071551e-02 1.80372432e-01 -4.24026430e-01
4.80174720e-01 2.24134028e-01 -6.24190234e-02 -1.20013759e-01
4.36985165e-01 3.92463923e-01 7.18463898e-01 -1.02326177e-01
1.06145680e+00 9.34215546e-01 3.89997452e-01 -9.87107575e-01
-5.90058506e-01 -9.48209703e-01 -1.08137810e+00 -4.74046409e-01
7.62461960e-01 -7.36460507e-01 -8.13590407e-01 6.71224058e-01
-1.19715607e+00 -7.11710677e-02 -1.26918793e-01 6.98450446e-01
-5.04182279e-01 9.31078076e-01 -4.84216571e-01 -7.83287585e-01
-3.25065255e-01 -9.92880106e-01 7.57684171e-01 7.51014173e-01
8.79095867e-02 -1.26568377e+00 3.55326384e-01 -1.02871172e-01
5.02882935e-02 3.83413285e-01 2.61745602e-01 7.31301308e-02
-8.83681118e-01 -1.35010108e-01 -4.22003150e-01 -1.46930605e-01
2.87375063e-01 3.50020111e-01 -6.39881551e-01 -1.59275308e-01
-3.97043228e-01 3.72249514e-01 5.90652585e-01 4.39558685e-01
6.02573395e-01 1.28840104e-01 -7.98818946e-01 9.31892991e-01
1.56794834e+00 2.13963300e-01 6.31310821e-01 7.25001752e-01
1.11522806e+00 4.53251541e-01 8.53195548e-01 4.02898282e-01
6.13343418e-01 8.99986088e-01 1.60381258e-01 -2.94786245e-01
-3.79792482e-01 -6.96592510e-01 2.29727626e-01 7.10013986e-01
-3.23142600e-03 -7.06917048e-02 -7.10763335e-01 4.32620615e-01
-2.12076616e+00 -9.93023038e-01 -7.41507947e-01 2.45924878e+00
4.61087704e-01 3.13787252e-01 1.44249812e-01 3.44383478e-01
9.06377375e-01 1.45006254e-01 -3.87332141e-01 2.30316818e-02
1.40754106e-02 -3.42472732e-01 7.89075673e-01 6.49075627e-01
-1.09282732e+00 1.06033111e+00 5.28117657e+00 5.32589674e-01
-1.34093869e+00 -5.65089226e-01 -7.77571425e-02 5.38248956e-01
-1.00510105e-01 1.91504404e-01 -1.15917206e+00 4.19810921e-01
5.31364381e-02 -1.72885224e-01 1.15383983e-01 6.51392996e-01
5.83926022e-01 -3.98736626e-01 -6.45162225e-01 1.17812812e+00
1.13676056e-01 -1.35204625e+00 -2.57265061e-01 -1.78692922e-01
9.00743842e-01 -1.80589676e-01 -3.26999873e-01 -3.10158700e-01
-2.13782787e-01 -2.94979662e-01 6.76851451e-01 7.45198309e-01
4.30867583e-01 -5.43115199e-01 4.17549133e-01 3.71901721e-01
-1.54837346e+00 2.80842930e-01 -4.89168912e-01 -3.10195200e-02
4.36107427e-01 6.94499373e-01 -8.90419066e-01 8.57055485e-01
3.51813346e-01 9.43651676e-01 -5.08312047e-01 2.01947117e+00
-4.05373305e-01 2.89846331e-01 -4.63375747e-01 7.53853768e-02
2.65220404e-01 -4.71680075e-01 5.37835836e-01 1.08609498e+00
2.53317714e-01 -3.06602597e-01 4.89352703e-01 7.54468441e-01
3.98361564e-01 3.26197565e-01 -5.98338306e-01 5.92341840e-01
7.65188217e-01 1.13244748e+00 -8.54654431e-01 -2.16914609e-01
-6.17789567e-01 1.01569521e+00 4.04393703e-01 4.35789019e-01
-7.32051551e-01 -6.97883487e-01 4.41422671e-01 2.71571964e-01
3.36320102e-01 -8.82681131e-01 -2.61240959e-01 -1.09502721e+00
1.68231398e-01 -5.50212488e-02 7.69997807e-03 -8.17412317e-01
-7.84492135e-01 3.30375880e-01 -3.44737709e-01 -1.82071841e+00
-1.28921911e-01 -2.30488196e-01 -5.66386282e-01 8.21139514e-01
-2.11252809e+00 -9.61328328e-01 -8.37451637e-01 6.82863057e-01
3.77689302e-01 3.91255170e-01 2.91441202e-01 2.95501828e-01
-5.58858514e-01 2.51134425e-01 1.93940073e-01 4.85735327e-01
8.24737966e-01 -8.70033085e-01 3.07931721e-01 1.14711165e+00
1.81785136e-01 5.92497826e-01 4.37068105e-01 -8.11052322e-01
-1.03101313e+00 -8.38164270e-01 7.70653903e-01 5.52440174e-02
4.11738873e-01 -4.09348728e-03 -9.49028313e-01 6.04028702e-01
-1.69178486e-01 2.43119210e-01 1.19903348e-01 -4.57395673e-01
-7.58683234e-02 -2.89699465e-01 -9.01365578e-01 7.27173269e-01
1.15747273e+00 -1.92656144e-01 -3.73026878e-01 -2.66498383e-02
4.08950806e-01 -7.87300646e-01 -5.40445447e-01 3.62087578e-01
5.74904919e-01 -1.28269076e+00 1.07236493e+00 1.75990462e-01
-2.21623421e-01 -1.09262311e+00 5.76138735e-01 -1.15018439e+00
-2.74323672e-01 -7.25513637e-01 1.04880370e-01 1.31481314e+00
-1.03326924e-01 -6.99488640e-01 9.37386394e-01 3.19141001e-01
-2.44249821e-01 -5.31306803e-01 -6.66967452e-01 -6.30569756e-01
-7.25794375e-01 -1.01647198e-01 4.60273951e-01 1.00602722e+00
-5.55525459e-02 1.20533049e-01 -4.01975155e-01 4.04246330e-01
9.36919391e-01 2.77589291e-01 1.19219291e+00 -1.17392623e+00
1.67609423e-01 -3.83539468e-01 -7.90967882e-01 -1.63572299e+00
-1.68555528e-01 -3.94738495e-01 7.09439218e-02 -1.85446620e+00
-3.80191743e-01 -6.84910774e-01 1.96744323e-01 1.26809120e-01
-3.67545635e-01 1.64520919e-01 3.61441940e-01 6.27395988e-01
-4.65512455e-01 5.56836247e-01 1.47526467e+00 2.56369621e-01
-5.93719363e-01 1.11569203e-01 1.56254783e-01 9.84994531e-01
5.28703392e-01 -1.80397123e-01 -4.43436354e-01 -4.01815265e-01
-1.83750153e-01 1.07784510e-01 2.52689660e-01 -1.37034559e+00
7.09392428e-01 -1.60705104e-01 6.41152501e-01 -8.97606313e-01
2.64985174e-01 -8.74515951e-01 9.44895297e-03 7.41435766e-01
6.29350841e-02 -1.18429065e-02 6.26987666e-02 4.67381269e-01
-2.27732286e-01 -3.09140652e-01 6.96157277e-01 1.08446151e-01
-1.08142281e+00 5.71857810e-01 1.47386789e-01 -2.71070957e-01
1.30107653e+00 -7.38383710e-01 -5.53214073e-01 -2.38649532e-01
-2.59578496e-01 5.19492269e-01 8.06588173e-01 1.64257094e-01
7.05362439e-01 -1.27052760e+00 -4.68424171e-01 5.15181720e-01
2.63452917e-01 3.06351691e-01 1.43141985e-01 9.84312117e-01
-1.23193336e+00 5.40153205e-01 -3.65516305e-01 -8.75678778e-01
-9.50189292e-01 4.92749155e-01 4.22762245e-01 7.01069087e-02
-1.06866610e+00 5.36795020e-01 1.11864232e-01 6.77776933e-02
1.40002310e-01 -4.27801460e-01 -3.45533133e-01 -2.50481039e-01
3.66580307e-01 7.70329058e-01 -3.38383734e-01 -6.98495686e-01
-1.88653901e-01 1.31308353e+00 2.03498647e-01 2.88662761e-02
8.90971482e-01 -5.57037950e-01 2.76032358e-01 4.37351674e-01
7.40572512e-01 6.30483389e-01 -1.73256075e+00 -2.92197049e-01
3.27273794e-02 -8.40391994e-01 -7.94791207e-02 -7.71418586e-02
-9.50796723e-01 8.85885179e-01 4.53268766e-01 6.62351102e-02
6.41190708e-01 -6.84707940e-01 1.06713068e+00 -5.98010384e-02
5.97117782e-01 -7.43572831e-01 -1.51977211e-01 2.47321904e-01
3.01846951e-01 -9.06228662e-01 2.26324141e-01 -1.14585745e+00
-3.99798691e-01 1.56389713e+00 8.63245249e-01 -2.11300865e-01
2.85370976e-01 9.79033858e-02 1.49461523e-01 1.41667619e-01
1.64804906e-01 -2.82317191e-01 2.23054498e-01 7.36556292e-01
2.52155334e-01 -3.56871426e-01 -2.76328862e-01 -4.48643744e-01
6.92498032e-03 3.01482290e-01 5.45743644e-01 8.75592113e-01
-8.76845062e-01 -1.03694808e+00 -5.35783827e-01 -6.92229420e-02
2.65061408e-01 1.94570526e-01 2.01622888e-01 8.15502882e-01
-9.67165083e-02 6.43397689e-01 2.02240020e-01 -5.99107984e-03
6.14655614e-01 -3.88297737e-01 5.64661562e-01 -1.94599420e-01
-9.15639624e-02 1.04922727e-01 -4.51482236e-02 -6.75053239e-01
-5.78559697e-01 -6.83285594e-01 -1.76280463e+00 -2.63024062e-01
-5.54347992e-01 5.15269376e-02 6.58394039e-01 7.36853838e-01
3.73362839e-01 2.43736893e-01 6.16891503e-01 -7.28366613e-01
-2.72605624e-02 -4.76309299e-01 -4.38232541e-01 3.71057183e-01
4.86715227e-01 -6.97290659e-01 -2.89271213e-02 -1.06225185e-01] | [8.318408012390137, -1.6073408126831055] |
40619599-923b-4c39-b47e-04be7e0131da | cross-modal-contrastive-learning-for-speech | null | null | https://openreview.net/forum?id=zmxg59rhm3D | https://openreview.net/pdf?id=zmxg59rhm3D | Cross-modal Contrastive Learning for Speech Translation | How to learn similar representations for spoken utterances and their written text? We believe a unified and aligned representation of speech and text will lead to improvement in speech translation. To this end, we propose ConST, a cross-modal contrastive learning method for end-to-end speech-to-text translation. We evaluate ConST and a variety of previous baselines on multiple language directions (En-De/Fr/Ru) of a popular benchmark MuST-C. Experiments show that the proposed ConST consistently outperforms all previous methods, and achieves the state-of-the-art average BLEU of 28.5. The analysis further verifies that ConST indeed closes the representation gap of different modalities --- its learned representation improves the accuracy of cross-modal text retrieval from 4% to 88%. | ['Anonymous'] | 2021-12-17 | null | null | null | acl-arr-december-2022-12 | ['speech-to-text-translation'] | ['natural-language-processing'] | [ 1.94466472e-01 3.50832455e-02 -4.87640679e-01 -5.53165257e-01
-2.00670671e+00 -7.91557133e-01 1.05213523e+00 -1.88353047e-01
-3.89033973e-01 6.93165362e-01 8.93285334e-01 -3.80943686e-01
3.46237481e-01 -8.54450017e-02 -7.49795496e-01 -3.49577904e-01
5.07345438e-01 9.20198441e-01 -2.23874956e-01 -6.08034670e-01
-1.51339963e-01 1.38289882e-02 -9.95244205e-01 8.94055009e-01
6.85413241e-01 6.94468141e-01 -1.54937943e-03 6.16869748e-01
-2.80881464e-01 6.69061601e-01 -5.75513721e-01 -6.47509336e-01
-5.00721075e-02 -6.52082741e-01 -1.14374733e+00 -2.21588850e-01
8.30037355e-01 -2.42418602e-01 -5.35926998e-01 7.52722383e-01
1.02339208e+00 2.18409166e-01 1.00231636e+00 -9.13858354e-01
-1.27070308e+00 9.56567109e-01 -3.96078974e-01 7.61965141e-02
6.79382205e-01 -3.47603559e-01 1.16156745e+00 -1.29290867e+00
5.99286735e-01 1.53397048e+00 3.49270970e-01 1.02366471e+00
-1.22340775e+00 -4.41573530e-01 -1.92433700e-01 1.19112534e-02
-1.45494568e+00 -1.18325877e+00 3.16028178e-01 -8.66337027e-03
1.24527740e+00 6.21125579e-01 -2.10004494e-01 1.54619241e+00
-6.27538562e-02 1.13930321e+00 1.06797779e+00 -7.29007900e-01
-2.35821083e-01 1.06375650e-01 -2.22100824e-01 4.42816228e-01
-3.36541206e-01 -6.31933138e-02 -9.41738427e-01 1.09605258e-02
1.58282131e-01 -4.91319358e-01 -4.45660144e-01 1.73987269e-01
-1.56385911e+00 6.97802722e-01 1.22589953e-01 4.32347894e-01
-4.47987430e-02 7.81506002e-02 8.70338678e-01 7.04272926e-01
6.52172744e-01 3.56103688e-01 -5.54472268e-01 -3.71365845e-01
-9.85969961e-01 9.41180438e-02 7.13932693e-01 1.19018304e+00
2.39425570e-01 1.59601644e-01 -5.42098641e-01 1.31367087e+00
3.61205071e-01 1.25822592e+00 7.52974868e-01 -7.66814172e-01
1.04686165e+00 1.26464516e-01 -5.92384562e-02 -4.24814075e-01
1.49790440e-02 -2.66635478e-01 -7.62099981e-01 -6.42874658e-01
6.31328598e-02 -1.10780157e-01 -8.54249537e-01 1.85511947e+00
-1.81158051e-01 -2.88269758e-01 6.98959351e-01 7.94121742e-01
1.22965276e+00 9.96920824e-01 -3.54619659e-02 -2.62552559e-01
1.19036984e+00 -1.34193444e+00 -1.10614145e+00 -5.28672993e-01
6.07762754e-01 -1.32363629e+00 1.29798162e+00 -3.40395570e-01
-1.32839155e+00 -5.61596215e-01 -6.98131204e-01 -3.73649299e-01
-2.96684027e-01 5.86502910e-01 1.22902960e-01 4.47492242e-01
-1.22815382e+00 1.33972421e-01 -5.78010738e-01 -5.96152186e-01
-2.25805908e-01 5.94633333e-02 -4.21319813e-01 -1.51722834e-01
-1.43372297e+00 1.17169440e+00 1.18534215e-01 -2.99543619e-01
-8.05354536e-01 -3.27272177e-01 -8.29558015e-01 -1.00664247e-03
-5.48998006e-02 -8.20339978e-01 1.64767289e+00 -9.24405575e-01
-1.77579772e+00 1.07664120e+00 -6.35514855e-01 -3.55764866e-01
2.17661053e-01 -4.69567150e-01 -7.59395242e-01 1.01094432e-01
1.02431044e-01 8.31275344e-01 7.84337819e-01 -1.06716752e+00
-1.85069263e-01 -1.36888593e-01 -1.13569155e-01 6.38264835e-01
-3.19602787e-01 4.36604291e-01 -6.94205344e-01 -6.35453701e-01
1.03787035e-01 -1.05015421e+00 3.84014875e-01 -2.27132097e-01
-2.52770841e-01 -3.23945880e-01 5.74741244e-01 -9.12505329e-01
1.19754863e+00 -2.02508855e+00 6.22302711e-01 -4.79614645e-01
-3.90529811e-01 1.58848569e-01 -5.43005705e-01 9.44567740e-01
-4.03681397e-02 1.45540247e-03 -6.54142424e-02 -8.72247159e-01
1.78999439e-01 2.82388747e-01 -6.68016613e-01 3.36973011e-01
6.82597086e-02 1.11784065e+00 -6.49748504e-01 -4.66325939e-01
9.09033492e-02 5.46299577e-01 -1.33160755e-01 4.48802501e-01
-3.92459892e-02 3.99504870e-01 -1.52637765e-01 5.60583293e-01
3.36312473e-01 -3.04203741e-02 1.47601366e-01 -1.62352160e-01
2.01249927e-01 1.00860643e+00 -2.86179930e-01 2.16807747e+00
-5.85735559e-01 8.79082561e-01 -5.56671843e-02 -7.36827075e-01
8.75877321e-01 7.66572654e-01 1.73585862e-01 -1.06767166e+00
1.60328269e-01 4.45805937e-01 -4.85224456e-01 -3.39871556e-01
7.78676748e-01 1.90405664e-03 -2.82381982e-01 5.15818417e-01
2.70195425e-01 -5.06016374e-01 -2.20932364e-02 2.49792635e-01
6.06297255e-01 -5.47060408e-02 2.41819322e-02 -2.56635129e-01
6.24549747e-01 -2.08977386e-01 2.62734164e-02 4.83556509e-01
-8.55591819e-02 7.90266633e-01 -7.50906439e-03 7.60336444e-02
-9.69819069e-01 -1.15110600e+00 1.42934978e-01 1.52656221e+00
-1.76960662e-01 -4.39886153e-01 -9.06103790e-01 -8.13303113e-01
-1.97728455e-01 1.01617396e+00 -4.27617908e-01 -2.93152839e-01
-5.55359066e-01 -2.42991433e-01 1.02359128e+00 3.91415060e-01
3.24474841e-01 -6.54988468e-01 2.75307447e-01 -4.62129414e-02
-9.47928011e-01 -1.45107698e+00 -9.79280651e-01 -7.05661774e-02
-6.57086551e-01 -3.49692851e-01 -1.11575437e+00 -1.03286791e+00
4.20027941e-01 4.98765320e-01 1.42682052e+00 -4.25152749e-01
4.21348721e-01 5.56376457e-01 -6.77072883e-01 -1.34072065e-01
-1.03473163e+00 3.28671336e-01 2.91599959e-01 -2.15987921e-01
3.51061225e-01 -6.32234290e-02 -2.18272910e-01 4.07035977e-01
-7.06835926e-01 3.49793397e-02 4.81113940e-01 9.59606647e-01
4.67411488e-01 -9.52672839e-01 5.85798621e-01 -2.29044050e-01
9.41172600e-01 -2.69588023e-01 -1.26829624e-01 7.09891260e-01
-4.15617615e-01 2.45706216e-01 3.42894644e-01 -4.36067194e-01
-9.23668027e-01 -2.21338362e-01 -2.79184133e-01 -4.12141681e-01
6.14589378e-02 6.65814698e-01 3.44782099e-02 3.78895879e-01
7.59457409e-01 6.47711694e-01 8.79698321e-02 -4.76145834e-01
8.99724364e-01 1.30618441e+00 6.62939727e-01 -7.98234642e-01
5.11133492e-01 7.99071603e-03 -5.40280461e-01 -6.06426775e-01
-8.43478858e-01 -4.24535960e-01 -4.61719573e-01 -5.11425845e-02
8.21769178e-01 -1.37287462e+00 -1.99032068e-01 1.48708940e-01
-1.46314049e+00 -2.78657228e-01 -5.14797196e-02 6.59255087e-01
-8.33781660e-01 3.74627829e-01 -7.60575116e-01 -5.30549288e-01
-7.06948161e-01 -1.18000400e+00 1.78105247e+00 -3.06096703e-01
-4.12904739e-01 -9.09717262e-01 2.97312647e-01 8.24681342e-01
6.81430399e-01 -5.14676094e-01 6.33761287e-01 -8.13587070e-01
1.13689236e-03 5.98474108e-02 -2.01704040e-01 4.39293623e-01
3.45417708e-01 -2.20590621e-01 -1.08286512e+00 -6.45900846e-01
-3.03224325e-01 -7.73082674e-01 7.93920696e-01 4.78696264e-02
5.17526746e-01 -4.42553610e-01 -5.55058417e-04 1.57431453e-01
8.95012796e-01 -1.03127085e-01 5.41629553e-01 2.78743245e-02
3.85813385e-01 5.30022740e-01 6.25558674e-01 1.77001655e-02
4.25005525e-01 1.13687575e+00 1.00048864e-02 -5.98603226e-02
-6.61649525e-01 -3.33536625e-01 1.01285923e+00 1.77132630e+00
3.12900364e-01 -5.39596915e-01 -8.23506773e-01 6.18658781e-01
-1.82078409e+00 -9.06439900e-01 2.68204391e-01 2.01300311e+00
1.30947256e+00 -4.07522768e-01 1.87974293e-02 -3.86049628e-01
5.84840894e-01 3.61278415e-01 -8.74629617e-02 -5.49897075e-01
-3.01500648e-01 1.78843159e-02 2.90896893e-01 7.14379191e-01
-9.21342909e-01 1.34598613e+00 7.48940802e+00 1.04265058e+00
-1.24190366e+00 4.87130404e-01 4.33119297e-01 -7.17223734e-02
-4.37988043e-01 -4.04487103e-01 -8.52933884e-01 1.40038401e-01
1.56353283e+00 -4.00022656e-01 6.70592904e-01 6.75404727e-01
1.16327345e-01 5.35305679e-01 -1.36214650e+00 1.17008078e+00
6.73931539e-01 -1.33690095e+00 3.96789372e-01 -3.90983284e-01
9.16110754e-01 6.11952066e-01 2.48355106e-01 6.34246767e-01
2.10159272e-01 -1.01134968e+00 8.19235682e-01 2.50125319e-01
1.33900642e+00 -4.52199936e-01 7.23221481e-01 1.68859705e-01
-1.04274774e+00 4.04538363e-01 -2.77398258e-01 3.74044806e-01
2.88431734e-01 -3.49145159e-02 -1.09360385e+00 8.00506413e-01
3.32154840e-01 6.27753675e-01 -3.84296626e-01 2.69726336e-01
-1.36512145e-01 6.08973742e-01 -1.12098776e-01 -1.21574879e-01
3.13506335e-01 1.89802915e-01 4.66985375e-01 1.61966836e+00
4.15143222e-01 -4.74518865e-01 9.03641954e-02 5.70932448e-01
-5.15165031e-01 4.23046798e-01 -7.85781503e-01 -4.61625278e-01
6.77201807e-01 6.06659293e-01 1.03467003e-01 -5.22982299e-01
-5.80072939e-01 1.42384839e+00 4.25897539e-01 5.10679066e-01
-7.39590943e-01 -8.84214789e-02 6.75544024e-01 -4.32659358e-01
1.18471131e-01 -4.14539605e-01 4.50332707e-04 -1.31628740e+00
9.88559574e-02 -1.39260709e+00 1.47245333e-01 -8.76011074e-01
-1.44695497e+00 9.38187599e-01 -5.27267642e-02 -1.40713024e+00
-7.48925447e-01 -3.29210669e-01 4.04624036e-03 1.02975535e+00
-1.48396504e+00 -1.51561952e+00 2.82830626e-01 7.56987989e-01
1.16891789e+00 -6.58325195e-01 1.37505221e+00 4.44321632e-01
-1.97296694e-01 1.19209969e+00 6.57367706e-01 3.03331703e-01
1.28635085e+00 -8.06528628e-01 7.30752289e-01 6.91274762e-01
5.66313446e-01 6.49555087e-01 6.48669183e-01 -3.55611086e-01
-1.56141829e+00 -1.03206813e+00 1.34621358e+00 -6.64661348e-01
7.70778179e-01 -3.07733625e-01 -6.88031137e-01 6.92872345e-01
8.97902608e-01 -1.73084408e-01 5.79955041e-01 3.06242947e-02
-8.06877196e-01 -1.53243527e-01 -8.25578213e-01 8.02707851e-01
7.38466263e-01 -1.40844858e+00 -8.77853692e-01 5.93379080e-01
1.19839060e+00 -4.98528510e-01 -9.37025189e-01 3.71826321e-01
5.99676788e-01 -3.77500355e-01 9.58138585e-01 -8.40784669e-01
4.46230054e-01 4.30973284e-02 -9.64957118e-01 -1.48133016e+00
9.79878530e-02 -6.98304951e-01 -5.15883490e-02 1.39839745e+00
8.09028506e-01 -4.23764616e-01 1.45372406e-01 2.03854978e-01
-4.85341221e-01 -5.63711166e-01 -1.35938632e+00 -9.23236609e-01
5.21502018e-01 -3.09348762e-01 5.37155449e-01 1.12342632e+00
1.86193094e-01 9.01339710e-01 -5.29545009e-01 -1.38128502e-02
1.68165252e-01 -7.23708943e-02 7.48999119e-01 -6.06459141e-01
-3.42130423e-01 -3.93049002e-01 1.91578157e-02 -1.58730924e+00
6.31292403e-01 -1.18036938e+00 3.05270944e-02 -1.51153839e+00
2.49948874e-01 5.99863939e-02 -6.50896952e-02 5.41937292e-01
-9.18718874e-02 1.58940852e-01 1.62847444e-01 3.92071187e-01
-7.10294724e-01 1.05442286e+00 1.22112954e+00 -6.21810675e-01
1.56331524e-01 -2.31469005e-01 -5.37868083e-01 1.13111772e-01
7.16726482e-01 -3.30707461e-01 -3.00312489e-01 -1.04345429e+00
-8.17526877e-02 2.99216121e-01 -2.86387980e-01 -6.36134744e-01
7.80484900e-02 -9.56365746e-03 -2.16599584e-01 -5.85839927e-01
7.08952904e-01 -5.80289662e-01 -3.01944762e-01 -5.35300300e-02
-9.74884629e-01 3.36661547e-01 3.13870311e-01 1.63225085e-01
-6.38636589e-01 3.73892337e-02 6.23062015e-01 1.35269880e-01
-2.76394248e-01 -1.73012495e-01 -3.75698835e-01 3.50887805e-01
3.03163767e-01 4.59574670e-01 -8.20064783e-01 -8.97732675e-01
-5.13661146e-01 -1.12911351e-02 2.33113691e-01 9.69083607e-01
5.81723154e-01 -1.63082027e+00 -1.25134015e+00 9.38855782e-02
4.66520876e-01 -7.69459724e-01 -1.57994807e-01 8.80780339e-01
-2.52567437e-02 8.39988351e-01 8.97958204e-02 -7.08630323e-01
-1.65814650e+00 3.06889135e-02 3.63066345e-01 -1.76120043e-01
-1.65594146e-01 8.79794478e-01 -2.12153956e-01 -9.45075572e-01
3.95049423e-01 -1.04848497e-01 5.96088581e-02 -1.42250210e-01
6.26700521e-01 1.59216866e-01 2.73899049e-01 -1.22935927e+00
-4.46357787e-01 5.39395750e-01 -2.57406861e-01 -6.77421510e-01
9.94304895e-01 -6.44024253e-01 -1.56920910e-01 6.70261383e-01
1.49749660e+00 1.78662062e-01 -4.95422184e-01 -5.82239926e-01
-2.19269514e-01 -1.84718311e-01 -1.02236047e-02 -1.16768980e+00
-7.56346047e-01 9.21406269e-01 7.43190348e-01 -2.56056845e-01
8.77314031e-01 3.83297473e-01 9.75779355e-01 8.58179867e-01
3.30587953e-01 -1.01022327e+00 1.91044182e-01 1.04982173e+00
1.40782881e+00 -1.38450670e+00 -1.46972060e-01 -7.30986372e-02
-9.66269255e-01 8.99435699e-01 1.82589740e-01 5.32314777e-01
6.10991307e-02 2.45081447e-02 6.00247025e-01 1.72689453e-01
-9.30810690e-01 -1.91811845e-01 7.77016580e-01 5.01861930e-01
1.10575819e+00 2.31249630e-01 -2.46236056e-01 1.19051889e-01
-2.39538446e-01 -3.82356554e-01 7.03447834e-02 6.76923394e-01
-2.75988221e-01 -1.32469928e+00 -2.53660262e-01 -1.58030435e-01
-5.40559769e-01 -4.42328036e-01 -9.04679358e-01 4.86621112e-01
-6.78567171e-01 1.30470717e+00 -1.83665216e-01 -5.00911474e-01
3.60753894e-01 4.63649124e-01 4.34916914e-01 -5.21881104e-01
-5.19393802e-01 3.31411034e-01 6.25065506e-01 -5.08843303e-01
-5.85981250e-01 -5.42573988e-01 -1.07304144e+00 -3.63022268e-01
-3.14231306e-01 2.76464581e-01 9.16163266e-01 8.12725961e-01
5.90889454e-01 3.97331744e-01 6.97591186e-01 -8.17177176e-01
-8.96487474e-01 -1.38930368e+00 -7.57553056e-02 3.74771982e-01
4.68612194e-01 -3.85592073e-01 -4.19542015e-01 -8.34644027e-03] | [14.478581428527832, 7.1685943603515625] |
460ac0e5-c658-472b-899d-dcfddfce355f | relation3dmot-exploiting-deep-affinity-for-3d | 2011.12850 | null | https://arxiv.org/abs/2011.12850v1 | https://arxiv.org/pdf/2011.12850v1.pdf | Relation3DMOT: Exploiting Deep Affinity for 3D Multi-Object Tracking from View Aggregation | Autonomous systems need to localize and track surrounding objects in 3D space for safe motion planning. As a result, 3D multi-object tracking (MOT) plays a vital role in autonomous navigation. Most MOT methods use a tracking-by-detection pipeline, which includes object detection and data association processing. However, many approaches detect objects in 2D RGB sequences for tracking, which is lack of reliability when localizing objects in 3D space. Furthermore, it is still challenging to learn discriminative features for temporally-consistent detection in different frames, and the affinity matrix is normally learned from independent object features without considering the feature interaction between detected objects in the different frames. To settle these problems, We firstly employ a joint feature extractor to fuse the 2D and 3D appearance features captured from both 2D RGB images and 3D point clouds respectively, and then propose a novel convolutional operation, named RelationConv, to better exploit the correlation between each pair of objects in the adjacent frames, and learn a deep affinity matrix for further data association. We finally provide extensive evaluation to reveal that our proposed model achieves state-of-the-art performance on KITTI tracking benchmark. | ['Antonios Tsourdos', 'Luca Zanotti Fragonara', 'Can Chen'] | 2020-11-25 | null | null | null | null | ['3d-multi-object-tracking'] | ['computer-vision'] | [-2.86594898e-01 -7.72832930e-01 8.65383167e-03 -1.12090819e-01
-3.59108388e-01 -5.78965127e-01 4.02763933e-01 7.92478547e-02
-7.13152885e-01 2.93533444e-01 -1.81822643e-01 7.05482736e-02
-1.40765935e-01 -5.82622290e-01 -7.69860685e-01 -8.40772152e-01
-4.48766500e-02 5.53273797e-01 1.14915514e+00 -1.74251243e-01
6.77537778e-03 8.17615271e-01 -1.71535981e+00 -2.42315128e-01
5.40928543e-01 1.18140984e+00 5.19440293e-01 5.35071731e-01
-1.81559682e-01 5.80385268e-01 -3.13901275e-01 1.47798449e-01
4.98956889e-01 -7.79923648e-02 -1.92540169e-01 1.15869418e-01
6.22951925e-01 -5.10781467e-01 -6.53471410e-01 1.20977879e+00
3.59231442e-01 3.70287061e-01 3.93183857e-01 -1.38565588e+00
-3.42633963e-01 -6.66930079e-02 -7.00318754e-01 6.11637592e-01
3.11388284e-01 4.71000612e-01 6.42046273e-01 -7.83125222e-01
5.07460952e-01 1.28802443e+00 4.49415326e-01 4.78580773e-01
-7.54844785e-01 -7.86143959e-01 4.34857786e-01 3.93569946e-01
-1.37932026e+00 -1.78949952e-01 6.85698628e-01 -5.13417959e-01
6.50127530e-01 2.53795743e-01 1.12098348e+00 6.91063046e-01
4.15586203e-01 8.61239910e-01 7.42173672e-01 7.37794787e-02
-1.54763311e-01 -1.60861649e-02 1.00197665e-01 7.89747894e-01
5.54565847e-01 2.65270799e-01 -5.13850331e-01 5.93722574e-02
7.65596509e-01 5.73259413e-01 -1.72920272e-01 -7.67944098e-01
-1.48601723e+00 4.04644787e-01 8.25564265e-01 2.15722650e-01
-4.32472706e-01 3.36275160e-01 7.66982213e-02 3.03687062e-02
8.56931955e-02 -2.29352847e-01 -2.72838265e-01 4.62148376e-02
-4.90097433e-01 2.96862245e-01 1.83237642e-01 1.20634484e+00
9.47533131e-01 -1.45745352e-01 -1.51890963e-01 2.75902003e-01
8.70207012e-01 9.41311896e-01 3.40959787e-01 -6.07914388e-01
3.25318873e-01 8.53662908e-01 3.90406311e-01 -1.15382254e+00
-5.18423259e-01 -3.95094037e-01 -6.98665857e-01 4.70739543e-01
3.35106611e-01 1.65038630e-01 -8.63491356e-01 1.39168048e+00
9.58729982e-01 4.20804203e-01 -2.41116732e-02 1.38801920e+00
8.62132728e-01 4.37180728e-01 -2.84290519e-02 -1.40639246e-01
1.43154478e+00 -8.60363126e-01 -5.65280139e-01 -4.01981324e-01
3.86629850e-01 -6.55544698e-01 3.87351245e-01 -1.10112935e-01
-8.08229625e-01 -8.79685640e-01 -9.99796152e-01 -2.51098275e-02
-2.76411504e-01 1.03853837e-01 5.31245351e-01 3.42990935e-01
-5.28471231e-01 1.69886425e-01 -1.19855070e+00 -3.30251217e-01
4.72066671e-01 5.78503549e-01 -4.14373070e-01 -2.13182479e-01
-9.23740149e-01 9.57042933e-01 5.62955916e-01 4.28010464e-01
-1.01479471e+00 -3.35059822e-01 -8.15908194e-01 -2.88075387e-01
5.07331610e-01 -7.86435843e-01 7.22495914e-01 -3.17877918e-01
-1.08649492e+00 6.70134187e-01 -2.45698094e-01 -2.04580352e-01
4.94957596e-01 -5.49466789e-01 -3.86253834e-01 -2.69513905e-01
1.61400750e-01 6.18056655e-01 7.76957512e-01 -1.18374646e+00
-1.29474318e+00 -6.17687106e-01 -2.51767132e-02 4.81738746e-01
-7.04071224e-02 -4.02376428e-02 -1.06075168e+00 -1.54597178e-01
6.52626216e-01 -1.18363214e+00 -3.68130118e-01 3.75900120e-01
-2.11356819e-01 -4.46256518e-01 1.23092639e+00 -1.20141193e-01
7.81671345e-01 -2.17838311e+00 3.47956747e-01 -3.01494002e-02
3.13218385e-01 1.04464218e-01 1.32340163e-01 -2.81618983e-01
5.34035265e-01 -5.72380841e-01 2.24889353e-01 -4.07057226e-01
-1.25729730e-02 3.04717064e-01 -1.87665336e-02 7.74042130e-01
2.49104410e-01 8.76733184e-01 -1.01908481e+00 -6.37656868e-01
6.30433500e-01 5.05461156e-01 -2.70845413e-01 1.69946477e-01
-2.14097083e-01 7.22568929e-01 -9.24069941e-01 8.50057602e-01
8.76336396e-01 -3.53956282e-01 -3.74159217e-01 -4.01393712e-01
-5.23720682e-01 -2.94294767e-02 -1.49065197e+00 1.98359692e+00
1.39737085e-01 4.99077201e-01 -7.95605779e-02 -5.62864661e-01
8.29146028e-01 -4.32892218e-02 7.81269670e-01 -5.70867419e-01
1.37341678e-01 2.52574623e-01 1.99943371e-02 -4.18352693e-01
6.15773976e-01 2.87049890e-01 -7.88451172e-03 4.18380983e-02
-1.22847065e-01 5.35350256e-02 -3.89195443e-03 4.17939872e-02
1.19128668e+00 3.28634918e-01 -4.14485112e-02 9.18313712e-02
7.37845302e-01 3.17218870e-01 9.07109261e-01 7.37033606e-01
-5.49939513e-01 2.33777240e-01 -3.32250893e-01 -6.45184338e-01
-6.92130506e-01 -1.02484596e+00 -1.67921688e-02 7.27062225e-01
1.11041057e+00 -6.81439489e-02 1.43214449e-01 -7.29958236e-01
3.69971216e-01 -5.80390356e-02 -5.68918586e-01 -1.98124498e-01
-7.10446835e-01 -6.04651153e-01 7.14445040e-02 3.48810941e-01
5.60869336e-01 -6.78687930e-01 -1.21419954e+00 2.36237898e-01
-6.34592725e-03 -1.26593852e+00 -4.05065775e-01 2.94620216e-01
-7.36697197e-01 -1.12404680e+00 -4.92409229e-01 -5.90339303e-01
5.00175297e-01 8.89115691e-01 6.49640143e-01 2.98567116e-01
-1.93679914e-01 3.65810245e-01 -3.68561238e-01 -3.97403985e-01
8.97957981e-02 -1.68409541e-01 4.01341647e-01 3.18165794e-02
5.24939716e-01 -2.56232917e-01 -7.17001617e-01 6.61293209e-01
-5.63357890e-01 1.14077339e-02 8.18400621e-01 5.21818340e-01
8.57856095e-01 3.62841189e-02 -1.52230024e-01 -5.73305488e-02
-3.34961712e-01 -3.64671558e-01 -9.98186171e-01 2.04854682e-01
-2.29136483e-03 -1.29534870e-01 1.22736491e-01 -4.46973979e-01
-5.37578464e-01 7.08875716e-01 1.40504539e-01 -1.06779015e+00
-1.89389035e-01 1.53402969e-01 -2.32096180e-01 -3.89730126e-01
2.30515823e-01 3.61543357e-01 -5.72251081e-02 -3.30754697e-01
2.32980087e-01 2.73978680e-01 5.47306478e-01 -1.31878763e-01
1.18881655e+00 8.68050039e-01 3.12591583e-01 -5.10127604e-01
-9.07767057e-01 -9.01989877e-01 -9.41053987e-01 -6.51476502e-01
1.19094658e+00 -1.28772938e+00 -8.76393139e-01 3.53781939e-01
-1.22125852e+00 1.24968328e-01 -1.98075213e-02 9.41820145e-01
-2.08996385e-01 2.43498489e-01 -1.30819812e-01 -8.35455835e-01
-8.96270126e-02 -1.29410326e+00 1.34414983e+00 6.08520925e-01
3.77954155e-01 -5.76391339e-01 1.68144479e-01 1.56298205e-02
1.21543996e-01 1.98378742e-01 1.54207304e-01 -3.99765462e-01
-1.29765415e+00 -2.79111683e-01 -3.12392741e-01 -2.92824030e-01
3.13108146e-01 -9.56762284e-02 -6.53987944e-01 -4.26892817e-01
-3.84445935e-02 -3.34577076e-02 8.93037975e-01 3.94452691e-01
5.86486101e-01 2.75174052e-01 -8.81096005e-01 6.91565990e-01
1.27244556e+00 2.09409833e-01 2.05984920e-01 5.10149539e-01
1.06889069e+00 2.92355865e-01 1.11468589e+00 4.23518300e-01
4.81926411e-01 9.40416098e-01 7.42088914e-01 2.63990343e-01
-6.56602308e-02 1.22899793e-01 3.56669456e-01 7.18372464e-01
-1.16866089e-01 -4.51654121e-02 -8.22578549e-01 3.68768036e-01
-2.28070450e+00 -8.96996140e-01 -3.62264931e-01 2.00819373e+00
2.21582547e-01 4.29914922e-01 1.12834133e-01 -3.41402233e-01
7.74624467e-01 5.23211695e-02 -8.93449247e-01 9.17354345e-01
-2.74981618e-01 -4.16221619e-01 7.92259395e-01 2.14378938e-01
-1.46982837e+00 8.34460855e-01 4.80035019e+00 5.59592128e-01
-9.62034464e-01 1.17161237e-01 -2.04382330e-01 -2.62070268e-01
6.85384572e-02 1.47839710e-01 -1.34542954e+00 5.57632267e-01
3.48030508e-01 1.83215171e-01 -1.48353249e-01 8.81725967e-01
3.78012564e-03 -1.51119664e-01 -9.19856727e-01 1.18009424e+00
-1.16802320e-01 -1.27342689e+00 -1.60051644e-01 1.11992285e-01
4.79586214e-01 4.63285655e-01 -1.02247700e-01 1.81963980e-01
2.45556667e-01 -3.86069298e-01 9.53247666e-01 6.60373092e-01
4.95634042e-02 -5.05296111e-01 6.30751431e-01 5.75085878e-01
-1.87410009e+00 -1.73581541e-01 -6.99132681e-01 1.66940875e-02
2.96016455e-01 3.88132244e-01 -4.76798713e-01 8.47274005e-01
1.14556491e+00 1.14043081e+00 -6.38731301e-01 1.56993437e+00
6.07271232e-02 -6.30009398e-02 -6.73218012e-01 -2.38391906e-01
2.73060858e-01 -1.04472995e-01 8.16878498e-01 6.63189530e-01
4.90252554e-01 2.94173002e-01 6.40760958e-01 6.46354496e-01
3.59437793e-01 -3.49213958e-01 -4.98981029e-01 3.64941031e-01
6.08165383e-01 1.38454640e+00 -9.21663523e-01 -3.82710814e-01
-5.89155555e-01 8.93415034e-01 2.01801896e-01 -3.41255181e-02
-1.05254388e+00 -7.77636915e-02 9.81244266e-01 -2.30852395e-01
6.66236937e-01 -7.40226328e-01 2.70144135e-01 -1.17426574e+00
1.46220982e-01 -3.11302155e-01 3.37185860e-01 -7.21524000e-01
-1.05673528e+00 4.63786334e-01 -2.03818232e-01 -1.85870934e+00
2.05820322e-01 -5.60317278e-01 -2.94535458e-01 7.61495411e-01
-1.59939444e+00 -1.14931679e+00 -8.51938605e-01 7.79068947e-01
3.80276173e-01 9.53979343e-02 2.35699534e-01 6.32176042e-01
-6.58631980e-01 1.24427520e-01 4.81642038e-02 1.80074096e-01
5.48647523e-01 -8.95473480e-01 3.29585999e-01 9.79773223e-01
2.39835829e-01 4.08452719e-01 5.43025911e-01 -9.64774132e-01
-2.07625818e+00 -1.25807559e+00 3.00736308e-01 -7.99520433e-01
4.20832396e-01 -2.90348649e-01 -8.56592774e-01 6.89255059e-01
-2.23873481e-01 5.55002272e-01 2.20907435e-01 -3.21590722e-01
3.11083850e-02 -8.55533108e-02 -7.36299217e-01 3.16448003e-01
1.43870640e+00 -1.05868302e-01 -4.75302070e-01 4.10182208e-01
9.23225224e-01 -9.33910072e-01 -7.43987262e-01 5.72041988e-01
6.09817982e-01 -7.75245726e-01 1.21075356e+00 -3.83128494e-01
-4.52869534e-01 -1.27021658e+00 -2.96125144e-01 -8.17832887e-01
-5.54986417e-01 -2.67433852e-01 -3.45027894e-01 8.88697207e-01
-7.37023205e-02 -3.65173280e-01 1.00854445e+00 3.71141464e-01
-4.55663681e-01 -3.06161553e-01 -1.20803165e+00 -8.92332613e-01
-5.74619710e-01 -3.99055064e-01 5.86089194e-01 6.50508940e-01
-6.64394975e-01 2.40069285e-01 -4.61974889e-01 8.84536147e-01
9.70017791e-01 4.61994380e-01 1.25873613e+00 -1.49914289e+00
3.74702699e-02 -3.17169338e-01 -9.66944337e-01 -1.61503422e+00
-8.64032805e-02 -6.55052722e-01 4.08468485e-01 -1.43860316e+00
1.02061316e-01 -7.84121394e-01 -4.42511648e-01 2.55014986e-01
-4.09730345e-01 2.02033058e-01 3.46905380e-01 6.15532815e-01
-1.20951676e+00 8.98715854e-01 1.28042173e+00 -3.20060164e-01
-1.74602225e-01 5.45662753e-02 -8.34667935e-06 4.80394930e-01
1.92066178e-01 -5.52396238e-01 3.79542494e-03 -6.86106622e-01
-1.05343759e-01 -6.52841479e-02 7.47294307e-01 -1.52618873e+00
8.96139324e-01 -2.94695914e-01 7.16240942e-01 -1.47945321e+00
6.98549211e-01 -1.36002588e+00 4.03574318e-01 7.26258457e-01
3.18983436e-01 2.83650637e-01 3.34072620e-01 8.71677339e-01
-7.35929906e-02 1.04784884e-01 5.30187130e-01 -1.26235560e-01
-1.45488250e+00 8.13409865e-01 -9.00343060e-02 -3.57221961e-01
1.26685977e+00 -3.56237143e-01 -2.32599452e-01 2.84671634e-01
-5.28937876e-01 7.20135093e-01 5.67794204e-01 6.39640629e-01
8.41945529e-01 -1.72562754e+00 -4.99175996e-01 3.13610524e-01
2.76840359e-01 5.40652931e-01 5.55595458e-01 1.14497328e+00
-2.86152482e-01 3.13331634e-01 -4.12424386e-01 -1.37294424e+00
-1.42530584e+00 5.57090282e-01 3.26715529e-01 1.29627243e-01
-7.85971045e-01 1.03796172e+00 1.54847711e-01 -1.91404819e-01
2.96208769e-01 -4.72045094e-01 -1.43800497e-01 -1.48020655e-01
5.67699313e-01 1.23293988e-01 -8.45148563e-02 -8.44782412e-01
-7.73944080e-01 9.74959075e-01 -1.12692416e-01 1.57224000e-01
1.06602168e+00 -4.54558164e-01 8.76930803e-02 5.37207067e-01
8.47999871e-01 -2.70292699e-01 -1.64895678e+00 -4.87761468e-01
-4.94172722e-02 -8.36722374e-01 1.70183703e-02 -9.20333639e-02
-1.03767955e+00 6.72452807e-01 9.73902166e-01 6.08851947e-02
8.63212168e-01 1.58178523e-01 7.53937662e-01 6.14893377e-01
5.67404509e-01 -7.00097203e-01 1.53761536e-01 7.85708785e-01
3.66297752e-01 -1.55891550e+00 1.92729756e-01 -2.18129739e-01
-3.04558218e-01 9.13486838e-01 9.72897351e-01 -4.58051786e-02
6.74293637e-01 -1.92284603e-02 7.14628845e-02 -3.89239192e-01
-5.05141854e-01 -6.36617601e-01 3.81455690e-01 5.13961554e-01
-1.84885621e-01 -4.09887880e-01 3.02634925e-01 1.20631441e-01
3.32018256e-01 -2.75583535e-01 -1.07184261e-01 1.26619744e+00
-7.79584765e-01 -8.82013381e-01 -6.74471200e-01 2.63316840e-01
1.17591187e-01 3.78327906e-01 -1.06472924e-01 9.49513733e-01
4.03937936e-01 7.00470090e-01 2.42002442e-01 -6.75876677e-01
4.83499408e-01 -2.99505681e-01 5.78792334e-01 -4.58743811e-01
-3.27020645e-01 2.94691145e-01 -4.60415065e-01 -6.79813743e-01
-8.76630425e-01 -1.01940811e+00 -1.43646908e+00 -9.15485919e-02
-6.45377278e-01 7.15611875e-03 6.71432912e-01 1.02993250e+00
3.77653271e-01 6.72602057e-01 4.56400841e-01 -1.23535204e+00
-1.25605762e-01 -6.50058806e-01 -4.69707251e-01 3.01168174e-01
7.00297773e-01 -1.31888568e+00 -3.06299906e-02 -3.02485168e-01] | [6.53314208984375, -2.2412307262420654] |
28d230e5-c2ca-40f0-9571-09179bb56a95 | direction-aware-spatial-context-features-for | 1712.04142 | null | http://arxiv.org/abs/1712.04142v2 | http://arxiv.org/pdf/1712.04142v2.pdf | Direction-aware Spatial Context Features for Shadow Detection | Shadow detection is a fundamental and challenging task, since it requires an
understanding of global image semantics and there are various backgrounds
around shadows. This paper presents a novel network for shadow detection by
analyzing image context in a direction-aware manner. To achieve this, we first
formulate the direction-aware attention mechanism in a spatial recurrent neural
network (RNN) by introducing attention weights when aggregating spatial context
features in the RNN. By learning these weights through training, we can recover
direction-aware spatial context (DSC) for detecting shadows. This design is
developed into the DSC module and embedded in a CNN to learn DSC features at
different levels. Moreover, a weighted cross entropy loss is designed to make
the training more effective. We employ two common shadow detection benchmark
datasets and perform various experiments to evaluate our network. Experimental
results show that our network outperforms state-of-the-art methods and achieves
97% accuracy and 38% reduction on balance error rate. | ['Pheng-Ann Heng', 'Chi-Wing Fu', 'Xiaowei Hu', 'Lei Zhu', 'Jing Qin'] | 2017-12-12 | direction-aware-spatial-context-features-for-2 | http://openaccess.thecvf.com/content_cvpr_2018/html/Hu_Direction-Aware_Spatial_Context_CVPR_2018_paper.html | http://openaccess.thecvf.com/content_cvpr_2018/papers/Hu_Direction-Aware_Spatial_Context_CVPR_2018_paper.pdf | cvpr-2018-6 | ['shadow-detection', 'detecting-shadows'] | ['computer-vision', 'computer-vision'] | [ 6.22648776e-01 -2.43540689e-01 -6.40462264e-02 -7.20957398e-01
-3.02112907e-01 -5.70137091e-02 3.73755187e-01 -4.46170747e-01
-3.39715540e-01 6.53160095e-01 6.07940853e-01 -5.65314233e-01
3.08500051e-01 -7.39935219e-01 -6.99710011e-01 -1.00201619e+00
1.18911117e-01 -4.15161490e-01 8.59540880e-01 -1.82642058e-01
3.07055920e-01 5.53108871e-01 -1.28465343e+00 2.94155419e-01
8.94431233e-01 1.16297436e+00 8.49134386e-01 7.61126101e-01
1.15125999e-01 1.37109625e+00 -8.90680671e-01 1.49754047e-01
2.68848147e-02 -3.55395854e-01 -3.90303850e-01 -1.93615392e-01
2.96743482e-01 -5.37923336e-01 -6.62171006e-01 6.31541491e-01
6.18158937e-01 2.45409891e-01 2.91579336e-01 -9.86309469e-01
-8.10168028e-01 2.42306054e-01 -4.89824057e-01 4.47088480e-01
9.17070545e-03 -1.17653254e-02 9.31722760e-01 -9.18588281e-01
2.70055830e-01 1.19127798e+00 5.80463529e-01 2.66161025e-01
-6.89068079e-01 -5.74512303e-01 5.99893570e-01 5.87051868e-01
-1.20869482e+00 -4.99209277e-02 1.07081354e+00 2.84812510e-01
7.21767128e-01 3.85323644e-01 6.27566814e-01 1.24718189e+00
2.96640068e-01 1.21527421e+00 1.14864349e+00 -2.42993489e-01
1.21831231e-01 -1.06150039e-01 1.44402698e-01 9.06341851e-01
9.59813818e-02 1.12792455e-01 -6.94607258e-01 1.44895539e-01
6.00093126e-01 2.61596560e-01 -6.45751119e-01 -2.86869437e-01
-9.84413445e-01 6.52644396e-01 1.10431600e+00 1.04903683e-01
-1.54833063e-01 6.03631556e-01 2.28742689e-01 -3.29029232e-01
3.35492790e-01 4.35942365e-03 -3.29528540e-01 2.38557115e-01
-7.30535328e-01 -5.89155778e-02 5.11425853e-01 8.11547220e-01
6.41608298e-01 2.04732612e-01 -6.64365292e-01 7.09807217e-01
3.21438789e-01 8.64029229e-01 2.98239797e-01 -8.57284606e-01
3.90262812e-01 5.54495454e-01 8.35877657e-02 -1.28088582e+00
-4.53504324e-01 -6.14978790e-01 -7.41985261e-01 1.92865834e-01
-1.63884476e-01 -8.55037719e-02 -1.10216701e+00 1.74909842e+00
1.91788912e-01 7.04122126e-01 1.87457725e-03 1.12950873e+00
8.47084343e-01 7.99675822e-01 -1.11885078e-03 -1.18471883e-01
1.26876724e+00 -1.32430375e+00 -9.57414389e-01 -4.96978194e-01
1.30590901e-01 -5.84624827e-01 1.37691391e+00 3.61557193e-02
-4.54702437e-01 -6.27945244e-01 -1.47767889e+00 -2.45189682e-01
-7.01118350e-01 3.61792922e-01 6.16792798e-01 4.63866472e-01
-9.26258922e-01 2.44534671e-01 -5.83804190e-01 -2.19092771e-01
5.36852241e-01 1.68361247e-01 4.19240445e-01 1.81649141e-02
-1.25253820e+00 7.48147666e-01 1.34738624e-01 4.67939585e-01
-9.27481055e-01 -3.59617770e-01 -9.26041901e-01 1.60223335e-01
6.58706903e-01 -3.97418171e-01 1.14630365e+00 -9.22714651e-01
-1.30479014e+00 2.39929438e-01 -6.03254020e-01 -5.10987282e-01
3.16913754e-01 -5.60591996e-01 -5.98826349e-01 -3.09714694e-02
8.41567516e-02 2.86979705e-01 8.29532146e-01 -1.78695762e+00
-8.65667403e-01 -1.96189824e-02 2.25607991e-01 3.96687239e-01
-3.78101498e-01 -1.32440478e-01 -7.20286310e-01 -9.42347944e-01
6.20681383e-02 -8.63254547e-01 -1.75691515e-01 4.93928194e-02
-5.98361135e-01 1.24055952e-01 1.58844686e+00 -7.90383220e-01
1.49188042e+00 -1.92850065e+00 -1.50296912e-01 2.40895569e-01
2.28419825e-01 4.46922183e-01 1.39987737e-01 -5.46768941e-02
3.11516762e-01 -2.85151809e-01 -6.90212727e-01 -4.02601093e-01
-4.80136611e-02 4.95419741e-01 -8.10065866e-01 2.51199663e-01
9.29126143e-02 1.07313490e+00 -9.56267297e-01 -5.17463744e-01
3.90030533e-01 7.91099608e-01 -1.82575479e-01 4.09494400e-01
-1.94860935e-01 1.35844275e-01 -5.64366102e-01 8.97930145e-01
7.50856638e-01 -3.72638553e-01 3.07990223e-01 -4.23029959e-01
-1.57995149e-01 1.97032988e-01 -7.94241250e-01 1.36191034e+00
-7.78676748e-01 1.16211390e+00 -2.25554705e-01 -7.05259800e-01
7.26697326e-01 -2.41483644e-01 3.54884490e-02 -9.62793827e-01
2.04692736e-01 -7.02886283e-02 -2.46469527e-01 -4.78025168e-01
8.49475443e-01 3.44907165e-01 -8.33085403e-02 3.91104043e-01
-4.34685498e-01 4.07571375e-01 -4.88595039e-01 1.81358695e-01
1.22957516e+00 1.33294925e-01 1.04080044e-01 -2.77845532e-01
6.33252859e-01 -5.29343486e-01 8.41319501e-01 8.12489271e-01
-2.51439393e-01 6.97820961e-01 2.81759322e-01 -5.24851680e-01
-3.21551144e-01 -1.04585910e+00 1.39091954e-01 1.44292533e+00
7.40361214e-01 -2.29211301e-01 -5.35729945e-01 -1.01853502e+00
-8.15936401e-02 8.21232438e-01 -9.82541323e-01 -2.12011129e-01
-8.83240700e-01 -8.90654385e-01 3.53814632e-01 1.07689095e+00
1.15111637e+00 -1.32484496e+00 -1.13670433e+00 -1.06617190e-01
-3.59395146e-01 -1.26129889e+00 -4.59636271e-01 4.69133765e-01
-3.70992869e-01 -9.77187216e-01 -6.98629498e-01 -7.75331438e-01
6.06517255e-01 9.08793807e-01 1.05649555e+00 2.91662961e-01
-3.26909184e-01 2.54920870e-01 -3.64212632e-01 -7.15382457e-01
3.66063207e-01 1.52370587e-01 -3.00921500e-01 1.20176286e-01
7.19900504e-02 -5.96752048e-01 -1.09880745e+00 3.03326726e-01
-8.34291399e-01 9.95115191e-02 9.93526459e-01 8.85242522e-01
4.69480038e-01 -1.87290654e-01 2.87824363e-01 -9.76614833e-01
5.31066656e-01 -2.60270178e-01 -6.40849471e-01 5.33927023e-01
-4.93104637e-01 5.42823710e-02 4.95084256e-01 -4.91956249e-02
-1.58518600e+00 7.37235919e-02 1.50110424e-01 -2.36641243e-01
1.20852396e-01 1.05713837e-01 -4.41760153e-01 -3.54860812e-01
3.51846993e-01 5.34304857e-01 -6.54153764e-01 -5.17274737e-02
3.32382411e-01 4.27345008e-01 5.21875560e-01 -1.96920767e-01
9.26883042e-01 7.90307820e-01 -8.94885361e-02 -7.63613045e-01
-1.32389522e+00 -3.59932214e-01 -4.95902032e-01 -3.84564191e-01
8.67898405e-01 -7.98361957e-01 -7.98505485e-01 4.93589729e-01
-1.07514215e+00 -8.65339816e-01 1.26729369e-01 -1.28133848e-01
-2.89995819e-01 2.41536155e-01 -1.86299503e-01 -8.69695961e-01
-2.85169244e-01 -1.05548120e+00 1.30640030e+00 4.59391475e-01
3.13374341e-01 -1.04578280e+00 -1.21090651e-01 2.48373970e-02
6.05893731e-01 2.57492870e-01 6.61964834e-01 -1.38455015e-02
-1.07807398e+00 1.63492471e-01 -8.50929797e-01 3.45600903e-01
3.06359142e-01 -3.58840436e-01 -1.35527778e+00 1.06706873e-01
1.70893315e-02 -9.77685526e-02 1.42590368e+00 4.83426750e-01
1.93863821e+00 -3.04952443e-01 -5.48263431e-01 8.73260200e-01
1.53850400e+00 1.36045530e-01 7.76466429e-01 3.21482658e-01
1.10628772e+00 2.95447290e-01 8.36807311e-01 3.45109999e-01
5.47263980e-01 5.53985775e-01 6.37696922e-01 -4.24048245e-01
-3.48833114e-01 -6.33919388e-02 2.18823820e-01 3.76697272e-01
-1.07750140e-01 -5.73234141e-01 -6.95043087e-01 4.01038498e-01
-2.07858992e+00 -9.21365976e-01 1.41015187e-01 1.77930093e+00
4.85723704e-01 2.59519547e-01 -4.17842418e-01 -1.33507606e-03
5.15265763e-01 9.94650006e-01 -7.44601548e-01 -4.95027564e-02
-3.54857415e-01 -7.26687610e-02 7.87912309e-01 6.54322207e-01
-1.34732771e+00 1.33259737e+00 6.09528255e+00 7.51680434e-01
-1.36865926e+00 7.68468808e-03 7.00559318e-01 8.17566440e-02
-3.37159157e-01 -5.86497784e-02 -6.35441303e-01 6.43250763e-01
3.74733001e-01 4.48099405e-01 3.68885338e-01 8.26867282e-01
2.96339363e-01 -4.46087807e-01 -3.74595642e-01 6.99468732e-01
4.27764326e-01 -1.33570313e+00 -1.76033854e-01 -1.51016414e-01
7.38073766e-01 1.38030797e-01 1.80988491e-01 3.24784577e-01
3.16062540e-01 -9.60626006e-01 5.95357656e-01 6.73564374e-01
5.80586970e-01 -6.55459642e-01 7.49710381e-01 -9.55966562e-02
-1.61459434e+00 -4.60585445e-01 -4.64549959e-01 2.00588539e-01
1.85691714e-01 6.34304702e-01 -8.61194432e-01 4.12234813e-01
9.31749880e-01 7.25905895e-01 -6.53554022e-01 6.10996664e-01
-5.92274189e-01 6.65559888e-01 -5.84615022e-02 -3.16809654e-01
3.29429686e-01 7.25118145e-02 2.06090972e-01 1.48464763e+00
8.37977007e-02 2.42608771e-01 9.49560553e-02 5.76328516e-01
-1.94391757e-01 -3.86245579e-01 -5.31454623e-01 6.24665201e-01
5.41172028e-01 1.39224517e+00 -9.10630465e-01 -3.79133105e-01
-3.46156895e-01 1.33640099e+00 2.08403498e-01 7.07306564e-01
-1.41645980e+00 -6.53697908e-01 5.56953549e-01 -3.09096664e-01
3.93984228e-01 -2.18522802e-01 -4.39848721e-01 -7.84847617e-01
1.45472169e-01 -3.97103846e-01 9.78414342e-02 -1.21226335e+00
-7.20838487e-01 5.84210992e-01 -2.67594606e-01 -9.96541858e-01
2.84708709e-01 -7.42433608e-01 -9.57197607e-01 6.61084056e-01
-2.21285415e+00 -1.47104502e+00 -1.22313976e+00 5.39449096e-01
7.04556346e-01 6.54911771e-02 4.20274973e-01 1.55199364e-01
-6.76571727e-01 5.84876716e-01 -5.32035381e-02 2.02713236e-01
7.50746310e-01 -1.29937458e+00 4.25380647e-01 9.74806726e-01
-1.99203610e-01 4.14881378e-01 4.88486141e-01 -6.96254730e-01
-1.11352289e+00 -1.53547823e+00 7.48917282e-01 -3.11791211e-01
4.10917282e-01 -4.94899541e-01 -8.66275132e-01 5.28051674e-01
2.76293516e-01 2.89999545e-01 4.95728850e-01 -9.40343440e-02
-3.68819743e-01 -3.65970105e-01 -7.28441477e-01 9.10766602e-01
1.56622720e+00 -6.69857442e-01 -3.39212775e-01 3.55507731e-01
1.09345257e+00 -5.25793731e-01 -6.31927997e-02 7.11001992e-01
6.35089636e-01 -1.28064418e+00 1.20349169e+00 4.77178060e-02
2.60847390e-01 -4.75827694e-01 -5.40721059e-01 -9.82003808e-01
-2.16248870e-01 -3.44081581e-01 -5.21118581e-01 9.64187682e-01
2.41536453e-01 -5.95394731e-01 8.26934278e-01 5.11087812e-02
-5.13842821e-01 -1.33937860e+00 -6.59356356e-01 -5.22553146e-01
-6.44044280e-01 -4.45325226e-01 7.20195293e-01 5.18111885e-01
-6.79592311e-01 2.19145417e-01 -5.72031021e-01 5.74493706e-01
3.85220349e-01 4.64860022e-01 5.66108048e-01 -7.33547390e-01
4.58265506e-02 -3.97832513e-01 -1.79497257e-03 -1.42153537e+00
2.39976749e-01 -3.55202585e-01 5.99262595e-01 -1.62670112e+00
3.21304947e-01 -3.96473795e-01 -6.24941230e-01 5.79389513e-01
-5.65157712e-01 2.64643282e-01 1.47385016e-01 2.31779013e-02
-9.65597212e-01 1.06932390e+00 1.04900742e+00 -1.20100446e-01
-5.06666563e-02 1.09266952e-01 -6.41022503e-01 8.76417875e-01
8.37839544e-01 -1.40991926e-01 -6.44962132e-01 -5.72705030e-01
-1.17754921e-01 -3.88272077e-01 7.34799027e-01 -1.27776551e+00
3.01333696e-01 -3.17657799e-01 7.20055461e-01 -1.04112804e+00
7.08942652e-01 -8.16245615e-01 -6.96723521e-01 4.39685613e-01
-2.79426455e-01 -6.02285266e-02 2.77441014e-02 8.98087084e-01
2.20872890e-02 3.04133505e-01 5.57439208e-01 1.46062076e-01
-1.26257372e+00 1.50428951e-01 -2.29338497e-01 -1.23922355e-01
8.34414780e-01 -1.23953566e-01 -5.11472046e-01 -5.09417415e-01
-9.20304582e-02 3.04216862e-01 1.83775902e-01 3.76397192e-01
1.06075811e+00 -1.31568396e+00 -7.00536817e-02 1.27204090e-01
7.70710632e-02 5.41124074e-03 2.54470378e-01 5.92202246e-01
-4.89579260e-01 4.25978422e-01 3.10697779e-02 -5.32342970e-01
-1.22846198e+00 1.71050549e-01 4.18776602e-01 -1.85936883e-01
-5.83159089e-01 1.01931417e+00 6.19359732e-01 -2.65098721e-01
5.92205524e-01 -5.46459198e-01 -2.53876179e-01 -2.28614584e-01
4.41650629e-01 2.78564543e-01 -1.72052816e-01 -5.42611063e-01
-3.64338070e-01 5.88926017e-01 2.83466190e-01 7.86892772e-02
1.14666319e+00 -2.06031680e-01 1.04219824e-01 3.31385553e-01
1.17996931e+00 8.04660395e-02 -1.75559473e+00 -3.06585878e-01
-1.24718852e-01 -4.71566081e-01 1.98462874e-01 -1.05600929e+00
-1.24336278e+00 8.72590303e-01 8.50374043e-01 1.68529071e-03
1.50993562e+00 -1.93133935e-01 1.05693328e+00 7.62707949e-01
1.14241228e-01 -1.28486550e+00 5.10036588e-01 8.21254432e-01
9.66457367e-01 -1.49328899e+00 1.42027184e-01 -4.08704370e-01
-7.05551863e-01 8.51291001e-01 8.40536475e-01 -2.24282935e-01
8.26509178e-01 2.30631217e-01 1.55348137e-01 -2.09927082e-01
-3.62266749e-01 -4.15815830e-01 4.06719953e-01 5.38277090e-01
1.48594126e-01 3.32789533e-02 1.11300156e-01 5.93680024e-01
8.65352526e-02 -3.58146399e-01 1.50857344e-01 1.15694547e+00
-7.75705695e-01 -6.38728261e-01 -2.41608977e-01 2.83305973e-01
-8.72144923e-02 -2.71920174e-01 -5.94742060e-01 7.05848038e-01
2.42303416e-01 8.18449020e-01 -1.55197605e-01 -7.24324226e-01
1.56003356e-01 -3.47018391e-01 2.66936403e-02 -2.99920976e-01
-1.33227259e-01 -2.59527594e-01 -1.35063857e-01 -8.73581469e-01
-5.13103545e-01 -2.71046430e-01 -1.45174539e+00 -1.80039834e-02
-3.15093517e-01 -1.77782565e-01 6.21117413e-01 1.12930238e+00
4.08933014e-01 1.34476030e+00 8.52127612e-01 -1.04274285e+00
-2.87651405e-04 -6.01234198e-01 -2.12778434e-01 -9.87863168e-02
6.80702627e-01 -8.55420530e-01 -1.12275437e-01 -1.88623294e-01] | [10.854467391967773, -4.114120960235596] |
1defcf2f-1cb5-4fdc-9418-5a4dd052c190 | team-triple-check-at-factify-2-parameter | 2302.07740 | null | https://arxiv.org/abs/2302.07740v1 | https://arxiv.org/pdf/2302.07740v1.pdf | Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation Models with Feature Representations for Multi-Modal Fact Verification | Multi-modal fact verification has become an important but challenging issue on social media due to the mismatch between the text and images in the misinformation of news content, which has been addressed by considering cross-modalities to identify the veracity of the news in recent years. In this paper, we propose the Pre-CoFactv2 framework with new parameter-efficient foundation models for modeling fine-grained text and input embeddings with lightening parameters, multi-modal multi-type fusion for not only capturing relations for the same and different modalities but also for different types (i.e., claim and document), and feature representations for explicitly providing metadata for each sample. In addition, we introduce a unified ensemble method to boost model performance by adjusting the importance of each trained model with not only the weights but also the powers. Extensive experiments show that Pre-CoFactv2 outperforms Pre-CoFact by a large margin and achieved new state-of-the-art results at the Factify challenge at AAAI 2023. We further illustrate model variations to verify the relative contributions of different components. Our team won the first prize (F1-score: 81.82%) and we made our code publicly available at https://github.com/wwweiwei/Pre-CoFactv2-AAAI-2023. | ['Wen-Chih Peng', 'Wei-Yao Wang', 'Hong-Wei Wu', 'Wei-Wei Du'] | 2023-02-12 | null | null | null | null | ['fact-verification'] | ['natural-language-processing'] | [-2.61380076e-01 -8.05261061e-02 -2.92466938e-01 -2.58052200e-01
-1.20751190e+00 -7.25973904e-01 1.16878498e+00 2.45509237e-01
-3.68300587e-01 5.20242631e-01 9.25443769e-01 1.57955606e-02
4.75021973e-02 -4.48090583e-01 -1.00123024e+00 -2.63567746e-01
2.02287152e-01 4.37628567e-01 5.74516580e-02 -1.56295463e-01
3.71562652e-02 -8.72219428e-02 -1.34708893e+00 9.37344491e-01
5.89714646e-01 1.28747773e+00 -2.67189950e-01 4.85429525e-01
-3.37467678e-02 8.70292366e-01 -2.68963337e-01 -1.26678240e+00
2.40244150e-01 -5.95596209e-02 -7.91730464e-01 1.99606925e-01
7.48533785e-01 -1.79116547e-01 -7.26301193e-01 1.15596104e+00
3.10109675e-01 -1.88224792e-01 7.48907924e-01 -1.35214055e+00
-1.07249534e+00 9.09421384e-01 -8.13293755e-01 3.65566283e-01
2.03686118e-01 -5.49480729e-02 1.34044516e+00 -1.17976320e+00
8.02211761e-01 1.09477198e+00 7.14068890e-01 3.09045672e-01
-1.06555569e+00 -6.04165137e-01 7.43783340e-02 7.77488232e-01
-1.37302351e+00 -5.99203289e-01 6.31008625e-01 -7.09241033e-01
3.46932977e-01 3.26487422e-01 2.09005341e-01 1.42918718e+00
4.04948555e-02 1.00921631e+00 1.37925637e+00 -1.58248633e-01
-2.44245797e-01 3.61848444e-01 2.40678385e-01 6.70364022e-01
1.93410575e-01 -1.74609363e-01 -6.67119384e-01 -4.38955307e-01
2.40760222e-01 1.45536333e-01 -4.09046799e-01 -2.15543434e-01
-1.46677506e+00 9.70470548e-01 4.85767990e-01 4.01881605e-01
-5.37415504e-01 4.52961363e-02 5.90858877e-01 1.82258368e-01
7.32524574e-01 2.35590026e-01 -4.24267977e-01 2.10309547e-04
-9.05705750e-01 3.29759628e-01 5.19922614e-01 6.21466517e-01
2.97824144e-01 -4.79265153e-01 -4.73929286e-01 1.00157285e+00
2.52079636e-01 4.21759248e-01 3.79951268e-01 -9.36380863e-01
8.87519896e-01 7.35171974e-01 2.64941901e-01 -1.37385285e+00
-3.14499319e-01 -6.42681718e-01 -1.17957485e+00 -1.77228138e-01
3.47411722e-01 8.85222256e-02 -6.41056299e-01 1.65487742e+00
4.73739743e-01 2.77499557e-01 -1.55122643e-02 8.39469075e-01
9.71235156e-01 5.72566986e-01 -1.07109630e-02 -1.17287757e-02
1.89180183e+00 -9.95036304e-01 -7.71441042e-01 -1.07794948e-01
3.95715207e-01 -8.38224411e-01 8.09270740e-01 1.30673587e-01
-8.77998054e-01 -3.06282252e-01 -8.98152292e-01 -2.02956274e-01
-5.43004036e-01 3.31622452e-01 2.61179864e-01 2.68594056e-01
-5.76533079e-01 1.59656376e-01 -3.32771629e-01 4.27486189e-02
6.38312459e-01 -4.90746170e-01 -6.47873223e-01 -3.80360723e-01
-1.53761101e+00 9.33323622e-01 2.97844559e-01 -6.51080385e-02
-5.59929430e-01 -7.08506882e-01 -6.48806870e-01 -4.28512599e-03
6.01117074e-01 -6.35939419e-01 8.80735755e-01 -6.04711413e-01
-7.60553062e-01 1.02195573e+00 -6.96646273e-02 -6.90202951e-01
8.65994453e-01 -2.74488688e-01 -9.63742793e-01 1.94597110e-01
1.61993966e-01 1.96834117e-01 6.90353394e-01 -1.49653876e+00
-5.14960766e-01 -4.05023098e-01 1.67800367e-01 2.85935365e-02
-2.99309790e-01 1.76614642e-01 -5.74368536e-01 -7.31346667e-01
-2.24132016e-02 -8.96963656e-01 3.16365868e-01 5.43242767e-02
-5.08762419e-01 -2.93772906e-01 5.40729105e-01 -1.05740559e+00
1.26598644e+00 -2.13246512e+00 3.95892970e-02 -7.37161860e-02
5.82218528e-01 1.39023408e-01 -1.55827746e-01 4.05918449e-01
1.03069820e-01 3.07571709e-01 -8.82921442e-02 -5.33176363e-01
2.34460935e-01 -8.73587057e-02 -4.57557499e-01 5.91863573e-01
-3.02336607e-02 9.98456538e-01 -6.73738360e-01 -5.00429928e-01
-1.89130068e-01 6.56941175e-01 -2.13046074e-01 -1.52992994e-01
-1.31542251e-01 1.12425931e-01 -1.67181328e-01 5.61822712e-01
7.52991974e-01 -6.69100404e-01 1.73461094e-01 -8.62036586e-01
1.87441751e-01 1.81413695e-01 -1.23046148e+00 1.33221281e+00
-3.05867463e-01 4.62432206e-01 2.06675112e-01 -7.05130577e-01
3.93599629e-01 4.98562664e-01 4.10316676e-01 -5.79465330e-01
2.96008468e-01 1.16421878e-01 -3.46604794e-01 -4.89746749e-01
7.66187191e-01 -9.93863940e-02 -2.92267472e-01 4.93470699e-01
1.05449289e-01 2.79363215e-01 2.40949810e-01 6.56743169e-01
6.52099490e-01 -2.38266632e-01 1.81509703e-01 1.44499987e-01
3.73100936e-01 -1.31875962e-01 3.93386453e-01 6.44830644e-01
-1.91175580e-01 7.26768911e-01 3.40991795e-01 -2.26131603e-01
-1.07551003e+00 -6.64846778e-01 -1.80254295e-01 9.28472638e-01
1.09025121e-01 -4.57554847e-01 -2.19512716e-01 -1.01058722e+00
1.98970929e-01 8.33176076e-01 -9.39689696e-01 1.51014656e-01
-2.18652278e-01 -7.59786367e-01 5.46438694e-01 2.91299254e-01
5.93799353e-01 -4.03400213e-01 1.14777476e-01 -4.65899296e-02
-9.38744843e-01 -1.39700472e+00 -6.38267815e-01 -4.91758019e-01
-1.19047746e-01 -1.36680126e+00 -6.66101277e-01 -3.00404519e-01
2.62805313e-01 4.23358709e-01 9.79701459e-01 1.32253677e-01
1.81545272e-01 3.44747305e-01 -5.16805053e-01 -1.77162260e-01
-3.41709554e-01 -2.12941945e-01 1.79380421e-02 6.65592074e-01
6.48241788e-02 -1.28417119e-01 -4.19514805e-01 2.80182600e-01
-1.12145376e+00 2.25255847e-01 2.85831809e-01 8.50683987e-01
4.60422277e-01 1.10672619e-02 3.99810910e-01 -9.21789289e-01
5.71658790e-01 -9.73261476e-01 -2.26013005e-01 5.72082758e-01
-6.26861572e-01 -2.28231505e-01 3.41152221e-01 -3.85509312e-01
-8.98427904e-01 -5.83291411e-01 8.21366310e-02 -4.06044245e-01
3.12561959e-01 9.11653936e-01 -5.60139492e-02 3.87498558e-01
5.68056226e-01 1.19511791e-01 -1.81686893e-01 -5.04293859e-01
6.96579754e-01 8.38589847e-01 5.54109275e-01 -3.32521439e-01
9.40472484e-01 6.25283599e-01 -3.54628593e-01 -2.90118366e-01
-1.45889544e+00 -5.21323562e-01 -1.66595355e-01 -2.91323304e-01
5.94044030e-01 -1.28446722e+00 -5.49699128e-01 6.06879175e-01
-1.06173968e+00 2.12543935e-01 -1.08946517e-01 5.20429730e-01
-7.58211315e-02 4.51635212e-01 -7.47769535e-01 -6.71412706e-01
-1.97876006e-01 -7.77899861e-01 6.14810944e-01 -1.53264493e-01
1.25509426e-01 -8.47031176e-01 -6.95864260e-02 1.15411484e+00
4.06265587e-01 1.75463110e-01 6.17340744e-01 -9.63829756e-01
-3.54257822e-01 -4.51686352e-01 -6.63684726e-01 4.21299070e-01
-2.55100042e-01 -1.61610171e-01 -9.36945796e-01 -1.38430163e-01
-6.76389784e-02 -4.73362267e-01 1.35279453e+00 8.83227065e-02
1.03231049e+00 -7.67003953e-01 -7.94614106e-02 2.42014915e-01
1.35339296e+00 -6.41476393e-01 5.53529084e-01 4.81064558e-01
7.67297924e-01 3.27164531e-01 4.56363142e-01 4.67234939e-01
9.78145540e-01 8.13085616e-01 4.89615232e-01 2.33736604e-01
-4.11948711e-01 -3.74292880e-01 2.43627921e-01 8.43557358e-01
-1.52263165e-01 -5.38347900e-01 -7.97890007e-01 7.45121717e-01
-1.88084066e+00 -1.44443333e+00 -2.98989147e-01 1.89131415e+00
9.36472654e-01 -3.62909702e-03 8.50251913e-02 -1.00080511e-02
8.47067893e-01 5.29265523e-01 -2.13238508e-01 2.03092754e-01
-7.15066075e-01 -5.60449958e-01 5.91531694e-01 5.74168324e-01
-1.30221868e+00 4.27434564e-01 5.16093969e+00 1.04783618e+00
-7.31938899e-01 8.50501716e-01 6.05037630e-01 -1.56051934e-01
-6.97245598e-01 -2.12175716e-02 -6.97860599e-01 7.70398557e-01
7.16798365e-01 -1.81361109e-01 3.01415503e-01 4.80762511e-01
-3.06291282e-01 2.29678378e-01 -5.04468024e-01 8.75506520e-01
5.16870022e-01 -1.97753990e+00 4.30001412e-03 2.51441598e-01
1.00439763e+00 4.45077449e-01 1.15860358e-01 5.09617388e-01
2.40938261e-01 -5.97699046e-01 1.07361698e+00 6.80096924e-01
8.19589853e-01 -3.74131113e-01 1.04308617e+00 2.78860062e-01
-9.46878493e-01 -1.93125784e-01 -2.01477651e-02 3.47580910e-01
3.60226363e-01 1.02676857e+00 -4.08041447e-01 8.82369637e-01
5.45195818e-01 6.63597703e-01 -6.83240116e-01 8.66083980e-01
-9.37874764e-02 6.33121908e-01 -2.23441243e-01 2.21969649e-01
3.92217487e-02 3.09505939e-01 5.82379460e-01 1.11886752e+00
3.74180704e-01 -6.06922247e-02 1.51007414e-01 6.13661468e-01
-7.69126236e-01 -2.93306541e-02 -5.58657199e-02 -1.64788023e-01
5.96536636e-01 1.29870629e+00 -1.35345399e-01 -6.58446848e-01
-5.64125836e-01 8.16688478e-01 4.91837323e-01 2.81873882e-01
-1.08328307e+00 2.51847655e-01 3.13082159e-01 2.25938872e-01
4.66250032e-01 -1.77603364e-01 -8.31668302e-02 -1.70401168e+00
1.36309609e-01 -7.97300339e-01 7.07543135e-01 -8.37594807e-01
-1.81219769e+00 6.27427399e-01 -1.45228237e-01 -1.26935375e+00
1.61530733e-01 -4.35150385e-01 -1.17032953e-01 7.59905934e-01
-1.65069652e+00 -1.66125011e+00 -1.01047136e-01 5.75063348e-01
1.28992319e-01 -3.13219011e-01 5.56173086e-01 4.74480838e-01
-3.65328014e-01 6.96880639e-01 3.60231638e-01 2.90626228e-01
9.00910079e-01 -8.76529157e-01 8.35163891e-02 9.28243220e-01
3.45811248e-01 3.08696657e-01 6.81726456e-01 -6.61202788e-01
-1.08002138e+00 -1.08364451e+00 1.32318854e+00 -6.30643547e-01
1.09223759e+00 -2.11788073e-01 -8.79181147e-01 7.67924726e-01
3.04139197e-01 2.17798844e-01 7.78189659e-01 3.73622358e-01
-1.11113477e+00 -3.79400514e-02 -1.17401636e+00 3.65127206e-01
6.81922317e-01 -8.01293015e-01 -5.69100022e-01 5.15115440e-01
5.94259381e-01 -3.41617763e-01 -9.55289721e-01 1.83071747e-01
5.48066318e-01 -8.76595259e-01 9.13590729e-01 -6.18173778e-01
8.48714590e-01 -3.87902051e-01 -6.70320749e-01 -1.19956338e+00
-6.23490274e-01 -4.55434956e-02 -5.96422076e-01 1.50725961e+00
5.82940757e-01 -6.13906860e-01 1.80709139e-01 4.61354375e-01
1.06656015e-01 -6.18159652e-01 -1.25125539e+00 -6.39692307e-01
-1.38007700e-01 -6.37028933e-01 5.91705859e-01 1.33216786e+00
-4.29345593e-02 3.40755045e-01 -8.48625779e-01 3.93357605e-01
5.94411016e-01 3.86490703e-01 5.64086616e-01 -1.02914500e+00
-2.71879435e-01 -4.17353362e-01 -3.54455262e-01 -7.51751840e-01
6.70745596e-02 -1.15954936e+00 -3.39445025e-01 -1.56732738e+00
8.42571855e-01 -2.78691649e-01 -4.07358706e-01 5.30570149e-01
-3.97490114e-01 4.65383053e-01 4.53580827e-01 5.87076366e-01
-6.82275057e-01 5.76886356e-01 1.07050824e+00 -4.20146316e-01
6.80525661e-01 -1.63359508e-01 -9.19363678e-01 5.08671582e-01
5.69778562e-01 -3.92830849e-01 1.40330106e-01 -5.76307416e-01
5.29825389e-01 -1.04965352e-01 9.71749187e-01 -8.19621801e-01
1.91044554e-01 -1.44336164e-01 2.77861118e-01 -5.41660011e-01
5.64643323e-01 -8.46676350e-01 1.70946091e-01 1.19032129e-03
-6.29139900e-01 -4.35666107e-02 -1.51984051e-01 9.65709686e-01
-3.18098307e-01 -1.40783876e-01 4.59076792e-01 -6.14991970e-02
-5.41562736e-01 4.00264353e-01 6.58255294e-02 3.41488987e-01
6.31991208e-01 3.41011584e-01 -9.93519127e-01 -5.78061044e-01
-6.63951457e-01 1.80098966e-01 3.50948364e-01 5.74896395e-01
4.13473368e-01 -1.65919137e+00 -1.34299648e+00 -1.80733681e-01
5.28991818e-01 -6.99304402e-01 9.19111431e-01 1.20467567e+00
1.42280683e-01 1.69160381e-01 1.17224492e-01 -1.51795715e-01
-1.29442132e+00 6.58812582e-01 -7.26645514e-02 -5.88572741e-01
-3.87534291e-01 8.77382278e-01 -1.89677551e-01 -3.70304227e-01
-6.72590733e-02 5.49055673e-02 -2.00374544e-01 4.05077696e-01
8.79025340e-01 2.69373745e-01 2.87017468e-02 -1.22761679e+00
-4.53621328e-01 2.55540729e-01 -2.19406664e-01 -1.13232657e-01
1.33766031e+00 -4.08101648e-01 1.27542794e-01 5.32631338e-01
1.36287987e+00 3.71260077e-01 -8.95763516e-01 -8.79429340e-01
-4.10825580e-01 -5.59931695e-01 3.15372825e-01 -1.27802932e+00
-1.21565866e+00 5.00313878e-01 4.11999285e-01 4.31486547e-01
5.72713912e-01 4.73472983e-01 9.27601576e-01 -2.51646340e-01
1.57395810e-01 -1.10635936e+00 -3.73855866e-02 5.21549284e-01
1.37285280e+00 -1.53019810e+00 3.92739803e-01 -2.45130494e-01
-1.05830634e+00 7.71374226e-01 4.82004955e-02 1.06741816e-01
7.21440911e-01 -2.45195374e-01 6.97337613e-02 -4.65571433e-01
-7.92131186e-01 -5.10056056e-02 7.46095121e-01 1.50061369e-01
3.17631900e-01 3.57254118e-01 -3.14071387e-01 9.05826688e-01
9.64719057e-03 -1.51399020e-02 4.24489051e-01 5.67811370e-01
-9.86186266e-02 -7.23737061e-01 -3.75283867e-01 6.12164736e-01
-6.26585424e-01 -5.37670664e-02 -5.67037128e-02 5.45044184e-01
2.96861082e-01 9.35750246e-01 -2.60764807e-01 -7.27208614e-01
2.04242513e-01 1.26912758e-01 1.97609767e-01 -1.52005017e-01
-5.04027367e-01 -1.19510874e-01 5.92406690e-01 -2.98398197e-01
-6.46647990e-01 -8.12920213e-01 -7.29251802e-01 -5.74992597e-01
-3.67321551e-01 6.81802556e-02 7.80427814e-01 9.89832282e-01
8.43103051e-01 2.14085847e-01 5.63122272e-01 -5.79439282e-01
-6.60113811e-01 -1.24389374e+00 -6.04073763e-01 8.12260628e-01
3.70516747e-01 -7.92870879e-01 -6.07659519e-01 5.74455783e-02] | [8.226394653320312, 10.254549980163574] |
2a8a523a-2c45-4d6d-98f2-9ea481d167f9 | relation-adversarial-network-for-low-resource | 1911.03091 | null | https://arxiv.org/abs/1911.03091v6 | https://arxiv.org/pdf/1911.03091v6.pdf | Relation Adversarial Network for Low Resource Knowledge Graph Completion | Knowledge Graph Completion (KGC) has been proposed to improve Knowledge Graphs by filling in missing connections via link prediction or relation extraction. One of the main difficulties for KGC is a low resource problem. Previous approaches assume sufficient training triples to learn versatile vectors for entities and relations, or a satisfactory number of labeled sentences to train a competent relation extraction model. However, low resource relations are very common in KGs, and those newly added relations often do not have many known samples for training. In this work, we aim at predicting new facts under a challenging setting where only limited training instances are available. We propose a general framework called Weighted Relation Adversarial Network, which utilizes an adversarial procedure to help adapt knowledge/features learned from high resource relations to different but related low resource relations. Specifically, the framework takes advantage of a relation discriminator to distinguish between samples from different relations, and help learn relation-invariant features more transferable from source relations to target relations. Experimental results show that the proposed approach outperforms previous methods regarding low resource settings for both link prediction and relation extraction. | ['Huajun Chen', 'Wei zhang', 'Ningyu Zhang', 'Jiaoayan Chen', 'Shumin Deng', 'Zhanlin Sun'] | 2019-11-08 | null | null | null | null | ['partial-domain-adaptation'] | ['methodology'] | [ 1.89102843e-01 6.64879978e-01 -7.08083034e-01 -3.14628601e-01
-5.31000257e-01 -5.05012810e-01 5.87379754e-01 3.83258224e-01
-2.60149330e-01 1.32354522e+00 6.31429404e-02 -1.91592783e-01
-2.57850021e-01 -1.36748898e+00 -8.35727572e-01 -1.98388070e-01
-2.81263441e-01 8.24229300e-01 2.01125965e-01 -5.49363494e-01
-5.89575291e-01 5.83873808e-01 -1.05319619e+00 2.45439947e-01
1.18316305e+00 8.20121229e-01 -2.25834653e-01 1.95395306e-01
-3.15643877e-01 1.12219870e+00 -4.84136164e-01 -1.15845251e+00
2.17602938e-01 -1.83449820e-01 -1.30822897e+00 -3.56839359e-01
3.04923095e-02 7.39220977e-02 -6.42788351e-01 1.04949820e+00
1.85762972e-01 3.40226591e-01 6.78399146e-01 -1.39050686e+00
-9.53553796e-01 1.21491230e+00 -2.48591632e-01 1.85746223e-01
5.52932203e-01 -3.23730826e-01 1.26771700e+00 -9.49612081e-01
9.81474280e-01 1.14897764e+00 5.84235430e-01 5.40086627e-01
-1.05578291e+00 -7.68900692e-01 7.06111267e-02 5.96887648e-01
-1.52464426e+00 -4.85396534e-01 8.57099891e-01 -1.69600174e-01
1.04938018e+00 1.81573555e-01 4.96281594e-01 1.17180073e+00
-3.42329651e-01 6.04971290e-01 7.64540136e-01 -5.78932703e-01
-1.32528663e-01 4.45016235e-01 2.16097444e-01 6.34465933e-01
6.46548152e-01 -2.44285583e-01 -6.59878612e-01 -4.64469679e-02
4.81846273e-01 -1.70238957e-01 -5.12179971e-01 -4.37065512e-01
-9.84441698e-01 6.48002088e-01 8.66871893e-01 3.51007015e-01
-1.76623628e-01 -2.95896918e-01 4.52041745e-01 4.65408534e-01
6.59201443e-01 5.55942893e-01 -8.49554837e-01 2.45348826e-01
-2.12806880e-01 -1.85213666e-02 1.01345551e+00 1.41228402e+00
9.79147792e-01 -1.09808691e-01 -1.66943729e-01 9.04012978e-01
2.42872946e-02 4.47751790e-01 2.44833857e-01 -3.77338469e-01
1.27454126e+00 1.03298056e+00 -2.02277049e-01 -1.28765535e+00
-3.92144412e-01 -4.13424671e-01 -1.13783669e+00 -3.65183234e-01
2.56887764e-01 -1.06589735e-01 -5.53368986e-01 1.62768698e+00
5.95736206e-01 2.77004212e-01 6.69196308e-01 5.49154043e-01
1.30164123e+00 2.54370958e-01 1.81120798e-01 -3.51221114e-01
1.17671120e+00 -8.63639832e-01 -8.19043815e-01 -2.75451064e-01
8.74484777e-01 -3.43788862e-01 8.09893429e-01 -1.90712288e-01
-7.75842130e-01 -3.81388843e-01 -1.07200861e+00 -1.93974689e-01
-9.27561045e-01 -1.46849349e-03 1.24282444e+00 5.57316601e-01
-3.96501690e-01 7.33926356e-01 -4.73749787e-01 -2.25328088e-01
7.81075597e-01 4.75468397e-01 -9.82434869e-01 -5.05528510e-01
-1.90683687e+00 1.19408417e+00 1.01968431e+00 3.90124351e-01
-3.15325975e-01 -6.62832022e-01 -1.31852281e+00 1.77896306e-01
9.92670596e-01 -7.05940723e-01 4.13453847e-01 -4.70436305e-01
-1.21440899e+00 6.61882818e-01 1.98747844e-01 -5.73045492e-01
2.24265978e-01 -2.80226558e-01 -7.51140177e-01 2.98774689e-02
2.33776737e-02 2.45330967e-02 4.56753880e-01 -1.36332810e+00
-3.84711146e-01 -3.30293030e-01 4.42248732e-01 3.38408977e-01
-5.17917991e-01 -1.79450542e-01 -4.95711714e-01 -4.48772162e-01
3.81439715e-03 -5.33236623e-01 -6.24374822e-02 -6.82780206e-01
-8.60162079e-01 -2.55596548e-01 5.28914869e-01 -5.75832069e-01
9.09023166e-01 -1.45672750e+00 2.35746801e-01 5.50018430e-01
3.48685384e-01 6.90719604e-01 -1.26412839e-01 3.57162684e-01
-2.64096528e-01 2.32904822e-01 3.41676921e-02 2.72916760e-02
-2.56082296e-01 5.30158341e-01 -1.59265384e-01 1.80192925e-02
5.15325010e-01 1.19413316e+00 -1.09777975e+00 -7.42148161e-01
-1.14225402e-01 3.51043582e-01 -1.64192408e-01 2.10768431e-01
-7.83572346e-02 4.59840208e-01 -6.01493597e-01 6.38324022e-01
7.63177216e-01 -2.97647834e-01 6.40949965e-01 -4.82230216e-01
8.18245828e-01 2.58481085e-01 -1.18504989e+00 1.44917834e+00
-6.33982062e-01 5.10492958e-02 -4.40181881e-01 -1.38949025e+00
1.07100153e+00 3.46182495e-01 3.23232085e-01 -2.39648685e-01
6.63788542e-02 3.78142460e-03 -1.86898131e-02 -6.31163538e-01
4.36667681e-01 -1.33137539e-01 9.57336947e-02 -1.28457258e-02
5.91569483e-01 -5.31127453e-02 3.42051834e-01 5.29874861e-01
1.31293774e+00 1.20220199e-01 6.24608755e-01 4.06504571e-01
7.84466207e-01 -1.00061618e-01 9.87984836e-01 3.89794320e-01
1.31922826e-01 1.04954392e-01 6.88696206e-01 -2.83236265e-01
-5.12036860e-01 -8.46939623e-01 9.80040953e-02 6.22959435e-01
1.88765332e-01 -6.72398150e-01 -1.52583599e-01 -1.39577651e+00
3.35086510e-02 5.64358413e-01 -7.42630124e-01 -4.69164282e-01
-5.45750320e-01 -6.79603577e-01 5.54472685e-01 5.27058005e-01
5.13960004e-01 -1.17546415e+00 4.32135463e-01 1.35566458e-01
-2.43556589e-01 -1.71466541e+00 5.44216000e-02 2.23858625e-01
-5.73798239e-01 -1.58718288e+00 -1.60469592e-01 -7.70503938e-01
8.56240571e-01 -9.06770527e-02 1.38278890e+00 9.77543890e-02
-4.92562354e-02 1.27240598e-01 -7.43046701e-01 -1.08767405e-01
-3.72487098e-01 5.04343152e-01 2.26041928e-01 6.77051395e-02
4.10498649e-01 -6.73076749e-01 3.40714492e-02 1.50214210e-02
-6.57434106e-01 7.90412258e-03 6.61940992e-01 1.07461417e+00
5.19844532e-01 4.72683460e-01 8.27593505e-01 -1.87008440e+00
5.52907407e-01 -6.61384881e-01 -1.76948830e-01 8.43099177e-01
-7.50236273e-01 1.25635743e-01 8.86258006e-01 -3.93617898e-01
-1.29746008e+00 -3.45678702e-02 1.45372957e-01 -4.09907728e-01
1.69741333e-01 8.62132311e-01 -8.67285669e-01 -1.71303675e-01
8.14074337e-01 -1.48178101e-01 -4.13839132e-01 -1.96958378e-01
7.60537267e-01 1.65488243e-01 3.92852634e-01 -9.02222514e-01
1.39276373e+00 1.37067348e-01 4.00627196e-01 -1.83749795e-01
-1.25302231e+00 -2.42417619e-01 -1.08296645e+00 9.91140306e-02
4.71330047e-01 -9.14849460e-01 -7.00388610e-01 -1.66360393e-01
-1.04763854e+00 -1.33473754e-01 -6.69036031e-01 5.84215343e-01
-1.79017901e-01 1.88117474e-01 -6.16014063e-01 -5.72660804e-01
-4.19813305e-01 -6.32639706e-01 3.56108606e-01 3.45828414e-01
1.90951601e-01 -1.25260055e+00 -1.15045629e-01 5.50147772e-01
2.76043732e-02 3.85533571e-01 1.05549896e+00 -1.15462673e+00
-6.04237437e-01 -5.62255979e-01 -3.81969064e-01 3.72784197e-01
4.70219731e-01 -3.61547738e-01 -7.25648642e-01 5.79821737e-03
-5.44513822e-01 -7.22313464e-01 7.71672130e-01 -4.26712036e-01
8.69369447e-01 -3.64319593e-01 -6.08180761e-01 5.52051187e-01
1.26441407e+00 -1.34848177e-01 6.74389303e-01 6.41566738e-02
1.34730589e+00 7.01654673e-01 9.31901872e-01 -3.36070471e-02
6.38081133e-01 5.77546000e-01 5.82045577e-02 3.23036429e-03
-1.90828428e-01 -4.84527379e-01 -2.27227528e-02 9.78614867e-01
-6.67454422e-01 -1.48547187e-01 -8.77972484e-01 4.16915447e-01
-1.87359953e+00 -7.85150290e-01 -3.93960550e-02 1.97801042e+00
1.37029397e+00 2.13090971e-01 -3.53279173e-01 1.89602390e-01
6.75074697e-01 -1.01149522e-01 -4.46541667e-01 1.17388405e-01
-3.45805556e-01 5.98592997e-01 5.33608198e-01 4.40970093e-01
-1.06612849e+00 1.35100341e+00 4.91923332e+00 1.02601933e+00
-3.76984596e-01 1.57889560e-01 2.80458808e-01 3.18856925e-01
-4.25106317e-01 2.61250436e-01 -8.08156252e-01 -9.45739076e-02
6.84534848e-01 -3.18183005e-01 3.40717375e-01 7.92609334e-01
-5.44624448e-01 2.42957175e-01 -1.17601883e+00 8.22309911e-01
1.33881629e-01 -1.25401008e+00 1.29916131e-01 -2.22567096e-01
7.39363492e-01 -5.39426744e-01 -2.91503787e-01 8.42191637e-01
6.87031150e-01 -1.10377038e+00 -1.91744804e-01 6.85179055e-01
9.86366153e-01 -8.38159144e-01 1.14400256e+00 1.36525288e-01
-1.41537476e+00 2.67726690e-01 -6.43779635e-01 6.23583607e-02
-1.21261232e-01 7.72378862e-01 -1.14394081e+00 1.47483444e+00
4.36335951e-01 9.18499827e-01 -7.14058816e-01 4.47509408e-01
-7.85271108e-01 4.39499050e-01 -1.00006342e-01 6.12505004e-02
-4.31552261e-01 -1.54802456e-01 1.31128684e-01 8.40044677e-01
-5.66387437e-02 3.92532080e-01 2.55918086e-01 4.76307809e-01
-7.04257607e-01 4.70918775e-01 -8.58480930e-01 9.41124633e-02
6.70371532e-01 1.45461810e+00 -5.42649806e-01 -3.62658173e-01
-6.41385794e-01 8.54570627e-01 1.07451415e+00 5.10869324e-01
-5.29233456e-01 -4.70767617e-01 2.05228314e-01 -3.36784333e-01
1.36499986e-01 2.14916334e-01 -2.79487409e-02 -1.59713292e+00
1.89654604e-01 -6.47941053e-01 6.23628199e-01 -4.81178433e-01
-1.50450611e+00 6.14028573e-01 -3.34269553e-02 -1.12799513e+00
-1.79318354e-01 -4.83673364e-01 -2.87982404e-01 9.49747384e-01
-1.68836498e+00 -1.77168274e+00 -1.88802838e-01 8.37152541e-01
-5.56150377e-02 -5.96453965e-01 1.16734219e+00 4.48829919e-01
-8.26166928e-01 9.91684258e-01 -3.17714065e-01 5.51941931e-01
7.21696377e-01 -1.37219238e+00 1.39495909e-01 7.93823361e-01
4.83386993e-01 7.25401580e-01 3.62843275e-01 -9.36306119e-01
-1.28556740e+00 -1.29684806e+00 1.06404948e+00 -4.58819836e-01
7.33095229e-01 -3.58050585e-01 -1.11833906e+00 1.05011117e+00
-2.16452390e-01 7.78706312e-01 9.86494780e-01 9.15007830e-01
-6.60032570e-01 -3.52167577e-01 -1.18327856e+00 4.80085522e-01
1.39717948e+00 -6.28285885e-01 -5.99333882e-01 5.46913326e-01
7.94991076e-01 -4.75866765e-01 -1.40349209e+00 7.15451062e-01
1.59539893e-01 -2.94419616e-01 1.16081131e+00 -1.18840516e+00
4.30216849e-01 -1.36099204e-01 2.18930114e-02 -1.45554662e+00
-1.26799569e-01 -4.33392137e-01 -7.07537830e-01 1.85685897e+00
8.77123952e-01 -6.86975598e-01 1.03340566e+00 6.82082713e-01
1.38220370e-01 -8.25334311e-01 -6.82027161e-01 -8.58608305e-01
3.73253104e-04 -2.94747919e-01 8.30109477e-01 1.50742626e+00
3.12897712e-01 9.94765162e-01 -5.30206084e-01 4.07853514e-01
3.83765012e-01 1.93258584e-01 8.70151103e-01 -1.39538336e+00
-3.20775926e-01 2.68762171e-01 -6.36720717e-01 -4.41487491e-01
7.15942264e-01 -1.39568603e+00 -3.03110242e-01 -1.66907895e+00
1.77896023e-01 -9.24061120e-01 -2.44931355e-01 8.98452222e-01
-6.89950049e-01 2.39861943e-02 3.84779274e-02 1.06270209e-01
-5.78543782e-01 8.59323740e-01 1.42429042e+00 -4.01536047e-01
-8.87325481e-02 2.63176918e-01 -7.94734538e-01 5.71594834e-01
6.48906291e-01 -5.09492397e-01 -7.88224459e-01 -2.29649451e-02
5.50744951e-01 1.43070430e-01 1.54366508e-01 -7.19840169e-01
3.25241536e-01 -1.01972088e-01 4.96524304e-01 -2.25754946e-01
4.33026344e-01 -1.06383944e+00 3.49875391e-02 -4.75817360e-02
-3.31323892e-01 -6.14924848e-01 -8.58328268e-02 8.37763071e-01
-2.71572143e-01 -3.31491083e-01 1.76080525e-01 -5.24276793e-02
-7.26579249e-01 5.89536548e-01 4.96441901e-01 3.90923321e-01
1.11651170e+00 2.91295290e-01 -4.92240191e-01 -2.13912502e-01
-1.13365579e+00 3.79251748e-01 -9.57975537e-02 3.05989444e-01
7.07809567e-01 -1.68498409e+00 -6.98857903e-01 -6.82008117e-02
4.34454471e-01 3.35840851e-01 2.15416625e-01 3.98456007e-01
-1.93402037e-01 1.75932616e-01 -4.11257558e-02 1.96631700e-01
-1.17872095e+00 9.74236548e-01 1.65262315e-02 -9.39241171e-01
-5.83139956e-01 1.00443947e+00 -3.12847853e-01 -7.44758368e-01
-6.11700825e-02 -6.02632500e-02 -6.70410633e-01 1.64855659e-01
2.43322879e-01 1.30691797e-01 1.79100499e-01 -6.35125041e-01
-3.72197390e-01 2.76173711e-01 -3.88494521e-01 3.92195076e-01
1.32168496e+00 8.50060657e-02 -1.11869767e-01 3.12915653e-01
9.51038659e-01 2.16960490e-01 -6.93744600e-01 -9.07297134e-01
1.07758932e-01 -3.97157311e-01 -5.09087384e-01 -7.27595985e-01
-1.30327964e+00 4.47902888e-01 7.45999999e-03 2.54262090e-01
9.44285333e-01 3.31452042e-01 6.48372948e-01 7.24045336e-01
5.87763965e-01 -7.97667384e-01 -2.18510345e-01 4.63044286e-01
8.83338511e-01 -1.51009285e+00 3.74867082e-01 -1.36661923e+00
-6.52036667e-01 9.10926938e-01 8.75599444e-01 1.05527386e-01
7.64006317e-01 1.02394015e-01 -2.64010102e-01 -3.03143710e-01
-5.62221646e-01 -6.59495831e-01 4.59654450e-01 1.14012134e+00
2.41979122e-01 1.46554679e-01 -2.32156500e-01 9.16247547e-01
-2.33553201e-01 -2.90881991e-01 2.62810946e-01 5.18369913e-01
1.82141095e-01 -1.48321259e+00 6.41373545e-02 7.08575070e-01
-4.20689642e-01 -3.20022523e-01 -3.22760254e-01 9.81006563e-01
3.25259894e-01 9.93281305e-01 -4.89600211e-01 -6.16901934e-01
6.00590169e-01 1.87606201e-01 5.80695868e-01 -9.45624590e-01
-3.86418611e-01 -8.19801629e-01 6.31030738e-01 -3.74659091e-01
-7.66213596e-01 -4.12306607e-01 -1.17437065e+00 -1.62343338e-01
-7.55298495e-01 3.70821267e-01 1.43649802e-02 1.15253055e+00
1.68947577e-01 9.01801348e-01 5.34916699e-01 -2.02599064e-01
-8.24271664e-02 -1.13776863e+00 -7.90549397e-01 7.30139971e-01
-1.42534807e-01 -9.82443929e-01 2.92601567e-02 6.95079640e-02] | [8.996519088745117, 8.143061637878418] |
a14168c1-b0b4-4641-860c-84e480d4ab93 | generative-entity-to-entity-stance-detection | 2211.01467 | null | https://arxiv.org/abs/2211.01467v1 | https://arxiv.org/pdf/2211.01467v1.pdf | Generative Entity-to-Entity Stance Detection with Knowledge Graph Augmentation | Stance detection is typically framed as predicting the sentiment in a given text towards a target entity. However, this setup overlooks the importance of the source entity, i.e., who is expressing the opinion. In this paper, we emphasize the need for studying interactions among entities when inferring stances. We first introduce a new task, entity-to-entity (E2E) stance detection, which primes models to identify entities in their canonical names and discern stances jointly. To support this study, we curate a new dataset with 10,619 annotations labeled at the sentence-level from news articles of different ideological leanings. We present a novel generative framework to allow the generation of canonical names for entities as well as stances among them. We further enhance the model with a graph encoder to summarize entity activities and external knowledge surrounding the entities. Experiments show that our model outperforms strong comparisons by large margins. Further analyses demonstrate the usefulness of E2E stance detection for understanding media quotation and stance landscape, as well as inferring entity ideology. | ['Lu Wang', 'Nick Beauchamp', 'Xinliang Frederick Zhang'] | 2022-11-02 | null | null | null | null | ['stance-detection'] | ['natural-language-processing'] | [ 5.25881611e-02 5.38708270e-01 -5.42242467e-01 -5.28447807e-01
-5.91123819e-01 -1.05457342e+00 1.08366621e+00 4.67335433e-01
-2.21413508e-01 7.02159405e-01 1.09058893e+00 -3.10601622e-01
3.69381547e-01 -9.67320681e-01 -8.45596194e-01 -4.53024685e-01
1.36892378e-01 4.98470277e-01 4.09181975e-02 -5.57140946e-01
4.32519466e-01 -3.15566063e-01 -1.11794031e+00 5.27581751e-01
9.88301218e-01 6.50870085e-01 -2.98457474e-01 2.57744163e-01
-1.07778341e-01 1.24476779e+00 -9.99239326e-01 -1.08861101e+00
-2.38986731e-01 -5.91314852e-01 -6.99558437e-01 5.14569320e-02
4.39226747e-01 6.67639971e-02 5.11993188e-03 1.04792404e+00
3.39788347e-01 -3.59936237e-01 8.89657021e-01 -1.13844502e+00
-8.17824483e-01 1.37592494e+00 -7.06369638e-01 3.28174710e-01
3.26550603e-01 -3.85226727e-01 1.85839379e+00 -9.67802823e-01
1.33635819e+00 1.16319036e+00 7.40985394e-01 8.82560685e-02
-1.00111008e+00 -4.75451320e-01 4.75269437e-01 6.74296618e-02
-8.15369725e-01 -3.85224462e-01 1.03605568e+00 -7.09608495e-01
4.95468557e-01 2.24025652e-01 4.80445325e-01 1.50142205e+00
4.06790450e-02 8.35604668e-01 1.19715691e+00 -3.89763862e-01
4.91779670e-02 2.12077200e-01 7.42634833e-01 6.28600717e-01
7.28455067e-01 -6.56682372e-01 -7.27214634e-01 -2.49647230e-01
2.65446119e-02 -5.65421760e-01 -1.50764316e-01 -5.49828680e-03
-1.41701269e+00 1.17727101e+00 5.27837396e-01 5.29294789e-01
-4.96084780e-01 -1.08049534e-01 5.89004993e-01 -1.65357888e-02
9.34448183e-01 8.39635193e-01 -2.99540192e-01 6.19049277e-03
-8.93530607e-01 4.28900182e-01 1.24720061e+00 6.79429591e-01
5.47636867e-01 -3.19506824e-01 -3.15664053e-01 4.82174665e-01
2.98720568e-01 5.12287796e-01 9.43511724e-02 -5.46107411e-01
7.30216265e-01 8.09917688e-01 2.64758348e-01 -1.58253717e+00
-4.06399012e-01 -7.31984854e-01 -3.38243991e-01 -4.88527447e-01
2.76557565e-01 -5.19479394e-01 -4.91013914e-01 1.85292637e+00
5.87346435e-01 -7.93747753e-02 1.27684459e-01 6.24809325e-01
1.14468408e+00 5.41678965e-01 1.74165443e-02 -1.56712592e-01
1.71987545e+00 -8.64164829e-01 -8.69892299e-01 -4.14885551e-01
7.64616847e-01 -7.09760368e-01 6.67925477e-01 -1.65293977e-01
-7.59576738e-01 -1.16792910e-01 -9.25543725e-01 -1.22636333e-01
-4.58879620e-01 2.53362447e-01 5.74100733e-01 4.14923131e-01
-5.60876787e-01 3.82944703e-01 -5.69019318e-01 -8.50594118e-02
3.90567660e-01 -1.56952903e-01 -8.91774707e-03 5.63700497e-01
-1.74760532e+00 1.06167400e+00 3.78161401e-01 -4.99834195e-02
-3.00594300e-01 -6.33784473e-01 -1.07469201e+00 -2.61495173e-01
5.24574399e-01 -6.75741613e-01 9.45507467e-01 -1.02207077e+00
-9.39495623e-01 1.09917462e+00 -3.50890964e-01 -7.25848138e-01
4.64381337e-01 -2.99938262e-01 -5.69036841e-01 -1.74574107e-01
8.24860573e-01 9.89471897e-02 4.82575119e-01 -1.23559344e+00
-6.39085829e-01 -2.43970513e-01 4.98185366e-01 3.86532307e-01
-2.82538325e-01 2.26716235e-01 1.01384066e-01 -6.14648223e-01
1.17951974e-01 -1.05220604e+00 1.60904035e-01 -8.23127687e-01
-1.03627765e+00 -5.66891372e-01 5.26902974e-01 -8.03207397e-01
1.65423095e+00 -1.86748743e+00 2.63407499e-01 1.86698452e-01
6.10730350e-01 -4.46236402e-01 5.62718809e-01 5.51990986e-01
7.45387450e-02 3.26060086e-01 8.31476003e-02 -2.44131207e-01
4.35589015e-01 5.04235700e-02 -6.42610848e-01 4.40817207e-01
8.74932259e-02 1.17525315e+00 -9.88013923e-01 -5.48047245e-01
-5.41658640e-01 2.23393947e-01 -6.33464873e-01 -2.84096152e-01
-3.36425304e-01 2.53028184e-01 -6.29723608e-01 7.14662850e-01
1.69200510e-01 -8.00341725e-01 7.16695786e-01 -5.87190032e-01
-2.40699589e-01 1.01399302e+00 -8.63867760e-01 1.06753457e+00
-2.73979574e-01 8.82076204e-01 -1.14063531e-01 -6.12430811e-01
7.71275461e-01 1.64934650e-01 3.70591372e-01 -4.47326452e-01
2.94621676e-01 4.13288683e-01 8.38981867e-02 -2.28459686e-01
8.58065426e-01 7.26987468e-03 -6.84325874e-01 5.33278704e-01
-2.77468592e-01 3.32328379e-01 6.35373831e-01 5.22019982e-01
7.80401647e-01 3.40392925e-02 6.35187447e-01 -5.19316852e-01
3.15552413e-01 2.53182888e-01 6.24929667e-01 4.58450675e-01
2.17437074e-01 1.70216322e-01 9.89823818e-01 -3.32747072e-01
-1.01328409e+00 -6.25334263e-01 -1.66801780e-01 1.25118411e+00
2.22491920e-01 -7.72846103e-01 -5.92584074e-01 -1.11884427e+00
1.07685626e-01 1.03835034e+00 -1.10078073e+00 4.03526008e-01
-9.62500334e-01 -1.03227568e+00 4.06623989e-01 4.38031703e-01
3.11347008e-01 -8.14113855e-01 -4.42501396e-01 1.35497972e-01
-8.79621267e-01 -1.25672090e+00 -3.16808283e-01 6.64876923e-02
-1.65039495e-01 -1.14889753e+00 -3.44462752e-01 -5.66180050e-01
6.27342701e-01 -1.83153346e-01 1.57996857e+00 -2.21622825e-01
5.21110594e-01 -2.07667127e-01 -3.65463823e-01 -5.36206067e-01
-6.63137853e-01 4.24620718e-01 -8.25991556e-02 1.50542468e-01
3.73256356e-01 -3.69400054e-01 -4.72955406e-01 2.83801481e-02
-4.30543482e-01 2.88829327e-01 2.22839788e-01 6.04326308e-01
2.24924564e-01 -1.88539743e-01 5.30675530e-01 -1.80837584e+00
7.28517890e-01 -8.71671081e-01 -1.80684686e-01 1.91539124e-01
-6.47096574e-01 1.09284282e-01 3.58788759e-01 -1.36498377e-01
-1.06080556e+00 -5.95519602e-01 -1.07598685e-01 4.40917969e-01
3.93989921e-01 1.01223350e+00 -7.24189728e-02 7.09142268e-01
7.68904090e-01 -8.41017589e-02 -5.72735608e-01 -2.05816939e-01
5.84226787e-01 5.71232677e-01 3.28820527e-01 -6.03436172e-01
8.23442340e-01 5.12416780e-01 -2.44712725e-01 -5.99992573e-01
-1.74445689e+00 -3.89211863e-01 -5.01782894e-01 -1.13798887e-01
8.93464684e-01 -1.28804827e+00 -4.15880948e-01 1.46507964e-01
-1.31703329e+00 9.97315422e-02 -7.99343139e-02 1.15971945e-01
-1.73470721e-01 1.65201470e-01 -7.98957527e-01 -3.12091440e-01
-5.03699064e-01 -7.81764805e-01 1.06078410e+00 2.14722976e-02
-8.04139256e-01 -1.27564847e+00 4.64072585e-01 6.18503451e-01
1.07313991e-01 8.16984355e-01 9.11903441e-01 -1.02159750e+00
-2.45931461e-01 1.00748591e-01 -6.40938804e-02 -5.46086431e-02
2.47771218e-01 2.02362850e-01 -7.11535990e-01 -6.87291671e-04
-1.97763190e-01 -1.88680530e-01 8.91067266e-01 3.76144350e-01
3.56126159e-01 -8.57486665e-01 -5.17614603e-01 2.24477187e-01
1.14611721e+00 -3.03341329e-01 3.27406794e-01 7.56817043e-01
8.66281688e-01 6.98264122e-01 5.36278427e-01 3.11679155e-01
8.98597062e-01 5.23470521e-01 2.08949834e-01 -1.35068923e-01
-1.58325300e-01 -4.92728889e-01 4.67119366e-01 1.01446867e+00
-1.46520898e-01 -4.52291399e-01 -8.80911231e-01 6.86762571e-01
-1.76443362e+00 -1.13580918e+00 -4.80671614e-01 1.43247676e+00
1.09328651e+00 6.01309299e-01 7.71021321e-02 -8.87828991e-02
8.32259119e-01 7.35339463e-01 -1.91660225e-01 -1.53348604e-02
-5.36075592e-01 -8.07507783e-02 4.36087638e-01 6.75496042e-01
-1.26345289e+00 9.36680734e-01 5.48710489e+00 4.72099662e-01
-9.66997802e-01 1.55032784e-01 4.70459044e-01 2.46210858e-01
-8.30877721e-01 2.00312033e-01 -1.21155870e+00 6.86144948e-01
6.40114605e-01 -4.17855710e-01 -2.90665954e-01 9.40650582e-01
7.50832483e-02 9.27915052e-02 -8.85716021e-01 4.10288453e-01
3.69144022e-01 -1.62808251e+00 -6.80070668e-02 2.04019636e-01
1.13922584e+00 3.54611613e-02 -8.73179212e-02 1.90646037e-01
5.40910304e-01 -5.26852190e-01 1.15640759e+00 1.13787107e-01
4.66147035e-01 -5.66671968e-01 7.54596233e-01 1.24225475e-01
-9.07507777e-01 1.74409255e-01 4.71044444e-02 -5.08460030e-02
3.01255524e-01 9.62759078e-01 -1.11398041e+00 7.25413024e-01
1.27758875e-01 1.10225677e+00 -6.72814012e-01 7.96661675e-02
-7.82132030e-01 9.28629220e-01 -5.00120968e-03 -3.13095450e-01
2.76068032e-01 -6.91152969e-03 7.24268615e-01 1.42269325e+00
1.41446799e-01 -6.40807077e-02 1.44600257e-01 8.09930861e-01
-5.37114918e-01 2.37092733e-01 -5.54295003e-01 -3.48881871e-01
6.48073852e-01 1.40322077e+00 -1.02617371e+00 -5.52799463e-01
-3.52623582e-01 6.43868089e-01 4.64837700e-01 1.38907462e-01
-1.09613383e+00 -8.07182789e-02 5.09590805e-01 3.14129412e-01
2.51980990e-01 -1.30241245e-01 -3.63714427e-01 -1.48340845e+00
6.74309507e-02 -9.28353190e-01 3.42537135e-01 -4.88733500e-01
-1.26274240e+00 5.44854164e-01 -2.25235313e-01 -9.86479402e-01
-4.08465445e-01 -4.41346288e-01 -6.00012243e-01 5.43637931e-01
-1.48508477e+00 -1.51182389e+00 -7.74083510e-02 -1.25559876e-02
3.39120448e-01 2.73768097e-01 4.02138829e-01 2.26908788e-01
-4.98003602e-01 1.73509628e-01 -1.63836643e-01 7.24874198e-01
8.89069080e-01 -1.45891047e+00 6.87672138e-01 9.98955846e-01
5.11243045e-01 8.81120086e-01 1.11819220e+00 -9.57828462e-01
-8.61956179e-01 -1.01337135e+00 1.69044220e+00 -1.01316953e+00
1.18371940e+00 -4.94941056e-01 -4.88573521e-01 9.76531625e-01
5.40572107e-01 -6.38985157e-01 9.03725803e-01 8.26225758e-01
-6.43831134e-01 3.83766383e-01 -4.86072153e-01 7.01618254e-01
1.12737656e+00 -5.33326149e-01 -9.22498167e-01 4.47097927e-01
8.34132016e-01 -5.99121332e-01 -7.29005873e-01 3.98211598e-01
3.72245282e-01 -7.74704397e-01 7.38383770e-01 -6.08415008e-01
1.13004756e+00 -3.19602907e-01 -1.68475091e-01 -1.36662900e+00
-3.21375400e-01 -2.33092591e-01 -5.22945225e-01 1.41301715e+00
8.69989693e-01 -4.36609507e-01 5.62743723e-01 2.46595263e-01
-1.23491414e-01 -6.99105263e-01 -3.70373160e-01 -1.17316276e-01
-7.23730307e-03 -1.95738114e-02 4.08040136e-01 1.49454272e+00
2.00027183e-01 1.15080237e+00 -3.59880924e-01 2.43888497e-01
3.96735996e-01 9.03316677e-01 5.88226974e-01 -1.31962800e+00
-2.06265494e-01 -4.95796502e-01 -4.68921028e-02 -8.70267928e-01
4.51213598e-01 -1.02258801e+00 -2.25694209e-01 -1.87140489e+00
3.73415619e-01 -2.41302282e-01 -6.77642077e-02 2.71338463e-01
-5.15583456e-01 2.95431048e-01 -7.09343329e-02 3.37767899e-01
-8.54667187e-01 2.01823160e-01 1.13021684e+00 -1.74854130e-01
2.13304348e-02 -1.19491205e-01 -1.20905340e+00 1.04856622e+00
6.02314591e-01 -4.99940366e-01 -6.15015179e-02 -3.58192027e-01
1.12089837e+00 -3.45720798e-01 2.60555923e-01 -3.86444271e-01
1.41218752e-01 -7.18568787e-02 1.88995332e-01 -7.33056307e-01
7.60406209e-03 -1.90746933e-01 -2.36877874e-02 2.16200992e-01
-5.97225845e-01 1.65930822e-01 -4.42912102e-01 5.33888638e-01
-3.36885393e-01 -3.65224071e-02 1.94739461e-01 -2.11934313e-01
-7.10072339e-01 -1.98247090e-01 8.29865709e-02 6.98963344e-01
8.71992171e-01 1.90620124e-01 -8.15303326e-01 -3.83108735e-01
-7.51421332e-01 8.11905041e-02 5.70349872e-01 4.58935916e-01
1.84610318e-02 -1.26763976e+00 -1.11897337e+00 -3.89891505e-01
2.75799930e-01 -3.67274284e-01 -6.34071082e-02 9.97598529e-01
-2.00207472e-01 2.92149752e-01 2.39348516e-01 -2.79079378e-01
-1.33639395e+00 2.01097906e-01 -4.43630666e-02 -5.78683317e-01
-3.65298063e-01 8.22353125e-01 3.43292385e-01 -3.59407634e-01
-4.65742737e-01 -1.59684762e-01 -6.49137139e-01 8.97876143e-01
2.26895660e-01 1.34198591e-01 -9.08930600e-03 -1.01852012e+00
-4.66943771e-01 1.82764515e-01 -9.06133726e-02 -2.21087411e-02
1.39708471e+00 -3.10288459e-01 -4.61311519e-01 6.94547892e-01
9.26232696e-01 9.27425802e-01 -8.42987180e-01 -2.49899745e-01
4.09746289e-01 -1.32678956e-01 -3.27000201e-01 -7.46577442e-01
-5.54536939e-01 2.34591261e-01 -5.68676114e-01 5.91134250e-01
3.49416316e-01 4.21010345e-01 6.68583333e-01 1.01333313e-01
2.23852903e-01 -1.20336747e+00 2.58553941e-02 7.96868026e-01
6.61092460e-01 -1.16308868e+00 1.80124402e-01 -6.62722945e-01
-9.71770883e-01 8.26351047e-01 3.23946834e-01 -7.72288591e-02
5.08032620e-01 2.33444035e-01 2.34698877e-01 -7.12443352e-01
-6.53903544e-01 -2.11967468e-01 5.70411623e-01 -1.41420290e-01
9.49392557e-01 3.90682518e-01 -8.14635217e-01 6.19333327e-01
-8.54344785e-01 -6.02246583e-01 6.69645905e-01 6.91296935e-01
-4.07513916e-01 -8.58868420e-01 4.89526205e-02 3.41216356e-01
-8.85190666e-01 -5.02081811e-01 -7.36295283e-01 6.93512619e-01
2.15980321e-01 8.06484282e-01 -4.08665873e-02 -2.84402102e-01
2.13170677e-01 7.04885423e-02 1.05154037e-01 -7.74181187e-01
-6.98601723e-01 -9.75860357e-02 1.02668166e+00 -9.14267600e-02
-8.70178998e-01 -7.76229739e-01 -1.07639682e+00 -4.00754839e-01
-3.01630437e-01 4.42242086e-01 5.38905203e-01 1.09145808e+00
4.39726084e-01 6.94640040e-01 6.15045607e-01 -1.07134745e-01
-5.28651357e-01 -9.06620502e-01 -3.87786299e-01 7.02648580e-01
2.33534694e-01 -6.99800432e-01 -3.42834353e-01 1.97162449e-01] | [8.887505531311035, 10.00265121459961] |
445f3852-e726-4dc3-bdfb-78776ccf87b6 | generalized-bayesian-inference-for-scientific | 2305.15208 | null | https://arxiv.org/abs/2305.15208v1 | https://arxiv.org/pdf/2305.15208v1.pdf | Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation | Simulation-based inference (SBI) enables amortized Bayesian inference for simulators with implicit likelihoods. But when we are primarily interested in the quality of predictive simulations, or when the model cannot exactly reproduce the observed data (i.e., is misspecified), targeting the Bayesian posterior may be overly restrictive. Generalized Bayesian Inference (GBI) aims to robustify inference for (misspecified) simulator models, replacing the likelihood-function with a cost function that evaluates the goodness of parameters relative to data. However, GBI methods generally require running multiple simulations to estimate the cost function at each parameter value during inference, making the approach computationally infeasible for even moderately complex simulators. Here, we propose amortized cost estimation (ACE) for GBI to address this challenge: We train a neural network to approximate the cost function, which we define as the expected distance between simulations produced by a parameter and observed data. The trained network can then be used with MCMC to infer GBI posteriors for any observation without running additional simulations. We show that, on several benchmark tasks, ACE accurately predicts cost and provides predictive simulations that are closer to synthetic observations than other SBI methods, especially for misspecified simulators. Finally, we apply ACE to infer parameters of the Hodgkin-Huxley model given real intracellular recordings from the Allen Cell Types Database. ACE identifies better data-matching parameters while being an order of magnitude more simulation-efficient than a standard SBI method. In summary, ACE combines the strengths of SBI methods and GBI to perform robust and simulation-amortized inference for scientific simulators. | ['Jakob H. Macke', 'Michael Deistler', 'Richard Gao'] | 2023-05-24 | null | null | null | null | ['bayesian-inference'] | ['methodology'] | [ 3.58199179e-01 -3.57258677e-01 5.34281731e-02 -2.61000693e-01
-1.02467811e+00 -6.23161256e-01 5.49105763e-01 8.09219554e-02
-7.33161867e-01 1.46002078e+00 -4.06974733e-01 -8.22974384e-01
-1.17856197e-01 -7.37284184e-01 -1.23573279e+00 -8.04168880e-01
-8.67743939e-02 8.83526206e-01 3.98015790e-02 4.04642135e-01
3.22273195e-01 7.61391878e-01 -1.38676155e+00 -2.92853117e-01
8.02199423e-01 6.36509418e-01 1.56670883e-01 8.69337380e-01
5.69959760e-01 2.22653091e-01 -8.19177628e-01 4.55358485e-03
-3.08057666e-01 -3.67720366e-01 -4.24213499e-01 -5.85832655e-01
1.12168320e-01 -4.46226716e-01 1.91029161e-02 9.76951540e-01
4.94474977e-01 6.46145875e-03 1.02234042e+00 -1.46937919e+00
4.19039935e-01 5.58547258e-01 -2.35760048e-01 2.33424321e-01
1.96412802e-01 5.15620768e-01 4.99602705e-01 -5.24452627e-01
4.93204325e-01 1.28058934e+00 8.28537405e-01 2.54056394e-01
-1.97917795e+00 -9.08847630e-01 -5.12542203e-02 -2.12216452e-01
-1.75120628e+00 -3.72325689e-01 7.38304928e-02 -4.05675173e-01
1.18004143e+00 7.27827549e-02 6.64909959e-01 1.23261046e+00
7.17506170e-01 2.73654103e-01 1.22666883e+00 -3.47914062e-02
7.81126976e-01 -2.25070015e-01 1.00601092e-01 2.33822763e-01
6.89089954e-01 4.85355496e-01 -2.85580665e-01 -6.81723893e-01
8.29439759e-01 -1.96655661e-01 -2.57143468e-01 4.81179431e-02
-1.20828760e+00 5.36749959e-01 -2.76948780e-01 -2.60430783e-01
-3.04962307e-01 8.36906374e-01 3.73811841e-01 3.91429700e-02
1.11545309e-01 6.25003994e-01 -7.20164657e-01 -4.35970873e-01
-1.15829885e+00 8.41726959e-01 1.09078193e+00 7.38194168e-01
7.57671595e-01 2.16823757e-01 3.89059335e-02 4.40767527e-01
4.07085806e-01 7.66457617e-01 6.50087893e-02 -1.41659319e+00
-6.33400679e-02 1.13109127e-01 4.06044692e-01 -4.29696232e-01
-4.59464550e-01 -4.55742598e-01 -9.58842456e-01 4.02498603e-01
6.64081633e-01 -2.06885949e-01 -9.81655896e-01 2.06399369e+00
6.27681166e-02 7.13664055e-01 -3.39426510e-02 5.15405178e-01
2.74549574e-01 9.14412916e-01 1.16490722e-01 -3.50935668e-01
1.06747949e+00 -2.72532646e-03 -3.94346744e-01 -1.80020034e-01
4.62118596e-01 -3.24917316e-01 8.55807602e-01 5.26518226e-01
-1.34563339e+00 -1.72853947e-01 -1.28315318e+00 5.15581071e-01
-1.73173010e-01 -2.70133525e-01 4.61063802e-01 6.98937118e-01
-9.47040677e-01 9.06259477e-01 -1.30734146e+00 -1.47314360e-02
3.91565889e-01 6.01612747e-01 4.27186303e-02 1.55805171e-01
-1.08667493e+00 8.77318859e-01 4.32164341e-01 8.68420675e-03
-1.54515266e+00 -1.15540302e+00 -6.48382068e-01 3.40373874e-01
2.17108771e-01 -8.45156491e-01 1.09120154e+00 -3.77286732e-01
-1.63135540e+00 3.20727050e-01 -2.88010716e-01 -7.64119625e-01
3.55675399e-01 3.67397994e-01 -2.70109233e-02 -2.08332464e-01
-1.85520247e-01 6.67020917e-01 5.18842995e-01 -1.24570191e+00
-6.67240396e-02 -1.29296422e-01 -1.51691586e-01 -2.45925665e-01
5.69038987e-01 -1.47537902e-01 -3.08483481e-01 -3.29907119e-01
-8.51040147e-03 -1.00769973e+00 -3.59754026e-01 -4.18606363e-02
-4.02042836e-01 1.89755604e-01 3.51520866e-01 -5.13228238e-01
1.01046932e+00 -1.82302582e+00 -9.04305875e-02 4.26042646e-01
1.21277839e-01 7.06500560e-02 7.45956153e-02 3.10425073e-01
7.53188580e-02 2.31969461e-01 -7.05447018e-01 -2.62735605e-01
3.79019976e-02 3.31313163e-01 -2.79311121e-01 5.24398923e-01
8.72002840e-02 8.26408982e-01 -7.04825819e-01 -5.01455724e-01
1.36506081e-01 5.07022679e-01 -6.53761566e-01 1.85468599e-01
-3.88804823e-01 5.90328693e-01 -1.27988160e-01 2.72179604e-01
8.62301528e-01 -5.02168119e-01 3.39642435e-01 -1.06330000e-01
-7.21212709e-03 3.49646419e-01 -1.36166000e+00 1.15842831e+00
-5.88613570e-01 4.66730177e-01 -2.55798269e-02 -1.04150629e+00
5.57412028e-01 1.26699790e-01 -3.26859169e-02 -3.05292577e-01
2.40470171e-01 3.36942494e-01 1.07174791e-01 2.61816651e-01
3.73614430e-02 -2.06195638e-01 -2.29309320e-01 5.67899466e-01
8.85809511e-02 -6.67711139e-01 1.67904496e-01 2.49538809e-01
1.12761784e+00 3.65171611e-01 4.87639457e-01 -4.68561977e-01
8.71802941e-02 -1.92434892e-01 7.27701783e-01 1.23923004e+00
-1.75489020e-02 4.12047178e-01 6.13723516e-01 -9.22796130e-02
-1.16611731e+00 -1.44132221e+00 -4.31277007e-01 3.71083617e-01
-3.92840542e-02 -8.28358531e-02 -8.32966268e-01 -1.33066118e-01
1.07413165e-01 1.01813686e+00 -3.77051085e-01 -1.92022011e-01
-3.28423083e-01 -1.03397143e+00 8.37927341e-01 6.06473446e-01
1.86697483e-01 -7.84388781e-01 -7.22810149e-01 3.92947495e-01
-3.58977616e-02 -9.01528776e-01 -1.54887035e-01 5.06090999e-01
-9.76891160e-01 -6.47736728e-01 -4.22422916e-01 -2.58106533e-02
5.42406082e-01 -4.72510904e-01 1.23159015e+00 2.08746731e-01
-2.29331806e-01 -1.67250842e-01 2.70734608e-01 -4.86946911e-01
-7.28624821e-01 -2.53408253e-01 1.48425400e-01 -7.38818824e-01
-5.58090918e-02 -9.41756487e-01 -5.00982821e-01 3.65392566e-01
-8.12027514e-01 8.26019943e-02 1.62897632e-01 1.10177553e+00
8.59513938e-01 -1.16377724e-02 7.20267773e-01 -7.71065414e-01
3.52198273e-01 -4.18616533e-01 -1.30011964e+00 1.72016367e-01
-7.23325610e-01 3.38267952e-01 8.04682016e-01 -5.49660861e-01
-9.73223388e-01 -1.96054056e-01 -2.99145818e-01 -3.52044463e-01
-1.12870790e-01 7.50982344e-01 -1.56010702e-01 -3.73491831e-03
5.77991605e-01 1.04784794e-01 6.98769093e-02 -1.77320719e-01
-3.30416828e-01 2.78066576e-01 5.33815563e-01 -9.39672291e-01
1.98203951e-01 3.94866586e-01 4.38098848e-01 -4.94287640e-01
-4.02831942e-01 2.37520531e-01 -1.32705823e-01 -1.09889239e-01
3.34001243e-01 -7.97626793e-01 -1.34814775e+00 6.68839633e-01
-1.05216408e+00 -7.19362319e-01 -5.00568748e-02 7.77929604e-01
-9.14928496e-01 2.29063272e-01 -5.40958226e-01 -9.85830188e-01
-1.22501500e-01 -1.45554900e+00 1.00346267e+00 1.58601984e-01
-5.98510265e-01 -1.03009892e+00 9.36339498e-02 -2.65718430e-01
2.38964647e-01 1.57107294e-01 1.12665319e+00 -6.42032623e-01
-7.10606039e-01 -2.88941741e-01 -1.93130985e-01 6.74740374e-02
-5.34388959e-01 3.87577564e-01 -1.04493546e+00 -3.80296737e-01
-1.66687429e-01 -3.22094679e-01 6.75759733e-01 1.11685514e+00
1.50456202e+00 -1.71181217e-01 -6.41358137e-01 8.80287409e-01
1.53183877e+00 2.93821156e-01 8.51678729e-01 -5.90830818e-02
1.71798944e-01 -3.07744049e-04 4.14188921e-01 7.50608742e-01
-3.70970322e-03 5.42869985e-01 2.40089864e-01 2.41529047e-01
4.72370356e-01 -3.00287485e-01 1.38446212e-01 4.56243902e-01
1.73292950e-01 -5.48525155e-01 -9.84117329e-01 3.57023239e-01
-1.51139379e+00 -8.19048584e-01 3.74125205e-02 2.72408438e+00
1.07201874e+00 4.36514765e-01 -1.00827895e-01 -8.93495008e-02
5.79198837e-01 -4.78582501e-01 -1.08277261e+00 -3.84586424e-01
-3.07798665e-03 5.07184327e-01 6.80148721e-01 7.41478622e-01
-4.26139861e-01 5.50841987e-01 7.10601616e+00 1.18180513e+00
-7.40091622e-01 -5.85251786e-02 9.14020658e-01 -2.18292922e-02
-4.01110142e-01 4.59667355e-01 -1.06668949e+00 7.49785423e-01
1.76221812e+00 -4.60210919e-01 6.96264267e-01 4.45956439e-01
4.03149545e-01 -7.67565787e-01 -1.37678564e+00 8.07791948e-01
-4.71354574e-01 -1.60330153e+00 -7.24963173e-02 2.71932542e-01
6.27821982e-01 8.70015323e-02 -1.09932661e-01 3.52049351e-01
7.82629848e-01 -1.35498071e+00 5.62080622e-01 8.20347071e-01
7.86894441e-01 -9.54884648e-01 9.12730575e-01 6.44354999e-01
-6.95838690e-01 4.42677319e-01 -3.35992515e-01 -1.09230340e-01
3.48766685e-01 8.20969224e-01 -1.00504375e+00 1.06414333e-01
5.87046206e-01 2.60289699e-01 -5.64287752e-02 1.11155093e+00
1.36068910e-01 1.06150019e+00 -9.85724986e-01 -2.69210190e-01
-1.42547265e-01 -2.22525746e-01 4.77596670e-01 1.11898959e+00
5.02941549e-01 -1.69859424e-01 -1.67311296e-01 1.50780988e+00
7.97095001e-02 -5.75070381e-01 -4.89407539e-01 -1.46155134e-01
1.09505641e+00 8.62939358e-01 -8.42972517e-01 -5.29568315e-01
1.72422767e-01 4.54005659e-01 4.20683436e-02 5.93080580e-01
-1.01959336e+00 -2.62166649e-01 5.98555446e-01 -1.92634344e-01
1.83262050e-01 -1.87747851e-01 -4.75913107e-01 -7.41255641e-01
-4.66398984e-01 -1.03106856e+00 1.85713097e-01 -1.10270822e+00
-1.15539551e+00 9.54264924e-02 5.57443261e-01 -9.40984368e-01
-7.73226500e-01 -6.90584898e-01 -5.49341917e-01 1.23024666e+00
-1.06136370e+00 -4.89790142e-01 1.40363216e-01 5.36843613e-02
9.13119018e-02 2.66817153e-01 9.43763256e-01 -3.40626948e-02
-6.13649607e-01 5.98097682e-01 4.59892988e-01 -4.48373348e-01
4.75116491e-01 -1.03009439e+00 5.78284919e-01 5.89899123e-01
-5.10647774e-01 9.63019371e-01 1.25666392e+00 -8.63824904e-01
-1.31517553e+00 -8.65398467e-01 4.40145284e-01 -2.08753273e-01
6.73122823e-01 -2.31687322e-01 -1.01330531e+00 7.29148805e-01
-2.87671447e-01 -8.42029303e-02 3.53241235e-01 -1.71876466e-03
-7.36963004e-02 1.09486900e-01 -1.20505917e+00 7.97951460e-01
6.20976985e-01 -4.22369212e-01 -1.02296583e-01 3.86402793e-02
4.06845778e-01 -3.36496323e-01 -1.06193936e+00 5.35986125e-01
8.42450798e-01 -7.50923514e-01 1.00184941e+00 -3.12432438e-01
8.16078857e-02 -4.35961455e-01 -2.58861512e-01 -1.32450819e+00
2.21670210e-01 -6.94790244e-01 -1.20382950e-01 9.62404728e-01
5.65175235e-01 -8.57978225e-01 6.22673929e-01 5.75694025e-01
1.71188682e-01 -6.28634214e-01 -1.14778936e+00 -1.01718318e+00
3.21327358e-01 -8.66179228e-01 8.20464551e-01 4.64127690e-01
-2.55640388e-01 2.47913431e-02 -4.54606116e-02 3.60246122e-01
9.62450385e-01 -8.53118226e-02 8.44565451e-01 -1.17968714e+00
-6.51246667e-01 -4.20331031e-01 -3.42373282e-01 -9.92713630e-01
3.85459125e-01 -6.21251881e-01 4.94641423e-01 -1.06516635e+00
5.73864996e-01 -3.18974495e-01 5.11112139e-02 1.76808909e-01
-2.37287670e-01 1.45332571e-02 -2.58644670e-01 -1.34021929e-02
-2.62304246e-01 2.98844814e-01 9.44083452e-01 1.70430958e-01
1.02769174e-01 2.22238842e-02 -1.98835939e-01 8.55584264e-01
6.72684014e-01 -7.82639503e-01 -3.12095165e-01 9.29677933e-02
5.54402292e-01 6.16207123e-01 9.87492919e-01 -1.06750560e+00
3.02512139e-01 -2.73776144e-01 4.41874951e-01 -9.30287063e-01
4.13392931e-01 -5.06278992e-01 7.19224453e-01 4.38481003e-01
-2.36930549e-01 -6.29173368e-02 5.49734056e-01 6.08465195e-01
1.86806858e-01 -4.79816288e-01 1.02264512e+00 4.65724431e-02
-7.90257528e-02 1.12006687e-01 -9.77315068e-01 2.11980879e-01
5.21716595e-01 -2.05208406e-01 -2.64676511e-01 -4.92909521e-01
-6.31769240e-01 2.24938869e-01 7.02975035e-01 -7.65796006e-01
6.09698832e-01 -6.98402941e-01 -6.08546972e-01 2.21983239e-01
-4.80880737e-02 -3.67844217e-02 3.56090039e-01 8.12882245e-01
-5.38300693e-01 1.78939641e-01 -1.16226235e-02 -8.20394397e-01
-8.92105818e-01 2.44487628e-01 5.98469853e-01 -4.69714314e-01
-2.20202968e-01 6.15181029e-01 2.11275473e-01 -6.00046992e-01
1.65442061e-02 -5.84965467e-01 4.17208135e-01 -4.91602480e-01
3.00862253e-01 4.70489591e-01 -6.82904348e-02 3.89858149e-02
-3.22916001e-01 1.15588866e-01 4.48470823e-02 -4.90682036e-01
1.05683637e+00 -1.57424267e-02 -1.58900376e-02 8.21904123e-01
1.06898916e+00 -4.03752953e-01 -1.68770587e+00 2.42458329e-01
-3.41784954e-01 -1.03773654e-01 2.30753541e-01 -1.10400093e+00
-4.40566957e-01 1.02689874e+00 3.90284806e-01 -2.70653337e-01
7.90783107e-01 -2.99048334e-01 4.27631974e-01 5.35436094e-01
5.93888462e-01 -9.59021449e-01 -4.62943226e-01 4.75516140e-01
4.67731059e-01 -8.55400383e-01 3.06435585e-01 -7.50552490e-02
-2.19018951e-01 7.57807672e-01 3.96579921e-01 -1.69133335e-01
7.09638536e-01 9.70333755e-01 -4.96833533e-01 1.55858500e-02
-1.00437987e+00 3.83791566e-01 -1.59257695e-01 4.79538560e-01
1.41698986e-01 2.33164504e-02 9.42158885e-03 5.88077605e-01
-3.06049827e-02 4.35514599e-01 6.29203200e-01 8.68946195e-01
-2.32084647e-01 -5.98597944e-01 -3.93923581e-01 7.94480145e-01
-3.60177070e-01 -2.86813766e-01 2.58994281e-01 9.05170262e-01
-3.67209554e-01 7.50536978e-01 3.24058652e-01 5.06193265e-02
-6.82979301e-02 1.00076295e-01 6.05805814e-01 -3.09000462e-01
-1.77585751e-01 1.59355864e-01 1.67429104e-01 -5.59153140e-01
-9.05439481e-02 -7.05924988e-01 -1.41044235e+00 -6.96899891e-01
-5.45432270e-01 1.39929831e-01 7.31587052e-01 1.14041233e+00
3.58896703e-01 5.98025441e-01 1.94578066e-01 -1.03390157e+00
-6.52347565e-01 -7.97206402e-01 -6.43451750e-01 -5.82737736e-02
1.66227624e-01 -7.61798561e-01 -7.85401881e-01 -4.54791896e-02] | [6.821859359741211, 3.932614326477051] |
78fc7477-d36c-43cc-94fd-384fc72b38f3 | reasoning-about-liquids-via-closed-loop | 1703.01656 | null | http://arxiv.org/abs/1703.01656v2 | http://arxiv.org/pdf/1703.01656v2.pdf | Reasoning About Liquids via Closed-Loop Simulation | Simulators are powerful tools for reasoning about a robot's interactions with
its environment. However, when simulations diverge from reality, that reasoning
becomes less useful. In this paper, we show how to close the loop between
liquid simulation and real-time perception. We use observations of liquids to
correct errors when tracking the liquid's state in a simulator. Our results
show that closed-loop simulation is an effective way to prevent large
divergence between the simulated and real liquid states. As a direct
consequence of this, our method can enable reasoning about liquids that would
otherwise be infeasible due to large divergences, such as reasoning about
occluded liquid. | ['Dieter Fox', 'Connor Schenck'] | 2017-03-05 | null | null | null | null | ['liquid-simulation'] | ['miscellaneous'] | [ 2.14939676e-02 3.17518145e-01 4.65632737e-01 -8.34420845e-02
-2.89824069e-01 -7.40640998e-01 5.63269973e-01 2.76953101e-01
-3.79428595e-01 9.55750644e-01 -2.47331455e-01 -5.78106105e-01
5.03816187e-01 -1.17057133e+00 -9.35614705e-01 -4.90957767e-01
-2.02235073e-01 5.25984287e-01 7.29718447e-01 -4.46309805e-01
1.97368100e-01 5.68447113e-01 -1.70996487e+00 1.17355302e-01
8.76462698e-01 4.64628637e-01 4.05960143e-01 8.75290334e-01
-4.03770924e-01 8.56051028e-01 -4.12080228e-01 1.93993732e-01
1.82761610e-01 -3.45983773e-01 -6.69698000e-01 -5.29502034e-02
-6.39204308e-02 -4.01694417e-01 -2.93520033e-01 1.19635129e+00
-9.90983397e-02 7.42634386e-02 4.47897881e-01 -1.41380715e+00
2.83711344e-01 3.24531496e-01 -6.41499758e-02 -4.06317979e-01
1.16227472e+00 4.84768003e-01 1.74935892e-01 -4.43028122e-01
7.95586884e-01 1.49236095e+00 7.85140097e-01 4.51427400e-01
-1.05424666e+00 -5.81546247e-01 4.79865819e-01 -2.72161067e-01
-1.25531352e+00 -4.33669627e-01 3.99770737e-01 -3.10958564e-01
1.36117220e+00 3.30948442e-01 1.07206368e+00 7.59505987e-01
9.63572979e-01 4.15503800e-01 1.12500572e+00 -4.28822279e-01
6.82365537e-01 3.21798056e-01 -2.53392428e-01 6.34979486e-01
8.07240069e-01 3.79125446e-01 -3.66532862e-01 -3.76978040e-01
7.69143701e-01 -3.66181135e-01 -3.42958927e-01 -7.83988059e-01
-8.78967047e-01 3.26292753e-01 2.68640876e-01 -4.34702188e-02
-4.02254462e-01 4.51585472e-01 2.72187352e-01 4.77956951e-01
3.87051404e-02 5.25553644e-01 -2.40698293e-01 -5.45903563e-01
-1.12987561e-02 7.18120575e-01 1.52411079e+00 9.95320976e-01
4.46143389e-01 -1.24255218e-01 7.50325859e-01 -2.43773311e-03
6.81234241e-01 7.32216358e-01 -2.61212252e-02 -1.13475072e+00
3.14079046e-01 4.08934206e-01 8.60412836e-01 -6.86046600e-01
-3.70252520e-01 3.81815970e-01 -9.49951559e-02 1.18222821e+00
6.03387177e-01 -1.40805215e-01 -7.86076307e-01 1.36941779e+00
4.89160210e-01 4.20736708e-02 7.15917826e-01 7.78693557e-01
3.88016522e-01 6.30589724e-01 -1.17135551e-02 -3.33146244e-01
8.02178800e-01 -5.33438206e-01 -8.36166859e-01 -4.74639773e-01
9.34680998e-01 -6.66703343e-01 8.91709507e-01 5.95209658e-01
-1.13070226e+00 -1.91549808e-01 -9.98446643e-01 3.66265476e-01
-4.38294441e-01 -1.03122759e+00 9.72173929e-01 4.04346287e-01
-1.07832944e+00 9.63024735e-01 -1.20235908e+00 -6.16215289e-01
-2.39203781e-01 4.53141272e-01 -3.28923494e-01 6.01067841e-02
-1.11945415e+00 1.49854922e+00 2.45941192e-01 3.74538600e-01
-5.07838130e-01 -2.18289584e-01 -1.05008852e+00 -3.03375781e-01
4.22430694e-01 -3.35730672e-01 1.81835055e+00 -5.29400110e-01
-1.80119729e+00 4.88793850e-01 -4.42919493e-01 -3.91297519e-01
9.19199765e-01 -3.89607728e-01 1.21626537e-02 -1.32148877e-01
-1.55590385e-01 3.61600071e-01 1.11859843e-01 -1.87413025e+00
-4.55566496e-01 -8.11566710e-02 1.96748048e-01 5.72169363e-01
6.42434180e-01 -5.96471906e-01 -1.41426459e-01 4.71887618e-01
6.35876119e-01 -1.05008447e+00 -7.26294041e-01 4.27118599e-01
-1.22429579e-01 2.29191825e-01 8.32023919e-01 -1.71192437e-01
4.95996416e-01 -1.71501637e+00 -1.82626963e-01 3.25224519e-01
7.19216317e-02 -3.97107750e-03 2.16672927e-01 8.71568084e-01
2.87039071e-01 -1.28444880e-01 3.68175544e-02 -1.43665895e-01
2.43174821e-01 4.98500049e-01 -5.14082253e-01 6.17296219e-01
-2.66026586e-01 6.32884622e-01 -1.29021430e+00 -4.05070484e-01
6.98407054e-01 2.98566848e-01 -3.23284864e-01 4.03934985e-01
-5.39975345e-01 6.09026015e-01 -5.39972067e-01 4.16770041e-01
9.40224349e-01 2.42954224e-01 5.99916995e-01 2.78842896e-01
-4.57516432e-01 5.83277583e-01 -1.32432151e+00 1.20928907e+00
-6.74684227e-01 3.30475986e-01 4.84815925e-01 -1.25382364e-01
7.94068217e-01 2.48348594e-01 2.41940916e-01 -7.78466821e-01
2.77192593e-01 4.69480336e-01 5.55251129e-02 -7.29260921e-01
4.67407495e-01 -4.85109180e-01 -1.53500393e-01 4.28515524e-01
-8.90283644e-01 -1.41994858e+00 -6.31271750e-02 1.88108519e-01
1.22601545e+00 7.11951733e-01 4.66663241e-01 -1.02441557e-01
1.59130424e-01 3.94268930e-01 3.01625282e-01 8.21317077e-01
-2.80453801e-01 3.18577439e-02 3.41323227e-01 -4.32909846e-01
-9.25345719e-01 -1.31903601e+00 1.08971708e-01 1.76152408e-01
1.05685043e+00 -4.56361651e-01 -5.30963182e-01 -1.62389964e-01
3.19278836e-01 1.00665724e+00 -2.56209910e-01 -3.37310731e-01
-6.14360988e-01 -1.21140778e-01 7.16163814e-02 6.40678227e-01
3.72203976e-01 -1.08536267e+00 -1.42819166e+00 3.72091264e-01
-2.84069069e-02 -1.03519392e+00 1.93842143e-01 5.46686113e-01
-9.60604966e-01 -1.12718248e+00 -5.80615550e-03 -4.42476451e-01
6.97783291e-01 4.63527262e-01 1.00243843e+00 3.26557845e-01
6.45155907e-02 4.70769227e-01 -1.73705921e-01 -5.08029521e-01
-8.79720867e-01 -8.10465276e-01 6.74042776e-02 -1.14388967e+00
1.28251612e-01 -4.99984890e-01 -1.90250009e-01 1.68252811e-01
-5.11608720e-01 2.28561252e-01 -6.80661425e-02 3.64683241e-01
2.98176289e-01 3.08606267e-01 -2.28413314e-01 -7.97285974e-01
9.23544943e-01 -2.22693712e-01 -1.03488326e+00 4.67027724e-02
-3.75307977e-01 2.04189181e-01 8.40737224e-01 -5.67836761e-01
-1.03531909e+00 3.28766972e-01 9.81737673e-02 -6.01927266e-02
-2.14913070e-01 3.38949144e-01 -8.51795450e-02 -2.17452079e-01
5.41802645e-01 -1.10723689e-01 4.53436524e-02 -7.98928738e-02
8.88438374e-02 4.64629710e-01 3.69841427e-01 -8.24878812e-01
7.30792880e-01 5.65847874e-01 1.00133836e-01 -5.52786946e-01
-2.86249399e-01 3.29524651e-03 -6.35872602e-01 -4.52399224e-01
5.21973789e-01 -6.63752317e-01 -1.47642493e+00 5.04948974e-01
-1.26710057e+00 -1.00865281e+00 -3.81032169e-01 4.65087175e-01
-7.87647605e-01 4.38515544e-01 -6.48542523e-01 -1.45994639e+00
4.44634795e-01 -1.30883670e+00 1.05968273e+00 3.41369301e-01
-7.46666729e-01 -9.45996642e-01 1.30756855e-01 -3.86394441e-01
2.41878271e-01 4.34294939e-01 4.18871701e-01 1.12852445e-02
-8.29392314e-01 -1.12745136e-01 7.62600750e-02 -5.19960582e-01
2.13515043e-01 7.38440603e-02 -9.70655620e-01 -3.28271270e-01
2.28044152e-01 -3.40442389e-01 4.08514708e-01 -5.55782467e-02
4.85367060e-01 -1.02877147e-01 -8.27116013e-01 1.97203889e-01
1.33175254e+00 8.12800169e-01 6.92927063e-01 6.18892431e-01
3.54701519e-01 5.53023458e-01 1.21065092e+00 3.20782423e-01
2.68067211e-01 4.40309733e-01 6.74236655e-01 8.44903737e-02
2.70525604e-01 -4.82948244e-01 4.15770799e-01 3.67826432e-01
1.91174448e-01 -3.27596068e-01 -1.09020019e+00 1.47123158e-01
-1.87949288e+00 -6.89572096e-01 -2.99842417e-01 2.33040094e+00
6.65641189e-01 6.64231062e-01 -3.30873907e-01 3.17496881e-02
2.42379397e-01 -2.70860374e-01 -8.94546628e-01 -8.68377447e-01
5.24560630e-01 -1.16753832e-01 7.12711930e-01 1.18209720e+00
-7.15500593e-01 1.27039480e+00 7.56791401e+00 -9.56542790e-02
-9.18292284e-01 -2.72886813e-01 -2.45762616e-01 3.89389306e-01
-4.50209647e-01 3.02272797e-01 -5.04369199e-01 1.46150097e-01
8.74747813e-01 -2.70951629e-01 4.79669303e-01 8.53899598e-01
4.11071360e-01 -1.17602253e+00 -1.37181425e+00 5.99275887e-01
-2.54362851e-01 -8.03432941e-01 -3.45437199e-01 -6.99020848e-02
1.93893284e-01 -4.30637002e-01 -1.71920955e-01 2.83890545e-01
1.03453183e+00 -1.14180875e+00 1.02406144e+00 3.49450767e-01
4.80239868e-01 -6.09050214e-01 8.10062110e-01 7.92800128e-01
-1.25199950e+00 2.54349232e-01 -2.47881576e-01 -6.86274171e-01
5.12563765e-01 3.28915119e-01 -1.27699757e+00 2.95400526e-02
4.08127367e-01 1.07577324e-01 9.83876884e-02 9.06840444e-01
-2.26142392e-01 -4.45370264e-02 -7.23605454e-01 -4.03690308e-01
1.08151183e-01 -3.74427438e-01 4.97944087e-01 9.42549765e-01
1.45836204e-01 2.41007492e-01 3.98179770e-01 8.68055403e-01
7.83594012e-01 -5.35823941e-01 -1.44759583e+00 1.18751697e-01
5.30397236e-01 4.54122484e-01 -9.53408241e-01 -2.62736946e-01
-6.91606551e-02 1.01496744e+00 1.80957705e-01 3.50835979e-01
-9.57974315e-01 -9.92302522e-02 8.53373051e-01 4.12486196e-02
-1.63710520e-01 -6.29218340e-01 -3.03712010e-01 -9.58024442e-01
-7.81108886e-02 -6.24594867e-01 -3.66788536e-01 -1.25947499e+00
-6.66264355e-01 4.88203228e-01 1.15176111e-01 -1.33356476e+00
-5.02974689e-01 -5.91332555e-01 -4.08343166e-01 7.94560254e-01
-1.13831449e+00 -5.64023376e-01 -3.58535528e-01 4.72583137e-02
3.40034485e-01 7.33457208e-01 1.12052691e+00 -4.53791618e-01
2.53529042e-01 -8.35826322e-02 -1.48277372e-01 -5.23961425e-01
4.36014473e-01 -1.19535840e+00 5.61745524e-01 5.38171470e-01
-5.12261391e-01 5.83880067e-01 1.58893847e+00 -1.26176548e+00
-1.78409612e+00 -4.76593524e-01 3.05447280e-01 -4.26469743e-01
7.40106702e-01 -5.04612982e-01 -1.02760386e+00 9.10876751e-01
-2.81930000e-01 -1.98145092e-01 -1.67648077e-01 -8.04670155e-02
-2.03131899e-01 3.15024495e-01 -1.52069664e+00 1.18140566e+00
1.05950630e+00 -4.73424315e-01 -3.91172975e-01 3.39520156e-01
8.12356472e-01 -1.15423155e+00 -5.27279794e-01 3.09665650e-01
7.62686312e-01 -1.06965172e+00 7.10517883e-01 -9.00471732e-02
-1.14065766e-01 -4.52471614e-01 -2.52623022e-01 -1.37683487e+00
1.66848972e-01 -7.05107331e-01 -1.27412993e-02 3.80763054e-01
2.26978704e-01 -1.03214979e+00 8.48089993e-01 1.04825401e+00
9.91532058e-02 -5.24096847e-01 -7.73499250e-01 -8.41928422e-01
1.76494807e-01 -6.12203717e-01 2.85522759e-01 4.74281311e-01
7.06406713e-01 -1.00322023e-01 8.66938680e-02 4.88564163e-01
6.67179286e-01 1.90873414e-01 8.40900183e-01 -9.91081953e-01
-1.56514376e-01 -1.52932722e-02 -3.30968827e-01 -1.03571618e+00
3.56885284e-01 -2.92736351e-01 9.51912940e-01 -1.75922132e+00
9.17524751e-03 -7.40700245e-01 4.85813797e-01 1.76309109e-01
2.67128170e-01 -4.41743135e-01 3.73480201e-01 -5.68374619e-02
-6.10288024e-01 4.03876781e-01 1.51392865e+00 3.06274474e-01
-4.55608428e-01 -1.41366506e-02 -1.91499159e-01 1.23315287e+00
8.69089305e-01 -3.32390964e-01 -4.67854202e-01 -1.06514350e-01
3.33244741e-01 4.70559776e-01 3.07881117e-01 -1.18096089e+00
2.39854798e-01 -6.26615286e-01 1.35911509e-01 -6.64105892e-01
8.44845057e-01 -1.13639581e+00 4.19328243e-01 1.10120583e+00
-9.15861875e-02 1.30366161e-02 7.29559064e-01 5.17527699e-01
1.44436330e-01 -2.70753235e-01 6.82082951e-01 -4.93493438e-01
-6.87349498e-01 -4.01099145e-01 -1.05981004e+00 -4.09660280e-01
1.26134205e+00 -5.69345057e-01 -4.00410146e-01 -7.76039064e-01
-8.65416825e-01 4.57013309e-01 1.19293976e+00 -1.18378159e-02
8.35785151e-01 -8.01778674e-01 2.05349460e-01 1.94494590e-01
-2.94152737e-01 3.65808994e-01 -2.36053288e-01 3.91674042e-01
-1.05559683e+00 3.12628567e-01 5.96726127e-03 -6.18752599e-01
-1.36769700e+00 5.37824988e-01 7.19778717e-01 -1.88380539e-01
-1.01153588e+00 6.15132749e-01 3.32440138e-01 -7.38136590e-01
3.06607842e-01 -8.65400434e-01 3.81941080e-01 -8.49474907e-01
3.73643011e-01 1.36207063e-02 -2.31658593e-01 -2.93158442e-01
-5.09866655e-01 7.42603838e-01 1.58647925e-01 -5.93625963e-01
1.03047144e+00 -3.64565641e-01 -2.82155126e-02 1.02370512e+00
5.39623618e-01 1.15765601e-01 -1.64293587e+00 3.55211973e-01
-8.61413181e-02 -6.16969585e-01 -3.65932405e-01 -6.59870088e-01
-1.71448335e-01 6.22478306e-01 3.74909580e-01 1.85431749e-01
5.51023483e-01 4.25963923e-02 7.41753459e-01 8.77825618e-01
1.22733581e+00 -8.80960345e-01 -6.14679456e-02 7.53849268e-01
8.28260899e-01 -1.01862562e+00 6.81969374e-02 -1.19998264e+00
-5.23762465e-01 1.06760192e+00 1.04560399e+00 -2.15584755e-01
4.49686557e-01 1.36605906e+00 2.92285800e-01 -4.81047295e-02
-8.75362694e-01 -4.02852818e-02 -9.18789268e-01 8.77661705e-01
1.80524468e-01 1.41319901e-01 2.74459004e-01 -9.96403396e-02
-4.33979601e-01 1.36806130e-01 1.00605643e+00 1.58441806e+00
-9.61197257e-01 -8.26460719e-01 -8.97526264e-01 -1.63223892e-02
3.45391154e-01 3.51331115e-01 -3.36818039e-01 1.05122745e+00
-1.24903165e-01 1.07273746e+00 1.12282053e-01 -1.54867440e-01
4.23824608e-01 -1.47079617e-01 9.88893270e-01 -6.03436232e-01
-3.08477968e-01 -6.00373298e-02 4.53422308e-01 -1.05357599e+00
-3.62525657e-02 -5.15610397e-01 -2.18094254e+00 -5.22195816e-01
-3.51653457e-01 1.66449189e-01 4.76146191e-01 8.89332235e-01
-2.21700907e-01 4.01491702e-01 1.15287095e-01 -1.10247576e+00
-5.62020779e-01 -3.21157664e-01 -5.31196833e-01 3.10432732e-01
4.64302421e-01 -8.65417004e-01 -5.93521357e-01 -2.85476834e-01] | [4.591772079467773, 0.9643433094024658] |
f369ea1d-e19c-4171-a28a-68323377d99c | can-an-embodied-agent-find-your-cat-shaped | 2303.03480 | null | https://arxiv.org/abs/2303.03480v1 | https://arxiv.org/pdf/2303.03480v1.pdf | Can an Embodied Agent Find Your "Cat-shaped Mug"? LLM-Based Zero-Shot Object Navigation | We present LGX, a novel algorithm for Object Goal Navigation in a "language-driven, zero-shot manner", where an embodied agent navigates to an arbitrarily described target object in a previously unexplored environment. Our approach leverages the capabilities of Large Language Models (LLMs) for making navigational decisions by mapping the LLMs implicit knowledge about the semantic context of the environment into sequential inputs for robot motion planning. Simultaneously, we also conduct generalized target object detection using a pre-trained Vision-Language grounding model. We achieve state-of-the-art zero-shot object navigation results on RoboTHOR with a success rate (SR) improvement of over 27% over the current baseline of the OWL-ViT CLIP on Wheels (OWL CoW). Furthermore, we study the usage of LLMs for robot navigation and present an analysis of the various semantic factors affecting model output. Finally, we showcase the benefits of our approach via real-world experiments that indicate the superior performance of LGX when navigating to and detecting visually unique objects. | ['Dinesh Manocha', 'James F. Mullen Jr.', 'Vishnu Sashank Dorbala'] | 2023-03-06 | null | null | null | null | ['robot-navigation', 'motion-planning'] | ['robots', 'robots'] | [ 1.91444144e-01 4.38565582e-01 1.98524058e-01 -5.85362971e-01
-7.41404474e-01 -3.49511772e-01 7.07357645e-01 -1.08753435e-01
-7.88639843e-01 4.11955088e-01 7.10280165e-02 -2.45528072e-01
-3.06525733e-03 -6.94974363e-01 -7.99231172e-01 -4.06424046e-01
-3.25839162e-01 7.05952466e-01 4.11324680e-01 -6.22800291e-01
5.38153648e-01 2.86131650e-01 -1.72214270e+00 8.80516991e-02
3.15956950e-01 5.64631820e-01 1.20645773e+00 7.57883370e-01
-9.43830460e-02 1.04440928e+00 -9.54144895e-02 2.57410079e-01
1.98909581e-01 -2.54328579e-01 -9.88591909e-01 -7.58290812e-02
3.61554593e-01 -4.21731532e-01 -3.85718882e-01 1.11429977e+00
2.29899287e-01 4.88302201e-01 6.90060437e-01 -1.46663141e+00
-5.35142601e-01 5.22352993e-01 -3.06758404e-01 3.82256624e-03
4.95169103e-01 6.18513644e-01 8.64398539e-01 -9.14679110e-01
1.10764229e+00 1.72211552e+00 5.70489705e-01 7.55220175e-01
-1.19359481e+00 -2.63652056e-01 5.03183544e-01 2.95930415e-01
-1.24236608e+00 -7.98699558e-01 5.74099980e-02 -4.30509299e-01
1.51165545e+00 -4.50385392e-01 3.51301610e-01 1.12174821e+00
3.41364294e-01 7.78439820e-01 7.03484237e-01 -4.15413201e-01
6.15862131e-01 -2.18851119e-01 2.53443569e-01 1.20505095e+00
2.48533517e-01 3.32247913e-01 -8.39931190e-01 7.57036805e-02
4.59552914e-01 -4.97418970e-01 3.30346003e-02 -9.75142002e-01
-1.39488804e+00 7.69644618e-01 7.89314389e-01 9.14804824e-03
-4.87241149e-01 6.44431770e-01 2.02505693e-01 8.45012162e-03
-2.34813944e-01 5.17559886e-01 -4.62240815e-01 -7.91807473e-02
-9.10228938e-02 4.76894051e-01 8.32451344e-01 1.60831749e+00
8.37317765e-01 7.71995410e-02 -4.05861298e-03 6.41079962e-01
7.84788191e-01 7.80444086e-01 5.09937704e-01 -1.49917173e+00
4.73650992e-01 3.47844660e-01 5.83006263e-01 -7.84547627e-01
-9.72221076e-01 9.46894959e-02 2.31056184e-01 8.36899757e-01
2.89129138e-01 1.69693269e-02 -1.27956188e+00 1.87583768e+00
8.07769522e-02 -3.99645060e-01 8.10902178e-01 9.44711447e-01
7.77089894e-01 5.00206649e-01 5.95393181e-01 6.39532804e-01
1.49558723e+00 -1.38690758e+00 -4.03327584e-01 -1.21359766e+00
1.09592032e+00 3.20679396e-02 1.20488107e+00 1.09542683e-01
-6.44167840e-01 -3.25535297e-01 -1.19945121e+00 -3.47092181e-01
-7.29704261e-01 1.06449842e-01 7.28551626e-01 2.00996548e-01
-1.28081536e+00 3.11391592e-01 -1.00278175e+00 -1.28930211e+00
4.19720292e-01 2.26142675e-01 -6.73341990e-01 -1.99271888e-01
-6.86562955e-01 1.44876921e+00 7.77502239e-01 -2.99069914e-04
-1.52589047e+00 -8.42920877e-03 -1.32043040e+00 -2.05050781e-01
5.36140800e-01 -6.84390783e-01 1.68294132e+00 -3.10814828e-01
-1.33828056e+00 1.08361661e+00 -2.65583217e-01 -7.05280781e-01
1.61065355e-01 -5.05621791e-01 -4.37861197e-02 1.83056667e-01
7.51901269e-01 1.45097792e+00 2.67247796e-01 -1.46201456e+00
-1.15257788e+00 -4.50859189e-01 1.71541229e-01 5.21351695e-01
4.59476411e-01 -2.82107085e-01 -4.83503729e-01 1.02304861e-01
4.59912181e-01 -1.05700386e+00 -5.98241270e-01 2.75794655e-01
-1.74936354e-01 -6.95152581e-02 6.21224225e-01 -3.84240836e-01
2.79809177e-01 -2.18976283e+00 2.44794682e-01 -2.95277983e-01
-1.49463028e-01 -4.52658117e-01 -5.82729042e-01 5.37358820e-01
5.47579348e-01 -3.53467971e-01 -2.35671699e-01 -4.36730295e-01
3.19663644e-01 4.31940764e-01 -4.58936661e-01 2.91551918e-01
-2.75497548e-02 1.17330551e+00 -1.29448903e+00 -2.46777460e-01
3.06333512e-01 -4.49517090e-03 -4.75149274e-01 2.53221877e-02
-5.05425334e-01 1.10023357e-01 -2.45162249e-01 7.09992647e-01
1.42843977e-01 -2.63889711e-02 2.97535747e-01 2.44330525e-01
-3.39644521e-01 1.23955518e-01 -7.65657067e-01 2.38621283e+00
-3.69871348e-01 7.46038854e-01 3.00005935e-02 -3.96217585e-01
7.54406810e-01 -2.39101142e-01 -2.29928181e-01 -8.92514229e-01
3.84437218e-02 2.93005466e-01 -6.20587915e-02 -5.71168661e-01
7.31396377e-01 1.31494775e-01 -3.18501413e-01 2.70280182e-01
3.72645080e-01 -1.49807140e-01 -5.30388094e-02 3.38313401e-01
1.28558147e+00 8.34705114e-01 4.23047602e-01 -5.17527759e-01
-9.60851014e-02 8.25789094e-01 -4.88984920e-02 1.52462113e+00
-4.91859496e-01 5.37669837e-01 -6.81538880e-03 -3.33542168e-01
-8.02992046e-01 -1.11352468e+00 2.53106117e-01 1.58607280e+00
7.88330078e-01 -2.44859427e-01 -7.35255241e-01 -3.28813523e-01
1.22094370e-01 1.50155640e+00 -9.03295159e-01 -3.68512511e-01
-4.68093663e-01 -5.25430977e-01 5.18761635e-01 6.78112864e-01
3.13362420e-01 -1.64260089e+00 -1.76652992e+00 2.92919904e-01
-2.22615033e-01 -1.24862576e+00 2.77075380e-01 8.29001307e-01
-6.72532439e-01 -1.08299696e+00 -2.34015852e-01 -1.10243213e+00
7.59199202e-01 6.42075896e-01 9.51419294e-01 -3.38227898e-01
-5.13321579e-01 7.56695330e-01 -3.47465754e-01 -4.37714726e-01
-3.74459803e-01 9.68772452e-03 2.41196603e-01 -7.64035642e-01
5.96963108e-01 5.69266975e-02 -3.34861010e-01 1.37808248e-01
-2.08708256e-01 3.64917040e-01 6.35816932e-01 6.38893247e-01
1.82046831e-01 -3.67992818e-01 5.20305216e-01 -4.34535086e-01
4.55448657e-01 -5.63629389e-01 -7.70487428e-01 1.61664903e-01
-5.71909368e-01 3.30588460e-01 -5.16330861e-02 -2.40306839e-01
-1.07806456e+00 3.48308533e-01 1.88096106e-01 3.01376551e-01
-3.80029291e-01 3.83681387e-01 -4.27712984e-02 -2.02930018e-01
7.60608256e-01 2.59314209e-01 5.17074987e-02 -3.97023380e-01
8.35967004e-01 2.14569703e-01 9.34901536e-01 -4.16824192e-01
3.43474686e-01 7.36594737e-01 -8.25634301e-02 -6.60202444e-01
-3.48116189e-01 -4.46386963e-01 -6.33125246e-01 -1.19705647e-01
9.52930331e-01 -1.13422787e+00 -8.62801552e-01 4.85045046e-01
-1.04113424e+00 -1.04348361e+00 -2.01538444e-01 3.30177963e-01
-1.29025435e+00 -5.43079078e-02 -2.78639138e-01 -9.15362477e-01
1.82504933e-02 -1.07627499e+00 1.37197304e+00 2.01459944e-01
-4.61995691e-01 -5.12212574e-01 -7.48616457e-02 -5.83214164e-02
3.09760898e-01 -3.47365797e-01 1.07228744e+00 -7.08140135e-01
-7.61429071e-01 4.77969721e-02 -5.22671580e-01 -6.71632349e-01
-1.74403146e-01 -8.22293878e-01 -8.53160024e-01 -1.63804218e-01
-3.28169078e-01 -6.02549374e-01 8.95939648e-01 2.84466535e-01
9.29130688e-02 1.05922483e-01 -9.67071831e-01 3.52649182e-01
1.68364286e+00 5.04593253e-01 4.44282681e-01 1.17239177e+00
3.82869393e-01 8.99785578e-01 1.12382746e+00 3.82975370e-01
7.34280884e-01 5.91741681e-01 8.78105223e-01 4.11176831e-01
-5.19461483e-02 -4.91518885e-01 4.16967511e-01 -3.19970042e-01
4.73588735e-01 -3.78413916e-01 -1.19480801e+00 8.37602496e-01
-2.15877581e+00 -5.77158153e-01 1.30835727e-01 1.79733038e+00
2.04025194e-01 1.66263655e-01 -2.52593637e-01 -6.69204593e-01
2.28429317e-01 -8.40683002e-03 -8.33595932e-01 -4.94097127e-03
-5.60554415e-02 -5.51384568e-01 8.32765520e-01 8.47934306e-01
-1.00928330e+00 1.75655973e+00 7.05426598e+00 2.58921295e-01
-5.47356308e-01 9.44483355e-02 -2.12394908e-01 9.98297986e-03
1.73749477e-01 1.36350125e-01 -1.04457378e+00 -1.49807081e-01
8.55212748e-01 8.89599845e-02 4.45892006e-01 1.34743440e+00
4.32351455e-02 -8.97393405e-01 -1.24681509e+00 7.81812072e-01
2.11460575e-01 -9.80334938e-01 -1.27705500e-01 -7.19546452e-02
2.14150637e-01 6.92028284e-01 -8.86038095e-02 7.43976414e-01
1.08168077e+00 -1.00712132e+00 1.30257356e+00 6.32625461e-01
2.10344285e-01 -2.44625583e-01 3.20072562e-01 5.69815278e-01
-9.96998429e-01 -4.82310861e-01 -5.84807932e-01 -1.51207119e-01
4.40358251e-01 -6.24609530e-01 -1.21427727e+00 1.87195972e-01
8.15449893e-01 3.42106849e-01 -6.18904769e-01 9.54505801e-01
-2.49096066e-01 -8.77472386e-02 -3.13205898e-01 -3.27362627e-01
7.13828385e-01 -5.89150228e-02 6.88831925e-01 1.02227044e+00
2.41964042e-01 1.91026837e-01 2.62169451e-01 8.70476246e-01
4.57391322e-01 -1.40213177e-01 -1.07511735e+00 1.74942195e-01
3.45784992e-01 8.27098906e-01 -1.03186607e+00 -2.88465947e-01
-3.00737888e-01 1.19758034e+00 5.47216833e-01 5.94257951e-01
-5.41860700e-01 -4.96599644e-01 6.95801198e-01 -3.99684787e-01
4.32683140e-01 -4.63395596e-01 -2.73565829e-01 -6.21187449e-01
-1.65925354e-01 -4.02668685e-01 -3.94638851e-02 -1.51878214e+00
-5.79735219e-01 5.80241501e-01 3.01158540e-02 -8.66409898e-01
-4.20841902e-01 -9.68413591e-01 -2.95463074e-02 7.51353204e-01
-1.38559377e+00 -1.33901060e+00 -6.09927237e-01 7.12396926e-04
1.01192605e+00 -3.51044774e-01 1.20398319e+00 -5.03682196e-01
3.90333980e-02 -1.35412753e-01 1.21880338e-01 -1.92636147e-01
4.86510932e-01 -1.10682631e+00 1.04063475e+00 6.63143396e-01
-3.39282840e-03 6.03540599e-01 1.03466809e+00 -9.19635236e-01
-1.59909499e+00 -9.62144136e-01 5.75589538e-01 -7.81989992e-01
5.14800906e-01 -5.10004878e-01 -6.13093376e-01 1.22515154e+00
-3.33051085e-02 -3.41093332e-01 1.43907666e-01 7.45936260e-02
-4.35874879e-01 4.83178765e-01 -1.12762809e+00 1.22383988e+00
1.53728914e+00 -3.54803205e-01 -1.01047027e+00 2.55777329e-01
7.99642026e-01 -3.87881488e-01 1.59901455e-01 3.49089801e-01
9.33163941e-01 -6.79002404e-01 9.59450066e-01 -9.36358392e-01
1.27096832e-01 -5.76428056e-01 -8.11908603e-01 -1.18372762e+00
-5.33748031e-01 -3.39817554e-02 1.68610439e-01 5.73669016e-01
4.72799897e-01 -4.35310721e-01 7.02722907e-01 5.39063036e-01
-2.44313896e-01 -9.76818129e-02 -8.32075179e-01 -8.58407140e-01
-4.82900023e-01 -6.88237250e-01 1.21650144e-01 2.13443309e-01
2.23342985e-01 3.65954310e-01 -1.32013738e-01 6.17855906e-01
6.19193971e-01 -1.27764419e-01 8.12059700e-01 -9.99725401e-01
2.49543428e-01 -3.17583591e-01 -6.92108274e-01 -1.32457113e+00
4.13951904e-01 -8.80049229e-01 1.21260512e+00 -2.07682681e+00
1.36858836e-01 -2.42563233e-01 -1.33453980e-01 6.80648386e-01
3.64020020e-01 -1.74810123e-02 3.94729018e-01 1.57708019e-01
-1.05589521e+00 5.12883067e-01 5.75094223e-01 -2.45124996e-01
-3.13828796e-01 -5.41214287e-01 -7.23720849e-01 9.92043257e-01
5.34127712e-01 -4.60371852e-01 -4.35679138e-01 -8.55280101e-01
4.21501771e-02 -1.10381141e-01 5.88087022e-01 -1.31446683e+00
6.49819255e-01 -1.39798820e-01 1.30030662e-01 -6.64670587e-01
6.94784701e-01 -8.07847500e-01 -2.03052267e-01 8.63692403e-01
-5.18964171e-01 -1.41244054e-01 4.96479154e-01 9.25586820e-01
4.61200327e-01 -6.68506086e-01 5.86925864e-01 -5.54595888e-01
-2.03673625e+00 -3.05073023e-01 -9.55143273e-01 -1.90600783e-01
9.96283710e-01 -3.38952869e-01 -4.17538613e-01 -1.97946280e-01
-8.38398874e-01 7.12554276e-01 6.93131804e-01 8.63279104e-01
7.49643505e-01 -9.11228001e-01 -2.76576042e-01 1.72567815e-01
8.10790598e-01 -2.13266671e-01 -2.97913533e-02 2.85063267e-01
-6.94382310e-01 7.88880944e-01 -4.99215603e-01 -6.39270365e-01
-8.70280683e-01 6.27541065e-01 2.87012488e-01 5.70663571e-01
-9.38925028e-01 1.05886316e+00 6.46623492e-01 -8.31764698e-01
4.27506387e-01 -3.78671676e-01 -2.88196862e-01 -2.44109288e-01
4.18009102e-01 2.21928641e-01 -3.06784600e-01 -8.62721264e-01
-5.59706867e-01 4.38257247e-01 5.61765321e-02 -6.97680473e-01
1.05451989e+00 -7.02461481e-01 1.52297512e-01 8.12168419e-01
6.16391599e-01 -6.34292901e-01 -1.47093534e+00 -1.05544172e-01
6.12271309e-01 1.42611852e-02 -2.36304432e-01 -1.07200348e+00
-1.35773718e-01 5.66018522e-01 8.56355488e-01 -4.92653251e-01
2.66335636e-01 3.06681156e-01 2.78196037e-01 1.37945986e+00
1.22986221e+00 -1.02583981e+00 6.08632006e-02 9.82724011e-01
8.21054280e-01 -1.59037340e+00 -3.72023106e-01 -4.03861031e-02
-7.61585832e-01 9.60698068e-01 9.42879379e-01 4.49565090e-02
1.87178597e-01 1.15964621e-01 3.98103803e-01 -4.51302439e-01
-8.71389925e-01 -5.32421768e-01 -3.00264448e-01 1.09098053e+00
-3.41498464e-01 -8.09868500e-02 4.88875598e-01 4.74088967e-01
-1.98272854e-01 -2.55101640e-02 4.14096087e-01 1.45877731e+00
-1.24622679e+00 -2.39273787e-01 -1.57963082e-01 4.33813743e-02
2.68463522e-01 -2.59946197e-01 -2.89199680e-01 9.68022168e-01
-2.50070065e-01 1.07372475e+00 -7.31473640e-02 -2.44225517e-01
3.74774575e-01 4.15907949e-01 4.94311124e-01 -1.02370572e+00
1.02425568e-01 -3.66038680e-01 2.70951241e-01 -8.94119024e-01
-1.43691406e-01 -6.27588034e-01 -1.94592118e+00 5.45355439e-01
-1.12536259e-01 -2.66263485e-01 9.51692104e-01 1.04451180e+00
3.85472059e-01 4.42733914e-01 -3.10603410e-01 -1.13946736e+00
-4.07588840e-01 -8.46968770e-01 -4.44714069e-01 4.47161272e-02
3.94342631e-01 -9.88332987e-01 -2.55302370e-01 2.31039729e-02] | [4.54332160949707, 0.6076425313949585] |
9b2ab74e-34e9-4d14-b0ac-1f6104d018ab | knowledge-graph-deep-learning-a-case-study-in | 2205.15952 | null | https://arxiv.org/abs/2205.15952v2 | https://arxiv.org/pdf/2205.15952v2.pdf | Knowledge Graph - Deep Learning: A Case Study in Question Answering in Aviation Safety Domain | In the commercial aviation domain, there are a large number of documents, like, accident reports (NTSB, ASRS) and regulatory directives (ADs). There is a need for a system to access these diverse repositories efficiently in order to service needs in the aviation industry, like maintenance, compliance, and safety. In this paper, we propose a Knowledge Graph (KG) guided Deep Learning (DL) based Question Answering (QA) system for aviation safety. We construct a Knowledge Graph from Aircraft Accident reports and contribute this resource to the community of researchers. The efficacy of this resource is tested and proved by the aforesaid QA system. Natural Language Queries constructed from the documents mentioned above are converted into SPARQL (the interface language of the RDF graph database) queries and answered. On the DL side, we have two different QA models: (i) BERT QA which is a pipeline of Passage Retrieval (Sentence-BERT based) and Question Answering (BERT based), and (ii) the recently released GPT-3. We evaluate our system on a set of queries created from the accident reports. Our combined QA system achieves 9.3% increase in accuracy over GPT-3 and 40.3% increase over BERT QA. Thus, we infer that KG-DL performs better than either singly. | ['Ravi Shankar', 'Rajesh Zele', 'Prabhjit Thind', 'Asif Ekbal', 'Satyanarayan Kar', 'Pushpak Bhattacharyya', 'Shreya Laddha', 'Raj Gite', 'Ankush Agarwal'] | 2022-05-31 | null | https://aclanthology.org/2022.lrec-1.673 | https://aclanthology.org/2022.lrec-1.673.pdf | lrec-2022-6 | ['passage-retrieval'] | ['natural-language-processing'] | [-2.42477253e-01 1.80048287e-01 1.18212134e-01 -4.27701235e-01
-1.18109572e+00 -5.99546432e-01 3.61702949e-01 7.06457615e-01
-4.27149832e-01 8.36032808e-01 4.40950274e-01 -7.35344648e-01
-6.92973793e-01 -1.40236318e+00 -7.92989850e-01 3.36724818e-02
5.59015609e-02 8.72264802e-01 6.54360771e-01 -8.81733775e-01
-1.81339160e-02 5.06780684e-01 -1.34277606e+00 7.90475965e-01
8.79621446e-01 1.18946207e+00 3.49124409e-02 5.30410171e-01
-3.89002979e-01 1.37256920e+00 -6.19124532e-01 -5.14093816e-01
1.91194844e-02 -2.01037496e-01 -1.41780949e+00 -6.73720479e-01
2.50057906e-01 -2.50114858e-01 -3.05284023e-01 7.98142076e-01
5.07227957e-01 1.43706650e-01 2.17637688e-01 -1.34339011e+00
-6.64789498e-01 6.09709740e-01 1.80951908e-01 1.62785754e-01
7.31966853e-01 7.94710368e-02 1.18354690e+00 -6.18808568e-01
7.82180011e-01 1.13595259e+00 3.41937840e-01 1.64094433e-01
-3.98601890e-01 -3.06677461e-01 -2.50063807e-01 5.81312895e-01
-1.15511131e+00 -1.19150423e-01 4.52348262e-01 -4.66889173e-01
1.54934514e+00 3.45486283e-01 3.45576704e-01 6.18984699e-01
5.03874362e-01 4.31429952e-01 4.42629516e-01 -3.53343517e-01
3.81552637e-01 5.19412048e-02 2.58231372e-01 9.30476844e-01
2.13505223e-01 -1.23858809e-01 -4.81639266e-01 -1.78542107e-01
3.37397754e-01 -1.49976537e-01 -3.32566828e-01 -1.94200426e-01
-9.23550427e-01 6.78868532e-01 5.23296535e-01 3.73479575e-01
-6.38700008e-01 -3.30633372e-02 6.76034391e-01 6.62630916e-01
2.66413391e-01 6.57851577e-01 -8.30516219e-01 -5.88518679e-02
-5.13992608e-01 7.03122914e-01 1.30410433e+00 1.31227493e+00
6.15087211e-01 -2.46392518e-01 -4.92114097e-01 7.28252709e-01
5.22902489e-01 4.13103819e-01 8.77039284e-02 -6.65473163e-01
8.03166389e-01 8.76189888e-01 1.90844283e-01 -1.01319671e+00
-5.76043189e-01 -4.23144698e-01 -3.84953707e-01 -2.87024468e-01
5.74790351e-02 -2.42577508e-01 -7.30092764e-01 1.38826823e+00
2.98113704e-01 -4.30745572e-01 3.97249073e-01 9.08346236e-01
1.53310299e+00 7.52667129e-01 3.11699748e-01 1.41961738e-01
1.52768672e+00 -9.08263862e-01 -8.83000135e-01 -2.88061053e-02
9.30733740e-01 -5.64954698e-01 9.62119877e-01 1.99011147e-01
-1.01511943e+00 -5.48685193e-01 -8.81920159e-01 -2.42867738e-01
-7.77399480e-01 -1.27774552e-01 3.15480053e-01 1.76686570e-01
-1.02240169e+00 3.19695503e-01 -4.03254330e-01 -5.48936427e-01
1.37937337e-01 1.76436082e-01 -2.87727803e-01 -3.35982144e-01
-1.82016301e+00 9.68742847e-01 6.93969429e-01 1.64709948e-02
-9.72730458e-01 -7.52808750e-01 -1.02744842e+00 3.27598482e-01
8.07555377e-01 -1.11708939e+00 1.31970072e+00 -2.40435302e-02
-9.40585911e-01 5.82628608e-01 1.71893507e-01 -6.24875546e-01
1.69453591e-01 -3.91576976e-01 -8.60551596e-01 3.28613132e-01
1.96503147e-01 2.23574325e-01 1.92618132e-01 -1.02873766e+00
-6.62695169e-01 -4.68010008e-01 8.68885040e-01 1.82209667e-02
9.70989540e-02 2.15411440e-01 -4.55940902e-01 6.64767399e-02
-3.95836234e-01 -4.07202393e-01 2.30018999e-02 -4.04035479e-01
-2.82972604e-01 -6.24821961e-01 4.08761561e-01 -1.24702835e+00
1.42589974e+00 -1.78129995e+00 -1.13034539e-01 1.25582352e-01
2.18642890e-01 3.87040049e-01 -2.80508310e-01 1.21247363e+00
-1.56518564e-01 3.65172960e-02 -1.51951447e-01 3.33151102e-01
3.13474476e-01 2.81780720e-01 -5.17426431e-01 -1.83847383e-01
3.81138682e-01 1.12684810e+00 -9.69383240e-01 -5.60261667e-01
-1.81389302e-01 -4.77481894e-02 -5.34941077e-01 2.79487759e-01
-7.52036989e-01 2.56367117e-01 -7.59459674e-01 8.19499850e-01
3.66000384e-01 -1.23960316e-01 2.19616443e-01 -4.94034201e-01
8.34989771e-02 4.97048467e-01 -4.88019198e-01 1.79747546e+00
-4.28919435e-01 9.86395776e-02 -1.91297382e-01 -8.07044506e-01
1.01295972e+00 5.22410274e-01 4.41424012e-01 -1.14288712e+00
9.51626003e-02 2.21914247e-01 -3.15710902e-01 -1.17562938e+00
7.00701118e-01 -1.96481362e-01 -2.82181978e-01 1.54241800e-01
3.77696395e-01 -2.03283310e-01 3.45815331e-01 5.40435851e-01
1.58857453e+00 5.84362894e-02 1.05320916e-01 -2.41232701e-02
7.24844098e-01 4.97719109e-01 2.35911995e-01 5.16831994e-01
8.05397853e-02 2.40894586e-01 6.66705370e-01 -5.20189583e-01
-7.90550470e-01 -8.63756359e-01 1.30999893e-01 8.68545771e-01
-5.99519648e-02 -7.53480017e-01 -6.32968009e-01 -9.92468178e-01
3.92624252e-02 1.05488825e+00 -9.54392552e-02 -3.60487938e-01
-5.21484971e-01 -6.03271462e-02 6.78456903e-01 5.48889637e-01
6.88525438e-01 -1.31441450e+00 -4.81482744e-01 1.28119931e-01
-4.61692214e-01 -1.29923224e+00 2.37764660e-02 -2.00718075e-01
-4.99271035e-01 -1.37226236e+00 -1.58337727e-01 -6.27468467e-01
1.92988262e-01 -2.09477484e-01 1.56837547e+00 1.72719792e-01
3.65208462e-02 7.48766720e-01 -7.26231337e-01 -5.37610114e-01
-6.32505596e-01 9.08925608e-02 -2.23637894e-01 -4.97665018e-01
5.15200913e-01 4.04908881e-02 -4.30356830e-01 1.31958067e-01
-1.38336527e+00 -3.20158839e-01 4.41291153e-01 4.00314033e-01
5.29736519e-01 3.30961674e-01 1.06868422e+00 -8.76188576e-01
1.16475320e+00 -6.94340706e-01 -7.58556902e-01 5.88142753e-01
-5.24271667e-01 -2.49760468e-02 5.70672631e-01 5.39751470e-01
-1.06132853e+00 -5.59586883e-01 -7.99681962e-01 -1.77287892e-01
-2.77067512e-01 1.39387071e+00 -3.02760512e-01 2.54272401e-01
7.58680463e-01 -1.58800930e-01 -1.17795818e-01 -5.89959919e-01
3.35606724e-01 7.44898319e-01 4.08912003e-01 -6.24847054e-01
4.93659258e-01 -1.51808545e-01 -1.44634321e-01 -4.24024045e-01
-9.58208859e-01 -5.06335855e-01 -3.52018774e-01 -3.21162015e-01
1.17723453e+00 -7.15446353e-01 -8.50600898e-01 -7.78403133e-02
-1.33820498e+00 -6.72082976e-02 -6.10399783e-01 3.08844626e-01
-5.47401965e-01 4.04447764e-01 -5.34384131e-01 -6.12890661e-01
-6.98234141e-01 -8.36451054e-01 1.17205167e+00 -8.11463147e-02
4.68123285e-03 -8.58092248e-01 2.05285683e-01 8.86423528e-01
4.18185085e-01 2.69750595e-01 1.53791416e+00 -1.07661223e+00
-6.60864770e-01 -4.52023447e-01 -3.21014374e-01 6.51167750e-01
8.66248533e-02 -5.09376884e-01 -6.46404743e-01 -2.70154655e-01
-1.03844926e-01 -5.71862996e-01 4.48053479e-01 -1.21198349e-01
9.56924856e-01 -2.01787770e-01 7.27808103e-02 -1.42187700e-01
1.52308559e+00 5.46832800e-01 8.09489250e-01 4.10465151e-01
3.60567182e-01 7.74243891e-01 9.19777453e-01 3.04641485e-01
6.30151927e-01 4.02691960e-01 6.23430073e-01 2.09231555e-01
-5.26208393e-02 -3.73868287e-01 1.84279755e-01 1.10838485e+00
-3.27666067e-02 -5.02686024e-01 -1.36766589e+00 5.78168333e-01
-1.94425106e+00 -7.03916907e-01 -2.97529370e-01 2.11861515e+00
8.00519705e-01 2.29864661e-02 -2.27402538e-01 -2.05828249e-01
1.06783941e-01 -8.17382410e-02 -4.71127689e-01 -4.24543798e-01
1.63603485e-01 4.06532884e-01 1.53722003e-01 3.45280290e-01
-7.17436492e-01 8.15809488e-01 5.92602730e+00 5.24926305e-01
-4.09182966e-01 6.96475282e-02 1.64957251e-02 2.98433542e-01
-4.47365910e-01 -7.44774416e-02 -7.54104793e-01 -2.57436000e-02
1.43535554e+00 -4.87085730e-01 2.09201351e-01 5.95450044e-01
5.00402823e-02 1.36879813e-02 -1.04434896e+00 6.08240366e-01
-5.63111752e-02 -1.59271884e+00 5.20954967e-01 -1.78337261e-01
2.01174200e-01 1.85721815e-01 -4.23210800e-01 8.69404972e-01
3.76854032e-01 -7.68593848e-01 5.16618073e-01 1.00492096e+00
5.35976112e-01 -7.02744484e-01 1.34999263e+00 4.91630137e-01
-1.04039729e+00 -2.99079299e-01 -4.68668193e-01 3.96955252e-01
3.94524395e-01 5.42579949e-01 -1.04094982e+00 1.71100724e+00
8.19154441e-01 3.78090382e-01 -5.15470445e-01 9.90139306e-01
-1.05395548e-01 5.61406672e-01 3.00511019e-03 7.56528527e-02
3.13062131e-01 4.88595255e-02 4.48249012e-01 9.48698163e-01
3.44696283e-01 1.97029680e-01 -1.12534668e-02 9.18423772e-01
-2.93802589e-01 2.77445585e-01 -7.82435894e-01 -4.58626091e-01
1.85318723e-01 9.55877483e-01 5.49683794e-02 -4.94627953e-01
-5.11129797e-01 4.65312302e-01 1.81058645e-01 5.41410327e-01
-9.04137015e-01 -7.94966936e-01 3.01357388e-01 1.24008648e-01
2.52237588e-01 -2.27693722e-01 5.89747667e-01 -8.21210206e-01
2.63186246e-01 -1.11396599e+00 8.08057308e-01 -1.30452871e+00
-1.46679103e+00 1.00769925e+00 3.68156850e-01 -1.00967753e+00
-3.35475594e-01 -5.85828602e-01 4.78329090e-03 1.02188790e+00
-1.72578764e+00 -1.09093308e+00 -3.72467548e-01 7.32661128e-01
4.57825154e-01 -2.97672302e-01 8.19307804e-01 8.10702443e-01
-2.65078753e-01 -2.06088033e-02 -3.68616849e-01 2.25876361e-01
5.00419259e-01 -1.13085985e+00 2.93732554e-01 2.81666070e-01
8.04825407e-03 7.10622370e-01 2.97707498e-01 -9.66718376e-01
-1.64105928e+00 -1.43460000e+00 1.25030220e+00 -6.82716906e-01
8.90929580e-01 -3.11562419e-02 -1.00102925e+00 7.44118154e-01
5.40192544e-01 -4.41207498e-01 8.12857687e-01 -1.20507449e-01
-4.31112200e-02 -2.72834301e-01 -1.10707450e+00 1.16985679e-01
8.07515204e-01 -7.06377745e-01 -1.00036240e+00 8.55324507e-01
1.40914583e+00 -3.98315638e-01 -1.46461391e+00 5.87428093e-01
7.89376795e-02 -6.83677912e-01 7.97929585e-01 -1.31152689e+00
4.27037418e-01 -4.88650978e-01 -4.22114879e-01 -1.13787293e+00
-1.81015313e-01 -6.91487342e-02 1.38626928e-02 1.14812684e+00
6.76209867e-01 -7.76851594e-01 1.89055547e-01 8.44927371e-01
-5.81927836e-01 -8.02334666e-01 -8.50979745e-01 -8.03116024e-01
-8.72510299e-02 -7.04461873e-01 1.06742823e+00 8.14620316e-01
-5.32273129e-02 6.73914075e-01 1.71457171e-01 4.66140926e-01
5.90531202e-03 1.12329885e-01 5.64620435e-01 -1.21991694e+00
-2.05882579e-01 2.16365635e-01 -2.91500539e-01 -9.06185031e-01
-8.16079602e-02 -1.10850656e+00 -1.74249724e-01 -2.40699577e+00
-2.89792925e-01 -3.22388321e-01 -3.97553205e-01 8.62021685e-01
4.06989515e-01 -5.00861824e-01 -8.82818084e-03 -9.14881006e-03
-8.25989604e-01 6.80326700e-01 1.25157034e+00 -4.14036393e-01
1.70303702e-01 -1.64370120e-01 -7.31270850e-01 3.55793327e-01
6.97579741e-01 -3.45685661e-01 -5.50624192e-01 -7.45589614e-01
9.31009114e-01 4.69940394e-01 4.65113640e-01 -9.53106403e-01
5.29211223e-01 2.29686275e-01 -2.00924814e-01 -8.00897121e-01
1.51217654e-01 -9.79471326e-01 6.08948506e-02 1.07117459e-01
-3.24310988e-01 3.64725858e-01 5.03491700e-01 5.04534662e-01
-7.31385350e-01 -5.16197681e-01 1.60048958e-02 -2.46994048e-01
-7.91634142e-01 3.19220454e-01 -2.51364797e-01 1.89101145e-01
6.57320499e-01 3.88031662e-01 -8.22191000e-01 -5.20188093e-01
-6.82051539e-01 6.85719907e-01 -2.33030349e-01 5.65999210e-01
9.44591165e-01 -1.15286875e+00 -5.96317232e-01 1.80330783e-01
4.49915022e-01 8.47001001e-02 3.54857087e-01 7.85128593e-01
-7.90717542e-01 1.06745291e+00 1.73601899e-02 -1.75618336e-01
-8.30122113e-01 5.42778969e-01 2.89484471e-01 -6.35975838e-01
-4.31175083e-01 5.14485061e-01 -2.28941292e-01 -9.45985198e-01
-4.14359150e-03 -6.33654237e-01 -5.72686791e-01 -1.17514677e-01
4.15758491e-01 2.90010810e-01 6.46210194e-01 -3.35081279e-01
-3.25263470e-01 1.51112065e-01 -9.70001798e-03 1.27255321e-01
1.35629702e+00 2.24297360e-01 -5.12179494e-01 1.77167848e-01
9.30467844e-01 -1.20511845e-01 -2.38389418e-01 -1.25724897e-01
2.50780851e-01 -2.38683090e-01 -2.23315489e-02 -1.27222872e+00
-9.53375936e-01 6.85577929e-01 4.38153893e-01 7.53121197e-01
1.15284503e+00 2.74420470e-01 1.12949169e+00 8.92283797e-01
7.02850103e-01 -8.26943398e-01 -2.59997845e-01 7.14719057e-01
1.35942388e+00 -8.16844821e-01 -2.30907485e-01 -2.04218522e-01
-6.38593733e-01 9.38752592e-01 4.71674532e-01 3.48134696e-01
6.16694510e-01 -1.06208473e-01 -2.72621459e-04 -1.05965829e+00
-9.54801559e-01 -3.32643300e-01 5.10616899e-01 4.33335930e-01
2.44007722e-01 -3.04217875e-01 -2.42231175e-01 7.73967266e-01
-1.22762688e-01 4.57271874e-01 7.52823129e-02 1.23108578e+00
-5.48045397e-01 -1.08116794e+00 2.00637113e-02 5.34379721e-01
-2.07297340e-01 -2.07173392e-01 -4.04097527e-01 8.86933386e-01
-7.33730644e-02 1.29841840e+00 -3.26327115e-01 -6.28476739e-01
1.17327309e+00 2.61965156e-01 1.20048776e-01 -7.89679885e-01
-8.43353510e-01 -5.46521366e-01 8.46788287e-01 -7.43315220e-01
-3.13176662e-01 -1.11007251e-01 -1.44139683e+00 8.89765397e-02
-1.49074778e-01 8.00295889e-01 5.98513782e-01 9.94608700e-01
6.47502363e-01 9.15310025e-01 6.26945794e-02 2.62154281e-01
-5.10320604e-01 -7.85950303e-01 -6.42058730e-01 2.81088829e-01
-4.31551896e-02 -4.33604479e-01 8.81204680e-02 -8.86119381e-02] | [10.356539726257324, 7.928412914276123] |
71cbffa2-3bfb-4a16-b7f1-0496530cc659 | uncertainty-aware-deep-learning-for-digital | 2303.10954 | null | https://arxiv.org/abs/2303.10954v1 | https://arxiv.org/pdf/2303.10954v1.pdf | Uncertainty-aware deep learning for digital twin-driven monitoring: Application to fault detection in power lines | Deep neural networks (DNNs) are often coupled with physics-based models or data-driven surrogate models to perform fault detection and health monitoring of systems in the low data regime. These models serve as digital twins to generate large quantities of data to train DNNs which would otherwise be difficult to obtain from the real-life system. However, such models can exhibit parametric uncertainty that propagates to the generated data. In addition, DNNs exhibit uncertainty in the parameters learnt during training. In such a scenario, the performance of the DNN model will be influenced by the uncertainty in the physics-based model as well as the parameters of the DNN. In this article, we quantify the impact of both these sources of uncertainty on the performance of the DNN. We perform explicit propagation of uncertainty in input data through all layers of the DNN, as well as implicit prediction of output uncertainty to capture the former. Furthermore, we adopt Monte Carlo dropout to capture uncertainty in DNN parameters. We demonstrate the approach for fault detection of power lines with a physics-based model, two types of input data and three different neural network architectures. We compare the performance of such uncertainty-aware probabilistic models with their deterministic counterparts. The results show that the probabilistic models provide important information regarding the confidence of predictions, while also delivering an improvement in performance over deterministic models. | ['Giovanni Sansavini', 'Blazhe Gjorgiev', 'Laya Das'] | 2023-03-20 | null | null | null | null | ['fault-detection'] | ['miscellaneous'] | [-1.77076623e-01 8.21096003e-02 2.85732448e-01 -4.40582156e-01
-6.86701536e-01 -2.67513365e-01 5.67956567e-01 2.56752282e-01
7.48864934e-02 1.17209101e+00 -8.34990963e-02 -2.13216409e-01
-4.60704237e-01 -1.18945968e+00 -1.20557094e+00 -9.25991535e-01
-9.92907956e-02 9.18889225e-01 1.99517146e-01 -1.12613872e-01
-3.39122802e-01 7.50276923e-01 -1.28023481e+00 1.10137641e-01
9.48814452e-01 1.25255537e+00 -2.94168890e-01 5.30790150e-01
-7.14305323e-03 7.72035837e-01 -1.08274996e+00 -7.50828609e-02
1.23211481e-02 -1.30464047e-01 -2.73683906e-01 -4.88040209e-01
-3.03456634e-02 -6.86092794e-01 -9.20391679e-01 1.21358693e+00
3.58476967e-01 5.64049669e-02 8.10053647e-01 -1.30208147e+00
-2.67765343e-01 1.07504022e+00 -2.64938120e-02 5.93611598e-02
-1.00273922e-01 5.93241572e-01 5.23706317e-01 -1.78842187e-01
-7.46374354e-02 1.04525137e+00 8.23046982e-01 4.12068516e-01
-1.27639019e+00 -4.73543167e-01 -2.12548673e-01 -7.24224970e-02
-1.24744463e+00 -1.95975974e-01 8.08688283e-01 -4.73182946e-01
6.36891603e-01 -2.24190816e-01 5.25032401e-01 1.42059171e+00
6.29231930e-01 5.25464475e-01 6.52508974e-01 -2.46028572e-01
7.68545806e-01 -5.48872980e-04 2.77266949e-01 4.04247224e-01
4.97087777e-01 8.25114787e-01 -4.90768492e-01 -4.00567383e-01
6.57340229e-01 9.61583927e-02 -3.82569492e-01 1.97089668e-02
-4.84337956e-01 5.78310490e-01 7.61919260e-01 5.24883419e-02
-5.27035773e-01 9.51308489e-01 2.88416028e-01 1.80020451e-03
2.71306902e-01 3.48410875e-01 -4.34826404e-01 2.17291676e-02
-1.12902319e+00 4.51778859e-01 8.84746969e-01 6.33239985e-01
4.76017475e-01 5.63490212e-01 -5.82586348e-01 4.16999459e-01
6.33490622e-01 6.94753647e-01 6.92991540e-02 -6.23863816e-01
2.03554690e-01 3.02976221e-01 2.65345305e-01 -4.01066184e-01
-4.44988877e-01 -7.12391555e-01 -9.37808931e-01 4.58681047e-01
5.03523290e-01 -4.61874098e-01 -1.37255144e+00 1.65593433e+00
-8.20269734e-02 3.47524434e-01 -2.84629781e-03 6.89498484e-01
3.32606345e-01 8.82421553e-01 -7.45807365e-02 3.98428112e-01
8.35251391e-01 -3.61452550e-01 -6.66052759e-01 5.87993348e-03
4.67142314e-01 -1.06165446e-01 5.33642530e-01 4.83011067e-01
-1.03243220e+00 -3.34583938e-01 -1.42863369e+00 5.70442080e-01
-2.00575143e-01 -3.69315147e-02 2.12320402e-01 8.11579943e-01
-9.53570127e-01 1.21747291e+00 -1.09869790e+00 1.09150879e-01
4.67461914e-01 2.69337684e-01 3.90830845e-01 -1.88945413e-01
-1.81325376e+00 9.02566135e-01 4.85263288e-01 5.90327621e-01
-1.71817946e+00 -1.13095558e+00 -6.07861996e-01 3.67504567e-01
6.07404672e-02 -7.24902451e-01 1.38608539e+00 -4.24843311e-01
-1.27615249e+00 -2.68493682e-01 4.91211265e-01 -9.57064688e-01
7.92758405e-01 -1.36051312e-01 -4.81951326e-01 6.75778463e-02
-3.85294288e-01 2.24130526e-01 6.98149860e-01 -1.26693332e+00
-2.57236212e-01 -5.32395802e-02 8.01461041e-02 -4.42056328e-01
2.50387788e-01 -5.36737621e-01 5.06536588e-02 -4.86396998e-01
-1.78930447e-01 -6.29619420e-01 -3.67970526e-01 1.43258467e-01
-8.38753462e-01 1.28442749e-01 7.34877586e-01 -6.10833287e-01
7.34367073e-01 -1.90350091e+00 -3.93365651e-01 5.15495181e-01
7.46892542e-02 1.22946255e-01 2.92156547e-01 5.66197038e-01
1.06433176e-01 5.54812467e-03 -5.83930314e-01 -1.26201138e-01
3.61418515e-01 5.48093021e-01 -4.91416782e-01 3.44880641e-01
6.12988651e-01 7.74461091e-01 -6.59466326e-01 1.19187497e-01
3.67373198e-01 7.16869056e-01 -2.61506379e-01 2.49683455e-01
-7.61407614e-01 3.70318651e-01 -5.76860249e-01 2.70985216e-01
7.27247596e-01 2.73243692e-02 -1.96529835e-01 -3.64001751e-01
3.76744658e-01 3.71594489e-01 -9.82539535e-01 1.14596486e+00
-6.77013457e-01 4.12935555e-01 -1.16240688e-01 -8.50242913e-01
8.11808944e-01 4.05727148e-01 2.68490434e-01 -3.91613990e-01
3.20471168e-01 1.25639021e-01 2.03512132e-01 -7.44380280e-02
2.30824262e-01 -4.90576267e-01 -1.70978144e-01 4.39016163e-01
4.17012036e-01 -4.12454009e-01 -5.49107157e-02 1.02179796e-01
1.47674358e+00 -8.46438706e-02 -5.52760363e-01 -4.39843535e-01
6.32307455e-02 -8.39803517e-02 6.16378903e-01 9.88491178e-01
1.29799306e-01 5.91582179e-01 8.76897693e-01 -2.85151958e-01
-1.14058208e+00 -1.54335487e+00 -4.59969282e-01 -8.75326991e-02
-1.85487419e-01 2.09944695e-01 -8.84886682e-01 -6.15831792e-01
3.87844771e-01 1.38297665e+00 -5.82851946e-01 -8.23737979e-01
-1.25976264e-01 -1.31267023e+00 8.76998484e-01 8.19103301e-01
3.51443857e-01 -6.42452776e-01 -3.04387152e-01 4.80302751e-01
4.66644019e-01 -8.98722529e-01 3.29798222e-01 6.99623346e-01
-8.85597944e-01 -9.18850183e-01 -4.71923530e-01 1.20716617e-01
6.08140886e-01 -8.62520814e-01 1.20160902e+00 3.48414667e-02
-3.30821365e-01 2.03804255e-01 -1.07199326e-02 -4.08273071e-01
-9.26563978e-01 -2.89997458e-01 2.69471586e-01 -2.24071145e-01
-1.15404993e-01 -7.47980416e-01 -4.00064379e-01 7.72894993e-02
-1.18080592e+00 -3.04825068e-01 3.56104165e-01 8.71437311e-01
2.68032074e-01 7.92462826e-01 5.95340967e-01 -8.22759986e-01
6.21162772e-01 -6.35796905e-01 -1.10365617e+00 2.75705308e-01
-7.06490278e-01 5.91122687e-01 9.19026315e-01 -1.69572562e-01
-1.18827868e+00 -1.48131475e-01 -3.76457244e-01 -6.25821590e-01
-1.03506990e-01 6.14172697e-01 -4.14069146e-01 1.17171355e-01
6.64854050e-01 -1.26453161e-01 -3.56821656e-01 -3.76166523e-01
2.34579705e-02 3.40821534e-01 6.58330798e-01 -1.13644874e+00
8.80546510e-01 2.66093016e-01 3.25883806e-01 -4.15727615e-01
-6.81483448e-01 5.25755703e-01 -3.82147759e-01 -2.82718658e-01
3.40731114e-01 -7.52107739e-01 -4.92253661e-01 8.52822065e-01
-1.20925260e+00 -4.45999503e-01 -8.49169195e-01 5.43749034e-01
-4.15902227e-01 -1.30236566e-01 -8.81115496e-01 -1.02423465e+00
-1.34520665e-01 -1.30218315e+00 7.86931753e-01 3.50712270e-01
2.00364903e-01 -1.21903384e+00 -6.82952106e-02 -3.97860318e-01
5.70600510e-01 5.34867167e-01 1.34606600e+00 -7.95538723e-01
-7.11993814e-01 -6.47760510e-01 -2.25305185e-01 7.57605493e-01
-3.40767890e-01 4.19585705e-01 -1.26478648e+00 6.57403320e-02
3.61218095e-01 -2.15740159e-01 7.47235298e-01 8.10964227e-01
1.09286368e+00 -1.33330703e-01 -2.03164533e-01 2.63102323e-01
1.62052321e+00 8.47995803e-02 5.61280429e-01 -3.11304957e-01
4.93766755e-01 3.46431881e-01 -1.22208513e-01 5.65732062e-01
-8.54454860e-02 3.26396048e-01 6.53648913e-01 2.34511122e-01
9.17946100e-02 -3.48703593e-01 2.44725972e-01 4.06977296e-01
5.12568653e-01 -5.80542743e-01 -1.29123771e+00 3.53388608e-01
-1.68667412e+00 -5.84724128e-01 -3.74738961e-01 2.30240655e+00
7.40675807e-01 7.49435782e-01 -2.85755306e-01 2.02227890e-01
6.56342030e-01 -2.59352475e-01 -8.76016736e-01 -2.48260975e-01
-2.74311528e-02 1.82624176e-01 6.18675649e-01 3.76987964e-01
-6.33510768e-01 1.49096981e-01 6.50564623e+00 7.49766827e-01
-8.69981825e-01 -1.89588182e-02 8.85613501e-01 -1.88400134e-01
-5.75976610e-01 -1.20382700e-02 -7.28712142e-01 7.42739320e-01
1.75509048e+00 -1.71456620e-01 9.62593257e-02 5.61493695e-01
3.91018182e-01 -4.70873445e-01 -1.45113790e+00 3.83577794e-01
-5.47495723e-01 -1.37049985e+00 5.17400466e-02 6.71885833e-02
8.83758783e-01 3.15868706e-01 -6.69629276e-02 3.99344772e-01
9.63540137e-01 -1.13244295e+00 8.53557169e-01 1.01507139e+00
4.59554553e-01 -1.02332282e+00 1.15055323e+00 4.85000551e-01
-4.71513420e-01 -2.91800145e-02 -3.44104946e-01 1.15834668e-01
4.07709569e-01 1.74959934e+00 -6.88701749e-01 5.97320020e-01
4.74495023e-01 1.21093638e-01 -2.20492482e-01 1.28901935e+00
-4.69279408e-01 1.11094701e+00 -7.91665137e-01 1.08976118e-01
3.23090613e-01 1.02235548e-01 4.11612660e-01 6.73610210e-01
3.24745089e-01 -3.54847699e-01 -5.52705862e-02 1.70506811e+00
-2.36598447e-01 -1.00869703e+00 -3.14897925e-01 -1.07735597e-01
4.79730427e-01 7.78456211e-01 -4.08338487e-01 -2.23243222e-01
4.09195535e-02 3.73194784e-01 -1.32724151e-01 4.56947386e-01
-1.17841136e+00 -1.87478215e-01 6.18574262e-01 1.27065629e-01
-6.75758198e-02 1.54632973e-02 -3.48417670e-01 -7.15731323e-01
1.37222335e-02 -3.11291277e-01 9.50497314e-02 -8.67118120e-01
-1.61768663e+00 5.59468150e-01 2.11891010e-01 -8.41278672e-01
-5.03054917e-01 -8.05748641e-01 -8.41622412e-01 1.31338394e+00
-1.35493386e+00 -6.81650400e-01 1.11498393e-01 7.21344650e-02
-7.99098834e-02 2.34621540e-01 5.48652470e-01 1.60309851e-01
-8.44557166e-01 3.29667866e-01 6.40108645e-01 1.82587385e-01
1.89426720e-01 -1.21926844e+00 5.62102735e-01 7.64340758e-01
-2.33836487e-01 1.92229152e-01 1.04378355e+00 -7.86825895e-01
-1.13849998e+00 -1.25237226e+00 4.92675602e-02 -3.78605306e-01
8.97818506e-01 -3.18661511e-01 -1.09604108e+00 2.81457692e-01
-9.54683200e-02 4.47162241e-01 2.68810719e-01 -1.47453591e-01
-7.10932165e-02 -7.39852265e-02 -1.62998784e+00 3.47457826e-02
2.84440130e-01 -6.05998814e-01 -4.36129212e-01 2.37084642e-01
7.28018105e-01 -4.57108468e-01 -9.00515139e-01 5.45030117e-01
2.97567785e-01 -9.37745035e-01 7.32691944e-01 -4.48926419e-01
5.61026871e-01 -3.26316029e-01 -1.82544500e-01 -1.69817054e+00
1.36806354e-01 -1.79389820e-01 -5.24302602e-01 1.31426454e+00
6.69449270e-01 -5.40434897e-01 7.41658926e-01 1.16237152e+00
-3.21251929e-01 -6.96585715e-01 -1.12860894e+00 -9.32530880e-01
4.43437070e-01 -9.02423918e-01 9.87205565e-01 4.37395602e-01
-4.46791828e-01 -2.77108520e-01 3.48643847e-02 8.28251421e-01
8.52884889e-01 -3.05916905e-01 -2.93907505e-02 -1.31116092e+00
-4.34791833e-01 -2.82263786e-01 -4.46771890e-01 -4.53493297e-01
5.48133627e-02 -4.32375371e-01 4.10199791e-01 -1.50875950e+00
-2.04442501e-01 -6.15069091e-01 -5.62678576e-01 8.93788338e-02
7.62178078e-02 -3.26581001e-01 -1.89354002e-01 -6.45697191e-02
1.10847540e-01 8.70905161e-01 4.65982467e-01 -2.30748639e-01
2.25170180e-01 3.37960064e-01 -5.69784865e-02 6.07133269e-01
7.22392201e-01 -8.81347239e-01 -3.90782088e-01 -4.10568923e-01
3.51814955e-01 2.69344509e-01 8.72964442e-01 -1.62226188e+00
3.30512106e-01 1.83024555e-01 7.64416099e-01 -6.98349357e-01
1.85522720e-01 -9.62220907e-01 2.98193455e-01 6.04322135e-01
-1.51480779e-01 -3.05973798e-01 5.90420008e-01 6.94878042e-01
-1.71312228e-01 -6.30314052e-01 7.59193718e-01 3.21830660e-02
-1.92943946e-01 3.01856786e-01 -5.90462089e-01 5.13373017e-02
5.33538282e-01 3.14263046e-01 -2.67006248e-01 -3.55933487e-01
-6.68692946e-01 5.10388255e-01 2.75535196e-01 5.85933961e-02
3.27566385e-01 -1.18308520e+00 -5.52649677e-01 1.53182343e-01
-2.19970673e-01 4.17803794e-01 4.97426063e-01 3.66346717e-01
-4.37437683e-01 2.36383304e-01 -2.54220190e-03 -6.18877649e-01
1.15707695e-01 2.15895429e-01 1.01085162e+00 -3.31783682e-01
-4.43685114e-01 7.46422052e-01 -2.89991572e-02 -6.05012000e-01
1.84594080e-01 -7.59433210e-01 4.41967726e-01 -2.77424127e-01
2.74940938e-01 3.67315620e-01 4.49292064e-01 5.05743697e-02
-1.41190976e-01 -1.72152832e-01 1.28080130e-01 -1.60085231e-01
1.26765358e+00 2.77550668e-01 8.97524208e-02 7.85926819e-01
7.74487972e-01 -6.24572515e-01 -1.74169338e+00 -1.84613332e-01
1.54085476e-02 1.34968802e-01 7.13732064e-01 -1.24153435e+00
-1.34141219e+00 1.10277605e+00 6.30628109e-01 2.87240744e-01
9.14763153e-01 -1.91357881e-01 6.65204227e-01 3.05489898e-01
4.15431857e-01 -1.02378941e+00 -5.77968895e-01 3.03271741e-01
6.11791432e-01 -8.16110849e-01 -1.07910097e-01 1.22787140e-01
-8.86240005e-02 1.19077170e+00 5.84739029e-01 -3.69314224e-01
1.06973851e+00 9.08092022e-01 -3.16510409e-01 -2.06210405e-01
-9.32574868e-01 4.02688175e-01 1.08910024e-01 4.67469066e-01
-1.78005528e-02 -4.58418503e-02 5.82651615e-01 9.65929985e-01
1.30501002e-01 2.06554547e-01 6.97881937e-01 9.15305078e-01
-1.84267953e-01 -7.54265487e-01 -4.75346297e-01 8.11569631e-01
-2.71524698e-01 -9.20936316e-02 1.39586508e-01 5.52872241e-01
-1.98951185e-01 6.76141918e-01 1.82795316e-01 -1.97349116e-01
5.02596557e-01 1.74062356e-01 3.12587976e-01 -4.51094508e-01
-5.24161220e-01 -4.36412334e-01 1.29778191e-01 -3.86013865e-01
4.74929541e-01 -4.33006048e-01 -1.45079756e+00 -3.93629462e-01
-3.69547665e-01 2.37511382e-01 8.85432482e-01 1.12320495e+00
1.45369619e-01 1.24701476e+00 4.41921592e-01 -9.15001094e-01
-1.17610621e+00 -8.89186382e-01 -9.07418907e-01 -2.45274737e-01
4.74052638e-01 -6.73807442e-01 -6.59001291e-01 -5.39158344e-01] | [7.216508388519287, 3.699934244155884] |
1817c8f2-3d6f-447b-af48-a52f4bf86ae9 | cutting-edge-techniques-for-depth-map-super | 2306.15244 | null | https://arxiv.org/abs/2306.15244v1 | https://arxiv.org/pdf/2306.15244v1.pdf | Cutting-Edge Techniques for Depth Map Super-Resolution | To overcome hardware limitations in commercially available depth sensors which result in low-resolution depth maps, depth map super-resolution (DMSR) is a practical and valuable computer vision task. DMSR requires upscaling a low-resolution (LR) depth map into a high-resolution (HR) space. Joint image filtering for DMSR has been applied using spatially-invariant and spatially-variant convolutional neural network (CNN) approaches. In this project, we propose a novel joint image filtering DMSR algorithm using a Swin transformer architecture. Furthermore, we introduce a Nonlinear Activation Free (NAF) network based on a conventional CNN model used in cutting-edge image restoration applications and compare the performance of the techniques. The proposed algorithms are validated through numerical studies and visual examples demonstrating improvements to state-of-the-art performance while maintaining competitive computation time for noisy depth map super-resolution. | ['Josiah Smith', 'Ryan Peterson'] | 2023-06-27 | null | null | null | null | ['depth-map-super-resolution', 'super-resolution', 'image-restoration'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [ 8.32265615e-01 4.73682098e-02 3.93181711e-01 -3.10553640e-01
-9.53962684e-01 2.08703458e-01 4.63164121e-01 -4.13458675e-01
-6.96561992e-01 1.09432983e+00 3.82756650e-01 1.66665018e-01
-3.55859339e-01 -1.14577615e+00 -5.90773404e-01 -4.79661196e-01
3.02154303e-01 1.01463445e-01 6.64201915e-01 -5.42998791e-01
4.39027339e-01 9.54940796e-01 -1.97974932e+00 4.50926453e-01
8.07753980e-01 8.82109880e-01 7.21214116e-01 7.89093018e-01
6.77276701e-02 5.80829144e-01 -4.95226651e-01 1.47603631e-01
5.40494859e-01 -1.86135426e-01 -7.92786181e-01 -2.29682058e-01
9.37992394e-01 -5.30120432e-01 -5.48747718e-01 1.25530708e+00
5.09983122e-01 2.62448967e-01 1.32750794e-01 -3.47419351e-01
-6.60916388e-01 2.84213066e-01 -6.32894814e-01 6.31487489e-01
3.34329188e-01 -3.22454095e-01 1.90898538e-01 -9.04396117e-01
8.95210683e-01 1.17463183e+00 8.22638869e-01 7.75122881e-01
-1.29031813e+00 -5.92408359e-01 -3.45125079e-01 1.05391018e-01
-1.25893509e+00 -1.92516670e-01 6.12922192e-01 -8.04762095e-02
1.27045548e+00 1.55567884e-01 4.08195078e-01 5.60526073e-01
3.67494822e-01 -9.51473117e-02 1.50816059e+00 -2.67382026e-01
2.76258022e-01 -1.78535134e-01 -1.15781024e-01 5.98828137e-01
3.34261775e-01 3.88168126e-01 -9.25296843e-01 3.47145438e-01
1.71782160e+00 -1.87401593e-01 -4.15445507e-01 1.79085329e-01
-9.05259907e-01 4.96554464e-01 7.22954750e-01 5.62288344e-01
-4.96799350e-01 1.53696895e-01 -8.01516399e-02 1.10473946e-01
7.57282555e-01 2.72884846e-01 -1.28937453e-01 8.42362270e-02
-1.18250799e+00 1.99432582e-01 -1.53892012e-02 5.14595509e-01
9.30894136e-01 4.17023212e-01 8.76794010e-02 7.68508673e-01
-1.65089145e-01 1.83544844e-01 6.04559839e-01 -1.30986416e+00
2.08918974e-01 3.28660637e-01 1.59005389e-01 -7.66826093e-01
-4.54468757e-01 -4.45013851e-01 -1.23391378e+00 1.05202699e+00
2.53452897e-01 3.87502939e-01 -1.27783954e+00 1.21480691e+00
8.99979472e-02 1.90857083e-01 4.52926815e-01 1.23458600e+00
1.11120629e+00 6.88724577e-01 -3.71707916e-01 -1.57947868e-01
1.17483962e+00 -5.37012100e-01 -7.71163344e-01 -2.80471295e-01
-2.28270888e-01 -5.19631565e-01 7.49514043e-01 6.99135959e-01
-1.48282957e+00 -7.49346256e-01 -1.30499530e+00 -7.92463601e-01
-2.71896631e-01 -6.81599788e-03 5.04087925e-01 4.48409528e-01
-1.50450730e+00 9.91337836e-01 -7.12617755e-01 -1.45016044e-01
3.53306532e-01 4.81362462e-01 -7.29291320e-01 -3.00091684e-01
-1.06756246e+00 9.03697848e-01 1.94929853e-01 1.78695083e-01
-7.09441006e-01 -9.11464036e-01 -7.07664251e-01 -1.35864198e-01
-2.57211417e-01 -6.73317134e-01 8.71974409e-01 -6.06185198e-01
-1.70668113e+00 8.70981038e-01 -3.16424608e-01 -7.11117566e-01
5.90947092e-01 -2.02378824e-01 -2.87344605e-01 4.94177610e-01
1.22914044e-02 6.79312170e-01 7.93001831e-01 -1.29396009e+00
-1.04467165e+00 -6.92821622e-01 -3.18205543e-02 2.64590234e-01
1.44264802e-01 -4.13481183e-02 -7.50990957e-02 -5.93681097e-01
8.44573617e-01 -1.52305350e-01 -4.02869493e-01 9.56207886e-02
1.77478924e-01 4.48167950e-01 8.37830603e-01 -9.72604990e-01
7.74357200e-01 -1.87091136e+00 2.28941366e-01 -7.50926509e-02
3.44471782e-01 1.45879656e-01 1.84537500e-01 -1.25578776e-01
-2.60912359e-01 -1.64849967e-01 -3.28291893e-01 -5.07806420e-01
-9.36744630e-01 3.23780715e-01 -3.55240218e-02 6.49821877e-01
7.84486905e-03 5.65434515e-01 -6.36671066e-01 -2.17868894e-01
6.41255319e-01 1.23571575e+00 -3.05537879e-01 -9.82302874e-02
3.22979391e-01 7.22298622e-01 6.00441322e-02 5.65036714e-01
9.59302008e-01 1.47288918e-01 -3.46825063e-01 -6.73606038e-01
-7.13749349e-01 -1.71410844e-01 -1.26167071e+00 1.80110276e+00
-8.54273677e-01 9.74682570e-01 3.37280631e-01 -6.80231273e-01
1.27895892e+00 1.26505960e-02 2.20836893e-01 -1.19479382e+00
-7.58231953e-02 4.34296757e-01 -5.95863581e-01 -9.45551395e-02
1.05308938e+00 -4.60109830e-01 5.56790650e-01 -1.92170560e-01
9.16133523e-02 -3.39974076e-01 -2.28979126e-01 -1.82084441e-01
9.93338346e-01 2.91209817e-02 8.43578950e-02 -4.74321902e-01
7.50469148e-01 -1.15695028e-02 4.57139939e-01 5.95648885e-01
6.21961802e-02 1.18166351e+00 -1.34826899e-01 -7.19621837e-01
-1.38068891e+00 -1.05377340e+00 -3.65296513e-01 2.45891094e-01
2.57599652e-01 2.77888834e-01 -7.45147169e-01 3.38869363e-01
-3.56926680e-01 1.39650822e-01 -7.52962947e-01 2.39639193e-01
-9.45028007e-01 -7.07836330e-01 2.11326644e-01 6.67531908e-01
1.17212629e+00 -8.22459340e-01 -9.43676353e-01 2.48377427e-01
-1.85097948e-01 -1.39119029e+00 2.13285998e-01 2.20554009e-01
-1.32477617e+00 -7.81233370e-01 -9.81151879e-01 -8.98376226e-01
5.62445283e-01 3.27377796e-01 9.76272643e-01 -2.67827153e-01
-6.24951005e-01 3.13003622e-02 -1.60359904e-01 1.03956029e-01
-2.27456257e-01 -2.98260540e-01 -6.11738414e-02 -1.29349187e-01
-7.83901364e-02 -8.52568150e-01 -7.76589572e-01 1.02925837e-01
-1.10423613e+00 2.72768766e-01 5.78230143e-01 8.45501304e-01
9.62160289e-01 4.47444022e-01 3.89770985e-01 -6.13199234e-01
4.64328974e-01 2.78258979e-01 -1.05788994e+00 -2.76656032e-01
-7.04399228e-01 7.24068880e-02 4.04111981e-01 -1.69086710e-01
-1.48368299e+00 2.10347340e-01 -2.25532100e-01 -4.71865445e-01
-1.18832849e-01 -8.74739327e-03 1.61476970e-01 -6.77996516e-01
9.20436740e-01 3.75376940e-01 5.45506477e-02 -5.26145220e-01
9.05262679e-02 5.66522121e-01 1.28381276e+00 -7.72782937e-02
8.60152364e-01 1.18984652e+00 4.13160682e-01 -1.11680758e+00
-6.26282752e-01 -3.95245254e-01 -6.15230501e-01 -2.78894097e-01
1.17765915e+00 -1.24566483e+00 -5.53906620e-01 6.52605414e-01
-9.84024107e-01 -2.85872161e-01 -3.30775112e-01 5.33463955e-01
-5.63007474e-01 1.55337766e-01 -8.19529653e-01 -7.86192119e-01
-3.75652105e-01 -1.05779958e+00 1.02580428e+00 7.19471633e-01
3.98731530e-01 -7.56763399e-01 -1.28348365e-01 5.87957203e-01
9.69172776e-01 4.49887097e-01 4.54799771e-01 4.38665241e-01
-1.08929002e+00 1.16451830e-01 -7.00697660e-01 4.89398241e-01
3.32615338e-02 -3.64093870e-01 -1.08711982e+00 -1.77351475e-01
2.38356307e-01 7.53553659e-02 1.07987654e+00 7.62451410e-01
9.55170214e-01 2.25067526e-01 -1.54953059e-02 1.14105761e+00
2.31723404e+00 8.75262767e-02 1.22671902e+00 7.05393076e-01
5.41962087e-01 4.22607452e-01 4.87979531e-01 1.96570024e-01
2.00064126e-02 6.67640924e-01 5.58197975e-01 -3.72175276e-01
-6.61140800e-01 -2.72060409e-02 -7.95869753e-02 1.17203884e-01
-6.00794613e-01 3.12857926e-01 -5.65122783e-01 7.31281161e-01
-1.53042603e+00 -9.51585829e-01 -3.37482631e-01 2.15146327e+00
6.68267608e-01 1.01671606e-01 -5.49403906e-01 3.94049942e-01
7.37690628e-01 8.59234929e-02 -2.78566569e-01 -3.48932028e-01
-5.73744953e-01 8.96081388e-01 1.03137898e+00 9.76987541e-01
-8.40194941e-01 8.39236975e-01 6.51539850e+00 8.26722503e-01
-1.21182132e+00 3.47362697e-01 4.56648499e-01 -2.84909923e-03
7.20603392e-04 -5.03470659e-01 -9.17403460e-01 -1.46079008e-02
7.17335105e-01 -2.56088078e-02 4.67112929e-01 5.22720933e-01
3.12272310e-01 -6.19927943e-01 -5.73303580e-01 1.59391046e+00
1.22885585e-01 -1.73593724e+00 2.84552332e-02 -1.67667612e-01
1.03817606e+00 1.63627833e-01 1.38137072e-01 -3.72005284e-01
-4.85767499e-02 -1.28813207e+00 3.83470565e-01 6.10504985e-01
1.13740802e+00 -1.01402295e+00 8.07198286e-01 -9.26088914e-02
-1.30546916e+00 -3.01048785e-01 -7.45332420e-01 -1.39710054e-01
2.50375718e-01 7.05661535e-01 -8.59623626e-02 6.18933558e-01
1.29310644e+00 4.49391127e-01 -4.05468196e-01 8.21166217e-01
7.71385133e-02 -2.73442954e-01 -2.41828144e-01 6.08738601e-01
6.71204329e-02 -1.61285758e-01 4.39621776e-01 9.01010215e-01
3.28672945e-01 5.81569612e-01 -6.40134156e-01 9.99722838e-01
1.00946501e-01 -3.98657501e-01 -4.48706388e-01 6.34489238e-01
1.24238603e-01 1.27018273e+00 -8.38014901e-01 -2.92199045e-01
-2.63794124e-01 1.13403118e+00 -4.58313487e-02 2.80212641e-01
-3.18346977e-01 -3.80845606e-01 7.70597637e-01 4.88110304e-01
6.68207482e-02 -2.17535853e-01 -6.81151330e-01 -9.77854550e-01
-2.47214399e-02 -2.97502160e-01 -5.57614863e-02 -1.21417511e+00
-8.28319311e-01 9.81010616e-01 -1.97728295e-02 -1.12882090e+00
-1.02058612e-02 -5.58959365e-01 -1.28355652e-01 1.38455403e+00
-2.05307961e+00 -9.95540380e-01 -9.94826078e-01 8.45783353e-01
7.22428381e-01 5.74069247e-02 5.52600622e-01 4.75928664e-01
5.83409183e-02 1.23219974e-01 5.63581549e-02 -9.80805382e-02
2.88869679e-01 -1.13020432e+00 3.94773334e-01 1.09432948e+00
-5.16798139e-01 1.87477157e-01 8.95807147e-01 -7.41127968e-01
-9.63558078e-01 -1.04508817e+00 5.37721932e-01 8.35522339e-02
1.63625064e-03 -6.16010390e-02 -1.09868765e+00 4.16280180e-01
-9.49516222e-02 3.15391958e-01 -2.21510679e-01 -6.22239709e-01
-1.52884305e-01 -3.12696338e-01 -1.86110795e+00 2.56250739e-01
1.05538476e+00 -6.94944203e-01 -5.74864149e-01 -8.38882923e-02
6.73234403e-01 -8.03196073e-01 -8.14451516e-01 6.03309691e-01
4.82777923e-01 -1.51077414e+00 1.37427664e+00 3.37002039e-01
6.62009478e-01 -5.97517669e-01 -3.05152595e-01 -1.02333224e+00
-2.78552711e-01 -2.57377535e-01 2.22760797e-01 5.74500322e-01
4.22347523e-02 -6.64581597e-01 1.18515337e+00 4.23670918e-01
-2.88818389e-01 -4.69224989e-01 -1.31790447e+00 -6.00523710e-01
-1.72280252e-01 -1.26698732e-01 1.20759353e-01 6.38810873e-01
-4.42407042e-01 -9.48986560e-02 -2.32190058e-01 6.65396094e-01
1.19375575e+00 -2.70849109e-01 1.50103435e-01 -1.37540174e+00
5.04934452e-02 -1.19161732e-01 -7.31958091e-01 -7.05449283e-01
-3.54760170e-01 -4.09992009e-01 -3.63265388e-02 -1.94294930e+00
-7.79370666e-02 -6.41716942e-02 -9.44178924e-02 1.81204304e-02
2.94617832e-01 1.01319778e+00 -2.07149506e-01 2.11181697e-02
1.86414018e-01 1.69024393e-01 1.22069657e+00 2.80197024e-01
-3.57436061e-01 -3.48328441e-01 -1.76278055e-01 6.01923287e-01
7.50729144e-01 -1.09954514e-01 -3.44538778e-01 -5.11576295e-01
2.01073766e-01 4.15037334e-01 5.07822514e-01 -1.54322350e+00
4.72108573e-01 2.90965706e-01 6.96193933e-01 -7.91114569e-01
8.25839937e-01 -7.28121102e-01 4.65046227e-01 4.33158457e-01
-1.08046867e-01 8.57505128e-02 2.69175589e-01 3.22207391e-01
-5.30367315e-01 4.53013508e-03 1.51960909e+00 -4.80690777e-01
-9.36294973e-01 9.38340873e-02 -2.67392486e-01 -4.81071889e-01
6.82214737e-01 -8.17009568e-01 -4.31155860e-01 -2.09778771e-01
-8.75501037e-01 -5.02177656e-01 5.43235540e-01 1.90315872e-01
1.39022899e+00 -9.40588593e-01 -6.71903908e-01 3.27715427e-01
-2.96444148e-01 4.02268350e-01 7.40706682e-01 3.40246826e-01
-1.18177295e+00 3.55801046e-01 -8.70905936e-01 -4.22313571e-01
-1.43785036e+00 2.09215656e-01 7.73319721e-01 -1.16158903e-01
-1.18930972e+00 9.65901911e-01 1.45216868e-03 2.75115129e-02
9.87295527e-03 -4.76106614e-01 -3.76334786e-01 -3.44146371e-01
1.00186157e+00 5.60358465e-01 3.92172515e-01 -5.29175997e-01
-5.73462248e-02 1.07149303e+00 1.10078119e-01 -4.27698374e-01
1.66772068e+00 -4.83384460e-01 -2.21796185e-01 1.33995991e-03
9.16047692e-01 -2.76549101e-01 -1.28945303e+00 -1.96033344e-01
-4.21631336e-01 -6.94349527e-01 8.11180055e-01 -7.34148443e-01
-1.24085450e+00 7.78549910e-01 1.23413634e+00 -3.81781191e-01
1.59358370e+00 -2.85661191e-01 6.34422362e-01 5.30665852e-02
6.55613184e-01 -1.05939734e+00 -3.50137497e-03 2.21807465e-01
8.95593166e-01 -1.21423757e+00 1.66156009e-01 -5.28541982e-01
-3.54463123e-02 1.26126420e+00 6.63080215e-01 -4.98875082e-01
6.59814894e-01 5.23573816e-01 6.32157400e-02 -1.79605678e-01
-3.15460861e-01 -3.17311883e-01 -2.09600583e-01 9.86905158e-01
9.81938243e-02 -3.90641838e-01 -3.91326338e-01 7.76954293e-02
-1.47596553e-01 4.10321683e-01 1.11210418e+00 7.35111177e-01
-6.17065191e-01 -6.53006911e-01 -5.95777333e-01 2.64567602e-02
-6.88838363e-01 -1.65393502e-01 2.97620207e-01 6.54156625e-01
2.30741993e-01 6.43046260e-01 3.61830264e-01 -2.46597722e-01
3.59703839e-01 -4.43874240e-01 6.80241644e-01 -3.14900696e-01
-4.87452060e-01 -1.10438682e-01 -1.82567313e-01 -9.22182918e-01
-7.22238243e-01 -1.02577917e-01 -1.22773945e+00 -1.77453071e-01
7.96748549e-02 -3.07305545e-01 1.02441061e+00 4.85252291e-01
1.22472741e-01 8.41845989e-01 1.15988687e-01 -1.27780426e+00
2.55321771e-01 -8.81556153e-01 -8.22097600e-01 -1.08773567e-01
7.04305649e-01 -5.09728909e-01 -3.85338604e-01 5.28246947e-02] | [10.103425025939941, -2.3030197620391846] |
1db7dab5-c1cd-4cbf-9933-2bc94e98526b | fan-fatigue-aware-network-for-click-through | 2304.04529 | null | https://arxiv.org/abs/2304.04529v1 | https://arxiv.org/pdf/2304.04529v1.pdf | FAN: Fatigue-Aware Network for Click-Through Rate Prediction in E-commerce Recommendation | Since clicks usually contain heavy noise, increasing research efforts have been devoted to modeling implicit negative user behaviors (i.e., non-clicks). However, they either rely on explicit negative user behaviors (e.g., dislikes) or simply treat non-clicks as negative feedback, failing to learn negative user interests comprehensively. In such situations, users may experience fatigue because of seeing too many similar recommendations. In this paper, we propose Fatigue-Aware Network (FAN), a novel CTR model that directly perceives user fatigue from non-clicks. Specifically, we first apply Fourier Transformation to the time series generated from non-clicks, obtaining its frequency spectrum which contains comprehensive information about user fatigue. Then the frequency spectrum is modulated by category information of the target item to model the bias that both the upper bound of fatigue and users' patience is different for different categories. Moreover, a gating network is adopted to model the confidence of user fatigue and an auxiliary task is designed to guide the learning of user fatigue, so we can obtain a well-learned fatigue representation and combine it with user interests for the final CTR prediction. Experimental results on real-world datasets validate the superiority of FAN and online A/B tests also show FAN outperforms representative CTR models significantly. | ['Bo Cao', 'Chengjun Mao', 'Yingmin Su', 'Ningning Li', 'Yang Huang', 'Xiaofeng Pan', 'Naiyin Liu', 'Ming Li'] | 2023-04-10 | null | null | null | null | ['click-through-rate-prediction'] | ['miscellaneous'] | [-7.99115598e-02 -4.45784837e-01 -3.72298777e-01 -5.07779419e-01
-1.76513970e-01 -2.39866674e-01 4.62212339e-02 -2.85268366e-01
-4.48265433e-01 4.65378791e-01 1.61349684e-01 -1.52414665e-01
-1.16256364e-01 -4.55661982e-01 -1.06359735e-01 -5.19413471e-01
1.86124876e-01 -1.06763661e-01 7.13359788e-02 -3.31672400e-01
4.68442768e-01 -2.97652155e-01 -1.45968735e+00 -2.19862163e-03
1.23150933e+00 1.20076072e+00 4.38346237e-01 4.63557333e-01
2.34468624e-01 3.41449320e-01 -7.14401007e-01 2.12071873e-02
-1.87724113e-01 -5.87655962e-01 -3.30536753e-01 -3.87028366e-01
-8.68330374e-02 -3.36357534e-01 -4.87092465e-01 1.00523496e+00
6.75332785e-01 4.62013364e-01 4.34343249e-01 -1.22206247e+00
-9.11533415e-01 4.24444646e-01 -4.88861263e-01 7.06399560e-01
6.05639160e-01 4.35811043e-01 9.21718597e-01 -7.45706081e-01
6.19152673e-02 1.13766336e+00 5.04280686e-01 8.24045181e-01
-1.16708803e+00 -8.98392439e-01 5.92495024e-01 6.20175064e-01
-1.26779807e+00 -1.64181128e-01 1.03623343e+00 -3.31577867e-01
5.64708114e-01 5.21241486e-01 8.13859880e-01 1.59641361e+00
3.42586190e-01 8.55324984e-01 8.60839188e-01 3.26175541e-02
1.50619745e-01 1.66540802e-01 6.04659081e-01 1.37527436e-01
1.69585079e-01 3.27453792e-01 -6.04933143e-01 1.67598343e-03
5.66565454e-01 3.56794506e-01 -6.92782879e-01 1.48519367e-01
-8.96146953e-01 6.17583096e-01 5.81335962e-01 4.43235487e-01
-4.17731464e-01 -1.00073524e-01 2.33683333e-01 4.83904094e-01
3.23521972e-01 2.51947224e-01 -5.18715858e-01 -4.20970738e-01
-5.60677290e-01 -3.94596942e-02 5.66786826e-01 5.54446161e-01
5.31294048e-01 1.33707210e-01 -6.21791065e-01 7.20378280e-01
3.03089052e-01 5.55567503e-01 8.99231911e-01 -6.16670191e-01
1.05629258e-01 4.43643898e-01 5.23966551e-01 -1.14390409e+00
-6.48748040e-01 -8.97755146e-01 -8.51260602e-01 -3.93503368e-01
1.20250136e-01 -6.53533861e-02 -6.56998158e-01 2.19789076e+00
-1.74996331e-01 2.57242590e-01 -5.97478092e-01 1.15742362e+00
4.57383990e-01 5.78901730e-02 3.82822096e-01 -7.03998327e-01
1.17932320e+00 -6.49027467e-01 -1.17911959e+00 -3.64642441e-01
3.86092871e-01 -4.73757029e-01 1.75972342e+00 8.47607911e-01
-8.10034335e-01 -1.02859426e+00 -7.81312168e-01 2.36198425e-01
-2.02274188e-01 1.41914278e-01 6.78882182e-01 6.55617654e-01
-5.88881850e-01 7.69842029e-01 -7.36911774e-01 5.50547503e-02
2.23520607e-01 3.96411330e-01 3.90296727e-01 1.01206087e-01
-1.75088382e+00 7.20539093e-01 -1.72316413e-02 3.87378216e-01
-5.76385021e-01 -6.72066987e-01 -4.68613893e-01 3.18645120e-01
3.94180417e-01 -7.22805023e-01 1.27814555e+00 -1.12192333e+00
-1.17046928e+00 1.00591600e-01 -3.12228650e-01 -4.71322723e-02
4.01673734e-01 -6.87269211e-01 -1.00377929e+00 -2.68911302e-01
-1.31382629e-01 1.36442199e-01 1.06222975e+00 -9.27654028e-01
-2.93878406e-01 -4.49236095e-01 -7.59597644e-02 1.39003083e-01
-8.42761874e-01 -5.42572498e-01 -4.02886242e-01 -5.74420154e-01
-9.93873179e-03 -7.90970266e-01 -1.11468188e-01 -2.53089011e-01
-3.89686078e-01 -6.50631607e-01 7.72320926e-01 -4.93607312e-01
2.33631539e+00 -2.28885198e+00 -2.42301673e-01 3.80936623e-01
4.91509080e-01 3.14195216e-01 -2.37882197e-01 1.57819122e-01
-2.49495897e-02 2.90806502e-01 3.12033266e-01 1.36407912e-02
-1.00443615e-02 4.07767743e-02 -1.65730000e-01 3.16583753e-01
1.24226838e-01 8.81694198e-01 -1.24555886e+00 -9.13218260e-02
3.69717591e-02 4.70891982e-01 -7.65725434e-01 3.55938464e-01
-2.13940674e-03 4.90330577e-01 -6.54479265e-01 1.35675460e-01
6.97193801e-01 -4.81711388e-01 -1.37556233e-02 -5.54391980e-01
-1.29285797e-01 3.52638453e-01 -7.37390757e-01 1.34765947e+00
-6.04774654e-01 3.52815390e-01 -2.67891616e-01 -7.26036251e-01
7.87492931e-01 2.20844015e-01 2.64214426e-01 -1.23063946e+00
3.29489827e-01 -8.24528635e-02 4.27583873e-01 -7.99339414e-01
2.41803527e-01 -1.30169854e-01 1.34122401e-01 5.99791229e-01
-2.39981905e-01 4.20395404e-01 1.71958625e-01 2.26206243e-01
1.11127973e+00 -3.33002172e-02 -1.11835346e-01 -1.71661228e-02
7.06479073e-01 -7.16281474e-01 5.55932581e-01 8.50182474e-01
-5.69939673e-01 2.94163764e-01 4.36229438e-01 9.82569605e-02
-3.91860604e-01 -1.02726400e+00 2.25318402e-01 1.56107938e+00
3.79072279e-01 -5.78097165e-01 -4.60577577e-01 -6.58545792e-01
-1.86924055e-01 1.10065329e+00 -9.13684189e-01 -1.11331391e+00
-2.69532412e-01 -6.04436278e-01 -6.27757087e-02 5.71675539e-01
1.73114628e-01 -1.20731342e+00 -3.24469626e-01 1.90933898e-01
-5.96712053e-01 -5.29711783e-01 -9.84601438e-01 1.23756289e-01
-7.89026976e-01 -1.14124215e+00 -3.60443592e-01 -4.49987710e-01
6.01052105e-01 6.44030094e-01 1.11425483e+00 4.82938439e-01
-2.22362041e-01 3.72283071e-01 -1.81481451e-01 -1.14752933e-01
3.63723874e-01 2.93537732e-02 3.96261901e-01 8.16500857e-02
8.31845880e-01 -5.08032858e-01 -1.25626266e+00 6.84902668e-01
-7.40585566e-01 -3.69973928e-01 7.25238740e-01 9.15671647e-01
2.82305717e-01 1.75678745e-01 1.05457330e+00 -8.46870482e-01
1.23251975e+00 -7.26695657e-01 1.86660498e-01 -4.56857607e-02
-9.83077645e-01 -2.35472351e-01 7.60877788e-01 -1.09703612e+00
-1.29805756e+00 -6.66614890e-01 -1.98665857e-01 -4.36520278e-01
9.01358500e-02 6.36163592e-01 -1.79464482e-02 4.01071668e-01
7.56807983e-01 3.41555774e-01 -1.08043246e-01 -4.48198646e-01
1.76286474e-01 8.82408798e-01 2.99508691e-01 -1.79133371e-01
6.00527525e-01 1.63651496e-01 -6.78981781e-01 -6.97584748e-01
-1.42196512e+00 -7.03336298e-01 -1.71668738e-01 -5.23837805e-01
4.73160148e-01 -6.54470205e-01 -1.24714279e+00 2.40561232e-01
-6.69030368e-01 -2.46684596e-01 1.15918495e-01 5.96386731e-01
-5.32577693e-01 3.90925795e-01 -6.21332407e-01 -1.22935903e+00
-4.50236082e-01 -4.55417961e-01 4.58563417e-01 5.81050038e-01
-6.13554597e-01 -9.43859637e-01 7.15631694e-02 1.43670082e-01
7.72360265e-01 -3.86663944e-01 7.91548193e-01 -5.08035183e-01
-1.95204169e-02 -3.63966435e-01 -1.17702782e-01 5.12029171e-01
2.06872657e-01 -3.28647912e-01 -8.76570940e-01 -3.26647788e-01
4.71515894e-01 -4.84224409e-01 6.56415045e-01 3.86486620e-01
1.66411889e+00 -1.83821753e-01 -2.84903556e-01 5.27499430e-02
1.10152316e+00 6.58631027e-02 8.69346678e-01 -2.61942834e-01
3.38572800e-01 3.29471380e-01 9.77127552e-01 6.59295440e-01
1.92434974e-02 3.47425252e-01 3.76770973e-01 3.28132957e-02
3.46146464e-01 -3.44139099e-01 4.70804334e-01 1.06558073e+00
-2.70964235e-01 -3.44021916e-01 -2.04274729e-01 3.91721129e-02
-1.85533392e+00 -1.01109648e+00 -4.03393537e-01 2.49947715e+00
8.47852170e-01 6.08473063e-01 -4.59914692e-02 2.29098991e-01
6.34831309e-01 -8.11780989e-02 -1.10333836e+00 6.34172857e-02
1.89192921e-01 1.79844335e-01 -9.53285694e-02 3.49315964e-02
-5.61398447e-01 5.44526935e-01 5.69794703e+00 8.38092029e-01
-1.13648820e+00 4.07071188e-02 4.77153629e-01 -3.64868402e-01
-4.05123651e-01 -5.05424321e-01 -3.96863222e-01 8.68344486e-01
1.10595989e+00 -1.58076569e-01 6.83897436e-01 6.34510875e-01
1.01477325e+00 -7.76346549e-02 -9.19769406e-01 9.55685318e-01
-1.07077263e-01 -1.96306005e-01 -3.20408434e-01 -1.34174049e-01
3.27219874e-01 -1.37484267e-01 3.30299675e-01 1.03729391e+00
-1.29202545e-01 -7.87680507e-01 4.66816574e-01 1.26075804e+00
7.50520051e-01 -5.77550411e-01 7.45709717e-01 6.51240826e-01
-9.38846171e-01 -3.29314023e-01 -4.45103794e-01 -2.72243410e-01
1.18292399e-01 6.48522794e-01 -2.12315455e-01 1.40288204e-01
5.59716880e-01 8.36753309e-01 -7.20215917e-01 1.06979668e+00
-2.40510270e-01 9.24518943e-01 -1.20091699e-01 -2.73175001e-01
-2.37577304e-01 -1.99172243e-01 1.50234163e-01 9.37319458e-01
3.48505199e-01 1.52797759e-01 1.06179252e-01 9.36291933e-01
7.70548284e-02 -7.84744769e-02 -8.64852443e-02 -3.22285980e-01
2.99917161e-01 1.45855975e+00 -2.49248505e-01 -3.25441211e-01
-4.73951787e-01 9.86406744e-01 2.11693600e-01 7.49263823e-01
-9.07362640e-01 -5.86728156e-01 5.30996978e-01 9.19133276e-02
8.55801776e-02 -8.41893926e-02 -1.72606781e-01 -1.15215683e+00
-1.52963981e-01 -4.83218044e-01 3.29865962e-01 -1.03216040e+00
-1.61214602e+00 3.40874523e-01 -5.90258896e-01 -1.41413176e+00
-1.60009917e-02 -3.14776450e-01 -8.99737120e-01 1.07527661e+00
-1.29546022e+00 -2.99279004e-01 -6.94800913e-01 8.31384301e-01
4.74106103e-01 5.70062518e-01 6.02859735e-01 4.53690857e-01
-8.15668106e-01 7.69842625e-01 -3.43003094e-01 -2.80201793e-01
1.00434387e+00 -1.11789882e+00 -2.02214867e-01 1.66915923e-01
-4.48110133e-01 1.31547797e+00 7.67821193e-01 -7.23852634e-01
-1.20940256e+00 -8.39442134e-01 7.66904533e-01 -4.30913627e-01
7.59860754e-01 -2.70744324e-01 -1.12467444e+00 2.52854913e-01
-2.41414756e-02 -2.25849316e-01 1.03320587e+00 3.81553978e-01
-6.89873472e-02 -1.12314140e-02 -7.36109614e-01 6.47168458e-01
1.32344186e+00 -5.10804296e-01 -5.97157419e-01 1.32259026e-01
6.17507458e-01 2.38754913e-01 -6.86654806e-01 1.52144983e-01
7.00140297e-01 -1.05482733e+00 7.80195773e-01 -7.92799532e-01
7.17531592e-02 -1.36680737e-01 3.62151295e-01 -1.58449054e+00
-7.85857320e-01 -4.64741528e-01 -5.06559908e-01 8.97893012e-01
1.26127750e-01 -4.42038924e-01 5.76054633e-01 5.45550406e-01
-1.81906104e-01 -6.69897497e-01 -3.54770303e-01 -6.05200052e-01
-5.54282248e-01 -5.58916152e-01 6.91370964e-02 6.57915592e-01
2.46211097e-01 7.94252694e-01 -7.40313828e-01 -2.97156364e-01
2.42902607e-01 -1.00815527e-01 2.89826989e-01 -1.63290656e+00
-2.65839249e-01 -5.29457629e-01 2.45598212e-01 -1.52049363e+00
-2.54681408e-01 -4.47982967e-01 1.83605835e-01 -1.14978170e+00
1.85009956e-01 -1.56721875e-01 -1.02655327e+00 2.49555200e-01
-6.02750123e-01 2.10802004e-01 -3.51634502e-01 9.32827219e-02
-1.08147943e+00 9.38967824e-01 1.60038888e+00 1.23234972e-01
-4.50342894e-01 6.08204246e-01 -1.16920054e+00 6.35581195e-01
7.55786240e-01 -1.46385312e-01 -5.66556633e-01 1.75728932e-01
5.21087646e-01 1.15872636e-01 5.73865287e-02 -8.15275908e-01
-3.26441298e-03 -2.11426988e-01 6.51973069e-01 -6.39868259e-01
2.94505954e-01 -7.36301661e-01 -3.88588816e-01 6.74706757e-01
-5.24921834e-01 -2.13214979e-01 -1.18894212e-01 1.15702832e+00
7.60635659e-02 -9.73371193e-02 5.49252570e-01 3.94559540e-02
-2.66823679e-01 3.74218017e-01 -3.96359146e-01 1.27509400e-01
3.38563979e-01 4.64463718e-02 -2.84145266e-01 -6.06233358e-01
-1.08373821e+00 4.67110097e-01 -8.06426257e-02 8.24126720e-01
5.84096909e-01 -1.37633979e+00 -1.77749261e-01 3.36173177e-01
1.56653389e-01 -6.74559474e-01 8.72608721e-01 1.28529584e+00
6.03619993e-01 5.49991429e-01 1.22831173e-01 -4.08354551e-01
-1.03727949e+00 7.01092422e-01 8.51860046e-02 -1.52772844e-01
-5.09735979e-02 6.58042789e-01 3.31488967e-01 9.57768485e-02
3.78068715e-01 -1.71973571e-01 -5.60576022e-01 2.38061458e-01
8.77683520e-01 4.25119013e-01 1.92621592e-02 -9.63322818e-02
-2.43380353e-01 1.45414010e-01 -1.85764804e-01 2.76523471e-01
1.10189927e+00 -5.50690353e-01 2.53909916e-01 8.22805703e-01
9.68281746e-01 -1.56771675e-01 -1.21156061e+00 -2.27472231e-01
-9.12747309e-02 -5.64764917e-01 1.41649708e-01 -1.12275863e+00
-1.05986917e+00 8.81974876e-01 9.65602040e-01 4.19689357e-01
1.28893650e+00 -1.62972718e-01 7.48558223e-01 3.36197585e-01
2.75952011e-01 -1.47048378e+00 6.71990216e-01 4.51139390e-01
7.65691519e-01 -1.12335873e+00 -3.87127072e-01 -1.09312184e-01
-6.20881259e-01 9.51308668e-01 1.09974241e+00 -1.20923765e-01
8.68123770e-01 -4.23036754e-01 -1.15318308e-02 -1.76369101e-02
-1.06483376e+00 -3.25302750e-01 3.74848217e-01 5.52185774e-01
6.80592179e-01 1.60148703e-02 -8.08956861e-01 1.40570951e+00
-1.93416238e-01 3.78741443e-01 3.41647655e-01 6.19540036e-01
-6.38771236e-01 -6.48953617e-01 3.96603607e-02 1.01242316e+00
-1.91924453e-01 -1.46584973e-01 -1.02905475e-01 3.87130499e-01
1.01707533e-01 1.11565101e+00 6.19658642e-02 -9.33761656e-01
5.95233917e-01 2.04700023e-01 1.39627814e-01 -6.45786166e-01
-5.44745982e-01 3.58446568e-01 -2.96238393e-01 -6.56356454e-01
-1.94952697e-01 -3.59497696e-01 -1.06962872e+00 -1.76768512e-01
-8.25661302e-01 3.09328377e-01 4.03195620e-01 8.12328398e-01
3.01740348e-01 9.55584347e-01 9.05217528e-01 -5.38259268e-01
-8.29480231e-01 -1.43011129e+00 -7.37407088e-01 7.49639392e-01
2.23807737e-01 -9.77801025e-01 -9.31668639e-01 -3.60728830e-01] | [10.114383697509766, 5.515572547912598] |
1a57accd-82e6-46ff-a700-1a8f71a5255d | floors-are-flat-leveraging-semantics-for-real | 1906.06792 | null | https://arxiv.org/abs/1906.06792v1 | https://arxiv.org/pdf/1906.06792v1.pdf | Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction | We propose 4 insights that help to significantly improve the performance of deep learning models that predict surface normals and semantic labels from a single RGB image. These insights are: (1) denoise the "ground truth" surface normals in the training set to ensure consistency with the semantic labels; (2) concurrently train on a mix of real and synthetic data, instead of pretraining on synthetic and finetuning on real; (3) jointly predict normals and semantics using a shared model, but only backpropagate errors on pixels that have valid training labels; (4) slim down the model and use grayscale instead of color inputs. Despite the simplicity of these steps, we demonstrate consistently improved results on several datasets, using a model that runs at 12 fps on a standard mobile phone. | ['Karthik Raveendran', 'Steven Hickson', 'Kevin Murphy', 'Irfan Essa', 'Alireza Fathi'] | 2019-06-16 | null | null | null | null | ['surface-normals-estimation'] | ['computer-vision'] | [ 7.31070042e-01 4.22870070e-01 3.36157590e-01 -6.59436524e-01
-9.66362834e-01 -3.92294288e-01 3.98162276e-01 -1.19804546e-01
-4.59297657e-01 6.52378678e-01 -1.34038359e-01 -2.80995429e-01
4.90768909e-01 -8.98020148e-01 -9.80158031e-01 -5.96646607e-01
1.07021734e-01 4.45276141e-01 4.94073331e-01 4.14496772e-02
1.15780763e-01 4.40425366e-01 -1.83197808e+00 6.00259244e-01
5.90510905e-01 1.45931697e+00 -3.14067192e-02 1.01982546e+00
6.79267719e-02 8.68058681e-01 -3.90697479e-01 -1.60539240e-01
6.34094536e-01 -4.69824761e-01 -8.55298102e-01 3.61133486e-01
7.69132912e-01 -4.67895746e-01 -9.45648178e-02 1.04864013e+00
-1.03313727e-02 -4.02729027e-02 4.31447059e-01 -1.12198925e+00
-4.79171932e-01 -1.52500197e-01 -5.11647046e-01 -2.27241710e-01
2.05271304e-01 6.55821383e-01 7.10133016e-01 -6.39367640e-01
5.78818500e-01 1.07012296e+00 8.49954665e-01 5.99751770e-01
-1.38288820e+00 -5.05811155e-01 2.33027488e-01 -1.67285308e-01
-1.16880596e+00 -6.04419649e-01 3.36984009e-01 -2.25596860e-01
8.56167614e-01 1.86864257e-01 8.41905355e-01 1.14266932e+00
3.14418636e-02 2.95547754e-01 1.53869927e+00 -3.75585914e-01
5.63614726e-01 -9.26401690e-02 -2.81018496e-01 9.46478784e-01
3.78511846e-02 -9.73463580e-02 -5.52054822e-01 3.55675966e-02
8.40077877e-01 -9.91570950e-02 -2.12154761e-01 -3.67092758e-01
-1.23960626e+00 4.76484358e-01 4.93166476e-01 -2.60907084e-01
-4.05142695e-01 5.53366661e-01 -6.24450855e-02 2.38437936e-01
3.57263535e-01 3.29499841e-01 -5.94261289e-01 -2.99074620e-01
-9.05327201e-01 5.85868396e-02 5.99053502e-01 7.16395974e-01
1.43118525e+00 -4.62771654e-02 2.95320064e-01 4.90701795e-01
3.68229628e-01 8.21127236e-01 3.49757135e-01 -1.62402320e+00
2.34008908e-01 3.76779675e-01 3.92430067e-01 -6.88857734e-01
-2.71928489e-01 -2.39100993e-01 -1.69658855e-01 9.42989290e-01
6.88077748e-01 -1.19113132e-01 -1.56269908e+00 1.45741820e+00
2.31752202e-01 2.19484776e-01 7.58997127e-02 8.69867802e-01
3.03432554e-01 4.61409330e-01 4.26663645e-02 6.69631243e-01
8.73006284e-01 -9.47709620e-01 -7.15731978e-02 -5.62127411e-01
6.88294768e-01 -5.74207187e-01 1.74530280e+00 8.17880154e-01
-1.13385081e+00 -5.33240497e-01 -1.19245350e+00 -2.83831924e-01
-4.78192508e-01 1.70827940e-01 6.40841663e-01 6.75922990e-01
-1.52422881e+00 9.39284503e-01 -1.39172602e+00 -3.95134628e-01
4.81614619e-01 3.74247104e-01 -3.44078451e-01 -9.43837836e-02
-6.77959681e-01 6.13364398e-01 1.01889528e-01 3.75440530e-02
-1.07426703e+00 -5.65409601e-01 -6.91354036e-01 -1.20606199e-01
1.24981269e-01 -6.91569149e-01 1.26164317e+00 -1.67898464e+00
-1.73526978e+00 1.06145716e+00 -2.53338248e-01 -1.92595273e-01
6.35721743e-01 -2.39312679e-01 -1.49145082e-01 1.66660771e-01
5.87642267e-02 1.01568091e+00 7.00445235e-01 -1.67289221e+00
-7.60339618e-01 -2.23612562e-01 1.04954593e-01 1.98643953e-01
-6.86242580e-02 -3.49375427e-01 -5.91159463e-01 -2.21980914e-01
5.13585806e-01 -8.92547488e-01 -1.31523386e-01 5.27840793e-01
-5.16006470e-01 5.52964270e-01 7.59711564e-01 -7.33729422e-01
4.06174928e-01 -2.03727627e+00 -1.24676518e-01 4.07821923e-01
5.79885095e-02 -1.76874489e-01 -1.57957152e-01 -1.89188659e-01
3.08848191e-02 3.93726863e-02 -3.82365078e-01 -5.78744531e-01
-1.59382671e-01 4.59804207e-01 -3.01383823e-01 4.16560888e-01
1.44733340e-01 8.05665851e-01 -9.51252699e-01 -2.33431309e-01
2.74210930e-01 4.77773368e-01 -4.18895483e-01 1.27463425e-02
-4.64205056e-01 4.79955971e-01 -1.01024754e-01 6.43937290e-01
6.57441854e-01 -6.33298039e-01 1.03216574e-01 -2.54963726e-01
6.67936131e-02 5.52192926e-01 -1.29140699e+00 1.77746546e+00
-5.43275893e-01 5.13371527e-01 1.67454809e-01 -4.40040827e-01
5.68865955e-01 -1.13514602e-01 4.11622226e-01 -7.69569099e-01
-5.78851588e-02 1.97905198e-01 -4.76475030e-01 -1.94403410e-01
2.47767419e-01 -1.41378850e-01 2.79110432e-01 7.33176589e-01
-1.46700874e-01 -4.26409692e-01 -4.37288821e-01 -3.25302780e-02
1.26207423e+00 6.27471864e-01 -4.19634819e-01 8.86866003e-02
1.12729497e-01 1.24393061e-01 5.04008472e-01 6.35930359e-01
-1.30204514e-01 1.07361996e+00 6.09834671e-01 -4.93336350e-01
-1.30413783e+00 -1.47875249e+00 1.94789842e-01 9.96215284e-01
3.75485599e-01 -8.20836350e-02 -8.26492667e-01 -7.96817899e-01
3.86691876e-02 6.46108747e-01 -8.52883637e-01 2.03871969e-02
-4.01776880e-01 -7.96440482e-01 6.71234488e-01 7.99316406e-01
6.38640583e-01 -6.98098898e-01 -9.57431674e-01 -1.85264215e-01
-2.04419787e-03 -1.02148342e+00 1.18886359e-01 4.67116833e-01
-8.40453446e-01 -1.12865531e+00 -2.93280959e-01 -3.66847038e-01
9.35129166e-01 4.20663431e-02 1.23717880e+00 3.43191922e-01
-3.77960466e-02 4.36839551e-01 -2.47195721e-01 -1.51213914e-01
-3.24990362e-01 -1.85319737e-01 -3.64944845e-01 1.04941204e-01
3.63441259e-02 -4.83974308e-01 -8.40533197e-01 2.13028327e-01
-8.23811471e-01 5.21306753e-01 3.01026106e-01 6.03728831e-01
8.33995104e-01 -2.84320951e-01 3.79256718e-02 -1.05292773e+00
-7.11080432e-02 -1.58023581e-01 -7.01421738e-01 2.66655624e-01
-7.67018378e-01 8.36071223e-02 4.59771246e-01 3.19421366e-02
-1.19631290e+00 2.35085517e-01 -1.92700878e-01 -4.29929346e-01
-3.81556273e-01 -1.14176713e-01 4.65951525e-02 -3.66528362e-01
6.93385899e-01 -1.59662478e-02 8.01194161e-02 -3.44705522e-01
3.71134639e-01 5.23618042e-01 8.80373895e-01 -6.33065283e-01
5.93409359e-01 1.07571888e+00 1.43065810e-01 -5.42343676e-01
-8.24572086e-01 -3.75070572e-02 -5.87048471e-01 -1.59371287e-01
9.46832240e-01 -1.02337873e+00 -5.27488649e-01 6.91658497e-01
-7.36902773e-01 -1.18082857e+00 -4.69419658e-01 1.82722449e-01
-6.11499548e-01 1.68460235e-01 -8.32463026e-01 -6.00296557e-01
-3.31630222e-02 -9.62046981e-01 1.44378185e+00 3.42777938e-01
-1.63348600e-01 -9.27250803e-01 -2.49905169e-01 1.51578546e-01
4.61066455e-01 4.66843963e-01 7.27235377e-01 -1.60865813e-01
-8.75213325e-01 5.88721819e-02 -5.12858868e-01 5.25739074e-01
2.74078250e-01 2.83764154e-01 -1.49637496e+00 -5.90750016e-02
-2.11690590e-01 -6.79282725e-01 7.36496329e-01 8.57399553e-02
1.29280531e+00 6.84615225e-02 -2.66618729e-01 1.08248389e+00
1.49537504e+00 -1.84736937e-01 7.02103615e-01 6.20923460e-01
8.46779346e-01 6.12562537e-01 2.98670560e-01 1.81507513e-01
6.81064248e-01 2.93801129e-01 7.53281176e-01 -4.74571317e-01
-4.51258898e-01 -4.18977767e-01 2.61902928e-01 3.10803384e-01
1.41351938e-01 3.59814800e-02 -9.71966147e-01 3.48716348e-01
-1.70187736e+00 -4.13498729e-01 -7.64181316e-02 2.27159429e+00
7.55535185e-01 3.16311359e-01 -8.18908736e-02 4.40851636e-02
3.66767079e-01 6.39219955e-02 -8.34871173e-01 -2.21683919e-01
-3.39366913e-01 5.71588516e-01 9.38419878e-01 7.36355841e-01
-9.57223237e-01 1.12205553e+00 6.95063066e+00 1.34108230e-01
-1.68684232e+00 1.31877571e-01 1.12509811e+00 -2.65638411e-01
-6.67238891e-01 1.50302798e-01 -4.17885542e-01 4.32923675e-01
9.39560592e-01 5.22997141e-01 8.30438793e-01 8.57989848e-01
4.10814770e-02 -4.11617994e-01 -1.09286904e+00 7.66492724e-01
-7.32914582e-02 -1.10786867e+00 -1.90204620e-01 2.30285972e-02
1.02390766e+00 4.28637385e-01 1.79588184e-01 -4.77443822e-02
7.41600394e-01 -1.18612766e+00 9.42978203e-01 7.43934989e-01
1.05991769e+00 -2.44911328e-01 4.54503953e-01 7.71752521e-02
-6.03977323e-01 2.38060758e-01 -2.25089133e-01 -1.11406446e-01
9.26593691e-02 5.40088296e-01 -8.23450565e-01 2.11563513e-01
8.90982151e-01 5.55247366e-01 -8.65500748e-01 6.80748284e-01
-6.10612810e-01 5.46677113e-01 -7.10236728e-01 3.41031253e-01
1.20246239e-01 -6.15388304e-02 -2.78600067e-01 8.87081921e-01
2.62040704e-01 -2.21070930e-01 -1.06878318e-01 1.00292051e+00
9.04457867e-02 -4.35958117e-01 -1.68052584e-01 2.10356012e-01
4.36540484e-01 1.09120512e+00 -1.08076584e+00 -3.88575464e-01
-4.48589891e-01 1.38614678e+00 1.95401400e-01 6.81472421e-01
-8.46397758e-01 -2.90397257e-01 8.07111740e-01 2.71159858e-01
3.27208430e-01 -4.18496311e-01 -9.35074806e-01 -1.13934290e+00
1.46343373e-02 -5.49977899e-01 -2.61614416e-02 -1.39262247e+00
-8.70558739e-01 5.57091594e-01 -5.04063010e-01 -9.23240364e-01
-1.76703930e-01 -8.77155423e-01 -4.80850786e-01 1.10766673e+00
-1.66201556e+00 -1.14118958e+00 -7.94009089e-01 5.45709610e-01
1.00164488e-02 4.75991368e-01 8.54530632e-01 4.61283550e-02
-2.44045898e-01 4.19372737e-01 9.46644619e-02 -6.39635846e-02
6.23568892e-01 -1.48882020e+00 8.23203504e-01 7.78940797e-01
1.04944311e-01 4.48688775e-01 5.79712570e-01 -6.22849464e-01
-1.07796109e+00 -1.04648900e+00 4.43559378e-01 -6.60319746e-01
4.41936553e-01 -3.10292006e-01 -8.41752350e-01 1.03386414e+00
-1.97364986e-01 3.64034474e-01 2.47772172e-01 -1.10705502e-01
-4.51947093e-01 -2.27235273e-01 -1.34555161e+00 5.05445659e-01
1.00250304e+00 -6.43984556e-01 -3.84595282e-02 3.38201791e-01
4.99903351e-01 -7.80200899e-01 -5.74952424e-01 3.35322529e-01
7.70738125e-01 -1.44130111e+00 8.38907719e-01 -4.04508621e-01
3.54277402e-01 -6.15218818e-01 -3.59705687e-01 -1.18764162e+00
2.11581811e-01 -2.78091431e-01 1.44790649e-01 7.09833324e-01
4.75586444e-01 -7.51523852e-01 1.33445287e+00 1.02504551e+00
-1.27627984e-01 -9.60837662e-01 -7.66589582e-01 -3.85147482e-01
-1.25187725e-01 -6.47887230e-01 7.59972095e-01 5.74471533e-01
-6.29522920e-01 -2.69111812e-01 -3.81203331e-02 1.95620641e-01
3.87841791e-01 -6.55610338e-02 9.05488372e-01 -9.82411683e-01
-4.98260975e-01 -1.05284326e-01 -2.65679568e-01 -1.08547521e+00
-7.08810613e-02 -4.21286136e-01 2.98935026e-01 -1.50498152e+00
-2.24738419e-01 -8.65155637e-01 -2.21482471e-01 1.02012181e+00
2.06488408e-02 7.68161416e-01 -7.24854469e-02 2.45879143e-01
-6.65164709e-01 2.46956602e-01 9.15583968e-01 1.23684458e-01
9.87839624e-02 -3.48786920e-01 -7.65891731e-01 9.56775248e-01
6.08728886e-01 -2.50287414e-01 -3.10417324e-01 -7.84234047e-01
4.95916098e-01 -3.84020299e-01 7.35909760e-01 -1.25534081e+00
-6.07127212e-02 -2.68834680e-01 8.90664935e-01 -5.04936166e-02
5.40872276e-01 -7.19388247e-01 1.18087366e-01 2.95621693e-01
-1.97358191e-01 5.18127717e-02 1.03062645e-01 4.12342727e-01
2.04325587e-01 -1.14870751e-02 9.36359525e-01 -1.88512102e-01
-7.86071718e-01 -6.93783760e-02 -7.17990473e-03 -1.13644518e-01
8.35647464e-01 -5.71334660e-01 -2.97505915e-01 -4.15487587e-01
-7.86279440e-01 -9.29000899e-02 1.45736039e+00 6.07855543e-02
4.15592283e-01 -9.76362646e-01 -5.98565442e-03 5.81472754e-01
2.27034111e-02 3.58089060e-01 -8.00505057e-02 4.30144846e-01
-1.12858486e+00 1.90496556e-02 -1.13436736e-01 -7.27734864e-01
-6.77178442e-01 -1.70692671e-02 6.73661232e-01 1.52650476e-01
-6.13533199e-01 1.17302012e+00 1.51420027e-01 -4.78560597e-01
1.64781526e-01 -5.15017331e-01 5.30169189e-01 -5.74139714e-01
2.44594172e-01 2.36014262e-01 3.84589165e-01 -4.84753847e-01
-3.56072873e-01 5.55895388e-01 3.49605799e-01 -6.30631328e-01
1.20489883e+00 -2.21779123e-01 1.15812430e-02 5.56039512e-01
1.07091081e+00 1.04093127e-01 -2.12802577e+00 2.30303891e-02
-1.02549009e-01 -6.60023451e-01 6.81028217e-02 -1.15585196e+00
-1.08347070e+00 8.65859687e-01 8.27515662e-01 -1.23170748e-01
1.16871083e+00 -1.57027841e-01 9.50070977e-01 2.47087717e-01
4.69386637e-01 -1.15770423e+00 9.69571397e-02 2.77311802e-01
2.18594238e-01 -1.12267423e+00 3.29855131e-03 -1.98286504e-01
-6.33887708e-01 1.28309524e+00 6.95717335e-01 -2.63861835e-01
3.28737289e-01 4.73194450e-01 4.66640711e-01 -1.84747025e-01
-6.95708454e-01 -9.95968804e-02 -1.11855403e-01 6.94962680e-01
3.04327369e-01 -1.33067444e-01 5.61529934e-01 1.46642268e-01
-2.04671502e-01 1.87213689e-01 4.60466564e-01 9.34170187e-01
-4.38681930e-01 -9.70578909e-01 -3.57484758e-01 4.42526698e-01
-1.61160737e-01 -5.23677468e-02 -3.12715113e-01 5.32317936e-01
3.69375378e-01 8.33482504e-01 1.66601107e-01 -6.09167337e-01
2.58579999e-01 8.67173821e-02 5.78570902e-01 -6.96076691e-01
-3.01640838e-01 -1.44749165e-01 7.48573020e-02 -1.03324187e+00
-1.75777137e-01 -6.32763624e-01 -1.49705434e+00 -1.54857144e-01
1.79327935e-01 -2.23250166e-01 1.00628638e+00 1.01578546e+00
5.30785143e-01 4.95634466e-01 3.83026838e-01 -1.05844951e+00
-4.21335936e-01 -8.19691241e-01 -3.78687739e-01 5.84903896e-01
4.55038518e-01 -4.65296417e-01 -6.72077060e-01 3.88415098e-01] | [9.553008079528809, -2.9111857414245605] |
05ac3ada-ca3c-4498-a4f2-91b4a3cc6a26 | constrained-low-rank-learning-using-least | 1611.04870 | null | http://arxiv.org/abs/1611.04870v1 | http://arxiv.org/pdf/1611.04870v1.pdf | Constrained Low-Rank Learning Using Least Squares-Based Regularization | Low-rank learning has attracted much attention recently due to its efficacy
in a rich variety of real-world tasks, e.g., subspace segmentation and image
categorization. Most low-rank methods are incapable of capturing
low-dimensional subspace for supervised learning tasks, e.g., classification
and regression. This paper aims to learn both the discriminant low-rank
representation (LRR) and the robust projecting subspace in a supervised manner.
To achieve this goal, we cast the problem into a constrained rank minimization
framework by adopting the least squares regularization. Naturally, the data
label structure tends to resemble that of the corresponding low-dimensional
representation, which is derived from the robust subspace projection of clean
data by low-rank learning. Moreover, the low-dimensional representation of
original data can be paired with some informative structure by imposing an
appropriate constraint, e.g., Laplacian regularizer. Therefore, we propose a
novel constrained LRR method. The objective function is formulated as a
constrained nuclear norm minimization problem, which can be solved by the
inexact augmented Lagrange multiplier algorithm. Extensive experiments on image
classification, human pose estimation, and robust face recovery have confirmed
the superiority of our method. | ['Xuelong. Li', 'Luming Zhang', 'Meng Wang', 'Jun Yu', 'Deng Cai', 'Ping Li'] | 2016-11-15 | null | null | null | null | ['image-categorization'] | ['computer-vision'] | [ 2.37374440e-01 -3.17804337e-01 -2.86898404e-01 -3.56412590e-01
-7.31234193e-01 -4.38958049e-01 2.72089362e-01 -6.07107103e-01
-3.13081115e-01 5.00542700e-01 3.87485534e-01 5.16280951e-03
-3.89560193e-01 -9.97229889e-02 -4.96394873e-01 -1.06743634e+00
5.24323523e-01 1.70065969e-01 -4.98364806e-01 8.08409378e-02
1.14445135e-01 4.34958547e-01 -1.25297797e+00 -1.47126332e-01
9.59841013e-01 8.06240320e-01 1.98637217e-01 -1.63397700e-01
1.93859816e-01 4.13077116e-01 -3.84548008e-02 7.00512007e-02
2.42930472e-01 -3.88428301e-01 -3.76621574e-01 6.10729933e-01
4.80979055e-01 -1.40471369e-01 -5.53779185e-01 1.40480053e+00
4.65169519e-01 2.78411597e-01 5.87762535e-01 -1.20435047e+00
-5.04086316e-01 1.04649246e-01 -9.34957147e-01 -2.07121208e-01
5.10795951e-01 -2.77337223e-01 8.36220145e-01 -1.40267372e+00
4.96624559e-01 1.48378253e+00 2.37670928e-01 4.97359931e-01
-1.56054485e+00 -7.47272670e-01 1.66849554e-01 1.35586172e-01
-1.69611180e+00 -5.76077998e-01 1.29137957e+00 -5.83844244e-01
-6.11064136e-02 3.46999079e-01 2.02109233e-01 9.69707370e-01
-3.61474752e-01 9.35234785e-01 1.29315698e+00 -1.87730283e-01
5.22264205e-02 5.61698005e-02 -6.85703382e-02 8.36399913e-01
4.13163960e-01 -1.10349387e-01 -4.20678526e-01 -2.89169639e-01
8.25349331e-01 2.28173390e-01 -7.31900752e-01 -8.12243402e-01
-1.38954222e+00 7.49645233e-01 2.93565184e-01 2.49837995e-01
-3.39424700e-01 -2.78700173e-01 2.05771595e-01 -2.25528643e-01
4.71572995e-01 5.19945063e-02 -5.23008332e-02 4.48688269e-01
-7.77114868e-01 -1.46536529e-01 4.59550917e-01 8.48397732e-01
7.07765758e-01 2.66747028e-01 1.19787958e-02 1.23502338e+00
7.31735468e-01 7.19488978e-01 5.61479270e-01 -1.04301775e+00
4.20858532e-01 4.85548317e-01 3.26459147e-02 -1.41127586e+00
-2.15481177e-01 -4.14851934e-01 -1.34736013e+00 -1.52008785e-02
3.53033006e-01 3.01740747e-02 -4.98917878e-01 1.82583654e+00
3.66131127e-01 4.50098008e-01 9.37250182e-02 1.34832025e+00
6.88423336e-01 7.94304669e-01 -3.43723476e-01 -7.70084202e-01
1.15644455e+00 -6.45564914e-01 -8.36466551e-01 -2.44026467e-01
1.74002454e-01 -7.56871700e-01 9.27019715e-01 4.74651128e-01
-6.75257444e-01 -3.83329481e-01 -9.26403582e-01 9.19632912e-02
4.21420932e-01 6.12197042e-01 5.15114248e-01 3.12015176e-01
-5.05875289e-01 2.04592586e-01 -5.91880381e-01 -1.37569025e-01
1.60697043e-01 3.18246037e-01 -8.00748408e-01 -3.70836407e-01
-7.73482859e-01 2.39619210e-01 3.35137963e-01 5.06686091e-01
-5.89240372e-01 -1.05946913e-01 -1.01268959e+00 -2.76149124e-01
6.23056054e-01 -3.19042385e-01 7.13876367e-01 -6.13110363e-01
-1.36764896e+00 8.72837186e-01 -4.89000708e-01 3.29940200e-01
3.45199138e-01 -2.91586399e-01 -3.43734235e-01 1.66203141e-01
3.48645061e-01 1.82173830e-02 1.39037502e+00 -1.45300221e+00
-1.88086376e-01 -7.57559419e-01 -3.41175735e-01 3.78533125e-01
-6.37580991e-01 -8.06652829e-02 -7.95386732e-01 -9.37100053e-01
9.34837997e-01 -1.18314087e+00 -2.85147369e-01 -8.51728097e-02
-4.55950230e-01 -1.47076562e-01 9.30256844e-01 -7.74354458e-01
1.09799874e+00 -2.41723275e+00 6.77564442e-01 3.47452343e-01
1.67023957e-01 8.70102420e-02 -1.66394636e-01 -1.53120933e-02
-4.47572559e-01 -1.71538725e-01 -4.60487843e-01 -1.60740271e-01
-2.84682333e-01 1.46070629e-01 -3.53868574e-01 9.73523259e-01
-1.01277918e-01 4.55374181e-01 -9.15588617e-01 -6.38244390e-01
1.14337780e-01 6.11218512e-01 -3.81038278e-01 3.17079246e-01
1.59592032e-01 9.23078060e-01 -7.41469026e-01 5.47849417e-01
7.66188085e-01 -2.00436965e-01 1.16758682e-01 -7.49176741e-01
-1.09167971e-01 -3.71843398e-01 -1.60881567e+00 1.99318266e+00
-3.26965988e-01 3.38433623e-01 6.03943229e-01 -1.12020457e+00
9.47109222e-01 2.82198489e-01 7.40951598e-01 -3.81383598e-01
-7.74537921e-02 4.18224633e-01 -2.62213260e-01 -4.60069478e-01
2.02078715e-01 -1.60169393e-01 7.61029497e-02 3.34324807e-01
-3.68481278e-01 1.75011501e-01 -5.66632226e-02 1.84192255e-01
4.10339773e-01 2.74454206e-01 1.47368267e-01 -2.39208683e-01
1.12178648e+00 -4.45769370e-01 1.02926660e+00 1.62785247e-01
2.48956326e-02 6.68207109e-01 1.80417225e-01 -9.21298265e-02
-6.57700658e-01 -6.56707406e-01 -4.80224937e-01 8.97323012e-01
3.36952597e-01 -1.37367204e-01 -5.84251821e-01 -5.99320292e-01
-1.30553693e-01 2.51361310e-01 -1.59135416e-01 -2.88378149e-01
-7.88477004e-01 -7.81753600e-01 1.10460259e-01 2.63035983e-01
6.22965932e-01 -6.76426470e-01 1.91008240e-01 2.45097764e-02
-4.44777817e-01 -1.15062428e+00 -8.66388917e-01 -2.69380897e-01
-9.27026331e-01 -1.05281293e+00 -9.74295795e-01 -1.12321317e+00
1.19984210e+00 8.67627144e-01 4.24737394e-01 -1.59203559e-01
-1.66668639e-01 5.16273201e-01 -9.40273106e-02 2.93714762e-01
1.70080513e-01 -3.55710775e-01 6.91410005e-01 6.41482115e-01
1.70449704e-01 -3.77183348e-01 -4.67504710e-01 7.10225642e-01
-9.57522035e-01 -3.72893326e-02 7.39983320e-01 1.15512669e+00
9.97635067e-01 2.89983511e-01 4.57423896e-01 -8.58235776e-01
5.21175027e-01 -2.17245966e-01 -6.54995978e-01 2.16658801e-01
-4.38434750e-01 2.26979658e-01 7.25039542e-01 -4.49448794e-01
-1.17812538e+00 5.41563034e-01 6.25448972e-02 -8.49061489e-01
2.69762110e-02 6.45481765e-01 -7.80705810e-01 -1.59866124e-01
3.49976689e-01 5.37724137e-01 1.24059230e-01 -7.60260284e-01
4.70402956e-01 7.95723498e-01 6.67692542e-01 -7.52936482e-01
1.36456549e+00 5.15466034e-01 2.30537593e-01 -1.02072132e+00
-1.05396748e+00 -6.70179307e-01 -6.78787172e-01 -1.54323474e-01
6.95182145e-01 -1.11066997e+00 -6.48968220e-01 5.04360557e-01
-8.67797434e-01 2.31365010e-01 -1.15673272e-02 8.05244684e-01
-4.32630211e-01 8.69270504e-01 -3.93781781e-01 -7.35386670e-01
-5.93192596e-03 -1.01242995e+00 1.02581477e+00 1.00465812e-01
2.88979560e-01 -7.98859656e-01 -1.24879945e-02 6.35686338e-01
-1.88669756e-01 2.45387733e-01 6.75409317e-01 -2.77827829e-01
-3.98442298e-01 -2.99184948e-01 -3.41054320e-01 5.26331544e-01
2.27407828e-01 -4.10671711e-01 -8.51329744e-01 -7.45732367e-01
3.87764633e-01 -3.37041110e-01 8.20775330e-01 2.60053039e-01
1.27870870e+00 -5.29109001e-01 -2.59969443e-01 8.67125690e-01
1.17882967e+00 -1.45285577e-01 1.48166165e-01 -4.44213040e-02
1.21436453e+00 8.76927316e-01 8.76017272e-01 3.87529016e-01
-2.70247422e-02 8.64858568e-01 2.57428646e-01 6.44491464e-02
2.33053118e-01 -3.71628970e-01 2.81149983e-01 1.19543123e+00
-2.59902254e-02 4.64230508e-01 -7.84571052e-01 7.85440728e-02
-2.18965220e+00 -7.82520831e-01 -1.28559127e-01 2.43125653e+00
6.35853350e-01 -2.30166584e-01 -9.02690142e-02 1.93508297e-01
9.88616168e-01 3.65257233e-01 -7.64163792e-01 4.07893479e-01
-2.06965104e-01 -5.93035698e-01 8.90786424e-02 3.44988227e-01
-1.10598755e+00 7.58559406e-01 4.86003971e+00 9.63263214e-01
-9.43362057e-01 -2.30502725e-01 3.49917740e-01 2.39413887e-01
-2.22102880e-01 -6.59564808e-02 -5.87926388e-01 4.97576147e-01
1.91220269e-01 -2.59456992e-01 7.08261132e-01 8.71891141e-01
4.32243943e-01 3.32438827e-01 -9.99184608e-01 1.66088486e+00
4.80429560e-01 -7.59497404e-01 1.56266153e-01 2.52580404e-01
7.97500908e-01 -6.17426932e-01 3.13062251e-01 1.71616197e-01
-2.66164273e-01 -8.70604396e-01 4.53709394e-01 4.73550707e-01
1.19185901e+00 -7.43200779e-01 4.06891376e-01 5.11073112e-01
-1.22967601e+00 -8.21391344e-02 -6.40535593e-01 2.18970731e-01
1.90586150e-02 7.51431286e-01 -1.18942194e-01 4.43750232e-01
4.05568689e-01 1.25438762e+00 -2.36862868e-01 8.67927849e-01
-3.68856460e-01 4.18471098e-01 -2.10912347e-01 4.93986130e-01
-1.48155540e-02 -9.76447701e-01 9.09250319e-01 7.87056386e-01
1.52327374e-01 5.32419026e-01 6.20038271e-01 5.91778755e-01
-2.39447638e-01 4.98151183e-01 -6.27894521e-01 -2.62833741e-02
3.28576386e-01 1.49400067e+00 -4.37021941e-01 1.75225645e-01
-4.62277889e-01 1.03269160e+00 1.24246083e-01 6.42529368e-01
-4.30562764e-01 -1.59371153e-01 4.67089534e-01 -1.07201487e-01
-6.71073496e-02 -3.24929267e-01 -6.06610775e-02 -1.60570014e+00
2.59098172e-01 -9.88078713e-01 2.48228893e-01 -5.35114050e-01
-1.32661057e+00 4.26482260e-01 -1.38918027e-01 -1.64257276e+00
-1.78449094e-01 -6.36794925e-01 -5.46061397e-01 9.03002560e-01
-1.26288748e+00 -1.04931283e+00 -4.90230501e-01 9.88073528e-01
2.54258692e-01 -3.23148787e-01 5.70676804e-01 3.98311406e-01
-1.13831127e+00 4.10250545e-01 5.11243641e-01 2.57426143e-01
8.47890794e-01 -1.11430407e+00 -5.85599065e-01 8.73933792e-01
4.29430604e-02 8.25197637e-01 5.54545879e-01 -5.05187213e-01
-1.89136970e+00 -1.27733588e+00 3.13553929e-01 1.18213512e-01
5.42005837e-01 -2.32998267e-01 -1.02315843e+00 4.34090853e-01
-4.20511663e-01 2.89992392e-01 7.94489980e-01 -1.75461657e-02
-4.77840573e-01 -2.99439937e-01 -8.95540655e-01 5.52961290e-01
9.34916079e-01 -7.42760956e-01 -4.10138607e-01 6.51566863e-01
3.78030419e-01 -2.79536217e-01 -7.21059263e-01 5.18382907e-01
4.90430951e-01 -4.04624164e-01 1.00944054e+00 -4.71552134e-01
1.43998086e-01 -6.88318431e-01 -2.97282696e-01 -1.22218072e+00
-5.53205490e-01 -5.97396255e-01 -3.28206837e-01 1.35354662e+00
-1.37029156e-01 -5.55856943e-01 8.66442204e-01 5.30897021e-01
5.25962152e-02 -7.17163026e-01 -9.25488830e-01 -8.92456651e-01
-3.52468848e-01 -1.20557040e-01 6.67501986e-03 1.03541219e+00
-1.41048536e-01 6.26073003e-01 -8.16232264e-01 3.61402422e-01
1.22087371e+00 4.56319898e-01 6.61974609e-01 -1.30860043e+00
-2.24757642e-01 -1.41355574e-01 -2.16440782e-01 -1.34815109e+00
7.45347023e-01 -9.98491585e-01 3.07453722e-01 -1.35075057e+00
5.27733803e-01 -3.58789414e-01 -2.45628104e-01 3.32095742e-01
-3.21082860e-01 3.05029154e-01 7.42227212e-02 8.44315171e-01
-5.89954555e-01 8.86679292e-01 1.27975106e+00 -2.23546579e-01
-2.99088746e-01 1.83774270e-02 -7.62662470e-01 1.00823081e+00
5.69023430e-01 -2.98440069e-01 -3.52595896e-01 -2.97160983e-01
8.16234946e-02 1.67379409e-01 1.73744336e-01 -7.51939893e-01
2.32425317e-01 -2.57862389e-01 3.29067826e-01 -3.96743268e-01
4.15537298e-01 -9.57163036e-01 -5.87108433e-02 2.45459333e-01
-1.76361635e-01 -4.58139956e-01 -2.87193418e-01 9.56430733e-01
-4.22730029e-01 -2.64094144e-01 8.40332389e-01 1.16530664e-01
-6.36412621e-01 5.95212400e-01 6.75711110e-02 2.73932982e-03
8.52831900e-01 -1.91574737e-01 -2.87105702e-02 -3.67283940e-01
-7.14527786e-01 3.00676435e-01 4.90456611e-01 4.38179612e-01
9.50270712e-01 -1.70871568e+00 -8.91999543e-01 3.20690393e-01
2.14486599e-01 1.14093326e-01 1.53431699e-01 8.43329787e-01
-4.42128368e-02 4.30740237e-01 4.51427363e-02 -6.80791497e-01
-1.25452173e+00 6.97421134e-01 9.67599824e-02 7.09381998e-02
-5.75733781e-01 4.63475883e-01 4.30614144e-01 -3.34147334e-01
3.23893905e-01 4.94957626e-01 -5.09252727e-01 1.80678576e-01
5.56976318e-01 5.26215851e-01 -3.38792354e-01 -1.36662006e+00
-5.12334228e-01 1.04555130e+00 -1.00282207e-02 -2.63367649e-02
1.27251256e+00 -2.71155000e-01 -5.85416794e-01 3.27640116e-01
1.62441337e+00 2.22977310e-01 -1.31193888e+00 -6.09103680e-01
-5.37821325e-03 -7.09229290e-01 3.52342635e-01 -2.93181166e-02
-1.24748254e+00 7.42112279e-01 5.30155540e-01 -3.40009898e-01
1.15042770e+00 -1.68784365e-01 5.89324653e-01 5.80673039e-01
6.07072532e-01 -8.97257030e-01 2.85906106e-01 2.74508208e-01
1.12190366e+00 -1.34600985e+00 2.35843003e-01 -6.60944521e-01
-4.46012914e-01 9.11192060e-01 5.70035160e-01 -8.97162333e-02
5.61683714e-01 -4.63626713e-01 -9.49987322e-02 3.60306054e-02
-9.95742455e-02 -6.23042546e-02 7.25916386e-01 3.11790287e-01
4.29309547e-01 8.04398805e-02 -4.03624207e-01 6.16930246e-01
2.44992733e-01 -3.63767982e-01 2.47125030e-01 5.00045002e-01
-3.28958482e-01 -9.61820066e-01 -8.18995416e-01 3.54772478e-01
-2.15922624e-01 2.44986385e-01 -2.43102118e-01 1.07334182e-01
-1.39642030e-01 9.99645710e-01 -4.35047925e-01 -3.18166882e-01
2.97614306e-01 -1.82898328e-01 2.03641847e-01 -7.90707886e-01
3.27113330e-01 6.62583053e-01 -4.94688720e-01 -6.09761238e-01
-4.12937313e-01 -8.28454435e-01 -1.03526664e+00 2.11756259e-01
-3.72943848e-01 3.63854766e-01 5.04577398e-01 6.19925380e-01
-6.10340871e-02 7.69948736e-02 1.03890872e+00 -9.37176347e-01
-7.50503421e-01 -6.06909633e-01 -9.40419078e-01 7.55561292e-01
2.58222759e-01 -6.52650774e-01 -5.88177025e-01 -3.40381749e-02] | [7.893273830413818, 4.4512619972229] |
21726eb2-334e-4b26-8d05-93d33726e329 | classifying-tweet-level-judgements-of-rumours | 1506.00468 | null | http://arxiv.org/abs/1506.00468v2 | http://arxiv.org/pdf/1506.00468v2.pdf | Classifying Tweet Level Judgements of Rumours in Social Media | Social media is a rich source of rumours and corresponding community
reactions. Rumours reflect different characteristics, some shared and some
individual. We formulate the problem of classifying tweet level judgements of
rumours as a supervised learning task. Both supervised and unsupervised domain
adaptation are considered, in which tweets from a rumour are classified on the
basis of other annotated rumours. We demonstrate how multi-task learning helps
achieve good results on rumours from the 2011 England riots. | ['Kalina Bontcheva', 'Michal Lukasik', 'Trevor Cohn'] | 2015-06-01 | classifying-tweet-level-judgements-of-rumours-1 | https://aclanthology.org/D15-1311 | https://aclanthology.org/D15-1311.pdf | emnlp-2015-9 | ['rumour-detection'] | ['natural-language-processing'] | [-2.64140695e-01 2.08166793e-01 -6.01113617e-01 -5.43997705e-01
-4.15553480e-01 -1.19779907e-01 1.04780936e+00 6.01185024e-01
-1.38651446e-01 9.61239636e-01 8.45288813e-01 -8.32230449e-02
2.01537654e-01 -8.29545200e-01 -2.61066288e-01 -4.61827189e-01
-3.29193324e-01 7.44252980e-01 2.64837831e-01 -9.47570324e-01
7.84496784e-01 -2.12714151e-01 -1.06134975e+00 9.82533038e-01
4.16118383e-01 6.53555393e-01 -2.52690345e-01 5.56661367e-01
-4.73971397e-01 1.73798561e+00 -1.00108612e+00 -3.89207035e-01
-2.54290789e-01 -5.32232940e-01 -1.34004307e+00 3.73572737e-01
2.59378571e-02 -5.72855286e-02 3.94627266e-02 7.93679476e-01
3.21089536e-01 1.46375343e-01 1.08119023e+00 -1.21217239e+00
-6.63290620e-01 9.75923955e-01 -5.43669939e-01 7.37486660e-01
5.75491488e-01 -4.33362216e-01 9.08045769e-01 -7.69363403e-01
5.54470479e-01 1.23332822e+00 9.07451212e-01 2.05874607e-01
-1.24036825e+00 -8.53420794e-01 -2.34967396e-01 3.91410798e-01
-9.77577865e-01 -2.27794766e-01 9.74557579e-01 -1.10653627e+00
5.88355362e-01 1.10369645e-01 1.89977288e-01 1.44776821e+00
4.00202155e-01 6.01187050e-01 1.61058652e+00 5.97450435e-02
1.90470263e-01 8.80179107e-01 3.18886876e-01 2.34673724e-01
-3.51216406e-01 -1.30336836e-01 -8.06041002e-01 -8.39107513e-01
1.63037643e-01 -1.01338364e-01 4.60765548e-02 1.51884377e-01
-9.23255622e-01 1.60730934e+00 5.77169836e-01 8.97527412e-02
-7.59282827e-01 -6.42128646e-01 7.96401680e-01 1.14706957e+00
1.60643685e+00 5.43349683e-01 -3.18885535e-01 2.98871368e-01
-1.04020500e+00 4.95708615e-01 1.36164916e+00 2.81486750e-01
9.53520775e-01 -1.61629766e-01 2.68779874e-01 1.46811354e+00
2.41894573e-02 2.29750708e-01 7.25407541e-01 -2.96870142e-01
2.34598443e-01 3.34747046e-01 4.26862597e-01 -1.53499925e+00
-8.69405091e-01 -3.78438234e-01 -7.17535555e-01 -5.79367690e-02
2.12738797e-01 -6.50418460e-01 -3.09721202e-01 9.72097099e-01
3.20018411e-01 -2.60860045e-02 -3.86346504e-02 8.61034811e-01
9.44345713e-01 7.15482473e-01 -9.78028774e-02 -4.47447866e-01
1.23682880e+00 -7.54282534e-01 -8.67159843e-01 -4.42319959e-01
2.97347605e-01 -9.78666961e-01 3.47060204e-01 4.37975734e-01
-8.44643295e-01 -1.44911036e-01 -8.65068436e-01 5.74812174e-01
-4.83551174e-01 -8.14215362e-01 3.29741955e-01 4.62626666e-01
-5.29729843e-01 7.00569630e-01 1.57505676e-01 -2.48940900e-01
3.15371871e-01 -1.46034481e-02 1.22532748e-01 2.71542221e-01
-1.86945045e+00 1.18107665e+00 2.70469993e-01 -4.76281166e-01
-9.34656799e-01 -1.19438767e-01 -4.54712868e-01 -6.47454977e-01
-4.33252640e-02 -3.13321859e-01 1.48890936e+00 -1.29033768e+00
-1.46622097e+00 1.17749608e+00 6.35856241e-02 -7.59896934e-01
6.53103888e-01 1.87850043e-01 -8.93834114e-01 -2.37551015e-02
3.76492023e-01 -2.50868708e-01 1.43742096e+00 -1.09414089e+00
-7.61690915e-01 -2.02803925e-01 -3.70965093e-01 2.41768528e-02
-3.19239914e-01 8.70137691e-01 1.01503384e+00 -3.41137171e-01
-7.05966428e-02 -7.08320439e-01 -1.74481273e-01 -1.11466944e+00
-3.98627490e-01 -4.78408098e-01 6.46671951e-01 -5.29416084e-01
8.34493101e-01 -1.53947866e+00 -3.17741007e-01 7.41772577e-02
6.35747194e-01 -3.74717116e-02 3.45820457e-01 6.93198383e-01
7.08564594e-02 2.06696510e-01 2.46689126e-01 -1.45312384e-01
-2.48564228e-01 1.33156925e-02 -5.06458879e-01 8.08587968e-01
1.44366175e-01 3.79014492e-01 -1.30459940e+00 -3.59950393e-01
-3.72560889e-01 -5.31572551e-02 -1.86086580e-01 4.67662334e-01
-1.27708420e-01 5.97742498e-01 -4.69161183e-01 1.60888657e-01
6.31035507e-01 -4.63178545e-01 1.74605206e-01 3.53645802e-01
-2.58246571e-01 1.05867577e+00 -4.27497864e-01 4.71680015e-01
-3.94692868e-01 7.93505967e-01 1.22216202e-01 -9.19469178e-01
1.40949917e+00 6.52367771e-01 3.08728874e-01 -3.86183828e-01
3.73163581e-01 2.42931306e-01 -2.31420025e-01 -6.66352034e-01
7.22906590e-01 -1.02222788e+00 -4.96375799e-01 9.99018371e-01
-1.61705941e-01 -3.09664309e-01 -3.51380825e-01 2.96342403e-01
7.74254322e-01 -7.52237558e-01 7.88348198e-01 -4.18119639e-01
2.31882378e-01 4.42771941e-01 9.28611532e-02 7.42513359e-01
-2.84098655e-01 3.65749478e-01 6.90728962e-01 -6.90968692e-01
-1.00134671e+00 -6.81264222e-01 -3.89702111e-01 1.91524017e+00
-1.20306231e-01 5.03062308e-02 -1.86478853e-01 -7.32146919e-01
1.53073668e-01 6.62981272e-01 -1.03062546e+00 2.74235576e-01
-1.68782070e-01 -1.38364458e+00 4.21012163e-01 -2.18599048e-02
3.40227515e-01 -1.20034444e+00 1.38212994e-01 4.81192797e-01
-6.05209589e-01 -8.93628776e-01 -2.21671060e-01 2.54952341e-01
-5.61070681e-01 -8.36217463e-01 -6.32010996e-01 -8.56046736e-01
1.26182720e-01 3.27805191e-01 1.33627665e+00 6.02345057e-02
5.05477548e-01 -3.90378386e-01 -6.30090773e-01 -6.11685693e-01
-1.12900996e+00 3.09732351e-02 2.31414258e-01 2.71094471e-01
5.51095724e-01 -7.38036156e-01 -1.25577545e-03 7.67648637e-01
-4.04086471e-01 -1.67453527e-01 7.15581328e-02 8.81947219e-01
-3.76247168e-01 -7.63981119e-02 1.35403299e+00 -1.46636713e+00
1.36638260e+00 -1.73610556e+00 3.77835780e-01 -6.65059984e-01
-5.64172447e-01 -5.59537649e-01 4.35054213e-01 -4.50485319e-01
-1.04244626e+00 -6.85834408e-01 1.03884161e-01 4.65130001e-01
-2.78510541e-01 7.93733418e-01 9.53923523e-01 7.36369193e-02
1.56568336e+00 7.91360438e-02 1.40505448e-01 -5.09733617e-01
1.39372274e-01 1.52791834e+00 6.68449998e-02 -1.97756603e-01
4.72576469e-01 4.63739306e-01 -6.03565037e-01 -1.01591361e+00
-1.56013286e+00 -1.14479887e+00 -6.75357640e-01 -4.74232107e-01
3.99997950e-01 -9.67764795e-01 -3.96263272e-01 4.65863585e-01
-1.23357236e+00 -3.91377538e-01 3.15788776e-01 1.23272710e-01
-4.13657576e-01 5.62432408e-02 -1.25663769e+00 -8.76612902e-01
-2.10417226e-01 -2.53349930e-01 -1.30746653e-02 -2.32914507e-01
-8.14558089e-01 -1.31953239e+00 6.29055679e-01 6.30645156e-01
7.14087009e-01 3.06937248e-01 4.81084317e-01 -1.58024204e+00
4.39955443e-01 -2.13853016e-01 -4.72520351e-01 2.11367324e-01
2.04573438e-01 -5.20826399e-01 -9.49344397e-01 -1.24227501e-01
3.88272375e-01 -9.82127666e-01 9.32991683e-01 -2.04627410e-01
1.92234203e-01 -9.32545245e-01 -1.07916780e-01 -2.53233224e-01
9.23677921e-01 -3.05868089e-01 2.01102257e-01 7.23345220e-01
3.47100854e-01 1.00584590e+00 4.70157474e-01 9.13068712e-01
5.83021820e-01 3.11894566e-01 4.71012264e-01 1.44650489e-01
2.27476165e-01 -2.23109424e-02 7.39464998e-01 1.01994157e+00
-6.21235371e-02 -3.01025212e-02 -1.17254090e+00 8.46450508e-01
-1.81830776e+00 -1.26908112e+00 -7.05782473e-01 1.65507543e+00
1.05154049e+00 2.15433881e-01 8.51283371e-01 3.41639221e-02
1.03584290e+00 6.96687698e-01 -5.78921922e-02 -1.00725687e+00
-2.36054495e-01 -3.49591523e-01 4.50802326e-01 6.55463994e-01
-1.09489727e+00 5.42381287e-01 7.31902313e+00 1.76299050e-01
-1.13468599e+00 6.84638321e-01 3.70636553e-01 -1.29025474e-01
-6.00922592e-02 -4.95679617e-01 -4.97342676e-01 4.76373106e-01
1.38971090e+00 -3.28814626e-01 3.10138464e-01 7.25896120e-01
3.36712122e-01 1.26347184e-01 -4.92937952e-01 1.78439990e-01
5.25275528e-01 -1.29340720e+00 -2.23218679e-01 7.63922418e-03
1.17563248e+00 8.04400384e-01 -3.27442028e-02 5.92356503e-01
7.46361434e-01 -7.77902901e-01 6.69751465e-01 9.69826356e-02
-1.75845120e-02 -7.03080177e-01 9.16316032e-01 7.85322964e-01
-2.39399925e-01 -1.35737464e-01 -4.06600565e-01 -7.32597351e-01
2.80924827e-01 8.12202394e-01 -1.86788237e+00 9.49733034e-02
4.88602549e-01 1.08209562e+00 -1.32748872e-01 6.90390527e-01
-3.44866902e-01 1.01317704e+00 2.00256422e-01 -2.83325553e-01
3.62952948e-01 2.67147928e-01 7.91656554e-01 1.81047261e+00
-3.91406208e-01 -5.54339290e-02 5.81496060e-01 6.29946113e-01
-1.75010011e-01 4.72638339e-01 -4.57696646e-01 2.00365007e-01
1.45755038e-01 1.04502666e+00 -3.43149811e-01 -5.28864503e-01
-2.77838588e-01 8.63895655e-01 4.17605996e-01 8.76697525e-03
-6.31666541e-01 1.06868977e-02 5.79311848e-01 6.50432408e-01
-9.08938721e-02 3.30674082e-01 -2.70429850e-01 -1.06103015e+00
-8.02285016e-01 -7.84485102e-01 4.84495282e-01 -3.65316987e-01
-2.14170623e+00 7.55061865e-01 -2.69668728e-01 -9.94037926e-01
-4.42539454e-01 -8.60053599e-02 -9.90334511e-01 6.72216237e-01
-1.75353563e+00 -7.66701996e-01 -2.23934233e-01 6.64187491e-01
6.10399842e-01 -2.40811542e-01 6.96417332e-01 1.31358638e-01
-2.46617720e-01 -6.13593645e-02 1.33943275e-01 3.04882854e-01
1.14618528e+00 -1.33645070e+00 3.99687171e-01 -1.78952858e-01
-4.87868786e-01 2.39799276e-01 1.29193151e+00 -7.06153810e-01
-2.11172581e-01 -1.14216566e+00 1.38002491e+00 -6.10257685e-01
1.50855923e+00 -5.85969212e-03 -1.19036150e+00 7.90174961e-01
4.25098330e-01 -3.64922166e-01 9.89187241e-01 8.25810432e-01
-6.28664970e-01 5.82571566e-01 -1.27171171e+00 3.52929868e-02
3.15734148e-01 -8.40142071e-01 -1.19721842e+00 1.10592628e+00
1.58012792e-01 5.88962547e-02 -9.37857926e-01 -2.00126007e-01
2.33814076e-01 -1.11158276e+00 6.71031654e-01 -1.08813894e+00
8.74536216e-01 2.30114236e-01 8.14574137e-02 -2.00845838e+00
-5.54675877e-01 -7.17934132e-01 2.18342483e-01 9.17565644e-01
5.80577791e-01 -9.25859690e-01 6.75177276e-01 -4.48719924e-03
2.87005037e-01 -1.45123139e-01 -4.47631210e-01 -6.91844642e-01
4.76601690e-01 -2.17897654e-01 2.68315285e-01 1.73028147e+00
1.04395545e+00 1.01262152e+00 -1.03826201e+00 -7.10315630e-02
7.14886963e-01 2.81744987e-01 7.24982083e-01 -1.58674943e+00
6.91139475e-02 -5.18457592e-01 -4.49092947e-02 -8.35774958e-01
3.13061833e-01 -9.17269051e-01 3.10581237e-01 -1.09500992e+00
4.43097591e-01 -3.06892961e-01 -2.94994950e-01 5.65170906e-02
6.37803599e-03 4.52097267e-01 -1.79448664e-01 7.63296187e-01
-6.24275029e-01 7.06761554e-02 1.00077212e+00 -2.10002184e-01
-2.33870789e-01 5.65076828e-01 -5.19789875e-01 1.08128417e+00
1.18079031e+00 -1.07398069e+00 2.40201175e-01 2.74371356e-01
7.10660636e-01 4.54567820e-01 2.08440676e-01 -3.74668330e-01
2.77976424e-01 -4.52636808e-01 -2.28913173e-01 -4.20427173e-01
3.46196324e-01 1.11672051e-01 -2.61288613e-01 1.33118212e-01
-7.93205500e-01 -3.58736366e-01 -3.06423873e-01 7.46569157e-01
-3.71067286e-01 -2.34029725e-01 9.89506721e-01 -4.26213354e-01
-4.68902737e-01 -8.46585631e-02 -1.12068927e+00 2.91789502e-01
5.58188975e-01 1.79671824e-01 -6.33793831e-01 -8.73237193e-01
-1.10263312e+00 -1.27645984e-01 2.70231634e-01 3.99732918e-01
4.85476643e-01 -7.99140275e-01 -1.68989897e+00 -1.71781734e-01
2.07758188e-01 -8.54891598e-01 -4.08742167e-02 1.18374145e+00
1.73882008e-01 9.30525362e-02 -4.84214216e-01 -2.47653916e-01
-1.06996334e+00 4.77740198e-01 2.32141539e-01 -2.31406406e-01
-3.10973525e-01 8.15447330e-01 -1.42060220e-02 -7.15705395e-01
-3.47412199e-01 5.31569898e-01 -8.14019024e-01 8.85169268e-01
9.79611456e-01 6.14628017e-01 5.06365485e-02 -9.11949158e-01
-8.91421437e-02 -3.25823814e-01 -3.11529607e-01 4.81595360e-02
1.32053840e+00 -4.77715820e-01 -4.11343604e-01 9.87725437e-01
1.32760251e+00 1.48382813e-01 -4.86136943e-01 -7.82930553e-01
4.12053794e-01 -3.55125934e-01 3.42660666e-01 -8.35232913e-01
-4.98961180e-01 4.56345052e-01 -3.76400858e-01 1.14397609e+00
2.95428246e-01 1.67879581e-01 9.50433552e-01 7.32670799e-02
3.96931618e-01 -1.07983303e+00 3.17011535e-01 1.00158012e+00
1.01879311e+00 -1.62172282e+00 2.04321265e-01 -2.92750925e-01
-1.22389662e+00 1.04548311e+00 1.71952695e-02 -5.77477515e-01
9.27857161e-01 -1.54970825e-01 3.31674397e-01 -5.68980634e-01
-9.63363349e-01 -1.85413714e-02 9.77066383e-02 4.57651854e-01
5.96187532e-01 3.88265222e-01 -3.37259442e-01 5.04021406e-01
-3.36989492e-01 -2.14580700e-01 1.07449543e+00 4.88420576e-01
-1.05530977e+00 -4.03201133e-01 -5.69945514e-01 6.49882853e-01
-9.37777281e-01 -4.32299413e-02 -8.73435676e-01 3.75845045e-01
-1.50031313e-01 1.38956547e+00 -1.02637984e-01 -7.36938953e-01
-5.64993471e-02 2.39746079e-01 -2.07266927e-01 -1.05226099e+00
-1.17771494e+00 -3.06298465e-01 1.02684367e+00 -3.39602195e-02
-5.44438303e-01 -9.00004685e-01 -8.22711945e-01 -8.19363654e-01
-4.94031817e-01 6.74750626e-01 6.58648551e-01 1.18210232e+00
-2.88547486e-01 2.27982715e-01 1.32124829e+00 -8.93996716e-01
-8.35872650e-01 -1.40409982e+00 -9.66440916e-01 7.08426476e-01
8.85342062e-01 -5.31005859e-01 -8.92192602e-01 2.76913438e-02] | [8.224727630615234, 10.052042007446289] |
6d31000b-1b48-47f6-8f5b-d01b7296c8b9 | an-interpretable-generative-model-for | 1811.04507 | null | http://arxiv.org/abs/1811.04507v1 | http://arxiv.org/pdf/1811.04507v1.pdf | An Interpretable Generative Model for Handwritten Digit Image Synthesis | An interpretable generative model for handwritten digits synthesis is
proposed in this work. Modern image generative models, such as Generative
Adversarial Networks (GANs) and Variational Autoencoders (VAEs), are trained by
backpropagation (BP). The training process is complex and the underlying
mechanism is difficult to explain. We propose an interpretable multi-stage PCA
method to achieve the same goal and use handwritten digit images synthesis as
an illustrative example. First, we derive principal-component-analysis-based
(PCA-based) transform kernels at each stage based on the covariance of its
inputs. This results in a sequence of transforms that convert input images of
correlated pixels to spectral vectors of uncorrelated components. In other
words, it is a whitening process. Then, we can synthesize an image based on
random vectors and multi-stage transform kernels through a coloring process.
The generative model is a feedforward (FF) design since no BP is used in model
parameter determination. Its design complexity is significantly lower, and the
whole design process is explainable. Finally, we design an FF generative model
using the MNIST dataset, compare synthesis results with those obtained by
state-of-the-art GAN and VAE methods, and show that the proposed generative
model achieves comparable performance. | ['C. -C. Jay Kuo', 'Yao Zhu', 'Yueru Chen', 'Pranav Kulkarni', 'Jiali Duan', 'Saksham Suri'] | 2018-11-11 | null | null | null | null | ['handwritten-digit-image-synthesis'] | ['computer-vision'] | [ 4.20574605e-01 2.76609659e-01 9.84895751e-02 -5.26574664e-02
-2.36842319e-01 -4.92353827e-01 8.11731339e-01 -9.26221550e-01
1.40690550e-01 8.52537036e-01 1.20970219e-01 -2.54340976e-01
7.02839270e-02 -1.01181233e+00 -9.84559178e-01 -1.11747766e+00
7.59018242e-01 5.20493686e-01 -1.62534088e-01 -1.01373062e-01
-1.00675113e-01 6.98737741e-01 -9.26581264e-01 2.45834559e-01
9.14334357e-01 6.09514773e-01 3.45604979e-02 8.10444295e-01
-2.49108583e-01 1.11353779e+00 -7.54115522e-01 -7.24723756e-01
1.23387009e-01 -1.18302286e+00 -4.94661331e-01 5.70021391e-01
-1.17508166e-01 -1.42443761e-01 -7.11386144e-01 1.07949650e+00
1.14422634e-01 -7.17860088e-02 1.21861422e+00 -1.35223162e+00
-1.61498165e+00 7.94055879e-01 -4.02817070e-01 -4.49137330e-01
-4.68363971e-01 1.12314023e-01 6.13230765e-01 -9.21682775e-01
4.25546080e-01 1.21998918e+00 4.42944646e-01 8.99721384e-01
-1.58879423e+00 -4.83241260e-01 -8.67204517e-02 1.53920367e-01
-1.13335228e+00 -1.47921935e-01 1.27734840e+00 -4.74558175e-01
5.32515228e-01 4.70145315e-01 8.76829684e-01 1.53831911e+00
5.37543416e-01 7.83390462e-01 1.16255701e+00 -5.05818427e-01
4.41948593e-01 1.34384073e-03 -3.25733304e-01 6.02161944e-01
8.76300186e-02 1.69600084e-01 -2.32874677e-01 2.45160684e-01
1.34949136e+00 3.60623240e-01 -3.78747880e-01 -3.09408039e-01
-1.08898234e+00 1.09456265e+00 7.44209051e-01 1.96059197e-01
-6.55526757e-01 6.14857733e-01 -2.32791170e-01 7.98197687e-02
3.17368567e-01 3.80137742e-01 6.27600402e-02 2.41539955e-01
-9.03729439e-01 -7.83752128e-02 8.28595102e-01 8.98770154e-01
7.29498684e-01 8.59962344e-01 -3.14540863e-01 7.89314270e-01
4.82438594e-01 7.72081494e-01 5.67948282e-01 -8.20090234e-01
1.92304462e-01 4.50428575e-01 -3.25631887e-01 -7.48108387e-01
4.98601906e-02 -7.10500717e-01 -1.50239205e+00 6.02817535e-01
1.40196517e-01 -2.68593401e-01 -1.50843692e+00 1.43305159e+00
-1.81234360e-01 7.65371323e-02 2.75275558e-01 8.97936881e-01
7.23676145e-01 1.01478124e+00 -5.02341688e-02 -3.49931116e-03
1.15284991e+00 -1.19439983e+00 -9.69339132e-01 -3.32619309e-01
-3.95173550e-01 -7.90316164e-01 8.82789552e-01 3.19885552e-01
-9.68526244e-01 -8.19090009e-01 -1.21600485e+00 1.47678301e-01
-1.60384819e-01 5.35851836e-01 6.65771186e-01 7.72409141e-01
-9.84729230e-01 5.51656306e-01 -9.35322106e-01 3.56592424e-02
3.69054526e-01 7.76234642e-02 -3.13783772e-02 1.92586839e-01
-8.09660494e-01 7.29067802e-01 3.57439399e-01 3.81780028e-01
-1.07596171e+00 -3.31242114e-01 -6.00930274e-01 2.46536538e-01
-1.66916288e-02 -1.00538135e+00 7.49602437e-01 -1.34977937e+00
-2.06707311e+00 3.12280864e-01 -1.68430403e-01 -3.54087800e-01
6.25274479e-01 -2.75828484e-02 -3.59336406e-01 6.90681338e-02
-3.86292011e-01 7.28047192e-01 1.51984310e+00 -1.66443551e+00
-5.45221157e-02 1.17064394e-01 -2.32562363e-01 -2.74895519e-01
-1.29397616e-01 -3.99777710e-01 -3.16623062e-01 -1.08798528e+00
3.04136783e-01 -1.09963894e+00 -2.92260498e-01 -2.06346095e-01
-7.35536993e-01 4.70441073e-01 7.79423296e-01 -8.85932922e-01
7.07808137e-01 -2.03162718e+00 5.48579037e-01 3.41807634e-01
2.52995521e-01 1.42248109e-01 -1.89122185e-01 3.35861683e-01
-2.61513412e-01 1.46531478e-01 -4.65266377e-01 -2.92525113e-01
9.99157950e-02 5.76606035e-01 -7.15810835e-01 5.92900142e-02
6.08297169e-01 1.39341104e+00 -4.86056387e-01 -1.02942750e-01
4.25756544e-01 8.71468008e-01 -5.38507938e-01 2.32900545e-01
-1.96532249e-01 6.72179461e-01 -2.87551194e-01 4.53647465e-01
5.85619390e-01 -3.64560872e-01 -3.10457358e-03 -4.69532996e-01
1.45888820e-01 -2.83117622e-01 -7.62714565e-01 1.31843281e+00
-6.02139354e-01 8.65828931e-01 -5.34160316e-01 -9.73359644e-01
1.44987631e+00 2.98643291e-01 5.48457466e-02 -1.93630546e-01
1.00701123e-01 1.42684162e-01 1.36607692e-01 -1.05730735e-01
1.67152137e-01 -1.87444866e-01 2.48885557e-01 2.98215240e-01
2.59398758e-01 -3.35865319e-01 -1.21339284e-01 -7.23686367e-02
1.00287771e+00 3.94384980e-01 1.15523212e-01 3.35547924e-02
5.33969462e-01 -1.07830510e-01 3.72700244e-01 5.00847876e-01
5.16487122e-01 1.01401222e+00 5.60951769e-01 -4.46798384e-01
-1.51588833e+00 -1.18208301e+00 2.45758265e-01 2.33509287e-01
-1.70706496e-01 -2.37684362e-02 -1.00025344e+00 -4.32679832e-01
-3.53156298e-01 1.03627181e+00 -8.02288294e-01 -3.60713065e-01
-5.75227797e-01 -9.64428127e-01 3.64903897e-01 7.49733984e-01
8.68765891e-01 -1.25759661e+00 -1.69901088e-01 3.65155697e-01
-5.42053059e-02 -9.46332157e-01 -1.78409055e-01 4.24529850e-01
-8.88598621e-01 -5.83910882e-01 -1.19287443e+00 -7.47981787e-01
1.13276386e+00 -3.51892531e-01 9.07045364e-01 -3.75878602e-01
-7.90913627e-02 1.14970185e-01 -3.32886457e-01 -3.07409018e-01
-8.64878118e-01 -2.65854955e-01 -2.89367884e-01 3.20364267e-01
-1.80516392e-02 -8.94079030e-01 -4.27968442e-01 2.69259870e-01
-1.04783916e+00 4.07146692e-01 1.12606657e+00 1.41555643e+00
9.22690690e-01 1.62661180e-01 3.53142470e-01 -8.94288599e-01
6.29541636e-01 -4.40835766e-02 -6.52031422e-01 4.84664589e-01
-5.06760061e-01 4.20212150e-01 1.06912029e+00 -7.11269796e-01
-1.26533389e+00 3.04143161e-01 -2.72247970e-01 -9.11735952e-01
-1.16329551e-01 3.09945077e-01 -3.04388076e-01 -1.97479486e-01
7.34234273e-01 7.90004492e-01 -1.07561000e-01 -3.71432900e-01
5.93017220e-01 2.81750917e-01 7.57399142e-01 -3.55069280e-01
1.26781178e+00 3.49372596e-01 1.62145540e-01 -6.18557334e-01
-2.87449986e-01 6.76567137e-01 -4.84691173e-01 -2.49586433e-01
1.05133760e+00 -6.31146133e-01 -4.98938888e-01 5.37561297e-01
-1.38449669e+00 -4.25488144e-01 -6.12566650e-01 5.21601617e-01
-7.44857967e-01 -3.58766839e-02 -8.28083336e-01 -7.43019640e-01
-3.61600965e-01 -1.28185511e+00 6.54103220e-01 3.94493848e-01
6.83888867e-02 -9.17484879e-01 -1.32727027e-01 1.86605871e-01
4.74888533e-01 4.46353734e-01 1.08883762e+00 -3.28306794e-01
-8.64291668e-01 6.13555172e-03 -3.91809791e-02 7.01139927e-01
3.79210055e-01 2.73449302e-01 -9.99360681e-01 3.89927663e-02
1.75896555e-01 1.63646057e-01 9.88390923e-01 6.02232814e-01
1.30543971e+00 -5.74008703e-01 -6.89990819e-02 9.87417877e-01
1.42995679e+00 6.56153440e-01 1.20004296e+00 2.00444385e-01
9.89551902e-01 4.03195098e-02 -2.40579948e-01 1.20896019e-01
-2.62860149e-01 3.21783870e-01 3.75216186e-01 -4.32991326e-01
-5.05388737e-01 -5.08619308e-01 3.55952054e-01 1.02218783e+00
-6.49000227e-01 -3.96484137e-01 -6.11315906e-01 1.40044857e-02
-1.91277790e+00 -9.23525095e-01 -9.45269391e-02 1.69387877e+00
5.60755551e-01 3.55394185e-02 -3.57332885e-01 3.00052732e-01
8.00936580e-01 5.64855263e-02 -6.71351075e-01 -3.88041228e-01
-2.58525103e-01 6.39967620e-01 5.80487192e-01 2.57425338e-01
-8.25899601e-01 9.38981771e-01 6.25653028e+00 8.55999649e-01
-1.32033026e+00 -6.29950464e-02 8.54790390e-01 3.89006883e-01
-5.42013109e-01 -4.54602465e-02 -3.09224755e-01 4.04620826e-01
5.95695257e-01 4.55693826e-02 8.65525305e-01 9.43488717e-01
-7.46522918e-02 4.42996562e-01 -1.06049085e+00 1.16545558e+00
9.98793244e-02 -1.50722528e+00 5.17325759e-01 1.15631811e-01
9.54236925e-01 -6.31260335e-01 4.33164358e-01 9.30715501e-02
4.27421063e-01 -1.25142086e+00 9.39409852e-01 8.99103522e-01
7.15471268e-01 -1.01751530e+00 5.94729185e-01 1.54427409e-01
-8.64821792e-01 1.38207942e-01 -6.20752454e-01 2.81310886e-01
1.08877860e-01 6.62531674e-01 -5.94143629e-01 3.90132517e-01
3.10696006e-01 4.70750093e-01 -3.33714932e-01 7.50516415e-01
-9.20145214e-01 9.10911262e-01 1.95374683e-01 -1.76273689e-01
2.17811942e-01 -6.21023476e-01 4.63690877e-01 8.82339060e-01
6.06325746e-01 1.60640076e-01 -5.15824497e-01 1.77212870e+00
-2.46203378e-01 -3.78026694e-01 -2.59078115e-01 -2.78315008e-01
1.04820698e-01 1.23553729e+00 -9.41794634e-01 -3.32556427e-01
-1.42085701e-01 1.46529138e+00 -1.21343859e-01 7.80449867e-01
-1.09501195e+00 -4.42902237e-01 3.67594808e-01 -2.94166952e-01
6.37322068e-01 -1.83637604e-01 -3.83834451e-01 -1.25853479e+00
-1.36426613e-01 -9.40269411e-01 -4.19713706e-01 -1.11764896e+00
-1.34514689e+00 9.35915172e-01 -4.33483541e-01 -1.27955925e+00
-4.78266627e-01 -7.32371628e-01 -7.33974457e-01 1.15349245e+00
-1.31300282e+00 -1.25535572e+00 -3.94082338e-01 6.31953835e-01
5.93447387e-01 -4.81658220e-01 9.36679363e-01 6.33690273e-03
-5.67298412e-01 5.35399020e-01 3.29461724e-01 3.68030131e-01
1.78689361e-01 -1.25079596e+00 6.23308122e-01 1.09947550e+00
5.11787713e-01 4.80164081e-01 6.66429579e-01 -5.72304606e-01
-1.47440350e+00 -1.25765026e+00 2.95475394e-01 -5.67373931e-02
4.44776714e-01 -2.90428191e-01 -7.65469551e-01 8.43045235e-01
4.68905151e-01 -1.28831491e-01 5.38557708e-01 -3.99173051e-01
-8.74201357e-02 -4.72826250e-02 -1.03307748e+00 7.02728570e-01
8.16654801e-01 -3.26820821e-01 -5.75225711e-01 9.95208770e-02
6.06904089e-01 -4.20815438e-01 -6.44046187e-01 1.54238362e-02
4.31822062e-01 -8.18614304e-01 1.04339981e+00 -4.17129874e-01
1.04317498e+00 -3.86914670e-01 2.84148827e-02 -1.77721679e+00
-8.48822713e-01 -6.41643941e-01 -2.60555446e-01 1.29882860e+00
5.16468048e-01 -7.13610947e-01 7.14159548e-01 5.36904514e-01
-2.16641858e-01 -5.61875582e-01 -4.19707775e-01 -8.51884246e-01
-1.47257969e-01 -2.63380967e-02 7.82008946e-01 7.81229794e-01
-5.93846738e-01 4.86313462e-01 -7.36206830e-01 1.63261175e-01
8.56647849e-01 2.99634725e-01 7.39136219e-01 -8.16195726e-01
-7.18292832e-01 -3.53257358e-01 -4.07432765e-01 -1.04475534e+00
5.17380424e-02 -6.85230792e-01 -2.37833131e-02 -1.64871395e+00
-2.65754778e-02 -1.41069695e-01 -5.11235408e-02 5.64168692e-01
-4.26875092e-02 2.74752706e-01 3.60372901e-01 3.68500531e-01
4.10138458e-01 9.70437706e-01 1.57405913e+00 -5.63273847e-01
-9.52235535e-02 2.30903998e-02 -4.25509453e-01 6.32766902e-01
7.54072428e-01 -3.63158703e-01 -4.48631853e-01 -3.02126467e-01
-7.35234171e-02 1.49216622e-01 5.66002131e-01 -1.10730600e+00
3.32351848e-02 -1.15376301e-01 1.12596583e+00 -3.92562687e-01
5.03884137e-01 -8.98188412e-01 9.71443951e-01 7.55526721e-01
-2.22354144e-01 -2.35196412e-01 1.63755137e-02 3.96729052e-01
-4.15805101e-01 -3.20199788e-01 7.12759197e-01 -1.33702636e-01
-4.57890421e-01 2.06355616e-01 -3.66104215e-01 -4.58114117e-01
7.90452063e-01 -2.28952333e-01 -3.89406085e-01 -4.74498928e-01
-9.14438426e-01 -6.09950185e-01 2.35609889e-01 1.57571763e-01
8.61616910e-01 -1.74760127e+00 -7.74967432e-01 2.94508934e-01
-3.73472869e-01 -1.25252515e-01 1.05232723e-01 4.01794732e-01
-9.17726040e-01 2.72061676e-01 -6.70305669e-01 -4.27762181e-01
-7.85947919e-01 6.41439438e-01 3.55203480e-01 -1.34837672e-01
-6.78717852e-01 7.41809368e-01 4.32250321e-01 -1.31386444e-01
-2.63377428e-01 -3.04713339e-01 -8.47246647e-02 -3.54878753e-01
2.92850256e-01 1.07481226e-01 -2.90842623e-01 -3.74531388e-01
5.46792708e-02 6.07793212e-01 4.56952214e-01 -1.51140451e-01
1.58446097e+00 3.82058084e-01 -8.93193707e-02 8.72165635e-02
9.78138030e-01 -1.11125097e-01 -1.48418927e+00 2.24929508e-02
-6.67234182e-01 -3.13852876e-01 -4.21731360e-02 -7.36597955e-01
-1.73730052e+00 1.02283657e+00 4.60175484e-01 2.26582244e-01
1.25919235e+00 -1.97096989e-01 5.12900412e-01 3.04410040e-01
4.70268391e-02 -7.42121696e-01 1.43589690e-01 1.79897785e-01
1.23591793e+00 -6.99334502e-01 -1.90449819e-01 -4.78594720e-01
-7.28238940e-01 1.53383386e+00 4.52027678e-01 -4.44040567e-01
3.90033156e-01 3.29885095e-01 -2.08538584e-02 2.68921126e-02
-4.74298537e-01 2.17134487e-02 5.06335020e-01 6.31862521e-01
8.91164318e-02 2.43555471e-01 -1.93253636e-01 6.52051389e-01
-4.44582105e-01 -9.35678855e-02 4.05539900e-01 5.69395602e-01
-2.51712231e-03 -1.09982336e+00 -5.57052910e-01 2.01434702e-01
-8.46119747e-02 -1.17281884e-01 -4.64767694e-01 6.71746790e-01
2.27357820e-02 6.23128355e-01 -3.01264413e-02 -6.88033044e-01
1.09306827e-01 1.58630937e-01 6.47001386e-01 -9.64875743e-02
-2.58076280e-01 2.31592909e-01 -4.86656725e-01 -1.34823054e-01
-3.75282496e-01 -1.84924304e-01 -9.69970465e-01 -3.06979060e-01
-1.46248579e-01 -3.64214480e-02 7.97227025e-01 7.41706371e-01
1.25306278e-01 1.29648411e+00 6.88942254e-01 -9.28755641e-01
-3.55854869e-01 -8.28902781e-01 -5.98347247e-01 1.64879844e-01
1.22188609e-02 -3.92278165e-01 -3.50979686e-01 6.48383677e-01] | [11.612869262695312, -0.4621635973453522] |
846d6f6e-6b97-473d-baca-b97122e80b96 | identification-and-molecular-dynamic | 2211.02826 | null | https://arxiv.org/abs/2211.02826v1 | https://arxiv.org/pdf/2211.02826v1.pdf | Identification and Molecular Dynamic Simulation of Flavonoids from Mediterranean species of Oregano against the Zika NS2B-NS3 Protease | The Zika virus, is an emerging infectious disease causing severe complications such as microcephaly in infants and Guillain Barre syndrome in adults. There is no licensed vaccination or approved medicine to treat ZIKV infection. Therefore, extensive research is being carried out to find compounds that can be used effectively as therapeutic molecules to treat ZIKV infection. Oregano, a commonly found herb in the Mediterranean region, has been used predominantly for culinary purposes. The fact that the members of the Origanum species are a storehouse of various bioactive compounds gives us a solid reason to study compounds extracted from it for therapeutic purposes. In this study, were retrieved 20 Flavonoids found in various Origanum species belonging to the Mediterranean region from the PubChem database and pharmacological analysis using SwissADME and Molecular docking using AutoDock Vina 4.0. were carried out against the NS2B NS3 protease since it serves as an effective drug target owing to its role in viral replication and immune evasion within the host. The best hit compounds were subjected to MD simulation at 100 ns using Desmond Schrodinger to analyze the molecule's stability. We observed Cirsiliol as the best hit compound against the NS2B NS3 complex with a binding affinity of -8.5 kcal per mol. It also showed good stability during MD simulation. We recommend the use of Cirsiliol for in vitro and in vivo studies for further investigation concerning the ZIKA virus. | ['Sameer Sharma', 'Arka Sanyal', 'Anushikha Ghosh'] | 2022-11-05 | null | null | null | null | ['molecular-docking'] | ['medical'] | [ 8.27118903e-02 -2.35973805e-01 -4.19161707e-01 -6.65965676e-02
5.20052239e-02 -6.38039231e-01 2.11730197e-01 8.14483941e-01
-4.94858831e-01 1.41633809e+00 -2.02540100e-01 -4.07485396e-01
4.16558720e-02 -7.35495687e-01 -2.77658254e-01 -1.17304027e+00
-3.39607954e-01 5.06685555e-01 7.87575990e-02 -3.32889467e-01
3.58023256e-01 9.90200758e-01 -9.88870621e-01 -1.03666470e-03
1.51682794e+00 3.10322791e-01 3.91617894e-01 2.38238230e-01
-1.05077298e-02 2.66082734e-01 -5.97854614e-01 -1.70196056e-01
-8.07616860e-02 -6.91437185e-01 -4.53747869e-01 -5.09125710e-01
-2.20050886e-01 -3.97005916e-01 5.00584722e-01 7.56861389e-01
3.70463699e-01 5.78288659e-02 1.06227970e+00 -8.81832004e-01
-2.80504972e-01 -1.34061985e-02 -5.47079742e-01 2.33160317e-01
5.03561139e-01 -7.35930726e-02 3.72149795e-01 -7.94527709e-01
7.95857370e-01 9.65676367e-01 3.03388625e-01 5.29299498e-01
-1.00712216e+00 -8.44211102e-01 -5.60823023e-01 5.31594217e-01
-1.53786719e+00 -4.82587516e-02 2.81619906e-01 -4.08103466e-01
1.40491235e+00 1.53008491e-01 8.63505781e-01 5.67060709e-01
8.91056418e-01 7.53560141e-02 9.79357481e-01 -8.96639004e-02
3.97422791e-01 1.59517266e-02 -9.13137849e-03 5.43132067e-01
8.03965449e-01 1.39304781e-02 -1.24019377e-01 -4.91895407e-01
3.05011064e-01 2.43773401e-01 -3.56908411e-01 -1.93471283e-01
-4.17434752e-01 1.20990348e+00 5.72771251e-01 5.75192213e-01
-5.46395838e-01 -3.90151143e-01 3.75321448e-01 -8.99907723e-02
1.72174230e-01 2.71537989e-01 -7.97615826e-01 8.38588029e-02
-2.93987244e-01 1.89127490e-01 6.72793925e-01 -3.43162306e-02
3.24004680e-01 8.04187134e-02 5.37726700e-01 6.12205625e-01
5.73296487e-01 6.62588835e-01 -1.10996682e-02 -1.35393441e-01
-2.64792621e-01 5.57035506e-01 1.12517439e-01 -7.83400476e-01
-6.34246707e-01 -1.52067328e-02 -6.91728473e-01 2.87167221e-01
3.07212532e-01 -3.55265051e-01 -7.72135735e-01 1.59041512e+00
7.17114389e-01 1.08351141e-01 2.63208777e-01 7.23988295e-01
8.69056046e-01 9.81762707e-01 6.50107265e-01 -8.47660899e-01
1.64576435e+00 -2.54458070e-01 -7.17438698e-01 8.11252415e-01
3.50438327e-01 -9.16229069e-01 2.84371585e-01 8.50448012e-01
-8.10597301e-01 1.90433100e-01 -1.14388824e+00 5.90424180e-01
-6.70244157e-01 -1.43999115e-01 7.33709514e-01 9.44902718e-01
-5.20270705e-01 6.19074345e-01 -1.05831695e+00 -8.23885024e-01
2.84262091e-01 6.84627593e-01 -5.41571021e-01 -1.69181246e-02
-1.15436769e+00 1.35607660e+00 7.25673735e-01 -1.14406817e-01
-4.27876383e-01 -5.44679582e-01 -5.15320778e-01 -1.31977126e-01
2.08865568e-01 -7.40733862e-01 5.75989008e-01 -4.92213964e-01
-1.41201186e+00 5.95447600e-01 -3.59315157e-01 -4.42052573e-01
-3.78295600e-01 -2.06970870e-02 -6.57513261e-01 4.06630963e-01
-1.44417793e-01 1.76542535e-01 1.95152566e-01 -8.38024914e-01
-3.17063242e-01 -8.20270717e-01 -1.80198655e-01 2.95784837e-03
3.86474073e-01 2.59393901e-01 3.55720818e-01 -7.36032426e-01
4.06708103e-03 -8.60306203e-01 -2.16755837e-01 -5.02396166e-01
-2.19108447e-01 -3.62735450e-01 6.39655888e-01 -6.25395358e-01
9.21411812e-01 -1.27721214e+00 1.14308437e-02 5.86272657e-01
-4.76420857e-02 7.06396759e-01 2.65295297e-01 9.86277163e-01
-6.09696582e-02 3.64183426e-01 1.17195673e-01 9.37129021e-01
-7.10181832e-01 -8.05742145e-02 1.84128076e-01 7.93788731e-01
-5.22059835e-02 3.54823381e-01 -8.65753949e-01 -2.42194742e-01
1.21135727e-01 1.02307141e+00 -3.28443110e-01 -1.67472616e-01
-3.51107389e-01 6.00853980e-01 -9.98249292e-01 8.82807612e-01
1.09555340e+00 1.09022260e-01 3.77276033e-01 -1.06201187e-01
-2.84793764e-01 1.70778155e-01 -7.02628911e-01 1.23131156e+00
2.41604477e-01 8.93367603e-02 -3.22940424e-02 -4.73612040e-01
5.61467707e-01 6.51801586e-01 4.24436778e-01 -7.56780624e-01
5.04548907e-01 1.23148680e-01 2.68047124e-01 -3.31440091e-01
9.17399004e-02 -3.86246115e-01 7.41694450e-01 1.28605634e-01
-2.34013274e-01 4.77559000e-01 4.83010858e-01 4.02770132e-01
4.46675211e-01 1.65321454e-01 7.28381693e-01 -5.85836291e-01
7.43962407e-01 2.72907853e-01 4.76803362e-01 -7.86951706e-02
7.03029409e-02 -3.37024182e-01 2.68449098e-01 -4.49784458e-01
-7.60973334e-01 -1.08148217e+00 -7.28137195e-01 5.64162672e-01
-2.99251676e-02 -4.03546244e-01 -7.63311625e-01 -8.94612074e-02
-3.37041616e-01 5.70495605e-01 -4.84042406e-01 3.18446979e-02
-1.82744682e-01 -8.98073554e-01 3.95820558e-01 -3.17877054e-01
5.50481677e-01 -9.38961923e-01 -6.15751386e-01 4.11511689e-01
2.83302158e-01 -3.27936739e-01 8.46080706e-02 3.55284549e-02
-9.90288138e-01 -1.46159041e+00 -6.25681043e-01 -5.23102582e-01
3.44800502e-01 1.01906694e-01 3.87504846e-01 2.24921033e-01
-3.52406085e-01 -4.47312444e-01 -4.59766477e-01 -8.14634025e-01
-4.46071506e-01 -2.01622054e-01 2.77294487e-01 -7.02567041e-01
5.75067580e-01 -6.43127441e-01 -1.00840640e+00 8.32833126e-02
-6.91999257e-01 -2.36127108e-01 2.57151067e-01 4.36424732e-01
3.31591308e-01 1.38271973e-01 8.39723647e-01 -1.16757882e+00
5.64852238e-01 -7.87562907e-01 -7.61472762e-01 1.17753699e-01
-5.25537789e-01 -1.30755782e-01 5.27738273e-01 -1.75636351e-01
-8.96794319e-01 -2.07174346e-01 -3.86999220e-01 3.74852389e-01
-1.02114372e-01 6.61298990e-01 -4.17520732e-01 -1.28584862e-01
4.56120759e-01 -2.47851461e-02 2.17539191e-01 -5.17622769e-01
-2.42350876e-01 4.66718078e-01 -3.22992131e-02 -2.96932399e-01
4.17046696e-01 3.63264084e-01 4.55618829e-01 -1.36919522e+00
-2.01376811e-01 -5.23491085e-01 -9.75315794e-02 5.77169657e-02
1.43787229e+00 -5.60812473e-01 -1.69136202e+00 2.66897410e-01
-1.09037745e+00 2.60957003e-01 1.09945059e+00 7.11189330e-01
5.04999757e-02 3.80191147e-01 -5.53606212e-01 -7.63983667e-01
-1.10005975e+00 -8.72492075e-01 7.12255985e-02 5.87533653e-01
-1.69208005e-01 -8.26583683e-01 7.10770249e-01 2.40587085e-01
3.58012825e-01 8.41152430e-01 1.45842445e+00 -7.65955865e-01
-3.22073102e-01 9.46329981e-02 7.88492858e-02 -1.31304607e-01
3.77267957e-01 2.85173118e-01 -5.42305231e-01 -2.89004803e-01
-1.66243568e-01 -2.48259678e-02 4.50274318e-01 5.19410551e-01
2.30961397e-01 -2.64703453e-01 -5.43106377e-01 4.30889010e-01
1.81872272e+00 1.31329679e+00 8.77624214e-01 3.29108357e-01
4.12493557e-01 4.23970342e-01 8.36706460e-01 5.59288323e-01
-1.82916790e-01 5.76965630e-01 4.71122026e-01 2.22784579e-02
5.88159084e-01 3.47498134e-02 8.88083056e-02 7.50540793e-02
-6.91081822e-01 -4.19809341e-01 -7.57134974e-01 1.57114342e-02
-1.25523293e+00 -1.29219544e+00 -6.64481878e-01 2.52269292e+00
7.81126320e-01 -3.72297883e-01 2.73219049e-01 -9.35155824e-02
2.24894002e-01 -6.79939210e-01 -4.60067749e-01 -8.10870409e-01
-5.33850193e-02 9.18208301e-01 4.76597577e-01 4.67976063e-01
-7.76806593e-01 8.78193140e-01 5.49092627e+00 6.96526170e-01
-1.29832661e+00 -2.30266020e-01 2.06596464e-01 1.22772723e-01
7.80080706e-02 3.10698420e-01 -5.42033672e-01 4.10158277e-01
9.26574886e-01 -2.69734919e-01 2.39870504e-01 2.57299840e-01
6.07199192e-01 -8.24569106e-01 -4.93376762e-01 7.34079182e-01
-3.39341998e-01 -1.44999123e+00 1.13644607e-01 4.10016060e-01
5.03983140e-01 -7.26241991e-02 -3.65888685e-01 -2.64044017e-01
-1.78993925e-01 -1.16664803e+00 -1.48249149e-01 2.70867378e-01
2.63042271e-01 -1.62218928e+00 6.72826290e-01 3.50886554e-01
-1.01787710e+00 6.04402900e-01 -4.86546278e-01 1.96133927e-01
1.46833852e-01 2.17404246e-01 -1.06110239e+00 3.69549692e-01
3.75225127e-01 2.89984047e-01 -2.10031494e-01 1.17850232e+00
-1.28447503e-01 2.94219702e-01 -3.02666008e-01 -2.37895414e-01
2.20169529e-01 -1.01918018e+00 3.82810920e-01 5.91693103e-01
5.49495146e-02 6.60614729e-01 4.20181826e-02 3.66910785e-01
3.28495741e-01 8.45308900e-01 -6.26010895e-01 -2.21336365e-01
8.44453946e-02 8.39510262e-01 -1.10857713e+00 -2.71755904e-01
-2.86189198e-01 7.22849727e-01 -1.50258377e-01 4.06118631e-01
-6.02013648e-01 -3.19594145e-01 1.00682187e+00 2.62086421e-01
2.48352334e-01 9.30681154e-02 3.47731382e-01 -7.13597417e-01
-8.85046721e-01 -8.54187846e-01 6.66954637e-01 -4.67523962e-01
-6.31742656e-01 3.83883476e-01 3.54895592e-01 -6.58142328e-01
-5.74678034e-02 -3.71623963e-01 -5.39065599e-01 1.08700502e+00
-1.03937125e+00 -8.76270533e-01 2.76597261e-01 4.40251142e-01
1.93699002e-01 1.02148004e-01 1.28772676e+00 -1.50344327e-01
-6.30421758e-01 -3.30076404e-02 5.89954555e-01 -4.93884444e-01
5.78118861e-01 -8.00607562e-01 -5.75454891e-01 3.40756059e-01
-4.25419748e-01 1.21036017e+00 1.11604905e+00 -1.13382566e+00
-1.23986876e+00 -6.07460499e-01 8.45608175e-01 8.73551890e-02
3.53545159e-01 1.01368912e-01 -8.75341713e-01 2.88421273e-01
7.71586597e-01 -1.05950820e+00 1.35401702e+00 -2.21154511e-01
-5.17047755e-02 4.90033776e-01 -1.65041113e+00 6.93855405e-01
1.39158785e-01 7.46686533e-02 -3.50597620e-01 4.12544817e-01
2.85169810e-01 -1.28644444e-02 -1.13224590e+00 3.41329932e-01
8.17404628e-01 -8.30451727e-01 9.30900097e-01 -7.45606601e-01
-2.28138287e-02 -6.59651279e-01 2.44299486e-01 -1.12816584e+00
-6.15718812e-02 -4.81023669e-01 1.13463931e-01 8.67879570e-01
2.48453617e-01 -8.22873354e-01 6.38825178e-01 3.50553393e-01
4.17321503e-01 -7.72594869e-01 -6.63878381e-01 -4.02634025e-01
9.28298160e-02 3.61362845e-01 3.46498907e-01 6.53984547e-01
1.26864687e-01 8.32403421e-01 -2.20367387e-01 -3.28441188e-02
6.65818751e-01 3.44585851e-02 3.73282701e-01 -1.41691291e+00
-3.36603187e-02 -2.01900583e-02 -2.58797884e-01 -8.55102912e-02
-1.70456812e-01 -6.15233421e-01 -9.60346460e-01 -1.70938790e+00
4.11260188e-01 -4.49914932e-02 1.08430088e-01 2.79019922e-01
1.67802304e-01 1.60953313e-01 7.45456964e-02 -6.17026500e-02
7.58431181e-02 1.45066932e-01 9.54643190e-01 8.28130320e-02
-6.39271259e-01 2.55999148e-01 -6.92699492e-01 6.13331258e-01
1.12125337e+00 -6.53706968e-01 -7.66346931e-01 5.34565926e-01
4.58665401e-01 4.59450893e-02 -3.80624801e-01 -2.16166288e-01
-4.11341041e-01 -6.24538004e-01 5.48395872e-01 -1.10602283e+00
3.92043084e-01 -9.62419391e-01 8.18283737e-01 1.14443433e+00
6.53902292e-01 -2.31342316e-01 2.81052202e-01 1.79047525e-01
3.25444430e-01 -2.68485814e-01 9.72927868e-01 2.08694991e-02
-3.57995212e-01 1.69161916e-01 -1.10724628e+00 -3.73841226e-01
1.20803213e+00 -5.48883736e-01 -2.64465064e-01 -1.95711836e-01
-8.14506352e-01 1.70971021e-01 8.24667275e-01 -1.11562917e-02
5.47697544e-01 -7.71540225e-01 -5.16131341e-01 -7.54016340e-02
1.49972156e-01 -5.81259191e-01 5.17751575e-01 1.07377779e+00
-1.28689051e+00 8.01621974e-01 -7.13503063e-01 -3.20763022e-01
-1.89936948e+00 8.95569026e-01 8.74187425e-02 1.88072808e-02
-2.51282543e-01 3.52087408e-01 1.79302946e-01 4.19115007e-01
-5.51954508e-02 -1.39135972e-01 -8.91079843e-01 1.46346673e-01
8.42243552e-01 5.57919681e-01 1.97071552e-01 -9.93899822e-01
-8.14630806e-01 4.44110572e-01 -1.61148280e-01 5.32118380e-01
1.42181170e+00 2.55093545e-01 -3.95215839e-01 -1.10929355e-03
1.08139074e+00 1.84963286e-01 -4.73875970e-01 4.98240560e-01
-2.82609742e-02 -4.23189640e-01 -1.78834558e-01 -1.15015697e+00
-5.45288205e-01 2.87713975e-01 8.89522195e-01 -2.32763022e-01
1.05514765e+00 -1.43590271e-01 6.49275243e-01 3.53536010e-01
6.30092204e-01 -6.32221520e-01 -5.20177305e-01 3.17807138e-01
7.71540105e-01 -9.65301216e-01 9.73394886e-02 -5.92247367e-01
-4.58967566e-01 8.85765672e-01 2.06573531e-01 -9.73099619e-02
6.25460207e-01 2.78120302e-03 6.05354942e-02 -3.06461185e-01
-7.89561570e-01 -4.22319323e-02 1.42260566e-01 5.94371378e-01
1.07652211e+00 4.31725904e-02 -1.55767143e+00 2.37988874e-01
2.23125607e-01 -6.90229877e-04 4.13038254e-01 1.15455985e+00
-6.25859559e-01 -1.65418458e+00 -5.73016703e-01 3.83756250e-01
-1.00300407e+00 -6.59194663e-02 -6.33559465e-01 1.08260405e+00
2.77980894e-01 1.04021680e+00 -4.15049225e-01 2.74635226e-01
1.31829217e-01 2.15231478e-02 9.32179868e-01 -2.79977143e-01
-8.66639197e-01 6.04690075e-01 5.43603078e-02 -1.92750394e-01
-6.53544128e-01 -2.04018101e-01 -1.94482279e+00 -7.83937335e-01
-3.83660585e-01 7.67618179e-01 1.01425207e+00 8.67587328e-01
2.19168104e-02 -1.19779080e-01 4.78287637e-01 -3.36473525e-01
3.90092820e-01 -9.14979696e-01 -9.51033115e-01 -7.63158733e-03
-1.09777432e-02 -7.01609313e-01 1.53770998e-01 -1.45439535e-01] | [4.664817810058594, 5.107767581939697] |
00b136e8-9d8d-4cc0-bf92-4521f9b2e6d8 | sparse-graph-to-sequence-learning-for-vision | 2007.06077 | null | https://arxiv.org/abs/2007.06077v1 | https://arxiv.org/pdf/2007.06077v1.pdf | Sparse Graph to Sequence Learning for Vision Conditioned Long Textual Sequence Generation | Generating longer textual sequences when conditioned on the visual information is an interesting problem to explore. The challenge here proliferate over the standard vision conditioned sentence-level generation (e.g., image or video captioning) as it requires to produce a brief and coherent story describing the visual content. In this paper, we mask this Vision-to-Sequence as Graph-to-Sequence learning problem and approach it with the Transformer architecture. To be specific, we introduce Sparse Graph-to-Sequence Transformer (SGST) for encoding the graph and decoding a sequence. The encoder aims to directly encode graph-level semantics, while the decoder is used to generate longer sequences. Experiments conducted with the benchmark image paragraph dataset show that our proposed achieve 13.3% improvement on the CIDEr evaluation measure when comparing to the previous state-of-the-art approach. | ['Aditya Mogadala', 'Marius Mosbach', 'Dietrich Klakow'] | 2020-07-12 | null | null | null | null | ['graph-to-sequence'] | ['natural-language-processing'] | [ 9.50991392e-01 3.77281904e-01 8.02076422e-04 -2.30679855e-01
-9.51336801e-01 -5.03439248e-01 1.02425992e+00 -2.11139247e-01
-2.16404963e-02 8.68886411e-01 6.24842465e-01 -2.38900587e-01
7.79767454e-01 -6.11854017e-01 -1.17006874e+00 -5.59469104e-01
2.31539890e-01 2.74447203e-01 -2.29944848e-02 -2.94230670e-01
3.00929397e-01 1.49773620e-02 -1.33520460e+00 9.15680885e-01
7.17692435e-01 8.90497684e-01 8.36886525e-01 9.05590475e-01
-2.67487943e-01 1.35097039e+00 -6.45220220e-01 -7.17226446e-01
-4.90257889e-02 -1.08403301e+00 -7.46914744e-01 5.34738481e-01
7.03258276e-01 -4.82941896e-01 -3.92381817e-01 1.02282321e+00
2.88431674e-01 -1.89893112e-01 8.12361419e-01 -1.35767376e+00
-1.03737330e+00 7.34482169e-01 -5.84965765e-01 -2.20327616e-01
8.15562785e-01 5.03390253e-01 1.10478199e+00 -9.44696724e-01
1.20319963e+00 1.32637966e+00 7.77699128e-02 7.65300155e-01
-1.22390604e+00 -2.53396541e-01 1.82560191e-01 5.35343230e-01
-1.20822179e+00 -4.64996606e-01 7.87659943e-01 -6.31745040e-01
8.98732483e-01 2.09296480e-01 7.73697436e-01 1.70415068e+00
2.05361679e-01 9.79461849e-01 9.36639547e-01 -5.00968575e-01
1.53642625e-01 -1.78798318e-01 -3.71906579e-01 7.18951523e-01
2.55109161e-01 1.22508474e-01 -6.20319784e-01 3.12049896e-01
7.27949321e-01 -4.54667538e-01 -4.81670171e-01 -3.71697783e-01
-1.29938543e+00 9.14482892e-01 3.68595243e-01 7.29814917e-02
-5.38599312e-01 5.06248116e-01 4.53008115e-01 1.12990700e-01
2.68161595e-01 3.06856960e-01 3.83753896e-01 -8.50775540e-02
-1.23027468e+00 4.23134893e-01 6.55440569e-01 1.41447663e+00
5.56140423e-01 5.51189125e-01 -8.22368503e-01 4.81218278e-01
2.83277392e-01 4.84521806e-01 1.20589420e-01 -8.57122302e-01
8.24109137e-01 1.38796076e-01 -1.08409356e-02 -8.60644996e-01
2.76342839e-01 -3.19296658e-01 -1.00738156e+00 5.23798056e-02
1.17802687e-01 -4.05989364e-02 -1.20603681e+00 1.59852016e+00
-2.36366630e-01 3.43949646e-01 2.16944754e-01 1.05133629e+00
1.05699098e+00 1.09841597e+00 7.38105923e-02 -3.37976336e-01
1.27402234e+00 -1.24233031e+00 -8.38511825e-01 -6.05421126e-01
3.88927251e-01 -6.95998549e-01 1.14512539e+00 1.94394708e-01
-1.30226362e+00 -6.65924549e-01 -1.18943095e+00 -1.08258873e-01
-4.74245586e-02 1.05156519e-01 7.85316303e-02 3.32509249e-01
-1.38484633e+00 2.49560088e-01 -3.22853297e-01 -2.92295963e-01
3.77914697e-01 -2.60845453e-01 -3.25880438e-01 -3.48579526e-01
-1.24372983e+00 7.95853615e-01 7.66659439e-01 -1.16568491e-01
-1.43205249e+00 -3.98232728e-01 -1.27310634e+00 4.00651991e-02
3.55481595e-01 -1.26050544e+00 1.25143194e+00 -1.06501901e+00
-1.37573385e+00 8.92957687e-01 -2.24953964e-01 -8.65347683e-01
6.85999393e-01 1.15753673e-02 9.09919664e-02 4.65716749e-01
1.66561350e-01 1.22939241e+00 1.21700597e+00 -1.54887426e+00
-2.63123572e-01 2.33875751e-01 7.51135722e-02 3.73867154e-01
9.88080949e-02 -1.71392765e-02 -7.47712076e-01 -8.72209191e-01
-5.72902262e-01 -9.11032319e-01 -2.62620181e-01 -2.16137201e-01
-5.90848267e-01 6.23613000e-02 7.20566690e-01 -1.01182592e+00
9.80863392e-01 -1.94025993e+00 4.22114223e-01 -2.04678595e-01
9.85061899e-02 8.59206691e-02 -5.11121571e-01 8.98803174e-01
-2.04499394e-01 7.53692314e-02 -4.43090409e-01 -4.60867882e-01
-2.26837303e-02 3.20034996e-02 -4.19615984e-01 1.88070938e-01
4.88958955e-01 1.39946318e+00 -1.08067262e+00 -7.10587859e-01
2.89901704e-01 4.71803069e-01 -5.04947901e-01 5.29762506e-01
-7.64965713e-01 5.85837901e-01 -2.03033641e-01 3.17289621e-01
4.91982549e-01 -5.28813660e-01 1.86609685e-01 -4.20709193e-01
1.56314075e-01 1.82178039e-02 -4.49974775e-01 2.20329046e+00
-2.69229889e-01 8.56403768e-01 -2.76607782e-01 -1.06669116e+00
7.41405725e-01 3.85611176e-01 3.19987275e-02 -8.02001059e-01
-5.05100451e-02 -5.02340160e-02 -2.36406967e-01 -4.58451718e-01
6.99740827e-01 -7.29561076e-02 -2.08235815e-01 2.39778012e-02
1.66031897e-01 -3.90519768e-01 4.97268856e-01 7.20632374e-01
8.82358432e-01 5.76609015e-01 3.15342724e-01 1.36058748e-01
6.67813241e-01 9.28322226e-02 -1.58246160e-02 6.69772506e-01
3.00875247e-01 1.00411046e+00 6.68684065e-01 9.87891257e-02
-1.46856320e+00 -1.17423606e+00 7.41273046e-01 5.16954064e-01
1.86171718e-02 -5.57236135e-01 -1.02461493e+00 -7.31320083e-01
-5.29489279e-01 1.18126595e+00 -4.39752996e-01 -7.40752891e-02
-6.10482574e-01 -1.02909304e-01 3.69694412e-01 4.21394974e-01
4.58298862e-01 -1.27162802e+00 -4.01702166e-01 1.83403954e-01
-6.98758602e-01 -1.70115674e+00 -8.05018783e-01 -4.88933444e-01
-3.91307861e-01 -5.69619119e-01 -1.15773785e+00 -9.43316579e-01
6.40499353e-01 8.61949846e-02 1.46063495e+00 -1.03387058e-01
-2.58778453e-01 3.94755453e-01 -6.49560571e-01 -2.12341264e-01
-8.54015112e-01 -2.27533668e-01 -6.59863949e-01 2.45276004e-01
-4.52558488e-01 -3.10955077e-01 -7.35752940e-01 -3.01861167e-01
-1.04431307e+00 8.63127351e-01 8.63184333e-01 7.85546839e-01
6.34436786e-01 -5.69382071e-01 5.03854573e-01 -8.45881164e-01
6.44904852e-01 -2.99627841e-01 -4.89455223e-01 4.08746392e-01
-2.67471910e-01 2.17498451e-01 7.02684224e-01 -1.90185681e-01
-1.06832933e+00 3.05302978e-01 -8.22064653e-02 -6.29851043e-01
-6.74518794e-02 5.21096587e-01 -1.78673908e-01 2.82513976e-01
4.20740426e-01 8.99387062e-01 -8.98602009e-02 -9.70249623e-03
9.52432215e-01 4.66591716e-01 7.78788745e-01 -3.92964929e-01
8.42891276e-01 2.98627734e-01 1.06082752e-01 -8.67698669e-01
-7.22136915e-01 -1.73504069e-01 -3.08225662e-01 -5.85683167e-01
1.37294602e+00 -1.14495003e+00 -2.51684785e-01 2.45830208e-01
-1.67274320e+00 -4.29145634e-01 -2.47206628e-01 1.07083730e-02
-1.13264310e+00 5.41588843e-01 -4.95215654e-01 -6.98547006e-01
-5.25936902e-01 -1.19984591e+00 1.43288410e+00 -1.42677233e-01
-1.62206843e-01 -8.84812295e-01 -1.43550649e-01 4.97705042e-01
1.40568092e-01 6.62896872e-01 6.52435064e-01 -6.79921508e-02
-1.09490299e+00 2.68571973e-01 -5.21377385e-01 3.49385470e-01
-2.01151580e-01 -3.60118598e-01 -7.64804900e-01 -4.16328877e-01
-1.23338304e-01 -5.43998480e-01 9.64599669e-01 2.31298342e-01
1.31954181e+00 -6.26683831e-01 -1.24370731e-01 4.91747528e-01
1.65210807e+00 1.06075443e-01 1.13287091e+00 3.88252661e-02
1.14999247e+00 5.89311540e-01 6.24699533e-01 3.38772088e-01
4.04829532e-01 8.07853639e-01 5.95223904e-01 -1.14299051e-01
-9.29654717e-01 -8.20737123e-01 6.69110894e-01 8.17754805e-01
1.81815803e-01 -7.94756472e-01 -5.96392155e-01 6.40140474e-01
-1.87506521e+00 -1.14305520e+00 -2.94552833e-01 1.70840204e+00
7.71928608e-01 -4.99725454e-02 6.29697219e-02 -9.65116024e-02
7.36014426e-01 5.87684631e-01 -1.73463851e-01 -5.11739016e-01
-2.18009800e-01 -5.26955687e-02 4.14999217e-01 5.83631814e-01
-6.53854787e-01 1.13623679e+00 5.72418356e+00 1.10625100e+00
-1.11586833e+00 5.35009801e-03 7.41158485e-01 1.94036856e-01
-4.07521039e-01 4.03875746e-02 -4.99194264e-01 4.67073828e-01
9.61355269e-01 -3.04368436e-01 4.32813346e-01 4.61540133e-01
4.38942999e-01 6.54150546e-02 -1.23740172e+00 1.30384338e+00
6.54437721e-01 -1.74917221e+00 8.40667784e-01 -1.51795605e-02
8.99357080e-01 -3.40019614e-01 1.24568995e-02 1.14527375e-01
1.15129627e-01 -1.24873865e+00 1.29040945e+00 6.40734375e-01
1.31859255e+00 -4.28086281e-01 4.16091830e-01 2.37082005e-01
-1.20445168e+00 4.60296541e-01 -1.69221640e-01 1.04235724e-01
7.39928424e-01 4.80979562e-01 -1.17270207e+00 9.12135661e-01
1.90891922e-01 9.37616169e-01 -5.57983041e-01 8.69714737e-01
-5.16896725e-01 6.71123505e-01 4.11158890e-01 -8.66645202e-02
5.73742926e-01 -1.53057933e-01 6.62049770e-01 1.48148358e+00
5.25401890e-01 -1.16577335e-01 3.36381346e-01 1.09895825e+00
-2.41003126e-01 1.14647999e-01 -1.04725111e+00 -3.80933315e-01
-7.91082904e-02 1.04171979e+00 -5.96478283e-01 -6.85659051e-01
-4.79883164e-01 1.68428028e+00 2.29682773e-01 5.80968559e-01
-9.15898800e-01 -1.74709603e-01 7.32967257e-02 2.23416641e-01
7.46903241e-01 -2.45462000e-01 -1.72182977e-01 -1.15635419e+00
1.18046291e-01 -1.00573134e+00 1.54663816e-01 -1.38882899e+00
-1.06637311e+00 6.84605122e-01 1.28459781e-01 -1.37111568e+00
-7.53535450e-01 -4.25140351e-01 -4.99567330e-01 8.32667530e-01
-1.51898384e+00 -1.43630981e+00 -4.34546024e-01 5.89426696e-01
1.03139043e+00 -9.09896195e-02 4.56844717e-01 -5.26372157e-02
1.38594523e-01 4.83406067e-01 -2.92024016e-01 1.99480206e-01
3.05188745e-01 -1.05451202e+00 7.94649124e-01 1.14037633e+00
4.56623554e-01 -3.15815769e-02 9.93217707e-01 -8.69926393e-01
-1.53710747e+00 -1.46456230e+00 9.86950755e-01 -2.85913944e-01
5.42854369e-01 -7.61965454e-01 -5.31590402e-01 5.37147701e-01
9.15756404e-01 -2.83978909e-01 1.18449025e-01 -1.00714934e+00
-3.59631687e-01 2.83232599e-01 -8.26775730e-01 9.45629418e-01
1.33992290e+00 -4.90264714e-01 -4.56265956e-01 3.26676011e-01
1.08405411e+00 -4.36242938e-01 -4.08478647e-01 2.24318385e-01
1.82649150e-01 -8.49916816e-01 9.98298049e-01 -2.98299909e-01
1.11839807e+00 -4.38670933e-01 -1.61526144e-01 -1.43500257e+00
-2.82188863e-01 -9.71680284e-01 -2.43171658e-02 1.10418689e+00
4.80479717e-01 5.46213612e-03 6.89716697e-01 -2.12634861e-01
-3.47435176e-01 -5.00390530e-01 -5.52954555e-01 -9.60194886e-01
-2.11788327e-01 -3.41989815e-01 2.64197201e-01 6.21676743e-01
-1.62048936e-01 9.02282536e-01 -9.10437226e-01 -1.15186326e-01
8.94593537e-01 1.81034818e-01 8.08986068e-01 -3.93931776e-01
-4.20479447e-01 -3.60420108e-01 -4.06810552e-01 -1.32963264e+00
1.89944610e-01 -1.19748378e+00 3.22502226e-01 -2.24268699e+00
3.55241150e-01 4.40152526e-01 3.07191342e-01 7.94544220e-02
-2.33483121e-01 3.23987752e-01 6.98414564e-01 -1.86211199e-01
-8.45047891e-01 8.51873577e-01 1.74838448e+00 -4.89720583e-01
3.51020843e-01 -6.54902577e-01 -6.26502931e-01 1.01015575e-01
5.03157437e-01 -1.44992828e-01 -7.72675455e-01 -4.82021362e-01
5.30801862e-02 6.47748947e-01 5.29188633e-01 -8.74976873e-01
-2.34392043e-02 -2.00560778e-01 2.00643480e-01 -7.33871043e-01
5.86234987e-01 -4.02693212e-01 2.25455880e-01 5.55032253e-01
-5.35263002e-01 1.59831151e-01 -1.14933131e-02 6.39023721e-01
-3.97600234e-01 -8.06327686e-02 5.36164224e-01 -3.29482466e-01
-8.63223374e-01 2.86808491e-01 -3.30053926e-01 3.26046616e-01
1.08103704e+00 -2.19550282e-01 -4.24130410e-01 -1.05718923e+00
-5.39003968e-01 1.09227046e-01 4.98951703e-01 6.29712939e-01
1.21060050e+00 -1.49403119e+00 -1.44395018e+00 -5.02716824e-02
4.35620278e-01 -2.99144149e-01 1.99157357e-01 4.05421287e-01
-6.25823736e-01 6.42917871e-01 -2.52812535e-01 -7.73396611e-01
-1.31553757e+00 7.83433259e-01 -7.99206793e-02 -3.88049245e-01
-6.63557529e-01 7.30268717e-01 6.65453136e-01 3.78270298e-01
9.14868414e-02 -1.65494815e-01 -1.97725117e-01 -1.51648402e-01
5.13835311e-01 -9.86097381e-02 -2.66268075e-01 -8.66901338e-01
-1.37089729e-01 3.13350797e-01 -7.55276158e-02 -5.56773067e-01
1.04217494e+00 -1.33021161e-01 3.12137045e-03 3.62617522e-01
1.18745816e+00 -4.21176821e-01 -1.21068275e+00 1.08621068e-01
-9.99155790e-02 -3.77681196e-01 -3.03301245e-01 -7.76141047e-01
-8.64960611e-01 8.75106096e-01 2.65372664e-01 3.26384120e-02
9.35486376e-01 1.41778946e-01 9.29233611e-01 -1.02717550e-02
2.79626459e-01 -6.14906311e-01 4.59992468e-01 5.11991501e-01
1.57250631e+00 -9.07598913e-01 -1.87614262e-01 -5.84086895e-01
-1.09270561e+00 8.22875738e-01 5.29502690e-01 -2.66597867e-01
-1.49689075e-02 -2.26506796e-02 -2.02778965e-01 -9.38363448e-02
-1.04036462e+00 -2.87764221e-01 6.00490510e-01 8.27080905e-01
4.56092358e-01 3.70701812e-02 -4.34102684e-01 6.10343600e-03
-3.59805018e-01 3.01465597e-02 7.71839261e-01 6.05644941e-01
-1.20559394e-01 -1.06452072e+00 -2.58827001e-01 2.64300168e-01
-2.26365522e-01 -5.35390735e-01 -5.88273764e-01 3.95930678e-01
-1.52823657e-01 1.00878012e+00 -9.57566649e-02 -1.91027984e-01
1.38973132e-01 -6.95029870e-02 8.18808019e-01 -8.52185845e-01
-2.74752080e-01 1.68971792e-01 5.08697867e-01 -7.34266877e-01
-5.29611588e-01 -6.01794124e-01 -1.12551367e+00 1.15669578e-01
1.99042052e-01 -7.18520731e-02 6.54329658e-01 7.92040586e-01
1.99360684e-01 7.53390789e-01 3.23354334e-01 -8.92112553e-01
-2.39386827e-01 -8.49157333e-01 -6.56322092e-02 7.45314658e-01
4.60213661e-01 -1.70239270e-01 5.25221415e-03 6.36706293e-01] | [11.203448295593262, 0.6955252289772034] |
cd1cf891-60cd-4bf6-886c-5ab0da4964c1 | deep-learning-for-brain-age-estimation-a | 2212.03868 | null | https://arxiv.org/abs/2212.03868v1 | https://arxiv.org/pdf/2212.03868v1.pdf | Deep Learning for Brain Age Estimation: A Systematic Review | Over the years, Machine Learning models have been successfully employed on neuroimaging data for accurately predicting brain age. Deviations from the healthy brain aging pattern are associated to the accelerated brain aging and brain abnormalities. Hence, efficient and accurate diagnosis techniques are required for eliciting accurate brain age estimations. Several contributions have been reported in the past for this purpose, resorting to different data-driven modeling methods. Recently, deep neural networks (also referred to as deep learning) have become prevalent in manifold neuroimaging studies, including brain age estimation. In this review, we offer a comprehensive analysis of the literature related to the adoption of deep learning for brain age estimation with neuroimaging data. We detail and analyze different deep learning architectures used for this application, pausing at research works published to date quantitatively exploring their application. We also examine different brain age estimation frameworks, comparatively exposing their advantages and weaknesses. Finally, the review concludes with an outlook towards future directions that should be followed by prospective studies. The ultimate goal of this paper is to establish a common and informed reference for newcomers and experienced researchers willing to approach brain age estimation by using deep learning models | ['Chin-Teng Lin', 'Javier Del Ser', 'Yu-Dong Zhang', 'Kaizhu Huang', 'Kuan-Ting Lai', 'Nehal Ahmad', 'Tripti Goel', 'Iman Beheshti', 'M. A. Ganaie', 'M. Tanveer'] | 2022-12-07 | null | null | null | null | ['age-estimation', 'age-estimation'] | ['computer-vision', 'miscellaneous'] | [-1.81194112e-01 3.45164016e-02 -3.12548161e-01 -6.72814071e-01
-9.29313246e-03 2.85207927e-01 3.95111769e-01 3.50718141e-01
-8.36120188e-01 8.23579252e-01 1.32266521e-01 -1.03737928e-01
-1.21148214e-01 -5.51993787e-01 -1.65336743e-01 -6.84623182e-01
-5.12555599e-01 5.36227882e-01 -3.58925253e-01 2.22008079e-01
5.08776248e-01 4.28459674e-01 -1.75550210e+00 -3.81422222e-01
1.43515337e+00 9.95003521e-01 6.82890192e-02 5.02876341e-01
-6.95333853e-02 5.74586928e-01 -4.22917515e-01 -6.31502092e-01
-2.12843210e-01 -7.76973963e-02 -7.92826355e-01 -1.93681538e-01
5.93417943e-01 -6.91417575e-01 -2.16469705e-01 7.23293841e-01
9.10073876e-01 -1.37545288e-01 1.12762856e+00 -1.31388485e+00
-9.55668271e-01 6.23110235e-01 -5.56961238e-01 7.31415212e-01
1.09476678e-01 -2.84602828e-02 4.55821842e-01 -9.22342718e-01
3.16302590e-02 8.97989511e-01 7.17801154e-01 1.03997386e+00
-5.66217661e-01 -8.38717699e-01 1.55128732e-01 9.04814661e-01
-1.03626108e+00 -4.87441957e-01 7.36163616e-01 -7.58168578e-01
7.92887151e-01 -2.63863087e-01 1.17142773e+00 1.29033363e+00
7.28115499e-01 6.19881451e-01 1.41030896e+00 -3.18932414e-01
3.10627878e-01 -3.55417997e-01 5.43340087e-01 7.03175902e-01
6.75585687e-01 1.06308341e-01 -6.16827965e-01 1.38207123e-01
5.26475012e-01 -2.59235710e-01 2.76918501e-01 -3.67082596e-01
-9.24604475e-01 6.73696518e-01 3.44242752e-01 5.95406771e-01
-7.57777214e-01 3.04806903e-02 6.47779524e-01 2.52700508e-01
8.65105569e-01 7.73366690e-02 -4.65474516e-01 -2.71764416e-02
-1.14083290e+00 4.79049832e-01 3.45409542e-01 3.62186491e-01
1.23226270e-01 4.43275601e-01 1.72206536e-01 9.55443442e-01
4.25976902e-01 4.75344300e-01 8.22209179e-01 -9.03066695e-01
-9.36782956e-02 2.54738867e-01 -3.87556225e-01 -6.26043141e-01
-9.63386655e-01 -3.94231915e-01 -1.01949286e+00 4.04224843e-01
7.08554089e-01 -2.03570187e-01 -8.37958157e-01 1.65958202e+00
1.93269655e-01 2.16954127e-02 -3.02317113e-01 5.66227853e-01
9.01540101e-01 -7.88140297e-03 8.55921090e-01 -1.80221185e-01
1.92407882e+00 -6.82057977e-01 -6.42294943e-01 -3.82324755e-01
5.22621572e-01 -2.07218274e-01 5.66019475e-01 5.61865449e-01
-1.37404490e+00 -4.77140576e-01 -1.00749338e+00 -2.61155516e-01
-5.51124275e-01 9.69138220e-02 9.90751088e-01 1.16305149e+00
-1.27950740e+00 5.04472017e-01 -1.24441457e+00 -7.42182732e-01
8.37229967e-01 4.47966248e-01 -4.40597355e-01 8.78844559e-02
-1.21044755e+00 1.50729454e+00 2.98907876e-01 7.76097849e-02
-8.44274044e-01 -1.08971095e+00 -7.51685679e-01 -3.15507144e-01
-3.85143906e-01 -1.29836667e+00 1.22263587e+00 -8.36043775e-01
-1.02408350e+00 1.55682480e+00 -6.54951930e-02 -9.26612675e-01
3.88330698e-01 -5.06580472e-01 -5.42220414e-01 2.10061610e-01
-9.57204700e-02 8.78235519e-01 7.44139671e-01 -5.73486328e-01
-4.67429876e-01 -1.06222069e+00 -2.54528373e-01 -8.46678987e-02
-6.36019111e-01 5.05502224e-01 5.32558441e-01 -5.10551989e-01
2.50993297e-02 -4.62877065e-01 -6.83229566e-02 2.69863755e-01
2.71914154e-01 -5.92315495e-01 4.86035645e-01 -1.31010389e+00
1.29430342e+00 -1.28416657e+00 1.39374003e-01 -2.87618548e-01
9.74922538e-01 1.78393349e-01 2.12296516e-01 1.18562996e-01
-3.89680922e-01 -1.40803844e-01 -1.90659061e-01 -3.99646401e-01
-1.02232374e-01 -5.89485280e-02 3.04959983e-01 8.50092053e-01
-4.86719087e-02 8.81428540e-01 -7.74393976e-01 -6.37208998e-01
1.95798218e-01 5.03041565e-01 -1.82389364e-01 1.44584358e-01
5.04003108e-01 4.84677792e-01 -2.04008147e-01 8.92887235e-01
7.18104661e-01 1.97331175e-01 -2.61896342e-01 -9.82494187e-03
-3.40785265e-01 -1.49195969e-01 -2.21623644e-01 1.45394397e+00
-3.49008113e-01 4.77622598e-01 -3.05681136e-02 -1.31281519e+00
1.08511031e+00 2.93534309e-01 5.54183125e-01 -7.79387772e-01
5.69463432e-01 5.64449668e-01 4.43935126e-01 -5.63899517e-01
-3.59339789e-02 -2.29119495e-01 3.48706722e-01 4.14362669e-01
3.78455788e-01 1.71401381e-01 2.33500570e-01 -1.77573189e-01
7.10868299e-01 -8.01185668e-02 6.20099843e-01 -4.69279647e-01
1.07489371e+00 -7.63625503e-01 4.28233296e-01 3.01140219e-01
-1.05464613e+00 7.14000091e-02 4.58182037e-01 -9.19625938e-01
-1.35482502e+00 -1.00281322e+00 -4.14031774e-01 9.84550774e-01
-7.92437434e-01 2.18004733e-02 -1.26239371e+00 -4.02910829e-01
-1.33397102e-01 4.76661414e-01 -1.02630055e+00 -2.77710855e-01
-4.40307319e-01 -1.13902831e+00 5.84784925e-01 9.05888021e-01
6.82903349e-01 -1.04323220e+00 -8.12309027e-01 -5.99006042e-02
7.36105293e-02 -7.71066129e-01 2.55506337e-01 -1.34600475e-01
-1.40466416e+00 -1.07392859e+00 -1.57691324e+00 -8.43176126e-01
7.44422615e-01 -3.60422581e-01 1.14304364e+00 3.33399802e-01
-3.92968982e-01 5.61790049e-01 -1.88313663e-01 -8.63151431e-01
-2.84631312e-01 6.42666817e-01 7.26040304e-01 -4.44011837e-01
8.28044295e-01 -1.02447212e+00 -1.01231086e+00 -1.59817085e-01
-4.60663438e-01 -1.72560796e-01 8.22065711e-01 6.84451878e-01
-7.68680647e-02 -5.36441267e-01 1.27701473e+00 -3.95535827e-01
5.37769556e-01 -5.84415019e-01 -2.17265353e-01 2.28591412e-02
-1.21900415e+00 -1.37957498e-01 3.69811915e-02 -2.04895318e-01
-1.00297534e+00 -4.59852725e-01 -5.42340457e-01 1.72224149e-01
-3.68185163e-01 4.06952232e-01 8.23860988e-03 -2.01523885e-01
5.54581523e-01 9.78375226e-02 4.81213659e-01 -5.60978293e-01
7.48904422e-02 6.25006497e-01 5.79377174e-01 -6.69669569e-01
4.50678587e-01 2.51198739e-01 7.41326734e-02 -9.23773587e-01
-6.43652320e-01 4.64118719e-02 -1.05556893e+00 -7.37301767e-01
1.08219290e+00 -7.47150719e-01 -3.16704243e-01 1.52979195e+00
-8.38991344e-01 -3.28135818e-01 3.27229351e-01 6.76257670e-01
-6.64698362e-01 5.81601977e-01 -7.50807643e-01 -8.68091762e-01
-1.13727510e+00 -8.55285823e-01 5.38017869e-01 5.21934986e-01
-4.79058892e-01 -1.35673583e+00 1.65271923e-01 5.31689107e-01
5.91477931e-01 2.06848413e-01 1.13362646e+00 -6.05443001e-01
2.57118911e-01 -3.22551131e-01 -2.20640630e-01 3.60566825e-01
-1.70543134e-01 6.90715015e-02 -1.01849461e+00 -2.01803967e-01
3.84662002e-02 -2.98330188e-01 6.75446749e-01 9.16163743e-01
1.24623430e+00 2.43810445e-01 -2.10562915e-01 3.17828715e-01
9.13444698e-01 3.13920349e-01 7.36003935e-01 5.99746108e-01
4.65206057e-01 9.40702021e-01 3.06917012e-01 3.94164473e-01
7.01358616e-01 1.07665256e-01 2.82636613e-01 1.50695071e-02
-1.55386850e-01 3.54282349e-01 7.18762130e-02 1.03684032e+00
-6.93605959e-01 4.01964068e-01 -1.24990511e+00 5.78035057e-01
-1.14263737e+00 -7.85294116e-01 -2.36873895e-01 2.10870719e+00
4.78118181e-01 1.13211475e-01 5.32971144e-01 3.27502847e-01
7.93485105e-01 1.69617921e-01 -7.40898728e-01 -6.26884162e-01
-6.19888492e-02 3.50174934e-01 2.36560777e-01 -8.73756967e-03
-9.82504725e-01 4.91002589e-01 7.50900698e+00 1.59483269e-01
-1.11877537e+00 2.77799517e-01 8.84085953e-01 1.26235425e-01
1.25763908e-01 -4.80101615e-01 -4.00832951e-01 4.05363560e-01
1.31200767e+00 -4.79755223e-01 1.12471700e-01 8.26615155e-01
3.38583708e-01 -1.76207304e-01 -8.88318300e-01 9.88553464e-01
2.44564191e-01 -7.53638387e-01 -2.76195675e-01 2.09423020e-01
4.18757379e-01 -2.63003074e-02 3.74473989e-01 2.92590976e-01
-5.22709310e-01 -9.45329368e-01 5.91359317e-01 9.08161879e-01
7.51852393e-01 -8.14812779e-01 8.42284381e-01 -1.60163045e-02
-9.39846575e-01 -3.90262783e-01 -3.59526038e-01 -5.39578438e-01
1.14034034e-01 9.24184978e-01 -3.24710280e-01 2.68199503e-01
8.44717085e-01 7.01976061e-01 -8.98195267e-01 1.34156930e+00
-2.06791043e-01 3.10214311e-01 2.90634453e-01 1.15005493e-01
-1.55000478e-01 -2.19040930e-01 9.72334072e-02 7.27946758e-01
5.43302178e-01 -1.37383759e-01 -5.39410114e-01 7.68977702e-01
2.78281271e-01 3.96570027e-01 -3.12163979e-01 -2.74575830e-01
3.10020745e-01 1.29351449e+00 -7.48041511e-01 -2.26880237e-01
-7.47908175e-01 6.07270777e-01 3.50498855e-01 -5.25094680e-02
-5.94630957e-01 -2.09032774e-01 7.82118201e-01 2.31394932e-01
-5.17506540e-01 -4.25665438e-01 -7.04949796e-01 -8.99122715e-01
-3.35821122e-01 -6.07441723e-01 4.84887570e-01 -8.38023126e-01
-1.55055416e+00 2.96257168e-01 2.88235486e-01 -4.39636230e-01
-2.33709857e-01 -8.30552578e-01 -7.78498113e-01 9.13864493e-01
-1.30494916e+00 -1.30773354e+00 -2.66736776e-01 1.24302082e-01
5.05171180e-01 -3.42216939e-01 7.92397797e-01 4.57807004e-01
-8.38633776e-01 4.31605011e-01 -2.59617567e-01 2.71054711e-02
7.61149168e-01 -1.42033339e+00 4.72170413e-01 7.71262705e-01
-7.30023980e-01 6.38649940e-01 5.88636518e-01 -6.88868940e-01
-7.75745869e-01 -5.94794035e-01 1.33398438e+00 -3.45714003e-01
7.71426737e-01 -3.48768272e-02 -8.72787952e-01 5.98877549e-01
3.25204402e-01 -4.47665393e-01 9.61194277e-01 3.30520451e-01
-1.87583759e-01 -2.25459903e-01 -1.33604574e+00 6.53205812e-01
1.05165565e+00 -2.53810048e-01 -8.42751324e-01 -1.54006556e-01
9.75190550e-02 -3.09777241e-02 -1.24671006e+00 3.50324631e-01
1.06368554e+00 -1.01554894e+00 1.03004932e+00 -6.15817606e-01
5.81092119e-01 3.53423327e-01 6.79578304e-01 -1.11660361e+00
-3.89107347e-01 1.33948728e-01 -7.14980006e-01 1.18841684e+00
-1.70308188e-01 -7.06098557e-01 9.65390205e-01 8.90964687e-01
-3.00107509e-01 -1.01199341e+00 -9.54801023e-01 -5.77186465e-01
7.99225450e-01 -2.96951294e-01 6.67535722e-01 6.17430151e-01
-1.13575742e-01 -9.01688337e-02 -2.36033320e-01 -1.66453749e-01
9.16774094e-01 -7.71954060e-01 2.14875653e-01 -1.86075389e+00
7.11373806e-01 -8.93888354e-01 -7.51287282e-01 -1.54460758e-01
5.39231002e-01 -5.28063357e-01 -5.71830690e-01 -1.65748358e+00
3.85861814e-01 -2.37245653e-02 -4.96824533e-01 1.47909448e-01
-1.97452664e-01 1.94270119e-01 -3.70146960e-01 -2.22371161e-01
4.84478846e-03 3.69442940e-01 1.05972779e+00 -4.26215604e-02
2.34399289e-01 1.20625429e-01 -8.77998948e-01 9.36011970e-01
1.37666011e+00 -6.63961694e-02 -4.35583293e-01 -2.88884401e-01
1.74259380e-01 -4.31821287e-01 1.75997302e-01 -1.51019359e+00
-8.11385922e-03 2.16827050e-01 8.48809540e-01 -5.95780849e-01
7.87154958e-02 -4.31034684e-01 -1.12742499e-01 8.90362024e-01
-8.12942311e-02 5.45190215e-01 -7.25880265e-02 2.69148086e-06
2.01007247e-01 -4.40126002e-01 1.13581944e+00 -1.25330269e-01
-9.66199636e-01 6.99565172e-01 -8.84674191e-01 -2.62835085e-01
1.18001306e+00 -2.98889488e-01 -7.06841052e-02 -2.07707778e-01
-9.92247045e-01 2.61830151e-01 3.21489185e-01 4.09838080e-01
6.15480363e-01 -1.27736926e+00 -7.67299533e-01 -6.50989115e-02
1.85162067e-01 -7.06839442e-01 9.28058743e-01 1.35042274e+00
-6.86464429e-01 4.91463751e-01 -1.10663319e+00 -1.52853936e-01
-1.31372285e+00 7.57761657e-01 5.12312889e-01 -1.11870572e-01
-3.93279552e-01 6.83279872e-01 -6.03198111e-02 -1.02147028e-01
2.99424440e-01 -2.93780446e-01 -7.34996855e-01 4.70858425e-01
9.60608184e-01 1.01967955e+00 2.08465204e-01 -5.31596601e-01
-4.20800090e-01 3.65431488e-01 -2.87143409e-01 1.54281482e-01
1.39195168e+00 -5.28957307e-01 -4.80572701e-01 4.87249225e-01
6.51603341e-01 -6.13991141e-01 -8.03115845e-01 1.36292100e-01
1.86119556e-01 1.79025099e-01 1.92268029e-01 -7.30308592e-01
-1.35452092e+00 1.12763274e+00 1.15790582e+00 -1.17664322e-01
1.19931710e+00 -6.93874210e-02 8.46571386e-01 -1.01400740e-01
5.49546123e-01 -1.33691204e+00 -3.97421941e-02 2.56719261e-01
7.50442147e-01 -1.14776516e+00 1.85542002e-01 3.52636166e-02
-2.05578268e-01 1.40074313e+00 9.05151248e-01 -8.81565437e-02
7.31986761e-01 -1.67472973e-01 1.42153814e-01 -1.82590321e-01
-3.37268293e-01 -5.62053472e-02 1.46517336e-01 1.23266602e+00
8.05108070e-01 5.21650352e-02 -1.19328177e+00 8.05977523e-01
-4.03671116e-01 3.17583054e-01 3.16729605e-01 6.09996080e-01
-6.41983628e-01 -1.39977074e+00 -4.66147631e-01 9.76291120e-01
-7.51490891e-01 4.35040183e-02 -2.90665716e-01 6.78323269e-01
3.42009783e-01 6.06915951e-01 1.91856116e-01 -1.49974823e-02
-1.23380356e-01 5.16666114e-01 8.05330694e-01 -2.19258055e-01
-2.22963974e-01 -6.45724833e-01 6.05220459e-02 -2.19905734e-01
-6.09215736e-01 -9.78415191e-01 -8.76359224e-01 -5.37073970e-01
1.86683625e-01 -5.84019646e-02 8.44171703e-01 9.71601248e-01
-5.77066764e-02 4.81015831e-01 -3.42181101e-02 -9.47552085e-01
-1.97253183e-01 -1.18143773e+00 -9.40566123e-01 -2.76375949e-01
5.14074117e-02 -1.13276970e+00 -1.60416737e-01 -1.94198394e-03] | [14.084338188171387, -1.5378623008728027] |
86834192-fc95-45fc-ad9d-f3b6c5270473 | an-optimistic-perspective-on-offline-deep | null | null | https://proceedings.icml.cc/static/paper_files/icml/2020/5394-Paper.pdf | https://proceedings.icml.cc/static/paper_files/icml/2020/5394-Paper.pdf | An Optimistic Perspective on Offline Deep Reinforcement Learning | Off-policy reinforcement learning (RL) using a fixed offline dataset of logged interactions is an important consideration in real world applications. This paper studies offline RL using the DQN replay dataset comprising the entire replay experience of a DQN agent on 60 Atari 2600 games. We demonstrate that recent off-policy deep RL algorithms, even when trained solely on this fixed dataset, outperform the fully trained DQN agent. To enhance generalization in the offline setting, we present Random Ensemble Mixture (REM), a robust Q-learning algorithm that enforces optimal Bellman consistency on random convex combinations of multiple Q-value estimates. Offline REM trained on the DQN replay dataset surpasses strong RL baselines. Ablation studies highlight the role of offline dataset size and diversity as well as the algorithm choice in our positive results. Overall, the results here present an optimistic view that robust RL algorithms trained on sufficiently large and diverse offline datasets can lead to high quality policies. The DQN replay dataset can serve as an offline RL benchmark and is open-sourced. | ['Mohammad Norouzi', 'Dale Schuurmans', 'Rishabh Agarwal'] | null | null | https://proceedings.icml.cc/static/paper_files/icml/2020/5394-Paper.pdf | https://proceedings.icml.cc/static/paper_files/icml/2020/5394-Paper.pdf | icml-2020-1 | ['dqn-replay-dataset', 'dqn-replay-dataset'] | ['miscellaneous', 'playing-games'] | [-4.40859944e-01 -3.00735533e-01 -5.98141730e-01 -1.70303658e-01
-1.16484928e+00 -9.16109979e-01 8.81900489e-01 -3.54699880e-01
-1.02906477e+00 1.13758671e+00 1.61535159e-01 -4.60156053e-01
-2.25403503e-01 -2.08628088e-01 -8.23129356e-01 -6.64424181e-01
-5.02525270e-01 8.74229074e-01 -1.05245434e-01 -5.43481827e-01
4.86459285e-02 2.40274936e-01 -1.41930866e+00 -1.62029907e-01
5.92905164e-01 9.74049032e-01 -7.49983191e-02 8.64869416e-01
4.37348247e-01 1.29551160e+00 -1.02920246e+00 -1.87809825e-01
9.06142294e-01 -3.68502587e-01 -3.56832951e-01 -1.93987489e-01
2.10161179e-01 -1.08662891e+00 -4.48099554e-01 8.09313297e-01
8.81812274e-01 5.94311774e-01 2.96711713e-01 -1.76531553e+00
-1.24148980e-01 7.61711657e-01 -4.88327235e-01 3.84812325e-01
6.02491163e-02 8.18699121e-01 1.18448818e+00 4.54341061e-03
4.51504439e-01 1.16998541e+00 3.85132909e-01 6.18916810e-01
-1.27829599e+00 -9.43207622e-01 3.24882567e-02 -1.74806882e-02
-6.20708883e-01 -3.91703367e-01 4.68560398e-01 -5.73729053e-02
1.20972693e+00 -1.97778523e-01 7.06952572e-01 1.81822312e+00
4.10061300e-01 1.13815200e+00 1.34673417e+00 1.74562447e-02
7.36346483e-01 -3.75884086e-01 -2.77680874e-01 3.51851791e-01
1.32025450e-01 9.56590116e-01 -6.05564415e-01 -5.27021289e-01
7.58432627e-01 -1.83831885e-01 1.34711400e-01 -4.38755363e-01
-1.02882004e+00 1.15963936e+00 -3.40531766e-02 -3.32287103e-01
-5.95070004e-01 6.89180315e-01 7.68062472e-01 8.56621027e-01
3.77570033e-01 7.59230852e-01 -7.88593709e-01 -1.03738058e+00
-6.58358335e-01 8.95280182e-01 1.00551355e+00 8.53419363e-01
4.54000324e-01 3.25610697e-01 -3.44866872e-01 6.77468479e-01
-6.35892339e-03 8.40901554e-01 5.69510758e-01 -1.82160664e+00
4.72144455e-01 -3.89604419e-02 6.36808395e-01 -3.49414408e-01
-5.25783956e-01 -3.74270409e-01 -9.07900333e-02 6.56533897e-01
5.82082450e-01 -8.68598521e-01 -3.98292869e-01 2.01842833e+00
3.31586778e-01 4.42186035e-02 2.81701803e-01 9.28098619e-01
2.76106209e-01 3.91730577e-01 4.43247519e-02 -3.88399839e-01
7.66156256e-01 -1.06748521e+00 -5.01723051e-01 -1.64259702e-01
5.62002659e-01 -4.32876438e-01 1.13695979e+00 8.77249897e-01
-9.51569140e-01 -2.91453689e-01 -9.44954753e-01 2.89879203e-01
6.85386732e-02 -8.40228572e-02 9.34306860e-01 4.49580163e-01
-1.18821621e+00 7.36657739e-01 -9.01149631e-01 -7.69006759e-02
2.64342666e-01 7.07217872e-01 3.70953642e-02 1.26622856e-01
-1.02273393e+00 1.07318926e+00 4.08159256e-01 -2.07838655e-01
-1.64251089e+00 -4.46346790e-01 -5.54785252e-01 -3.90632421e-01
1.08717561e+00 -1.64222717e-01 2.20583701e+00 -1.20124412e+00
-2.26812959e+00 3.48662764e-01 4.69809085e-01 -8.91542494e-01
9.57022727e-01 -3.75429779e-01 -1.97604820e-01 6.46813819e-03
-1.51028717e-02 7.13894188e-01 8.78679335e-01 -1.03848898e+00
-6.84544623e-01 -7.92344213e-02 3.84259969e-01 5.38789392e-01
2.88887858e-01 -1.53905451e-01 8.53658095e-02 -3.93465579e-01
-9.45806146e-01 -1.25058293e+00 -3.14870238e-01 -5.55165589e-01
9.10441726e-02 -4.58854258e-01 6.59720361e-01 -3.43662620e-01
6.85311794e-01 -1.87872708e+00 1.98316444e-02 5.93787134e-02
1.57613724e-01 1.65367872e-01 -4.70491469e-01 5.35654545e-01
4.09287095e-01 -3.78457516e-01 2.22934619e-01 -3.05638701e-01
4.86336946e-01 5.18219829e-01 -4.45701241e-01 7.05149710e-01
-2.79761672e-01 1.07442296e+00 -1.23899615e+00 -2.06310719e-01
2.12821990e-01 -2.34033763e-01 -7.44189739e-01 4.33304548e-01
-8.99949729e-01 7.14727938e-01 -3.18241119e-01 3.61824930e-01
3.53131890e-01 -1.56833958e-02 4.92157668e-01 4.38946158e-01
3.18351947e-02 1.19898692e-01 -8.10200810e-01 1.81033802e+00
-3.94376189e-01 4.47845042e-01 1.86211169e-01 -6.62140548e-01
6.33489907e-01 2.32445508e-01 9.52459812e-01 -1.19036043e+00
3.29720944e-01 1.68483317e-01 3.25729162e-01 -2.01031774e-01
6.68801725e-01 -3.58540341e-02 -4.44204748e-01 1.04732406e+00
3.16650033e-01 -1.37660310e-01 2.39862248e-01 2.40461484e-01
1.40393841e+00 5.25706887e-01 3.45585287e-01 -1.31796926e-01
-2.28990346e-01 1.46460906e-01 5.44672906e-01 1.31390131e+00
-6.68551624e-01 -1.69723541e-01 8.28006864e-01 -5.32918394e-01
-1.14055777e+00 -1.02786195e+00 2.80139297e-01 1.62818766e+00
1.25934193e-02 -2.60577083e-01 -5.46240807e-01 -1.12836933e+00
3.71648610e-01 8.38378787e-01 -6.71989143e-01 -2.22775206e-01
-4.49763268e-01 -8.88515592e-01 6.65157855e-01 3.38922948e-01
4.39414471e-01 -1.40855765e+00 -8.28225613e-01 5.11779428e-01
2.09494829e-02 -1.05455256e+00 -5.27485251e-01 3.32310438e-01
-5.80913126e-01 -1.06114221e+00 -3.97756785e-01 7.89622441e-02
-1.24737017e-01 1.35330886e-01 1.39164019e+00 -2.94881135e-01
3.63890707e-01 8.04336250e-01 -4.77887392e-01 -3.40193331e-01
-6.93431139e-01 -4.44688238e-02 5.91889441e-01 -3.64106536e-01
3.57950717e-01 -5.84773123e-01 -5.83887160e-01 3.03777337e-01
-5.65946162e-01 -4.44844097e-01 4.85554814e-01 8.04294169e-01
2.04510197e-01 -2.95328587e-01 8.34126532e-01 -6.85901105e-01
1.11632895e+00 -6.57676578e-01 -1.15470934e+00 5.20361699e-02
-6.67734563e-01 4.69890654e-01 9.10915375e-01 -7.63882935e-01
-9.30475116e-01 -2.80619651e-01 1.13488026e-01 -6.52911842e-01
1.40816182e-01 -6.32658005e-02 2.57090032e-01 7.26740137e-02
8.18420053e-01 4.56044041e-02 4.99566436e-01 -1.83548898e-01
4.93459344e-01 3.91152263e-01 2.36643597e-01 -1.18631637e+00
2.70925134e-01 2.35976800e-01 -1.77967846e-01 -2.12396801e-01
-6.70523584e-01 -1.96116820e-01 1.07812338e-01 -3.86104256e-01
4.54285383e-01 -1.03106892e+00 -1.45417035e+00 4.46672082e-01
-6.77113414e-01 -1.44993651e+00 -5.01421571e-01 6.45713806e-01
-1.25614786e+00 -2.14554034e-02 -7.15840220e-01 -9.44613159e-01
-2.50735253e-01 -1.32983220e+00 1.02244961e+00 1.92069337e-01
-1.43891992e-02 -9.06628668e-01 7.34935462e-01 1.76927209e-01
3.33226532e-01 8.55872557e-02 3.01918179e-01 -1.04588521e+00
-2.09478468e-01 3.18168491e-01 1.49737850e-01 3.49227369e-01
-4.53812107e-02 -8.77690315e-02 -8.42023611e-01 -8.44808936e-01
-1.52205944e-01 -1.25619507e+00 5.07131279e-01 4.94662017e-01
8.90987158e-01 -4.03484523e-01 3.46425802e-01 2.83020943e-01
1.26587117e+00 3.43445837e-01 1.18005306e-01 4.91859287e-01
2.85337538e-01 7.10649565e-02 8.30351710e-01 1.02888584e+00
4.32044923e-01 6.37554705e-01 6.18240654e-01 3.65258396e-01
3.80834639e-01 -4.64722574e-01 1.06481385e+00 3.11375171e-01
8.50204844e-03 -3.77141953e-01 -6.10994816e-01 9.63858664e-02
-2.14241290e+00 -1.06718719e+00 7.06417918e-01 2.39727378e+00
1.00283301e+00 2.54517317e-01 9.18947697e-01 -4.92880762e-01
1.70409486e-01 1.78650498e-01 -1.28514946e+00 -5.55703461e-01
-7.34335333e-02 2.52808422e-01 8.51395071e-01 4.97523159e-01
-8.33499789e-01 1.11881614e+00 6.84292698e+00 1.13981080e+00
-1.00956321e+00 2.97736704e-01 4.18851703e-01 -8.11013818e-01
3.08234300e-02 -1.45937085e-01 -7.49953508e-01 6.18277133e-01
1.41354907e+00 -9.39736962e-02 1.32713711e+00 8.67418349e-01
5.62457502e-01 -3.99969041e-01 -1.04732764e+00 9.34878051e-01
-2.17543468e-01 -1.04043448e+00 -5.19960403e-01 5.73510110e-01
9.74180162e-01 7.58043051e-01 1.76348016e-01 1.22986054e+00
1.69744790e+00 -1.07320118e+00 7.36337602e-01 2.62118012e-01
5.57640851e-01 -1.02705801e+00 6.35409176e-01 6.01228595e-01
-4.59022641e-01 -4.29240048e-01 -2.62582809e-01 -1.46294385e-01
-2.95321852e-01 -8.59524757e-02 -8.65356803e-01 2.36398593e-01
5.97397268e-01 6.71329975e-01 -3.39355826e-01 5.58404922e-01
-1.13235123e-01 7.93641388e-01 -6.15116775e-01 -1.75846592e-01
7.40613520e-01 -2.76432365e-01 3.86532843e-01 6.27324939e-01
-2.00249106e-01 4.47944254e-02 5.00828862e-01 4.86683965e-01
-1.51604161e-01 -6.35810196e-02 -7.16294944e-01 -2.59925961e-01
3.51897120e-01 1.12901819e+00 -2.87394434e-01 -2.07832873e-01
-2.51631618e-01 6.49371326e-01 7.14226067e-01 4.85261917e-01
-1.05758524e+00 3.19953769e-01 9.04743910e-01 -4.45157498e-01
1.56956166e-01 -3.86612296e-01 3.70841563e-01 -1.15659893e+00
-2.54977643e-01 -1.66871059e+00 6.14155531e-01 -4.67659503e-01
-1.34144521e+00 2.20136896e-01 1.82463288e-01 -1.26884031e+00
-1.03724432e+00 -4.88267273e-01 -3.03710520e-01 1.36359319e-01
-1.25300157e+00 -5.56669176e-01 2.31821790e-01 6.00902557e-01
5.68186820e-01 -5.31950474e-01 5.36354899e-01 -8.64583999e-02
-5.93501925e-01 5.97609937e-01 6.41962111e-01 -4.14420618e-03
7.44796336e-01 -1.37686300e+00 1.05184995e-01 3.94085854e-01
2.60367364e-01 2.54895359e-01 8.14339221e-01 -5.10878503e-01
-1.59239423e+00 -7.44786441e-01 -3.77784938e-01 -6.80324256e-01
7.71101773e-01 -2.54769474e-01 -3.38253379e-01 9.19614017e-01
4.17420715e-01 1.21358268e-01 4.02910173e-01 9.76879150e-02
-1.37245357e-01 -2.38246843e-01 -1.12766933e+00 7.84814060e-01
8.85492384e-01 -3.55362266e-01 -2.39608601e-01 3.52551341e-01
5.92426777e-01 -6.39590919e-01 -8.61557126e-01 1.44904301e-01
5.83872557e-01 -1.07919717e+00 6.05791330e-01 -8.95758033e-01
1.17062233e-01 1.39653146e-01 -1.50020972e-01 -1.58464670e+00
2.95535445e-01 -1.26776493e+00 -3.77334476e-01 6.13919556e-01
5.90937585e-02 -6.09239936e-01 7.64695883e-01 5.03290534e-01
3.49404663e-01 -5.99183261e-01 -1.07082093e+00 -1.15277469e+00
3.16858530e-01 -6.08239830e-01 5.22062004e-01 4.45944548e-01
1.88136436e-02 1.43569693e-01 -8.14799845e-01 -2.76708961e-01
8.46470416e-01 5.96949868e-02 1.29804468e+00 -6.64571762e-01
-7.90372491e-01 -4.15126085e-01 2.09783375e-01 -1.16362381e+00
7.73600698e-01 -5.44058621e-01 1.78125739e-01 -7.58816123e-01
7.16281980e-02 -5.57732463e-01 -3.49638194e-01 4.58862454e-01
4.68209237e-02 -1.69580206e-01 3.54695171e-01 2.25018665e-01
-1.35435414e+00 1.09662938e+00 1.24417245e+00 7.80558512e-02
-4.49121624e-01 1.29867867e-01 -3.86672944e-01 3.84009808e-01
9.95801389e-01 -6.27873719e-01 -7.38537073e-01 -1.67328283e-01
1.24003969e-01 5.95510721e-01 2.70630211e-01 -7.72867262e-01
-1.77080669e-02 -5.89420557e-01 4.08441387e-03 -1.30307734e-01
4.98227894e-01 -6.03277981e-01 -1.77245423e-01 3.73148561e-01
-5.85424662e-01 4.20984685e-01 4.78257537e-01 8.92829597e-01
2.91164279e-01 9.24325362e-03 6.33711934e-01 -3.06535721e-01
-7.70142734e-01 4.25900012e-01 -5.00388443e-01 7.42989779e-01
1.09412849e+00 2.13591754e-01 -2.89932668e-01 -1.03243840e+00
-3.21934253e-01 6.71020865e-01 3.98295075e-01 4.37606096e-01
2.22810715e-01 -1.02663958e+00 -7.70446420e-01 1.27470428e-02
-1.86588451e-01 -4.43568438e-01 -6.27326518e-02 6.96066141e-01
-2.69038737e-01 1.99109823e-01 -5.19292414e-01 -3.51606160e-01
-6.07721746e-01 4.86175925e-01 7.41959155e-01 -7.19186723e-01
-4.58967000e-01 5.07951081e-01 -4.41926032e-01 -7.50855684e-01
3.00488293e-01 -1.85976103e-01 1.84811428e-01 -1.73944831e-01
3.39090496e-01 4.02030677e-01 -1.69469580e-01 -2.59066701e-01
-5.06301969e-02 -2.00622350e-01 -7.29826614e-02 -8.59767258e-01
1.13278747e+00 1.89353198e-01 4.02630031e-01 4.71197546e-01
9.26659286e-01 -7.40528107e-04 -2.23443294e+00 -2.17795014e-01
-9.03160684e-03 -2.04574585e-01 1.50107755e-03 -9.76478279e-01
-1.01494956e+00 2.34934941e-01 4.70059782e-01 1.79670267e-02
7.15134740e-01 -3.93655777e-01 6.90263808e-01 6.66719377e-01
9.70980763e-01 -1.43835604e+00 3.00550461e-01 6.05548203e-01
6.56408787e-01 -1.68112421e+00 1.23713925e-01 9.58573222e-01
-1.27277040e+00 8.26913536e-01 7.92874038e-01 -5.20085096e-01
3.56767982e-01 3.14148575e-01 1.94290668e-01 1.22754194e-01
-1.45427859e+00 -2.52619117e-01 -3.40011597e-01 4.67606992e-01
-2.02978209e-01 2.45260715e-01 -6.49041981e-02 4.73765492e-01
-4.06292796e-01 1.29601792e-01 5.11908114e-01 8.79756808e-01
-5.05638346e-02 -1.18614709e+00 -1.14333101e-01 4.08531308e-01
-4.32598263e-01 1.72212690e-01 -2.19131574e-01 9.81333554e-01
-2.99496055e-01 1.25537002e+00 4.78596501e-02 -3.68671775e-01
-1.57406647e-02 -2.91816950e-01 8.15413296e-01 -1.91825792e-01
-9.81010318e-01 2.64933845e-03 3.39171201e-01 -1.14706624e+00
-2.63903648e-01 -7.96868443e-01 -1.18318534e+00 -7.89173543e-01
1.12966344e-01 2.91666806e-01 3.83886158e-01 1.11820352e+00
3.09822857e-01 5.76020479e-02 6.57477915e-01 -9.49710906e-01
-1.56048656e+00 -9.47413683e-01 -7.10342765e-01 2.40989327e-01
5.72977543e-01 -9.10339832e-01 -4.37850684e-01 -6.88855231e-01] | [3.9963927268981934, 1.7655084133148193] |
6e011e5d-18a7-451e-9fce-be33317d6c7f | continuous-time-video-generation-via-learning | 2112.10960 | null | https://arxiv.org/abs/2112.10960v1 | https://arxiv.org/pdf/2112.10960v1.pdf | Continuous-Time Video Generation via Learning Motion Dynamics with Neural ODE | In order to perform unconditional video generation, we must learn the distribution of the real-world videos. In an effort to synthesize high-quality videos, various studies attempted to learn a mapping function between noise and videos, including recent efforts to separate motion distribution and appearance distribution. Previous methods, however, learn motion dynamics in discretized, fixed-interval timesteps, which is contrary to the continuous nature of motion of a physical body. In this paper, we propose a novel video generation approach that learns separate distributions for motion and appearance, the former modeled by neural ODE to learn natural motion dynamics. Specifically, we employ a two-stage approach where the first stage converts a noise vector to a sequence of keypoints in arbitrary frame rates, and the second stage synthesizes videos based on the given keypoints sequence and the appearance noise vector. Our model not only quantitatively outperforms recent baselines for video generation, but also demonstrates versatile functionality such as dynamic frame rate manipulation and motion transfer between two datasets, thus opening new doors to diverse video generation applications. | ['Edward Choi', 'Jaegul Choo', 'Sookyung Kim', 'Joonseok Lee', 'Junsoo Lee', 'Sunghyun Park', 'Kangyeol Kim'] | 2021-12-21 | null | null | null | null | ['unconditional-video-generation'] | ['computer-vision'] | [ 2.52663821e-01 -2.49857932e-01 6.72897547e-02 7.57569596e-02
-6.09800458e-01 -6.85253263e-01 7.17232466e-01 -6.34764194e-01
-2.09594488e-01 8.69921207e-01 2.46383816e-01 6.21118993e-02
2.24179223e-01 -8.54177296e-01 -1.02366292e+00 -9.56822813e-01
1.22378156e-01 1.02295138e-01 2.09190786e-01 -1.32144094e-01
-6.55664206e-02 3.12111557e-01 -1.61011887e+00 6.91317692e-02
4.95707959e-01 9.41271603e-01 2.01339051e-01 1.14977419e+00
1.92635790e-01 1.08065259e+00 -7.28744268e-01 -2.30538651e-01
4.79782552e-01 -1.05860364e+00 -3.98070097e-01 1.48432568e-01
5.94526827e-01 -6.19771659e-01 -8.72207284e-01 9.54401016e-01
4.74089056e-01 4.57157552e-01 8.26102495e-01 -1.35701454e+00
-8.08894157e-01 3.06333035e-01 -4.02801216e-01 -4.64643985e-02
5.07056177e-01 6.81817472e-01 6.20654941e-01 -5.71019888e-01
9.36986148e-01 1.25417364e+00 4.69721079e-01 1.08315849e+00
-1.34328914e+00 -5.93440115e-01 1.04602993e-01 -1.98106319e-02
-1.17582381e+00 -3.38831961e-01 8.03440511e-01 -7.07011819e-01
4.08401340e-01 2.96277404e-02 1.07619929e+00 1.67695951e+00
3.45206141e-01 7.03335941e-01 7.15314209e-01 -1.29317328e-01
3.76588643e-01 -4.41323102e-01 -8.01157117e-01 4.87486631e-01
8.24396983e-02 3.04227322e-01 -5.46572447e-01 -8.74638557e-02
1.44404531e+00 -1.69641197e-01 -5.02848089e-01 -3.84967387e-01
-1.56410110e+00 6.62504911e-01 -2.56809779e-02 -1.10056689e-02
-4.29690868e-01 7.28403509e-01 2.38867179e-01 3.59379053e-01
1.32286042e-01 3.59222144e-01 -6.72643706e-02 -3.49622339e-01
-1.00424123e+00 7.60524333e-01 8.22669387e-01 9.53050375e-01
6.46677196e-01 5.04552603e-01 -5.41739702e-01 4.43583935e-01
1.77811459e-01 7.69488811e-01 4.12705064e-01 -1.41196394e+00
2.29676276e-01 -9.74924564e-02 3.15960020e-01 -1.14759707e+00
1.73730373e-01 6.08849414e-02 -1.11752033e+00 2.38105670e-01
5.25813043e-01 -5.81206918e-01 -1.04877865e+00 1.99945307e+00
4.43872482e-01 6.28493607e-01 -4.84099351e-02 1.02465475e+00
5.46171546e-01 8.67648900e-01 -4.12690379e-02 -3.07526648e-01
8.65934372e-01 -8.79379213e-01 -8.09451222e-01 1.76194295e-01
1.14959568e-01 -7.51287282e-01 7.92003930e-01 4.42285478e-01
-1.50523484e+00 -7.60099173e-01 -8.84750664e-01 2.07589958e-02
1.88536391e-01 1.92900393e-02 3.27474445e-01 3.25058341e-01
-1.26854682e+00 7.48882473e-01 -8.66586328e-01 -1.27780601e-01
1.62695438e-01 2.39035085e-01 -2.96710551e-01 8.15311447e-02
-1.19908440e+00 3.75007451e-01 2.16269091e-01 6.92721903e-02
-1.35077560e+00 -7.52351165e-01 -1.01347661e+00 -2.04425916e-01
2.52961725e-01 -1.37206078e+00 1.31501389e+00 -1.20373130e+00
-2.01090503e+00 3.70674640e-01 5.65183274e-02 -3.34765553e-01
8.65143538e-01 -2.92582452e-01 -1.34645760e-01 2.66840309e-01
-7.10349083e-02 1.05740571e+00 1.33954573e+00 -1.22868907e+00
-7.08526969e-01 2.76611209e-01 4.08848636e-02 2.69121915e-01
-1.44077122e-01 -3.31640810e-01 -6.12315178e-01 -1.17213321e+00
-3.87222588e-01 -9.84913349e-01 -2.64142126e-01 3.88997227e-01
-1.22831225e-01 1.28952116e-01 9.11764324e-01 -5.92868745e-01
1.25328267e+00 -2.05819225e+00 7.51181006e-01 -9.54485610e-02
2.63212353e-01 1.23513520e-01 -3.05253804e-01 3.41076136e-01
-1.37734143e-02 2.05166508e-02 -1.15999401e-01 -2.45218009e-01
-6.90593570e-02 1.99650779e-01 -4.03074920e-01 3.40011597e-01
3.61898839e-01 8.97886872e-01 -1.27322710e+00 -2.77490228e-01
2.19932646e-01 6.40688062e-01 -8.46044362e-01 5.39211512e-01
-4.67243075e-01 8.83800745e-01 -3.40568513e-01 3.24471503e-01
4.55254197e-01 6.95872772e-03 5.73071018e-02 -3.35471720e-01
7.28960633e-02 -2.17746839e-01 -1.26307857e+00 1.78269517e+00
-2.36329436e-01 5.94522059e-01 6.87540844e-02 -7.25972831e-01
6.69965982e-01 5.56175292e-01 7.65444934e-01 -3.46791595e-01
2.62801349e-01 -2.90994737e-02 -1.69207409e-01 -5.85171938e-01
5.62380433e-01 -3.73600066e-01 3.88178378e-02 2.54554957e-01
2.32329577e-01 -5.87819397e-01 4.03497964e-01 7.39556849e-02
1.10676980e+00 6.65543199e-01 5.23921736e-02 4.10991162e-02
3.63689870e-01 -2.66119629e-01 6.17295861e-01 7.37189114e-01
-4.00502281e-03 1.11423039e+00 5.54353952e-01 -5.10246038e-01
-1.39478552e+00 -1.32094598e+00 5.00519753e-01 4.39599812e-01
2.57213414e-01 -3.03191066e-01 -8.77721190e-01 -5.33755898e-01
-1.78787708e-01 3.04886878e-01 -5.68857372e-01 -4.41628188e-01
-9.35810864e-01 -4.47193652e-01 4.62251097e-01 5.00143528e-01
3.78300130e-01 -1.09120643e+00 -5.51436186e-01 4.02411878e-01
-3.56240094e-01 -1.20398819e+00 -9.63285744e-01 -3.86985600e-01
-5.83204567e-01 -9.19501483e-01 -1.08240175e+00 -7.05137730e-01
5.38044393e-01 6.09886050e-02 1.12979364e+00 -1.90885961e-02
-4.08018053e-01 5.97413778e-01 -2.75896758e-01 3.09235211e-02
-6.53465748e-01 -1.37527645e-01 1.63961664e-01 2.25079983e-01
-2.14736447e-01 -7.52661467e-01 -9.60718751e-01 1.45339742e-01
-1.26760519e+00 2.41342768e-01 4.20658886e-01 9.29085612e-01
5.94857872e-01 -7.27226958e-02 3.94629300e-01 -3.22367102e-01
4.43378001e-01 -6.14443600e-01 -5.87248981e-01 4.38888231e-03
1.96897537e-01 4.00732607e-02 8.54277015e-01 -8.92824173e-01
-1.08593881e+00 2.38613546e-01 -1.84842214e-01 -8.08048785e-01
-2.30569467e-01 1.05508091e-02 -1.36803493e-01 5.26599437e-02
5.47472954e-01 4.22279328e-01 1.90677077e-01 -5.69395944e-02
5.93912363e-01 1.72414988e-01 8.53674591e-01 -9.04121637e-01
1.12107527e+00 5.87792218e-01 2.73487903e-02 -9.33468163e-01
-3.73942792e-01 1.88593268e-02 -4.49714690e-01 -3.93875957e-01
1.19274926e+00 -1.02329361e+00 -5.67057908e-01 8.13266456e-01
-1.17186403e+00 -7.54468977e-01 -5.52340806e-01 5.34450114e-01
-1.02693486e+00 4.04505759e-01 -8.97961497e-01 -5.68179131e-01
-8.39602798e-02 -1.13258433e+00 1.25689375e+00 2.58248210e-01
-2.53841996e-01 -9.65453982e-01 2.70374864e-01 -1.52383894e-01
3.72388840e-01 6.18500829e-01 6.50497079e-01 3.30988139e-01
-9.64509666e-01 2.01129824e-01 1.81870654e-01 5.38627446e-01
3.56306016e-01 3.44121754e-01 -4.45919216e-01 -4.50621545e-01
-3.11053246e-02 -2.92682141e-01 6.10751152e-01 6.44289732e-01
1.02061880e+00 -3.36951762e-01 -1.38757437e-01 9.56690073e-01
1.29470229e+00 3.55401725e-01 8.47455561e-01 1.02522276e-01
7.44635940e-01 2.33489037e-01 3.34992617e-01 5.07310152e-01
1.46811783e-01 6.65854514e-01 1.80669323e-01 -1.60391591e-02
-4.68074590e-01 -4.76200223e-01 6.20997846e-01 8.48353326e-01
-3.22259575e-01 -4.88670677e-01 -4.16340441e-01 5.59246004e-01
-1.89487481e+00 -1.28636730e+00 3.57969731e-01 2.13649821e+00
8.30858469e-01 -6.39654994e-02 3.55780870e-01 -2.53202111e-01
6.70174479e-01 1.80773765e-01 -6.04211450e-01 2.07458273e-01
-1.38491660e-01 1.13498308e-01 1.89054459e-01 3.59211594e-01
-1.07174087e+00 8.24203372e-01 7.11547852e+00 6.48863673e-01
-1.36304641e+00 -2.62796938e-01 5.84253848e-01 -4.38186198e-01
-4.16306198e-01 -2.35283405e-01 -6.38673067e-01 6.56165600e-01
7.96115100e-01 -3.00334811e-01 5.00193059e-01 6.03855789e-01
4.43758011e-01 2.58664399e-01 -1.13126099e+00 1.01715267e+00
-4.76864818e-03 -1.54566085e+00 5.31021476e-01 -8.28217864e-02
1.08342218e+00 -4.68016982e-01 2.17285261e-01 1.96469724e-01
4.56800967e-01 -9.70021963e-01 1.05608535e+00 7.30144024e-01
9.14325535e-01 -6.18353605e-01 2.57945836e-01 2.38852993e-01
-1.30175972e+00 4.71293703e-02 -1.94016010e-01 -7.85341021e-03
6.36062980e-01 3.39354813e-01 -2.12880552e-01 4.63791877e-01
6.26388788e-01 8.32940519e-01 -4.62959446e-02 9.98265803e-01
-1.27591670e-01 4.99447137e-01 -1.76876128e-01 2.85330713e-01
1.15084738e-01 -3.99059683e-01 6.96062386e-01 1.05290139e+00
6.94951832e-01 1.35656837e-02 2.49139249e-01 9.71889973e-01
-1.94865644e-01 -2.66885757e-01 -7.17777669e-01 -1.18103974e-01
2.35334128e-01 1.13028467e+00 -5.36114991e-01 -4.14403737e-01
-4.47920173e-01 1.22518027e+00 6.23852126e-02 6.41001165e-01
-1.21630847e+00 -1.79618523e-01 1.04041684e+00 2.26183400e-01
4.53495920e-01 -5.42352796e-01 3.55119050e-01 -1.42643833e+00
-1.28068859e-02 -1.04150236e+00 -5.13908900e-02 -7.08645880e-01
-1.18846357e+00 5.21436214e-01 9.73060578e-02 -1.46354473e+00
-5.97492874e-01 -3.96274865e-01 -5.66241622e-01 6.41991854e-01
-1.05512786e+00 -1.00711131e+00 -3.80788565e-01 5.56790292e-01
7.77604997e-01 -8.75297636e-02 4.69582051e-01 3.56960088e-01
-2.70964473e-01 4.13490176e-01 9.26806629e-02 1.82688206e-01
7.98386395e-01 -1.09715152e+00 6.94534242e-01 9.18260694e-01
-3.84443579e-03 4.63197917e-01 8.20487380e-01 -7.26235569e-01
-1.49974227e+00 -1.25989687e+00 7.53823146e-02 -3.64231884e-01
5.64017653e-01 -3.98041725e-01 -7.03188658e-01 5.60164511e-01
3.03108752e-01 1.76384002e-01 2.81760454e-01 -9.05606449e-01
-1.17476005e-02 -3.59799084e-03 -8.72278094e-01 8.94024253e-01
1.21130490e+00 -2.39679128e-01 -2.31302574e-01 -5.03863655e-02
7.30763912e-01 -6.60377622e-01 -8.30795586e-01 3.35362405e-01
6.82684839e-01 -8.39038491e-01 1.06053817e+00 -5.78130603e-01
8.32298160e-01 -5.68526208e-01 -5.27717872e-04 -1.49087393e+00
-3.77514124e-01 -1.18325174e+00 -4.64564681e-01 1.04243302e+00
-3.65314297e-02 -7.45569095e-02 8.53139758e-01 3.50009382e-01
1.05285190e-01 -5.87847054e-01 -6.23550177e-01 -7.23747730e-01
1.78224504e-01 -1.26551673e-01 4.60739195e-01 6.43864393e-01
-5.56424737e-01 8.43471885e-02 -9.01880264e-01 -6.59767166e-02
6.29330218e-01 -1.52943805e-01 1.05025637e+00 -6.56215847e-01
-6.52887225e-01 -3.98756802e-01 -5.14447272e-01 -1.57303226e+00
1.81170061e-01 -3.05915713e-01 3.06564718e-01 -1.24979794e+00
1.10045053e-01 -2.03408077e-02 1.52879238e-01 -1.15400016e-01
-3.10486197e-01 3.57118130e-01 3.10872495e-01 2.20835153e-02
-3.26392353e-01 8.39519382e-01 1.63845754e+00 -4.71835881e-02
-1.37310341e-01 -1.54289261e-01 -2.98070580e-01 6.94126129e-01
4.30486858e-01 -1.60379365e-01 -7.86477685e-01 -5.85446596e-01
1.39269605e-01 3.46982956e-01 5.05027533e-01 -1.16174126e+00
1.23463809e-01 -5.05954802e-01 4.87065524e-01 -2.70678431e-01
4.19049054e-01 -5.30586720e-01 5.74885368e-01 4.11640853e-01
-1.49549440e-01 1.80953979e-01 8.50772951e-03 8.68890285e-01
-3.07572514e-01 1.85374588e-01 8.83529603e-01 -3.75066340e-01
-6.32670581e-01 6.67333007e-01 -6.52781010e-01 2.78617352e-01
1.14980912e+00 -2.49635965e-01 -9.06110331e-02 -7.44132102e-01
-8.68594348e-01 -8.64525661e-02 7.06075847e-01 6.55645847e-01
6.36372328e-01 -1.66120493e+00 -6.94292307e-01 2.76110321e-01
-3.54046822e-01 1.91367880e-01 3.64152670e-01 4.53226775e-01
-8.03132057e-01 -1.57985255e-01 -3.53593081e-01 -6.57904387e-01
-8.86611402e-01 5.84058583e-01 3.93725604e-01 4.97170761e-02
-7.18192816e-01 7.64492333e-01 5.38693368e-01 3.79273966e-02
1.13215148e-01 -2.47642413e-01 1.53261974e-01 -2.59321034e-01
7.03722417e-01 2.76133925e-01 -4.95029837e-01 -5.98083735e-01
2.22262830e-01 7.17094839e-01 1.91057906e-01 -2.72094369e-01
1.07130778e+00 -1.43364981e-01 1.49980098e-01 3.67545962e-01
1.14729416e+00 -1.70885757e-01 -1.98727071e+00 2.12602258e-01
-4.26507384e-01 -6.35557473e-01 -3.84867460e-01 -2.79743135e-01
-1.25328338e+00 5.29947281e-01 2.95766890e-01 3.19629908e-02
1.11882758e+00 -2.88994282e-01 1.12137306e+00 -5.31374216e-02
4.77610797e-01 -9.47150290e-01 5.39151669e-01 4.25250083e-01
7.56538451e-01 -9.61698234e-01 -3.91466200e-01 -3.02868068e-01
-5.40430009e-01 1.10091257e+00 7.90113807e-01 -3.80586326e-01
4.79264110e-01 5.51308572e-01 4.12072465e-02 2.57908285e-01
-9.21449721e-01 1.86409906e-01 2.82700777e-01 8.87526810e-01
4.19174522e-01 -2.55178392e-01 -1.06766410e-01 2.11155698e-01
-1.58991113e-01 2.93997526e-01 6.41955495e-01 8.28494549e-01
-1.61301360e-01 -1.14083552e+00 -3.43003184e-01 1.72105506e-01
-4.41686004e-01 2.13799804e-01 -5.77074774e-02 7.03283846e-01
3.04829866e-01 5.41955471e-01 1.03387147e-01 -3.24372590e-01
2.63412297e-01 -1.94913357e-01 7.17442214e-01 -4.41737354e-01
-2.75450706e-01 2.04041153e-01 -2.65667021e-01 -7.00922489e-01
-4.40590024e-01 -6.74655318e-01 -9.55066442e-01 -3.43433559e-01
4.13194187e-02 7.77463019e-02 1.62509009e-01 5.80684304e-01
3.14875811e-01 6.53109491e-01 4.42955852e-01 -1.37159765e+00
-4.90874261e-01 -5.99341512e-01 -4.93703365e-01 8.18312347e-01
6.09495163e-01 -5.69692910e-01 -4.53001082e-01 7.84374416e-01] | [10.850439071655273, -0.6314538717269897] |
ae9ae372-5a7d-42ea-87ba-fdc8e85c9ac9 | learning-interpretable-low-dimensional | 2302.10890 | null | https://arxiv.org/abs/2302.10890v2 | https://arxiv.org/pdf/2302.10890v2.pdf | Learning Interpretable Low-dimensional Representation via Physical Symmetry | Interpretable representation learning has been playing a key role in creative intelligent systems. In the music domain, current learning algorithms can successfully learn various features such as pitch, timbre, chord, texture, etc. However, most methods rely heavily on music domain knowledge. It remains an open question what general computational principles give rise to interpretable representations, especially low-dim factors that agree with human perception. In this study, we take inspiration from modern physics and use physical symmetry as a self-consistency constraint for the latent space. Specifically, it requires the prior model that characterises the dynamics of the latent states to be equivariant with respect to certain group transformations. We show that physical symmetry leads the model to learn a linear pitch factor from unlabelled monophonic music audio in a self-supervised fashion. In addition, the same methodology can be applied to computer vision, learning a 3D Cartesian space from videos of a simple moving object without labels. Furthermore, physical symmetry naturally leads to representation augmentation, a new technique which improves sample efficiency. | ['Gus Xia', 'Yichen Huang', 'Daniel Chin', 'Xuanjie Liu'] | 2023-02-05 | null | null | null | null | ['open-question'] | ['natural-language-processing'] | [ 6.54615045e-01 1.65185750e-01 -2.93904573e-01 -1.42911837e-01
-2.00539663e-01 -6.92704797e-01 7.56680548e-01 -2.29933977e-01
-6.24588877e-02 5.62490821e-01 2.92059094e-01 2.08846509e-01
-5.94196439e-01 -6.34494901e-01 -5.90990722e-01 -9.86383975e-01
1.57412738e-01 3.84297192e-01 -2.24901736e-01 -2.35687569e-01
2.31815234e-01 5.03143430e-01 -1.71366417e+00 1.68618679e-01
5.11691093e-01 6.55099690e-01 -4.51809466e-02 6.52892947e-01
1.06901847e-01 7.11191595e-01 -2.15819225e-01 -7.98345506e-02
3.17393392e-01 -6.59591019e-01 -1.04990685e+00 4.17672366e-01
2.93061644e-01 2.83998787e-01 -3.02357465e-01 1.12197554e+00
3.92406695e-02 3.56587529e-01 1.06109238e+00 -1.07071662e+00
-4.83196527e-01 5.61853588e-01 -2.51750022e-01 -2.83332974e-01
2.99859077e-01 -3.45375448e-01 1.33212721e+00 -5.43124676e-01
6.17382288e-01 1.21885788e+00 5.12795269e-01 4.85451996e-01
-1.58015525e+00 -3.57585192e-01 -1.77622139e-01 4.01002944e-01
-1.13501084e+00 -2.25211397e-01 1.24330819e+00 -5.62745512e-01
2.08625138e-01 5.65389514e-01 9.13289189e-01 1.09158432e+00
1.34115607e-01 6.08583212e-01 1.09284186e+00 -9.19326663e-01
3.25449824e-01 -6.73576444e-02 -1.80361733e-01 5.88004172e-01
-8.66786465e-02 -1.41112849e-01 -8.23633313e-01 -4.19954881e-02
9.72634614e-01 -9.69942063e-02 -4.14394617e-01 -8.23438644e-01
-1.44668043e+00 9.85207975e-01 2.22470924e-01 3.77395332e-01
-2.11574420e-01 2.99313605e-01 2.61317104e-01 3.71847779e-01
2.32451424e-01 8.88014674e-01 -2.66292870e-01 -1.34886086e-01
-6.98947072e-01 1.24467768e-01 7.36911178e-01 4.45680141e-01
6.94818914e-01 2.32193157e-01 2.88390636e-01 5.35966218e-01
3.24216843e-01 5.49357891e-01 5.57272196e-01 -1.44513440e+00
-1.13696814e-01 4.13296282e-01 -6.56305328e-02 -1.15312088e+00
-2.53443033e-01 -4.87284899e-01 -1.06481934e+00 3.44009459e-01
4.71922994e-01 3.24606597e-01 -4.97119874e-01 1.93377340e+00
1.07165724e-01 3.13160360e-01 4.56671230e-02 1.00293314e+00
1.35752410e-01 4.94834572e-01 -4.30367798e-01 -3.47024649e-01
1.34768867e+00 -5.24657845e-01 -7.87627280e-01 1.38674408e-01
7.72065669e-02 -8.93442690e-01 1.21334445e+00 8.92458975e-01
-7.76177943e-01 -7.15278029e-01 -1.15412593e+00 6.38497472e-02
-4.63635921e-02 9.26135480e-02 9.68082547e-01 4.57635254e-01
-5.36819875e-01 1.01793706e+00 -8.37415755e-01 -2.53084332e-01
-7.77248517e-02 3.19819152e-01 -5.06526947e-01 4.10127997e-01
-1.02983880e+00 5.40442467e-01 5.06028891e-01 1.07015145e-03
-5.39948821e-01 -3.79238307e-01 -7.16393948e-01 -2.13968143e-01
3.18776935e-01 -7.29689598e-01 1.18197644e+00 -1.18704665e+00
-2.01052380e+00 8.38496029e-01 2.51420178e-02 -3.43433350e-01
3.56891453e-01 -2.75049567e-01 -2.07506463e-01 3.26612443e-01
-5.52242137e-02 4.49948430e-01 1.51033270e+00 -1.09189665e+00
-8.20378363e-02 -1.63735643e-01 3.27841729e-01 2.16655418e-01
-3.93830061e-01 -5.35595119e-01 -4.56474982e-02 -9.09795463e-01
5.69290102e-01 -1.29941630e+00 -6.76946044e-02 3.58926952e-02
-3.43230397e-01 -2.85281427e-02 6.14066005e-01 -2.65575528e-01
8.08264792e-01 -2.25519800e+00 9.12043571e-01 3.76424849e-01
-2.51353718e-02 -2.22629353e-01 8.78691226e-02 1.64231256e-01
-2.77771056e-01 -1.43506885e-01 -3.00102264e-01 7.12588802e-02
2.41326571e-01 4.24309641e-01 -7.08441257e-01 4.70318586e-01
9.62156802e-02 5.72243273e-01 -8.41956198e-01 -2.61483431e-01
3.00407261e-01 5.70070922e-01 -8.44564319e-01 -6.47844747e-02
-3.69001031e-01 8.90599966e-01 -4.95904863e-01 1.88951716e-02
2.00527653e-01 -2.24394873e-01 1.39608294e-01 -3.05099547e-01
-1.46552369e-01 3.27185303e-01 -1.55582094e+00 2.16055465e+00
-4.32666421e-01 6.10014498e-01 2.81723011e-02 -1.31563675e+00
9.77343678e-01 4.11499560e-01 5.43982565e-01 -1.82520896e-01
-6.33316627e-03 1.54966041e-01 5.40084913e-02 -3.44226658e-01
4.13599402e-01 -5.39103210e-01 -1.23445921e-01 4.86278176e-01
4.98277247e-02 -4.13959920e-01 -5.23560084e-02 -1.12706661e-01
6.78251624e-01 2.98480064e-01 4.10746843e-01 -2.21153483e-01
5.92918158e-01 -2.41714939e-01 3.98108155e-01 5.10518253e-01
4.71870542e-01 5.89815497e-01 4.20571536e-01 -4.67380911e-01
-1.11176491e+00 -1.12460041e+00 -2.88205773e-01 8.04594278e-01
-3.01475301e-02 -4.37755764e-01 -6.43057048e-01 -1.37009084e-01
-2.86497593e-01 3.85066122e-01 -6.11250639e-01 -4.38255429e-01
-4.92306650e-01 -4.48897302e-01 2.66613513e-01 2.35556751e-01
3.81371826e-01 -1.20395362e+00 -7.78998435e-01 2.06211641e-01
-1.99030936e-01 -8.43724430e-01 -2.87242681e-01 3.25581670e-01
-9.39938784e-01 -1.00256240e+00 -5.97334266e-01 -4.77922052e-01
4.41759259e-01 4.00672294e-02 8.40178132e-01 -2.20978618e-01
-5.31166553e-01 5.31606376e-01 -3.11499685e-01 -2.92218894e-01
-4.76455629e-01 6.84475675e-02 5.46921551e-01 3.92642945e-01
-1.17605746e-01 -9.01828527e-01 -2.36862838e-01 2.77100623e-01
-9.91556823e-01 4.47716743e-01 3.89457583e-01 8.34370911e-01
7.96705782e-01 2.07166821e-01 3.24952841e-01 -7.53423393e-01
3.17440093e-01 -2.21157800e-02 -2.97479242e-01 8.38041008e-02
-2.71339923e-01 5.58992445e-01 6.11994028e-01 -7.72481382e-01
-8.42077076e-01 4.26220804e-01 1.49299636e-01 -5.62980711e-01
-1.15330927e-01 4.66963768e-01 -3.20883274e-01 7.86190480e-02
7.57405758e-01 1.52318105e-01 3.80831733e-02 -6.16419077e-01
6.86970115e-01 4.55843061e-01 7.64412940e-01 -7.65682817e-01
1.01206267e+00 7.18569040e-01 4.02733356e-01 -1.13929760e+00
-1.06447852e+00 -3.73928964e-01 -1.01685798e+00 -5.39726429e-02
8.48432064e-01 -6.97404802e-01 -8.55421901e-01 1.82286426e-01
-9.43134487e-01 -1.22869357e-01 -8.43133092e-01 8.83195400e-01
-1.20456493e+00 4.56236988e-01 -3.82667691e-01 -8.85954559e-01
-1.14010386e-01 -7.43817210e-01 9.79859352e-01 -6.10681847e-02
-6.36842430e-01 -8.94805610e-01 3.55632722e-01 3.11267823e-01
-3.65332216e-02 3.58772427e-01 1.06487751e+00 -9.93700325e-02
-5.58869362e-01 5.03076799e-02 3.51330370e-01 4.37734276e-01
2.82842487e-01 -6.35819137e-02 -1.13509226e+00 -6.28399849e-02
3.07381064e-01 -2.21631244e-01 8.59388232e-01 3.19573700e-01
1.11750889e+00 -4.16187704e-01 1.97306037e-01 6.18176758e-01
9.27614331e-01 -6.03034645e-02 3.69817704e-01 2.08005384e-01
8.11061144e-01 5.95518529e-01 3.22492898e-01 5.14379740e-01
-2.07515553e-01 1.02664816e+00 3.88554901e-01 7.43061379e-02
4.19861376e-02 -3.40854853e-01 4.63874757e-01 1.24718904e+00
-4.62455869e-01 2.34798074e-01 -5.69608867e-01 8.08166787e-02
-1.88659942e+00 -1.16566575e+00 4.90252161e-03 2.26274180e+00
8.07811618e-01 7.79713020e-02 4.54782471e-02 9.51561749e-01
5.13483346e-01 7.41533712e-02 -5.19105911e-01 -2.65883327e-01
-1.84534162e-01 4.05094504e-01 8.96555334e-02 4.65383142e-01
-1.16189146e+00 6.60160482e-01 5.80687332e+00 7.55271792e-01
-1.25892782e+00 -1.71042666e-01 -1.31042182e-01 2.44356692e-01
-4.67872113e-01 1.87285170e-01 -2.52136469e-01 1.38285682e-01
6.27255261e-01 -1.27902746e-01 7.91260481e-01 6.86803520e-01
1.23478316e-01 3.33777219e-01 -1.26501274e+00 1.15501285e+00
1.52967423e-01 -1.17797840e+00 3.45329255e-01 2.26003066e-01
6.28770769e-01 -5.86604893e-01 2.76897788e-01 -3.07543352e-02
-2.18435824e-01 -1.04699707e+00 8.60006213e-01 9.30274546e-01
8.05546105e-01 -7.65222728e-01 2.51135707e-01 4.34886694e-01
-1.07403362e+00 1.30733326e-01 -3.68218005e-01 -3.72658938e-01
5.44855073e-02 3.37345749e-01 -6.83631957e-01 5.51023066e-01
3.21725398e-01 9.56489146e-01 -3.34379196e-01 7.72450864e-01
-5.17785132e-01 6.18487954e-01 -3.68283272e-01 3.33406597e-01
-7.64071420e-02 -5.51332057e-01 6.96900606e-01 7.46083081e-01
3.25660974e-01 9.49876979e-02 1.55607518e-02 7.74752975e-01
5.89796156e-02 1.38744771e-01 -5.82511306e-01 -2.97655374e-01
-1.71869084e-01 1.23231578e+00 -8.86998534e-01 -1.56806767e-01
-1.41139631e-03 1.04290926e+00 -1.22435845e-01 2.10886747e-01
-4.67584014e-01 -1.99501902e-01 6.46352530e-01 1.12898782e-01
1.17780440e-01 -4.41448957e-01 -2.21798866e-04 -1.39270651e+00
-9.53730568e-02 -9.43889260e-01 1.13985524e-01 -7.63234913e-01
-1.04629397e+00 2.31361076e-01 -3.06134764e-02 -1.50675368e+00
-5.34467399e-01 -7.29176641e-01 -4.59865868e-01 4.60416943e-01
-1.16834998e+00 -9.70748246e-01 -1.20437711e-01 7.34409213e-01
4.52404112e-01 -2.12540716e-01 1.28646052e+00 1.74782295e-02
-1.02353610e-01 1.57306686e-01 1.20244585e-01 2.87202150e-02
6.11283839e-01 -1.47246003e+00 1.11470267e-03 4.02909338e-01
1.06567645e+00 6.85157418e-01 9.61897612e-01 -1.94456920e-01
-1.49431014e+00 -6.52148306e-01 4.54757512e-01 -4.16938305e-01
7.72739887e-01 -3.34775656e-01 -9.07423079e-01 4.82841164e-01
-1.31913051e-01 -1.11924529e-01 7.48930931e-01 4.17859316e-01
-4.38996881e-01 -9.00486112e-03 -5.46632230e-01 5.24403572e-01
1.02385449e+00 -8.92167509e-01 -7.99738586e-01 3.25578839e-01
4.42593306e-01 -2.07623899e-01 -8.14153492e-01 3.42642099e-01
7.65797138e-01 -6.04912817e-01 1.04374528e+00 -7.80605316e-01
2.39106461e-01 -5.32629073e-01 -1.53195724e-01 -1.12991583e+00
-4.36261863e-01 -8.96348774e-01 -2.02385217e-01 9.68024969e-01
-2.24843808e-02 -2.92403340e-01 6.39797151e-01 7.31265321e-02
8.65121707e-02 -2.46078268e-01 -9.70134079e-01 -8.68687093e-01
-8.64156261e-02 -4.92340297e-01 2.53738731e-01 1.12245035e+00
1.46569788e-01 6.81365550e-01 -6.96190655e-01 1.30781442e-01
7.34294474e-01 4.43281740e-01 8.07666600e-01 -1.82892239e+00
-7.35175490e-01 -2.78607339e-01 -6.95944548e-01 -9.35945868e-01
4.83398736e-01 -1.23666000e+00 -1.93450525e-01 -1.01230001e+00
2.00325802e-01 -2.85823464e-01 -3.01215678e-01 3.99716467e-01
4.17651236e-01 5.08276045e-01 3.74279201e-01 4.49648887e-01
-4.86576498e-01 7.45277226e-01 1.36734164e+00 -1.15177281e-01
-2.56986588e-01 2.62617111e-01 -4.93737698e-01 1.21804786e+00
8.34888220e-01 -3.87194425e-01 -4.89546806e-01 -1.33893415e-01
6.83972716e-01 -4.01883386e-02 5.86285532e-01 -9.85436916e-01
5.04563265e-02 -2.27117389e-01 2.59447098e-01 -5.82595356e-02
6.42139554e-01 -8.14030230e-01 5.01608551e-01 4.47994769e-01
-5.46914339e-01 -3.42982054e-01 -9.91634354e-02 6.46209121e-01
-2.87484616e-01 -5.12736976e-01 6.63023710e-01 -8.80504623e-02
-3.95356745e-01 -2.45480835e-02 -3.16176653e-01 5.14380820e-02
5.05411148e-01 -2.49141589e-01 4.06597376e-01 -4.73213404e-01
-1.04746675e+00 -4.97633725e-01 4.14371610e-01 5.09264290e-01
2.73296267e-01 -1.51434970e+00 -5.34806609e-01 4.74940985e-01
4.19719405e-02 -1.45709038e-01 1.34026855e-01 6.56199992e-01
-3.78234148e-01 3.03400904e-01 -2.98745632e-01 -8.34444940e-01
-1.21154082e+00 4.27593052e-01 6.58572093e-02 5.94675541e-02
-8.78059149e-01 3.69905859e-01 2.59300560e-01 -3.22574586e-01
4.94557209e-02 -3.98022056e-01 -2.20442668e-01 2.11224690e-01
3.67388189e-01 1.86130509e-01 -2.12210685e-01 -8.49572599e-01
-1.33621961e-01 1.06442690e+00 3.10173810e-01 -4.94627804e-01
1.33514118e+00 1.81066141e-01 -2.94152345e-03 1.04001236e+00
1.02305877e+00 2.48809785e-01 -1.25060129e+00 -2.89775968e-01
4.92029786e-02 -3.10353547e-01 -8.21113065e-02 -2.24758387e-01
-7.90995181e-01 1.03261495e+00 4.34837550e-01 3.46322238e-01
1.03887463e+00 8.40306804e-02 2.19370320e-01 6.88245714e-01
4.11939263e-01 -9.37212646e-01 3.92419428e-01 5.11294663e-01
1.13650990e+00 -9.07194018e-01 4.68430966e-02 -3.58764142e-01
-4.55548584e-01 1.40347922e+00 -1.28296837e-01 -2.34035432e-01
5.75870693e-01 -2.03689829e-01 -1.38861015e-01 1.35497842e-02
-4.62786436e-01 -6.67562336e-02 7.13147819e-01 3.00513148e-01
4.53119993e-01 2.98227876e-01 3.25608850e-02 2.96037853e-01
-8.83866012e-01 -1.20959327e-01 4.51360017e-01 4.47099537e-01
-3.83663476e-01 -1.28016508e+00 -3.78281653e-01 3.14624310e-02
-3.13054979e-01 2.14954361e-01 -3.13420355e-01 6.00472212e-01
3.28278124e-01 5.89524567e-01 -1.06928488e-02 -1.53039753e-01
2.98611403e-01 2.22288549e-01 9.12666142e-01 -6.49194717e-01
8.63445364e-03 2.42985412e-01 -4.19278443e-01 -2.31336728e-01
-7.94965684e-01 -8.80107462e-01 -1.37075365e+00 -5.95574966e-03
-2.50991851e-01 5.15933752e-01 7.14491248e-01 9.22261417e-01
-3.24774235e-02 6.05440140e-01 5.23845136e-01 -9.25235093e-01
-5.04749000e-01 -7.72062004e-01 -8.78583431e-01 6.13843977e-01
4.22998577e-01 -8.79393816e-01 -6.32650197e-01 5.62201083e-01] | [15.764603614807129, 5.38908576965332] |
f7b4d81e-5e96-4160-8354-b8b3b2cea284 | xtransct-ultra-fast-volumetric-ct | 2305.19621 | null | https://arxiv.org/abs/2305.19621v1 | https://arxiv.org/pdf/2305.19621v1.pdf | XTransCT: Ultra-Fast Volumetric CT Reconstruction using Two Orthogonal X-Ray Projections via a Transformer Network | Computed tomography (CT) scans offer a detailed, three-dimensional representation of patients' internal organs. However, conventional CT reconstruction techniques necessitate acquiring hundreds or thousands of x-ray projections through a complete rotational scan of the body, making navigation or positioning during surgery infeasible. In image-guided radiation therapy, a method that reconstructs ultra-sparse X-ray projections into CT images, we can exploit the substantially reduced radiation dose and minimize equipment burden for localization and navigation. In this study, we introduce a novel Transformer architecture, termed XTransCT, devised to facilitate real-time reconstruction of CT images from two-dimensional X-ray images. We assess our approach regarding image quality and structural reliability using a dataset of fifty patients, supplied by a hospital, as well as the larger public dataset LIDC-IDRI, which encompasses thousands of patients. Additionally, we validated our algorithm's generalizability on the LNDb dataset. Our findings indicate that our algorithm surpasses other methods in image quality, structural precision, and generalizability. Moreover, in comparison to previous 3D convolution-based approaches, we note a substantial speed increase of approximately 300 $\%$, achieving 44 ms per 3D image reconstruction. To guarantee the replicability of our results, we have made our code publicly available. | ['Xiaokun Liang', 'Yaoqin Xie', 'Wenfeng He', 'Lin Liu', 'Yinping Chan', 'Xuan Liu', 'Tangsheng Wang', 'Jingjing Dai', 'Chulong Zhang'] | 2023-05-31 | null | null | null | null | ['image-reconstruction', 'computed-tomography-ct'] | ['computer-vision', 'methodology'] | [ 3.97703797e-02 1.01749385e-02 -2.16969222e-01 -3.01424116e-01
-1.10759544e+00 -5.83466291e-01 1.90974370e-01 7.15213940e-02
-5.42417347e-01 3.01815271e-01 3.47153574e-01 -8.59045088e-01
-1.39833510e-01 -8.20053935e-01 -6.83862507e-01 -3.63991022e-01
-2.06399918e-01 6.59023166e-01 -1.45028047e-02 1.94356143e-01
-1.31943285e-01 7.81441808e-01 -6.40607774e-01 3.52898419e-01
3.68364692e-01 1.22108233e+00 3.45012993e-01 6.49665117e-01
2.39779800e-01 6.09037101e-01 -1.19932584e-01 -3.57724458e-01
4.27853346e-01 -2.81434536e-01 -8.79176259e-01 1.77713454e-01
4.48411137e-01 -8.35687101e-01 -6.96294606e-01 5.00809133e-01
7.52762258e-01 -2.00082242e-01 3.52187246e-01 -3.83906156e-01
-3.53545606e-01 2.84773976e-01 -3.47005874e-01 3.56950104e-01
3.80095810e-01 3.03837866e-01 2.64631510e-01 -8.89969945e-01
7.53448367e-01 4.47225541e-01 1.17101312e+00 5.28929889e-01
-9.01817262e-01 -4.75492567e-01 -4.79117006e-01 -3.44111383e-01
-1.32534635e+00 -1.88155860e-01 2.20380902e-01 -1.40756249e-01
8.11152756e-01 6.25412285e-01 7.90704429e-01 9.01832461e-01
6.27353132e-01 3.44822764e-01 1.11150885e+00 -3.60347897e-01
9.47721079e-02 -1.28984824e-01 -3.02173227e-01 1.07202804e+00
2.18699142e-01 3.93046916e-01 -1.96248502e-01 -5.81905067e-01
1.23097610e+00 4.93124157e-01 -6.07423007e-01 -4.35315877e-01
-1.43902552e+00 5.58982313e-01 7.28160024e-01 2.67088801e-01
-5.71481586e-01 3.72320652e-01 5.06669164e-01 -1.55625030e-01
1.65699273e-01 1.31383136e-01 -1.28998235e-01 -1.65400892e-01
-7.53580332e-01 -2.69091696e-01 5.30680954e-01 1.12973106e+00
4.61328253e-02 -2.63082772e-01 4.25799936e-02 4.56697226e-01
6.93457872e-02 4.34812188e-01 8.62794816e-01 -7.82078505e-01
5.76462924e-01 2.86193430e-01 -2.66471833e-01 -5.96195936e-01
-7.58337915e-01 -6.73780620e-01 -1.17803264e+00 2.49533681e-03
2.22232461e-01 5.35305962e-02 -9.31985617e-01 1.22967482e+00
2.91163176e-01 8.31184536e-02 -2.06317112e-01 1.19346035e+00
8.67826641e-01 7.44492263e-02 -4.34437282e-02 -1.93834886e-01
1.60473001e+00 -6.92228615e-01 -3.07283998e-01 -7.74790868e-02
6.69322431e-01 -7.58420765e-01 1.14379930e+00 5.26948512e-01
-1.39758396e+00 -2.65476286e-01 -8.05630803e-01 1.99065790e-01
2.47500494e-01 2.31312469e-01 9.36886370e-01 9.53889906e-01
-9.00500417e-01 6.42585099e-01 -1.29903519e+00 -2.56943434e-01
5.92294574e-01 5.29787481e-01 -5.70535779e-01 -4.14879590e-01
-5.89930654e-01 9.46282864e-01 -4.73451056e-02 -1.12396717e-01
-6.84080184e-01 -1.09806871e+00 -5.69328308e-01 -4.77637984e-02
3.27408731e-01 -9.30095673e-01 1.47427583e+00 -1.41451329e-01
-1.29986250e+00 8.92349124e-01 1.06065914e-01 -2.63474077e-01
6.44479573e-01 2.99108084e-02 -2.94573694e-01 6.04951024e-01
-6.87397867e-02 2.21158385e-01 1.97258115e-01 -9.78838563e-01
-1.42775312e-01 -6.47956312e-01 -1.29178792e-01 3.30520600e-01
-9.70678031e-02 -1.71325117e-01 -1.00066936e+00 -6.73400223e-01
8.07339370e-01 -1.03069842e+00 -6.99714124e-01 5.86615741e-01
-2.35609099e-01 6.56744897e-01 2.35913500e-01 -6.03078187e-01
9.01534975e-01 -2.06064844e+00 -3.50332737e-01 4.25280422e-01
5.07094324e-01 -1.81301475e-01 3.35444093e-01 2.26715282e-01
-3.32516819e-01 3.38412193e-03 -2.86596984e-01 -4.00523424e-01
-4.05511826e-01 3.08767587e-01 1.38566701e-03 9.20956790e-01
-6.40752554e-01 1.07076728e+00 -6.44099534e-01 -6.35290682e-01
4.31054801e-01 5.43247342e-01 -5.78021467e-01 -7.81143308e-02
4.46211219e-01 7.54347682e-01 -6.85208499e-01 7.65314400e-01
7.47850060e-01 -7.44019210e-01 4.44204956e-01 -3.28764468e-01
6.64648265e-02 3.31126750e-01 -7.30718136e-01 2.30045891e+00
-8.50276470e-01 8.59718323e-02 1.15496896e-01 -4.26032454e-01
3.26781243e-01 6.05149865e-01 1.00714254e+00 -1.04167497e+00
2.65802294e-01 2.00927690e-01 -1.98285490e-01 -2.00283617e-01
2.21808314e-01 -5.78466594e-01 -3.75476964e-02 7.57256866e-01
-3.33951652e-01 -4.76500064e-01 -4.24739182e-01 2.13097408e-01
1.39375734e+00 -3.40137333e-01 2.53341079e-01 -1.57121599e-01
-8.87576863e-02 1.95883885e-01 -5.14259078e-02 7.69151390e-01
1.30760921e-02 1.07859993e+00 3.23331915e-02 -7.16084659e-01
-1.03070581e+00 -1.45200992e+00 -6.88867629e-01 2.99767226e-01
5.33373058e-02 -4.12242323e-01 -5.75900495e-01 -7.42930651e-01
-6.28290921e-02 3.55831802e-01 -5.71555853e-01 1.08330153e-01
-8.77932131e-01 -8.53848159e-01 6.46527052e-01 7.32064009e-01
1.77186862e-01 -5.05302727e-01 -1.00062323e+00 2.10879475e-01
-1.37361288e-01 -1.05339718e+00 -6.61080718e-01 2.41844237e-01
-1.44606519e+00 -1.25272107e+00 -8.25417876e-01 -2.81684011e-01
9.97895360e-01 3.98198813e-01 1.39499080e+00 2.89088488e-01
-6.59898281e-01 6.21915519e-01 -1.92395926e-01 -3.69410515e-02
-2.66647667e-01 -2.06228361e-01 9.18488950e-02 -7.92347133e-01
-2.90974408e-01 -5.50433040e-01 -1.11828959e+00 4.08793628e-01
-9.44717109e-01 8.72622505e-02 7.89623439e-01 8.07320118e-01
9.58605409e-01 -1.81139171e-01 -1.55865625e-01 -1.21164775e+00
3.75286371e-01 -3.74788284e-01 -5.65953135e-01 7.09567964e-02
-6.10031545e-01 -2.50723362e-01 6.51812971e-01 -7.68639818e-02
-9.16005075e-01 2.74420112e-01 -6.11198843e-01 -5.23892581e-01
-1.55188923e-03 5.63977957e-01 5.63316941e-01 -4.60031658e-01
8.28275800e-01 4.81730074e-01 1.47057384e-01 -3.85705680e-01
2.40282670e-01 1.98131949e-01 6.90274894e-01 -4.35405493e-01
5.57777464e-01 8.20575714e-01 2.13375390e-01 -4.03408438e-01
-4.89625484e-01 -3.40920568e-01 -5.95071912e-01 -1.32069290e-01
5.60890973e-01 -9.12222147e-01 -1.04451978e+00 -1.91202864e-01
-8.37210774e-01 -2.93145962e-02 -4.37383622e-01 9.89371061e-01
-6.82837903e-01 5.14208555e-01 -9.15381491e-01 -2.01824196e-02
-6.38216674e-01 -1.47452927e+00 1.23244321e+00 -3.21479589e-01
-2.55722702e-01 -7.73505270e-01 7.50557333e-02 1.10778503e-01
6.39205754e-01 3.36646080e-01 8.09155285e-01 -3.41513976e-02
-7.75056183e-01 -4.92846459e-01 -2.00485826e-01 -5.03421500e-02
7.44427890e-02 -7.85886705e-01 -5.21032393e-01 -4.74469423e-01
4.04808521e-01 -2.41557091e-01 3.64329249e-01 6.82840645e-01
1.81139398e+00 -2.74538174e-02 -5.09789050e-01 1.11714995e+00
1.60819328e+00 7.67715946e-02 7.17667043e-01 1.01046838e-01
4.22360569e-01 -9.19202417e-02 4.18012381e-01 6.79118216e-01
2.00873822e-01 6.13128960e-01 5.58983862e-01 -3.73763233e-01
-9.68399942e-02 -1.40294150e-01 -4.63664711e-01 8.56872439e-01
-3.36387783e-01 4.40504104e-02 -1.10730374e+00 5.44257574e-02
-1.01079321e+00 -5.19653440e-01 -2.03357190e-01 2.21392202e+00
6.03125751e-01 4.39712964e-02 -2.01322198e-01 -1.55492827e-01
1.02065675e-01 -1.38618723e-01 -3.76705378e-01 7.61008561e-02
4.65184361e-01 7.14819133e-01 1.06034207e+00 1.65595740e-01
-6.38176084e-01 2.13328674e-02 7.73529482e+00 5.81083417e-01
-1.35265791e+00 5.34936190e-01 7.11518228e-01 -4.71181661e-01
-2.77061254e-01 -3.85999411e-01 -1.77300468e-01 3.53316098e-01
8.19103956e-01 1.84448957e-01 1.33947909e-01 9.74159479e-01
6.72982782e-02 -3.21669579e-01 -1.13809526e+00 1.13656342e+00
-2.89907609e-03 -1.83892965e+00 -2.90254295e-01 3.64132375e-01
3.17125559e-01 3.47180188e-01 2.28390589e-01 -9.20598730e-02
1.36714756e-01 -1.20882678e+00 4.12464559e-01 3.30648899e-01
1.48246610e+00 -6.41408145e-01 5.07983148e-01 4.59200323e-01
-9.28850889e-01 2.94122845e-01 -2.64920354e-01 3.89854133e-01
2.81235844e-01 6.17042124e-01 -1.13797224e+00 9.02504504e-01
6.43909156e-01 1.06246457e-01 -3.99848759e-01 8.96768749e-01
2.58284688e-01 3.96563321e-01 -5.40146470e-01 4.92850482e-01
1.79505125e-01 -1.65082868e-02 4.23530973e-02 8.82510245e-01
6.43785000e-01 8.35969746e-01 -6.57970756e-02 3.77088010e-01
-1.30398959e-01 -7.57160857e-02 -5.90171814e-01 4.76339579e-01
2.19784811e-01 1.10939848e+00 -8.25481355e-01 -3.69625181e-01
-5.32193720e-01 1.02385128e+00 4.98480164e-02 -2.30916008e-01
-1.09942091e+00 2.50245005e-01 3.80800888e-02 4.00100172e-01
6.39614509e-03 -3.87303740e-01 -6.41236424e-01 -1.00522172e+00
1.78712770e-01 -7.39934742e-01 4.85277385e-01 -7.67358303e-01
-9.23830271e-01 1.13488650e+00 -1.44535720e-01 -1.66917741e+00
-3.82670850e-01 -7.22995996e-01 -4.08573955e-01 9.38760400e-01
-1.02378654e+00 -9.92511928e-01 -5.21878302e-01 7.29109645e-01
1.74096212e-01 2.21510530e-01 1.16428626e+00 6.80375993e-01
-1.36650470e-03 5.45747042e-01 2.28507265e-01 3.81349064e-02
3.44565570e-01 -1.00954032e+00 3.05924565e-01 3.00657392e-01
-1.22738190e-01 6.91393793e-01 2.20980778e-01 -5.56040108e-01
-2.07820630e+00 -9.42435741e-01 2.98047215e-01 -7.53939807e-01
1.20639689e-01 -2.55083684e-02 -4.66448635e-01 1.03515196e+00
-1.18636779e-01 5.98065853e-01 9.31284726e-01 -1.62750706e-01
1.09662995e-01 1.39169574e-01 -1.47477388e+00 3.25131506e-01
1.13236904e+00 -2.93320775e-01 -2.44463325e-01 6.33670270e-01
3.40930730e-01 -1.26035798e+00 -1.25217736e+00 4.28005069e-01
6.58152878e-01 -1.06863129e+00 1.38257325e+00 -1.39075831e-01
4.46401358e-01 1.50902912e-01 -2.20391393e-01 -1.02012086e+00
-2.32866883e-01 -4.18796614e-02 1.94142297e-01 1.38804078e-01
1.13146491e-01 -6.54767632e-01 1.24026108e+00 7.66747653e-01
-5.03583312e-01 -1.03874326e+00 -1.20539093e+00 -5.40491700e-01
-4.70766751e-03 -8.09443414e-01 5.73110163e-01 8.38485479e-01
8.64567459e-02 -3.56346905e-01 -6.17793277e-02 3.36545140e-01
5.94693482e-01 2.24953905e-01 4.61801320e-01 -5.34116924e-01
-7.35388577e-01 -9.64711532e-02 -1.88792065e-01 -1.15106344e+00
-5.51462054e-01 -1.11308420e+00 -2.07136437e-01 -1.43507922e+00
4.24724847e-01 -8.75306487e-01 5.39567247e-02 2.32475102e-01
2.35079557e-01 7.53020406e-01 -2.66904105e-02 3.43580008e-01
-2.53787994e-01 2.37951085e-01 1.75278950e+00 2.85072654e-01
2.94454485e-01 2.24003658e-01 -5.07632971e-01 8.46134901e-01
4.34996098e-01 -6.39149845e-01 -3.72680455e-01 -7.57349610e-01
-1.42496198e-01 8.88434112e-01 3.73182744e-01 -1.07804835e+00
2.90074289e-01 1.02848589e-01 9.37477827e-01 -9.39461291e-01
6.32854283e-01 -1.13260853e+00 5.04416704e-01 1.06282675e+00
1.20061241e-01 4.02579725e-01 3.04570884e-01 2.00185597e-01
-1.11994736e-01 -1.12755649e-01 7.63247311e-01 -6.98358059e-01
-1.35007143e-01 6.79010212e-01 -3.75601947e-01 -3.20378810e-01
1.02155125e+00 -1.64431170e-01 -6.87743202e-02 -2.38131940e-01
-8.05685163e-01 -2.50881046e-01 4.54746455e-01 -2.64248282e-01
1.04315484e+00 -1.41700888e+00 -4.88067985e-01 2.99073488e-01
-5.79162836e-02 2.59240270e-01 6.38926864e-01 1.12098956e+00
-1.23475468e+00 7.22956061e-01 -9.21964198e-02 -8.00977826e-01
-1.07829154e+00 5.61673939e-01 4.55392569e-01 -5.00168264e-01
-1.27108431e+00 5.76687217e-01 3.27198118e-01 -6.24890566e-01
-8.99578258e-02 -5.88028848e-01 5.36583483e-01 -7.37528384e-01
4.63161200e-01 -7.20925629e-02 5.97390175e-01 -3.11615855e-01
-4.61215496e-01 4.73546743e-01 -3.83710787e-02 -1.29586905e-01
1.28551543e+00 -1.32365376e-01 2.24557877e-01 -2.82003790e-01
1.18492007e+00 1.53585091e-01 -8.53496075e-01 -2.23558977e-01
-4.94757533e-01 -8.19742024e-01 3.14942569e-01 -9.27698851e-01
-1.15619981e+00 6.53982341e-01 7.18464375e-01 -1.61382943e-01
1.37639952e+00 2.95523971e-01 9.36779439e-01 1.07801445e-01
7.90941238e-01 -2.80375898e-01 -9.90557019e-03 1.08518228e-01
7.75874257e-01 -1.09611022e+00 4.07447278e-01 -7.45830536e-01
-4.88192469e-01 1.01749313e+00 3.81180793e-01 1.51223233e-02
6.08232677e-01 6.64559305e-01 2.87198313e-02 -5.85084617e-01
-4.43159223e-01 4.14314419e-01 2.25840062e-01 4.01139438e-01
5.12450933e-01 2.11680338e-01 -1.23471901e-01 5.02705634e-01
-3.51670593e-01 2.08921120e-01 3.42171162e-01 1.31754041e+00
1.46634569e-02 -9.49136853e-01 -6.22959018e-01 5.78937113e-01
-6.24373496e-01 -3.27967197e-01 2.77634203e-01 1.03154469e+00
-2.90507853e-01 1.84699655e-01 5.92965521e-02 3.62310857e-02
6.43178999e-01 -4.59369332e-01 8.48415136e-01 -6.45959318e-01
-6.75837755e-01 -1.03073921e-02 -1.51574060e-01 -9.29157555e-01
8.12095925e-02 -3.41261834e-01 -1.40683067e+00 -5.09039998e-01
-4.06953432e-02 -3.22541520e-02 9.71431196e-01 5.97465277e-01
2.46817619e-01 7.76833832e-01 6.07078254e-01 -6.82698965e-01
-7.35975444e-01 -5.82833707e-01 -5.61819553e-01 1.79962799e-01
6.88066036e-02 -3.33315253e-01 2.00032130e-01 -1.46558702e-01] | [13.569624900817871, -2.600358247756958] |
4ce4d776-fd48-47b2-8e75-ae783bf88b7d | towards-realistic-visual-dubbing-with | 2201.06260 | null | https://arxiv.org/abs/2201.06260v1 | https://arxiv.org/pdf/2201.06260v1.pdf | Towards Realistic Visual Dubbing with Heterogeneous Sources | The task of few-shot visual dubbing focuses on synchronizing the lip movements with arbitrary speech input for any talking head video. Albeit moderate improvements in current approaches, they commonly require high-quality homologous data sources of videos and audios, thus causing the failure to leverage heterogeneous data sufficiently. In practice, it may be intractable to collect the perfect homologous data in some cases, for example, audio-corrupted or picture-blurry videos. To explore this kind of data and support high-fidelity few-shot visual dubbing, in this paper, we novelly propose a simple yet efficient two-stage framework with a higher flexibility of mining heterogeneous data. Specifically, our two-stage paradigm employs facial landmarks as intermediate prior of latent representations and disentangles the lip movements prediction from the core task of realistic talking head generation. By this means, our method makes it possible to independently utilize the training corpus for two-stage sub-networks using more available heterogeneous data easily acquired. Besides, thanks to the disentanglement, our framework allows a further fine-tuning for a given talking head, thereby leading to better speaker-identity preserving in the final synthesized results. Moreover, the proposed method can also transfer appearance features from others to the target speaker. Extensive experimental results demonstrate the superiority of our proposed method in generating highly realistic videos synchronized with the speech over the state-of-the-art. | ['Zejun Ma', 'Yang Zhang', 'Jiali Yao', 'Mingjie Wang', 'Jianfei Yang', 'Xiang Yin', 'Benlai Tang', 'Cheng Bi', 'Liucheng Liao', 'Tianyi Xie'] | 2022-01-17 | null | null | null | null | ['talking-head-generation'] | ['computer-vision'] | [ 1.55274689e-01 1.91210181e-01 -2.26742387e-01 -1.68004781e-01
-1.09175456e+00 -3.31534475e-01 5.72533846e-01 -6.27968729e-01
2.09312104e-02 6.96351767e-01 4.06836450e-01 9.82250199e-02
2.36457828e-02 -3.11489344e-01 -7.87912786e-01 -8.53627443e-01
4.34160113e-01 1.45177335e-01 -1.48258656e-01 1.37100387e-02
-1.02923967e-01 5.07480919e-01 -1.91588509e+00 2.08794326e-01
7.60670424e-01 1.07335043e+00 5.34953177e-01 5.11533856e-01
1.15984298e-01 5.95711052e-01 -3.89825851e-01 -3.53798985e-01
1.88490063e-01 -4.25167263e-01 -3.23188990e-01 5.31442225e-01
5.70132077e-01 -4.51077521e-01 -3.52847755e-01 9.84337747e-01
8.56125891e-01 2.70736247e-01 4.49829757e-01 -1.41901433e+00
-3.88809085e-01 4.27015305e-01 -6.25586331e-01 -2.05649763e-01
6.33027554e-01 5.16586244e-01 9.16027308e-01 -1.22963250e+00
7.08380938e-01 1.38906348e+00 3.97523642e-01 8.74624670e-01
-1.18514740e+00 -8.62238467e-01 1.59099594e-01 3.26626241e-01
-1.57571566e+00 -1.33211279e+00 1.17698598e+00 -2.49608785e-01
2.25119159e-01 2.72959352e-01 5.28133988e-01 1.52071714e+00
-6.09782815e-01 9.49888110e-01 1.03955364e+00 -2.20469445e-01
4.66172360e-02 1.30534425e-01 -4.33333218e-01 4.80309278e-01
-7.89173320e-02 1.11259580e-01 -7.28095114e-01 3.32754664e-02
5.31937897e-01 -8.34372044e-02 -7.29152858e-01 -5.50565898e-01
-1.28678536e+00 5.35981119e-01 1.74152598e-01 3.21990639e-01
-3.16420317e-01 -1.11836344e-01 3.02950710e-01 -6.24323729e-03
4.52834159e-01 1.07541792e-01 -1.56893432e-01 -1.26731202e-01
-1.26454246e+00 -1.08723957e-02 6.32847726e-01 1.07142353e+00
5.95499098e-01 2.64027476e-01 -2.89575994e-01 9.96999025e-01
2.34242156e-01 4.59947020e-01 5.69619715e-01 -8.36175561e-01
8.03196549e-01 3.72060426e-02 2.00143725e-01 -9.78316486e-01
-2.36836404e-01 -1.65954649e-01 -9.43966269e-01 2.01437008e-02
5.82058847e-01 -1.69622600e-01 -7.44388103e-01 2.14032769e+00
4.81083542e-01 5.88175654e-01 1.69554010e-01 1.11580205e+00
7.95474887e-01 6.52155876e-01 -2.14069828e-01 -6.27268136e-01
1.33375645e+00 -9.92447436e-01 -9.30934846e-01 -6.36938661e-02
8.91406387e-02 -7.70611048e-01 1.11718500e+00 2.39958093e-01
-1.13431668e+00 -8.22209895e-01 -7.92411745e-01 3.27350534e-02
3.32087949e-02 2.91406095e-01 3.66656363e-01 4.22127575e-01
-1.07572055e+00 2.43554562e-01 -5.16909301e-01 -2.37733364e-01
3.78328741e-01 2.73696870e-01 -5.98468542e-01 -1.92441761e-01
-1.11311018e+00 4.99423474e-01 2.08225220e-01 2.30305687e-01
-1.10392785e+00 -6.73714817e-01 -1.01415551e+00 1.31547421e-01
7.37583458e-01 -7.99845994e-01 1.12599003e+00 -1.08865869e+00
-1.92521763e+00 7.14955628e-01 -4.61201668e-01 -1.90130889e-01
8.38985145e-01 -9.04322267e-02 -3.20547402e-01 2.80106843e-01
-2.90478785e-02 7.84656644e-01 1.44810236e+00 -1.53306174e+00
-4.19488400e-01 -2.25614294e-01 6.76497221e-02 3.72559905e-01
-5.39920986e-01 -1.57805234e-01 -7.77138054e-01 -7.64915168e-01
-1.25507385e-01 -9.81091022e-01 1.63330570e-01 1.42620787e-01
-5.46380758e-01 -1.34345606e-01 7.74925828e-01 -6.80466712e-01
8.20993960e-01 -2.47763705e+00 3.36682111e-01 -1.25060022e-01
1.85242727e-01 1.85627952e-01 -2.68982589e-01 1.76036909e-01
-2.06849635e-01 -1.27688572e-01 -8.98072775e-03 -8.27957571e-01
-2.91181020e-02 -1.17420172e-02 -3.72583061e-01 6.54640913e-01
1.74237520e-01 7.21492767e-01 -8.89234483e-01 -6.56093478e-01
2.51907289e-01 7.30506301e-01 -5.33860445e-01 5.00707507e-01
-2.97855623e-02 8.66290689e-01 -3.39191884e-01 5.45122385e-01
6.32177591e-01 -1.15327306e-01 9.87017304e-02 -4.46241468e-01
-5.80476038e-03 3.68632935e-02 -1.21709716e+00 2.10684466e+00
-8.13948095e-01 6.33096278e-01 3.51187408e-01 -8.93680573e-01
7.51491487e-01 7.70821691e-01 5.27727902e-01 -4.02835935e-01
9.34658051e-02 9.64374244e-02 -2.00667724e-01 -8.06301475e-01
3.29428762e-01 -2.04094499e-01 4.49622646e-02 2.79203385e-01
1.61693543e-01 -5.77543825e-02 -8.75068456e-02 -1.28272027e-01
5.50922036e-01 2.43982092e-01 1.36840567e-01 2.45019570e-01
7.95759618e-01 -7.30128706e-01 6.08200192e-01 3.81027162e-01
-2.43920624e-01 9.26960826e-01 2.58338183e-01 1.75395593e-01
-1.01336992e+00 -9.44387674e-01 5.19386865e-02 9.64675605e-01
1.43089846e-01 -2.52068400e-01 -9.05696750e-01 -4.15092468e-01
-2.98376530e-01 4.87929642e-01 -4.68051940e-01 -2.36583427e-02
-5.04892468e-01 -3.84879798e-01 5.18697977e-01 1.94258809e-01
4.09896314e-01 -1.06817949e+00 -2.85065144e-01 -5.09275012e-02
-6.09488070e-01 -1.48008072e+00 -6.88302457e-01 -3.98509085e-01
-4.68945324e-01 -6.96165264e-01 -1.20549035e+00 -7.53600240e-01
6.78548038e-01 4.39248443e-01 6.53728306e-01 -2.29520276e-01
-1.80634111e-01 3.46674711e-01 -1.48914769e-01 1.15738593e-01
-4.77110088e-01 -6.85283467e-02 2.42569029e-01 7.62925684e-01
-2.45631084e-01 -7.33896375e-01 -6.63772106e-01 2.78646857e-01
-7.82952726e-01 3.54180366e-01 5.91525257e-01 9.97988641e-01
3.46376300e-01 -1.65619701e-01 7.62426496e-01 -3.03709507e-01
4.55815732e-01 -5.19546926e-01 -4.29942280e-01 2.15074643e-01
-1.31753966e-01 -8.66981000e-02 8.67120743e-01 -8.29367220e-01
-1.28664041e+00 1.63856998e-01 -9.07601267e-02 -1.05940437e+00
-2.21974507e-01 3.53087410e-02 -7.22154200e-01 8.70079249e-02
1.96705878e-01 3.37036639e-01 2.37069428e-01 -5.27590394e-01
6.79637194e-01 9.04807031e-01 7.41041005e-01 -4.40841824e-01
8.81646454e-01 5.64898849e-01 -1.73215345e-01 -9.03920114e-01
-5.14907479e-01 -3.84446949e-01 -4.09423500e-01 -3.28211814e-01
7.62026846e-01 -1.14430463e+00 -9.36973631e-01 5.46257675e-01
-1.17813575e+00 -3.73257212e-02 -1.36794582e-01 4.33450103e-01
-8.38172138e-01 5.29118538e-01 -2.58165300e-01 -8.57282043e-01
-9.03078914e-02 -1.34346688e+00 1.26206875e+00 1.57352343e-01
-1.32347103e-02 -6.36465788e-01 -1.49778441e-01 6.23468578e-01
1.62137866e-01 6.22110702e-02 5.32797337e-01 -4.93230402e-01
-7.14345932e-01 -6.57601431e-02 -1.40358672e-01 2.32146546e-01
4.61971372e-01 -8.13864172e-02 -1.51145947e+00 -3.85026693e-01
1.13574333e-01 -5.82178712e-01 5.48796654e-01 3.09067667e-01
1.28659189e+00 -4.91664797e-01 -2.27782607e-01 7.30610490e-01
9.45178092e-01 -1.20940566e-01 4.77208465e-01 -2.50176340e-01
9.24487293e-01 1.02632070e+00 7.61431217e-01 5.31429112e-01
3.75728101e-01 1.20740163e+00 3.79508704e-01 -2.76530415e-01
-4.36863452e-01 -5.09841383e-01 5.36340356e-01 9.51716661e-01
3.72542366e-02 -3.11687171e-01 -4.88087207e-01 6.86979711e-01
-1.73190248e+00 -1.16432786e+00 5.87994874e-01 2.26281309e+00
9.40089643e-01 -3.28204691e-01 2.05064312e-01 2.12102532e-01
1.05734098e+00 4.13045198e-01 -6.76234305e-01 1.81687519e-01
-5.75190522e-02 -2.17829555e-01 -1.83497258e-02 4.38978732e-01
-8.15186322e-01 8.78077269e-01 4.59934187e+00 1.10566807e+00
-1.35849178e+00 2.53041297e-01 5.95100939e-01 -4.22361463e-01
-3.06471169e-01 -2.85744637e-01 -6.97180152e-01 6.33358955e-01
7.86699057e-01 -2.17531770e-01 6.04555190e-01 7.27456272e-01
6.88337803e-01 2.44360149e-01 -1.19855142e+00 1.41292703e+00
3.62696558e-01 -1.12761879e+00 9.07436162e-02 5.52957542e-02
4.93432164e-01 -3.18430901e-01 2.98370898e-01 5.85443489e-02
-1.67299375e-01 -8.16816688e-01 9.58495140e-01 5.39114237e-01
1.29937148e+00 -7.15087652e-01 1.62159741e-01 4.31482136e-01
-1.14847636e+00 -1.63795859e-01 -6.73054233e-02 4.48417872e-01
3.59388918e-01 2.74119109e-01 -9.93774652e-01 6.27612412e-01
4.84368771e-01 6.53693438e-01 -2.86428571e-01 8.14798236e-01
-2.55848132e-02 2.49560609e-01 -2.18122259e-01 2.66996294e-01
-7.26039931e-02 4.48947623e-02 8.59734952e-01 8.50159585e-01
4.11338687e-01 -4.74828742e-02 1.03344485e-01 6.76423013e-01
-2.02483609e-01 1.92225412e-01 -9.09621239e-01 1.08549707e-01
5.83220482e-01 1.30450213e+00 -2.80169994e-01 -3.05747807e-01
-4.07777458e-01 9.11751151e-01 2.34485120e-01 5.41930497e-01
-9.22854781e-01 -1.07286341e-01 7.79030025e-01 7.76810125e-02
3.26077580e-01 3.11903507e-02 1.74720287e-01 -1.46564758e+00
2.74465322e-01 -1.20384848e+00 -9.91580188e-02 -8.94701898e-01
-1.18057895e+00 6.87741339e-01 -2.91658901e-02 -1.53120911e+00
-7.04129457e-01 -2.39189744e-01 -4.30045545e-01 7.67247200e-01
-1.50722468e+00 -1.56157982e+00 -4.52787519e-01 1.09427488e+00
9.19352889e-01 -1.62844986e-01 6.44317627e-01 3.72616351e-01
-6.07263684e-01 9.76427972e-01 -8.84351656e-02 -5.31496815e-02
1.00794148e+00 -5.88215351e-01 3.11245415e-02 7.85842478e-01
2.31555015e-01 4.84575808e-01 6.93011582e-01 -3.03618193e-01
-1.41207552e+00 -9.49475467e-01 5.84403098e-01 7.87511021e-02
6.77425504e-01 -6.67661190e-01 -8.61069262e-01 3.66656512e-01
1.49351895e-01 2.18025163e-01 5.66083729e-01 -2.00646088e-01
-2.72161454e-01 -4.24068063e-01 -9.58710790e-01 8.50388110e-01
1.13854778e+00 -7.84429967e-01 -4.69138294e-01 2.00884357e-01
7.36186445e-01 -2.62544185e-01 -6.40004337e-01 3.67991447e-01
6.13478422e-01 -9.75344181e-01 1.06557631e+00 -4.08945084e-01
2.98640162e-01 -2.58871734e-01 -6.39524236e-02 -1.19645214e+00
1.42350048e-01 -1.15571988e+00 -1.38688818e-01 1.76252389e+00
1.74112394e-01 -5.03951967e-01 5.38872778e-01 4.27663535e-01
-1.50954604e-01 -5.05321026e-01 -1.13269329e+00 -6.32145941e-01
-2.82353669e-01 -4.74394768e-01 7.60747492e-01 9.04836237e-01
-2.74991393e-02 2.13555768e-01 -9.80493724e-01 1.45241007e-01
5.81769705e-01 1.73834279e-01 1.08958423e+00 -9.96572852e-01
-4.74315226e-01 -1.83065727e-01 -3.43936682e-01 -1.27347183e+00
6.70685709e-01 -6.74869299e-01 3.33882660e-01 -9.72113848e-01
1.18964754e-01 -4.63034332e-01 -1.62248954e-01 3.51491243e-01
-1.63381502e-01 3.14162165e-01 4.32788044e-01 3.28015745e-01
-3.64827931e-01 9.09150660e-01 1.45313287e+00 -1.74360543e-01
-1.86772421e-01 9.56025869e-02 -5.77655494e-01 6.79914355e-01
4.67431307e-01 -2.58128911e-01 -7.05553830e-01 -2.60935903e-01
-2.25515172e-01 6.25712931e-01 5.66363931e-01 -8.74990880e-01
2.09888622e-01 -2.93905511e-02 1.26862168e-01 -2.79993653e-01
8.07290912e-01 -8.91402364e-01 1.64925188e-01 -7.85577819e-02
-2.71631449e-01 -3.56650114e-01 1.02291711e-01 7.64925420e-01
-3.83427322e-01 -4.12274897e-02 8.68497968e-01 1.67075455e-01
-4.78739947e-01 4.31043029e-01 1.04592284e-02 1.65985490e-03
1.00148809e+00 -2.78329372e-01 -2.03640368e-02 -7.92433619e-01
-7.67251551e-01 -9.68892500e-02 6.01421535e-01 7.93892622e-01
6.37215972e-01 -1.40250480e+00 -6.34770274e-01 2.90143162e-01
1.30916372e-01 2.43435856e-02 5.07350326e-01 9.77741838e-01
1.69162586e-01 2.39906043e-01 -2.70934910e-01 -8.48796129e-01
-1.30078673e+00 7.60929525e-01 1.03084125e-01 1.11608259e-01
-7.43003845e-01 6.03079855e-01 7.26686120e-01 1.16801515e-01
3.07259947e-01 -1.01615787e-02 -2.26426542e-01 2.66274244e-01
4.98595804e-01 1.18669711e-01 -1.33013651e-01 -9.82024908e-01
-1.93060830e-01 6.45641267e-01 -4.64086654e-03 -3.38930130e-01
1.11635005e+00 -5.14441073e-01 2.77859718e-01 6.14531577e-01
1.33116245e+00 3.05184960e-01 -1.64308977e+00 -2.05274776e-01
-4.23973233e-01 -4.84984159e-01 -2.08608106e-01 -2.71111786e-01
-1.28113794e+00 1.01905882e+00 5.34433365e-01 -1.45293459e-01
1.32394922e+00 3.73896658e-02 7.34693944e-01 7.90667683e-02
3.75258654e-01 -7.98370421e-01 2.16632426e-01 -1.70211554e-01
9.88157690e-01 -1.31885290e+00 -3.88111889e-01 -4.13247913e-01
-7.77992368e-01 8.96629035e-01 3.78384352e-01 3.53455812e-01
3.10853004e-01 4.68893647e-02 5.80082536e-02 2.41844878e-01
-7.13240802e-01 -1.90546483e-01 3.74815166e-01 6.43752933e-01
2.60921139e-02 -1.45681009e-01 1.68016389e-01 5.76389909e-01
-1.65508330e-01 8.03329498e-02 3.25211406e-01 3.20976704e-01
-1.21618640e-02 -8.73929858e-01 -4.85299498e-01 -1.63058817e-01
-4.56565917e-01 -9.40276906e-02 -1.05785012e-01 7.21061647e-01
3.15297069e-03 1.13169968e+00 -8.97597745e-02 -1.93969220e-01
1.37461811e-01 1.14248022e-01 3.71220827e-01 -4.05851483e-01
-1.43703461e-01 3.99594456e-01 1.69115921e-03 -6.39658093e-01
-4.69401568e-01 -7.01123774e-01 -8.50522757e-01 -1.25070393e-01
-4.32347894e-01 2.97986362e-02 5.92377782e-01 9.20010269e-01
5.34386516e-01 3.36225510e-01 1.01518476e+00 -1.35027897e+00
-5.90357244e-01 -1.04985368e+00 -4.33441728e-01 6.31238878e-01
6.82378292e-01 -9.89976287e-01 -5.76598167e-01 2.96076089e-01] | [13.197988510131836, -0.3605812191963196] |
585e4fb2-8ada-4454-b007-513daec7ed77 | noise-audits-improve-moral-foundation | 2210.07415 | null | https://arxiv.org/abs/2210.07415v1 | https://arxiv.org/pdf/2210.07415v1.pdf | Noise Audits Improve Moral Foundation Classification | Morality plays an important role in culture, identity, and emotion. Recent advances in natural language processing have shown that it is possible to classify moral values expressed in text at scale. Morality classification relies on human annotators to label the moral expressions in text, which provides training data to achieve state-of-the-art performance. However, these annotations are inherently subjective and some of the instances are hard to classify, resulting in noisy annotations due to error or lack of agreement. The presence of noise in training data harms the classifier's ability to accurately recognize moral foundations from text. We propose two metrics to audit the noise of annotations. The first metric is entropy of instance labels, which is a proxy measure of annotator disagreement about how the instance should be labeled. The second metric is the silhouette coefficient of a label assigned by an annotator to an instance. This metric leverages the idea that instances with the same label should have similar latent representations, and deviations from collective judgments are indicative of errors. Our experiments on three widely used moral foundations datasets show that removing noisy annotations based on the proposed metrics improves classification performance. | ['Kristina Lerman', 'Fred Morstatter', 'Bahareh Harandizadeh', 'Frederic R. Hopp', 'Negar Mokhberian'] | 2022-10-13 | null | null | null | null | ['culture'] | ['speech'] | [ 1.63357362e-01 6.45186007e-01 -4.12564397e-01 -7.68125594e-01
-6.10296667e-01 -5.94595551e-01 4.81848180e-01 6.55753493e-01
-5.60499549e-01 8.18035305e-01 7.38893986e-01 4.59417552e-01
1.58697724e-01 -5.48939347e-01 -5.48234731e-02 -8.75127375e-01
4.44627166e-01 2.56679237e-01 -6.13095999e-01 -7.09273443e-02
5.12152910e-01 -2.87482381e-01 -1.27457130e+00 4.69611913e-01
9.88484323e-01 1.14249551e+00 -6.73637271e-01 2.03582138e-01
-1.86076667e-02 1.45277560e+00 -9.29918468e-01 -1.02696335e+00
5.98693192e-02 -5.13130069e-01 -9.96269941e-01 -1.96520805e-01
2.74853259e-01 -4.88364622e-02 3.08996677e-01 1.31242490e+00
1.43870190e-01 -1.09971814e-01 1.30189812e+00 -1.48205352e+00
-1.02320492e+00 6.51502311e-01 -3.40069711e-01 -2.33538970e-01
4.68441486e-01 -2.29907990e-01 1.65473080e+00 -4.65514302e-01
6.53089523e-01 1.16878700e+00 1.03674757e+00 7.22877562e-01
-1.17313278e+00 -6.72615826e-01 -1.40301973e-01 -9.07019600e-02
-1.11344671e+00 -3.66213381e-01 7.43124187e-01 -1.13148284e+00
2.49951944e-01 1.63895324e-01 4.40679789e-01 1.28812134e+00
4.37431931e-02 3.76900375e-01 1.44248700e+00 -3.42916101e-01
5.42196274e-01 3.72987837e-01 3.07004273e-01 5.45954764e-01
3.65197361e-01 -4.23086643e-01 -6.74240053e-01 -5.32078743e-01
2.31616542e-01 -1.06700376e-01 -1.67915776e-01 -1.83167588e-02
-1.17861307e+00 1.05187643e+00 4.33767796e-01 1.21625647e-01
-4.42533642e-01 2.16606379e-01 7.47192919e-01 1.55128852e-01
7.71454930e-01 9.08828557e-01 -1.66762844e-01 -5.30270040e-01
-7.83306003e-01 9.99777541e-02 9.82987046e-01 3.90743166e-01
6.27385020e-01 -5.08034408e-01 -3.51075739e-01 1.06244791e+00
5.95529787e-02 2.94571102e-01 5.98739088e-01 -1.51915097e+00
1.54691681e-01 1.08195353e+00 3.52099359e-01 -1.40039134e+00
-3.77882957e-01 -1.54338866e-01 -7.91351557e-01 1.75624445e-01
6.32103920e-01 -1.95011318e-01 -1.95938140e-01 2.02533627e+00
5.47662377e-02 -4.40478057e-01 2.60235578e-01 1.16685522e+00
8.54676425e-01 2.85798490e-01 3.83479625e-01 -1.37286901e-01
1.32904124e+00 -5.88884473e-01 -9.22698319e-01 -1.46314964e-01
1.14432251e+00 -7.15356290e-01 9.40341473e-01 2.12246418e-01
-6.96003318e-01 3.20716575e-02 -8.37247908e-01 -9.60047543e-02
-2.14256957e-01 2.57026106e-01 7.41417527e-01 5.83394706e-01
-4.78517354e-01 7.81633914e-01 -2.16357440e-01 -4.52608526e-01
5.91073632e-01 3.04447431e-02 -6.09131992e-01 3.23688656e-01
-1.22152138e+00 9.16745543e-01 9.55287516e-02 -4.70182747e-02
-2.64307290e-01 -3.42411280e-01 -6.80385351e-01 1.77033525e-02
1.21429525e-01 -1.92890048e-01 1.03470886e+00 -1.48802090e+00
-9.81461167e-01 1.50936806e+00 2.79154964e-02 -1.34741411e-01
5.81850231e-01 -2.45125219e-01 -2.38270968e-01 -5.59035055e-02
6.27475858e-01 5.39185464e-01 5.59743643e-01 -1.41508520e+00
-4.37140882e-01 -2.93224394e-01 -1.14024011e-02 2.04147235e-01
-7.40213573e-01 -4.99672964e-02 6.12470329e-01 -5.52989364e-01
1.33011907e-01 -9.26169276e-01 2.01726839e-01 5.49783669e-02
-4.11805391e-01 -5.42520165e-01 3.20048004e-01 -5.19512773e-01
1.31783259e+00 -2.17321730e+00 -1.31098747e-01 1.55466288e-01
4.26566839e-01 -2.34807983e-01 3.29945683e-01 3.99292201e-01
8.35280716e-02 5.11169076e-01 -1.80996850e-01 -2.74856359e-01
2.88183808e-01 2.38045931e-01 -4.04563606e-01 4.98625815e-01
-8.79408605e-03 4.22303140e-01 -1.13704038e+00 -6.94374263e-01
-4.24950480e-01 1.28284112e-01 -5.21008611e-01 1.17997967e-01
1.12408020e-01 3.13204259e-01 -2.34125018e-01 7.01712549e-01
1.53089091e-01 -3.73927206e-01 2.28764489e-01 -1.43924728e-01
2.73370892e-01 4.21812028e-01 -6.25054121e-01 1.08687532e+00
-1.50928810e-01 6.90899551e-01 -2.07232535e-01 -9.80382085e-01
1.29581416e+00 4.29702997e-01 4.09011632e-01 -4.52687591e-01
2.81369269e-01 3.56428742e-01 -1.99080348e-01 -5.17537236e-01
7.20219612e-01 -4.30564255e-01 -6.95897341e-01 8.78108919e-01
-2.74688631e-01 -1.68602914e-02 5.40521853e-02 2.61823833e-01
1.05990636e+00 3.66949812e-02 4.46948320e-01 -3.49527925e-01
2.61100590e-01 3.92888635e-02 1.16064322e+00 5.75669646e-01
-7.07065165e-01 3.12353969e-01 1.19094741e+00 -7.10092127e-01
-1.03983915e+00 -7.24499762e-01 -1.18085720e-01 1.39806998e+00
3.82706942e-03 -5.33200800e-01 -8.14477384e-01 -9.54977334e-01
6.64143860e-02 7.05293238e-01 -1.11820889e+00 -3.19633186e-01
-3.63153517e-02 -7.10299015e-01 7.84575284e-01 4.66601551e-01
2.44446501e-01 -9.17715609e-01 -8.88618410e-01 -1.22528881e-01
-6.28945887e-01 -1.06354058e+00 -5.91527857e-02 3.22380304e-01
-4.66163903e-01 -1.07662618e+00 -3.24760348e-01 -5.20368934e-01
1.04149747e+00 -1.76338762e-01 1.20152104e+00 3.83333355e-01
9.93991420e-02 1.47388518e-01 -6.04274392e-01 -2.39274040e-01
-7.44506836e-01 -6.70556948e-02 3.06289136e-01 1.34296846e-02
9.55854237e-01 -5.10878116e-02 -4.72759664e-01 3.27877253e-01
-6.53874278e-01 -1.12125710e-01 -5.45703135e-02 1.03024006e+00
9.33511481e-02 -2.37571388e-01 6.77707613e-01 -9.92527723e-01
1.00311112e+00 -5.05000114e-01 1.26592964e-01 2.32322633e-01
-6.89244211e-01 -8.43860880e-02 7.02235401e-01 -1.62047908e-01
-7.78834820e-01 -2.65225410e-01 4.01797563e-01 2.11429253e-01
-1.95481740e-02 4.10447687e-01 4.54008788e-01 4.23304647e-01
8.91744435e-01 -5.56517661e-01 3.11063416e-02 -8.67045820e-02
1.95188820e-02 1.05934799e+00 4.23989862e-01 -8.41921628e-01
2.81437993e-01 4.69265342e-01 -1.61856875e-01 -2.75201023e-01
-1.75986612e+00 -5.06583273e-01 -6.26109838e-01 -5.57401240e-01
1.02081430e+00 -9.08628583e-01 -9.52981830e-01 1.02991812e-01
-1.11150980e+00 -9.17276889e-02 -2.81810433e-01 4.60697085e-01
-4.92676437e-01 2.01386407e-01 -5.28278291e-01 -1.07304716e+00
-3.88174504e-01 -8.21994603e-01 9.25912142e-01 2.82030672e-01
-1.28176749e+00 -1.13627636e+00 8.91193375e-02 8.01605165e-01
-1.63763054e-02 5.92692256e-01 1.06901670e+00 -8.88230920e-01
5.77801645e-01 -5.23034871e-01 -1.13357663e-01 5.82522988e-01
1.33744985e-01 9.96846184e-02 -1.11507452e+00 8.87781605e-02
-1.89541858e-02 -1.09559834e+00 7.32700944e-01 -9.64998826e-02
8.49146962e-01 -6.53050423e-01 -9.48759690e-02 1.48888364e-01
1.06429386e+00 -2.53350496e-01 4.12469029e-01 5.88542938e-01
5.85019946e-01 1.10554707e+00 7.13880897e-01 8.12339842e-01
5.44874191e-01 4.89261746e-01 2.16492295e-01 5.43090291e-02
5.99823534e-01 -1.87194571e-01 5.19081235e-01 5.54284751e-01
-3.08113992e-01 2.49475688e-01 -1.19014585e+00 3.29261512e-01
-2.09510779e+00 -1.26783812e+00 -2.08659694e-01 2.15810728e+00
1.18399489e+00 -3.03092469e-02 -3.69609590e-03 3.36522013e-01
8.85992348e-01 1.42226052e-02 -1.64106518e-01 -9.40764129e-01
-2.75242832e-02 -3.86576742e-01 4.23651397e-01 3.18923444e-01
-1.14399254e+00 9.10576642e-01 6.27484703e+00 3.96658033e-01
-7.34293997e-01 5.92782982e-02 9.34233308e-01 -7.98612982e-02
-2.52723247e-01 2.16465406e-02 -4.48244572e-01 5.46114445e-01
4.80455279e-01 -1.91579446e-01 8.33642259e-02 1.03058517e+00
1.21067911e-01 -1.97213918e-01 -1.33225441e+00 8.16137850e-01
3.50357413e-01 -8.50096464e-01 -2.79900819e-01 7.09112063e-02
9.44192171e-01 -5.14136612e-01 2.81479936e-02 3.23755860e-01
5.78062296e-01 -1.26074111e+00 9.05954421e-01 5.89938521e-01
7.22203791e-01 -5.97124934e-01 1.20456111e+00 2.65075803e-01
-4.12258118e-01 -2.58834571e-01 -4.64970142e-01 -5.94544411e-01
-1.75770983e-01 7.48684287e-01 -8.46542478e-01 -2.32670233e-01
7.78587222e-01 7.10059643e-01 -5.04429936e-01 3.90301168e-01
-5.01696229e-01 5.15912592e-01 4.27768603e-02 -2.35658541e-01
2.52165079e-01 -2.49737024e-01 4.83848304e-02 1.09847748e+00
2.40162387e-02 -5.44849038e-02 1.42657995e-01 1.02554274e+00
-4.45088178e-01 2.27421820e-01 -5.66653609e-01 -2.60802627e-01
4.86701846e-01 1.44694924e+00 -6.01544023e-01 -3.49959999e-01
-2.31428191e-01 8.69413972e-01 6.30460560e-01 1.89950034e-01
-6.97108448e-01 -2.12748736e-01 6.12347126e-01 -2.04324320e-01
-5.07489860e-01 3.01329046e-01 -8.81171584e-01 -9.69819725e-01
3.57818976e-02 -7.49850333e-01 5.07159591e-01 -7.58554697e-01
-1.87547100e+00 2.73794144e-01 -5.48708558e-01 -1.17578685e+00
-1.00365736e-01 -4.68749344e-01 -4.67519850e-01 5.06071270e-01
-1.00432718e+00 -8.35547090e-01 -7.16342449e-01 4.05480489e-02
-2.94119775e-01 -9.87202823e-02 1.21650982e+00 -1.64371312e-01
-3.93908292e-01 6.85185790e-01 5.06415628e-02 7.20122218e-01
1.31343138e+00 -1.35613430e+00 -2.70523578e-01 1.05161481e-01
-2.75380820e-01 6.55714214e-01 7.98520863e-01 -6.53712332e-01
-3.51945579e-01 -6.95846081e-01 1.25921106e+00 -6.60729945e-01
7.24460840e-01 -1.90978006e-01 -8.09576511e-01 4.84720409e-01
-2.59763956e-01 -4.88254800e-02 1.60812032e+00 4.82424527e-01
-9.29572165e-01 1.77022904e-01 -1.31627584e+00 5.03968000e-01
7.78702855e-01 -7.40930259e-01 -8.64503980e-01 5.18375218e-01
8.18660334e-02 1.53660715e-01 -1.13017821e+00 1.11382827e-01
8.80438268e-01 -1.08816266e+00 4.25984412e-01 -7.40783513e-01
1.14445376e+00 -3.91009338e-02 -3.58956069e-01 -1.28369236e+00
-4.11340445e-01 -2.85676241e-01 4.00505751e-01 1.39961100e+00
3.77306402e-01 -2.87215918e-01 6.42489731e-01 1.38065898e+00
2.96155006e-01 -7.91412175e-01 -8.82776320e-01 -6.51350200e-01
3.33506942e-01 -8.68556127e-02 4.01032299e-01 1.68736088e+00
8.11233997e-01 5.40344000e-01 -3.57340455e-01 -4.63953674e-01
5.16915321e-01 -4.21675928e-02 6.06145561e-01 -1.77660596e+00
2.89853990e-01 -5.73598921e-01 -6.31523550e-01 -2.22208619e-01
6.29708588e-01 -1.16746128e+00 4.03939970e-02 -1.63988590e+00
5.50440311e-01 -5.46231627e-01 -9.66142640e-02 7.05815136e-01
-3.10092330e-01 4.97797102e-01 5.30626485e-03 7.74509132e-01
-8.46884131e-01 5.37821233e-01 8.39011192e-01 -4.56480943e-02
5.55761904e-02 -6.47955477e-01 -9.49797273e-01 1.28686392e+00
7.71915019e-01 -8.40064168e-01 1.70437083e-01 -9.29871500e-02
8.13129663e-01 -4.24571812e-01 5.53423405e-01 -8.19900930e-01
-5.06796082e-03 -2.77624130e-01 4.98465806e-01 1.90085933e-01
3.40661883e-01 -6.98914349e-01 -2.20244825e-01 3.60179305e-01
-1.03892756e+00 -1.29800454e-01 -6.98010445e-01 3.43115926e-01
-2.79751897e-01 -5.60820997e-01 8.46996188e-01 -2.78688550e-01
-2.54240900e-01 -4.03926551e-01 -1.61573052e-01 5.03104150e-01
1.08551228e+00 -1.47912934e-01 -8.14447582e-01 -5.00277698e-01
-3.66050422e-01 9.11034569e-02 1.08142722e+00 2.37033233e-01
1.20276339e-01 -1.57662928e+00 -7.77938783e-01 -4.15433496e-01
6.59105062e-01 -5.12177467e-01 -2.02596501e-01 8.84075582e-01
-4.11453724e-01 -1.94551460e-02 -1.32368758e-01 -4.13777709e-01
-1.19765651e+00 4.54332456e-02 2.03132927e-01 -1.10498950e-01
-2.78713077e-01 8.70923460e-01 5.95808737e-02 -4.12698627e-01
1.53847292e-01 3.47183496e-02 -4.41187441e-01 5.37396550e-01
2.67761499e-01 4.23642278e-01 -4.57403600e-01 -1.10518265e+00
-5.11761248e-01 5.80893576e-01 7.79375783e-04 2.68569384e-02
1.18427980e+00 9.73432139e-02 -5.11100709e-01 9.58146930e-01
1.10703146e+00 -1.42187491e-01 -8.29301298e-01 -1.12260304e-01
2.49379158e-01 -5.98426759e-01 -7.60410503e-02 -8.90462637e-01
-4.82737452e-01 8.01065385e-01 5.54984882e-02 3.85486186e-01
5.10232568e-01 -2.35253751e-01 5.71650207e-01 4.99042213e-01
3.27383518e-01 -2.01029825e+00 3.77008766e-01 5.99625230e-01
6.87958241e-01 -1.54500997e+00 2.07178995e-01 -1.20983280e-01
-1.42033875e+00 1.13090098e+00 7.27523744e-01 9.88035575e-02
1.15937009e-01 -9.31919931e-05 5.17251015e-01 -2.66863167e-01
-7.04052329e-01 2.90299594e-01 9.90354568e-02 2.36159816e-01
1.04196680e+00 4.10161823e-01 -6.01946592e-01 9.11955595e-01
-5.45993805e-01 -9.97392088e-02 8.14288676e-01 6.44625664e-01
-4.66474116e-01 -5.34908950e-01 -4.79227632e-01 6.28049672e-01
-8.39673281e-01 1.00484394e-01 -9.48688447e-01 1.09913468e-01
1.05371423e-01 1.09268546e+00 -1.15879960e-02 -4.40240264e-01
-1.18924499e-01 3.60366344e-01 3.46984714e-03 -6.02653682e-01
-8.02304149e-01 -6.40644073e-01 3.83022130e-01 -4.57460642e-01
-7.11484671e-01 -6.16721213e-01 -1.51405299e+00 -3.90103608e-01
-1.44802764e-01 4.67474580e-01 4.74916846e-01 1.04992855e+00
1.29265785e-01 4.20330651e-02 5.17532766e-01 -1.69244885e-01
-7.95939624e-01 -8.74880195e-01 -6.12526894e-01 1.24677730e+00
1.31597608e-01 -8.79612684e-01 -8.84091914e-01 2.41690323e-01] | [9.138702392578125, 10.11815071105957] |
7d265cc2-b5fa-46a9-8848-0b5ccd4b0ddd | validity-of-web-based-self-directed | 2208.04841 | null | https://arxiv.org/abs/2208.04841v1 | https://arxiv.org/pdf/2208.04841v1.pdf | Validity of Web-based, Self-directed, NeuroCognitive Performance Test in MCI | Digital cognitive tests offer several potential advantages over established paper-pencil tests but have not yet been fully evaluated for the clinical evaluation of mild cognitive impairment. The NeuroCognitive Performance Test (NCPT) is a web-based, self-directed, modular battery intended for repeated assessments of multiple cognitive domains. Our objective was to examine its relationship with the ADAS-Cog and MMSE as well as with established paper-pencil tests of cognition and daily functioning in MCI. We used Spearman correlations, regressions and principal components analysis followed by a factor analysis (varimax rotated) to examine our objectives. In MCI subjects, the NCPT composite is significantly correlated with both a composite measure of established tests (r=0.78, p<0.0001) as well as with the ADAS-Cog (r=0.55, p<0.0001). Both NCPT and paper-pencil test batteries had a similar factor structure that included a large g component with a high eigenvalue. The correlation for the analogous tests (e.g. Trails A and B, learning memory tests) were significant (p<0.0001). Further, both the NCPT and established tests significantly (p< 0.01) predicted the University of California San Diego Performance-Based Skills Assessment and Functional Activities Questionnaire, measures of daily functioning. The NCPT, a web-based, self-directed, computerized test, shows high concurrent validity with established tests and hence offers promise for use as a research or clinical tool in MCI. Despite limitations such as a relatively small sample, absence of control group and cross-sectional nature, these findings are consistent with the growing literature on the promise of self-directed, web-based cognitive assessments for MCI. | ['Davangere P. Devanand', 'Joel Sneed', 'Howards Andrews', 'Jeffrey R. Petrella', 'Andrew M. Michael', 'Caroline Hellegers', 'Charlie Ndouli', 'Julia Phillips', "Jessica D'Antonio", 'Izael Nino', 'Adaora Nwosu', 'Alexandra R. Linares', 'Min Qian', 'Terry E. Goldberg', 'P. Murali Doraiswamy'] | 2022-07-11 | null | null | null | null | ['skills-assessment'] | ['computer-vision'] | [-4.65591699e-01 -3.89476717e-01 -3.14416796e-01 -2.70224452e-01
-8.23328197e-01 -6.63870871e-01 3.76588792e-01 3.72643411e-01
-9.27829087e-01 1.07364142e+00 3.23665738e-01 -7.07126796e-01
-8.19271922e-01 -7.87985086e-01 -6.95746467e-02 1.36079311e-01
-7.10999787e-01 6.82410479e-01 3.14352512e-01 1.06172718e-01
2.00165480e-01 4.08935219e-01 -1.18911541e+00 -4.15547863e-02
1.15053463e+00 7.50344992e-01 4.87046599e-01 5.03944278e-01
-5.25393616e-03 6.90059781e-01 -4.67166543e-01 -2.32321665e-01
-2.60413706e-01 -3.70947301e-01 -6.14095867e-01 1.34233117e-01
1.46025240e-01 -8.91399264e-01 -3.55201125e-01 5.29212117e-01
6.01612508e-01 2.83144355e-01 2.65003234e-01 -8.63497913e-01
-8.95350873e-01 -1.31547153e-01 5.38906120e-02 4.46694314e-01
6.56513512e-01 3.26811910e-01 5.99588156e-01 -1.12589180e+00
3.42703223e-01 9.85918701e-01 7.74462998e-01 5.19854054e-02
-1.18988872e+00 -8.24954927e-01 -1.61832571e-01 7.13332295e-01
-1.03513718e+00 -1.90644994e-01 -4.38612401e-02 -5.43452919e-01
8.47830653e-01 3.32912683e-01 1.35804975e+00 4.20591891e-01
6.02382362e-01 1.53722176e-02 1.85055387e+00 -1.38082117e-01
5.67643523e-01 -1.15745716e-01 5.59740424e-01 4.39391673e-01
8.87865007e-01 1.34870008e-01 -6.02851845e-02 -4.66277272e-01
8.48345697e-01 2.36712664e-01 -1.70307517e-01 -1.84904528e-03
-1.01537442e+00 6.30820870e-01 1.07218206e-01 5.43356717e-01
-5.90372980e-01 -2.49857038e-01 4.04356837e-01 4.83140409e-01
3.82037126e-02 -1.74634904e-02 -1.72928035e-01 -5.21364689e-01
-1.02622378e+00 4.05968040e-01 7.05917776e-01 1.93233892e-01
-8.29429552e-02 1.26757547e-01 -5.11832654e-01 8.27289104e-01
6.02167666e-01 8.49888325e-01 7.30473161e-01 -8.21063161e-01
2.34702870e-01 5.66452086e-01 1.69168383e-01 -4.79197145e-01
-9.80959415e-01 -8.80719423e-01 -2.15728328e-01 9.57784534e-01
5.44928193e-01 -1.25003055e-01 -5.13453543e-01 1.41880190e+00
-3.16718280e-01 -5.53146958e-01 -2.74246335e-01 1.10128415e+00
2.30553284e-01 -2.71693081e-01 4.89633411e-01 -4.03469145e-01
1.66185975e+00 -4.01586741e-01 -6.01310790e-01 -5.36998749e-01
5.72834015e-01 -4.81854498e-01 1.25259888e+00 3.23690772e-01
-1.32759690e+00 -4.19965148e-01 -1.01991904e+00 8.96480083e-02
-3.08780313e-01 6.72600791e-02 4.38323110e-01 1.34691107e+00
-1.44339025e+00 5.04258633e-01 -9.94144738e-01 -4.97279495e-01
5.33001125e-01 2.39387944e-01 -4.62977916e-01 -6.35506749e-01
-6.90155089e-01 1.25565374e+00 3.43016148e-01 -2.29559034e-01
-2.84951359e-01 -4.07799333e-01 -2.79439658e-01 8.63931999e-02
-5.50089888e-02 -8.12117100e-01 1.02817357e+00 -5.83981752e-01
-1.20964539e+00 5.47622621e-01 -2.23620668e-01 -1.96932361e-01
3.60338479e-01 -9.10612568e-02 -9.01779354e-01 5.47528684e-01
5.55838883e-01 7.15243518e-02 2.75539104e-02 -2.08496436e-01
-6.18289530e-01 -1.01359332e+00 7.22464696e-02 4.79624987e-01
-4.61471140e-01 1.93160307e-02 3.98625880e-01 -3.63296688e-01
4.23345387e-01 -6.74675822e-01 1.24053463e-01 3.40378702e-01
2.51513124e-01 7.54486471e-02 3.83134991e-01 -1.25109076e+00
8.96550953e-01 -1.67155647e+00 -7.29904950e-01 4.98383850e-01
5.71579576e-01 1.32497042e-01 4.68872115e-02 2.56945878e-01
5.12987338e-02 3.21955562e-01 3.48703489e-02 3.80989283e-01
5.50647937e-02 1.50012961e-02 8.14776361e-01 5.95400333e-01
-7.75911212e-02 1.17871153e+00 -9.96406615e-01 -1.98140666e-01
2.78422475e-01 4.10788506e-01 -2.40119830e-01 -3.33123565e-01
4.83792394e-01 1.01691142e-01 -1.57881513e-01 2.91661054e-01
6.90919101e-01 -1.64610907e-01 5.14363170e-01 5.36698818e-01
-5.24038315e-01 3.98593158e-01 -6.26916707e-01 1.20989597e+00
3.73735905e-01 5.17230749e-01 -5.41785359e-02 -6.01147771e-01
1.00913811e+00 3.92734289e-01 1.96716473e-01 -1.40726697e+00
-1.31142497e-01 3.55405509e-01 5.65599382e-01 -2.89749265e-01
-2.88814694e-01 -5.98451555e-01 6.09919131e-01 4.96809721e-01
-2.11956725e-01 7.07663953e-01 6.39447272e-01 1.42473429e-01
1.68632841e+00 -1.66647777e-01 6.45174205e-01 -4.91344094e-01
4.66235340e-01 -2.48426218e-02 2.03494176e-01 8.48914623e-01
-3.31510633e-01 2.73272276e-01 5.07380366e-01 1.76943496e-01
-8.00845027e-01 -1.51929259e+00 -3.65047872e-01 5.35923660e-01
-5.52033901e-01 -3.51112902e-01 -2.58246064e-01 -2.35624686e-01
4.51305419e-01 8.83042634e-01 -1.62964940e-01 -1.15582302e-01
-7.68521056e-02 -5.35328925e-01 3.48076284e-01 9.11046147e-01
9.68565166e-01 -4.00229514e-01 -4.41968530e-01 5.98924816e-01
-1.13998335e-02 -6.50013924e-01 -1.70286417e-01 -2.50830144e-01
-1.57224238e+00 -1.32492173e+00 -1.01062644e+00 -7.37652898e-01
3.81120741e-01 4.84059036e-01 9.37910438e-01 2.21876223e-02
2.20518023e-01 1.05145490e+00 -2.09250465e-01 -8.45541283e-02
1.13709614e-01 -4.67401892e-01 -6.37523606e-02 -6.73410773e-01
4.71892625e-01 -8.85336876e-01 -1.00772703e+00 3.63966733e-01
-6.22235715e-01 -2.59182245e-01 1.19563603e+00 3.20070654e-01
3.80533367e-01 -3.19485247e-01 7.49771714e-01 -3.75211984e-02
1.01215458e+00 -5.83285689e-01 -1.40342847e-01 3.57762650e-02
-1.22833538e+00 -5.02794683e-01 1.99421510e-01 -4.51978832e-01
-8.66223156e-01 -8.10423851e-01 9.17370841e-02 5.36624014e-01
-2.35925063e-01 1.00077808e+00 3.34659964e-02 -2.78339714e-01
5.72348058e-01 2.45799720e-01 4.64291155e-01 -5.63586414e-01
-3.24698091e-01 5.13899505e-01 3.93447548e-01 -4.12417293e-01
7.24572062e-01 9.32128131e-02 1.27497226e-01 -9.33510065e-01
-1.69636235e-01 -3.43849808e-01 -4.90427554e-01 -2.71848857e-01
7.49670029e-01 -1.02376342e+00 -1.03010380e+00 1.75057799e-01
-3.43163401e-01 -4.31872159e-01 1.31287813e-01 1.41672337e+00
-4.49623317e-01 3.52179497e-01 -4.93996084e-01 -6.67596817e-01
-4.57877845e-01 -6.44454718e-01 -1.47705609e-02 6.72481135e-02
-7.21531689e-01 -8.74868155e-01 2.61768132e-01 2.80251920e-01
6.14506662e-01 2.16800705e-01 1.08789766e+00 -6.84219956e-01
-3.92568678e-01 -7.49913752e-01 -5.63210607e-01 1.03698261e-01
2.38431871e-01 -1.06664181e+00 1.74293712e-01 -3.74866217e-01
4.57437664e-01 -7.04978853e-02 1.01187915e-01 3.87184948e-01
1.59773737e-01 6.47606254e-02 9.47140530e-02 -1.79875001e-01
1.32686067e+00 6.62917852e-01 1.07323003e+00 1.22204506e+00
-7.27619529e-02 -1.17712297e-01 1.78087920e-01 7.84359574e-02
6.11058354e-01 4.64651704e-01 -1.69840142e-01 4.83247727e-01
-3.13147396e-01 3.78674388e-01 5.08256018e-01 4.68196929e-01
-3.33610564e-01 4.05287087e-01 -1.13370609e+00 -9.79780480e-02
-1.36633706e+00 -9.67411339e-01 -5.49437761e-01 2.60258055e+00
2.53649861e-01 5.59990346e-01 6.50665820e-01 2.29592815e-01
5.20170748e-01 -3.55104059e-01 -8.07398260e-01 1.34220487e-02
-2.98243672e-01 4.03272063e-01 3.09407651e-01 3.33280377e-02
-2.29653254e-01 3.01915333e-02 6.43609810e+00 -1.39761895e-01
-4.55566317e-01 4.50426370e-01 3.22366208e-01 -5.95793009e-01
1.41483814e-01 1.16922088e-01 -1.67035386e-01 3.11279267e-01
1.48190856e+00 -8.17124188e-01 5.92435718e-01 3.97397250e-01
8.36404800e-01 -5.57690561e-01 -7.27879882e-01 6.71685219e-01
-9.95203406e-02 -8.03972065e-01 -5.13744414e-01 4.09331977e-01
3.99827734e-02 1.19583204e-01 -3.01610562e-03 4.31259036e-01
-2.25396305e-01 -6.45282745e-01 8.78210306e-01 9.15788174e-01
1.06229913e+00 -4.70849544e-01 6.65279925e-01 -3.32215875e-01
-1.10105240e+00 -1.34182885e-01 -9.85548124e-02 -8.78046155e-01
2.32364818e-01 6.57280922e-01 -4.27979201e-01 -6.54605702e-02
5.93643486e-01 1.83194250e-01 -6.68760836e-01 1.60667789e+00
-2.43698165e-01 6.67669713e-01 -4.08078209e-02 -1.76237568e-01
2.35058129e-01 -1.99720755e-01 3.59458655e-01 6.90061092e-01
6.07880473e-01 4.56562877e-01 -5.96847571e-02 7.36229241e-01
4.36182022e-01 1.96661726e-01 1.55197784e-01 -4.41833675e-01
3.81771833e-01 8.10467422e-01 -1.06471109e+00 -4.60213929e-01
-1.11524439e+00 5.40946066e-01 1.33023113e-01 5.55013299e-01
-2.31341243e-01 -2.18894303e-01 4.21601504e-01 7.23105729e-01
-7.14370236e-02 -9.37027335e-01 -7.77462423e-01 -6.54570520e-01
5.03235400e-01 -9.59267914e-01 4.81441766e-01 -9.34655190e-01
-8.79453719e-01 -5.83009496e-02 -2.96484530e-01 -9.73938823e-01
1.43098589e-02 -5.88605404e-01 -5.26733637e-01 1.39270484e+00
-9.68298733e-01 -4.95484591e-01 -4.99542564e-01 6.93521321e-01
-1.16951130e-02 -8.42035806e-04 1.06409001e+00 1.67661849e-02
-3.23361337e-01 1.32082194e-01 5.87936819e-01 1.56745747e-01
6.69142306e-01 -1.23391354e+00 -9.77090374e-02 5.06242692e-01
-9.10540283e-01 8.42712581e-01 1.08114786e-01 -1.56643307e+00
-1.35443461e+00 -7.28855610e-01 7.71557033e-01 2.02028211e-02
6.37650728e-01 2.69521326e-01 -8.04585576e-01 8.16723943e-01
-3.17273229e-01 -7.60543764e-01 1.07230651e+00 2.15616897e-01
-4.14771028e-02 5.24793193e-02 -1.32379830e+00 6.73569262e-01
1.19475925e+00 -6.42218709e-01 -7.90770710e-01 3.77425134e-01
-9.31049362e-02 2.35125497e-01 -1.29088295e+00 -6.75533786e-02
1.18204951e+00 -1.06530201e+00 1.09981990e+00 -3.29959840e-01
1.05231389e-01 7.36621693e-02 -5.14065921e-02 -1.03518391e+00
-1.12005210e+00 1.52616739e-01 3.04784961e-02 8.62304032e-01
9.57076848e-02 -1.33478451e+00 7.76334703e-01 1.37431860e+00
-2.92424709e-01 -1.61777541e-01 -9.78172958e-01 -1.27471972e+00
1.93384647e-01 -3.56865019e-01 7.85748437e-02 4.02083248e-01
6.66294575e-01 1.58275634e-01 4.72377062e-01 -2.59800348e-02
7.14201629e-01 -5.82441390e-01 3.79484966e-02 -1.74415004e+00
-7.55711645e-02 -6.32421494e-01 -9.12833691e-01 -6.87894821e-02
-4.07436341e-01 -1.17934823e+00 -1.10411489e+00 -2.23755360e+00
3.58435601e-01 1.57220632e-01 -6.54550865e-02 3.34225148e-01
-7.46449456e-02 -1.79170325e-01 3.10066134e-01 2.59959102e-01
-3.57721120e-01 3.27346623e-01 7.70669878e-01 3.33801284e-02
-6.39823079e-01 -1.78627864e-01 -1.28461039e+00 2.29840875e-01
1.37826383e+00 -3.23438495e-01 -5.58890760e-01 -1.86658084e-01
-7.44476616e-02 2.77676880e-01 5.94053030e-01 -1.54810238e+00
1.06845878e-01 1.28800711e-02 1.34781015e+00 -3.51981103e-01
3.79581213e-01 -4.97196347e-01 3.51062596e-01 9.93554056e-01
1.72116056e-01 4.75118101e-01 3.93451840e-01 9.00942013e-02
3.23399067e-01 -2.91343421e-01 3.57807279e-01 -3.25707972e-01
-4.79591697e-01 -1.22261740e-01 -1.09370828e+00 -8.18498582e-02
5.94290137e-01 -5.78235984e-01 -7.43155479e-01 -6.39235258e-01
-1.01636970e+00 1.53908553e-02 2.91616738e-01 1.00334764e-01
6.99422657e-01 -1.39600360e+00 -6.16054833e-01 -2.52279729e-01
-2.31783748e-01 -9.20877457e-01 2.81801939e-01 1.37772214e+00
-5.55253148e-01 8.69470537e-01 -7.57848501e-01 5.30113466e-02
-8.68757188e-01 3.80622447e-01 6.73869997e-02 -1.20474704e-01
-1.04219389e+00 -4.23022211e-01 -3.54907215e-01 4.87341732e-01
-8.64518583e-02 1.51621833e-01 -1.78627893e-01 -3.73051353e-02
1.51312923e+00 1.25809824e+00 2.28575125e-01 -3.45410407e-01
-3.95282179e-01 5.24201952e-02 -9.83735397e-02 -7.76161492e-01
1.40813482e+00 -3.62230599e-01 -3.16965699e-01 5.08705914e-01
8.58730972e-01 -4.08005178e-01 -7.41117537e-01 -3.00932731e-02
2.98699290e-01 -3.52671981e-01 2.43186459e-01 -1.29012465e+00
-3.15397263e-01 1.94599643e-01 1.39923739e+00 2.68167891e-02
9.64325488e-01 -3.37486982e-01 3.31948519e-01 4.84491944e-01
3.97577196e-01 -9.81556535e-01 -6.97331056e-02 4.38679099e-01
9.20865715e-01 -3.19011301e-01 -3.09760924e-02 1.03306092e-01
-1.53682217e-01 1.24541080e+00 2.39934042e-01 -1.34328157e-01
5.43041229e-01 -9.52294394e-02 -2.90463179e-01 -1.03421025e-01
-1.79654643e-01 -3.77965242e-01 2.78286070e-01 1.10585046e+00
6.38613045e-01 5.01813889e-01 -1.46166134e+00 8.13699126e-01
-4.02403772e-01 6.60896838e-01 4.09647852e-01 1.20112562e+00
-1.07739198e+00 -9.32119727e-01 -9.52106774e-01 1.39533865e+00
-1.25774145e-01 1.44503638e-01 -4.04243052e-01 1.19536197e+00
-4.14176553e-01 1.18889117e+00 1.11011654e-01 1.04374483e-01
6.10336065e-01 7.82047272e-01 5.06882668e-01 -3.19431096e-01
-2.54670262e-01 4.72695753e-02 5.02505779e-01 -4.64606017e-01
-2.32267916e-01 -1.26704156e+00 -9.89084780e-01 -6.27339303e-01
5.48786879e-01 -1.92370471e-02 5.04433393e-01 1.25776792e+00
2.22942904e-01 5.21889389e-01 -3.44842792e-01 -4.72973704e-01
-3.09732080e-01 -1.19174123e+00 -1.18217874e+00 2.20783334e-02
-2.68945426e-01 -7.71108270e-01 -1.37335686e-02 -6.21692538e-01] | [14.162188529968262, -1.6678729057312012] |
3dd7a224-6c32-49f2-a9ef-90a55a5b568e | graph-based-neural-network-models-with-1 | 2011.07267 | null | https://arxiv.org/abs/2011.07267v2 | https://arxiv.org/pdf/2011.07267v2.pdf | Graph-Based Neural Network Models with Multiple Self-Supervised Auxiliary Tasks | Self-supervised learning is currently gaining a lot of attention, as it allows neural networks to learn robust representations from large quantities of unlabeled data. Additionally, multi-task learning can further improve representation learning by training networks simultaneously on related tasks, leading to significant performance improvements. In this paper, we propose three novel self-supervised auxiliary tasks to train graph-based neural network models in a multi-task fashion. Since Graph Convolutional Networks are among the most promising approaches for capturing relationships among structured data points, we use them as a building block to achieve competitive results on standard semi-supervised graph classification tasks. | ['Alessandro Rozza', 'Franco Manessi'] | 2020-11-14 | graph-based-neural-network-models-with | null | null | null | ['auxiliary-learning'] | ['methodology'] | [ 3.77757668e-01 1.86405286e-01 -6.39979601e-01 -5.00940084e-01
-6.11412942e-01 -2.27192774e-01 5.00536084e-01 5.26932299e-01
-1.89192146e-01 4.92936939e-01 1.66940734e-01 -2.19977602e-01
-1.82739962e-02 -7.32209384e-01 -7.13613570e-01 -4.51461345e-01
-1.59134328e-01 6.17192686e-01 1.99820995e-01 -7.71482661e-02
-9.71864462e-02 3.29203576e-01 -1.13331044e+00 2.03008294e-01
9.29582000e-01 9.25997257e-01 1.16099283e-01 2.72958547e-01
-2.16989800e-01 1.31906283e+00 -2.29717880e-01 -3.51169795e-01
-1.18113749e-01 -2.37582773e-01 -9.19802725e-01 1.80207431e-01
6.07697904e-01 4.85136025e-02 -5.34276307e-01 9.99967992e-01
1.67319149e-01 2.37400368e-01 6.99666440e-01 -1.35294831e+00
-1.04416358e+00 5.60460091e-01 -7.59593546e-01 1.47031680e-01
1.45665199e-01 -3.02508146e-01 1.43389606e+00 -5.65496147e-01
4.10998881e-01 1.18236113e+00 5.28208733e-01 3.27487350e-01
-1.24572742e+00 -6.03813052e-01 4.05054212e-01 3.23794276e-01
-1.26339376e+00 -3.54262471e-01 1.25888884e+00 -2.85323858e-01
9.40454900e-01 -1.74612522e-01 3.43844384e-01 1.03431702e+00
1.89387370e-02 1.13891757e+00 8.91168237e-01 -3.44892591e-01
-1.43550768e-01 -1.71382248e-01 3.12953353e-01 1.14012349e+00
3.88479084e-01 -2.33333036e-01 -3.50066990e-01 -1.50000185e-01
7.70293534e-01 3.93210739e-01 -1.99283421e-01 -6.66087627e-01
-9.58480597e-01 1.03104722e+00 9.74099100e-01 4.03330117e-01
-2.08910570e-01 3.87005895e-01 6.11793339e-01 3.68352205e-01
8.67299736e-01 3.31530601e-01 -2.48249367e-01 2.84935147e-01
-5.49374938e-01 -1.47274092e-01 4.34776515e-01 8.72451007e-01
1.03515577e+00 3.66312623e-01 -1.26710944e-02 1.02927005e+00
4.78634983e-01 2.15342045e-01 5.08516908e-01 -3.17404687e-01
7.20921040e-01 1.06911099e+00 -5.71121573e-01 -1.06997550e+00
-5.96234798e-01 -6.64585054e-01 -1.29793704e+00 -1.41840369e-01
7.84685314e-02 -4.91211787e-02 -9.37459767e-01 1.62527084e+00
-1.32969311e-02 1.63236603e-01 5.87777933e-03 5.52166760e-01
1.06920075e+00 5.70176840e-01 1.05168775e-01 -7.47991167e-03
1.07846594e+00 -1.44952989e+00 -7.13038445e-01 -6.39977276e-01
8.67056966e-01 -3.13763767e-01 8.63377094e-01 2.04818696e-01
-6.21777594e-01 -6.53581500e-01 -8.76768351e-01 1.54811493e-03
-4.50624168e-01 1.34046655e-02 1.14196956e+00 1.71546027e-01
-1.08375514e+00 5.35022557e-01 -8.43564808e-01 -9.67501774e-02
8.88932705e-01 2.95107186e-01 -5.87016225e-01 -4.04337585e-01
-1.02310801e+00 7.58182347e-01 6.05074167e-01 7.82573000e-02
-8.18589151e-01 -2.26668105e-01 -1.39031184e+00 2.25861832e-01
5.38976252e-01 -3.98254454e-01 7.30689287e-01 -7.69684792e-01
-9.66695249e-01 9.79671001e-01 -1.75851192e-02 -5.29254138e-01
6.90047666e-02 -8.02456811e-02 -3.61037433e-01 1.86445221e-01
6.78769127e-02 4.53006238e-01 1.04068828e+00 -1.16868687e+00
-7.92177841e-02 -5.25313795e-01 -7.63195902e-02 7.78499469e-02
-7.58888185e-01 -3.19859460e-02 -4.54357356e-01 -7.96968758e-01
4.92304005e-02 -8.92436385e-01 -6.25341833e-01 -1.82487518e-01
-5.76755047e-01 -7.66791165e-01 9.61733043e-01 -3.01510900e-01
9.34363008e-01 -2.07763791e+00 3.34177643e-01 6.16149269e-02
7.46516943e-01 4.94629472e-01 -5.13528764e-01 4.06530976e-01
-2.02902034e-01 3.75483185e-02 -2.93948919e-01 -5.90923071e-01
-3.30440700e-01 3.00743043e-01 -3.10459789e-02 3.98062408e-01
4.43419904e-01 1.44739151e+00 -9.13822532e-01 -4.20889765e-01
9.45846289e-02 3.63919854e-01 -1.61382869e-01 4.81837630e-01
-3.43565196e-01 3.64253581e-01 -7.27241457e-01 4.17825580e-01
3.83695126e-01 -9.78838444e-01 2.42571190e-01 -6.71303421e-02
6.10593975e-01 8.27985108e-02 -7.86197424e-01 1.89009869e+00
-5.29261291e-01 6.17186189e-01 -2.64149494e-02 -1.77212393e+00
1.26578379e+00 1.32020310e-01 5.05867600e-01 -7.11087048e-01
4.83170748e-02 -1.46098673e-01 -6.77252859e-02 -2.12454513e-01
1.57575145e-01 -5.22772968e-02 -1.17695548e-01 5.68381786e-01
3.14188421e-01 -6.59488663e-02 2.74946481e-01 4.56069827e-01
1.06923974e+00 -8.70973021e-02 5.08609533e-01 -1.34211391e-01
4.78737503e-01 -1.41151980e-01 3.93957466e-01 2.95520484e-01
-1.31157845e-01 4.74815607e-01 3.02076221e-01 -6.12119675e-01
-4.70133215e-01 -7.37289608e-01 2.64106512e-01 1.26182950e+00
3.36829796e-02 -5.68380237e-01 -1.72980979e-01 -1.13907444e+00
2.13375866e-01 1.88363716e-01 -7.23372519e-01 -5.03812313e-01
-5.70289910e-01 -5.24590969e-01 3.55693430e-01 8.73359621e-01
4.78099406e-01 -1.04253542e+00 1.20743871e-01 2.26680055e-01
2.95238495e-02 -1.42402291e+00 -3.65543395e-01 5.39554417e-01
-1.10665441e+00 -1.39794564e+00 -8.10986280e-01 -1.20374858e+00
9.15006101e-01 7.65788794e-01 1.21919787e+00 5.35782337e-01
-1.58427253e-01 2.59174824e-01 -5.08267224e-01 -3.48582268e-01
-2.75314212e-01 3.83192331e-01 -9.21692327e-02 1.22180276e-01
2.53665689e-02 -6.25528634e-01 -8.83956775e-02 1.21005319e-01
-9.61508334e-01 1.35058701e-01 5.54979503e-01 9.10765827e-01
6.04966998e-01 4.57480643e-03 8.83455038e-01 -1.30682850e+00
6.77937150e-01 -5.19582808e-01 -5.26354074e-01 4.19726789e-01
-6.76737130e-01 3.79996300e-01 1.12619352e+00 -2.81134486e-01
-7.37313032e-01 9.47489589e-02 1.16959192e-01 -6.98558331e-01
-9.17282701e-02 1.04405987e+00 -4.79351878e-02 -4.20833737e-01
5.31932235e-01 2.52331495e-01 6.77942038e-02 -5.90077400e-01
5.43913782e-01 3.56308937e-01 1.82373688e-01 -3.73911828e-01
9.22148168e-01 3.37663174e-01 2.00262025e-01 -5.81322432e-01
-1.35848176e+00 -6.80656493e-01 -9.16251242e-01 -1.16374949e-02
7.29793608e-01 -1.11302245e+00 -2.77787596e-01 3.90636027e-01
-8.91743541e-01 -5.79847515e-01 -3.44331609e-04 3.52561861e-01
-3.64907354e-01 5.60967565e-01 -4.61461097e-01 -4.05880868e-01
-4.21442717e-01 -9.72481787e-01 1.06049943e+00 5.35847172e-02
1.74349472e-01 -1.68646884e+00 7.51000345e-02 5.53926408e-01
3.17865133e-01 3.49863231e-01 8.83779645e-01 -1.11218870e+00
-4.55963135e-01 -4.12775874e-01 -6.07183039e-01 3.84160757e-01
4.85486329e-01 -2.74927258e-01 -6.29295945e-01 -6.65055692e-01
-4.35899764e-01 -9.55590844e-01 1.32951546e+00 2.92262554e-01
1.42428005e+00 -5.95618188e-02 -5.34068823e-01 7.28188515e-01
1.30385494e+00 -3.55454952e-01 1.72534943e-01 4.68591861e-02
1.47184300e+00 4.58375245e-01 2.32597008e-01 8.48724097e-02
7.71094680e-01 6.12558007e-01 6.31498218e-01 -5.55362105e-01
-2.92723536e-01 -3.47354233e-01 6.15260527e-02 9.46745634e-01
5.88258030e-03 -1.83287561e-01 -1.10209465e+00 3.39555472e-01
-2.18094182e+00 -5.98244369e-01 -3.17652732e-01 1.86466038e+00
4.43602622e-01 1.46801159e-01 1.72719747e-01 -6.28997311e-02
6.90776169e-01 7.06270158e-01 -5.89855850e-01 -1.44906724e-02
-8.77352282e-02 2.69540906e-01 4.59019095e-01 4.74312529e-02
-1.40024137e+00 1.25577152e+00 6.66234827e+00 6.83732331e-01
-1.11593902e+00 3.09979860e-02 6.11444652e-01 4.01891589e-01
-2.28493810e-01 -2.56699592e-01 -4.64116573e-01 6.07022606e-02
7.29370475e-01 -3.36313069e-01 1.61039203e-01 9.31829929e-01
-5.18073365e-02 3.00359607e-01 -1.08385658e+00 1.04804528e+00
3.94203603e-01 -1.37825513e+00 3.00329447e-01 3.77720222e-02
9.14853156e-01 3.65324855e-01 -9.03183818e-02 4.52136815e-01
7.20784843e-01 -1.19536543e+00 1.45382822e-01 4.78859246e-02
7.57025242e-01 -5.94725490e-01 6.41836643e-01 4.11361158e-01
-1.63743782e+00 1.51405945e-01 -4.81772065e-01 -2.31870666e-01
1.08334765e-01 6.51095629e-01 -5.73270679e-01 9.03962672e-01
3.25034887e-01 1.43183291e+00 -8.91678751e-01 1.00485218e+00
-5.25204182e-01 7.08381534e-01 1.92749742e-02 -2.91869380e-02
3.70624065e-01 -1.98442340e-01 5.86393215e-02 9.84507620e-01
-2.58131772e-01 -2.92197317e-01 8.08869660e-01 6.04251027e-01
-6.10014021e-01 2.94124007e-01 -1.04054511e+00 -4.50348616e-01
-3.65973189e-02 1.36526036e+00 -8.50505233e-01 -3.75613958e-01
-7.45378911e-01 9.21116173e-01 1.16278553e+00 3.61101210e-01
-5.20093501e-01 -2.88255453e-01 3.11405540e-01 -3.19051266e-01
1.74368054e-01 -6.04703784e-01 -1.07709967e-01 -1.45387411e+00
-1.05582535e-01 -6.08399570e-01 7.59443283e-01 -4.25810307e-01
-1.47412539e+00 5.31013668e-01 -2.44390145e-01 -1.04490876e+00
-2.16350362e-01 -6.92378342e-01 -8.09897125e-01 5.54536879e-01
-1.99964464e+00 -1.67908156e+00 -4.21706587e-01 8.65378916e-01
4.72465545e-01 -4.80672091e-01 9.28427815e-01 1.43108591e-01
-6.96783602e-01 5.61514437e-01 7.20057562e-02 6.29577219e-01
6.33161068e-01 -1.40378499e+00 7.07333863e-01 8.00424695e-01
8.24072659e-01 4.10162121e-01 -2.86775846e-02 -5.88275075e-01
-1.52109575e+00 -1.43840957e+00 4.32373911e-01 -1.04835160e-01
8.72874081e-01 -4.70223546e-01 -1.32689250e+00 8.30483913e-01
4.34934832e-02 5.56973159e-01 9.58563566e-01 5.32051563e-01
-7.23116517e-01 -1.43313050e-01 -5.29396951e-01 1.73142821e-01
1.09675825e+00 -8.61409485e-01 -4.26064163e-01 7.75849402e-01
6.86437786e-01 -1.35352537e-01 -7.77033150e-01 4.10133183e-01
-3.65674011e-02 -5.49814999e-01 9.34181154e-01 -8.95610452e-01
4.35702622e-01 9.41664949e-02 2.15303212e-01 -1.72237301e+00
-4.30463970e-01 -5.45843065e-01 -4.49384451e-01 1.03729236e+00
4.24441636e-01 -7.07989275e-01 1.05402303e+00 1.85888782e-01
-1.38321310e-01 -7.92359293e-01 -5.11102021e-01 -8.57307196e-01
2.55780239e-02 -1.51463419e-01 1.81606039e-01 1.22883725e+00
5.36866933e-02 8.42276454e-01 -6.15491092e-01 -1.69622213e-01
8.14526796e-01 4.30193365e-01 7.76166201e-01 -1.61323667e+00
-1.69314340e-01 -4.35805500e-01 -5.77319205e-01 -1.14572382e+00
8.30224633e-01 -1.57831490e+00 -1.10763088e-01 -2.03360295e+00
3.19534004e-01 -3.71539205e-01 -5.58061182e-01 8.96596789e-01
-6.07357264e-01 3.18892181e-01 8.96991044e-02 2.83169001e-01
-1.09220314e+00 8.41176569e-01 1.42016375e+00 -4.04582679e-01
-1.00497375e-04 2.59903878e-01 -9.88833070e-01 5.51142097e-01
8.19948733e-01 -3.63879561e-01 -5.81111312e-01 -7.45385230e-01
1.21549806e-02 -2.55253371e-02 9.54742357e-02 -8.44329596e-01
2.82255441e-01 -8.70737806e-02 1.55026019e-01 -3.04080933e-01
1.71560526e-01 -9.01545584e-01 -3.51775885e-01 4.41161036e-01
-4.62744236e-01 1.01797739e-02 8.66780877e-02 8.95353794e-01
-5.98618448e-01 -5.14550414e-03 7.24074960e-01 -1.54372096e-01
-9.06493127e-01 8.63819182e-01 3.17812599e-02 7.62931406e-02
1.01368403e+00 8.99463221e-02 -3.06201369e-01 -4.87837225e-01
-6.22943044e-01 5.76114237e-01 2.13562563e-01 6.41794801e-01
8.59384060e-01 -1.43170619e+00 -7.23521829e-01 1.20335206e-01
5.30108511e-01 2.24923506e-01 5.78486212e-02 4.95475084e-01
-1.25297382e-01 3.91416132e-01 -1.61196187e-01 -5.41398585e-01
-1.25838053e+00 7.91346729e-01 -5.45617752e-03 -6.37501717e-01
-6.71766996e-01 9.51104283e-01 1.92523569e-01 -4.60499018e-01
1.99221417e-01 -2.38777354e-01 -4.53807622e-01 -3.96442227e-03
3.13111514e-01 3.26015428e-02 5.95550835e-02 -6.68873489e-01
-3.66027892e-01 4.79439527e-01 -3.31555337e-01 6.30619228e-01
1.53489935e+00 1.96437418e-01 -4.31793183e-02 3.63356143e-01
1.66222703e+00 -3.50527614e-01 -1.04117668e+00 -8.47226977e-01
3.58068675e-01 -1.69613421e-01 2.53940523e-01 -3.51153642e-01
-1.36656475e+00 1.05639148e+00 -3.54600437e-02 3.43782663e-01
9.90403950e-01 3.98642778e-01 6.91879630e-01 7.25991309e-01
3.82439494e-01 -7.18149185e-01 6.40104532e-01 5.31536818e-01
7.81265378e-01 -1.79425967e+00 2.33347237e-01 -6.13717556e-01
-7.38746345e-01 1.18178034e+00 7.03471303e-01 -4.04928923e-01
6.94596350e-01 3.67296636e-02 -5.55419698e-02 -5.90403795e-01
-7.06587851e-01 -6.23360991e-01 7.08784997e-01 8.67791116e-01
6.34212971e-01 8.05661231e-02 2.34185070e-01 3.87409568e-01
3.57675344e-01 -1.90212086e-01 1.76330745e-01 6.72676146e-01
-3.79785180e-01 -1.30757546e+00 2.52301842e-01 9.43776667e-01
-1.99751332e-01 -1.22608878e-01 -4.64041412e-01 5.52925229e-01
-6.33442402e-01 9.51556742e-01 -1.34958416e-01 -3.99989784e-01
1.98465198e-01 -1.92703545e-01 3.00663650e-01 -1.15969658e+00
-3.52136165e-01 -1.06000535e-01 9.17368829e-02 -5.69043636e-01
-5.99912405e-01 -2.51931757e-01 -1.19734013e+00 1.50458857e-01
-4.63210613e-01 3.31247389e-01 2.76185036e-01 1.16805804e+00
3.53386849e-01 7.95923054e-01 8.81359935e-01 -7.21840680e-01
-3.68374109e-01 -9.75171089e-01 -5.11159837e-01 5.90338171e-01
1.42626539e-01 -7.44536877e-01 -1.35085240e-01 -1.20843321e-01] | [7.288985729217529, 6.290165901184082] |
ce15c345-cd00-4c36-976c-4e67e791463e | correcting-diverse-factual-errors-in | 2210.12378 | null | https://arxiv.org/abs/2210.12378v2 | https://arxiv.org/pdf/2210.12378v2.pdf | Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling | Abstractive summarization models often generate inconsistent summaries containing factual errors or hallucinated content. Recent works focus on correcting factual errors in generated summaries via post-editing. Such correction models are trained using adversarial non-factual summaries constructed using heuristic rules for injecting errors. However, generating non-factual summaries using heuristics often does not generalize well to actual model errors. In this work, we propose to generate hard, representative synthetic examples of non-factual summaries through infilling language models. With this data, we train a more robust fact-correction model to post-edit the summaries to improve factual consistency. Through quantitative and qualitative experiments on two popular summarization datasets -- CNN/DM and XSum -- we show that our approach vastly outperforms prior methods in correcting erroneous summaries. Our model -- FactEdit -- improves factuality scores by over ~11 points on CNN/DM and over ~31 points on XSum on average across multiple summarization models, producing more factual summaries while maintaining competitive summarization quality. | ['William W. Cohen', 'Yulia Tsvetkov', 'Hannaneh Hajishirzi', 'Vidhisha Balachandran'] | 2022-10-22 | null | null | null | null | ['abstractive-text-summarization'] | ['natural-language-processing'] | [ 3.08624417e-01 8.39792669e-01 -1.04809307e-01 -2.68896639e-01
-1.45675433e+00 -4.84171927e-01 7.90843010e-01 7.64345884e-01
2.75813369e-03 1.35417736e+00 1.14439905e+00 -1.53401392e-02
4.66112584e-01 -7.68796563e-01 -1.08366811e+00 9.14643630e-02
2.84297317e-01 3.34595561e-01 -2.35377774e-01 -3.82307321e-01
8.43146324e-01 -2.49941349e-01 -1.17312527e+00 7.39687383e-01
1.74877763e+00 2.05505282e-01 -2.31374949e-01 1.19927120e+00
-8.74414593e-02 1.19385827e+00 -1.64638460e+00 -1.00768113e+00
-1.43540576e-01 -8.92591298e-01 -7.53629386e-01 -8.07968229e-02
1.20694506e+00 -5.44781625e-01 -3.83477539e-01 1.21783423e+00
7.57881820e-01 1.60569474e-01 7.83333600e-01 -1.01395023e+00
-1.33957171e+00 1.28307593e+00 -3.24273467e-01 2.51697481e-01
7.64255583e-01 4.59469497e-01 1.10139096e+00 -6.38287723e-01
8.57978880e-01 1.38196456e+00 8.01664948e-01 9.08650756e-01
-1.08152902e+00 -4.55332249e-01 -3.06167696e-02 -2.28305489e-01
-8.45657289e-01 -7.61308610e-01 6.06425762e-01 -6.95841238e-02
1.13011670e+00 6.74646795e-01 5.07199883e-01 1.50019324e+00
6.64744675e-01 1.11492527e+00 5.23859501e-01 -4.74828631e-02
2.60402441e-01 -5.30391140e-03 4.16699797e-02 5.04293144e-01
9.78350103e-01 -3.63072038e-01 -7.13820398e-01 -2.72537768e-01
1.84201211e-01 -2.73808479e-01 -4.10311013e-01 6.29090786e-01
-1.35453701e+00 7.72162616e-01 2.84679294e-01 -1.57431662e-02
-5.47846615e-01 4.14609492e-01 9.17129934e-01 1.48087934e-01
8.72260988e-01 1.38411140e+00 1.62030049e-02 -3.85058403e-01
-1.45926499e+00 1.03177905e+00 8.30034614e-01 1.26178825e+00
2.55419612e-01 6.39948487e-01 -9.12374496e-01 7.93612897e-01
-4.27470386e-01 7.97972202e-01 5.40743589e-01 -1.26818931e+00
9.70876634e-01 3.53844047e-01 3.91564667e-01 -1.28851748e+00
-7.44166747e-02 -5.83662212e-01 -1.09074032e+00 -4.00574207e-01
-2.52865493e-01 -1.82318389e-01 -6.67281389e-01 1.45174384e+00
-4.92028564e-01 -6.72017485e-02 3.98814768e-01 4.25023079e-01
1.31416225e+00 9.92021799e-01 -9.74103659e-02 -3.70765805e-01
7.49274969e-01 -1.05048823e+00 -1.19317555e+00 -3.30823421e-01
5.79760909e-01 -6.27754867e-01 1.36427104e+00 3.99488300e-01
-1.81052208e+00 -2.85186470e-01 -1.24051261e+00 -2.62024164e-01
-8.84081796e-02 2.70901918e-01 1.11929670e-01 1.31370395e-01
-1.19359851e+00 9.41324651e-01 -4.92137551e-01 -3.01969945e-01
7.45561540e-01 -3.02409172e-01 -2.14609161e-01 -2.20197067e-02
-9.75484848e-01 8.29700649e-01 4.28557456e-01 -5.40354848e-01
-8.39007556e-01 -9.85024691e-01 -1.12204421e+00 1.31598130e-01
1.42539605e-01 -1.22343051e+00 1.74297440e+00 -5.06554008e-01
-1.24846375e+00 5.54880917e-01 -4.06853110e-01 -8.78985107e-01
8.67760181e-01 -6.72649920e-01 -4.64440107e-01 7.83112571e-02
5.98648787e-01 6.05353177e-01 5.22126496e-01 -1.62631977e+00
-4.02292401e-01 9.50717032e-02 -1.71023488e-01 1.96937889e-01
-1.88048750e-01 -3.29123199e-01 -1.09962218e-06 -1.23009539e+00
-3.78651410e-01 -3.19654256e-01 -2.25358114e-01 -4.77129728e-01
-1.47910571e+00 -1.60472058e-02 4.71574992e-01 -1.00322831e+00
1.58524156e+00 -1.65117049e+00 -5.45162112e-02 -4.88362759e-01
5.25323868e-01 4.37779576e-01 -2.48485133e-01 6.54009521e-01
4.05624568e-01 6.94776654e-01 -6.45904183e-01 -7.86153078e-01
3.10694445e-02 -1.51122706e-02 -1.09031224e+00 -8.93371850e-02
4.13097769e-01 1.21105182e+00 -1.44581044e+00 -4.75693822e-01
-1.53789908e-01 1.11263134e-01 -7.95138061e-01 2.94185013e-01
-6.44496739e-01 -6.21372974e-03 -1.30021706e-01 4.24097180e-01
5.98964512e-01 -1.45568922e-01 -4.10967171e-01 8.98262113e-02
1.07517280e-01 7.17276394e-01 -4.80703115e-01 1.85891664e+00
-3.47942591e-01 1.04747665e+00 -5.24698973e-01 -4.51578528e-01
8.96848619e-01 1.99296013e-01 -1.45800903e-01 -6.30261421e-01
-1.49289891e-02 3.18860888e-01 -5.22728443e-01 -5.97715318e-01
1.75067961e+00 -2.21207347e-02 -4.28920984e-01 6.52551413e-01
2.93798707e-02 -8.94585848e-01 5.53212523e-01 9.88408148e-01
1.23193991e+00 -4.24298972e-01 2.86071092e-01 3.23028415e-02
5.69303632e-02 2.97184527e-01 5.77605188e-01 1.33922565e+00
1.87755562e-02 1.20183027e+00 8.09659660e-01 -1.36893624e-02
-1.31172299e+00 -1.12683344e+00 3.25454503e-01 2.10508451e-01
-9.60163772e-02 -8.41818213e-01 -9.69501078e-01 -7.66101241e-01
8.50520805e-02 1.91040611e+00 -6.17007971e-01 -6.31061614e-01
-4.76405978e-01 -5.02912760e-01 1.13382065e+00 5.49586415e-01
6.20815873e-01 -1.12928319e+00 -3.70953202e-01 4.14342791e-01
-5.02027452e-01 -7.76847780e-01 -6.95784867e-01 -5.34920037e-01
-9.94112730e-01 -7.16826975e-01 -6.47534251e-01 -1.63360596e-01
5.97212791e-01 1.78203404e-01 1.43149662e+00 1.75861701e-01
8.34041312e-02 1.97387666e-01 -1.70883432e-01 -8.37936163e-01
-1.17621243e+00 1.58163130e-01 4.91696149e-02 -5.76609612e-01
-1.83151811e-01 -3.66707712e-01 -3.94601196e-01 -5.31130791e-01
-1.18422771e+00 2.95246691e-01 4.02121365e-01 7.26996362e-01
3.14216197e-01 -3.05177599e-01 1.15744090e+00 -1.34047151e+00
1.46732819e+00 -5.81406474e-01 2.69357204e-01 2.34354928e-01
-5.98343194e-01 3.73917073e-02 1.17245901e+00 -2.04875126e-01
-1.14578056e+00 -1.01284397e+00 3.96603011e-02 -2.83504248e-01
2.20485896e-01 4.42716718e-01 1.65672489e-02 8.30729663e-01
1.19779956e+00 5.08147717e-01 -3.31766784e-01 -6.33103997e-02
6.04092300e-01 5.61827838e-01 1.28528261e+00 -4.84620601e-01
6.68210328e-01 3.85461509e-01 -6.47783041e-01 -5.73732913e-01
-1.20773971e+00 1.53835371e-01 -4.99898419e-02 -9.56220254e-02
5.09929717e-01 -9.55530465e-01 4.76034097e-02 3.82968426e-01
-1.69452608e+00 -2.13481441e-01 -7.30968356e-01 -3.18233366e-03
-5.58051467e-01 4.65562731e-01 -8.19358706e-01 -5.53092897e-01
-1.00181913e+00 -7.21387208e-01 1.14783156e+00 3.49058658e-01
-8.64513338e-01 -9.71613824e-01 3.01310837e-01 2.79617429e-01
6.09310091e-01 6.82727575e-01 7.16757357e-01 -8.24716449e-01
-3.10224861e-01 -4.85007018e-01 -2.11206406e-01 4.17556047e-01
1.15521431e-01 4.49674726e-01 -7.56372631e-01 -7.31161386e-02
-3.70401055e-01 -4.21450704e-01 1.16340125e+00 3.79649073e-01
1.18183255e+00 -1.26682007e+00 -1.32361695e-01 2.35478565e-01
9.92758930e-01 -2.34847814e-01 8.52988839e-01 -5.93505278e-02
7.13907480e-01 2.08549991e-01 6.46511197e-01 7.68160939e-01
5.70110738e-01 3.48899961e-02 2.61163503e-01 2.60127097e-01
-4.42488939e-01 -8.99790823e-01 4.38398838e-01 1.10949385e+00
3.17268699e-01 -1.06966674e+00 -5.97352862e-01 1.06752110e+00
-1.91854942e+00 -1.51368594e+00 -2.70608783e-01 1.87560570e+00
1.24567819e+00 3.65960687e-01 -2.66797692e-01 -5.27282357e-02
6.52940392e-01 5.68813562e-01 -5.62961102e-01 -9.03987944e-01
-4.93790597e-01 -1.11100428e-01 1.74636558e-01 5.71618557e-01
-6.84604406e-01 9.47322309e-01 6.24822617e+00 6.69634640e-01
-1.01369774e+00 1.18677039e-02 6.19962871e-01 -5.56123674e-01
-1.06506944e+00 -1.99174315e-01 -4.99865741e-01 7.54033029e-01
9.06402111e-01 -8.91792774e-01 -3.41722853e-02 6.96796000e-01
5.56824327e-01 -1.64769962e-01 -1.04139662e+00 6.59280717e-01
6.76374912e-01 -2.00952625e+00 8.26874077e-01 -3.76908988e-01
1.43042183e+00 -3.00015897e-01 1.44551005e-02 4.39296901e-01
7.40680993e-01 -1.10417950e+00 1.05859017e+00 7.61730790e-01
8.46134245e-01 -8.02658558e-01 8.19010496e-01 3.46131355e-01
-2.08852708e-01 2.76821792e-01 -5.53973258e-01 -7.32279615e-03
3.81382585e-01 1.08658803e+00 -9.37902570e-01 6.53635740e-01
2.73603380e-01 1.14231992e+00 -7.83681154e-01 9.54473138e-01
-4.36257631e-01 7.59446323e-01 2.33005881e-01 -1.59390599e-01
6.84974194e-02 3.41686040e-01 1.07576442e+00 1.71320355e+00
6.15578711e-01 2.33241506e-02 -3.27541023e-01 1.20856309e+00
-7.46710360e-01 -2.20798552e-01 -9.90070522e-01 -2.89092779e-01
8.10985506e-01 7.69140363e-01 -8.37164074e-02 -9.67404187e-01
2.82993346e-01 1.13347900e+00 2.76024401e-01 2.23709390e-01
-8.56240332e-01 -8.01545560e-01 4.30104911e-01 1.48821063e-02
-2.13984281e-01 2.11681858e-01 -1.01221097e+00 -1.45661056e+00
1.30412027e-01 -1.04583013e+00 1.39412209e-01 -1.22701144e+00
-1.21200418e+00 5.79355419e-01 -9.37079638e-02 -1.06827497e+00
-3.22111756e-01 3.65467101e-01 -1.40094352e+00 4.90471482e-01
-1.27145290e+00 -8.44783485e-01 -3.72072607e-01 -1.06709272e-01
1.00727463e+00 -1.86436638e-01 4.91322070e-01 -1.84895277e-01
-6.83120430e-01 8.03703368e-01 2.44210325e-02 -1.53689235e-01
1.10782886e+00 -1.56917965e+00 9.94975030e-01 1.30622721e+00
-3.35055918e-01 6.83456123e-01 1.48239398e+00 -1.24994469e+00
-8.62867355e-01 -1.63587511e+00 1.33722210e+00 -7.26978481e-01
3.38136613e-01 1.02180690e-02 -1.24075973e+00 7.97575712e-01
8.59755099e-01 -6.57263577e-01 4.61878061e-01 -3.94735008e-01
-4.18974608e-01 2.56935090e-01 -1.26226830e+00 9.87331450e-01
1.07436061e+00 -3.72874230e-01 -1.03763783e+00 6.00795686e-01
1.17677665e+00 -6.32700861e-01 -5.13150156e-01 2.50406206e-01
-5.07805534e-02 -7.64424682e-01 6.62882268e-01 -8.24259579e-01
1.71630585e+00 -1.48118943e-01 1.49634778e-01 -2.07272387e+00
1.73158180e-02 -1.08887804e+00 -4.04601485e-01 1.55704474e+00
4.56561148e-01 -2.66689420e-01 3.66285652e-01 4.98870075e-01
-7.81157494e-01 -4.76133406e-01 -5.40654540e-01 -6.26934290e-01
3.74886215e-01 -1.74897090e-01 7.30343521e-01 9.65800285e-01
2.87589997e-01 3.30621839e-01 -3.55956733e-01 -1.18744820e-01
5.47244728e-01 -1.64969400e-01 1.11191690e+00 -6.76560402e-01
6.45834580e-02 -7.31389821e-01 6.02531657e-02 -8.23424339e-01
3.17066848e-01 -9.06482041e-01 3.50504905e-01 -2.14851213e+00
2.86029935e-01 2.36841932e-01 5.24691343e-01 3.24003279e-01
-8.31045985e-01 -5.82568981e-02 7.45946690e-02 1.01927876e-01
-8.96138251e-01 9.81009841e-01 1.36322808e+00 -4.89283651e-01
-1.27080798e-01 -3.33475918e-01 -1.30369377e+00 4.11335468e-01
7.80584514e-01 -5.32103658e-01 -2.90211797e-01 -6.36825621e-01
3.83995473e-01 2.30940759e-01 3.95209968e-01 -1.16591763e+00
1.73256814e-01 -8.38577226e-02 5.43285087e-02 -7.82181084e-01
-5.92233799e-02 3.06555271e-01 -1.98446363e-01 3.80728096e-01
-1.06383622e+00 3.48712683e-01 3.15876544e-01 8.09260786e-01
-2.93830752e-01 -1.75220847e-01 4.80487049e-01 -3.08146179e-01
-5.60837314e-02 -1.97465703e-01 -5.50746799e-01 7.75687397e-01
5.38156748e-01 6.43881783e-03 -1.29061460e+00 -9.42701519e-01
-7.08875880e-02 4.05175149e-01 7.48662353e-01 3.68878126e-01
8.40813279e-01 -1.17059064e+00 -1.36669469e+00 -3.86586338e-01
2.34880865e-01 3.10284257e-01 3.57949287e-01 3.86090159e-01
-6.87641442e-01 3.96574110e-01 -1.02717347e-01 -1.72674373e-01
-7.69963562e-01 1.94209129e-01 3.48760486e-02 -3.93097341e-01
-6.64040327e-01 7.99910724e-01 -1.61360726e-01 -4.89046752e-01
-7.98895285e-02 -5.77569067e-01 1.15822606e-01 -1.97962038e-02
8.64414394e-01 7.51923978e-01 2.26606742e-01 -1.07155539e-01
2.24785343e-01 -1.23320431e-01 -4.01124001e-01 -1.94297299e-01
1.18201816e+00 -7.17036128e-02 -7.83706978e-02 4.24549937e-01
1.00710964e+00 5.41853607e-01 -1.14651036e+00 6.09288504e-03
-1.81031063e-01 -3.82990122e-01 -2.05069289e-01 -1.04438448e+00
-7.12816596e-01 7.66506433e-01 -5.99239528e-01 2.35725686e-01
6.24709964e-01 -3.10073555e-01 1.24365759e+00 4.97975260e-01
-6.26069456e-02 -1.05442023e+00 4.20718253e-01 6.12136126e-01
1.60376692e+00 -1.21349239e+00 3.12457651e-01 -8.44644979e-02
-1.07019031e+00 9.85680401e-01 7.63667285e-01 -4.12601143e-01
-2.83667564e-01 2.29696464e-02 -5.55784442e-02 -2.15104267e-01
-1.10710168e+00 6.47118688e-01 1.61962137e-01 4.88129705e-01
4.19803083e-01 2.00187713e-01 -3.35146517e-01 7.84956932e-01
-9.45983291e-01 -6.03641421e-02 1.55997229e+00 7.51779318e-01
-4.85980779e-01 -3.66845757e-01 -2.21969858e-01 9.78963852e-01
-4.19433266e-01 -2.94929117e-01 -7.85491526e-01 5.32836556e-01
-6.26488745e-01 1.16214156e+00 1.36029124e-01 -3.60991478e-01
4.72095698e-01 -1.85726374e-01 1.55865043e-01 -8.55940759e-01
-9.61399198e-01 -6.35356128e-01 4.91261631e-01 -3.61890584e-01
6.48933873e-02 -7.78905928e-01 -1.31380737e+00 -9.37640607e-01
-2.78796833e-02 1.80518657e-01 3.47005457e-01 6.53644443e-01
7.56306708e-01 8.68879795e-01 2.66214162e-01 -7.14570224e-01
-7.54412353e-01 -1.10653508e+00 -1.90939367e-01 5.48612833e-01
5.67821443e-01 7.99438357e-02 -5.47689557e-01 9.68768299e-02] | [12.189502716064453, 9.190875053405762] |
f4445e86-8686-485e-860b-ecfe02a92d92 | parameter-is-not-all-you-need-starting-from | 2303.08134 | null | https://arxiv.org/abs/2303.08134v2 | https://arxiv.org/pdf/2303.08134v2.pdf | Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis | We present a Non-parametric Network for 3D point cloud analysis, Point-NN, which consists of purely non-learnable components: farthest point sampling (FPS), k-nearest neighbors (k-NN), and pooling operations, with trigonometric functions. Surprisingly, it performs well on various 3D tasks, requiring no parameters or training, and even surpasses existing fully trained models. Starting from this basic non-parametric model, we propose two extensions. First, Point-NN can serve as a base architectural framework to construct Parametric Networks by simply inserting linear layers on top. Given the superior non-parametric foundation, the derived Point-PN exhibits a high performance-efficiency trade-off with only a few learnable parameters. Second, Point-NN can be regarded as a plug-and-play module for the already trained 3D models during inference. Point-NN captures the complementary geometric knowledge and enhances existing methods for different 3D benchmarks without re-training. We hope our work may cast a light on the community for understanding 3D point clouds with non-parametric methods. Code is available at https://github.com/ZrrSkywalker/Point-NN. | ['Ziyu Guo', 'Jianbo Shi', 'Hongsheng Li', 'Peng Gao', 'Yali Wang', 'Liuhui Wang', 'Renrui Zhang'] | 2023-03-14 | null | null | null | null | ['training-free-3d-point-cloud-classification', '3d-point-cloud-classification', 'training-free-3d-part-segmentation'] | ['computer-vision', 'computer-vision', 'computer-vision'] | [-4.19513881e-01 1.27448872e-01 -4.34133023e-01 -5.41408598e-01
-8.98938656e-01 -6.02257073e-01 7.38160193e-01 -1.89119920e-01
-9.67095569e-02 3.05742204e-01 -1.64628416e-01 -5.17035723e-01
-1.20795518e-01 -8.61298084e-01 -1.34498644e+00 -5.71999967e-01
-2.66372651e-01 7.63741910e-01 4.92461681e-01 -9.78241414e-02
2.37509608e-01 1.37207031e+00 -1.49541008e+00 4.99562547e-03
4.94183600e-01 1.31155825e+00 3.64928357e-02 4.42489684e-01
-1.64441764e-01 9.56734493e-02 -2.11457685e-01 -3.89592230e-01
5.65187275e-01 6.43953860e-01 -4.75917161e-01 -3.44899803e-01
6.67726040e-01 -7.12533474e-01 -3.89214814e-01 5.83174407e-01
5.23381472e-01 4.72756438e-02 8.16716015e-01 -1.32722259e+00
-8.33524823e-01 2.57466704e-01 -3.37886274e-01 -3.14401656e-01
-7.61158988e-02 2.85669029e-01 1.00175118e+00 -1.32288778e+00
4.24432725e-01 1.50425947e+00 1.16955984e+00 3.75243634e-01
-1.13176858e+00 -5.55172145e-01 -1.10985346e-01 7.54436431e-03
-1.56937265e+00 -2.52611458e-01 1.02483964e+00 -4.12900090e-01
1.09524035e+00 1.26460552e-01 7.08763361e-01 1.02837646e+00
-1.14695586e-01 8.62253964e-01 5.41278064e-01 -1.31448403e-01
2.45756656e-01 -1.33430719e-01 -8.71015619e-03 5.19985080e-01
7.00415522e-02 3.55179280e-01 -2.62795925e-01 -4.19979542e-01
1.47439837e+00 1.55549243e-01 -1.27498567e-01 -9.35121655e-01
-1.10281694e+00 6.84245884e-01 7.26067126e-01 -4.84971702e-02
-2.33033299e-01 5.00353575e-01 2.12379858e-01 8.63411427e-02
5.94128251e-01 3.82494688e-01 -7.26683855e-01 -2.39155665e-01
-9.42909479e-01 5.54080486e-01 7.79063404e-01 1.43648005e+00
1.18981862e+00 -8.42299014e-02 -1.06018253e-01 8.05444658e-01
1.50221348e-01 6.09326482e-01 -2.07048044e-01 -1.17883492e+00
2.22439885e-01 5.97986221e-01 2.26677716e-01 -8.13590944e-01
-4.83546317e-01 -3.08955789e-01 -7.03956962e-01 4.97125208e-01
3.21262538e-01 1.58409610e-01 -8.98620605e-01 1.35493243e+00
3.76299351e-01 4.39980209e-01 -5.28758228e-01 6.49512827e-01
8.89069736e-01 6.43432558e-01 -2.44782895e-01 5.84550500e-01
1.14337480e+00 -8.20277691e-01 6.13832437e-02 8.35833848e-02
4.51935440e-01 -5.53430676e-01 1.27311766e+00 1.14686027e-01
-1.27553129e+00 -5.81968009e-01 -9.98505235e-01 -6.30227923e-01
-5.19775927e-01 1.64364487e-01 7.80296087e-01 2.63031602e-01
-1.39794672e+00 9.20724034e-01 -1.07309413e+00 -1.91376626e-01
8.57208669e-01 6.24071240e-01 -2.25792632e-01 -5.68686165e-02
-8.19081366e-01 8.08002293e-01 1.29240572e-01 1.41631991e-01
-7.25295842e-01 -1.26859200e+00 -7.40387559e-01 2.02563703e-02
2.74545193e-01 -1.10385513e+00 1.44808185e+00 -1.42717525e-01
-1.88397813e+00 9.19753253e-01 -3.04628134e-01 -3.70474041e-01
5.41076720e-01 -2.97647059e-01 3.32824960e-02 1.50491506e-01
-2.38832623e-01 9.43378389e-01 8.37914646e-01 -1.39195359e+00
-2.35335141e-01 -4.54431742e-01 2.49637559e-01 1.62087400e-02
6.73488453e-02 -2.27716371e-01 -7.53142953e-01 -4.66755122e-01
3.67295235e-01 -1.01024675e+00 -1.39685884e-01 6.30576372e-01
-3.40439796e-01 -6.35594010e-01 9.22945380e-01 -1.80085018e-01
5.39991498e-01 -2.20180178e+00 -1.98648661e-01 2.38664746e-01
3.84021193e-01 2.93092966e-01 -1.55026853e-01 3.30095589e-01
-2.55464986e-02 2.79876530e-01 -2.07395256e-01 -6.02940321e-01
4.25164759e-01 2.28173286e-01 -3.65745783e-01 5.38972080e-01
6.05968118e-01 1.41618168e+00 -6.91726744e-01 -2.35949785e-01
6.42506361e-01 7.73864031e-01 -6.63620532e-01 -4.22666483e-02
-4.38378572e-01 1.80143923e-01 -4.66867477e-01 9.23304081e-01
1.13617575e+00 -3.59602749e-01 -6.09458983e-01 -3.38772148e-01
-3.65645476e-02 3.28271776e-01 -9.22265887e-01 1.93633795e+00
-4.36663598e-01 3.98178548e-01 2.72419974e-02 -8.01083088e-01
1.12142098e+00 6.27361238e-02 4.25802022e-01 -1.91878080e-01
3.82567197e-02 4.34511930e-01 -4.75228667e-01 -1.79956272e-01
4.38328415e-01 6.26216829e-02 2.11875420e-02 -3.31572294e-02
2.53105581e-01 -7.50735462e-01 -3.62663984e-01 -2.22946092e-01
8.74371409e-01 5.41325927e-01 9.56081375e-02 -1.99273780e-01
2.32888877e-01 -3.11414991e-02 2.13005587e-01 7.59918571e-01
-3.47254355e-03 7.41436720e-01 6.20004237e-01 -7.31887996e-01
-1.31152582e+00 -1.54730380e+00 -3.89043748e-01 9.35259998e-01
1.01690657e-01 -2.69406915e-01 -3.21692407e-01 -3.96828711e-01
5.44610560e-01 6.75845206e-01 -4.97331560e-01 -1.20000378e-03
-7.48673081e-01 -8.96515548e-02 7.24864066e-01 7.08673954e-01
2.52050906e-01 -7.83022702e-01 -3.02015785e-02 -1.08759932e-01
4.43952560e-01 -1.06535709e+00 -2.47559130e-01 2.20520705e-01
-1.34359515e+00 -7.54894257e-01 -7.14958251e-01 -6.50716424e-01
5.46790242e-01 3.19755256e-01 1.45419371e+00 -1.69674262e-01
2.88184345e-01 2.58069575e-01 -3.94654125e-02 -6.12257719e-01
-3.80413160e-02 3.90292764e-01 -1.99920535e-02 -5.79466403e-01
6.90662682e-01 -1.31786668e+00 -6.69869304e-01 4.31159347e-01
-6.17058814e-01 -1.15588784e-01 7.68206716e-01 4.66331214e-01
1.03701675e+00 -3.91843408e-01 2.98715353e-01 -5.60108006e-01
2.80132234e-01 -4.03392822e-01 -8.05609167e-01 -2.17884868e-01
4.15338203e-03 -3.23715657e-02 6.80012882e-01 -3.45110655e-01
-4.66937214e-01 1.85048833e-01 -3.82131279e-01 -1.16625285e+00
-3.48489404e-01 -4.72405590e-02 -3.56225371e-01 -3.83327097e-01
6.15614414e-01 9.17689800e-02 5.51712280e-03 -7.56285727e-01
7.40842164e-01 4.40715104e-01 6.84125543e-01 -9.19090450e-01
1.27170897e+00 8.12819898e-01 2.97087252e-01 -8.60351086e-01
-5.42454243e-01 -5.35259366e-01 -1.02607286e+00 2.57944375e-01
5.78848600e-01 -9.97279406e-01 -8.40334237e-01 4.66054589e-01
-1.55506742e+00 -3.91947299e-01 -6.08159661e-01 2.16629311e-01
-7.76197672e-01 1.71502784e-01 -4.72205549e-01 -5.83229303e-01
-2.87933290e-01 -1.06785858e+00 1.46737337e+00 -1.77503079e-01
5.05192466e-02 -8.72201681e-01 -2.28654757e-01 -6.86760098e-02
3.40661258e-01 2.72968590e-01 1.06870556e+00 -6.63367867e-01
-1.00831211e+00 -3.01055014e-01 -4.13266957e-01 6.19118571e-01
-6.61496967e-02 1.83776885e-01 -1.13429105e+00 -3.32863890e-02
-1.26619667e-01 -6.66232929e-02 6.26429796e-01 6.03436947e-01
1.80394197e+00 -2.19477639e-01 -4.07556742e-01 1.29897296e+00
1.21553516e+00 -2.42911905e-01 4.87324476e-01 1.67961210e-01
9.37695861e-01 1.32530302e-01 6.57187477e-02 2.25457028e-01
7.12445021e-01 5.94412267e-01 7.29423821e-01 -1.46116227e-01
7.83840269e-02 -5.01405656e-01 -7.37827271e-02 6.58767879e-01
-3.98880690e-01 8.33016336e-02 -1.09413803e+00 3.38874102e-01
-1.71294212e+00 -6.50497496e-01 -8.15666988e-02 2.20358968e+00
6.33687198e-01 2.62439221e-01 1.81962460e-01 -1.32566214e-01
5.52530050e-01 2.57325321e-01 -8.07263553e-01 -1.98529348e-01
-1.73558518e-01 4.56453800e-01 7.04028428e-01 3.49502802e-01
-1.19595897e+00 9.59606230e-01 6.11892700e+00 1.05212080e+00
-1.13261640e+00 -7.13001266e-02 3.43054712e-01 -1.86769173e-01
-5.01392543e-01 -2.92746592e-02 -9.47637677e-01 3.50597322e-01
7.98778117e-01 9.90161821e-02 3.27266216e-01 1.26546192e+00
2.50836045e-01 4.61455107e-01 -1.57539225e+00 1.14917839e+00
-2.81596065e-01 -1.71588707e+00 3.32207441e-01 1.66168422e-01
4.70036834e-01 5.86395741e-01 1.05342068e-01 4.68735725e-01
2.49480978e-01 -1.09530795e+00 7.23630428e-01 5.57044804e-01
9.37300086e-01 -7.60391176e-01 5.46462595e-01 4.46521819e-01
-1.06786323e+00 2.26741806e-01 -7.24850178e-01 -5.37250517e-03
1.55737370e-01 8.06311250e-01 -8.34056437e-01 5.90279222e-01
6.96415067e-01 7.62977481e-01 -3.15944016e-01 1.18765378e+00
-1.85256496e-01 4.16003913e-01 -9.24387395e-01 4.10166979e-02
2.99535722e-01 -1.41152725e-01 7.34301805e-01 1.00265050e+00
5.43680429e-01 1.78652070e-02 -8.42689723e-02 1.22041142e+00
-3.43446016e-01 -9.14890319e-02 -7.29752481e-01 2.64638871e-01
8.09232950e-01 1.00870073e+00 -4.01087940e-01 -1.54872239e-01
-4.55107301e-01 5.95700681e-01 5.07430553e-01 3.47606301e-01
-7.53361583e-01 -3.81058604e-01 8.81457090e-01 5.21185935e-01
6.36982501e-01 -7.11939812e-01 -6.04221702e-01 -8.32972288e-01
2.32107967e-01 -3.05623323e-01 -2.62335688e-01 -9.99550641e-01
-1.45077384e+00 3.85075092e-01 2.28757933e-01 -1.41327131e+00
-1.47484243e-01 -1.01198030e+00 -5.63567877e-01 9.29397762e-01
-1.86424041e+00 -1.40783989e+00 -3.23161304e-01 4.39477712e-01
1.68905392e-01 1.61497593e-01 6.79247737e-01 1.85653180e-01
-1.32601678e-01 6.33148968e-01 1.18761219e-01 8.97429362e-02
4.73855644e-01 -1.27089489e+00 1.10792327e+00 2.31330782e-01
-8.91443621e-03 7.56427944e-01 1.64483577e-01 -3.93047154e-01
-1.59984195e+00 -1.19080651e+00 5.53499997e-01 -8.63386869e-01
6.34735465e-01 -6.91929221e-01 -1.06357932e+00 7.34928429e-01
-5.41213989e-01 3.45932364e-01 5.06153524e-01 1.62833169e-01
-4.59995061e-01 -5.41497655e-02 -9.71701384e-01 5.83462000e-01
1.30871022e+00 -5.48244238e-01 -6.35213614e-01 2.71919101e-01
1.22787499e+00 -8.37032676e-01 -1.11461616e+00 5.77956736e-01
4.30648863e-01 -1.01020300e+00 1.56882358e+00 -2.86779583e-01
4.78383929e-01 -2.80867666e-01 -2.09617466e-01 -1.04276049e+00
-4.85195100e-01 -7.50394881e-01 -5.01140594e-01 8.86450112e-01
3.63121331e-01 -5.91988027e-01 1.13136137e+00 5.64265907e-01
-6.38881445e-01 -1.30667520e+00 -1.11737370e+00 -1.04734409e+00
5.12212992e-01 -9.39210355e-01 1.26072502e+00 7.34090090e-01
-6.64845943e-01 -5.88149903e-03 -7.53916427e-02 4.09092188e-01
4.73822355e-01 -1.80924349e-02 1.20039856e+00 -1.46091878e+00
-7.60277584e-02 -6.02925479e-01 -5.26531816e-01 -1.80016661e+00
2.15765953e-01 -9.84522343e-01 -2.16086701e-01 -1.46975505e+00
-4.52589780e-01 -7.40810752e-01 5.05390717e-03 5.52108049e-01
1.32445708e-01 2.01321945e-01 3.48042846e-02 4.21062559e-01
-3.01702201e-01 8.11322331e-01 1.41900516e+00 1.32735923e-01
-4.66338366e-01 3.75151068e-01 -5.20061910e-01 1.04140222e+00
8.26351643e-01 -2.42893666e-01 -2.40845516e-01 -7.32728839e-01
1.77911129e-02 -1.86200991e-01 7.53708303e-01 -9.83222604e-01
3.09729248e-01 -1.72377322e-02 4.68291283e-01 -1.18592978e+00
8.28192115e-01 -9.45005238e-01 2.19877232e-02 -1.64291292e-01
2.72575468e-01 6.06518723e-02 4.35512632e-01 3.10284913e-01
9.43502225e-03 -3.37952301e-02 6.38075888e-01 -1.72720730e-01
-5.94971120e-01 8.79963815e-01 3.09116811e-01 -1.86317876e-01
7.32906520e-01 -6.74042583e-01 -2.72915572e-01 -1.33491874e-01
-3.99711996e-01 1.80226699e-01 7.77325988e-01 3.18561077e-01
5.82339883e-01 -1.50954473e+00 -5.19553065e-01 3.30948949e-01
4.93515581e-02 9.01431978e-01 2.53020853e-01 4.72961128e-01
-7.63722897e-01 4.85946357e-01 6.15544012e-03 -1.09491360e+00
-4.17890936e-01 4.10739601e-01 3.06167603e-01 4.52188402e-02
-7.52959967e-01 9.26627874e-01 1.65137872e-01 -1.01530206e+00
2.19813421e-01 -8.66595387e-01 4.91218776e-01 -3.71481270e-01
1.31477043e-01 4.62059647e-01 2.35589266e-01 -3.67161870e-01
-3.18639040e-01 8.97305191e-01 1.47850290e-01 2.82420397e-01
1.60403013e+00 3.09330583e-01 -1.89253896e-01 6.63728774e-01
1.42108071e+00 -1.08495444e-01 -1.53715992e+00 -3.72296274e-01
-2.74354488e-01 -3.46940905e-01 -3.46843079e-02 -4.43090826e-01
-7.27040887e-01 9.62645829e-01 4.30638790e-02 2.66351476e-02
7.86405087e-01 3.16916078e-01 7.00928748e-01 6.94581807e-01
4.70833004e-01 -5.39448440e-01 -3.50619614e-01 7.39117444e-01
1.01175189e+00 -1.04690051e+00 6.71680868e-02 -6.31220043e-01
-1.97053589e-02 1.16382790e+00 4.80784327e-01 -6.45786047e-01
1.08045065e+00 3.68786514e-01 -1.83933720e-01 -1.94769248e-01
-5.53157449e-01 1.25618666e-01 5.23014963e-01 8.64361882e-01
8.59085023e-02 6.57580644e-02 5.02118945e-01 7.10224450e-01
-7.26548672e-01 1.99972674e-01 1.27153937e-02 5.55062830e-01
-2.98666209e-01 -1.00983357e+00 -2.16566324e-01 5.95652163e-01
7.09076971e-03 -1.21136710e-01 -1.63244531e-01 1.22800446e+00
3.79484482e-02 6.74800724e-02 2.93787837e-01 -3.18700165e-01
6.31454170e-01 3.56955342e-02 4.38808948e-01 -4.51634169e-01
-2.14245781e-01 -2.19950646e-01 -2.96265751e-01 -8.92408729e-01
-1.10411972e-01 -4.55320805e-01 -1.00904572e+00 -6.27584040e-01
-4.42722961e-02 -1.33759618e-01 7.64602482e-01 5.50992191e-01
8.51100445e-01 1.34318069e-01 4.66495842e-01 -1.69505608e+00
-6.85230434e-01 -8.02629352e-01 -4.54319239e-01 5.21725714e-02
4.66445625e-01 -7.73995817e-01 -4.18186694e-01 -3.52947980e-01] | [8.092841148376465, -3.6542787551879883] |
77a822c0-502d-460f-9146-3d42fa1822cf | insertgnn-can-graph-neural-networks | 2103.15066 | null | https://arxiv.org/abs/2103.15066v2 | https://arxiv.org/pdf/2103.15066v2.pdf | InsertGNN: Can Graph Neural Networks Outperform Humans in TOEFL Sentence Insertion Problem? | Sentence insertion is an interesting NLP problem but received insufficient attention. Existing approaches in sentence ordering, text coherence, and question answering are neither suitable nor good enough at solving it. To bridge this gap, we propose InsertGNN, a simple yet effective model that represents the problem as a graph and adopts a hierarchical graph neural network (GNN) to learn the connection between sentences. We evaluate our method in our newly collected TOEFL dataset and further verify its effectiveness on the larger arXiv dataset using cross-domain learning. Extensive experiments demonstrate that InsertGNN outperforms all baselines by a large margin with an accuracy of 70\%, rivaling the average human test scores. | ['Stan Z. Li', 'Fang Wu'] | 2021-03-28 | null | null | null | null | ['sentence-ordering'] | ['natural-language-processing'] | [-7.38318563e-02 3.81839037e-01 -3.80601794e-01 -3.82105112e-01
-8.87125909e-01 -5.21110058e-01 7.11004615e-01 6.29313767e-01
-3.11246485e-01 8.42624128e-01 6.80924892e-01 -5.11970043e-01
-3.82089287e-01 -5.39472222e-01 -7.31975317e-01 1.23711109e-01
-1.56365782e-01 8.47115695e-01 5.82274377e-01 -6.48432910e-01
5.11289477e-01 -2.43492573e-01 -7.96356857e-01 3.96656096e-01
1.18818903e+00 6.13336325e-01 -1.76767039e-03 8.06415021e-01
-3.18907619e-01 1.20542705e+00 -7.04833984e-01 -7.00239062e-01
-1.01039670e-01 -2.73553878e-01 -1.56798410e+00 -1.76759914e-01
8.96864951e-01 -1.80089355e-01 -6.85182750e-01 9.14163649e-01
3.93556505e-01 1.78739682e-01 4.83282089e-01 -8.77301633e-01
-9.85153198e-01 1.18580425e+00 -3.34640235e-01 3.30525964e-01
7.81816900e-01 -6.88973144e-02 1.85994041e+00 -7.21385598e-01
7.28543818e-01 1.28029931e+00 7.38508999e-01 3.10253292e-01
-1.22119761e+00 -1.96098208e-01 2.20885321e-01 2.07301959e-01
-1.02820611e+00 -2.49142036e-01 7.75470376e-01 -1.96371675e-01
1.50994062e+00 2.87937313e-01 5.43059349e-01 1.00096536e+00
1.75851479e-01 7.92929590e-01 7.26183057e-01 -4.26599264e-01
-1.13928489e-01 -2.95543194e-01 7.54702508e-01 5.82630515e-01
3.26072693e-01 -5.82297027e-01 -8.12856317e-01 -1.24093577e-01
1.62779197e-01 -4.82216775e-01 -3.69635820e-01 -9.38631818e-02
-9.69821036e-01 8.39986324e-01 6.44896030e-01 4.22406703e-01
7.41688302e-03 2.07190871e-01 3.79044592e-01 6.85785770e-01
7.87519395e-01 1.04904282e+00 -5.34011424e-01 5.09344041e-02
-7.56480873e-01 4.02866870e-01 1.27843797e+00 9.79985833e-01
4.10368025e-01 -3.98941487e-01 -3.97308022e-01 8.09662342e-01
1.50893465e-01 2.55190790e-01 2.46663451e-01 -8.54673803e-01
8.41281652e-01 8.42179298e-01 -2.37343535e-01 -1.31380749e+00
-6.41466677e-01 -5.93092501e-01 -8.34795475e-01 -7.34309733e-01
4.43748504e-01 -4.22348902e-02 -4.45422381e-01 1.55500352e+00
7.40885437e-02 3.62283140e-02 -8.12859386e-02 6.24114871e-01
1.22213519e+00 5.95097721e-01 -1.26990169e-01 -7.85393268e-02
1.10062349e+00 -1.19484043e+00 -6.03783727e-01 -6.74337029e-01
9.48789060e-01 -6.41312540e-01 1.30285680e+00 3.91756773e-01
-1.09362209e+00 -2.81310320e-01 -1.02131295e+00 -6.58421159e-01
-1.17547594e-01 -2.66667098e-01 7.94468462e-01 1.69955313e-01
-1.54897439e+00 7.55020499e-01 -3.31618071e-01 -7.17907429e-01
2.21811011e-01 4.44394886e-01 -2.39968494e-01 -1.61581874e-01
-1.46965826e+00 8.90083790e-01 6.27684653e-01 -9.29868072e-02
-3.26809615e-01 -7.47336686e-01 -7.92048931e-01 1.66361541e-01
5.30499756e-01 -1.00322688e+00 1.39298344e+00 -8.15573186e-02
-1.31572866e+00 8.27957630e-01 -4.31362577e-02 -9.81274307e-01
1.52119711e-01 -3.37191463e-01 -3.38502109e-01 2.19609290e-01
3.52161415e-02 5.58038592e-01 3.25987250e-01 -7.22086668e-01
-2.56844282e-01 -3.87707911e-02 2.26799548e-01 2.49292314e-01
-6.85593784e-01 -1.43069625e-01 -5.74707150e-01 -2.91324109e-01
9.90015641e-02 -7.40911484e-01 -1.85410708e-01 -7.90774822e-01
-9.87688541e-01 -8.79084766e-01 3.68230879e-01 -7.17892349e-01
1.69173634e+00 -1.57734704e+00 2.03056872e-01 3.89249176e-02
7.00291276e-01 1.24137066e-01 -4.39752847e-01 7.92022049e-01
1.05074771e-01 3.27494949e-01 -1.18691809e-01 -3.59016865e-01
1.22040331e-01 -2.74174307e-02 -2.77031183e-01 1.53986305e-01
1.43480748e-01 1.34526265e+00 -1.14844608e+00 -6.43589914e-01
-2.56094813e-01 -8.37785751e-02 -7.44136691e-01 7.89017230e-02
-6.24731123e-01 1.75772179e-02 -2.52756178e-01 3.05465937e-01
3.35888982e-01 -7.95103848e-01 6.91691101e-01 7.05775246e-02
4.64470923e-01 8.58298779e-01 -5.90660095e-01 1.75409091e+00
-4.19477327e-03 8.39618027e-01 -2.46550620e-01 -9.11664307e-01
8.43252361e-01 -6.08959533e-02 2.31437191e-01 -9.67940807e-01
-2.33243302e-01 1.25067353e-01 7.74021596e-02 -6.68195248e-01
9.15839374e-01 2.38863379e-01 -2.73872137e-01 3.98650140e-01
1.67815432e-01 -4.84485865e-01 5.66019535e-01 1.07281470e+00
1.63568842e+00 -3.69723767e-01 2.97082782e-01 -4.80678499e-01
3.83932292e-01 2.19436996e-02 7.33491853e-02 1.10493767e+00
4.89677154e-02 4.27628666e-01 1.04467702e+00 -1.34682223e-01
-8.46879125e-01 -7.39666402e-01 1.03860468e-01 1.14064670e+00
1.13976104e-02 -9.65126932e-01 -6.96844876e-01 -9.75430906e-01
2.20796421e-01 8.83639932e-01 -4.92138624e-01 -6.69522285e-02
-7.08191276e-01 -6.05482757e-01 2.69521952e-01 3.54490072e-01
3.51012468e-01 -1.03967774e+00 3.13271523e-01 8.91356915e-02
-6.24521315e-01 -1.52910435e+00 -6.29831195e-01 -1.09547459e-01
-9.20633614e-01 -1.09333265e+00 -2.46131256e-01 -9.77218747e-01
4.32665586e-01 4.48993713e-01 2.02335310e+00 5.30249536e-01
1.29487932e-01 2.99696684e-01 -3.70196223e-01 -6.20242842e-02
-3.60083461e-01 7.35248148e-01 -2.78874725e-01 -6.13584518e-01
3.68042618e-01 -4.71552074e-01 -6.02863610e-01 -2.25190714e-01
-7.13744581e-01 -2.25476891e-01 3.21767688e-01 8.42777193e-01
-3.15838754e-02 -2.08163291e-01 8.05829704e-01 -1.37485838e+00
1.37103224e+00 -5.43999255e-01 -3.78066719e-01 3.29740465e-01
-8.49024296e-01 1.52590871e-03 5.29019177e-01 1.49333432e-01
-6.32442474e-01 -5.18827081e-01 -1.79916978e-01 3.72903317e-01
2.90681213e-01 9.75271761e-01 1.75612897e-01 9.28474888e-02
7.19114304e-01 -1.10303439e-01 -2.29037091e-01 -3.08656871e-01
5.83910227e-01 4.03256595e-01 5.23207903e-01 -3.52214277e-01
7.16977894e-01 3.61126326e-02 -1.06540509e-01 -6.68460786e-01
-1.55933499e+00 -6.52163684e-01 -5.91877878e-01 6.29365295e-02
7.26890087e-01 -8.33154678e-01 -7.95821309e-01 7.11550787e-02
-1.43919623e+00 -4.34324652e-01 -2.42799949e-02 8.40179622e-02
-1.08845502e-01 7.66270459e-01 -1.00446904e+00 -3.75447452e-01
-5.78167498e-01 -4.43054438e-01 1.04174650e+00 4.13731672e-02
-5.09782255e-01 -1.34128439e+00 1.42042160e-01 7.40165353e-01
3.56139451e-01 -1.10151753e-01 1.13620257e+00 -9.96820927e-01
-6.57007337e-01 -2.61791676e-01 -3.99714947e-01 1.55336991e-01
-2.48548344e-01 -5.96362576e-02 -4.90548819e-01 -2.97081828e-01
-2.24379092e-01 -6.52979016e-01 1.29032159e+00 2.80241489e-01
1.17623591e+00 -4.15098667e-01 -2.97823578e-01 1.03333980e-01
1.26533890e+00 -4.18692410e-01 5.83973229e-01 3.85354877e-01
7.47819424e-01 6.15279675e-01 2.02244192e-01 2.53630787e-01
9.59541202e-01 4.44022357e-01 5.27320862e-01 -2.86993627e-02
-3.67232651e-01 -4.29362476e-01 1.39888257e-01 1.54975498e+00
4.10195172e-01 -8.37875485e-01 -1.15809643e+00 4.96895730e-01
-2.03627849e+00 -9.13613379e-01 -5.58013797e-01 1.79137552e+00
9.74281311e-01 6.86792314e-01 1.69226378e-02 -1.68491900e-01
4.24525976e-01 3.75733733e-01 -1.45066574e-01 -3.77454132e-01
-4.49232638e-01 2.89092958e-01 3.78148742e-02 9.62014496e-01
-1.24101031e+00 1.18996620e+00 7.13314676e+00 6.03313804e-01
-5.79736829e-01 -2.38049388e-01 6.24669313e-01 8.97174031e-02
-6.77692950e-01 1.27006918e-01 -6.93660140e-01 2.33655706e-01
9.53732550e-01 -3.55615497e-01 4.46303546e-01 4.76671994e-01
-2.16462165e-02 -9.21408311e-02 -1.15284121e+00 6.74211144e-01
4.02919322e-01 -1.55082238e+00 1.17545366e-01 -3.32028627e-01
8.27251673e-01 2.54923671e-01 -1.09243296e-01 6.71191275e-01
6.43467069e-01 -1.10888624e+00 2.17088565e-01 5.95379114e-01
2.76205689e-01 -4.90665376e-01 8.11294615e-01 3.79084706e-01
-7.91745007e-01 1.39917761e-01 -4.18983668e-01 -4.02812719e-01
4.31292318e-02 8.38301897e-01 -1.32976043e+00 8.01115274e-01
5.34451663e-01 9.30690289e-01 -1.26382244e+00 1.06480122e+00
-4.74419773e-01 9.86082315e-01 -5.66192232e-02 -4.95824486e-01
3.35960388e-01 -2.21156087e-02 5.03069162e-01 1.34361494e+00
-8.54380429e-03 -9.54621658e-02 3.43143702e-01 5.47479033e-01
-6.94091558e-01 2.78503537e-01 -6.48041785e-01 -2.70584106e-01
4.11775142e-01 1.20343184e+00 -4.73919362e-01 -3.22673053e-01
-3.94240141e-01 1.00251961e+00 9.62812662e-01 4.24758196e-01
-5.74664772e-01 -5.55316448e-01 3.03696468e-02 -9.75334272e-02
1.69068336e-01 -3.87286127e-01 -4.41295326e-01 -1.34934640e+00
2.47151181e-01 -8.64841163e-01 5.32098234e-01 -6.27189934e-01
-1.73421812e+00 6.91256046e-01 -2.16984093e-01 -9.18120146e-01
-4.10833091e-01 -4.37425733e-01 -5.34094751e-01 5.85737705e-01
-1.55596435e+00 -1.02605188e+00 -2.20969558e-01 3.09707075e-01
2.89300203e-01 -2.50297263e-02 6.46548748e-01 1.30991176e-01
-6.59316480e-01 5.15495777e-01 -3.85892647e-03 2.81999320e-01
8.02219033e-01 -1.64414549e+00 8.16178381e-01 8.16466808e-01
3.63530099e-01 8.19070816e-01 8.74537587e-01 -7.34492242e-01
-1.37841296e+00 -9.36186552e-01 1.73848581e+00 -8.44978333e-01
1.16052485e+00 -6.17720306e-01 -1.01507437e+00 6.76383317e-01
9.41624165e-01 -3.05352926e-01 6.34908080e-01 8.44569266e-01
-5.10028899e-01 -1.84248537e-02 -5.72505176e-01 7.13888943e-01
1.20596397e+00 -6.26402259e-01 -8.85404050e-01 1.05791426e+00
1.43701839e+00 -5.48408628e-01 -8.58751297e-01 3.87160778e-01
-1.39456332e-01 -8.83918881e-01 9.18239474e-01 -8.82178545e-01
8.21014881e-01 8.34497288e-02 2.08830070e-02 -1.30327237e+00
-4.64064419e-01 -8.40739429e-01 -2.92134017e-01 1.35089004e+00
8.40238690e-01 -5.41576922e-01 8.81225109e-01 4.25670803e-01
-2.34972641e-01 -8.71255875e-01 -7.78244019e-01 -7.59599447e-01
3.12973082e-01 -4.66192573e-01 4.30898726e-01 9.95596588e-01
5.26215255e-01 1.21880364e+00 -2.60020435e-01 -1.94374949e-01
4.89345878e-01 1.59695163e-01 6.51405394e-01 -1.33984172e+00
-4.00865555e-01 -5.80973566e-01 -3.87606397e-02 -1.38754845e+00
5.31368256e-01 -1.36087489e+00 -9.08394009e-02 -2.18359995e+00
5.13357162e-01 -8.33477452e-03 -1.00348264e-01 1.96274176e-01
-5.33739209e-01 -4.47169058e-02 2.01712534e-01 6.96454197e-02
-1.58267236e+00 5.96665204e-01 1.26329279e+00 -4.17329222e-01
1.18797749e-01 -2.46947408e-01 -1.08928013e+00 5.08902252e-01
6.82822883e-01 -2.98788846e-01 -4.68718857e-01 -8.02675784e-01
7.48846531e-01 3.75473984e-02 2.59186745e-01 -8.04071248e-01
7.04341650e-01 2.09486559e-01 1.10175513e-01 -7.30144918e-01
-1.68037768e-02 -1.99792102e-01 -6.63047433e-01 2.16713890e-01
-8.00365865e-01 2.10666016e-01 -4.95444089e-02 7.94026613e-01
-3.35541815e-01 -1.34595588e-01 1.42206684e-01 -2.65057404e-02
-5.54524839e-01 2.71343350e-01 3.89073230e-02 8.34211707e-01
4.07023937e-01 3.53061408e-01 -9.45099235e-01 -8.08969140e-01
-3.57161760e-01 7.80130148e-01 7.28062615e-02 4.64182824e-01
6.58587933e-01 -1.13361001e+00 -8.60437632e-01 -3.84233981e-01
1.35485366e-01 -9.71988067e-02 1.02293618e-01 8.25102508e-01
-5.22061765e-01 9.09905910e-01 6.10129833e-01 -5.12008548e-01
-9.96223211e-01 4.53324825e-01 1.52332067e-01 -8.62823486e-01
-4.91761148e-01 1.13054121e+00 -3.35795134e-01 -7.96804547e-01
1.92206383e-01 -3.27503532e-01 -4.81820941e-01 -5.64970262e-02
1.96119368e-01 1.14505462e-01 2.39739761e-01 -2.51975581e-02
-3.38960439e-01 3.18353087e-01 -3.41840863e-01 2.67203957e-01
1.30699575e+00 -1.73487365e-01 -6.36774421e-01 1.71626002e-01
1.26532996e+00 6.57432526e-02 -5.22605121e-01 -5.85153759e-01
7.48533547e-01 -1.37054279e-01 -1.90235779e-01 -7.31313229e-01
-4.69554663e-01 5.91519535e-01 -2.73843914e-01 9.32424426e-01
8.97969604e-01 2.91904300e-01 1.05968940e+00 7.96753645e-01
7.00854138e-02 -1.08244157e+00 7.30573893e-01 1.26097226e+00
1.08757687e+00 -1.35811281e+00 1.59307390e-01 -6.15621805e-01
-6.00447178e-01 1.19134700e+00 8.19689214e-01 -3.15343857e-01
4.80002791e-01 4.96371761e-02 -2.64070541e-01 -4.82469440e-01
-1.17771029e+00 -2.23529309e-01 6.78346276e-01 2.12277636e-01
7.72083759e-01 -7.12381676e-02 -5.38968265e-01 4.69482869e-01
-4.75524336e-01 -1.93661243e-01 5.70112228e-01 5.78509569e-01
-5.65711737e-01 -1.08529627e+00 2.68575281e-01 6.83017612e-01
-2.64530629e-01 -5.49146831e-01 -8.16362202e-01 7.27277219e-01
-5.12385488e-01 1.27893448e+00 -9.12343040e-02 -6.79964721e-01
4.31175917e-01 -1.36562154e-01 3.68617415e-01 -8.89527917e-01
-8.02242160e-01 -1.69459179e-01 6.82164073e-01 -5.41933179e-01
-1.72208130e-01 -4.96163934e-01 -1.20860362e+00 -4.71965849e-01
-2.22457498e-01 2.51728743e-01 4.87369634e-02 9.70334888e-01
5.19847631e-01 7.05426693e-01 4.46180284e-01 -1.11255690e-01
-8.41046393e-01 -1.09206986e+00 -3.46753299e-01 4.80192959e-01
1.97073460e-01 4.99950051e-02 -4.12276864e-01 -4.52098131e-01] | [11.329943656921387, 8.782584190368652] |
c78132f9-1b83-4c8d-9c67-e08e40e9f4c7 | mono-camera-3d-multi-object-tracking-using | 1802.09975 | null | http://arxiv.org/abs/1802.09975v1 | http://arxiv.org/pdf/1802.09975v1.pdf | Mono-Camera 3D Multi-Object Tracking Using Deep Learning Detections and PMBM Filtering | Monocular cameras are one of the most commonly used sensors in the automotive
industry for autonomous vehicles. One major drawback using a monocular camera
is that it only makes observations in the two dimensional image plane and can
not directly measure the distance to objects. In this paper, we aim at filling
this gap by developing a multi-object tracking algorithm that takes an image as
input and produces trajectories of detected objects in a world coordinate
system. We solve this by using a deep neural network trained to detect and
estimate the distance to objects from a single input image. The detections from
a sequence of images are fed in to a state-of-the art Poisson multi-Bernoulli
mixture tracking filter. The combination of the learned detector and the PMBM
filter results in an algorithm that achieves 3D tracking using only mono-camera
images as input. The performance of the algorithm is evaluated both in 3D world
coordinates, and 2D image coordinates, using the publicly available KITTI
object tracking dataset. The algorithm shows the ability to accurately track
objects, correctly handle data associations, even when there is a big overlap
of the objects in the image, and is one of the top performing algorithms on the
KITTI object tracking benchmark. Furthermore, the algorithm is efficient,
running on average close to 20 frames per second. | ['Emil Rosenberg', 'Joachim Benjaminsson', 'Karl Granstrom', 'Samuel Scheidegger', 'Amrit Krishnan'] | 2018-02-27 | null | null | null | null | ['3d-multi-object-tracking'] | ['computer-vision'] | [-2.90846229e-01 -6.00440979e-01 -1.76310182e-01 9.94986370e-02
-4.66810197e-01 -6.19376242e-01 7.87829399e-01 -3.43088627e-01
-8.61852467e-01 3.80438328e-01 -8.20845068e-01 -1.05150379e-01
2.11678714e-01 -5.35596192e-01 -1.12974107e+00 -8.94255877e-01
3.83295059e-01 1.09386730e+00 9.46011722e-01 4.56595510e-01
1.11091118e-02 9.06972170e-01 -1.81613731e+00 -1.43262610e-01
1.23507781e-02 1.21762443e+00 4.69323307e-01 1.01422632e+00
-2.21350603e-02 5.27656257e-01 -4.99670953e-01 -3.25168848e-01
4.15304124e-01 1.84975177e-01 -4.22542207e-02 1.90470576e-01
9.28535819e-01 -4.79178280e-01 -3.80687177e-01 1.12500393e+00
9.02765244e-02 -2.04486132e-01 6.96571350e-01 -1.60457516e+00
-1.09065436e-01 -3.73116583e-02 -7.42625773e-01 5.05187035e-01
-2.49601658e-02 4.09149915e-01 3.57795984e-01 -1.03220391e+00
6.68993592e-01 1.47813988e+00 6.98342562e-01 5.28938770e-01
-9.37215090e-01 -9.12257969e-01 -5.73802069e-02 3.36160481e-01
-1.37214530e+00 -2.91123062e-01 2.56946981e-01 -7.28423715e-01
8.83219242e-01 -1.43333256e-01 5.08302212e-01 9.21868265e-01
5.64457357e-01 6.36113822e-01 8.01348269e-01 -1.24344051e-01
1.00393422e-01 2.75986493e-01 2.49035716e-01 5.82667947e-01
6.20216548e-01 5.83082497e-01 -1.80665046e-01 -6.34909645e-02
6.26706719e-01 3.51408362e-01 3.15369427e-01 -7.24450290e-01
-1.02007937e+00 7.01211214e-01 1.62426189e-01 2.63684452e-01
-1.88906893e-01 6.09356165e-01 6.60639107e-02 6.84520369e-03
4.06679958e-01 -3.91879648e-01 -2.34729573e-01 -7.75875151e-02
-9.26865637e-01 4.44549859e-01 4.75990891e-01 1.13974595e+00
7.28975832e-01 -2.04510510e-01 3.60639617e-02 2.84376621e-01
6.21650457e-01 1.16845250e+00 -3.98632186e-03 -9.60976005e-01
2.46071875e-01 4.41970885e-01 3.43620211e-01 -7.51444101e-01
-4.99343395e-01 -2.35314071e-01 -3.67546588e-01 9.75029647e-01
6.60345554e-01 -1.25089467e-01 -8.22572589e-01 1.49537814e+00
6.56586528e-01 4.52082992e-01 -9.32764038e-02 8.95967245e-01
5.98103762e-01 5.48454225e-01 -1.60303459e-01 -1.03162222e-01
1.48552465e+00 -8.06423903e-01 -5.79940915e-01 -4.62788969e-01
4.14140046e-01 -8.78716648e-01 -9.40751210e-02 2.33729288e-01
-1.04639828e+00 -8.59574735e-01 -9.67362165e-01 3.19611847e-01
-4.70048815e-01 4.17415828e-01 -1.05945744e-01 7.57794619e-01
-8.36917818e-01 2.06411853e-01 -1.04702568e+00 -3.02140504e-01
4.30918306e-01 4.44891125e-01 -3.95956993e-01 -2.87689745e-01
-6.58514559e-01 1.31407177e+00 5.70505142e-01 -1.67787969e-01
-9.99378562e-01 -8.02793205e-01 -7.79646814e-01 -3.23070824e-01
5.28632343e-01 -5.24630070e-01 1.07611704e+00 -5.63694894e-01
-1.11106062e+00 9.20245349e-01 -3.63425136e-01 -7.61459053e-01
8.47116172e-01 -5.46751261e-01 -3.44403833e-01 2.87018996e-02
1.06094241e-01 1.02697802e+00 1.03438926e+00 -1.36170220e+00
-1.35938776e+00 -5.24438083e-01 -2.99568236e-01 -1.12876274e-01
2.65870720e-01 3.43716234e-01 -8.18758607e-01 8.42284858e-02
-2.76647061e-01 -1.33912206e+00 -5.34200296e-03 1.81122676e-01
-7.52591491e-02 -3.77987027e-01 1.58195579e+00 -2.11253315e-01
4.39683765e-01 -2.28841972e+00 3.21946815e-02 -2.09734499e-01
2.39299506e-01 4.63045925e-01 1.46133795e-01 -1.93605255e-02
2.94450402e-01 -5.41409969e-01 2.59198874e-01 -8.23397815e-01
-1.43232226e-01 2.86415488e-01 -1.03617564e-01 1.06259465e+00
1.24501809e-01 9.10274088e-01 -8.70567381e-01 -4.82549489e-01
6.79982841e-01 4.37914938e-01 -1.37293428e-01 7.79731050e-02
-4.54344898e-01 4.42132831e-01 4.11171988e-02 2.53664851e-01
1.10673451e+00 -3.46642174e-02 -3.85248989e-01 -5.72837330e-02
-4.39692199e-01 -3.42416018e-01 -1.47768104e+00 1.05762386e+00
-1.28795579e-01 9.88975942e-01 -5.19060493e-02 -4.45533514e-01
7.90096223e-01 1.92997813e-01 7.34721959e-01 -3.75457138e-01
3.91223878e-01 1.73107430e-01 -6.57505989e-02 -1.75997108e-01
4.49046284e-01 2.85682530e-04 9.23556983e-02 3.54057163e-01
1.54148445e-01 -2.26012934e-02 4.74809021e-01 -6.14138804e-02
1.03043842e+00 1.10979285e-02 -1.59490407e-02 1.85141891e-01
4.91639465e-01 2.17555627e-01 4.77200359e-01 8.40038180e-01
-2.47783199e-01 5.75535595e-01 4.96382006e-02 -5.92815161e-01
-1.19165993e+00 -1.12184107e+00 -1.41887411e-01 5.93416333e-01
5.68407595e-01 8.24812502e-02 -4.39155549e-01 -5.43909609e-01
3.89622152e-01 5.81073582e-01 -5.46698749e-01 -1.56511173e-01
-7.57574022e-01 -5.24914682e-01 4.35339153e-01 5.58871269e-01
3.24207306e-01 -7.64656544e-01 -1.13043499e+00 1.62620932e-01
2.44707614e-01 -1.81173217e+00 -2.54486263e-01 4.89525013e-02
-5.64613581e-01 -1.32531869e+00 -6.50162995e-01 -4.67014104e-01
4.32550311e-01 7.68383026e-01 9.92488444e-01 -1.51705593e-01
-4.39399809e-01 6.04659259e-01 6.94418624e-02 -8.22299302e-01
-6.87772274e-01 -3.34995687e-01 3.21413815e-01 1.59635678e-01
7.40093589e-01 1.50949106e-01 -3.63915712e-01 6.16314292e-01
-6.38310611e-01 -3.34533639e-02 6.94117606e-01 3.59945714e-01
4.85305935e-01 -1.39333736e-02 -8.64120573e-03 -4.45722371e-01
-2.57698148e-01 -4.99417216e-01 -1.56916010e+00 -1.30316541e-01
-2.02639431e-01 -2.71912128e-01 2.04266429e-01 -6.06428504e-01
-6.73428833e-01 6.90330803e-01 1.50077164e-01 -1.11166537e+00
-4.59567815e-01 -2.77240247e-01 9.58372280e-02 -2.54399419e-01
2.57628053e-01 1.55667812e-01 3.04238290e-01 -3.03476870e-01
4.13439721e-01 2.91570008e-01 5.65320790e-01 1.31758228e-01
1.05876386e+00 9.18218493e-01 3.56881410e-01 -9.25286174e-01
-7.15195119e-01 -9.77486789e-01 -9.72536325e-01 -6.50274098e-01
1.13816595e+00 -1.15822816e+00 -9.36071217e-01 6.54797435e-01
-1.43425691e+00 -9.35681686e-02 4.92891390e-03 7.08122253e-01
-5.97946286e-01 2.80853242e-01 -2.15954453e-01 -1.09629226e+00
1.54972568e-01 -1.27586734e+00 1.39275825e+00 3.56479555e-01
2.18898788e-01 -8.11410546e-01 1.97086886e-01 1.89100191e-01
2.22616002e-01 -4.23203819e-02 2.53338307e-01 -4.59560901e-01
-1.15467680e+00 -5.36002994e-01 -3.36919129e-01 2.91318148e-01
-1.16493516e-01 1.39624447e-01 -9.42586482e-01 -3.73900056e-01
9.87159610e-02 4.19772156e-02 1.01852787e+00 7.21225560e-01
5.77048540e-01 3.52329314e-01 -9.09574986e-01 2.73114383e-01
1.44244504e+00 3.47622365e-01 2.85312623e-01 1.86140761e-01
6.81299329e-01 2.01274827e-01 8.57398570e-01 1.30329311e-01
1.81556493e-01 1.14040887e+00 8.09316516e-01 2.39764675e-01
-2.39119411e-01 3.43156725e-01 4.94441926e-01 1.15200125e-01
2.27182850e-01 -1.89240038e-01 -8.78990948e-01 5.05702078e-01
-2.05041218e+00 -1.12403810e+00 -4.62046862e-01 2.18374920e+00
1.99355632e-01 4.46723521e-01 5.18280923e-01 -1.56182006e-01
8.23186100e-01 -2.73164660e-01 -4.25963521e-01 2.83513427e-01
-8.38568211e-02 -3.15063417e-01 1.15847695e+00 5.32714367e-01
-1.49663043e+00 8.35735321e-01 5.92122841e+00 5.47974050e-01
-1.08262300e+00 2.51369864e-01 7.59106949e-02 -2.94936240e-01
6.30237818e-01 -2.63013810e-01 -1.81696999e+00 6.35146499e-01
1.11306727e+00 1.95930433e-02 -4.98889014e-02 9.04161632e-01
-6.00834424e-03 -5.28166294e-01 -1.17690837e+00 1.25182891e+00
3.54506552e-01 -1.39042461e+00 -3.09213340e-01 2.56776541e-01
5.21474063e-01 4.98464525e-01 1.01268142e-01 3.64172719e-02
3.45567912e-01 -8.06549489e-01 1.14330566e+00 5.58058798e-01
2.82984644e-01 -6.82607770e-01 8.26770425e-01 7.54343092e-01
-1.25718498e+00 -1.63189068e-01 -5.94444811e-01 1.03469528e-01
4.64445174e-01 4.52231437e-01 -1.04851592e+00 4.38867480e-01
7.70937562e-01 6.47666931e-01 -5.26351035e-01 1.62707078e+00
3.19978684e-01 2.74934262e-01 -6.74599588e-01 -1.05947927e-01
2.53068656e-01 -9.56639200e-02 9.41569805e-01 1.16044664e+00
4.07577664e-01 -3.80249321e-01 3.36071789e-01 8.83107364e-01
1.98133081e-01 -6.72064483e-01 -9.71947134e-01 4.45669085e-01
3.98195803e-01 1.24120641e+00 -8.26519668e-01 -3.14215690e-01
-6.31174088e-01 5.12046695e-01 4.85241152e-02 -3.69459018e-02
-1.25517929e+00 4.01179373e-01 8.25033903e-01 7.49776289e-02
8.96578968e-01 -5.91716886e-01 -4.38363068e-02 -5.92489660e-01
-1.17978401e-01 -3.63234699e-01 3.96372983e-03 -7.22028732e-01
-9.61328089e-01 4.01647687e-01 2.95466304e-01 -1.31152010e+00
-2.74706155e-01 -1.17160654e+00 -2.81337380e-01 7.54492700e-01
-1.39709604e+00 -1.06435895e+00 -4.93729085e-01 3.71887922e-01
4.89278704e-01 -2.99891800e-01 2.49118090e-01 7.11473763e-01
-3.74877393e-01 1.90572366e-01 1.97082892e-01 2.73306258e-02
5.35886526e-01 -1.14335930e+00 5.98274708e-01 8.70434761e-01
3.91493469e-01 3.93176638e-02 8.59418035e-01 -6.95005059e-01
-1.54983842e+00 -1.47444689e+00 4.88156110e-01 -1.16435087e+00
5.04473150e-01 -3.57304037e-01 -6.64112449e-01 8.28672767e-01
1.41584277e-01 3.73256683e-01 1.10550679e-01 -6.68802440e-01
3.52907777e-02 -1.25055701e-01 -9.21404779e-01 2.33808905e-01
7.94209421e-01 -4.65986431e-02 -3.98494810e-01 4.30415750e-01
4.57545519e-01 -8.44742358e-01 -3.96057487e-01 2.61595666e-01
5.28255820e-01 -8.59333932e-01 1.20324624e+00 -3.22698861e-01
-1.54812232e-01 -7.25174427e-01 6.53279126e-02 -1.00139737e+00
-1.51457727e-01 -2.71395296e-01 -3.29394192e-01 1.05702829e+00
1.41184866e-01 -4.75192696e-01 8.97953570e-01 1.39026716e-01
8.87547657e-02 -2.20971420e-01 -1.36588812e+00 -1.18577743e+00
-1.61387801e-01 -6.08937979e-01 1.37524486e-01 -9.45263915e-03
-9.53998327e-01 1.75028265e-01 -4.66287792e-01 5.90490997e-01
1.18408537e+00 7.84245506e-02 1.28112864e+00 -1.51891220e+00
-6.80059269e-02 -3.88219655e-01 -8.06027472e-01 -1.15002549e+00
3.01341832e-01 -5.35905719e-01 2.56728023e-01 -1.07549214e+00
3.81046027e-01 -4.00817782e-01 1.71688274e-01 -9.03784558e-02
-4.49650213e-02 5.12429595e-01 4.46323872e-01 1.51055053e-01
-8.89556408e-01 9.69852507e-02 7.62694776e-01 -1.40535712e-01
3.58576715e-01 4.55306470e-01 1.67706504e-01 7.24938750e-01
5.00213325e-01 -8.60301733e-01 1.64464086e-01 -4.12333161e-01
1.49316499e-02 -1.26194313e-01 9.11204100e-01 -1.45947671e+00
6.58277869e-01 6.29969090e-02 6.25225127e-01 -1.46358061e+00
7.73253798e-01 -1.28839326e+00 4.94889319e-01 7.36140013e-01
3.23955685e-01 2.87759423e-01 4.97448772e-01 7.14825153e-01
5.46010844e-02 -4.87745076e-01 1.27754855e+00 -3.25955935e-02
-9.54436421e-01 4.39621508e-01 -4.69402343e-01 -1.81347102e-01
1.64496529e+00 -3.57251227e-01 -2.88659513e-01 4.32694294e-02
-4.36724812e-01 2.50954062e-01 6.43373489e-01 6.96684659e-01
4.25535589e-01 -1.35611677e+00 -6.12296581e-01 1.64608106e-01
2.25445088e-02 -4.71616387e-02 -3.18414420e-02 8.86180878e-01
-5.17484188e-01 8.92074823e-01 -2.57895738e-01 -1.46260929e+00
-1.79097509e+00 8.56904566e-01 4.90139633e-01 -4.08863984e-02
-7.28680730e-01 5.80295742e-01 1.85216278e-01 -1.34459242e-01
3.92033041e-01 -3.65986019e-01 -1.16043016e-01 -3.70229557e-02
6.91977620e-01 4.95604873e-01 7.47764930e-02 -1.00371063e+00
-4.49864089e-01 9.14916813e-01 2.46192794e-02 -2.14623541e-01
9.30531740e-01 -1.23188034e-01 1.96542904e-01 6.56372964e-01
9.79518950e-01 -1.50831893e-01 -1.66943061e+00 -2.29787648e-01
1.92225557e-02 -6.12868726e-01 -2.00363360e-02 -2.57143706e-01
-1.01622188e+00 8.46505284e-01 1.06762612e+00 2.03758374e-01
2.58596957e-01 2.83578247e-01 6.81515217e-01 2.40999416e-01
4.77681696e-01 -6.43961430e-01 1.01073220e-01 8.53763878e-01
3.50910425e-01 -1.40350592e+00 -1.14298396e-01 -3.16658527e-01
-2.52247483e-01 1.09237003e+00 6.82183921e-01 -3.54563832e-01
7.18253732e-01 6.54298782e-01 1.73592433e-01 -1.31561056e-01
-7.15055525e-01 -4.12200153e-01 2.45976150e-01 6.53388977e-01
-2.64099747e-01 -1.88236549e-01 2.96126783e-01 -1.66366711e-01
2.44846642e-01 -2.04131491e-02 3.36451650e-01 8.30916941e-01
-7.56275535e-01 -8.30648899e-01 -8.57275426e-01 2.03491300e-01
-4.15491998e-01 5.09119511e-01 -1.58044636e-01 9.33934271e-01
3.11987400e-01 9.14994895e-01 4.83397782e-01 5.28701246e-02
2.73642272e-01 -1.06153265e-02 6.80729151e-01 -4.84002143e-01
-1.79723561e-01 -1.40741706e-01 -3.67716879e-01 -5.31812370e-01
-4.82921869e-01 -9.78656888e-01 -1.03778076e+00 -1.62632763e-01
-4.97810453e-01 -1.67876244e-01 9.07337785e-01 1.25067699e+00
2.93894321e-01 4.47679847e-01 3.40325564e-01 -1.40098524e+00
-3.98324341e-01 -7.98397064e-01 -2.63973057e-01 2.36253545e-01
5.62421739e-01 -1.22444057e+00 -1.67052492e-01 3.73953432e-02] | [6.646108627319336, -2.1483237743377686] |
59426c04-bf10-4764-9cf4-101bb3f40c2c | approximate-bijective-correspondence-for | null | null | https://openreview.net/forum?id=uY6fuowMIT | https://openreview.net/pdf?id=uY6fuowMIT | Approximate Bijective Correspondence for isolating factors of variation | Representational learning forms the backbone of most deep learning applications, and the value of a learned representation is intimately tied to its information content regarding different factors of variation. Finding good representations depends on the nature of supervision and the learning algorithm. We propose a novel algorithm that relies on a weak form of supervision where the data is partitioned into sets according to certain \textit{inactive} factors of variation. Our key insight is that by seeking approximate correspondence between elements of different sets, we learn strong representations that exclude the inactive factors of variation and isolate the \textit{active} factors which vary within all sets. Importantly, the information isolated is complementary to that of most other contrastive learning approaches, which isolate the inactive factors of variation. We demonstrate that the method can work in a semi-supervised scenario, and that a portion of the unsupervised data can belong to a different domain entirely. Further control over the content of the learned representations is possible by folding in data augmentation to suppress nuisance factors. We outperform competing baselines on the challenging problem of synthetic-to-real object pose transfer. | ['Ameesh Makadia', 'Srikumar Ramalingam', 'Varun Jampani', 'Kieran A Murphy'] | 2021-09-29 | null | null | null | null | ['pose-transfer'] | ['computer-vision'] | [ 5.60172498e-01 4.04857814e-01 -4.52877223e-01 -4.24913973e-01
-5.94909132e-01 -8.70945573e-01 7.30533063e-01 -6.85850605e-02
-2.12035030e-01 6.46794319e-01 4.33798164e-01 3.40888910e-02
-2.92648584e-01 -4.46302474e-01 -1.20797491e+00 -7.59034991e-01
1.31123945e-01 7.36383915e-01 1.59077913e-01 -4.74761337e-01
7.42256502e-03 5.37492454e-01 -1.55765128e+00 3.86034071e-01
5.05328536e-01 7.50296116e-01 1.83792692e-02 3.02211106e-01
-2.48543937e-02 6.83943391e-01 -7.44534314e-01 8.41345266e-02
5.93983293e-01 -5.90193987e-01 -6.93328500e-01 4.71507639e-01
8.14757466e-01 3.00646387e-02 -2.94838190e-01 9.46012497e-01
1.95597053e-01 1.28929228e-01 9.81147945e-01 -1.19609058e+00
-5.72196007e-01 3.98656070e-01 -5.91598094e-01 1.44811139e-01
1.02509461e-01 -6.01024972e-03 1.14368272e+00 -8.30328047e-01
7.59683311e-01 1.24639714e+00 5.45945585e-01 5.88693142e-01
-1.73435903e+00 -4.01921481e-01 4.77064848e-01 -2.71975636e-01
-1.10541999e+00 -5.02159297e-01 8.78546596e-01 -7.79933870e-01
4.06930119e-01 2.15820938e-01 3.35615814e-01 1.21008956e+00
-1.29603937e-01 9.09187853e-01 9.13421333e-01 -4.66229349e-01
2.12705761e-01 2.35292405e-01 1.82783768e-01 5.55178881e-01
1.63723677e-01 2.61797775e-02 -5.82814813e-01 -1.20212659e-01
7.52854466e-01 -2.80141793e-02 -4.45295870e-01 -1.10853457e+00
-1.01523757e+00 9.41298366e-01 5.53900957e-01 1.13475077e-01
9.20768455e-02 1.39196530e-01 2.46499017e-01 3.62653792e-01
1.91365927e-01 6.89605296e-01 -8.05884302e-01 2.60206044e-01
-7.17806578e-01 3.41226727e-01 6.51823044e-01 9.95151460e-01
1.10518670e+00 3.51554602e-02 -1.67177051e-01 8.52424264e-01
1.63907140e-01 2.45732009e-01 4.52915996e-01 -9.73950624e-01
5.01098752e-01 4.86207247e-01 2.38267094e-01 -8.34298491e-01
-1.84648037e-01 -5.52108705e-01 -5.23864388e-01 3.76697242e-01
6.87568307e-01 -2.02746212e-01 -1.22996235e+00 2.17028666e+00
1.96007043e-01 -2.87358761e-01 -2.35341460e-01 8.03101301e-01
4.77413207e-01 2.84850299e-01 -3.00648272e-01 4.74098250e-02
9.66222525e-01 -8.09480250e-01 -4.67025816e-01 -4.91031945e-01
3.48554730e-01 -5.85265756e-01 1.11194658e+00 2.96523184e-01
-7.57900417e-01 -5.83516717e-01 -1.18885124e+00 -7.66676888e-02
-2.37717718e-01 -3.34879309e-02 4.00297970e-01 4.41845179e-01
-7.99019814e-01 6.46236777e-01 -6.69499695e-01 -1.57511272e-02
6.14043355e-01 5.28187156e-01 -4.21975821e-01 -1.08530529e-01
-8.81370544e-01 6.95893824e-01 3.62523705e-01 -1.23617910e-01
-8.22778583e-01 -8.00315261e-01 -1.10064840e+00 -1.62891969e-01
6.23715103e-01 -4.22944605e-01 9.73181784e-01 -1.58148634e+00
-1.01348841e+00 8.52536023e-01 -1.00776069e-01 -1.87480375e-01
6.36779666e-01 -3.21786076e-01 5.59540838e-02 6.21849857e-02
2.00095877e-01 7.42047608e-01 1.33629620e+00 -1.52061176e+00
-9.34797823e-02 -5.19335032e-01 -5.74332476e-03 1.65020674e-01
-1.16811581e-01 -2.02847272e-01 -5.87917268e-01 -8.37675154e-01
1.25019819e-01 -1.23499274e+00 -2.35706687e-01 3.34601671e-01
-2.80976206e-01 2.43703090e-02 9.31382298e-01 -3.11001122e-01
6.94550812e-01 -2.30728674e+00 4.74589497e-01 3.29205006e-01
3.73983085e-01 1.02721371e-01 -2.26960465e-01 3.28658015e-01
-3.06399345e-01 -6.87044710e-02 -4.68237996e-01 -2.30075210e-01
-2.75686327e-02 4.81849045e-01 -6.03041232e-01 5.21205366e-01
6.90311730e-01 7.88765311e-01 -7.57964551e-01 -1.01841725e-01
9.13126543e-02 3.81846666e-01 -5.87822318e-01 1.36506289e-01
-5.31002104e-01 6.78027570e-01 -5.21609306e-01 2.42066115e-01
5.36992967e-01 -3.14442158e-01 9.99719575e-02 -2.30963022e-01
2.52386302e-01 3.84433985e-01 -1.31346476e+00 1.79180229e+00
-7.27302134e-02 6.22770011e-01 1.79448068e-01 -1.13838375e+00
8.69393349e-01 2.75104772e-03 5.57356477e-01 -3.10165197e-01
-1.42512107e-02 -3.35992537e-02 1.81114435e-01 -1.48355976e-01
4.18373466e-01 -1.75354898e-01 -2.90955715e-02 5.53316176e-01
2.81290442e-01 -1.67036071e-01 1.19491905e-01 2.52295017e-01
1.07102692e+00 3.90421212e-01 1.93412676e-01 -4.29520309e-01
4.93128486e-02 -1.17612183e-01 6.78603172e-01 8.02117705e-01
-3.81097406e-01 1.06631088e+00 7.94112086e-01 -4.87518579e-01
-1.09013808e+00 -1.20094502e+00 -3.46659750e-01 1.17000842e+00
1.75613716e-01 -2.70554185e-01 -4.51069027e-01 -1.06201375e+00
2.43592903e-01 3.83199751e-01 -1.14394450e+00 -2.90955007e-01
-6.11747801e-01 -5.91149986e-01 3.25116068e-01 6.06302619e-01
-1.44486830e-01 -1.08994055e+00 -5.58779836e-01 2.75101662e-02
1.51617125e-01 -9.71013367e-01 -5.27971506e-01 7.29273200e-01
-6.15575373e-01 -1.11733258e+00 -5.20274699e-01 -5.46480536e-01
9.38751757e-01 1.49453864e-01 1.32151139e+00 -1.52379796e-01
-1.41314134e-01 3.33362609e-01 -2.34103858e-01 -5.28428912e-01
-3.48138213e-01 4.25112695e-02 -1.60169467e-01 1.31383166e-01
2.93949634e-01 -5.97522557e-01 -3.29161048e-01 3.72219473e-01
-9.60027039e-01 -1.58962488e-01 5.17558694e-01 8.22417796e-01
5.87069154e-01 -2.24959984e-01 4.08885270e-01 -1.24874496e+00
3.16003680e-01 -5.15632033e-01 -2.94405967e-01 -2.05225335e-03
-1.94392487e-01 6.07397318e-01 6.52454972e-01 -7.58249223e-01
-7.34190106e-01 3.78828526e-01 4.08236831e-01 -7.68591762e-01
-1.56488746e-01 2.24444583e-01 -4.09717262e-01 2.52205551e-01
9.55256343e-01 -4.74026427e-02 2.73048103e-01 -5.53768754e-01
4.18635517e-01 8.35568905e-02 4.14615273e-01 -9.21093941e-01
9.13994193e-01 5.17035604e-01 -7.98853636e-02 -7.88559258e-01
-1.05905771e+00 -2.39322871e-01 -7.72720456e-01 4.60918024e-02
5.75842202e-01 -9.16277647e-01 -8.09737891e-02 6.57070354e-02
-8.58358562e-01 -3.24100852e-01 -8.61664236e-01 2.69149274e-01
-6.14821970e-01 1.77636281e-01 -2.26522893e-01 -4.25797611e-01
2.79842824e-01 -1.28099430e+00 1.26551175e+00 -8.40871036e-02
-5.29218137e-01 -7.26158321e-01 2.15063140e-01 3.09858590e-01
1.35157388e-02 3.42599005e-01 8.62436652e-01 -8.16100895e-01
-4.82949466e-01 -1.50244251e-01 1.08746337e-02 5.64265013e-01
3.38986814e-01 -4.13142107e-02 -9.70041513e-01 -4.18549687e-01
-9.15571954e-03 -7.18821049e-01 1.20715249e+00 3.87405634e-01
1.09099054e+00 -3.27804506e-01 -8.04864168e-02 5.66303909e-01
1.01130283e+00 -1.50175899e-01 5.83394647e-01 1.64859906e-01
1.01692522e+00 9.31321025e-01 1.51593313e-01 1.99782506e-01
3.65524292e-02 6.29781008e-01 3.69049311e-01 -1.60245255e-01
-4.74733561e-02 -2.31524900e-01 2.57129401e-01 3.24996322e-01
2.64934659e-01 -1.20939083e-01 -7.04930604e-01 6.60093844e-01
-1.79512906e+00 -9.22759891e-01 2.52679795e-01 2.21767163e+00
8.77504528e-01 2.77659655e-01 2.42194206e-01 2.65347391e-01
7.23502219e-01 4.72772539e-01 -7.81969666e-01 -3.26331615e-01
-1.45239532e-01 3.54529679e-01 3.74079734e-01 3.43777627e-01
-1.26811302e+00 6.98260605e-01 6.55174780e+00 5.71793675e-01
-9.55825388e-01 -3.59169364e-01 5.10317087e-01 -2.08147690e-01
-5.81974387e-01 -1.52740404e-01 -5.98935366e-01 4.00586307e-01
4.61221993e-01 2.09922969e-01 3.03886890e-01 7.26922095e-01
-1.54020995e-01 9.36210752e-02 -1.64791131e+00 5.70547640e-01
2.51087040e-01 -1.08228695e+00 1.84410557e-01 2.16125220e-01
9.01706159e-01 6.86412081e-02 2.18387485e-01 2.32658267e-01
4.44226861e-01 -1.17181432e+00 7.83434749e-01 3.24222088e-01
5.91257334e-01 -6.66704774e-01 2.36575812e-01 4.05308902e-01
-7.95243025e-01 3.92375514e-02 -2.24403828e-01 -1.05388455e-01
-3.45290929e-01 5.03083944e-01 -6.13849878e-01 2.61710942e-01
4.90619272e-01 8.32710624e-01 -5.76598525e-01 3.41493905e-01
-3.00463140e-01 4.87600267e-01 -3.47679317e-01 3.36726695e-01
1.13979734e-01 -2.68940926e-01 6.07720435e-01 1.08253646e+00
-2.11928055e-01 -2.64132738e-01 3.81370068e-01 1.07003522e+00
-2.67962337e-01 -1.96300596e-01 -7.96291471e-01 -7.13854358e-02
2.81676084e-01 8.52997243e-01 -5.13674676e-01 -1.17453650e-01
-4.24177259e-01 7.59525478e-01 5.86473703e-01 4.83516902e-01
-4.81774420e-01 -1.89363342e-02 8.86605382e-01 2.05755666e-01
7.54884481e-01 -1.83046103e-01 -3.61010313e-01 -1.22608352e+00
4.14700478e-01 -1.19317651e+00 3.38248789e-01 -4.89221513e-01
-1.37516069e+00 3.01098078e-01 2.96097789e-02 -1.36613929e+00
-3.72447729e-01 -6.22341216e-01 -3.47387403e-01 8.51053715e-01
-1.25597298e+00 -1.05430067e+00 -9.99003351e-02 6.22227669e-01
5.81600428e-01 -1.00076362e-01 6.88836634e-01 -7.50911012e-02
-4.35969472e-01 5.87566614e-01 1.64023861e-01 2.80834645e-01
8.31353128e-01 -1.31012166e+00 1.73947304e-01 8.10117900e-01
5.22270322e-01 7.67756760e-01 8.37426305e-01 -4.55654800e-01
-1.23732972e+00 -1.13010740e+00 4.01627392e-01 -7.63639152e-01
6.32642508e-01 -6.05856240e-01 -1.04138660e+00 1.06752694e+00
-1.62439961e-02 4.07597125e-01 6.45266950e-01 3.08858454e-01
-9.37657475e-01 -2.92779934e-02 -9.41838145e-01 4.53959227e-01
9.79917645e-01 -6.78704917e-01 -9.05461848e-01 1.37053102e-01
7.26443052e-01 -4.09556538e-01 -3.72489035e-01 4.72522914e-01
5.47071576e-01 -8.69635105e-01 9.18288112e-01 -9.38549399e-01
6.97616994e-01 -3.07756990e-01 -3.26178133e-01 -1.37710357e+00
-2.20056236e-01 -5.85617900e-01 -3.12508523e-01 1.00109255e+00
3.99880826e-01 -3.47808689e-01 9.35618937e-01 7.14219451e-01
-8.37486982e-02 -5.79085231e-01 -5.51412761e-01 -7.53570557e-01
3.33349735e-01 -2.56665617e-01 3.55587363e-01 1.14686930e+00
-4.63736147e-01 6.32636964e-01 -3.48213464e-01 1.07415386e-01
5.88117182e-01 1.53466374e-01 9.53021884e-01 -1.32663107e+00
-7.36175239e-01 -2.28822574e-01 -5.27446926e-01 -1.12241423e+00
2.73626417e-01 -8.22130382e-01 1.42786905e-01 -1.00417364e+00
2.37282515e-01 -3.82477403e-01 -5.23327768e-01 5.77377379e-01
-2.03964785e-01 2.33997166e-01 2.40739286e-01 3.06727290e-01
-3.46330762e-01 6.48507357e-01 1.20289254e+00 -2.27852240e-01
-3.81595075e-01 -1.35626242e-01 -9.63475823e-01 8.01178515e-01
5.79441667e-01 -5.10521472e-01 -6.54558778e-01 -6.26477718e-01
1.23171963e-01 -4.18011874e-01 2.31822997e-01 -6.53876543e-01
-1.28191367e-01 -2.05593184e-01 6.57925725e-01 -3.79051000e-01
3.40565920e-01 -7.52782345e-01 -2.29317024e-02 7.76778832e-02
-7.73183882e-01 -3.02706063e-01 1.78469107e-01 6.78362668e-01
-1.73805639e-01 -8.55793506e-02 9.70714271e-01 -1.50855765e-01
-4.20434684e-01 2.27507457e-01 -8.61999243e-02 5.80087841e-01
8.30488503e-01 -2.21459627e-01 -1.26055434e-01 -3.20146918e-01
-7.58239388e-01 -1.43657075e-02 6.49657667e-01 4.96045291e-01
2.21076146e-01 -1.27409744e+00 -6.76411390e-01 5.53144276e-01
3.92235845e-01 3.05870056e-01 -2.36963302e-01 3.55579436e-01
2.51928922e-02 -7.35827396e-03 -2.96334833e-01 -8.23270380e-01
-9.00162458e-01 5.42830586e-01 2.65935838e-01 -1.17870145e-01
-6.77391768e-01 8.61185968e-01 7.09811211e-01 -5.28083444e-01
2.81175137e-01 -1.26736462e-01 -5.92603348e-02 2.81885564e-01
3.81654710e-01 7.75412545e-02 3.82374488e-02 -7.89219320e-01
-3.02507281e-01 5.37417531e-01 -4.27576780e-01 -1.22465149e-01
1.52298272e+00 1.50449455e-01 2.11354315e-01 6.48689330e-01
1.41835284e+00 1.35942593e-01 -1.76432478e+00 -3.99114251e-01
4.29131389e-02 -5.04696667e-01 -1.99877635e-01 -6.69255912e-01
-1.06223238e+00 7.09490657e-01 2.61402160e-01 -8.81012753e-02
9.09189463e-01 2.35114425e-01 2.61803210e-01 4.09547478e-01
1.79135159e-01 -9.77817297e-01 2.49612346e-01 4.89439219e-01
1.05058789e+00 -1.39144838e+00 1.04738750e-01 -2.98405498e-01
-6.94811583e-01 8.61773431e-01 5.49245894e-01 -5.46141326e-01
4.38333541e-01 4.44669098e-01 9.28695202e-02 -2.56189317e-01
-6.50772035e-01 -2.20212162e-01 6.56344831e-01 7.22457170e-01
4.00901616e-01 -1.11250691e-01 8.45606849e-02 3.33034605e-01
-2.26167321e-01 -3.59920055e-01 4.05141741e-01 1.09821832e+00
-2.56525457e-01 -1.12299013e+00 -3.66680592e-01 5.44653237e-01
-2.86518961e-01 9.85658467e-02 -8.66825819e-01 1.00832140e+00
2.48073488e-01 5.23450077e-01 1.75264001e-01 -1.11906968e-01
3.11727673e-01 1.59890592e-01 6.11256838e-01 -8.98990512e-01
-3.88803154e-01 2.21602842e-01 -7.07702562e-02 -5.26148379e-01
-4.07165438e-01 -8.63288522e-01 -1.11438262e+00 2.76287466e-01
7.53378868e-03 -1.84280071e-02 3.42896253e-01 1.12253988e+00
2.18632877e-01 5.08956313e-01 7.24311531e-01 -9.71675515e-01
-6.50800765e-01 -7.60824382e-01 -6.11246884e-01 9.68392253e-01
8.78527939e-01 -8.93965423e-01 -6.17075205e-01 2.16286629e-01] | [9.488444328308105, 2.2172560691833496] |
cb3dc9ca-70b4-4a49-83e2-bfddc144e887 | age-estimation-using-expectation-of-label | null | null | http://www.lamda.nju.edu.cn/gaobb/Pub_files/IJCAI2018_DLDLv2.pdf | http://www.lamda.nju.edu.cn/gaobb/Pub_files/IJCAI2018_DLDLv2.pdf | Age Estimation Using Expectation of Label Distribution Learning | Age estimation performance has been greatly improved by using convolutional neural network. However, existing methods have an inconsistency between the training objectives and evaluation metric, so they may be suboptimal. In addition, these methods always adopt image classification or face recognition models with a large amount of parameters, which bring expensive computation cost and
storage overhead. To alleviate these issues, we design a lightweight network architecture and propose a unified framework which can jointly learn age distribution and regress age. The effectiveness of our approach has been demonstrated on apparent and real age estimation tasks. Our method achieves new state-of-the-art results using the single model with 36× fewer parameters and 2.6× reduction in inference time. Moreover, our method can achieve comparable results as the state-of-the-art even though model parameters are further reduced to 0.9M (3.8MB disk storage). We also analyze that Ranking methods are implicitly learning label
distributions. | ['Xin Geng', 'Jianxin Wu', 'Hong-Yu Zhou', 'Bin-Bin Gao'] | 2018-07-13 | null | null | null | null | ['age-estimation', 'age-estimation'] | ['computer-vision', 'miscellaneous'] | [-2.06833124e-01 -1.14642596e-03 -3.26287627e-01 -7.35295713e-01
-4.61456329e-01 -1.13767646e-01 3.81554514e-01 -3.40943076e-02
-8.40783954e-01 7.34274685e-01 -8.81471634e-02 -1.50495991e-01
-1.04085445e-01 -7.62962341e-01 -5.79258025e-01 -6.30615652e-01
1.61917228e-02 4.81892377e-01 -1.43822938e-01 3.60890597e-01
2.07180470e-01 1.25311270e-01 -1.72002172e+00 -3.11114132e-01
1.03290880e+00 1.41029775e+00 -6.61500767e-02 6.11104727e-01
4.43573147e-02 8.02980542e-01 -5.99743783e-01 -7.43393421e-01
-8.41918513e-02 2.42830232e-01 -7.18497932e-01 -3.61176848e-01
7.64618099e-01 -1.00699794e+00 -7.02602863e-01 8.70743692e-01
7.78125167e-01 -2.27686644e-01 7.29201972e-01 -1.42213929e+00
-1.00898468e+00 6.53679609e-01 -8.01793277e-01 -1.83689564e-01
-1.45825773e-01 -4.41579074e-01 7.02441275e-01 -6.38413429e-01
-4.97814491e-02 1.30310225e+00 6.97876275e-01 9.38002825e-01
-6.60279512e-01 -1.12554634e+00 2.50233680e-01 4.10495907e-01
-1.48527110e+00 -4.62132424e-01 3.11208308e-01 -8.91240016e-02
5.37152588e-01 1.19377702e-01 2.92164892e-01 1.20933127e+00
-1.53661847e-01 7.50602901e-01 1.08529675e+00 -2.79287457e-01
7.25219119e-03 -6.82045072e-02 3.56130958e-01 1.04960942e+00
4.83948171e-01 -4.77400385e-02 -7.03682899e-01 -5.54586984e-02
5.55152178e-01 1.33298218e-01 3.13533336e-01 6.27637282e-02
-8.34949195e-01 6.91464186e-01 2.31594816e-01 -1.81452900e-01
-9.50300228e-03 7.02660978e-01 3.78931582e-01 -2.31443550e-02
7.64213383e-01 -3.82122472e-02 -5.27561843e-01 -3.58553410e-01
-7.23529398e-01 3.17892849e-01 5.10054708e-01 9.28065598e-01
4.35076326e-01 -1.30258769e-01 -2.67242581e-01 1.05756772e+00
3.89997452e-01 7.22440660e-01 2.93081641e-01 -1.27317452e+00
2.20367327e-01 4.02548283e-01 -1.38506126e-02 -7.57468343e-01
-5.47290504e-01 -4.77074116e-01 -9.21136558e-01 -6.87396526e-02
6.44467354e-01 -1.42512649e-01 -1.14231884e+00 2.05878925e+00
2.54764736e-01 1.59647003e-01 -3.68490249e-01 5.29025435e-01
6.68257713e-01 4.09466803e-01 2.26299733e-01 -2.53865719e-01
1.48556554e+00 -1.19564474e+00 -7.62721181e-01 -2.47149527e-01
6.08207405e-01 -4.46870118e-01 9.08217192e-01 5.97163200e-01
-1.21808887e+00 -5.31218588e-01 -1.09509051e+00 -1.76766738e-01
-3.06156099e-01 5.65544248e-01 1.20854557e+00 9.56984878e-01
-1.11611092e+00 5.78034520e-01 -8.52347612e-01 -2.42967233e-01
6.49255216e-01 7.48450398e-01 -7.40905330e-02 -7.55228251e-02
-1.13080657e+00 6.37245238e-01 1.22586213e-01 1.85893402e-01
-7.68829763e-01 -7.65040159e-01 -6.38437450e-01 1.12641722e-01
3.25605303e-01 -7.79047072e-01 1.42119658e+00 -4.96038407e-01
-1.37698364e+00 7.46813655e-01 -2.25511000e-01 -3.22687447e-01
4.54987049e-01 -7.16047406e-01 -3.68240595e-01 -1.13878943e-01
-2.13061512e-01 7.55141556e-01 6.50297940e-01 -8.82326901e-01
-7.17132807e-01 -7.20375061e-01 5.35307042e-02 6.64376318e-02
-1.28962517e+00 1.93611026e-01 -8.15935493e-01 -5.08453846e-01
-3.20886485e-02 -8.95260811e-01 1.12574980e-01 2.76709408e-01
1.17428228e-01 -6.20374739e-01 5.96670508e-01 -8.34324300e-01
1.88720584e+00 -1.86267841e+00 9.42891184e-03 -1.39537871e-01
4.88402903e-01 2.20849544e-01 4.82605062e-02 -1.64821059e-01
4.36590105e-01 1.60085291e-01 1.29643232e-01 -7.96502769e-01
1.16852425e-01 6.72224909e-02 9.96863991e-02 2.67886221e-01
-2.00791091e-01 7.15591848e-01 -6.59841895e-01 -8.20659935e-01
-1.40430585e-01 5.09381294e-01 -4.59404230e-01 2.90858090e-01
1.78588942e-01 4.55746837e-02 -4.14729267e-01 9.33549464e-01
8.18909347e-01 -4.07808423e-01 2.53607839e-01 -1.76385880e-01
1.30914077e-01 1.98216271e-02 -8.88173759e-01 1.70216358e+00
-5.99388599e-01 2.38673583e-01 -1.64184466e-01 -8.30846429e-01
7.75922060e-01 -1.03413545e-01 3.14462930e-01 -7.64006495e-01
3.01057160e-01 1.59037933e-01 -5.15459590e-02 -3.54296327e-01
5.22414446e-01 4.31218743e-01 -4.94042858e-02 5.52977145e-01
-5.42944334e-02 6.11141264e-01 2.18689188e-01 1.61295772e-01
8.97240639e-01 1.86814412e-01 -2.46416554e-01 -9.95162278e-02
4.32839990e-01 -9.89791691e-01 7.35510707e-01 6.87726617e-01
-3.74004841e-01 3.65242362e-01 4.91596133e-01 -6.24494970e-01
-1.04987705e+00 -1.13289607e+00 -2.27173910e-01 1.40869176e+00
5.15676066e-02 -6.11975551e-01 -1.03999233e+00 -8.37488592e-01
7.42066801e-02 1.80292413e-01 -9.14584160e-01 -1.86101988e-01
-5.83929539e-01 -1.02251673e+00 8.49501729e-01 9.37238157e-01
6.39655113e-01 -6.42654121e-01 -1.52931735e-01 -1.21510133e-01
-1.45888016e-01 -1.07186258e+00 -2.64510989e-01 -4.11015123e-01
-9.36631382e-01 -7.83700168e-01 -8.25363636e-01 -5.79679549e-01
9.15072441e-01 -8.12546015e-02 1.15012145e+00 3.88847768e-01
-1.57748953e-01 3.30562703e-02 -6.00065254e-02 -6.19412541e-01
2.01646701e-01 6.27226174e-01 5.89089632e-01 -1.72251970e-01
5.91877699e-01 -6.33097768e-01 -9.69186604e-01 2.31064573e-01
-6.40200377e-01 8.95987153e-02 6.49061203e-01 8.65554810e-01
1.29684120e-01 -9.21911150e-02 8.81959558e-01 -7.84700096e-01
2.99966723e-01 -2.38863274e-01 -6.71448469e-01 5.01731336e-01
-1.36352777e+00 3.41366351e-01 3.34686577e-01 -5.95373273e-01
-1.24353492e+00 -1.71127930e-01 4.21963492e-03 -1.99240848e-01
1.56547591e-01 3.26447099e-01 -2.23072190e-02 1.72086209e-01
2.32906789e-01 -2.11046100e-01 1.02147050e-01 -6.12139821e-01
1.79306522e-01 1.04330528e+00 5.67580521e-01 -8.85930419e-01
5.92863739e-01 3.80415261e-01 -6.90465514e-03 -2.73608029e-01
-1.24344695e+00 1.10970840e-01 -3.17054451e-01 -2.46171296e-01
5.74884057e-01 -1.26086569e+00 -1.19711065e+00 1.22381985e+00
-9.36971843e-01 -3.01029742e-01 5.70852995e-01 4.77711290e-01
-1.19361110e-01 4.73444074e-01 -1.11550939e+00 -1.00590277e+00
-7.30726600e-01 -8.57378840e-01 1.02685285e+00 5.49469650e-01
-5.40092252e-02 -6.84063673e-01 -3.89602005e-01 6.22036636e-01
5.08514404e-01 -1.49332628e-01 8.44248176e-01 -1.29188687e-01
-3.52575779e-01 -1.88016370e-01 -7.50554204e-01 3.15155119e-01
-2.48151179e-02 9.47781429e-02 -1.20869434e+00 -5.04021406e-01
-5.84463179e-01 -6.75773799e-01 9.78785515e-01 4.78291422e-01
2.21025348e+00 -2.97421012e-02 -3.82181615e-01 7.01245248e-01
1.12513912e+00 1.65753718e-02 6.62916720e-01 1.60214707e-01
8.52854550e-01 6.84265614e-01 7.34364450e-01 6.26010895e-01
6.88806176e-01 5.42977095e-01 3.32499146e-01 2.21181698e-02
2.03201622e-02 -1.87033027e-01 2.26790860e-01 1.01078534e+00
-4.68321770e-01 -2.29198858e-01 -7.80283332e-01 4.73566741e-01
-1.98118186e+00 -4.42379326e-01 1.08524889e-01 2.35225987e+00
1.05339682e+00 2.26197913e-01 2.68001348e-01 2.59015653e-02
6.48348689e-01 1.64731219e-01 -6.48229182e-01 -3.10368180e-01
2.44535595e-01 2.60203421e-01 7.18656361e-01 3.00496608e-01
-9.84718502e-01 7.13373899e-01 6.63846684e+00 1.06661880e+00
-9.87756312e-01 -2.52558896e-03 1.05812538e+00 -4.69661564e-01
6.57171085e-02 -3.61476034e-01 -1.03720510e+00 7.71528423e-01
1.10795248e+00 -9.00472179e-02 5.08905888e-01 9.12670851e-01
-3.46870333e-01 -7.31679648e-02 -1.19670880e+00 1.41442907e+00
3.17835093e-01 -8.62516701e-01 -2.40912616e-01 3.43235046e-01
5.64898551e-01 -3.62148613e-01 5.09518266e-01 4.86296266e-01
1.67641401e-01 -1.20662498e+00 4.79614109e-01 5.51642895e-01
1.24327183e+00 -1.14669812e+00 8.38705182e-01 3.37519385e-02
-9.35230672e-01 -3.35972577e-01 -5.25688469e-01 -4.21984464e-01
-1.20165177e-01 7.97782481e-01 -2.28398502e-01 3.95083398e-01
1.15303552e+00 4.90080863e-01 -9.65159774e-01 5.85523784e-01
-1.20166697e-01 5.29973805e-01 -3.36954415e-01 -2.43898779e-01
-2.44518608e-01 1.47115896e-02 -4.88242358e-01 6.66685402e-01
6.62954271e-01 -7.19851628e-02 -2.27932155e-01 3.33972663e-01
-5.69439352e-01 -2.17776909e-01 -2.05361798e-01 -1.93160489e-01
8.56380403e-01 1.43210697e+00 -3.92255902e-01 -3.69619906e-01
-3.53031605e-01 8.29082251e-01 8.23899388e-01 1.38439506e-01
-1.14276874e+00 -4.62935090e-01 6.56213939e-01 -3.26562300e-03
-5.26107382e-04 -1.76722735e-01 -2.17856005e-01 -9.68028545e-01
2.57144477e-02 -5.76637506e-01 2.57092059e-01 -5.86105049e-01
-1.38234162e+00 2.87408084e-01 -1.58497505e-02 -6.06560826e-01
-2.16600180e-01 -8.80094230e-01 -2.40020379e-01 4.70598578e-01
-1.26986372e+00 -1.28136992e+00 -5.77797234e-01 1.34214446e-01
1.66171297e-01 -1.87306643e-01 8.13286304e-01 8.42771649e-01
-9.05207634e-01 1.39142203e+00 1.90245241e-01 1.32287323e-01
1.19758439e+00 -1.35127616e+00 2.74555832e-01 5.50518990e-01
-3.34933102e-01 6.14510477e-01 3.36833209e-01 -3.47335815e-01
-1.14167714e+00 -8.90156686e-01 1.13820612e+00 -5.82209885e-01
4.34179425e-01 -6.60927355e-01 -6.70842350e-01 5.11791646e-01
5.19976094e-02 -7.65033066e-02 6.63232625e-01 8.34597647e-01
-7.65440047e-01 -5.63985527e-01 -8.50670516e-01 7.83720851e-01
1.42356062e+00 -3.36280018e-01 -4.76808138e-02 7.67040774e-02
8.22391093e-01 -3.67800206e-01 -1.08318698e+00 6.50486052e-01
1.25792038e+00 -7.20122874e-01 1.02178288e+00 -4.89089966e-01
7.40491509e-01 -2.48437021e-02 1.16569966e-01 -7.40492821e-01
-3.34465981e-01 -2.40617484e-01 -9.96706843e-01 1.59961581e+00
2.61226952e-01 -6.13520920e-01 1.08696234e+00 7.68435240e-01
1.79905057e-01 -1.34742880e+00 -5.53147078e-01 -7.78680086e-01
1.84531093e-01 -2.66733736e-01 8.75317335e-01 6.49278045e-01
-4.01112616e-01 4.21621770e-01 -8.31817150e-01 -7.12946244e-03
8.14297676e-01 -2.74679273e-01 6.22667253e-01 -1.46521354e+00
-1.17162511e-01 -3.79301190e-01 -2.45596450e-02 -9.01374161e-01
4.41388994e-01 -2.14189589e-01 -2.01587841e-01 -1.29163444e+00
6.42218232e-01 -7.36549199e-01 -8.39714229e-01 5.49151897e-01
-4.84476954e-01 3.13564122e-01 -1.60613522e-01 -1.44656837e-01
-7.75631666e-01 5.64332247e-01 8.93503606e-01 -5.93057498e-02
3.90347332e-01 -1.99780196e-01 -8.65551591e-01 7.83944011e-01
1.01927960e+00 -3.45056653e-01 -5.46442032e-01 -8.69283795e-01
5.63093543e-01 -3.23076189e-01 4.13041860e-02 -9.94844139e-01
2.10634753e-01 1.70380622e-02 7.83121943e-01 -6.73097372e-01
4.29460227e-01 -3.59304726e-01 -1.88720718e-01 4.58557367e-01
-3.38230580e-01 2.30043367e-01 -5.32559417e-02 4.82832432e-01
1.14490598e-01 -1.50801644e-01 5.27123630e-01 2.83338487e-01
-5.33759117e-01 8.18983853e-01 1.35782897e-01 -3.19377780e-01
7.66331315e-01 1.23754524e-01 -6.87907279e-01 -2.68611819e-01
-3.02001745e-01 5.04523456e-01 4.64368701e-01 5.31360686e-01
3.41474086e-01 -1.58748806e+00 -6.36774063e-01 -1.12360217e-01
1.61053449e-01 5.32087637e-03 6.18528664e-01 6.32187843e-01
-4.85014617e-01 2.96411842e-01 -1.55441225e-01 -3.89174432e-01
-1.53399920e+00 5.68059206e-01 2.24616192e-02 -5.19016564e-01
1.34259716e-01 1.04595578e+00 1.93075985e-01 -4.81889397e-01
6.76124334e-01 2.26021424e-01 -1.94475859e-01 1.00367993e-01
6.81626678e-01 7.56398737e-01 -1.22161843e-01 -9.45064984e-03
-3.24693084e-01 5.10424018e-01 -4.92573917e-01 1.02169119e-01
1.19378388e+00 -2.74808794e-01 -2.12322623e-01 2.45606944e-01
1.07174647e+00 -1.58481181e-01 -1.16325474e+00 -2.76237249e-01
-1.87391654e-01 -4.66508389e-01 2.02500686e-01 -8.20092857e-01
-1.17329931e+00 9.35759604e-01 9.83879566e-01 -1.89133078e-01
1.28051925e+00 -1.84430145e-02 1.03512180e+00 4.93512660e-01
4.17295486e-01 -1.63850105e+00 2.61872232e-01 3.20407391e-01
3.58882099e-01 -1.41623926e+00 5.15524268e-01 -4.12672013e-01
-1.33294731e-01 7.41843522e-01 1.22993672e+00 2.71400660e-01
5.67165852e-01 1.66990459e-02 -1.35363103e-03 4.76348363e-02
-8.93889546e-01 7.70315602e-02 2.18612120e-01 4.15597796e-01
6.32277071e-01 1.78104848e-01 -7.12767839e-01 7.64165819e-01
-1.36431292e-01 1.65420044e-02 1.74958676e-01 6.33485615e-01
-1.18404187e-01 -1.40590620e+00 -4.29141521e-02 6.96361780e-01
-9.03162718e-01 -1.00632384e-01 -6.08641654e-03 6.02765620e-01
6.87295422e-02 8.11737716e-01 3.14002872e-01 -5.81078529e-01
-1.81126699e-01 -1.82184484e-02 8.13783288e-01 -1.99034587e-01
-1.29532218e-01 -2.63419867e-01 1.48004606e-01 -5.19664109e-01
-4.21192169e-01 -3.54500711e-01 -9.11994934e-01 -7.94011950e-01
-2.86279440e-01 -5.10246046e-02 7.46528208e-01 6.89469039e-01
4.14965689e-01 5.94170988e-01 7.49565423e-01 -3.28205585e-01
-7.65354574e-01 -1.22989428e+00 -6.69605851e-01 2.49470025e-01
-1.55283540e-01 -9.19198871e-01 -1.00616701e-01 -1.16283894e-01] | [13.611734390258789, 0.89747154712677] |
11f9f6ce-d8d7-476d-9018-720843be9258 | contrastive-meta-learning-for-few-shot-node | 2306.15154 | null | https://arxiv.org/abs/2306.15154v1 | https://arxiv.org/pdf/2306.15154v1.pdf | Contrastive Meta-Learning for Few-shot Node Classification | Few-shot node classification, which aims to predict labels for nodes on graphs with only limited labeled nodes as references, is of great significance in real-world graph mining tasks. Particularly, in this paper, we refer to the task of classifying nodes in classes with a few labeled nodes as the few-shot node classification problem. To tackle such a label shortage issue, existing works generally leverage the meta-learning framework, which utilizes a number of episodes to extract transferable knowledge from classes with abundant labeled nodes and generalizes the knowledge to other classes with limited labeled nodes. In essence, the primary aim of few-shot node classification is to learn node embeddings that are generalizable across different classes. To accomplish this, the GNN encoder must be able to distinguish node embeddings between different classes, while also aligning embeddings for nodes in the same class. Thus, in this work, we propose to consider both the intra-class and inter-class generalizability of the model. We create a novel contrastive meta-learning framework on graphs, named COSMIC, with two key designs. First, we propose to enhance the intra-class generalizability by involving a contrastive two-step optimization in each episode to explicitly align node embeddings in the same classes. Second, we strengthen the inter-class generalizability by generating hard node classes via a novel similarity-sensitive mix-up strategy. Extensive experiments on few-shot node classification datasets verify the superiority of our framework over state-of-the-art baselines. Our code is provided at https://github.com/SongW-SW/COSMIC. | ['Jundong Li', 'Huan Liu', 'Zhen Tan', 'Song Wang'] | 2023-06-27 | null | null | null | null | ['graph-mining', 'node-classification', 'meta-learning', 'classification-1'] | ['graphs', 'graphs', 'methodology', 'methodology'] | [ 8.19640607e-02 1.84239239e-01 -5.31333864e-01 -5.03290951e-01
-2.81921446e-01 -5.04587770e-01 4.82561082e-01 4.58766937e-01
-1.59352809e-01 2.99596906e-01 -9.73253921e-02 -2.45222494e-01
-2.15960592e-01 -1.23231447e+00 -5.06228447e-01 -7.05323815e-01
2.84085609e-02 1.44877285e-01 2.44099021e-01 -2.63790756e-01
-1.09793611e-01 3.19562048e-01 -1.27205038e+00 1.96519941e-02
8.18431318e-01 8.29710722e-01 1.21529803e-01 4.67286050e-01
-2.67229438e-01 6.53592646e-01 -1.63656339e-01 -5.57887256e-01
1.82887062e-01 -5.17938077e-01 -9.56151664e-01 1.61442056e-01
3.51783574e-01 -7.69556547e-03 -6.16165102e-01 1.31507492e+00
2.92466104e-01 2.03311011e-01 6.91896856e-01 -1.68267369e+00
-8.80279422e-01 7.65971661e-01 -5.74835598e-01 2.46431276e-01
-4.24846634e-02 4.06628698e-02 1.48932195e+00 -6.90723121e-01
5.99551916e-01 9.38138723e-01 7.37272739e-01 7.89526463e-01
-1.38386035e+00 -6.95620298e-01 3.30476731e-01 2.27147445e-01
-1.55496764e+00 -2.89063394e-01 1.04031479e+00 -4.07406718e-01
4.58349705e-01 1.41537517e-01 3.71424198e-01 1.08981144e+00
-1.12921491e-01 4.70632464e-01 5.71944594e-01 -2.63736755e-01
3.78845006e-01 1.29138067e-01 4.45670456e-01 7.73542285e-01
2.66701937e-01 -1.80366278e-01 -2.77450290e-02 -5.05383052e-02
2.68175244e-01 6.03964567e-01 -2.30845854e-01 -6.25571787e-01
-1.05905139e+00 9.75802958e-01 9.63682950e-01 5.90520978e-01
-2.25346074e-01 9.07265171e-02 6.61247492e-01 3.51205051e-01
8.55507135e-01 3.24146152e-01 -4.09844220e-01 3.39048475e-01
-6.90129459e-01 -2.38571361e-01 7.83512592e-01 1.13298941e+00
1.18881834e+00 -2.55114168e-01 -2.56480187e-01 8.64148438e-01
3.11475188e-01 -3.54664726e-03 5.20431399e-01 -4.75725144e-01
4.23214287e-01 8.60502183e-01 -4.96879697e-01 -1.14431584e+00
-4.23775554e-01 -7.59686768e-01 -1.13482809e+00 -1.77505746e-01
4.21194471e-02 -1.42590463e-01 -1.04454195e+00 2.11005211e+00
5.81227958e-01 6.93413496e-01 8.98947045e-02 5.45108557e-01
1.04895222e+00 7.01949537e-01 2.71358699e-01 -1.62987724e-01
1.27864230e+00 -1.15100348e+00 -3.64311069e-01 -2.70730942e-01
1.04063547e+00 -1.18916273e-01 1.01467872e+00 -4.65348899e-01
-5.00936866e-01 -5.48552036e-01 -1.08311975e+00 -5.44263385e-02
-6.03230655e-01 -2.91208953e-01 6.75397396e-01 5.73218644e-01
-8.61993670e-01 7.48208106e-01 -7.50981331e-01 -5.90264082e-01
6.58074677e-01 1.34010121e-01 -4.17660385e-01 -1.51146948e-01
-1.21257138e+00 3.70406181e-01 6.44513130e-01 -1.31680638e-01
-8.12247813e-01 -9.19763923e-01 -1.19500971e+00 5.59791088e-01
7.03768194e-01 -5.61959624e-01 1.01565540e+00 -8.64246368e-01
-9.72934842e-01 9.42252934e-01 -1.24862544e-01 -1.04640149e-01
1.08312733e-01 5.47165453e-01 -4.89792019e-01 3.47498469e-02
3.44036967e-01 5.13095677e-01 6.34847522e-01 -1.22693598e+00
-6.38324499e-01 -4.11460519e-01 2.84794778e-01 -5.09533323e-02
-9.57731843e-01 -5.78637779e-01 -4.38961357e-01 -6.25522554e-01
1.31360993e-01 -8.60663593e-01 -1.94502905e-01 1.12557635e-01
-5.06759763e-01 -5.51180243e-01 6.95668638e-01 -1.06996156e-01
1.32212532e+00 -2.23564243e+00 2.34781399e-01 2.72010475e-01
7.94181585e-01 1.77664191e-01 -4.72269624e-01 4.97812420e-01
-2.03511968e-01 2.80024558e-01 -2.25626647e-01 -4.69227344e-01
-7.01821689e-03 2.70041645e-01 -1.33459970e-01 3.95993620e-01
1.90271482e-01 1.11455476e+00 -1.21212149e+00 -5.01508474e-01
-3.41737904e-02 2.45043755e-01 -3.21817309e-01 2.21753865e-01
-6.58216402e-02 4.34172861e-02 -4.42811191e-01 6.23072624e-01
6.08651698e-01 -6.63174033e-01 3.62421632e-01 -3.67067426e-01
3.10992211e-01 2.65350286e-02 -9.17594671e-01 1.70129776e+00
-5.67376196e-01 3.34433824e-01 -1.13270260e-01 -1.33646286e+00
7.52935708e-01 1.74367741e-01 4.32755977e-01 -4.24103826e-01
2.16603249e-01 2.03049511e-01 1.34794572e-02 -3.48448306e-01
1.98418438e-01 -1.66630715e-01 -8.33613798e-02 4.97918129e-01
3.79322767e-01 3.75512332e-01 3.06855440e-01 6.25385284e-01
1.24814928e+00 -3.68189365e-01 3.67871881e-01 -3.00409257e-01
3.96390200e-01 -3.20350528e-01 8.20835233e-01 5.35256982e-01
-3.40755194e-01 4.56596881e-01 6.27208352e-01 -4.63264644e-01
-8.41043055e-01 -9.51410770e-01 9.49252397e-02 1.35461664e+00
4.62769032e-01 -7.29300022e-01 -5.20224988e-01 -1.17619014e+00
6.28691316e-02 5.28251767e-01 -9.95623112e-01 -6.35281682e-01
-3.60857725e-01 -7.55608022e-01 2.83604026e-01 6.19428635e-01
2.91465044e-01 -7.45233834e-01 -1.67070046e-01 9.05559137e-02
7.27177784e-02 -9.20058787e-01 -5.79012334e-01 3.28731239e-01
-7.36765981e-01 -1.18926227e+00 -7.05235600e-01 -1.20424843e+00
8.73999596e-01 6.72374189e-01 1.08020568e+00 4.64516401e-01
-3.59557331e-01 2.67595947e-01 -7.17085361e-01 7.59387687e-02
-2.47120589e-01 6.22824848e-01 -4.31311131e-02 2.19897807e-01
4.00107235e-01 -8.10674846e-01 -4.57652360e-01 2.08063260e-01
-8.39956164e-01 6.04857765e-02 5.12057483e-01 9.19456899e-01
3.66378248e-01 1.09663531e-01 8.03236485e-01 -1.43924367e+00
3.72140020e-01 -1.13697624e+00 -1.97946116e-01 4.82631475e-01
-7.43711174e-01 4.62264270e-02 9.73864377e-01 -5.30371368e-01
-5.98198593e-01 -1.59896553e-01 -8.41183029e-03 -4.66285169e-01
8.70887190e-02 6.59689367e-01 -4.11741555e-01 -3.91267762e-02
5.34669161e-01 1.17061213e-01 -6.54361993e-02 -2.91423649e-01
5.25479615e-01 5.86906314e-01 2.45576963e-01 -3.99801970e-01
1.11981821e+00 3.66333902e-01 1.04557119e-01 -6.15292668e-01
-9.90774512e-01 -6.20403230e-01 -6.30792618e-01 -5.55339865e-02
6.37927234e-01 -7.81844795e-01 -4.52377558e-01 3.86491984e-01
-7.91119695e-01 -4.45613354e-01 -3.45637977e-01 1.37647361e-01
-1.37966692e-01 3.13824803e-01 -5.96143901e-01 -3.59049082e-01
-3.35644722e-01 -8.95701826e-01 7.74775088e-01 4.63758647e-01
7.12812841e-02 -1.40007865e+00 1.65946364e-01 -1.15147091e-01
3.20769787e-01 7.20346868e-02 1.07357252e+00 -1.16169178e+00
-2.11819410e-01 -2.54286885e-01 -3.91705751e-01 1.44078106e-01
5.24870276e-01 -1.67964578e-01 -8.90022278e-01 -6.62733138e-01
-3.96026999e-01 -4.43859011e-01 1.09158742e+00 -3.92064229e-02
1.24920642e+00 -2.11824104e-01 -7.61788845e-01 7.80172408e-01
1.41252708e+00 -2.48565152e-01 3.04030836e-01 6.13982230e-02
1.07485104e+00 5.76247334e-01 4.74251807e-01 2.46824175e-01
6.02559805e-01 5.78468978e-01 4.49466705e-01 5.35805523e-02
-2.29694307e-01 -4.16187942e-01 -1.32971719e-01 8.44812870e-01
4.85211372e-01 -5.03274500e-01 -8.96794975e-01 7.61516631e-01
-1.75444710e+00 -8.81284535e-01 2.20866889e-01 1.87470961e+00
6.90894604e-01 -6.50037685e-03 1.18613215e-02 9.56029445e-02
1.07752526e+00 5.45862556e-01 -5.60131013e-01 5.76339150e-03
3.35510820e-01 9.67519637e-03 1.87957674e-01 3.03069115e-01
-1.19685030e+00 8.74120533e-01 4.48319340e+00 9.88720715e-01
-1.11534512e+00 4.06753957e-01 7.05644131e-01 2.14000240e-01
-4.04586315e-01 2.46418789e-01 -7.28268921e-01 6.11291587e-01
7.85272658e-01 -3.44705760e-01 1.83838964e-01 9.19187188e-01
-3.74146998e-01 5.12462378e-01 -1.36927962e+00 7.88520157e-01
2.37427652e-01 -1.29861343e+00 -9.47608724e-02 3.28621827e-02
9.08442497e-01 -3.49762267e-04 -1.52836278e-01 7.10733712e-01
1.76284224e-01 -7.91641951e-01 2.50903875e-01 1.85498819e-01
8.58180583e-01 -6.28181815e-01 6.32898629e-01 3.85924727e-01
-1.64508343e+00 -7.69326687e-02 -4.52609360e-01 7.92508498e-02
-7.26811364e-02 6.24977052e-01 -5.69811344e-01 6.96599901e-01
4.53393042e-01 1.13948631e+00 -7.37660468e-01 9.23610270e-01
-1.67795062e-01 4.52452391e-01 -6.97190166e-02 -7.30564669e-02
2.32711583e-01 -6.04721531e-02 3.07382286e-01 9.15349483e-01
2.23774254e-01 1.05132379e-01 4.34521586e-01 8.15627992e-01
-5.84532261e-01 -4.71899137e-02 -5.23635805e-01 -1.65182471e-01
8.80428016e-01 1.67622185e+00 -8.35326791e-01 -3.91136080e-01
-6.01695716e-01 1.11269677e+00 7.24675953e-01 2.51724541e-01
-7.19611943e-01 -8.58112037e-01 5.89764476e-01 -7.21521080e-02
2.61787295e-01 1.77739322e-01 -1.12114988e-01 -1.26446581e+00
-8.58157687e-03 -3.54079634e-01 6.13762915e-01 -2.20280200e-01
-1.68375075e+00 5.73868573e-01 -1.61355004e-01 -1.36931026e+00
6.86708912e-02 -4.67377841e-01 -1.03734958e+00 5.32700837e-01
-1.58396506e+00 -1.54330301e+00 -6.32397175e-01 3.53703976e-01
4.78634030e-01 -1.53929386e-02 7.43233562e-01 4.32042897e-01
-8.11518669e-01 1.01708782e+00 7.37696961e-02 4.78394121e-01
6.06354415e-01 -1.17103267e+00 4.16195244e-01 7.57528543e-01
3.02225560e-01 6.42313242e-01 3.88518453e-01 -5.91817081e-01
-1.19659328e+00 -1.58166611e+00 9.33250070e-01 -7.69979507e-02
7.36518979e-01 -5.15093088e-01 -1.17480671e+00 8.52921247e-01
-1.52159095e-01 7.33184934e-01 8.06342602e-01 3.24416608e-01
-7.04609752e-01 -3.77038658e-01 -1.06031215e+00 5.00445247e-01
1.22251189e+00 -7.15799212e-01 -3.43297362e-01 4.19234246e-01
9.01657045e-01 6.72996938e-02 -9.88641798e-01 4.25330341e-01
3.38646531e-01 -5.00135124e-01 8.04332674e-01 -8.68954122e-01
4.74084556e-01 -1.03611007e-01 -7.09443465e-02 -1.66171610e+00
-6.19503200e-01 -2.27419853e-01 -2.95503944e-01 1.62464452e+00
4.23070163e-01 -7.49602914e-01 9.43807542e-01 3.38696063e-01
-2.05457583e-01 -7.69955277e-01 -6.90246224e-01 -8.81822586e-01
1.45328313e-01 1.42533723e-02 6.03896201e-01 1.39608932e+00
2.09834635e-01 5.25088906e-01 -2.35720217e-01 2.94642180e-01
7.20322669e-01 3.65160972e-01 6.09468758e-01 -1.58846283e+00
-3.11255723e-01 -3.79733354e-01 -7.02600479e-01 -8.53192031e-01
6.71919227e-01 -1.45221114e+00 3.84862199e-02 -1.48051274e+00
7.14953423e-01 -8.33373070e-01 -5.93773127e-01 7.28878736e-01
-5.21014392e-01 2.53593743e-01 1.50041029e-01 2.03089744e-01
-8.11883986e-01 7.55690157e-01 8.47656786e-01 -3.86359185e-01
-7.74343358e-03 -5.45984134e-02 -8.48331571e-01 4.60576832e-01
8.63835335e-01 -6.15079880e-01 -6.06977940e-01 -3.69502932e-01
1.79233193e-01 -3.82585496e-01 4.06087130e-01 -9.26507294e-01
5.04986107e-01 -1.44909456e-01 2.83262320e-02 -2.33722880e-01
1.37999594e-01 -8.52234066e-01 -1.11282833e-01 5.75722933e-01
-4.80592698e-01 -2.30245218e-01 -2.82049805e-01 9.05217946e-01
-3.37625928e-02 -3.96389961e-01 8.57066393e-01 8.22285935e-03
-1.06346476e+00 8.02455664e-01 3.02736253e-01 3.85486990e-01
1.41305804e+00 2.49153022e-02 -5.14447153e-01 -1.11318827e-01
-6.04741752e-01 5.92891276e-01 6.87459648e-01 4.85074699e-01
4.43379015e-01 -1.52306342e+00 -5.87004602e-01 1.47785977e-01
6.95662677e-01 -2.73983553e-02 3.84255797e-01 7.26631224e-01
-1.20645516e-01 -3.80822271e-02 4.97875735e-02 -4.49249864e-01
-1.11235785e+00 8.08477998e-01 2.66360819e-01 -1.40934706e-01
-5.51138937e-01 1.02083516e+00 2.11634472e-01 -7.56226420e-01
1.45720407e-01 1.49802029e-01 -1.70267388e-01 1.98322207e-01
4.45380211e-01 3.56479079e-01 -9.22336727e-02 -5.71926475e-01
-3.98043036e-01 5.14496624e-01 -3.59944165e-01 4.98196542e-01
1.26452732e+00 -1.68625116e-01 -1.48335308e-01 6.57138169e-01
1.70788181e+00 -2.92891830e-01 -1.05201876e+00 -5.79407156e-01
2.42895186e-02 -3.70759338e-01 -1.57022588e-02 -3.05644721e-01
-1.48223507e+00 8.66995633e-01 3.82946759e-01 3.23671311e-01
9.70136523e-01 3.33351910e-01 8.40224624e-01 3.15221697e-01
2.38149032e-01 -7.92210698e-01 1.55462310e-01 2.88913906e-01
1.47036254e-01 -1.49635589e+00 -1.22641146e-01 -7.15414882e-01
-3.76473844e-01 1.03750432e+00 8.44549298e-01 -9.66531113e-02
8.45324218e-01 -8.60388279e-02 -2.16275781e-01 -3.29329938e-01
-7.62745380e-01 -2.14857936e-01 1.39530897e-01 4.49341804e-01
2.77664632e-01 1.69645503e-01 -2.02585027e-01 6.64363801e-01
3.49111080e-01 -2.57060587e-01 4.03709531e-01 9.33144748e-01
-4.09833550e-01 -1.12147343e+00 3.91440570e-01 6.27000928e-01
-9.22898948e-02 -1.91276997e-01 -2.30052561e-01 5.39884508e-01
3.59099358e-02 9.42181289e-01 9.70854089e-02 -7.30295479e-01
1.32905215e-01 7.48281106e-02 1.02351524e-01 -1.04778123e+00
-3.88747573e-01 -4.88256842e-01 -2.55653173e-01 -2.89136082e-01
-2.32565776e-01 -2.26144552e-01 -1.12172413e+00 -3.65875334e-01
-4.45351362e-01 2.90809661e-01 3.09316128e-01 8.53346586e-01
4.66972321e-01 6.41812086e-01 1.02979934e+00 -6.94062710e-01
-8.26504111e-01 -9.47402358e-01 -7.78458416e-01 6.90883994e-01
2.99946398e-01 -6.54615581e-01 -6.41048014e-01 -3.48210335e-01] | [7.396748065948486, 6.176048755645752] |
4e687ee6-7bee-4112-bd4d-122c8015b623 | personalized-one-shot-lipreading-for-an-als | 2111.01740 | null | https://arxiv.org/abs/2111.01740v1 | https://arxiv.org/pdf/2111.01740v1.pdf | Personalized One-Shot Lipreading for an ALS Patient | Lipreading or visually recognizing speech from the mouth movements of a speaker is a challenging and mentally taxing task. Unfortunately, multiple medical conditions force people to depend on this skill in their day-to-day lives for essential communication. Patients suffering from Amyotrophic Lateral Sclerosis (ALS) often lose muscle control, consequently their ability to generate speech and communicate via lip movements. Existing large datasets do not focus on medical patients or curate personalized vocabulary relevant to an individual. Collecting a large-scale dataset of a patient, needed to train mod-ern data-hungry deep learning models is, however, extremely challenging. In this work, we propose a personalized network to lipread an ALS patient using only one-shot examples. We depend on synthetically generated lip movements to augment the one-shot scenario. A Variational Encoder based domain adaptation technique is used to bridge the real-synthetic domain gap. Our approach significantly improves and achieves high top-5accuracy with 83.2% accuracy compared to 62.6% achieved by comparable methods for the patient. Apart from evaluating our approach on the ALS patient, we also extend it to people with hearing impairment relying extensively on lip movements to communicate. | ['C V Jawahar', 'Vinay Namboodiri', 'Rudrabha Mukhopadhyay', 'Aditya Agarwal', 'Bipasha Sen'] | 2021-11-02 | personalized-one-shot-lipreading-for-an-als-1 | https://arxiv.org/abs/2111.01740 | https://arxiv.org/pdf/2111.01740.pdf | null | ['lipreading'] | ['computer-vision'] | [ 4.89111096e-01 5.02495408e-01 -1.78400859e-01 -1.89693913e-01
-1.42352116e+00 -3.61138508e-02 2.89133042e-01 -5.54274857e-01
-4.73324180e-01 9.92714345e-01 5.58809400e-01 6.17406331e-02
1.18117481e-01 -1.54940560e-01 -4.52654719e-01 -6.08005106e-01
4.96399492e-01 7.87222147e-01 -8.03146660e-02 -1.33658081e-01
-3.30243222e-02 1.56706795e-01 -1.50865340e+00 4.90075350e-01
8.55003476e-01 6.49420619e-01 6.38023615e-01 7.62797594e-01
-2.76950598e-01 3.84256721e-01 -6.68295622e-01 -2.11579040e-01
-5.29419854e-02 -5.15956283e-01 -7.26573408e-01 3.11864585e-01
1.93744168e-01 -5.26696682e-01 -1.21951863e-01 8.15601826e-01
1.19357502e+00 -2.12231725e-01 7.01722622e-01 -1.19796503e+00
-4.15671825e-01 5.15023470e-01 -2.49694020e-01 -4.28071022e-01
3.97393763e-01 3.51247460e-01 6.97503805e-01 -6.95538461e-01
8.04310322e-01 1.07605803e+00 6.11404479e-01 1.40450299e+00
-1.20169020e+00 -5.54043591e-01 -2.25697458e-01 2.88010150e-01
-1.09638524e+00 -1.21347475e+00 8.25393736e-01 -4.45127964e-01
8.32675457e-01 -3.07878107e-02 6.42699897e-01 1.74278367e+00
-3.64922106e-01 9.00478005e-01 8.09773684e-01 -3.53135675e-01
1.71389014e-01 1.66003287e-01 -3.89709413e-01 1.50952160e-01
-3.38960528e-01 -6.75756782e-02 -8.14412653e-01 2.69320626e-02
3.32039356e-01 -3.42712849e-01 -6.11746669e-01 -3.27624768e-01
-1.48842454e+00 6.05902135e-01 -2.15449668e-02 2.62307107e-01
-4.43026721e-01 7.90333897e-02 4.33169127e-01 1.48826405e-01
2.69372523e-01 3.26019526e-02 -6.02769256e-01 -7.30171621e-01
-8.79626155e-01 2.54703104e-01 6.87981665e-01 8.41395915e-01
6.60231188e-02 -3.82843986e-02 -2.63083011e-01 1.34600472e+00
3.16773564e-01 5.22915602e-01 9.11235332e-01 -1.06867099e+00
5.54385960e-01 3.66737962e-01 7.44207725e-02 -1.61134511e-01
-5.36229551e-01 -6.74023665e-03 -6.88296497e-01 3.25902581e-01
6.95354700e-01 -1.42990306e-01 -8.44617426e-01 2.05674124e+00
3.48584026e-01 -3.84793617e-03 4.49986458e-01 6.91794693e-01
7.40206182e-01 2.20394760e-01 1.18078463e-01 -4.25803095e-01
1.27851748e+00 -9.08897102e-01 -8.73252690e-01 -3.80593181e-01
6.59149110e-01 -6.18026555e-01 1.47637331e+00 4.33534056e-01
-1.35292137e+00 -6.98312446e-02 -6.40185058e-01 -1.68779507e-01
-1.54919857e-02 2.10351154e-01 9.07823220e-02 5.26183486e-01
-1.07637286e+00 6.06272697e-01 -6.45279765e-01 -5.21907628e-01
8.09054554e-01 4.98415142e-01 -5.80277979e-01 1.33999482e-01
-1.11294162e+00 8.94942045e-01 -5.66394217e-02 -4.06967998e-01
-3.69844198e-01 -8.72685194e-01 -8.48543167e-01 -2.69672096e-01
1.21952735e-01 -9.55351532e-01 1.58507121e+00 -7.92186975e-01
-1.86369824e+00 1.20850968e+00 -4.05030966e-01 -5.04649520e-01
1.02506232e+00 -2.83480454e-02 -3.17515790e-01 3.61900359e-01
-7.57513791e-02 9.56153512e-01 1.00809836e+00 -1.12436390e+00
-4.15261418e-01 -4.50828969e-01 -3.83784890e-01 2.65780389e-01
-2.53562659e-01 2.38043051e-02 -2.03740582e-01 -7.32007444e-01
-6.20241091e-02 -7.85573542e-01 2.30905831e-01 5.25145710e-01
-5.84972084e-01 -1.47953466e-01 9.20789301e-01 -9.37453926e-01
7.55511224e-01 -2.05677152e+00 1.89174056e-01 -4.69679505e-01
1.88237950e-01 4.11711931e-01 -8.20512623e-02 2.70406544e-01
-6.08152989e-03 -8.48121867e-02 -7.30505764e-01 -8.92482638e-01
3.05319965e-01 1.90749094e-01 -6.69180080e-02 3.78570735e-01
8.86964127e-02 9.64157164e-01 -6.59119010e-01 -6.74633622e-01
1.39779136e-01 9.11006212e-01 -7.11348653e-01 1.17213912e-01
-2.41095811e-01 8.31549108e-01 -9.41424221e-02 6.76637173e-01
3.42817456e-01 -2.04252899e-01 7.14400336e-02 -8.56136903e-02
4.05342072e-01 2.26734877e-01 -6.59104109e-01 2.17265129e+00
-7.45177507e-01 6.28827870e-01 4.15419012e-01 -1.06407845e+00
5.92307985e-01 7.02838480e-01 6.79760575e-01 -5.59010267e-01
1.02670662e-01 3.77839476e-01 4.51831147e-02 -9.45416570e-01
-1.26587301e-01 -6.69303775e-01 1.45980611e-01 3.32415015e-01
-2.70163983e-01 -2.35363066e-01 -6.91980645e-02 -1.32364735e-01
8.72666955e-01 3.28683436e-01 3.01145613e-01 1.27858236e-01
5.80919206e-01 -3.45295250e-01 3.47892582e-01 7.65087232e-02
-4.93871242e-01 9.55532312e-01 4.20193881e-01 1.43895492e-01
-1.05313098e+00 -1.16043568e+00 -1.86415061e-01 7.38212347e-01
-3.48724693e-01 -2.48459056e-02 -1.09946942e+00 -4.15666163e-01
-1.41357526e-01 1.02009988e+00 -2.93405950e-01 -1.68333262e-01
-3.42056096e-01 -2.50430375e-01 6.79243922e-01 4.12973821e-01
3.28486025e-01 -1.38879454e+00 -5.85430324e-01 3.48510891e-01
-7.18644142e-01 -1.27979934e+00 -6.42249286e-01 -4.16718572e-01
-4.21007931e-01 -8.51590872e-01 -1.47545922e+00 -9.15182829e-01
2.90789187e-01 -4.29342240e-01 7.49481738e-01 -4.43993211e-01
-5.49460590e-01 4.18960840e-01 -8.64533782e-02 -5.66377759e-01
-9.35205936e-01 -7.99933299e-02 3.98645431e-01 -1.86956432e-02
3.67045283e-01 -9.44602311e-01 -6.01440430e-01 2.40584075e-01
-4.96473521e-01 3.82165343e-01 5.56190014e-01 9.05371845e-01
5.79164624e-01 -5.77345610e-01 9.66305196e-01 -1.94522694e-01
7.13673949e-01 -2.02217326e-01 3.24585326e-02 1.04042470e-01
-2.53469646e-01 4.25560288e-02 2.87147373e-01 -9.30873990e-01
-7.77462721e-01 2.19689757e-01 -4.77574915e-01 -5.51419616e-01
-3.65286916e-01 -2.20359832e-01 -4.77884203e-01 3.95999163e-01
5.29003024e-01 4.09214348e-01 6.09070063e-01 -6.15491152e-01
3.16616654e-01 1.37202263e+00 7.90541768e-01 -2.73392081e-01
3.68449688e-01 4.80584890e-01 -2.61336684e-01 -1.16416562e+00
-4.19347078e-01 -2.01947629e-01 -4.62618262e-01 -1.45856097e-01
9.38906670e-01 -6.33455396e-01 -1.10890317e+00 7.75228977e-01
-1.25753999e+00 -6.73759758e-01 -4.71216232e-01 4.75945830e-01
-1.32546306e+00 3.18112671e-01 -1.63690835e-01 -8.99739385e-01
-5.24028480e-01 -1.37653351e+00 1.44579256e+00 -1.18388325e-01
-5.47912717e-01 -7.15104461e-01 6.12314306e-02 7.90535748e-01
4.12430912e-01 6.55393451e-02 6.71513617e-01 -6.17126822e-01
-1.66744947e-01 -1.75482422e-01 -7.96421021e-02 3.65309715e-01
4.56001639e-01 -5.82011342e-01 -1.39858258e+00 -2.43612435e-02
-1.32308483e-01 -6.70896530e-01 6.44496202e-01 5.26710033e-01
1.19387853e+00 -3.19033325e-01 -3.76652986e-01 3.84020805e-01
6.81653798e-01 -6.60215169e-02 6.18519545e-01 -1.15515366e-01
4.67448056e-01 1.02255678e+00 1.55937970e-01 5.13241768e-01
4.80942100e-01 9.70587313e-01 1.77239075e-01 3.59253883e-01
-6.44839108e-01 -3.40691239e-01 5.03854334e-01 6.25210583e-01
1.43021330e-01 -3.17996055e-01 -9.53999877e-01 7.85650015e-01
-1.49971044e+00 -9.01866794e-01 2.46179089e-01 2.10842919e+00
1.10938096e+00 -6.18430823e-02 2.58951604e-01 4.43843722e-01
7.88034678e-01 -1.98374495e-01 -9.60799277e-01 -5.52291647e-02
-6.39566109e-02 -1.16781034e-02 1.41810337e-02 6.07975602e-01
-7.29721665e-01 8.77441049e-01 5.63253021e+00 7.98573017e-01
-1.21892965e+00 1.88470408e-01 3.16043228e-01 -5.39807975e-01
-1.72058284e-01 -6.81486011e-01 -6.09424472e-01 5.37018597e-01
1.16785431e+00 -1.63780749e-01 5.36332011e-01 5.34886181e-01
6.02758586e-01 1.99643984e-01 -1.18333054e+00 1.54899621e+00
1.11256361e-01 -1.02872217e+00 -2.64113277e-01 2.27103129e-01
1.19710177e-01 -3.13223246e-03 2.45811209e-01 6.16806373e-02
-1.14886194e-01 -1.17989695e+00 5.76176941e-01 7.40420103e-01
1.37828565e+00 -5.01493990e-01 1.91063121e-01 6.32646322e-01
-7.51003504e-01 -6.35384768e-02 1.00020982e-01 4.41552311e-01
6.44259036e-01 2.09985673e-01 -1.23674786e+00 -7.61814415e-02
3.90154719e-01 3.97978246e-01 1.96615800e-01 6.76888824e-01
-1.62601098e-01 2.69451648e-01 -4.17815417e-01 1.61234196e-02
-3.13459694e-01 2.97529131e-01 9.18194056e-01 6.76190615e-01
5.64383388e-01 -1.64410472e-01 -4.15319383e-01 1.00743091e+00
-1.33079633e-01 2.88021713e-01 -6.86673880e-01 -3.04820627e-01
1.69475183e-01 8.14744651e-01 1.32907197e-01 -8.21586698e-02
-2.03753725e-01 1.31241345e+00 1.01694711e-01 1.87698558e-01
-5.15297592e-01 -2.79226154e-01 1.04485893e+00 3.64281535e-01
1.51376471e-01 1.07347585e-01 -1.74073517e-01 -9.56601202e-01
2.58447737e-01 -9.91604805e-01 -1.52902231e-01 -1.07457709e+00
-1.16161597e+00 4.81168360e-01 -2.17743024e-01 -1.33135939e+00
-8.61853421e-01 -6.58901215e-01 -3.92745674e-01 1.07652175e+00
-1.47495258e+00 -1.33480418e+00 -2.25421011e-01 7.51251757e-01
8.95569623e-01 -2.46256903e-01 1.03778160e+00 1.82817385e-01
-2.71684289e-01 7.97689319e-01 -3.87607403e-02 -1.27379283e-01
1.00464571e+00 -9.84583378e-01 2.56919444e-01 1.24293931e-01
-2.01903909e-01 3.31517100e-01 7.13358581e-01 -5.46269536e-01
-1.01280248e+00 -8.15198839e-01 1.24667549e+00 -3.44710737e-01
5.61687171e-01 -4.52785105e-01 -8.07657182e-01 2.72761434e-01
6.81922957e-02 -9.87205952e-02 6.35595083e-01 -3.63544047e-01
-2.33661942e-02 7.13363588e-02 -1.65008855e+00 7.98128366e-01
1.38219428e+00 -6.15760088e-01 -6.73870146e-01 5.35143673e-01
8.62268746e-01 -2.99294621e-01 -7.49132454e-01 2.42165983e-01
7.88640141e-01 -7.47622728e-01 9.71003592e-01 -6.87174261e-01
4.67665821e-01 2.18387544e-01 -2.67148346e-01 -1.38738072e+00
5.96829712e-01 -1.04510868e+00 -1.91161186e-01 1.10608554e+00
4.57348496e-01 -7.28839695e-01 1.02581346e+00 6.30866289e-01
-6.34880140e-02 -7.06854045e-01 -1.17775810e+00 -7.04440832e-01
5.07239819e-01 -8.77252817e-01 5.47912359e-01 5.08202374e-01
3.14490229e-01 1.87076807e-01 -4.53387469e-01 -7.68156126e-02
7.49146402e-01 -3.59459370e-01 7.71522701e-01 -1.28240991e+00
-2.48740554e-01 -5.07955015e-01 -2.45073557e-01 -9.61985826e-01
4.27948952e-01 -9.05510247e-01 1.67865157e-01 -1.67749786e+00
4.38968875e-02 -1.12009771e-01 2.67432511e-01 4.29578543e-01
1.65838540e-01 1.42570585e-01 8.69578794e-02 9.53447372e-02
1.74857061e-02 7.02902675e-01 1.42178309e+00 -3.07795703e-01
-2.52998084e-01 3.01726073e-01 -6.46816790e-01 9.11661565e-01
9.61915851e-01 -2.63745159e-01 -5.50907850e-01 -7.89017007e-02
-1.05136730e-01 2.79374808e-01 4.38366920e-01 -7.94440627e-01
1.27694726e-01 8.45934153e-02 -2.28468683e-02 -4.36550766e-01
9.84092593e-01 -5.23551881e-01 -2.59109318e-01 4.18415397e-01
-3.24516833e-01 -6.65331304e-01 1.58412769e-01 4.53029513e-01
1.05033860e-01 -1.74355537e-01 1.08736861e+00 -1.66318402e-01
-4.50440615e-01 3.65920156e-01 -3.47045332e-01 3.82057041e-01
9.76778805e-01 -3.18596184e-01 -4.92290258e-02 -7.35810876e-01
-1.40622544e+00 -2.22223606e-02 4.49505508e-01 4.33281690e-01
7.64198363e-01 -1.23780084e+00 -8.47314954e-01 4.07454878e-01
3.16685259e-01 1.31928371e-02 4.52219456e-01 1.02323711e+00
-2.71671861e-01 4.19708639e-01 -5.42682111e-02 -6.02457583e-01
-1.51095879e+00 3.38492930e-01 5.78560174e-01 7.35560805e-02
-9.97062504e-01 8.51904452e-01 2.07668856e-01 -4.97040242e-01
5.45020700e-01 -2.82559127e-01 -4.48463187e-02 1.20563194e-01
7.40845323e-01 2.20939845e-01 -8.10121596e-02 -7.83282161e-01
-2.82826066e-01 6.45701706e-01 1.70423821e-01 -6.23247862e-01
1.21773863e+00 -2.81608164e-01 5.03023565e-01 4.79832888e-01
1.25787115e+00 8.59726500e-03 -1.32378840e+00 -8.32450241e-02
-4.05744642e-01 -1.09231882e-01 -9.89440531e-02 -1.01028621e+00
-8.50760639e-01 1.24297798e+00 7.20591247e-01 -2.75899142e-01
1.02939880e+00 3.17475259e-01 1.12695992e+00 2.72033095e-01
3.01502258e-01 -1.12818873e+00 1.18532568e-01 7.87903368e-02
1.32899892e+00 -1.35646367e+00 -5.45012653e-01 -1.45293906e-01
-1.01017618e+00 8.53522956e-01 9.55405086e-02 4.68485683e-01
4.84453410e-01 3.29883039e-01 3.12113166e-01 4.02544677e-01
-6.84046507e-01 -2.95664161e-01 9.10114124e-02 1.22739089e+00
2.15324506e-01 -5.49577884e-02 -4.73331176e-02 7.67494380e-01
-4.71601278e-01 3.84446532e-01 2.60976821e-01 5.99175096e-01
-2.94215828e-01 -1.30663371e+00 -3.14306617e-01 3.01993430e-01
-4.29960519e-01 -1.17777765e-01 -3.86553556e-01 7.27475464e-01
4.64369133e-02 9.02491748e-01 9.82641429e-02 -6.61148597e-03
3.92499208e-01 6.37960494e-01 5.24741828e-01 -3.99612039e-01
9.61493775e-02 6.75582215e-02 2.09951714e-01 -4.81436938e-01
-3.57151300e-01 -1.04609334e+00 -1.46137595e+00 -8.27007070e-02
1.86619475e-01 -5.96146047e-01 1.04056048e+00 1.02227092e+00
3.64041567e-01 5.13591468e-01 1.49644256e-01 -9.38035309e-01
-8.28414917e-01 -1.29521227e+00 -5.19356191e-01 4.61299807e-01
7.90871620e-01 -6.92436039e-01 -5.18831849e-01 2.00266600e-01] | [14.330784797668457, 4.9878926277160645] |
2ab4eecd-939f-41c5-8f57-0f27fe7c5a0a | rf-next-efficient-receptive-field-search-for | 2206.06637 | null | https://arxiv.org/abs/2206.06637v2 | https://arxiv.org/pdf/2206.06637v2.pdf | RF-Next: Efficient Receptive Field Search for Convolutional Neural Networks | Temporal/spatial receptive fields of models play an important role in sequential/spatial tasks. Large receptive fields facilitate long-term relations, while small receptive fields help to capture the local details. Existing methods construct models with hand-designed receptive fields in layers. Can we effectively search for receptive field combinations to replace hand-designed patterns? To answer this question, we propose to find better receptive field combinations through a global-to-local search scheme. Our search scheme exploits both global search to find the coarse combinations and local search to get the refined receptive field combinations further. The global search finds possible coarse combinations other than human-designed patterns. On top of the global search, we propose an expectation-guided iterative local search scheme to refine combinations effectively. Our RF-Next models, plugging receptive field search to various models, boost the performance on many tasks, e.g., temporal action segmentation, object detection, instance segmentation, and speech synthesis. The source code is publicly available on http://mmcheng.net/rfnext. | ['Liang Wang', 'Ming-Ming Cheng', 'Qi Han', 'Zhong-Yu Li', 'ShangHua Gao'] | 2022-06-14 | null | null | null | null | ['action-segmentation'] | ['computer-vision'] | [ 1.50651962e-01 -1.44835696e-01 -3.21448088e-01 -5.40390730e-01
-6.21907651e-01 -6.27411962e-01 4.94538426e-01 -2.90858895e-01
-5.92557192e-01 4.48636413e-01 3.99849981e-01 -1.69801682e-01
-2.28406534e-01 -5.83250046e-01 -6.21598542e-01 -6.46173537e-01
2.23514035e-01 1.93760067e-01 8.68872464e-01 -2.46277377e-01
6.29015028e-01 5.82229137e-01 -1.42591119e+00 8.24869454e-01
5.36598742e-01 9.36157644e-01 9.64365661e-01 7.02132046e-01
-2.46567696e-01 8.28503370e-01 -3.35403651e-01 2.38539577e-01
1.91738054e-01 -3.43857199e-01 -1.15146089e+00 8.93859938e-03
9.31705013e-02 -1.09142251e-01 -4.69158664e-02 1.02208400e+00
3.25623721e-01 5.73319376e-01 2.77470201e-01 -6.82924867e-01
-5.34441411e-01 8.46604645e-01 -4.30693388e-01 6.02061510e-01
9.16657224e-02 2.14540243e-01 1.11298096e+00 -9.40475702e-01
6.86365545e-01 1.51522160e+00 3.29025567e-01 8.66710067e-01
-1.22253692e+00 -4.75645393e-01 6.95952237e-01 4.58262824e-02
-1.49841559e+00 -7.49143898e-01 4.68983591e-01 -2.55916566e-01
1.34507573e+00 3.92934024e-01 6.94655597e-01 7.34269977e-01
1.50438130e-01 9.97262180e-01 1.03443527e+00 -3.70598227e-01
2.47637168e-01 -1.78358391e-01 6.82030246e-02 3.98290634e-01
-5.75846016e-01 1.09579600e-01 -4.40911531e-01 1.51523516e-01
1.28916335e+00 1.76600590e-01 -1.34440035e-01 3.29813838e-01
-1.39764619e+00 5.16104400e-01 6.52381361e-01 7.97885835e-01
-5.76874018e-01 3.20935935e-01 -3.23584937e-02 1.51287839e-01
2.17060909e-01 8.58410597e-01 -7.44779766e-01 1.24135308e-01
-1.06682694e+00 4.41760123e-01 1.66758567e-01 8.44652355e-01
1.06795251e+00 -3.86442572e-01 -5.62826335e-01 1.23774981e+00
5.27299047e-01 1.04456320e-01 5.87804258e-01 -1.36568546e+00
5.85933328e-01 4.58153665e-01 -7.35057667e-02 -6.37544751e-01
-3.51718307e-01 -1.85979515e-01 -7.43785381e-01 -2.38975827e-02
3.39231431e-01 1.89203635e-01 -1.27875042e+00 1.58765054e+00
2.96605110e-01 3.42519730e-02 -1.98948354e-01 9.11725998e-01
7.01266468e-01 8.85832608e-01 1.15606174e-01 -3.00606936e-02
1.36344242e+00 -1.22051859e+00 -6.13926053e-01 -6.43877804e-01
4.92213100e-01 -7.97757328e-01 8.75771880e-01 1.82712570e-01
-1.18732178e+00 -8.52803469e-01 -4.71716136e-01 1.32861072e-02
-2.27396294e-01 2.51077026e-01 6.29896104e-01 3.06415241e-02
-1.62144041e+00 6.76073968e-01 -7.64297605e-01 -2.42876634e-01
4.90405262e-01 6.58180118e-01 -1.84249341e-01 2.27981091e-01
-1.08083427e+00 5.58761716e-01 6.82553232e-01 3.65966946e-01
-7.18575954e-01 -2.28894413e-01 -5.86829364e-01 -2.91062500e-02
4.62651044e-01 -4.88531649e-01 1.49567056e+00 -9.18165863e-01
-1.37491500e+00 6.32979870e-01 -5.87691069e-01 -2.92466760e-01
-1.19611241e-01 9.04055387e-02 -1.48097292e-01 -1.07663739e-02
1.10968150e-01 1.49063063e+00 8.71638298e-01 -9.52381015e-01
-7.83219397e-01 -1.49025962e-01 8.59305784e-02 3.23915750e-01
1.55975223e-01 4.09410298e-01 -8.19139004e-01 -9.29408073e-01
6.19896889e-01 -8.73052359e-01 -7.69204497e-01 -3.52999389e-01
-3.01638246e-01 -5.75393260e-01 2.13735253e-01 -5.58108926e-01
1.43203175e+00 -2.28317499e+00 1.16226397e-01 3.27918828e-01
1.77015841e-01 2.12356627e-01 -4.25856739e-01 6.37236163e-02
-2.76634935e-02 2.81194687e-01 1.00692585e-01 -2.47491524e-01
-2.56397069e-01 2.37128481e-01 -2.87621289e-01 -4.73030917e-02
2.84179986e-01 1.14506149e+00 -8.02676260e-01 -6.18383050e-01
1.63675785e-01 9.89098027e-02 -6.76623881e-01 -4.46482934e-02
-4.66994077e-01 5.75188220e-01 -8.19132745e-01 6.22373879e-01
5.65993547e-01 -3.33108842e-01 4.13540378e-02 -9.49920062e-03
-3.51763219e-01 6.93524837e-01 -1.23896742e+00 1.71204782e+00
-3.31788987e-01 4.62541252e-01 4.96575534e-02 -8.21180820e-01
9.55965757e-01 1.18559271e-01 1.46643162e-01 -1.21364319e+00
3.60570252e-02 2.84502774e-01 1.06534921e-01 -3.31920683e-01
4.61683452e-01 8.92750546e-02 1.44647837e-01 2.74853796e-01
-1.92522164e-02 8.74151886e-02 2.78184384e-01 -6.00410253e-02
1.12603331e+00 3.44405979e-01 2.25094408e-01 -1.92821264e-01
3.66360515e-01 -1.26486808e-01 7.63435245e-01 9.77091014e-01
-1.27103060e-01 7.31704473e-01 1.74875557e-01 -5.31117976e-01
-7.02491522e-01 -6.25212908e-01 3.57677378e-02 1.48189950e+00
1.83762833e-01 -5.16682565e-01 -7.96157956e-01 -5.25850773e-01
-5.00708699e-01 3.80966753e-01 -5.93409359e-01 2.67304808e-01
-9.67673421e-01 -3.57702911e-01 3.84848535e-01 8.65810871e-01
5.68100512e-01 -1.90478921e+00 -6.62498713e-01 3.97783339e-01
-2.86895126e-01 -8.30242574e-01 -7.66953230e-01 4.15135324e-01
-1.16820776e+00 -4.71049666e-01 -8.80162776e-01 -8.75614285e-01
7.00062096e-01 3.29579860e-01 8.77939820e-01 1.05567880e-01
5.86031340e-02 -1.75991043e-01 -4.41713661e-01 6.30546510e-02
-2.03066349e-01 1.08652271e-01 -2.21554935e-01 -1.60093978e-01
2.05533832e-01 -4.17341381e-01 -7.88259566e-01 7.44973302e-01
-9.09979045e-01 2.67325848e-01 8.92780304e-01 6.50530934e-01
9.61230397e-01 4.76091206e-02 2.03844011e-01 -5.89086592e-01
5.17264724e-01 -9.79037508e-02 -5.19103765e-01 3.47617298e-01
-1.10051669e-01 4.49231833e-01 2.65515983e-01 -7.11617351e-01
-1.05003834e+00 2.54594028e-01 -5.09822547e-01 -4.19704407e-01
-5.90500832e-01 3.66420597e-01 -3.07542458e-02 1.29479885e-01
6.67400181e-01 2.57315159e-01 -6.00094199e-01 -7.13332355e-01
1.36927679e-01 3.52536589e-01 2.15974927e-01 -5.55078804e-01
1.77073747e-01 2.09965751e-01 -4.31033969e-01 -6.08917594e-01
-5.73551655e-01 -7.25222766e-01 -6.63409710e-01 8.56269151e-03
1.03961766e+00 -5.79312801e-01 -5.03701985e-01 4.54565257e-01
-1.41685319e+00 -8.56677711e-01 -1.37100518e-01 4.91401345e-01
-4.76313442e-01 -1.03351936e-01 -5.33140302e-01 -7.63021410e-01
3.89575809e-02 -1.31160593e+00 1.31230736e+00 3.21765840e-01
-5.34471571e-01 -7.92556524e-01 5.31116538e-02 1.45665720e-01
2.84282029e-01 -6.05084002e-01 5.35492837e-01 -4.53218430e-01
-9.42540586e-01 3.37726682e-01 -2.06726506e-01 3.26708257e-02
1.08038656e-01 -1.48149759e-01 -1.08633173e+00 6.34897798e-02
-2.78755009e-01 -7.87619427e-02 1.38568234e+00 9.27582383e-01
1.44051135e+00 -4.37641799e-01 -6.31581306e-01 6.20385945e-01
9.54049289e-01 6.58860028e-01 8.57434332e-01 2.47246698e-01
4.65446591e-01 8.31352949e-01 7.93880105e-01 2.98091561e-01
1.64383724e-01 7.51685798e-01 -1.86135760e-03 -2.19833683e-02
-2.41933241e-01 -3.24791849e-01 1.07086517e-01 5.03140092e-01
-4.37973171e-01 -2.99072564e-01 -9.15109932e-01 6.86728835e-01
-2.00970268e+00 -1.15276110e+00 2.60699868e-01 1.78175163e+00
8.96307766e-01 2.97065884e-01 6.48069978e-02 -2.16760598e-02
8.14765811e-01 3.22128177e-01 -3.32025111e-01 -3.83993149e-01
-2.89552920e-02 2.40561023e-01 3.84947389e-01 6.54355466e-01
-1.12980819e+00 1.47395611e+00 6.42456961e+00 1.28861368e+00
-1.11721528e+00 1.25754718e-02 8.44692647e-01 1.45498946e-01
-5.00389993e-01 1.85500443e-01 -1.31707311e+00 1.42174199e-01
5.62940061e-01 6.21596336e-01 7.70058453e-01 5.22145808e-01
3.73045146e-01 -2.73642868e-01 -8.65647495e-01 1.01865232e+00
-3.86765987e-01 -1.72813725e+00 -1.54616401e-01 1.53217763e-01
6.85605884e-01 1.53593704e-01 7.94544071e-02 2.11246252e-01
3.52989435e-01 -1.09772897e+00 9.68191087e-01 6.27797186e-01
4.57310319e-01 -1.87456965e-01 3.10137302e-01 5.62300146e-01
-1.52460849e+00 -1.92549571e-01 -3.27915281e-01 1.98220164e-02
-5.00712655e-02 2.02156827e-01 -8.46804738e-01 -1.20454490e-01
1.05728769e+00 5.80169261e-01 -5.76881468e-01 1.07122791e+00
-2.00313628e-01 5.79130292e-01 -4.90004927e-01 -2.60109574e-01
5.33291996e-01 1.92261972e-02 4.12248731e-01 1.28690135e+00
2.51941830e-01 2.03089342e-01 3.39080244e-02 1.14393163e+00
1.97688788e-01 -1.26064355e-02 -3.23778957e-01 -1.29639044e-01
4.99556333e-01 1.09783912e+00 -1.30101299e+00 -1.50283694e-01
-1.60811007e-01 9.29230869e-01 2.82558531e-01 7.42726564e-01
-5.68160594e-01 -2.22544745e-01 4.00698334e-01 1.87632948e-01
5.46138048e-01 -2.73826778e-01 -2.08821088e-01 -8.60666275e-01
-7.88934752e-02 -8.22706461e-01 2.73317754e-01 -7.73037136e-01
-7.93381989e-01 9.59363163e-01 2.42450088e-01 -9.86240029e-01
-4.13717538e-01 -4.74038929e-01 -5.47590733e-01 9.32629704e-01
-1.11320996e+00 -9.10666823e-01 1.36270195e-01 6.43464625e-01
1.10302341e+00 -3.57983224e-02 4.68271255e-01 4.11533713e-02
-2.35134244e-01 3.48516881e-01 -3.28180611e-01 1.17678523e-01
3.98506850e-01 -9.61381793e-01 7.14526057e-01 7.94823945e-01
4.30544585e-01 9.48311269e-01 3.40906829e-01 -7.49892175e-01
-5.89822650e-01 -9.51355219e-01 1.27040803e+00 -1.87121585e-01
2.29817793e-01 -4.33076799e-01 -9.21356082e-01 5.70277631e-01
6.09783866e-02 4.37916890e-02 2.13270620e-01 1.79418191e-01
-8.86818022e-02 -1.79008141e-01 -7.76139915e-01 7.52672017e-01
1.24966443e+00 -4.17781055e-01 -4.89720941e-01 7.30294734e-02
6.62136137e-01 -2.92464674e-01 -3.42231035e-01 3.54428113e-01
5.79252481e-01 -8.35097313e-01 9.34997320e-01 -2.08719045e-01
1.09440356e-01 -5.91172576e-01 -2.11151883e-01 -1.12752521e+00
-7.27139413e-01 -8.22883785e-01 2.47453883e-01 1.12650061e+00
8.34981740e-01 -5.38647115e-01 6.35772586e-01 4.97528791e-01
-2.68740475e-01 -8.30615461e-01 -8.59697223e-01 -4.87609535e-01
-1.08834960e-01 -6.53676987e-01 7.01737821e-01 3.68656099e-01
-2.89954931e-01 1.40317366e-01 -5.39019182e-02 5.70211234e-03
4.76574861e-02 1.47372186e-01 1.87091842e-01 -9.41016078e-01
-6.90726161e-01 -7.42999911e-01 -2.28093136e-02 -1.75881910e+00
7.04223216e-02 -5.56150854e-01 5.00550032e-01 -1.68843055e+00
1.16739161e-01 -8.58491719e-01 -5.08327484e-01 1.03604627e+00
-1.14330232e-01 2.36973315e-01 2.09316090e-01 4.07719553e-01
-8.63793135e-01 1.62957683e-01 1.72987461e+00 -2.29219809e-01
-7.64257371e-01 3.87389809e-01 -6.73789442e-01 8.10314596e-01
9.74296868e-01 -5.12792230e-01 -3.75663579e-01 -5.59835255e-01
4.44675893e-01 3.27021293e-02 4.20183420e-01 -8.82171631e-01
3.99988115e-01 -5.95851898e-01 5.06343663e-01 -6.51104152e-01
3.32713187e-01 -3.03737104e-01 -2.10015308e-02 1.13074370e-01
-7.52331197e-01 -4.83277924e-02 2.20422000e-01 2.52269179e-01
-3.53292227e-01 -3.74384165e-01 7.16634214e-01 -5.12365580e-01
-1.31537080e+00 2.54870802e-01 -6.43362463e-01 -1.84504762e-01
6.30147934e-01 -4.49554563e-01 -2.24475190e-02 -1.50856346e-01
-1.09588909e+00 1.78367510e-01 -5.36426902e-03 4.64401305e-01
9.42406654e-01 -1.12554014e+00 -4.02537346e-01 3.67015600e-01
-4.01028804e-02 1.47184998e-01 1.97878361e-01 9.39159095e-01
-2.83208519e-01 6.19491577e-01 -3.40338387e-02 -5.69687963e-01
-1.33029532e+00 4.29748029e-01 4.79404539e-01 -2.71268576e-01
-4.12548631e-01 1.52653551e+00 7.79703200e-01 -4.62829083e-01
2.36896396e-01 -9.57623363e-01 -5.20033658e-01 -2.32118487e-01
6.98068917e-01 1.74209341e-01 -1.49110258e-01 -4.63822544e-01
-6.41135097e-01 7.78988779e-01 -1.84170008e-01 -4.16982472e-01
1.13500249e+00 -3.73129934e-01 -1.52585655e-01 2.22913519e-01
8.11203659e-01 -1.05020106e-01 -1.40188539e+00 -3.04520309e-01
7.02994019e-02 -3.30198318e-01 1.30381614e-01 -7.34295785e-01
-9.87309873e-01 9.21799481e-01 3.17330360e-01 1.06750220e-01
1.36032701e+00 6.06020629e-01 6.17331684e-01 4.65166956e-01
3.02982122e-01 -1.15572977e+00 1.65900752e-01 8.95991385e-01
1.00665677e+00 -9.21409428e-01 -4.46053237e-01 -4.68498468e-01
-8.82842660e-01 9.90467668e-01 7.73356080e-01 -1.29208580e-01
5.46646833e-01 3.87389451e-01 -4.15148549e-02 -8.35632067e-03
-1.04336023e+00 -5.94074726e-01 6.33314788e-01 3.86037648e-01
5.07134080e-01 -7.36149773e-03 4.00338098e-02 5.38221836e-01
1.04695126e-01 2.72559915e-02 -3.38433355e-01 7.45947719e-01
-7.81928062e-01 -1.35107601e+00 -3.62960517e-01 3.46345663e-01
-3.59050006e-01 -4.48314697e-01 -2.91437835e-01 2.26009369e-01
6.41234756e-01 9.81623054e-01 2.87875384e-01 -4.68595237e-01
1.00701153e-01 -2.22139046e-01 5.74802399e-01 -6.80360377e-01
-6.87555015e-01 9.18311238e-01 -8.98773223e-02 -7.87438691e-01
-5.86923122e-01 -6.39686048e-01 -1.46667624e+00 1.41733706e-01
-2.33927637e-01 2.71288063e-02 2.63343185e-01 1.17993784e+00
2.18363479e-01 5.70749342e-01 3.59196514e-01 -8.84174347e-01
-1.82856381e-01 -1.03534508e+00 -4.65173870e-01 -6.92765191e-02
3.68535370e-01 -3.36543888e-01 4.37329188e-02 1.45864770e-01] | [9.61306095123291, 0.5690454840660095] |
c5a75a3b-06f0-4f4c-989b-28c621a65fe5 | the-devil-is-in-the-task-exploiting-1 | 2112.14023 | null | https://arxiv.org/abs/2112.14023v1 | https://arxiv.org/pdf/2112.14023v1.pdf | The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection | Low-cost monocular 3D object detection plays a fundamental role in autonomous driving, whereas its accuracy is still far from satisfactory. In this paper, we dig into the 3D object detection task and reformulate it as the sub-tasks of object localization and appearance perception, which benefits to a deep excavation of reciprocal information underlying the entire task. We introduce a Dynamic Feature Reflecting Network, named DFR-Net, which contains two novel standalone modules: (i) the Appearance-Localization Feature Reflecting module (ALFR) that first separates taskspecific features and then self-mutually reflects the reciprocal features; (ii) the Dynamic Intra-Trading module (DIT) that adaptively realigns the training processes of various sub-tasks via a self-learning manner. Extensive experiments on the challenging KITTI dataset demonstrate the effectiveness and generalization of DFR-Net. We rank 1st among all the monocular 3D object detectors in the KITTI test set (till March 16th, 2021). The proposed method is also easy to be plug-and-play in many cutting-edge 3D detection frameworks at negligible cost to boost performance. The code will be made publicly available. | ['Errui Ding', 'xiangyang xue', 'Jianfeng Feng', 'Li Zhang', 'Xiao Tan', 'Xianhui Cheng', 'Liang Du', 'Xiaoqing Ye', 'Zhikang Zou'] | 2021-12-28 | the-devil-is-in-the-task-exploiting | http://openaccess.thecvf.com//content/ICCV2021/html/Zou_The_Devil_Is_in_the_Task_Exploiting_Reciprocal_Appearance-Localization_Features_ICCV_2021_paper.html | http://openaccess.thecvf.com//content/ICCV2021/papers/Zou_The_Devil_Is_in_the_Task_Exploiting_Reciprocal_Appearance-Localization_Features_ICCV_2021_paper.pdf | iccv-2021-1 | ['self-learning'] | ['natural-language-processing'] | [-1.26176015e-01 -1.95982277e-01 -4.97112907e-02 -3.17401141e-01
-4.05501902e-01 -5.04429221e-01 6.56475186e-01 -5.41242301e-01
-5.25553048e-01 2.32334405e-01 -4.70039159e-01 -5.02290130e-01
-2.87265691e-04 -3.24995548e-01 -8.57026458e-01 -6.72977507e-01
-7.90850446e-02 3.41016650e-01 7.37957120e-01 -2.78838933e-01
2.17840850e-01 7.49673426e-01 -1.94730997e+00 -5.53679056e-02
7.01387227e-01 1.53530848e+00 5.86460590e-01 5.76039433e-01
2.09121272e-01 6.37894869e-01 -3.10907900e-01 -1.84207156e-01
7.03201592e-01 3.30373608e-02 -3.13993037e-01 1.48330316e-01
4.64574784e-01 -3.51044297e-01 -4.21296626e-01 9.26623702e-01
5.67742586e-01 -4.94656228e-02 6.47368133e-01 -1.53609741e+00
-4.57908124e-01 2.05439273e-02 -7.61487365e-01 4.86333758e-01
7.08897859e-02 4.82437760e-01 8.93815100e-01 -1.26497972e+00
3.76635969e-01 1.20424616e+00 6.15162432e-01 2.90401131e-01
-7.75253475e-01 -8.48106027e-01 3.99016351e-01 4.06247318e-01
-1.25718832e+00 -4.29639637e-01 8.76045942e-01 -5.76767325e-01
9.90678191e-01 -3.84383723e-02 8.05278420e-01 9.18093681e-01
2.52548873e-01 1.18597257e+00 1.06166899e+00 -1.35333776e-01
2.74681468e-02 2.19048873e-01 1.84813336e-01 7.76925087e-01
4.08419281e-01 6.59663022e-01 -5.57843387e-01 3.43046427e-01
6.37387335e-01 -8.47004801e-02 7.16106147e-02 -9.61731613e-01
-8.58615875e-01 6.50310457e-01 6.95036829e-01 1.11916922e-02
-1.30088866e-01 1.24274835e-01 1.29740953e-01 4.65532213e-01
5.31580031e-01 1.10164344e-01 -3.64717603e-01 2.03809813e-01
-4.41466093e-01 4.09612417e-01 2.92467713e-01 1.14581299e+00
9.32394981e-01 1.59997165e-01 3.80396284e-02 8.67553949e-01
3.20233792e-01 5.22424817e-01 3.83622319e-01 -7.03103364e-01
4.34910476e-01 8.02089453e-01 2.82236844e-01 -7.54533887e-01
-6.30768061e-01 -8.80743146e-01 -4.47706670e-01 7.23170877e-01
2.37021148e-01 -2.11578459e-02 -8.51699948e-01 1.45853293e+00
6.95339143e-01 7.43203685e-02 -2.48658985e-01 1.24024069e+00
1.11318171e+00 2.49773487e-01 -2.36130774e-01 3.50247204e-01
1.32046080e+00 -1.09899068e+00 -1.83287382e-01 -7.74480283e-01
3.97135466e-01 -6.06734574e-01 6.99379325e-01 9.00558680e-02
-8.38884294e-01 -9.93148983e-01 -1.43394601e+00 -2.02898681e-01
-5.61107457e-01 4.17343646e-01 6.36344194e-01 5.96059203e-01
-1.05306649e+00 4.05896641e-02 -5.40593922e-01 -1.79564953e-01
5.90907097e-01 4.63889718e-01 -4.10443127e-01 -3.30518074e-02
-9.25329983e-01 1.13731146e+00 4.02538389e-01 2.12750420e-01
-1.07316113e+00 -4.95992124e-01 -8.69538784e-01 -2.34018266e-01
7.61518180e-01 -7.97491431e-01 1.28695452e+00 -7.52337515e-01
-1.52918744e+00 1.21236587e+00 7.29100704e-02 -5.31015337e-01
7.42107451e-01 -3.51673752e-01 -2.69352347e-01 -1.50716871e-01
1.89760700e-01 8.32522571e-01 1.22141242e+00 -1.47918284e+00
-1.26700473e+00 -6.29739821e-01 1.53391629e-01 5.18079162e-01
7.85665587e-02 -2.50598073e-01 -5.32052934e-01 -1.95581824e-01
2.97850668e-01 -9.77690756e-01 8.40449855e-02 2.37478897e-01
-1.88374892e-01 -5.89280069e-01 9.13762867e-01 -7.32685998e-02
5.35248399e-01 -2.36784768e+00 -1.52173005e-02 -2.12003008e-01
4.13122416e-01 2.90534943e-01 -1.27879903e-01 7.23849759e-02
-9.51972082e-02 -5.64852715e-01 -9.34148729e-02 -3.69092703e-01
5.67385778e-02 -1.17474243e-01 -1.62837654e-01 8.25559497e-01
4.64274615e-01 1.25983870e+00 -9.62758422e-01 -1.91155329e-01
3.78839642e-01 1.50291398e-01 -3.13791126e-01 1.40233174e-01
-7.50247389e-02 2.07293659e-01 -5.72165608e-01 9.82712269e-01
8.87458384e-01 -1.00304611e-01 -5.02512872e-01 -1.08199745e-01
-4.45517331e-01 1.27814427e-01 -1.16449130e+00 1.52162516e+00
-1.71887279e-01 5.85551023e-01 2.27071777e-01 -9.92116451e-01
1.19515562e+00 -2.57107884e-01 2.43588030e-01 -9.66287613e-01
3.32429647e-01 2.98298061e-01 2.10071489e-01 -3.98738980e-01
6.21901155e-01 5.57157360e-02 -2.26942033e-01 1.34982765e-01
1.26011297e-01 -3.01557720e-01 -2.24212296e-02 6.71350211e-02
1.05221033e+00 4.24500495e-01 3.08998078e-01 -2.17470884e-01
4.75704014e-01 8.00965577e-02 3.17079633e-01 9.84826446e-01
-6.18564248e-01 4.07963276e-01 2.10079685e-01 -4.73738551e-01
-8.76873732e-01 -1.17659426e+00 -2.01220378e-01 1.07774317e+00
7.46440947e-01 1.04405455e-01 -2.04657555e-01 -8.72783005e-01
5.93157589e-01 4.10334766e-01 -8.47647905e-01 -2.37411752e-01
-2.73174644e-01 -4.21150029e-01 8.64636377e-02 5.91222882e-01
6.53925121e-01 -1.05953419e+00 -9.53746855e-01 -1.18043095e-01
1.90725178e-01 -1.15356874e+00 -3.25916678e-01 6.65247560e-01
-5.55857539e-01 -9.77979302e-01 -5.78493714e-01 -8.74004006e-01
4.18739080e-01 1.11723387e+00 7.88600862e-01 -2.84899861e-01
-4.27064240e-01 4.12991345e-01 -3.52441043e-01 -8.04334223e-01
-3.24815512e-02 1.52417198e-01 1.73519939e-01 2.35118061e-01
4.41561103e-01 -3.95808071e-01 -7.09309816e-01 6.33140087e-01
-3.58131379e-01 3.88522306e-03 1.02637804e+00 7.25818038e-01
4.24645007e-01 -2.28728145e-01 4.76891190e-01 -5.98446012e-01
1.44249976e-01 -2.70627975e-01 -9.86979008e-01 -2.23329395e-01
-4.31936264e-01 -2.91636348e-01 2.33148530e-01 -2.99622536e-01
-9.31874812e-01 5.10964274e-01 9.35834274e-02 -5.86648822e-01
-1.38240457e-01 -9.68479291e-02 -1.31216928e-01 -4.79977489e-01
6.32744074e-01 5.25945604e-01 6.38531074e-02 -3.80496889e-01
4.71879393e-01 7.33724236e-01 7.72194862e-01 -1.20222241e-01
1.45856369e+00 6.49831533e-01 -1.05235234e-01 -8.20706785e-01
-1.09112298e+00 -7.84039080e-01 -6.78711534e-01 -4.98714834e-01
6.12264574e-01 -1.42542255e+00 -8.29035819e-01 7.90202916e-01
-9.43880439e-01 -3.69225979e-01 -2.40780622e-01 2.56853163e-01
-5.30985415e-01 1.36884093e-01 -1.28140569e-01 -9.28208053e-01
3.19613591e-02 -8.90174270e-01 1.22148085e+00 3.73747081e-01
4.58898097e-01 -3.46891850e-01 -1.64012417e-01 3.22156459e-01
2.44115680e-01 -1.33942515e-01 4.83851492e-01 -3.41649979e-01
-8.67957175e-01 -4.16103780e-01 -7.11310446e-01 3.94380093e-01
1.27127636e-02 -4.32548553e-01 -1.31000328e+00 -3.60174775e-01
1.26173310e-02 -5.06544530e-01 1.33027017e+00 3.16597283e-01
9.88924026e-01 4.09231633e-01 -3.90197963e-01 6.75098419e-01
1.17272019e+00 3.19991499e-01 3.34426880e-01 5.30795336e-01
7.09820151e-01 5.93062758e-01 7.46895432e-01 3.37041795e-01
6.17238820e-01 7.36309230e-01 7.96980619e-01 -4.05407846e-01
-3.68311465e-01 -2.76419610e-01 3.46832156e-01 3.90287846e-01
5.71591556e-02 -1.73524488e-02 -5.39849401e-01 5.00138223e-01
-1.83190393e+00 -8.60256732e-01 -6.16407506e-02 1.89083707e+00
2.48868048e-01 6.64752185e-01 4.25063908e-01 5.99166006e-02
6.21891737e-01 2.77762562e-01 -9.38538373e-01 -1.10585727e-02
-1.81643933e-01 -3.39359730e-01 6.23534262e-01 2.39688903e-01
-1.42176688e+00 9.93955493e-01 5.74604321e+00 8.55930209e-01
-9.70234513e-01 1.35474503e-01 4.61070240e-01 7.89090618e-02
2.32224703e-01 -1.01189904e-01 -1.24474621e+00 2.37184256e-01
1.91339046e-01 1.39048155e-02 2.11464182e-01 1.19674385e+00
1.68626662e-02 -1.54857531e-01 -1.01476705e+00 1.02927601e+00
2.08057866e-01 -9.61167991e-01 -1.40699804e-01 2.40662992e-02
6.45627856e-01 5.12325883e-01 2.02716976e-01 4.84692305e-01
2.66386837e-01 -6.68813348e-01 1.32373607e+00 1.67367250e-01
6.73503816e-01 -5.75607479e-01 5.92598379e-01 4.41327006e-01
-1.48973918e+00 -6.50488436e-01 -6.69122994e-01 -2.47992113e-01
-5.93699552e-02 5.93873382e-01 -6.74056113e-01 6.00008011e-01
8.20536554e-01 9.39104617e-01 -7.30524063e-01 1.41607320e+00
-2.61344790e-01 5.60872331e-02 -2.25525424e-01 -2.24628747e-01
4.14275557e-01 -2.84659788e-02 7.98273861e-01 9.49072003e-01
1.12614967e-01 -1.68401062e-01 1.82870507e-01 7.94949710e-01
1.03129791e-02 -2.87203401e-01 -7.83236265e-01 4.26410407e-01
3.50103080e-01 1.48244286e+00 -6.71205282e-01 -1.41336828e-01
-6.35235786e-01 7.53791690e-01 5.25523245e-01 1.84968650e-01
-8.74173999e-01 -3.83224517e-01 6.88957751e-01 2.78571635e-01
8.80721450e-01 -2.78844476e-01 -1.91650659e-01 -8.77839386e-01
1.69155151e-01 -5.67689776e-01 9.20189843e-02 -9.18533921e-01
-1.43818998e+00 5.84342003e-01 -1.33599296e-01 -1.55406070e+00
2.33210653e-01 -1.05707252e+00 -4.05336112e-01 5.75520754e-01
-1.99958622e+00 -1.11136460e+00 -6.85931087e-01 4.48753923e-01
6.98074520e-01 -2.49717981e-01 1.54990196e-01 3.07870299e-01
-6.19133055e-01 6.55546844e-01 -5.05149597e-04 -1.06071122e-01
6.24344170e-01 -1.07286608e+00 6.93501472e-01 7.28511333e-01
1.26277938e-01 -2.79109497e-02 3.08186501e-01 -4.66839522e-01
-1.56368840e+00 -1.18057334e+00 6.59530699e-01 -6.08194053e-01
7.01202095e-01 -7.83291280e-01 -5.30410528e-01 5.14694631e-01
-2.01184690e-01 1.63993955e-01 -5.06747216e-02 -1.03976488e-01
-4.07483041e-01 -5.01052678e-01 -7.19323099e-01 4.15800840e-01
1.59117365e+00 -3.27149779e-01 -5.95910311e-01 2.91478515e-01
7.24658251e-01 -6.52686357e-01 -1.72732815e-01 5.29944241e-01
6.06202781e-01 -1.15074229e+00 1.20795846e+00 -1.84899226e-01
1.25593334e-01 -6.27635896e-01 -1.85737729e-01 -9.75010395e-01
-5.98570883e-01 -4.61792469e-01 -1.72858015e-01 7.92672455e-01
3.74763966e-01 -9.07648563e-01 8.15265119e-01 -1.65167719e-01
-5.62354147e-01 -6.81837797e-01 -1.23842454e+00 -1.12685394e+00
-3.88874173e-01 -5.94238997e-01 3.81484807e-01 3.92222553e-01
-4.84518915e-01 5.70824385e-01 -2.69725144e-01 2.54715621e-01
7.39033639e-01 3.74967575e-01 1.04743588e+00 -1.33236551e+00
-3.89058858e-01 -6.45812869e-01 -6.25659406e-01 -1.75110626e+00
-1.08303577e-01 -9.89211857e-01 4.41293240e-01 -1.15769327e+00
2.49635145e-01 -5.31298935e-01 -3.84890556e-01 3.59032899e-01
-2.08279520e-01 4.41715926e-01 1.19054720e-01 2.64729351e-01
-9.13686752e-01 8.77214730e-01 1.39309001e+00 -2.63103783e-01
-1.31717414e-01 2.98815280e-01 -7.54507840e-01 6.29350007e-01
3.51840883e-01 -4.05192077e-01 -4.19746995e-01 -3.08711439e-01
-2.10923195e-01 -2.54911184e-01 7.84381926e-01 -1.12901402e+00
2.39412576e-01 1.23676397e-01 5.98643363e-01 -1.12698007e+00
4.03141201e-01 -6.70234740e-01 -3.13365906e-01 5.32101095e-01
1.79350317e-01 -6.26348481e-02 3.22980434e-01 6.53064013e-01
4.83765900e-02 -3.92683893e-02 8.22152674e-01 -1.04804151e-01
-1.17014396e+00 4.82364714e-01 -2.23234579e-01 2.31634397e-02
1.13626099e+00 -6.23993397e-01 -3.17654431e-01 -5.63663207e-02
-3.50174904e-01 3.95304769e-01 2.80943364e-01 8.29797804e-01
6.25828624e-01 -1.26793015e+00 -6.91786289e-01 4.30505872e-01
4.75747526e-01 1.20523795e-01 2.94603020e-01 7.45015621e-01
-1.37193128e-01 4.71879393e-01 -2.09715113e-01 -1.03242791e+00
-8.70881259e-01 5.15039921e-01 4.69227076e-01 1.84888691e-02
-7.26315737e-01 1.02704799e+00 7.10785925e-01 -4.57803160e-01
3.30943853e-01 -8.73473659e-02 -2.25133687e-01 1.81166232e-02
3.31545740e-01 2.49489933e-01 1.38399690e-01 -5.42521358e-01
-6.18377805e-01 7.59055734e-01 -9.31216180e-02 2.51024455e-01
1.34265995e+00 -3.32845241e-01 3.20486903e-01 4.47975546e-01
1.03798831e+00 -5.65300465e-01 -1.89588535e+00 -3.36424202e-01
-2.61171043e-01 -4.74088818e-01 2.04123423e-01 -7.80967593e-01
-9.00604248e-01 7.02787101e-01 9.68986452e-01 1.45132869e-01
9.56481755e-01 2.57772088e-01 4.54249471e-01 4.94550556e-01
5.37387013e-01 -8.69017899e-01 3.87476534e-01 5.89841604e-01
8.71064126e-01 -1.41475189e+00 -1.48756076e-02 -4.05772507e-01
-4.11374032e-01 7.45974720e-01 8.68461728e-01 -4.20763880e-01
6.35508001e-01 1.80167183e-01 7.83945173e-02 -2.83775091e-01
-6.57938242e-01 -6.03152335e-01 5.08996427e-01 7.81559050e-01
-2.91005880e-01 5.96696474e-02 8.52790549e-02 5.61583877e-01
-4.68751639e-02 -2.93095052e-01 4.75845076e-02 8.16463053e-01
-7.69645095e-01 -6.92467034e-01 -1.18248783e-01 3.74858141e-01
2.94279277e-01 1.71868503e-01 -4.59546596e-01 1.08371329e+00
4.86725479e-01 8.30126524e-01 1.80776995e-02 -6.26973689e-01
5.75675845e-01 -1.51542589e-01 4.81697232e-01 -4.04429018e-01
-2.90537089e-01 -8.87878835e-02 -5.75598739e-02 -6.39930308e-01
-2.89372414e-01 -6.99894190e-01 -7.80343354e-01 4.10792492e-02
-5.56222260e-01 -3.14939022e-01 6.87924266e-01 9.13564086e-01
3.62569362e-01 5.14867365e-01 9.32129681e-01 -1.37030578e+00
-7.68177152e-01 -7.64921665e-01 -5.97671092e-01 -2.39496920e-02
4.46347654e-01 -1.25632989e+00 -4.38242048e-01 -3.20366561e-01] | [7.865596771240234, -2.386770009994507] |
a9ed7f35-c60e-4981-b39a-5a0496d356fa | parameterization-of-state-duration-in-hidden | 2211.09478 | null | https://arxiv.org/abs/2211.09478v1 | https://arxiv.org/pdf/2211.09478v1.pdf | Parameterization of state duration in Hidden semi-Markov Models: an application in electrocardiography | This work aims at providing a new model for time series classification based on learning from just one example. We assume that time series can be well characterized as a parametric random process, a sort of Hidden semi-Markov Model representing a sequence of regression models with variable duration. We introduce a parametric stochastic model for time series pattern recognition and provide a maximum-likelihood estimation of its parameters. Particularly, we are interested in examining two different representations for state duration: i) a discrete density distribution requiring an estimate for each possible duration; and ii) a parametric family of continuous density functions, here the Gamma distribution, with just two parameters to estimate. An application on heartbeat classification reveals the main strengths and weaknesses of each alternative. | ['Jesús María Rodríguez Presedo', 'Paulo Félix Lamas', 'Adrián Pérez Herrero'] | 2022-11-17 | null | null | null | null | ['heartbeat-classification'] | ['medical'] | [ 1.76378280e-01 -1.05633342e-03 -5.93857348e-01 -4.20600414e-01
-5.72630227e-01 -4.75091040e-01 6.33476436e-01 -7.07552060e-02
-8.87533184e-03 6.55665517e-01 -2.32104465e-01 -5.26662111e-01
-3.63647789e-01 -3.88781428e-01 -2.80970693e-01 -9.78952289e-01
-6.80531919e-01 8.92278433e-01 1.48030937e-01 1.21440940e-01
6.14977293e-02 5.37294626e-01 -1.37142265e+00 -1.96242943e-01
3.61272961e-01 1.04147136e+00 -2.75855750e-01 9.51048732e-01
-1.13519415e-01 7.42647409e-01 -1.06650054e+00 1.31697908e-01
-3.07312943e-02 -4.20215547e-01 -5.62319875e-01 2.44723856e-01
-5.51451921e-01 -1.39161572e-01 -6.00995086e-02 5.53220868e-01
4.55505997e-02 -3.58968116e-02 1.19510806e+00 -1.65865850e+00
-2.15514332e-01 4.67247218e-01 -2.48112991e-01 4.94433403e-01
4.33517992e-01 8.16028342e-02 5.09671092e-01 -1.75411865e-01
3.08935225e-01 1.08834243e+00 8.53711247e-01 3.40415806e-01
-1.67103159e+00 -2.39546359e-01 -8.83917809e-02 2.31983870e-01
-1.58921194e+00 -1.22930408e-01 7.59632945e-01 -5.85477948e-01
9.63634253e-01 2.20396653e-01 8.35101247e-01 1.28900719e+00
6.00813150e-01 7.05119193e-01 1.24317455e+00 -4.77132380e-01
6.47548974e-01 -7.86333606e-02 2.99451470e-01 1.98483974e-01
-9.06212330e-02 1.95049703e-01 -2.04343259e-01 -8.30278933e-01
8.18452775e-01 2.49647245e-01 -8.67535397e-02 -3.39230925e-01
-1.13955200e+00 7.38582850e-01 -5.91749370e-01 4.67849791e-01
-4.79955047e-01 7.39664137e-02 3.14127117e-01 6.25554085e-01
2.83115774e-01 1.80809274e-02 -7.16826975e-01 -3.83265913e-01
-1.04810703e+00 4.47290614e-02 1.30909538e+00 8.16017866e-01
7.75422335e-01 4.72025067e-01 -2.47929525e-02 3.70048404e-01
2.15640992e-01 6.87458456e-01 7.08500564e-01 -6.99962199e-01
-1.66276589e-01 -1.57081351e-01 4.24572349e-01 -2.90901393e-01
-5.31879187e-01 -2.20264658e-01 -9.51830149e-01 -5.13041764e-02
7.86042213e-01 -1.62252724e-01 -8.86902750e-01 1.74287021e+00
-2.66751442e-02 6.66035771e-01 -3.72517854e-02 2.69121587e-01
4.31647226e-02 9.62550819e-01 1.84420884e-01 -1.01645601e+00
1.07071602e+00 -2.83831745e-01 -1.07514524e+00 3.89010996e-01
2.73309350e-01 -4.95059758e-01 5.73760450e-01 6.36057556e-01
-8.96030128e-01 -5.30730903e-01 -8.75370502e-01 5.58029056e-01
-1.75690264e-01 -1.63147107e-01 5.17853618e-01 9.23248410e-01
-9.87259567e-01 8.48162532e-01 -1.33971429e+00 -3.36054683e-01
-3.63938957e-01 3.49512637e-01 1.13400899e-01 6.18180871e-01
-1.12220812e+00 8.63377690e-01 2.99885809e-01 -5.54823093e-02
-1.07781756e+00 -5.37066281e-01 -4.93662685e-01 4.22396511e-02
-1.15699679e-01 -5.32300055e-01 1.38562846e+00 -7.79531240e-01
-1.71144748e+00 6.13550961e-01 -3.79206628e-01 -6.43363774e-01
4.30858284e-01 2.00960293e-01 -8.35792243e-01 2.02332333e-01
-2.80558288e-01 -1.26732200e-01 1.54988837e+00 -9.72307742e-01
-8.96878764e-02 -1.14826016e-01 -4.80823159e-01 -5.17849386e-01
1.28869310e-01 5.28294928e-02 2.69704819e-01 -7.41646767e-01
2.89871067e-01 -1.10533285e+00 -2.72395253e-01 -3.37216914e-01
-3.71070504e-01 -4.67949748e-01 6.52250290e-01 -7.57935762e-01
1.59487391e+00 -2.07038236e+00 -5.86562417e-03 4.34268743e-01
-7.02326745e-02 -2.08315298e-01 1.80146664e-01 8.80388498e-01
-5.52887261e-01 2.43846893e-01 -3.71913821e-01 -2.86153674e-01
-3.29388753e-02 3.59021097e-01 -6.53298378e-01 8.24338794e-01
1.84654921e-01 3.60948175e-01 -8.24266195e-01 -3.30544531e-01
2.13071004e-01 4.94241029e-01 3.02926093e-01 2.04056397e-01
-5.56539148e-02 5.18105328e-01 -4.71257567e-01 4.78555351e-01
5.22911906e-01 -2.18484908e-01 2.64808774e-01 1.11930288e-01
-2.20406204e-01 -6.82531595e-02 -1.22933364e+00 1.09345818e+00
-1.83067396e-01 4.47612762e-01 -4.59027082e-01 -1.20908427e+00
1.25477791e+00 8.49287868e-01 9.86724734e-01 1.08196072e-01
2.75346279e-01 1.65090114e-01 8.05273429e-02 -4.00360554e-01
-6.52720630e-02 -5.63535571e-01 -2.39405468e-01 7.83586442e-01
2.73637414e-01 -2.56456107e-01 2.62884870e-02 -3.64936888e-01
1.25810075e+00 8.71143639e-02 6.84059560e-01 -2.12027967e-01
2.28811845e-01 -3.93330991e-01 4.70365196e-01 7.76198268e-01
-4.40904975e-01 4.81830239e-01 7.99169660e-01 -6.08156919e-01
-9.87471879e-01 -1.31852007e+00 -3.48760277e-01 4.91187721e-01
-4.60334152e-01 -4.00873512e-01 -2.87030637e-01 -8.20127204e-02
-1.47509634e-01 7.37255752e-01 -6.44325018e-01 -2.38822773e-01
-4.96114194e-01 -9.49000239e-01 4.88012165e-01 4.43753839e-01
-9.84305441e-02 -8.91351044e-01 -7.23251879e-01 2.36010730e-01
-1.98537529e-01 -8.26468706e-01 -2.30606422e-01 7.41692126e-01
-1.20830476e+00 -7.99709022e-01 -7.24693835e-01 -4.00719106e-01
1.14039473e-01 -2.53764957e-01 1.15847886e+00 -3.10710967e-01
-2.26850480e-01 7.24783361e-01 -1.66784897e-01 -6.97832704e-01
-8.33327711e-01 -2.57553607e-01 2.54064977e-01 2.95476407e-01
3.57297540e-01 -8.14355731e-01 -3.76280099e-01 3.39158654e-01
-8.19984734e-01 -5.47451019e-01 3.54061484e-01 5.49596071e-01
5.63831985e-01 3.10077280e-01 6.35282278e-01 -4.42616463e-01
4.39730257e-01 -7.99218893e-01 -3.66540492e-01 3.06229740e-01
-5.61520875e-01 7.65026063e-02 6.16980791e-01 -9.09183383e-01
-7.63564348e-01 2.55645573e-01 7.24527910e-02 -8.15554976e-01
-4.81250554e-01 4.43168938e-01 1.32984221e-01 4.12977576e-01
4.51949596e-01 7.22642601e-01 2.72810996e-01 -5.14188766e-01
1.65028855e-01 5.48493147e-01 4.47985500e-01 -5.53675234e-01
6.36009037e-01 6.09184146e-01 2.89375663e-01 -1.20458186e+00
-3.23213518e-01 -6.47537470e-01 -8.86282921e-01 -3.09329808e-01
7.12036371e-01 -6.69976354e-01 -7.12671041e-01 7.12649822e-01
-8.43923271e-01 -3.40332568e-01 -5.71149170e-01 6.82309031e-01
-1.37371087e+00 3.68658692e-01 -8.76192510e-01 -1.39580560e+00
6.48052469e-02 -5.86064339e-01 9.35991943e-01 -1.67325940e-02
-6.56341314e-01 -1.43675029e+00 4.68353599e-01 -4.89293844e-01
2.21098095e-01 4.12018180e-01 1.02216053e+00 -9.27704513e-01
-1.30101040e-01 -4.62606579e-01 5.35743594e-01 2.06523865e-01
1.53250560e-01 4.92353559e-01 -8.30745816e-01 -3.96283507e-01
6.14164889e-01 1.22808389e-01 4.30712879e-01 7.66952634e-01
1.08155966e+00 -1.76528737e-01 -4.33845490e-01 3.74540210e-01
1.30431807e+00 6.29628181e-01 6.16656423e-01 1.63655162e-01
5.47731072e-02 3.93398523e-01 5.31811476e-01 8.95444155e-01
1.15743198e-01 3.76552701e-01 1.20645985e-01 3.03366005e-01
5.31546235e-01 -1.07677609e-01 3.75481486e-01 7.00329304e-01
-2.07245201e-01 -1.90245599e-01 -1.05040967e+00 5.45820892e-01
-1.77899039e+00 -1.37757599e+00 -2.96911448e-01 2.62703800e+00
7.88582385e-01 2.61272311e-01 7.41623163e-01 6.18147135e-01
8.55739236e-01 5.94512150e-02 -5.13696790e-01 -4.53619123e-01
-5.02936803e-02 4.39514130e-01 2.20962510e-01 2.42310315e-01
-1.22395241e+00 2.42170393e-01 8.54273510e+00 6.46669388e-01
-1.01853228e+00 -2.82909751e-01 3.81347597e-01 2.73688078e-01
-4.05493155e-02 2.36158907e-01 -5.67339718e-01 7.63276041e-01
1.74781621e+00 -5.11948705e-01 1.40913082e-02 4.51587528e-01
4.41197038e-01 2.25300286e-02 -1.13569975e+00 1.05726552e+00
-3.35814834e-01 -8.66254807e-01 -2.89586782e-02 8.32289085e-02
4.87778872e-01 -2.89212912e-01 7.76055455e-03 3.52912635e-01
1.95375755e-01 -8.20137024e-01 7.54569173e-01 1.02184141e+00
5.76810956e-01 -6.10674739e-01 4.39678133e-01 6.47211611e-01
-1.22523367e+00 -2.73664951e-01 -1.28581822e-01 -1.32865325e-01
4.06148672e-01 6.76545978e-01 -6.04551077e-01 3.76702875e-01
3.80991518e-01 6.42840087e-01 -8.52283239e-02 1.34164810e+00
1.33073740e-02 1.09129357e+00 -5.60871840e-01 8.04131851e-02
-1.91109836e-01 -2.25438759e-01 8.20115328e-01 1.17274308e+00
6.68082654e-01 -1.13080978e-01 4.26025778e-01 6.82386279e-01
9.81854200e-01 -3.12857002e-01 -4.86899853e-01 -1.97428674e-01
5.85054696e-01 9.31784928e-01 -1.01574779e+00 -3.89450222e-01
-4.07163203e-01 5.69197953e-01 -2.60119647e-01 5.81563532e-01
-9.74633098e-01 -1.51741564e-01 2.19884738e-01 1.71675548e-01
4.23029512e-01 -4.51287746e-01 7.71643445e-02 -1.12981176e+00
-3.88811260e-01 -4.98845786e-01 6.22631371e-01 -7.25769758e-01
-1.47727370e+00 5.48450649e-01 6.13421738e-01 -1.75722480e+00
-8.64587069e-01 -4.25499648e-01 -8.29735339e-01 1.00036836e+00
-1.12185252e+00 -9.77356613e-01 3.53446841e-01 6.66037798e-01
3.71108532e-01 1.99272968e-02 1.11080635e+00 -7.66551942e-02
-4.66321677e-01 3.87109481e-02 1.41182840e-01 -2.59320438e-01
4.95138973e-01 -1.54727125e+00 2.26273850e-01 3.16171259e-01
-9.44424942e-02 6.47940814e-01 1.31960392e+00 -5.27884364e-01
-1.32272482e+00 -8.46003413e-01 8.12462389e-01 -4.68238235e-01
9.09497142e-01 9.23978761e-02 -1.12324011e+00 9.36496496e-01
-1.02951668e-01 -3.50784779e-01 1.00823462e+00 1.09952241e-01
-9.89078451e-03 3.15514565e-01 -9.24288094e-01 8.26677456e-02
3.03899139e-01 -5.64298511e-01 -8.39115441e-01 2.95671999e-01
3.11906710e-02 1.84665307e-01 -1.10716331e+00 2.85555512e-01
6.08090699e-01 -9.08315659e-01 7.73502767e-01 -4.57913727e-01
-3.76387507e-01 -2.96913624e-01 -1.04147680e-02 -1.27292657e+00
-4.67365384e-01 -1.27513456e+00 -6.69223070e-01 1.00782824e+00
4.69789430e-02 -6.50645792e-01 5.08211851e-01 4.53764796e-01
1.61106035e-01 -6.21303022e-01 -1.17277825e+00 -1.44028342e+00
-2.80747544e-02 -6.42445147e-01 5.31526744e-01 8.95284414e-01
4.56488654e-02 1.81349859e-01 -4.65927243e-01 3.22804190e-02
6.83647394e-01 2.19628975e-01 5.73271275e-01 -1.44015574e+00
-4.79875445e-01 -2.28436917e-01 -5.28931916e-01 -1.05239892e+00
1.89435303e-01 -2.98673660e-01 1.12945199e-01 -9.28722501e-01
1.24870807e-01 -2.23908558e-01 -3.42522830e-01 1.50217056e-01
3.07570815e-01 -2.62739062e-01 -2.73732394e-01 5.67454219e-01
-2.64707714e-01 4.04193133e-01 6.56048179e-01 2.06282482e-01
-2.94538647e-01 8.30308914e-01 1.56726286e-01 7.68240750e-01
8.75063360e-01 -6.16113186e-01 -5.41016340e-01 5.13807952e-01
-2.62432154e-02 9.76711690e-01 4.58477229e-01 -1.04516077e+00
-3.53461355e-02 -2.79454231e-01 2.72074759e-01 -1.02672899e+00
5.80585480e-01 -7.23402679e-01 5.71938396e-01 6.67166531e-01
-8.66802558e-02 1.70988351e-01 2.42413189e-02 8.97916794e-01
-3.03211570e-01 -3.01878303e-01 6.68924093e-01 -6.92113563e-02
-5.62452972e-01 2.98702925e-01 -1.07204139e+00 -3.77792716e-01
1.00002408e+00 -4.09270763e-01 8.92332271e-02 -7.77518570e-01
-1.60258651e+00 -1.57871008e-01 1.15167648e-01 1.95266560e-01
3.56260389e-01 -1.19138718e+00 -4.32303488e-01 3.05604726e-01
-1.25886068e-01 -8.20384622e-01 2.56144106e-01 1.07477999e+00
-8.38877335e-02 4.14365470e-01 -2.65019059e-01 -9.44449663e-01
-9.16154981e-01 9.50741053e-01 5.10439038e-01 -3.66489351e-01
-4.60906237e-01 2.19092175e-01 -2.53942609e-01 -4.44518477e-02
-4.57439832e-02 -5.66834033e-01 -3.01321179e-01 3.01305920e-01
5.42286038e-01 5.63319504e-01 -2.83961773e-01 -5.80657840e-01
-3.15823585e-01 6.26101911e-01 3.77739638e-01 -3.76386523e-01
9.53792810e-01 -3.29221874e-01 -9.39601511e-02 1.53932619e+00
1.04195642e+00 -5.10571361e-01 -1.22466981e+00 -7.53146112e-02
3.64851743e-01 -2.01172009e-02 -4.03642058e-01 -4.28137511e-01
-3.49345684e-01 7.64486551e-01 6.40001833e-01 1.11946440e+00
1.17983484e+00 -2.05048230e-02 4.05234009e-01 3.62227075e-02
4.80564952e-01 -6.30344689e-01 -1.32741615e-01 4.40896749e-01
7.23885536e-01 -6.96177244e-01 -1.70683861e-01 -2.28485376e-01
-4.24674511e-01 1.54899645e+00 -1.50937259e-01 -3.09876472e-01
1.38409948e+00 3.74495149e-01 1.98150147e-02 8.52647722e-02
-1.18016243e+00 -2.12611765e-01 2.93827921e-01 9.72725332e-01
4.39708114e-01 2.74658114e-01 -1.89158976e-01 6.65824473e-01
-2.52871156e-01 1.27133027e-01 6.96456254e-01 1.05859542e+00
-3.42638910e-01 -9.19395685e-01 -4.49068546e-01 3.61806452e-01
-6.63422048e-01 4.17992175e-01 1.24852151e-01 7.35205770e-01
-2.74487853e-01 1.05526102e+00 2.39463061e-01 -1.58209637e-01
1.83320969e-01 5.82247496e-01 4.13890481e-01 -5.37206531e-01
-6.32254332e-02 5.31750560e-01 -2.07680777e-01 -2.69311279e-01
-4.47214544e-01 -1.09866571e+00 -1.01803195e+00 -7.62870312e-02
-2.49732554e-01 2.78304458e-01 6.71571612e-01 9.11236644e-01
-1.67541996e-01 3.08489710e-01 8.49648714e-01 -8.91418874e-01
-1.00242019e+00 -1.00778186e+00 -1.11753058e+00 1.01328716e-01
7.30590582e-01 -5.27393878e-01 -8.07819247e-01 4.25803304e-01] | [7.04304838180542, 3.738914966583252] |
4975ec95-105f-49b1-a93b-4a5073de9ec9 | annotating-inter-sentence-temporal-relations | null | null | https://aclanthology.org/L14-1129 | https://aclanthology.org/L14-1129.pdf | Annotating Inter-Sentence Temporal Relations in Clinical Notes | Owing in part to the surge of interest in temporal relation extraction, a number of datasets manually annotated with temporal relations between event-event pairs and event-time pairs have been produced recently. However, it is not uncommon to find missing annotations in these manually annotated datasets. Many researchers attributed this problem to {``}annotator fatigue{''}. While some of these missing relations can be recovered automatically, many of them cannot. Our goals in this paper are to (1) manually annotate certain types of missing links that cannot be automatically recovered in the i2b2 Clinical Temporal Relations Challenge Corpus, one of the recently released evaluation corpora for temporal relation extraction; and (2) empirically determine the usefulness of these additional annotations. We will make our annotations publicly available, in hopes of enabling a more accurate evaluation of temporal relation extraction systems. | ["Jennifer D{'}Souza", 'Vincent Ng'] | 2014-05-01 | null | null | null | lrec-2014-5 | ['temporal-relation-extraction', 'temporal-information-extraction'] | ['natural-language-processing', 'natural-language-processing'] | [ 3.94138336e-01 5.03896058e-01 -5.61765075e-01 -4.95242268e-01
-1.00321805e+00 -7.66730368e-01 5.79465091e-01 9.28692281e-01
-4.00035322e-01 1.11150670e+00 6.50258780e-01 -5.92895746e-01
-5.43316782e-01 -4.01100606e-01 -2.63242424e-01 -2.53909320e-01
-5.97690403e-01 6.71379149e-01 5.26828349e-01 -9.01008621e-02
-1.25783712e-01 3.89555514e-01 -9.64237750e-01 5.97265661e-01
4.72379893e-01 7.23330021e-01 -2.55305976e-01 4.50190336e-01
1.25710025e-01 1.34505796e+00 -3.27231616e-01 -3.72787267e-01
-1.76199064e-01 -6.80504203e-01 -1.56574440e+00 -1.77256167e-01
-3.99949282e-01 -1.29611522e-01 -3.82252812e-01 5.50144613e-01
2.58082688e-01 8.55817795e-02 4.24034297e-01 -1.18276799e+00
-3.54066901e-02 9.04406011e-01 -4.80645657e-01 8.63052189e-01
6.78650618e-01 -8.27901438e-02 1.15472889e+00 -2.50955790e-01
1.42674959e+00 6.80910885e-01 7.20601618e-01 2.95027792e-01
-1.30859804e+00 -6.34602129e-01 -1.16317019e-01 2.22013652e-01
-1.35229182e+00 -5.81367195e-01 4.11098093e-01 -4.27705497e-01
1.33815253e+00 2.99777508e-01 5.55459023e-01 1.16857588e+00
1.26543269e-01 6.11794591e-01 1.04492843e+00 -4.47598219e-01
-2.31024206e-01 -1.16108738e-01 1.97653577e-01 5.09351134e-01
-2.04264224e-02 1.67722687e-01 -7.33833015e-01 -5.00699937e-01
4.37326461e-01 -3.91979843e-01 -4.30685848e-01 1.20688349e-01
-1.47863126e+00 4.85299677e-01 3.58313285e-02 5.85814655e-01
-3.89507025e-01 -5.19583710e-02 7.82007337e-01 7.35620484e-02
6.47482574e-01 3.69412571e-01 -6.13979161e-01 -5.96872926e-01
-7.96532094e-01 1.48645863e-01 8.21459055e-01 1.09285164e+00
2.15498190e-02 -6.73658669e-01 4.60283868e-02 6.12830758e-01
-3.87597643e-03 -4.46411431e-01 4.84457850e-01 -7.96089530e-01
4.78152961e-01 4.56859320e-01 3.86595398e-01 -8.23299646e-01
-8.76445174e-01 -1.39875129e-01 -5.09599686e-01 -4.74957228e-01
7.36433804e-01 -1.16946474e-01 -4.41606402e-01 1.74482620e+00
1.69017598e-01 2.17081666e-01 1.21005766e-01 4.96087760e-01
7.65665293e-01 7.73662776e-02 2.67141789e-01 -9.06586230e-01
1.65452039e+00 -3.53018403e-01 -1.32683420e+00 1.27326831e-01
1.28943753e+00 -1.02462542e+00 2.04305604e-01 1.89626276e-01
-1.01651394e+00 1.95381716e-01 -8.49563062e-01 1.61145981e-02
-2.08955213e-01 -2.82888442e-01 1.05418622e+00 1.65443480e-01
-8.06431949e-01 6.62891328e-01 -1.26813483e+00 -6.33302987e-01
3.20448130e-01 3.30457300e-01 -6.70893431e-01 2.68467456e-01
-1.55259311e+00 1.20849693e+00 5.10565937e-01 1.16747424e-01
-2.20670834e-01 -6.36554539e-01 -8.70548844e-01 -3.76022428e-01
5.99667728e-01 -3.73789370e-01 1.48219943e+00 -4.53572333e-01
-2.84734845e-01 1.08826602e+00 -4.22030151e-01 -5.93932748e-01
3.09708536e-01 1.58157155e-01 -9.40411925e-01 1.52137488e-01
3.47124815e-01 3.34008694e-01 -1.99656948e-01 -6.70522630e-01
-8.73611033e-01 -2.90374458e-01 -9.29396376e-02 -2.34379843e-02
-1.27338395e-02 5.21939814e-01 -3.18854034e-01 -7.60221779e-01
1.10844143e-01 -9.37191427e-01 -3.14968765e-01 -2.55464196e-01
-4.22960490e-01 -6.74546242e-01 6.98667824e-01 -8.31969440e-01
1.53634870e+00 -1.88592243e+00 -2.09932551e-01 -2.99659669e-02
2.96242833e-01 -4.70704436e-02 2.77989745e-01 7.32525051e-01
-6.23659909e-01 2.47453511e-01 -1.61266327e-01 -2.92780176e-02
-4.48082507e-01 4.11554068e-01 -4.00810778e-01 5.05607009e-01
3.56802195e-01 8.94529819e-01 -1.31964099e+00 -9.24202323e-01
-1.31929085e-01 1.18128575e-01 -2.06446275e-01 -1.83893383e-01
-1.84494257e-01 5.82848489e-01 -5.79444110e-01 5.90127468e-01
-1.23486742e-02 -3.36048454e-01 5.94725788e-01 -2.40885377e-01
-2.90163308e-01 1.05577886e+00 -8.45194101e-01 1.61932993e+00
1.40988991e-01 6.59809887e-01 -4.35037792e-01 -7.82649934e-01
4.57204700e-01 1.07831764e+00 1.29608798e+00 -4.95451152e-01
1.45671830e-01 8.62401798e-02 2.37977490e-01 -6.58602417e-01
5.30200422e-01 -4.54158902e-01 -1.38595060e-01 6.48096919e-01
-1.14889592e-01 1.83696628e-01 6.54144645e-01 3.32730860e-01
1.55952311e+00 1.63638517e-01 8.10986519e-01 -4.34273183e-02
1.01693355e-01 4.97012436e-01 9.53155518e-01 1.82787254e-01
-4.50611830e-01 5.15713513e-01 9.45343018e-01 -6.87066972e-01
-9.60317552e-01 -5.94491363e-01 -5.86295485e-01 3.19341689e-01
-3.21008176e-01 -9.38099325e-01 2.22203825e-02 -7.93768227e-01
-4.18373138e-01 6.77291155e-01 -6.73667312e-01 1.04793146e-01
-6.67699873e-01 -1.14060366e+00 9.97877181e-01 7.71364987e-01
-1.95342213e-01 -9.28128541e-01 -6.56927347e-01 6.39176011e-01
-1.01086748e+00 -1.51607370e+00 -3.00454706e-01 5.97475111e-01
-7.66902506e-01 -1.44289899e+00 -3.51660745e-03 -5.03709257e-01
3.63383919e-01 -2.76399493e-01 1.12524593e+00 4.17374857e-02
-2.15792701e-01 7.72602763e-03 -6.37870371e-01 -5.57983339e-01
-5.13705432e-01 -2.72194277e-02 -1.70732826e-01 -5.04520535e-01
6.98608100e-01 -5.31392574e-01 -3.67092043e-01 3.77547681e-01
-9.32935834e-01 8.77663791e-02 1.78403556e-01 7.51218200e-01
5.71752489e-01 1.46627784e-01 5.96521676e-01 -1.29610491e+00
5.26910543e-01 -6.51541352e-01 -3.35556120e-01 6.13120981e-02
-7.08556890e-01 -1.38130048e-02 5.60268983e-02 -3.97457659e-01
-8.64266396e-01 1.27306029e-01 -1.93326280e-01 1.50680438e-01
-1.15406483e-01 9.46856678e-01 3.77957553e-01 5.02823293e-01
8.49021375e-01 -2.54651994e-01 -2.13399127e-01 -2.26032928e-01
6.16144910e-02 3.97157282e-01 5.37680864e-01 -4.79126781e-01
3.84223193e-01 4.03231144e-01 1.02231234e-01 -2.36112684e-01
-1.08368874e+00 -7.68677473e-01 -6.76290154e-01 8.92197564e-02
9.14836645e-01 -7.14517355e-01 -6.71458960e-01 -2.24891752e-01
-1.09149015e+00 -3.58511001e-01 -4.13366348e-01 7.40574479e-01
-4.56985295e-01 2.82482922e-01 -8.73205304e-01 -5.46666443e-01
-4.15126793e-02 -9.22804534e-01 6.88629210e-01 -1.60580903e-01
-1.24154437e+00 -1.00300813e+00 2.67969340e-01 3.84004474e-01
-1.68236554e-01 5.37480533e-01 1.02918994e+00 -9.41500664e-01
-2.50529975e-01 -5.04193962e-01 -1.75793603e-01 -4.29841429e-01
4.68457878e-01 3.30313966e-02 -6.57281756e-01 4.45846021e-02
-2.02309117e-01 -1.99458703e-01 5.24843812e-01 3.41064662e-01
6.65550351e-01 -3.28837812e-01 -8.96783710e-01 3.82812019e-03
9.17992175e-01 6.37110353e-01 5.59197366e-01 1.82528779e-01
1.39244884e-01 6.96852505e-01 7.69889235e-01 4.15774584e-01
5.13883710e-01 9.10627484e-01 -3.98672111e-02 -3.28373769e-03
2.80216951e-02 -1.96980372e-01 -2.10061297e-01 5.85883915e-01
-3.45417649e-01 -2.77908474e-01 -1.20438111e+00 1.00713074e+00
-2.00819802e+00 -1.07692230e+00 -4.38350558e-01 1.83408582e+00
1.35570908e+00 3.55516136e-01 2.48425379e-01 1.94481090e-01
4.19044286e-01 -1.01269409e-01 -8.51062611e-02 -2.44566783e-01
-6.62662834e-02 2.28915200e-01 4.74752128e-01 3.56576204e-01
-1.13007092e+00 7.40073919e-01 6.65445995e+00 2.94112891e-01
-6.56632066e-01 1.65875211e-01 6.07549012e-01 -3.89559269e-02
-1.28329992e-01 5.12162805e-01 -6.11573875e-01 2.48979300e-01
1.24639308e+00 -3.57298374e-01 -2.99019739e-02 2.30146497e-01
4.08643842e-01 -2.35067323e-01 -1.34354734e+00 6.62832260e-01
-3.84707063e-01 -1.49491191e+00 -5.67296326e-01 1.93835363e-01
5.68151593e-01 -1.67337492e-01 -5.85813582e-01 9.41361487e-02
5.77709258e-01 -9.12344456e-01 5.00953019e-01 4.70276237e-01
8.37106228e-01 -5.38292110e-01 9.87389922e-01 1.06202349e-01
-1.14956510e+00 2.19953090e-01 3.05088818e-01 -4.48587090e-02
5.98422229e-01 7.53759086e-01 -1.25315499e+00 8.51665258e-01
6.11565590e-01 8.32285523e-01 -3.15769315e-01 1.06534386e+00
-4.11687493e-01 7.41369307e-01 -2.80363739e-01 1.77055299e-01
1.60099566e-02 2.94489413e-01 5.43453813e-01 1.09368849e+00
4.11835760e-02 8.11705053e-01 -1.65934321e-02 6.27834737e-01
-5.05117550e-02 -1.89401936e-02 -7.35542655e-01 -6.10671759e-01
4.37321246e-01 1.14073300e+00 -1.07729983e+00 -2.07811296e-01
-5.65430582e-01 6.24983072e-01 2.38939464e-01 1.98084638e-01
-9.22189236e-01 -2.02067092e-01 5.17821729e-01 3.19353521e-01
-2.19051182e-01 -1.07720129e-01 -2.15745345e-01 -9.08002794e-01
-5.22440858e-02 -7.33908832e-01 1.16241610e+00 -8.62301588e-01
-1.11486626e+00 6.92813635e-01 2.57345498e-01 -1.08116639e+00
-7.72843659e-01 -4.64869626e-02 4.24405970e-02 8.03738236e-01
-8.32649410e-01 -1.05586290e+00 2.18889549e-01 3.29685092e-01
2.36321345e-01 5.01293719e-01 1.05534029e+00 5.57388306e-01
-3.65906775e-01 4.66613054e-01 -6.47774696e-01 3.28547955e-01
1.06902957e+00 -1.06757641e+00 2.06744298e-01 7.58104205e-01
1.46957308e-01 7.29126394e-01 1.02522528e+00 -8.41425359e-01
-6.42668366e-01 -9.32826400e-01 1.71337044e+00 -8.04499626e-01
1.02840269e+00 1.31380752e-01 -9.21700060e-01 1.34672844e+00
6.51797503e-02 -1.02321424e-01 8.31470549e-01 4.40875024e-01
-3.34910512e-01 2.16839790e-01 -9.68957245e-01 4.87394512e-01
1.13230026e+00 -5.20824969e-01 -7.41192043e-01 7.25342751e-01
7.52736926e-01 -6.44863367e-01 -1.28937578e+00 8.16780865e-01
2.75104612e-01 -5.01471281e-01 8.45432341e-01 -7.71678388e-01
4.77128416e-01 -3.22334260e-01 1.98687270e-01 -8.56138468e-01
2.63384283e-02 -7.80392826e-01 1.76022753e-01 1.38737631e+00
7.70132005e-01 -4.29515749e-01 5.20109057e-01 8.69147003e-01
-2.47268006e-01 -7.77515769e-01 -1.13992608e+00 -5.87422669e-01
-2.17323631e-01 -6.39270604e-01 2.62497663e-01 1.57294416e+00
9.07577336e-01 4.16636616e-01 -1.74913034e-01 -5.12942066e-03
2.65281759e-02 -4.29585762e-02 1.33275971e-01 -1.18656158e+00
-2.05218136e-01 -2.46831402e-01 -4.38817769e-01 -3.02485347e-01
-1.08774610e-01 -9.13048029e-01 -9.41126198e-02 -1.68498242e+00
4.68919367e-01 -6.66500211e-01 -1.39790833e-01 1.21981001e+00
1.46367389e-03 3.41890723e-01 -6.48792148e-01 3.77300620e-01
-5.23037374e-01 -4.19030599e-02 1.02610230e+00 1.28258318e-01
-2.95373082e-01 -1.32579647e-03 -6.81522906e-01 6.64580166e-01
4.93777514e-01 -7.50729859e-01 -5.04929125e-01 -3.02774627e-02
4.32855248e-01 7.64851034e-01 2.64374435e-01 -4.44949657e-01
2.39917889e-01 -2.69042939e-01 7.30613396e-02 -9.10452545e-01
1.12765469e-01 -5.39102376e-01 5.52864015e-01 3.69451106e-01
-4.81842756e-01 1.54028729e-01 5.19414604e-01 4.28279430e-01
-3.34921509e-01 -1.30146667e-01 4.59745497e-01 -7.39454255e-02
-4.30150419e-01 1.89906340e-02 -5.85338533e-01 2.22214460e-01
1.08314013e+00 2.48464048e-01 -6.51403725e-01 -3.03847939e-01
-1.05488300e+00 1.51918054e-01 1.90307707e-01 4.05376166e-01
1.39885023e-01 -1.18087614e+00 -5.55064738e-01 -5.65349162e-01
2.96114147e-01 1.96584929e-02 1.34050786e-01 1.42890537e+00
-3.67602468e-01 8.13859105e-01 1.35878935e-01 -1.88416064e-01
-1.51060450e+00 8.25273037e-01 7.63129070e-02 -7.82696545e-01
-9.69974279e-01 6.70949697e-01 -2.75979370e-01 4.80938442e-02
9.18146968e-02 -3.04400861e-01 -8.01288038e-02 3.77531052e-01
3.96195710e-01 -6.53027371e-02 2.05569670e-01 -5.51086366e-01
-7.75863647e-01 -3.78108680e-01 -2.85480529e-01 -4.36808467e-01
1.52997291e+00 5.01751062e-03 -3.47454429e-01 4.95945245e-01
8.35106969e-01 -3.86409201e-02 -5.51900089e-01 -3.26808661e-01
7.09084272e-01 6.75668865e-02 -3.46511662e-01 -8.49581599e-01
-4.51525927e-01 2.99157649e-01 1.77758679e-01 3.11877102e-01
1.17589724e+00 3.73466223e-01 8.57322752e-01 3.50161199e-03
3.43358219e-01 -7.77796745e-01 -2.97898352e-01 1.96669474e-01
6.14059627e-01 -9.80514884e-01 2.76776344e-01 -7.22670019e-01
-4.01655644e-01 8.82139325e-01 2.43233904e-01 5.62793195e-01
3.79802972e-01 6.57624900e-01 -5.90032935e-02 -4.53360498e-01
-1.26466155e+00 -3.53479356e-01 2.15145111e-01 4.46780264e-01
1.08084500e+00 -5.94867170e-02 -1.05898786e+00 6.90282702e-01
-1.00670017e-01 3.55875432e-01 6.81401551e-01 1.11720681e+00
2.57451028e-01 -1.50355053e+00 -1.70258190e-02 4.32253599e-01
-8.08500767e-01 -2.69946218e-01 -4.66763347e-01 9.58711922e-01
1.09438390e-01 1.13403749e+00 -5.00291102e-02 -7.10424110e-02
3.55445862e-01 3.05097044e-01 4.58627611e-01 -5.27979851e-01
-4.26996529e-01 2.70271927e-01 1.01952112e+00 -5.79024494e-01
-6.81720197e-01 -1.09165621e+00 -1.61122572e+00 -1.62681639e-02
-2.87229955e-01 3.84286880e-01 2.29087286e-02 1.20484591e+00
1.36257755e-02 8.28241408e-01 -9.87637565e-02 9.47058946e-02
-7.88884982e-03 -9.04119432e-01 -3.50591034e-01 6.90121114e-01
-8.38097855e-02 -6.85425043e-01 -6.31936789e-02 5.16363382e-01] | [8.684209823608398, 9.08314323425293] |
151bd158-4fbd-4697-8084-6a6e28caf1a2 | dual-decoder-transformer-for-joint-automatic | 2011.00747 | null | https://arxiv.org/abs/2011.00747v1 | https://arxiv.org/pdf/2011.00747v1.pdf | Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech Translation | We introduce dual-decoder Transformer, a new model architecture that jointly performs automatic speech recognition (ASR) and multilingual speech translation (ST). Our models are based on the original Transformer architecture (Vaswani et al., 2017) but consist of two decoders, each responsible for one task (ASR or ST). Our major contribution lies in how these decoders interact with each other: one decoder can attend to different information sources from the other via a dual-attention mechanism. We propose two variants of these architectures corresponding to two different levels of dependencies between the decoders, called the parallel and cross dual-decoder Transformers, respectively. Extensive experiments on the MuST-C dataset show that our models outperform the previously-reported highest translation performance in the multilingual settings, and outperform as well bilingual one-to-one results. Furthermore, our parallel models demonstrate no trade-off between ASR and ST compared to the vanilla multi-task architecture. Our code and pre-trained models are available at https://github.com/formiel/speech-translation. | ['Laurent Besacier', 'Didier Schwab', 'Jiatao Gu', 'Changhan Wang', 'Juan Pino', 'Hang Le'] | 2020-11-02 | null | https://aclanthology.org/2020.coling-main.314 | https://aclanthology.org/2020.coling-main.314.pdf | coling-2020-8 | ['speech-to-text-translation'] | ['natural-language-processing'] | [ 1.10033184e-01 3.00751954e-01 -2.11364329e-01 -2.54721463e-01
-1.56690598e+00 -7.56150484e-01 1.05298662e+00 -2.86479503e-01
-9.14036855e-02 6.59274399e-01 5.64720750e-01 -8.42307210e-01
6.65663838e-01 -3.01555336e-01 -1.05446994e+00 -4.95644271e-01
4.22659814e-01 8.97685945e-01 1.03823632e-01 -4.66517657e-01
-3.12141418e-01 -1.33723557e-01 -8.97710264e-01 6.44167244e-01
8.83912861e-01 5.97502291e-01 3.42713535e-01 6.72309220e-01
6.86910450e-02 8.90060484e-01 -3.70785058e-01 -7.85637498e-01
1.34727046e-01 -4.10980910e-01 -8.38574767e-01 -7.34690577e-02
1.66406840e-01 -3.18836063e-01 -5.93862355e-01 7.61562049e-01
5.89902341e-01 -4.36777502e-01 4.95963633e-01 -8.46214056e-01
-1.18803489e+00 1.06483710e+00 -2.98303545e-01 1.71625108e-01
3.51358801e-01 -3.74683812e-02 1.23127341e+00 -1.23756266e+00
2.64365852e-01 1.28642106e+00 4.25791025e-01 7.16574311e-01
-1.26000857e+00 -4.87883300e-01 1.59797564e-01 1.67652786e-01
-1.34854841e+00 -1.18414009e+00 3.79959047e-01 -3.24326217e-01
1.38887012e+00 9.61329639e-02 2.07382336e-01 1.62933326e+00
2.01318190e-01 1.13024640e+00 1.17950428e+00 -4.54839587e-01
-1.55013114e-01 2.13445961e-01 -2.61474371e-01 5.12924135e-01
-1.27936289e-01 5.02182133e-02 -7.18597889e-01 6.76460862e-02
5.45692861e-01 -4.12371874e-01 -4.60037649e-01 -5.06751575e-02
-1.57738543e+00 6.38642907e-01 -6.66934326e-02 4.77236181e-01
-2.41915107e-01 1.33079812e-01 4.00889128e-01 7.02885211e-01
6.46873534e-01 -1.53568084e-03 -7.59377539e-01 -2.94478059e-01
-7.27997243e-01 -2.74695516e-01 7.93835819e-01 1.20042717e+00
5.09745061e-01 1.50755197e-01 -1.94035053e-01 9.78874981e-01
4.56270367e-01 7.92836666e-01 7.40602791e-01 -3.66894186e-01
1.03279221e+00 9.63689834e-02 -1.29645795e-01 -2.24223584e-01
1.19291827e-01 -6.38445258e-01 -5.14964819e-01 -4.99379784e-01
1.17993511e-01 -9.53593329e-02 -9.56290901e-01 1.77577960e+00
-1.17988579e-01 1.51412144e-01 2.90558130e-01 7.45230854e-01
7.38528967e-01 8.33525360e-01 -1.09016068e-01 1.39881253e-01
1.31361210e+00 -1.40646017e+00 -7.26652682e-01 -6.76837206e-01
7.11229444e-01 -1.13000929e+00 1.08694732e+00 -4.28758940e-04
-1.43967795e+00 -3.25390756e-01 -9.96265709e-01 -3.99115801e-01
-2.43017286e-01 5.09529948e-01 2.00995132e-01 5.47516525e-01
-1.59829700e+00 8.58344361e-02 -1.06116247e+00 -4.19791579e-01
-8.46782923e-02 2.46936530e-01 -2.82271713e-01 2.06577927e-01
-1.42666590e+00 1.24437487e+00 -9.46757048e-02 7.55072609e-02
-1.41594255e+00 -3.48253816e-01 -8.03146839e-01 2.40066387e-02
1.67583138e-01 -6.86555982e-01 2.01748347e+00 -1.06326973e+00
-1.95451880e+00 1.12609756e+00 -4.86046046e-01 -5.35560012e-01
3.71755958e-01 -3.46105248e-01 -4.41090763e-01 -9.07825306e-02
2.40963638e-01 3.63454282e-01 6.13188148e-01 -1.13130116e+00
-4.63049829e-01 -1.82992399e-01 -4.07948047e-02 3.72141540e-01
-8.55361149e-02 4.40323025e-01 -7.15571404e-01 -7.58952320e-01
-1.65336609e-01 -9.83287990e-01 1.31384343e-01 -5.36996126e-01
-5.61703801e-01 4.25364301e-02 4.73074198e-01 -1.08483243e+00
1.29865980e+00 -1.95649970e+00 5.41427970e-01 -3.74061614e-01
1.83843374e-02 3.80041003e-01 -4.74885195e-01 7.89295256e-01
-2.42120758e-01 1.17808595e-01 -4.21747535e-01 -8.52437913e-01
5.08470908e-02 2.84864426e-01 -4.92666811e-01 3.53219241e-01
3.74967694e-01 1.13489473e+00 -7.46380568e-01 -5.11676557e-02
-9.39823780e-03 6.25131428e-01 -2.49438778e-01 2.00984463e-01
-2.08801404e-01 7.22295403e-01 -2.39939794e-01 5.52355230e-01
3.65821928e-01 -2.64704138e-01 5.41034579e-01 1.65844068e-01
-2.36349165e-01 1.34319627e+00 -4.37254876e-01 1.78791523e+00
-8.77894521e-01 6.56545877e-01 4.17643309e-01 -9.77800310e-01
6.52230024e-01 1.00120103e+00 -2.69491877e-02 -9.47258055e-01
1.16976112e-01 7.54932463e-01 3.43506336e-02 -1.25527203e-01
3.09591740e-01 -1.75534025e-01 -1.01992458e-01 7.13181019e-01
3.38915229e-01 2.33408079e-01 6.75807372e-02 3.05595219e-01
9.16921854e-01 2.14074075e-01 3.25326085e-01 -2.47709483e-01
6.21979594e-01 -2.73016334e-01 4.91838008e-01 4.37756032e-01
-5.93640655e-02 5.58004260e-01 5.31200409e-01 -3.17492988e-03
-1.25465453e+00 -1.26029205e+00 1.40267879e-01 1.21277392e+00
-2.35023171e-01 -5.05131900e-01 -7.60536253e-01 -6.16312861e-01
-3.61470729e-01 9.26778913e-01 -3.45913887e-01 -5.11553586e-02
-8.84902894e-01 -3.98043782e-01 8.57285440e-01 4.53838378e-01
1.96477532e-01 -7.59431422e-01 6.14546891e-03 2.28502497e-01
-7.52369583e-01 -1.41666508e+00 -8.57073188e-01 1.76103041e-01
-5.58854520e-01 -6.09341621e-01 -9.03331816e-01 -9.76236403e-01
3.16815168e-01 3.21847349e-01 1.39793432e+00 -1.59928367e-01
5.84621191e-01 2.90680230e-01 -3.68729055e-01 -4.56803814e-02
-1.05065715e+00 4.42040443e-01 4.27924991e-02 1.63121104e-01
2.45165020e-01 -5.69914818e-01 -1.42409459e-01 3.63713682e-01
-5.32167733e-01 4.01423901e-01 7.96594739e-01 7.96776354e-01
3.80121320e-01 -8.87092233e-01 5.16554534e-01 -5.71125925e-01
6.32059693e-01 -6.87454879e-01 -4.27181125e-01 4.54285651e-01
-3.81199449e-01 2.51056552e-01 6.93275094e-01 -1.75622329e-01
-8.53217423e-01 -1.72071069e-01 -4.36936587e-01 -3.34615082e-01
3.56054939e-02 4.31790262e-01 -3.25306773e-01 2.82059252e-01
1.22753292e-01 7.45003164e-01 -1.80678040e-01 -7.47995853e-01
4.28366542e-01 9.60250795e-01 2.67758787e-01 -6.30780756e-01
6.69302106e-01 3.85621339e-02 -6.59324586e-01 -4.89475191e-01
-7.06036389e-01 -1.61025584e-01 -5.46385765e-01 3.39639708e-02
9.02728319e-01 -1.36768258e+00 -2.45366022e-01 5.27486622e-01
-1.65163755e+00 -6.32955730e-01 1.33531094e-01 4.19620425e-01
-6.55262768e-01 1.49538025e-01 -1.02106106e+00 -5.19062459e-01
-3.97909015e-01 -1.61879551e+00 1.43887043e+00 -4.66039121e-01
1.07776895e-01 -1.12119806e+00 1.64942995e-01 5.37302494e-01
5.78259110e-01 -5.21934092e-01 8.15067947e-01 -8.31200659e-01
-6.87261283e-01 2.18142241e-01 -4.71770056e-02 4.33868587e-01
2.50056423e-02 -2.88129807e-01 -1.00934970e+00 -3.81624997e-01
4.20857593e-02 -3.73751044e-01 8.62506270e-01 6.34434521e-02
4.95144248e-01 -5.50606132e-01 -2.22541735e-01 4.36176509e-01
1.00691676e+00 1.59782663e-01 5.88911593e-01 1.23035677e-01
7.27676451e-01 2.29045644e-01 -1.03579737e-01 -1.13939017e-01
9.68514025e-01 1.07643759e+00 1.16209932e-01 -1.56801492e-01
-4.21210051e-01 -5.15936494e-01 1.16279364e+00 1.82145715e+00
1.66442290e-01 -4.69498366e-01 -1.12256908e+00 7.21782386e-01
-1.87935972e+00 -6.84916258e-01 -2.14816689e-01 2.24391294e+00
9.94095862e-01 -1.27643168e-01 7.99530521e-02 -1.93418592e-01
7.16189861e-01 2.30267823e-01 -1.89957738e-01 -6.90362453e-01
-3.36207122e-01 2.96463281e-01 5.25937915e-01 1.00158334e+00
-8.54589105e-01 1.33878505e+00 6.64636755e+00 7.34531581e-01
-1.18037593e+00 7.86334872e-01 5.46979427e-01 -1.66327819e-01
-5.59127927e-01 2.19267219e-01 -7.81633437e-01 3.90516013e-01
1.57550824e+00 -1.23860911e-01 8.00878525e-01 3.76075715e-01
1.44943029e-01 5.02905250e-01 -1.17978537e+00 7.33889878e-01
1.68812677e-01 -1.13561904e+00 3.06424141e-01 7.32863024e-02
4.52375144e-01 7.45899677e-01 9.89312679e-02 4.92558569e-01
6.37636483e-01 -8.19358706e-01 1.16462576e+00 3.27497162e-02
9.89370108e-01 -3.72045189e-01 2.92959660e-01 3.52256745e-01
-1.30752766e+00 1.12424739e-01 6.24305159e-02 1.31903082e-01
4.84315813e-01 3.01693976e-01 -7.83840120e-01 7.37104356e-01
3.54249120e-01 7.54103124e-01 -2.76562363e-01 2.88799405e-01
-6.91271424e-01 9.30434287e-01 -8.04852415e-03 2.98380435e-01
3.01022828e-01 -1.71588302e-01 7.43426561e-01 1.32764447e+00
4.22649592e-01 -3.70116234e-01 -2.30360981e-02 6.76309764e-01
-2.93142766e-01 2.04061586e-02 -5.87495685e-01 -2.21302927e-01
5.73503554e-01 9.01738465e-01 -1.24680445e-01 -5.46389461e-01
-8.20164979e-01 1.30100596e+00 5.67852616e-01 5.50966799e-01
-9.76812541e-01 -2.73587257e-02 8.28336596e-01 1.67171672e-01
4.41206574e-01 -6.25547886e-01 -2.49857470e-01 -1.58211529e+00
1.74219728e-01 -1.39393127e+00 3.73940207e-02 -7.05772758e-01
-1.03144264e+00 9.56470311e-01 -5.05737960e-01 -1.10053575e+00
-3.12014788e-01 -5.04128218e-01 -3.97090167e-01 1.16004407e+00
-1.83894467e+00 -1.57612872e+00 5.26765943e-01 5.46619773e-01
8.85708511e-01 -2.41158217e-01 1.02056015e+00 7.58229077e-01
-6.67045653e-01 7.40282655e-01 2.66157061e-01 2.78390616e-01
8.07021201e-01 -1.10687613e+00 1.12980723e+00 1.10073423e+00
2.84945428e-01 6.26868665e-01 2.83496231e-01 -4.51384842e-01
-1.55559015e+00 -1.00084889e+00 1.65074265e+00 -6.48578644e-01
9.93724763e-01 -9.32722151e-01 -6.26808345e-01 1.43084931e+00
8.37540269e-01 -5.64657390e-01 7.23356605e-01 1.22679092e-01
-5.61251044e-01 6.29373193e-02 -4.64087576e-01 7.15097666e-01
1.00394285e+00 -9.55525160e-01 -5.40233016e-01 3.68134141e-01
1.00749564e+00 -4.80623096e-01 -6.65585160e-01 1.05002776e-01
3.17394316e-01 -7.81933010e-01 6.90294623e-01 -4.55833852e-01
6.02403581e-01 -1.51558384e-01 -4.92202133e-01 -1.64476991e+00
-3.32243770e-01 -8.93460512e-01 -1.90830499e-01 1.09072065e+00
1.05463147e+00 -9.35186565e-01 -5.37243821e-02 -4.83911904e-03
-7.77661920e-01 -6.69708908e-01 -1.15736055e+00 -9.17643428e-01
4.32715595e-01 -4.13857609e-01 6.59588337e-01 9.19186413e-01
3.07184663e-02 1.00660181e+00 -5.64863324e-01 2.81213015e-01
3.14875990e-01 -1.46092981e-01 6.12797737e-01 -7.52658784e-01
-7.09460914e-01 -6.10457480e-01 2.26693839e-01 -1.58479548e+00
2.26638839e-01 -1.51176560e+00 3.52923609e-02 -1.65506542e+00
9.58956704e-02 -1.54320538e-01 -1.17599085e-01 7.77623475e-01
2.45938320e-02 8.16087574e-02 1.91445395e-01 4.40746427e-01
-4.27861243e-01 9.18649733e-01 1.05900204e+00 -1.38457105e-01
1.69067457e-01 -1.81291610e-01 -8.23307335e-01 2.91806698e-01
8.11296821e-01 -4.22763228e-01 -2.88507253e-01 -1.41998899e+00
-5.25519019e-03 2.51486480e-01 4.99964878e-02 -6.68077946e-01
1.78053990e-01 2.88702786e-01 -3.20825547e-01 -2.56433189e-01
3.84636939e-01 -3.80259424e-01 1.21429600e-02 3.28353226e-01
-4.41609472e-01 5.50399542e-01 1.49294466e-01 1.70815423e-01
-3.98421615e-01 3.21547598e-01 7.29431152e-01 -1.18268616e-01
-1.73759386e-01 2.19953328e-01 -7.81748295e-01 6.33760542e-02
6.80971026e-01 2.92531043e-01 -4.52808589e-01 -5.91466844e-01
-7.16800153e-01 1.99636027e-01 2.05690935e-01 8.82615983e-01
3.34322184e-01 -1.39941275e+00 -1.12862527e+00 2.56398112e-01
1.32696345e-01 -5.13128519e-01 -2.07189485e-01 1.18213868e+00
-1.25641674e-01 9.78384316e-01 2.34863698e-01 -4.55385983e-01
-8.56857598e-01 3.54328543e-01 4.84313071e-01 -4.56816614e-01
-3.43048930e-01 7.58602679e-01 3.63176525e-01 -8.35027039e-01
1.04866084e-02 -2.05517158e-01 4.06754076e-01 -3.80041629e-01
4.48759526e-01 9.79076847e-02 3.41948777e-01 -9.29269433e-01
-6.13063931e-01 3.32251102e-01 -2.92446077e-01 -6.00635767e-01
1.10378861e+00 -3.70724946e-01 -1.69710264e-01 6.38970077e-01
1.09358871e+00 9.95293185e-02 -7.92596221e-01 -5.24645746e-01
2.81186141e-02 -1.30417980e-02 -3.02933902e-02 -1.09836984e+00
-1.01258719e+00 1.13175297e+00 2.91711967e-02 -8.56140815e-03
9.73085701e-01 1.48722082e-01 1.10049605e+00 7.85640702e-02
3.71952355e-01 -1.05602670e+00 -1.67161912e-01 9.31172192e-01
1.09082675e+00 -9.60784137e-01 -7.56604791e-01 -2.39551380e-01
-7.99824536e-01 7.29674876e-01 4.20510888e-01 2.62790412e-01
4.12477434e-01 5.94838917e-01 3.95757407e-01 1.76898286e-01
-1.34726322e+00 -2.67957360e-01 1.40821829e-01 4.93168592e-01
1.09368563e+00 3.55876207e-01 -3.73922139e-01 4.66582239e-01
-2.07061157e-01 -1.86763316e-01 3.41615111e-01 6.44698024e-01
-1.17466830e-01 -1.59278190e+00 -1.76159665e-01 -5.53425960e-02
-5.67420781e-01 -6.36549175e-01 -6.95535004e-01 4.43110317e-01
-3.91208470e-01 1.20816612e+00 -1.86882745e-02 -5.73616445e-01
2.15700969e-01 2.87450880e-01 4.12252247e-01 -6.93204045e-01
-7.32357562e-01 2.09555864e-01 5.03153205e-01 -5.20560622e-01
2.28421632e-02 -6.30724251e-01 -8.55407834e-01 -3.84154856e-01
-1.27540112e-01 1.51063859e-01 7.47775316e-01 8.90126467e-01
7.80758202e-01 5.33207297e-01 6.67696118e-01 -5.41831613e-01
-7.03912437e-01 -1.13715065e+00 -2.40763705e-02 -7.25739896e-02
5.38137257e-01 -2.46927351e-01 -2.26259962e-01 4.51191738e-02] | [14.458165168762207, 7.248569488525391] |
d51dbada-2b59-4be6-927b-28190d594781 | neural-voice-cloning-with-a-few-samples | 1802.06006 | null | http://arxiv.org/abs/1802.06006v3 | http://arxiv.org/pdf/1802.06006v3.pdf | Neural Voice Cloning with a Few Samples | Voice cloning is a highly desired feature for personalized speech interfaces.
Neural network based speech synthesis has been shown to generate high quality
speech for a large number of speakers. In this paper, we introduce a neural
voice cloning system that takes a few audio samples as input. We study two
approaches: speaker adaptation and speaker encoding. Speaker adaptation is
based on fine-tuning a multi-speaker generative model with a few cloning
samples. Speaker encoding is based on training a separate model to directly
infer a new speaker embedding from cloning audios and to be used with a
multi-speaker generative model. In terms of naturalness of the speech and its
similarity to original speaker, both approaches can achieve good performance,
even with very few cloning audios. While speaker adaptation can achieve better
naturalness and similarity, the cloning time or required memory for the speaker
encoding approach is significantly less, making it favorable for low-resource
deployment. | ['Sercan O. Arik', 'Wei Ping', 'Kainan Peng', 'Yanqi Zhou', 'Jitong Chen'] | 2018-02-14 | neural-voice-cloning-with-a-few-samples-1 | http://papers.nips.cc/paper/8206-neural-voice-cloning-with-a-few-samples | http://papers.nips.cc/paper/8206-neural-voice-cloning-with-a-few-samples.pdf | neurips-2018-12 | ['voice-cloning'] | ['speech'] | [ 2.76123971e-01 4.83366400e-01 -4.51756902e-02 -5.69993436e-01
-9.41715777e-01 -3.25752586e-01 4.74691033e-01 -1.06629469e-01
-6.14778921e-02 6.00345731e-01 5.92709959e-01 -2.00342372e-01
4.79481637e-01 -4.55683857e-01 -6.54943049e-01 -5.58736265e-01
1.74986422e-01 4.85363036e-01 1.23775303e-01 -1.80696040e-01
-1.83564827e-01 5.28770685e-01 -1.92126787e+00 3.23990971e-01
6.70445919e-01 7.55392730e-01 4.41448003e-01 1.23463571e+00
-4.85514879e-01 2.74439245e-01 -1.17340446e+00 -1.39798641e-01
-1.01418853e-01 -8.36160123e-01 -8.23555350e-01 -1.01473138e-01
3.08201134e-01 -3.88052642e-01 -5.30077927e-02 7.34452665e-01
9.74965334e-01 2.64959961e-01 4.83288109e-01 -1.16737270e+00
-4.76735532e-01 1.00942278e+00 2.37257823e-01 2.04417408e-01
4.18276846e-01 -6.57351688e-02 9.63461816e-01 -8.22239816e-01
2.47354865e-01 1.52968502e+00 4.29387450e-01 9.12426353e-01
-1.43422353e+00 -7.40723670e-01 5.84551208e-02 -2.52786189e-01
-1.47212934e+00 -1.19136226e+00 7.12787688e-01 -2.70010233e-01
1.19259179e+00 5.54281116e-01 5.85966170e-01 1.11979151e+00
-8.33113566e-02 6.83211386e-01 3.84848118e-01 -5.09639263e-01
4.85921741e-01 6.67392850e-01 -2.78258622e-01 2.91061997e-01
-3.60370010e-01 7.26587102e-02 -7.79732645e-01 -2.67925590e-01
7.36943841e-01 -3.38812649e-01 -2.80785948e-01 3.10278255e-02
-9.17495728e-01 9.29369748e-01 2.54537821e-01 4.14743036e-01
-5.55705011e-01 2.11183593e-01 3.17723364e-01 4.11409914e-01
3.39356273e-01 5.81338346e-01 -8.96636620e-02 -4.62644219e-01
-1.32206571e+00 1.89776361e-01 9.88331914e-01 1.15344226e+00
5.87547958e-01 7.75582433e-01 -1.53181776e-01 1.10957551e+00
1.55628353e-01 4.69846040e-01 9.80597854e-01 -7.59127438e-01
1.27960205e-01 1.58165935e-02 -1.12896949e-01 -6.29274428e-01
-7.78595507e-02 -4.79774386e-01 -5.20425916e-01 5.70885465e-02
-6.47704154e-02 -2.88665265e-01 -8.92013073e-01 1.85186362e+00
2.00654507e-01 1.41038328e-01 2.73715526e-01 5.69763422e-01
8.17068756e-01 1.19522333e+00 -2.09347785e-01 -1.21970490e-01
1.10810328e+00 -1.19642138e+00 -6.92127407e-01 -4.69702780e-01
2.33021155e-01 -9.51081991e-01 1.46535838e+00 1.85970932e-01
-1.23613048e+00 -6.89223349e-01 -9.90419686e-01 2.11040050e-01
-6.59360811e-02 4.90361527e-02 1.72625065e-01 1.15426683e+00
-1.29217660e+00 3.76508355e-01 -6.21566355e-01 -4.60159302e-01
9.61351395e-02 5.22637129e-01 -2.38109678e-02 2.72911042e-01
-9.60900724e-01 6.28008008e-01 2.41386503e-01 -4.70902324e-01
-9.56485510e-01 -7.04593897e-01 -6.17762864e-01 4.91914272e-01
-1.98920831e-01 -6.39191687e-01 1.58563769e+00 -1.12111962e+00
-2.29444695e+00 2.05203593e-01 -4.74086553e-01 -4.54119831e-01
1.43113032e-01 9.16849542e-03 -7.73191690e-01 5.52114891e-03
-1.41374856e-01 9.52176452e-01 1.41935682e+00 -1.15474117e+00
-6.89444900e-01 1.21198222e-01 -3.17967683e-01 1.72752291e-01
-6.95515335e-01 1.33177772e-01 -1.63424954e-01 -7.04811156e-01
2.38158065e-03 -9.00376737e-01 8.58812109e-02 -3.56682986e-01
-4.25045699e-01 2.24583838e-02 7.80959249e-01 -7.12333083e-01
1.28378594e+00 -2.26899457e+00 1.70528933e-01 1.97180416e-02
-1.49775222e-01 3.17805231e-01 -2.96435267e-01 4.66453016e-01
-3.02905440e-02 1.65926427e-01 7.42905289e-02 -7.26027429e-01
-5.56989275e-02 5.52194566e-02 -4.84719753e-01 -1.15383193e-01
3.84204775e-01 5.37654221e-01 -4.35216129e-01 -5.01136146e-02
-1.00384973e-01 8.26026320e-01 -8.34064364e-01 4.81141657e-01
-9.53576937e-02 2.45481804e-01 1.30032420e-01 3.52812290e-01
2.82904416e-01 2.26274550e-01 -6.97787777e-02 2.31368653e-02
3.75489444e-02 8.22392404e-01 -1.23265469e+00 1.42755079e+00
-8.22472870e-01 6.03383005e-01 2.90563881e-01 -3.50972235e-01
1.16795480e+00 7.84860969e-01 3.09848841e-02 -2.05176264e-01
5.82557395e-02 2.86309242e-01 9.05751884e-02 -3.14789146e-01
7.46275365e-01 -4.69338477e-01 -1.39653133e-02 6.33091629e-01
2.32041433e-01 -4.00300413e-01 -2.42095649e-01 4.13120352e-02
7.74500310e-01 -4.47937459e-01 1.32896572e-01 -1.59411859e-02
2.44144648e-01 -4.13889617e-01 3.34138900e-01 5.88812590e-01
8.08138773e-02 6.33776128e-01 -5.63701466e-02 1.13408729e-01
-1.10841417e+00 -1.16461134e+00 1.85854644e-01 1.48520505e+00
-3.26651305e-01 -5.03551006e-01 -9.97141004e-01 -8.07685256e-02
-1.87671453e-01 1.14286709e+00 -1.34321675e-01 -5.42066395e-01
-4.24685806e-01 -1.57141149e-01 8.92011940e-01 5.66110134e-01
-1.33165687e-01 -1.05613923e+00 -2.81677753e-01 5.80963135e-01
-1.57082498e-01 -8.16663623e-01 -1.03907502e+00 2.02886477e-01
-8.42189550e-01 1.02473877e-01 -9.61102188e-01 -9.93620455e-01
4.00167286e-01 1.39542341e-01 8.33768904e-01 -3.06041598e-01
5.68040498e-02 8.94962475e-02 -2.56604403e-01 -6.72453940e-01
-1.27388525e+00 3.82955700e-01 4.87240136e-01 6.22639693e-02
3.93475825e-03 -7.86819875e-01 -8.51078331e-02 1.78718776e-01
-8.04025650e-01 -4.83729094e-02 6.05019093e-01 8.81215751e-01
1.96433231e-01 8.01525339e-02 1.04581916e+00 -3.79119128e-01
1.05424058e+00 -1.89036146e-01 -1.67150870e-01 -2.99760513e-02
-5.10058522e-01 1.72984928e-01 8.36107790e-01 -9.01106179e-01
-9.83532250e-01 1.25506267e-01 -4.22567934e-01 -3.60346645e-01
-1.94444343e-01 3.09663087e-01 -2.89863676e-01 1.50516659e-01
7.78526366e-01 3.89550149e-01 2.44037330e-01 -6.76384032e-01
4.83168334e-01 1.21208310e+00 5.35032988e-01 -3.17303002e-01
4.72471088e-01 -1.87551811e-01 -7.82161832e-01 -1.27633166e+00
4.73457389e-02 -3.26234460e-01 -3.40455353e-01 -3.89593728e-02
4.58307654e-01 -8.61288190e-01 -3.89309257e-01 2.90907502e-01
-1.04150629e+00 -1.39796525e-01 -5.46068728e-01 5.98846078e-01
-5.89643180e-01 -3.20941284e-02 -5.27591825e-01 -1.01890242e+00
-6.96347833e-01 -1.38703763e+00 1.08889961e+00 1.92977145e-01
-7.19763815e-01 -7.14408517e-01 3.48123200e-02 3.67229991e-02
9.38037217e-01 -5.46747088e-01 9.88580465e-01 -9.01555836e-01
-3.03072840e-01 -2.41751030e-01 3.47411752e-01 4.87200052e-01
4.88702744e-01 -4.86557931e-02 -1.31737292e+00 -5.07923067e-01
-4.94393930e-02 -1.07257850e-01 3.97296458e-01 2.65145808e-01
6.56675518e-01 -6.66260421e-01 -1.78673133e-01 3.74462575e-01
8.69385839e-01 5.20412207e-01 3.90320837e-01 -1.97277367e-01
4.91927773e-01 5.76097488e-01 8.44207257e-02 3.80770326e-01
1.00024482e-02 7.98859715e-01 -3.67396623e-02 1.26266489e-02
-3.80772978e-01 -4.29947197e-01 6.80230081e-01 1.20697820e+00
4.22496587e-01 -3.89142215e-01 -7.77038932e-01 5.96950173e-01
-1.30753243e+00 -9.59261358e-01 6.16497576e-01 2.32669187e+00
1.00288343e+00 1.22989260e-01 5.91275573e-01 1.54652730e-01
8.79767358e-01 -6.07622862e-02 -5.00183165e-01 -8.39964926e-01
9.66464803e-02 4.65495169e-01 -1.86808240e-02 6.94322169e-01
-4.76971179e-01 1.00563228e+00 7.43288565e+00 7.14855671e-01
-1.59590101e+00 1.48077413e-01 2.51724541e-01 -6.46573305e-01
-5.10745108e-01 -2.98827589e-01 -1.08621061e+00 4.74746615e-01
1.62638497e+00 -5.87636828e-01 7.38474309e-01 8.85611713e-01
2.76193261e-01 3.93120646e-01 -1.35095727e+00 1.03235769e+00
3.01078707e-01 -1.41974342e+00 4.41259980e-01 2.17181575e-02
3.89142543e-01 -1.32299110e-01 1.04288056e-01 2.77525961e-01
7.16398582e-02 -1.12659180e+00 1.05815959e+00 1.45215333e-01
8.25674534e-01 -9.68392849e-01 3.43816221e-01 3.57131541e-01
-1.08307755e+00 -6.12072796e-02 -2.80833691e-01 2.40164533e-01
4.39629614e-01 2.10330874e-01 -1.54502547e+00 -1.33003090e-02
6.06172860e-01 -1.09679967e-01 -3.33668172e-01 9.16151583e-01
1.46724686e-01 1.01892662e+00 -4.66294348e-01 -2.68027008e-01
-2.67761443e-02 2.30745792e-01 7.57599294e-01 1.25125432e+00
6.59243166e-01 -3.12880218e-01 -8.12935364e-03 9.60226297e-01
-1.12655133e-01 3.20121497e-01 -4.05156106e-01 -4.00111437e-01
9.08286273e-01 8.49518001e-01 -2.79808104e-01 -5.47970414e-01
-1.00675495e-02 1.25585699e+00 5.68807684e-02 2.74925411e-01
-6.22130930e-01 -6.53572440e-01 9.30820823e-01 1.29296035e-01
4.29003626e-01 -3.99536230e-02 -1.16413742e-01 -7.75302589e-01
-2.09457040e-01 -1.05606246e+00 -2.50520885e-01 -7.01918364e-01
-8.63406658e-01 1.17170990e+00 -3.53708863e-01 -1.03180206e+00
-9.33124423e-01 2.02009417e-02 -7.61031270e-01 1.28106165e+00
-8.63021672e-01 -9.66409624e-01 1.24069422e-01 3.21922839e-01
8.49675775e-01 -6.26584828e-01 1.30862129e+00 3.27708095e-01
-5.39125681e-01 1.09683502e+00 2.24420905e-01 -2.26793140e-01
7.36706138e-01 -9.86729801e-01 7.86368310e-01 6.94464266e-01
1.60538375e-01 8.06430876e-01 9.03666317e-01 -3.61731231e-01
-1.12568581e+00 -1.15043390e+00 1.08063340e+00 -1.95153654e-02
1.52614310e-01 -5.94246268e-01 -1.04550529e+00 5.84679902e-01
3.73316407e-01 -5.77203631e-01 1.03029382e+00 1.92452803e-01
-1.68145001e-01 -1.66104749e-01 -1.13417828e+00 6.14345789e-01
6.35626853e-01 -8.58453214e-01 -5.33435464e-01 -1.44378664e-02
1.12477160e+00 -1.50224134e-01 -9.08382475e-01 -3.41416299e-01
5.51415145e-01 -6.06044531e-01 8.51994932e-01 -4.59351093e-01
-6.11926839e-02 -7.73109719e-02 -2.50129938e-01 -1.68972039e+00
-4.93948787e-01 -8.20291698e-01 1.17759496e-01 1.70971215e+00
8.52356970e-01 -7.65207291e-01 7.63623774e-01 5.83744407e-01
-2.53333598e-01 -3.56908262e-01 -1.00050759e+00 -1.14844596e+00
4.17161122e-04 -1.84025988e-01 1.15355277e+00 6.30789459e-01
8.14822093e-02 8.15929711e-01 -4.51402098e-01 2.65733868e-01
1.76133797e-01 -1.08050583e-02 8.19707692e-01 -9.16202605e-01
-5.90681732e-01 -5.12404680e-01 -2.38676131e-01 -1.03172004e+00
5.45991994e-02 -9.21971738e-01 4.24063116e-01 -1.13158226e+00
-2.92319298e-01 -3.21248531e-01 7.67856315e-02 3.36529493e-01
-6.80332482e-02 -1.79189801e-01 1.07265495e-01 2.76650172e-02
1.74411267e-01 8.00349057e-01 6.19386554e-01 -2.20226705e-01
-9.12574530e-01 3.71386796e-01 -6.16326571e-01 3.31239581e-01
9.06671107e-01 -5.75959623e-01 -6.74263775e-01 -3.36793214e-01
-5.17784715e-01 1.46692514e-01 -1.40412509e-01 -1.23149478e+00
2.35889629e-01 1.70420051e-01 6.43875822e-02 -3.17556977e-01
8.03660691e-01 -5.28665543e-01 5.05855799e-01 3.99119645e-01
-6.21718466e-01 -1.75521392e-02 4.34124529e-01 3.75553936e-01
-3.45662624e-01 -4.07726169e-01 9.43332195e-01 8.58560801e-02
-2.80817062e-01 -7.21211312e-03 -8.30782771e-01 -2.02553093e-01
6.02627039e-01 -3.62656355e-01 2.84085482e-01 -8.73266220e-01
-8.47572684e-01 -4.44579989e-01 3.70839387e-01 7.57508814e-01
7.10875630e-01 -1.52651846e+00 -6.36693001e-01 6.66540861e-01
9.43774432e-02 -3.09245557e-01 3.67799476e-02 1.86580956e-01
-1.48132488e-01 4.44727689e-01 -4.48598340e-02 -5.99023521e-01
-1.57342732e+00 4.47156042e-01 3.20411831e-01 4.45416033e-01
-4.44784492e-01 1.17954278e+00 -2.84421053e-02 -4.22165126e-01
4.24138457e-01 -5.12599528e-01 3.12227514e-02 -7.22338110e-02
8.38081956e-01 2.16286629e-01 1.89922959e-01 -7.53840506e-01
-2.48109162e-01 5.72837666e-02 -2.24094138e-01 -5.95041811e-01
1.18187034e+00 -1.39740303e-01 2.38140777e-01 7.11219728e-01
1.31510234e+00 2.09555790e-01 -9.88291740e-01 -3.01486790e-01
-3.57197762e-01 -3.78397554e-01 3.22180599e-01 -6.29944682e-01
-7.68447518e-01 8.68243515e-01 6.47114038e-01 3.06486696e-01
9.30078447e-01 4.59026732e-02 1.01824427e+00 3.52729052e-01
2.45817080e-01 -1.03024435e+00 1.18257545e-01 3.44241023e-01
1.12174904e+00 -7.16205657e-01 -5.32542646e-01 -3.99610460e-01
-6.95688784e-01 9.53064620e-01 4.12258118e-01 4.16384757e-01
5.56683123e-01 4.25153553e-01 1.79694518e-01 2.58696705e-01
-8.21449459e-01 1.08154424e-01 3.04556757e-01 6.97288990e-01
4.58751291e-01 1.81290820e-01 3.86422753e-01 6.90942466e-01
-9.75580573e-01 -2.52889156e-01 4.79425102e-01 6.81358397e-01
-7.80734062e-01 -1.18482256e+00 -5.65236688e-01 4.08762246e-01
-1.58002302e-01 -3.02395195e-01 -5.11070251e-01 3.73878814e-02
-2.80287892e-01 1.23421204e+00 2.18803629e-01 -6.24490201e-01
3.84332508e-01 4.51137036e-01 1.90476477e-01 -9.71371830e-01
-7.74521708e-01 2.88078487e-01 3.10852379e-01 -2.06645340e-01
1.30055487e-01 -5.77374637e-01 -1.19828880e+00 -4.09301937e-01
-5.42381942e-01 3.82929236e-01 1.04429126e+00 6.11602724e-01
6.47472858e-01 7.01692045e-01 8.17326128e-01 -9.07363534e-01
-7.42557824e-01 -1.06142271e+00 -7.50349760e-01 -4.23417240e-02
4.49435353e-01 -1.83498755e-01 -3.61408532e-01 1.82265058e-01] | [14.848723411560059, 6.518815994262695] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.