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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
76b89547-5a7e-491a-9d9c-1381c3b8e362 | clipsitu-effectively-leveraging-clip-for | 2307.00586 | null | https://arxiv.org/abs/2307.00586v1 | https://arxiv.org/pdf/2307.00586v1.pdf | ClipSitu: Effectively Leveraging CLIP for Conditional Predictions in Situation Recognition | Situation Recognition is the task of generating a structured summary of what is happening in an image using an activity verb and the semantic roles played by actors and objects. In this task, the same activity verb can describe a diverse set of situations as well as the same actor or object category can play a diverse set of semantic roles depending on the situation depicted in the image. Hence model needs to understand the context of the image and the visual-linguistic meaning of semantic roles. Therefore, we leverage the CLIP foundational model that has learned the context of images via language descriptions. We show that deeper-and-wider multi-layer perceptron (MLP) blocks obtain noteworthy results for the situation recognition task by using CLIP image and text embedding features and it even outperforms the state-of-the-art CoFormer, a Transformer-based model, thanks to the external implicit visual-linguistic knowledge encapsulated by CLIP and the expressive power of modern MLP block designs. Motivated by this, we design a cross-attention-based Transformer using CLIP visual tokens that model the relation between textual roles and visual entities. Our cross-attention-based Transformer known as ClipSitu XTF outperforms existing state-of-the-art by a large margin of 14.1% on semantic role labelling (value) for top-1 accuracy using imSitu dataset. We will make the code publicly available. | ['Basura Fernando', 'Dhruv Verma', 'Debaditya Roy'] | 2023-07-02 | null | null | null | null | ['grounded-situation-recognition'] | ['computer-vision'] | [ 6.10919118e-01 3.17993969e-01 -3.84307206e-01 -5.15563428e-01
-5.55643082e-01 -7.98014998e-01 1.22585225e+00 2.68855929e-01
-4.02863294e-01 4.90810126e-01 9.50251937e-01 -1.00228429e-01
4.99964468e-02 -4.63662744e-01 -1.08242917e+00 -6.48015082e-01
2.46423945e-01 2.42785692e-01 1.92357540e-01 -2.59156317e-01
3.43571641e-02 6.37675226e-02 -1.64140761e+00 1.27640057e+00
-9.96273663e-03 1.17671120e+00 4.81080770e-01 4.70372856e-01
-3.37521940e-01 1.57890630e+00 -5.46570241e-01 -5.35759509e-01
-2.11677819e-01 -2.75904149e-01 -8.46523821e-01 2.36937866e-01
5.73880851e-01 -1.53608188e-01 -5.07943988e-01 6.27180874e-01
3.23126048e-01 -8.86441302e-03 6.60456419e-01 -1.34456360e+00
-1.05286527e+00 1.01281822e+00 -3.40822577e-01 1.20031603e-01
4.73143876e-01 8.67803618e-02 1.37974286e+00 -1.01042819e+00
1.08545613e+00 1.41157460e+00 2.53998369e-01 6.90233231e-01
-1.29202688e+00 -3.29138368e-01 6.27148628e-01 6.80524051e-01
-8.86343598e-01 -5.01150429e-01 9.90528703e-01 -3.75613123e-01
1.29271913e+00 1.19942129e-01 6.13663614e-01 1.63402033e+00
-2.09278315e-01 1.22804916e+00 1.00586450e+00 -4.59313720e-01
-4.32993770e-02 3.44882071e-01 -2.80860681e-02 5.17355740e-01
-2.56200641e-01 -2.86403954e-01 -8.21676970e-01 2.69789487e-01
4.88368720e-01 7.85267502e-02 -4.87300381e-02 -4.45214659e-01
-1.59335721e+00 6.46547198e-01 5.83693027e-01 4.29821670e-01
-2.55185783e-01 6.84363425e-01 7.60739207e-01 1.62298992e-01
2.55099982e-01 3.29615772e-01 -3.82053882e-01 -7.33764917e-02
-4.75968242e-01 2.68096719e-02 5.51032841e-01 8.13554823e-01
4.26138490e-01 3.26360762e-02 -5.72522700e-01 7.78851151e-01
3.17150176e-01 3.80299717e-01 2.92395532e-01 -8.83901715e-01
6.40050769e-01 8.24185133e-01 2.07223296e-02 -8.15188169e-01
-5.03616333e-02 -3.73930037e-01 -5.60346484e-01 1.18516289e-01
3.96695018e-01 1.95157424e-01 -1.00585365e+00 1.82165134e+00
1.53218776e-01 7.15465620e-02 1.87381774e-01 7.28876948e-01
1.15711462e+00 1.00184429e+00 6.24987006e-01 1.82043374e-01
1.78678262e+00 -1.00000834e+00 -7.46082604e-01 -5.66581845e-01
2.83953190e-01 -3.21932465e-01 1.32169402e+00 5.79393841e-03
-1.03067386e+00 -6.47230387e-01 -1.07436967e+00 -5.07466018e-01
-6.98240876e-01 2.33353332e-01 4.84954387e-01 1.61797479e-01
-1.08679998e+00 1.74100608e-01 -2.50093490e-01 -3.50811452e-01
8.06375027e-01 -4.82307188e-02 -7.52180874e-01 -1.31656483e-01
-1.24288082e+00 8.25260043e-01 5.88496804e-01 -2.08313670e-02
-1.31619906e+00 -8.70486915e-01 -1.16984141e+00 3.64408553e-01
6.90120876e-01 -6.43836915e-01 1.06940854e+00 -1.47749102e+00
-1.00799990e+00 1.38977158e+00 -2.73339987e-01 -6.10499918e-01
4.04978216e-01 -8.50832760e-02 -3.77372891e-01 5.51066995e-01
1.90926269e-01 1.04169917e+00 9.55597818e-01 -1.43020678e+00
-7.77607322e-01 -2.13466734e-01 6.20439410e-01 3.37100416e-01
-1.97470680e-01 2.34972909e-01 -6.23907685e-01 -6.24022305e-01
-4.87218052e-01 -6.02879524e-01 1.32613748e-01 3.21227998e-01
-2.62247175e-01 -2.76669264e-01 9.32464600e-01 -5.72367668e-01
9.83072281e-01 -2.60716009e+00 7.64590278e-02 -3.18757445e-01
1.54124558e-01 -2.03196164e-02 -1.85481325e-01 6.36623144e-01
-4.01519954e-01 2.50684321e-01 -2.72292137e-01 -5.44891477e-01
3.37127447e-01 4.06200290e-01 -6.51833236e-01 2.94552624e-01
4.04638052e-01 1.11326003e+00 -1.00141168e+00 -5.55552304e-01
4.31615800e-01 7.05328882e-01 -3.67536455e-01 9.30906385e-02
-5.00983775e-01 1.18526101e-01 -2.12531716e-01 4.46950048e-01
1.19953267e-01 -4.95332897e-01 3.90011728e-01 -4.44404989e-01
5.12886234e-03 3.06878418e-01 -9.26556230e-01 1.75719154e+00
-7.18039155e-01 9.45421278e-01 -3.97030152e-02 -1.03013539e+00
4.56271827e-01 5.78360260e-01 4.38841470e-02 -8.30349863e-01
-1.02708943e-01 -1.70257196e-01 -2.05759674e-01 -5.14227271e-01
2.25771576e-01 -2.85313278e-01 -4.53791708e-01 3.76548767e-01
3.01881671e-01 3.35425764e-01 3.18804890e-01 4.70252812e-01
8.75496447e-01 4.68350947e-01 5.84599674e-01 -4.85838652e-02
6.45633638e-01 -1.56849232e-02 2.07455710e-01 7.98939884e-01
-1.81224138e-01 4.90033567e-01 1.12738895e+00 -4.81891513e-01
-1.06322324e+00 -1.11854351e+00 1.79507639e-02 1.64596844e+00
9.13323835e-02 -3.79888684e-01 -4.00314003e-01 -8.42434049e-01
7.80497417e-02 8.22695851e-01 -1.14445651e+00 5.69061041e-02
-6.14913285e-01 -1.74810156e-01 4.95580763e-01 8.97734940e-01
5.19107461e-01 -1.61966872e+00 -7.99224615e-01 5.45524284e-02
1.44859850e-02 -1.54483283e+00 -2.78646588e-01 1.52254522e-01
-2.69460768e-01 -1.13059914e+00 -4.69272047e-01 -9.52232242e-01
6.49714351e-01 -8.71936679e-02 1.18665469e+00 -3.40881974e-01
-8.03108811e-02 5.69286168e-01 -4.26767111e-01 -2.74344444e-01
-4.39779103e-01 -3.11608732e-01 -5.26553035e-01 4.99541909e-01
-7.25143701e-02 -5.16573787e-01 -5.35510421e-01 4.25842181e-02
-9.91339624e-01 6.24967277e-01 6.98253274e-01 7.36441493e-01
6.40770197e-01 -2.18587592e-01 3.65302712e-01 -1.09700072e+00
2.12370485e-01 -7.32199490e-01 -1.16777644e-01 5.57401478e-01
2.40617841e-02 3.24198693e-01 7.47335374e-01 -4.59328979e-01
-1.41456044e+00 1.80451393e-01 1.92635298e-01 -5.35842121e-01
-4.19452101e-01 3.24330717e-01 -4.83844489e-01 5.77631474e-01
3.77918124e-01 3.90201479e-01 -4.49142873e-01 -2.86577046e-01
1.03116941e+00 3.65305096e-01 7.50261724e-01 -5.03383994e-01
3.41468990e-01 7.95248032e-01 -4.09407588e-03 -6.16565466e-01
-1.19191158e+00 -5.62520981e-01 -4.10497546e-01 -3.86434257e-01
1.31443644e+00 -1.07473934e+00 -6.52422786e-01 3.42729121e-01
-1.32982075e+00 -5.32351255e-01 -3.70793164e-01 -2.44422168e-01
-5.94609499e-01 1.94080640e-02 -4.62718695e-01 -6.47172034e-01
-1.22555718e-01 -9.86439347e-01 1.35609019e+00 -1.72892094e-01
-1.24096498e-01 -1.03595662e+00 -5.69181144e-01 4.84646350e-01
2.18171582e-01 6.83102012e-01 1.17394710e+00 -6.86777055e-01
-5.54581940e-01 1.14386864e-01 -6.00513756e-01 2.49263018e-01
-2.09367275e-01 -3.57855827e-01 -1.15124643e+00 2.32115179e-01
-1.42210916e-01 -4.42637861e-01 9.97962832e-01 1.89157203e-01
1.30059588e+00 -5.17114401e-01 -3.24267715e-01 3.08464497e-01
1.53357697e+00 9.91993323e-02 6.61133587e-01 2.34105587e-01
9.80238974e-01 9.23524797e-01 2.76718140e-01 1.86441034e-01
4.84150440e-01 7.46570408e-01 5.93578815e-01 -8.71560201e-02
-5.08448541e-01 -6.48866415e-01 4.75950599e-01 -4.89316955e-02
1.43381029e-01 -2.49265701e-01 -9.24187005e-01 8.90354693e-01
-2.12884378e+00 -1.46502280e+00 -1.31000549e-01 1.57931411e+00
8.79510164e-01 2.52136230e-01 -3.43475118e-02 1.31314307e-01
6.74132943e-01 6.99362576e-01 -4.68569487e-01 -3.82752687e-01
-3.57867479e-01 -2.01803476e-01 2.13917136e-01 3.14716965e-01
-1.22282636e+00 1.03129685e+00 5.54996586e+00 1.05940413e+00
-1.02075660e+00 4.43602532e-01 7.24499643e-01 -2.89909303e-01
-4.19342846e-01 -5.29779494e-02 -6.94159031e-01 3.71034056e-01
8.09796631e-01 -1.78856142e-02 2.34887585e-01 8.84237230e-01
7.06353784e-02 -8.56787562e-02 -1.39337802e+00 1.15377784e+00
5.17052531e-01 -1.67798841e+00 3.08745414e-01 -2.13984415e-01
4.51493710e-01 -9.87480432e-02 1.66411906e-01 3.31242412e-01
8.65331516e-02 -1.16248536e+00 1.57006812e+00 3.94187540e-01
1.09449661e+00 -3.79682004e-01 4.19485450e-01 -1.64061524e-02
-1.31513286e+00 -4.95981783e-01 1.32453069e-01 -1.18873566e-01
3.60722035e-01 2.63837963e-01 -7.49685526e-01 2.62920260e-01
6.31866813e-01 1.10687852e+00 -5.96149802e-01 3.86822522e-01
-7.58227587e-01 6.01548374e-01 1.53733984e-01 3.13273631e-02
4.62010562e-01 3.69826049e-01 4.94894832e-01 1.44118929e+00
-2.40103871e-01 -1.53803736e-01 -8.51090923e-02 1.03494465e+00
-3.35085273e-01 -1.64670110e-01 -7.99697995e-01 -1.03052735e-01
1.34843796e-01 1.16813731e+00 -6.14965379e-01 -5.78573108e-01
-4.99537259e-01 1.14690733e+00 3.86000812e-01 4.37815756e-01
-9.48900998e-01 -5.68289645e-02 5.03999352e-01 2.58250684e-01
6.68179035e-01 4.16423902e-02 -2.21950829e-01 -9.30759370e-01
1.61202446e-01 -6.53106213e-01 5.39682925e-01 -1.41629052e+00
-1.12327933e+00 5.39872885e-01 3.60209435e-01 -9.56371605e-01
-8.29950124e-02 -9.31199431e-01 -4.24219310e-01 3.99935752e-01
-1.61880600e+00 -1.84174776e+00 -1.17055669e-01 6.94217324e-01
8.85240138e-01 -7.71866366e-02 6.67951941e-01 1.27684638e-01
-2.52460688e-01 2.16207579e-01 -3.77043664e-01 2.61824608e-01
5.19408047e-01 -1.47295928e+00 1.82949334e-01 7.64079213e-01
4.56745356e-01 3.83583695e-01 6.21606231e-01 -2.90560931e-01
-1.15840948e+00 -1.12394917e+00 1.16502726e+00 -8.09321821e-01
8.49188387e-01 -8.61178756e-01 -5.79167128e-01 8.84167850e-01
5.66755712e-01 3.07555318e-01 6.74628437e-01 -1.42309189e-01
-8.15938115e-01 -1.96417794e-01 -9.18239057e-01 7.43787229e-01
1.45482016e+00 -1.01150918e+00 -9.41259861e-01 1.28187239e-01
1.02244830e+00 -1.81166530e-01 -4.02804375e-01 -4.40529101e-02
6.12527192e-01 -9.01325464e-01 1.10594809e+00 -7.50106215e-01
1.00631201e+00 -2.85836965e-01 -4.70612139e-01 -9.53776240e-01
-2.91043609e-01 -3.97662073e-01 -2.08486006e-01 1.39424968e+00
6.30337536e-01 -2.70957768e-01 3.18927497e-01 4.12387431e-01
-2.21910954e-01 -6.70697093e-01 -9.13104296e-01 -3.62896800e-01
-3.23589027e-01 -7.64653444e-01 3.51677239e-01 9.12201524e-01
2.64867730e-02 6.91218197e-01 -3.34423184e-01 -4.47365269e-02
3.36419910e-01 4.73145247e-02 2.78468907e-01 -7.49681473e-01
-3.34174126e-01 -3.75703514e-01 -3.23834538e-01 -7.10426092e-01
6.22768521e-01 -1.04024410e+00 -1.98151156e-01 -1.86903274e+00
4.20136184e-01 -2.26328578e-02 -3.90501708e-01 9.69178677e-01
1.14619751e-02 3.68235648e-01 6.26982450e-01 3.18552628e-02
-1.10463309e+00 3.90908509e-01 1.11997175e+00 -3.86394680e-01
2.05903068e-01 -6.32559955e-01 -9.70166981e-01 6.66425169e-01
3.83668661e-01 -3.66381258e-01 -5.46582103e-01 -6.71497941e-01
6.86775565e-01 5.07406658e-03 7.89830625e-01 -7.58489728e-01
1.38989845e-02 -6.43858984e-02 4.21872079e-01 -1.68700978e-01
4.67617422e-01 -1.08908737e+00 -3.61677669e-02 1.57220110e-01
-8.59425843e-01 -1.67087719e-01 2.69280374e-01 8.19790840e-01
-3.42969269e-01 5.71825542e-02 3.71273905e-01 -2.55565464e-01
-1.37062848e+00 -3.52105275e-02 -3.37493181e-01 6.80899918e-02
1.13345027e+00 -2.83770144e-01 -5.68075359e-01 -4.83901769e-01
-8.76952052e-01 2.08732441e-01 2.53247410e-01 6.62852108e-01
5.81716537e-01 -1.32711565e+00 -7.25280225e-01 6.98632598e-02
6.56997442e-01 -2.27060750e-01 4.79342759e-01 5.87187946e-01
-8.73878971e-02 3.46042693e-01 -2.32258290e-01 -4.61642385e-01
-1.32686996e+00 6.02151096e-01 2.50512272e-01 -2.43272483e-01
-6.34855032e-01 7.57160544e-01 8.35859120e-01 -7.73196993e-03
1.68418229e-01 -3.74359965e-01 -5.14427364e-01 4.01368976e-01
7.91571438e-01 -1.30320564e-01 -2.81249881e-01 -1.03977263e+00
-4.62465763e-01 4.75642711e-01 1.02041341e-01 -3.03378582e-01
1.30222905e+00 3.98064442e-02 -6.98536187e-02 5.80753267e-01
1.34793890e+00 -1.86240584e-01 -1.57303584e+00 -7.97879696e-02
-1.03659347e-01 -2.56241798e-01 -7.62757286e-02 -1.30370963e+00
-8.88455689e-01 9.91367280e-01 2.14000002e-01 1.12135470e-01
1.12361693e+00 6.76304221e-01 2.26223379e-01 8.51269439e-02
2.54876763e-02 -8.76515746e-01 4.75605279e-01 3.98641557e-01
1.57544100e+00 -1.13581228e+00 -2.60962576e-01 -4.29391682e-01
-1.28962195e+00 8.47226322e-01 4.33137596e-01 2.35155765e-02
3.48297358e-01 2.35258192e-02 -3.10114976e-02 -3.27429026e-01
-1.10720909e+00 -3.66978079e-01 4.55570757e-01 7.73130119e-01
2.94492543e-01 5.72011247e-02 1.40839681e-01 7.23132133e-01
2.12835088e-01 -2.22444251e-01 2.84534574e-01 6.83549404e-01
-6.77807853e-02 -8.96311879e-01 -5.87169267e-02 1.11303411e-01
-6.09058499e-01 -2.49944657e-01 -4.00698751e-01 7.98161924e-01
5.61622143e-01 8.60940337e-01 2.91434050e-01 1.15043879e-01
3.56129259e-01 3.35779846e-01 4.75342453e-01 -8.19432259e-01
-7.30895460e-01 -2.42708951e-01 6.11496389e-01 -7.92203128e-01
-7.83842802e-01 -5.37156045e-01 -1.35805738e+00 2.53809392e-01
5.60028434e-01 -4.30546373e-01 6.65462852e-01 9.73099887e-01
3.67673308e-01 6.30019605e-01 2.00150311e-01 -7.31821835e-01
-9.93696302e-02 -7.68419862e-01 -3.73845249e-01 9.55710471e-01
4.70830828e-01 -5.39723575e-01 -2.84675628e-01 4.93199825e-01] | [10.543034553527832, 1.4296187162399292] |
27b7f301-6f62-42e6-a296-3c3d4d8e897c | on-training-deep-networks-for-satellite-image | 1906.06697 | null | https://arxiv.org/abs/1906.06697v1 | https://arxiv.org/pdf/1906.06697v1.pdf | On training deep networks for satellite image super-resolution | The capabilities of super-resolution reconstruction (SRR)---techniques for enhancing image spatial resolution---have been recently improved significantly by the use of deep convolutional neural networks. Commonly, such networks are learned using huge training sets composed of original images alongside their low-resolution counterparts, obtained with bicubic downsampling. In this paper, we investigate how the SRR performance is influenced by the way such low-resolution training data are obtained, which has not been explored up to date. Our extensive experimental study indicates that the training data characteristics have a large impact on the reconstruction accuracy, and the widely-adopted approach is not the most effective for dealing with satellite images. Overall, we argue that developing better training data preparation routines may be pivotal in making SRR suitable for real-world applications. | ['Szymon Piechaczek', 'Pawel Benecki', 'Krzysztof Hrynczenko', 'Jakub Nalepa', 'Daniel Kostrzewa', 'Michal Kawulok'] | 2019-06-16 | null | null | null | null | ['satellite-image-super-resolution'] | ['computer-vision'] | [ 4.29831982e-01 -2.89274037e-01 -2.63528097e-02 -2.23387361e-01
-6.55706584e-01 -7.50368461e-02 6.22035205e-01 -3.05470556e-01
-5.21761656e-01 9.89416957e-01 2.67749548e-01 -1.10142551e-01
-3.83333981e-01 -1.13837910e+00 -7.92092741e-01 -8.22913349e-01
-1.48626149e-01 7.47959837e-02 1.48103252e-01 -6.62950635e-01
2.37804011e-01 8.90739739e-01 -1.72584391e+00 2.50863761e-01
7.55073249e-01 9.34130609e-01 5.20404577e-01 6.04095578e-01
-1.30585104e-01 7.30263114e-01 -4.85002309e-01 1.26027986e-01
3.85049969e-01 -3.05191427e-01 -6.77506387e-01 -2.93898340e-02
2.67167866e-01 -5.65104127e-01 -2.83903152e-01 9.35910821e-01
5.37647188e-01 6.78400993e-02 4.21668500e-01 -1.33052409e-01
-7.33970106e-01 5.01733303e-01 -6.61655009e-01 6.48132503e-01
8.72254521e-02 -1.89385191e-01 5.37272513e-01 -9.94824111e-01
6.51833117e-01 9.63151813e-01 9.98455942e-01 3.75470459e-01
-1.37547362e+00 -5.91921866e-01 -4.14086312e-01 1.12485945e-01
-1.46740544e+00 -5.48640072e-01 7.38849461e-01 -2.46766165e-01
5.17055154e-01 2.56131887e-01 3.41371387e-01 8.41932774e-01
1.47201065e-02 -4.08177711e-02 1.51707125e+00 -5.39093971e-01
5.40178157e-02 1.58407748e-01 -3.40167612e-01 1.00184426e-01
4.10589397e-01 2.94358581e-01 -2.88177282e-01 3.19570869e-01
1.40932727e+00 -2.84525961e-01 -5.86564720e-01 -1.88387096e-01
-8.64338219e-01 6.61795318e-01 7.60432720e-01 8.10699821e-01
-5.39341569e-01 -1.57226250e-02 2.55239189e-01 4.64486420e-01
7.75429308e-01 5.80620646e-01 -2.97484636e-01 1.70133397e-01
-1.21366572e+00 1.11398846e-01 1.46064788e-01 3.73505801e-01
7.63687015e-01 2.99672365e-01 3.99601251e-01 9.74046230e-01
-2.77076662e-01 1.24461144e-01 4.58114475e-01 -9.04931366e-01
1.74870893e-01 4.03013915e-01 3.99213344e-01 -9.48182106e-01
-4.11892653e-01 -6.36184812e-01 -1.18676567e+00 4.88360226e-01
5.92094719e-01 8.99467021e-02 -5.93779922e-01 1.30491138e+00
2.10574448e-01 1.14368178e-01 3.13187659e-01 1.16075242e+00
9.16892409e-01 6.35241807e-01 -9.01581347e-02 -1.97626352e-01
1.18259168e+00 -3.31217945e-01 -7.39849985e-01 -1.08317815e-01
1.44127131e-01 -6.97216928e-01 1.10570920e+00 3.87050599e-01
-1.06549287e+00 -8.75935674e-01 -1.16389012e+00 -1.39048621e-01
-3.86675358e-01 3.16070139e-01 3.34536046e-01 3.69563580e-01
-1.05117285e+00 1.07112670e+00 -3.71530563e-01 -3.49636286e-01
5.40412366e-01 1.33479908e-01 -6.78321242e-01 -2.22997367e-01
-1.33744538e+00 1.14889014e+00 4.41166461e-01 3.80175769e-01
-6.42239690e-01 -7.04016864e-01 -4.97214049e-01 1.16483420e-01
1.46288097e-01 -3.18628550e-01 8.31757247e-01 -1.00644553e+00
-1.45311296e+00 8.19542825e-01 2.39594072e-01 -5.37018597e-01
5.45010269e-01 -1.71264365e-01 -4.62248027e-01 3.20852369e-01
-1.53173521e-01 3.33502561e-01 1.01831424e+00 -1.58686483e+00
-5.26772082e-01 -5.43603957e-01 4.54585925e-02 1.64980337e-01
-2.69252717e-01 2.33745202e-01 1.13689438e-01 -6.44486427e-01
1.98082298e-01 -4.27157730e-01 -4.65743750e-01 -5.32954298e-02
2.71844119e-01 3.18390816e-01 7.89977491e-01 -8.97724390e-01
9.07305598e-01 -2.19114852e+00 2.87806801e-02 -7.73071349e-02
6.28110990e-02 4.91963476e-01 -1.41187245e-03 2.22227558e-01
-3.47347766e-01 2.60329306e-01 -1.28045350e-01 7.20125288e-02
-6.01352036e-01 4.62780818e-02 -3.26842934e-01 6.15732789e-01
3.23633403e-01 5.87403119e-01 -5.13248026e-01 -3.22944880e-01
5.50864875e-01 1.12523437e+00 -7.79059380e-02 1.61994219e-01
6.34692460e-02 8.81374598e-01 -3.72343242e-01 2.14900449e-01
1.12746298e+00 -3.07386488e-01 1.22785017e-01 -2.36833498e-01
-4.93542433e-01 3.61985154e-02 -1.17696393e+00 1.44485497e+00
-7.05427706e-01 7.35513330e-01 2.07078859e-01 -9.51177895e-01
1.25371206e+00 2.05082074e-01 4.84764040e-01 -1.05905628e+00
-1.48698492e-02 2.75574565e-01 -1.88382715e-01 -4.15101498e-01
8.69820714e-01 -3.97064716e-01 5.33956528e-01 5.40538644e-03
-3.07234675e-01 3.29269990e-02 -9.84093621e-02 -3.60068530e-01
5.07734358e-01 2.57907510e-01 4.09203053e-01 -4.26397681e-01
7.19164431e-01 2.10921675e-01 2.77411371e-01 6.39752090e-01
1.96016699e-01 9.36620891e-01 1.58166707e-01 -6.59541845e-01
-1.48273981e+00 -6.56532347e-01 -6.93282664e-01 7.81630158e-01
4.52852584e-02 1.75922588e-02 -7.75730968e-01 9.14021675e-03
-4.55933750e-01 4.29302752e-01 -6.30129337e-01 2.75979817e-01
-7.71345496e-01 -9.82759655e-01 3.70829940e-01 4.75484073e-01
7.22044468e-01 -1.05433047e+00 -9.94689286e-01 2.66220033e-01
-1.46087363e-01 -1.35499680e+00 3.02781671e-01 1.62652284e-01
-1.29867887e+00 -8.47655416e-01 -1.05236137e+00 -3.64944071e-01
4.12305117e-01 5.11592209e-01 1.10222256e+00 2.40216210e-01
-2.82089770e-01 -1.60702765e-01 -5.86218238e-01 5.20195998e-02
-4.14392769e-01 1.71844110e-01 -2.24597111e-01 -6.87820315e-02
7.60765094e-03 -7.88313985e-01 -6.95721745e-01 1.58893302e-01
-1.09966755e+00 -2.95012090e-02 7.77944624e-01 6.55796349e-01
5.93304038e-01 5.14563799e-01 6.03722155e-01 -8.42863798e-01
3.94235164e-01 -2.25128368e-01 -6.38875663e-01 -6.98252320e-02
-4.88252878e-01 9.37111583e-03 9.69866216e-01 -1.75836056e-01
-1.28990674e+00 -2.03511477e-01 -4.39377725e-01 -3.19435924e-01
-5.38735390e-01 4.45841402e-01 1.89175755e-01 -4.44335788e-01
9.78830695e-01 3.67303967e-01 4.94049862e-02 -8.75848472e-01
1.62036270e-01 6.68449104e-01 5.91982424e-01 -4.08762753e-01
8.36455941e-01 8.33404243e-01 1.94465950e-01 -1.25265479e+00
-6.88734055e-01 -3.80967855e-01 -6.91830993e-01 -1.31242722e-01
8.90033305e-01 -1.05396163e+00 1.78323407e-02 3.47990543e-01
-8.19785774e-01 -3.63211870e-01 -3.76751810e-01 4.96730655e-01
-3.65936816e-01 3.72328460e-01 -4.07167971e-01 -7.04196334e-01
-3.11773837e-01 -1.12853050e+00 9.14472699e-01 3.59949201e-01
3.73023003e-01 -7.13507414e-01 -6.16701506e-02 3.78071874e-01
1.11930823e+00 2.70490944e-01 6.81315720e-01 -9.55881774e-02
-5.71784675e-01 1.93059936e-01 -6.38989866e-01 2.92193234e-01
2.08071917e-02 -1.12721704e-01 -1.09289432e+00 -3.87059033e-01
1.93848073e-01 -2.42558792e-01 8.99943531e-01 6.08735144e-01
1.35614049e+00 5.17270267e-02 1.69018149e-01 8.26749563e-01
1.96699905e+00 -2.72656292e-01 1.20614457e+00 8.41365337e-01
3.63717020e-01 6.68023765e-01 6.71561897e-01 5.21484733e-01
5.95874973e-02 8.42364609e-01 5.77104628e-01 -3.30631733e-01
-3.73220861e-01 1.72699571e-01 6.27147481e-02 2.68571585e-01
-7.15028167e-01 2.70678759e-01 -5.77872694e-01 4.15149152e-01
-1.37375700e+00 -1.11757767e+00 -3.16745609e-01 2.24763846e+00
6.44537508e-01 -1.30754277e-01 -6.41358504e-03 3.17742139e-01
5.89446902e-01 4.41446960e-01 -2.25718051e-01 -9.14062336e-02
-3.39273900e-01 4.74680245e-01 5.94370246e-01 4.13726658e-01
-1.02804732e+00 6.57686174e-01 6.25499344e+00 6.70723557e-01
-1.48138773e+00 1.00061826e-01 5.65530956e-01 1.75861821e-01
-1.17564149e-01 -2.18620837e-01 -5.75290084e-01 2.90256023e-01
1.08916020e+00 1.82152972e-01 4.45077449e-01 7.73283780e-01
5.60177743e-01 -1.70148715e-01 -4.38374817e-01 8.36943090e-01
-2.36837462e-01 -1.38922572e+00 -7.46272653e-02 1.47078693e-01
6.22733533e-01 3.46148312e-02 1.77685186e-01 5.97158484e-02
-1.10091962e-01 -1.31788778e+00 3.97745103e-01 4.99384403e-01
1.08817112e+00 -8.52060020e-01 9.05081928e-01 2.03396991e-01
-1.22118354e+00 -1.24865107e-01 -8.58572066e-01 3.00491452e-02
-9.62347817e-03 7.37393439e-01 -3.43562633e-01 8.19903970e-01
1.11891115e+00 3.98039371e-01 -7.21553564e-01 7.76295245e-01
4.95622195e-02 3.98084402e-01 -1.16779588e-01 5.64698458e-01
6.83851764e-02 -3.73052925e-01 4.44766283e-01 1.08585131e+00
4.86204088e-01 2.94975102e-01 -3.88910532e-01 8.30943108e-01
1.46432742e-01 1.97556436e-01 -6.65628076e-01 1.98574886e-01
3.02049071e-01 1.31752157e+00 -6.76658511e-01 -7.26192892e-02
-4.71998900e-01 5.99643052e-01 2.28049442e-01 3.17091972e-01
-6.01532161e-01 -2.53769029e-02 4.85261142e-01 6.53971076e-01
5.54940820e-01 -1.73475668e-01 -4.75423157e-01 -1.09466970e+00
-1.07939303e-01 -1.02042282e+00 2.17604741e-01 -1.11138999e+00
-1.04229808e+00 8.80127907e-01 4.00531515e-02 -1.21072710e+00
-8.31199810e-02 -5.42129219e-01 -4.20985699e-01 1.01664793e+00
-1.99846363e+00 -9.87796903e-01 -5.60814023e-01 4.27666694e-01
5.42415261e-01 1.63227953e-02 7.02854335e-01 3.96275997e-01
-4.18927819e-01 7.23546669e-02 3.86124134e-01 -9.23323631e-02
3.97903919e-01 -9.52959657e-01 6.60042018e-02 1.01162469e+00
-1.89780608e-01 4.58555639e-01 1.06886971e+00 -2.39305034e-01
-1.11659217e+00 -1.01817870e+00 5.21429121e-01 3.27494703e-02
2.92953491e-01 2.31425002e-01 -1.39121640e+00 3.55269164e-01
1.09999858e-01 3.47528785e-01 3.35898608e-01 3.57911214e-02
-1.31427824e-01 -2.93913513e-01 -1.38825822e+00 3.27938527e-01
8.29210699e-01 -4.86560285e-01 -5.19596934e-01 -2.46357381e-01
3.40472728e-01 -3.06867957e-01 -1.27630949e+00 6.18029118e-01
3.91342431e-01 -1.38002658e+00 1.36329663e+00 -2.42201194e-01
8.72022748e-01 -3.74516338e-01 -2.56406307e-01 -1.24641001e+00
-4.92826790e-01 2.67587483e-01 1.87098101e-01 8.65604162e-01
6.58202469e-02 -5.30984879e-01 7.63243675e-01 9.78092253e-02
1.68256730e-01 -5.06696939e-01 -8.89638722e-01 -6.01478100e-01
1.95300892e-01 -4.92996722e-02 8.64637136e-01 1.05037344e+00
-7.22406566e-01 2.55393069e-02 -5.22591829e-01 3.80643219e-01
6.95670545e-01 1.96847811e-01 7.59072185e-01 -1.36396742e+00
2.67291218e-02 -3.65000248e-01 -1.17276609e-01 -5.44060290e-01
-1.62633613e-01 -3.31532627e-01 -1.16212860e-01 -1.44447601e+00
8.29626247e-02 -5.47244668e-01 -2.51857638e-01 3.59799042e-02
-7.34887272e-02 6.99093103e-01 -1.48746558e-02 4.03121352e-01
-3.40805985e-02 4.40959156e-01 1.39352059e+00 4.39554930e-01
-1.16194718e-01 -1.37927115e-01 -6.64917469e-01 6.17824972e-01
9.62370813e-01 -2.77799040e-01 -1.53249338e-01 -4.57949132e-01
2.15826705e-01 2.85163730e-01 3.86122018e-01 -1.20446277e+00
-1.65532604e-01 -4.68847491e-02 6.83389187e-01 -4.87324297e-01
3.96700531e-01 -9.58312035e-01 6.00606620e-01 1.68540880e-01
-2.63066947e-01 -2.05031205e-02 1.17985062e-01 3.09035569e-01
-2.74278194e-01 -4.04023051e-01 1.31888020e+00 -5.46903074e-01
-9.82243478e-01 4.31963988e-02 -1.74744517e-01 -3.92395228e-01
5.97429335e-01 -3.40555519e-01 -1.55938879e-01 -2.66766280e-01
-5.41066885e-01 -5.16443551e-01 7.29263246e-01 1.05642378e-01
5.45399785e-01 -1.09106314e+00 -9.81790543e-01 1.05503425e-01
-1.15500443e-01 2.65870482e-01 4.74292487e-01 6.77678347e-01
-9.02699828e-01 2.06908524e-01 -6.24345183e-01 -4.48266774e-01
-1.17916000e+00 4.65908647e-01 4.58795786e-01 -4.65063602e-01
-1.06345546e+00 3.53788406e-01 -1.10858440e-01 -4.05871153e-01
-1.57015353e-01 -9.53982398e-02 -6.63994908e-01 -2.24339776e-02
8.04831862e-01 4.52740192e-01 2.29843378e-01 -7.86548376e-01
-4.07986604e-02 7.71999776e-01 4.11909297e-02 5.00139333e-02
1.92905092e+00 -3.33293527e-01 -1.74698070e-01 1.05904348e-01
7.44641542e-01 -1.71307236e-01 -1.22320449e+00 -2.96868294e-01
-1.38271660e-01 -8.36578548e-01 5.16887426e-01 -4.04934645e-01
-1.27058530e+00 8.22567403e-01 8.11138332e-01 3.32491070e-01
1.40057433e+00 -3.52042437e-01 4.27450299e-01 1.45219654e-01
5.24718702e-01 -9.62468088e-01 -8.72271881e-02 1.84369579e-01
1.08087349e+00 -1.40370560e+00 3.14599127e-01 -1.52127773e-01
-3.20440680e-01 1.26807117e+00 3.86050165e-01 -2.63656020e-01
4.39504713e-01 3.64796847e-01 -4.91788611e-02 -7.52574205e-02
-3.72062922e-01 -3.44416857e-01 -7.89502412e-02 6.08826458e-01
5.28585076e-01 -9.85882729e-02 -3.40169281e-01 2.08270997e-01
-8.47532153e-02 5.16050637e-01 7.32507467e-01 4.74427491e-01
-5.22135079e-01 -8.85693908e-01 -8.84769857e-01 2.95665234e-01
-6.97342634e-01 -2.85706725e-02 6.12051450e-02 9.58659887e-01
7.79737681e-02 5.99823236e-01 7.28172297e-03 -1.85931489e-01
2.75536060e-01 -3.14990073e-01 5.40023565e-01 -2.72026241e-01
-3.77954841e-01 -1.47210807e-01 2.51706298e-02 -4.29827273e-01
-7.56321073e-01 -5.03594875e-01 -8.50718498e-01 -5.89755774e-01
-2.67647505e-01 -1.69805475e-02 7.34293163e-01 7.49328315e-01
1.22592479e-01 5.93647659e-01 5.66804826e-01 -1.29149616e+00
-6.89159989e-01 -1.06144142e+00 -6.40514255e-01 1.86755225e-01
4.41751212e-01 -6.56460464e-01 -3.82844836e-01 -2.15861320e-01] | [10.490184783935547, -1.9518300294876099] |
1c789cb0-c14d-4ea5-b44e-c2bb1f124986 | asymmetric-quantum-decision-making | 2305.02117 | null | https://arxiv.org/abs/2305.02117v1 | https://arxiv.org/pdf/2305.02117v1.pdf | Asymmetric quantum decision-making | Collective decision-making is crucial to information and communication systems. Decision conflicts among agents hinder the maximization of potential utilities of the entire system. Quantum processes can realize conflict-free joint decisions among two agents using the entanglement of photons or quantum interference of orbital angular momentum (OAM). However, previous studies have always presented symmetric resultant joint decisions. Although this property helps maintain and preserve equality, it cannot resolve disparities. Global challenges, such as ethics and equity, are recognized in the field of responsible artificial intelligence as responsible research and innovation paradigm. Thus, decision-making systems must not only preserve existing equality but also tackle disparities. This study theoretically and numerically investigates asymmetric collective decision-making using quantum interference of photons carrying OAM or entangled photons. Although asymmetry is successfully realized, a photon loss is inevitable in the proposed models. The available range of asymmetry and method for obtaining the desired degree of asymmetry are analytically formulated. | ['Makoto Naruse', 'Ryoichi Horisaki', 'Tomoki Yamagami', 'Guillaume Bachelier', 'Jonathan Laurent', 'Etsuo Segawa', 'Nicolas Chauvet', 'André Röhm', 'Hiroaki Shinkawa', 'Honoka Shiratori'] | 2023-05-03 | null | null | null | null | ['ethics'] | ['miscellaneous'] | [ 1.63043365e-01 3.17024410e-01 -1.99640751e-01 3.96212414e-02
5.70746899e-01 -4.30147707e-01 7.61996090e-01 -1.53319001e-01
-8.27404380e-01 1.35443950e+00 -2.59582121e-02 -3.51846933e-01
-6.54030204e-01 -9.84521627e-01 1.22182578e-01 -1.19286549e+00
1.17629431e-01 2.92451710e-01 -4.62687194e-01 -3.16328019e-01
8.44925284e-01 4.14955050e-01 -1.58556402e+00 -3.54662776e-01
1.27602172e+00 6.85386419e-01 -2.46035576e-01 5.13116241e-01
2.37561800e-02 8.87745082e-01 -5.99979460e-01 -4.71582741e-01
5.36327899e-01 -6.97488844e-01 -7.82388866e-01 -2.81898588e-01
-4.60859716e-01 -4.46404010e-01 -3.83887172e-01 1.39955473e+00
3.86268198e-01 -1.61908492e-02 1.01963103e+00 -1.66106641e+00
-1.05418098e+00 5.17411947e-01 -3.24785262e-01 1.17466003e-01
1.29478708e-01 4.33127105e-01 8.01463425e-01 -6.64899424e-02
6.87185705e-01 8.55640471e-01 -1.13203347e-01 7.81948745e-01
-1.03578830e+00 -6.62007391e-01 -7.60308862e-01 5.71153700e-01
-1.43235278e+00 -4.28396732e-01 5.96060932e-01 -3.36837590e-01
9.34828401e-01 5.34262896e-01 9.10301626e-01 5.19547760e-01
1.07245386e+00 -4.48153391e-02 1.61178052e+00 -6.78779244e-01
4.57461596e-01 7.95995146e-02 -3.95444259e-02 1.12618096e-01
9.84403193e-01 6.50696814e-01 -7.56247461e-01 -5.32404706e-02
5.98134756e-01 -2.90730387e-01 1.84485447e-02 -2.12162454e-02
-1.63584340e+00 4.22567129e-01 3.24012071e-01 4.83897328e-01
-8.73551548e-01 1.08116604e-01 -5.18187821e-01 6.06188655e-01
-1.57302395e-01 7.46058762e-01 1.47089884e-01 -1.96481273e-01
-2.35601261e-01 2.13454247e-01 9.65850830e-01 4.29007202e-01
7.54719198e-01 -1.61521152e-01 -3.29750925e-01 -2.76273757e-01
5.17411768e-01 8.07856500e-01 -4.34496216e-02 -1.44099498e+00
1.19323485e-01 5.43898523e-01 6.00767493e-01 -1.12751245e+00
-5.70221364e-01 -4.38678354e-01 -1.08146060e+00 6.86023295e-01
4.62639838e-01 -4.81402159e-01 -2.01545283e-01 1.65781474e+00
2.90619999e-01 -6.50809765e-01 6.96942210e-01 9.79867160e-01
4.19508308e-01 4.65631396e-01 2.77380794e-02 -7.84537435e-01
1.24011028e+00 -4.58493441e-01 -1.34396160e+00 1.84009541e-02
3.37160975e-01 -8.46520603e-01 -1.19062074e-01 3.53648141e-02
-1.05796325e+00 2.58673489e-01 -9.15773630e-01 2.20142946e-01
-1.07280537e-02 -3.62539738e-01 1.18516338e+00 9.17195022e-01
-9.20546234e-01 4.08685863e-01 -5.87354839e-01 -1.99789211e-01
3.43191862e-01 4.88970846e-01 -2.67220318e-01 4.08722043e-01
-1.12177861e+00 1.29755688e+00 5.67630008e-02 2.59689271e-01
-1.60014585e-01 -5.94278537e-02 -7.47752702e-03 -1.42007232e-01
5.98628819e-02 -1.25493920e+00 9.03581023e-01 -8.29064846e-01
-1.94405198e+00 7.76656270e-01 1.25207528e-01 -2.88227111e-01
5.62326491e-01 5.50910592e-01 -3.54762822e-01 1.50830597e-01
3.39710712e-01 5.85598826e-01 2.13485554e-01 -8.31348240e-01
-6.62251294e-01 -4.64019954e-01 3.40517938e-01 6.80506349e-01
-1.10215373e-01 -1.29744887e-01 7.84177721e-01 1.24495670e-01
5.25638998e-01 -1.05066121e+00 -2.21254334e-01 -2.73662955e-01
-7.01160431e-01 -3.44591528e-01 1.91279083e-01 6.62225708e-02
7.60644317e-01 -1.67183614e+00 5.11750132e-02 -2.98390118e-03
3.01567793e-01 -2.96504259e-01 1.07030869e-01 8.89756560e-01
5.54772079e-01 3.01432103e-01 9.51795503e-02 2.08345950e-01
2.61901051e-01 1.42546847e-01 2.25320071e-01 7.54337251e-01
8.05635229e-02 8.21795642e-01 -6.23107076e-01 -2.76456445e-01
-3.02355289e-02 -1.61699150e-02 -5.75118244e-01 -1.74900800e-01
3.57987493e-01 7.80126512e-01 -7.08234966e-01 7.40641534e-01
8.71592343e-01 -1.53113723e-01 5.30914962e-01 -1.21058859e-01
-9.23506379e-01 2.82083333e-01 -1.10974753e+00 1.02801442e+00
1.08587876e-01 6.46078765e-01 1.43395364e-01 -7.77085245e-01
5.09747326e-01 2.09926069e-01 5.81194282e-01 -1.22099125e+00
4.05174494e-01 5.00635862e-01 9.91602600e-01 -4.34595883e-01
7.74993241e-01 -5.81458986e-01 -1.88928977e-01 9.38864172e-01
-2.33121961e-01 -3.36011112e-01 2.87536919e-01 4.53742482e-02
8.40496898e-01 -2.69552946e-01 6.52763188e-01 -5.54664135e-01
3.66859525e-01 9.49396268e-02 6.77207768e-01 7.83713222e-01
-8.38082850e-01 -2.49690756e-01 5.46403408e-01 -4.43056941e-01
-8.18688989e-01 -8.94560039e-01 -3.73662382e-01 2.82215595e-01
1.27437413e+00 1.95428520e-01 -3.04731131e-01 1.92859441e-01
8.15482158e-03 9.75386322e-01 -2.35554606e-01 -1.21727601e-01
2.99998168e-02 -1.27384913e+00 4.09735292e-01 -4.14397031e-01
9.71423864e-01 -1.04197335e+00 -1.03523183e+00 1.34553596e-01
-1.50516853e-01 -9.86802280e-01 3.06535363e-01 8.49836096e-02
-4.71867472e-01 -1.06316423e+00 -2.40948007e-01 -8.08635503e-02
7.35563040e-01 4.02279198e-01 6.56255722e-01 1.76581740e-01
-6.56704828e-02 2.20275626e-01 -1.23601206e-01 -3.86630893e-01
-6.50235474e-01 -4.70078349e-01 6.60770774e-01 -9.70005542e-02
4.57730085e-01 -6.59262359e-01 -8.26961279e-01 1.72072157e-01
-4.41606075e-01 3.95361364e-01 8.40239465e-01 4.14116144e-01
-8.30741017e-04 4.20515060e-01 3.88832301e-01 1.83229536e-01
7.35708177e-01 -2.27758691e-01 -4.92189616e-01 1.91141963e-01
-6.91618621e-01 1.34943962e-01 1.60671651e-01 3.48255992e-01
-1.31159246e+00 -8.69119823e-01 6.27533197e-01 8.47161651e-01
-2.59204626e-01 2.66629785e-01 2.40153164e-01 -5.50700784e-01
3.49165618e-01 4.40602191e-03 1.69573039e-01 2.61446089e-01
2.69475281e-01 8.19702327e-01 -3.92262675e-02 -2.57393658e-01
6.71461880e-01 7.61316121e-01 8.63126755e-01 -7.86946416e-01
-1.52073860e-01 2.47970536e-01 -3.36147487e-01 -4.64923471e-01
1.02485394e+00 -4.21728224e-01 -1.51477516e+00 8.67592990e-01
-1.38818526e+00 3.63527328e-01 -2.52570927e-01 1.11744487e+00
-2.57292926e-01 3.42311114e-01 -4.35588330e-01 -1.46220493e+00
-8.46818089e-02 -1.08544528e+00 2.21357182e-01 8.07317734e-01
1.08505890e-01 -5.93027353e-01 1.27131417e-01 6.22692585e-01
7.09457397e-01 -1.70171913e-02 5.24627149e-01 -2.14762896e-01
-1.29038417e+00 -6.79252222e-02 -2.68336952e-01 -2.49415547e-01
3.33924115e-01 8.87271762e-02 -6.41068578e-01 1.53592572e-01
-6.68676198e-03 -1.34354785e-01 4.65400875e-01 3.97571981e-01
-1.88698068e-01 -3.22216988e-01 -1.93356395e-01 1.13746323e-01
1.06793499e+00 6.24997497e-01 7.04107642e-01 7.91769922e-01
-5.02723735e-03 1.07204127e+00 3.77595335e-01 7.69424021e-01
7.63842225e-01 5.38481772e-01 5.92760801e-01 4.11425680e-01
2.26199150e-01 5.77339351e-01 1.34058207e-01 7.67842352e-01
-1.04350710e+00 -2.26603180e-01 -7.80304551e-01 3.04117538e-02
-1.57940447e+00 -1.27532566e+00 -5.06862283e-01 2.24780893e+00
5.68251669e-01 -3.17996621e-01 -4.26577270e-01 -1.29315089e-02
7.48093963e-01 -1.95789829e-01 -3.69433939e-01 -4.54154551e-01
-6.68523371e-01 -3.96079779e-01 6.13724351e-01 5.55232942e-01
-7.20211625e-01 5.27992606e-01 6.42527390e+00 4.18607205e-01
-9.98776138e-01 1.71708331e-01 3.29226106e-01 -1.82390198e-01
-7.47852147e-01 5.40021002e-01 -4.13297147e-01 3.93270165e-01
3.89924556e-01 -7.59297907e-01 5.79487503e-01 -8.19740072e-02
3.63976866e-01 -1.00549912e+00 -5.89414179e-01 8.31984818e-01
-5.78135490e-01 -1.26507092e+00 -1.46893874e-01 7.23670304e-01
1.03845918e+00 -4.16506797e-01 -2.26794332e-02 -1.06550857e-01
5.47102652e-02 -8.75100851e-01 7.90817082e-01 9.20960367e-01
3.69658381e-01 -6.63838863e-01 1.02788746e+00 6.26146138e-01
-4.29572940e-01 -1.58174098e-01 -2.39832237e-01 -1.08030403e+00
3.64189237e-01 7.41895616e-01 -2.70287246e-01 8.62115383e-01
1.48082614e-01 1.22126788e-01 4.09763269e-02 7.19090581e-01
-3.33372504e-01 -1.87001973e-01 -5.52509129e-01 -5.83961010e-01
1.07667156e-01 -1.13057041e+00 9.69048381e-01 1.75004542e-01
5.13530850e-01 3.10858637e-01 -4.92089927e-01 1.28469205e+00
2.15486318e-01 -4.03128639e-02 -6.31435692e-01 -7.27358937e-01
6.59251392e-01 1.13519132e+00 -8.14669549e-01 1.08009838e-01
-2.13352423e-02 8.18996251e-01 -9.19005573e-02 2.90784150e-01
-4.51824844e-01 -1.44332960e-01 1.09013820e+00 -5.41820049e-01
-5.05263090e-01 -4.75068748e-01 -6.24431491e-01 -1.32802403e+00
-1.50533825e-01 -2.10099161e-01 -2.69655317e-01 -3.66627604e-01
-1.09319341e+00 1.29360572e-01 -2.49398977e-01 -1.19380283e+00
-6.27819821e-02 -2.80919939e-01 -6.94965363e-01 8.18578780e-01
-1.59548581e+00 -8.57390523e-01 -6.09000251e-02 8.24803263e-02
-4.57931936e-01 -2.43094772e-01 7.55371273e-01 -3.29684429e-02
-7.99759567e-01 -3.38711105e-02 3.87489080e-01 -4.58613724e-01
3.50427210e-01 -8.87312710e-01 -4.67132777e-01 7.95292139e-01
-2.82946587e-01 7.37338841e-01 1.02549493e+00 -6.41362727e-01
-1.72400451e+00 -3.35771069e-02 1.14465880e+00 -1.30498886e-01
5.29820085e-01 3.29598457e-01 1.42304227e-01 -5.15033677e-02
8.17584932e-01 -4.44260418e-01 8.84238601e-01 -3.95097844e-02
2.95958281e-01 8.25990662e-02 -1.17212701e+00 9.73156631e-01
1.10307670e+00 -4.19329941e-01 -5.58678627e-01 3.28761399e-01
1.20375760e-01 2.58342564e-01 -4.89810914e-01 2.95951933e-01
8.63100469e-01 -1.53566587e+00 6.83805645e-01 -4.30487186e-01
2.06317753e-01 -4.82494235e-01 -2.34259695e-01 -1.12359941e+00
-2.63753414e-01 -8.39387715e-01 6.18414938e-01 7.73094594e-01
1.35054708e-01 -1.36388445e+00 5.54827213e-01 9.87953961e-01
3.34882379e-01 -6.54912069e-02 -1.50331795e+00 -8.20690334e-01
2.29794830e-01 -1.02645002e-01 4.70371217e-01 1.12682188e+00
4.69420463e-01 5.50042540e-02 -3.59973937e-01 2.47569472e-01
1.22536719e+00 2.18128249e-01 5.30597270e-01 -1.21743083e+00
1.88221946e-01 -8.12090993e-01 -6.83796704e-01 -5.05969584e-01
-4.75346902e-03 -7.03664362e-01 -3.51291865e-01 -1.74118853e+00
2.60369897e-01 -4.19739842e-01 -2.25177780e-01 -2.16767900e-02
1.75430074e-01 1.21936932e-01 4.57770795e-01 8.12059879e-01
-5.36574483e-01 9.07126486e-01 1.71528316e+00 8.56221691e-02
-2.72461355e-01 -2.26215944e-01 -6.90714955e-01 5.24232507e-01
9.28818762e-01 -5.02267361e-01 4.72905748e-02 -1.19929686e-01
8.31293523e-01 1.61291689e-01 4.28290337e-01 -1.00469065e+00
7.65235066e-01 -8.24544311e-01 -3.89196903e-01 -1.92651421e-01
3.50537121e-01 -5.38975120e-01 6.37409568e-01 9.64472651e-01
6.27194420e-02 -4.10050511e-01 -4.75363195e-01 3.23800176e-01
-6.71283007e-02 -3.99450123e-01 4.71626908e-01 -1.44643515e-01
-6.47155285e-01 -1.90866277e-01 -1.01259995e+00 -5.55709839e-01
1.52834857e+00 -2.45914474e-01 -1.09619296e+00 -2.98333555e-01
-2.49678403e-01 1.79642051e-01 7.23266244e-01 -9.28356946e-02
8.73819813e-02 -1.17213976e+00 -6.26678824e-01 -7.72096813e-02
-2.63329685e-01 -6.24655545e-01 4.92842227e-01 1.30255818e+00
-8.96129847e-01 8.70907247e-01 -8.54085863e-01 -1.74478263e-01
-8.00968528e-01 2.37152241e-02 4.93606806e-01 -2.38228496e-03
1.23733416e-01 5.68976700e-01 1.60841420e-01 -3.47193986e-01
-5.85586309e-01 1.22190952e-01 -3.93359721e-01 1.88800484e-01
3.18302870e-01 5.92762768e-01 -5.44392049e-01 -7.31909573e-01
-7.03103542e-01 6.19025350e-01 5.43817341e-01 -4.64365542e-01
9.17332947e-01 -6.65574372e-01 -7.16564655e-01 -8.24265741e-03
3.50381881e-01 2.58178085e-01 -8.12330484e-01 3.70837837e-01
-2.99343288e-01 -5.43839157e-01 2.54519075e-01 -7.02744186e-01
-4.08481628e-01 4.92692858e-01 2.66679317e-01 9.38045681e-01
7.97875047e-01 -2.00098708e-01 7.81044886e-02 7.63048947e-01
9.38480318e-01 -1.21823728e+00 -1.99589923e-01 3.18832576e-01
5.97340286e-01 -1.17956972e+00 1.33412421e-01 -5.44602275e-01
-6.02031469e-01 1.10205626e+00 4.08507794e-01 1.71104372e-01
4.78540510e-01 -9.27632451e-02 -4.18379083e-02 -9.48044732e-02
-7.93870986e-01 -5.27757704e-01 -1.86735615e-01 8.10045302e-01
2.67277420e-01 5.82869887e-01 -1.26736760e+00 4.48218733e-01
-1.60888419e-01 1.14869259e-01 1.04349041e+00 1.10142934e+00
-4.06796277e-01 -1.24629247e+00 -5.63814402e-01 3.44486758e-02
-2.71268815e-01 -3.77268232e-02 -4.43968385e-01 7.01238692e-01
5.02726078e-01 1.38040340e+00 1.81550696e-01 -9.90411937e-02
6.02077730e-02 -2.87272483e-01 6.73627794e-01 3.53368409e-02
-1.05068944e-01 -3.97949010e-01 4.68645960e-01 -2.79819876e-01
-1.16856456e+00 -7.60004461e-01 -1.21823347e+00 -9.81729865e-01
-3.39444727e-01 4.07691240e-01 7.83625722e-01 1.17803180e+00
6.60493791e-01 2.84641445e-01 5.78022599e-01 -4.45832580e-01
-6.91832423e-01 -7.61710942e-01 -1.10249507e+00 1.85460821e-02
1.10536516e-01 -9.37804341e-01 -7.62764812e-01 -5.94212592e-01] | [5.584012508392334, 4.788204669952393] |
2169cf63-6e83-47f6-84bb-2cfb7a548f68 | a-novel-viewport-adaptive-motion-compensation | 2202.13892 | null | https://arxiv.org/abs/2202.13892v1 | https://arxiv.org/pdf/2202.13892v1.pdf | A Novel Viewport-Adaptive Motion Compensation Technique for Fisheye Video | Although fisheye cameras are in high demand in many application areas due to their large field of view, many image and video signal processing tasks such as motion compensation suffer from the introduced strong radial distortions. A recently proposed projection-based approach takes the fisheye projection into account to improve fisheye motion compensation. However, the approach does not consider the large field of view of fisheye lenses that requires the consideration of different motion planes in 3D space. We propose a novel viewport-adaptive motion compensation technique that applies the motion vectors in different perspective viewports in order to realize these motion planes. Thereby, some pixels are mapped to so-called virtual image planes and require special treatment to obtain reliable mappings between the perspective viewports and the original fisheye image. While the state-of-the-art ultra wide-angle compensation is sufficiently accurate, we propose a virtual image plane compensation that leads to perfect mappings. All in all, we achieve average gains of +2.40 dB in terms of PSNR compared to the state of the art in fisheye motion compensation. | ['André Kaup', 'Christian Herglotz', 'Andy Regensky'] | 2022-02-28 | null | null | null | null | ['motion-compensation'] | ['computer-vision'] | [ 2.44292393e-01 -3.21734697e-01 1.27909347e-01 -2.28314921e-01
-2.03069985e-01 -3.06723446e-01 4.79299724e-01 -6.54542804e-01
-4.58012164e-01 3.15178603e-01 2.79207349e-01 -1.78251326e-01
-4.16306332e-02 -7.50965655e-01 -6.93552196e-01 -7.13127434e-01
6.45379126e-01 -2.25807786e-01 6.73866510e-01 -2.28867799e-01
5.61938524e-01 4.18418676e-01 -1.22047770e+00 6.82999194e-02
7.40188956e-01 7.97809958e-01 4.19123352e-01 5.32882094e-01
4.73301969e-02 2.13403597e-01 -2.66867548e-01 -4.59709287e-01
6.19661212e-01 -3.63490045e-01 4.98335287e-02 2.83458114e-01
7.66395032e-01 -8.29951644e-01 -4.68359172e-01 1.25517368e+00
4.29367632e-01 6.86687827e-02 2.66085804e-01 -7.81004429e-01
-4.78977174e-01 -1.86551381e-02 -8.70542586e-01 1.55667132e-02
4.60882276e-01 3.96084860e-02 6.04986846e-01 -1.14478660e+00
6.86257184e-01 9.58952427e-01 4.26140428e-01 5.95903397e-01
-7.84982920e-01 -6.08575523e-01 -5.91449700e-02 4.09480751e-01
-1.15858090e+00 -4.63054955e-01 8.82517457e-01 -3.88075858e-01
4.78699654e-01 3.42051297e-01 7.14869857e-01 4.15971160e-01
5.13927996e-01 3.54004532e-01 8.86753678e-01 -3.81526828e-01
-3.82735059e-02 1.89031243e-01 -1.20159559e-01 4.12208259e-01
1.42333865e-01 1.37135312e-01 -4.47865367e-01 3.11462462e-01
1.22145367e+00 5.25903702e-01 -1.03443289e+00 -8.98652256e-01
-1.42474735e+00 2.72857755e-01 3.00880313e-01 1.39763057e-01
-2.32118681e-01 1.16853984e-02 -2.43276600e-02 4.58981618e-02
2.78375506e-01 3.69563341e-01 -6.35963827e-02 7.24658221e-02
-9.83200431e-01 6.41857535e-02 4.21970397e-01 1.12926352e+00
3.92844051e-01 1.09663650e-01 3.16180915e-01 5.98580420e-01
4.15997595e-01 6.84421718e-01 1.76725641e-01 -1.15730321e+00
9.33105350e-01 4.50129122e-01 3.73912036e-01 -1.15944302e+00
-2.00693890e-01 -2.85563022e-01 -8.18802476e-01 6.16696537e-01
4.69702691e-01 1.00792877e-01 -4.05559868e-01 1.09221828e+00
1.98275581e-01 -2.61277780e-02 6.32064417e-02 1.24552798e+00
5.38609803e-01 8.94626617e-01 -7.66618729e-01 -4.71927315e-01
1.11811852e+00 -9.94284987e-01 -9.07974601e-01 -1.21700108e-01
2.12911263e-01 -1.11350107e+00 9.84816730e-01 6.63419485e-01
-1.48867702e+00 -4.38159972e-01 -1.29431522e+00 9.95441247e-03
3.24526459e-01 2.26389557e-01 -5.51625937e-02 7.14699030e-01
-7.73684621e-01 2.90371597e-01 -5.56871593e-01 -1.38301834e-01
-2.70018816e-01 1.77182004e-01 -4.88629282e-01 -3.03639412e-01
-8.10735464e-01 9.64566410e-01 -8.37555304e-02 1.96321890e-01
-3.12877268e-01 -6.29325092e-01 -5.23297191e-01 3.72222841e-01
7.34567463e-01 -6.16910636e-01 7.82404959e-01 -4.35929537e-01
-1.88825035e+00 3.60302746e-01 -1.57609314e-01 -5.32177314e-02
8.35964978e-01 -4.69509423e-01 -4.44465101e-01 3.81422877e-01
-5.05680978e-01 2.98686862e-01 8.96294057e-01 -1.14811194e+00
-6.61613703e-01 -4.79237616e-01 1.85921118e-01 6.10772908e-01
-5.97014546e-01 -9.16584879e-02 -6.99159563e-01 -4.89029080e-01
6.64670765e-01 -9.32140410e-01 -5.29362215e-03 4.57165003e-01
-2.74394184e-01 5.20178735e-01 1.13239598e+00 -5.30017674e-01
1.33714080e+00 -2.09496665e+00 2.36193001e-01 -1.71916902e-01
2.54544556e-01 3.41182917e-01 3.44713569e-01 3.86446267e-01
1.33036733e-01 -3.68999332e-01 1.46303354e-02 -2.03045625e-02
-4.62170631e-01 -2.70088524e-01 -1.89405710e-01 7.05964565e-01
-4.93974686e-01 3.66905451e-01 -7.09484160e-01 -2.05441732e-02
6.95899427e-01 6.18951440e-01 -9.12263393e-01 1.76328868e-01
3.47983271e-01 5.29682577e-01 -1.20334037e-01 2.25131541e-01
1.28999960e+00 1.35282278e-01 1.49260744e-01 -4.69304085e-01
-5.06149054e-01 -1.06571354e-01 -1.18536329e+00 1.45168686e+00
-5.55398822e-01 8.27047825e-01 1.77940652e-01 -4.10411119e-01
1.03317630e+00 2.87699699e-01 4.04088140e-01 -5.62698781e-01
-2.30098054e-01 3.41302663e-01 -1.26207054e-01 -4.21835184e-01
7.05647469e-01 -2.60364383e-01 1.52513728e-01 -4.92072180e-02
-3.37347031e-01 -3.63352120e-01 -1.74096748e-01 -1.31989822e-01
5.73514104e-01 1.42995805e-01 3.71566564e-01 -1.29929259e-01
1.04610252e+00 -4.96419638e-01 6.33419096e-01 3.54476348e-02
1.19036317e-01 9.90951121e-01 3.57155234e-01 -5.48602700e-01
-1.35050774e+00 -9.03781474e-01 5.80894463e-02 2.59598941e-01
7.36597121e-01 -3.88663650e-01 -6.95479453e-01 -3.19077700e-01
-3.62004697e-01 5.81692457e-01 7.82396346e-02 -9.97846015e-04
-9.44718778e-01 -2.78718591e-01 3.73976156e-02 2.68902987e-01
1.04017055e+00 -3.11262667e-01 -1.16192901e+00 -3.28140855e-02
-1.19842097e-01 -1.28663027e+00 -9.17390764e-01 -6.95718169e-01
-9.75339293e-01 -1.17003357e+00 -1.31181979e+00 -3.02744091e-01
7.30444670e-01 1.00641644e+00 6.74234092e-01 -3.97638619e-01
3.00056845e-01 1.85371861e-01 -1.65926307e-01 1.53803572e-01
-3.01259667e-01 -5.57654262e-01 7.61632398e-02 1.00535370e-01
1.33156016e-01 -4.05407786e-01 -1.13228464e+00 1.00722742e+00
-8.63526642e-01 2.17897519e-01 6.28589690e-01 7.78833628e-01
2.70671695e-01 6.91804439e-02 -1.43431157e-01 -5.99110305e-01
4.89568971e-02 -5.10941707e-02 -1.17853069e+00 8.35797191e-02
-6.46631598e-01 -2.28238583e-01 7.79590964e-01 -9.24500152e-02
-1.21638525e+00 1.44740436e-02 -2.20849272e-02 -7.00738668e-01
8.99721012e-02 -1.59287736e-01 -4.13323045e-01 -2.21249163e-01
2.72601396e-01 3.63120914e-01 5.65772690e-02 -4.92150694e-01
1.49109796e-01 5.15563726e-01 4.40272778e-01 4.55359727e-01
8.14375401e-01 7.08924532e-01 2.42860585e-01 -1.05106223e+00
-1.63796991e-01 -5.07737815e-01 -5.89958012e-01 -5.88073790e-01
9.50704157e-01 -7.51850784e-01 -6.86818421e-01 6.25781417e-01
-1.17088974e+00 2.28303298e-01 2.41168320e-01 8.87989581e-01
-4.51062381e-01 7.91530848e-01 -2.98292518e-01 -5.38423002e-01
-1.28540784e-01 -1.61005008e+00 7.31946647e-01 2.36695156e-01
1.87308908e-01 -7.94748306e-01 -3.14718723e-01 3.95639330e-01
4.04909462e-01 -2.19617680e-01 7.52023399e-01 2.95638561e-01
-1.05272293e+00 -1.36079386e-01 -1.57915935e-01 3.80130053e-01
1.56965293e-02 -1.26368463e-01 -6.45382166e-01 -2.23614037e-01
4.47613716e-01 4.86893982e-01 6.22892201e-01 5.73405087e-01
6.08241320e-01 -1.65206164e-01 -1.88056782e-01 9.77517784e-01
1.57089961e+00 4.44871634e-01 9.87574816e-01 3.63548398e-01
6.65768564e-01 5.62739730e-01 8.91324580e-01 4.25400019e-01
1.31946966e-01 1.33880937e+00 6.04500353e-01 1.61189869e-01
-6.61551021e-03 -1.85023502e-01 4.02749896e-01 8.36688459e-01
-2.32268736e-01 -5.14997303e-01 -5.81649959e-01 1.58114627e-01
-1.52230752e+00 -1.05158401e+00 -5.34328997e-01 2.79232097e+00
1.74513802e-01 1.81382909e-01 -2.42687196e-01 3.76271576e-01
7.49400139e-01 3.96831006e-01 -3.09179008e-01 -3.13976407e-01
1.66610807e-01 -6.10689580e-01 8.56588125e-01 7.16390789e-01
-6.60164654e-01 5.05627751e-01 5.75584126e+00 5.71469128e-01
-1.45814621e+00 -1.77505687e-02 -5.17958961e-02 -1.91419587e-01
-4.76014376e-01 9.45668593e-02 -1.00131130e+00 5.95288932e-01
2.91976422e-01 1.42697811e-01 1.48753509e-01 5.55346370e-01
4.14721370e-01 -4.81405646e-01 -7.25061893e-01 1.25785220e+00
2.50335842e-01 -1.05686641e+00 -5.21912761e-02 3.78264606e-01
6.77662432e-01 -5.50954878e-01 2.63291359e-01 -5.27542591e-01
-6.75763130e-01 -3.51142168e-01 5.39519787e-01 6.16536617e-01
8.60965908e-01 -7.32923925e-01 5.88161707e-01 5.98986626e-01
-8.24996471e-01 -3.05978265e-02 -6.10557377e-01 5.19749299e-02
6.06511474e-01 8.17626655e-01 -6.19299054e-01 5.11312187e-01
5.06684422e-01 5.52281737e-01 -8.35809037e-02 1.13240063e+00
-1.10643573e-01 1.31237745e-01 -8.98553804e-02 2.42858231e-01
1.12146281e-01 -6.64866149e-01 8.85308087e-01 5.39097250e-01
9.99405563e-01 2.37301245e-01 -4.66469109e-01 6.23902202e-01
2.08906814e-01 -3.70198712e-02 -7.86801875e-01 5.93493640e-01
2.52682239e-01 9.92664695e-01 -4.38653916e-01 -2.08270341e-01
-8.43113840e-01 1.21763706e+00 -5.91202378e-01 3.16114336e-01
-7.22376883e-01 -3.92216951e-01 5.23616731e-01 6.64277911e-01
3.23951364e-01 -5.65156102e-01 -1.64272472e-01 -1.41126847e+00
1.49293393e-01 -3.86543602e-01 -3.40948075e-01 -8.75447094e-01
-4.28122163e-01 4.48523879e-01 3.37959006e-02 -2.03461242e+00
-2.91038573e-01 -6.29871428e-01 -4.71299291e-01 8.40607405e-01
-1.38961768e+00 -7.16004431e-01 -6.98718607e-01 5.30957520e-01
8.98531020e-01 -9.84946340e-02 3.69309813e-01 4.70920801e-01
-1.34593919e-01 3.72041881e-01 4.90925878e-01 -4.34298843e-01
1.15696371e+00 -8.98751736e-01 2.91024983e-01 1.06669414e+00
-2.72132039e-01 5.99002123e-01 7.82382131e-01 -4.00207222e-01
-1.50632894e+00 -5.88028789e-01 7.72431672e-01 -2.42465124e-01
7.90596381e-02 -1.89145938e-01 -7.62975276e-01 4.36248541e-01
3.30689251e-01 1.88463241e-01 3.92312914e-01 -7.15250194e-01
-2.58904304e-02 -3.80818576e-01 -1.07017851e+00 6.01040661e-01
1.07435632e+00 -9.13314223e-02 -2.64175564e-01 -2.94629097e-01
2.72788256e-01 -6.50261164e-01 -6.14058614e-01 3.40798318e-01
9.12258983e-01 -1.65075779e+00 1.06777275e+00 3.19765806e-01
7.21990943e-01 -5.65789640e-01 -1.93473801e-01 -1.35330546e+00
-1.68081880e-01 -5.72659075e-01 2.50396430e-01 9.55992997e-01
-5.90846576e-02 -7.67650783e-01 8.09529006e-01 4.46154654e-01
-2.62247026e-01 -5.74913144e-01 -8.46133053e-01 -5.47476947e-01
-3.85691524e-01 1.31039158e-01 1.18334606e-01 6.99157476e-01
2.04784587e-01 1.87155634e-01 -9.19011891e-01 2.11289763e-01
6.51023984e-01 6.45065904e-02 9.47245061e-01 -8.92239690e-01
-4.31340039e-01 -1.53021351e-01 -6.29675269e-01 -1.74983823e+00
-5.00984609e-01 -1.81845725e-01 -8.73915032e-02 -1.34888351e+00
5.10171577e-02 -2.22878084e-01 2.06039939e-02 -5.88053763e-01
-4.18942682e-02 4.45756078e-01 6.48986936e-01 4.33429092e-01
-1.39579609e-01 4.68081027e-01 1.62079597e+00 2.21372589e-01
-3.09511960e-01 4.75843996e-01 -3.22178602e-01 9.44404662e-01
4.20289248e-01 6.26891479e-02 -7.30649233e-01 -8.43303859e-01
2.90172040e-01 6.21129155e-01 2.21539095e-01 -1.13721120e+00
4.91887420e-01 -1.37137681e-01 2.68873006e-01 -9.07215893e-01
7.09792316e-01 -1.18736398e+00 3.33250105e-01 3.45967948e-01
-9.06917453e-02 2.13778049e-01 -2.16808319e-01 6.04073048e-01
-3.08223426e-01 -3.36134076e-01 1.01607108e+00 -1.51418582e-01
-6.79965556e-01 -3.37860025e-02 -3.19965959e-01 -4.12476778e-01
1.18840897e+00 -6.14168823e-01 -2.97907412e-01 -7.87408113e-01
-3.03415686e-01 -1.45440891e-01 1.10905957e+00 1.30355105e-01
1.11579728e+00 -1.15022075e+00 -3.17252219e-01 4.00824606e-01
-2.26923302e-01 -4.73631509e-02 5.03856480e-01 1.11102569e+00
-8.90583098e-01 7.11956561e-01 -4.85404670e-01 -5.96356332e-01
-1.62092304e+00 6.15595877e-01 2.54452080e-01 -5.74584566e-02
-8.79782021e-01 5.50390720e-01 6.84629440e-01 6.55017002e-03
-2.43072286e-01 -1.91708058e-01 -3.16729963e-01 -3.50643665e-01
6.52725458e-01 7.63717711e-01 -5.08134700e-02 -6.79959416e-01
-2.04577088e-01 1.37618065e+00 1.97785258e-01 -3.68869871e-01
1.08810878e+00 -5.57490230e-01 2.57962197e-01 -6.27066121e-02
1.10181439e+00 7.50808716e-01 -1.54690862e+00 1.84240248e-02
-4.41043615e-01 -1.39491963e+00 7.71925822e-02 -2.67314374e-01
-1.22738230e+00 1.47247481e+00 5.85253179e-01 -1.30124569e-01
1.35995698e+00 -5.27770102e-01 9.51264262e-01 1.64781645e-01
5.01382351e-01 -8.27588737e-01 -8.78964439e-02 1.56890437e-01
8.17881882e-01 -8.86198401e-01 2.98898458e-01 -9.36798811e-01
-6.21364415e-01 1.53926861e+00 5.95663965e-01 -1.69854864e-01
2.75503337e-01 2.93106548e-02 -3.66306491e-02 2.10010976e-01
-4.66724485e-01 4.08292979e-01 2.46896476e-01 3.84382904e-01
3.52019131e-01 -3.89105797e-01 -6.51687562e-01 3.57221114e-03
1.14707328e-01 3.89251634e-02 1.01866341e+00 5.95477283e-01
-5.24387002e-01 -9.61454868e-01 -6.72990978e-01 -4.93986495e-02
-3.96009922e-01 -2.31432002e-02 1.17998898e-01 7.05052972e-01
-9.09459144e-02 7.09623277e-01 1.50920391e-01 -4.44733113e-01
6.19647086e-01 -3.32111597e-01 6.05213106e-01 -2.59244949e-01
-7.33795539e-02 4.32584614e-01 -1.06004380e-01 -6.64734185e-01
-4.29387778e-01 -3.86696160e-01 -9.20438886e-01 -2.95642883e-01
-4.08397436e-01 -1.57860935e-01 6.73272133e-01 4.92057920e-01
1.75647721e-01 1.70203954e-01 8.77232552e-01 -1.01400530e+00
-5.70452034e-01 -5.66837370e-01 -6.04958534e-01 2.59599060e-01
3.48154068e-01 -5.20771444e-01 -4.04497594e-01 -1.12486444e-01] | [9.122180938720703, -2.44962739944458] |
c561ed38-015a-4950-96d5-d3f0be9bbcc3 | finite-state-script-normalization-and | null | null | https://aclanthology.org/2021.eacl-demos.3 | https://aclanthology.org/2021.eacl-demos.3.pdf | Finite-state script normalization and processing utilities: The Nisaba Brahmic library | This paper presents an open-source library for efficient low-level processing of ten major South Asian Brahmic scripts. The library provides a flexible and extensible framework for supporting crucial operations on Brahmic scripts, such as NFC, visual normalization, reversible transliteration, and validity checks, implemented in Python within a finite-state transducer formalism. We survey some common Brahmic script issues that may adversely affect the performance of downstream NLP tasks, and provide the rationale for finite-state design and system implementation details. | ['Brian Roark', 'Alexander Gutkin', 'Lawrence Wolf-Sonkin', 'Cibu Johny'] | 2021-04-01 | null | null | null | eacl-2021-2 | ['transliteration'] | ['natural-language-processing'] | [ 5.42088985e-01 -1.50161281e-01 -2.21724570e-01 -8.80180299e-01
-8.13108385e-01 -1.16026986e+00 6.88679576e-01 4.92889024e-02
-5.86605608e-01 4.86440837e-01 4.79375213e-01 -1.06868148e+00
1.32006565e-02 -4.48016196e-01 -2.79840231e-01 -3.83058727e-01
5.04116535e-01 5.18532157e-01 -1.12358652e-01 -2.98685700e-01
2.58865476e-01 7.42392421e-01 -7.57755697e-01 3.01226616e-01
6.13338888e-01 2.47035772e-02 -1.46387555e-02 1.17607212e+00
-3.92534584e-01 8.75710249e-01 -7.33061612e-01 -8.27165842e-01
5.56525253e-02 -5.63242018e-01 -1.07831681e+00 -4.78528947e-01
1.75227985e-01 -2.54811645e-01 -1.13832079e-01 1.05323970e+00
5.00770628e-01 -8.16348419e-02 5.07617235e-01 -6.87469244e-01
-4.21541274e-01 1.12074411e+00 2.54012495e-01 4.67280567e-01
5.53348958e-01 4.51450735e-01 8.64636660e-01 -6.44350886e-01
9.44002390e-01 1.32387471e+00 7.89221287e-01 4.25820112e-01
-1.20237374e+00 -6.45673037e-01 -3.37280005e-01 -2.64063895e-01
-1.54544830e+00 -1.05449629e+00 6.01704866e-02 -4.24785197e-01
1.28242099e+00 7.06198931e-01 4.24188465e-01 1.00856829e+00
2.79784739e-01 3.38665158e-01 1.02428102e+00 -5.36520720e-01
5.01195230e-02 -2.63617873e-01 2.15075359e-01 6.07771575e-01
1.07742488e-01 -3.76887083e-01 -3.67945135e-01 -3.68325919e-01
8.87553513e-01 -6.75858080e-01 4.55593258e-01 5.27563989e-01
-9.64995086e-01 9.59811151e-01 -3.36764872e-01 5.72328448e-01
-2.78132483e-02 3.70284580e-02 8.82075012e-01 4.69950289e-02
2.65687138e-01 4.23704147e-01 -4.08908695e-01 -6.41614020e-01
-1.03908324e+00 -3.21656056e-02 8.00914049e-01 1.05107987e+00
7.22777471e-02 3.31144482e-01 -1.83213174e-01 7.43819535e-01
4.24095780e-01 5.62970757e-01 3.08422208e-01 -9.66208279e-01
5.35554945e-01 1.09029949e-01 -3.14103127e-01 -5.19060254e-01
-3.24292153e-01 1.29127949e-01 -5.37540019e-01 -3.45077932e-01
4.77829486e-01 -4.02830124e-01 -1.30462039e+00 1.37250185e+00
2.66763479e-01 -6.06425226e-01 2.64310390e-01 5.32641947e-01
9.40355241e-01 1.00466108e+00 7.39544749e-01 -3.45453471e-01
1.33836508e+00 -4.75355983e-01 -1.11421204e+00 -2.92697072e-01
9.16832983e-01 -1.26087105e+00 1.01170337e+00 3.57064754e-02
-1.33304167e+00 -6.12175539e-02 -8.62128794e-01 -6.66038632e-01
-4.55400050e-01 2.52171844e-01 1.01036131e+00 1.29323041e+00
-9.33158576e-01 4.97303009e-01 -1.17582023e+00 -6.43303454e-01
9.73899290e-02 2.46930912e-01 -4.17888403e-01 1.57460138e-01
-1.19906461e+00 1.25557697e+00 8.33212793e-01 4.19614196e-01
-3.25691670e-01 -3.70024145e-01 -1.11974585e+00 -7.19393194e-02
3.61160599e-02 -2.45037880e-02 1.52858627e+00 -5.07817805e-01
-1.93313801e+00 1.01815641e+00 -2.36747995e-01 -3.47020254e-02
2.72951931e-01 -2.01882944e-01 -7.46919096e-01 -4.63533662e-02
7.44422600e-02 2.83762693e-01 4.70237315e-01 -2.39299804e-01
-2.42756158e-01 -1.36451975e-01 -7.31635571e-01 3.74232054e-01
2.21735820e-01 1.30128479e+00 -7.77984619e-01 -7.39893973e-01
2.05370456e-01 -7.64941156e-01 -3.75034451e-01 -3.54696333e-01
-3.17588866e-01 -6.78790510e-02 3.71440828e-01 -1.31979847e+00
1.37588072e+00 -2.17310548e+00 -2.91693628e-01 4.97645915e-01
-2.93724179e-01 6.06832862e-01 -1.46433234e-01 5.59910297e-01
-8.17291215e-02 4.81163025e-01 -1.23352490e-01 7.14837760e-02
1.27168670e-01 5.98194003e-01 -2.55845040e-01 6.95183218e-01
1.56963810e-01 1.17953312e+00 -6.78039432e-01 -6.30711317e-01
3.72528523e-01 3.03103805e-01 -1.65611759e-01 3.77634466e-02
-1.32687101e-02 1.56301990e-01 -4.61729467e-02 7.00394511e-01
5.88482380e-01 3.37440282e-01 7.78840303e-01 2.25954592e-01
-6.76467955e-01 1.09397590e+00 -1.01732934e+00 1.53046083e+00
-1.02520473e-01 5.98359823e-01 2.27266133e-01 -3.93205225e-01
8.67793500e-01 4.39476520e-01 -3.73175174e-01 -4.36452091e-01
1.85210362e-01 9.95860994e-02 5.26146553e-02 -4.12101239e-01
8.04696739e-01 -3.17791700e-01 -4.75781202e-01 4.85080302e-01
3.73195320e-01 -7.18583524e-01 5.47740817e-01 5.05320847e-01
7.83303440e-01 2.15366259e-01 8.66101742e-01 -3.26769888e-01
3.99698079e-01 5.42882644e-02 7.58887768e-01 8.98219407e-01
-1.54570863e-01 2.16795921e-01 8.39973211e-01 -1.92381755e-01
-1.38643944e+00 -1.08051789e+00 -1.50597095e-01 1.53074014e+00
-7.40481615e-01 -8.32042813e-01 -7.19608545e-01 -2.11095408e-01
-5.96604109e-01 9.84730124e-01 -3.22783142e-01 1.23937547e-01
-8.70526731e-01 -8.12753975e-01 1.66024315e+00 5.94942331e-01
9.38068256e-02 -1.00448453e+00 -2.98338681e-01 1.65314451e-01
-9.81276110e-02 -1.28355014e+00 -3.62643629e-01 5.19737482e-01
-8.42641830e-01 -5.21311998e-01 -1.32595673e-01 -7.92042434e-01
3.56295019e-01 -4.32629257e-01 5.74863374e-01 -3.41380358e-01
-1.93666771e-01 -1.79896489e-01 -7.75141269e-02 -3.37891757e-01
-1.09168673e+00 1.75419033e-01 -1.64132863e-01 -7.63292015e-01
2.64809340e-01 -1.37043998e-01 3.75798404e-01 -1.01343140e-01
-8.77658427e-01 2.44081855e-01 5.62930048e-01 3.96185607e-01
3.08552057e-01 -3.86593193e-01 4.60757762e-02 -1.34197235e+00
8.05690348e-01 2.87760720e-02 -8.98036540e-01 4.56298321e-01
-3.94062668e-01 1.45380273e-01 7.49442160e-01 8.31945091e-02
-1.55806041e+00 4.47456211e-01 -8.66434574e-01 6.03359759e-01
-1.37844011e-01 7.07092941e-01 -3.94967437e-01 -4.82141078e-02
6.99066818e-01 2.74488866e-01 -2.15205640e-01 -5.92383087e-01
8.16077352e-01 9.63106513e-01 1.03856850e+00 -4.36884552e-01
7.80680180e-01 3.35565545e-02 -2.93081641e-01 -9.52522516e-01
-4.36555922e-01 -4.62730259e-01 -5.95624208e-01 2.70419735e-02
8.81423891e-01 -8.31154883e-01 -5.07180214e-01 6.83465481e-01
-1.27463019e+00 -3.73625040e-01 -2.53519532e-03 3.04587007e-01
-2.21731439e-01 2.93163866e-01 -1.30032372e+00 -6.34266734e-01
-6.78332388e-01 -1.11772168e+00 6.07087076e-01 1.79903314e-01
-8.26006591e-01 -8.52131009e-01 3.94734412e-01 3.83635253e-01
1.57557935e-01 -1.22769937e-01 1.19198525e+00 -8.67174685e-01
3.22852015e-01 -5.74374720e-02 -2.43244380e-01 2.33171076e-01
-7.61889890e-02 6.83868945e-01 -6.97552025e-01 1.57942772e-01
-2.54698962e-01 -1.95740193e-01 1.75052330e-01 -1.31821379e-01
6.08619928e-01 -5.27983487e-01 -5.04360832e-02 7.89528608e-01
9.99794304e-01 1.88934982e-01 6.55229449e-01 -1.26147181e-01
5.17569423e-01 1.69767097e-01 4.03339565e-01 2.16083840e-01
-7.99540803e-02 2.76363701e-01 -2.65863180e-01 3.84907238e-02
1.76822528e-01 -4.17690277e-01 6.58008516e-01 1.10445213e+00
2.01613046e-02 -4.53972332e-02 -1.18850815e+00 4.00065958e-01
-1.47081840e+00 -6.81138873e-01 -4.09923613e-01 1.64360511e+00
1.24543369e+00 -1.23404980e-01 -5.87322451e-02 8.11588317e-02
8.63271236e-01 1.88122645e-01 2.96885967e-02 -1.39246273e+00
-3.32838386e-01 7.27444828e-01 9.05618131e-01 6.01886332e-01
-1.04171944e+00 1.80485284e+00 8.88810635e+00 7.50648141e-01
-9.72283959e-01 2.66443312e-01 1.18642233e-01 3.60389776e-03
-1.45011634e-01 1.48737967e-01 -9.88366306e-01 1.57527357e-01
1.53895426e+00 -2.55839407e-01 4.38289851e-01 6.37193978e-01
6.13330066e-01 -8.00622180e-02 -6.54882908e-01 6.26217186e-01
-1.44427702e-01 -1.59104431e+00 -6.87600598e-02 -3.29194397e-01
3.63899350e-01 2.20145121e-01 -2.55995899e-01 1.32169634e-01
9.62328374e-01 -9.42299426e-01 8.54874372e-01 -1.42172262e-01
1.23320711e+00 -7.40411103e-01 5.14587641e-01 -1.71347484e-01
-8.02723765e-01 2.74458885e-01 -3.31687778e-01 -2.61920840e-01
6.10514522e-01 4.02637631e-01 -9.94151354e-01 3.38905871e-01
4.68860984e-01 3.02266240e-01 -6.66151702e-01 5.29910445e-01
-7.07019806e-01 1.22108555e+00 -5.45781434e-01 -1.01868995e-01
3.42447132e-01 -3.05685222e-01 3.91126037e-01 2.07018852e+00
-3.53382691e-03 4.38648373e-01 -4.12581831e-01 4.35278505e-01
1.84963018e-01 6.34611487e-01 -3.39717805e-01 -6.78899407e-01
4.09950942e-01 1.25857675e+00 -1.10015798e+00 -5.24641812e-01
-2.36003056e-01 1.01391280e+00 2.78856605e-01 1.47879347e-01
-8.40957761e-01 -7.53075838e-01 6.44554555e-01 -2.10964218e-01
8.61141086e-02 -5.90823591e-01 -7.62463748e-01 -1.01687443e+00
-4.19442326e-01 -1.16271639e+00 8.57173502e-01 -8.63174081e-01
-5.76243460e-01 1.37951717e-01 -2.35319398e-02 -2.71712512e-01
-3.96459013e-01 -6.45391226e-01 -5.61092913e-01 9.51727331e-01
-4.01351511e-01 -1.12258053e+00 5.46179473e-01 4.47090298e-01
1.98189259e-01 1.79715618e-01 1.09929264e+00 9.66394022e-02
-8.55549574e-01 5.52974761e-01 1.92994386e-01 5.13320088e-01
5.41106761e-01 -8.94994259e-01 1.09250510e+00 1.42374587e+00
1.13554290e-02 1.15661192e+00 6.90322876e-01 -1.07636857e+00
-1.37736189e+00 -1.05337489e+00 1.60243702e+00 -2.24136218e-01
9.31282282e-01 -8.01039457e-01 -6.89213336e-01 1.26361918e+00
-6.92773908e-02 -5.33046663e-01 9.10388112e-01 2.00018495e-01
-3.05610865e-01 3.21165353e-01 -9.95806038e-01 1.07934868e+00
8.78824711e-01 -7.76630938e-01 -7.65329242e-01 4.02104706e-01
5.57677090e-01 -6.14151299e-01 -8.97254586e-01 -2.73740776e-02
5.57928383e-01 -4.45417836e-02 4.68289405e-01 -9.02676344e-01
-6.88915141e-03 -2.45469004e-01 2.04130232e-01 -7.85345733e-01
-4.69071507e-01 -1.34554517e+00 4.68013763e-01 1.42732978e+00
5.97264707e-01 -5.17977536e-01 3.80248308e-01 8.61796558e-01
-1.43264130e-01 3.25224698e-01 -9.27290320e-01 -5.38437784e-01
1.07048161e-01 -9.67920959e-01 3.32246631e-01 8.94361734e-01
5.67423582e-01 6.18450224e-01 -3.37240964e-01 -4.37201113e-02
-1.12299323e-02 -4.40083742e-01 3.77391130e-01 -6.47647440e-01
-2.02339310e-02 -1.04256399e-01 -3.70815486e-01 -6.94582462e-01
1.23145454e-01 -1.02862835e+00 2.64588088e-01 -1.39511085e+00
1.63309410e-01 -1.66244879e-01 2.95037001e-01 9.70601797e-01
7.87237138e-02 3.68265688e-01 2.06987888e-01 -2.89493930e-02
-4.82535928e-01 -8.24893638e-02 5.57923079e-01 3.19945127e-01
-3.81577373e-01 -2.36810088e-01 -7.65181243e-01 7.57065117e-01
1.01619947e+00 -7.20938861e-01 1.53702719e-03 -5.41192114e-01
5.11588454e-01 -1.37834296e-01 -6.88341260e-02 -4.39767122e-01
2.24919185e-01 -6.95163727e-01 4.13969547e-01 -5.69817305e-01
-1.45816309e-02 -1.91598222e-01 5.12849927e-01 4.82353479e-01
-4.61699843e-01 2.89649576e-01 4.35217172e-01 -2.32441142e-01
3.56974453e-01 -5.27242362e-01 1.00001276e+00 -1.15167826e-01
-6.33452952e-01 -4.11517918e-01 -1.44124758e+00 7.99211953e-03
6.07221723e-01 7.58875459e-02 -3.02435100e-01 -3.28902781e-01
-6.17642581e-01 -1.90061361e-01 3.24644476e-01 2.69446105e-01
2.26233482e-01 -7.71889269e-01 -5.58575094e-01 3.93336087e-01
-1.24407664e-01 -4.89747375e-01 -1.13339491e-01 5.74711859e-01
-1.25141656e+00 8.34839761e-01 -3.64216626e-01 1.96818281e-02
-1.49050856e+00 6.72164485e-02 -3.43923606e-02 -2.30547458e-01
-4.84829307e-01 6.02472544e-01 -4.92089659e-01 -6.93772793e-01
-2.13201642e-01 -3.23384553e-01 5.44341505e-02 -2.69372791e-01
5.45192897e-01 4.65937227e-01 2.73412943e-01 -9.77283776e-01
-6.22280836e-01 4.16982807e-02 -1.52021721e-01 -8.51404548e-01
8.96944404e-01 -8.46393928e-02 -5.53948522e-01 3.85117412e-01
7.79391885e-01 1.35058537e-01 -3.61359209e-01 1.08168252e-01
1.17375582e-01 6.87642768e-02 -7.08375722e-02 -8.98104787e-01
-3.76515448e-01 5.60913980e-01 3.84068005e-02 -5.29597998e-01
6.53941095e-01 -1.17142379e-01 4.91229326e-01 5.85186362e-01
-3.04406404e-01 -1.59568763e+00 -9.62516248e-01 1.13651216e+00
4.57661033e-01 -4.22251880e-01 2.55429953e-01 -6.56866789e-01
-6.60119534e-01 9.69300151e-01 1.55017868e-01 5.57886660e-01
1.79501355e-01 7.47033715e-01 5.16965449e-01 -7.11261779e-02
-5.80143869e-01 2.28596181e-02 -1.96366102e-01 5.49835205e-01
7.65405655e-01 2.02793822e-01 -1.03975844e+00 6.91011071e-01
-6.66344106e-01 -5.87747283e-02 6.47988617e-01 1.13820446e+00
-1.81155697e-01 -1.11869562e+00 -6.41122758e-01 4.29706633e-01
-9.96499240e-01 -5.81806064e-01 -4.98900741e-01 6.65214241e-01
-1.91975281e-01 8.55864644e-01 1.40222684e-01 -5.85892946e-02
1.35509092e-02 5.15683472e-01 2.92418510e-01 -6.79758787e-01
-1.14146221e+00 2.84340352e-01 6.73421919e-01 -4.00384873e-01
1.22743905e-01 -9.42588508e-01 -1.36976171e+00 -6.34689987e-01
-3.01717836e-02 2.12311268e-01 9.59055007e-01 9.99853790e-01
1.79714625e-04 -6.65554106e-02 -1.72813594e-01 -2.96325624e-01
-3.55507404e-01 -1.02399611e+00 -3.62192392e-01 -7.55003542e-02
-4.20164943e-01 3.56262058e-01 -2.83315461e-02 3.40484887e-01] | [10.464888572692871, 10.25110149383545] |
1c853903-ac13-4972-99f0-8c8a4fbaae98 | discovering-intrinsic-spatial-temporal-logic | 2306.12244 | null | https://arxiv.org/abs/2306.12244v1 | https://arxiv.org/pdf/2306.12244v1.pdf | Discovering Intrinsic Spatial-Temporal Logic Rules to Explain Human Actions | We propose a logic-informed knowledge-driven modeling framework for human movements by analyzing their trajectories. Our approach is inspired by the fact that human actions are usually driven by their intentions or desires, and are influenced by environmental factors such as the spatial relationships with surrounding objects. In this paper, we introduce a set of spatial-temporal logic rules as knowledge to explain human actions. These rules will be automatically discovered from observational data. To learn the model parameters and the rule content, we design an expectation-maximization (EM) algorithm, which treats the rule content as latent variables. The EM algorithm alternates between the E-step and M-step: in the E-step, the posterior distribution over the latent rule content is evaluated; in the M-step, the rule generator and model parameters are jointly optimized by maximizing the current expected log-likelihood. Our model may have a wide range of applications in areas such as sports analytics, robotics, and autonomous cars, where understanding human movements are essential. We demonstrate the model's superior interpretability and prediction performance on pedestrian and NBA basketball player datasets, both achieving promising results. | ['Shuang Li', 'Chao Yang', 'Chengzhi Cao'] | 2023-06-21 | null | null | null | null | ['sports-analytics'] | ['computer-vision'] | [ 3.85548845e-02 3.13008279e-01 -5.65287292e-01 -5.77634692e-01
1.00077644e-01 -2.44638398e-01 7.67472386e-01 1.57950874e-02
-3.09998959e-01 5.45356333e-01 4.01894093e-01 -4.72861499e-01
-4.43981379e-01 -9.75417376e-01 -8.57026637e-01 -4.30792093e-01
-1.33496404e-01 5.54652989e-01 3.26337039e-01 -2.59091407e-01
1.13600396e-01 2.21831366e-01 -1.60716391e+00 1.87201530e-01
8.81765187e-01 6.65598512e-01 1.78145289e-01 6.59621418e-01
1.77272901e-01 1.44543004e+00 1.58552706e-01 -5.22134840e-01
4.75472137e-02 -5.10645211e-01 -7.53540277e-01 3.01175505e-01
-5.90819180e-01 -2.69454122e-01 -3.98142844e-01 9.44255948e-01
-3.00609678e-01 5.16357720e-01 7.08754897e-01 -1.53333855e+00
-5.37093759e-01 6.59292340e-01 -1.24578752e-01 -2.56447822e-01
3.44497085e-01 4.63686287e-01 1.13061011e+00 -6.14734232e-01
6.45415366e-01 1.40113056e+00 3.63451928e-01 3.75571936e-01
-1.18939543e+00 -1.97665796e-01 5.36418021e-01 7.06384242e-01
-1.30629599e+00 -3.45141262e-01 7.67793894e-01 -7.85055876e-01
6.53459311e-01 9.87042263e-02 9.36518192e-01 9.82302189e-01
1.94891244e-01 1.27566338e+00 6.56541407e-01 -4.87340808e-01
6.23105884e-01 2.38580070e-02 -1.53721049e-02 7.77455389e-01
1.05734974e-01 4.21600223e-01 -8.03764462e-01 -1.03990108e-01
6.69950366e-01 7.79132992e-02 1.83925316e-01 -5.05044222e-01
-1.19670939e+00 9.00096953e-01 1.09414458e-01 -1.87029719e-01
-6.84025526e-01 3.38291109e-01 -5.79087436e-02 -1.72104388e-01
1.61417976e-01 1.24479413e-01 -3.03497314e-01 -4.22522098e-01
-5.42751193e-01 6.68045998e-01 6.80847943e-01 9.00920451e-01
6.44503415e-01 -4.03650314e-01 -2.41837114e-01 5.31376839e-01
8.73959303e-01 5.14645040e-01 8.70578513e-02 -1.10922563e+00
3.83801311e-01 6.87334836e-01 6.61917508e-01 -1.14568830e+00
-3.30691218e-01 -8.27500895e-02 -4.23379064e-01 -7.03018084e-02
4.75779474e-01 -9.76110771e-02 -7.89608657e-01 1.82184243e+00
6.04476452e-01 2.12217689e-01 -6.81076869e-02 9.13361371e-01
2.76282549e-01 5.14784098e-01 2.59521872e-01 -1.26995236e-01
1.20442843e+00 -7.49387801e-01 -7.21827388e-01 -4.51251447e-01
6.12795651e-01 -1.82562470e-01 9.07216012e-01 3.91006559e-01
-1.08356285e+00 -5.14985442e-01 -6.22413218e-01 8.13401490e-02
-7.64964223e-02 2.51608044e-01 7.77967751e-01 2.10714236e-01
-4.87187892e-01 4.35295492e-01 -1.31945872e+00 -3.92012388e-01
4.41522032e-01 1.59328997e-01 3.40618975e-02 3.57153654e-01
-1.19743776e+00 8.52557719e-01 5.86144030e-01 2.71626979e-01
-8.83001149e-01 -1.41179711e-01 -8.64526629e-01 -2.13084724e-02
7.24054694e-01 -6.71883106e-01 1.37817919e+00 -5.91232836e-01
-1.64983451e+00 6.09968483e-01 -4.38068509e-01 -7.05073357e-01
5.01522183e-01 -2.20018625e-01 -3.52124870e-01 -1.87150896e-01
2.10319549e-01 5.72777748e-01 5.24737835e-01 -1.03326297e+00
-1.00307786e+00 -2.35317096e-01 1.74015641e-01 2.27175966e-01
5.93435988e-02 -2.49755055e-01 -6.33633733e-01 -4.04362798e-01
1.31422698e-01 -1.20674288e+00 -4.90772992e-01 -6.91051707e-02
-4.21038121e-01 -3.29862356e-01 3.05414915e-01 -4.38578397e-01
1.37712300e+00 -2.17658305e+00 2.26367086e-01 5.25422513e-01
2.75778901e-02 -1.07746676e-01 2.65478283e-01 3.34495306e-01
4.88002986e-01 -1.30824104e-01 -3.62438075e-02 3.12554613e-02
4.00185734e-01 4.30484384e-01 -5.59412420e-01 2.68010080e-01
5.79469092e-02 1.10801601e+00 -1.10584843e+00 -5.54565251e-01
3.60224813e-01 1.60981044e-02 -7.12240636e-01 1.22381330e-01
-7.12996364e-01 5.10350525e-01 -9.49491560e-01 2.93876827e-01
8.95003497e-04 -4.00113076e-01 5.28005600e-01 1.57546610e-01
-1.30564943e-01 3.64993989e-01 -1.17067146e+00 1.31836188e+00
-1.35954648e-01 5.35893977e-01 -3.30318511e-01 -9.41215873e-01
7.59657204e-01 3.79163846e-02 4.38366026e-01 -5.30394852e-01
9.23410654e-02 -2.04985172e-01 9.75999311e-02 -1.08885002e+00
5.14329135e-01 -1.85592845e-01 -1.93476766e-01 4.72898006e-01
-4.44717288e-01 2.23089591e-01 3.49861741e-01 1.68658152e-01
8.82814348e-01 6.52475297e-01 5.48532069e-01 4.38774005e-02
4.00937796e-01 3.43544930e-01 9.90615785e-01 9.09916043e-01
-2.13548005e-01 -1.05836704e-01 6.01890802e-01 -6.81636930e-01
-7.66721606e-01 -1.02234209e+00 2.28890568e-01 1.05489528e+00
2.95761496e-01 -4.62471396e-01 -5.27992785e-01 -3.82608980e-01
3.19416672e-02 1.24162102e+00 -6.81586325e-01 -4.90028203e-01
-5.63733757e-01 -6.35630965e-01 2.35176489e-01 7.04313219e-01
4.76650566e-01 -1.10241508e+00 -8.40098321e-01 3.07601810e-01
-5.70168316e-01 -1.11821949e+00 -2.59066343e-01 -2.21455738e-01
-6.58812046e-01 -1.03039861e+00 2.40838215e-01 -3.61186713e-01
6.73922420e-01 -1.19997494e-01 8.29489052e-01 -2.02362575e-02
7.90707488e-03 3.90027374e-01 -4.14630622e-01 -6.22166812e-01
-3.25591862e-01 -2.91628510e-01 2.37929299e-01 4.55335706e-01
7.47735858e-01 -4.17523414e-01 -4.41128314e-01 4.99669909e-01
-5.86907864e-01 4.66421425e-01 5.07210672e-01 5.38267493e-01
6.68873847e-01 2.87109196e-01 1.23106420e-01 -7.06169307e-01
2.95761079e-01 -6.32699788e-01 -6.90413475e-01 4.29742634e-01
-5.63301802e-01 3.16386312e-01 3.51336509e-01 -6.59624875e-01
-1.31904268e+00 4.19731379e-01 2.53074497e-01 -2.44277060e-01
-3.42972815e-01 7.40729630e-01 -4.25473630e-01 7.34519422e-01
4.42594916e-01 2.99367398e-01 -2.14667737e-01 -2.97005832e-01
5.15636086e-01 4.97504711e-01 4.92845774e-01 -7.58045793e-01
6.15102828e-01 6.87846541e-01 7.43085518e-02 -7.03661442e-01
-9.93144393e-01 -1.78860247e-01 -7.04209149e-01 -5.88482499e-01
1.14774895e+00 -7.20294476e-01 -1.14761198e+00 3.30473453e-01
-9.00739074e-01 -5.92420995e-01 -3.47268343e-01 8.56164515e-01
-9.34140742e-01 5.69050200e-03 -2.12703332e-01 -1.22243607e+00
4.48852152e-01 -1.11167145e+00 9.03774440e-01 2.17823043e-01
-5.62962711e-01 -1.12287974e+00 -1.49632068e-02 4.53191042e-01
-2.20327422e-01 1.10670373e-01 1.02890003e+00 -5.50541520e-01
-7.78695941e-01 -7.70176500e-02 2.88761526e-01 -2.41210654e-01
1.14281625e-01 -5.97284958e-02 -4.55264002e-01 2.40393132e-01
-2.79524565e-01 -2.22799275e-02 4.81057376e-01 6.54111087e-01
1.17357779e+00 -4.77242053e-01 -6.04064047e-01 3.31618458e-01
8.52349877e-01 4.04887497e-01 5.26499569e-01 3.33863139e-01
4.15285707e-01 7.28683949e-01 9.66447651e-01 5.94959199e-01
9.04541016e-01 8.54386926e-01 3.81195724e-01 4.56584543e-01
3.44327003e-01 -9.62091804e-01 5.01505017e-01 2.02699974e-01
-1.15828969e-01 -2.94643462e-01 -1.01755428e+00 6.68116808e-01
-2.65195227e+00 -1.34859776e+00 -2.81896561e-01 2.06103301e+00
6.07986927e-01 2.23692134e-01 4.16943401e-01 -1.49346799e-01
5.63722730e-01 -1.14011362e-01 -8.28503132e-01 8.42745677e-02
1.31854773e-01 -4.93857533e-01 3.86048287e-01 7.57177234e-01
-8.62062216e-01 1.09426439e+00 6.38224554e+00 5.77900529e-01
-5.03758490e-01 -1.10589057e-01 4.46121782e-01 -3.88977081e-01
-3.72864217e-01 5.10473132e-01 -8.26130927e-01 5.04610002e-01
6.96167231e-01 -6.71036169e-02 4.56309080e-01 7.42014885e-01
7.57239521e-01 -2.78358102e-01 -1.26242256e+00 7.60462165e-01
-3.47357929e-01 -1.26319933e+00 -4.49570157e-02 5.10045826e-01
4.79222059e-01 -3.17453206e-01 -1.62593007e-01 3.02970082e-01
9.33191657e-01 -8.24590325e-01 1.27461028e+00 1.09000301e+00
1.07377321e-01 -6.60401583e-01 2.30756000e-01 8.92514467e-01
-1.10270882e+00 -4.26612735e-01 -6.53854012e-02 -5.02951145e-01
5.61358631e-01 6.17173195e-01 -7.90969133e-01 1.98809639e-01
5.64141572e-01 8.22684228e-01 -9.90531370e-02 6.51253223e-01
-6.75575614e-01 7.87101567e-01 -2.30114445e-01 -3.40148032e-01
-1.60035342e-02 -5.70500612e-01 6.92174315e-01 7.42952168e-01
1.89702827e-02 4.04080778e-01 2.69754946e-01 1.18291950e+00
3.49952579e-01 -2.42447481e-01 -4.91948366e-01 -5.50792478e-02
4.84256357e-01 7.25894034e-01 -8.55988741e-01 -2.92466402e-01
-2.26966634e-01 5.75331151e-01 2.85343170e-01 4.88296419e-01
-1.09146369e+00 6.58540204e-02 7.91254818e-01 2.23245621e-01
4.72200662e-01 -3.41224402e-01 -3.08886826e-01 -1.14577365e+00
1.92897081e-01 -7.22049117e-01 2.70259738e-01 -7.08386898e-01
-9.82916534e-01 -4.33232002e-02 5.30398548e-01 -1.14911830e+00
-6.14285290e-01 -6.25195801e-01 -5.37470639e-01 3.10384691e-01
-1.00368726e+00 -1.03395128e+00 1.72364071e-01 4.28256929e-01
4.64314073e-01 -1.86498128e-02 2.74186373e-01 -1.49636403e-01
-5.73940396e-01 5.88184185e-02 -8.96682516e-02 2.60272861e-01
1.37508960e-06 -9.96323824e-01 2.53182262e-01 8.94202292e-01
2.70940751e-01 6.21515393e-01 1.08448458e+00 -9.47109878e-01
-1.29002154e+00 -1.11554980e+00 1.09020853e+00 -6.09257460e-01
6.38118863e-01 -2.60720819e-01 -4.74783331e-01 1.09101474e+00
-4.91407901e-01 -2.52131313e-01 7.41544068e-01 3.59495372e-01
8.98015574e-02 1.06650017e-01 -8.20752442e-01 9.66134131e-01
1.25643420e+00 -2.95841962e-01 -5.90192437e-01 2.64316589e-01
3.71261388e-01 -2.85994112e-01 -5.83467305e-01 2.98473269e-01
7.37185180e-01 -8.22232962e-01 8.99333596e-01 -9.92955387e-01
4.59714502e-01 -5.51903784e-01 -2.35124752e-01 -1.06209838e+00
-5.75876892e-01 -6.09785497e-01 -5.10144114e-01 9.31760132e-01
5.13725996e-01 -3.25924188e-01 7.25988984e-01 1.03835261e+00
1.81728795e-01 -7.97763646e-01 -7.53451765e-01 -7.47038662e-01
-3.45146894e-01 -1.02516413e+00 9.84202981e-01 6.21175289e-01
2.47995913e-01 1.94157824e-01 -6.49007082e-01 2.93795168e-01
6.46441102e-01 2.79333204e-01 1.01996529e+00 -1.20062292e+00
-5.83541811e-01 -3.63562942e-01 -3.39116991e-01 -1.47165537e+00
1.93943173e-01 -5.96867621e-01 3.81850868e-01 -1.52946734e+00
2.61516333e-01 -2.62929201e-01 9.19001475e-02 6.02298737e-01
-1.90381780e-01 -4.92996216e-01 1.27214253e-01 2.18147054e-01
-9.50301707e-01 7.79001176e-01 9.50762808e-01 5.92196696e-02
-4.54060405e-01 3.57260287e-01 -5.59182644e-01 1.22403979e+00
6.11499727e-01 -4.38682586e-01 -6.77383482e-01 -4.02754456e-01
6.76574290e-01 1.18362568e-01 6.85684204e-01 -5.81233084e-01
3.68214518e-01 -1.00401437e+00 8.74177180e-03 -5.38861036e-01
4.27075028e-01 -7.54548669e-01 2.58407354e-01 4.49287951e-01
-6.38771057e-01 -1.27007976e-01 -2.60550320e-01 8.90213132e-01
4.47649471e-02 1.90707929e-02 3.21077257e-01 -7.37611353e-02
-7.70253718e-01 2.70875722e-01 -7.96056807e-01 -1.40972704e-01
1.19433987e+00 -2.13982731e-01 1.58597216e-01 -7.64510214e-01
-1.03625441e+00 6.67684674e-01 2.51980841e-01 6.00017190e-01
6.59625649e-01 -1.48801947e+00 -4.99372482e-01 1.77020013e-01
1.56223491e-01 2.17324980e-02 8.64848942e-02 9.08358872e-01
-7.64668286e-02 3.80969942e-01 1.62349552e-01 -5.98702669e-01
-8.80189180e-01 4.17039633e-01 3.70381236e-01 -2.53429294e-01
-5.65270662e-01 5.74601889e-01 1.20636351e-01 -4.76151317e-01
6.35925606e-02 -3.26099962e-01 -1.74617246e-01 -3.90641898e-01
4.84542727e-01 6.60609424e-01 -5.94837904e-01 -7.63761997e-01
-2.96564668e-01 2.53927320e-01 2.71194369e-01 -5.01797199e-01
1.36469448e+00 -3.60171169e-01 1.06170870e-01 6.95193231e-01
4.61950123e-01 -1.91675588e-01 -1.58123672e+00 -5.00924051e-01
3.59941244e-01 -4.77968454e-01 -1.64145455e-02 -5.78226030e-01
-5.77053785e-01 4.18601781e-01 1.45932630e-01 9.54895020e-02
8.45253944e-01 2.80557424e-01 5.92316806e-01 4.87605572e-01
5.05296826e-01 -1.34243047e+00 -1.19883128e-01 5.02501190e-01
4.63646948e-01 -1.20617425e+00 -1.47836041e-02 -2.66481608e-01
-9.94527340e-01 7.53352582e-01 5.89241922e-01 1.95534974e-01
8.14404547e-01 -4.20274353e-03 -3.28579426e-01 -3.75133842e-01
-1.08822715e+00 -3.87138158e-01 3.79330754e-01 4.16610599e-01
-4.68196487e-03 3.88369948e-01 -1.93171963e-01 8.20939720e-01
-4.18422431e-01 3.12933534e-01 2.16880798e-01 9.35167253e-01
-5.85463226e-01 -1.06819379e+00 -3.39434773e-01 4.31675881e-01
1.98177919e-02 3.80023897e-01 -3.54759812e-01 6.09100580e-01
4.00607139e-01 1.29971361e+00 9.68222022e-02 -5.91476917e-01
3.75622332e-01 1.55188203e-01 3.58019114e-01 -3.95469546e-01
1.80280954e-01 -2.20156252e-01 1.08682498e-01 -6.94331169e-01
-5.20124674e-01 -1.14461923e+00 -1.42238045e+00 -2.84283608e-01
-4.98824194e-02 1.89627752e-01 4.36493516e-01 1.53935969e+00
3.28532904e-01 1.96295291e-01 4.67290372e-01 -3.80942315e-01
-4.09877390e-01 -6.47239208e-01 -4.21023846e-01 5.27074397e-01
1.12060688e-01 -8.69038641e-01 2.92256512e-02 5.20126820e-01] | [7.406071186065674, 0.6564618349075317] |
1eb8e0c0-775e-4912-ae66-7299a413b1fa | unediting-detecting-disfluencies-without | null | null | https://aclanthology.info/papers/N15-1161/n15-1161 | https://www.aclweb.org/anthology/N15-1161 | Unediting: Detecting Disfluencies Without Careful Transcripts | null | ['Victoria Zayats', 'Mari Ostendorf', 'Hannaneh Hajishirzi'] | 2015-05-01 | null | null | null | hlt-2015-5 | ['electrical-engineering'] | ['miscellaneous'] | [-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] | [-1.5391420125961304, 15.869156837463379] |
866d2f36-516f-470a-8af3-2d21e8cdc5fb | enhancing-learnability-of-classification | 1912.04453 | null | https://arxiv.org/abs/1912.04453v1 | https://arxiv.org/pdf/1912.04453v1.pdf | Enhancing Learnability of classification algorithms using simple data preprocessing in fMRI scans of Alzheimer's disease | Alzheimer's Disease (AD) is the most common type of dementia. In all leading countries, it is one of the primary reasons of death in senior citizens. Currently, it is diagnosed by calculating the MSME score and by the manual study of MRI Scan. Also, different machine learning methods are utilized for automatic diagnosis but existing has some limitations in terms of accuracy. In this paper, we have proposed some novel preprocessing techniques that have significantly increased the accuracy and at the same time decreased the training time of various classification algorithms. First, we have converted the ADNI dataset which was in 4D format into 2D form. We have also mitigated the computation costs by reducing the parameters of the input dataset while preserving important and relevant data. We have achieved this by using different preprocessing steps like grayscale image conversion, Histogram equalization and selective clipping of dataset. We observed a highest accuracy of 97.52% and a sensitivity of 97.6% in our testing dataset. | ['Rekh Ram Janghel', 'Rishu Garg', 'Yogesh Rathore'] | 2019-12-10 | null | null | null | null | ['3d-classification'] | ['computer-vision'] | [-1.50231589e-02 -2.43550792e-01 2.24265784e-01 -5.95457971e-01
-5.41503370e-01 -2.69520968e-01 3.10150504e-01 1.87442407e-01
-9.11737740e-01 1.09416878e+00 1.68481752e-01 -2.53624707e-01
-1.21417902e-01 -9.00777817e-01 -1.10578917e-01 -4.98473257e-01
-1.23672776e-01 4.85409737e-01 6.24326229e-01 1.61495745e-01
3.61824542e-01 5.39669216e-01 -1.38407469e+00 3.12474042e-01
1.19717097e+00 8.72574091e-01 4.29938853e-01 2.53254563e-01
-7.97894821e-02 4.76183236e-01 -5.53492069e-01 -2.54420549e-01
3.37421119e-01 -2.22830474e-01 -6.58585429e-01 -9.94660258e-02
1.64537922e-01 -6.53602540e-01 -3.21266949e-01 1.11603868e+00
7.18896568e-01 -1.20587759e-01 8.21519256e-01 -9.86420035e-01
-4.70543802e-01 -9.08565968e-02 -6.67075515e-01 5.62296510e-01
3.05996984e-02 -1.73309863e-01 2.44425699e-01 -7.23624885e-01
5.24079442e-01 1.10021985e+00 5.72635651e-01 5.69242895e-01
-9.90886390e-01 -7.73666143e-01 -3.63562077e-01 8.19450557e-01
-1.30685174e+00 -1.51770964e-01 5.90395868e-01 -6.85330749e-01
6.25918210e-01 3.18276018e-01 9.75283325e-01 3.79846722e-01
6.09354019e-01 2.28966296e-01 1.66487968e+00 -5.63163102e-01
2.93524921e-01 1.30678281e-01 3.32664877e-01 4.61360514e-01
5.02423644e-01 -3.71652514e-01 3.85158181e-01 -3.95807207e-01
7.22374916e-01 3.77321750e-01 -1.16753846e-01 -8.78612101e-02
-1.04944694e+00 8.71785104e-01 3.03585678e-01 4.39842731e-01
-4.07181412e-01 -4.27818716e-01 4.94536102e-01 1.19882286e-01
1.44170597e-01 1.75114088e-02 -3.43132585e-01 2.47556731e-01
-9.50174034e-01 1.31358221e-01 4.06577528e-01 4.34566557e-01
1.09660544e-01 -3.09349716e-01 4.36560474e-02 9.13089097e-01
3.42041492e-01 5.69656670e-01 9.00808871e-01 -7.74432957e-01
3.87887567e-01 8.79191160e-01 -2.29128357e-02 -8.75124574e-01
-5.25420904e-01 -2.73718268e-01 -9.75940347e-01 6.82173729e-01
3.94173235e-01 -8.52810070e-02 -1.21360195e+00 1.38325787e+00
-3.45133170e-02 -3.66356403e-01 -2.96800751e-02 8.60382617e-01
5.52892566e-01 4.67120051e-01 4.21993434e-01 -1.79787219e-01
1.77025485e+00 -5.22243261e-01 -7.99055696e-01 -7.14394227e-02
2.31093600e-01 -7.65969694e-01 1.05700183e+00 4.71170187e-01
-7.30078280e-01 -3.46159965e-01 -1.18714166e+00 -1.99639946e-02
-4.82828289e-01 3.42424572e-01 5.12056172e-01 8.32618654e-01
-9.70228851e-01 1.69143051e-01 -9.05129373e-01 -5.91561258e-01
6.09336615e-01 4.02406096e-01 -6.80519700e-01 -7.03485981e-02
-1.08787000e+00 1.26542640e+00 2.52565801e-01 -1.93348885e-01
-4.01966155e-01 -4.38544333e-01 -2.27439433e-01 -2.07186148e-01
-1.80626094e-01 -5.86856425e-01 8.36107194e-01 -6.27427876e-01
-7.76949644e-01 9.25477207e-01 -1.45043537e-01 -5.10144293e-01
6.61912560e-01 -1.72637045e-01 -7.69688189e-01 3.49490941e-01
2.95687914e-01 6.83870792e-01 3.16642463e-01 -7.86309004e-01
-7.30607688e-01 -9.23385799e-01 -3.20819885e-01 -2.49073543e-02
-3.87886554e-01 1.94077432e-01 -1.88108478e-02 -7.31762350e-01
3.87397081e-01 -8.41247499e-01 -3.11818361e-01 1.98102847e-01
6.97419792e-02 1.39301255e-01 9.73704875e-01 -1.32428551e+00
1.13624430e+00 -2.00185418e+00 -4.26552236e-01 2.91251391e-01
3.94938350e-01 4.02099192e-01 6.00823164e-01 -1.55824706e-01
-4.90183085e-02 1.32419676e-01 -3.26122910e-01 9.51992571e-02
-3.83324414e-01 7.58870766e-02 7.30474442e-02 4.03829038e-01
-6.74589127e-02 4.40479249e-01 -4.66156900e-01 -7.35107720e-01
2.62978613e-01 7.43059278e-01 -4.61594552e-01 -5.38344309e-02
4.10819262e-01 2.92006493e-01 -3.60654414e-01 4.79101121e-01
8.61446500e-01 1.00775801e-01 1.44510612e-01 -3.20235670e-01
-1.54649481e-01 2.34256350e-02 -1.10709763e+00 1.10929596e+00
-7.32093155e-02 5.66942275e-01 -2.91276932e-01 -9.54771638e-01
9.12857652e-01 3.66527885e-01 6.19406283e-01 -9.39782798e-01
1.33296743e-01 3.79970491e-01 2.81086028e-01 -8.13047469e-01
8.13019276e-02 -4.79054824e-02 2.45945767e-01 2.10696384e-01
-5.02263725e-01 4.10602778e-01 2.01424345e-01 -5.72518148e-02
8.25160742e-01 -4.15399998e-01 6.30358458e-01 -4.55410808e-01
5.69173574e-01 9.90810096e-02 5.90078533e-01 3.96442175e-01
-5.55527449e-01 6.23436034e-01 3.53978962e-01 -4.65540528e-01
-1.20849884e+00 -1.05544138e+00 -5.29081345e-01 2.83994555e-01
-2.20717430e-01 -3.32902558e-02 -7.84938455e-01 -4.31473076e-01
-1.17411748e-01 4.93724674e-01 -4.36562538e-01 -7.57834613e-02
-7.14796662e-01 -1.17127550e+00 4.89227593e-01 5.78894854e-01
1.17957473e+00 -7.00227976e-01 -7.93723106e-01 2.37478226e-01
-1.62866227e-02 -8.32673728e-01 -2.85639316e-01 -8.53089839e-02
-1.44271028e+00 -1.22704709e+00 -1.06087542e+00 -1.03398073e+00
9.91304100e-01 1.70090511e-01 5.89166880e-01 4.51670401e-02
-5.92523575e-01 -6.58129603e-02 -1.97021633e-01 -3.45933527e-01
-8.62551928e-02 -6.89135864e-02 -6.52904017e-03 -3.07356775e-01
3.72292578e-01 -7.41359651e-01 -9.08377528e-01 1.48664936e-01
-7.09693253e-01 -1.26439422e-01 9.96638477e-01 2.95261830e-01
6.71982348e-01 4.20168608e-01 7.09363818e-01 -6.78877234e-01
7.70360053e-01 -1.67991713e-01 -3.32032710e-01 1.77080616e-01
-8.44707429e-01 -8.27454180e-02 3.35136890e-01 -3.15923393e-01
-9.04699206e-01 1.50688678e-01 -1.07014574e-01 3.80396098e-01
-2.93943197e-01 2.96937022e-02 -3.49029779e-01 -1.05219692e-01
3.68327349e-01 1.90569967e-01 3.87848914e-01 -7.37777174e-01
-3.28696936e-01 1.06926048e+00 4.10306901e-01 -1.63294643e-01
2.94395775e-01 4.62889701e-01 -4.85336967e-03 -6.50343537e-01
-2.74569750e-01 -2.29660705e-01 -7.04134226e-01 -1.49362817e-01
1.15264261e+00 -8.04309368e-01 -3.80612016e-01 8.07443082e-01
-8.36876094e-01 1.87436298e-01 3.80721569e-01 8.33286524e-01
2.73369178e-02 4.61842418e-01 -3.11549604e-01 -5.17550290e-01
-8.27144980e-01 -1.25772476e+00 2.62297392e-01 3.53969902e-01
-2.02580482e-01 -7.92484522e-01 -1.19097233e-01 2.70044386e-01
7.50427842e-01 4.33285624e-01 1.29687321e+00 -4.84408617e-01
-5.05892141e-03 -3.65731806e-01 -6.24815285e-01 3.07691365e-01
5.34899950e-01 -4.38696086e-01 -5.93434155e-01 -1.68991715e-01
3.14352363e-01 4.13195312e-01 6.92987740e-01 4.85756576e-01
9.10580397e-01 -1.66473120e-01 -3.71893972e-01 9.25028250e-02
1.46478331e+00 9.59023416e-01 9.74725187e-01 1.02176154e+00
3.02958637e-01 1.61881551e-01 4.29808497e-01 6.96777105e-02
4.28294152e-01 6.34644687e-01 9.35470015e-02 -1.09925024e-01
-3.40873092e-01 3.57939661e-01 1.76115051e-01 4.66679037e-01
-3.41397285e-01 4.34008926e-01 -1.00056887e+00 3.78676593e-01
-1.57530665e+00 -9.81557786e-01 -4.83327180e-01 2.29085875e+00
7.91711569e-01 2.75638342e-01 3.14682305e-01 4.44603771e-01
1.02959943e+00 -4.50878233e-01 -3.56732130e-01 -8.19112808e-02
-7.47885332e-02 2.03934759e-01 6.49833202e-01 2.66981900e-01
-1.15223014e+00 2.42741287e-01 6.46941137e+00 1.43872619e-01
-1.32679772e+00 2.87888318e-01 4.40715581e-01 1.70730166e-02
3.21564257e-01 -3.49976838e-01 -6.20586395e-01 8.50925744e-01
6.19491875e-01 -1.18080072e-01 3.30106616e-02 8.77953231e-01
4.72046465e-01 -4.18716431e-01 -4.47071552e-01 8.33139896e-01
1.09551273e-01 -7.85457551e-01 1.27318174e-01 1.72992840e-01
2.76898056e-01 -3.16490322e-01 -2.48848617e-01 1.65628234e-03
-4.60900307e-01 -7.49791980e-01 5.61806142e-01 6.94362402e-01
7.75331914e-01 -6.61642849e-01 9.91984725e-01 -1.69496417e-01
-9.23720479e-01 -5.55395037e-02 -1.58990815e-01 -1.62590995e-01
1.30119607e-01 7.29317307e-01 -9.07123864e-01 8.84161741e-02
9.21587169e-01 2.98489749e-01 -9.04327869e-01 1.62516236e+00
-4.21726443e-02 4.66560483e-01 -2.87719578e-01 1.45634800e-01
-1.17621288e-01 -2.85978884e-01 3.19580555e-01 9.49909091e-01
4.53643382e-01 1.46205157e-01 -4.34810519e-02 4.42621231e-01
3.74414235e-01 1.82046220e-01 -2.26782590e-01 3.48696202e-01
4.53927040e-01 8.98918509e-01 -9.40912724e-01 -4.20124233e-01
-4.57619667e-01 7.67964840e-01 -2.44061083e-01 -1.27939945e-02
-7.46481478e-01 -6.84423745e-01 1.72008723e-01 5.36818326e-01
3.07657290e-03 -3.58388096e-01 -6.15999818e-01 -9.46631134e-01
2.75044799e-01 -6.59880996e-01 5.95386326e-01 -6.01961672e-01
-9.50220585e-01 6.52125001e-01 4.92585227e-02 -1.15239966e+00
1.67804971e-01 -6.48281515e-01 -5.40791333e-01 8.23010743e-01
-1.09995353e+00 -8.57312024e-01 -4.58429337e-01 7.42700040e-01
3.62454653e-01 -4.09295559e-01 8.11571002e-01 9.52093959e-01
-6.18283868e-01 2.05102324e-01 1.67470470e-01 2.23596796e-01
8.82970691e-01 -1.25597692e+00 -1.08539231e-01 8.51214707e-01
-8.73612940e-01 7.06880212e-01 5.65409482e-01 -8.66794109e-01
-6.51548743e-01 -9.24933195e-01 9.85061705e-01 1.88036814e-01
3.12720150e-01 5.57294264e-02 -8.43557417e-01 5.55149496e-01
-1.12621121e-01 -4.10903960e-01 6.13233328e-01 -5.55552065e-01
4.37944829e-02 -2.37929836e-01 -1.74094522e+00 4.36525613e-01
5.45950115e-01 -1.37036130e-01 -8.57472777e-01 4.81899232e-02
9.19820145e-02 -1.70403477e-02 -9.90584731e-01 2.83068925e-01
8.12363684e-01 -8.07885170e-01 1.07793534e+00 -4.21568930e-01
1.36460662e-01 -5.17916858e-01 -2.85285801e-01 -8.36468756e-01
-4.11023945e-01 3.95666599e-01 2.64705092e-01 1.31096840e+00
3.35405856e-01 -9.96660411e-01 5.06072640e-01 1.06461859e+00
-3.59859094e-02 -5.14604330e-01 -8.23274255e-01 -5.58358908e-01
-1.08003043e-01 8.90522748e-02 4.29503351e-01 7.43305802e-01
-2.88492978e-01 -8.72767121e-02 -1.38494521e-01 5.67573719e-02
8.32803965e-01 -2.25004926e-01 9.19780061e-02 -1.49231875e+00
4.18816566e-01 -2.28132352e-01 -7.70429254e-01 1.35713175e-01
-3.34924459e-01 -7.61216700e-01 -5.80666363e-01 -1.89534140e+00
6.31413937e-01 -4.46665257e-01 -3.08267742e-01 5.02377033e-01
-6.31224513e-02 4.55702275e-01 -7.40802512e-02 4.66112792e-01
1.30695486e-02 -3.00761182e-02 1.16225231e+00 1.81623977e-02
-3.40292364e-01 1.41823804e-02 -7.74475396e-01 7.23255754e-01
1.43495917e+00 -6.04665339e-01 -3.30399692e-01 -4.11093473e-01
-2.31728181e-01 -5.70901453e-01 6.03237092e-01 -1.28524065e+00
-4.28425521e-02 2.34709345e-02 9.10528839e-01 -5.43415308e-01
2.30213538e-01 -9.69034255e-01 4.13480431e-01 9.74746943e-01
9.64779705e-02 1.31661206e-01 4.97378297e-02 7.76301473e-02
2.70141326e-02 -3.08513343e-01 1.18087304e+00 -1.31271392e-01
-9.38365936e-01 -8.89712498e-02 -4.94600177e-01 -2.94948637e-01
1.23311353e+00 -3.15725595e-01 -3.93135071e-01 6.26469105e-02
-7.83564985e-01 -1.72732249e-01 4.45843697e-01 9.06213224e-02
5.42802393e-01 -1.31582010e+00 -4.40684050e-01 7.25678578e-02
-2.70305991e-01 -4.83143777e-01 9.63930041e-02 1.16408527e+00
-9.28082466e-01 4.78237629e-01 -1.11397016e+00 -2.37572864e-01
-1.64709198e+00 2.50836790e-01 3.44377637e-01 -1.25162736e-01
-1.05894244e+00 -2.59368680e-03 -2.87161112e-01 7.53777251e-02
2.24948287e-01 -2.84427464e-01 -7.20062077e-01 1.78098455e-01
9.38243449e-01 8.05901945e-01 3.44878972e-01 -4.98364896e-01
-7.28618503e-01 6.92567945e-01 -4.44827467e-01 -1.58198267e-01
1.40418446e+00 -1.59329489e-01 -3.51917475e-01 -6.29592389e-02
1.01714873e+00 8.52585770e-03 -5.54371715e-01 3.23990047e-01
2.66465601e-02 -3.41393709e-01 3.28811646e-01 -9.89052892e-01
-1.12960649e+00 6.03685617e-01 1.46994007e+00 1.49567164e-02
1.25476754e+00 -1.40338972e-01 1.03543794e+00 2.39685491e-01
3.98557872e-01 -9.90379989e-01 -5.63902438e-01 7.21547976e-02
7.18597949e-01 -1.19789839e+00 1.83032900e-01 -2.52443641e-01
-4.54829484e-01 1.23415661e+00 3.24956119e-01 -2.15129644e-01
6.98358357e-01 2.01374188e-01 2.32297227e-01 2.20653582e-02
-1.42646924e-01 2.07831971e-02 8.72056633e-02 7.55796850e-01
4.79461312e-01 1.52281672e-01 -1.12300563e+00 1.00904381e+00
-2.49618605e-01 4.77627665e-01 3.66915017e-01 1.25190413e+00
-9.04107749e-01 -1.15237200e+00 -7.08358049e-01 9.11688328e-01
-7.85130620e-01 1.17112696e-01 -2.41945639e-01 9.15787220e-01
2.86957830e-01 7.59472847e-01 -2.86892764e-02 -1.32461578e-01
4.41821486e-01 1.73771471e-01 5.49427032e-01 -7.71610364e-02
-1.10997565e-01 -1.71205059e-01 6.72354847e-02 -3.49384844e-02
-4.12642568e-01 -7.76225924e-01 -1.51719809e+00 -2.37568140e-01
2.57329375e-01 1.47075862e-01 7.28923976e-01 9.20364857e-01
4.15688723e-01 5.65590560e-01 1.05734915e-01 -4.04960722e-01
-2.70015121e-01 -1.03103340e+00 -6.51568174e-01 2.67392427e-01
-1.61499698e-02 -8.84216487e-01 -2.45937407e-01 4.44730341e-01] | [14.157700538635254, -1.7526860237121582] |
beb2357c-8e43-452f-8063-ddfdd04503bc | border-an-oriented-rectangles-approach-to | null | null | http://openaccess.thecvf.com/content_cvpr_2016/html/Chan_BORDER_An_Oriented_CVPR_2016_paper.html | http://openaccess.thecvf.com/content_cvpr_2016/papers/Chan_BORDER_An_Oriented_CVPR_2016_paper.pdf | BORDER: An Oriented Rectangles Approach to Texture-Less Object Recognition | This paper presents an algorithm coined BORDER (Bounding Oriented-Rectangle Descriptors for Enclosed Regions) for texture-less object recognition. By fusing a regional object encompassment concept with descriptor-based pipelines, we extend local-patches into scalable object-sized oriented rectangles for optimal object information encapsulation with minimal outliers. We correspondingly introduce a modified line-segment detection technique termed Linelets to stabilize keypoint repeatability in homogenous conditions. In addition, a unique sampling technique facilitates the incorporation of robust angle primitives to produce discriminative rotation-invariant descriptors. BORDER's high competence in object recognition particularly excels in homogenous conditions obtaining superior detection rates in the presence of high-clutter, occlusion and scale-rotation changes when compared with modern state-of-the-art texture-less object detectors such as BOLD and LINE2D on public texture-less object databases. | ['Qian Kemao', 'Jimmy Addison Lee', 'Jacob Chan'] | 2016-06-01 | null | null | null | cvpr-2016-6 | ['line-segment-detection'] | ['computer-vision'] | [ 9.51376110e-02 -3.00695449e-01 -1.28903717e-01 -3.47200632e-01
-1.02628183e+00 -6.08245254e-01 5.78956008e-01 4.01471853e-01
-1.22135587e-01 6.79024234e-02 -3.00553679e-01 2.08202764e-01
-1.67168826e-01 -5.10830164e-01 -4.21308607e-01 -5.40103316e-01
-1.61583766e-01 5.25640130e-01 7.37896502e-01 -1.94606051e-01
5.63718498e-01 1.54472625e+00 -1.69864690e+00 4.56676006e-01
2.05836788e-01 1.43513477e+00 6.15524687e-03 5.16138196e-01
-1.10543661e-01 5.51312193e-02 -5.57875156e-01 -3.59210707e-02
5.88407099e-01 3.54571462e-01 -9.04160067e-02 3.67679805e-01
1.14076662e+00 -2.73435861e-01 -1.20307632e-01 4.20529455e-01
6.44065440e-01 -1.65878624e-01 6.92410648e-01 -8.18035364e-01
-4.59549069e-01 -1.25326201e-01 -7.88023829e-01 3.24795216e-01
5.82643807e-01 4.34853248e-02 7.10148752e-01 -1.57779229e+00
9.31395233e-01 1.35495675e+00 9.46554244e-01 -2.32427120e-01
-1.53629196e+00 -1.97759867e-01 -1.01844389e-02 -2.78408676e-01
-1.72158921e+00 -4.70052987e-01 5.80083728e-01 -3.89720708e-01
1.49116325e+00 5.11194527e-01 6.31285787e-01 7.73986220e-01
6.23253465e-01 6.83675587e-01 9.24632668e-01 -5.26701272e-01
6.54767975e-02 5.68156131e-03 -2.47147590e-01 5.50080836e-01
5.08549511e-01 1.45002350e-01 -6.97716177e-01 -9.05274302e-02
1.10303271e+00 -1.46075971e-02 1.59142345e-01 -1.21391094e+00
-1.41427398e+00 4.54233348e-01 3.86617571e-01 8.71689469e-02
-4.82997298e-01 -1.18161388e-01 5.29196858e-01 2.27765486e-01
7.02214539e-01 3.96452427e-01 -2.95795947e-01 4.16945629e-02
-1.06347120e+00 3.62953484e-01 4.62273449e-01 1.47414625e+00
7.92312384e-01 2.72913843e-01 -2.48236537e-01 8.46051037e-01
2.74780393e-01 9.50260460e-01 -2.15690155e-02 -3.58359843e-01
4.14759129e-01 7.55938232e-01 4.55541648e-02 -1.24290681e+00
-6.02584243e-01 -5.21499574e-01 -3.74337882e-01 2.89263278e-01
2.06890211e-01 7.62499869e-01 -9.03052449e-01 5.30616343e-01
6.77017808e-01 -5.82877934e-01 -4.43100959e-01 9.00986850e-01
7.73651659e-01 1.90969314e-02 -3.09626937e-01 1.70344710e-01
1.84535015e+00 -5.20389318e-01 -1.20553784e-01 3.19379801e-03
5.41830719e-01 -1.32925725e+00 4.82059687e-01 4.55403119e-01
-6.65045023e-01 -8.27939034e-01 -1.06547427e+00 -2.30528042e-01
-6.74214423e-01 3.05303127e-01 6.75152242e-01 8.65106583e-01
-7.54201770e-01 3.58942181e-01 -6.38170898e-01 -5.74095368e-01
6.80594385e-01 5.70998192e-01 -8.86883199e-01 8.92271101e-02
-1.81104973e-01 1.02583194e+00 2.17427015e-01 4.54721488e-02
-5.79511404e-01 -7.84708381e-01 -9.61199939e-01 -4.43149805e-01
3.11520547e-01 -3.81744385e-01 7.96773970e-01 -3.80986840e-01
-1.36620140e+00 1.35693741e+00 -4.71021794e-02 -2.59580702e-01
7.87324429e-01 -4.37066942e-01 -2.52150685e-01 3.96363467e-01
2.36759916e-01 5.51481783e-01 1.25401962e+00 -8.41749489e-01
-7.18419671e-01 -4.96744394e-01 -6.68080330e-01 9.50053707e-02
1.73376054e-01 2.61763513e-01 -6.27817154e-01 -7.34775543e-01
6.83826864e-01 -5.60330689e-01 6.26268610e-02 3.83230120e-01
-2.30295688e-01 -3.41450125e-01 1.24069059e+00 -3.65663886e-01
9.60421562e-01 -2.26378632e+00 -4.62803841e-01 5.13757765e-01
2.32422605e-01 8.93001482e-02 -1.60774812e-01 5.31992793e-01
-1.52746215e-01 -2.92153478e-01 4.56696361e-01 -3.95855587e-03
-4.57874639e-03 -1.50626063e-01 -3.04332703e-01 1.06339133e+00
7.22644210e-01 8.27419341e-01 -4.64528859e-01 -4.85799432e-01
7.21437693e-01 5.59523761e-01 -3.65258813e-01 -1.35272875e-01
9.37980786e-03 9.13883224e-02 -7.05397248e-01 1.46927094e+00
1.06611860e+00 2.98004478e-01 -3.24369907e-01 -5.84017456e-01
-7.06434667e-01 -1.75635085e-01 -1.56651437e+00 1.43405759e+00
-1.06199078e-01 8.95073235e-01 1.67452712e-02 -5.56320250e-01
1.75968456e+00 -4.03755419e-02 6.30468607e-01 -8.71347725e-01
6.92028925e-02 4.95102555e-01 -4.72676605e-01 -1.93888217e-01
8.48337531e-01 4.29237574e-01 1.30314320e-01 -3.73057164e-02
-8.78185257e-02 -4.60919201e-01 -6.74828514e-03 -2.36932054e-01
9.66466248e-01 6.38125122e-01 4.96570021e-01 -5.11178553e-01
3.98298621e-01 1.75155252e-01 1.34251282e-01 1.06248379e+00
-2.44530812e-01 1.07047808e+00 2.62645513e-01 -6.88935757e-01
-1.47685468e+00 -8.93749952e-01 -9.43921924e-01 9.92227674e-01
-7.45695923e-03 -4.45631057e-01 -1.88887730e-01 -3.17352831e-01
6.80291474e-01 -8.72956142e-02 -6.39134169e-01 3.72744769e-01
-7.82735527e-01 -3.51622343e-01 4.21636939e-01 5.65085351e-01
3.39620113e-01 -5.31656921e-01 -8.89226377e-01 3.60415101e-01
6.69881880e-01 -1.05907226e+00 -2.14034230e-01 6.42022312e-01
-8.16855073e-01 -9.69252586e-01 -9.31388438e-01 -6.78502917e-01
6.08904302e-01 6.01136208e-01 1.05773580e+00 -4.45987284e-01
-1.07058537e+00 7.05225348e-01 -3.30065727e-01 -3.77038509e-01
1.02033623e-01 2.03346033e-02 -3.70711572e-02 -7.10962415e-02
4.56052810e-01 1.86782390e-01 -7.67484784e-01 8.37454617e-01
-5.84370196e-01 -2.19677836e-01 6.99859560e-01 7.66266584e-01
1.11168790e+00 -3.69605571e-01 -1.01359159e-01 -1.74168080e-01
7.79808089e-02 -1.59072317e-03 -9.86703455e-01 1.48152307e-01
-3.18565339e-01 -9.76347253e-02 4.99626696e-02 -6.22026801e-01
-7.16512561e-01 2.79554337e-01 4.32445496e-01 -3.84733588e-01
-3.55946958e-01 -1.91197798e-01 -1.04919001e-02 -6.85562849e-01
8.09402704e-01 1.03437901e-01 3.76920961e-02 -5.58415174e-01
3.96840334e-01 7.11641967e-01 3.66114914e-01 -7.33192205e-01
8.33175898e-01 8.39092433e-01 2.29881838e-01 -1.26074767e+00
-2.94865847e-01 -1.03546703e+00 -1.09460855e+00 -2.37953737e-01
5.17414987e-01 -9.31150138e-01 -7.84318984e-01 4.10930514e-01
-1.02509844e+00 1.72228590e-01 -5.24384081e-01 4.12410259e-01
-6.67698860e-01 2.81053871e-01 3.67723145e-02 -9.17609334e-01
-1.72582284e-01 -1.14866376e+00 1.96670747e+00 2.49546200e-01
-4.69034724e-02 -5.59539616e-01 6.35000691e-02 1.45376241e-02
4.16208357e-01 5.58884740e-01 2.75346100e-01 -7.21119344e-01
-8.48626554e-01 -7.04950333e-01 -5.10665178e-01 5.69989607e-02
-9.39603616e-03 4.40272629e-01 -8.88470948e-01 -2.57104307e-01
-5.21748066e-01 -2.17112061e-02 5.84472060e-01 2.19374582e-01
6.48138940e-01 4.20698017e-01 -5.77430487e-01 8.04165483e-01
1.40980971e+00 4.29464504e-03 4.71942753e-01 9.31487679e-01
5.51781118e-01 3.89528424e-01 1.05989063e+00 7.10016906e-01
-9.57499966e-02 1.13966095e+00 1.07386962e-01 -4.56047803e-01
-3.39603633e-01 1.06362984e-01 4.27325852e-02 3.30554321e-02
-1.44394711e-01 1.80631220e-01 -1.00752389e+00 3.01383257e-01
-1.43947017e+00 -7.23449647e-01 -5.71185827e-01 2.25601029e+00
4.05576825e-01 2.00892672e-01 2.22255066e-01 -7.32831359e-02
6.64572418e-01 6.01756722e-02 -3.32248390e-01 -5.03259301e-01
-7.06730247e-01 4.44441587e-01 8.79242480e-01 -8.30274895e-02
-1.51279271e+00 1.18116844e+00 6.90716219e+00 9.96596694e-01
-1.14248359e+00 -3.94039989e-01 1.25891685e-01 2.45707527e-01
3.06182593e-01 9.88198668e-02 -1.36001444e+00 -1.89056709e-01
3.56666565e-01 3.57160896e-01 -2.89805740e-01 1.28350723e+00
9.80768725e-02 -4.66166526e-01 -9.74043310e-01 1.09408140e+00
2.22698525e-01 -1.08915889e+00 -1.32943451e-01 6.55062199e-02
4.49186981e-01 1.63670540e-01 1.83834806e-01 -1.25622839e-01
-3.81273508e-01 -7.37361908e-01 9.86080170e-01 5.81336915e-01
1.02185047e+00 -4.44429189e-01 5.52819133e-01 -4.32037562e-01
-1.61516714e+00 3.51873666e-01 -7.28953958e-01 4.24480587e-01
-3.23254406e-01 5.51120043e-01 -1.26909602e+00 8.20477962e-01
6.50894880e-01 6.02552891e-01 -1.10058641e+00 1.27314138e+00
2.82981694e-01 -6.04729466e-02 -8.00571561e-01 1.02892779e-01
9.17739719e-02 -1.05449334e-02 6.84386432e-01 1.73277235e+00
5.88118583e-02 -4.22295898e-01 2.62713552e-01 4.33173478e-01
6.50220513e-01 4.17065799e-01 -7.64805138e-01 2.48053655e-01
4.22661483e-01 1.42674804e+00 -1.14707720e+00 -8.02617520e-02
-4.04439479e-01 7.10832179e-01 1.11946054e-01 1.12500265e-01
-4.84798312e-01 -4.99896049e-01 3.97283822e-01 4.78169948e-01
9.93686140e-01 -6.94787860e-01 -2.16248408e-01 -8.55875731e-01
1.75518051e-01 -8.75409067e-01 2.42328405e-01 -7.33108938e-01
-1.07861876e+00 4.71333772e-01 1.16671734e-01 -1.52959919e+00
2.15954021e-01 -1.07526183e+00 -7.98815712e-02 7.16071784e-01
-1.33723116e+00 -1.84715259e+00 -5.36340952e-01 4.83940125e-01
4.83450830e-01 -4.62845832e-01 7.91801393e-01 5.86341973e-03
-3.09919924e-01 5.78964233e-01 4.06645209e-01 -1.68287065e-02
9.49111164e-01 -1.01986396e+00 3.88430446e-01 6.39187396e-01
6.64469674e-02 7.40539074e-01 5.61048925e-01 -7.72891045e-01
-1.93799806e+00 -6.85832143e-01 3.13528627e-01 -7.13739753e-01
7.09375918e-01 -7.11635470e-01 -6.46833181e-01 3.31398040e-01
-3.91156465e-01 5.06527424e-01 3.30964655e-01 -7.31774792e-03
-7.83956587e-01 -3.67761880e-01 -9.65503097e-01 1.63078934e-01
8.59452605e-01 -5.33373833e-01 -4.83990490e-01 4.23687935e-01
-2.77052373e-01 -7.64830828e-01 -1.20047796e+00 6.13463759e-01
9.97723520e-01 -1.10092497e+00 1.18364513e+00 -3.70192498e-01
-4.14736241e-01 -4.75124389e-01 -2.57049084e-01 -4.75502133e-01
-4.94648457e-01 -7.70771861e-01 1.66596532e-01 1.09660208e+00
-8.85300636e-02 -7.81489313e-01 8.02475750e-01 9.15362686e-02
-2.00252026e-01 -5.00806093e-01 -1.29881442e+00 -1.06470907e+00
-4.65837806e-01 -3.44420403e-01 3.01273197e-01 4.11236763e-01
-4.73280489e-01 -3.48315179e-01 2.30850399e-01 6.35448396e-02
6.50614262e-01 3.61408025e-01 1.27212059e+00 -1.28265321e+00
2.85997361e-01 -5.45776129e-01 -1.29249024e+00 -1.03431189e+00
-3.54516894e-01 -6.82026625e-01 -2.18541175e-01 -1.02058864e+00
-1.29367083e-01 -7.41572976e-01 -2.54649278e-02 3.67142200e-01
2.73148835e-01 6.16018534e-01 -3.92187908e-02 4.18066859e-01
-7.20281243e-01 2.52893180e-01 1.09477246e+00 1.33921176e-01
-5.56574911e-02 -1.95255265e-01 -3.12469602e-02 3.76857370e-01
3.44210833e-01 -4.31703806e-01 2.39409462e-01 -2.62091737e-02
-3.64047363e-02 -5.23391306e-01 3.86407733e-01 -1.01416743e+00
1.55325755e-01 -6.27451763e-02 9.74628806e-01 -1.18284535e+00
3.02370161e-01 -9.04140711e-01 1.12450719e-01 2.39157632e-01
1.81384400e-01 9.74376425e-02 3.98933440e-01 3.65281522e-01
-1.38946250e-01 1.85040787e-01 9.50758040e-01 9.33373049e-02
-7.94690132e-01 2.36154839e-01 -3.31972271e-01 -3.14339221e-01
1.34265006e+00 -1.08783913e+00 -4.34122801e-01 2.65702009e-01
-4.80727881e-01 -2.09215671e-01 7.97209978e-01 6.07055664e-01
7.35576510e-01 -1.19616890e+00 -8.99745643e-01 7.60191619e-01
6.08722210e-01 -1.14551954e-01 7.06364214e-02 1.13902080e+00
-1.10271204e+00 8.01937342e-01 -3.24737370e-01 -1.27688265e+00
-1.39592183e+00 3.99330705e-01 3.28922659e-01 1.23485431e-01
-9.32396412e-01 7.76434004e-01 4.17371280e-02 -6.93294108e-02
2.74150912e-02 -4.82543677e-01 2.08521754e-01 3.91259491e-01
3.22035402e-01 4.93389189e-01 7.47446597e-01 -7.79493928e-01
-8.05866778e-01 1.02875471e+00 -3.40426832e-01 2.14716658e-01
1.27599537e+00 1.02310002e-01 1.44206911e-01 1.53144017e-01
9.42934811e-01 3.77076894e-01 -1.25866842e+00 -1.55271322e-01
2.56025791e-01 -7.25734770e-01 1.40726745e-01 -3.17951262e-01
-4.12560165e-01 4.22766715e-01 1.00062978e+00 2.33420923e-01
6.21552646e-01 5.62819205e-02 1.94613934e-02 3.87642443e-01
4.98722821e-01 -1.19632435e+00 -1.88094452e-02 4.98960167e-01
1.29105246e+00 -1.17407405e+00 6.83200300e-01 -5.90726554e-01
-2.20041111e-01 1.80825114e+00 3.34063560e-01 -3.29509258e-01
4.93804961e-01 5.66285849e-01 1.37557998e-01 -4.04096544e-01
-2.84796566e-01 -4.95868087e-01 7.65134752e-01 9.84663785e-01
4.04776156e-01 -1.50432214e-01 1.31132737e-01 -1.98676929e-01
-7.41972700e-02 -5.63147128e-01 -2.76621550e-01 1.19178331e+00
-6.53679192e-01 -9.30494368e-01 -1.05692422e+00 3.45349818e-01
-2.00051472e-01 1.90623567e-01 -2.98677564e-01 1.28483391e+00
-6.89141229e-02 4.32890058e-01 4.32115734e-01 2.47316901e-03
7.11651266e-01 -1.11523993e-01 6.79800212e-01 -6.60469472e-01
-7.91547835e-01 7.18166709e-01 1.09390311e-01 -9.87477362e-01
-2.47045770e-01 -7.81958342e-01 -6.86581731e-01 -5.82812838e-02
-7.00463355e-01 -5.02507687e-01 1.05737567e+00 4.49766099e-01
6.68562233e-01 2.43433878e-01 5.33482909e-01 -1.34366059e+00
-3.79647940e-01 -7.97701359e-01 -6.93028569e-01 1.17686190e-01
1.19619995e-01 -1.00557280e+00 -3.39455344e-02 -1.55594721e-01] | [7.868295669555664, -2.2570960521698] |
28701b4a-9fe8-4558-b81c-92d1fef6e98e | learning-node-embeddings-via-summary-graphs-a | 2207.01189 | null | https://arxiv.org/abs/2207.01189v1 | https://arxiv.org/pdf/2207.01189v1.pdf | Learning node embeddings via summary graphs: a brief theoretical analysis | Graph representation learning plays an important role in many graph mining applications, but learning embeddings of large-scale graphs remains a problem. Recent works try to improve scalability via graph summarization -- i.e., they learn embeddings on a smaller summary graph, and then restore the node embeddings of the original graph. However, all existing works depend on heuristic designs and lack theoretical analysis. Different from existing works, we contribute an in-depth theoretical analysis of three specific embedding learning methods based on introduced kernel matrix, and reveal that learning embeddings via graph summarization is actually learning embeddings on a approximate graph constructed by the configuration model. We also give analysis about approximation error. To the best of our knowledge, this is the first work to give theoretical analysis of this approach. Furthermore, our analysis framework gives interpretation of some existing methods and provides great insights for future work on this problem. | ['Xueqi Cheng', 'HuaWei Shen', 'Danai Koutra', 'Shenghua Liu', 'Houquan Zhou'] | 2022-07-04 | null | null | null | null | ['graph-mining'] | ['graphs'] | [ 1.81041248e-02 6.44222140e-01 -5.55335343e-01 6.86122628e-04
-2.06253007e-01 -4.43321824e-01 7.03650713e-02 7.66168237e-01
-6.85756048e-03 2.69156903e-01 3.24380189e-01 -5.85045993e-01
-3.88689637e-01 -1.06242955e+00 -6.04751229e-01 -4.28027749e-01
-6.06836855e-01 5.01665294e-01 3.44575256e-01 -2.04268649e-01
3.09866041e-01 3.63475502e-01 -9.19675231e-01 -1.35986596e-01
6.15201950e-01 4.75650400e-01 -1.76302165e-01 8.82633150e-01
-2.05132470e-01 7.79744864e-01 -4.02594209e-01 -6.79962099e-01
2.38875300e-01 -4.80292290e-01 -9.80122805e-01 1.52707443e-01
3.48562866e-01 -2.90248275e-01 -1.03625190e+00 1.21705508e+00
4.19064164e-01 9.06643495e-02 6.79074049e-01 -1.47415888e+00
-1.40559471e+00 8.84752631e-01 -4.59071159e-01 1.99844226e-01
3.86363715e-01 -3.35486323e-01 1.50886583e+00 -6.57169223e-01
4.41403568e-01 9.69684064e-01 8.58138263e-01 4.25792009e-01
-1.33105326e+00 -2.62356311e-01 1.99330628e-01 4.23252285e-01
-1.22175777e+00 -5.86002022e-02 1.08613706e+00 -1.89342931e-01
1.00840199e+00 3.16965401e-01 8.61970007e-01 6.03480279e-01
9.13500786e-02 8.11047971e-01 7.96712697e-01 -5.94709516e-01
3.40601355e-01 2.77664691e-01 5.17132342e-01 1.11733770e+00
1.13598740e+00 -2.78399378e-01 -1.97316036e-01 -4.14014220e-01
6.38805449e-01 2.18873397e-01 -3.64554703e-01 -9.88820970e-01
-7.93775737e-01 1.06149662e+00 5.87477207e-01 3.52473587e-01
-1.73523352e-01 5.15291989e-01 5.00598013e-01 6.47115469e-01
5.77676713e-01 5.71464479e-01 -3.51328820e-01 8.13754275e-02
-5.95342457e-01 -8.50524381e-02 1.21786523e+00 1.17454386e+00
1.00083852e+00 1.03421047e-01 4.49130744e-01 4.64179963e-01
1.42860189e-01 2.38786102e-03 3.67874116e-01 -6.17142498e-01
4.08144593e-01 8.80132616e-01 -4.33455825e-01 -1.50054944e+00
-3.61123949e-01 -2.08251432e-01 -8.74707639e-01 -3.05767268e-01
3.05739969e-01 3.42651047e-02 -4.31769937e-01 1.34746516e+00
1.17106922e-01 4.04234588e-01 1.08512798e-02 5.99863470e-01
7.85402119e-01 5.73804617e-01 -5.63366234e-01 -2.34059960e-01
1.14315903e+00 -1.22662401e+00 -7.62393415e-01 -1.12487219e-01
1.01353562e+00 -2.14868486e-01 8.73018801e-01 1.69150352e-01
-7.82410860e-01 -8.13235343e-02 -1.18813622e+00 -5.73323928e-02
-4.51847076e-01 -1.00148112e-01 1.11660588e+00 8.85010779e-01
-1.41809702e+00 7.32548654e-01 -8.05464983e-01 -9.66292560e-01
2.42195621e-01 3.40889722e-01 -6.10602260e-01 -3.99592221e-01
-8.75608087e-01 6.70210242e-01 5.34952819e-01 -1.49908811e-01
-2.78540909e-01 -5.73461592e-01 -1.20315325e+00 1.67232171e-01
7.69626617e-01 -6.95794046e-01 9.54170287e-01 -5.18474758e-01
-1.17339694e+00 3.31905603e-01 -7.40191713e-02 -5.86553276e-01
-2.16837898e-01 1.04452498e-01 -2.05298603e-01 2.44639009e-01
-2.32718989e-01 -8.76466334e-02 5.62228262e-01 -1.04898024e+00
-7.12049454e-02 -5.80389798e-01 4.57037359e-01 -1.63383380e-01
-1.16147947e+00 -3.18658113e-01 -4.56289500e-01 -6.37759268e-01
2.37558603e-01 -9.19428408e-01 -6.27327681e-01 -1.10754140e-01
-4.13623631e-01 -3.85194004e-01 5.73178709e-01 -5.18883705e-01
1.87602806e+00 -1.84731090e+00 4.25848097e-01 2.75229931e-01
8.83473337e-01 2.84872085e-01 -2.35491648e-01 1.19534016e+00
-2.84358382e-01 5.58380902e-01 -1.47398815e-01 -6.59966841e-02
2.01381251e-01 3.20356518e-01 -2.99995661e-01 5.70460141e-01
2.72700172e-02 1.11742890e+00 -1.06146097e+00 -3.66561711e-01
1.59243241e-01 1.55684769e-01 -7.29904771e-01 9.53157842e-02
9.04904604e-02 -6.53039575e-01 -5.40306151e-01 4.70722020e-01
6.27560556e-01 -4.38674569e-01 6.83219254e-01 -4.13297206e-01
3.13726157e-01 8.59753937e-02 -1.29686356e+00 1.60007370e+00
-3.03968400e-01 5.73535323e-01 -2.43061632e-01 -1.67321014e+00
7.78665543e-01 7.82970265e-02 5.25172293e-01 -1.68809161e-01
-2.70889327e-03 5.62168024e-02 -4.53807004e-02 -4.43994224e-01
6.53912544e-01 9.16025192e-02 -2.04338416e-01 8.36608112e-01
1.11403964e-01 9.77970362e-02 2.07659468e-01 6.82416856e-01
1.62436056e+00 -4.59612101e-01 7.77287543e-01 -7.54622668e-02
1.47738621e-01 -2.96981335e-02 2.22200736e-01 6.96466804e-01
-2.70248890e-01 3.55535805e-01 1.03818846e+00 -7.68070042e-01
-1.15169609e+00 -9.14219618e-01 2.50796109e-01 6.73774540e-01
-9.47672967e-03 -1.38932407e+00 -6.05976522e-01 -9.60972369e-01
1.71049118e-01 3.79886717e-01 -7.75641680e-01 -4.51406866e-01
-4.37091082e-01 -7.74052620e-01 2.91504890e-01 8.38101983e-01
-2.50193208e-01 -4.88272667e-01 1.59257010e-01 2.54047185e-01
1.96468651e-01 -1.00378489e+00 -5.80776274e-01 -3.48280072e-02
-1.29422033e+00 -1.37904954e+00 -2.13195130e-01 -1.10663712e+00
9.49076056e-01 6.78608239e-01 8.60999107e-01 4.96347606e-01
-2.00698599e-01 7.07184434e-01 -6.47706270e-01 -6.17052875e-02
-2.36106828e-01 3.49862367e-01 1.56739891e-01 -1.50745198e-01
5.04517794e-01 -1.00768733e+00 -3.83165449e-01 3.26997638e-02
-1.00576329e+00 -1.85034290e-01 7.69710004e-01 8.13475788e-01
5.58532298e-01 4.69025612e-01 4.87616897e-01 -1.27653337e+00
9.97899830e-01 -6.31820917e-01 -3.78396809e-01 2.68501103e-01
-1.11560786e+00 5.71741521e-01 9.91465628e-01 -3.34522158e-01
-5.84978908e-02 -7.09007382e-02 1.20434716e-01 -5.31127572e-01
3.49863648e-01 6.77661896e-01 -1.00754716e-01 -2.57258058e-01
4.41840351e-01 3.47703099e-01 8.66193771e-02 -4.90492344e-01
7.70840466e-01 5.71740389e-01 5.43708950e-02 -3.69384587e-01
1.11011684e+00 4.21976447e-01 1.00307375e-01 -9.80543494e-01
-5.04442513e-01 -5.65875411e-01 -6.48254812e-01 1.49089709e-01
3.01583648e-01 -3.81114960e-01 -4.24474925e-01 -2.12010056e-01
-1.03313839e+00 -1.53862417e-01 -3.08955640e-01 4.07766521e-01
-5.08749902e-01 9.24282849e-01 -6.66175783e-01 -7.41681993e-01
-1.60675794e-01 -6.89173102e-01 7.07788825e-01 -1.53325856e-01
-6.55212179e-02 -1.37853062e+00 4.95485127e-01 -2.52699070e-02
2.53982544e-01 1.74264014e-01 9.20325041e-01 -9.06299770e-01
-6.35896325e-01 -5.15293300e-01 -3.17438692e-01 2.50794798e-01
3.00041437e-01 -8.34056437e-02 -5.41600168e-01 -5.96260965e-01
-3.00642669e-01 1.75535493e-02 1.04222333e+00 2.17513695e-01
1.18990481e+00 -6.38438940e-01 -5.33872962e-01 5.76183856e-01
1.71435440e+00 -4.13804173e-01 6.91550672e-01 6.37189671e-02
1.02758324e+00 4.63415533e-01 2.08880574e-01 3.75974298e-01
5.76417387e-01 3.62207770e-01 4.21679765e-01 2.73684382e-01
-1.85674369e-01 -5.61346889e-01 3.35498542e-01 1.33024871e+00
-1.15898542e-01 -2.62428373e-01 -6.33739650e-01 8.08262110e-01
-2.02720499e+00 -9.17956293e-01 -1.88991547e-01 2.13957286e+00
3.93368930e-01 -1.90743667e-04 3.07433754e-01 3.76925021e-01
7.94897795e-01 5.46926916e-01 -2.97826737e-01 -6.59974813e-01
2.84655243e-01 4.84724253e-01 7.62719572e-01 5.02972424e-01
-7.98973322e-01 9.70404863e-01 6.53821611e+00 5.98344386e-01
-5.52636862e-01 1.19039886e-01 -1.09038018e-01 1.68845713e-01
-6.43851697e-01 6.06474996e-01 -2.76699275e-01 8.57232213e-02
1.08800662e+00 -7.59486437e-01 6.71103895e-01 1.11980903e+00
-2.91586906e-01 4.05945569e-01 -1.17159224e+00 9.21843112e-01
3.74359310e-01 -1.43949497e+00 2.18848124e-01 4.07286912e-01
5.53003252e-01 -1.96366221e-01 -1.47510618e-01 4.36159819e-01
3.32329780e-01 -9.30319846e-01 -9.46557969e-02 2.04094544e-01
6.54209375e-01 -8.45126748e-01 8.11270654e-01 9.10237134e-02
-1.73837781e+00 -9.98814777e-02 -8.92489493e-01 -3.25738341e-01
9.60491151e-02 7.03029633e-01 -8.54367673e-01 9.55949962e-01
3.27653587e-01 1.06079209e+00 -6.96118414e-01 9.20442224e-01
-2.56146342e-01 9.12045240e-01 -8.37958381e-02 -4.06714082e-01
-1.08253673e-01 -2.85047293e-01 6.85020328e-01 9.59672034e-01
1.60159677e-01 -8.34306404e-02 3.24699789e-01 5.93406618e-01
-2.39890009e-01 3.28041345e-01 -1.23396194e+00 -7.13796079e-01
4.69965756e-01 1.29533112e+00 -7.35730231e-01 -1.20710038e-01
-6.92749143e-01 1.06616223e+00 8.58165801e-01 9.42481235e-02
-6.07591867e-01 -8.51545513e-01 6.15371943e-01 3.82587790e-01
5.50225675e-01 -6.22764230e-01 6.60247635e-03 -1.33868444e+00
2.52050102e-01 -5.07937372e-01 6.43604815e-01 -2.48299360e-01
-1.33750081e+00 4.37197685e-01 -3.18289758e-03 -9.73828554e-01
-8.46750811e-02 -7.05927730e-01 -6.32784963e-01 1.91109836e-01
-1.37087369e+00 -9.27905142e-01 6.54639378e-02 2.12093174e-01
1.23635679e-01 -5.13717905e-02 9.83202875e-01 6.38730600e-02
-6.33855224e-01 8.98122966e-01 2.66723812e-01 3.10731411e-01
4.11635578e-01 -1.52208066e+00 6.31076753e-01 7.95472383e-01
5.35535574e-01 7.29367971e-01 6.33316040e-01 -6.16108537e-01
-2.23234391e+00 -1.20379329e+00 9.13117766e-01 -4.99981850e-01
1.16944361e+00 -4.03123647e-01 -9.28729773e-01 1.11019897e+00
1.78857312e-01 3.08933288e-01 9.25676346e-01 3.84780437e-01
-4.49030399e-01 -1.80804789e-01 -8.63561630e-01 6.52457595e-01
1.38262904e+00 -6.06761694e-01 -5.81266403e-01 3.33729357e-01
1.05007172e+00 -5.73746162e-03 -1.18102574e+00 2.99349823e-03
4.51802939e-01 -6.96301997e-01 8.94736052e-01 -1.05443871e+00
3.28070857e-02 -2.59831369e-01 -2.29816303e-01 -1.49979508e+00
-6.68336928e-01 -7.32707441e-01 -7.16578424e-01 1.04175317e+00
1.76002294e-01 -9.77767706e-01 9.43329871e-01 1.58940524e-01
-2.41457652e-02 -9.69368875e-01 -5.49821854e-01 -1.10686207e+00
4.08710241e-02 -3.84564698e-01 6.38993084e-01 1.03981411e+00
5.31894147e-01 4.74196076e-01 -4.50665385e-01 5.44694841e-01
7.39014685e-01 1.76256746e-01 1.10803139e+00 -1.24041545e+00
-3.36704433e-01 -3.15583199e-01 -1.17905915e+00 -9.19667304e-01
3.69679630e-01 -1.33427584e+00 -6.17796123e-01 -2.01662374e+00
3.06105107e-01 -1.14166908e-01 -2.74939984e-01 3.32528949e-01
-6.11086264e-02 4.96543758e-02 -9.28540528e-02 1.08786533e-02
-7.72456765e-01 6.31727278e-01 9.65806603e-01 -1.38887018e-01
-3.52339298e-02 -2.03554526e-01 -1.18932760e+00 3.40671897e-01
1.08217084e+00 -6.66788816e-01 -7.41184413e-01 -2.98453510e-01
4.80239362e-01 -1.93485782e-01 7.08761960e-02 -6.70948803e-01
3.32265347e-01 -1.58539414e-01 -3.76344413e-01 -2.45568424e-01
-1.87304303e-01 -7.80034602e-01 -1.25014126e-01 5.53893924e-01
-6.51361421e-02 3.41003388e-01 -1.94611270e-02 1.18997431e+00
1.84327364e-03 -3.29021245e-01 3.75588149e-01 1.16185687e-01
-7.19811976e-01 6.56992376e-01 -1.98098093e-01 1.70609221e-01
1.06855452e+00 -2.72385955e-01 -2.86826789e-01 -4.77604896e-01
-5.63735783e-01 7.36894086e-02 7.59956539e-01 1.96831748e-01
7.97497809e-01 -1.66667545e+00 -6.19141161e-01 -3.74267052e-04
3.43383670e-01 -1.24286346e-01 -6.78170994e-02 7.46275127e-01
-6.27450764e-01 2.01557115e-01 1.97478145e-01 -9.48354527e-02
-1.06346953e+00 1.07506704e+00 2.47100601e-03 -4.55487430e-01
-8.63894224e-01 4.00731564e-01 -8.74460563e-02 -4.49802488e-01
3.98497004e-03 -4.02807027e-01 3.28980871e-02 -1.81550860e-01
6.46889269e-01 4.82683480e-01 -7.35714734e-02 -1.89088151e-01
-3.92089069e-01 5.19440889e-01 -2.53578275e-01 3.61628026e-01
1.53176391e+00 5.79558015e-02 -4.16676611e-01 3.81914645e-01
1.55936384e+00 2.97432423e-01 -4.32883173e-01 -4.10077482e-01
6.20522387e-02 -5.95117807e-01 -9.37632099e-02 1.68380871e-01
-1.13033712e+00 7.03172445e-01 -5.05379774e-02 7.58436918e-01
1.00630748e+00 3.35275769e-01 8.34215105e-01 7.53430963e-01
3.04347545e-01 -9.44454908e-01 3.62416863e-01 2.46604696e-01
6.49848342e-01 -9.70475197e-01 3.29451919e-01 -5.48617184e-01
-2.08071709e-01 1.38572931e+00 5.29825151e-01 -5.35100222e-01
8.43852639e-01 7.30868652e-02 -7.42851675e-01 -4.25814331e-01
-7.50741601e-01 -3.30895394e-01 1.56250000e-01 9.06143367e-01
2.47086182e-01 1.80773735e-01 -4.32707399e-01 7.80019403e-01
-2.87458509e-01 -2.08388105e-01 9.90994513e-01 9.18562353e-01
-5.28261602e-01 -1.39512908e+00 1.07104689e-01 6.90741301e-01
9.54867825e-02 -1.99208438e-01 -6.97776735e-01 9.59778368e-01
-5.77751219e-01 7.82616556e-01 -1.30900249e-01 -7.85027921e-01
4.08492178e-01 -5.45343272e-02 7.33883917e-01 -9.26055729e-01
1.33786649e-01 -5.34736276e-01 7.79591873e-02 -4.70859885e-01
-9.23946649e-02 -4.31029677e-01 -1.10142744e+00 -8.05503488e-01
-6.24443769e-01 4.62600529e-01 3.50309014e-01 3.63038421e-01
5.09982824e-01 4.06650752e-01 7.36613333e-01 -4.98465329e-01
-6.68591738e-01 -7.84829378e-01 -1.07948005e+00 2.10833073e-01
1.45931572e-01 -4.10764605e-01 -6.36623442e-01 -4.68832374e-01] | [7.133735179901123, 6.092657089233398] |
710d8813-ea67-4657-b25d-2172fd8cf3a2 | ecg-heartbeat-classification-a-deep | 1805.00794 | null | http://arxiv.org/abs/1805.00794v2 | http://arxiv.org/pdf/1805.00794v2.pdf | ECG Heartbeat Classification: A Deep Transferable Representation | Electrocardiogram (ECG) can be reliably used as a measure to monitor the
functionality of the cardiovascular system. Recently, there has been a great
attention towards accurate categorization of heartbeats. While there are many
commonalities between different ECG conditions, the focus of most studies has
been classifying a set of conditions on a dataset annotated for that task
rather than learning and employing a transferable knowledge between different
tasks. In this paper, we propose a method based on deep convolutional neural
networks for the classification of heartbeats which is able to accurately
classify five different arrhythmias in accordance with the AAMI EC57 standard.
Furthermore, we suggest a method for transferring the knowledge acquired on
this task to the myocardial infarction (MI) classification task. We evaluated
the proposed method on PhysionNet's MIT-BIH and PTB Diagnostics datasets.
According to the results, the suggested method is able to make predictions with
the average accuracies of 93.4% and 95.9% on arrhythmia classification and MI
classification, respectively. | ['Shayan Fazeli', 'Mohammad Kachuee', 'Majid Sarrafzadeh'] | 2018-04-19 | null | null | null | null | ['myocardial-infarction-detection', 'arrhythmia-detection', 'heartbeat-classification', 'electrocardiography-ecg'] | ['medical', 'medical', 'medical', 'methodology'] | [ 1.51785374e-01 -7.69520253e-02 2.18638584e-01 -6.06530726e-01
-5.50546348e-01 -3.62056106e-01 1.10752083e-01 4.78742033e-01
-2.32361361e-01 8.06323349e-01 -3.06652844e-01 -3.82103235e-01
-2.43910998e-01 -6.85992062e-01 -1.22674540e-01 -4.90024626e-01
-1.66760132e-01 4.24233049e-01 -2.74971485e-01 7.82300606e-02
1.88002005e-01 6.25792503e-01 -1.12663579e+00 4.83607441e-01
6.18915975e-01 1.36805463e+00 -3.16812903e-01 8.37338626e-01
2.98954666e-01 7.60402262e-01 -9.85269845e-01 -1.44938961e-01
2.17673741e-02 -8.40243697e-01 -9.31417584e-01 -2.72668689e-01
1.03565499e-01 -5.24957897e-03 1.63614884e-01 5.94651163e-01
1.02692056e+00 -4.84807134e-01 7.31527567e-01 -1.03396380e+00
-1.18011452e-01 6.64696753e-01 -7.43076438e-03 6.56664312e-01
1.08023666e-01 -1.12827376e-01 6.87925875e-01 -4.54104125e-01
3.35866660e-01 4.56918806e-01 1.14994884e+00 3.57053787e-01
-8.97089601e-01 -5.98249853e-01 -5.74063063e-01 4.30389702e-01
-1.49729097e+00 -2.11806044e-01 7.86099613e-01 -7.10846126e-01
5.58008492e-01 4.54365581e-01 9.31950629e-01 7.73911774e-01
4.55392212e-01 1.90604165e-01 1.12648094e+00 -4.70207244e-01
1.64855659e-01 2.31268376e-01 4.82728392e-01 4.37526256e-01
3.82207483e-01 -2.28724658e-01 -2.98577398e-01 -2.08114505e-01
5.44556856e-01 2.88154837e-02 -3.82506549e-01 -1.60281535e-03
-1.28651536e+00 4.23514456e-01 1.76982179e-01 7.66627669e-01
-6.02437496e-01 -4.91011404e-02 1.07869220e+00 4.18700725e-01
4.28126544e-01 7.18832672e-01 -7.32630491e-01 -2.61206418e-01
-8.74559402e-01 2.89275534e-02 9.23106968e-01 3.79849702e-01
4.20027196e-01 7.29107484e-02 -2.96438873e-01 6.32249177e-01
8.68137926e-02 1.81256875e-01 6.84519708e-01 -6.23328507e-01
1.49696529e-01 7.18194246e-01 1.56553853e-02 -1.14843392e+00
-8.68793368e-01 -8.67750883e-01 -1.33785248e+00 7.16755316e-02
3.33644837e-01 -4.44328576e-01 -5.94608188e-01 1.49819994e+00
-1.13244466e-01 3.15600157e-01 1.08452201e-01 8.35438073e-01
9.92306769e-01 2.82947779e-01 5.36190234e-02 -2.90059179e-01
1.20422304e+00 -1.65169403e-01 -7.85342336e-01 3.71808708e-01
8.62884045e-01 -3.80757511e-01 5.99367023e-01 7.02954590e-01
-7.93240845e-01 -9.66973662e-01 -1.21238923e+00 3.47078234e-01
-2.62205333e-01 6.00450695e-01 4.20132071e-01 9.10641253e-01
-1.03999805e+00 7.76970148e-01 -7.63094008e-01 -5.61601102e-01
4.00740325e-01 2.77459472e-01 -1.50168166e-01 4.89131004e-01
-1.50543165e+00 9.38747168e-01 6.60910189e-01 4.07713801e-01
-7.92318404e-01 -5.80544174e-01 -3.71707559e-01 1.90255880e-01
-3.71170342e-01 -7.28390574e-01 8.29983115e-01 -9.35636044e-01
-1.31265545e+00 1.06726205e+00 3.51570994e-01 -8.95995736e-01
5.98744154e-01 -1.49291337e-01 -6.38439894e-01 1.41691968e-01
-2.00014204e-01 3.30323160e-01 5.79903543e-01 -8.25573385e-01
-5.71273565e-01 -3.58365059e-01 -1.42702296e-01 4.34364080e-02
-4.18224603e-01 -5.53052053e-02 -4.73236777e-02 -5.04479527e-01
1.87407453e-02 -9.09059525e-01 6.49437755e-02 -3.44667941e-01
-4.87645119e-01 -1.60423338e-01 5.88242948e-01 -8.02517831e-01
1.49209154e+00 -2.05843496e+00 1.43698737e-01 3.27346563e-01
4.76584822e-01 5.21570683e-01 3.76212299e-01 3.49786282e-01
-3.64479184e-01 1.36221781e-01 -3.38870734e-01 -4.80940863e-02
-3.85550827e-01 2.04210326e-01 -1.46740571e-01 4.56110448e-01
-2.18521897e-03 7.94866085e-01 -4.94662970e-01 -3.51970732e-01
3.39713603e-01 4.71689761e-01 -1.17397800e-01 2.01946273e-01
4.08033639e-01 9.31988776e-01 -2.99129307e-01 3.42542291e-01
3.09919000e-01 -1.27953336e-01 4.67633784e-01 -3.61078203e-01
2.14558437e-01 4.10068929e-02 -9.88244116e-01 1.53785574e+00
-3.58731091e-01 6.56511486e-01 -5.03619611e-01 -1.54761589e+00
1.21746957e+00 8.15536499e-01 7.94577599e-01 -1.72850639e-01
3.79924864e-01 2.86909461e-01 5.39713144e-01 -5.83626688e-01
-2.99255341e-01 -1.05245963e-01 6.90564979e-03 4.25579250e-01
1.31555215e-01 6.06363602e-02 4.35526520e-02 -3.16879183e-01
1.09832859e+00 -2.79124007e-02 5.59151053e-01 -4.69158500e-01
8.80616367e-01 -2.54500210e-01 6.27530098e-01 7.00856924e-01
-4.04477566e-01 6.49315894e-01 3.86217684e-01 -1.14319849e+00
-6.91456020e-01 -6.72371626e-01 -4.32412386e-01 3.22818369e-01
-2.19454482e-01 -4.32503462e-01 -8.77657413e-01 -5.69954872e-01
-2.42284611e-01 2.38232151e-01 -7.19267249e-01 -3.38411450e-01
-4.86914754e-01 -1.10982418e+00 1.18295097e+00 5.81391811e-01
6.93919599e-01 -1.38269770e+00 -1.25733113e+00 3.20334077e-01
-2.91356236e-01 -9.06283081e-01 3.38125676e-01 3.12938541e-01
-1.00802028e+00 -1.24042487e+00 -6.86437309e-01 -6.98642373e-01
1.66319594e-01 -4.71656084e-01 1.19515264e+00 2.32305586e-01
-7.71783769e-01 1.43774137e-01 -4.21886951e-01 -8.93716455e-01
-6.46011353e-01 3.99570286e-01 1.16944790e-01 3.96303236e-01
2.59597331e-01 -5.50212979e-01 -7.45075643e-01 1.82182804e-01
-5.60194314e-01 1.76019110e-02 4.88134652e-01 6.06721878e-01
4.26732630e-01 -3.25108320e-02 1.12454963e+00 -1.03603959e+00
7.12735653e-01 -3.31858367e-01 -5.12802787e-02 1.10075235e-01
-8.71615946e-01 -4.94410098e-01 5.86450219e-01 -3.51765081e-02
-5.81897378e-01 7.43940026e-02 -3.56325567e-01 -2.83818454e-01
-5.31970918e-01 6.58990562e-01 -1.30141554e-02 9.72132012e-02
9.34819996e-01 1.75773755e-01 -1.35069802e-01 -2.68249035e-01
-2.16917932e-01 9.50577557e-01 5.52325308e-01 -4.18554515e-01
2.11705104e-01 1.58948004e-01 2.12426752e-01 -7.74436176e-01
-8.06670487e-01 -4.18885767e-01 -8.56500983e-01 -3.61838877e-01
1.13395154e+00 -6.46587074e-01 -5.12373984e-01 8.01147699e-01
-1.04755402e+00 -6.08241074e-02 -3.22767198e-01 5.01422286e-01
-5.46838164e-01 4.59402174e-01 -6.47249997e-01 -6.73304200e-01
-8.48316371e-01 -9.24634635e-01 7.32207716e-01 -2.18452662e-01
-6.39094770e-01 -9.98109579e-01 2.25476250e-01 9.01039019e-02
4.45796132e-01 6.97118461e-01 9.20368433e-01 -9.23830688e-01
1.05772234e-01 -4.55048889e-01 8.22316762e-03 7.27758467e-01
5.35640895e-01 -1.64531350e-01 -1.16914010e+00 -2.10364625e-01
2.71204978e-01 -1.17159635e-01 4.97269839e-01 4.41035628e-01
1.53178704e+00 1.54331923e-01 -2.21724257e-01 6.70576751e-01
1.18639898e+00 5.56407511e-01 8.26859057e-01 2.08194733e-01
5.61398804e-01 1.90299392e-01 4.05693233e-01 5.19557714e-01
4.49950397e-02 6.27636373e-01 2.54385173e-01 -3.88109565e-01
8.27725679e-02 4.75715101e-01 -1.09809145e-01 8.75874937e-01
-5.55367529e-01 -4.64402102e-02 -1.20557523e+00 2.77096689e-01
-1.77963543e+00 -8.06313038e-01 -4.18538511e-01 2.14822602e+00
7.92321146e-01 2.11160108e-01 5.27007505e-02 8.20841551e-01
8.35727513e-01 -2.30646595e-01 -3.10783744e-01 -5.75547397e-01
5.84100485e-02 4.46399033e-01 -8.21511149e-02 4.25042547e-02
-1.33595407e+00 2.79202253e-01 6.16412640e+00 2.68238604e-01
-1.54183888e+00 1.58491030e-01 1.02550566e+00 5.18581450e-01
5.44945002e-01 -4.38186824e-01 -3.56975436e-01 5.12630522e-01
1.32988524e+00 -2.57500783e-02 -5.97382076e-02 4.40579057e-01
2.00357065e-01 3.63788992e-01 -1.28035629e+00 1.21293521e+00
1.24320798e-01 -1.25205028e+00 -1.34951055e-01 -2.48449594e-01
3.51318657e-01 -2.02627957e-01 -1.74688295e-01 2.78080821e-01
-6.95126534e-01 -1.10925412e+00 3.13351870e-01 8.11936915e-01
9.77038920e-01 -6.80557907e-01 1.35125220e+00 3.18396062e-01
-8.47024262e-01 -2.53784820e-04 -9.20997038e-02 -2.44949728e-01
-2.71017164e-01 7.15371668e-01 -1.00118577e+00 7.96419919e-01
8.35719585e-01 9.65904415e-01 -5.30804038e-01 1.11285543e+00
-3.27283889e-02 9.80994761e-01 -5.62093174e-03 2.68675476e-01
-2.95091242e-01 -7.76120201e-02 3.04501981e-01 1.16245842e+00
3.97627801e-01 -1.17767125e-01 1.52790427e-01 5.81461608e-01
8.19584802e-02 4.39073652e-01 -5.80919385e-01 1.11809857e-01
-4.89082523e-02 1.36822903e+00 -8.07592154e-01 -6.69250965e-01
-6.76012933e-02 8.59076202e-01 -3.31620090e-02 5.98409027e-02
-1.04381716e+00 -5.46739221e-01 1.02505997e-01 7.20568225e-02
-1.54533267e-01 3.58043730e-01 -7.19257832e-01 -9.69853759e-01
-8.00024346e-02 -8.60187709e-01 4.60113376e-01 -7.21326828e-01
-1.11736441e+00 1.00663686e+00 -2.26389885e-01 -1.47778904e+00
-2.54436970e-01 -5.30496776e-01 -6.79872513e-01 1.12373781e+00
-1.11885107e+00 -8.90725970e-01 -6.10235333e-01 3.68259698e-01
2.94168115e-01 -2.98705667e-01 1.41480923e+00 6.87151730e-01
-5.28431952e-01 5.56134105e-01 -2.46856451e-01 3.94922346e-01
8.27380121e-01 -1.34999120e+00 1.00579755e-02 5.86563587e-01
1.01182476e-01 4.75789309e-01 4.40917969e-01 -2.23182261e-01
-6.59365594e-01 -1.34618354e+00 8.93955648e-01 -5.10992706e-01
1.48344070e-01 7.57439584e-02 -9.35258508e-01 4.96086895e-01
1.76689342e-01 1.99814409e-01 1.00196564e+00 2.42839847e-02
-2.97624152e-02 -4.40712124e-01 -1.08408761e+00 -8.55105519e-02
5.30357301e-01 -3.96420032e-01 -5.89821517e-01 2.30961800e-01
-1.59939408e-01 -4.45906639e-01 -1.33631098e+00 8.06509376e-01
6.80668890e-01 -1.01928413e+00 7.67078698e-01 -6.97165489e-01
3.37742329e-01 -3.51995677e-01 1.90003797e-01 -1.45824718e+00
-2.18066320e-01 -3.57565582e-01 -5.79384491e-02 9.47939873e-01
2.94189185e-01 -7.22488046e-01 4.99479651e-01 1.69464976e-01
-2.33876616e-01 -9.06279266e-01 -7.48397768e-01 -3.50214303e-01
-1.19174428e-01 -4.73022223e-01 3.84517789e-01 1.25093532e+00
-1.22834623e-01 3.73358846e-01 -3.03699821e-01 6.49234578e-02
2.63693005e-01 1.76504761e-01 6.29775405e-01 -1.80334651e+00
-3.09471011e-01 -2.43605003e-01 -9.10609484e-01 -1.57965459e-02
-8.19200054e-02 -1.10562313e+00 -2.37013713e-01 -1.42318904e+00
1.77619621e-01 -6.24063730e-01 -1.14104223e+00 4.41267431e-01
-9.00363252e-02 6.09418511e-01 -1.03182845e-01 2.73159951e-01
-2.96120137e-01 -1.73436210e-01 7.77009964e-01 -8.41631964e-02
-3.47301930e-01 4.21555251e-01 -5.40808082e-01 8.08950484e-01
1.23506975e+00 -2.79406160e-01 -4.80191022e-01 -1.97422579e-02
2.15919062e-01 2.55439430e-01 2.93363184e-01 -1.62768018e+00
-3.00573826e-01 5.29134393e-01 6.71205521e-01 -4.64161694e-01
4.73001190e-02 -7.15308070e-01 5.34847558e-01 8.95070016e-01
-5.84187210e-01 4.74056080e-02 2.15928555e-01 3.42194647e-01
-4.35636848e-01 -7.19142407e-02 7.79786825e-01 -1.12235770e-01
-3.58528525e-01 2.10314065e-01 -4.98176455e-01 1.15878776e-01
1.09349513e+00 -9.60647315e-02 1.09089136e-01 -2.40858689e-01
-1.18434250e+00 -2.21642315e-01 -8.67223293e-02 2.84452289e-01
5.44683516e-01 -1.10054195e+00 -8.68391037e-01 1.35617837e-01
2.91479439e-01 -2.64277369e-01 2.69569576e-01 1.16011918e+00
-9.85622704e-01 6.12720668e-01 -6.33161545e-01 -9.26813900e-01
-1.39401352e+00 3.01718980e-01 8.53717506e-01 -2.64344126e-01
-7.30927587e-01 3.67572337e-01 -1.05194166e-01 -1.61423147e-01
2.07735822e-01 -6.59919620e-01 -7.46326923e-01 1.26323208e-01
3.62777323e-01 3.76332968e-01 5.90359926e-01 -3.72537464e-01
-4.58134383e-01 5.45371652e-01 2.36446068e-01 3.78201485e-01
1.20302951e+00 1.19346984e-01 -2.03937516e-01 7.93738127e-01
9.29626703e-01 -3.89831305e-01 -3.48762512e-01 2.58740783e-01
7.44616315e-02 9.32029411e-02 -3.97693105e-02 -1.04643929e+00
-1.24054420e+00 1.36671841e+00 1.30628765e+00 6.26824915e-01
1.29257202e+00 -5.22593319e-01 5.92390776e-01 4.42404687e-01
4.68701631e-01 -8.16017210e-01 -4.62450415e-01 1.07605979e-01
6.99843824e-01 -1.02926278e+00 -1.64308682e-01 -3.44114006e-01
-6.71231627e-01 1.41849899e+00 3.49380583e-01 -1.28323942e-01
8.77481699e-01 -5.46848495e-03 4.30861831e-01 -2.62617856e-01
-4.02132303e-01 2.36814633e-01 2.58182943e-01 5.49065769e-01
7.95758009e-01 2.32945114e-01 -6.89251661e-01 6.69898570e-01
2.14915246e-01 5.26901603e-01 5.73051810e-01 7.26494551e-01
-2.16546267e-01 -1.01757002e+00 -5.27578443e-02 6.40867174e-01
-9.85836029e-01 3.69929299e-02 -4.02532160e-01 5.80673575e-01
4.31438953e-01 8.28227222e-01 -1.63680330e-01 -4.13073570e-01
1.40453145e-01 5.33008873e-01 3.68242174e-01 -7.41358161e-01
-9.51819658e-01 -1.98727503e-01 1.13976181e-01 -1.82427198e-01
-6.88928902e-01 -4.06268179e-01 -1.11370885e+00 4.34842706e-01
6.57868385e-02 2.82406598e-01 5.62291563e-01 1.01313353e+00
5.49545407e-01 1.03670895e+00 5.75779855e-01 -4.08033133e-01
-4.15023685e-01 -1.27127635e+00 -7.17455804e-01 6.45924509e-01
1.31395027e-01 -3.87068659e-01 -1.66518494e-01 3.14862132e-01] | [14.323248863220215, 3.3144633769989014] |
64a4f6a5-e7e4-486c-85f4-9d1b697cca67 | fine-grained-analysis-of-propaganda-in-news | 1910.02517 | null | https://arxiv.org/abs/1910.02517v1 | https://arxiv.org/pdf/1910.02517v1.pdf | Fine-Grained Analysis of Propaganda in News Articles | Propaganda aims at influencing people's mindset with the purpose of advancing a specific agenda. Previous work has addressed propaganda detection at the document level, typically labelling all articles from a propagandistic news outlet as propaganda. Such noisy gold labels inevitably affect the quality of any learning system trained on them. A further issue with most existing systems is the lack of explainability. To overcome these limitations, we propose a novel task: performing fine-grained analysis of texts by detecting all fragments that contain propaganda techniques as well as their type. In particular, we create a corpus of news articles manually annotated at the fragment level with eighteen propaganda techniques and we propose a suitable evaluation measure. We further design a novel multi-granularity neural network, and we show that it outperforms several strong BERT-based baselines. | ['Alberto Barrón-Cedeño', 'Giovanni Da San Martino', 'Rostislav Petrov', 'Preslav Nakov', 'Seunghak Yu'] | 2019-10-06 | null | null | null | null | ['propaganda-detection'] | ['natural-language-processing'] | [ 3.16335678e-01 3.19319814e-01 -7.29676306e-01 -1.87919185e-01
-8.99928093e-01 -5.77664137e-01 1.30751777e+00 4.56806034e-01
-4.17267501e-01 7.30855286e-01 1.10967600e+00 -6.48846269e-01
3.92947108e-01 -7.95423329e-01 -7.21347809e-01 -4.07545954e-01
3.65956515e-01 3.67972165e-01 2.26707347e-02 -3.19262981e-01
5.45623899e-01 -2.76571542e-01 -7.91514218e-01 7.84550667e-01
9.98377979e-01 2.89023578e-01 -4.65594918e-01 6.24700129e-01
-1.82978347e-01 1.43882346e+00 -1.20025253e+00 -5.57347417e-01
-1.39956057e-01 -7.35443473e-01 -1.20283508e+00 -4.96768728e-02
6.31363571e-01 -3.96803051e-01 -4.04144600e-02 1.06137669e+00
1.64341450e-01 -3.14161420e-01 9.85335588e-01 -5.57543755e-01
-1.03590989e+00 1.41132498e+00 -6.52266502e-01 4.25364763e-01
3.59935820e-01 -2.16044948e-01 1.18416452e+00 -4.97158200e-01
8.78187358e-01 1.53197432e+00 7.11046815e-01 6.87227249e-01
-1.14013815e+00 -3.11431050e-01 4.20787215e-01 1.12192683e-01
-7.40604877e-01 -2.62941122e-01 9.11446333e-01 -7.72759616e-01
6.05726480e-01 2.70517826e-01 5.50032079e-01 1.87117302e+00
3.23322713e-01 8.97456348e-01 1.24202943e+00 -6.82417512e-01
6.25275075e-02 -8.46038014e-02 5.40544689e-01 6.42616987e-01
3.84968311e-01 -3.16869020e-01 -3.55218828e-01 -2.42901683e-01
2.96734512e-01 -3.91798556e-01 -2.04592928e-01 3.37312043e-01
-1.18165290e+00 1.33512294e+00 4.86559540e-01 6.39991820e-01
-2.63332576e-01 3.30531836e-01 4.81675386e-01 1.89425543e-01
1.10222232e+00 7.54150927e-01 -1.41145915e-01 -1.05632968e-01
-9.99187768e-01 6.67268276e-01 9.56946313e-01 3.42666298e-01
2.11426839e-01 -3.03971022e-01 -6.36077702e-01 4.59901750e-01
1.51172459e-01 3.97180110e-01 2.55624235e-01 -3.81971002e-01
6.35225475e-01 5.23000538e-01 1.61754906e-01 -1.33750665e+00
-7.27214098e-01 -6.11453295e-01 -6.94500685e-01 -2.51755089e-01
6.04725599e-01 -3.39346349e-01 -8.56462955e-01 1.51301372e+00
3.82052332e-01 -2.81724364e-01 -4.35190946e-01 8.89303386e-01
9.96597946e-01 7.65238941e-01 3.40746999e-01 -2.89218545e-01
1.42850792e+00 -1.18869781e+00 -9.86235738e-01 -2.90553778e-01
1.00433886e+00 -8.41791272e-01 9.77823436e-01 2.36601606e-01
-6.60918534e-01 -9.64801162e-02 -7.93669522e-01 -2.30673000e-01
-2.27146104e-01 1.41836116e-02 6.47744119e-01 6.07873857e-01
-3.76390219e-01 3.67175579e-01 -6.82787120e-01 -1.94146946e-01
4.11918581e-01 -4.47563350e-01 2.01720774e-01 3.38194430e-01
-1.41666532e+00 1.24406815e+00 3.00791979e-01 -1.83849007e-01
-7.83131599e-01 -6.40038848e-01 -7.39554644e-01 -6.75810650e-02
5.26840091e-01 -6.20947063e-01 1.45767128e+00 -1.14149344e+00
-1.03339505e+00 7.84830689e-01 4.47893329e-02 -7.13738203e-01
5.75168312e-01 -6.34166539e-01 -5.62511742e-01 -2.76726037e-02
4.89829838e-01 7.22540468e-02 1.10570133e+00 -1.06507444e+00
-5.83234787e-01 7.30516389e-02 3.01843464e-01 -3.24799940e-02
-3.05076748e-01 5.23697197e-01 3.64205748e-01 -9.72000659e-01
-2.59491742e-01 -7.27948427e-01 -9.05704349e-02 -6.49440885e-01
-8.35728109e-01 -5.64191997e-01 6.08752191e-01 -7.80970752e-01
1.62222111e+00 -1.71399736e+00 -2.55945530e-02 -6.11710474e-02
6.96985841e-01 3.16263497e-01 -3.91477831e-02 5.56836665e-01
2.97302306e-01 6.39589310e-01 1.87051356e-01 4.08746228e-02
3.22330594e-02 -1.16702572e-01 -5.49809277e-01 6.58073306e-01
2.42947772e-01 9.49359834e-01 -1.08674157e+00 -4.35635298e-01
-2.17237085e-01 2.95552760e-01 -6.69829130e-01 -1.73285499e-01
-7.03445852e-01 3.92621249e-01 -7.83151090e-01 3.49472195e-01
3.07125002e-01 -6.62292123e-01 1.46462813e-01 1.28712729e-01
-3.23187739e-01 1.19549310e+00 -4.24477816e-01 1.13222897e+00
-3.39313686e-01 8.19980383e-01 -4.30337414e-02 -7.12792575e-01
3.02834213e-01 2.73954749e-01 1.79761052e-01 -4.92893726e-01
4.36113566e-01 -4.98661362e-02 1.32047534e-01 -4.72287655e-01
5.68751156e-01 -2.57481605e-01 -5.22260010e-01 1.01412904e+00
-3.32705826e-01 2.49087915e-01 2.27792516e-01 6.15312874e-01
1.26404119e+00 -1.19593874e-01 6.78550541e-01 -2.93299615e-01
3.86369824e-01 4.54803199e-01 1.99895233e-01 1.27677584e+00
-2.67684370e-01 3.65914255e-01 5.47883809e-01 -8.72226417e-01
-9.11392510e-01 -7.05939710e-01 -2.02837870e-01 1.61078942e+00
-1.16177619e-01 -7.58955598e-01 -8.30643058e-01 -1.35104334e+00
-2.14174226e-01 9.20274496e-01 -1.15457630e+00 2.46250749e-01
-9.29552913e-01 -8.54552686e-01 5.38288236e-01 1.69829726e-01
3.90643150e-01 -1.09606361e+00 -5.25992393e-01 4.55458343e-01
-5.59637129e-01 -8.22864473e-01 -3.87899846e-01 -4.43194844e-02
-1.05767161e-01 -1.21690500e+00 -3.00140291e-01 -6.27822399e-01
5.21821737e-01 1.75023943e-01 1.30711007e+00 3.65470797e-01
1.76672101e-01 -2.27850586e-01 -6.92267954e-01 -5.09712756e-01
-1.16052186e+00 4.16231513e-01 -1.28470421e-01 -3.62543136e-01
4.42041427e-01 -7.76373297e-02 -2.71622211e-01 -2.54548162e-01
-6.84387684e-01 3.86081189e-01 4.28122520e-01 8.88867319e-01
-1.90093070e-01 -1.26682758e-01 6.62298560e-01 -1.46039677e+00
1.09840524e+00 -5.61870456e-01 -1.41371042e-01 1.71820208e-01
-3.05126578e-01 7.35058263e-02 7.07403421e-01 -4.40416545e-01
-1.13619077e+00 -5.01575947e-01 -2.45541900e-01 7.11197436e-01
-2.43722826e-01 7.18129098e-01 4.25078511e-01 4.33713883e-01
1.48615217e+00 -1.35741353e-01 -4.53562915e-01 -5.58913589e-01
7.52322912e-01 7.86644340e-01 3.59207898e-01 -4.17471975e-01
8.96574438e-01 3.22266072e-01 -5.47080517e-01 -5.98787308e-01
-1.96674228e+00 -6.29739702e-01 -3.79053861e-01 -3.21647115e-02
7.35799968e-01 -7.38476217e-01 -4.10622299e-01 1.43724009e-01
-1.53936744e+00 -1.16625428e-01 1.25962585e-01 3.49031687e-01
-2.41579950e-01 2.83414543e-01 -1.04903126e+00 -7.49354243e-01
-5.42450607e-01 -4.59998816e-01 8.65606904e-01 -2.55534887e-01
-7.21149147e-01 -1.11579216e+00 3.72954518e-01 5.47344506e-01
2.50504225e-01 3.90358120e-01 1.04339099e+00 -9.44272816e-01
4.48481329e-02 -5.90158962e-02 -2.27149293e-01 -5.68464585e-02
1.69468999e-01 -6.73013180e-02 -7.27526426e-01 7.97664151e-02
1.68599054e-01 -5.09337425e-01 1.19518983e+00 4.85528886e-01
5.65974295e-01 -1.34612811e+00 -4.02855247e-01 3.87286842e-02
8.63322973e-01 -3.17559272e-01 2.31163159e-01 8.43057454e-01
7.98394442e-01 5.32256305e-01 3.83586943e-01 3.26581746e-01
3.12365502e-01 3.97761256e-01 2.52136976e-01 -1.48831666e-01
-1.62878111e-01 -4.71042782e-01 4.83798027e-01 6.17463887e-01
-4.87595126e-02 -5.70720196e-01 -9.55400884e-01 6.76626325e-01
-1.88478792e+00 -1.56524694e+00 -5.01574695e-01 1.39542150e+00
1.23837137e+00 3.09817821e-01 2.97970772e-01 1.42815486e-01
7.44119227e-01 5.83446205e-01 2.63345659e-01 -6.33672535e-01
2.81132068e-02 -5.93914017e-02 1.45031348e-01 7.84685075e-01
-1.77599657e+00 1.04760242e+00 6.94282532e+00 7.66236544e-01
-9.86283243e-01 3.03599149e-01 5.03832638e-01 -2.24319786e-01
-4.31710750e-01 -2.31570065e-01 -8.76321256e-01 4.99565899e-01
8.90377164e-01 -4.80193943e-02 8.03795159e-02 9.23034668e-01
4.73350972e-01 1.28018409e-01 -8.06577027e-01 2.49389529e-01
2.53958911e-01 -1.84896517e+00 2.38938615e-01 -2.23318487e-02
1.14493966e+00 -5.43219503e-03 -1.10454455e-01 3.40685040e-01
6.85592175e-01 -1.03556597e+00 1.10991037e+00 -2.45337680e-01
2.84879565e-01 -4.31051910e-01 6.37447417e-01 6.32498205e-01
-4.59825814e-01 1.40695468e-01 4.02855054e-02 -6.48359716e-01
4.80691791e-01 7.77729750e-01 -1.13373041e+00 1.76294401e-01
1.13885239e-01 6.49239302e-01 -6.02946401e-01 4.88794267e-01
-9.71744776e-01 1.41319835e+00 -9.71393734e-02 -5.51178455e-01
7.38083720e-01 4.92927462e-01 6.52329922e-01 1.61902905e+00
-1.93392649e-01 3.82510535e-02 3.55840474e-01 9.13832307e-01
-2.86648035e-01 2.34879524e-01 -3.31910253e-01 -3.45631897e-01
2.44747207e-01 1.13345277e+00 -5.92574060e-01 -5.71973801e-01
-3.09981674e-01 5.34234822e-01 4.96445298e-01 1.25759885e-01
-9.73827660e-01 2.21016571e-01 2.29126200e-01 4.33023751e-01
-6.69439062e-02 -8.30668658e-02 -3.86818022e-01 -1.23398066e+00
-5.89607880e-02 -9.35895622e-01 5.26088655e-01 -1.19608991e-01
-1.45449829e+00 4.62225258e-01 -2.93053627e-01 -6.52677953e-01
-4.14875299e-01 -3.65143955e-01 -7.14939594e-01 4.30101693e-01
-1.26933658e+00 -1.48994708e+00 -5.85284550e-04 3.16614136e-02
7.28519440e-01 3.27666372e-01 5.66283643e-01 -1.06002875e-01
-3.10824752e-01 2.68192649e-01 -1.33481130e-01 4.74842846e-01
7.95712113e-01 -1.16991842e+00 6.88609004e-01 1.05005598e+00
3.57252359e-01 8.86213183e-01 1.28749311e+00 -9.42922413e-01
-6.92366660e-01 -1.16785181e+00 1.51893282e+00 -9.85517561e-01
1.17866254e+00 -4.20240194e-01 -8.57075155e-01 7.15882540e-01
3.74660045e-01 -5.80914140e-01 5.96402824e-01 8.52114916e-01
-7.60896087e-01 7.87736297e-01 -7.72792101e-01 6.11755252e-01
9.86969471e-01 -3.84486586e-01 -1.06588197e+00 9.20460463e-01
6.37052417e-01 -2.78712481e-01 -1.55352026e-01 4.67846431e-02
4.45446342e-01 -5.30723870e-01 4.72045541e-01 -1.13609374e+00
1.16270721e+00 6.76797656e-03 4.25055504e-01 -1.32853222e+00
-6.35088742e-01 -6.03727579e-01 -2.99927950e-01 1.08163011e+00
4.83703673e-01 -2.07107216e-01 6.15307987e-01 5.23148514e-02
-1.56305190e-02 -3.93433362e-01 -6.58944309e-01 -6.90827608e-01
4.30102110e-01 -3.21515501e-01 7.40718991e-02 1.24611402e+00
4.84927982e-01 9.92565274e-01 -9.48845744e-01 -4.12679166e-02
4.37663674e-01 2.02509865e-01 7.03428328e-01 -1.04564905e+00
-2.69465744e-01 -5.96359313e-01 8.73969570e-02 -1.04482174e+00
1.18556470e-01 -8.24832439e-01 2.71728873e-01 -1.87613320e+00
5.45213223e-01 -1.10521317e-02 9.77582783e-02 4.58604574e-01
-3.80062252e-01 1.69408619e-01 -9.94987264e-02 2.90448874e-01
-8.37188721e-01 2.16891259e-01 1.23440683e+00 -3.54712784e-01
-2.44693920e-01 -1.50007859e-01 -9.96903956e-01 1.16465759e+00
8.57160807e-01 -7.87252486e-01 1.23949982e-01 -6.42878592e-01
5.82613409e-01 -4.73445624e-01 4.45650309e-01 -5.60097039e-01
-7.53177702e-02 -4.92993176e-01 1.85400426e-01 -5.69482625e-01
-2.53240287e-01 -8.80402103e-02 -3.49649549e-01 6.51393652e-01
-8.58350635e-01 -3.02225679e-01 -4.22222972e-01 6.05358481e-01
2.52632871e-02 -1.98412329e-01 6.07152462e-01 -1.45857260e-01
-2.85476118e-01 -1.89675897e-01 -8.54246378e-01 3.95186961e-01
5.53867161e-01 4.13890421e-01 -1.32221437e+00 -3.96331638e-01
-4.90156412e-01 -1.99989960e-01 3.61513942e-01 5.15045464e-01
-6.51475880e-03 -1.17726958e+00 -1.15388596e+00 -2.55823433e-01
1.14271440e-01 -4.08733815e-01 -1.80361301e-01 8.91586781e-01
-5.83542824e-01 5.67171454e-01 1.61766082e-01 -9.63445827e-02
-1.17422283e+00 5.80573559e-01 -6.97354451e-02 -6.04754448e-01
-7.93411255e-01 7.46952116e-01 3.17343742e-01 3.83447930e-02
-5.04699312e-02 -2.47403726e-01 -5.30623913e-01 1.07840322e-01
9.68424261e-01 1.90104365e-01 -1.91422582e-01 -7.04854786e-01
-3.77749979e-01 -1.08993299e-01 -4.47775751e-01 -4.01527062e-03
1.26006138e+00 -1.06105255e-02 -1.76811337e-01 2.17786759e-01
8.21965694e-01 6.03662133e-01 -6.45420551e-01 -2.34824002e-01
1.99438304e-01 -2.60855973e-01 2.40487996e-02 -1.12252510e+00
-2.56773949e-01 5.53422391e-01 -2.43697047e-01 7.80048311e-01
3.98553222e-01 3.83975059e-01 7.44983971e-01 4.11480814e-01
-2.71187518e-02 -1.27190542e+00 1.86497122e-01 8.91852856e-01
1.02909791e+00 -1.21721423e+00 1.96102470e-01 -5.52290678e-01
-3.97339195e-01 8.46474349e-01 3.34185511e-01 -9.83852223e-02
2.79437691e-01 1.10792898e-01 4.52895015e-01 -6.10158324e-01
-7.05105126e-01 -1.69313729e-01 6.55090511e-01 2.94360280e-01
9.26817298e-01 2.25974202e-01 -1.14056337e+00 6.26847684e-01
-3.73151511e-01 -5.09309173e-01 6.53143644e-01 7.42584527e-01
-9.74611104e-01 -7.54406214e-01 -4.43236262e-01 4.33590680e-01
-1.00834012e+00 -4.03446615e-01 -1.08565712e+00 6.28993750e-01
1.54705852e-01 1.16158652e+00 -3.04903060e-01 -1.89428300e-01
-2.72400856e-01 -1.83503926e-01 4.14710760e-01 -9.58923161e-01
-1.05323529e+00 1.88889295e-01 8.75357926e-01 -1.65906966e-01
-6.30279899e-01 -4.24317420e-01 -8.82101417e-01 -6.19401217e-01
-4.15193319e-01 4.69484121e-01 4.87636387e-01 1.30924642e+00
-1.26488537e-01 4.02272433e-01 3.50156546e-01 -4.26926404e-01
-7.75757015e-01 -1.29645479e+00 -5.02182096e-02 8.40673804e-01
5.17296493e-01 -4.53159243e-01 -4.24214751e-01 1.48514673e-01] | [8.506986618041992, 10.600865364074707] |
65e075f7-1b16-4e1f-a526-db701b63db70 | better-query-graph-selection-for-knowledge | 2204.12662 | null | https://arxiv.org/abs/2204.12662v1 | https://arxiv.org/pdf/2204.12662v1.pdf | Better Query Graph Selection for Knowledge Base Question Answering | This paper presents a novel approach based on semantic parsing to improve the performance of Knowledge Base Question Answering (KBQA). Specifically, we focus on how to select an optimal query graph from a candidate set so as to retrieve the answer from knowledge base (KB). In our approach, we first propose to linearize the query graph into a sequence, which is used to form a sequence pair with the question. It allows us to use mature sequence modeling, such as BERT, to encode the sequence pair. Then we use a ranking method to sort candidate query graphs. In contrast to the previous studies, our approach can efficiently model semantic interactions between the graph and the question as well as rank the candidate graphs from a global view. The experimental results show that our system achieves the top performance on ComplexQuestions and the second best performance on WebQuestions. | ['Wenliang Chen', 'Yonghui Jia'] | 2022-04-27 | null | null | null | null | ['knowledge-base-question-answering'] | ['natural-language-processing'] | [ 4.55130078e-02 3.74510914e-01 -2.20627680e-01 -3.42232317e-01
-1.18966949e+00 -9.49079812e-01 1.19037054e-01 2.41566941e-01
-2.89829850e-01 7.84160554e-01 1.03217393e-01 -4.86622125e-01
-1.41696885e-01 -1.23495603e+00 -9.39135790e-01 -2.56191492e-02
3.67801994e-01 8.46754193e-01 1.17606592e+00 -5.73525250e-01
4.34501916e-01 1.10774197e-01 -1.54603589e+00 6.52582109e-01
1.35319054e+00 7.77987659e-01 6.15463316e-01 7.20097959e-01
-1.01263034e+00 9.72779930e-01 -5.81400871e-01 -7.52337158e-01
-2.94096768e-01 -7.48282492e-01 -1.63538480e+00 -3.70524704e-01
4.43724334e-01 -1.94307372e-01 -2.98563652e-02 1.17903674e+00
2.96266437e-01 8.43706876e-02 2.47272223e-01 -1.04183757e+00
-5.80153286e-01 6.26613200e-01 7.71918818e-02 2.37090215e-01
1.04131567e+00 -4.31735247e-01 1.49347067e+00 -6.10447109e-01
9.46474910e-01 1.37028515e+00 1.75370172e-01 6.28835261e-01
-6.59961760e-01 -3.99113774e-01 1.77391142e-01 9.91693735e-01
-1.10786939e+00 -1.87205359e-01 7.10059941e-01 -3.04296911e-02
9.89804387e-01 5.41897237e-01 5.24231732e-01 3.22289735e-01
-2.74159312e-01 8.25407505e-01 7.10936129e-01 -6.97836101e-01
2.96394616e-01 -9.54733342e-02 8.19944263e-01 1.12679183e+00
1.27681583e-01 -5.60491145e-01 -3.70870203e-01 -5.91552913e-01
4.21497345e-01 -5.89477777e-01 -2.78026193e-01 -3.80224973e-01
-7.19699621e-01 8.70124280e-01 3.82973611e-01 1.51928514e-01
-2.39090323e-01 3.10725898e-01 1.88994512e-01 4.14224088e-01
-7.45994300e-02 6.76199496e-01 -6.94834292e-01 6.28399327e-02
-3.07381511e-01 4.66822743e-01 1.41919518e+00 9.75818694e-01
1.15735590e+00 -7.24046767e-01 -1.56118333e-01 7.83541024e-01
4.33126628e-01 4.57013160e-01 2.39146248e-01 -1.17266905e+00
7.09675252e-01 9.48263943e-01 2.70650685e-01 -1.01934767e+00
-1.41166970e-01 9.73785743e-02 2.64164954e-01 -6.40159965e-01
4.06564444e-01 2.86603391e-01 -8.66313994e-01 1.60605669e+00
4.78833348e-01 2.13778347e-01 3.17264557e-01 8.19550455e-01
1.20540190e+00 8.20430934e-01 1.46403596e-01 -1.71485022e-01
1.83803272e+00 -1.10085237e+00 -5.97584069e-01 -2.54087895e-01
1.06019199e+00 -4.85420942e-01 1.07085526e+00 1.77623646e-03
-9.19744551e-01 -3.55991036e-01 -8.34322572e-01 -3.33614826e-01
-5.03092349e-01 -2.33505607e-01 3.90778929e-01 5.58494210e-01
-1.12173426e+00 2.23495483e-01 -5.14386117e-01 -5.19732833e-01
-1.86374620e-01 2.27873608e-01 -5.99317290e-02 -4.72014397e-01
-1.63004851e+00 9.23181593e-01 1.06586158e+00 -2.46323079e-01
-6.29724562e-01 -4.54153508e-01 -8.32268298e-01 3.07674587e-01
1.00289655e+00 -1.11634278e+00 1.31086743e+00 -7.14854062e-01
-1.36007905e+00 6.77626610e-01 -5.79874098e-01 -3.49248707e-01
-2.60341823e-01 -1.20893501e-01 -4.10502404e-01 6.35871172e-01
1.28927410e-01 2.91482270e-01 1.51776642e-01 -1.24081051e+00
-7.84255803e-01 -4.63591725e-01 7.79993713e-01 3.62708420e-01
-4.20240266e-03 4.04409885e-01 -1.15548813e+00 -1.33647799e-01
3.78166229e-01 -8.08691859e-01 -1.70795932e-01 -5.49531460e-01
-1.69224203e-01 -6.40795112e-01 6.70861125e-01 -1.00953662e+00
1.52386177e+00 -1.59432757e+00 2.47935310e-01 3.87867868e-01
1.79331318e-01 3.09807539e-01 -1.28376335e-01 7.56440282e-01
1.46743655e-01 2.09521189e-01 -2.11048439e-01 5.27301252e-01
-4.15484793e-02 5.02464652e-01 -4.31949615e-01 -3.31629723e-01
-1.00381762e-01 1.42283022e+00 -1.01821601e+00 -7.94687510e-01
-3.68424177e-01 -3.18276376e-01 -6.92492723e-01 4.64141279e-01
-1.11887336e+00 -1.42847836e-01 -1.10864556e+00 4.52145457e-01
5.10706902e-01 -6.23991549e-01 5.99692702e-01 -1.84658378e-01
4.81145024e-01 5.84950209e-01 -1.12031090e+00 1.72487652e+00
-1.63534909e-01 -1.34998783e-01 -5.48827760e-02 -8.71910274e-01
9.79835272e-01 1.60426453e-01 8.47779866e-03 -6.94363356e-01
-3.11659247e-01 5.37448168e-01 -2.73007244e-01 -8.75765443e-01
5.14977992e-01 -5.66513650e-02 -2.29309976e-01 3.10269475e-01
-3.34572941e-02 -8.38472098e-02 3.80037338e-01 5.01605630e-01
1.20822442e+00 2.43383035e-01 3.64752322e-01 -1.48790821e-01
9.90854323e-01 5.28143346e-01 3.31605345e-01 7.44174898e-01
2.54403144e-01 -2.09636521e-02 6.91075265e-01 -1.84115037e-01
-5.89552701e-01 -9.40063834e-01 7.32382596e-01 1.32043588e+00
6.06028438e-01 -6.27450824e-01 -1.02680850e+00 -1.15673256e+00
-2.23017976e-01 8.77582550e-01 -5.74053936e-02 -2.16639921e-01
-1.04618597e+00 -3.38359207e-01 4.05232936e-01 3.99769902e-01
4.83931959e-01 -1.12564087e+00 -1.82749167e-01 3.36309195e-01
-7.64146507e-01 -1.09193337e+00 -3.42430651e-01 -1.54117405e-01
-8.02856445e-01 -1.39036191e+00 -1.63721085e-01 -1.12792718e+00
4.72704053e-01 2.24196330e-01 1.23292112e+00 4.87087786e-01
2.19053328e-01 5.10109544e-01 -6.76330984e-01 -2.13039458e-01
-4.90063787e-01 3.07050377e-01 -7.14605510e-01 -3.72127801e-01
4.77574557e-01 -2.42593274e-01 -4.56478834e-01 2.75330663e-01
-1.03471768e+00 -1.50198549e-01 3.07114899e-01 4.92104471e-01
5.95452309e-01 -1.22496031e-01 8.75856102e-01 -1.04682398e+00
7.92289555e-01 -5.46561837e-01 -7.51730025e-01 1.13465953e+00
-4.70763892e-01 4.99682575e-01 7.90937304e-01 9.60058048e-02
-1.16299975e+00 -7.70518184e-02 -2.84739286e-01 7.14723095e-02
1.03418902e-01 8.75131845e-01 -4.95269686e-01 -2.49725441e-03
5.52524030e-01 2.63880700e-01 -2.34714508e-01 -6.08819306e-01
6.81608975e-01 4.23860431e-01 4.43475932e-01 -9.13651943e-01
6.06594026e-01 1.22827776e-01 -2.21887872e-01 -4.99036700e-01
-8.91383529e-01 -8.18221509e-01 -4.07721758e-01 9.39342603e-02
8.90664220e-01 -5.02874970e-01 -9.06148314e-01 -7.55065531e-02
-1.41759288e+00 9.64753330e-02 6.96427003e-02 1.79131389e-01
-6.30268276e-01 7.46977448e-01 -5.66077113e-01 -6.83815598e-01
-3.82427484e-01 -8.45231771e-01 1.00354993e+00 1.95935190e-01
4.44474295e-02 -8.43053222e-01 2.77834564e-01 8.79696608e-01
-3.66052091e-02 -2.07063660e-01 1.62074614e+00 -1.16059434e+00
-1.13594115e+00 9.16329622e-02 -3.41708153e-01 -3.18301003e-03
-9.83277708e-02 -5.76102078e-01 -4.39721406e-01 2.95415055e-02
-2.48038694e-01 -3.33228141e-01 7.14748085e-01 -2.35330224e-01
1.01610923e+00 -3.30690563e-01 -4.57722276e-01 2.59589076e-01
1.50850689e+00 5.74888825e-01 8.25785458e-01 4.54196036e-01
6.23960078e-01 6.75245702e-01 8.52299988e-01 -1.86633214e-01
8.19075108e-01 6.50161982e-01 3.00400227e-01 4.39906448e-01
-6.21271692e-02 -7.08677351e-01 1.37441814e-01 1.07757270e+00
2.21085221e-01 -4.30056542e-01 -9.58017468e-01 4.01941180e-01
-2.13551259e+00 -8.04347992e-01 -6.72621429e-02 1.94927323e+00
6.96671486e-01 -2.50431597e-01 -2.52998155e-03 -2.71579355e-01
7.71856964e-01 -3.89084220e-02 -4.83946204e-01 -3.03312868e-01
1.32587925e-01 3.99000347e-01 3.68227661e-01 8.40835750e-01
-5.04399300e-01 1.46781921e+00 6.85961056e+00 8.70262921e-01
-5.25229573e-01 -5.51447533e-02 8.11244845e-02 5.78806996e-01
-8.42493474e-01 5.17217696e-01 -1.01338971e+00 1.61900833e-01
1.01306880e+00 -4.38270926e-01 5.61147690e-01 6.95038915e-01
-2.69565701e-01 -8.31699744e-02 -7.58473754e-01 5.97146690e-01
1.82505429e-01 -1.45913875e+00 5.71930528e-01 -3.74009430e-01
1.28772095e-01 -4.20548558e-01 -7.04854369e-01 5.12726784e-01
4.99525428e-01 -7.89540648e-01 3.13494503e-01 6.24364436e-01
2.47511417e-01 -7.48892963e-01 6.51957870e-01 6.26316011e-01
-1.36395764e+00 -2.68778801e-02 -5.24224579e-01 2.79908240e-01
1.08537272e-01 6.74070120e-02 -1.18400311e+00 1.21269178e+00
5.49033046e-01 8.43788013e-02 -4.80161011e-01 9.18272853e-01
-4.96509284e-01 5.82269549e-01 -2.07040295e-01 -5.30870497e-01
6.85117617e-02 -3.69577706e-01 3.66145194e-01 9.58820522e-01
3.03065121e-01 7.06034482e-01 4.46922749e-01 4.82999325e-01
-2.00849637e-01 6.36834443e-01 -3.13135028e-01 -1.53578088e-01
5.39498270e-01 7.76893258e-01 -6.45112514e-01 -7.97107279e-01
-4.25416112e-01 1.09694517e+00 7.15895474e-01 4.51298922e-01
-7.52757132e-01 -6.27980769e-01 1.72946692e-01 -9.79068130e-02
4.60398018e-01 -6.63865209e-02 4.12371874e-01 -1.15190077e+00
4.57150429e-01 -1.08402002e+00 1.20365191e+00 -1.05117691e+00
-8.73631835e-01 5.61657369e-01 1.73581615e-01 -3.73259604e-01
-3.84459287e-01 -3.41731042e-01 -2.70521075e-01 9.17434692e-01
-1.73375654e+00 -9.84031260e-01 -1.76822454e-01 5.99017501e-01
2.42900491e-01 2.64622033e-01 8.12905073e-01 1.32458001e-01
-1.46574005e-01 1.94644123e-01 -1.89215809e-01 2.56576519e-02
3.75740707e-01 -1.23235691e+00 3.91157717e-01 7.02460349e-01
2.61062354e-01 8.14561546e-01 4.94296402e-01 -8.34132016e-01
-1.65851474e+00 -7.20738709e-01 1.20328176e+00 -5.10829926e-01
7.00198650e-01 -1.16035305e-01 -1.30948627e+00 6.84201539e-01
9.88735184e-02 -3.30925375e-01 5.58613062e-01 -8.55592545e-03
-6.83751285e-01 -6.42342865e-02 -9.50563908e-01 4.84566629e-01
1.25320804e+00 -7.04697251e-01 -1.29747486e+00 3.22113395e-01
1.40607023e+00 -3.55825812e-01 -7.40766406e-01 3.60107303e-01
3.32392633e-01 -6.79011881e-01 1.00905979e+00 -1.04527354e+00
1.12881981e-01 -6.48117125e-01 -2.39873618e-01 -1.01978779e+00
-1.87661126e-01 -4.64196146e-01 -3.56627375e-01 9.13490355e-01
7.50132978e-01 -7.31102943e-01 1.07577014e+00 6.04359269e-01
-8.42489898e-02 -5.87746084e-01 -8.92837346e-01 -7.76599884e-01
-2.36242428e-01 -2.33172774e-01 9.37201023e-01 7.19258070e-01
8.34047943e-02 7.25407183e-01 1.76933985e-02 4.89164323e-01
2.47355133e-01 7.93846190e-01 6.54646695e-01 -1.15797567e+00
-3.86490792e-01 -1.33815393e-01 -1.11234874e-01 -1.54893386e+00
3.25495690e-01 -1.11547589e+00 7.22091272e-02 -2.18667889e+00
2.25296244e-01 -2.61145711e-01 -2.95000821e-01 2.85060465e-01
-5.74635148e-01 -3.38627487e-01 9.26703885e-02 7.09482282e-02
-1.00706148e+00 3.42931777e-01 1.31285274e+00 1.29008979e-01
-2.02953741e-01 -1.94978252e-01 -9.48813319e-01 3.50394309e-01
6.39240205e-01 -4.94070590e-01 -7.41080344e-01 -4.21892047e-01
6.16719365e-01 6.24700427e-01 1.36430413e-01 -4.67194676e-01
4.50072706e-01 -4.29236472e-01 -3.06970865e-01 -5.51465511e-01
2.60712922e-01 -7.71951020e-01 -7.11790323e-02 5.44327199e-01
-3.09861243e-01 7.27232248e-02 -3.67013179e-02 6.99410379e-01
-5.10238051e-01 -7.38916755e-01 3.46018463e-01 -3.72831553e-01
-1.17918110e+00 2.12227404e-01 9.26698968e-02 3.78002703e-01
8.79091680e-01 4.99420166e-02 -6.74022317e-01 -4.95330632e-01
-7.61208475e-01 7.03362465e-01 2.90643781e-01 4.07792419e-01
6.32466435e-01 -1.02537239e+00 -4.40055281e-01 -4.02614146e-01
4.19919997e-01 -2.17474207e-01 -1.49092835e-03 1.58504143e-01
-8.34695339e-01 7.74677038e-01 1.77028641e-01 -9.56089795e-02
-1.44042051e+00 7.95716763e-01 2.23268509e-01 -5.08582413e-01
-2.30214059e-01 7.05887675e-01 1.77642241e-01 -5.98833978e-01
-1.14854854e-02 -2.55381972e-01 -5.78807652e-01 -1.42922938e-01
5.23950100e-01 2.26902902e-01 6.13076240e-02 -3.18186283e-01
-5.60590804e-01 6.65474713e-01 -3.36958878e-02 -3.64237167e-02
8.68837774e-01 -9.99770463e-02 -6.51952147e-01 2.59498460e-03
1.26285708e+00 1.22550689e-01 -2.09779024e-01 -4.21000808e-01
7.71146894e-01 -2.48720884e-01 -4.09085393e-01 -7.20759571e-01
-5.73657453e-01 2.82543808e-01 8.12029615e-02 4.03264791e-01
1.04457819e+00 6.13529265e-01 1.18596125e+00 9.61936057e-01
5.85745811e-01 -8.73610497e-01 1.37796760e-01 7.67975569e-01
7.14635968e-01 -7.66369820e-01 -3.09928209e-01 -1.09481418e+00
-3.76320332e-01 1.08294010e+00 7.10518658e-01 1.07241832e-01
2.97538191e-01 -3.64420414e-01 -1.87940523e-02 -5.24006605e-01
-8.73126805e-01 -5.92531800e-01 3.97236496e-01 2.99142450e-01
-1.75560191e-02 -1.58922046e-01 -6.81253374e-01 5.64206123e-01
-2.20115289e-01 3.45621109e-02 2.45015129e-01 1.08881676e+00
-1.20863271e+00 -1.49810183e+00 -2.81689405e-01 3.19390476e-01
-4.60015267e-01 -2.58894444e-01 -7.35757828e-01 6.50067687e-01
-2.25155100e-01 1.06486428e+00 -2.88247049e-01 -3.26513231e-01
7.10613847e-01 6.74595714e-01 5.25611520e-01 -8.56785774e-01
-5.03950834e-01 -3.30721647e-01 6.90156639e-01 -6.28371656e-01
-3.09084803e-01 1.63733065e-02 -1.63200021e+00 1.46291703e-01
-4.91427481e-01 9.68967855e-01 4.47962016e-01 9.77578819e-01
4.28593308e-01 7.05803186e-02 2.87568301e-01 6.62500322e-01
-3.09523553e-01 -4.87717867e-01 -2.45920762e-01 3.24442387e-01
-8.38849023e-02 -3.08250129e-01 -1.60675958e-01 3.02936584e-02] | [10.487818717956543, 7.943595886230469] |
48c8266e-34a5-405e-8f24-238715a213ad | generalizing-to-evolving-domains-with-latent | 2205.07649 | null | https://arxiv.org/abs/2205.07649v2 | https://arxiv.org/pdf/2205.07649v2.pdf | Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder | Domain generalization aims to improve the generalization capability of machine learning systems to out-of-distribution (OOD) data. Existing domain generalization techniques embark upon stationary and discrete environments to tackle the generalization issue caused by OOD data. However, many real-world tasks in non-stationary environments (e.g. self-driven car system, sensor measures) involve more complex and continuously evolving domain drift, which raises new challenges for the problem of domain generalization. In this paper, we formulate the aforementioned setting as the problem of evolving domain generalization. Specifically, we propose to introduce a probabilistic framework called Latent Structure-aware Sequential Autoencoder (LSSAE) to tackle the problem of evolving domain generalization via exploring the underlying continuous structure in the latent space of deep neural networks, where we aim to identify two major factors namely covariate shift and concept shift accounting for distribution shift in non-stationary environments. Experimental results on both synthetic and real-world datasets show that LSSAE can lead to superior performances based on the evolving domain generalization setting. | ['Haoliang Li', 'Shiqi Wang', 'Tiexin Qin'] | 2022-05-16 | null | null | null | null | ['evolving-domain-generalization'] | ['computer-vision'] | [ 3.33073825e-01 -3.81584942e-01 4.78018634e-02 -4.19424683e-01
-2.17368841e-01 -4.52323914e-01 4.39134359e-01 -7.82684311e-02
-2.06768855e-01 7.83798516e-01 -1.25439927e-01 -1.81893095e-01
-4.72264200e-01 -6.13943458e-01 -6.60590947e-01 -1.02455294e+00
-2.02860072e-01 3.19012135e-01 7.66495168e-02 -1.99883237e-01
-1.13665678e-01 3.36587995e-01 -1.63931930e+00 -1.93271875e-01
1.27849960e+00 8.26310873e-01 2.95891315e-01 2.75106341e-01
-1.29908144e-01 -1.20958790e-01 -8.56570542e-01 8.67039636e-02
3.93304825e-01 -1.83340579e-01 -1.42785966e-01 2.54869401e-01
3.01480182e-02 -1.29812792e-01 -1.87627509e-01 1.26735234e+00
5.12161970e-01 4.90899265e-01 9.29132283e-01 -1.78544271e+00
-8.45005095e-01 3.36704522e-01 -4.83596444e-01 6.65836871e-01
-2.81121612e-01 -1.28696114e-02 2.73196906e-01 -6.76882148e-01
2.45339245e-01 1.48207319e+00 5.99558532e-01 8.51354957e-01
-1.33461869e+00 -9.30372596e-01 7.51658320e-01 1.38360441e-01
-1.36713040e+00 1.27270371e-01 1.01320517e+00 -5.80474138e-01
5.22491872e-01 -2.82447934e-01 2.56230652e-01 1.78399277e+00
3.13882709e-01 9.02103722e-01 1.00932515e+00 4.61213179e-02
8.56109083e-01 3.06930691e-01 1.68132380e-01 -3.77221465e-01
4.47610199e-01 1.14851244e-01 -3.42423409e-01 -3.37573290e-01
5.61062992e-01 3.31944048e-01 -1.90824777e-01 -8.61889243e-01
-8.16367269e-01 6.75518692e-01 1.68540299e-01 1.91481143e-01
-4.84531909e-01 -3.03690344e-01 4.77325290e-01 4.33899224e-01
7.96318531e-01 -3.94320637e-02 -7.09921300e-01 -5.36773615e-02
-4.20388460e-01 6.25030518e-01 3.75507712e-01 1.16935539e+00
6.01151943e-01 3.65451306e-01 1.90803453e-01 7.19476700e-01
1.25995308e-01 5.67407966e-01 9.54484940e-01 -4.45652038e-01
6.32870913e-01 5.16166091e-01 3.01438332e-01 -7.04332411e-01
-3.02320778e-01 -8.47468317e-01 -1.10566485e+00 7.05069005e-02
1.48281053e-01 -4.24044967e-01 -8.69959056e-01 2.04275942e+00
7.09870636e-01 5.80990195e-01 5.82139909e-01 4.81741577e-01
1.43023700e-01 6.59561694e-01 3.02978694e-01 -2.69250810e-01
9.22955215e-01 -4.33555782e-01 -8.23436081e-01 -2.10724965e-01
5.72403133e-01 -1.22100059e-02 1.12480795e+00 4.30313438e-01
-5.68791986e-01 -8.60049427e-01 -1.26616788e+00 5.89562237e-01
-4.38215017e-01 -4.48979050e-01 5.93291335e-02 5.94039500e-01
-6.86804950e-01 5.31745732e-01 -9.56324875e-01 -5.04437089e-01
4.77967769e-01 2.24849135e-01 -1.42677933e-01 -1.66984379e-01
-1.53937602e+00 3.54092419e-01 1.04329550e+00 -2.05534650e-03
-8.70158970e-01 -1.03217185e+00 -8.08320522e-01 -1.25979468e-01
4.80922461e-01 -7.06628799e-01 1.18661940e+00 -9.32851374e-01
-1.27953899e+00 3.02554518e-01 -1.45214424e-01 -6.72527134e-01
4.55965668e-01 -3.98765206e-01 -8.00948679e-01 -3.85692209e-01
7.33385310e-02 1.44800171e-01 1.15085936e+00 -1.23556864e+00
-8.44924986e-01 -7.96883643e-01 -4.78079498e-01 2.96351880e-01
-7.85305023e-01 -5.44926524e-01 3.20936143e-01 -8.85402560e-01
1.14374533e-01 -1.02834976e+00 2.22238451e-02 -4.29138631e-01
1.45328090e-01 -7.03829587e-01 1.40808308e+00 -5.42256415e-01
1.27787483e+00 -2.67525029e+00 1.89810172e-01 -1.16671830e-01
1.25056989e-02 2.29244724e-01 2.03984424e-01 1.83835238e-01
-3.00713390e-01 -1.07369199e-01 -4.91457134e-01 -2.32732981e-01
2.23072082e-01 6.07757330e-01 -6.33344531e-01 3.00944269e-01
3.04084271e-01 4.50343877e-01 -9.79084492e-01 -1.05661348e-01
-1.08663030e-01 3.68727535e-01 -1.93987176e-01 -1.06331082e-02
-3.18253070e-01 6.77868247e-01 -6.42534494e-01 4.33557838e-01
1.06935990e+00 5.94641343e-02 -6.41330481e-02 5.00727296e-01
1.09081991e-01 -3.83372515e-01 -1.50429511e+00 1.77614188e+00
-2.36963421e-01 3.29597086e-01 -1.17032319e-01 -1.27560306e+00
1.31972766e+00 1.23753250e-01 3.52654815e-01 -5.53852618e-01
-5.15013635e-02 2.90371716e-01 -2.98900642e-02 -3.71081114e-01
4.95489091e-01 -4.99823272e-01 -3.03182214e-01 1.63249344e-01
-1.11216330e-03 1.85998097e-01 -2.04728529e-01 -1.96628764e-01
8.36175561e-01 1.47424325e-01 1.30886957e-01 -5.48291028e-01
4.40979362e-01 -3.58223796e-01 1.03255522e+00 6.65005922e-01
-6.10576928e-01 7.73885995e-02 1.72744274e-01 -3.57289582e-01
-9.82711017e-01 -1.41915703e+00 -3.52544904e-01 9.23035383e-01
3.83775085e-01 2.43330836e-01 -7.51976907e-01 -5.42783737e-01
3.23724002e-01 1.09773111e+00 -5.86042583e-01 -8.36320639e-01
-4.63934451e-01 -9.89686906e-01 2.10919783e-01 8.32895279e-01
6.46180093e-01 -6.22846365e-01 -6.46968842e-01 5.07352710e-01
1.24772854e-01 -9.09601212e-01 -8.06235000e-02 3.87762040e-01
-1.18852711e+00 -5.73987305e-01 -1.04202187e+00 -6.40806139e-01
2.74285287e-01 1.78431585e-01 7.71519125e-01 -8.59099746e-01
6.85673812e-03 5.38929582e-01 -2.63361394e-01 -1.00591981e+00
-4.34675813e-01 2.19561413e-01 8.22412789e-01 2.72605240e-01
7.31740773e-01 -8.84642363e-01 -5.44179618e-01 3.99175912e-01
-1.43879521e+00 -5.78071952e-01 2.97491282e-01 8.15777957e-01
4.57767457e-01 9.27938282e-01 1.07828152e+00 -4.35542345e-01
9.15418625e-01 -9.35052872e-01 -4.88659531e-01 2.17775702e-01
-7.54155517e-01 3.23167980e-01 6.54831171e-01 -9.91872847e-01
-1.44062579e+00 -1.67792544e-01 5.51650405e-01 -6.58866346e-01
-4.40752834e-01 2.83375084e-01 -6.99614763e-01 7.36254811e-01
6.61482394e-01 5.62294722e-01 -1.78946614e-01 -5.70142150e-01
7.60616437e-02 8.59162986e-01 6.99746072e-01 -8.48038375e-01
9.74654138e-01 6.34019136e-01 -6.06223419e-02 -7.58835554e-01
-5.58614969e-01 -4.64854181e-01 -7.35491216e-01 9.18808356e-02
6.45173132e-01 -1.03982460e+00 -1.95661515e-01 8.47020686e-01
-7.55256772e-01 -3.95604938e-01 -3.84896010e-01 4.58728254e-01
-5.68495631e-01 3.37115705e-01 1.13702945e-01 -1.14067197e+00
-3.10050342e-02 -7.06366718e-01 1.10367227e+00 4.25456613e-01
-3.28389890e-02 -1.31771076e+00 2.17866123e-01 -2.71091402e-01
3.10272038e-01 5.08660853e-01 1.15705585e+00 -9.91212845e-01
-8.86083543e-02 -4.91723977e-02 2.30744123e-01 6.79726660e-01
3.84634942e-01 -4.94951874e-01 -8.86029541e-01 -6.19706571e-01
4.59714741e-01 6.54745623e-02 6.56674385e-01 4.03183848e-01
1.19386220e+00 8.19158629e-02 -5.52045226e-01 4.52585578e-01
1.10211134e+00 6.15136921e-01 1.74362123e-01 5.33310175e-01
3.11630845e-01 7.04789758e-01 9.17289019e-01 7.02034712e-01
2.22919375e-01 4.72679406e-01 3.33570272e-01 3.18054855e-01
4.21249539e-01 -3.86184543e-01 3.03143471e-01 4.75301683e-01
5.75335622e-01 -4.28880930e-01 -1.02353251e+00 8.61437798e-01
-1.94869018e+00 -6.29492223e-01 2.20646545e-01 2.23579597e+00
5.59083879e-01 3.05969834e-01 1.29941791e-01 2.55533427e-01
1.11606431e+00 -1.22437321e-01 -1.47699153e+00 -5.09041734e-02
-2.88484722e-01 -1.60105035e-01 1.93598241e-01 -7.51490146e-02
-1.07848811e+00 5.97518265e-01 4.71970749e+00 7.72166669e-01
-9.76001620e-01 4.07173671e-02 3.50198746e-01 6.78942278e-02
-1.77331880e-01 -3.23831737e-01 -1.09150970e+00 8.35681677e-01
1.01561141e+00 -6.41699910e-01 4.23336290e-02 1.08882129e+00
-8.95145088e-02 2.65327811e-01 -1.22021687e+00 1.08413053e+00
-1.20543636e-01 -4.22035992e-01 -2.02738568e-02 1.14705428e-01
9.46557999e-01 -8.77855569e-02 6.14728332e-01 7.57194102e-01
3.56700778e-01 -4.96502101e-01 4.74047691e-01 4.53984410e-01
5.46087742e-01 -8.14802170e-01 5.47427833e-01 8.56188297e-01
-1.00308704e+00 -6.15328133e-01 -4.14858878e-01 6.95418939e-02
4.18616720e-02 5.05997062e-01 -7.09355891e-01 5.89745402e-01
1.06250250e+00 8.39101315e-01 -3.53908330e-01 8.30091834e-01
3.12423080e-01 5.05228579e-01 -3.55232179e-01 1.86886549e-01
1.15863018e-01 -1.84346773e-02 9.04331207e-01 6.09695375e-01
6.18817031e-01 -8.70671421e-02 7.28131235e-02 7.06609964e-01
2.13972718e-01 -4.25555557e-01 -7.01139331e-01 1.32021874e-01
6.49396956e-01 4.20187831e-01 -6.08868599e-01 -3.16994309e-01
-1.34810358e-01 1.10447395e+00 -1.19580641e-01 8.68217587e-01
-8.78922880e-01 -3.65666538e-01 8.95535171e-01 6.46954775e-02
5.20807683e-01 -3.61275196e-01 -7.49513879e-03 -1.17260659e+00
3.13519806e-01 -7.01230884e-01 6.91888273e-01 -4.24624532e-01
-1.58989549e+00 5.46371341e-01 5.04205465e-01 -1.34375072e+00
-3.79209191e-01 -5.72262049e-01 -3.64024878e-01 7.09020138e-01
-1.69475985e+00 -7.17701018e-01 -4.19107467e-01 8.17961872e-01
8.08663547e-01 -2.40747511e-01 5.24524331e-01 2.78994083e-01
-5.63371599e-01 6.37510002e-01 9.69084620e-01 -3.25823337e-01
8.39557290e-01 -1.33301890e+00 5.49618542e-01 7.27383137e-01
-3.82238626e-01 5.72406530e-01 9.23009455e-01 -8.24910641e-01
-8.74232531e-01 -1.47401965e+00 1.47636250e-01 -4.87241358e-01
6.82117999e-01 -7.10193634e-01 -1.44590771e+00 5.85247397e-01
-2.78661579e-01 -5.61311170e-02 5.79438329e-01 -1.21260464e-01
-2.23546371e-01 -3.30945879e-01 -1.14209294e+00 3.59050691e-01
1.25905728e+00 -2.77251124e-01 -7.23565638e-01 9.56780091e-02
1.04587042e+00 -2.96757609e-01 -7.39181459e-01 6.83809578e-01
1.49778351e-01 -4.66277480e-01 9.26021457e-01 -9.34907079e-01
-2.05642700e-01 -2.86182761e-01 -3.49175036e-01 -1.59930885e+00
-2.88872272e-01 -5.14912009e-01 -3.82321805e-01 1.38197029e+00
-9.12996978e-02 -1.00451148e+00 7.08742857e-01 4.98586565e-01
-8.91768262e-02 -4.14344132e-01 -1.21584392e+00 -1.52594054e+00
5.74962258e-01 -2.84592628e-01 1.07458305e+00 7.98169017e-01
-5.23208618e-01 1.54985204e-01 -8.65094662e-02 6.19292319e-01
7.98845649e-01 -6.58586696e-02 7.81042337e-01 -1.69389963e+00
-1.80139527e-01 -7.48566315e-02 -5.81377208e-01 -1.07239819e+00
5.25759518e-01 -5.18399775e-01 -4.11441922e-02 -8.95036757e-01
-9.29631293e-02 -3.54318440e-01 -6.66077912e-01 -1.74335957e-01
-3.40651155e-01 -6.10810220e-01 -1.05021209e-01 1.84658214e-01
-6.31551087e-01 1.22244251e+00 6.68080330e-01 -2.20520854e-01
-5.01339138e-01 4.03505683e-01 -6.87394142e-01 5.83948076e-01
8.46215427e-01 -5.93236387e-01 -9.46524441e-01 -4.58463728e-01
-1.10940471e-01 -2.85318792e-01 4.17209238e-01 -1.18432510e+00
5.15568554e-02 -2.96380579e-01 2.59982020e-01 -7.12598085e-01
1.30031660e-01 -1.09932184e+00 1.32261127e-01 4.78186458e-01
1.41526433e-02 1.13644704e-01 5.96853495e-01 1.32220936e+00
-2.36553788e-01 3.85770462e-02 6.23000860e-01 1.22159399e-01
-9.90494430e-01 4.20500368e-01 -2.46263847e-01 1.86534390e-01
1.32845461e+00 -4.11205828e-01 -3.66674997e-02 -1.84811935e-01
-8.21289361e-01 4.40774530e-01 2.56288379e-01 9.17222321e-01
3.22150737e-01 -1.40237558e+00 -6.07768178e-01 4.33835626e-01
3.96615237e-01 5.45236528e-01 7.96475649e-01 3.24593425e-01
3.62780571e-01 3.81947726e-01 -6.33011432e-03 -1.05703592e+00
-9.07643199e-01 8.63700330e-01 3.91288072e-01 -3.12681422e-02
-5.80558419e-01 8.07178855e-01 6.96847856e-01 -5.55258453e-01
3.97022665e-01 -6.07521832e-01 6.08423240e-02 8.71387273e-02
3.85758430e-01 4.80787069e-01 1.16301244e-02 -3.14509809e-01
-3.15468311e-01 2.16938406e-01 -1.90481097e-01 6.66154921e-02
1.29812467e+00 -4.70508069e-01 5.13710618e-01 8.95460606e-01
1.01661146e+00 -8.11595142e-01 -1.84732568e+00 -7.35592544e-01
3.13796878e-01 -2.08781153e-01 -1.71778083e-01 -4.93174344e-01
-3.03412765e-01 9.56085563e-01 1.20032310e+00 2.78278142e-01
1.24592113e+00 -1.07171312e-01 8.53941143e-01 3.30241084e-01
3.30757916e-01 -1.38894439e+00 2.66578376e-01 3.51840347e-01
6.25240624e-01 -1.16536999e+00 -4.33452338e-01 1.92752406e-01
-6.50385678e-01 7.56304264e-01 7.54937053e-01 -5.29270954e-02
8.60023439e-01 -5.96767142e-02 -1.24807894e-01 2.08704978e-01
-6.61171317e-01 2.74370879e-01 2.00844128e-02 9.90316570e-01
-3.53103906e-01 9.94898975e-02 2.09377453e-01 9.95101988e-01
-1.60345793e-01 1.73697304e-02 2.84321725e-01 1.02268970e+00
-2.97437489e-01 -1.01086259e+00 -5.69474876e-01 -2.24528499e-02
-5.06652240e-03 4.14521217e-01 -4.29772660e-02 9.48377848e-01
2.88067251e-01 5.90489268e-01 1.74323872e-01 -1.94693193e-01
5.89901507e-01 4.87949252e-01 1.22756869e-01 -5.08638978e-01
2.34988526e-01 -5.81679121e-02 -7.59758353e-01 -3.66615206e-02
-2.52112508e-01 -1.14647746e+00 -1.15853119e+00 1.78818077e-01
-1.91731229e-01 1.76096320e-01 6.69021070e-01 8.40876102e-01
5.91984808e-01 6.73766851e-01 6.51047289e-01 -3.84801030e-01
-1.31343901e+00 -9.92218375e-01 -1.13660276e+00 6.91141605e-01
7.06694663e-01 -1.08816028e+00 -6.14872694e-01 9.08550620e-02] | [10.303328514099121, 3.0186173915863037] |
d9ef9ebd-4d5c-41e8-8b2a-fa6a653ebe64 | mri-images-analysis-method-for-early-stage | 2012.00830 | null | https://arxiv.org/abs/2012.00830v1 | https://arxiv.org/pdf/2012.00830v1.pdf | MRI Images Analysis Method for Early Stage Alzheimer's Disease Detection | Alzheimer's disease is a neurogenerative disease that alters memories, cognitive functions leading to death. Early diagnosis of the disease, by detection of the preliminary stage, called Mild Cognitive Impairment (MCI), remains a challenging issue. In this respect, we introduce, in this paper, a powerful classification architecture that implements the pre-trained network AlexNet to automatically extract the most prominent features from Magnetic Resonance Imaging (MRI) images in order to detect the Alzheimer's disease at the MCI stage. The proposed method is evaluated using a big database from OASIS Database Brain. Various sections of the brain: frontal, sagittal and axial were used. The proposed method achieved 96.83% accuracy by using 420 subjects: 210 Normal and 210 MRI | ['Amira ben Rabeh', 'Taoufik Yeferny', 'Achraf Ben Miled'] | 2020-11-27 | null | null | null | null | ['alzheimer-s-disease-detection'] | ['medical'] | [-1.54558554e-01 -2.71670669e-01 2.50017732e-01 -4.84274179e-01
-2.83420205e-01 9.26458929e-03 3.98678690e-01 -8.44162256e-02
-9.30978715e-01 1.15195775e+00 3.37977380e-01 -8.36759731e-02
-1.31898254e-01 -6.60305619e-01 -1.85467139e-01 -4.55224633e-01
-6.21684253e-01 5.34324050e-01 3.55712831e-01 -4.51501198e-02
1.58589721e-01 5.98403513e-01 -1.27934408e+00 5.40170431e-01
9.48087513e-01 1.11643624e+00 4.32827085e-01 5.54697514e-01
1.04081035e-01 6.92733586e-01 -6.29290581e-01 2.99620945e-02
1.87027231e-01 -8.82467926e-02 -6.44014299e-01 -9.27951559e-02
4.19154823e-01 -7.03011870e-01 8.89429152e-02 1.29031873e+00
8.03159714e-01 -2.58569419e-01 6.79356158e-01 -7.22357452e-01
-7.24991858e-01 9.80767310e-02 -3.12830865e-01 1.26931036e+00
-1.82740867e-01 7.41584450e-02 3.85074466e-01 -1.29730427e+00
5.63010752e-01 1.16192138e+00 7.58625627e-01 6.48984730e-01
-6.99322701e-01 -8.22648764e-01 -2.85800874e-01 1.07953310e+00
-1.13751066e+00 -2.33884737e-01 4.94170994e-01 -7.94243693e-01
8.03043902e-01 -4.68689622e-03 1.02080917e+00 9.12692070e-01
8.93525124e-01 2.76112884e-01 1.76379430e+00 -1.53592810e-01
5.08877575e-01 -7.31213689e-02 1.04366279e+00 7.04347491e-01
4.91803974e-01 3.41730914e-03 1.23311311e-01 -3.31178814e-01
5.32435775e-01 1.47205487e-01 -1.59684032e-01 1.07040003e-01
-9.65119123e-01 7.23765910e-01 5.85860491e-01 7.17886925e-01
-8.03789079e-01 -5.11857927e-01 3.97779107e-01 4.51462507e-01
2.88442761e-01 -3.38158578e-01 -2.86280930e-01 5.11935472e-01
-9.30381775e-01 1.15254723e-01 2.76890606e-01 3.44383448e-01
9.51462090e-02 3.19123417e-01 -6.05991781e-02 8.30022633e-01
5.60436785e-01 3.14219922e-01 1.20384777e+00 -6.46685421e-01
2.83391684e-01 7.47724295e-01 -1.93123788e-01 -6.16821408e-01
-8.82288337e-01 -7.30467439e-01 -1.17062354e+00 8.29537690e-01
1.48395300e-01 -2.75878727e-01 -1.20831084e+00 1.34367347e+00
9.82405171e-02 -2.08240971e-01 6.68564439e-02 1.19879711e+00
8.93267155e-01 4.10199851e-01 5.00447631e-01 -3.58919293e-01
1.91661859e+00 -5.63710690e-01 -7.47352779e-01 -3.41354728e-01
2.00027004e-02 -5.40763021e-01 1.00516808e+00 2.96143919e-01
-8.87207866e-01 -5.90362012e-01 -1.40516162e+00 2.66692173e-02
-5.91008425e-01 4.82430339e-01 5.62565804e-01 5.82888961e-01
-1.15547943e+00 3.47543091e-01 -8.14853132e-01 -5.06890774e-01
7.71740139e-01 5.99526882e-01 -5.45465112e-01 -6.12099543e-02
-1.21496153e+00 1.13694406e+00 4.74673361e-01 1.92952052e-01
-9.61250842e-01 -5.07825077e-01 -8.00349936e-02 -3.72797623e-02
-3.03876519e-01 -9.80412543e-01 7.52906501e-01 -1.07270551e+00
-8.24539006e-01 1.15384758e+00 -9.16318893e-02 -7.65840352e-01
5.48521638e-01 -4.59841490e-01 -7.59896755e-01 3.17696542e-01
1.72323361e-01 5.84260702e-01 5.95505893e-01 -6.55721128e-01
-4.83887017e-01 -1.26101029e+00 -2.79129505e-01 -8.64674821e-02
-2.47339293e-01 4.25990224e-01 5.39312184e-01 -6.78210497e-01
2.54454076e-01 -7.45181918e-01 -2.20521256e-01 1.73820630e-01
-3.21429491e-01 -2.18739897e-01 8.56451631e-01 -1.28239346e+00
6.81663454e-01 -1.84374654e+00 -3.51261139e-01 1.60288867e-02
6.17318273e-01 5.03609002e-01 4.31605935e-01 -5.51031709e-01
-2.84352303e-01 -1.27484292e-01 -1.81232035e-01 1.12820886e-01
-4.17670608e-01 -5.87526597e-02 3.59805763e-01 4.29776490e-01
7.98134431e-02 6.52554750e-01 -1.73616827e-01 -5.04752696e-01
8.14966708e-02 6.46572113e-01 -1.68726683e-01 1.18002258e-01
2.79731452e-01 4.59806234e-01 -4.09259290e-01 7.67249405e-01
8.17017913e-01 -4.16438766e-02 -6.42701983e-02 -5.01713216e-01
-1.04405776e-01 -3.29949826e-01 -8.06294084e-01 1.09784985e+00
1.75571531e-01 5.36606491e-01 1.17750809e-01 -1.10819054e+00
8.42758536e-01 5.24690807e-01 3.97019207e-01 -9.98821080e-01
5.13785005e-01 4.26262915e-01 4.65185016e-01 -8.82486105e-01
-3.83034378e-01 -2.36377001e-01 5.74093401e-01 2.97283977e-01
-2.33250558e-02 1.14087307e+00 2.70186543e-01 -2.47836858e-01
1.02484357e+00 -5.87083995e-01 5.64610124e-01 -5.57055593e-01
9.16845381e-01 6.14863150e-02 6.84902310e-01 3.65332693e-01
-8.03638339e-01 3.23406667e-01 1.11055441e-01 -9.59580481e-01
-1.19441557e+00 -1.31769228e+00 -3.13321918e-01 5.14223993e-01
-6.44990802e-01 2.35446289e-01 -8.70734036e-01 -5.59489429e-01
-2.90642262e-01 1.84324384e-01 -6.38782978e-01 -2.39139810e-01
-9.74301815e-01 -1.40913355e+00 1.96676359e-01 5.61439633e-01
1.35347438e+00 -1.03240311e+00 -6.58755124e-01 2.11793691e-01
1.72964200e-01 -6.81924880e-01 -1.72496006e-01 7.03492910e-02
-1.46560955e+00 -1.32226443e+00 -1.34345531e+00 -1.27272356e+00
7.24220634e-01 -1.34453535e-01 9.09844875e-01 -8.91705826e-02
-6.84943140e-01 -9.30780619e-02 1.53788328e-01 -3.37534666e-01
-2.12093815e-01 -1.49845362e-01 4.57599275e-02 -4.76156622e-02
5.42660177e-01 -1.02600551e+00 -9.98937666e-01 -2.99558584e-02
-5.23114324e-01 -2.97844231e-01 1.24505436e+00 4.89825070e-01
7.21318960e-01 -3.53638530e-02 8.00835371e-01 -5.72224617e-01
8.02697003e-01 -4.52574849e-01 -2.06607461e-01 1.58310995e-01
-6.54868662e-01 -1.70080602e-01 4.02092397e-01 -2.52897531e-01
-8.65360081e-01 1.64218247e-01 -3.79150391e-01 1.98344402e-02
-5.82679927e-01 3.28123391e-01 -4.32001621e-01 2.19337549e-02
5.84642351e-01 3.27663749e-01 9.05761197e-02 -8.93533885e-01
-1.94305897e-01 9.27793324e-01 8.99619877e-01 5.72007336e-02
8.84506479e-02 4.86882448e-01 4.44509201e-02 -9.15106714e-01
-5.91071486e-01 -1.61402240e-01 -9.61618066e-01 -2.18252614e-01
1.07250655e+00 -1.05048013e+00 -1.72294796e-01 3.65042031e-01
-1.14331818e+00 1.90751031e-01 2.86809057e-01 8.20028901e-01
-1.00266129e-01 2.09845826e-01 -7.33869255e-01 -3.37659061e-01
-1.31600630e+00 -9.33270514e-01 3.28443468e-01 1.26787826e-01
-1.91606909e-01 -7.33461857e-01 6.60461634e-02 4.15845782e-01
7.58501291e-01 1.99354485e-01 1.41879642e+00 -6.90048218e-01
-2.55064100e-01 -1.93501681e-01 -5.09524643e-01 5.74666321e-01
1.65866852e-01 -5.54649770e-01 -6.35675967e-01 -2.26189077e-01
5.12337863e-01 1.48537174e-01 9.40000355e-01 5.36763370e-01
5.11574090e-01 -2.64980614e-01 -1.10731833e-01 2.49085039e-01
1.43396401e+00 7.87121773e-01 9.35819268e-01 8.34395349e-01
2.83027411e-01 9.07648206e-02 7.21429959e-02 1.52488649e-01
2.85976291e-01 3.57957125e-01 1.98425651e-01 -2.71755853e-03
-6.23181522e-01 8.62260580e-01 4.66790289e-01 8.28638971e-01
-4.37459886e-01 5.52725375e-01 -9.26541209e-01 2.44853765e-01
-1.27613974e+00 -1.00392401e+00 -3.46353501e-01 1.88710809e+00
6.39619112e-01 3.20964038e-01 1.19678676e-01 3.12518120e-01
1.01166987e+00 -2.95886099e-01 -4.66919035e-01 6.77843317e-02
-3.76989871e-01 4.68891054e-01 5.05504496e-02 2.38073945e-01
-1.15336859e+00 2.46071294e-01 6.29300833e+00 5.98828904e-02
-1.42051280e+00 7.44325876e-01 5.97504497e-01 -4.36057374e-02
5.12330055e-01 -5.19542634e-01 -7.49043107e-01 6.62195206e-01
9.87845540e-01 2.76078209e-02 3.72917764e-02 8.59090328e-01
5.59547603e-01 -1.99309196e-02 -5.66714168e-01 8.55798244e-01
2.33119190e-01 -9.62517798e-01 3.47330749e-01 -2.13444412e-01
1.46187067e-01 1.42023802e-01 -6.59767017e-02 2.64907449e-01
-3.76683980e-01 -8.68692338e-01 4.28702027e-01 1.03031862e+00
3.56832445e-01 -7.22736776e-01 9.41770613e-01 4.99529531e-03
-8.88089538e-01 -3.64418507e-01 -4.59293514e-01 -1.38691306e-01
-1.65528469e-02 8.61366928e-01 -8.74894619e-01 -2.03734085e-01
9.27197933e-01 4.65781599e-01 -1.13114536e+00 1.50645721e+00
3.13599929e-02 6.41379476e-01 -1.08500272e-01 1.85934812e-01
8.86791348e-02 4.59174067e-02 6.43717170e-01 9.34746385e-01
5.56573510e-01 6.89345971e-02 1.57559723e-01 9.12686825e-01
1.85064837e-01 3.42222869e-01 -2.54305512e-01 3.52220505e-01
1.21420212e-02 1.13586271e+00 -9.19428766e-01 -5.51040888e-01
-2.94416368e-01 6.67771161e-01 -8.37135538e-02 3.48517820e-02
-3.61307353e-01 -2.82410979e-01 2.46133748e-02 2.19929203e-01
-1.13600167e-03 -1.97609693e-01 -5.19856811e-01 -9.90895450e-01
3.54109019e-01 -8.51713777e-01 6.83212578e-01 -8.62261713e-01
-1.05912435e+00 9.72663581e-01 -2.66328752e-01 -8.94952536e-01
1.27373338e-01 -7.89741337e-01 -1.00460804e+00 8.66308451e-01
-1.22732317e+00 -1.00915456e+00 -6.43153548e-01 9.07358766e-01
5.99637508e-01 -6.38818622e-01 8.38413656e-01 9.01110053e-01
-6.86285615e-01 -1.61977056e-02 3.41775045e-02 2.54938990e-01
4.70294237e-01 -1.28639972e+00 -2.07799003e-01 6.11072600e-01
-6.01625025e-01 7.28942156e-01 5.42408407e-01 -9.64411438e-01
-5.83433509e-01 -1.29402328e+00 9.15622175e-01 1.80430844e-01
2.81675816e-01 1.35309458e-01 -8.32769394e-01 6.10558867e-01
2.39402741e-01 -6.31791800e-02 6.08714104e-01 -4.76388663e-01
-3.21114378e-04 -3.12963575e-01 -1.48675203e+00 4.47998255e-01
5.42026699e-01 -1.62866071e-01 -1.14130890e+00 3.86061609e-01
1.20736159e-01 2.60216832e-01 -9.95866418e-01 3.16578686e-01
6.88745022e-01 -9.90772963e-01 1.36536515e+00 -7.62149036e-01
1.14788882e-01 -8.34964141e-02 -2.41017476e-01 -1.05193305e+00
-5.03379881e-01 3.83273214e-01 -2.41207406e-01 9.02188361e-01
6.70806840e-02 -4.84647900e-01 8.42434645e-01 4.57272649e-01
-3.65417659e-01 -6.42640471e-01 -1.08290386e+00 -8.27630043e-01
2.89896071e-01 6.35439157e-02 3.90732318e-01 5.29184699e-01
-6.19842708e-01 5.60329080e-01 3.47574539e-02 2.30000541e-01
9.52067614e-01 -3.22805315e-01 -1.79963186e-01 -1.94766116e+00
4.88744646e-01 -2.51314819e-01 -9.02589142e-01 2.03715160e-01
-9.51494128e-02 -9.78928566e-01 -5.63655257e-01 -1.63596857e+00
5.62540412e-01 -6.73126522e-03 -7.67381728e-01 3.14591438e-01
4.49439734e-02 4.77790922e-01 -1.00033544e-01 4.12213802e-01
-1.83413535e-01 2.91870058e-01 1.03302169e+00 -4.92646128e-01
-1.09010093e-01 5.47438748e-02 -5.01528084e-01 9.36939120e-01
1.31134450e+00 -4.40663248e-01 -2.63431698e-01 -1.57521605e-01
-4.89598185e-01 -4.04970497e-01 7.77821004e-01 -1.92092752e+00
-1.50901703e-02 2.90778965e-01 1.29150534e+00 -7.24147975e-01
4.17012662e-01 -6.90737367e-01 1.47342712e-01 1.06468308e+00
-2.19096705e-01 3.25300068e-01 -3.98158934e-03 1.68324322e-01
6.24331012e-02 -3.57982218e-01 1.12989950e+00 -6.18921399e-01
-8.82830024e-01 2.80815691e-01 -8.05972099e-01 -1.78878099e-01
1.12439442e+00 -1.04897477e-01 -2.78112143e-01 3.55316550e-01
-1.54603648e+00 -3.59301627e-01 -2.98795611e-01 2.00213671e-01
8.03640723e-01 -1.50958395e+00 -6.30185127e-01 3.55235375e-02
-2.94865578e-01 -7.61322558e-01 2.51119614e-01 1.24836111e+00
-6.13241792e-01 5.97944617e-01 -1.17876506e+00 -3.46897870e-01
-1.72446108e+00 4.33867425e-01 5.78627884e-01 -1.85384274e-01
-1.02011752e+00 1.36367381e-01 -1.96541712e-01 2.01955706e-01
2.43665516e-01 -3.41817766e-01 -1.05527663e+00 1.81815580e-01
1.03902578e+00 6.14829719e-01 4.22527671e-01 -7.61409819e-01
-4.15718853e-01 3.47916365e-01 -5.66953480e-01 2.14111786e-02
1.56167877e+00 -1.88734487e-01 -4.43905294e-01 2.52452016e-01
1.12601745e+00 -5.73561668e-01 -4.33230698e-01 -3.32523994e-02
2.63365626e-01 1.37946799e-01 4.23734426e-01 -1.16312778e+00
-1.34549117e+00 1.11121082e+00 2.10246801e+00 -2.04946727e-01
7.85004497e-01 -1.99538559e-01 1.06081736e+00 7.78680682e-01
2.99818039e-01 -1.07748306e+00 -1.21784493e-01 2.81873405e-01
1.07864356e+00 -1.05332446e+00 5.49677648e-02 2.42873505e-02
-2.20672756e-01 1.49920368e+00 5.98134220e-01 -4.55273390e-01
9.24521565e-01 -1.57008953e-02 2.39478081e-01 -5.16410232e-01
-2.90803701e-01 -1.21784709e-01 1.49366289e-01 8.29519868e-01
4.23094422e-01 5.08211255e-02 -7.72349477e-01 1.27817762e+00
-7.44354427e-02 6.25576615e-01 2.63526261e-01 1.12467802e+00
-1.09223282e+00 -6.36206329e-01 -7.78928697e-01 1.10643709e+00
-9.99327779e-01 -4.63080369e-02 -5.40588915e-01 6.81821585e-01
6.22924924e-01 4.91341054e-01 2.31037438e-02 6.17373176e-02
3.01842272e-01 4.88165557e-01 2.80807763e-01 -2.62197435e-01
-2.46198893e-01 -1.72545686e-01 9.17276591e-02 -2.89942086e-01
-4.05818582e-01 -5.86357117e-01 -1.33050334e+00 9.06613618e-02
4.41739470e-01 -9.64816138e-02 5.52137733e-01 1.17050493e+00
3.82467538e-01 6.93018436e-01 1.18588604e-01 -6.32970572e-01
-3.29057127e-01 -1.30899632e+00 -7.09247410e-01 3.02080870e-01
3.27592671e-01 -1.00844300e+00 -1.41991153e-01 3.41783136e-01] | [14.1611967086792, -1.751629114151001] |
1e92f91a-8cc0-4e2c-ac7c-96d4bff3fb2a | toward-educator-focused-automated-scoring | 2112.11973 | null | https://arxiv.org/abs/2112.11973v1 | https://arxiv.org/pdf/2112.11973v1.pdf | Toward Educator-focused Automated Scoring Systems for Reading and Writing | This paper presents methods for improving automated essay scoring with techniques that address the computational trade-offs of self-attention and document length. To make Automated Essay Scoring (AES) more useful to practitioners, researchers must overcome the challenges of data and label availability, authentic and extended writing, domain scoring, prompt and source variety, and transfer learning. This paper addresses these challenges using neural network models by employing techniques that preserve essay length as an important feature without increasing model training costs. It introduces techniques for minimizing classification loss on ordinal labels using multi-objective learning, capturing semantic information across the entire essay using sentence embeddings to use transformer architecture across arbitrarily long documents, the use of such models for transfer learning, automated hyperparameter generation based on prompt-corpus metadata, and, most importantly, the use of semantic information to provide meaningful insights into student reading through analysis of passage-dependent writing resulting in state-of-the-art results for various essay tasks. | ['Mike Hardy'] | 2021-12-22 | null | null | null | null | ['automated-essay-scoring'] | ['natural-language-processing'] | [ 2.27263600e-01 -1.26781330e-01 -3.70059848e-01 -6.43074393e-01
-1.34915984e+00 -9.36964989e-01 2.43460968e-01 7.46749699e-01
-6.69284761e-01 7.95948207e-01 5.35511136e-01 -3.75074923e-01
-5.78264594e-01 -5.43957591e-01 -2.18575805e-01 -5.69771826e-02
5.93705833e-01 5.10161102e-01 1.55033134e-02 -4.16984111e-01
9.65155840e-01 2.39328489e-01 -1.38633573e+00 2.13027015e-01
1.03626454e+00 8.06921542e-01 -8.49917531e-02 8.49349499e-01
-5.40698051e-01 1.05247855e+00 -9.09194767e-01 -6.66718543e-01
-1.21088572e-01 -2.63812661e-01 -7.62342453e-01 -2.84161329e-01
1.01394761e+00 -3.29254001e-01 3.30137312e-02 7.71179676e-01
5.52574933e-01 5.70206225e-01 9.36127663e-01 -9.45299506e-01
-1.41975486e+00 6.64788365e-01 -2.14892924e-01 1.80356473e-01
3.18997681e-01 -4.36304808e-02 1.46143186e+00 -7.22908974e-01
2.68965900e-01 8.41659546e-01 9.46719289e-01 5.44618011e-01
-1.18121207e+00 -5.46900153e-01 -3.46155435e-01 4.81481016e-01
-6.30244076e-01 -4.04197663e-01 8.63182366e-01 -5.68667710e-01
7.38895237e-01 2.12039039e-01 3.47845674e-01 1.01661503e+00
6.79486915e-02 8.52671564e-01 1.13218510e+00 -9.53101218e-01
-8.54981554e-05 5.74850321e-01 9.66274679e-01 8.16564441e-01
-5.71694635e-02 -2.99599111e-01 -9.44727659e-01 -1.46119073e-01
2.26658612e-01 -2.26348892e-01 -7.68688172e-02 -1.38806432e-01
-8.48313689e-01 1.01809406e+00 -2.15309471e-01 1.14100650e-01
1.64517775e-01 -6.98300228e-02 6.03603065e-01 6.85491145e-01
4.72822160e-01 1.17564118e+00 -9.49639082e-01 -4.70285684e-01
-1.30913115e+00 2.82093495e-01 9.01890337e-01 6.99648380e-01
4.09681648e-01 -7.85814971e-02 -6.07836485e-01 1.28246069e+00
1.62060201e-01 1.07343383e-01 1.00799096e+00 -1.07263076e+00
6.93410277e-01 9.19628084e-01 8.65311455e-03 -5.97475886e-01
-4.94676918e-01 -4.02153492e-01 -2.02629827e-02 1.55486092e-01
6.71803892e-01 4.26007509e-02 -4.15657043e-01 1.74839699e+00
-6.77653328e-02 -3.70690852e-01 -6.31027147e-02 4.66792166e-01
7.32960820e-01 2.73398429e-01 2.63392210e-01 8.50303546e-02
1.36220515e+00 -1.23189223e+00 -6.31752431e-01 4.68122400e-02
9.86612499e-01 -9.08309519e-01 1.72867703e+00 3.39678884e-01
-1.47405553e+00 -7.55579710e-01 -1.22081113e+00 -8.62726331e-01
-6.45140588e-01 4.63723838e-01 1.40572876e-01 7.66068697e-01
-1.03054965e+00 6.67400479e-01 -3.48927319e-01 -9.70650092e-02
3.66840005e-01 3.94209802e-01 9.67009664e-02 1.53233021e-01
-1.02087557e+00 1.17981517e+00 -1.23409368e-02 -8.14441085e-01
-7.39553571e-02 -1.41130710e+00 -7.42834687e-01 6.64789021e-01
-1.26198232e-01 -4.83881295e-01 1.53600335e+00 -8.44976485e-01
-1.91593826e+00 6.65057003e-01 6.59399554e-02 -9.78781879e-02
2.77531147e-01 -2.45654270e-01 -3.33552808e-03 -1.33450329e-01
9.22385156e-02 3.59733909e-01 4.09208000e-01 -3.31318498e-01
-3.17899078e-01 -5.18591940e-01 -2.13103160e-01 4.37777817e-01
-1.41616726e+00 1.36716098e-01 2.86409587e-01 -6.93230629e-01
-2.90603310e-01 -6.45273089e-01 3.62336010e-01 -1.96480781e-01
1.16009831e-01 -8.33765149e-01 6.05151892e-01 -1.10296178e+00
1.44860744e+00 -1.84863663e+00 -3.77028659e-02 -1.77500341e-02
5.63486107e-02 2.28206977e-01 -5.70296168e-01 1.78328186e-01
1.39959872e-01 3.67518589e-02 1.20819174e-01 -5.17959893e-01
2.30417833e-01 -4.71802562e-01 -1.41248137e-01 8.57669953e-03
-1.69285014e-02 9.21769738e-01 -8.27259243e-01 -5.77249229e-01
1.79238990e-02 9.30759162e-02 -4.98838514e-01 3.78291965e-01
-1.68458015e-01 -1.07994109e-01 -1.66630089e-01 6.30263388e-01
2.91883312e-02 -2.09586650e-01 -1.43554285e-01 1.70080081e-01
-1.71343267e-01 8.32094848e-01 -7.97985971e-01 1.70964754e+00
-8.42184901e-01 8.68093252e-01 -2.40517661e-01 -6.75193608e-01
1.08889723e+00 2.10220620e-01 3.42100322e-01 -8.54242921e-01
4.06922549e-02 1.90205887e-01 -2.86637634e-01 -5.59157610e-01
9.26231802e-01 -6.49377378e-03 -5.13564870e-02 1.19974172e+00
3.50989908e-01 -2.46959880e-01 2.11572781e-01 1.11510344e-01
1.12477767e+00 8.91430005e-02 -1.06011312e-02 -3.83043081e-01
4.21278447e-01 1.05222903e-01 -1.49445266e-01 6.14598393e-01
-2.32225835e-01 4.38342214e-01 1.86688751e-01 -2.61153370e-01
-1.18506873e+00 -9.14586127e-01 -1.57758668e-01 2.00561786e+00
-4.26952153e-01 -1.08119942e-01 -7.06890166e-01 -5.98040998e-01
2.23199710e-01 1.17130208e+00 -5.23296297e-01 -4.45889294e-01
-5.75383961e-01 -5.54330528e-01 7.02764869e-01 6.83215022e-01
8.45054016e-02 -8.56959105e-01 -6.75725043e-01 5.37933171e-01
-2.07768127e-01 -6.96364701e-01 -7.80848265e-01 4.61012840e-01
-9.27813649e-01 -9.49631035e-01 -6.06256962e-01 -7.78264523e-01
2.99902231e-01 6.89109117e-02 1.35118949e+00 2.08001621e-02
-3.25743079e-01 6.89313650e-01 -5.30217104e-02 -5.87147474e-01
-3.44811559e-01 7.22940862e-01 -1.64372981e-01 -6.37852192e-01
8.25963080e-01 -2.77917534e-01 -3.85324396e-02 -1.57774687e-01
-6.12251043e-01 -2.58688390e-01 1.96751893e-01 1.17319179e+00
5.48249111e-02 -5.52656174e-01 1.03017855e+00 -8.04844737e-01
1.42330432e+00 -4.05593216e-01 -4.06534791e-01 8.05526078e-01
-1.21856689e+00 3.95764470e-01 8.85843873e-01 -4.87736911e-01
-1.17646849e+00 -4.81212735e-01 1.45048216e-01 5.35773672e-02
1.38775840e-01 4.90716070e-01 3.45310420e-01 -1.10740222e-01
9.56083894e-01 1.40439570e-01 3.33021551e-01 -5.11101902e-01
2.48579845e-01 9.07139659e-01 3.36698204e-01 -8.32533002e-01
2.08100513e-01 -2.16933459e-01 1.61664430e-02 -4.21911955e-01
-1.58808243e+00 -7.08410025e-01 -9.14440691e-01 -3.17588337e-02
4.59028631e-01 -6.63984895e-01 -6.94610059e-01 2.41266489e-01
-8.45213056e-01 -3.75323892e-01 -4.43906844e-01 3.71394098e-01
-5.11054337e-01 1.98971838e-01 -9.54481900e-01 -5.05562484e-01
-5.89134276e-01 -9.82647777e-01 5.11966169e-01 4.14766908e-01
-7.79089987e-01 -1.50655746e+00 4.44830239e-01 1.05934608e+00
5.96886754e-01 -4.33995485e-01 1.41503358e+00 -1.22559929e+00
-2.80174226e-01 -1.61223218e-01 -2.75216371e-01 4.68274564e-01
-5.34643307e-02 1.49351899e-02 -9.43227530e-01 -1.84205323e-02
-1.38287708e-01 -1.04982781e+00 7.04999447e-01 3.07021558e-01
1.36579680e+00 -3.44282240e-01 4.64211524e-01 5.36005914e-01
1.27698553e+00 -2.19578192e-01 4.51201899e-03 8.34103644e-01
6.81618690e-01 7.80662775e-01 3.24902415e-01 3.26618910e-01
7.86289752e-01 5.05397797e-01 -2.11436465e-01 4.51945603e-01
-3.95260662e-01 -1.73126489e-01 3.44544590e-01 1.17437291e+00
3.78882647e-01 -1.41939493e-02 -7.65514791e-01 7.48530030e-01
-1.44902408e+00 -8.80967975e-01 -9.01585519e-02 2.06286645e+00
1.48364735e+00 -1.25667915e-01 4.28844765e-02 1.62067801e-01
1.75944775e-01 7.38249347e-02 -4.52682287e-01 -1.06846857e+00
5.67466021e-02 5.98822117e-01 6.83888495e-01 6.46625519e-01
-7.49104321e-01 7.08515227e-01 6.33651066e+00 6.41611516e-01
-6.94470346e-01 2.48891771e-01 4.23860878e-01 -3.64232838e-01
-3.94452721e-01 -3.32811683e-01 -1.14338171e+00 4.64307457e-01
1.42504525e+00 -1.96677431e-01 5.02354324e-01 7.49063849e-01
1.15001887e-01 1.81845576e-01 -1.12545156e+00 4.61514980e-01
5.93536854e-01 -1.18756890e+00 -1.47428468e-01 -3.49056035e-01
9.58968043e-01 -2.65179604e-01 3.73352170e-01 5.79801321e-01
4.57644284e-01 -9.98552442e-01 7.28676736e-01 5.14509439e-01
7.64700949e-01 -6.67053759e-01 6.22796953e-01 1.98326185e-01
-4.48612183e-01 -5.47971606e-01 -3.28724980e-01 -2.55013049e-01
-4.22224015e-01 3.88834983e-01 -9.64039505e-01 -1.33767977e-01
2.83723623e-01 6.01548314e-01 -9.09400463e-01 8.07486534e-01
-1.40457451e-01 8.18822920e-01 -9.57800001e-02 -6.51780367e-01
2.00181335e-01 -5.61860949e-02 7.09382296e-02 1.26612401e+00
4.05537575e-01 -1.17076695e-01 -2.11159000e-03 8.01605403e-01
-4.41643298e-01 2.68545210e-01 -1.83556244e-01 7.19757900e-02
7.07460821e-01 1.13191545e+00 -2.18106955e-01 -1.50291547e-01
-3.70730817e-01 7.78506637e-01 7.22616553e-01 -7.09085772e-03
-4.11364824e-01 -6.33534133e-01 3.34545344e-01 -2.27998979e-02
-2.40845308e-01 -1.64676651e-01 -1.34399629e+00 -9.07874644e-01
3.35857607e-02 -8.47501159e-01 5.98926842e-01 -5.77294946e-01
-1.42292690e+00 -1.61742330e-01 -3.53879899e-01 -7.22946942e-01
-1.43522501e-01 -7.99045980e-01 -7.24816442e-01 9.97506559e-01
-1.70384300e+00 -1.00198174e+00 -2.03348801e-01 2.83650875e-01
9.27103460e-01 -6.80739045e-01 8.98134410e-01 2.19664425e-01
-3.16561997e-01 1.26502645e+00 5.93593955e-01 6.84062392e-02
1.32093263e+00 -1.67282009e+00 -1.00653008e-01 2.70199597e-01
2.04883814e-01 4.04077321e-01 1.82387426e-01 -2.77795821e-01
-8.72052014e-01 -6.99951231e-01 1.48300457e+00 -1.14678252e+00
8.53845298e-01 4.40150797e-02 -9.87494349e-01 4.85221207e-01
2.09160507e-01 -7.36177623e-01 1.24831522e+00 5.99887729e-01
-5.85442066e-01 -1.44301066e-02 -9.78383601e-01 5.58476269e-01
3.99063081e-01 -7.71460772e-01 -8.83049786e-01 3.40594858e-01
4.31334317e-01 -2.75978059e-01 -9.74991798e-01 -1.01311021e-01
7.91075587e-01 -6.99854612e-01 8.67752552e-01 -7.83695579e-01
9.22808826e-01 4.17563081e-01 2.68708497e-01 -1.60851169e+00
-5.01892269e-01 -1.28367260e-01 -2.57800907e-01 1.27937162e+00
4.76834536e-01 3.91808450e-02 8.62448514e-01 1.06581938e+00
-3.01989943e-01 -8.56790662e-01 -7.92085886e-01 -5.61922908e-01
5.73898554e-01 1.87403038e-02 6.51745021e-01 1.23386538e+00
4.86359030e-01 5.58893263e-01 2.03511253e-01 -5.25580168e-01
6.87305272e-01 -6.30710721e-02 2.63855189e-01 -1.51216972e+00
3.19838859e-02 -8.56750190e-01 8.98205414e-02 -7.98258185e-01
6.20172739e-01 -1.06435871e+00 -1.76672116e-01 -1.25864172e+00
3.76557052e-01 -5.57673812e-01 -5.61851919e-01 4.92352575e-01
-4.50668901e-01 5.24053536e-02 1.31059185e-01 1.22981824e-01
-6.96799278e-01 4.08733368e-01 1.06429005e+00 -1.74573079e-01
-2.45262608e-01 -9.77735445e-02 -8.94042671e-01 5.24982393e-01
9.94540513e-01 -5.84014177e-01 -4.67183888e-01 -8.21867764e-01
2.63624161e-01 5.99589311e-02 6.66895881e-02 -9.35455322e-01
6.05869889e-01 -2.43926868e-01 6.23183727e-01 -2.59454399e-01
2.35320881e-01 -5.60259879e-01 -9.52746511e-01 2.47729700e-02
-1.39675844e+00 4.30702001e-01 1.43643603e-01 -7.88458623e-03
-7.39762112e-02 -9.67884481e-01 8.51693153e-01 -1.76102281e-01
-2.64748275e-01 -3.01384062e-01 -1.55579090e-01 4.85716462e-01
7.18971729e-01 -1.92044169e-01 -4.52023357e-01 -2.44314790e-01
-3.49963248e-01 3.03827852e-01 3.21308404e-01 6.06069326e-01
3.40159088e-01 -1.09954405e+00 -9.47979569e-01 2.51924783e-01
1.02919549e-01 -4.94814008e-01 3.32375690e-02 4.10215050e-01
-3.84308130e-01 7.91528940e-01 -4.19140339e-01 -1.93356294e-02
-1.54906917e+00 -9.57067162e-02 7.65518248e-02 -8.28590930e-01
2.17993069e-03 9.97041404e-01 -6.98968530e-01 -9.66244519e-01
3.70394349e-01 -6.91338852e-02 -4.08017218e-01 3.34677845e-01
6.04853392e-01 8.42431486e-01 3.59536409e-01 1.11743577e-01
3.82150739e-01 3.60305220e-01 -2.95186341e-01 -2.58244783e-01
1.30930901e+00 -1.26490906e-01 1.10974565e-01 5.67501187e-01
1.15182722e+00 1.86485812e-01 -1.05247390e+00 -1.38759091e-01
3.75101477e-01 -1.62948832e-01 2.38970786e-01 -1.55498755e+00
-3.65105212e-01 1.04410708e+00 3.43141973e-01 -1.04537003e-01
5.70232451e-01 -4.96790349e-01 1.00020444e+00 6.81834817e-01
-2.47865662e-01 -1.71658778e+00 5.13378203e-01 8.59150827e-01
3.88718188e-01 -1.26876080e+00 1.43417284e-01 4.19048548e-01
-4.46045071e-01 1.54167509e+00 8.88969123e-01 1.75103858e-01
3.67798448e-01 1.30789787e-01 2.65474647e-01 9.58764926e-02
-7.68831670e-01 5.16342998e-01 5.93045175e-01 2.51708746e-01
8.77372205e-01 8.85232389e-02 -2.71464974e-01 9.46919322e-01
-4.88096297e-01 1.10677913e-01 7.99683809e-01 6.13458276e-01
-5.68671465e-01 -1.29877818e+00 -4.09002811e-01 9.37797368e-01
-7.48543084e-01 -5.01397371e-01 -4.64422435e-01 3.60860527e-01
-2.14692339e-01 8.14727247e-01 -3.23532820e-02 -2.42661107e-02
1.42982721e-01 9.34141755e-01 6.98451638e-01 -8.74879837e-01
-1.09570944e+00 -8.31294358e-01 2.57685315e-04 2.10830241e-01
-8.75957087e-02 -7.29575872e-01 -8.59100819e-01 -2.59248942e-01
-6.01184964e-01 1.71162248e-01 9.63129401e-01 1.03419578e+00
2.53160894e-01 6.70261383e-01 4.48632240e-01 -2.04953358e-01
-1.60767019e+00 -1.21449935e+00 -4.22467291e-01 4.59107131e-01
2.97624588e-01 -4.06853884e-01 -4.72558796e-01 2.24824563e-01] | [11.31344985961914, 9.359574317932129] |
506e201a-f419-4b91-b8c5-a622fc270aa5 | aligning-synthetic-medical-images-with | 2306.12438 | null | https://arxiv.org/abs/2306.12438v1 | https://arxiv.org/pdf/2306.12438v1.pdf | Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback | Generative models capable of capturing nuanced clinical features in medical images hold great promise for facilitating clinical data sharing, enhancing rare disease datasets, and efficiently synthesizing annotated medical images at scale. Despite their potential, assessing the quality of synthetic medical images remains a challenge. While modern generative models can synthesize visually-realistic medical images, the clinical validity of these images may be called into question. Domain-agnostic scores, such as FID score, precision, and recall, cannot incorporate clinical knowledge and are, therefore, not suitable for assessing clinical sensibility. Additionally, there are numerous unpredictable ways in which generative models may fail to synthesize clinically plausible images, making it challenging to anticipate potential failures and manually design scores for their detection. To address these challenges, this paper introduces a pathologist-in-the-loop framework for generating clinically-plausible synthetic medical images. Starting with a diffusion model pretrained using real images, our framework comprises three steps: (1) evaluating the generated images by expert pathologists to assess whether they satisfy clinical desiderata, (2) training a reward model that predicts the pathologist feedback on new samples, and (3) incorporating expert knowledge into the diffusion model by using the reward model to inform a finetuning objective. We show that human feedback significantly improves the quality of synthetic images in terms of fidelity, diversity, utility in downstream applications, and plausibility as evaluated by experts. | ['Ahmed M. Alaa', 'Atul Butte', 'Gregory M. Goldgof', 'Shenghuan Sun'] | 2023-06-16 | null | null | null | null | ['clinical-knowledge'] | ['miscellaneous'] | [ 5.07311106e-01 4.62724537e-01 -3.32942195e-02 -3.28043491e-01
-1.10440707e+00 -6.84948504e-01 4.41968441e-01 2.16231450e-01
-2.85024047e-01 8.47739458e-01 3.03979427e-01 -4.46086586e-01
-1.06284268e-01 -6.66898608e-01 -5.06266534e-01 -6.63204730e-01
5.06342098e-04 8.10132563e-01 3.68875153e-02 3.01780134e-01
-1.59515589e-01 5.12791038e-01 -9.96193528e-01 4.48250204e-01
1.15714931e+00 8.74862731e-01 1.59579247e-01 9.28338706e-01
4.39931870e-01 7.58921742e-01 -7.17502177e-01 -5.24136007e-01
2.27316231e-01 -9.09568369e-01 -5.01484215e-01 4.53127682e-01
1.41968817e-01 -5.38193107e-01 -1.43405318e-01 9.23794508e-01
6.29676044e-01 -2.55168110e-01 8.29634309e-01 -1.02073479e+00
-9.09687579e-01 4.24172908e-01 -2.74941921e-01 1.20942757e-01
2.01038375e-01 8.98053885e-01 6.32876635e-01 -6.34661555e-01
9.44815040e-01 8.96218896e-01 5.23423910e-01 8.05733979e-01
-1.34032619e+00 -4.41181719e-01 -1.49973795e-01 -1.76276997e-01
-1.22053647e+00 -3.65559220e-01 2.61201978e-01 -6.59142077e-01
4.55089420e-01 4.66707140e-01 7.90989459e-01 9.59363461e-01
4.48878765e-01 5.30879736e-01 1.07653964e+00 -1.08989365e-01
3.08536053e-01 2.41706818e-01 -5.39464712e-01 7.92972386e-01
2.61276513e-01 2.93900371e-01 -1.44683361e-01 -3.21400464e-01
8.99790466e-01 -3.71038541e-03 -4.22290355e-01 -2.08253160e-01
-1.34525204e+00 6.91964090e-01 6.43191159e-01 6.56246021e-02
-6.55489385e-01 2.00461194e-01 1.14160359e-01 6.29476681e-02
1.76729590e-01 7.06018031e-01 3.99397500e-02 2.04010859e-01
-1.07051706e+00 2.03276023e-01 2.71104455e-01 6.65596008e-01
1.88705683e-01 1.26053803e-02 -4.61453825e-01 5.91046989e-01
1.90514848e-01 5.70971370e-01 6.75862849e-01 -1.02758467e+00
-8.46550241e-02 5.34735680e-01 2.61601031e-01 -7.27520287e-01
-2.59487480e-01 -6.35514617e-01 -9.15961206e-01 2.57793307e-01
1.76275924e-01 -1.57981396e-01 -1.18933272e+00 1.59690094e+00
3.55910510e-01 3.66719104e-02 4.80209142e-02 1.02962971e+00
5.89509010e-01 4.11176771e-01 4.31458801e-01 -2.98856437e-01
1.29804134e+00 -6.64650083e-01 -4.91226524e-01 -2.27361292e-01
5.74357986e-01 -6.80296600e-01 1.00009847e+00 3.76598477e-01
-1.39257562e+00 -2.23584890e-01 -8.98513973e-01 3.73121679e-01
1.21949166e-01 1.73500657e-01 4.50683743e-01 5.71364284e-01
-1.19710159e+00 5.00370562e-01 -1.04890800e+00 -1.03740916e-01
7.80913174e-01 2.60154575e-01 -2.01557100e-01 -2.98971921e-01
-9.98881221e-01 8.17081928e-01 1.39960840e-01 -1.19187403e-02
-1.24262035e+00 -9.42147017e-01 -6.59316897e-01 -5.20914309e-02
1.59907714e-01 -1.17786586e+00 1.26633275e+00 -1.01371789e+00
-9.94892538e-01 8.80176723e-01 7.21908733e-02 -4.15123045e-01
9.98792350e-01 4.42580312e-01 -4.86736029e-01 1.85160637e-01
1.15843900e-01 1.03219128e+00 6.43848956e-01 -1.41768384e+00
-6.23693228e-01 -2.43097082e-01 -1.72704995e-01 2.07293913e-01
4.43621390e-02 -3.18670452e-01 -3.36899459e-01 -8.48399401e-01
-2.29701132e-01 -1.03133142e+00 -8.13508570e-01 4.56804454e-01
-4.16031092e-01 4.98780161e-01 3.06641281e-01 -6.13745451e-01
1.10232186e+00 -2.04038739e+00 -3.36248040e-01 4.44403887e-01
4.72189069e-01 4.40644175e-01 -1.82232931e-01 1.90202408e-02
9.79514122e-02 2.79598832e-01 -2.34541133e-01 9.48124155e-02
-3.71159673e-01 -4.11042720e-02 -5.10129035e-02 2.57156163e-01
5.85314214e-01 1.24912441e+00 -1.18314064e+00 -6.21780336e-01
1.01196811e-01 6.11987710e-01 -7.97431707e-01 2.20608711e-01
-2.79684097e-01 8.30466509e-01 -4.55396533e-01 5.98346651e-01
3.37481111e-01 -8.50244462e-01 3.08151633e-01 -7.02348873e-02
5.08658290e-01 -7.66335949e-02 -8.61866653e-01 1.15644276e+00
-4.04900253e-01 3.67630988e-01 -2.05815792e-01 -4.17232573e-01
5.97907901e-01 4.60233659e-01 5.18586814e-01 -5.48556566e-01
3.02076638e-02 2.23032922e-01 2.92325646e-01 -4.50055778e-01
1.47160843e-01 -5.46850026e-01 1.49050161e-01 6.91300571e-01
-3.61712515e-01 -2.91325122e-01 7.24751353e-02 2.26932570e-01
1.33538985e+00 -3.41023684e-01 1.12579107e-01 2.16196582e-01
2.44414106e-01 2.27586344e-01 4.79429960e-01 5.45937538e-01
-2.82714576e-01 9.21215832e-01 5.64556003e-01 -2.84491181e-01
-1.25859272e+00 -1.44997382e+00 -6.40311092e-02 3.07247549e-01
-2.16797352e-01 9.35185477e-02 -6.43872201e-01 -6.83804214e-01
-7.10670231e-03 6.78538024e-01 -7.81334937e-01 -4.07792538e-01
-1.31577402e-01 -8.64537299e-01 4.58948731e-01 6.98714733e-01
-3.75807770e-02 -1.01912475e+00 -8.16537857e-01 3.54297340e-01
-1.57394975e-01 -9.24161792e-01 -7.54141390e-01 -3.28552455e-01
-8.92526925e-01 -1.10519993e+00 -1.13374233e+00 -5.13733208e-01
1.21903348e+00 -3.56014781e-02 1.13895488e+00 2.01539576e-01
-6.97719097e-01 1.83818236e-01 -1.10464431e-01 -4.80107784e-01
-1.08629835e+00 -4.60399747e-01 -3.40850174e-01 -1.29709303e-01
-1.67877510e-01 -2.29997173e-01 -1.27289927e+00 4.42026943e-01
-1.15873408e+00 2.10723355e-01 9.24820125e-01 1.14561021e+00
9.52901661e-01 -3.31249416e-01 7.01537907e-01 -1.21596229e+00
9.63977039e-01 -4.03479874e-01 -3.79397005e-01 4.19214994e-01
-9.18744624e-01 3.47910784e-02 5.06964207e-01 -5.92055261e-01
-9.82174218e-01 2.17210546e-01 -9.49580818e-02 -6.52552962e-01
2.19165206e-01 4.53379840e-01 3.01423579e-01 8.10668841e-02
1.14032018e+00 2.03247771e-01 2.69039124e-01 2.48438656e-01
2.88674384e-01 4.51658189e-01 6.45981550e-01 -2.23962113e-01
5.24883866e-01 5.41411698e-01 -7.02285543e-02 -2.14495435e-01
-6.72045887e-01 -2.36039199e-02 -7.32988492e-02 -3.50267678e-01
7.86901295e-01 -9.50254083e-01 -4.91394579e-01 2.75053661e-02
-6.79700375e-01 -3.75955224e-01 -6.12526476e-01 3.61508727e-01
-5.77182353e-01 1.03841767e-01 -5.93031943e-01 -5.68925202e-01
-3.69292289e-01 -1.62442732e+00 9.80802059e-01 2.29203314e-01
-6.09215975e-01 -1.03293264e+00 -3.76067646e-02 4.54745114e-01
5.43632507e-01 5.56134820e-01 1.11600947e+00 -2.73997724e-01
-8.37578177e-01 -4.37835395e-01 -1.73217148e-01 2.06655160e-01
2.10077152e-01 1.68451518e-01 -7.98939168e-01 -2.05312982e-01
-3.96764576e-01 -3.90256107e-01 5.20564795e-01 7.43204117e-01
1.09745955e+00 -2.85128474e-01 -3.82299274e-01 4.68706965e-01
1.11684549e+00 3.72777939e-01 6.60832167e-01 -2.68231183e-01
2.64794320e-01 4.35829222e-01 4.45896387e-01 4.33962375e-01
3.94270301e-01 3.44313353e-01 2.34990627e-01 -4.52919990e-01
-3.18644643e-01 -4.75344002e-01 -4.54041362e-02 3.68970156e-01
1.45597219e-01 -4.73348022e-01 -1.01566601e+00 7.58157372e-01
-1.60188520e+00 -7.73594379e-01 1.88958555e-01 2.13649392e+00
1.00169873e+00 2.17615232e-01 1.43979564e-01 -1.85198739e-01
6.84506536e-01 -3.78971100e-01 -8.53944242e-01 -1.58610776e-01
-9.96690895e-03 6.90893754e-02 4.31550175e-01 3.62069875e-01
-4.99633729e-01 6.50006115e-01 6.76927233e+00 5.55355370e-01
-1.34154141e+00 1.30208626e-01 1.38935649e+00 -1.65500343e-01
-7.29948819e-01 -3.53793949e-02 -2.24113271e-01 4.12127912e-01
8.14479709e-01 -3.48430067e-01 2.11889848e-01 5.82705855e-01
5.15907347e-01 -5.27571812e-02 -1.08138919e+00 6.56748950e-01
-3.91551182e-02 -1.70919931e+00 3.62381876e-01 1.85377344e-01
1.00121725e+00 -3.11170459e-01 5.09634554e-01 -1.60742819e-01
7.32101679e-01 -1.35198414e+00 5.54514527e-01 7.58353949e-01
1.35377121e+00 -5.80790639e-01 6.28300190e-01 2.28209853e-01
-4.95888650e-01 2.30246887e-01 -1.62568122e-01 7.28828847e-01
2.62956113e-01 6.48436666e-01 -1.41843331e+00 1.98820665e-01
7.20844492e-02 2.11470440e-01 -5.39058506e-01 1.09286427e+00
-1.75597101e-01 4.76153880e-01 -1.01897428e-02 7.22672641e-02
1.79639429e-01 2.38269821e-01 1.70114622e-01 1.05575454e+00
4.37166125e-01 2.01885238e-01 -1.19953491e-01 1.04138637e+00
-8.49587619e-02 1.78606343e-02 -3.27838302e-01 -3.61704826e-01
4.43544239e-01 1.23492694e+00 -9.18879449e-01 -4.84148204e-01
-3.55631020e-03 8.34462106e-01 -1.82665795e-01 3.23089898e-01
-7.15109944e-01 9.63562280e-02 2.91804940e-01 4.91015404e-01
-9.94559191e-03 4.01412070e-01 -5.63794792e-01 -8.48518789e-01
-2.48452350e-01 -1.13757551e+00 3.92734587e-01 -1.12747800e+00
-1.17186284e+00 7.88506329e-01 -4.00111854e-01 -1.45169759e+00
-5.98394871e-01 -4.03486013e-01 -4.60479617e-01 9.44778919e-01
-1.15598321e+00 -1.06732106e+00 -4.60757971e-01 3.02666962e-01
2.48361155e-01 -2.03328654e-02 7.67215669e-01 1.68095976e-01
-2.13340491e-01 7.95249999e-01 -4.67917845e-02 -1.20284349e-01
7.90960729e-01 -1.11045527e+00 4.39002395e-01 4.81924176e-01
-1.03072822e-01 4.61439013e-01 8.34170282e-01 -8.05854797e-01
-9.36894596e-01 -1.30581331e+00 5.73386073e-01 -3.95432919e-01
4.37776595e-01 2.28226244e-01 -8.68947506e-01 4.52905446e-01
-3.43239754e-01 1.57371968e-01 8.38873744e-01 -5.38504720e-01
-5.32323085e-02 6.18276373e-03 -1.48573625e+00 8.60063851e-01
7.53510833e-01 -1.84376717e-01 -4.25783321e-02 4.42313522e-01
3.64948064e-01 -4.73481625e-01 -1.02409971e+00 3.44160229e-01
5.41928947e-01 -6.59965634e-01 8.79468560e-01 -6.85161769e-01
7.50623286e-01 -1.27924040e-01 2.51460105e-01 -1.46688986e+00
-2.57137716e-01 -4.49413359e-01 2.49963060e-01 6.65973544e-01
8.76516998e-01 -4.15258855e-01 1.01547730e+00 8.56056392e-01
5.11835068e-02 -1.07732773e+00 -5.83375514e-01 -4.00970578e-01
4.04604748e-02 -2.45704249e-01 5.61446667e-01 8.27169657e-01
-6.19415678e-02 4.80602644e-02 -1.76418155e-01 1.28634507e-02
3.95276845e-01 -1.16790585e-01 5.45468926e-01 -8.16067874e-01
-5.52697301e-01 -5.88781059e-01 -4.71441597e-01 -6.45085037e-01
-4.19632882e-01 -8.20832729e-01 7.55534917e-02 -1.75090969e+00
3.96528035e-01 -6.79283202e-01 -1.54611051e-01 3.79813522e-01
-5.69289923e-01 4.09204155e-01 1.04841396e-01 3.60508621e-01
-3.31218570e-01 1.93880886e-01 1.81883240e+00 -1.95007220e-01
6.88628703e-02 -6.17661588e-02 -9.12425578e-01 5.10490358e-01
4.42929894e-01 -4.46891636e-01 -6.28595531e-01 -2.15814069e-01
2.88445294e-01 6.50602400e-01 5.67558646e-01 -9.35871840e-01
3.50097790e-02 -3.40243161e-01 7.53024101e-01 -1.89216152e-01
9.83396694e-02 -3.80875915e-01 6.28880978e-01 1.01639807e+00
-4.87945080e-01 1.50446460e-01 5.64812906e-02 6.14581704e-01
-1.73363209e-01 -5.75094372e-02 1.00701630e+00 -2.49838367e-01
-2.05963314e-01 4.34643656e-01 -4.32574987e-01 3.10510665e-01
1.14875066e+00 -2.51629204e-01 -1.20838098e-01 -6.61522567e-01
-9.20640171e-01 3.39536160e-01 7.67972171e-01 1.30664766e-01
7.92232096e-01 -1.14322162e+00 -1.04231369e+00 7.25670904e-02
2.21423820e-01 8.99226230e-04 6.68003321e-01 7.18619287e-01
-8.20758581e-01 1.77288100e-01 -4.34545986e-02 -6.40600801e-01
-1.00830984e+00 5.46263397e-01 5.42068660e-01 -7.00004041e-01
-2.33696088e-01 8.15849960e-01 6.26411319e-01 -5.22073731e-02
-6.77424893e-02 -2.18129188e-01 3.12791288e-01 -3.22227657e-01
4.03778732e-01 -1.09649643e-01 6.21917509e-02 -3.92961293e-01
-2.77828485e-01 9.73987803e-02 -3.03539038e-01 -3.09017718e-01
1.13889861e+00 1.09331086e-01 5.96049190e-01 -2.18613483e-02
6.37297273e-01 -8.89866725e-02 -1.50627935e+00 -1.50317892e-01
-3.80078018e-01 -4.21765417e-01 -4.47302163e-02 -1.45126188e+00
-1.10747671e+00 7.78050065e-01 7.55683303e-01 -1.68175593e-01
1.27188575e+00 -2.08476409e-02 7.68901706e-01 -2.58388489e-01
1.16630100e-01 -7.84822941e-01 3.22051734e-01 -2.47731954e-01
8.09772670e-01 -1.19606769e+00 -6.75321138e-03 -3.10763538e-01
-1.22689211e+00 6.77038789e-01 3.98845047e-01 6.55510426e-02
3.59381288e-01 4.15140480e-01 4.35086131e-01 -1.16761997e-01
-1.17661989e+00 2.05136329e-01 3.79140794e-01 8.11583102e-01
3.82455617e-01 3.08717787e-01 -2.36387178e-01 2.93171465e-01
-1.17865875e-01 3.52921993e-01 5.86605549e-01 7.94069052e-01
-2.09996119e-01 -9.14061964e-01 -2.94095546e-01 7.79441118e-01
-4.99703825e-01 -9.20845941e-02 -2.69010186e-01 4.38106894e-01
1.68738827e-01 5.26611447e-01 -7.69957304e-02 -2.81094581e-01
4.08934772e-01 -3.24666828e-01 4.25958723e-01 -6.86862886e-01
-6.13887906e-01 9.87877026e-02 -1.15549400e-01 -2.79020518e-01
8.60630497e-02 -6.49534822e-01 -1.13981390e+00 -1.20068148e-01
-1.60858870e-01 1.91591941e-02 5.50569713e-01 6.72527850e-01
6.02232575e-01 7.45244265e-01 5.45087397e-01 -2.05966905e-01
-6.77865028e-01 -6.45454586e-01 -1.63428918e-01 5.70684791e-01
2.74877012e-01 -3.14864576e-01 -6.16156124e-02 4.05818462e-01] | [14.293296813964844, -1.9216371774673462] |
31e7df59-db6e-455c-b330-dd2432064ef5 | eend-ss-joint-end-to-end-neural-speaker | 2203.17068 | null | https://arxiv.org/abs/2203.17068v2 | https://arxiv.org/pdf/2203.17068v2.pdf | EEND-SS: Joint End-to-End Neural Speaker Diarization and Speech Separation for Flexible Number of Speakers | In this paper, we present a novel framework that jointly performs three tasks: speaker diarization, speech separation, and speaker counting. Our proposed framework integrates speaker diarization based on end-to-end neural diarization (EEND) models, speaker counting with encoder-decoder based attractors (EDA), and speech separation using Conv-TasNet. In addition, we propose a multiple 1x1 convolutional layer architecture for estimating the separation masks corresponding to a flexible number of speakers and a fusion technique for refining the separated speech signal with obtained speaker diarization information to improve the joint framework. Experiments using the LibriMix dataset show that our proposed method outperforms the single-task baselines in both diarization and separation metrics for fixed and flexible numbers of speakers and improves speaker counting performance for flexible numbers of speakers. All materials will be open-sourced and reproducible in ESPnet toolkit. | ['Soumi Maiti', 'Yong Xu', 'Shi-Xiong Zhang', 'Meng Yu', 'Chunlei Zhang', 'Shinji Watanabe', 'Yushi Ueda'] | 2022-03-31 | null | null | null | null | ['speech-separation'] | ['speech'] | [-4.84543666e-02 -1.88287601e-01 3.16634178e-01 -5.09529233e-01
-1.11524498e+00 -6.55965447e-01 5.41293025e-01 -3.09418142e-01
-5.99729121e-01 1.72993511e-01 3.56364310e-01 -1.77031353e-01
1.65551558e-01 9.56436992e-02 -2.74310231e-01 -5.32476127e-01
6.35698959e-02 4.61008936e-01 2.19259243e-02 1.75861746e-01
9.20180827e-02 5.00597298e-01 -1.51744056e+00 8.76772925e-02
8.31337929e-01 8.45006526e-01 1.22985967e-01 1.21340036e+00
2.98294537e-02 2.34472737e-01 -1.22412443e+00 -2.02524006e-01
1.65190965e-01 -2.75506973e-01 -4.19187814e-01 7.59689137e-02
6.66333914e-01 -3.12684804e-01 -3.25334072e-01 9.87351894e-01
1.09807134e+00 2.25473687e-01 6.09368622e-01 -1.03699410e+00
-4.11745071e-01 9.53463495e-01 -4.71804947e-01 6.41318977e-01
7.02105314e-02 -6.75128549e-02 5.44371963e-01 -9.22101140e-01
-2.10268840e-01 1.73147631e+00 5.91653287e-01 9.02474463e-01
-1.07763255e+00 -1.25437701e+00 2.41714969e-01 -2.90803730e-01
-1.59281695e+00 -1.15415049e+00 6.82680726e-01 -3.15775126e-01
1.20832646e+00 3.73901725e-01 1.84527546e-01 1.17808807e+00
-2.77453631e-01 9.11467016e-01 4.67536300e-01 -3.94797087e-01
2.57839411e-01 6.14021085e-02 6.27027452e-01 4.29221570e-01
-4.73956801e-02 -7.11066872e-02 -7.96979427e-01 1.35928124e-01
8.36280286e-01 -2.87488669e-01 1.15187198e-01 5.73170781e-01
-1.18934190e+00 6.32323503e-01 -7.81162679e-02 3.92312795e-01
-1.61104098e-01 -1.87263601e-02 4.58289564e-01 7.62060583e-02
6.30875766e-01 6.07811585e-02 -9.91531610e-02 -7.94726908e-02
-1.48242390e+00 1.98899731e-01 7.85424173e-01 1.17121792e+00
1.39824435e-01 5.96201777e-01 -5.58483303e-01 1.01631629e+00
4.79882360e-01 7.86229789e-01 7.84783602e-01 -1.01636815e+00
5.37747324e-01 2.95874923e-01 -1.60402358e-02 -5.06124616e-01
-2.81264603e-01 -5.06546736e-01 -8.62799466e-01 -5.31435106e-03
3.13293278e-01 -4.27382141e-01 -1.12456036e+00 1.95367956e+00
1.24164522e-01 5.48608840e-01 2.44109780e-01 8.39260101e-01
1.09331846e+00 6.44019723e-01 1.15503594e-02 3.35258730e-02
1.51469958e+00 -1.10947895e+00 -9.81511295e-01 -3.99764061e-01
8.35479349e-02 -6.85855985e-01 7.49499202e-01 3.97390962e-01
-1.44223166e+00 -7.78045654e-01 -1.19729352e+00 -2.43919529e-03
-1.35189533e-01 7.10119903e-01 1.22930519e-01 9.72195327e-01
-1.35730588e+00 1.78262331e-02 -1.18852055e+00 -2.31576666e-01
3.44875067e-01 7.08939910e-01 1.58004612e-01 7.67010391e-01
-1.09303010e+00 6.11177206e-01 1.18983582e-01 1.30262613e-01
-1.14393330e+00 -4.01119500e-01 -9.19215679e-01 3.95942390e-01
-2.13627875e-01 -5.54610908e-01 1.57663608e+00 -8.80606651e-01
-1.85902297e+00 8.88549984e-01 -4.67708647e-01 -8.95191729e-01
2.85380721e-01 -2.55037904e-01 -6.90611124e-01 4.00075950e-02
1.12823278e-01 9.73610699e-01 1.02392137e+00 -7.98819721e-01
-5.81225574e-01 -4.91762072e-01 -6.54263020e-01 3.70088458e-01
-3.36079121e-01 5.19793391e-01 -5.65762222e-01 -6.70226455e-01
6.96536303e-02 -6.63872480e-01 2.74973512e-01 -5.40003717e-01
-7.61542797e-01 -4.07508641e-01 7.00353265e-01 -9.96964335e-01
1.39935696e+00 -2.46110034e+00 8.15180317e-02 -6.46320581e-02
3.84576410e-01 5.02809107e-01 -1.40357032e-01 -9.67147499e-02
-8.53426158e-02 -7.81807750e-02 -8.83614644e-02 -1.24270737e+00
2.31678322e-01 -4.16563123e-01 -2.09682286e-01 3.20167989e-01
1.66471034e-01 4.42708939e-01 -4.72740293e-01 -4.72275019e-01
4.10980403e-01 8.48208964e-01 -3.71059388e-01 2.18713894e-01
3.72011989e-01 3.79344791e-01 1.28184587e-01 4.74623919e-01
9.30687070e-01 2.13765174e-01 -3.13336939e-01 2.55870640e-01
-2.85661966e-01 5.48329592e-01 -1.51525712e+00 1.59152794e+00
-4.92177099e-01 7.91657507e-01 5.97559810e-01 -4.43588436e-01
1.14576459e+00 4.43197191e-01 -1.51293352e-01 -2.37674385e-01
4.36945349e-01 1.96795568e-01 -1.27667915e-02 -4.59750704e-02
3.05197895e-01 6.90829679e-02 -1.47525251e-01 3.34727794e-01
5.54903328e-01 1.09200299e-01 1.53636977e-01 2.09501565e-01
7.70971179e-01 -5.26295364e-01 7.48025104e-02 -3.98372084e-01
7.81977952e-01 -8.40251386e-01 4.19238746e-01 6.18744850e-01
-6.78637266e-01 6.13192976e-01 1.63991749e-01 3.90556119e-02
-6.46680117e-01 -1.23768163e+00 -1.92450523e-01 1.16405857e+00
-2.39986628e-02 -2.37051308e-01 -1.43721330e+00 -1.81906417e-01
-2.52765656e-01 1.07468307e+00 -4.17248935e-01 -1.73509881e-01
-7.06132054e-01 -5.11840224e-01 1.32219064e+00 7.35813260e-01
7.40095794e-01 -1.01845741e+00 -3.24434876e-01 1.73870265e-01
-3.86533588e-01 -1.13265705e+00 -1.23771739e+00 4.90297437e-01
-4.94191200e-01 -2.62315363e-01 -9.14892077e-01 -1.21504879e+00
1.76130980e-01 2.84509242e-01 7.74202406e-01 -4.87797767e-01
3.81954806e-03 6.69087991e-02 2.61998922e-01 -5.82474470e-01
-5.70411444e-01 3.26019913e-01 3.38115841e-01 6.76304102e-02
8.50026548e-01 -5.37655890e-01 -5.57086825e-01 3.25475365e-01
-4.62543577e-01 -1.52135029e-01 3.33487153e-01 2.87126213e-01
2.13985339e-01 -2.22862095e-01 8.83078933e-01 -4.29393873e-02
8.26858103e-01 -1.35714069e-01 -6.29369140e-01 1.39242128e-01
-1.10591628e-01 2.52242744e-01 2.84257472e-01 -6.32838607e-01
-1.06359816e+00 6.98516667e-02 -3.05727333e-01 -6.37752473e-01
-4.77356285e-01 -3.09386492e-01 -4.09088790e-01 3.38746846e-01
5.37594378e-01 3.97765875e-01 -2.04698788e-03 -5.07395148e-01
1.25032052e-01 1.27911985e+00 8.21633160e-01 -2.08358858e-02
2.38341644e-01 1.58843726e-01 -9.18171167e-01 -1.00350404e+00
-5.55429876e-01 -7.08454669e-01 -6.67797506e-01 -2.94086821e-02
1.17262483e+00 -1.31372917e+00 -9.12750602e-01 9.56924021e-01
-1.42087567e+00 -1.46742448e-01 1.00488551e-01 6.30255401e-01
-1.51989847e-01 2.49736235e-01 -5.83838642e-01 -1.24832714e+00
-9.54517603e-01 -1.33197331e+00 1.54694331e+00 4.65900987e-01
-3.75877708e-01 -7.50652909e-01 1.80074111e-01 3.52778822e-01
4.36597556e-01 -2.94664413e-01 1.08510837e-01 -1.28851044e+00
-1.80904835e-01 -2.92602241e-01 2.47594416e-02 5.13641119e-01
5.92887364e-02 -1.16654057e-02 -1.32297790e+00 -1.93025783e-01
1.36361361e-01 7.30707943e-02 1.17997992e+00 8.67168784e-01
9.45130706e-01 -2.74968415e-01 -2.76112169e-01 6.96108282e-01
7.02784181e-01 2.94494599e-01 3.23678464e-01 -1.32859170e-01
4.67061788e-01 2.80283839e-01 -3.06926966e-01 4.35121864e-01
4.77710903e-01 5.70839822e-01 7.66782612e-02 9.77070555e-02
-5.00192106e-01 9.87596288e-02 5.87132692e-01 1.18034828e+00
3.62374961e-01 -5.52112401e-01 -7.38826990e-01 6.42238319e-01
-1.41941154e+00 -1.11431956e+00 1.13833606e-01 2.32168341e+00
8.07271898e-01 2.35105395e-01 6.57913446e-01 2.22345427e-01
1.40434968e+00 3.58583033e-02 -6.69836879e-01 -5.52470386e-01
-1.93468049e-01 1.20573401e-01 3.90114397e-01 9.05664802e-01
-1.14262843e+00 1.01280463e+00 6.39296293e+00 8.03999782e-01
-1.12906671e+00 1.51368484e-01 5.04001737e-01 -4.89744514e-01
2.59613037e-01 -7.15678513e-01 -1.48384535e+00 7.19869077e-01
1.48175251e+00 2.25594994e-02 6.33806825e-01 5.79328895e-01
1.23158470e-01 2.60647625e-01 -1.09492028e+00 1.37361002e+00
5.35879493e-01 -8.00082922e-01 -1.21342853e-01 -2.42914006e-01
2.46889070e-01 1.59429237e-01 1.62123039e-01 3.95918727e-01
4.50226158e-01 -8.98495078e-01 9.70225096e-01 3.05335343e-01
7.61544824e-01 -7.61881709e-01 4.11026239e-01 3.29370499e-01
-1.21614444e+00 -7.80035257e-02 -4.94950116e-02 3.47685903e-01
9.15162191e-02 2.57974535e-01 -9.94808197e-01 -3.05070225e-02
6.44799411e-01 2.80829072e-01 -5.67761958e-01 9.29243267e-01
4.57057282e-02 8.44077468e-01 -4.42023695e-01 6.01342395e-02
6.58799335e-02 2.74127573e-01 8.67312729e-01 1.64779317e+00
2.86225855e-01 -2.14624003e-01 -2.37098604e-01 9.72377002e-01
-2.16759875e-01 -4.45809454e-01 -7.74775743e-02 6.16474859e-02
1.02886891e+00 1.33511865e+00 -8.25973451e-01 -3.94069433e-01
-4.60550152e-02 1.10185599e+00 6.90015256e-02 4.39494491e-01
-9.86600816e-01 -7.31961966e-01 6.63446665e-01 -2.41152659e-01
4.41390574e-01 -3.13479751e-01 -4.78938073e-01 -1.10094202e+00
-2.91212052e-01 -7.85794914e-01 2.31186390e-01 -4.11256135e-01
-9.62352037e-01 9.78715301e-01 -8.25090334e-02 -9.30300653e-01
-2.90483624e-01 -3.05887908e-01 -9.43628907e-01 1.10984647e+00
-1.13330185e+00 -9.14374948e-01 -2.70113111e-01 6.08117342e-01
1.07475162e+00 -5.03107846e-01 7.97415435e-01 4.53597784e-01
-9.77757990e-01 1.20087385e+00 7.36507848e-02 4.02275831e-01
7.73029983e-01 -1.35111594e+00 9.22370732e-01 1.07275653e+00
2.14241683e-01 5.82189798e-01 5.56441545e-01 -4.13729578e-01
-6.58615828e-01 -1.16208065e+00 1.02169132e+00 -5.14952779e-01
1.78033009e-01 -1.04273641e+00 -7.62713611e-01 7.65737236e-01
3.86852294e-01 -4.68874842e-01 7.64863193e-01 -3.10236053e-03
-1.56832457e-01 -1.55566618e-01 -1.04422045e+00 4.31674510e-01
7.24754035e-01 -4.90274787e-01 -5.72384417e-01 8.60150382e-02
8.66262078e-01 -4.62488621e-01 -2.46442556e-01 -1.53817281e-01
3.62825841e-01 -6.33593082e-01 1.07849669e+00 -9.23724025e-02
-3.22880417e-01 -1.81110919e-01 -1.14974760e-01 -1.17018092e+00
-3.56073916e-01 -9.03235853e-01 -2.76361465e-01 1.68685794e+00
3.78905386e-01 -5.04146457e-01 3.08679521e-01 4.50313598e-01
-4.06214446e-01 -1.38298780e-01 -1.23494565e+00 -8.77749085e-01
1.09570846e-01 -2.59452850e-01 8.71126413e-01 4.00776893e-01
-1.39555112e-01 7.41844058e-01 -2.29257837e-01 5.63986242e-01
6.67706490e-01 -3.33623588e-01 4.58615363e-01 -1.16295028e+00
-6.49421364e-02 -7.59017110e-01 -2.25025356e-01 -1.12750137e+00
3.55436385e-01 -8.96888554e-01 2.97451019e-01 -1.14226830e+00
3.01322620e-02 3.10067654e-01 -2.77747363e-01 1.98191106e-01
-1.92976713e-01 -1.22999243e-01 1.50408344e-02 5.28905392e-02
-8.82602751e-01 5.54023743e-01 6.03050053e-01 -1.26642212e-01
-7.40132034e-01 2.77674973e-01 -6.65754795e-01 7.30467677e-01
8.59639108e-01 -4.56169575e-01 -1.61879733e-01 -7.10186839e-01
-6.02340341e-01 1.22755289e-01 3.97113115e-01 -1.37829459e+00
4.58927631e-01 6.11090600e-01 4.07246351e-01 -9.67505813e-01
4.71092969e-01 -2.97680438e-01 -3.66583139e-01 2.65438050e-01
-7.60523438e-01 -1.54934824e-01 5.25560260e-01 3.98888260e-01
-3.45428251e-02 -7.57042170e-02 9.19355869e-01 2.61383086e-01
-6.44549131e-02 2.98572574e-02 -6.56957507e-01 1.52229682e-01
7.18077779e-01 -3.32397342e-01 -1.02116354e-01 -4.17721808e-01
-8.60669196e-01 3.72624069e-01 -2.96459436e-01 5.02970099e-01
3.87186855e-01 -1.29870164e+00 -9.99189615e-01 6.13202214e-01
-3.03940326e-01 -4.20692600e-02 2.58463919e-01 6.43435895e-01
-2.08353460e-01 5.90053082e-01 6.32670820e-02 -6.10460162e-01
-1.55889213e+00 2.50056654e-01 7.03026533e-01 5.43980263e-02
-1.96467862e-01 1.34694374e+00 4.52807993e-01 -5.20303071e-01
9.32711899e-01 -6.23324096e-01 -2.79908687e-01 5.87367862e-02
8.76007915e-01 7.30217099e-01 1.38714954e-01 -7.80447245e-01
-7.77725160e-01 1.33365080e-01 -2.99060374e-01 -4.94395226e-01
1.10310686e+00 -5.32121897e-01 4.80647862e-01 6.06979072e-01
1.00599039e+00 -1.70901436e-02 -1.60087562e+00 -2.26511225e-01
-2.19996065e-01 1.57400802e-01 2.26283178e-01 -9.90124822e-01
-9.61546540e-01 1.30739403e+00 8.87290478e-01 1.13062464e-01
1.00965834e+00 5.06566018e-02 8.95264149e-01 4.41452712e-02
-3.61238420e-01 -1.10426474e+00 2.00309232e-02 6.82551324e-01
8.76858592e-01 -1.03309786e+00 -7.76007414e-01 1.78691503e-02
-7.43881464e-01 9.08239901e-01 7.81560481e-01 -2.56001860e-01
5.69391429e-01 6.59991145e-01 1.01075538e-01 -2.13154554e-02
-5.68174183e-01 -1.35734022e-01 4.23008561e-01 4.84895080e-01
5.52878380e-01 9.07407627e-02 3.41470420e-01 1.21912777e+00
-4.28953439e-01 -4.91114527e-01 1.83952242e-01 2.78633595e-01
-5.58378875e-01 -5.52874386e-01 -5.97330391e-01 1.07962541e-01
-5.78420401e-01 -4.91692036e-01 -7.02593744e-01 2.66842514e-01
1.08377831e-02 1.21186519e+00 5.01167357e-01 -3.89948159e-01
1.95850089e-01 5.12400270e-01 1.76819548e-01 -5.88240981e-01
-9.01913643e-01 6.50283039e-01 -1.77058086e-01 1.16925836e-01
-1.68882564e-01 -8.40814292e-01 -1.36400437e+00 -3.14108014e-01
-7.29975283e-01 1.67712048e-02 7.97826588e-01 8.78305316e-01
6.85603976e-01 8.42333317e-01 5.04894793e-01 -9.34155345e-01
-6.50158942e-01 -1.52366364e+00 -6.93984270e-01 -2.22924396e-01
7.45118439e-01 -2.88745940e-01 -7.27158844e-01 1.48838729e-01] | [14.650282859802246, 6.12100076675415] |
1a71df22-240c-4d95-a782-9ed13f32bcde | towards-accurate-human-motion-prediction-via | 2305.04443 | null | https://arxiv.org/abs/2305.04443v1 | https://arxiv.org/pdf/2305.04443v1.pdf | Towards Accurate Human Motion Prediction via Iterative Refinement | Human motion prediction aims to forecast an upcoming pose sequence given a past human motion trajectory. To address the problem, in this work we propose FreqMRN, a human motion prediction framework that takes into account both the kinematic structure of the human body and the temporal smoothness nature of motion. Specifically, FreqMRN first generates a fixed-size motion history summary using a motion attention module, which helps avoid inaccurate motion predictions due to excessively long motion inputs. Then, supervised by the proposed spatial-temporal-aware, velocity-aware and global-smoothness-aware losses, FreqMRN iteratively refines the predicted motion though the proposed motion refinement module, which converts motion representations back and forth between pose space and frequency space. We evaluate FreqMRN on several standard benchmark datasets, including Human3.6M, AMASS and 3DPW. Experimental results demonstrate that FreqMRN outperforms previous methods by large margins for both short-term and long-term predictions, while demonstrating superior robustness. | ['Girish Chowdhary', 'Jiarui Sun'] | 2023-05-08 | null | null | null | null | ['motion-prediction', 'human-motion-prediction'] | ['computer-vision', 'time-series'] | [ 2.48480700e-02 1.70588624e-02 -3.88214707e-01 -1.34249911e-01
-5.60847640e-01 -4.67776554e-03 5.09114325e-01 -2.61767685e-01
-5.51086664e-01 6.94318831e-01 7.75192857e-01 1.91077664e-01
1.01963738e-02 -4.18720543e-01 -6.14954114e-01 -4.41074073e-01
-2.95895398e-01 2.53906846e-01 5.40208995e-01 -1.08181655e-01
5.74286953e-02 2.60207802e-01 -1.35042810e+00 -3.31966765e-02
5.29616475e-01 7.20836818e-01 3.95561606e-01 9.22895193e-01
5.92364371e-01 1.16133666e+00 -6.76732510e-02 -1.62765235e-01
1.64398536e-01 -4.95359659e-01 -1.01954114e+00 7.19970316e-02
1.13661222e-01 -4.03973490e-01 -7.38439798e-01 5.11668563e-01
4.67689067e-01 8.58816087e-01 4.26750779e-01 -1.10814118e+00
-2.45580792e-01 2.45990410e-01 -5.91202378e-01 3.48095775e-01
6.24994457e-01 6.49549663e-01 1.07597685e+00 -8.56124580e-01
8.42140138e-01 1.33378220e+00 8.63141179e-01 8.41561139e-01
-9.97961581e-01 -3.71961296e-01 4.40790862e-01 3.86577308e-01
-1.24511349e+00 -1.97179228e-01 7.31996477e-01 -4.84684527e-01
1.15688264e+00 2.16269702e-01 7.49037862e-01 1.04947770e+00
7.35421240e-01 1.08961391e+00 1.01955384e-01 1.73877016e-01
1.08317107e-01 -7.81492770e-01 -1.09275579e-01 5.76145947e-01
-2.87413180e-01 2.37069011e-01 -6.12207890e-01 -4.49654721e-02
8.25236738e-01 -4.44525443e-02 -4.33694065e-01 -2.32883453e-01
-1.59693575e+00 4.50573683e-01 4.48866010e-01 5.71096912e-02
-7.93677986e-01 5.43030500e-01 4.25102621e-01 -1.73858836e-01
3.00216913e-01 1.95499092e-01 -4.72922683e-01 -4.22892451e-01
-1.17329800e+00 6.94595575e-01 2.12083519e-01 8.93660784e-01
5.19288003e-01 1.77991074e-02 -4.31640178e-01 4.07456547e-01
4.73422438e-01 3.52912456e-01 8.42750371e-01 -1.29356599e+00
6.43598378e-01 2.20994771e-01 3.72950524e-01 -1.36154544e+00
-7.16603696e-01 -1.33493841e-01 -9.75098729e-01 -1.24904215e-01
1.77817047e-01 -1.03603572e-01 -8.39535236e-01 1.84491062e+00
5.63298464e-01 5.78918993e-01 -1.25292391e-01 1.37273932e+00
5.59543312e-01 8.46006930e-01 6.23995185e-01 -8.63508061e-02
1.08365297e+00 -1.44120789e+00 -6.74714327e-01 -4.53179240e-01
6.51349008e-01 -4.01609868e-01 8.53961170e-01 1.31123483e-01
-1.31165743e+00 -1.03471422e+00 -8.42019200e-01 -1.67822435e-01
4.68861997e-01 1.43183812e-01 2.99232483e-01 1.32465929e-01
-8.65222633e-01 1.04124594e+00 -1.29818106e+00 -2.29620054e-01
2.06807569e-01 2.38576844e-01 -3.61309975e-01 4.24586199e-02
-1.26050806e+00 6.15406334e-01 5.27698576e-01 2.78047800e-01
-7.26521373e-01 -7.23618150e-01 -1.20728183e+00 -9.88833830e-02
2.03287587e-01 -1.18076527e+00 1.29788816e+00 -6.62011027e-01
-1.52970338e+00 2.66898036e-01 -3.73356521e-01 -6.60515428e-01
9.37414169e-01 -7.95174837e-01 -3.18156749e-01 2.11372301e-01
6.84550405e-02 1.02356982e+00 7.60505497e-01 -6.64964139e-01
-8.60408247e-01 -3.06599252e-02 -3.92444074e-01 5.08527040e-01
3.66089672e-01 -4.55215812e-01 -7.47271419e-01 -1.10562658e+00
-1.16450815e-02 -1.10180271e+00 -6.50090635e-01 -9.73073691e-02
-2.32381463e-01 -1.28034025e-01 6.42396867e-01 -9.22586501e-01
1.55854702e+00 -2.01249933e+00 7.04565823e-01 1.25148937e-01
-6.39750808e-02 2.95996666e-01 -2.23037452e-01 2.80228794e-01
8.31235722e-02 -2.39640966e-01 -2.92580813e-01 -5.99833131e-01
-1.38767704e-01 2.69972205e-01 -2.76187509e-01 5.75341284e-01
2.25427747e-01 1.22338820e+00 -1.10692608e+00 -4.81535494e-01
4.56351668e-01 5.37257254e-01 -8.55314791e-01 2.82525897e-01
-3.42605829e-01 8.94539475e-01 -4.81817096e-01 3.70018601e-01
3.07263106e-01 -3.28078866e-01 8.06501210e-02 -9.99066159e-02
1.03361055e-01 1.60078198e-01 -1.03469038e+00 2.08738351e+00
-2.96667695e-01 4.23062891e-01 -4.41992790e-01 -4.15920705e-01
6.06930494e-01 2.95709312e-01 9.16986644e-01 -5.32516420e-01
-2.94324346e-02 -6.96138218e-02 -4.50563520e-01 -5.43543696e-01
1.00058293e+00 -8.39113891e-02 -7.55276456e-02 1.02055833e-01
-1.12142846e-01 4.72679257e-01 -1.22323163e-01 -6.28035236e-03
1.04879975e+00 7.45542884e-01 4.61747289e-01 8.65214542e-02
8.44484687e-01 1.22462124e-01 9.50708210e-01 2.80693680e-01
-5.74536085e-01 8.93004060e-01 -8.79826769e-02 -5.40375650e-01
-9.13393855e-01 -9.96330440e-01 6.41103506e-01 1.07457018e+00
4.53223914e-01 -5.93682468e-01 -5.79372883e-01 -5.44888675e-01
-2.51840502e-02 5.37634552e-01 -5.19335687e-01 -3.53082418e-01
-1.23297024e+00 -4.51361686e-01 2.20846042e-01 9.88454819e-01
4.83043969e-01 -1.30931950e+00 -1.06257284e+00 5.86845458e-01
-6.15795970e-01 -9.36898172e-01 -1.06457067e+00 -6.95060134e-01
-9.48990464e-01 -8.23355079e-01 -1.08894777e+00 -7.07054913e-01
1.85601190e-01 1.59186095e-01 9.72967088e-01 1.30258501e-01
-2.20075190e-01 3.79493028e-01 -4.71215278e-01 2.88647830e-01
-7.42434561e-02 1.02815029e-04 7.17724487e-02 -3.02419290e-02
8.29023048e-02 -4.17340159e-01 -1.13579631e+00 3.98628265e-01
-5.20549715e-01 1.75574422e-01 5.19924223e-01 8.62888336e-01
7.79958487e-01 -8.88694748e-02 4.29940790e-01 -4.24199373e-01
1.00752264e-01 -6.16000354e-01 -1.11183852e-01 -9.77806840e-03
-2.51285195e-01 -3.91840823e-02 3.55285108e-01 -4.52448130e-01
-1.03593588e+00 4.98589635e-01 -4.22541320e-01 -6.02169812e-01
-3.79246399e-02 3.39148641e-01 -2.04923540e-01 4.22655195e-01
3.41144562e-01 4.01309937e-01 -2.12927610e-01 -3.11947614e-01
5.45316756e-01 -3.37041877e-02 1.11212015e+00 -1.20364733e-01
7.09967792e-01 5.72783828e-01 -2.34000757e-02 -7.78264523e-01
-4.35211092e-01 -8.04259717e-01 -7.26446986e-01 -4.43062484e-01
1.28769636e+00 -1.00872028e+00 -8.50598931e-01 4.46715891e-01
-1.26093256e+00 -4.63188410e-01 -3.49658191e-01 7.96489239e-01
-1.03480029e+00 7.77133167e-01 -8.14874947e-01 -9.04364705e-01
-4.94298846e-01 -9.90682065e-01 1.21481287e+00 2.59621572e-02
-9.98061955e-01 -9.31872308e-01 3.70820612e-01 1.98372141e-01
-1.37171045e-01 4.81575161e-01 4.12055820e-01 -9.30261239e-02
-6.78815782e-01 -8.16384330e-02 2.49476045e-01 -4.78784591e-02
1.94823556e-02 -4.05969232e-01 -5.37662268e-01 -3.58673483e-01
-3.00192475e-01 -3.51306014e-02 1.01455271e+00 6.26701295e-01
8.83957744e-01 -3.74217182e-01 -4.80989307e-01 7.23219752e-01
1.04916215e+00 7.33170435e-02 8.74505818e-01 3.77951384e-01
9.97391045e-01 7.28521049e-01 1.19279468e+00 6.68637037e-01
6.21256411e-01 8.30405116e-01 3.16346049e-01 2.80134439e-01
-1.80923954e-01 -6.69396520e-01 4.81210113e-01 7.57752836e-01
-2.07509309e-01 -2.90353537e-01 -6.68866873e-01 6.62566245e-01
-2.24988961e+00 -1.22101581e+00 -3.13228816e-02 1.93672490e+00
4.27600622e-01 6.90058619e-02 5.50915897e-01 1.59555510e-01
5.69147706e-01 4.61644948e-01 -6.54718041e-01 6.19880781e-02
1.86327815e-01 -1.27806813e-01 3.68975073e-01 6.41996861e-01
-1.39261413e+00 9.94744897e-01 6.06869698e+00 6.86016679e-01
-8.62500429e-01 -6.22492284e-02 3.86220247e-01 -2.07645968e-01
-1.77425265e-01 -2.99728960e-01 -6.12776577e-01 5.42707086e-01
7.27973878e-01 -4.15776223e-02 -1.42419124e-02 7.52018452e-01
4.95070636e-01 6.43851459e-02 -1.04099393e+00 9.80640709e-01
-2.56422400e-01 -1.25706935e+00 2.00226735e-02 -1.74845621e-01
5.40617466e-01 -1.21818848e-01 3.45546305e-02 1.59396157e-01
7.86301568e-02 -9.97105837e-01 1.06403744e+00 9.07581627e-01
4.23524618e-01 -9.45273578e-01 5.69072008e-01 6.60226762e-01
-1.70384121e+00 -5.64676300e-02 -7.21229911e-02 -5.00606745e-02
8.00064564e-01 1.75155178e-01 -4.26361233e-01 7.34308600e-01
6.02829874e-01 1.27661908e+00 -1.49627417e-01 9.40278649e-01
-1.99750811e-01 5.11148632e-01 2.30105687e-02 2.79949993e-01
2.97524333e-01 1.08658142e-01 7.95375764e-01 1.21280181e+00
4.17557836e-01 3.87101531e-01 3.84409547e-01 5.41724563e-01
4.13488477e-01 -1.36188135e-01 -1.71646610e-01 2.16232508e-01
1.84206963e-01 8.71276259e-01 -4.32183146e-01 -2.68380046e-01
-1.98034212e-01 1.39610445e+00 9.03189629e-02 3.72385949e-01
-9.30219591e-01 3.46627235e-02 8.52424383e-01 1.85124695e-01
4.09081042e-01 -4.34007823e-01 4.57751192e-02 -9.95409071e-01
1.32825896e-01 -4.11346972e-01 6.21689975e-01 -6.89924061e-01
-9.37750101e-01 5.52441657e-01 -1.73418701e-01 -1.57978761e+00
-8.94496441e-01 -4.67422158e-02 -5.32487035e-01 8.60812962e-01
-1.22980499e+00 -1.14240646e+00 -1.83312714e-01 4.16432738e-01
9.39461291e-01 1.56940177e-01 3.84807050e-01 2.18939319e-01
-3.80011797e-01 4.63058710e-01 -5.30018210e-01 -1.09548643e-02
5.02217412e-01 -9.51096416e-01 1.16653061e+00 8.15755606e-01
-9.61151496e-02 2.94922739e-01 8.62127542e-01 -1.10738587e+00
-1.13579750e+00 -1.57901311e+00 1.07748556e+00 -6.02104366e-01
4.60160822e-01 3.03431004e-01 -1.14116871e+00 6.93306327e-01
-3.12265992e-01 1.27978384e-01 3.96555722e-01 -5.69906235e-01
1.12195447e-01 4.14897621e-01 -8.76717091e-01 7.10303068e-01
1.43627214e+00 -1.59694389e-01 -7.27334738e-01 -1.33522853e-01
8.06739271e-01 -6.36532068e-01 -8.35536242e-01 5.54424465e-01
8.36311162e-01 -7.52532661e-01 1.24617243e+00 -6.47718668e-01
5.76952755e-01 -3.71378452e-01 -1.28321409e-01 -1.09381580e+00
-7.81396806e-01 -9.29321647e-01 -5.54702818e-01 6.76765084e-01
7.50218034e-02 7.01017976e-02 1.18406141e+00 5.44733822e-01
-6.43772483e-02 -8.54598999e-01 -9.18435752e-01 -8.07228267e-01
-1.16492249e-01 -6.17273808e-01 5.28901517e-01 5.58824062e-01
-9.75705683e-02 8.60560406e-03 -1.15528286e+00 1.89175949e-01
4.90084827e-01 -1.51151624e-02 9.24060285e-01 -7.46040106e-01
-5.59181511e-01 -3.12181979e-01 -7.46676326e-01 -1.68916202e+00
2.20066696e-01 -5.20403087e-01 4.91747975e-01 -1.44470704e+00
6.28342619e-04 1.71866834e-01 -1.23003855e-01 8.41871276e-02
-6.97720766e-01 1.18864924e-01 4.56778377e-01 4.19324994e-01
-8.33259523e-01 9.45217371e-01 1.38540316e+00 2.68967208e-02
-5.12246072e-01 1.79032862e-01 -2.15637442e-02 9.20452595e-01
5.18877923e-01 -2.56400555e-01 -6.13639057e-01 -2.33615175e-01
-1.53594926e-01 4.51132059e-01 6.85804069e-01 -1.43151581e+00
2.96953976e-01 -3.04900289e-01 5.41625917e-01 -1.05358207e+00
5.22962332e-01 -5.85941494e-01 4.94532436e-01 9.12049711e-01
-4.78851348e-01 3.39416385e-01 7.36401826e-02 1.14839399e+00
-1.60030916e-01 4.82381821e-01 6.65826738e-01 4.89336886e-02
-1.37512910e+00 6.10876322e-01 -5.11637449e-01 6.60848320e-02
9.63450193e-01 -3.48729104e-01 2.62923330e-01 -5.36426961e-01
-1.03012347e+00 5.70226490e-01 3.95088196e-01 6.59824610e-01
9.06461656e-01 -1.64317048e+00 -4.87881839e-01 -2.03433391e-02
5.66886142e-02 9.66996774e-02 8.28372061e-01 8.04407597e-01
-5.78246832e-01 3.58855963e-01 -2.40189597e-01 -6.86336696e-01
-1.18545413e+00 7.02668786e-01 1.62527919e-01 -3.25346410e-01
-1.24198246e+00 9.29367065e-01 2.86128610e-01 -1.23218231e-01
1.70052484e-01 -4.53676820e-01 -2.85878360e-01 -4.68892634e-01
6.96293652e-01 7.24735558e-01 -4.47543919e-01 -1.25157511e+00
-4.30396080e-01 7.85769820e-01 3.33852321e-01 -2.85625160e-01
9.43077981e-01 -5.82257986e-01 4.97590035e-01 3.88790280e-01
1.08517718e+00 -3.17106485e-01 -1.97436082e+00 -1.63349584e-01
2.08832249e-01 -5.75213850e-01 -3.67254257e-01 -3.93584132e-01
-1.01760578e+00 6.99721694e-01 3.12471986e-01 -6.12664282e-01
1.18742085e+00 -1.87757909e-01 1.55157650e+00 -4.14627492e-02
4.54827577e-01 -1.06954837e+00 2.98800707e-01 6.01772785e-01
8.51565719e-01 -9.21385169e-01 7.99836740e-02 -4.59502220e-01
-1.04648602e+00 6.22013688e-01 6.31381750e-01 -2.19691470e-01
5.65602064e-01 -3.63205642e-01 -1.65798128e-01 1.62413061e-01
-8.45968962e-01 -1.47345528e-01 8.38261247e-01 5.70970058e-01
3.62481833e-01 -5.19860759e-02 -2.51425833e-01 7.88183987e-01
-2.90050477e-01 2.33219638e-01 3.38106193e-02 9.49538291e-01
-4.98606026e-01 -8.48840177e-01 -2.78100669e-01 -6.73039705e-02
-3.29274595e-01 3.06980520e-01 -9.95773822e-02 7.94815898e-01
9.05600041e-02 7.03105927e-01 6.18576147e-02 -8.09762895e-01
4.36567545e-01 -1.87450945e-01 2.61978060e-01 -2.41555840e-01
-4.70414996e-01 2.24160016e-01 8.59030038e-02 -1.24096215e+00
-5.06821752e-01 -7.66099095e-01 -1.68385029e+00 -3.11130881e-01
2.86152303e-01 -9.18096080e-02 -6.09026924e-02 8.12844098e-01
4.20450509e-01 6.20437741e-01 2.83837080e-01 -1.28280783e+00
-4.02362525e-01 -8.15569282e-01 -3.57687533e-01 8.18552077e-01
5.83679378e-01 -6.68386400e-01 2.75603011e-02 3.00801784e-01] | [7.281731128692627, -0.25001752376556396] |
3235edc5-e75b-4601-a31e-0452cadc6503 | adapting-a-language-model-while-preserving | 2301.08986 | null | https://arxiv.org/abs/2301.08986v1 | https://arxiv.org/pdf/2301.08986v1.pdf | Adapting a Language Model While Preserving its General Knowledge | Domain-adaptive pre-training (or DA-training for short), also known as post-training, aims to train a pre-trained general-purpose language model (LM) using an unlabeled corpus of a particular domain to adapt the LM so that end-tasks in the domain can give improved performances. However, existing DA-training methods are in some sense blind as they do not explicitly identify what knowledge in the LM should be preserved and what should be changed by the domain corpus. This paper shows that the existing methods are suboptimal and proposes a novel method to perform a more informed adaptation of the knowledge in the LM by (1) soft-masking the attention heads based on their importance to best preserve the general knowledge in the LM and (2) contrasting the representations of the general and the full (both general and domain knowledge) to learn an integrated representation with both general and domain-specific knowledge. Experimental results will demonstrate the effectiveness of the proposed approach. | ['Bing Liu', 'Lei Shu', 'Hu Xu', 'Haowei Lin', 'Yijia Shao', 'Zixuan Ke'] | 2023-01-21 | null | null | null | null | ['general-knowledge'] | ['miscellaneous'] | [ 1.22217394e-01 3.48756820e-01 -2.13511914e-01 -4.40324754e-01
-5.16241431e-01 -6.88531995e-01 7.80917943e-01 -2.23835781e-01
-6.16558492e-01 1.07351625e+00 4.65182036e-01 -3.59031767e-01
1.89547822e-01 -3.81273180e-01 -6.06476724e-01 -7.08986163e-01
5.91732085e-01 7.14481175e-01 5.30778408e-01 -2.03513294e-01
3.51359010e-01 5.21013021e-01 -1.33243966e+00 3.79512280e-01
8.99628460e-01 4.54730868e-01 7.25876510e-01 3.60020190e-01
-5.36538064e-01 8.73935819e-01 -7.77008116e-01 -1.92669943e-01
1.07857361e-01 -8.17289233e-01 -1.19878161e+00 2.74326771e-01
2.85818696e-01 -6.61082193e-02 -1.48057222e-01 1.03591347e+00
5.48354030e-01 6.00719154e-01 5.91880262e-01 -4.13714260e-01
-9.43779528e-01 7.27853537e-01 -2.60298252e-01 4.87073690e-01
1.23965114e-01 -4.81358245e-02 5.30285358e-01 -1.05570769e+00
8.45872879e-01 1.21619010e+00 1.60245836e-01 9.28890646e-01
-9.53062177e-01 -4.89940137e-01 5.85271835e-01 3.62044513e-01
-1.45339620e+00 -7.53312707e-01 9.74283576e-01 -3.62892270e-01
1.02593863e+00 -1.53484613e-01 -2.72428095e-02 8.28787029e-01
-1.94652393e-01 7.01010168e-01 1.07601881e+00 -9.53009248e-01
2.26300776e-01 7.80669212e-01 4.69091646e-02 3.55839789e-01
-3.64859514e-02 6.27872674e-03 -5.20877540e-01 2.31743790e-02
3.85881484e-01 -6.02852285e-01 -3.58117342e-01 -6.07061505e-01
-9.51812446e-01 5.42267859e-01 1.44827813e-01 9.11196470e-01
-5.93426526e-01 -4.99311715e-01 4.89752740e-01 4.13296998e-01
3.67517561e-01 6.79436147e-01 -7.95982778e-01 2.12751746e-01
-1.01830995e+00 -1.26953542e-01 6.43942893e-01 9.44891810e-01
9.97325361e-01 3.76793414e-01 -3.15570712e-01 1.04493332e+00
2.29995772e-01 3.32585156e-01 1.05133748e+00 -5.45482099e-01
5.36908507e-01 6.47954702e-01 2.26071551e-01 -4.40989137e-01
-1.85809895e-01 -6.08892202e-01 -4.70748752e-01 9.15013999e-02
3.15979421e-01 -3.77994090e-01 -9.64124203e-01 2.02809501e+00
2.26676330e-01 2.04415947e-01 3.53482157e-01 6.49589181e-01
6.97602212e-01 8.17064404e-01 2.87064940e-01 -2.65190214e-01
8.29767048e-01 -1.17521024e+00 -8.03101897e-01 -7.80150890e-01
6.93235576e-01 -7.55092323e-01 1.18529177e+00 1.21811092e-01
-1.21759927e+00 -1.10663152e+00 -1.08440292e+00 -3.93006690e-02
-5.26264906e-01 3.08383346e-01 -1.40273809e-01 3.50860715e-01
-1.21132410e+00 3.98820043e-01 -4.91326332e-01 -5.90723753e-01
-3.98297645e-02 5.60095549e-01 -2.02744782e-01 -1.96626216e-01
-1.39614129e+00 1.46958888e+00 8.91850710e-01 -1.76485598e-01
-8.48781645e-01 -3.92630577e-01 -8.52063417e-01 2.86996067e-02
4.43771034e-01 -6.53968036e-01 1.38884211e+00 -1.81589007e+00
-1.87557685e+00 9.04368460e-01 -3.46479952e-01 -3.51747811e-01
1.44584969e-01 -1.76642150e-01 -5.52893698e-01 5.64276613e-02
-2.78627109e-02 5.45714319e-01 9.13099647e-01 -1.48166144e+00
-8.69267881e-01 -3.24727207e-01 3.89329270e-02 6.34756684e-01
-6.28169954e-01 -3.24421003e-02 -5.82591712e-01 -6.80502832e-01
-5.88150360e-02 -6.63476706e-01 -1.52140915e-01 -6.29063606e-01
-8.60664845e-02 -1.14537738e-01 9.74768281e-01 -9.64736283e-01
1.62537253e+00 -2.15210581e+00 2.78627485e-01 4.12423350e-03
-3.47013175e-01 9.67799187e-01 -4.69756752e-01 4.09575462e-01
-1.41328201e-01 -1.50712594e-01 -1.95380285e-01 -4.06169534e-01
-3.01535606e-01 4.58115697e-01 -2.55090117e-01 3.40060562e-01
2.13597685e-01 6.37042344e-01 -9.86832678e-01 -4.23019499e-01
3.39607239e-01 2.92286277e-01 -4.64993894e-01 4.21594918e-01
-3.49305153e-01 1.03864121e+00 -5.27808070e-01 8.16402733e-02
5.98536968e-01 7.22440109e-02 4.28027838e-01 -2.57414132e-02
-2.24834561e-01 5.20778596e-01 -1.02635229e+00 1.75585282e+00
-5.58726966e-01 6.53162122e-01 1.42237157e-01 -1.26525629e+00
1.12524319e+00 4.74946946e-01 2.35723004e-01 -7.66421735e-01
3.76299173e-02 9.76018235e-02 1.41932666e-01 -5.30425727e-01
5.33304393e-01 -2.79323786e-01 1.11871257e-01 3.13787609e-01
2.69142270e-01 1.22593664e-01 6.99965954e-02 -1.03374515e-02
7.00497806e-01 3.79232585e-01 7.39012718e-01 -3.74000013e-01
1.30017006e+00 8.16042870e-02 5.09961009e-01 6.39237702e-01
-1.75924316e-01 3.09392899e-01 -1.53480813e-01 -2.38224506e-01
-9.95662749e-01 -6.30978525e-01 5.41314147e-02 1.47371292e+00
-4.00596634e-02 2.11181834e-01 -7.17790246e-01 -8.97946060e-01
-3.38645160e-01 1.43992662e+00 -3.94631088e-01 -4.91411775e-01
-9.19086337e-01 -2.67178416e-01 2.87740231e-01 4.70158607e-01
7.07425356e-01 -1.43024623e+00 -2.33278841e-01 3.74189079e-01
-1.74781270e-02 -1.09396780e+00 -5.21827996e-01 3.02864730e-01
-8.62110198e-01 -5.77209651e-01 -8.65148485e-01 -1.23987031e+00
1.16657388e+00 9.80851501e-02 1.08493221e+00 -3.48495245e-02
7.21870661e-01 3.74085665e-01 -3.34731162e-01 -1.57744378e-01
-9.12779748e-01 2.57759243e-01 -4.14308421e-02 2.21706703e-01
5.63617587e-01 -3.50638807e-01 -4.48654592e-03 1.89642578e-01
-9.09948289e-01 -2.02119082e-01 8.29688549e-01 8.08846831e-01
5.63808620e-01 1.15102455e-01 9.63586450e-01 -1.31755471e+00
6.52950406e-01 -4.42273527e-01 -4.33226347e-01 4.57117379e-01
-7.59967744e-01 3.36879283e-01 8.86479497e-01 -7.43157864e-01
-1.70886922e+00 2.61365563e-01 -2.26947159e-01 -2.92538077e-01
-3.16697657e-01 6.66234672e-01 -6.03906512e-01 4.93404805e-04
7.43148029e-01 6.13206327e-01 -4.52638596e-01 -7.61448205e-01
4.10829931e-01 7.27220297e-01 7.82788157e-01 -8.11682642e-01
6.71092391e-01 1.46262392e-01 -4.65635747e-01 -7.22016037e-01
-9.28822756e-01 -7.38772511e-01 -1.34689808e+00 1.31709173e-01
5.08082211e-01 -7.60952532e-01 3.64119530e-01 2.27410823e-01
-1.12496960e+00 -5.16184211e-01 -4.61911708e-01 4.21586722e-01
-3.92608285e-01 5.61744332e-01 -1.83694229e-01 -7.37642169e-01
-1.67614803e-01 -8.23370397e-01 4.75896806e-01 3.15758884e-01
-1.37544498e-01 -1.40702534e+00 3.48467946e-01 5.10885306e-02
4.05836910e-01 -4.47603405e-01 1.19297302e+00 -1.21267581e+00
-1.27590150e-01 -3.93656939e-02 4.70186844e-02 8.70608985e-01
3.18159550e-01 -4.13296372e-01 -1.07654071e+00 -3.54213983e-01
3.02601177e-02 1.29250274e-03 7.00560629e-01 3.05165946e-01
7.95259714e-01 -3.82009923e-01 -3.28384936e-01 3.06758910e-01
1.32813072e+00 4.93738830e-01 7.16845810e-01 6.05344892e-01
3.49424213e-01 4.96839374e-01 7.40512192e-01 1.96328729e-01
2.16183528e-01 6.97095275e-01 3.66349593e-02 -1.90322638e-01
-5.68283975e-01 -3.11326683e-01 7.24291146e-01 9.87770319e-01
2.19471470e-01 -3.44887137e-01 -7.82741427e-01 9.89826024e-01
-1.76737142e+00 -7.41575897e-01 4.23537344e-01 2.39057064e+00
1.14828181e+00 1.42599940e-01 -9.88422148e-03 -2.27460802e-01
1.02903247e+00 -4.99972664e-02 -7.16821909e-01 -7.12500215e-01
-2.72156447e-01 2.63754427e-01 3.08368921e-01 7.54630327e-01
-9.81236398e-01 1.42612326e+00 6.36281443e+00 5.87948382e-01
-1.28257215e+00 2.83428818e-01 9.90065560e-02 3.05514187e-01
-1.59387991e-01 1.56065747e-01 -1.03931642e+00 2.80707926e-01
1.12261307e+00 -3.57713789e-01 2.01967061e-01 9.35028374e-01
1.43879950e-01 8.39008763e-02 -9.92857933e-01 3.21592182e-01
2.71329165e-01 -9.13595676e-01 5.05016565e-01 -2.02041671e-01
1.01605523e+00 -1.94233850e-01 -2.20042057e-02 7.53454387e-01
2.95812994e-01 -5.29614627e-01 6.48387253e-01 5.76249123e-01
5.79273105e-01 -6.41098619e-01 8.54167819e-01 7.68095672e-01
-8.08272839e-01 3.13152149e-02 -5.73606491e-01 -5.55901043e-03
3.60635072e-02 1.84026942e-01 -1.13757670e+00 5.28020740e-01
1.85989603e-01 5.18571258e-01 -5.89832485e-01 9.25294757e-01
-5.85613906e-01 7.14356363e-01 8.53780285e-02 2.05424696e-01
4.02387917e-01 5.74621707e-02 6.82842612e-01 1.45112157e+00
3.01898062e-01 -3.88395414e-02 2.32137978e-01 6.87310755e-01
-9.00277719e-02 2.82752991e-01 -5.36443114e-01 -1.31292641e-01
5.49954057e-01 7.60111094e-01 -2.70120770e-01 -5.50128996e-01
-7.19055951e-01 1.09434128e+00 3.51811588e-01 5.85332334e-01
-4.22908872e-01 -1.57822639e-01 4.26328689e-01 -1.51398871e-02
6.80682063e-01 -1.01355031e-01 2.08218880e-02 -9.74832356e-01
-3.06305379e-01 -8.15215588e-01 6.46488428e-01 -7.30944932e-01
-1.17236912e+00 8.40559244e-01 7.27874110e-04 -1.07965744e+00
-5.75019181e-01 -4.72256809e-01 -2.74534374e-01 1.17901409e+00
-1.87533391e+00 -1.18562961e+00 2.49186009e-01 8.35204303e-01
8.87142360e-01 -4.38132733e-01 9.13947999e-01 2.91816026e-01
-4.21921790e-01 7.10949779e-01 3.03900898e-01 2.93810293e-02
9.09697056e-01 -1.13638806e+00 9.57424380e-03 1.04901958e+00
5.20851202e-02 7.23628223e-01 7.25042701e-01 -7.16975391e-01
-7.54616797e-01 -1.10960841e+00 1.32659125e+00 -3.77361268e-01
2.87061930e-01 4.65202928e-02 -1.27813137e+00 8.78470302e-01
3.90702665e-01 -3.89666289e-01 4.83214080e-01 -2.14312170e-02
3.11602885e-03 -3.52109671e-02 -1.13765907e+00 5.02100945e-01
6.55709147e-01 -4.57229763e-01 -1.23827231e+00 1.29967868e-01
6.34670079e-01 -2.96294659e-01 -4.54793543e-01 3.67580205e-01
-2.40558498e-02 -6.05707586e-01 8.64259303e-01 -8.94041419e-01
-1.56126603e-01 -5.02429068e-01 -3.94682921e-02 -1.44153118e+00
-6.35754049e-01 -3.43144536e-01 -1.08767204e-01 1.53436661e+00
3.25333595e-01 -5.45776367e-01 4.94618684e-01 3.58368009e-01
-4.67240006e-01 -1.58550680e-01 -8.12777877e-01 -9.02167857e-01
3.33490670e-01 -5.75878024e-02 5.24699986e-01 1.07054436e+00
-1.27193242e-01 7.90104508e-01 -3.97850752e-01 3.64622772e-01
-8.25179219e-02 -6.38213232e-02 6.55012548e-01 -1.08348763e+00
-4.64943163e-02 -3.96114945e-01 -2.12191558e-03 -1.32703662e+00
6.37121022e-01 -9.86141026e-01 1.54093668e-01 -1.47956300e+00
4.65537794e-02 -2.23583713e-01 -6.67345047e-01 5.66692352e-01
-2.61184663e-01 -3.53063673e-01 1.08548231e-01 3.43416125e-01
-6.84251547e-01 4.58481699e-01 1.33793771e+00 1.61371268e-02
-5.63648403e-01 9.51189324e-02 -8.99016857e-01 7.30851233e-01
6.17164195e-01 -4.51892227e-01 -7.37195015e-01 -7.17229128e-01
-1.68649778e-01 -2.33471826e-01 -1.08068876e-01 -1.06150746e+00
4.54337448e-01 -1.77240551e-01 2.80016243e-01 -4.74906832e-01
9.59582850e-02 -9.41278815e-01 -2.31958643e-01 3.66736352e-01
-6.33800328e-01 -2.37053961e-01 6.43283248e-01 2.86242455e-01
-3.46780837e-01 -7.64655828e-01 1.16304231e+00 -3.18334758e-01
-1.34613073e+00 -9.32463631e-02 -4.60922003e-01 3.36269885e-02
7.51640737e-01 -2.08892435e-01 -8.56138095e-02 -5.32890260e-01
-8.95337284e-01 7.94206113e-02 4.38866109e-01 2.62670845e-01
2.72091597e-01 -1.06407106e+00 -6.93600059e-01 2.03501359e-01
5.88359348e-02 -1.87147379e-01 1.11040555e-01 4.09951121e-01
-4.70039323e-02 7.33014286e-01 -2.96371967e-01 -1.01600766e-01
-9.44470584e-01 9.08813179e-01 4.77950424e-01 -7.16125309e-01
-3.80805016e-01 8.22239995e-01 5.08710742e-01 -6.69559419e-01
3.43840778e-01 8.53872374e-02 -6.66564286e-01 -1.11655273e-01
6.02300406e-01 -1.63879595e-04 1.78983673e-01 -8.24411511e-01
-4.24378783e-01 4.78203297e-01 -1.41538426e-01 -1.96103483e-01
1.16208911e+00 -7.02926338e-01 8.04091021e-02 4.10328180e-01
8.16189349e-01 2.33078629e-01 -1.20819175e+00 -9.58176613e-01
3.09734732e-01 -1.59768239e-01 1.89360604e-01 -1.23619854e+00
-8.82836938e-01 1.06903064e+00 3.04006100e-01 -2.85958111e-01
1.44763470e+00 1.77867338e-02 5.49499989e-01 5.85316479e-01
1.89149782e-01 -1.37346470e+00 -3.36366147e-02 7.53084540e-01
9.29902554e-01 -8.10350657e-01 2.78421398e-02 2.00395752e-02
-9.60246861e-01 1.16340721e+00 9.61201310e-01 -5.03276847e-02
5.17317414e-01 -1.14665799e-01 2.32640952e-01 2.39606380e-01
-7.22295523e-01 -5.32954574e-01 6.64380074e-01 8.43316913e-01
3.40461820e-01 -4.59133059e-01 -3.36664170e-01 8.79604399e-01
1.66591167e-01 6.07398525e-02 1.58352837e-01 9.26165879e-01
-6.64760470e-01 -1.39749634e+00 -3.29198301e-01 -7.01437965e-02
-2.90498644e-01 -6.74018040e-02 -7.54936934e-01 7.93293059e-01
4.26944137e-01 8.43367457e-01 -3.08592290e-01 -1.89385951e-01
4.87354547e-01 5.94980359e-01 2.45843992e-01 -1.09785426e+00
-6.27308607e-01 1.41963392e-01 8.87809992e-02 -6.93918616e-02
-4.76290166e-01 -6.71755433e-01 -1.30205059e+00 1.05748147e-01
-2.26449251e-01 2.60891318e-01 5.65402210e-01 1.27320004e+00
3.78063947e-01 4.78668749e-01 4.10628438e-01 -4.97194260e-01
-6.64747715e-01 -1.18474293e+00 -4.28490937e-01 4.36299741e-01
3.08911085e-01 -6.31373703e-01 -3.45069975e-01 3.98446828e-01] | [10.471186637878418, 8.116803169250488] |
073bdf6e-7dcd-4aab-ba4a-afde7fa571e7 | regularizing-class-wise-predictions-via-self | 2003.13964 | null | https://arxiv.org/abs/2003.13964v2 | https://arxiv.org/pdf/2003.13964v2.pdf | Regularizing Class-wise Predictions via Self-knowledge Distillation | Deep neural networks with millions of parameters may suffer from poor generalization due to overfitting. To mitigate the issue, we propose a new regularization method that penalizes the predictive distribution between similar samples. In particular, we distill the predictive distribution between different samples of the same label during training. This results in regularizing the dark knowledge (i.e., the knowledge on wrong predictions) of a single network (i.e., a self-knowledge distillation) by forcing it to produce more meaningful and consistent predictions in a class-wise manner. Consequently, it mitigates overconfident predictions and reduces intra-class variations. Our experimental results on various image classification tasks demonstrate that the simple yet powerful method can significantly improve not only the generalization ability but also the calibration performance of modern convolutional neural networks. | ['Jinwoo Shin', 'Kimin Lee', 'Jongjin Park', 'Sukmin Yun'] | 2020-03-31 | regularizing-class-wise-predictions-via-self-1 | http://openaccess.thecvf.com/content_CVPR_2020/html/Yun_Regularizing_Class-Wise_Predictions_via_Self-Knowledge_Distillation_CVPR_2020_paper.html | http://openaccess.thecvf.com/content_CVPR_2020/papers/Yun_Regularizing_Class-Wise_Predictions_via_Self-Knowledge_Distillation_CVPR_2020_paper.pdf | cvpr-2020-6 | ['self-knowledge-distillation'] | ['computer-vision'] | [ 9.61300954e-02 6.94347918e-02 -1.46950498e-01 -8.90826344e-01
-3.27213883e-01 -6.49164081e-01 3.32880855e-01 -1.28820926e-01
-4.89701331e-01 8.51849735e-01 -2.59033620e-01 -3.04039270e-01
6.51122332e-02 -6.61530077e-01 -1.07040441e+00 -8.68870497e-01
4.77803111e-01 6.56705946e-02 3.21921229e-01 1.59027606e-01
3.01214717e-02 3.01908016e-01 -1.18543220e+00 1.99302748e-01
1.15447879e+00 1.31922126e+00 -7.86759183e-02 -3.14059071e-02
1.32715359e-01 8.07422519e-01 -6.22637331e-01 -8.45838249e-01
3.16058397e-01 -2.22625867e-01 -5.30001223e-01 -7.92303756e-02
8.28130960e-01 -2.46407539e-01 -9.13589522e-02 1.35056329e+00
1.29883975e-01 5.29207662e-02 5.54980755e-01 -1.21331334e+00
-7.43421793e-01 7.76482880e-01 -6.37188911e-01 -2.76558497e-03
-5.07408321e-01 2.19668150e-01 8.52185428e-01 -7.94185519e-01
1.44913673e-01 1.09900045e+00 1.09357178e+00 5.74534178e-01
-1.60954356e+00 -1.23819840e+00 2.35958844e-01 -1.34178936e-01
-1.46088421e+00 -4.46444988e-01 6.13485336e-01 -4.60054636e-01
3.76083434e-01 1.34375477e-02 3.55331093e-01 1.20791733e+00
2.77602166e-01 5.16822696e-01 8.77779901e-01 -7.00891167e-02
2.21203893e-01 4.16383803e-01 2.44728372e-01 5.75177014e-01
7.25939333e-01 1.02016926e-01 -3.34331721e-01 -1.28168821e-01
7.15335965e-01 7.67683536e-02 -3.18840474e-01 -4.46707845e-01
-8.85660470e-01 7.58682191e-01 5.40941358e-01 9.40907672e-02
-1.54204339e-01 9.15089175e-02 2.86908299e-01 2.23572329e-01
4.71724451e-01 4.86844957e-01 -7.58118927e-01 2.74943709e-01
-7.79334188e-01 1.03573585e-02 8.00062597e-01 7.35430062e-01
1.15500998e+00 1.18257642e-01 -2.51519650e-01 1.03071702e+00
1.52823865e-01 4.26466227e-01 5.33588111e-01 -8.17363858e-01
3.72814775e-01 5.53077102e-01 -1.15911603e-01 -1.19354284e+00
-3.10728133e-01 -1.05045557e+00 -1.10654831e+00 1.10003330e-01
4.86632794e-01 -4.20373082e-01 -9.65220571e-01 2.13283873e+00
4.15540077e-02 3.71897757e-01 6.19285814e-02 6.85259163e-01
7.43908644e-01 3.13500881e-01 4.69612956e-01 7.62041435e-02
7.63128698e-01 -9.39594567e-01 -3.46128047e-01 -5.68922281e-01
5.10035932e-01 -5.25240660e-01 9.44056094e-01 2.84710646e-01
-7.65432537e-01 -6.84884846e-01 -1.13434601e+00 2.58125454e-01
-9.16217789e-02 2.43388951e-01 6.46982014e-01 5.42341352e-01
-7.15285182e-01 8.85475516e-01 -6.62539721e-01 1.77913353e-01
8.42318535e-01 4.07862544e-01 -5.37402928e-01 -4.21066321e-02
-1.00375962e+00 7.03080535e-01 9.15876508e-01 -6.91295713e-02
-4.99879241e-01 -1.01035106e+00 -5.71859062e-01 3.16511303e-01
3.65741879e-01 -4.99229491e-01 1.14638782e+00 -1.52549541e+00
-1.30920875e+00 7.08608150e-01 5.07048629e-02 -5.16745150e-01
5.77140510e-01 -3.09576750e-01 -2.60326654e-01 -3.99825484e-01
-5.95912002e-02 8.40550661e-01 9.39757586e-01 -1.34144592e+00
-5.05704761e-01 -2.71055818e-01 -3.09448838e-01 -1.39310762e-01
-6.84268236e-01 -5.77428102e-01 -4.15798664e-01 -6.51333511e-01
3.80333215e-01 -1.02084649e+00 -9.25277472e-02 -4.21041250e-02
-5.42531908e-01 -1.39762059e-01 4.93684679e-01 -3.68311077e-01
1.01833105e+00 -2.43280578e+00 -3.40140015e-01 4.34911788e-01
3.61761838e-01 4.74234045e-01 -2.33546227e-01 -2.78382689e-01
-2.81244427e-01 3.28396440e-01 -2.09591046e-01 -3.57845575e-01
-2.76742607e-01 5.60475290e-01 -4.56712961e-01 3.10553491e-01
4.75661129e-01 8.10833633e-01 -8.48336756e-01 -1.95043251e-01
-2.08923519e-01 4.46879834e-01 -6.04508638e-01 1.94853231e-01
-1.41237378e-01 5.26148796e-01 -3.22032332e-01 1.50021136e-01
1.01306772e+00 -6.58441007e-01 2.59596407e-01 -2.18382388e-01
2.94305295e-01 2.56069034e-01 -9.73657191e-01 1.25681055e+00
-3.53942484e-01 5.37613034e-01 -4.75525260e-01 -1.07886899e+00
1.21180129e+00 -6.05143271e-02 1.63613498e-01 -5.44060647e-01
1.18062086e-01 1.72165990e-01 1.09079964e-01 -1.70300126e-01
2.91504741e-01 -3.26800704e-01 2.14926004e-01 2.18084469e-01
2.56454408e-01 4.38375890e-01 -2.54192173e-01 -3.65142077e-02
6.93982065e-01 -6.01512566e-02 6.05020747e-02 -3.37468743e-01
2.46289343e-01 -3.32777143e-01 1.11243904e+00 9.64227259e-01
-1.12462528e-02 4.53261852e-01 5.67382753e-01 -4.40041900e-01
-1.09357858e+00 -1.15158582e+00 -2.64003664e-01 1.00958347e+00
5.90655161e-03 -1.12842456e-01 -6.52298927e-01 -8.67713451e-01
3.77312809e-01 7.47576892e-01 -6.36126935e-01 -7.35511482e-01
-3.72907072e-01 -9.01832283e-01 6.26210868e-01 7.79154420e-01
7.02734888e-01 -5.67753136e-01 -5.68479151e-02 -2.72647920e-03
6.50045797e-02 -1.03368485e+00 -1.45083845e-01 4.95484084e-01
-1.13681555e+00 -9.82239902e-01 -4.29384291e-01 -7.76983202e-01
9.63694572e-01 2.19314292e-01 1.40839410e+00 1.81354180e-01
3.77304494e-01 -3.43007982e-01 -4.63688225e-02 -4.57139313e-01
-4.73917812e-01 9.85939652e-02 2.05698103e-01 9.99364182e-02
5.97424805e-01 -5.22884488e-01 -4.85117108e-01 5.81637740e-01
-7.48249173e-01 -7.26211220e-02 6.15118742e-01 1.15937126e+00
6.77868187e-01 1.92939043e-01 7.80090868e-01 -1.23978603e+00
4.45320129e-01 -6.21156394e-01 -7.20301628e-01 3.68312657e-01
-1.00733173e+00 3.12597901e-01 9.45963025e-01 -8.05296063e-01
-1.09816217e+00 8.35008472e-02 6.19806536e-02 -5.94567358e-01
1.87517013e-02 2.70208061e-01 7.80230239e-02 -3.39265555e-01
8.25386763e-01 1.02502033e-01 -5.43151833e-02 -4.61457461e-01
1.27536267e-01 4.31657225e-01 6.51513934e-01 -5.25540113e-01
8.41725111e-01 1.72325104e-01 -7.10173175e-02 -2.00572550e-01
-1.37633348e+00 -1.23315066e-01 -5.03990173e-01 7.13438913e-02
4.83031005e-01 -1.13355732e+00 -6.81843460e-01 5.96494257e-01
-9.75094318e-01 -4.14622515e-01 -2.06111863e-01 5.94825089e-01
-1.09964289e-01 5.97218722e-02 -3.75777900e-01 -4.96285796e-01
-2.07290202e-01 -9.02430832e-01 4.39025223e-01 6.00579500e-01
-1.62507564e-01 -1.03172541e+00 -1.78019971e-01 6.34359419e-02
3.73331010e-01 3.02906185e-02 8.37783635e-01 -9.83824372e-01
-4.04460162e-01 -2.59974360e-01 -4.78668392e-01 9.40070152e-01
5.34095466e-02 6.83901906e-02 -1.24235535e+00 -2.99405426e-01
1.52081512e-02 -4.24671590e-01 1.23515272e+00 2.34835550e-01
1.48138356e+00 -4.64234322e-01 -2.83277243e-01 7.91387022e-01
1.28187954e+00 -2.46051289e-02 5.81505120e-01 2.80708075e-01
7.13321149e-01 3.15634340e-01 2.76542127e-01 3.42607021e-01
1.23611882e-01 2.89961249e-01 3.16097945e-01 -7.61406273e-02
1.84502229e-02 -4.36187923e-01 -7.32065411e-03 4.84673291e-01
9.85511541e-02 -1.74319252e-01 -8.18475604e-01 1.83130637e-01
-1.80691421e+00 -7.52586544e-01 8.95645469e-02 2.31321239e+00
1.19881535e+00 2.21768171e-01 -3.42831016e-01 -1.16397604e-01
7.29824543e-01 -1.51232611e-02 -8.91117573e-01 -3.54250744e-02
-2.77102113e-01 5.30378185e-02 6.57179236e-01 1.67754188e-01
-1.03493273e+00 9.32344198e-01 6.83894920e+00 8.44838798e-01
-1.26305532e+00 4.68508638e-02 1.11135077e+00 7.75078461e-02
-2.35983968e-01 -1.71829641e-01 -9.74119604e-01 6.33613944e-01
8.08690965e-01 7.47355223e-02 2.40260035e-01 1.11581528e+00
-1.82938844e-01 2.31159646e-02 -1.11626709e+00 9.03659701e-01
-9.15484279e-02 -1.38967395e+00 -2.47138832e-02 -7.01899379e-02
1.02938747e+00 1.77328080e-01 3.24749172e-01 3.29415679e-01
4.67694074e-01 -1.07637107e+00 7.45774925e-01 6.12023592e-01
6.20991170e-01 -7.64159501e-01 9.53137100e-01 4.56720531e-01
-5.90069950e-01 -2.01850399e-01 -7.68510222e-01 4.33832780e-02
-4.57737654e-01 1.08515847e+00 -8.74338925e-01 9.84054878e-02
7.26605952e-01 8.44703376e-01 -6.48234963e-01 1.07878339e+00
-4.13792402e-01 8.51244926e-01 -1.77537069e-01 1.00241542e-01
7.83640742e-02 -2.64540941e-01 -3.66461165e-02 1.00604045e+00
1.73072770e-01 -1.14804313e-01 9.83030722e-02 1.19280267e+00
-4.87173676e-01 -2.24470183e-01 -3.46223682e-01 1.36271924e-01
6.55684710e-01 1.11916745e+00 -3.95534426e-01 -2.56376535e-01
-3.19888592e-01 7.19339430e-01 8.87184262e-01 5.11704624e-01
-8.34038317e-01 -6.96417093e-02 6.23452842e-01 -9.44729671e-02
2.35189363e-01 1.44753205e-02 -7.12668598e-01 -1.02464068e+00
2.16407731e-01 -5.87330997e-01 3.14531624e-01 -5.17664552e-01
-1.67288578e+00 5.62420726e-01 -3.93141598e-01 -1.17279899e+00
9.96112227e-02 -6.46096706e-01 -6.97811007e-01 1.02552903e+00
-1.70566666e+00 -5.85400820e-01 -3.19028944e-01 4.01227266e-01
-7.55089670e-02 -2.23327518e-01 6.98903441e-01 2.84554124e-01
-7.98173964e-01 1.09453213e+00 3.40894461e-01 3.27256590e-01
1.06155992e+00 -9.99070525e-01 2.65434772e-01 6.19807720e-01
-7.42876530e-02 8.25882316e-01 4.49202746e-01 -4.92451936e-01
-7.84233570e-01 -1.33310294e+00 7.24766254e-01 -2.21119702e-01
7.20722854e-01 4.51327488e-02 -1.30740583e+00 7.07155764e-01
-3.80406082e-01 2.11041942e-01 1.00083733e+00 4.00214583e-01
-8.95151436e-01 -5.47969818e-01 -1.18257809e+00 4.10425127e-01
6.77319825e-01 -3.99675131e-01 -3.93035054e-01 3.41506869e-01
5.77817321e-01 -3.41019303e-01 -8.69476795e-01 5.14340162e-01
6.52225196e-01 -1.11956489e+00 9.30637479e-01 -8.14124942e-01
4.14123535e-01 -3.09896003e-02 -9.95196402e-02 -1.35994530e+00
-5.28446019e-01 -3.39459091e-01 -5.32124750e-02 1.27889311e+00
5.94887435e-01 -8.11915517e-01 8.98627281e-01 8.88617158e-01
-6.12332001e-02 -7.75095284e-01 -7.45403409e-01 -9.76934671e-01
4.02812392e-01 -2.26480201e-01 6.33969307e-01 1.18166983e+00
-3.58866662e-01 2.39333436e-01 -3.47790122e-01 3.38415623e-01
6.58142149e-01 -9.89285558e-02 5.66644132e-01 -1.66994417e+00
-3.72373164e-01 -3.78269255e-01 -4.33332592e-01 -9.83537257e-01
3.95357192e-01 -8.45436096e-01 1.84545830e-01 -7.00763524e-01
4.43629563e-01 -8.90353501e-01 -5.69447219e-01 7.53841877e-01
-4.91346031e-01 4.29851443e-01 3.52845006e-02 3.88731182e-01
-5.18716037e-01 3.57640147e-01 1.21912909e+00 6.87701851e-02
-9.94957015e-02 6.69210032e-02 -9.64756489e-01 9.25550222e-01
1.09582961e+00 -8.61576736e-01 -3.73189867e-01 -5.80369473e-01
2.88224548e-01 -5.78587532e-01 6.06150210e-01 -1.13479137e+00
6.99888989e-02 -1.88049927e-01 9.12092924e-01 -2.11789429e-01
6.56817015e-03 -8.45167935e-01 1.55953959e-01 4.37780440e-01
-5.56768298e-01 -2.43787646e-01 2.85916388e-01 7.69548714e-01
-1.51455164e-01 -3.80073398e-01 1.16473711e+00 -2.56190337e-02
-4.21954513e-01 3.38039666e-01 3.05835217e-01 1.31892756e-01
7.42899835e-01 -5.40429205e-02 -5.56721091e-01 -1.00098334e-01
-4.33429301e-01 2.64793068e-01 4.57762986e-01 2.91056693e-01
3.16730022e-01 -1.39465523e+00 -5.17426312e-01 4.91067618e-01
1.19537786e-01 1.10463656e-01 3.00486963e-02 6.63929462e-01
-9.22269225e-02 9.33868513e-02 -2.64307201e-01 -6.93070650e-01
-1.01706803e+00 2.03108281e-01 5.86158991e-01 -9.54487696e-02
-3.89533967e-01 1.24748850e+00 3.40018392e-01 -3.64725053e-01
3.76727700e-01 -1.17475182e-01 -7.58377984e-02 -2.21457824e-01
5.48422039e-01 2.29084641e-02 2.01531090e-02 -3.97799432e-01
-2.63729572e-01 4.06475335e-01 -4.72573251e-01 4.80624318e-01
1.23386252e+00 5.11875972e-02 -1.53892152e-02 4.52103913e-01
1.21549284e+00 -2.25867063e-01 -1.87274396e+00 -5.48489630e-01
-1.04670048e-01 -4.49926227e-01 1.84024036e-01 -1.04560530e+00
-1.40659261e+00 8.44285011e-01 4.61351544e-01 1.36462554e-01
9.36213076e-01 -1.42173767e-01 5.67631006e-01 7.42027581e-01
8.86619687e-02 -1.08810532e+00 9.18652713e-02 6.62542224e-01
5.32840192e-01 -1.56340814e+00 -1.34975603e-02 -2.80052036e-01
-7.27098644e-01 1.30357087e+00 7.81712294e-01 -1.84352756e-01
6.39342070e-01 9.25261527e-02 5.73787466e-02 1.51086897e-01
-5.91356158e-01 4.01952684e-01 3.79485726e-01 4.76075619e-01
4.64162588e-01 6.36257306e-02 1.22563422e-01 9.35875952e-01
-1.87729642e-01 1.72041386e-01 2.77362764e-01 5.15459478e-01
-4.37715530e-01 -7.42815793e-01 -1.09975398e-01 5.48000276e-01
-3.83901060e-01 -2.07106084e-01 -2.38954961e-01 4.92430061e-01
3.48363549e-01 8.18175912e-01 1.89088762e-01 -7.51981020e-01
2.25541368e-01 9.88053456e-02 1.17272809e-01 -4.95483965e-01
-5.44678628e-01 -2.97029823e-01 -1.27323225e-01 -4.59458500e-01
-3.17057222e-01 -2.25042805e-01 -1.16919684e+00 -5.40134132e-01
-4.46627557e-01 6.61240565e-03 3.97107601e-01 9.14206445e-01
4.37022656e-01 5.05323946e-01 7.84859657e-01 -4.40852761e-01
-1.18855309e+00 -8.54490519e-01 -5.76571345e-01 6.02189064e-01
3.06112170e-01 -7.61256635e-01 -5.23229420e-01 -1.05618596e-01] | [9.3204927444458, 3.750525951385498] |
1644bc53-de76-4fed-a7fc-f87005baa24a | galaxy-a-generative-pre-trained-model-for | 2111.14592 | null | https://arxiv.org/abs/2111.14592v8 | https://arxiv.org/pdf/2111.14592v8.pdf | GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection | Pre-trained models have proved to be powerful in enhancing task-oriented dialog systems. However, current pre-training methods mainly focus on enhancing dialog understanding and generation tasks while neglecting the exploitation of dialog policy. In this paper, we propose GALAXY, a novel pre-trained dialog model that explicitly learns dialog policy from limited labeled dialogs and large-scale unlabeled dialog corpora via semi-supervised learning. Specifically, we introduce a dialog act prediction task for policy optimization during pre-training and employ a consistency regularization term to refine the learned representation with the help of unlabeled dialogs. We also implement a gating mechanism to weigh suitable unlabeled dialog samples. Empirical results show that GALAXY substantially improves the performance of task-oriented dialog systems, and achieves new state-of-the-art results on benchmark datasets: In-Car, MultiWOZ2.0 and MultiWOZ2.1, improving their end-to-end combined scores by 2.5, 5.3 and 5.5 points, respectively. We also show that GALAXY has a stronger few-shot ability than existing models under various low-resource settings. | ['Yongbin Li', 'Jian Sun', 'Luo Si', 'Fei Huang', 'Min Yang', 'Peng Jiang', 'Dermot Liu', 'Zheng Cao', 'Yuchuan Wu', 'Yinhe Zheng', 'Yinpei Dai', 'Wanwei He'] | 2021-11-29 | null | null | null | null | ['end-to-end-dialogue-modelling'] | ['natural-language-processing'] | [-2.58202672e-01 5.43090701e-01 -3.07529241e-01 -8.46168578e-01
-8.55730653e-01 -6.76203370e-01 9.05328631e-01 -5.29343374e-02
-5.83830595e-01 9.85949039e-01 6.61722064e-01 -2.82660782e-01
2.98477262e-01 -4.83470112e-01 -9.42747444e-02 -2.91637957e-01
4.57739472e-01 1.09819055e+00 4.46196586e-01 -7.49532700e-01
1.85910150e-01 -2.01988310e-01 -9.28641915e-01 2.81065643e-01
8.85804117e-01 7.47366607e-01 4.19329196e-01 6.49827540e-01
-4.03666645e-01 1.05287600e+00 -5.47845304e-01 -5.84006310e-01
-5.67140467e-02 -2.57885903e-01 -1.11636472e+00 4.22474027e-01
7.78090023e-03 -6.89728320e-01 -2.19881758e-01 6.79676712e-01
4.89005476e-01 5.83829939e-01 3.47771257e-01 -9.32004392e-01
-5.62071502e-01 7.51845837e-01 -1.08360760e-01 -1.81331843e-01
1.69133022e-01 4.79650527e-01 1.22030139e+00 -9.62645411e-01
6.19626343e-01 1.65680993e+00 -6.18598387e-02 1.18137288e+00
-1.04044259e+00 -4.72553790e-01 3.50025237e-01 -2.52430648e-01
-6.94002032e-01 -5.86793900e-01 6.98997557e-01 -4.30678785e-01
1.01271904e+00 1.63504630e-02 -2.73790322e-02 1.27864444e+00
-4.03752103e-02 8.73140693e-01 1.07143223e+00 -3.93655121e-01
2.61383295e-01 4.01261181e-01 5.81326067e-01 8.15631509e-01
-6.99204862e-01 4.03174870e-02 -5.62204182e-01 -2.71200061e-01
4.37935382e-01 3.54024884e-03 1.05068097e-02 -7.37405941e-02
-9.22605157e-01 1.42520595e+00 2.31720567e-01 4.46384735e-02
-8.30620527e-02 -2.46143341e-01 3.06297868e-01 2.33330071e-01
7.87289917e-01 6.82148993e-01 -5.80688179e-01 -1.90517336e-01
-1.99506655e-01 2.89770216e-01 9.23557937e-01 9.91173029e-01
7.13532329e-01 -5.92952184e-02 -7.22588778e-01 1.30133533e+00
4.35263932e-01 4.54119265e-01 6.23214841e-01 -1.23064160e+00
5.70820868e-01 7.19835877e-01 3.07558358e-01 1.15480855e-01
-2.67655373e-01 2.25153327e-01 -5.23611009e-01 1.31774038e-01
5.41445434e-01 -5.84206164e-01 -6.01584017e-01 1.96402383e+00
3.46132398e-01 -8.68682265e-02 4.94265556e-01 8.46923470e-01
1.02970576e+00 6.28340900e-01 4.26439077e-01 -1.13457486e-01
1.56026900e+00 -1.59489381e+00 -9.79150414e-01 -6.54031873e-01
3.96624893e-01 -7.46821821e-01 1.59822762e+00 1.13367379e-01
-1.19138908e+00 -6.41370833e-01 -6.17992461e-01 -8.10062215e-02
-2.17584506e-01 1.85046241e-01 6.02193236e-01 3.94813716e-01
-9.49902773e-01 1.87862009e-01 -5.92519820e-01 -1.23065822e-01
4.68443893e-02 3.76171529e-01 -8.92888159e-02 3.03582907e-01
-1.41489887e+00 1.03904510e+00 2.51156151e-01 -4.14800256e-01
-1.02670228e+00 -5.09307027e-01 -7.92736828e-01 4.10914838e-01
9.39669728e-01 -4.36293364e-01 2.17363381e+00 -2.68813580e-01
-2.28992009e+00 8.01220715e-01 -2.49647081e-01 -7.04687119e-01
3.99593025e-01 -6.07432723e-01 5.36489561e-02 -1.36065558e-01
-7.78234527e-02 1.09780133e+00 4.54905868e-01 -1.07219589e+00
-5.96640170e-01 -1.35693118e-01 4.73913521e-01 4.04603869e-01
-3.83678466e-01 6.68368712e-02 -5.88916838e-01 -2.91939259e-01
-5.80456018e-01 -1.04815686e+00 -5.83879232e-01 -4.25703168e-01
-4.16993976e-01 -8.84143472e-01 9.57542181e-01 -2.35364243e-01
9.18146729e-01 -1.86956656e+00 -1.31090535e-02 -5.34538329e-01
3.60079885e-01 4.04518098e-01 -1.05114549e-01 4.50131088e-01
6.28877997e-01 -1.92866519e-01 -7.30230883e-02 -8.57189655e-01
1.43025011e-01 3.22774649e-01 -5.83644092e-01 -3.50033104e-01
3.54976594e-01 9.10171568e-01 -9.21564877e-01 -3.82404298e-01
5.89453697e-01 -6.33000880e-02 -7.67291546e-01 1.06471574e+00
-8.50760102e-01 8.16125870e-01 -5.72142363e-01 1.93240181e-01
2.94559002e-01 -4.90917921e-01 2.87739098e-01 4.28792804e-01
-3.72013934e-02 5.78334570e-01 -3.76543403e-01 1.97969186e+00
-7.49513388e-01 3.36736858e-01 1.83072239e-01 -4.80596066e-01
1.20481694e+00 4.41012710e-01 5.35053648e-02 -4.69666451e-01
3.85391027e-01 -2.68271506e-01 3.40393744e-02 -3.39997321e-01
7.33347416e-01 -9.66184661e-02 -4.06085193e-01 5.18295467e-01
5.23880243e-01 -2.58705348e-01 6.55650645e-02 5.58047414e-01
7.15629458e-01 -2.58922279e-01 2.37905428e-01 -1.36251256e-01
7.45257318e-01 -7.08572790e-02 2.28751406e-01 7.40337551e-01
-3.27305377e-01 3.84070337e-01 4.80172098e-01 -2.03388035e-02
-4.66335982e-01 -1.03455639e+00 3.04674357e-01 1.83771217e+00
1.17854171e-01 -3.53311628e-01 -7.21428514e-01 -1.12550879e+00
-5.92351630e-02 1.09141409e+00 -4.41551983e-01 -2.77291954e-01
-3.93155575e-01 -5.05534708e-01 3.01551729e-01 5.62543154e-01
7.98654675e-01 -1.34938383e+00 -3.85926574e-01 3.88700426e-01
-3.04289043e-01 -1.43330073e+00 -6.49714649e-01 2.06754029e-01
-7.36248374e-01 -8.06722820e-01 -5.37679374e-01 -6.64802253e-01
3.63463938e-01 3.75647664e-01 1.23183417e+00 -1.57317713e-01
2.59172916e-01 2.97145933e-01 -3.73335361e-01 -2.90336221e-01
-6.16021752e-01 1.75336003e-01 -1.28908351e-01 -3.01318854e-01
4.59623009e-01 -1.68118834e-01 -4.29556221e-01 7.05615759e-01
-4.58840877e-01 1.51814163e-01 4.20238107e-01 1.31348407e+00
-5.24160005e-02 -7.07990050e-01 1.00756478e+00 -1.20894396e+00
1.07764375e+00 -2.39549533e-01 -7.26940870e-01 3.01746696e-01
-6.74729466e-01 3.87183845e-01 4.43484128e-01 -5.71592748e-01
-1.94046223e+00 8.52418765e-02 -2.59120107e-01 -3.24100286e-01
-2.48313561e-01 2.84570187e-01 -2.71150082e-01 4.23839450e-01
4.94839966e-01 -2.15649173e-01 9.60201025e-02 -5.91509461e-01
8.78672600e-01 9.00700748e-01 7.05270588e-01 -8.53661478e-01
4.16570693e-01 2.65300661e-01 -8.39065909e-01 -5.40300071e-01
-1.21962798e+00 -7.65146196e-01 -4.84635890e-01 -1.46778926e-01
1.12676811e+00 -9.95819926e-01 -9.09963667e-01 2.47693419e-01
-1.19471204e+00 -9.82077658e-01 -2.72614270e-01 3.01972479e-01
-2.96633065e-01 1.17713824e-01 -8.76116514e-01 -1.03082168e+00
-6.13039434e-01 -1.24801278e+00 1.24024653e+00 4.37401146e-01
-3.20510119e-01 -1.11393452e+00 3.13374013e-01 8.79148245e-01
3.49906355e-01 -6.10832810e-01 7.50614882e-01 -1.22146273e+00
-3.51203740e-01 1.18184879e-01 -1.33473381e-01 3.33525658e-01
2.08993971e-01 -5.58588147e-01 -1.24702907e+00 -1.67898893e-01
9.11457166e-02 -1.10033953e+00 6.77306771e-01 1.14089899e-01
8.05878639e-01 -2.87881941e-01 -5.00967763e-02 -1.68589905e-01
7.77535379e-01 4.41936046e-01 2.52469152e-01 -1.96989387e-01
3.17494750e-01 1.10881948e+00 9.37594950e-01 6.17520094e-01
3.94181311e-01 7.67634571e-01 2.20044643e-01 8.18145722e-02
1.62930600e-02 -2.57641912e-01 4.37379688e-01 6.91781461e-01
3.37574959e-01 -4.50037509e-01 -7.46992171e-01 4.65362072e-01
-2.13645864e+00 -6.86186194e-01 1.73740268e-01 1.87721658e+00
1.21450174e+00 4.16221321e-01 2.09979370e-01 -7.59654820e-01
6.43232346e-01 3.95862550e-01 -6.02137446e-01 -1.54699102e-01
1.87603265e-01 3.07362914e-01 7.48734400e-02 1.05205333e+00
-1.25356352e+00 1.75079215e+00 5.53032970e+00 6.48437321e-01
-8.55003417e-01 4.01692629e-01 8.51141155e-01 2.57456750e-02
1.12343818e-01 8.29422176e-02 -1.17604446e+00 2.52587348e-01
9.92036521e-01 -2.01408744e-01 2.25351840e-01 1.17513454e+00
2.95346349e-01 -8.92719328e-02 -9.59049225e-01 3.85492355e-01
-2.42708996e-01 -1.16614795e+00 -2.48227790e-01 2.63674706e-02
6.98181033e-01 5.96435294e-02 3.34789753e-02 1.07439268e+00
1.20816600e+00 -7.89821148e-01 2.47427315e-01 -1.30848456e-02
4.35079604e-01 -3.72100145e-01 8.51914763e-01 5.65567911e-01
-8.35498333e-01 7.97281787e-02 -4.13551837e-01 -1.55894384e-01
5.25885403e-01 -3.20242830e-02 -1.48946548e+00 2.54342079e-01
2.17598468e-01 3.04377437e-01 -4.39830601e-01 3.16002548e-01
-5.32051980e-01 6.73895657e-01 5.83742857e-02 -2.95270532e-01
6.50599003e-01 -2.02467099e-01 1.41843140e-01 1.10488689e+00
-1.71477020e-01 4.05270964e-01 7.12313950e-01 7.55781412e-01
-3.79966229e-01 -2.65582767e-03 -4.15102333e-01 1.34958431e-01
5.26043057e-01 1.43793690e+00 -2.26267248e-01 -6.44622147e-01
-6.00850046e-01 7.83178806e-01 4.89916980e-01 1.66028276e-01
-7.30314493e-01 1.02515571e-01 5.68017542e-01 -4.20203954e-01
7.59493560e-02 -4.80698720e-02 -1.16877936e-01 -1.18105769e+00
-5.04978895e-01 -8.22999835e-01 4.09326792e-01 -7.17368722e-01
-1.46365643e+00 7.10179508e-01 1.37721285e-01 -8.69012177e-01
-8.02631021e-01 -5.99288881e-01 -9.21028554e-01 8.00050199e-01
-1.32075846e+00 -1.04069543e+00 -3.50321263e-01 5.57082832e-01
1.45741343e+00 -4.97149765e-01 1.00341368e+00 -1.18404202e-01
-4.57581997e-01 3.91134530e-01 -8.53033736e-02 2.93748856e-01
1.27896571e+00 -1.64539456e+00 4.45511013e-01 2.99713731e-01
-1.63139850e-01 6.04273319e-01 5.51588774e-01 -5.54803312e-01
-9.99289036e-01 -1.09514034e+00 7.60148227e-01 -5.82425237e-01
7.40291059e-01 -5.78726292e-01 -9.87026095e-01 7.47010887e-01
9.28367555e-01 -4.41958904e-01 6.38680816e-01 4.33191895e-01
-2.57395416e-01 3.59564453e-01 -1.00876486e+00 6.50919616e-01
6.97637320e-01 -5.00814497e-01 -1.09182966e+00 5.10720432e-01
1.20111573e+00 -5.86176217e-01 -5.57880580e-01 2.71841586e-01
2.11559206e-01 -7.13662624e-01 9.74979043e-01 -9.14824128e-01
3.84181261e-01 3.35049778e-01 -6.28862232e-02 -1.25817060e+00
-4.22272570e-02 -8.69443715e-01 -5.24923205e-02 1.39518201e+00
5.14054954e-01 -4.39295381e-01 1.03587162e+00 7.80782759e-01
-3.47045094e-01 -6.05120122e-01 -5.85800350e-01 -6.39751971e-01
1.13751523e-01 6.09328784e-02 2.11360589e-01 8.03844810e-01
3.92395705e-01 1.32569277e+00 -7.75058329e-01 -2.95299679e-01
2.07031235e-01 1.22764483e-01 1.08519208e+00 -1.32648909e+00
-4.97290999e-01 -3.01125586e-01 5.80630600e-01 -1.68118072e+00
6.17313921e-01 -5.16731143e-01 5.18791556e-01 -1.20483673e+00
1.30788952e-01 -2.76159167e-01 -7.52729997e-02 5.62275350e-01
-7.08598077e-01 -4.07374263e-01 2.18558908e-01 2.21530408e-01
-9.62053061e-01 1.07513118e+00 1.22694468e+00 -2.91206121e-01
-5.65321147e-01 3.14094961e-01 -7.68310606e-01 7.50700474e-01
1.04232335e+00 -1.55627415e-01 -8.56185496e-01 -2.09076017e-01
-7.78942168e-01 4.23495144e-01 6.03649579e-02 -5.05894005e-01
2.38783166e-01 -3.43300253e-01 -2.94234782e-01 -5.09922326e-01
8.11842382e-01 -4.59190756e-01 -7.00187981e-01 3.46924305e-01
-1.02109027e+00 -1.43370226e-01 1.69198692e-01 6.42699003e-01
-2.35448152e-01 -4.54660028e-01 8.18507373e-01 -3.08403671e-01
-7.48712718e-01 9.30202007e-02 -5.06628156e-01 3.20093870e-01
8.51572156e-01 8.34701478e-01 -7.06724286e-01 -8.85400951e-01
-7.35627413e-01 8.88092875e-01 -1.46936551e-02 6.43494785e-01
4.25215125e-01 -9.65648711e-01 -5.77105463e-01 -1.66218981e-01
2.50753522e-01 6.70310762e-03 1.97579190e-01 3.46920371e-01
1.32601783e-01 6.73900485e-01 -1.15690596e-01 -5.10074556e-01
-1.50016665e+00 3.89090240e-01 1.58573482e-02 -1.06677520e+00
-3.27165157e-01 9.52200413e-01 6.94468975e-01 -8.68383408e-01
5.60930252e-01 -3.11931729e-01 -3.72301817e-01 -7.43493214e-02
4.51620221e-01 -1.04573034e-01 -2.76945114e-01 -1.35076419e-01
2.35461723e-02 -1.11218870e-01 -4.93285179e-01 -7.16174304e-01
1.02032697e+00 -1.00331157e-01 4.83278424e-01 3.45388323e-01
6.98240876e-01 4.67222836e-03 -1.62388098e+00 -6.44009590e-01
2.28236124e-01 -2.05470949e-01 -3.37093651e-01 -1.13601100e+00
-6.90957546e-01 1.10133135e+00 3.65594625e-01 1.83946431e-01
7.19761014e-01 3.10444534e-01 9.11150336e-01 9.51774001e-01
2.88699627e-01 -9.50944006e-01 8.19248676e-01 9.85041499e-01
7.79569089e-01 -1.76593614e+00 -4.49317783e-01 -6.04279339e-01
-1.38343751e+00 7.71249950e-01 1.32689404e+00 8.78709778e-02
2.90281951e-01 8.76791477e-02 4.21935320e-01 -1.38001531e-01
-1.34580672e+00 -3.69339317e-01 1.27547994e-01 2.74497837e-01
5.86147964e-01 -1.16735004e-01 -1.47019804e-01 8.66770446e-01
-1.38056204e-02 -2.21860006e-01 1.83140218e-01 8.99722040e-01
-7.66410053e-01 -1.47180676e+00 -7.56561309e-02 5.66111095e-02
-2.66002983e-01 -6.72439858e-02 -9.10087347e-01 7.93670475e-01
-6.12427950e-01 1.40762556e+00 -1.54583767e-01 -4.07566190e-01
3.40921760e-01 4.93757516e-01 4.32040244e-02 -9.70241249e-01
-1.03616667e+00 4.32479590e-01 4.95375901e-01 -3.02146614e-01
-2.41055414e-01 -1.28641203e-01 -1.22910595e+00 -7.48396963e-02
-5.46401203e-01 6.32432342e-01 1.26131818e-01 9.46078598e-01
3.78213435e-01 5.86330891e-01 6.43114030e-01 -5.89771867e-01
-1.01990175e+00 -1.53035724e+00 -1.27873838e-01 4.10631895e-01
-9.74806398e-02 -8.34784687e-01 -1.74291089e-01 1.35996565e-01] | [12.83259391784668, 7.984288692474365] |
9f432228-6a2e-4e2b-a400-52fdc8e95a0a | lung-cancer-diagnosis-using-deep-attention | 2104.14655 | null | https://arxiv.org/abs/2104.14655v2 | https://arxiv.org/pdf/2104.14655v2.pdf | Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics | Early diagnosis of lung cancer is a key intervention for the treatment of lung cancer computer aided diagnosis (CAD) can play a crucial role. However, most published CAD methods treat lung cancer diagnosis as a lung nodule classification problem, which does not reflect clinical practice, where clinicians diagnose a patient based on a set of images of nodules, instead of one specific nodule. Besides, the low interpretability of the output provided by these methods presents an important barrier for their adoption. In this article, we treat lung cancer diagnosis as a multiple instance learning (MIL) problem in order to better reflect the diagnosis process in the clinical setting and for the higher interpretability of the output. We chose radiomics as the source of input features and deep attention-based MIL as the classification algorithm.The attention mechanism provides higher interpretability by estimating the importance of each instance in the set for the final diagnosis.In order to improve the model's performance in a small imbalanced dataset, we introduce a new bag simulation method for MIL.The results show that our method can achieve a mean accuracy of 0.807 with a standard error of the mean (SEM) of 0.069, a recall of 0.870 (SEM 0.061), a positive predictive value of 0.928 (SEM 0.078), a negative predictive value of 0.591 (SEM 0.155) and an area under the curve (AUC) of 0.842 (SEM 0.074), outperforming other MIL methods.Additional experiments show that the proposed oversampling strategy significantly improves the model's performance. In addition, our experiments show that our method provides an indication of the importance of each nodule in determining the diagnosis, which combined with the well-defined radiomic features, make the results more interpretable and acceptable for doctors and patients. | ['Inigo Bermejo', 'Leonard Wee', 'Andre Dekker', 'Zhenwei Shi', 'Chong Zhang', 'Haiyan Zeng', 'Junhua Chen'] | 2021-04-29 | null | null | null | null | ['deep-attention', 'lung-cancer-diagnosis', 'lung-nodule-classification', 'deep-attention'] | ['computer-vision', 'medical', 'medical', 'natural-language-processing'] | [-4.30319160e-02 2.82540798e-01 -5.52788079e-01 -2.77556688e-01
-8.74744475e-01 -1.43121064e-01 3.00830513e-01 3.13282549e-01
-2.28461102e-01 6.94115222e-01 1.21561281e-01 -4.79455471e-01
-2.44941592e-01 -8.87716293e-01 -4.49091315e-01 -7.98832178e-01
3.33463758e-01 6.58270657e-01 1.04969785e-01 3.79640698e-01
-1.48155391e-01 3.15602481e-01 -1.25718403e+00 4.59457755e-01
1.14174271e+00 1.07068765e+00 2.20515281e-01 5.66752255e-01
7.06333444e-02 9.73514497e-01 -5.17918527e-01 -3.48046958e-01
-2.67120879e-02 -4.97469634e-01 -7.43916333e-01 3.02653998e-01
2.12295458e-01 -5.14856398e-01 -2.64828324e-01 6.99552238e-01
3.44191700e-01 -2.30554491e-01 1.06541681e+00 -9.55778241e-01
-3.99297118e-01 3.89963448e-01 -5.79633832e-01 7.54285604e-02
-1.72000811e-01 2.53606617e-01 1.16595662e+00 -7.08965719e-01
1.41333759e-01 8.22585464e-01 6.39484942e-01 5.98160088e-01
-7.85946071e-01 -5.29854238e-01 -6.11681608e-04 7.37345070e-02
-1.15419567e+00 -9.99487489e-02 2.08480552e-01 -4.29194838e-01
4.92671221e-01 5.07396877e-01 9.51107979e-01 7.50102222e-01
4.89037156e-01 7.23880708e-01 7.69022465e-01 -2.83813238e-01
2.88025200e-01 4.19280440e-01 1.40220463e-01 8.52460444e-01
8.42692077e-01 -6.80058599e-02 7.23104328e-02 -1.86787024e-01
8.70897233e-01 6.83855057e-01 -1.65546224e-01 -8.12729523e-02
-1.36941957e+00 9.63209152e-01 9.95524466e-01 3.62953275e-01
-5.54498553e-01 3.11577976e-01 1.90170661e-01 -1.70933947e-01
2.93915212e-01 3.04323167e-01 -1.26270667e-01 3.89775395e-01
-7.40057111e-01 1.16255051e-02 7.14229643e-01 4.48597908e-01
9.71062183e-02 -1.43897161e-01 -7.01769054e-01 6.12279117e-01
3.91470879e-01 6.93117499e-01 6.59382463e-01 -6.20921493e-01
2.13189527e-01 8.17803085e-01 7.55625218e-02 -7.19098210e-01
-3.31272840e-01 -8.57727051e-01 -1.25668144e+00 -1.17882498e-01
4.98900890e-01 7.91987926e-02 -1.01721179e+00 1.50297749e+00
1.04943356e-02 1.96287110e-02 5.61580202e-03 7.75172174e-01
8.33243191e-01 3.40027839e-01 2.33247966e-01 -2.94529229e-01
1.68342674e+00 -1.06792092e+00 -6.33017838e-01 -3.44930589e-01
8.21533024e-01 -2.10754320e-01 1.05849659e+00 3.29161920e-02
-7.34713793e-01 -3.32563788e-01 -8.14170599e-01 2.77119964e-01
4.52428199e-02 5.84983706e-01 6.47714615e-01 5.13348222e-01
-6.77849948e-01 1.88685015e-01 -1.00158477e+00 -3.36191386e-01
7.98202813e-01 3.68083090e-01 -1.28770888e-01 -4.19486821e-01
-1.02310216e+00 7.14885771e-01 1.40759066e-01 -2.59752981e-02
-7.32114434e-01 -8.61709297e-01 -4.38645869e-01 3.15402061e-01
2.28768632e-01 -1.08920121e+00 1.27641034e+00 -9.33257818e-01
-7.81722486e-01 8.90870869e-01 -2.35050395e-01 -4.87658560e-01
6.43741012e-01 9.97805297e-02 -2.87504736e-02 2.32960105e-01
1.07784279e-01 6.32692218e-01 5.18497944e-01 -9.89165366e-01
-9.26814437e-01 -3.86151820e-01 -8.93360600e-02 2.59004176e-01
-3.04473758e-01 -4.78708416e-01 -3.87437284e-01 -4.38288003e-01
1.91273391e-01 -9.50363994e-01 -4.94483531e-01 1.60758734e-01
-3.63501072e-01 -1.46769047e-01 3.27040374e-01 -6.07755482e-01
1.38736653e+00 -2.03732729e+00 -2.52421379e-01 2.28225097e-01
7.81684518e-01 1.76749513e-01 3.12766969e-01 -1.28086746e-01
1.94047745e-02 3.51572186e-01 -3.22159171e-01 5.72761223e-02
-3.74386609e-01 -1.62208639e-02 2.43904009e-01 3.26321602e-01
3.72153640e-01 1.20511425e+00 -8.62448871e-01 -4.27581221e-01
2.17869565e-01 3.72893989e-01 -5.23989141e-01 3.45582098e-01
2.39791460e-02 2.79154956e-01 -6.81450844e-01 5.67265689e-01
3.53860438e-01 -8.17913473e-01 2.93287516e-01 -2.15803266e-01
4.63881850e-01 6.05083071e-02 -8.08207452e-01 8.07120740e-01
-4.00004327e-01 3.91956061e-01 -4.11266208e-01 -8.55964780e-01
6.78463936e-01 5.19471943e-01 7.94305325e-01 -4.49075401e-01
1.71315536e-01 3.26337516e-01 4.95911956e-01 -5.44620931e-01
-2.82878518e-01 -2.93373644e-01 1.57244667e-01 4.76869136e-01
-4.41010088e-01 -1.88060552e-02 2.86910241e-03 1.72701463e-01
1.26406395e+00 -8.39056730e-01 7.62533069e-01 -2.06883714e-01
3.90263349e-01 1.43043116e-01 3.14739883e-01 7.15264797e-01
-2.00399846e-01 6.01211190e-01 6.27282381e-01 -2.92833567e-01
-8.94835532e-01 -9.38444674e-01 -3.45721751e-01 3.28562975e-01
-1.22095741e-01 -4.50698361e-02 -7.24546731e-01 -1.02916503e+00
1.67531267e-01 6.41726077e-01 -6.79056704e-01 -3.59284133e-01
-2.08899334e-01 -1.05883372e+00 1.80764318e-01 8.77962887e-01
4.62437242e-01 -9.24797595e-01 -6.46108210e-01 -2.40424145e-02
-4.81969327e-01 -8.32300484e-01 -2.94353217e-01 2.12987393e-01
-1.14003861e+00 -1.31660593e+00 -8.45260441e-01 -6.52966440e-01
1.04016507e+00 3.44919920e-01 1.29822624e+00 4.05835658e-01
-2.32707709e-01 2.28062138e-01 -5.77148832e-02 -4.68999177e-01
-4.15639937e-01 1.85395494e-01 -1.59496278e-01 -1.06968604e-01
4.22939986e-01 1.02725446e-01 -7.79569268e-01 2.27478921e-01
-9.11950827e-01 2.13553160e-01 1.05277276e+00 1.14973974e+00
6.97815239e-01 2.05623433e-01 6.50262594e-01 -1.20684993e+00
4.38541681e-01 -6.59022748e-01 -1.59958035e-01 1.90592974e-01
-8.66585553e-01 -7.24607334e-02 5.63371897e-01 -4.03265059e-01
-8.84627938e-01 8.45791698e-02 1.22193441e-01 -3.12586457e-01
-1.75439455e-02 5.10856032e-01 4.30694818e-02 4.35592234e-01
6.77854061e-01 -2.19835639e-02 2.55834967e-01 -1.06216207e-01
-2.53193885e-01 8.26706409e-01 1.51272729e-01 -7.41175711e-02
5.61787486e-01 2.50471205e-01 1.05191953e-01 -4.39575940e-01
-1.29997694e+00 -5.33742428e-01 -4.08276528e-01 -3.20255719e-02
7.26069033e-01 -1.14369333e+00 -7.33979404e-01 1.80128545e-01
-5.70952833e-01 -2.85007596e-01 -3.08047414e-01 7.03302920e-01
-3.51995975e-01 -6.05964214e-02 -5.54876208e-01 -7.59222627e-01
-5.45395017e-01 -1.15953934e+00 9.32242811e-01 2.37810388e-01
-4.23201531e-01 -1.08772981e+00 -3.85015637e-01 6.93206310e-01
4.00054365e-01 2.18673587e-01 1.05654562e+00 -7.87811279e-01
-6.81700230e-01 -7.28739977e-01 -5.65217376e-01 2.43513227e-01
4.41090345e-01 -7.94016048e-02 -9.61156428e-01 -2.00369179e-01
1.53833643e-01 -1.99826136e-01 8.59848976e-01 7.41438568e-01
1.46704340e+00 -3.27899635e-01 -6.18989587e-01 1.94598883e-01
1.45115542e+00 2.95332670e-01 5.99744201e-01 4.41574492e-03
7.53404319e-01 2.64432162e-01 7.28830159e-01 3.52324098e-01
3.27745676e-01 3.06318790e-01 6.59530818e-01 -3.44970822e-01
-1.03653334e-01 -1.21236227e-01 6.54171407e-02 5.19873440e-01
9.09919664e-02 -5.43622673e-01 -1.07647073e+00 5.19843161e-01
-1.76300168e+00 -7.51923323e-01 -3.80493194e-01 2.32100677e+00
7.00461447e-01 1.72546431e-01 -1.25529896e-02 2.73407400e-01
6.35633230e-01 -2.82263041e-01 -5.39245605e-01 -3.16404970e-03
3.89445186e-01 8.50128308e-02 3.68094146e-01 2.30238929e-01
-9.75743413e-01 2.74054229e-01 5.89588928e+00 7.52101779e-01
-1.13685167e+00 -1.97251469e-01 1.32203162e+00 1.36051416e-01
-2.48085022e-01 -4.34961110e-01 -7.04464495e-01 6.82952285e-01
9.46442604e-01 -1.27814114e-01 8.38335138e-03 7.32587755e-01
2.10444003e-01 -3.37500542e-01 -1.28682685e+00 8.24527085e-01
-3.17675360e-02 -1.13270009e+00 2.94038672e-02 2.91213065e-01
6.59909964e-01 -2.21249998e-01 1.68573916e-01 3.24754775e-01
5.27283512e-02 -1.41919482e+00 2.12012574e-01 5.07312238e-01
1.02972317e+00 -4.93090987e-01 1.29963171e+00 5.75248837e-01
-9.36354101e-01 -2.08958715e-01 -2.32763365e-01 9.35824588e-02
-3.90269786e-01 9.85551178e-01 -1.38940394e+00 2.61503249e-01
5.05629241e-01 5.94130874e-01 -5.67799091e-01 9.63477314e-01
-5.64366952e-02 8.90655696e-01 -3.88483196e-01 -3.18487316e-01
8.52967799e-02 1.56988010e-01 4.21819240e-02 9.85599756e-01
4.27083224e-01 2.17898235e-01 5.68953343e-02 7.84222186e-01
-1.91240683e-01 1.36351317e-01 -4.20450270e-01 -1.22734845e-01
4.10601318e-01 1.18088138e+00 -7.82200694e-01 -4.63904858e-01
-2.49684811e-01 5.53765297e-01 4.24628556e-02 2.66182944e-02
-1.09425902e+00 -7.58306757e-02 2.95957059e-01 4.09052402e-01
1.83080927e-01 6.18511856e-01 -6.49517000e-01 -1.04065406e+00
1.77138764e-02 -8.51850271e-01 5.49638689e-01 -5.56528091e-01
-1.22955561e+00 4.69128698e-01 -3.39742422e-01 -1.39538836e+00
-2.15687886e-01 -5.89232266e-01 -7.13051975e-01 7.77592957e-01
-1.18082595e+00 -8.78982663e-01 -8.79695952e-01 7.12039694e-03
4.68715489e-01 4.90234932e-03 8.07760835e-01 1.56694695e-01
-7.40776539e-01 6.06225729e-01 1.13800839e-01 1.93839952e-01
6.27542317e-01 -1.31529105e+00 -1.57021329e-01 4.13069159e-01
-1.49518326e-01 2.34347776e-01 1.56415388e-01 -4.94919389e-01
-1.01738918e+00 -1.35245872e+00 8.72849286e-01 -5.77189624e-01
2.05478236e-01 2.23975286e-01 -9.00548041e-01 5.21749973e-01
-4.62619960e-01 2.05479518e-01 7.76423275e-01 -2.23066658e-01
1.15936026e-01 -3.05241704e-01 -1.44674897e+00 4.51314539e-01
6.47009790e-01 -9.94158238e-02 -1.26925439e-01 4.21265066e-01
4.98681962e-01 -3.93243194e-01 -1.02141023e+00 6.75093710e-01
6.15964532e-01 -8.94274116e-01 1.03950906e+00 -4.97395456e-01
7.36012876e-01 -1.31418139e-01 7.93467928e-03 -1.09291160e+00
-7.09549069e-01 5.24714291e-01 -1.30509749e-01 7.89618134e-01
5.87828636e-01 -5.92876852e-01 9.31400239e-01 6.87639832e-01
1.65456519e-01 -1.32359242e+00 -5.34829617e-01 -3.13154429e-01
-1.82391927e-02 -2.28696346e-01 3.81152838e-01 7.27196276e-01
-2.98831940e-01 2.14258909e-01 8.78090411e-03 2.92234439e-02
5.15577495e-01 8.27462301e-02 3.54665786e-01 -1.39915109e+00
-3.13807815e-01 -3.04288924e-01 -2.46400818e-01 -5.79107761e-01
-2.83795804e-01 -1.05631185e+00 -1.16781861e-01 -1.85920477e+00
9.18279767e-01 -6.21170938e-01 -5.91018498e-01 5.05074620e-01
-6.14737928e-01 1.90698266e-01 -6.45375550e-02 3.99491549e-01
-2.91014642e-01 1.83919907e-01 1.41149461e+00 -3.31831127e-01
5.54345287e-02 5.92639863e-01 -1.05185664e+00 6.87487960e-01
9.37501311e-01 -5.84797621e-01 -4.25993532e-01 -1.26132146e-01
-1.63492337e-01 2.67782509e-01 3.91560137e-01 -9.76128936e-01
-5.31468205e-02 -2.05980018e-01 8.27538013e-01 -4.67089683e-01
1.02677532e-01 -1.03458786e+00 2.12582543e-01 1.33235610e+00
-3.14912438e-01 -3.28446448e-01 -5.37415259e-02 7.37098396e-01
-1.75532430e-01 -3.06726456e-01 8.50304604e-01 -2.46380448e-01
-2.36044317e-01 4.33322847e-01 -4.35591519e-01 7.37163350e-02
1.15688789e+00 -1.71710610e-01 -5.42430729e-02 -3.10254097e-01
-4.56441492e-01 2.52167344e-01 2.29574382e-01 -3.78656834e-02
4.92144048e-01 -1.32065463e+00 -8.09917390e-01 1.70793846e-01
2.18008742e-01 4.00604606e-01 9.52935368e-02 1.15513468e+00
-6.18473768e-01 5.81753433e-01 1.72927126e-01 -8.95394921e-01
-1.27157092e+00 2.23929644e-01 6.20423853e-01 -7.93461084e-01
-5.09696901e-01 5.74688971e-01 5.83389401e-01 -1.22440785e-01
3.55418384e-01 -6.28805757e-01 -2.12451026e-01 -5.98354489e-02
4.04251307e-01 3.60674322e-01 1.57366410e-01 -7.41254464e-02
-4.14654791e-01 2.89503485e-01 -6.52846247e-02 3.62034112e-01
1.21723568e+00 2.04172164e-01 -2.34915726e-02 4.21848238e-01
8.34065914e-01 -1.87238321e-01 -8.24699700e-01 -4.19700965e-02
-1.79331601e-01 -3.67732704e-01 1.39559776e-01 -1.05252397e+00
-1.23507595e+00 7.74517119e-01 7.16677725e-01 9.31649134e-02
1.09506214e+00 5.57520650e-02 6.50951564e-01 4.02811199e-01
-9.01733190e-02 -4.89720941e-01 2.53851861e-01 1.50762081e-01
6.69696271e-01 -1.62146032e+00 3.61721255e-02 -6.59855962e-01
-8.28751981e-01 1.04868925e+00 7.21846581e-01 1.45006210e-01
5.81519067e-01 2.45836630e-01 7.62352161e-03 -6.87232837e-02
-9.39920187e-01 -4.78161909e-02 4.56322849e-01 3.45527738e-01
6.63547397e-01 3.93757582e-01 -2.27544084e-01 9.87131536e-01
1.39357641e-01 1.55135825e-01 3.18695337e-01 5.08346438e-01
-6.23200953e-01 -5.98750949e-01 -3.92230481e-01 1.16769016e+00
-6.17603123e-01 6.87408522e-02 -2.36455441e-01 7.29897141e-01
-9.05973911e-02 7.42616534e-01 3.54359210e-01 -1.10755920e-01
2.07140103e-01 6.43202215e-02 2.13689864e-01 -7.87092924e-01
-4.90248173e-01 5.72573580e-03 -1.57162413e-01 -2.00384587e-01
-1.39793471e-01 -2.71449655e-01 -1.48050094e+00 -3.27993363e-01
-4.84246612e-01 1.00926951e-01 2.74557292e-01 7.66357005e-01
1.84922993e-01 1.02512586e+00 7.37371147e-01 -1.44677877e-01
-7.17833817e-01 -8.80065262e-01 -5.15345693e-01 5.04072666e-01
2.32928634e-01 -4.22073066e-01 -5.43251812e-01 -5.81687279e-02] | [15.357486724853516, -2.169893264770508] |
ced714a5-1edc-4f5a-9bed-04c1736a414e | optimal-01-matrix-completion-with | 2209.04373 | null | https://arxiv.org/abs/2209.04373v1 | https://arxiv.org/pdf/2209.04373v1.pdf | Optimal $(0,1)$-Matrix Completion with Majorization Ordered Objectives (To the memory of Pravin Varaiya) | We propose and examine two optimal $(0,1)$-matrix completion problems with majorization ordered objectives. They elevate the seminal study by Gale and Ryser from feasibility to optimality in partial order programming (POP), referring to optimization with partially ordered objectives. We showcase their applications in electric vehicle charging, portfolio optimization, and secure data storage. Solving such integer POP (iPOP) problems is challenging because of the possible non-comparability among objective values and the integer requirements. Nevertheless, we prove the essential uniqueness of all optimal objective values and identify two particular ones for each of the two inherently symmetric iPOP problems. Furthermore, for every optimal objective value, we decompose the construction of an associated optimal~$(0,1)$-matrix into a series of sorting processes, respectively agreeing with the rule of thumb "peak shaving" or "valley filling." We show that the resulting algorithms have linear time complexities and verify their empirical efficiency via numerical simulations compared to the standard order-preserving method for POP. | ['Li Qiu', 'Keyou You', 'Wei Chen', 'Yanfang Mo'] | 2022-09-09 | null | null | null | null | ['matrix-completion', 'portfolio-optimization'] | ['methodology', 'time-series'] | [ 3.22185427e-01 2.69020319e-01 -6.32314458e-02 -1.64000049e-01
-6.27711415e-01 -1.01915658e+00 1.63237229e-01 5.01535058e-01
-3.36948335e-01 6.03205502e-01 -7.25649521e-02 -5.62940776e-01
-1.11007428e+00 -5.93427062e-01 -8.83363426e-01 -8.91119063e-01
-4.23553109e-01 1.03801632e+00 -4.23142433e-01 -3.33530873e-01
5.96691668e-01 6.70350194e-01 -1.32763529e+00 1.48700297e-01
1.04360902e+00 1.16391039e+00 2.93476254e-01 3.98042232e-01
-1.75135836e-01 3.20417434e-01 -3.17811370e-01 -4.89202738e-01
7.27083325e-01 2.61490345e-01 -1.00538182e+00 2.53747523e-01
-5.28640747e-02 8.12028125e-02 -1.66552916e-01 1.22740889e+00
1.69157460e-01 -6.08170368e-02 4.17649508e-01 -1.84515035e+00
-4.48370129e-01 7.39902020e-01 -8.02588284e-01 -9.15587172e-02
8.84287655e-02 -3.57762724e-01 1.37168360e+00 -8.04503739e-01
5.37421584e-01 7.93626189e-01 3.35697889e-01 1.06591798e-01
-1.65344930e+00 -3.13481450e-01 1.14993006e-02 1.70763582e-01
-1.42567825e+00 -1.94550127e-01 8.59211087e-01 -3.12120348e-01
5.87884605e-01 8.14880073e-01 4.43404853e-01 6.40086783e-03
2.57941876e-02 7.26888716e-01 1.24262154e+00 -2.34034196e-01
3.06374818e-01 2.82213539e-01 4.83412147e-01 2.38927066e-01
6.50024056e-01 -2.05532670e-01 -3.45684260e-01 -4.16492492e-01
-1.69532169e-02 -1.13634191e-01 -3.23790699e-01 -8.50140929e-01
-1.14249969e+00 5.90520740e-01 2.82943528e-02 2.70743519e-01
-4.07929480e-01 1.33846939e-01 1.88366011e-01 5.19421279e-01
7.65284300e-02 4.71779406e-01 -2.80571222e-01 1.16658829e-01
-7.92128444e-01 4.44026858e-01 1.01682401e+00 1.18676150e+00
6.73086524e-01 -1.53215230e-01 -1.22954786e-01 4.00106102e-01
3.24884169e-02 4.43947017e-01 -4.20823485e-01 -9.01496112e-01
1.10320497e+00 3.52483898e-01 5.82092762e-01 -1.23397040e+00
-5.40703118e-01 -5.78207135e-01 -7.36719012e-01 -4.51745763e-02
2.94039428e-01 5.92311844e-02 -3.08642182e-02 1.63936591e+00
1.08929433e-01 -3.27477157e-01 1.48066565e-01 6.07958198e-01
7.36188665e-02 8.40300500e-01 -3.31383735e-01 -7.70171404e-01
1.11095166e+00 -6.38428211e-01 -7.32414305e-01 8.65082219e-02
4.78726357e-01 -5.58881044e-01 6.00999355e-01 6.30881071e-01
-1.40936136e+00 1.04516774e-01 -1.10137975e+00 2.63786107e-01
-2.24723324e-01 1.36948973e-01 7.43563950e-01 8.94176006e-01
-1.27994978e+00 6.62272036e-01 -1.96896195e-01 2.13204697e-01
-9.83770639e-02 8.96291733e-01 -3.55553895e-01 -2.16076300e-02
-7.96653152e-01 4.24311936e-01 2.27518782e-01 4.90121424e-01
-4.38926935e-01 -9.67088223e-01 -3.96745026e-01 2.51953602e-01
6.07455909e-01 -2.76871383e-01 6.19225621e-01 -3.24206024e-01
-8.89507830e-01 7.93893397e-01 -5.69674522e-02 -4.38888580e-01
5.39917588e-01 4.01026368e-01 -5.67964390e-02 2.04137340e-02
4.78377789e-02 1.69292048e-01 4.97899562e-01 -1.42728925e+00
-6.31893039e-01 -5.11751771e-01 4.04701740e-01 2.32178345e-01
-4.78697389e-01 1.26485126e-02 -2.75099367e-01 -3.59916866e-01
2.76283354e-01 -9.41916108e-01 -5.87181687e-01 -3.10182333e-01
-4.67452943e-01 1.06669525e-02 1.26611203e-01 -7.12958515e-01
1.53881001e+00 -2.27184272e+00 5.97688794e-01 8.67237806e-01
3.32316369e-01 -4.28946972e-01 -1.14039347e-01 8.06294680e-01
-3.95956963e-01 2.35323489e-01 -3.31141114e-01 -2.89870113e-01
6.08717263e-01 2.87429780e-01 -3.47331792e-01 7.80809820e-01
-1.83993012e-01 5.95527112e-01 -5.21144569e-01 -2.09599063e-01
-2.04155117e-01 -1.91458911e-01 -7.46958494e-01 -2.34949484e-01
2.87486725e-02 5.11200093e-02 -3.98221046e-01 4.79755342e-01
1.16730666e+00 5.34844734e-02 7.77404904e-01 -3.70876789e-01
-4.81375664e-01 -9.25007239e-02 -1.79071438e+00 1.15223503e+00
-2.80222178e-01 2.79322237e-01 8.91267478e-01 -1.37121427e+00
7.18103588e-01 2.75976993e-02 1.08046663e+00 -7.07524478e-01
2.09979564e-02 3.93654883e-01 -2.75639504e-01 -7.21865240e-03
1.07418120e+00 6.52987976e-03 -4.25291389e-01 5.54131091e-01
-5.74988365e-01 5.65211587e-02 7.57645607e-01 3.31752032e-01
1.14091814e+00 -7.58196652e-01 -2.13786453e-01 -1.06019652e+00
7.60220230e-01 -1.31991589e-02 6.96091473e-01 5.68515301e-01
2.22366527e-01 3.44149053e-01 1.22307217e+00 -1.64480984e-01
-1.01350796e+00 -1.00375736e+00 -2.72984236e-01 6.86728597e-01
3.41939062e-01 -3.59195799e-01 -4.96061057e-01 -1.65318519e-01
2.92508304e-01 6.78326666e-01 -5.52171528e-01 3.90683353e-01
-5.94417095e-01 -1.13573205e+00 -8.12510997e-02 9.46009383e-02
6.91303536e-02 -3.27469170e-01 -2.78466940e-01 4.26775455e-01
-2.01805040e-01 -8.32307279e-01 -5.45929730e-01 4.51744050e-01
-7.06199050e-01 -8.97063196e-01 -5.50605953e-01 -5.11003613e-01
1.05339170e+00 2.11709663e-01 1.01577342e+00 -5.92403971e-02
-1.29509225e-01 5.37839413e-01 -6.53039813e-02 -1.15475155e-01
-1.65056109e-01 -1.08662643e-01 3.35076034e-01 2.76464880e-01
-3.47110838e-01 -5.46198428e-01 -5.00963926e-01 4.29940104e-01
-1.18789721e+00 -2.72030801e-01 4.28606182e-01 5.34518957e-01
7.91393399e-01 6.72368407e-01 2.02064991e-01 -8.15147102e-01
8.53421032e-01 -4.54332978e-01 -1.35918760e+00 5.41067243e-01
-9.89963472e-01 4.68316317e-01 4.79620546e-01 1.32055268e-01
-5.86134970e-01 5.16104139e-02 1.55819163e-01 -1.71731427e-01
7.21925914e-01 5.51782429e-01 -4.61546689e-01 -3.05548459e-01
-2.12203607e-01 3.24240893e-01 -4.64277752e-02 -4.39098209e-01
2.32906401e-01 2.10111678e-01 4.43306595e-01 -8.95749211e-01
9.80821669e-01 5.77367187e-01 5.79428077e-01 -4.43155229e-01
-8.18973035e-02 -3.75863612e-01 -2.66999662e-01 -6.05484582e-02
4.10555661e-01 -3.09628159e-01 -1.44549751e+00 9.03963298e-03
-1.10624349e+00 1.55207843e-01 -4.50040847e-01 -3.39593925e-02
-7.40582824e-01 6.84816539e-01 -4.48288321e-01 -9.47577894e-01
-1.78565741e-01 -1.32498837e+00 6.00359201e-01 -2.38490492e-01
2.39590108e-01 -6.07764244e-01 -5.05882083e-03 2.84309536e-01
1.95917621e-01 1.05126545e-01 1.26398861e+00 -3.21519703e-01
-9.54195440e-01 -1.21381871e-01 -3.57322067e-01 2.46603526e-02
-4.41500217e-01 -2.20900238e-01 -1.12585954e-01 -4.76177514e-01
1.17283419e-01 3.19600374e-01 2.45452225e-01 2.22661898e-01
1.09907508e+00 -9.10659015e-01 -2.44455606e-01 4.46421117e-01
1.83105898e+00 2.13574439e-01 5.55732131e-01 3.72339398e-01
2.52054572e-01 9.36677039e-01 7.69128740e-01 8.87602687e-01
4.43703532e-01 7.65935659e-01 6.68235600e-01 1.30172580e-01
7.16358125e-01 3.21964711e-01 1.04722030e-01 7.73111761e-01
1.83911219e-01 -2.47746289e-01 -6.32516444e-01 7.96173096e-01
-1.84609890e+00 -7.21067607e-01 -4.18367177e-01 2.59313917e+00
4.24971223e-01 2.31897086e-03 1.29350185e-01 4.08727139e-01
6.80374384e-01 6.93326071e-02 -1.55625150e-01 -7.92708337e-01
-2.91815251e-01 1.42100707e-01 1.24142098e+00 6.69405043e-01
-6.64121389e-01 -9.21479799e-03 6.05863190e+00 8.13554883e-01
-5.46299934e-01 8.51133689e-02 6.41045690e-01 -1.81418702e-01
-1.02269351e+00 1.67658806e-01 -6.12074554e-01 4.86586064e-01
5.77638030e-01 -6.40657127e-01 8.03337336e-01 6.09281182e-01
5.93969524e-02 -1.34390425e-02 -1.19652319e+00 1.11242783e+00
-1.97202995e-01 -1.43481982e+00 -3.40375483e-01 5.54502606e-01
8.34802151e-01 -4.83819187e-01 3.12150925e-01 -1.18493095e-01
6.72788844e-02 -7.98808575e-01 8.97022784e-01 4.23841566e-01
4.32563096e-01 -1.12303472e+00 3.99024278e-01 8.79025608e-02
-1.44059193e+00 -5.43638527e-01 -2.74729818e-01 2.27285147e-01
3.65635067e-01 6.96656406e-01 -1.35029659e-01 1.00472033e+00
4.38438237e-01 -4.10532653e-02 -9.21918303e-02 9.85829890e-01
5.20002604e-01 -6.84536025e-02 -7.78641701e-01 -5.89593090e-02
1.96187094e-01 -8.13874006e-01 6.63216949e-01 6.61430955e-01
3.99559379e-01 2.32338786e-01 2.28542127e-02 7.14770436e-01
-9.07797664e-02 2.61090666e-01 -3.58387649e-01 -2.81766891e-01
3.92484903e-01 1.08904660e+00 -7.31175840e-01 2.38315165e-02
-2.32337683e-01 5.40409863e-01 -4.90127131e-02 1.92331716e-01
-7.78804660e-01 -5.67150950e-01 8.74850929e-01 2.30816051e-01
3.91480982e-01 -3.20409268e-01 -7.22983599e-01 -7.64904320e-01
6.20457649e-01 -7.10776448e-01 4.23224002e-01 -1.03668250e-01
-1.03000307e+00 4.61634129e-01 2.47164100e-01 -1.18869305e+00
-6.85175285e-02 -6.19398534e-01 -3.06889534e-01 7.04716563e-01
-1.34309566e+00 -5.12915254e-01 3.49032432e-01 3.83622289e-01
5.11570787e-03 2.25491822e-01 2.68138438e-01 7.97212303e-01
-5.82553148e-01 5.44429779e-01 7.16637969e-01 -5.12650192e-01
-1.42219111e-01 -1.24128878e+00 -8.83186460e-02 9.47053313e-01
-2.30857611e-01 3.75790685e-01 1.11024690e+00 -3.08840156e-01
-2.27873778e+00 -5.30094266e-01 1.13845611e+00 -2.05196261e-01
9.78676915e-01 -4.07870263e-01 -3.84400487e-01 4.25681323e-01
2.02072427e-01 -2.97381103e-01 3.31519455e-01 -9.41220019e-03
1.29357815e-01 -7.52510309e-01 -1.18074155e+00 5.45890212e-01
1.00965178e+00 -2.20516771e-01 -1.74729864e-03 6.12371087e-01
5.12050629e-01 -1.64266571e-01 -1.02849281e+00 5.49613774e-01
3.93012255e-01 -7.25612402e-01 1.19334054e+00 -3.67913425e-01
1.11495845e-01 -4.03421700e-01 -4.77158964e-01 -7.32838154e-01
-2.62397140e-01 -9.49221432e-01 2.82493651e-01 1.22290182e+00
6.17051244e-01 -7.14918256e-01 9.05074596e-01 1.04274082e+00
-7.99746215e-02 -8.57143819e-01 -1.15594494e+00 -8.72478008e-01
-4.95427959e-02 -4.38173562e-01 8.72707248e-01 7.32654750e-01
3.58637482e-01 -4.24708128e-02 -5.25974512e-01 4.61013943e-01
1.01467645e+00 6.26923323e-01 5.38620293e-01 -9.66791153e-01
-6.49509966e-01 -4.65012908e-01 -6.22729808e-02 -9.55642283e-01
-9.11655724e-02 -1.05105126e+00 -1.54533640e-01 -1.40188384e+00
2.35507116e-01 -9.91990924e-01 -4.10975069e-01 7.38937259e-02
5.22429705e-01 -8.02309811e-02 5.66579938e-01 1.32367954e-01
-6.42146111e-01 2.62696654e-01 7.99480081e-01 -3.35927963e-01
-1.53349712e-01 1.04161754e-01 -8.66066575e-01 8.29882324e-02
4.64366853e-01 -4.59281236e-01 -4.79528278e-01 -5.14371872e-01
8.71738434e-01 6.89523101e-01 -9.64911878e-02 -6.68638825e-01
3.44160467e-01 -2.86076844e-01 -5.16004384e-01 -9.99661565e-01
3.05395842e-01 -1.14886642e+00 7.60334909e-01 5.28652370e-01
-1.99407533e-01 6.16428256e-01 4.32032645e-02 5.27938366e-01
1.55871287e-02 -7.47343659e-01 2.78125167e-01 2.26289690e-01
-5.49363196e-01 3.24516922e-01 -3.85991365e-01 -2.91392744e-01
1.19380212e+00 -8.06560144e-02 -2.43540183e-01 -2.42112219e-01
-8.94816041e-01 6.92023098e-01 2.22266540e-01 -9.24137011e-02
3.74409676e-01 -1.18867600e+00 -5.74276865e-01 -7.15088248e-02
-1.64548844e-01 -3.48284245e-01 5.61649024e-01 1.12970197e+00
-6.39207602e-01 8.64160061e-01 -1.78082466e-01 -3.81502062e-01
-1.20279348e+00 8.68471324e-01 -2.89906144e-01 -9.70969856e-01
-6.07949274e-04 4.91475821e-01 1.99948773e-01 -2.76055723e-01
1.48853883e-01 -1.51480362e-01 6.08542822e-02 2.75238216e-01
1.07608758e-01 6.94398761e-01 2.37894043e-01 -2.73039430e-01
-4.27484751e-01 3.51989388e-01 2.31528208e-02 -1.71014801e-01
1.50740552e+00 -4.17210013e-01 -7.16043651e-01 -1.75289690e-01
1.21621072e+00 2.65441000e-01 -6.92226291e-01 8.95559043e-02
2.49059126e-01 -5.38357913e-01 -3.23626399e-01 -1.06429666e-01
-1.15011799e+00 4.06222373e-01 3.60590398e-01 4.60918546e-01
1.44575608e+00 -2.07173184e-01 5.03872275e-01 5.11385441e-01
9.03311849e-01 -1.18902230e+00 -3.97896767e-01 2.51136929e-01
9.15273428e-01 -5.05289018e-01 1.17204353e-01 -7.63704538e-01
-3.96648705e-01 9.18707013e-01 -1.25566244e-01 5.75969834e-03
6.43175602e-01 5.31070948e-01 -7.61545360e-01 3.19609381e-02
-6.87422097e-01 -4.81381938e-02 5.68019226e-02 1.64957583e-01
-1.54788598e-01 2.18126506e-01 -1.24177790e+00 7.20697701e-01
-1.66035682e-01 -3.44514281e-01 6.19372845e-01 9.36885834e-01
-7.91969299e-02 -1.69273472e+00 -5.69303632e-01 5.11261880e-01
-4.01574582e-01 -1.57444626e-01 1.43582765e-02 6.32988214e-01
-1.34032801e-01 8.42063785e-01 2.78555974e-02 -1.85545325e-01
4.00976509e-01 -2.10565612e-01 4.65801328e-01 -1.95983537e-02
-4.31219846e-01 -1.30246148e-01 3.03528577e-01 -4.58179444e-01
7.51310959e-02 -8.66153955e-01 -1.00765741e+00 -6.61468089e-01
-2.60056313e-02 5.64295530e-01 8.87175798e-01 7.53460586e-01
3.46661389e-01 2.94197708e-01 1.20505428e+00 -3.60379726e-01
-9.16762650e-01 -1.04109161e-01 -1.00505459e+00 6.10900186e-02
-4.65652868e-02 -3.74776334e-01 -3.24193865e-01 -5.25394738e-01] | [6.555875778198242, 4.77060079574585] |
75858124-1c26-49c6-bb71-f2b92a60a062 | gum-net-unsupervised-geometric-matching-for | null | null | http://openaccess.thecvf.com/content_CVPR_2020/html/Zeng_Gum-Net_Unsupervised_Geometric_Matching_for_Fast_and_Accurate_3D_Subtomogram_CVPR_2020_paper.html | http://openaccess.thecvf.com/content_CVPR_2020/papers/Zeng_Gum-Net_Unsupervised_Geometric_Matching_for_Fast_and_Accurate_3D_Subtomogram_CVPR_2020_paper.pdf | Gum-Net: Unsupervised Geometric Matching for Fast and Accurate 3D Subtomogram Image Alignment and Averaging | We propose a Geometric unsupervised matching Net-work (Gum-Net) for finding the geometric correspondence between two images with application to 3D subtomogram alignment and averaging. Subtomogram alignment is the most important task in cryo-electron tomography (cryo-ET), a revolutionary 3D imaging technique for visualizing the molecular organization of unperturbed cellular landscapes in single cells. However, subtomogram alignment and averaging are very challenging due to severe imaging limits such as noise and missing wedge effects. We introduce an end-to-end trainable architecture with three novel modules specifically designed for preserving feature spatial information and propagating feature matching information. The training is performed in a fully unsupervised fashion to optimize a matching metric. No ground truth transformation information nor category-level or instance-level matching supervision information is needed. After systematic assessments on six real and nine simulated datasets, we demonstrate that Gum-Net reduced the alignment error by 40 to 50% and improved the averaging resolution by 10%. Gum-Net also achieved 70 to 110 times speedup in practice with GPU acceleration compared to state-of-the-art subtomogram alignment methods. Our work is the first 3D unsupervised geometric matching method for images of strong transformation variation and high noise level. The training code, trained model, and datasets are available in our open-source software AITom.
| [' Min Xu', 'Xiangrui Zeng'] | 2020-06-01 | null | null | null | cvpr-2020-6 | ['geometric-matching', 'electron-tomography'] | ['computer-vision', 'medical'] | [ 5.73602080e-01 -3.51102769e-01 4.44890589e-01 -3.62895638e-01
-9.36251640e-01 -4.51371491e-01 4.25635189e-01 2.38819197e-01
-4.94650632e-01 5.76366782e-01 -1.20455064e-01 -2.15816513e-01
-1.93500221e-01 -4.01683837e-01 -8.52107286e-01 -1.11839700e+00
-2.17408046e-01 8.07455719e-01 1.02330536e-01 -4.54377457e-02
6.63196266e-01 8.30532312e-01 -9.82063413e-01 2.20514610e-01
7.20681727e-01 7.09524333e-01 5.25482893e-01 9.71002698e-01
2.22543418e-01 2.75195926e-01 -1.37784734e-01 9.27239135e-02
4.16662425e-01 -3.98889959e-01 -8.56213212e-01 -2.89608706e-02
9.17903900e-01 1.07627660e-01 -3.94553803e-02 1.07227731e+00
9.52629983e-01 -1.17968723e-01 8.30316246e-01 -7.23349392e-01
-3.97160590e-01 -1.33694485e-01 -5.32403052e-01 4.52312201e-01
1.90459758e-01 3.28963310e-01 5.29177308e-01 -1.00734282e+00
1.14470041e+00 7.91716933e-01 7.91195452e-01 3.72199982e-01
-1.73935974e+00 -2.46331185e-01 -3.70396733e-01 4.83351275e-02
-1.02996409e+00 -4.01306093e-01 6.85584486e-01 -6.24125242e-01
1.39055681e+00 3.67265046e-01 5.15993059e-01 6.73805058e-01
9.00206149e-01 -7.07788914e-02 1.44753397e+00 -5.56298316e-01
1.70462847e-01 -4.83483970e-01 1.44241691e-01 9.06169713e-01
-2.54351851e-02 1.66067228e-01 -4.76363868e-01 -2.42453098e-01
1.04703772e+00 -2.26008892e-02 -2.21001446e-01 -7.55879402e-01
-1.54403484e+00 2.57061124e-01 6.48345947e-01 3.24155152e-01
-1.39121220e-01 1.10281117e-01 4.38679248e-01 4.38213319e-01
4.35534209e-01 9.99994814e-01 -2.94298470e-01 -6.76122680e-02
-8.07703137e-01 2.43796036e-01 2.57437468e-01 8.54813516e-01
8.92083287e-01 -2.58543730e-01 1.21640630e-01 4.96712208e-01
-2.13061899e-01 3.45420629e-01 2.31349513e-01 -1.12227249e+00
2.52744168e-01 8.01360965e-01 5.89720495e-02 -1.09027123e+00
-8.36700737e-01 -3.90003711e-01 -1.16045105e+00 2.51801878e-01
5.96337736e-01 2.38678545e-01 -1.15305281e+00 1.54532945e+00
3.54764611e-01 -1.61822699e-02 -3.19626927e-01 9.45671260e-01
6.06224895e-01 3.18848997e-01 -4.13329691e-01 -3.66622180e-01
1.20818782e+00 -6.98916614e-01 -4.22459632e-01 8.15545693e-02
9.62728918e-01 -8.74173403e-01 1.01646268e+00 -5.12959585e-02
-1.07005453e+00 -2.27960929e-01 -9.58856761e-01 -3.28368813e-01
-4.74716365e-01 -1.19186088e-01 4.03665423e-01 2.44140625e-01
-1.04895067e+00 9.29374933e-01 -1.00599372e+00 -7.29195416e-01
6.63056791e-01 5.88567138e-01 -6.85447693e-01 1.34858638e-01
-4.54461008e-01 9.46764171e-01 1.45898445e-03 -1.91216990e-01
-7.40790367e-01 -1.14112973e+00 -6.15083694e-01 -1.66382775e-01
-6.65439516e-02 -1.15416026e+00 6.77686453e-01 -4.29573148e-01
-1.49288368e+00 1.38021135e+00 -2.75349855e-01 -5.42824984e-01
4.56901610e-01 1.55062228e-01 1.22137614e-01 2.06382602e-01
1.42582268e-01 5.30023694e-01 3.10510278e-01 -1.06595039e+00
7.82460272e-02 -8.04435790e-01 -4.22841311e-01 2.38208160e-01
9.89030823e-02 1.44190326e-01 -4.09407541e-02 -3.94664764e-01
4.32451874e-01 -7.49658406e-01 -5.07206082e-01 7.58081377e-02
-4.28463995e-01 5.80948710e-01 9.43992019e-01 -4.57150280e-01
7.05348790e-01 -1.66131616e+00 3.60105634e-01 6.27004057e-02
4.83524442e-01 -4.70052958e-02 6.33328259e-02 4.99062181e-01
-2.41600156e-01 -2.26557031e-01 -6.20430529e-01 -3.51151466e-01
-3.22265238e-01 -1.11909226e-01 -7.25641176e-02 7.84233093e-01
-1.88245237e-01 1.03260469e+00 -9.93514955e-01 -4.13961291e-01
4.30531472e-01 3.68377149e-01 -4.65127766e-01 1.74894899e-01
1.21411175e-01 9.61195588e-01 1.01236828e-01 5.95266223e-01
8.61928821e-01 -5.41382194e-01 2.40246311e-01 -6.29146874e-01
-2.57831812e-01 9.01887938e-02 -7.07970679e-01 1.99106932e+00
-2.80953258e-01 6.29761040e-01 1.83768757e-02 -1.04730380e+00
8.93107533e-01 -1.38032064e-01 7.11429119e-01 -8.55715990e-01
7.04962611e-02 3.06944191e-01 3.77940796e-02 -2.63109058e-01
3.39464813e-01 -6.67807981e-02 -3.91476275e-03 5.18713295e-01
1.38348222e-01 -4.51914817e-01 4.82866280e-02 2.10154876e-01
1.27244186e+00 8.05985704e-02 2.44384140e-01 -9.56463337e-01
3.79095763e-01 7.08056837e-02 3.24322313e-01 6.88750744e-01
-4.90322821e-02 8.96894932e-01 2.72242248e-01 -9.67299700e-01
-1.82726490e+00 -9.08113480e-01 -4.27770108e-01 5.61596274e-01
2.69384414e-01 -3.67391020e-01 -9.60620403e-01 -1.98890284e-01
-2.89904445e-01 -1.13500051e-01 -6.67322040e-01 1.45790383e-01
-6.94154799e-01 -1.16804886e+00 3.54889572e-01 3.38246822e-01
4.62740690e-01 -6.91296220e-01 -7.82802820e-01 2.24869817e-01
1.07533641e-01 -1.11345994e+00 -6.41886353e-01 4.95540828e-01
-1.01297414e+00 -1.13839734e+00 -4.46519136e-01 -7.86348343e-01
1.29490411e+00 3.36822242e-01 1.10686851e+00 3.75106977e-03
-7.76752293e-01 2.94855591e-02 1.47468030e-01 -1.47283189e-02
-1.36023015e-01 9.99282300e-02 2.62356639e-01 -4.93685395e-01
1.41158491e-01 -1.06304097e+00 -8.91657054e-01 7.02050149e-01
-6.11506581e-01 5.20401299e-01 3.12736243e-01 1.24012017e+00
1.22558963e+00 -3.85498434e-01 9.19978544e-02 -9.09594119e-01
4.17741477e-01 2.90235281e-01 -7.45770872e-01 7.55123124e-02
-4.17309403e-01 1.30714187e-02 9.61838365e-01 -8.33480060e-02
-5.83285987e-01 3.10559124e-01 8.52040499e-02 -3.35061103e-01
-2.07660601e-01 1.18690826e-01 -3.57347876e-02 -6.33550525e-01
9.29130018e-01 3.16732377e-01 2.20447138e-01 -1.43881649e-01
7.14318529e-02 1.81535706e-01 8.18380177e-01 -7.22566724e-01
7.09443331e-01 9.81624126e-01 6.19214714e-01 -7.89337397e-01
-5.70523322e-01 -5.47887921e-01 -1.12118495e+00 -1.37343511e-01
8.66797984e-01 -4.50697571e-01 -7.72123575e-01 6.47159696e-01
-1.01007617e+00 -6.08882129e-01 -5.89565299e-02 2.74879485e-01
-9.86397624e-01 5.40302634e-01 -6.65633738e-01 -9.59006175e-02
-7.69086540e-01 -1.31009626e+00 1.25635004e+00 4.19942625e-02
-2.01474026e-01 -1.09169376e+00 3.48742217e-01 2.08828881e-01
6.02945685e-01 5.59558690e-01 1.09125972e+00 -1.85539186e-01
-7.17181504e-01 2.16257963e-02 -3.71142834e-01 -3.49770010e-01
2.46701449e-01 1.26236109e-02 -8.01144898e-01 -6.30536318e-01
1.17254227e-01 -2.09044382e-01 7.87600219e-01 5.75392127e-01
1.21353006e+00 -2.12309994e-02 -4.42708671e-01 1.08605409e+00
1.53325713e+00 -3.86447124e-02 7.14454591e-01 5.41453779e-01
8.32854211e-01 4.30521846e-01 3.67627800e-01 5.02870269e-02
-1.06235459e-01 1.01233983e+00 5.19298196e-01 -3.81871223e-01
4.34492268e-02 1.66612238e-01 -1.42906210e-03 1.03453135e+00
-3.31012517e-01 1.30460992e-01 -9.73368943e-01 3.71362895e-01
-1.75864470e+00 -1.23667228e+00 -2.05332130e-01 2.40018344e+00
6.00233555e-01 -3.99877615e-02 -6.17833361e-02 -2.24536046e-01
6.86494768e-01 1.82144642e-02 -6.17011130e-01 -3.63318801e-01
-2.34177738e-01 1.98901609e-01 6.39642894e-01 6.50002956e-01
-1.12156236e+00 7.21637607e-01 6.14834452e+00 7.52621949e-01
-1.12106693e+00 1.19664874e-02 9.78386223e-01 3.56924981e-02
-1.07641436e-01 8.41096863e-02 -6.09418869e-01 4.62499022e-01
5.63779891e-01 -5.39720096e-02 4.28116739e-01 3.77991766e-01
4.46943521e-01 -1.72587350e-01 -1.21753097e+00 1.16299307e+00
-1.07355215e-01 -1.90117395e+00 3.79534289e-02 2.94276685e-01
9.21591878e-01 2.73244768e-01 -3.27112190e-02 -5.44510722e-01
9.03645083e-02 -1.18756104e+00 1.31481498e-01 6.93935156e-01
9.77674842e-01 -6.98113859e-01 6.38252020e-01 2.14735582e-01
-1.13853371e+00 4.88651782e-01 -8.25475812e-01 5.53176627e-02
2.90501505e-01 8.50990236e-01 -7.19420850e-01 7.86484659e-01
6.20912910e-01 6.50521815e-01 -4.36875433e-01 1.06616318e+00
3.66341561e-01 6.14171326e-02 -4.15156394e-01 1.89482749e-01
2.22806275e-01 -5.39011657e-01 6.96613252e-01 1.30872750e+00
3.14954460e-01 2.88458858e-02 -2.91308966e-02 9.19333994e-01
-2.42996305e-01 -3.52751873e-02 -7.41557300e-01 3.10099572e-01
3.78257155e-01 1.47382164e+00 -1.01244771e+00 -1.12922564e-01
1.83765858e-01 1.02963603e+00 6.07498825e-01 3.66763100e-02
-6.69891417e-01 -5.09659052e-01 5.86277604e-01 3.73400092e-01
-4.07603681e-02 -4.80078548e-01 -5.34135222e-01 -1.04661465e+00
-6.27969280e-02 -5.70232809e-01 6.83823451e-02 -9.12361979e-01
-1.39217341e+00 5.70655644e-01 -3.24311167e-01 -1.16644466e+00
3.52142639e-02 -8.39874983e-01 -7.70572066e-01 7.69534290e-01
-1.07073486e+00 -1.04645133e+00 -6.24919653e-01 2.47680023e-01
1.79745421e-01 -5.13722673e-02 1.08622253e+00 1.41413525e-01
-3.43067914e-01 4.11333948e-01 6.91209853e-01 -6.11290038e-02
8.60386729e-01 -1.41986060e+00 6.33384705e-01 6.33995831e-01
-1.03922032e-01 7.42674887e-01 7.16324687e-01 -4.64885384e-01
-1.54593968e+00 -1.02686548e+00 7.68335462e-01 -6.60483778e-01
5.75080514e-01 -6.20475173e-01 -9.74460185e-01 4.33501929e-01
2.57665664e-01 2.39179432e-01 5.67762434e-01 -3.31858546e-01
-1.46231860e-01 -6.26099631e-02 -1.39643168e+00 7.09568381e-01
1.40433383e+00 -7.67223120e-01 -2.00717658e-01 6.93209946e-01
4.85703260e-01 -9.02599812e-01 -1.15721631e+00 4.05673116e-01
5.40892541e-01 -1.12590265e+00 9.48860884e-01 -4.25345093e-01
4.57896173e-01 -5.64207494e-01 -1.18903510e-01 -1.32891691e+00
-4.70835119e-01 -8.60410452e-01 2.92019278e-01 5.87109685e-01
3.33216578e-01 -6.34203911e-01 1.03336132e+00 2.59065896e-01
-5.39569914e-01 -1.03100824e+00 -1.10838604e+00 -6.71046317e-01
9.97407809e-02 8.30221772e-02 4.24040169e-01 1.10349560e+00
6.75801784e-02 2.12671965e-01 -1.70398906e-01 2.41275609e-01
1.01384270e+00 3.97205979e-01 1.01795447e+00 -8.38791609e-01
-2.30405051e-02 -3.09775352e-01 -8.40325296e-01 -1.04406083e+00
-1.94301099e-01 -9.27742779e-01 -9.72396433e-02 -1.27224159e+00
6.83426619e-01 -1.32826790e-01 9.32816975e-03 9.58882272e-02
1.28683180e-01 4.24723566e-01 -1.55833557e-01 3.74451935e-01
-6.19603693e-01 4.13893819e-01 1.46371257e+00 -8.53537321e-02
-3.14392410e-02 -6.28607154e-01 -2.54721045e-01 4.73357081e-01
7.33262539e-01 -3.49155784e-01 -6.55247495e-02 -4.60930943e-01
9.89984348e-02 -2.54811615e-01 5.75316846e-01 -1.20389020e+00
7.12563813e-01 1.55957777e-03 5.76555550e-01 -7.33375490e-01
2.48112187e-01 -7.36834764e-01 4.08995658e-01 3.40358526e-01
-1.90312579e-01 2.65553951e-01 2.18881756e-01 3.14762414e-01
7.05002919e-02 1.75516307e-01 1.13122487e+00 -3.22063416e-01
-1.06440067e-01 4.62599128e-01 -3.01584005e-01 -7.01836571e-02
9.11415040e-01 -5.79161167e-01 -6.89858496e-01 7.75402132e-03
-6.98918939e-01 9.64328125e-02 1.28081918e+00 -5.15048981e-01
7.05170751e-01 -1.27600718e+00 -4.48303461e-01 2.42144510e-01
1.31510288e-01 2.99933970e-01 4.66315359e-01 1.12449920e+00
-9.95551646e-01 5.60207009e-01 -6.84534490e-01 -1.06722701e+00
-1.35656941e+00 2.71238327e-01 8.56047750e-01 -6.47854030e-01
-6.15516484e-01 5.95737338e-01 2.77777612e-01 -9.19687688e-01
-3.15214276e-01 -2.88788706e-01 2.94412643e-01 -6.39722943e-01
3.50922167e-01 3.05631220e-01 4.60527480e-01 -6.08713269e-01
-3.44231009e-01 1.21357214e+00 -4.64816332e-01 4.09492970e-01
1.59067798e+00 -1.29160643e-01 -3.44212145e-01 9.84924510e-02
1.28345668e+00 -3.25629652e-01 -1.23042119e+00 -5.35216741e-02
-2.44336396e-01 -5.30544281e-01 -1.63416952e-01 -4.74718273e-01
-6.95355654e-01 8.96171212e-01 7.42753923e-01 -1.26952708e-01
9.99077737e-01 -1.20607257e-01 5.80693543e-01 6.03088021e-01
6.53526902e-01 -9.62871492e-01 6.19142465e-02 6.44859791e-01
6.55742168e-01 -1.11653507e+00 3.81942630e-01 -4.38554972e-01
1.20278290e-02 1.10586464e+00 7.00505912e-01 -3.86654168e-01
2.72536665e-01 4.76160467e-01 -2.12211683e-02 -7.70578146e-01
-6.83529556e-01 3.06879729e-01 -6.20308854e-02 6.96594357e-01
4.01651233e-01 -2.24153042e-01 -1.01546623e-01 -1.42717540e-01
-1.48002908e-01 -2.54036367e-01 3.65421414e-01 9.47094560e-01
-4.12263542e-01 -9.17333484e-01 -1.62978381e-01 6.10218048e-01
-4.30818737e-01 -1.20747685e-01 -3.59810591e-01 5.05703211e-01
-2.72380739e-01 1.22816063e-01 3.04242700e-01 -3.27708006e-01
3.26959997e-01 -1.55470729e-01 9.36361492e-01 -4.27997053e-01
-5.98891318e-01 -4.70870659e-02 -1.61138833e-01 -6.87275589e-01
-7.16819048e-01 -3.28178495e-01 -1.33123553e+00 -5.32568038e-01
-2.89176017e-01 -2.91906688e-02 3.96612912e-01 7.67350078e-01
8.76488030e-01 4.05373484e-01 6.30722880e-01 -1.34746742e+00
-2.61620415e-04 -8.37477028e-01 -3.19056153e-01 4.75592643e-01
1.20638590e-02 -4.94160056e-01 -3.59877348e-01 1.65821329e-01] | [13.52585220336914, -3.0498239994049072] |
980a3e39-60c1-411e-b86d-8e8d04cb882f | sparse-lidar-assisted-self-supervised-stereo | 2112.15355 | null | https://arxiv.org/abs/2112.15355v1 | https://arxiv.org/pdf/2112.15355v1.pdf | Sparse LiDAR Assisted Self-supervised Stereo Disparity Estimation | Deep stereo matching has made significant progress in recent years. However, state-of-the-art methods are based on expensive 4D cost volume, which limits their use in real-world applications. To address this issue, 3D correlation maps and iterative disparity updates have been proposed. Regarding that in real-world platforms, such as self-driving cars and robots, the Lidar is usually installed. Thus we further introduce the sparse Lidar point into the iterative updates, which alleviates the burden of network updating the disparity from zero states. Furthermore, we propose training the network in a self-supervised way so that it can be trained on any captured data for better generalization ability. Experiments and comparisons show that the presented method is effective and achieves comparable results with related methods. | ['Zhengguo Li', 'Peter C. Y. Chen', 'Xingming Wu', 'Weihai Chen', 'Xiaoming Zhao'] | 2021-12-31 | null | null | null | null | ['stereo-matching-1'] | ['computer-vision'] | [-6.32582903e-02 -2.23526821e-01 -2.75875151e-01 -5.06854475e-01
-1.60562117e-02 1.08972289e-01 3.71700227e-01 -1.61142811e-01
-6.46775424e-01 6.87236965e-01 -4.74089801e-01 -1.88103288e-01
1.46805674e-01 -1.04789698e+00 -7.91554272e-01 -5.16935706e-01
1.95026785e-01 4.24283713e-01 6.42520905e-01 -2.12779135e-01
3.01782042e-01 4.27342027e-01 -1.87771690e+00 -3.26777667e-01
1.16064560e+00 1.04728043e+00 6.11938238e-01 -1.58514410e-01
-2.68196493e-01 3.93067449e-01 -1.98124811e-01 -3.04857612e-01
6.16601646e-01 4.60112281e-02 -1.24738783e-01 -6.95428392e-03
5.51845253e-01 -7.33170509e-01 -7.02935278e-01 1.34129012e+00
4.27503616e-01 1.20367274e-01 1.45718411e-01 -1.25864732e+00
-2.71127939e-01 1.29448116e-01 -7.49460459e-01 9.94210970e-03
-2.79539172e-02 2.13591859e-01 5.81927598e-01 -9.49483573e-01
4.41200614e-01 1.35033143e+00 7.40333438e-01 4.19444472e-01
-9.78945434e-01 -1.28889477e+00 1.31857738e-01 5.73007822e-01
-1.35928988e+00 -3.63996059e-01 1.03685594e+00 -2.88766533e-01
8.41196299e-01 -4.61367100e-01 7.54410207e-01 7.20975220e-01
1.58748254e-01 6.71205401e-01 9.20675337e-01 -1.03262728e-02
2.26384342e-01 6.34015948e-02 -1.14778012e-01 5.97830057e-01
5.98641515e-01 2.78593659e-01 -4.91817266e-01 3.17077279e-01
9.52957273e-01 2.51266807e-01 6.29898801e-04 -8.01832914e-01
-9.82367039e-01 8.36872220e-01 7.64303565e-01 1.47807986e-01
-3.11745793e-01 1.52912244e-01 3.63191634e-01 3.36469747e-02
3.29330564e-01 -1.16097011e-01 -5.10247983e-02 -7.82329366e-02
-8.06114018e-01 1.38581365e-01 3.25716555e-01 1.03035140e+00
1.33514559e+00 1.51685327e-01 5.08825004e-01 8.46892595e-01
4.05804783e-01 6.17280841e-01 4.30297464e-01 -1.06743479e+00
7.57780194e-01 7.77805567e-01 6.47170246e-02 -1.22159469e+00
-4.64667976e-01 -5.81884444e-01 -1.26328838e+00 3.47790897e-01
2.21070014e-02 -3.63092422e-02 -7.06881046e-01 1.65638745e+00
3.76197994e-01 5.56138754e-01 -2.26197727e-02 1.08996582e+00
5.43055594e-01 4.99597549e-01 -1.99264973e-01 -1.70099400e-02
7.71429777e-01 -7.19288886e-01 -7.36119151e-01 -6.09005272e-01
3.38217944e-01 -6.32238686e-01 8.13261092e-01 2.61939794e-01
-8.63258779e-01 -9.90660548e-01 -1.39000356e+00 -5.19212596e-02
-2.22698331e-01 -5.47251524e-03 7.59468675e-01 3.92081708e-01
-8.29746544e-01 7.08222985e-01 -1.09995258e+00 -3.99388134e-01
4.77985203e-01 6.12954974e-01 -2.86856145e-01 -1.90295964e-01
-1.27990186e+00 1.08827519e+00 4.89168286e-01 3.90563011e-01
-5.35721123e-01 -4.31922555e-01 -9.92823720e-01 -2.01756805e-01
2.29136288e-01 -6.96624875e-01 1.14248991e+00 -5.09098947e-01
-1.69419301e+00 6.29904389e-01 -2.95467108e-01 -6.54226422e-01
5.95733523e-01 -3.61530960e-01 -2.71753162e-01 -1.44707143e-01
1.90940753e-01 1.00692236e+00 5.41693926e-01 -1.15105808e+00
-9.36119020e-01 -5.82920194e-01 2.20560044e-01 2.90746868e-01
-4.76005495e-01 -6.63443327e-01 -6.58118606e-01 -2.47055843e-01
6.26845121e-01 -1.09733105e+00 -4.49719340e-01 3.75641078e-01
-7.38953501e-02 -7.11592287e-02 1.12077367e+00 -8.81355628e-02
8.13683689e-01 -2.16750765e+00 -1.95728123e-01 6.11646399e-02
1.47158364e-02 3.10368985e-01 1.48612157e-01 9.61674824e-02
2.86332160e-01 -4.42260593e-01 -1.15260392e-01 -5.43354154e-01
-1.64249480e-01 4.87587810e-01 -8.61351043e-02 6.12387240e-01
1.60805061e-01 4.71487671e-01 -7.96758711e-01 -5.61738133e-01
6.90847754e-01 4.62248564e-01 -6.38454497e-01 7.77650923e-02
1.43424034e-01 5.49798310e-01 -5.26708484e-01 3.34270120e-01
1.21070755e+00 -3.75043117e-02 -4.65779146e-03 -3.96472692e-01
-4.71375197e-01 3.40933383e-01 -1.42801523e+00 2.03896022e+00
-6.60661578e-01 6.28668785e-01 -2.00712699e-02 -1.16078424e+00
1.28830922e+00 -1.99275121e-01 4.12328720e-01 -9.90897179e-01
2.24020332e-01 3.52614999e-01 -2.24450380e-02 -1.86360553e-01
6.37299955e-01 -4.29937653e-02 2.68780500e-01 -1.07722051e-01
-3.27178448e-01 -2.34712809e-01 1.97854415e-01 -2.02401817e-01
6.27567887e-01 2.87476301e-01 1.59480393e-01 -1.34348214e-01
8.42107058e-01 1.19589552e-01 1.02865338e+00 2.71764159e-01
-1.53262705e-01 4.42603916e-01 -2.05282316e-01 -5.27234614e-01
-9.10240233e-01 -9.90326941e-01 -2.88478851e-01 2.40621552e-01
9.04722929e-01 -1.41995847e-02 -4.69021916e-01 -2.48815715e-01
2.36915544e-01 3.70129108e-01 -9.69814658e-02 -1.49183065e-01
-9.11413670e-01 -3.16424131e-01 1.62739858e-01 6.22828901e-01
1.29009914e+00 -5.99504709e-01 -9.16806102e-01 4.42910671e-01
-1.25250861e-01 -1.38121510e+00 -9.30891037e-02 -3.05738449e-02
-1.35834754e+00 -9.32336032e-01 -4.45964485e-01 -9.08137083e-01
6.73416913e-01 7.92347074e-01 6.05429173e-01 -8.76299515e-02
-6.36257380e-02 -2.19555855e-01 9.01171491e-02 -2.62616664e-01
-4.08774279e-02 1.62965029e-01 3.12884271e-01 -1.82146609e-01
4.86366212e-01 -9.02653277e-01 -7.65755892e-01 4.75635856e-01
-5.45886457e-01 2.40557671e-01 6.74805164e-01 7.28083491e-01
6.46245956e-01 1.07790858e-01 4.48478311e-01 -5.88246763e-01
2.73517400e-01 -5.66311069e-02 -1.14416170e+00 -3.62042278e-01
-6.94466174e-01 9.09588262e-02 6.49756908e-01 -2.32417047e-01
-1.04575098e+00 3.44847649e-01 -2.44430989e-01 -7.11121082e-01
-3.18174716e-03 2.84616739e-01 -4.35631052e-02 -2.46461883e-01
3.73952091e-01 1.84943587e-01 3.02040488e-01 -4.02272582e-01
8.49170163e-02 7.20363259e-01 7.03163028e-01 -2.59773731e-01
1.08877504e+00 7.34809279e-01 1.86001137e-01 -6.22937977e-01
-5.45570433e-01 -4.31631863e-01 -5.97650468e-01 -2.44178846e-01
6.39048994e-01 -1.26328480e+00 -7.85912991e-01 6.16663277e-01
-1.30302346e+00 -4.81265336e-02 -3.90351713e-02 8.37793291e-01
-4.66709256e-01 5.26484907e-01 -4.88166422e-01 -6.34366512e-01
-1.71419889e-01 -1.28117990e+00 8.19964826e-01 5.29823244e-01
1.60517395e-01 -6.66687131e-01 5.04732430e-02 1.05101779e-01
4.54733372e-01 -2.93000564e-02 5.19450307e-01 -4.97543141e-02
-1.04789650e+00 -1.29539579e-01 -4.09877837e-01 3.61075997e-01
1.54964030e-01 -2.64780551e-01 -8.51345539e-01 -2.97530293e-01
-2.13004965e-02 -1.86450079e-01 6.55674100e-01 1.95819467e-01
1.13309538e+00 3.17796469e-01 -5.87813437e-01 7.07122982e-01
1.42287004e+00 3.56866062e-01 5.94851613e-01 7.10783064e-01
5.24547338e-01 5.13165951e-01 9.48330760e-01 3.40408176e-01
6.95344985e-01 6.86123192e-01 8.12031090e-01 -1.67238221e-01
3.21656242e-02 -3.50908637e-01 6.71338961e-02 9.24884319e-01
6.55663982e-02 2.51449198e-01 -7.97130764e-01 3.73401135e-01
-2.02166581e+00 -7.87111461e-01 2.43226322e-03 2.25334048e+00
4.47191805e-01 5.56621790e-01 -4.12170559e-01 9.89803076e-02
9.49021459e-01 2.37410143e-01 -9.23725963e-01 -5.55012971e-02
1.40896216e-02 3.20956036e-02 6.85973346e-01 2.42528334e-01
-1.03974509e+00 8.62306952e-01 5.94910145e+00 5.88740110e-01
-1.48709249e+00 8.37045386e-02 3.11494708e-01 6.60795644e-02
-1.55856490e-01 -3.14423703e-02 -9.52102840e-01 4.90610421e-01
4.53828275e-01 -1.25752628e-01 1.88601285e-01 1.04601288e+00
3.99283439e-01 -2.66885847e-01 -9.58198786e-01 1.36113870e+00
-1.64101869e-01 -1.28398526e+00 -1.13275170e-01 1.06833942e-01
7.85849929e-01 2.92953670e-01 5.66145256e-02 4.00811672e-01
2.56379128e-01 -3.88477951e-01 5.54315984e-01 1.70362607e-01
6.72402442e-01 -8.22965860e-01 9.30662692e-01 6.84196532e-01
-1.26543438e+00 -2.03445461e-02 -7.88147032e-01 -2.94693083e-01
3.62387270e-01 8.99522066e-01 -5.43734550e-01 6.39462531e-01
8.09653759e-01 1.02509224e+00 -3.06271404e-01 1.14880061e+00
-6.33719936e-02 3.66379097e-02 -6.05556488e-01 -9.00503155e-03
3.31644863e-01 -4.92025077e-01 2.81479746e-01 6.34025156e-01
6.65770113e-01 -1.74450800e-01 4.09785748e-01 7.44000435e-01
1.92662477e-02 -1.33560568e-01 -8.08943152e-01 5.66566348e-01
6.34855509e-01 1.05226207e+00 -4.37227815e-01 -3.40073138e-01
-6.08633935e-01 6.14559829e-01 3.05352986e-01 4.07886766e-02
-8.66752207e-01 -4.40516025e-01 8.84723127e-01 1.50540531e-01
3.14537793e-01 -5.73048353e-01 -3.01165491e-01 -1.08059096e+00
1.99926913e-01 -3.85337204e-01 -5.05347662e-02 -6.75054252e-01
-1.05973136e+00 4.44015115e-01 -1.01957604e-01 -1.73024309e+00
-3.59322846e-01 -4.52674419e-01 -5.03734887e-01 6.98943377e-01
-2.04358101e+00 -6.71335697e-01 -8.07466745e-01 5.66779315e-01
5.11086762e-01 -9.62436199e-02 3.13623607e-01 7.15166032e-01
-7.40229666e-01 3.60849351e-01 4.87229638e-02 -8.88230428e-02
6.98386312e-01 -6.67480171e-01 5.67248046e-01 8.46669674e-01
-2.85680115e-01 5.99284947e-01 6.48428321e-01 -5.12886763e-01
-1.35613453e+00 -1.08652163e+00 5.85127711e-01 4.21884537e-01
5.66281915e-01 -2.16275990e-01 -8.12075734e-01 3.42400342e-01
1.60000086e-01 1.59832463e-01 3.95589843e-02 -1.45417117e-02
-7.63219744e-02 -6.96635425e-01 -1.09731328e+00 6.13009274e-01
1.38846874e+00 -3.89533758e-01 -4.96921659e-01 6.79628104e-02
4.60531116e-01 -7.76209950e-01 -4.46026653e-01 8.05670440e-01
4.37395066e-01 -1.26492786e+00 7.53449380e-01 2.22847998e-01
1.89954236e-01 -6.70789480e-01 -6.51897267e-02 -1.11770868e+00
-1.99902117e-01 -2.16441765e-01 -2.32196432e-02 1.00647914e+00
-1.16178645e-02 -1.07034624e+00 1.18403614e+00 2.23592892e-01
-2.70224154e-01 -7.26967275e-01 -1.14125252e+00 -8.53252411e-01
-2.74945498e-01 -4.18219030e-01 7.05283046e-01 6.19079411e-01
-3.91168773e-01 2.89047837e-01 -1.42070726e-01 3.22208166e-01
7.93043196e-01 3.36809546e-01 1.07850063e+00 -1.42682612e+00
1.25465930e-01 -2.84075975e-01 -8.87481213e-01 -1.71040750e+00
2.98570186e-01 -5.99251211e-01 1.80232704e-01 -1.50046253e+00
-3.53423879e-02 -8.44552934e-01 -1.66868880e-01 8.25481638e-02
-1.05025265e-02 2.46771097e-01 7.87282512e-02 3.43947977e-01
-3.17102820e-01 8.56561661e-01 1.16627359e+00 -2.52422392e-01
-1.06853217e-01 7.13181635e-03 -2.30270386e-01 8.61472368e-01
8.98199856e-01 -3.23557615e-01 -5.84440291e-01 -6.98825538e-01
-1.08152278e-01 -1.43109038e-01 2.60475516e-01 -1.63279760e+00
6.43563569e-01 -1.70854274e-02 2.08944708e-01 -1.21816635e+00
6.82676077e-01 -1.05631506e+00 1.03222631e-01 7.12309182e-01
2.82469869e-01 2.61497527e-01 2.10283533e-01 4.70483392e-01
-6.03397667e-01 -1.05538055e-01 8.86624038e-01 3.27181295e-02
-8.97129476e-01 6.33530080e-01 -6.49462044e-02 -1.80552110e-01
1.01214838e+00 -5.97106218e-01 -1.40416890e-01 -2.92238414e-01
-6.86919913e-02 3.80038112e-01 5.79266965e-01 4.42126423e-01
5.97554922e-01 -1.50373733e+00 -3.10573936e-01 3.50520670e-01
-2.55114064e-02 6.10623479e-01 3.66041720e-01 6.51839852e-01
-6.17475033e-01 5.22794247e-01 -4.58223253e-01 -1.07938576e+00
-8.72466445e-01 3.66382509e-01 2.44183838e-01 -4.43536937e-02
-6.72047913e-01 2.49566749e-01 2.35485300e-01 -4.61419493e-01
2.76114583e-01 -3.93919557e-01 -1.53626382e-01 -2.16458768e-01
1.27271265e-01 3.49835664e-01 -2.12807227e-02 -4.89203066e-01
-3.44850689e-01 9.79410470e-01 -1.43202180e-02 7.96434432e-02
1.17106378e+00 -2.54760146e-01 1.19313836e-01 4.16252911e-01
1.22605646e+00 -3.58524293e-01 -1.39861143e+00 -3.79934043e-01
-2.11230025e-01 -6.01361394e-01 1.52195990e-01 2.45443970e-01
-1.38170183e+00 1.08529723e+00 8.86058569e-01 -2.15891391e-01
9.11949515e-01 -5.80768824e-01 1.18851089e+00 8.62088203e-01
8.78017604e-01 -1.19466400e+00 -1.10918634e-01 6.36353433e-01
4.17538345e-01 -1.45071054e+00 1.85919300e-01 -5.52576959e-01
-2.02982694e-01 1.06702793e+00 1.06310582e+00 -3.54397625e-01
6.85446680e-01 2.33303443e-01 1.66063726e-01 1.41023964e-01
-3.78151566e-01 -2.00229838e-01 -2.70394087e-01 5.73655784e-01
3.59466970e-02 -2.69067436e-01 -2.84788221e-01 2.33027060e-02
-2.44759247e-01 1.90740988e-01 2.30705142e-01 1.04670262e+00
-5.15734792e-01 -1.11992872e+00 -1.84386149e-01 2.61645973e-01
3.13401856e-02 1.87100053e-01 3.25104535e-01 9.54082251e-01
2.21971110e-01 7.09529161e-01 3.86503011e-01 -4.71738368e-01
6.22267604e-01 -2.63406605e-01 3.82900596e-01 -3.54027987e-01
-5.41687980e-02 -1.90702304e-01 -9.46034491e-02 -6.74766421e-01
-6.70701325e-01 -5.98947942e-01 -1.46168268e+00 -4.44535971e-01
-4.96386409e-01 -8.20170939e-02 8.51784706e-01 7.83417106e-01
5.54117203e-01 2.16894314e-01 7.95586944e-01 -1.09805000e+00
-5.27046263e-01 -7.48536706e-01 -3.02411199e-01 1.68248117e-01
1.64901510e-01 -1.16478884e+00 -2.36184254e-01 -2.54658312e-01] | [8.485450744628906, -2.3708674907684326] |
5c03fe43-23b6-4194-a7b2-d1cf685827a8 | incomplete-multi-view-clustering-via-graph | 1809.05998 | null | http://arxiv.org/abs/1809.05998v1 | http://arxiv.org/pdf/1809.05998v1.pdf | Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization | Clustering with incomplete views is a challenge in multi-view clustering. In
this paper, we provide a novel and simple method to address this issue.
Specifically, the proposed method simultaneously exploits the local information
of each view and the complementary information among views to learn the common
latent representation for all samples, which can greatly improve the
compactness and discriminability of the obtained representation. Compared with
the conventional graph embedding methods, the proposed method does not
introduce any extra regularization term and corresponding penalty parameter to
preserve the local structure of data, and thus does not increase the burden of
extra parameter selection. By imposing the orthogonal constraint on the basis
matrix of each view, the proposed method is able to handle the out-of-sample.
Moreover, the proposed method can be viewed as a unified framework for
multi-view learning since it can handle both incomplete and complete multi-view
clustering and classification tasks. Extensive experiments conducted on several
multi-view datasets prove that the proposed method can significantly improve
the clustering performance. | ['Jie Wen', 'Zuofeng Zhong', 'Yong Xu', 'Zheng Zhang'] | 2018-09-17 | null | null | null | null | ['incomplete-multi-view-clustering'] | ['computer-vision'] | [-2.62182236e-01 -2.95555472e-01 -3.86325091e-01 -1.99395180e-01
-5.27704477e-01 -5.38730860e-01 3.49672049e-01 1.85568035e-01
-8.70113671e-02 1.87164053e-01 8.16951469e-02 2.75014102e-01
-3.82720590e-01 -6.23436451e-01 -7.57673010e-02 -1.24439740e+00
4.81757492e-01 2.67802507e-01 2.88996883e-02 2.70109653e-01
6.05387846e-03 2.36404762e-01 -1.25476635e+00 3.32873315e-02
9.42827106e-01 8.32013130e-01 4.10390854e-01 -6.22396097e-02
7.00978041e-02 4.56509322e-01 -1.86406046e-01 -1.16924614e-01
1.04443632e-01 -3.68770540e-01 -3.99421453e-01 7.39004314e-01
1.93791360e-01 5.30657582e-02 -2.51314551e-01 1.12026477e+00
5.65317929e-01 2.24518165e-01 6.19741619e-01 -1.23294353e+00
-5.15000820e-01 3.34333807e-01 -1.15794849e+00 5.68240806e-02
4.28256057e-02 -3.79973859e-01 1.12096977e+00 -9.73820865e-01
5.58750510e-01 1.15048802e+00 3.36719543e-01 1.56562537e-01
-1.25235140e+00 -5.55780292e-01 5.45735598e-01 3.23832721e-01
-1.56208742e+00 -3.68391633e-01 1.17796385e+00 -4.51355606e-01
7.47644529e-02 1.13277942e-01 6.87916994e-01 6.83341920e-01
-3.03995788e-01 9.05587971e-01 1.13624871e+00 -1.34079441e-01
2.86025465e-01 2.42296830e-01 2.52424717e-01 7.35334218e-01
4.30387497e-01 -4.57461119e-01 -2.03607962e-01 -4.00604725e-01
4.67406571e-01 4.91076708e-01 -7.07632482e-01 -1.18456364e+00
-1.29543948e+00 9.34330046e-01 2.78871536e-01 4.81178701e-01
-2.35468417e-01 -2.78617293e-01 4.30795431e-01 -1.39547825e-01
5.02936661e-01 -2.50174999e-01 8.04765299e-02 2.36239284e-01
-8.15570414e-01 -2.97924489e-01 4.80117708e-01 9.63224590e-01
8.13801050e-01 5.81600182e-02 2.39610463e-01 1.02200592e+00
3.98312032e-01 4.39213097e-01 3.49191874e-01 -7.50204384e-01
7.27343202e-01 9.52463150e-01 -5.68797924e-02 -1.51313639e+00
-3.56301039e-01 -4.58280683e-01 -1.16089523e+00 -2.11554885e-01
1.49375573e-01 -9.86441374e-02 -4.52257544e-01 1.56885386e+00
6.15242898e-01 1.53534725e-01 -5.76542225e-03 7.79999733e-01
7.29274213e-01 6.80612564e-01 -4.13222581e-01 -5.38236201e-01
1.24131477e+00 -9.46082592e-01 -9.00363386e-01 -2.53866352e-02
3.47591877e-01 -7.02273309e-01 6.54414296e-01 3.05885553e-01
-8.63416970e-01 -5.24554014e-01 -1.20041680e+00 3.30500215e-01
-3.14503722e-02 4.99500096e-01 5.48887253e-01 4.31356400e-01
-6.22177482e-01 1.28003091e-01 -9.48237360e-01 -3.16368401e-01
2.54554868e-01 3.26145083e-01 -6.62351429e-01 -4.75113839e-01
-5.72544396e-01 2.52708286e-01 6.66337013e-01 2.28940859e-01
-4.54952955e-01 -3.92941386e-01 -8.37478876e-01 2.04234555e-01
6.16583169e-01 -5.32007933e-01 3.78361076e-01 -5.98305404e-01
-1.12551343e+00 5.04710495e-01 -4.62290734e-01 3.10822994e-01
2.53956020e-01 1.59417167e-02 -3.88043791e-01 4.67878073e-01
1.52717590e-01 6.18119203e-02 8.61086011e-01 -1.69134152e+00
-3.71202588e-01 -8.06131482e-01 -1.47522315e-01 4.21526462e-01
-7.43612051e-01 -3.57975692e-01 -8.77630889e-01 -6.26265407e-01
7.10282922e-01 -9.81169164e-01 -1.88608840e-01 -2.01410830e-01
-2.47603342e-01 -1.00869365e-01 1.12864006e+00 -4.15648103e-01
1.21522963e+00 -2.40866470e+00 6.74943507e-01 2.98468918e-01
3.68990362e-01 1.36326477e-01 6.22410364e-02 7.18265831e-01
-9.75456461e-02 -1.38426110e-01 -2.79515088e-01 -3.22041094e-01
-2.48652428e-01 2.60202199e-01 2.05707416e-01 8.54054868e-01
-2.89679587e-01 4.43094850e-01 -8.58404100e-01 -6.35897636e-01
4.06059444e-01 5.85514903e-01 -4.99378175e-01 1.48913369e-01
3.19620669e-01 5.72648704e-01 -6.32178426e-01 3.03425044e-01
9.70131636e-01 -5.32476842e-01 6.07503951e-01 -4.78688419e-01
2.49182492e-01 -3.69110882e-01 -1.70078826e+00 1.78002787e+00
-4.58971590e-01 3.75928730e-02 4.53981906e-01 -1.31528008e+00
9.35437977e-01 4.17442679e-01 7.48838305e-01 -2.45029852e-01
8.35218206e-02 -5.36738569e-03 -1.35979176e-01 -5.03654361e-01
5.50673082e-02 -1.04560345e-01 2.31374707e-02 6.49458826e-01
1.25531862e-02 5.16022205e-01 1.84386060e-01 2.08287314e-01
5.18458664e-01 -2.57520437e-01 6.13321066e-01 -3.07620585e-01
1.09292221e+00 -5.93952477e-01 9.69129324e-01 7.57133290e-02
1.48757966e-02 3.20720404e-01 3.07517946e-01 -2.42671788e-01
-8.63886952e-01 -8.90596211e-01 3.20620649e-02 6.20808303e-01
4.85744059e-01 -6.06448233e-01 -6.29086912e-01 -8.53896379e-01
-6.74340874e-02 2.04535455e-01 -4.07568693e-01 -6.53024856e-03
-3.31230730e-01 -8.57097566e-01 -9.16992407e-03 4.70114708e-01
4.81926471e-01 -3.20048273e-01 -2.86205690e-02 -4.47659940e-02
-5.38083434e-01 -1.21579051e+00 -6.37883186e-01 -2.31984720e-01
-1.14784586e+00 -1.28695822e+00 -6.50859773e-01 -9.93442297e-01
1.05689812e+00 1.04224086e+00 5.55291057e-01 7.71839172e-02
9.01504382e-02 5.34014523e-01 -4.25980777e-01 3.45962286e-01
-1.26860410e-01 4.77218926e-02 8.38441253e-02 7.44314909e-01
4.16297823e-01 -7.46321023e-01 -5.23674846e-01 5.37829816e-01
-9.99963880e-01 2.30694488e-02 4.20364231e-01 1.19422770e+00
7.73404896e-01 4.53318477e-01 5.87537467e-01 -9.10218418e-01
3.77742290e-01 -4.82379287e-01 -5.99140406e-01 4.16901827e-01
-7.88543522e-01 -5.33485524e-02 9.51001346e-01 -1.54794544e-01
-1.01302826e+00 2.35084012e-01 3.42464298e-01 -7.28811502e-01
-9.64954197e-02 5.42677045e-01 -6.79053962e-01 -7.16980323e-02
-1.70577496e-01 5.75096607e-01 9.28292647e-02 -8.55318487e-01
5.19332051e-01 6.52877569e-01 1.35661379e-01 -3.81504774e-01
8.22880387e-01 9.42492187e-01 2.01610088e-01 -7.74455488e-01
-6.14707887e-01 -9.24375594e-01 -1.10748971e+00 -7.25570843e-02
9.05247271e-01 -1.24994636e+00 -8.20016146e-01 2.26573706e-01
-6.73708200e-01 6.60650969e-01 2.57865220e-01 6.87687337e-01
-3.92096967e-01 1.13771820e+00 -4.21958357e-01 -7.61251450e-01
-1.09785572e-01 -1.14321911e+00 7.59139478e-01 -2.90971845e-02
3.12477410e-01 -1.35647130e+00 -1.70580409e-02 7.27502823e-01
-2.13480815e-01 2.27077812e-01 1.08350945e+00 -5.91894567e-01
-4.13384378e-01 -2.96092838e-01 -1.83433294e-01 3.48732561e-01
5.84859908e-01 -2.16833338e-01 -6.69011474e-01 -7.68866241e-01
4.89381820e-01 -2.03911096e-01 8.27008843e-01 1.27709925e-01
1.02919436e+00 -2.48461142e-01 -4.38742161e-01 5.97123802e-01
1.69661558e+00 1.43068433e-01 1.23464271e-01 9.60072726e-02
1.19288814e+00 6.24446750e-01 5.74000418e-01 6.82569802e-01
4.96556938e-01 7.04918027e-01 3.65976155e-01 -7.88790509e-02
3.17397296e-01 -1.93535477e-01 2.40121663e-01 1.59512365e+00
-2.62564942e-02 -8.55257660e-02 -6.36501014e-01 5.84870994e-01
-2.04519725e+00 -1.15144098e+00 -1.61036789e-01 2.22385716e+00
2.11967394e-01 -3.62336665e-01 2.04004511e-01 3.59798133e-01
1.07822967e+00 5.71975231e-01 -4.42230374e-01 1.44537210e-01
-8.28054640e-03 -4.66953427e-01 1.22725882e-01 3.64109129e-01
-1.15848255e+00 4.23632085e-01 5.67930126e+00 9.39414680e-01
-7.84909189e-01 1.66677892e-01 2.30719700e-01 -5.44272289e-02
-3.72222036e-01 8.85707662e-02 -6.27095342e-01 5.37268758e-01
3.43292594e-01 -1.38956726e-01 3.99561852e-01 8.58412385e-01
3.67574006e-01 -2.85262591e-03 -9.55828309e-01 1.29673064e+00
5.07733941e-01 -9.44991469e-01 2.83411413e-01 2.25042433e-01
7.50404835e-01 -4.92015600e-01 3.91847529e-02 -2.40438193e-01
-1.78935722e-01 -6.20400906e-01 2.25545377e-01 1.52244940e-01
4.87918675e-01 -1.15727913e+00 7.31111348e-01 5.92596769e-01
-1.55851030e+00 -1.70983180e-01 -5.79855919e-01 2.20149592e-01
1.17105529e-01 6.20314479e-01 -4.60376889e-01 1.23696518e+00
4.32678610e-01 1.25165796e+00 -6.33137763e-01 7.38639653e-01
7.10239187e-02 2.55511999e-01 -2.05973685e-02 3.46781343e-01
1.46308035e-01 -8.55117977e-01 5.20230770e-01 7.20810533e-01
2.52077907e-01 4.62325336e-03 7.54269361e-01 4.57083136e-01
1.96473181e-01 4.29320902e-01 -7.15536773e-01 6.00148588e-02
4.88459468e-01 1.45835710e+00 -8.25728655e-01 -3.04648191e-01
-8.75503242e-01 1.01548421e+00 4.51407969e-01 4.35947061e-01
-5.98567128e-01 -9.77425575e-02 3.19068551e-01 -1.27168939e-01
7.67383635e-01 -2.08556145e-01 -8.05064887e-02 -1.62745595e+00
2.89768308e-01 -9.48061407e-01 6.61858082e-01 -2.58184284e-01
-1.40381479e+00 3.43834966e-01 -5.85962720e-02 -1.68377101e+00
1.11701665e-02 -3.05245727e-01 -4.64024037e-01 6.05655134e-01
-1.33329391e+00 -1.31598091e+00 -3.60504389e-01 9.21447277e-01
2.94943810e-01 -2.82508284e-01 7.02735782e-01 5.19679010e-01
-8.71665478e-01 4.17454600e-01 7.11096585e-01 1.17790200e-01
6.87880397e-01 -1.12441587e+00 -5.32601833e-01 8.09290230e-01
1.66882858e-01 7.67052352e-01 2.21679285e-01 -3.71095538e-01
-1.47399497e+00 -1.01212382e+00 3.50299001e-01 -2.51484644e-02
4.71680462e-01 -4.22983319e-01 -8.74425411e-01 5.79644442e-01
2.46011242e-01 -6.95394650e-02 1.37205446e+00 2.85212755e-01
-4.87038791e-01 -3.78403097e-01 -8.85837913e-01 3.14274073e-01
6.19615555e-01 -5.20176589e-01 -4.66031343e-01 2.72058606e-01
3.96795124e-01 2.60391627e-02 -1.31960690e+00 3.45993966e-01
3.74835998e-01 -1.24356544e+00 1.02640951e+00 -3.25700879e-01
1.53770432e-01 -5.86455166e-01 -3.18477809e-01 -1.33631706e+00
-7.38060474e-01 -1.85167149e-01 -3.06754798e-01 1.61915910e+00
-3.75202186e-02 -6.93033755e-01 6.60485446e-01 1.60715327e-01
7.03741163e-02 -7.98980415e-01 -9.13527727e-01 -8.84869933e-01
-1.87286288e-01 1.57629579e-01 4.30080891e-01 1.15797353e+00
1.38996411e-02 4.55883563e-01 -6.87024832e-01 4.51408565e-01
1.06341827e+00 7.47120321e-01 7.18808234e-01 -1.30133021e+00
-5.00134170e-01 -9.60943326e-02 -5.37088394e-01 -9.00055289e-01
2.03388155e-01 -1.11134589e+00 -3.82301152e-01 -1.61950719e+00
7.57617533e-01 -3.21332991e-01 -5.22479296e-01 9.92294326e-02
-4.58795279e-01 -1.30276345e-02 2.82793254e-01 6.20652080e-01
-6.79496884e-01 8.70867133e-01 1.32614970e+00 -1.11163989e-01
-7.42035657e-02 2.13842224e-02 -8.17665040e-01 8.59830081e-01
4.77234930e-01 -3.94934088e-01 -7.53386199e-01 -2.85265625e-01
-1.44358799e-01 2.67073721e-01 1.19421497e-01 -8.30821574e-01
2.83817977e-01 -1.49106950e-01 3.93671066e-01 -7.23155558e-01
4.99248683e-01 -1.17589509e+00 2.60403365e-01 3.48255455e-01
1.42422870e-01 1.41613826e-01 -1.52037680e-01 1.22497916e+00
-5.25212765e-01 -1.37660518e-01 8.78396153e-01 -8.92823339e-02
-5.21930337e-01 4.30281281e-01 -2.52271108e-02 -6.78267330e-02
1.25490057e+00 -4.08917479e-02 -1.26449108e-01 -4.17007089e-01
-8.24824274e-01 5.47970235e-01 8.25743318e-01 3.94873142e-01
6.05384529e-01 -1.71436262e+00 -3.93396527e-01 2.22588494e-01
3.95625144e-01 -1.30581707e-01 6.17191494e-01 1.03786385e+00
-9.03641358e-02 4.28797543e-01 -5.34820519e-02 -7.54978716e-01
-1.46626413e+00 1.17750633e+00 -1.55944169e-01 -3.36629093e-01
-7.46877909e-01 2.14654177e-01 4.88104641e-01 -3.77773762e-01
2.03008410e-02 3.34256560e-01 -5.74805081e-01 4.38294709e-01
4.35201049e-01 5.76886415e-01 -2.99232364e-01 -9.42678988e-01
-3.91517609e-01 1.06031883e+00 -1.17292628e-01 1.26889780e-01
1.50828624e+00 -5.78529000e-01 -4.52182472e-01 8.28572392e-01
1.46163213e+00 2.51625627e-01 -9.00071502e-01 -3.66602927e-01
-2.87532479e-01 -6.37203991e-01 7.28805130e-03 -5.01614697e-02
-1.49061882e+00 1.00618780e+00 3.29770625e-01 1.58093169e-01
1.20867240e+00 -1.26830131e-01 5.98579705e-01 2.98019439e-01
2.73837417e-01 -1.03135157e+00 1.36406556e-01 -1.35204002e-01
5.51094472e-01 -1.22728407e+00 4.02907550e-01 -8.00759017e-01
-7.34671354e-01 1.01523292e+00 5.86732209e-01 -3.08754593e-02
7.54395127e-01 -3.74943018e-01 -1.25038832e-01 -4.35609221e-01
-5.68971455e-01 -2.83463132e-02 2.53911257e-01 4.48302031e-01
3.16144198e-01 2.02546385e-03 -4.91227448e-01 3.49034190e-01
4.17732984e-01 -4.05342370e-01 4.68093336e-01 6.80177569e-01
-2.14623064e-01 -1.23436928e+00 -3.85327399e-01 3.38556975e-01
-3.19041997e-01 3.05187047e-01 -3.05885673e-01 6.79110289e-01
1.18705267e-02 1.20673525e+00 -3.11099291e-01 -4.07299072e-01
9.09230933e-02 9.12288651e-02 3.03522229e-01 -6.27068520e-01
-5.88748679e-02 5.92764676e-01 -2.91453898e-01 -3.59807402e-01
-8.79891634e-01 -8.06586266e-01 -9.66358960e-01 -2.49604583e-01
-5.85867167e-01 3.82819265e-01 2.19438076e-01 7.25127459e-01
5.43268621e-01 2.38779992e-01 1.16333997e+00 -5.66351295e-01
-5.30245006e-01 -5.50235212e-01 -1.02709460e+00 6.64781153e-01
1.12862408e-01 -7.73247898e-01 -4.92758065e-01 1.66164432e-02] | [8.225054740905762, 4.601219654083252] |
6c233ea5-7786-4516-b362-dad5b5b522a7 | integrating-connection-search-in-graph | 2208.04802 | null | https://arxiv.org/abs/2208.04802v1 | https://arxiv.org/pdf/2208.04802v1.pdf | Integrating connection search in graph queries | Graph data management and querying has many practical applications. When graphs are very heterogeneous and/or users are unfamiliar with their structure, they may need to find how two or more groups of nodes are connected in a graph, even when users are not able to describe the connections. This is only partially supported by existing query languages, which allow searching for paths, but not for trees connecting three or more node groups. The latter is related to the NP-hard Group Steiner Tree problem, and has been previously considered for keyword search in databases. In this work, we formally show how to integrate connecting tree patterns (CTPs, in short) within a graph query language such as SPARQL or Cypher, leading to an Extended Query Language (or EQL, in short). We then study a set of algorithms for evaluating CTPs; we generalize prior keyword search work, most importantly by (i) considering bidirectional edge traversal and (ii) allowing users to select any score function for ranking CTP results. To cope with very large search spaces, we propose an efficient pruning technique and formally establish a large set of cases where our algorithm, MOLESP, is complete even with pruning. Our experiments validate the performance of our CTP and EQL evaluation algorithms on a large set of synthetic and real-world workloads. | ['Madhulika Mohanty', 'Ioana Manolescu', 'Angelos Christos Anadiotis'] | 2022-08-09 | null | null | null | null | ['steiner-tree-problem'] | ['graphs'] | [ 3.35204862e-02 5.16635031e-02 -2.25481734e-01 -5.65972552e-02
-2.75338918e-01 -9.40265954e-01 1.45630494e-01 9.45180595e-01
-1.62876606e-01 5.95284522e-01 -2.69913703e-01 -6.96359634e-01
-7.19709277e-01 -1.48930442e+00 -4.76767838e-01 1.36933126e-03
-6.39967322e-01 9.76549268e-01 1.07553256e+00 -3.21883738e-01
1.78259894e-01 9.23896909e-01 -1.61668873e+00 -8.61198008e-02
7.29909301e-01 9.57570314e-01 1.38661727e-01 6.17144704e-01
-4.30391431e-01 5.65105498e-01 -5.49209118e-01 -5.90426922e-01
2.32376307e-01 -1.94339151e-03 -1.28987026e+00 -2.01234102e-01
1.95936203e-01 7.60124996e-02 -8.23717415e-02 8.15813899e-01
3.67610216e-01 -7.67978206e-02 7.47240037e-02 -1.58786511e+00
2.80649085e-02 6.39507711e-01 -3.47255468e-01 1.26069307e-01
8.23171079e-01 -3.17846954e-01 1.29112053e+00 -4.46495771e-01
9.38755393e-01 9.40467536e-01 3.65102321e-01 -1.28961593e-01
-1.37474799e+00 -1.95878372e-01 2.94732694e-02 4.11568999e-01
-1.75245702e+00 -1.79621398e-01 3.49419355e-01 -1.04843818e-01
1.25252151e+00 9.08233762e-01 5.42471707e-01 6.35800511e-03
-1.02590539e-01 1.40743345e-01 6.05465174e-01 -4.10792708e-01
2.38474160e-01 1.84785813e-01 2.60034472e-01 6.36316359e-01
5.43340087e-01 -2.20808715e-01 -5.13228774e-01 -7.30724216e-01
4.87642050e-01 -3.16618472e-01 -3.37315947e-01 -7.95949638e-01
-1.03511488e+00 7.06869245e-01 3.83559138e-01 3.88456345e-01
-2.30868295e-01 5.32661974e-02 4.46800500e-01 6.25805557e-01
-5.27596623e-02 4.43384081e-01 -4.93873149e-01 2.03473464e-01
-7.49751389e-01 2.47217298e-01 1.77308774e+00 1.43413889e+00
9.77449358e-01 -6.12558901e-01 -2.16708317e-01 7.28355885e-01
2.17189435e-02 8.09252486e-02 -2.76857197e-01 -8.52645218e-01
3.48203689e-01 9.51440632e-01 1.37801757e-02 -1.15059483e+00
-4.24037874e-01 -3.48787576e-01 -6.34512484e-01 -2.91511029e-01
1.83639243e-01 4.99774128e-01 -3.79699439e-01 1.64416778e+00
5.60506284e-01 -3.52912009e-01 -4.40915488e-02 5.30922472e-01
6.99456275e-01 5.46820045e-01 -1.69681802e-01 -6.48093343e-01
1.53805673e+00 -6.57213330e-01 -3.36634368e-01 8.60136375e-02
8.76392186e-01 -6.94573462e-01 8.83075476e-01 3.39208335e-01
-1.25149930e+00 -1.13070905e-01 -6.81792319e-01 -5.75216040e-02
-6.63390040e-01 -6.50164247e-01 6.52225256e-01 6.64117396e-01
-1.65534389e+00 4.12029982e-01 -5.10976851e-01 -8.50559354e-01
-6.83215037e-02 4.66131568e-01 -2.75075644e-01 -3.13639492e-01
-1.20135093e+00 6.54596090e-01 6.65432096e-01 -3.21393549e-01
-2.90496081e-01 -5.00835240e-01 -6.03659034e-01 3.60223949e-01
1.19050157e+00 -8.78808379e-01 9.75282133e-01 -2.08436310e-01
-6.16401792e-01 8.16769898e-01 -2.28691012e-01 -3.55748802e-01
2.46749476e-01 4.04316664e-01 -5.55936396e-01 2.15389609e-01
1.40319988e-01 2.62444854e-01 -7.21679926e-02 -1.00510383e+00
-5.07667482e-01 -5.28254151e-01 6.70489371e-01 1.95937529e-01
-3.40653270e-01 3.24494064e-01 -1.19819784e+00 -1.95618019e-01
2.71137029e-01 -7.35242903e-01 -3.32966119e-01 7.95478076e-02
-6.52475655e-01 -5.60005069e-01 6.06448650e-01 -1.95203260e-01
1.86979556e+00 -1.72895777e+00 9.29467902e-02 1.08345354e+00
4.05252486e-01 -3.21951099e-02 8.10276940e-02 1.34910858e+00
2.11708054e-01 5.33180594e-01 -2.23347098e-01 2.49362960e-01
6.76160231e-02 6.69842958e-01 -1.51403874e-01 -3.89438048e-02
-2.52231419e-01 6.52611136e-01 -7.57961035e-01 -9.06002462e-01
-3.32505405e-01 -7.85127506e-02 -6.72460854e-01 -1.20858341e-01
-4.86471146e-01 -1.98726460e-01 -4.73121911e-01 8.01724255e-01
7.07101464e-01 -6.24224186e-01 6.53979421e-01 -1.71259373e-01
-1.96228802e-01 2.12764114e-01 -1.57783067e+00 1.41269886e+00
-2.18403071e-01 -5.77000305e-02 2.54582047e-01 -8.85618031e-01
7.27018654e-01 7.72399455e-02 6.28431022e-01 -6.17875993e-01
-5.11534035e-01 5.09164929e-01 -2.25779131e-01 -4.24417347e-01
6.48638308e-01 3.74952972e-01 -2.33135939e-01 5.50883234e-01
-3.97340894e-01 -1.67482406e-01 9.07413483e-01 6.89048231e-01
1.63019538e+00 -4.76985812e-01 3.67316067e-01 -3.32790613e-01
6.52101696e-01 2.43565455e-01 3.58720034e-01 9.14980233e-01
4.11030769e-01 2.16833681e-01 1.05202484e+00 -2.59488493e-01
-5.53779423e-01 -1.01096797e+00 -9.09599587e-02 9.31854844e-01
3.42952043e-01 -1.08033514e+00 -2.96719283e-01 -4.63561386e-01
2.31475502e-01 5.41095793e-01 1.89483408e-02 1.09709345e-01
-5.30950248e-01 -1.87043682e-01 2.43301824e-01 2.12715879e-01
4.78970557e-02 -8.58782768e-01 -7.20403194e-01 4.26838994e-01
-2.43531577e-02 -1.26829445e+00 -5.09124517e-01 9.83140338e-03
-7.60927141e-01 -1.51270509e+00 5.81361838e-02 -6.69938564e-01
4.60318327e-01 3.19832414e-01 1.55420995e+00 7.37733245e-01
-3.21373940e-01 7.11533964e-01 -3.96010190e-01 -1.30777229e-02
-1.34408072e-01 2.02266559e-01 -4.24900293e-01 -4.60407525e-01
1.78177029e-01 -7.12902129e-01 -5.03142953e-01 7.72756279e-01
-1.28466189e+00 -6.85958639e-02 3.16981882e-01 3.85625750e-01
9.64508832e-01 4.98549998e-01 2.64294237e-01 -1.34939790e+00
7.19341159e-01 -5.43688178e-01 -9.72257912e-01 6.61515892e-01
-1.12549436e+00 1.78641900e-01 4.02388364e-01 1.06530063e-01
-2.24180907e-01 -1.03724040e-01 -2.17070475e-01 -1.58277869e-01
3.40442389e-01 1.17413378e+00 -2.92312562e-01 -2.71957934e-01
2.85546392e-01 -6.68829028e-03 -2.19838768e-01 -3.33819777e-01
2.84920752e-01 1.85622767e-01 3.61003578e-01 -7.92025864e-01
6.24806702e-01 4.09837842e-01 4.82946783e-01 -5.74490666e-01
-6.08533435e-02 -7.37574935e-01 -4.06434685e-01 -1.39548611e-02
2.93959558e-01 -3.28788906e-01 -1.09207630e+00 -1.94629863e-01
-1.12360060e+00 -2.71147341e-02 -2.52794027e-01 -6.17925823e-02
-3.01325709e-01 6.92284048e-01 -3.55511427e-01 -6.34895325e-01
-1.93739757e-01 -1.04286623e+00 9.04250383e-01 -2.42539316e-01
-1.20430663e-01 -7.38729596e-01 1.63332358e-01 -1.62611410e-01
5.29737353e-01 3.68698120e-01 1.38909853e+00 -9.91678774e-01
-9.65710104e-01 -2.55526423e-01 -4.21448052e-01 -3.15665364e-01
-2.06811041e-01 -9.80744436e-02 -1.22881651e-01 -4.30345863e-01
-4.83938485e-01 4.83365506e-02 3.61649662e-01 -1.58622503e-01
1.33025813e+00 -4.59568679e-01 -8.31367731e-01 3.75950158e-01
1.78130734e+00 2.10795235e-02 5.77013612e-01 1.68064490e-01
3.62579554e-01 8.09949279e-01 4.92872745e-01 5.00169575e-01
6.76620364e-01 9.71416891e-01 6.47979975e-01 7.73420706e-02
3.18686128e-01 -2.62025028e-01 -2.62221664e-01 7.00637996e-01
5.83888926e-02 -7.47933149e-01 -1.05098987e+00 3.96628976e-01
-1.73404038e+00 -5.52153826e-01 -5.39719820e-01 2.60301661e+00
6.30450904e-01 9.15707946e-02 3.06822151e-01 2.72072792e-01
5.83635747e-01 -7.67311603e-02 -5.73587954e-01 -6.39019728e-01
-8.91037583e-02 6.84086919e-01 7.75348306e-01 3.72349799e-01
-4.05727863e-01 7.51628697e-01 6.14411974e+00 5.96002460e-01
-6.29674733e-01 1.28231116e-03 1.22540303e-01 9.69275013e-02
-7.24436343e-01 5.68767011e-01 -5.93529820e-01 5.56867570e-02
9.73934293e-01 -7.07015812e-01 5.94139516e-01 5.15464723e-01
-6.15193918e-02 -2.78695792e-01 -1.23865736e+00 8.01415861e-01
-2.77534992e-01 -1.20457709e+00 7.07906112e-02 3.52885783e-01
2.21257925e-01 -5.57969436e-02 -5.30216098e-01 9.36881304e-02
3.43328059e-01 -8.54920566e-01 3.32540035e-01 3.09205502e-01
7.78740466e-01 -6.49115682e-01 3.12266260e-01 3.44437659e-01
-1.57278097e+00 -2.25810073e-02 -2.29860291e-01 3.25260609e-01
1.59380481e-01 6.09526753e-01 -6.84026003e-01 1.15358424e+00
8.73351932e-01 1.08086288e-01 -5.75022638e-01 1.34239435e+00
1.45027310e-01 1.67381778e-01 -9.45442915e-01 -1.47609472e-01
-1.25742346e-01 -1.62940338e-01 6.19669139e-01 9.96544302e-01
7.48046041e-01 1.23373255e-01 2.27471411e-01 7.75150359e-01
-2.04405874e-01 4.96803552e-01 -6.04410470e-01 -8.54844823e-02
9.63975012e-01 1.10627437e+00 -9.27869558e-01 -2.15954959e-01
-5.98479271e-01 6.19626820e-01 3.63271326e-01 4.29785192e-01
-4.83054847e-01 -6.71257138e-01 4.04222578e-01 6.23326480e-01
2.57377863e-01 -3.26704800e-01 2.92307585e-01 -8.13856959e-01
3.79264385e-01 -8.51470709e-01 1.18698382e+00 -6.80857241e-01
-1.04532802e+00 5.65125763e-01 3.66324633e-01 -7.52007127e-01
-2.56210804e-01 -2.71653473e-01 -4.09857273e-01 8.33713174e-01
-1.43526435e+00 -7.22322583e-01 -3.11040908e-01 8.41358483e-01
-1.22809246e-01 4.92746800e-01 8.65737736e-01 4.66144621e-01
-3.04401934e-01 4.63549465e-01 -3.33923966e-01 -5.16940713e-01
3.66106719e-01 -1.16983354e+00 1.52567938e-01 6.55301273e-01
1.28739789e-01 6.94979250e-01 6.44999683e-01 -5.21066785e-01
-1.98844469e+00 -7.70288527e-01 1.19385123e+00 2.45884284e-02
5.88101208e-01 -4.19790685e-01 -1.03899121e+00 5.96397161e-01
4.98972647e-03 1.47422358e-01 3.94943118e-01 1.18903533e-01
-3.25867236e-01 -4.32998240e-01 -1.22458303e+00 4.24797088e-01
1.54045141e+00 -2.97455251e-01 6.87623844e-02 6.32824481e-01
8.87123823e-01 -3.71753186e-01 -1.25487649e+00 7.54557073e-01
3.47767949e-01 -1.11483288e+00 1.06605089e+00 -4.45435733e-01
-3.97824258e-01 -6.06274366e-01 -2.21773148e-01 -7.58535147e-01
-8.86461362e-02 -8.71084094e-01 -1.92791924e-01 1.08744431e+00
5.25748253e-01 -8.98336172e-01 7.77435660e-01 6.20019972e-01
7.39739761e-02 -9.39777315e-01 -9.56363499e-01 -9.30842042e-01
-4.37507063e-01 -4.86317456e-01 1.00328851e+00 8.70227754e-01
1.21954218e-01 2.92098254e-01 1.94573104e-01 4.68578428e-01
4.55980301e-01 5.52857161e-01 7.86764979e-01 -1.47750103e+00
-5.03773153e-01 -5.59520185e-01 -4.99229580e-01 -1.04598939e+00
-2.62886912e-01 -1.12594271e+00 -5.63787758e-01 -2.11579132e+00
3.92983258e-02 -9.14205909e-01 -2.75028683e-02 5.22632301e-01
3.92315894e-01 -1.99215189e-01 -9.07620639e-02 3.64694685e-01
-7.32751429e-01 -8.46610740e-02 9.51459408e-01 4.58767079e-02
-2.19452173e-01 2.37021104e-01 -6.71907961e-01 9.84073803e-02
3.65532845e-01 -4.54911798e-01 -6.95323229e-01 -2.16895938e-01
9.68504012e-01 6.18948162e-01 3.01554978e-01 -7.83779562e-01
8.70471060e-01 -3.02286536e-01 -5.31307220e-01 -7.94587851e-01
1.53196096e-01 -1.07582271e+00 9.00327206e-01 5.70017576e-01
-1.00189507e-01 4.99441504e-01 1.37954205e-01 5.21661162e-01
-3.64205450e-01 -1.91009879e-01 1.95950612e-01 -1.31329983e-01
-6.32286549e-01 6.83610320e-01 2.70524658e-02 1.38695911e-01
1.13334370e+00 -3.16693455e-01 -4.74550664e-01 -3.53715777e-01
-8.18856120e-01 9.28261399e-01 7.96684265e-01 8.97536650e-02
6.85815811e-01 -1.13429701e+00 -5.14040470e-01 -9.63836350e-03
6.03250802e-01 -2.79970728e-02 -1.49986923e-01 8.92849147e-01
-7.21882641e-01 3.47204506e-01 3.66978526e-01 -3.86960179e-01
-1.34955633e+00 9.28104579e-01 1.35738045e-01 -6.06172323e-01
-3.97314429e-01 4.32806909e-01 -1.74135298e-01 -2.80661345e-01
2.62853771e-01 -2.38885880e-01 -3.21963429e-02 -7.53006786e-02
6.99995756e-02 2.27180883e-01 3.48967701e-01 -3.15484196e-01
-5.06817579e-01 5.42915702e-01 1.33381709e-01 1.43032372e-01
1.11948073e+00 -1.56618655e-01 -8.68941486e-01 8.55182931e-02
9.47940886e-01 2.26467967e-01 2.93015558e-02 -4.87851799e-01
4.85600561e-01 -4.69320267e-01 -3.45782906e-01 -6.17063880e-01
-9.62716818e-01 2.69619077e-01 1.01823747e-01 9.47412312e-01
1.48819065e+00 4.19659495e-01 8.36847246e-01 6.08121037e-01
8.91184747e-01 -7.39983976e-01 -4.06044990e-01 3.08084667e-01
7.48997808e-01 -5.34930348e-01 1.44819722e-01 -1.06138074e+00
-1.24036998e-01 1.13196898e+00 4.65104043e-01 4.26101357e-01
8.12740445e-01 3.38902473e-01 -6.54173970e-01 -6.62465215e-01
-1.03024185e+00 -5.45844913e-01 -4.55057025e-02 2.67836988e-01
8.28443170e-02 -7.53818676e-02 -8.50763917e-01 1.79324582e-01
-1.88703343e-01 4.16298676e-03 4.07639235e-01 1.30401933e+00
-4.89558697e-01 -1.75794005e+00 -4.85776812e-02 6.50686741e-01
-2.78010935e-01 -1.41398564e-01 -5.18072665e-01 8.62112641e-01
-1.40483201e-01 1.02307034e+00 1.16324171e-01 -2.01383621e-01
7.51830339e-01 -1.13923132e-01 4.19669986e-01 -7.28705704e-01
-5.64545274e-01 -1.92800492e-01 5.34836829e-01 -7.46027470e-01
-1.74468949e-01 -3.02505553e-01 -1.26157212e+00 -4.55945432e-01
-3.47521901e-01 6.27497196e-01 4.85113502e-01 2.92853504e-01
6.44917905e-01 1.20800160e-01 4.71851140e-01 2.24005923e-01
-2.59337485e-01 -4.79310304e-01 -7.53888369e-01 1.16205476e-01
-2.29353130e-01 -4.40847069e-01 -9.05976817e-03 -4.08837140e-01] | [7.204141616821289, 5.634772300720215] |
795127f0-bfd3-44c6-ad53-2660cd5d6918 | localizing-small-apples-in-complex-apple | 2202.11372 | null | https://arxiv.org/abs/2202.11372v1 | https://arxiv.org/pdf/2202.11372v1.pdf | Localizing Small Apples in Complex Apple Orchard Environments | The localization of fruits is an essential first step in automated agricultural pipelines for yield estimation or fruit picking. One example of this is the localization of apples in images of entire apple trees. Since the apples are very small objects in such scenarios, we tackle this problem by adapting the object proposal generation system AttentionMask that focuses on small objects. We adapt AttentionMask by either adding a new module for very small apples or integrating it into a tiling framework. Both approaches clearly outperform standard object proposal generation systems on the MinneApple dataset covering complex apple orchard environments. Our evaluation further analyses the improvement w.r.t. the apple sizes and shows the different characteristics of our two approaches. | ['Simone Frintrop', 'Robert Johanson', 'Christian Wilms'] | 2022-02-23 | null | null | null | null | ['object-proposal-generation'] | ['computer-vision'] | [ 2.74419844e-01 1.42889097e-01 2.71360930e-02 -3.57956082e-01
-3.91650647e-01 -1.06462491e+00 5.27706683e-01 6.55171216e-01
-2.56922454e-01 1.06108576e-01 -3.95096987e-01 -1.69056937e-01
-9.00283456e-02 -8.70135784e-01 -8.88127267e-01 -5.68466246e-01
-1.28426567e-01 5.98597646e-01 9.48642075e-01 -1.17610637e-02
3.90409023e-01 5.71635842e-01 -1.76948237e+00 2.21909329e-01
7.54344523e-01 8.17571580e-01 1.06525147e+00 1.12055302e+00
-4.91071403e-01 -8.39553494e-03 -7.33122408e-01 -2.46565253e-01
3.28502238e-01 -6.77651241e-02 -3.71050745e-01 8.83080810e-02
6.29946828e-01 -4.56444830e-01 5.86576581e-01 1.09922552e+00
3.17128420e-01 -4.22516614e-01 5.42373657e-01 -1.36724806e+00
-4.84784454e-01 1.23177493e+00 -9.37561989e-01 -2.08079200e-02
-1.01757757e-01 1.73708871e-01 9.28169906e-01 -7.55502343e-01
5.77943802e-01 1.37642181e+00 6.41734660e-01 2.69713607e-02
-1.33450651e+00 -3.43289733e-01 2.81176418e-01 2.22474143e-01
-1.34946251e+00 -2.69215703e-01 2.56041825e-01 -1.63934901e-01
4.33361471e-01 4.59071517e-01 5.02907395e-01 4.22128022e-01
1.51066650e-02 1.10778034e+00 6.00119412e-01 -6.01765692e-01
3.58190715e-01 1.40024990e-01 2.08481684e-01 1.81219116e-01
7.21036434e-01 -1.54250875e-01 -5.59681989e-02 1.31281614e-01
6.55386150e-01 -4.42590378e-02 1.23213828e-01 -7.13986099e-01
-1.38599777e+00 7.75697589e-01 7.68089533e-01 2.23276809e-01
-5.52751660e-01 3.00811738e-01 2.76086688e-01 -2.19875187e-01
2.87850380e-01 6.74831271e-01 -7.32060015e-01 1.52623564e-01
-1.03052473e+00 3.62106949e-01 7.71589220e-01 1.37201786e+00
4.49388504e-01 -1.59808636e-01 -4.85555828e-01 4.92805749e-01
2.99172014e-01 6.52546644e-01 -8.61106366e-02 -8.39178264e-01
7.01490510e-03 7.50887036e-01 3.40070337e-01 -5.97837448e-01
-3.99250120e-01 -2.71986693e-01 -3.62425089e-01 4.90528703e-01
8.66973519e-01 -6.91852793e-02 -1.16561484e+00 1.38788426e+00
7.02856064e-01 -1.62897781e-01 -3.01306933e-01 7.80425191e-01
9.84037280e-01 6.52012885e-01 4.01633769e-01 2.62768358e-01
1.93870223e+00 -7.62698889e-01 -5.46204746e-01 -3.91896456e-01
5.13445497e-01 -1.12529910e+00 8.90690446e-01 3.81259590e-01
-8.31949949e-01 -6.43483400e-01 -9.41629648e-01 1.18089609e-01
-7.21696675e-01 9.23899353e-01 7.22370446e-01 6.83231533e-01
-5.99791586e-01 7.67017663e-01 -7.25848258e-01 -7.13357389e-01
5.96932232e-01 2.53506899e-01 -9.39976797e-02 -6.23644516e-02
-3.95542264e-01 9.64401901e-01 9.15816307e-01 3.37182671e-01
-7.23011434e-01 -7.25283206e-01 -7.05896437e-01 3.95724177e-01
6.39634311e-01 -9.72222537e-02 1.13764715e+00 -1.03294861e+00
-1.44000101e+00 8.03488493e-01 1.71267018e-01 -5.15929937e-01
2.67987639e-01 -5.67955673e-01 1.09109759e-01 -8.61123875e-02
2.13079661e-01 1.25903559e+00 1.20474434e+00 -1.14345646e+00
-9.66457367e-01 -3.51309389e-01 6.93710074e-02 -4.89107929e-02
2.82898843e-02 2.06159338e-01 -1.24538057e-01 -5.57196021e-01
7.94127360e-02 -1.01086533e+00 -4.57765579e-01 3.74491513e-01
-5.94782770e-01 -1.26099318e-01 1.14543712e+00 -5.65306962e-01
8.35196018e-01 -1.74380326e+00 4.50306013e-02 -8.46350119e-02
3.95436138e-02 5.42920649e-01 -6.38617814e-01 8.42472836e-02
-1.35518968e-01 -3.49397250e-02 -1.51755661e-01 5.76673355e-03
7.09306672e-02 7.01027736e-02 1.02060363e-02 1.38235733e-01
7.17610002e-01 1.14677691e+00 -9.70763862e-01 -5.21873653e-01
4.84162331e-01 2.31420010e-01 -1.04637995e-01 1.14761166e-01
-6.68394446e-01 -3.39041948e-02 -3.56155723e-01 1.18513799e+00
1.28213298e+00 9.81102809e-02 8.97443201e-03 -3.02774459e-01
-5.48435748e-01 -2.15376854e-01 -1.38759935e+00 1.60778141e+00
-1.16418026e-01 4.85266477e-01 3.91117841e-01 -6.24592125e-01
8.85081410e-01 7.31099863e-04 1.37145922e-01 1.11282937e-01
1.87375426e-01 9.67032090e-02 4.87715721e-01 -1.97553232e-01
7.46327460e-01 5.10927081e-01 6.45869821e-02 1.14964455e-01
1.99181363e-01 -4.12786752e-01 7.08737493e-01 2.47000858e-01
1.11643338e+00 7.18925536e-01 7.13859260e-01 -5.35238504e-01
1.06236465e-01 3.55105877e-01 2.55092025e-01 9.05067265e-01
-1.24020718e-01 8.10701370e-01 8.51015508e-01 -1.62165344e-01
-1.00668383e+00 -1.03175688e+00 -1.39368340e-01 1.49284828e+00
-5.51395342e-02 -6.85195625e-01 -8.88709128e-01 -1.17656350e+00
1.41566336e-01 8.85860920e-01 -8.24144304e-01 2.42056586e-02
-3.92069131e-01 -1.03367031e+00 1.99369565e-01 6.47587001e-01
1.80670664e-01 -1.31001437e+00 -1.39047325e+00 1.22449733e-01
1.50846034e-01 -1.03211415e+00 -7.49633240e-04 7.48672724e-01
-7.48565733e-01 -1.03964663e+00 -9.43714619e-01 -4.72751319e-01
6.48883045e-01 3.25963587e-01 1.44300032e+00 -2.17535734e-01
-6.98446751e-01 -5.38256066e-03 -8.55440021e-01 -1.29933619e+00
-5.10455310e-01 6.83862507e-01 -6.12698793e-01 -3.42207730e-01
5.54858804e-01 6.02906533e-02 -4.61420268e-01 1.42997742e-01
-9.03876245e-01 -2.29368880e-01 1.07617784e+00 5.58646262e-01
5.33224821e-01 -9.91192833e-02 3.61815900e-01 -7.59451509e-01
7.16459304e-02 -5.50067425e-01 -1.44194007e+00 4.70565468e-01
-2.58582942e-02 2.63362914e-01 3.04112494e-01 -7.89097428e-01
-6.66696250e-01 9.83024359e-01 4.77215610e-02 -1.19111083e-01
-6.32165849e-01 1.79823786e-02 -7.17292190e-01 -5.28327897e-02
4.60638732e-01 -2.42103264e-01 -9.98479798e-02 -6.10715508e-01
6.71159387e-01 2.25861177e-01 3.15170765e-01 -1.33399650e-01
8.94178510e-01 1.18771821e-01 2.54641265e-01 -1.02157545e+00
-5.55885136e-01 -5.43617725e-01 -1.08392203e+00 -5.80213033e-02
8.24684381e-01 -4.05521274e-01 -8.10788989e-01 4.36547101e-01
-1.42265642e+00 -2.96501935e-01 -8.31593454e-01 2.45245785e-01
-1.04113996e-01 1.89430267e-01 1.08087003e-01 -6.20243609e-01
-3.24653506e-01 -1.18988621e+00 1.65736532e+00 4.31166768e-01
-1.31433710e-01 -4.31048840e-01 -2.45106250e-01 -4.84681606e-01
3.78191233e-01 2.44544029e-01 5.20177782e-01 -8.10408413e-01
-6.07254028e-01 -5.39089859e-01 -5.96188128e-01 -1.31690670e-02
1.80583522e-01 4.42318410e-01 -1.05049837e+00 1.89528704e-01
-5.87287009e-01 1.01646729e-01 1.02259338e+00 8.59459639e-01
9.78742003e-01 3.27140808e-01 -6.05737329e-01 4.01330203e-01
1.47401035e+00 -7.35651255e-02 5.76756835e-01 3.29517931e-01
6.26711726e-01 8.79453659e-01 1.13700736e+00 5.36287069e-01
7.33003914e-02 6.19915903e-01 1.11773813e+00 -1.45403504e-01
-1.34415537e-01 2.10833505e-01 2.74293631e-01 -1.81886956e-01
8.74764174e-02 -3.83121431e-01 -7.70960748e-01 7.96360016e-01
-1.89622891e+00 -6.09057069e-01 -5.29214025e-01 2.18176007e+00
4.22427297e-01 3.95543016e-02 1.48947641e-01 3.05289365e-02
7.81064272e-01 -5.63432612e-02 -6.45645440e-01 -3.25851411e-01
-9.36849117e-02 3.94065917e-01 1.13469636e+00 9.41797867e-02
-1.58646178e+00 1.22938049e+00 6.60324383e+00 7.63446689e-01
-7.99489856e-01 -4.41591665e-02 2.39366040e-01 -4.07947935e-02
3.91315222e-01 3.63183707e-01 -1.27249205e+00 3.65941018e-01
5.61195433e-01 3.85122836e-01 -3.18389498e-02 1.06207693e+00
-3.46929953e-02 -6.40649855e-01 -1.08341002e+00 2.44907245e-01
-2.58056492e-01 -9.29614663e-01 -1.46380514e-01 -2.61027783e-01
1.91358238e-01 -1.05196647e-01 -2.97435015e-01 9.07337070e-02
6.49936557e-01 -8.36877644e-01 8.27525437e-01 2.48035461e-01
4.30408567e-01 -3.55697662e-01 8.86815965e-01 1.56094015e-01
-1.42971802e+00 -7.39034126e-03 -6.49651051e-01 2.99087107e-01
1.01348966e-01 8.14061880e-01 -1.19164705e+00 2.26230234e-01
8.44585299e-01 4.34617817e-01 -1.29400814e+00 1.48021245e+00
-4.19166446e-01 5.83595216e-01 -8.77101839e-01 -1.97224557e-01
1.36541128e-01 -3.04175764e-02 6.73307002e-01 1.23276055e+00
4.90993381e-01 -4.36419517e-01 -5.44067957e-02 1.27437949e+00
2.04044715e-01 2.46932022e-02 -5.11452794e-01 -6.52595907e-02
5.40438235e-01 1.95574784e+00 -1.39423501e+00 -2.53015786e-01
8.68943613e-03 9.71738517e-01 -1.52809322e-01 -1.51153505e-01
-7.98256516e-01 -7.69598961e-01 3.36055577e-01 1.51492104e-01
1.05373120e+00 8.78549218e-02 -1.40050396e-01 -6.93527341e-01
-5.39875366e-02 -5.39767146e-01 4.44198027e-02 -8.96043658e-01
-8.08132827e-01 1.23037085e-01 2.51492560e-01 -9.66995478e-01
-6.16140887e-02 -8.76527965e-01 -8.77844453e-01 5.77839375e-01
-1.34348810e+00 -1.72996211e+00 -6.63556874e-01 -1.64450198e-01
6.65193975e-01 3.57647091e-01 8.93816292e-01 -2.90666699e-01
-4.33174908e-01 1.85805723e-01 2.32926384e-01 -2.49758810e-01
6.97089374e-01 -1.65413094e+00 7.06262827e-01 1.05514908e+00
2.13348985e-01 1.08673461e-01 8.03314686e-01 -6.51969492e-01
-1.27646184e+00 -1.20475817e+00 5.01780748e-01 -6.22556210e-01
4.52863812e-01 -6.18560493e-01 -8.20235193e-01 5.81638217e-01
3.50677907e-01 1.17277175e-01 5.64094074e-03 8.89716074e-02
3.04001762e-04 -6.61131069e-02 -1.09576249e+00 2.84675121e-01
5.06828368e-01 5.52971900e-01 -1.16457015e-01 3.63570839e-01
5.81146121e-01 -2.02908397e-01 -8.64682436e-01 4.55688357e-01
7.33043015e-01 -6.06386304e-01 1.17767119e+00 -2.37945661e-01
3.33336085e-01 -4.93759900e-01 -1.67418808e-01 -1.40834105e+00
-3.66591603e-01 -3.31609726e-01 -1.29936680e-01 1.57608628e+00
2.42106155e-01 -1.19040743e-01 8.66846383e-01 6.78158402e-02
4.91041988e-02 -3.94353792e-02 -4.37790185e-01 -7.62941003e-01
-5.56755997e-02 -1.08688109e-01 9.22913849e-01 4.68936473e-01
-5.02823949e-01 8.00820291e-02 8.34061205e-02 3.90157104e-01
6.82632565e-01 3.14508259e-01 8.71912479e-01 -1.46884632e+00
-1.50815621e-01 -5.28096139e-01 -4.20395225e-01 -5.86867630e-01
-2.69444227e-01 -6.07394695e-01 5.21444380e-01 -1.47641790e+00
7.90946856e-02 -6.08755469e-01 8.33787248e-02 6.48494422e-01
-6.03991687e-01 1.70418441e-01 5.60360789e-01 -3.17858517e-01
-5.27338684e-01 1.10636741e-01 8.79306495e-01 -7.14230239e-02
-3.48253489e-01 3.05764019e-01 -4.32097882e-01 9.73435938e-01
1.04253674e+00 -6.53559089e-01 -2.07970291e-02 -5.43660223e-01
-4.64243330e-02 -5.57962775e-01 5.08263171e-01 -9.99993503e-01
-2.16716290e-01 -4.74078991e-02 5.13522863e-01 -1.13509130e+00
2.20510170e-01 -1.08154309e+00 -2.49094293e-01 6.24668121e-01
-1.24124780e-01 -4.46526846e-03 5.18500865e-01 2.38867164e-01
3.44633698e-01 -8.75171363e-01 7.94254541e-01 -3.24602544e-01
-9.57061529e-01 -2.02968612e-01 -4.62812066e-01 -3.70677680e-01
1.32920945e+00 -1.97784245e-01 -1.68913484e-01 2.09839419e-01
-7.78688192e-01 2.09783524e-01 3.02705973e-01 7.33827233e-01
2.62202203e-01 -8.26259673e-01 -1.03211737e+00 2.44754031e-01
4.02573049e-01 3.22007000e-01 -4.76271570e-01 6.84116423e-01
-8.62828076e-01 3.01491737e-01 -4.49477673e-01 -9.88366902e-01
-1.66710067e+00 6.00445330e-01 -8.02745745e-02 -2.82842427e-01
-2.93823600e-01 8.23048890e-01 4.30678487e-01 -4.52872455e-01
1.60449386e-01 -9.12672698e-01 -4.74825323e-01 3.68948936e-01
4.15543854e-01 3.70270818e-01 5.74033745e-02 -3.87636483e-01
-4.35234010e-01 4.34960872e-01 -1.31175607e-01 2.93580621e-01
1.42394853e+00 2.03437731e-01 -5.18822335e-02 2.94003278e-01
2.07635313e-01 -1.37261763e-01 -1.39620304e+00 2.11259410e-01
4.79218364e-01 -4.65897143e-01 5.74503914e-02 -9.49077845e-01
-1.02982891e+00 8.34324658e-01 1.01750779e+00 2.70259202e-01
1.13393867e+00 2.34956235e-01 4.07903679e-02 2.40118086e-01
1.11662172e-01 -8.00105155e-01 -3.85199398e-01 2.11717322e-01
9.51618254e-01 -1.49761474e+00 3.22794676e-01 -6.76497638e-01
-5.00383914e-01 1.26128304e+00 7.21466005e-01 -2.22959667e-01
6.55787170e-01 6.85365796e-01 -1.93546847e-01 -9.82735232e-02
-5.28543651e-01 -6.69142604e-01 2.90087610e-01 1.02371824e+00
4.21163172e-01 3.05556774e-01 -2.09542349e-01 5.52064240e-01
1.48164764e-01 -3.83650996e-02 4.94926304e-01 1.10095227e+00
-6.45306826e-01 -1.17119145e+00 -8.64409566e-01 4.85765755e-01
-2.22926781e-01 -3.04009527e-01 -6.89337611e-01 9.37409520e-01
5.22896767e-01 6.17738843e-01 1.39268011e-01 4.22529168e-02
4.27963078e-01 -1.35852575e-01 5.82095861e-01 -7.86166012e-01
-9.24401522e-01 1.26805648e-01 -1.88817590e-01 -4.61381942e-01
-1.52919784e-01 -8.62354696e-01 -7.54157960e-01 2.01258451e-01
-1.15038788e+00 -4.15090859e-01 1.11076510e+00 4.21838492e-01
3.48519713e-01 8.79133344e-01 8.70025232e-02 -1.22474051e+00
-4.35386956e-01 -1.35173714e+00 -5.79254925e-01 -2.33008377e-02
-5.71239069e-02 -4.03442383e-01 2.32244194e-01 2.41268367e-01] | [9.068378448486328, -1.432457447052002] |
52ac3ad8-77d7-4476-9e9e-2e3075eb7b29 | non-intrusive-load-monitoring-nilm-using-deep | 2306.05017 | null | https://arxiv.org/abs/2306.05017v1 | https://arxiv.org/pdf/2306.05017v1.pdf | Non-Intrusive Load Monitoring (NILM) using Deep Neural Networks: A Review | Demand-side management now encompasses more residential loads. To efficiently apply demand response strategies, it's essential to periodically observe the contribution of various domestic appliances to total energy consumption. Non-intrusive load monitoring (NILM), also known as load disaggregation, is a method for decomposing the total energy consumption profile into individual appliance load profiles within the household. It has multiple applications in demand-side management, energy consumption monitoring, and analysis. Various methods, including machine learning and deep learning, have been used to implement and improve NILM algorithms. This paper reviews some recent NILM methods based on deep learning and introduces the most accurate methods for residential loads. It summarizes public databases for NILM evaluation and compares methods using standard performance metrics. | ['Abouzar Estebsari', 'Roozbeh Rajabi', 'Mohammad Irani Azad'] | 2023-06-08 | null | null | null | null | ['non-intrusive-load-monitoring', 'non-intrusive-load-monitoring', 'total-energy', 'non-intrusive-load-monitoring'] | ['knowledge-base', 'miscellaneous', 'miscellaneous', 'time-series'] | [-3.50146383e-01 -4.38415140e-01 -4.51949030e-01 -5.92949867e-01
-6.20372832e-01 -4.95104700e-01 4.73261774e-01 -4.29657176e-02
2.09166586e-01 7.50573397e-01 4.60495085e-01 -2.33643338e-01
-2.40353614e-01 -1.10282993e+00 -4.22117449e-02 -1.14714539e+00
-5.94289228e-02 6.33105755e-01 -7.37796307e-01 8.35102499e-02
-4.09396440e-01 5.34197330e-01 -1.20272744e+00 2.50346184e-01
8.96681309e-01 1.19224060e+00 -1.10052265e-02 3.67339402e-01
2.17501089e-01 8.43320370e-01 -9.08176839e-01 7.59620294e-02
-1.05496787e-01 -3.06172132e-01 -6.81866586e-01 -1.59254566e-01
-2.54197359e-01 -1.00084567e+00 -2.97561258e-01 9.26526904e-01
9.65057194e-01 1.66002870e-01 8.61671031e-01 -1.63492930e+00
-5.53729713e-01 1.00192225e+00 -5.42964816e-01 4.63789880e-01
4.59465742e-01 7.29201408e-03 7.05727518e-01 4.44753245e-02
-4.34193462e-01 8.05591345e-01 5.86070299e-01 2.64916718e-01
-1.55631781e+00 -7.86793053e-01 -1.26586452e-01 8.66340220e-01
-1.15477836e+00 -1.35097116e-01 1.18602061e+00 -4.01795745e-01
1.79674292e+00 7.57155418e-01 4.24186319e-01 1.16360366e+00
1.63088113e-01 1.25061584e+00 9.20458436e-01 -2.82726943e-01
5.88197708e-01 -5.53393178e-02 2.77464628e-01 -1.98562011e-01
3.86625499e-01 1.83654100e-01 8.02236125e-02 -4.57074225e-01
-2.19185680e-01 -8.78161862e-02 -7.90658370e-02 1.74345300e-01
-4.73334074e-01 8.25922310e-01 1.22627258e-01 6.04242623e-01
-6.22116804e-01 1.79799438e-01 8.40351403e-01 6.32064715e-02
6.82368994e-01 8.38452298e-03 -6.75481439e-01 -3.26775700e-01
-1.23026192e+00 -8.01541209e-02 1.10765660e+00 8.14925611e-01
5.92915714e-01 5.40124953e-01 -8.91773105e-02 8.00591111e-01
3.24269891e-01 6.11499727e-01 9.44878936e-01 -9.52688396e-01
6.50130287e-02 6.47349477e-01 8.37025866e-02 -4.71149594e-01
-9.72000837e-01 5.64064495e-02 -1.49851787e+00 6.41706735e-02
-4.50354278e-01 -4.87260103e-01 -4.68997359e-01 1.49581563e+00
7.23788515e-02 -8.10896754e-02 -1.78401649e-01 2.17235759e-01
8.20224464e-01 8.98803830e-01 3.94279838e-01 -7.28037059e-01
1.10925961e+00 -6.78130209e-01 -1.19497001e+00 2.27208316e-01
6.69063807e-01 -3.04617494e-01 4.31430161e-01 3.34756851e-01
-8.77296865e-01 -2.73129463e-01 -8.32649708e-01 -1.38937077e-02
-8.34518611e-01 7.10946647e-03 3.02694708e-01 9.06821430e-01
-7.16725647e-01 7.61845410e-01 -8.86776984e-01 -3.97215843e-01
6.07478499e-01 5.97296953e-01 2.04068631e-01 5.26976407e-01
-1.11576366e+00 1.01512635e+00 5.99976897e-01 -5.69883697e-02
-6.81705713e-01 -7.92819440e-01 -8.14662933e-01 1.95303187e-01
-2.35681981e-01 -4.39690381e-01 1.63848519e+00 -3.18015307e-01
-1.62369919e+00 4.26086932e-01 5.80756180e-02 -4.59790677e-01
4.62994635e-01 -1.24163702e-01 -9.20099139e-01 -4.96071458e-01
-1.13372304e-01 -8.63146558e-02 5.87639928e-01 -9.49592412e-01
-8.36066544e-01 -4.84246612e-01 -5.28332770e-01 -2.22402826e-01
-1.63327873e-01 -2.25643188e-01 5.76729119e-01 -4.45838481e-01
-4.55369443e-01 -5.40702045e-01 1.05789475e-01 -9.77087319e-01
-8.14711988e-01 -8.88780117e-01 1.58114779e+00 -1.06678367e+00
1.40415776e+00 -1.98384976e+00 -4.51920450e-01 1.99867904e-01
3.06593180e-02 3.57360601e-01 2.51333237e-01 6.86648607e-01
-4.14488792e-01 -1.74636483e-01 -1.20967291e-01 -5.46055317e-01
8.00830841e-01 5.31566799e-01 -1.66088685e-01 7.01806366e-01
-6.06238604e-01 1.53265524e+00 -7.23668575e-01 1.57928560e-02
1.27371502e+00 4.68340307e-01 8.11372772e-02 3.32324773e-01
-2.40573287e-01 2.18263924e-01 -6.62011206e-02 7.16718554e-01
8.76675785e-01 -1.58015370e-01 2.84712553e-01 -7.10122883e-01
-7.67637789e-02 5.27582347e-01 -8.67553592e-01 1.02604139e+00
-6.16728127e-01 7.29342818e-01 -1.57193184e-01 -1.47584438e+00
4.03369784e-01 7.20485091e-01 1.17526579e+00 -1.01619780e+00
5.18766224e-01 3.46865095e-02 -4.09239173e-01 -5.73140681e-01
9.47595015e-02 2.25608677e-01 -3.60375792e-01 8.31399739e-01
2.53132693e-02 2.24398255e-01 2.29665354e-01 -5.91875494e-01
9.28813517e-01 -2.11897299e-01 8.23839307e-01 -5.72472155e-01
2.84461737e-01 -3.86607945e-01 4.44747418e-01 2.90607631e-01
-4.06558484e-01 -2.99826384e-01 -9.15700719e-02 -7.10517883e-01
-8.68798196e-01 -9.78229821e-01 -2.81160414e-01 1.28561103e+00
-3.97785991e-01 5.73563315e-02 -9.02377367e-01 -5.22785962e-01
3.65079731e-01 1.54293215e+00 -5.28674364e-01 -3.72662425e-01
-6.85442388e-01 -1.59891152e+00 1.22524716e-01 9.02482688e-01
9.17925477e-01 -1.11818337e+00 -7.31766403e-01 6.67122364e-01
-4.44444358e-01 -7.53459036e-01 -4.14641947e-01 7.14523911e-01
-4.71587330e-01 -1.11282492e+00 -2.64278054e-01 -6.06242716e-01
1.24720961e-01 -2.95478925e-02 1.57130158e+00 -7.29843199e-01
-3.64251733e-01 3.11275095e-01 -1.32911041e-01 -5.75299501e-01
-5.34024060e-01 5.45731843e-01 2.81142563e-01 -1.80873349e-01
1.36408460e+00 -1.25086486e+00 -7.09919930e-01 2.45258406e-01
-5.04164040e-01 -3.52245569e-01 2.31038496e-01 1.99706629e-01
4.63851124e-01 7.48602271e-01 9.01801467e-01 -5.52689075e-01
6.83232129e-01 -8.62040281e-01 -8.46908689e-01 1.55456647e-01
-1.00682676e+00 -3.66025120e-01 6.57174647e-01 -3.44604790e-01
-8.58034551e-01 -1.51142076e-01 -4.42811221e-01 -3.01462170e-02
-7.46180296e-01 -1.73035070e-01 -7.70609140e-01 4.44381416e-01
1.87738612e-01 4.00422484e-01 -6.11293256e-01 -1.08283293e+00
3.94761533e-01 9.35876846e-01 5.85347652e-01 -1.48783237e-01
5.29726505e-01 3.47975224e-01 -2.82831103e-01 -7.40188777e-01
-4.12692070e-01 -5.14194667e-01 -7.02267468e-01 1.60145201e-02
9.46611881e-01 -8.15886676e-01 -1.41367829e+00 7.76616573e-01
-8.32932651e-01 -6.54856324e-01 -8.57669055e-01 2.12328106e-01
-7.24121153e-01 1.04652219e-01 -6.15160048e-01 -9.06893075e-01
-1.00732160e+00 -9.22186017e-01 9.83974636e-01 2.87883967e-01
-7.50184715e-01 -1.23431277e+00 2.77560890e-01 1.06709704e-01
6.30063832e-01 5.59395611e-01 1.21278965e+00 -7.14661539e-01
-4.75307591e-02 -2.73993134e-01 3.03697027e-03 6.16327107e-01
8.94607961e-01 -3.34480941e-01 -1.29813766e+00 -6.33800507e-01
3.45527649e-01 1.96724370e-01 3.91978830e-01 8.26420188e-01
1.52558184e+00 -7.54769564e-01 -5.30004382e-01 6.18182302e-01
1.60559702e+00 6.74691260e-01 4.79542136e-01 2.34726459e-01
6.56310022e-01 1.42485425e-01 -4.32362497e-01 8.34850073e-01
5.99915147e-01 3.12469035e-01 3.77321810e-01 -6.07169233e-02
1.84745535e-01 1.15779124e-01 3.00695568e-01 9.99655247e-01
2.96665907e-01 -7.18814969e-01 -3.60916764e-01 5.09879112e-01
-1.96345663e+00 -1.31946981e+00 2.11940613e-02 1.40795183e+00
6.09662890e-01 -3.97475541e-01 6.35966361e-01 6.56872332e-01
3.61536622e-01 2.66873240e-01 -1.24765527e+00 -6.37476623e-01
-1.41332494e-02 -6.52744472e-02 6.40642285e-01 1.24594763e-01
-1.12026167e+00 -1.98819578e-01 7.68211937e+00 7.57664144e-01
-5.40279686e-01 4.93915558e-01 7.34245479e-01 -2.40408450e-01
-3.94235030e-02 -9.81025279e-01 -7.30426788e-01 1.15521395e+00
1.33821774e+00 -5.63651145e-01 7.29811251e-01 1.07250667e+00
8.05832922e-01 -4.02673513e-01 -1.61149299e+00 1.26114511e+00
-3.15450877e-01 -8.98928285e-01 -3.32744122e-01 4.54701215e-01
1.13396037e+00 3.69719476e-01 -1.85441926e-01 3.31530333e-01
9.43858504e-01 -7.65422702e-01 6.23587742e-02 5.27718782e-01
4.26410109e-01 -1.06594002e+00 9.27160740e-01 4.25854743e-01
-1.48804295e+00 -5.21797359e-01 1.38996705e-01 -1.46961575e-02
4.47778463e-01 1.00069666e+00 -2.75371343e-01 5.24033189e-01
1.15638709e+00 6.23951614e-01 -3.23448889e-02 5.60916722e-01
1.39864117e-01 7.45710492e-01 -7.89131165e-01 3.39580238e-01
-1.39419451e-01 -3.05294603e-01 2.06611399e-02 1.21198118e+00
6.22196905e-02 3.13536003e-02 2.78684020e-01 8.49565804e-01
-2.60974079e-01 -3.20288152e-01 -4.42698538e-01 3.86197090e-01
4.64604139e-01 1.22901833e+00 -1.25542030e-01 -5.04707396e-01
-6.01657093e-01 1.10718513e+00 -3.72174472e-01 3.54626745e-01
-9.06723619e-01 -1.35308340e-01 1.26411283e+00 -7.78634921e-02
3.38784046e-02 -7.23066926e-03 -2.37820402e-01 -7.85464942e-01
-2.25003600e-01 -4.92453784e-01 7.28629589e-01 -5.49102902e-01
-1.83694017e+00 -2.25382045e-01 3.94484401e-01 -7.15195358e-01
-8.44131649e-01 -2.78857052e-01 -1.01250196e+00 8.17072332e-01
-1.47334027e+00 -9.50579703e-01 -4.08111095e-01 6.85151339e-01
7.08849847e-01 -9.62590575e-02 1.12103724e+00 8.21885109e-01
-1.13526392e+00 6.00556731e-01 1.03716123e+00 2.31093585e-01
-1.89789802e-01 -1.67582583e+00 6.04000449e-01 3.05644125e-01
-3.08823228e-01 -5.78284800e-01 6.25545382e-01 -3.51064235e-01
-1.10640430e+00 -1.50533402e+00 5.85268259e-01 -4.77800667e-01
3.07059199e-01 -2.99160749e-01 -6.05922818e-01 9.01405156e-01
7.28071153e-01 -5.14418125e-01 1.30361855e+00 -3.48168612e-01
3.05650771e-01 -5.51693439e-01 -1.56902313e+00 -1.32097363e-01
5.60202241e-01 -6.46337271e-01 -4.32467014e-01 5.91615260e-01
2.87930489e-01 2.18181714e-01 -1.28643060e+00 4.46768463e-01
2.39778399e-01 -8.29966187e-01 7.81862617e-01 -4.91180234e-02
-5.70606291e-01 -1.18049659e-01 -5.79638958e-01 -1.60289609e+00
-9.83870029e-01 -6.57057941e-01 -1.32395017e+00 1.57738066e+00
-3.77866179e-01 -7.68146396e-01 4.96034563e-01 9.47020769e-01
1.62344649e-01 -4.99822915e-01 -1.10885262e+00 -9.27482009e-01
1.37664244e-01 -4.93915200e-01 1.63459730e+00 8.65462661e-01
1.06372960e-01 1.27375126e-01 -1.19485602e-01 2.75789231e-01
9.01974142e-01 3.82227331e-01 1.86168626e-01 -1.14872098e+00
2.37397149e-01 -9.02660966e-01 -3.61691639e-02 -5.56367934e-01
1.91000149e-01 -6.43295825e-01 -2.24459827e-01 -1.83905947e+00
1.52170703e-01 2.82455564e-01 -6.76167250e-01 5.89537680e-01
6.04582310e-01 3.54921818e-01 -2.94846624e-01 1.97538733e-01
-2.36514747e-01 6.30473733e-01 2.31568158e-01 -5.95213532e-01
-2.79795140e-01 2.61724770e-01 -4.27237660e-01 8.16375256e-01
1.51481152e+00 -4.97610904e-02 -3.39969337e-01 -2.61180878e-01
-1.70335174e-01 -5.83920479e-01 4.89222705e-02 -9.28566754e-01
-1.25184104e-01 -2.14199439e-01 7.89103031e-01 -1.49022198e+00
-5.76161407e-02 -1.14669621e+00 6.54886663e-01 5.78649938e-01
1.01089098e-01 2.47844845e-01 2.63618976e-01 1.64634183e-01
2.91807115e-01 1.37256414e-01 9.97781157e-01 -1.20155044e-01
-8.35210800e-01 3.21001440e-01 -8.19895208e-01 -4.29069310e-01
1.29288781e+00 1.29328415e-01 -2.73258150e-01 -2.26084560e-01
-8.49413097e-01 5.86994946e-01 -1.28884643e-01 5.11261821e-01
-2.42914677e-01 -1.89480913e+00 -5.46790302e-01 2.90065557e-01
-2.91312248e-01 -3.02552909e-01 2.01599553e-01 5.32492816e-01
3.30897537e-03 6.37248695e-01 3.14873219e-01 -4.63763744e-01
-7.89591730e-01 9.51117873e-01 9.12747145e-01 -3.66258562e-01
-5.18535495e-01 3.29431929e-02 -5.28562814e-02 -2.05695748e-01
3.37096930e-01 -6.00296259e-01 -2.12843046e-01 6.91386819e-01
7.39420116e-01 1.47252429e+00 5.11043549e-01 -6.28960609e-01
-4.49393719e-01 3.46568763e-01 2.83060074e-01 7.29608357e-01
1.36656141e+00 -6.38998449e-01 -2.52175957e-01 5.65953314e-01
1.71852756e+00 -8.95782053e-01 -7.14933872e-01 5.24363248e-04
1.24563366e-01 1.16718441e-01 4.23458904e-01 -1.16513240e+00
-1.35373974e+00 5.94642639e-01 1.25448406e+00 1.01004374e+00
1.67472398e+00 5.76461293e-02 1.41861081e+00 1.77060157e-01
3.88199270e-01 -1.68531096e+00 -5.58179677e-01 -1.17496744e-01
4.02591646e-01 -1.36682129e+00 -7.35033974e-02 4.64460939e-01
4.17689592e-01 7.35140622e-01 3.74933183e-01 1.89297304e-01
1.37583828e+00 6.18161142e-01 -1.97058573e-01 5.86885922e-02
-4.50709194e-01 -1.62576750e-01 2.65218019e-02 7.83597946e-01
1.33091018e-01 7.05314398e-01 8.46621320e-02 6.06164932e-01
-2.94593930e-01 1.63199529e-01 -7.62935728e-02 7.06462443e-01
-1.97602317e-01 -8.88706386e-01 -2.37313822e-01 1.03224027e+00
-2.86548138e-01 3.53945524e-01 1.60630837e-01 4.15654123e-01
4.00023103e-01 1.34761631e+00 3.89394671e-01 -2.99089968e-01
5.76648414e-01 3.40498120e-01 1.29822552e-01 1.29389046e-02
-2.63843834e-01 -6.99476004e-02 -2.02955499e-01 -7.13939071e-01
-3.61265928e-01 -6.55330837e-01 -8.77641976e-01 -1.22360349e+00
-2.31874824e-01 -2.17905954e-01 4.91511405e-01 1.01512825e+00
2.47453541e-01 7.80162632e-01 1.18993068e+00 -1.20382607e+00
-5.15858769e-01 -1.12424314e+00 -9.64931071e-01 4.63357031e-01
6.09055698e-01 -2.98505694e-01 -3.43032598e-01 -1.41874358e-01] | [16.051790237426758, 7.571531772613525] |
651010cd-a768-42c4-8c26-a4d726e8891d | learning-term-embeddings-for-taxonomic | null | null | https://aclanthology.org/D16-1039 | https://aclanthology.org/D16-1039.pdf | Learning Term Embeddings for Taxonomic Relation Identification Using Dynamic Weighting Neural Network | null | ['See Kiong Ng', 'Anh Tuan Luu', 'Yi Tay', 'Siu Cheung Hui'] | 2016-11-01 | null | null | null | emnlp-2016-11 | ['learning-word-embeddings'] | ['methodology'] | [-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] | [-7.355753421783447, 3.682218551635742] |
f6c44c8c-94c1-405d-b4ae-df50ef0bde6d | learning-to-generate-text-grounded-mask-for | 2212.00785 | null | https://arxiv.org/abs/2212.00785v2 | https://arxiv.org/pdf/2212.00785v2.pdf | Learning to Generate Text-grounded Mask for Open-world Semantic Segmentation from Only Image-Text Pairs | We tackle open-world semantic segmentation, which aims at learning to segment arbitrary visual concepts in images, by using only image-text pairs without dense annotations. Existing open-world segmentation methods have shown impressive advances by employing contrastive learning (CL) to learn diverse visual concepts and transferring the learned image-level understanding to the segmentation task. However, these CL-based methods suffer from a train-test discrepancy, since it only considers image-text alignment during training, whereas segmentation requires region-text alignment during testing. In this paper, we proposed a novel Text-grounded Contrastive Learning (TCL) framework that enables a model to directly learn region-text alignment. Our method generates a segmentation mask for a given text, extracts text-grounded image embedding from the masked region, and aligns it with text embedding via TCL. By learning region-text alignment directly, our framework encourages a model to directly improve the quality of generated segmentation masks. In addition, for a rigorous and fair comparison, we present a unified evaluation protocol with widely used 8 semantic segmentation datasets. TCL achieves state-of-the-art zero-shot segmentation performances with large margins in all datasets. Code is available at https://github.com/kakaobrain/tcl. | ['Byungseok Roh', 'Jonghwan Mun', 'Junbum Cha'] | 2022-12-01 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Cha_Learning_To_Generate_Text-Grounded_Mask_for_Open-World_Semantic_Segmentation_From_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Cha_Learning_To_Generate_Text-Grounded_Mask_for_Open-World_Semantic_Segmentation_From_CVPR_2023_paper.pdf | cvpr-2023-1 | ['unsupervised-semantic-segmentation-with', 'zero-shot-segmentation'] | ['computer-vision', 'computer-vision'] | [ 6.05044723e-01 2.37574026e-01 -3.71205181e-01 -5.07966161e-01
-1.16267788e+00 -6.75230920e-01 4.86564368e-01 -1.05118491e-01
-5.27208924e-01 2.89362818e-01 -1.18370362e-01 -1.39096037e-01
3.77906859e-01 -6.44367933e-01 -9.27498281e-01 -6.28373265e-01
4.99898970e-01 6.26662493e-01 7.39528835e-01 -9.56312194e-02
2.54304141e-01 -8.32016617e-02 -1.34620106e+00 3.55715722e-01
1.24770570e+00 9.81563866e-01 5.36910176e-01 6.41107321e-01
-4.92067993e-01 7.53574789e-01 -3.58371109e-01 -4.05714959e-01
3.63565445e-01 -7.30979502e-01 -1.22887075e+00 2.62914360e-01
6.01324975e-01 -2.48524159e-01 6.08022101e-02 1.20901990e+00
2.52692789e-01 8.60900208e-02 6.35520160e-01 -1.41990852e+00
-7.52378166e-01 6.33388042e-01 -7.34004557e-01 -2.75039524e-02
-3.73224192e-03 3.29428434e-01 1.25123549e+00 -8.77979100e-01
7.30946958e-01 8.52742791e-01 4.60692495e-01 8.19257617e-01
-1.26435590e+00 -4.90196854e-01 2.30382293e-01 1.67192623e-01
-1.20072246e+00 -1.92798167e-01 8.66670549e-01 -5.69452524e-01
5.71949124e-01 2.23026305e-01 8.48596513e-01 9.52283978e-01
-1.54433772e-01 1.30951631e+00 1.07719386e+00 -4.56918836e-01
3.56645912e-01 3.11965067e-02 1.64428413e-01 7.77995646e-01
-4.63024825e-02 -2.49959603e-01 -3.36944997e-01 4.51970756e-01
6.83361351e-01 4.63492312e-02 -2.49986380e-01 -6.68818533e-01
-1.18527246e+00 7.56390810e-01 6.96016014e-01 3.17924947e-01
-2.82523734e-03 2.68298775e-01 3.80007803e-01 -7.49981031e-02
6.76364005e-01 2.00802162e-01 -4.17606175e-01 1.15726031e-01
-1.34790301e+00 -6.06645308e-02 6.37943208e-01 1.00937998e+00
1.15899384e+00 -8.96861032e-02 -3.72224301e-01 9.08328772e-01
2.44072542e-01 5.47544956e-01 4.13351119e-01 -9.38735664e-01
3.87851655e-01 6.54840112e-01 -3.65344763e-01 -5.36191702e-01
-1.01922296e-01 -1.32494777e-01 -6.14762366e-01 1.38175845e-01
4.92355168e-01 -1.30212773e-02 -1.50217736e+00 1.54006410e+00
3.71324688e-01 4.35387224e-01 9.00672972e-02 1.05153382e+00
8.66484046e-01 6.77939892e-01 1.50753245e-01 1.55521631e-01
1.24463654e+00 -1.54734063e+00 -4.45260584e-01 -6.29562914e-01
6.36118233e-01 -6.82655334e-01 1.51849318e+00 7.84471855e-02
-1.06883550e+00 -4.90825772e-01 -1.06632948e+00 -5.66684902e-01
-4.24037993e-01 -7.05121383e-02 2.03451335e-01 5.09560823e-01
-1.05027199e+00 2.83092946e-01 -8.37837636e-01 -3.09111297e-01
8.11955392e-01 1.34211304e-02 -5.12070134e-02 -1.66513965e-01
-9.32725370e-01 4.74116534e-01 5.72356701e-01 -9.53448713e-02
-1.05495059e+00 -7.05736220e-01 -1.06469297e+00 3.48096006e-02
8.02191138e-01 -5.73262691e-01 1.24429488e+00 -1.30636251e+00
-1.36200917e+00 1.32090342e+00 -1.83950830e-02 -4.34598207e-01
7.95582592e-01 -1.99819133e-01 7.12107047e-02 4.72144663e-01
4.51591879e-01 1.31847107e+00 9.00670767e-01 -1.58136666e+00
-4.22848970e-01 -2.58170336e-01 -6.52943626e-02 1.92535311e-01
-3.40314768e-02 -3.29579175e-01 -1.03368163e+00 -5.45467436e-01
1.22727931e-01 -8.09466720e-01 -3.80117953e-01 2.74346918e-01
-6.80672288e-01 -4.56323363e-02 9.10809636e-01 -6.09032929e-01
8.52551401e-01 -2.07199025e+00 1.75394237e-01 -7.90335536e-02
3.47428143e-01 4.22201395e-01 -2.68701822e-01 8.74430984e-02
3.17753881e-01 1.69902042e-01 -9.85837758e-01 -6.41743124e-01
1.05390893e-02 2.92115957e-01 -1.93986133e-01 2.55259037e-01
3.16301614e-01 1.56314969e+00 -8.96060169e-01 -1.01900661e+00
6.33962333e-01 2.56907880e-01 -6.07842207e-01 2.39365175e-01
-7.66804636e-01 4.97486115e-01 -2.89494723e-01 7.81805992e-01
6.85841382e-01 -3.95582676e-01 -7.33449906e-02 -9.44205076e-02
6.46217987e-02 -4.01869506e-01 -7.53499746e-01 1.99611521e+00
-3.30239981e-01 7.58235276e-01 -5.54060079e-02 -1.25193095e+00
7.29718208e-01 -2.81296601e-03 4.42929119e-01 -9.02961910e-01
3.03971112e-01 2.37367108e-01 -3.83606493e-01 -5.19091845e-01
2.69154340e-01 1.15512647e-02 -2.34052464e-01 3.86345744e-01
2.15485319e-01 -6.95052147e-01 1.82992250e-01 3.53624761e-01
5.05444825e-01 2.48371378e-01 5.27652027e-03 -2.91733801e-01
4.30500388e-01 1.83262512e-01 5.14553249e-01 7.62136340e-01
-4.81181711e-01 1.06808162e+00 5.19693315e-01 -1.00108117e-01
-1.16710258e+00 -1.24212027e+00 -6.97047040e-02 1.17575562e+00
5.70890486e-01 -1.08884551e-01 -1.31461120e+00 -8.80173981e-01
-3.16552520e-01 6.90058172e-01 -7.75994897e-01 1.06387913e-01
-3.75843704e-01 -3.22019666e-01 4.94303316e-01 5.91149807e-01
9.13752735e-01 -1.17063367e+00 -6.05111003e-01 -7.96218291e-02
-4.83272523e-01 -1.34449291e+00 -8.90779972e-01 1.15949206e-01
-7.50514209e-01 -1.15227580e+00 -9.62110579e-01 -1.29692495e+00
7.01043963e-01 4.32791114e-01 1.10962844e+00 9.78486165e-02
-6.28276289e-01 3.70301753e-01 -3.43821377e-01 -3.15361500e-01
-3.11529785e-01 1.61684185e-01 -7.47971833e-01 4.77035306e-02
1.84407651e-01 -2.06312567e-01 -7.51597226e-01 3.98922175e-01
-1.18194294e+00 5.24496138e-01 5.05399823e-01 7.83978164e-01
8.57078135e-01 -5.49655616e-01 3.68138105e-01 -1.04522741e+00
1.78387761e-01 -2.86103100e-01 -5.56686401e-01 4.44850236e-01
-5.25958538e-01 -5.98341338e-02 3.61561090e-01 -2.10483402e-01
-9.44746792e-01 2.23615125e-01 -2.26056799e-01 -5.78473866e-01
-2.45492488e-01 1.99740395e-01 -1.58839434e-01 3.73570025e-02
5.09610534e-01 3.91985536e-01 4.82627526e-02 -1.48988158e-01
8.81947935e-01 6.57717705e-01 6.92729592e-01 -5.22520959e-01
6.65794373e-01 6.78557575e-01 -5.02348244e-01 -8.23742032e-01
-1.23150063e+00 -7.85585701e-01 -9.21630263e-01 -2.49066204e-01
1.47430587e+00 -8.96437764e-01 -3.11799180e-02 6.70241654e-01
-8.91368985e-01 -1.01034904e+00 -4.61379647e-01 1.49554133e-01
-8.20603490e-01 4.51276511e-01 -5.41746318e-01 -3.79918844e-01
-4.55404073e-01 -1.34991074e+00 1.37626660e+00 3.06424946e-01
1.17547691e-01 -1.14190197e+00 -9.09644514e-05 8.28431487e-01
1.31024852e-01 2.11299554e-01 6.57659829e-01 -6.48079813e-01
-7.47145116e-01 1.39019519e-01 -5.38519025e-01 5.74669540e-01
-5.81451394e-02 -6.02043346e-02 -1.10734892e+00 -1.56406656e-01
-2.19445065e-01 -6.63439274e-01 1.16174626e+00 5.82841396e-01
1.41820097e+00 -3.90016325e-02 -2.60452986e-01 8.53238761e-01
1.55486190e+00 -4.66913581e-02 7.62343466e-01 1.26542747e-01
1.17053366e+00 4.47168946e-01 6.92586899e-01 -5.25685400e-02
3.87681216e-01 4.92176265e-01 2.58961529e-01 -6.39301658e-01
-3.91957849e-01 -3.00255448e-01 1.64912902e-02 6.29325807e-01
3.02971631e-01 -3.64131331e-01 -9.94446039e-01 8.18955183e-01
-1.89360213e+00 -6.21809423e-01 -1.13351375e-01 1.88016558e+00
1.01148307e+00 1.88387185e-01 5.76847419e-02 -1.82689786e-01
8.41131866e-01 2.99059272e-01 -8.44580531e-01 -2.05419466e-01
3.85696031e-02 3.02633077e-01 5.56580544e-01 6.76600873e-01
-1.13503659e+00 1.61050105e+00 5.24574041e+00 1.07389748e+00
-1.12591362e+00 4.27927971e-01 9.62050259e-01 -2.08503939e-02
-3.57738405e-01 1.32818483e-02 -4.36004400e-01 4.37282801e-01
4.47416395e-01 -9.53323394e-02 2.21183285e-01 8.49932790e-01
1.82834119e-02 -2.16673031e-01 -9.70933020e-01 9.27285969e-01
3.03683519e-01 -1.43710935e+00 1.68605939e-01 -1.55703604e-01
1.23019731e+00 2.45748207e-01 6.85666054e-02 2.92430431e-01
1.53284892e-01 -9.02913034e-01 8.33848298e-01 2.02846080e-01
8.95391166e-01 -4.09714490e-01 5.03129959e-01 1.27731219e-01
-1.27640653e+00 1.57845914e-01 -8.27770606e-02 3.22954386e-01
2.71489263e-01 5.24228394e-01 -5.84111989e-01 4.40949291e-01
6.45896137e-01 8.29157352e-01 -7.44273365e-01 8.87437165e-01
-3.68680567e-01 6.77851856e-01 3.26093398e-02 1.57955378e-01
5.91021538e-01 -3.74036640e-01 3.31910431e-01 1.21343505e+00
-1.41903520e-01 -1.93449870e-01 5.04186690e-01 1.23255706e+00
-2.50318795e-01 2.22900569e-01 -4.10596699e-01 9.16382356e-04
3.17130148e-01 1.24573469e+00 -1.34012926e+00 -6.12088501e-01
-3.35273296e-01 1.41274607e+00 2.98146546e-01 4.42674756e-01
-1.00895321e+00 -4.19671059e-01 2.99542993e-01 -1.71992723e-02
4.21096683e-01 -6.59205690e-02 -5.55556118e-01 -1.18810010e+00
-3.23544890e-02 -5.59278548e-01 2.89477378e-01 -8.84323597e-01
-1.06793165e+00 3.88871700e-01 5.86821735e-02 -1.10487497e+00
8.11551064e-02 -4.39088911e-01 -7.37512648e-01 4.66266841e-01
-1.38639164e+00 -1.39337838e+00 -4.75181133e-01 6.22701287e-01
1.12487149e+00 2.07487106e-01 2.88999915e-01 1.24515139e-01
-5.60956538e-01 5.38685739e-01 -4.01819795e-02 4.74832892e-01
5.99415302e-01 -1.47721982e+00 6.90998971e-01 9.50987041e-01
3.33176583e-01 1.38953209e-01 3.99458855e-01 -6.42759681e-01
-8.30806732e-01 -1.32185686e+00 3.31446618e-01 -3.88695061e-01
5.88139772e-01 -6.59153759e-01 -1.00542939e+00 7.01719999e-01
3.53061229e-01 2.96705276e-01 3.62583488e-01 -2.92165458e-01
-2.90960252e-01 1.11228496e-01 -1.04126990e+00 6.85448408e-01
1.07199240e+00 -6.41526699e-01 -5.52315116e-01 2.74082541e-01
1.00728893e+00 -4.23497289e-01 -4.78431463e-01 1.97905764e-01
3.31464350e-01 -9.55486655e-01 9.36755300e-01 -2.00332910e-01
6.25486732e-01 -2.95525432e-01 5.52792219e-04 -1.13730192e+00
2.45351851e-01 -2.44935483e-01 2.91815221e-01 1.11596513e+00
4.18910980e-01 -5.08111119e-01 8.15019608e-01 3.51987392e-01
-3.90521169e-01 -8.12591434e-01 -8.07556629e-01 -6.50324821e-01
3.58191311e-01 -4.48508322e-01 8.48210156e-02 9.59591806e-01
-2.48933926e-01 3.65456581e-01 -1.78947538e-01 -7.70414248e-02
7.70497859e-01 1.46869689e-01 6.91655397e-01 -1.00161636e+00
-1.40611902e-01 -6.02078736e-01 -3.60944539e-01 -1.12129366e+00
2.56520212e-01 -1.14390051e+00 5.44026434e-01 -1.84083104e+00
5.53792059e-01 -3.05261195e-01 -6.33622184e-02 4.94605273e-01
-4.11184907e-01 8.10488641e-01 3.95439178e-01 1.15058795e-01
-1.01094162e+00 5.25016367e-01 1.63252068e+00 -4.16918129e-01
-2.08216637e-01 -3.06302756e-01 -5.74159563e-01 6.95013404e-01
9.27769661e-01 -3.92874718e-01 -6.40197873e-01 -4.09847617e-01
-2.41608307e-01 -1.97381288e-01 6.61333084e-01 -1.02712727e+00
1.37202650e-01 -1.04373656e-01 2.14613259e-01 -6.35768116e-01
1.07345060e-01 -4.29316849e-01 -3.89431536e-01 4.63900447e-01
-4.33669955e-01 -6.38872266e-01 1.60667151e-01 5.98162651e-01
-2.19654381e-01 -3.04695666e-01 9.72357750e-01 -2.61406481e-01
-1.05299258e+00 4.02544498e-01 -7.59205520e-02 7.18189955e-01
1.21510935e+00 -3.86947691e-01 -3.95603597e-01 -9.92970094e-02
-7.04839826e-01 5.24975240e-01 7.46531069e-01 4.75185961e-01
6.22607529e-01 -8.79720151e-01 -5.71888328e-01 1.86491489e-01
3.63770574e-01 4.76487905e-01 5.07956147e-01 9.12648499e-01
-6.81822300e-01 1.81150705e-01 -9.81568098e-02 -1.12322235e+00
-1.19297385e+00 5.12307703e-01 3.99696678e-01 3.18786204e-02
-7.90503561e-01 1.03676820e+00 6.45263135e-01 -5.82239926e-01
1.56879887e-01 -4.80112731e-01 2.23983884e-01 -1.29593192e-02
2.51369476e-01 5.04572205e-02 -1.74363956e-01 -5.66281736e-01
-1.57704934e-01 9.96327460e-01 -1.61580488e-01 -3.11895043e-01
8.66640210e-01 -1.98349640e-01 1.00056112e-01 6.00177348e-01
1.45765793e+00 -3.62969398e-01 -1.74332392e+00 -3.15596312e-01
-7.82541707e-02 -4.04575765e-01 1.38810158e-01 -7.35734224e-01
-1.28599823e+00 1.08064854e+00 6.02998137e-01 -3.31513137e-02
1.00234687e+00 4.16430444e-01 1.06994736e+00 1.36467159e-01
1.83769256e-01 -1.29460406e+00 6.27797484e-01 3.56992751e-01
4.71545815e-01 -1.64023566e+00 -2.58962214e-01 -6.26593709e-01
-1.04573572e+00 7.56438375e-01 7.15654969e-01 -5.50379008e-02
4.08018440e-01 6.43484816e-02 3.90171260e-01 -2.25758389e-01
-2.98156559e-01 -7.75631726e-01 4.17171925e-01 5.81508458e-01
1.11754656e-01 8.09425861e-02 -6.77693784e-02 2.95780629e-01
7.82459006e-02 -9.69183818e-02 3.76622528e-01 9.11857486e-01
-6.08877361e-01 -9.47129011e-01 -6.65899441e-02 3.34683567e-01
-1.37890548e-01 -2.07388982e-01 -4.62208271e-01 7.02343822e-01
1.40861526e-01 8.38609457e-01 2.96606570e-01 -1.21651039e-01
2.53004767e-03 9.27783847e-02 4.59107965e-01 -7.52498865e-01
-2.49810204e-01 2.07804531e-01 -4.09873158e-01 -6.70498967e-01
-4.76335675e-01 -5.67547262e-01 -1.62820160e+00 1.36704043e-01
-2.44832143e-01 5.55037670e-02 5.73264539e-01 1.05093384e+00
1.22481763e-01 5.89033544e-01 4.57108051e-01 -8.82084846e-01
-3.94610316e-03 -6.93631709e-01 -4.25309420e-01 6.28954291e-01
3.33146662e-01 -4.24443334e-01 -3.60428035e-01 4.14949507e-01] | [9.714420318603516, 0.7795840501785278] |
1bc46737-0f28-458e-b98a-45bb44f85d34 | eda-easy-data-augmentation-techniques-for | 1901.11196 | null | https://arxiv.org/abs/1901.11196v2 | https://arxiv.org/pdf/1901.11196v2.pdf | EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks | We present EDA: easy data augmentation techniques for boosting performance on text classification tasks. EDA consists of four simple but powerful operations: synonym replacement, random insertion, random swap, and random deletion. On five text classification tasks, we show that EDA improves performance for both convolutional and recurrent neural networks. EDA demonstrates particularly strong results for smaller datasets; on average, across five datasets, training with EDA while using only 50% of the available training set achieved the same accuracy as normal training with all available data. We also performed extensive ablation studies and suggest parameters for practical use. | ['Kai Zou', 'Jason Wei'] | 2019-01-31 | eda-easy-data-augmentation-techniques-for-1 | https://aclanthology.org/D19-1670 | https://aclanthology.org/D19-1670.pdf | ijcnlp-2019-11 | ['text-augmentation', 'subjectivity-analysis'] | ['natural-language-processing', 'natural-language-processing'] | [ 1.31533086e-01 -1.17387697e-01 -5.23500264e-01 -5.03554165e-01
-4.32214260e-01 -4.11289304e-01 7.68213928e-01 3.98319572e-01
-9.95136499e-01 7.98004687e-01 2.51544774e-01 -8.87997031e-01
3.00990492e-01 -5.24338484e-01 -3.36791366e-01 -1.66048214e-01
2.96322145e-02 6.28056705e-01 -3.24416846e-01 -6.43077195e-01
-1.56725626e-02 2.84211487e-01 -1.27428234e+00 5.53708494e-01
5.18196225e-01 6.68992996e-01 -2.68329471e-01 6.28745854e-01
-4.41711515e-01 9.61586595e-01 -8.90626550e-01 -7.52555311e-01
1.43525600e-01 -1.24456935e-01 -1.16799176e+00 -5.33751488e-01
4.63752419e-01 -3.63362640e-01 -4.49848711e-01 4.10758704e-01
7.98433661e-01 2.37923056e-01 5.05104303e-01 -1.19956398e+00
-8.75515163e-01 1.66164780e+00 -6.28327549e-01 4.86994117e-01
2.15133905e-01 -7.59409443e-02 1.33684289e+00 -1.22898471e+00
4.30480748e-01 1.08949172e+00 1.18375909e+00 6.71568155e-01
-1.31256437e+00 -1.06941450e+00 3.09935242e-01 -1.36638254e-01
-1.20976138e+00 -5.36096275e-01 2.16603965e-01 1.54864505e-01
1.66332293e+00 3.56383264e-01 3.32273304e-01 1.58056986e+00
-9.12839845e-02 1.05409539e+00 7.07210302e-01 -6.41676486e-01
-1.04887687e-01 -7.76374638e-02 1.07515156e+00 5.23120344e-01
4.93231833e-01 -3.53836626e-01 -6.95758045e-01 -5.73427498e-01
3.27018686e-02 3.38752083e-02 -6.48886263e-02 3.31158578e-01
-1.00810540e+00 8.60608399e-01 3.98289502e-01 2.76869774e-01
-1.85416058e-01 3.61396164e-01 8.03924263e-01 5.98474264e-01
6.15744650e-01 8.78352165e-01 -9.58676517e-01 -3.76834065e-01
-6.97837710e-01 3.03190529e-01 6.61898851e-01 8.26570511e-01
3.06455880e-01 1.83561176e-01 -4.11653638e-01 1.42030847e+00
-3.85751218e-01 3.59370798e-01 1.12232673e+00 -3.76707524e-01
7.18788385e-01 7.28193402e-01 -1.68890193e-01 -4.34510916e-01
-1.02435648e+00 -7.91868329e-01 -1.26476240e+00 -1.77547932e-01
3.22057456e-01 -5.82400143e-01 -1.08152986e+00 1.80433011e+00
-3.50747108e-01 -1.65876836e-01 4.26154919e-02 1.11634538e-01
1.22522569e+00 4.79005009e-01 2.81660020e-01 7.00317845e-02
1.23609209e+00 -1.06709290e+00 -9.15038109e-01 -6.18120074e-01
1.45772934e+00 -6.76053882e-01 1.31354344e+00 4.32462960e-01
-1.16273808e+00 -4.03537542e-01 -1.03599119e+00 -3.45835865e-01
-7.83109367e-01 4.70927626e-01 1.06890619e+00 8.58227968e-01
-1.11212802e+00 5.07473409e-01 -5.75554788e-01 -2.89011210e-01
4.81849879e-01 4.11220133e-01 -4.49194014e-01 1.02846302e-01
-1.60135889e+00 9.74929690e-01 4.59568352e-01 1.04463533e-01
-1.17001273e-01 -8.15242350e-01 -7.86177576e-01 7.85920769e-02
-1.03644542e-01 -9.36012566e-01 1.60078204e+00 -5.52724004e-01
-1.09330297e+00 1.11105680e+00 -1.60747617e-01 -1.07176697e+00
3.63745123e-01 -7.88532913e-01 -4.38027292e-01 -7.51132190e-01
-1.64863393e-01 8.05265129e-01 5.54644287e-01 -6.22993231e-01
-5.18977344e-01 -1.79400027e-01 -2.85334080e-01 1.83139235e-01
-7.19174802e-01 1.92088142e-01 -2.03785419e-01 -1.08755624e+00
-9.43116993e-02 -9.05063570e-01 -4.16940302e-02 -4.41345274e-01
-6.00445926e-01 -5.28257132e-01 7.20424891e-01 -6.63687825e-01
1.56097388e+00 -1.82864451e+00 -6.50745258e-02 3.84012423e-02
2.87163168e-01 4.59004134e-01 -3.72573465e-01 3.28808159e-01
-6.80148661e-01 5.17563045e-01 -2.22499482e-02 -7.52808452e-01
-1.38734683e-01 -4.27663326e-05 -6.91581368e-01 -8.77995510e-03
1.01196878e-01 1.16801429e+00 -5.72393239e-01 1.55929010e-02
-1.12181030e-01 2.85404086e-01 -5.90380013e-01 -2.45818928e-01
-1.12046763e-01 -2.28449956e-01 -9.56138819e-02 3.27781409e-01
5.17314136e-01 -5.63182294e-01 1.18847273e-01 1.75083444e-01
5.71162939e-01 8.83304954e-01 -8.47691476e-01 1.53612292e+00
-9.43751514e-01 9.46476281e-01 -4.08547223e-01 -5.37867546e-01
8.76364529e-01 7.10547641e-02 1.45430192e-01 -7.33298063e-01
1.53640360e-01 1.04655541e-01 1.57510951e-01 9.32820067e-02
1.03203380e+00 4.42464530e-01 -1.98101386e-01 9.62711036e-01
-6.19771481e-02 1.08650841e-01 -1.62533857e-02 6.48515463e-01
1.42476583e+00 -3.93151909e-01 3.79986674e-01 5.59464889e-03
1.20772034e-01 -2.71043658e-01 -2.30347980e-02 1.40061486e+00
2.28723660e-01 3.11835468e-01 4.52569038e-01 -9.15792644e-01
-1.01925325e+00 -3.28132242e-01 -2.97485948e-01 1.77949142e+00
-5.94832718e-01 -9.70505953e-01 -4.52221870e-01 -9.21347618e-01
3.06012541e-01 1.05835843e+00 -1.09128034e+00 -5.08293629e-01
-6.19625986e-01 -1.42753959e+00 1.11029196e+00 7.30276108e-01
6.52693033e-01 -1.22930074e+00 -8.30606222e-02 -1.22501934e-02
-1.08092703e-01 -9.39175725e-01 -3.78894866e-01 8.04618061e-01
-8.02818418e-01 -5.89861512e-01 -4.08232838e-01 -6.81668580e-01
2.31675193e-01 3.72245729e-01 1.68244994e+00 6.04363441e-01
-3.03077519e-01 -1.79417893e-01 -6.34585083e-01 -4.22525793e-01
-5.48660219e-01 9.88028347e-01 -8.94555748e-02 -6.88844800e-01
5.44381499e-01 -4.19272989e-01 -2.02221200e-01 1.92398295e-01
-6.15090668e-01 9.45668444e-02 3.55350792e-01 1.30203092e+00
-2.39906415e-01 -2.39427879e-01 7.71033645e-01 -1.35382307e+00
1.08554208e+00 -3.79167199e-01 -4.20974120e-02 2.06768572e-01
-8.28362763e-01 1.76775351e-01 6.38911366e-01 -3.90546262e-01
-7.46136129e-01 -3.70496243e-01 -4.68683839e-01 1.19308375e-01
1.51809469e-01 6.25821471e-01 3.87726724e-01 4.46180016e-01
1.24879372e+00 3.21455523e-02 -2.13172644e-01 -5.75726390e-01
5.18954158e-01 9.07983780e-01 3.80225360e-01 -4.26751167e-01
3.48111123e-01 1.47429168e-01 -4.33151424e-01 -5.45001686e-01
-9.17072177e-01 -3.07973444e-01 -5.63777566e-01 5.95463455e-01
1.60082281e-01 -1.09881389e+00 -6.60611749e-01 8.68038535e-01
-1.18078351e+00 -4.85284477e-01 -2.88563728e-01 1.66002661e-01
2.59614706e-01 3.07558458e-02 -7.74573207e-01 -4.23860043e-01
-1.03083467e+00 -8.64510298e-01 8.38973641e-01 -1.83605671e-01
-7.74860263e-01 -1.01574957e+00 -1.99505642e-01 1.84767529e-01
5.87789416e-01 -5.37366033e-01 1.16347134e+00 -1.40806627e+00
2.50590056e-01 -3.10249656e-01 -1.16331071e-01 2.46751562e-01
4.79728639e-01 2.02405043e-02 -1.06066144e+00 -4.70733374e-01
-6.04479790e-01 -7.37989247e-01 1.53462529e+00 3.62964183e-01
1.68427706e+00 -1.38908550e-01 -3.65442157e-01 7.11373150e-01
5.58856785e-01 4.34745550e-02 4.21913415e-01 5.03227055e-01
7.53893137e-01 1.69133989e-03 1.99031428e-01 6.21108770e-01
4.41801399e-02 7.17106223e-01 4.88400608e-02 -3.30774695e-01
-2.06310660e-01 -7.98217878e-02 7.46835843e-02 6.35962188e-01
2.82293320e-01 -6.57111049e-01 -1.26979399e+00 3.41463208e-01
-1.65212226e+00 -6.21347666e-01 -2.27890655e-01 1.96514487e+00
1.11735845e+00 5.18094540e-01 1.97607860e-01 3.02790791e-01
6.79711401e-01 1.94563046e-01 -7.14756966e-01 -7.29920805e-01
-5.96213460e-01 6.88480318e-01 7.04919457e-01 3.45704138e-01
-1.16077936e+00 1.07199013e+00 8.27432919e+00 8.84985805e-01
-9.11084235e-01 6.27497137e-02 9.76062894e-01 -3.51294845e-01
-3.85244250e-01 -4.12714183e-01 -1.13565445e+00 4.05385464e-01
9.58599806e-01 1.09435683e-02 3.71092707e-01 7.38690674e-01
-4.40887064e-01 3.20152968e-01 -1.15421116e+00 1.07576680e+00
5.89832850e-02 -1.56939149e+00 4.07707185e-01 -3.66185069e-01
6.86597943e-01 3.79466444e-01 2.25869119e-01 7.32130110e-01
1.17742991e+00 -1.37160027e+00 1.51924074e-01 -1.90852135e-01
8.57770503e-01 -8.58471692e-01 9.10116971e-01 8.22406262e-02
-5.58009744e-01 -2.63726354e-01 -1.32500008e-01 -2.51857996e-01
-4.59347039e-01 7.33553052e-01 -1.09231067e+00 2.68517911e-01
6.87147498e-01 9.72759902e-01 -1.22907853e+00 3.95186752e-01
-2.38509744e-01 7.38104582e-01 -4.61787522e-01 -2.80711114e-01
1.55734628e-01 4.48923171e-01 2.18501478e-01 1.48597753e+00
-2.81378627e-01 -4.11330163e-01 -2.63370156e-01 1.42619044e-01
-8.96492362e-01 1.66598305e-01 -6.08815908e-01 2.19673485e-01
7.92198181e-01 1.09320676e+00 -5.25940835e-01 -4.86478508e-01
-2.74920881e-01 8.08625937e-01 7.26419985e-01 3.50149453e-01
-7.10533381e-01 -5.43178856e-01 6.04746461e-01 -4.18709725e-01
7.99112171e-02 1.52424574e-01 -6.07430041e-01 -1.10935163e+00
-7.00350255e-02 -1.22478938e+00 9.45551634e-01 -8.87783587e-01
-1.28219783e+00 6.77434325e-01 -6.72324672e-02 -5.67119181e-01
-5.80113232e-01 -5.81900895e-01 -6.31919265e-01 1.01764548e+00
-1.10489142e+00 -9.93876398e-01 -2.31756762e-01 4.10093606e-01
6.62145972e-01 -6.85231268e-01 1.12033057e+00 2.13570222e-01
-1.01468849e+00 1.46134531e+00 4.07401413e-01 6.57575846e-01
9.75186527e-01 -1.24108398e+00 1.59704888e+00 5.72203696e-01
1.44434124e-01 8.52891028e-01 4.59382147e-01 -5.73982477e-01
-9.45646644e-01 -9.31361914e-01 9.03218091e-01 -4.94078696e-01
6.91568613e-01 -6.28575444e-01 -1.14603829e+00 1.33353424e+00
3.67886990e-01 -3.53795700e-02 6.26515210e-01 1.06053519e+00
-7.28265107e-01 1.13951266e-02 -7.13683069e-01 7.69531965e-01
1.24175596e+00 -4.65662956e-01 -5.91176569e-01 4.72697139e-01
8.09221387e-01 -4.04663354e-01 -5.27650654e-01 4.14986938e-01
6.09851837e-01 -4.49443430e-01 9.59159613e-01 -1.28935075e+00
4.77480322e-01 4.15538818e-01 1.47368848e-01 -1.47498953e+00
-2.41841614e-01 -7.22515643e-01 -1.18200801e-01 1.14344478e+00
8.31357956e-01 -9.89113092e-01 8.19585025e-01 4.90596235e-01
3.56590515e-03 -6.88356459e-01 -7.77414203e-01 -5.91636539e-01
6.39736831e-01 -4.32883859e-01 6.88820958e-01 1.43630493e+00
8.44106637e-03 8.51064503e-01 -3.89829576e-01 -4.79197025e-01
-7.02339411e-02 -1.51028797e-01 8.15233469e-01 -1.06034207e+00
-7.00732246e-02 -7.66021729e-01 -3.59440371e-02 -9.79509234e-01
5.16757667e-01 -1.26685095e+00 -4.56724107e-01 -1.26369417e+00
3.19269806e-01 -7.58430064e-01 -4.14498895e-01 1.20683455e+00
-5.68036735e-01 1.73957512e-01 -1.34258002e-01 1.60023913e-01
-3.40946287e-01 4.73043382e-01 6.40823483e-01 -3.77846301e-01
-2.87494928e-01 -3.63636725e-02 -9.97655809e-01 4.43749040e-01
1.01062775e+00 -5.85020661e-01 -2.61658221e-01 -6.25653923e-01
7.59700060e-01 -4.10531491e-01 9.44484258e-04 -6.16381943e-01
9.90201980e-02 3.96921366e-01 6.65241480e-01 -7.33188808e-01
1.48428157e-01 -3.19284827e-01 -2.76737601e-01 5.40735364e-01
-1.17523146e+00 7.04617679e-01 7.19312787e-01 2.79499181e-02
7.41107836e-02 -3.30551445e-01 6.04284525e-01 1.66551143e-01
-3.66828740e-01 -2.34142020e-01 -4.90442485e-01 3.27938974e-01
3.31311166e-01 1.83670014e-01 -7.17793405e-01 -4.20264244e-01
-6.06385887e-01 3.47437680e-01 9.06723514e-02 6.99877739e-01
3.51304591e-01 -1.23900604e+00 -9.58533645e-01 3.21552843e-01
1.20873019e-01 -1.00053534e-01 -6.27222646e-04 2.72106558e-01
-2.25322947e-01 6.06600702e-01 -6.53955787e-02 -3.75242740e-01
-1.53986919e+00 4.56105351e-01 5.29938459e-01 -6.85638785e-01
-6.26239419e-01 9.55469012e-01 -2.20691934e-01 -7.66267061e-01
5.31101763e-01 -4.52630728e-01 -2.60766089e-01 8.63420516e-02
6.15871310e-01 3.11078757e-01 8.68035078e-01 1.20835558e-01
-3.42585534e-01 2.31761988e-02 -1.09231257e+00 1.57537237e-01
1.04579091e+00 2.01564342e-01 6.02405667e-02 4.33328271e-01
1.13274276e+00 -7.74549553e-03 -2.65870035e-01 -5.75883865e-01
-8.91838446e-02 3.06694265e-02 3.33400905e-01 -1.29053092e+00
-9.66427207e-01 6.54494226e-01 3.75437260e-01 2.22985491e-01
9.57396328e-01 -3.47639263e-01 6.15981221e-01 1.24879777e+00
-2.69314170e-01 -8.53976369e-01 -6.70790151e-02 9.36947465e-01
7.94713676e-01 -1.21054375e+00 3.48314166e-01 5.07138632e-02
-6.22480929e-01 9.31897998e-01 6.70943141e-01 3.18457514e-01
7.31301129e-01 3.74323666e-01 7.89414421e-02 -8.35232064e-02
-1.36565173e+00 3.62148881e-02 -3.87582090e-03 1.32479504e-01
8.37343872e-01 -2.18805030e-01 -7.35513717e-02 5.47000766e-01
-6.39546216e-01 -1.37275189e-01 5.38109243e-01 1.01112068e+00
1.27466042e-02 -1.17872179e+00 -7.47314766e-02 9.55646694e-01
-7.25003004e-01 -7.64323235e-01 -6.64958298e-01 1.12874711e+00
-4.89243567e-01 5.92903435e-01 4.00137573e-01 -5.03903270e-01
2.72083730e-01 6.27307296e-01 1.41065881e-01 -5.33967018e-01
-1.21231484e+00 -6.68326795e-01 5.18120527e-01 1.47576574e-02
-1.17958903e-01 -6.42267883e-01 -1.20732737e+00 -7.04757333e-01
-3.98930162e-01 1.51312485e-01 7.07873464e-01 7.76245415e-01
5.34267664e-01 7.78375387e-01 5.57807922e-01 -2.56089389e-01
-5.73347390e-01 -1.56700778e+00 -1.01856835e-01 5.60406268e-01
5.07524490e-01 -4.05685991e-01 -3.62443835e-01 -3.68451029e-01] | [10.801412582397461, 7.97304630279541] |
3dd8e516-b029-43d1-a2b9-1bf64b4be9e0 | unsupervised-ct-metal-artifact-learning-using | 2007.03480 | null | https://arxiv.org/abs/2007.03480v1 | https://arxiv.org/pdf/2007.03480v1.pdf | Unsupervised CT Metal Artifact Learning using Attention-guided beta-CycleGAN | Metal artifact reduction (MAR) is one of the most important research topics in computed tomography (CT). With the advance of deep learning technology for image reconstruction,various deep learning methods have been also suggested for metal artifact removal, among which supervised learning methods are most popular. However, matched non-metal and metal image pairs are difficult to obtain in real CT acquisition. Recently, a promising unsupervised learning for MAR was proposed using feature disentanglement, but the resulting network architecture is complication and difficult to handle large size clinical images. To address this, here we propose a much simpler and much effective unsupervised MAR method for CT. The proposed method is based on a novel beta-cycleGAN architecture derived from the optimal transport theory for appropriate feature space disentanglement. Another important contribution is to show that attention mechanism is the key element to effectively remove the metal artifacts. Specifically, by adding the convolutional block attention module (CBAM) layers with a proper disentanglement parameter, experimental results confirm that we can get more improved MAR that preserves the detailed texture of the original image. | ['Jawook Gu', 'Jong Chul Ye', 'Junghyun Lee'] | 2020-07-07 | null | null | null | null | ['metal-artifact-reduction'] | ['medical'] | [ 2.06020564e-01 -1.37392789e-01 -2.50499584e-02 -1.90175399e-01
-7.67930329e-01 3.15275431e-01 2.18281567e-01 -1.27717137e-01
-2.96486109e-01 6.24624789e-01 3.23738873e-01 8.94722342e-02
-4.77374852e-01 -7.28866994e-01 -5.11767447e-01 -1.11642802e+00
2.13267237e-01 -5.64710982e-02 1.50908634e-01 -2.11180210e-01
5.96272387e-02 4.50496644e-01 -8.51841211e-01 1.96409747e-01
9.87309992e-01 9.65453565e-01 3.15655231e-01 3.55372936e-01
4.59335707e-02 1.09818101e+00 -2.56971270e-01 -8.13581049e-02
3.59263211e-01 -8.32655370e-01 -7.49090612e-01 8.74040797e-02
-2.49392949e-02 -3.85160267e-01 -7.16908813e-01 1.17649007e+00
7.93631673e-01 1.12490386e-01 6.83625460e-01 -7.03342557e-01
-6.16770864e-01 7.34143257e-01 -9.08173323e-01 5.28362513e-01
-2.44543478e-01 1.49271637e-01 5.69648862e-01 -8.34284604e-01
2.47219205e-01 9.62965786e-01 5.00184596e-01 5.43543518e-01
-1.01802313e+00 -7.91972160e-01 -1.83937311e-01 4.50168371e-01
-1.34509420e+00 -7.98999891e-02 1.12050343e+00 -2.05119610e-01
3.85222346e-01 4.25063908e-01 7.64048994e-01 9.13137734e-01
7.28235364e-01 7.89064646e-01 1.17421007e+00 -3.67335111e-01
-6.96036518e-02 -2.53816303e-02 2.31633410e-02 7.52238989e-01
4.85306263e-01 1.57661662e-01 -1.00277901e-01 1.09698407e-01
1.13945115e+00 4.82806772e-01 -6.24725759e-01 -4.25425619e-01
-1.27290523e+00 7.82508194e-01 8.90015364e-01 5.40868819e-01
-4.14851546e-01 2.59896815e-01 4.12452757e-01 1.38582988e-02
3.32488030e-01 5.95713735e-01 -7.57438391e-02 2.05346867e-01
-6.05835497e-01 -7.33145177e-02 1.21403687e-01 5.90721428e-01
4.40585852e-01 3.69768560e-01 -2.63358861e-01 7.01986849e-01
3.24361980e-01 4.48938996e-01 8.10388982e-01 -4.67310101e-01
2.03244761e-01 4.76962775e-01 -3.01039159e-01 -1.27751148e+00
-5.41163027e-01 -7.55374193e-01 -1.48126590e+00 2.69599468e-01
1.40043572e-02 -1.14187926e-01 -8.80533218e-01 1.30564880e+00
2.73516029e-01 4.42205846e-01 -2.56312996e-01 1.23004818e+00
8.96337390e-01 3.56679380e-01 4.22729924e-02 -3.67375344e-01
1.59865427e+00 -8.90247166e-01 -9.96801138e-01 -5.48143573e-02
3.87883186e-01 -6.68926954e-01 7.51511335e-01 4.57758844e-01
-9.48687196e-01 -3.70423377e-01 -1.41982973e+00 -1.03013046e-01
8.49639624e-02 -4.03876789e-02 9.80212271e-01 5.54338753e-01
-5.56209922e-01 7.01941550e-01 -1.19017887e+00 -2.82989908e-02
7.08332896e-01 4.97072548e-01 -3.46192271e-01 -1.44624516e-01
-1.12672019e+00 9.59678173e-01 5.79625443e-02 5.90384603e-01
-8.66821766e-01 -5.28955460e-01 -7.30683625e-01 5.53636393e-03
4.34177727e-01 -7.41507709e-01 1.07272124e+00 -1.27221370e+00
-1.65599382e+00 3.13270956e-01 4.37144160e-01 -2.36404091e-01
4.42897946e-01 -2.58073300e-01 -3.08640927e-01 2.85215288e-01
-6.67022318e-02 6.72259405e-02 1.02728009e+00 -1.00336349e+00
-8.63771513e-02 -2.75048226e-01 -3.95660073e-01 1.97871566e-01
-3.96796346e-01 1.25277368e-02 -1.11985438e-01 -1.03015363e+00
4.35513824e-01 -6.91618741e-01 -6.35640919e-01 6.44883290e-02
-3.07000041e-01 1.94078818e-01 3.40012968e-01 -7.89367139e-01
1.15484524e+00 -2.00607467e+00 1.69951722e-01 2.49929622e-01
6.65492654e-01 1.54696688e-01 1.14978246e-01 -6.24633813e-03
-4.15817678e-01 1.01170130e-01 -6.16718411e-01 1.09195113e-01
-6.24713182e-01 -5.21505550e-02 1.41720861e-01 6.90235078e-01
2.77800590e-01 8.97226334e-01 -8.30707252e-01 -6.24563098e-01
2.73733318e-01 4.94396031e-01 -5.94232976e-01 2.38149941e-01
2.03867882e-01 1.01216817e+00 -8.30036998e-01 2.30334744e-01
9.92576063e-01 -4.67906564e-01 1.16960697e-01 -6.17530704e-01
3.27278674e-02 5.32190092e-02 -9.58139896e-01 1.81865525e+00
-3.52143764e-01 4.78474259e-01 -1.71685264e-01 -1.01220977e+00
6.58403456e-01 3.39879662e-01 9.62419927e-01 -9.13387895e-01
5.65789640e-01 2.74242073e-01 4.52271789e-01 -9.37524617e-01
1.88683957e-01 -4.53820050e-01 2.23656312e-01 3.90721023e-01
-2.61017978e-01 5.25717251e-03 -4.53841031e-01 1.30115012e-02
1.14548862e+00 -1.87634230e-01 3.33529651e-01 -4.34974313e-01
5.01879513e-01 -2.43278444e-01 6.66469336e-01 5.02050221e-01
-1.13973789e-01 9.67429459e-01 3.55054177e-02 -6.09899402e-01
-9.67763782e-01 -7.39045322e-01 -1.50785148e-01 1.49527267e-01
3.97344083e-01 6.95378035e-02 -7.09934771e-01 -6.42320096e-01
-5.07466197e-01 6.69839904e-02 -7.05951929e-01 -4.93954450e-01
-1.04391122e+00 -1.10572231e+00 1.97958812e-01 6.27933025e-01
8.18108499e-01 -1.03827643e+00 -4.69196707e-01 2.77204096e-01
-3.14646751e-01 -7.53653288e-01 -4.97520000e-01 1.02048777e-01
-1.07018065e+00 -1.18617427e+00 -9.43397284e-01 -8.37414443e-01
8.87488484e-01 5.74067175e-01 6.33391500e-01 4.93794173e-01
-5.85008562e-01 -7.51809925e-02 -4.53680128e-01 -2.85117060e-01
-1.06182382e-01 9.42542255e-02 -2.16085061e-01 2.59118110e-01
-1.64339505e-02 -5.57035387e-01 -1.12139106e+00 1.22514009e-01
-1.18017209e+00 3.17962885e-01 8.81954670e-01 1.05811882e+00
5.80923021e-01 1.16152175e-01 5.25625706e-01 -8.84255230e-01
4.24130827e-01 -4.54309583e-01 -2.99173295e-01 1.67124383e-02
-5.62378287e-01 2.93883920e-01 5.92835844e-01 -3.81411672e-01
-1.24046695e+00 -1.61476523e-01 -3.32917839e-01 -3.98052961e-01
1.92584887e-01 3.76069158e-01 -1.58412620e-01 -3.08584034e-01
5.52032232e-01 3.45247954e-01 8.68189409e-02 -4.29896742e-01
5.55589423e-02 4.51740712e-01 1.50189847e-01 -3.47073466e-01
7.24838376e-01 7.20998764e-01 2.28497684e-01 -6.22502863e-01
-7.17490494e-01 -1.44556329e-01 -4.05154645e-01 -3.34016718e-02
1.13811922e+00 -7.20685303e-01 -6.65738821e-01 5.24015725e-01
-1.01545322e+00 -5.19957244e-02 -1.93983287e-01 1.08569562e+00
-2.68573880e-01 7.11671293e-01 -7.77243316e-01 -4.86436129e-01
-7.06810892e-01 -1.49977601e+00 5.39986193e-01 3.37906659e-01
2.44761199e-01 -6.59856737e-01 1.32504746e-01 1.58818558e-01
6.05020225e-01 3.58752400e-01 1.13980365e+00 -4.17618215e-01
-7.70364702e-01 3.23087461e-02 -4.24017370e-01 3.63753140e-01
4.20303404e-01 -3.96040410e-01 -6.76095784e-01 -2.28682935e-01
7.00591326e-01 1.15698382e-01 8.83760214e-01 6.22584343e-01
1.54493320e+00 -1.68163121e-01 -2.57512271e-01 8.68693411e-01
1.52014971e+00 3.13079715e-01 9.66348231e-01 5.10513067e-01
1.02370107e+00 1.68795973e-01 3.85006994e-01 2.60732621e-01
9.52373818e-02 5.07461429e-01 6.26608491e-01 -4.48495090e-01
-3.91318142e-01 9.76988971e-02 -1.19595997e-01 1.34683943e+00
-2.40346804e-01 1.14802428e-01 -6.42412543e-01 3.48336875e-01
-1.72252953e+00 -6.86631143e-01 -3.54526579e-01 2.13879681e+00
7.38951087e-01 -6.29068688e-02 -3.15269321e-01 1.49482623e-01
6.25111341e-01 2.66895089e-02 -4.45911765e-01 1.81790933e-01
-3.88330333e-02 6.09681726e-01 5.01249969e-01 2.22504005e-01
-9.84764040e-01 3.92272145e-01 5.38296032e+00 9.19746399e-01
-1.19507933e+00 3.72165203e-01 6.98067367e-01 8.86164084e-02
-3.20938438e-01 -1.67453349e-01 -1.38112098e-01 5.22566617e-01
4.04143035e-01 2.31003791e-01 1.44771159e-01 5.90402186e-01
3.98073941e-01 -5.60721643e-02 -8.03317904e-01 1.28070891e+00
1.31167755e-01 -1.26186240e+00 1.64993498e-02 -4.61501628e-02
6.67828560e-01 -2.55915046e-01 7.32415691e-02 1.35786876e-01
-1.49888113e-01 -9.91154671e-01 2.99063385e-01 6.54950142e-01
6.69937551e-01 -8.08876812e-01 9.85653102e-01 -2.38529779e-02
-9.61465061e-01 1.92621090e-02 -5.26189148e-01 2.60898650e-01
-6.16555735e-02 6.36448801e-01 -4.07047957e-01 9.05119598e-01
6.41741037e-01 7.95388043e-01 -5.25541306e-01 1.48244572e+00
-2.92808682e-01 4.65465218e-01 1.91226639e-02 -3.07809934e-03
-2.63299346e-02 -8.30542371e-02 5.31077325e-01 8.46732020e-01
3.51119608e-01 4.53231573e-01 -2.17497889e-02 6.82528913e-01
-1.11436211e-01 2.36432910e-01 -3.50274891e-01 4.38367307e-01
-5.99376075e-02 1.33666456e+00 -8.87822509e-01 -1.84738770e-01
-3.86980891e-01 9.62332487e-01 8.23500380e-02 1.63404688e-01
-9.40826535e-01 -4.52688873e-01 3.43564004e-01 2.34858871e-01
8.06227922e-02 -1.19275816e-01 -4.05656040e-01 -1.35404217e+00
-1.04720682e-01 -9.36327577e-01 3.33007336e-01 -7.71973729e-01
-1.30969191e+00 7.31033325e-01 -1.74321696e-01 -1.57074058e+00
4.17777389e-01 -4.79221731e-01 -6.40868068e-01 6.60198271e-01
-1.65937221e+00 -1.03555810e+00 -5.45258105e-01 7.05592453e-01
6.67475820e-01 9.11495239e-02 5.44452012e-01 6.45275295e-01
-6.85505092e-01 5.90760648e-01 1.61233589e-01 3.29640508e-01
6.62120938e-01 -9.47919905e-01 -2.01701984e-01 9.35647428e-01
-2.14829311e-01 4.79184031e-01 3.99093419e-01 -6.98835731e-01
-1.53749073e+00 -1.02586102e+00 2.16107145e-01 2.06172261e-02
4.44224387e-01 -5.50892055e-02 -1.02581012e+00 5.35354137e-01
4.34551358e-01 2.01039642e-01 4.82467920e-01 -5.94706953e-01
1.99376326e-02 -2.78429866e-01 -1.10429955e+00 7.20389426e-01
8.14796448e-01 -5.15628643e-02 -4.84922826e-01 3.00195456e-01
7.49291778e-01 -5.44520795e-01 -8.39452684e-01 5.48044562e-01
4.26653892e-01 -8.22399855e-01 8.75866115e-01 -4.41514611e-01
7.57586479e-01 -3.93919557e-01 2.05126449e-01 -1.21476054e+00
-6.53716743e-01 -4.37321126e-01 8.80853161e-02 6.96154535e-01
6.76995739e-02 -7.16636717e-01 7.61945248e-01 4.51530874e-01
-4.19295788e-01 -9.24892366e-01 -9.02645409e-01 -4.57262307e-01
1.48984194e-01 -2.03636482e-01 5.91925681e-01 9.99271333e-01
-1.12188108e-01 1.71679527e-01 -6.66288733e-01 1.58792689e-01
6.71465516e-01 -6.50989264e-02 4.00342882e-01 -9.56165433e-01
-4.06895161e-01 -3.88501853e-01 -4.10530925e-01 -8.82497668e-01
-3.57257575e-01 -1.05250931e+00 9.43840966e-02 -1.47987258e+00
5.81311882e-01 -4.87711877e-01 -6.46645844e-01 2.70046622e-01
-3.39714527e-01 2.47115180e-01 -4.59812805e-02 3.87867838e-01
-2.95133442e-01 8.62921536e-01 1.90042663e+00 -2.90625095e-01
-1.95662174e-02 -1.06024161e-01 -8.50372195e-01 6.47742569e-01
7.08542228e-01 -7.41284847e-01 -2.37234175e-01 -7.09270716e-01
2.30181739e-01 1.71106562e-01 3.18002194e-01 -9.79550898e-01
1.63538471e-01 -1.27091661e-01 5.75411081e-01 -3.16886216e-01
9.90116373e-02 -1.15884984e+00 1.59083024e-01 7.16470838e-01
-1.36489779e-01 -3.08780018e-02 1.30700722e-01 6.03031754e-01
-1.94524929e-01 -1.76357970e-01 1.03717875e+00 -3.55799228e-01
-3.58439445e-01 6.70358837e-01 -3.60239178e-01 -2.32140392e-01
8.20436239e-01 -7.36108571e-02 -6.81448653e-02 -1.49668142e-01
-5.83548784e-01 -6.88609555e-02 -8.64959881e-02 1.26400888e-01
1.02275550e+00 -1.56894195e+00 -8.17071617e-01 3.25548023e-01
-9.61294174e-02 2.30378777e-01 7.26436973e-01 1.40429044e+00
-7.52650976e-01 8.38748887e-02 -2.27605611e-01 -5.83796918e-01
-8.43415499e-01 4.28055078e-01 5.01017094e-01 -6.35237515e-01
-1.01074636e+00 7.31295407e-01 4.95050132e-01 -4.93589602e-03
-2.36087695e-01 -3.78207922e-01 -1.77909553e-01 -5.01469493e-01
6.66394711e-01 3.19823056e-01 3.51568729e-01 -4.15924549e-01
-2.26471290e-01 6.75183892e-01 -4.08489913e-01 2.38749132e-01
1.53106236e+00 -1.48104459e-01 -1.41732082e-01 -1.26608461e-01
1.14019835e+00 7.28603452e-03 -9.89354253e-01 -3.15786600e-01
-2.72771001e-01 -5.92484653e-01 3.07958037e-01 -4.96459544e-01
-1.66775620e+00 9.64575112e-01 9.70840991e-01 -1.29918875e-02
1.23086095e+00 -4.21531200e-01 1.05114770e+00 9.15384851e-03
3.42833430e-01 -6.72266662e-01 4.96297985e-01 9.65144858e-02
8.96751165e-01 -1.34132540e+00 2.65138328e-01 -4.49495494e-01
-4.42378134e-01 1.10998130e+00 6.91975176e-01 -4.55255270e-01
8.28957677e-01 -6.96596317e-03 -4.56116349e-02 -5.03659666e-01
-5.59417047e-02 8.76300335e-02 2.26928473e-01 3.26267272e-01
4.20101374e-01 -5.88259138e-02 -5.93995214e-01 9.31740463e-01
2.39231110e-01 -7.65446946e-02 6.37647569e-01 8.05644274e-01
-3.24701130e-01 -9.68422472e-01 -4.09962505e-01 6.30162656e-01
-7.75055468e-01 -2.71991104e-01 2.36251935e-01 7.98049510e-01
-1.13963515e-01 6.83213413e-01 -2.12946966e-01 -3.60875309e-01
2.49699622e-01 -4.90309536e-01 6.58573806e-01 -7.38300145e-01
-7.09202290e-01 2.96842098e-01 -4.81909066e-01 -4.49277431e-01
-4.73882705e-01 -2.51755446e-01 -1.31002641e+00 -6.14116304e-02
-8.12431276e-01 1.08777747e-01 4.55610931e-01 9.23010826e-01
1.89607039e-01 1.04889083e+00 8.76722574e-01 -7.38352239e-01
-2.73465425e-01 -9.99275148e-01 -6.94228172e-01 4.16148126e-01
2.57051915e-01 -6.97265744e-01 -1.88188151e-01 -2.04160810e-01] | [13.503172874450684, -2.549690008163452] |
325af689-e21f-4bb3-becd-86bdc1303c90 | super-resolution-radar-imaging-with-sparse | 2306.09839 | null | https://arxiv.org/abs/2306.09839v1 | https://arxiv.org/pdf/2306.09839v1.pdf | Super-Resolution Radar Imaging with Sparse Arrays Using a Deep Neural Network Trained with Enhanced Virtual Data | This paper introduces a method based on a deep neural network (DNN) that is perfectly capable of processing radar data from extremely thinned radar apertures. The proposed DNN processing can provide both aliasing-free radar imaging and super-resolution. The results are validated by measuring the detection performance on realistic simulation data and by evaluating the Point-Spread-function (PSF) and the target-separation performance on measured point-like targets. Also, a qualitative evaluation of a typical automotive scene is conducted. It is shown that this approach can outperform state-of-the-art subspace algorithms and also other existing machine learning solutions. The presented results suggest that machine learning approaches trained with sufficiently sophisticated virtual input data are a very promising alternative to compressed sensing and subspace approaches in radar signal processing. The key to this performance is that the DNN is trained using realistic simulation data that perfectly mimic a given sparse antenna radar array hardware as the input. As ground truth, ultra-high resolution data from an enhanced virtual radar are simulated. Contrary to other work, the DNN utilizes the complete radar cube and not only the antenna channel information at certain range-Doppler detections. After training, the proposed DNN is capable of sidelobe- and ambiguity-free imaging. It simultaneously delivers nearly the same resolution and image quality as would be achieved with a fully occupied array. | ['Martin Vossiek', 'Marcel Hoffmann', 'Christian Schuessler'] | 2023-06-16 | null | null | null | null | ['super-resolution'] | ['computer-vision'] | [ 5.78406513e-01 -2.62272090e-01 4.95773196e-01 -2.72860527e-01
-7.38872468e-01 -2.80889779e-01 7.05347061e-01 -6.39925241e-01
-4.36564952e-01 7.00819135e-01 6.28031343e-02 -3.14357996e-01
-7.43911982e-01 -7.45039999e-01 -4.35029477e-01 -1.05595040e+00
-5.19531429e-01 6.86995149e-01 -3.27967644e-01 -2.08102182e-01
6.63316622e-03 1.12413120e+00 -1.74047112e+00 -6.98178634e-02
7.36272037e-01 1.29472780e+00 2.60916978e-01 4.92490560e-01
3.14383924e-01 3.29609126e-01 -7.66026199e-01 1.91640873e-02
8.23339820e-01 -4.44935374e-02 7.06368804e-01 -7.22474381e-02
9.10527050e-01 -7.02381372e-01 -6.28657937e-01 1.26286077e+00
6.62781894e-01 -7.34984353e-02 5.90333581e-01 -6.19204164e-01
-3.39402765e-01 3.31320316e-01 -2.45203957e-01 2.38927484e-01
-1.14733823e-01 1.05386585e-01 2.40863502e-01 -1.20723045e+00
3.83598536e-01 8.96060407e-01 6.50119185e-01 -7.04394057e-02
-8.99962664e-01 -7.44260371e-01 -7.90768743e-01 2.21370593e-01
-1.33062649e+00 -4.81124818e-01 8.69640112e-01 -3.33798319e-01
5.56597471e-01 3.30912173e-01 5.83171666e-01 1.00994194e+00
5.23333848e-01 2.22038358e-01 1.19619942e+00 -5.02860129e-01
3.93135071e-01 -2.09464952e-01 2.15331391e-01 6.35771230e-02
8.64590287e-01 1.18731487e+00 -2.63476223e-01 -1.15531467e-01
9.29049671e-01 3.05788238e-02 -8.02772939e-01 -7.94292152e-01
-1.26770067e+00 7.92413592e-01 3.41329664e-01 4.71921712e-01
-8.57452989e-01 -5.69790564e-02 -2.84396615e-02 3.81621689e-01
2.00556159e-01 7.45530725e-01 3.07932142e-02 3.71656209e-01
-1.58706248e+00 3.47894341e-01 8.90819728e-01 5.29912829e-01
3.54397506e-01 1.31741154e+00 -2.05466881e-01 3.51539373e-01
1.60540864e-01 1.55877280e+00 1.26871467e-01 -9.40329731e-01
1.32586390e-01 -4.27588895e-02 4.43158120e-01 -9.29300725e-01
-5.08704007e-01 -1.69262028e+00 -1.14623797e+00 9.61246729e-01
3.36321145e-01 -4.09791440e-01 -1.13558626e+00 1.41379750e+00
1.11679452e-04 3.10511559e-01 8.09531689e-01 1.32928824e+00
6.15291178e-01 7.13270545e-01 -7.87854433e-01 -5.27143419e-01
1.15866125e+00 -2.77622372e-01 -9.97088194e-01 -4.66442287e-01
-6.02300726e-02 -8.26583803e-01 -1.12452023e-01 8.76357853e-01
-7.46021986e-01 -7.75456607e-01 -1.51362026e+00 9.79314685e-01
7.11395442e-02 1.88163891e-01 4.41884607e-01 7.94939399e-01
-8.57363105e-01 3.71353418e-01 -4.47256416e-01 8.07063654e-03
1.32081270e-01 -1.56826109e-01 -2.28536949e-01 -6.54474854e-01
-1.23433578e+00 1.01491117e+00 1.31083459e-01 4.90079552e-01
-1.20160604e+00 -1.08093154e+00 -8.53765011e-01 1.57065734e-01
8.45488906e-02 -3.98730814e-01 8.37776601e-01 -9.59729970e-01
-1.03636646e+00 1.95855200e-01 2.52722889e-01 -1.10920334e+00
1.50186241e-01 -5.96592724e-01 -1.02619052e+00 4.61530834e-01
-3.01721752e-01 4.16404679e-02 1.17278409e+00 -1.46894515e+00
-1.62409157e-01 -3.92286956e-01 -6.92523777e-01 1.29890561e-01
2.99472898e-01 -2.84788698e-01 4.41976041e-01 -6.40087843e-01
2.96819746e-01 -4.60760325e-01 -4.07762289e-01 -2.56553888e-01
1.13629662e-02 7.89466679e-01 8.16235721e-01 -7.30145454e-01
6.46186590e-01 -2.14930677e+00 -2.46781513e-01 4.26018089e-01
3.03419102e-02 6.37032330e-01 -3.27624559e-01 4.91394758e-01
-3.73325616e-01 -9.77075577e-01 -3.62780184e-01 2.95336872e-01
-2.57565677e-01 -1.58234790e-01 -5.77751815e-01 7.97567308e-01
-9.83832255e-02 5.71533561e-01 -2.25616947e-01 3.30672145e-01
5.26567817e-01 7.79680073e-01 -2.18853485e-02 9.19622332e-02
4.74545360e-02 3.89983654e-01 -1.12367526e-01 7.77712703e-01
1.35685372e+00 3.35409880e-01 -1.00639917e-01 -5.49026370e-01
-3.91341269e-01 -6.66003644e-01 -1.30636919e+00 1.34102261e+00
-2.78900087e-01 1.04779315e+00 8.13686848e-01 -1.21470249e+00
1.52148104e+00 2.46149898e-01 2.47886717e-01 -1.27465808e+00
8.00538808e-02 4.19029713e-01 4.79559481e-01 -2.07024157e-01
1.42050102e-01 -4.39976990e-01 1.86668530e-01 9.54190120e-02
-7.78382970e-03 -1.00635596e-01 -4.21896458e-01 -1.09302692e-01
1.19648767e+00 -2.60229111e-01 3.56354922e-01 -4.59906131e-01
6.08824074e-01 2.73382545e-01 3.89914751e-01 9.97555673e-01
2.12955371e-01 3.85558099e-01 -2.37941757e-01 -4.96471375e-01
-1.27129364e+00 -1.35662568e+00 -5.37733138e-01 2.39013791e-01
-9.52147990e-02 5.11096954e-01 -4.85284448e-01 4.66447353e-01
4.82753403e-02 1.10348654e+00 -2.52088904e-01 9.86692831e-02
-6.41856015e-01 -7.20862687e-01 4.01115656e-01 9.97102857e-02
5.70781767e-01 -6.55151606e-01 -1.21699882e+00 1.98838443e-01
2.77885765e-01 -1.39324725e+00 6.14470661e-01 2.86313087e-01
-9.24701273e-01 -8.14591646e-01 -7.64581203e-01 -3.61668676e-01
3.18463236e-01 6.78352118e-01 1.00364196e+00 -6.41482055e-01
-6.17918253e-01 4.56295192e-01 -4.52593058e-01 -4.21753645e-01
-2.88539946e-01 -1.04851222e+00 4.16672587e-01 1.44297257e-01
3.79500628e-01 -8.67868960e-01 -4.81284231e-01 -2.60598250e-02
-7.31913984e-01 -1.63055986e-01 1.40737844e+00 9.46795702e-01
2.36304313e-01 1.26366958e-01 3.50223571e-01 -3.48516822e-01
3.01081568e-01 -7.76160359e-02 -1.07045412e+00 -1.51609644e-01
-4.73753303e-01 9.57189724e-02 8.78009498e-01 -1.66131794e-01
-1.22390163e+00 -1.51381232e-02 6.81717396e-02 -7.93310761e-01
-4.71644193e-01 6.80843711e-01 -1.76592901e-01 -5.13598859e-01
9.57019389e-01 8.24351311e-01 3.35828274e-01 -3.24828207e-01
9.40560400e-02 4.85919982e-01 1.05324960e+00 1.47807419e-01
1.57262814e+00 7.62048304e-01 4.95195985e-01 -1.47692120e+00
-5.51393807e-01 -4.33030158e-01 -4.83496040e-01 -3.29454929e-01
4.32703584e-01 -1.16208613e+00 -2.85149485e-01 3.21813434e-01
-8.37082088e-01 8.13755542e-02 -3.55102211e-01 1.22389305e+00
-3.86643857e-01 4.37404186e-01 2.09913701e-02 -1.18964803e+00
-5.08600235e-01 -5.36099434e-01 7.55725205e-01 3.70180644e-02
3.77767771e-01 -6.74512565e-01 2.38043979e-01 2.24962786e-01
1.02410305e+00 4.29674834e-01 5.15100300e-01 -8.59560251e-01
-8.39293659e-01 -5.65022409e-01 -1.79750115e-01 5.02240777e-01
-4.60705608e-01 -7.12989211e-01 -7.78252542e-01 -7.30374157e-01
6.59054518e-01 2.07130029e-03 8.75923991e-01 9.50783730e-01
2.27155164e-01 -1.03064820e-01 -2.37060636e-01 1.11066377e+00
2.04477072e+00 3.32620651e-01 8.08756649e-01 1.73053667e-01
1.04077823e-01 4.85346973e-01 8.97389591e-01 4.43371713e-01
-8.25129807e-01 6.40149891e-01 9.21472669e-01 -8.24855417e-02
-2.80183017e-01 4.71745074e-01 4.15924400e-01 1.59933150e-01
-2.31550671e-02 -8.79284516e-02 -6.88790500e-01 4.11112756e-01
-1.26388717e+00 -1.38308167e+00 -2.28442773e-01 2.26618457e+00
-2.64605075e-01 2.42553819e-02 -6.38962388e-01 2.32547119e-01
3.98614019e-01 3.13896418e-01 -4.45951402e-01 -1.69088528e-01
-6.08957469e-01 7.11307049e-01 8.24456930e-01 5.98796785e-01
-9.41143095e-01 2.65159845e-01 5.67911386e+00 6.72222376e-01
-1.26487803e+00 2.14546148e-04 -2.14429334e-01 -1.98618546e-01
-2.60117710e-01 -3.16434979e-01 -6.71532512e-01 -2.84788664e-02
1.24579251e+00 -1.68918267e-01 2.47639030e-01 7.27374971e-01
2.34854564e-01 -2.43868649e-01 -7.25436568e-01 1.22647727e+00
5.53402960e-01 -1.49917948e+00 2.15474620e-01 2.51120299e-01
2.94506043e-01 -5.45089319e-03 2.23424330e-01 2.84540832e-01
-6.15117289e-02 -1.38041735e+00 2.78103501e-01 9.79244709e-01
7.63308704e-01 -9.10774410e-01 1.26104057e+00 6.40239894e-01
-7.24369705e-01 -2.26859212e-01 -4.93085027e-01 -2.83996373e-01
3.33748788e-01 1.20944321e+00 -8.36892605e-01 1.02443111e+00
3.10524195e-01 4.96453084e-02 -1.90305129e-01 1.24953115e+00
3.89816165e-02 5.56929946e-01 -3.56779337e-01 2.12099016e-01
4.97477561e-01 -4.36093390e-01 1.21152961e+00 1.24169099e+00
1.16627693e+00 2.86176026e-01 9.85333249e-02 8.42782676e-01
7.09335804e-01 -4.24399614e-01 -1.08742154e+00 1.74570546e-01
4.52096254e-01 1.49310219e+00 -9.90540758e-02 -1.64812896e-02
-3.53618920e-01 2.97348201e-01 -7.07752705e-01 6.75395310e-01
-6.30126834e-01 -2.76077330e-01 7.21657872e-01 2.70997256e-01
6.92101240e-01 -3.81611347e-01 -1.32846739e-02 -5.87614536e-01
-6.55263662e-02 -9.57265079e-01 -2.31572956e-01 -1.00659335e+00
-1.09586298e+00 8.78082752e-01 1.04940698e-01 -1.77658737e+00
-4.77965683e-01 -1.04437220e+00 -4.01293933e-01 1.21267712e+00
-1.59191263e+00 -1.16206360e+00 -5.83286643e-01 4.46413994e-01
2.29329199e-01 -9.39282775e-01 9.32069540e-01 1.13747120e-01
1.56224042e-01 3.02541293e-02 4.76940572e-01 1.15714028e-01
4.13417280e-01 -6.33233130e-01 4.53340784e-02 1.41598070e+00
2.95716878e-02 2.94517696e-01 1.48581076e+00 -5.92535198e-01
-1.81180513e+00 -1.05924582e+00 3.68260480e-02 1.46658614e-01
4.43627685e-01 -2.26550683e-01 -7.52351522e-01 3.04494888e-01
3.88528615e-01 1.04800880e-01 5.78587770e-01 -4.75770772e-01
-2.10109949e-01 -3.91133159e-01 -9.37836945e-01 8.01681653e-02
6.50600195e-01 6.95782155e-02 -1.01125491e+00 2.66167998e-01
3.02075595e-01 -2.70482004e-01 -3.76798570e-01 1.06896722e+00
5.13693094e-01 -1.43620706e+00 1.27706039e+00 -1.87483758e-01
2.20544323e-01 -3.26329172e-01 -7.83001065e-01 -1.50846827e+00
-6.41980171e-01 -1.63164720e-01 -2.87280619e-01 4.09262925e-01
1.62921697e-01 -7.03019977e-01 8.91760826e-01 -5.45543849e-01
-3.60673964e-01 -2.98380584e-01 -1.24359596e+00 -1.27003765e+00
-1.20648004e-01 -4.60393369e-01 1.32859731e-02 6.53082907e-01
-7.28033960e-01 2.32351750e-01 -5.17575800e-01 1.02578437e+00
1.68735349e+00 6.50996745e-01 8.07040513e-01 -1.78940082e+00
-3.95248234e-01 -2.08851732e-02 -6.29156411e-01 -7.71306455e-01
3.59379761e-02 -6.71439111e-01 -5.15132211e-02 -1.44713962e+00
-3.35199624e-01 -2.00441614e-01 8.75534639e-02 -4.95889843e-01
6.55406058e-01 1.88848197e-01 1.58832297e-01 8.41273665e-02
2.36250550e-01 4.90227789e-01 1.01759529e+00 -5.59124015e-02
2.13588953e-01 2.74194986e-01 -3.93018246e-01 6.39318168e-01
5.53824723e-01 -8.79322365e-02 -1.79422960e-01 -3.60004425e-01
-3.73725928e-02 6.60266340e-01 8.50778103e-01 -1.96358550e+00
5.99305332e-01 1.71001732e-01 9.29770648e-01 -1.06520331e+00
7.60045111e-01 -1.11946261e+00 6.16908133e-01 8.05407047e-01
3.58717799e-01 -5.18059373e-01 2.27980688e-01 6.91222131e-01
-5.75385690e-01 -2.19333991e-01 9.18347418e-01 -8.78246874e-02
-9.62118864e-01 -2.25330722e-02 -3.97462606e-01 -4.57013488e-01
1.08571684e+00 -6.29304767e-01 -4.40539747e-01 -6.59871697e-01
-5.64454913e-01 -1.51673958e-01 7.08731413e-02 -1.40490010e-01
1.01998866e+00 -1.13909447e+00 -1.24917841e+00 6.85274363e-01
-8.30337331e-02 -5.69456100e-01 6.36445940e-01 6.58774018e-01
-5.74048042e-01 1.02602708e+00 -7.28364706e-01 -7.04110861e-01
-1.07673419e+00 6.41295910e-01 4.76818144e-01 -7.61168078e-02
-8.10599148e-01 4.76766616e-01 1.89564511e-01 -4.53978777e-01
1.48507148e-01 2.50012368e-01 -2.47150660e-01 -1.16386540e-01
9.95795727e-01 4.89191040e-02 1.34358898e-01 -5.67135751e-01
-3.81307483e-01 6.58009052e-01 3.81456047e-01 -3.68772477e-01
1.52302861e+00 3.76041859e-01 6.86071739e-02 8.66727158e-02
6.16909921e-01 3.47013652e-01 -1.18373322e+00 -4.10668314e-01
-4.55770433e-01 -4.62168813e-01 5.72006524e-01 -9.82105494e-01
-8.78006160e-01 1.00205219e+00 1.17583847e+00 7.25088939e-02
1.34479833e+00 -5.08588135e-01 2.98732311e-01 7.29094744e-01
5.81360340e-01 -4.66155678e-01 -3.63226235e-02 6.80627704e-01
1.03160334e+00 -7.63805032e-01 2.89739460e-01 -2.03122824e-01
-2.34540105e-01 1.34699190e+00 9.13323462e-02 -5.73786497e-01
5.78891933e-01 8.95071089e-01 1.96723849e-01 -3.37317586e-01
-4.36542362e-01 -2.54293919e-01 1.54861599e-01 1.02449870e+00
-1.01846062e-01 6.72312975e-02 -5.31650195e-03 5.28836966e-01
-3.37022632e-01 -1.60567626e-01 7.56977141e-01 5.08464873e-01
-1.03345823e+00 -4.62204248e-01 -1.31216013e+00 5.45624971e-01
-3.70921195e-02 -2.85007238e-01 1.10578820e-01 1.05172896e+00
-2.17160910e-01 7.12528467e-01 2.13079199e-01 -1.60673261e-01
3.82166445e-01 3.04466002e-02 5.39699495e-01 -3.14883262e-01
-1.26700148e-01 2.12674022e-01 4.97876965e-02 -5.20438254e-01
-1.60563320e-01 -5.82730889e-01 -5.92610240e-01 5.52417897e-02
-1.02483489e-01 3.28873783e-01 7.51572371e-01 6.46907151e-01
1.95774004e-01 7.15290904e-01 5.13261497e-01 -1.10870922e+00
-1.03511739e+00 -9.68759418e-01 -9.34720337e-01 -3.53696078e-01
6.42287731e-01 -6.45698607e-01 -8.15710068e-01 -4.44265723e-01] | [6.79036808013916, 1.0294370651245117] |
5a6ad24f-8d31-49ba-92c9-e92c6f26747f | point-teaching-weakly-semi-supervised-object | 2206.00274 | null | https://arxiv.org/abs/2206.00274v2 | https://arxiv.org/pdf/2206.00274v2.pdf | Point-Teaching: Weakly Semi-Supervised Object Detection with Point Annotations | Point annotations are considerably more time-efficient than bounding box annotations. However, how to use cheap point annotations to boost the performance of semi-supervised object detection remains largely unsolved. In this work, we present Point-Teaching, a weakly semi-supervised object detection framework to fully exploit the point annotations. Specifically, we propose a Hungarian-based point matching method to generate pseudo labels for point annotated images. We further propose multiple instance learning (MIL) approaches at the level of images and points to supervise the object detector with point annotations. Finally, we propose a simple-yet-effective data augmentation, termed point-guided copy-paste, to reduce the impact of the unmatched points. Experiments demonstrate the effectiveness of our method on a few datasets and various data regimes. | ['Chunhua Shen', 'Zhibin Wang', 'Hao Li', 'Xinlong Wang', 'Qiang Zhou', 'Yongtao Ge'] | 2022-06-01 | null | null | null | null | ['semi-supervised-object-detection'] | ['computer-vision'] | [ 4.10789490e-01 2.10213333e-01 -2.73195952e-01 -4.66883302e-01
-1.32106137e+00 -5.40368557e-01 5.44719577e-01 2.37658292e-01
-3.30643862e-01 2.26862743e-01 -3.66217226e-01 -2.15438884e-02
2.30557114e-01 -5.42175651e-01 -1.23753691e+00 -4.28372890e-01
2.98656642e-01 5.16740143e-01 8.02814424e-01 -1.95675585e-02
3.78224820e-01 8.02152991e-01 -1.53525281e+00 1.71212867e-01
7.64295340e-01 8.90004694e-01 2.08833769e-01 4.07766014e-01
-1.17746219e-01 4.46055442e-01 -2.67443299e-01 -4.26539272e-01
6.19406223e-01 -2.50848103e-02 -7.60704994e-01 5.84576428e-01
8.24065268e-01 -4.75066066e-01 -1.19914263e-01 9.26464498e-01
2.35740423e-01 9.77502391e-02 5.32415211e-01 -1.40783978e+00
-1.51421264e-01 1.76916480e-01 -1.03491962e+00 -1.47790179e-01
1.44768357e-01 1.88206494e-01 1.02981031e+00 -1.43480396e+00
5.33388436e-01 1.09122610e+00 8.13912511e-01 3.69055122e-01
-1.23274386e+00 -6.83690131e-01 6.44873455e-02 -7.28714839e-02
-1.54103994e+00 -4.18028772e-01 1.20371878e+00 -3.42078447e-01
6.02284193e-01 5.70948161e-02 3.52005243e-01 6.88149095e-01
-5.90749979e-01 8.62114429e-01 7.92259097e-01 -6.65419817e-01
1.67170927e-01 -1.33552426e-03 -5.52967414e-02 1.03410649e+00
1.05678953e-01 1.27318397e-01 -2.91532397e-01 -4.34624583e-01
1.06276762e+00 4.19365615e-01 1.63023502e-01 -9.85217392e-01
-1.36327744e+00 6.65945232e-01 7.02328146e-01 -2.08262920e-01
-3.13720256e-01 2.59023011e-01 2.68999547e-01 -2.92225808e-01
6.60986662e-01 1.86597303e-01 -4.92422760e-01 2.26711944e-01
-9.99542534e-01 2.04254270e-01 3.20688635e-01 1.47397745e+00
1.18674707e+00 -3.40594321e-01 -1.70631647e-01 7.55027652e-01
2.78588891e-01 4.94820207e-01 -1.65715113e-01 -1.07772720e+00
5.76956332e-01 1.05259848e+00 2.71574587e-01 -7.82511055e-01
-1.78696290e-01 -2.65662760e-01 -4.75889951e-01 4.21882242e-01
4.82500404e-01 1.73172921e-01 -1.11047745e+00 1.19536865e+00
7.60494709e-01 4.23278868e-01 -3.50625068e-01 8.83593857e-01
5.48976958e-01 3.91241461e-01 1.47268072e-01 2.71841168e-01
1.25665689e+00 -1.24436259e+00 -2.09688887e-01 -3.61591935e-01
7.28193223e-01 -5.62074661e-01 1.21049380e+00 -6.61168024e-02
-1.14687514e+00 -6.15181327e-01 -9.15514410e-01 -2.88218111e-01
-1.84627801e-01 5.12803018e-01 4.49293256e-01 2.87520438e-01
-4.13587838e-01 5.54789007e-01 -1.10158932e+00 -5.56424670e-02
9.14268851e-01 5.49133003e-01 -5.15513659e-01 -2.35338118e-02
-4.44589794e-01 5.57116151e-01 4.87371117e-01 -3.34436335e-02
-7.71344066e-01 -8.86796415e-01 -1.02585435e+00 -3.17149721e-02
6.86880946e-01 -5.66173494e-01 1.20346820e+00 -6.84453368e-01
-1.16962445e+00 1.19523597e+00 -2.95523942e-01 -3.82252991e-01
6.27892435e-01 -3.70685875e-01 2.01559380e-01 1.78887337e-01
3.26381028e-01 1.05656803e+00 9.06041384e-01 -1.49576831e+00
-1.01550829e+00 -6.06037498e-01 -9.37051624e-02 3.55027989e-02
-8.05360377e-02 3.78898978e-02 -8.81212056e-01 -5.69580853e-01
3.94299001e-01 -1.01243460e+00 -5.58487117e-01 6.36990964e-01
-5.48850358e-01 -4.57336962e-01 8.95968258e-01 -4.41855431e-01
5.75790823e-01 -2.35079694e+00 -1.23940006e-01 3.29817235e-01
1.92727968e-01 1.82453617e-01 -1.56690180e-01 1.36616036e-01
7.24613592e-02 -1.22705869e-01 -5.89030027e-01 -7.46929824e-01
-7.37291798e-02 2.78464437e-01 -3.13899159e-01 5.92437625e-01
6.69645548e-01 1.01196039e+00 -9.05688107e-01 -8.24130118e-01
4.72987682e-01 3.30905706e-01 -6.06824338e-01 2.55990803e-01
-3.00748289e-01 3.06383103e-01 -3.68844748e-01 9.78483200e-01
8.30578387e-01 -2.85195678e-01 -4.73512083e-01 -4.07579452e-01
-1.00648679e-01 -1.22284733e-01 -1.20969164e+00 1.95802593e+00
-1.30477279e-01 2.79753506e-01 -1.24987252e-01 -6.61801577e-01
1.03376079e+00 -1.31385759e-01 4.67100322e-01 -1.99089095e-01
8.32032226e-03 2.79866666e-01 -4.16887969e-01 -1.69252276e-01
4.12519276e-01 1.21988028e-01 8.47696140e-02 1.91116542e-01
7.91946873e-02 -2.26691768e-01 -2.48470362e-02 1.10574275e-01
9.93270218e-01 5.54370701e-01 3.19004834e-01 8.58848244e-02
4.52180922e-01 3.80420506e-01 4.96857643e-01 6.58667922e-01
-2.74003536e-01 9.71425772e-01 2.47172080e-02 -3.46309245e-01
-1.37089753e+00 -1.02673948e+00 -1.29220545e-01 1.15367508e+00
4.80117232e-01 -3.11095566e-01 -7.04811871e-01 -1.04614282e+00
1.22550286e-01 2.99366236e-01 -3.35861355e-01 -1.23508740e-02
-7.51917481e-01 -2.23013863e-01 3.45377982e-01 9.32620347e-01
4.30435747e-01 -8.93424869e-01 -5.63594520e-01 -7.72525668e-02
-1.08796999e-01 -1.34729326e+00 -6.47015512e-01 1.99665502e-01
-1.10481000e+00 -9.98338044e-01 -8.86789083e-01 -9.58388805e-01
1.21859813e+00 4.39432800e-01 8.05668890e-01 1.68941066e-01
-3.26842159e-01 3.06336135e-01 -3.44525099e-01 -5.47981381e-01
-1.62522808e-01 1.82324901e-01 -8.95171519e-03 5.11077307e-02
4.44481760e-01 -2.85004675e-01 -6.78284466e-01 6.58531606e-01
-7.16358781e-01 -1.71521511e-02 9.23845053e-01 7.30643928e-01
1.17279303e+00 -3.36011291e-01 1.58194155e-01 -9.02065217e-01
-2.28939489e-01 3.42543274e-02 -7.99717009e-01 2.00313881e-01
-2.04873264e-01 9.11466628e-02 1.09863997e-01 -4.47870612e-01
-8.47342789e-01 1.03746307e+00 -3.95086966e-02 -8.28862250e-01
-3.36373478e-01 -2.50376880e-01 -2.10239291e-01 -6.58429682e-01
6.06505096e-01 9.31596607e-02 -1.00994915e-01 -6.55998826e-01
7.13439584e-01 5.76571465e-01 9.94015753e-01 -6.27004743e-01
1.36370325e+00 1.02858829e+00 2.60575637e-02 -6.33329272e-01
-9.60354865e-01 -9.79917705e-01 -1.20652211e+00 -2.16911621e-02
7.27625608e-01 -1.02752554e+00 -3.43133390e-01 7.27840597e-05
-1.32451427e+00 -2.01207191e-01 -5.85672140e-01 2.09106982e-01
-8.01007152e-01 5.74670613e-01 -3.23611140e-01 -7.85386622e-01
-3.21238160e-01 -9.24627304e-01 1.75465930e+00 -2.08087522e-03
2.91353539e-02 -4.93254542e-01 2.17230767e-02 5.14092863e-01
-2.74749070e-01 2.37774953e-01 3.97245228e-01 -7.21577585e-01
-9.79176462e-01 -4.16472167e-01 -5.72137356e-01 3.07665348e-01
-1.07639432e-01 -1.24184765e-01 -8.72002900e-01 -1.51270226e-01
-3.87055516e-01 -2.75061727e-01 6.33903861e-01 -1.80268139e-02
1.45416582e+00 -5.54610677e-02 -7.11960196e-01 7.00301945e-01
1.20884180e+00 -2.31992990e-01 4.85817254e-01 3.26347619e-01
1.02306890e+00 6.12882018e-01 9.52807009e-01 4.80496764e-01
1.39375761e-01 8.03377271e-01 4.49745089e-01 -4.36229557e-01
-2.09805459e-01 -7.13381588e-01 -3.89542952e-02 1.39766812e-01
-1.77950948e-01 3.46192360e-01 -1.02514279e+00 6.75207913e-01
-1.87246180e+00 -6.86751425e-01 -4.56654608e-01 2.08164096e+00
6.22876883e-01 2.16314092e-01 2.24158317e-01 1.40714556e-01
8.08545291e-01 -2.51299649e-01 -5.26351750e-01 5.55993557e-01
5.34886830e-02 1.37282252e-01 8.78900766e-01 2.81447142e-01
-1.41019368e+00 1.07343626e+00 5.91897154e+00 8.42737317e-01
-4.45349425e-01 1.66229188e-01 3.87007654e-01 1.91227227e-01
1.41683489e-01 1.66731253e-01 -8.99440348e-01 2.91042119e-01
2.25737363e-01 2.99366862e-01 -1.09504096e-01 1.45118630e+00
8.93869549e-02 2.13477895e-01 -1.31196249e+00 1.14568317e+00
1.09510988e-01 -1.32533169e+00 -8.19009021e-02 -8.50846618e-03
7.07441866e-01 1.10539809e-01 -2.05939740e-01 1.73737809e-01
1.02763996e-03 -3.37186277e-01 7.59374201e-01 1.64152429e-01
7.56173432e-01 -7.63865054e-01 4.70941603e-01 4.32417572e-01
-1.24052227e+00 4.97535290e-03 -5.10938644e-01 2.14969486e-01
2.18203574e-01 4.41623926e-01 -8.61495972e-01 3.39151353e-01
6.95087254e-01 5.08635223e-01 -9.13832664e-01 1.27620554e+00
-2.99409509e-01 3.92678469e-01 -5.84329844e-01 3.05887848e-01
1.38576925e-01 -7.84190279e-03 4.83494520e-01 1.13646746e+00
7.98588544e-02 2.71040261e-01 3.86205643e-01 1.01405001e+00
-1.00557424e-01 5.04048429e-02 -4.87131625e-01 4.38740999e-01
5.13182998e-01 1.40405083e+00 -9.36194718e-01 -3.09149951e-01
-3.99398863e-01 1.10971510e+00 5.38553536e-01 1.56093940e-01
-7.60125279e-01 -4.16797876e-01 2.87474453e-01 4.15914595e-01
4.50745404e-01 -3.31638157e-01 -3.83007109e-01 -1.01655388e+00
2.81919986e-01 -3.49957675e-01 2.25382552e-01 -7.67470956e-01
-1.24053061e+00 9.93401930e-02 9.27525386e-02 -1.45973253e+00
-1.79161690e-02 -5.35310745e-01 -5.85952044e-01 5.46350956e-01
-1.55388808e+00 -1.48982418e+00 -5.15642226e-01 6.46569967e-01
6.94182336e-01 1.71854079e-01 3.05233479e-01 3.93845022e-01
-4.05584604e-01 5.71699142e-01 -1.64443195e-01 5.25286436e-01
6.20074332e-01 -1.26253247e+00 6.00249588e-01 7.21544683e-01
4.79186952e-01 5.24435520e-01 3.44188511e-01 -6.20639265e-01
-1.21161914e+00 -1.30534363e+00 5.23408711e-01 -8.22517872e-01
3.29335213e-01 -6.74390018e-01 -1.10593832e+00 7.41731286e-01
-4.15348291e-01 5.01858532e-01 3.34819466e-01 -1.65737197e-01
-3.62486392e-01 3.84749770e-02 -1.18412042e+00 5.26347220e-01
1.20959044e+00 -5.33451617e-01 -6.66829348e-01 6.28331721e-01
8.82110238e-01 -5.75427115e-01 -5.80659807e-01 7.31015384e-01
1.88695833e-01 -6.20553851e-01 1.43491232e+00 -3.62483233e-01
2.43280441e-01 -5.67472994e-01 1.38152689e-02 -7.24763572e-01
-1.95240498e-01 -4.59021360e-01 -2.63780713e-01 1.35900438e+00
3.00454408e-01 -1.35953084e-01 1.42678583e+00 6.33481503e-01
-1.59357503e-01 -5.88359416e-01 -8.72185528e-01 -8.21908295e-01
-3.34352553e-01 -3.75958323e-01 4.77043331e-01 7.69284964e-01
-1.51106432e-01 1.02938421e-01 -1.65412068e-01 3.97873461e-01
1.04255760e+00 1.35461047e-01 1.25526857e+00 -1.24007595e+00
-1.69426203e-01 -1.25863552e-01 -6.42118990e-01 -1.19631851e+00
1.57893732e-01 -7.61810660e-01 3.55195820e-01 -1.32438743e+00
2.94318825e-01 -5.86192667e-01 -1.80760380e-02 6.82657301e-01
-3.52348506e-01 5.73560119e-01 1.30280733e-01 5.18417656e-01
-8.22662175e-01 4.88771170e-01 9.31605935e-01 -1.00730456e-01
-2.47839332e-01 2.22550929e-01 -1.36485204e-01 9.82559800e-01
5.52585483e-01 -5.91418087e-01 -8.00459683e-02 -2.73522139e-01
-2.33417705e-01 -2.48140648e-01 7.51459718e-01 -1.03937733e+00
4.21865344e-01 3.96336801e-03 3.40967119e-01 -1.19243109e+00
4.26218450e-01 -1.11938691e+00 -3.12288970e-01 3.09394509e-01
-3.60663295e-01 -1.22273877e-01 9.46573392e-02 8.90444040e-01
2.77876910e-02 -2.81120330e-01 7.43154347e-01 2.08113603e-02
-7.82526731e-01 6.27254546e-01 5.13724387e-01 -2.55145907e-01
1.40091443e+00 -2.70628631e-01 8.61863643e-02 1.17136881e-01
-5.75210392e-01 2.83005714e-01 5.31515121e-01 3.12129021e-01
8.66137147e-01 -1.37559974e+00 -5.72700620e-01 3.16773385e-01
6.78063691e-01 6.28223360e-01 8.01133886e-02 6.03027821e-01
-5.30809999e-01 1.25235841e-01 1.46984965e-01 -1.06294870e+00
-1.35652363e+00 8.60401690e-01 1.16665252e-01 2.10104913e-01
-9.36661363e-01 7.17083871e-01 3.48331749e-01 -7.10712016e-01
4.37472731e-01 -4.40488607e-01 2.85809457e-01 -3.95288646e-01
3.81599218e-01 5.63792169e-01 1.29340246e-01 -6.42941236e-01
-3.55854392e-01 9.17698562e-01 -1.29990160e-01 -6.68489188e-02
1.08550644e+00 3.08149159e-02 1.67335346e-01 1.96979687e-01
1.22398901e+00 -2.00267017e-01 -1.63912022e+00 -5.27867258e-01
2.51267970e-01 -7.09853768e-01 -5.39431386e-02 -4.16099995e-01
-6.93177581e-01 8.15831721e-01 6.07217610e-01 -3.05218905e-01
7.26677895e-01 4.35582221e-01 7.16087639e-01 5.28546572e-01
4.35859382e-01 -9.83748019e-01 1.22221515e-01 -4.95658033e-02
7.66332269e-01 -1.61976850e+00 2.44864784e-02 -8.98858547e-01
-4.76927847e-01 9.65839744e-01 8.96075547e-01 -2.81566173e-01
3.80041242e-01 1.46074444e-01 -1.83154210e-01 -2.65574485e-01
-1.06178887e-01 -3.98918778e-01 4.70891148e-01 6.68465316e-01
-8.73822346e-02 -2.19539836e-01 9.54932496e-02 1.75722167e-01
1.73496783e-01 1.01398073e-01 -2.50573121e-02 1.10974407e+00
-5.86062491e-01 -9.95136678e-01 -6.92059577e-01 2.60547221e-01
-1.32221296e-01 1.74124390e-01 -5.87000132e-01 7.68693388e-01
6.77906424e-02 5.22627234e-01 1.71890736e-01 -7.28720129e-02
5.86520612e-01 4.58349772e-02 3.78464758e-01 -7.94952750e-01
-2.17412293e-01 9.45823714e-02 -4.62290615e-01 -6.10891521e-01
-5.38249612e-01 -5.99277020e-01 -1.49023807e+00 2.02260613e-01
-7.24897921e-01 -1.20588124e-01 7.24761128e-01 8.64948392e-01
4.99424219e-01 2.18771011e-01 5.85723221e-01 -1.32352376e+00
-7.56054282e-01 -6.89272046e-01 -2.12516204e-01 6.33395433e-01
2.76491880e-01 -7.46284902e-01 -3.31611246e-01 1.34672448e-01] | [7.897679328918457, -2.7432332038879395] |
56ad3b82-3e92-42f2-a211-1b306ad72069 | fooling-thermal-infrared-detectors-in | 2304.10712 | null | https://arxiv.org/abs/2304.10712v3 | https://arxiv.org/pdf/2304.10712v3.pdf | Adversarial Infrared Blocks: A Black-box Attack to Thermal Infrared Detectors at Multiple Angles in Physical World | Infrared imaging systems have a vast array of potential applications in pedestrian detection and autonomous driving, and their safety performance is of great concern. However, few studies have explored the safety of infrared imaging systems in real-world settings. Previous research has used physical perturbations such as small bulbs and thermal "QR codes" to attack infrared imaging detectors, but such methods are highly visible and lack stealthiness. Other researchers have used hot and cold blocks to deceive infrared imaging detectors, but this method is limited in its ability to execute attacks from various angles. To address these shortcomings, we propose a novel physical attack called adversarial infrared blocks (AdvIB). By optimizing the physical parameters of the adversarial infrared blocks, this method can execute a stealthy black-box attack on thermal imaging system from various angles. We evaluate the proposed method based on its effectiveness, stealthiness, and robustness. Our physical tests show that the proposed method achieves a success rate of over 80% under most distance and angle conditions, validating its effectiveness. For stealthiness, our method involves attaching the adversarial infrared block to the inside of clothing, enhancing its stealthiness. Additionally, we test the proposed method on advanced detectors, and experimental results demonstrate an average attack success rate of 51.2%, proving its robustness. Overall, our proposed AdvIB method offers a promising avenue for conducting stealthy, effective and robust black-box attacks on thermal imaging system, with potential implications for real-world safety and security applications. | ['Xiaoqian Chen', 'Ling Tian', 'Wen Yao', 'Tingsong Jiang', 'Weiwen Shi', 'Chengyin Hu'] | 2023-04-21 | null | null | null | null | ['pedestrian-detection'] | ['computer-vision'] | [ 1.44040108e-01 -3.54553014e-01 5.70422895e-02 2.10947081e-01
-1.82541698e-01 -9.56274509e-01 2.01384321e-01 -5.93326211e-01
-4.99780953e-01 4.23743159e-01 -3.57383102e-01 -7.57934868e-01
3.42059314e-01 -7.61008382e-01 -6.54428601e-01 -9.57892299e-01
6.54554889e-02 -8.20060909e-01 4.82305288e-01 -4.09526289e-01
1.26188159e-01 6.17276073e-01 -1.21938372e+00 -3.69650453e-01
8.30209792e-01 8.04662168e-01 -5.12879252e-01 9.06276345e-01
8.72513592e-01 5.55258691e-01 -9.12418723e-01 -5.46708465e-01
6.30932987e-01 -8.45309123e-02 -1.32190749e-01 -6.24526799e-01
3.56294930e-01 -7.56187916e-01 -7.27297187e-01 9.94569838e-01
8.40938985e-01 8.58238316e-04 3.70998621e-01 -1.41818678e+00
-7.17119217e-01 -1.75526634e-01 -1.00952542e+00 5.48424423e-02
5.42213976e-01 5.84561229e-01 2.77017742e-01 -1.14735186e-01
-2.33762056e-01 1.00421762e+00 7.37116992e-01 9.35310185e-01
-8.15698683e-01 -1.39596713e+00 -1.45038724e-01 1.07572645e-01
-1.37157261e+00 -3.69080901e-01 8.53402555e-01 -1.95186287e-01
4.89278555e-01 6.11824334e-01 5.15113056e-01 1.25501764e+00
6.78732872e-01 3.82012010e-01 1.40417755e+00 -3.10479522e-01
2.41652697e-01 2.38386959e-01 -1.39695760e-02 6.70416057e-01
5.56635797e-01 8.83876801e-01 -3.96332704e-02 -3.31225038e-01
5.06980717e-01 -1.70960009e-01 -2.20316842e-01 1.00434273e-01
-7.62191355e-01 6.94973826e-01 5.80099106e-01 -3.45479429e-01
2.17468783e-01 4.91471380e-01 3.51510406e-01 5.25011308e-02
1.87417760e-01 1.68638080e-01 1.50171772e-01 8.13703761e-02
-1.76103935e-01 1.16230160e-01 3.13876241e-01 7.13796556e-01
1.32892936e-01 2.24359453e-01 -9.58125293e-02 5.77828825e-01
4.68263716e-01 1.33353555e+00 7.88572244e-03 -5.54917574e-01
4.19037849e-01 5.29420450e-02 3.24664533e-01 -1.01057160e+00
-3.29984635e-01 -3.59486639e-02 -6.69021010e-01 1.03535533e+00
2.32129514e-01 -5.42257905e-01 -9.48223054e-01 1.67208028e+00
5.57150900e-01 2.05204070e-01 1.40920922e-01 1.09638345e+00
7.91490316e-01 5.86887360e-01 3.13198626e-01 6.81974664e-02
1.41631734e+00 -4.36124414e-01 -4.31587756e-01 -3.08778167e-01
3.48699182e-01 -1.00398397e+00 7.22049117e-01 3.21848989e-01
-6.39713883e-01 -7.40007699e-01 -1.31641996e+00 4.54293698e-01
-4.35845889e-02 -1.43207368e-02 3.64296466e-01 1.78299809e+00
-7.76840925e-01 -1.86619684e-01 -6.26239777e-01 -1.92655981e-01
2.24438086e-01 4.83466744e-01 -1.35767087e-01 6.12975471e-03
-1.43129814e+00 8.83143008e-01 -9.57200304e-02 2.47563481e-01
-7.41628110e-01 -4.88269478e-01 -8.02438796e-01 -5.55318773e-01
1.86640024e-01 -6.54321313e-01 8.62929583e-01 -4.87096399e-01
-1.76809955e+00 5.64831555e-01 1.13921143e-01 -3.50249857e-01
4.77964014e-01 -5.37218451e-01 -8.55204463e-01 2.85249501e-01
-1.63806498e-01 3.83096248e-01 1.17579246e+00 -1.26689243e+00
-3.15794855e-01 -2.98858374e-01 4.31716770e-01 -2.61461567e-02
-5.26113451e-01 4.01547879e-01 1.33928254e-01 -6.89979553e-01
-3.58064502e-01 -1.41721737e+00 -2.53597591e-02 1.09205917e-01
-5.90912163e-01 2.12207794e-01 1.26198030e+00 -3.82373542e-01
9.43280399e-01 -2.35228252e+00 -6.45312130e-01 3.26075673e-01
5.54625615e-02 8.81874025e-01 6.00346848e-02 2.33069420e-01
-2.54327338e-02 3.42408210e-01 1.90760702e-01 2.41861582e-01
-6.72588125e-02 -3.16397846e-01 -4.97595608e-01 9.13562536e-01
-1.60991326e-01 7.60120571e-01 -5.81834435e-01 -1.85803533e-01
5.69374025e-01 6.18679821e-01 -2.57508427e-01 8.53454396e-02
4.65654552e-01 4.90896523e-01 -8.46609592e-01 7.18812406e-01
1.08094728e+00 6.77918494e-01 -5.15730739e-01 -4.02187973e-01
-1.04309000e-01 -5.16304016e-01 -8.34705353e-01 5.34549177e-01
-3.43779773e-01 6.15314722e-01 -1.78531155e-01 -4.85342950e-01
8.89739394e-01 2.05455825e-01 3.17145407e-01 -9.91555989e-01
3.21974218e-01 -1.69927612e-01 -1.14340164e-01 -7.48161077e-01
4.96436924e-01 -2.20745817e-01 -2.90854901e-01 4.29444492e-01
-9.25844908e-01 -1.90750323e-02 -6.39905334e-01 1.80080220e-01
1.24141085e+00 2.23261937e-01 -1.94149196e-01 1.15478002e-01
6.09575212e-01 -2.21266747e-01 2.71191865e-01 8.75422478e-01
-6.62048161e-01 3.03759098e-01 -1.75558627e-01 -3.58221322e-01
-1.00738490e+00 -1.16666067e+00 -7.58988634e-02 8.05106938e-01
9.78453994e-01 2.66807936e-02 -7.24616885e-01 -6.06085956e-01
-3.42956260e-02 4.97725457e-01 -3.34292978e-01 -8.15728605e-01
-5.88110387e-01 -6.86765611e-01 1.27955592e+00 5.62751174e-01
1.09690273e+00 -5.37770212e-01 -9.02215123e-01 -3.71416390e-01
-1.93387792e-01 -1.39808309e+00 -4.31728274e-01 -6.47953331e-01
-2.35933363e-01 -1.05651569e+00 -5.10492623e-01 -3.62879485e-01
6.47146523e-01 9.57566619e-01 4.29039836e-01 2.90923715e-01
-6.32624924e-01 5.33937752e-01 -4.51763928e-01 -6.75981104e-01
-5.40207028e-01 -6.44719064e-01 3.27524811e-01 4.63333428e-02
2.09686652e-01 -5.21933287e-02 -1.11947107e+00 9.24905121e-01
-7.73321450e-01 -4.81258780e-01 5.04970074e-01 5.23289621e-01
-1.89603567e-01 5.00820875e-01 2.65864670e-01 -2.91448623e-01
4.69308883e-01 -7.37371147e-02 -8.43475759e-01 2.17285962e-03
-2.43096963e-01 -1.66785106e-01 8.71943474e-01 -5.96160769e-01
-1.18199944e+00 -2.08992124e-01 -2.30965003e-01 -1.01779893e-01
-1.41568571e-01 -2.39212438e-01 -1.49189264e-01 -1.04235160e+00
9.96159971e-01 -1.23571262e-01 3.78594808e-02 1.86431766e-01
3.19522262e-01 7.53816366e-01 5.10295391e-01 -4.97669458e-01
1.59713852e+00 8.60038400e-01 2.16969609e-01 -9.96056437e-01
-3.74014527e-01 -3.51035237e-01 1.19812958e-01 -5.67763984e-01
9.49133992e-01 -9.07276213e-01 -1.48913348e+00 9.25858438e-01
-7.55019128e-01 -3.62506211e-02 4.54860002e-01 5.34561872e-01
-7.03804791e-02 8.07189524e-01 -4.81427699e-01 -1.19539297e+00
-3.92941356e-01 -1.06813645e+00 1.01733077e+00 3.70576560e-01
-5.83852641e-02 -6.86239123e-01 -1.29881173e-01 8.32517505e-01
4.30534065e-01 6.75197721e-01 4.36716229e-01 1.90926254e-01
-4.30391490e-01 -5.33375025e-01 -1.47792652e-01 3.46934080e-01
5.85933030e-02 1.83672756e-01 -1.20553112e+00 -6.83903873e-01
2.47681402e-02 -3.04042399e-01 6.68728769e-01 2.95106649e-01
9.82089996e-01 -3.62232178e-01 -5.45208395e-01 6.98335230e-01
1.39702761e+00 4.72880304e-01 1.08818102e+00 6.22040987e-01
6.69702649e-01 3.15755218e-01 8.21582615e-01 2.20709234e-01
-2.09873378e-01 7.79870629e-01 6.88733876e-01 -5.02291083e-01
1.82249799e-01 9.42179188e-02 8.94385517e-01 -2.38750383e-01
-2.91305333e-01 -2.95518607e-01 -5.21792769e-01 -1.03854481e-02
-1.33955657e+00 -1.29715526e+00 -2.75211871e-01 2.45756602e+00
3.69426757e-01 4.33405161e-01 3.87139857e-01 1.94938317e-01
8.15847635e-01 1.23146459e-01 -6.07772529e-01 -6.57860339e-01
3.03992152e-01 1.97211668e-01 1.19964206e+00 2.32532471e-01
-1.29016006e+00 6.57308459e-01 6.98481369e+00 6.67339563e-01
-1.17638350e+00 4.75103743e-02 4.78672206e-01 -7.63387233e-02
-1.03564359e-01 -8.82841572e-02 -8.69503260e-01 5.42120337e-01
7.56021082e-01 1.62970349e-01 6.53427988e-02 5.59383512e-01
4.57920462e-01 -3.71893078e-01 -4.52064455e-01 7.18997657e-01
6.82366416e-02 -5.96391976e-01 -3.54555249e-01 1.09696008e-01
3.64557117e-01 -4.01780725e-01 6.02071702e-01 -1.11637944e-02
3.83562177e-01 -9.99659419e-01 7.38816321e-01 6.64944947e-02
9.77890790e-01 -1.11969900e+00 6.16481602e-01 2.10264221e-01
-1.28283334e+00 -3.24469626e-01 -4.13904369e-01 -4.11964022e-02
3.54907736e-02 2.56576300e-01 -3.59169334e-01 5.05289793e-01
7.20966280e-01 -3.53506170e-02 -5.57729959e-01 7.45895982e-01
-4.17835057e-01 8.07574332e-01 -3.04307133e-01 -2.90775687e-01
1.97241753e-01 -5.40601835e-02 7.69528389e-01 8.18672121e-01
1.19707018e-01 2.55278945e-01 2.44295392e-02 7.14457512e-01
4.17811662e-01 -4.43278849e-01 -1.08008945e+00 5.16481459e-01
4.59374607e-01 1.19839394e+00 -3.35944891e-01 8.87042731e-02
-4.82908905e-01 7.81338036e-01 -4.64188457e-01 6.33239269e-01
-1.60453403e+00 -7.04993427e-01 9.57737327e-01 8.83520395e-02
-6.28579557e-02 -5.16864479e-01 -2.63857424e-01 -7.72263587e-01
2.20437944e-01 -8.13822031e-01 1.36833414e-01 -7.73205101e-01
-9.32997942e-01 3.13767076e-01 1.02080025e-01 -1.54920411e+00
3.96815866e-01 -6.67558670e-01 -7.72049844e-01 8.41988146e-01
-1.24203598e+00 -1.29061985e+00 -5.09287477e-01 6.74970448e-01
1.18097663e-02 -1.38013229e-01 3.54335457e-01 8.64838362e-02
-7.10912824e-01 1.15604091e+00 8.86024237e-02 3.06738973e-01
6.86662912e-01 -5.53566039e-01 6.91287518e-01 1.33848226e+00
-5.41345656e-01 7.11772859e-01 8.58370543e-01 -6.30693495e-01
-1.69131207e+00 -1.07652926e+00 -2.42024988e-01 -5.52489460e-01
4.79722977e-01 -3.69869679e-01 -4.39060181e-01 2.28427544e-01
1.33698106e-01 5.07331565e-02 6.18267357e-01 -3.92202079e-01
-5.18125534e-01 -4.00365353e-01 -1.45970333e+00 1.00729406e+00
9.09237504e-01 -5.15694737e-01 -2.62165934e-01 2.59579778e-01
7.10156381e-01 -2.40089297e-01 -4.61635709e-01 5.02205968e-01
1.01982272e+00 -9.18577135e-01 1.42621279e+00 -6.06896877e-02
-1.06892630e-01 -5.49058616e-01 3.09145421e-01 -9.91186500e-01
-3.00181925e-01 -9.66055572e-01 2.36296728e-01 1.01096857e+00
-1.05109245e-01 -1.18256068e+00 7.07045972e-01 7.89242446e-01
1.33965507e-01 -2.89302588e-01 -7.64739692e-01 -1.12157965e+00
-9.91635397e-02 -4.17412788e-01 3.26778024e-01 4.49102372e-01
-1.13487415e-01 -5.19127771e-02 -7.34360337e-01 8.84419560e-01
9.91321743e-01 -5.92498362e-01 1.08820379e+00 -4.05815750e-01
-2.39061072e-01 -1.34622619e-01 -8.51913333e-01 -7.19206095e-01
-1.86941884e-02 -2.18514234e-01 6.67689145e-02 -8.40585530e-01
2.97138989e-02 -4.05647546e-01 2.42341701e-02 3.55176091e-01
-4.93831545e-01 7.98155665e-01 -5.34841269e-02 -1.12985820e-01
-1.18173711e-01 3.12447280e-01 9.35688376e-01 -5.24424553e-01
4.89598187e-03 2.66562670e-01 -6.22107923e-01 6.30072832e-01
9.85004604e-01 -2.13690013e-01 -5.49043715e-01 -2.35696778e-01
1.83357969e-01 -3.51906657e-01 9.84231174e-01 -1.41447937e+00
1.06528722e-01 -2.98286617e-01 4.10122603e-01 -1.11413673e-01
3.53589892e-01 -9.91998613e-01 1.53334171e-01 8.68250012e-01
2.74638921e-01 -5.15062436e-02 5.81366420e-01 5.42581320e-01
3.89634937e-01 -5.11761801e-03 1.08200657e+00 1.90149009e-01
-7.58662641e-01 2.36353859e-01 -6.34395003e-01 -2.21256450e-01
1.71873903e+00 -7.88075209e-01 -9.16192532e-01 -3.50403279e-01
5.17124534e-02 -8.62844661e-02 6.51809871e-01 3.38457704e-01
8.31191599e-01 -1.31844759e+00 -5.87920487e-01 4.79836762e-01
1.61149636e-01 -5.87648332e-01 2.99176037e-01 5.92382371e-01
-7.82471120e-01 2.07477391e-01 -1.94240287e-01 -6.80939853e-01
-1.80532217e+00 7.74037480e-01 4.11837995e-01 4.75078166e-01
-6.00970805e-01 6.14461601e-01 3.89754415e-01 1.75770670e-01
-6.24221489e-02 1.78900614e-01 -4.67862412e-02 -9.07133639e-01
6.47029221e-01 5.26910245e-01 -2.04947472e-01 -6.53868318e-01
-5.41320324e-01 1.15380764e+00 7.31454566e-02 -2.18420789e-01
5.22703290e-01 -1.34896427e-01 1.73970908e-01 -4.62127626e-01
9.53031659e-01 3.72476161e-01 -1.21617949e+00 2.46831909e-01
-7.68099666e-01 -8.52478623e-01 -7.89052173e-02 -5.31825244e-01
-9.00080085e-01 6.49746180e-01 9.24362361e-01 2.74167776e-01
1.29850137e+00 -3.59409839e-01 1.02619183e+00 2.18107864e-01
5.02374589e-01 -8.53023946e-01 3.08425367e-01 7.95038044e-03
3.41544718e-01 -1.11763966e+00 1.94927558e-01 -6.30646646e-01
-4.56012398e-01 7.52210796e-01 8.18896711e-01 -8.49939510e-02
3.67974102e-01 3.64217967e-01 3.34101439e-01 3.63470204e-02
-1.11172184e-01 1.24337479e-01 1.79918155e-01 9.08692122e-01
6.02989830e-02 1.36778295e-01 -1.75842434e-01 -7.53068700e-02
-1.21385559e-01 -3.78688335e-01 4.65753704e-01 1.12806308e+00
-4.57997680e-01 -9.42401171e-01 -1.14258409e+00 -7.01435581e-02
-6.21604979e-01 2.14208618e-01 -3.31231982e-01 7.13979661e-01
4.07146476e-02 1.52130151e+00 -5.35557449e-01 -8.23806286e-01
3.62998486e-01 -5.04703343e-01 3.42223287e-01 1.19049037e-02
-3.17671716e-01 -2.06158161e-01 6.89250901e-02 -6.32580161e-01
-3.30928922e-01 -1.30296007e-01 -8.44262302e-01 -9.09198821e-01
-4.78705406e-01 -1.75507009e-01 6.38203561e-01 9.16355133e-01
1.09081119e-01 3.81461114e-01 1.26064825e+00 -5.05440235e-01
-6.57318830e-01 -3.84615481e-01 -2.63242543e-01 4.49709415e-01
4.38709080e-01 -7.12440670e-01 -3.60778838e-01 -3.19402277e-01] | [5.34542989730835, 8.022085189819336] |
05b4d980-4ee4-482a-a877-c55b9f697b0b | crop-yield-prediction-integrating-genotype | 2006.13847 | null | https://arxiv.org/abs/2006.13847v1 | https://arxiv.org/pdf/2006.13847v1.pdf | Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning | Accurate prediction of crop yield supported by scientific and domain-relevant insights, can help improve agricultural breeding, provide monitoring across diverse climatic conditions and thereby protect against climatic challenges to crop production including erratic rainfall and temperature variations. We used historical performance records from Uniform Soybean Tests (UST) in North America spanning 13 years of data to build a Long Short Term Memory - Recurrent Neural Network based model to dissect and predict genotype response in multiple-environments by leveraging pedigree relatedness measures along with weekly weather parameters. Additionally, for providing explainability of the important time-windows in the growing season, we developed a model based on temporal attention mechanism. The combination of these two models outperformed random forest (RF), LASSO regression and the data-driven USDA model for yield prediction. We deployed this deep learning framework as a 'hypotheses generation tool' to unravel GxExM relationships. Attention-based time series models provide a significant advancement in interpretability of yield prediction models. The insights provided by explainable models are applicable in understanding how plant breeding programs can adapt their approaches for global climate change, for example identification of superior varieties for commercial release, intelligent sampling of testing environments in variety development, and integrating weather parameters for a targeted breeding approach. Using DL models as hypothesis generation tools will enable development of varieties with plasticity response in variable climatic conditions. We envision broad applicability of this approach (via conducting sensitivity analysis and "what-if" scenarios) for soybean and other crop species under different climatic conditions. | ['Linjiang Wu', 'Tryambak Gangopadhyay', 'Johnathon Shook', 'Baskar Ganapathysubramanian', 'Asheesh K. Singh', 'Soumik Sarkar'] | 2020-06-24 | null | null | null | null | ['explainable-models', 'crop-yield-prediction', 'crop-yield-prediction'] | ['computer-vision', 'computer-vision', 'miscellaneous'] | [ 1.60182297e-01 -3.63368005e-01 -5.96279323e-01 -5.16957402e-01
7.63337910e-02 -9.06605184e-01 -4.85116383e-03 4.50928301e-01
3.08304250e-01 6.45293355e-01 1.45335376e-01 -9.49647844e-01
-5.57716966e-01 -1.19577861e+00 -6.55154347e-01 -6.42296433e-01
-6.10000134e-01 1.94812149e-01 -2.61029691e-01 -6.84901357e-01
1.84284538e-04 6.47789478e-01 -1.57159853e+00 4.27069776e-02
1.03538859e+00 6.70709968e-01 9.19404924e-01 6.15254700e-01
-3.12280143e-03 -8.86943117e-02 -3.36887270e-01 1.52409256e-01
2.01576538e-02 -2.21064895e-01 -3.86586636e-01 -3.05553019e-01
-2.55547881e-01 -3.57402742e-01 1.66376323e-01 7.67949760e-01
5.01334190e-01 -1.95858225e-01 3.30874771e-01 -8.45005691e-01
-1.32293320e+00 1.27904344e+00 -9.60640311e-01 7.41227642e-02
-8.89246911e-02 3.52457374e-01 8.06541979e-01 -4.09073085e-01
5.67978799e-01 1.09172058e+00 7.60650754e-01 -1.04895890e-01
-1.61802137e+00 -5.96532702e-01 4.03502256e-01 3.56420159e-01
-9.35469866e-01 -8.27815607e-02 3.66024226e-01 -3.96446556e-01
1.01617253e+00 4.65819716e-01 8.77826810e-01 8.96964371e-01
6.42669857e-01 5.57264745e-01 9.30701554e-01 -9.37041864e-02
9.15168002e-02 -4.69803959e-01 3.11907381e-01 3.39466035e-01
2.52115518e-01 7.52981603e-01 -2.50693768e-01 -2.98162736e-02
7.00877488e-01 2.57424802e-01 -2.34891117e-01 -5.20053729e-02
-1.13365078e+00 7.79448152e-01 9.06984448e-01 2.74567865e-02
-7.35384226e-01 -2.84977816e-02 3.93974870e-01 3.06868106e-01
5.56096673e-01 7.76833415e-01 -1.43179190e+00 1.46513149e-01
-1.07391179e+00 3.26004893e-01 6.81519330e-01 8.08395565e-01
6.32877290e-01 6.87239468e-01 -1.91322982e-01 7.78647900e-01
3.24237674e-01 1.07091033e+00 3.52061152e-01 -6.56909764e-01
-1.68491215e-01 4.44026828e-01 2.09719256e-01 -1.21151829e+00
-1.01606250e+00 -5.83740830e-01 -9.19468164e-01 -1.48345875e-02
4.17986363e-02 -3.41099203e-01 -1.08186853e+00 2.03339195e+00
5.15409857e-02 -3.62311453e-02 8.13427642e-02 9.42307949e-01
4.21499401e-01 7.91257560e-01 3.72751802e-01 -4.36471939e-01
1.45735598e+00 -1.29266202e-01 -7.39799976e-01 -7.27059096e-02
7.60617495e-01 -5.77107549e-01 7.10827470e-01 7.14797378e-02
-4.48835164e-01 -6.02936506e-01 -1.02124691e+00 6.41871214e-01
-8.67415488e-01 3.60724419e-01 1.41072059e+00 4.93237108e-01
-7.61604786e-01 9.03587520e-01 -1.02862370e+00 -7.79363453e-01
2.52693713e-01 2.69439459e-01 -1.13410912e-01 2.22512484e-01
-1.14834070e+00 1.15778637e+00 5.32209158e-01 1.08156455e+00
-1.09319627e+00 -1.04594612e+00 -8.17156076e-01 2.57104039e-01
1.54308140e-01 -4.13036585e-01 5.89276373e-01 -7.05886483e-01
-1.43547642e+00 5.96838057e-01 -2.95970794e-02 -6.27579927e-01
-4.36990798e-01 -4.11898375e-01 -7.39815891e-01 -5.88838995e-01
1.99479297e-01 5.61429262e-01 3.68685186e-01 -7.11126804e-01
-2.31238663e-01 -7.27747202e-01 -6.49017990e-01 -3.64890903e-01
2.53397785e-02 1.39889970e-01 6.56564295e-01 -7.44188011e-01
3.97616118e-01 -1.05666327e+00 -7.37718284e-01 -2.30134428e-01
-2.70703554e-01 4.60049212e-01 8.22040081e-01 -1.05793929e+00
9.21396613e-01 -1.74922979e+00 9.97542515e-02 5.51676229e-02
-2.53514022e-01 3.86932164e-01 -6.19150341e-01 4.94686395e-01
-3.75527829e-01 3.62368971e-01 -1.03010193e-01 9.37155426e-01
-1.21013820e-01 2.31007814e-01 -5.55903733e-01 2.23602176e-01
8.69401515e-01 9.72325921e-01 -8.56441796e-01 4.92518246e-01
2.25254312e-01 7.34209567e-02 -2.78297424e-01 3.61960173e-01
-5.40562153e-01 3.59150201e-01 -5.28437912e-01 1.18107045e+00
1.16450429e+00 1.38291553e-01 3.28415573e-01 -1.41540900e-01
-6.52222931e-01 -2.03197598e-01 -6.33242548e-01 1.50879371e+00
-2.77610868e-01 4.65300709e-01 -4.07469533e-02 -1.14594924e+00
1.53355014e+00 2.10231431e-02 2.31688946e-01 -4.50834274e-01
-2.10441217e-01 1.31449774e-01 3.58138621e-01 -4.71624523e-01
4.70455438e-01 4.32523310e-01 -6.03293180e-02 1.15989409e-01
1.01897202e-01 1.66322842e-01 3.84039767e-02 -4.04085279e-01
7.04500377e-01 1.06169581e+00 2.82460243e-01 -7.19068944e-01
-5.51607199e-02 2.23598704e-01 1.09384787e+00 6.11945450e-01
-3.00270766e-01 3.67561430e-01 5.75196862e-01 -7.76556849e-01
-8.58325899e-01 -7.68603861e-01 -5.89693666e-01 1.49823749e+00
-3.53361666e-01 9.56967380e-03 1.61262080e-01 -4.96669626e-03
4.75647897e-01 9.55445170e-01 -7.96724916e-01 -5.83504617e-01
-1.72852576e-01 -1.70535910e+00 4.84629452e-01 8.08561981e-01
2.52386868e-01 -1.12857890e+00 -6.26122236e-01 5.74947774e-01
6.76354691e-02 -4.85882193e-01 2.04102442e-01 1.10541904e+00
-8.44066978e-01 -5.90775132e-01 -7.03994572e-01 -3.67104143e-01
1.64971709e-01 1.68962002e-01 1.19375491e+00 -4.86133665e-01
-5.61783969e-01 -4.33399111e-01 -4.77529466e-01 -6.26970708e-01
-3.44337374e-01 3.94024640e-01 7.47640505e-02 -6.21054351e-01
5.96658647e-01 -9.19494033e-01 -5.71965873e-01 3.70398372e-01
-6.06759608e-01 2.66447701e-02 6.65499032e-01 1.23034704e+00
3.44871223e-01 -2.60064423e-01 1.19994187e+00 -5.20066559e-01
1.20618299e-01 -1.16339087e+00 -1.02655995e+00 7.04246879e-01
-8.44536304e-01 3.09202850e-01 3.50839108e-01 -4.32085395e-01
-1.10383427e+00 -6.56000618e-03 2.22317293e-01 1.99763581e-01
-2.34126791e-01 1.32041824e+00 -2.35535756e-01 3.18703622e-01
5.39663553e-01 -3.44999571e-04 -5.63929304e-02 -3.12930644e-01
4.81373906e-01 2.39538059e-01 6.21329725e-01 -7.15901017e-01
5.96359968e-01 -3.80873442e-01 1.50088355e-01 -5.39216816e-01
-5.39676487e-01 1.66690268e-03 -8.00997376e-01 -5.59180230e-02
6.66845083e-01 -9.94611323e-01 -8.70167315e-01 5.07015347e-01
-8.86637688e-01 -3.48248869e-01 4.15570252e-02 6.43704534e-01
-4.07474160e-01 -3.61374050e-01 -3.11388671e-01 -6.47857547e-01
-4.93695885e-01 -8.17966461e-01 8.14958453e-01 6.59249485e-01
-1.25077054e-01 -9.14637566e-01 1.55972391e-01 -2.05399454e-01
8.19676220e-01 6.82593942e-01 1.28829587e+00 -4.86214131e-01
-3.14279735e-01 -1.10709578e-01 -3.59391510e-01 -1.20902762e-01
4.19552624e-01 6.86064482e-01 -8.42914701e-01 -1.07966755e-02
-5.17079711e-01 -3.54896307e-01 8.28341782e-01 1.13340449e+00
1.01643479e+00 2.35224366e-01 -3.33115160e-01 1.06578457e+00
1.46911836e+00 3.91741872e-01 4.44602400e-01 2.44462296e-01
4.43429142e-01 7.54166782e-01 9.26298022e-01 5.65524995e-01
2.70117968e-01 3.48801047e-01 6.31549776e-01 -4.62947756e-01
4.31914210e-01 -2.28234604e-01 4.68707353e-01 3.22877973e-01
-1.00750074e-01 -1.18745498e-01 -1.07095659e+00 6.53851330e-01
-2.08668637e+00 -1.17996156e+00 -2.92513579e-01 2.26198316e+00
7.70491302e-01 -2.64071167e-01 -1.83635890e-01 -4.86648858e-01
4.44049865e-01 2.07119465e-01 -1.08883822e+00 -9.13456500e-01
-8.91321421e-01 1.35101274e-01 1.12538886e+00 -4.71540391e-02
-9.78357971e-01 1.34808004e+00 6.99266100e+00 2.20914125e-01
-1.33270562e+00 -6.97789907e-01 1.01882517e+00 2.19073772e-01
-3.36525083e-01 5.82646191e-01 -9.76186991e-01 -5.23090288e-02
1.43808877e+00 -2.18665615e-01 3.61673981e-01 6.56530976e-01
9.12377954e-01 -1.66607946e-01 -7.04865634e-01 -2.05026031e-01
-5.59309185e-01 -1.29412401e+00 -2.22921565e-01 -1.39006913e-01
6.95686579e-01 1.43465489e-01 4.98185828e-02 3.58834773e-01
9.71481204e-01 -1.02451301e+00 1.29027411e-01 7.13745534e-01
5.77207148e-01 -6.22335076e-01 7.28987634e-01 -8.77123550e-02
-1.28140318e+00 -1.95112973e-01 -8.32665145e-01 -2.28063345e-01
-1.41654894e-01 8.20853829e-01 -8.83107483e-01 9.02078509e-01
8.40400279e-01 1.12498832e+00 -7.49480367e-01 6.92012906e-01
1.69772029e-01 1.00734425e+00 -3.26550812e-01 2.22305834e-01
-4.07984741e-02 -4.03559059e-01 3.29601675e-01 9.55882192e-01
5.39320648e-01 -1.57296062e-01 2.08391234e-01 1.31792915e+00
6.17735803e-01 -8.69612768e-02 -6.48379087e-01 -2.64370531e-01
5.66121995e-01 1.27570486e+00 -8.51151228e-01 3.36462647e-01
7.00731054e-02 5.98196208e-01 2.69104224e-02 5.98345220e-01
-7.07484007e-01 -3.06136996e-01 7.99416184e-01 -4.41326320e-01
4.52343553e-01 -3.03376645e-01 -3.32913041e-01 -9.58123624e-01
-4.06506926e-01 -7.71957397e-01 7.66954273e-02 -1.03374970e+00
-1.04524457e+00 1.57555133e-01 3.22631858e-02 -8.28929961e-01
-3.20739567e-01 -6.43804193e-01 -7.88034379e-01 1.49495411e+00
-1.61783254e+00 -1.63915873e+00 -1.90627828e-01 -2.01495856e-01
3.69592339e-01 -3.14178467e-01 1.44436359e+00 -2.99501687e-01
-1.02486289e+00 2.24918947e-01 5.82754552e-01 -4.54018593e-01
8.13922167e-01 -1.07082260e+00 4.99399602e-01 9.49664712e-01
-4.39348638e-01 5.14229000e-01 8.18295062e-01 -1.01564085e+00
-1.69292426e+00 -1.30638301e+00 5.29715359e-01 2.30222389e-01
9.24924314e-01 -1.24847107e-01 -9.96839523e-01 7.19222069e-01
-3.68690379e-02 -1.15323581e-01 8.89664531e-01 7.56115198e-01
-1.99874371e-01 -4.94808376e-01 -8.33789051e-01 3.81269634e-01
6.62270248e-01 -2.08951696e-03 1.96334615e-01 1.72687128e-01
9.49180365e-01 1.04687899e-01 -1.40418100e+00 7.40948081e-01
9.39255655e-01 -3.09361964e-01 7.84871697e-01 -1.06701314e+00
5.24019957e-01 -1.48202941e-01 -4.66016114e-01 -1.71574032e+00
-8.79405260e-01 -6.95411026e-01 2.91233093e-01 1.67212498e+00
7.47915328e-01 -3.86053741e-01 2.56935954e-01 3.87309462e-01
-5.48814945e-02 -5.22605121e-01 -1.72487915e-01 -5.10310411e-01
2.61655509e-01 -1.81886837e-01 1.09574854e+00 9.56418872e-01
-2.09079698e-01 -2.15676591e-01 -4.57285941e-01 6.64828241e-01
8.90117884e-02 5.44197977e-01 3.68280888e-01 -1.22567010e+00
-3.69618051e-02 -6.42200470e-01 -4.29024160e-01 -2.05523103e-01
2.23430663e-01 -7.07208216e-01 -5.92387617e-02 -8.60530615e-01
1.57552227e-01 -5.57561219e-01 -3.68526876e-01 8.77455056e-01
-7.20617354e-01 -6.31736934e-01 -1.19216569e-01 -2.24525556e-01
5.37003458e-01 6.29824460e-01 7.53145337e-01 -1.15461238e-02
-5.38617492e-01 3.26720595e-01 -9.06285167e-01 2.00409561e-01
9.24233317e-01 -4.07323360e-01 -3.06735873e-01 -5.99330485e-01
3.92500013e-01 5.36484540e-01 3.16271305e-01 -5.14305055e-01
-5.37133217e-01 -9.85437334e-01 7.86325216e-01 -9.42791283e-01
-4.58642453e-01 -5.89569926e-01 4.03266072e-01 5.38765728e-01
-5.15347838e-01 4.93978649e-01 8.38957250e-01 4.96446103e-01
1.67861387e-01 1.49845809e-01 1.49160594e-01 1.98387265e-01
-8.11375320e-01 3.21696907e-01 -5.10428727e-01 -7.25578785e-01
7.67093897e-01 -4.90064621e-02 -5.17455578e-01 -3.05213798e-02
-9.68170881e-01 7.90565252e-01 3.56628150e-02 8.52318943e-01
3.02720279e-01 -1.21677470e+00 -1.36813486e+00 5.08760631e-01
1.42162487e-01 -5.52696705e-01 3.30007046e-01 5.97185731e-01
-6.85056806e-01 3.67585301e-01 -8.02794278e-01 -7.76929438e-01
-8.68086040e-01 6.38303638e-01 3.02382410e-01 -3.01781833e-01
-2.89915912e-02 6.22050166e-01 -6.48419037e-02 -7.46203303e-01
-2.43620560e-01 -6.14950240e-01 -5.17260313e-01 3.26854587e-01
1.87452853e-01 -9.67119448e-03 -1.15033798e-01 -2.12774649e-01
-3.16724360e-01 1.10829927e-01 -6.92155957e-03 2.54638791e-01
1.89733040e+00 -9.50856656e-02 -1.54994890e-01 9.52419043e-01
5.71189165e-01 -7.14627802e-01 -1.24442577e+00 2.49245837e-02
5.10017574e-01 -1.46169603e-01 2.81983942e-01 -1.37701476e+00
-1.21789312e+00 6.08915806e-01 1.21412492e+00 7.49915913e-02
1.50119567e+00 -6.60977185e-01 1.44453332e-01 2.76758075e-01
-2.30351333e-02 -6.33930266e-01 -8.84668410e-01 4.72403616e-01
1.01439846e+00 -1.50626528e+00 5.65147847e-02 1.85021237e-01
-3.20331484e-01 1.41830051e+00 6.10464573e-01 1.75815210e-01
8.62238169e-01 4.31682467e-01 7.38452189e-03 5.45066558e-02
-1.19649804e+00 -2.58802682e-01 -2.37518027e-02 1.11626828e+00
9.99586880e-01 7.95032024e-01 -1.16316587e-01 6.57596767e-01
-3.14562708e-01 4.86371815e-02 3.47183883e-01 7.77263939e-01
-3.19521576e-01 -1.10970831e+00 -4.84066695e-01 7.27236331e-01
-1.06938370e-01 -4.03742999e-01 -1.22000791e-01 4.29206401e-01
-6.72700852e-02 6.88825786e-01 -6.46610409e-02 -3.58060628e-01
4.44544517e-02 1.58599675e-01 -3.27308988e-03 -4.27084416e-01
-6.60837770e-01 2.22485378e-01 7.07029132e-04 -4.04023200e-01
-1.84110910e-01 -1.02661514e+00 -7.10782409e-01 -5.97298920e-01
-8.37916315e-01 -2.88396329e-01 9.07335103e-01 7.32080400e-01
6.60559654e-01 8.42372179e-01 1.09342706e+00 -7.94176817e-01
-6.02625787e-01 -1.21811283e+00 -7.71662652e-01 -2.87114650e-01
2.08415478e-01 -3.53726804e-01 2.56221652e-01 5.52941449e-02] | [9.34849739074707, -1.6020731925964355] |
357ad2a0-25f1-4c2e-9784-8b02d5fe8459 | graph-convolutional-networks-from-the | 2208.09309 | null | https://arxiv.org/abs/2208.09309v1 | https://arxiv.org/pdf/2208.09309v1.pdf | Graph Convolutional Networks from the Perspective of Sheaves and the Neural Tangent Kernel | Graph convolutional networks are a popular class of deep neural network algorithms which have shown success in a number of relational learning tasks. Despite their success, graph convolutional networks exhibit a number of peculiar features, including a bias towards learning oversmoothed and homophilic functions, which are not easily diagnosed due to the complex nature of these algorithms. We propose to bridge this gap in understanding by studying the neural tangent kernel of sheaf convolutional networks--a topological generalization of graph convolutional networks. To this end, we derive a parameterization of the neural tangent kernel for sheaf convolutional networks which separates the function into two parts: one driven by a forward diffusion process determined by the graph, and the other determined by the composite effect of nodes' activations on the output layer. This geometrically-focused derivation produces a number of immediate insights which we discuss in detail. | ['Thomas Gebhart'] | 2022-08-19 | null | null | null | null | ['relational-reasoning'] | ['natural-language-processing'] | [-6.15648814e-02 4.49255019e-01 -2.00189035e-02 -4.75915790e-01
4.94299054e-01 -6.87620282e-01 8.65009189e-01 2.59224355e-01
-4.36888449e-03 3.43065381e-01 3.29424202e-01 -4.80786055e-01
-4.71297860e-01 -9.92663026e-01 -7.83732057e-01 -8.08387637e-01
-6.56353831e-01 4.49264348e-01 3.54211956e-01 -5.66504180e-01
-8.84315651e-03 6.37557447e-01 -9.56579924e-01 1.24293268e-01
6.55093133e-01 9.65937555e-01 -5.42280912e-01 6.68747067e-01
-7.26789236e-02 1.10755324e+00 -6.75632507e-02 -6.35782838e-01
8.01109523e-02 -4.29339498e-01 -9.11004543e-01 -3.72854471e-01
5.08213818e-01 -6.81845695e-02 -8.13448370e-01 1.17412019e+00
1.15116499e-02 1.96892723e-01 9.00021076e-01 -1.14591181e+00
-8.53459954e-01 7.57734597e-01 -1.29424338e-03 3.81043822e-01
-2.49643773e-01 4.50344197e-02 1.49924254e+00 -5.47450781e-01
7.30924606e-01 1.36225545e+00 1.15812647e+00 3.00640970e-01
-1.40009868e+00 -2.17816591e-01 -7.97439590e-02 -1.38709739e-01
-9.87119138e-01 -1.01422794e-01 9.06201541e-01 -7.47509897e-01
7.11189151e-01 1.44454732e-03 8.85130048e-01 9.36785877e-01
4.29508030e-01 5.78100204e-01 8.97159696e-01 1.30905099e-02
1.16473302e-01 -1.65673926e-01 3.34833205e-01 1.22746170e+00
3.56027097e-01 1.55820414e-01 -2.54934430e-01 -1.16084918e-01
1.26455307e+00 -2.62757074e-02 -4.17342424e-01 -9.26272035e-01
-8.62769783e-01 1.10075951e+00 1.03913188e+00 4.16845977e-01
-2.34928384e-01 6.46816134e-01 3.53429109e-01 5.69665551e-01
5.00663757e-01 4.63647813e-01 -3.23107868e-01 1.48638383e-01
-5.54734588e-01 7.07946718e-02 9.97374237e-01 5.59121430e-01
8.74866545e-01 -7.81893730e-03 1.68200836e-01 4.43863451e-01
2.05162451e-01 -5.19275442e-02 1.23217784e-01 -5.58152437e-01
1.15097627e-01 9.15228009e-01 -4.03299004e-01 -1.31882954e+00
-7.18056917e-01 -6.73048019e-01 -1.11091864e+00 1.59684300e-01
9.15029168e-01 -7.12400451e-02 -7.00905859e-01 1.80043769e+00
-2.63617355e-02 -4.87388708e-02 -2.37679988e-01 7.61500120e-01
7.72824705e-01 2.76935786e-01 -1.18756309e-01 3.14406902e-01
8.92202199e-01 -5.87795496e-01 -2.88227439e-01 2.03579396e-01
8.35343242e-01 -8.38720724e-02 9.67205882e-01 2.77470779e-02
-1.19705796e+00 -1.98878706e-01 -1.09233308e+00 -2.19254479e-01
-8.23935449e-01 -2.87225842e-01 1.01150048e+00 4.25170720e-01
-1.40875411e+00 1.25785959e+00 -8.93922508e-01 -5.52823126e-01
7.51095712e-01 4.98969674e-01 -3.40497226e-01 2.14230612e-01
-1.13789630e+00 7.49795914e-01 2.77534425e-02 2.39104211e-01
-6.37875438e-01 -7.34985709e-01 -6.94782913e-01 4.59308386e-01
3.62283620e-03 -5.64390004e-01 1.03112352e+00 -1.12204802e+00
-1.22786009e+00 7.48819709e-01 3.94771934e-01 -5.39389729e-01
8.46185863e-01 5.20613268e-02 -7.25995237e-03 2.31480360e-01
-4.26203638e-01 3.01780850e-01 7.47125804e-01 -9.13264215e-01
-9.48439017e-02 -3.97920489e-01 1.97888941e-01 -1.13031119e-01
-4.67499673e-01 -4.91841227e-01 -1.64642762e-02 -6.04963541e-01
8.47586095e-02 -8.60987782e-01 -2.15854689e-01 2.01974735e-01
-4.27679628e-01 -3.74560863e-01 7.40728915e-01 -1.94527209e-01
1.05264068e+00 -2.01184082e+00 2.83290237e-01 4.41312551e-01
1.03537118e+00 1.85128778e-01 -6.12164661e-02 6.32959783e-01
-2.91880339e-01 2.63355255e-01 -2.32405767e-01 1.01208381e-01
-5.73748201e-02 1.04574651e-01 -3.07784528e-01 7.99264193e-01
4.63722408e-01 1.38605058e+00 -1.19308436e+00 3.06571368e-03
1.25925809e-01 6.84143722e-01 -2.45657489e-01 -1.69805065e-02
-2.86569268e-01 2.02667028e-01 -5.10028720e-01 3.17098469e-01
4.03618544e-01 -5.91606259e-01 1.76254407e-01 -8.30751285e-02
3.47171575e-02 2.91618794e-01 -6.36805892e-01 1.23823965e+00
5.05566187e-02 1.10150254e+00 1.16768368e-01 -1.30244637e+00
9.27861273e-01 2.83171348e-02 5.77451825e-01 -3.49111497e-01
3.94388348e-01 7.76967406e-02 3.87301594e-01 -3.65798205e-01
2.69404560e-01 -3.05795580e-01 1.26015738e-01 5.36820471e-01
3.70760530e-01 1.34953156e-01 -1.46697342e-01 4.12887305e-01
1.41316247e+00 -2.27437392e-01 -5.36463894e-02 -8.59090388e-01
2.92907149e-01 -1.56305209e-01 1.43209025e-01 6.23514354e-01
-3.43697637e-01 3.46294016e-01 1.27835214e+00 -9.47391808e-01
-1.08359289e+00 -1.18061399e+00 -9.06010717e-02 9.04460430e-01
-9.98568349e-03 -3.48302186e-01 -7.27683187e-01 -7.61448145e-01
3.33910942e-01 -9.42170992e-02 -1.17640889e+00 -5.69331646e-01
-6.66215241e-01 -6.94334030e-01 7.73996174e-01 6.14304841e-01
4.95385259e-01 -8.75195026e-01 -4.05956119e-01 -6.99315639e-03
4.47355390e-01 -9.39175069e-01 -2.64599264e-01 3.39775532e-01
-1.07125103e+00 -1.43099236e+00 -6.55296803e-01 -8.30629408e-01
7.74426460e-01 3.67234312e-02 1.33335197e+00 4.18823153e-01
-1.71403855e-01 4.11777258e-01 9.35918912e-02 -2.15351686e-01
-4.60709780e-01 3.40687841e-01 -1.02299951e-01 3.13590825e-01
1.77056193e-01 -8.08546543e-01 -5.20199180e-01 1.60580933e-01
-9.01051939e-01 -2.23984793e-01 5.40069401e-01 7.76926219e-01
3.59642841e-02 6.01163656e-02 3.07550162e-01 -1.09184504e+00
9.93056715e-01 -6.25327826e-01 -6.62718713e-01 1.99513018e-01
-5.17804921e-01 3.31099153e-01 8.69945228e-01 -3.85479480e-01
-5.89923620e-01 -7.40439221e-02 1.98838979e-01 -3.53010714e-01
1.37115479e-01 5.35841167e-01 2.50202864e-01 -5.55100679e-01
7.49408305e-01 -7.03414828e-02 2.52480328e-01 -3.53107601e-01
5.78053534e-01 1.14245359e-02 5.36994815e-01 -4.24681485e-01
9.20336127e-01 5.35327375e-01 5.08410752e-01 -9.96226788e-01
-5.36639512e-01 -6.33827448e-02 -8.23293507e-01 -4.22046602e-01
9.08330321e-01 -3.26155633e-01 -9.13531125e-01 5.24290800e-01
-9.41674650e-01 -8.55439126e-01 -4.06191289e-01 2.10438982e-01
-4.42331284e-01 -6.04949296e-02 -9.01525497e-01 -4.99039322e-01
-6.91078007e-02 -6.81644559e-01 4.13556367e-01 1.93317145e-01
-5.40172644e-02 -1.74994063e+00 1.48044482e-01 -4.20273274e-01
6.61975920e-01 5.50850034e-01 1.32377529e+00 -7.73849189e-01
-7.25523531e-01 -1.71927840e-01 -4.59421754e-01 2.45797798e-01
-1.05700448e-01 2.55307555e-01 -7.88541615e-01 -2.10904017e-01
-3.62495661e-01 -1.61354497e-01 1.22259414e+00 5.95256150e-01
7.54667461e-01 -1.91155910e-01 -2.79353410e-01 9.39861417e-01
1.42972076e+00 -3.00185531e-01 3.77713472e-01 -6.68082833e-02
9.58068132e-01 6.79666698e-01 -4.11900073e-01 -1.44565970e-01
2.18143433e-01 1.29370421e-01 6.61365807e-01 -3.02298903e-01
-1.52435750e-01 -4.19405669e-01 -2.77936887e-02 7.72242546e-01
-3.97318482e-01 2.35056914e-02 -1.06843626e+00 4.66047764e-01
-1.97440600e+00 -7.88175702e-01 -3.79586965e-01 1.99178159e+00
3.14985245e-01 3.61733079e-01 4.24896240e-01 -4.41393442e-02
5.08820295e-01 3.82015765e-01 -5.57661235e-01 -4.21165109e-01
-3.27719778e-01 3.22393090e-01 6.08321965e-01 6.15275800e-01
-8.63396943e-01 9.86107886e-01 7.03523874e+00 1.59014568e-01
-1.34394670e+00 -3.14699590e-01 6.73035324e-01 3.14672858e-01
-5.10010421e-01 -7.10471123e-02 -1.24200754e-01 9.55106765e-02
6.89604223e-01 -5.59371710e-02 4.44155335e-01 6.61127448e-01
-1.83019504e-01 2.61142403e-01 -1.31677115e+00 5.65755606e-01
-3.80960077e-01 -1.81861973e+00 6.96012378e-02 2.07624093e-01
5.33259690e-01 4.31293994e-01 1.87192068e-01 1.00696139e-01
7.70980358e-01 -1.34082043e+00 6.12217188e-01 6.24258757e-01
5.73996961e-01 -5.61685562e-01 3.61376584e-01 -1.27026485e-02
-1.29678655e+00 -1.73233703e-01 -3.54146630e-01 -3.57200265e-01
-3.00652742e-01 6.03835404e-01 -7.12114155e-01 1.63405165e-01
6.68977439e-01 1.03455520e+00 -6.30233645e-01 9.66744900e-01
-3.12310085e-02 6.28665149e-01 -1.07404537e-01 -3.46142054e-01
4.01778191e-01 -5.23228467e-01 4.69857156e-01 1.30829704e+00
-1.66763350e-01 -7.97977298e-02 -3.15106571e-01 1.37405944e+00
-3.59456688e-01 -2.37052720e-02 -1.06675804e+00 -4.61908817e-01
-2.45742383e-03 1.45682800e+00 -1.06072378e+00 5.50420992e-02
-3.65816087e-01 6.44058406e-01 8.75837684e-01 5.31230628e-01
-5.30582666e-01 -5.69576085e-01 8.00427437e-01 3.02715927e-01
3.86373281e-01 -5.21091819e-01 -2.60434180e-01 -1.14247334e+00
-8.38293508e-02 -1.74656183e-01 2.39406362e-01 -4.51638132e-01
-1.37118256e+00 5.35204053e-01 -1.82903200e-01 -5.57046413e-01
4.77841385e-02 -9.41316664e-01 -9.42379832e-01 5.90279996e-01
-1.37532210e+00 -1.07863557e+00 -2.85766453e-01 7.72653222e-01
-2.12808132e-01 -7.28435814e-03 4.95407641e-01 1.77694291e-01
-4.85808343e-01 4.19411749e-01 7.07744434e-02 5.71171045e-01
1.48485258e-01 -1.53343201e+00 9.35954928e-01 4.68076378e-01
1.22014284e-01 7.85178483e-01 5.15584886e-01 -4.69383419e-01
-1.48223376e+00 -8.99936199e-01 8.64278734e-01 -5.42702794e-01
1.19377887e+00 -6.96761787e-01 -1.06343710e+00 8.34875584e-01
-1.40968889e-01 4.60431129e-01 2.21873581e-01 2.52775371e-01
-5.85911453e-01 -2.30144579e-02 -8.45776737e-01 5.91578960e-01
1.19631755e+00 -7.02545702e-01 -2.12367967e-01 1.38196722e-01
4.97811794e-01 -7.96102956e-02 -9.92621481e-01 2.42854461e-01
5.88155210e-01 -1.27196908e+00 8.11666429e-01 -9.65609848e-01
4.36878145e-01 1.99752837e-01 2.25335911e-01 -1.39114308e+00
-6.20192230e-01 -1.02897513e+00 -8.58976394e-02 6.65448606e-01
3.51208091e-01 -9.77274895e-01 9.18246210e-01 4.29269403e-01
-4.75931726e-02 -1.08599353e+00 -6.00538611e-01 -6.22205853e-01
5.15877664e-01 2.64175087e-02 3.81041050e-01 1.15035617e+00
2.26404026e-01 6.06800556e-01 3.84569094e-02 -3.40844512e-01
5.06377876e-01 -2.25231096e-01 4.37286556e-01 -1.78978288e+00
4.49427664e-02 -1.12337017e+00 -5.47792375e-01 -1.00744283e+00
-8.91877245e-03 -1.14906037e+00 -3.28124642e-01 -1.27565980e+00
-5.85440807e-02 -4.94279087e-01 -2.33188659e-01 2.12082803e-01
3.68337750e-01 8.30752850e-02 -1.26042292e-01 2.81343192e-01
-3.19355041e-01 3.42186064e-01 1.38773978e+00 1.16118126e-01
-1.85264707e-01 2.92035379e-02 -5.38879752e-01 7.74705231e-01
7.58797526e-01 -9.77327600e-02 -5.36510766e-01 -3.49256903e-01
6.83141530e-01 -1.98489085e-01 5.74430585e-01 -7.89861321e-01
1.45138100e-01 1.83911532e-01 2.52868354e-01 -3.24468985e-02
4.14057225e-02 -5.39679825e-01 -1.59587041e-01 6.28457367e-01
-6.08344555e-01 3.32612187e-01 -2.35875830e-01 7.82327354e-01
4.15763892e-02 3.58505577e-01 8.93217027e-01 -2.96363503e-01
-1.15886889e-01 6.63685143e-01 -3.40999514e-01 2.05541834e-01
6.27060354e-01 -4.10224982e-02 -6.05621815e-01 -6.24060512e-01
-5.71544111e-01 -5.48507795e-02 3.99530739e-01 2.18424410e-01
3.96949708e-01 -1.41186070e+00 -4.26745504e-01 3.15588772e-01
-2.49347165e-01 -6.90394416e-02 -2.01521397e-01 1.14445424e+00
-7.97464609e-01 3.13648552e-01 -3.65284681e-01 -5.96253991e-01
-7.12451279e-01 3.99630964e-01 9.36614990e-01 -1.87737823e-01
-8.98392439e-01 9.23915744e-01 3.96120995e-01 -4.31950420e-01
3.39982539e-01 -6.94033206e-01 -8.75453129e-02 -6.06380589e-02
4.69085090e-02 4.17093426e-01 5.82150556e-03 -6.05398893e-01
-1.64500281e-01 4.19443250e-01 1.14088520e-01 2.84713864e-01
1.54369080e+00 3.71165901e-01 -3.80250633e-01 5.44995546e-01
1.43816137e+00 -3.36501956e-01 -1.43423247e+00 -2.37637818e-01
3.19254875e-01 1.86525770e-02 -1.86439659e-02 -3.61655980e-01
-1.32759464e+00 1.11765313e+00 1.22800648e-01 1.03229320e+00
6.11754000e-01 2.24516571e-01 7.46159077e-01 3.81526589e-01
-2.91162342e-01 -9.42310452e-01 3.16595316e-01 7.87484467e-01
7.05711007e-01 -9.63478446e-01 -1.79356322e-01 -1.89521000e-01
-7.21464753e-02 1.54022789e+00 3.54987830e-01 -8.32910001e-01
1.11183965e+00 1.05724759e-01 -1.70498595e-01 -8.34848404e-01
-7.18664348e-01 -1.70401603e-01 4.63024288e-01 6.00081742e-01
4.27341968e-01 6.39475957e-02 2.64351536e-02 2.13639051e-01
-2.20419541e-01 -2.50124633e-01 4.23433065e-01 6.29521489e-01
-5.11614382e-01 -6.59995675e-01 3.84269774e-01 4.33517724e-01
-3.27888519e-01 -6.15359917e-02 -1.01035106e+00 9.95352328e-01
-2.42306203e-01 3.50693375e-01 2.67208248e-01 -5.34538746e-01
1.63925558e-01 2.05806065e-02 5.99300206e-01 -2.10460618e-01
-6.34038150e-01 -3.36252898e-01 -5.46022244e-02 -5.62849641e-01
-1.27220124e-01 -5.07957935e-01 -1.04485893e+00 -6.43096209e-01
-1.43299907e-01 -1.10285848e-01 5.34588873e-01 8.77192616e-01
1.96498573e-01 4.45469350e-01 4.07353580e-01 -8.43939543e-01
-5.29038727e-01 -7.16210604e-01 -6.91750765e-01 5.02679288e-01
8.50085258e-01 -6.02922082e-01 -4.90453482e-01 -3.96049261e-01] | [6.8180251121521, 6.011591911315918] |
53fcc245-eea7-4ce5-ac4c-d082d142e60a | industrial-scene-text-detection-with-refined | 2110.12663 | null | https://arxiv.org/abs/2110.12663v2 | https://arxiv.org/pdf/2110.12663v2.pdf | Industrial Scene Text Detection with Refined Feature-attentive Network | Detecting the marking characters of industrial metal parts remains challenging due to low visual contrast, uneven illumination, corroded character structures, and cluttered background of metal part images. Affected by these factors, bounding boxes generated by most existing methods locate low-contrast text areas inaccurately. In this paper, we propose a refined feature-attentive network (RFN) to solve the inaccurate localization problem. Specifically, we design a parallel feature integration mechanism to construct an adaptive feature representation from multi-resolution features, which enhances the perception of multi-scale texts at each scale-specific level to generate a high-quality attention map. Then, an attentive refinement network is developed by the attention map to rectify the location deviation of candidate boxes. In addition, a re-scoring mechanism is designed to select text boxes with the best rectified location. Moreover, we construct two industrial scene text datasets, including a total of 102156 images and 1948809 text instances with various character structures and metal parts. Extensive experiments on our dataset and four public datasets demonstrate that our proposed method achieves the state-of-the-art performance. | ['Xinping Guan', 'Kaijie Wu', 'Qi Feng', 'Jingzheng Tu', 'Changsheng Lu', 'Chaochen Gu', 'Tongkun Guan'] | 2021-10-25 | null | null | null | null | ['scene-text-detection'] | ['computer-vision'] | [ 3.26849848e-01 -4.82251585e-01 3.34621489e-01 -2.85387546e-01
-6.95502818e-01 -2.93229163e-01 3.08680862e-01 -1.62627399e-01
-1.54241428e-01 1.95495442e-01 1.58749804e-01 2.93320775e-01
-4.56801355e-02 -7.08965361e-01 -6.66104615e-01 -5.66593170e-01
6.65190458e-01 2.95925707e-01 7.92629421e-01 -4.00326610e-01
6.91646457e-01 4.62947130e-01 -1.29652476e+00 4.84039724e-01
1.02686524e+00 1.03094947e+00 7.04537630e-01 2.89524853e-01
-3.54747444e-01 6.27272248e-01 -9.22493398e-01 -4.29237694e-01
2.14616716e-01 -1.01199575e-01 -3.64903539e-01 6.04375958e-01
5.42467356e-01 -4.06444281e-01 -4.28218633e-01 1.26383543e+00
4.09391880e-01 2.49346480e-01 6.95791781e-01 -9.37416315e-01
-1.28062987e+00 5.07514358e-01 -1.13538325e+00 8.23655501e-02
1.44788191e-01 1.14834949e-01 6.52025580e-01 -1.28549826e+00
3.49172771e-01 1.42374110e+00 5.21095097e-01 2.90219903e-01
-8.53148043e-01 -7.88672209e-01 6.30807161e-01 1.99667543e-01
-1.53448915e+00 -1.45815969e-01 1.03047299e+00 -2.11450547e-01
5.48277617e-01 9.64340344e-02 3.40232372e-01 8.80331635e-01
2.65948772e-01 8.93053710e-01 7.72607028e-01 -2.17525154e-01
-2.80226082e-01 2.64498264e-01 -2.02550724e-01 8.93167317e-01
3.97529274e-01 -5.09383321e-01 -3.99155468e-01 1.89506546e-01
1.19850397e+00 3.91210735e-01 -2.83298343e-01 -3.49427581e-01
-1.18846238e+00 4.93552148e-01 6.56397045e-01 2.21267805e-01
-3.49915713e-01 -2.07725354e-02 4.64147121e-01 -2.24067554e-01
3.02605599e-01 4.31599587e-01 -4.87542033e-01 2.35496983e-01
-6.07814848e-01 2.15992276e-02 8.36262628e-02 1.17068279e+00
7.47595906e-01 9.84887183e-02 -2.74750203e-01 1.08681881e+00
2.72463411e-01 5.74412644e-01 4.22428489e-01 -5.29836655e-01
8.78442168e-01 9.98460829e-01 3.99736203e-02 -1.35015678e+00
-3.72025341e-01 -3.03018540e-01 -9.74037051e-01 1.11625031e-01
1.51921675e-01 -8.74004811e-02 -9.03321683e-01 1.08742857e+00
2.41272613e-01 -1.99291989e-01 -1.82025716e-01 1.16617894e+00
7.14112639e-01 7.88653970e-01 -1.34169877e-01 2.30774641e-01
1.66201234e+00 -1.28298688e+00 -8.31024706e-01 -5.04315615e-01
9.20924917e-02 -1.05831635e+00 1.32552540e+00 4.85686451e-01
-9.57981288e-01 -8.25287282e-01 -1.22259688e+00 -2.31588230e-01
-4.00003523e-01 6.64307833e-01 2.08784282e-01 2.78059721e-01
-3.40985239e-01 3.69433314e-01 -4.11598414e-01 -1.03675470e-01
5.94054997e-01 2.11590335e-01 -1.04958691e-01 -2.60795176e-01
-9.15105879e-01 5.86795628e-01 2.25060001e-01 6.00322008e-01
-3.74433249e-01 -3.21997017e-01 -8.56229901e-01 1.09624393e-01
7.15756536e-01 -2.57662624e-01 8.01946640e-01 -1.04371774e+00
-1.37052298e+00 4.25935119e-01 1.49275362e-01 2.30511069e-01
7.66518354e-01 -4.69356686e-01 -5.43314993e-01 2.25600660e-01
3.14945251e-01 4.19107676e-01 9.48715985e-01 -1.46027637e+00
-7.47445226e-01 -3.70160341e-01 -3.47664773e-01 4.92082238e-01
-3.62421393e-01 1.71988621e-01 -8.09137344e-01 -8.71815860e-01
3.75510901e-01 -4.08453494e-01 -2.44972676e-01 1.03006326e-01
-6.83627665e-01 -1.51796803e-01 1.01197255e+00 -6.86137438e-01
1.06056929e+00 -2.23310685e+00 -3.22209895e-02 1.56902775e-01
6.52350038e-02 4.64502126e-02 -2.85884321e-01 3.73331942e-02
1.73142493e-01 1.07557280e-02 -2.52280887e-02 -1.99320480e-01
1.03052305e-02 -2.59695947e-01 -2.51993895e-01 4.38789189e-01
5.76083422e-01 8.27663720e-01 -4.94839489e-01 -8.33133161e-01
5.25664330e-01 3.73715520e-01 -1.90290049e-01 -2.29411833e-02
-1.52239516e-01 1.98044465e-03 -8.27352643e-01 9.29019630e-01
9.88202155e-01 -2.88994610e-01 -1.19332783e-01 -5.93772948e-01
-2.02617869e-01 -3.34325552e-01 -1.43209064e+00 1.57006156e+00
-3.23607564e-01 5.23321033e-01 2.72299293e-02 -5.05942643e-01
1.41444981e+00 -2.49593899e-01 2.41102025e-01 -8.41620684e-01
4.10757989e-01 7.71163926e-02 -2.47596532e-01 -6.12813830e-01
9.40698385e-01 3.64244074e-01 -2.50841171e-01 7.57207200e-02
-5.04452109e-01 -1.16589986e-01 1.12635391e-02 -4.70857415e-03
9.08739269e-01 1.98119551e-01 -8.54614824e-02 -1.62188083e-01
8.05650830e-01 -5.27904183e-02 6.26632154e-01 5.92726231e-01
-1.57678455e-01 1.05844450e+00 2.75717258e-01 -6.43690944e-01
-1.05906081e+00 -8.64799619e-01 -1.22876018e-01 1.20359755e+00
7.96799600e-01 -3.02621216e-01 -6.16172671e-01 -7.12679148e-01
-1.25372812e-01 1.90889686e-01 -7.55484879e-01 -1.83771059e-01
-9.39283848e-01 -5.59396744e-01 2.30660975e-01 7.77187228e-01
1.12551618e+00 -1.42162919e+00 -4.90736246e-01 1.93929955e-01
-2.06270009e-01 -1.10077834e+00 -8.75375152e-01 2.02408910e-01
-4.40600872e-01 -1.14304686e+00 -9.44967866e-01 -1.31321669e+00
8.46922040e-01 4.92222637e-01 8.47510219e-01 1.89371884e-01
-4.35076654e-01 -3.37642491e-01 -4.12019998e-01 -2.89094418e-01
5.26473932e-02 -2.22591385e-02 -3.03080171e-01 2.47109365e-02
2.84976780e-01 1.54378355e-01 -6.55618906e-01 6.49340630e-01
-8.22892129e-01 9.03274342e-02 9.66297567e-01 7.92749286e-01
6.98332131e-01 3.26266140e-01 4.05756891e-01 -6.88391924e-01
6.17796957e-01 -8.47519264e-02 -6.61354303e-01 4.26852763e-01
-3.41895819e-01 -1.44086167e-01 9.54197466e-01 -6.83102190e-01
-1.21969402e+00 2.52538830e-01 1.74467266e-01 -4.87071335e-01
-2.58168370e-01 -8.22875053e-02 -5.41060627e-01 8.29841942e-02
3.81352514e-01 5.25979936e-01 -3.41604650e-01 -4.82495934e-01
1.75258070e-01 7.82981515e-01 6.89403832e-01 -5.94453514e-01
9.76749241e-01 2.88654178e-01 -3.26884776e-01 -6.90742254e-01
-8.88338208e-01 -1.54268786e-01 -6.59792304e-01 -1.55374482e-01
9.98302281e-01 -8.52150500e-01 -4.93327618e-01 7.38572717e-01
-1.16601157e+00 -1.30773440e-01 -2.37402599e-02 1.61737099e-01
-3.71337146e-01 6.22034490e-01 -6.32523000e-01 -6.24908864e-01
-4.25087720e-01 -1.22872472e+00 1.54450309e+00 5.14483988e-01
3.10534596e-01 -2.50150800e-01 -4.27195340e-01 3.45036566e-01
1.95365697e-01 -4.40789666e-03 9.18269873e-01 -2.69669354e-01
-7.37579703e-01 -1.39863998e-01 -8.70868027e-01 1.43354803e-01
2.08015203e-01 1.13070063e-01 -6.51951432e-01 2.88647674e-02
-2.94273466e-01 -1.86837673e-01 7.97859013e-01 2.88101733e-01
1.50883400e+00 4.78190780e-02 -3.12808126e-01 5.64354837e-01
1.32436550e+00 3.09865594e-01 6.00867689e-01 5.97662210e-01
9.86442983e-01 4.83244866e-01 1.09936309e+00 5.54686844e-01
1.41477451e-01 5.32115698e-01 4.90717024e-01 -3.65875453e-01
-3.17505635e-02 -1.97936326e-01 7.38693774e-02 4.12108183e-01
1.12856269e-01 -2.79108703e-01 -5.38069308e-01 3.18755031e-01
-1.79283297e+00 -7.06238747e-01 -2.04080105e-01 1.79401183e+00
5.55005133e-01 3.60642225e-01 -1.16493985e-01 -7.99023509e-02
1.24767244e+00 1.94097310e-01 -7.18558371e-01 1.55463666e-02
-3.44282866e-01 -2.07750276e-01 5.06798744e-01 -1.07197531e-01
-1.28284979e+00 1.11414170e+00 5.61824656e+00 9.63703632e-01
-8.71792555e-01 -2.81881630e-01 6.09940469e-01 1.79479256e-01
-1.36787286e-02 -4.48228300e-01 -8.69809270e-01 6.67559922e-01
-7.56609580e-03 2.72429526e-01 2.82253593e-01 9.99654531e-01
-1.08052641e-02 1.75224319e-01 -4.99567986e-01 1.03095150e+00
3.96436721e-01 -1.09257984e+00 1.01634286e-01 -1.36329502e-01
8.68797660e-01 -2.56580055e-01 2.07057729e-01 1.91924259e-01
1.50115147e-01 -7.47500420e-01 9.81136739e-01 5.27778447e-01
8.28420520e-01 -9.89002705e-01 8.13566089e-01 8.16517975e-03
-1.63608098e+00 -3.82308275e-01 -7.46300459e-01 5.11105716e-01
3.63224298e-02 3.63629431e-01 -3.65391850e-01 5.08750141e-01
8.60430598e-01 6.84178472e-01 -8.49820852e-01 9.93794441e-01
-2.10345462e-01 -8.06598067e-02 -9.91147980e-02 -3.38693291e-01
2.98798323e-01 -7.74843246e-02 1.03187479e-01 1.09865212e+00
2.61929154e-01 -4.16856026e-03 3.47050786e-01 1.09085667e+00
-9.48721394e-02 3.55260491e-01 -2.24925369e-01 2.66262949e-01
5.82537591e-01 1.49224913e+00 -1.04457498e+00 -2.36414641e-01
-5.49732387e-01 1.31833744e+00 3.07566524e-01 2.63038486e-01
-1.03004038e+00 -9.63111341e-01 4.00005490e-01 -1.29423235e-02
6.29707873e-01 -8.52053463e-02 -2.94748783e-01 -1.01436126e+00
1.54435158e-01 -8.46067190e-01 1.10073544e-01 -1.19979107e+00
-1.32800663e+00 6.81532025e-01 -4.11648929e-01 -1.27373672e+00
5.67919731e-01 -7.96364725e-01 -7.58176744e-01 8.37617040e-01
-1.42322648e+00 -1.20550644e+00 -8.52165520e-01 5.51059902e-01
1.21976757e+00 -1.40542671e-01 3.10491204e-01 2.62211502e-01
-9.12382662e-01 5.22891104e-01 1.76232696e-01 4.33383584e-01
9.14054632e-01 -1.13114369e+00 4.90184426e-01 8.06236863e-01
-2.73598731e-01 4.24291104e-01 2.74127245e-01 -8.62092257e-01
-1.26947963e+00 -1.27171314e+00 1.56996533e-01 -2.96520799e-01
4.54636216e-01 -5.59319794e-01 -1.06328773e+00 4.09608066e-01
5.59102604e-03 1.00714393e-01 -9.98752937e-03 -2.55146563e-01
-1.58875033e-01 -8.90199766e-02 -9.36964810e-01 6.55647993e-01
8.98373365e-01 -1.55652359e-01 -5.72425306e-01 3.32707167e-01
6.57356918e-01 -5.32730162e-01 -6.82830513e-01 2.49654457e-01
5.21231830e-01 -8.09857428e-01 9.71788406e-01 -6.69670338e-03
6.28473997e-01 -5.36842287e-01 -4.93061878e-02 -8.20927739e-01
-6.00625336e-01 -2.02854246e-01 2.94725806e-01 1.40510774e+00
2.16010913e-01 -3.76844883e-01 8.65324557e-01 2.01222360e-01
-4.35052693e-01 -7.87801802e-01 -4.93848473e-01 -4.48170155e-01
-2.05273330e-01 1.31862342e-01 8.94397736e-01 6.94459021e-01
-4.41634327e-01 4.01860356e-01 -3.27218831e-01 2.89669901e-01
3.79185647e-01 3.65749031e-01 7.27068067e-01 -1.21712410e+00
1.27279818e-01 -4.81511503e-01 -3.08600307e-01 -1.29088068e+00
-3.31624039e-02 -2.88309097e-01 5.05061448e-01 -1.53084803e+00
4.30002242e-01 -4.52954024e-01 -3.04931372e-01 3.31399471e-01
-4.36373234e-01 3.86411220e-01 1.96381629e-01 7.28415921e-02
-9.21581328e-01 7.51820505e-01 1.62344968e+00 -4.46052521e-01
-8.15597400e-02 -2.64973551e-01 -7.77455151e-01 8.55464935e-01
7.16338813e-01 -1.79552063e-01 -7.65635595e-02 -5.79184175e-01
5.44140823e-02 -3.04370314e-01 3.05498749e-01 -1.04847765e+00
1.92764699e-01 -2.42733106e-01 1.23568010e+00 -1.21100831e+00
3.75174433e-01 -1.00464034e+00 -4.73044842e-01 3.19051743e-01
-2.14217067e-01 2.94144630e-01 5.53019084e-02 6.66089416e-01
5.41818738e-02 -3.99783552e-01 7.31437922e-01 -2.28971392e-01
-9.22189415e-01 2.25922689e-01 -2.80873984e-01 1.19570922e-02
9.08195913e-01 -4.02907610e-01 -6.71636343e-01 1.63327530e-01
-1.56625479e-01 4.02967721e-01 6.12393379e-01 6.99453831e-01
9.80931342e-01 -1.29911160e+00 -5.96347153e-01 5.11353135e-01
2.54974097e-01 4.12577122e-01 5.88213444e-01 5.54590106e-01
-6.52621925e-01 4.29145731e-02 -3.32895726e-01 -3.78810436e-01
-1.20063400e+00 5.96463919e-01 3.65471870e-01 -3.97640616e-02
-9.66030657e-01 6.85320258e-01 4.00632322e-01 -2.57224202e-01
1.20990507e-01 -4.32856858e-01 -2.92529643e-01 -2.35095963e-01
5.84162354e-01 4.17911887e-01 -5.89378132e-03 -6.70290947e-01
-3.59380364e-01 1.16224027e+00 -4.94514644e-01 4.13786620e-01
1.08398354e+00 -3.75407308e-01 1.17846131e-01 1.45226847e-02
9.11802292e-01 2.84545958e-01 -1.57912838e+00 -2.68888831e-01
-4.47122931e-01 -7.16325521e-01 -1.14939064e-01 -7.64881313e-01
-1.22743142e+00 7.35657394e-01 6.49045706e-01 -2.72226501e-02
1.16963351e+00 -1.05568841e-01 7.45840371e-01 5.22262573e-01
-1.09353298e-02 -1.46560395e+00 6.94847047e-01 3.99110764e-01
8.89351785e-01 -1.34537625e+00 1.33451864e-01 -6.00236118e-01
-8.33660841e-01 1.34283638e+00 1.34704554e+00 -4.19526070e-01
1.51892558e-01 4.05706316e-01 1.90339863e-01 -3.40401143e-01
-3.20510715e-01 -9.18682516e-02 1.73853055e-01 6.53317451e-01
9.94976461e-02 -3.17789853e-01 8.16915706e-02 9.29145515e-01
3.85541581e-02 -5.69073379e-01 5.60100079e-01 9.40041542e-01
-7.91138351e-01 -4.88233566e-01 -7.01869726e-01 4.50886965e-01
-3.75979960e-01 -9.01296437e-02 -4.77863967e-01 8.35942626e-01
1.91911310e-01 8.52993011e-01 3.33119959e-01 -4.61696684e-01
6.07891083e-01 -3.52435946e-01 2.99454808e-01 -4.75738466e-01
-6.03499055e-01 3.32275480e-01 -3.30630124e-01 -3.81337345e-01
6.65506497e-02 -4.65968907e-01 -1.45791399e+00 4.55349348e-02
-8.78884315e-01 -1.40676484e-01 5.33920765e-01 6.76363945e-01
1.94839954e-01 1.07004189e+00 8.34278822e-01 -9.36950505e-01
-5.28187871e-01 -1.03944278e+00 -8.09628606e-01 4.36078727e-01
6.65022200e-03 -7.14711905e-01 -1.69298097e-01 -1.06467649e-01] | [12.072015762329102, 2.2017946243286133] |
c2605656-a29a-4f4e-98f2-cb565b4d213d | learned-image-compression-with-generalized | 2209.03353 | null | https://arxiv.org/abs/2209.03353v1 | https://arxiv.org/pdf/2209.03353v1.pdf | Learned Image Compression with Generalized Octave Convolution and Cross-Resolution Parameter Estimation | The application of the context-adaptive entropy model significantly improves the rate-distortion (R-D) performance, in which hyperpriors and autoregressive models are jointly utilized to effectively capture the spatial redundancy of the latent representations. However, the latent representations still contain some spatial correlations. In addition, these methods based on the context-adaptive entropy model cannot be accelerated in the decoding process by parallel computing devices, e.g. FPGA or GPU. To alleviate these limitations, we propose a learned multi-resolution image compression framework, which exploits the recently developed octave convolutions to factorize the latent representations into the high-resolution (HR) and low-resolution (LR) parts, similar to wavelet transform, which further improves the R-D performance. To speed up the decoding, our scheme does not use context-adaptive entropy model. Instead, we exploit an additional hyper layer including hyper encoder and hyper decoder to further remove the spatial redundancy of the latent representation. Moreover, the cross-resolution parameter estimation (CRPE) is introduced into the proposed framework to enhance the flow of information and further improve the rate-distortion performance. An additional information-fidelity loss is proposed to the total loss function to adjust the contribution of the LR part to the final bit stream. Experimental results show that our method separately reduces the decoding time by approximately 73.35 % and 93.44 % compared with that of state-of-the-art learned image compression methods, and the R-D performance is still better than H.266/VVC(4:2:0) and some learning-based methods on both PSNR and MS-SSIM metrics across a wide bit rates. | ['Feng Liang', 'Haisheng Fu'] | 2022-09-07 | null | null | null | null | ['ms-ssim'] | ['computer-vision'] | [ 3.04268390e-01 -4.15927470e-01 -1.96584091e-01 -1.13304876e-01
-7.26250768e-01 1.26529828e-01 1.68763623e-01 -1.28141955e-01
-3.68545353e-01 4.63536650e-01 4.27342266e-01 -6.07024995e-04
-2.01272324e-01 -9.13893878e-01 -5.39007306e-01 -9.73263860e-01
-1.57215431e-01 -4.85538751e-01 2.63628930e-01 -4.38612141e-02
3.41650546e-01 1.88459724e-01 -1.40687895e+00 4.35858160e-01
9.58722472e-01 1.26508808e+00 6.86412573e-01 5.29926479e-01
5.54949529e-02 5.99088013e-01 -2.16253936e-01 -1.92667022e-01
2.32930303e-01 -3.97684216e-01 -8.40358585e-02 -7.87902847e-02
-9.62593257e-02 -8.23537469e-01 -7.80879974e-01 1.23272002e+00
7.24997163e-01 -1.05087524e-02 3.95819157e-01 -5.18333793e-01
-5.36129415e-01 3.30880642e-01 -1.07410467e+00 2.56487280e-01
1.54396221e-01 -3.62293655e-03 6.25973344e-01 -1.00057328e+00
1.90235585e-01 1.30936229e+00 5.31570733e-01 9.95595902e-02
-9.57563341e-01 -1.03646159e+00 -9.64664742e-02 5.35801888e-01
-1.73561025e+00 -4.53228235e-01 7.72314847e-01 -1.13237295e-02
8.24937940e-01 9.90951955e-02 3.84740353e-01 7.39500940e-01
1.67081997e-01 5.32179952e-01 9.53791201e-01 -3.39299947e-01
-2.80442480e-02 -2.02842414e-01 -2.36547634e-01 5.92293024e-01
2.97317743e-01 1.60635278e-01 -5.25254965e-01 1.55113488e-01
1.29034913e+00 4.61000167e-02 -6.03680015e-01 5.83153777e-02
-1.04589510e+00 5.69742262e-01 3.95023346e-01 1.84384078e-01
-3.96757990e-01 8.26302022e-02 4.96833861e-01 -6.63600564e-02
2.51612961e-01 -1.23533107e-01 -2.96939760e-01 -2.08027139e-01
-1.21542907e+00 -1.42024264e-01 2.91710228e-01 1.06691051e+00
6.70298278e-01 2.41998285e-01 -3.53405416e-01 1.20554125e+00
5.58913112e-01 3.81586909e-01 7.50812769e-01 -1.04020846e+00
8.85721445e-01 2.74832338e-01 -1.29030511e-01 -1.16875088e+00
2.09719632e-02 -6.64438605e-01 -1.51211178e+00 -7.63759091e-02
-3.39254260e-01 1.54261470e-01 -7.64923751e-01 1.30227077e+00
-6.64559752e-02 4.41407531e-01 2.52326220e-01 1.04318845e+00
7.12796271e-01 1.16288412e+00 -2.93253995e-02 -8.28343809e-01
1.38140130e+00 -9.95840192e-01 -1.04531288e+00 -1.64878834e-02
1.30712852e-01 -1.00018787e+00 7.48393595e-01 4.28132385e-01
-1.48317337e+00 -8.72280061e-01 -1.51244783e+00 -2.56999344e-01
3.64805281e-01 4.32082325e-01 2.82044053e-01 5.77521503e-01
-6.56894147e-01 6.75631702e-01 -8.50015640e-01 4.14711237e-01
4.86330569e-01 2.67731428e-01 5.25559448e-02 -3.34140956e-01
-1.26924109e+00 4.06098962e-01 4.86064643e-01 2.17665248e-02
-6.73517346e-01 -6.90426767e-01 -7.65437007e-01 3.66895139e-01
1.55410111e-01 -3.96931231e-01 6.25334501e-01 -5.87933540e-01
-1.62431109e+00 1.65144444e-01 -2.71112114e-01 -3.65621179e-01
3.99477899e-01 -3.52701694e-01 -6.13679945e-01 4.89628643e-01
-2.92328745e-01 4.07762200e-01 8.47626567e-01 -1.09315753e+00
-5.79162419e-01 -1.34978682e-01 -2.56274790e-01 3.91051024e-01
-5.83608568e-01 1.66126378e-02 -1.10971951e+00 -1.15588892e+00
4.31032211e-01 -5.40740669e-01 -2.08198011e-01 3.92955504e-02
7.77686387e-02 5.32826841e-01 8.74645352e-01 -1.06708395e+00
1.72347927e+00 -2.49330091e+00 5.79294153e-02 -4.72833924e-02
6.07567839e-02 5.77432334e-01 -3.09042577e-02 5.25187589e-02
-8.40997174e-02 1.57569200e-01 -3.25732768e-01 -2.49105215e-01
-3.48147959e-01 2.13539332e-01 -2.90183276e-01 4.06972319e-01
-2.59254742e-02 3.67581248e-01 -5.37478328e-01 -5.38828194e-01
2.93445796e-01 1.11545300e+00 -7.36081898e-01 2.43105873e-01
2.92203277e-01 2.84529269e-01 -3.73033851e-01 3.09891254e-01
1.20012009e+00 -1.54251233e-01 1.53087184e-01 -5.99532664e-01
-1.94551334e-01 3.01890790e-01 -1.26046121e+00 1.85485673e+00
-6.73924387e-01 3.86054933e-01 -2.45328192e-02 -8.19426417e-01
1.05076230e+00 3.81241083e-01 4.10932511e-01 -1.06160545e+00
-7.40268901e-02 2.64414489e-01 -1.85064614e-01 -3.46636981e-01
5.17674506e-01 -9.94552579e-03 2.78420568e-01 -3.57186534e-02
-1.13145664e-01 4.80488956e-01 -4.03572768e-02 -1.05036452e-01
7.11821079e-01 1.25993490e-01 2.94829994e-01 2.86134947e-02
8.82422566e-01 -7.74372697e-01 9.52279925e-01 2.31902078e-01
1.59221962e-02 8.79258513e-01 1.82999611e-01 -7.49816746e-02
-1.40223622e+00 -8.81558716e-01 -3.95191371e-01 4.71508354e-01
5.37129164e-01 -6.75516367e-01 -6.19557798e-01 -4.70468923e-02
-5.01156390e-01 6.37584329e-01 1.01117469e-01 -3.49362701e-01
-7.75367975e-01 -9.05625999e-01 3.76713067e-01 4.12663311e-01
1.16031361e+00 -5.98720491e-01 -4.85166907e-01 3.10985357e-01
-4.22200471e-01 -1.30440259e+00 -3.69359791e-01 -2.45486200e-01
-1.10991597e+00 -5.56128919e-01 -9.12644029e-01 -4.39541548e-01
5.09132981e-01 3.91924083e-01 5.49003601e-01 2.40487093e-03
-1.42420560e-01 -1.74142346e-01 -6.07393742e-01 3.13683629e-01
-2.36861274e-01 -2.41556615e-01 -2.31961459e-01 5.08235842e-02
-4.24332321e-02 -8.92845511e-01 -1.00356925e+00 4.27978426e-01
-1.04546976e+00 4.49539125e-01 8.91378403e-01 8.54134679e-01
8.47131491e-01 6.07966006e-01 2.48112887e-01 -2.81733662e-01
2.69926310e-01 -3.61909866e-01 -5.74780107e-01 -3.14419195e-02
-8.07768226e-01 1.27249971e-01 8.29255342e-01 -3.47236663e-01
-1.21064913e+00 -1.82229698e-01 -3.01075161e-01 -6.28570735e-01
3.78750801e-01 4.11448628e-01 -3.62222224e-01 -9.81030539e-02
1.09192804e-01 6.49296820e-01 -2.11544722e-01 -6.52536750e-01
4.51107547e-02 7.18294680e-01 5.08256257e-01 -2.46866986e-01
8.10415208e-01 1.89937383e-01 1.95354789e-01 -7.35837758e-01
-3.55737001e-01 -3.17306459e-01 -1.42118320e-01 9.64453071e-02
7.03259945e-01 -1.46323597e+00 -5.16805887e-01 3.28847677e-01
-1.11125875e+00 1.46066889e-01 4.66127656e-02 9.56001997e-01
-6.86906695e-01 7.82352626e-01 -8.20743024e-01 -7.17405319e-01
-5.53796172e-01 -1.50384283e+00 8.50640357e-01 2.86584169e-01
3.98583651e-01 -3.57832372e-01 -5.32987714e-01 2.06669927e-01
6.41293705e-01 -1.11879997e-01 9.41339672e-01 1.18271314e-01
-8.97227466e-01 7.93818608e-02 -7.04395235e-01 4.98676032e-01
-5.60070015e-02 -3.42662752e-01 -8.38320434e-01 -5.30369878e-01
2.85584778e-01 2.68774834e-02 1.10732841e+00 3.79661292e-01
1.61658907e+00 -5.24396777e-01 -9.47891399e-02 1.15172267e+00
1.71554101e+00 3.17440778e-01 1.33683276e+00 2.17220411e-01
4.64612007e-01 1.21006906e-01 6.70668542e-01 9.37418699e-01
2.27793157e-01 8.92102540e-01 3.54934275e-01 4.38715657e-03
-5.19745469e-01 -2.36987382e-01 4.89814132e-01 1.24433339e+00
-3.46992373e-01 -9.84983146e-02 -4.56839263e-01 1.97333366e-01
-1.60645187e+00 -9.96682823e-01 1.28355846e-02 2.43161464e+00
1.07519984e+00 1.69338331e-01 -4.86672699e-01 4.18287247e-01
8.36324513e-01 4.18312371e-01 -4.20952320e-01 -1.12705834e-01
-1.50761768e-01 1.96844086e-01 7.73246348e-01 3.59010160e-01
-9.92703021e-01 4.20795113e-01 5.39458799e+00 1.44762969e+00
-1.06772602e+00 1.05591692e-01 6.60056531e-01 -1.23706758e-01
-1.86845869e-01 -5.79012558e-03 -8.81143928e-01 6.95728004e-01
1.08765948e+00 -1.63471937e-01 6.72988057e-01 6.48578942e-01
4.18037385e-01 1.03539869e-01 -5.28009236e-01 1.31335938e+00
2.48802453e-03 -1.09495735e+00 1.43871516e-01 2.07852870e-01
4.38634306e-01 -3.61839145e-01 2.33066812e-01 2.29538172e-01
-3.52245480e-01 -9.50925171e-01 5.55482566e-01 5.95970094e-01
1.32366037e+00 -1.00883114e+00 5.87497652e-01 2.42160201e-01
-1.51935446e+00 -3.11972141e-01 -7.90707707e-01 2.93274164e-01
2.58309454e-01 8.38158607e-01 -1.76177859e-01 7.68270731e-01
7.79802918e-01 6.84295952e-01 -2.10198283e-01 1.03889680e+00
-2.03142479e-01 5.13617456e-01 -2.03050375e-01 6.11633480e-01
-4.11476083e-02 -1.99978322e-01 5.66415846e-01 1.34532046e+00
7.34610736e-01 3.96012038e-01 -9.89686996e-02 5.70337474e-01
-5.19555658e-02 7.91896209e-02 7.93186799e-02 2.98978508e-01
3.87290657e-01 1.03499317e+00 -1.64501026e-01 -2.77558386e-01
-5.12024164e-01 1.13485563e+00 -2.36887947e-01 4.27867591e-01
-1.05133057e+00 -5.50499320e-01 4.85924244e-01 1.96818188e-01
7.12794363e-01 -3.87397826e-01 -2.29539752e-01 -1.24141717e+00
2.38151431e-01 -8.58983159e-01 -2.88103484e-02 -8.28518033e-01
-6.28661931e-01 4.23738301e-01 -9.83400196e-02 -1.62466860e+00
-6.39597699e-02 -7.58992583e-02 -4.27086204e-02 1.09355319e+00
-2.16729474e+00 -7.97752678e-01 -5.04407287e-01 3.89083803e-01
7.19854653e-01 -1.91286132e-01 6.87545419e-01 7.35361516e-01
-6.07585132e-01 8.23380947e-01 3.58030736e-01 -7.82573745e-02
6.53206944e-01 -4.98872072e-01 5.15966825e-02 1.03637028e+00
-3.41196924e-01 5.62867761e-01 3.66499394e-01 -5.52631021e-01
-1.53034496e+00 -1.20265901e+00 4.93410468e-01 7.65530646e-01
1.73305020e-01 -1.27388164e-02 -1.16434562e+00 9.02215093e-02
1.26475124e-02 2.97369659e-01 5.49673855e-01 -4.89249945e-01
-4.86279845e-01 -3.85684282e-01 -1.06153584e+00 5.80007195e-01
8.26097012e-01 -5.46604753e-01 -1.49334773e-01 -1.56258553e-01
9.57854927e-01 -4.11969066e-01 -1.07420921e+00 7.53355145e-01
6.14026725e-01 -1.17177391e+00 1.27648330e+00 2.69785851e-01
9.56486940e-01 -5.32519758e-01 -6.12598598e-01 -7.92683840e-01
-6.22829199e-01 -5.36257029e-01 -5.53328454e-01 1.34441829e+00
6.75722118e-03 -2.95183986e-01 3.73799503e-01 2.20898405e-01
-1.64583862e-01 -9.30578053e-01 -9.36429799e-01 -6.04154408e-01
-3.86638910e-01 -2.78343081e-01 5.38448811e-01 5.30650556e-01
-2.51456887e-01 8.71771201e-03 -5.91185391e-01 4.89288419e-01
7.69024134e-01 -7.99920186e-02 3.19264978e-01 -6.57155931e-01
-5.31792223e-01 -3.19016784e-01 -4.40961570e-01 -1.56274450e+00
-3.33263993e-01 -5.96009672e-01 -2.32441410e-01 -1.32445514e+00
3.36181521e-01 -4.59393144e-01 -5.61241448e-01 6.66909814e-02
-2.71723390e-01 2.20277414e-01 1.89462498e-01 5.45260012e-01
-3.55522513e-01 9.36245441e-01 1.39857101e+00 6.45502359e-02
-9.80619416e-02 -2.46797085e-01 -5.86990058e-01 6.73818409e-01
6.27275705e-01 -2.62926698e-01 -4.06645656e-01 -5.63564360e-01
6.46745563e-02 5.73640347e-01 2.07515314e-01 -1.24950898e+00
2.87410915e-01 8.27621296e-02 7.11953282e-01 -5.89271963e-01
5.71304321e-01 -9.24596071e-01 1.36874706e-01 3.84028137e-01
-2.05460235e-01 -2.24378496e-01 2.47022256e-01 7.00772703e-01
-4.48920697e-01 -1.40305087e-01 1.12829840e+00 7.35930726e-02
-5.16583383e-01 3.78549546e-01 -6.66815415e-02 -4.22915280e-01
8.23070288e-01 -3.27864885e-01 -2.86889195e-01 -2.94356078e-01
-1.81967154e-01 -1.01093732e-01 4.52718318e-01 1.40877217e-01
1.09434581e+00 -1.43306375e+00 -8.52451324e-01 4.24487114e-01
-1.95162088e-01 -2.77388282e-02 7.74295986e-01 7.72153795e-01
-6.33800745e-01 2.70320565e-01 -2.05910861e-01 -3.42493296e-01
-1.12752485e+00 5.28300822e-01 -6.51159734e-02 -5.10994017e-01
-8.30649257e-01 4.95343089e-01 3.14924419e-01 5.70706129e-01
1.55979469e-01 9.16472748e-02 -3.20298642e-01 -2.62020677e-01
8.99787962e-01 5.15062928e-01 -1.34561852e-01 -7.65087247e-01
-1.27895221e-01 8.21825504e-01 -1.99577123e-01 1.81402992e-02
1.42141950e+00 -3.98596734e-01 -2.65196171e-02 -4.38656993e-02
1.52488518e+00 1.01987660e-01 -1.35793996e+00 -1.92330793e-01
-6.40972018e-01 -9.13156688e-01 6.34325325e-01 -5.95298886e-01
-1.35186112e+00 1.07142866e+00 9.27634597e-01 -3.11327666e-01
1.87962604e+00 -6.44489110e-01 1.21752155e+00 -2.94673264e-01
2.36938730e-01 -9.77458894e-01 1.40390024e-01 3.19503158e-01
9.84899521e-01 -7.49399602e-01 5.90400875e-01 -5.97203434e-01
-4.71842408e-01 1.30934703e+00 2.73589373e-01 -6.42512590e-02
5.04828274e-01 3.29878718e-01 -4.87561047e-01 3.23372304e-01
-5.69056273e-01 1.42828941e-01 2.33223036e-01 3.09405059e-01
5.17571032e-01 -1.39774829e-01 -7.38883972e-01 6.54736459e-01
1.18793137e-01 8.72887745e-02 5.07321954e-01 5.27132869e-01
-4.91730630e-01 -1.04167140e+00 -3.26377094e-01 1.85304597e-01
-6.69286728e-01 -4.61295426e-01 7.94191241e-01 2.55200803e-01
2.39747360e-01 8.86629999e-01 -2.53481306e-02 -5.57702661e-01
1.99422747e-01 -4.10385638e-01 2.74122119e-01 -8.19240138e-02
-8.51139873e-02 6.49707258e-01 -2.18440726e-01 -5.92334330e-01
-3.36109042e-01 -3.44071716e-01 -1.26838887e+00 -3.01779985e-01
-3.65926862e-01 -1.47834912e-01 8.04642975e-01 4.76072550e-01
5.18373013e-01 8.24079096e-01 1.02196944e+00 -7.00791001e-01
-4.13199961e-01 -7.28778124e-01 -5.46246648e-01 6.51063472e-02
3.06720227e-01 -4.65472847e-01 -3.04983437e-01 1.21915735e-01] | [11.295381546020508, -1.7159520387649536] |
19bfd50d-ceb2-46d1-8413-fbb07eb8a4bb | conversational-semantic-role-labeling | 2104.04947 | null | https://arxiv.org/abs/2104.04947v1 | https://arxiv.org/pdf/2104.04947v1.pdf | Conversational Semantic Role Labeling | Semantic role labeling (SRL) aims to extract the arguments for each predicate in an input sentence. Traditional SRL can fail to analyze dialogues because it only works on every single sentence, while ellipsis and anaphora frequently occur in dialogues. To address this problem, we propose the conversational SRL task, where an argument can be the dialogue participants, a phrase in the dialogue history or the current sentence. As the existing SRL datasets are in the sentence level, we manually annotate semantic roles for 3,000 chit-chat dialogues (27,198 sentences) to boost the research in this direction. Experiments show that while traditional SRL systems (even with the help of coreference resolution or rewriting) perform poorly for analyzing dialogues, modeling dialogue histories and participants greatly helps the performance, indicating that adapting SRL to conversations is very promising for universal dialogue understanding. Our initial study by applying CSRL to two mainstream conversational tasks, dialogue response generation and dialogue context rewriting, also confirms the usefulness of CSRL. | ['Dong Yu', 'Linqi Song', 'Haisong Zhang', 'Linfeng Song', 'Han Wu', 'Kun Xu'] | 2021-04-11 | null | null | null | null | ['dialogue-understanding'] | ['natural-language-processing'] | [ 5.85125208e-01 8.36486697e-01 -1.86430305e-01 -5.80866277e-01
-8.21801901e-01 -9.47718143e-01 1.07849073e+00 3.82420272e-01
-3.39539796e-01 1.16167259e+00 1.12712419e+00 -2.94155031e-01
7.39225447e-02 -4.95379686e-01 3.77426371e-02 -2.11320817e-01
3.38082552e-01 7.63344169e-01 4.37733471e-01 -1.12052870e+00
4.38728184e-01 4.37327921e-02 -1.22020698e+00 8.68409395e-01
5.04782140e-01 2.03563452e-01 1.83036074e-01 8.10486376e-01
-6.37413085e-01 1.47597468e+00 -1.13144541e+00 -2.96765119e-01
-3.04294735e-01 -9.70079303e-01 -1.76171017e+00 -1.20331615e-01
-9.70898867e-02 -1.38417259e-01 -1.21139333e-01 6.77916288e-01
4.98714656e-01 3.65541101e-01 1.48759499e-01 -1.25561965e+00
-6.72744308e-03 1.21615493e+00 1.98730137e-02 3.86832923e-01
1.27164876e+00 -3.16835165e-01 1.48332953e+00 -4.58981067e-01
1.02039289e+00 1.96745551e+00 5.68904459e-01 1.20666647e+00
-1.02159059e+00 -9.61123481e-02 1.11917540e-01 1.51497245e-01
-3.68673295e-01 -7.31150627e-01 7.41497874e-01 -1.37978181e-01
1.25563455e+00 5.79616785e-01 2.43397892e-01 1.27290475e+00
-2.52089262e-01 8.86274159e-01 1.04731536e+00 -7.51567364e-01
-5.51092513e-02 2.96754744e-02 6.83117092e-01 2.07026526e-01
-4.17617947e-01 -6.20152771e-01 -7.49192476e-01 -5.59731960e-01
2.76886851e-01 -7.05932915e-01 -2.64962196e-01 3.74284893e-01
-1.14748287e+00 9.34091687e-01 -2.44393378e-01 6.65994942e-01
5.31335622e-02 -3.81280959e-01 9.26335216e-01 8.79216194e-01
3.26996297e-01 1.01366782e+00 -4.44999218e-01 -6.76289439e-01
-1.22175261e-01 6.87580347e-01 1.64957011e+00 6.46692991e-01
1.90855354e-01 -5.05646288e-01 -4.76939261e-01 1.24436879e+00
-3.48991901e-02 -4.35603186e-02 4.64319646e-01 -1.52649474e+00
6.36354744e-01 1.00156260e+00 4.69626427e-01 -7.05722511e-01
-7.44624257e-01 6.13350451e-01 -6.49485439e-02 -4.12444770e-01
8.18320692e-01 -3.34953606e-01 -3.04402169e-02 1.80733395e+00
4.31907505e-01 -4.80781347e-01 6.94302797e-01 7.80219316e-01
1.31319797e+00 6.29157424e-01 1.63722306e-01 -5.39966226e-01
1.76513553e+00 -9.92343783e-01 -1.07698429e+00 -3.72209668e-01
9.53683496e-01 -9.05862153e-01 1.26532161e+00 -1.01747327e-02
-1.12380302e+00 -1.86034650e-01 -6.67999268e-01 -2.80837357e-01
3.02415192e-02 -2.61110932e-01 5.33849299e-01 2.26359442e-01
-8.80080640e-01 3.77784014e-01 -3.22886765e-01 -5.03027141e-01
-3.65705132e-01 6.53617382e-02 -3.07363987e-01 1.36382416e-01
-1.87982249e+00 1.26978004e+00 1.80784211e-01 -2.59989262e-01
-2.86402076e-01 -3.25317383e-01 -1.02902102e+00 -8.71895626e-02
6.05168283e-01 -3.02810609e-01 1.89600718e+00 -6.52175486e-01
-1.63730633e+00 1.06106675e+00 -4.13612098e-01 -6.86745763e-01
3.11398566e-01 -1.82961568e-01 -1.49758533e-01 2.82601386e-01
3.84611845e-01 3.91385287e-01 2.83492774e-01 -9.35460567e-01
-9.54079032e-01 -2.84215480e-01 7.66011000e-01 7.65956283e-01
1.35983825e-01 7.38458276e-01 8.38709250e-02 -2.06106499e-01
1.20213050e-02 -7.97747612e-01 -1.22009479e-01 -7.49880552e-01
-3.84952903e-01 -1.05068302e+00 7.80533254e-01 -7.24889994e-01
1.18658555e+00 -1.87670219e+00 2.91036278e-01 -3.99120688e-01
1.27789140e-01 1.52266398e-01 -2.02608109e-03 8.52353573e-01
1.45533485e-02 9.24550816e-02 -2.23611161e-01 -3.19840252e-01
1.22285709e-01 5.29566109e-01 -4.41144854e-01 -1.92204621e-02
1.46214098e-01 6.79434180e-01 -1.19472599e+00 -5.07486522e-01
1.47439037e-02 4.58553135e-02 -3.08701873e-01 4.64124054e-01
-5.08944273e-01 7.36567616e-01 -4.82687235e-01 1.25614271e-01
-6.07091412e-02 -1.09756030e-01 6.43785477e-01 3.19726825e-01
-1.66583791e-01 1.44620931e+00 -7.85715580e-01 1.51296997e+00
-4.32278663e-01 7.40216672e-01 5.21128118e-01 -7.70929635e-01
7.83142209e-01 8.38898003e-01 3.26014429e-01 -6.62139595e-01
-2.06296608e-01 7.97136202e-02 4.37871903e-01 -5.58487535e-01
6.04255915e-01 -1.61514506e-01 -6.60452247e-01 1.01383662e+00
-1.53923362e-01 -1.29663810e-01 6.56687140e-01 5.07432580e-01
1.23967600e+00 -1.48144543e-01 5.74495137e-01 -1.46692678e-01
1.03906155e+00 5.78293860e-01 5.99354982e-01 6.90982342e-01
-2.60093182e-01 2.14281648e-01 1.18459511e+00 -3.55478048e-01
-7.48297393e-01 -4.74463820e-01 9.19929072e-02 1.66273952e+00
1.51704997e-01 -6.90187871e-01 -1.11917400e+00 -9.08891797e-01
-2.89424092e-01 9.96026039e-01 -2.07118914e-01 1.43438339e-01
-1.24631727e+00 -5.18862844e-01 8.12606037e-01 1.50813997e-01
4.38050866e-01 -1.62705994e+00 -5.21548688e-01 6.68310106e-01
-7.55321681e-01 -1.40835333e+00 -2.26598218e-01 -1.23232298e-01
-3.15725863e-01 -1.44484127e+00 1.00819863e-01 -6.87325478e-01
1.71035767e-01 1.68906420e-01 1.28807580e+00 2.62181163e-01
3.74360988e-03 4.34697241e-01 -6.67086482e-01 -2.77174860e-01
-1.27078736e+00 1.89889640e-01 -9.86136124e-02 -3.68779868e-01
5.41605949e-01 -3.33072275e-01 -9.63964537e-02 3.06758344e-01
-3.23902309e-01 1.92309078e-02 -3.21247637e-01 9.32596862e-01
-2.86634922e-01 -2.84313470e-01 9.46459472e-01 -1.42856109e+00
1.36836755e+00 -2.87339628e-01 3.73330861e-02 2.77602524e-01
-2.40032747e-01 1.03367113e-01 6.34178102e-01 -8.68716612e-02
-1.59402025e+00 -3.59930754e-01 -4.69656587e-01 7.63399422e-01
-4.03131187e-01 3.07652831e-01 -1.17727332e-01 4.68674809e-01
8.67907405e-01 7.87787780e-04 4.45704818e-01 -5.61287165e-01
1.98680967e-01 7.15224504e-01 4.78820264e-01 -8.18661928e-01
2.21390247e-01 2.05462962e-01 -3.88450116e-01 -9.45778131e-01
-1.24159431e+00 -7.97540009e-01 -5.79188108e-01 -2.18146257e-02
7.29044735e-01 -6.70593619e-01 -9.79982197e-01 1.02157168e-01
-1.59268391e+00 -3.75592828e-01 -3.50619376e-01 8.41726214e-02
-5.37549794e-01 6.12172306e-01 -1.01831615e+00 -1.00314975e+00
-4.53180671e-01 -8.38908732e-01 8.90268385e-01 1.27727166e-01
-1.20048118e+00 -1.16113412e+00 3.14338803e-02 8.14573586e-01
2.53356129e-01 8.36088806e-02 1.12347829e+00 -1.32998264e+00
1.61420375e-01 9.63964835e-02 -1.35499910e-02 1.07944436e-01
3.14253539e-01 -4.58845168e-01 -7.98542559e-01 5.93471453e-02
4.18376654e-01 -6.65707827e-01 3.91175747e-01 -2.93558240e-01
3.15399498e-01 -7.32687473e-01 -8.69243592e-02 -4.65945095e-01
5.32271087e-01 4.54304278e-01 4.71008986e-01 3.83767188e-01
4.00925487e-01 1.40667021e+00 9.79033470e-01 3.73311728e-01
7.16985047e-01 7.45208859e-01 -6.26225024e-03 1.35988817e-01
-1.83849946e-01 -1.95874900e-01 5.84684074e-01 7.08993673e-01
7.74557590e-02 -1.42231762e-01 -9.18595970e-01 3.07587981e-01
-2.16777515e+00 -1.10833752e+00 -5.16736090e-01 1.55248272e+00
1.43279254e+00 2.06559241e-01 2.05332294e-01 2.22834826e-01
7.98967481e-01 4.56208587e-01 -8.97942111e-02 -6.71351135e-01
-2.03934729e-01 -1.58139747e-02 -2.47324660e-01 1.12487972e+00
-8.39798391e-01 1.16619158e+00 6.24453068e+00 3.94379467e-01
-6.29275560e-01 2.20734656e-01 2.25422293e-01 2.79533088e-01
-2.28524521e-01 2.35479742e-01 -1.12908721e+00 2.64612079e-01
9.36483324e-01 -3.07138979e-01 4.71898764e-01 6.49791598e-01
4.12749767e-01 -2.12215453e-01 -1.27513695e+00 5.41253090e-01
8.86737257e-02 -1.30842519e+00 -1.29705235e-01 -4.89778876e-01
1.65310413e-01 -3.84622276e-01 -8.16667676e-01 5.43794453e-01
5.04211009e-01 -9.79567170e-01 2.91364163e-01 -3.25696617e-02
2.08888084e-01 -4.10047889e-01 8.34764302e-01 7.06300855e-01
-7.99458086e-01 -3.66890393e-02 -7.97554031e-02 -4.89173293e-01
4.12305683e-01 -2.32229471e-01 -1.46600282e+00 2.70838261e-01
2.96585023e-01 5.50960779e-01 -3.51236612e-01 9.02911574e-02
-6.43485248e-01 7.22447574e-01 -1.41640812e-01 -2.13283107e-01
2.37086162e-01 -1.13620304e-01 1.05811417e+00 1.34120464e+00
-5.15135467e-01 4.53917861e-01 4.73555297e-01 4.32295084e-01
6.04575034e-04 8.62256214e-02 -5.41449845e-01 -8.91696736e-02
7.50840485e-01 1.14274108e+00 -5.97958326e-01 -2.42852569e-01
-2.04721183e-01 8.27455819e-01 7.45029077e-02 1.25302123e-02
-2.85971969e-01 -3.37477624e-01 6.98183060e-01 1.31088898e-01
-5.23234189e-01 3.75964940e-02 -1.80510968e-01 -8.63733292e-01
-7.00624809e-02 -1.36156166e+00 7.45508373e-01 -5.28350770e-01
-1.19106805e+00 5.63730061e-01 1.04197405e-01 -6.30332351e-01
-8.82166088e-01 -4.88464236e-01 -7.33631551e-01 7.33380616e-01
-1.27763009e+00 -9.11014795e-01 3.65780257e-02 3.77817601e-01
1.24691296e+00 -7.49942064e-02 1.13466942e+00 -1.27017900e-01
-2.74919838e-01 1.77358970e-01 -6.17593586e-01 3.48567992e-01
9.09726441e-01 -1.46092296e+00 5.15664220e-01 2.96329796e-01
-2.20969468e-01 7.50935555e-01 1.02103400e+00 -4.77923900e-01
-1.08561981e+00 -3.40628266e-01 1.68932223e+00 -8.43349874e-01
8.62983406e-01 -4.40883249e-01 -1.22985661e+00 4.51393425e-01
5.76171637e-01 -7.88967311e-01 7.07736075e-01 3.69473487e-01
-8.43712762e-02 4.28761870e-01 -1.07130849e+00 6.83461070e-01
1.17271769e+00 -7.69697487e-01 -1.58093989e+00 6.12459064e-01
1.06784666e+00 -8.04382741e-01 -7.14290917e-01 2.30569765e-01
7.52199739e-02 -7.59060383e-01 8.02935600e-01 -9.88852084e-01
4.88853663e-01 -6.35142550e-02 1.04234695e-01 -1.13002419e+00
2.83064812e-01 -1.12780452e+00 -3.95771191e-02 1.48280406e+00
5.41500390e-01 -4.51430172e-01 4.70745534e-01 1.09073853e+00
-1.99053004e-01 -2.14184985e-01 -9.70244944e-01 -2.61304408e-01
-1.25643939e-01 -1.91069216e-01 4.77570444e-01 1.16311955e+00
8.25155914e-01 1.45258439e+00 -1.81546897e-01 -4.52447265e-01
1.97409973e-01 2.04659015e-01 7.65256882e-01 -1.55554783e+00
-2.04917669e-01 -3.75182509e-01 3.22526395e-01 -9.65589702e-01
7.23399341e-01 -7.03069806e-01 2.34287411e-01 -1.72423697e+00
-6.72842190e-02 -3.54416072e-01 5.40722013e-01 6.45203650e-01
-3.40143234e-01 -4.16086495e-01 1.18541054e-01 2.27525577e-01
-8.27078521e-01 3.24410290e-01 1.23760998e+00 3.89925241e-02
-4.99281883e-01 2.61750937e-01 -8.54409635e-01 9.41237152e-01
7.20335662e-01 -4.18941796e-01 -4.65856701e-01 2.83712745e-02
1.41463101e-01 6.23000860e-01 -6.18480407e-02 -1.67429119e-01
3.99583459e-01 -2.27002457e-01 -5.25847912e-01 -1.54666975e-01
4.46073651e-01 -3.06910753e-01 -3.91599089e-01 2.83208489e-01
-9.70124185e-01 -8.46209750e-02 -4.81903218e-02 3.53859752e-01
-4.24384922e-01 -6.99008644e-01 4.33227718e-01 -4.94180977e-01
-7.29480445e-01 -6.39740586e-01 -8.04555595e-01 6.44362390e-01
6.43689156e-01 -1.29180342e-01 -5.72379291e-01 -7.33351648e-01
-8.89538407e-01 6.26424611e-01 2.76867092e-01 6.03011012e-01
3.75507385e-01 -7.35937953e-01 -8.54726613e-01 -1.90491050e-01
-8.09380487e-02 1.24675795e-01 -2.88218856e-02 5.48922896e-01
-2.55147308e-01 4.90797728e-01 -1.22101288e-02 -2.87057370e-01
-1.79147482e+00 -9.01733860e-02 1.66115031e-01 -6.13470912e-01
-7.02088714e-01 6.84480786e-01 -1.56588525e-01 -7.45321810e-01
3.30811769e-01 1.57620490e-01 -9.96643186e-01 5.04789650e-01
7.55810916e-01 2.47306019e-01 -1.04336567e-01 -7.13462472e-01
-3.44669789e-01 -1.81263074e-01 -2.65699387e-01 -5.04305959e-01
1.18958867e+00 -4.91988450e-01 -7.26435423e-01 7.32441425e-01
7.15729654e-01 1.45183563e-01 -9.02522981e-01 -4.29238379e-01
8.29555690e-01 -1.21251300e-01 -6.80996835e-01 -6.38955057e-01
1.29849419e-01 5.00104189e-01 -4.95755523e-01 9.29040015e-01
4.37908649e-01 2.56368905e-01 8.81435096e-01 6.67833447e-01
4.74764347e-01 -1.31680429e+00 1.86398208e-01 1.41085100e+00
1.16030812e+00 -1.20091951e+00 -2.38256216e-01 -7.44394481e-01
-1.17924690e+00 1.19930232e+00 8.18459749e-01 2.81803429e-01
7.22949803e-02 1.96487069e-01 2.67954856e-01 -3.52965921e-01
-1.14285219e+00 -9.15312991e-02 -1.97427183e-01 2.83604920e-01
9.47513878e-01 -1.53823420e-01 -7.94720590e-01 6.34433925e-01
-5.31814814e-01 -6.42841876e-01 9.51214731e-01 1.13440216e+00
-4.28168476e-01 -1.58671975e+00 -2.97024608e-01 1.48945272e-01
-7.34559298e-01 -8.52983538e-03 -1.34060955e+00 7.49250114e-01
-5.78444004e-01 1.45539975e+00 1.00141779e-01 -2.78827436e-02
5.76115549e-01 5.43171704e-01 2.57519394e-01 -1.36459470e+00
-1.19355488e+00 -3.33625853e-01 1.30483806e+00 -4.37313378e-01
-7.60315239e-01 -6.88447833e-01 -1.79742026e+00 -2.37435684e-01
-3.85142118e-02 8.54740977e-01 3.10067087e-01 1.23707128e+00
3.11579742e-03 2.50217468e-01 6.04854047e-01 -2.61600763e-01
-8.12194943e-01 -1.18113327e+00 -7.10484609e-02 7.47673035e-01
3.20555985e-01 -4.51927453e-01 -4.77619708e-01 -5.86568639e-02] | [12.515206336975098, 8.091487884521484] |
6f6f2528-4105-4b0e-a78b-87992f41f273 | generalized-deep-3d-shape-prior-via-part | null | null | http://openaccess.thecvf.com//content/CVPR2023/html/Li_Generalized_Deep_3D_Shape_Prior_via_Part-Discretized_Diffusion_Process_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Li_Generalized_Deep_3D_Shape_Prior_via_Part-Discretized_Diffusion_Process_CVPR_2023_paper.pdf | Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process | We develop a generalized 3D shape generation prior model, tailored for multiple 3D tasks including unconditional shape generation, point cloud completion, and cross-modality shape generation, etc. On one hand, to precisely capture local fine detailed shape information, a vector quantized variational autoencoder (VQ-VAE) is utilized to index local geometry from a compactly learned codebook based on a broad set of task training data. On the other hand, a discrete diffusion generator is introduced to model the inherent structural dependencies among different tokens. In the meantime, a multi-frequency fusion module (MFM) is developed to suppress high-frequency shape feature fluctuations, guided by multi-frequency contextual information. The above designs jointly equip our proposed 3D shape prior model with high-fidelity, diverse features as well as the capability of cross-modality alignment, and extensive experiments have demonstrated superior performances on various 3D shape generation tasks. | ['Fuzhen Wang', 'Yutian Liu', 'Yilin Sun', 'Bingbing Ni', 'Xuanhong Chen', 'Yishun Dou', 'Yuhan Li'] | 2023-01-01 | null | null | null | cvpr-2023-1 | ['point-cloud-completion', '3d-shape-generation'] | ['computer-vision', 'computer-vision'] | [-1.25313312e-01 -2.43634842e-02 2.27856353e-01 -1.63396716e-01
-1.05612135e+00 -4.79800820e-01 8.63620043e-01 2.12063938e-02
3.14942986e-01 3.71546179e-01 3.32730561e-01 2.03118458e-01
-1.71557292e-01 -9.56009388e-01 -6.16770446e-01 -8.83459628e-01
4.11568433e-01 5.08649170e-01 -1.27644718e-01 -2.87522316e-01
2.03540027e-01 7.35408962e-01 -1.29822409e+00 -7.50026898e-03
1.02925682e+00 9.41270709e-01 5.45930326e-01 2.03601390e-01
-2.67373055e-01 4.71245758e-02 -2.15568498e-01 -2.09862411e-01
-1.25413248e-02 1.55039271e-02 -2.54228711e-01 3.88147414e-01
1.42024636e-01 -1.59215540e-01 -3.88110220e-01 8.89224291e-01
7.46139705e-01 2.40731150e-01 1.23880088e+00 -8.56928110e-01
-1.05683720e+00 3.70566100e-02 -6.01945758e-01 -3.69503647e-01
3.33543479e-01 3.08975399e-01 1.04921710e+00 -1.32056522e+00
7.42292643e-01 1.30638230e+00 4.28602487e-01 4.13405478e-01
-1.31276011e+00 -3.63449842e-01 1.21021353e-01 -3.43159229e-01
-1.44741893e+00 -1.55001327e-01 1.53236699e+00 -4.95975465e-01
8.62876832e-01 -8.20546993e-04 6.28903210e-01 1.24040103e+00
2.25634933e-01 8.39394271e-01 6.11410558e-01 -1.18956484e-01
1.17183112e-01 -1.45537347e-01 -6.88375473e-01 5.90486944e-01
-1.07831225e-01 1.33441374e-01 -2.95999914e-01 -4.64527100e-01
1.32329857e+00 -1.42132286e-02 -3.16345572e-01 -5.89541733e-01
-1.28990448e+00 8.04016352e-01 4.70901310e-01 5.38484514e-01
-6.17482722e-01 -1.06783509e-01 9.99997258e-02 -1.55626222e-01
6.02917790e-01 1.25505134e-01 -2.74525315e-01 1.25848651e-01
-6.77665293e-01 4.36780959e-01 3.66719306e-01 1.18468130e+00
9.41611171e-01 5.19332945e-01 -5.33016384e-01 1.02797186e+00
7.60792494e-01 9.59639370e-01 2.69529045e-01 -7.96058655e-01
5.54620206e-01 5.32453775e-01 -1.11628165e-02 -1.16952384e+00
-1.66131090e-03 -5.03818333e-01 -1.40844452e+00 3.25905830e-02
-3.15875024e-01 1.16320044e-01 -9.82614160e-01 1.79463673e+00
6.03463352e-01 2.57181764e-01 -5.31482287e-02 9.25570071e-01
9.55778539e-01 7.30508029e-01 -1.15089640e-01 -1.72087550e-01
9.91917253e-01 -2.28411391e-01 -4.20690298e-01 3.68672103e-01
-3.27861169e-03 -8.55935872e-01 7.99151003e-01 -6.82660714e-02
-1.07850206e+00 -8.95925879e-01 -9.68002379e-01 -5.86127304e-02
-2.40621846e-02 1.27812669e-01 4.76916850e-01 3.12502161e-02
-7.94092417e-01 4.11912084e-01 -8.96100104e-01 7.00355992e-02
5.70020080e-01 7.95386359e-02 -2.48186693e-01 -8.38225484e-02
-9.73347187e-01 3.25925082e-01 1.24794640e-01 -4.32669464e-03
-8.28237653e-01 -7.28649676e-01 -1.06200111e+00 -9.71948057e-02
-1.54648304e-01 -1.26777852e+00 7.18933165e-01 -2.04974487e-01
-1.65360641e+00 6.59147382e-01 -2.02064469e-01 2.34436050e-01
2.28767440e-01 2.07608759e-01 -1.95901975e-01 1.30607486e-01
2.40829140e-01 7.18862951e-01 1.23488069e+00 -1.59415269e+00
-6.49644881e-02 -3.95929635e-01 -2.91256934e-01 5.95603049e-01
2.80201230e-02 -7.21822917e-01 -4.94297028e-01 -1.13699412e+00
4.51669335e-01 -7.40287840e-01 -2.32265592e-01 -2.60531366e-01
-3.90863001e-01 -4.69852328e-01 8.39232922e-01 -4.87286448e-01
8.29553425e-01 -2.23599267e+00 4.17238265e-01 4.59206462e-01
1.99782178e-01 -1.29946411e-01 -3.45077962e-01 5.06079495e-01
9.35869291e-02 6.22504689e-02 -6.09051228e-01 -5.62798262e-01
1.90326199e-01 2.84642041e-01 -4.10097808e-01 2.02424839e-01
5.81020057e-01 1.14453411e+00 -8.49582791e-01 -3.91621590e-01
4.80849385e-01 8.07457030e-01 -6.43269837e-01 2.97534764e-01
-3.50680411e-01 8.98555458e-01 -9.74789798e-01 6.73840284e-01
9.49108481e-01 -4.06150401e-01 -3.69734496e-01 -5.02625108e-01
4.57805209e-02 -2.63301760e-01 -1.17569244e+00 2.37087870e+00
-4.83773500e-01 -1.88959956e-01 1.40194818e-01 -8.94322693e-01
1.22832847e+00 5.76263428e-01 9.19119239e-01 -5.89837670e-01
-4.87777730e-03 2.91269332e-01 -5.24756789e-01 -2.20527157e-01
5.04776597e-01 -1.27226040e-01 -4.34145369e-02 3.94355148e-01
2.75589526e-01 -7.23744452e-01 -3.66523862e-01 1.41185850e-01
6.07940495e-01 5.07061481e-01 -4.04623076e-02 -1.35680452e-01
7.35410929e-01 -3.33335429e-01 5.27126431e-01 4.60217297e-01
1.78440467e-01 1.15230024e+00 -2.27099136e-01 -9.00724679e-02
-1.34749746e+00 -1.31763077e+00 -1.98123395e-01 3.74570787e-01
3.43367219e-01 -1.77736387e-01 -4.49163347e-01 -4.13159430e-01
1.59157738e-01 5.75564384e-01 -4.51661229e-01 -2.39475086e-01
-5.19926906e-01 -5.87411225e-01 1.45420834e-01 3.68935376e-01
3.35933745e-01 -1.01709867e+00 2.22496223e-02 4.58018422e-01
-1.19886093e-01 -1.01595795e+00 -7.45264530e-01 -4.07920659e-01
-8.82631540e-01 -8.32990646e-01 -1.04967952e+00 -8.47903252e-01
6.50050044e-01 2.85476714e-01 1.05013371e+00 -8.67747366e-02
-1.19997598e-01 6.59891427e-01 -3.64126176e-01 -1.03940822e-01
-4.08392549e-01 1.13787213e-02 6.38354719e-02 3.12748164e-01
-1.47043273e-01 -1.23744106e+00 -5.40614426e-01 -1.79695692e-02
-1.01772952e+00 1.56974912e-01 8.26413870e-01 1.12100446e+00
1.19856215e+00 -1.02508359e-01 6.41901553e-01 -1.88566431e-01
6.13639772e-01 -4.67912704e-01 -3.54807526e-01 2.10566014e-01
-1.58901483e-01 2.56295741e-01 5.76254427e-01 -3.95218134e-01
-1.33857894e+00 1.81160402e-02 -5.21544814e-01 -1.03528678e+00
-3.75153989e-01 3.30006272e-01 -5.84163189e-01 1.12921797e-01
3.88375938e-01 7.90410876e-01 6.61619008e-02 -6.60369992e-01
6.18592083e-01 4.33785141e-01 5.13701975e-01 -9.40599024e-01
1.08573008e+00 4.87746537e-01 1.36883333e-01 -9.68816936e-01
-4.16074187e-01 -1.59336239e-01 -7.28280485e-01 5.67180812e-02
9.35444176e-01 -1.02626967e+00 -4.23194855e-01 5.78297496e-01
-1.26520514e+00 -5.68475947e-02 -3.74064207e-01 4.42503899e-01
-8.48816276e-01 4.26679879e-01 -3.67373556e-01 -6.86134160e-01
-7.30724037e-01 -1.05743015e+00 1.73059559e+00 2.30504707e-01
2.71515936e-01 -9.71435189e-01 8.10425803e-02 1.82964176e-01
2.02033013e-01 6.12940907e-01 9.37245131e-01 -5.56510501e-02
-8.36139500e-01 3.13760862e-02 -1.98398545e-01 3.09456199e-01
4.87679958e-01 -1.15224563e-01 -7.50882685e-01 -3.03401947e-01
1.02692777e-02 -1.49977237e-01 5.91133714e-01 5.48787475e-01
1.07935405e+00 5.55502661e-02 -3.23152244e-01 5.68794668e-01
1.37358797e+00 -7.46877044e-02 2.37558156e-01 -5.07550955e-01
1.13014495e+00 1.57758132e-01 3.17103326e-01 6.74134016e-01
5.10908663e-01 6.48120403e-01 2.88929343e-01 1.47554606e-01
-2.18652666e-01 -6.12073898e-01 -7.02846721e-02 1.26357782e+00
-1.08674102e-01 -1.03990287e-01 -5.98218858e-01 4.58390772e-01
-1.64446664e+00 -7.74546444e-01 8.35190862e-02 2.04424238e+00
5.83070874e-01 -5.17949946e-02 -2.19135270e-01 -1.55115709e-01
6.59537494e-01 3.55891973e-01 -6.05184495e-01 2.96574324e-01
-3.43374878e-01 8.75406340e-02 -1.46545991e-01 3.99421513e-01
-8.71736288e-01 8.04667652e-01 5.16126394e+00 1.34195423e+00
-1.02952194e+00 -2.58857775e-02 3.18599403e-01 2.90602803e-01
-1.07864952e+00 -1.86581254e-01 -3.88646245e-01 5.38216174e-01
-1.21749798e-03 -1.59240276e-01 2.91108817e-01 6.42949700e-01
1.81016922e-01 4.10704076e-01 -5.95010161e-01 1.29884088e+00
-5.57821244e-02 -1.39374399e+00 4.44554269e-01 2.19161868e-01
1.05622482e+00 1.06859989e-01 1.14785321e-01 1.16895258e-01
2.57034987e-01 -7.07343340e-01 7.77917862e-01 1.07166576e+00
1.12554550e+00 -9.47962523e-01 3.11539888e-01 4.41223711e-01
-1.58777106e+00 3.39302301e-01 -3.89652550e-01 5.32050073e-01
4.65920359e-01 9.18111801e-01 -3.94139946e-01 1.32351482e+00
3.14985216e-01 1.01330388e+00 -9.27145481e-02 8.26104283e-01
-7.06792176e-02 2.00156257e-01 -4.68944013e-01 2.65196949e-01
1.60600483e-01 -4.48500037e-01 1.02029014e+00 6.27171695e-01
6.69806778e-01 3.90089869e-01 2.56917059e-01 1.27431345e+00
9.73344892e-02 9.25896168e-02 -6.81587398e-01 1.27954200e-01
5.91839135e-01 1.29879582e+00 -4.36809897e-01 -2.75293976e-01
-3.25993180e-01 9.02708054e-01 1.19260788e-01 4.85812187e-01
-5.32335579e-01 -5.61123937e-02 6.47697449e-01 -1.88613847e-01
5.05325139e-01 -5.93820572e-01 -3.10272962e-01 -1.45775461e+00
1.42617598e-01 -4.23089296e-01 -9.04830992e-02 -9.73962367e-01
-1.69667137e+00 3.88741761e-01 -1.28604457e-01 -1.64694548e+00
-2.54733294e-01 -1.76533446e-01 -7.46527731e-01 1.20692778e+00
-1.37903571e+00 -1.59416902e+00 -2.29883179e-01 7.56248713e-01
3.56198192e-01 -3.11280489e-01 8.50396335e-01 1.64660692e-01
-1.95519567e-01 3.50904763e-01 8.48575383e-02 1.17367938e-01
3.59661549e-01 -1.17724252e+00 5.20151615e-01 4.32410359e-01
2.86038786e-01 5.04600465e-01 1.64283708e-01 -9.15113211e-01
-1.49599159e+00 -1.25438666e+00 3.54964137e-01 -3.67515922e-01
1.02567919e-01 -2.28619859e-01 -1.02799892e+00 1.11353293e-01
-1.75581515e-01 7.79678524e-02 3.62666309e-01 -3.13981056e-01
-8.24858472e-02 1.45217687e-01 -9.30073798e-01 3.97242665e-01
1.27566040e+00 -8.20838511e-01 -6.86967134e-01 1.61938742e-01
7.39799261e-01 -7.02288091e-01 -1.34936798e+00 7.58926749e-01
2.89083958e-01 -6.97831690e-01 1.19452834e+00 -1.50170580e-01
4.67265248e-01 -3.98658872e-01 -3.72989535e-01 -1.43259001e+00
-5.98940551e-01 -6.37737811e-01 -3.51280838e-01 1.43492115e+00
-2.44763903e-02 -2.42859468e-01 7.68746018e-01 2.41287559e-01
-5.14057279e-01 -9.89693344e-01 -8.90405655e-01 -5.38250089e-01
1.48799986e-01 -4.73336339e-01 1.12790453e+00 8.96136880e-01
-6.89297557e-01 4.60223615e-01 -3.20639700e-01 3.15046132e-01
8.20616841e-01 6.70850992e-01 6.52389050e-01 -1.30111885e+00
-2.95282334e-01 -5.68380475e-01 -2.41591737e-01 -1.47195554e+00
2.16186404e-01 -1.10509682e+00 -1.68675214e-01 -1.64165461e+00
-1.41925648e-01 -6.23878241e-01 -1.84294775e-01 1.13815412e-01
-2.67782658e-01 6.48065507e-02 9.74459499e-02 2.38605618e-01
-1.71233356e-01 1.55989909e+00 1.93076491e+00 -2.54261345e-01
-3.19280893e-01 2.50506382e-02 -6.26826108e-01 4.01970655e-01
2.95249254e-01 -1.51747912e-01 -6.09462678e-01 -6.11526847e-01
-1.49962381e-01 3.91426295e-01 5.20989299e-01 -7.87363708e-01
1.09135307e-01 -3.91801089e-01 5.77544034e-01 -1.02452612e+00
5.27014434e-01 -7.01745391e-01 2.09292591e-01 -2.24386111e-01
1.96753129e-01 -3.22621912e-01 1.73707642e-02 8.86550486e-01
-2.90785342e-01 3.28016669e-01 5.91451347e-01 -1.58186823e-01
-5.12000442e-01 1.09550834e+00 2.28958994e-01 4.77320403e-02
6.16145790e-01 -2.21540272e-01 3.86600614e-01 -1.87450692e-01
-8.78818452e-01 8.96900967e-02 5.74662924e-01 5.91668844e-01
9.02458012e-01 -2.12647986e+00 -8.21879387e-01 7.46378422e-01
3.41285348e-01 6.88943684e-01 9.43597138e-01 4.67101544e-01
4.33005765e-03 2.12213501e-01 -3.65384668e-02 -9.39959288e-01
-4.88365263e-01 3.20107281e-01 2.95765340e-01 -1.16647497e-01
-8.26310992e-01 7.89394915e-01 3.23304653e-01 -6.98409200e-01
-3.01854014e-01 -1.82881877e-01 -1.36652201e-01 -5.28532602e-02
1.76436454e-01 -1.08196117e-01 7.80126154e-02 -9.91599143e-01
-1.40056908e-01 1.11006975e+00 3.95320863e-01 -1.67503685e-01
1.48371577e+00 -2.58633316e-01 1.56896308e-01 2.19062552e-01
1.25339699e+00 1.18037336e-01 -1.73876095e+00 -5.07061362e-01
-4.82012033e-01 -2.89794028e-01 1.57748699e-01 -3.15689653e-01
-1.05459082e+00 7.10553885e-01 2.04909369e-01 -4.74063195e-02
9.87743258e-01 1.43711185e-02 9.12770450e-01 8.74043792e-04
5.41494310e-01 -9.06987369e-01 1.81137174e-01 6.32529974e-01
1.29288864e+00 -1.09417582e+00 -9.93798375e-02 -3.53659838e-01
-6.15822434e-01 9.39406991e-01 4.32086825e-01 -3.31565946e-01
9.26049590e-01 -7.98625350e-02 -2.69439250e-01 -2.41347402e-01
-5.26102066e-01 -1.71062574e-01 6.40978515e-01 8.43728125e-01
-6.24172576e-02 7.56481737e-02 1.71362728e-01 7.58399785e-01
-1.13077387e-01 -2.49809444e-01 -2.07571089e-02 5.98655224e-01
-4.13592309e-02 -1.21098971e+00 -2.38000438e-01 3.25042814e-01
1.52551174e-01 5.77654466e-02 1.00681633e-02 4.52600509e-01
2.43573591e-01 4.34160054e-01 1.45676821e-01 -5.02212882e-01
3.71960133e-01 -1.31011784e-01 5.32800376e-01 -4.87412810e-01
-1.80605296e-02 5.51585376e-01 -5.25336504e-01 -3.92728567e-01
-4.12509710e-01 -7.43030488e-01 -1.14083731e+00 8.34767055e-03
-6.98665008e-02 7.71409972e-03 4.00277734e-01 8.95903885e-01
7.85268784e-01 3.93116772e-01 9.71530080e-01 -1.36307776e+00
-4.98412669e-01 -9.50000405e-01 -7.25727618e-01 6.99257374e-01
2.32141167e-01 -9.18032467e-01 -5.71141392e-02 -3.49235982e-02] | [8.776833534240723, -3.650559186935425] |
27c2774a-f5f6-4092-91a3-c3e4ff3f9c94 | towards-domain-generalization-for-ecg-and-eeg | 2303.11338 | null | https://arxiv.org/abs/2303.11338v3 | https://arxiv.org/pdf/2303.11338v3.pdf | Towards Domain Generalization for ECG and EEG Classification: Algorithms and Benchmarks | Despite their immense success in numerous fields, machine and deep learning systems have not yet been able to firmly establish themselves in mission-critical applications in healthcare. One of the main reasons lies in the fact that when models are presented with previously unseen, Out-of-Distribution samples, their performance deteriorates significantly. This is known as the Domain Generalization (DG) problem. Our objective in this work is to propose a benchmark for evaluating DG algorithms, in addition to introducing a novel architecture for tackling DG in biosignal classification. In this paper, we describe the Domain Generalization problem for biosignals, focusing on electrocardiograms (ECG) and electroencephalograms (EEG) and propose and implement an open-source biosignal DG evaluation benchmark. Furthermore, we adapt state-of-the-art DG algorithms from computer vision to the problem of 1D biosignal classification and evaluate their effectiveness. Finally, we also introduce a novel neural network architecture that leverages multi-layer representations for improved model generalizability. By implementing the above DG setup we are able to experimentally demonstrate the presence of the DG problem in ECG and EEG datasets. In addition, our proposed model demonstrates improved effectiveness compared to the baseline algorithms, exceeding the state-of-the-art in both datasets. Recognizing the significance of the distribution shift present in biosignal datasets, the presented benchmark aims at urging further research into the field of biomedical DG by simplifying the evaluation process of proposed algorithms. To our knowledge, this is the first attempt at developing an open-source framework for evaluating ECG and EEG DG algorithms. | ['Christos Diou', 'Aristotelis Ballas'] | 2023-03-20 | null | null | null | null | ['electrocardiography-ecg', 'eeg', 'eeg'] | ['methodology', 'methodology', 'time-series'] | [ 4.63860542e-01 1.64992698e-02 3.10113817e-01 -3.31189305e-01
-5.43257654e-01 -3.20768207e-01 4.49765205e-01 3.71791214e-01
-4.24931407e-01 8.93005013e-01 -1.28062889e-01 -1.53071627e-01
-5.82478166e-01 -3.65686208e-01 -6.66417301e-01 -7.52164245e-01
-5.60455322e-01 4.22654539e-01 -1.69560194e-01 -1.55796170e-01
1.28307521e-01 7.45428264e-01 -1.45388997e+00 3.17423165e-01
7.56043792e-01 1.21489429e+00 -1.57188967e-01 4.62775290e-01
5.35303593e-01 2.11820185e-01 -9.58979249e-01 -6.79548830e-02
1.31856591e-01 -6.34007037e-01 -7.05096185e-01 -2.93412179e-01
4.00544256e-01 -1.52454570e-01 -6.33281395e-02 8.61796439e-01
1.10709608e+00 -1.96051877e-02 9.41091955e-01 -1.23924053e+00
-4.53665674e-01 3.55538726e-01 -2.20615521e-01 5.39049089e-01
2.91824937e-01 -3.51953134e-02 6.57148063e-01 -5.15984774e-01
4.62697148e-01 8.02692175e-01 9.25056040e-01 6.36563718e-01
-1.39948428e+00 -6.69439614e-01 1.19580999e-02 4.15471256e-01
-1.38911688e+00 -2.34600738e-01 9.08550918e-01 -6.15004957e-01
1.11871946e+00 2.16471538e-01 5.72877407e-01 1.74640477e+00
3.77577752e-01 5.70076823e-01 1.27791357e+00 -3.01220566e-01
5.17858684e-01 7.33373985e-02 2.87518144e-01 8.44632834e-02
4.69363332e-01 1.58863798e-01 -4.22762662e-01 -7.39738196e-02
3.55053544e-01 -1.59655795e-01 -5.68121493e-01 -4.49551970e-01
-1.19274020e+00 3.56790572e-01 3.59082848e-01 7.70732045e-01
-6.63562298e-01 1.37683585e-01 6.79253101e-01 3.59596670e-01
4.76442367e-01 5.79103231e-01 -4.32753891e-01 -2.93997556e-01
-1.20534551e+00 3.07480514e-01 7.72815824e-01 5.37192345e-01
2.36994475e-01 1.09074794e-01 -1.28584087e-01 8.11275661e-01
-7.53572732e-02 1.95200339e-01 9.19743717e-01 -3.94839883e-01
2.77705818e-01 4.33625311e-01 -1.16265282e-01 -9.82698917e-01
-9.28516328e-01 -1.09271538e+00 -1.11110497e+00 9.73507985e-02
2.31833816e-01 -1.73903495e-01 -7.14226127e-01 1.66619384e+00
-5.24342693e-02 3.83744627e-01 2.17546359e-01 8.36887419e-01
7.59932160e-01 1.54216781e-01 -7.53331408e-02 -1.90337464e-01
1.11921751e+00 -2.07121521e-01 -6.19796395e-01 7.15388916e-03
4.81775165e-01 -1.90302536e-01 8.23850334e-01 9.48214710e-01
-8.31997573e-01 -6.89568281e-01 -1.46710885e+00 3.96531105e-01
-4.04922068e-01 7.28217885e-02 3.50945413e-01 8.43670130e-01
-1.05504966e+00 9.22868371e-01 -8.37268114e-01 -6.81915104e-01
4.72169667e-01 5.52114129e-01 -4.07300949e-01 2.81589359e-01
-1.31663501e+00 1.03715801e+00 4.00903821e-01 1.61425278e-01
-1.03222775e+00 -8.12330961e-01 -4.71391469e-01 -1.16157696e-01
-9.64686796e-02 -5.49121559e-01 8.31922472e-01 -9.11843956e-01
-1.17351818e+00 9.52845693e-01 4.01878893e-01 -8.96238506e-01
7.55142629e-01 -1.41011834e-01 -8.48454058e-01 1.43670693e-01
-1.50885180e-01 3.71449560e-01 8.53705466e-01 -1.16460407e+00
-2.90595472e-01 -5.93262553e-01 -9.51906517e-02 -3.15072566e-01
-4.44049597e-01 -4.88965750e-01 2.54808694e-01 -7.61601388e-01
3.47977914e-02 -7.62229681e-01 1.35765150e-01 -4.82516289e-01
-3.04860801e-01 -3.19478922e-02 4.33385462e-01 -5.22640169e-01
1.26608443e+00 -2.34845567e+00 2.43156284e-01 1.58801705e-01
2.42490277e-01 1.39769837e-01 -2.02948712e-02 5.14521360e-01
-6.13900900e-01 -1.51527911e-01 -4.23235804e-01 -1.29705429e-01
2.44297106e-02 1.39168739e-01 -3.78287166e-01 7.70362854e-01
2.21559376e-01 6.64666772e-01 -6.10136986e-01 4.76225130e-02
1.09884530e-01 6.22930288e-01 -4.24122602e-01 -1.06657520e-01
2.81686276e-01 6.48412287e-01 -1.36236131e-01 3.69343966e-01
6.64282978e-01 4.32241429e-03 4.47240695e-02 -4.79752958e-01
1.16238244e-01 1.21985890e-01 -1.13122916e+00 1.77862942e+00
-2.11982578e-01 5.34652710e-01 -3.43124688e-01 -1.76068246e+00
9.76639867e-01 5.13013899e-01 6.39774144e-01 -7.72286117e-01
2.03096271e-01 4.92839336e-01 3.93446773e-01 -5.76860726e-01
1.90524366e-02 -4.96952236e-01 8.17728713e-02 1.95750728e-01
3.48791808e-01 6.58141971e-02 7.38356262e-02 -2.33001098e-01
1.11127448e+00 9.33525413e-02 3.37416351e-01 -6.31080806e-01
6.66510522e-01 -4.07101452e-01 2.58240163e-01 7.93166220e-01
-3.21994662e-01 6.84970558e-01 5.45767069e-01 -4.92944866e-01
-6.36775196e-01 -1.13546419e+00 -6.76697969e-01 5.86275280e-01
-1.94737658e-01 -1.44306630e-01 -9.86503422e-01 -5.92783749e-01
1.91469520e-01 7.15854824e-01 -8.67109418e-01 -4.51172978e-01
-3.87681752e-01 -1.24083233e+00 1.02792835e+00 6.55470788e-01
3.09175253e-01 -9.50913310e-01 -1.02722585e+00 4.06869382e-01
5.22906035e-02 -1.02698851e+00 2.90390760e-01 5.53024113e-01
-1.06361103e+00 -1.04158723e+00 -9.54679608e-01 -3.83005828e-01
2.52720863e-01 -3.70273471e-01 9.30558920e-01 -3.04280728e-01
-5.26645064e-01 7.23412752e-01 -2.80011326e-01 -7.71955371e-01
-4.42197055e-01 8.83144885e-02 3.24288070e-01 1.82152495e-01
3.15306038e-01 -9.36266243e-01 -9.27118897e-01 2.26074144e-01
-1.06479824e+00 -4.21881169e-01 5.67033827e-01 8.11277211e-01
3.42382342e-01 -1.59105271e-01 1.33206320e+00 -5.81937790e-01
9.49951053e-01 -5.15385032e-01 -1.87040359e-01 -4.17728862e-03
-8.67540598e-01 2.09075455e-02 6.49638236e-01 -3.48835111e-01
-4.42703962e-01 -2.87368298e-01 -3.81566107e-01 -7.48808607e-02
-4.82356071e-01 5.15947878e-01 6.59510866e-02 -1.25995707e-02
1.02195764e+00 3.03495854e-01 -8.19490626e-02 -5.64271927e-01
-1.49875656e-01 7.40700305e-01 5.83040714e-01 -5.06384492e-01
2.19282061e-01 4.75247055e-01 2.75147915e-01 -8.88223529e-01
-3.55951339e-01 -3.88818324e-01 -6.63238764e-01 -4.39347550e-02
6.43801510e-01 -7.40347207e-01 -4.88548726e-01 5.21551728e-01
-9.65780258e-01 -1.58972517e-01 -3.11646461e-01 5.41126370e-01
-7.25889742e-01 5.03735900e-01 -2.62584686e-01 -7.34686434e-01
-4.16788936e-01 -1.09630191e+00 9.36895192e-01 -2.80903995e-01
-4.42705870e-01 -1.00308526e+00 1.34657294e-01 2.86829695e-02
5.16129732e-01 7.25143015e-01 9.85568702e-01 -1.00695932e+00
7.23119751e-02 -3.61232638e-01 1.29384100e-01 8.24311733e-01
1.10314198e-01 -4.64104861e-01 -1.50577772e+00 -6.07118309e-01
2.96352506e-01 -1.13971487e-01 7.64885366e-01 4.33824956e-01
1.21805143e+00 2.12977573e-01 -3.06345493e-01 5.62793136e-01
1.17014146e+00 3.98915142e-01 5.72181582e-01 4.65485096e-01
1.76513672e-01 4.57807600e-01 2.10450262e-01 5.38532555e-01
2.97822915e-02 6.43809259e-01 4.45553124e-01 -2.20189795e-01
-1.41365051e-01 2.63632804e-01 1.48850128e-01 4.98913258e-01
-2.95669079e-01 -1.25487924e-01 -1.10130322e+00 5.66304326e-01
-1.60735762e+00 -7.11020589e-01 -9.43072960e-02 2.31771851e+00
4.27229136e-01 1.71479821e-01 1.99629545e-01 7.74336636e-01
3.42264205e-01 -2.11369112e-01 -6.32224321e-01 -4.11478579e-01
-1.76007092e-01 5.96380949e-01 8.22920352e-02 -7.68034086e-02
-1.10955930e+00 1.48633271e-01 5.84341192e+00 4.40603942e-01
-1.53054833e+00 2.11811528e-01 6.05696797e-01 -7.13281855e-02
2.30809808e-01 -6.63926780e-01 -4.19911563e-01 4.42632228e-01
1.14572227e+00 -1.26582593e-01 3.54223341e-01 6.36881649e-01
1.34250626e-01 7.74040371e-02 -1.63312733e+00 1.36966348e+00
3.53150129e-01 -9.76880908e-01 -8.58954042e-02 -9.54344217e-03
4.64610487e-01 1.92982227e-01 1.97392538e-01 3.41767699e-01
-8.35917175e-01 -1.27822936e+00 6.69449389e-01 4.85508233e-01
7.88785398e-01 -6.27654552e-01 9.40973878e-01 1.80986792e-01
-6.28312051e-01 -2.15571821e-01 -2.50609815e-01 -1.20085888e-01
-2.07640767e-01 7.17402637e-01 -9.12870109e-01 8.52999210e-01
8.43737543e-01 8.02916050e-01 -6.60947800e-01 1.07185459e+00
6.61097392e-02 5.79566658e-01 -1.28816545e-01 1.14001550e-01
1.43939167e-01 2.28566080e-01 5.70555806e-01 1.48900378e+00
5.14301777e-01 -2.53083795e-01 -3.54725420e-01 9.59564686e-01
3.06922290e-02 6.26155883e-02 -5.94717085e-01 -5.57918474e-02
-5.65320440e-02 1.02360749e+00 -5.96901655e-01 -2.71570206e-01
-2.33799487e-01 1.05614972e+00 2.23185476e-02 4.44390893e-01
-8.63874316e-01 -5.12556791e-01 4.76665467e-01 1.90589517e-01
6.98154652e-03 5.63221192e-03 -3.66399258e-01 -1.02489364e+00
1.85904801e-01 -1.05935657e+00 3.69877815e-01 -4.74269122e-01
-1.51827121e+00 8.46523106e-01 2.54377574e-01 -1.15861273e+00
-3.48731697e-01 -9.14933741e-01 -2.50678778e-01 8.44684720e-01
-1.48772418e+00 -7.65999079e-01 -4.88907844e-01 6.07236087e-01
1.27987117e-01 -1.97395608e-01 1.08097529e+00 5.92817545e-01
-3.83938372e-01 5.77837586e-01 2.03544736e-01 -2.63545096e-01
7.92542040e-01 -1.17803025e+00 3.46318126e-01 5.26820600e-01
5.45996837e-02 6.38098001e-01 7.88254559e-01 -1.92298815e-01
-1.07675123e+00 -9.16196048e-01 3.84679377e-01 -3.63064259e-01
5.71347713e-01 -5.31459630e-01 -9.95931745e-01 3.59717160e-01
1.71523377e-01 -9.95073700e-04 7.54991293e-01 3.96356359e-02
-6.12389520e-02 -4.75560784e-01 -1.23880005e+00 1.99190468e-01
1.04833782e+00 -4.14005548e-01 -8.94317985e-01 2.76008278e-01
1.62513349e-02 -2.36056417e-01 -9.45232928e-01 8.74480903e-01
6.09505355e-01 -1.23414266e+00 1.01313603e+00 -5.38588047e-01
1.90103561e-01 -5.06997630e-02 -1.62484661e-01 -1.53157055e+00
-1.25830233e-01 -3.99940073e-01 -1.55334353e-01 9.61382449e-01
2.53859729e-01 -9.60906148e-01 5.07055998e-01 5.11547998e-02
-2.68627375e-01 -1.00074482e+00 -1.22468972e+00 -9.87573147e-01
3.53726774e-01 -6.50819063e-01 5.32333732e-01 9.37509239e-01
1.16786376e-01 2.03612804e-01 -1.45908892e-01 1.35367498e-01
5.17253816e-01 -8.06503445e-02 4.35032248e-01 -1.45218766e+00
-3.76137406e-01 -4.91181076e-01 -1.03667474e+00 -4.73782271e-01
-1.64373044e-03 -1.04408908e+00 -2.08956495e-01 -1.41013098e+00
4.89418581e-02 -2.08715662e-01 -1.03556871e+00 2.12817594e-01
1.82213232e-01 4.86410737e-01 -2.54656072e-03 -5.27511723e-02
-1.90049544e-01 2.78027833e-01 7.09677637e-01 -2.42341280e-01
-7.08157942e-02 -9.92283002e-02 -6.31407619e-01 5.27268052e-01
1.05501187e+00 -3.67253661e-01 -5.19509673e-01 -9.35344547e-02
1.58134606e-02 -2.59351641e-01 7.73654282e-01 -1.69355822e+00
-5.83021082e-02 5.78382194e-01 7.17478335e-01 -3.84465545e-01
2.79614419e-01 -7.78091013e-01 2.35807642e-01 6.26111925e-01
-2.10400090e-01 1.50015196e-02 6.44096792e-01 4.75158215e-01
-2.37679258e-01 -3.84815149e-02 8.17044199e-01 1.54220819e-01
-5.24255991e-01 -4.26973775e-02 -3.84817779e-01 1.78801432e-01
1.11501539e+00 -4.64780062e-01 -1.02152616e-01 -7.37447366e-02
-9.90450203e-01 -2.28639051e-01 1.14731170e-01 4.85581070e-01
5.97112179e-01 -1.02578545e+00 -6.80667102e-01 5.01285613e-01
3.08558524e-01 -4.94797617e-01 4.85789686e-01 1.29310012e+00
-3.41760784e-01 5.94867945e-01 -5.00119686e-01 -9.16672289e-01
-9.87260222e-01 4.78620857e-01 7.27312148e-01 3.02376784e-03
-6.94860995e-01 7.18141854e-01 3.86587769e-01 -2.47156724e-01
4.17631626e-01 -8.20750773e-01 -1.31271273e-01 1.66416258e-01
4.05870527e-01 4.41953272e-01 8.43007505e-01 -2.08193317e-01
-7.61759698e-01 3.92668575e-01 7.60392249e-02 8.85531455e-02
1.54211330e+00 2.78304338e-01 4.65769470e-02 5.65804899e-01
1.14020014e+00 -4.11883295e-01 -8.26429784e-01 5.08932531e-01
1.84073046e-01 1.01731509e-01 -1.62365139e-02 -1.32072592e+00
-7.15809464e-01 1.28351605e+00 1.29660428e+00 2.19964281e-01
1.38964272e+00 -3.34851593e-01 4.59749609e-01 4.88491833e-01
4.94309425e-01 -1.01786292e+00 4.37352434e-02 7.92648494e-02
1.19310045e+00 -9.22429144e-01 -9.02877152e-02 1.83465436e-01
-4.91189212e-01 1.16496336e+00 1.68062657e-01 -2.43007630e-01
6.03055060e-01 3.56770724e-01 8.78530834e-03 -2.88063228e-01
-3.30886185e-01 2.23503798e-01 4.61848646e-01 8.53950858e-01
7.13652134e-01 6.29170798e-03 -4.93901432e-01 9.70027924e-01
-8.20058435e-02 3.11928600e-01 4.83528733e-01 8.16759527e-01
-2.42651701e-02 -1.08586657e+00 -2.73533642e-01 4.31713939e-01
-7.02905595e-01 -3.41486419e-03 -4.26432192e-01 9.85224247e-01
3.00535887e-01 7.91367173e-01 -3.27332318e-01 -3.51695687e-01
7.03816593e-01 4.04868066e-01 6.75516188e-01 -3.45799327e-01
-7.21992791e-01 -1.95628539e-01 -7.64990747e-02 -5.24445891e-01
-4.85499680e-01 -5.91170669e-01 -1.11208129e+00 2.70066172e-01
5.00186905e-02 8.80486295e-02 7.95953214e-01 8.04579377e-01
6.05573535e-01 1.11483932e+00 9.56241414e-02 -8.44355226e-01
-8.16844404e-01 -1.11893153e+00 -8.27603042e-01 7.09200621e-01
5.60345113e-01 -8.89247358e-01 -3.12513351e-01 -1.35313720e-01] | [13.635369300842285, 3.315863847732544] |
bc9254e7-43dd-4a87-a2d1-915c5bf3ea7c | a-fast-and-accurate-iris-segmentation-method | 2201.06176 | null | https://arxiv.org/abs/2201.06176v1 | https://arxiv.org/pdf/2201.06176v1.pdf | A fast and accurate iris segmentation method using an LoG filter and its zero-crossings | This paper presents a hybrid approach to achieve iris localization based on a Laplacian of Gaussian (LoG) filter, region growing, and zero-crossings of the LoG filter. In the proposed method, an LoG filter with region growing is used to detect the pupil region. Subsequently, zero-crossings of the LoG filter are used to accurately mark the inner and outer circular boundaries. The use of LoG based blob detection along with zero-crossings makes the inner and outer circle detection fast and robust. The proposed method has been tested on three public databases: MMU version 1.0, CASIA-IrisV1 and CASIA-IrisV3- Lamp. The experimental results demonstrate the segmentation accuracy of the proposed method. The robustness of the proposed method is also validated in the presence of noise, such as eyelashes, a reflection of the pupil, Poisson, Gaussian, speckle and salt-and-pepper noise. The comparison with well-known methods demonstrates the superior performance of the proposed method's accuracy and speed. | ['Yinan Kong', 'Donald G. bailey', 'Tariq M. Khan'] | 2022-01-17 | null | null | null | null | ['iris-segmentation'] | ['medical'] | [-2.89105568e-02 -3.87819946e-01 9.74367112e-02 1.39650181e-01
-1.25854105e-01 -6.70271516e-01 3.07916701e-01 4.33034092e-01
-5.08943379e-01 5.94545364e-01 2.07929928e-02 -2.08074927e-01
-5.52221462e-02 -4.22687620e-01 -1.99776828e-01 -7.48418331e-01
1.80573672e-01 -1.21783353e-01 4.20169592e-01 2.32573584e-01
6.35023355e-01 7.03353584e-01 -1.65273094e+00 -1.87571213e-01
1.09903491e+00 7.76301205e-01 -1.83477581e-01 9.99553502e-01
1.08833991e-01 7.75926858e-02 -6.35851622e-01 -6.71377778e-02
4.38628614e-01 -3.94628376e-01 -5.09115219e-01 4.41521615e-01
4.32399988e-01 -1.91790938e-01 2.85413623e-01 1.37851071e+00
6.26693666e-01 8.06280747e-02 5.74782789e-01 -7.41519451e-01
-2.43846312e-01 -4.12798792e-01 -1.33105206e+00 3.30199599e-01
3.04326594e-01 3.26647073e-01 2.36844927e-01 -5.79272687e-01
7.05957174e-01 1.02926922e+00 7.60219097e-01 -6.17455086e-03
-9.93420243e-01 -5.71453452e-01 -4.86926913e-01 -1.01177871e-01
-1.70978105e+00 -6.58370480e-02 2.83693641e-01 -6.79360271e-01
6.88675463e-01 3.04603487e-01 6.55261517e-01 -2.80613542e-01
3.07844937e-01 3.76097113e-01 1.76115048e+00 -7.94902682e-01
-6.53394312e-02 5.63885927e-01 1.89347744e-01 8.85638714e-01
4.22771633e-01 2.20685601e-01 -1.10893389e-02 -2.30683103e-01
7.61730373e-01 -2.07005441e-01 -2.22114697e-01 -7.98465088e-02
-6.52209103e-01 4.14194047e-01 1.79674521e-01 4.97622490e-01
-4.82187331e-01 -4.37420785e-01 2.46950060e-01 -2.77965605e-01
2.99836963e-01 9.61918384e-03 6.66340813e-02 -1.24547586e-01
-1.14906657e+00 6.33861944e-02 4.21635300e-01 8.88752520e-01
5.34873366e-01 -3.42882514e-01 -1.39627397e-01 5.48973858e-01
7.63822258e-01 3.75050753e-01 3.90731007e-01 -4.41632956e-01
6.94573224e-02 8.73785436e-01 4.99867231e-01 -8.81327271e-01
-2.60203481e-01 -5.47963202e-01 -5.51001310e-01 6.91734254e-01
7.26085126e-01 -2.48165473e-01 -1.34986115e+00 7.89272308e-01
7.60100782e-01 5.29290140e-01 6.11047409e-02 7.70251036e-01
8.03246558e-01 4.44766045e-01 -1.11756399e-01 -4.20601040e-01
1.30108643e+00 -6.60289288e-01 -8.99884701e-01 5.71959972e-01
3.40221912e-01 -1.51842082e+00 4.48928207e-01 5.52787244e-01
-1.00703669e+00 -6.72174454e-01 -8.53727996e-01 2.49158517e-01
-3.69062871e-01 5.52450597e-01 1.94392756e-01 9.46251094e-01
-8.95844698e-01 3.06646585e-01 -7.15891659e-01 -7.60492206e-01
3.59970152e-01 6.73746705e-01 -2.18584523e-01 1.73588455e-01
-3.80173892e-01 6.25733852e-01 3.60923141e-01 1.28119022e-01
4.03606966e-02 -1.76512152e-01 -6.88003898e-01 -3.43921095e-01
-6.36694059e-02 -2.90606916e-01 7.65055835e-01 -7.36757934e-01
-1.35831416e+00 1.24094748e+00 -5.59734166e-01 -3.94669175e-01
3.12594980e-01 1.87579654e-02 -4.40659583e-01 2.63703644e-01
-2.77868301e-01 6.60539046e-02 6.68904603e-01 -1.03404534e+00
-1.04787993e+00 -7.53570676e-01 -3.65961313e-01 1.33989125e-01
3.13106477e-01 4.75027800e-01 -5.90023637e-01 -4.18753982e-01
3.34017009e-01 -7.14010775e-01 1.49990059e-02 -3.47274125e-01
-6.22361004e-01 -3.55446547e-01 8.76058340e-01 -8.28836560e-01
1.53020978e+00 -2.37774277e+00 -6.06546223e-01 6.67434335e-01
9.21630710e-02 8.40913713e-01 3.35949033e-01 3.08584154e-01
7.41924569e-02 1.62075698e-01 5.62523939e-02 -1.30078286e-01
-4.57555383e-01 -1.34009391e-01 3.93847317e-01 9.97298539e-01
-1.38851598e-01 3.56696099e-01 -5.53923130e-01 -6.41570985e-01
5.07776558e-01 7.19979405e-01 5.80350049e-02 -5.36563098e-02
2.93078631e-01 5.03989697e-01 -4.11039367e-02 7.63717115e-01
9.42287028e-01 1.68484449e-01 -4.60852236e-01 -1.32445395e-01
-6.64677382e-01 -1.81127235e-01 -1.72700512e+00 1.04746699e+00
1.70418844e-01 5.33662438e-01 1.77749217e-01 -3.10911655e-01
1.13451719e+00 5.32158077e-01 2.07874209e-01 -2.74467498e-01
5.08190632e-01 3.09426188e-01 7.08777085e-02 -7.46987522e-01
3.92806560e-01 2.67342292e-02 8.78649175e-01 1.87963426e-01
-2.31079280e-01 1.16750464e-01 4.74816084e-01 -2.36321256e-01
2.90858835e-01 1.75085217e-01 6.12836361e-01 -1.62013352e-01
1.05824220e+00 1.99928116e-02 5.40935874e-01 3.18505168e-01
-6.51044726e-01 4.11068350e-01 2.93984413e-01 -1.29298016e-01
-8.08190525e-01 -6.78642869e-01 -6.43182635e-01 8.62486809e-02
3.21654767e-01 -1.11487769e-01 -1.10142279e+00 -3.18207949e-01
1.16594598e-01 2.59490013e-01 -4.88964647e-01 5.07950425e-01
-1.94382131e-01 -8.69449914e-01 7.83121958e-02 -1.50304481e-01
6.99042201e-01 -7.58987665e-01 -6.98173881e-01 -1.82981789e-02
3.47471982e-01 -8.45261693e-01 -3.45503122e-01 -7.80389071e-01
-8.82784188e-01 -1.41054451e+00 -8.42579842e-01 -1.01542938e+00
1.00099456e+00 6.18732497e-02 4.16443199e-01 2.70709127e-01
-9.19634938e-01 2.22045839e-01 -2.52358735e-01 -5.50289035e-01
-4.53663290e-01 -5.46627283e-01 -1.33810535e-01 4.79724348e-01
8.08681965e-01 -7.26575553e-02 -9.06525433e-01 3.52665573e-01
-5.76487482e-01 -3.25465649e-01 5.01600206e-01 5.13293684e-01
7.51366794e-01 6.88960075e-01 5.82940243e-02 -8.04409385e-01
7.50059724e-01 3.34631209e-03 -1.17381561e+00 1.06709771e-01
-8.73839378e-01 -4.84312505e-01 6.17495999e-02 -2.50785619e-01
-9.03492749e-01 1.50657967e-01 2.71156818e-01 -1.48003206e-01
-4.93559480e-01 6.37629852e-02 3.91487449e-01 -5.60762882e-01
7.23523021e-01 2.02890649e-01 3.20771784e-01 -6.61957800e-01
1.33902103e-01 1.27126920e+00 7.93217778e-01 1.14591666e-01
6.86902523e-01 5.63516259e-01 1.15353979e-01 -8.94999087e-01
-1.21100247e-01 -1.14423835e+00 -7.12791204e-01 -1.79011822e-01
1.02157676e+00 -5.71829200e-01 -1.11695874e+00 1.00971484e+00
-9.60075259e-01 4.37133789e-01 7.48927593e-02 6.96903944e-01
-3.00631970e-02 6.04632676e-01 -5.62050998e-01 -1.42305398e+00
-6.18056834e-01 -1.26250255e+00 4.89559263e-01 1.27140582e+00
2.09757686e-01 -9.15632188e-01 -6.10743724e-02 3.87376845e-01
3.77495259e-01 5.60543060e-01 6.08204901e-01 -3.32483470e-01
-4.43886280e-01 -7.25079417e-01 -3.26263815e-01 4.15712982e-01
3.90791535e-01 5.46419442e-01 -8.73910725e-01 -3.48893315e-01
-1.39136121e-01 2.32092172e-01 4.16798085e-01 7.15732992e-01
4.94530916e-01 -1.42855600e-01 -4.23704118e-01 6.66712701e-01
1.90174234e+00 6.25967085e-01 7.68071830e-01 2.45974571e-01
1.49363950e-01 4.96728331e-01 9.10655916e-01 4.40986812e-01
3.95385176e-02 3.39181423e-01 3.95115316e-01 -6.96440041e-01
-2.72271514e-01 3.64506952e-02 -2.63133854e-01 1.71754897e-01
-3.92924100e-01 1.97435737e-01 -8.22025120e-01 6.90669894e-01
-1.33548188e+00 -6.46444380e-01 -7.36261368e-01 2.66313910e+00
8.41309905e-01 -1.62606351e-02 3.38096082e-01 3.73023719e-01
9.05728698e-01 -4.89050746e-01 -2.18093574e-01 -5.69455147e-01
5.05919233e-02 5.63722908e-01 8.57034922e-01 8.49362075e-01
-1.24628353e+00 9.63565350e-01 5.85935640e+00 5.12019038e-01
-1.30700862e+00 -1.68509349e-01 5.31589210e-01 2.61143565e-01
4.72225636e-01 -8.96928981e-02 -1.05948448e+00 4.09190625e-01
4.04942065e-01 4.04242687e-02 2.47649968e-01 2.54568487e-01
6.09538376e-01 -1.01946998e+00 -6.33062869e-02 1.04295957e+00
-1.77318156e-02 -9.57699120e-01 -5.48688114e-01 2.76026636e-01
7.70927787e-01 -2.33404607e-01 9.00307968e-02 -5.00116825e-01
-1.37853771e-01 -1.07026958e+00 -1.33789524e-01 5.99101841e-01
7.16598272e-01 -8.49107087e-01 1.03576815e+00 -8.50771461e-03
-1.08365405e+00 7.29122683e-02 -1.41777396e-01 2.14946970e-01
-1.22781806e-01 2.63305873e-01 -1.37137020e+00 3.05630684e-01
4.56119090e-01 3.50634456e-01 -6.94821298e-01 1.95930469e+00
-1.03841737e-01 6.78661048e-01 -4.49987680e-01 7.72203133e-02
1.65566042e-01 -6.14778876e-01 8.05211902e-01 1.19962025e+00
1.07484385e-01 5.85286915e-02 -1.36048734e-01 8.47764254e-01
4.13070083e-01 8.34417343e-01 -3.65578562e-01 -1.23509362e-01
3.16019446e-01 1.21773171e+00 -8.66481721e-01 -1.98447093e-01
-6.07277155e-01 6.38673842e-01 -5.45730054e-01 5.65873921e-01
-3.44403148e-01 -8.56703758e-01 3.81228566e-01 4.73316014e-01
1.82292148e-01 -3.68791185e-02 -4.30023193e-01 -3.12876493e-01
-1.40979469e-01 -7.81725883e-01 3.81631434e-01 -6.34006560e-01
-4.67207611e-01 3.95450383e-01 -1.70178622e-01 -1.05212831e+00
7.44715631e-02 -5.11414230e-01 -7.17151821e-01 1.58378899e+00
-1.34845710e+00 -1.22729886e+00 -2.97591925e-01 5.51963270e-01
1.37359932e-01 -3.30579996e-01 6.25974655e-01 1.57472342e-01
-7.06125081e-01 5.61313033e-01 1.14638716e-01 1.91888362e-01
6.84330344e-01 -1.28585291e+00 -8.01664293e-02 1.22037625e+00
-1.79664463e-01 8.29178929e-01 7.57095277e-01 -8.38942409e-01
-8.64877582e-01 -5.25769949e-01 9.48798239e-01 1.39467373e-01
2.30052486e-01 1.36913478e-01 -7.49319196e-01 3.99463087e-01
3.37238491e-01 8.55788067e-02 5.95216811e-01 -1.03934236e-01
3.54569294e-02 -1.57540187e-01 -1.51614666e+00 1.80547833e-01
-1.20043829e-01 -2.87437066e-02 -3.82458478e-01 3.33796442e-01
-1.90856591e-01 -6.64590657e-01 -1.06279826e+00 3.54421109e-01
5.60204625e-01 -1.28097606e+00 4.79711205e-01 -2.18144000e-01
-4.25429434e-01 -8.75549316e-01 5.93889832e-01 -6.60437763e-01
-5.74987493e-02 -1.10699189e+00 4.76448089e-01 1.28710592e+00
3.47035229e-01 -8.54640841e-01 7.39339709e-01 2.38936156e-01
4.24189597e-01 -7.82819986e-01 -6.74891174e-01 -1.90966755e-01
-4.12857771e-01 3.23649108e-01 1.80957735e-01 5.89423895e-01
-1.51990950e-01 -2.12596640e-01 -1.75324362e-02 4.91084278e-01
7.77178407e-01 -2.19366536e-03 9.95440304e-01 -1.39977968e+00
-4.06300575e-02 -1.98888496e-01 -8.90723705e-01 -4.86668646e-01
-7.33497024e-01 -2.93816149e-01 -2.78044969e-01 -1.45486593e+00
-4.04693596e-02 -3.98487717e-01 -1.84482306e-01 2.83516049e-01
-3.35027158e-01 4.52942222e-01 -5.72085157e-02 7.22933486e-02
1.59108937e-01 -4.82448936e-01 1.43359137e+00 3.94670039e-01
-8.30363929e-01 4.39424217e-01 -3.33395332e-01 6.94077194e-01
8.45869720e-01 -1.89475685e-01 -2.23124653e-01 3.14235330e-01
-1.82329029e-01 -2.47227281e-01 9.52225029e-02 -9.12583053e-01
4.01489884e-01 9.77334380e-02 3.15090954e-01 -9.56773043e-01
7.08330646e-02 -5.48937678e-01 1.89998075e-02 4.85400051e-01
3.11351508e-01 -5.91769479e-02 4.87316489e-01 4.52843338e-01
-2.51952082e-01 -4.50349838e-01 1.38574207e+00 -6.81315660e-02
-4.02303755e-01 -4.83210571e-02 -1.22759365e-01 -3.86985093e-01
1.51515508e+00 -8.33693385e-01 -3.33634406e-01 -1.00448109e-01
-8.10123205e-01 8.97445306e-02 7.62510240e-01 1.46282343e-02
5.13466775e-01 -6.51696622e-01 -7.70014942e-01 7.85373807e-01
5.56355529e-02 -1.97723135e-02 3.18756029e-02 1.50106478e+00
-1.11677253e+00 4.80067790e-01 -1.71645731e-01 -7.12031245e-01
-2.25124168e+00 3.85314077e-01 5.71706116e-01 7.55468756e-02
-4.43988383e-01 8.72268736e-01 -2.60649145e-01 3.51444513e-01
5.66939592e-01 -4.12065864e-01 -5.14853835e-01 -3.15946370e-01
6.37440085e-01 4.71248865e-01 -2.37891272e-01 -9.56098914e-01
-9.67857316e-02 1.11885870e+00 -8.03261325e-02 -3.69139463e-02
5.94717920e-01 -2.88869500e-01 -6.42125607e-01 1.73157722e-01
7.17860103e-01 6.47063196e-01 -6.36419296e-01 -1.76965743e-01
-7.05877990e-02 -7.66484976e-01 2.49609470e-01 -9.08208072e-01
-6.70178771e-01 8.28884065e-01 1.19531119e+00 3.46482657e-02
1.35599387e+00 -5.13466597e-01 5.41462898e-01 -7.59846032e-01
-1.48699835e-01 -1.17927051e+00 -7.32370198e-01 -1.05756126e-01
2.89745063e-01 -1.05453110e+00 1.18663549e-01 -5.98137617e-01
-4.08380896e-01 1.11334026e+00 3.66266072e-01 3.12704407e-02
8.33445430e-01 1.54347017e-01 4.15178508e-01 -1.56168845e-02
-7.68639743e-02 -7.81374335e-01 6.44543529e-01 6.21149242e-01
5.98725259e-01 -5.10255657e-02 -1.02074528e+00 -1.72907859e-01
2.22403780e-02 4.04744864e-01 6.01787567e-01 8.36151183e-01
-7.32356012e-01 -1.01067603e+00 -9.14976418e-01 3.88754368e-01
-1.03931177e+00 6.71819076e-02 -3.55295837e-01 9.41443801e-01
5.92899740e-01 1.25654578e+00 1.42089173e-01 -5.76238967e-02
3.02459355e-02 -6.85729682e-02 4.44930345e-01 -4.46479946e-01
-7.75247395e-01 7.86367953e-01 -2.46804312e-01 -3.03840280e-01
-5.46097696e-01 -5.12213767e-01 -1.32087195e+00 -1.53174475e-01
-5.37480891e-01 2.91925848e-01 1.10856938e+00 6.29438162e-01
2.66821563e-01 -4.06670645e-02 3.70481312e-01 2.54902449e-02
-2.26552129e-01 -1.23645175e+00 -9.89481151e-01 4.59221274e-01
5.96555710e-01 -4.73535120e-01 -3.74170780e-01 2.98304588e-01] | [3.7535364627838135, -3.625347137451172] |
68394ba8-38b6-4c0f-bf56-2ff729d819fa | msp-former-multi-scale-projection-transformer | 2207.05621 | null | https://arxiv.org/abs/2207.05621v3 | https://arxiv.org/pdf/2207.05621v3.pdf | MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing | Snow removal causes challenges due to its characteristic of complex degradations. To this end, targeted treatment of multi-scale snow degradations is critical for the network to learn effective snow removal. In order to handle the diverse scenes, we propose a multi-scale projection transformer (MSP-Former), which understands and covers a variety of snow degradation features in a multi-path manner, and integrates comprehensive scene context information for clean reconstruction via self-attention operation. For the local details of various snow degradations, the local capture module is introduced in parallel to assist in the rebuilding of a clean image. Such design achieves the SOTA performance on three desnowing benchmark datasets while costing the low parameters and computational complexity, providing a guarantee of practicality. | ['Peng Chen', 'Jingxia Jiang', 'ErKang Chen', 'Taodong Liao', 'Yun Liu', 'Tian Ye', 'Sixiang Chen'] | 2022-07-12 | null | null | null | null | ['single-image-desnowing'] | ['computer-vision'] | [ 3.61595958e-01 -3.31832051e-01 2.12540835e-01 -4.15436238e-01
-6.42574728e-01 -1.42304793e-01 2.10095495e-01 -3.25481206e-01
3.34803089e-02 5.79537809e-01 5.96062541e-01 -2.92600170e-02
6.52978346e-02 -7.37862349e-01 -6.84792221e-01 -1.19384229e+00
3.41270357e-01 -8.94801989e-02 2.59682357e-01 -5.16262293e-01
-7.06944838e-02 5.64071059e-01 -1.63491559e+00 1.32905766e-01
1.24222958e+00 8.65972519e-01 6.99708641e-01 5.77690661e-01
3.26858871e-02 7.47360408e-01 -2.69552380e-01 -3.71123552e-01
1.65560961e-01 -1.23099402e-01 -3.56169343e-01 3.90531808e-01
6.36187136e-01 -4.92325336e-01 -7.91923940e-01 1.08561456e+00
5.28764725e-01 1.50163710e-01 3.29505175e-01 -8.28774571e-01
-3.51363540e-01 3.32235366e-01 -8.14983428e-01 5.91956973e-01
-1.73500236e-02 5.48404157e-01 8.74498248e-01 -8.44741821e-01
2.67851770e-01 1.16492367e+00 5.87779880e-01 4.87650990e-01
-9.11868811e-01 -7.19800293e-01 7.06872344e-01 5.25970638e-01
-1.13738096e+00 -5.81773758e-01 7.59632945e-01 -4.60209027e-02
5.22564590e-01 4.86429632e-01 1.03950119e+00 1.10384655e+00
1.61251098e-01 1.09386456e+00 1.27645659e+00 1.41635194e-01
-1.81176383e-02 -1.40845612e-01 3.75060081e-01 3.07537019e-01
1.68315783e-01 -8.71289447e-02 -8.12040031e-01 2.88260460e-01
3.58050197e-01 3.88884544e-01 -6.12599432e-01 -5.12602963e-02
-6.59084141e-01 3.49572808e-01 8.27222526e-01 -2.55295455e-01
-4.49701786e-01 1.78707242e-01 3.28158677e-01 2.33503014e-01
6.92600012e-01 -1.76621899e-01 -4.28095579e-01 9.52656865e-02
-9.51480985e-01 2.41573334e-01 2.75590181e-01 8.86425674e-01
7.70670533e-01 3.42688829e-01 -1.74063087e-01 5.54783523e-01
3.69525552e-01 9.93887186e-01 -5.79823814e-02 -5.83395660e-01
7.19551325e-01 5.38150668e-01 9.44992304e-02 -7.61024892e-01
-4.26998794e-01 -1.00697136e+00 -1.44536781e+00 1.42357260e-01
-7.73351565e-02 1.75518289e-01 -1.12640476e+00 1.61140049e+00
5.74744999e-01 4.14074659e-01 1.02782205e-01 1.11651635e+00
7.90653467e-01 7.67736733e-01 3.05928010e-02 -3.13390017e-01
1.40394425e+00 -1.11248434e+00 -7.42412210e-01 -8.54956567e-01
-4.96281274e-02 -4.42503542e-01 1.34580600e+00 3.30431759e-01
-7.88793862e-01 -4.21089470e-01 -1.02407050e+00 -1.34090826e-01
-9.40320119e-02 -9.02491212e-02 4.82062906e-01 2.84893125e-01
-8.97335112e-01 4.56130981e-01 -8.53654563e-01 -4.27432567e-01
6.31056249e-01 -1.36227250e-01 -1.41346961e-01 -6.43276513e-01
-1.07108271e+00 8.41979086e-01 -5.08762635e-02 9.17596221e-01
-1.31279886e+00 -8.31637919e-01 -8.68491232e-01 2.99649626e-01
2.53109187e-01 -9.24321651e-01 8.05531085e-01 -6.97040021e-01
-1.28775799e+00 5.01709998e-01 -4.36009139e-01 -4.16210771e-01
6.84474528e-01 -6.97118342e-01 -4.11201239e-01 6.42758757e-02
-3.66628692e-02 2.71908998e-01 1.39291811e+00 -1.33282673e+00
-5.76438308e-01 -4.71152663e-01 1.11934565e-01 9.21837628e-01
-3.70963991e-01 -2.41100695e-02 -6.33616686e-01 -6.57641709e-01
2.90376157e-01 -8.56233299e-01 -3.14127713e-01 2.67599337e-02
-3.40579480e-01 4.88008082e-01 8.79172564e-01 -1.10191369e+00
9.79189992e-01 -2.26838160e+00 5.13062239e-01 -1.99894667e-01
6.20933592e-01 2.25530148e-01 -1.23748541e-01 2.58560389e-01
-4.24121469e-02 -3.11101913e-01 -6.73221648e-01 -7.95801759e-01
-2.11610898e-01 3.92925978e-01 -6.27496421e-01 7.19010532e-01
2.31684402e-01 8.08376849e-01 -6.76992893e-01 -2.36091420e-01
2.72169977e-01 4.40278292e-01 -1.01300187e-01 4.24264282e-01
4.79240976e-02 4.47640896e-01 -3.34430933e-01 7.53465533e-01
1.32623529e+00 1.37025952e-01 -2.21715212e-01 -3.26016873e-01
1.79126531e-01 4.66875955e-02 -1.12480366e+00 1.46838450e+00
-6.16046429e-01 5.90703070e-01 6.09006643e-01 -4.90403026e-01
7.10435867e-01 -1.32188916e-01 -5.64480387e-02 -8.16902936e-01
5.88164441e-02 -8.39797258e-02 -4.07498449e-01 -6.18123353e-01
5.26778698e-01 -2.20899254e-01 1.03112087e-01 1.23322003e-01
-4.98670548e-01 -1.46566540e-01 -1.73529163e-01 4.15983915e-01
1.09581172e+00 2.02250659e-01 -4.99261767e-02 -2.35665858e-01
5.17584145e-01 -2.71524549e-01 9.27623034e-01 5.65938056e-01
-3.01716805e-01 8.24310780e-01 -1.96994320e-02 -5.72519600e-01
-8.63606453e-01 -1.12515700e+00 7.85714537e-02 9.45942283e-01
6.43184781e-01 -2.65971482e-01 -6.50117278e-01 -3.62895608e-01
-1.14208467e-01 4.43176270e-01 -7.62268782e-01 -4.53959435e-01
-4.91614848e-01 -1.05142772e+00 9.18866321e-02 5.04554331e-01
7.29474843e-01 -1.05740678e+00 -5.61713696e-01 -1.53174894e-02
-2.92280316e-01 -1.12000680e+00 -6.33477271e-01 2.44752854e-01
-9.00488317e-01 -1.04061389e+00 -5.63220143e-01 -5.13019323e-01
6.79553032e-01 9.59388912e-01 1.00303233e+00 1.44094944e-01
-1.21064790e-01 -1.68917686e-01 -4.30955172e-01 -2.16007233e-01
4.37300615e-02 1.54288054e-01 -5.03411237e-03 2.58311540e-01
7.80934095e-02 -9.55403328e-01 -6.50344908e-01 1.74349442e-01
-1.01997423e+00 3.18410814e-01 8.40433002e-01 1.02563798e+00
5.24150014e-01 1.74441472e-01 1.29837587e-01 -7.28053927e-01
3.09719771e-01 -4.73400772e-01 -3.70302707e-01 1.25582486e-01
-3.39256972e-01 -3.76463711e-01 6.85387433e-01 -9.93364975e-02
-1.38633513e+00 -1.26902098e-02 -5.73785901e-02 -5.31633496e-01
-1.01372048e-01 3.81174386e-01 -7.27605402e-01 -1.82431385e-01
3.50464553e-01 1.03686750e+00 -2.04478592e-01 -7.04482913e-01
2.64275491e-01 5.99378586e-01 5.76170146e-01 -1.75737232e-01
1.25855005e+00 7.43802130e-01 6.87304419e-03 -8.92501116e-01
-1.26126909e+00 -4.50957894e-01 -5.42917967e-01 -3.03048015e-01
4.07180488e-01 -1.56581175e+00 -4.83540475e-01 1.11493313e+00
-7.96579063e-01 -3.45294148e-01 -2.60231525e-01 -1.35201320e-01
-1.23007022e-01 5.30381560e-01 -5.68461239e-01 -8.92627597e-01
-8.23083341e-01 -9.52546954e-01 1.17678595e+00 5.28240919e-01
4.91941780e-01 -3.41009706e-01 -3.35235655e-01 5.51009059e-01
6.35235548e-01 -7.65184015e-02 3.93687695e-01 3.90546620e-01
-1.01115441e+00 4.46882285e-03 -6.45048380e-01 4.44403321e-01
1.12418137e-01 -3.25962156e-01 -1.20338237e+00 -5.98361254e-01
2.72693187e-01 -2.27909279e-03 1.45051551e+00 4.19310123e-01
1.07523763e+00 -6.00092672e-02 -8.24665874e-02 1.23557293e+00
1.37132943e+00 -2.86916733e-01 8.54547262e-01 5.26598275e-01
1.07843530e+00 4.61144894e-01 7.86963344e-01 4.69370067e-01
7.32346773e-01 2.43867278e-01 8.96028280e-01 -4.04734820e-01
-4.81744707e-01 -2.07469583e-01 5.16819894e-01 8.47959936e-01
3.56255412e-01 -2.59904236e-01 -5.11446357e-01 7.49917507e-01
-1.90900278e+00 -7.60850787e-01 -5.91128953e-02 1.74696028e+00
5.39819419e-01 1.92663372e-01 -2.41758198e-01 1.21490108e-02
5.88278353e-01 8.19436491e-01 -1.05592382e+00 5.51264137e-02
-5.92590988e-01 -2.55799174e-01 6.03910267e-01 4.64576125e-01
-1.03102314e+00 1.16627252e+00 6.09048033e+00 8.72745097e-01
-8.26364160e-01 2.00608090e-01 3.87805134e-01 -2.13013545e-01
-3.45491976e-01 7.21025392e-02 -7.98006415e-01 6.02817178e-01
6.13065362e-01 9.52518508e-02 6.14597559e-01 5.17129481e-01
5.50888717e-01 -1.97310925e-01 -1.70314685e-01 9.62472498e-01
1.06383339e-01 -1.12826598e+00 1.46841425e-02 -2.94813961e-01
5.99505365e-01 3.29158485e-01 -1.11075163e-01 8.09686109e-02
2.61597157e-01 -6.33554161e-01 7.63296664e-01 7.58119285e-01
5.64433038e-01 -5.74445546e-01 6.48120999e-01 3.97991627e-01
-1.40914619e+00 -2.41806731e-01 -5.13942480e-01 -2.39857808e-01
3.59109551e-01 9.20342565e-01 -2.84367710e-01 7.96383917e-01
1.14118361e+00 1.16422474e+00 -6.05352044e-01 1.26405692e+00
-6.22748554e-01 7.28663146e-01 -4.51417208e-01 4.62890834e-01
-1.70780544e-03 -4.21203852e-01 8.74243796e-01 1.11468387e+00
1.05576426e-01 3.26035395e-02 4.33962122e-02 3.41719776e-01
-4.56884615e-02 -1.97872207e-01 -2.44342402e-01 4.34578449e-01
3.78461182e-01 1.33329523e+00 -3.05172563e-01 -3.37350577e-01
-1.65015295e-01 1.19193268e+00 3.34286571e-01 3.31644148e-01
-8.92530739e-01 -9.27329436e-02 1.25682092e+00 6.97616711e-02
3.71305466e-01 -9.24447700e-02 -4.27208453e-01 -1.58889890e+00
4.22797054e-01 -1.03110123e+00 2.08008140e-01 -1.07663345e+00
-1.25222027e+00 8.18179309e-01 -3.23019058e-01 -1.25436735e+00
8.10897052e-01 -1.19628251e-01 -8.61434162e-01 1.09034967e+00
-2.31681776e+00 -1.85096765e+00 -1.15205050e+00 6.29382253e-01
7.72310138e-01 2.32266784e-01 2.85525531e-01 4.00759101e-01
-1.02763176e+00 2.65494257e-01 1.42383352e-01 -4.86122429e-01
7.11238742e-01 -1.25012994e+00 8.50276530e-01 1.63315940e+00
-3.30397666e-01 1.07889734e-01 1.05255723e+00 -7.63401449e-01
-1.51465654e+00 -1.52197051e+00 4.94153500e-01 -6.80070817e-02
3.54105800e-01 -3.44998211e-01 -1.14844227e+00 5.64908087e-01
4.52091433e-02 1.51320219e-01 1.34752572e-01 4.99024540e-02
-4.14251536e-01 -6.98793769e-01 -8.57289672e-01 7.16264904e-01
1.36602259e+00 -5.99228919e-01 -3.70091915e-01 5.39182007e-01
9.84368265e-01 -7.24765122e-01 -3.84599686e-01 2.79957503e-01
1.79685622e-01 -9.51711655e-01 8.90032887e-01 -3.60424250e-01
4.33687985e-01 -7.27262616e-01 -2.38871321e-01 -1.50346160e+00
-5.84880650e-01 -7.01312184e-01 -3.02165180e-01 1.26179910e+00
-5.31909429e-02 -6.54077888e-01 8.47222269e-01 4.51270372e-01
-5.60945570e-01 -5.77436984e-01 -8.12008560e-01 -3.75490248e-01
-4.03132647e-01 -4.02697295e-01 9.36817110e-01 4.57024515e-01
-7.61289775e-01 2.16754422e-01 -1.03064775e+00 8.27009499e-01
1.05684078e+00 5.04229248e-01 8.94263744e-01 -9.74431217e-01
-7.65008032e-02 -1.50657028e-01 -2.11434796e-01 -1.19586432e+00
5.57803996e-02 -3.96672100e-01 1.72853887e-01 -1.60482550e+00
4.76896912e-01 -2.31632635e-01 -3.44472229e-01 4.16308999e-01
-7.55401015e-01 3.30498844e-01 3.02918673e-01 2.66710252e-01
-5.56600988e-01 1.24582577e+00 1.34940529e+00 -3.37599695e-01
2.22243946e-02 1.83079094e-01 -9.25282836e-01 6.39546037e-01
5.46501994e-01 -6.07605457e-01 -2.56739527e-01 -8.76918256e-01
9.63418484e-02 -3.54219577e-03 3.33311588e-01 -1.22639191e+00
1.75412267e-01 -3.64967555e-01 1.60015821e-01 -7.56287634e-01
6.95111215e-01 -7.82810032e-01 2.21229330e-01 2.91945308e-01
9.36566219e-02 -8.67792442e-02 1.63245022e-01 9.63417351e-01
-3.19365084e-01 2.14072242e-01 9.85733509e-01 3.95208001e-02
-9.38017607e-01 7.22210884e-01 -8.45042393e-02 -2.21058637e-01
7.53301203e-01 -2.81148646e-02 -4.23079342e-01 -3.46591353e-01
-6.06792986e-01 7.50961363e-01 7.16430485e-01 3.03263962e-01
6.35696888e-01 -8.32849979e-01 -8.61498833e-01 4.04836386e-01
1.94770262e-01 4.47599918e-01 1.11886358e+00 7.88296103e-01
-5.81378698e-01 -3.08222383e-01 -1.55074850e-01 -3.66749227e-01
-1.32127845e+00 3.11539680e-01 4.35241789e-01 -2.93622911e-01
-1.23385108e+00 9.63653445e-01 4.93268460e-01 -1.45432666e-01
7.65518919e-02 -1.23836420e-01 -2.48433009e-01 1.22049667e-01
8.69221449e-01 1.90519065e-01 2.19948560e-01 -6.51164949e-01
-2.42225349e-01 6.08407140e-01 -1.64907858e-01 5.12954652e-01
1.67944241e+00 -9.21171486e-01 -6.77495897e-02 1.08800791e-01
6.26658320e-01 -1.33052051e-01 -1.93819571e+00 -7.15838969e-01
-6.47720218e-01 -8.32021356e-01 4.25930709e-01 -7.28478193e-01
-1.53058159e+00 9.84250724e-01 6.79792285e-01 -2.31293961e-01
1.65004981e+00 -3.77210557e-01 1.14331555e+00 1.62951678e-01
1.25416994e-01 -7.87329316e-01 -2.22077057e-01 4.33254302e-01
1.01343560e+00 -1.20757914e+00 1.92556381e-01 -4.95765179e-01
-1.02084088e+00 7.11905181e-01 7.34500051e-01 -1.02239802e-01
4.21383351e-01 3.12573969e-01 1.53059080e-01 -2.31710881e-01
-6.78194642e-01 -3.68520200e-01 -4.83584292e-02 6.58470571e-01
-5.38381517e-01 2.21937582e-01 2.80331820e-01 5.93578160e-01
1.10037372e-01 -1.49225622e-01 6.82602048e-01 7.56042182e-01
-5.71645617e-01 -6.14797890e-01 -3.98272425e-01 5.99366009e-01
1.11159123e-01 -3.57852876e-01 4.38721478e-03 1.10845730e-01
-3.93344909e-02 8.06351006e-01 -2.99382359e-01 -3.79362881e-01
4.41390753e-01 -3.25872749e-01 -3.54703665e-02 -4.18966323e-01
-5.16085327e-01 1.08403740e-02 -7.75500685e-02 -7.27069736e-01
-3.07291299e-01 -8.43409777e-01 -4.77236599e-01 -4.08538878e-01
-2.39665881e-01 -2.09685221e-01 3.23068291e-01 1.09147298e+00
5.23296118e-01 7.34817624e-01 8.76423001e-01 -1.21478474e+00
-4.64690864e-01 -1.13324976e+00 -1.04761529e+00 4.26500112e-01
7.29160786e-01 -6.17724359e-01 -5.25690258e-01 -1.80193216e-01] | [10.980676651000977, -3.1357266902923584] |
86ff698f-94e0-4e16-ad74-5b4f4e1edff8 | how-would-stance-detection-techniques-evolve | 2212.14548 | null | https://arxiv.org/abs/2212.14548v3 | https://arxiv.org/pdf/2212.14548v3.pdf | How would Stance Detection Techniques Evolve after the Launch of ChatGPT? | Stance detection refers to the task of extracting the standpoint (Favor, Against or Neither) towards a target in given texts. Such research gains increasing attention with the proliferation of social media contents. The conventional framework of handling stance detection is converting it into text classification tasks. Deep learning models have already replaced rule-based models and traditional machine learning models in solving such problems. Current deep neural networks are facing two main challenges which are insufficient labeled data and information in social media posts and the unexplainable nature of deep learning models. A new pre-trained language model chatGPT was launched on Nov 30, 2022. For the stance detection tasks, our experiments show that ChatGPT can achieve SOTA or similar performance for commonly used datasets including SemEval-2016 and P-Stance. At the same time, ChatGPT can provide explanation for its own prediction, which is beyond the capability of any existing model. The explanations for the cases it cannot provide classification results are especially useful. ChatGPT has the potential to be the best AI model for stance detection tasks in NLP, or at least change the research paradigm of this field. ChatGPT also opens up the possibility of building explanatory AI for stance detection. | ['Liwen Jing', 'Daijun Ding', 'BoWen Zhang'] | 2022-12-30 | null | null | null | null | ['stance-detection'] | ['natural-language-processing'] | [ 1.24182411e-01 6.08793795e-01 -6.96096182e-01 -4.03292120e-01
-5.08254051e-01 -3.53174537e-01 9.20802236e-01 3.31520945e-01
-2.16414407e-01 8.08366120e-01 6.12706602e-01 -6.05640352e-01
9.90191698e-02 -1.00339985e+00 -4.57433820e-01 -5.33625305e-01
2.56144673e-01 8.15866113e-01 1.80132896e-01 -7.64056146e-01
4.08732295e-01 -3.44431460e-01 -1.46288860e+00 8.81795764e-01
9.56284761e-01 9.75433350e-01 -2.40224794e-01 3.22478503e-01
-4.02850688e-01 1.11783779e+00 -6.84507906e-01 -6.12032473e-01
-1.30169094e-01 -4.99513268e-01 -9.91801322e-01 -2.43236721e-01
1.43613890e-01 -2.39066616e-01 -1.10686958e-01 7.75043905e-01
5.36657572e-01 -4.04039025e-01 5.56389034e-01 -1.33133233e+00
-8.25681210e-01 1.32463610e+00 -5.31261921e-01 3.16405565e-01
2.62749225e-01 -6.04229979e-02 1.49494720e+00 -7.41912305e-01
5.87558627e-01 1.31276345e+00 6.71718359e-01 5.65681398e-01
-7.23625243e-01 -4.67573732e-01 2.49287814e-01 6.65573716e-01
-3.05064321e-01 -8.95681456e-02 9.78925765e-01 -6.36398852e-01
9.10896838e-01 3.22937936e-01 7.91766822e-01 1.78219414e+00
2.10077986e-01 1.28526127e+00 1.15994608e+00 -5.11411965e-01
-8.98285061e-02 -6.86471984e-02 7.69936442e-01 3.62616688e-01
2.87542373e-01 -1.52808174e-01 -7.96417773e-01 1.00356003e-03
8.62702578e-02 -2.22011715e-01 3.82998437e-02 3.18299085e-01
-1.25403690e+00 1.33701968e+00 4.39614117e-01 5.94456077e-01
-2.35149845e-01 -9.09562483e-02 7.74808824e-01 4.30322111e-01
9.74625230e-01 6.92334533e-01 -5.02278209e-01 -1.40343547e-01
-8.66225958e-01 7.22052872e-01 9.10019577e-01 3.83990347e-01
-9.90522839e-03 1.01317972e-01 -2.31352061e-01 6.69633567e-01
2.93297380e-01 3.19323599e-01 6.14559770e-01 -5.86027503e-01
7.67260194e-01 9.43143129e-01 -1.14638351e-01 -9.57075179e-01
-6.95934653e-01 -5.91468632e-01 -4.64017540e-01 1.13091536e-01
5.46612263e-01 -4.11031216e-01 -6.85349047e-01 1.43109679e+00
2.27804914e-01 -5.54945827e-01 5.19279130e-02 7.51567125e-01
1.29935133e+00 6.67758286e-01 -1.60382427e-02 -1.71023205e-01
1.36864007e+00 -8.75705481e-01 -9.53412414e-01 -8.15404952e-01
7.29547620e-01 -8.41958106e-01 1.03724098e+00 5.82480311e-01
-9.57121551e-01 -1.90780908e-01 -1.27146089e+00 -2.19830856e-01
-6.42678559e-01 -1.52929664e-01 6.90473974e-01 3.50524306e-01
-6.39077067e-01 5.36735058e-01 -3.94771546e-01 -1.95521683e-01
5.83747149e-01 2.20027238e-01 1.61330193e-01 2.32876316e-01
-1.81145990e+00 1.22788441e+00 4.61438864e-01 2.26258129e-01
-4.77615863e-01 -5.19711077e-01 -7.47015834e-01 -1.89752445e-01
5.54597199e-01 -4.22601074e-01 1.34148109e+00 -1.17077339e+00
-1.10701847e+00 1.11072278e+00 -1.21480078e-02 -8.70326221e-01
7.66044557e-01 -5.45202136e-01 -3.63367110e-01 -3.65289450e-01
4.64641422e-01 2.77060717e-01 7.17088163e-01 -8.43838573e-01
-4.50091749e-01 -2.96571195e-01 1.51286423e-01 1.47483557e-01
-4.26524043e-01 3.51092756e-01 3.62373918e-01 -5.10986626e-01
1.59444049e-01 -8.26285303e-01 1.62666649e-01 -3.19811493e-01
-4.73618925e-01 -8.18421721e-01 1.15963817e+00 -7.22457170e-01
1.26257956e+00 -1.50684595e+00 8.17297548e-02 -2.11002767e-01
4.19041216e-01 4.78892267e-01 3.05038035e-01 5.51211476e-01
-2.97376543e-01 2.65568107e-01 2.61935173e-03 -5.86477444e-02
1.40936941e-01 2.40824357e-01 -5.58301449e-01 3.03809047e-01
2.39254579e-01 1.07219803e+00 -9.33006644e-01 -5.58173060e-01
-9.76094529e-02 1.45994201e-01 -5.53979635e-01 -1.66894242e-01
-7.18530774e-01 2.40814209e-01 -4.24011588e-01 4.33488667e-01
1.81895524e-01 -2.70282656e-01 4.61693108e-01 7.73898661e-02
-2.82099515e-01 1.10579455e+00 -2.94861019e-01 1.00557387e+00
-9.13400725e-02 1.18513370e+00 -3.35889399e-01 -1.30740404e+00
9.53070462e-01 5.85607290e-01 5.46144545e-01 -9.27671611e-01
5.75756133e-01 4.79320526e-01 6.38187289e-01 -5.98053575e-01
4.28688496e-01 -1.87533736e-01 -2.50439465e-01 8.09329391e-01
-3.41039270e-01 2.36931503e-01 3.03253084e-01 3.67239714e-02
8.20955217e-01 1.64194986e-01 3.38472933e-01 -4.21994686e-01
3.59953195e-01 1.96419135e-01 5.41428208e-01 4.40388203e-01
-2.14542523e-01 3.65461886e-01 8.52249503e-01 -7.18691409e-01
-1.10651946e+00 -4.13665265e-01 -2.17465892e-01 1.38233542e+00
-4.04506028e-01 -4.81474787e-01 -7.08939791e-01 -8.80524874e-01
1.01281963e-02 8.41167271e-01 -1.06400895e+00 -3.23076993e-02
-9.42911148e-01 -8.95962656e-01 4.28087831e-01 6.01337850e-01
7.85476685e-01 -1.61316788e+00 -6.17619634e-01 2.71954924e-01
-7.81907260e-01 -9.79118228e-01 1.31563768e-01 4.91946906e-01
-6.95054650e-01 -1.24182403e+00 -3.26538831e-01 -6.97776496e-01
7.54506513e-02 7.58821890e-02 1.14501929e+00 2.74470329e-01
4.56750512e-01 -5.72074652e-01 -6.12276256e-01 -9.36402917e-01
-6.83214664e-01 3.35696012e-01 5.25994037e-05 -3.36483598e-01
7.57994890e-01 -4.29709285e-01 -5.00506699e-01 8.45448077e-02
-5.54439902e-01 2.46502474e-01 1.82957590e-01 8.42548668e-01
-7.48491213e-02 -2.69758075e-01 1.03153706e+00 -1.33674312e+00
8.75180244e-01 -7.08408296e-01 1.22147631e-02 -1.21786498e-01
-8.52435768e-01 -1.89807117e-01 3.66623908e-01 -2.53262967e-01
-9.34731662e-01 -8.19137454e-01 -4.87461239e-01 3.12098086e-01
1.53614521e-01 1.06626379e+00 -5.19545712e-02 7.16036081e-01
9.95356143e-01 -6.15740940e-02 -2.73917206e-02 -3.36208254e-01
8.13080966e-02 8.06647837e-01 2.02269107e-01 -4.49262887e-01
4.48290110e-01 2.94388354e-01 -4.14814800e-01 -6.43057942e-01
-1.70941103e+00 -2.13902295e-01 -5.96647143e-01 -2.67281234e-01
9.51674521e-01 -5.54305375e-01 -6.03019714e-01 3.93380225e-01
-1.18706501e+00 -4.86235112e-01 8.65638349e-03 -6.59072697e-02
-3.97008151e-01 1.86807901e-01 -6.93843067e-01 -5.63951313e-01
-7.51994610e-01 -7.36577928e-01 5.98555207e-01 -5.30784614e-02
-9.39980268e-01 -1.15735638e+00 4.43632379e-02 1.04106557e+00
2.71474630e-01 4.66465950e-01 1.29344785e+00 -1.06580460e+00
1.91207886e-01 -2.82839119e-01 -4.50789146e-02 1.67078570e-01
-1.67054087e-02 1.46267861e-01 -9.96498942e-01 7.47438446e-02
1.00844175e-01 -6.25983894e-01 9.36630130e-01 5.20182610e-01
1.01135838e+00 -6.41159415e-01 -1.54795617e-01 -8.35883096e-02
7.45003819e-01 2.59973943e-01 5.59282064e-01 9.48475182e-01
4.37941015e-01 7.23065019e-01 8.59944165e-01 1.87131852e-01
3.26030642e-01 6.32537365e-01 6.62601113e-01 -7.57722631e-02
-1.45647794e-01 -1.58694595e-01 5.19655764e-01 6.71928763e-01
-1.40214041e-01 -3.73136342e-01 -1.28643799e+00 4.83082145e-01
-2.27432418e+00 -1.22107649e+00 -6.83559775e-01 1.58321595e+00
9.94917035e-01 9.20216560e-01 2.11301357e-01 8.09702218e-01
3.63790363e-01 4.22056168e-01 -4.55213368e-01 -8.75919998e-01
-3.66060078e-01 1.81227885e-02 -1.95404425e-01 4.23012286e-01
-1.29685950e+00 9.50219452e-01 6.00983000e+00 4.31824535e-01
-1.07445657e+00 2.68969566e-01 4.83530730e-01 7.05567673e-02
-3.00370365e-01 -1.57462895e-01 -8.38597715e-01 5.02340317e-01
1.01471138e+00 -2.39912137e-01 -3.60276818e-01 8.76918495e-01
4.88815099e-01 -7.73250610e-02 -1.14430416e+00 4.95346069e-01
2.45940030e-01 -1.59472537e+00 4.57255729e-02 2.21859068e-01
5.75638711e-01 7.27035254e-02 1.67395651e-01 6.76231980e-01
3.58184576e-01 -1.00609529e+00 1.00458550e+00 -8.19807723e-02
4.02338326e-01 -5.13362348e-01 1.01578784e+00 6.11794353e-01
-4.78135437e-01 -3.27769339e-01 -1.81405976e-01 -6.83940232e-01
-7.03219622e-02 5.70555031e-01 -1.13935542e+00 2.04664245e-01
4.88097787e-01 1.02310884e+00 -4.49523121e-01 5.64117312e-01
-6.38975024e-01 1.11436081e+00 4.18890268e-02 -3.26662153e-01
5.35835087e-01 1.84154838e-01 6.18844748e-01 9.86976922e-01
-1.28488958e-01 -4.38239053e-02 1.54781878e-01 6.90535426e-01
-1.24559760e-01 -1.91564132e-02 -5.59419930e-01 -2.82360733e-01
2.56730795e-01 9.07066405e-01 -6.96122587e-01 -5.24255455e-01
-2.05421612e-01 3.76184195e-01 2.91689038e-01 -5.31733632e-02
-9.64465976e-01 2.55112380e-01 5.31733155e-01 5.28744042e-01
-1.29248872e-01 -9.66795161e-03 -8.85950923e-01 -9.27723229e-01
-2.08987042e-01 -1.32980490e+00 5.44416487e-01 -6.94105208e-01
-1.12725234e+00 4.54630792e-01 -1.73737854e-01 -9.77540374e-01
-4.97739315e-01 -8.05573404e-01 -8.81799877e-01 5.34356952e-01
-1.24971962e+00 -1.37951422e+00 -9.57595408e-02 2.51321971e-01
1.00600946e+00 -1.10281676e-01 8.21876884e-01 1.80204481e-01
-5.57266772e-01 3.20164323e-01 -2.74321526e-01 6.04470551e-01
7.69783437e-01 -1.37193108e+00 5.19713879e-01 5.50326467e-01
-4.19496596e-02 4.12641406e-01 1.26192069e+00 -7.27280676e-01
-7.36367285e-01 -8.78001094e-01 1.48048806e+00 -9.02433097e-01
9.78292644e-01 -3.24783325e-01 -8.70054901e-01 8.06099892e-01
4.65496153e-01 -7.79419899e-01 1.01226664e+00 7.37120986e-01
-4.46500331e-01 3.27953070e-01 -6.17859900e-01 7.21031070e-01
9.22425210e-01 -3.14405620e-01 -1.22777700e+00 7.28731215e-01
6.98963821e-01 -4.80140120e-01 -4.37783271e-01 3.07941526e-01
5.51719785e-01 -8.93595219e-01 7.35472918e-01 -1.07204950e+00
1.38356054e+00 2.40847021e-01 5.07327132e-02 -1.30600119e+00
-1.37059897e-01 -2.73735285e-01 -3.25578034e-01 1.05254328e+00
8.29550266e-01 -4.26592708e-01 8.97009969e-01 3.48356903e-01
-3.69107604e-01 -1.12228072e+00 -6.61896884e-01 -3.84589911e-01
7.18662560e-01 -4.79729712e-01 3.88218820e-01 1.20769596e+00
3.74234319e-01 9.81209338e-01 -4.59012032e-01 -4.23282713e-01
4.23225522e-01 5.02382696e-01 4.91884321e-01 -1.61337972e+00
-1.08788796e-01 -7.15275884e-01 -3.86054665e-02 -6.40550554e-01
3.24785471e-01 -9.70935047e-01 -1.79945081e-01 -2.05839658e+00
3.04890543e-01 -1.81083187e-01 7.22834002e-03 7.95092463e-01
-1.76323786e-01 1.14843227e-01 -6.62439596e-03 2.69219726e-01
-3.21615756e-01 3.81120145e-01 1.19795597e+00 -3.99296761e-01
1.34391161e-02 2.33361825e-01 -1.00200379e+00 1.03950429e+00
1.09660196e+00 -5.25474787e-01 -3.04508775e-01 -4.30284083e-01
8.29905689e-01 -1.78858340e-01 3.00958395e-01 -6.14593148e-01
-1.42005086e-01 -1.81271717e-01 2.71772236e-01 -9.03037488e-01
2.76195407e-01 -3.34129572e-01 -4.57588255e-01 6.48137271e-01
-5.39822519e-01 4.19687815e-02 8.68864730e-03 2.78330952e-01
-2.96860784e-01 -9.21578780e-02 5.20316184e-01 -1.94850087e-01
-5.21404684e-01 -5.66899814e-02 -6.30169511e-01 2.56166041e-01
7.02604890e-01 -2.25080013e-01 -9.64189470e-01 -4.88330424e-01
-8.24857116e-01 3.82941931e-01 -1.20175667e-01 8.32197368e-01
5.10174751e-01 -1.10422838e+00 -1.00628674e+00 -3.17324817e-01
4.76123095e-02 -1.39243960e-01 -1.38988808e-01 9.29450035e-01
-2.75846630e-01 5.76250970e-01 -2.54121959e-01 -4.46904927e-01
-1.54660201e+00 3.44460577e-01 2.61174232e-01 -4.79923159e-01
-7.62250662e-01 7.29351282e-01 3.96991372e-02 -3.31070483e-01
-3.73965316e-02 -1.65526643e-01 -7.31064856e-01 6.59238517e-01
5.71114480e-01 -8.07610899e-03 2.83211797e-01 -5.14179647e-01
-3.07535678e-01 -7.72946551e-02 -2.45397732e-01 1.04608424e-01
1.64784873e+00 2.47664496e-01 -1.58724278e-01 8.53278160e-01
6.82223439e-01 -1.50833353e-01 -6.71375036e-01 -2.23543152e-01
3.61456126e-01 3.36502418e-02 -3.34934369e-02 -1.06605518e+00
-7.17620015e-01 1.21959567e+00 -6.28699139e-02 5.87902248e-01
3.55999202e-01 -7.45138759e-03 8.56873810e-01 3.49858612e-01
1.09393252e-02 -1.32016253e+00 3.72636378e-01 1.12670004e+00
1.16194642e+00 -1.45684016e+00 4.83327322e-02 -1.66059315e-01
-5.79303622e-01 1.15408504e+00 7.39285588e-01 4.16408330e-02
4.95817780e-01 1.77688107e-01 2.91086674e-01 -6.19609773e-01
-9.71209228e-01 -4.62940261e-02 2.40062803e-01 3.25047433e-01
1.22035730e+00 1.81899026e-01 -9.16734278e-01 7.62509584e-01
-7.44462252e-01 -3.62535059e-01 6.12669051e-01 7.34440327e-01
-8.50405991e-01 -1.22003424e+00 -1.85695618e-01 5.80708086e-01
-6.87937677e-01 -2.37958118e-01 -1.05972087e+00 9.02492464e-01
2.45548934e-01 1.16377556e+00 -1.81590289e-01 -3.74984086e-01
1.08410999e-01 4.11527038e-01 1.06140018e-01 -8.00214231e-01
-8.95240724e-01 -8.41506571e-02 8.61515820e-01 -2.06395775e-01
-4.02086347e-01 -8.00368905e-01 -1.23721802e+00 -7.64834404e-01
-1.64580837e-01 2.54830420e-01 4.41292137e-01 1.41070843e+00
-2.72115260e-01 7.18774617e-01 1.80887669e-01 -5.43784022e-01
-6.46636903e-01 -1.19201016e+00 -1.37086688e-02 1.95366725e-01
1.61010683e-01 -8.71925890e-01 -1.52049839e-01 -2.41924837e-01] | [8.836859703063965, 10.05069637298584] |
5205b6d4-cf1d-49e2-bc99-e7223e2c9959 | unbiased-multiple-instance-learning-for | 2303.12369 | null | https://arxiv.org/abs/2303.12369v1 | https://arxiv.org/pdf/2303.12369v1.pdf | Unbiased Multiple Instance Learning for Weakly Supervised Video Anomaly Detection | Weakly Supervised Video Anomaly Detection (WSVAD) is challenging because the binary anomaly label is only given on the video level, but the output requires snippet-level predictions. So, Multiple Instance Learning (MIL) is prevailing in WSVAD. However, MIL is notoriously known to suffer from many false alarms because the snippet-level detector is easily biased towards the abnormal snippets with simple context, confused by the normality with the same bias, and missing the anomaly with a different pattern. To this end, we propose a new MIL framework: Unbiased MIL (UMIL), to learn unbiased anomaly features that improve WSVAD. At each MIL training iteration, we use the current detector to divide the samples into two groups with different context biases: the most confident abnormal/normal snippets and the rest ambiguous ones. Then, by seeking the invariant features across the two sample groups, we can remove the variant context biases. Extensive experiments on benchmarks UCF-Crime and TAD demonstrate the effectiveness of our UMIL. Our code is provided at https://github.com/ktr-hubrt/UMIL. | ['Hanwang Zhang', 'Zhen Cui', 'Bin Luo', 'Qianru Sun', 'Zhongqi Yue', 'Hui Lv'] | 2023-03-22 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Lv_Unbiased_Multiple_Instance_Learning_for_Weakly_Supervised_Video_Anomaly_Detection_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Lv_Unbiased_Multiple_Instance_Learning_for_Weakly_Supervised_Video_Anomaly_Detection_CVPR_2023_paper.pdf | cvpr-2023-1 | ['video-anomaly-detection', 'multiple-instance-learning'] | ['computer-vision', 'methodology'] | [ 1.47300839e-01 -2.58453429e-01 -3.82751882e-01 -3.52034837e-01
-7.51156211e-01 -2.65596777e-01 3.69936377e-01 4.66339067e-02
-1.57250002e-01 5.72560906e-01 -1.11098378e-03 -1.66160643e-01
-7.30116665e-02 -5.34074008e-01 -6.88061833e-01 -9.66509700e-01
-1.10204376e-01 4.03375179e-01 3.00058693e-01 1.47573441e-01
1.16390027e-01 4.41680774e-02 -1.46948755e+00 5.53416967e-01
9.42966640e-01 1.40363610e+00 -3.03611010e-01 3.24013025e-01
-3.12747121e-01 9.42596972e-01 -4.85294104e-01 -3.88849884e-01
3.98585051e-01 -4.52173799e-01 -4.83316481e-01 1.77097261e-01
6.33626938e-01 -5.03360868e-01 -2.89292157e-01 1.23884344e+00
3.43890578e-01 -7.01164082e-02 6.22026801e-01 -1.81117737e+00
-2.96486199e-01 4.03713763e-01 -9.02002215e-01 5.21219313e-01
3.84433836e-01 3.26983422e-01 1.10680556e+00 -1.20100367e+00
3.46757412e-01 1.14102340e+00 4.74085480e-01 6.71207845e-01
-1.02126086e+00 -8.77919495e-01 8.40072751e-01 4.54535544e-01
-1.36787868e+00 -3.61920774e-01 7.45139360e-01 -4.92330730e-01
2.75148869e-01 3.35403085e-01 3.65106046e-01 1.45122612e+00
-1.84244946e-01 1.22379816e+00 8.18104446e-01 7.84096643e-02
3.31826776e-01 2.32027303e-02 2.65145481e-01 7.18898296e-01
4.85756427e-01 -3.19637567e-01 -3.89911950e-01 -3.53794426e-01
3.48073542e-01 3.95482242e-01 -3.13952237e-01 -4.52184916e-01
-1.03692615e+00 6.15238726e-01 6.34048283e-02 2.69028060e-02
-3.25147986e-01 -1.94859385e-01 6.85399294e-01 3.70021462e-01
5.62589824e-01 1.21253937e-01 -4.76762176e-01 -1.00662276e-01
-7.18042552e-01 4.24647838e-01 5.02790570e-01 7.83548772e-01
6.03571057e-01 6.08410984e-02 -6.56737447e-01 8.75712574e-01
2.44348615e-01 3.55069846e-01 4.76749271e-01 -5.84212244e-01
6.43863738e-01 7.59075880e-01 1.07158147e-01 -1.26949048e+00
-4.59455512e-02 -3.90864342e-01 -8.23485553e-01 1.22805662e-01
4.90112573e-01 -2.59072632e-01 -9.39587891e-01 1.63165545e+00
4.91294503e-01 7.92487025e-01 -1.19121507e-01 1.06810558e+00
7.34211743e-01 7.14071274e-01 1.05258234e-01 -2.79742241e-01
1.02585471e+00 -9.40688848e-01 -6.63614154e-01 -3.89327288e-01
7.16044009e-01 -4.37871546e-01 1.01403379e+00 4.80310768e-01
-6.90817714e-01 -1.62902206e-01 -9.85011220e-01 4.22387898e-01
-7.33912960e-02 7.67820626e-02 3.58971179e-01 3.29194725e-01
-3.42570543e-01 3.88327032e-01 -7.18248248e-01 4.83623531e-04
8.79590809e-01 -8.47080499e-02 -2.71337539e-01 -3.52341145e-01
-1.06641197e+00 3.66203725e-01 4.40935940e-01 2.24726200e-01
-9.74903047e-01 -6.12624049e-01 -8.70694339e-01 -1.78543806e-01
8.46062899e-01 -2.22900912e-01 1.07878089e+00 -1.36446452e+00
-8.09898913e-01 7.35938489e-01 -3.39034140e-01 -4.74734604e-01
1.00222003e+00 -3.38967919e-01 -6.04166865e-01 -4.50818501e-02
2.36264542e-01 1.24014646e-01 1.19025517e+00 -1.22072780e+00
-9.06234682e-01 -3.39003652e-01 -1.46447480e-01 1.83955669e-01
-1.91256016e-01 -1.09735548e-01 -5.16064405e-01 -6.55829012e-01
3.15979779e-01 -5.71004510e-01 2.72117667e-02 -6.39553666e-02
-6.87778234e-01 -3.65289867e-01 1.06817520e+00 -7.18873858e-01
1.55330276e+00 -2.47037172e+00 -4.68295589e-02 4.58464622e-01
3.65506530e-01 3.55240703e-01 -6.73734397e-02 -1.23000339e-01
-2.59597689e-01 1.38049141e-01 -3.25594276e-01 -2.24612400e-01
-9.30190608e-02 2.09721446e-01 -4.23257411e-01 3.84173125e-01
3.95356715e-01 3.27757478e-01 -1.12907112e+00 -4.93220389e-01
6.73806295e-02 -1.82448342e-01 -6.34995520e-01 3.02281648e-01
-1.95028469e-01 3.98056209e-01 -7.48131692e-01 1.12931156e+00
8.02130997e-01 -1.03795126e-01 -1.13826305e-01 -1.65145651e-01
8.69275853e-02 7.64638111e-02 -1.51560152e+00 1.08588755e+00
9.51967314e-02 3.68278861e-01 -1.17634103e-01 -1.09439051e+00
7.84617305e-01 1.67352140e-01 4.91083205e-01 -4.81212854e-01
6.99688308e-03 4.57567722e-01 -5.55275232e-02 -8.18705440e-01
1.87533259e-01 1.63043365e-01 2.59229671e-02 2.02207804e-01
4.67936136e-02 5.57093799e-01 2.00652808e-01 3.09881508e-01
1.07487619e+00 1.00139424e-01 2.71644056e-01 1.94609046e-01
6.46670699e-01 -2.62923688e-01 1.14584565e+00 1.01787913e+00
-6.21277869e-01 7.52116263e-01 1.06318974e+00 -5.43419719e-01
-9.26366746e-01 -1.25857556e+00 -1.19021229e-01 9.77762282e-01
2.40457624e-01 -3.74089122e-01 -6.30159020e-01 -1.24971259e+00
1.48548400e-02 6.33333802e-01 -4.84276652e-01 -4.08851355e-01
-3.76624197e-01 -7.45755076e-01 4.35668230e-01 3.33123058e-01
5.53181231e-01 -9.92673218e-01 3.66033874e-02 -6.49017841e-02
-2.93736100e-01 -1.02549303e+00 -4.22277361e-01 -6.13527074e-02
-5.45307636e-01 -1.20009184e+00 -4.39109653e-01 -5.47874987e-01
8.30711126e-01 1.03775010e-01 8.94202769e-01 2.05381259e-01
-9.74816084e-02 6.78304657e-02 -6.06045604e-01 -4.42707092e-01
-1.79294452e-01 -1.96869269e-01 3.53077620e-01 6.16493523e-01
7.19852209e-01 -3.75966251e-01 -5.00231326e-01 3.96469474e-01
-8.06839824e-01 -2.24646881e-01 5.41501164e-01 8.86286616e-01
8.62804532e-01 -3.35528664e-02 7.16298640e-01 -9.91976738e-01
3.49106401e-01 -1.04809439e+00 -3.22456717e-01 -1.89545061e-02
-3.90608490e-01 -1.72273427e-01 6.15937054e-01 -5.41916549e-01
-7.85240710e-01 -7.17974305e-02 -1.70382574e-01 -8.39943647e-01
-5.10389090e-01 3.10788363e-01 -4.23413426e-01 3.62235248e-01
5.47568798e-01 3.18375677e-01 -2.89947577e-02 -3.47701848e-01
-2.53831476e-01 6.08622730e-01 5.04398227e-01 -5.11245608e-01
8.63406897e-01 2.98161626e-01 -4.15424854e-01 -7.14218140e-01
-1.11690164e+00 -5.05928874e-01 -2.19443202e-01 -3.03251296e-01
6.37779295e-01 -8.81781280e-01 -1.11426316e-01 7.66000211e-01
-6.29244387e-01 -5.24575859e-02 -3.24879795e-01 3.51868331e-01
-1.88870549e-01 4.48013961e-01 -2.61990815e-01 -8.53667557e-01
-6.47797287e-02 -1.20908117e+00 9.26776230e-01 2.77416080e-01
-1.57296315e-01 -5.25057852e-01 -9.14275125e-02 2.58778751e-01
-7.75023401e-02 3.91164273e-01 7.81241298e-01 -1.37081695e+00
-4.26124424e-01 -6.20789826e-01 -1.88929334e-01 5.94610274e-01
1.32922679e-01 1.97909385e-01 -1.01490712e+00 -1.75270081e-01
-1.93778753e-01 -2.39474595e-01 1.06241953e+00 3.38779807e-01
1.74873805e+00 -4.59678620e-01 -1.91134200e-01 5.94741762e-01
1.14240623e+00 8.19744617e-02 5.10113239e-01 4.49048966e-01
8.29035521e-01 1.12961411e-01 9.38144863e-01 5.16745031e-01
1.46305233e-01 4.35338289e-01 7.02100813e-01 1.80805326e-01
3.52613211e-01 -3.97348136e-01 6.78406596e-01 3.06791663e-01
-5.25598042e-02 -2.00358003e-01 -7.00377882e-01 5.71527123e-01
-2.12360120e+00 -1.16373873e+00 -7.95450062e-02 2.29750776e+00
5.33221424e-01 5.08298159e-01 2.69047976e-01 2.75240868e-01
9.64266539e-01 3.75760108e-01 -7.40777254e-01 -1.32329747e-01
-5.90158030e-02 -3.27388316e-01 1.70063943e-01 1.57212853e-01
-1.46769214e+00 6.72121227e-01 4.45426035e+00 1.11405599e+00
-8.30859423e-01 -6.49572909e-02 9.62409914e-01 -4.62785155e-01
-9.98914763e-02 -1.09626532e-01 -8.11110735e-01 9.57992852e-01
3.70852500e-01 1.20384281e-03 1.59117877e-01 1.19656408e+00
2.81629026e-01 6.98941797e-02 -1.21901321e+00 1.01891661e+00
1.52784060e-06 -9.93901908e-01 3.20726931e-01 -2.80444384e-01
6.12855673e-01 -1.19823776e-01 1.37736434e-02 6.30634308e-01
-1.77895442e-01 -6.93114460e-01 7.67556727e-01 4.23678815e-01
5.07710993e-01 -8.12425613e-01 1.00425553e+00 4.38814491e-01
-1.06335223e+00 -4.01056707e-01 -3.67988080e-01 -1.72200724e-02
-1.80365622e-01 8.80946219e-01 -6.16191745e-01 4.55598265e-01
8.72777402e-01 9.37815070e-01 -5.15603840e-01 1.17868316e+00
-1.04069382e-01 8.22820842e-01 -2.28681847e-01 2.02107847e-01
2.67212898e-01 -3.29191238e-01 9.93611574e-01 1.07090771e+00
3.09088916e-01 -3.29545662e-02 4.35380697e-01 5.00804245e-01
-7.36880675e-02 1.84950694e-01 -7.03522325e-01 1.76058203e-01
5.37821651e-01 1.16351140e+00 -3.52980524e-01 -3.36135715e-01
-5.76254845e-01 9.19281900e-01 2.01712385e-01 4.94234264e-01
-9.40626085e-01 -1.99146807e-01 1.00603867e+00 2.77794395e-02
2.03439191e-01 3.67739975e-01 -1.83365390e-01 -1.50081706e+00
3.87424886e-01 -1.02773225e+00 8.51328433e-01 -4.22615707e-01
-1.57977986e+00 3.55215281e-01 -5.77062778e-02 -1.64872873e+00
8.45821649e-02 -6.51461959e-01 -9.63062763e-01 5.10831892e-01
-1.32830286e+00 -7.48872995e-01 -4.25376773e-01 7.42625833e-01
6.90763116e-01 -2.49368116e-01 3.17478448e-01 5.20743370e-01
-1.11963892e+00 9.75365996e-01 -3.01725604e-02 4.94013339e-01
7.39498675e-01 -1.18056107e+00 3.38470004e-02 1.02008808e+00
-1.58896625e-01 7.55407438e-02 7.43744552e-01 -6.94614470e-01
-8.76013279e-01 -1.45297348e+00 4.85221446e-01 -3.39159787e-01
7.27901399e-01 -2.19228074e-01 -1.26520646e+00 8.61038029e-01
-4.35015321e-01 2.80027241e-01 5.37748992e-01 -4.21879925e-02
-3.85554612e-01 -3.21527213e-01 -1.23151207e+00 8.55497181e-01
1.05026436e+00 -2.25045130e-01 -5.48282564e-01 4.31588918e-01
5.97681344e-01 -4.56349880e-01 -2.76174724e-01 5.34705997e-01
2.82694936e-01 -9.92616951e-01 8.22747827e-01 -8.54634881e-01
5.89182556e-01 -4.19253469e-01 -1.99294999e-01 -1.28196847e+00
-1.15955688e-01 -1.20402358e-01 -5.53425372e-01 1.43251872e+00
5.48438668e-01 -7.82499969e-01 5.69944382e-01 4.91024107e-01
-2.35967785e-01 -1.01320183e+00 -9.69389856e-01 -7.15542555e-01
-4.40446168e-01 -6.78280413e-01 6.11264527e-01 1.10541916e+00
-1.09339587e-01 -4.69414555e-02 -7.56896079e-01 4.77766067e-01
7.10959017e-01 -5.38148843e-02 6.71730936e-01 -1.14698195e+00
-1.78965539e-01 -4.18793827e-01 -5.91159582e-01 -8.11281383e-01
6.18683621e-02 -7.54736781e-01 6.94593042e-02 -8.97051096e-01
2.88235337e-01 -3.58030528e-01 -5.19783914e-01 4.90779757e-01
-5.94057858e-01 1.32534131e-02 -1.89150646e-01 1.23513997e-01
-9.33592856e-01 4.23715711e-01 8.96713734e-01 -1.09259777e-01
-1.54329330e-01 3.94804567e-01 -6.20019317e-01 1.26270700e+00
8.93542528e-01 -4.73817199e-01 -2.27639735e-01 -2.25077733e-01
1.54930487e-01 -4.11458910e-01 4.00712967e-01 -9.60246384e-01
-4.17203307e-02 -2.20281184e-01 5.59253335e-01 -5.94807386e-01
9.11783613e-03 -8.28519821e-01 -3.71666610e-01 3.61010790e-01
-4.32373315e-01 -1.82104215e-01 -1.02233082e-01 8.34585190e-01
-2.18018100e-01 -2.67535239e-01 6.77185714e-01 -2.19631642e-02
-9.73717093e-01 8.43959868e-01 -2.10454375e-01 3.70432049e-01
1.16608644e+00 -1.42384917e-01 -2.74312913e-01 -3.00933659e-01
-8.01199377e-01 7.24387109e-01 2.61549592e-01 4.06396925e-01
7.29690254e-01 -1.53426492e+00 -8.28321695e-01 3.53127450e-01
4.64382738e-01 2.25885898e-01 4.44462746e-01 9.51447010e-01
-1.54859379e-01 -2.94163972e-01 7.49729499e-02 -8.35045218e-01
-1.24439216e+00 4.70421731e-01 3.79639894e-01 -1.68781906e-01
-5.97364187e-01 7.74843037e-01 2.08292425e-01 -3.96716535e-01
4.40656006e-01 -1.18595555e-01 -2.90401995e-01 9.30604786e-02
7.85922647e-01 4.55196202e-01 -4.45419699e-02 -4.96860385e-01
-4.15994972e-01 2.23440692e-01 -2.51675934e-01 5.22644401e-01
1.04697180e+00 -6.50872812e-02 1.13468394e-01 6.06504440e-01
9.31725025e-01 9.78146959e-03 -1.38856816e+00 -3.78529042e-01
9.53242276e-03 -8.59930992e-01 -1.43824577e-01 -4.75178123e-01
-1.08054864e+00 5.98595083e-01 6.14112556e-01 3.13161045e-01
1.13714254e+00 -3.50683518e-02 6.53303385e-01 3.73037130e-01
8.12790319e-02 -1.11795652e+00 1.21887527e-01 4.11643535e-01
6.88026130e-01 -1.58230054e+00 -1.60420805e-01 -2.07645401e-01
-1.03455245e+00 7.54282534e-01 1.26217377e+00 -2.13756353e-01
3.50986600e-01 -1.45060625e-02 -1.83901176e-01 -6.55021667e-02
-6.83150649e-01 -1.03318342e-03 2.20578313e-01 3.87301266e-01
1.46855889e-02 2.03404240e-02 -1.62361920e-01 8.21791828e-01
3.32011223e-01 -2.20842972e-01 4.26003337e-01 7.17553854e-01
-5.61978638e-01 -5.76722324e-01 -3.80955875e-01 1.02229607e+00
-6.89357340e-01 -8.94203491e-04 -2.41918147e-01 5.67588925e-01
3.00708413e-01 6.73708439e-01 2.42100492e-01 -5.06751835e-01
4.09352809e-01 4.78950411e-01 -1.34538427e-01 -4.15216446e-01
-3.43447900e-03 -8.13407078e-03 1.04704320e-01 -7.74485409e-01
2.92631630e-02 -9.10683393e-01 -1.13806319e+00 -1.87798202e-01
-1.51475109e-02 1.36737391e-01 7.90076237e-03 1.14791834e+00
2.43830577e-01 4.14728284e-01 9.80629086e-01 -5.83058059e-01
-4.50796783e-01 -8.34028423e-01 -4.69764411e-01 6.14484847e-01
7.24205971e-01 -8.03433955e-01 -7.85432577e-01 -2.19029590e-01] | [7.817310333251953, 1.6572784185409546] |
1cf89cf0-5940-48dc-b012-746344a6a73f | graph-scaling-cut-with-l1-norm-for | 1709.02920 | null | http://arxiv.org/abs/1709.02920v1 | http://arxiv.org/pdf/1709.02920v1.pdf | Graph Scaling Cut with L1-Norm for Classification of Hyperspectral Images | In this paper, we propose an L1 normalized graph based dimensionality
reduction method for Hyperspectral images, called as L1-Scaling Cut (L1-SC).
The underlying idea of this method is to generate the optimal projection matrix
by retaining the original distribution of the data. Though L2-norm is generally
preferred for computation, it is sensitive to noise and outliers. However,
L1-norm is robust to them. Therefore, we obtain the optimal projection matrix
by maximizing the ratio of between-class dispersion to within-class dispersion
using L1-norm. Furthermore, an iterative algorithm is described to solve the
optimization problem. The experimental results of the HSI classification
confirm the effectiveness of the proposed L1-SC method on both noisy and
noiseless data. | ['S. L. Happy', 'Ramanarayan Mohanty', 'Aurobinda Routray'] | 2017-09-09 | null | null | null | null | ['classification-of-hyperspectral-images'] | ['computer-vision'] | [ 4.50561315e-01 -1.59704193e-01 -7.49927759e-02 -1.47805765e-01
-3.20763290e-01 -3.97599161e-01 1.23898871e-01 -1.28989905e-01
-6.46790415e-02 4.74008292e-01 1.81636557e-01 -3.74926664e-02
-8.19436431e-01 -9.41453278e-01 -1.21770218e-01 -1.10494244e+00
2.10981011e-01 -2.12046415e-01 -2.66348153e-01 -3.43706235e-02
2.57593215e-01 6.15958631e-01 -1.36259437e+00 -1.73962057e-01
1.29416096e+00 9.22646821e-01 1.72480226e-01 2.47273400e-01
8.66112337e-02 2.55213916e-01 -3.37717116e-01 1.46110445e-01
7.27145314e-01 -9.32478666e-01 -5.29800832e-01 7.63075948e-01
1.00832947e-01 -2.56213807e-02 -2.21096903e-01 1.76801288e+00
3.86075318e-01 4.87147480e-01 8.06821585e-01 -1.21729279e+00
-6.18092418e-01 3.28207880e-01 -9.60167050e-01 -1.96639393e-02
1.32412627e-01 -1.86266407e-01 8.99675727e-01 -9.44117367e-01
6.27510071e-01 1.02287912e+00 4.34464633e-01 -4.58200909e-02
-1.39843059e+00 -4.65489745e-01 -4.45071049e-02 2.62978762e-01
-1.78877032e+00 -5.87081909e-02 1.00319016e+00 -3.74833584e-01
3.13390642e-01 3.47991467e-01 6.43107653e-01 2.73419648e-01
-1.12428190e-02 4.53045368e-01 1.27881837e+00 -4.99431789e-01
2.11596131e-01 -1.10024966e-01 2.90856630e-01 4.29885268e-01
6.73160017e-01 -9.91342589e-02 -1.40001789e-01 -2.28584826e-01
3.13112855e-01 5.95805012e-02 -6.93461239e-01 -5.37914932e-01
-7.91279733e-01 9.12055612e-01 4.05857742e-01 1.08219221e-01
-4.95238572e-01 -6.86665893e-01 1.31221250e-01 1.07947640e-01
4.08406198e-01 2.15130568e-01 2.22583205e-01 4.27277893e-01
-9.34326470e-01 -4.52707857e-02 4.19281214e-01 8.33233714e-01
8.66727293e-01 1.69449165e-01 7.61969909e-02 1.13420975e+00
4.24933493e-01 6.94356143e-01 3.09858412e-01 -6.96651161e-01
4.41567361e-01 9.05714869e-01 -1.55085132e-01 -1.59251022e+00
-5.56052446e-01 -6.06721818e-01 -1.18866241e+00 2.55129278e-01
5.44206873e-02 -2.13443339e-01 -7.06112742e-01 1.45998573e+00
3.55064332e-01 1.97699293e-01 3.42845559e-01 1.12633622e+00
5.19784331e-01 7.75549412e-01 -2.14444712e-01 -7.00951099e-01
7.38934219e-01 -5.30422628e-01 -9.08128679e-01 1.31479278e-02
4.51173544e-01 -6.75255358e-01 9.55185711e-01 2.92875379e-01
-5.25748968e-01 -2.28734225e-01 -1.03567445e+00 4.26681757e-01
-7.23945722e-02 3.12466174e-01 2.22006306e-01 7.41066158e-01
-5.49076617e-01 3.17245007e-01 -5.35100460e-01 -5.79709649e-01
2.67626643e-01 1.14610143e-01 -3.85520726e-01 -3.54266047e-01
-7.97991753e-01 3.98225069e-01 7.36848772e-01 1.92301914e-01
-3.31718504e-01 -4.72274005e-01 -6.21387482e-01 9.94323641e-02
5.38232446e-01 -9.57174599e-03 3.56782079e-01 -5.73799908e-01
-1.25732350e+00 4.41256225e-01 -1.09867588e-01 2.03366503e-02
1.71410620e-01 2.27538615e-01 -5.53333223e-01 2.43149683e-01
2.60760337e-02 -7.63408244e-02 8.75387549e-01 -1.46054649e+00
-3.95283103e-01 -5.97753048e-01 -4.01737571e-01 4.60434109e-01
-6.63113713e-01 -3.44676703e-01 -5.35071418e-02 -6.19805455e-01
9.98338342e-01 -1.13545310e+00 -1.19422384e-01 -1.58684283e-01
-6.40967309e-01 1.33690268e-01 1.37090874e+00 -7.69907773e-01
1.43251479e+00 -2.40740228e+00 1.35999203e-01 8.31277549e-01
1.15595169e-01 3.53743076e-01 -2.64245152e-01 4.68389511e-01
-3.73088896e-01 -2.68006255e-03 -7.89387584e-01 2.90891171e-01
-2.42032915e-01 2.10637804e-02 -1.65745273e-01 7.63418555e-01
-5.22184819e-02 2.46482536e-01 -8.04026723e-01 -2.38898322e-01
3.01224142e-01 3.41535777e-01 -2.77814865e-01 4.39504571e-02
3.64559531e-01 2.62317896e-01 -2.71969020e-01 6.96661890e-01
1.29744971e+00 1.00310184e-02 3.63859564e-01 -6.56777978e-01
-2.31256321e-01 -4.18860853e-01 -1.75905621e+00 1.25770032e+00
2.22483918e-01 4.08513248e-01 4.57950860e-01 -1.24525344e+00
1.16320026e+00 1.32295877e-01 8.03879082e-01 -3.14075291e-01
1.81987390e-01 1.40353099e-01 4.49906923e-02 -4.97403890e-01
2.48168647e-01 -3.71059000e-01 4.12745774e-01 4.25053656e-01
-3.30761611e-01 -2.50325203e-01 5.12161374e-01 1.19981825e-01
5.45890868e-01 -2.93571979e-01 5.95923722e-01 -5.32053649e-01
9.10508752e-01 9.49328393e-02 8.90945554e-01 2.41105825e-01
-3.38485867e-01 5.80321670e-01 5.21717966e-01 -2.11950783e-02
-8.31643164e-01 -7.15864897e-01 -3.64443481e-01 3.71679783e-01
4.04435724e-01 -2.35035017e-01 -7.15151966e-01 -5.81793487e-01
-1.25366017e-01 8.11713576e-01 -2.19704211e-01 -2.49937028e-01
-7.22415522e-02 -1.38568985e+00 1.84653938e-01 -3.40845771e-02
8.04240584e-01 -5.09653211e-01 -6.36974722e-02 7.95543939e-02
-2.32476145e-01 -9.21384931e-01 -4.82563883e-01 -1.69667557e-01
-9.69507813e-01 -1.34043968e+00 -3.72444630e-01 -5.81841767e-01
1.06793845e+00 9.17327285e-01 3.06972355e-01 -9.79417786e-02
-3.36333483e-01 8.86698663e-02 -5.24681628e-01 -2.70288140e-01
-7.42921233e-02 -8.85748640e-02 2.08453268e-01 5.35647511e-01
3.60025018e-01 -5.59434652e-01 -5.36969900e-01 3.74045283e-01
-1.11692047e+00 -2.14044541e-01 4.82059509e-01 7.71196842e-01
8.23505104e-01 1.00871980e+00 2.78774917e-01 -7.37652779e-01
1.03473437e+00 -2.82546639e-01 -7.66991615e-01 2.56646544e-01
-1.05609214e+00 -2.70236105e-01 7.41761267e-01 -1.19405314e-01
-1.03582871e+00 2.97761887e-01 4.38028246e-01 -4.29001629e-01
-1.58988894e-03 7.42539525e-01 -4.17885661e-01 -3.94969463e-01
5.42438030e-01 5.09119987e-01 9.65010524e-02 -3.97964925e-01
3.68223339e-01 8.19523871e-01 3.39751959e-01 -2.30079770e-01
1.05492175e+00 5.41993320e-01 4.20089811e-01 -1.34061992e+00
-7.78210044e-01 -5.39398611e-01 -7.61169851e-01 -2.64593691e-01
7.01961994e-01 -5.77413917e-01 -4.97996569e-01 5.21965384e-01
-6.27133489e-01 3.37049305e-01 -2.31918082e-01 8.20137978e-01
-1.21978588e-01 6.87100112e-01 -4.02876809e-02 -9.13174152e-01
-2.91232616e-01 -1.05314553e+00 4.00026441e-01 3.71379644e-01
3.00845474e-01 -8.62527192e-01 9.12046731e-02 2.70972073e-01
1.31965101e-01 4.66713160e-01 1.03128481e+00 -3.16512138e-01
-1.95043683e-01 -2.64103740e-01 -4.89301473e-01 6.80678248e-01
5.27318418e-01 1.75964057e-01 -5.73168516e-01 -5.64183474e-01
1.60630584e-01 6.94507882e-02 5.75468004e-01 5.22091985e-01
1.15923512e+00 -3.23437154e-01 -1.48482829e-01 9.05979693e-01
1.92079759e+00 3.85310650e-01 5.48386335e-01 2.17037201e-01
8.58182967e-01 5.91886759e-01 6.45144999e-01 5.95679224e-01
-3.55575085e-02 1.89238340e-01 4.62940246e-01 -1.78169817e-01
2.35000141e-02 9.15578939e-03 -5.71710020e-02 1.09661043e+00
-9.65274125e-02 -2.05444649e-01 -8.59658539e-01 3.77933621e-01
-1.69978499e+00 -9.82896984e-01 -5.68736732e-01 2.29790425e+00
2.16213644e-01 -2.61269122e-01 -1.30184919e-01 5.41599691e-01
9.66445208e-01 3.13401222e-01 -6.19283259e-01 -1.24878744e-02
-5.31213522e-01 -2.41251394e-01 6.72611833e-01 6.43991232e-01
-9.86413062e-01 5.66209793e-01 6.24611568e+00 7.06088424e-01
-1.20075595e+00 -2.70348996e-01 2.40976393e-01 2.76726168e-02
-2.03714833e-01 -5.14258107e-04 -4.40625638e-01 4.78552341e-01
1.80188328e-01 -5.73480248e-01 6.91510320e-01 7.05148995e-01
6.47526205e-01 -1.41912282e-01 -2.29419395e-01 1.14765155e+00
2.31681928e-01 -8.11718524e-01 1.86507538e-01 2.14682057e-01
1.04215634e+00 -3.07938814e-01 -1.58519745e-01 -2.83639729e-01
-1.27083957e-01 -6.43772244e-01 2.13526368e-01 3.63121450e-01
7.66626298e-01 -1.03262293e+00 6.57454014e-01 3.43573958e-01
-1.30501306e+00 -2.76022792e-01 -6.28619790e-01 1.38046294e-01
5.00565320e-02 1.07935560e+00 -4.49099422e-01 9.11182821e-01
4.73027289e-01 9.52218354e-01 -4.13954943e-01 1.12770307e+00
-3.08639288e-01 4.87383991e-01 -2.85291642e-01 3.50456804e-01
2.45373443e-01 -1.35723579e+00 9.27030087e-01 8.01845253e-01
6.88413262e-01 5.16394436e-01 4.25062209e-01 5.87806165e-01
-3.28902565e-02 4.71569031e-01 -7.74695754e-01 -2.65000165e-01
5.56884050e-01 1.22012758e+00 -8.14933836e-01 -2.59276181e-02
-3.47502977e-01 7.27510989e-01 1.82246920e-02 5.85754633e-01
-4.27709162e-01 -8.75657320e-01 6.47417724e-01 -2.25137025e-02
1.17693424e-01 -3.16714525e-01 -4.66788560e-01 -9.17315304e-01
7.96864480e-02 -9.66019154e-01 5.38096547e-01 -6.76787078e-01
-1.20891106e+00 5.48762441e-01 6.83915317e-02 -1.50032759e+00
4.38801080e-01 -6.41828656e-01 -6.29651427e-01 7.35281467e-01
-1.54487109e+00 -7.63582110e-01 -7.59323716e-01 5.54696083e-01
1.54161125e-01 -2.49028996e-01 6.26078427e-01 2.22533762e-01
-1.07582724e+00 1.79085955e-01 6.90951169e-01 -6.85406849e-02
4.06184733e-01 -9.39183593e-01 -5.27938604e-01 1.32691574e+00
-2.65663147e-01 4.54097033e-01 5.67614973e-01 -7.36765802e-01
-1.28228188e+00 -1.08531201e+00 4.67717916e-01 5.63260257e-01
5.81691146e-01 1.84515730e-01 -9.50578451e-01 3.31730783e-01
-1.15436643e-01 -9.18724164e-02 8.57740045e-01 -3.06614697e-01
-1.10581942e-01 -3.51884633e-01 -1.39895725e+00 4.58524257e-01
8.52616131e-01 -4.10484761e-01 -2.45297983e-01 7.90049970e-01
3.54439318e-01 -8.56358409e-02 -1.14042974e+00 5.10544896e-01
2.36500993e-01 -9.09717560e-01 8.38997543e-01 -2.21405864e-01
1.45847782e-01 -7.46831298e-01 -3.83744895e-01 -1.54383862e+00
-7.93084443e-01 -4.20804024e-01 3.32648605e-01 1.08990228e+00
2.51480997e-01 -8.06489646e-01 7.95276761e-01 3.50944161e-01
2.29645818e-02 -4.16273355e-01 -6.41805410e-01 -1.09797132e+00
-2.72161961e-01 -2.27334231e-01 6.53693140e-01 1.27900386e+00
1.56086273e-02 2.04403102e-01 -4.10992175e-01 5.80075622e-01
1.22981024e+00 1.94435567e-01 4.99410421e-01 -1.38144374e+00
1.91136271e-01 -3.45841229e-01 -4.47749436e-01 -4.75827605e-01
1.13676578e-01 -1.04697800e+00 3.06162369e-02 -1.73642623e+00
1.70040101e-01 -2.15377167e-01 -2.19902292e-01 2.12389052e-01
-3.31902891e-01 2.01584890e-01 2.26826623e-01 5.02841771e-01
8.89175087e-02 7.78168201e-01 1.40630054e+00 -1.68122619e-01
-5.60400307e-01 -9.90433246e-02 -7.15193689e-01 4.90381658e-01
9.19569254e-01 -6.07688844e-01 -7.21765995e-01 -2.46323377e-01
-1.04041547e-01 -2.39577368e-01 -1.90018743e-01 -9.68455076e-01
1.15867920e-01 -5.71705341e-01 1.17388718e-01 -7.54606009e-01
1.55924171e-01 -1.11107075e+00 2.72305101e-01 3.89369905e-01
-9.08637643e-02 -3.08151186e-01 -1.08646058e-01 6.36316895e-01
-3.20507973e-01 -4.05723721e-01 1.13332379e+00 2.71673538e-02
-5.33448458e-01 4.14955765e-01 -2.20641896e-01 -7.58151114e-02
1.16967118e+00 -4.33766574e-01 -3.03758055e-01 -2.37412736e-01
-6.52471602e-01 1.56506851e-01 5.40317655e-01 -1.17886595e-01
7.02984810e-01 -1.48567259e+00 -9.73805010e-01 5.23639381e-01
2.37044156e-01 -1.81900412e-01 1.96824417e-01 9.29542422e-01
-5.88895202e-01 3.13004673e-01 -1.71440378e-01 -5.97168386e-01
-1.45953679e+00 4.44992274e-01 2.34055281e-01 1.10357583e-01
-6.58980906e-01 5.53949177e-01 1.34090837e-02 -5.97720325e-01
-1.75009131e-01 1.04488350e-01 -3.55032742e-01 1.73846379e-01
5.66651642e-01 9.18535590e-01 7.84706995e-02 -9.15129244e-01
-2.62868524e-01 9.10639405e-01 3.38167071e-01 -8.31418950e-03
1.44243968e+00 -2.96846420e-01 -7.08129466e-01 8.68015923e-04
1.33340752e+00 -1.10469155e-01 -9.90151465e-01 -2.13531196e-01
-1.09175086e-01 -9.35475886e-01 4.55247849e-01 -1.43034905e-01
-1.21676147e+00 5.75333655e-01 6.72507405e-01 3.70325714e-01
1.50905049e+00 -7.73423493e-01 3.88616204e-01 4.88762051e-01
-4.66870777e-02 -1.34362173e+00 -2.00664371e-01 3.77677530e-01
7.87500858e-01 -9.86915708e-01 5.77269435e-01 -9.04457510e-01
-5.46399713e-01 1.09468818e+00 5.66500306e-01 -5.86204454e-02
9.03557658e-01 -1.11829437e-01 1.36350572e-01 -3.34279686e-01
2.76315529e-02 -2.66111523e-01 2.64622569e-01 7.28661120e-01
1.21819578e-01 1.80527821e-01 -7.65756905e-01 -4.15399894e-02
-1.37836695e-01 -2.09856808e-01 7.21213758e-01 8.17671895e-01
-5.49640298e-01 -8.65694225e-01 -8.64928424e-01 6.90952539e-01
1.00384802e-01 2.74564862e-01 -4.94912833e-01 5.74203491e-01
5.53387962e-02 1.24836230e+00 -2.95687467e-01 -5.24233222e-01
5.92255831e-01 6.26012757e-02 1.29677966e-01 -4.67848152e-01
2.45339036e-01 2.91129917e-01 -3.47298950e-01 -3.23371023e-01
-5.74848771e-01 -6.93551779e-01 -1.21288526e+00 -2.84778386e-01
-6.46851838e-01 1.87599778e-01 7.71168888e-01 7.37979650e-01
1.75134063e-01 2.55888164e-01 1.12727630e+00 -5.24591565e-01
-7.08474815e-01 -8.33518147e-01 -1.32549620e+00 5.29655397e-01
-4.46813963e-02 -5.60624421e-01 -7.90020287e-01 4.36134785e-02] | [10.020586013793945, -1.9113413095474243] |
5621ee5c-038e-4a1f-8d9e-6d5cda5a63f1 | a-robust-panel-extraction-method-for-manga | null | null | http://visal.cs.cityu.edu.hk/static/pubs/conf/mm14-panels.pdf | http://visal.cs.cityu.edu.hk/static/pubs/conf/mm14-panels.pdf | A Robust Panel Extraction Method for Manga | Automatically extracting frames/panels from digital comic pages is crucial for techniques that facilitate comic reading on mobile devices with limited display areas. However, automatic panel extraction for manga, i.e., Japanese comics, can be especially challenging, largely because of its complex panel layout design mixed with various visual symbols throughout the page. In this paper, we propose a robust method for automatically extracting panels from digital manga pages. Our method first extracts the panel block by closing open panels and identifying a page background mask. It then performs a recursive binary splitting to partition the panel block into a set of sub-blocks, where an optimal splitting line at each recursive level is determined adaptively. Finally, it recovers accurate panel shapes from the computed subblocks. Our experiments show that the proposed method can robustly segment panels on the manga pages with various styles. | ['Rynson W. H. Lau', 'Ying Cao', 'Xufang Pang', 'and Antoni B. Chan'] | 2014-01-01 | null | null | null | video-image-and-sound-analysis-lab-visal-at | ['layout-design'] | ['computer-vision'] | [ 4.72370982e-01 -2.69219220e-01 -7.35968500e-02 2.99325645e-01
-5.75111568e-01 -1.05517447e+00 1.68700218e-01 -1.99196324e-01
3.74212027e-01 4.29687053e-01 6.62799701e-02 -6.44199133e-01
1.77315488e-01 -6.05355442e-01 -5.36820233e-01 -5.74835837e-01
4.74280357e-01 4.53968309e-02 6.31635427e-01 2.66246498e-01
3.65228921e-01 6.70307577e-01 -1.39985120e+00 5.85151553e-01
1.31436241e+00 8.81124556e-01 4.22033429e-01 8.59286010e-01
-3.23637635e-01 6.38572752e-01 -6.81394577e-01 -5.22203803e-01
1.66488782e-01 -6.10536933e-01 -2.60779023e-01 6.88419640e-01
5.19584239e-01 -6.05562449e-01 -2.12444693e-01 1.16584265e+00
4.39312309e-02 -4.61473256e-01 7.94700861e-01 -8.38954687e-01
-2.31166407e-01 4.16432798e-01 -1.14502966e+00 -2.88602024e-01
3.39985669e-01 -6.29913360e-02 7.23696291e-01 -9.52914000e-01
6.88943207e-01 9.37563956e-01 3.61989945e-01 -6.46578893e-02
-1.03983283e+00 -6.90571487e-01 1.40076727e-01 -1.22000724e-01
-1.42026043e+00 -3.91204089e-01 1.10017061e+00 -5.22715747e-01
1.21244594e-01 6.79269969e-01 8.37634981e-01 4.89962518e-01
1.45599961e-01 9.66534853e-01 1.40877974e+00 -5.76379120e-01
1.94471166e-01 -5.47974035e-02 3.81762445e-01 8.98436606e-01
6.27089679e-01 -7.60208368e-01 -2.92101055e-01 -1.25487819e-01
1.03271770e+00 6.55715689e-02 -4.08893973e-01 -3.24830025e-01
-1.10001004e+00 2.90388644e-01 -1.49000064e-01 3.17708477e-02
-1.96280539e-01 -1.03023835e-01 -4.08141837e-02 -2.44389802e-01
-3.05251144e-02 1.06315780e-02 -2.97401194e-02 -5.13225757e-02
-1.11677992e+00 3.74611020e-02 9.04253900e-01 1.34961712e+00
6.60583496e-01 -8.09325203e-02 2.09152535e-01 1.19221723e+00
2.93010384e-01 7.41491735e-01 -1.93585426e-01 -7.33705103e-01
8.41472030e-01 7.82935500e-01 4.15228844e-01 -1.17748559e+00
-5.37772886e-02 3.15364212e-01 -7.86937475e-01 3.63754094e-01
5.75732827e-01 -5.52428424e-01 -7.88297176e-01 7.24206448e-01
2.72784740e-01 -3.61381024e-01 -4.96940583e-01 5.40487349e-01
4.81792063e-01 6.66291654e-01 -3.82026762e-01 -3.27296078e-01
1.77507901e+00 -8.93537521e-01 -8.91568601e-01 -2.73197532e-01
2.07594689e-02 -1.19946778e+00 1.20993078e+00 7.34586358e-01
-1.06610429e+00 -4.58795696e-01 -1.62933171e+00 -6.09484911e-02
7.08987704e-03 1.03934264e+00 1.97888762e-01 7.72122800e-01
-5.37970066e-01 -1.04781821e-01 -6.22104347e-01 -1.57597095e-01
2.87841529e-01 2.06589103e-01 1.04544938e-01 2.92574823e-01
-2.70084769e-01 2.47590080e-01 -5.70155457e-02 1.69469059e-01
-2.76869405e-02 -8.59835967e-02 -5.42448342e-01 2.12536126e-01
6.58179700e-01 -1.73306823e-01 1.06880069e+00 -1.02391148e+00
-1.85772216e+00 7.27864981e-01 -4.00595129e-01 4.15307023e-02
6.55774057e-01 -5.21615863e-01 -6.47050977e-01 3.78565639e-01
-3.39934140e-01 1.80074781e-01 1.26053345e+00 -1.59678173e+00
-5.82304060e-01 -2.86786199e-01 -1.51956871e-01 2.55457073e-01
-2.19197258e-01 -4.67835292e-02 -1.19857144e+00 -7.33305752e-01
4.33049768e-01 -1.11833000e+00 1.74953029e-01 -2.10570589e-01
-9.23678517e-01 1.85012877e-01 1.11875165e+00 -1.29303563e+00
1.81418824e+00 -2.21614504e+00 -2.96146274e-01 6.67756557e-01
3.35749060e-01 2.00718492e-01 2.44399667e-01 4.05134082e-01
4.24395591e-01 1.11507438e-01 3.73700149e-02 2.86448479e-01
-9.89108905e-02 -5.28815269e-01 -5.01220167e-01 1.31545663e-01
-2.33941928e-01 5.36673248e-01 -1.64724633e-01 -8.03872466e-01
9.59589705e-02 9.17777568e-02 -2.10793197e-01 -8.08851495e-02
-1.16087280e-01 -9.68171358e-02 -4.25336301e-01 1.10155010e+00
1.18835080e+00 -4.03603464e-01 9.98141646e-01 -2.52755523e-01
-3.02851349e-01 2.22998839e-02 -1.40317881e+00 9.96953964e-01
-2.29150966e-01 9.25757945e-01 4.19492424e-01 -1.37713373e-01
1.02079582e+00 -1.81009516e-01 2.24012941e-01 -4.34127718e-01
1.78572759e-01 2.35781461e-01 -3.66812311e-02 -4.23736572e-01
8.66644084e-01 5.55417180e-01 -1.27412334e-01 2.23123923e-01
-9.40658152e-01 -6.69376403e-02 2.25764662e-01 1.74304500e-01
9.18994665e-01 1.82332009e-01 4.66539413e-01 -2.37017229e-01
5.85061193e-01 -3.32229435e-02 6.00692332e-01 3.18959504e-01
-1.49658183e-02 8.19359720e-01 7.45053887e-01 -1.01087680e-02
-1.07704532e+00 -9.42559600e-01 1.47184566e-01 5.07077038e-01
4.84456301e-01 -6.04026079e-01 -1.29052985e+00 -7.68641353e-01
-7.51413777e-02 3.01205754e-01 -1.88837811e-01 6.50679886e-01
-8.68013024e-01 -3.94018412e-01 5.66548319e-04 4.37471241e-01
7.85298049e-01 -7.20030606e-01 -5.64925253e-01 -5.75352162e-02
-6.94859475e-02 -1.00785530e+00 -1.07485545e+00 -4.46947254e-02
-8.35286617e-01 -1.31459355e+00 -7.47456193e-01 -1.18057406e+00
9.78264093e-01 8.79816711e-01 8.34377766e-01 1.94908127e-01
1.12840183e-01 -1.06642768e-01 -1.71782374e-01 5.67693543e-03
-1.75858647e-01 1.72059555e-02 -4.37233984e-01 1.99510023e-01
-9.41157248e-03 -3.58401418e-01 -7.53669918e-01 7.87746310e-01
-6.95283592e-01 6.95884228e-01 6.42330885e-01 2.16193184e-01
6.98081732e-01 4.04234566e-02 2.87567172e-02 -1.25663769e+00
5.73678613e-01 -2.87310947e-02 -1.01154315e+00 3.69597673e-01
-9.13026258e-02 -3.23412597e-01 7.46788800e-01 -4.71630394e-01
-1.31519890e+00 1.17618740e-01 3.95497471e-01 1.16236452e-02
2.95327865e-02 1.38127312e-01 -1.06961870e+00 1.16931453e-01
1.80885687e-01 -1.42167151e-01 -3.12618405e-01 -5.18318176e-01
4.40518528e-01 1.03755474e+00 4.22234714e-01 -3.12907875e-01
9.55897212e-01 4.57255751e-01 -3.55850101e-01 -1.12289190e+00
-7.64445961e-02 -2.09030509e-02 -6.53938890e-01 -4.60763067e-01
9.26097274e-01 -5.92518628e-01 -8.11616540e-01 6.90683961e-01
-9.62641835e-01 -4.39584672e-01 3.23242903e-01 1.38693467e-01
-4.13911343e-02 6.41855001e-01 -7.03282773e-01 -7.76154101e-01
-1.34029984e-01 -9.17660415e-01 9.72830236e-01 8.56163085e-01
-2.67596453e-01 -4.68871534e-01 -6.71543106e-02 4.77220744e-01
-4.03161764e-01 9.16414857e-02 1.11932135e+00 1.08914070e-01
-1.06761968e+00 -2.15194881e-01 -4.56003577e-01 5.26600331e-02
3.17510992e-01 6.51159585e-01 -6.41332507e-01 2.07213968e-01
-4.05413836e-01 3.51057082e-01 4.67151612e-01 2.12690920e-01
1.24354100e+00 -2.65248924e-01 -5.66187263e-01 5.73532343e-01
1.37086797e+00 9.26784098e-01 8.26920986e-01 3.65618646e-01
9.29790795e-01 2.76929051e-01 6.19443595e-01 3.21062058e-01
1.22002691e-01 5.44817090e-01 -1.74681887e-01 -2.50440231e-03
-3.18470120e-01 -4.95844424e-01 5.35038292e-01 1.13288522e+00
1.58512801e-01 -4.16510314e-01 -6.52239025e-01 1.79259524e-01
-1.51216638e+00 -5.35875082e-01 -5.54547966e-01 2.23429346e+00
6.88907504e-01 9.99576747e-02 2.65116125e-01 1.25722453e-01
1.08354998e+00 2.38822103e-01 -5.17569005e-01 -4.12425727e-01
-3.69752079e-01 -1.89309224e-01 6.39874220e-01 2.93505162e-01
-1.01538277e+00 7.00127602e-01 6.24817038e+00 8.70531023e-01
-8.10995460e-01 -3.97252053e-01 6.95062220e-01 1.52866557e-01
-3.84267211e-01 2.21198484e-01 -9.00670350e-01 9.24050629e-01
1.29631773e-01 4.03518975e-01 4.00253117e-01 4.80382055e-01
2.16925964e-01 -6.62085652e-01 -6.66431785e-01 1.15254855e+00
1.99705079e-01 -1.28987110e+00 -4.48533297e-02 3.83647740e-01
1.03311312e+00 -9.24870372e-01 4.72377948e-02 -2.96476632e-01
3.03840429e-01 -5.58988571e-01 9.00431931e-01 4.49133784e-01
8.45048249e-01 -5.30839026e-01 1.10340953e-01 1.27888083e-01
-1.39388621e+00 7.10398629e-02 2.37462036e-02 1.43385500e-01
2.36193445e-02 7.14535594e-01 -5.71107328e-01 2.57261664e-01
2.63544798e-01 9.45378244e-02 -8.50855708e-01 1.16120172e+00
-3.03774804e-01 8.15527737e-01 -3.27908188e-01 -3.78710568e-01
-3.50538760e-01 -1.01850712e+00 2.84930199e-01 1.06108236e+00
5.88337719e-01 -5.62729351e-02 -1.63159389e-02 4.65515256e-01
-3.62669140e-01 3.78588617e-01 -3.98518264e-01 -1.13942020e-03
7.90344238e-01 1.39211702e+00 -1.34203327e+00 -4.89700317e-01
-6.21738076e-01 1.12246990e+00 1.06431678e-01 6.87495172e-01
-9.75570142e-01 -8.03384185e-01 -1.61133870e-01 4.36458856e-01
5.48498631e-01 -5.77571034e-01 -1.03365207e+00 -1.19911480e+00
4.17499155e-01 -1.29896402e+00 1.03861161e-01 -9.46048439e-01
-6.90394223e-01 1.84055761e-01 -3.39406341e-01 -1.67232120e+00
3.92775744e-01 -4.53768939e-01 -7.99059451e-01 6.45042896e-01
-5.91869771e-01 -1.20178890e+00 -5.50483167e-01 2.16430407e-02
6.76220536e-01 2.39746701e-02 1.90286309e-01 8.24245140e-02
-8.51955891e-01 4.18017030e-01 5.42096078e-01 2.20587134e-01
6.93154752e-01 -1.25966620e+00 3.00815135e-01 1.10457730e+00
1.32230759e-01 8.19540501e-01 3.17315936e-01 -1.07696605e+00
-1.60914660e+00 -5.29016137e-01 4.43100601e-01 -1.11561932e-01
5.83379388e-01 -6.78311944e-01 -7.92632103e-01 4.84671712e-01
5.35986125e-01 -8.00411105e-01 6.42839909e-01 -2.12091990e-02
-7.12767988e-02 -2.43159041e-01 -6.56290889e-01 1.07211590e+00
8.27759922e-01 -4.22991782e-01 -2.47405767e-01 -2.40018182e-02
-4.43492979e-02 -4.05675590e-01 -4.68619764e-01 -5.09211533e-02
1.07969403e+00 -8.35156858e-01 6.16563618e-01 4.46925849e-01
2.44299784e-01 -8.85246694e-01 8.90616477e-02 -7.35650063e-01
-3.16535234e-02 -1.08603549e+00 -2.98576266e-01 1.57960224e+00
4.08088148e-01 -3.73002321e-01 9.41817343e-01 5.47073424e-01
6.05238229e-02 -4.79029506e-01 -1.64513692e-01 -4.22342181e-01
-5.57851255e-01 3.31347436e-02 6.54649734e-01 5.55211544e-01
-2.54782718e-02 4.29076523e-01 -5.04585683e-01 1.65674224e-01
4.56114054e-01 6.53602183e-01 1.22550118e+00 -1.00473821e+00
-1.84122369e-01 -4.19471383e-01 2.45945677e-01 -1.55370212e+00
-3.90925258e-01 -1.76354975e-01 -3.22076306e-02 -1.49634206e+00
3.59109461e-01 -3.71565551e-01 3.92068535e-01 -1.88404873e-01
-4.90101486e-01 2.12213188e-01 4.28023845e-01 5.30955017e-01
-4.59300071e-01 -3.32709178e-02 1.33724940e+00 -1.81045428e-01
-5.47822058e-01 1.46845475e-01 -7.48879969e-01 1.10550225e+00
7.65615880e-01 1.22314401e-01 -4.54974502e-01 -2.59245157e-01
3.47003847e-01 8.26812685e-02 -3.77719849e-02 -9.18780446e-01
-2.02037068e-03 -2.34545961e-01 8.13777089e-01 -1.35557485e+00
-3.75434011e-02 -6.85191274e-01 3.12183827e-01 2.01036364e-01
2.30253205e-01 2.69258380e-01 1.34963080e-01 4.90872651e-01
7.92106539e-02 -2.73711979e-01 5.44932544e-01 3.37608606e-01
-3.91642749e-01 -2.58053362e-01 -7.86355555e-01 -2.88579822e-01
9.73339558e-01 -6.06422961e-01 -4.23002690e-01 -2.53229707e-01
-4.24894542e-01 2.36262497e-03 1.17059970e+00 -3.13367299e-03
4.70763803e-01 -1.40502417e+00 -1.10563517e-01 1.28804401e-01
-3.00947458e-01 -2.18524992e-01 3.48354042e-01 6.94470167e-01
-1.31427014e+00 2.29096115e-01 5.30744046e-02 -3.29184234e-01
-1.80417609e+00 3.75948757e-01 -1.85227707e-01 -1.90092415e-01
-7.48689175e-01 5.62168099e-02 5.75923324e-01 5.19720078e-01
9.06963423e-02 -6.88111961e-01 -5.63388355e-02 2.00823590e-01
4.94714200e-01 8.08595181e-01 -1.77318633e-01 -3.37418079e-01
-1.89967930e-01 8.09737384e-01 -4.72438484e-02 -3.70443404e-01
6.52899683e-01 -3.30250740e-01 -6.11432008e-02 3.65505099e-01
7.95890570e-01 1.16827083e+00 -1.49789953e+00 2.95420736e-01
-1.35200649e-01 -6.40285194e-01 -5.29444575e-01 -7.75652945e-01
-7.10543275e-01 7.20614910e-01 2.03196123e-01 3.73050779e-01
1.24936318e+00 -3.03269804e-01 1.01707864e+00 9.46817100e-02
2.20224887e-01 -1.45813334e+00 -1.58880297e-02 1.99249700e-01
7.02604175e-01 -5.25130093e-01 3.34349215e-01 -9.25516427e-01
-6.33745015e-01 1.16794598e+00 7.01995313e-01 -1.17315643e-01
1.98469028e-01 4.98424500e-01 2.00395975e-02 -9.06663612e-02
-1.82628781e-01 1.35655394e-02 4.97679263e-01 3.50433677e-01
2.51555681e-01 4.03741151e-01 -5.22438645e-01 8.27398956e-01
-1.51145503e-01 -3.21161151e-01 6.81146562e-01 1.08828557e+00
-7.34666228e-01 -1.08206856e+00 -9.03071761e-01 4.89653409e-01
-3.95390600e-01 -6.20322451e-02 -8.63366902e-01 9.36401904e-01
1.30222008e-01 8.52865636e-01 8.90886933e-02 -3.63798738e-01
2.87685663e-01 -3.15024406e-02 5.29435694e-01 -2.26749927e-01
-2.72706628e-01 9.63296473e-01 3.17531705e-01 -1.81585923e-01
1.09374993e-01 -9.78012621e-01 -1.17080903e+00 -2.00831264e-01
-3.73376787e-01 -8.07702988e-02 4.50649470e-01 3.50173324e-01
2.88080812e-01 4.16803777e-01 6.40372276e-01 -3.77011001e-01
2.76043952e-01 -8.41587543e-01 -6.92659557e-01 2.70962417e-01
1.32167861e-02 -3.44726592e-01 1.42024398e-01 5.20707309e-01] | [11.974807739257812, 2.2394771575927734] |
138b2400-b86b-44f3-bf1c-4e8e7e597cf6 | estimating-parameters-of-nonlinear-systems | 1604.04198 | null | http://arxiv.org/abs/1604.04198v4 | http://arxiv.org/pdf/1604.04198v4.pdf | Estimating parameters of nonlinear systems using the elitist particle filter based on evolutionary strategies | In this article, we present the elitist particle filter based on evolutionary
strategies (EPFES) as an efficient approach for nonlinear system
identification. The EPFES is derived from the frequently-employed state-space
model, where the relevant information of the nonlinear system is captured by an
unknown state vector. Similar to classical particle filtering, the EPFES
consists of a set of particles and respective weights which represent different
realizations of the latent state vector and their likelihood of being the
solution of the optimization problem. As main innovation, the EPFES includes an
evolutionary elitist-particle selection which combines long-term information
with instantaneous sampling from an approximated continuous posterior
distribution. In this article, we propose two advancements of the
previously-published elitist-particle selection process. Further, the EPFES is
shown to be a generalization of the widely-used Gaussian particle filter and
thus evaluated with respect to the latter for two completely different
scenarios: First, we consider the so-called univariate nonstationary growth
model with time-variant latent state variable, where the evolutionary selection
of elitist particles is evaluated for non-recursively calculated particle
weights. Second, the problem of nonlinear acoustic echo cancellation is
addressed in a simulated scenario with speech as input signal: By using
long-term fitness measures, we highlight the efficacy of the well-generalizing
EPFES in estimating the nonlinear system even for large search spaces. Finally,
we illustrate similarities between the EPFES and evolutionary algorithms to
outline future improvements by fusing the achievements of both fields of
research. | ['Christian Hofmann', 'Roland Maas', 'Walter Kellermann', 'Christian Huemmer'] | 2016-04-14 | null | null | null | null | ['acoustic-echo-cancellation', 'acoustic-echo-cancellation'] | ['medical', 'speech'] | [ 1.51434928e-01 -3.44539434e-01 5.40980339e-01 3.33878160e-01
-3.23348761e-01 -1.89129367e-01 7.10849941e-01 -1.42511025e-01
-6.11714244e-01 9.50387716e-01 -3.96445505e-02 5.41884080e-02
-7.47433364e-01 -6.34717107e-01 -5.14111221e-01 -1.13101315e+00
-1.86461881e-01 6.90367579e-01 2.51585931e-01 -4.59311336e-01
1.52461067e-01 4.85276967e-01 -2.08736706e+00 -5.29102445e-01
1.04084635e+00 7.47716367e-01 4.66996044e-01 9.22993243e-01
2.11198136e-01 -5.01526184e-02 -1.05715740e+00 -2.60594904e-01
-2.80464478e-02 -4.88348961e-01 -1.26252566e-02 2.52998471e-02
-1.90914631e-01 4.35357928e-01 1.50954770e-02 1.13907802e+00
7.56426156e-01 6.38637245e-01 7.37710059e-01 -8.60244572e-01
-3.63558829e-01 1.85043901e-01 3.05127591e-01 3.27052414e-01
7.24791065e-02 3.81732620e-02 5.38258374e-01 -8.83751094e-01
3.75341773e-01 1.10795617e+00 9.24793661e-01 4.85222816e-01
-1.11450052e+00 -2.79546767e-01 -2.71707643e-02 2.05949515e-01
-1.40631831e+00 -3.91711771e-01 6.16599202e-01 -4.44447011e-01
7.77534842e-01 5.90301335e-01 1.03072846e+00 9.07753289e-01
3.91607642e-01 6.44237459e-01 1.13346601e+00 -6.33952081e-01
6.56545341e-01 1.89239398e-01 2.43987620e-01 4.86245781e-01
3.60171676e-01 7.42880702e-01 -2.34556094e-01 -6.39570832e-01
4.57280546e-01 -3.03191781e-01 -4.39651102e-01 -2.60401607e-01
-7.70433426e-01 7.24886537e-01 -2.92784452e-01 6.09302640e-01
-7.32942164e-01 -1.37722433e-01 -6.84679225e-02 1.66623056e-01
7.41267741e-01 5.14147222e-01 -2.06127390e-01 -2.13389009e-01
-1.13112664e+00 4.80325878e-01 1.20239854e+00 5.34928560e-01
3.71256918e-01 5.60760379e-01 -4.45810497e-01 6.09454274e-01
4.86291945e-01 9.21712101e-01 4.31754470e-01 -6.32883668e-01
-2.64570594e-01 -8.50316137e-02 5.66803992e-01 -7.03121066e-01
-3.43858749e-01 -1.24392927e+00 -6.68088019e-01 4.83796746e-01
2.28058919e-01 -3.80718201e-01 -6.55956507e-01 1.72422338e+00
3.39269042e-01 8.10768723e-01 3.41101825e-01 5.21016479e-01
2.42557824e-01 8.42547536e-01 -1.71417385e-01 -9.13867593e-01
1.07699585e+00 -8.11801195e-01 -1.02971125e+00 2.27012292e-01
-2.93881118e-01 -7.41731048e-01 3.92974406e-01 5.33306479e-01
-1.35739005e+00 -7.46111631e-01 -9.53089654e-01 8.31975162e-01
-1.85859263e-01 1.60194919e-01 -1.84238038e-03 1.00628400e+00
-1.22494626e+00 9.02036190e-01 -8.71459842e-01 -1.99397475e-01
-3.45784396e-01 3.81106973e-01 3.48307371e-01 4.86129820e-01
-1.34486377e+00 1.01659226e+00 1.30189911e-01 5.09359300e-01
-6.58254743e-01 -6.92564726e-01 -4.30858821e-01 2.41313532e-01
1.64959878e-01 -9.12813246e-01 1.10516119e+00 -7.02543974e-01
-2.16405153e+00 8.29659924e-02 -5.14393449e-01 -4.85392779e-01
6.40909076e-01 -1.40388593e-01 -6.64652407e-01 -2.13551581e-01
-3.20785731e-01 -3.54408264e-01 1.45575309e+00 -1.26247120e+00
-6.64378166e-01 8.02141652e-02 -5.85558593e-01 3.00206482e-01
-3.34420055e-01 -9.09509659e-02 -3.02924156e-01 -7.20939577e-01
-1.03156634e-01 -1.09651577e+00 -3.58033508e-01 -7.26756334e-01
-8.02872777e-02 -1.77819356e-01 7.28490055e-01 -5.61864018e-01
1.53777695e+00 -2.10153437e+00 6.87276065e-01 4.13523525e-01
2.29442399e-03 6.60341322e-01 1.02313243e-01 7.91073382e-01
1.52187318e-01 -3.06432307e-01 -4.51917022e-01 -7.05072761e-01
1.95027679e-01 2.08365604e-01 -2.99262911e-01 5.26510656e-01
-8.73100236e-02 5.82815647e-01 -9.08284068e-01 -1.47377271e-02
3.42246950e-01 8.72285843e-01 -3.15750927e-01 8.77275988e-02
7.65444934e-02 5.80921590e-01 -3.14018250e-01 7.34816715e-02
5.96631527e-01 5.92746995e-02 -1.90183073e-01 -1.16420545e-01
-6.64061069e-01 -4.48739499e-01 -1.45091808e+00 9.15664494e-01
-3.80020380e-01 3.93477499e-01 3.88702899e-01 -1.01858795e+00
9.07654822e-01 5.96370161e-01 4.28784668e-01 2.32548323e-02
2.16332421e-01 4.85845089e-01 1.55632524e-02 -3.98689181e-01
4.84699994e-01 -3.66742760e-01 1.75889000e-01 1.70363516e-01
1.75300285e-01 -2.73108304e-01 3.92907292e-01 -4.53473270e-01
8.08491766e-01 -8.28192979e-02 3.92326385e-01 -5.55481374e-01
9.40856457e-01 -3.37178677e-01 4.21185642e-01 1.12949955e+00
-1.59631386e-01 3.92545164e-01 -2.76546571e-02 6.41467422e-02
-8.15438688e-01 -1.04574978e+00 -4.85031635e-01 5.37874401e-01
3.92298549e-02 -2.91648712e-02 -6.13326252e-01 -1.10586450e-01
-1.14531787e-02 9.10109401e-01 -4.78064597e-01 -2.35309705e-01
-6.75431788e-01 -1.28365993e+00 2.41915166e-01 -1.10256270e-01
-2.02724850e-03 -9.14231956e-01 -7.21275628e-01 5.67750931e-01
2.86653012e-01 -5.79774976e-01 -5.68153150e-02 1.39973849e-01
-7.78022468e-01 -5.97330749e-01 -1.10617077e+00 -5.70579886e-01
3.55614752e-01 -3.72688442e-01 1.09233105e+00 -5.11902981e-02
7.96839595e-02 7.09304810e-01 -2.38759950e-01 -4.78075385e-01
-9.55843866e-01 -3.79703373e-01 3.75425458e-01 3.42724532e-01
-2.01048926e-02 -5.85756660e-01 -4.28365350e-01 3.24555784e-01
-7.29589403e-01 -3.12865555e-01 2.88174063e-01 1.07049823e+00
4.45966065e-01 7.40045905e-01 4.67947662e-01 -4.01969224e-01
1.06030178e+00 -4.00237650e-01 -8.91659200e-01 3.45432520e-01
-6.35357261e-01 1.10877655e-01 6.30392671e-01 -7.59558618e-01
-1.19036424e+00 -2.09345877e-01 -5.19225657e-01 -3.77137333e-01
-7.01397099e-03 4.76843208e-01 1.84514448e-01 -3.15889686e-01
2.66934723e-01 6.34783149e-01 6.58075884e-02 -4.13308442e-01
1.76792815e-02 4.36053991e-01 4.84409720e-01 -4.77950752e-01
8.96425545e-01 4.44227844e-01 1.94669724e-01 -1.04871750e+00
-3.42350394e-01 -3.32622766e-01 -1.81961000e-01 -3.34406018e-01
5.65547585e-01 -2.98907697e-01 -8.91015410e-01 8.04782629e-01
-1.00356340e+00 -9.14773419e-02 -8.62867653e-01 8.37109029e-01
-6.43778503e-01 3.75821829e-01 -4.72027928e-01 -1.64832318e+00
-2.50361264e-01 -1.21033978e+00 8.89401138e-01 3.33550185e-01
6.86856359e-02 -1.32676685e+00 5.75317383e-01 -3.72792989e-01
6.02046549e-01 -9.64752436e-02 6.75635517e-01 -5.61053216e-01
-7.12251440e-02 -3.91745120e-01 6.29076302e-01 4.78228390e-01
-1.34804860e-01 2.37202674e-01 -6.13720357e-01 -6.51437759e-01
7.68986404e-01 6.35051310e-01 6.74891233e-01 9.72553670e-01
1.72035247e-01 1.75624371e-01 -4.66889620e-01 4.32744265e-01
1.41594183e+00 6.50967181e-01 2.88921714e-01 1.64488107e-01
5.76755032e-02 4.94250506e-01 3.40204418e-01 5.39905429e-01
-1.05970234e-01 7.96816647e-01 2.37879857e-01 4.47385907e-02
-3.92706040e-03 1.93574533e-01 3.21969122e-01 1.22562194e+00
-3.02481055e-01 -6.73919678e-01 -5.25427461e-01 2.86742061e-01
-1.87440884e+00 -1.17519140e+00 -1.22719109e-01 2.40935802e+00
3.78257751e-01 -3.63724865e-02 -3.61578837e-02 2.23711833e-01
9.87083316e-01 -1.96260497e-01 -4.48006332e-01 -2.28906292e-02
-3.84629518e-01 3.64207417e-01 3.30230653e-01 9.28171158e-01
-9.86473978e-01 3.70957017e-01 6.69057894e+00 9.74423170e-01
-9.87284660e-01 3.27164650e-01 -6.60441518e-02 4.52259444e-02
-1.03098124e-01 -1.58554539e-01 -1.22185540e+00 8.56566191e-01
1.19984818e+00 -4.12925690e-01 3.92532021e-01 2.06160724e-01
3.81749332e-01 -3.94800492e-02 -3.90605241e-01 6.90144420e-01
8.11200961e-02 -1.04138136e+00 -4.06283975e-01 2.23914236e-01
8.41686308e-01 -2.09866986e-01 5.08027434e-01 3.49662244e-01
1.06427439e-01 -5.44274867e-01 8.69605541e-01 1.06313217e+00
1.64042294e-01 -6.77272379e-01 7.79651701e-01 5.45555592e-01
-1.10575485e+00 -5.46339035e-01 -2.80730218e-01 -6.47371681e-03
8.95743012e-01 7.94169009e-01 -3.29529345e-01 6.88657403e-01
4.20692056e-01 3.64755571e-01 -9.11031291e-02 1.65270782e+00
6.86379224e-02 7.91000724e-01 -6.21274889e-01 -3.99084002e-01
1.01057313e-01 -5.40516615e-01 1.54295707e+00 1.03937232e+00
1.09191561e+00 -7.72806853e-02 -1.00911535e-01 7.21121967e-01
7.85665810e-01 -3.84120680e-02 1.19133368e-02 1.56157851e-01
4.14241552e-01 9.51924086e-01 -7.09157228e-01 -3.89393210e-01
4.18373309e-02 6.81544840e-01 -1.84775725e-01 5.70843458e-01
-7.09057868e-01 -1.98305041e-01 5.24322033e-01 -1.66789204e-01
6.84945107e-01 -1.16783500e-01 3.03784162e-01 -1.03177202e+00
-3.53941143e-01 -5.67280948e-01 2.62288302e-02 -4.35403019e-01
-1.27700472e+00 1.01664412e+00 3.03258151e-01 -1.23601532e+00
-5.74546754e-01 -6.08412743e-01 -5.73810458e-01 1.25745225e+00
-1.40947723e+00 -6.03894889e-01 2.05483332e-01 3.04380774e-01
5.17881930e-01 -4.75620955e-01 9.36073184e-01 2.40723431e-01
-7.15106964e-01 1.94121659e-01 9.87519801e-01 -8.42579603e-01
2.23988473e-01 -1.24830985e+00 4.47878838e-01 9.34265137e-01
-8.45141709e-02 7.99503326e-01 1.55235934e+00 -9.42377269e-01
-1.11789036e+00 -7.09260106e-01 8.16087306e-01 -4.01498139e-01
7.15905726e-01 -2.01235905e-01 -8.61031473e-01 2.50236467e-02
8.46187323e-02 -1.39204666e-01 4.39058781e-01 -2.23837912e-01
6.29058361e-01 1.73534960e-01 -1.03144181e+00 5.68008244e-01
7.56783366e-01 4.76170555e-02 -6.40062928e-01 3.06194484e-01
3.00310493e-01 -4.22359526e-01 -8.39524686e-01 5.65750122e-01
5.88420928e-01 -9.58141267e-01 1.16405714e+00 -1.84094459e-01
-5.28041184e-01 -4.72037762e-01 5.36092035e-02 -1.64825010e+00
-6.91738844e-01 -9.97138262e-01 -4.82245505e-01 8.89773369e-01
1.52063712e-01 -1.07102549e+00 6.94405854e-01 -1.62947681e-02
-3.44473749e-01 -7.72407234e-01 -1.31253028e+00 -1.06854391e+00
-4.51552868e-02 -3.12814593e-01 5.39617836e-01 1.11483663e-01
-5.12192488e-01 5.91763966e-02 -5.26999652e-01 5.57297468e-01
8.91325891e-01 -7.95944110e-02 2.14057520e-01 -1.52499592e+00
-8.94611478e-01 -5.78978539e-01 -2.64191598e-01 -9.48365033e-01
3.00212860e-01 -3.75909686e-01 2.97778666e-01 -1.11528015e+00
-2.86765844e-01 -3.83403093e-01 -3.98680061e-01 -6.64779186e-01
-3.56178045e-01 1.62176415e-01 2.17602029e-01 2.28670299e-01
-1.38780624e-01 7.45227873e-01 1.00972974e+00 2.56659806e-01
-3.94326150e-01 8.96424711e-01 -5.49399778e-02 6.19700491e-01
3.68328959e-01 -5.02627492e-01 -4.77504492e-01 6.74384385e-02
2.05890015e-01 2.36909986e-01 3.44577879e-01 -1.31778061e+00
4.44365323e-01 2.66088396e-01 5.22352643e-02 -6.74149156e-01
8.18789721e-01 -8.18806469e-01 8.15434456e-01 8.95694673e-01
6.08737022e-02 9.26678255e-02 1.48238912e-01 9.55997527e-01
-1.95764422e-01 -8.01137567e-01 7.29543149e-01 1.58971325e-02
-4.87631470e-01 -5.32686077e-02 -8.66174698e-01 -3.78958911e-01
9.35760200e-01 -3.78037304e-01 5.95526025e-02 -4.18338031e-01
-1.17289937e+00 -2.41990864e-01 2.01742291e-01 1.51704298e-02
3.87896240e-01 -9.17454422e-01 -8.68758380e-01 3.49500865e-01
-5.11701763e-01 -7.05097318e-01 5.07345498e-01 1.06623757e+00
-8.65582153e-02 4.06462222e-01 1.39146164e-01 -6.60163581e-01
-1.38085854e+00 4.96123463e-01 4.98229593e-01 -3.50103259e-01
-4.35653478e-01 9.79159594e-01 -4.36272174e-02 -3.47007006e-01
-4.09544930e-02 -7.70022348e-03 -4.71877813e-01 2.24129716e-03
4.70681727e-01 7.59065926e-01 1.12899013e-01 -8.72919858e-01
-7.16223344e-02 6.68554664e-01 6.46976888e-01 -4.58719134e-01
1.23107219e+00 -3.42230946e-01 -2.28479579e-01 5.93223572e-01
7.73724139e-01 3.53403777e-01 -1.37690294e+00 -7.12185130e-02
-2.16771156e-01 9.72066261e-03 1.71005070e-01 -6.92322254e-01
-5.95878422e-01 3.68566722e-01 9.35706377e-01 6.32654369e-01
1.20733273e+00 -4.15814102e-01 5.34495652e-01 -2.65824515e-02
3.12126368e-01 -7.58427382e-01 -4.50073451e-01 6.85446382e-01
7.24023283e-01 -5.77671349e-01 -1.45008191e-02 -2.40947306e-01
-6.22664914e-02 1.05889356e+00 -6.97469190e-02 -2.55493253e-01
9.76344943e-01 5.49478173e-01 -1.92101642e-01 6.09447919e-02
-6.26139283e-01 -3.12108696e-01 6.08285010e-01 6.34383380e-01
-1.62206532e-03 -2.85487883e-02 -7.28800774e-01 5.24793029e-01
-2.29286715e-01 -1.25808612e-01 2.12620124e-01 8.18389416e-01
-5.18326044e-01 -1.18404365e+00 -8.10919166e-01 1.82351992e-01
-2.80798227e-01 -1.00470118e-01 3.87369573e-01 5.32088220e-01
8.88515934e-02 9.53093112e-01 -1.71203504e-03 -8.77376422e-02
4.86531258e-01 3.05171888e-02 4.54002589e-01 -4.57535475e-01
-8.35431755e-01 3.97559732e-01 -1.90506026e-01 -3.02584134e-02
-4.01658982e-01 -1.05654287e+00 -5.98508835e-01 4.60186824e-02
-6.72739983e-01 8.91263902e-01 8.68448913e-01 1.04928982e+00
2.59005189e-01 7.68161714e-01 3.31349790e-01 -1.29475725e+00
-9.75775182e-01 -7.77699828e-01 -6.13717437e-01 -6.40601963e-02
4.19878870e-01 -8.55508566e-01 -7.20941544e-01 -3.35217118e-01] | [6.511843681335449, 3.5623154640197754] |
338c3bfc-381c-4b49-88f2-7875d15f8c9a | presenting-multiagent-challenges-in-team | 2303.13660 | null | https://arxiv.org/abs/2303.13660v1 | https://arxiv.org/pdf/2303.13660v1.pdf | Presenting Multiagent Challenges in Team Sports Analytics | This paper draws correlations between several challenges and opportunities within the area of team sports analytics and key research areas within multiagent systems (MAS). We specifically consider invasion games, defined as sports where players invade the opposing team's territory and can interact anywhere on a playing surface such as ice hockey, soccer, and basketball. We argue that MAS is well-equipped to study invasion games and will benefit both MAS and sports analytics fields. Our discussion highlights areas for MAS implementation and further development along two axes: short-term in-game strategy (coaching) and long-term team planning (management). | ['Alexi Orchard', 'David Radke'] | 2023-03-23 | null | null | null | null | ['sports-analytics'] | ['computer-vision'] | [-1.92839354e-01 1.55391723e-01 -4.97265048e-02 1.60005942e-01
-1.23294123e-01 -7.13320434e-01 5.79230368e-01 4.71925080e-01
-4.04950708e-01 7.19716847e-01 -7.78606569e-04 -2.24963829e-01
-6.78929985e-01 -1.18869412e+00 -2.11802602e-01 -3.37493479e-01
-6.07864380e-01 8.69923592e-01 3.94578815e-01 -1.51007998e+00
2.46431202e-01 1.63544536e-01 -1.73357463e+00 1.69597089e-01
3.71401578e-01 5.46546638e-01 -2.18753994e-01 1.02261055e+00
3.16173166e-01 1.36996567e+00 -9.10924733e-01 -5.52566409e-01
5.98554075e-01 -2.82013893e-01 -9.30508018e-01 7.74967447e-02
-4.60307062e-01 1.81816950e-01 -3.18541497e-01 6.33350015e-01
1.47605106e-01 4.23460424e-01 -4.27986048e-02 -1.93566704e+00
2.61455268e-01 9.38731134e-01 -5.11494398e-01 5.97187698e-01
8.63784909e-01 5.19171298e-01 8.45683992e-01 -1.24352373e-01
5.92440486e-01 7.61664093e-01 5.79356372e-01 3.76670286e-02
-5.81156731e-01 -6.32505536e-01 2.97470927e-01 4.04029191e-01
-1.27353907e+00 -1.29874181e-02 4.14893866e-01 -4.73009944e-01
8.32533598e-01 5.94694734e-01 1.28673959e+00 4.58602130e-01
5.20247638e-01 8.38983476e-01 1.14985037e+00 -3.93563926e-01
4.35457051e-01 -4.63468790e-01 2.36646965e-01 7.54762962e-02
5.88534586e-02 2.27915376e-01 -1.20566285e+00 -2.91905135e-01
1.00757468e+00 -4.05427516e-01 5.43398678e-01 -9.83649194e-02
-1.41607654e+00 8.68956089e-01 -1.97074980e-01 1.36104017e-01
-8.18849444e-01 1.53246447e-01 5.50668418e-01 8.26609850e-01
2.39683911e-01 6.43730462e-01 1.20624781e-01 -1.23427403e+00
-6.26475871e-01 1.07202232e+00 1.01779401e+00 6.94285750e-01
5.04966438e-01 1.59270409e-02 4.54055488e-01 2.68290550e-01
5.81707247e-02 -9.53050479e-02 -2.90573746e-01 -1.27947342e+00
6.04528248e-01 6.79328620e-01 1.82864875e-01 -1.06692290e+00
-7.15391994e-01 -3.85652661e-01 -4.58326012e-01 5.39921701e-01
4.92578536e-01 -3.59811664e-01 -3.39122526e-02 1.20054328e+00
6.33328140e-01 2.74030030e-01 2.72016793e-01 1.01309252e+00
8.73769104e-01 2.69868612e-01 -5.28592691e-02 -3.46777916e-01
1.54626429e+00 -9.97989058e-01 -6.25631928e-01 -5.45282662e-01
4.67892259e-01 -4.37571645e-01 5.92927396e-01 7.06361711e-01
-1.67804766e+00 -1.86061278e-01 -7.75840700e-01 6.35771632e-01
-2.11279839e-01 -8.09485555e-01 9.12050605e-01 5.95448136e-01
-8.76162171e-01 1.59778267e-01 -1.10710013e+00 -3.23504150e-01
-9.91948098e-02 5.15284956e-01 -1.07512929e-01 4.50436115e-01
-1.34283423e+00 1.06789827e+00 1.30584717e-01 4.73245680e-02
-1.04310668e+00 -4.37563986e-01 -7.27544606e-01 -1.05582058e-01
9.75562513e-01 -5.27077973e-01 1.24162710e+00 -6.60090625e-01
-1.70770192e+00 1.02151084e+00 7.96391666e-01 -3.92057508e-01
5.37617862e-01 -4.12744051e-03 -3.20650637e-01 -2.62293190e-01
6.12439215e-01 -2.23641589e-01 -5.92205711e-02 -6.80031419e-01
-1.21199560e+00 -3.66682559e-01 8.82188797e-01 8.77211213e-01
2.76609480e-01 7.29944885e-01 -8.26241374e-02 -3.47977966e-01
1.93011031e-01 -1.05863965e+00 -8.34358275e-01 -1.07840836e+00
-3.01526338e-01 -2.35162809e-01 1.67700604e-01 -1.62090808e-02
1.41999722e+00 -1.75098205e+00 6.92976952e-01 5.07553697e-01
5.44137061e-01 -2.00258419e-01 1.54999867e-01 1.31867778e+00
3.77191454e-01 -1.01650335e-01 6.93467617e-01 2.30769873e-01
2.32372046e-01 2.26377770e-01 2.03446560e-02 3.10835212e-01
-4.85012680e-01 7.74387181e-01 -8.51297319e-01 -1.05176426e-01
1.60071924e-01 -5.60240984e-01 -2.73908943e-01 1.12317670e-02
-1.18138216e-01 3.76583010e-01 -6.23257279e-01 8.27391982e-01
4.78460848e-01 1.69943776e-02 6.69821143e-01 7.70964026e-01
-7.72026479e-01 1.65157467e-01 -1.75902808e+00 1.50721657e+00
1.71677709e-01 3.71697605e-01 6.23353839e-01 -8.78653884e-01
8.17647517e-01 2.07834706e-01 8.70918572e-01 -4.34641868e-01
3.12494665e-01 -2.05623750e-02 4.60536242e-01 -3.73277515e-01
9.97299671e-01 -1.53865814e-01 -8.56973410e-01 1.16100359e+00
-3.85976315e-01 -2.56602675e-01 6.95955992e-01 3.29354942e-01
1.27671874e+00 -2.38644734e-01 5.65592945e-01 -4.83698875e-01
1.40826270e-01 8.85113478e-01 6.81556046e-01 1.17394805e+00
-6.78328633e-01 -2.52900094e-01 8.03137481e-01 -1.01571822e+00
-6.94931686e-01 -9.68823671e-01 6.57503247e-01 1.94422233e+00
7.53078163e-01 -9.67566729e-01 -4.53957975e-01 -3.76800410e-02
1.58857964e-02 2.81133931e-02 -6.54865563e-01 2.32459575e-01
-8.58211696e-01 -5.38735688e-01 6.83661520e-01 4.21947896e-01
4.09134001e-01 -1.01697576e+00 -9.46725786e-01 6.22086525e-01
-4.98117894e-01 -9.53948677e-01 -4.01896238e-02 -5.64952791e-02
-3.97169024e-01 -1.36985588e+00 -5.13759814e-02 -4.62550581e-01
-3.55351627e-01 4.04044658e-01 1.31375456e+00 2.05640242e-01
-1.75076202e-01 8.28254521e-01 -6.08860433e-01 -9.52247083e-01
-3.54785889e-01 2.15018570e-01 5.37020326e-01 -3.50815684e-01
6.73933268e-01 -6.36293650e-01 -3.43211025e-01 7.66718745e-01
-4.02371496e-01 1.91003874e-01 -7.07750767e-02 1.80554405e-01
2.61770368e-01 2.38869503e-01 3.16560179e-01 -3.14939141e-01
1.10563529e+00 -6.19554400e-01 -4.70696747e-01 2.35187754e-01
-2.66408473e-02 -1.01682711e+00 8.51693228e-02 -2.77887285e-01
-3.24062437e-01 -5.78379810e-01 2.24216655e-01 1.59330413e-01
-3.72240730e-02 8.91996086e-01 1.43762842e-01 -1.49882913e-01
7.79407203e-01 7.94844106e-02 5.63912213e-01 2.04797909e-01
-5.82579486e-02 3.47649336e-01 3.56672406e-01 -7.73546875e-01
6.16690278e-01 6.58001900e-01 7.45427758e-02 -7.87315249e-01
-2.07527637e-01 -3.11208844e-01 -4.42834079e-01 -1.20691955e+00
7.81341612e-01 -1.07036972e+00 -1.76690722e+00 5.79241276e-01
-4.76413161e-01 -5.28586507e-01 -4.04445022e-01 5.90325177e-01
-7.98158884e-01 3.90154906e-02 -9.07835841e-01 -9.73259389e-01
1.37943877e-02 -9.25545216e-01 5.67221582e-01 5.51203012e-01
-4.40883905e-01 -7.75299549e-01 5.34347892e-01 8.66673291e-01
3.91076982e-01 5.85259855e-01 2.81731915e-02 -6.51205480e-01
-6.10494435e-01 -6.35080710e-02 7.49138176e-01 -3.63029569e-01
-2.63212174e-01 1.37553826e-01 5.83707653e-02 -2.09255844e-01
-2.42187440e-01 -5.07975638e-01 -2.56193519e-01 5.01333117e-01
2.48575434e-02 2.50921249e-01 -4.26182717e-01 -9.85767320e-02
9.73460495e-01 2.95182019e-01 5.56494415e-01 1.38397896e+00
6.40538558e-02 8.24973881e-01 1.50817180e+00 1.03810322e+00
1.01578379e+00 8.15238655e-01 5.51266730e-01 1.16967045e-01
6.41820908e-01 8.42030346e-02 2.67594218e-01 7.99627006e-01
-1.11365032e+00 -2.16657724e-02 -1.35693872e+00 3.59943956e-01
-2.46341443e+00 -1.30713034e+00 -5.27936518e-01 1.63584459e+00
2.44261488e-01 4.62644219e-01 1.05251873e+00 1.63100898e-01
6.60163224e-01 4.46849577e-02 -2.07632780e-01 -7.28959203e-01
-2.18896970e-01 1.82158276e-01 3.67513627e-01 5.32289803e-01
-1.01312566e+00 1.16419578e+00 7.63112450e+00 6.85554564e-01
-2.12926462e-01 1.79108188e-01 2.35877380e-01 -5.88922739e-01
2.41007313e-01 3.07882190e-01 -5.55199683e-01 -4.98830341e-02
8.18521917e-01 -7.17143953e-01 5.87117732e-01 6.87799394e-01
5.27107954e-01 -5.02349973e-01 -6.86727643e-01 6.75850987e-01
-2.49822944e-01 -1.75640416e+00 -5.81509233e-01 4.72980827e-01
4.72408116e-01 4.08125663e-04 -2.19248354e-01 6.10381782e-01
1.01347637e+00 -1.02289534e+00 1.06367099e+00 3.98052126e-01
1.62587073e-02 -1.04380965e+00 7.51703620e-01 6.76403701e-01
-1.45104635e+00 -2.81361431e-01 5.81277050e-02 -1.51081693e+00
5.55237293e-01 -3.69636357e-01 -2.40418166e-01 7.77857959e-01
1.12576210e+00 4.76509839e-01 2.49481834e-02 7.68887460e-01
2.17932954e-01 2.24329278e-01 -4.44314301e-01 -2.28037372e-01
6.36767209e-01 -7.40692854e-01 8.73769224e-01 3.24365646e-01
-1.90674484e-01 7.34735966e-01 1.04267538e+00 2.26191819e-01
7.81864762e-01 -2.05698274e-02 -4.96351629e-01 6.74769506e-02
5.71166635e-01 9.57996607e-01 -9.14461553e-01 -2.20444202e-01
-1.84181750e-01 3.78113911e-02 -2.58619953e-02 -4.13617864e-02
-8.80103528e-01 -5.12681864e-02 1.33165300e+00 3.31288069e-01
-1.12186275e-01 -4.67097461e-01 -6.26873255e-01 -7.85125613e-01
-2.77969420e-01 -1.62259650e+00 7.97746480e-01 -4.80569005e-01
-9.61768627e-01 4.99398589e-01 1.37993112e-01 -1.40486932e+00
-4.68142837e-01 -4.84687909e-02 -9.29314911e-01 3.05433005e-01
-6.57374740e-01 -1.26426518e+00 -3.04294258e-01 6.41898692e-01
4.87272292e-01 -6.08144045e-01 5.50100625e-01 1.44053893e-02
-5.95478177e-01 1.13435142e-01 -2.08774537e-01 -4.57422845e-02
-3.14356163e-02 -9.46878850e-01 2.74709433e-01 5.71582973e-01
-1.74103051e-01 1.94153339e-01 1.10122204e+00 -7.69764125e-01
-1.59768689e+00 -1.71820745e-01 2.40283728e-01 -5.26300967e-01
1.05934465e+00 -4.01128471e-01 -6.62903041e-02 9.49255407e-01
3.91372800e-01 -6.59311235e-01 1.18928087e+00 7.01715648e-01
4.61672992e-01 3.35299224e-02 -6.13002062e-01 8.94002199e-01
9.29029822e-01 -1.23759516e-01 -4.75657225e-01 4.98209804e-01
1.27996713e-01 -8.03221285e-01 -1.04842901e+00 4.79378402e-02
5.62290967e-01 -1.24072707e+00 8.14675272e-01 -1.08592665e+00
2.78265715e-01 -2.12719023e-01 -3.76491100e-02 -1.18090236e+00
-3.44549030e-01 -1.15563273e+00 3.46537888e-01 6.24830604e-01
1.25723109e-01 -3.99816573e-01 1.41329217e+00 9.86379921e-01
-2.30335683e-01 -4.33291614e-01 -9.85409200e-01 -8.94684136e-01
1.57004669e-01 -7.80718803e-01 8.03425610e-01 9.70290899e-01
1.04092836e+00 7.16199260e-03 -5.72564721e-01 2.28706539e-01
7.34156728e-01 1.98932931e-01 1.53861296e+00 -1.20794988e+00
-4.23833221e-01 -5.19272208e-01 -8.92115831e-01 -6.92712724e-01
-3.86728108e-01 -3.11590731e-01 -2.68844545e-01 -1.45736361e+00
-1.05352178e-01 -6.45324409e-01 1.77826136e-02 2.48108581e-01
3.42163265e-01 2.48441175e-01 5.36736190e-01 3.52793843e-01
-1.29232597e+00 7.50012100e-02 1.13108218e+00 2.25618854e-01
-5.13357282e-01 3.24027091e-01 -7.47457802e-01 6.77361965e-01
6.14173353e-01 -3.89430940e-01 -4.93813679e-02 -3.31776999e-02
7.93665469e-01 8.94723356e-01 8.79648179e-02 -9.21776533e-01
8.39913011e-01 -1.09840405e+00 -8.17939222e-01 -2.41050839e-01
4.88239735e-01 -2.54093081e-01 5.69277406e-01 6.35291994e-01
3.16239558e-02 5.36326170e-01 9.72920731e-02 3.69984061e-01
-5.25921226e-01 1.39098063e-01 5.62544465e-02 -5.25925756e-01
-8.17510188e-01 1.34000974e-02 -1.39669681e+00 2.03141674e-01
2.00546217e+00 -7.62339413e-01 -5.76590002e-01 -8.72107565e-01
-1.28628409e+00 9.92378294e-01 3.59001070e-01 3.55802208e-01
3.50524724e-01 -1.12557924e+00 -1.24265313e+00 -1.98877960e-01
-5.84773049e-02 -3.98624152e-01 7.11943209e-01 1.10144866e+00
-1.01425803e+00 -6.66333288e-02 -7.50177920e-01 -5.47984660e-01
-1.50718737e+00 8.82641692e-03 3.56553555e-01 -4.96430099e-01
-5.76623321e-01 7.47082829e-01 -2.92778313e-01 -4.64802235e-01
1.54319666e-02 1.98734701e-01 -4.31192487e-01 6.55592382e-02
6.17416024e-01 7.71162987e-01 -3.08981597e-01 -6.26763105e-01
-7.11403310e-01 1.75895408e-01 1.40118942e-01 -3.40193570e-01
1.45045817e+00 -3.08784306e-01 -3.74187618e-01 6.27083898e-01
-3.14253151e-01 -6.82129934e-02 -7.72512376e-01 -2.18885634e-02
6.55793548e-02 -6.33544803e-01 -3.26516181e-01 -5.37439048e-01
-7.35622883e-01 -3.01864967e-02 5.62417172e-02 1.10839486e+00
7.80168056e-01 1.24863900e-01 4.65692133e-01 3.18766981e-02
9.55534458e-01 -1.62691116e+00 3.00350040e-01 7.67497838e-01
6.66352391e-01 -9.53860879e-01 4.63838950e-02 -5.91871023e-01
-1.32165217e+00 1.04995227e+00 9.34963763e-01 -5.17995179e-01
6.64431930e-01 6.82881713e-01 3.80920947e-01 -9.85614359e-01
-1.23341906e+00 -4.13286477e-01 -3.90216768e-01 7.30010390e-01
-1.24122031e-01 4.59077209e-01 -4.28655475e-01 9.62233365e-01
-8.04323733e-01 -1.54789791e-01 1.45516801e+00 1.64391148e+00
-4.79897559e-01 -1.14071071e+00 -7.43064523e-01 4.36775297e-01
-1.98924512e-01 3.24428350e-01 -5.47689974e-01 1.16951895e+00
1.62220776e-01 1.44301093e+00 3.35624635e-01 -7.88203299e-01
6.89592183e-01 -4.53312784e-01 1.47386000e-01 -7.26237953e-01
-1.53512311e+00 -7.79544413e-02 5.70710540e-01 -7.28416622e-01
-7.07438052e-01 -1.01165533e+00 -9.16200638e-01 -1.31576741e+00
-1.87548712e-01 6.36478603e-01 3.25335443e-01 9.27205384e-01
9.84086916e-02 5.10383189e-01 3.76062542e-01 -6.32642686e-01
-6.77089766e-02 -7.90859103e-01 -1.11411166e+00 -1.97178870e-01
-3.80664021e-01 -9.24685359e-01 -5.53858317e-02 -6.37024105e-01] | [3.473937511444092, 1.4138745069503784] |
39498db8-45a5-4cf8-a52c-c018bf9459ab | cycledrums-automatic-drum-arrangement-for | 2104.00353 | null | https://arxiv.org/abs/2104.00353v2 | https://arxiv.org/pdf/2104.00353v2.pdf | CycleDRUMS: Automatic Drum Arrangement For Bass Lines Using CycleGAN | The two main research threads in computer-based music generation are: the construction of autonomous music-making systems, and the design of computer-based environments to assist musicians. In the symbolic domain, the key problem of automatically arranging a piece music was extensively studied, while relatively fewer systems tackled this challenge in the audio domain. In this contribution, we propose CycleDRUMS, a novel method for generating drums given a bass line. After converting the waveform of the bass into a mel-spectrogram, we are able to automatically generate original drums that follow the beat, sound credible and can be directly mixed with the input bass. We formulated this task as an unpaired image-to-image translation problem, and we addressed it with CycleGAN, a well-established unsupervised style transfer framework, originally designed for treating images. The choice to deploy raw audio and mel-spectrograms enabled us to better represent how humans perceive music, and to potentially draw sounds for new arrangements from the vast collection of music recordings accumulated in the last century. In absence of an objective way of evaluating the output of both generative adversarial networks and music generative systems, we further defined a possible metric for the proposed task, partially based on human (and expert) judgement. Finally, as a comparison, we replicated our results with Pix2Pix, a paired image-to-image translation network, and we showed that our approach outperforms it. | ['Fabrizio Silvestri', 'Fabio Petroni', 'Angela Fan', 'Cesare Campagnano', 'Lorenzo Lastilla', 'Giovanni Trappolini', 'Giorgio Barnabò'] | 2021-04-01 | null | null | null | null | ['music-generation', 'music-generation'] | ['audio', 'music'] | [ 6.78992748e-01 1.90812141e-01 4.83153194e-01 1.40317246e-01
-7.77400672e-01 -1.11019802e+00 7.53936529e-01 -4.74865526e-01
-2.31216744e-01 7.01926410e-01 -8.90732463e-03 7.80785307e-02
-5.97830638e-02 -9.37733710e-01 -9.06570196e-01 -7.89470792e-01
1.93431914e-01 4.57981020e-01 -2.03381525e-03 -3.98163974e-01
1.13648124e-01 4.67786729e-01 -1.74023676e+00 4.51620877e-01
5.01182973e-01 8.07270646e-01 1.37491018e-01 1.04710293e+00
1.20497592e-01 5.64828813e-01 -9.62616265e-01 -6.01231992e-01
5.06523967e-01 -1.11038673e+00 -6.74109459e-01 -2.73163188e-02
3.63978595e-01 7.95714334e-02 -3.65554206e-02 1.12590218e+00
7.28737533e-01 -1.45018235e-01 8.31869304e-01 -1.23951221e+00
-5.22824168e-01 1.15163434e+00 -1.29953660e-02 -4.52450752e-01
5.15624881e-01 3.50174308e-01 1.01454175e+00 -5.76713562e-01
8.40641141e-01 9.95644510e-01 7.10213065e-01 6.29410803e-01
-1.54400909e+00 -6.62867010e-01 -7.50933051e-01 8.37831944e-02
-1.24550176e+00 -4.57186878e-01 9.16704476e-01 -4.88931686e-01
1.46024078e-01 6.55367970e-01 1.06641984e+00 1.38473737e+00
-1.89791262e-01 6.50761724e-01 1.30324686e+00 -8.40472043e-01
1.85323417e-01 1.37599707e-01 -8.14251184e-01 1.74645767e-01
-3.54130626e-01 2.96705037e-01 -5.70672870e-01 9.24613923e-02
1.08805418e+00 -5.58817804e-01 -3.01065683e-01 -5.09360321e-02
-1.52400744e+00 6.03428245e-01 3.50331873e-01 6.75422609e-01
-4.14288461e-01 5.22306979e-01 2.42457271e-01 4.12816495e-01
-1.67053025e-02 9.47420895e-01 5.24466857e-02 -1.73734874e-01
-1.20745802e+00 5.86385369e-01 1.02955401e+00 5.93915343e-01
4.53917086e-01 3.72985631e-01 -3.22331250e-01 4.40730453e-01
-1.16378635e-01 6.35557830e-01 4.89353627e-01 -1.09817982e+00
1.78346634e-02 2.61062868e-02 -3.60124893e-02 -9.57247615e-01
-5.15921786e-02 -4.84212726e-01 -9.85032141e-01 5.75860977e-01
7.14768767e-01 -1.45047471e-01 -5.38287461e-01 1.79589677e+00
3.57845537e-02 3.88828516e-01 7.75566772e-02 1.01453447e+00
4.54205662e-01 5.90477467e-01 -4.75307673e-01 -6.67778999e-02
1.32766044e+00 -7.23661840e-01 -5.66303015e-01 3.88211131e-01
-7.73488209e-02 -1.19993889e+00 1.30070198e+00 8.11015069e-01
-1.36005998e+00 -8.23332906e-01 -1.07922196e+00 1.20515019e-01
-2.29843244e-01 1.34273902e-01 2.92131066e-01 5.01747549e-01
-1.24313140e+00 8.61015499e-01 -2.38132730e-01 -4.92740534e-02
1.42734841e-01 1.04990974e-01 -1.92464158e-01 5.57128370e-01
-1.18542051e+00 5.89395463e-01 3.59529912e-01 -6.15435354e-02
-9.24737513e-01 -5.65856099e-01 -3.25859100e-01 8.20253491e-02
1.10087924e-01 -1.05244768e+00 1.33270228e+00 -1.48076141e+00
-2.11706090e+00 1.02707827e+00 3.98344636e-01 -6.60966158e-01
8.55621874e-01 3.72473300e-02 -3.07368487e-01 9.84950066e-02
-1.07205637e-01 7.79303908e-01 1.31978810e+00 -1.43516302e+00
-3.04072946e-01 2.15113367e-04 -6.06755912e-02 5.45999855e-02
-6.31415248e-02 -2.05416784e-01 -2.58628279e-01 -1.16650832e+00
-2.55783617e-01 -1.13906610e+00 -3.74671444e-02 -1.72375962e-01
-6.73121035e-01 3.72584313e-01 3.65883529e-01 -4.84869123e-01
8.32478285e-01 -2.28405476e+00 5.60741425e-01 3.40637177e-01
-8.26384798e-02 3.31108451e-01 -2.64463544e-01 5.55128574e-01
-2.05061063e-01 -5.52905053e-02 -4.41255182e-01 -2.37320527e-01
2.08654910e-01 -8.36720094e-02 -8.68581533e-01 2.78730672e-02
4.52122279e-02 1.00249112e+00 -9.27705467e-01 -3.28594834e-01
3.83536518e-02 5.58905602e-01 -5.98073184e-01 2.96572655e-01
-4.62552100e-01 8.56296182e-01 -3.75401080e-02 1.49183631e-01
2.28983119e-01 2.58250326e-01 4.53150198e-02 -2.44754463e-01
-8.47526193e-02 2.48936079e-02 -1.21039999e+00 2.11504531e+00
-6.35695815e-01 7.87940979e-01 -5.21933511e-02 -7.35723078e-01
1.13349915e+00 5.85200667e-01 5.04288793e-01 -5.83275139e-01
2.21579209e-01 2.88254857e-01 1.49837777e-01 -2.54481077e-01
5.55284560e-01 -3.88703376e-01 -2.13892803e-01 5.77733994e-01
9.70599204e-02 -9.28074241e-01 2.80899946e-02 -2.70235479e-01
1.02233827e+00 5.01385212e-01 1.34929106e-01 1.14941984e-01
4.51067895e-01 1.36391511e-02 -1.64542153e-01 6.84295475e-01
3.28418732e-01 1.04081237e+00 4.09925044e-01 -3.01910877e-01
-1.29210198e+00 -1.22365522e+00 1.69272721e-01 9.00046110e-01
-2.31195644e-01 -2.10686058e-01 -1.35067081e+00 -1.91619068e-01
-3.08717042e-01 7.39886224e-01 -5.13853192e-01 -9.01773199e-02
-5.64886153e-01 -3.03612769e-01 1.23188746e+00 -7.63309896e-02
3.28405678e-01 -1.63566387e+00 -5.66200197e-01 5.26552498e-01
-2.69042760e-01 -7.62675405e-01 -5.44431925e-01 2.08989158e-02
-5.23791790e-01 -8.82965922e-01 -1.09763563e+00 -7.85468757e-01
1.63211048e-01 -2.57583380e-01 1.29219699e+00 -1.62407860e-01
-5.00078022e-01 3.33273113e-01 -4.09961760e-01 -6.64453089e-01
-1.03519821e+00 3.60850245e-02 8.63276348e-02 2.89163440e-01
-3.85871232e-01 -1.18228078e+00 -5.68846166e-01 2.95884430e-01
-1.37235224e+00 3.68358344e-01 7.25887418e-01 6.91434741e-01
6.45036757e-01 -5.75445071e-02 7.29717731e-01 -7.64355600e-01
7.88792312e-01 8.00392106e-02 -3.36315185e-01 -3.20877992e-02
-1.76895082e-01 6.46107867e-02 8.70306134e-01 -7.24824786e-01
-5.64512789e-01 2.35206127e-01 -4.28538769e-01 -4.95847583e-01
-3.17049354e-01 1.37767941e-01 -1.60387903e-01 5.33183031e-02
9.72851157e-01 4.23606634e-01 -8.56446195e-03 -3.34846735e-01
9.02595103e-01 5.92239976e-01 1.19388342e+00 -6.10761344e-01
1.05489385e+00 4.01678234e-01 9.63178352e-02 -7.49984801e-01
-4.10849065e-01 6.37651607e-02 -5.83892167e-01 -3.83625776e-01
9.58667278e-01 -6.14313304e-01 -7.90754974e-01 5.90397954e-01
-1.29604185e+00 -4.78627801e-01 -1.07226288e+00 2.04581648e-01
-1.24192476e+00 1.18519679e-01 -5.21669805e-01 -7.05294192e-01
-4.83389407e-01 -9.32293534e-01 1.05148959e+00 4.92239110e-02
-4.10331219e-01 -6.24930680e-01 5.31645000e-01 4.89343964e-02
3.66131634e-01 5.47372341e-01 8.18356872e-01 -2.49222174e-01
-4.75779682e-01 -7.90215582e-02 1.83689058e-01 4.91620332e-01
1.36430427e-01 7.69471899e-02 -1.32157850e+00 3.68463546e-02
4.24805284e-02 -2.15907454e-01 6.35444701e-01 1.46191075e-01
1.01677871e+00 -4.41978276e-01 2.96811849e-01 5.99117994e-01
1.15729964e+00 1.73739076e-01 1.04515433e+00 2.30362475e-01
5.78837335e-01 4.56759036e-01 1.81384712e-01 2.90701926e-01
-1.79134890e-01 1.22363424e+00 3.49688977e-01 -2.47227579e-01
-6.43684804e-01 -5.73963344e-01 5.73406875e-01 8.40662897e-01
-5.31660676e-01 -2.51376122e-01 -3.73204768e-01 2.83851355e-01
-1.57972848e+00 -1.26296544e+00 -1.66084301e-02 2.09803581e+00
1.05369711e+00 3.69382906e-03 4.20345783e-01 6.61679626e-01
7.50210047e-01 -1.94255710e-01 -2.51214206e-01 -3.13548774e-01
-3.04936349e-01 9.09837484e-01 1.16765782e-01 2.23969147e-01
-8.88420820e-01 9.23175752e-01 6.35778952e+00 1.13645697e+00
-1.35058713e+00 -9.37336683e-02 2.41893962e-01 5.47464862e-02
-3.52544755e-01 -1.60542175e-01 -4.01466303e-02 3.76421899e-01
8.39934230e-01 -1.64506555e-01 1.04643571e+00 5.49745381e-01
2.28057116e-01 2.92809457e-01 -1.24064457e+00 1.08186579e+00
-7.49602972e-04 -1.31931627e+00 2.20615849e-01 7.86567554e-02
7.60117173e-01 -5.61179161e-01 3.54334831e-01 -5.85043477e-03
3.69922854e-02 -1.23635066e+00 1.35812032e+00 8.98175180e-01
1.08337593e+00 -6.70097828e-01 3.49187553e-01 2.36171395e-01
-9.99461770e-01 2.51686394e-01 8.05818290e-02 -9.97681990e-02
1.78083763e-01 5.49664974e-01 -1.12511659e+00 5.48756778e-01
3.47284198e-01 4.05289203e-01 -3.52137268e-01 9.94426012e-01
-5.07763207e-01 7.16147244e-01 -2.28736743e-01 1.40560672e-01
-1.17501812e-02 -2.95653880e-01 8.74528706e-01 1.08831358e+00
7.50052869e-01 -2.98189253e-01 -2.79957056e-01 1.29871190e+00
-1.09419599e-01 1.43015742e-01 -7.01923251e-01 -1.78032845e-01
1.22719474e-01 1.37574673e+00 -7.80313551e-01 -2.17708647e-01
3.96448821e-01 1.30855787e+00 -2.44998261e-01 9.96824652e-02
-9.80174124e-01 -5.80098093e-01 2.85565764e-01 1.87270939e-01
1.90899253e-01 -6.96402788e-02 -3.39113593e-01 -9.11401331e-01
-1.82921007e-01 -1.16119528e+00 -1.95102200e-01 -1.19811988e+00
-1.14828241e+00 8.54762197e-01 -3.97249609e-01 -1.54576433e+00
-6.32748485e-01 -3.21060151e-01 -7.93433189e-01 7.75812566e-01
-8.56045842e-01 -1.25903535e+00 -1.25595301e-01 5.54190934e-01
2.63823032e-01 -2.05421850e-01 1.18461788e+00 3.32744151e-01
7.18795657e-02 4.59134638e-01 3.62092489e-03 8.81347507e-02
8.51981640e-01 -1.37533343e+00 5.22732973e-01 5.89206576e-01
9.14191782e-01 1.59401342e-01 9.99476194e-01 -7.71662518e-02
-1.23419428e+00 -8.79975677e-01 4.74747032e-01 -4.36853051e-01
5.64107001e-01 -4.05594885e-01 -6.94699407e-01 2.15939537e-01
3.62609237e-01 -6.24286532e-01 5.20089924e-01 -5.45518100e-01
-1.54670596e-01 -9.90380198e-02 -9.57248807e-01 6.12922668e-01
9.83980000e-01 -5.86975992e-01 -6.54851615e-01 3.64351785e-04
7.05507457e-01 -3.82221907e-01 -7.39821076e-01 1.28775192e-02
7.42736101e-01 -1.20656848e+00 1.08327615e+00 -1.91194683e-01
7.52222955e-01 -5.77545345e-01 2.32720189e-03 -1.50450790e+00
-4.92058247e-02 -1.04821205e+00 2.50751406e-01 1.37863851e+00
3.62137854e-01 -2.33875632e-01 5.50754786e-01 -1.37200788e-01
-2.30122045e-01 -1.46747783e-01 -7.89137661e-01 -5.81287920e-01
-9.36473627e-03 -5.34856379e-01 8.07102680e-01 7.99412668e-01
-2.31038988e-01 2.26557136e-01 -6.51648998e-01 -1.35829002e-01
4.12432045e-01 2.75065869e-01 1.30617249e+00 -1.02534366e+00
-8.88580978e-01 -7.33780682e-01 -5.43300748e-01 -6.20226622e-01
5.65794371e-02 -1.04255283e+00 3.16963494e-01 -1.06889141e+00
-2.14103565e-01 -3.09622318e-01 -4.98336367e-03 3.13713193e-01
1.89403817e-01 1.01825690e+00 6.42159939e-01 3.09237212e-01
6.77661300e-02 3.56130987e-01 1.58453918e+00 -2.10495993e-01
-2.69219398e-01 2.67790645e-01 -4.71449703e-01 6.71799242e-01
6.36029124e-01 -5.19458234e-01 -1.48609713e-01 -1.14453413e-01
5.37772059e-01 2.05986708e-01 7.72282064e-01 -1.41255093e+00
-1.18761677e-02 1.47469372e-01 2.63555050e-01 -2.36795455e-01
4.22446072e-01 -8.08411896e-01 8.92181516e-01 4.23458695e-01
-4.30043280e-01 -2.88313150e-01 7.72825442e-03 1.86363459e-01
-4.20464575e-01 -3.05696189e-01 7.46461272e-01 -1.97179601e-01
-2.38598228e-01 -1.18005894e-01 -2.73246646e-01 -1.42893210e-01
7.84290910e-01 -1.44288525e-01 1.06553927e-01 -6.77357972e-01
-9.86633837e-01 -6.89881206e-01 5.61465800e-01 3.14240098e-01
2.90834695e-01 -1.52068853e+00 -8.78314495e-01 2.04959556e-01
-2.08999231e-01 -1.26567230e-01 1.39134318e-01 4.63439256e-01
-7.17593968e-01 8.59633312e-02 -5.00203311e-01 -5.53695500e-01
-9.57883835e-01 4.50545847e-01 2.41534218e-01 -1.75328493e-01
-5.80065787e-01 4.81257111e-01 1.24874048e-01 -2.67420441e-01
7.32776374e-02 -3.40780407e-01 -8.39245915e-02 1.35805771e-01
4.41665739e-01 2.22731397e-01 -9.00887027e-02 -5.23985088e-01
2.54528999e-01 6.71123147e-01 9.13809657e-01 -8.62283170e-01
1.35958958e+00 2.66686916e-01 -1.81031123e-01 6.86029732e-01
7.72448897e-01 3.13406318e-01 -9.34546053e-01 2.44812593e-01
-3.46149445e-01 -1.56269178e-01 -3.28944266e-01 -8.31457257e-01
-9.98213947e-01 8.04296613e-01 5.39188743e-01 7.20390081e-01
1.37088048e+00 -2.33786076e-01 8.43096673e-01 2.06612691e-01
5.77167869e-01 -6.06395125e-01 2.24906847e-01 2.86688775e-01
1.18115640e+00 -4.90075022e-01 -4.93624955e-01 -1.97821110e-01
-5.06687760e-01 1.24653482e+00 -9.11208913e-02 -2.65186250e-01
2.27267057e-01 3.13788235e-01 2.47149378e-01 1.15046114e-01
-1.80507302e-01 -2.42516011e-01 4.89573449e-01 6.97511911e-01
3.35677683e-01 2.03024611e-01 -6.77329376e-02 7.60952532e-01
-1.12999129e+00 3.37145448e-01 5.62709868e-01 3.67688000e-01
-1.40888944e-01 -1.41721213e+00 -7.56858349e-01 -1.43618122e-01
-3.89437944e-01 -9.35766473e-02 -7.27395952e-01 5.85429549e-01
5.57087243e-01 6.43493533e-01 7.68843247e-03 -5.82839847e-01
4.17221934e-01 1.47817105e-01 8.49511564e-01 -4.01256055e-01
-9.04953897e-01 1.95351839e-01 -1.63567677e-01 -2.37525225e-01
-5.77453613e-01 -4.08266932e-01 -9.03976619e-01 -2.10153744e-01
-1.03149980e-01 2.52472669e-01 8.41961026e-01 6.28829539e-01
7.84004703e-02 8.65044475e-01 7.60150850e-01 -1.45496726e+00
-3.01247954e-01 -9.16231275e-01 -7.93685675e-01 6.88972056e-01
7.23147541e-02 -8.30830261e-02 -3.21109831e-01 7.52327442e-01] | [15.843621253967285, 5.616282939910889] |
83176151-55ac-4ac9-a7af-3db1f7d4db21 | artificial-intelligence-for-emergency | 2306.10068 | null | https://arxiv.org/abs/2306.10068v1 | https://arxiv.org/pdf/2306.10068v1.pdf | Artificial Intelligence for Emergency Response | Emergency response management (ERM) is a challenge faced by communities across the globe. First responders must respond to various incidents, such as fires, traffic accidents, and medical emergencies. They must respond quickly to incidents to minimize the risk to human life. Consequently, considerable attention has been devoted to studying emergency incidents and response in the last several decades. In particular, data-driven models help reduce human and financial loss and improve design codes, traffic regulations, and safety measures. This tutorial paper explores four sub-problems within emergency response: incident prediction, incident detection, resource allocation, and resource dispatch. We aim to present mathematical formulations for these problems and broad frameworks for each problem. We also share open-source (synthetic) data from a large metropolitan area in the USA for future work on data-driven emergency response. | ['Ayan Mukhopadhyay'] | 2023-06-15 | null | null | null | null | ['management'] | ['miscellaneous'] | [ 3.59545499e-01 -1.80813089e-01 8.00528377e-02 -3.06834340e-01
-7.15201795e-01 -1.60042509e-01 1.58141613e-01 7.61129677e-01
-7.87625790e-01 7.79988468e-01 6.24372840e-01 -5.63654304e-01
-6.87400103e-01 -1.01133895e+00 1.78515360e-01 -4.24813509e-01
-2.19156608e-01 5.47687769e-01 -1.57970384e-01 -5.28259158e-01
3.51846665e-01 8.82817090e-01 -9.37167704e-01 1.18145980e-01
6.21508598e-01 8.49207938e-01 -5.56866862e-02 5.04661262e-01
3.06896627e-01 8.54860961e-01 -3.85975212e-01 2.61153251e-01
2.08951488e-01 -1.74435303e-01 -9.21396077e-01 2.11084895e-02
-8.25510859e-01 -3.58903229e-01 -4.50699866e-01 2.73754328e-01
9.53111231e-01 7.12150872e-01 8.71613443e-01 -1.31051636e+00
1.08736651e-02 1.81046516e-01 -4.90575910e-01 6.46672606e-01
6.16828084e-01 2.16264203e-01 3.76707971e-01 -8.55093420e-01
2.59484857e-01 8.94343197e-01 3.69310349e-01 5.80434501e-01
-9.01330590e-01 -3.12019408e-01 2.11845174e-01 2.74614364e-01
-1.46753943e+00 -5.82063496e-01 1.93962187e-01 -4.19979244e-01
1.37763560e+00 5.25411189e-01 9.21990648e-02 5.11555195e-01
-3.73981558e-02 2.65235364e-01 3.57144147e-01 -3.53551149e-01
3.12584817e-01 -1.26129627e-01 2.14863241e-01 -4.26399522e-02
7.40770064e-03 1.08720042e-01 -3.25275324e-02 -4.00945961e-01
2.50031441e-01 4.23928648e-01 -3.77144039e-01 3.14245671e-01
-1.03030944e+00 7.67283916e-01 3.18405360e-01 -1.20017352e-02
-1.07105243e+00 -2.52621055e-01 5.02292216e-01 1.29793689e-01
3.27338159e-01 7.01319948e-02 -2.05023617e-01 -3.76559496e-02
-5.02788663e-01 2.44333848e-01 7.07850158e-01 8.59750211e-01
3.33360523e-01 1.37177736e-01 -6.53648227e-02 6.66435838e-01
-1.16805337e-01 6.65009916e-01 -3.69128227e-01 -8.40437114e-01
8.68298054e-01 2.89322764e-01 3.24859798e-01 -1.39777768e+00
-9.79651749e-01 3.48191038e-02 -1.43533909e+00 -5.52717984e-01
-1.06026709e-01 -5.65936029e-01 -2.82974273e-01 1.28326809e+00
2.64542788e-01 -4.27872613e-02 -1.08339358e-02 9.23908293e-01
3.52870703e-01 8.35223019e-01 5.20705640e-01 -6.46094978e-01
1.07564592e+00 -2.75462091e-01 -5.09700656e-01 -3.79445106e-01
5.91936231e-01 -4.93295312e-01 2.14795738e-01 -5.43312579e-02
-1.10699284e+00 -1.45453436e-03 9.73481312e-02 4.73676711e-01
-1.56850904e-01 -4.22321737e-01 1.07816532e-01 1.86545447e-01
-5.09161592e-01 -8.23609084e-02 -3.73773217e-01 -7.42482483e-01
1.11622795e-01 2.92337269e-01 -1.70650870e-01 -2.61125326e-01
-1.18314779e+00 9.72790062e-01 2.32849538e-01 9.77247730e-02
-4.93829519e-01 -6.10660136e-01 -7.09616303e-01 1.76737338e-01
4.19175655e-01 -9.01140511e-01 1.07352316e+00 7.81191289e-02
-4.15727466e-01 5.84596217e-01 -1.13240458e-01 -3.23874980e-01
1.47793740e-01 1.35029480e-01 -7.31611490e-01 2.15272740e-01
7.92343542e-02 2.36238047e-01 2.24941298e-01 -8.40314209e-01
-9.54823673e-01 -2.70697683e-01 -1.25792027e-01 1.77647561e-01
-1.41553074e-01 7.96598136e-01 4.32176709e-01 -4.84413058e-01
-1.74337268e-01 -8.36899996e-01 -9.37919736e-01 -6.71438992e-01
-2.28320897e-01 -6.34529488e-03 4.48621035e-01 -5.04833221e-01
1.68476188e+00 -2.02842093e+00 -1.92442060e-01 3.43687117e-01
-1.15072943e-01 1.69943824e-01 -1.76174894e-01 1.16803086e+00
-3.58088106e-01 4.00094539e-01 -2.02052653e-01 -2.79753618e-02
-2.34153748e-01 1.56097293e-01 -7.47734368e-01 4.38974440e-01
1.10918701e-01 2.94410139e-01 -7.41478801e-01 -1.71908170e-01
3.47551376e-01 1.68028921e-01 -4.05733585e-01 2.95117587e-01
3.11547250e-01 7.32273281e-01 -6.29244030e-01 5.78617096e-01
2.80403614e-01 2.56914869e-02 -2.01119199e-01 3.61294746e-01
-5.03130019e-01 2.18668565e-01 -9.44982529e-01 6.70976996e-01
-5.63097298e-01 3.13852161e-01 2.64920264e-01 -1.35597467e+00
6.43384814e-01 7.47366905e-01 1.01891589e+00 -8.46121430e-01
2.44496971e-01 3.43298502e-02 -3.61668557e-01 -7.16399252e-01
4.83530790e-01 -9.89599600e-02 -4.99865919e-01 9.36905265e-01
-1.08108318e+00 1.97817653e-01 2.36879379e-01 2.89663285e-01
1.29042423e+00 -1.09602070e+00 4.68991369e-01 -7.37946555e-02
2.83183604e-01 3.43966842e-01 5.41513562e-01 5.45584261e-01
-2.87575364e-01 3.85353744e-01 1.42753152e-02 -9.61882174e-01
-9.40833926e-01 -7.63639808e-01 9.46648940e-02 9.61052418e-01
-1.18026122e-01 4.00957465e-02 -4.71911430e-01 -8.17150325e-02
-2.37678245e-01 9.09728467e-01 1.13420887e-02 -1.64661154e-01
-9.03512895e-01 -9.70209897e-01 1.90154970e-01 5.18526733e-01
3.68179262e-01 -1.16476488e+00 -8.66317213e-01 5.83367109e-01
-8.18850696e-01 -1.18675029e+00 -5.28290451e-01 -6.86472282e-02
-3.72531801e-01 -1.24487865e+00 -5.65988839e-01 -3.94765198e-01
7.90566146e-01 6.36152208e-01 7.63243258e-01 2.29690835e-01
-7.36114740e-01 9.73142207e-01 -4.46834415e-01 -3.38117033e-01
4.55811247e-03 4.06687744e-02 5.59745431e-01 -2.09224876e-02
4.28567261e-01 -2.78273791e-01 -8.26480448e-01 5.00721276e-01
-9.95263338e-01 -4.17302430e-01 -1.36380792e-01 2.81890869e-01
4.95819777e-01 2.85374612e-01 9.70040381e-01 -3.12053770e-01
1.06029296e+00 -1.00521028e+00 -2.38980576e-01 2.07654878e-01
-3.18580866e-01 -5.10505319e-01 5.32679200e-01 8.35796744e-02
-7.68504500e-01 -1.33933872e-01 -7.02172592e-02 3.87232304e-01
-6.37739182e-01 6.62074089e-01 2.63593107e-01 2.60405213e-01
6.87563062e-01 6.30120635e-02 -4.57405925e-01 -1.95418507e-01
-2.74100393e-01 1.04956698e+00 3.02026689e-01 -4.10300285e-01
5.34809053e-01 4.06988025e-01 1.28617525e-01 -1.09232950e+00
-6.66265905e-01 -9.26740885e-01 -1.96838543e-01 -3.70786518e-01
6.86159909e-01 -6.76993847e-01 -1.03113770e+00 2.04958886e-01
-1.33037198e+00 -1.68253034e-01 -1.36303201e-01 3.41811895e-01
-5.04889131e-01 7.74805769e-02 -4.66728151e-01 -1.25111961e+00
-4.85705644e-01 -5.44184029e-01 7.80716658e-01 2.09423393e-01
-4.32431698e-01 -9.62724805e-01 2.01586619e-01 1.37838587e-01
7.46364236e-01 4.54932719e-01 8.94371748e-01 -3.93921077e-01
-5.11360109e-01 -3.18741500e-01 -3.14188629e-01 -9.79997218e-02
8.76447037e-02 -1.78753495e-01 -3.53474021e-01 -4.17537868e-01
-1.08311482e-01 4.64725494e-02 6.19102478e-01 5.48886299e-01
9.41565096e-01 -5.84678113e-01 -5.69109797e-01 1.49762362e-01
1.16974330e+00 5.59577048e-01 6.46640420e-01 3.47694546e-01
-5.20741241e-03 1.18793344e+00 8.43557954e-01 1.22969830e+00
7.04919100e-01 3.86265755e-01 3.84253442e-01 -1.37305498e-01
7.86458313e-01 2.22419456e-01 -1.62463561e-01 6.14559472e-01
-2.45001554e-01 -1.01641273e+00 -1.66759992e+00 6.99756444e-01
-2.01510739e+00 -1.41936123e+00 -4.42444086e-01 2.09850335e+00
4.43274528e-02 -3.76374453e-01 2.97272384e-01 3.14205259e-01
6.93195760e-01 -2.11522922e-01 -1.81115106e-01 -5.04204273e-01
6.87716231e-02 -1.85083047e-01 4.93303776e-01 3.45610857e-01
-9.44253564e-01 3.84860992e-01 7.14854288e+00 2.92304933e-01
-9.09899056e-01 -2.78549284e-01 9.07431006e-01 -3.80472168e-02
-2.99049765e-02 -1.02187172e-01 -5.99727511e-01 2.90414929e-01
1.25733626e+00 -5.58355510e-01 5.98401427e-01 5.81466317e-01
1.09232497e+00 -3.11358213e-01 -6.14687920e-01 7.89496481e-01
-3.42992723e-01 -1.09935474e+00 -2.24009454e-01 -9.88520905e-02
4.67436284e-01 -1.06021740e-01 -5.11532463e-02 9.16179493e-02
1.20213218e-01 -9.02279854e-01 -8.76709912e-03 9.40270960e-01
7.32159972e-01 -1.17336488e+00 6.91025972e-01 8.12551856e-01
-1.26816785e+00 -6.49276853e-01 -9.71146747e-02 -5.35702705e-01
1.08947623e+00 5.45475125e-01 -5.72315991e-01 3.19207907e-01
6.68299735e-01 1.99781936e-02 3.10220212e-01 1.20620155e+00
1.22160934e-01 3.11926603e-01 -4.10542697e-01 2.93623090e-01
1.61516920e-01 4.54966314e-02 5.71673632e-01 1.05184054e+00
3.16919982e-01 1.14710391e+00 7.12510765e-01 1.63127005e-01
4.76895124e-01 5.81313623e-03 -6.90088391e-01 9.11041945e-02
6.09689832e-01 8.79310429e-01 -5.00916183e-01 -6.07930915e-03
-2.27212787e-01 6.31709218e-01 -1.27456695e-01 6.45073950e-01
-7.67428517e-01 -5.49511909e-01 8.16528320e-01 7.35244095e-01
-4.89880860e-01 -4.65633720e-01 -5.89178167e-02 -5.41722417e-01
-4.00018811e-01 -5.67664742e-01 6.68613970e-01 -5.19621968e-01
-1.30943429e+00 6.13230407e-01 4.05515820e-01 -1.09561574e+00
-5.69033444e-01 -2.32322440e-01 -7.06807971e-01 9.64068234e-01
-1.40464127e+00 -2.79649496e-01 -2.64958173e-01 8.41873169e-01
4.21639323e-01 -2.74996012e-02 9.42635775e-01 7.95430839e-01
-9.48709905e-01 -4.31319103e-02 -1.64870381e-01 9.62010846e-02
5.05872190e-01 -3.84024918e-01 3.89993787e-01 6.84980392e-01
-8.11190307e-01 4.52914029e-01 5.09644806e-01 -5.87398052e-01
-8.66939485e-01 -1.32131410e+00 1.42095160e+00 -6.72163963e-02
3.86819035e-01 1.90654323e-01 -5.34793437e-01 4.14446354e-01
4.88918535e-02 -3.32882792e-01 8.05076063e-01 -2.89303273e-01
4.21857268e-01 -3.41632478e-02 -1.21864557e+00 6.18181407e-01
8.50130081e-01 -3.59165072e-01 5.31579442e-02 6.08279109e-01
4.58984286e-01 3.58745281e-04 -4.19030428e-01 3.47531229e-01
-1.36250168e-01 -7.23277688e-01 9.20742333e-01 -8.89625847e-01
-1.83770955e-01 4.19072323e-02 -2.04838768e-01 -1.28021574e+00
-5.91054916e-01 -7.10872591e-01 3.55608970e-01 8.42304826e-01
1.00905336e-01 -7.62776792e-01 1.89005792e-01 1.49247396e+00
-1.51342601e-01 -5.37433505e-01 -8.18420589e-01 -5.09576201e-01
-2.44574308e-01 -7.21304774e-01 6.43045902e-01 7.31992662e-01
1.73816547e-01 1.00491032e-01 -5.44858277e-01 3.33973944e-01
5.37604928e-01 -1.70254573e-01 4.85762000e-01 -1.05683124e+00
4.48191941e-01 -1.35164335e-01 -4.86285761e-02 -6.13014221e-01
-9.81789082e-02 -3.60634416e-01 -5.10565750e-02 -1.76910508e+00
1.78540006e-01 -6.62961245e-01 -1.44195989e-01 6.85714722e-01
1.71275154e-01 -1.90718666e-01 2.41599083e-02 7.39272907e-02
-5.23837566e-01 3.95096660e-01 4.81203049e-01 -6.10298663e-02
-2.16614023e-01 3.90498936e-01 -5.00202656e-01 5.58567822e-01
1.38309550e+00 -8.78330708e-01 -1.73486680e-01 -5.40383101e-01
4.49951857e-01 8.11577320e-01 5.63658655e-01 -7.27749228e-01
6.34786010e-01 -1.05041850e+00 -2.92973071e-01 -5.47250807e-01
-2.88101123e-03 -1.22816992e+00 4.49339896e-01 4.86853719e-01
-1.79076508e-01 6.40307605e-01 1.13664433e-01 5.46607137e-01
-2.47779816e-01 2.01179795e-02 6.22149110e-01 2.52831336e-02
-4.90584224e-01 6.27140164e-01 -1.07383180e+00 2.76264936e-01
1.41492510e+00 -1.21460587e-03 -4.62459803e-01 -7.60070324e-01
-8.64022672e-01 7.44719982e-01 -4.59356606e-02 2.98425913e-01
8.99236679e-01 -1.02475679e+00 -9.95411813e-01 -3.17724012e-02
-1.25182167e-01 -1.71102732e-01 7.81249344e-01 1.12731552e+00
-5.09934187e-01 6.65601432e-01 1.39762079e-02 -1.97060429e-03
-1.01453745e+00 7.36364603e-01 2.12053373e-01 -2.32169375e-01
-3.18186045e-01 3.55054617e-01 -1.36638418e-01 -2.04806954e-01
2.38576964e-01 2.17254311e-01 6.08114861e-02 1.93922251e-01
9.89908159e-01 1.08393729e+00 7.05982978e-03 -6.94764078e-01
-6.46498322e-01 2.02378511e-01 3.03889900e-01 5.00029251e-02
1.39248681e+00 -5.16689479e-01 -8.34570229e-02 -2.64654905e-01
8.00437629e-01 -3.43158752e-01 -4.73731846e-01 -1.25023112e-01
8.84954855e-02 -2.74764955e-01 -4.45595086e-02 -4.23755229e-01
-8.81594181e-01 8.19791615e-01 2.25525334e-01 6.19703650e-01
1.54389238e+00 -3.62922430e-01 1.09688687e+00 4.66025651e-01
6.35792196e-01 -1.27238703e+00 -1.20938890e-01 7.36282825e-01
9.52854216e-01 -1.05043745e+00 -2.88420707e-01 -1.46845087e-01
-7.60090590e-01 9.03878987e-01 1.88022092e-01 8.27164799e-02
9.39394116e-01 3.12069654e-01 -2.12627128e-01 -2.84144469e-02
-8.02924275e-01 -2.13233873e-01 -2.32574299e-01 7.38783300e-01
1.29582286e-01 1.02520794e-01 -3.01306993e-01 4.43150252e-01
4.76379216e-01 -2.59372801e-01 4.50037062e-01 1.09850228e+00
-7.17712462e-01 -9.16510165e-01 -5.87502360e-01 3.87276858e-01
-2.32777417e-01 -3.15225631e-01 -2.48339087e-01 4.93429303e-01
-1.60899267e-01 1.57767189e+00 1.36996731e-01 -2.55663484e-01
7.46701241e-01 -2.15939417e-01 -3.64073575e-01 -5.59088707e-01
-5.87430298e-01 -3.81842554e-01 1.29792541e-01 -3.02210599e-01
-2.66058713e-01 -6.47195220e-01 -1.60285676e+00 -1.02030766e+00
8.62413719e-02 1.78723812e-01 3.82299662e-01 7.78773844e-01
6.06143236e-01 6.09581292e-01 1.00985384e+00 -5.99613667e-01
-3.74687493e-01 -4.90946382e-01 -5.49153984e-01 9.40428465e-04
2.64542997e-01 -3.26481104e-01 -3.58829588e-01 -2.17882410e-01] | [6.147292137145996, 3.9482293128967285] |
deb29f8f-d1f7-4a83-bf83-84f22cc9e8dc | unsupervised-video-object-segmentation-via | 2209.03712 | null | https://arxiv.org/abs/2209.03712v1 | https://arxiv.org/pdf/2209.03712v1.pdf | Unsupervised Video Object Segmentation via Prototype Memory Network | Unsupervised video object segmentation aims to segment a target object in the video without a ground truth mask in the initial frame. This challenging task requires extracting features for the most salient common objects within a video sequence. This difficulty can be solved by using motion information such as optical flow, but using only the information between adjacent frames results in poor connectivity between distant frames and poor performance. To solve this problem, we propose a novel prototype memory network architecture. The proposed model effectively extracts the RGB and motion information by extracting superpixel-based component prototypes from the input RGB images and optical flow maps. In addition, the model scores the usefulness of the component prototypes in each frame based on a self-learning algorithm and adaptively stores the most useful prototypes in memory and discards obsolete prototypes. We use the prototypes in the memory bank to predict the next query frames mask, which enhances the association between distant frames to help with accurate mask prediction. Our method is evaluated on three datasets, achieving state-of-the-art performance. We prove the effectiveness of the proposed model with various ablation studies. | ['Sangyoun Lee', 'Chaewon Park', 'Seunghoon Lee', 'Suhwan Cho', 'Minhyeok Lee'] | 2022-09-08 | null | null | null | null | ['unsupervised-video-object-segmentation', 'self-learning'] | ['computer-vision', 'natural-language-processing'] | [ 2.16644153e-01 -1.28384471e-01 -4.46202129e-01 -1.09215751e-01
-3.11191022e-01 -3.45580786e-01 7.35923499e-02 6.61932305e-02
-7.33094931e-01 5.97848654e-01 -5.14624715e-02 3.41374278e-01
-2.92791636e-03 -5.78286469e-01 -6.50546789e-01 -6.76817000e-01
-9.12618730e-03 1.38468623e-01 9.57605302e-01 2.04445675e-01
4.86190438e-01 4.28775966e-01 -1.69977653e+00 4.65366215e-01
8.72301400e-01 1.31678867e+00 7.60784686e-01 4.27702427e-01
-2.67654002e-01 1.07121527e+00 -5.05222082e-01 5.09083606e-02
3.46155941e-01 -4.53467965e-01 -8.86458576e-01 2.62304574e-01
6.29159272e-01 -7.56171942e-01 -4.70187724e-01 1.09401989e+00
7.62693435e-02 4.62116539e-01 2.60259628e-01 -1.17469728e+00
-2.18400449e-01 5.21051884e-01 -3.95781696e-01 6.87439978e-01
1.51640505e-01 2.51985013e-01 7.42347240e-01 -1.04602945e+00
8.27358007e-01 8.83304656e-01 1.70164570e-01 5.06629527e-01
-8.55958462e-01 -5.90108514e-01 4.72706795e-01 7.34233797e-01
-1.51990354e+00 -5.27857780e-01 9.32695389e-01 -3.97906393e-01
8.34155262e-01 1.78013101e-01 1.04314435e+00 5.35121083e-01
-1.44419834e-01 1.03240216e+00 5.98796010e-01 -1.01757824e-01
3.21646035e-01 8.91638696e-02 2.23665863e-01 1.04602504e+00
6.32929951e-02 -8.63494934e-04 -7.92679548e-01 2.92139411e-01
9.38674152e-01 2.30832696e-01 -6.88463926e-01 -3.73639345e-01
-1.34996569e+00 4.02708620e-01 7.78899908e-01 4.33512747e-01
-5.66765368e-01 6.14472665e-02 -1.27865896e-01 -1.38912335e-01
6.59482032e-02 2.87568837e-01 -3.60629857e-01 -1.06476126e-02
-1.49884367e+00 -2.70113736e-01 3.69516581e-01 8.27631593e-01
1.12705612e+00 -6.55490020e-03 -3.54441345e-01 5.82028389e-01
2.29422122e-01 4.98373844e-02 5.24637341e-01 -1.44978464e+00
3.11206251e-01 8.01912248e-01 2.03983858e-01 -1.07586479e+00
-3.34628046e-01 -3.15134495e-01 -6.21646225e-01 1.13115229e-01
4.60657358e-01 1.40594900e-01 -1.07734179e+00 1.43687820e+00
4.50566560e-01 8.82180631e-01 -1.96518913e-01 1.33577347e+00
9.26401377e-01 7.61098504e-01 1.04008518e-01 -6.16717994e-01
7.33169138e-01 -1.32943416e+00 -5.66750348e-01 -3.02590936e-01
2.68626750e-01 -5.77446997e-01 6.54046416e-01 2.03340292e-01
-1.23338366e+00 -9.69575047e-01 -1.02133560e+00 -4.32233401e-02
-2.66064275e-02 1.53669536e-01 3.44714254e-01 3.07057053e-01
-1.04111040e+00 7.47522950e-01 -9.46131825e-01 -1.32665351e-01
5.98932564e-01 5.44713616e-01 -2.15376571e-01 -1.35135576e-01
-9.11617219e-01 5.42624235e-01 8.43557537e-01 3.48816693e-01
-1.03855574e+00 -5.72497368e-01 -6.86942101e-01 1.26417145e-01
4.47975487e-01 -6.09381318e-01 7.24333584e-01 -1.33825374e+00
-1.28166211e+00 4.44560528e-01 -3.73349249e-01 -4.27598804e-01
4.74386483e-01 -2.35244229e-01 -8.34597945e-02 6.53720915e-01
-8.59785229e-02 1.35933495e+00 1.15714371e+00 -1.07958150e+00
-1.09898150e+00 -1.07061982e-01 7.79408813e-02 3.10220748e-01
-5.05637407e-01 -2.70869732e-01 -1.07753158e+00 -5.68030894e-01
3.72685671e-01 -8.24175000e-01 -1.41933665e-01 1.68940842e-01
-1.86031669e-01 -1.30932912e-01 1.02215707e+00 -7.23681211e-01
1.41584635e+00 -2.08648396e+00 3.06357384e-01 1.34683311e-01
2.38320276e-01 4.66061980e-01 -1.74408734e-01 -3.96031857e-01
2.69611776e-01 -2.02764526e-01 -3.09457749e-01 -9.68477279e-02
-5.93664765e-01 1.79118812e-01 -8.23130086e-02 3.53123337e-01
2.83021361e-01 8.76768172e-01 -1.01945674e+00 -1.03707480e+00
5.54808378e-01 3.62094522e-01 -7.14415491e-01 3.08969378e-01
-2.95691311e-01 6.89689279e-01 -4.56650198e-01 7.00577497e-01
3.89543027e-01 -3.78784955e-01 -4.50795740e-02 -5.35033703e-01
-1.07253045e-02 -1.00456201e-01 -1.33078051e+00 2.08506513e+00
2.68120319e-01 6.63825929e-01 -2.44592413e-01 -1.00090373e+00
6.64460778e-01 7.67451385e-03 7.66257405e-01 -6.22318387e-01
7.10073784e-02 7.43011534e-02 1.31017372e-01 -7.06223249e-01
5.48679113e-01 4.51713741e-01 4.63667214e-01 2.60309041e-01
1.63276851e-01 3.81158143e-01 4.71592426e-01 1.05739802e-01
8.55918765e-01 3.90069932e-01 -7.71315023e-02 8.25251043e-02
7.13268638e-01 7.16882199e-02 7.49187827e-01 7.10423350e-01
-5.55344105e-01 7.05198765e-01 5.51661402e-02 -5.93397975e-01
-7.25833476e-01 -8.63943756e-01 2.33763069e-01 8.26388955e-01
7.07943797e-01 -2.99848557e-01 -7.37643480e-01 -8.37521255e-01
-2.76489377e-01 4.54822630e-01 -5.46186090e-01 -3.16073924e-01
-8.01157713e-01 -4.85003412e-01 -1.19731247e-01 5.15160978e-01
8.17034304e-01 -1.24507833e+00 -1.03198922e+00 2.10979939e-01
-5.79963982e-01 -1.13877976e+00 -5.32757878e-01 -2.01972008e-01
-1.07862234e+00 -1.14586830e+00 -6.90871775e-01 -1.02480114e+00
8.39601159e-01 5.28683066e-01 9.24569547e-01 3.72592479e-01
-2.85314083e-01 2.24187434e-01 -2.67682046e-01 3.82926136e-01
-1.53192401e-01 -3.95477973e-02 -2.72569358e-01 3.17028135e-01
1.90140963e-01 -1.51530251e-01 -1.09479403e+00 4.14231181e-01
-8.52833271e-01 3.14272404e-01 6.09121442e-01 6.13165498e-01
8.49742830e-01 4.54785069e-03 2.53610194e-01 -4.06650305e-01
-3.01939156e-02 -2.04783916e-01 -5.07206321e-01 3.26438665e-01
-2.39963800e-01 7.70901963e-02 2.57747561e-01 -4.49285209e-01
-8.04958522e-01 4.19258237e-01 2.92440563e-01 -8.72581124e-01
-5.60428351e-02 2.32017130e-01 3.05997510e-03 -6.51743710e-02
2.97256440e-01 3.59917909e-01 -1.68716401e-01 -2.09016293e-01
3.97054046e-01 4.26409572e-01 6.81234956e-01 -1.54994875e-01
3.41654181e-01 5.84135056e-01 -1.70814738e-01 -7.52410233e-01
-8.31095040e-01 -6.28053010e-01 -9.34022188e-01 -7.31204629e-01
9.63212967e-01 -8.76019239e-01 -5.53496957e-01 2.72611797e-01
-1.08342457e+00 -2.70080000e-01 -3.15643549e-01 5.88136733e-01
-4.44864631e-01 4.53482032e-01 -5.70074499e-01 -6.35650337e-01
-2.76854098e-01 -1.30161798e+00 8.33323956e-01 5.32075584e-01
-2.12211698e-01 -4.33614224e-01 -2.85807371e-01 2.72131473e-01
1.11425184e-01 -2.39999723e-02 6.12781286e-01 -2.13188946e-01
-1.24412441e+00 5.89275360e-02 -3.13121766e-01 3.92010093e-01
1.12154946e-01 7.54818991e-02 -7.94257402e-01 -2.19657511e-01
2.33923085e-02 -9.44630150e-03 1.31207752e+00 5.48638701e-01
1.27786601e+00 -1.26500800e-01 -4.84756202e-01 6.45528972e-01
1.30770242e+00 3.08672190e-01 5.68261385e-01 2.36643389e-01
1.00017262e+00 5.69972992e-01 7.62052059e-01 2.71503597e-01
1.44018486e-01 6.13225043e-01 4.60649848e-01 8.75786319e-02
-4.07149315e-01 -2.45078262e-02 3.98141831e-01 7.48195410e-01
-9.14117023e-02 3.96240950e-02 -6.39169216e-01 5.75604856e-01
-2.06166577e+00 -1.05294347e+00 1.55821458e-01 2.21247888e+00
6.58330739e-01 3.41524899e-01 4.87227216e-02 3.20273731e-03
8.77853632e-01 8.63553062e-02 -7.60970592e-01 3.44467372e-01
-1.54251218e-01 1.04161445e-02 2.79269695e-01 3.87828499e-01
-1.26451921e+00 1.16093659e+00 5.73135328e+00 6.18695498e-01
-1.09078956e+00 1.53673604e-01 8.92450988e-01 -4.55289721e-01
1.31294087e-01 7.33983442e-02 -6.87374353e-01 5.93044281e-01
4.28838938e-01 1.15539014e-01 5.05467951e-01 6.46113813e-01
3.05394471e-01 -5.46823621e-01 -1.16199017e+00 1.15417135e+00
2.76034504e-01 -1.57184935e+00 2.08799124e-01 -3.37462544e-01
9.37230587e-01 2.93982606e-02 5.63550100e-04 -1.00915439e-01
-3.14160854e-01 -6.70126498e-01 8.30305099e-01 8.39013159e-01
3.97282988e-01 -6.75538301e-01 4.70442951e-01 2.32470110e-01
-1.09375989e+00 -3.57649207e-01 -4.57626969e-01 6.95283636e-02
6.11186177e-02 3.41254026e-01 -6.62103355e-01 2.37635911e-01
7.97801077e-01 9.65503633e-01 -7.50511408e-01 1.46826541e+00
-6.47991523e-02 4.12073374e-01 -3.28495979e-01 1.53258577e-01
3.09595674e-01 -2.78970927e-01 3.94982308e-01 9.24332559e-01
2.80337781e-01 8.01450610e-02 3.86979908e-01 8.68132532e-01
2.04317248e-03 1.86116919e-02 -8.50751400e-02 1.04842119e-01
4.81186837e-01 1.31469870e+00 -1.21395397e+00 -6.40680790e-01
-4.33354169e-01 1.21185935e+00 4.38688964e-01 6.46700680e-01
-8.00716341e-01 2.42996439e-02 4.07352090e-01 6.43638745e-02
5.64327002e-01 -3.16525072e-01 1.67393554e-02 -1.07680643e+00
9.07846319e-04 -4.83969063e-01 5.30611396e-01 -8.90381873e-01
-6.40887856e-01 5.96795261e-01 -2.54804075e-01 -1.42473614e+00
-3.08975756e-01 -3.23979676e-01 -2.56723106e-01 4.29001600e-01
-1.41539824e+00 -6.72818959e-01 -6.88874722e-01 7.49335170e-01
6.97789252e-01 7.66666373e-03 3.03449899e-01 3.26041758e-01
-7.68131077e-01 2.38989979e-01 -1.58533305e-01 2.79121161e-01
5.39459705e-01 -9.27740991e-01 2.12867223e-02 1.14040601e+00
4.60957497e-01 3.31980020e-01 3.36609930e-01 -7.77651191e-01
-1.11677825e+00 -1.25964022e+00 4.49343979e-01 -2.48805970e-01
2.18101636e-01 7.84102529e-02 -9.61320102e-01 3.21801871e-01
-3.95754501e-02 3.30516279e-01 3.08969587e-01 -6.81418836e-01
1.35389760e-01 -2.09776595e-01 -7.46869504e-01 4.77893382e-01
1.16638803e+00 -2.07107171e-01 -4.97152090e-01 1.09312750e-01
6.47840500e-01 -2.66147703e-01 -4.67422485e-01 4.39663202e-01
5.36561370e-01 -1.09850836e+00 9.39805269e-01 -4.32655364e-01
3.35696548e-01 -8.00355017e-01 -3.47076729e-02 -9.36035693e-01
-2.95414031e-01 -4.53532159e-01 -4.87345010e-01 9.79438186e-01
1.36816531e-01 1.27959713e-01 1.12064350e+00 7.92659521e-01
-7.26974607e-02 -6.63087487e-01 -9.33978796e-01 -3.49004149e-01
-5.80680966e-01 -3.41579795e-01 1.64761767e-01 7.74189353e-01
-2.53387868e-01 8.24250281e-02 -2.73351192e-01 1.90638795e-01
6.51947021e-01 3.97096217e-01 5.72013617e-01 -9.52705920e-01
-2.61651635e-01 -5.55390537e-01 -6.23346210e-01 -1.34397721e+00
1.95844829e-01 -8.63748252e-01 1.72974437e-01 -1.53417218e+00
3.32745254e-01 -3.32782507e-01 -6.75205767e-01 3.48853558e-01
-5.44684291e-01 5.14140844e-01 5.07228792e-01 5.37537515e-01
-1.13840985e+00 3.60574961e-01 1.38368082e+00 -4.53933924e-01
-6.03046596e-01 -2.56421417e-01 -1.54946640e-01 7.46749580e-01
5.42957485e-01 -2.76608795e-01 -4.33492571e-01 -4.56558347e-01
-2.82110423e-01 1.53610315e-02 4.92727667e-01 -1.44630730e+00
5.63042760e-01 -1.02433115e-01 9.94695425e-01 -6.70474470e-01
3.44877571e-01 -8.53574157e-01 1.50945917e-01 6.34406030e-01
-2.33296797e-01 -1.16486333e-01 1.86289269e-02 6.28653347e-01
-2.77994782e-01 -3.49661350e-01 6.87228739e-01 -2.80230820e-01
-1.50774050e+00 4.62408394e-01 7.15123024e-03 -1.34182677e-01
1.15354490e+00 -5.88746369e-01 -1.69295356e-01 -1.16319858e-01
-9.83337283e-01 2.48893663e-01 4.58532810e-01 5.93038380e-01
1.07897115e+00 -1.06582296e+00 -3.30658317e-01 5.00152230e-01
-1.07932612e-01 4.16207202e-02 4.74921525e-01 9.03761506e-01
-6.49909675e-01 1.88755229e-01 -4.41635162e-01 -9.91796196e-01
-1.07117414e+00 8.94815743e-01 3.77548993e-01 2.63666064e-01
-5.57504833e-01 9.55508590e-01 3.77321154e-01 6.35620654e-01
4.81794655e-01 -4.48335141e-01 -4.93556350e-01 1.09856337e-01
6.27756596e-01 4.07296479e-01 -1.19276427e-01 -9.44517434e-01
-3.59310180e-01 6.41295612e-01 -8.58135819e-02 -3.00150011e-02
9.37640071e-01 -4.15117890e-01 -9.95452255e-02 3.93744260e-01
1.17881525e+00 -4.84640628e-01 -1.79861069e+00 -2.79639065e-01
-7.18554598e-04 -7.50714719e-01 2.32077882e-01 -5.17037034e-01
-1.53330159e+00 7.26148665e-01 8.64098072e-01 -1.78537533e-01
1.33022940e+00 -7.98604935e-02 8.84113669e-01 1.89153954e-01
3.78028512e-01 -1.19010830e+00 3.52170765e-01 1.42561287e-01
4.49044138e-01 -1.18189657e+00 -3.98336388e-02 -4.27477986e-01
-5.34038842e-01 1.07388604e+00 8.74784052e-01 -1.24719314e-01
5.27736545e-01 -1.24082513e-01 -9.86276120e-02 1.18179269e-01
-5.40112376e-01 -4.04914349e-01 4.57440615e-01 3.86432618e-01
-1.20096402e-02 -3.40797931e-01 -1.77370444e-01 2.67876506e-01
2.58277923e-01 1.13504417e-01 3.49033624e-01 8.81030858e-01
-7.66552925e-01 -7.56081879e-01 -2.78204978e-01 5.39868712e-01
-1.89438120e-01 2.05327570e-02 -2.19402641e-01 4.29268092e-01
3.59433264e-01 9.54717278e-01 4.14061487e-01 -3.96123767e-01
4.99046221e-02 9.01797935e-02 5.85493147e-01 -2.99125344e-01
-3.52107584e-01 4.52646077e-01 -3.99426013e-01 -9.12735760e-01
-9.52701747e-01 -4.98453796e-01 -1.49547875e+00 1.46764442e-01
-3.08091402e-01 1.04911616e-02 2.93305010e-01 8.98781717e-01
4.66565132e-01 5.63522339e-01 4.69678313e-01 -1.04670191e+00
1.14656433e-01 -6.63730323e-01 -2.79035419e-01 6.21995270e-01
4.22546059e-01 -7.82636464e-01 -1.11169205e-03 4.32786733e-01] | [9.23890495300293, -0.22559285163879395] |
86862cf4-0d12-4b8d-a92f-ff39b1bb8cc2 | learning-local-recurrent-models-for-human | 2107.12847 | null | https://arxiv.org/abs/2107.12847v1 | https://arxiv.org/pdf/2107.12847v1.pdf | Learning Local Recurrent Models for Human Mesh Recovery | We consider the problem of estimating frame-level full human body meshes given a video of a person with natural motion dynamics. While much progress in this field has been in single image-based mesh estimation, there has been a recent uptick in efforts to infer mesh dynamics from video given its role in alleviating issues such as depth ambiguity and occlusions. However, a key limitation of existing work is the assumption that all the observed motion dynamics can be modeled using one dynamical/recurrent model. While this may work well in cases with relatively simplistic dynamics, inference with in-the-wild videos presents many challenges. In particular, it is typically the case that different body parts of a person undergo different dynamics in the video, e.g., legs may move in a way that may be dynamically different from hands (e.g., a person dancing). To address these issues, we present a new method for video mesh recovery that divides the human mesh into several local parts following the standard skeletal model. We then model the dynamics of each local part with separate recurrent models, with each model conditioned appropriately based on the known kinematic structure of the human body. This results in a structure-informed local recurrent learning architecture that can be trained in an end-to-end fashion with available annotations. We conduct a variety of experiments on standard video mesh recovery benchmark datasets such as Human3.6M, MPI-INF-3DHP, and 3DPW, demonstrating the efficacy of our design of modeling local dynamics as well as establishing state-of-the-art results based on standard evaluation metrics. | ['Ziyan Wu', 'Bir Bhanu', 'Terrence Chen', 'Ren Li', 'Srikrishna Karanam', 'Runze Li'] | 2021-07-27 | null | null | null | null | ['human-mesh-recovery'] | ['computer-vision'] | [ 2.05440387e-01 -3.26140895e-02 -6.20374605e-02 2.91606523e-02
-6.20178521e-01 -2.24200830e-01 3.23515981e-01 -3.42329323e-01
-1.53952911e-01 5.52792609e-01 4.45701122e-01 3.70208561e-01
1.18171431e-01 -5.74256003e-01 -9.32479858e-01 -6.28377199e-01
-2.61689931e-01 8.72923493e-01 3.36846739e-01 -2.02585533e-01
-1.74740762e-01 2.93530136e-01 -1.53879631e+00 2.01869652e-01
2.49677211e-01 5.92536151e-01 -1.20980836e-01 1.00128019e+00
3.35928828e-01 8.35175991e-01 -3.83827060e-01 -3.49470586e-01
3.54236662e-01 -4.90018129e-01 -1.07776654e+00 5.64619303e-01
9.22627568e-01 -6.02968276e-01 -7.37582922e-01 4.91065085e-01
4.99717802e-01 2.72982091e-01 5.06505311e-01 -9.24054384e-01
1.84125543e-01 5.78101426e-02 -8.72806787e-01 7.07681179e-02
7.32362509e-01 2.00061098e-01 6.73901796e-01 -6.56688571e-01
1.25881124e+00 1.37252474e+00 9.76038039e-01 5.86873889e-01
-1.50850320e+00 -4.07082558e-01 1.97260559e-01 -7.99336098e-03
-1.30212390e+00 -4.80997443e-01 7.52011776e-01 -5.53547502e-01
7.94258773e-01 1.91773893e-03 1.14372706e+00 1.16913891e+00
4.28414226e-01 8.10980141e-01 6.14915609e-01 -2.87587047e-01
-1.75699100e-01 -6.55884624e-01 -1.49338529e-01 9.97225463e-01
7.32433945e-02 -1.00192644e-01 -7.68032491e-01 -2.95009196e-01
1.06563127e+00 -8.51713568e-02 -3.41817379e-01 -8.21854949e-01
-1.34395671e+00 4.79890227e-01 8.08258057e-02 -1.39237925e-01
-4.78412777e-01 5.41795790e-01 4.86279488e-01 1.36200398e-01
5.90652823e-01 -2.37797305e-01 -2.90015846e-01 -3.50503981e-01
-1.21241367e+00 9.72037256e-01 9.65616465e-01 7.79152393e-01
5.04136801e-01 6.48179501e-02 2.26959839e-01 6.51098073e-01
2.19543055e-01 2.88674146e-01 5.06117791e-02 -1.38564408e+00
4.00284380e-01 1.09121114e-01 2.07541242e-01 -1.12037075e+00
-3.49515706e-01 -1.56011924e-01 -7.44458497e-01 2.86828816e-01
8.04385602e-01 -1.42695010e-01 -9.99701619e-01 1.87489772e+00
7.12467432e-01 6.79610729e-01 -3.98410231e-01 9.63015735e-01
5.74366033e-01 5.38757682e-01 -1.45318478e-01 -1.78478375e-01
1.29388678e+00 -9.94673550e-01 -4.78011936e-01 -1.66577145e-01
3.23129535e-01 -7.09490359e-01 6.41431630e-01 4.65153158e-01
-1.48662126e+00 -4.35309887e-01 -7.21006751e-01 -1.74744189e-01
3.52498740e-01 -3.91856581e-01 2.94793785e-01 1.27844349e-01
-7.90053010e-01 7.84344494e-01 -1.35473907e+00 -6.10081792e-01
1.73697382e-01 3.30719411e-01 -5.75281024e-01 -2.35975027e-01
-8.35080564e-01 7.07427502e-01 -6.57042414e-02 2.54747808e-01
-8.50914955e-01 -7.63351679e-01 -9.23386633e-01 -3.64602208e-01
5.08939505e-01 -1.36492097e+00 1.40816081e+00 -9.05656517e-01
-1.28843522e+00 9.11820233e-01 -4.07391489e-01 -3.68068308e-01
1.03116381e+00 -3.49908978e-01 5.09866001e-03 3.34985942e-01
5.02277315e-02 6.34943187e-01 9.71289337e-01 -1.21682239e+00
-5.04141510e-01 -2.78702974e-01 8.62849578e-02 4.76553321e-01
1.81367472e-01 -1.37453480e-02 -9.76547360e-01 -9.22951221e-01
1.41938806e-01 -1.48233330e+00 -9.78337824e-02 3.93699288e-01
-2.36889288e-01 1.56193301e-01 8.03395033e-01 -1.00815332e+00
1.18679023e+00 -1.78396928e+00 8.68077755e-01 1.57670528e-01
2.95992523e-01 -1.45637020e-01 1.77764773e-01 3.46120238e-01
1.16379395e-01 -2.41614535e-01 -3.61016214e-01 -8.48360240e-01
-3.17881584e-01 3.51630896e-01 4.74284478e-02 8.20741653e-01
-2.82299202e-02 6.69936359e-01 -8.82020354e-01 -6.49641275e-01
2.48919457e-01 8.09627950e-01 -7.20839918e-01 8.48349705e-02
-1.38611510e-01 6.92019582e-01 -2.08980232e-01 8.04428458e-01
2.30357364e-01 -3.05164844e-01 3.77422184e-01 -2.64469773e-01
1.37088940e-01 5.83692603e-02 -1.64276147e+00 2.09620881e+00
-2.15016544e-01 4.77259874e-01 4.58690882e-01 -7.76833951e-01
-4.10102680e-02 6.20017290e-01 9.86589968e-01 -1.52625442e-01
-1.69411581e-02 2.73084398e-02 -4.13975120e-02 -5.27296960e-01
4.27752316e-01 -2.21390978e-01 2.23672658e-01 3.71082842e-01
-9.99187976e-02 2.17543751e-01 1.95009783e-01 9.25476924e-02
1.19595623e+00 7.48066962e-01 8.10227096e-02 -2.92700417e-02
8.03526044e-02 1.13386698e-01 6.10842645e-01 3.71262550e-01
-1.30976290e-01 1.09242809e+00 2.58738875e-01 -5.88698626e-01
-1.14510012e+00 -9.90601361e-01 2.68568993e-02 7.42933273e-01
1.83714554e-01 -7.04333961e-01 -7.63050437e-01 -2.33351484e-01
4.60339971e-02 -7.61179551e-02 -6.26964688e-01 1.86384290e-01
-1.15448153e+00 -5.90272248e-01 3.73995513e-01 5.63788414e-01
3.36047739e-01 -1.00039065e+00 -9.15947735e-01 6.01542413e-01
-6.38753533e-01 -1.26566792e+00 -6.06552243e-01 -4.60446060e-01
-9.75763202e-01 -1.25237083e+00 -8.72441769e-01 -7.33046710e-01
5.12072027e-01 2.85251409e-01 1.43981516e+00 2.94113785e-01
-6.38920367e-01 8.01284134e-01 -6.55996948e-02 1.39723629e-01
-2.60803163e-01 -1.15061015e-01 1.70383453e-01 5.08950800e-02
-3.09243470e-01 -6.52061760e-01 -8.86144102e-01 2.83239216e-01
-7.33572781e-01 2.46500701e-01 -2.85312664e-02 7.27692306e-01
8.06682646e-01 1.17033780e-01 -9.62181166e-02 -8.05584013e-01
1.13176584e-01 -5.19574463e-01 -1.22330926e-01 -4.79457006e-02
-8.44856650e-02 -2.97877908e-01 2.06768408e-01 -6.17619574e-01
-9.11726952e-01 3.24135214e-01 -5.93210571e-02 -8.12077463e-01
-1.31401578e-02 4.20909643e-01 5.14205359e-02 -1.39732957e-01
3.60296190e-01 -1.24554366e-01 3.39458317e-01 -4.47138369e-01
9.44637507e-02 -1.80057622e-02 7.90117264e-01 -8.30997407e-01
7.95385480e-01 7.79753387e-01 1.93515047e-01 -1.14631581e+00
-5.39372921e-01 -5.07199526e-01 -7.23453641e-01 -4.51196134e-01
9.44339216e-01 -1.10249424e+00 -6.55361176e-01 7.38581896e-01
-9.87774014e-01 -5.60932755e-01 -1.28584176e-01 3.29363585e-01
-7.38324463e-01 6.62201285e-01 -1.00418639e+00 -6.30139112e-01
-1.81084663e-01 -1.12796581e+00 1.37457442e+00 -1.94956303e-01
-8.19502831e-01 -1.09906650e+00 2.69174725e-01 5.02479434e-01
-7.01724663e-02 8.89512777e-01 6.85690224e-01 2.89237022e-01
-6.42917514e-01 -2.76543736e-01 4.35069889e-01 -2.00897176e-02
-4.61365562e-03 1.24278337e-01 -4.97976422e-01 -5.07031739e-01
-2.72258192e-01 -3.77391249e-01 6.30676031e-01 6.21892154e-01
6.59643948e-01 -1.37473255e-01 -4.14489895e-01 6.86075389e-01
1.25073385e+00 -4.28920120e-01 5.89070618e-01 1.94601193e-01
1.15868926e+00 6.94861114e-01 4.49238777e-01 3.30293804e-01
6.47126257e-01 1.12120843e+00 2.71791816e-01 3.17538739e-03
-4.13723230e-01 -2.81899810e-01 3.38058174e-01 6.08071446e-01
-6.61618531e-01 -1.57308012e-01 -1.00485492e+00 5.06557107e-01
-2.03757048e+00 -1.14283681e+00 -1.42440632e-01 2.27139997e+00
5.81655920e-01 1.62232965e-01 6.34502292e-01 6.23907410e-02
4.50043291e-01 1.89312294e-01 -5.12477994e-01 1.61191866e-01
-3.30010280e-02 1.98584810e-01 2.68000871e-01 6.24945164e-01
-1.06378472e+00 6.96821690e-01 6.08882713e+00 2.86579013e-01
-9.12013888e-01 -1.11274906e-01 2.72113293e-01 -4.91516113e-01
5.01319394e-02 5.35362139e-02 -6.52438402e-01 3.35827440e-01
5.96143067e-01 1.37877330e-01 4.28430051e-01 4.13973480e-01
4.03772414e-01 -1.77805081e-01 -1.21580505e+00 1.15622938e+00
1.70197517e-01 -1.21811461e+00 -4.94874194e-02 3.28467220e-01
6.53526664e-01 -2.56355833e-02 -3.07369113e-01 3.24734859e-02
-3.84331793e-02 -7.95824766e-01 1.01412547e+00 6.53452814e-01
7.28459179e-01 -5.56382716e-01 3.08657855e-01 4.24694896e-01
-1.52115226e+00 2.73992807e-01 3.03646661e-02 -2.24969789e-01
5.73446274e-01 3.46987844e-01 -2.91552722e-01 5.99401176e-01
8.22592854e-01 8.65690649e-01 -2.01383188e-01 8.92973185e-01
1.73606873e-01 6.14418805e-01 -5.65278769e-01 8.18320394e-01
-1.84429526e-01 -2.04134107e-01 7.85141110e-01 9.88620698e-01
6.06678277e-02 2.63420820e-01 5.47445536e-01 4.41717446e-01
-8.73377323e-02 -1.21799633e-01 -5.45895875e-01 1.85951874e-01
1.25755340e-01 9.81692255e-01 -7.34315455e-01 -2.99894989e-01
-5.33254087e-01 1.16401958e+00 2.68555880e-01 4.11528081e-01
-8.50332558e-01 3.23130429e-01 7.09273636e-01 8.44041526e-01
2.06176236e-01 -5.56164682e-01 1.90211847e-01 -1.38413620e+00
3.51866335e-01 -1.06490779e+00 4.71664578e-01 -5.62195480e-01
-1.10307240e+00 1.94846869e-01 3.03173214e-01 -1.14366293e+00
-6.07084692e-01 -1.63857847e-01 -3.88938248e-01 6.42323673e-01
-8.61482978e-01 -1.34303701e+00 -3.80880982e-01 6.11273468e-01
9.26964283e-01 4.40750510e-01 5.95314622e-01 3.60614121e-01
-5.32794118e-01 2.92870283e-01 -3.27727854e-01 1.58320338e-01
7.84564853e-01 -9.49674428e-01 5.20911634e-01 8.41688633e-01
1.51296631e-01 4.82255250e-01 9.04758811e-01 -1.04832327e+00
-1.69593334e+00 -8.74285638e-01 6.22891009e-01 -6.07894242e-01
4.43114847e-01 -3.44622672e-01 -9.34106529e-01 9.97549176e-01
-1.77158624e-01 2.04596385e-01 2.84593463e-01 5.89229316e-02
-8.47844109e-02 2.33338863e-01 -8.61756861e-01 7.77480543e-01
1.46662807e+00 -3.53182942e-01 -3.51978540e-01 3.36163342e-01
2.40579188e-01 -1.08111203e+00 -1.05194926e+00 4.70739752e-01
1.04220688e+00 -8.49568129e-01 1.20301604e+00 -5.68090260e-01
5.31005323e-01 -3.39001358e-01 -2.49483846e-02 -8.85056674e-01
-2.75638729e-01 -8.70682299e-01 -7.11296320e-01 9.08334315e-01
-2.61952341e-01 -7.91090541e-03 1.09296024e+00 8.28783095e-01
9.57461968e-02 -9.67234373e-01 -8.53274882e-01 -5.12068272e-01
-6.01482503e-02 -3.19653749e-01 4.36723717e-02 7.86686718e-01
-3.29064548e-01 1.87479749e-01 -8.72901261e-01 1.08689545e-02
8.35235775e-01 -1.19513467e-01 1.19414365e+00 -1.21749949e+00
-4.59729880e-01 -1.05587028e-01 -5.78051507e-01 -1.17971265e+00
3.58337075e-01 -4.33694065e-01 3.00880568e-03 -1.52751482e+00
2.67138630e-01 -7.48996362e-02 2.57117003e-01 1.97681993e-01
-1.50783494e-01 4.61162508e-01 1.99912623e-01 4.40940350e-01
-3.74046564e-01 2.07392231e-01 1.22730768e+00 -1.58188231e-02
-1.20107062e-01 5.14923409e-03 -1.71350688e-02 1.04609168e+00
3.17953080e-01 -3.51933479e-01 -4.95357782e-01 -5.47468305e-01
1.30430147e-01 5.56466579e-01 7.74214923e-01 -1.14754367e+00
1.50019631e-01 6.77541122e-02 3.95979226e-01 -3.90361458e-01
6.34603798e-01 -7.03218400e-01 7.55025029e-01 4.75724101e-01
6.93227947e-02 3.76697689e-01 9.28260162e-02 9.14965332e-01
8.90001829e-04 1.76794872e-01 7.50477612e-01 -3.53392571e-01
-5.71769953e-01 6.39483154e-01 -2.55831689e-01 3.16265702e-01
7.31560230e-01 -6.27439916e-01 3.17775905e-01 -5.18860221e-01
-9.95096207e-01 1.96336746e-01 9.76871610e-01 4.22987521e-01
4.64606583e-01 -1.18404830e+00 -8.18369269e-01 1.42055806e-02
-1.43477529e-01 3.24547172e-01 3.64768118e-01 9.91484642e-01
-7.42754459e-01 -1.72144532e-01 -2.95392033e-02 -8.46146643e-01
-1.54982281e+00 1.85175911e-01 4.78777766e-01 -3.07266146e-01
-1.31862855e+00 5.79667926e-01 1.74999923e-01 -3.87270488e-02
3.44964027e-01 -1.99707121e-01 1.31399512e-01 -1.15253210e-01
3.15103233e-01 6.72880828e-01 2.15171892e-02 -1.13652909e+00
-2.69918561e-01 9.92625296e-01 7.79798552e-02 -2.25711018e-01
1.14289451e+00 -1.46691859e-01 3.19190025e-02 5.81185997e-01
1.04354835e+00 1.45559311e-01 -1.49196911e+00 -1.98356941e-01
-4.36729282e-01 -4.48899537e-01 -3.11021864e-01 -2.87069350e-01
-1.04852128e+00 4.92652744e-01 3.71431589e-01 -2.02172980e-01
8.71402144e-01 -1.36671215e-01 1.25644803e+00 4.82989587e-02
6.44990027e-01 -9.04098153e-01 -7.24605564e-03 4.09168661e-01
7.43125200e-01 -9.48876858e-01 3.36061865e-01 -5.37715614e-01
-3.27568889e-01 9.95806098e-01 4.03456897e-01 -3.58282149e-01
6.64883494e-01 3.15368325e-01 -1.96403697e-01 -3.21815640e-01
-6.51958406e-01 1.31074458e-01 2.81935871e-01 3.70351583e-01
5.19499481e-01 -1.20255932e-01 -7.84225166e-02 -1.57617390e-01
-1.59731030e-01 1.87466830e-01 4.64288324e-01 1.31319535e+00
-7.39014447e-02 -1.10419798e+00 -5.25712669e-01 3.43076974e-01
-6.05602086e-01 3.00475359e-01 -1.89759314e-01 1.07012057e+00
1.61275506e-01 5.90698123e-01 1.08504836e-02 -1.38874143e-01
5.28601944e-01 9.61748436e-02 1.06106961e+00 -5.67261934e-01
-3.95366609e-01 4.16339308e-01 2.58661807e-01 -8.62907529e-01
-7.48915195e-01 -1.10255718e+00 -1.34051418e+00 -5.86264968e-01
7.20924586e-02 -3.12333971e-01 1.16465993e-01 9.31776166e-01
2.00107932e-01 5.33803701e-01 -8.01351219e-02 -1.46191823e+00
-2.07734928e-01 -6.41099393e-01 -4.69256788e-01 9.06297266e-01
4.94904220e-01 -1.02110016e+00 -1.41885832e-01 6.15919113e-01] | [7.279355049133301, -0.8428763151168823] |
a586d80d-dfd0-481c-85e9-ec3cdb8677c1 | j-score-a-robust-measure-of-clustering | 2109.01306 | null | https://arxiv.org/abs/2109.01306v1 | https://arxiv.org/pdf/2109.01306v1.pdf | J-Score: A Robust Measure of Clustering Accuracy | Background. Clustering analysis discovers hidden structures in a data set by partitioning them into disjoint clusters. Robust accuracy measures that evaluate the goodness of clustering results are critical for algorithm development and model diagnosis. Common problems of current clustering accuracy measures include overlooking unmatched clusters, biases towards excessive clusters, unstable baselines, and difficult interpretation. In this study, we presented a novel accuracy measure, J-score, that addresses these issues. Methods. Given a data set with known class labels, J-score quantifies how well the hypothetical clusters produced by clustering analysis recover the true classes. It starts with bidirectional set matching to identify the correspondence between true classes and hypothetical clusters based on Jaccard index. It then computes two weighted sums of Jaccard indices measuring the reconciliation from classes to clusters and vice versa. The final J-score is the harmonic mean of the two weighted sums. Results. Via simulation studies, we evaluated the performance of J-score and compared with existing measures. Our results show that J-score is effective in distinguishing partition structures that differ only by unmatched clusters, rewarding correct inference of class numbers, addressing biases towards excessive clusters, and having a relatively stable baseline. The simplicity of its calculation makes the interpretation straightforward. It is a valuable tool complementary to other accuracy measures. We released an R/jScore package implementing the algorithm. | ['Li Liu', 'Navid Ahmadinejad'] | 2021-09-03 | null | null | null | null | ['set-matching'] | ['computer-vision'] | [ 1.50220677e-01 -6.43180236e-02 -2.01156870e-01 -5.78957617e-01
-8.95766199e-01 -9.15592551e-01 5.41825473e-01 6.21512890e-01
-2.11341351e-01 5.50258100e-01 1.25738040e-01 -2.57818997e-01
-6.76516473e-01 -7.18309104e-01 -2.04432547e-01 -9.70485449e-01
-4.28970009e-01 8.58206451e-01 1.89922929e-01 4.17933196e-01
3.61585289e-01 3.33776832e-01 -1.72563457e+00 4.60452825e-01
1.02890158e+00 7.18558729e-01 -4.27164137e-02 5.57468891e-01
8.13180134e-02 6.06621444e-01 -7.74657309e-01 -3.83280069e-01
1.28381759e-01 -7.19364643e-01 -8.11838925e-01 -4.78620306e-02
9.30204839e-02 1.92167997e-01 4.20284599e-01 1.09319353e+00
3.19744438e-01 -2.49655306e-01 1.05409777e+00 -1.65443850e+00
-1.65075183e-01 6.74755454e-01 -5.16423941e-01 1.46383643e-01
2.38402203e-01 1.02738254e-01 1.06687903e+00 -6.05881631e-01
4.78422433e-01 1.19662678e+00 1.13368964e+00 7.05901608e-02
-1.69255114e+00 -7.92514563e-01 -3.66610825e-01 4.22536880e-02
-1.81299341e+00 -3.45704794e-01 4.17029619e-01 -8.87877703e-01
5.67697525e-01 8.70591342e-01 5.33728838e-01 2.19764769e-01
-9.38925073e-02 3.28096271e-01 1.27040386e+00 -2.25167289e-01
4.72742587e-01 1.41799569e-01 3.68798107e-01 2.83386648e-01
6.11230493e-01 1.55420765e-01 -1.50297619e-02 -5.44538260e-01
2.66364068e-01 -1.45057335e-01 -1.01983197e-01 -5.26109159e-01
-1.38416517e+00 8.64373088e-01 3.98887247e-01 4.29951727e-01
-2.06286848e-01 -2.36402258e-01 1.58264801e-01 8.62442628e-02
4.43454325e-01 5.62059641e-01 -1.34484261e-01 3.78310643e-02
-1.36317956e+00 8.66686404e-02 5.97688198e-01 6.94661379e-01
6.67443812e-01 -3.85275215e-01 -6.88390583e-02 8.10121417e-01
1.40751645e-01 3.07727367e-01 4.26848590e-01 -1.23585927e+00
9.45646986e-02 8.75733435e-01 -8.56927037e-02 -1.43555069e+00
-6.45823002e-01 -5.23578286e-01 -1.04856241e+00 1.23102916e-02
5.27827799e-01 8.13163295e-02 -3.86070460e-01 1.86417270e+00
2.93535918e-01 -1.24201410e-01 3.08029004e-03 6.15274191e-01
5.62936425e-01 3.82330656e-01 3.48856188e-02 -4.69122618e-01
1.07702947e+00 -2.97026485e-01 -6.36209130e-01 2.40567878e-01
7.54208207e-01 -7.49929965e-01 6.17317200e-01 3.80618647e-02
-1.05876851e+00 -5.41947544e-01 -8.57928276e-01 5.47878802e-01
-2.86458582e-01 3.34410719e-03 3.83164048e-01 8.02664936e-01
-1.24365771e+00 7.15138853e-01 -7.04095840e-01 -3.81910771e-01
1.90777436e-01 5.67785919e-01 -2.35018700e-01 2.04714164e-01
-8.12849820e-01 6.31431997e-01 5.95054865e-01 -1.80461973e-01
-2.67542154e-01 -5.09600818e-01 -5.39899945e-01 1.57273099e-01
3.60732228e-02 -4.59909558e-01 7.71681547e-01 -9.01121616e-01
-5.70016384e-01 1.02215481e+00 -1.26786038e-01 -2.77486354e-01
4.36998159e-01 6.43039167e-01 -4.65202749e-01 7.64864087e-02
4.33926314e-01 5.79717278e-01 3.13783407e-01 -1.59705567e+00
-6.96340561e-01 -5.44314206e-01 -5.80140471e-01 4.20741141e-02
2.46638972e-02 -3.33909765e-02 -1.88001439e-01 -5.05684137e-01
4.40864801e-01 -8.60628486e-01 -3.12247396e-01 -3.94646794e-01
-4.34736967e-01 -1.60003394e-01 4.04875815e-01 -4.29949164e-01
1.72692680e+00 -2.26116705e+00 -1.44869387e-01 8.12702835e-01
6.05532765e-01 4.85219434e-02 1.33519471e-01 3.71252775e-01
-3.03726524e-01 3.30305070e-01 -7.12937653e-01 2.90843427e-01
-9.84195098e-02 -1.25488296e-01 1.12891853e-01 6.26682520e-01
1.34316325e-01 5.45861125e-01 -9.40356672e-01 -7.60028601e-01
2.41281345e-01 2.14460120e-01 -5.02953827e-01 1.72313735e-01
4.56589699e-01 1.27416819e-01 2.44585991e-01 4.10577327e-01
6.61634088e-01 -4.82856512e-01 6.58621192e-01 -4.80174124e-02
-7.77424574e-02 7.23616779e-02 -1.42809904e+00 7.10674465e-01
3.00201923e-01 6.31874561e-01 -1.47541136e-01 -9.95745063e-01
1.24962974e+00 5.65090328e-02 6.71992064e-01 -2.26093695e-01
1.11877374e-01 2.59107351e-01 4.27423209e-01 -1.53376386e-01
1.61165416e-01 -1.80811539e-01 9.71052609e-03 5.87015450e-01
-3.63153100e-01 -1.23018518e-01 1.95363864e-01 2.52344429e-01
1.06297934e+00 -5.50081670e-01 6.09639645e-01 -6.93176389e-01
2.59992987e-01 2.48436704e-01 5.68161130e-01 7.86421299e-01
-2.74889231e-01 6.74240172e-01 5.92677712e-01 -2.30914533e-01
-1.11250794e+00 -1.48231268e+00 -4.09487188e-01 6.79594457e-01
7.21947998e-02 -5.24039865e-01 -8.56012046e-01 -3.85628581e-01
9.60316360e-02 5.71777523e-01 -6.31130099e-01 -4.20096397e-01
-1.50554627e-01 -1.13305819e+00 6.79306805e-01 3.97689104e-01
2.59662688e-01 -6.00931525e-01 -5.60579002e-01 6.69177249e-02
-4.83767629e-01 -5.88851571e-01 -2.17269763e-01 2.27331892e-01
-1.00867689e+00 -1.63844657e+00 -4.59350765e-01 -8.89407218e-01
7.91529715e-01 3.68264645e-01 1.27918065e+00 2.89236099e-01
-2.90479034e-01 1.12223208e-01 -1.80930927e-01 -1.20791212e-01
-6.12459838e-01 -1.58478141e-01 1.58602923e-01 -7.50749931e-02
7.72410452e-01 -3.39541972e-01 -4.87839699e-01 7.82560229e-01
-8.15539598e-01 -1.54054105e-01 3.89878780e-01 6.16674125e-01
5.90668797e-01 6.34252787e-01 5.52288115e-01 -8.59701931e-01
6.41780376e-01 -7.03897595e-01 -4.44561332e-01 3.43391806e-01
-8.78800929e-01 -1.62227396e-02 3.46470207e-01 -2.60955185e-01
-6.62050724e-01 -2.26740669e-02 3.12343746e-01 -1.32376656e-01
-1.85754016e-01 2.87119061e-01 1.82367563e-02 5.87608933e-01
7.25981355e-01 -5.85955083e-02 2.27451578e-01 -1.66216746e-01
1.78125247e-01 1.00077057e+00 7.07079947e-01 -4.42797095e-01
6.20813847e-01 4.95701164e-01 -1.00287341e-01 -7.62817085e-01
-4.76655632e-01 -8.76558423e-01 -9.17062283e-01 -3.11848879e-01
6.94627821e-01 -7.06493020e-01 -8.55447888e-01 7.52968490e-02
-6.68404996e-01 -9.04941037e-02 -8.91964287e-02 5.18279076e-01
-4.00612980e-01 4.92910951e-01 -1.95878267e-01 -8.70963335e-01
-2.23218083e-01 -1.08392990e+00 8.31241131e-01 -2.59300530e-01
-8.79725993e-01 -1.10465598e+00 2.58337885e-01 2.41966024e-01
4.76750545e-02 5.74309409e-01 1.05096304e+00 -8.94965112e-01
-1.05847895e-01 -2.28751764e-01 -2.39896044e-01 -1.35476664e-02
2.64929444e-01 5.03740788e-01 -9.79384899e-01 -4.67374235e-01
-2.54672587e-01 2.53591716e-01 7.19912708e-01 6.33488595e-01
1.02706099e+00 -4.50001210e-01 -7.06990004e-01 4.35350001e-01
1.25926304e+00 6.19058609e-01 4.43723947e-01 3.10193896e-01
3.74043584e-01 1.03234577e+00 4.39730525e-01 2.84207940e-01
2.97322214e-01 5.74501038e-01 2.75882725e-02 -1.63818136e-01
1.17679007e-01 -3.05048712e-02 -5.50369881e-02 1.08642268e+00
9.30136144e-02 9.27647948e-02 -1.32321835e+00 5.93436658e-01
-1.76006007e+00 -1.20272040e+00 -6.88722968e-01 2.58656502e+00
7.20910788e-01 3.27955902e-01 6.66365921e-01 5.89560509e-01
1.36252260e+00 -4.37102139e-01 -2.82439381e-01 -1.70617938e-01
-7.36524463e-02 -4.50742356e-02 2.53846735e-01 5.98208964e-01
-9.47473884e-01 4.33055371e-01 7.34065151e+00 7.60085285e-01
-4.89526987e-01 -2.81026572e-01 8.03320050e-01 -6.86026737e-03
-1.06424272e-01 9.96609852e-02 -3.89296293e-01 7.47745752e-01
1.05851328e+00 -4.45493758e-01 4.36676331e-02 5.94196320e-01
1.46551803e-01 -7.96494484e-02 -1.22393847e+00 8.17456722e-01
-2.01572418e-01 -1.13077819e+00 -1.14755057e-01 2.86656767e-01
6.95791900e-01 -2.20440879e-01 -4.13476005e-02 -6.82621077e-02
7.22878635e-01 -1.05046141e+00 5.27630389e-01 3.33055675e-01
8.71227264e-01 -9.40716624e-01 9.80691791e-01 2.16207638e-01
-1.12791777e+00 -7.06177428e-02 -2.73579031e-01 -1.35260448e-01
-3.26819390e-01 1.04761100e+00 -1.11540651e+00 4.23069954e-01
8.07205975e-01 5.97207010e-01 -7.84332633e-01 1.16142678e+00
3.56404394e-01 7.08710611e-01 -4.24204439e-01 9.73873734e-02
1.55711370e-02 -4.18197304e-01 2.52465457e-01 1.30827868e+00
2.23181129e-01 1.36299610e-01 4.68215942e-02 8.67575705e-01
3.69987220e-01 -3.14476155e-03 -6.51653826e-01 1.05129465e-01
1.09410644e+00 1.02173162e+00 -1.28733873e+00 -5.67201912e-01
5.48378862e-02 3.41386527e-01 1.10083126e-01 2.68413983e-02
-6.32412434e-01 -4.87640947e-01 6.48715258e-01 1.32495090e-01
-1.10376626e-01 1.09051429e-01 -5.92620492e-01 -6.14034772e-01
-2.41720513e-01 -8.52137208e-01 9.41145301e-01 -5.14235556e-01
-1.38867617e+00 5.33204317e-01 1.96169510e-01 -1.32636547e+00
-1.87793136e-01 -2.29337811e-01 -5.04086316e-01 4.57522154e-01
-6.82344317e-01 -4.28932071e-01 -3.44418257e-01 3.92773449e-01
4.30498868e-02 6.20868430e-03 6.94516957e-01 1.24475956e-01
-6.06119990e-01 6.34034455e-01 6.68848157e-01 2.15565279e-01
6.94637835e-01 -1.48175669e+00 7.64386579e-02 5.46126306e-01
-1.03750959e-01 8.65549326e-01 6.99398398e-01 -7.22357154e-01
-2.98649549e-01 -9.46919501e-01 8.89789104e-01 -7.47505188e-01
4.57233608e-01 -1.04740694e-01 -9.95972693e-01 5.14477253e-01
-2.94065356e-01 -5.52118897e-01 1.23881459e+00 8.82230401e-02
-3.73506606e-01 -1.10840872e-01 -1.25797153e+00 4.00322109e-01
7.46181667e-01 -2.40133569e-01 -5.61225712e-01 1.04533322e-01
1.63309008e-01 2.93208092e-01 -1.23553646e+00 4.96337444e-01
6.43075824e-01 -1.43381166e+00 1.01654613e+00 -4.78957683e-01
3.20143372e-01 -5.09238780e-01 -3.39340001e-01 -1.24202192e+00
-8.25845182e-01 -2.42187470e-01 4.98819530e-01 1.22778940e+00
4.33254033e-01 -4.35391873e-01 6.09335542e-01 5.34020483e-01
2.14336112e-01 -3.99604082e-01 -7.73250818e-01 -9.11744952e-01
1.65619180e-01 -2.61877030e-01 9.11890149e-01 1.52250552e+00
3.68988216e-01 3.41114759e-01 1.03913665e-01 1.72322929e-01
1.13749564e+00 2.05430746e-01 6.67675674e-01 -1.80224442e+00
-5.28728440e-02 -9.88706708e-01 -6.43189847e-01 -1.77388750e-02
-9.67383385e-02 -1.16575253e+00 -1.27333954e-01 -1.43979764e+00
5.83908617e-01 -7.15038538e-01 -4.56164218e-02 3.36985767e-01
-3.71226519e-01 3.91238421e-01 1.28120854e-01 7.13672638e-01
-5.57258606e-01 -7.50620961e-02 6.68785095e-01 -1.09828569e-01
-3.36990118e-01 3.17887180e-02 -7.08288670e-01 7.35055983e-01
1.06823468e+00 -6.38848960e-01 -2.81199396e-01 1.78983077e-01
9.24799889e-02 -9.04163048e-02 2.19661921e-01 -1.18796027e+00
1.94976389e-01 -5.49454130e-02 5.64305902e-01 -6.36195004e-01
-1.82182282e-01 -9.61243808e-01 8.88559282e-01 8.75114262e-01
-5.86101651e-01 3.94115001e-01 -4.35699299e-02 4.18455839e-01
-8.90142098e-02 -1.19132824e-01 1.00761950e+00 -1.18505254e-01
-2.42761999e-01 -3.00976664e-01 -4.59694505e-01 1.16984490e-02
1.31475580e+00 -4.77726996e-01 -2.48948663e-01 -3.77114832e-01
-7.78579533e-01 2.65642732e-01 7.15781510e-01 1.72658563e-01
4.08038408e-01 -1.39379227e+00 -8.01605761e-01 2.11914122e-01
3.44315231e-01 -2.46659279e-01 -2.40804449e-01 9.44285333e-01
-6.69654965e-01 3.66712898e-01 -5.95732853e-02 -1.05102289e+00
-1.72975862e+00 7.00857103e-01 2.72305310e-01 -1.68938756e-01
-1.80686280e-01 3.92384797e-01 2.42780522e-01 -7.01970816e-01
1.87185705e-01 -8.52921456e-02 -1.54073790e-01 3.16206664e-01
5.05101442e-01 8.99786115e-01 -5.48887849e-02 -8.01493108e-01
-5.70841372e-01 6.23663306e-01 2.24848747e-01 1.11626647e-01
1.09076715e+00 -1.90669775e-01 -4.93925601e-01 6.40844524e-01
1.19519806e+00 -2.43759185e-01 -6.62411273e-01 1.35378063e-01
4.84027535e-01 -4.17422682e-01 -2.89219290e-01 -8.12902272e-01
-7.18414664e-01 6.19435906e-01 7.07560718e-01 7.06394315e-01
1.03521883e+00 1.59935355e-01 7.80967996e-02 1.08156793e-01
1.04520097e-01 -1.00707734e+00 -8.15667287e-02 -3.82583775e-02
2.54597366e-01 -1.25582504e+00 1.85394049e-01 -3.97001088e-01
-6.59186006e-01 8.39145124e-01 3.49144310e-01 2.65085548e-01
5.86588323e-01 7.35040009e-02 1.43837452e-01 -4.36809659e-01
-4.58490312e-01 -1.91139817e-01 2.91085005e-01 6.36420667e-01
4.58361804e-01 4.57034558e-01 -4.23490375e-01 3.59480798e-01
-6.01777017e-01 -4.46519762e-01 3.45875531e-01 6.00229740e-01
-6.73101962e-01 -6.04173720e-01 -8.41904819e-01 7.59932995e-01
-3.25577617e-01 9.94510502e-02 -9.23850417e-01 8.88748944e-01
5.77419549e-02 1.36265171e+00 5.11058867e-01 -7.04785824e-01
3.67730297e-02 -6.64969906e-03 4.16764803e-02 -2.64662117e-01
-6.41385674e-01 1.46381363e-01 -6.32008389e-02 -3.28353167e-01
-6.52353406e-01 -6.78746939e-01 -1.02676868e+00 -6.45186126e-01
-4.95200217e-01 7.03852475e-01 3.71998072e-01 5.08917630e-01
3.26700151e-01 2.52911925e-01 8.87747824e-01 -4.19217438e-01
-3.43688995e-01 -8.01715314e-01 -6.63316548e-01 7.02013195e-01
2.01585650e-01 -5.58427870e-01 -7.30288684e-01 1.30929798e-02] | [7.607521057128906, 4.562572956085205] |
01af5efc-f2b8-44e0-96dc-8d5e2405da80 | causality-matters-in-medical-imaging | 1912.08142 | null | https://arxiv.org/abs/1912.08142v1 | https://arxiv.org/pdf/1912.08142v1.pdf | Causality matters in medical imaging | This article discusses how the language of causality can shed new light on the major challenges in machine learning for medical imaging: 1) data scarcity, which is the limited availability of high-quality annotations, and 2) data mismatch, whereby a trained algorithm may fail to generalize in clinical practice. Looking at these challenges through the lens of causality allows decisions about data collection, annotation procedures, and learning strategies to be made (and scrutinized) more transparently. We discuss how causal relationships between images and annotations can not only have profound effects on the performance of predictive models, but may even dictate which learning strategies should be considered in the first place. For example, we conclude that semi-supervision may be unsuitable for image segmentation---one of the possibly surprising insights from our causal analysis, which is illustrated with representative real-world examples of computer-aided diagnosis (skin lesion classification in dermatology) and radiotherapy (automated contouring of tumours). We highlight that being aware of and accounting for the causal relationships in medical imaging data is important for the safe development of machine learning and essential for regulation and responsible reporting. To facilitate this we provide step-by-step recommendations for future studies. | ['Ian Walker', 'Daniel C. Castro', 'Ben Glocker'] | 2019-12-17 | null | null | null | null | ['skin-lesion-classification'] | ['medical'] | [ 9.65393603e-01 5.03916204e-01 -7.59095967e-01 -5.67932129e-01
-8.39678943e-01 -5.36060393e-01 5.87890565e-01 7.39501297e-01
-4.80904549e-01 7.34852314e-01 6.81754291e-01 -9.38839972e-01
-6.57523870e-01 -3.53255004e-01 -6.96944535e-01 -8.49041581e-01
-1.25326604e-01 3.83461118e-01 -1.23370513e-01 3.95816118e-01
1.26960054e-01 4.07823056e-01 -9.99058068e-01 3.17483276e-01
6.63352370e-01 5.74769855e-01 9.51328427e-02 5.91227829e-01
9.79077220e-02 1.21454322e+00 -2.27393657e-01 -4.59523559e-01
-1.78345084e-01 -6.64721787e-01 -9.48971748e-01 3.82258356e-01
2.14954734e-01 -3.57399285e-01 9.60712284e-02 6.64415777e-01
4.39458966e-01 -4.39245790e-01 7.88371861e-01 -8.73652995e-01
-4.29219663e-01 7.37815917e-01 -4.13662255e-01 4.66068685e-01
5.03995493e-02 4.01883751e-01 6.96707368e-01 -1.33182600e-01
7.46847212e-01 9.43497598e-01 5.87327838e-01 5.02079248e-01
-1.19319963e+00 -3.92616302e-01 2.37615138e-01 -3.15303355e-02
-8.58245850e-01 -5.71286738e-01 1.17377080e-01 -8.38162839e-01
5.20293176e-01 5.47245502e-01 7.39407957e-01 1.12275994e+00
5.73878050e-01 4.21516597e-01 1.11422014e+00 -7.03408778e-01
-7.06781680e-03 9.87997130e-02 -1.04441576e-01 7.32100487e-01
4.70559627e-01 2.22302601e-01 -4.73489493e-01 -4.58239168e-01
7.29987979e-01 -2.68719971e-01 -3.64788026e-01 -2.66849190e-01
-1.24595666e+00 7.37055361e-01 2.58112431e-01 3.21766496e-01
-2.51613438e-01 2.21288934e-01 5.53373039e-01 -5.57597838e-02
2.99937785e-01 4.07831281e-01 -3.88848335e-01 5.07002026e-02
-7.06965685e-01 -3.94093208e-02 3.59623194e-01 2.74221987e-01
-7.89975971e-02 -3.03365111e-01 1.76815614e-01 6.00843430e-01
4.07213539e-01 5.57205863e-02 3.28263015e-01 -9.22897577e-01
5.59418127e-02 2.82703280e-01 4.71089371e-02 -6.79457963e-01
-5.77005506e-01 -5.17343283e-01 -5.96390426e-01 1.51058003e-01
7.17242956e-01 -2.06388995e-01 -8.36508632e-01 1.41568172e+00
2.43549958e-01 1.08550481e-01 -1.07223287e-01 8.59635055e-01
6.10215366e-01 -2.31178299e-01 8.08417201e-01 -5.79493523e-01
1.44959044e+00 -2.19834864e-01 -8.01076412e-01 -2.47179970e-01
1.10964215e+00 -7.22305059e-01 9.04767811e-01 4.18305278e-01
-1.02451527e+00 1.13170944e-01 -9.68228519e-01 1.08732365e-01
-2.36034603e-03 -4.71045859e-02 7.68735766e-01 7.05991328e-01
-5.62303603e-01 7.14480639e-01 -1.10340369e+00 -7.09684253e-01
6.94228232e-01 3.06761414e-01 -3.67321998e-01 -1.25909790e-01
-9.58781958e-01 1.09879518e+00 1.17253408e-01 2.32733756e-01
-5.94646156e-01 -8.85307550e-01 -5.36277354e-01 -3.05794865e-01
6.18677318e-01 -9.47900355e-01 1.25840795e+00 -1.01502132e+00
-6.96738243e-01 1.13352215e+00 -3.13916579e-02 -3.27882856e-01
5.54992318e-01 5.94222546e-03 -3.99612844e-01 4.03080992e-02
3.25479865e-01 4.78776574e-01 4.77158993e-01 -1.21014559e+00
-9.58374500e-01 -6.61656380e-01 -3.17269772e-01 1.86819926e-01
-5.64848743e-02 2.15546936e-01 -1.41417339e-01 -5.63042164e-01
6.93672746e-02 -7.98024654e-01 -6.71630085e-01 1.08708769e-01
-1.29547611e-01 -2.45011151e-02 4.10790443e-01 -5.48815608e-01
1.14993215e+00 -2.02307940e+00 -2.90543497e-01 -6.42717332e-02
3.43898028e-01 -2.91137993e-01 4.40153748e-01 -8.33826326e-03
-4.22424972e-01 5.44193625e-01 -1.63087562e-01 1.94588184e-01
-5.62547147e-01 4.53857303e-01 -1.43274650e-01 8.10291588e-01
3.78654927e-01 7.95447707e-01 -1.01644623e+00 -7.19917059e-01
3.01367700e-01 3.31214249e-01 -3.04402113e-01 -1.55664101e-01
-4.83928323e-02 8.88073087e-01 -4.31442201e-01 4.15178984e-01
3.41517589e-04 -5.39507568e-01 6.29214883e-01 -9.47140306e-02
-2.36258402e-01 4.71950978e-01 -6.19516850e-01 1.28035879e+00
-2.79637903e-01 5.60793817e-01 -1.35900036e-01 -8.53944302e-01
3.11057866e-01 5.97803593e-01 6.76029146e-01 -5.09129226e-01
1.35263234e-01 2.88040429e-01 4.84627128e-01 -9.25017297e-01
-1.56444997e-01 -6.77072048e-01 3.42709869e-01 5.24534404e-01
-3.68994117e-01 -5.63627705e-02 -1.00801028e-01 3.63587402e-02
1.04214418e+00 -1.72981843e-01 3.72397393e-01 -3.52518469e-01
1.12941675e-01 4.19113487e-01 8.36380601e-01 6.51970387e-01
-1.89570576e-01 5.66867590e-01 8.00370693e-01 -3.38151157e-01
-9.08469439e-01 -7.69014299e-01 -6.94382846e-01 6.86293483e-01
-4.30046082e-01 -7.26414174e-02 -2.91729510e-01 -7.79674351e-01
-4.19645719e-02 8.72016847e-01 -9.78612304e-01 -2.75784861e-02
-4.54492122e-01 -1.24534833e+00 2.65795201e-01 6.50042474e-01
-3.14815372e-01 -7.57312834e-01 -1.06926012e+00 9.75191295e-02
3.20609063e-02 -1.03779721e+00 -2.42936276e-02 2.98649251e-01
-1.00595903e+00 -1.51660740e+00 -5.48792005e-01 -4.02464360e-01
8.65952194e-01 -3.13498378e-02 9.74075139e-01 4.30826426e-01
-3.88442814e-01 6.28669560e-01 -3.05907190e-01 -8.40148270e-01
-9.82193887e-01 -2.39981577e-01 -2.88644254e-01 -3.10639769e-01
1.66840851e-01 -2.25210398e-01 -6.35684073e-01 2.06661731e-01
-9.80779231e-01 1.26319993e-02 7.92572796e-01 8.18992794e-01
5.76638997e-01 7.35417381e-02 4.07816976e-01 -1.49921143e+00
5.17598212e-01 -6.29104018e-01 -2.97646314e-01 5.29335797e-01
-1.06931126e+00 -2.05212563e-01 6.49698824e-02 -7.33841807e-02
-1.16152668e+00 -1.47992456e-02 2.29629368e-01 5.01827337e-03
-2.14928001e-01 7.85393238e-01 2.58291990e-01 6.94343373e-02
1.02407157e+00 -2.96684116e-01 1.57404497e-01 -2.03141347e-01
1.18219696e-01 4.84491944e-01 5.51180363e-01 -4.29859966e-01
1.93103209e-01 7.96888828e-01 1.55041188e-01 -6.41709805e-01
-8.73427570e-01 -3.14426035e-01 -6.70227408e-01 -2.24289641e-01
1.03508961e+00 -7.21745908e-01 -3.53034586e-01 -1.10956967e-01
-7.98813879e-01 -5.31534731e-01 -2.59121507e-01 7.18043804e-01
-4.47261482e-01 -2.06405893e-02 -3.20327252e-01 -6.84593856e-01
9.79327038e-02 -1.40309668e+00 6.28050625e-01 1.32517172e-02
-8.55032146e-01 -1.29035974e+00 -1.70912609e-01 5.89551866e-01
1.15096189e-01 5.46934843e-01 1.49746847e+00 -5.13845265e-01
-3.76893818e-01 -8.03041309e-02 -6.99961707e-02 4.32879031e-02
5.03124118e-01 3.30193073e-01 -8.84982049e-01 2.14070022e-01
1.51231647e-01 -2.30232701e-01 5.52494466e-01 7.86800146e-01
1.11061132e+00 -2.84458756e-01 -5.03191173e-01 1.40442178e-01
1.29583764e+00 2.74837047e-01 2.50304490e-01 2.36457348e-01
6.61989093e-01 1.06063652e+00 5.89918494e-01 1.92268729e-01
3.90550643e-01 4.44699705e-01 3.86924475e-01 -3.64091963e-01
-1.05318114e-01 -1.59571350e-01 -2.44581208e-01 3.29777688e-01
1.14301192e-02 3.09693106e-02 -1.32618034e+00 6.86739743e-01
-1.79794371e+00 -5.04789174e-01 -5.80294967e-01 2.20571017e+00
8.52128267e-01 3.27132791e-01 1.53498396e-01 -6.76918328e-02
4.91484344e-01 -3.97900827e-02 -4.23570186e-01 -3.01661521e-01
1.06279880e-01 -1.34519696e-01 7.48432219e-01 5.18484652e-01
-8.68593633e-01 4.62886781e-01 7.26910019e+00 3.02634954e-01
-1.20676231e+00 2.65742093e-01 1.08339572e+00 -8.83670300e-02
-4.89820391e-01 1.62599280e-01 -1.40668735e-01 3.63081783e-01
9.23752844e-01 -8.23274776e-02 -1.57313704e-01 4.04085934e-01
7.82516479e-01 -5.49303174e-01 -1.30239916e+00 4.51238483e-01
-2.15370402e-01 -1.56183267e+00 -1.93980321e-01 6.15823567e-02
4.41359550e-01 -5.14638573e-02 8.01307932e-02 -5.28083324e-01
4.01191890e-01 -1.21725690e+00 6.02189600e-01 2.48131797e-01
8.94814134e-01 -3.50591719e-01 6.33526921e-01 1.97949260e-01
-3.08451325e-01 -2.75768731e-02 -8.27794895e-03 -3.35346954e-03
1.79186121e-01 6.65239751e-01 -1.22811162e+00 4.78211313e-01
5.56804240e-01 5.37194729e-01 -3.24605644e-01 8.54879022e-01
-3.55463356e-01 9.03686583e-01 1.24908693e-01 3.09108019e-01
1.22583341e-02 2.61025071e-01 3.07652801e-01 1.20863450e+00
-2.20150158e-01 5.56004643e-01 -1.90817863e-01 5.22106111e-01
2.42388979e-01 -9.63674113e-03 -4.29401457e-01 -2.71550745e-01
1.94788814e-01 1.14855230e+00 -1.04778230e+00 -5.75667135e-02
-5.78462005e-01 3.80706310e-01 -2.91348714e-02 1.51221603e-01
-5.29551327e-01 6.35437608e-01 2.95876116e-01 6.70616508e-01
-2.96144873e-01 1.06660537e-01 -8.16658616e-01 -6.94324374e-01
-2.63852030e-01 -9.13014472e-01 8.99059415e-01 -6.83757901e-01
-1.17456234e+00 1.19706675e-01 1.74970001e-01 -7.12471843e-01
-2.21691698e-01 -5.17488182e-01 -3.78291756e-01 6.69702172e-01
-1.33048022e+00 -9.94192064e-01 8.17097500e-02 5.91006055e-02
2.36863747e-01 3.12845618e-01 8.33064258e-01 3.37545760e-03
-5.27254820e-01 3.68957341e-01 -9.33733061e-02 3.01014278e-02
8.64487827e-01 -1.21280742e+00 1.71213597e-02 4.72892314e-01
6.44555166e-02 4.90014076e-01 7.86822796e-01 -8.57056677e-01
-9.56680298e-01 -8.37886214e-01 8.85480106e-01 -7.68104732e-01
8.15164626e-01 2.56089330e-01 -8.61676633e-01 8.22050333e-01
-1.26066888e-02 -1.50743246e-01 1.22900832e+00 3.70124727e-01
6.76561967e-02 1.48853242e-01 -1.06000721e+00 6.93637371e-01
7.58517504e-01 -1.83826387e-01 -3.50855529e-01 6.11178994e-01
3.81504834e-01 -5.01382291e-01 -9.40281212e-01 5.42376578e-01
6.83822274e-01 -9.09827709e-01 4.37719107e-01 -9.48627174e-01
6.74148738e-01 3.64452489e-02 1.58481747e-01 -8.37960124e-01
-3.05675089e-01 -3.24594140e-01 5.52780926e-01 8.62308681e-01
7.04939127e-01 -4.54415709e-01 8.80591750e-01 1.24801493e+00
9.41821188e-02 -1.07820582e+00 -6.85124457e-01 -2.13949129e-01
2.57377297e-01 -7.17546165e-01 2.37303883e-01 1.34279573e+00
2.61099599e-02 -1.16652099e-03 7.79427812e-02 2.73182660e-01
4.91989851e-01 -3.09147924e-01 3.04889441e-01 -9.43980098e-01
-3.64932477e-01 -2.49189585e-01 -2.80401707e-01 -2.84138113e-01
-2.03070566e-01 -5.68319023e-01 -3.52404088e-01 -1.50924909e+00
5.25991142e-01 -7.50616372e-01 -1.22249104e-01 5.25040984e-01
-2.88197130e-01 -3.08641177e-02 3.06077916e-02 4.18391675e-01
-6.86180368e-02 -1.09520264e-01 1.23839045e+00 1.73313141e-01
-5.96504062e-02 1.03464983e-01 -1.19500184e+00 1.02605486e+00
4.69961524e-01 -7.24728644e-01 -4.54252809e-01 -5.44247150e-01
3.67655903e-01 2.68872887e-01 7.12760091e-01 -4.17974353e-01
2.90240109e-01 -4.78281409e-01 3.54643941e-01 -4.01064232e-02
-3.54488462e-01 -8.78243983e-01 2.07061186e-01 7.63817549e-01
-6.61790311e-01 -9.39004570e-02 2.02877268e-01 6.48026407e-01
8.58823806e-02 -3.78665686e-01 6.19940341e-01 -4.84750390e-01
-3.91874164e-01 -5.05223610e-02 -3.57055217e-01 8.33982751e-02
1.01332736e+00 -1.80522472e-01 -2.65052289e-01 -3.58350009e-01
-1.01027215e+00 3.07049841e-01 3.61751139e-01 3.14946920e-01
9.08089727e-02 -9.14465070e-01 -8.90984774e-01 -2.55998760e-01
2.77293585e-02 2.13858441e-01 4.78225321e-01 1.22055888e+00
-3.36034626e-01 5.83068311e-01 2.18253359e-01 -7.35558212e-01
-1.37546849e+00 2.76666522e-01 4.96826112e-01 -2.92207450e-01
-4.72141862e-01 6.91560507e-01 3.07019293e-01 1.14232294e-01
2.04349518e-01 -1.77219868e-01 -1.49930371e-02 6.61279559e-02
2.64092147e-01 1.35620505e-01 2.62340367e-01 -3.80936384e-01
-5.15935600e-01 1.18268900e-01 -5.01144707e-01 -1.92104369e-01
1.46329176e+00 -1.39426127e-01 -1.81129590e-01 6.12989306e-01
6.21246099e-01 -1.14921346e-01 -1.26554263e+00 1.31728966e-03
1.22042596e-01 -4.59789038e-01 2.33578429e-01 -1.27731061e+00
-7.43092895e-01 6.80711269e-01 5.57545602e-01 5.18193133e-02
1.08062613e+00 2.37505421e-01 4.57616374e-02 -3.90733749e-01
1.81353614e-02 -8.94684553e-01 -2.06842989e-01 -4.61367816e-01
8.71311963e-01 -1.28914034e+00 4.99289364e-01 -6.71707988e-01
-8.07242513e-01 1.05288649e+00 1.59523040e-01 4.91459817e-01
6.08058333e-01 4.01119649e-01 3.36509138e-01 -4.91306007e-01
-9.74739134e-01 6.39615729e-02 1.26225084e-01 3.81614625e-01
8.52527738e-01 1.98444873e-01 -6.15551233e-01 3.94106358e-01
7.64932409e-02 2.71823853e-01 6.18244112e-01 1.01208699e+00
3.40904668e-02 -1.43819523e+00 -4.82952774e-01 7.64806330e-01
-9.25053537e-01 -2.10369340e-08 -4.15825993e-01 9.95158017e-01
2.92858809e-01 8.13378453e-01 -2.49023288e-02 2.56915614e-02
3.00033689e-01 2.83250511e-02 6.35898054e-01 -8.02450240e-01
-3.74527037e-01 3.67752463e-01 3.55439812e-01 -3.10335845e-01
-7.03314722e-01 -1.08556616e+00 -1.21793628e+00 3.61033455e-02
-4.50402886e-01 -1.80605501e-01 6.33649766e-01 1.35951471e+00
1.44822031e-01 6.92831576e-01 1.57274172e-01 -3.34312506e-02
-5.41670620e-01 -4.25297260e-01 -4.15496171e-01 1.42863184e-01
3.17575008e-01 -4.47826415e-01 -3.41365874e-01 3.91050458e-01] | [8.420768737792969, 5.708489894866943] |
66b40dfd-93c0-4a93-aacc-c68e0610191d | paraformer-parallel-attention-transformer-for | 2303.00941 | null | https://arxiv.org/abs/2303.00941v2 | https://arxiv.org/pdf/2303.00941v2.pdf | ParaFormer: Parallel Attention Transformer for Efficient Feature Matching | Heavy computation is a bottleneck limiting deep-learningbased feature matching algorithms to be applied in many realtime applications. However, existing lightweight networks optimized for Euclidean data cannot address classical feature matching tasks, since sparse keypoint based descriptors are expected to be matched. This paper tackles this problem and proposes two concepts: 1) a novel parallel attention model entitled ParaFormer and 2) a graph based U-Net architecture with attentional pooling. First, ParaFormer fuses features and keypoint positions through the concept of amplitude and phase, and integrates self- and cross-attention in a parallel manner which achieves a win-win performance in terms of accuracy and efficiency. Second, with U-Net architecture and proposed attentional pooling, the ParaFormer-U variant significantly reduces computational complexity, and minimize performance loss caused by downsampling. Sufficient experiments on various applications, including homography estimation, pose estimation, and image matching, demonstrate that ParaFormer achieves state-of-the-art performance while maintaining high efficiency. The efficient ParaFormer-U variant achieves comparable performance with less than 50% FLOPs of the existing attention-based models. | ['Songlin Du', 'Bin Kang', 'Yaping Yan', 'Xiaoyong Lu'] | 2023-03-02 | null | null | null | null | ['homography-estimation'] | ['computer-vision'] | [-1.69763848e-01 -3.34030002e-01 -1.59272447e-01 -1.59178108e-01
-5.33572853e-01 -9.20881033e-02 3.54453027e-01 2.21595764e-01
-4.43880022e-01 1.34908438e-01 1.60446689e-01 1.26369596e-01
-3.06979120e-01 -9.48358536e-01 -8.52305114e-01 -4.76566285e-01
-1.69112891e-01 1.10215597e-01 3.45477283e-01 -1.97528511e-01
4.85072762e-01 8.14978600e-01 -1.68480372e+00 -1.30295858e-01
7.28511810e-01 1.39160264e+00 2.53508180e-01 4.37284321e-01
2.63055470e-02 4.71916050e-01 -2.23284975e-01 -2.87295967e-01
6.13050997e-01 1.17728963e-01 -3.98602962e-01 -4.43498522e-01
9.74364400e-01 -4.21962708e-01 -8.60689163e-01 9.88947451e-01
7.60260880e-01 4.34160680e-01 2.65396267e-01 -1.36379683e+00
-9.16708350e-01 2.78226197e-01 -8.13900411e-01 2.55122364e-01
3.55351001e-01 -1.19000025e-01 1.21137452e+00 -1.14468873e+00
5.12249768e-01 1.23586047e+00 9.10974205e-01 1.41212136e-01
-9.32513237e-01 -7.36555755e-01 1.65626600e-01 5.41794956e-01
-1.67941558e+00 -2.21359596e-01 7.88329005e-01 -4.68477532e-02
1.45926845e+00 2.09032416e-01 7.26235449e-01 4.71392572e-01
5.47346652e-01 7.92469800e-01 4.17625934e-01 -1.56430647e-01
-5.83790876e-02 -3.46916765e-01 1.87917247e-01 7.73484111e-01
3.79635483e-01 1.18544996e-01 -7.92830586e-01 -1.17889248e-01
1.08403051e+00 3.58516842e-01 -4.36495304e-01 -5.68239987e-01
-1.36417007e+00 6.99788630e-01 1.10274875e+00 3.97063404e-01
-6.33173943e-01 5.92884421e-01 3.18143636e-01 3.07970792e-01
2.76512951e-01 4.49611902e-01 -3.23534191e-01 5.86715266e-02
-9.77525175e-01 3.23671490e-01 4.54404324e-01 1.25812542e+00
8.88946176e-01 7.53081515e-02 -1.53450042e-01 5.32498419e-01
2.61237711e-01 5.21608472e-01 6.40822351e-01 -5.73582768e-01
3.88687074e-01 7.00136602e-01 -1.71356708e-01 -1.65201700e+00
-6.40395463e-01 -5.74709892e-01 -9.49807823e-01 4.17683646e-02
8.28169435e-02 6.66752681e-02 -8.38570595e-01 1.52758408e+00
2.25770667e-01 3.98066282e-01 -3.72352302e-01 1.13574851e+00
1.10267055e+00 5.52225113e-01 -2.95434773e-01 1.74107775e-01
1.20709741e+00 -1.22550368e+00 -6.31399989e-01 -1.32516578e-01
3.23546171e-01 -9.73106086e-01 6.91950142e-01 -1.42025352e-02
-1.03976119e+00 -8.77956927e-01 -1.33528495e+00 -4.83799964e-01
-3.73559415e-01 -2.35590748e-02 9.55547631e-01 4.91638750e-01
-1.23289049e+00 9.76111472e-01 -7.56770015e-01 -3.13957155e-01
3.22304547e-01 8.39394569e-01 -4.71980870e-01 8.64272937e-02
-9.48195517e-01 5.88006794e-01 7.26903006e-02 1.43428534e-01
-1.43937975e-01 -9.55938995e-01 -1.05058467e+00 6.25803292e-01
9.81543064e-02 -8.44217360e-01 9.46876585e-01 -6.85169160e-01
-1.35512650e+00 4.50917870e-01 -2.34869748e-01 -3.74532849e-01
3.25013489e-01 -5.15766144e-01 -8.16075504e-03 1.57410100e-01
-2.79372763e-02 7.08756030e-01 7.18903422e-01 -6.17661297e-01
-5.72047055e-01 -4.79977816e-01 -6.30504563e-02 3.02862108e-01
-4.62631851e-01 -2.36243367e-01 -6.08483851e-01 -7.44469225e-01
6.43867135e-01 -7.33161569e-01 -1.83729336e-01 4.04812396e-01
5.07408194e-02 -4.09329623e-01 1.04856277e+00 -3.24434072e-01
1.10713327e+00 -2.00553322e+00 -1.41249048e-02 4.15863961e-01
3.50386560e-01 2.92518377e-01 -2.22378716e-01 3.93576056e-01
-1.39330819e-01 -3.26961040e-01 3.03081930e-01 -2.08058804e-01
9.86297280e-02 -1.36499479e-01 -1.51604444e-01 7.06418574e-01
2.09445029e-01 1.18898284e+00 -7.50705242e-01 -2.86340654e-01
4.80827004e-01 6.80977046e-01 -9.26905751e-01 1.16757400e-01
1.86419383e-01 -1.69562832e-01 -3.75956953e-01 8.42083633e-01
8.56758773e-01 -3.52374554e-01 -4.72716875e-02 -7.95701027e-01
-2.25929469e-01 -1.44646645e-01 -1.34695756e+00 2.04178190e+00
-5.49083531e-01 8.73065531e-01 -1.76222213e-02 -9.47299421e-01
1.16335845e+00 5.98661937e-02 6.29056811e-01 -9.80197310e-01
4.93020952e-01 2.53378153e-01 1.84380747e-02 -1.36046022e-01
8.54736924e-01 5.39479375e-01 1.01923309e-01 1.73984796e-01
2.36816496e-01 2.18462914e-01 5.13893291e-02 7.24396780e-02
1.10267806e+00 2.25958571e-01 4.25015181e-01 -5.37403643e-01
5.09462297e-01 -3.60694617e-01 5.05892217e-01 7.30214417e-01
-1.81606844e-01 6.70368850e-01 1.80765972e-01 -8.16768646e-01
-8.18040788e-01 -7.72398412e-01 3.82534601e-02 1.03427553e+00
6.03589356e-01 -4.10456330e-01 -3.94119292e-01 -1.32744893e-01
2.84639210e-01 -8.50742534e-02 -6.44154012e-01 -4.45786119e-02
-7.54882514e-01 -3.40236396e-01 1.41979903e-01 8.77628207e-01
7.48348653e-01 -9.22300994e-01 -9.55890775e-01 2.47054249e-01
2.08103076e-01 -9.86760914e-01 -8.48960996e-01 2.76084454e-03
-7.76259005e-01 -1.21133924e+00 -9.08943236e-01 -1.00690198e+00
7.21641064e-01 5.95679283e-01 9.02117610e-01 2.31001183e-01
-4.55038071e-01 3.17158937e-01 -2.70401388e-01 -1.13615885e-01
7.59095371e-01 1.72614440e-01 -3.69924568e-02 1.00071020e-01
5.81593156e-01 -7.16197133e-01 -9.37715828e-01 2.26046771e-01
-5.10036588e-01 -2.07343206e-01 8.82418692e-01 9.18705642e-01
6.27760887e-01 -6.19909704e-01 2.41121799e-01 -3.40779990e-01
4.51428145e-01 -1.51593134e-01 -7.38265038e-01 1.28725857e-01
-4.89155263e-01 1.90117329e-01 6.43920243e-01 -4.47745949e-01
-6.15111232e-01 1.41589239e-01 -2.84586698e-02 -8.52268100e-01
2.86047161e-01 3.03772449e-01 2.82796714e-02 -8.23239982e-01
3.75258744e-01 1.62739918e-01 -1.40056491e-01 -3.44735086e-01
2.38555431e-01 3.82736474e-01 5.67082524e-01 -4.19250816e-01
7.86629319e-01 3.86028349e-01 2.54666358e-01 -9.77847695e-01
-3.13792765e-01 -6.79834902e-01 -5.14090955e-01 -5.01143076e-02
5.84497750e-01 -9.11188006e-01 -1.18505037e+00 4.72639114e-01
-1.24478340e+00 8.51999149e-02 -1.56540982e-02 7.32077599e-01
-5.70026934e-01 3.73435885e-01 -5.28508842e-01 -4.09331739e-01
-8.69504511e-01 -1.08082402e+00 1.09787953e+00 5.64947963e-01
-2.65296455e-02 -6.63026690e-01 -1.39024362e-01 -1.18842587e-01
6.71644747e-01 1.67483732e-01 6.02986455e-01 -5.52774310e-01
-1.07166088e+00 -4.41388160e-01 -8.26444030e-01 -1.87550858e-01
-1.59822196e-01 -2.67069340e-01 -8.64039719e-01 -4.68083918e-01
-3.43593925e-01 -1.36922881e-01 7.23667979e-01 5.52652657e-01
1.20782030e+00 -9.96126700e-03 -3.24794233e-01 1.16800392e+00
1.62672508e+00 2.29415208e-01 5.79651713e-01 3.67225856e-01
7.38030970e-01 1.24154605e-01 4.78689522e-01 4.52032566e-01
3.14399302e-01 7.33252823e-01 4.86348897e-01 -1.76553592e-01
-2.32448146e-01 -2.03716606e-01 -1.05348416e-01 8.89889598e-01
-1.11948542e-01 -3.07516214e-02 -6.65757298e-01 6.46761358e-01
-2.18598318e+00 -8.11960757e-01 1.41540006e-01 2.17029238e+00
1.34256244e-01 -6.96876273e-02 -2.35276535e-01 -4.61946651e-02
6.43516719e-01 2.90883958e-01 -4.99555111e-01 -2.39931032e-01
7.57329091e-02 5.60235441e-01 6.92422867e-01 3.15150410e-01
-1.10292256e+00 7.35674739e-01 5.91764021e+00 7.65065849e-01
-1.35322475e+00 -7.54632056e-03 1.92348748e-01 -1.05284572e-01
-1.31440431e-01 -1.78931907e-01 -6.74520910e-01 1.35648057e-01
4.00967449e-01 -2.96086729e-01 2.20654041e-01 1.00735259e+00
-2.00365812e-01 1.15398996e-01 -1.18889236e+00 1.50264335e+00
3.92811358e-01 -1.53109944e+00 1.51605740e-01 -1.22372217e-01
6.72725141e-01 2.46287480e-01 -8.23725834e-02 1.51817709e-01
-1.80942804e-01 -7.71878600e-01 5.95505893e-01 4.59161997e-01
6.48442805e-01 -9.15512979e-01 1.05709004e+00 -1.06684767e-01
-1.83972907e+00 -2.77859997e-02 -6.30846024e-01 -6.96336851e-02
-3.11945118e-02 3.02603453e-01 -1.93402499e-01 7.72548378e-01
8.84702027e-01 8.46131265e-01 -2.90208966e-01 1.44020748e+00
8.16937611e-02 -2.63935864e-01 -4.51963484e-01 -4.02076721e-01
4.77375597e-01 -3.75574492e-02 4.56039965e-01 1.04788387e+00
5.44640005e-01 -8.50396045e-03 2.80902952e-01 6.98129773e-01
-1.78269774e-01 2.24615678e-01 -4.50469345e-01 1.43811062e-01
6.05788648e-01 1.26569247e+00 -8.09029460e-01 -2.44525909e-01
-6.34664834e-01 9.75526690e-01 2.92085230e-01 2.14693263e-01
-7.24464774e-01 -1.25539088e+00 8.48069131e-01 8.82188231e-02
6.08446240e-01 -3.01285893e-01 -1.03448927e-01 -1.10848904e+00
1.18407175e-01 -4.94377375e-01 1.29581317e-01 -7.20123708e-01
-9.65082228e-01 7.57641315e-01 -3.01150262e-01 -1.30577278e+00
-9.41252150e-03 -7.51765728e-01 -7.04193532e-01 8.60856593e-01
-1.61637104e+00 -1.30130935e+00 -8.50278735e-01 7.04819202e-01
5.39176345e-01 -1.38036549e-01 6.33939147e-01 6.80248082e-01
-3.32726479e-01 9.00934875e-01 -5.30922227e-02 1.99187040e-01
6.39522552e-01 -9.66908455e-01 6.57219052e-01 8.11719239e-01
2.14989066e-01 8.74450028e-01 3.54230225e-01 -4.12052423e-01
-1.83701837e+00 -8.33971798e-01 9.41022336e-01 1.95330173e-01
6.39151454e-01 -1.56568974e-01 -7.13979840e-01 4.10462201e-01
1.32037610e-01 4.12125528e-01 3.21776241e-01 8.38787332e-02
-5.01835883e-01 -3.89402300e-01 -1.01718438e+00 4.60101187e-01
1.17937446e+00 -4.58021700e-01 -4.45927829e-01 2.12793559e-01
6.56231880e-01 -6.49032116e-01 -9.90005851e-01 3.70307267e-01
9.34836447e-01 -1.14043057e+00 9.87002075e-01 -5.44614866e-02
1.32058069e-01 -2.39789829e-01 -2.40322933e-01 -9.23266590e-01
-7.25111127e-01 -7.04786658e-01 -1.82042047e-01 7.11277306e-01
2.60835495e-02 -8.44427884e-01 9.89646137e-01 3.19393009e-01
-2.90358603e-01 -9.83809471e-01 -9.49465215e-01 -7.21418500e-01
-4.06889468e-01 -1.57306433e-01 7.35596955e-01 8.41145515e-01
-1.63691044e-01 5.01724258e-02 -3.11757863e-01 1.64568558e-01
7.26841092e-01 4.45007324e-01 7.68413842e-01 -1.02934635e+00
-1.52685270e-01 -6.08168900e-01 -1.04351246e+00 -1.44859123e+00
-9.00994688e-02 -7.46895373e-01 -1.61278248e-01 -1.38556159e+00
6.99280500e-02 -2.70484954e-01 -2.68795162e-01 4.03002262e-01
3.58251333e-02 4.15109813e-01 3.19494337e-01 1.53234825e-01
-4.38961774e-01 7.30856299e-01 9.97150540e-01 -4.41066809e-02
-1.92940816e-01 -3.25874180e-01 -3.14972550e-01 5.69657147e-01
4.97276366e-01 -1.21772341e-01 -2.80700862e-01 -6.80586159e-01
-3.43244406e-03 -1.20900236e-01 3.30619484e-01 -1.36948645e+00
7.46679306e-01 2.11076528e-01 6.19797826e-01 -8.93434346e-01
4.10336435e-01 -9.04836237e-01 -4.49654944e-02 7.20768929e-01
3.59983332e-02 6.69295192e-01 2.98360884e-01 4.19939846e-01
-4.58043993e-01 9.70587358e-02 5.91903269e-01 -6.43463656e-02
-1.09380174e+00 8.25885475e-01 1.73575908e-01 -2.83167839e-01
9.46534455e-01 -6.03413582e-01 -2.56839484e-01 -2.78951228e-01
-3.28077644e-01 2.18467712e-01 2.07927242e-01 6.18957400e-01
8.61519933e-01 -1.60763443e+00 -4.16491359e-01 6.33996546e-01
-3.39833759e-02 -9.75210071e-02 4.23372030e-01 7.86789000e-01
-9.75114226e-01 7.81554341e-01 -5.36536336e-01 -5.91722488e-01
-1.26304054e+00 3.85237426e-01 2.49916837e-01 -1.19724199e-01
-6.65607870e-01 1.01003647e+00 2.10795626e-01 -2.13515148e-01
3.61104727e-01 -2.47613758e-01 -4.45117056e-02 1.63294957e-03
5.45834124e-01 5.30732930e-01 2.11803645e-01 -5.71112931e-01
-5.65567851e-01 1.07904303e+00 -1.05168402e-01 4.65423435e-01
1.35115457e+00 1.34785891e-01 -5.97158596e-02 -1.55877933e-01
1.45592690e+00 -3.02579194e-01 -1.14216793e+00 -3.98173869e-01
-2.82557756e-01 -7.61265635e-01 4.01220888e-01 -9.75077003e-02
-1.41450441e+00 8.30890775e-01 7.06203997e-01 -1.57716170e-01
1.14821887e+00 -4.40198481e-01 1.05632532e+00 6.19364202e-01
4.38119501e-01 -9.71568942e-01 1.65473372e-01 5.04512429e-01
1.01747012e+00 -1.07276368e+00 1.94122583e-01 -3.04635525e-01
5.72114661e-02 1.26798439e+00 9.37884808e-01 -6.89115107e-01
9.05341804e-01 9.98269245e-02 -1.04320057e-01 -1.99396059e-01
-5.13083577e-01 -2.61279732e-01 6.69192314e-01 4.31770504e-01
5.08282661e-01 -2.76080906e-01 -3.02433819e-01 2.87874371e-01
-6.44678473e-02 -2.36913338e-01 4.32271771e-02 1.04167271e+00
-4.56261426e-01 -8.14259946e-01 -3.57442588e-01 4.43324596e-01
-3.03816527e-01 -1.32223085e-01 -6.39972165e-02 9.43828523e-01
4.87919636e-02 4.15811747e-01 5.57809889e-01 -5.61695814e-01
5.85319519e-01 -4.79160875e-01 6.21222794e-01 -1.92017421e-01
-8.30095112e-01 1.65789008e-01 -5.56348801e-01 -1.14178360e+00
-4.58258837e-01 -7.32804537e-02 -9.13139224e-01 -6.18334770e-01
-4.87648010e-01 -1.12195257e-02 6.41666830e-01 6.15434766e-01
7.32604444e-01 5.13899028e-01 4.79880303e-01 -1.34883714e+00
-5.38205802e-01 -8.07557404e-01 -4.73252356e-01 2.98488617e-01
3.42305511e-01 -7.75977254e-01 -8.72704312e-02 -5.36789119e-01] | [8.129951477050781, -1.9023139476776123] |
da65999d-f01a-444c-aa91-626fae87333c | memrein-rein-the-domain-shift-for-cross | null | null | https://openreview.net/forum?id=fY2-WyfrXhU | https://openreview.net/pdf?id=fY2-WyfrXhU | MemREIN: Rein the Domain Shift for Cross-Domain Few-Shot Learning | Few-shot learning aims to enable models generalize to new categories (query instances) with only limited labeled samples (support instances) from each category. Metric-based mechanism is a promising direction which compares feature embeddings via different metrics. However, it always fail to generalize to unseen domains due to the considerable domain gap challenge. In this paper, we propose a novel framework, MemREIN, which considers Memorized, Restitution, and Instance Normalization for cross-domain few-shot learning. Specifically, an instance normalization algorithm is explored to alleviate feature dissimilarity, which provides the initial model generalization ability. However, naively normalizing the feature would lose fine-grained discriminative knowledge between different classes. To this end, a memorized module is further proposed to separate the most refined knowledge and remember it. Then, a restitution module is utilized to restitute the discrimination ability from the learned knowledge. A novel reverse contrastive learning strategy is proposed to stabilize the distillation process. Extensive experiments on five popular benchmark datasets demonstrate that MemREIN well addresses the domain shift challenge, and significantly improves the performance up to $16.37\%$ compared with state-of-the-art baselines. | ['Yun Fu', 'Yulun Zhang', 'Can Qin', 'Yizhou Wang', 'Lichen Wang', 'Yi Xu'] | 2021-09-29 | null | null | null | null | ['cross-domain-few-shot', 'cross-domain-few-shot-learning'] | ['computer-vision', 'computer-vision'] | [ 2.15342283e-01 -3.18128854e-01 -3.47592682e-01 -6.33279800e-01
-6.12585902e-01 -3.57348174e-01 6.50233448e-01 2.88944453e-01
-5.31906068e-01 7.72103786e-01 -1.79556254e-02 1.17705412e-01
-2.14936942e-01 -8.57893765e-01 -3.30750823e-01 -7.99373269e-01
3.31800371e-01 1.56735420e-01 4.75460112e-01 -2.41858006e-01
3.55625182e-01 1.64412037e-01 -1.53985834e+00 1.96652547e-01
1.07129478e+00 1.21590340e+00 1.76345512e-01 -1.00562930e-01
-6.09141350e-01 4.74602759e-01 -4.26601648e-01 -2.14364856e-01
1.64986074e-01 -3.79624933e-01 -6.27459645e-01 -2.98988707e-02
3.89504224e-01 -2.73819417e-01 -2.50816166e-01 1.03782475e+00
6.03521049e-01 7.06666052e-01 8.28952432e-01 -1.18230927e+00
-9.82579708e-01 2.82817036e-01 -5.81432462e-01 5.20030200e-01
2.38741308e-01 1.56283677e-01 8.22826505e-01 -1.30156291e+00
4.55933690e-01 9.74527121e-01 3.39484364e-01 7.82228887e-01
-1.13262701e+00 -1.01964366e+00 3.69918555e-01 5.82337916e-01
-1.53926218e+00 -4.49243814e-01 9.35723960e-01 -3.12351972e-01
8.25991273e-01 8.15459341e-03 2.43667260e-01 1.03234935e+00
-1.41287282e-01 6.17653847e-01 9.93660033e-01 -3.23790878e-01
5.89830458e-01 4.10095632e-01 4.97437119e-01 2.89113551e-01
2.95266747e-01 -8.64835978e-02 -5.62335908e-01 -6.78313151e-02
2.49227017e-01 4.34644282e-01 -2.27681443e-01 -8.77649128e-01
-9.73920405e-01 6.41855896e-01 6.68065786e-01 3.66418272e-01
-1.69762373e-01 -5.21681488e-01 4.77288693e-01 4.55149561e-01
4.70502764e-01 4.82803464e-01 -5.53091168e-01 4.22181338e-02
-8.65673304e-01 1.44947767e-01 4.47643906e-01 1.06299591e+00
1.17545879e+00 -1.09896705e-01 -3.83717299e-01 1.16467226e+00
-4.02694270e-02 1.07308701e-01 1.03293109e+00 -3.34845990e-01
5.74392974e-01 1.02670085e+00 -1.01136811e-01 -8.43058705e-01
-1.65818989e-01 -5.51879108e-01 -9.66788709e-01 -2.33995825e-01
-6.24400973e-02 -2.03722138e-02 -1.12022817e+00 1.67787528e+00
4.31315601e-01 5.80146551e-01 1.35913789e-01 7.58604527e-01
8.02927256e-01 6.60291374e-01 2.88962960e-01 -1.48018643e-01
1.24346828e+00 -8.64811182e-01 -4.11051422e-01 -4.81644630e-01
6.43341839e-01 -5.09876907e-01 1.17412627e+00 9.61696804e-02
-6.91756666e-01 -8.51240158e-01 -1.38049543e+00 4.32196110e-02
-8.08956683e-01 -4.29434210e-01 2.98992574e-01 5.36909461e-01
-4.42438692e-01 6.12207770e-01 -4.99071211e-01 -5.30055523e-01
6.77602768e-01 1.06495388e-01 -3.14832270e-01 -5.53061187e-01
-1.44100869e+00 8.36454570e-01 8.53950918e-01 -4.44116354e-01
-5.51124692e-01 -9.46505308e-01 -1.02532649e+00 1.40604243e-01
3.07921797e-01 -4.92783964e-01 1.03263772e+00 -5.19637585e-01
-1.34887540e+00 8.25677335e-01 -1.34996265e-01 -3.44027460e-01
2.09405392e-01 5.37438095e-02 -7.83719599e-01 -1.62787035e-01
2.32714921e-01 5.32919347e-01 8.90801072e-01 -9.98287320e-01
-9.00970459e-01 -4.41594809e-01 -1.48751989e-01 2.79296249e-01
-9.06558692e-01 -4.06721771e-01 -2.83688933e-01 -6.85075521e-01
3.44909430e-01 -6.09495461e-01 2.72944663e-02 -2.06677854e-01
-9.52732400e-04 -4.40213323e-01 7.67222822e-01 -2.00139686e-01
1.51094937e+00 -2.44098568e+00 2.95355748e-02 9.65695158e-02
1.47206113e-01 4.97354776e-01 -2.80749410e-01 2.02569410e-01
-2.41349831e-01 -1.53300315e-01 -3.76519531e-01 -1.68623492e-01
6.46506175e-02 1.96013585e-01 -3.87293398e-01 2.43895978e-01
3.54910702e-01 8.14931333e-01 -9.04537201e-01 -4.18513924e-01
2.53062844e-01 3.03472355e-02 -4.87171024e-01 2.41278321e-01
7.11449236e-02 1.28710881e-01 -2.69784182e-01 6.62242830e-01
1.04268229e+00 -1.66714177e-01 5.39069846e-02 -1.14065580e-01
5.97340912e-02 8.68586451e-02 -1.36362863e+00 2.01307797e+00
-3.23534966e-01 3.67060639e-02 -4.92505550e-01 -1.33755100e+00
1.24054742e+00 -1.61807999e-01 2.00500682e-01 -9.55041230e-01
2.06135347e-01 2.33433232e-01 -2.14541797e-02 -3.74492258e-01
3.43695045e-01 -3.27758372e-01 -2.55985528e-01 3.51088256e-01
3.31831068e-01 4.29850295e-02 8.23356062e-02 1.85664967e-02
9.18704391e-01 -6.35679737e-02 5.81686258e-01 -2.94399887e-01
7.55529523e-01 -2.40663998e-02 7.85097361e-01 5.02694428e-01
-6.49375856e-01 5.38043797e-01 1.52524898e-03 -4.87479150e-01
-7.30106831e-01 -1.35285556e+00 -1.85280532e-01 1.67106795e+00
6.51534200e-01 -1.55435473e-01 -5.42761266e-01 -8.45943332e-01
1.62521720e-01 8.54093730e-01 -7.22712040e-01 -8.86721015e-01
-3.84240836e-01 -7.53347874e-01 1.05957188e-01 6.76486313e-01
7.32313395e-01 -7.53421187e-01 -3.93068969e-01 2.22126335e-01
3.27570662e-02 -6.47384822e-01 -4.90248978e-01 2.75105059e-01
-8.04554224e-01 -9.09642339e-01 -9.59228992e-01 -1.11933720e+00
5.76756239e-01 6.52549088e-01 7.20264673e-01 -3.33645880e-01
-2.19529301e-01 -3.45913619e-02 -5.19976020e-01 -2.14137807e-01
2.62365997e-01 3.02970171e-01 3.03377002e-01 9.41850618e-02
1.18486214e+00 -6.55139923e-01 -7.90443301e-01 4.99074161e-01
-9.87107754e-01 -4.08358216e-01 7.05559433e-01 1.18319082e+00
6.07533455e-01 -6.21631853e-02 8.82787585e-01 -7.87732899e-01
7.68530846e-01 -8.16503227e-01 -6.67920113e-02 4.28944916e-01
-8.74579132e-01 1.98667392e-01 7.67393887e-01 -7.61193395e-01
-1.18094635e+00 -2.86376715e-01 3.86324972e-01 -3.26803029e-01
-2.67898619e-01 2.79971719e-01 -4.12710458e-01 6.67615235e-02
8.29222262e-01 5.61869800e-01 -1.54472157e-01 -5.46463728e-01
5.04839242e-01 9.11872029e-01 4.68572736e-01 -5.59655309e-01
9.03041124e-01 3.11194360e-01 -5.53888142e-01 -5.66967845e-01
-9.50882077e-01 -6.77448273e-01 -8.07682514e-01 3.33532542e-01
4.41169709e-01 -9.43599105e-01 -1.32690743e-01 3.21857303e-01
-7.50477493e-01 1.31560028e-01 -4.52687204e-01 4.90510702e-01
-3.67833048e-01 2.21967086e-01 -1.45200506e-01 -3.69299293e-01
-3.32260609e-01 -6.71544254e-01 6.44023657e-01 6.49289191e-01
-1.62440106e-01 -6.58894360e-01 1.82286292e-01 1.05593398e-01
6.23678684e-01 -8.89571290e-03 1.03715885e+00 -1.11087191e+00
-1.23525947e-01 -2.07921088e-01 -4.97797966e-01 4.81260240e-01
3.88525426e-01 -5.84496856e-01 -1.07332253e+00 -4.75676626e-01
1.49632365e-01 -4.07139331e-01 1.12478578e+00 -1.26738653e-01
1.15814078e+00 -4.99011949e-02 -4.39250618e-01 5.69100499e-01
1.20696259e+00 4.44471270e-01 4.79647398e-01 4.99010175e-01
4.52388823e-01 3.43403012e-01 8.84972870e-01 5.40936232e-01
3.66745859e-01 3.72253150e-01 1.44015374e-02 2.21541479e-01
-1.14070587e-01 -2.39990115e-01 5.42268157e-02 8.35995078e-01
3.45607549e-01 2.22370282e-01 -7.86317050e-01 6.18007123e-01
-1.72452676e+00 -8.47849905e-01 7.26093411e-01 2.13632512e+00
9.35446560e-01 3.82772535e-01 -3.43855955e-02 9.05777365e-02
9.47387934e-01 3.41764927e-01 -1.02080047e+00 -1.86135247e-01
4.46731877e-03 3.89882356e-01 1.26252159e-01 -1.01926103e-02
-1.14336824e+00 9.94556546e-01 4.72344112e+00 1.13660574e+00
-1.10348749e+00 2.42999569e-01 2.80788660e-01 -1.55660346e-01
4.37952206e-02 -8.70572180e-02 -8.43131959e-01 5.70004463e-01
5.46934664e-01 -6.60930514e-01 2.06298918e-01 1.10417342e+00
-2.93637246e-01 1.58004671e-01 -1.12775564e+00 1.13255906e+00
3.24425220e-01 -9.57340181e-01 2.14818507e-01 -2.78906614e-01
7.83664584e-01 -1.81295291e-01 2.02521652e-01 1.04610550e+00
-8.97026658e-02 -5.47147512e-01 2.00821191e-01 6.19610965e-01
7.83122122e-01 -1.01496685e+00 6.21536672e-01 4.33959335e-01
-1.25566423e+00 -3.63002598e-01 -9.05440331e-01 -1.03697695e-01
-1.91022798e-01 3.14028323e-01 -7.80859530e-01 5.96529424e-01
5.40896237e-01 8.43181729e-01 -8.14504623e-01 1.08796847e+00
5.14585078e-02 1.60982579e-01 1.11628778e-01 -5.52630313e-02
2.18239829e-01 1.15071535e-01 1.68290466e-01 1.02050650e+00
3.71439368e-01 2.58448720e-01 2.72925138e-01 5.58775127e-01
-1.88739672e-01 1.72904387e-01 -4.32629943e-01 2.05909669e-01
7.81679571e-01 1.09791303e+00 -3.56076717e-01 -6.62022233e-01
-5.09562850e-01 1.20634329e+00 5.84657073e-01 3.54426563e-01
-7.50854909e-01 -9.77734208e-01 8.39250743e-01 1.23044334e-01
3.49183321e-01 1.48976780e-03 -1.25146762e-01 -1.42658162e+00
3.46492650e-03 -5.21744728e-01 7.04325259e-01 -3.53595376e-01
-1.72333026e+00 4.33848083e-01 -3.79145257e-02 -1.62501431e+00
-1.12618245e-01 -4.56751317e-01 -7.04597116e-01 9.03706253e-01
-1.87941110e+00 -9.05504882e-01 -5.16766131e-01 7.55993962e-01
7.43337870e-01 -4.13584530e-01 8.53572369e-01 4.32447404e-01
-7.37962067e-01 1.06742513e+00 4.34078425e-01 9.99975950e-02
1.23998713e+00 -1.03870487e+00 2.31315702e-01 6.65350914e-01
-2.02200368e-01 9.68178391e-01 3.98220599e-01 -4.99684215e-01
-1.10709965e+00 -1.38664985e+00 6.32844150e-01 -1.43488020e-01
6.48791015e-01 -2.61412382e-01 -1.37723672e+00 3.72400552e-01
-1.22701507e-02 3.47923249e-01 1.02472234e+00 8.16239417e-02
-7.09434092e-01 -5.26409328e-01 -1.19776404e+00 4.48040813e-01
1.08030272e+00 -5.16569674e-01 -1.25972331e+00 -9.54451561e-02
8.61938596e-01 -5.15192151e-02 -7.64177501e-01 4.72618639e-01
4.76226330e-01 -7.31840670e-01 9.12696004e-01 -8.60180914e-01
2.25227192e-01 -2.68073946e-01 -3.92013937e-01 -1.42994905e+00
-7.73284674e-01 -1.01340704e-01 -3.38311166e-01 1.53427887e+00
1.68966204e-01 -7.32065558e-01 6.92482173e-01 6.15861416e-01
-3.26836221e-02 -6.92391574e-01 -9.20446098e-01 -1.22634220e+00
2.38945991e-01 -3.84108387e-02 9.21756327e-01 1.34695280e+00
2.19867021e-01 5.20057440e-01 -1.53007820e-01 -8.82439613e-02
6.40494704e-01 3.23042810e-01 6.65397465e-01 -1.41192842e+00
4.94599268e-02 -3.73045266e-01 -6.42426312e-01 -1.06211090e+00
1.39603972e-01 -1.10023296e+00 -1.58448771e-01 -1.27548885e+00
3.50800604e-01 -2.87521690e-01 -1.09802413e+00 3.96332532e-01
-3.84493113e-01 6.52095154e-02 9.17164534e-02 2.38805205e-01
-9.09683526e-01 8.70838702e-01 1.02559555e+00 -3.92360300e-01
-4.31674659e-01 -1.18482560e-01 -1.10959172e+00 5.61521292e-01
9.39532161e-01 -4.27511752e-01 -5.78129053e-01 -3.62663835e-01
-5.34354866e-01 -5.79363406e-01 1.64968148e-01 -1.30605841e+00
5.27620018e-01 -3.64412487e-01 7.53298998e-01 -4.61334556e-01
2.55729258e-01 -6.77339911e-01 -4.10933256e-01 4.29831147e-01
-3.54400456e-01 -2.56411284e-01 1.61630288e-01 8.15544009e-01
-2.75243282e-01 -2.10842490e-01 1.08369458e+00 -1.09555289e-01
-1.33454800e+00 4.80245054e-01 2.75588304e-01 3.93545777e-01
1.36724949e+00 -3.98839176e-01 -4.34774339e-01 3.55942994e-01
-6.98723793e-01 4.43157107e-01 3.86814207e-01 7.22948015e-01
7.24927485e-01 -1.67461765e+00 -5.00930965e-01 3.91427368e-01
8.34385633e-01 -7.29871839e-02 6.45948946e-01 4.18079644e-01
1.42908350e-01 2.39472494e-01 -3.62417728e-01 -4.65471566e-01
-7.70696580e-01 1.01883614e+00 -5.80278225e-03 -2.66378783e-02
-3.20457041e-01 9.35124040e-01 1.95340350e-01 -4.98195916e-01
2.11518675e-01 -1.27637684e-01 -2.98254192e-01 5.69040179e-01
9.05125737e-01 5.34884810e-01 1.41839623e-01 -3.49516869e-01
-6.31478727e-01 6.00868762e-01 -6.07417107e-01 2.71498382e-01
1.27692175e+00 -3.93187821e-01 2.93247432e-01 4.55451608e-01
1.38239872e+00 -5.22363186e-01 -1.10554731e+00 -8.47362876e-01
2.33284011e-01 -5.72423339e-01 -2.79087335e-01 -7.07343698e-01
-6.22668087e-01 1.05468047e+00 9.49830830e-01 4.13003974e-02
1.19707620e+00 -9.88487452e-02 9.63654101e-01 4.97097075e-01
3.35914046e-01 -1.38612878e+00 1.79630846e-01 6.73056662e-01
4.89958405e-01 -1.44816148e+00 -1.26031712e-01 6.44447887e-03
-4.79559869e-01 8.34807217e-01 1.16828251e+00 -2.55578279e-01
7.17449367e-01 -2.90000379e-01 -2.80272365e-01 1.63325682e-01
-6.06459856e-01 -2.82303870e-01 3.07937145e-01 6.36691988e-01
1.62082329e-01 -3.66411023e-02 -4.63064551e-01 1.12355554e+00
7.83054605e-02 2.77739298e-02 4.87441570e-02 1.09848034e+00
-9.94550169e-01 -9.42246854e-01 -5.60927130e-02 4.53961253e-01
1.11981153e-01 -1.42971113e-01 -1.49958745e-01 5.57617843e-01
4.50615466e-01 8.66355121e-01 1.26429752e-01 -6.22590601e-01
6.98283017e-01 4.36397374e-01 1.69034243e-01 -9.92147565e-01
-1.98203072e-01 -3.24116379e-01 -5.64058900e-01 -3.96037102e-01
-1.28182709e-01 -3.44164401e-01 -1.13325477e+00 -6.13221228e-02
-2.39848539e-01 2.00636849e-01 2.17918366e-01 8.74745369e-01
5.59347153e-01 4.55394417e-01 8.59915555e-01 -5.35172582e-01
-8.74921143e-01 -1.01177371e+00 -6.85195863e-01 5.52851975e-01
2.44042516e-01 -9.81344223e-01 -5.16552389e-01 -1.43244863e-01] | [10.110654830932617, 3.0531911849975586] |
545f063c-6bf4-4bb6-8dca-ba04dbdbb5fb | repnet-weakly-supervised-training-of-an | 1902.09868 | null | http://arxiv.org/abs/1902.09868v2 | http://arxiv.org/pdf/1902.09868v2.pdf | RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation | This paper addresses the problem of 3D human pose estimation from single
images. While for a long time human skeletons were parameterized and fitted to
the observation by satisfying a reprojection error, nowadays researchers
directly use neural networks to infer the 3D pose from the observations.
However, most of these approaches ignore the fact that a reprojection
constraint has to be satisfied and are sensitive to overfitting. We tackle the
overfitting problem by ignoring 2D to 3D correspondences. This efficiently
avoids a simple memorization of the training data and allows for a weakly
supervised training. One part of the proposed reprojection network (RepNet)
learns a mapping from a distribution of 2D poses to a distribution of 3D poses
using an adversarial training approach. Another part of the network estimates
the camera. This allows for the definition of a network layer that performs the
reprojection of the estimated 3D pose back to 2D which results in a
reprojection loss function. Our experiments show that RepNet generalizes well
to unknown data and outperforms state-of-the-art methods when applied to unseen
data. Moreover, our implementation runs in real-time on a standard desktop PC. | ['Bastian Wandt', 'Bodo Rosenhahn'] | 2019-02-26 | repnet-weakly-supervised-training-of-an-1 | http://openaccess.thecvf.com/content_CVPR_2019/html/Wandt_RepNet_Weakly_Supervised_Training_of_an_Adversarial_Reprojection_Network_for_CVPR_2019_paper.html | http://openaccess.thecvf.com/content_CVPR_2019/papers/Wandt_RepNet_Weakly_Supervised_Training_of_an_Adversarial_Reprojection_Network_for_CVPR_2019_paper.pdf | cvpr-2019-6 | ['monocular-3d-human-pose-estimation', 'weakly-supervised-3d-human-pose-estimation'] | ['computer-vision', 'computer-vision'] | [ 5.68184927e-02 2.17944220e-01 -3.29029374e-02 -4.11759913e-01
-4.80310291e-01 -4.40795898e-01 4.58417863e-01 -1.86389759e-01
-8.20707083e-01 6.25196397e-01 -1.22145362e-01 1.89108729e-01
9.02534425e-02 -8.10143709e-01 -1.26887476e+00 -4.77845997e-01
2.51657814e-01 9.60942328e-01 2.58588433e-01 -4.52216752e-02
-7.05630109e-02 6.23143673e-01 -1.21828437e+00 -3.66527766e-01
5.03412485e-01 7.75767028e-01 -1.67052243e-02 5.66659331e-01
2.41945252e-01 1.46507517e-01 -6.30138993e-01 -4.49282706e-01
5.11722088e-01 -2.47708067e-01 -6.41029358e-01 4.54152733e-01
7.61234999e-01 -4.44417983e-01 -3.83871317e-01 1.09718168e+00
5.97937942e-01 1.45427480e-01 6.10877216e-01 -1.07264936e+00
-3.13231051e-01 -2.04504970e-02 -3.89459819e-01 -3.36513281e-01
5.73048532e-01 -1.07868500e-01 6.15830123e-01 -7.59262085e-01
8.13470960e-01 1.12102771e+00 1.03655875e+00 5.97324073e-01
-1.41059208e+00 -3.94899398e-01 -1.77292705e-01 -1.47746012e-01
-1.54330230e+00 -1.43353865e-01 9.11414623e-01 -4.21125770e-01
5.92036724e-01 -3.45755033e-02 9.66999054e-01 1.37440896e+00
2.05826357e-01 6.74237072e-01 8.98270905e-01 -4.29576218e-01
2.68630862e-01 -1.35438964e-02 -2.47185439e-01 7.55497456e-01
1.29266873e-01 7.29002059e-02 -3.64916742e-01 -2.63462123e-02
1.29672384e+00 1.81564271e-01 -2.63836712e-01 -9.67501521e-01
-1.07783175e+00 7.54714429e-01 6.40291512e-01 -1.42613441e-01
-3.96484017e-01 2.67959237e-01 2.55980968e-01 1.54664502e-01
3.79492491e-01 4.11024690e-01 -4.30942476e-01 1.18501239e-01
-8.31743181e-01 3.69532615e-01 8.27119112e-01 7.81210780e-01
8.51757944e-01 -1.96086943e-01 4.01114136e-01 6.90759063e-01
1.93980783e-01 4.94114041e-01 4.75942522e-01 -9.88239884e-01
5.20506799e-01 3.51798803e-01 1.10700950e-01 -1.07964611e+00
-5.74742377e-01 -6.35436475e-01 -7.36858189e-01 3.65696371e-01
7.61606932e-01 -8.22458938e-02 -9.01938498e-01 1.86200356e+00
5.82159162e-01 2.34065592e-01 -1.57588258e-01 1.17486858e+00
2.45770827e-01 2.74274707e-01 -2.59242415e-01 2.35135898e-01
1.09021473e+00 -8.72464716e-01 -3.03532839e-01 -4.86510903e-01
1.59956202e-01 -5.70978701e-01 9.60289240e-01 4.72573489e-01
-1.06517076e+00 -6.21240139e-01 -1.02240598e+00 -2.15173975e-01
-1.51916638e-01 1.71039980e-02 3.83866847e-01 5.53587675e-01
-8.05697680e-01 8.32131803e-01 -1.07410467e+00 -5.24085343e-01
2.25119323e-01 5.84005058e-01 -8.44099522e-01 9.89725664e-02
-1.06925952e+00 1.06710362e+00 5.30461192e-01 2.94623971e-01
-7.63397217e-01 -3.00526828e-01 -1.02633178e+00 -2.72480726e-01
6.43698931e-01 -1.16072023e+00 1.01333356e+00 -1.00991774e+00
-1.73491323e+00 1.01989996e+00 2.08666950e-01 -4.87726450e-01
1.01306438e+00 -7.56268501e-01 8.58234614e-02 2.02214360e-01
-1.31462263e-02 6.94431484e-01 1.13636386e+00 -1.19669342e+00
-3.62145342e-02 -6.04773819e-01 1.89602092e-01 3.10422152e-01
-9.41851363e-02 -6.74267113e-01 -9.31381345e-01 -7.39902198e-01
4.75748390e-01 -1.10730779e+00 -2.08823577e-01 3.38837981e-01
-5.60406446e-01 1.12903394e-01 4.99462843e-01 -5.13370454e-01
6.54976130e-01 -1.86514795e+00 6.58348501e-01 3.46712559e-01
-2.40941579e-03 1.84865639e-01 -5.00509217e-02 2.53747493e-01
-1.91231906e-01 -3.34645927e-01 -2.78590292e-01 -6.83472991e-01
2.82299612e-02 3.71318132e-01 -1.15346089e-01 9.68800068e-01
-2.77660992e-02 8.80709529e-01 -7.93146312e-01 -3.08073401e-01
4.75971967e-01 8.14183354e-01 -7.32626557e-01 4.12166238e-01
-2.82780319e-01 7.16727495e-01 -2.86908299e-01 8.40692222e-02
5.98643243e-01 -1.91025585e-01 1.08782321e-01 -2.58247167e-01
2.73070395e-01 7.02807009e-02 -1.21987605e+00 2.33293462e+00
-4.73807603e-01 1.50569305e-01 -2.30926543e-01 -1.10403681e+00
1.01112378e+00 3.07060838e-01 5.03351688e-01 -5.42001463e-02
3.81616741e-01 1.90836146e-01 -5.16961038e-01 -4.77596074e-01
2.91166395e-01 -3.55954736e-01 -1.15610011e-01 3.78834099e-01
2.70186305e-01 -3.55863541e-01 -3.93803388e-01 -1.80462018e-01
8.22630465e-01 7.62374640e-01 3.29771161e-01 1.42674342e-01
5.05237043e-01 -2.38043547e-01 4.16492313e-01 3.81498575e-01
6.50118291e-02 9.27455187e-01 3.67466688e-01 -7.99675286e-01
-1.22119749e+00 -1.32499290e+00 9.09262002e-02 4.93286967e-01
1.22031376e-01 -1.06448673e-01 -9.68132257e-01 -8.42050374e-01
5.99978343e-02 3.94966155e-01 -7.79396176e-01 -3.02969068e-01
-6.70039535e-01 -3.19583207e-01 5.62616467e-01 5.22478640e-01
5.91753840e-01 -7.80821860e-01 -6.32608235e-01 1.00900896e-01
-2.57267982e-01 -1.21217966e+00 -6.23177111e-01 7.39714950e-02
-1.02424705e+00 -1.08399916e+00 -8.76621664e-01 -6.89070165e-01
9.39467430e-01 -1.59902513e-01 9.56423402e-01 -1.63763702e-01
-1.54062957e-01 4.01037246e-01 -9.13918391e-02 -1.68612227e-01
-3.22685122e-01 2.03760952e-01 2.29836777e-01 2.96709817e-02
3.69143337e-01 -7.37050831e-01 -4.49327379e-01 4.44489896e-01
-8.27854991e-01 -1.00517645e-01 4.75318134e-01 8.39610219e-01
8.33847642e-01 -2.37829238e-02 2.58443803e-01 -7.77457356e-01
1.93248555e-01 -1.12050943e-01 -6.74805701e-01 4.08469550e-02
-1.27899602e-01 3.26810479e-01 6.50826156e-01 -7.09172547e-01
-7.78171718e-01 7.42157876e-01 -3.58734608e-01 -7.32686579e-01
-3.50954860e-01 1.29675582e-01 -2.29242265e-01 -1.72181819e-02
7.91912258e-01 7.08579645e-02 3.09158921e-01 -6.68334782e-01
3.41562718e-01 2.71194041e-01 9.80124116e-01 -5.30310690e-01
1.07169390e+00 7.13637233e-01 2.17418611e-01 -6.64031446e-01
-1.09287763e+00 -3.06065679e-01 -1.15634298e+00 -1.48952365e-01
9.48117673e-01 -8.88294160e-01 -7.11711586e-01 5.31849980e-01
-1.13247085e+00 -2.38996342e-01 -4.68618184e-01 6.77631855e-01
-9.74212945e-01 7.05048800e-01 -3.12034160e-01 -5.02857447e-01
-1.06251091e-01 -1.04524064e+00 1.21657503e+00 -1.40029460e-01
-4.46184039e-01 -9.98046637e-01 2.00617656e-01 2.65324742e-01
-1.07541919e-01 5.24067819e-01 3.65486890e-01 -3.27345431e-01
-3.03906411e-01 -5.80444574e-01 1.69218227e-01 5.32143474e-01
-3.60040367e-02 -5.00816107e-01 -8.61188412e-01 -3.55016798e-01
2.29930326e-01 -3.86841059e-01 6.25879884e-01 3.97128969e-01
1.03214967e+00 -1.24563426e-01 -1.51975229e-01 8.70113313e-01
1.21051288e+00 -4.43764359e-01 5.95526338e-01 4.46387589e-01
7.90260077e-01 5.66941202e-01 3.71960133e-01 2.58593827e-01
2.89223313e-01 9.15796340e-01 7.53572226e-01 -2.90197674e-02
-3.51650752e-02 -7.74909437e-01 2.24075869e-01 4.95498151e-01
-1.50580481e-01 -6.24057576e-02 -6.61245227e-01 2.99522728e-01
-1.78661489e+00 -5.38640797e-01 1.97112635e-01 2.60109138e+00
7.27882266e-01 3.48293245e-01 2.48027593e-01 1.55767307e-01
7.88030207e-01 -6.30699545e-02 -6.77624702e-01 -1.93724800e-02
2.24891663e-01 2.66827434e-01 6.29462004e-01 6.28099859e-01
-1.20417476e+00 9.35815990e-01 5.92217350e+00 5.06449699e-01
-1.10023963e+00 5.20091616e-02 -1.53409527e-03 -1.02356290e-02
4.11796831e-02 -8.95377025e-02 -5.94294965e-01 1.82257414e-01
4.73685235e-01 3.71558785e-01 4.29841906e-01 8.88209343e-01
1.88581701e-02 3.37343365e-02 -1.29335022e+00 9.77588713e-01
2.54120559e-01 -8.22038710e-01 -1.16550215e-02 1.24023080e-01
4.57000732e-01 -1.07373722e-01 -1.08618073e-01 -6.63806126e-02
8.27263203e-03 -8.80334556e-01 9.48024571e-01 7.36957252e-01
8.00788105e-01 -7.80992031e-01 6.71472609e-01 7.53274322e-01
-7.83448040e-01 1.96435928e-01 -5.03291011e-01 -8.22960883e-02
3.00033838e-01 5.05934417e-01 -8.00802171e-01 3.94235075e-01
4.72804725e-01 6.38096929e-01 -3.89684916e-01 9.54040766e-01
-6.55760467e-01 4.49714717e-03 -5.88448048e-01 2.77851492e-01
7.14278407e-03 -2.12155327e-01 7.04448760e-01 7.10364282e-01
3.15523297e-01 -3.91114444e-01 1.62190244e-01 7.67727733e-01
-1.54796466e-01 -7.08838031e-02 -5.77235162e-01 3.36390555e-01
2.03986183e-01 8.26963127e-01 -6.69694662e-01 -2.83146836e-02
1.64475497e-02 1.43215120e+00 5.11032760e-01 1.99825481e-01
-7.92803884e-01 -2.53464818e-01 3.95102233e-01 2.96203405e-01
2.92520583e-01 -5.25600672e-01 -1.34155229e-01 -1.34173322e+00
2.28250608e-01 -6.32634401e-01 1.46238938e-01 -7.86398292e-01
-1.29571450e+00 5.84792078e-01 1.55616343e-01 -1.24894869e+00
-4.31493521e-01 -5.18447459e-01 -2.94200450e-01 6.87263548e-01
-1.13580120e+00 -9.72760737e-01 -3.40289682e-01 5.64697266e-01
2.53256887e-01 4.58596610e-02 8.18402410e-01 2.37444058e-01
-2.25329936e-01 5.00211895e-01 -2.63509274e-01 2.87720859e-01
9.28280175e-01 -1.35558081e+00 6.08110607e-01 5.94081819e-01
2.28456631e-01 6.57382667e-01 8.43551338e-01 -5.69432199e-01
-1.20574772e+00 -8.88703704e-01 8.52987885e-01 -6.28485322e-01
3.42751294e-01 -4.57087755e-01 -7.77426124e-01 8.67804706e-01
-2.95205772e-01 2.63608158e-01 2.83997715e-01 -9.63576660e-02
-4.16070133e-01 -6.36790991e-02 -1.25021458e+00 4.41501886e-01
1.12214530e+00 -5.22480309e-01 -7.76448548e-01 2.68337697e-01
4.07025427e-01 -8.30895364e-01 -9.03453887e-01 1.30702570e-01
7.45427728e-01 -9.65076566e-01 1.21203506e+00 -5.70458293e-01
3.23127717e-01 -3.76043022e-01 1.80529766e-02 -1.24416602e+00
1.18629359e-01 -5.67402661e-01 -7.87701532e-02 6.01268172e-01
-6.24678917e-02 -5.46565175e-01 1.07902706e+00 4.07489032e-01
7.96022415e-02 -5.91278851e-01 -1.10569513e+00 -8.55891883e-01
1.46956310e-01 -5.01845598e-01 4.53841925e-01 6.96532667e-01
-4.61501688e-01 3.84376466e-01 -6.34384930e-01 3.73974741e-01
8.34568322e-01 -1.25918493e-01 1.29371727e+00 -1.21665299e+00
-5.61199784e-01 2.42048558e-02 -7.59749413e-01 -1.44564104e+00
4.05321628e-01 -7.59853303e-01 1.20128609e-01 -1.20766258e+00
-8.12021345e-02 -2.28129372e-01 2.50817627e-01 3.09259385e-01
1.10037364e-01 5.76208711e-01 1.42405212e-01 1.98048905e-01
-2.67020196e-01 4.79908049e-01 1.29679346e+00 7.44045079e-02
-1.89351842e-01 3.79371971e-01 -1.98991403e-01 1.15720809e+00
6.10620797e-01 -6.61247909e-01 -3.78665566e-01 -6.45535111e-01
2.40488052e-01 8.60880781e-03 8.14718187e-01 -1.12018776e+00
1.97081298e-01 2.13680223e-01 4.97183681e-01 -5.63337088e-01
7.13339567e-01 -1.15597296e+00 4.52374488e-01 3.17866772e-01
-2.06343189e-01 -1.63426280e-01 -1.37051880e-01 7.34404027e-01
2.25154404e-02 -3.64779055e-01 8.15620661e-01 -2.99848199e-01
-2.22591355e-01 3.73250812e-01 1.27869293e-01 -5.10560572e-02
9.73613739e-01 -5.36240458e-01 3.73441845e-01 -5.10137081e-01
-1.12347257e+00 -9.03218016e-02 8.36619914e-01 3.40345293e-01
5.73064864e-01 -1.34706354e+00 -3.97540718e-01 4.37356144e-01
-1.76365286e-01 5.14905751e-01 1.12213038e-01 5.85981727e-01
-7.90443420e-01 1.25336096e-01 -2.82065809e-01 -8.18263292e-01
-1.00666773e+00 5.56178749e-01 6.90647304e-01 -2.30269060e-01
-9.08612669e-01 7.24099278e-01 3.34764645e-02 -8.49485874e-01
4.36630189e-01 -8.40542018e-02 1.83056489e-01 -2.53090501e-01
6.51180521e-02 2.84720451e-01 -7.41159990e-02 -9.31348979e-01
-2.20007852e-01 1.01679623e+00 2.24796638e-01 -2.14120939e-01
1.46785855e+00 -2.55400464e-02 8.40432271e-02 4.00960684e-01
1.53928888e+00 -9.39920545e-02 -1.58501995e+00 -3.92079204e-01
-3.55438441e-01 -5.47339559e-01 -1.93479478e-01 -3.79480630e-01
-1.07964063e+00 9.06011701e-01 4.46948349e-01 -2.65837878e-01
9.08641040e-01 -7.66298994e-02 8.69721115e-01 5.72883070e-01
4.17603314e-01 -1.12276280e+00 2.89308071e-01 4.43472326e-01
9.16801870e-01 -1.04374635e+00 2.12716758e-01 -3.65124345e-01
-3.20107728e-01 1.26265752e+00 4.13354993e-01 -5.47621727e-01
7.08826125e-01 5.57317212e-02 9.22543779e-02 -3.33624333e-02
-1.22707160e-02 8.80222395e-02 3.59803408e-01 6.51782572e-01
6.05858713e-02 -1.11776769e-01 -1.92938790e-01 1.40088841e-01
-4.93951648e-01 1.39283136e-01 3.41669977e-01 8.29790533e-01
-2.48222485e-01 -1.28531253e+00 -6.65664434e-01 -1.29056469e-01
-4.13420200e-01 4.64274377e-01 -2.52314240e-01 9.75734949e-01
2.86435544e-01 3.30751479e-01 1.05600134e-01 -2.65752584e-01
6.20281041e-01 9.92457196e-02 7.55097985e-01 -5.89120269e-01
-3.61151546e-01 2.27671787e-01 -3.19933742e-01 -6.24907672e-01
-5.26477933e-01 -5.70790946e-01 -1.16855216e+00 -7.87414834e-02
-4.08044040e-01 -1.03442390e-02 8.28635991e-01 9.60198820e-01
7.20977485e-02 3.48458439e-01 3.18172425e-01 -1.16271627e+00
-8.53266180e-01 -7.83420622e-01 -6.08781993e-01 6.69786334e-01
3.43133956e-01 -9.71396863e-01 -2.13553503e-01 1.31771505e-01] | [7.010972023010254, -1.0538285970687866] |
3ca6a3df-3d5c-4bbb-a22e-c48e35378ed9 | proximal-nested-sampling-with-data-driven | 2307.00056 | null | https://arxiv.org/abs/2307.00056v1 | https://arxiv.org/pdf/2307.00056v1.pdf | Proximal nested sampling with data-driven priors for physical scientists | Proximal nested sampling was introduced recently to open up Bayesian model selection for high-dimensional problems such as computational imaging. The framework is suitable for models with a log-convex likelihood, which are ubiquitous in the imaging sciences. The purpose of this article is two-fold. First, we review proximal nested sampling in a pedagogical manner in an attempt to elucidate the framework for physical scientists. Second, we show how proximal nested sampling can be extended in an empirical Bayes setting to support data-driven priors, such as deep neural networks learned from training data. | ['Marcelo Pereyra', 'Xiaohao Cai', 'Matthew A. Price', 'Tobías I. Liaudat', 'Jason D. McEwen'] | 2023-06-30 | null | null | null | null | ['model-selection'] | ['methodology'] | [ 4.13046122e-01 4.09224629e-01 -2.63015062e-01 -5.43249369e-01
-8.77170384e-01 -1.06811225e-01 4.87466812e-01 -2.35350356e-01
-5.42864203e-01 5.85733116e-01 1.59059808e-01 -4.25102383e-01
-6.56361938e-01 -5.32524884e-01 -7.56649852e-01 -8.84822011e-01
-2.99854338e-01 4.67698038e-01 1.23661481e-01 4.64353561e-01
3.50928485e-01 6.98006868e-01 -1.36514699e+00 -5.24626821e-02
6.14232957e-01 6.89898431e-01 5.94297349e-01 6.31482899e-01
4.05717820e-01 3.83267641e-01 1.78274997e-02 -3.83795798e-01
1.30802915e-01 -1.33650035e-01 -6.04902804e-01 8.77170041e-02
4.66617584e-01 -5.41022360e-01 -4.87528861e-01 1.06193733e+00
5.95720172e-01 3.29060912e-01 9.47054505e-01 -8.87531459e-01
-2.95680314e-01 3.19723606e-01 -5.87731600e-01 2.07549244e-01
-6.86261579e-02 -2.08982885e-01 7.31045544e-01 -1.09469450e+00
5.99753857e-01 1.54391313e+00 5.19772351e-01 5.83803117e-01
-1.36092389e+00 -2.23458901e-01 1.83964133e-01 2.90442854e-01
-1.12286770e+00 -4.37292546e-01 6.70003414e-01 -7.08164632e-01
1.86499342e-01 1.67377889e-01 7.05542743e-01 1.34084034e+00
2.24440530e-01 1.04799390e+00 1.34865558e+00 -7.45649576e-01
5.14307678e-01 3.78918760e-02 3.51526499e-01 5.02755165e-01
1.36526376e-01 3.04136217e-01 -6.10672474e-01 -7.34831035e-01
1.12735593e+00 -2.29009539e-01 -2.33167902e-01 -6.20715559e-01
-9.53615785e-01 1.22451174e+00 4.93960306e-02 -8.83621648e-02
-3.59896928e-01 2.58820921e-01 1.31070018e-01 -3.33211005e-01
6.80613756e-01 1.59901395e-01 -3.30799401e-01 -9.82658416e-02
-1.10564363e+00 4.04185742e-01 7.51147628e-01 8.15018296e-01
3.52564305e-01 -1.40429348e-01 -3.23091984e-01 9.32983577e-01
1.03573704e+00 4.76905406e-01 -8.59894976e-02 -1.37070751e+00
-1.09548554e-01 -6.02089942e-01 1.97066292e-01 -5.45024276e-01
-3.01979214e-01 -5.78860760e-01 -8.37363064e-01 4.12571847e-01
5.29048800e-01 -1.03274100e-01 -7.64594972e-01 1.78676832e+00
5.23165464e-01 2.81902671e-01 -4.82443660e-01 8.23157072e-01
4.82438833e-01 5.02718449e-01 5.09649813e-02 -4.05318111e-01
1.45586824e+00 -4.87397552e-01 -4.75921571e-01 -1.76097989e-01
2.30171382e-01 -6.32657826e-01 1.01236463e+00 8.20832133e-01
-1.15617287e+00 -8.37296546e-02 -7.47451484e-01 -1.07385658e-01
2.53436625e-01 1.58076301e-01 6.27808630e-01 6.95931256e-01
-9.52235818e-01 5.68343818e-01 -1.23322809e+00 -4.18669820e-01
6.61197126e-01 -9.26112607e-02 2.58348882e-01 -4.87295799e-02
-1.00552177e+00 8.05618286e-01 1.09926850e-01 1.38749361e-01
-1.26006889e+00 -7.78241158e-01 -7.52493858e-01 -5.04337661e-02
4.07929033e-01 -1.04523921e+00 1.49089468e+00 -2.70200551e-01
-1.55669320e+00 9.13936675e-01 -4.44597870e-01 -4.56478328e-01
8.34494650e-01 -3.58899236e-01 2.41119176e-01 3.67149800e-01
-1.13444954e-01 5.64776659e-01 1.13565457e+00 -1.06654537e+00
-1.61410525e-01 -5.55773973e-01 1.49074212e-01 2.21214101e-01
-4.99430299e-02 1.69514462e-01 -3.71334106e-01 -6.30613148e-01
2.98404127e-01 -9.27860260e-01 -7.89550245e-01 4.71613109e-01
-5.31223416e-01 -2.13856831e-01 2.49551147e-01 -3.16578984e-01
8.25484812e-01 -1.97414637e+00 9.25154462e-02 1.69868439e-01
4.71237957e-01 -2.94034779e-01 2.51986414e-01 1.63245082e-01
-1.01453528e-01 -9.54587534e-02 -3.48389864e-01 -4.32055593e-01
2.28861198e-01 1.13998950e-01 -4.31075454e-01 8.58062863e-01
1.81123331e-01 5.50593376e-01 -8.16170990e-01 -5.16075313e-01
2.51393497e-01 5.58403790e-01 -7.01814413e-01 1.02783553e-01
-1.65563017e-01 4.90242481e-01 -6.20375335e-01 2.85810858e-01
7.39153862e-01 -4.50868845e-01 -5.93188889e-02 -3.51030864e-02
-1.92393661e-01 3.63666266e-01 -1.33243132e+00 1.53384423e+00
-2.71938026e-01 6.24970615e-01 5.83187997e-01 -1.12320685e+00
3.39677542e-01 3.12157512e-01 4.38235968e-01 4.02977094e-02
-1.04903452e-01 3.56134437e-02 -2.77336270e-01 -5.08899808e-01
2.06533134e-01 -4.54400569e-01 3.83523494e-01 3.09520930e-01
8.85288790e-02 -1.96998358e-01 8.04742202e-02 3.75192434e-01
8.26398790e-01 1.65995494e-01 4.85044181e-01 -7.96808720e-01
5.70050515e-02 -2.43158698e-01 4.22129750e-01 1.42814982e+00
-1.22940391e-01 5.96354842e-01 5.97362936e-01 -2.88988143e-01
-9.99723673e-01 -1.31259382e+00 -1.01513362e+00 1.06824946e+00
-2.42427409e-01 -1.42466560e-01 -6.23380780e-01 -3.28651428e-01
-3.63048792e-01 5.11989057e-01 -5.84011257e-01 1.96840495e-01
-2.88646609e-01 -1.34195006e+00 1.18605681e-01 3.36298347e-01
-1.45140618e-01 -6.77239716e-01 -6.26372993e-01 9.45585407e-03
8.34331959e-02 -8.76138151e-01 -8.96370038e-02 5.25978446e-01
-1.10916126e+00 -8.52873385e-01 -1.13035023e+00 -3.22124004e-01
5.90949953e-01 -5.90326916e-03 1.20729232e+00 -3.17779690e-01
-3.12595606e-01 9.02084291e-01 -1.01464409e-02 -5.73822379e-01
-1.50752217e-01 -2.25099102e-02 2.30773225e-01 -1.63947433e-01
2.51143962e-01 -5.82890868e-01 -5.99741995e-01 2.07525373e-01
-1.10667896e+00 1.53490201e-01 4.79756176e-01 1.01503849e+00
5.52852154e-01 -2.88375914e-01 3.86158794e-01 -1.02343512e+00
3.83396208e-01 -6.61058068e-01 -8.82841885e-01 6.16225675e-02
-4.09293562e-01 -8.84634182e-02 -2.02699453e-02 -5.75132906e-01
-1.22619104e+00 3.96698080e-02 -3.30223233e-01 -4.50540632e-02
-1.99991897e-01 7.93872058e-01 4.96286154e-03 -9.19363946e-02
7.62451291e-01 7.40509899e-03 -2.01442316e-01 -6.20706439e-01
3.45843226e-01 4.72226441e-01 2.49753669e-01 -1.09038389e+00
4.28023845e-01 8.02897036e-01 3.12824488e-01 -1.09834361e+00
-1.19306588e+00 -1.67003214e-01 -6.34606361e-01 -1.10318437e-01
7.98260212e-01 -8.15737903e-01 -5.88737428e-01 3.80635560e-01
-1.25481951e+00 -6.59729838e-01 -4.26475614e-01 9.87318099e-01
-1.05232751e+00 3.61511171e-01 -6.47368491e-01 -1.17416692e+00
2.58520693e-01 -1.30317795e+00 1.11567593e+00 3.76369625e-01
5.80678843e-02 -1.33772528e+00 6.80578202e-02 1.01897120e-01
1.04310036e-01 -2.96107411e-01 7.81943500e-01 -4.70918298e-01
-6.65450513e-01 1.51484534e-01 -2.40860850e-01 8.30120370e-02
-4.13886130e-01 1.34111732e-01 -1.39680982e+00 -1.18068762e-01
5.74004352e-01 -3.59057277e-01 9.04766977e-01 1.35944855e+00
1.70402300e+00 2.80383285e-02 -3.57972443e-01 7.87859499e-01
1.11041915e+00 -1.43140525e-01 4.23458725e-01 1.66390732e-01
2.29946688e-01 8.41629624e-01 3.04734528e-01 6.92737222e-01
5.27960137e-02 5.47035873e-01 5.36527276e-01 -8.15710332e-03
1.01515897e-01 -2.11205261e-04 -6.23668768e-02 4.82808888e-01
3.13437700e-01 1.03026219e-01 -9.58340704e-01 5.26586235e-01
-1.77291524e+00 -8.17536175e-01 -3.16079855e-01 2.18999290e+00
9.44204569e-01 4.51250002e-02 3.26345116e-02 -3.84803057e-01
8.29624593e-01 -9.84458923e-02 -7.10065663e-01 8.78980979e-02
-8.31109807e-02 2.06770405e-01 4.80299801e-01 7.44773090e-01
-1.07001758e+00 3.56682628e-01 7.89429474e+00 1.21907878e+00
-5.47641337e-01 3.21761996e-01 9.60595429e-01 -1.56418070e-01
-4.33745712e-01 1.68655068e-01 -1.03851795e+00 3.11926037e-01
8.84308457e-01 6.26730919e-02 1.92487702e-01 8.97174239e-01
6.87742412e-01 -3.62208545e-01 -1.26431859e+00 1.00395167e+00
-2.57657707e-01 -1.29684162e+00 -3.00027221e-01 5.00080168e-01
6.02702081e-01 2.55752623e-01 2.38809198e-01 9.77348238e-02
5.56013644e-01 -9.95336175e-01 4.67787415e-01 6.77043021e-01
4.10870194e-01 -3.11569691e-01 2.35136047e-01 6.73957527e-01
-4.53612804e-01 2.63096303e-01 -6.54668868e-01 -1.22768678e-01
5.62054873e-01 1.43988955e+00 -6.94472432e-01 1.14647448e-01
7.71261752e-01 5.64170599e-01 -1.02024674e-01 1.51694143e+00
-6.23563081e-02 8.86371970e-01 -6.60853982e-01 6.45786896e-02
1.26527801e-01 -4.63811070e-01 9.10065651e-01 1.17946064e+00
3.46862584e-01 1.26879066e-02 1.25371635e-01 1.18164396e+00
2.40666404e-01 -1.88205644e-01 -5.76757133e-01 3.42729658e-01
4.23360109e-01 1.28718209e+00 -6.45444214e-01 -3.53851050e-01
-3.06745976e-01 3.41221273e-01 2.03901306e-01 4.99591738e-01
-6.25463128e-01 1.21084519e-01 3.54098499e-01 3.12465310e-01
9.68260616e-02 -4.32298571e-01 -4.09944981e-01 -1.09504771e+00
-1.78082749e-01 -4.16141450e-01 2.36440554e-01 -9.81021941e-01
-1.63293815e+00 2.23464575e-02 7.90182412e-01 -7.87613809e-01
-2.10171238e-01 -1.07145345e+00 -3.11519623e-01 9.13839936e-01
-1.43261552e+00 -7.97762811e-01 2.47736070e-02 2.88011402e-01
3.38562518e-01 1.54989064e-01 6.69362426e-01 1.84579238e-01
-4.94206548e-01 -7.67565295e-02 4.86007273e-01 -1.40153859e-02
6.28138542e-01 -1.51808608e+00 1.41821548e-01 8.45072448e-01
1.38987407e-01 1.00306559e+00 9.03741658e-01 -4.55590755e-01
-1.21816456e+00 -6.59896672e-01 3.44776005e-01 -2.08267748e-01
8.38229656e-01 -3.90708447e-01 -7.30221689e-01 5.53322315e-01
2.01523975e-02 3.33709568e-01 8.50980461e-01 3.88235539e-01
-1.11081898e-01 2.56499767e-01 -1.18550897e+00 7.12377250e-01
8.81242812e-01 -3.68507206e-01 -3.05022269e-01 6.47185802e-01
2.73023188e-01 -5.14837980e-01 -9.22493935e-01 3.29524934e-01
6.79897666e-01 -8.94313753e-01 1.16131198e+00 -6.63790345e-01
2.96914458e-01 1.11112759e-01 -3.57885331e-01 -1.16887629e+00
-4.02070522e-01 -8.28079522e-01 -4.66472030e-01 8.29521060e-01
2.58010514e-02 -6.91240072e-01 8.97765994e-01 7.22331941e-01
-7.67967626e-02 -8.82907033e-01 -1.19249797e+00 -6.85109377e-01
4.58015710e-01 -8.88746381e-01 -9.27792490e-02 5.76475203e-01
-2.01713905e-01 1.14370987e-01 -2.28177816e-01 1.14785865e-01
1.30940700e+00 -3.85936469e-01 4.06377554e-01 -1.52504742e+00
-6.32701457e-01 -5.13884485e-01 -1.00431688e-01 -1.78206217e+00
1.74474157e-02 -5.71969867e-01 3.18053305e-01 -1.21715057e+00
6.55026436e-01 -6.98859334e-01 -1.62181526e-03 -1.13411047e-01
-1.57159418e-01 1.24949366e-01 -3.44856940e-02 4.21621241e-02
-3.49032581e-01 6.63188577e-01 1.19302785e+00 1.39044642e-01
2.67900527e-01 4.14577335e-01 -8.15511525e-01 1.10471821e+00
6.51919305e-01 -7.26151764e-01 -5.38600504e-01 -4.74347144e-01
5.48590362e-01 2.15984419e-01 7.02446699e-01 -5.22293091e-01
2.04575554e-01 -4.22466487e-01 2.86660075e-01 -6.27942920e-01
5.38101852e-01 -5.74435413e-01 -1.98694199e-01 2.41001010e-01
-4.99369472e-01 -5.16892254e-01 -1.67906314e-01 7.32075870e-01
1.54385850e-01 -9.66025949e-01 1.06523299e+00 -2.83441633e-01
-8.79275352e-02 4.09293622e-01 -6.69275582e-01 3.10451597e-01
6.98898017e-01 -4.07445617e-02 -3.82171832e-02 -5.15402734e-01
-1.09901452e+00 -4.80280779e-02 1.61071435e-01 -3.79509121e-01
5.55762887e-01 -1.18539178e+00 -8.45764875e-01 -7.80665800e-02
-1.08519532e-01 3.73015970e-01 3.99426609e-01 1.26292896e+00
-2.88944066e-01 3.41912836e-01 3.42175156e-01 -1.13586664e+00
-9.82958317e-01 1.40169069e-01 3.80547136e-01 -1.72462434e-01
-5.79352736e-01 1.02138913e+00 6.72340512e-01 -3.94814730e-01
4.18890089e-01 -2.61015862e-01 1.26707911e-01 -1.29891008e-01
8.44376981e-01 3.96092057e-01 -1.25759527e-01 -7.75042772e-02
-3.11983764e-01 2.84360260e-01 -3.37172374e-02 -6.26157880e-01
1.64333439e+00 -3.29495281e-01 -7.60158524e-02 8.16662014e-01
9.71536696e-01 -1.26366004e-01 -1.69192839e+00 -3.89820307e-01
-9.09401998e-02 -4.37785685e-01 4.05994594e-01 -4.19640779e-01
-5.98603666e-01 1.16446149e+00 5.19084930e-01 2.32336968e-01
7.39421248e-01 2.38242999e-01 -3.79119702e-02 2.65534520e-01
2.46205464e-01 -8.73563290e-01 -6.59829378e-02 4.32696074e-01
8.60872149e-01 -1.31818271e+00 3.50052536e-01 -2.89024055e-01
-1.23202547e-01 1.31666899e+00 8.49399716e-02 -2.32033193e-01
1.40998161e+00 4.98077452e-01 -5.03821671e-01 -3.34953964e-01
-7.92775810e-01 -5.72296530e-02 4.34379339e-01 8.70609343e-01
5.79899251e-01 -2.78682053e-01 -2.46558517e-01 2.60570586e-01
1.58361152e-01 1.01630226e-01 7.85418630e-01 7.66431630e-01
-4.92177516e-01 -9.68490124e-01 -6.47085011e-01 7.45763183e-01
-4.86001372e-01 -2.97226787e-01 1.76586345e-01 4.04465169e-01
-1.97088048e-01 6.62913382e-01 -6.88098511e-03 6.44781649e-01
-3.04634154e-01 -2.15144716e-02 9.58614707e-01 -7.74262846e-01
2.20957801e-01 5.47037363e-01 -1.81159303e-01 -2.90414512e-01
-5.53199232e-01 -1.20795298e+00 -5.89315355e-01 -2.68979762e-02
-3.83721381e-01 2.14576051e-02 8.31837058e-01 1.05508471e+00
-4.78100069e-02 4.32722479e-01 2.02811629e-01 -1.15575159e+00
-9.18448269e-01 -1.17176044e+00 -8.92269492e-01 -1.17210180e-01
4.52783734e-01 -9.41483498e-01 -4.78261709e-01 9.53884348e-02] | [7.0455780029296875, 3.921231746673584] |
da20550c-2d77-46fb-b0c2-10ee32df700a | a-domain-independent-agent-architecture-for | 2306.06272 | null | https://arxiv.org/abs/2306.06272v1 | https://arxiv.org/pdf/2306.06272v1.pdf | A Domain-Independent Agent Architecture for Adaptive Operation in Evolving Open Worlds | Model-based reasoning agents are ill-equipped to act in novel situations in which their model of the environment no longer sufficiently represents the world. We propose HYDRA - a framework for designing model-based agents operating in mixed discrete-continuous worlds, that can autonomously detect when the environment has evolved from its canonical setup, understand how it has evolved, and adapt the agents' models to perform effectively. HYDRA is based upon PDDL+, a rich modeling language for planning in mixed, discrete-continuous environments. It augments the planning module with visual reasoning, task selection, and action execution modules for closed-loop interaction with complex environments. HYDRA implements a novel meta-reasoning process that enables the agent to monitor its own behavior from a variety of aspects. The process employs a diverse set of computational methods to maintain expectations about the agent's own behavior in an environment. Divergences from those expectations are useful in detecting when the environment has evolved and identifying opportunities to adapt the underlying models. HYDRA builds upon ideas from diagnosis and repair and uses a heuristics-guided search over model changes such that they become competent in novel conditions. The HYDRA framework has been used to implement novelty-aware agents for three diverse domains - CartPole++ (a higher dimension variant of a classic control problem), Science Birds (an IJCAI competition problem), and PogoStick (a specific problem domain in Minecraft). We report empirical observations from these domains to demonstrate the efficacy of various components in the novelty meta-reasoning process. | ['Johan de Kleer', 'Jacob Le', 'Sookyung Kim', 'Sachin Grover', 'Roni Stern', 'Wiktor Piotrowski', 'Shiwali Mohan'] | 2023-06-09 | null | null | null | null | ['visual-reasoning', 'visual-reasoning'] | ['computer-vision', 'reasoning'] | [-1.74296260e-01 3.54982674e-01 2.51187623e-01 -1.52144143e-02
-6.46797102e-03 -5.94914258e-01 1.01138687e+00 2.78450429e-01
-3.96951765e-01 6.45615876e-01 2.33329535e-02 -9.73666832e-02
-3.01368833e-01 -7.82519102e-01 -5.13002455e-01 -4.74245667e-01
-6.36350334e-01 1.16118717e+00 5.31751335e-01 -7.93366015e-01
4.21655625e-01 4.82429236e-01 -1.82477570e+00 1.12175405e-01
5.40225744e-01 1.26148894e-01 4.67836589e-01 9.44088280e-01
2.18132168e-01 8.76287341e-01 -5.70762396e-01 2.84157872e-01
5.11956990e-01 -3.40865195e-01 -1.03010881e+00 2.44058415e-01
-5.68103433e-01 1.49972379e-01 8.02837908e-02 8.45832288e-01
2.97309667e-01 5.37726223e-01 4.92293864e-01 -1.47513688e+00
-1.53175011e-01 5.03334224e-01 4.84234244e-02 1.18111685e-01
8.53198946e-01 1.02532327e+00 3.14841121e-01 -3.39937866e-01
9.68048096e-01 1.57188034e+00 4.55191165e-01 8.21845353e-01
-1.24628377e+00 -6.43040240e-02 4.06502455e-01 1.79641128e-01
-1.26384127e+00 -4.36264575e-01 4.22481120e-01 -5.16264021e-01
1.60000968e+00 4.13409263e-01 1.06291902e+00 9.14464056e-01
6.41085148e-01 6.56014323e-01 1.12567472e+00 -4.68698472e-01
1.05486226e+00 7.04457536e-02 -6.30165160e-01 6.34545743e-01
-3.95888798e-02 5.74855864e-01 -6.93426013e-01 -5.27797759e-01
4.98412699e-01 -3.39516848e-01 5.84062040e-02 -7.23009288e-01
-1.26903081e+00 3.68268967e-01 1.61389709e-01 3.06870133e-01
-7.43432462e-01 1.52509123e-01 2.67730772e-01 6.81410611e-01
-1.80644453e-01 1.40832150e+00 -6.93357110e-01 -4.89456385e-01
-2.45918453e-01 9.72187698e-01 1.02375209e+00 8.00621212e-01
6.31721258e-01 1.35589570e-01 8.87348354e-02 1.54843256e-01
4.38005894e-01 -4.72342670e-02 7.62875378e-01 -1.37234628e+00
-2.16095727e-02 8.12816143e-01 5.32309353e-01 -7.32151628e-01
-7.44152665e-01 -1.59377947e-01 7.87692443e-02 1.10671973e+00
-5.95011935e-02 -2.35042781e-01 -8.33446324e-01 1.58631277e+00
7.32764244e-01 -9.20928568e-02 6.65915489e-01 6.94002867e-01
-1.52758481e-02 5.47838271e-01 -1.29027180e-02 -1.52025372e-01
9.87272322e-01 -1.04454207e+00 -2.44155198e-01 -6.51918471e-01
7.36817360e-01 -1.89426333e-01 9.42685068e-01 5.42422950e-01
-1.37336910e+00 -3.88361067e-01 -1.15214074e+00 6.89391553e-01
-5.43184161e-01 -9.78980720e-01 6.77730262e-01 1.68377370e-01
-1.33668685e+00 7.41982758e-01 -1.03859818e+00 -8.93166304e-01
-2.28602543e-01 3.01980913e-01 -1.62456304e-01 2.78823555e-01
-9.19149935e-01 1.34536231e+00 8.79743874e-01 -2.51576036e-01
-1.44317567e+00 -2.30649248e-01 -8.98663282e-01 -1.22927971e-01
6.62201345e-01 -1.01898885e+00 1.77462089e+00 -9.21916902e-01
-1.83762240e+00 5.66008151e-01 3.40045601e-01 -6.21952474e-01
6.93356335e-01 4.26984936e-01 -3.77169877e-01 -3.66751581e-01
2.47234970e-01 4.97013927e-01 6.02148890e-01 -1.34088540e+00
-9.47323143e-01 -3.84041369e-01 3.57546300e-01 7.96767473e-01
5.49094081e-01 -5.43508977e-02 -1.75042972e-02 -2.35869870e-01
6.83208704e-02 -1.09352624e+00 -8.98334742e-01 -1.89731166e-01
-5.39382920e-04 2.16530226e-02 5.40191770e-01 7.01010134e-03
7.10029364e-01 -1.88812113e+00 4.78133410e-01 3.84209603e-01
-7.45719448e-02 -2.27098502e-02 -1.93575889e-01 9.95463789e-01
2.33797133e-01 1.16214812e-01 -2.64736488e-02 1.20065985e-02
3.16531122e-01 3.98621380e-01 8.85547101e-02 5.58256358e-03
-4.44857478e-02 4.38544184e-01 -1.12879908e+00 -8.35033655e-02
1.50513262e-01 -1.10478334e-01 -6.17316663e-01 3.39020818e-01
-8.90774250e-01 5.63499808e-01 -6.27177715e-01 5.45781493e-01
1.49979293e-01 2.25419909e-01 4.62167531e-01 7.90293038e-01
-4.95217085e-01 -4.49377950e-03 -1.34622085e+00 1.66954863e+00
-3.59704822e-01 1.87584102e-01 2.48690292e-01 -5.88520706e-01
7.53251076e-01 2.14620069e-01 1.50644377e-01 -7.60500431e-01
4.02722396e-02 3.05510033e-02 2.76691198e-01 -8.95613015e-01
4.57636386e-01 -1.31340757e-01 -2.34805778e-01 5.12795329e-01
-2.75919467e-01 -7.59287536e-01 4.95282322e-01 -1.79326862e-01
1.63892865e+00 2.54911721e-01 6.26757026e-01 -2.83876270e-01
1.44587055e-01 7.59762168e-01 6.65547967e-01 1.24631155e+00
-3.68757695e-01 1.58927985e-03 2.33224317e-01 -1.04458821e+00
-7.92601883e-01 -9.53497767e-01 3.07655305e-01 1.16578722e+00
4.91898328e-01 -4.95676070e-01 -4.52228993e-01 -3.34231168e-01
-1.17613852e-01 1.35072386e+00 -8.83847654e-01 -4.69206631e-01
-4.07797277e-01 -5.44754982e-01 1.09552070e-01 1.19200595e-01
4.48870212e-01 -1.57926607e+00 -1.65634084e+00 5.17984867e-01
3.18480819e-01 -3.78452063e-01 1.45835206e-01 5.78292310e-01
-6.47900701e-01 -1.07501209e+00 1.21276170e-01 -5.27957559e-01
5.89105725e-01 -9.84855890e-02 9.96263921e-01 9.37902629e-02
-2.30894744e-01 6.66366220e-01 -2.98534960e-01 -6.34468019e-01
-1.02790296e+00 -2.73418725e-01 3.68388087e-01 -6.99784338e-01
1.90853029e-02 -5.84968507e-01 -9.33799520e-02 4.29545611e-01
-8.55079353e-01 3.55638117e-01 2.64792770e-01 8.47704351e-01
2.60656029e-01 8.60664606e-01 8.96071866e-02 -5.46155810e-01
1.05206430e+00 -4.61619347e-01 -6.48112714e-01 4.17194277e-01
-6.73927009e-01 2.96249241e-01 4.82485324e-01 -5.41276932e-01
-1.11849725e+00 3.31839882e-02 3.57317775e-01 6.67324848e-03
-3.54105473e-01 6.76411986e-01 -1.77312762e-01 7.23011866e-02
1.06782341e+00 2.90977955e-01 3.73936817e-02 -2.08984107e-01
1.49443626e-01 8.84278193e-02 4.86156791e-01 -9.74718988e-01
8.07454169e-01 1.62764102e-01 -3.22254598e-01 -4.00154769e-01
-1.63472760e-02 -3.63187045e-02 -4.10005927e-01 -3.15570742e-01
5.04132032e-01 -5.72769880e-01 -8.94959867e-01 5.60404956e-01
-8.23063374e-01 -1.03719032e+00 -7.49946654e-01 9.86076072e-02
-1.03033531e+00 -1.47142202e-01 -8.13152567e-02 -9.95002747e-01
1.44132093e-01 -1.24725199e+00 5.81646740e-01 5.78228116e-01
-5.28777003e-01 -8.96265149e-01 7.38240719e-01 -1.47992959e-02
7.03759968e-01 4.82163519e-01 1.09164691e+00 -8.68107736e-01
-3.08159441e-01 7.56688192e-02 7.97352493e-01 -4.94741112e-01
-8.16111937e-02 4.63779829e-02 -5.46642065e-01 -4.59785879e-01
6.31390810e-02 -2.39540324e-01 -6.95028866e-04 1.30399261e-02
4.91345674e-01 -5.34514606e-01 -5.72246552e-01 1.22866690e-01
1.01588917e+00 8.66081774e-01 4.89426285e-01 1.38387418e+00
-2.20405161e-01 5.35557628e-01 9.07105207e-01 7.80464590e-01
5.60487926e-01 8.27280104e-01 8.88834000e-01 1.24647647e-01
4.54794139e-01 -5.13124764e-02 4.93807912e-01 3.16322148e-02
-9.84376483e-03 -1.37549222e-01 -1.31578314e+00 5.34079254e-01
-2.35009766e+00 -1.14232516e+00 5.84291697e-01 2.08710790e+00
8.43392253e-01 4.90881413e-01 3.35763961e-01 -3.07847202e-01
4.65363085e-01 -1.55811161e-01 -1.01735806e+00 -8.19349527e-01
2.51272112e-01 -1.84535399e-01 3.83864343e-02 5.44063926e-01
-7.96376109e-01 1.10140038e+00 6.72691202e+00 1.39624834e-01
-7.03849256e-01 -2.07186982e-01 1.08685657e-01 -1.27434984e-01
-1.00821644e-01 3.18001151e-01 -1.52439296e-01 1.56846344e-01
8.27445090e-01 -6.49819076e-01 8.86278868e-01 1.16779852e+00
2.75416344e-01 -5.24370670e-01 -1.31151211e+00 3.54452759e-01
-2.37968028e-01 -1.35984516e+00 -2.87779391e-01 -9.39865261e-02
6.18814230e-01 1.52911931e-01 1.23852707e-01 6.82916701e-01
1.08870685e+00 -8.88812780e-01 1.22669578e+00 6.02767408e-01
-1.43185675e-01 -7.34658718e-01 4.90801662e-01 9.77977097e-01
-9.48493421e-01 -5.49153209e-01 -1.51031256e-01 -6.63814664e-01
1.03539079e-01 -3.95188361e-01 -1.52900827e+00 2.79380202e-01
8.57161641e-01 7.69250542e-02 -5.56621790e-01 1.16992605e+00
-3.16607282e-02 -1.42851949e-01 -3.21316004e-01 -4.70142141e-02
2.68010587e-01 8.48604366e-02 1.17832494e+00 7.06777036e-01
1.50055245e-01 8.82162154e-02 7.00284243e-01 8.65049422e-01
8.04516435e-01 -3.47878605e-01 -8.35491300e-01 1.52438626e-01
5.90820611e-01 6.89528644e-01 -7.58721530e-01 -2.41657913e-01
2.18651876e-01 6.62939012e-01 1.72611058e-01 3.48039895e-01
-4.61700737e-01 -7.28295930e-03 8.94811690e-01 4.26099822e-02
-5.38110659e-02 -2.73221642e-01 1.80688888e-01 -9.24158394e-01
-2.92727947e-01 -1.49661279e+00 3.22149336e-01 -9.85556424e-01
-8.33357155e-01 6.70431435e-01 2.86434323e-01 -9.56178546e-01
-7.35920131e-01 -1.25982985e-01 -7.87993908e-01 4.97808576e-01
-9.53098476e-01 -7.80453742e-01 -2.59096652e-01 4.87550497e-01
9.04535234e-01 -5.06693244e-01 1.05582893e+00 -7.78636634e-01
-5.79803348e-01 -2.06156984e-01 -3.05661447e-02 -6.91862702e-01
2.49213934e-01 -1.25509846e+00 7.97273219e-01 7.82256067e-01
-3.28582406e-01 5.79903603e-01 1.39078856e+00 -8.78198087e-01
-1.50455809e+00 -8.48642826e-01 1.84649944e-01 -3.38471204e-01
5.75784147e-01 -1.84267029e-01 -8.00116479e-01 7.69570947e-01
2.37173542e-01 -4.98043388e-01 2.03811988e-01 -1.31521612e-01
-2.41176109e-04 2.13279650e-01 -1.55501127e+00 1.29651022e+00
1.04338300e+00 3.50175761e-02 -9.16194618e-01 4.34349388e-01
5.72489023e-01 -6.35281622e-01 -4.23635066e-01 2.51208276e-01
3.97005290e-01 -1.24234176e+00 6.97432160e-01 -8.89250457e-01
-2.12058023e-01 -6.65534556e-01 -1.61795452e-01 -1.79962611e+00
-6.28528655e-01 -1.05773342e+00 2.99773384e-02 6.16786242e-01
3.19506764e-01 -9.00737822e-01 4.87220198e-01 1.10918164e+00
-1.80226311e-01 -4.72711354e-01 -8.67071688e-01 -7.78352499e-01
-3.37288946e-01 -3.33945215e-01 9.93671775e-01 8.36260915e-01
4.58613604e-01 1.42374064e-03 9.36511382e-02 3.51607382e-01
2.99874455e-01 -1.66017219e-01 1.06033301e+00 -1.16931045e+00
-7.15774894e-01 -4.62565809e-01 -4.71662849e-01 -2.67122507e-01
1.12246096e-01 -4.85321045e-01 4.62890983e-01 -1.51515841e+00
-7.17867464e-02 -5.10748148e-01 4.77375537e-02 8.00563514e-01
4.08652216e-01 -8.47416639e-01 4.76765931e-01 3.12567562e-01
-8.42985570e-01 4.34673041e-01 9.19180691e-01 -3.02819699e-01
-7.85249829e-01 6.64496049e-02 -5.54940104e-01 1.08723497e+00
9.54979718e-01 -5.34855664e-01 -5.96644938e-01 -3.97990137e-01
5.99215686e-01 2.35444784e-01 1.39098600e-01 -1.59250677e+00
5.10404468e-01 -8.65552604e-01 2.30910227e-01 1.24281123e-02
3.23881924e-01 -9.65963185e-01 7.79937863e-01 1.09624183e+00
-5.36615193e-01 6.76679790e-01 4.83880728e-01 6.22991264e-01
1.82045922e-01 -3.02522510e-01 5.30617595e-01 -6.63203418e-01
-1.34397721e+00 -2.00984791e-01 -1.30724061e+00 -8.52613524e-02
1.66751289e+00 -5.11505425e-01 -4.40374196e-01 -2.12827504e-01
-1.05761230e+00 7.40193725e-01 1.21512699e+00 5.66421628e-01
5.31415761e-01 -8.75925243e-01 -4.25205648e-01 3.67124349e-01
3.06362242e-01 -1.48710227e-02 6.75572902e-02 4.03739214e-01
-7.22158730e-01 -2.13881686e-01 -7.43342578e-01 -3.36144477e-01
-1.02320647e+00 7.16977417e-01 7.92458832e-01 -3.18639100e-01
-6.90571189e-01 7.24512994e-01 9.30539370e-02 -8.33867610e-01
1.66273609e-01 -2.75578648e-01 -1.49102822e-01 -5.08022368e-01
6.16564631e-01 3.05354327e-01 -9.42008346e-02 -1.80056065e-01
-5.44533610e-01 7.17108101e-02 8.95330030e-03 -5.49889624e-01
1.44181168e+00 -1.53301969e-01 -2.09465884e-02 5.74622273e-01
1.53046355e-01 -5.02474725e-01 -1.45839393e+00 -5.98657988e-02
2.78237581e-01 -4.10481334e-01 -2.55344391e-01 -1.22572267e+00
-1.68769047e-01 5.51595241e-02 5.16972601e-01 4.16695744e-01
9.88240540e-01 -1.15508728e-01 -2.74692606e-02 9.52372372e-01
1.01815999e+00 -1.42783058e+00 2.78176069e-01 7.67198741e-01
1.22080112e+00 -8.36485267e-01 -4.30853944e-03 4.09318209e-01
-9.22134757e-01 1.04962099e+00 9.56674039e-01 1.61172897e-01
1.68225780e-01 4.42414910e-01 5.83291873e-02 -5.98712981e-01
-1.44850028e+00 -9.10419077e-02 -4.30327296e-01 1.18247044e+00
-6.73858762e-01 7.87507519e-02 4.58329141e-01 1.80129662e-01
-2.37889916e-01 -1.88753024e-01 9.09917772e-01 1.57528138e+00
-7.22498655e-01 -9.25633371e-01 -6.26048386e-01 -1.38291689e-02
3.81677985e-01 4.64905381e-01 -6.54835582e-01 9.48090076e-01
2.34729260e-01 1.00236511e+00 -1.11083321e-01 -3.55661631e-01
5.60657442e-01 9.66484845e-02 3.95764560e-01 -9.66753423e-01
-9.05898929e-01 -2.81061947e-01 2.83828974e-01 -8.23953390e-01
-2.08212212e-01 -9.85305429e-01 -1.47833431e+00 -1.81256384e-01
1.78742692e-01 2.49398634e-01 6.62648380e-01 8.38592827e-01
4.44554061e-01 5.19902050e-01 4.41243052e-01 -1.19989526e+00
-5.57507694e-01 -5.12546837e-01 -3.81222129e-01 3.87170054e-02
1.60341188e-01 -8.39828849e-01 -1.68226406e-01 -1.78307578e-01] | [3.885042428970337, 1.581701636314392] |
b756eed6-baee-43f4-8b63-9d13b43df463 | user-embedding-for-scholarly-microblog | null | null | https://aclanthology.org/P16-2073 | https://aclanthology.org/P16-2073.pdf | User Embedding for Scholarly Microblog Recommendation | null | ['Yang Yu', 'Xinjie Zhou', 'Xiaojun Wan'] | 2016-08-01 | null | null | null | acl-2016-8 | ['collaborative-ranking'] | ['graphs'] | [-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] | [-7.306517124176025, 3.714883327484131] |
2d524ac1-520d-40bd-bf6f-992b6dfef562 | meeting-the-needs-of-low-resource-languages | 2302.07912 | null | https://arxiv.org/abs/2302.07912v1 | https://arxiv.org/pdf/2302.07912v1.pdf | Meeting the Needs of Low-Resource Languages: The Value of Automatic Alignments via Pretrained Models | Large multilingual models have inspired a new class of word alignment methods, which work well for the model's pretraining languages. However, the languages most in need of automatic alignment are low-resource and, thus, not typically included in the pretraining data. In this work, we ask: How do modern aligners perform on unseen languages, and are they better than traditional methods? We contribute gold-standard alignments for Bribri--Spanish, Guarani--Spanish, Quechua--Spanish, and Shipibo-Konibo--Spanish. With these, we evaluate state-of-the-art aligners with and without model adaptation to the target language. Finally, we also evaluate the resulting alignments extrinsically through two downstream tasks: named entity recognition and part-of-speech tagging. We find that although transformer-based methods generally outperform traditional models, the two classes of approach remain competitive with each other. | ['Katharina Kann', 'Rolando Coto-Solano', 'Gustavo A. Giménez-Lugo', 'John E. Ortega', 'Luis Chiruzzo', 'Arturo Oncevay', 'Arya D. McCarthy', 'Abteen Ebrahimi'] | 2023-02-15 | null | null | null | null | ['word-alignment', 'part-of-speech-tagging'] | ['natural-language-processing', 'natural-language-processing'] | [-1.60356462e-01 1.52109578e-01 -2.93387055e-01 -6.39481664e-01
-1.27441335e+00 -9.60477531e-01 5.28645158e-01 1.15013950e-01
-8.61033618e-01 1.02413464e+00 3.03358287e-01 -6.41647398e-01
4.75878537e-01 -4.92208421e-01 -6.30512714e-01 -4.06898737e-01
2.38728568e-01 1.19251132e+00 6.64203018e-02 -6.09169185e-01
-7.57817551e-02 1.53402716e-01 -7.19226182e-01 2.58748621e-01
9.70240474e-01 1.21004649e-01 8.32312182e-02 3.34120721e-01
-1.51095629e-01 3.26490223e-01 -5.49469709e-01 -9.65821028e-01
1.14191882e-01 -5.06742179e-01 -1.01432931e+00 -5.79240203e-01
6.85078561e-01 1.21629201e-01 -5.70675172e-02 1.11296773e+00
4.07191694e-01 -1.40097514e-01 5.85352004e-01 -8.24982941e-01
-5.58265388e-01 1.21337271e+00 -4.57930565e-01 4.82074529e-01
2.91222960e-01 -1.00662857e-01 1.40471780e+00 -9.36405122e-01
9.50827241e-01 1.19692719e+00 9.76191640e-01 6.26893222e-01
-1.22159886e+00 -9.09257770e-01 3.16392094e-01 -3.36347297e-02
-1.27685630e+00 -7.50699937e-01 3.79241675e-01 -3.59998763e-01
1.49957776e+00 1.33539215e-01 3.65000784e-01 1.27022839e+00
1.69974059e-01 7.16533005e-01 1.07432234e+00 -7.95401514e-01
-2.93884516e-01 5.14759980e-02 1.18783556e-01 4.90105778e-01
4.52774197e-01 5.25672100e-02 -5.86508811e-01 -8.72773826e-02
3.52494180e-01 -6.20867193e-01 -1.36462348e-02 4.74601388e-02
-1.55219042e+00 7.20793962e-01 1.32386135e-02 8.08894515e-01
-1.80428103e-01 -1.82778865e-01 3.45072359e-01 4.47095722e-01
7.57209241e-01 6.87493443e-01 -9.54601109e-01 -1.58395633e-01
-9.85287905e-01 2.44951189e-01 9.04829204e-01 1.26351142e+00
7.96241224e-01 8.13794285e-02 2.57695317e-01 1.07812405e+00
2.02597633e-01 7.53897548e-01 4.96506751e-01 -4.87579823e-01
1.04572427e+00 1.42766446e-01 1.09972186e-01 -3.84744078e-01
-3.92308712e-01 -2.58054137e-01 -4.56667125e-01 -2.52240747e-01
7.01393545e-01 -3.56521755e-01 -9.48261678e-01 2.10978007e+00
1.45452484e-01 -3.08622211e-01 3.40289831e-01 5.44250965e-01
4.69148725e-01 5.31693578e-01 3.84249806e-01 -1.05795301e-01
1.37684155e+00 -1.32919121e+00 -6.40625536e-01 -9.46130514e-01
9.10128713e-01 -1.30363560e+00 8.25257540e-01 -9.15741269e-03
-1.17326117e+00 -5.55005670e-01 -8.10014069e-01 -4.21699733e-02
-4.67606843e-01 1.15529247e-01 5.99062324e-01 6.07464492e-01
-1.20304728e+00 4.28737670e-01 -1.01132798e+00 -8.13310921e-01
-1.95376128e-01 4.35363293e-01 -7.69797206e-01 7.26303011e-02
-1.26869595e+00 1.50603557e+00 5.13089418e-01 -1.18445992e-01
-5.36216915e-01 -3.89023811e-01 -9.41359818e-01 -2.56190538e-01
-8.83859247e-02 -4.22086298e-01 1.58225870e+00 -1.18375897e+00
-1.21249914e+00 1.47928488e+00 -4.02239889e-01 -2.98777640e-01
1.28877863e-01 -4.41509336e-01 -6.74316168e-01 -3.63120079e-01
5.17566681e-01 7.23265111e-01 1.93497181e-01 -9.65296507e-01
-9.48973536e-01 -3.58312517e-01 -1.70755804e-01 3.32000136e-01
-9.57886428e-02 6.30155683e-01 -2.61278778e-01 -7.88488030e-01
5.53715751e-02 -1.13916600e+00 -4.13166791e-01 -9.13934469e-01
-4.27407950e-01 -1.22824371e-01 2.25386396e-01 -1.12144256e+00
1.15439618e+00 -2.04246926e+00 8.95946026e-02 7.69508407e-02
-2.90486008e-01 3.15669119e-01 -4.17422175e-01 6.21441424e-01
-3.76884818e-01 2.63988346e-01 -1.58935919e-01 -2.95796305e-01
-9.41113308e-02 3.76748234e-01 -8.64063799e-02 2.63090551e-01
3.87130857e-01 9.08754468e-01 -9.77542341e-01 -5.02417445e-01
-1.59663275e-01 1.23566031e-01 -5.85436583e-01 2.54996061e-01
-5.78242615e-02 6.19858086e-01 -2.54965901e-01 7.62130558e-01
4.35960978e-01 2.18696833e-01 6.40482664e-01 -1.59282535e-02
-3.10163677e-01 9.14362490e-01 -7.62922525e-01 1.78016138e+00
-4.79222715e-01 4.39757824e-01 1.54639170e-01 -8.94964874e-01
9.98746872e-01 4.19566989e-01 3.22984666e-01 -6.59915030e-01
-4.01541293e-02 9.56197500e-01 5.47753692e-01 -1.31927192e-01
7.22658753e-01 -3.30520004e-01 -3.93955141e-01 3.19464058e-01
4.37212765e-01 -3.84973101e-02 4.41474766e-01 -2.79969871e-01
1.02019167e+00 4.65370506e-01 7.47293055e-01 -4.79664922e-01
2.99026728e-01 4.29988027e-01 8.63248289e-01 4.78729248e-01
-1.20700382e-01 5.37402809e-01 -3.64683233e-02 -4.12786275e-01
-1.40587056e+00 -1.00988472e+00 -1.35253981e-01 1.36307979e+00
-1.42941222e-01 -4.24298406e-01 -8.42379212e-01 -8.05385768e-01
-3.85608286e-01 8.41643393e-01 -2.42242798e-01 2.85275817e-01
-1.24733651e+00 -7.22721696e-01 9.22596276e-01 4.95726913e-01
-1.22181565e-01 -1.22106159e+00 -3.31195742e-02 6.74510658e-01
-6.47641003e-01 -1.26294732e+00 -6.92011893e-01 5.36068797e-01
-7.97190011e-01 -8.59296322e-01 -8.09507549e-01 -1.28974223e+00
5.04604042e-01 -1.07213974e-01 1.73402834e+00 -1.22603975e-01
2.86237329e-01 -1.09374104e-02 -4.27548677e-01 -3.75021517e-01
-8.23385179e-01 7.54428029e-01 6.11739308e-02 -5.22442043e-01
8.71506512e-01 -4.99805778e-01 -6.79228306e-02 3.96829665e-01
-3.60498637e-01 -1.18233688e-01 7.41987109e-01 8.79588783e-01
5.13581514e-01 -7.56442130e-01 3.31817865e-01 -1.11584806e+00
2.15084553e-01 -4.00150418e-01 -4.53960776e-01 3.78701359e-01
-3.78808320e-01 4.48688194e-02 6.69856369e-01 -3.97939771e-01
-9.76146400e-01 1.54300705e-02 -6.07287169e-01 1.64364621e-01
-3.84048074e-01 4.40843493e-01 -4.61188495e-01 2.21475124e-01
6.57830238e-01 -2.97948897e-01 -5.47803760e-01 -7.01636314e-01
3.46234024e-01 7.02436924e-01 8.14130545e-01 -7.41910160e-01
8.52880120e-01 6.94661885e-02 -5.88998079e-01 -5.24315298e-01
-9.41377282e-01 -5.76725781e-01 -9.61524010e-01 3.26329380e-01
1.12796462e+00 -1.24271083e+00 2.68333316e-01 4.94669169e-01
-1.52708137e+00 -5.12651861e-01 -1.18838966e-01 6.28514230e-01
-3.38381201e-01 2.68827647e-01 -9.18506086e-01 -3.26753139e-01
-4.98338044e-01 -1.19910586e+00 1.09373009e+00 1.54669657e-01
-7.31987715e-01 -1.22094595e+00 6.13907099e-01 2.82965243e-01
2.98334450e-01 -1.32497415e-01 9.60860729e-01 -1.34541512e+00
-1.11630231e-01 9.39131249e-03 1.14357270e-01 2.73551464e-01
7.04208240e-02 -8.57291296e-02 -6.47967219e-01 -3.49222869e-01
-4.08831090e-01 -1.06083289e-01 3.52296114e-01 8.53945538e-02
1.66388601e-01 -1.92497253e-01 -5.47592402e-01 6.54823720e-01
1.22150886e+00 2.72018552e-01 4.67927843e-01 7.87661612e-01
6.14668906e-01 5.40910125e-01 8.28384638e-01 -1.99656785e-01
7.21224427e-01 8.09323668e-01 -2.57985368e-02 -3.36639553e-01
-1.33793116e-01 -3.65590453e-01 6.96857750e-01 1.67267084e+00
-1.41611576e-01 -3.61417830e-01 -1.31271100e+00 9.71065104e-01
-1.68152261e+00 -7.72982180e-01 -3.42907906e-01 2.04732370e+00
1.24101591e+00 5.81574300e-03 -6.00797310e-02 -4.72155064e-01
7.47418344e-01 1.64835423e-01 9.07475948e-02 -5.56444287e-01
-4.02195990e-01 7.52676249e-01 6.00999236e-01 6.48189485e-01
-1.27721488e+00 1.65401626e+00 6.94253874e+00 6.27430022e-01
-1.02521920e+00 3.31655353e-01 5.42899549e-01 4.52788681e-01
-3.93485874e-01 5.29980659e-01 -1.35102582e+00 2.74130523e-01
1.33103359e+00 1.27677426e-01 2.70525157e-01 8.44358623e-01
-2.73702651e-01 1.81836948e-01 -1.42411017e+00 6.60745025e-01
1.12424769e-01 -7.76915729e-01 -9.30328369e-02 -8.57303888e-02
9.15623486e-01 7.08017588e-01 -4.54291523e-01 4.94583160e-01
8.76911581e-01 -9.35765922e-01 8.89087141e-01 8.37467238e-02
7.30050325e-01 -5.15226960e-01 9.59321260e-01 1.94989502e-01
-1.06488526e+00 5.29395819e-01 -4.83074397e-01 2.39943311e-01
4.93467361e-01 3.48109066e-01 -6.02856874e-01 7.03236699e-01
6.02982879e-01 5.00055790e-01 -5.46771586e-01 9.28178430e-01
-5.01736879e-01 9.31535959e-01 -2.96347916e-01 1.11930601e-01
4.30287898e-01 -3.97752702e-01 4.94348913e-01 1.67899299e+00
5.37132978e-01 -2.70426840e-01 3.20159882e-01 1.50338933e-01
-2.53141839e-02 4.44903374e-01 -6.65757179e-01 -1.58025175e-01
5.20214260e-01 1.13411915e+00 -4.35004234e-01 -3.88618261e-01
-6.29823148e-01 9.48101699e-01 7.10459054e-01 2.14034915e-01
-6.58456206e-01 -3.39519501e-01 8.23579848e-01 -4.47597690e-02
2.30891794e-01 -3.51479918e-01 -4.80693541e-02 -1.42687142e+00
-2.20469609e-02 -1.50773704e+00 5.31018376e-01 -5.67445040e-01
-1.43774307e+00 9.08493102e-01 -3.95786539e-02 -9.88925278e-01
-5.85923076e-01 -8.25819492e-01 -4.27040875e-01 1.09651637e+00
-1.53270388e+00 -1.47575510e+00 1.45817041e-01 2.46265456e-01
5.17680466e-01 -5.05199552e-01 1.26927483e+00 5.97813845e-01
-3.67248684e-01 6.68212235e-01 2.47974619e-01 7.26234138e-01
1.30859184e+00 -1.23904824e+00 1.08425105e+00 1.12572718e+00
6.86133146e-01 5.85248828e-01 6.32397890e-01 -6.30964041e-01
-7.37089992e-01 -8.56255889e-01 1.72734916e+00 -6.31302416e-01
1.03695202e+00 -3.34346801e-01 -7.89314330e-01 1.27264643e+00
7.00228810e-01 -2.61471450e-01 8.70766997e-01 6.77488208e-01
-6.05652511e-01 8.11434463e-02 -6.26595974e-01 6.65213048e-01
1.22826195e+00 -4.83475119e-01 -9.46531475e-01 3.78800780e-01
5.73623180e-01 -5.10935664e-01 -8.64599168e-01 3.13498676e-01
4.37948018e-01 -6.09244645e-01 7.44961083e-01 -1.13225937e+00
2.39344642e-01 -5.48156016e-02 -2.87217170e-01 -1.74955618e+00
-4.76482511e-01 -6.63044274e-01 6.59268498e-01 1.55351472e+00
9.94737267e-01 -6.46395087e-01 6.12744331e-01 -3.85248624e-02
-4.60671008e-01 -8.16746578e-02 -1.06449807e+00 -9.01959300e-01
6.86360598e-01 -2.20063657e-01 5.79980254e-01 1.38236010e+00
4.20267321e-03 7.24220991e-01 -2.48990908e-01 1.01992354e-01
3.34614277e-01 -1.02068938e-01 8.49836290e-01 -1.02545369e+00
-4.96421725e-01 -4.13311005e-01 -2.88616329e-01 -9.00744855e-01
5.52174926e-01 -1.14076388e+00 3.16504240e-01 -1.37755406e+00
6.64327890e-02 -7.86644995e-01 -1.90540701e-01 9.30662811e-01
-5.02055705e-01 2.40458623e-01 7.54589066e-02 2.44910836e-01
-3.99878442e-01 -1.19250955e-03 6.96412921e-01 -1.06978752e-01
4.68624756e-02 -1.75830960e-01 -5.72631419e-01 7.61775911e-01
7.82449961e-01 -8.70033324e-01 2.31151998e-01 -9.60879505e-01
2.88877934e-01 -1.49798542e-01 -3.54301184e-01 -8.44736934e-01
-9.96571928e-02 -2.00838819e-01 7.07237944e-02 -3.77317369e-01
5.52211292e-02 -5.96983612e-01 2.05115333e-01 2.54722863e-01
-8.29634815e-03 6.86054528e-01 2.29815871e-01 -1.79006770e-01
-4.92803901e-01 -4.92734700e-01 7.80422509e-01 -3.25866967e-01
-6.06008470e-01 1.17702737e-01 -3.98759812e-01 6.38421297e-01
6.43306434e-01 1.50418237e-01 -2.50689805e-01 -1.65219635e-01
-6.12933457e-01 -1.14552900e-02 5.15746772e-01 5.78565538e-01
-3.00342143e-01 -1.30876637e+00 -1.06006312e+00 7.25791510e-03
2.61860430e-01 -1.57718927e-01 -4.07020420e-01 8.61541569e-01
-6.89877152e-01 4.35799867e-01 -3.15105140e-01 -3.99745435e-01
-1.21272457e+00 2.98278898e-01 2.08355337e-01 -8.86997998e-01
-1.77109912e-01 8.53950679e-01 1.68949872e-01 -1.11238599e+00
-1.57347485e-01 -1.42950818e-01 -5.01604402e-04 4.82295230e-02
5.96496984e-02 -1.94012061e-01 3.37004751e-01 -1.07630146e+00
-6.08723581e-01 4.82120275e-01 -2.15066433e-01 -3.05703521e-01
1.25703406e+00 1.41872540e-01 -2.96373457e-01 3.58516574e-01
9.13932264e-01 5.89618802e-01 -4.13548291e-01 -1.48569882e-01
6.73100412e-01 -7.49350786e-02 -7.30330467e-01 -7.41080821e-01
-6.92823768e-01 8.40153337e-01 1.30209014e-01 -1.92414358e-01
7.24973202e-01 6.97288439e-02 7.60390937e-01 4.08978015e-01
6.09943688e-01 -1.10618925e+00 -5.18818498e-01 1.08163416e+00
3.70879143e-01 -1.12793577e+00 -2.65595675e-01 -3.54929894e-01
-4.81645405e-01 8.85438323e-01 6.45652950e-01 8.71487632e-02
3.93432468e-01 4.65577811e-01 7.38547862e-01 2.09107041e-01
-5.70414126e-01 -3.69432747e-01 2.62359381e-01 6.62965417e-01
1.11918604e+00 9.93015617e-02 -6.29114449e-01 5.91849267e-01
-8.21789145e-01 -6.54456437e-01 1.70812830e-01 8.60984802e-01
-2.48234943e-01 -1.81351840e+00 -3.65922213e-01 9.23501924e-02
-9.05625880e-01 -6.46519363e-01 -5.13319850e-01 1.21257567e+00
8.78711566e-02 8.01956177e-01 9.24249440e-02 -1.01688601e-01
4.30066466e-01 4.89746004e-01 3.95285845e-01 -9.60166037e-01
-9.15645421e-01 3.63139868e-01 7.37518013e-01 -1.53072894e-01
-4.56280202e-01 -8.97846043e-01 -1.02932966e+00 -9.33077931e-02
-4.91268128e-01 5.96146584e-01 5.62262774e-01 1.10929179e+00
-3.68113406e-02 1.65665746e-02 2.19734386e-01 -6.85805321e-01
-6.02219343e-01 -1.23609531e+00 -1.84147552e-01 3.80804598e-01
-1.64524630e-01 -2.65458912e-01 -1.74233884e-01 7.44986534e-02] | [10.644481658935547, 9.941319465637207] |
cf67a9c6-57d9-4da9-af4b-68698197e4f7 | towards-real-time-multi-object-tracking | 1909.12605 | null | https://arxiv.org/abs/1909.12605v2 | https://arxiv.org/pdf/1909.12605v2.pdf | Towards Real-Time Multi-Object Tracking | Modern multiple object tracking (MOT) systems usually follow the \emph{tracking-by-detection} paradigm. It has 1) a detection model for target localization and 2) an appearance embedding model for data association. Having the two models separately executed might lead to efficiency problems, as the running time is simply a sum of the two steps without investigating potential structures that can be shared between them. Existing research efforts on real-time MOT usually focus on the association step, so they are essentially real-time association methods but not real-time MOT system. In this paper, we propose an MOT system that allows target detection and appearance embedding to be learned in a shared model. Specifically, we incorporate the appearance embedding model into a single-shot detector, such that the model can simultaneously output detections and the corresponding embeddings. We further propose a simple and fast association method that works in conjunction with the joint model. In both components the computation cost is significantly reduced compared with former MOT systems, resulting in a neat and fast baseline for future follow-ups on real-time MOT algorithm design. To our knowledge, this work reports the first (near) real-time MOT system, with a running speed of 22 to 40 FPS depending on the input resolution. Meanwhile, its tracking accuracy is comparable to the state-of-the-art trackers embodying separate detection and embedding (SDE) learning ($64.4\%$ MOTA \vs $66.1\%$ MOTA on MOT-16 challenge). Code and models are available at \url{https://github.com/Zhongdao/Towards-Realtime-MOT}. | ['Ya-Li Li', 'Liang Zheng', 'Shengjin Wang', 'Zhongdao Wang', 'Yixuan Liu'] | 2019-09-27 | null | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/1292_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123560103.pdf | eccv-2020-8 | ['real-time-multi-object-tracking'] | ['computer-vision'] | [-2.74825264e-02 -2.67126530e-01 -1.51496753e-01 7.18736500e-02
-6.98536158e-01 -5.68756104e-01 5.82485914e-01 -7.44736101e-03
-5.39628685e-01 2.59198248e-01 -4.60194647e-01 -2.77011126e-01
2.81074375e-01 -5.22005558e-01 -7.90020943e-01 -7.70916283e-01
-1.77454829e-01 6.07548654e-01 7.95839190e-01 6.29823208e-02
-2.19668463e-01 1.53457806e-01 -1.74674165e+00 -2.27019340e-01
3.55437279e-01 9.28058326e-01 3.00603211e-01 1.00923026e+00
1.73885345e-01 5.59301138e-01 -5.86365938e-01 -2.40358233e-01
4.91020143e-01 -5.20804524e-02 -1.69539317e-01 -4.02581483e-01
9.40438688e-01 -4.29252207e-01 -5.73621929e-01 1.00125468e+00
6.18433893e-01 -1.58351839e-01 3.69626969e-01 -1.59525001e+00
-4.97802466e-01 3.84627223e-01 -8.39275539e-01 3.34978104e-01
1.02315336e-01 5.00188172e-01 9.50591028e-01 -7.27435112e-01
2.13718459e-01 1.22767794e+00 8.87090206e-01 7.64661372e-01
-1.40926218e+00 -9.83937562e-01 2.41613835e-01 2.14682743e-02
-1.48322332e+00 -6.18598521e-01 3.05605412e-01 -4.92311835e-01
8.08232963e-01 3.09192687e-01 7.88523197e-01 1.12639260e+00
2.62357533e-01 9.30330992e-01 8.14637840e-01 -1.69768453e-01
-4.74930257e-02 2.50844240e-01 2.74223000e-01 8.32156003e-01
5.43169618e-01 5.60516238e-01 -4.97447371e-01 -1.31808311e-01
6.61735296e-01 1.31555155e-01 -3.26497369e-02 -4.90892410e-01
-1.35259831e+00 5.75737596e-01 5.89055955e-01 1.46431416e-01
-1.72325835e-01 7.80401289e-01 2.42407084e-01 2.12483987e-01
1.90403283e-01 9.29117724e-02 -1.48916692e-01 -8.16877112e-02
-9.76450086e-01 1.56442538e-01 6.51561499e-01 1.13321424e+00
6.67587578e-01 8.79992247e-02 -1.84504777e-01 2.65792698e-01
7.17925906e-01 9.81526494e-01 9.36701372e-02 -5.77105045e-01
1.10064141e-01 5.54455757e-01 2.67433435e-01 -8.09655726e-01
-3.22523624e-01 -4.39919025e-01 -3.15235168e-01 4.86742556e-01
5.63790977e-01 -1.40976205e-01 -6.62070930e-01 1.96613562e+00
7.34403729e-01 6.67758226e-01 -2.15760097e-01 8.86637688e-01
7.93879509e-01 3.24983150e-01 1.40394136e-01 2.20359132e-01
1.73552024e+00 -1.09015656e+00 -7.64532328e-01 -3.87684196e-01
7.56876111e-01 -7.93953955e-01 6.67022705e-01 1.46604240e-01
-7.85914481e-01 -6.43156350e-01 -1.32452893e+00 -4.17237133e-02
-4.04807687e-01 3.68297905e-01 6.53486907e-01 7.77518451e-01
-1.32598102e+00 3.71704847e-01 -1.27633476e+00 -7.48350620e-01
3.14682364e-01 7.98969984e-01 -2.71030795e-03 1.04447491e-01
-7.51960874e-01 8.73489261e-01 1.26980484e-01 -3.01254652e-02
-1.06462824e+00 -5.04299700e-01 -6.94645524e-01 -2.37844571e-01
4.42076087e-01 -8.67811024e-01 1.29987860e+00 -4.75856990e-01
-1.23436880e+00 6.97434723e-01 -2.36092761e-01 -4.65545028e-01
4.36439008e-01 -4.89052624e-01 -4.84256893e-01 -2.17696533e-01
1.72650591e-01 9.26853180e-01 9.57168758e-01 -1.08447647e+00
-9.03598249e-01 -1.82930663e-01 1.14208631e-01 -7.24671036e-02
-5.43624282e-01 9.69048217e-02 -7.93371737e-01 -4.02486861e-01
-3.24692488e-01 -1.20392466e+00 1.76348127e-02 6.38136566e-01
-8.85529816e-02 -3.17563146e-01 1.40187967e+00 -3.51489186e-01
1.31840336e+00 -2.31651926e+00 -3.97575460e-02 -3.26053590e-01
4.56268758e-01 5.93077004e-01 -1.93988666e-01 2.17255637e-01
3.47402930e-01 -3.58888656e-01 2.14909703e-01 -7.87756562e-01
2.30734363e-01 -2.06469987e-02 -8.74798223e-02 8.70108247e-01
1.09679393e-01 9.93879080e-01 -1.08323467e+00 -5.43790996e-01
5.35508037e-01 6.65929854e-01 -3.48964959e-01 7.60637298e-02
-1.32296324e-01 2.76943594e-01 -2.68691301e-01 8.92546177e-01
6.26790762e-01 -3.44203621e-01 9.97173488e-02 -3.48799109e-01
-4.06414777e-01 2.02318996e-01 -1.28152573e+00 1.56520450e+00
-1.70071214e-01 7.93122053e-01 3.98365915e-01 -5.04765332e-01
7.69718885e-01 1.86767489e-01 7.40630388e-01 -5.35757482e-01
2.87850410e-01 1.82121113e-01 1.21065475e-01 -3.87136303e-02
7.66402125e-01 1.62409455e-01 1.07323518e-02 3.56609702e-01
3.99005134e-03 4.16478902e-01 1.68177351e-01 2.45960400e-01
1.41052711e+00 3.84269029e-01 2.83138789e-02 -1.68424666e-01
1.34005278e-01 2.24536926e-01 5.57492793e-01 8.42411757e-01
-6.86741471e-01 1.80448696e-01 -2.00205788e-01 -2.71838486e-01
-7.35124588e-01 -1.16304302e+00 -1.29022062e-01 1.08409274e+00
7.74724662e-01 -7.23740995e-01 -3.53818059e-01 -6.14598572e-01
2.90109068e-01 2.51176059e-01 -4.99544889e-01 -8.00771341e-02
-7.96781480e-01 -6.32916987e-01 7.54622340e-01 7.74136901e-01
1.22083440e-01 -7.97769785e-01 -9.20458734e-01 3.96822065e-01
1.64996684e-01 -1.13496637e+00 -6.03435099e-01 1.11479349e-01
-6.43460691e-01 -1.19951010e+00 -3.66719157e-01 -4.59924638e-01
4.68922138e-01 7.68365085e-01 8.17173541e-01 3.18948954e-01
-4.52228040e-01 5.83067596e-01 -1.92439213e-01 -5.96605122e-01
4.56257276e-02 -2.27908835e-01 5.25820553e-01 -8.35406184e-02
6.13659382e-01 -3.29078406e-01 -8.01570177e-01 4.90992993e-01
-6.66359603e-01 -1.20676188e-02 8.22501302e-01 6.55147254e-01
5.24722397e-01 -3.04346681e-01 -9.55945253e-03 -2.00100064e-01
-6.76396303e-04 -5.60581863e-01 -9.20631170e-01 1.19540989e-01
-4.92862493e-01 -1.69230238e-01 3.73771638e-01 -7.27704227e-01
-5.26117563e-01 4.33457851e-01 1.02300681e-01 -8.16084921e-01
1.83013454e-02 -1.76978722e-01 1.18602343e-01 -3.22234422e-01
6.06952190e-01 1.45550594e-01 7.16216266e-02 -5.42066872e-01
3.75253260e-01 4.69779521e-01 5.29391408e-01 -4.70228195e-01
1.21207750e+00 7.66111195e-01 -4.47025113e-02 -6.71462357e-01
-5.15476227e-01 -8.90085995e-01 -5.44972956e-01 -4.37029421e-01
7.93436110e-01 -1.20766854e+00 -9.15994525e-01 3.50924820e-01
-9.78777111e-01 -4.51100200e-01 -2.55406320e-01 7.31974959e-01
-3.00102532e-01 2.76276976e-01 -4.77263898e-01 -8.99977624e-01
-3.34663302e-01 -1.13782930e+00 1.48048663e+00 3.53645623e-01
-1.57173157e-01 -8.04893374e-01 2.40390107e-01 1.60993308e-01
5.20184100e-01 1.01171538e-01 -1.47955805e-01 -4.17402625e-01
-1.07620633e+00 -3.00450385e-01 -3.81845772e-01 -2.12263778e-01
5.04255630e-02 -5.63627947e-03 -1.12485111e+00 -9.79977846e-01
-3.00661832e-01 -1.20191991e-01 1.03409672e+00 3.68556648e-01
5.51231921e-01 -2.84609711e-03 -1.05715346e+00 5.72508037e-01
1.37117124e+00 3.36204842e-03 2.71612912e-01 3.46411020e-01
8.81563067e-01 1.25473127e-01 8.73860478e-01 3.94357622e-01
5.35609603e-01 1.26867902e+00 6.28119767e-01 -1.08658694e-01
-5.70178151e-01 -7.32883513e-02 9.27494764e-01 6.65129900e-01
1.62494540e-01 -3.11976880e-01 -7.55394042e-01 7.18599200e-01
-2.17435002e+00 -1.05310655e+00 -4.33171779e-01 2.30577302e+00
3.46107721e-01 1.13951214e-01 4.75375444e-01 -3.16530883e-01
7.09474564e-01 1.47553578e-01 -5.46014965e-01 1.31839350e-01
3.05063397e-01 2.42479239e-03 7.96389818e-01 4.43525791e-01
-1.52559543e+00 9.16388452e-01 5.50880909e+00 8.32345665e-01
-1.18367982e+00 3.67261440e-01 -4.45427746e-01 -5.33125222e-01
2.76448190e-01 2.31631607e-01 -1.47563052e+00 4.85373378e-01
1.10284603e+00 1.69611812e-01 2.48863444e-01 8.78822446e-01
-9.95980427e-02 6.28536642e-02 -1.14021492e+00 9.50035334e-01
-1.41588479e-01 -1.09639549e+00 -4.16527122e-01 3.75719696e-01
7.76691288e-02 4.71329540e-01 8.58298317e-02 5.27110279e-01
4.66962010e-01 -6.35578513e-01 1.03753662e+00 2.22791910e-01
8.42885375e-01 -6.29278123e-02 5.96292615e-01 3.46619993e-01
-2.16691041e+00 -8.54989141e-03 -2.01395482e-01 1.05695702e-01
2.67083764e-01 2.23112524e-01 -6.85417831e-01 6.59917057e-01
9.90789652e-01 1.01177156e+00 -7.87960231e-01 1.22325051e+00
8.29919353e-02 4.63110745e-01 -8.44666958e-01 -1.03084341e-01
-2.20027100e-02 1.25988275e-01 8.82185519e-01 1.26580369e+00
3.02618384e-01 -2.48078793e-01 5.78816950e-01 7.87827015e-01
1.81820706e-01 -3.85775238e-01 -6.99640334e-01 -7.60346502e-02
7.27861464e-01 1.46437693e+00 -6.98961675e-01 -3.81723434e-01
-6.69243455e-01 7.24715829e-01 3.03416044e-01 -1.45871818e-01
-1.41978550e+00 -1.12218723e-01 9.00787890e-01 1.77656934e-01
6.71444774e-01 -3.66730452e-01 1.75225548e-02 -1.12263393e+00
1.34054616e-01 -5.35241008e-01 4.24996465e-01 -1.48409799e-01
-1.19487643e+00 4.02175814e-01 -1.08158812e-01 -1.68518972e+00
2.62052536e-01 -6.42131090e-01 -4.79103684e-01 5.31953692e-01
-1.54060841e+00 -1.46234763e+00 -2.85437018e-01 4.92910802e-01
2.97965616e-01 1.43653065e-01 7.03100502e-01 7.87414908e-01
-8.41972768e-01 9.62383747e-01 1.00297309e-01 8.89553800e-02
9.03597474e-01 -1.22097802e+00 4.27839786e-01 1.01666796e+00
2.91213810e-01 7.92027414e-01 6.77090526e-01 -7.03143895e-01
-1.94297469e+00 -1.28532517e+00 5.18408239e-01 -9.40324247e-01
8.19213867e-01 -6.95133209e-01 -6.20084643e-01 9.00849283e-01
2.65301347e-01 3.65940154e-01 4.84988689e-01 1.04090199e-01
-2.63083607e-01 -1.99095860e-01 -9.25917208e-01 5.76052964e-01
1.11874402e+00 -2.26792797e-01 -2.22624689e-01 1.99738085e-01
6.45922661e-01 -4.78738725e-01 -8.11742127e-01 3.69089872e-01
8.20291460e-01 -6.76637709e-01 1.10919666e+00 5.77360317e-02
-6.18282318e-01 -1.11950481e+00 -2.03207821e-01 -5.69364309e-01
-4.86806214e-01 -6.89332485e-01 -8.31010878e-01 1.25406647e+00
1.30821422e-01 -6.17712736e-01 6.71962798e-01 1.89076126e-01
-2.13456959e-01 -6.22682214e-01 -1.06890368e+00 -1.18025672e+00
-4.78583068e-01 -3.46999586e-01 3.26761335e-01 7.30452120e-01
-3.43641669e-01 2.63206124e-01 -6.31028056e-01 6.28045619e-01
9.93770957e-01 6.91904277e-02 1.18111801e+00 -1.21819866e+00
-5.80412686e-01 -3.06804180e-01 -4.73554611e-01 -1.47761333e+00
-3.45912784e-01 -6.98818684e-01 2.77819753e-01 -1.17753303e+00
2.25847885e-01 -7.38633335e-01 -5.47943413e-01 7.18467116e-01
-1.54060945e-01 3.62171918e-01 3.66914779e-01 5.55247664e-01
-1.11144006e+00 5.64907372e-01 6.89726174e-01 -1.83762252e-01
-9.03430134e-02 -1.75200596e-01 -5.34657240e-01 4.76687461e-01
6.27510011e-01 -8.20005000e-01 -6.89527392e-02 -5.41564643e-01
-3.59830856e-01 -2.55962253e-01 8.51036191e-01 -1.52946901e+00
6.71827614e-01 1.59280315e-01 1.82732955e-01 -7.41656125e-01
7.56088793e-01 -9.92648244e-01 3.72161567e-01 8.25650573e-01
2.58350760e-01 1.76755175e-01 5.71273327e-01 8.70952010e-01
2.04323590e-01 2.78902054e-01 7.56770611e-01 2.63506949e-01
-9.41727698e-01 4.78970468e-01 -1.53963014e-01 -4.30587053e-01
1.43498206e+00 -3.80058795e-01 -5.75649023e-01 1.30344003e-01
-2.92229980e-01 4.28347796e-01 6.62031651e-01 6.58646584e-01
3.36856812e-01 -1.41791165e+00 -5.49773872e-01 -6.37802631e-02
2.24688709e-01 -2.76159883e-01 -4.07074206e-02 1.39735782e+00
-1.46578878e-01 3.53399754e-01 2.70392634e-02 -1.09127748e+00
-1.59205127e+00 6.93314195e-01 1.89025253e-01 -3.06529343e-01
-7.52712131e-01 7.88542092e-01 1.96200758e-01 -2.42472455e-01
4.26633477e-01 -1.06341459e-01 1.62919015e-01 -2.30197117e-01
6.62197888e-01 3.25687349e-01 -2.69553512e-01 -6.96551561e-01
-7.74886370e-01 6.59273565e-01 -2.72768587e-01 4.46559340e-02
1.00404632e+00 -7.53136948e-02 2.51113027e-01 2.70867348e-01
7.03561008e-01 -9.35894474e-02 -1.44752073e+00 -3.14828962e-01
-9.46964324e-02 -5.54412842e-01 3.10663208e-02 -5.91717303e-01
-9.44080770e-01 7.60157645e-01 1.19442880e+00 9.35520902e-02
8.00370336e-01 2.31506571e-01 9.28331554e-01 1.81904376e-01
6.42697692e-01 -6.78059757e-01 1.44176796e-01 2.68790752e-01
3.73173386e-01 -1.36416948e+00 8.80553350e-02 -2.45445415e-01
-1.35413587e-01 7.79379785e-01 1.04093790e+00 -1.06739357e-01
4.42714095e-01 6.60582662e-01 1.11445673e-01 -4.91856635e-01
-8.10995340e-01 -5.08766294e-01 2.37496957e-01 6.28523052e-01
3.52172583e-01 1.25168040e-01 -1.09912209e-01 1.71380848e-01
1.39369473e-01 -1.82541907e-01 -5.51912896e-02 1.24566162e+00
-4.15565997e-01 -1.28501070e+00 -5.93856573e-01 2.08294630e-01
-9.12299678e-02 7.15951845e-02 -3.41894239e-01 9.83183920e-01
3.43847781e-01 1.14425516e+00 -5.14685549e-02 -7.70943880e-01
2.87629128e-01 -2.48957619e-01 5.63960969e-01 -6.06846809e-01
-6.48011506e-01 6.83205202e-02 -3.52417938e-02 -8.55639756e-01
-4.06230330e-01 -8.52589726e-01 -1.22259200e+00 -5.84798396e-01
-8.04468274e-01 -1.95219383e-01 5.90867639e-01 6.12604916e-01
6.65821016e-01 6.14858210e-01 1.46440297e-01 -1.12049437e+00
-3.72548878e-01 -8.72204840e-01 -2.74997503e-01 1.25381514e-01
5.96188009e-01 -1.10834777e+00 -1.29730806e-01 -2.09433287e-01] | [6.352555751800537, -2.073401689529419] |
3e821fd0-d6d4-4c24-a8f3-df0a4b06ad98 | a-learning-system-for-motion-planning-of-free | 2207.02464 | null | https://arxiv.org/abs/2207.02464v1 | https://arxiv.org/pdf/2207.02464v1.pdf | A Learning System for Motion Planning of Free-Float Dual-Arm Space Manipulator towards Non-Cooperative Object | Recent years have seen the emergence of non-cooperative objects in space, like failed satellites and space junk. These objects are usually operated or collected by free-float dual-arm space manipulators. Thanks to eliminating the difficulties of modeling and manual parameter-tuning, reinforcement learning (RL) methods have shown a more promising sign in the trajectory planning of space manipulators. Although previous studies demonstrate their effectiveness, they cannot be applied in tracking dynamic targets with unknown rotation (non-cooperative objects). In this paper, we proposed a learning system for motion planning of free-float dual-arm space manipulator (FFDASM) towards non-cooperative objects. Specifically, our method consists of two modules. Module I realizes the multi-target trajectory planning for two end-effectors within a large target space. Next, Module II takes as input the point clouds of the non-cooperative object to estimate the motional property, and then can predict the position of target points on an non-cooperative object. We leveraged the combination of Module I and Module II to track target points on a spinning object with unknown regularity successfully. Furthermore, the experiments also demonstrate the scalability and generalization of our learning system. | ['Tao Zhang', 'Xiang Zheng', 'Yuxue Cao', 'Shengjie Wang'] | 2022-07-06 | null | null | null | null | ['trajectory-planning'] | ['robots'] | [-4.20567602e-01 2.15589236e-02 -2.23065794e-01 2.29143813e-01
-5.28186262e-01 -8.27713966e-01 3.45927864e-01 -3.79256338e-01
-2.94431269e-01 8.67818952e-01 -5.47660410e-01 -3.76683414e-01
-9.42172468e-01 -3.40308309e-01 -5.91003358e-01 -9.92219090e-01
-4.28625375e-01 8.54840577e-01 3.97449613e-01 -4.35223848e-01
1.96981773e-01 8.78420830e-01 -1.06447291e+00 -4.75298285e-01
7.78348804e-01 5.72170079e-01 7.95930147e-01 5.44363379e-01
3.47509384e-01 5.35827756e-01 -2.96075702e-01 4.16435272e-01
4.31624502e-01 9.41999629e-02 -5.11589468e-01 1.95996910e-01
-2.46138737e-01 -1.55116990e-01 -6.66863859e-01 7.19145477e-01
2.16631174e-01 5.77789366e-01 6.92008317e-01 -1.56651437e+00
-2.36621484e-01 4.29445952e-01 -5.43035328e-01 -1.72370132e-02
1.68070659e-01 4.86106724e-01 6.84177518e-01 -6.10189915e-01
5.69150686e-01 1.27439225e+00 5.43583095e-01 3.43445897e-01
-5.23862481e-01 -3.11854541e-01 1.00678556e-01 1.65038779e-01
-1.26281309e+00 -8.31056908e-02 6.68149233e-01 -5.63526630e-01
6.73607945e-01 8.40206519e-02 7.05541790e-01 1.02342665e+00
5.76451540e-01 9.09168959e-01 7.16489792e-01 -1.62496343e-01
3.43284816e-01 -2.74896920e-01 -2.30195314e-01 6.42750561e-01
2.79516190e-01 4.62001175e-01 9.18933675e-02 -1.19351424e-01
1.05704105e+00 3.37831855e-01 -2.39232749e-01 -7.83328652e-01
-1.59188330e+00 8.41712236e-01 5.70444226e-01 2.84087449e-01
-5.36569476e-01 2.13761225e-01 -1.60749286e-01 3.35464984e-01
-1.39808580e-01 5.38915694e-01 -6.07346416e-01 -1.32995829e-01
-2.66207159e-01 5.49995363e-01 6.87667012e-01 1.42986310e+00
2.98645943e-01 7.31002092e-02 5.82396276e-02 2.97792524e-01
4.63647842e-01 5.17036855e-01 2.91344732e-01 -9.98510838e-01
6.61087513e-01 5.43831527e-01 7.59365261e-01 -7.22598612e-01
-8.50167334e-01 -6.53198957e-01 -6.39723778e-01 7.07085073e-01
4.71934766e-01 -4.15142596e-01 -7.21454620e-01 1.34343243e+00
5.91118097e-01 -2.77032495e-01 1.57129645e-01 1.41999638e+00
-9.35484096e-02 5.96617639e-01 -2.94660717e-01 -3.76937747e-01
9.23033416e-01 -1.12371254e+00 -4.87994790e-01 -7.87414238e-02
6.45199776e-01 -7.36478388e-01 8.50347757e-01 3.46082628e-01
-9.18149233e-01 -5.57418108e-01 -9.16596353e-01 4.34976459e-01
-3.80480289e-02 3.76815408e-01 6.33290350e-01 -7.77384937e-02
-5.36515176e-01 9.06240344e-01 -1.29278970e+00 -2.49277920e-01
2.63575047e-01 6.11933470e-01 -1.91695035e-01 2.05817997e-01
-6.71806514e-01 1.17121983e+00 5.96788406e-01 2.39550173e-01
-1.08651567e+00 -3.65496218e-01 -4.82275397e-01 -2.04055592e-01
8.86316419e-01 -9.01265085e-01 1.30150712e+00 -4.25988734e-01
-1.76017594e+00 1.96917579e-02 3.83943588e-01 -6.24863766e-02
7.02933133e-01 -4.71424937e-01 -1.82012141e-01 -1.03322782e-01
1.22803457e-01 3.03440392e-01 9.14019406e-01 -1.33555722e+00
-9.43341434e-01 -4.38576549e-01 2.16026783e-01 5.35138011e-01
1.23693332e-01 -5.54110169e-01 -2.00690702e-01 -4.33507532e-01
7.12296426e-01 -1.45150006e+00 -4.04629409e-01 5.30877300e-02
-3.53368163e-01 -5.39589882e-01 1.16234887e+00 -2.87288338e-01
6.65555000e-01 -2.11185575e+00 6.44147098e-01 -5.36169447e-02
-1.68405354e-01 2.99545024e-02 -2.50281185e-01 6.89903080e-01
2.43307710e-01 -4.83623683e-01 7.04094246e-02 1.50215536e-01
-7.35156164e-02 3.84485453e-01 -3.82017344e-01 6.24637425e-01
-6.05536401e-02 8.73863161e-01 -1.21742928e+00 -2.13066354e-01
1.13290578e-01 1.40272519e-02 -2.66748250e-01 2.27996275e-01
-4.22513247e-01 7.27066100e-01 -1.08394086e+00 9.08891976e-01
3.62016410e-01 -1.11703075e-01 1.51506171e-01 -5.13894111e-02
-5.50022066e-01 -3.10698986e-01 -1.29502273e+00 1.73871279e+00
-2.65860021e-01 1.11258522e-01 3.19560975e-01 -7.84719169e-01
9.15765703e-01 7.94970989e-02 6.61495507e-01 -2.62304693e-01
1.60671875e-01 3.42339128e-01 4.88826558e-02 -9.64358449e-01
5.70122540e-01 -5.81227317e-02 3.85082848e-02 1.25190809e-01
-7.34708980e-02 -5.69822371e-01 -1.14978962e-01 -2.94102490e-01
1.16097653e+00 5.28227985e-01 2.13540569e-01 -7.37901554e-02
6.34332597e-01 4.83761042e-01 4.32091743e-01 5.33718169e-01
-9.09043625e-02 1.76497340e-01 -3.78802270e-02 -4.86747831e-01
-9.21213031e-01 -1.08353102e+00 3.22913200e-01 8.31906080e-01
7.12412119e-01 1.98849306e-01 -1.73294351e-01 -5.16348183e-01
4.45087254e-01 6.02835834e-01 -3.76423113e-02 -5.20604439e-02
-7.97942102e-01 -4.26620811e-01 -2.35086251e-02 4.67067838e-01
1.40728489e-01 -7.86110818e-01 -9.56673622e-01 3.56186032e-01
1.96091756e-01 -8.24188352e-01 -4.29280609e-01 1.19401865e-01
-1.19659984e+00 -1.40818167e+00 -6.01714969e-01 -9.74965572e-01
6.65602148e-01 6.33753598e-01 2.05639407e-01 -5.97974584e-02
-7.25370497e-02 5.87929666e-01 -3.00765753e-01 -4.40937251e-01
-2.54751533e-01 2.84917325e-01 5.95290065e-01 -2.89344370e-01
-2.67877698e-01 -5.23500443e-01 -4.93682861e-01 9.05008674e-01
-5.74233949e-01 -2.59954393e-01 9.95714784e-01 8.10598314e-01
5.63585937e-01 2.94289351e-01 4.66599703e-01 9.39780101e-02
4.88914371e-01 -5.43921471e-01 -9.92450476e-01 2.34184295e-01
-1.60860285e-01 3.47239594e-03 6.32137239e-01 -8.38139892e-01
-7.36141145e-01 6.40427530e-01 4.34096336e-01 -8.11830640e-01
-1.84802711e-02 5.55801332e-01 7.85943493e-02 -2.60490179e-01
4.22859609e-01 5.37888147e-02 4.96738255e-01 -4.26872134e-01
2.37326220e-01 5.46293497e-01 3.91705751e-01 -5.50082088e-01
1.29724956e+00 3.09737384e-01 4.02165562e-01 -6.43407226e-01
-4.62055326e-01 -5.19974291e-01 -8.74882936e-01 -4.21843141e-01
5.62969625e-01 -7.02129543e-01 -1.38899636e+00 3.04190427e-01
-1.24831033e+00 -4.01549309e-01 -3.23123246e-01 9.74338114e-01
-9.50649500e-01 4.30772036e-01 -3.33870411e-01 -1.11206686e+00
1.87543556e-02 -1.01322019e+00 1.10850930e+00 3.13662350e-01
1.22302711e-01 -8.64626765e-01 1.16259404e-01 1.23275757e-01
2.36393213e-01 2.24638984e-01 6.97332084e-01 -3.92970324e-01
-9.65608835e-01 -2.14880675e-01 3.99378121e-01 -3.61283988e-01
3.03825945e-01 -2.54566759e-01 -3.24320525e-01 -8.88553202e-01
3.22542518e-01 -2.96772689e-01 2.12901458e-01 4.89313155e-01
6.46799624e-01 -3.13165039e-01 -8.70592237e-01 3.38718981e-01
1.33292139e+00 5.73565960e-01 1.65386468e-01 7.43431151e-01
4.70476836e-01 5.38205743e-01 1.45185840e+00 4.23358381e-01
1.79789707e-01 8.05297673e-01 1.06318533e+00 3.47211182e-01
4.72893119e-01 -8.24601129e-02 3.34487855e-01 7.80864477e-01
-3.79561126e-01 -1.80189982e-01 -9.03914511e-01 5.61601162e-01
-2.27378082e+00 -6.80096865e-01 -3.27693284e-01 1.96020532e+00
2.52180874e-01 3.16554680e-02 1.16968244e-01 -1.49936110e-01
7.03296840e-01 -2.61440009e-01 -9.43744540e-01 5.63814402e-01
1.63080975e-01 -6.73562467e-01 6.76718593e-01 4.28973496e-01
-1.10389149e+00 8.63313675e-01 5.54776716e+00 6.40339792e-01
-1.02322710e+00 -1.66278347e-01 -3.16236883e-01 -6.86708763e-02
1.30715489e-01 1.33189738e-01 -8.36114585e-01 3.60492408e-01
4.38847363e-01 -6.07981347e-02 5.92858911e-01 1.17514002e+00
1.40171334e-01 -3.82339433e-02 -9.34337199e-01 8.79313886e-01
-4.28883135e-01 -1.19090855e+00 -3.37535203e-01 1.78409398e-01
5.99635541e-01 6.25323579e-02 -4.51903492e-02 4.95824695e-01
3.03138494e-01 -5.04597485e-01 9.79575813e-01 7.24644959e-01
1.45933986e-01 -4.94435638e-01 6.32006764e-01 1.02594531e+00
-9.90639269e-01 -8.74784887e-01 -5.22135437e-01 -1.72519356e-01
5.04714310e-01 2.74286836e-01 -1.15877783e+00 1.09382522e+00
3.04971576e-01 5.13264954e-01 -7.33315712e-04 1.33063829e+00
1.13551151e-02 -7.35741109e-02 -4.49409127e-01 -3.64077300e-01
5.96199214e-01 -5.36238492e-01 1.06959283e+00 1.36034653e-01
6.96656048e-01 2.93286800e-01 4.83149201e-01 6.92517400e-01
6.05516493e-01 -2.98558205e-01 -6.87034786e-01 8.21230859e-02
4.20973599e-01 1.32732654e+00 -6.58448219e-01 -1.98128037e-02
-1.06532149e-01 6.34062231e-01 1.83785439e-01 3.72695446e-01
-9.26371932e-01 -2.89611310e-01 5.44126689e-01 8.28803405e-02
4.96606141e-01 -9.92676616e-01 5.17624430e-02 -8.96131039e-01
1.68297574e-01 -5.02631485e-01 2.65563518e-01 -9.55550313e-01
-1.19213212e+00 3.88269067e-01 -4.64666560e-02 -1.94972050e+00
-2.80184895e-01 -8.12568843e-01 -3.50618899e-01 6.07164145e-01
-1.31707084e+00 -1.19720793e+00 -3.11704010e-01 5.14799953e-01
8.31584573e-01 -5.77000022e-01 5.37651181e-01 -2.91918814e-01
-2.76741087e-01 -1.37125552e-01 4.54208165e-01 -3.66189212e-01
3.91237170e-01 -9.97190952e-01 -7.99631402e-02 3.29082221e-01
-3.46857578e-01 5.36045015e-01 6.55369997e-01 -9.68998611e-01
-2.24908733e+00 -1.08149302e+00 1.08163781e-01 -4.96461719e-01
9.68600631e-01 6.12837970e-02 -6.54072583e-01 8.93748462e-01
-3.13098639e-01 -1.10640183e-01 -2.80041486e-01 -2.52492368e-01
4.84935552e-01 6.17281161e-02 -9.60454881e-01 5.85980713e-01
1.02245617e+00 2.56954163e-01 -8.08431387e-01 8.03285301e-01
8.81350517e-01 -1.01203573e+00 -8.34401727e-01 6.29052341e-01
3.96614343e-01 -1.13317765e-01 1.02988076e+00 -9.56337273e-01
1.04744276e-02 -7.37776637e-01 5.99327497e-02 -1.48741651e+00
-7.84431636e-01 -1.00636733e+00 -3.87112379e-01 5.69591880e-01
-4.96011451e-02 -5.36151230e-01 8.24632406e-01 -8.47187713e-02
-6.56042397e-01 -7.94676483e-01 -1.20623040e+00 -1.31855726e+00
-1.20264143e-01 8.87445733e-02 4.50357407e-01 6.92448139e-01
1.05048940e-02 3.04589540e-01 -2.97442198e-01 7.85829663e-01
6.40261292e-01 3.61790478e-01 8.95460844e-01 -1.30989122e+00
-2.75198370e-01 -1.09727457e-01 -2.67363399e-01 -1.27143514e+00
2.29653403e-01 -8.12533796e-01 3.62242907e-01 -1.41538894e+00
-5.21729290e-01 -8.91082585e-01 1.79883853e-01 3.78136814e-01
1.53215438e-01 -5.78251481e-01 2.12926984e-01 7.91224957e-01
-6.24788344e-01 8.28263342e-01 1.72725093e+00 -1.91037983e-01
-5.35006344e-01 7.03569949e-01 -1.52866855e-01 6.50534987e-01
7.91231155e-01 -3.96871656e-01 -5.42989373e-01 -5.84386528e-01
-6.94651380e-02 8.03338408e-01 4.83470619e-01 -1.17581069e+00
7.10612118e-01 -7.06269562e-01 1.86923876e-01 -9.80826914e-01
4.99895126e-01 -1.24847269e+00 3.07859898e-01 1.03059042e+00
1.34337708e-01 1.16348907e-01 9.38285068e-02 8.90528381e-01
7.16084987e-02 -4.46620911e-01 4.75990057e-01 -5.46225719e-02
-5.38760662e-01 3.76885951e-01 -3.96205634e-01 -5.88726401e-01
1.53997123e+00 -9.63409469e-02 -2.94165730e-01 -5.19292951e-02
-8.80231619e-01 7.75270462e-01 2.83045053e-01 5.57779253e-01
5.96671999e-01 -1.21328998e+00 -3.69992495e-01 1.91527121e-02
-1.86448500e-01 4.28207934e-01 2.56921411e-01 1.10206079e+00
-3.43271047e-01 6.61514103e-01 -3.79563659e-01 -9.92158115e-01
-8.96989763e-01 9.22628045e-01 2.87223816e-01 -5.59409522e-03
-6.56732500e-01 3.75156164e-01 -1.90582305e-01 -6.10788584e-01
1.82533607e-01 -5.25078237e-01 -1.25141442e-01 -1.93370312e-01
6.58824295e-02 6.17490351e-01 -1.17934838e-01 -3.27406466e-01
-1.97497517e-01 8.13714504e-01 1.19121425e-01 -6.72302619e-02
1.84685528e+00 -9.14816335e-02 1.14785038e-01 4.39959943e-01
5.11431694e-01 -3.94591600e-01 -1.58466828e+00 -4.80888262e-02
1.95723504e-01 -4.56441343e-01 -2.76293784e-01 -6.39872253e-01
-6.99561715e-01 2.78138906e-01 5.09850979e-01 1.23401590e-01
6.02237701e-01 9.70500931e-02 6.56944692e-01 8.48776102e-01
9.87671018e-01 -1.01717734e+00 4.68811274e-01 8.46475184e-01
1.25968909e+00 -9.75524247e-01 -7.22846016e-02 -3.74448061e-01
-6.25260472e-01 1.51559687e+00 6.52740538e-01 -1.78034618e-01
3.67640525e-01 5.53946011e-02 1.90979242e-02 -2.20656261e-01
-7.01010644e-01 7.65580460e-02 1.50183126e-01 6.92573428e-01
-3.54574561e-01 2.94365268e-02 -1.55321822e-01 3.62674922e-01
-1.22667648e-01 2.16577891e-02 4.90055025e-01 1.39860988e+00
-9.07480001e-01 -8.56307149e-01 -7.41613150e-01 6.73909783e-02
4.10733938e-01 7.84792125e-01 4.23658118e-02 1.18433917e+00
-1.23617589e-01 6.66664720e-01 -7.12653846e-02 -4.04108524e-01
7.42319643e-01 -2.85550356e-01 6.23315692e-01 -3.50090384e-01
-2.56556690e-01 3.73605080e-02 -2.72165596e-01 -4.89233077e-01
-2.68715173e-01 -8.80435169e-01 -1.46647930e+00 1.43650994e-01
-5.40749252e-01 2.80182838e-01 1.00542486e+00 9.50969219e-01
3.35742772e-01 4.41209197e-01 9.62516904e-01 -1.16061437e+00
-1.40546429e+00 -8.89801800e-01 -6.24835730e-01 3.09161358e-02
5.06995559e-01 -1.12271881e+00 -3.53442311e-01 -3.12579066e-01] | [4.8237385749816895, 1.1756937503814697] |
1c6b35a8-a7cc-4ad7-8110-88683318460b | whats-missing-a-knowledge-gap-guided-approach | 1909.09253 | null | https://arxiv.org/abs/1909.09253v1 | https://arxiv.org/pdf/1909.09253v1.pdf | What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering | Multi-hop textual question answering requires combining information from multiple sentences. We focus on a natural setting where, unlike typical reading comprehension, only partial information is provided with each question. The model must retrieve and use additional knowledge to correctly answer the question. To tackle this challenge, we develop a novel approach that explicitly identifies the knowledge gap between a key span in the provided knowledge and the answer choices. The model, GapQA, learns to fill this gap by determining the relationship between the span and an answer choice, based on retrieved knowledge targeting this gap. We propose jointly training a model to simultaneously fill this knowledge gap and compose it with the provided partial knowledge. On the OpenBookQA dataset, given partial knowledge, explicitly identifying what's missing substantially outperforms previous approaches. | ['Peter Clark', 'Ashish Sabharwal', 'Tushar Khot'] | 2019-09-19 | whats-missing-a-knowledge-gap-guided-approach-1 | https://aclanthology.org/D19-1281 | https://aclanthology.org/D19-1281.pdf | ijcnlp-2019-11 | ['multi-hop-question-answering'] | ['knowledge-base'] | [ 3.19844872e-01 3.62192810e-01 -2.30642587e-01 -3.16810250e-01
-1.61767292e+00 -1.04265010e+00 3.34001809e-01 8.76180291e-01
-4.92943913e-01 8.59163344e-01 4.73480016e-01 -5.62213838e-01
-4.26319569e-01 -8.74253333e-01 -9.73166525e-01 1.63702205e-01
5.24926245e-01 6.24458253e-01 6.50601447e-01 -4.33721513e-01
4.12998170e-01 -3.22955877e-01 -1.30636537e+00 6.65447354e-01
1.21146715e+00 9.16430175e-01 5.27079642e-01 8.61216843e-01
-6.97785676e-01 1.28105569e+00 -5.98010600e-01 -4.30303514e-01
-1.39367476e-01 -5.30548871e-01 -1.76951039e+00 -1.21366128e-01
7.12535441e-01 -5.03565192e-01 -1.53793260e-01 5.98282039e-01
8.24177489e-02 2.61574894e-01 4.16678876e-01 -7.39030719e-01
-5.24815321e-01 9.31863189e-01 6.20264634e-02 5.81271589e-01
1.18557501e+00 -1.24064952e-01 1.54499602e+00 -6.53162062e-01
6.32770598e-01 9.50234532e-01 4.19304103e-01 4.32519794e-01
-9.76345897e-01 3.19238938e-02 3.77730727e-01 5.49332082e-01
-1.08490705e+00 -3.70078057e-01 6.95194304e-01 -3.65385622e-01
1.01599097e+00 2.42627278e-01 2.24987805e-01 7.36203969e-01
-4.35526520e-01 8.11593175e-01 9.05713439e-01 -7.56971419e-01
5.60575090e-02 6.14340715e-02 7.58749008e-01 6.38030887e-01
-1.95218697e-01 -5.32621801e-01 -7.90292740e-01 -3.19748461e-01
9.56545770e-02 -3.76757443e-01 -5.10933757e-01 -3.36517543e-02
-8.85676980e-01 6.84746981e-01 1.02260873e-01 2.46318325e-01
-3.06876034e-01 3.21569224e-03 1.54821485e-01 6.91717982e-01
9.69984010e-02 8.95458460e-01 -9.42799449e-01 -3.93468171e-01
-8.92596066e-01 4.39210624e-01 1.49088788e+00 8.75284970e-01
1.13934386e+00 -8.58902097e-01 -4.67481405e-01 7.95206964e-01
4.22146916e-02 3.58993530e-01 1.90479472e-01 -1.31166470e+00
9.05488253e-01 9.29804802e-01 6.20551348e-01 -7.63913155e-01
-1.77540347e-01 -4.02695507e-01 1.33712292e-01 -7.33201981e-01
9.74968255e-01 -1.62408188e-01 -4.90314424e-01 1.92607677e+00
5.99476099e-01 -3.57245933e-03 1.70491427e-01 6.95486069e-01
9.82454360e-01 6.14954889e-01 -7.44276270e-02 -1.25065163e-01
1.59502912e+00 -9.25312161e-01 -6.89774990e-01 -4.60783631e-01
9.10095990e-01 -7.03458190e-01 1.15422118e+00 4.79512140e-02
-1.11917090e+00 -2.40261629e-01 -8.77577364e-01 -5.41240692e-01
-9.82351229e-02 7.60592297e-02 8.07834342e-02 2.13113241e-02
-1.06600332e+00 3.33042055e-01 -2.10822240e-01 -1.96113333e-01
-2.05474123e-02 5.26660196e-02 -3.80169936e-02 -6.65860772e-01
-1.56784594e+00 9.65003252e-01 3.60322446e-01 -1.13113962e-01
-7.02953398e-01 -1.03075016e+00 -7.57169187e-01 2.00215161e-01
1.11548722e+00 -9.64358866e-01 1.82772231e+00 -7.08596766e-01
-1.27383208e+00 7.26979136e-01 -6.97126985e-01 -5.69209695e-01
2.05340073e-01 -4.84724462e-01 7.49090984e-02 5.36858320e-01
3.06958765e-01 4.78527427e-01 6.20926321e-01 -1.19255304e+00
-5.61800063e-01 -3.23770553e-01 9.42146719e-01 4.38272148e-01
4.51028310e-02 -1.54438198e-01 -5.07443309e-01 -7.50024766e-02
1.86352238e-01 -3.77807617e-01 1.49265245e-01 -3.53327632e-01
-4.52280968e-01 -6.45768106e-01 5.55840552e-01 -1.06273007e+00
1.60995162e+00 -1.60425365e+00 1.48369446e-01 7.09009841e-02
3.85605097e-01 1.17130332e-01 -2.83021599e-01 7.64695644e-01
5.03825426e-01 1.50763029e-02 -3.00950974e-01 -6.99918270e-02
-2.60334630e-02 2.57724106e-01 -6.03059292e-01 -2.03853369e-01
1.83427542e-01 1.10679412e+00 -1.20160627e+00 -4.95120943e-01
-4.69689697e-01 -8.01934600e-02 -5.19033372e-01 5.01646817e-01
-1.07951903e+00 3.38219285e-01 -8.37613165e-01 5.45610547e-01
3.50608617e-01 -5.17264545e-01 6.45909384e-02 -1.53783914e-02
2.73482293e-01 8.13044548e-01 -9.74275470e-01 1.78602457e+00
-6.68453455e-01 4.30513054e-01 2.22831607e-01 -8.42646122e-01
8.00453961e-01 2.91183352e-01 1.32876113e-01 -7.50416815e-01
-7.52784535e-02 3.79518449e-01 -1.80818602e-01 -1.03487289e+00
4.85699534e-01 -8.00052509e-02 3.72841768e-02 7.94905066e-01
2.92091608e-01 -1.47488117e-01 4.23816442e-01 6.72221959e-01
1.50455177e+00 -2.09456459e-02 2.58726001e-01 -2.28701290e-02
8.05049777e-01 2.54657745e-01 6.48267940e-02 1.11209381e+00
-4.76089865e-02 3.36596936e-01 8.08654845e-01 -9.65847727e-03
-7.30663061e-01 -8.38611245e-01 3.70621413e-01 1.24421668e+00
1.41820654e-01 -6.36258602e-01 -8.57019782e-01 -1.00394583e+00
1.06910486e-02 9.58087981e-01 -5.56979179e-01 -9.93655473e-02
-7.82145798e-01 3.13569814e-01 3.53927761e-01 4.04756337e-01
4.62301075e-01 -9.00784791e-01 -5.59538424e-01 2.77810395e-01
-9.85507131e-01 -1.32128203e+00 -6.40358508e-01 5.26587665e-03
-7.44120300e-01 -1.50530791e+00 -2.83760399e-01 -7.87606299e-01
4.59250271e-01 1.97257906e-01 1.66186619e+00 5.71747839e-01
1.82548344e-01 9.75405037e-01 -6.56859040e-01 -8.44358131e-02
-3.96600366e-01 4.13411140e-01 -7.03372538e-01 -1.55413762e-01
5.23589313e-01 -4.40390259e-01 -4.88358527e-01 9.91448238e-02
-9.00981188e-01 -4.09820415e-02 4.25321549e-01 6.38895929e-01
3.73655379e-01 -2.69668788e-01 1.06166971e+00 -8.74482691e-01
9.20310080e-01 -8.49540532e-01 -3.59076500e-01 8.07301283e-01
-2.03747049e-01 4.36439514e-01 5.53355813e-01 -1.29734367e-01
-1.06734598e+00 -2.18520448e-01 -2.03588024e-01 9.76580661e-03
-7.78200552e-02 9.71572876e-01 -1.36266932e-01 3.22606593e-01
6.25317931e-01 1.65241271e-01 -1.75340325e-01 -6.39921129e-01
5.85014760e-01 4.20877963e-01 5.29902756e-01 -9.65788126e-01
6.35759950e-01 4.97276150e-02 -3.95881951e-01 -4.38355684e-01
-1.75231040e+00 -8.64239275e-01 -6.34931207e-01 -4.49030250e-02
5.97521722e-01 -6.88569188e-01 -6.77941680e-01 3.76952253e-02
-1.40815759e+00 -3.77162576e-01 -4.69972968e-01 1.46312520e-01
-5.09177983e-01 4.00787950e-01 -2.95926839e-01 -7.65574396e-01
-2.52670139e-01 -5.84690154e-01 8.01858664e-01 1.77147657e-01
-3.92119020e-01 -1.20237279e+00 1.56011030e-01 1.00801325e+00
2.84695119e-01 -3.28747034e-01 1.31521976e+00 -1.10857618e+00
-8.16823006e-01 -1.82694674e-01 -1.60797298e-01 1.75013751e-01
7.81371370e-02 -5.52925527e-01 -7.05270946e-01 1.57907307e-01
1.25697389e-01 -8.17230642e-01 9.96862233e-01 -4.05040793e-02
9.52203512e-01 -6.45952880e-01 -1.29372033e-03 -1.56793013e-01
1.22966266e+00 -1.97392210e-01 3.01004440e-01 2.47486517e-01
3.90792310e-01 9.67836082e-01 4.85462338e-01 2.01660603e-01
1.01109457e+00 4.04447287e-01 2.00421438e-01 4.82292980e-01
-1.21041685e-01 -6.07136071e-01 2.85745296e-03 8.97424877e-01
6.28304839e-01 -2.55002767e-01 -9.78663385e-01 8.85950446e-01
-1.68218160e+00 -6.82734609e-01 1.72229439e-01 2.05833650e+00
1.52367198e+00 2.71386672e-02 -1.36503220e-01 2.56873276e-02
2.63525873e-01 9.22050998e-02 -7.24286914e-01 -1.84584141e-01
-9.21971425e-02 3.24811906e-01 4.01484296e-02 1.20158565e+00
-6.34509087e-01 8.37918580e-01 6.56581163e+00 7.46172607e-01
-4.30922657e-01 7.60913864e-02 2.28834927e-01 1.43303692e-01
-9.11485970e-01 3.87030005e-01 -8.18466187e-01 1.21293232e-01
9.08773839e-01 -3.31122726e-01 4.72361982e-01 1.87029943e-01
-9.66726057e-03 -6.65536880e-01 -1.45499647e+00 3.11687768e-01
3.24761331e-01 -1.22544515e+00 2.58994848e-01 -5.55954456e-01
5.39468527e-01 -4.16253328e-01 -3.09267998e-01 4.91864949e-01
3.63278568e-01 -9.73749757e-01 4.57992762e-01 8.26893210e-01
3.59591573e-01 -3.24312568e-01 6.79147720e-01 8.43571544e-01
-9.45689023e-01 -1.93912208e-01 -1.05862776e-02 -3.37999582e-01
7.93292150e-02 4.59511191e-01 -1.01921856e+00 6.63470864e-01
1.93104252e-01 3.48876297e-01 -6.70618832e-01 1.00674105e+00
-6.85321867e-01 8.76318276e-01 -2.76299596e-01 -2.05067888e-01
2.42645517e-01 9.38841924e-02 5.77741921e-01 7.61154592e-01
1.96216524e-01 4.30977374e-01 1.99280843e-01 9.48525786e-01
-4.70356643e-01 2.37404808e-01 -2.64778942e-01 -9.80671719e-02
8.10840189e-01 7.58370459e-01 -1.19247884e-01 -4.71896678e-01
-6.14056766e-01 7.67029881e-01 8.14090610e-01 6.01987064e-01
-3.78478587e-01 -2.43229330e-01 1.35852590e-01 -3.78610101e-03
3.72270584e-01 -1.26935884e-01 -1.33093953e-01 -1.07505155e+00
5.09151816e-01 -8.87224972e-01 7.63293207e-01 -1.04485345e+00
-1.07717121e+00 9.95869935e-02 3.11425254e-02 -5.61815262e-01
-3.65928143e-01 -2.29513437e-01 -4.55319732e-01 1.03873646e+00
-1.93997490e+00 -8.84788394e-01 -1.62008360e-01 4.33180660e-01
6.78761601e-01 3.61088842e-01 7.30284095e-01 4.51598242e-02
-1.72765940e-01 4.68463510e-01 -2.33391747e-01 6.46876395e-02
6.86869621e-01 -1.41593242e+00 -1.51499882e-01 5.44510722e-01
2.48658344e-01 7.47693241e-01 8.29127431e-01 -6.14979923e-01
-1.56160653e+00 -6.03187740e-01 1.47724140e+00 -9.26117361e-01
8.13290298e-01 5.61808376e-03 -1.39153969e+00 7.19612896e-01
3.55363220e-01 -4.24024791e-01 7.71780610e-01 2.99022138e-01
-8.06292057e-01 -3.07241045e-02 -8.55480313e-01 2.16874778e-01
6.47753656e-01 -9.38245296e-01 -1.41046476e+00 3.21418673e-01
1.33628976e+00 -5.35122752e-01 -6.86279118e-01 1.26352847e-01
1.28236845e-01 -4.92796957e-01 6.95607066e-01 -8.90869915e-01
6.11015677e-01 -2.69699007e-01 -3.25137287e-01 -1.24501753e+00
3.46346706e-01 -5.61776996e-01 -6.25457644e-01 1.03826344e+00
9.76293802e-01 -2.63334394e-01 7.04340279e-01 9.21427369e-01
-1.21366031e-01 -1.00556922e+00 -1.12419009e+00 -4.02567565e-01
3.55175167e-01 -3.06447357e-01 5.90111196e-01 5.88586509e-01
2.69186229e-01 7.05284536e-01 -5.12795597e-02 9.02367607e-02
2.97292769e-01 4.05190766e-01 5.71443439e-01 -1.02604997e+00
-2.76058793e-01 -6.43971041e-02 3.76963854e-01 -1.75512898e+00
3.07553589e-01 -8.12487721e-01 9.08722058e-02 -2.07167578e+00
3.90585542e-01 -2.12540075e-01 -1.98985822e-02 4.90902185e-01
-6.98704898e-01 -4.36343461e-01 1.03608847e-01 -1.77345313e-02
-1.18103027e+00 4.27925915e-01 1.34116590e+00 -1.90724477e-01
-1.00609906e-01 -2.26485822e-02 -1.09849524e+00 4.63454455e-01
6.23696446e-01 -3.26778203e-01 -6.41863942e-01 -6.91269040e-01
8.11193883e-01 5.52720428e-01 3.23508292e-01 -6.70197666e-01
8.07174921e-01 -2.58708864e-01 -2.26988479e-01 -6.34683073e-01
2.67702460e-01 -6.57040894e-01 -6.10082030e-01 7.25407079e-02
-1.02225447e+00 -1.02000713e-01 1.52318105e-01 6.47584438e-01
-3.98204416e-01 -6.46114588e-01 8.77312385e-03 -3.50496650e-01
-6.13800704e-01 2.12543514e-02 -1.98529050e-01 8.72279704e-01
5.22479773e-01 1.56698227e-01 -6.14937544e-01 -7.13993490e-01
-8.70828629e-01 9.44348395e-01 2.63370108e-02 3.58681530e-01
6.29467249e-01 -8.96108747e-01 -8.91160250e-01 -3.22490811e-01
1.46924347e-01 1.20794505e-01 3.76480192e-01 7.28137612e-01
-4.56145629e-02 7.14399695e-01 3.88900101e-01 -1.35161400e-01
-1.13427222e+00 3.73284072e-01 4.79408771e-01 -6.18688226e-01
-2.55933881e-01 8.58179569e-01 -2.46569991e-01 -6.39767110e-01
3.33275795e-01 -3.89897585e-01 -6.28545702e-01 2.24162683e-01
5.80726445e-01 3.05327415e-01 2.37010017e-01 -2.63888747e-01
-7.20484853e-02 3.78366977e-01 -1.25130251e-01 -3.57768208e-01
8.11563551e-01 -6.65493786e-01 -3.44600827e-01 6.08687282e-01
1.16075611e+00 1.59490824e-01 -1.01635110e+00 -1.03973711e+00
3.72983813e-01 -2.82911330e-01 -3.26067597e-01 -1.33882272e+00
-3.91275197e-01 7.17722714e-01 -2.82215476e-01 2.34848097e-01
8.94906104e-01 5.18878341e-01 1.16355813e+00 1.00102592e+00
9.56080332e-02 -1.03168178e+00 4.60895091e-01 1.08203292e+00
9.43058372e-01 -1.19654691e+00 -1.90711796e-01 -4.37448174e-01
-3.45319390e-01 1.14689720e+00 9.35471594e-01 4.01836663e-01
3.64379138e-01 -1.52030975e-01 1.48233414e-01 -4.43281114e-01
-1.20543361e+00 -3.89956325e-01 4.27851379e-01 2.65704066e-01
2.78736830e-01 -2.71354824e-01 -3.14251006e-01 8.87428105e-01
-4.05608058e-01 -3.84412743e-02 5.11597335e-01 1.22258651e+00
-1.03843606e+00 -1.12527049e+00 -2.67281234e-01 7.51487911e-01
-4.97798324e-01 -3.19748163e-01 -7.67699420e-01 2.80946612e-01
-2.55075634e-01 1.47934186e+00 -1.68221712e-01 -7.02302605e-02
4.34720039e-01 4.70391005e-01 5.29177785e-01 -8.05273175e-01
-5.84281504e-01 -5.74623287e-01 4.39882070e-01 -3.51010859e-01
-3.47887307e-01 -3.08873177e-01 -1.24215317e+00 5.19990735e-02
-3.62931103e-01 7.83227205e-01 2.70470798e-01 1.55957997e+00
3.31990868e-01 3.53359759e-01 3.78486454e-01 3.24305773e-01
-9.84266400e-01 -8.89868081e-01 -1.13233715e-01 3.30813795e-01
7.37385035e-01 -3.27627599e-01 -4.16889548e-01 -4.02102545e-02] | [11.173632621765137, 7.977997303009033] |
14d6c172-fe3f-4924-8445-6211f197dc7d | multi-task-driven-feature-models-for-thermal | 1911.11384 | null | https://arxiv.org/abs/1911.11384v1 | https://arxiv.org/pdf/1911.11384v1.pdf | Multi-Task Driven Feature Models for Thermal Infrared Tracking | Existing deep Thermal InfraRed (TIR) trackers usually use the feature models of RGB trackers for representation. However, these feature models learned on RGB images are neither effective in representing TIR objects nor taking fine-grained TIR information into consideration. To this end, we develop a multi-task framework to learn the TIR-specific discriminative features and fine-grained correlation features for TIR tracking. Specifically, we first use an auxiliary classification network to guide the generation of TIR-specific discriminative features for distinguishing the TIR objects belonging to different classes. Second, we design a fine-grained aware module to capture more subtle information for distinguishing the TIR objects belonging to the same class. These two kinds of features complement each other and recognize TIR objects in the levels of inter-class and intra-class respectively. These two feature models are learned using a multi-task matching framework and are jointly optimized on the TIR tracking task. In addition, we develop a large-scale TIR training dataset to train the network for adapting the model to the TIR domain. Extensive experimental results on three benchmarks show that the proposed algorithm achieves a relative gain of 10% over the baseline and performs favorably against the state-of-the-art methods. Codes and the proposed TIR dataset are available at {https://github.com/QiaoLiuHit/MMNet}. | ['Nana Fan', 'Wei Liu', 'Qiao Liu', 'Yonsheng Liang', 'Zhenyu He', 'Xin Li', 'Di Yuan'] | 2019-11-26 | null | null | null | null | ['thermal-infrared-object-tracking'] | ['computer-vision'] | [ 1.24964051e-01 -5.64788401e-01 -2.09360838e-01 -6.03567302e-01
-8.10205281e-01 -5.16517341e-01 3.60875249e-01 -8.51663172e-01
-2.39294931e-01 2.33110994e-01 -9.24783200e-02 -8.09183866e-02
-8.74142051e-02 -3.77714485e-01 -5.06043315e-01 -1.17191291e+00
6.70793712e-01 1.91026628e-01 3.28070045e-01 5.95152788e-02
1.13285162e-01 4.49237347e-01 -1.80569613e+00 2.49278605e-01
8.34651589e-01 1.49164379e+00 2.73329079e-01 3.93084943e-01
-4.63489071e-02 5.86382151e-01 -3.58747333e-01 7.84719437e-02
5.73351860e-01 1.09627672e-01 -3.69242311e-01 -1.56662837e-01
7.56150961e-01 -3.12261879e-01 -5.12810290e-01 8.00906241e-01
4.23467636e-01 2.87240148e-01 5.17624736e-01 -1.32495880e+00
-6.11045659e-01 -1.26006573e-01 -8.68887722e-01 1.05174825e-01
-1.49228886e-01 4.13028449e-01 7.23082840e-01 -9.65069175e-01
-1.15313344e-01 1.38585973e+00 7.04843283e-01 5.67327559e-01
-7.45292664e-01 -1.08786798e+00 3.39030862e-01 1.31859407e-01
-1.31006837e+00 -5.39903581e-01 8.43331873e-01 -2.71648556e-01
3.80625039e-01 3.53126615e-01 9.45686996e-02 9.05705154e-01
1.58502534e-01 8.81313145e-01 1.09392798e+00 1.51448250e-02
-3.61967146e-01 -2.94287335e-02 4.02651548e-01 5.59442103e-01
3.55089307e-01 4.19522077e-01 -2.67570943e-01 1.73537228e-02
6.14998162e-01 3.12961817e-01 9.96416714e-03 -2.84914225e-01
-1.10063827e+00 5.78239024e-01 4.64069575e-01 2.69072771e-01
-3.94379869e-02 5.79767466e-01 3.49049419e-01 -1.54929766e-02
4.46758866e-01 -3.22056115e-01 -6.84533238e-01 1.02271937e-01
-3.37795049e-01 6.28807098e-02 2.71238107e-02 1.03943050e+00
1.19276261e+00 -1.54340953e-01 -5.96603155e-01 6.47738576e-01
7.24654734e-01 1.10200942e+00 2.07543030e-01 -7.78272986e-01
4.75838542e-01 5.33685029e-01 2.21322671e-01 -8.43224406e-01
-4.23551023e-01 -3.66555721e-01 -6.90475821e-01 1.44263551e-01
3.41944695e-01 -9.81729254e-02 -1.13569736e+00 1.50412083e+00
6.65844262e-01 4.19191658e-01 -3.39998454e-02 1.09435010e+00
1.06764102e+00 3.99372190e-01 8.33571479e-02 2.10706681e-01
1.55631173e+00 -1.03487575e+00 -5.95276237e-01 -5.61842799e-01
6.76366091e-01 -8.25472176e-01 8.94563496e-01 4.39870842e-02
-3.59612942e-01 -1.12628615e+00 -5.71000576e-01 2.47487128e-02
-3.92051905e-01 9.01825845e-01 8.60594988e-01 7.52134025e-01
-7.90902019e-01 1.19122900e-01 -6.59696102e-01 -1.63765863e-01
4.89756405e-01 5.08880734e-01 -1.07148625e-01 -3.57709050e-01
-1.07933843e+00 6.35130584e-01 2.57937640e-01 9.06235397e-01
-7.31112540e-01 -5.09303689e-01 -7.54349768e-01 -3.96335512e-01
3.22545111e-01 -5.67000568e-01 1.04106355e+00 -7.30050504e-01
-1.47145331e+00 7.08719194e-01 -2.89987922e-01 1.99932352e-01
1.05427265e-01 -3.50095481e-01 -6.20510042e-01 -9.97342467e-02
9.24176127e-02 4.43496048e-01 1.13787746e+00 -1.30572557e+00
-1.04153395e+00 -3.29650104e-01 -5.49400644e-03 3.42112780e-02
-2.01508552e-01 2.08561257e-01 -7.35862255e-01 -2.69080997e-01
-4.43539321e-02 -1.18092179e+00 -6.34320453e-02 -1.46871330e-02
-3.30106020e-01 -7.40000844e-01 1.40030253e+00 -1.88807756e-01
9.11408544e-01 -2.24184990e+00 -3.00948143e-01 -3.96107510e-02
3.34146500e-01 5.00787497e-01 -2.63640940e-01 7.06037134e-02
4.74291891e-02 -2.02793762e-01 3.48613620e-01 -4.93477941e-01
1.13166720e-01 3.46444431e-03 -3.12775910e-01 6.51969433e-01
2.05375671e-01 1.02993917e+00 -8.18380117e-01 -5.15552223e-01
5.98360956e-01 4.97801632e-01 1.91226691e-01 3.47797155e-01
7.49183446e-02 7.57352531e-01 -1.16782379e+00 9.43626463e-01
1.03796589e+00 -2.96324193e-01 -1.48102567e-01 -1.11449397e+00
-2.58358628e-01 -2.29434446e-02 -8.32210004e-01 1.31247234e+00
-4.74627763e-01 3.29579711e-01 -3.03331226e-01 -7.34031856e-01
1.24620986e+00 3.60619240e-02 5.82720995e-01 -7.46106029e-01
4.11498249e-01 6.40974566e-02 -2.34587654e-01 -2.88636923e-01
5.78063309e-01 1.64158672e-01 -3.80667925e-01 3.34233820e-01
-2.94728547e-01 3.10158551e-01 -1.87200010e-01 -2.32247412e-01
8.81780386e-01 5.19649446e-01 -4.29619819e-01 1.39198720e-01
6.65772438e-01 -7.23651946e-02 1.03410733e+00 7.76079714e-01
-4.41419005e-01 5.75287461e-01 -3.12660873e-01 -6.70387208e-01
-5.03261626e-01 -8.84117126e-01 -2.05977157e-01 1.31388879e+00
5.65975904e-01 1.20794423e-01 -1.20547973e-01 -8.25520337e-01
7.90368244e-02 1.35192588e-01 -7.36875415e-01 -3.11229944e-01
-5.75132132e-01 -6.60423338e-01 5.62244415e-01 7.94507921e-01
7.17790902e-01 -8.85945201e-01 -6.29383266e-01 -2.61759698e-01
-3.34510744e-01 -1.43284917e+00 -5.85556626e-01 2.29794547e-01
-8.13001096e-01 -9.90567625e-01 -5.66131651e-01 -5.49823046e-01
4.81564879e-01 9.53776360e-01 7.45280981e-01 2.31817424e-01
-4.63851988e-01 3.66391361e-01 -4.13518786e-01 -3.46781671e-01
4.51856077e-01 3.62101779e-03 1.66984588e-01 3.87044758e-01
8.57269406e-01 3.26348692e-02 -6.49975657e-01 7.09567606e-01
-7.42249548e-01 -8.69182497e-02 8.76202762e-01 5.94825268e-01
5.63058197e-01 -2.01281626e-02 1.47908002e-01 -3.68714780e-01
-3.43412571e-02 -1.89444125e-01 -8.10034513e-01 3.23414177e-01
-2.38270730e-01 6.96307123e-02 5.40618777e-01 -3.05035770e-01
-1.33812749e+00 5.80955327e-01 2.61412352e-01 -9.13699508e-01
-3.63141030e-01 8.08684453e-02 -3.01369429e-01 -5.19476354e-01
1.40215233e-01 1.61155626e-01 -2.67890602e-01 -7.48221099e-01
5.31157196e-01 6.47219002e-01 5.20163059e-01 -6.82756543e-01
1.48149908e+00 7.46810615e-01 2.95739211e-02 -4.32896852e-01
-1.40381384e+00 -9.83828902e-01 -8.39605629e-01 -3.68199259e-01
1.02366602e+00 -1.23192918e+00 -9.99066234e-01 6.69552565e-01
-9.16992188e-01 -3.16616982e-01 6.35384470e-02 4.41864401e-01
-2.71461487e-01 4.78984237e-01 -1.93117604e-01 -8.90134931e-01
-4.57887888e-01 -1.01576328e+00 1.82440722e+00 7.94009328e-01
7.36679077e-01 -7.51891434e-01 2.38142535e-01 5.24992645e-01
3.88005227e-01 8.55660513e-02 1.66890994e-01 -2.35315114e-02
-8.00333917e-01 -2.14973345e-01 -7.21879661e-01 1.99903935e-01
4.59751785e-01 7.95907602e-02 -1.37244964e+00 -3.67885053e-01
-4.75554079e-01 -6.12267852e-01 1.23285592e+00 2.77249515e-01
1.33129704e+00 3.77625257e-01 -8.95327449e-01 9.80489910e-01
1.33927786e+00 1.73470527e-02 6.25623107e-01 3.14613223e-01
1.32168150e+00 4.21670258e-01 1.48507607e+00 3.04021508e-01
5.99553704e-01 1.01396537e+00 5.02322495e-01 -2.54289538e-01
-7.59786926e-04 1.16974182e-01 4.32598889e-01 3.99131089e-01
-1.83623940e-01 1.51353683e-02 -7.29708493e-01 3.22351903e-01
-2.19536662e+00 -8.98174226e-01 -3.35670918e-01 2.01142740e+00
4.19720501e-01 -5.96334487e-02 2.56294429e-01 -4.44116473e-01
7.38090098e-01 2.43329182e-01 -6.28347635e-01 8.02077055e-02
2.98993196e-02 -5.68119297e-03 1.02897191e+00 -8.92652571e-02
-1.56710041e+00 1.26439750e+00 5.08700228e+00 9.23541784e-01
-1.10669971e+00 -6.34634402e-03 2.50699371e-01 2.34237164e-01
-5.04503660e-02 6.90322220e-02 -1.40097666e+00 3.88026267e-01
9.22259390e-01 2.79426426e-01 1.72569245e-01 7.16183722e-01
2.22864032e-01 1.12586074e-01 -6.11632705e-01 1.01710820e+00
-1.72458634e-01 -8.42757165e-01 -5.09209275e-01 1.06250055e-01
4.07169312e-01 4.20750141e-01 2.40047649e-01 4.35302287e-01
4.25657302e-01 -8.05230856e-01 5.59052110e-01 9.30447698e-01
9.69897330e-01 -6.11555994e-01 7.85847783e-01 -4.69960868e-02
-2.14075875e+00 -1.90347016e-01 -8.86217654e-01 4.45810407e-01
-1.67468563e-01 5.02163947e-01 -2.09079906e-01 1.03554523e+00
1.07626283e+00 1.02213824e+00 -7.74322093e-01 9.76745963e-01
-4.66750599e-02 3.85437906e-01 -2.50925839e-01 3.00318569e-01
2.82337636e-01 -1.39329776e-01 -1.13282092e-02 9.25728738e-01
1.07127815e-01 9.42635909e-02 4.21729475e-01 7.39323854e-01
2.48208791e-01 -6.57554328e-01 -5.39396942e-01 5.79968132e-02
4.88485307e-01 1.87906909e+00 -3.53009969e-01 -7.95522109e-02
-6.89136863e-01 8.07872176e-01 1.67131305e-01 4.48945165e-01
-1.20666575e+00 -5.80599189e-01 1.12196767e+00 -5.33271492e-01
8.09010565e-01 -3.38010460e-01 1.26067698e-01 -1.00794232e+00
-1.12408578e-01 -5.57233274e-01 2.91787207e-01 -8.64710927e-01
-1.41775715e+00 6.74602985e-01 -7.13535845e-02 -1.65182257e+00
1.30671918e-01 -9.18673337e-01 -6.79548025e-01 1.10975730e+00
-1.95035458e+00 -1.71730053e+00 -1.02229857e+00 7.95199454e-01
1.29923016e-01 2.08572727e-02 4.43032384e-01 3.91063988e-01
-8.72493505e-01 8.19656372e-01 2.52170861e-01 3.32993329e-01
9.17987883e-01 -7.54842341e-01 5.59341967e-01 6.78288817e-01
-3.09506536e-01 6.32156491e-01 2.34518260e-01 -4.92381960e-01
-1.95137191e+00 -1.60779810e+00 5.05986452e-01 -8.75047863e-01
5.10983944e-01 -4.38900739e-01 -7.69292057e-01 5.73238313e-01
-2.16815919e-01 6.63527668e-01 3.76175582e-01 1.26375973e-01
-5.63667536e-01 -6.11846268e-01 -8.92660081e-01 7.34023154e-02
1.07533610e+00 -6.72617197e-01 -3.61850262e-01 3.32881510e-01
6.97471619e-01 -3.43749851e-01 -8.91825974e-01 4.31691408e-01
8.68471086e-01 -7.18849897e-01 1.25922179e+00 -2.76922464e-01
-2.59567350e-01 -9.25869226e-01 -8.76181945e-02 -8.12830865e-01
-4.93937463e-01 -3.18990111e-01 4.11619730e-02 1.34351611e+00
-2.01517731e-01 -6.76933289e-01 7.76947916e-01 4.92512614e-01
-4.14250314e-01 -4.03255552e-01 -6.77181482e-01 -9.43274736e-01
-3.44351649e-01 -4.09112304e-01 6.69247270e-01 5.71912229e-01
-7.01276481e-01 2.22196892e-01 -7.60092616e-01 4.26782638e-01
1.03041220e+00 6.72942162e-01 1.08039176e+00 -1.41202879e+00
-4.61355150e-02 1.94947086e-02 -1.88682020e-01 -1.24449337e+00
3.24282169e-01 -5.96701443e-01 5.94413936e-01 -1.36531949e+00
2.87283242e-01 -1.01420760e+00 -6.63778543e-01 7.89845586e-01
-4.36304748e-01 4.73426044e-01 2.98450559e-01 4.11000013e-01
-1.13115907e+00 7.58043528e-01 1.12488151e+00 -1.50356382e-01
4.59253900e-02 2.15435654e-01 -8.00090075e-01 4.44910884e-01
8.28526378e-01 -5.41944027e-01 -1.65647909e-01 -6.79266691e-01
-1.54069781e-01 -3.90797406e-01 6.41852379e-01 -1.03792846e+00
2.90298253e-01 -4.46327925e-01 5.36683142e-01 -1.16159141e+00
4.10778284e-01 -1.09128201e+00 6.47796467e-02 1.83686167e-01
1.19026043e-01 -2.58249402e-01 4.32471573e-01 7.67986536e-01
1.23779535e-01 2.77175337e-01 6.56187534e-01 2.43405864e-01
-1.17041910e+00 7.46565163e-01 7.55619584e-03 -1.73720732e-01
7.84435451e-01 -3.67255747e-01 -6.73997521e-01 6.17503300e-02
7.23161176e-02 4.34477657e-01 3.21112901e-01 7.99988985e-01
4.50484484e-01 -1.50767601e+00 -3.02320361e-01 1.01650819e-01
6.38883293e-01 -8.53379965e-02 4.22507077e-01 1.07838392e+00
1.97686836e-01 7.27960289e-01 -2.38055348e-01 -9.05984938e-01
-1.34308612e+00 3.88743788e-01 5.09330928e-01 -1.54711872e-01
-3.88759971e-01 8.34317625e-01 8.29531133e-01 -6.63411677e-01
8.67495164e-02 -4.70091224e-01 -2.34269917e-01 -3.67830366e-01
5.30542493e-01 1.51021138e-01 -1.32384062e-01 -9.28534210e-01
-8.55188966e-01 1.31105936e+00 -6.25631511e-02 7.13149309e-01
1.08502352e+00 -5.02092481e-01 1.98035449e-01 2.89152920e-01
1.20137107e+00 -3.61968815e-01 -1.57934821e+00 -5.99231660e-01
-9.44656283e-02 -7.66737580e-01 2.68745482e-01 -6.26487792e-01
-1.33444238e+00 8.26902866e-01 1.06643403e+00 -3.90178978e-01
1.50317121e+00 4.49688397e-02 8.61894667e-01 4.92875099e-01
4.72293615e-01 -9.11445320e-01 1.02788024e-01 6.51451826e-01
1.89789057e-01 -1.51861978e+00 -1.11522295e-01 -3.32416236e-01
-6.57804012e-01 1.11239588e+00 8.85655940e-01 -1.26330674e-01
3.32611471e-01 8.09473768e-02 3.96847159e-01 -3.99375290e-01
-5.80110013e-01 -7.79959381e-01 7.04708099e-01 8.51919711e-01
5.02472997e-01 -4.33377326e-02 -2.36163978e-02 3.23888868e-01
5.92828453e-01 1.57084122e-01 -1.99117541e-01 7.66743362e-01
-6.47201002e-01 -1.21668410e+00 -5.13201654e-01 3.96736175e-01
-1.70102760e-01 -8.95735063e-03 -3.20249021e-01 6.15634382e-01
2.10349917e-01 1.11307871e+00 -4.25691158e-02 -9.93088126e-01
2.56802082e-01 -4.44152713e-01 3.79589319e-01 -4.07947212e-01
-5.23236156e-01 9.75921005e-02 -7.80372741e-03 -9.87803757e-01
-6.67236984e-01 -6.43351555e-01 -1.00373340e+00 -2.47365832e-01
-4.85589921e-01 -8.10906067e-02 5.77801466e-01 1.09089339e+00
4.21634823e-01 5.70712447e-01 9.95517373e-01 -1.09129369e+00
-4.73531634e-01 -7.11518109e-01 -4.49745238e-01 7.18804374e-02
4.72944826e-01 -1.07289493e+00 -2.32164845e-01 -3.11717063e-01] | [6.353494644165039, -2.2246108055114746] |
79a17966-e34a-44e8-a220-198f66ba394d | the-singing-voice-conversion-challenge-2023 | 2306.14422 | null | https://arxiv.org/abs/2306.14422v2 | https://arxiv.org/pdf/2306.14422v2.pdf | The Singing Voice Conversion Challenge 2023 | We present the latest iteration of the voice conversion challenge (VCC) series, a bi-annual scientific event aiming to compare and understand different voice conversion (VC) systems based on a common dataset. This year we shifted our focus to singing voice conversion (SVC), thus named the challenge the Singing Voice Conversion Challenge (SVCC). A new database was constructed for two tasks, namely in-domain and cross-domain SVC. The challenge was run for two months, and in total we received 26 submissions, including 2 baselines. Through a large-scale crowd-sourced listening test, we observed that for both tasks, although human-level naturalness was achieved by the top system, no team was able to obtain a similarity score as high as the target speakers. Also, as expected, cross-domain SVC is harder than in-domain SVC, especially in the similarity aspect. We also investigated whether existing objective measurements were able to predict perceptual performance, and found that only few of them could reach a significant correlation. | ['Tomoki Toda', 'Jiatong Shi', 'Songxiang Liu', 'Lester Phillip Violeta', 'Wen-Chin Huang'] | 2023-06-26 | null | null | null | null | ['voice-conversion', 'voice-conversion'] | ['audio', 'speech'] | [-1.09712325e-01 -2.83766001e-01 2.94414610e-01 4.27127033e-02
-1.43009245e+00 -1.03548753e+00 7.39036083e-01 -1.57562569e-01
-3.78944993e-01 6.94341600e-01 5.50240815e-01 -2.16141671e-01
2.29072765e-01 -4.38520908e-02 -3.79534841e-01 -2.76013225e-01
3.18603843e-01 5.05496681e-01 4.23116356e-01 -4.37956989e-01
-5.33616804e-02 2.41041124e-01 -1.76747608e+00 4.06730950e-01
7.37027347e-01 5.95816135e-01 3.70493263e-01 1.23457205e+00
-5.12198247e-02 2.29816630e-01 -1.18076742e+00 -3.58099788e-01
1.87000260e-01 -8.46876442e-01 -9.26663876e-01 -4.35065866e-01
6.57503486e-01 4.00914848e-01 2.10098058e-01 7.75263608e-01
1.22028553e+00 3.13334435e-01 2.94880122e-01 -1.01032269e+00
-4.69971478e-01 4.67773050e-01 3.03944230e-01 1.56932026e-01
8.32919359e-01 3.19206804e-01 1.39148271e+00 -9.85412359e-01
8.33304584e-01 1.19427550e+00 8.45137060e-01 7.46163666e-01
-1.28329313e+00 -4.89173919e-01 -2.15753138e-01 1.15106858e-01
-1.14162278e+00 -9.28862631e-01 4.64724720e-01 -4.50672418e-01
1.01861072e+00 7.60407269e-01 7.48090565e-01 1.31512451e+00
-5.69749713e-01 4.25107121e-01 1.58973908e+00 -6.12870038e-01
3.23511958e-01 4.55420643e-01 -3.87354642e-01 -7.93029368e-02
-3.29996854e-01 4.00096744e-01 -8.47705603e-01 -1.01829141e-01
3.01138967e-01 -1.10527313e+00 -6.57317638e-01 3.17083955e-01
-1.53340352e+00 4.68513697e-01 -3.82865369e-02 7.71509230e-01
1.37413489e-02 -2.35723287e-01 5.34582853e-01 7.83982098e-01
2.04307348e-01 9.86331820e-01 -4.24844772e-01 -8.12415123e-01
-1.09379959e+00 3.71270388e-01 1.17661428e+00 8.14572275e-01
-6.38756678e-02 2.31752336e-01 -4.85768437e-01 1.33607006e+00
-2.00323045e-01 4.52679098e-01 7.68253863e-01 -1.23446405e+00
4.80470479e-01 -2.86371768e-01 3.60306143e-03 -3.93838435e-01
-1.41222239e-01 -5.48381448e-01 -3.93663883e-01 1.40758097e-01
5.67537248e-01 -2.53112137e-01 -3.69489789e-01 1.78617382e+00
-6.30879635e-03 6.45032004e-02 -4.88421284e-02 1.06552553e+00
1.00725198e+00 5.76934934e-01 -1.31658539e-01 -5.05450010e-01
1.25611341e+00 -1.08471704e+00 -9.24444675e-01 1.04060797e-02
8.10150504e-02 -1.48854673e+00 1.67629087e+00 6.04990125e-01
-1.40267730e+00 -1.01803041e+00 -1.12015307e+00 9.82899070e-02
-2.58396834e-01 4.31004539e-02 1.48648486e-01 9.80606735e-01
-1.45953512e+00 7.46520519e-01 -3.90132964e-01 -4.42085981e-01
-3.90014291e-01 -2.49141213e-02 -4.09031004e-01 4.13802743e-01
-1.14473295e+00 9.86422360e-01 -2.41919160e-01 -3.44896793e-01
-9.61809456e-01 -8.47149730e-01 -2.75335789e-01 -2.51362532e-01
1.30136058e-01 -3.70764822e-01 1.81015384e+00 -7.07657218e-01
-2.06200337e+00 9.69229698e-01 -2.79292792e-01 -1.81654021e-01
7.62087643e-01 -2.91748762e-01 -1.02511907e+00 -2.02023447e-01
8.31267759e-02 4.67187792e-01 8.55387568e-01 -1.30667722e+00
-6.50212467e-01 4.24027182e-02 -4.55572575e-01 2.87663192e-01
-1.14166349e-01 5.02411366e-01 -3.10715914e-01 -7.72561431e-01
-2.31100708e-01 -8.99397910e-01 3.56322110e-01 -5.08904159e-01
-4.99845564e-01 -1.35248914e-01 5.17022491e-01 -9.15404260e-01
1.16984713e+00 -2.26159525e+00 1.33258656e-01 -2.47624874e-01
1.27459347e-01 6.44006729e-01 -2.70796061e-01 5.96100152e-01
-1.05075546e-01 3.06399912e-01 -2.60733724e-01 -7.26572037e-01
2.02404544e-01 -1.22233637e-01 -4.78309244e-01 1.34381190e-01
3.75250988e-02 4.76369709e-01 -8.47377896e-01 -3.06343824e-01
-1.41520083e-01 2.35530823e-01 -6.68149292e-01 5.29387593e-01
2.98340693e-02 7.12324202e-01 5.84770620e-01 3.62823337e-01
5.24071753e-01 5.67725539e-01 1.06814489e-01 2.18576029e-01
-5.17290115e-01 7.30198622e-01 -1.04607189e+00 1.51543355e+00
-9.07970607e-01 1.10295737e+00 5.27653873e-01 -5.71262121e-01
9.18817639e-01 8.59183669e-01 6.49803430e-02 -5.78697145e-01
-3.16217959e-01 7.97540843e-01 3.68509680e-01 -1.88856915e-01
6.18408918e-01 -3.49580705e-01 3.21556404e-02 1.68721616e-01
4.05903727e-01 -9.11275864e-01 1.57396331e-01 -1.85275480e-01
9.04015958e-01 -1.93365291e-01 2.41254587e-02 -3.83998603e-01
6.29678488e-01 -4.58067134e-02 5.77195764e-01 7.05735326e-01
-5.31577885e-01 1.29801226e+00 2.79673249e-01 3.91020358e-01
-7.55463421e-01 -1.47601557e+00 3.05060986e-02 1.15786195e+00
-3.73333067e-01 -6.98345363e-01 -1.08479762e+00 -1.54658094e-01
-4.21922892e-01 8.60502601e-01 -1.07003465e-01 8.74170363e-02
-5.32077432e-01 6.95139691e-02 9.71439123e-01 2.44508266e-01
1.87099770e-01 -1.15923083e+00 -1.32280132e-02 2.35440627e-01
-4.18126136e-01 -1.34608269e+00 -1.00377679e+00 2.82834545e-02
-5.26085973e-01 -7.93452621e-01 -9.04745221e-01 -1.05098653e+00
-3.73649061e-01 9.26919430e-02 1.38053286e+00 -3.08401864e-02
-2.31937051e-01 4.87743288e-01 -4.66158003e-01 -4.30200398e-01
-1.04723430e+00 1.28062651e-01 5.38620472e-01 -3.71873200e-01
1.27835723e-03 -6.45639956e-01 -3.62766027e-01 5.02928078e-01
-3.26007366e-01 -4.33329105e-01 2.86719263e-01 7.25241840e-01
2.89626002e-01 -3.33478898e-01 7.94606268e-01 -4.63724792e-01
1.16582310e+00 8.97682160e-02 -3.88371140e-01 2.70887315e-02
-4.62343752e-01 -4.79267091e-01 9.44265544e-01 -4.31246728e-01
-8.49741578e-01 -2.74899870e-01 -6.13965333e-01 -2.31839031e-01
-3.93734455e-01 -9.26504470e-03 -2.23517269e-01 3.02344114e-01
8.13864231e-01 2.59485632e-01 -1.33806439e-02 -8.82999718e-01
3.53971660e-01 1.12953758e+00 1.07769179e+00 -5.77737212e-01
9.41088021e-01 -1.02358796e-01 -5.11371076e-01 -1.22140515e+00
-4.05028582e-01 -5.09862304e-01 -4.92086649e-01 -2.15221345e-01
9.22254145e-01 -9.20352697e-01 -4.53157783e-01 5.63140273e-01
-1.34051144e+00 -4.58655983e-01 -6.49983227e-01 8.21513772e-01
-6.56649709e-01 1.56361520e-01 -3.90369684e-01 -8.12132001e-01
-8.52289274e-02 -1.25638473e+00 8.57067943e-01 -2.62842737e-02
-5.65169215e-01 -1.01796198e+00 6.55691743e-01 5.13384700e-01
7.76473880e-01 -2.12422743e-01 6.26225233e-01 -9.27488685e-01
2.21349195e-01 8.95040929e-02 3.51592720e-01 9.06722724e-01
2.15042785e-01 2.14541852e-01 -1.44254947e+00 -3.46988708e-01
-1.21546209e-01 -3.72005165e-01 5.66961229e-01 1.66777149e-02
7.16597736e-01 1.13076732e-01 3.99349123e-01 3.89038652e-01
6.16513431e-01 7.09928125e-02 5.82201898e-01 3.54293101e-02
2.19510630e-01 7.46640682e-01 4.72554654e-01 -1.19274892e-02
5.13136424e-02 1.21232343e+00 -9.91465449e-02 -2.37623174e-02
-9.37804759e-01 -5.03774762e-01 7.75934398e-01 1.54478037e+00
-4.36101586e-01 -1.17143035e-01 -6.94503367e-01 6.82933986e-01
-9.61213708e-01 -8.28289449e-01 -3.52467805e-01 2.54476166e+00
1.15428782e+00 -3.74340126e-03 5.58434308e-01 4.28381741e-01
9.65466499e-01 1.43668786e-01 -7.78556317e-02 -8.18297744e-01
-2.67989665e-01 6.11909688e-01 -1.02276921e-01 7.78312802e-01
-6.96191251e-01 1.10447228e+00 7.52946615e+00 1.04519665e+00
-1.21478748e+00 3.43710870e-01 1.19812533e-01 -2.32194409e-01
-3.12083751e-01 -6.06871434e-02 -6.29493058e-01 3.16450745e-01
1.30513346e+00 -1.42907247e-01 8.80440652e-01 5.42921066e-01
3.10874730e-01 3.32083017e-01 -1.08325529e+00 9.42726195e-01
-2.69593336e-02 -1.01096642e+00 -3.90870512e-01 -6.75351694e-02
6.55955374e-01 1.95131227e-01 2.61689704e-02 6.95607007e-01
9.57096517e-02 -1.08198643e+00 1.07017100e+00 2.28551999e-01
1.33708692e+00 -4.08486009e-01 4.98176217e-01 1.27472267e-01
-1.22329926e+00 2.93317884e-01 -1.02464303e-01 -5.87282479e-02
1.67605668e-01 2.68691957e-01 -1.01962590e+00 3.43108565e-01
6.47829413e-01 1.37160957e-01 -5.81242621e-01 1.09194779e+00
-3.01368117e-01 1.16209078e+00 -1.62843466e-01 -8.06372985e-03
-2.27893755e-01 1.68467537e-02 1.14258945e+00 1.44044447e+00
4.86207604e-01 -3.15871626e-01 -1.56148106e-01 6.79583728e-01
-2.06632107e-01 2.97665626e-01 -2.02643216e-01 -2.24871680e-01
8.06008279e-01 1.19903886e+00 -2.55174637e-01 -1.16862737e-01
-1.77897930e-01 1.13267899e+00 6.81730360e-02 1.96587741e-01
-6.50138617e-01 -5.56702375e-01 9.42594528e-01 1.12555124e-01
1.82840392e-01 -2.83600152e-01 -2.37343505e-01 -8.04110229e-01
1.51599841e-02 -1.14987731e+00 -1.76345333e-02 -6.55426025e-01
-1.21850300e+00 9.83454764e-01 -2.89509624e-01 -1.41787112e+00
-4.68135953e-01 -5.39456606e-01 -1.00888109e+00 1.03690481e+00
-1.38722551e+00 -4.85806048e-01 -3.07099462e-01 6.15181386e-01
6.98253572e-01 -6.68067157e-01 1.12583065e+00 3.89850855e-01
-2.18747199e-01 8.72838199e-01 1.85461730e-01 -2.82135904e-01
1.39238691e+00 -1.58045828e+00 7.10116923e-01 6.60933852e-01
6.17228508e-01 5.18352509e-01 9.29107785e-01 -2.10761875e-01
-1.05142581e+00 -8.50433767e-01 1.10090435e+00 -5.86792052e-01
6.12431705e-01 -5.95970750e-01 -6.94267452e-01 3.72877344e-02
4.77333009e-01 4.09919210e-02 8.08635056e-01 1.71393663e-01
-3.74675244e-01 -6.81030303e-02 -8.95354211e-01 4.76545960e-01
1.30469573e+00 -9.29286242e-01 -7.70018339e-01 1.92330405e-01
1.14446223e+00 -4.80797350e-01 -8.81057858e-01 1.16135264e-02
4.29783463e-01 -1.18286991e+00 8.64054561e-01 -5.80878973e-01
2.78992981e-01 -2.75663078e-01 -4.62363660e-01 -1.97285521e+00
-1.84569255e-01 -1.10406649e+00 2.66963571e-01 1.73162389e+00
7.06071317e-01 -6.18682563e-01 1.09640040e-01 -4.36960794e-02
-6.48966849e-01 1.24635361e-03 -1.15284467e+00 -1.35433352e+00
4.00338888e-01 -7.25380778e-01 5.31082749e-01 7.53173172e-01
-1.97200790e-01 4.85034525e-01 -2.05216348e-01 -1.39499187e-01
8.74875635e-02 -1.18814453e-01 8.34550023e-01 -1.26934755e+00
-7.36757100e-01 -6.75398052e-01 -7.69274682e-02 -6.36591613e-01
2.49583554e-03 -1.04365802e+00 2.99270064e-01 -1.20351219e+00
-3.38685036e-01 -1.61712557e-01 -6.42301217e-02 2.22907253e-02
-1.98343679e-01 4.27294433e-01 7.68107235e-01 2.72941411e-01
-3.19337487e-01 4.84138250e-01 1.37539232e+00 1.09596200e-01
-5.01972318e-01 3.96305174e-01 -7.36050904e-01 4.38536465e-01
7.46789753e-01 -2.21339837e-01 -1.44778684e-01 -2.58854866e-01
-3.81197751e-01 8.09325650e-02 3.05649996e-01 -1.33558190e+00
1.79325730e-01 1.00320242e-01 -1.70334592e-01 -2.27584586e-01
7.11590886e-01 -2.37339497e-01 1.03214107e-01 2.36523539e-01
-4.67491388e-01 -2.10265175e-01 2.29784966e-01 1.70984983e-01
-5.68100274e-01 -1.12433009e-01 8.54749501e-01 9.74197984e-02
-4.31991965e-01 -3.34524184e-01 -5.14051974e-01 6.64407849e-01
4.68681574e-01 -7.47883832e-03 -2.12016255e-01 -6.91801727e-01
-8.19445372e-01 -2.40293071e-01 3.01237345e-01 6.89299107e-01
2.92917818e-01 -1.25343001e+00 -1.05508411e+00 2.95933615e-02
5.64101115e-02 -5.31272829e-01 1.03234224e-01 8.69510591e-01
-3.98247957e-01 5.27408838e-01 5.79559319e-02 -5.43872118e-01
-1.44336677e+00 -1.75967347e-02 4.65749770e-01 -5.56078181e-02
-2.51955390e-01 1.01082242e+00 -4.16790634e-01 -9.93794739e-01
3.77290159e-01 -1.08965777e-01 -1.02934457e-01 1.81182578e-01
5.25335908e-01 5.82203329e-01 4.95360643e-01 -7.46579409e-01
-3.95775080e-01 5.46199918e-01 4.97604072e-01 -8.69744301e-01
9.94679749e-01 7.22433552e-02 8.07884559e-02 8.13069820e-01
1.22752023e+00 7.43271351e-01 -8.34867120e-01 4.63009849e-02
-1.77273229e-01 -5.25105119e-01 1.06913865e-01 -1.12613082e+00
-6.87723994e-01 9.82191265e-01 6.33805394e-01 4.25916791e-01
9.62191641e-01 -1.19141169e-01 8.69534433e-01 1.60628527e-01
9.92724150e-02 -1.53950715e+00 -3.53358723e-02 7.74226785e-01
1.39099813e+00 -9.94876683e-01 -5.96119642e-01 -4.76968795e-01
-9.83346343e-01 9.30547833e-01 4.82248515e-01 2.35849917e-01
4.68756586e-01 9.99567956e-02 3.18781793e-01 3.41969043e-01
-8.64475965e-01 -4.02253181e-01 3.28088462e-01 1.09818792e+00
8.49514425e-01 3.98586750e-01 -2.63505399e-01 8.43981385e-01
-1.21001089e+00 -4.49681461e-01 4.81440067e-01 2.46733040e-01
-2.92840421e-01 -1.32693994e+00 -5.90524435e-01 -5.16130477e-02
-3.98811370e-01 -1.21188641e-01 -9.29391265e-01 7.26784587e-01
-4.85916771e-02 1.52134669e+00 -8.25385563e-03 -7.62505114e-01
8.30630660e-01 1.08259581e-01 3.03050756e-01 -7.69569218e-01
-1.00701821e+00 9.13410708e-02 5.33416152e-01 -3.77427280e-01
-5.99760041e-02 -8.69389713e-01 -8.29701483e-01 -2.19412163e-01
-9.79182199e-02 6.10925317e-01 9.18435752e-01 5.54940999e-01
1.79907516e-01 7.36169159e-01 9.84811604e-01 -8.44180226e-01
-8.35795581e-01 -1.24214971e+00 -6.29771650e-01 3.60585213e-01
4.26896304e-01 -4.01840776e-01 -8.26939523e-01 -1.51791107e-02] | [14.927760124206543, 6.438412189483643] |
f415371e-2e55-46f4-a009-b1a8a84f41ac | recognizing-unseen-objects-via-multimodal | 2306.08487 | null | https://arxiv.org/abs/2306.08487v2 | https://arxiv.org/pdf/2306.08487v2.pdf | Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation | Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously. Recently, the Knowledge Graph (KG) has been proven as an effective scheme for handling the zero-shot task with large-scale and non-attribute data. Prior studies always embed relationships of seen and unseen objects into visual information from existing knowledge graphs to promote the cognitive ability of the unseen data. Actually, real-world knowledge is naturally formed by multimodal facts. Compared with ordinary structural knowledge from a graph perspective, multimodal KG can provide cognitive systems with fine-grained knowledge. For example, the text description and visual content can depict more critical details of a fact than only depending on knowledge triplets. Unfortunately, this multimodal fine-grained knowledge is largely unexploited due to the bottleneck of feature alignment between different modalities. To that end, we propose a multimodal intensive ZSL framework that matches regions of images with corresponding semantic embeddings via a designed dense attention module and self-calibration loss. It makes the semantic transfer process of our ZSL framework learns more differentiated knowledge between entities. Our model also gets rid of the performance limitation of only using rough global features. We conduct extensive experiments and evaluate our model on large-scale real-world data. The experimental results clearly demonstrate the effectiveness of the proposed model in standard zero-shot classification tasks. | ['Enhong Chen', 'Nicholas Jing Yuan', 'Baoxing Huai', 'Qi Liu', 'Zhefeng Wang', 'Hongke Zhao', 'Zhi Li', 'Likang Wu'] | 2023-06-14 | null | null | null | null | ['knowledge-graphs'] | ['knowledge-base'] | [-2.08485529e-01 1.92148820e-01 -2.77508825e-01 -4.05537009e-01
-4.92713869e-01 -3.73448223e-01 6.42327130e-01 3.47793341e-01
-2.14853093e-01 4.80952233e-01 3.42290729e-01 1.33205950e-01
-2.79275477e-01 -1.10173893e+00 -8.12712431e-01 -6.15014911e-01
2.83246607e-01 3.32973748e-01 2.92778403e-01 -3.59539330e-01
-1.73380766e-02 7.13033974e-02 -1.69678330e+00 5.45283616e-01
7.84012139e-01 1.14503968e+00 2.50267893e-01 1.48748353e-01
-6.34045243e-01 8.23953032e-01 -2.82666087e-01 -9.38216746e-01
-9.65730101e-02 -1.67406604e-01 -7.55247414e-01 2.17423186e-01
6.94734931e-01 -1.91773161e-01 -6.30957603e-01 1.28708327e+00
5.16054392e-01 2.33050421e-01 5.25915205e-01 -1.47535849e+00
-1.46267629e+00 5.97663879e-01 -3.85081947e-01 1.76641434e-01
3.86322916e-01 5.63687533e-02 1.08911991e+00 -1.15357018e+00
6.66310430e-01 1.52242076e+00 3.05578530e-01 3.78773391e-01
-8.20725679e-01 -5.38123310e-01 1.22401580e-01 8.47724438e-01
-1.55152130e+00 -2.79796332e-01 9.54029083e-01 -3.71311277e-01
5.67943633e-01 4.01254231e-03 5.66369236e-01 1.09433949e+00
-1.12640418e-01 8.98556054e-01 8.09558928e-01 -3.30420107e-01
1.16415463e-01 3.89396399e-01 1.89975038e-01 8.92005026e-01
3.18257779e-01 -2.66811818e-01 -7.51852214e-01 1.41850248e-01
6.57042623e-01 4.07854229e-01 -5.17634094e-01 -8.34048212e-01
-1.47765005e+00 7.35401094e-01 9.33790922e-01 3.18085760e-01
-5.06530032e-02 1.78186558e-02 3.42579395e-01 3.08768928e-01
6.08630031e-02 1.32888258e-01 -2.68727779e-01 2.13337615e-01
-2.68359631e-01 -3.32833856e-01 5.56337059e-01 1.35270596e+00
1.17338812e+00 -5.64016737e-02 -3.07403564e-01 8.17581773e-01
2.83063382e-01 5.39127886e-01 6.76554620e-01 -5.72470367e-01
5.38479507e-01 1.19903636e+00 -1.12215161e-01 -1.36463869e+00
-1.86374247e-01 -4.95870590e-01 -8.59883070e-01 -2.16126800e-01
9.72482637e-02 1.21489681e-01 -8.38874757e-01 1.61218286e+00
4.28332090e-01 3.12178671e-01 3.10146302e-01 1.03810108e+00
1.44622958e+00 5.55909157e-01 1.13475598e-01 -1.40181789e-03
1.55156171e+00 -9.28552151e-01 -8.78662348e-01 -1.43011853e-01
4.11471814e-01 -2.66673684e-01 1.29493189e+00 -1.93886161e-01
-6.23885274e-01 -6.30844295e-01 -1.03707027e+00 -3.54882568e-01
-1.00631142e+00 -2.25639775e-01 6.73700511e-01 4.37901437e-01
-7.10021138e-01 2.36027971e-01 -2.66734660e-01 -6.02268159e-01
6.71549678e-01 8.43636692e-02 -6.89587772e-01 -5.36384881e-01
-1.56130290e+00 6.23656571e-01 9.24404860e-01 5.91073744e-02
-7.46805131e-01 -5.58376372e-01 -1.26614892e+00 3.81599277e-01
8.80529046e-01 -8.00276339e-01 6.95227802e-01 -9.82751608e-01
-1.01216280e+00 9.22060251e-01 6.33220896e-02 7.86449481e-03
1.76963970e-01 -1.24043617e-02 -7.37399757e-01 2.58371145e-01
7.59612769e-02 5.17903388e-01 1.01859581e+00 -1.56227028e+00
-5.54583669e-01 -6.11556888e-01 3.70114148e-01 3.56291860e-01
-7.98753440e-01 -4.57399756e-01 -6.53761923e-01 -5.19323826e-01
4.81211692e-02 -3.86838138e-01 3.37543041e-01 9.08672437e-02
-1.56717822e-01 -2.62695253e-01 9.18662846e-01 -3.51430625e-01
1.04438531e+00 -2.20877361e+00 2.37295240e-01 2.95068836e-04
5.22519588e-01 1.38055474e-01 -2.15826094e-01 4.16009754e-01
1.06548499e-02 -1.41257599e-01 -7.50061646e-02 1.68066531e-01
1.17441215e-01 3.29906911e-01 -2.72685766e-01 1.59744143e-01
8.35569948e-02 1.60958517e+00 -1.30413795e+00 -7.03579545e-01
1.87076852e-01 3.99729162e-01 -6.77901786e-03 1.90909743e-01
5.59313339e-04 3.77461012e-03 -4.42097843e-01 9.44553494e-01
5.36468089e-01 -6.18828118e-01 2.23665368e-02 -6.68397903e-01
4.24661964e-01 -7.08526254e-01 -1.08886611e+00 1.96750498e+00
-1.66958123e-01 3.74475092e-01 -2.95331657e-01 -1.12497759e+00
8.83742511e-01 2.13338867e-01 4.24104109e-02 -7.15251446e-01
2.94132739e-01 -1.46063760e-01 -2.78066188e-01 -9.12458837e-01
2.70278513e-01 -3.87630582e-01 -2.65331030e-01 4.98682261e-02
7.26860225e-01 2.57236719e-01 -1.28084913e-01 5.67391157e-01
7.86295593e-01 -1.51040882e-01 4.69683349e-01 1.86035351e-03
4.59307790e-01 -1.53386295e-01 4.99906749e-01 5.95310926e-01
-3.66245627e-01 2.80066520e-01 3.04884970e-01 -3.78710598e-01
-7.30912089e-01 -1.31716871e+00 -3.17300558e-02 1.30063117e+00
8.86214674e-01 -2.88547546e-01 -3.55723500e-01 -8.15103889e-01
2.80718088e-01 5.77726364e-01 -8.53038192e-01 -4.85169590e-01
8.09303373e-02 -4.47894275e-01 1.56578153e-01 5.37619591e-01
6.38562322e-01 -1.05878341e+00 -1.65866792e-01 -1.18891113e-02
-2.27214366e-01 -1.23151326e+00 -4.10771221e-01 -2.03986555e-01
-5.63391626e-01 -1.35041940e+00 -6.01569653e-01 -1.05289149e+00
6.52485132e-01 7.26270080e-01 1.16985428e+00 3.45426984e-02
-4.16514248e-01 9.43731368e-01 -6.96549475e-01 -2.38585517e-01
1.21087603e-01 -3.35707426e-01 -1.20566459e-02 6.20460391e-01
7.06051588e-01 -4.35373217e-01 -6.78175628e-01 2.90020734e-01
-1.11034822e+00 8.27415064e-02 7.56235719e-01 9.59795773e-01
5.05385220e-01 1.94353655e-01 9.09717023e-01 -8.69292557e-01
5.77088058e-01 -8.13904583e-01 -1.21182635e-01 8.18114638e-01
-3.24358970e-01 1.28373101e-01 4.64684546e-01 -3.60147834e-01
-1.25106347e+00 -2.57714003e-01 6.18357241e-01 -8.95465553e-01
-1.53492138e-01 6.16860867e-01 -7.05257952e-01 -2.56272048e-01
4.17545289e-01 3.08548570e-01 -1.63578808e-01 -2.43948579e-01
9.35525775e-01 6.13715231e-01 7.26333201e-01 -6.15795434e-01
7.99574554e-01 6.27615333e-01 -1.07349582e-01 -6.15330815e-01
-1.12032020e+00 -6.56441271e-01 -7.68710136e-01 -3.29249173e-01
9.29811299e-01 -1.07153499e+00 -8.15892816e-01 2.22557545e-01
-9.77656245e-01 2.56611943e-01 -3.36746365e-01 2.89819926e-01
-4.37798679e-01 5.18020332e-01 -3.43361527e-01 -5.13236582e-01
-8.94710869e-02 -6.64182901e-01 1.11122096e+00 4.13176090e-01
4.76473570e-01 -1.05438530e+00 -1.23451263e-01 4.96069521e-01
5.96833192e-02 1.78000838e-01 1.15525758e+00 -5.20816088e-01
-7.69057810e-01 -1.57231748e-01 -6.51859224e-01 7.37894475e-02
1.11382261e-01 -3.99460644e-01 -1.01448500e+00 -2.74127871e-01
-9.58582088e-02 -7.36527026e-01 1.04665983e+00 -2.60168076e-01
1.18492329e+00 -2.45465681e-01 -3.12132537e-01 4.42506075e-01
1.69435596e+00 -8.14763829e-02 4.84793931e-01 8.87109712e-02
1.19428194e+00 7.44969487e-01 6.04655206e-01 4.36289757e-01
8.10282052e-01 2.92313695e-01 6.40710890e-01 1.32839024e-01
-1.64126188e-01 -5.55328608e-01 8.82145017e-03 9.92490649e-01
-2.92822905e-02 -1.80683479e-01 -9.70952928e-01 6.70516551e-01
-2.13916779e+00 -1.20042562e+00 2.39998028e-01 2.07589078e+00
6.11047208e-01 -9.26569402e-02 -3.54004532e-01 -1.86015502e-01
1.01895714e+00 1.56860322e-01 -7.05797255e-01 1.67945698e-01
-3.74724150e-01 -3.57672364e-01 1.91844225e-01 1.09421186e-01
-1.10256648e+00 1.06518114e+00 4.75180864e+00 1.09754443e+00
-7.29153693e-01 2.52883494e-01 2.19839886e-01 1.39891647e-03
-5.36589980e-01 -1.23883918e-01 -6.01220429e-01 3.88075709e-01
3.10055971e-01 -4.36600357e-01 3.59538734e-01 8.19304824e-01
-4.61641014e-01 1.81765214e-01 -1.13962662e+00 1.55053723e+00
5.66972554e-01 -1.32285011e+00 5.87146878e-01 -1.68484733e-01
7.21759200e-01 -3.36352468e-01 4.80553322e-03 7.55474031e-01
1.16753891e-01 -9.96827900e-01 4.55953747e-01 8.75256836e-01
8.16174686e-01 -7.30345309e-01 7.24818170e-01 2.66017526e-01
-1.47161126e+00 -4.13570166e-01 -7.28143334e-01 1.09393805e-01
1.12623885e-01 3.96605253e-01 -5.11292994e-01 8.95230472e-01
7.31725097e-01 1.03223562e+00 -8.98994267e-01 8.81159961e-01
-1.59253180e-01 7.08181709e-02 3.07990909e-01 3.84980179e-02
1.72727734e-01 1.94726083e-02 2.98713952e-01 8.70740712e-01
2.05101877e-01 4.54961598e-01 1.51601806e-01 7.71273077e-01
-4.21140283e-01 2.31687099e-01 -8.27569187e-01 -2.43861675e-01
4.20306325e-01 1.39274204e+00 -5.09803414e-01 -5.17933428e-01
-8.72285306e-01 1.00981581e+00 8.45764995e-01 6.14089668e-01
-6.48197412e-01 -5.46996415e-01 3.84187967e-01 -1.41954139e-01
3.74448061e-01 1.05784610e-02 1.18692435e-01 -1.68527198e+00
1.30027868e-02 -4.46159244e-01 7.21746027e-01 -1.11539352e+00
-1.87835777e+00 4.80391055e-01 -1.63350075e-01 -1.31641877e+00
4.14001197e-01 -7.27053761e-01 -4.01180267e-01 4.19918656e-01
-1.65728676e+00 -1.50011992e+00 -8.26285422e-01 1.06923544e+00
4.75048363e-01 -3.07741404e-01 7.73149490e-01 2.24766687e-01
-4.18009043e-01 5.99038422e-01 1.10726006e-01 3.30553383e-01
8.75901580e-01 -1.26775849e+00 -1.40965477e-01 3.85181040e-01
2.50604600e-01 5.59242070e-01 3.55679005e-01 -7.81202555e-01
-1.79135835e+00 -1.05852616e+00 3.76470566e-01 -7.02479303e-01
9.66965497e-01 -2.71857411e-01 -1.25980246e+00 6.28762782e-01
1.76791742e-01 3.78996313e-01 9.28853512e-01 1.73417464e-01
-7.92535782e-01 -2.83480078e-01 -8.76037598e-01 3.89830947e-01
1.20273519e+00 -8.35945427e-01 -1.07238495e+00 1.74810588e-01
1.12127292e+00 -6.24062456e-02 -1.07964706e+00 4.59003329e-01
4.76041555e-01 -8.08972657e-01 9.28738654e-01 -9.75931764e-01
3.46382171e-01 -3.56957704e-01 -3.76909494e-01 -1.29951119e+00
-3.92588437e-01 1.70797426e-02 -4.37915742e-01 1.30850494e+00
3.96321565e-02 -4.12720859e-01 5.11966407e-01 5.87582469e-01
-4.57164198e-02 -5.46535492e-01 -8.51551175e-01 -6.78698838e-01
-3.24944288e-01 -1.89413264e-01 6.64916992e-01 1.58645415e+00
3.60116959e-01 7.46528924e-01 -3.80227745e-01 2.60294616e-01
9.04491067e-01 5.06937563e-01 5.76636732e-01 -1.41540873e+00
-5.19831516e-02 -2.62422681e-01 -1.09629869e+00 -6.30873263e-01
3.70650172e-01 -1.13083351e+00 -3.35872769e-01 -1.67922783e+00
7.55061865e-01 5.57739064e-02 -7.23207891e-01 5.96635640e-01
-4.74694788e-01 7.66809806e-02 2.32773677e-01 1.50713116e-01
-1.16130888e+00 1.00689745e+00 1.55724418e+00 -6.09248161e-01
2.53482193e-01 -7.09097147e-01 -6.80927813e-01 5.88488042e-01
4.86074477e-01 2.56162826e-02 -7.75644779e-01 -5.06889820e-01
5.00893414e-01 5.10585830e-02 7.60711133e-01 -6.55696094e-01
4.99667734e-01 -1.70966864e-01 4.59211558e-01 -3.63901943e-01
3.84313524e-01 -1.19241464e+00 -1.36140481e-01 -5.96593693e-02
-1.18080035e-01 -3.13644528e-01 -4.25419882e-02 1.24150729e+00
-5.14024138e-01 9.46007296e-02 5.85990131e-01 -1.69694364e-01
-1.52704668e+00 5.97845137e-01 4.63191956e-01 2.74215579e-01
1.24704385e+00 -2.58908093e-01 -7.71910310e-01 -3.25094789e-01
-9.10248756e-01 5.56751132e-01 4.22582448e-01 7.74535120e-01
9.81979609e-01 -1.81851113e+00 -3.00831616e-01 1.61865041e-01
9.49949563e-01 -1.30876854e-01 7.96557009e-01 5.57815790e-01
-9.16114450e-02 3.46116632e-01 -3.71685237e-01 -4.13113236e-01
-9.51107323e-01 1.33323717e+00 1.96560055e-01 3.74235511e-01
-6.35319054e-01 8.40934813e-01 6.79498553e-01 -3.70183229e-01
2.54613489e-01 1.20534427e-01 -4.35788393e-01 2.89469719e-01
5.90899825e-01 3.26041758e-01 -2.06022784e-01 -9.35349286e-01
-2.70488143e-01 6.96938455e-01 2.00961176e-02 2.98774749e-01
9.91839767e-01 -5.23847580e-01 -2.39486381e-01 8.61349165e-01
1.25220120e+00 -3.75192434e-01 -9.93475020e-01 -7.94310689e-01
-1.79845244e-01 -6.44533098e-01 4.42980453e-02 -6.51419818e-01
-1.01382494e+00 1.05830753e+00 5.34184694e-01 1.06643654e-01
9.04604614e-01 4.37157571e-01 7.11650610e-01 6.32726610e-01
5.87611496e-01 -1.06226456e+00 3.98987681e-01 2.63321996e-01
8.18386316e-01 -1.75538039e+00 -2.64115691e-01 -4.49449033e-01
-9.05414939e-01 1.04760993e+00 9.43614066e-01 2.26068988e-01
6.75607800e-01 -4.72467870e-01 -1.44600764e-01 -6.42051697e-01
-6.24085248e-01 -5.22957742e-01 5.57373166e-01 5.61286688e-01
-1.51573494e-01 1.57112494e-01 1.59476906e-01 9.04871821e-01
1.66592821e-01 -6.17006607e-02 1.93268061e-01 7.78088629e-01
-7.93009698e-01 -5.56780577e-01 -2.66557276e-01 3.68999481e-01
2.12538421e-01 -1.51666522e-01 -3.97213608e-01 5.90588152e-01
2.35848218e-01 8.24578345e-01 -1.26931886e-03 -3.99914443e-01
3.75399977e-01 1.46791384e-01 4.61411804e-01 -6.18039250e-01
1.05191007e-01 -3.77371669e-01 -3.28263223e-01 -5.53331077e-01
-4.85333741e-01 -6.29088283e-02 -1.24096370e+00 -1.69098660e-01
-1.20800577e-01 5.29756583e-02 2.24163026e-01 1.01599014e+00
4.63726550e-01 5.82913458e-01 4.39611375e-01 -4.20968920e-01
-1.96975395e-01 -5.76457500e-01 -8.99360061e-01 8.15389335e-01
2.09396094e-01 -1.14768291e+00 -2.07632259e-01 1.35493413e-01] | [10.191065788269043, 2.171614170074463] |
af700e02-4170-4869-8c48-37568a6a0b62 | aggressive-language-in-an-online-hacking | null | null | https://aclanthology.org/W18-5109 | https://aclanthology.org/W18-5109.pdf | Aggressive language in an online hacking forum | We probe the heterogeneity in levels of abusive language in different sections of the Internet, using an annotated corpus of Wikipedia page edit comments to train a binary classifier for abuse detection. Our test data come from the CrimeBB Corpus of hacking-related forum posts and we find that (a) forum interactions are rarely abusive, (b) the abusive language which does exist tends to be relatively mild compared to that found in the Wikipedia comments domain, and tends to involve aggressive posturing rather than hate speech or threats of violence. We observe that the purpose of conversations in online forums tend to be more constructive and informative than those in Wikipedia page edit comments which are geared more towards adversarial interactions, and that this may explain the lower levels of abuse found in our forum data than in Wikipedia comments. Further work remains to be done to compare these results with other inter-domain classification experiments, and to understand the impact of aggressive language in forum conversations. | ['Sergio Pastrana', 'Paula Buttery', 'Andrew Caines', 'Alice Hutchings'] | 2018-10-01 | null | null | null | ws-2018-10 | ['abuse-detection'] | ['natural-language-processing'] | [-2.53488868e-01 1.21597379e-01 -6.08581677e-02 -2.49617308e-01
-2.73881465e-01 -1.17478251e+00 9.33799982e-01 5.44147372e-01
-3.45703483e-01 7.37727821e-01 8.13351989e-01 -5.55863798e-01
1.12766765e-01 -7.24210262e-01 -2.21301720e-01 -9.57923084e-02
-1.78617343e-01 1.11425683e-01 8.58623162e-02 -6.78363442e-01
6.99019909e-01 1.42777279e-01 -6.92549646e-01 4.57299471e-01
8.37902188e-01 1.32714778e-01 -3.76934648e-01 7.58174241e-01
-4.04998869e-01 1.46422362e+00 -1.12670124e+00 -1.06344116e+00
1.54251635e-01 -4.17365283e-01 -1.15293229e+00 1.88766003e-01
7.02378869e-01 -5.55692196e-01 -5.19502461e-01 1.30408394e+00
2.49135911e-01 -5.52134626e-02 7.89542913e-01 -9.62113678e-01
-5.05936086e-01 6.82021916e-01 -8.24480057e-01 9.41358924e-01
8.06520283e-01 2.79957354e-01 9.15184081e-01 -2.88480610e-01
1.24030674e+00 1.48750734e+00 6.86743021e-01 4.48766023e-01
-1.32526422e+00 -7.22282827e-01 -2.63090968e-01 -4.07033622e-01
-8.17687750e-01 -3.36395025e-01 7.22775400e-01 -1.19175053e+00
7.63494968e-01 1.15802743e-01 6.18185878e-01 1.79836094e+00
3.91460389e-01 2.10576594e-01 1.01133049e+00 -1.13990329e-01
-6.57535018e-03 5.66916049e-01 5.87731481e-01 6.68533981e-01
5.75980961e-01 -5.33212066e-01 -4.48527306e-01 -9.84552920e-01
3.76710355e-01 -2.64602274e-01 -3.58109534e-01 2.24912524e-01
-6.63552046e-01 1.58710063e+00 2.02349037e-01 7.30035186e-01
-2.92648435e-01 -2.68913478e-01 1.21932101e+00 6.32779777e-01
8.08854699e-01 1.00351584e+00 -1.02012642e-01 -7.81988621e-01
-6.50839269e-01 5.21328807e-01 1.44441068e+00 4.00916189e-01
6.04917049e-01 -3.17876667e-01 3.65438759e-01 1.33320534e+00
-5.57053275e-03 3.52855213e-02 3.59883666e-01 -1.10841429e+00
1.02775729e+00 5.04387975e-01 4.45008278e-02 -1.48523700e+00
-8.55132490e-02 -1.58887535e-01 -8.06261748e-02 6.90560564e-02
8.44142795e-01 -6.01893544e-01 -1.51946306e-01 1.60485590e+00
4.00263295e-02 -7.06509233e-01 -3.99807721e-01 4.43474561e-01
3.40124309e-01 3.69021386e-01 2.87575245e-01 -1.14273325e-01
1.25138366e+00 -2.61340469e-01 -7.19061852e-01 -3.60503405e-01
1.10690916e+00 -8.54671657e-01 1.07032728e+00 2.70694107e-01
-7.80481637e-01 2.53130138e-01 -1.08316731e+00 -9.71545801e-02
-5.62475681e-01 -8.68229449e-01 4.48314190e-01 1.11103821e+00
-6.02083504e-01 6.66172922e-01 -2.77719200e-01 -7.67611384e-01
4.82594669e-01 -3.72123390e-01 -5.76426089e-01 1.54240906e-01
-1.29023409e+00 1.28583252e+00 1.56629384e-01 -7.29522049e-01
-5.05329907e-01 -4.66266274e-01 -8.39572847e-01 -4.77402687e-01
2.37085715e-01 3.83260138e-02 1.20467198e+00 -1.20608318e+00
-8.60220611e-01 1.19674897e+00 2.62008756e-01 -3.25479299e-01
7.14513719e-01 -2.77276546e-01 -2.78344810e-01 2.47639135e-01
4.13818389e-01 -5.19042276e-02 6.55740440e-01 -1.14245725e+00
-1.71149939e-01 -5.03980100e-01 6.58530414e-01 -1.64999485e-01
-7.98086286e-01 8.62201631e-01 4.85558391e-01 -6.60517335e-01
-5.61399221e-01 -7.58685768e-01 1.21929228e-01 -2.80974090e-01
-5.79328954e-01 -1.80795997e-01 9.70284045e-01 -1.13999164e+00
1.73398030e+00 -1.97461128e+00 -5.97076975e-02 1.78151175e-01
7.01617062e-01 1.98814273e-01 3.35840017e-01 1.04564881e+00
-5.03615104e-02 8.57263803e-01 -2.05987558e-01 -1.43991694e-01
-1.23447545e-01 1.91591591e-01 -3.86014640e-01 8.27558219e-01
-4.15491611e-02 2.67152190e-01 -9.16394114e-01 -5.56563258e-01
-2.96742737e-01 -5.63625731e-02 -5.86834848e-01 -9.14694462e-03
1.13203146e-01 1.38997003e-01 -4.30503696e-01 4.74342227e-01
4.66006130e-01 2.33054981e-02 2.39898916e-02 5.72564244e-01
-3.75510544e-01 8.41304839e-01 -3.07978362e-01 9.53110695e-01
-3.11765730e-01 1.34696376e+00 5.59816658e-01 -4.24091130e-01
6.31110847e-01 1.49254337e-01 -1.96406916e-02 -2.44268924e-01
4.45609331e-01 1.60902679e-01 5.11107981e-01 -7.49745190e-01
5.51852584e-01 -2.41043955e-01 -1.83977142e-01 9.14810181e-01
-9.24317259e-03 -1.73454717e-01 4.25616622e-01 7.69955575e-01
1.52744710e+00 -5.31849563e-01 4.43619847e-01 -3.95271957e-01
1.32958129e-01 1.38134450e-01 4.00128156e-01 7.63857961e-01
-5.92181742e-01 1.57733068e-01 1.35642707e+00 -2.65228361e-01
-1.23542130e+00 -7.60874927e-01 -5.39896727e-01 1.07122648e+00
-1.75181150e-01 -8.04076195e-01 -1.00968194e+00 -1.00429046e+00
8.82321373e-02 7.72247970e-01 -6.62658691e-01 6.10742457e-02
-4.37859654e-01 -4.70820308e-01 1.01073003e+00 9.57301855e-02
4.71649885e-01 -8.00084233e-01 -3.45084488e-01 2.25899890e-01
-2.28963554e-01 -1.05469847e+00 -3.82563055e-01 -8.86520296e-02
-5.44184029e-01 -1.33790457e+00 -2.30402604e-01 -1.86456501e-01
4.12280917e-01 -1.19506493e-01 9.22082484e-01 5.10787010e-01
-2.56475985e-01 2.90622026e-01 -7.97780216e-01 -5.74582517e-01
-9.89917099e-01 1.62041351e-01 -3.97579595e-02 -3.32028866e-01
5.55573940e-01 -6.53704405e-01 5.90782352e-02 2.26747915e-02
-9.27412033e-01 -7.13072002e-01 -8.40977654e-02 7.02371359e-01
-1.05930352e+00 -2.21997023e-01 3.32274526e-01 -1.59823120e+00
1.22677827e+00 -1.33068848e+00 9.63859335e-02 -4.36531305e-01
-1.50463641e-01 -5.93868911e-01 7.22656488e-01 -4.06060278e-01
-9.84746099e-01 -8.66509974e-01 -1.31905168e-01 1.48210093e-01
-3.45211744e-01 3.64766032e-01 5.19102573e-01 -1.99957833e-01
1.21102750e+00 -4.05478299e-01 2.58782953e-01 -4.78773594e-01
-3.16476882e-01 1.08943927e+00 -1.51951402e-01 -6.78615868e-01
1.06143963e+00 2.18413338e-01 -7.47215807e-01 -1.34837580e+00
-7.00566709e-01 -5.38380325e-01 -3.23040098e-01 -3.61112654e-01
1.01674080e+00 -6.70497298e-01 -3.53963643e-01 5.24416864e-01
-1.41165936e+00 -4.40952510e-01 4.95059758e-01 1.11841790e-01
-1.08642697e-01 8.81268680e-01 -1.47817218e+00 -1.06322730e+00
-1.93024818e-02 -7.92114258e-01 4.08214450e-01 -6.87875375e-02
-1.18762970e+00 -1.23920250e+00 5.36104798e-01 6.55314207e-01
4.14971262e-01 4.78158385e-01 1.19761658e+00 -1.21725476e+00
2.19191641e-01 -2.48790741e-01 1.59609672e-02 3.83609563e-01
2.43493930e-01 5.07122338e-01 -7.35015571e-01 -4.25351225e-02
1.92088693e-01 -8.82325172e-01 3.27563465e-01 -5.10390520e-01
4.95864481e-01 -7.74281204e-01 -1.72093421e-01 -3.00966620e-01
1.16541481e+00 1.55713782e-01 7.05467939e-01 6.49333775e-01
3.12846184e-01 1.11140335e+00 2.51620233e-01 6.52292609e-01
-9.21207964e-02 4.21931386e-01 2.03177378e-01 3.74251992e-01
4.03211445e-01 -1.81940645e-01 7.09353983e-01 5.57487547e-01
1.62438810e-01 -2.42637396e-01 -1.23542356e+00 5.07468045e-01
-1.42822611e+00 -1.47897935e+00 -4.59100544e-01 1.67301488e+00
8.29815745e-01 3.77902657e-01 6.21468008e-01 7.45908394e-02
8.73929679e-01 5.52766144e-01 4.42561843e-02 -1.14413011e+00
2.44062230e-01 4.55579460e-02 2.56109953e-01 6.90592051e-01
-1.03879905e+00 4.75233495e-01 6.69175339e+00 5.42557716e-01
-8.32615077e-01 4.87215519e-01 5.40808737e-01 -2.61741161e-01
-1.93510965e-01 -2.09745303e-01 -2.90504068e-01 9.58931029e-01
9.79671061e-01 -4.82260138e-02 4.35649842e-01 8.80685687e-01
1.03052735e-01 -2.08988264e-01 -8.79089832e-01 4.98433143e-01
1.40261725e-01 -9.29936528e-01 -4.61389333e-01 3.69053245e-01
3.94629210e-01 1.78273827e-01 -1.46972299e-01 3.92474860e-01
5.67618132e-01 -9.95689213e-01 7.11647332e-01 -1.98166400e-01
1.77788571e-01 -6.05921626e-01 8.41298521e-01 6.52609348e-01
-1.92157820e-01 -2.15048388e-01 -2.18245283e-01 -6.46397769e-01
2.04380482e-01 6.03602707e-01 -7.43209660e-01 -4.65180390e-02
8.13403547e-01 5.30222416e-01 -6.41253471e-01 5.87432444e-01
-8.90781954e-02 8.32384706e-01 -1.27797082e-01 -3.81278217e-01
4.20652419e-01 -3.86276007e-01 1.05933392e+00 1.60588777e+00
-4.28618133e-01 -5.41821495e-02 -1.06389068e-01 6.64895356e-01
-2.64942944e-01 -1.27305568e-03 -1.30566859e+00 -8.17753732e-01
5.51100373e-01 1.43907475e+00 -4.31899041e-01 6.19601160e-02
-6.07733130e-01 8.45480859e-01 8.50808978e-01 1.53124973e-01
-6.99492216e-01 -5.47782123e-01 9.75530863e-01 7.60408878e-01
-1.41851157e-01 -4.26486135e-01 -2.67694056e-01 -1.17011166e+00
-8.05065315e-03 -1.12300670e+00 3.09376717e-01 -3.31352472e-01
-1.85646105e+00 2.72981435e-01 5.56171164e-02 -6.18546367e-01
-4.08732504e-01 -7.10737407e-01 -1.07923782e+00 6.49262547e-01
-6.70814991e-01 -3.97439927e-01 9.88217723e-03 3.13965797e-01
3.46787333e-01 -2.25187913e-02 4.73791689e-01 3.48498851e-01
-5.73007345e-01 2.80314684e-01 -3.43002915e-01 8.12411904e-01
8.57480705e-01 -1.11495578e+00 2.07948744e-01 6.42771602e-01
-3.28027219e-01 1.13743305e+00 1.11864340e+00 -9.46410656e-01
-7.76053429e-01 -4.81909096e-01 7.14676559e-01 -1.00788271e+00
1.54619956e+00 -4.65248019e-01 -1.03300595e+00 9.18160975e-01
7.84285069e-01 -5.20359159e-01 1.09661329e+00 4.80973423e-01
-8.65754187e-01 7.67215371e-01 -1.45059812e+00 5.89575768e-01
1.19081354e+00 -8.72092664e-01 -9.43935454e-01 6.72605217e-01
3.83887231e-01 -2.04327509e-01 -7.15923846e-01 -4.91343856e-01
2.24505022e-01 -1.16397536e+00 3.09359312e-01 -1.03479242e+00
1.10289335e+00 3.89271736e-01 1.46234185e-01 -1.24655509e+00
-2.45489076e-01 -6.75111115e-01 2.87493527e-01 1.68753338e+00
5.98067284e-01 -8.28179121e-01 4.67374235e-01 7.65940011e-01
-1.06967846e-03 -4.35970753e-01 -8.16396475e-01 -3.96372736e-01
5.72002113e-01 -1.53437406e-01 -2.65858263e-01 1.76597548e+00
5.14772654e-01 3.94655913e-01 -5.35449497e-02 -3.85642380e-01
3.54823172e-01 -7.72214890e-01 6.86320662e-01 -1.22194290e+00
-3.80459666e-01 -5.13695776e-01 -5.59447825e-01 -3.09374213e-01
4.93268996e-01 -6.08286619e-01 -4.27737832e-01 -9.80587661e-01
4.96422440e-01 -1.57042399e-01 8.68090153e-01 2.26166084e-01
8.55948851e-02 3.10846329e-01 3.14320475e-01 1.43053710e-01
-3.31569672e-01 4.74600233e-02 8.20820272e-01 -1.71919484e-02
-4.14124830e-03 -4.32545781e-01 -9.46728528e-01 1.13534153e+00
6.52483582e-01 -6.30633950e-01 -1.11079209e-01 4.05242015e-03
4.16930050e-01 -1.43312320e-01 1.88204914e-01 -5.21233261e-01
-2.56134063e-01 -1.16587058e-01 8.38825777e-02 3.69684517e-01
1.93996921e-01 -4.82886642e-01 -3.64141792e-01 5.34206092e-01
-3.69582891e-01 9.60170925e-02 -1.03404047e-03 5.04244804e-01
-7.74184838e-02 -7.06760705e-01 9.46548164e-01 -3.10348064e-01
3.10390685e-02 -2.22367242e-01 -1.32482827e+00 7.14768410e-01
1.15479743e+00 -3.17804068e-01 -8.35078597e-01 -8.57353687e-01
-4.18113947e-01 -6.31089881e-02 1.00295424e+00 2.47952297e-01
-1.09777808e-01 -8.66455853e-01 -7.57169247e-01 -5.10373473e-01
6.40586838e-02 -8.84133935e-01 -1.43106878e-01 8.00340652e-01
-8.33894789e-01 -1.11226268e-01 -1.96979359e-01 1.16426703e-02
-1.19272721e+00 2.16084883e-01 3.55113626e-01 -2.31716260e-01
-3.16836596e-01 6.49281919e-01 -1.00483976e-01 -4.31483030e-01
-1.30976453e-01 5.82712770e-01 -2.05576986e-01 4.45194036e-01
7.07617819e-01 7.97867000e-01 -2.07924694e-01 -7.53389239e-01
-4.31200564e-01 -1.84168667e-01 -6.90356553e-01 -9.89153758e-02
1.17387938e+00 1.04667880e-01 -6.33576274e-01 5.80817699e-01
1.60212278e+00 6.85874224e-01 -3.99572551e-01 3.14041138e-01
3.75463575e-01 -9.05595303e-01 -3.74344498e-01 -4.38614428e-01
-4.12238926e-01 4.64481890e-01 -3.76920730e-01 1.06255400e+00
2.05204234e-01 1.44113526e-01 7.44166017e-01 2.59793252e-01
5.18289506e-01 -1.29848194e+00 4.20819223e-01 6.88604951e-01
1.21611595e+00 -9.63895977e-01 1.16734318e-02 -5.06492794e-01
-7.67347693e-01 1.16010213e+00 9.32816029e-01 -3.13046426e-01
5.21158874e-01 4.41096276e-01 8.32215697e-02 -5.48875451e-01
-6.00507557e-01 4.99602556e-01 -5.78136146e-01 4.59251314e-01
9.20155346e-01 -2.44819760e-01 -1.02036953e+00 2.79652953e-01
-4.85546499e-01 -6.35233223e-01 1.19823396e+00 8.92478883e-01
-3.36390942e-01 -1.01110435e+00 -4.17523265e-01 7.99970627e-01
-1.09329391e+00 6.27545035e-03 -1.53186285e+00 9.95780766e-01
-6.76491633e-02 1.24231613e+00 1.83770582e-01 -5.28279126e-01
-1.43478781e-01 2.47082502e-01 2.56239295e-01 -1.01745558e+00
-1.22696102e+00 -5.52771091e-01 1.04476249e+00 -6.01869524e-01
-1.28374115e-01 -9.09663618e-01 -7.26534128e-01 -1.10289729e+00
-3.67149681e-01 2.26091400e-01 3.25090080e-01 9.28035557e-01
3.24116014e-02 -2.25235417e-01 3.62742931e-01 -6.11810744e-01
-6.05979145e-01 -1.25690138e+00 -8.56994808e-01 8.73484015e-01
3.16207916e-01 -7.06196606e-01 -9.04777348e-01 -4.38690722e-01] | [8.614115715026855, 10.410286903381348] |
57e3b7b1-6d2a-405d-969d-66487ea12018 | video-shadow-detection-via-spatio-temporal-1 | 2206.08801 | null | https://arxiv.org/abs/2206.08801v1 | https://arxiv.org/pdf/2206.08801v1.pdf | Video Shadow Detection via Spatio-Temporal Interpolation Consistency Training | It is challenging to annotate large-scale datasets for supervised video shadow detection methods. Using a model trained on labeled images to the video frames directly may lead to high generalization error and temporal inconsistent results. In this paper, we address these challenges by proposing a Spatio-Temporal Interpolation Consistency Training (STICT) framework to rationally feed the unlabeled video frames together with the labeled images into an image shadow detection network training. Specifically, we propose the Spatial and Temporal ICT, in which we define two new interpolation schemes, \textit{i.e.}, the spatial interpolation and the temporal interpolation. We then derive the spatial and temporal interpolation consistency constraints accordingly for enhancing generalization in the pixel-wise classification task and for encouraging temporal consistent predictions, respectively. In addition, we design a Scale-Aware Network for multi-scale shadow knowledge learning in images, and propose a scale-consistency constraint to minimize the discrepancy among the predictions at different scales. Our proposed approach is extensively validated on the ViSha dataset and a self-annotated dataset. Experimental results show that, even without video labels, our approach is better than most state of the art supervised, semi-supervised or unsupervised image/video shadow detection methods and other methods in related tasks. Code and dataset are available at \url{https://github.com/yihong-97/STICT}. | ['Chunxia Xiao', 'Yimin Yang', 'Xuanyu Zhou', 'Zipei Chen', 'Chengjiang Long', 'Sheng Liu', 'Yihong Cao', 'Xiao Lu'] | 2022-06-17 | video-shadow-detection-via-spatio-temporal | http://openaccess.thecvf.com//content/CVPR2022/html/Lu_Video_Shadow_Detection_via_Spatio-Temporal_Interpolation_Consistency_Training_CVPR_2022_paper.html | http://openaccess.thecvf.com//content/CVPR2022/papers/Lu_Video_Shadow_Detection_via_Spatio-Temporal_Interpolation_Consistency_Training_CVPR_2022_paper.pdf | cvpr-2022-1 | ['shadow-detection'] | ['computer-vision'] | [ 4.84252542e-01 -1.77000329e-01 -5.00242472e-01 -5.83661258e-01
-5.99871039e-01 -3.31338137e-01 2.18105540e-01 -4.53127742e-01
-1.88902721e-01 8.21945190e-01 -1.74972475e-01 -2.68153638e-01
2.82534603e-02 -3.26202631e-01 -8.35766017e-01 -8.57298791e-01
1.77022427e-01 -6.91813007e-02 8.37574422e-01 2.83410549e-01
1.39418751e-01 2.94404298e-01 -1.51658332e+00 3.77559006e-01
9.11057174e-01 1.41358256e+00 4.88163501e-01 4.71586317e-01
5.18171825e-02 1.29393470e+00 -1.99016377e-01 8.53984579e-02
1.97672859e-01 -5.52839756e-01 -6.59788489e-01 2.89598137e-01
6.09887779e-01 -5.37125230e-01 -2.95313656e-01 8.17107141e-01
2.40928710e-01 2.25934267e-01 3.60938638e-01 -1.59027338e+00
-4.77966815e-01 1.59906253e-01 -7.21475959e-01 3.35392356e-01
1.28564939e-01 -3.73629807e-03 5.95915377e-01 -9.52325106e-01
6.77705824e-01 9.07208979e-01 8.78532052e-01 4.34689611e-01
-8.30602825e-01 -7.55720973e-01 3.99825424e-01 5.03053427e-01
-1.44362831e+00 -4.76437449e-01 9.63638544e-01 -3.16547811e-01
2.98851937e-01 1.76872447e-01 4.61922169e-01 1.12422097e+00
-1.02490656e-01 9.87536013e-01 1.46373677e+00 -3.45080614e-01
2.08376244e-01 5.28997034e-02 -9.41428393e-02 9.27278519e-01
-9.37673450e-02 2.86471993e-01 -7.75587022e-01 1.07563160e-01
7.51725793e-01 -2.15044245e-02 -3.56800079e-01 -4.43373591e-01
-1.18929720e+00 3.89550716e-01 4.89397615e-01 5.32987490e-02
-2.88354635e-01 3.03263575e-01 3.67428869e-01 -1.61657333e-01
7.39811420e-01 -2.78147340e-01 -7.04266429e-01 2.69307464e-01
-1.06746984e+00 -1.26124516e-01 3.51410419e-01 9.64996755e-01
9.00663495e-01 2.04673428e-02 -2.11713806e-01 7.97353745e-01
2.37039149e-01 5.95207751e-01 2.45526031e-01 -1.26101661e+00
3.94274414e-01 3.42716932e-01 2.42750525e-01 -8.75368536e-01
-4.19978738e-01 -1.55022606e-01 -6.50526166e-01 6.71429560e-02
4.13590789e-01 -1.29801229e-01 -9.05298233e-01 1.63147569e+00
5.15882134e-01 9.94651914e-01 -6.62303157e-03 1.10841811e+00
8.11876833e-01 6.98065042e-01 1.55911237e-01 -6.49106324e-01
1.00319207e+00 -1.32526386e+00 -7.80909657e-01 -2.83480823e-01
4.31579977e-01 -7.21597373e-01 1.13377321e+00 1.32473767e-01
-8.11807036e-01 -7.22358584e-01 -8.94794345e-01 1.10136501e-01
-3.15675676e-01 6.50056243e-01 5.97362339e-01 3.37429136e-01
-9.01010573e-01 4.55434620e-01 -8.22278500e-01 -4.03057814e-01
5.49028397e-01 1.60084873e-01 -5.68062551e-02 -7.66269043e-02
-1.04225779e+00 5.11087954e-01 5.42487979e-01 3.28478783e-01
-8.36837530e-01 -5.38178623e-01 -6.36171758e-01 -4.13776487e-01
6.79666579e-01 -2.49078751e-01 1.10887218e+00 -1.38951373e+00
-1.16864526e+00 6.79578483e-01 -3.47178280e-01 -3.78044248e-01
5.48688054e-01 -1.09571725e-01 -3.21076781e-01 2.33760357e-01
2.83119321e-01 8.19988310e-01 8.62081349e-01 -1.64003325e+00
-9.78302240e-01 -5.37379496e-02 9.66836661e-02 3.44720215e-01
-4.88506585e-01 -3.22120776e-03 -9.30051804e-01 -6.59459293e-01
1.28720373e-01 -1.14718831e+00 -2.21232474e-02 3.37969303e-01
-3.06693703e-01 -1.85369551e-01 1.34482050e+00 -8.81525099e-01
1.22408235e+00 -2.04970646e+00 -9.11574736e-02 5.63095510e-02
-1.49588242e-01 2.75154710e-01 -1.11238507e-03 -8.35203379e-02
1.47308484e-01 -2.40656778e-01 -3.97554249e-01 -4.01168108e-01
-4.38682795e-01 4.33459967e-01 -2.57420033e-01 5.21979451e-01
1.91238913e-04 8.32422256e-01 -1.03177011e+00 -9.00169075e-01
4.52234358e-01 3.93930316e-01 -5.00567406e-02 3.29482973e-01
-3.87046456e-01 6.41493559e-01 -4.85788524e-01 9.59734917e-01
6.60162866e-01 -4.58552569e-01 1.70704961e-01 -5.74848533e-01
-1.91878453e-01 -2.09569931e-01 -1.05331421e+00 1.60081375e+00
-4.33898270e-01 8.36474657e-01 -1.86728492e-01 -9.07016754e-01
6.21596158e-01 2.22176448e-01 6.95467889e-01 -6.65826261e-01
9.16601047e-02 2.83337563e-01 -5.86425245e-01 -6.30514383e-01
2.50945091e-01 2.30220437e-01 1.83505103e-01 2.05229610e-01
-2.96695232e-01 2.08483145e-01 1.82475984e-01 1.09982245e-01
7.31182396e-01 6.85663223e-01 6.60385191e-02 -1.76875755e-01
7.26459742e-01 1.63945910e-02 9.20731783e-01 5.50153375e-01
-4.16908979e-01 6.88977778e-01 2.14234039e-01 -5.02515793e-01
-9.36002553e-01 -8.99371564e-01 -1.21008679e-01 1.12861705e+00
8.17353129e-01 -1.93593323e-01 -7.13597298e-01 -1.02057457e+00
-1.38964385e-01 3.22977424e-01 -6.16165102e-01 2.02869028e-01
-6.43744051e-01 -5.59155345e-01 4.12231058e-01 8.84285212e-01
9.36720490e-01 -1.09918952e+00 -5.15462577e-01 -1.81756526e-01
-5.28219163e-01 -1.60925674e+00 -6.92743301e-01 1.58388957e-01
-6.08617127e-01 -1.09929752e+00 -5.67103744e-01 -1.00941050e+00
7.29024887e-01 6.31116748e-01 7.61282444e-01 2.79853314e-01
-1.34194836e-01 2.05190510e-01 -4.38187361e-01 -1.86681613e-01
-1.63743675e-01 -2.37841561e-01 1.50285348e-01 1.96302772e-01
-1.18932622e-02 -4.44512933e-01 -8.32137942e-01 7.85495579e-01
-8.98640513e-01 6.07565820e-01 5.50344408e-01 7.99544930e-01
8.86741400e-01 5.78712374e-02 4.98392344e-01 -9.40434992e-01
-7.11940080e-02 -2.94969678e-01 -6.95722044e-01 5.55783212e-01
-7.94900775e-01 -2.70674288e-01 6.11460090e-01 -5.43041945e-01
-1.35645735e+00 5.59918582e-01 2.38121092e-01 -8.06806147e-01
-2.32833967e-01 1.20542578e-01 -5.42379543e-02 -4.65596288e-01
4.84585196e-01 3.60097647e-01 -3.49574536e-01 -1.14745595e-01
2.65528142e-01 6.39683723e-01 6.80441380e-01 -4.57544893e-01
9.02700424e-01 7.82063305e-01 -1.50562003e-01 -7.12303460e-01
-1.31742156e+00 -7.37810075e-01 -8.94980729e-01 -7.14628041e-01
1.05267441e+00 -1.09575403e+00 -1.87034160e-01 5.08198321e-01
-1.02565837e+00 -8.20721745e-01 -1.89246645e-03 2.60802299e-01
-6.83673799e-01 5.89669585e-01 -4.01334941e-01 -8.51540625e-01
-1.32277787e-01 -9.70653713e-01 1.24068367e+00 3.78846288e-01
1.93166152e-01 -9.89669561e-01 -2.53997952e-01 6.21979237e-01
1.99788004e-01 3.07673544e-01 3.86398256e-01 -1.08337291e-01
-9.07540202e-01 2.09426984e-01 -7.10572302e-01 6.03785336e-01
1.46899581e-01 -1.27613559e-01 -1.06550944e+00 -8.83123875e-02
-3.34944963e-01 -4.45837945e-01 9.14197028e-01 5.46808243e-01
1.55285871e+00 -1.59783199e-01 -3.80737334e-01 7.61120915e-01
1.38676560e+00 2.76308417e-01 4.56701696e-01 3.07123750e-01
1.09219050e+00 4.83678252e-01 1.23480308e+00 4.42915916e-01
3.83689821e-01 8.23784292e-01 2.17829362e-01 -3.00148726e-01
-4.45784777e-01 -2.38122195e-01 3.97832960e-01 4.22993869e-01
-2.44022921e-01 -3.07698637e-01 -7.69430280e-01 3.75699461e-01
-2.29846025e+00 -8.61646950e-01 -1.72445059e-01 1.96273756e+00
7.08717287e-01 -2.65550502e-02 -4.26657088e-02 -7.99226109e-03
7.22609103e-01 4.05038506e-01 -5.87952316e-01 2.85434932e-01
-2.54774988e-01 -1.82950005e-01 8.65938962e-01 4.07700300e-01
-1.45540845e+00 1.24476051e+00 5.31601429e+00 1.00690651e+00
-1.11870694e+00 4.36117500e-01 8.65494132e-01 1.28555238e-01
-8.03045779e-02 2.09255084e-01 -6.52941048e-01 6.15260243e-01
5.88268697e-01 2.95567393e-01 5.10248363e-01 7.78848469e-01
6.06585503e-01 -3.41042757e-01 -8.32975626e-01 9.42996502e-01
2.87107229e-01 -1.42621648e+00 -2.78365195e-01 -2.91607738e-01
1.08801115e+00 7.98187393e-04 -1.04578473e-01 -1.18902630e-04
-1.52873501e-01 -5.74456930e-01 9.28988814e-01 4.86638069e-01
9.04417753e-01 -3.45897377e-01 5.81163168e-01 2.35296637e-01
-1.66476405e+00 -2.35050365e-01 -7.63622224e-02 3.29071939e-01
2.48306826e-01 3.49519372e-01 -4.35399443e-01 4.64899480e-01
9.44905818e-01 9.91827726e-01 -6.73786521e-01 8.12568069e-01
-3.59422326e-01 5.88398278e-01 -1.54109284e-01 2.25990549e-01
4.96678567e-03 -1.01071924e-01 1.00960553e-01 1.15102756e+00
1.56822115e-01 2.41450042e-01 5.05752623e-01 4.82294708e-01
3.35997506e-03 -7.50441998e-02 -3.17472130e-01 2.94909090e-01
6.00780427e-01 1.33986962e+00 -1.08723223e+00 -4.04279947e-01
-4.94458139e-01 1.31226254e+00 1.71214700e-01 6.72499478e-01
-1.35033870e+00 1.58031926e-01 6.18219152e-02 5.14155105e-02
1.11028932e-01 -1.86066583e-01 -1.84466928e-01 -1.05039537e+00
2.90667892e-01 -4.66923416e-01 4.13471013e-01 -1.20904410e+00
-9.67063129e-01 5.54878652e-01 1.64834514e-01 -1.41184783e+00
8.25046077e-02 -4.51605976e-01 -6.32898927e-01 3.38673681e-01
-1.87395108e+00 -1.57273996e+00 -8.89787197e-01 7.49420524e-01
8.31175447e-01 -8.47693067e-03 2.57553101e-01 4.98656392e-01
-7.22775638e-01 4.06203181e-01 -3.18597518e-02 -1.08783571e-02
8.91415060e-01 -9.86949205e-01 -7.11123496e-02 9.49953377e-01
1.21760130e-01 -2.07187068e-02 5.17081499e-01 -7.21061587e-01
-1.10829711e+00 -1.50734830e+00 5.82931876e-01 -3.04650784e-01
6.52067721e-01 -1.63668171e-01 -8.75744998e-01 5.07565498e-01
-2.89898086e-02 5.38082659e-01 2.39679977e-01 -3.80503476e-01
-2.39530370e-01 -3.80167812e-01 -8.01061869e-01 2.77275294e-01
1.35909021e+00 -6.17542624e-01 1.11102492e-01 8.36117566e-01
8.07996213e-01 -5.59880018e-01 -6.64121985e-01 7.42777824e-01
5.96694052e-01 -1.09452772e+00 1.07177913e+00 -5.46577238e-02
3.61257553e-01 -6.42145336e-01 -2.62021720e-01 -6.37683094e-01
-3.45852710e-02 -3.23860347e-01 -2.79905498e-01 1.28511274e+00
2.45156944e-01 -2.31625378e-01 1.12608624e+00 3.63917023e-01
-2.26132646e-01 -9.92204845e-01 -8.71024966e-01 -8.93973649e-01
-5.08781672e-01 -5.11323810e-01 1.31606385e-02 8.10881138e-01
-4.56160545e-01 1.95858702e-02 -7.73298264e-01 6.11469448e-01
8.31139386e-01 2.76766568e-01 6.36287987e-01 -8.33337665e-01
-1.92003533e-01 6.65932568e-03 -1.21409208e-01 -1.11916852e+00
3.75901997e-01 -4.08668876e-01 4.34714258e-01 -1.42553353e+00
3.44621330e-01 -7.98560083e-01 -3.34939808e-01 6.45505905e-01
-2.03067645e-01 6.69601083e-01 3.34452949e-02 6.02422535e-01
-1.09260273e+00 5.06157279e-01 1.06557190e+00 1.15791224e-01
-2.26202652e-01 6.11817166e-02 3.11665772e-03 8.87006402e-01
9.16707039e-01 -2.39682287e-01 -6.49199903e-01 -1.67700872e-01
-2.46498361e-01 1.67989895e-01 7.56071866e-01 -1.12006831e+00
2.05096260e-01 -6.21049166e-01 4.22775477e-01 -7.80920386e-01
4.13741648e-01 -8.48244667e-01 1.87157288e-01 2.76161045e-01
-3.44159961e-01 -2.67530769e-01 -2.15061791e-02 8.05773616e-01
-8.53360519e-02 9.13191810e-02 9.75199819e-01 1.01366900e-01
-1.32389057e+00 5.20537794e-01 5.06273061e-02 -2.42052659e-01
1.28998911e+00 -1.43698812e-01 -3.77473474e-01 -2.72511780e-01
-5.30221164e-01 3.79770279e-01 4.40792263e-01 5.51395774e-01
7.40468442e-01 -1.33484197e+00 -3.33404094e-01 4.39499617e-02
3.02578568e-01 -1.07392678e-02 4.65034366e-01 1.17122459e+00
-5.41731000e-01 2.69340694e-01 -3.28825228e-02 -8.17546904e-01
-1.50564384e+00 4.30916786e-01 3.48144740e-01 1.03599340e-01
-4.56211925e-01 7.03861177e-01 3.57944876e-01 -1.62071943e-01
4.80018169e-01 -3.34556639e-01 2.28212569e-02 -2.32615426e-01
2.53005475e-01 2.05333993e-01 -2.39246756e-01 -7.32856154e-01
-4.43981469e-01 6.80093706e-01 2.95446754e-01 1.95252895e-01
9.47440982e-01 -4.20935750e-01 3.64758559e-02 4.57507551e-01
1.10970378e+00 -2.18336552e-01 -1.81110263e+00 -4.53913093e-01
-2.38267761e-02 -6.08811557e-01 2.15759315e-02 -6.16653740e-01
-1.27921712e+00 4.28820193e-01 1.01623023e+00 1.51568111e-02
1.47287476e+00 1.56989917e-01 9.08311546e-01 2.53756911e-01
3.28091234e-01 -1.24991572e+00 3.43627453e-01 2.84601957e-01
5.45065045e-01 -1.56995678e+00 9.82663631e-02 -7.01055348e-01
-7.94831514e-01 9.55309689e-01 9.31147814e-01 9.28976387e-02
5.42823076e-01 2.58930475e-01 1.45315811e-01 6.48518130e-02
-5.60098112e-01 -2.83434898e-01 3.63755316e-01 5.11357427e-01
2.48535603e-01 -1.52911514e-01 -2.81174272e-01 2.43212000e-01
5.13116539e-01 2.33704880e-01 1.93752676e-01 8.92904699e-01
-5.18192768e-01 -9.86892939e-01 -3.44984591e-01 2.19057962e-01
3.63920480e-02 -1.17228925e-02 -3.15608561e-01 6.38538659e-01
6.17864192e-01 8.78404915e-01 -3.10087442e-01 -6.11127198e-01
5.35430424e-02 -1.61073595e-01 2.65555263e-01 -2.33051822e-01
5.01968823e-02 1.22814052e-01 1.49116024e-01 -6.96209133e-01
-1.03084826e+00 -6.55248940e-01 -1.47493958e+00 -1.66917443e-02
-4.84460801e-01 -9.42259133e-02 5.22411287e-01 1.01207507e+00
1.22215383e-01 4.79849100e-01 8.33045185e-01 -1.11650372e+00
-7.66010806e-02 -6.71953440e-01 -3.85928541e-01 3.71196032e-01
2.82897621e-01 -7.55829990e-01 -3.48565787e-01 5.51582217e-01] | [9.232215881347656, -0.06549634784460068] |
29ce3675-48a1-4b1e-8978-cae6a92919eb | denoising-enhanced-distantly-supervised | 2210.09599 | null | https://arxiv.org/abs/2210.09599v1 | https://arxiv.org/pdf/2210.09599v1.pdf | Denoising Enhanced Distantly Supervised Ultrafine Entity Typing | Recently, the task of distantly supervised (DS) ultra-fine entity typing has received significant attention. However, DS data is noisy and often suffers from missing or wrong labeling issues resulting in low precision and low recall. This paper proposes a novel ultra-fine entity typing model with denoising capability. Specifically, we build a noise model to estimate the unknown labeling noise distribution over input contexts and noisy type labels. With the noise model, more trustworthy labels can be recovered by subtracting the estimated noise from the input. Furthermore, we propose an entity typing model, which adopts a bi-encoder architecture, is trained on the denoised data. Finally, the noise model and entity typing model are trained iteratively to enhance each other. We conduct extensive experiments on the Ultra-Fine entity typing dataset as well as OntoNotes dataset and demonstrate that our approach significantly outperforms other baseline methods. | ['Ping Li', 'Hongliang Fei', 'Yue Zhang'] | 2022-10-18 | null | null | null | null | ['entity-typing'] | ['natural-language-processing'] | [ 7.26673156e-02 -3.25082615e-02 -9.02707353e-02 -8.14377964e-01
-1.27377391e+00 -5.39058626e-01 1.42320290e-01 -4.36004363e-02
-5.89940012e-01 9.08259928e-01 3.41563791e-01 1.49813086e-01
2.57695019e-01 -6.08398616e-01 -8.11939776e-01 -6.49262905e-01
6.88764155e-01 2.41596878e-01 -2.09295020e-01 1.71079755e-01
-1.46486238e-01 -4.15596753e-01 -1.54448926e+00 3.77331227e-01
1.21735227e+00 1.16073644e+00 1.62025437e-01 5.70674658e-01
-2.25979745e-01 8.26397657e-01 -9.61278915e-01 -9.99494791e-01
-3.92678045e-02 6.10688291e-02 -6.48648798e-01 -4.85300511e-01
7.89722502e-01 -4.60978866e-01 -3.00646842e-01 1.46524704e+00
7.89335489e-01 -9.28166583e-02 5.15072048e-01 -1.09439254e+00
-1.12589037e+00 7.22423553e-01 -3.47878546e-01 -1.72695875e-01
3.48928243e-01 -1.19821042e-01 9.80808973e-01 -1.01263320e+00
6.10414743e-01 1.19576025e+00 1.34313917e+00 8.62794161e-01
-1.17937958e+00 -7.96979904e-01 2.57535487e-01 9.22475308e-02
-1.57423353e+00 -4.43777114e-01 3.62188935e-01 -2.10067227e-01
6.19865596e-01 1.05003789e-01 -1.74735650e-01 1.77383602e+00
-1.56322300e-01 9.18502629e-01 1.20345306e+00 -3.14416111e-01
1.62697330e-01 2.23853737e-01 5.38205326e-01 5.73851109e-01
4.57099825e-01 1.11684270e-01 -6.26749575e-01 -2.47451648e-01
3.38173896e-01 -1.50170192e-01 -2.50140905e-01 3.53832543e-01
-1.01636958e+00 2.74784744e-01 2.65869558e-01 1.16814822e-01
-2.55788535e-01 3.47531229e-01 4.82248873e-01 2.25019708e-01
6.93231642e-01 2.99755833e-04 -5.24102628e-01 -4.34302121e-01
-6.82155669e-01 8.57634619e-02 9.52182949e-01 1.29644156e+00
6.96761549e-01 -5.18369637e-02 -4.52971637e-01 1.24938512e+00
3.90603572e-01 6.68449879e-01 1.45833120e-01 -9.70937788e-01
6.31816268e-01 2.83160299e-01 2.36096531e-01 -7.85764694e-01
-2.04590097e-01 -5.70681751e-01 -1.12061870e+00 -9.42510143e-02
4.03543651e-01 -5.11572599e-01 -9.29763556e-01 2.04800248e+00
3.70451272e-01 8.30734968e-01 1.57526266e-02 7.84661233e-01
1.08856893e+00 2.89408684e-01 3.97713840e-01 -2.27888871e-04
1.37186992e+00 -8.44477415e-01 -1.33581352e+00 -1.94286361e-01
5.56290984e-01 -7.70098150e-01 9.61016893e-01 4.67129976e-01
-7.40917385e-01 -7.44237006e-01 -1.01608324e+00 -5.25267839e-01
-3.74403685e-01 4.47845578e-01 2.66001105e-01 7.54379809e-01
-6.96895719e-01 7.07633793e-01 -7.50712812e-01 1.70878068e-01
6.44629896e-01 1.56018034e-01 -3.68424416e-01 -2.58356035e-01
-1.50981724e+00 6.96634114e-01 2.12805331e-01 5.75192809e-01
-5.24788797e-01 -7.56472766e-01 -8.51319551e-01 -8.68843868e-03
3.36755633e-01 -8.80463183e-01 1.45495784e+00 -6.32248342e-01
-1.36731219e+00 6.62843883e-01 -4.64299321e-01 -9.69434306e-02
4.96913642e-01 -5.19201517e-01 -6.34245813e-01 -4.55348760e-01
3.65025163e-01 1.19350314e-01 6.93709731e-01 -1.50184929e+00
-7.88746774e-01 -4.31834906e-01 -1.05032371e-02 1.69225171e-01
-2.53549099e-01 -2.67220140e-01 -5.58869898e-01 -1.12856913e+00
-5.34559451e-02 -6.84881806e-01 1.84390377e-02 -2.65494704e-01
-5.24545312e-01 -4.33660507e-01 4.27108288e-01 -1.03893387e+00
1.55673361e+00 -2.35450292e+00 2.16793381e-02 2.43289229e-02
4.14663583e-01 1.90098614e-01 -4.08625938e-02 -7.40673468e-02
2.32097879e-01 2.29211897e-01 -1.17139608e-01 -8.49562585e-01
4.29872900e-01 5.55281699e-01 -1.43255964e-01 1.47561029e-01
-9.95487273e-02 8.51233065e-01 -1.16779220e+00 -3.83977413e-01
-2.56368548e-01 6.26375914e-01 -2.46900320e-01 3.73214036e-01
-8.72726664e-02 8.44717920e-02 -3.83417487e-01 8.63943338e-01
1.14373064e+00 -1.42187461e-01 2.44255930e-01 -5.51941812e-01
2.39953533e-01 2.97946930e-01 -1.41951764e+00 1.88978505e+00
-6.10999763e-01 3.00825208e-01 2.33485267e-01 -3.97345990e-01
7.76326120e-01 4.72151756e-01 4.42291163e-02 -5.56656301e-01
1.54259190e-01 3.78156275e-01 -6.06769621e-01 -7.49379337e-01
7.85690069e-01 -2.69533813e-01 -3.89134437e-01 3.81604403e-01
3.61313581e-01 6.79769456e-01 -2.70277888e-01 2.64878094e-01
9.81701434e-01 3.03327262e-01 -3.13688546e-01 1.73750177e-01
1.89586461e-01 -3.33959222e-01 1.28101838e+00 9.71310794e-01
-2.72540540e-01 6.76252127e-01 2.92042822e-01 -1.33336917e-01
-7.91546464e-01 -1.04012573e+00 -2.70820588e-01 1.08224094e+00
5.33308625e-01 -6.59152627e-01 -9.74958956e-01 -1.20793068e+00
2.28235811e-01 4.41203803e-01 -7.04953134e-01 -1.25958249e-01
-5.41228712e-01 -7.42261350e-01 1.16404235e+00 8.97668302e-01
5.32260358e-01 -7.68809915e-01 4.61672753e-01 2.22830594e-01
-7.87159145e-01 -1.17846262e+00 -6.55269086e-01 3.50761771e-01
-3.97834271e-01 -9.44534838e-01 -4.34390157e-01 -1.06956816e+00
5.89196026e-01 2.26269830e-02 1.24135935e+00 1.52187213e-01
7.11659715e-02 -1.19456075e-01 -3.52648228e-01 -2.58007526e-01
-3.67034525e-01 2.24463999e-01 3.79843801e-01 9.38566178e-02
9.03327763e-01 -1.91045508e-01 -4.76198643e-01 3.09594721e-01
-5.89744508e-01 -4.03353333e-01 6.37303352e-01 1.31827831e+00
7.53194988e-01 -2.06700880e-02 9.05635595e-01 -1.63368499e+00
6.18375719e-01 -4.99579787e-01 -1.09665722e-01 5.48387766e-01
-6.76306307e-01 1.22505717e-01 7.61850536e-01 -3.74972463e-01
-1.61063278e+00 -1.17241316e-01 -6.68683231e-01 -4.27853674e-01
-1.87415168e-01 3.54229152e-01 -6.73742890e-01 1.04818366e-01
6.81503296e-01 -1.01113923e-01 -5.61570525e-01 -1.01078594e+00
4.53980356e-01 1.36286736e+00 1.05417299e+00 -7.90994823e-01
7.14699686e-01 1.63877308e-01 -7.29978740e-01 -1.98955148e-01
-1.32373130e+00 -3.87623340e-01 -5.95362544e-01 1.60374835e-01
6.20206833e-01 -1.22149861e+00 -7.53747940e-01 1.00994694e+00
-1.16883647e+00 -8.60525444e-02 -9.30194631e-02 2.57925928e-01
-1.37724578e-01 5.81321776e-01 -9.62455511e-01 -6.93745971e-01
-3.79417598e-01 -8.06131899e-01 1.33144152e+00 3.46555740e-01
-1.39804021e-01 -9.69342172e-01 6.17714971e-02 5.18845558e-01
2.39910930e-01 -1.19920531e-02 5.74759185e-01 -3.59954774e-01
-4.55476254e-01 -2.50092119e-01 -2.65286267e-01 5.79535067e-01
2.55169183e-01 -2.84064293e-01 -1.36100566e+00 -9.26540345e-02
-6.35691360e-02 -4.58362848e-01 1.01711929e+00 2.66647767e-02
1.16105115e+00 -2.76373774e-01 -3.93043160e-01 9.72567379e-01
1.37902546e+00 -2.74223775e-01 5.51383257e-01 6.32317215e-02
1.12054873e+00 2.09320500e-01 9.50150430e-01 2.69802660e-01
7.42948472e-01 5.39905310e-01 -1.38183102e-01 1.40791893e-01
-3.00623685e-01 -7.18212724e-01 7.35275969e-02 1.18446088e+00
5.86907007e-02 -2.83169746e-01 -5.32338917e-01 4.11368102e-01
-2.00330210e+00 -8.85932863e-01 -1.49669483e-01 1.93123102e+00
1.25090325e+00 4.93410677e-02 -2.80507594e-01 -6.89759478e-02
9.02275681e-01 -1.53832594e-02 -6.54900908e-01 -1.51394665e-01
-3.54581267e-01 2.08616838e-01 4.69326198e-01 5.57920337e-01
-1.21414483e+00 9.03734982e-01 6.22051716e+00 1.09257686e+00
-6.21577978e-01 4.36358631e-01 4.34644341e-01 3.07366639e-01
-4.33709651e-01 -1.89828485e-01 -1.18043029e+00 1.07219326e+00
7.39257276e-01 3.93529758e-02 2.98551023e-01 7.51595914e-01
-1.98966801e-01 1.61663383e-01 -1.03386545e+00 1.15918815e+00
6.99657351e-02 -9.70903039e-01 -2.38394082e-01 -2.58870482e-01
6.30034029e-01 -2.53066748e-01 -8.94700289e-02 5.79241514e-01
6.47718191e-01 -9.08833742e-01 6.20996058e-01 7.05051601e-01
1.19340944e+00 -6.73411310e-01 1.07528007e+00 4.49335009e-01
-1.21063304e+00 4.04049736e-03 -5.10870755e-01 2.02836767e-01
1.74651161e-01 8.40785623e-01 -3.17339599e-01 6.99689090e-01
7.44277954e-01 7.98979700e-01 -3.74774843e-01 6.97711527e-01
-5.44920623e-01 5.86787939e-01 -1.84146538e-01 2.33871713e-02
-3.48120004e-01 -3.84193510e-02 1.71490297e-01 1.42396045e+00
1.62520483e-01 1.30182028e-01 1.63419247e-02 7.75497615e-01
-7.23488748e-01 -3.67067695e-01 -1.82580248e-01 3.12553376e-01
1.02495253e+00 1.41247678e+00 3.31368595e-02 -6.05247259e-01
-4.99946415e-01 1.21147740e+00 7.77427852e-01 5.21309257e-01
-9.17224348e-01 -6.03001595e-01 8.80050719e-01 -4.42078143e-01
1.49384737e-01 1.89414918e-01 -7.06678391e-01 -1.70971537e+00
3.04514021e-01 -8.96253943e-01 4.98344779e-01 -6.16569757e-01
-1.79860342e+00 6.66832507e-01 -7.69459486e-01 -1.15971065e+00
1.12387292e-01 -3.55526894e-01 -1.55240297e-01 1.16820717e+00
-1.43898666e+00 -1.23203290e+00 -6.43158674e-01 2.37085253e-01
2.79311836e-01 1.55744284e-01 9.57669437e-01 1.00475299e+00
-8.46148908e-01 1.51216054e+00 4.42690969e-01 5.09832144e-01
1.23355782e+00 -1.73474014e+00 5.53913832e-01 7.36914456e-01
-1.11513637e-01 8.86603177e-01 3.38047832e-01 -9.96820986e-01
-1.12044287e+00 -1.51409841e+00 1.21258867e+00 -8.58479083e-01
3.01865608e-01 -5.74262917e-01 -1.16001856e+00 8.04065466e-01
-7.95878917e-02 1.09962314e-01 9.04171407e-01 5.00731289e-01
-8.18177164e-01 -2.27647215e-01 -1.33684969e+00 2.49734357e-01
1.42363381e+00 -9.07549918e-01 -6.96256399e-01 -9.74747632e-03
6.45983875e-01 -7.83511758e-01 -1.15906179e+00 3.50123882e-01
8.20051610e-01 -4.63167667e-01 8.39023232e-01 -4.07174408e-01
1.46293193e-01 -4.45613593e-01 -1.57724038e-01 -1.53696334e+00
-5.25230765e-01 -3.23464304e-01 -4.68526810e-01 1.85344315e+00
3.54353875e-01 -3.51965159e-01 8.95210803e-01 7.61875153e-01
-2.52027631e-01 -4.85982805e-01 -8.80092263e-01 -6.23205423e-01
-1.38993159e-01 -2.75294095e-01 6.02262914e-01 1.11173820e+00
-2.32845962e-01 5.53975880e-01 -8.36582422e-01 3.23708177e-01
9.73287761e-01 -4.23421971e-02 5.72325766e-01 -1.07988214e+00
-4.12634283e-01 2.23940134e-01 -1.42130271e-01 -1.34095705e+00
4.40196902e-01 -7.47609138e-01 5.25117338e-01 -1.27914345e+00
2.17698395e-01 -8.82649362e-01 -4.69206333e-01 4.55866218e-01
-8.97024155e-01 4.95650202e-01 -2.99348325e-01 7.92040825e-02
-7.44591892e-01 3.40083212e-01 8.35438967e-01 -1.47144571e-01
2.08807558e-01 1.57523826e-02 -1.02403080e+00 7.11153209e-01
4.54023272e-01 -5.76833308e-01 -1.50775770e-02 -8.88342798e-01
3.99771988e-01 -2.53495246e-01 6.63110390e-02 -5.48071623e-01
5.26317120e-01 2.75334924e-01 4.40542132e-01 -5.86630285e-01
2.55303115e-01 -6.26697183e-01 1.53390467e-01 -6.06067628e-02
-3.78381461e-01 -2.42343426e-01 -3.70379239e-01 9.34672356e-01
-3.30996513e-01 -3.11151236e-01 5.89412451e-01 1.45954549e-01
-7.29952216e-01 3.64614874e-01 6.27176687e-02 4.46674228e-01
4.73697841e-01 -3.63907330e-02 -6.28719270e-01 -7.25058839e-02
-7.99999058e-01 4.53913391e-01 4.32572275e-01 4.64522958e-01
4.50770885e-01 -1.71483195e+00 -6.76714420e-01 9.32153240e-02
2.18102738e-01 3.43999028e-01 5.77487648e-01 4.47067618e-01
-1.95143551e-01 -1.71991661e-01 2.33411178e-01 -4.30241585e-01
-1.33237576e+00 4.74740505e-01 2.23907724e-01 -1.54152870e-01
-4.35473561e-01 1.13391280e+00 -1.16857454e-01 -8.27215970e-01
7.82364845e-01 -2.66436279e-01 -4.09597754e-02 9.40995291e-02
6.99334681e-01 4.95781988e-01 1.19038351e-01 -5.86006403e-01
-3.56367290e-01 6.10725045e-01 -2.81397790e-01 2.49007851e-01
1.15812457e+00 -4.07015711e-01 6.88669682e-02 4.43735629e-01
1.21564829e+00 2.20221773e-01 -1.20017314e+00 -7.12954581e-01
2.66471833e-01 -6.49061799e-01 -9.71046612e-02 -1.05898058e+00
-8.36560607e-01 7.86954165e-01 5.96750438e-01 -8.46262369e-03
9.28691447e-01 -2.95971334e-01 1.26701951e+00 2.87285775e-01
4.12188917e-01 -1.46636617e+00 -2.01894864e-01 6.20108008e-01
2.39346370e-01 -1.43594372e+00 -3.48046601e-01 -6.78086400e-01
-5.05853295e-01 6.52936757e-01 8.20088565e-01 7.43750930e-02
5.11151910e-01 8.48585844e-01 5.27207911e-01 2.13729337e-01
-7.61901498e-01 -5.75689413e-02 1.01066113e-01 8.78368914e-01
3.39165986e-01 2.03416124e-01 -1.18538551e-01 1.52899730e+00
-1.30354650e-02 3.83617222e-01 2.65988082e-01 7.82717645e-01
-1.37090027e-01 -1.34595215e+00 -1.74678147e-01 5.94222128e-01
-7.60828555e-01 -3.57119322e-01 -3.79961967e-01 7.80653581e-02
5.80832243e-01 9.07883465e-01 -2.68424034e-01 -7.80221879e-01
4.79599357e-01 1.83351815e-01 3.39936227e-01 -6.42676115e-01
-8.44360352e-01 -1.86738625e-01 4.99732882e-01 -3.48290324e-01
-2.52817512e-01 -3.50428700e-01 -9.55813468e-01 -6.12035394e-01
-6.74044847e-01 2.16743693e-01 4.88019437e-01 7.73955882e-01
5.52193701e-01 5.87864459e-01 6.23748600e-01 -2.14373544e-01
-8.28065634e-01 -1.11942780e+00 -7.32310295e-01 7.52849042e-01
3.71068776e-01 -7.00596094e-01 -3.58971387e-01 3.66317071e-02] | [9.569132804870605, 8.981311798095703] |
ee1b2750-e996-47d3-90e0-1231257aeaff | large-language-models-are-reasoners-with-self | 2212.09561 | null | https://arxiv.org/abs/2212.09561v4 | https://arxiv.org/pdf/2212.09561v4.pdf | Large Language Models are Better Reasoners with Self-Verification | Recently, with the chain of thought (CoT) prompting, large language models (LLMs), e.g., GPT-3, have shown strong reasoning ability in several natural language processing tasks such as arithmetic, commonsense, and logical reasoning. However, LLMs with CoT require multi-step prompting and multi-token prediction, which is highly sensitive to individual mistakes and vulnerable to error accumulation. The above issues make the LLMs need the ability to verify the answers. In fact, after inferring conclusions in some thinking decision tasks, people often check them by re-verifying steps to avoid some mistakes. In this paper, we propose and prove that LLMs also have similar self-verification abilities. We take the conclusion obtained by CoT as one of the conditions for solving the original problem. By taking turns masking the original conditions and predicting their results, we calculate an explainable answer verification score based on whether the re-predicted conditions are correct. Experimental results demonstrate that the proposed method can improve the reasoning performance on various arithmetic, commonsense, and logical reasoning datasets. Our code is publicly available at: https://github.com/WENGSYX/Self-Verification. | ['Jun Zhao', 'Kang Liu', 'Bin Li', 'Fei Xia', 'Shizhu He', 'Minjun Zhu', 'Yixuan Weng'] | 2022-12-19 | null | null | null | null | ['arithmetic-reasoning', 'logical-reasoning', 'common-sense-reasoning'] | ['reasoning', 'reasoning', 'reasoning'] | [-1.25913352e-01 9.50934067e-02 1.27212614e-01 -4.88657296e-01
-3.29444975e-01 -3.98220479e-01 2.51717061e-01 5.47282934e-01
-2.43538395e-01 5.92272580e-01 1.19572736e-01 -6.65011644e-01
-1.18108906e-01 -1.11930120e+00 -5.31253636e-01 -1.60749242e-01
4.85863805e-01 3.16650182e-01 3.16974759e-01 -2.80566245e-01
7.65510201e-01 -1.43251553e-01 -1.32954168e+00 6.84011936e-01
1.61220253e+00 7.69422233e-01 2.20121428e-01 4.97562587e-01
-4.71196920e-01 1.86277950e+00 -5.80996275e-01 -8.44544232e-01
-1.97414652e-01 -6.04223788e-01 -1.18893266e+00 -4.71666068e-01
4.65580747e-02 -4.23477411e-01 -1.25444710e-01 1.49023998e+00
2.27938354e-01 1.52539000e-01 2.63827801e-01 -1.37324309e+00
-1.15396762e+00 1.19358480e+00 -1.27900824e-01 2.11239174e-01
9.97628987e-01 2.54710287e-01 9.60605562e-01 -8.31209660e-01
1.33806959e-01 1.46564341e+00 7.27162957e-01 4.80641723e-01
-7.20510364e-01 -7.77952015e-01 1.05649181e-01 9.95106995e-01
-1.31245339e+00 -2.96708524e-01 6.65512204e-01 -2.17538983e-01
1.02769494e+00 2.95366198e-01 3.22119147e-01 6.59924090e-01
5.08163214e-01 7.49068081e-01 1.57047379e+00 -5.87221086e-01
2.77839452e-01 1.27213418e-01 5.29451549e-01 9.38294053e-01
2.86993235e-01 -3.61592501e-01 -4.40105408e-01 1.13759428e-01
4.51462507e-01 3.21738044e-05 -1.91779941e-01 6.03973210e-01
-1.34312499e+00 4.78905529e-01 3.95919919e-01 4.17240143e-01
-2.56348103e-01 -4.45733927e-02 3.22892606e-01 4.44617718e-01
-2.76270658e-02 4.26788807e-01 -5.68765819e-01 -9.26689878e-02
-6.35448396e-01 3.52350503e-01 7.77062595e-01 9.24258113e-01
5.54139078e-01 -1.95013717e-01 -4.50599432e-01 4.86936361e-01
2.69910634e-01 5.77570140e-01 8.30618262e-01 -1.03849077e+00
6.46409214e-01 1.06881297e+00 9.52362642e-02 -1.50251102e+00
-4.07066852e-01 -2.66892493e-01 -1.00463986e+00 -1.88634664e-01
5.17616630e-01 7.44391605e-02 -2.16348276e-01 1.80041301e+00
3.55713814e-01 2.88691193e-01 1.78817287e-01 8.16776872e-01
9.33527887e-01 5.02592385e-01 1.83197111e-01 -8.37956592e-02
1.45931256e+00 -9.08679008e-01 -9.56931472e-01 -2.13826761e-01
8.59767318e-01 -6.67486072e-01 1.34129500e+00 4.73134935e-01
-1.14364684e+00 -7.40804732e-01 -8.12471509e-01 -4.58250195e-01
-7.29778633e-02 1.64392784e-01 6.65326357e-01 1.78190544e-01
-8.42364013e-01 5.59483111e-01 -4.97149616e-01 2.90840697e-02
1.89681441e-01 -1.59332991e-01 -8.23622271e-02 -3.92675042e-01
-1.78708577e+00 1.14114177e+00 5.44149041e-01 2.49909922e-01
-4.01094526e-01 -5.69055140e-01 -8.47732723e-01 3.90975386e-01
5.91877401e-01 -6.09456420e-01 1.45422935e+00 -5.25363982e-01
-1.21429133e+00 6.55024052e-01 -5.64884007e-01 -3.05532873e-01
6.61731124e-01 -2.48891801e-01 -6.32916331e-01 7.07486048e-02
4.66394722e-01 1.39522403e-01 2.56941736e-01 -5.85346103e-01
-3.92926872e-01 -2.50926465e-01 4.97992337e-01 -4.29114290e-02
8.53998214e-02 2.16055647e-01 2.60882199e-01 -3.46787214e-01
5.09759367e-01 -4.52147752e-01 3.75218168e-02 -6.68984726e-02
-6.08668089e-01 -7.45900631e-01 7.82887638e-02 -8.78860593e-01
1.48354256e+00 -1.95990634e+00 -1.72657534e-01 5.08974679e-02
4.76558536e-01 1.75911441e-01 6.60983399e-02 3.25322807e-01
-3.22775431e-02 4.21660304e-01 -4.00372073e-02 1.38025165e-01
3.16295624e-01 9.83674638e-03 -5.34089983e-01 -6.95953444e-02
1.83099777e-01 1.14347136e+00 -1.09476721e+00 -8.49127412e-01
7.60968626e-02 -1.57345846e-01 -5.43127358e-01 1.53286546e-01
-4.62428212e-01 1.68353915e-01 -4.57775235e-01 5.51164865e-01
7.30289340e-01 -6.48079813e-01 1.22224912e-01 1.89757213e-01
1.08101219e-01 8.00027728e-01 -1.30800068e+00 1.18259442e+00
-3.77033919e-01 3.19583595e-01 -6.63911045e-01 -9.01781201e-01
9.88539755e-01 2.42095888e-01 -4.78171289e-01 -8.05692315e-01
6.70432746e-02 4.04246420e-01 3.74104977e-01 -9.67174590e-01
2.52366006e-01 -2.99637765e-01 2.89950124e-03 5.99273741e-01
-4.12718922e-01 -1.71835423e-02 3.18802893e-01 6.02945805e-01
9.92708385e-01 -3.44862565e-02 6.18040740e-01 -1.03262357e-01
1.12331796e+00 5.93673103e-02 8.65140319e-01 7.64039338e-01
-3.58622998e-01 -1.01566967e-02 8.24081600e-01 -3.42461705e-01
-6.32382154e-01 -7.43379176e-01 2.02731863e-01 6.71523452e-01
1.41217992e-01 -6.13000154e-01 -5.88940203e-01 -2.16745153e-01
-4.35500294e-02 1.36933732e+00 -2.83395797e-01 -3.69806200e-01
-3.85705262e-01 -1.83592260e-01 8.00201297e-01 5.99667311e-01
1.20389748e+00 -1.19387114e+00 -4.30184960e-01 2.16142401e-01
-7.25922406e-01 -1.23622203e+00 1.19364738e-01 -3.33789319e-01
-6.26001894e-01 -1.22172809e+00 6.51058257e-02 -7.16205835e-01
7.84708142e-01 1.95596188e-01 1.05241394e+00 1.02674401e+00
1.94488406e-01 8.87699425e-03 -5.36605954e-01 -2.67107308e-01
-4.97628272e-01 -4.48868364e-01 2.16128454e-01 -4.29816335e-01
7.17532158e-01 -4.36318964e-01 -2.97315955e-01 2.12601304e-01
-6.02587938e-01 5.26454389e-01 2.98015714e-01 5.15380263e-01
3.78492773e-01 4.90120292e-01 5.42963624e-01 -6.90558612e-01
9.05103862e-01 -4.99913722e-01 -3.43418777e-01 7.36619294e-01
-6.79929376e-01 2.27478877e-01 1.02593017e+00 -3.05990696e-01
-1.15572810e+00 -7.59302914e-01 7.78410630e-03 7.71724656e-02
-6.87648058e-02 8.53147805e-01 -1.30162105e-01 2.14868337e-01
5.16484022e-01 5.81561983e-01 -2.33390719e-01 -4.38222028e-02
3.30107696e-02 5.16720235e-01 5.26068330e-01 -1.11683559e+00
8.36801767e-01 -2.15984404e-01 -1.05214149e-01 -5.58297299e-02
-1.30709767e+00 1.29574731e-01 -2.98501462e-01 -2.21099183e-01
7.03898430e-01 -7.78037012e-01 -1.35312402e+00 6.25516713e-01
-1.43797147e+00 -3.00549120e-01 2.83878088e-01 4.20841157e-01
-3.17434102e-01 6.95090711e-01 -8.66123617e-01 -9.88587558e-01
-3.82065386e-01 -8.63103032e-01 4.02532220e-01 5.68978727e-01
-5.80329001e-01 -8.77382576e-01 -3.46155584e-01 6.02314532e-01
2.76546717e-01 -1.76356986e-01 1.43960142e+00 -7.69916832e-01
-5.55091321e-01 -1.07987583e-01 -2.02971756e-01 3.26746881e-01
-7.78886750e-02 -1.24224890e-02 -6.51671886e-01 4.13264483e-01
3.84559274e-01 -4.90122050e-01 5.15714645e-01 -9.47901309e-02
1.51932013e+00 -5.11073649e-01 1.46744713e-01 1.66789263e-01
1.08906627e+00 -4.58558835e-02 8.49829495e-01 2.92653620e-01
3.41199517e-01 3.78398180e-01 7.13891745e-01 3.31074595e-01
9.71271336e-01 1.31838555e-02 -6.31969422e-02 5.65496981e-01
1.67766526e-01 -6.08459353e-01 3.81407440e-01 1.03051949e+00
-1.42455712e-01 5.54649858e-03 -1.27804577e+00 3.03087085e-01
-1.89698470e+00 -1.30551302e+00 -6.03963137e-01 1.77082980e+00
1.29797482e+00 2.43332371e-01 -5.98149180e-01 6.03683114e-01
6.71218634e-01 -2.49585703e-01 -4.71617192e-01 -4.56362993e-01
-2.18760446e-01 2.29922622e-01 -3.49173814e-01 7.97758937e-01
-3.59744430e-01 1.03332555e+00 5.13045597e+00 6.84561610e-01
-5.90678394e-01 -7.98118412e-02 5.19561827e-01 3.52181047e-01
-6.06589258e-01 2.13142708e-01 -5.27655959e-01 5.83442748e-01
6.84291780e-01 -6.26735747e-01 5.85096121e-01 5.74145854e-01
1.93283752e-01 -4.81761515e-01 -1.15992558e+00 7.83883154e-01
5.47719141e-03 -1.04404247e+00 2.10202336e-01 -7.86498129e-01
4.15724218e-01 -6.95232213e-01 -2.77915984e-01 8.16038311e-01
2.47112080e-01 -1.00638473e+00 8.31857145e-01 8.32175195e-01
2.77511030e-01 -4.97394502e-01 1.03672266e+00 9.01645958e-01
-1.06753886e+00 -7.06600100e-02 -5.52393079e-01 -1.02012289e+00
-1.70697227e-01 8.20999622e-01 -4.83349591e-01 5.85480094e-01
4.30515677e-01 5.04088640e-01 -8.16454411e-01 7.83457160e-01
-1.19403851e+00 5.30276179e-01 6.79282025e-02 -4.52653110e-01
-3.25153500e-01 -1.59550235e-02 8.05735365e-02 6.60309076e-01
3.21313709e-01 7.97402680e-01 1.14534631e-01 1.26982951e+00
2.97559798e-02 -7.51722306e-02 2.81502642e-02 -9.76340324e-02
9.43711579e-01 9.13545847e-01 -5.80363691e-01 -8.49934816e-01
-1.34123400e-01 8.31887901e-01 7.01883614e-01 2.08193630e-01
-1.00603533e+00 -5.61050534e-01 2.81865597e-01 -1.11179739e-01
-3.26203138e-01 -1.49681583e-01 -8.32106531e-01 -1.45013952e+00
4.29647565e-01 -1.01081622e+00 2.01796398e-01 -1.47877026e+00
-1.32315290e+00 1.86154723e-01 -1.02883480e-01 -8.02571177e-01
2.07713782e-03 -7.47064292e-01 -8.83125067e-01 9.74861920e-01
-1.50225103e+00 -6.24708414e-01 -4.65428919e-01 5.97131371e-01
2.90015668e-01 2.01785907e-01 8.23717773e-01 1.88818067e-01
-6.05125487e-01 6.07564390e-01 -7.43285060e-01 4.83736038e-01
5.72267115e-01 -1.05253875e+00 2.62292594e-01 9.96311247e-01
-3.59879464e-01 1.17754972e+00 7.13966370e-01 -9.15071309e-01
-1.19284153e+00 -7.06438184e-01 1.81402659e+00 -4.42364186e-01
8.95164490e-01 4.69664782e-02 -1.30147064e+00 9.53107893e-01
8.92745238e-03 -2.83971071e-01 6.22442782e-01 9.11424756e-02
-5.71534276e-01 1.21267200e-01 -1.21161234e+00 7.55959809e-01
1.06505585e+00 -7.44617105e-01 -1.30241728e+00 5.61395764e-01
8.43176782e-01 -5.94771862e-01 -5.56981623e-01 1.06569991e-01
2.71232784e-01 -1.06569088e+00 6.24887168e-01 -8.27874184e-01
1.21338701e+00 -6.03525758e-01 -1.16581611e-01 -1.05080521e+00
-5.26508093e-01 -1.00952037e-01 -6.48847176e-03 1.34884298e+00
3.10976326e-01 -8.62533092e-01 5.66852205e-02 1.13539660e+00
2.20807418e-02 -6.49007320e-01 -6.98605716e-01 -6.34794414e-01
3.76633741e-03 -7.52841771e-01 9.56963480e-01 1.15590763e+00
6.23278499e-01 1.80735379e-01 -5.90164140e-02 4.11901593e-01
4.13981944e-01 3.81354928e-01 4.69937921e-01 -1.15525770e+00
-2.00113684e-01 -3.79494339e-01 -1.73867330e-01 -9.15273607e-01
4.45567936e-01 -1.18637633e+00 -1.47984952e-01 -1.76843071e+00
4.25492704e-01 -3.70779693e-01 -2.18431383e-01 7.49753118e-01
-7.71935403e-01 -5.52700520e-01 1.74322367e-01 8.20612237e-02
-8.27619195e-01 3.97971541e-01 1.36058319e+00 -7.46280029e-02
2.72980183e-01 -2.83175498e-01 -8.67629409e-01 9.10465598e-01
1.19150102e+00 -4.43939596e-01 -2.71633029e-01 -6.57422364e-01
8.85756671e-01 1.64740071e-01 7.64387548e-01 -1.14215779e+00
6.40362322e-01 -5.14626861e-01 4.18264806e-01 -4.26987767e-01
-1.69870600e-01 -5.05172372e-01 -1.96244508e-01 8.33693981e-01
-6.10083163e-01 5.07770419e-01 1.69643104e-01 1.21205404e-01
-1.53147206e-01 -4.30034697e-01 2.41403490e-01 -3.92618209e-01
-8.18683445e-01 -2.93178678e-01 -1.94002390e-01 3.11883330e-01
8.33089769e-01 1.07307650e-01 -7.55167603e-01 -3.15649390e-01
-4.11511302e-01 5.72262764e-01 1.30224422e-01 7.65879080e-02
8.99253845e-01 -1.34059095e+00 -9.25694585e-01 1.32789575e-02
6.93601090e-03 1.15849920e-01 4.97091442e-01 1.12041867e+00
-5.90364814e-01 5.07200778e-01 -1.16179951e-01 -1.99093685e-01
-1.07473278e+00 6.00659549e-01 2.89039046e-01 -2.72281945e-01
-4.97045547e-01 9.94012535e-01 -3.38216364e-01 -6.12295926e-01
-8.71356130e-02 -9.12941873e-01 -1.14317037e-01 -3.58567297e-01
9.27617311e-01 2.64903516e-01 -1.67333379e-01 8.11719447e-02
-5.87715626e-01 3.11569333e-01 1.89917992e-04 2.17021346e-01
8.76906574e-01 -5.92018515e-02 -7.62769639e-01 6.56850874e-01
3.36476117e-01 1.11177273e-01 -3.37722719e-01 -4.68832731e-01
2.66264770e-02 -4.93996918e-01 -4.02054638e-01 -1.09157467e+00
-5.43352187e-01 8.47750723e-01 -3.59983593e-01 1.19814076e-01
9.27324474e-01 -1.67269841e-01 7.53077507e-01 8.29838037e-01
6.97747886e-01 -8.65882397e-01 -1.19599156e-01 9.17687893e-01
7.21710086e-01 -1.24046350e+00 -4.63369722e-03 -4.97548372e-01
-6.04295552e-01 1.19806874e+00 1.04129171e+00 -4.38689552e-02
1.71244875e-01 1.62931472e-01 -1.00596488e-01 1.18489871e-02
-1.09042060e+00 2.75591731e-01 -1.18988901e-01 1.88480482e-01
6.11136019e-01 3.11331153e-01 -6.07902646e-01 1.16107607e+00
-6.88187420e-01 3.60076815e-01 5.93335807e-01 7.28027940e-01
-6.46978915e-01 -6.21328890e-01 -6.02580607e-01 2.92830229e-01
-7.96598196e-02 -5.57267189e-01 -4.78106081e-01 4.79474604e-01
1.17094539e-01 1.32641578e+00 -1.75571159e-01 -5.54949045e-01
1.05493985e-01 3.96642864e-01 5.03024995e-01 -3.99792463e-01
-4.57897872e-01 -1.14570224e+00 2.38938406e-02 -5.11171520e-01
-2.16399163e-01 -4.19668555e-01 -2.02304888e+00 -1.06330395e+00
-1.26686826e-01 1.90329105e-01 -8.85420591e-02 1.51023054e+00
1.33080125e-01 5.94205558e-01 1.37636736e-01 2.80506194e-01
-9.66255248e-01 -9.56173003e-01 -2.24681005e-01 4.14609939e-01
1.76458359e-02 -5.71899772e-01 -4.59405303e-01 -1.90683246e-01] | [9.59062385559082, 7.500366687774658] |
d10e989c-6223-4690-b958-499d2fe6f13d | measuring-compositional-consistency-for-video | 2204.07190 | null | https://arxiv.org/abs/2204.07190v2 | https://arxiv.org/pdf/2204.07190v2.pdf | Measuring Compositional Consistency for Video Question Answering | Recent video question answering benchmarks indicate that state-of-the-art models struggle to answer compositional questions. However, it remains unclear which types of compositional reasoning cause models to mispredict. Furthermore, it is difficult to discern whether models arrive at answers using compositional reasoning or by leveraging data biases. In this paper, we develop a question decomposition engine that programmatically deconstructs a compositional question into a directed acyclic graph of sub-questions. The graph is designed such that each parent question is a composition of its children. We present AGQA-Decomp, a benchmark containing $2.3M$ question graphs, with an average of $11.49$ sub-questions per graph, and $4.55M$ total new sub-questions. Using question graphs, we evaluate three state-of-the-art models with a suite of novel compositional consistency metrics. We find that models either cannot reason correctly through most compositions or are reliant on incorrect reasoning to reach answers, frequently contradicting themselves or achieving high accuracies when failing at intermediate reasoning steps. | ['Maneesh Agrawala', 'Ranjay Krishna', 'Madeleine Grunde-McLaughlin', 'Eva Prakash', 'Mustafa Omer Gul', 'Mona Gandhi'] | 2022-04-14 | null | http://openaccess.thecvf.com//content/CVPR2022/html/Gandhi_Measuring_Compositional_Consistency_for_Video_Question_Answering_CVPR_2022_paper.html | http://openaccess.thecvf.com//content/CVPR2022/papers/Gandhi_Measuring_Compositional_Consistency_for_Video_Question_Answering_CVPR_2022_paper.pdf | cvpr-2022-1 | ['video-question-answering'] | ['computer-vision'] | [ 1.49678141e-01 5.45851946e-01 -5.42514026e-02 -5.53951979e-01
-1.09839284e+00 -8.38453531e-01 5.32835007e-01 2.72584409e-01
6.68130815e-02 4.46211666e-01 4.58741903e-01 -9.41211581e-01
-2.00966746e-01 -1.01366472e+00 -1.12434793e+00 2.20445380e-01
2.35734835e-01 8.45951319e-01 8.38020205e-01 -4.04596925e-01
2.38214105e-01 -2.42440492e-01 -1.67843902e+00 1.09770501e+00
8.81244957e-01 9.05531287e-01 -5.13667166e-01 1.20947278e+00
-6.79901421e-01 2.11717010e+00 -5.36089301e-01 -1.25283659e+00
1.50647864e-01 -7.90440977e-01 -1.52203918e+00 -7.81028196e-02
1.51153135e+00 -7.48766422e-01 -4.33577031e-01 1.01000202e+00
-3.57278466e-01 -8.68672058e-02 3.09041917e-01 -1.49792588e+00
-8.98724318e-01 8.35926473e-01 -8.73602331e-02 3.71662349e-01
8.85344267e-01 3.42140734e-01 1.83271039e+00 -5.58461607e-01
7.20280111e-01 1.24246168e+00 7.06713080e-01 7.33491242e-01
-1.25204635e+00 -3.52564365e-01 5.84555209e-01 6.68703556e-01
-6.29407108e-01 -3.57073903e-01 5.45748651e-01 -3.78885895e-01
1.19709015e+00 8.34889293e-01 5.56624770e-01 6.84177339e-01
3.68826240e-01 7.51703560e-01 1.18883371e+00 7.06000477e-02
3.34877014e-01 -3.76940191e-01 6.76027298e-01 1.26135945e+00
3.77326816e-01 -4.70063269e-01 -7.84435153e-01 -4.19444323e-01
1.04407500e-02 -3.63093615e-01 -8.62144455e-02 -2.83170372e-01
-8.06698978e-01 7.63307214e-01 4.23033118e-01 -7.91780353e-02
-1.38962850e-01 5.25838733e-01 7.61820450e-02 7.20567644e-01
-9.28534120e-02 7.14161634e-01 -5.11565089e-01 -1.89262137e-01
-7.87123263e-01 9.82815325e-01 1.29707038e+00 9.90942419e-01
6.95401728e-01 -3.50435972e-01 -1.49473459e-01 4.18597907e-01
3.55494887e-01 4.32325095e-01 2.30601221e-01 -1.75494480e+00
6.06083810e-01 1.25898635e+00 -1.05594680e-01 -1.08456588e+00
-2.52340823e-01 -1.03119217e-01 -2.00128481e-01 -1.32180050e-01
8.90799761e-01 3.32249910e-01 -5.86517692e-01 1.71073687e+00
2.90726155e-01 -3.26098263e-01 -2.26528704e-01 8.86007667e-01
1.10161841e+00 4.43732649e-01 8.92224014e-02 3.03474039e-01
1.61038101e+00 -1.30597746e+00 -3.67981702e-01 -5.15805542e-01
4.36814636e-01 -5.08199692e-01 1.42574167e+00 4.21129972e-01
-1.64801931e+00 -4.47797567e-01 -7.47552514e-01 -4.54582453e-01
-9.44915973e-03 -6.81933343e-01 4.99780029e-01 4.47557628e-01
-1.26126349e+00 2.51577884e-01 -4.32889313e-01 -2.90023983e-01
3.74969751e-01 1.65669128e-01 -1.54349998e-01 -5.14298856e-01
-8.48159850e-01 8.12778771e-01 -2.74705946e-01 -4.54718143e-01
-9.81124163e-01 -9.84237790e-01 -6.93225622e-01 9.51587707e-02
7.16253221e-01 -1.15135801e+00 1.89238524e+00 -8.70882809e-01
-9.78835702e-01 8.44453752e-01 -3.88257563e-01 -5.41454613e-01
4.32768583e-01 -1.81040868e-01 -2.79638082e-01 5.62531531e-01
2.69311637e-01 6.97931528e-01 6.64626360e-01 -1.15307796e+00
-8.17601085e-01 -4.28388864e-01 1.00442433e+00 -1.30777517e-02
-3.17772944e-03 -1.48181573e-01 -3.50834817e-01 -1.72190979e-01
4.36205149e-01 -8.21195245e-01 8.51237252e-02 1.40009806e-01
-1.92559272e-01 -4.23925966e-01 4.39922512e-01 -7.87444353e-01
1.25527501e+00 -1.50145888e+00 8.88294280e-02 -1.47950724e-01
8.57443094e-01 -3.42897177e-01 -3.22019935e-01 3.03418726e-01
1.60940111e-01 4.21183765e-01 -2.95635849e-01 5.33460863e-02
4.02474523e-01 4.08330292e-01 -6.19880378e-01 6.99041411e-02
3.73404473e-01 1.18892109e+00 -1.02409947e+00 -6.74285352e-01
-3.26598763e-01 -3.37170362e-01 -1.25578034e+00 2.98715770e-01
-1.17150557e+00 -1.82850167e-01 -1.46346033e-01 7.71899521e-01
5.23360670e-01 -7.14178324e-01 3.86449218e-01 -7.92366564e-02
4.55525070e-01 1.06149507e+00 -8.40994596e-01 1.44341612e+00
-6.16896572e-03 5.49974442e-01 1.07645951e-01 -5.81354022e-01
5.55924118e-01 -1.20253377e-01 1.35660782e-01 -9.78517175e-01
-2.85042226e-01 2.17743978e-01 -1.28945161e-03 -8.60833347e-01
6.49611712e-01 -7.07499385e-02 -6.61021844e-02 7.13304996e-01
-2.46635284e-02 -4.78583217e-01 6.64472520e-01 6.11421585e-01
1.87876689e+00 9.09783021e-02 -1.99312195e-01 -2.09683910e-01
7.05269873e-01 6.46852791e-01 3.61106455e-01 9.59030151e-01
-2.62988955e-01 5.40021718e-01 1.07801187e+00 -7.14960575e-01
-9.58215058e-01 -1.32178652e+00 5.04919171e-01 1.52077377e+00
9.74342749e-02 -8.73950064e-01 -7.64261484e-01 -1.05969059e+00
1.22677892e-01 9.02382612e-01 -4.54119056e-01 -1.73826426e-01
-8.14217865e-01 -1.40309811e-01 6.97965384e-01 5.02859533e-01
4.78891432e-01 -6.68505371e-01 -7.72320628e-01 7.93047473e-02
-6.61863387e-01 -1.07881439e+00 -3.74374181e-01 -2.18414336e-01
-9.37961698e-01 -1.73910582e+00 -2.35657915e-02 -6.77876651e-01
7.01258361e-01 2.60992080e-01 2.18568754e+00 8.21151018e-01
3.76141369e-01 8.35893571e-01 -3.47961366e-01 6.08267076e-02
-6.95636749e-01 2.26111606e-01 -6.24298871e-01 -3.65927309e-01
6.72442555e-01 -3.51056218e-01 -7.49745131e-01 4.49592382e-01
-9.45874929e-01 9.17352214e-02 1.02470696e-01 5.08924901e-01
3.92625391e-01 -1.06630124e-01 2.44755149e-01 -1.22553408e+00
6.87718451e-01 -6.71383917e-01 -5.08012354e-01 5.31409383e-01
-6.44297779e-01 3.58206302e-01 8.25114012e-01 -9.15445462e-02
-9.39828157e-01 -4.70971137e-01 -2.35953227e-01 -1.76032651e-02
1.77154690e-02 3.42520535e-01 1.89872563e-01 1.90102831e-01
9.35561061e-01 1.40154198e-01 -2.77332552e-02 2.98572388e-02
5.63606381e-01 7.19275698e-02 6.59807980e-01 -1.19960713e+00
7.00514317e-01 3.88633728e-01 -9.79396179e-02 -3.69551778e-01
-1.18442333e+00 -1.56459406e-01 9.57977325e-02 -3.93136382e-01
7.58817196e-01 -6.12842560e-01 -1.10328352e+00 3.48754786e-02
-1.20485747e+00 -5.03907740e-01 -3.56890142e-01 -2.46230796e-01
-5.43056905e-01 4.24305499e-01 -8.91640425e-01 -4.53974009e-01
-3.01632732e-01 -1.15339053e+00 7.26897717e-01 3.36602032e-02
-8.64989579e-01 -5.71542621e-01 1.66107208e-01 1.47339094e+00
4.82276291e-01 -3.07434022e-01 1.64979553e+00 -5.47406077e-01
-1.05382252e+00 2.18441486e-02 -3.14603806e-01 1.83039114e-01
-3.96014661e-01 9.78066251e-02 -6.95032597e-01 1.12497315e-01
2.64809970e-02 -6.77316606e-01 4.84197348e-01 -2.48286560e-01
1.10538256e+00 -6.37815356e-01 3.85769427e-01 1.06113009e-01
1.27163315e+00 -1.09788023e-01 6.60649419e-01 2.67163217e-01
4.75642085e-01 7.26059973e-01 2.77337916e-02 -9.84633788e-02
1.26220703e+00 -8.95274244e-03 7.93022156e-01 8.28315794e-01
-4.11897928e-01 -6.47274852e-01 2.04175562e-01 7.38415539e-01
2.73417771e-01 -1.24961428e-01 -1.16209948e+00 8.22177351e-01
-1.86021399e+00 -9.76558149e-01 -7.71600485e-01 1.71508110e+00
9.70787168e-01 1.98280200e-01 1.46240249e-01 1.25696570e-01
1.08083762e-01 3.19121361e-01 -6.89328074e-01 -4.23943490e-01
-4.98981327e-02 3.78042668e-01 1.29790353e-02 7.52627075e-01
-5.05515695e-01 6.29059374e-01 6.86293316e+00 4.96021286e-02
-4.40240860e-01 1.78673398e-02 5.20488977e-01 -2.14351475e-01
-1.17930150e+00 3.12579602e-01 -4.61442798e-01 2.30514407e-01
9.32841122e-01 1.07389390e-01 7.17155457e-01 6.47273481e-01
-5.96391737e-01 -4.23607379e-01 -1.36157167e+00 5.52348614e-01
2.70192504e-01 -1.51712239e+00 5.85022271e-01 -4.41332370e-01
8.24897766e-01 -1.89170375e-01 -8.27938914e-02 6.02984548e-01
7.23769069e-01 -1.01239419e+00 1.02208078e+00 5.84328890e-01
1.20166600e-01 -3.68534714e-01 4.57989335e-01 3.19036424e-01
-1.04630291e+00 -3.18716615e-01 -1.03854977e-01 -4.51394767e-01
-2.24801332e-01 1.43099710e-01 -4.98574078e-01 2.89215505e-01
9.77671027e-01 -6.95086643e-03 -1.13829660e+00 5.35880089e-01
-4.27426696e-01 8.70344102e-01 -2.20704824e-01 -3.70273232e-01
1.63391188e-01 1.18605323e-01 2.35446230e-01 7.70335436e-01
-5.26611991e-02 3.74816328e-01 -1.58881888e-01 1.03930914e+00
-4.45627987e-01 -2.43285000e-01 -1.79234087e-01 -6.38222024e-02
2.69926667e-01 8.85056913e-01 -2.46222675e-01 -5.39850116e-01
-7.27468550e-01 5.74537218e-01 6.31777585e-01 2.86524326e-01
-9.90262270e-01 1.13981850e-01 8.07859123e-01 6.18026495e-01
1.28565252e-01 -1.83688447e-01 -5.36710083e-01 -1.35717666e+00
4.36273247e-01 -1.71196914e+00 8.17707300e-01 -1.27902114e+00
-1.34770036e+00 4.91336018e-01 -1.25847951e-01 -2.52498865e-01
-2.29100645e-01 -6.27279341e-01 -4.08669651e-01 3.62054825e-01
-1.40672576e+00 -8.49035263e-01 -6.05764031e-01 5.73180437e-01
5.10109723e-01 1.66850224e-01 6.18804216e-01 1.59566566e-01
-2.31868163e-01 4.28858578e-01 -7.29012907e-01 5.31787090e-02
3.87363970e-01 -1.44989991e+00 5.78949034e-01 8.69599581e-01
2.47243017e-01 6.71675980e-01 8.43605161e-01 -5.12128115e-01
-1.83007133e+00 -8.81376624e-01 1.22229934e+00 -1.13763678e+00
1.00090909e+00 1.63454562e-02 -1.08889747e+00 9.29031372e-01
5.01250386e-01 -2.15003286e-02 6.06017411e-01 7.60160908e-02
-1.18087745e+00 -3.71052206e-01 -9.99445796e-01 8.22595358e-01
1.36353076e+00 -9.43347275e-01 -1.18433487e+00 2.25816414e-01
7.81525791e-01 -4.61946875e-01 -7.45833457e-01 3.47372115e-01
5.51453114e-01 -1.55701268e+00 7.63479173e-01 -1.21090615e+00
1.27046955e+00 -3.97696286e-01 -5.39676130e-01 -6.59997582e-01
-4.16200846e-01 -3.81370395e-01 -6.77932620e-01 8.25527549e-01
7.06951141e-01 -4.03315514e-01 1.21177769e+00 1.18521547e+00
3.59181091e-02 -9.39820528e-01 -6.61409378e-01 -3.28301758e-01
2.19883561e-01 -7.17475772e-01 8.69558752e-01 5.37539303e-01
8.55769292e-02 5.70604026e-01 2.63317883e-01 2.42973045e-02
7.34908044e-01 5.31641126e-01 9.04761732e-01 -8.83515239e-01
-5.41135550e-01 -6.95253134e-01 -1.57062267e-03 -1.38976467e+00
8.13285857e-02 -8.27177703e-01 -5.33620417e-02 -2.04632163e+00
2.34459385e-01 -3.03532160e-03 1.72929883e-01 3.72775525e-01
-2.92001456e-01 6.42744154e-02 2.34492868e-01 1.59369931e-02
-1.17637527e+00 9.96988937e-02 1.26366484e+00 -5.70377350e-01
6.24780297e-01 -3.95382136e-01 -1.13935864e+00 7.52620161e-01
7.29417443e-01 -3.55742633e-01 -6.74570560e-01 -9.69703794e-01
1.18312407e+00 2.16622069e-01 6.77360058e-01 -9.52923834e-01
6.10537052e-01 -1.84425950e-01 -8.28067809e-02 -6.26540720e-01
9.63283479e-02 -7.21169651e-01 1.49926558e-01 5.59853852e-01
-6.01036608e-01 5.67966521e-01 4.41724807e-02 3.92900318e-01
-3.01891059e-01 -3.07461172e-01 3.83673668e-01 -4.71721500e-01
-5.73204279e-01 1.32069401e-02 -3.94405097e-01 8.65727186e-01
6.85986340e-01 6.76871464e-02 -8.77388716e-01 -5.58618963e-01
-3.43584895e-01 5.16269028e-01 4.38792557e-01 4.02390659e-01
6.02629781e-01 -1.21672547e+00 -7.07422733e-01 -1.24092199e-01
3.41772497e-01 8.04962218e-02 4.74488437e-01 6.23202741e-01
-1.04326105e+00 3.77622485e-01 1.47047579e-01 -4.13118690e-01
-1.25209785e+00 5.62597632e-01 6.50614262e-01 -3.74684513e-01
-2.42113471e-01 9.25950468e-01 -9.66486558e-02 -8.22425127e-01
1.18701011e-01 -8.73046994e-01 2.35844478e-01 -1.46883935e-01
5.09171963e-01 5.28952062e-01 9.02263001e-02 -7.85747245e-02
-4.07032132e-01 5.06891251e-01 1.45243946e-02 3.63218524e-02
9.41373587e-01 1.64138377e-01 -6.57528043e-01 6.22816086e-02
8.78731787e-01 4.59104739e-02 -1.02510178e+00 -2.87987173e-01
4.81284596e-02 -3.95922691e-01 -4.95089352e-01 -9.81633782e-01
-8.85980666e-01 5.56079328e-01 -3.95625651e-01 6.74124002e-01
9.21947956e-01 2.90801018e-01 1.06980205e+00 6.12384260e-01
4.61135685e-01 -7.65198588e-01 4.51059073e-01 6.37801707e-01
1.04599452e+00 -1.07128561e+00 -7.13423938e-02 -2.31774509e-01
-3.02152872e-01 9.38184679e-01 1.05484402e+00 -1.45101994e-01
1.71264827e-01 1.67078868e-01 3.01980451e-02 -5.38671970e-01
-1.55376720e+00 1.51973188e-01 3.49844873e-01 1.59154892e-01
4.46767747e-01 7.67276215e-04 1.51682850e-02 6.80841506e-01
-6.51654303e-01 -5.38402833e-02 5.34923673e-01 9.09842253e-01
-5.31511068e-01 -7.92219639e-01 -4.36965585e-01 7.22134054e-01
-5.47749221e-01 -7.08925277e-02 -8.60333622e-01 5.22621095e-01
-6.75351471e-02 1.42594802e+00 8.08658749e-02 -5.77001989e-01
5.18719077e-01 3.40207249e-01 8.10190618e-01 -3.70738357e-01
-8.87889147e-01 -9.81297195e-01 5.28727412e-01 -9.05380726e-01
-2.20778078e-01 -5.38117230e-01 -1.32344389e+00 -1.08676755e+00
2.51317799e-01 1.00666471e-01 7.66294599e-02 9.03648674e-01
4.01607364e-01 5.81417739e-01 -1.37361903e-02 4.87903804e-01
-8.10157537e-01 -4.63444591e-01 2.08736911e-01 6.64090633e-01
2.97823370e-01 8.49123150e-02 -4.07425761e-01 1.41148731e-01] | [10.949237823486328, 7.879020690917969] |
adaf4f57-e406-47d9-8beb-2efed2239fbe | unifiedqa-crossing-format-boundaries-with-a | 2005.00700 | null | https://arxiv.org/abs/2005.00700v3 | https://arxiv.org/pdf/2005.00700v3.pdf | UnifiedQA: Crossing Format Boundaries With a Single QA System | Question answering (QA) tasks have been posed using a variety of formats, such as extractive span selection, multiple choice, etc. This has led to format-specialized models, and even to an implicit division in the QA community. We argue that such boundaries are artificial and perhaps unnecessary, given the reasoning abilities we seek to teach are not governed by the format. As evidence, we use the latest advances in language modeling to build a single pre-trained QA model, UnifiedQA, that performs surprisingly well across 17 QA datasets spanning 4 diverse formats. UnifiedQA performs on par with 9 different models that were trained on individual datasets themselves. Even when faced with 12 unseen datasets of observed formats, UnifiedQA performs surprisingly well, showing strong generalization from its out-of-format training data. Finally, simply fine-tuning this pre-trained QA model into specialized models results in a new state of the art on 6 datasets, establishing UnifiedQA as a strong starting point for building QA systems. | ['Sewon Min', 'Ashish Sabharwal', 'Daniel Khashabi', 'Tushar Khot', 'Hannaneh Hajishirzi', 'Peter Clark', 'Oyvind Tafjord'] | 2020-05-02 | null | https://aclanthology.org/2020.findings-emnlp.171 | https://aclanthology.org/2020.findings-emnlp.171.pdf | findings-of-the-association-for-computational | ['multi-task-language-understanding'] | ['methodology'] | [ 1.74052507e-01 2.35788465e-01 1.79990903e-01 -5.95417738e-01
-1.61976099e+00 -1.11012983e+00 8.00209820e-01 2.63459623e-01
-3.00253898e-01 7.92155325e-01 5.88660002e-01 -8.01964521e-01
-2.99442738e-01 -8.07615519e-01 -6.99021459e-01 -1.33561537e-01
2.86704302e-01 1.11096668e+00 4.23170596e-01 -9.55576658e-01
2.33182251e-01 1.05325125e-01 -1.35325527e+00 7.79122829e-01
1.23080540e+00 9.46006000e-01 -1.51386440e-01 7.35512018e-01
-5.93655050e-01 1.27399790e+00 -6.95414722e-01 -1.06705630e+00
1.37695715e-01 -3.23679745e-01 -1.59331059e+00 -1.96955070e-01
1.07151377e+00 -2.51298666e-01 -2.87379384e-01 5.26710033e-01
3.38980407e-01 -7.39213824e-02 4.93855596e-01 -9.00673389e-01
-9.88439500e-01 6.62296116e-01 2.56851584e-01 7.70585090e-02
9.62545753e-01 2.63309330e-01 1.61281919e+00 -5.67913651e-01
8.72100294e-01 1.21538126e+00 6.92297041e-01 6.13424480e-01
-1.29815507e+00 -1.09917916e-01 -2.28526652e-01 3.11083198e-01
-8.75227690e-01 -3.97435039e-01 4.10687417e-01 -2.32062548e-01
9.80360270e-01 4.82546151e-01 1.16581686e-01 1.07362390e+00
8.85080174e-02 8.98552120e-01 1.37985551e+00 -6.08668447e-01
3.78655922e-03 -2.22903062e-02 5.02213657e-01 5.99485576e-01
1.58519417e-01 -4.15896833e-01 -4.15309817e-01 -5.71024418e-01
1.81133464e-01 -5.01377165e-01 -4.38065410e-01 -2.53349006e-01
-1.09513438e+00 9.60959315e-01 1.34015903e-01 1.80115148e-01
9.35489088e-02 -2.69010127e-01 4.60912615e-01 1.00539470e+00
-7.53444955e-02 1.23598766e+00 -9.97806370e-01 -2.32100204e-01
-8.20402384e-01 7.27861643e-01 1.25068426e+00 8.10093701e-01
6.68341041e-01 -5.20698786e-01 -2.70182371e-01 9.33611929e-01
1.18404329e-01 4.29137230e-01 3.62476438e-01 -1.25186121e+00
8.98651421e-01 9.70899403e-01 2.60939747e-01 -4.75884259e-01
-3.77698600e-01 -2.13687167e-01 -1.84520423e-01 -2.05229640e-01
1.07923627e+00 -4.93597314e-02 -1.02065802e+00 1.66808438e+00
1.19025754e-02 -8.67556930e-01 7.52975196e-02 6.11669540e-01
8.77657831e-01 5.08375227e-01 3.45087558e-01 1.68572232e-01
1.53792191e+00 -7.25897729e-01 -6.14283502e-01 -3.74962658e-01
1.13490939e+00 -8.36901546e-01 1.63642919e+00 7.37626672e-01
-1.21232605e+00 -2.90215224e-01 -8.21875453e-01 -7.02781677e-01
-6.00588202e-01 -2.74101824e-01 8.94735575e-01 8.71919692e-01
-1.07803297e+00 2.50882179e-01 -2.85909653e-01 -2.86543518e-01
2.83972651e-01 1.32871300e-01 -5.56960762e-01 -7.25863338e-01
-1.44246566e+00 1.42228663e+00 2.73367107e-01 -2.62639403e-01
-8.41637254e-01 -6.47447050e-01 -1.03566396e+00 1.13008320e-02
6.85586631e-01 -1.09212923e+00 1.61103392e+00 -6.56375706e-01
-1.26892209e+00 8.85727525e-01 -2.46579513e-01 -4.92251962e-01
3.17597002e-01 -4.12658095e-01 -6.26324296e-01 4.34217118e-02
2.04056114e-01 4.37619567e-01 3.89726996e-01 -1.14916945e+00
-4.61841077e-01 -3.51178318e-01 7.19732821e-01 1.83285967e-01
5.49548902e-02 2.48360068e-01 5.87602369e-02 -1.59283489e-01
1.76974282e-01 -5.85788667e-01 1.82213001e-02 -3.22752148e-01
-1.67766631e-01 -6.77507639e-01 3.49550635e-01 -8.19889665e-01
1.28332615e+00 -1.63573551e+00 8.15627649e-02 -9.18983668e-02
1.21778086e-01 3.87304835e-02 -3.61579061e-01 8.46214890e-01
1.25547603e-01 2.38416791e-01 -3.90424639e-01 -9.43426713e-02
4.15457755e-01 3.70870769e-01 -7.06976175e-01 3.51347737e-02
6.88397229e-01 9.44585621e-01 -8.72958958e-01 -6.45145118e-01
-2.05081165e-01 -1.46621212e-01 -6.72136068e-01 3.08482885e-01
-6.70901060e-01 1.01811647e-01 -4.71985012e-01 8.84134054e-01
5.59789717e-01 -4.47012782e-01 1.68346956e-01 1.12054579e-01
1.98106423e-01 1.14057803e+00 -8.69965374e-01 1.98705387e+00
-3.81324232e-01 3.95071685e-01 -2.33238172e-02 -7.46133447e-01
6.51748836e-01 3.89204025e-01 6.70359144e-03 -1.00465345e+00
-6.60299361e-02 6.21070623e-01 2.56006181e-01 -6.20630503e-01
8.11067522e-01 -2.63907999e-01 -4.24759448e-01 4.94390905e-01
6.33089185e-01 -6.01269901e-01 5.55981219e-01 5.41205764e-01
1.37305844e+00 4.91306111e-02 -5.34431823e-02 -2.29208171e-01
6.86016858e-01 5.89070559e-01 1.10169485e-01 9.72996235e-01
-1.74587980e-01 7.21803963e-01 4.79361355e-01 -4.19361770e-01
-8.41816723e-01 -1.25645602e+00 -4.32602853e-01 1.34843814e+00
-1.80207938e-01 -6.84136808e-01 -4.40660179e-01 -9.98938799e-01
-1.16396539e-01 8.35723281e-01 -4.56393957e-01 1.23569518e-01
-7.07385421e-01 -4.47695911e-01 9.41430688e-01 2.27601245e-01
3.07247996e-01 -9.53581393e-01 -3.28022808e-01 2.48909429e-01
-3.20356816e-01 -1.02104175e+00 1.64276958e-01 3.49228889e-01
-7.98815131e-01 -1.08944952e+00 -3.82931411e-01 -5.74255049e-01
1.50567219e-01 -1.62475660e-01 1.95910907e+00 2.14095458e-01
1.82831079e-01 6.34467483e-01 -5.31897724e-01 -3.82106185e-01
-5.45277178e-01 3.64619017e-01 -4.12128687e-01 -6.07860804e-01
3.92555088e-01 -1.98118597e-01 -2.20017552e-01 8.93974863e-03
-1.23046565e+00 -4.58007574e-01 5.91321528e-01 1.07367778e+00
4.45642807e-02 -4.14148778e-01 7.36322939e-01 -1.15424061e+00
8.82722259e-01 -5.76905608e-01 -2.75660515e-01 7.37901151e-01
-3.71968538e-01 3.94967228e-01 6.81989431e-01 9.45152119e-02
-1.25259900e+00 -4.06710178e-01 -4.77169573e-01 4.73109066e-01
-3.90597165e-01 6.68970942e-01 -3.89702678e-01 -8.03233404e-03
8.90367150e-01 1.27600566e-01 -1.14738576e-01 -5.62048316e-01
7.94834614e-01 5.61564386e-01 4.62212145e-01 -1.08607721e+00
7.44793475e-01 1.64230645e-01 -2.32964650e-01 -5.35985947e-01
-1.12498403e+00 -2.59104460e-01 -4.32008207e-01 3.33861172e-01
7.26337433e-01 -8.13448966e-01 -5.32928705e-01 1.22562200e-01
-1.06044221e+00 -3.32648188e-01 -2.57666856e-01 -1.54314730e-02
-5.32127082e-01 5.70837796e-01 -8.09890926e-01 -6.32788301e-01
-2.40533337e-01 -1.01610184e+00 9.16503608e-01 5.21933287e-02
-5.30902684e-01 -1.12661684e+00 2.90542305e-01 1.09159589e+00
5.26300311e-01 -2.21105993e-01 1.44679534e+00 -1.07551694e+00
-6.19611144e-01 -1.24327898e-01 -1.14940338e-01 3.28661114e-01
-1.33775827e-02 -1.42053545e-01 -9.41989422e-01 1.95407756e-02
1.01836555e-01 -1.12731326e+00 7.78126359e-01 -2.48444512e-01
8.85535657e-01 -7.75873363e-02 2.35466123e-01 2.41829336e-01
1.32812822e+00 -6.32228926e-02 7.93911457e-01 7.27419198e-01
2.84445047e-01 6.92528069e-01 4.74353671e-01 -2.26790890e-01
8.71013820e-01 2.92715788e-01 3.61247569e-01 3.87141407e-01
-4.38712873e-02 -2.24653438e-01 3.32237631e-01 5.89455485e-01
2.67754763e-01 -3.03147078e-01 -1.18993163e+00 5.80422997e-01
-1.28055346e+00 -9.51098800e-01 -2.75583625e-01 2.06097603e+00
1.24372387e+00 2.20049709e-01 -3.94925177e-02 7.47052068e-03
-2.22729832e-01 9.95807424e-02 -8.72430205e-02 -7.75686204e-01
-5.77027380e-01 8.46506596e-01 7.62526467e-02 4.79705036e-01
-9.63177204e-01 8.50125730e-01 7.55972862e+00 7.27824271e-01
-7.59835124e-01 -9.44495946e-02 4.10394281e-01 4.28684413e-01
-8.67222428e-01 2.02693164e-01 -6.15377128e-01 1.56782135e-01
1.24428773e+00 5.37401065e-02 4.48045820e-01 5.46278000e-01
-5.85062146e-01 -2.47757643e-01 -1.27987301e+00 5.00094593e-01
1.25005320e-01 -1.32601559e+00 6.15691781e-01 -2.71779716e-01
4.88117069e-01 1.97555140e-01 3.15281153e-02 8.76579106e-01
7.20604420e-01 -1.46321070e+00 5.25240541e-01 2.78909177e-01
4.38220561e-01 -3.18859547e-01 7.93814838e-01 5.22538900e-01
-5.17079175e-01 -1.78790271e-01 -4.03235465e-01 -2.99752772e-01
2.07306802e-01 1.39096916e-01 -7.83164382e-01 9.36003745e-01
5.29621303e-01 -1.78370834e-03 -1.10671091e+00 8.88184309e-01
-2.28151441e-01 8.01673651e-01 -2.76937485e-01 1.42196715e-01
4.19588864e-01 2.74280645e-02 2.82962143e-01 1.14733219e+00
-3.68075855e-02 1.30151406e-01 -1.99460596e-01 6.76432788e-01
-1.39700770e-01 1.07343934e-01 -4.45155263e-01 -2.17806682e-01
3.69761050e-01 1.06774199e+00 3.44223306e-02 -4.65100259e-01
-8.36770833e-01 7.09851861e-01 5.58032513e-01 2.17023581e-01
-5.12911737e-01 -4.08759415e-01 4.00065035e-01 -1.67771801e-01
2.08879963e-01 -3.81570429e-01 -3.82265627e-01 -1.49734056e+00
1.54869080e-01 -1.69093752e+00 1.00243783e+00 -9.79052126e-01
-1.62171757e+00 6.31748915e-01 -8.58831182e-02 -8.44175279e-01
-3.64263624e-01 -9.40002739e-01 -3.61451328e-01 9.69348133e-01
-1.61366594e+00 -1.12250781e+00 -9.49013680e-02 7.05756545e-01
4.45375293e-01 4.74170074e-02 1.06979024e+00 3.82033229e-01
4.37198989e-02 7.21725762e-01 -1.37549326e-01 2.29495347e-01
1.09425795e+00 -1.63087308e+00 2.87989080e-01 6.83264375e-01
6.32044554e-01 1.12642634e+00 7.43686855e-01 -3.25081944e-01
-1.70737064e+00 -3.97492766e-01 1.35201609e+00 -1.52021754e+00
9.63914812e-01 -2.37808436e-01 -1.24530256e+00 9.24042642e-01
6.91120923e-01 -3.52953047e-01 7.68155217e-01 4.45758432e-01
-8.84479523e-01 9.15172175e-02 -1.09193003e+00 4.93696064e-01
8.89758587e-01 -9.45098639e-01 -1.50509596e+00 3.53377998e-01
8.44518304e-01 -6.29776895e-01 -1.04620969e+00 4.37473685e-01
2.80531734e-01 -8.43748033e-01 9.15333033e-01 -1.31385422e+00
5.82627535e-01 -2.45305598e-01 -3.52298230e-01 -1.25195789e+00
-1.35961816e-01 -5.24179280e-01 -7.24935606e-02 1.26627254e+00
9.48067486e-01 -6.19054615e-01 5.12647271e-01 1.05341887e+00
-4.33434844e-01 -6.60405397e-01 -8.95508885e-01 -5.51288784e-01
7.07075834e-01 -5.59000254e-01 7.12443531e-01 1.03892732e+00
8.71478766e-02 7.58851409e-01 1.11662790e-01 -5.88973276e-02
2.04308182e-01 1.52408987e-01 8.63088310e-01 -1.13665593e+00
-4.44283783e-01 -3.24540913e-01 -1.01803258e-01 -1.42295504e+00
-9.62165147e-02 -8.86419237e-01 -2.17155531e-01 -1.77563512e+00
8.57292190e-02 -6.17625296e-01 -1.15080841e-01 4.39013749e-01
-3.92603338e-01 3.50326532e-03 1.40410557e-01 9.49931368e-02
-8.90972972e-01 3.56842726e-01 1.34051180e+00 -1.73015177e-01
1.78477466e-01 -2.30276719e-01 -1.10145426e+00 3.72994781e-01
4.47982639e-01 -1.07497379e-01 -3.24522138e-01 -9.75201130e-01
7.23859608e-01 2.98873596e-02 2.28963315e-01 -8.84886146e-01
9.26926807e-02 -6.92550391e-02 2.79250056e-01 -3.25908363e-01
4.56299812e-01 -6.36754155e-01 -4.07314837e-01 7.81516731e-02
-5.88076174e-01 2.60787696e-01 2.62335271e-01 6.29520416e-02
-5.29367566e-01 -3.96239400e-01 1.25663206e-01 -3.38296294e-01
-7.92360842e-01 -8.98675323e-02 -2.27946550e-01 8.58807802e-01
1.99518502e-01 3.36499698e-02 -1.00621343e+00 -5.19993067e-01
-6.34503722e-01 5.29007494e-01 3.41020763e-01 3.15442860e-01
1.88849315e-01 -9.62286294e-01 -8.79724145e-01 -6.03864640e-02
4.94669348e-01 8.79375264e-02 1.56936929e-01 5.96012115e-01
-5.06173372e-01 7.60988593e-01 -1.38920173e-01 -4.75150615e-01
-8.07375491e-01 3.32335025e-01 2.79567808e-01 -6.15169704e-01
-1.96700376e-02 8.75922978e-01 -1.59944355e-01 -1.00591445e+00
-2.91738331e-01 -5.26443541e-01 -2.15385646e-01 4.52550203e-02
3.52283329e-01 -1.95004418e-02 4.20940995e-01 -3.96108061e-01
-1.93921953e-01 1.45872474e-01 -2.13252187e-01 -2.29948476e-01
1.23286474e+00 1.05810643e-03 -3.56937259e-01 3.52356672e-01
8.96389604e-01 3.84650618e-01 -5.59792578e-01 -2.84073442e-01
5.19375384e-01 -3.47367167e-01 -5.18892884e-01 -1.34928441e+00
-2.30722427e-01 9.48660970e-01 4.54015918e-02 5.21628022e-01
1.00446069e+00 2.30320230e-01 8.52352917e-01 7.85619020e-01
7.14682519e-01 -7.29292452e-01 -9.52608809e-02 1.05156469e+00
8.87696326e-01 -1.37359738e+00 -1.41041130e-01 -1.99109286e-01
-7.02494442e-01 1.12819004e+00 7.07410753e-01 -4.53003868e-02
1.35762751e-01 -1.37525305e-01 4.05109048e-01 -3.42222661e-01
-1.00691736e+00 -2.72898942e-01 4.50292438e-01 5.89588046e-01
8.02121878e-01 -1.32961869e-01 -4.59531814e-01 7.17575073e-01
-6.17425442e-01 -1.30565375e-01 4.95627820e-01 1.12265277e+00
-4.42722023e-01 -1.57489157e+00 -4.42205131e-01 5.66783786e-01
-5.55129826e-01 -2.81460971e-01 -6.55453324e-01 1.16221046e+00
-6.78788172e-03 1.07115138e+00 -2.29717165e-01 -1.76106855e-01
4.60795552e-01 7.18552113e-01 7.83075094e-01 -7.12310493e-01
-9.93202686e-01 -7.74165392e-01 7.47062206e-01 -5.16937673e-01
-5.18223420e-02 -6.05578780e-01 -9.37321603e-01 -2.02961937e-01
-2.04176068e-01 4.84982312e-01 1.81566626e-01 1.24481952e+00
3.06827039e-01 -4.53734584e-02 4.82307337e-02 5.64633776e-03
-1.14562321e+00 -1.08920527e+00 -1.82882220e-01 7.61751711e-01
3.74850571e-01 -2.71553159e-01 -3.19461733e-01 -1.10725537e-01] | [11.164799690246582, 8.06218433380127] |
bab49e6b-d9c3-4272-89ae-d92a99b3a222 | physics-informed-neural-networks-based-model | 2109.10793 | null | https://arxiv.org/abs/2109.10793v1 | https://arxiv.org/pdf/2109.10793v1.pdf | Physics-informed Neural Networks-based Model Predictive Control for Multi-link Manipulators | We discuss nonlinear model predictive control (NMPC) for multi-body dynamics via physics-informed machine learning methods. Physics-informed neural networks (PINNs) are a promising tool to approximate (partial) differential equations. PINNs are not suited for control tasks in their original form since they are not designed to handle variable control actions or variable initial values. We thus present the idea of enhancing PINNs by adding control actions and initial conditions as additional network inputs. The high-dimensional input space is subsequently reduced via a sampling strategy and a zero-hold assumption. This strategy enables the controller design based on a PINN as an approximation of the underlying system dynamics. The additional benefit is that the sensitivities are easily computed via automatic differentiation, thus leading to efficient gradient-based algorithms. Finally, we present our results using our PINN-based MPC to solve a tracking problem for a complex mechanical system, a multi-link manipulator. | ['Benjamin Unger', 'Jörg Fehr', 'Jonas Kneifl', 'Jonas Nicodemus'] | 2021-09-22 | null | null | null | null | ['physics-informed-machine-learning'] | ['graphs'] | [ 1.46778226e-01 4.85997975e-01 -4.64902341e-01 5.25267899e-01
-2.40353554e-01 -3.36828172e-01 6.18275344e-01 7.38200918e-02
-5.27619958e-01 1.16268373e+00 -5.03438771e-01 -1.37035489e-01
-6.18712783e-01 -5.33247173e-01 -8.74617159e-01 -9.35555995e-01
-6.62084147e-02 7.73491919e-01 -7.82139599e-02 -5.38655639e-01
2.40943935e-02 7.52311110e-01 -9.40551102e-01 -4.24653739e-01
9.17687654e-01 7.57467687e-01 8.41939822e-02 7.54801393e-01
4.26097840e-01 6.98857427e-01 -1.20488293e-01 4.53435928e-02
3.91129673e-01 -2.48924091e-01 -5.61678231e-01 5.60364835e-02
-1.21251583e-01 -1.70667067e-01 -1.86372325e-01 1.01632643e+00
5.59214711e-01 9.61504757e-01 7.64272511e-01 -1.20009458e+00
-1.61724210e-01 3.13154936e-01 -5.26506975e-02 -3.32874715e-01
-1.92916214e-01 3.53895634e-01 7.02498972e-01 -5.29123187e-01
6.16218090e-01 1.31419790e+00 8.94827604e-01 5.95882952e-01
-1.63388205e+00 -3.56405438e-03 7.42735714e-02 6.72858059e-02
-1.24051571e+00 1.19905666e-01 7.28215694e-01 -7.89844513e-01
5.11388302e-01 3.96323800e-01 8.17693293e-01 9.51746106e-01
6.52103901e-01 4.49193627e-01 9.33519840e-01 -2.88897157e-01
5.72601616e-01 7.23037124e-02 -1.76018640e-01 6.30685389e-01
2.04569012e-01 5.11517406e-01 1.01678021e-01 -2.87561864e-01
1.27968514e+00 -2.78268047e-02 -4.92199987e-01 -8.32952142e-01
-1.16000831e+00 1.21697545e+00 7.00704813e-01 3.00747231e-02
-7.99804509e-01 3.13919693e-01 3.27127576e-01 1.82540238e-01
3.60332012e-01 1.09043157e+00 -6.11571848e-01 1.18432358e-01
-5.19666374e-01 9.04492974e-01 1.05606508e+00 8.38377297e-01
4.57383007e-01 5.70760906e-01 -5.11124879e-02 5.46181321e-01
2.34003700e-02 3.88807744e-01 2.13172421e-01 -1.46059883e+00
6.62422404e-02 3.39170486e-01 6.18144155e-01 -8.13796699e-01
-6.85810685e-01 -5.20825624e-01 -1.12645745e+00 6.90026760e-01
5.06522596e-01 -6.86328411e-01 -6.82248771e-01 1.68153036e+00
5.67221105e-01 -2.08025709e-01 -1.32242039e-01 1.19187856e+00
-2.53136456e-01 1.00303304e+00 -5.71999066e-02 -4.22728926e-01
1.10948920e+00 -8.14449310e-01 -7.35975027e-01 1.59665853e-01
5.36902189e-01 -1.95847735e-01 8.01585615e-01 6.95035636e-01
-1.19513345e+00 -4.62302506e-01 -9.14146066e-01 3.47412109e-01
-3.49448860e-01 8.09026212e-02 1.13222353e-01 -6.62997141e-02
-7.20427513e-01 1.51431322e+00 -1.00641680e+00 4.65937927e-02
-2.08723992e-01 6.67063594e-01 2.03397851e-02 6.45247817e-01
-1.23104763e+00 1.38566482e+00 7.81404376e-01 4.14616644e-01
-5.86931467e-01 -9.21324551e-01 -6.53666019e-01 -9.09944400e-02
9.73615050e-01 -9.59827185e-01 1.26292408e+00 -9.45769548e-01
-2.17880201e+00 1.06891179e-02 3.00937086e-01 -5.74013829e-01
7.41129577e-01 -1.06484398e-01 1.88887209e-01 1.94140881e-01
-4.09392834e-01 5.20412862e-01 1.03145516e+00 -1.16801989e+00
-1.40441626e-01 3.28953624e-01 1.18282340e-01 8.05031285e-02
8.49887822e-03 -4.92784053e-01 -3.75186279e-02 -8.70928288e-01
-2.83315480e-01 -1.39617074e+00 -8.48556578e-01 3.25374693e-01
-6.28842175e-01 4.86078635e-02 4.95633096e-01 -6.79389000e-01
6.95759475e-01 -1.48524952e+00 9.43591118e-01 3.19741756e-01
-1.98090374e-02 5.20109832e-01 4.44212332e-02 6.34045124e-01
-1.68805167e-01 -1.46399736e-01 -3.55620682e-01 1.24066785e-01
1.26658380e-01 2.55547225e-01 -2.30771676e-01 3.16672832e-01
5.01778662e-01 7.02092648e-01 -8.34601581e-01 -3.57278913e-01
4.78274167e-01 5.92072904e-01 -6.71554804e-01 -6.89357659e-03
-8.01925719e-01 8.55239809e-01 -8.17032933e-01 -1.74932536e-02
3.40735793e-01 5.16475551e-02 5.15709221e-02 -2.00522229e-01
-4.23281491e-01 -3.74301285e-01 -1.29793644e+00 1.26044023e+00
-7.97154546e-01 2.56655991e-01 7.03942776e-01 -1.28951299e+00
8.72356236e-01 4.44255918e-01 6.20757341e-01 -1.62074581e-01
6.29917145e-01 3.60045165e-01 1.34107322e-01 -2.96542615e-01
2.42190748e-01 -5.21161914e-01 1.14633441e-01 -2.19354227e-01
-9.73893404e-02 -5.14866710e-01 8.31605345e-02 -3.76214325e-01
7.02361107e-01 3.63407046e-01 4.04254854e-01 -6.32051170e-01
1.01933575e+00 4.29573834e-01 7.23024428e-01 2.38592103e-01
1.95242003e-01 1.41260192e-01 6.03913844e-01 -1.89842984e-01
-1.35203588e+00 -6.62362158e-01 -7.45374486e-02 5.42134404e-01
-2.31697872e-01 2.37544298e-01 -7.56942987e-01 6.78177401e-02
2.72770077e-01 8.23598206e-01 -4.39133167e-01 -3.65931451e-01
-1.01178968e+00 -3.65095258e-01 -2.51257747e-01 4.86101598e-01
-1.25491887e-01 -7.47600555e-01 -6.44069672e-01 6.92867041e-01
2.96560585e-01 -7.96668708e-01 -1.71506345e-01 3.34984004e-01
-1.07911503e+00 -1.07885838e+00 -1.07877994e+00 -5.02415538e-01
5.42021930e-01 -8.94566655e-01 4.47149605e-01 -2.63920158e-01
-2.24198088e-01 3.95243287e-01 2.63938159e-01 -3.15013558e-01
-7.70225823e-01 1.01191923e-01 5.14116824e-01 -1.34570450e-01
-6.69770122e-01 -3.72156024e-01 -2.05973819e-01 3.32712114e-01
-6.08641922e-01 5.04067875e-02 5.72239459e-01 1.13499618e+00
8.16213489e-01 5.35681583e-02 6.17154300e-01 -5.29261529e-01
6.93082750e-01 -1.60209894e-01 -1.46266901e+00 -1.89606726e-01
-3.20181161e-01 2.57392347e-01 1.40875828e+00 -1.04187620e+00
-9.88068044e-01 4.19169217e-01 -1.53517708e-01 -7.89963901e-01
1.43205881e-01 4.61830258e-01 1.13031298e-01 -4.44088578e-01
3.10627788e-01 -2.97641419e-02 5.31544566e-01 -7.28250504e-01
4.46211457e-01 1.24036148e-01 6.12301767e-01 -8.81093383e-01
8.75854194e-01 -3.90182845e-02 9.80324626e-01 -8.68126988e-01
-3.10438663e-01 -7.73483962e-02 -8.06975484e-01 -1.62966087e-01
7.76668310e-01 -5.29553235e-01 -1.43387163e+00 2.22952321e-01
-1.15185630e+00 -6.77416086e-01 -6.31606579e-01 7.17596233e-01
-1.25989485e+00 2.02406794e-02 -9.13289309e-01 -1.34262383e+00
-3.18262815e-01 -1.12524867e+00 6.20921373e-01 1.35723576e-01
-2.42400363e-01 -1.21665323e+00 1.51796162e-01 -3.07155669e-01
4.88196075e-01 8.56910765e-01 1.15335095e+00 -2.94296116e-01
-3.76291573e-01 -3.46627623e-01 4.06875938e-01 3.18204105e-01
-2.27971345e-01 2.82822065e-02 -4.42223847e-01 -5.53665996e-01
2.39798829e-01 -5.85253872e-02 2.88087845e-01 6.76625013e-01
8.68479848e-01 -6.76178038e-01 -5.57116985e-01 2.67914772e-01
1.72867262e+00 3.63125026e-01 -2.13912398e-01 3.26822728e-01
7.82818973e-01 7.56778300e-01 5.41535378e-01 3.14506888e-01
-2.58768827e-01 1.05037200e+00 6.59786999e-01 1.15276664e-01
3.77990305e-01 -5.43073267e-02 2.41094604e-01 4.93832439e-01
-3.25698167e-01 3.09769083e-02 -7.40131795e-01 4.70517009e-01
-1.92975926e+00 -4.12139475e-01 -5.06785929e-01 2.21792293e+00
8.03905725e-01 -1.43771797e-01 3.44706118e-01 1.30936071e-01
1.05468738e+00 -4.36767042e-01 -8.56920838e-01 -5.19570529e-01
2.09307343e-01 5.05845807e-02 6.78867102e-01 6.75122261e-01
-1.05191600e+00 3.07431519e-01 5.45858955e+00 8.32873285e-01
-1.21977198e+00 -1.97288617e-01 3.18095803e-01 -8.07767436e-02
4.66268808e-01 -1.62925586e-01 -6.13023698e-01 5.28005838e-01
1.13922727e+00 -2.66253024e-01 6.19142711e-01 1.06581807e+00
7.83497512e-01 4.07866761e-02 -9.40525293e-01 4.64318573e-01
-7.27694750e-01 -1.33528626e+00 -3.07901353e-01 1.34106576e-01
8.55866194e-01 -3.18735749e-01 -4.84201089e-02 1.09804288e-01
1.04376055e-01 -5.56619167e-01 8.73464882e-01 8.17106009e-01
2.97225654e-01 -8.25311661e-01 6.38517141e-01 5.93604624e-01
-7.26177871e-01 -3.99535716e-01 -3.56613964e-01 -3.20374787e-01
6.98643267e-01 4.60954726e-01 -4.64038551e-01 5.29147685e-01
-1.08215801e-01 3.59649420e-01 1.19705305e-01 1.24855769e+00
2.40045208e-02 2.44084343e-01 -4.84981447e-01 -6.09090149e-01
4.01613623e-01 -6.01225972e-01 1.16514802e+00 6.61769986e-01
2.09974930e-01 -6.76137432e-02 2.48057857e-01 1.26635027e+00
5.22467136e-01 -6.60601333e-02 -4.96747196e-01 1.34765580e-01
-7.77662024e-02 1.18097091e+00 -4.41110611e-01 -1.68993816e-01
2.53503889e-01 5.59840739e-01 -1.07102748e-02 3.63893718e-01
-7.47471273e-01 -6.36272311e-01 7.66825080e-01 2.65865624e-02
2.44000852e-01 -4.71142620e-01 9.76373777e-02 -8.90089393e-01
-9.92844701e-02 -6.24981999e-01 -5.31791374e-02 -6.20045602e-01
-1.21113575e+00 2.44044632e-01 2.47007564e-01 -1.34230006e+00
-8.86672556e-01 -1.08588672e+00 -4.87867057e-01 9.61736858e-01
-1.29720044e+00 -5.41627467e-01 4.81685936e-01 2.77240813e-01
3.24386150e-01 2.85100549e-01 7.44687796e-01 8.60598162e-02
-7.44868815e-01 -1.71413645e-01 5.78401268e-01 -1.80812374e-01
1.95213318e-01 -1.47134709e+00 -1.23394832e-01 5.41475594e-01
-9.10125673e-01 5.04571438e-01 1.23833466e+00 -5.63828528e-01
-1.87659895e+00 -1.20211792e+00 3.30638736e-01 4.65488620e-02
1.10694253e+00 -1.03522085e-01 -1.05661058e+00 5.04775941e-01
1.03392147e-01 7.57954316e-03 -4.71857667e-01 -4.87325996e-01
7.57022202e-01 -7.13168234e-02 -1.13891339e+00 7.61401355e-01
3.88660610e-01 2.51563620e-02 -4.14703459e-01 3.96213561e-01
7.86686599e-01 -6.27801180e-01 -1.19130790e+00 3.69580507e-01
3.10882866e-01 1.17219575e-02 1.01399255e+00 -6.13806844e-01
3.25937212e-01 -4.01025832e-01 3.28840464e-01 -1.77246654e+00
-3.16893667e-01 -1.17485249e+00 -5.27568042e-01 9.24734652e-01
1.67266056e-01 -9.37737286e-01 7.75489032e-01 5.44391453e-01
-1.56144112e-01 -1.06778121e+00 -9.55059707e-01 -1.28025711e+00
4.66103673e-01 -1.33802399e-01 1.21175162e-01 7.04348981e-01
4.84053008e-02 1.16546750e-01 -5.02500653e-01 3.36546361e-01
5.96308231e-01 -1.29195839e-01 5.03820837e-01 -1.19630599e+00
-6.01092875e-01 -5.64453542e-01 -9.65209380e-02 -7.70896375e-01
3.95523310e-01 -3.50324184e-01 3.95776689e-01 -1.16345930e+00
-4.86716986e-01 -2.94896811e-01 1.55977905e-01 1.91068992e-01
-2.19940934e-02 -1.21299706e-01 2.91094214e-01 -6.45685121e-02
1.89606935e-01 8.40579271e-01 1.39458025e+00 -1.70409217e-01
-4.86848384e-01 5.98003924e-01 8.01500380e-02 7.91679442e-01
9.20764148e-01 -2.00265795e-01 -4.33816135e-01 5.74187152e-02
6.84329942e-02 5.20633459e-01 6.45284057e-01 -1.14275563e+00
2.33952217e-02 -3.78329635e-01 1.47334486e-01 -5.70005715e-01
6.86233222e-01 -1.02737367e+00 4.04938877e-01 1.19791174e+00
-3.18260580e-01 3.26642133e-02 2.91104674e-01 6.05595171e-01
-1.97567701e-01 -4.82167363e-01 1.15862429e+00 -9.19533074e-02
-3.71097207e-01 2.08632246e-01 -7.77294159e-01 -3.79378021e-01
7.83144236e-01 1.80163711e-01 9.71124917e-02 -3.00837517e-01
-1.18833232e+00 3.66253287e-01 4.33728725e-01 -2.20923703e-02
4.04959843e-02 -1.19068158e+00 -2.61952907e-01 -1.49425268e-01
-4.71087009e-01 -2.33845841e-02 1.41738698e-01 9.03731883e-01
-5.20155549e-01 7.41572917e-01 -3.80680442e-01 -4.62030202e-01
-6.62683964e-01 8.75715435e-01 7.44081855e-01 -3.52558315e-01
-5.54270685e-01 3.27613920e-01 -6.73042685e-02 -7.16028571e-01
-4.35438976e-02 -7.92772412e-01 4.50279713e-02 -2.01496556e-01
3.16650867e-02 7.70766318e-01 -7.69787580e-02 -2.58677125e-01
2.44753808e-02 7.24612653e-01 5.99620581e-01 -2.38987371e-01
1.48326147e+00 1.40093744e-01 1.31437108e-01 5.03151536e-01
1.01920402e+00 -6.27804995e-01 -1.61492622e+00 5.07836677e-02
-3.92459668e-02 2.34780610e-01 1.65393457e-01 -6.03996754e-01
-9.66298342e-01 6.50160015e-01 3.15790027e-01 2.01080710e-01
8.66045296e-01 -6.93248510e-01 4.53256547e-01 7.08258212e-01
2.92988420e-01 -1.21102464e+00 -2.97392935e-01 7.39520013e-01
1.13123739e+00 -6.79051638e-01 1.02098502e-01 -5.60553193e-01
-3.32879364e-01 1.45028317e+00 5.03675997e-01 -6.51542068e-01
4.38576996e-01 1.91798374e-01 -3.58822167e-01 3.47764939e-01
-6.17118001e-01 3.16838995e-02 4.52068359e-01 5.54930806e-01
6.30482733e-02 -4.95733693e-02 -7.06318319e-01 2.98767716e-01
1.48684546e-01 1.11225620e-01 5.82249582e-01 8.63408387e-01
-3.57309848e-01 -1.09483016e+00 -6.40629590e-01 1.38748392e-01
-2.01855764e-01 3.61130893e-01 -1.95512474e-02 1.40316987e+00
-1.38712883e-01 5.09186625e-01 -1.36827201e-01 1.07521951e-01
5.77456653e-01 1.64987102e-01 5.26794016e-01 -3.76840025e-01
-3.79185885e-01 1.16447829e-01 1.66323576e-02 -5.99497557e-01
-4.91690710e-02 -5.53574979e-01 -1.20456564e+00 -1.46973088e-01
-5.71555257e-01 2.45506078e-01 7.91406333e-01 8.38236928e-01
1.86728835e-01 6.92621052e-01 3.12385708e-01 -1.56713247e+00
-1.10553217e+00 -8.03882301e-01 -6.20968103e-01 -2.03392729e-01
6.02019668e-01 -1.05645537e+00 -1.64810732e-01 -1.75336689e-01] | [5.429316997528076, 2.6298117637634277] |
057eaa32-558a-4714-9380-c2c7f2bb8c0f | self-improving-slam-in-dynamic-environments | 2210.08350 | null | https://arxiv.org/abs/2210.08350v3 | https://arxiv.org/pdf/2210.08350v3.pdf | Self-Improving SLAM in Dynamic Environments: Learning When to Mask | Visual SLAM - Simultaneous Localization and Mapping - in dynamic environments typically relies on identifying and masking image features on moving objects to prevent them from negatively affecting performance. Current approaches are suboptimal: they either fail to mask objects when needed or, on the contrary, mask objects needlessly. Thus, we propose a novel SLAM that learns when masking objects improves its performance in dynamic scenarios. Given a method to segment objects and a SLAM, we give the latter the ability of Temporal Masking, i.e., to infer when certain classes of objects should be masked to maximize any given SLAM metric. We do not make any priors on motion: our method learns to mask moving objects by itself. To prevent high annotations costs, we created an automatic annotation method for self-supervised training. We constructed a new dataset, named ConsInv, which includes challenging real-world dynamic sequences respectively indoors and outdoors. Our method reaches the state of the art on the TUM RGB-D dataset and outperforms it on KITTI and ConsInv datasets. | ['Hervé Le Borgne', 'Mohamed Tamaazousti', 'Romain Dupont', 'Adrian Bojko'] | 2022-10-15 | null | null | null | null | ['simultaneous-localization-and-mapping'] | ['computer-vision'] | [ 2.74735570e-01 -9.43924710e-02 -5.11737093e-02 -5.22220135e-01
-5.45380831e-01 -7.53322363e-01 5.74108183e-01 -9.10953581e-02
-6.69814110e-01 6.36980534e-01 -1.30152896e-01 -1.81172431e-01
1.60279080e-01 -3.12980145e-01 -1.03718257e+00 -5.40986657e-01
-3.14391255e-01 6.54536247e-01 7.73819685e-01 -1.43618375e-01
2.75399357e-01 4.54294682e-01 -1.65722859e+00 -2.63965521e-02
8.66036773e-01 8.31326663e-01 7.10544169e-01 7.09089279e-01
1.25350595e-01 9.10342872e-01 -3.46108288e-01 2.07217947e-01
5.95077276e-01 -4.52717096e-01 -7.04681695e-01 1.74705952e-01
6.91483736e-01 -1.07641630e-01 -1.95394576e-01 9.70305145e-01
2.80952156e-01 2.52210826e-01 3.34605485e-01 -1.47587299e+00
-1.59285232e-01 3.40790570e-01 -6.59839571e-01 3.71703148e-01
3.50515395e-01 4.24857438e-01 6.75961912e-01 -7.55310953e-01
8.30996633e-01 9.53868032e-01 7.55942345e-01 4.12381351e-01
-1.30214834e+00 -4.08802003e-01 5.44159055e-01 2.21186906e-01
-1.59765875e+00 -8.28613997e-01 4.98700976e-01 -6.61934495e-01
9.41811860e-01 3.36768597e-01 5.67830086e-01 1.02828789e+00
7.71385208e-02 6.67066276e-01 1.22752512e+00 -2.34956801e-01
4.48003650e-01 9.37115252e-02 -1.83709875e-01 8.76186669e-01
1.90177158e-01 1.76318035e-01 -8.37431848e-01 1.24524958e-01
5.13824224e-01 -2.40354314e-01 -2.12832928e-01 -1.11548805e+00
-1.61663294e+00 3.97582233e-01 5.60713649e-01 -8.68814811e-03
-2.28586093e-01 4.59275395e-01 3.37104648e-02 1.84811875e-01
3.06833684e-01 2.76085556e-01 -5.32608151e-01 -7.33833387e-02
-1.01281464e+00 1.91601202e-01 2.64538318e-01 1.08542585e+00
1.26000571e+00 -1.93070561e-01 1.02384180e-01 3.54507238e-01
1.54631689e-01 4.84942406e-01 2.47382820e-01 -9.52788293e-01
5.03517628e-01 3.17321956e-01 6.08208776e-01 -8.92463624e-01
-6.17938221e-01 -2.31507242e-01 -2.91718423e-01 3.58365625e-01
3.45919549e-01 6.77412376e-02 -1.29448855e+00 1.82227433e+00
5.09426415e-01 4.09674048e-01 -2.87528858e-02 1.29777014e+00
3.28171611e-01 3.19991887e-01 -2.16020525e-01 -4.80265822e-03
8.77538621e-01 -1.09555006e+00 -6.72057092e-01 -9.88213658e-01
6.58971727e-01 -6.48649812e-01 1.17126465e+00 2.77337968e-01
-5.47954202e-01 -6.14786506e-01 -1.15353835e+00 1.60026252e-01
-3.00568640e-01 1.04113154e-01 8.39268506e-01 4.73369330e-01
-1.04678297e+00 5.57584941e-01 -1.30276072e+00 -5.79923272e-01
1.36757225e-01 3.26290905e-01 -5.26588857e-01 9.49165076e-02
-6.94218218e-01 1.14360762e+00 4.43085849e-01 2.26296276e-01
-1.31612706e+00 -2.97104120e-01 -1.06389773e+00 -5.22792399e-01
6.42382681e-01 -5.12034118e-01 1.01205301e+00 -1.15847540e+00
-1.26912749e+00 1.01130235e+00 -2.83254385e-01 -6.68374062e-01
8.58427525e-01 -5.20085096e-01 -9.39052403e-02 -3.77199091e-02
4.38942462e-01 1.06027019e+00 7.65738904e-01 -1.59427142e+00
-8.06168616e-01 -2.23214507e-01 4.21519615e-02 4.07892823e-01
2.67773211e-01 -4.79232192e-01 -7.08319008e-01 -3.36166173e-01
7.21194446e-01 -1.25175548e+00 -4.65227336e-01 4.68739904e-02
-4.12463874e-01 3.15187544e-01 9.00520623e-01 -4.08224493e-01
5.73772848e-01 -2.11714053e+00 2.56332755e-01 1.05261346e-02
-4.52415086e-02 -2.14130640e-01 -1.23926617e-01 2.02979565e-01
2.63553619e-01 -6.26904443e-02 -3.78900558e-01 -7.68592417e-01
-8.72073248e-02 5.87092757e-01 -2.63143003e-01 1.08604038e+00
1.61583394e-01 7.79622555e-01 -1.01461780e+00 -4.93137032e-01
6.12691224e-01 9.90323275e-02 -6.80111408e-01 1.49889827e-01
-5.37001312e-01 9.70494390e-01 -1.06643260e-01 7.18182564e-01
9.09966052e-01 -1.29647359e-01 3.42443623e-02 1.90507069e-01
-3.42331290e-01 4.30004746e-01 -1.46998143e+00 2.36321735e+00
-4.53647405e-01 7.65050828e-01 1.20301366e-01 -6.59250140e-01
6.93254292e-01 -2.27871239e-01 5.27599573e-01 -6.75566852e-01
-7.74762630e-02 3.05913001e-01 -1.74454167e-01 -5.45518339e-01
6.22758746e-01 1.29132926e-01 -1.77990392e-01 1.14921495e-01
-6.31247461e-02 -1.83932349e-01 -3.81278992e-02 2.10515633e-01
1.33577740e+00 7.33626127e-01 2.80799717e-01 -3.19079071e-01
3.24094057e-01 3.08506906e-01 8.05489361e-01 1.09705412e+00
-3.66946012e-01 7.84872293e-01 5.85530140e-03 -4.64019090e-01
-6.99468851e-01 -1.13185382e+00 1.04926407e-01 1.06134558e+00
9.46362317e-01 -1.95813283e-01 -3.52955908e-01 -9.56533551e-01
1.15792118e-01 4.58834559e-01 -7.58029640e-01 -3.19863483e-02
-5.02682805e-01 -4.81600106e-01 2.47241646e-01 2.62095362e-01
3.24808389e-01 -9.84226823e-01 -1.29437590e+00 8.55786204e-02
-4.63450074e-01 -1.33949876e+00 -4.00256276e-01 7.11544633e-01
-5.53892612e-01 -9.74052846e-01 -1.24291539e-01 -5.30725598e-01
6.38295591e-01 6.47653937e-01 1.09374952e+00 3.83139439e-02
-1.49589911e-01 1.83543608e-01 -3.89127135e-01 -2.61305481e-01
-1.46104962e-01 1.04538046e-01 4.00348783e-01 1.89150516e-02
4.03122082e-02 -6.58177972e-01 -5.02458572e-01 5.18277645e-01
-4.89047706e-01 3.49447489e-01 6.86818719e-01 4.37669873e-01
7.29966938e-01 -3.70266795e-01 7.19377175e-02 -6.26339436e-01
-3.86587590e-01 -2.35980839e-01 -8.77469301e-01 1.12883598e-01
-3.81635696e-01 1.48392811e-01 2.48767242e-01 -5.07256031e-01
-6.80906594e-01 7.71331728e-01 2.45513767e-01 -4.89365339e-01
-2.82571405e-01 1.02577098e-01 -2.38549426e-01 -5.72836936e-01
6.96420729e-01 2.25600928e-01 -4.45368886e-01 -5.16900659e-01
4.10970926e-01 3.17805409e-01 7.59675503e-01 -3.96671832e-01
9.26442802e-01 9.92477357e-01 -1.22071719e-02 -5.51628172e-01
-8.81565571e-01 -7.71513462e-01 -9.39444125e-01 -2.84269184e-01
9.24172461e-01 -1.06957269e+00 -5.24832249e-01 7.37570077e-02
-1.01228034e+00 -7.14661956e-01 -1.28563240e-01 3.76412809e-01
-8.16706479e-01 3.45070004e-01 -7.20672682e-02 -8.65377069e-01
3.26461524e-01 -1.13322532e+00 1.21699643e+00 -9.71713811e-02
-1.03039823e-01 -6.16933644e-01 1.67279184e-01 6.54577985e-02
2.23559827e-01 5.18918037e-01 -1.46296248e-02 -3.25873554e-01
-1.09436774e+00 1.26864910e-01 -4.41064648e-02 -7.50618707e-03
2.00190261e-01 -5.21067381e-01 -1.00660825e+00 -4.02952582e-01
-1.89813361e-01 -4.05127525e-01 1.06995809e+00 5.07905334e-02
8.76717269e-01 -1.76161125e-01 -6.10432565e-01 1.01424444e+00
1.48023784e+00 9.61816311e-03 3.78420264e-01 6.43756628e-01
8.09805036e-01 5.10741651e-01 9.61554050e-01 3.59152585e-01
4.69851792e-01 9.99903679e-01 9.00895774e-01 -1.40006498e-01
-5.82342781e-02 -4.81449842e-01 3.58188927e-01 2.21500322e-01
1.29636571e-01 -2.89698958e-01 -1.13278973e+00 7.31994033e-01
-2.11063504e+00 -5.88337481e-01 -6.29011467e-02 2.21217418e+00
5.43378353e-01 3.21386486e-01 -1.67244688e-01 -2.48516634e-01
3.29001516e-01 3.82134676e-01 -4.84098732e-01 3.33987504e-01
-2.29711726e-01 -2.50405490e-01 1.05016375e+00 9.02236581e-01
-1.37225401e+00 1.45236313e+00 5.54690933e+00 2.80830652e-01
-1.14952409e+00 4.25831050e-01 -9.26315635e-02 -1.87022761e-01
-1.14299050e-02 4.88074392e-01 -7.48027265e-01 3.76746684e-01
5.58636487e-01 4.35280651e-01 5.28505206e-01 8.35618258e-01
2.79970050e-01 -6.94752157e-01 -1.17672479e+00 9.78507221e-01
5.00007533e-02 -1.19208121e+00 -4.37561095e-01 4.37596142e-02
7.45442390e-01 4.66598123e-01 -1.37414560e-01 8.77805278e-02
5.24467766e-01 -7.99077928e-01 1.44674170e+00 4.15348947e-01
3.90385121e-01 -3.94525796e-01 5.26629031e-01 6.53031588e-01
-1.09999526e+00 1.61885440e-01 -2.11952627e-01 -2.87451774e-01
2.54963934e-01 2.18688354e-01 -1.03738201e+00 6.79467916e-01
7.12575734e-01 7.59421647e-01 -1.00793672e+00 1.16520226e+00
-3.23515981e-01 2.63018906e-01 -5.38347900e-01 1.81558847e-01
3.30710351e-01 2.50428822e-02 6.59674227e-01 1.23954117e+00
1.69450015e-01 -2.92220801e-01 7.29708731e-01 6.14748061e-01
4.12095636e-01 -2.49611557e-01 -6.56678319e-01 5.21915376e-01
4.49381918e-01 1.04726124e+00 -1.13924730e+00 -1.76571742e-01
-1.17872640e-01 1.40844977e+00 4.68163341e-01 2.83209801e-01
-9.68168736e-01 2.12585554e-01 8.37637842e-01 1.13193773e-01
3.89769137e-01 -6.35037303e-01 -3.31817299e-01 -1.30431461e+00
1.21986233e-01 -4.92778122e-01 2.14307696e-01 -8.13865900e-01
-7.32066214e-01 5.14431119e-01 -1.28060222e-01 -1.36627984e+00
-6.47293553e-02 -2.62529612e-01 -6.67388225e-03 6.06864333e-01
-1.53091347e+00 -1.18049729e+00 -7.69358873e-01 4.46017385e-01
5.34026206e-01 3.81578594e-01 3.59137684e-01 2.13328227e-01
-1.51931331e-01 6.62101731e-02 -1.56119689e-01 -1.11332797e-01
9.05085564e-01 -1.21093535e+00 4.60141271e-01 1.45311105e+00
6.09490693e-01 3.64224762e-01 1.19236624e+00 -8.08436215e-01
-1.37259722e+00 -1.08300591e+00 7.57612884e-01 -9.33101833e-01
4.00740594e-01 -1.00365460e+00 -6.79999948e-01 1.07357669e+00
-1.82685822e-01 4.41818744e-01 -1.74610764e-02 -5.95761351e-02
-1.29320472e-01 -4.87553813e-02 -9.12829936e-01 5.10092735e-01
1.60894001e+00 -3.46006334e-01 -3.67558718e-01 5.52032173e-01
8.03652644e-01 -8.61870527e-01 5.69107418e-04 6.64355695e-01
3.31219405e-01 -1.25793540e+00 9.07487035e-01 -4.02391732e-01
-3.05844158e-01 -1.06364679e+00 -5.16633868e-01 -1.09322727e+00
-5.56846000e-02 -5.20890892e-01 -1.18305646e-01 1.00425231e+00
1.73933804e-01 -4.03712094e-01 9.81692493e-01 9.10729691e-02
-3.32434803e-01 -1.25171483e-01 -1.25580847e+00 -1.16565740e+00
-6.63073421e-01 -7.41977870e-01 3.29129100e-01 9.80521619e-01
-5.68461776e-01 -3.00316270e-02 -7.36099958e-01 7.58814633e-01
6.25946641e-01 1.02804422e-01 1.30824268e+00 -8.06459844e-01
-1.86397657e-01 -1.26190081e-01 -6.27017558e-01 -1.29645896e+00
1.68571919e-01 -7.44454622e-01 8.16859484e-01 -1.38361681e+00
-1.04458258e-01 -8.39845479e-01 -1.68714970e-01 6.77941620e-01
-1.21433668e-01 5.44522285e-01 7.70812631e-02 3.82193923e-01
-1.12842083e+00 4.24089015e-01 7.38581419e-01 3.83120659e-03
-4.32016134e-01 -1.74729586e-01 -1.23978496e-01 7.02791631e-01
5.48875093e-01 -7.09171236e-01 -3.07836264e-01 -6.32747948e-01
2.47752130e-01 -6.61600893e-03 7.43254006e-01 -1.33752084e+00
2.97164649e-01 -4.23422009e-01 2.39352092e-01 -8.67306352e-01
4.61145490e-01 -9.35800076e-01 3.53465050e-01 6.26729190e-01
-1.08629666e-01 3.34689743e-04 1.73359647e-01 6.18660629e-01
1.31549701e-01 -2.83779968e-02 7.24411905e-01 -1.65450379e-01
-1.35155964e+00 2.28815898e-01 -2.38750681e-01 -4.06005420e-02
1.08260500e+00 -1.76982030e-01 -6.30146116e-02 -2.60579407e-01
-6.01212621e-01 4.14182901e-01 1.13902891e+00 6.66710258e-01
5.18986881e-01 -1.12009382e+00 -3.09633315e-01 3.41945291e-01
4.96428937e-01 2.40730211e-01 8.77624601e-02 1.09871769e+00
-7.26517141e-01 2.38151208e-01 -7.15091974e-02 -1.09847474e+00
-1.17146921e+00 7.51046896e-01 4.44071740e-01 9.52363163e-02
-7.54250228e-01 1.02009594e+00 3.05340946e-01 -4.73938674e-01
3.62307727e-01 -4.90351945e-01 2.45193064e-01 -2.87640452e-01
2.68617660e-01 -2.29918342e-02 2.10500583e-01 -7.40385771e-01
-8.76937866e-01 5.18380821e-01 2.70461321e-01 -4.67171669e-01
1.04490352e+00 -6.37692094e-01 3.17570977e-02 7.80530274e-01
8.37975264e-01 2.97220469e-01 -1.85501122e+00 -1.98258862e-01
3.24290693e-01 -8.53832722e-01 -1.58004493e-01 -7.74488151e-01
-5.53058505e-01 5.30353606e-01 7.76772201e-01 -1.35638848e-01
8.85629952e-01 2.63380975e-01 2.77427018e-01 4.38142240e-01
9.89552915e-01 -9.50100720e-01 1.77819207e-01 6.50557280e-01
6.33752882e-01 -1.54590905e+00 3.72634493e-02 -3.51946324e-01
-7.49436319e-01 6.83461607e-01 8.01358759e-01 -1.52769491e-01
1.16199799e-01 4.29182678e-01 3.79362553e-01 -2.78697200e-02
-4.99625951e-01 -6.56231165e-01 2.30109006e-01 7.73856103e-01
-1.74832195e-01 -9.84817222e-02 9.45888534e-02 3.53398209e-04
-4.12579119e-01 -2.50853479e-01 3.10922474e-01 1.36818647e+00
-5.72892964e-01 -7.08952963e-01 -4.52270061e-01 -1.28365621e-01
-2.62556523e-02 9.95368809e-02 -5.67520201e-01 9.44927394e-01
6.45298243e-01 8.32450092e-01 -2.02411655e-02 -6.61266148e-01
1.23227634e-01 -1.25455767e-01 5.83249271e-01 -5.90029240e-01
-1.87138617e-01 -5.69056906e-02 9.61776003e-02 -9.77982640e-01
-6.99448943e-01 -9.26656604e-01 -1.21195877e+00 2.43326519e-02
-3.11822295e-01 -1.34128025e-02 8.38682413e-01 1.04421020e+00
2.48439357e-01 4.39582318e-01 3.78813207e-01 -1.28859484e+00
-1.48483545e-01 -7.80503511e-01 -2.62677342e-01 3.35659802e-01
8.01399112e-01 -9.42761004e-01 -3.25263172e-01 1.00558929e-01] | [7.6886444091796875, -2.1451621055603027] |
a9805586-bc58-440f-863e-2d4dee449530 | meshstereo-a-global-stereo-model-with-mesh | null | null | http://openaccess.thecvf.com/content_iccv_2015/html/Zhang_MeshStereo_A_Global_ICCV_2015_paper.html | http://openaccess.thecvf.com/content_iccv_2015/papers/Zhang_MeshStereo_A_Global_ICCV_2015_paper.pdf | MeshStereo: A Global Stereo Model With Mesh Alignment Regularization for View Interpolation | We present a novel global stereo model designed for view interpolation. Unlike existing stereo models which only output a disparity map, our model is able to output a 3D triangular mesh, which can be directly used for view interpolation. To this aim, we partition the input stereo images into 2D triangles with shared vertices. Lifting the 2D triangulation to 3D naturally generates a corresponding mesh. A technical difficulty is to properly split vertices to multiple copies when they appear at depth discontinuous boundaries. To deal with this problem, we formulate our objective as a two-layer MRF, with the upper layer modeling the splitting properties of the vertices and the lower layer optimizing a region-based stereo matching. Experiments on the Middlebury and the Herodion datasets demonstrate that our model is able to synthesize visually coherent new view angles with high PSNR, as well as outputting high quality disparity maps which rank at the first place on the new challenging high resolution Middlebury 3.0 benchmark. | ['Zhiwei Li', 'Yong Rui', 'Rui Cai', 'Hongyang Chao', 'Yanhua Cheng', 'Chi Zhang'] | 2015-12-01 | null | null | null | iccv-2015-12 | ['stereo-matching'] | ['computer-vision'] | [ 2.44945765e-01 1.71752065e-01 9.54616368e-02 -1.83380663e-01
-6.33773386e-01 -5.51782310e-01 5.61581790e-01 -6.75471872e-02
3.69999148e-02 6.79661691e-01 2.16503412e-01 -8.65596756e-02
4.03010428e-01 -9.04938817e-01 -9.86967325e-01 -5.33434153e-01
3.30222815e-01 6.56535625e-01 4.14270699e-01 -2.33795598e-01
3.23794246e-01 5.61900437e-01 -1.89005804e+00 6.21889412e-01
1.07415056e+00 9.38150764e-01 1.47236437e-01 6.22207105e-01
5.55023886e-02 4.08338070e-01 -2.79282145e-02 -3.54083568e-01
6.96381688e-01 -2.97410131e-01 -8.21955085e-01 4.22058493e-01
1.14618838e+00 -5.49892008e-01 2.95420773e-02 9.09577847e-01
3.19100052e-01 -1.20183855e-01 4.47923720e-01 -1.04066515e+00
-1.39551923e-01 6.98987693e-02 -7.61290848e-01 -4.08514947e-01
7.77971506e-01 1.92126236e-03 8.70232105e-01 -1.09502637e+00
1.20717072e+00 1.29458082e+00 6.40680134e-01 2.59788662e-01
-1.87110364e+00 -3.94369394e-01 -6.35343045e-02 7.49696344e-02
-1.32571411e+00 -3.78494978e-01 6.52474403e-01 -7.91085601e-01
6.34481788e-01 3.24933469e-01 8.87385726e-01 9.22562957e-01
1.32740587e-01 3.69498104e-01 1.46850109e+00 -2.64512867e-01
9.03039202e-02 -1.43194988e-01 -1.58217430e-01 6.00960553e-01
-4.39942703e-02 3.01712215e-01 -7.47942924e-01 -3.25314626e-02
1.19597363e+00 -1.99181587e-01 -5.85246980e-01 -8.96305919e-01
-1.44687867e+00 5.39493501e-01 5.24517357e-01 -1.74043640e-01
-2.93814898e-01 -5.82044646e-02 1.86895043e-01 2.98006862e-01
5.75277328e-01 4.53490466e-02 -1.75709888e-01 2.39374787e-01
-9.87365425e-01 4.57629055e-01 6.25880778e-01 1.05942452e+00
1.14121437e+00 -1.55970737e-01 -3.61734107e-02 7.32458293e-01
5.85683063e-02 4.55615550e-01 -1.76620364e-01 -1.46558988e+00
6.86976492e-01 5.29024839e-01 2.99116582e-01 -9.16173637e-01
-1.58067137e-01 -2.36040875e-01 -1.04987144e+00 8.43751907e-01
4.26908433e-01 4.25054520e-01 -9.26697075e-01 1.39283800e+00
4.29246336e-01 1.84457913e-01 -2.55165637e-01 9.42684352e-01
7.31528997e-01 5.48620343e-01 -5.24910152e-01 -5.79562746e-02
1.15089774e+00 -9.23489034e-01 -3.85415763e-01 -5.64541407e-02
1.90990716e-01 -9.29651260e-01 9.71994281e-01 6.43216610e-01
-1.62932754e+00 -7.66734898e-01 -1.02810669e+00 -7.06311882e-01
1.86305586e-02 -2.08407536e-01 1.36101454e-01 3.42083186e-01
-1.29549766e+00 6.04101539e-01 -5.64454079e-01 6.52096495e-02
1.11299157e-01 2.00558618e-01 -4.84968454e-01 -2.64985144e-01
-8.72243047e-01 7.09274948e-01 1.62395924e-01 -6.12493139e-03
-4.80668575e-01 -1.02405441e+00 -1.05246031e+00 -1.21972293e-01
1.50047526e-01 -1.38496685e+00 9.32314873e-01 -8.34420323e-01
-1.40681410e+00 1.35135543e+00 -4.84020263e-01 -2.96748817e-01
1.14354527e+00 1.40240312e-01 1.49198458e-01 1.39274240e-01
1.27550468e-01 1.04404032e+00 7.80876875e-01 -1.82257271e+00
-7.39913762e-01 -4.28353369e-01 1.32551625e-01 3.33689660e-01
3.67468774e-01 -5.80264390e-01 -7.22787261e-01 -6.32889748e-01
5.07367015e-01 -8.00239325e-01 -2.08597854e-01 3.42454106e-01
-4.88617927e-01 3.79787892e-01 4.17003661e-01 -7.76034534e-01
7.65373170e-01 -2.04397798e+00 7.58945107e-01 3.88900608e-01
5.47149003e-01 -2.48650163e-01 1.17001511e-01 1.02467425e-01
-5.64318746e-02 -2.30589598e-01 -3.04156005e-01 -8.10517848e-01
-1.70881689e-01 1.79840952e-01 -2.24850550e-01 3.20501983e-01
-1.60215706e-01 6.18950188e-01 -8.42565179e-01 -3.89638454e-01
5.22914469e-01 8.06923687e-01 -9.95995224e-01 1.12762846e-01
-1.30268082e-01 9.82037425e-01 -1.72254946e-02 3.55166316e-01
1.16322720e+00 -1.34220257e-01 4.89842221e-02 -4.92754132e-01
-4.02962089e-01 2.61686414e-01 -1.49251986e+00 1.98645651e+00
-6.97124183e-01 5.74646056e-01 3.07309896e-01 -2.72078961e-01
7.52048790e-01 1.43738106e-01 3.91957223e-01 -8.57377052e-01
-1.67550921e-01 3.22455287e-01 -5.80322564e-01 2.81373914e-02
7.14156806e-01 -1.36747882e-01 2.69115865e-01 -3.38282473e-02
-2.81151026e-01 -5.08535326e-01 1.19390879e-02 5.63733205e-02
6.10077322e-01 3.28844965e-01 -1.96781531e-02 -3.24110836e-01
6.97781146e-01 -6.50563166e-02 4.42420423e-01 2.51689076e-01
5.83719134e-01 1.36842561e+00 5.66886008e-01 -4.96814519e-01
-1.45103192e+00 -1.43322468e+00 -2.80756414e-01 3.48549843e-01
2.79961467e-01 -2.96020031e-01 -6.83711886e-01 -1.22041017e-01
1.38145627e-03 4.87018734e-01 -6.38916790e-01 3.89847517e-01
-6.12744808e-01 7.29100555e-02 -1.39621913e-01 2.94093341e-01
5.58646500e-01 -6.26844347e-01 -6.87350869e-01 6.93603233e-02
-6.26767159e-01 -1.33001053e+00 -5.70149302e-01 -8.92442912e-02
-1.06594276e+00 -9.94002521e-01 -1.11722112e+00 -8.22077751e-01
8.09323788e-01 2.58002043e-01 1.51768458e+00 -3.17897312e-02
-5.17118648e-02 1.10984899e-01 8.06929320e-02 2.13450164e-01
-4.90828216e-01 -2.01865807e-02 -3.15126956e-01 1.60388336e-01
-3.92674506e-01 -8.01705062e-01 -7.32170105e-01 4.63626772e-01
-1.03179991e+00 8.88881087e-01 -7.32428953e-02 7.66538799e-01
9.80213106e-01 -4.22521651e-01 -1.15800336e-01 -9.38942909e-01
-5.01145348e-02 -1.10874176e-02 -9.52706099e-01 6.25267699e-02
-2.98670948e-01 9.96397585e-02 6.67857945e-01 1.27697617e-01
-9.67295468e-01 3.75371844e-01 -2.04864115e-01 -6.18661463e-01
-1.05417166e-02 4.23157103e-02 -2.26740733e-01 -8.81502181e-02
5.02939105e-01 6.88303262e-02 -7.04725608e-02 -6.38851464e-01
3.37712198e-01 2.03351498e-01 7.13201165e-01 -5.52179813e-01
8.68703127e-01 9.34785485e-01 4.32014227e-01 -8.30283225e-01
-5.74138165e-01 -3.81535590e-01 -1.04803813e+00 -2.89108664e-01
1.01213968e+00 -1.05938089e+00 -6.65736258e-01 4.84205276e-01
-1.25044250e+00 -4.25996691e-01 -3.77085268e-01 5.83200566e-02
-9.35274720e-01 5.04945636e-01 -4.86212671e-01 -2.87654787e-01
3.99168171e-02 -1.41354847e+00 1.47774613e+00 -2.32734367e-01
2.91153695e-02 -1.02241886e+00 2.60720968e-01 4.97415066e-01
9.37520415e-02 5.79830527e-01 8.12042415e-01 6.59640491e-01
-1.10960209e+00 2.83916324e-01 -2.38688067e-01 2.46016666e-01
-1.54575706e-01 -3.21304910e-02 -1.07724893e+00 -1.83938414e-01
-1.58087865e-01 -1.73104301e-01 8.87542963e-01 3.89568120e-01
1.09043562e+00 1.21705048e-01 4.44902573e-03 1.19834602e+00
1.69240355e+00 -3.43515068e-01 9.80961144e-01 2.74038941e-01
9.58764434e-01 7.12973654e-01 3.44222069e-01 3.33945990e-01
6.42183840e-01 1.21394658e+00 6.22862995e-01 -2.82934517e-01
-3.34385127e-01 -4.74175364e-01 7.28882700e-02 6.26583695e-01
-5.01346767e-01 8.91850293e-02 -9.19416904e-01 3.00748408e-01
-1.69073200e+00 -7.50732839e-01 -7.56555080e-01 2.74358130e+00
7.28122115e-01 6.30616769e-02 4.09116335e-02 2.35436097e-01
4.23993289e-01 1.21874288e-01 -2.45413303e-01 -3.56382549e-01
-3.01427096e-01 2.69868582e-01 4.48498249e-01 1.08724499e+00
-6.42708778e-01 6.51091635e-01 5.84748030e+00 4.71642971e-01
-1.03330016e+00 -9.84555632e-02 6.58271611e-01 -4.73792478e-03
-6.90096140e-01 7.01947957e-02 -7.18021214e-01 3.17998409e-01
3.54385406e-01 -9.69511494e-02 5.56526363e-01 2.70578325e-01
2.81619251e-01 -2.59630680e-01 -1.39799404e+00 1.23131931e+00
-1.20057866e-01 -1.55525839e+00 3.68826807e-01 3.19371104e-01
1.19264722e+00 -1.71875745e-01 1.15424655e-01 -1.81121945e-01
5.62025327e-03 -1.14210618e+00 9.06864464e-01 6.34112656e-01
1.15711403e+00 -6.45408452e-01 2.48721525e-01 3.36167037e-01
-1.26777470e+00 4.90334779e-01 -3.79705608e-01 8.29940513e-02
4.20718879e-01 5.68402648e-01 -4.05080497e-01 9.66851592e-01
5.91215611e-01 8.98896694e-01 -4.20195937e-01 1.11015165e+00
-7.04698190e-02 -1.86205909e-01 -3.03548902e-01 9.19939399e-01
-2.44963095e-02 -5.79928696e-01 5.65354347e-01 6.94611013e-01
3.87323767e-01 -8.10150951e-02 1.18700385e-01 8.30208242e-01
-1.47197619e-01 -1.90357817e-03 -6.93354905e-01 9.75112438e-01
9.22167748e-02 8.93644035e-01 -4.94167536e-01 -3.49562526e-01
-3.71095389e-01 1.39986706e+00 3.49700063e-01 4.40032184e-01
-6.66484773e-01 1.68785036e-01 5.77996016e-01 5.47598720e-01
2.18787432e-01 -3.17168236e-01 -7.19786108e-01 -1.47553182e+00
3.28790724e-01 -9.44144309e-01 6.16076849e-02 -1.07136250e+00
-9.12876546e-01 6.27778053e-01 -9.35380980e-02 -1.61665797e+00
-2.05886215e-01 -4.75887507e-01 -1.82406828e-01 1.23590147e+00
-1.61275649e+00 -1.04471803e+00 -6.46797836e-01 6.87108457e-01
5.23280025e-01 6.11526310e-01 6.42630756e-01 4.47970241e-01
-4.60484289e-02 2.80376732e-01 8.50998983e-02 -2.83373535e-01
7.55824625e-01 -1.32836699e+00 5.77948868e-01 6.40277445e-01
-1.38294637e-01 2.47661605e-01 7.32266307e-01 -5.25501907e-01
-1.22521532e+00 -8.43953371e-01 1.07125127e+00 -4.97843623e-01
9.88114476e-02 -3.76205206e-01 -9.20806408e-01 6.84869766e-01
7.64153898e-02 8.84364545e-02 2.01173984e-02 -1.92405462e-01
-4.69316691e-01 -4.09280919e-02 -1.21914828e+00 6.64480686e-01
1.28338563e+00 -5.16512215e-01 -3.33542407e-01 1.73900798e-01
3.67035300e-01 -9.97679889e-01 -1.01421571e+00 3.53319943e-01
6.96861207e-01 -1.67787182e+00 1.35718465e+00 -1.20012812e-01
9.20419455e-01 -4.27959800e-01 -1.71525583e-01 -1.30209589e+00
-1.42141998e-01 -5.69263816e-01 1.31465286e-01 8.76077890e-01
2.20546454e-01 -4.37506765e-01 7.48547256e-01 4.00676101e-01
-1.31494522e-01 -6.59150600e-01 -1.01148307e+00 -6.51338160e-01
6.97216168e-02 -1.18155099e-01 4.55600947e-01 7.54026830e-01
-4.95062351e-01 2.41410419e-01 -4.14111882e-01 2.00864181e-01
1.17525995e+00 3.91620249e-01 9.23344970e-01 -1.34123015e+00
-3.47081602e-01 -4.00660932e-01 -3.59411955e-01 -1.58062851e+00
-1.33990824e-01 -8.40511203e-01 -6.26712516e-02 -1.59337950e+00
5.63062876e-02 -4.61698622e-01 3.92516851e-01 -1.44277811e-01
-6.98857978e-02 6.44465744e-01 1.65055066e-01 8.84432048e-02
-3.33690681e-02 3.59678686e-01 1.67761123e+00 1.49190351e-01
-2.23184466e-01 -6.88679591e-02 -1.19389839e-01 8.49304497e-01
5.04741013e-01 -3.27003263e-02 -3.62162441e-01 -7.57717192e-01
6.36910796e-01 5.57959139e-01 6.82721794e-01 -9.74519730e-01
8.70762393e-02 -2.33716890e-03 3.90908241e-01 -9.47535932e-01
7.26512015e-01 -8.94684315e-01 6.84626758e-01 1.88497216e-01
-1.48260072e-01 1.64637882e-02 8.18811357e-03 3.87941420e-01
-2.27116540e-01 1.37397453e-01 1.09037006e+00 -9.34041888e-02
-4.12667304e-01 4.46170330e-01 1.50787428e-01 2.23233119e-01
7.79143035e-01 -5.48077703e-01 1.35844937e-02 -3.22458237e-01
-9.64510083e-01 3.53460133e-01 1.31534207e+00 2.45150372e-01
6.62555397e-01 -1.48193800e+00 -8.78052831e-01 6.42318308e-01
1.11192033e-01 4.89091933e-01 3.29424858e-01 6.97198033e-01
-9.50964093e-01 2.05404162e-01 -4.25641179e-01 -1.06344938e+00
-1.35336125e+00 3.71758372e-01 4.38203275e-01 -3.21395904e-01
-8.96195471e-01 5.78551471e-01 5.49226344e-01 -3.68952513e-01
2.22321033e-01 -6.05667889e-01 -3.14600556e-03 6.43822774e-02
2.74218917e-01 4.49143052e-01 2.02814862e-01 -7.84154296e-01
9.73714981e-03 1.17076218e+00 3.99654031e-01 -3.76634985e-01
1.21074808e+00 -3.14018458e-01 -1.63047299e-01 4.90619063e-01
1.21602392e+00 3.08237791e-01 -1.54705763e+00 -1.30095586e-01
-3.86867613e-01 -1.00370479e+00 -2.87023205e-02 -3.54649663e-01
-1.05803359e+00 9.40868795e-01 3.53704780e-01 1.62399903e-01
1.08020008e+00 -2.57576704e-01 9.54222202e-01 -1.45264655e-01
8.17080021e-01 -6.92938089e-01 -3.18255633e-01 5.75264275e-01
1.19310498e+00 -1.03016853e+00 -6.02004454e-02 -9.24931467e-01
-3.38938177e-01 1.17556620e+00 2.69866168e-01 -1.90220475e-01
4.55276132e-01 2.08578497e-01 -4.81673367e-02 -6.10824861e-02
-5.66373050e-01 -8.11770856e-02 5.30519605e-01 5.76635897e-01
3.46748024e-01 -6.25750050e-02 -2.12196916e-01 -2.88433284e-01
-4.31815088e-01 5.84860006e-03 5.33815503e-01 5.65969646e-01
-2.26863101e-01 -1.47995722e+00 -5.91566682e-01 9.49363038e-02
-1.41286060e-01 -1.15308270e-01 -1.27729744e-01 4.43526208e-01
2.46738061e-01 5.98645926e-01 1.97970957e-01 -1.15604535e-01
7.25172877e-01 -1.46682203e-01 7.49160469e-01 -5.86114526e-01
-5.33064723e-01 5.03753386e-02 7.97244236e-02 -8.57956111e-01
-4.53415126e-01 -5.20679712e-01 -8.76352847e-01 -5.35555542e-01
2.25469694e-01 -2.96369225e-01 4.89936054e-01 3.98825765e-01
2.24377096e-01 3.27694684e-01 7.88275480e-01 -1.40992475e+00
-1.11700490e-01 -3.51837873e-01 -4.09438461e-01 7.07205057e-01
6.74284399e-01 -5.23847997e-01 -4.52613860e-01 3.77629697e-01] | [9.129422187805176, -3.0092766284942627] |
20d1eab9-f3c4-46e6-8a42-6bbe83883c5e | point-cloud-pre-training-by-mixing-and | 2109.00452 | null | https://arxiv.org/abs/2109.00452v3 | https://arxiv.org/pdf/2109.00452v3.pdf | Self-supervised Point Cloud Representation Learning via Separating Mixed Shapes | The manual annotation for large-scale point clouds costs a lot of time and is usually unavailable in harsh real-world scenarios. Inspired by the great success of the pre-training and fine-tuning paradigm in both vision and language tasks, we argue that pre-training is one potential solution for obtaining a scalable model to 3D point cloud downstream tasks as well. In this paper, we, therefore, explore a new self-supervised learning method, called Mixing and Disentangling (MD), for 3D point cloud representation learning. As the name implies, we mix two input shapes and demand the model learning to separate the inputs from the mixed shape. We leverage this reconstruction task as the pretext optimization objective for self-supervised learning. There are two primary advantages: 1) Compared to prevailing image datasets, eg, ImageNet, point cloud datasets are de facto small. The mixing process can provide a much larger online training sample pool. 2) On the other hand, the disentangling process motivates the model to mine the geometric prior knowledge, eg, key points. To verify the effectiveness of the proposed pretext task, we build one baseline network, which is composed of one encoder and one decoder. During pre-training, we mix two original shapes and obtain the geometry-aware embedding from the encoder, then an instance-adaptive decoder is applied to recover the original shapes from the embedding. Albeit simple, the pre-trained encoder can capture the key points of an unseen point cloud and surpasses the encoder trained from scratch on downstream tasks. The proposed method has improved the empirical performance on both ModelNet-40 and ShapeNet-Part datasets in terms of point cloud classification and segmentation tasks. We further conduct ablation studies to explore the effect of each component and verify the generalization of our proposed strategy by harnessing different backbones. | ['Mingliang Xu', 'Xiaohan Wang', 'Yi Yang', 'Zhedong Zheng', 'Chao Sun'] | 2021-09-01 | null | null | null | null | ['point-cloud-pre-training', '3d-part-segmentation'] | ['computer-vision', 'computer-vision'] | [ 4.96961176e-02 1.93976149e-01 -8.83679166e-02 -3.83156359e-01
-8.74937654e-01 -7.30131507e-01 5.66436172e-01 -1.38051316e-01
-4.14108634e-01 1.54853582e-01 -2.14700535e-01 -3.86465013e-01
1.19038373e-01 -7.84820795e-01 -1.16917622e+00 -6.95298433e-01
2.54878223e-01 6.51062787e-01 1.17265493e-01 1.57110114e-02
3.87299433e-02 6.33467138e-01 -1.38794577e+00 -3.87452580e-02
9.84571993e-01 1.10781670e+00 6.82146966e-01 3.37067127e-01
-3.65638584e-01 2.18988419e-01 -2.88835078e-01 -5.61708152e-01
7.36437321e-01 1.24730691e-01 -6.11351252e-01 2.92961508e-01
4.94260818e-01 -4.45871860e-01 -3.81775558e-01 1.01548743e+00
4.78430748e-01 -1.65781811e-01 6.22909725e-01 -1.15932405e+00
-6.44191027e-01 4.37541008e-01 -6.98899925e-01 -3.16664010e-01
-2.06434548e-01 3.29660594e-01 1.03434050e+00 -1.15173340e+00
5.06965339e-01 1.03760779e+00 6.70671046e-01 5.00588477e-01
-1.14257169e+00 -8.38068664e-01 2.43923590e-01 -2.07241938e-01
-1.47708559e+00 -4.22720820e-01 1.04637909e+00 -4.48668301e-01
7.16125727e-01 -7.60442987e-02 6.24410748e-01 1.03608775e+00
-3.28328252e-01 9.11153913e-01 8.13087881e-01 -1.68427169e-01
1.66380778e-01 2.37986892e-01 -2.39243954e-01 6.82856798e-01
1.72039554e-01 1.99817702e-01 -7.00991079e-02 -8.57893080e-02
1.04499638e+00 2.03739792e-01 -1.65259913e-01 -7.12751329e-01
-1.17004919e+00 7.01536298e-01 7.63695478e-01 1.37013778e-01
-2.70326227e-01 2.43646979e-01 1.83780402e-01 2.10970744e-01
4.56607997e-01 3.61937255e-01 -5.97991228e-01 7.16464520e-02
-1.01625907e+00 1.03563994e-01 6.37104332e-01 1.27636075e+00
1.03129244e+00 -9.42539275e-02 1.45845801e-01 8.44019353e-01
4.78627115e-01 6.49706602e-01 1.27702460e-01 -6.16302311e-01
8.27204764e-01 7.14975476e-01 -5.32588810e-02 -7.43424654e-01
-1.35001704e-01 -6.11432135e-01 -8.66615713e-01 2.50427544e-01
3.50509554e-01 -2.11443361e-02 -1.07594526e+00 1.70113492e+00
3.10988963e-01 4.59647596e-01 -1.09918946e-02 9.95803356e-01
7.19516933e-01 5.13639867e-01 -7.64774308e-02 2.84413666e-01
1.19399834e+00 -9.97116029e-01 -6.42400384e-02 -4.21508223e-01
5.22431135e-01 -6.51158214e-01 1.10719967e+00 3.70234139e-02
-9.15544689e-01 -6.83183908e-01 -1.08537567e+00 -1.91592574e-01
-1.28852129e-01 3.60136479e-01 6.58651948e-01 2.19080120e-01
-7.51929879e-01 6.54989004e-01 -1.06788886e+00 -1.35317624e-01
8.73409092e-01 3.89044017e-01 -3.27959150e-01 -2.20540673e-01
-6.53115869e-01 5.97449899e-01 1.89756945e-01 1.02729961e-01
-9.49911714e-01 -7.80136645e-01 -8.22681546e-01 6.35766909e-02
4.18334484e-01 -9.60051000e-01 9.59460795e-01 -8.98085594e-01
-1.37167609e+00 9.67756033e-01 -1.11189656e-01 -2.79282063e-01
6.52117431e-01 -1.88300654e-01 1.15100034e-01 7.73686692e-02
1.96137592e-01 9.55690920e-01 1.12687254e+00 -1.55127919e+00
-5.55591404e-01 -5.19676030e-01 1.87003940e-01 2.25948066e-01
-1.10359609e-01 -5.68799734e-01 -8.76293480e-01 -6.31558657e-01
3.00114423e-01 -1.05700815e+00 -2.61591762e-01 1.87891871e-01
-4.65302974e-01 -8.50735605e-02 8.35743666e-01 -2.96157360e-01
5.91242254e-01 -2.45443821e+00 1.29689530e-01 2.88755089e-01
2.97065705e-01 1.62100390e-01 -4.25992519e-01 1.82577252e-01
-9.85423923e-02 1.62896797e-01 -4.98984307e-01 -8.29719245e-01
-1.75799057e-02 4.33917075e-01 -5.54242253e-01 4.33572263e-01
5.29274106e-01 1.24317670e+00 -8.13714683e-01 -4.17024851e-01
4.17335123e-01 4.38831598e-01 -6.62355602e-01 2.78726429e-01
-4.08086658e-01 6.19483232e-01 -5.89750469e-01 6.52734041e-01
1.02078640e+00 -4.68120515e-01 -2.72003651e-01 -3.36692750e-01
-3.03976797e-02 2.21696660e-01 -1.13547170e+00 2.13993740e+00
-5.83475947e-01 3.37197542e-01 -1.56204100e-03 -1.03051186e+00
8.97027671e-01 1.53126135e-01 6.06766045e-01 -4.66022700e-01
6.96578398e-02 3.22156996e-01 -9.16299000e-02 -4.85469729e-01
2.19436720e-01 -2.11964741e-01 1.17518604e-01 2.87864715e-01
2.01660454e-01 -4.64638680e-01 -3.02063435e-01 1.31630078e-01
9.81202662e-01 3.76204699e-01 -6.54022694e-02 6.81098253e-02
3.92022222e-01 -2.29863431e-02 5.20422697e-01 5.46631634e-01
-4.01193881e-03 8.95282388e-01 3.38629276e-01 -2.76988626e-01
-1.08737969e+00 -1.07608080e+00 -1.50087938e-01 6.84193254e-01
4.05208021e-01 -3.83737922e-01 -4.77725178e-01 -8.94951820e-01
2.34598666e-01 5.55396736e-01 -2.83127755e-01 -1.41755283e-01
-6.20797515e-01 -4.24756199e-01 4.80998278e-01 6.52072191e-01
4.80102867e-01 -7.50640631e-01 -4.08761472e-01 -8.40082299e-03
-1.93208363e-02 -1.49940884e+00 -4.49937671e-01 1.68312833e-01
-1.12690246e+00 -9.84833479e-01 -5.73443592e-01 -7.70032704e-01
9.17528987e-01 5.25563359e-01 1.12580764e+00 1.90066665e-01
1.11423321e-01 2.94259191e-01 -3.62370998e-01 -3.93660754e-01
-1.21300638e-01 3.53833199e-01 -2.24617183e-01 3.33865695e-02
2.52677530e-01 -9.30805087e-01 -6.64663792e-01 2.47297958e-01
-8.78434181e-01 2.99432993e-01 1.06012368e+00 7.81286478e-01
8.97240222e-01 -9.33281034e-02 4.28602219e-01 -8.51403177e-01
9.34080184e-02 -3.30727637e-01 -7.99035668e-01 2.56417636e-02
-3.78875196e-01 2.32504889e-01 6.30195439e-01 -3.29901069e-01
-7.26954043e-01 4.69570637e-01 -3.84910226e-01 -9.75430608e-01
-2.18324989e-01 3.53158921e-01 -5.30064642e-01 -2.69669443e-01
3.43920648e-01 2.80227512e-01 5.16523123e-02 -7.28265643e-01
6.70280278e-01 6.23833358e-01 4.62925285e-01 -6.67334318e-01
1.35863936e+00 7.36423314e-01 -1.11888632e-01 -7.12435722e-01
-7.29935288e-01 -4.55798060e-01 -7.96624660e-01 1.55800149e-01
8.88352215e-01 -1.15495038e+00 -5.33945084e-01 3.16627085e-01
-1.37902308e+00 -2.30780885e-01 -4.15340751e-01 3.32562447e-01
-5.50074577e-01 3.98988932e-01 -2.58863449e-01 -5.81408799e-01
-3.34591597e-01 -1.32204926e+00 1.41352832e+00 -6.58706278e-02
3.03578973e-01 -7.91696191e-01 -2.36440688e-01 4.22403306e-01
7.16739073e-02 1.44386023e-01 9.92816389e-01 -6.69574440e-01
-1.03753972e+00 -1.35736734e-01 -5.24657905e-01 5.49823880e-01
1.18378997e-01 -2.13411912e-01 -1.15279388e+00 -3.14198166e-01
2.41738856e-01 -3.01100314e-01 9.08639550e-01 9.45386961e-02
1.42513251e+00 -7.45598525e-02 -4.03451324e-01 1.05531466e+00
1.55139124e+00 -1.98978826e-01 4.79777187e-01 1.43924221e-01
1.14174962e+00 3.83610964e-01 3.57304603e-01 1.76182583e-01
6.37463331e-01 5.47098160e-01 7.04980850e-01 -2.59331822e-01
-1.87620118e-01 -6.03170633e-01 1.36002660e-01 9.90502298e-01
-1.61121413e-01 4.69476730e-02 -9.31874692e-01 4.85764861e-01
-1.68914270e+00 -5.70795655e-01 1.72611326e-01 2.24655199e+00
7.38892794e-01 2.22536951e-01 -2.10472867e-01 -1.07388042e-01
3.72776359e-01 2.51031131e-01 -7.62743175e-01 3.26198041e-01
-8.03340413e-03 2.28844732e-01 7.24983096e-01 4.24301893e-01
-1.07359111e+00 1.19291520e+00 4.83180141e+00 9.04819429e-01
-1.42466152e+00 1.12174518e-01 4.05275136e-01 -6.54065190e-03
-4.23663169e-01 2.65680701e-01 -6.39897585e-01 4.48393077e-01
4.11014557e-01 1.97622716e-01 3.52120519e-01 9.46482122e-01
8.03938210e-02 3.94658297e-01 -1.39640224e+00 1.24261773e+00
-1.22109182e-01 -1.34490943e+00 1.14000671e-01 1.78631261e-01
5.56662619e-01 5.39547682e-01 -2.59828568e-03 3.39748055e-01
6.00056164e-02 -8.67481112e-01 9.16820645e-01 3.11119109e-01
1.01058984e+00 -5.34905374e-01 5.56862533e-01 6.51694477e-01
-1.14497125e+00 5.70999868e-02 -5.29053807e-01 1.82092488e-01
1.85476080e-01 7.12439835e-01 -7.51578867e-01 8.33029449e-01
4.61010545e-01 8.81584406e-01 -5.19358099e-01 1.04468739e+00
-3.71913165e-01 5.66415846e-01 -5.53716481e-01 4.44072336e-01
2.72434115e-01 -4.17519599e-01 6.69376791e-01 9.20516133e-01
2.25928381e-01 -2.35257205e-02 1.39026925e-01 1.25980425e+00
-2.57258087e-01 -1.88926637e-01 -6.10976338e-01 -1.10467337e-01
5.60993671e-01 1.26066601e+00 -6.32973731e-01 -1.83505163e-01
-6.22014463e-01 9.06946957e-01 4.96903121e-01 4.80089933e-01
-8.40509951e-01 -1.19788505e-01 6.44517958e-01 1.59050494e-01
6.15170777e-01 -5.19594550e-01 -6.95233464e-01 -1.40349376e+00
2.11052984e-01 -7.53908038e-01 -5.62832020e-02 -4.93092448e-01
-1.38928449e+00 6.11526787e-01 -5.00239357e-02 -1.43977845e+00
5.37805185e-02 -5.43168664e-01 -6.46110415e-01 9.21187520e-01
-1.81742609e+00 -1.47000873e+00 -4.26971912e-01 4.12605375e-01
5.85720420e-01 -1.08356522e-02 4.84162182e-01 4.38068718e-01
-5.04686177e-01 6.39587522e-01 -1.93944097e-01 3.39969277e-01
4.59752798e-01 -1.23292971e+00 6.36484265e-01 7.44818687e-01
4.50603038e-01 5.81246138e-01 1.60786912e-01 -6.02178752e-01
-1.59921682e+00 -1.32597935e+00 4.89410490e-01 -6.29922748e-01
4.46619540e-01 -8.13381910e-01 -1.04755020e+00 5.56302130e-01
-2.41391405e-01 2.14935869e-01 3.49063307e-01 -1.41178980e-01
-3.96847486e-01 -9.54039618e-02 -8.67609560e-01 5.23108125e-01
1.30293632e+00 -6.17041409e-01 -5.95821023e-01 2.27677181e-01
1.04482567e+00 -5.25162697e-01 -6.97197199e-01 5.59355378e-01
2.67546237e-01 -7.11426497e-01 1.19193184e+00 -3.55021268e-01
5.90519428e-01 -3.63262653e-01 -3.03162813e-01 -1.15894580e+00
-1.04190916e-01 -4.34622556e-01 -1.92759201e-01 1.30339432e+00
4.61612880e-01 -5.72191298e-01 1.08552718e+00 6.03940010e-01
-3.11215729e-01 -1.04836416e+00 -8.84671390e-01 -8.22954416e-01
3.06706190e-01 -6.98562443e-01 9.51329887e-01 8.15036774e-01
-6.96925402e-01 5.27994573e-01 -7.26863816e-02 3.89241278e-01
6.66219711e-01 3.59829605e-01 1.04252291e+00 -1.12041700e+00
-3.65132332e-01 -3.87259692e-01 -2.82067597e-01 -1.66878450e+00
2.80965000e-01 -1.15505683e+00 -3.57980095e-02 -1.41471505e+00
-8.65033790e-02 -1.10496342e+00 -9.79380310e-02 5.21136701e-01
-1.38179213e-01 4.11362201e-03 4.26831067e-01 5.64281344e-01
-2.97805220e-01 8.36339355e-01 1.41386199e+00 -2.48526841e-01
-2.36617148e-01 1.86782792e-01 -7.20334470e-01 7.25689292e-01
4.87465978e-01 -4.95963216e-01 -5.08272469e-01 -9.10404682e-01
2.28635177e-01 -1.32591784e-01 6.76872611e-01 -7.88657904e-01
2.60067374e-01 -9.17492248e-03 1.76466167e-01 -7.18351722e-01
4.32284653e-01 -1.23470283e+00 -9.76918116e-02 1.34825096e-01
7.60543644e-02 -2.44741917e-01 1.43884987e-01 6.48158967e-01
-1.42115235e-01 -2.28048056e-01 6.70287907e-01 -1.31174237e-01
-5.53174317e-01 7.53310204e-01 4.83111650e-01 -5.27960211e-02
7.90515959e-01 -4.38574582e-01 -4.94326726e-02 -7.36740306e-02
-4.73871022e-01 3.13984901e-01 7.48285949e-01 4.67037350e-01
7.40970433e-01 -1.27894878e+00 -5.42380631e-01 4.63010222e-01
1.51376307e-01 8.63326550e-01 8.38990360e-02 8.44116628e-01
-4.29471463e-01 1.29765600e-01 5.26009910e-02 -9.05412197e-01
-7.87879288e-01 6.12360299e-01 3.48631829e-01 7.17862742e-03
-8.74731541e-01 7.99323797e-01 5.42229354e-01 -6.52578950e-01
1.98525265e-01 -4.90444124e-01 1.63358033e-01 -2.16360062e-01
2.80737560e-02 -4.64753620e-02 1.40491739e-01 -5.97966731e-01
-3.33969593e-01 8.52923036e-01 -2.51885876e-02 -3.55378017e-02
1.52198780e+00 -1.81741025e-02 -2.13688966e-02 2.68583238e-01
1.45085418e+00 6.65299362e-03 -1.57189822e+00 -4.07682776e-01
-1.07442722e-01 -6.33087099e-01 1.40742343e-02 -4.43218231e-01
-1.31203806e+00 1.07416630e+00 4.31603432e-01 -8.92245919e-02
9.37773705e-01 3.00002903e-01 8.47559750e-01 3.64641160e-01
4.55539048e-01 -7.43075848e-01 2.83043869e-02 4.79158461e-01
9.11023140e-01 -1.45366538e+00 -2.16241539e-01 -6.76863551e-01
-5.65893412e-01 8.97673190e-01 6.64047658e-01 -3.31832319e-01
7.41002738e-01 2.39062950e-01 7.35262036e-03 -3.76567096e-01
-6.67320490e-01 -2.64519691e-01 3.61297697e-01 4.94941741e-01
2.38060206e-02 -2.82831099e-02 3.05047214e-01 7.37884820e-01
-4.26083177e-01 -5.75071201e-02 7.91152492e-02 6.77523136e-01
-9.08245966e-02 -1.12452781e+00 -1.60496190e-01 4.16273475e-01
-9.92817897e-03 6.27432689e-02 -4.48298097e-01 6.68052137e-01
4.39639658e-01 5.48657417e-01 4.55515198e-02 -5.45530140e-01
4.62982297e-01 -1.56303823e-01 4.65063632e-01 -7.50938654e-01
-3.19073886e-01 4.83135320e-03 -3.39267701e-01 -5.55107951e-01
-2.38587156e-01 -4.83475506e-01 -1.26155531e+00 -1.89256407e-02
-5.73088229e-01 -8.43941122e-02 7.32896328e-01 1.05931604e+00
6.71660781e-01 3.84130120e-01 7.47440934e-01 -1.10075462e+00
-7.74966300e-01 -8.06648135e-01 -1.95786297e-01 5.17649055e-01
3.90283823e-01 -6.83225930e-01 -2.86772907e-01 -4.59231474e-02] | [8.146618843078613, -3.4138267040252686] |
6f36664f-9c76-403a-8fea-f98832cb4cf5 | cascaded-cross-attention-networks-for-data | 2305.06963 | null | https://arxiv.org/abs/2305.06963v1 | https://arxiv.org/pdf/2305.06963v1.pdf | Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers | Whole-Slide Imaging allows for the capturing and digitization of high-resolution images of histological specimen. An automated analysis of such images using deep learning models is therefore of high demand. The transformer architecture has been proposed as a possible candidate for effectively leveraging the high-resolution information. Here, the whole-slide image is partitioned into smaller image patches and feature tokens are extracted from these image patches. However, while the conventional transformer allows for a simultaneous processing of a large set of input tokens, the computational demand scales quadratically with the number of input tokens and thus quadratically with the number of image patches. To address this problem we propose a novel cascaded cross-attention network (CCAN) based on the cross-attention mechanism that scales linearly with the number of extracted patches. Our experiments demonstrate that this architecture is at least on-par with and even outperforms other attention-based state-of-the-art methods on two public datasets: On the use-case of lung cancer (TCGA NSCLC) our model reaches a mean area under the receiver operating characteristic (AUC) of 0.970 $\pm$ 0.008 and on renal cancer (TCGA RCC) reaches a mean AUC of 0.985 $\pm$ 0.004. Furthermore, we show that our proposed model is efficient in low-data regimes, making it a promising approach for analyzing whole-slide images in resource-limited settings. To foster research in this direction, we make our code publicly available on GitHub: XXX. | ['Daniel Truhn', 'Johannes Stegmaier', 'Christiane Kuhl', 'Sven Nebelung', 'Tianyu Han', 'Jakob Nikolas Kather', 'Firas Khader'] | 2023-05-11 | null | null | null | null | ['whole-slide-images'] | ['computer-vision'] | [ 2.15234786e-01 2.17737496e-01 -2.02694699e-01 4.16502077e-03
-1.41435456e+00 -3.92695904e-01 3.66505712e-01 5.14936328e-01
-7.33114779e-01 4.22965586e-01 -2.52508610e-01 -4.70611215e-01
-1.38461098e-01 -8.04274559e-01 -8.14226389e-01 -9.89744306e-01
-6.08331859e-02 3.67356300e-01 1.43535882e-01 2.14137673e-01
2.83928923e-02 7.02442229e-01 -1.08786321e+00 3.46667856e-01
6.25374138e-01 1.15364242e+00 2.59384453e-01 7.29055524e-01
1.94789581e-02 3.39996725e-01 -1.47851393e-01 -4.11051184e-01
1.19161271e-01 -2.87060775e-02 -7.94523060e-01 3.64037380e-02
3.74666721e-01 -2.37407774e-01 -2.98322171e-01 9.84620690e-01
4.77493584e-01 -3.78413826e-01 5.41233957e-01 -7.73610830e-01
-4.94545788e-01 4.01323706e-01 -7.59836376e-01 3.82475972e-01
-2.39220917e-01 1.38608262e-01 1.17887604e+00 -7.94363439e-01
6.23704255e-01 5.79339027e-01 6.20513856e-01 3.62451792e-01
-1.39431500e+00 -5.75805545e-01 -1.45796582e-01 1.05883777e-01
-1.38721561e+00 -1.79659173e-01 4.64182019e-01 -2.03890383e-01
9.65138018e-01 2.70385891e-01 6.78668082e-01 7.39639819e-01
5.17856419e-01 8.07770729e-01 1.07829738e+00 -4.05378520e-01
2.93651968e-03 1.87751099e-01 -3.61197162e-03 7.93185234e-01
1.71777964e-01 -2.04224676e-01 -1.56749174e-01 -5.54354824e-02
8.70178998e-01 4.62318450e-01 -2.15079546e-01 -4.58622277e-02
-1.22802973e+00 7.41400242e-01 7.56364703e-01 7.30092049e-01
-2.21742541e-01 3.27859432e-01 3.10892522e-01 1.30275860e-01
4.51057792e-01 2.63073742e-01 -1.71360254e-01 1.31422505e-01
-1.00772619e+00 -1.78289562e-01 2.57562071e-01 4.67591792e-01
5.62598050e-01 -4.67290074e-01 -1.72894806e-01 6.88425839e-01
6.76521054e-03 3.30652356e-01 5.59576392e-01 -4.45601881e-01
1.66501403e-01 9.23136532e-01 -6.15292378e-02 -6.38865769e-01
-6.23081267e-01 -6.00518286e-01 -1.15270555e+00 5.76552972e-02
6.77676141e-01 1.97798580e-01 -7.59633958e-01 1.56157267e+00
2.73925722e-01 2.50325855e-02 -1.14247091e-01 6.66868627e-01
5.86462080e-01 3.28610867e-01 5.06811254e-02 -1.36860415e-01
1.90175533e+00 -7.64919102e-01 -5.01991570e-01 5.17676622e-02
7.52162635e-01 -5.67780435e-01 1.14936101e+00 1.48492262e-01
-1.06080055e+00 -1.87939882e-01 -8.62736166e-01 -3.38109493e-01
-4.30502504e-01 3.53958756e-01 4.16533351e-01 4.71752495e-01
-1.18137252e+00 3.59234571e-01 -1.09199762e+00 -3.71073157e-01
8.74650955e-01 6.13135993e-01 -6.55454457e-01 -2.39366755e-01
-6.69842124e-01 5.56630492e-01 -6.66297674e-02 2.12759703e-01
-7.13277757e-01 -9.58945394e-01 -5.57380915e-01 5.26048243e-01
8.70785043e-02 -6.29069686e-01 8.81354928e-01 -7.82942414e-01
-1.21357453e+00 1.15868771e+00 -1.62776224e-02 -4.48402077e-01
5.80162823e-01 1.64629430e-01 6.88874274e-02 3.18767130e-01
-4.15271781e-02 7.37323344e-01 5.02038181e-01 -7.41448224e-01
-6.29677653e-01 -5.99362850e-01 -9.04528052e-03 -5.75031936e-02
-6.24377608e-01 -2.04776868e-01 -5.67512929e-01 -2.81498522e-01
-1.81916162e-01 -9.66359198e-01 -3.52381319e-01 1.61323830e-01
-3.49697948e-01 -2.27840524e-02 4.89100903e-01 -4.43971395e-01
9.37605977e-01 -2.25695062e+00 -5.49017191e-02 1.34492323e-01
4.08885211e-01 1.43380463e-01 -9.99143049e-02 3.21452647e-01
2.97474470e-02 3.66686225e-01 -1.56737253e-01 -2.83582091e-01
-1.68185249e-01 -3.26525271e-01 1.10913217e-01 7.92630434e-01
2.92647034e-01 1.19020522e+00 -6.94728673e-01 -6.46169007e-01
5.56224696e-02 6.76072776e-01 -4.90581393e-01 1.41364988e-02
1.21225789e-01 2.43920788e-01 -4.23320949e-01 5.99126160e-01
6.40339494e-01 -8.57139051e-01 4.79157627e-01 -2.45542601e-01
-1.51308000e-01 -1.25257656e-01 -6.07450724e-01 1.59163904e+00
-5.54351330e-01 7.36823916e-01 1.52058423e-01 -9.16033864e-01
6.02226257e-01 3.36031228e-01 7.46226132e-01 -6.15943074e-01
3.18308413e-01 1.53906420e-01 2.01769218e-01 -3.29860538e-01
7.80430138e-02 -4.23543006e-01 -7.37283081e-02 4.57418352e-01
9.91587341e-03 2.08559781e-01 1.02171205e-01 1.73108682e-01
1.49419343e+00 -5.28831959e-01 4.01090235e-01 -3.24290037e-01
4.32972997e-01 -3.37331481e-02 1.74344674e-01 5.00269234e-01
-1.26380846e-01 4.62553948e-01 8.15857947e-01 -4.88913089e-01
-1.09196031e+00 -7.94592083e-01 -5.39749861e-01 6.28223896e-01
-1.27936453e-01 -1.47415340e-01 -7.59226143e-01 -6.85721219e-01
4.67003211e-02 5.46184927e-02 -1.05987334e+00 2.62057275e-01
-3.08861703e-01 -9.75930572e-01 6.19843781e-01 6.00091696e-01
3.43543202e-01 -9.48887885e-01 -8.37226033e-01 1.42842516e-01
-1.62996709e-01 -1.07099855e+00 -3.27917546e-01 2.52664298e-01
-7.29540467e-01 -1.18392444e+00 -9.12932754e-01 -6.92112744e-01
8.84711087e-01 2.54289538e-01 8.97458196e-01 3.00752342e-01
-6.19202077e-01 2.09495813e-01 -2.22943053e-01 -3.68443638e-01
-3.40748951e-02 3.37849438e-01 -4.45564687e-01 1.80575132e-01
3.31824392e-01 -4.36139166e-01 -7.67945349e-01 9.03657824e-03
-1.15117073e+00 1.07098863e-01 1.04684556e+00 1.23581612e+00
9.40024495e-01 -1.47985548e-01 5.09601712e-01 -1.09087157e+00
1.54514447e-01 -4.93859589e-01 -7.18355834e-01 2.94793814e-01
-3.14530194e-01 -8.04811493e-02 7.76943922e-01 -2.69306451e-01
-6.65487409e-01 9.35907513e-02 -2.22368464e-01 -4.25475985e-01
4.90916185e-02 6.25916958e-01 6.97663799e-02 -1.35945603e-01
3.12968791e-01 2.58637249e-01 2.16157496e-01 -2.42746770e-01
-7.45933056e-02 5.00726163e-01 3.97260368e-01 -3.60965133e-02
5.88739038e-01 9.01171148e-01 2.48190731e-01 -7.55531311e-01
-5.10851026e-01 -4.81649965e-01 -5.08668542e-01 -2.17785835e-02
8.00536692e-01 -7.66299009e-01 -1.08334196e+00 3.57960582e-01
-6.44902825e-01 -5.62218130e-01 -6.13021851e-02 3.11693698e-01
-4.18109864e-01 2.44775876e-01 -9.23017204e-01 -4.36003357e-01
-6.12504780e-01 -1.17163622e+00 1.25127923e+00 1.74897268e-01
-1.15704508e-02 -1.00295937e+00 -1.69315785e-02 4.40334201e-01
4.37099099e-01 3.83416504e-01 1.11680114e+00 -7.24054873e-01
-8.15527737e-01 -6.36612356e-01 -5.46907902e-01 -1.50676340e-01
1.62759095e-01 1.14124606e-03 -1.02349162e+00 -4.47118431e-01
-2.09219530e-01 -2.44432360e-01 8.94182503e-01 6.35637581e-01
1.52351189e+00 -1.02043092e-01 -6.03718877e-01 6.14339530e-01
1.72002327e+00 -1.27358958e-01 7.05022216e-01 3.18658412e-01
4.79548007e-01 3.97718847e-01 4.37578201e-01 2.47707874e-01
2.13046476e-01 6.91931605e-01 5.24375916e-01 -5.88366449e-01
-2.12435778e-02 5.03465272e-02 -1.35205001e-01 3.34144801e-01
1.93168879e-01 -3.40570092e-01 -1.00210547e+00 7.92069793e-01
-1.47157431e+00 -7.54177749e-01 -1.81073230e-02 2.19276738e+00
6.62168264e-01 3.94153148e-02 -1.05494866e-02 1.80897072e-01
4.50455546e-01 -1.10349871e-01 -5.49160600e-01 -2.15669736e-01
6.85407668e-02 3.16283345e-01 5.01652718e-01 3.32928956e-01
-9.48906004e-01 5.42366087e-01 5.47283220e+00 9.78388071e-01
-1.38710332e+00 1.93752512e-01 1.16077018e+00 -3.52882087e-01
-7.46425837e-02 -3.03874105e-01 -6.22939229e-01 5.64919055e-01
1.03507555e+00 -2.05592483e-01 6.14416488e-02 5.85373580e-01
1.43577009e-01 -1.58607826e-01 -1.13861966e+00 8.19958687e-01
-1.18161231e-01 -1.58028853e+00 -1.57141015e-01 6.59197927e-01
5.72796464e-01 2.24680781e-01 3.79342765e-01 6.55873260e-03
-1.92235839e-02 -1.18309593e+00 7.15191439e-02 2.02085689e-01
1.26868522e+00 -7.31241703e-01 1.11449695e+00 1.68933660e-01
-1.01243591e+00 -1.21673375e-01 -2.43140653e-01 3.92273277e-01
-1.45689666e-01 7.65662074e-01 -1.07270133e+00 4.62747365e-01
7.35300362e-01 4.95705992e-01 -5.80352366e-01 8.68577003e-01
3.66440564e-01 3.84645373e-01 -3.57866496e-01 3.34895924e-02
3.81528109e-01 1.82681590e-01 7.88049623e-02 1.29342186e+00
4.73454416e-01 1.60920188e-01 -2.73246437e-01 6.31671190e-01
-3.31407249e-01 3.26995909e-01 -3.95876855e-01 7.47410057e-04
2.10472792e-01 1.70586586e+00 -1.06999099e+00 -3.33865881e-01
-5.59193671e-01 5.42682350e-01 5.17026722e-01 6.15641773e-02
-7.89399445e-01 -3.52358073e-01 1.83761418e-01 4.18993801e-01
5.86968839e-01 2.23931491e-01 -3.33374560e-01 -9.77663696e-01
-2.22960897e-02 -7.13289142e-01 5.26581228e-01 -3.80215675e-01
-1.22810352e+00 6.78010404e-01 -3.98704946e-01 -1.29214001e+00
1.13744788e-01 -7.39673376e-01 -5.26533425e-01 6.16387665e-01
-1.73748410e+00 -1.34365928e+00 -3.90271485e-01 4.07120705e-01
2.98936635e-01 1.96569651e-01 8.66257548e-01 2.87100613e-01
-6.63321912e-01 7.73453593e-01 4.78413284e-01 2.47706324e-01
6.22946739e-01 -1.14183915e+00 3.24539095e-02 5.05561650e-01
6.00224521e-05 4.39228743e-01 3.26922119e-01 -8.15195218e-02
-1.46954107e+00 -1.01581359e+00 8.29316974e-01 -3.07730615e-01
6.76035523e-01 -3.39862853e-01 -8.85018408e-01 7.76175022e-01
2.09831804e-01 3.13596904e-01 1.11697793e+00 -3.77271213e-02
-1.71476722e-01 -3.35278958e-01 -1.21628129e+00 4.31277066e-01
4.42614734e-01 -3.79773051e-01 1.89135954e-01 3.72556984e-01
1.73873380e-01 -4.01755989e-01 -1.25821078e+00 2.04749033e-01
7.02969491e-01 -9.93151903e-01 7.39043772e-01 -1.18124925e-01
5.03415346e-01 -1.12563707e-01 4.99244034e-02 -9.91505980e-01
-4.78730232e-01 -2.06231236e-01 3.16380680e-01 9.12622213e-01
5.10823846e-01 -7.60049224e-01 9.29651499e-01 5.17195225e-01
-1.84869170e-02 -1.26057339e+00 -1.19307911e+00 -4.45653409e-01
3.17454875e-01 -9.87408012e-02 3.68918985e-01 6.96590304e-01
3.63049716e-01 5.00680394e-02 8.78574699e-02 -6.08147457e-02
4.76425231e-01 2.90050477e-01 6.04650557e-01 -9.58537221e-01
-2.33821094e-01 -6.26572967e-01 -5.19445181e-01 -6.68899953e-01
4.90753073e-03 -9.41108942e-01 -3.19310248e-01 -1.34122968e+00
7.95193315e-01 -5.08800626e-01 -5.74946821e-01 5.32725036e-01
-2.11486772e-01 4.66975510e-01 6.97400048e-02 3.02315533e-01
-5.50532162e-01 1.70968279e-01 1.19924307e+00 -2.92294800e-01
7.28495568e-02 -1.08350530e-01 -8.14100146e-01 2.95640349e-01
6.80806577e-01 -5.37600040e-01 2.94072926e-02 -2.70832688e-01
9.21273232e-02 1.96649641e-01 3.58152151e-01 -9.38614905e-01
2.96989381e-01 4.80994619e-02 4.93598759e-01 -5.23510516e-01
3.53798658e-01 -8.81642044e-01 2.09224641e-01 7.41053402e-01
-3.73787135e-01 -4.76973616e-02 3.76574785e-01 5.83076298e-01
-2.56010115e-01 6.70577809e-02 9.11946476e-01 -1.78119227e-01
3.25330831e-02 4.25687820e-01 -4.46757227e-01 -4.36450869e-01
1.13984132e+00 -2.27898583e-01 -4.79960352e-01 -9.54380929e-02
-4.72900987e-01 1.07978284e-01 5.93601763e-01 1.60811748e-02
3.50972295e-01 -1.13545251e+00 -7.77292550e-01 1.90447137e-01
1.42715767e-01 1.22023754e-01 7.69138277e-01 1.24963772e+00
-4.62364852e-01 7.17765987e-01 -2.13242680e-01 -7.02505350e-01
-1.40068340e+00 5.82340240e-01 3.81650567e-01 -1.02510011e+00
-6.21896744e-01 7.34359503e-01 6.26841843e-01 -4.37459461e-02
-1.56332374e-01 -4.80746746e-01 -1.41126946e-01 -1.16425656e-01
6.15810394e-01 1.15099840e-01 1.80230051e-01 -5.04447699e-01
-4.26515192e-01 5.45628011e-01 -4.22369957e-01 1.19042508e-01
1.48427701e+00 1.79720595e-01 -2.01089308e-01 1.99077994e-01
1.50677252e+00 -2.40444914e-02 -1.24091637e+00 -1.83735400e-01
-1.91061288e-01 -3.93078655e-01 1.42316565e-01 -6.65129423e-01
-1.27402091e+00 9.29165184e-01 6.70487106e-01 1.63147092e-01
1.33660007e+00 1.04743838e-01 7.00262308e-01 1.20225707e-02
5.29943220e-02 -6.09635830e-01 1.33391827e-01 1.14525244e-01
6.06139064e-01 -1.24394453e+00 3.37394215e-02 -2.75525063e-01
-3.51421982e-01 9.94384766e-01 3.38797778e-01 -1.02628537e-01
5.40031314e-01 5.05485177e-01 -2.60570664e-02 -3.91143203e-01
-1.08548939e+00 -2.88614514e-03 1.36114910e-01 3.23912919e-01
5.90846300e-01 1.61113396e-01 -1.82045281e-01 6.22532368e-01
1.12271376e-01 1.08072385e-01 5.26076019e-01 7.12851763e-01
-1.39762163e-01 -1.05497777e+00 -1.63140595e-01 7.02075064e-01
-9.59607482e-01 -9.88476053e-02 -1.80261537e-01 9.12782729e-01
-2.37117410e-01 6.19284570e-01 2.70979106e-01 4.56419699e-02
1.16916254e-01 -1.03800952e-01 4.14543957e-01 -3.98103565e-01
-7.76713729e-01 2.75155097e-01 -3.33797544e-01 -2.83463478e-01
-2.72344649e-01 -6.00451469e-01 -1.12340093e+00 -3.02741706e-01
-4.17228073e-01 -5.68093732e-02 5.69949865e-01 7.74027467e-01
5.06458759e-01 5.32554030e-01 4.85941648e-01 -7.33502865e-01
-2.86815822e-01 -9.27195668e-01 -6.86105907e-01 2.64215440e-01
4.26650703e-01 -4.15050924e-01 -2.18190432e-01 5.09174615e-02] | [15.052903175354004, -2.9066896438598633] |
b2c58b33-e6dd-4943-af43-58b3def94918 | ssn-stockwell-scattering-network-for-sar | 2304.11404 | null | https://arxiv.org/abs/2304.11404v1 | https://arxiv.org/pdf/2304.11404v1.pdf | SSN: Stockwell Scattering Network for SAR Image Change Detection | Recently, synthetic aperture radar (SAR) image change detection has become an interesting yet challenging direction due to the presence of speckle noise. Although both traditional and modern learning-driven methods attempted to overcome this challenge, deep convolutional neural networks (DCNNs)-based methods are still hindered by the lack of interpretability and the requirement of large computation power. To overcome this drawback, wavelet scattering network (WSN) and Fourier scattering network (FSN) are proposed. Combining respective merits of WSN and FSN, we propose Stockwell scattering network (SSN) based on Stockwell transform which is widely applied against noisy signals and shows advantageous characteristics in speckle reduction. The proposed SSN provides noise-resilient feature representation and obtains state-of-art performance in SAR image change detection as well as high computational efficiency. Experimental results on three real SAR image datasets demonstrate the effectiveness of the proposed method. | ['Kim-Hui Yap', 'Yi Wang', 'Yanan Zhao', 'Gong Chen'] | 2023-04-22 | null | null | null | null | ['change-detection'] | ['computer-vision'] | [ 6.79737210e-01 -7.88672209e-01 5.64576387e-01 -4.81812537e-01
-4.90455359e-01 -2.09998235e-01 6.55244589e-01 -6.01706266e-01
-4.84728843e-01 8.58181596e-01 1.15747929e-01 -3.91985737e-02
-7.13173866e-01 -9.28803742e-01 -2.38174856e-01 -1.16694129e+00
-1.22007951e-01 -1.31625667e-01 3.51488322e-01 -6.00503385e-01
-7.49970973e-02 7.27154851e-01 -1.34462464e+00 -7.74527937e-02
9.44876611e-01 1.30803668e+00 1.54357046e-01 2.83556968e-01
2.55356103e-01 6.61386609e-01 -4.05834794e-01 9.79723632e-02
5.74785888e-01 -3.95708114e-01 -2.15810671e-01 -8.72534439e-02
3.02944571e-01 -2.52324581e-01 -5.88516235e-01 1.41028678e+00
8.26923609e-01 2.79702634e-01 2.50323266e-01 -6.00060105e-01
-6.81277037e-01 5.04922509e-01 -7.35113502e-01 8.12901378e-01
-4.22346711e-01 1.56378105e-01 4.32094246e-01 -8.55806053e-01
5.24428070e-01 9.30097222e-01 8.51492405e-01 2.88283616e-01
-9.11695540e-01 -7.55861580e-01 -2.64653087e-01 2.06778228e-01
-1.02718568e+00 -3.89980227e-01 1.23510849e+00 -1.12847760e-01
4.55988407e-01 2.72634625e-01 5.55038512e-01 8.82804036e-01
1.92746773e-01 5.37337363e-01 1.57438099e+00 -1.92983031e-01
1.52693748e-01 -5.53655505e-01 1.33560419e-01 4.75197554e-01
6.52515471e-01 3.48774761e-01 -2.43164197e-01 2.48128429e-01
8.43973815e-01 1.85456812e-01 -5.11679292e-01 -5.04540913e-02
-1.33862352e+00 7.48111665e-01 9.45416272e-01 6.48997366e-01
-5.36537528e-01 2.75435418e-01 1.32281259e-01 3.90640259e-01
5.05713463e-01 3.14675331e-01 -2.50051916e-01 1.73027173e-01
-9.62310731e-01 1.85644448e-01 1.44737080e-01 1.72353327e-01
3.65183949e-01 8.84255230e-01 4.69274111e-02 5.17613351e-01
1.23895094e-01 1.02670360e+00 1.94132313e-01 -5.62234819e-01
1.45032331e-01 4.02248710e-01 1.64930031e-01 -1.34794497e+00
-6.43622398e-01 -1.22937250e+00 -1.70378149e+00 3.86205137e-01
4.09805998e-02 -2.73987830e-01 -1.08095765e+00 1.46393371e+00
1.03352904e-01 2.39387661e-01 4.58410174e-01 1.15995300e+00
9.28566515e-01 5.22636831e-01 -8.54986235e-02 -2.59844899e-01
1.13325131e+00 -4.58474725e-01 -7.80990362e-01 -3.06056857e-01
1.99306279e-01 -6.43144369e-01 4.89156008e-01 1.88506827e-01
-6.08942330e-01 -6.37585044e-01 -1.15308356e+00 5.02904177e-01
1.25099556e-04 1.47371009e-01 7.42220998e-01 7.36493409e-01
-7.09932029e-01 4.43277985e-01 -1.02930522e+00 -1.46030813e-01
9.42867815e-01 2.91279107e-01 -8.33026171e-02 -2.38993049e-01
-1.20421612e+00 6.86629713e-01 9.92854461e-02 9.08833921e-01
-5.37105143e-01 -5.69121659e-01 -5.65677285e-01 7.25081861e-02
2.10418239e-01 -5.70069671e-01 6.96531475e-01 -1.16229510e+00
-1.37465584e+00 1.94255874e-01 4.75515187e-01 -6.98836088e-01
3.87363851e-01 -3.28479260e-01 -9.39322591e-01 3.22251141e-01
-2.82337070e-01 2.00117100e-02 1.03604650e+00 -1.19801605e+00
-3.32234710e-01 -3.72851729e-01 -2.13382065e-01 1.61115751e-02
-2.16902226e-01 4.80986647e-02 6.30597413e-01 -8.62223208e-01
5.91666043e-01 -6.35080278e-01 -2.99493819e-01 4.35701795e-02
-2.04552710e-01 1.93188459e-01 1.35067141e+00 -5.79393864e-01
9.59162712e-01 -2.08267379e+00 -2.57521451e-01 2.81275392e-01
2.07838848e-01 9.75869834e-01 -3.11985165e-01 2.37650380e-01
-1.33917406e-01 -2.27979824e-01 -6.14023685e-01 6.21776760e-01
-3.44443142e-01 -7.71316215e-02 -2.97143131e-01 6.93144441e-01
3.89162540e-01 9.26062107e-01 -7.10509658e-01 -2.32425034e-02
3.85775089e-01 6.96331382e-01 -1.21461913e-01 -1.25527337e-01
-1.10141233e-01 7.42471635e-01 -8.03416133e-01 8.34032297e-01
1.17321324e+00 -1.19872414e-01 -1.34185359e-01 -7.54264474e-01
-3.08450162e-01 -4.45974648e-01 -1.29388702e+00 1.04719818e+00
-1.43307030e-01 5.51931918e-01 5.67774028e-02 -1.21817529e+00
1.21162951e+00 -2.85480917e-02 4.03621942e-01 -9.82503235e-01
3.81546944e-01 3.75070065e-01 3.55074763e-01 -6.76892340e-01
8.43197554e-02 -4.72042292e-01 2.11454555e-01 3.17951918e-01
-4.82900500e-01 -4.72958758e-02 -2.19666675e-01 -3.99261773e-01
1.28720522e+00 7.05025271e-02 3.37998211e-01 -3.41363072e-01
6.97138488e-01 1.22627914e-01 7.48775244e-01 5.28307080e-01
-2.59483337e-01 3.46529335e-01 -3.08741152e-01 -9.74518359e-01
-7.21492767e-01 -9.46868539e-01 -1.41447857e-01 3.74207973e-01
2.54259408e-01 5.40689468e-01 -2.29061872e-01 -3.00070882e-01
-3.93545151e-01 4.60551292e-01 -4.23660398e-01 -1.43653899e-02
-1.06537604e+00 -1.29351497e+00 6.08243644e-01 4.61436749e-01
1.43704903e+00 -9.98855412e-01 -8.95666659e-01 1.72146663e-01
-1.85037464e-01 -1.19619262e+00 2.10499078e-01 2.06632889e-03
-8.52476001e-01 -9.92504179e-01 -5.63817441e-01 -8.23985517e-01
5.47684312e-01 7.10222542e-01 6.83751404e-01 -5.53309023e-02
-4.31468785e-01 -2.50228345e-02 -4.12376016e-01 -2.63643801e-01
-2.65369087e-01 -3.67503434e-01 4.71678898e-02 3.42097521e-01
1.48032755e-01 -7.88311541e-01 -1.01716340e+00 2.39231959e-02
-1.26145363e+00 -2.91184068e-01 1.03549528e+00 1.13782704e+00
3.30442548e-01 6.47325277e-01 8.29778194e-01 -7.69960523e-01
2.52235949e-01 -1.26887783e-01 -8.01574528e-01 8.47288743e-02
-4.35117543e-01 -1.56091854e-01 7.81202853e-01 -1.46811277e-01
-1.54948151e+00 -3.62985618e-02 -9.98934149e-04 -1.04598567e-01
-1.89702824e-01 7.87281811e-01 1.17887840e-01 -5.48540533e-01
6.98028684e-01 4.33272630e-01 2.23262701e-02 -3.41675639e-01
-7.42771551e-02 5.32575488e-01 6.28396809e-01 1.35344891e-02
1.61738420e+00 9.07333016e-01 4.69035983e-01 -1.09070718e+00
-1.00740528e+00 -1.06130131e-01 -4.81930554e-01 -2.12436274e-01
7.95140862e-01 -1.02607858e+00 -5.98852813e-01 7.33323336e-01
-7.55124211e-01 1.17798582e-01 -1.67895049e-01 7.37382948e-01
-1.24276668e-01 5.05372763e-01 -2.41459385e-01 -9.02078509e-01
-7.31135368e-01 -6.89193726e-01 5.31046093e-01 3.98673087e-01
3.92522812e-01 -7.22479343e-01 -2.13539436e-01 4.42650914e-01
1.21662104e+00 8.79017115e-01 9.82462227e-01 -3.54065329e-01
-8.65901947e-01 -2.49488413e-01 -6.26779258e-01 5.23213804e-01
3.74282748e-01 -4.07364964e-01 -7.63866961e-01 -5.72690725e-01
4.70222652e-01 -2.00967923e-01 1.05660045e+00 7.53318250e-01
6.69910610e-01 4.37161606e-03 -7.81921856e-03 7.42973149e-01
2.09421706e+00 3.39313835e-01 7.74752915e-01 7.25401402e-01
3.75230253e-01 2.10488662e-01 4.58717614e-01 3.99626672e-01
-2.66983718e-01 2.60703057e-01 5.93165934e-01 -3.73759329e-01
-4.10965264e-01 5.00958443e-01 2.19548792e-01 8.70334208e-01
-5.01193643e-01 -1.72444880e-01 -7.96499312e-01 3.36528003e-01
-1.47326386e+00 -1.24588251e+00 -4.13615853e-01 1.69462383e+00
4.07740951e-01 1.43600315e-01 -5.90187907e-01 3.05843562e-01
5.51316381e-01 6.82457268e-01 -5.37619293e-01 3.87213230e-01
-8.49720240e-01 5.73308408e-01 5.19484341e-01 8.74148235e-02
-1.32875383e+00 7.19635606e-01 5.20546150e+00 7.95063794e-01
-1.30390322e+00 9.53386500e-02 3.03996861e-01 3.12276304e-01
-9.20434520e-02 -3.51399899e-01 -3.17569524e-01 2.23394409e-01
3.96905512e-01 2.49853268e-01 4.11751419e-01 3.16643298e-01
3.92515600e-01 -1.60550326e-01 -7.94974342e-02 8.41956437e-01
2.22921055e-02 -1.40479088e+00 1.29358366e-01 -4.44684952e-01
8.84119689e-01 2.32311755e-01 2.63804913e-01 -5.45715019e-02
1.46252975e-01 -7.70288765e-01 2.06266820e-01 6.86642706e-01
6.29825652e-01 -7.72112012e-01 1.28348529e+00 2.42260937e-02
-1.07014287e+00 -3.40772033e-01 -3.64015043e-01 -1.74455985e-01
8.31340179e-02 9.49289441e-01 -2.60826290e-01 8.02264392e-01
7.89538801e-01 7.19429195e-01 -3.57359320e-01 9.40647721e-01
6.56710763e-05 8.89674067e-01 -2.45649204e-01 1.31656855e-01
4.61574227e-01 -4.36908126e-01 1.02213871e+00 9.43726778e-01
6.16980255e-01 4.48978543e-01 7.30698779e-02 6.70351863e-01
1.34442672e-01 -4.20747548e-01 -4.70549613e-01 -1.04330130e-01
1.66896477e-01 1.45872974e+00 -1.06568730e+00 3.56565006e-02
-3.69238108e-01 5.25073171e-01 -4.12975997e-01 4.16407615e-01
-6.30174458e-01 -5.27987480e-01 5.73625922e-01 -7.25886179e-03
7.65185893e-01 -5.13130248e-01 -1.26428664e-01 -9.62203383e-01
3.89927961e-02 -8.65754724e-01 1.48886949e-01 -6.95181847e-01
-1.31657779e+00 1.05831313e+00 -3.33593339e-01 -1.79128110e+00
5.80911696e-01 -5.21891177e-01 -5.33290803e-01 5.94745934e-01
-2.30165267e+00 -1.47280884e+00 -7.72649288e-01 5.86827397e-01
4.98128206e-01 -4.25515831e-01 6.11808240e-01 2.69335419e-01
-4.50559914e-01 -5.83788864e-02 4.96831805e-01 3.06020766e-01
3.45627010e-01 -6.68865860e-01 2.08356321e-01 1.32421958e+00
-2.74878561e-01 2.21091509e-01 7.47283578e-01 -7.18923628e-01
-1.53804147e+00 -1.38044322e+00 3.77772957e-01 2.95647413e-01
7.98470378e-01 2.38823697e-01 -7.60718524e-01 3.03761750e-01
9.72737595e-02 3.73265326e-01 3.84909302e-01 -6.02469504e-01
-2.08871752e-01 -5.56694448e-01 -1.06891799e+00 3.12959701e-01
1.02881742e+00 6.79326802e-02 -5.47481358e-01 1.86550856e-01
4.06360716e-01 -2.15126038e-01 -5.42663455e-01 9.57983077e-01
2.16287702e-01 -1.07860363e+00 9.56406295e-01 -2.86290437e-01
3.63917232e-01 -6.64014161e-01 -4.47520405e-01 -1.37607121e+00
-6.35555327e-01 -5.50343812e-01 3.12303215e-01 8.68274450e-01
-1.26002654e-01 -7.82002270e-01 5.97690940e-01 -2.94807702e-01
-2.27125362e-01 -4.97948021e-01 -1.13339520e+00 -9.68585372e-01
-3.64586562e-01 -4.07962129e-02 4.84401971e-01 1.04487801e+00
-1.00440753e+00 2.08818167e-01 -5.19007385e-01 6.13272965e-01
1.00795460e+00 4.76755351e-01 3.19453090e-01 -1.68827689e+00
6.83261380e-02 -1.24240130e-01 -5.02660453e-01 -5.27000189e-01
-1.83969945e-01 -6.75071776e-01 1.11413762e-01 -1.58466887e+00
-6.70960248e-02 -4.19000655e-01 -5.31461418e-01 2.01330319e-01
1.24231666e-01 7.66804934e-01 -7.09913447e-02 3.35266620e-01
-3.54557395e-01 7.67964244e-01 1.44188082e+00 -2.73642957e-01
8.97254497e-02 1.88713074e-01 -4.17438626e-01 8.36863220e-01
8.12871099e-01 -3.92028004e-01 -1.17841549e-01 -7.02347159e-01
3.22924733e-01 2.65681949e-02 6.30478621e-01 -1.46088564e+00
2.83479959e-01 -6.14436716e-03 7.12467134e-01 -7.62353539e-01
2.07460105e-01 -9.64316308e-01 2.59246737e-01 9.45147932e-01
8.43046233e-02 -8.53525549e-02 -4.96907383e-02 8.32133710e-01
-4.67619836e-01 2.58607447e-01 1.19274175e+00 -4.49381284e-02
-9.25130188e-01 3.35816950e-01 -3.64513665e-01 -2.70505935e-01
7.50074863e-01 -3.89255702e-01 -6.02097392e-01 -2.57360995e-01
-3.88660759e-01 -2.19993323e-01 -3.07198077e-01 8.29524398e-02
8.04896712e-01 -1.17778170e+00 -9.83972669e-01 4.37406838e-01
-1.27902538e-01 -2.00216681e-01 6.10209048e-01 1.14049411e+00
-7.82105684e-01 1.79444566e-01 -5.99823594e-01 -3.91430169e-01
-1.14169466e+00 9.82483104e-02 2.90698469e-01 -1.78252578e-01
-9.08916712e-01 6.87376380e-01 -1.61874235e-01 -2.83891946e-01
-2.79652745e-01 -2.75737554e-01 -3.34859312e-01 -8.11920241e-02
4.60804492e-01 5.64614177e-01 1.03921868e-01 -7.07985580e-01
-3.42083156e-01 7.71887481e-01 1.43499106e-01 4.28479880e-01
2.07145596e+00 -9.21318904e-02 -2.29461879e-01 -1.48146838e-01
7.51887918e-01 -1.12998009e-01 -1.16662264e+00 -8.14276814e-01
1.95419360e-02 -5.34392118e-01 5.21761775e-01 -1.00451624e+00
-1.31176305e+00 6.92421734e-01 1.13354504e+00 1.24233052e-01
1.58413613e+00 -5.73881388e-01 1.24794805e+00 7.63829291e-01
2.01636821e-01 -8.76795471e-01 1.51663676e-01 4.85347420e-01
6.99137688e-01 -1.43217921e+00 2.83801913e-01 -4.60513741e-01
-2.28769138e-01 1.44893682e+00 3.17556918e-01 -4.62654710e-01
8.86694014e-01 3.36617708e-01 4.18988496e-01 -5.57920814e-01
-1.21059820e-01 -3.80209982e-01 -1.41239986e-02 6.76170886e-01
-4.47118543e-02 -3.19656283e-02 -3.08590442e-01 3.84113729e-01
-4.81152674e-03 6.45922050e-02 4.35091048e-01 1.13792896e+00
-7.30182230e-01 -6.35559022e-01 -4.18689221e-01 6.00361049e-01
-4.23290342e-01 -8.78619850e-02 1.01874925e-01 8.46715212e-01
9.33420360e-02 8.81340981e-01 -1.64600834e-01 -2.93784589e-01
2.73210853e-01 -4.75019634e-01 3.00385386e-01 -5.39060012e-02
-4.91845876e-01 2.23596916e-01 -7.60574937e-02 -2.21738413e-01
-1.10185659e+00 -4.13017750e-01 -9.38053071e-01 1.09718870e-02
-4.80260819e-01 -9.51983854e-02 5.96825540e-01 1.13253999e+00
2.25796387e-01 6.88715100e-01 8.71889830e-01 -5.42614698e-01
-7.87684023e-01 -1.04611278e+00 -8.48928511e-01 1.91214070e-01
5.32529473e-01 -5.80738246e-01 -3.99241805e-01 -2.83509884e-02] | [10.457472801208496, -2.219019889831543] |
4a413d14-b6f4-4547-a08f-2624cd6f2aad | a-survey-on-multi-resident-activity | 2304.12304 | null | https://arxiv.org/abs/2304.12304v1 | https://arxiv.org/pdf/2304.12304v1.pdf | A Survey on Multi-Resident Activity Recognition in Smart Environments | Human activity recognition (HAR) is a rapidly growing field that utilizes smart devices, sensors, and algorithms to automatically classify and identify the actions of individuals within a given environment. These systems have a wide range of applications, including assisting with caring tasks, increasing security, and improving energy efficiency. However, there are several challenges that must be addressed in order to effectively utilize HAR systems in multi-resident environments. One of the key challenges is accurately associating sensor observations with the identities of the individuals involved, which can be particularly difficult when residents are engaging in complex and collaborative activities. This paper provides a brief overview of the design and implementation of HAR systems, including a summary of the various data collection devices and approaches used for human activity identification. It also reviews previous research on the use of these systems in multi-resident environments and offers conclusions on the current state of the art in the field. | ['Shingo Yamaguchi', 'Mohd Anuaruddin Bin Ahmadon', 'Raihani Mohamed', 'Norwati Mustapha', 'Thinagaran Perumal', 'Farhad MortezaPour Shiri'] | 2023-04-24 | null | null | null | null | ['human-activity-recognition', 'human-activity-recognition'] | ['computer-vision', 'time-series'] | [ 2.52094597e-01 -3.51545036e-01 -3.08341205e-01 -2.62687892e-01
-1.30282804e-01 -2.28394791e-01 2.03046918e-01 5.85839510e-01
-5.51618636e-01 7.93007851e-01 6.56704545e-01 1.22215338e-01
-2.83331722e-01 -7.15086460e-01 2.57541090e-02 -5.85403264e-01
-3.03712547e-01 4.35819291e-02 -3.84050459e-02 -6.02250267e-03
5.44984043e-02 5.92412949e-01 -1.89651811e+00 -3.33961565e-03
3.74564499e-01 8.74191225e-01 -1.18463293e-01 7.59673834e-01
3.02324742e-01 1.04365349e+00 -9.31643426e-01 3.27257693e-01
-8.22281167e-02 -4.56394821e-01 -5.06125331e-01 2.35508215e-02
1.07505716e-01 -5.55287659e-01 -1.59396648e-01 3.00404340e-01
6.27160668e-01 6.49916351e-01 3.82320434e-01 -1.21196151e+00
-4.96908203e-02 6.10487424e-02 2.63576135e-02 5.35663188e-01
1.18843448e+00 -3.17623913e-01 3.96787256e-01 -4.84389991e-01
-1.71045750e-01 7.11847544e-01 8.30594480e-01 4.27995920e-01
-9.71554816e-01 -7.04075158e-01 1.06997207e-01 3.02517056e-01
-1.59596229e+00 -7.29188144e-01 4.50055093e-01 -4.86178696e-01
1.15789151e+00 4.03948963e-01 1.07118034e+00 1.11405408e+00
-1.62335277e-01 7.02204764e-01 7.84153104e-01 -4.79123116e-01
6.64185286e-01 1.68459818e-01 4.04472083e-01 2.72855610e-01
6.83874071e-01 -3.11672777e-01 -8.07137609e-01 -5.93635917e-01
5.43825805e-01 5.65415025e-01 -9.33129191e-02 -4.01201725e-01
-1.11992049e+00 4.66964453e-01 9.74380523e-02 5.34804642e-01
-6.66576982e-01 -1.36942178e-01 1.01289034e-01 -3.96018296e-01
-1.38373002e-01 4.26612556e-01 5.61809167e-02 -8.12855661e-01
-6.58388853e-01 1.46014899e-01 9.74270284e-01 7.60019422e-01
3.10162604e-01 -1.93215519e-01 -1.70796812e-01 6.72693133e-01
4.70586091e-01 5.03720701e-01 3.79233629e-01 -1.02224231e+00
2.35632598e-01 8.26218307e-01 5.33115089e-01 -7.94609606e-01
-5.80376804e-01 9.84236449e-02 -4.69384819e-01 -5.04162386e-02
2.13380828e-01 -4.67522562e-01 -2.83692956e-01 1.21933877e+00
4.59057301e-01 8.08624104e-02 -8.00631717e-02 3.76721591e-01
6.66013777e-01 2.08505258e-01 5.11243999e-01 -2.81665027e-01
1.49002266e+00 -7.00200021e-01 -1.11449754e+00 -6.20474994e-01
4.36390042e-01 -2.17266783e-01 5.73296845e-01 -7.44770886e-03
-8.43967736e-01 -2.88497359e-01 -1.18334043e+00 1.61642402e-01
-5.54246247e-01 -1.50227835e-02 5.70331395e-01 1.22698057e+00
-5.85920572e-01 7.40259811e-02 -1.31580937e+00 -9.63203788e-01
4.30708826e-01 5.37386358e-01 -3.10465366e-01 1.34950712e-01
-6.32518530e-01 8.33488107e-01 -1.29276350e-01 -1.26908749e-01
-2.66582578e-01 -2.76578069e-01 -1.10655880e+00 -6.31519109e-02
-1.09235495e-01 -2.58694947e-01 1.41852117e+00 -3.10704947e-01
-1.10424805e+00 6.09252870e-01 -5.01026630e-01 -2.93899238e-01
2.74183571e-01 -5.58750451e-01 -8.64823163e-01 -7.43922740e-02
2.39500672e-01 -2.73640268e-02 -4.89456020e-02 -5.51496565e-01
-9.01635110e-01 -6.36667967e-01 -1.71223253e-01 5.18905401e-01
-6.86226904e-01 2.06525445e-01 3.00039470e-01 -1.91945672e-01
-3.86497319e-01 -7.92191148e-01 -1.65472895e-01 -1.71549439e-01
1.79602697e-01 -7.43087381e-02 9.25923347e-01 -5.49727738e-01
1.70656037e+00 -2.38163614e+00 -7.13206470e-01 2.98557580e-01
-5.24687171e-02 3.01526636e-01 5.71121275e-01 8.71092319e-01
4.78723437e-01 -2.62189984e-01 6.66467920e-02 -4.02976871e-01
-6.72119483e-02 2.64430165e-01 2.80010253e-01 6.59752429e-01
-5.50396860e-01 5.89323521e-01 -1.00387442e+00 -4.74248350e-01
6.49380744e-01 5.48401237e-01 -5.40280268e-02 4.09127265e-01
6.79482758e-01 4.49975669e-01 -5.91846704e-01 7.49079347e-01
1.76742431e-02 -1.81455940e-01 5.03712773e-01 4.02447999e-01
-3.78751785e-01 4.33098048e-01 -1.61949933e+00 1.08526766e+00
-1.24326408e-01 6.30526185e-01 2.25133315e-01 -9.70977843e-01
7.03868151e-01 5.00517607e-01 1.13744187e+00 -6.06230140e-01
2.72684991e-01 6.76696524e-02 -4.58321720e-01 -8.71149659e-01
5.57054043e-01 3.55715185e-01 -2.69712538e-01 7.76451409e-01
-5.75390697e-01 8.11066687e-01 2.34376103e-01 -3.11618328e-01
1.66417742e+00 -2.26651311e-01 1.20849717e+00 -3.23033221e-02
4.66390073e-01 -1.88794881e-01 5.88300884e-01 7.16437042e-01
-8.49044383e-01 3.51545699e-02 -5.65118372e-01 -5.50456405e-01
-2.86010593e-01 -8.70159447e-01 6.13906793e-02 1.31864166e+00
2.82098085e-01 -3.90598953e-01 -7.74379790e-01 -3.54852438e-01
8.53112042e-02 4.36213821e-01 -5.52285969e-01 1.01586625e-01
-6.27587616e-01 -6.80890799e-01 6.03759527e-01 9.95719433e-01
9.59104240e-01 -1.11209965e+00 -1.53928101e+00 4.36995596e-01
-6.22602522e-01 -1.25203967e+00 -3.87992233e-01 1.60398826e-01
-7.20325828e-01 -1.27980614e+00 -1.53238311e-01 -8.23054671e-01
8.16782355e-01 7.98913717e-01 6.84486449e-01 2.01789498e-01
-4.71172601e-01 1.07359385e+00 -3.32834542e-01 -6.43119097e-01
2.14112610e-01 6.80203810e-02 3.19978863e-01 1.15132956e-02
1.14438105e+00 -4.79855329e-01 -7.85442531e-01 6.02059603e-01
-3.22932452e-01 -4.82013136e-01 2.57150531e-01 1.68728113e-01
2.12055400e-01 1.99655697e-01 4.14962769e-01 -4.85158324e-01
6.79299116e-01 -6.26273394e-01 7.44137689e-02 3.89359295e-01
-4.93696809e-01 -3.04473460e-01 1.71281561e-01 -5.07608056e-01
-8.82630348e-01 4.55641180e-01 1.49803907e-01 5.51875353e-01
-6.82177126e-01 2.69059967e-02 -2.72548765e-01 -1.67727739e-01
8.50401103e-01 -1.73385188e-01 -4.20268811e-02 -5.12526631e-01
-5.31266093e-01 1.21621120e+00 4.82179254e-01 -3.18594575e-01
1.82074741e-01 6.06466472e-01 -1.42004445e-01 -1.26168752e+00
-6.89318419e-01 -1.20587838e+00 -6.57304704e-01 -4.38772798e-01
8.65228176e-01 -9.84424174e-01 -1.04146159e+00 5.64270556e-01
-4.91233915e-01 -4.65489656e-01 -1.82773933e-01 6.24850154e-01
-2.30286241e-01 2.13460863e-01 -2.26079583e-01 -1.41679966e+00
-4.16567147e-01 -6.32222235e-01 8.01917970e-01 7.48012364e-01
-1.13635242e+00 -9.51414227e-01 3.71309668e-01 1.06891823e+00
3.96743268e-01 6.09772980e-01 1.15214020e-01 -4.38245237e-01
-1.06179811e-01 -6.02656603e-01 5.63206911e-01 -2.07932159e-01
6.59117043e-01 -4.59656686e-01 -9.73762393e-01 -2.71339804e-01
-1.90693557e-01 9.41261202e-02 -2.09829837e-01 4.08585101e-01
7.87884951e-01 -3.83808255e-01 -8.63009155e-01 8.92385542e-02
8.62696111e-01 6.33873224e-01 6.95556521e-01 5.50047398e-01
2.10975900e-01 3.48885298e-01 7.75775015e-01 8.52141500e-01
8.30303431e-01 7.17936397e-01 9.83868167e-02 9.57201514e-03
2.85787284e-01 -2.71653593e-01 5.72854400e-01 9.75117162e-02
-4.41513985e-01 -1.01572014e-01 -7.05372453e-01 6.46589339e-01
-2.13781834e+00 -1.45776713e+00 4.22039889e-02 2.40159225e+00
2.68137574e-01 -4.72238213e-01 7.07148790e-01 6.32128239e-01
5.58288038e-01 -5.38183972e-02 -4.98623967e-01 -2.17778429e-01
4.27961200e-01 1.93976179e-01 5.69267333e-01 1.96404576e-01
-1.29794192e+00 1.15375400e-01 7.85267973e+00 -4.06145960e-01
-4.78314966e-01 -4.65413406e-02 7.28441635e-03 -2.77678877e-01
7.15821683e-01 -4.70842510e-01 -9.98868644e-01 4.41886187e-01
9.74084258e-01 -2.39318311e-02 5.32161236e-01 1.07763541e+00
5.75388074e-01 -7.63622582e-01 -1.16224003e+00 1.16941381e+00
3.01556706e-01 -8.01315129e-01 -7.34636724e-01 4.15973097e-01
5.04302621e-01 -2.95190603e-01 -5.11891723e-01 2.04491422e-01
2.19293088e-01 -8.65852892e-01 4.27839398e-01 3.23976487e-01
2.68610835e-01 -5.58482945e-01 6.09057486e-01 5.51506341e-01
-1.72154188e+00 -6.19215190e-01 4.56879228e-01 -8.56666923e-01
3.26416343e-01 2.20304474e-01 -7.59433866e-01 -1.60883591e-01
1.31693709e+00 5.21367610e-01 -4.79921907e-01 1.26271486e+00
-1.71953663e-02 2.53557861e-01 -4.69899148e-01 -4.82052594e-01
-3.84075284e-01 -1.27292246e-01 5.49692661e-02 1.09571493e+00
4.52542186e-01 5.72753310e-01 4.73451078e-01 -4.68661301e-02
2.02189445e-01 -1.57287002e-01 -7.92935908e-01 7.04540731e-03
9.59436655e-01 1.15260577e+00 -4.57102269e-01 -2.22219557e-01
-4.70687449e-01 6.48445487e-01 9.51879099e-02 1.37007907e-01
-4.56860006e-01 -3.39106858e-01 1.08122587e+00 7.28910625e-01
-1.97471812e-01 -6.41281188e-01 -2.83167481e-01 -6.01434290e-01
4.06388380e-02 -7.15940177e-01 9.20167446e-01 -3.58089179e-01
-6.43239141e-01 -2.74694383e-01 2.10525125e-01 -1.29198766e+00
-4.22558576e-01 -2.17253253e-01 -6.04455113e-01 2.70167381e-01
-7.11567998e-01 -7.26120055e-01 -1.12508905e+00 6.78096473e-01
2.86709487e-01 1.67657927e-01 1.34158492e+00 5.31959236e-01
-7.37636447e-01 4.42740828e-01 -6.13267533e-02 3.51934522e-01
4.32451785e-01 -8.77457500e-01 -3.78507678e-03 9.38698351e-01
-1.84878513e-01 9.06691730e-01 4.49843079e-01 -6.70194983e-01
-1.39007199e+00 -8.24500084e-01 9.86940682e-01 -6.70522273e-01
4.70719635e-02 -4.45838928e-01 -5.13885081e-01 9.11720216e-01
-1.19744584e-01 -1.08514085e-01 1.56523860e+00 1.85563862e-01
2.53892690e-01 -1.76893115e-01 -1.52950108e+00 5.87355733e-01
1.29332995e+00 -4.24962342e-01 -3.94063711e-01 2.97416504e-02
-3.37568671e-01 -2.66730040e-01 -1.05796778e+00 1.63944975e-01
1.04701877e+00 -8.75217974e-01 1.03582537e+00 -1.17357798e-01
-6.50218844e-01 -4.37786162e-01 -1.16434991e-01 -8.60191107e-01
-4.92558688e-01 -4.98570800e-01 -6.52592182e-01 9.82332528e-01
-2.48327121e-01 -7.26835787e-01 8.68033469e-01 1.42245340e+00
1.90015614e-01 -1.59977853e-01 -6.88798428e-01 -5.87759078e-01
-1.10417914e+00 -5.52622788e-02 8.34952593e-01 7.16391802e-01
7.49221742e-01 2.37288028e-01 -2.97662437e-01 2.18780264e-01
6.83437645e-01 -5.00802457e-01 9.98358190e-01 -1.40795016e+00
7.01745749e-02 -1.19219363e-01 -7.00183332e-01 -7.93596148e-01
-3.98454577e-01 1.49031142e-02 2.01830938e-01 -1.90479028e+00
3.27500701e-02 -1.56314239e-01 -2.29627222e-01 6.90810561e-01
5.35003729e-02 -2.97780205e-02 -4.54959452e-01 1.37258008e-01
-8.94194901e-01 1.55855566e-01 2.67147422e-01 9.68879908e-02
-6.83804870e-01 4.86897886e-01 -8.56544137e-01 6.20437264e-01
1.16198647e+00 -1.07094921e-01 -2.79015988e-01 -1.03667192e-01
-5.21590412e-02 -2.41950855e-01 2.92254418e-01 -1.63088763e+00
6.47205234e-01 -5.52988291e-01 6.28118932e-01 -4.87351835e-01
5.81771016e-01 -1.18795812e+00 5.59406340e-01 6.55694366e-01
-1.36440486e-01 2.07609236e-01 -5.87619916e-02 5.50311029e-01
1.20701499e-01 5.32211587e-02 6.60350800e-01 -1.55691117e-01
-8.48459423e-01 -1.55463507e-02 -1.04694748e+00 -2.81779319e-01
1.61681759e+00 -6.28704488e-01 -2.63440490e-01 -4.35021341e-01
-4.70742792e-01 3.74564528e-01 5.23841977e-01 5.83413124e-01
3.79050046e-01 -1.37109423e+00 1.01434171e-01 4.94311720e-01
4.39886540e-01 -1.81208968e-01 1.25461876e-01 7.45393872e-01
-3.52341026e-01 2.06026688e-01 -2.94559658e-01 -1.89565942e-01
-1.84470749e+00 6.29116446e-02 4.00799662e-01 -5.55433100e-03
-5.55662632e-01 -3.73539813e-02 -5.80759585e-01 -5.33879623e-02
6.96703792e-01 -5.79336472e-02 -6.91684783e-01 -1.71988398e-01
1.22063601e+00 1.20457244e+00 3.85700986e-02 -7.38103092e-01
-8.75186861e-01 2.89664418e-01 3.42535019e-01 -8.12692195e-03
1.20188320e+00 -3.75573426e-01 2.48615697e-01 3.88705373e-01
6.24378145e-01 -3.13867182e-02 -9.36902106e-01 -2.09690198e-01
1.13824554e-01 -2.80331016e-01 -1.16202965e-01 -4.38567787e-01
-4.00616825e-01 4.57718879e-01 9.60382223e-01 2.79130995e-01
9.13467169e-01 -2.05675751e-01 7.67889380e-01 4.61753547e-01
7.42115796e-01 -1.64603770e+00 2.09729075e-01 1.18745014e-01
2.72548556e-01 -1.05183589e+00 2.17541784e-01 -1.81612238e-01
-4.25133437e-01 6.93320930e-01 5.57989955e-01 2.75206447e-01
8.56007159e-01 2.80431747e-01 -2.94728521e-02 -2.27952078e-01
-3.85961533e-02 -2.49974981e-01 -2.30157033e-01 1.02822268e+00
4.94825453e-01 4.49926108e-01 -1.09580852e-01 4.64506358e-01
-1.51223421e-01 2.84515411e-01 3.96398693e-01 1.88299477e+00
-7.03925014e-01 -1.02033019e+00 -8.55224371e-01 6.40389323e-01
-3.93873125e-01 7.40971565e-01 -4.27258462e-01 3.30758303e-01
2.07377046e-01 1.71432447e+00 -6.94700703e-02 -4.32666123e-01
7.54734218e-01 1.60410479e-01 2.39109054e-01 -7.35626638e-01
-7.70746469e-01 -4.65311050e-01 4.14737970e-01 -5.88522315e-01
-8.69222462e-01 -1.31406081e+00 -1.25256264e+00 -5.27193427e-01
2.46379599e-01 1.63561597e-01 6.27991080e-01 9.62328792e-01
5.61087489e-01 3.05195779e-01 4.95744586e-01 -7.60135055e-01
-4.72855987e-03 -8.01210105e-01 -7.13073194e-01 4.16101635e-01
3.31351131e-01 -8.44101131e-01 -1.76961541e-01 1.75638169e-01] | [7.259828090667725, 0.6421546936035156] |
6ba68499-bf4e-42ac-9fc7-c6958fae2071 | a-simple-and-effective-pruning-approach-for | 2306.11695 | null | https://arxiv.org/abs/2306.11695v1 | https://arxiv.org/pdf/2306.11695v1.pdf | A Simple and Effective Pruning Approach for Large Language Models | As their size increases, Large Languages Models (LLMs) are natural candidates for network pruning methods: approaches that drop a subset of network weights while striving to preserve performance. Existing methods, however, require either retraining, which is rarely affordable for billion-scale LLMs, or solving a weight reconstruction problem reliant on second-order information, which may also be computationally expensive. In this paper, we introduce a novel, straightforward yet effective pruning method, termed Wanda (Pruning by Weights and activations), designed to induce sparsity in pretrained LLMs. Motivated by the recent observation of emergent large magnitude features in LLMs, our approach prune weights with the smallest magnitudes multiplied by the corresponding input activations, on a per-output basis. Notably, Wanda requires no retraining or weight update, and the pruned LLM can be used as is. We conduct a thorough evaluation of our method on LLaMA across various language benchmarks. Wanda significantly outperforms the established baseline of magnitude pruning and competes favorably against recent methods involving intensive weight update. Code is available at https://github.com/locuslab/wanda. | ['J. Zico Kolter', 'Anna Bair', 'Zhuang Liu', 'MingJie Sun'] | 2023-06-20 | null | null | null | null | ['network-pruning'] | ['methodology'] | [ 1.41807005e-01 1.35206178e-01 -3.98779631e-01 -2.41372973e-01
-3.03050011e-01 -2.56283164e-01 4.35071647e-01 2.83557564e-01
-7.52823055e-01 5.91918409e-01 1.90588266e-01 -5.96924961e-01
-9.56536084e-02 -8.11555624e-01 -7.51366496e-01 -2.81254470e-01
-2.54805293e-02 2.77706653e-01 3.49011511e-01 -2.06875741e-01
1.12241872e-01 4.73467052e-01 -1.19586623e+00 2.97468871e-01
8.33921969e-01 1.03598797e+00 1.63615867e-01 4.42214727e-01
-2.58065879e-01 8.84815931e-01 -5.09036005e-01 -6.50182545e-01
4.51237768e-01 -1.11261718e-01 -8.94554198e-01 -2.16068938e-01
6.42528236e-01 -2.24746883e-01 -6.12125993e-01 9.94582653e-01
2.81695843e-01 3.87976974e-01 2.05255449e-01 -9.20529604e-01
-3.36800367e-01 1.35797429e+00 -7.05852747e-01 4.99599844e-01
-2.70932823e-01 1.32003933e-01 1.38594222e+00 -1.12745261e+00
5.28717816e-01 1.27308881e+00 9.06213403e-01 5.62268734e-01
-1.66568983e+00 -8.24685037e-01 5.47109008e-01 -1.34782523e-01
-1.47666144e+00 -8.53506207e-01 7.32754230e-01 1.01469971e-01
1.38530672e+00 3.30849558e-01 6.48936093e-01 1.08632398e+00
-1.13652639e-01 9.01920080e-01 6.37548447e-01 -5.63870430e-01
7.03459904e-02 5.44854179e-02 3.61207157e-01 1.00882447e+00
6.30418479e-01 -3.26781511e-01 -7.23016620e-01 -5.30732870e-01
4.40117031e-01 1.25079945e-01 -2.48868570e-01 -2.61520028e-01
-9.92820799e-01 8.02393675e-01 4.71678913e-01 3.26478571e-01
-2.08942175e-01 4.57638621e-01 4.63679850e-01 5.25050998e-01
6.64157152e-01 5.43548286e-01 -6.93663180e-01 -6.58045933e-02
-1.21056843e+00 1.27592027e-01 9.22719538e-01 7.90524125e-01
7.83838272e-01 2.53211707e-01 -2.72786975e-01 1.11683929e+00
9.68812481e-02 1.15138441e-01 4.37312275e-01 -7.70561993e-01
7.03040600e-01 7.31924117e-01 -4.47608292e-01 -8.76515746e-01
-3.80059481e-01 -6.94015443e-01 -1.02232754e+00 -3.11694350e-02
3.25125486e-01 -1.84011698e-01 -9.17375267e-01 1.95275116e+00
1.12752849e-02 2.54081696e-01 -2.47416496e-01 4.47282493e-01
5.20535469e-01 5.38802683e-01 8.70987773e-02 -1.64479882e-01
1.02500355e+00 -1.10278165e+00 -2.37755477e-01 -5.55133700e-01
7.99364448e-01 -5.97190320e-01 1.38940573e+00 5.11550367e-01
-1.25521839e+00 -9.81310010e-02 -9.85572994e-01 -5.63607588e-02
-1.87527999e-01 2.39724115e-01 8.10039401e-01 4.97603148e-01
-1.10524821e+00 9.81872559e-01 -9.89922583e-01 -2.50520706e-01
7.86476791e-01 6.71667755e-01 -1.43524110e-01 -1.17938332e-01
-9.75506127e-01 8.31177652e-01 3.61870795e-01 1.70659963e-02
-6.92154646e-01 -9.02540028e-01 -8.32152009e-01 4.16884214e-01
5.69725692e-01 -4.79981452e-01 1.22156942e+00 -6.38947725e-01
-1.37167311e+00 7.09663630e-01 -2.32269883e-01 -9.71909940e-01
3.69360924e-01 -3.40332121e-01 -2.65287459e-01 -1.31030694e-01
-4.24365729e-01 6.73297286e-01 8.98211241e-01 -9.39390361e-01
-3.82073641e-01 8.49818885e-02 2.12149307e-01 -7.31326342e-02
-9.79999959e-01 -9.62218046e-02 -6.12944603e-01 -8.96802127e-01
1.16715534e-02 -6.87906742e-01 -5.19052982e-01 -7.63131082e-02
-6.06602192e-01 -3.21562409e-01 4.93625402e-01 -3.27735484e-01
1.81269026e+00 -2.18535280e+00 1.98797375e-01 5.64006031e-01
8.51816356e-01 4.68269497e-01 -4.62289572e-01 2.00673759e-01
1.44754514e-01 3.57108444e-01 -2.69139886e-01 -6.95636034e-01
-3.32599599e-03 2.26591989e-01 -3.43329817e-01 3.75153571e-01
2.20115080e-01 8.42681766e-01 -7.86374331e-01 -4.77047741e-01
-1.18076488e-01 2.51736015e-01 -9.44391727e-01 -1.82341650e-01
-1.47221833e-01 -2.90905505e-01 -2.69825608e-01 6.65265799e-01
4.36055720e-01 -4.10798639e-01 2.52325237e-01 -3.36259365e-01
-9.55173932e-03 6.47148490e-01 -1.00095010e+00 1.64677048e+00
-4.73866761e-01 6.40860915e-01 1.39741734e-01 -1.05941081e+00
9.17675734e-01 -8.87288526e-02 2.04791918e-01 -4.05492187e-01
2.47276053e-01 3.17357898e-01 3.85401815e-01 2.01402247e-01
4.11274880e-01 1.78337380e-01 4.15862016e-02 5.77263713e-01
4.06871378e-01 -3.63909602e-02 5.96961081e-01 5.09072721e-01
1.55054748e+00 -3.57038438e-01 1.49890065e-01 -4.87327099e-01
3.70505661e-01 -2.77816504e-01 8.83533776e-01 9.70115781e-01
2.05509700e-02 2.80274808e-01 6.44277871e-01 -5.21684825e-01
-1.03444088e+00 -9.08849180e-01 -6.18603416e-02 1.32210267e+00
-2.88900495e-01 -9.06253755e-01 -6.21497571e-01 -7.01955318e-01
1.89349785e-01 5.57972729e-01 -3.58211637e-01 -4.25524682e-01
-8.63277018e-01 -8.94220591e-01 7.92719066e-01 3.87274384e-01
3.49676877e-01 -1.02588511e+00 -3.27010423e-01 3.25919539e-01
2.91957051e-01 -9.74750817e-01 -5.95064342e-01 6.22660041e-01
-1.15268767e+00 -8.23036671e-01 -5.06559432e-01 -6.88754320e-01
7.92236924e-01 1.91364184e-01 1.26694882e+00 6.59383953e-01
-2.81074941e-01 -9.97849405e-02 -3.96620259e-02 -3.13348442e-01
-1.54392853e-01 8.41520250e-01 3.66148710e-01 -2.61346728e-01
3.43292356e-01 -1.00425208e+00 -5.08035123e-01 -1.35608062e-01
-7.12090790e-01 1.36749864e-01 8.02884102e-01 8.15957367e-01
5.15126944e-01 -2.04672754e-01 5.45151711e-01 -1.41303778e+00
9.14936185e-01 -4.18364316e-01 -5.10882497e-01 3.14235866e-01
-7.18598962e-01 3.31438959e-01 7.00185955e-01 -7.70705640e-01
-6.53225183e-01 -1.62686244e-01 -7.78385699e-02 -4.68638629e-01
2.71450847e-01 5.90055048e-01 1.94974363e-01 -3.61215502e-01
7.55645633e-01 2.71802247e-02 -2.20786542e-01 -7.15557337e-01
3.05318892e-01 1.88714147e-01 3.19878280e-01 -9.06753838e-01
8.43293905e-01 3.07905674e-01 -1.77970201e-01 -6.03527308e-01
-1.00198507e+00 -2.23950714e-01 -3.97175848e-01 2.13753045e-01
4.45900559e-02 -8.25910330e-01 -3.90799522e-01 1.39842585e-01
-1.02978754e+00 -6.68832362e-01 -4.55903351e-01 2.95036614e-01
-2.82241534e-02 2.06566155e-01 -1.01321959e+00 -4.04038072e-01
-8.17102432e-01 -8.39625180e-01 4.28587466e-01 2.60593742e-03
-5.88363469e-01 -7.83799827e-01 -1.70773312e-01 -1.45179808e-01
7.74253368e-01 -1.04834601e-01 1.22157705e+00 -7.16988921e-01
-2.94388682e-01 -1.64105654e-01 -3.47657293e-01 4.34291899e-01
-8.14448446e-02 -1.68687422e-02 -6.42979383e-01 -3.84677768e-01
-2.06428349e-01 -5.47126830e-01 1.31856894e+00 1.63686708e-01
1.49874163e+00 -4.48981941e-01 -3.68497640e-01 7.96915591e-01
1.20813274e+00 -3.93010348e-01 8.26341212e-02 1.41643345e-01
7.37461865e-01 -3.79023585e-03 -1.77998189e-02 5.74547589e-01
4.93833609e-02 2.74799615e-01 2.14713991e-01 -1.53319851e-01
-2.64313132e-01 -2.69984275e-01 2.79772490e-01 1.41387498e+00
-1.11577965e-01 -2.05558538e-01 -9.63435292e-01 4.72764611e-01
-1.74806762e+00 -6.55322075e-01 1.81349665e-01 2.02749586e+00
1.29004300e+00 7.66820788e-01 -1.71122596e-01 1.74306378e-01
3.79091054e-01 3.99259627e-01 -7.17843354e-01 -5.08743227e-01
-1.51758045e-01 8.00615609e-01 7.30133712e-01 5.55215657e-01
-8.64465296e-01 1.14491749e+00 6.16329575e+00 1.06499207e+00
-9.66092527e-01 3.06921542e-01 8.04607630e-01 -7.19508052e-01
-4.52219605e-01 8.13470855e-02 -1.05647218e+00 1.69485778e-01
9.60271835e-01 -1.79700285e-01 7.74915874e-01 7.77713478e-01
3.37347165e-02 2.40194444e-02 -1.07975197e+00 8.79462600e-01
-1.02074429e-01 -1.51481009e+00 2.26430222e-01 -1.17120944e-01
8.23741913e-01 5.89668870e-01 -1.23574294e-01 6.20712757e-01
5.85762322e-01 -9.58421350e-01 6.98481858e-01 3.78968209e-01
6.38758242e-01 -8.49520922e-01 4.32186425e-01 4.64477748e-01
-1.22290957e+00 -8.16943198e-02 -7.13017285e-01 -2.61736155e-01
-3.00740302e-02 9.81236100e-01 -2.68225998e-01 -1.37027666e-01
6.85569704e-01 6.51367188e-01 -6.50056839e-01 1.01001287e+00
-2.97445476e-01 1.02594960e+00 -7.25973487e-01 -1.66865233e-02
3.16543639e-01 -3.19503285e-02 4.60047245e-01 1.41091967e+00
1.36862516e-01 -1.00785740e-01 2.46676832e-01 8.61666501e-01
-8.31614375e-01 7.21226484e-02 -3.85003000e-01 -1.50373533e-01
7.62943506e-01 1.29084170e+00 -7.46913433e-01 -4.39048469e-01
-4.85373825e-01 6.81245446e-01 9.96683359e-01 3.91475141e-01
-7.35112727e-01 -4.90799785e-01 7.49756396e-01 1.21577822e-01
3.57336015e-01 -1.86184049e-01 -3.50550860e-01 -1.33698058e+00
4.74256389e-02 -9.14956748e-01 2.96051532e-01 -1.00527048e-01
-1.07045233e+00 6.98755383e-01 -1.62268355e-01 -7.12159336e-01
2.28445634e-01 -4.97237325e-01 -7.65141785e-01 6.79549038e-01
-1.39809954e+00 -7.17092276e-01 4.95412480e-03 4.49448436e-01
6.50901914e-01 -2.08554253e-01 6.97460651e-01 5.36015272e-01
-9.60663676e-01 9.54079747e-01 -2.00643212e-01 1.15847746e-02
4.10106152e-01 -9.18734908e-01 5.48883557e-01 8.35745275e-01
5.52023172e-01 9.41509664e-01 4.64101255e-01 -5.06382406e-01
-1.27067506e+00 -1.11714935e+00 1.07922101e+00 -2.51225755e-02
9.24150586e-01 -7.89127171e-01 -1.12727118e+00 7.55710185e-01
1.80130601e-01 4.04273957e-01 4.81671274e-01 4.95433539e-01
-4.88564253e-01 -2.14240372e-01 -8.69421124e-01 8.09622228e-01
1.42419565e+00 -3.68160903e-01 -4.47760284e-01 3.36575717e-01
8.95591497e-01 -3.43241632e-01 -6.90732896e-01 4.36204791e-01
2.78458655e-01 -5.46093464e-01 9.94209886e-01 -6.92227542e-01
2.52701998e-01 4.75505143e-02 5.37398718e-02 -1.13705301e+00
-3.90755177e-01 -8.32593501e-01 -8.28556836e-01 1.17033172e+00
7.86277711e-01 -5.29545128e-01 9.62884367e-01 4.23641354e-01
1.66145689e-03 -1.19511783e+00 -8.35492790e-01 -8.82212937e-01
9.50925238e-03 -6.01723075e-01 6.17898881e-01 9.05914545e-01
-5.68759665e-02 3.53989691e-01 -3.97450507e-01 -1.32233471e-01
4.64110404e-01 -8.48672464e-02 4.11448121e-01 -1.28552449e+00
-4.85361159e-01 -9.24629390e-01 2.73496211e-02 -1.14604414e+00
2.67485142e-01 -1.23611546e+00 -1.61247492e-01 -1.14910579e+00
1.51590973e-01 -5.96854687e-01 -6.22649491e-01 9.39235568e-01
-4.11676336e-03 3.15920115e-01 2.84765750e-01 2.58052379e-01
-7.47405708e-01 5.65910220e-01 7.27396488e-01 -3.05948228e-01
-2.63692230e-01 7.52806664e-02 -7.49351978e-01 1.07098544e+00
1.07797718e+00 -8.29704642e-01 -4.49020177e-01 -7.60280252e-01
5.38513362e-01 -5.52740753e-01 -6.30885689e-03 -1.03892136e+00
3.70175153e-01 -3.26367281e-02 1.93034008e-01 -3.50758046e-01
2.24190190e-01 -5.08667409e-01 -4.19740856e-01 6.69739664e-01
-3.78523409e-01 1.80925295e-01 3.81204367e-01 3.49855721e-01
-5.55860884e-02 -5.07255316e-01 7.41461456e-01 -6.97132796e-02
-4.52112526e-01 4.78172183e-01 -2.61972368e-01 2.75149137e-01
4.80665505e-01 9.92783755e-02 -2.38562316e-01 5.01124598e-02
-5.86824715e-01 2.43766457e-01 1.01010725e-01 2.15449721e-01
5.95023990e-01 -1.26767445e+00 -5.00112951e-01 5.52660301e-02
-1.78599223e-01 4.61341813e-02 -1.64107233e-01 8.79375696e-01
-4.38909471e-01 2.30985180e-01 2.76122719e-01 -1.55586256e-02
-1.18274081e+00 3.18278939e-01 1.71272069e-01 -6.81107283e-01
-8.39348793e-01 1.28248894e+00 -1.72448248e-01 -4.90975767e-01
5.70858300e-01 -7.57538080e-01 1.04665615e-01 -1.00005940e-01
4.71084923e-01 2.91312665e-01 2.05149233e-01 -5.05733192e-02
-2.70003766e-01 4.54656594e-02 -4.56590921e-01 2.62322634e-01
1.70590460e+00 2.30702177e-01 -2.63117999e-01 3.61707389e-01
9.34665263e-01 2.40837455e-01 -1.14134777e+00 -8.11258554e-01
3.40332627e-01 -1.78526819e-01 1.87776849e-01 -4.04704630e-01
-1.52513945e+00 6.84321225e-01 -3.40639167e-02 3.16254050e-02
1.12646484e+00 -6.91435933e-02 9.72190022e-01 8.18093598e-01
3.04762572e-01 -1.13367832e+00 -3.78922336e-02 8.28216612e-01
7.45535314e-01 -1.00834548e+00 3.27934206e-01 -2.86559761e-01
-1.81534559e-01 9.16296542e-01 7.57662177e-01 -4.45228487e-01
7.92485535e-01 6.16236925e-01 -4.55116630e-01 -1.28670320e-01
-1.25308108e+00 2.15557218e-02 2.53434449e-01 6.28050119e-02
5.12434304e-01 -1.13134389e-03 -4.68675941e-01 7.77682185e-01
-2.31956080e-01 -2.35302210e-01 1.80275172e-01 1.03317595e+00
-5.75068653e-01 -1.20886838e+00 6.29765391e-02 1.08588338e+00
-4.81491715e-01 -6.89158320e-01 -2.83477187e-01 7.44665682e-01
1.47163719e-01 4.67423588e-01 4.22815531e-02 -2.94504821e-01
3.64738375e-01 1.08366735e-01 2.93030590e-01 -8.95025015e-01
-8.16324770e-01 -1.21832035e-01 1.73956186e-01 -6.12629890e-01
6.16792925e-02 -4.19381589e-01 -1.20498669e+00 -7.74235070e-01
-3.99639904e-01 -9.71067846e-02 1.46845818e-01 8.64928961e-01
3.75842065e-01 4.58567828e-01 1.63221031e-01 -6.75975263e-01
-7.02363074e-01 -1.06106699e+00 -4.07327622e-01 2.09857002e-01
1.37220532e-01 -4.01933789e-01 -2.80698657e-01 -3.98358047e-01] | [8.653300285339355, 3.4666733741760254] |
b623e22a-0274-4d45-b75a-9689938e3bda | towards-generative-aspect-based-sentiment | null | null | https://aclanthology.org/2021.acl-short.64/ | https://aclanthology.org/2021.acl-short.64.pdf | Towards Generative Aspect-Based Sentiment Analysis | Aspect-based sentiment analysis (ABSA) has received increasing attention recently. Most existing work tackles ABSA in a discriminative manner, designing various task-specific classification networks for the prediction. Despite their effectiveness, these methods ignore the rich label semantics in ABSA problems and require extensive task-specific designs. In this paper, we propose to tackle various ABSA tasks in a unified generative framework. Two types of paradigms, namely annotation-style and extraction-style modeling, are designed to enable the training process by formulating each ABSA task as a text generation problem. We conduct experiments on four ABSA tasks across multiple benchmark datasets where our proposed generative approach achieves new state-of-the-art results in almost all cases. This also validates the strong generality of the proposed framework which can be easily adapted to arbitrary ABSA task without additional taskspecific model design. | ['Wai Lam', 'Lidong Bing', 'Yang Deng', 'Xin Li', 'Wenxuan Zhang'] | 2021-08-01 | null | https://aclanthology.org/2021.acl-short.64 | https://aclanthology.org/2021.acl-short.64.pdf | acl-2021-5 | ['aspect-sentiment-triplet-extraction'] | ['natural-language-processing'] | [ 5.74449480e-01 1.20011710e-01 -1.66652530e-01 -6.56695724e-01
-8.66622388e-01 -4.71731067e-01 1.12225425e+00 -1.73288956e-01
-5.62238246e-02 5.45229912e-01 1.75447717e-01 -3.33885163e-01
-5.38644753e-03 -8.84565890e-01 -6.23974442e-01 -7.00572193e-01
6.10493481e-01 4.44030076e-01 6.67648017e-02 -2.96641082e-01
1.18208297e-01 -3.53515781e-02 -1.38309014e+00 5.20397127e-01
8.21925402e-01 1.10499990e+00 6.09850176e-02 3.46121669e-01
-3.93797368e-01 6.84113503e-01 -6.09033287e-01 -9.44104612e-01
1.31080583e-01 -6.12088561e-01 -7.79839754e-01 2.67247975e-01
2.27038011e-01 2.97864169e-01 9.91246030e-02 8.12314987e-01
3.23589832e-01 -5.09241931e-02 7.28897035e-01 -1.32566667e+00
-7.75929868e-01 7.88622797e-01 -5.75526297e-01 -3.21301371e-01
6.43500090e-02 4.62509841e-02 1.62296057e+00 -9.74364638e-01
3.83211315e-01 1.06806910e+00 6.74808681e-01 6.95022941e-01
-1.21183109e+00 -4.91685688e-01 5.81692994e-01 -1.49327368e-01
-9.93139625e-01 -2.25689068e-01 1.12435329e+00 -4.54646885e-01
9.76181030e-01 4.11347419e-01 7.58987248e-01 1.45912170e+00
1.32310167e-01 1.28722823e+00 1.40847051e+00 -3.96679014e-01
2.89950103e-01 1.73533976e-01 3.79118532e-01 3.76888096e-01
5.57640612e-01 -4.92823958e-01 -7.21859396e-01 -1.66067600e-01
2.15315729e-01 4.21828358e-03 1.66536216e-02 -4.01367873e-01
-1.01519120e+00 1.02472007e+00 -6.77449210e-03 2.31898561e-01
-1.82685137e-01 9.89985391e-02 5.65032840e-01 1.11210369e-01
7.72970974e-01 5.29326022e-01 -7.08396912e-01 5.78783303e-02
-8.27019155e-01 4.81130004e-01 8.98334861e-01 1.32161129e+00
6.32069349e-01 3.73900771e-01 -5.23745358e-01 9.61129427e-01
5.51326692e-01 4.28387195e-01 6.51565135e-01 -2.37938747e-01
3.92767549e-01 8.74991357e-01 -1.95305914e-01 -9.70030189e-01
-3.86906266e-01 -9.13557291e-01 -6.45621836e-01 -1.00921996e-01
2.32845917e-01 -2.16731891e-01 -9.99840140e-01 1.80627525e+00
3.02836537e-01 -4.83832583e-02 1.65220276e-01 5.54525435e-01
6.30641401e-01 6.07668698e-01 3.04648519e-01 5.23578674e-02
1.65408087e+00 -1.40863073e+00 -7.27662981e-01 -6.65867627e-01
5.93034208e-01 -9.01217878e-01 1.48473775e+00 5.30418515e-01
-8.28688383e-01 -3.58400136e-01 -1.20286548e+00 -7.89301544e-02
-5.21713436e-01 4.75243926e-01 8.72609079e-01 8.40018094e-01
-8.71748865e-01 8.78338441e-02 -6.73359513e-01 -4.62646663e-01
4.21738029e-01 1.46865472e-01 1.91534329e-02 1.06392987e-01
-1.03916085e+00 5.15920341e-01 3.47733706e-01 2.35424995e-01
-9.01186943e-01 -6.04128420e-01 -9.55062151e-01 7.39139393e-02
6.50084853e-01 -1.29117453e+00 1.37600756e+00 -1.07340634e+00
-1.66364026e+00 8.64648461e-01 -3.12500596e-01 -5.39760351e-01
2.87756890e-01 -5.86962342e-01 -2.64131337e-01 -4.92998719e-01
1.74530502e-02 2.44757026e-01 1.07537568e+00 -1.51998210e+00
-5.29856622e-01 -4.67693031e-01 3.71857911e-01 1.78216517e-01
-7.69388258e-01 -5.73354736e-02 -3.80537003e-01 -1.13072479e+00
-2.32260466e-01 -1.10096312e+00 -3.10452402e-01 -5.75902343e-01
-8.08426917e-01 -4.83116329e-01 8.25501680e-01 -1.84259742e-01
1.41989756e+00 -1.78179514e+00 1.47047713e-01 -4.43740040e-02
1.27395436e-01 2.26970524e-01 -2.35883892e-01 4.62929219e-01
1.11718304e-01 1.60517439e-01 -3.58618706e-01 -8.92050385e-01
4.57603842e-01 9.06545147e-02 -6.30464494e-01 -1.51605541e-02
2.90653795e-01 1.02391136e+00 -7.72855520e-01 -3.24559122e-01
1.96754932e-03 4.45698440e-01 -6.80738091e-01 4.64224458e-01
-6.50322735e-01 2.68595010e-01 -8.49471688e-01 6.73065722e-01
4.85073000e-01 -4.29058343e-01 3.68774533e-01 -2.54672050e-01
1.69580922e-01 4.42382514e-01 -7.18347490e-01 1.95682836e+00
-8.94266665e-01 3.14314187e-01 -2.38792762e-01 -1.11626136e+00
1.02555943e+00 2.09146604e-01 3.19622546e-01 -3.71780097e-01
3.08884710e-01 1.47188693e-01 -5.16117178e-02 -2.84147441e-01
7.53249884e-01 -3.55592877e-01 -4.32111859e-01 6.61726773e-01
3.95999312e-01 -1.46867737e-01 3.66083264e-01 1.06768735e-01
7.47208238e-01 5.44288397e-01 4.56863284e-01 -3.88582051e-01
6.81426823e-01 1.36411339e-02 6.32967889e-01 7.66267836e-01
2.31737390e-01 6.96499288e-01 4.61536318e-01 -4.93659288e-01
-9.31191862e-01 -6.25765443e-01 1.33703975e-02 1.40679789e+00
-1.25279129e-01 -8.96846592e-01 -7.85648763e-01 -1.18698084e+00
-2.62787312e-01 9.81287539e-01 -8.68867695e-01 -1.65144905e-01
-4.26027298e-01 -1.35051882e+00 3.22923779e-01 5.91130495e-01
2.81477928e-01 -1.08589399e+00 -2.36309350e-01 7.42022991e-02
-4.09586318e-02 -1.34010673e+00 -3.76721740e-01 1.63685847e-02
-8.20885718e-01 -8.13639462e-01 -6.23725355e-01 -7.66741157e-01
4.34767902e-01 2.46364206e-01 1.41919470e+00 -3.20315361e-01
-3.68485823e-02 3.01587075e-01 -5.85984170e-01 -7.05097735e-01
-3.12123388e-01 6.91772521e-01 -3.41991633e-01 5.48892736e-01
5.06488264e-01 -7.61966109e-01 -5.95276415e-01 1.96657911e-01
-9.16318715e-01 3.48707795e-01 8.05641174e-01 7.52186000e-01
6.76572263e-01 -1.79394469e-01 8.43485117e-01 -1.52128208e+00
7.91221559e-01 -5.91433167e-01 -3.23250264e-01 3.61917764e-01
-9.20978785e-01 2.28149351e-02 9.26752627e-01 -1.17670037e-01
-1.24186468e+00 -9.59565565e-02 -1.41491368e-01 -4.40203436e-02
-3.30829591e-01 6.20192170e-01 -4.63384837e-01 3.70657325e-01
3.57099086e-01 6.03660345e-01 -4.04161096e-01 -5.50077617e-01
3.80562514e-01 5.18378079e-01 -5.39069772e-02 -7.74219692e-01
8.07822168e-01 4.11804020e-01 -7.51431426e-03 -5.16095161e-01
-1.45531201e+00 -2.98076004e-01 -2.76372701e-01 1.67553425e-02
8.39258015e-01 -1.02679169e+00 -3.97137731e-01 5.68818629e-01
-1.03831029e+00 -1.81156859e-01 -2.96789646e-01 1.28061064e-02
-5.62544584e-01 5.34681417e-02 -2.99891889e-01 -7.82280326e-01
-8.83788884e-01 -1.32694960e+00 1.33422244e+00 1.96557194e-01
-3.32772493e-01 -1.09103239e+00 2.30582759e-01 7.19372213e-01
5.54146826e-01 5.90767525e-02 1.00670207e+00 -1.05413580e+00
-4.38419849e-01 -2.30019346e-01 -6.51148483e-02 4.66530442e-01
2.97118217e-01 -1.29345834e-01 -1.28224182e+00 -1.74558148e-01
1.31380931e-01 -3.65021229e-01 8.63137484e-01 1.43116564e-01
1.26620936e+00 -3.34478527e-01 -1.90974802e-01 4.77787316e-01
1.28946090e+00 1.02504469e-01 3.05376172e-01 4.76307005e-01
9.65244055e-01 4.31182176e-01 6.82896316e-01 4.01878536e-01
5.91857016e-01 7.90001273e-01 3.59462827e-01 1.03158310e-01
-2.44291410e-01 -3.50949347e-01 5.38811743e-01 1.20499372e+00
-2.72047240e-02 -6.37063026e-01 -8.14821243e-01 7.17487574e-01
-2.04188776e+00 -6.36626840e-01 -1.88545451e-01 1.83986890e+00
1.00633097e+00 1.48817822e-01 1.01484291e-01 -1.68881249e-02
2.58431524e-01 6.10024631e-01 -3.26982856e-01 -4.81564403e-01
-4.45908830e-02 2.68307477e-01 -1.65891275e-01 1.00765340e-01
-1.32637489e+00 1.01914871e+00 5.71724653e+00 1.22241914e+00
-9.86430228e-01 3.03632557e-01 7.08603799e-01 -4.63426560e-02
-7.12773085e-01 1.33870885e-01 -9.98266578e-01 3.29172820e-01
7.11315691e-01 -1.92062184e-01 -2.71680672e-02 1.23553014e+00
-3.35547440e-02 3.59087855e-01 -1.07190800e+00 6.60756290e-01
3.21102381e-01 -1.08371878e+00 7.18119681e-01 -1.88226461e-01
9.68794644e-01 -3.45740408e-01 2.57830441e-01 5.81531346e-01
2.77593553e-01 -8.48541439e-01 7.61425197e-01 3.10489625e-01
4.74288255e-01 -6.10551834e-01 7.85351157e-01 4.71518375e-02
-1.18895674e+00 1.08058669e-01 -1.01258926e-01 2.10773796e-02
2.10537255e-01 7.10624456e-01 -5.85717857e-01 1.00485504e+00
3.97841960e-01 8.65878880e-01 -8.10834110e-01 7.20803082e-01
-4.28101987e-01 8.69434178e-01 8.32784027e-02 -1.65541410e-01
5.06211638e-01 -3.09839338e-01 5.60295165e-01 1.40737832e+00
2.59639472e-01 -6.08996153e-01 1.56394869e-01 9.10752714e-01
-2.51699895e-01 5.22980452e-01 -5.18806159e-01 -1.65045246e-01
3.36249247e-02 1.57882655e+00 -7.12947607e-01 -2.40469158e-01
-7.62552083e-01 7.38565862e-01 2.80777842e-01 2.67993897e-01
-8.52305830e-01 -3.11863869e-01 5.04983962e-01 -4.70537283e-02
3.59802037e-01 6.50025904e-02 -6.64221942e-01 -1.42762411e+00
1.70385018e-01 -1.13514054e+00 3.40078622e-01 -5.86582184e-01
-1.54797935e+00 9.61987734e-01 -1.11549072e-01 -1.22491014e+00
-3.61496925e-01 -7.12999403e-01 -7.56209970e-01 6.40744209e-01
-1.56056929e+00 -1.90517223e+00 -2.43345827e-01 4.93067265e-01
1.03831971e+00 -2.83701688e-01 7.78640211e-01 2.61205107e-01
-7.82282233e-01 6.31917000e-01 -2.17455208e-01 -5.01848608e-02
7.18525171e-01 -1.48686600e+00 4.76720303e-01 9.99051511e-01
3.22631389e-01 7.98491240e-01 6.48329794e-01 -4.67398822e-01
-1.46217418e+00 -1.31707084e+00 1.06020975e+00 -6.30506158e-01
8.19890380e-01 -8.15736055e-01 -5.91662705e-01 8.66309404e-01
5.89791834e-01 -2.78898686e-01 9.33353424e-01 5.96303403e-01
-4.91696447e-01 -2.92659461e-01 -5.62019587e-01 6.97122991e-01
1.06400537e+00 -4.06241149e-01 -4.94951814e-01 3.26602012e-01
8.55639875e-01 -1.68971598e-01 -5.36712110e-01 5.28966010e-01
5.13675153e-01 -7.99824297e-01 6.99916899e-01 -7.67830610e-01
7.06463099e-01 -2.95740515e-01 -1.80266812e-01 -1.27807128e+00
-2.21270490e-02 -6.70431733e-01 -2.31692135e-01 1.66108596e+00
6.66466951e-01 -5.55793941e-01 6.44136190e-01 5.20159543e-01
-3.49368602e-01 -1.13247299e+00 -4.77875531e-01 -6.30549490e-01
5.21414280e-02 -6.34546459e-01 6.91791952e-01 1.00490463e+00
-2.84633160e-01 8.98118973e-01 -6.44676566e-01 -1.56291425e-01
4.64678168e-01 6.93359196e-01 9.68945265e-01 -1.00323176e+00
-5.09762526e-01 -6.73493803e-01 -8.17699209e-02 -9.01974857e-01
2.54469275e-01 -1.04380345e+00 -7.83066303e-02 -1.39864433e+00
4.13754731e-01 -5.82460523e-01 -3.47382843e-01 6.11056983e-01
-4.53432947e-01 3.34967464e-01 2.36362681e-01 5.01919501e-02
-7.44210303e-01 9.79578972e-01 1.11916625e+00 -2.26469994e-01
-1.02811521e-02 2.31563225e-01 -1.20038414e+00 8.67003620e-01
8.37117612e-01 -5.37780523e-01 -8.53648603e-01 -6.41912341e-01
5.83117247e-01 -4.96172875e-01 1.59640133e-01 -7.46653199e-01
-1.18783467e-01 -9.62434709e-02 -8.76667053e-02 -2.84895062e-01
2.00933024e-01 -7.32031882e-01 7.13952957e-03 -3.80132571e-02
-3.98751467e-01 -5.30133992e-02 9.15570036e-02 7.31648982e-01
-4.58109081e-01 -2.49690354e-01 4.32046235e-01 8.73816162e-02
-4.38985229e-01 3.50495070e-01 -1.76083311e-01 2.22557455e-01
9.59944963e-01 2.24172592e-01 -1.66875258e-01 -2.58108199e-01
-6.33801222e-01 -5.98663539e-02 1.68796599e-01 6.20689154e-01
2.18548402e-01 -1.23943543e+00 -6.04575634e-01 1.36521861e-01
4.25714403e-01 1.89409494e-01 2.83984393e-01 7.60948122e-01
4.46693636e-02 5.37264347e-01 2.22406954e-01 -4.10338134e-01
-9.33052659e-01 5.82167745e-01 6.21368624e-02 -9.21207964e-01
-4.42138076e-01 7.02537477e-01 6.68735266e-01 -4.71915156e-01
-1.07479699e-01 -1.03911407e-01 -3.29324514e-01 1.49243936e-01
2.68396884e-01 1.76324528e-02 2.03067347e-01 -5.29629529e-01
-7.78642520e-02 4.90467817e-01 -4.83123511e-01 5.83311319e-02
1.40606201e+00 -1.56120062e-01 1.76479146e-02 5.93510687e-01
8.92536342e-01 7.07916319e-02 -9.47151184e-01 -3.64641279e-01
3.26613933e-02 -1.88770294e-01 7.56347645e-03 -9.50314581e-01
-1.31091845e+00 1.06400311e+00 -5.41353114e-02 3.61176133e-01
1.17506409e+00 -3.22416276e-02 9.05456007e-01 2.07911715e-01
3.65231633e-01 -8.09530616e-01 1.25660405e-01 4.35751706e-01
9.32699382e-01 -1.08376741e+00 -1.09779902e-01 -4.53025907e-01
-9.44714606e-01 9.74821806e-01 7.32278764e-01 -7.61576965e-02
4.42772955e-01 1.38866752e-01 -2.29600389e-02 -2.49997318e-01
-8.71583045e-01 -1.38211623e-01 4.86336708e-01 3.20148438e-01
7.46688128e-01 -1.78095023e-03 -6.44209325e-01 1.50829458e+00
-2.88035661e-01 -1.37831330e-01 2.73278743e-01 1.00965643e+00
3.36762555e-02 -1.48897731e+00 1.95529997e-01 3.82603735e-01
-6.23307288e-01 -2.77449101e-01 -4.30906385e-01 8.80429327e-01
-1.13814190e-01 7.61409163e-01 -3.56853276e-01 -3.67186934e-01
3.00974935e-01 4.69383836e-01 2.44769812e-01 -7.69259870e-01
-8.11987102e-01 2.44303659e-01 2.16795310e-01 -4.54189301e-01
-7.06025839e-01 -6.62764609e-01 -7.38399863e-01 1.21188529e-01
-3.04924637e-01 1.16860099e-01 5.27730942e-01 9.96342123e-01
6.51672184e-01 6.93501472e-01 6.30938113e-01 -3.94789010e-01
-3.51291478e-01 -1.11639154e+00 -4.07769114e-01 4.98105496e-01
-6.08099140e-02 -5.82396567e-01 -7.76492432e-02 1.89827248e-01] | [11.441903114318848, 6.62898063659668] |
c6d53f92-c3c9-401a-b284-e8d9d0b669d5 | polcovid-a-multicenter-multiclass-chest-x-ray | 2211.16359 | null | https://arxiv.org/abs/2211.16359v3 | https://arxiv.org/pdf/2211.16359v3.pdf | POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021) | The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and required medical assistance. With chest radiographs (CXR) being one of the most common COVID-19 diagnosis methods, many artificial intelligence tools for image-based COVID-19 detection have been developed, often trained on a small number of images from COVID-19-positive patients. Thus, the need for high-quality and well-annotated CXR image databases increased. This paper introduces POLCOVID dataset, containing chest X-ray (CXR) images of patients with COVID-19 or other-type pneumonia, and healthy individuals gathered from 15 Polish hospitals. The original radiographs are accompanied by the preprocessed images limited to the lung area and the corresponding lung masks obtained with the segmentation model. Moreover, the manually created lung masks are provided for a part of POLCOVID dataset and the other four publicly available CXR image collections. POLCOVID dataset can help in pneumonia or COVID-19 diagnosis, while the set of matched images and lung masks may serve for the development of lung segmentation solutions. | ['Damian Piotrowski', 'POLCOVID Study Group', 'Joanna Polanska', 'Andrzej Cieszanowski', 'Michal Marczyk', 'Edyta Szurowska', 'Barbara Gizycka', 'Gabriela Zapolska', 'Krzysztof Simon', 'Robert Flisiak', 'Malgorzata Pawlowska', 'Piotr Fiedor', 'Mateusz Nowak', 'Grzegorz Przybylski', 'Tadeusz Popiela', 'Jerzy Walecki', 'Magdalena Sliwinska', 'Katarzyna Gruszczynska', 'Pawel Foszner', 'Marek Socha', 'Wojciech Prazuch', 'Joanna Tobiasz', 'Aleksandra Suwalska'] | 2022-11-29 | null | null | null | null | ['covid-19-detection'] | ['medical'] | [ 3.20110977e-01 -3.48448634e-01 1.03625216e-01 -4.22196873e-02
-7.00229049e-01 -5.77571869e-01 3.87597352e-01 6.32343948e-01
-8.12374651e-01 5.18641710e-01 -8.28549713e-02 -4.73943293e-01
-4.75502759e-01 -5.93260348e-01 -9.50051621e-02 -7.31977999e-01
9.65343118e-02 1.34467125e+00 4.60055411e-01 4.45239544e-01
-2.01267362e-01 8.43283713e-01 -9.36917782e-01 2.55612135e-01
5.37061036e-01 6.10246003e-01 1.04017639e+00 1.26865017e+00
1.65085718e-01 5.18639982e-01 -4.29380000e-01 -1.23426355e-01
1.78656563e-01 -5.76332510e-01 -5.39545774e-01 -1.25824466e-01
1.51097439e-02 -5.36082685e-01 -4.24895845e-02 3.94457161e-01
4.02576536e-01 -2.12923408e-01 9.56288159e-01 -7.80320525e-01
-5.76730818e-02 -1.07733190e-01 -2.99102157e-01 7.36286044e-01
-1.79692376e-02 5.48601627e-01 5.99879146e-01 -6.35210216e-01
9.87770736e-01 6.64276958e-01 6.55045450e-01 5.39347827e-01
-6.64279819e-01 -2.71333665e-01 -7.15149045e-01 3.77841473e-01
-1.11088777e+00 2.73949474e-01 3.37769538e-02 -1.10728407e+00
1.04970384e+00 6.30663872e-01 9.91875768e-01 8.18197370e-01
2.81956512e-02 2.05134898e-01 1.12777197e+00 -2.49095373e-02
-5.07199147e-04 1.27677649e-01 1.06309712e-01 5.42146504e-01
7.48062253e-01 -1.43142402e-01 4.72390682e-01 -4.83280212e-01
9.35896337e-01 6.08256638e-01 -4.47180599e-01 -1.51640579e-01
-1.47605228e+00 8.13406467e-01 2.34233409e-01 7.85032630e-01
-7.05857754e-01 -4.80561078e-01 3.95675182e-01 -2.57662296e-01
8.40593874e-02 4.42592472e-01 -5.08582592e-01 2.57656723e-01
-1.02618778e+00 3.40573303e-02 1.10355832e-01 3.18955660e-01
2.71239012e-01 -3.88649642e-01 -3.61468732e-01 7.95068502e-01
1.40869245e-01 1.09786117e+00 4.99084920e-01 -3.53064120e-01
5.16027927e-01 6.96895897e-01 3.26933414e-02 -8.56863737e-01
-7.03551352e-01 4.76149796e-03 -9.84611273e-01 -5.06594598e-01
5.79131186e-01 -1.24653943e-01 -1.03489995e+00 1.08478808e+00
3.27165753e-01 -3.97452079e-02 2.77686976e-02 8.65196109e-01
5.12744069e-01 6.94640160e-01 -1.04286999e-01 -3.68287355e-01
1.73171735e+00 -6.65566683e-01 -3.60031515e-01 1.31706856e-02
5.19465446e-01 -5.79171002e-01 8.03863943e-01 1.47338226e-01
-7.10507452e-01 -2.87237018e-01 -5.41386127e-01 4.10520762e-01
-3.85217577e-01 2.79909045e-01 -6.22324944e-02 5.10457397e-01
-7.25534499e-01 1.84422508e-01 -8.52226019e-01 -8.29128563e-01
4.09200907e-01 2.33486950e-01 -4.45054650e-01 -2.19108358e-01
-7.59788513e-01 1.06384504e+00 3.85290891e-01 -1.69815198e-02
-7.92782664e-01 -4.89147782e-01 -3.37246805e-01 -2.27385178e-01
4.56256926e-01 -9.20958579e-01 7.51956940e-01 -1.22179933e-01
-5.32497585e-01 1.30622828e+00 1.78972170e-01 -4.61545199e-01
7.65449941e-01 9.93622541e-02 -2.44667768e-01 8.95162880e-01
9.87260863e-02 3.11126977e-01 8.59394848e-01 -1.10574615e+00
-6.10106170e-01 -6.05936587e-01 -6.07919276e-01 -2.53199369e-01
1.68893859e-01 4.30421710e-01 -3.55245292e-01 -8.22417736e-01
-4.03068036e-01 -9.29846406e-01 -3.67838830e-01 -4.56033409e-01
-4.31196570e-01 -2.17767004e-02 9.02056992e-01 -1.20096254e+00
8.91004503e-01 -1.95811176e+00 -2.21441105e-01 2.57335722e-01
4.72847968e-01 7.10898697e-01 -5.83212562e-02 2.53164649e-01
-2.12655328e-02 2.97972143e-01 -7.95046568e-01 1.52716592e-01
-3.46456617e-01 2.67555863e-01 7.31207803e-02 6.25124991e-01
3.26755583e-01 6.26393974e-01 -8.05767596e-01 -1.02395642e+00
6.56750679e-01 5.36570489e-01 -3.26075286e-01 7.69974291e-01
-2.83780813e-01 1.04345262e+00 -4.76151675e-01 4.56573099e-01
5.13891637e-01 -4.61923212e-01 1.15304723e-01 1.56314954e-01
1.01635516e-01 -3.46229285e-01 -6.33084536e-01 6.63230002e-01
-2.14191437e-01 2.95346141e-01 1.76847085e-01 -6.91006660e-01
5.81161916e-01 8.26994598e-01 8.34174991e-01 -2.83043951e-01
3.11955810e-01 1.93726331e-01 1.92641094e-02 -1.03840661e+00
8.95550847e-02 -1.85333669e-01 4.77443248e-01 6.33279681e-01
-4.90750283e-01 -5.48630357e-01 5.50671220e-01 -8.60742852e-02
1.03455615e+00 -5.83427370e-01 5.35594940e-01 4.35056016e-02
8.74248981e-01 5.16510248e-01 1.42793998e-01 6.36204302e-01
-1.73232004e-01 1.00951362e+00 1.03630103e-01 -4.34930831e-01
-1.38268065e+00 -9.70716000e-01 -5.67558348e-01 3.39991212e-01
-5.06872714e-01 2.28546128e-01 -1.00773871e+00 -4.85311866e-01
-3.16046864e-01 3.99808139e-01 -5.22217691e-01 6.13013804e-01
-9.16894555e-01 -9.06726718e-01 5.11106372e-01 2.41809487e-01
2.96515405e-01 -1.31674492e+00 -1.14428496e+00 1.91561714e-01
-3.53204787e-01 -1.04141295e+00 -2.20157698e-01 -3.92607264e-02
-8.22730124e-01 -1.78830886e+00 -1.45341909e+00 -5.58313251e-01
7.33511925e-01 5.75707890e-02 8.53828609e-01 5.21654963e-01
-1.00755882e+00 3.88622999e-01 -3.77052039e-01 -3.71490180e-01
-8.15626264e-01 -8.72599036e-02 -1.13023542e-01 -1.80457622e-01
9.35479850e-02 -2.07750220e-02 -6.75797522e-01 2.44865611e-01
-1.02176023e+00 -1.72410570e-02 5.41239202e-01 5.37342668e-01
9.57021952e-01 -1.53917283e-01 2.97063947e-01 -8.11261594e-01
4.62057859e-01 -6.20984972e-01 -5.79615295e-01 3.73069882e-01
-3.74317676e-01 -6.16969585e-01 8.01868498e-01 -5.37472852e-02
-9.12797213e-01 -1.53734460e-01 -2.30672300e-01 -4.96433914e-01
-6.40626013e-01 5.65094836e-02 4.84137774e-01 5.92858136e-01
4.12615597e-01 1.77394897e-01 -3.19553949e-02 -6.15893722e-01
-7.34718516e-02 8.72147202e-01 7.20584810e-01 7.69416988e-02
7.59350896e-01 5.90299547e-01 4.05548960e-02 -1.17471576e+00
-4.74476129e-01 -1.02009404e+00 -8.21740091e-01 -1.22622088e-01
1.76680899e+00 -4.79702592e-01 -1.69880882e-01 4.92135614e-01
-1.07536793e+00 -2.77464598e-01 -3.87197882e-01 7.57456362e-01
-4.28826302e-01 2.77657181e-01 -6.27692759e-01 -6.76973164e-01
-5.99302709e-01 -1.33949685e+00 8.36570501e-01 -5.80576286e-02
-2.04863340e-01 -8.82064700e-01 7.34152377e-01 7.63612390e-01
3.16879749e-01 2.35139862e-01 1.32449615e+00 -1.15670228e+00
-4.59653407e-01 -4.68907893e-01 -3.86742294e-01 4.61827606e-01
2.45255426e-01 1.75357491e-01 -6.80368841e-01 -2.46753797e-01
4.39281195e-01 9.31763276e-03 8.76201034e-01 4.51959401e-01
7.98989773e-01 -1.71018794e-01 -4.67404336e-01 3.54743451e-01
1.50965023e+00 6.74172938e-01 1.14537612e-01 1.73637215e-02
7.05799341e-01 6.06236458e-01 3.46885473e-01 4.90789175e-01
4.90880758e-02 4.53708321e-01 3.62824649e-01 -3.01141411e-01
4.55095172e-02 4.19025809e-01 -2.97852844e-01 8.23695421e-01
-5.57675660e-01 -4.31263566e-01 -1.34554708e+00 7.16699243e-01
-1.13647020e+00 -8.07355821e-01 -7.07710147e-01 1.92281711e+00
4.53444809e-01 -4.16131288e-01 3.94404441e-01 3.81759219e-02
9.12344217e-01 6.75651580e-02 -2.80546725e-01 -1.60927206e-01
-1.20797336e-01 3.89973551e-01 1.88332528e-01 2.50870079e-01
-1.03259027e+00 8.70759264e-02 6.31056118e+00 3.58010262e-01
-9.84275579e-01 3.66368890e-01 4.87560600e-01 1.34384915e-01
9.94780511e-02 -4.92525369e-01 -4.13942993e-01 4.25792634e-01
7.09818006e-01 1.87062383e-01 1.59496114e-01 6.66266084e-01
3.34192783e-01 -3.33529443e-01 -6.87693655e-01 9.21421051e-01
6.96381181e-02 -1.33288109e+00 -2.90553309e-02 1.98355764e-02
5.67874432e-01 3.35414559e-01 -1.60257861e-01 -3.59833658e-01
-2.58395880e-01 -7.88084507e-01 1.67020053e-01 4.46334183e-01
1.13746798e+00 -4.15344775e-01 1.26506686e+00 3.09969395e-01
-1.20351803e+00 1.38249233e-01 -3.38558465e-01 6.23603582e-01
3.19626749e-01 4.63777065e-01 -1.52315342e+00 3.62281352e-01
6.73213363e-01 1.27775460e-01 -7.35260785e-01 9.57644343e-01
-7.16655776e-02 7.64608324e-01 -4.08456266e-01 -5.99086396e-02
1.39247507e-01 -4.78723794e-01 6.28177345e-01 1.49307775e+00
2.45008498e-01 3.70942712e-01 -1.78204134e-01 7.04763949e-01
2.40931109e-01 3.19754899e-01 -7.07214892e-01 -2.41797760e-01
5.75546101e-02 1.34323466e+00 -1.29416358e+00 -7.57076383e-01
-2.86155730e-01 7.23370433e-01 -3.68013918e-01 5.14585301e-02
-6.89388216e-01 8.86104554e-02 2.53393620e-01 6.02007329e-01
3.32252979e-01 1.65357009e-01 1.63021591e-02 -8.26493621e-01
-3.62924457e-01 -7.08812535e-01 5.91069341e-01 -7.55578876e-01
-1.14122510e+00 8.97608221e-01 3.48141223e-01 -6.22681677e-01
-4.19794887e-01 -5.87039113e-01 -6.54196143e-01 7.11130321e-01
-1.03801811e+00 -7.07732439e-01 -3.82252812e-01 5.71857512e-01
4.34527338e-01 -9.75817516e-02 9.46471632e-01 2.73161560e-01
-6.53928995e-01 -2.91625351e-01 3.16393942e-01 1.68338582e-01
1.66604966e-01 -1.03647339e+00 1.54621571e-01 6.37754500e-01
-3.11056674e-01 4.02849287e-01 3.00662935e-01 -8.62638235e-01
-6.23051763e-01 -1.20743883e+00 9.27754164e-01 -5.71709931e-01
2.67679304e-01 6.70114532e-02 -8.75118077e-01 5.55353403e-01
1.32709935e-01 -1.58246994e-01 5.31063259e-01 -1.32238865e+00
1.81813464e-01 4.37063873e-01 -1.45855093e+00 1.98514774e-01
5.35811126e-01 -3.73444617e-01 -9.58047152e-01 6.74432635e-01
3.86833310e-01 3.34114730e-02 -8.39213729e-01 4.59383428e-01
1.86020613e-01 -1.07024086e+00 1.17672372e+00 -3.76552343e-01
5.48379347e-02 -1.58113316e-01 1.60225872e-02 -7.32460082e-01
2.31778454e-02 -5.42314257e-03 5.85385621e-01 6.22545302e-01
3.79003845e-02 -6.69373810e-01 6.03606522e-01 5.78626171e-02
2.42765233e-01 -6.37358725e-01 -7.66327143e-01 -5.29379785e-01
-2.28293270e-01 -3.09878021e-01 4.35807437e-01 7.38517106e-01
-6.83320522e-01 -1.56714559e-01 2.30685577e-01 -1.83374882e-02
4.25969809e-01 8.98874849e-02 4.85516310e-01 -1.23112833e+00
-4.44313794e-01 -4.17960137e-01 1.90026015e-02 -1.60383806e-01
-5.07726073e-01 -8.33731055e-01 -1.23481676e-01 -2.00400758e+00
6.22893810e-01 -5.39323926e-01 3.17529738e-02 2.73255467e-01
-2.28400469e-01 5.60341537e-01 3.05748045e-01 6.61846220e-01
7.01331794e-02 -2.93008655e-01 1.35395145e+00 9.26991105e-02
-1.30523682e-01 1.30918011e-01 3.88363332e-01 9.45244908e-01
9.44035292e-01 -7.96369910e-01 -2.91420043e-01 8.95624012e-02
3.98047380e-02 3.22091639e-01 4.37637061e-01 -9.24147904e-01
-3.79728675e-01 -3.58994633e-01 3.57854456e-01 -1.25300515e+00
1.69146329e-01 -1.03375483e+00 5.78783929e-01 1.26179242e+00
1.55025288e-01 3.91720146e-01 -9.74483974e-03 4.09883738e-01
1.27497930e-02 -3.99439871e-01 1.15161490e+00 -4.51899439e-01
-5.08779176e-02 4.04824913e-01 -9.79190886e-01 3.97833675e-01
1.32360375e+00 -2.29614675e-01 -1.49603501e-01 2.22066671e-01
-5.66294670e-01 -2.68775582e-01 5.97177267e-01 -1.03706129e-01
6.38901770e-01 -4.99857098e-01 -9.50378180e-01 2.83720434e-01
3.58476751e-02 4.24758285e-01 3.84795606e-01 1.36205208e+00
-1.43333602e+00 8.87504697e-01 -2.65925318e-01 -8.71086776e-01
-1.53871620e+00 1.02179575e+00 3.15061331e-01 -6.98714435e-01
-7.13912189e-01 5.42547524e-01 4.25420523e-01 -1.01682581e-01
-1.01067670e-01 -4.80613321e-01 -3.65887135e-01 1.48450822e-01
4.81772393e-01 5.01914322e-01 4.60582301e-02 -9.43784833e-01
-5.92622817e-01 8.75408053e-01 2.87774414e-01 -4.36185561e-02
1.33187985e+00 1.28672376e-01 -2.83699870e-01 6.02168217e-02
1.00333810e+00 2.00569946e-02 -6.39492035e-01 1.54734015e-01
-1.29851386e-01 -2.49106005e-01 -4.16362762e-01 -6.57010853e-01
-9.11816239e-01 9.10781980e-01 7.81759322e-01 2.05404162e-01
1.04480934e+00 4.04083639e-01 7.70326674e-01 2.44309157e-01
3.85263003e-02 -5.30709684e-01 4.51002233e-02 1.01093821e-01
7.43681669e-01 -1.00096786e+00 -1.03632219e-01 -2.72269368e-01
-5.78785419e-01 8.84073138e-01 6.54974133e-02 4.99837957e-02
3.51901293e-01 2.63329953e-01 2.28161559e-01 -5.05235255e-01
-3.03466022e-01 -1.90266877e-01 7.71647766e-02 9.63240921e-01
3.14627774e-02 3.51880282e-01 -3.39834988e-01 5.25387228e-01
3.46374251e-02 -1.24332331e-01 2.32758284e-01 6.93822026e-01
-4.11788911e-01 -9.69847977e-01 -9.00339603e-01 1.01920867e+00
-7.95351446e-01 -2.72310108e-01 -5.31723320e-01 1.11728299e+00
5.05722165e-01 6.33170307e-01 1.76071391e-01 1.53870463e-01
2.69550443e-01 2.85322499e-02 5.04898131e-01 -6.21774077e-01
-9.09979045e-01 6.07241616e-02 -1.35778800e-01 -5.49584404e-02
-4.97412831e-01 -6.96639240e-01 -1.55651593e+00 6.54021744e-03
-3.37227553e-01 1.07602589e-01 6.20326281e-01 8.50989282e-01
-4.73632775e-02 3.69319946e-01 3.70151788e-01 -4.40454066e-01
-2.34374359e-01 -9.98501360e-01 -6.90585375e-01 5.43344140e-01
4.53320771e-01 -1.54541433e-01 -4.60360587e-01 3.40611011e-01] | [15.488753318786621, -1.7832316160202026] |
d0ca7226-5a38-4598-967d-4bc483b697d2 | retroprime-a-diverse-plausible-and | null | null | https://www.sciencedirect.com/science/article/pii/S1385894721014303?via%3Dihub | https://reader.elsevier.com/reader/sd/pii/S1385894721014303?token=421B055EB4B5E4561A9153E3E126DF84836F5355C84111D07A19462C5226B2124333B7E075E50F93E7519F751ED5ADEA&originRegion=eu-west-1&originCreation=20220211095011 | RetroPrime: A Diverse, plausible and Transformer-based method for Single-Step retrosynthesis predictions | Retrosynthesis prediction is a crucial task for organic synthesis. In this work, we propose a single-step template-free and Transformer-based method dubbed RetroPrime, integrating chemists’ retrosynthetic strategy of (1) decomposing a molecule into synthons then (2) generating reactants by attaching leaving groups. These two stages are accomplished with versatile Transformer models, respectively. RetroPrime achieves the Top-1 accuracy of 64.8% and 51.4%, when the reaction type is known and unknown, respectively, in the USPTO-50 K dataset. And the Top-1 accuracy is close to the state-of-the-art transformer-based method in the large dataset USPTO-full. It is known that outputs of the Transformer-based retrosynthesis model tend to suffer from insufficient diversity and high chemical implausibility. These problems may limit the potential of Transformer-based methods in real practice, yet few works address both issues simultaneously. RetroPrime is designed to tackle these challenges. | ['Xiaojun Yaoa', 'Chang-Yu Hsieh', 'Benben Liao', 'Huanxiang Liu', 'Guangyong Chen', 'Jiezhong Qiu', 'Yuquan Li', 'Xiaorui Wang'] | 2021-09-15 | null | null | null | chemical-engineering-journal-2021-9 | ['retrosynthesis'] | ['medical'] | [ 3.60002935e-01 -2.25164443e-01 -3.62511307e-01 1.42579392e-01
-4.90309507e-01 -1.19307709e+00 7.76802659e-01 3.68348777e-01
-1.47637561e-01 1.15266514e+00 -9.65445191e-02 -4.51692134e-01
2.60235995e-01 -6.75062180e-01 -5.93419313e-01 -1.01092279e+00
1.47407383e-01 3.99009854e-01 3.73260677e-01 -3.06405038e-01
6.06157124e-01 5.26284397e-01 -1.53506911e+00 2.91370362e-01
1.06404877e+00 9.69752431e-01 2.63842106e-01 2.91626424e-01
-1.92058757e-01 7.18720376e-01 -3.33305389e-01 -4.70728666e-01
4.19035852e-01 -4.39888775e-01 -5.34206390e-01 -5.44862151e-01
1.31249309e-01 1.67489558e-01 1.45075768e-01 8.90242517e-01
6.59800112e-01 5.53160049e-02 1.00425124e+00 -9.97292101e-01
-3.38107318e-01 8.60362589e-01 -8.48266408e-02 -2.92858064e-01
3.05228233e-01 -4.39628810e-02 9.35193777e-01 -1.28123438e+00
6.05540931e-01 1.04233265e+00 6.46771908e-01 3.51301372e-01
-1.13925409e+00 -1.17478073e+00 4.90050614e-02 -7.59361684e-02
-1.41329288e+00 -5.05699873e-01 3.88169795e-01 -7.53537834e-01
1.03636622e+00 2.20042184e-01 6.93183362e-01 1.16318059e+00
7.02736735e-01 3.14078987e-01 1.11918414e+00 6.87570274e-02
5.65452218e-01 7.00262636e-02 -2.74215072e-01 5.54298520e-01
1.77742332e-01 2.81985343e-01 -6.47152126e-01 -1.81011587e-01
2.84040093e-01 1.31007165e-01 -5.76367900e-02 -2.06281364e-01
-1.44763446e+00 6.96838260e-01 4.85274494e-01 2.37662122e-01
-2.79589087e-01 -2.44092092e-01 5.62954485e-01 2.83718705e-02
2.85531282e-01 1.13553965e+00 -6.73948288e-01 2.38903865e-01
-1.12816560e+00 3.01358819e-01 7.89921463e-01 1.28520000e+00
4.24225628e-01 2.33053993e-02 1.02094367e-01 4.97043967e-01
1.43591747e-01 4.45087478e-02 4.35310215e-01 -3.97237897e-01
3.47016692e-01 4.15168136e-01 2.10038662e-01 -6.44640565e-01
-6.81688070e-01 -2.47873485e-01 -7.75651395e-01 -3.08981091e-01
6.27688766e-01 1.18624672e-01 -1.07047951e+00 1.46443617e+00
6.03135705e-01 -1.60713628e-01 1.95467055e-01 5.10698438e-01
9.96982872e-01 1.11451042e+00 4.69619095e-01 -7.56289124e-01
1.26204026e+00 -1.19467092e+00 -6.00442708e-01 2.62038350e-01
4.68492210e-01 -1.25043166e+00 4.27815199e-01 1.03468823e+00
-8.99960876e-01 -4.55538869e-01 -1.28868282e+00 -1.43630162e-01
-1.01351881e+00 1.26053393e-01 7.57874548e-01 8.86412621e-01
-4.66082901e-01 1.02199280e+00 -4.09492046e-01 -1.79784641e-01
5.16589731e-03 5.56201816e-01 -4.27251548e-01 1.47068575e-01
-1.16595638e+00 8.93488586e-01 8.89507771e-01 1.61722720e-01
-1.53051877e+00 -1.00790632e+00 -4.15797472e-01 -1.12863004e-01
8.87708664e-01 -5.22277594e-01 1.11567414e+00 -3.75139385e-01
-1.82369685e+00 4.22000706e-01 1.77555248e-01 -9.22713056e-02
4.99492705e-01 5.39740063e-02 -3.71338725e-01 -1.92480385e-01
1.61917761e-01 5.52021146e-01 7.02174008e-01 -1.07544279e+00
-5.10006607e-01 -2.72349149e-01 -1.55373916e-01 -8.25515464e-02
4.85035852e-02 -9.64779928e-02 -5.23136482e-02 -7.87505865e-01
3.13662291e-01 -1.01187563e+00 -5.19279361e-01 -2.16125384e-01
-8.25028121e-01 -1.94328487e-01 2.08197743e-01 -4.15075779e-01
1.27943766e+00 -1.50425422e+00 3.42520177e-01 1.64278060e-01
3.04268692e-02 4.62168485e-01 -1.22320710e-03 1.05940568e+00
-5.59522808e-01 4.87751633e-01 -1.65325761e-01 3.05923402e-01
-1.36719704e-01 -3.49559069e-01 -5.01039147e-01 3.27669650e-01
2.68850196e-02 2.47397751e-01 -1.34482586e+00 -3.10071766e-01
1.91235021e-01 2.17110232e-01 -5.93313396e-01 -2.25555301e-02
-6.50113285e-01 4.85511452e-01 -6.01695240e-01 1.20217144e+00
6.50066912e-01 8.97604823e-02 7.35475659e-01 -5.92490256e-01
-9.43617165e-01 5.60872614e-01 -9.20946777e-01 1.78737605e+00
-4.91270870e-02 -2.51875311e-01 -4.50258344e-01 -6.64008677e-01
1.04174590e+00 6.21097565e-01 4.20802623e-01 -5.35402596e-01
1.45901829e-01 6.46556199e-01 9.19528753e-02 -9.22894925e-02
6.06390715e-01 -6.06169820e-01 -2.67103175e-03 -1.34958953e-01
1.54401675e-01 -1.38747618e-01 5.69643795e-01 1.02690645e-01
6.73274279e-01 6.20896995e-01 8.57402682e-01 -6.80728376e-01
8.37722003e-01 1.24327920e-01 8.21858823e-01 4.30248857e-01
2.92702727e-02 2.52848566e-01 4.64372218e-01 -5.91158986e-01
-1.26803744e+00 -7.83176184e-01 -2.59926300e-02 1.06343019e+00
-1.48325041e-01 -1.13892496e+00 -4.83521610e-01 -6.51234210e-01
-2.06483811e-01 6.24347568e-01 -4.46430266e-01 -6.21978901e-02
-2.74128467e-01 -7.63550401e-01 5.61510623e-01 1.70638859e-01
3.29051256e-01 -4.58665460e-01 1.89201921e-01 7.11985290e-01
-7.92972464e-03 -7.53218710e-01 -4.87662882e-01 5.08779049e-01
-6.43651545e-01 -1.31899393e+00 -5.68994701e-01 -4.10997897e-01
1.31418869e-01 3.60823482e-01 6.48424089e-01 -3.24965596e-01
-9.49853659e-02 -6.57764852e-01 -3.08093488e-01 -5.04629612e-01
-7.23209202e-01 3.02872628e-01 1.25896260e-01 -2.63003916e-01
-2.03423813e-01 -7.82479823e-01 -8.70547295e-01 5.56847572e-01
-6.66848660e-01 1.29818976e-01 5.65310121e-01 7.16629326e-01
8.24447989e-01 -5.76440133e-02 6.06098831e-01 -7.67498851e-01
9.58665162e-02 -7.14401841e-01 -1.00574756e+00 5.31508863e-01
-9.90809441e-01 3.03390801e-01 1.20334482e+00 -5.37496269e-01
-7.88819611e-01 5.49822152e-01 -1.46263048e-01 -1.21008806e-01
4.36011612e-01 4.95512903e-01 -4.60584909e-01 -3.32967797e-03
6.37238622e-01 4.05644357e-01 -4.11956787e-01 -5.92014134e-01
2.26758704e-01 4.24715906e-01 1.62244827e-01 -8.89120638e-01
6.34980261e-01 6.59196125e-03 5.68614960e-01 -6.75134003e-01
-8.49588037e-01 -5.47369003e-01 -5.07160366e-01 5.47193512e-02
8.36390436e-01 -1.06020021e+00 -1.09609461e+00 2.84723759e-01
-8.97609651e-01 -2.83676945e-02 3.72560054e-01 2.14269906e-01
-5.45501590e-01 4.93543059e-01 -3.96139055e-01 -6.16021633e-01
-6.74631238e-01 -1.62783253e+00 7.98645794e-01 -1.77030370e-01
-1.31303063e-02 -5.10556877e-01 1.53435230e-01 3.38582128e-01
-1.77946407e-02 4.73521292e-01 1.02752674e+00 -9.36488450e-01
-6.94602847e-01 1.56297714e-01 1.17740840e-01 -1.39865763e-02
4.34757441e-01 5.00563979e-01 -1.00107646e+00 -9.18295383e-02
-4.15346146e-01 -2.02541113e-01 7.73921430e-01 -1.02443621e-01
1.06895816e+00 -2.93154329e-01 -5.41761100e-01 4.63574857e-01
1.40073287e+00 6.88027263e-01 6.34850442e-01 3.29517990e-01
6.98676169e-01 5.08059800e-01 1.03042066e+00 5.78015804e-01
-1.06141986e-02 6.28319263e-01 5.25295198e-01 3.75717431e-01
3.19378942e-01 -8.70939851e-01 3.56580883e-01 5.77929914e-01
-3.43847245e-01 -5.31669974e-01 -8.91176462e-01 1.07354507e-01
-1.65535784e+00 -1.05170870e+00 -3.71107191e-01 2.35730815e+00
1.16162574e+00 -1.17148571e-01 4.09508914e-01 3.68924856e-01
5.16537905e-01 5.28895222e-02 -4.86618757e-01 -3.27727556e-01
1.68796003e-01 2.87447721e-01 7.50531375e-01 2.11847007e-01
-1.02677310e+00 1.39345276e+00 6.87822866e+00 1.24341798e+00
-1.24916875e+00 -2.50662506e-01 3.53073597e-01 1.64019555e-01
-1.30089536e-01 5.09590507e-01 -1.07849288e+00 6.96569204e-01
1.09386122e+00 -1.97276503e-01 3.55601221e-01 7.83579350e-01
2.23956794e-01 1.44269662e-02 -1.38432968e+00 7.33245134e-01
-3.58404070e-01 -1.68760061e+00 3.82656991e-01 6.01645783e-02
6.02607369e-01 -4.16515648e-01 -1.68670848e-01 1.85353488e-01
-1.95428077e-02 -9.50834513e-01 1.13307559e+00 1.65898636e-01
7.18494058e-01 -8.57668281e-01 1.89760670e-01 2.98440158e-01
-1.46564960e+00 2.04665177e-02 -2.68526107e-01 3.00170273e-01
-1.40016407e-01 5.36720872e-01 -1.24109209e+00 1.00769520e+00
2.49215603e-01 8.78721178e-01 -2.30687886e-01 7.86934674e-01
-3.38314503e-01 3.39197576e-01 -2.73898154e-01 -2.75004506e-01
3.39497060e-01 -6.82024777e-01 2.39234924e-01 1.08665943e+00
4.42781359e-01 1.97028384e-01 3.28368545e-01 6.59618616e-01
-1.25515044e-01 3.21099311e-01 -5.29054761e-01 -5.18041492e-01
6.53604805e-01 1.14615548e+00 -8.78716111e-01 -5.08796275e-01
-6.57725483e-02 5.90277195e-01 -1.61234379e-01 5.28806672e-02
-9.05693650e-01 -1.48947701e-01 5.20988226e-01 7.44921267e-02
4.37733233e-01 -1.65083021e-01 1.86367631e-01 -9.87462521e-01
-4.47505504e-01 -1.17763042e+00 4.71272588e-01 -5.87860167e-01
-9.56037879e-01 1.74314290e-01 -2.02235684e-01 -1.33583701e+00
3.35550994e-01 -9.79567468e-01 -3.01564217e-01 3.90519023e-01
-1.46394706e+00 -1.05636704e+00 1.54943973e-01 2.43039966e-01
8.36042047e-01 -3.47127467e-02 8.19836140e-01 2.93341726e-01
-8.25692952e-01 3.85642827e-01 3.60269874e-01 -6.91045821e-01
1.18987167e+00 -1.11830127e+00 6.46958649e-02 5.38278103e-01
-4.92191941e-01 1.06514561e+00 8.92321050e-01 -6.85082972e-01
-1.72956109e+00 -1.18575191e+00 8.75669420e-01 -2.64408886e-01
8.54141891e-01 -6.11705899e-01 -3.74469578e-01 4.24315453e-01
-1.46628365e-01 -4.45129752e-01 1.11299837e+00 -2.45303318e-01
-6.98569834e-01 -1.31359279e-01 -1.27751231e+00 7.09877133e-01
1.09205794e+00 -2.23623365e-01 -2.57451683e-01 7.38459587e-01
7.65134752e-01 -3.69267553e-01 -1.51703811e+00 2.62944639e-01
8.55681658e-01 -8.51628006e-01 1.20550478e+00 -5.98563790e-01
5.56765437e-01 -6.04740858e-01 -1.82372123e-01 -9.74579453e-01
-2.57086366e-01 -1.16242635e+00 2.67141551e-01 1.10718346e+00
6.89627469e-01 -7.02520370e-01 3.74951780e-01 2.35231504e-01
-4.55131412e-01 -5.13748050e-01 -6.43654585e-01 -1.02817810e+00
2.63493896e-01 2.00850204e-01 8.13521087e-01 1.12497687e+00
2.01813743e-01 6.82455719e-01 -5.78210592e-01 7.18972087e-02
3.23228836e-01 3.14790197e-02 6.19147360e-01 -1.15318465e+00
1.44306436e-01 -2.50051171e-01 6.15178701e-03 -7.36953795e-01
-2.04384685e-01 -9.65872586e-01 -1.14912547e-01 -9.13011551e-01
1.99703619e-01 -4.90173548e-01 -3.65973502e-01 5.15275657e-01
-1.33246621e-02 -6.28596246e-02 9.76633504e-02 2.15422153e-01
-2.46146679e-01 6.88550532e-01 1.30472147e+00 -2.49221608e-01
-1.42008677e-01 -3.07404906e-01 -7.26794243e-01 4.11630541e-01
9.35956478e-01 -7.49070108e-01 -5.50865948e-01 5.18602490e-01
6.69670224e-01 1.76322937e-01 -2.29764819e-01 -6.60486221e-01
1.32751614e-01 -5.95116496e-01 2.04414532e-01 -1.06480765e+00
3.46331716e-01 -6.94845676e-01 7.92881072e-01 7.92100906e-01
-9.86235440e-02 -3.70299518e-02 2.00552508e-01 5.73661983e-01
1.16037615e-01 -1.74950480e-01 6.03578806e-01 -5.23981988e-01
-3.25150937e-01 6.55507267e-01 -6.45286024e-01 -4.92427260e-01
9.83869612e-01 -1.78635105e-01 -4.66557562e-01 4.49410975e-01
-4.39420462e-01 5.85088953e-02 4.49383318e-01 2.19506845e-01
2.52039343e-01 -1.07119536e+00 -1.23711579e-01 -2.89906383e-01
3.43804896e-01 -4.38729599e-02 -4.60951403e-02 1.00201702e+00
-7.18348920e-01 6.86806440e-01 -1.56336844e-01 -3.10435832e-01
-1.19912183e+00 1.25764453e+00 3.39410514e-01 -2.08731726e-01
1.88776046e-01 6.24259114e-01 3.14550221e-01 -4.87429023e-01
-8.04118440e-02 -4.72334623e-01 -9.60803628e-02 4.74615574e-01
4.26957130e-01 4.22917277e-01 2.99079597e-01 -2.44687453e-01
-5.48462033e-01 5.19737542e-01 -3.49536449e-01 3.84969860e-01
1.24897850e+00 5.94038904e-01 -2.08688483e-01 1.34232029e-01
9.26179826e-01 -3.18961963e-02 -7.87103117e-01 1.30393013e-01
-2.98761129e-02 -2.49541730e-01 -1.20897450e-01 -8.89270902e-01
-5.25996685e-01 7.05164850e-01 2.36316845e-01 -7.43618384e-02
7.55209148e-01 -4.40626949e-01 5.75534701e-01 6.80924833e-01
3.12234253e-01 -1.06503451e+00 7.31169954e-02 2.00251788e-01
9.30106401e-01 -9.91709590e-01 4.55371916e-01 -8.32958460e-01
-2.40273148e-01 1.30387402e+00 3.39020729e-01 4.68450129e-01
2.17604861e-01 -1.38839588e-01 -5.61478317e-01 -1.40598625e-01
-8.93352449e-01 1.05493516e-01 5.49456812e-02 3.19910228e-01
7.12392032e-01 -1.29602142e-02 -7.42671669e-01 3.88294488e-01
-3.15467030e-01 -4.07044664e-02 3.15375447e-01 1.12097025e+00
-5.58458745e-01 -1.47016835e+00 -2.57173002e-01 -2.54596353e-01
-5.21919966e-01 -5.64043522e-01 -9.33049679e-01 9.05873716e-01
3.11545730e-01 1.01926327e+00 -7.83735633e-01 -4.88229781e-01
1.85398281e-01 2.29734674e-01 6.79821908e-01 -4.99768525e-01
-8.56700838e-01 3.44649017e-01 4.78484005e-01 -5.70500791e-01
-3.60685587e-01 -4.10081267e-01 -1.09734845e+00 -3.84467691e-01
-6.22270882e-01 5.28321028e-01 8.43007803e-01 6.79006159e-01
2.15369582e-01 1.48240298e-01 1.04876137e+00 -7.99839020e-01
-5.96129298e-01 -7.12880135e-01 -2.58335084e-01 -3.03505450e-01
-1.78529974e-02 -7.27046430e-01 -1.94084197e-01 2.24332092e-03] | [4.488991737365723, 6.1105875968933105] |
e5b7bc6e-4329-45d9-a0ce-f11192a8334c | dual-illumination-estimation-for-robust | 1910.13688 | null | https://arxiv.org/abs/1910.13688v1 | https://arxiv.org/pdf/1910.13688v1.pdf | Dual Illumination Estimation for Robust Exposure Correction | Exposure correction is one of the fundamental tasks in image processing and computational photography. While various methods have been proposed, they either fail to produce visually pleasing results, or only work well for limited types of image (e.g., underexposed images). In this paper, we present a novel automatic exposure correction method, which is able to robustly produce high-quality results for images of various exposure conditions (e.g., underexposed, overexposed, and partially under- and over-exposed). At the core of our approach is the proposed dual illumination estimation, where we separately cast the under- and over-exposure correction as trivial illumination estimation of the input image and the inverted input image. By performing dual illumination estimation, we obtain two intermediate exposure correction results for the input image, with one fixes the underexposed regions and the other one restores the overexposed regions. A multi-exposure image fusion technique is then employed to adaptively blend the visually best exposed parts in the two intermediate exposure correction images and the input image into a globally well-exposed image. Experiments on a number of challenging images demonstrate the effectiveness of the proposed approach and its superiority over the state-of-the-art methods and popular automatic exposure correction tools. | ['Wei-Shi Zheng', 'Yongwei Nie', 'Qing Zhang'] | 2019-10-30 | null | null | null | null | ['multi-exposure-image-fusion'] | ['computer-vision'] | [ 1.01364839e+00 -2.94222623e-01 4.76776540e-01 -2.90856689e-01
-5.39140224e-01 -3.82673204e-01 4.17918950e-01 1.14538856e-02
-3.92614812e-01 4.91654277e-01 -3.78758870e-02 -1.56454608e-01
-1.84108883e-01 -7.00888634e-01 -5.97699642e-01 -7.89633155e-01
5.95158279e-01 -1.20929860e-01 4.17970419e-01 -7.62933418e-02
3.55483055e-01 3.48018736e-01 -1.89405262e+00 -2.06819326e-01
1.25381279e+00 8.58346879e-01 4.71918702e-01 6.77085459e-01
1.47025302e-01 2.74413705e-01 -4.41168398e-01 -3.74344140e-01
4.91506606e-01 -6.36341870e-01 -4.53975230e-01 6.47438407e-01
8.48713338e-01 -3.97329807e-01 -3.89034906e-03 1.28847933e+00
3.45427155e-01 2.48959109e-01 5.33408880e-01 -9.37956572e-01
-6.08764172e-01 -1.61586285e-01 -1.01722300e+00 2.29875877e-01
3.01197469e-01 1.75338343e-01 2.69191384e-01 -9.86189485e-01
4.77989346e-01 9.20649230e-01 4.58456993e-01 5.45604378e-02
-1.40766156e+00 -4.88795072e-01 1.70386676e-02 1.04467325e-01
-1.21883047e+00 -5.08021295e-01 9.08953846e-01 -3.95641953e-01
3.27887893e-01 3.47209752e-01 5.27868927e-01 2.07625628e-01
5.00174880e-01 2.38717169e-01 1.68754911e+00 -6.52496517e-01
1.04903309e-02 2.73641855e-01 4.60177697e-02 5.67597985e-01
2.65724421e-01 1.51049525e-01 -1.67972028e-01 2.68698316e-02
4.57649529e-01 3.09633523e-01 -7.56035745e-01 -1.16455868e-01
-9.76783216e-01 1.85035139e-01 3.79696637e-01 2.27933690e-01
-7.04937339e-01 -3.60503733e-01 -1.01184517e-01 -4.99030799e-02
6.35093629e-01 1.33189633e-01 -5.82168996e-02 4.41278219e-01
-1.16021657e+00 2.38420650e-01 1.13645397e-01 6.07714474e-01
1.08535588e+00 -1.19246513e-01 -1.81392819e-01 9.44187284e-01
8.31959471e-02 4.90935802e-01 1.66479304e-01 -6.61303043e-01
5.14966905e-01 5.12309015e-01 3.37578028e-01 -1.09047997e+00
-1.00183122e-01 -3.92974734e-01 -8.29495609e-01 6.30672038e-01
4.50774491e-01 -4.48495299e-02 -9.74960208e-01 1.54459071e+00
5.90025306e-01 1.08797625e-01 2.46828750e-01 1.04182827e+00
6.06047869e-01 8.20339143e-01 -3.53506096e-02 -6.24036551e-01
1.42624402e+00 -1.08806312e+00 -1.08621502e+00 -5.32773852e-01
-2.28334740e-01 -1.28495944e+00 1.12033486e+00 4.95683819e-01
-1.56995523e+00 -7.80738890e-01 -1.26829565e+00 -1.00756928e-01
-1.49705812e-01 3.08193535e-01 5.33047281e-02 4.63790268e-01
-9.02534306e-01 3.27304155e-01 -2.75233060e-01 -2.03298733e-01
1.94085851e-01 4.17803824e-02 -3.59561890e-01 -4.46857750e-01
-8.07777941e-01 9.93415296e-01 2.61295825e-01 1.46993116e-01
-5.56224942e-01 -7.33682990e-01 -7.18842864e-01 -3.71136181e-02
5.41806102e-01 -4.44117695e-01 1.01840520e+00 -1.32744634e+00
-1.37592542e+00 8.39275062e-01 -2.24543288e-01 -4.01237756e-02
5.75745344e-01 -2.20843807e-01 -4.35255915e-01 2.33108342e-01
-1.27566382e-01 1.54103875e-01 1.13731277e+00 -1.68116570e+00
-5.96008599e-01 -4.35539424e-01 -1.06326409e-01 5.69897413e-01
-1.72695890e-01 1.64535686e-01 -7.14769125e-01 -6.64520383e-01
3.63365710e-01 -6.78664565e-01 -2.19395831e-02 1.81288198e-01
-3.39862138e-01 4.30510432e-01 1.04178989e+00 -1.05678797e+00
1.12005186e+00 -2.21991062e+00 6.05958812e-02 6.42590448e-02
-9.59297817e-04 4.35808450e-01 5.20653389e-02 3.59207809e-01
-2.18246654e-01 -3.05678248e-01 -5.95232487e-01 -5.82024872e-01
-4.12359744e-01 -5.48016373e-03 -1.55543074e-01 7.51704991e-01
-6.35402417e-03 3.31916720e-01 -8.39528382e-01 -5.62436819e-01
6.66667759e-01 7.08037078e-01 -1.01744264e-01 5.02672553e-01
8.68797973e-02 5.83601117e-01 2.26091072e-01 4.91128147e-01
1.14467168e+00 1.48614064e-01 -1.09462634e-01 -5.14874935e-01
-4.92200524e-01 -4.23409343e-01 -1.37718785e+00 1.29549074e+00
-5.39775491e-01 6.99538827e-01 2.75366485e-01 -2.82275379e-01
8.33906412e-01 9.48190466e-02 2.02691182e-01 -7.66028821e-01
2.97483057e-01 1.90029696e-01 -1.85135230e-01 -6.65895104e-01
7.63827801e-01 -5.20455956e-01 3.56098443e-01 5.80672622e-01
-3.22291285e-01 -2.57688254e-01 2.30624676e-01 4.59578224e-02
3.67954880e-01 1.08638316e-01 4.63370323e-01 5.36366180e-02
8.73929977e-01 -4.89483029e-01 4.34196889e-01 3.70452493e-01
-1.61898389e-01 1.17354405e+00 1.22104272e-01 -9.03358012e-02
-1.04165125e+00 -9.68831241e-01 -8.92069116e-02 8.23001564e-01
6.62084520e-01 -1.10497512e-02 -1.15103281e+00 -2.27377281e-01
-4.26819205e-01 6.03386223e-01 -4.02060747e-01 -1.92974340e-02
-4.67249036e-01 -6.14362657e-01 5.52431531e-02 1.35235265e-01
9.05783713e-01 -8.58484685e-01 -7.59740114e-01 -4.64519393e-03
-3.54570091e-01 -1.07653570e+00 -7.12349951e-01 -2.07653776e-01
-5.10376096e-01 -1.09182727e+00 -8.40476751e-01 -8.52556229e-01
1.05325651e+00 7.96961010e-01 7.73534894e-01 3.04609358e-01
-3.27651411e-01 -1.62151247e-01 -1.08754829e-01 -1.99928403e-01
-3.89689416e-01 -6.98484480e-01 -1.13703273e-01 7.63510942e-01
-5.60108364e-01 -3.64173442e-01 -9.08652723e-01 4.61298257e-01
-1.34315646e+00 3.10251981e-01 7.32430518e-01 7.05918908e-01
7.71419764e-01 4.88878995e-01 1.29285216e-01 -1.06157243e+00
5.26667833e-01 -1.10200547e-01 -7.73406863e-01 4.44940865e-01
-6.49164438e-01 -2.99029499e-01 7.18229175e-01 -5.12933969e-01
-1.68619061e+00 1.11738957e-01 1.39773473e-01 -4.33881313e-01
-1.73278168e-01 2.04030097e-01 -5.28853416e-01 -3.68132234e-01
4.61609334e-01 2.96275407e-01 -1.32415267e-02 -4.35660660e-01
4.22880679e-01 7.27280796e-01 1.02194178e+00 -8.24970752e-02
9.10099924e-01 5.78667462e-01 -8.85149315e-02 -8.33324671e-01
-7.31170118e-01 -2.39629075e-01 -5.44863939e-01 -5.53819776e-01
8.51747751e-01 -5.66583693e-01 -2.05337152e-01 8.16232741e-01
-9.38962221e-01 -1.53394982e-01 -1.00133466e-02 1.55140579e-01
-3.04211289e-01 7.83627689e-01 -1.55624360e-01 -8.23259473e-01
-3.62896889e-01 -1.21185088e+00 9.34476018e-01 7.97808766e-01
2.37326220e-01 -7.88027346e-01 4.26545814e-02 4.22300458e-01
4.04286742e-01 3.79463106e-01 8.87008309e-01 2.49111474e-01
-4.75753844e-01 -2.32740030e-01 -3.73106182e-01 5.88767350e-01
2.95997798e-01 2.34489754e-01 -1.03541386e+00 -2.91998267e-01
2.10918728e-02 1.04372226e-01 7.10282028e-01 3.61038715e-01
1.07840562e+00 -1.81065872e-01 -1.52444288e-01 7.56763995e-01
1.83289707e+00 1.24005251e-01 1.03309619e+00 1.48658127e-01
3.35389286e-01 6.81330860e-01 1.02659810e+00 1.32395104e-01
7.89925158e-02 7.69508779e-01 4.62794095e-01 -7.62577772e-01
-4.67063665e-01 -8.38053823e-02 7.73165002e-02 3.42567116e-01
-5.88116311e-02 -5.94798803e-01 -5.01817107e-01 4.73983109e-01
-1.58524597e+00 -8.61861587e-01 -4.31706160e-01 2.56225967e+00
7.24326253e-01 -9.49198008e-02 -2.32163161e-01 4.01399314e-01
1.01050866e+00 2.16780886e-01 -4.07752454e-01 -4.28715974e-01
-2.90078968e-01 2.15621218e-01 4.83467937e-01 7.21313477e-01
-1.07253778e+00 6.40616179e-01 5.88101912e+00 5.83830535e-01
-1.11372256e+00 1.82788491e-01 4.87086773e-01 1.92446649e-01
-1.99487284e-01 1.73974350e-01 -2.94817209e-01 7.00347900e-01
2.84325063e-01 -1.26208529e-01 4.13801610e-01 2.29373306e-01
3.20541382e-01 -7.52207458e-01 -6.38471007e-01 1.00940418e+00
4.97295797e-01 -6.89996004e-01 -2.25996003e-01 -9.95372534e-02
1.05340266e+00 -6.76849842e-01 3.97588462e-01 -2.87318498e-01
-3.12332690e-01 -6.58391535e-01 8.83464634e-01 8.07542324e-01
9.58323717e-01 -6.49782419e-01 6.72141075e-01 3.38939101e-01
-1.04496586e+00 -9.75123495e-02 -1.47549048e-01 7.63393473e-03
4.37030226e-01 5.89994669e-01 -4.07812595e-01 8.05646777e-01
5.67309618e-01 3.45827490e-01 -7.57809937e-01 1.23004305e+00
-4.35162336e-01 9.66598913e-02 -4.08274010e-02 6.31533086e-01
-1.05786763e-01 -5.84589720e-01 4.69505638e-01 9.09171641e-01
2.47088894e-01 4.66762096e-01 -1.53206463e-03 7.90678799e-01
8.08508545e-02 1.44839913e-01 -3.97461981e-01 4.31757808e-01
2.41566941e-01 1.49505365e+00 -7.58847892e-01 -5.31968713e-01
-3.73907626e-01 1.21184921e+00 3.21318135e-02 5.67350864e-01
-8.79028976e-01 -4.84094083e-01 3.76108259e-01 2.05459356e-01
1.24308586e-01 7.40703717e-02 -3.48998398e-01 -9.43062842e-01
2.72445679e-01 -7.90875256e-01 2.52361417e-01 -1.30208814e+00
-8.57597291e-01 6.27237678e-01 1.17997088e-01 -1.32466233e+00
1.92651406e-01 -1.98370382e-01 -9.08066094e-01 1.23968458e+00
-1.60108268e+00 -1.04103172e+00 -8.75563264e-01 3.58252257e-01
7.53203213e-01 3.03915679e-01 2.83221990e-01 4.55604374e-01
-6.85765684e-01 3.27384412e-01 2.88836509e-01 -5.65130413e-01
8.91260564e-01 -9.78622139e-01 -7.46710524e-02 1.50331259e+00
-3.44631523e-01 3.97318929e-01 9.23068643e-01 -6.78416073e-01
-1.00461948e+00 -1.15429401e+00 6.36119723e-01 1.55477095e-02
-3.49901617e-02 2.02419702e-02 -1.11673844e+00 2.97326356e-01
5.67796826e-01 -1.27951264e-01 3.11053067e-01 -7.19453156e-01
-1.00679798e-02 -3.37755293e-01 -1.32185483e+00 6.20425999e-01
4.36708361e-01 -1.91899985e-01 -5.04352689e-01 1.34415448e-01
3.25457841e-01 -6.04053259e-01 -5.93212247e-01 3.81590724e-01
5.59063613e-01 -1.29678333e+00 1.14281952e+00 2.50258535e-01
5.54995239e-01 -8.07570040e-01 7.12846741e-02 -1.25049102e+00
-1.14970937e-01 -5.27006269e-01 2.62522906e-01 1.48795247e+00
6.92865551e-02 -7.08788097e-01 1.82470396e-01 3.98724824e-01
-1.56660959e-01 -6.10049009e-01 -3.11065495e-01 -4.56041366e-01
-5.05365312e-01 5.38303517e-02 4.86048013e-01 6.39896691e-01
-5.00723362e-01 6.08800091e-02 -5.68455994e-01 4.56867158e-01
9.94448781e-01 4.41924006e-01 8.59190702e-01 -8.44846725e-01
-2.16045976e-01 -1.57737747e-01 -9.71773863e-02 -6.00011587e-01
-1.72632560e-01 -3.44120473e-01 4.30237114e-01 -1.61508095e+00
4.02382076e-01 -1.85723782e-01 -7.33035733e-04 1.98728636e-01
-7.80122638e-01 7.45306671e-01 1.64294660e-01 2.33267337e-01
-2.40340739e-01 1.51650012e-01 1.31890917e+00 4.52686325e-02
-2.90173024e-01 -8.51082280e-02 -7.47602582e-01 7.53582120e-01
7.05670297e-01 -2.25705087e-01 -4.27518457e-01 -3.97262454e-01
-1.36424825e-01 -5.52267097e-02 5.32713115e-01 -1.01244760e+00
1.93710029e-01 -1.26029581e-01 5.80380917e-01 -7.62964725e-01
3.52680892e-01 -8.10693085e-01 5.90195060e-01 2.88536370e-01
-1.76287636e-01 -7.11805671e-02 4.04102989e-02 6.04838729e-01
-1.45792365e-01 -3.17100465e-01 1.38323152e+00 -3.95354480e-02
-6.33808732e-01 1.21713698e-01 -1.03657551e-01 -2.82015353e-01
1.27688098e+00 -4.67370749e-01 -3.95109504e-01 -2.83083349e-01
-3.24982107e-01 -4.34662290e-02 9.82426643e-01 2.12269068e-01
8.83143008e-01 -9.38391149e-01 -6.68290615e-01 3.87765914e-01
3.72802988e-02 -1.56234354e-01 7.37587512e-01 1.03252208e+00
-6.92279160e-01 -2.69569695e-01 -2.80147582e-01 -4.82698768e-01
-1.87055671e+00 7.70939529e-01 3.40896487e-01 -3.22043244e-03
-6.03372991e-01 4.46354777e-01 5.02117634e-01 1.46260545e-01
1.79431736e-01 -1.58499256e-01 -2.94380993e-01 -2.00927198e-01
7.75351584e-01 4.80566204e-01 1.92908987e-01 -9.76685643e-01
-5.15063666e-02 1.11512661e+00 8.38478729e-02 -1.14432871e-01
1.11270678e+00 -6.63967729e-01 -2.24031612e-01 1.99079126e-01
1.10236132e+00 1.06024660e-01 -1.31480110e+00 -2.85721213e-01
-7.36473799e-01 -1.14202166e+00 2.70937532e-01 -7.33426034e-01
-1.01677072e+00 1.04093635e+00 9.19464469e-01 9.65277851e-02
1.86195469e+00 -3.44225913e-01 8.15185189e-01 -3.95248383e-01
-5.06077558e-02 -1.03819311e+00 7.24875107e-02 -1.16805017e-01
8.69158208e-01 -1.05049098e+00 4.68926430e-01 -7.34173536e-01
-5.33232331e-01 9.76654053e-01 5.80929339e-01 -1.35934763e-02
1.38996422e-01 6.50900900e-02 1.45583779e-01 -1.96236253e-01
-3.33892107e-01 -3.98136824e-01 4.63947058e-01 4.77945685e-01
1.31804898e-01 -2.73765504e-01 -4.68821436e-01 1.40481591e-01
1.62451014e-01 -2.72522360e-01 6.56261086e-01 8.87105644e-01
-5.30439377e-01 -7.82990754e-01 -9.66352105e-01 1.48311824e-01
-4.31983918e-01 1.17705561e-01 -3.40226203e-01 6.41179264e-01
5.83838642e-01 1.11909330e+00 -5.57299331e-02 -1.28282741e-01
5.65971971e-01 -2.26641253e-01 5.56489468e-01 -2.88306355e-01
-5.83410025e-01 2.77097434e-01 -3.24031323e-01 -3.50787073e-01
-5.64624071e-01 -5.98003626e-01 -9.26508665e-01 -1.22939937e-01
-6.26874864e-01 -2.97463059e-01 7.05750644e-01 7.26688445e-01
-5.71904294e-02 5.73451340e-01 8.32879603e-01 -1.12850881e+00
-1.05895102e-01 -8.03533256e-01 -5.58136225e-01 5.91776550e-01
5.45498610e-01 -6.58595443e-01 -5.52188039e-01 4.52145666e-01] | [10.85098648071289, -2.4802236557006836] |
d0a09d5e-0e59-4d57-9e8a-c0210aa0a6f3 | mining-unseen-classes-via-regional-objectness | 2211.06866 | null | https://arxiv.org/abs/2211.06866v3 | https://arxiv.org/pdf/2211.06866v3.pdf | Mining Unseen Classes via Regional Objectness: A Simple Baseline for Incremental Segmentation | Incremental or continual learning has been extensively studied for image classification tasks to alleviate catastrophic forgetting, a phenomenon that earlier learned knowledge is forgotten when learning new concepts. For class incremental semantic segmentation, such a phenomenon often becomes much worse due to the background shift, i.e., some concepts learned at previous stages are assigned to the background class at the current training stage, therefore, significantly reducing the performance of these old concepts. To address this issue, we propose a simple yet effective method in this paper, named Mining unseen Classes via Regional Objectness for Segmentation (MicroSeg). Our MicroSeg is based on the assumption that background regions with strong objectness possibly belong to those concepts in the historical or future stages. Therefore, to avoid forgetting old knowledge at the current training stage, our MicroSeg first splits the given image into hundreds of segment proposals with a proposal generator. Those segment proposals with strong objectness from the background are then clustered and assigned newly-defined labels during the optimization. In this way, the distribution characterizes of old concepts in the feature space could be better perceived, relieving the catastrophic forgetting caused by the background shift accordingly. Extensive experiments on Pascal VOC and ADE20K datasets show competitive results with state-of-the-art, well validating the effectiveness of the proposed MicroSeg. | ['Yunchao Wei', 'Jianbo Jiao', 'Zhiyuan Fang', 'Guangyu Gao', 'Zekang Zhang'] | 2022-11-13 | null | null | null | null | ['class-incremental-semantic-segmentation'] | ['computer-vision'] | [ 3.53392750e-01 1.75312102e-01 7.45828543e-03 -3.31257075e-01
-2.55360571e-03 -1.41470730e-01 2.61929721e-01 5.19182265e-01
-6.69110417e-01 9.45849359e-01 -3.97283852e-01 1.58425987e-01
6.12613000e-02 -9.29525435e-01 -8.04323554e-01 -1.10613513e+00
3.80963862e-01 4.56883013e-01 9.23824728e-01 1.13930134e-03
3.08587909e-01 1.32924587e-01 -1.84421015e+00 1.91413283e-01
1.25631499e+00 7.86513865e-01 5.70836723e-01 3.14903036e-02
-5.06002009e-01 5.00106096e-01 -9.85004663e-01 -4.09899056e-01
3.97992991e-02 -3.19668204e-01 -6.05273306e-01 5.33949018e-01
3.91695946e-01 3.56448740e-02 2.28260849e-02 1.31081808e+00
1.39518872e-01 4.09346849e-01 2.49983266e-01 -1.05516720e+00
-3.32749873e-01 6.41430259e-01 -8.52947891e-01 3.22905540e-01
-3.32969010e-01 1.04708746e-01 5.57720363e-01 -1.16737247e+00
4.90169764e-01 1.09910321e+00 4.58537787e-01 6.80974960e-01
-1.11670494e+00 -7.64073372e-01 9.32888567e-01 4.73930627e-01
-1.56938612e+00 -4.40481752e-02 8.01969290e-01 -2.20635071e-01
2.04490349e-01 2.18061596e-01 9.49860096e-01 7.64097750e-01
1.08765386e-01 1.07816839e+00 9.48968589e-01 -1.82068497e-01
4.64554429e-01 6.42945170e-01 4.07409877e-01 5.54106712e-01
5.16108036e-01 -3.14769149e-01 -5.56109309e-01 2.65965670e-01
2.38921523e-01 2.64465719e-01 -3.44184726e-01 -4.54518825e-01
-8.57054293e-01 5.07996261e-01 6.59287632e-01 4.54716295e-01
-2.68512368e-01 -2.43646473e-01 2.54397094e-01 -1.01917563e-02
5.51667869e-01 6.53004348e-02 -6.20253205e-01 4.07463551e-01
-9.97170269e-01 -2.18539685e-02 2.57566959e-01 8.78475606e-01
1.23370039e+00 -1.25309318e-01 -2.34695047e-01 8.03658843e-01
-3.82390283e-02 1.04277194e-01 8.12631786e-01 -4.43649173e-01
1.71244562e-01 9.32403803e-01 -7.92650282e-02 -9.01700139e-01
-2.40664512e-01 -1.03832531e+00 -8.19197237e-01 1.11742683e-01
2.90947378e-01 1.21972904e-01 -1.27232146e+00 1.59999347e+00
6.50492251e-01 4.04844135e-01 6.75462633e-02 7.28722870e-01
5.10910094e-01 8.21340621e-01 3.31267297e-01 -6.41891837e-01
1.08922052e+00 -1.12358451e+00 -5.49306870e-01 -5.57739854e-01
2.16043621e-01 -5.10953307e-01 1.04008508e+00 6.38691366e-01
-5.48394978e-01 -1.13314784e+00 -9.04363155e-01 5.08680701e-01
-3.23099285e-01 -2.58586137e-03 5.52931309e-01 5.60349703e-01
-6.56786740e-01 7.14014709e-01 -6.84239507e-01 -2.81537682e-01
7.62051761e-01 -3.96507569e-02 1.49413496e-01 -2.16091052e-01
-8.83599579e-01 4.21950579e-01 1.06980348e+00 1.21994048e-01
-9.55753505e-01 -7.60351002e-01 -3.47654402e-01 2.98843663e-02
8.36705804e-01 -4.48163539e-01 9.31964993e-01 -1.48017216e+00
-9.77435172e-01 5.60777783e-01 -1.99928150e-01 -5.37555814e-01
5.58623374e-01 -3.27343702e-01 -3.52182448e-01 -1.13642223e-01
2.82878816e-01 9.32342768e-01 1.40522766e+00 -1.46504343e+00
-1.07256579e+00 -5.09686112e-01 -1.37345165e-01 3.26336503e-01
-4.88395959e-01 -8.56685042e-01 -6.38956487e-01 -8.72909129e-01
7.12820947e-01 -9.55450892e-01 -2.26946026e-01 -1.46877632e-01
-2.20786259e-01 -3.97653461e-01 1.07999337e+00 -3.09632123e-01
1.30094194e+00 -2.28374529e+00 6.69145212e-02 1.13497935e-02
1.59078091e-01 4.00350928e-01 1.03318639e-01 -3.78125429e-01
-6.55858740e-02 -2.77537131e-03 -5.22831500e-01 -2.38725960e-01
-6.03223383e-01 4.22651768e-01 -3.45722705e-01 1.38767019e-01
2.44952574e-01 4.86603677e-01 -1.11549973e+00 -5.49452424e-01
1.64720073e-01 -4.09656391e-02 -3.70215237e-01 5.80665730e-02
-5.13501883e-01 5.86700320e-01 -3.73157293e-01 7.75839925e-01
1.01586521e+00 -1.63063984e-02 -1.12989210e-01 -1.45491123e-01
-2.48051081e-02 -4.00227696e-01 -1.20254600e+00 1.61384106e+00
-1.88449815e-01 2.76166558e-01 -2.07590044e-01 -1.09991515e+00
8.95147502e-01 -1.58930391e-01 2.23957524e-01 -6.00944042e-01
-1.11166544e-01 6.49783462e-02 -1.19802199e-01 -3.51724833e-01
6.08004272e-01 -2.73521900e-01 1.50907025e-01 -2.21832469e-02
2.84335157e-03 -1.69913415e-02 3.00792634e-01 2.65030414e-01
5.57110846e-01 2.16354281e-01 1.03202267e-02 -2.76327640e-01
7.03741133e-01 1.49811730e-01 1.15957522e+00 9.01052713e-01
-4.07986581e-01 4.68306899e-01 7.13401362e-02 -4.79710132e-01
-5.41556716e-01 -1.14949346e+00 -9.67331156e-02 1.04180336e+00
6.76407397e-01 -1.78625032e-01 -8.77066970e-01 -1.03552830e+00
-1.51923448e-01 1.00804460e+00 -5.17372549e-01 -4.93290097e-01
-6.26636922e-01 -1.00240171e+00 -9.49752405e-02 4.47987884e-01
8.07597876e-01 -1.18398845e+00 -7.21184611e-01 5.38651764e-01
-2.10417092e-01 -6.91386938e-01 -1.98774368e-01 1.07773200e-01
-1.31651711e+00 -9.02833939e-01 -9.86306012e-01 -6.58564210e-01
1.01459408e+00 5.96836269e-01 9.22848403e-01 2.09500849e-01
-3.07427317e-01 1.19397566e-02 -4.61971581e-01 -5.25999725e-01
-3.30306053e-01 4.60963435e-02 1.46732749e-02 3.97668332e-01
2.50786096e-01 -2.80578971e-01 -7.20149815e-01 3.74754399e-01
-9.82547343e-01 1.83258355e-01 7.03791440e-01 7.71310866e-01
9.00853395e-01 8.18863630e-01 8.13807845e-01 -9.77790892e-01
-7.80307502e-02 -3.82485986e-01 -5.20854473e-01 2.52763629e-01
-7.83299804e-01 -1.01540819e-01 5.15936017e-01 -7.85644293e-01
-1.42231917e+00 1.74078066e-02 1.05365105e-01 -4.09637749e-01
-1.85592592e-01 1.58098727e-01 -4.50367033e-01 1.61764696e-01
4.38282341e-01 4.18126762e-01 -3.90854836e-01 -4.22596067e-01
3.11433643e-01 2.52896875e-01 5.83884001e-01 -3.85926634e-01
7.58828402e-01 5.81358969e-01 -3.21741611e-01 -7.87658274e-01
-1.02591133e+00 -4.86539036e-01 -5.17103732e-01 -4.43628818e-01
6.83466673e-01 -8.32664371e-01 -1.08755447e-01 8.45749140e-01
-8.95620584e-01 -1.41094392e-03 -6.09314263e-01 2.30956554e-01
-3.13395471e-03 4.02748704e-01 -1.55486152e-01 -8.55867267e-01
-1.76297918e-01 -9.48032975e-01 6.36166513e-01 9.16146338e-01
3.41696329e-02 -5.36906540e-01 -4.54775780e-01 3.35629612e-01
1.63819015e-01 5.62072732e-02 1.02737463e+00 -4.22360808e-01
-7.66816556e-01 -2.29093339e-02 -1.81650147e-01 5.16363859e-01
3.19802880e-01 -2.33370706e-01 -9.67134714e-01 -5.60060978e-01
2.77387768e-01 -3.71899605e-02 1.43738496e+00 1.67726025e-01
1.32116771e+00 -2.63921142e-01 -6.83382392e-01 2.31621444e-01
1.37710798e+00 4.50183988e-01 4.60590273e-01 3.71902257e-01
6.79275572e-01 7.56773055e-01 1.18610048e+00 3.78872931e-01
1.00596584e-01 2.88633823e-01 3.75576556e-01 -1.71078831e-01
-2.25372046e-01 -1.78460538e-01 1.30809858e-01 6.72050178e-01
3.14799190e-01 -2.35911027e-01 -6.45529926e-01 7.20254660e-01
-1.87074029e+00 -5.85969031e-01 6.25926703e-02 2.37075472e+00
9.79566395e-01 7.85957634e-01 -2.73999959e-01 2.04428017e-01
1.07022381e+00 -4.98586334e-03 -9.65179086e-01 2.22400278e-01
-3.74957114e-01 1.40736759e-01 2.62817353e-01 1.22254848e-01
-1.04561937e+00 1.10409057e+00 3.77908254e+00 1.23097038e+00
-1.05387843e+00 2.88152248e-01 9.98672426e-01 6.37648180e-02
-3.30288820e-02 2.15577736e-01 -9.80486929e-01 5.55900455e-01
3.05208117e-01 -2.00752050e-01 -1.62243657e-02 9.60131586e-01
-3.35455909e-02 -6.98049784e-01 -7.26366699e-01 8.19577336e-01
5.42949885e-02 -9.86356914e-01 3.65240276e-01 -4.65741605e-01
9.24054444e-01 -3.89276147e-01 1.45620346e-01 5.77665329e-01
-2.19310090e-01 -2.74930388e-01 1.00991940e+00 5.73551118e-01
3.43728215e-01 -8.93447042e-01 6.66110396e-01 5.56017876e-01
-1.11765063e+00 -4.22121853e-01 -6.38033569e-01 3.87172669e-01
-6.58714175e-02 1.10312355e+00 -7.04646051e-01 5.22452533e-01
9.58111525e-01 5.49877405e-01 -1.01004899e+00 1.12842691e+00
-3.02354604e-01 6.78710699e-01 -1.59488127e-01 2.11114734e-01
1.75563321e-01 -1.03716686e-01 7.65989780e-01 7.83345282e-01
2.51064777e-01 1.17341392e-01 1.92018226e-01 8.83443832e-01
8.43179151e-02 2.21665930e-02 2.15701219e-02 3.30745548e-01
3.54834616e-01 1.08162868e+00 -1.47865629e+00 -6.71703756e-01
-6.63296729e-02 1.23796606e+00 1.23545796e-01 3.12592775e-01
-7.72460043e-01 -2.95802057e-01 9.12953317e-02 1.94434211e-01
4.71225798e-01 8.70752931e-02 -2.91877180e-01 -1.18623614e+00
1.64528713e-01 -4.98865068e-01 6.99849725e-01 -5.55773795e-01
-1.04718184e+00 5.86871386e-01 -9.05747190e-02 -1.12479317e+00
4.96445835e-01 -1.08387806e-01 -5.70784926e-01 3.41640085e-01
-1.33886504e+00 -6.11695826e-01 -6.15835786e-01 3.53195012e-01
1.14024222e+00 6.81301504e-02 1.90204635e-01 2.22630531e-01
-7.35460043e-01 3.73976588e-01 -9.07846242e-02 -3.45304638e-01
7.00312972e-01 -1.14272833e+00 9.51483175e-02 1.09204555e+00
2.38592297e-01 4.08317477e-01 6.13870680e-01 -9.61376071e-01
-4.98124629e-01 -1.46628559e+00 5.08542895e-01 -1.30741015e-01
1.41175091e-01 -3.00307721e-01 -1.43346882e+00 8.16889107e-02
-2.50702024e-01 -1.68134615e-01 2.31613472e-01 -1.88235745e-01
-2.40520500e-02 -6.19823694e-01 -1.13187993e+00 5.92449725e-01
9.12649155e-01 6.08219095e-02 -7.94325411e-01 2.50448287e-01
9.06069398e-01 -2.75418218e-02 -1.06025338e-01 7.11905122e-01
4.14358228e-02 -9.16749060e-01 6.39705360e-01 -3.33402939e-02
-1.25526518e-01 -7.02377439e-01 2.46329829e-01 -1.30507541e+00
-2.39376992e-01 -2.65933633e-01 -4.98986579e-02 1.52732480e+00
2.60414332e-01 -4.93432015e-01 1.02942777e+00 2.62619704e-01
-1.75649837e-01 -6.21681094e-01 -1.09888279e+00 -8.50718737e-01
-8.76044184e-02 -1.12803377e-01 4.66566890e-01 8.01977098e-01
-6.38280928e-01 3.29676867e-01 5.35790697e-02 2.05367267e-01
7.27750659e-01 2.06740245e-01 5.73877752e-01 -1.23389626e+00
-6.27707019e-02 -3.14493120e-01 -3.22845012e-01 -9.76158619e-01
-1.84853852e-01 -6.43602371e-01 3.79380345e-01 -1.16699505e+00
3.27882916e-01 -8.80013645e-01 -6.53291941e-01 4.68452454e-01
-7.95490801e-01 1.94240570e-01 2.20932961e-01 3.62001151e-01
-8.18042994e-01 8.22809756e-01 1.26361513e+00 -4.28459466e-01
-5.43328702e-01 2.89993584e-01 -5.38040221e-01 8.76800776e-01
7.04648554e-01 -7.97235131e-01 -5.43115199e-01 -1.08166210e-01
-1.59726799e-01 -3.95292103e-01 3.20677131e-01 -1.47274971e+00
2.01955229e-01 4.72921599e-03 5.88923514e-01 -9.12205338e-01
7.27167819e-03 -8.03034425e-01 8.92735422e-02 8.10572207e-01
4.06150445e-02 -3.82502168e-01 4.53616858e-01 1.03356421e+00
-1.10825792e-01 -4.39414382e-01 1.08258045e+00 -3.31185281e-01
-1.27331412e+00 2.32199326e-01 -2.95664161e-01 7.99091384e-02
1.22835553e+00 -4.93401855e-01 -2.81642824e-02 2.45050371e-01
-1.01465201e+00 2.71713138e-01 3.11143905e-01 5.60639501e-01
7.63338566e-01 -8.50032985e-01 -5.28696418e-01 2.67190486e-01
2.15224117e-01 4.97287452e-01 6.72911346e-01 6.28480673e-01
-1.93753660e-01 -1.35029063e-01 4.78403131e-03 -8.78931880e-01
-1.11492407e+00 9.15999293e-01 1.38469398e-01 -1.53283095e-02
-6.84828997e-01 1.08801317e+00 7.69634604e-01 1.03818320e-01
2.75648624e-01 -2.40017921e-01 -2.89251566e-01 3.92257184e-01
4.68046367e-01 3.17938715e-01 1.77306056e-01 -3.77480209e-01
-3.50473732e-01 4.28030998e-01 -6.12836123e-01 1.95204958e-01
9.54326391e-01 -4.20750082e-01 -1.27948463e-01 6.46154821e-01
6.12852097e-01 -2.10848808e-01 -1.39206862e+00 -4.21386898e-01
1.59593582e-01 -4.65836942e-01 -1.00090034e-01 -6.73259079e-01
-1.15097511e+00 6.58821404e-01 1.04545915e+00 -1.55342862e-01
1.36015344e+00 8.17657635e-02 8.68699312e-01 3.22222352e-01
6.03409410e-01 -1.44292819e+00 4.10346210e-01 2.94526339e-01
4.96655494e-01 -1.01851606e+00 9.66235623e-03 -5.56497872e-01
-7.18299031e-01 9.67293561e-01 1.04556036e+00 2.26185396e-01
5.32715857e-01 -3.12024057e-01 -5.72748743e-02 7.21343979e-02
-3.92234832e-01 -1.64911717e-01 3.62594090e-02 3.01190197e-01
-3.29663932e-01 2.21850537e-03 -3.90537590e-01 6.84186637e-01
1.07610479e-01 -1.56497136e-01 5.14745176e-01 1.07570994e+00
-8.30380976e-01 -7.76293457e-01 -3.69210839e-01 2.90256083e-01
-2.14474723e-01 -1.96653865e-02 -1.33283198e-01 4.52543795e-01
9.38613296e-01 8.71973336e-01 1.73011690e-01 -1.79244578e-01
3.18206638e-01 1.00315318e-01 2.58726269e-01 -7.83900499e-01
-3.02056730e-01 1.79683432e-01 -4.97481108e-01 -2.80523509e-01
-3.68162304e-01 -5.88608027e-01 -1.39941287e+00 2.25913808e-01
-7.97306478e-01 3.88360918e-01 3.62671554e-01 7.96526968e-01
1.80005074e-01 8.06780875e-01 5.36049426e-01 -4.67198700e-01
-1.62128836e-01 -8.09337676e-01 -4.81824338e-01 4.56126630e-01
1.59829289e-01 -8.24543297e-01 -3.41596067e-01 1.13926701e-01] | [9.40721321105957, 1.8321558237075806] |
fde6ac01-b8b9-4ccb-8091-ad6c9199cfcb | protein-secondary-structure-prediction-using | 1604.07176 | null | http://arxiv.org/abs/1604.07176v1 | http://arxiv.org/pdf/1604.07176v1.pdf | Protein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks | Protein secondary structure prediction is an important problem in
bioinformatics. Inspired by the recent successes of deep neural networks, in
this paper, we propose an end-to-end deep network that predicts protein
secondary structures from integrated local and global contextual features. Our
deep architecture leverages convolutional neural networks with different kernel
sizes to extract multiscale local contextual features. In addition, considering
long-range dependencies existing in amino acid sequences, we set up a
bidirectional neural network consisting of gated recurrent unit to capture
global contextual features. Furthermore, multi-task learning is utilized to
predict secondary structure labels and amino-acid solvent accessibility
simultaneously. Our proposed deep network demonstrates its effectiveness by
achieving state-of-the-art performance, i.e., 69.7% Q8 accuracy on the public
benchmark CB513, 76.9% Q8 accuracy on CASP10 and 73.1% Q8 accuracy on CASP11.
Our model and results are publicly available. | ['Yizhou Yu', 'Zhen Li'] | 2016-04-25 | null | null | null | null | ['protein-secondary-structure-prediction'] | ['medical'] | [ 3.58033985e-01 -1.31084785e-01 -9.97886583e-02 -6.15887761e-01
-1.15500665e+00 -4.58751976e-01 1.51429027e-01 4.64121699e-01
-5.98625302e-01 1.12210608e+00 1.51584908e-01 -7.24592984e-01
1.52725399e-01 -4.13119406e-01 -1.01032352e+00 -9.62004602e-01
3.82561460e-02 1.02148734e-01 -6.54883357e-03 -1.69881731e-01
4.74938810e-01 4.59791005e-01 -9.48215902e-01 5.86820364e-01
1.16853535e+00 7.92520881e-01 2.05128297e-01 7.69024611e-01
1.11697748e-01 8.84131849e-01 -4.67104435e-01 -9.47998613e-02
-2.45188043e-01 -5.46253443e-01 -9.53898787e-01 -4.69894260e-01
1.24919251e-01 -7.87288845e-02 -5.34523316e-02 7.06205249e-01
8.02614212e-01 -3.44539098e-02 6.42010868e-01 -2.93053180e-01
-7.59982586e-01 9.28083658e-02 -6.31224453e-01 2.80354440e-01
3.19907814e-01 5.29393911e-01 1.29329872e+00 -9.44786847e-01
7.72844553e-01 7.33222425e-01 7.52156973e-01 3.17106128e-01
-1.55135584e+00 -5.64668536e-01 1.85807385e-02 4.27202225e-01
-1.04264033e+00 -5.85193224e-02 4.48178589e-01 -2.26551950e-01
1.66856861e+00 -1.44739702e-01 4.63777393e-01 1.25861490e+00
9.54503000e-01 5.67184269e-01 1.06766343e+00 -1.56827182e-01
1.96110472e-01 -6.61742985e-01 3.24330389e-01 7.54056990e-01
-1.33171022e-01 -1.63413465e-01 -5.24575293e-01 -4.84854519e-01
3.18558544e-01 3.48000765e-01 -5.30990586e-02 -1.39662355e-01
-1.04086196e+00 9.41012025e-01 6.36801898e-01 1.84894931e-02
-6.29115999e-01 -2.44201366e-02 4.62171853e-01 2.17204303e-01
3.78682315e-01 3.87594998e-01 -9.87752438e-01 -2.32938081e-01
-5.93463182e-01 2.41564527e-01 5.57011306e-01 3.71605515e-01
7.98451066e-01 -4.91840094e-01 1.65179279e-02 7.80900002e-01
3.65400553e-01 2.17313230e-01 4.51991469e-01 -3.51606369e-01
1.32576615e-01 7.47082472e-01 5.85079789e-02 -3.96389157e-01
-8.67176890e-01 -4.74861652e-01 -8.57894182e-01 8.93761590e-02
1.57582775e-01 -1.20490849e-01 -1.00005031e+00 1.74458838e+00
3.05842340e-01 8.58052354e-03 3.20348591e-01 8.69229436e-01
8.33136261e-01 8.17598939e-01 4.87609297e-01 -2.32041538e-01
1.28072870e+00 -8.07268381e-01 -5.05331576e-01 2.92159945e-01
8.90834212e-01 -7.49458134e-01 9.52066302e-01 3.92772019e-01
-7.50120640e-01 -4.60159302e-01 -1.03815544e+00 -4.46250468e-01
-2.06621557e-01 1.45632476e-01 4.87558335e-01 1.21888444e-01
-6.50526345e-01 6.23194993e-01 -1.00246310e+00 -2.07590431e-01
2.25441545e-01 5.82781494e-01 -3.21346074e-01 2.01510042e-01
-1.35709119e+00 7.85373569e-01 3.36914420e-01 1.90636396e-01
-1.02268124e+00 -7.61709332e-01 -3.74786109e-01 4.53692749e-02
7.63054043e-02 -6.07433319e-01 1.22945464e+00 -9.39024925e-01
-1.70075071e+00 6.90039098e-01 -4.48136300e-01 -6.99909806e-01
1.64095908e-01 -4.50007319e-01 -1.72178701e-01 1.57993689e-01
-3.56250368e-02 4.57868248e-01 -2.24763080e-02 -5.55303991e-01
-5.03941894e-01 -5.88327765e-01 -1.29978523e-01 2.35003591e-01
1.70798376e-01 6.60997033e-02 2.38927454e-01 -5.55662870e-01
-2.17455477e-02 -8.93897176e-01 -7.21093774e-01 -4.22775179e-01
-4.72575635e-01 -2.66784996e-01 4.78259265e-01 -7.30969191e-01
9.65907693e-01 -1.63219917e+00 1.64783359e-01 2.37521827e-01
3.06837678e-01 3.81436497e-01 -2.25283355e-01 7.86140621e-01
-3.19246411e-01 -1.32102609e-01 -2.09906220e-01 2.96627432e-01
-2.29305983e-01 -3.09071749e-01 -1.46000326e-01 5.52345693e-01
5.40560246e-01 9.81128156e-01 -6.86424553e-01 8.85074064e-02
1.27864093e-01 9.34568405e-01 -7.00232685e-01 3.23971421e-01
-3.05360913e-01 5.07197380e-01 -6.21638656e-01 4.82727438e-01
5.65270245e-01 -7.75230229e-01 6.37781978e-01 -2.93282717e-01
-2.02822477e-01 6.76392257e-01 -3.14918041e-01 1.83605611e+00
-3.52414042e-01 1.53632298e-01 -2.55280167e-01 -1.00476229e+00
1.12360597e+00 2.03771636e-01 6.01790965e-01 -7.46728599e-01
-9.99572352e-02 2.28544220e-01 4.02885824e-01 -3.17779899e-01
1.58690125e-01 -1.78835109e-01 1.13068804e-01 3.44440073e-01
2.30903253e-01 6.32958949e-01 -1.45312175e-01 1.55422658e-01
1.38133907e+00 5.36509752e-01 5.15534341e-01 -5.19253254e-01
6.35109484e-01 -9.24448669e-02 9.40620482e-01 3.34471136e-01
-1.32726014e-01 5.65506518e-01 7.92040586e-01 -9.05533850e-01
-1.06253934e+00 -7.25376606e-01 -1.90451756e-01 1.46719730e+00
-9.55483615e-02 -7.76723325e-01 -7.21449435e-01 -8.30015182e-01
-2.69721717e-01 1.59116492e-01 -6.83504105e-01 -2.76215971e-01
-7.30771363e-01 -1.30363655e+00 3.60983163e-01 5.24474382e-01
1.47724107e-01 -1.28581035e+00 -6.25158489e-01 6.96615398e-01
-6.71474412e-02 -6.12222612e-01 -3.68674159e-01 8.42881739e-01
-7.96537876e-01 -1.33977520e+00 -5.86922109e-01 -7.86085665e-01
2.69772351e-01 -4.44530100e-02 1.01393068e+00 -9.24321711e-02
-4.03371274e-01 -5.84059417e-01 -3.11948061e-01 -2.93747216e-01
-1.95284620e-01 4.61179316e-01 -1.39059871e-01 -2.02266872e-01
7.38242447e-01 -6.41108632e-01 -1.07116830e+00 2.11513281e-01
-8.02277803e-01 2.41948336e-01 8.89898837e-01 1.37727654e+00
1.07734811e+00 -7.64411807e-01 9.38581884e-01 -1.10612082e+00
4.39662367e-01 -3.55737090e-01 -6.27512097e-01 3.02835763e-01
-6.10664666e-01 4.89497632e-01 9.21511054e-01 3.49510014e-02
-1.08602667e+00 3.94086659e-01 -6.38314784e-01 3.05580288e-01
-2.33718693e-01 7.46235311e-01 -1.41195521e-01 -6.77330866e-02
5.67356229e-01 3.95691395e-01 -9.41965207e-02 -6.45955324e-01
2.32871965e-01 6.56629324e-01 1.50712237e-01 -4.15628403e-01
-4.23630178e-02 1.33221552e-01 1.36553347e-01 -6.51413918e-01
-9.22396362e-01 -3.83278817e-01 -5.93746185e-01 4.51037973e-01
1.02034569e+00 -8.48733485e-01 -1.25963223e+00 6.00147605e-01
-1.05777466e+00 -2.67280340e-01 4.80726719e-01 3.98019761e-01
-6.24066949e-01 5.61304033e-01 -8.84850383e-01 -2.54966229e-01
-1.01887107e+00 -1.60374284e+00 1.10097146e+00 -1.15535399e-02
-1.00781277e-01 -6.50038779e-01 4.08079565e-01 4.65412647e-01
1.56431258e-01 4.07794923e-01 1.08258784e+00 -8.96358013e-01
-4.40488964e-01 2.56586254e-01 -2.83866882e-01 7.28735775e-02
2.07599536e-01 7.69371400e-03 -8.22938740e-01 -3.72319639e-01
-4.72946793e-01 -6.62454426e-01 1.16436636e+00 6.34918034e-01
1.12433517e+00 -7.34980851e-02 -2.73633033e-01 8.45529139e-01
1.38070726e+00 4.05376583e-01 4.45567667e-01 5.62261522e-01
7.57375479e-01 3.23291630e-01 5.74383974e-01 4.72742021e-01
1.81061089e-01 4.70510662e-01 3.97624463e-01 -2.47095272e-01
3.72788906e-01 -1.22608721e-01 2.69962847e-01 6.40500188e-01
-9.18554738e-02 -5.32494299e-02 -1.24125886e+00 8.99461508e-02
-1.94162929e+00 -7.29316175e-01 -1.11092672e-01 1.83674693e+00
1.04508042e+00 1.71020269e-01 5.60014695e-02 -4.91619796e-01
5.03753483e-01 1.14627101e-01 -1.12728918e+00 -4.82093304e-01
-1.90999597e-01 4.10770208e-01 4.23792660e-01 4.24406797e-01
-1.19876361e+00 1.00930500e+00 6.18120861e+00 6.07973874e-01
-1.10014939e+00 -1.85649410e-01 1.05000305e+00 -2.26039931e-01
-1.22186810e-01 1.87701324e-03 -8.08511972e-01 5.09265006e-01
1.33755159e+00 2.43682787e-01 -4.56568040e-02 5.30485809e-01
2.90896356e-01 1.69195145e-01 -6.88809156e-01 5.62776923e-01
-3.86273682e-01 -1.70099354e+00 -2.86773243e-03 2.61842042e-01
6.50404751e-01 5.88804126e-01 4.60158177e-02 7.52931982e-02
4.43123609e-01 -1.22937536e+00 1.64374011e-04 4.78962600e-01
7.63671577e-01 -1.42499161e+00 8.65651846e-01 1.71714261e-01
-1.03452194e+00 2.70358831e-01 -4.20544684e-01 4.33392040e-02
-1.34568602e-01 7.05248952e-01 -7.63854206e-01 4.51251924e-01
6.06469214e-01 9.15218949e-01 -3.42953861e-01 6.16651952e-01
-2.25257218e-01 7.09602714e-01 -2.68571656e-02 -2.34373242e-01
4.37440634e-01 -4.49502349e-01 -7.22478628e-02 1.36558044e+00
-3.25110316e-01 2.59114414e-01 1.74130589e-01 5.76361775e-01
-3.34749579e-01 4.01514292e-01 -1.68241173e-01 1.88297909e-02
1.32511497e-01 1.16507471e+00 -4.17106181e-01 -1.33328602e-01
-4.90921646e-01 9.08976912e-01 7.76899874e-01 3.97109181e-01
-9.81567562e-01 -8.73926878e-01 1.11433089e+00 -4.28951710e-01
3.57223272e-01 4.02522907e-02 1.77753702e-01 -1.21139872e+00
-1.83299720e-01 -1.13184440e+00 3.16321015e-01 -3.57583940e-01
-1.35653031e+00 5.39261818e-01 -8.46782327e-01 -7.22231746e-01
2.53392458e-02 -8.49983394e-01 -4.50200438e-01 9.39951301e-01
-1.51289153e+00 -1.16937196e+00 2.32074797e-01 7.39905238e-02
3.63389969e-01 -9.44132805e-02 9.56258416e-01 -1.21525981e-01
-8.10471296e-01 5.10965943e-01 8.26666296e-01 -7.80768692e-02
1.01546252e+00 -1.37359869e+00 7.92328060e-01 4.87272084e-01
-2.40584210e-01 1.08278394e+00 6.09901071e-01 -6.38474405e-01
-1.40547049e+00 -1.25811112e+00 9.14842606e-01 -1.20833732e-01
6.40275180e-01 -3.60743284e-01 -1.22884142e+00 5.23195326e-01
1.80253088e-01 1.78459678e-02 1.21869874e+00 2.86924750e-01
-4.19322878e-01 1.03578739e-01 -8.64783466e-01 3.29756200e-01
1.05362749e+00 -5.99844158e-01 -4.54753131e-01 4.69307870e-01
7.57585108e-01 -3.79014194e-01 -1.06369126e+00 5.81158876e-01
7.67599463e-01 -1.06754327e+00 9.31470156e-01 -1.10429156e+00
5.33146858e-01 -1.21394515e-01 -1.27140442e-02 -1.10705793e+00
-6.36335194e-01 -5.53182960e-01 3.48802172e-02 5.50148904e-01
7.71769524e-01 -7.14023054e-01 9.33170676e-01 6.66141734e-02
-3.49115908e-01 -1.34506178e+00 -7.38339901e-01 -2.60179758e-01
4.60514873e-01 2.39432722e-01 3.86989325e-01 5.93294561e-01
5.37671000e-02 6.63999438e-01 -2.86662698e-01 -1.96864426e-01
2.28147641e-01 6.14530444e-01 4.17806059e-01 -1.06609774e+00
-2.73569614e-01 -5.76078892e-02 -1.49869069e-01 -1.19862139e+00
4.62331176e-01 -8.69229615e-01 -6.89545646e-02 -1.31804240e+00
7.20042109e-01 1.08742140e-01 -1.16039467e+00 5.66644371e-01
-5.25072217e-01 2.69967496e-01 -2.76208997e-01 -4.13217302e-03
-9.83830810e-01 8.25672567e-01 9.79987800e-01 -8.12030360e-02
-2.61922389e-01 -2.79119849e-01 -5.86687148e-01 3.33393097e-01
1.02572286e+00 -4.21343178e-01 1.52003704e-04 -4.02348191e-02
3.74690354e-01 -1.91526562e-01 8.49353522e-02 -7.62697220e-01
-1.94661081e-01 -1.75897330e-01 6.99864566e-01 -7.51577556e-01
1.74892172e-01 -2.65090853e-01 -4.66930047e-02 8.64311516e-01
-6.68291509e-01 1.92531899e-01 9.31116343e-02 7.27048039e-01
-1.67975977e-01 3.32732350e-01 7.76628911e-01 6.22775182e-02
-3.80856782e-01 3.66659343e-01 -6.51099682e-01 -1.81863561e-01
8.17901611e-01 1.80754557e-01 -3.92134547e-01 2.00863346e-01
-6.76265717e-01 9.92780179e-02 5.86134553e-01 4.76612858e-02
6.19061530e-01 -9.01424885e-01 -6.78565443e-01 1.56897485e-01
2.86514610e-01 -3.86627346e-01 4.60125387e-01 8.30041051e-01
-8.64620984e-01 8.33927512e-01 -3.36271554e-01 -5.15626371e-01
-1.46730816e+00 4.01552528e-01 4.35061544e-01 -3.49950343e-01
-5.51659405e-01 7.83784330e-01 3.90908450e-01 -5.59798419e-01
-9.57503393e-02 -4.25465524e-01 -9.55128521e-02 -3.03108960e-01
5.10044754e-01 6.99040890e-02 3.74662220e-01 -5.04551649e-01
-5.69251597e-01 4.46111470e-01 -6.50504768e-01 5.09186804e-01
1.60527360e+00 3.43708456e-01 -8.44630077e-02 1.89233497e-01
1.50499976e+00 -3.26344341e-01 -1.46877456e+00 -2.29387090e-01
1.24638632e-01 1.90560207e-01 -3.82558778e-02 -1.20662045e+00
-4.57477987e-01 9.57439482e-01 7.01202631e-01 -5.44917703e-01
1.03494143e+00 -2.25415140e-01 1.04932523e+00 9.06666934e-01
1.49955288e-01 -8.58600080e-01 -1.41864598e-01 8.15167069e-01
4.95846421e-01 -1.52919912e+00 -6.64267838e-02 1.12683840e-01
-5.21384597e-01 1.18234456e+00 5.22953033e-01 -1.29002124e-01
2.12029248e-01 4.09775786e-02 2.88770646e-01 -2.46716052e-01
-1.19247353e+00 1.10009857e-01 1.47053614e-01 1.91516578e-01
1.21517849e+00 6.29676357e-02 -6.74424887e-01 7.09919393e-01
1.49425045e-01 -5.76687157e-02 1.66270211e-01 1.08540559e+00
-6.09943628e-01 -1.26872039e+00 1.82808802e-01 4.03423846e-01
-9.73759353e-01 -4.47146624e-01 -7.78242409e-01 2.62761831e-01
-2.69402474e-01 8.33211064e-01 -3.80934864e-01 -2.52665609e-01
6.91018328e-02 1.16936550e-01 3.82501662e-01 -4.12233084e-01
-9.98966336e-01 1.52291059e-01 -1.29692882e-01 -7.78034449e-01
-3.00209224e-01 -3.95571649e-01 -1.68745780e+00 -7.23848715e-02
-2.60283887e-01 3.61242324e-01 4.81642008e-01 8.10294807e-01
9.85051334e-01 5.75208545e-01 5.80760121e-01 -4.95128810e-01
-6.08290792e-01 -1.15640926e+00 -3.03348452e-01 2.96869963e-01
5.96687675e-01 -2.78512597e-01 1.30095825e-01 -6.92118481e-02] | [4.7120137214660645, 5.635164737701416] |
0a28149e-2a86-4619-b6b9-a9f9dab9df29 | chemellia-an-ecosystem-for-atomistic | 2305.12010 | null | https://arxiv.org/abs/2305.12010v1 | https://arxiv.org/pdf/2305.12010v1.pdf | Chemellia: An Ecosystem for Atomistic Scientific Machine Learning | Chemellia is an open-source framework for atomistic machine learning in the Julia programming language. The framework takes advantage of Julia's high speed as well as the ability to share and reuse code and interfaces through the paradigm of multiple dispatch. Chemellia is designed to make use of existing interfaces and avoid ``reinventing the wheel'' wherever possible. A key aspect of the Chemellia ecosystem is the ChemistryFeaturization interface for defining and encoding features -- it is designed to maximize interoperability between featurization schemes and elements thereof, to maintain provenance of encoded features, and to ensure easy decodability and reconfigurability to enable feature engineering experiments. This embodies the overall design principles of the Chemellia ecosystem: separation of concerns, interoperability, and transparency. We illustrate these principles by discussing the implementation of crystal graph convolutional neural networks for material property prediction. | ['Rachel C. Kurchin', 'Venkatasubramanian Viswanathan', 'Dhairya Gandhi', 'Anant Thazhemadam'] | 2023-05-19 | null | null | null | null | ['property-prediction', 'feature-engineering'] | ['medical', 'methodology'] | [-1.88309163e-01 7.89932013e-02 -2.06820928e-02 -3.10417295e-01
-3.11576933e-01 -6.25052273e-01 6.12085402e-01 4.98982787e-01
-2.28536993e-01 6.75761700e-01 3.44929174e-02 -5.04128933e-01
-2.18685955e-01 -1.20077980e+00 -8.08366597e-01 -6.09037638e-01
-1.75818801e-01 2.75122732e-01 6.19062148e-02 -3.31342965e-01
2.11345986e-01 8.37075293e-01 -1.86762047e+00 4.90426064e-01
5.85467279e-01 7.87445009e-01 5.26062101e-02 5.20218253e-01
-5.00512160e-02 7.86587596e-01 -1.37454554e-01 -2.22839236e-01
2.41140291e-01 -3.15828174e-02 -1.14575779e+00 -5.85179746e-01
3.15151483e-01 -9.66042653e-03 -1.45964593e-01 5.06761730e-01
4.28579062e-01 -2.11063772e-01 5.11329830e-01 -1.25062633e+00
-8.83172750e-01 3.85863006e-01 1.51162162e-01 -3.08652312e-01
2.78241366e-01 7.17490852e-01 1.15835655e+00 -6.64629400e-01
9.47660208e-01 8.69469047e-01 7.45601356e-01 5.59012651e-01
-1.40101182e+00 -6.30743563e-01 -1.87357679e-01 6.67223632e-02
-1.27901816e+00 -8.54407728e-01 1.73643872e-01 -7.62530506e-01
1.77684009e+00 2.94461638e-01 7.48974919e-01 8.35986137e-01
7.06008971e-01 2.02530563e-01 6.69396996e-01 -3.47235560e-01
4.41286087e-01 -5.42400032e-02 2.60967761e-01 8.44564736e-01
6.55914962e-01 2.51254708e-01 -7.92331338e-01 -5.11385560e-01
4.45493639e-01 4.53130119e-02 -1.77123607e-03 -7.58631110e-01
-9.78606343e-01 4.97661680e-01 4.18673158e-01 6.19470999e-02
-2.82988727e-01 5.33647716e-01 4.25329208e-01 3.28112483e-01
-3.01492903e-02 1.02935159e+00 -7.30109990e-01 -2.51891464e-01
-4.45743918e-01 5.80591559e-01 8.00256252e-01 1.03874707e+00
9.70236301e-01 -6.63029999e-02 2.31232658e-01 3.11817080e-01
5.93718529e-01 9.95064229e-02 2.02125132e-01 -8.63662302e-01
-5.06671593e-02 6.47713900e-01 1.14838347e-01 -4.29882228e-01
-6.08270168e-01 -4.63838607e-01 -1.25596404e-01 1.00462961e+00
1.57362103e-01 1.29332110e-01 -6.80236220e-01 1.55004847e+00
2.84955442e-01 -6.23832107e-01 2.34851897e-01 3.94611329e-01
1.01497698e+00 3.51411551e-01 3.24789047e-01 3.39467525e-01
1.03168786e+00 -6.28122509e-01 -9.40856114e-02 1.49221152e-01
9.51040387e-01 -6.17622614e-01 8.52303267e-01 4.16671783e-01
-1.14453626e+00 -3.88159424e-01 -1.58252430e+00 -4.60013270e-01
-9.06393349e-01 -3.97742718e-01 1.12690556e+00 7.75943875e-01
-9.13599432e-01 1.16275120e+00 -7.28355229e-01 -1.16355896e-01
4.96507168e-01 6.32174492e-01 -7.17284679e-01 2.14101300e-01
-1.04089642e+00 9.07944798e-01 5.22911668e-01 -2.71465451e-01
-6.52847350e-01 -1.12324178e+00 -7.96988010e-01 1.45469829e-01
-2.96360459e-02 -8.97631288e-01 1.21259606e+00 -8.36682379e-01
-1.22442102e+00 6.97495103e-01 3.21500242e-01 -2.59058505e-01
2.74191201e-01 -5.41854762e-02 -4.49222594e-01 -3.35261405e-01
-6.45759255e-02 5.87668478e-01 2.77149022e-01 -9.26127195e-01
-4.38704699e-01 -1.04034886e-01 -2.33891159e-02 -1.92047328e-01
-1.19000942e-01 -3.40911776e-01 9.21623141e-04 -1.35085255e-01
-2.97272712e-01 -7.06732094e-01 -8.82179365e-02 3.06867987e-01
-2.12917387e-01 8.39632377e-02 8.39252889e-01 -2.55473644e-01
8.91296208e-01 -1.92889738e+00 8.48953705e-03 5.12102544e-01
6.97489798e-01 1.16701499e-01 -9.72472355e-02 9.64241982e-01
-3.02479535e-01 2.92057931e-01 -9.92660299e-02 1.84195057e-01
1.36394218e-01 -1.17772549e-01 2.34548762e-01 5.41453063e-01
2.79605478e-01 8.29486728e-01 -8.28468800e-01 9.38949059e-04
2.46095791e-01 5.89137137e-01 -8.33343923e-01 -9.37019363e-02
-8.46035242e-01 2.47891277e-01 -4.05355930e-01 8.46951723e-01
6.92746818e-01 -3.33443195e-01 4.71349120e-01 -2.37229586e-01
-9.37017262e-01 7.50254512e-01 -9.99948561e-01 1.77989781e+00
-3.30150425e-01 2.26626396e-01 2.97336549e-01 -9.35571715e-02
8.09184730e-01 1.54450387e-01 6.91096365e-01 -6.76941812e-01
-2.93775424e-02 4.23309416e-01 1.23302236e-01 -4.22833741e-01
4.59343582e-01 1.55280113e-01 7.20862597e-02 7.29012668e-01
-1.76546853e-02 -9.91698429e-02 1.34268314e-01 2.19927654e-01
1.05512249e+00 9.39967871e-01 4.16063249e-01 -5.88371813e-01
2.19954699e-01 1.93434820e-01 2.77176380e-01 4.92859960e-01
1.33568197e-01 2.11471468e-01 2.35889122e-01 -7.45115399e-01
-1.43499792e+00 -9.60374594e-01 -4.30613637e-01 9.89317536e-01
-4.05201435e-01 -1.10401642e+00 -5.20799518e-01 -4.20914233e-01
4.12183940e-01 6.22589827e-01 -7.39423752e-01 -2.92090416e-01
-1.07008725e-01 -6.71595752e-01 2.44537145e-01 2.26609573e-01
2.92079687e-01 -1.07668638e+00 -8.80981266e-01 3.18758786e-01
5.80757916e-01 -2.42946103e-01 -8.33690539e-03 4.13455069e-01
-1.58164218e-01 -1.28311336e+00 1.79328665e-01 -4.22044277e-01
6.18366748e-02 1.07288606e-01 1.36255515e+00 2.95049787e-01
-6.66493118e-01 2.47389838e-01 -1.99787512e-01 -3.40942055e-01
-8.06236625e-01 3.68117332e-01 -2.58052140e-01 -5.77126920e-01
4.48055208e-01 -1.00626421e+00 -8.00793767e-01 -1.98339269e-01
-1.05681241e+00 3.77152383e-01 3.79922211e-01 6.43535256e-01
4.10681486e-01 -2.97220975e-01 3.81028056e-01 -9.06994820e-01
4.29145604e-01 -4.52282637e-01 -8.38571727e-01 3.18573087e-01
-1.24741149e+00 3.70139837e-01 6.78986847e-01 3.84106368e-01
-6.01845682e-01 2.45123863e-01 -3.11245799e-01 2.28439122e-01
-6.80725425e-02 5.16014218e-01 -6.25410736e-01 -4.11452919e-01
6.75170720e-01 -9.49400067e-02 3.32242072e-01 -4.64781433e-01
7.73113668e-01 7.93842852e-01 2.70278573e-01 -1.13400817e+00
3.73242140e-01 2.92228281e-01 1.66520476e-01 -6.96747959e-01
2.02510785e-02 8.97799954e-02 -5.99189579e-01 -8.73018503e-02
6.71218276e-01 -7.62373805e-01 -1.40467095e+00 4.19076979e-01
-8.97333324e-01 -2.19348431e-01 -4.09059554e-01 -2.89897360e-02
-4.94286150e-01 2.36716524e-01 -3.00830811e-01 -2.25703552e-01
-7.14563906e-01 -1.50920343e+00 5.67893386e-01 1.04708046e-01
-6.32829905e-01 -6.25249207e-01 2.48224750e-01 2.35405359e-02
7.18061686e-01 6.14468992e-01 1.35870183e+00 -4.87307698e-01
-8.08144629e-01 -4.59071286e-02 -1.13432124e-01 -2.85166204e-02
3.67767036e-01 4.73181069e-01 -1.07529986e+00 -3.08718324e-01
-6.34459138e-01 -4.54554528e-01 5.83794713e-01 -1.95983306e-01
8.45287263e-01 -2.04868376e-01 -2.96140701e-01 7.02173829e-01
1.45983601e+00 2.28136852e-01 6.24769568e-01 7.90832698e-01
7.65352666e-01 5.14104307e-01 -6.66365176e-02 5.29681504e-01
2.42590472e-01 5.83015203e-01 7.56786585e-01 1.01830494e-02
-8.54360461e-02 -1.31607562e-01 1.51549652e-01 5.03011644e-01
2.02182978e-02 7.95273632e-02 -1.03295052e+00 7.74993673e-02
-1.80981874e+00 -9.15466130e-01 -3.14711362e-01 2.25778270e+00
8.36256385e-01 -1.08338699e-01 6.85164034e-02 -2.10922152e-01
1.01882860e-01 -2.86540370e-02 -7.87858844e-01 -8.30345511e-01
9.68607515e-02 5.81181884e-01 6.09823048e-01 4.44635659e-01
-6.88273728e-01 8.77619088e-01 7.26434374e+00 3.48906279e-01
-1.13223040e+00 8.12861547e-02 3.42045188e-01 -1.84070528e-01
-7.02344418e-01 2.59653747e-01 -6.16906881e-01 3.31688106e-01
9.89715934e-01 -1.33263439e-01 6.83500946e-01 8.28586221e-01
1.86778158e-01 3.04363847e-01 -1.24904871e+00 4.04314935e-01
-5.07745981e-01 -2.34261370e+00 1.21635221e-01 1.44516900e-01
3.03509116e-01 4.67449993e-01 -1.25911593e-01 -1.59032032e-01
6.36163414e-01 -1.29828417e+00 1.09112239e+00 6.06071532e-01
7.57677555e-01 -9.46736038e-01 6.60940930e-02 -3.65215749e-01
-9.83393669e-01 2.81014472e-01 -1.36280492e-01 -1.63268119e-01
-3.01569581e-01 3.78676951e-01 -5.26741683e-01 6.74042821e-01
6.19373322e-01 6.51986599e-01 -3.82417083e-01 9.29624081e-01
2.36360297e-01 2.96687670e-02 -1.73077971e-01 1.13938637e-02
9.08207893e-02 -2.66965777e-01 1.02677897e-01 1.20648444e+00
-1.29155554e-02 -4.92508888e-01 8.77102837e-02 1.22921574e+00
-2.92155631e-02 8.38689283e-02 -4.49402750e-01 -3.01721931e-01
7.04442680e-01 1.00993013e+00 -4.35608625e-01 1.92981549e-02
-6.20986462e-01 5.80100417e-01 3.73248965e-01 4.68898527e-02
-5.83808422e-01 -6.67990863e-01 1.25213003e+00 3.64069432e-01
3.94791603e-01 -4.14729148e-01 -4.02633101e-01 -6.73385024e-01
-2.54035741e-01 -1.12564337e+00 8.29630569e-02 -7.75066614e-01
-9.98527706e-01 3.48047853e-01 -2.31289834e-01 -6.27951860e-01
1.32891849e-01 -1.05718708e+00 -4.51628327e-01 9.30987239e-01
-1.14680600e+00 -1.49030256e+00 -1.62779726e-02 2.15873450e-01
-2.64875263e-01 -1.70524195e-01 1.14166367e+00 7.76016116e-02
-4.88109529e-01 3.47585469e-01 5.44396222e-01 -5.49294293e-01
5.34685552e-01 -1.17444015e+00 9.05763388e-01 3.94211054e-01
-4.01495606e-01 1.14314365e+00 7.91610658e-01 -6.63707376e-01
-1.91021430e+00 -1.05625570e+00 5.11710525e-01 -3.61830682e-01
6.82824850e-01 -5.87561965e-01 -7.12351680e-01 5.72078168e-01
2.16449633e-01 -3.09192359e-01 9.73527551e-01 2.61961043e-01
-8.77359927e-01 -1.50054082e-01 -1.19873214e+00 6.12102747e-01
1.01291275e+00 -6.24010623e-01 9.86872241e-03 4.87658441e-01
6.87769592e-01 -9.74414498e-02 -1.43643320e+00 1.33187026e-01
1.00120056e+00 -1.17576313e+00 1.02735150e+00 -6.13314331e-01
3.82836878e-01 -5.05931079e-01 -1.83469921e-01 -8.23697448e-01
-6.87156618e-01 -1.06422102e+00 6.66882982e-03 1.12629032e+00
8.35645378e-01 -1.06908679e+00 7.34488487e-01 9.05074358e-01
-4.51920807e-01 -6.51308239e-01 -7.46520162e-01 -6.70532882e-01
5.23830414e-01 -3.43231440e-01 1.44075799e+00 9.07494605e-01
2.99760818e-01 1.89382687e-01 -1.02310777e-01 -7.48170838e-02
2.32059121e-01 1.07567944e-01 8.91657472e-01 -1.22087133e+00
-7.96153784e-01 -4.39581931e-01 -4.39829201e-01 -3.30616146e-01
-1.73910856e-01 -1.31494498e+00 -3.53702694e-01 -1.45189822e+00
2.99629509e-01 -6.71027958e-01 -3.56073260e-01 9.31033075e-01
5.88786840e-01 -5.31285070e-02 1.20192006e-01 4.04210836e-01
-4.01202470e-01 4.43413347e-01 1.03372777e+00 -3.32600065e-02
-1.63579822e-01 -6.52438045e-01 -1.01099467e+00 7.51325339e-02
7.68250585e-01 -5.34446478e-01 -3.12166542e-01 -2.44672284e-01
6.97596788e-01 -7.33034432e-01 4.43846911e-01 -1.23918080e+00
-1.01661310e-01 -3.23572218e-01 3.39767128e-01 -2.66832262e-01
2.99238831e-01 -7.30827034e-01 8.66605341e-01 6.47165954e-01
-2.51740396e-01 5.67760989e-02 2.65824467e-01 2.31064290e-01
4.40918952e-01 -1.29286960e-01 7.70047426e-01 -4.51428145e-01
-3.91331762e-01 4.20302361e-01 -5.41558027e-01 -4.09211099e-01
1.11353338e+00 -2.46194869e-01 -9.06982422e-01 2.51271069e-01
-4.50649858e-01 1.13358386e-01 1.55107093e+00 2.79416174e-01
1.70330107e-01 -1.05198848e+00 -1.21417373e-01 6.14038408e-01
6.23285413e-01 -1.18769735e-01 -8.39628000e-03 2.31820300e-01
-1.03086996e+00 4.07014906e-01 -3.93278122e-01 2.90770456e-02
-1.02690458e+00 5.29377699e-01 7.93545425e-01 8.03768188e-02
-7.50443757e-01 4.87901092e-01 -1.30837604e-01 -4.41105068e-01
-2.16502324e-01 -2.68886864e-01 4.38224912e-01 -4.70712274e-01
4.06143069e-01 5.43723144e-02 5.75130463e-01 -3.82980913e-01
-5.08758485e-01 1.04697071e-01 -4.89939660e-01 3.90696749e-02
1.73685455e+00 3.66960645e-01 -4.34102654e-01 1.35038674e-01
1.04979193e+00 8.71102288e-02 -1.40469372e+00 3.77674490e-01
-1.14394668e-02 -1.25694117e-02 1.97063759e-01 -1.25068438e+00
-6.24976397e-01 4.43495065e-01 6.52829289e-01 3.06240991e-02
2.94506907e-01 -1.20518863e-01 6.57437980e-01 5.47582805e-01
3.96811336e-01 -9.34509635e-01 -4.21989560e-01 3.60641390e-01
7.15906858e-01 -5.59125423e-01 4.57831621e-01 -2.54942268e-01
2.93089636e-02 1.38214958e+00 3.96577835e-01 2.37213135e-01
6.07256770e-01 3.47726524e-01 -7.57748932e-02 -7.83156276e-01
-8.88026714e-01 6.88403696e-02 -2.27120265e-01 9.11610603e-01
8.70052516e-01 1.24589704e-01 -9.38252807e-02 3.41281921e-01
-1.73676297e-01 1.49827406e-01 3.86149645e-01 1.59316576e+00
-6.04581237e-01 -1.83314228e+00 -2.84568220e-01 2.84784675e-01
-2.20595598e-01 -2.63807774e-01 -6.50905311e-01 8.89941394e-01
5.34287393e-01 5.92164934e-01 -2.02767119e-01 -3.78289551e-01
1.87273756e-01 2.46655434e-01 5.89533269e-01 -4.51133847e-01
-9.52778757e-01 -4.77571428e-01 4.30172056e-01 -5.72107852e-01
-1.69878319e-01 -6.00697339e-01 -1.35640109e+00 -7.91984022e-01
-1.67032093e-01 3.55367750e-01 1.01495051e+00 8.00577998e-01
1.15288413e+00 5.33231139e-01 3.10874730e-01 -8.37805927e-01
-1.06646933e-01 -3.73741180e-01 -3.95466655e-01 8.07769224e-02
9.87625644e-02 -5.17678082e-01 2.01828539e-01 -2.28905007e-01] | [5.113016605377197, 5.551919937133789] |
547fd164-4637-465a-afd7-650a27774bb2 | dialogue-act-classification-with-context | 1904.02594 | null | https://arxiv.org/abs/1904.02594v2 | https://arxiv.org/pdf/1904.02594v2.pdf | Dialogue Act Classification with Context-Aware Self-Attention | Recent work in Dialogue Act classification has treated the task as a sequence labeling problem using hierarchical deep neural networks. We build on this prior work by leveraging the effectiveness of a context-aware self-attention mechanism coupled with a hierarchical recurrent neural network. We conduct extensive evaluations on standard Dialogue Act classification datasets and show significant improvement over state-of-the-art results on the Switchboard Dialogue Act (SwDA) Corpus. We also investigate the impact of different utterance-level representation learning methods and show that our method is effective at capturing utterance-level semantic text representations while maintaining high accuracy. | ['Joel Tetreault', 'Vipul Raheja'] | 2019-04-04 | dialogue-act-classification-with-context-2 | https://aclanthology.org/N19-1373 | https://aclanthology.org/N19-1373.pdf | naacl-2019-6 | ['dialogue-act-classification'] | ['natural-language-processing'] | [ 5.34052908e-01 5.56463182e-01 -1.56135365e-01 -7.11526811e-01
-7.69077599e-01 -3.03949833e-01 1.13788700e+00 2.71953613e-01
-4.29921895e-01 6.85266852e-01 1.17796826e+00 -3.97750288e-01
4.76155251e-01 -5.48829079e-01 -1.08744518e-03 -2.55095124e-01
8.52967724e-02 8.75795186e-01 1.44873098e-01 -9.94772077e-01
3.63154888e-01 -1.59243703e-01 -1.03821504e+00 7.34080315e-01
5.77796459e-01 8.50523710e-01 -4.33988363e-01 9.97234464e-01
-3.04653317e-01 1.80661356e+00 -1.12413144e+00 -2.05814004e-01
-5.49169555e-02 -8.05982292e-01 -1.69083178e+00 2.52971470e-01
1.96394965e-01 -6.94950163e-01 -5.24096787e-01 4.10007775e-01
4.27618831e-01 6.59047723e-01 6.04538560e-01 -6.76703870e-01
-5.64828038e-01 7.19972312e-01 -6.09962009e-02 2.88060755e-01
7.00689197e-01 1.28521428e-01 1.41104412e+00 -3.67951721e-01
5.20246446e-01 1.43847632e+00 6.61548257e-01 9.44900632e-01
-1.34153199e+00 -1.02541633e-01 2.46624082e-01 1.39688119e-01
-5.20273924e-01 -8.10380816e-01 8.11165392e-01 -1.63271770e-01
1.91946304e+00 4.15801629e-02 3.72220099e-01 1.35853732e+00
4.22605732e-03 1.36068833e+00 9.64722633e-01 -7.44717956e-01
2.45902672e-01 -4.99706149e-01 7.72736490e-01 7.11646914e-01
-8.04559112e-01 -2.38134235e-01 -4.09587115e-01 -1.90789714e-01
5.11230350e-01 -1.81965768e-01 -5.96900508e-02 1.03351690e-01
-4.58658338e-01 1.30423868e+00 3.35319251e-01 5.34149468e-01
-4.35843319e-01 1.12741902e-01 1.14427638e+00 4.97107714e-01
9.02438641e-01 7.27557421e-01 -6.48129225e-01 -8.13963354e-01
-3.59746456e-01 2.86261737e-01 1.24641144e+00 5.82805753e-01
2.77223945e-01 3.06846708e-01 -6.03188634e-01 1.44043994e+00
1.19241193e-01 -3.67838949e-01 9.16949511e-01 -1.08773398e+00
4.92440939e-01 7.81166613e-01 -1.00720100e-01 -2.87144154e-01
-6.28130794e-01 1.57723367e-01 -4.09701109e-01 -4.79467735e-02
2.17957377e-01 -4.73817378e-01 -8.71169925e-01 1.62175190e+00
1.97710260e-03 -1.75202221e-01 4.47447717e-01 5.88390529e-01
8.80022168e-01 7.89851010e-01 5.24350047e-01 -1.46339253e-01
1.25517011e+00 -1.61068463e+00 -1.06923783e+00 -3.31948549e-01
1.06031156e+00 -1.62377760e-01 1.09223723e+00 1.63226888e-01
-1.39848185e+00 -3.05803627e-01 -1.09559357e+00 -4.32678670e-01
-3.24816287e-01 -1.17894672e-01 6.84557617e-01 5.72950900e-01
-1.13580060e+00 4.41001892e-01 -7.62476861e-01 -4.22379404e-01
1.92680106e-01 2.43926123e-01 -1.09904729e-01 2.53330529e-01
-1.44358408e+00 1.37941670e+00 4.59676117e-01 -8.63896683e-02
-8.89355004e-01 -3.78286660e-01 -1.24305224e+00 1.80609822e-01
3.36239398e-01 -4.80695575e-01 2.19098210e+00 -8.59083235e-01
-2.44180155e+00 6.68402493e-01 -1.57662839e-01 -9.97509718e-01
1.41440988e-01 -3.74335468e-01 -7.80171230e-02 2.46970043e-01
-2.17705056e-01 5.46064734e-01 4.13095415e-01 -8.52496743e-01
-6.19058907e-01 -3.37527543e-01 5.82949698e-01 8.32812309e-01
-3.61388326e-01 2.11687878e-01 1.57118544e-01 -4.50909019e-01
-3.99214864e-01 -8.87910843e-01 -3.90485168e-01 -9.26266849e-01
-1.28629684e-01 -9.90964413e-01 8.56108248e-01 -7.83615947e-01
1.23630297e+00 -1.74617457e+00 2.71387339e-01 -6.43515468e-01
2.51551479e-01 4.17937577e-01 -2.89429966e-02 7.24490762e-01
-8.23847204e-03 1.40302582e-02 -3.19085330e-01 -7.76650846e-01
1.53625131e-01 2.76602954e-01 -1.81578830e-01 2.20360383e-01
1.74968898e-01 1.01957166e+00 -8.08832288e-01 -1.90069929e-01
5.62955379e-01 1.29570559e-01 -4.84369427e-01 7.42173314e-01
-6.22404277e-01 1.85037211e-01 -3.63414049e-01 2.34276801e-01
-2.16822073e-01 -2.23917842e-01 5.15181839e-01 1.96258903e-01
1.03356406e-01 1.29827368e+00 -3.22620310e-02 1.89749992e+00
-9.08013701e-01 7.32009649e-01 7.31622204e-02 -1.21173680e+00
8.83583188e-01 7.41794109e-01 4.62812483e-01 -7.79156864e-01
2.62236148e-01 -2.95797139e-01 1.57919079e-01 -2.35306785e-01
8.21323931e-01 -4.39532727e-01 -3.88038069e-01 8.45249295e-01
3.91750813e-01 -1.86110675e-01 4.28510830e-02 3.69284868e-01
1.47741497e+00 1.94713429e-01 6.21408165e-01 -5.90681285e-02
4.98773336e-01 -2.49297682e-05 1.19259536e-01 7.50352561e-01
-5.05294263e-01 3.05718243e-01 6.07536614e-01 -5.72253942e-01
-8.93167436e-01 -4.13263798e-01 1.11029059e-01 2.02754259e+00
-4.03333008e-01 -6.84854805e-01 -8.35113168e-01 -1.13651752e+00
-4.00698215e-01 1.07741618e+00 -8.83821487e-01 -1.11575678e-01
-8.16565752e-01 -6.10044003e-01 8.93219888e-01 8.01610768e-01
7.86453605e-01 -1.46748984e+00 -7.09464729e-01 4.87626344e-01
-2.73860335e-01 -1.17920971e+00 -1.52444974e-01 3.30790073e-01
-6.01872027e-01 -8.14982951e-01 -2.92963207e-01 -7.25567877e-01
1.00442745e-01 5.87511659e-02 1.45292699e+00 1.47928864e-01
6.68856576e-02 4.92988467e-01 -8.07453573e-01 -1.98126212e-01
-8.54562521e-01 4.86609548e-01 -3.30313742e-01 -3.96611869e-01
4.90054399e-01 -2.62337416e-01 -4.22341414e-02 6.61147311e-02
-6.08957350e-01 1.03517093e-01 -6.66372925e-02 1.22043836e+00
-5.29892445e-01 -3.46479565e-01 8.37402225e-01 -1.13663769e+00
1.32737970e+00 -3.75128061e-01 -5.25135808e-02 7.74862394e-02
-4.09510523e-01 1.37239456e-01 5.86932063e-01 1.69519484e-01
-1.60744715e+00 -7.26425648e-02 -6.12610638e-01 2.08237380e-01
-5.10031343e-01 4.18057084e-01 2.04436690e-01 3.72514158e-01
7.47611165e-01 1.05861522e-01 2.07746163e-01 -2.60022074e-01
5.79531610e-01 9.04847324e-01 1.99135050e-01 -5.84625304e-01
-1.53635845e-01 4.24997173e-02 -4.63153362e-01 -1.09279978e+00
-1.08601093e+00 -5.86433232e-01 -6.78980708e-01 -1.04770102e-01
1.18238103e+00 -6.90435588e-01 -8.73830616e-01 4.93776202e-01
-1.22440958e+00 -8.65408659e-01 -2.11934566e-01 -1.25374883e-01
-9.15118277e-01 4.73831683e-01 -1.61688745e+00 -1.07740319e+00
-5.76095641e-01 -1.04220617e+00 1.07962859e+00 -1.92089882e-02
-7.25764930e-01 -1.49383724e+00 3.45451295e-01 8.12429905e-01
4.65113729e-01 -1.06431030e-01 9.37117457e-01 -1.46377087e+00
1.20696627e-01 -1.35964558e-01 -3.99897285e-02 2.25978911e-01
2.17467263e-01 -4.93062258e-01 -1.01518035e+00 -7.32606684e-04
3.29896241e-01 -1.24171853e+00 9.50042963e-01 2.28303283e-01
7.32512832e-01 -6.40453935e-01 9.15633440e-02 -6.94257915e-02
6.77963912e-01 4.07876790e-01 6.17224932e-01 3.09662431e-01
5.06052434e-01 8.18234622e-01 4.75399673e-01 4.74029481e-01
6.50335491e-01 9.02540326e-01 1.58574358e-01 -1.38707936e-01
2.33896691e-02 -1.55242190e-01 3.62876326e-01 7.04372644e-01
8.77019912e-02 -3.46350342e-01 -1.07482445e+00 4.62084591e-01
-2.16797590e+00 -9.43742275e-01 2.44976878e-01 1.49793434e+00
1.17626262e+00 1.71570823e-01 5.09359002e-01 -2.61878278e-02
3.52092505e-01 7.32236147e-01 -2.87436575e-01 -9.85228062e-01
2.14631215e-01 3.31724465e-01 1.42698372e-02 9.37634885e-01
-1.49193358e+00 1.42209816e+00 7.53194666e+00 4.27523762e-01
-5.93713939e-01 2.62984097e-01 7.97564089e-01 1.12106860e-01
1.74416393e-01 -2.85310805e-01 -6.33686662e-01 5.64208254e-02
1.46728468e+00 -6.70588091e-02 2.29401663e-01 7.95231819e-01
-7.59332553e-02 7.44907930e-02 -1.13375831e+00 3.65813941e-01
4.06708211e-01 -1.40851140e+00 -1.33628175e-01 2.46212501e-02
5.86640418e-01 1.71312541e-01 -4.97488976e-01 1.02201498e+00
1.19437027e+00 -1.19013846e+00 1.30726472e-02 -7.30074719e-02
2.18118578e-01 -4.30592090e-01 9.68064249e-01 2.49306589e-01
-8.45211208e-01 -2.22279280e-01 -5.28223626e-02 -6.46044672e-01
3.25161338e-01 -3.69796216e-01 -1.49997139e+00 4.54427987e-01
1.32658273e-01 1.06222296e+00 -3.27312320e-01 1.30822405e-01
-3.73016477e-01 9.66680169e-01 -2.65860669e-02 -1.72825143e-01
7.56739438e-01 -1.08143449e-01 2.45475262e-01 1.49965632e+00
-8.07715058e-01 5.79359531e-01 5.86475134e-01 2.31198445e-01
-2.50327915e-01 7.88853988e-02 -6.81901634e-01 -2.41960377e-01
2.02464074e-01 9.17496085e-01 -3.67242366e-01 -6.38199449e-01
-3.56200516e-01 9.97099936e-01 7.36931682e-01 9.60213467e-02
-4.28922892e-01 -7.26141706e-02 6.26571536e-01 -5.08247077e-01
1.47217155e-01 -2.92082727e-01 -3.78358990e-01 -1.03578556e+00
-5.11117995e-01 -1.02217197e+00 6.82005525e-01 -4.34132725e-01
-1.32125700e+00 7.13370085e-01 -1.83178559e-01 -6.40020430e-01
-1.02998233e+00 -5.06760657e-01 -7.62801588e-01 4.97633666e-01
-9.95769858e-01 -1.23579311e+00 7.88135752e-02 3.37845117e-01
1.62113273e+00 -3.56678426e-01 1.39529443e+00 -1.67557254e-01
-5.91393828e-01 3.79977167e-01 -2.28317916e-01 5.69199145e-01
4.24146831e-01 -1.59189630e+00 6.89586520e-01 3.05087626e-01
-1.13997534e-01 4.70620364e-01 5.79095662e-01 -5.85729301e-01
-8.70670080e-01 -5.64819157e-01 6.26383781e-01 -7.45970130e-01
7.77647793e-01 -5.03189445e-01 -1.01640928e+00 1.08953118e+00
9.98606682e-01 -5.78980446e-01 8.64792407e-01 7.88448274e-01
-3.30932289e-01 6.67043149e-01 -8.85107338e-01 5.75677574e-01
8.41618717e-01 -7.28825867e-01 -1.31897414e+00 4.21367049e-01
9.52182710e-01 -4.98699665e-01 -8.74897540e-01 3.82690907e-01
3.87163758e-01 -9.22738552e-01 7.44808137e-01 -1.28880501e+00
8.52130473e-01 5.11237085e-01 -1.73562746e-02 -1.48250329e+00
-1.54394105e-01 -6.46659315e-01 -1.58272237e-01 1.02008629e+00
3.83357525e-01 -3.72712910e-01 7.94345260e-01 9.01190937e-01
-6.69549882e-01 -7.40886807e-01 -9.67103720e-01 -2.89267957e-01
2.51398712e-01 2.50365920e-02 8.16194564e-02 1.15182567e+00
9.23522174e-01 1.42289543e+00 -5.75203001e-01 -7.74789691e-01
-6.39421046e-02 -2.62271374e-01 6.65123165e-01 -9.14588094e-01
-2.32539982e-01 -7.57809281e-01 -3.39430064e-01 -1.44810247e+00
9.06727850e-01 -5.91133773e-01 4.73220319e-01 -1.75074971e+00
-1.88718140e-01 7.75066018e-02 -1.03458717e-01 8.13536644e-01
-3.55099976e-01 -1.18126512e-01 1.80943102e-01 9.54680592e-02
-1.04522610e+00 1.19557381e+00 4.99983072e-01 -2.06919238e-01
-2.62220532e-01 -6.10306673e-02 -4.51950371e-01 7.00029373e-01
8.52163851e-01 1.37475114e-02 -4.39380825e-01 -3.11619610e-01
-4.89291668e-01 4.09481198e-01 -3.84816349e-01 -7.68280685e-01
9.09429565e-02 9.54334289e-02 1.07808076e-02 -3.41653317e-01
8.40895474e-01 -3.33343565e-01 -9.59259093e-01 3.76698732e-01
-1.42819929e+00 -8.35552216e-02 1.93733394e-01 4.72094506e-01
-2.74784833e-01 -3.83248687e-01 6.87107503e-01 -4.08713073e-01
-5.80846429e-01 -3.12165976e-01 -1.01788402e+00 1.99658364e-01
6.95531309e-01 1.25935912e-01 -7.18618572e-01 -9.43173945e-01
-6.54568851e-01 4.69067603e-01 1.14555679e-01 5.72934747e-01
3.87783021e-01 -9.46271837e-01 -7.87550211e-01 -1.39105007e-01
1.33052632e-01 -3.41966897e-01 5.93719333e-02 3.20785165e-01
-3.35979760e-01 7.35715866e-01 -1.79606810e-01 -3.83237898e-01
-1.24919319e+00 1.91740498e-01 5.45348287e-01 -7.58675516e-01
-7.40977824e-01 6.84661627e-01 4.66371588e-02 -7.71518290e-01
3.83961946e-01 6.97826371e-02 -6.20155931e-01 5.73482811e-02
5.12392104e-01 3.09458524e-01 1.26325348e-02 -5.13846397e-01
-6.22071400e-02 -3.16180736e-01 -5.94812870e-01 -4.70121235e-01
1.31227553e+00 -7.95399994e-02 8.04867074e-02 7.96127439e-01
1.02392602e+00 -4.60140944e-01 -1.15557146e+00 -3.98503035e-01
3.83192182e-01 7.90458638e-03 -2.79366355e-02 -1.02532470e+00
-4.36839581e-01 8.15060258e-01 1.11972682e-01 7.59680271e-01
7.37513423e-01 -1.07743144e-01 8.33946347e-01 7.71385491e-01
1.27317771e-01 -1.37144125e+00 5.19527018e-01 1.38397110e+00
8.54288101e-01 -1.34821379e+00 -1.11193091e-01 -9.60451365e-02
-1.20044863e+00 1.07883513e+00 1.01290715e+00 -2.70417064e-01
3.10024977e-01 1.64514288e-01 3.95192444e-01 -3.67723644e-01
-1.29010487e+00 -3.06667358e-01 -1.85388938e-01 3.17676365e-01
1.08415437e+00 -4.67787161e-02 -2.95215189e-01 3.09216976e-01
-7.76434988e-02 -1.83798432e-01 7.01374710e-01 1.28504908e+00
-4.91104513e-01 -1.18224156e+00 2.60517061e-01 3.82344037e-01
-4.95856375e-01 -2.97641277e-01 -1.02371228e+00 5.16406298e-01
-9.58424330e-01 1.36204398e+00 2.36813843e-01 -3.94337445e-01
2.38690615e-01 7.92743802e-01 2.75794715e-01 -1.21488941e+00
-1.29180515e+00 -7.09907711e-02 1.06664038e+00 -5.55137157e-01
-5.84525764e-01 -4.93366063e-01 -1.40698719e+00 -1.09619088e-02
-1.36332139e-01 4.46079999e-01 4.19568747e-01 1.42934024e+00
2.33421475e-01 7.64865220e-01 6.95316076e-01 -7.02918828e-01
-8.57749104e-01 -1.63130879e+00 -5.44866584e-02 6.61866009e-01
4.19093549e-01 -4.19573605e-01 -5.84042333e-02 -2.21265107e-01] | [12.767010688781738, 7.818905830383301] |
e6f69356-b12b-4db3-b4ab-d26d66d97a5e | guaranteed-tensor-recovery-fused-low-rankness | 2302.02155 | null | https://arxiv.org/abs/2302.02155v1 | https://arxiv.org/pdf/2302.02155v1.pdf | Guaranteed Tensor Recovery Fused Low-rankness and Smoothness | The tensor data recovery task has thus attracted much research attention in recent years. Solving such an ill-posed problem generally requires to explore intrinsic prior structures underlying tensor data, and formulate them as certain forms of regularization terms for guiding a sound estimate of the restored tensor. Recent research have made significant progress by adopting two insightful tensor priors, i.e., global low-rankness (L) and local smoothness (S) across different tensor modes, which are always encoded as a sum of two separate regularization terms into the recovery models. However, unlike the primary theoretical developments on low-rank tensor recovery, these joint L+S models have no theoretical exact-recovery guarantees yet, making the methods lack reliability in real practice. To this crucial issue, in this work, we build a unique regularization term, which essentially encodes both L and S priors of a tensor simultaneously. Especially, by equipping this single regularizer into the recovery models, we can rigorously prove the exact recovery guarantees for two typical tensor recovery tasks, i.e., tensor completion (TC) and tensor robust principal component analysis (TRPCA). To the best of our knowledge, this should be the first exact-recovery results among all related L+S methods for tensor recovery. Significant recovery accuracy improvements over many other SOTA methods in several TC and TRPCA tasks with various kinds of visual tensor data are observed in extensive experiments. Typically, our method achieves a workable performance when the missing rate is extremely large, e.g., 99.5%, for the color image inpainting task, while all its peers totally fail in such challenging case. | ['Deyu Meng', 'Jianjun Wang', 'Wenjin Qin', 'Jiangjun Peng', 'Hailin Wang'] | 2023-02-04 | null | null | null | null | ['image-inpainting', 'low-rank-matrix-completion'] | ['computer-vision', 'methodology'] | [ 6.64407015e-02 -2.68759072e-01 -2.64220625e-01 -2.74222177e-02
-7.24458158e-01 -4.13282543e-01 2.86053926e-01 -3.76711816e-01
-5.77186374e-03 3.48137558e-01 3.61466020e-01 -2.02414095e-01
-3.79072279e-01 -1.89115047e-01 -6.54668093e-01 -1.09615278e+00
-1.05848968e-01 1.32666975e-01 -4.58867922e-02 -3.37060124e-01
2.57255048e-01 2.64440238e-01 -1.06933761e+00 1.03118293e-01
9.73107338e-01 1.01564777e+00 3.33324932e-02 2.61333942e-01
1.44773740e-02 9.97218728e-01 4.72149029e-02 -4.20623958e-01
3.14846069e-01 4.26815217e-03 -1.02301967e+00 5.31783342e-01
3.51204962e-01 -4.76583034e-01 -5.13609886e-01 1.28990495e+00
8.12669545e-02 6.42384216e-02 3.75796974e-01 -1.21275890e+00
-8.52900743e-01 5.56537330e-01 -1.13820744e+00 6.91926777e-02
3.42418700e-01 -1.27898389e-02 1.19442558e+00 -1.14572847e+00
4.12409782e-01 1.08887351e+00 5.39605737e-01 1.70871660e-01
-1.29143643e+00 -4.95367438e-01 1.45592898e-01 2.10986838e-01
-1.24614513e+00 -4.57179248e-01 1.23181891e+00 -7.02122450e-01
2.63024509e-01 3.97422016e-01 3.33916128e-01 8.76300216e-01
-1.79170042e-01 1.09421420e+00 1.31064510e+00 -1.53628111e-01
-8.77486616e-02 -1.98444709e-01 3.54933858e-01 6.08615339e-01
3.31479490e-01 -1.80992872e-01 -5.11246979e-01 -2.97262073e-01
1.00161886e+00 2.42704630e-01 -5.70830286e-01 -2.20208272e-01
-1.81575656e+00 5.84116995e-01 3.16825926e-01 4.19717491e-01
-4.32279289e-01 1.20790444e-01 4.50171918e-01 2.84224540e-01
6.53954864e-01 8.07968751e-02 -2.51170307e-01 1.08729854e-01
-8.07138503e-01 2.37614974e-01 4.67752159e-01 1.00323534e+00
9.21962500e-01 3.15482527e-01 -9.83432904e-02 1.00152111e+00
3.07860970e-01 5.64987063e-01 2.90874153e-01 -1.05150235e+00
7.34896243e-01 2.72744477e-01 2.45638594e-01 -1.43396926e+00
1.34837849e-03 -5.45493245e-01 -1.38037336e+00 -2.67135501e-01
6.05902851e-01 3.34441006e-01 -5.61199307e-01 1.65351474e+00
4.43302691e-01 4.41929579e-01 -1.94735020e-01 1.36181784e+00
4.14544642e-01 4.74412501e-01 -3.76696944e-01 -3.35371554e-01
1.50333786e+00 -7.12681532e-01 -9.72120225e-01 1.90326944e-02
4.51156974e-01 -1.12096620e+00 1.00935614e+00 6.44151509e-01
-1.00310445e+00 -3.24435025e-01 -9.67619836e-01 -3.07220966e-01
3.47557455e-01 2.82531470e-01 1.03833652e+00 1.75010815e-01
-8.94522369e-01 5.82411587e-01 -1.00494516e+00 -2.87530776e-02
7.90311396e-02 1.22509897e-02 -6.99484050e-01 -6.54981315e-01
-8.41599524e-01 3.93688649e-01 -1.66861862e-01 7.36570835e-01
-7.95202017e-01 -6.17931783e-01 -4.87416685e-01 -4.27260697e-01
5.27575076e-01 -6.39050543e-01 9.40989017e-01 -6.79877281e-01
-1.36395907e+00 7.82540262e-01 -2.31823340e-01 1.51019052e-01
3.85884225e-01 -3.17647070e-01 -2.43888676e-01 3.30339730e-01
3.33994001e-01 -9.57244784e-02 1.34053802e+00 -1.41129613e+00
3.83454859e-02 -4.63732630e-01 1.17976181e-01 -4.19430770e-02
-3.74581933e-01 1.46968156e-01 -6.11732602e-01 -1.06330359e+00
8.75652432e-01 -1.01650095e+00 -2.78691500e-01 2.04994202e-01
-6.75875902e-01 -1.55726716e-01 5.51251948e-01 -1.10543120e+00
9.61896837e-01 -2.17478609e+00 7.58888781e-01 8.96226466e-02
6.29935801e-01 -6.83220476e-02 -1.97106466e-01 3.77024174e-01
-4.16940391e-01 -1.65680777e-02 -5.13311088e-01 -5.33925533e-01
-4.78919446e-02 4.02203560e-01 -7.08786964e-01 8.81034315e-01
1.04325227e-01 6.06156111e-01 -1.01760828e+00 -2.99163878e-01
-6.43928051e-02 5.42193413e-01 -5.72241247e-01 2.65037715e-01
1.69458717e-01 7.95505226e-01 -7.61379242e-01 7.24507093e-01
1.04259217e+00 -3.57676387e-01 9.95269343e-02 -7.91449547e-01
-7.06902444e-02 1.33572280e-01 -1.25586820e+00 1.84814262e+00
-1.27934307e-01 2.65353173e-01 6.96117401e-01 -1.35823941e+00
6.69588327e-01 3.95790458e-01 9.87716556e-01 -3.20942640e-01
-1.11390084e-01 5.30442655e-01 -1.18703827e-01 -6.48354888e-01
5.35514593e-01 -4.03239131e-01 2.11883366e-01 4.91192847e-01
-2.12293446e-01 1.00574955e-01 2.46761784e-01 3.93419802e-01
1.04002523e+00 1.54205486e-01 -1.69027761e-01 -2.80314654e-01
5.19491374e-01 -2.60064781e-01 7.53307879e-01 3.09710473e-01
-1.36751279e-01 7.13727474e-01 5.11439204e-01 -2.96620905e-01
-1.09850681e+00 -7.04892099e-01 -1.69920191e-01 8.30395699e-01
1.22510113e-01 -3.61185133e-01 -4.68746394e-01 -3.75020623e-01
-1.18470825e-01 7.74289593e-02 -4.45288360e-01 -2.35027559e-02
-7.87874162e-01 -1.04681587e+00 4.30546522e-01 1.97533295e-01
4.89897192e-01 -3.89361471e-01 3.39961559e-01 2.43028458e-02
-6.45387888e-01 -1.51425779e+00 -7.90652931e-01 -4.21187609e-01
-1.23026776e+00 -1.11884153e+00 -9.63196516e-01 -4.33061182e-01
8.11953843e-01 9.66165245e-01 7.89348602e-01 3.62090975e-01
1.28244534e-01 4.00726259e-01 -4.91851866e-01 4.87763733e-01
5.29646454e-03 -4.41450030e-01 2.46833205e-01 7.91067421e-01
-2.38035634e-01 -9.44759488e-01 -6.14165425e-01 6.07761264e-01
-1.24753940e+00 1.70881778e-01 6.97757781e-01 8.80750358e-01
5.91153026e-01 1.23859592e-01 7.76620656e-02 -5.31002164e-01
5.01866817e-01 -5.44381142e-01 -3.16561788e-01 1.12690762e-01
-4.65809673e-01 2.36081883e-01 5.70903361e-01 -5.32298625e-01
-8.69406581e-01 -2.76214033e-01 1.22065686e-01 -9.06123281e-01
3.66339445e-01 8.63971293e-01 -5.73243462e-02 -2.58098304e-01
2.94053942e-01 4.74225312e-01 5.63062318e-02 -9.74624753e-01
3.29126000e-01 2.02157646e-01 5.91841102e-01 -1.27286065e+00
1.32506979e+00 7.98159897e-01 1.59453496e-01 -7.78243005e-01
-1.10533321e+00 -7.85805047e-01 -5.93875051e-01 -8.58032927e-02
3.49145710e-01 -9.56739843e-01 -6.81111038e-01 7.23327935e-01
-1.13500071e+00 -3.35033648e-02 -4.97299246e-04 6.72963262e-01
-3.50212157e-01 1.08578956e+00 -8.59787107e-01 -6.77700162e-01
-5.57739958e-02 -1.33969438e+00 1.13530469e+00 -5.29453099e-01
4.68830258e-01 -9.44162905e-01 1.39686661e-02 7.72682965e-01
3.91290933e-01 2.57985741e-01 5.96641481e-01 1.58572227e-01
-9.01508689e-01 -1.42412215e-01 -6.53978169e-01 6.34096503e-01
1.27275050e-01 -1.20653339e-01 -7.84851193e-01 -4.13466215e-01
4.12856400e-01 -1.56689018e-01 9.38151240e-01 1.01386897e-01
1.19408607e+00 -5.67419171e-01 1.82618946e-02 8.48902106e-01
1.21232593e+00 -5.11288524e-01 7.56695688e-01 -8.91029686e-02
1.34130025e+00 6.14761174e-01 5.38638115e-01 4.00541186e-01
4.83201474e-01 8.80917430e-01 4.63412464e-01 -1.98012777e-02
-1.75056487e-01 1.68931428e-02 5.24075031e-01 1.63177121e+00
-7.80572534e-01 3.95487189e-01 -7.97100067e-01 4.92703527e-01
-1.98308444e+00 -8.65535676e-01 -6.14308119e-01 2.35383606e+00
1.05693471e+00 -2.21651226e-01 -1.30635928e-02 3.70695174e-01
6.71138108e-01 4.54262763e-01 -4.73931134e-01 3.53730351e-01
-1.87888801e-01 -1.37573659e-01 4.30579454e-01 4.22356814e-01
-9.68856156e-01 5.04699349e-01 5.64886045e+00 9.16055024e-01
-1.02471840e+00 3.13244075e-01 1.87512875e-01 3.00590426e-01
-5.59399784e-01 4.37230647e-01 -2.50212699e-01 3.47533911e-01
4.18135107e-01 1.00870006e-01 8.99681330e-01 5.83823264e-01
3.09867710e-01 2.92792350e-01 -8.34483564e-01 1.19148898e+00
1.62533578e-02 -1.01218987e+00 7.64871389e-02 2.47836575e-01
5.91474295e-01 -5.71984090e-02 8.94962922e-02 -3.71408798e-02
9.32549462e-02 -7.05538809e-01 6.99244857e-01 6.44301355e-01
9.41640019e-01 -2.75994211e-01 4.82495904e-01 2.25265741e-01
-1.27837265e+00 1.32486060e-01 -4.63709593e-01 -8.96549001e-02
2.21223563e-01 1.37541258e+00 -6.93032295e-02 1.01522505e+00
5.29870152e-01 1.36936963e+00 -1.82421044e-01 9.01390672e-01
-2.06916183e-01 8.76109898e-01 -3.64690155e-01 7.57416248e-01
2.11847380e-01 -7.74534345e-01 8.71436954e-01 7.37707496e-01
2.07163796e-01 1.18840605e-01 3.60663801e-01 7.43663013e-01
-5.14896847e-02 1.10933132e-01 -3.19977075e-01 -6.91969693e-02
-6.11429289e-02 1.46141076e+00 -4.08179909e-01 -1.34778738e-01
-4.85523283e-01 9.40461159e-01 3.40080917e-01 6.87824965e-01
-6.66711152e-01 3.18663754e-02 7.52033770e-01 2.05741182e-01
3.58648486e-02 -6.42671227e-01 -2.41109163e-01 -1.98183930e+00
6.35371745e-01 -9.52179909e-01 1.83927253e-01 -6.96157336e-01
-1.72851336e+00 2.86074162e-01 -9.03052185e-03 -1.63281584e+00
1.95604771e-01 -6.79816008e-01 -3.83649975e-01 7.77416050e-01
-1.82329023e+00 -1.39834082e+00 -2.96582043e-01 8.67862105e-01
9.16366130e-02 2.00222611e-01 3.82941723e-01 7.13878155e-01
-9.62836802e-01 3.28570783e-01 2.50097185e-01 3.18425298e-01
7.66401649e-01 -1.15996623e+00 -1.60347268e-01 1.13010824e+00
-7.30428100e-02 1.01885855e+00 6.54571712e-01 -5.14994621e-01
-2.18233156e+00 -9.06560898e-01 4.94534761e-01 -2.06269652e-01
1.24071991e+00 -1.70693755e-01 -1.24851036e+00 8.37794900e-01
-2.38719601e-02 4.49231565e-01 3.66190314e-01 1.59066811e-01
-8.74761939e-01 -2.37312645e-01 -7.34529078e-01 4.32452589e-01
1.05331087e+00 -7.47586787e-01 -2.79173613e-01 7.87176132e-01
6.64658308e-01 -3.21733892e-01 -1.26092041e+00 3.10248047e-01
4.15177822e-01 -9.24653590e-01 1.20776379e+00 -5.13608098e-01
4.73086745e-01 -6.98497891e-01 -4.62977916e-01 -9.27546620e-01
-3.41401488e-01 -1.06050098e+00 -4.01202261e-01 1.16166604e+00
-1.65338159e-01 -6.27692580e-01 3.96382004e-01 5.27188480e-01
-4.12715018e-01 -5.94465494e-01 -1.03043461e+00 -8.28159571e-01
-8.47838521e-02 -6.44534647e-01 3.59785676e-01 1.38496649e+00
-1.11914203e-01 1.99389875e-01 -9.51317072e-01 3.35436076e-01
1.17445064e+00 2.00872988e-01 6.91466331e-01 -1.00609577e+00
-4.82763797e-01 -3.95934314e-01 -2.33186960e-01 -1.45898092e+00
1.82180166e-01 -1.09869051e+00 -4.45550270e-02 -1.17369425e+00
3.38839889e-01 -7.52151668e-01 -3.06926191e-01 4.44261551e-01
-2.95928121e-01 1.99090227e-01 5.23166023e-02 1.02397847e+00
-3.44357103e-01 7.95009553e-01 1.74718809e+00 -2.61737972e-01
1.69667333e-01 -8.78414437e-02 -7.92894959e-01 6.28348589e-01
4.00372356e-01 -3.89055014e-01 -4.03256953e-01 -6.81754529e-01
4.65218157e-01 4.12388742e-01 5.65276980e-01 -4.74028349e-01
1.91620916e-01 -5.41948318e-01 -3.00549269e-01 -2.94351876e-01
3.24387819e-01 -6.64906383e-01 2.08438993e-01 2.95964275e-02
-2.89509706e-02 -8.98593366e-02 -2.60441929e-01 7.38312483e-01
-4.14101660e-01 8.31043422e-02 5.66556513e-01 -4.30662334e-02
-4.71988559e-01 7.50405133e-01 1.38183057e-01 -2.13628239e-03
2.91555524e-01 -1.21660000e-02 -3.46175253e-01 -2.33540669e-01
-5.96335769e-01 -3.67172472e-02 2.93857634e-01 1.45860627e-01
7.99703538e-01 -1.60421693e+00 -1.04243588e+00 9.57788080e-02
1.32321879e-01 1.96164548e-01 4.93152410e-01 1.73546088e+00
-2.39945382e-01 1.16257600e-01 4.09208089e-02 -6.92295790e-01
-6.84230685e-01 8.18245649e-01 1.12452470e-01 -5.48991799e-01
-8.53075147e-01 6.32404625e-01 3.22011739e-01 -2.70927131e-01
-9.19344947e-02 -4.36432213e-01 -1.37827350e-02 -1.61089748e-01
6.69933438e-01 4.97606784e-01 7.62197524e-02 -9.77966309e-01
-2.33117238e-01 9.78331566e-01 -1.05821230e-01 5.81916012e-02
1.35787320e+00 -1.75008789e-01 -7.55892217e-01 4.04379278e-01
1.29794919e+00 3.24141264e-01 -1.10127068e+00 -5.82181871e-01
-1.28256362e-02 -7.14880586e-01 2.76744962e-01 -1.51719823e-01
-1.51679516e+00 8.46384048e-01 -6.98312670e-02 3.05404752e-01
1.25333953e+00 -8.93591940e-02 1.00303662e+00 2.78424591e-01
5.39674699e-01 -5.75941920e-01 2.85260737e-01 2.77111053e-01
1.30673587e+00 -1.10374391e+00 3.58929574e-01 -7.59491384e-01
-3.74722719e-01 1.00774276e+00 8.78519490e-02 -3.19166899e-01
5.77603519e-01 -1.24537542e-01 -2.92207092e-01 -3.40290576e-01
-5.35389185e-01 -1.70619544e-02 6.47131324e-01 3.47455263e-01
4.90388483e-01 1.96987778e-01 -2.84949183e-01 3.10135037e-01
1.67319924e-01 -1.23382248e-01 6.22735023e-01 6.49783611e-01
-9.19815972e-02 -1.18366885e+00 -7.94531643e-01 2.37546399e-01
-4.57368344e-01 -1.29859164e-01 8.95952955e-02 4.03238565e-01
-3.43963027e-01 9.13988709e-01 -5.05190849e-01 -4.79998410e-01
1.99003905e-01 -3.49020243e-01 4.77054894e-01 -2.80784190e-01
-1.25032693e-01 4.57015246e-01 -1.73164457e-02 -7.82698035e-01
-8.18501770e-01 -7.98212767e-01 -9.30871665e-01 -6.67939603e-01
-3.03995550e-01 1.14410259e-01 4.51413810e-01 9.67957854e-01
1.67143404e-01 1.19631357e-01 8.48813057e-01 -9.83409643e-01
-7.04501629e-01 -9.89174008e-01 -9.74261105e-01 7.72563875e-01
5.40131986e-01 -9.22080278e-01 -5.63233137e-01 1.39337733e-01] | [7.435087203979492, 4.467124938964844] |
ad10de8b-c45d-4bdb-a6c3-bfdde9b7a2d8 | generative-adversarial-transformers | 2103.01209 | null | https://arxiv.org/abs/2103.01209v4 | https://arxiv.org/pdf/2103.01209v4.pdf | Generative Adversarial Transformers | We introduce the GANformer, a novel and efficient type of transformer, and explore it for the task of visual generative modeling. The network employs a bipartite structure that enables long-range interactions across the image, while maintaining computation of linear efficiency, that can readily scale to high-resolution synthesis. It iteratively propagates information from a set of latent variables to the evolving visual features and vice versa, to support the refinement of each in light of the other and encourage the emergence of compositional representations of objects and scenes. In contrast to the classic transformer architecture, it utilizes multiplicative integration that allows flexible region-based modulation, and can thus be seen as a generalization of the successful StyleGAN network. We demonstrate the model's strength and robustness through a careful evaluation over a range of datasets, from simulated multi-object environments to rich real-world indoor and outdoor scenes, showing it achieves state-of-the-art results in terms of image quality and diversity, while enjoying fast learning and better data-efficiency. Further qualitative and quantitative experiments offer us an insight into the model's inner workings, revealing improved interpretability and stronger disentanglement, and illustrating the benefits and efficacy of our approach. An implementation of the model is available at https://github.com/dorarad/gansformer. | ['C. Lawrence Zitnick', 'Drew A. Hudson'] | 2021-03-01 | null | null | null | null | ['scene-generation'] | ['computer-vision'] | [ 4.51021165e-01 2.54000753e-01 -1.80043429e-01 -1.19183011e-01
-4.82941180e-01 -7.36535907e-01 9.66498852e-01 -4.69047189e-01
2.11227566e-01 6.73223495e-01 5.50461948e-01 -1.33725643e-01
-2.51660079e-01 -8.23098958e-01 -7.80594230e-01 -1.00145185e+00
-1.87873557e-01 3.07022035e-01 2.75414195e-02 -2.93846130e-01
-2.13992134e-01 4.87313747e-01 -1.48720956e+00 2.86653131e-01
5.96263409e-01 8.44245672e-01 2.67297417e-01 7.12003410e-01
3.62343699e-01 9.30469334e-01 -2.53796607e-01 -5.07299662e-01
4.11498189e-01 -5.67301869e-01 -5.61534226e-01 4.76678371e-01
4.06921059e-01 -1.83427721e-01 -5.89195609e-01 6.13165379e-01
3.73651892e-01 -5.88492304e-03 4.46115077e-01 -1.09381533e+00
-1.08572710e+00 3.47627938e-01 -5.31710565e-01 3.89445089e-02
1.61612675e-01 4.74435002e-01 1.26280093e+00 -7.30124831e-01
8.62688065e-01 1.20949996e+00 4.76286948e-01 5.50374985e-01
-1.70999765e+00 -6.73712850e-01 2.44792312e-01 -5.28188832e-02
-1.20850909e+00 -7.15775907e-01 7.45919645e-01 -4.46055412e-01
6.60349607e-01 4.17470008e-01 9.91058230e-01 1.32164598e+00
1.81808367e-01 7.42491305e-01 1.09115803e+00 -3.52986813e-01
8.44605416e-02 4.03880104e-02 -4.90261018e-01 7.92242050e-01
-2.61327233e-02 5.15669107e-01 -9.21426237e-01 -5.84170409e-02
1.16992414e+00 3.35926600e-02 -4.65964973e-01 -7.56013036e-01
-1.20734012e+00 8.05206835e-01 8.79003763e-01 2.37745091e-01
-2.31020555e-01 4.36171353e-01 -2.57405341e-01 2.72269726e-01
4.55697238e-01 5.26836216e-01 -7.85797164e-02 1.14391856e-01
-9.11103606e-01 2.24058345e-01 4.92530376e-01 1.01971257e+00
6.43427610e-01 2.45873034e-01 -2.18587756e-01 5.89981318e-01
3.84876549e-01 4.04134154e-01 -1.59947220e-02 -1.19541109e+00
-3.77299078e-02 4.08203155e-01 -1.00995459e-01 -1.00230742e+00
-1.79789051e-01 -8.42047870e-01 -1.15226805e+00 4.39088911e-01
1.56611025e-01 1.36122420e-01 -1.00717115e+00 2.05682802e+00
1.55403897e-01 2.04107091e-01 -3.14575493e-01 7.86139846e-01
5.59020162e-01 7.06355214e-01 -1.56541988e-01 -6.64661303e-02
1.29342806e+00 -8.70356858e-01 -3.62222344e-01 -2.72562742e-01
2.68988591e-02 -5.55840671e-01 8.88718247e-01 2.96331137e-01
-1.29041553e+00 -5.22506356e-01 -9.34071958e-01 -1.74011976e-01
-1.20599292e-01 -1.85519800e-01 9.16615665e-01 4.83998656e-01
-1.51731610e+00 4.11220610e-01 -8.38638186e-01 -3.43389481e-01
6.84013486e-01 2.25620195e-01 -2.95531720e-01 -1.76551625e-01
-7.64265418e-01 5.66183150e-01 1.10954046e-03 -2.40629204e-02
-1.07946777e+00 -9.01000679e-01 -7.30332196e-01 8.89272094e-02
3.03772420e-01 -1.35957861e+00 1.02646518e+00 -1.11170232e+00
-1.44426930e+00 8.16540062e-01 -1.79548755e-01 -2.35701293e-01
4.66027677e-01 1.26843795e-01 -1.85433224e-01 3.86590250e-02
-1.69285566e-01 1.04175436e+00 9.20329988e-01 -1.53752649e+00
-4.32463616e-01 -1.99200317e-01 2.55289882e-01 2.48833388e-01
-1.79620907e-01 -2.85464048e-01 -5.10697663e-01 -9.58415926e-01
3.71456742e-02 -9.70999062e-01 -2.55266398e-01 3.07518959e-01
-3.34104270e-01 2.84476876e-01 6.49120271e-01 -4.96019900e-01
1.07710409e+00 -2.25186563e+00 7.01323152e-01 2.11332455e-01
7.24527359e-01 -1.26001701e-01 -2.28354335e-01 6.06790543e-01
-8.09408724e-02 8.57964680e-02 -4.63429034e-01 -5.57704151e-01
5.06376335e-03 2.24562496e-01 -3.45149666e-01 4.21572506e-01
3.29945296e-01 1.31398308e+00 -8.37382555e-01 -1.61476612e-01
2.62818426e-01 7.62251496e-01 -7.46055245e-01 2.05944076e-01
-2.19542176e-01 7.78435528e-01 -1.90252140e-01 5.62406421e-01
4.17726129e-01 -6.40962541e-01 3.41663808e-01 -2.65438914e-01
1.34722888e-02 1.57027721e-01 -8.81779611e-01 1.74590588e+00
-4.45988566e-01 8.85929763e-01 2.21792489e-01 -6.48356080e-01
6.17584527e-01 2.21545458e-01 3.53796363e-01 -8.42916191e-01
-1.20183490e-01 -5.42659350e-02 -1.16673499e-01 -1.16461843e-01
4.32348728e-01 -2.26074085e-01 1.22362137e-01 5.43045163e-01
3.09410810e-01 -1.63474500e-01 2.95656230e-02 4.55557197e-01
9.60866928e-01 3.53693157e-01 2.79755086e-01 -3.19175422e-01
-3.95007096e-02 -4.06445235e-01 2.07630485e-01 7.22641885e-01
3.14402908e-01 6.43793404e-01 3.26582283e-01 -3.33527267e-01
-1.34524941e+00 -1.41387141e+00 -2.03283112e-02 1.02558672e+00
1.74655002e-02 -5.68909407e-01 -3.67608756e-01 -2.23242998e-01
-4.07906324e-02 5.05642474e-01 -8.78506541e-01 -1.81590661e-01
-3.66279304e-01 -6.76467240e-01 3.26664537e-01 3.73925209e-01
3.68596494e-01 -9.74139512e-01 -6.16451085e-01 -1.79551154e-01
-1.30770475e-01 -9.44436848e-01 -3.26582789e-01 1.01975538e-01
-6.43121719e-01 -8.42026651e-01 -5.68603635e-01 -5.69334745e-01
6.22011602e-01 2.51984656e-01 1.42981982e+00 1.36216640e-01
-3.00802290e-01 4.77101475e-01 -1.62085831e-01 1.62362382e-02
-5.42416573e-01 -3.12862620e-02 -2.30542019e-01 6.58268109e-02
-4.69051510e-01 -1.10531592e+00 -7.52358735e-01 1.55681655e-01
-1.05764163e+00 5.97914040e-01 6.63042963e-01 1.00269914e+00
4.38406110e-01 -1.22078173e-01 1.28326207e-01 -7.60318995e-01
3.17981690e-01 -5.02191842e-01 -5.71904480e-01 1.70375973e-01
-5.42022526e-01 7.74256289e-02 4.54125732e-01 -2.33403131e-01
-9.48141992e-01 -2.23612189e-01 5.22120893e-02 -3.53450328e-01
8.83473381e-02 1.19444065e-01 -1.55499384e-01 -2.26417229e-01
5.26733696e-01 4.76397336e-01 4.85853478e-03 -3.84453326e-01
8.18925858e-01 1.19088873e-01 6.16892576e-01 -5.95683575e-01
1.07969844e+00 6.51544929e-01 1.58402875e-01 -8.42816532e-01
-5.81977963e-01 5.83902746e-02 -4.83414441e-01 -2.27202043e-01
6.71200335e-01 -1.00075817e+00 -6.04491472e-01 4.76217449e-01
-8.41805935e-01 -5.80633938e-01 -7.74033070e-01 -1.01258241e-01
-7.28804410e-01 -8.38562995e-02 -5.97620487e-01 -6.40076160e-01
5.98442219e-02 -9.45878625e-01 1.16905558e+00 1.63792565e-01
-8.04160163e-02 -1.22853458e+00 -4.48642019e-03 1.63557082e-01
5.68385780e-01 3.38321328e-01 1.05678594e+00 4.63179797e-02
-1.16687489e+00 2.94762164e-01 -1.73700169e-01 1.84488416e-01
1.75502270e-01 2.77285855e-02 -1.04328823e+00 -5.53737342e-01
-1.57071590e-01 -2.27465019e-01 1.07252121e+00 4.11123991e-01
9.50010300e-01 -5.48304558e-01 -3.10195386e-01 1.03921103e+00
1.40413618e+00 -1.37067035e-01 8.49831283e-01 6.20876849e-02
8.28782141e-01 4.64723617e-01 -8.28536302e-02 4.54290748e-01
5.93598783e-01 8.39104354e-01 5.94580889e-01 -4.71359313e-01
-5.14786959e-01 -4.42872792e-01 2.43592680e-01 7.26667583e-01
-2.07270175e-01 -5.06075621e-01 -5.68903148e-01 3.97742033e-01
-1.71834123e+00 -1.08994675e+00 3.12324405e-01 1.99311900e+00
7.39321828e-01 -8.76290798e-02 2.61807621e-01 -1.44877315e-01
3.60238910e-01 5.46434104e-01 -5.07650793e-01 -1.13173828e-01
-3.85841757e-01 2.90904701e-01 2.45053083e-01 4.92280602e-01
-7.60092378e-01 7.55505919e-01 7.46485376e+00 8.30391586e-01
-1.04918289e+00 1.59652710e-01 9.57605064e-01 -4.00783032e-01
-9.19691384e-01 1.45578086e-02 -3.62944543e-01 3.28113377e-01
6.28622234e-01 -7.19901994e-02 9.21368122e-01 2.71141171e-01
-1.65440608e-03 1.24200709e-01 -1.10603094e+00 7.84428060e-01
-1.05551057e-01 -1.89086390e+00 2.17687532e-01 2.77916253e-01
8.60372782e-01 3.11302319e-02 4.17594016e-01 -3.98951285e-02
6.27531588e-01 -1.17219138e+00 1.02872062e+00 5.98616064e-01
9.98488128e-01 -5.54293633e-01 7.98157975e-02 2.31023937e-01
-1.13617647e+00 -2.67321289e-01 3.14081460e-02 -1.07540615e-01
9.46711525e-02 5.02206266e-01 -3.55906427e-01 5.86799920e-01
6.91326320e-01 8.79494607e-01 -6.46534264e-01 6.47189677e-01
-3.19960713e-01 4.18952703e-01 -2.24957898e-01 3.35131973e-01
1.01515673e-01 -2.21564159e-01 6.63078487e-01 1.14476907e+00
3.80483598e-01 5.40823974e-02 -1.24929696e-02 1.29529178e+00
-1.21547930e-01 -3.42331707e-01 -8.19004893e-01 -2.98777837e-02
5.23957431e-01 1.25431621e+00 -5.99728167e-01 -1.26764894e-01
-1.20372541e-01 9.47364509e-01 3.06746155e-01 5.88038087e-01
-8.17322552e-01 2.78920084e-01 7.64805615e-01 3.45583916e-01
5.31377077e-01 -3.33929330e-01 -3.21346670e-01 -1.12870967e+00
-2.88377367e-02 -1.02035236e+00 2.01538518e-01 -9.93370175e-01
-1.13057375e+00 5.77740788e-01 -5.85538894e-02 -1.11085129e+00
-2.20527306e-01 -4.76715893e-01 -3.74908090e-01 6.70718670e-01
-1.28228664e+00 -1.63580394e+00 -3.72111797e-01 6.13249302e-01
2.78465658e-01 1.05976490e-02 7.90433466e-01 1.51559711e-01
-3.37565929e-01 5.37525952e-01 1.20811932e-01 -3.49003047e-01
3.73987526e-01 -1.02516627e+00 5.25606632e-01 1.06174779e+00
4.94677693e-01 5.63925683e-01 7.02754676e-01 -3.08647364e-01
-1.56515801e+00 -9.39827621e-01 4.21345621e-01 -5.86267591e-01
6.37901187e-01 -6.83745980e-01 -5.15021503e-01 9.00439680e-01
5.22254229e-01 -7.86050111e-02 5.61342061e-01 3.58690359e-02
-6.88463330e-01 -5.51288240e-02 -9.83267248e-01 8.28534424e-01
1.51109231e+00 -4.87998724e-01 8.79559014e-03 9.15594101e-02
8.56945872e-01 -3.62041652e-01 -6.97518706e-01 3.42833906e-01
7.39891589e-01 -1.44754219e+00 1.01426446e+00 -3.03536415e-01
7.04735398e-01 -2.74391264e-01 -3.76018673e-01 -1.35588801e+00
-9.62488651e-01 -9.57712531e-01 -3.55355233e-01 1.17907643e+00
2.64843285e-01 -6.17807567e-01 4.64133382e-01 2.70646721e-01
-1.61586568e-01 -9.73925889e-01 -9.15744483e-01 -5.65629423e-01
-8.75968114e-02 -3.14191043e-01 6.81629837e-01 8.24019492e-01
-3.77030015e-01 4.03684974e-01 -5.94093680e-01 5.58244139e-02
6.68687284e-01 2.42762357e-01 7.61162400e-01 -9.13040936e-01
-7.65436232e-01 -7.58102655e-01 -4.36851323e-01 -1.16961551e+00
-1.82216629e-01 -9.36570227e-01 -2.16315255e-01 -1.39792252e+00
3.56258601e-01 -4.06328738e-01 -7.08048791e-02 5.00348449e-01
1.28482118e-01 7.33873546e-01 5.44417679e-01 2.03718394e-01
-4.78869885e-01 7.25771308e-01 1.51235402e+00 -7.65902475e-02
7.81785510e-03 -1.36231109e-01 -1.10350835e+00 4.37304109e-01
4.48017359e-01 -1.99432060e-01 -5.60003936e-01 -5.91647029e-01
4.33192343e-01 -1.35041445e-01 7.71385252e-01 -8.76821518e-01
-7.35755488e-02 -1.33981600e-01 5.11075020e-01 1.04046009e-01
5.87768912e-01 -7.59590268e-01 7.09424675e-01 3.35668564e-01
-3.41709375e-01 7.61793107e-02 1.62919149e-01 5.51136315e-01
7.64223561e-02 5.43091834e-01 8.75347137e-01 -1.47208229e-01
-6.22692883e-01 4.71586615e-01 -8.94553512e-02 -5.82778417e-02
8.89989495e-01 -3.31985474e-01 -5.34154058e-01 -7.31246829e-01
-5.60148299e-01 8.85917023e-02 9.42431450e-01 4.48338062e-01
4.88861382e-01 -1.50908411e+00 -7.58991897e-01 6.14134014e-01
8.20549652e-02 -1.14873081e-01 2.92088419e-01 8.33820283e-01
-1.60834134e-01 1.60426095e-01 -3.51339519e-01 -7.98725665e-01
-9.25251424e-01 4.41102862e-01 4.36273664e-01 -3.35949570e-01
-7.37791955e-01 9.59571242e-01 8.05595696e-01 -9.05665532e-02
-9.12276357e-02 -1.12711623e-01 2.40432739e-01 -1.66273132e-01
3.71932298e-01 1.50415197e-01 -3.42150331e-01 -6.08453214e-01
-2.61397868e-01 5.04550517e-01 3.10102671e-01 -2.20455587e-01
1.41784096e+00 -3.72974336e-01 -2.58150488e-01 3.99088234e-01
8.89064133e-01 1.22339733e-01 -1.74899518e+00 -2.53947973e-01
-5.25237441e-01 -5.93409956e-01 -7.12790415e-02 -8.74294579e-01
-1.28784811e+00 6.48129582e-01 3.84294152e-01 3.59880120e-01
1.40233624e+00 3.52727562e-01 4.26218808e-01 -1.49132371e-01
4.79910880e-01 -4.06351686e-01 3.08778435e-01 2.26368353e-01
1.01105368e+00 -8.16715300e-01 9.46734799e-04 -3.13443184e-01
-5.32555521e-01 7.11431503e-01 2.60353357e-01 -2.07116231e-01
6.34460092e-01 4.94897991e-01 -1.62097245e-01 -2.75968283e-01
-1.10575962e+00 -4.67660651e-02 3.82796139e-01 7.26048291e-01
3.36757094e-01 1.75665468e-01 2.91527450e-01 1.71005502e-01
-4.29054141e-01 -1.89280078e-01 2.75679529e-01 6.54359758e-01
-1.17976144e-01 -1.05866456e+00 -2.42132563e-02 2.64073998e-01
-5.92415109e-02 -1.42791212e-01 -2.36478597e-01 7.58245826e-01
1.82893842e-01 8.02627683e-01 1.82919011e-01 -4.60681528e-01
9.02424566e-03 -1.48236781e-01 9.60692883e-01 -4.14294034e-01
-4.65417027e-01 1.88333601e-01 -8.65178332e-02 -8.39795411e-01
-6.31022215e-01 -4.76966172e-01 -6.20411456e-01 -6.05450630e-01
-9.18264240e-02 -1.96474910e-01 3.60173911e-01 7.71385491e-01
6.75991654e-01 7.90396035e-01 7.58354545e-01 -1.14560115e+00
-1.77319825e-01 -6.19129717e-01 -5.15393257e-01 3.29925895e-01
6.86190844e-01 -5.41395664e-01 -2.19386876e-01 2.16186702e-01] | [11.537423133850098, -0.4020812213420868] |
6764697f-1a9e-4a2b-87c3-daf1fec36d1d | pointinet-point-cloud-frame-interpolation | 2012.10066 | null | https://arxiv.org/abs/2012.10066v1 | https://arxiv.org/pdf/2012.10066v1.pdf | PointINet: Point Cloud Frame Interpolation Network | LiDAR point cloud streams are usually sparse in time dimension, which is limited by hardware performance. Generally, the frame rates of mechanical LiDAR sensors are 10 to 20 Hz, which is much lower than other commonly used sensors like cameras. To overcome the temporal limitations of LiDAR sensors, a novel task named Point Cloud Frame Interpolation is studied in this paper. Given two consecutive point cloud frames, Point Cloud Frame Interpolation aims to generate intermediate frame(s) between them. To achieve that, we propose a novel framework, namely Point Cloud Frame Interpolation Network (PointINet). Based on the proposed method, the low frame rate point cloud streams can be upsampled to higher frame rates. We start by estimating bi-directional 3D scene flow between the two point clouds and then warp them to the given time step based on the 3D scene flow. To fuse the two warped frames and generate intermediate point cloud(s), we propose a novel learning-based points fusion module, which simultaneously takes two warped point clouds into consideration. We design both quantitative and qualitative experiments to evaluate the performance of the point cloud frame interpolation method and extensive experiments on two large scale outdoor LiDAR datasets demonstrate the effectiveness of the proposed PointINet. Our code is available at https://github.com/ispc-lab/PointINet.git. | ['Alois Knoll', 'Yinlong Liu', 'Zhijun Li', 'Sanqing Qu', 'Guang Chen', 'Fan Lu'] | 2020-12-18 | null | null | null | null | ['3d-point-cloud-interpolation'] | ['computer-vision'] | [ 3.05965263e-02 -7.21323609e-01 -1.20725356e-01 -2.59341091e-01
-6.45127356e-01 -3.09622288e-01 4.38065827e-01 3.75163704e-02
-4.12925512e-01 6.56874299e-01 -3.27481866e-01 -1.81577057e-01
1.80836573e-01 -9.69640195e-01 -7.47719526e-01 -4.84899759e-01
2.49832973e-01 2.59907186e-01 4.40080166e-01 1.71438396e-01
2.45572001e-01 8.72233272e-01 -1.61283553e+00 -1.21216580e-01
9.05791342e-01 9.30204332e-01 3.73733193e-01 6.32224023e-01
-3.28356981e-01 1.43461600e-01 -2.12240189e-01 -7.21664429e-02
4.79537338e-01 -6.20899955e-03 -1.99009225e-01 1.33290738e-01
4.08717483e-01 -6.78372562e-01 -3.61827999e-01 9.40205574e-01
3.29603970e-01 2.51052856e-01 1.76285774e-01 -1.43118250e+00
-2.67305702e-01 -3.98934036e-02 -8.13465476e-01 7.99883902e-02
2.86763757e-01 3.57120663e-01 4.66265380e-01 -1.22120428e+00
5.24524271e-01 1.41101611e+00 6.61450803e-01 2.45878354e-01
-1.25454736e+00 -9.80682015e-01 5.03695458e-02 2.36097753e-01
-1.61859488e+00 -3.93290460e-01 1.09915018e+00 -4.87621009e-01
2.98463523e-01 7.37721175e-02 9.29886281e-01 6.02496028e-01
4.07567481e-03 4.42572832e-01 8.78415048e-01 -1.28069565e-01
2.54020810e-01 -1.71036780e-01 -2.31649324e-01 3.44424576e-01
2.36491859e-01 2.55807459e-01 -5.28869271e-01 -1.05881624e-01
1.26874435e+00 5.94272375e-01 -3.94381404e-01 -2.32407168e-01
-1.70120108e+00 6.95063472e-01 6.08281553e-01 -2.58796457e-02
-3.90322894e-01 3.08743685e-01 2.14450300e-01 3.33683975e-02
6.06943250e-01 -5.04678428e-01 -1.47345230e-01 -4.96689714e-02
-1.08417761e+00 2.72261381e-01 3.13965261e-01 1.31419039e+00
1.24275959e+00 6.48451895e-02 2.45896623e-01 5.18346429e-01
6.31351233e-01 8.32588017e-01 1.61468029e-01 -1.22145069e+00
6.38157904e-01 4.51894701e-01 1.75552651e-01 -1.08779764e+00
1.07635602e-01 7.66856074e-02 -9.98750150e-01 2.68457919e-01
2.19943032e-01 -1.33052140e-01 -5.03800929e-01 1.07490695e+00
7.57545054e-01 1.11543882e+00 -1.21193126e-01 1.06323373e+00
7.07872033e-01 1.10113454e+00 -8.31000656e-02 -4.40136075e-01
1.06829810e+00 -3.95254135e-01 -5.20094156e-01 3.32533717e-02
3.02840412e-01 -9.83947754e-01 8.71253729e-01 8.81691203e-02
-1.00629580e+00 -8.43374074e-01 -1.00550258e+00 -2.75457859e-01
9.24915001e-02 3.53415795e-02 2.26359561e-01 1.28038293e-02
-6.48998439e-01 5.58453858e-01 -1.14191866e+00 -5.47123589e-02
4.16116595e-01 1.69632763e-01 -1.34039909e-01 -1.41652077e-01
-8.68120193e-01 4.44563955e-01 3.59961182e-01 2.98487097e-01
-3.72467041e-01 -1.03617823e+00 -8.17255616e-01 -2.11908966e-01
1.24054573e-01 -7.58912027e-01 1.20093513e+00 -4.77757633e-01
-1.35894847e+00 4.42948341e-01 -6.49890423e-01 -2.94013262e-01
5.57476997e-01 -2.06290960e-01 -1.81230024e-01 1.23017959e-01
2.50230074e-01 8.45891416e-01 7.92280257e-01 -1.47563124e+00
-1.00169265e+00 -2.64115125e-01 -2.28188589e-01 1.76533937e-01
8.38983133e-02 -2.51815617e-01 -4.67143327e-01 -3.40219915e-01
3.88040364e-01 -8.61488402e-01 -1.76263526e-01 5.43882608e-01
-1.34473920e-01 -1.60567164e-01 1.40475440e+00 -2.94563919e-01
7.77831674e-01 -2.33052993e+00 -1.66710481e-01 -9.59614739e-02
-1.23438181e-03 3.00373197e-01 1.05948120e-01 1.92493185e-01
-7.36974599e-03 -1.39583126e-01 -3.59537095e-01 -5.81611216e-01
-4.54401284e-01 2.67829388e-01 -6.52704298e-01 4.92181420e-01
1.97695121e-01 4.96846318e-01 -1.07706177e+00 -6.82633042e-01
9.19075012e-01 8.38712513e-01 -4.00430083e-01 9.85834822e-02
-9.62471738e-02 7.75244832e-01 -4.94113714e-01 6.43353701e-01
1.24279106e+00 1.16062067e-01 -4.91213739e-01 -4.58172441e-01
-6.67494476e-01 -6.12154752e-02 -1.38666070e+00 1.82545173e+00
-5.21756351e-01 7.65256107e-01 -1.13306053e-01 -5.45017123e-01
1.19867456e+00 3.10325593e-01 7.87429512e-01 -2.44991064e-01
7.35848919e-02 3.25324744e-01 -4.65756148e-01 -3.12258065e-01
5.10154903e-01 -2.66378611e-01 3.32496911e-01 -6.73222020e-02
-2.83207059e-01 -6.79375470e-01 -2.89642103e-02 -4.61008139e-02
5.28574467e-01 4.12970543e-01 1.15498014e-01 2.03178704e-01
7.88428187e-01 9.12775397e-02 7.98963904e-01 1.32986069e-01
-1.75173163e-01 8.64546001e-01 2.49490351e-03 -4.41922784e-01
-1.25289369e+00 -1.07596850e+00 -2.39422679e-01 1.20387442e-01
5.95901430e-01 -3.92459273e-01 -3.57729852e-01 -1.23194315e-01
1.61248282e-01 5.56088030e-01 5.76884970e-02 2.26504773e-01
-9.42463934e-01 -1.23948887e-01 9.22544003e-02 4.47912961e-01
7.55918622e-01 -6.44546211e-01 -7.47700691e-01 2.92081743e-01
-2.72032708e-01 -1.42542696e+00 -5.91013074e-01 -5.18991411e-01
-1.38970435e+00 -8.85719955e-01 -5.71893871e-01 -6.34810507e-01
5.43493629e-01 8.74051213e-01 6.69891059e-01 2.28302523e-01
9.20023918e-02 2.15608239e-01 -1.18465409e-01 -5.33325970e-01
-1.51828239e-02 -2.05612779e-01 2.07191408e-01 1.05191179e-01
4.01742518e-01 -8.50945652e-01 -7.07565844e-01 3.22472394e-01
-9.72912550e-01 3.40458483e-01 3.17282766e-01 4.87001985e-01
1.11814785e+00 5.50686207e-04 5.65718561e-02 -1.79926008e-01
2.21161738e-01 -4.11747545e-01 -1.10638177e+00 -3.86122465e-01
-1.62182376e-01 -4.18185025e-01 5.22382736e-01 -4.51121092e-01
-8.61876726e-01 4.76581991e-01 -3.96605954e-02 -1.13959277e+00
-1.96075544e-01 3.82376969e-01 -2.64796522e-02 -3.52664441e-02
2.59585530e-01 2.11463630e-01 7.82495365e-02 -3.94751340e-01
3.39020342e-01 6.32417560e-01 8.72582972e-01 -6.16622269e-01
1.30717123e+00 8.79509509e-01 1.48565069e-01 -1.05720603e+00
-3.25232685e-01 -5.51960111e-01 -8.73431683e-01 -4.60397750e-01
8.02505672e-01 -1.22204244e+00 -9.18738306e-01 2.76489764e-01
-1.63403273e+00 1.37472805e-02 -3.16597193e-01 8.34895968e-01
-5.74731052e-01 5.34487545e-01 -4.01714355e-01 -7.66757429e-01
-2.26634845e-01 -1.22541249e+00 1.38235295e+00 4.64113533e-01
1.96079388e-01 -7.83623457e-01 1.21639818e-01 1.83904897e-02
-9.00294483e-02 4.98743325e-01 2.74147540e-01 2.64127672e-01
-1.16779089e+00 -9.44352672e-02 -3.22099358e-01 2.05433339e-01
3.05007100e-01 5.09424508e-01 -7.27474630e-01 -2.12965399e-01
2.45509073e-01 3.32711697e-01 4.29621637e-01 3.86172354e-01
1.03058779e+00 -6.85177222e-02 -4.13539499e-01 8.66178870e-01
1.70194829e+00 2.29413360e-01 5.46361744e-01 2.85363227e-01
8.71628523e-01 3.05579931e-01 1.01563108e+00 5.08794427e-01
5.24195015e-01 8.03279161e-01 5.13597429e-01 1.56340674e-01
-6.77154139e-02 -5.10688305e-01 2.69212842e-01 1.08669686e+00
-3.63033265e-01 1.22189835e-01 -9.07253265e-01 5.03106654e-01
-1.87316418e+00 -8.72621953e-01 -5.35027504e-01 2.42850733e+00
6.98156238e-01 7.05822334e-02 -1.13822922e-01 2.45939866e-01
9.06534672e-01 1.16283797e-01 -5.23101270e-01 6.89025149e-02
3.10710222e-01 1.34259492e-01 4.96590942e-01 6.66683078e-01
-7.58999884e-01 7.60875046e-01 4.31616926e+00 7.60147035e-01
-1.42745566e+00 1.22444071e-01 7.71442875e-02 -1.45135403e-01
-1.83712751e-01 4.16076899e-01 -9.07419145e-01 9.78804708e-01
8.43913913e-01 -4.94196594e-01 2.44505286e-01 6.85213864e-01
7.85684705e-01 1.70072466e-02 -1.04035866e+00 1.36809421e+00
-4.12586212e-01 -1.57136095e+00 1.36885479e-01 8.14047083e-02
4.21036214e-01 5.06709926e-02 -2.47107074e-01 -2.09245123e-02
-5.15766768e-03 -4.17618990e-01 6.96804821e-01 5.79983890e-01
9.10411060e-01 -7.70143628e-01 3.95098120e-01 5.76465666e-01
-1.69600070e+00 2.92644680e-01 -7.06879854e-01 -1.81988448e-01
6.22518957e-01 8.78994286e-01 -6.12960279e-01 7.30866253e-01
7.46505916e-01 1.16680551e+00 -1.91778943e-01 1.24734557e+00
-1.38475761e-01 3.34141105e-01 -7.03415334e-01 3.32211137e-01
6.64933696e-02 -6.82774842e-01 7.46625245e-01 8.39666367e-01
8.71894658e-01 5.36379635e-01 2.26944357e-01 9.12468910e-01
-5.69761265e-03 -1.21916600e-01 -7.77965546e-01 4.91454512e-01
1.01151466e+00 1.26135409e+00 -5.18010914e-01 -3.84805948e-01
-5.42930603e-01 6.40211284e-01 -1.28608122e-01 3.01589400e-01
-9.31631923e-01 -4.17928427e-01 7.92732477e-01 2.11110070e-01
5.34727499e-02 -8.02578747e-01 -3.41827571e-01 -1.39293396e+00
2.07628116e-01 -2.04118624e-01 -6.61490485e-02 -1.04673207e+00
-1.05156100e+00 1.86201289e-01 1.82560995e-01 -2.10006237e+00
5.49325608e-02 -1.37681574e-01 -7.92714000e-01 1.02385664e+00
-1.76783442e+00 -1.01936948e+00 -8.53075325e-01 8.29001427e-01
7.47669637e-01 3.02197903e-01 2.66161054e-01 5.27640700e-01
-3.87728035e-01 -6.55800551e-02 -7.60441413e-03 2.76730489e-02
6.00207090e-01 -7.31639028e-01 6.00019395e-01 9.32835996e-01
-7.24470094e-02 4.13336515e-01 4.57020015e-01 -8.03659618e-01
-1.46059430e+00 -1.34726548e+00 7.17652917e-01 -2.10989848e-01
5.27395487e-01 -1.50975019e-01 -1.11647630e+00 7.11053729e-01
-7.86089450e-02 4.14755464e-01 1.62616789e-01 -7.58373797e-01
5.46965003e-02 -4.91699547e-01 -1.12807488e+00 5.45436025e-01
8.19113672e-01 -3.75041395e-01 -4.86351877e-01 3.56642812e-01
1.00437903e+00 -7.84080029e-01 -9.95339274e-01 4.70866591e-01
2.80913532e-01 -8.74764085e-01 1.24454367e+00 1.38794035e-01
5.66795588e-01 -8.63997698e-01 -2.09254414e-01 -1.13208985e+00
-7.88457170e-02 -5.33627331e-01 -1.81592420e-01 1.37218201e+00
-3.09663653e-01 -7.47720063e-01 8.51110697e-01 4.22044307e-01
-7.53995031e-02 -5.35766006e-01 -1.18575585e+00 -7.75502682e-01
-9.93561298e-02 -5.64624727e-01 8.65095735e-01 8.29493463e-01
-4.76824760e-01 3.04216623e-01 -1.70083210e-01 5.39281547e-01
1.03246510e+00 2.06886098e-01 1.04224169e+00 -1.25248575e+00
2.98804879e-01 -1.83002487e-01 -5.65802217e-01 -1.29432166e+00
1.94394868e-02 -5.94166160e-01 4.70680855e-02 -1.38061023e+00
-4.23778355e-01 -7.35006213e-01 2.83318698e-01 4.29588556e-02
-1.33267850e-01 2.49008209e-01 5.04498363e-01 7.18096733e-01
1.91423923e-01 7.11689115e-01 1.23751414e+00 -3.63272950e-02
-3.93172115e-01 1.39423102e-01 -1.05825417e-01 7.95675337e-01
6.54762805e-01 -3.46020967e-01 -4.32330191e-01 -8.27914476e-01
-3.49746466e-01 4.26666796e-01 5.41502714e-01 -1.33856559e+00
4.69593346e-01 -3.95614862e-01 4.60656077e-01 -1.09677541e+00
6.87628627e-01 -1.20694661e+00 4.71239716e-01 4.17850494e-01
1.59159258e-01 1.91895157e-01 2.11574316e-01 5.49695134e-01
-3.04956526e-01 3.55807655e-02 8.88428748e-01 -4.10717055e-02
-5.78240037e-01 8.33415031e-01 1.56132907e-01 -4.18061584e-01
1.19086111e+00 -3.92026782e-01 -7.15069175e-02 -2.09357738e-01
-2.62608588e-01 2.56084561e-01 6.15329206e-01 2.99749166e-01
1.01397455e+00 -1.77994990e+00 -7.17361271e-01 3.27025741e-01
-5.59062995e-02 8.71792495e-01 1.96799859e-01 7.97356188e-01
-8.68285358e-01 2.44104445e-01 4.14133258e-03 -1.26352119e+00
-1.13100445e+00 4.46954042e-01 9.97394025e-02 4.08589721e-01
-8.97765398e-01 3.69300306e-01 -1.58499524e-01 -2.85480469e-01
-1.72466844e-01 -6.22641504e-01 1.49581611e-01 -7.19218850e-02
3.93928796e-01 5.11025310e-01 -6.22029379e-02 -8.02370548e-01
-2.73874998e-01 1.05487287e+00 3.03492934e-01 -1.55773655e-01
1.16282940e+00 -2.04442129e-01 -1.10237598e-01 6.38790011e-01
1.31990743e+00 -1.24094225e-01 -1.50846004e+00 -3.02831113e-01
-2.81671733e-01 -1.11185741e+00 3.67649365e-03 3.97007555e-01
-1.23598325e+00 1.02243423e+00 6.53704107e-01 -1.38011739e-01
1.06085682e+00 -3.66294295e-01 1.28393936e+00 1.36541590e-01
5.43874145e-01 -5.31825244e-01 -3.76046896e-01 3.29388559e-01
5.40490746e-01 -1.06624043e+00 2.81033725e-01 -6.62063777e-01
-1.04632191e-01 1.22107399e+00 5.13094664e-01 -4.69971269e-01
6.05800390e-01 1.37354240e-01 -4.98042442e-02 2.28917181e-01
-5.12279034e-01 2.47229859e-02 -2.03034773e-01 5.68614185e-01
1.48860052e-01 -7.55331889e-02 -2.45865434e-01 -2.08747610e-01
-2.03122079e-01 5.17246008e-01 6.60942852e-01 1.02738750e+00
-4.12408531e-01 -1.07502639e+00 -7.74262369e-01 1.53482303e-01
2.17202917e-01 1.72275335e-01 2.96294838e-01 6.50072336e-01
1.98164836e-01 8.06301415e-01 4.07378763e-01 -3.31504643e-01
5.30171096e-01 -3.76483023e-01 2.30899498e-01 -4.13605809e-01
5.12095466e-02 1.75927356e-01 -5.81613481e-01 -5.90471506e-01
-7.62155592e-01 -8.83479595e-01 -1.38179421e+00 -6.80403113e-01
-2.00243145e-01 1.12200014e-01 7.65942276e-01 5.81133783e-01
3.64180237e-01 1.23943679e-01 8.58735383e-01 -1.47218704e+00
8.91142618e-03 -4.86881256e-01 -2.83291489e-01 3.25657904e-01
5.91638088e-01 -6.36022031e-01 -4.54018354e-01 4.40551907e-01] | [8.554668426513672, -2.168421506881714] |
66190c33-335d-450d-a52d-00ef4584952d | multi-task-regularization-based-on-infrequent | 2007.04660 | null | https://arxiv.org/abs/2007.04660v1 | https://arxiv.org/pdf/2007.04660v1.pdf | Multi-task Regularization Based on Infrequent Classes for Audio Captioning | Audio captioning is a multi-modal task, focusing on using natural language for describing the contents of general audio. Most audio captioning methods are based on deep neural networks, employing an encoder-decoder scheme and a dataset with audio clips and corresponding natural language descriptions (i.e. captions). A significant challenge for audio captioning is the distribution of words in the captions: some words are very frequent but acoustically non-informative, i.e. the function words (e.g. "a", "the"), and other words are infrequent but informative, i.e. the content words (e.g. adjectives, nouns). In this paper we propose two methods to mitigate this class imbalance problem. First, in an autoencoder setting for audio captioning, we weigh each word's contribution to the training loss inversely proportional to its number of occurrences in the whole dataset. Secondly, in addition to multi-class, word-level audio captioning task, we define a multi-label side task based on clip-level content word detection by training a separate decoder. We use the loss from the second task to regularize the jointly trained encoder for the audio captioning task. We evaluate our method using Clotho, a recently published, wide-scale audio captioning dataset, and our results show an increase of 37\% relative improvement with SPIDEr metric over the baseline method. | ['Emre Çakır', 'Tuomas Virtanen', 'Konstantinos Drossos'] | 2020-07-09 | null | null | null | null | ['audio-captioning'] | ['audio'] | [ 4.79470909e-01 1.16337657e-01 4.63884063e-02 -3.58904123e-01
-1.53403318e+00 -4.78619099e-01 2.38828257e-01 4.11212921e-01
-2.87613273e-01 7.04640448e-01 6.71333551e-01 2.27700099e-01
3.35484475e-01 -4.28904831e-01 -1.14361000e+00 -6.57827795e-01
-5.54482937e-02 5.90187132e-01 1.75044928e-02 -1.54943675e-01
-2.00482741e-01 -1.81516275e-01 -1.71395099e+00 7.34828234e-01
1.96709752e-01 1.38922322e+00 2.01254427e-01 7.44465590e-01
-1.85294867e-01 6.75681293e-01 -8.67126048e-01 -4.45742935e-01
-1.61881566e-01 -4.45644915e-01 -7.12109625e-01 -6.68483004e-02
5.53622782e-01 -1.48776501e-01 -1.89690739e-01 9.98386800e-01
7.23888636e-01 8.47349316e-02 6.60718083e-01 -1.31468165e+00
-3.65936935e-01 9.96735156e-01 -4.66595799e-01 5.39397597e-02
5.68180501e-01 -2.67840296e-01 1.70144415e+00 -9.32479501e-01
1.89898610e-01 1.17970502e+00 7.09546030e-01 6.23410702e-01
-1.28971231e+00 -9.22217965e-01 8.17862377e-02 2.42190987e-01
-1.60767889e+00 -5.36591172e-01 1.00552106e+00 -6.12025201e-01
5.85990310e-01 2.77254790e-01 3.35709214e-01 1.39211690e+00
-1.35599881e-01 7.17048824e-01 5.28325498e-01 -4.26291943e-01
3.10301125e-01 1.10393271e-01 -1.32273361e-01 -1.00547001e-02
-2.66082555e-01 -1.67475656e-01 -6.44190073e-01 -2.79393792e-01
9.92079675e-02 -4.48743314e-01 -2.91390449e-01 1.44837946e-01
-1.15779483e+00 1.05706680e+00 1.65664166e-01 1.73851803e-01
-5.35889983e-01 4.82751191e-01 7.71108329e-01 -1.17942668e-01
4.62741226e-01 1.68918565e-01 -4.66249049e-01 -2.11047128e-01
-9.51346993e-01 4.27432299e-01 5.72202027e-01 9.62316871e-01
6.47421002e-01 -5.48329800e-02 -4.34776634e-01 1.32116413e+00
3.51700395e-01 4.68293577e-01 6.37585580e-01 -5.98761559e-01
6.75204575e-01 -7.09982738e-02 6.28153011e-02 -6.65792108e-01
-2.32362941e-01 -4.26434964e-01 -7.33686507e-01 -2.80607969e-01
5.51075712e-02 -2.90867686e-01 -8.37437630e-01 2.14854813e+00
-7.04568774e-02 3.03931713e-01 1.64039388e-01 1.03102803e+00
9.70665693e-01 1.28489530e+00 4.36665505e-01 -1.24448203e-01
1.83607769e+00 -8.89218211e-01 -6.97002649e-01 -4.50906724e-01
1.62353411e-01 -9.14156854e-01 1.13717794e+00 3.05436939e-01
-1.06413996e+00 -5.73992908e-01 -8.86055171e-01 3.10760271e-02
-1.94405422e-01 1.53488725e-01 2.01589316e-01 2.78925151e-01
-7.85896897e-01 1.24783076e-01 -2.47352988e-01 1.42526522e-01
1.40499160e-01 2.17344552e-01 -2.21856892e-01 2.44545981e-01
-1.72229910e+00 3.54256272e-01 7.14792788e-01 -2.87035167e-01
-1.25137281e+00 -8.15984964e-01 -1.03068566e+00 4.99917477e-01
1.19134523e-01 -2.82362282e-01 1.62193441e+00 -1.22516513e+00
-1.16826999e+00 7.42347896e-01 -8.44165310e-02 -7.54037738e-01
7.35658407e-03 -1.77818686e-01 -7.24068046e-01 3.58162165e-01
2.49780416e-01 1.12575233e+00 8.88808310e-01 -1.26210988e+00
-7.56861448e-01 2.80889273e-01 2.04632413e-02 2.18215406e-01
-5.14904082e-01 2.54187316e-01 -3.56648654e-01 -9.79318917e-01
-3.43657017e-01 -9.87537503e-01 1.74191937e-01 -1.42482430e-01
-5.07638872e-01 -2.06526965e-01 5.91875196e-01 -8.44740152e-01
1.36616242e+00 -2.60767126e+00 -5.13632782e-02 2.90282536e-02
-1.57900453e-02 1.08468980e-01 -2.61264116e-01 4.76048827e-01
-4.10958439e-01 -2.56730244e-02 -3.60235602e-01 -4.80696052e-01
2.10781977e-01 1.14484448e-02 -6.80874586e-01 7.15998709e-02
4.15376872e-01 4.04085845e-01 -8.20209563e-01 -5.51024079e-01
-1.41200110e-01 8.08479846e-01 -5.99846005e-01 4.29950148e-01
-4.90982324e-01 8.56084973e-02 -1.03390701e-01 3.77388954e-01
3.31463039e-01 -9.27043259e-02 -2.12124065e-01 -3.46971720e-01
1.37635097e-01 5.84144473e-01 -1.14582884e+00 1.58122182e+00
-8.09497774e-01 7.52281785e-01 1.46456838e-01 -8.85936379e-01
9.53089535e-01 9.15133059e-01 4.23084676e-01 -2.69888997e-01
1.37014881e-01 3.50888491e-01 -1.14461966e-01 -3.20126474e-01
4.96635675e-01 -6.05177999e-01 -4.10403758e-01 3.01333606e-01
3.86092156e-01 1.36128662e-03 1.33270979e-01 1.58737898e-01
9.07147050e-01 -2.77346641e-01 2.13815868e-01 8.55640694e-02
5.27769208e-01 -2.69212872e-01 4.81416762e-01 4.61062491e-01
1.61495153e-02 1.20908535e+00 4.92136836e-01 -3.24086808e-02
-1.17227769e+00 -1.01515698e+00 -1.46387115e-01 1.46916461e+00
-2.42089033e-01 -5.53304553e-01 -7.83357024e-01 -2.24514231e-01
-1.19889230e-01 8.00807953e-01 -5.22405744e-01 -3.52216482e-01
-4.79206800e-01 -4.51195568e-01 7.25098968e-01 5.10614991e-01
9.15704593e-02 -1.38422906e+00 -2.33244568e-01 5.79099357e-01
-6.85936689e-01 -1.28597915e+00 -8.23820174e-01 3.92872691e-01
-1.86802372e-01 -3.90221953e-01 -1.01158214e+00 -1.06245923e+00
1.46372736e-01 -2.41268486e-01 1.29989040e+00 -4.87758189e-01
-6.77035702e-03 2.59887964e-01 -6.29337609e-01 -7.24304080e-01
-6.39791965e-01 5.88215962e-02 1.22344688e-01 4.76350844e-01
2.33812734e-01 -6.51357710e-01 -4.03358132e-01 9.21903923e-02
-9.81268883e-01 1.22549916e-02 6.24757290e-01 8.27745199e-01
7.79577672e-01 -1.64275378e-01 9.23941255e-01 -4.64140087e-01
7.23429799e-01 -7.41526067e-01 -2.22777158e-01 -1.56713486e-01
-3.12148333e-02 -1.18269898e-01 8.83994997e-01 -8.69495511e-01
-6.10609174e-01 3.53903323e-01 -6.34057045e-01 -5.77972829e-01
-2.69088119e-01 5.98587215e-01 -3.72379541e-01 3.75982136e-01
5.43384850e-01 3.62452179e-01 -2.32713789e-01 -4.24963295e-01
2.06853911e-01 1.08587348e+00 7.42551744e-01 -5.39340258e-01
5.92237830e-01 8.34772438e-02 -3.36704969e-01 -8.62205625e-01
-1.04633701e+00 -6.19503736e-01 7.00014383e-02 -3.10618758e-01
9.70443189e-01 -1.38399744e+00 -4.63777781e-01 7.02079758e-02
-1.36704493e+00 7.93715864e-02 -4.48735088e-01 6.05849862e-01
-7.89299548e-01 5.93419299e-02 -4.84558731e-01 -8.80001605e-01
-5.22852421e-01 -1.05346274e+00 1.48949468e+00 2.98194848e-02
-4.54615027e-01 -6.15029097e-01 2.49790996e-01 2.60122299e-01
2.67441988e-01 2.02179611e-01 8.87604773e-01 -1.10311937e+00
7.39619806e-02 -2.84983784e-01 -8.19623321e-02 6.82569087e-01
-2.01429144e-01 -4.97489959e-01 -1.37032735e+00 -1.21917374e-01
-2.17781350e-01 -7.23961234e-01 7.18241692e-01 3.31270665e-01
1.32772934e+00 -5.39692998e-01 2.31739059e-02 2.18501627e-01
1.23074758e+00 2.56617516e-01 6.08961880e-01 -1.12845168e-01
5.13292849e-01 5.62777519e-01 5.36825240e-01 5.62576354e-01
1.96760774e-01 9.47271168e-01 5.34331858e-01 -4.59754579e-02
-2.69335568e-01 -4.68224943e-01 6.39957011e-01 1.02646732e+00
5.90718925e-01 -4.97357339e-01 -8.59149456e-01 9.38338041e-01
-1.52050102e+00 -9.28274632e-01 7.46589601e-02 2.05854368e+00
1.27786279e+00 1.74675792e-01 3.05952847e-01 4.64459658e-01
1.10991073e+00 1.22011155e-01 -2.64129072e-01 -4.84878331e-01
-7.60926008e-02 2.58920580e-01 4.04916294e-02 4.23138797e-01
-1.32479274e+00 4.42342728e-01 5.55001926e+00 1.05939651e+00
-1.01706421e+00 3.30338925e-01 4.74306345e-01 -1.88615024e-01
-3.21285516e-01 -2.77664840e-01 -8.05343807e-01 8.58718574e-01
1.48035836e+00 -1.83957383e-01 3.53053629e-01 7.15758145e-01
8.75648111e-02 3.06374818e-01 -1.24031591e+00 1.15607369e+00
2.79973179e-01 -1.05278468e+00 1.23816110e-01 -2.87169576e-01
4.54725176e-01 -3.42090987e-02 -6.57520071e-03 4.37900633e-01
-2.34498128e-01 -8.73870969e-01 1.35147130e+00 1.03213206e-01
1.03466702e+00 -6.70182645e-01 8.36135864e-01 -5.44059835e-02
-1.36106801e+00 2.04732660e-02 -1.43898085e-01 7.78978765e-02
5.32238185e-01 7.29593396e-01 -7.87035823e-01 2.21658155e-01
6.63393855e-01 3.25655758e-01 -8.46491233e-02 1.11790311e+00
-1.12466663e-01 1.03628409e+00 -3.48730117e-01 -1.19593434e-01
3.38498652e-01 2.75488019e-01 7.02041030e-01 1.60861421e+00
3.74844670e-01 -2.18288794e-01 7.44100213e-02 7.34267235e-01
-4.28392619e-01 2.19685927e-01 -2.88594961e-01 -2.09054247e-01
4.61857021e-01 1.05270004e+00 -2.39972204e-01 -3.21955621e-01
-4.19951469e-01 7.79543281e-01 -1.50175408e-01 2.24064633e-01
-1.16896701e+00 -7.37208128e-01 6.86476588e-01 1.87244177e-01
4.56204593e-01 3.15336019e-01 1.80726618e-01 -8.02987397e-01
2.17781916e-01 -7.69260287e-01 3.62492830e-01 -9.59398866e-01
-1.38953710e+00 7.75947154e-01 2.52569299e-02 -1.60543096e+00
-4.61613446e-01 -3.12891036e-01 -5.15738845e-01 8.35321069e-01
-1.49712133e+00 -9.10888493e-01 -2.22752616e-02 5.08562088e-01
6.64378345e-01 -1.63609728e-01 9.70241785e-01 9.60284412e-01
-1.51311502e-01 7.44702578e-01 -8.80921632e-02 2.27529630e-01
8.53842795e-01 -1.17797208e+00 1.49663329e-01 3.80104303e-01
3.88376832e-01 5.70422970e-02 1.05458415e+00 -1.58039898e-01
-8.46629262e-01 -1.46197593e+00 1.18248081e+00 -5.47217019e-03
7.85843432e-01 -8.98663580e-01 -9.41729724e-01 5.51676035e-01
1.17344312e-01 1.04176272e-02 9.78767395e-01 -7.92938024e-02
-4.43715215e-01 -2.33555451e-01 -8.34385812e-01 2.48425364e-01
4.61589158e-01 -7.99387217e-01 -7.07350373e-01 5.17822921e-01
1.21457970e+00 -2.74372846e-01 -6.06014550e-01 1.17769495e-01
5.28356254e-01 -4.47931767e-01 9.92052257e-01 -4.74196404e-01
7.25111425e-01 -3.58788908e-01 -4.14679527e-01 -1.30822098e+00
-1.35990262e-01 -5.30215621e-01 -7.32408911e-02 1.70403540e+00
6.85922861e-01 -9.94450077e-02 5.65373361e-01 -7.50875920e-02
-4.24170077e-01 -3.34980667e-01 -1.21888590e+00 -8.22223246e-01
-9.44980159e-02 -6.18944287e-01 4.78674442e-01 5.66311181e-01
-4.78153341e-02 7.86536217e-01 -8.24021459e-01 1.36028022e-01
3.27262521e-01 -5.24554774e-02 1.74750090e-01 -1.23818839e+00
-3.95699978e-01 -1.08919859e-01 -4.16762441e-01 -8.54961574e-01
3.17817211e-01 -9.58054245e-01 7.21576333e-01 -1.18638480e+00
1.61568880e-01 -6.82517290e-02 -2.93686479e-01 5.24806976e-01
1.10075906e-01 5.67114413e-01 2.16983780e-01 6.31572912e-03
-6.11927032e-01 6.76335275e-01 6.14707947e-01 -5.08399248e-01
-3.43731530e-02 1.23422444e-02 -6.24088049e-01 4.20817137e-01
7.40888417e-01 -7.82641768e-01 -1.45328686e-01 -3.03294569e-01
3.08111072e-01 1.88115045e-01 4.15252447e-01 -1.17325091e+00
2.19817515e-02 2.05677077e-01 -1.36566147e-01 -4.40961331e-01
7.27636874e-01 -9.40466046e-01 1.83468372e-01 1.91132471e-01
-7.47903347e-01 -1.64108142e-01 3.57352972e-01 5.61758101e-01
-7.86059022e-01 -4.86513942e-01 8.05544376e-01 1.83699355e-01
-3.67751062e-01 1.72776163e-01 -5.24724066e-01 3.40349406e-01
7.35751688e-01 2.86504298e-01 -2.69808918e-02 -8.00511897e-01
-8.91777992e-01 -3.67372632e-02 -1.85132474e-01 5.51551461e-01
5.62055290e-01 -1.72172213e+00 -1.08598721e+00 -9.22810435e-02
5.30598700e-01 -4.18571904e-02 1.67550117e-01 3.92695546e-01
-1.34909898e-01 4.28146094e-01 -7.27170333e-02 -4.28407162e-01
-1.05608296e+00 3.77074361e-01 1.34516418e-01 -3.03434674e-02
-3.92990828e-01 9.27059293e-01 4.33180988e-01 9.57835019e-02
6.96323097e-01 -1.65425152e-01 -3.24144781e-01 3.79958630e-01
7.27189481e-01 -1.12140231e-01 1.25639409e-01 -9.30819809e-01
-5.32791317e-01 4.12170678e-01 7.47702941e-02 -4.43780303e-01
1.18651724e+00 6.33341745e-02 7.17605725e-02 8.00055325e-01
1.60818720e+00 -2.78337654e-02 -9.58615065e-01 -1.22734465e-01
-1.94688693e-01 1.00133017e-01 1.86623156e-01 -8.17385256e-01
-8.82625818e-01 1.10706556e+00 6.00495636e-01 3.38314086e-01
1.25818729e+00 3.42642158e-01 1.00352407e+00 -3.35882567e-02
-1.23734390e-02 -1.07098305e+00 1.40392035e-01 5.06621778e-01
1.19668972e+00 -1.04311395e+00 -4.87670898e-01 -2.94021130e-01
-8.08003068e-01 9.49802816e-01 3.32316756e-01 1.15134165e-01
3.79816562e-01 2.17773125e-01 2.75709052e-02 -2.24650503e-04
-7.44161308e-01 -1.89872071e-01 3.47437859e-01 4.49374408e-01
3.85980099e-01 2.05024779e-01 -1.03965506e-01 1.09033573e+00
-4.11448061e-01 -2.75121838e-01 4.68671709e-01 3.58741790e-01
-4.18289065e-01 -9.17497814e-01 -5.44576526e-01 4.59564120e-01
-7.03946352e-01 -2.87629902e-01 -2.61791557e-01 1.71282068e-01
1.48539171e-01 1.00373149e+00 3.21093380e-01 -5.52866340e-01
3.97196233e-01 3.19605231e-01 -1.63651228e-01 -7.49087751e-01
-6.32948875e-01 2.75700003e-01 1.45968735e-01 -8.32449496e-02
-1.58846289e-01 -6.32284641e-01 -1.11825800e+00 3.12957823e-01
-3.11971903e-01 5.55384040e-01 7.70173609e-01 6.17146730e-01
1.79152369e-01 7.72554874e-01 6.82790935e-01 -8.44370186e-01
-5.01737297e-01 -1.07789707e+00 -6.06882870e-01 5.96055984e-01
6.68883741e-01 -5.05709589e-01 -6.96736038e-01 3.00401747e-01] | [15.267409324645996, 4.930999279022217] |
e30c7bee-8502-4bac-b253-6d0c2dd6d2ac | literature-review-on-vulnerability-detection | 2104.11230 | null | https://arxiv.org/abs/2104.11230v1 | https://arxiv.org/pdf/2104.11230v1.pdf | Literature review on vulnerability detection using NLP technology | Vulnerability detection has always been the most important task in the field of software security. With the development of technology, in the face of massive source code, automated analysis and detection of vulnerabilities has become a current research hotspot. For special text files such as source code, using some of the hottest NLP technologies to build models and realize the automatic analysis and detection of source code has become one of the most anticipated studies in the field of vulnerability detection. This article does a brief survey of some recent new documents and technologies, such as CodeBERT, and summarizes the previous technologies. | ['Jiajie Wu'] | 2021-04-23 | null | null | null | null | ['vulnerability-detection'] | ['miscellaneous'] | [-1.62249506e-01 -4.10094969e-02 -3.33046883e-01 -9.09178630e-02
-3.87616992e-01 -8.05598974e-01 2.60478854e-01 7.59923279e-01
-9.76822600e-02 1.69835776e-01 1.01543963e-01 -7.23261833e-01
-1.45910189e-01 -6.98889196e-01 -4.64542992e-02 -1.04378529e-01
-1.68769509e-01 -1.94897324e-01 4.93801326e-01 -3.79922062e-01
9.02147710e-01 1.08407795e-01 -1.29321206e+00 1.73257172e-01
7.17737198e-01 4.20129031e-01 -1.59158364e-01 3.90620708e-01
-8.81650746e-01 6.56886578e-01 -6.09437346e-01 -7.44684577e-01
1.14614993e-01 -9.11357924e-02 -7.73821890e-01 -5.47336817e-01
-2.41853923e-01 1.82512388e-01 2.24855989e-01 1.75698078e+00
2.32246265e-01 -4.42357391e-01 1.47535875e-01 -1.15610600e+00
-4.49317008e-01 1.09221888e+00 -9.85031843e-01 2.55334616e-01
6.57063305e-01 -3.84749711e-01 6.80081964e-01 -5.39994776e-01
4.49091405e-01 1.07679641e+00 4.59905237e-01 4.76131469e-01
-6.54506326e-01 -4.65445489e-01 -3.77558842e-02 1.86727285e-01
-1.34302437e+00 1.14236176e-01 9.39773262e-01 -8.18966746e-01
1.06709123e+00 1.72171861e-01 1.72180757e-01 6.27614856e-01
6.79971278e-01 4.63192403e-01 6.64270103e-01 -8.52722168e-01
1.84509277e-01 6.05623186e-01 8.06386232e-01 6.07260823e-01
4.27685708e-01 -1.92188367e-01 9.11924168e-02 -7.44655371e-01
-7.84419104e-02 1.11680673e-02 -8.02410021e-02 2.19350797e-03
-6.04059994e-01 8.77138853e-01 -1.25066459e-01 6.97174907e-01
1.87464565e-01 -1.96094364e-01 7.21538663e-01 2.64915347e-01
2.68582016e-01 5.03142834e-01 -4.84641463e-01 -6.85857773e-01
-8.89306307e-01 5.15602306e-02 8.22553992e-01 6.33851647e-01
3.69655669e-01 -7.75795504e-02 4.97999281e-01 4.31389660e-01
4.81711179e-01 2.21121669e-01 5.49251854e-01 -2.15040699e-01
6.55544639e-01 1.40662563e+00 -7.80178607e-02 -1.24953055e+00
-2.01432183e-01 -3.61463308e-01 -3.44978541e-01 4.23839420e-01
-5.41288257e-02 -2.38418937e-01 -4.12971109e-01 1.05026352e+00
2.07554027e-01 -4.49306756e-01 -3.45038809e-02 2.84276996e-02
5.24640858e-01 6.76692545e-01 2.59340882e-01 -2.11192057e-01
1.31418264e+00 -1.80331513e-01 -4.39362645e-01 -1.85598552e-01
5.35443783e-01 -9.72857952e-01 6.18343532e-01 3.47042680e-01
-2.06529856e-01 -1.12136222e-01 -9.87525105e-01 3.34123582e-01
-6.94627166e-01 -2.73656279e-01 6.75278604e-01 1.17441785e+00
-6.93416417e-01 1.05831854e-01 -5.31617999e-01 -3.64924192e-01
8.10413510e-02 -3.64491367e-03 -3.30240697e-01 1.31839156e-01
-1.11268103e+00 9.20506418e-01 7.06611097e-01 -3.64231884e-01
-5.36917567e-01 -4.21600133e-01 -5.40850937e-01 1.58166289e-01
5.73335946e-01 3.51283401e-01 8.47522259e-01 -7.36669064e-01
-8.96794617e-01 6.92152858e-01 6.64044917e-02 -4.50687259e-02
-5.71787991e-02 -5.34422934e-01 -8.23410988e-01 -3.40671092e-01
-9.98783112e-02 -2.33759150e-01 6.79867089e-01 -7.60500252e-01
-4.85963672e-01 -1.27802908e-01 1.89362660e-01 -4.96413022e-01
-8.55040729e-01 1.08418512e+00 1.13581732e-01 -3.37762564e-01
-3.09550941e-01 -5.79163134e-01 -2.75444239e-01 -4.62095201e-01
-3.80245805e-01 -4.48080093e-01 8.80188704e-01 -8.36408615e-01
1.95883775e+00 -2.35279584e+00 6.00598752e-02 3.68366033e-01
1.82443902e-01 5.04191339e-01 2.36533150e-01 8.40336978e-01
-4.18956995e-01 6.53171480e-01 -5.42792737e-01 1.65262863e-01
-9.73094553e-02 -4.70150888e-01 -6.05017662e-01 1.08886570e-01
-1.25847101e-01 4.01626557e-01 -7.08193898e-01 -6.11594081e-01
-1.36850655e-01 1.78949729e-01 -3.32262248e-01 4.08482477e-02
-2.68016100e-01 4.50760052e-02 -8.78118634e-01 7.42261767e-01
4.00378495e-01 5.57233952e-02 5.31271175e-02 4.05632854e-01
-7.03933418e-01 -1.15417503e-01 -9.96855497e-01 1.32477856e+00
-4.17473108e-01 6.06063426e-01 -2.33883426e-01 -6.06330633e-01
1.04081535e+00 5.80100179e-01 1.68050289e-01 -3.45318675e-01
2.47336537e-01 2.49239385e-01 1.60473391e-01 -1.02623236e+00
3.01618397e-01 2.96927482e-01 -6.21311367e-01 6.58603013e-01
-3.62410247e-01 6.62885094e-03 3.06441337e-01 3.10342759e-01
1.10566151e+00 -8.19000229e-02 8.27390194e-01 -1.94925115e-01
8.88388932e-01 2.45706290e-02 5.45589268e-01 8.15092549e-02
-1.09712586e-01 8.96186382e-03 9.61285710e-01 -5.81553638e-01
-7.91624546e-01 -5.38923919e-01 -1.45025849e-01 5.82049727e-01
-1.47723302e-01 -6.90022171e-01 -8.23043585e-01 -1.09623551e+00
-2.70211846e-01 4.39624578e-01 -4.20204997e-01 -8.20035413e-02
-5.91121316e-01 -8.68239939e-01 7.75089383e-01 2.25149214e-01
4.07248676e-01 -1.21048021e+00 -7.72212505e-01 1.45666674e-01
1.57827213e-02 -6.40981793e-01 1.32698238e-01 -7.95408636e-02
-6.71062350e-01 -1.16415834e+00 -2.12801293e-01 -5.47042191e-01
6.32462382e-01 -8.77991021e-02 8.73871684e-01 6.43861771e-01
-7.04127967e-01 -2.34544024e-01 -8.53780389e-01 -5.35843611e-01
-6.85887337e-01 1.73299044e-01 -3.08078021e-01 -3.05348545e-01
5.88729739e-01 -4.08683360e-01 8.68607163e-02 -9.90889817e-02
-9.65726376e-01 -6.33066833e-01 5.24673700e-01 1.75139964e-01
-8.42014179e-02 5.53352237e-01 5.24198174e-01 -1.06434834e+00
9.25601184e-01 -8.37364137e-01 -1.04312301e+00 5.61753392e-01
-5.03362536e-01 1.07740253e-01 5.89617372e-01 -4.39671539e-02
-1.15039515e+00 5.59458463e-03 -5.21481693e-01 5.00912011e-01
-2.53091723e-01 1.17599249e+00 -4.12903160e-01 -3.42928767e-01
7.23091424e-01 5.51698543e-02 -3.80567104e-01 -8.09789538e-01
1.97736949e-01 8.76831055e-01 -1.18430376e-01 -4.61607695e-01
9.90472138e-01 -7.10672960e-02 -1.70667574e-01 -7.54025519e-01
-3.05327177e-01 -5.30547619e-01 -3.79344136e-01 -1.95707619e-01
6.82365239e-01 -1.74286470e-01 -3.36932123e-01 4.74486202e-01
-1.27132785e+00 3.87563616e-01 2.03022987e-01 1.22505613e-01
3.00141424e-01 8.70719731e-01 -2.21479595e-01 -8.16733599e-01
-4.58209306e-01 -1.40669405e+00 2.88875669e-01 2.81338423e-01
-2.90887743e-01 -8.68565679e-01 6.76835537e-01 -2.55623609e-02
5.41153193e-01 4.26526725e-01 1.55205059e+00 -5.94465852e-01
-3.77626181e-01 -7.62203634e-01 -3.96305285e-02 2.99521595e-01
1.55062899e-01 7.28875160e-01 -6.29902184e-01 2.69029103e-02
2.88307726e-01 5.62221259e-02 2.94847667e-01 -3.00269097e-01
1.04803729e+00 -1.66594997e-01 -6.77731097e-01 1.62844568e-01
1.67425382e+00 6.53225064e-01 7.03489244e-01 5.52347541e-01
3.35967869e-01 8.93405259e-01 5.39428949e-01 3.20102721e-01
9.31203812e-02 3.70468676e-01 7.73311913e-01 5.55527806e-01
4.58494335e-01 -4.19820324e-02 4.11691368e-01 9.44618404e-01
2.00747758e-01 -5.95914647e-02 -1.64653337e+00 6.03650987e-01
-1.44370556e+00 -9.54824090e-01 -2.61823207e-01 1.93572426e+00
6.10514581e-01 3.27115625e-01 2.14502309e-02 5.34143448e-01
7.07155228e-01 -7.21518025e-02 6.41195253e-02 -5.08015275e-01
3.64969313e-01 -5.46912104e-02 7.05396086e-02 3.79461169e-01
-9.30747807e-01 6.63513899e-01 6.36998892e+00 6.05150402e-01
-9.51433957e-01 5.94928376e-02 1.43916517e-01 4.55921263e-01
-3.65246147e-01 4.61826861e-01 -8.52546513e-01 6.47792220e-01
9.26392019e-01 -3.02766263e-01 2.50252727e-02 1.35015094e+00
-1.33423001e-01 -2.57958561e-01 -5.92467070e-01 3.58343393e-01
1.18087716e-01 -8.87806535e-01 -1.34082973e-01 -1.00499354e-01
4.52332437e-01 -2.43379399e-01 8.19027871e-02 2.02801123e-01
1.71781898e-01 -7.53558159e-01 5.15332103e-01 1.04811087e-01
2.73646176e-01 -8.58510494e-01 1.08123410e+00 5.17433882e-01
-1.08848596e+00 -5.72898030e-01 -3.78243536e-01 -2.48642056e-04
1.66227162e-01 1.00510669e+00 -4.38976914e-01 5.71303844e-01
1.02299273e+00 5.46086550e-01 -7.40275145e-01 1.44606209e+00
-4.06511247e-01 5.94304383e-01 -1.15970932e-01 -3.00533563e-01
-2.97167063e-01 1.12782098e-01 5.83803117e-01 1.22548234e+00
2.39130393e-01 -1.45171329e-01 9.51321349e-02 6.95228040e-01
2.74580389e-01 3.50985020e-01 -5.61405063e-01 -3.88392448e-01
4.79004115e-01 1.32240534e+00 -9.51233804e-01 -6.92519844e-02
-6.49225593e-01 1.32797929e-02 1.68887094e-01 -1.46332368e-01
-6.37291253e-01 -1.02483463e+00 4.42729980e-01 4.78935391e-02
-2.86074311e-01 -3.87298584e-01 -2.99107552e-01 -1.05554807e+00
2.21625730e-01 -1.04410374e+00 3.57491255e-01 -1.32244855e-01
-8.35618496e-01 9.74022210e-01 1.98405072e-01 -1.17803299e+00
5.89027070e-02 -5.74450791e-01 -1.09722495e+00 7.58884549e-01
-1.17279696e+00 -7.80308843e-01 1.09708188e-02 2.58169591e-01
4.46929604e-01 -4.51949477e-01 9.51901138e-01 4.60984915e-01
-6.95392966e-01 3.30564737e-01 -1.34449765e-01 4.24556494e-01
3.52035254e-01 -9.12339926e-01 7.14274764e-01 1.37070346e+00
1.32970605e-02 1.15456939e+00 6.55959368e-01 -1.01745021e+00
-9.35921431e-01 -4.69953686e-01 1.03532100e+00 -5.85521042e-01
8.55121434e-01 -5.71056664e-01 -9.95753765e-01 4.42104757e-01
2.83676356e-01 -4.62537646e-01 8.07341218e-01 3.96172293e-02
-5.41687429e-01 -2.37773312e-03 -1.05631006e+00 3.40480089e-01
4.13335174e-01 -6.33215606e-01 -7.10420191e-01 -4.21711244e-02
6.70413673e-01 5.17928088e-03 -4.85723972e-01 1.34856254e-01
2.60806799e-01 -9.84299362e-01 5.74454963e-01 -2.45807588e-01
1.50193706e-01 -5.51939726e-01 1.00442290e-01 -8.63627255e-01
-5.05183311e-03 -5.08442163e-01 1.49586380e-01 1.58730948e+00
6.05627716e-01 -4.79580820e-01 6.57247961e-01 5.72416186e-01
1.97606325e-01 -3.09991568e-01 -8.00364971e-01 -3.78606409e-01
2.33629216e-02 -4.40380991e-01 7.41609097e-01 9.12108302e-01
7.71844208e-01 -3.32795560e-01 -3.25503200e-02 1.57023475e-01
4.96916473e-01 8.97988603e-02 3.25667381e-01 -1.48258102e+00
-3.29260707e-01 -3.96237850e-01 -6.64552808e-01 -1.98520765e-01
1.03756279e-01 -7.88329363e-01 -1.56311437e-01 -1.30830216e+00
3.51855546e-01 -1.06265679e-01 -1.34957790e-01 6.34263337e-01
-1.91673741e-01 -2.93572009e-01 1.21934274e-02 -2.72600278e-02
-3.16459924e-01 2.14603916e-03 2.46314719e-01 -5.73127121e-02
4.37109657e-02 3.26452523e-01 -6.63938880e-01 9.12831604e-01
8.98018718e-01 -1.00142884e+00 -4.82356459e-01 -3.20751280e-01
1.13690817e+00 1.20212749e-01 -2.44930401e-01 -9.24841285e-01
3.23089689e-01 -3.72368485e-01 -3.24203759e-01 -1.80144414e-01
-3.12808096e-01 -9.87477481e-01 3.33796516e-02 7.23611176e-01
-1.32142186e-01 6.11042261e-01 3.82757336e-01 2.16482341e-01
-4.16352212e-01 -9.04292405e-01 5.50355852e-01 -2.16272324e-01
-9.53495920e-01 1.14900686e-01 -5.83076954e-01 -9.99774113e-02
1.39483118e+00 3.61214727e-02 -5.72786927e-01 2.74787903e-01
-1.30016223e-01 4.95649055e-02 3.43592018e-01 1.06359231e+00
7.60159731e-01 -4.01314318e-01 -3.76001149e-01 7.82302320e-02
2.53044546e-01 -6.34209931e-01 2.09314466e-01 2.85610050e-01
-5.46110690e-01 3.63765150e-01 -3.29903364e-01 7.52768666e-02
-1.62809372e+00 9.32008743e-01 3.67755815e-02 -3.00585866e-01
-4.36266035e-01 6.80462122e-01 -1.73246175e-01 -3.07634380e-02
1.47090212e-01 1.61598861e-01 -9.62794363e-01 -2.79532641e-01
9.24418926e-01 3.46767545e-01 -5.77422604e-03 -3.80629241e-01
-6.45199120e-01 7.35811830e-01 -2.71562815e-01 2.08567947e-01
1.25229514e+00 2.08854347e-01 -9.28902626e-01 2.37992600e-01
7.83798635e-01 4.77340251e-01 -4.55370903e-01 2.65823901e-01
8.06040943e-01 -5.23762822e-01 -2.62622029e-01 -1.06336737e+00
-8.89570236e-01 1.09503818e+00 4.39229071e-01 5.22736251e-01
8.01809609e-01 -2.42808670e-01 2.94416815e-01 7.60645643e-02
8.79695535e-01 -6.57033503e-01 -1.48930177e-01 5.46193242e-01
5.33281803e-01 -1.09938788e+00 6.11880347e-02 -6.10787570e-01
-1.70090631e-01 1.26242566e+00 5.53691506e-01 1.29551381e-01
1.15248001e+00 7.04619408e-01 2.26403296e-01 -3.14971268e-01
-3.09385180e-01 4.09869581e-01 8.46502632e-02 5.07114112e-01
7.94305563e-01 -9.57773179e-02 -5.01156151e-01 5.77041924e-01
3.70842521e-03 -1.90316051e-01 8.21850121e-01 1.25629294e+00
-7.07767904e-01 -1.77758682e+00 -5.05454957e-01 2.43775323e-01
-1.13146448e+00 -2.44737908e-01 -6.01050854e-01 5.15470505e-01
1.37157395e-01 1.07793260e+00 -6.91597044e-01 -5.11490762e-01
2.46922567e-01 1.29538402e-01 -1.84140235e-01 -8.95361066e-01
-9.33834732e-01 -8.49309444e-01 -2.71340907e-01 -2.94994593e-01
-1.35572895e-01 -2.71076858e-01 -1.16069245e+00 -3.58375162e-01
-5.08134782e-01 8.09799433e-01 9.69278753e-01 8.09348226e-01
3.14666182e-01 3.33190620e-01 3.66969585e-01 -6.34319186e-02
-4.29950297e-01 -6.45655513e-01 -1.92136213e-01 5.11310846e-02
1.89947888e-01 -4.80433464e-01 -2.78776079e-01 -1.54078926e-03] | [7.034426689147949, 7.768433570861816] |
c0ed9ee6-c5e0-45b6-998d-35c1905191b2 | shoring-design-provable-conditional-high | 2107.01326 | null | https://arxiv.org/abs/2107.01326v1 | https://arxiv.org/pdf/2107.01326v1.pdf | SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing | Deep learning provides a promising way to extract effective representations from raw data in an end-to-end fashion and has proven its effectiveness in various domains such as computer vision, natural language processing, etc. However, in domains such as content/product recommendation and risk management, where sequence of event data is the most used raw data form and experts derived features are more commonly used, deep learning models struggle to dominate the game. In this paper, we propose a symbolic testing framework that helps to answer the question of what kinds of expert-derived features could be learned by a neural network. Inspired by this testing framework, we introduce an efficient architecture named SHORING, which contains two components: \textit{event network} and \textit{sequence network}. The \textit{event} network learns arbitrarily yet efficiently high-order \textit{event-level} embeddings via a provable reparameterization trick, the \textit{sequence} network aggregates from sequence of \textit{event-level} embeddings. We argue that SHORING is capable of learning certain standard symbolic expressions which the standard multi-head self-attention network fails to learn, and conduct comprehensive experiments and ablation studies on four synthetic datasets and three real-world datasets. The results show that SHORING empirically outperforms the state-of-the-art methods. | ['Yuan Qi', 'Tao Xiong', 'Leilei Shi', 'Shuai Chen', 'Weiqiang Wang', 'xiaofu Chang', 'Kai Xiao', 'Jinyu Xu', 'Ruofan Wu', 'Xing Fu', 'Hui Li'] | 2021-07-03 | null | null | null | null | ['product-recommendation'] | ['miscellaneous'] | [ 3.71487379e-01 1.27341613e-01 -4.06648368e-01 -4.60105419e-01
-5.40725708e-01 -6.83330715e-01 5.76551616e-01 1.84213027e-01
-6.48193955e-01 6.50923371e-01 -1.01164781e-01 -7.59155631e-01
-2.83987463e-01 -9.26462114e-01 -1.21631241e+00 -5.52508533e-01
-3.15324336e-01 4.76906568e-01 8.59211385e-02 -5.25652289e-01
8.39758515e-02 3.03561985e-01 -1.47904253e+00 4.65232521e-01
5.39140999e-01 1.40333152e+00 -1.44580260e-01 4.91450369e-01
-5.68117611e-02 1.12201881e+00 -4.15777236e-01 -6.45276666e-01
4.81127799e-01 -2.05535561e-01 -7.83917427e-01 -5.82643747e-01
6.43283874e-02 -4.05493647e-01 -4.87612814e-01 1.16356850e+00
4.45271432e-01 1.86975390e-01 4.52473819e-01 -1.47368705e+00
-8.87087524e-01 9.90483642e-01 -2.38929138e-01 3.95342201e-01
1.97499186e-01 3.68736297e-01 1.37880921e+00 -8.64042401e-01
5.59010506e-01 1.13094640e+00 4.87263888e-01 3.91380072e-01
-1.09882689e+00 -8.58546019e-01 -6.74515739e-02 5.51823676e-01
-1.19824195e+00 -8.09937194e-02 8.05977046e-01 -2.23422259e-01
1.04727530e+00 2.75221169e-01 4.46747780e-01 1.54341042e+00
4.03929889e-01 1.20253897e+00 1.03016210e+00 -2.08187416e-01
4.08006161e-01 -6.56180754e-02 3.27007353e-01 8.53659093e-01
1.60196349e-01 4.20065135e-01 -5.86353302e-01 -1.47861883e-01
6.08209968e-01 2.59289593e-01 1.41404085e-02 -2.86207683e-02
-1.17923439e+00 1.32252514e+00 4.40309346e-01 4.24119294e-01
-3.22134435e-01 5.86809158e-01 8.33565474e-01 6.55890346e-01
2.77619392e-01 5.90028465e-01 -8.21058333e-01 -6.63646832e-02
-7.55135834e-01 2.85465330e-01 7.27834761e-01 7.92460382e-01
5.79835355e-01 3.01378697e-01 -1.27346501e-01 3.41283888e-01
-1.24355935e-01 2.32804775e-01 6.86275065e-01 -7.35951900e-01
3.15183133e-01 4.79089260e-01 -8.93201828e-02 -7.86114931e-01
-4.83328015e-01 -4.70311195e-01 -9.14564788e-01 1.21251941e-01
3.19753855e-01 -2.76153415e-01 -7.08793998e-01 1.83936560e+00
8.62627849e-02 5.74113071e-01 1.42485667e-02 7.75139332e-01
4.83191311e-01 8.27262700e-01 -2.87086070e-02 -1.44909889e-01
1.23863316e+00 -9.23194110e-01 -3.87637079e-01 -2.14433640e-01
7.49246180e-01 -1.70093864e-01 1.19849396e+00 7.08736837e-01
-9.90107179e-01 -6.11083984e-01 -1.29859686e+00 -2.66009606e-02
-6.95652425e-01 -2.28268474e-01 1.03128052e+00 2.99314708e-01
-7.06491232e-01 8.45983446e-01 -5.69171250e-01 2.36810088e-01
4.01655614e-01 5.56983173e-01 -5.19761086e-01 1.41786814e-01
-1.63988006e+00 8.80107701e-01 7.74134457e-01 1.20944239e-01
-1.16191113e+00 -6.37368143e-01 -1.13819754e+00 3.20645690e-01
7.02335119e-01 -6.28836930e-01 1.28865874e+00 -1.06043732e+00
-1.65436006e+00 5.98792017e-01 3.17092448e-01 -9.05992150e-01
1.55437425e-01 -4.10099238e-01 -4.84661609e-01 1.37537062e-01
-5.27807660e-02 2.09621027e-01 9.75652993e-01 -4.89855319e-01
-4.41224039e-01 -4.00921226e-01 3.31083059e-01 -4.71348792e-01
-2.75156230e-01 2.30333418e-01 1.31136209e-01 -6.85732603e-01
-4.27386969e-01 -9.30055857e-01 -2.44499177e-01 -1.45698592e-01
-3.91681761e-01 -6.49893641e-01 5.41959405e-01 -3.76497865e-01
1.15713048e+00 -2.25319147e+00 3.30431342e-01 2.18573660e-01
2.80484229e-01 4.64365780e-01 -2.21061811e-01 4.88175273e-01
-4.21005189e-01 2.32986540e-01 -1.32084236e-01 4.92494181e-02
2.58398086e-01 2.28572652e-01 -6.95434093e-01 4.50555772e-01
5.79798460e-01 1.20277810e+00 -1.07773650e+00 -1.89976141e-01
1.35718942e-01 1.58149973e-01 -6.37347281e-01 1.28691912e-01
-5.98192632e-01 9.01644900e-02 -6.16464555e-01 4.89485919e-01
2.72612244e-01 -4.68449414e-01 -4.89822626e-02 4.15236019e-02
1.60353363e-01 2.01508030e-01 -1.03313220e+00 1.76011479e+00
-4.35687393e-01 3.97553533e-01 -4.67957228e-01 -1.43965161e+00
6.65564120e-01 4.48332168e-02 2.51013726e-01 -7.75866330e-01
4.43836421e-01 1.74499854e-01 1.50949299e-01 -5.21657407e-01
3.29998761e-01 -3.02922249e-01 -6.88762069e-01 3.60576361e-01
3.97795856e-01 5.33788055e-02 2.59247087e-02 1.12866044e-01
1.36747909e+00 2.94479746e-02 4.73425567e-01 -2.87765767e-02
4.80343312e-01 -1.74809650e-01 4.86435175e-01 7.43843973e-01
-9.01836380e-02 1.20600566e-01 8.45530450e-01 -8.91519427e-01
-9.96622622e-01 -1.10675991e+00 6.00625984e-02 1.63706803e+00
-3.69008854e-02 -5.06303728e-01 -4.74154174e-01 -7.89509833e-01
1.84782948e-02 1.06207943e+00 -8.72257113e-01 -6.58125758e-01
-6.10583723e-01 -4.81758773e-01 9.36768115e-01 8.34842205e-01
4.62182015e-01 -1.22536719e+00 -6.23544097e-01 3.88965547e-01
2.10111231e-01 -9.38473880e-01 -3.20023268e-01 6.06855333e-01
-3.77090067e-01 -9.22780454e-01 -1.87668964e-01 -6.51842952e-01
1.27397925e-01 -3.26361865e-01 1.08996129e+00 -2.29600459e-01
-3.65327865e-01 -8.95744264e-02 -4.13923115e-01 -7.01969147e-01
-2.82281071e-01 5.67107722e-02 1.60463348e-01 6.85494766e-02
5.04530251e-01 -6.35518968e-01 -3.72241080e-01 7.21347481e-02
-1.38863456e+00 -1.04063787e-01 7.71726072e-01 1.17787969e+00
5.05567968e-01 -1.57917589e-02 6.93251371e-01 -9.69829977e-01
6.12024963e-01 -7.17598259e-01 -7.23862410e-01 1.75618291e-01
-4.22545493e-01 5.08908987e-01 1.23636258e+00 -7.06711411e-01
-4.68126357e-01 -1.70043603e-01 -2.09995121e-01 -6.71058059e-01
1.67918444e-01 8.72205496e-01 8.29140618e-02 2.57844537e-01
7.11291611e-01 4.05979246e-01 -9.40189958e-02 -1.43408865e-01
4.23178464e-01 4.13090408e-01 5.36835253e-01 -7.50635505e-01
7.57359564e-01 1.44814894e-01 1.15043655e-01 -4.36635941e-01
-1.15685117e+00 -1.15379773e-01 -1.94199175e-01 2.51572788e-01
8.37723851e-01 -6.02186143e-01 -1.18358338e+00 2.18797043e-01
-1.13802493e+00 -3.24294716e-01 -6.19761288e-01 3.78770679e-01
-7.84050345e-01 5.94348051e-02 -7.56641626e-01 -6.36332512e-01
-4.10841912e-01 -1.17214525e+00 1.19637954e+00 7.31623843e-02
-7.68371075e-02 -7.85252094e-01 -1.27201602e-01 -8.56437255e-03
3.40938121e-01 5.40185809e-01 1.26750660e+00 -1.29942155e+00
-4.18388486e-01 -3.26338112e-01 2.74102110e-03 7.13755846e-01
-4.25288111e-01 -4.34027880e-01 -8.37392509e-01 -2.02094719e-01
1.80185303e-01 -7.57457256e-01 7.93339968e-01 1.48105863e-02
1.76949346e+00 -4.85518903e-01 1.34988144e-01 6.93109334e-01
1.26417947e+00 1.15865000e-01 7.31895387e-01 2.74400294e-01
4.10524994e-01 2.87724733e-01 3.92059505e-01 5.43189049e-01
1.44054711e-01 4.35876071e-01 7.04179585e-01 4.03486758e-01
4.74892139e-01 -3.70558977e-01 7.30345130e-01 6.78685784e-01
-2.29197070e-02 -1.38257340e-01 -6.67712569e-01 2.70385057e-01
-1.86880183e+00 -1.22565842e+00 4.66382861e-01 1.86771858e+00
8.85733664e-01 4.30000752e-01 -5.32533824e-02 2.72805512e-01
3.80719185e-01 2.75892794e-01 -8.97354424e-01 -7.20708311e-01
-4.80549894e-02 1.01668453e+00 4.48342115e-01 4.52153273e-02
-1.03945708e+00 1.00383246e+00 5.37971401e+00 1.06886828e+00
-1.20298088e+00 2.18434647e-01 6.54048145e-01 -1.78389296e-01
-3.14048439e-01 -1.61415890e-01 -7.00857282e-01 5.88074505e-01
1.49628794e+00 -3.70622635e-01 5.62067628e-01 1.13531339e+00
-2.95055211e-01 3.60252798e-01 -1.63334417e+00 9.90838349e-01
1.91553067e-02 -1.67802000e+00 5.92315048e-02 4.46398184e-02
3.37567925e-01 5.11935651e-02 3.07825208e-01 9.95719016e-01
4.39464748e-01 -1.46073592e+00 8.38007331e-01 3.09450597e-01
9.45513487e-01 -8.46048355e-01 7.12111473e-01 5.65604270e-01
-9.51888442e-01 -4.17742819e-01 -2.79343784e-01 -1.17025711e-01
-5.96848987e-02 4.29692596e-01 -8.30010772e-01 6.39098883e-01
4.97202903e-01 5.34761429e-01 -3.21943372e-01 3.92355740e-01
-3.21789205e-01 7.37993717e-01 -2.55744874e-01 -3.39281201e-01
6.19939029e-01 2.90735136e-03 2.18615294e-01 1.02235782e+00
2.30849892e-01 1.34492144e-01 1.71083361e-01 9.28805649e-01
-3.69983226e-01 -1.70311049e-01 -8.27782393e-01 -3.18541378e-01
1.89781800e-01 1.07063985e+00 -3.46484512e-01 -3.63757610e-01
-3.91161859e-01 9.71391261e-01 4.74565774e-01 1.66152716e-01
-1.23917460e+00 -6.88420773e-01 6.10762894e-01 -5.81166670e-02
4.75730360e-01 -2.14644223e-01 -4.57402207e-02 -1.28348398e+00
2.05936879e-02 -1.13850713e+00 5.07455766e-01 -6.90495133e-01
-1.26007473e+00 5.72531641e-01 4.60749529e-02 -9.58432734e-01
-6.86904311e-01 -1.14354551e+00 -5.31154633e-01 4.96013045e-01
-1.40694201e+00 -9.99621511e-01 2.93352693e-01 8.73575509e-01
5.78208864e-01 -3.71230245e-01 9.64161098e-01 1.48313195e-01
-5.24809837e-01 9.12156224e-01 1.31496359e-02 3.78593653e-01
1.91157669e-01 -1.17069852e+00 3.37690234e-01 6.57108247e-01
3.56602937e-01 7.77720571e-01 5.72763979e-01 -2.30281323e-01
-2.04119277e+00 -1.22978926e+00 5.10195911e-01 -3.24057847e-01
1.06394231e+00 -4.93898064e-01 -5.59646308e-01 1.13435709e+00
7.23549947e-02 5.36679983e-01 7.87032962e-01 2.17378736e-02
-6.75215244e-01 -2.00212777e-01 -1.13500381e+00 6.83704376e-01
1.16080308e+00 -8.36944222e-01 -8.18930268e-01 3.49827230e-01
1.13660395e+00 -3.48993957e-01 -7.79480219e-01 4.16202098e-01
4.20162976e-01 -8.09220731e-01 8.97494137e-01 -1.16809666e+00
7.52879322e-01 -3.55378278e-02 -3.31496835e-01 -1.30121458e+00
-3.08372557e-01 -9.57782924e-01 -5.29100001e-01 7.10760236e-01
4.03376818e-01 -8.03280532e-01 6.23702288e-01 3.07205439e-01
-2.95424908e-01 -1.01212120e+00 -1.16186690e+00 -9.38067555e-01
2.41656125e-01 -7.92875648e-01 6.40122950e-01 8.28831613e-01
-4.10722978e-02 6.33373976e-01 -3.97113651e-01 -1.28765842e-02
2.59227216e-01 2.35876963e-01 5.30677855e-01 -1.20556045e+00
-6.28667414e-01 -4.08438712e-01 -6.93983912e-01 -8.50861728e-01
5.95400214e-01 -1.26610899e+00 -2.51359105e-01 -8.19502652e-01
5.04064299e-02 -1.19667307e-01 -6.73484385e-01 6.44889593e-01
1.54175282e-01 -7.43322819e-02 1.06625110e-01 -3.60187531e-01
-6.87945545e-01 5.42238295e-01 9.85738993e-01 -3.77459943e-01
2.09861025e-01 -3.02302241e-01 -9.58487034e-01 7.82034278e-01
5.99375546e-01 -4.35754299e-01 -4.48482156e-01 -2.79608935e-01
6.82418764e-01 1.85757920e-01 4.86488044e-01 -7.88583696e-01
2.71945775e-01 -2.38289356e-01 2.60957718e-01 -3.19173962e-01
3.77147466e-01 -7.21348941e-01 -1.47027075e-01 5.12987792e-01
-6.69154227e-01 3.09649289e-01 1.39178842e-01 5.61319828e-01
-2.73654252e-01 -3.80358994e-01 5.59930921e-01 -1.59014165e-01
-8.22524488e-01 4.65525627e-01 -5.53091206e-02 3.11241597e-01
1.24664021e+00 2.18831614e-01 -2.55316377e-01 -2.16927767e-01
-6.09732807e-01 1.63015798e-01 -1.41358867e-01 4.72356886e-01
7.44245172e-01 -1.41424227e+00 -7.05916345e-01 3.77060622e-01
9.16254595e-02 1.18153721e-01 -3.92947979e-02 6.29455209e-01
-2.65096575e-01 4.21300352e-01 -1.22249760e-01 -3.47296268e-01
-5.84922254e-01 9.68507886e-01 -4.69207577e-03 -6.35513484e-01
-4.39426064e-01 9.04199421e-01 1.64259464e-01 -2.94304818e-01
1.94401607e-01 -8.21541607e-01 3.33520740e-01 -1.30690068e-01
7.45676816e-01 2.47270241e-01 8.46738070e-02 -2.65034497e-01
-2.74196506e-01 1.37071133e-01 -2.94637054e-01 5.87470792e-02
1.62383366e+00 6.80858135e-01 -3.24891061e-02 5.70354223e-01
1.52823651e+00 -4.29830432e-01 -8.43431413e-01 -2.13040695e-01
2.47669101e-01 -9.22404006e-02 -2.10125983e-01 -6.09522700e-01
-8.27876270e-01 9.95103538e-01 2.68798053e-01 3.70122045e-01
1.08337009e+00 4.52014655e-02 1.11499214e+00 8.53136361e-01
7.52085924e-01 -1.02132881e+00 3.69462043e-01 8.39083970e-01
9.74346876e-01 -1.05863893e+00 -4.03086066e-01 2.61087716e-02
-5.67470431e-01 1.16113484e+00 3.60375553e-01 -5.75114071e-01
6.60049915e-01 2.86920696e-01 -7.52936244e-01 -1.31337479e-01
-9.81034815e-01 -1.50323167e-01 1.71098828e-01 9.86241624e-02
2.43827421e-02 -1.35359699e-02 -2.24744789e-02 1.17441905e+00
-4.48630333e-01 2.73544908e-01 3.24005723e-01 8.20455790e-01
-3.06267917e-01 -1.08000028e+00 2.30221171e-02 6.63735926e-01
-6.87762558e-01 -2.75828212e-01 -6.47495836e-02 7.75865853e-01
3.55763704e-01 5.71984589e-01 -1.16687223e-01 -6.68755293e-01
3.09625715e-01 3.41300964e-01 5.31525791e-01 -6.36664510e-01
-7.40015447e-01 -4.05901790e-01 1.17379412e-01 -8.19425941e-01
4.57015894e-02 -3.92071337e-01 -1.44416285e+00 -3.62068772e-01
-2.29599372e-01 9.84239974e-04 4.49734420e-01 1.04554462e+00
3.67728889e-01 5.93220353e-01 8.04539025e-01 -7.51286864e-01
-1.24837053e+00 -7.58236408e-01 -5.32708526e-01 5.66236019e-01
3.86824697e-01 -6.33082926e-01 -4.05013531e-01 -9.70740318e-02] | [10.540862083435059, 8.0144624710083] |
d101f409-c278-492a-a957-ee867b82d38e | neural-residual-radiance-fields-for | 2304.04452 | null | https://arxiv.org/abs/2304.04452v2 | https://arxiv.org/pdf/2304.04452v2.pdf | Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos | The success of the Neural Radiance Fields (NeRFs) for modeling and free-view rendering static objects has inspired numerous attempts on dynamic scenes. Current techniques that utilize neural rendering for facilitating free-view videos (FVVs) are restricted to either offline rendering or are capable of processing only brief sequences with minimal motion. In this paper, we present a novel technique, Residual Radiance Field or ReRF, as a highly compact neural representation to achieve real-time FVV rendering on long-duration dynamic scenes. ReRF explicitly models the residual information between adjacent timestamps in the spatial-temporal feature space, with a global coordinate-based tiny MLP as the feature decoder. Specifically, ReRF employs a compact motion grid along with a residual feature grid to exploit inter-frame feature similarities. We show such a strategy can handle large motions without sacrificing quality. We further present a sequential training scheme to maintain the smoothness and the sparsity of the motion/residual grids. Based on ReRF, we design a special FVV codec that achieves three orders of magnitudes compression rate and provides a companion ReRF player to support online streaming of long-duration FVVs of dynamic scenes. Extensive experiments demonstrate the effectiveness of ReRF for compactly representing dynamic radiance fields, enabling an unprecedented free-viewpoint viewing experience in speed and quality. | ['Minye Wu', 'Lan Xu', 'Tinne Tuytelaars', 'Jingyi Yu', 'Ziyu Wang', 'Qihan He', 'Qiang Hu', 'Liao Wang'] | 2023-04-10 | null | http://openaccess.thecvf.com//content/CVPR2023/html/Wang_Neural_Residual_Radiance_Fields_for_Streamably_Free-Viewpoint_Videos_CVPR_2023_paper.html | http://openaccess.thecvf.com//content/CVPR2023/papers/Wang_Neural_Residual_Radiance_Fields_for_Streamably_Free-Viewpoint_Videos_CVPR_2023_paper.pdf | cvpr-2023-1 | ['neural-rendering'] | ['computer-vision'] | [ 2.70427912e-01 -6.13367379e-01 -1.26618430e-01 -4.08705235e-01
-4.78815019e-01 -3.72313738e-01 4.53440905e-01 -5.36226869e-01
-1.38023123e-01 2.48106197e-01 3.82936925e-01 -3.48119676e-01
-3.98261510e-02 -9.09718812e-01 -8.94241333e-01 -7.09562719e-01
-2.70508051e-01 -4.88055348e-01 2.47343704e-01 -3.66575658e-01
1.77817702e-01 6.80809796e-01 -1.93913054e+00 6.91567242e-01
4.59520429e-01 1.30462873e+00 7.10672259e-01 1.22619402e+00
6.54049888e-02 1.23025560e+00 -4.47298586e-01 6.45493269e-02
6.27106965e-01 -1.73467711e-01 -3.95983696e-01 -6.11639321e-02
7.28768170e-01 -1.12412441e+00 -9.86477256e-01 5.47164261e-01
6.13095105e-01 6.02191448e-01 1.12953141e-01 -8.33086967e-01
-5.90753436e-01 -9.65121109e-03 -4.50372100e-01 4.26202923e-01
5.58064044e-01 1.08437009e-01 8.21205199e-01 -7.84569621e-01
6.05209112e-01 1.01639044e+00 6.02493525e-01 5.53351521e-01
-7.49536514e-01 -3.45764965e-01 4.00633723e-01 2.44255438e-01
-1.29092979e+00 -4.74027187e-01 7.46744156e-01 -2.17364177e-01
1.42840683e+00 7.46381700e-01 8.04876924e-01 7.49283612e-01
4.99051422e-01 4.48053837e-01 4.94597584e-01 -1.14483580e-01
1.47542536e-01 -4.93757606e-01 -2.99434036e-01 7.22200096e-01
-5.13324797e-01 3.53328735e-01 -6.89210713e-01 -1.21147186e-01
1.37166393e+00 2.63845623e-01 -8.14579010e-01 -7.71290213e-02
-1.31483817e+00 7.65313268e-01 6.01032257e-01 -2.06250753e-02
-3.46095890e-01 6.89136088e-01 4.91734207e-01 3.26148480e-01
6.59221351e-01 -1.16005637e-01 -4.72161084e-01 -1.95528865e-01
-8.73308361e-01 1.29901096e-01 4.35361356e-01 9.63101029e-01
4.63119894e-01 5.32468200e-01 -5.73370233e-02 7.30453253e-01
1.45140246e-01 5.58421493e-01 6.35121942e-01 -1.44384456e+00
4.81380045e-01 -9.08119678e-02 7.40053579e-02 -1.35534346e+00
-2.45982572e-01 -1.48858011e-01 -9.45986927e-01 4.33779508e-01
-2.68295288e-01 6.63047209e-02 -7.87180722e-01 1.59438717e+00
4.62641954e-01 4.80217785e-01 2.53845397e-02 1.08432806e+00
9.43377733e-01 1.39065874e+00 -4.08664346e-01 -2.48887435e-01
9.45804477e-01 -9.26705182e-01 -6.10417783e-01 1.64239034e-01
4.72884566e-01 -5.01787901e-01 1.11552489e+00 4.76315618e-01
-1.26890790e+00 -8.94528687e-01 -1.01304984e+00 -4.38590199e-01
6.18614964e-02 -4.55298312e-02 7.69544005e-01 2.39922047e-01
-1.26276171e+00 8.66198897e-01 -1.05033827e+00 4.62656766e-01
8.30198303e-02 3.19877595e-01 -2.53995866e-01 -1.76276892e-01
-1.04911423e+00 1.92137778e-01 -1.29001476e-02 2.08127677e-01
-7.08722651e-01 -9.09298599e-01 -9.33326185e-01 2.37872079e-01
1.74869746e-01 -8.10950875e-01 1.14562070e+00 -1.10402286e+00
-1.76575279e+00 3.96495223e-01 -4.38347727e-01 -2.91660935e-01
4.17585254e-01 -4.36288655e-01 -5.74386001e-01 5.08377075e-01
-2.98660785e-01 5.49635112e-01 9.09414172e-01 -1.05087018e+00
-6.41915441e-01 1.34168565e-02 3.21883053e-01 4.45138544e-01
-1.52631894e-01 -1.41850822e-02 -5.55079639e-01 -8.72239530e-01
2.66304612e-01 -6.06001019e-01 -3.10038179e-01 4.41407561e-01
3.11651547e-02 1.20513253e-01 8.86880696e-01 -7.51167357e-01
1.11379540e+00 -2.26590824e+00 4.12272215e-02 -2.26489324e-02
3.73332262e-01 2.11435124e-01 -1.15157388e-01 2.12859184e-01
-1.03981435e-01 -3.01102042e-01 1.55892715e-01 -1.87300205e-01
-2.88623571e-01 2.82489598e-01 -7.62447774e-01 4.57287967e-01
-2.06969708e-01 7.60386765e-01 -8.55250001e-01 4.57250401e-02
4.79497969e-01 1.08130383e+00 -1.02403617e+00 4.51081872e-01
-3.16380620e-01 5.22518456e-01 -3.40324968e-01 4.04896170e-01
8.08094025e-01 -4.67565507e-01 -8.45877156e-02 -4.74834979e-01
-4.06671166e-01 4.28839326e-01 -1.12713504e+00 1.86973929e+00
-6.96362138e-01 9.42695737e-01 3.41673344e-02 -4.65457708e-01
7.61376858e-01 1.54677168e-01 6.54920101e-01 -1.01890111e+00
4.15672995e-02 1.87958013e-02 -6.02600157e-01 -4.96394217e-01
1.09494984e+00 2.01819196e-01 3.48505408e-01 1.52887538e-01
-2.78808206e-01 8.73718709e-02 -1.41482353e-01 1.72149792e-01
1.05638015e+00 5.69670022e-01 9.15331170e-02 9.75591019e-02
3.98461014e-01 -4.32521909e-01 6.16966724e-01 4.81471241e-01
1.84280202e-01 1.07231426e+00 -1.83713228e-01 -7.58464932e-01
-1.00841570e+00 -1.03262699e+00 6.82591647e-02 1.24940336e+00
3.99974853e-01 -6.56531334e-01 -2.84458995e-01 -2.15192810e-01
-2.30103299e-01 5.07134259e-01 -3.16988438e-01 2.36117467e-02
-1.10143447e+00 -2.87917525e-01 3.12727019e-02 6.44922495e-01
6.17620111e-01 -8.35562229e-01 -1.18522501e+00 2.18046755e-01
-3.51896405e-01 -1.09288490e+00 -5.88683009e-01 1.50802881e-01
-9.37575817e-01 -5.53260028e-01 -7.97921538e-01 -5.81754148e-01
2.51223385e-01 9.44347739e-01 1.17304838e+00 1.77805156e-01
-1.13623165e-01 3.82049203e-01 -3.55480999e-01 3.30247700e-01
-1.50804624e-01 -5.08088529e-01 -9.16720033e-02 -1.11661211e-01
-2.48414084e-01 -1.04515207e+00 -9.71659064e-01 2.16882631e-01
-1.10601664e+00 4.75226551e-01 2.66079195e-02 6.17580354e-01
8.82018924e-01 -1.15865603e-01 1.67943444e-02 -5.89117527e-01
-4.66320552e-02 -4.48646724e-01 -6.83210909e-01 -4.93596494e-02
-1.02180578e-01 -1.99016914e-01 9.73932505e-01 -5.46484947e-01
-1.15950572e+00 -2.45638371e-01 -5.41399956e-01 -9.76748943e-01
1.02632880e-01 2.68938571e-01 2.59901918e-02 -2.35246584e-01
3.94654095e-01 4.98958975e-01 -4.26667750e-01 -3.98756087e-01
4.95109499e-01 4.38498080e-01 9.47897077e-01 -2.58023024e-01
5.72007358e-01 7.91022241e-01 -1.67871658e-02 -7.86197901e-01
-6.43549025e-01 -4.41934407e-01 -3.60651791e-01 -3.31418782e-01
7.80130267e-01 -1.38810337e+00 -9.08245027e-01 3.70351285e-01
-1.13389075e+00 -7.45913327e-01 -4.62354928e-01 5.68787336e-01
-9.85838473e-01 5.21170199e-01 -8.80342305e-01 -4.84492481e-01
-3.69969636e-01 -9.65376437e-01 1.23719060e+00 7.76061416e-02
3.03678066e-01 -8.38374615e-01 1.55800983e-01 5.22563187e-03
6.26104593e-01 3.43641132e-01 6.23369932e-01 4.39657211e-01
-9.94252741e-01 1.58921689e-01 -2.48046502e-01 2.92296320e-01
1.31637633e-01 6.20112405e-04 -1.02025235e+00 -4.18202668e-01
3.71935278e-01 -1.56826869e-01 8.48182499e-01 6.77542984e-01
1.63258362e+00 -4.22217131e-01 -3.34540829e-02 1.60505366e+00
1.75462341e+00 3.84884506e-01 9.16927814e-01 1.99046806e-01
9.92936313e-01 2.04499960e-01 5.40466070e-01 9.56890821e-01
3.89215022e-01 8.13326359e-01 6.05504274e-01 -1.20610662e-01
-2.33804002e-01 -1.60923198e-01 5.15029609e-01 1.20077956e+00
-4.58217412e-01 -5.95154822e-01 -2.37862915e-01 2.43105263e-01
-1.56972051e+00 -1.23727560e+00 8.45649689e-02 2.14790201e+00
4.48633820e-01 -2.52278477e-01 -2.63779551e-01 2.83354595e-02
3.39694917e-01 8.33300531e-01 -5.34611523e-01 -4.99274462e-01
-1.15103647e-01 -6.32277057e-02 4.90306318e-01 5.59115767e-01
-8.38022590e-01 6.32844746e-01 6.06449032e+00 7.80792296e-01
-1.59766757e+00 4.74583060e-02 4.78695750e-01 -5.52461505e-01
-5.99425972e-01 -2.83926338e-01 -6.93143487e-01 4.50146139e-01
1.05237591e+00 2.12933153e-01 7.57342517e-01 8.54726613e-01
4.92566049e-01 9.61209014e-02 -7.78060138e-01 1.31513131e+00
1.62269652e-01 -1.66902065e+00 1.65028051e-01 -1.39251836e-02
7.61708617e-01 2.53269166e-01 2.89031118e-01 -8.17385912e-02
4.80975583e-02 -9.25154924e-01 1.00994182e+00 5.96733987e-01
1.43865371e+00 -7.92212903e-01 7.48205110e-02 2.48798400e-01
-1.53862190e+00 -1.85859859e-01 -8.04696143e-01 7.15345936e-03
6.58929229e-01 4.51979399e-01 -4.43883501e-02 6.89961970e-01
9.46302831e-01 1.01508522e+00 -1.38690114e-01 6.53599203e-01
3.52448881e-01 3.17058593e-01 -3.61190915e-01 4.08335745e-01
2.67771393e-01 -1.58803329e-01 4.92005438e-01 1.06551027e+00
6.80061281e-01 6.05746925e-01 1.50460184e-01 4.32116717e-01
2.83230990e-01 -9.83419418e-02 -5.79433024e-01 3.12213898e-01
3.80453141e-03 9.32488739e-01 -4.34139043e-01 -4.28737730e-01
-6.41190171e-01 1.33292484e+00 2.34836340e-01 4.43730831e-01
-1.10878420e+00 -1.94619536e-01 8.93848062e-01 2.25031510e-01
8.15955341e-01 -6.53262734e-01 2.01194078e-01 -1.54917693e+00
8.42468292e-02 -6.73614979e-01 1.71516597e-01 -1.21602595e+00
-7.49970675e-01 1.04444599e+00 -1.04175225e-01 -1.61946785e+00
-4.70334530e-01 -4.07626003e-01 -3.97198290e-01 6.54150128e-01
-1.73780012e+00 -8.79083633e-01 -6.79221392e-01 9.94638979e-01
8.32041562e-01 4.72255573e-02 5.58473051e-01 4.66525704e-01
-9.59879905e-02 3.24143916e-01 4.50120956e-01 -3.03776354e-01
2.68396884e-01 -7.90284514e-01 6.42651916e-01 8.39346409e-01
1.53164625e-01 4.38257158e-01 5.52631140e-01 -5.07679224e-01
-1.82929039e+00 -1.18451273e+00 3.51641387e-01 2.72705313e-03
7.70325288e-02 -2.61211544e-01 -9.35880303e-01 7.52442181e-01
-6.47079758e-03 4.47441280e-01 5.69772482e-01 -5.66406727e-01
-4.34933394e-01 -1.85311015e-03 -1.01718640e+00 5.65766990e-01
1.43953753e+00 -7.15495527e-01 -1.43326167e-02 2.50050366e-01
1.22977602e+00 -8.77245665e-01 -8.52675617e-01 4.56955433e-01
6.60033941e-01 -1.44624567e+00 1.36416149e+00 -3.06371868e-01
6.43382728e-01 -3.26789409e-01 -7.76587367e-01 -9.54693437e-01
-6.11476600e-01 -7.80406773e-01 -7.01508045e-01 7.87847281e-01
-4.78746742e-01 -3.82969975e-01 6.65651500e-01 3.44098538e-01
-4.64952469e-01 -8.68531525e-01 -8.02441955e-01 -5.46430647e-01
-4.11456585e-01 -8.12104166e-01 5.26365817e-01 6.45048201e-01
-5.52015364e-01 -2.04461083e-01 -7.58831382e-01 3.65292251e-01
2.21665829e-01 4.69889820e-01 6.88016951e-01 -5.80040872e-01
-8.29560161e-01 -1.62715688e-02 -4.33035493e-01 -2.03447390e+00
-6.38049096e-02 -5.88454485e-01 2.08254039e-01 -1.33015645e+00
-1.36737362e-01 -4.25735623e-01 -6.45415336e-02 -1.33349910e-01
3.37236822e-02 5.28249323e-01 2.97524333e-01 2.14460954e-01
-4.98869419e-01 7.33395457e-01 1.33433890e+00 2.91859269e-01
-3.55511546e-01 -1.26183659e-01 -2.08703250e-01 7.46606052e-01
4.14715499e-01 -4.40127328e-02 -6.81472778e-01 -9.04797435e-01
3.04179341e-01 4.18952852e-01 4.35618728e-01 -1.10436785e+00
9.00549889e-02 -2.99044222e-01 5.64790845e-01 -9.69669878e-01
7.98400879e-01 -7.71666050e-01 5.17468393e-01 2.17581883e-01
-2.85239577e-01 4.92136329e-01 6.76787049e-02 6.92580879e-01
-1.13100134e-01 1.62146971e-01 7.30301142e-01 -1.15441829e-01
-1.02881062e+00 5.67373753e-01 -2.99179792e-01 -2.59064227e-01
6.53153479e-01 -2.88498282e-01 -1.35366887e-01 -7.15110719e-01
-5.11526346e-01 -2.10900843e-01 5.34125209e-01 3.01516026e-01
1.03629899e+00 -1.42193651e+00 -4.68228549e-01 5.52923024e-01
-3.62836152e-01 1.19835801e-01 9.08581674e-01 3.77420336e-01
-1.06817472e+00 2.59080529e-01 -1.37978777e-01 -7.63187289e-01
-1.37137663e+00 8.11091006e-01 3.15385461e-01 -7.14563355e-02
-1.45555079e+00 9.39258218e-01 6.82144701e-01 -2.54811086e-02
1.86786965e-01 -5.82737029e-01 -1.20943345e-01 -4.78102803e-01
1.10747206e+00 4.03699338e-01 -1.16368964e-01 -7.96791732e-01
1.34504154e-01 7.80361176e-01 2.18013585e-01 -1.44256786e-01
1.42832577e+00 -5.15163898e-01 1.57361880e-01 3.95838231e-01
1.61193073e+00 3.06647211e-01 -1.97411048e+00 -2.25342631e-01
-8.73542726e-01 -1.08015931e+00 3.12000871e-01 -2.29696065e-01
-1.41707706e+00 8.39373589e-01 6.11082137e-01 -3.12781171e-03
1.51260340e+00 -4.26469266e-01 1.31071985e+00 3.13676119e-01
4.64197338e-01 -5.80479443e-01 1.01886146e-01 5.79730272e-01
8.85027766e-01 -7.95446515e-01 -4.56257127e-02 -6.17535591e-01
-4.24663216e-01 1.40139246e+00 3.54459494e-01 -3.23085755e-01
6.16834700e-01 4.39632267e-01 -1.68378036e-02 -4.17928062e-02
-1.06997204e+00 1.71012431e-01 2.84713060e-01 5.34023523e-01
3.10214609e-01 -2.45542258e-01 2.40347043e-01 1.07814573e-01
-3.13373238e-01 6.45742938e-03 5.06310821e-01 9.56928670e-01
-3.96091104e-01 -4.93920296e-01 -1.27935991e-01 2.80697554e-01
-5.28682709e-01 -2.51136690e-01 5.56191087e-01 3.14567685e-01
-3.93589847e-02 7.05929697e-01 4.07236248e-01 -6.16310418e-01
8.96905288e-02 -5.26489019e-01 5.42240441e-01 -1.17645204e-01
-5.59431434e-01 3.55399728e-01 -1.09927990e-01 -1.35283601e+00
-4.36018348e-01 -2.62280047e-01 -1.16628659e+00 -6.77042365e-01
-5.03492355e-02 -3.06698859e-01 5.88962913e-01 5.73793054e-01
5.42687178e-01 7.28722692e-01 1.10005069e+00 -1.39483666e+00
-3.16853285e-01 -3.32050860e-01 -5.11510491e-01 1.64522946e-01
8.31173658e-01 -3.02781433e-01 -2.91364908e-01 1.82864577e-01] | [10.485280990600586, -2.105069875717163] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.